2022/11/02 11:59:18 - 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: 335192945 GPU 0: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.10.0+cu111 OpenCV: 4.6.0 MMEngine: 0.2.0 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: 1 ------------------------------------------------------------ 2022/11/02 11:59:18 - mmengine - INFO - Config: file_client_args = dict(backend='disk') model = dict( type='DBNet', backbone=dict( type='mmdet.ResNet', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=-1, norm_cfg=dict(type='BN', requires_grad=True), norm_eval=True, style='pytorch', init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50')), neck=dict( type='FPNC', in_channels=[256, 512, 1024, 2048], lateral_channels=256), det_head=dict( type='DBHead', in_channels=256, module_loss=dict(type='DBModuleLoss'), postprocessor=dict(type='DBPostprocessor', text_repr_type='quad')), data_preprocessor=dict( type='TextDetDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], bgr_to_rgb=True, pad_size_divisor=32)) train_pipeline = [ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), color_type='color_ignore_orientation'), dict( type='LoadOCRAnnotations', with_bbox=True, with_polygon=True, with_label=True), dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.12549019607843137, saturation=0.5), dict( type='ImgAugWrapper', args=[['Fliplr', 0.5], { 'cls': 'Affine', 'rotate': [-10, 10] }, ['Resize', [0.5, 3.0]]]), dict(type='RandomCrop', min_side_ratio=0.1), dict(type='Resize', scale=(640, 640), keep_ratio=True), dict(type='Pad', size=(640, 640)), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape')) ] test_pipeline = [ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), color_type='color_ignore_orientation'), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) ] ic15_det_data_root = 'data/det/icdar2015' ic15_det_train = dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_training.json', data_prefix=dict(img_path='imgs/'), filter_cfg=dict(filter_empty_gt=True, min_size=32), pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), color_type='color_ignore_orientation'), dict( type='LoadOCRAnnotations', with_bbox=True, with_polygon=True, with_label=True), dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.12549019607843137, saturation=0.5), dict( type='ImgAugWrapper', args=[['Fliplr', 0.5], { 'cls': 'Affine', 'rotate': [-10, 10] }, ['Resize', [0.5, 3.0]]]), dict(type='RandomCrop', min_side_ratio=0.1), dict(type='Resize', scale=(640, 640), keep_ratio=True), dict(type='Pad', size=(640, 640)), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape')) ]) ic15_det_test = dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='disk'), color_type='color_ignore_orientation'), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) ]) 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=5), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=20, out_dir='sproject:s3://oclip'), 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='HmeanIOUMetric') test_evaluator = dict(type='HmeanIOUMetric') vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='TextDetLocalVisualizer', name='visualizer', vis_backends=[dict(type='LocalVisBackend')]) optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='SGD', lr=0.002, momentum=0.9, weight_decay=0.0001)) train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=1200, val_interval=20) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict(type='LinearLR', end=100, start_factor=0.001), dict(type='PolyLR', power=0.9, eta_min=1e-07, begin=100, end=1200) ] train_dataloader = dict( batch_size=16, num_workers=24, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/det/icdar2015', ann_file='instances_training.json', data_prefix=dict(img_path='imgs/'), filter_cfg=dict(filter_empty_gt=True, min_size=32), pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel'), color_type='color_ignore_orientation'), dict( type='LoadOCRAnnotations', with_bbox=True, with_polygon=True, with_label=True), dict( type='TorchVisionWrapper', op='ColorJitter', brightness=0.12549019607843137, saturation=0.5), dict( type='ImgAugWrapper', args=[['Fliplr', 0.5], { 'cls': 'Affine', 'rotate': [-10, 10] }, ['Resize', [0.5, 3.0]]]), dict(type='RandomCrop', min_side_ratio=0.1), dict(type='Resize', scale=(640, 640), keep_ratio=True), dict(type='Pad', size=(640, 640)), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape')) ])) val_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel'), color_type='color_ignore_orientation'), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) ])) test_dataloader = dict( batch_size=1, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='OCRDataset', data_root='openmmlab:s3://openmmlab/datasets/ocr/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=[ dict( type='LoadImageFromFile', file_client_args=dict(backend='petrel'), color_type='color_ignore_orientation'), dict(type='Resize', scale=(4068, 1024), keep_ratio=True), dict( type='LoadOCRAnnotations', with_polygon=True, with_bbox=True, with_label=True), dict( type='PackTextDetInputs', meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor')) ])) auto_scale_lr = dict(base_batch_size=16) launcher = 'slurm' work_dir = './work_dirs/dbnet_resnet50_1200e_icdar2015' Name of parameter - Initialization information backbone.conv1.weight - torch.Size([64, 3, 7, 7]): PretrainedInit: load from torchvision://resnet50 backbone.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn2.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn2.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn3.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.bn3.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.downsample.0.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.downsample.1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.0.downsample.1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn2.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn2.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn3.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.1.bn3.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn1.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn1.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn2.weight - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn2.bias - torch.Size([64]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn3.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer1.2.bn3.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv1.weight - torch.Size([128, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.downsample.0.weight - torch.Size([512, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.downsample.1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.0.downsample.1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.1.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.2.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn1.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn1.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn2.weight - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn2.bias - torch.Size([128]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn3.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer2.3.bn3.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv1.weight - torch.Size([256, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.downsample.0.weight - torch.Size([1024, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.downsample.1.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.0.downsample.1.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.1.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.2.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.3.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.4.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn1.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn1.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn2.weight - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn2.bias - torch.Size([256]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn3.weight - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer3.5.bn3.bias - torch.Size([1024]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv1.weight - torch.Size([512, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn2.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn2.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn3.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.bn3.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.downsample.0.weight - torch.Size([2048, 1024, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.downsample.1.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.0.downsample.1.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn2.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn2.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn3.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.1.bn3.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn1.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn1.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn2.weight - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn2.bias - torch.Size([512]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn3.weight - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 backbone.layer4.2.bn3.bias - torch.Size([2048]): PretrainedInit: load from torchvision://resnet50 neck.lateral_convs.0.conv.weight - torch.Size([256, 256, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.lateral_convs.1.conv.weight - torch.Size([256, 512, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.lateral_convs.2.conv.weight - torch.Size([256, 1024, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.lateral_convs.3.conv.weight - torch.Size([256, 2048, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.0.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.1.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.2.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.smooth_convs.3.conv.weight - torch.Size([64, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule det_head.binarize.0.weight - torch.Size([64, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.3.weight - torch.Size([64, 64, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.4.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.4.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.6.weight - torch.Size([64, 1, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.binarize.6.bias - torch.Size([1]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.0.weight - torch.Size([64, 256, 3, 3]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.1.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.1.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.3.weight - torch.Size([64, 64, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.3.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.4.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.4.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.6.weight - torch.Size([64, 1, 2, 2]): The value is the same before and after calling `init_weights` of DBNet det_head.threshold.6.bias - torch.Size([1]): The value is the same before and after calling `init_weights` of DBNet 2022/11/02 12:09:03 - mmengine - INFO - Epoch(train) [1][5/63] lr: 2.0000e-06 memory: 47141 data_time: 86.8242 loss: 23.8279 loss_prob: 19.6291 loss_thr: 3.2120 loss_db: 0.9868 time: 89.0249 2022/11/02 12:09:05 - mmengine - INFO - Epoch(train) [1][10/63] lr: 2.0000e-06 eta: 39 days, 3:37:05 time: 44.7496 data_time: 43.4147 memory: 14901 loss: 23.9391 loss_prob: 19.8101 loss_thr: 3.1407 loss_db: 0.9884 2022/11/02 12:09:08 - mmengine - INFO - Epoch(train) [1][15/63] lr: 2.0000e-06 eta: 39 days, 3:37:05 time: 0.4688 data_time: 0.0047 memory: 14901 loss: 23.4517 loss_prob: 19.3932 loss_thr: 3.0679 loss_db: 0.9905 2022/11/02 12:09:10 - mmengine - INFO - Epoch(train) [1][20/63] lr: 2.0000e-06 eta: 19 days, 18:27:18 time: 0.4485 data_time: 0.0045 memory: 14901 loss: 22.5083 loss_prob: 18.4504 loss_thr: 3.0660 loss_db: 0.9920 2022/11/02 12:09:13 - mmengine - INFO - Epoch(train) [1][25/63] lr: 2.0000e-06 eta: 19 days, 18:27:18 time: 0.4760 data_time: 0.0062 memory: 14901 loss: 21.3476 loss_prob: 17.2543 loss_thr: 3.1008 loss_db: 0.9926 2022/11/02 12:09:15 - mmengine - INFO - Epoch(train) [1][30/63] lr: 2.0000e-06 eta: 13 days, 7:58:03 time: 0.5297 data_time: 0.0177 memory: 14901 loss: 19.6873 loss_prob: 15.6127 loss_thr: 3.0828 loss_db: 0.9918 2022/11/02 12:09:18 - mmengine - INFO - Epoch(train) [1][35/63] lr: 2.0000e-06 eta: 13 days, 7:58:03 time: 0.5498 data_time: 0.0187 memory: 14901 loss: 18.4869 loss_prob: 14.5300 loss_thr: 2.9656 loss_db: 0.9913 2022/11/02 12:09:22 - mmengine - INFO - Epoch(train) [1][40/63] lr: 2.0000e-06 eta: 10 days, 3:18:16 time: 0.6404 data_time: 0.0072 memory: 14901 loss: 17.4091 loss_prob: 13.5187 loss_thr: 2.9005 loss_db: 0.9899 2022/11/02 12:09:24 - mmengine - INFO - Epoch(train) [1][45/63] lr: 2.0000e-06 eta: 10 days, 3:18:16 time: 0.6045 data_time: 0.0052 memory: 14901 loss: 16.6028 loss_prob: 12.7498 loss_thr: 2.8635 loss_db: 0.9894 2022/11/02 12:09:28 - mmengine - INFO - Epoch(train) [1][50/63] lr: 2.0000e-06 eta: 8 days, 5:12:44 time: 0.6182 data_time: 0.0232 memory: 14901 loss: 16.2948 loss_prob: 12.4761 loss_thr: 2.8294 loss_db: 0.9893 2022/11/02 12:09:30 - mmengine - INFO - Epoch(train) [1][55/63] lr: 2.0000e-06 eta: 8 days, 5:12:44 time: 0.6431 data_time: 0.0255 memory: 14901 loss: 16.1171 loss_prob: 12.2657 loss_thr: 2.8611 loss_db: 0.9903 2022/11/02 12:09:33 - mmengine - INFO - Epoch(train) [1][60/63] lr: 2.0000e-06 eta: 6 days, 22:11:47 time: 0.5361 data_time: 0.0073 memory: 14901 loss: 15.6535 loss_prob: 11.8348 loss_thr: 2.8276 loss_db: 0.9911 2022/11/02 12:09:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:09:52 - mmengine - INFO - Epoch(train) [2][5/63] lr: 2.2182e-05 eta: 6 days, 22:11:47 time: 1.9886 data_time: 0.2327 memory: 40375 loss: 15.5949 loss_prob: 11.8110 loss_thr: 2.7935 loss_db: 0.9904 2022/11/02 12:09:54 - mmengine - INFO - Epoch(train) [2][10/63] lr: 2.2182e-05 eta: 5 days, 19:15:10 time: 0.9313 data_time: 0.2351 memory: 14901 loss: 15.3425 loss_prob: 11.6522 loss_thr: 2.7006 loss_db: 0.9897 2022/11/02 12:09:57 - mmengine - INFO - Epoch(train) [2][15/63] lr: 2.2182e-05 eta: 5 days, 19:15:10 time: 0.5488 data_time: 0.0347 memory: 14901 loss: 13.4902 loss_prob: 9.9663 loss_thr: 2.5352 loss_db: 0.9887 2022/11/02 12:10:00 - mmengine - INFO - Epoch(train) [2][20/63] lr: 2.2182e-05 eta: 5 days, 3:56:53 time: 0.5891 data_time: 0.0325 memory: 14901 loss: 11.5401 loss_prob: 8.2317 loss_thr: 2.3214 loss_db: 0.9871 2022/11/02 12:10:03 - mmengine - INFO - Epoch(train) [2][25/63] lr: 2.2182e-05 eta: 5 days, 3:56:53 time: 0.6192 data_time: 0.0060 memory: 14901 loss: 10.0334 loss_prob: 6.9381 loss_thr: 2.1106 loss_db: 0.9847 2022/11/02 12:10:06 - mmengine - INFO - Epoch(train) [2][30/63] lr: 2.2182e-05 eta: 4 days, 15:53:44 time: 0.5719 data_time: 0.0191 memory: 14901 loss: 9.1358 loss_prob: 6.2043 loss_thr: 1.9454 loss_db: 0.9862 2022/11/02 12:10:09 - mmengine - INFO - Epoch(train) [2][35/63] lr: 2.2182e-05 eta: 4 days, 15:53:44 time: 0.5334 data_time: 0.0178 memory: 14901 loss: 8.2041 loss_prob: 5.4591 loss_thr: 1.7600 loss_db: 0.9850 2022/11/02 12:10:12 - mmengine - INFO - Epoch(train) [2][40/63] lr: 2.2182e-05 eta: 4 days, 6:10:13 time: 0.5657 data_time: 0.0111 memory: 14901 loss: 7.5904 loss_prob: 4.9837 loss_thr: 1.6260 loss_db: 0.9806 2022/11/02 12:10:14 - mmengine - INFO - Epoch(train) [2][45/63] lr: 2.2182e-05 eta: 4 days, 6:10:13 time: 0.5163 data_time: 0.0108 memory: 14901 loss: 7.2965 loss_prob: 4.7969 loss_thr: 1.5168 loss_db: 0.9828 2022/11/02 12:10:16 - mmengine - INFO - Epoch(train) [2][50/63] lr: 2.2182e-05 eta: 3 days, 22:00:14 time: 0.4783 data_time: 0.0169 memory: 14901 loss: 6.9801 loss_prob: 4.5656 loss_thr: 1.4305 loss_db: 0.9840 2022/11/02 12:10:19 - mmengine - INFO - Epoch(train) [2][55/63] lr: 2.2182e-05 eta: 3 days, 22:00:14 time: 0.4707 data_time: 0.0172 memory: 14901 loss: 6.7248 loss_prob: 4.3745 loss_thr: 1.3693 loss_db: 0.9810 2022/11/02 12:10:21 - mmengine - INFO - Epoch(train) [2][60/63] lr: 2.2182e-05 eta: 3 days, 15:08:41 time: 0.4663 data_time: 0.0056 memory: 14901 loss: 6.5488 loss_prob: 4.2586 loss_thr: 1.3102 loss_db: 0.9800 2022/11/02 12:10:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:10:27 - mmengine - INFO - Epoch(train) [3][5/63] lr: 4.2364e-05 eta: 3 days, 15:08:41 time: 0.6660 data_time: 0.1773 memory: 14901 loss: 6.2870 loss_prob: 4.0530 loss_thr: 1.2522 loss_db: 0.9819 2022/11/02 12:10:30 - mmengine - INFO - Epoch(train) [3][10/63] lr: 4.2364e-05 eta: 3 days, 7:56:30 time: 0.7401 data_time: 0.1967 memory: 14901 loss: 6.1447 loss_prob: 3.9320 loss_thr: 1.2273 loss_db: 0.9855 2022/11/02 12:10:32 - mmengine - INFO - Epoch(train) [3][15/63] lr: 4.2364e-05 eta: 3 days, 7:56:30 time: 0.5602 data_time: 0.0258 memory: 14901 loss: 6.0052 loss_prob: 3.8183 loss_thr: 1.2029 loss_db: 0.9840 2022/11/02 12:10:35 - mmengine - INFO - Epoch(train) [3][20/63] lr: 4.2364e-05 eta: 3 days, 3:09:36 time: 0.4901 data_time: 0.0070 memory: 14901 loss: 5.8839 loss_prob: 3.7161 loss_thr: 1.1853 loss_db: 0.9826 2022/11/02 12:10:38 - mmengine - INFO - Epoch(train) [3][25/63] lr: 4.2364e-05 eta: 3 days, 3:09:36 time: 0.5131 data_time: 0.0250 memory: 14901 loss: 5.8197 loss_prob: 3.6521 loss_thr: 1.1845 loss_db: 0.9831 2022/11/02 12:10:40 - mmengine - INFO - Epoch(train) [3][30/63] lr: 4.2364e-05 eta: 2 days, 23:03:02 time: 0.5345 data_time: 0.0324 memory: 14901 loss: 5.7635 loss_prob: 3.6016 loss_thr: 1.1804 loss_db: 0.9816 2022/11/02 12:10:43 - mmengine - INFO - Epoch(train) [3][35/63] lr: 4.2364e-05 eta: 2 days, 23:03:02 time: 0.5127 data_time: 0.0162 memory: 14901 loss: 5.7440 loss_prob: 3.5867 loss_thr: 1.1764 loss_db: 0.9809 2022/11/02 12:10:45 - mmengine - INFO - Epoch(train) [3][40/63] lr: 4.2364e-05 eta: 2 days, 19:22:23 time: 0.4843 data_time: 0.0083 memory: 14901 loss: 5.7137 loss_prob: 3.5542 loss_thr: 1.1747 loss_db: 0.9848 2022/11/02 12:10:47 - mmengine - INFO - Epoch(train) [3][45/63] lr: 4.2364e-05 eta: 2 days, 19:22:23 time: 0.4610 data_time: 0.0062 memory: 14901 loss: 5.6619 loss_prob: 3.5044 loss_thr: 1.1704 loss_db: 0.9871 2022/11/02 12:10:50 - mmengine - INFO - Epoch(train) [3][50/63] lr: 4.2364e-05 eta: 2 days, 16:07:07 time: 0.4891 data_time: 0.0183 memory: 14901 loss: 5.6188 loss_prob: 3.4628 loss_thr: 1.1695 loss_db: 0.9865 2022/11/02 12:10:52 - mmengine - INFO - Epoch(train) [3][55/63] lr: 4.2364e-05 eta: 2 days, 16:07:07 time: 0.5198 data_time: 0.0249 memory: 14901 loss: 5.6305 loss_prob: 3.4737 loss_thr: 1.1706 loss_db: 0.9862 2022/11/02 12:10:55 - mmengine - INFO - Epoch(train) [3][60/63] lr: 4.2364e-05 eta: 2 days, 13:14:26 time: 0.5125 data_time: 0.0116 memory: 14901 loss: 5.6037 loss_prob: 3.4520 loss_thr: 1.1675 loss_db: 0.9843 2022/11/02 12:10:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:11:01 - mmengine - INFO - Epoch(train) [4][5/63] lr: 6.2545e-05 eta: 2 days, 13:14:26 time: 0.7393 data_time: 0.1715 memory: 14901 loss: 5.4957 loss_prob: 3.3406 loss_thr: 1.1709 loss_db: 0.9843 2022/11/02 12:11:04 - mmengine - INFO - Epoch(train) [4][10/63] lr: 6.2545e-05 eta: 2 days, 10:03:20 time: 0.7843 data_time: 0.1758 memory: 14901 loss: 5.4611 loss_prob: 3.3057 loss_thr: 1.1677 loss_db: 0.9877 2022/11/02 12:11:07 - mmengine - INFO - Epoch(train) [4][15/63] lr: 6.2545e-05 eta: 2 days, 10:03:20 time: 0.5749 data_time: 0.0109 memory: 14901 loss: 5.4155 loss_prob: 3.2608 loss_thr: 1.1670 loss_db: 0.9877 2022/11/02 12:11:10 - mmengine - INFO - Epoch(train) [4][20/63] lr: 6.2545e-05 eta: 2 days, 7:48:23 time: 0.5347 data_time: 0.0066 memory: 14901 loss: 5.3875 loss_prob: 3.2324 loss_thr: 1.1655 loss_db: 0.9896 2022/11/02 12:11:12 - mmengine - INFO - Epoch(train) [4][25/63] lr: 6.2545e-05 eta: 2 days, 7:48:23 time: 0.5170 data_time: 0.0102 memory: 14901 loss: 5.3708 loss_prob: 3.2164 loss_thr: 1.1616 loss_db: 0.9928 2022/11/02 12:11:15 - mmengine - INFO - Epoch(train) [4][30/63] lr: 6.2545e-05 eta: 2 days, 5:47:13 time: 0.5605 data_time: 0.0303 memory: 14901 loss: 5.3516 loss_prob: 3.1950 loss_thr: 1.1637 loss_db: 0.9929 2022/11/02 12:11:18 - mmengine - INFO - Epoch(train) [4][35/63] lr: 6.2545e-05 eta: 2 days, 5:47:13 time: 0.5473 data_time: 0.0272 memory: 14901 loss: 5.3260 loss_prob: 3.1673 loss_thr: 1.1656 loss_db: 0.9931 2022/11/02 12:11:20 - mmengine - INFO - Epoch(train) [4][40/63] lr: 6.2545e-05 eta: 2 days, 3:53:11 time: 0.4977 data_time: 0.0099 memory: 14901 loss: 5.3128 loss_prob: 3.1540 loss_thr: 1.1654 loss_db: 0.9934 2022/11/02 12:11:23 - mmengine - INFO - Epoch(train) [4][45/63] lr: 6.2545e-05 eta: 2 days, 3:53:11 time: 0.4772 data_time: 0.0073 memory: 14901 loss: 5.3198 loss_prob: 3.1571 loss_thr: 1.1690 loss_db: 0.9937 2022/11/02 12:11:25 - mmengine - INFO - Epoch(train) [4][50/63] lr: 6.2545e-05 eta: 2 days, 2:07:37 time: 0.4776 data_time: 0.0085 memory: 14901 loss: 5.3089 loss_prob: 3.1465 loss_thr: 1.1680 loss_db: 0.9945 2022/11/02 12:11:27 - mmengine - INFO - Epoch(train) [4][55/63] lr: 6.2545e-05 eta: 2 days, 2:07:37 time: 0.4816 data_time: 0.0227 memory: 14901 loss: 5.3127 loss_prob: 3.1543 loss_thr: 1.1642 loss_db: 0.9942 2022/11/02 12:11:30 - mmengine - INFO - Epoch(train) [4][60/63] lr: 6.2545e-05 eta: 2 days, 0:29:58 time: 0.4663 data_time: 0.0187 memory: 14901 loss: 5.2994 loss_prob: 3.1447 loss_thr: 1.1597 loss_db: 0.9950 2022/11/02 12:11:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:11:36 - mmengine - INFO - Epoch(train) [5][5/63] lr: 8.2727e-05 eta: 2 days, 0:29:58 time: 0.7263 data_time: 0.2461 memory: 14901 loss: 5.2676 loss_prob: 3.1094 loss_thr: 1.1620 loss_db: 0.9962 2022/11/02 12:11:38 - mmengine - INFO - Epoch(train) [5][10/63] lr: 8.2727e-05 eta: 1 day, 22:41:56 time: 0.7685 data_time: 0.2443 memory: 14901 loss: 5.2765 loss_prob: 3.1163 loss_thr: 1.1634 loss_db: 0.9968 2022/11/02 12:11:41 - mmengine - INFO - Epoch(train) [5][15/63] lr: 8.2727e-05 eta: 1 day, 22:41:56 time: 0.5133 data_time: 0.0050 memory: 14901 loss: 5.2717 loss_prob: 3.1178 loss_thr: 1.1576 loss_db: 0.9963 2022/11/02 12:11:44 - mmengine - INFO - Epoch(train) [5][20/63] lr: 8.2727e-05 eta: 1 day, 21:22:56 time: 0.5278 data_time: 0.0051 memory: 14901 loss: 5.2554 loss_prob: 3.1065 loss_thr: 1.1529 loss_db: 0.9960 2022/11/02 12:11:46 - mmengine - INFO - Epoch(train) [5][25/63] lr: 8.2727e-05 eta: 1 day, 21:22:56 time: 0.5384 data_time: 0.0396 memory: 14901 loss: 5.2459 loss_prob: 3.0932 loss_thr: 1.1555 loss_db: 0.9972 2022/11/02 12:11:49 - mmengine - INFO - Epoch(train) [5][30/63] lr: 8.2727e-05 eta: 1 day, 20:09:24 time: 0.5252 data_time: 0.0417 memory: 14901 loss: 5.2309 loss_prob: 3.0766 loss_thr: 1.1567 loss_db: 0.9976 2022/11/02 12:11:52 - mmengine - INFO - Epoch(train) [5][35/63] lr: 8.2727e-05 eta: 1 day, 20:09:24 time: 0.5364 data_time: 0.0070 memory: 14901 loss: 5.2042 loss_prob: 3.0499 loss_thr: 1.1562 loss_db: 0.9980 2022/11/02 12:11:55 - mmengine - INFO - Epoch(train) [5][40/63] lr: 8.2727e-05 eta: 1 day, 19:05:47 time: 0.6388 data_time: 0.0058 memory: 14901 loss: 5.1818 loss_prob: 3.0272 loss_thr: 1.1562 loss_db: 0.9984 2022/11/02 12:11:59 - mmengine - INFO - Epoch(train) [5][45/63] lr: 8.2727e-05 eta: 1 day, 19:05:47 time: 0.7126 data_time: 0.0062 memory: 14901 loss: 5.1684 loss_prob: 3.0080 loss_thr: 1.1619 loss_db: 0.9985 2022/11/02 12:12:02 - mmengine - INFO - Epoch(train) [5][50/63] lr: 8.2727e-05 eta: 1 day, 18:08:13 time: 0.6831 data_time: 0.0348 memory: 14901 loss: 5.1525 loss_prob: 2.9919 loss_thr: 1.1618 loss_db: 0.9988 2022/11/02 12:12:05 - mmengine - INFO - Epoch(train) [5][55/63] lr: 8.2727e-05 eta: 1 day, 18:08:13 time: 0.5931 data_time: 0.0340 memory: 14901 loss: 5.1406 loss_prob: 2.9786 loss_thr: 1.1629 loss_db: 0.9991 2022/11/02 12:12:08 - mmengine - INFO - Epoch(train) [5][60/63] lr: 8.2727e-05 eta: 1 day, 17:08:44 time: 0.5439 data_time: 0.0044 memory: 14901 loss: 5.1313 loss_prob: 2.9682 loss_thr: 1.1638 loss_db: 0.9994 2022/11/02 12:12:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:12:14 - mmengine - INFO - Epoch(train) [6][5/63] lr: 1.0291e-04 eta: 1 day, 17:08:44 time: 0.7483 data_time: 0.2362 memory: 14901 loss: 5.1131 loss_prob: 2.9563 loss_thr: 1.1572 loss_db: 0.9996 2022/11/02 12:12:17 - mmengine - INFO - Epoch(train) [6][10/63] lr: 1.0291e-04 eta: 1 day, 16:02:02 time: 0.8409 data_time: 0.2350 memory: 14901 loss: 5.1083 loss_prob: 2.9544 loss_thr: 1.1544 loss_db: 0.9995 2022/11/02 12:12:21 - mmengine - INFO - Epoch(train) [6][15/63] lr: 1.0291e-04 eta: 1 day, 16:02:02 time: 0.6780 data_time: 0.0044 memory: 14901 loss: 5.1146 loss_prob: 2.9542 loss_thr: 1.1609 loss_db: 0.9995 2022/11/02 12:12:24 - mmengine - INFO - Epoch(train) [6][20/63] lr: 1.0291e-04 eta: 1 day, 15:14:06 time: 0.6431 data_time: 0.0053 memory: 14901 loss: 5.1099 loss_prob: 2.9506 loss_thr: 1.1597 loss_db: 0.9996 2022/11/02 12:12:27 - mmengine - INFO - Epoch(train) [6][25/63] lr: 1.0291e-04 eta: 1 day, 15:14:06 time: 0.6802 data_time: 0.0281 memory: 14901 loss: 5.1015 loss_prob: 2.9470 loss_thr: 1.1548 loss_db: 0.9997 2022/11/02 12:12:30 - mmengine - INFO - Epoch(train) [6][30/63] lr: 1.0291e-04 eta: 1 day, 14:27:05 time: 0.5918 data_time: 0.0346 memory: 14901 loss: 5.0943 loss_prob: 2.9403 loss_thr: 1.1543 loss_db: 0.9997 2022/11/02 12:12:33 - mmengine - INFO - Epoch(train) [6][35/63] lr: 1.0291e-04 eta: 1 day, 14:27:05 time: 0.5298 data_time: 0.0119 memory: 14901 loss: 5.1033 loss_prob: 2.9478 loss_thr: 1.1558 loss_db: 0.9997 2022/11/02 12:12:35 - mmengine - INFO - Epoch(train) [6][40/63] lr: 1.0291e-04 eta: 1 day, 13:40:40 time: 0.5344 data_time: 0.0067 memory: 14901 loss: 5.1114 loss_prob: 2.9535 loss_thr: 1.1582 loss_db: 0.9997 2022/11/02 12:12:38 - mmengine - INFO - Epoch(train) [6][45/63] lr: 1.0291e-04 eta: 1 day, 13:40:40 time: 0.5246 data_time: 0.0066 memory: 14901 loss: 5.1020 loss_prob: 2.9427 loss_thr: 1.1596 loss_db: 0.9997 2022/11/02 12:12:41 - mmengine - INFO - Epoch(train) [6][50/63] lr: 1.0291e-04 eta: 1 day, 12:57:24 time: 0.5516 data_time: 0.0189 memory: 14901 loss: 5.0985 loss_prob: 2.9378 loss_thr: 1.1609 loss_db: 0.9997 2022/11/02 12:12:44 - mmengine - INFO - Epoch(train) [6][55/63] lr: 1.0291e-04 eta: 1 day, 12:57:24 time: 0.5602 data_time: 0.0390 memory: 14901 loss: 5.0880 loss_prob: 2.9295 loss_thr: 1.1587 loss_db: 0.9998 2022/11/02 12:12:46 - mmengine - INFO - Epoch(train) [6][60/63] lr: 1.0291e-04 eta: 1 day, 12:15:59 time: 0.5384 data_time: 0.0248 memory: 14901 loss: 5.0810 loss_prob: 2.9259 loss_thr: 1.1553 loss_db: 0.9998 2022/11/02 12:12:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:12:52 - mmengine - INFO - Epoch(train) [7][5/63] lr: 1.2309e-04 eta: 1 day, 12:15:59 time: 0.7017 data_time: 0.2302 memory: 14901 loss: 5.0771 loss_prob: 2.9229 loss_thr: 1.1543 loss_db: 0.9998 2022/11/02 12:12:54 - mmengine - INFO - Epoch(train) [7][10/63] lr: 1.2309e-04 eta: 1 day, 11:25:42 time: 0.7117 data_time: 0.2286 memory: 14901 loss: 5.0729 loss_prob: 2.9181 loss_thr: 1.1550 loss_db: 0.9998 2022/11/02 12:12:57 - mmengine - INFO - Epoch(train) [7][15/63] lr: 1.2309e-04 eta: 1 day, 11:25:42 time: 0.4764 data_time: 0.0047 memory: 14901 loss: 5.0770 loss_prob: 2.9228 loss_thr: 1.1544 loss_db: 0.9998 2022/11/02 12:12:59 - mmengine - INFO - Epoch(train) [7][20/63] lr: 1.2309e-04 eta: 1 day, 10:47:04 time: 0.4782 data_time: 0.0051 memory: 14901 loss: 5.0838 loss_prob: 2.9247 loss_thr: 1.1593 loss_db: 0.9998 2022/11/02 12:13:02 - mmengine - INFO - Epoch(train) [7][25/63] lr: 1.2309e-04 eta: 1 day, 10:47:04 time: 0.5344 data_time: 0.0442 memory: 14901 loss: 5.0891 loss_prob: 2.9306 loss_thr: 1.1587 loss_db: 0.9999 2022/11/02 12:13:05 - mmengine - INFO - Epoch(train) [7][30/63] lr: 1.2309e-04 eta: 1 day, 10:11:48 time: 0.5260 data_time: 0.0482 memory: 14901 loss: 5.1286 loss_prob: 2.9723 loss_thr: 1.1565 loss_db: 0.9998 2022/11/02 12:13:07 - mmengine - INFO - Epoch(train) [7][35/63] lr: 1.2309e-04 eta: 1 day, 10:11:48 time: 0.5055 data_time: 0.0088 memory: 14901 loss: 5.1834 loss_prob: 3.0266 loss_thr: 1.1574 loss_db: 0.9993 2022/11/02 12:13:10 - mmengine - INFO - Epoch(train) [7][40/63] lr: 1.2309e-04 eta: 1 day, 9:38:21 time: 0.5303 data_time: 0.0048 memory: 14901 loss: 5.2158 loss_prob: 3.0554 loss_thr: 1.1621 loss_db: 0.9983 2022/11/02 12:13:12 - mmengine - INFO - Epoch(train) [7][45/63] lr: 1.2309e-04 eta: 1 day, 9:38:21 time: 0.4935 data_time: 0.0047 memory: 14901 loss: 5.2017 loss_prob: 3.0421 loss_thr: 1.1612 loss_db: 0.9984 2022/11/02 12:13:15 - mmengine - INFO - Epoch(train) [7][50/63] lr: 1.2309e-04 eta: 1 day, 9:05:48 time: 0.5082 data_time: 0.0203 memory: 14901 loss: 5.1669 loss_prob: 3.0096 loss_thr: 1.1580 loss_db: 0.9993 2022/11/02 12:13:17 - mmengine - INFO - Epoch(train) [7][55/63] lr: 1.2309e-04 eta: 1 day, 9:05:48 time: 0.5008 data_time: 0.0217 memory: 14901 loss: 5.1454 loss_prob: 2.9870 loss_thr: 1.1590 loss_db: 0.9994 2022/11/02 12:13:20 - mmengine - INFO - Epoch(train) [7][60/63] lr: 1.2309e-04 eta: 1 day, 8:34:23 time: 0.4957 data_time: 0.0060 memory: 14901 loss: 5.1228 loss_prob: 2.9612 loss_thr: 1.1620 loss_db: 0.9995 2022/11/02 12:13:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:13:26 - mmengine - INFO - Epoch(train) [8][5/63] lr: 1.4327e-04 eta: 1 day, 8:34:23 time: 0.7349 data_time: 0.2350 memory: 14901 loss: 5.1047 loss_prob: 2.9428 loss_thr: 1.1623 loss_db: 0.9996 2022/11/02 12:13:29 - mmengine - INFO - Epoch(train) [8][10/63] lr: 1.4327e-04 eta: 1 day, 7:58:05 time: 0.7332 data_time: 0.2347 memory: 14901 loss: 5.1361 loss_prob: 2.9770 loss_thr: 1.1596 loss_db: 0.9995 2022/11/02 12:13:31 - mmengine - INFO - Epoch(train) [8][15/63] lr: 1.4327e-04 eta: 1 day, 7:58:05 time: 0.4920 data_time: 0.0055 memory: 14901 loss: 5.1779 loss_prob: 3.0196 loss_thr: 1.1592 loss_db: 0.9991 2022/11/02 12:13:34 - mmengine - INFO - Epoch(train) [8][20/63] lr: 1.4327e-04 eta: 1 day, 7:29:55 time: 0.5041 data_time: 0.0082 memory: 14901 loss: 5.1676 loss_prob: 3.0095 loss_thr: 1.1591 loss_db: 0.9990 2022/11/02 12:13:36 - mmengine - INFO - Epoch(train) [8][25/63] lr: 1.4327e-04 eta: 1 day, 7:29:55 time: 0.4917 data_time: 0.0110 memory: 14901 loss: 5.1291 loss_prob: 2.9708 loss_thr: 1.1591 loss_db: 0.9992 2022/11/02 12:13:39 - mmengine - INFO - Epoch(train) [8][30/63] lr: 1.4327e-04 eta: 1 day, 7:03:02 time: 0.5071 data_time: 0.0289 memory: 14901 loss: 5.1223 loss_prob: 2.9633 loss_thr: 1.1598 loss_db: 0.9992 2022/11/02 12:13:41 - mmengine - INFO - Epoch(train) [8][35/63] lr: 1.4327e-04 eta: 1 day, 7:03:02 time: 0.5300 data_time: 0.0306 memory: 14901 loss: 5.1112 loss_prob: 2.9535 loss_thr: 1.1584 loss_db: 0.9993 2022/11/02 12:13:43 - mmengine - INFO - Epoch(train) [8][40/63] lr: 1.4327e-04 eta: 1 day, 6:36:31 time: 0.4790 data_time: 0.0099 memory: 14901 loss: 5.0879 loss_prob: 2.9324 loss_thr: 1.1560 loss_db: 0.9995 2022/11/02 12:13:46 - mmengine - INFO - Epoch(train) [8][45/63] lr: 1.4327e-04 eta: 1 day, 6:36:31 time: 0.4692 data_time: 0.0064 memory: 14901 loss: 5.0776 loss_prob: 2.9222 loss_thr: 1.1558 loss_db: 0.9996 2022/11/02 12:13:48 - mmengine - INFO - Epoch(train) [8][50/63] lr: 1.4327e-04 eta: 1 day, 6:11:21 time: 0.4893 data_time: 0.0203 memory: 14901 loss: 5.0665 loss_prob: 2.9073 loss_thr: 1.1595 loss_db: 0.9997 2022/11/02 12:13:51 - mmengine - INFO - Epoch(train) [8][55/63] lr: 1.4327e-04 eta: 1 day, 6:11:21 time: 0.4835 data_time: 0.0210 memory: 14901 loss: 5.0487 loss_prob: 2.8945 loss_thr: 1.1544 loss_db: 0.9997 2022/11/02 12:13:54 - mmengine - INFO - Epoch(train) [8][60/63] lr: 1.4327e-04 eta: 1 day, 5:47:49 time: 0.5142 data_time: 0.0098 memory: 14901 loss: 5.0460 loss_prob: 2.8896 loss_thr: 1.1567 loss_db: 0.9998 2022/11/02 12:13:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:13:59 - mmengine - INFO - Epoch(train) [9][5/63] lr: 1.6345e-04 eta: 1 day, 5:47:49 time: 0.6877 data_time: 0.2108 memory: 14901 loss: 5.0306 loss_prob: 2.8778 loss_thr: 1.1530 loss_db: 0.9999 2022/11/02 12:14:02 - mmengine - INFO - Epoch(train) [9][10/63] lr: 1.6345e-04 eta: 1 day, 5:19:26 time: 0.7038 data_time: 0.2096 memory: 14901 loss: 5.0239 loss_prob: 2.8688 loss_thr: 1.1553 loss_db: 0.9999 2022/11/02 12:14:04 - mmengine - INFO - Epoch(train) [9][15/63] lr: 1.6345e-04 eta: 1 day, 5:19:26 time: 0.4827 data_time: 0.0049 memory: 14901 loss: 5.0219 loss_prob: 2.8633 loss_thr: 1.1587 loss_db: 0.9999 2022/11/02 12:14:06 - mmengine - INFO - Epoch(train) [9][20/63] lr: 1.6345e-04 eta: 1 day, 4:56:57 time: 0.4744 data_time: 0.0046 memory: 14901 loss: 5.0129 loss_prob: 2.8588 loss_thr: 1.1541 loss_db: 0.9999 2022/11/02 12:14:09 - mmengine - INFO - Epoch(train) [9][25/63] lr: 1.6345e-04 eta: 1 day, 4:56:57 time: 0.4861 data_time: 0.0121 memory: 14901 loss: 5.0038 loss_prob: 2.8523 loss_thr: 1.1516 loss_db: 0.9999 2022/11/02 12:14:12 - mmengine - INFO - Epoch(train) [9][30/63] lr: 1.6345e-04 eta: 1 day, 4:36:35 time: 0.5286 data_time: 0.0337 memory: 14901 loss: 5.0022 loss_prob: 2.8470 loss_thr: 1.1553 loss_db: 0.9999 2022/11/02 12:14:14 - mmengine - INFO - Epoch(train) [9][35/63] lr: 1.6345e-04 eta: 1 day, 4:36:35 time: 0.5263 data_time: 0.0277 memory: 14901 loss: 4.9979 loss_prob: 2.8418 loss_thr: 1.1561 loss_db: 1.0000 2022/11/02 12:14:17 - mmengine - INFO - Epoch(train) [9][40/63] lr: 1.6345e-04 eta: 1 day, 4:16:42 time: 0.5175 data_time: 0.0080 memory: 14901 loss: 4.9937 loss_prob: 2.8400 loss_thr: 1.1538 loss_db: 1.0000 2022/11/02 12:14:19 - mmengine - INFO - Epoch(train) [9][45/63] lr: 1.6345e-04 eta: 1 day, 4:16:42 time: 0.5167 data_time: 0.0084 memory: 14901 loss: 4.9951 loss_prob: 2.8404 loss_thr: 1.1548 loss_db: 1.0000 2022/11/02 12:14:22 - mmengine - INFO - Epoch(train) [9][50/63] lr: 1.6345e-04 eta: 1 day, 3:58:08 time: 0.5443 data_time: 0.0121 memory: 14901 loss: 4.9922 loss_prob: 2.8381 loss_thr: 1.1542 loss_db: 1.0000 2022/11/02 12:14:25 - mmengine - INFO - Epoch(train) [9][55/63] lr: 1.6345e-04 eta: 1 day, 3:58:08 time: 0.5849 data_time: 0.0211 memory: 14901 loss: 4.9842 loss_prob: 2.8327 loss_thr: 1.1515 loss_db: 1.0000 2022/11/02 12:14:28 - mmengine - INFO - Epoch(train) [9][60/63] lr: 1.6345e-04 eta: 1 day, 3:40:32 time: 0.5580 data_time: 0.0177 memory: 14901 loss: 4.9817 loss_prob: 2.8302 loss_thr: 1.1516 loss_db: 1.0000 2022/11/02 12:14:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:14:35 - mmengine - INFO - Epoch(train) [10][5/63] lr: 1.8364e-04 eta: 1 day, 3:40:32 time: 0.8335 data_time: 0.2070 memory: 14901 loss: 4.9917 loss_prob: 2.8338 loss_thr: 1.1579 loss_db: 1.0000 2022/11/02 12:14:38 - mmengine - INFO - Epoch(train) [10][10/63] lr: 1.8364e-04 eta: 1 day, 3:21:20 time: 0.8535 data_time: 0.2086 memory: 14901 loss: 5.0023 loss_prob: 2.8427 loss_thr: 1.1597 loss_db: 1.0000 2022/11/02 12:14:42 - mmengine - INFO - Epoch(train) [10][15/63] lr: 1.8364e-04 eta: 1 day, 3:21:20 time: 0.6346 data_time: 0.0182 memory: 14901 loss: 4.9964 loss_prob: 2.8438 loss_thr: 1.1527 loss_db: 0.9999 2022/11/02 12:14:44 - mmengine - INFO - Epoch(train) [10][20/63] lr: 1.8364e-04 eta: 1 day, 3:07:29 time: 0.6726 data_time: 0.0103 memory: 14901 loss: 4.9914 loss_prob: 2.8403 loss_thr: 1.1511 loss_db: 0.9999 2022/11/02 12:14:48 - mmengine - INFO - Epoch(train) [10][25/63] lr: 1.8364e-04 eta: 1 day, 3:07:29 time: 0.6048 data_time: 0.0187 memory: 14901 loss: 4.9836 loss_prob: 2.8379 loss_thr: 1.1458 loss_db: 0.9999 2022/11/02 12:14:50 - mmengine - INFO - Epoch(train) [10][30/63] lr: 1.8364e-04 eta: 1 day, 2:52:14 time: 0.5839 data_time: 0.0256 memory: 14901 loss: 4.9859 loss_prob: 2.8367 loss_thr: 1.1493 loss_db: 0.9999 2022/11/02 12:14:53 - mmengine - INFO - Epoch(train) [10][35/63] lr: 1.8364e-04 eta: 1 day, 2:52:14 time: 0.5439 data_time: 0.0195 memory: 14901 loss: 4.9822 loss_prob: 2.8298 loss_thr: 1.1525 loss_db: 0.9999 2022/11/02 12:14:56 - mmengine - INFO - Epoch(train) [10][40/63] lr: 1.8364e-04 eta: 1 day, 2:37:21 time: 0.5773 data_time: 0.0217 memory: 14901 loss: 4.9785 loss_prob: 2.8289 loss_thr: 1.1497 loss_db: 1.0000 2022/11/02 12:14:59 - mmengine - INFO - Epoch(train) [10][45/63] lr: 1.8364e-04 eta: 1 day, 2:37:21 time: 0.6001 data_time: 0.0140 memory: 14901 loss: 4.9871 loss_prob: 2.8346 loss_thr: 1.1526 loss_db: 0.9999 2022/11/02 12:15:02 - mmengine - INFO - Epoch(train) [10][50/63] lr: 1.8364e-04 eta: 1 day, 2:23:45 time: 0.6168 data_time: 0.0151 memory: 14901 loss: 4.9910 loss_prob: 2.8355 loss_thr: 1.1556 loss_db: 0.9999 2022/11/02 12:15:06 - mmengine - INFO - Epoch(train) [10][55/63] lr: 1.8364e-04 eta: 1 day, 2:23:45 time: 0.7040 data_time: 0.0200 memory: 14901 loss: 4.9934 loss_prob: 2.8352 loss_thr: 1.1583 loss_db: 0.9999 2022/11/02 12:15:09 - mmengine - INFO - Epoch(train) [10][60/63] lr: 1.8364e-04 eta: 1 day, 2:12:38 time: 0.7201 data_time: 0.0116 memory: 14901 loss: 4.9899 loss_prob: 2.8337 loss_thr: 1.1562 loss_db: 0.9999 2022/11/02 12:15:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:15:17 - mmengine - INFO - Epoch(train) [11][5/63] lr: 2.0382e-04 eta: 1 day, 2:12:38 time: 0.9087 data_time: 0.2329 memory: 14901 loss: 4.9745 loss_prob: 2.8272 loss_thr: 1.1474 loss_db: 0.9999 2022/11/02 12:15:21 - mmengine - INFO - Epoch(train) [11][10/63] lr: 2.0382e-04 eta: 1 day, 2:00:03 time: 1.0053 data_time: 0.2324 memory: 14901 loss: 4.9633 loss_prob: 2.8189 loss_thr: 1.1445 loss_db: 0.9999 2022/11/02 12:15:24 - mmengine - INFO - Epoch(train) [11][15/63] lr: 2.0382e-04 eta: 1 day, 2:00:03 time: 0.6568 data_time: 0.0167 memory: 14901 loss: 4.9672 loss_prob: 2.8163 loss_thr: 1.1509 loss_db: 0.9999 2022/11/02 12:15:27 - mmengine - INFO - Epoch(train) [11][20/63] lr: 2.0382e-04 eta: 1 day, 1:46:57 time: 0.5782 data_time: 0.0141 memory: 14901 loss: 4.9715 loss_prob: 2.8175 loss_thr: 1.1540 loss_db: 0.9999 2022/11/02 12:15:29 - mmengine - INFO - Epoch(train) [11][25/63] lr: 2.0382e-04 eta: 1 day, 1:46:57 time: 0.5411 data_time: 0.0191 memory: 14901 loss: 4.9777 loss_prob: 2.8202 loss_thr: 1.1575 loss_db: 0.9999 2022/11/02 12:15:32 - mmengine - INFO - Epoch(train) [11][30/63] lr: 2.0382e-04 eta: 1 day, 1:33:02 time: 0.5135 data_time: 0.0283 memory: 14901 loss: 4.9832 loss_prob: 2.8255 loss_thr: 1.1578 loss_db: 1.0000 2022/11/02 12:15:34 - mmengine - INFO - Epoch(train) [11][35/63] lr: 2.0382e-04 eta: 1 day, 1:33:02 time: 0.4797 data_time: 0.0191 memory: 14901 loss: 5.0053 loss_prob: 2.8523 loss_thr: 1.1532 loss_db: 0.9999 2022/11/02 12:15:37 - mmengine - INFO - Epoch(train) [11][40/63] lr: 2.0382e-04 eta: 1 day, 1:19:10 time: 0.4943 data_time: 0.0123 memory: 14901 loss: 5.0389 loss_prob: 2.8840 loss_thr: 1.1554 loss_db: 0.9995 2022/11/02 12:15:39 - mmengine - INFO - Epoch(train) [11][45/63] lr: 2.0382e-04 eta: 1 day, 1:19:10 time: 0.5109 data_time: 0.0088 memory: 14901 loss: 5.0610 loss_prob: 2.9036 loss_thr: 1.1589 loss_db: 0.9986 2022/11/02 12:15:42 - mmengine - INFO - Epoch(train) [11][50/63] lr: 2.0382e-04 eta: 1 day, 1:05:49 time: 0.5009 data_time: 0.0221 memory: 14901 loss: 5.0546 loss_prob: 2.9026 loss_thr: 1.1532 loss_db: 0.9989 2022/11/02 12:15:44 - mmengine - INFO - Epoch(train) [11][55/63] lr: 2.0382e-04 eta: 1 day, 1:05:49 time: 0.5035 data_time: 0.0208 memory: 14901 loss: 5.0309 loss_prob: 2.8823 loss_thr: 1.1489 loss_db: 0.9997 2022/11/02 12:15:47 - mmengine - INFO - Epoch(train) [11][60/63] lr: 2.0382e-04 eta: 1 day, 0:52:43 time: 0.4925 data_time: 0.0062 memory: 14901 loss: 5.0174 loss_prob: 2.8692 loss_thr: 1.1486 loss_db: 0.9996 2022/11/02 12:15:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:15:53 - mmengine - INFO - Epoch(train) [12][5/63] lr: 2.2400e-04 eta: 1 day, 0:52:43 time: 0.6643 data_time: 0.2032 memory: 14901 loss: 5.0115 loss_prob: 2.8615 loss_thr: 1.1503 loss_db: 0.9997 2022/11/02 12:15:55 - mmengine - INFO - Epoch(train) [12][10/63] lr: 2.2400e-04 eta: 1 day, 0:37:09 time: 0.6930 data_time: 0.2023 memory: 14901 loss: 4.9986 loss_prob: 2.8466 loss_thr: 1.1522 loss_db: 0.9998 2022/11/02 12:15:57 - mmengine - INFO - Epoch(train) [12][15/63] lr: 2.2400e-04 eta: 1 day, 0:37:09 time: 0.4673 data_time: 0.0069 memory: 14901 loss: 4.9856 loss_prob: 2.8352 loss_thr: 1.1505 loss_db: 0.9999 2022/11/02 12:16:00 - mmengine - INFO - Epoch(train) [12][20/63] lr: 2.2400e-04 eta: 1 day, 0:24:54 time: 0.4947 data_time: 0.0057 memory: 14901 loss: 4.9838 loss_prob: 2.8340 loss_thr: 1.1499 loss_db: 0.9999 2022/11/02 12:16:03 - mmengine - INFO - Epoch(train) [12][25/63] lr: 2.2400e-04 eta: 1 day, 0:24:54 time: 0.5499 data_time: 0.0471 memory: 14901 loss: 4.9809 loss_prob: 2.8303 loss_thr: 1.1510 loss_db: 0.9996 2022/11/02 12:16:05 - mmengine - INFO - Epoch(train) [12][30/63] lr: 2.2400e-04 eta: 1 day, 0:13:31 time: 0.5249 data_time: 0.0478 memory: 14901 loss: 4.9671 loss_prob: 2.8213 loss_thr: 1.1463 loss_db: 0.9995 2022/11/02 12:16:08 - mmengine - INFO - Epoch(train) [12][35/63] lr: 2.2400e-04 eta: 1 day, 0:13:31 time: 0.4799 data_time: 0.0061 memory: 14901 loss: 4.9570 loss_prob: 2.8141 loss_thr: 1.1431 loss_db: 0.9998 2022/11/02 12:16:10 - mmengine - INFO - Epoch(train) [12][40/63] lr: 2.2400e-04 eta: 1 day, 0:01:59 time: 0.4989 data_time: 0.0069 memory: 14901 loss: 4.9376 loss_prob: 2.7996 loss_thr: 1.1386 loss_db: 0.9995 2022/11/02 12:16:12 - mmengine - INFO - Epoch(train) [12][45/63] lr: 2.2400e-04 eta: 1 day, 0:01:59 time: 0.4859 data_time: 0.0069 memory: 14901 loss: 4.9390 loss_prob: 2.7988 loss_thr: 1.1411 loss_db: 0.9991 2022/11/02 12:16:15 - mmengine - INFO - Epoch(train) [12][50/63] lr: 2.2400e-04 eta: 23:50:58 time: 0.5115 data_time: 0.0255 memory: 14901 loss: 4.9642 loss_prob: 2.8153 loss_thr: 1.1496 loss_db: 0.9992 2022/11/02 12:16:18 - mmengine - INFO - Epoch(train) [12][55/63] lr: 2.2400e-04 eta: 23:50:58 time: 0.5316 data_time: 0.0264 memory: 14901 loss: 4.9745 loss_prob: 2.8251 loss_thr: 1.1500 loss_db: 0.9995 2022/11/02 12:16:20 - mmengine - INFO - Epoch(train) [12][60/63] lr: 2.2400e-04 eta: 23:40:21 time: 0.5169 data_time: 0.0056 memory: 14901 loss: 4.9605 loss_prob: 2.8172 loss_thr: 1.1437 loss_db: 0.9997 2022/11/02 12:16:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:16:26 - mmengine - INFO - Epoch(train) [13][5/63] lr: 2.4418e-04 eta: 23:40:21 time: 0.6733 data_time: 0.2243 memory: 14901 loss: 4.9407 loss_prob: 2.8041 loss_thr: 1.1388 loss_db: 0.9979 2022/11/02 12:16:28 - mmengine - INFO - Epoch(train) [13][10/63] lr: 2.4418e-04 eta: 23:27:14 time: 0.6900 data_time: 0.2230 memory: 14901 loss: 4.9453 loss_prob: 2.8029 loss_thr: 1.1467 loss_db: 0.9957 2022/11/02 12:16:31 - mmengine - INFO - Epoch(train) [13][15/63] lr: 2.4418e-04 eta: 23:27:14 time: 0.4979 data_time: 0.0066 memory: 14901 loss: 4.9362 loss_prob: 2.8015 loss_thr: 1.1388 loss_db: 0.9960 2022/11/02 12:16:33 - mmengine - INFO - Epoch(train) [13][20/63] lr: 2.4418e-04 eta: 23:16:56 time: 0.4997 data_time: 0.0078 memory: 14901 loss: 4.9334 loss_prob: 2.8024 loss_thr: 1.1344 loss_db: 0.9966 2022/11/02 12:16:36 - mmengine - INFO - Epoch(train) [13][25/63] lr: 2.4418e-04 eta: 23:16:56 time: 0.4663 data_time: 0.0159 memory: 14901 loss: 4.9409 loss_prob: 2.7984 loss_thr: 1.1505 loss_db: 0.9920 2022/11/02 12:16:38 - mmengine - INFO - Epoch(train) [13][30/63] lr: 2.4418e-04 eta: 23:06:49 time: 0.4941 data_time: 0.0286 memory: 14901 loss: 4.9468 loss_prob: 2.8035 loss_thr: 1.1602 loss_db: 0.9831 2022/11/02 12:16:41 - mmengine - INFO - Epoch(train) [13][35/63] lr: 2.4418e-04 eta: 23:06:49 time: 0.4907 data_time: 0.0236 memory: 14901 loss: 4.9406 loss_prob: 2.8129 loss_thr: 1.1459 loss_db: 0.9818 2022/11/02 12:16:43 - mmengine - INFO - Epoch(train) [13][40/63] lr: 2.4418e-04 eta: 22:56:44 time: 0.4802 data_time: 0.0096 memory: 14901 loss: 4.9157 loss_prob: 2.8047 loss_thr: 1.1362 loss_db: 0.9748 2022/11/02 12:16:45 - mmengine - INFO - Epoch(train) [13][45/63] lr: 2.4418e-04 eta: 22:56:44 time: 0.4694 data_time: 0.0052 memory: 14901 loss: 4.9052 loss_prob: 2.8031 loss_thr: 1.1461 loss_db: 0.9559 2022/11/02 12:16:48 - mmengine - INFO - Epoch(train) [13][50/63] lr: 2.4418e-04 eta: 22:47:35 time: 0.5244 data_time: 0.0213 memory: 14901 loss: 4.8278 loss_prob: 2.7898 loss_thr: 1.1395 loss_db: 0.8985 2022/11/02 12:16:51 - mmengine - INFO - Epoch(train) [13][55/63] lr: 2.4418e-04 eta: 22:47:35 time: 0.5484 data_time: 0.0255 memory: 14901 loss: 4.7697 loss_prob: 2.7893 loss_thr: 1.1220 loss_db: 0.8583 2022/11/02 12:16:53 - mmengine - INFO - Epoch(train) [13][60/63] lr: 2.4418e-04 eta: 22:38:16 time: 0.4993 data_time: 0.0108 memory: 14901 loss: 4.8280 loss_prob: 2.8094 loss_thr: 1.1560 loss_db: 0.8625 2022/11/02 12:16:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:17:00 - mmengine - INFO - Epoch(train) [14][5/63] lr: 2.6436e-04 eta: 22:38:16 time: 0.7697 data_time: 0.2168 memory: 14901 loss: 4.8697 loss_prob: 2.8204 loss_thr: 1.1680 loss_db: 0.8813 2022/11/02 12:17:04 - mmengine - INFO - Epoch(train) [14][10/63] lr: 2.6436e-04 eta: 22:29:57 time: 0.8787 data_time: 0.2221 memory: 14901 loss: 4.7166 loss_prob: 2.8180 loss_thr: 1.1515 loss_db: 0.7471 2022/11/02 12:17:06 - mmengine - INFO - Epoch(train) [14][15/63] lr: 2.6436e-04 eta: 22:29:57 time: 0.6234 data_time: 0.0115 memory: 14901 loss: 4.8481 loss_prob: 2.8676 loss_thr: 1.1762 loss_db: 0.8043 2022/11/02 12:17:09 - mmengine - INFO - Epoch(train) [14][20/63] lr: 2.6436e-04 eta: 22:21:44 time: 0.5425 data_time: 0.0079 memory: 14901 loss: 5.0701 loss_prob: 2.9776 loss_thr: 1.1906 loss_db: 0.9018 2022/11/02 12:17:12 - mmengine - INFO - Epoch(train) [14][25/63] lr: 2.6436e-04 eta: 22:21:44 time: 0.5721 data_time: 0.0079 memory: 14901 loss: 5.2733 loss_prob: 3.2015 loss_thr: 1.2141 loss_db: 0.8577 2022/11/02 12:17:15 - mmengine - INFO - Epoch(train) [14][30/63] lr: 2.6436e-04 eta: 22:14:04 time: 0.5665 data_time: 0.0302 memory: 14901 loss: 5.5489 loss_prob: 3.3872 loss_thr: 1.2634 loss_db: 0.8983 2022/11/02 12:17:18 - mmengine - INFO - Epoch(train) [14][35/63] lr: 2.6436e-04 eta: 22:14:04 time: 0.6277 data_time: 0.0307 memory: 14901 loss: 5.6080 loss_prob: 3.3903 loss_thr: 1.2328 loss_db: 0.9849 2022/11/02 12:17:21 - mmengine - INFO - Epoch(train) [14][40/63] lr: 2.6436e-04 eta: 22:07:29 time: 0.6294 data_time: 0.0089 memory: 14901 loss: 5.5165 loss_prob: 3.3410 loss_thr: 1.1821 loss_db: 0.9934 2022/11/02 12:17:24 - mmengine - INFO - Epoch(train) [14][45/63] lr: 2.6436e-04 eta: 22:07:29 time: 0.5348 data_time: 0.0069 memory: 14901 loss: 5.4311 loss_prob: 3.2931 loss_thr: 1.1752 loss_db: 0.9629 2022/11/02 12:17:26 - mmengine - INFO - Epoch(train) [14][50/63] lr: 2.6436e-04 eta: 21:59:43 time: 0.5357 data_time: 0.0150 memory: 14901 loss: 5.6680 loss_prob: 3.4639 loss_thr: 1.2739 loss_db: 0.9302 2022/11/02 12:17:29 - mmengine - INFO - Epoch(train) [14][55/63] lr: 2.6436e-04 eta: 21:59:43 time: 0.5129 data_time: 0.0183 memory: 14901 loss: 5.8521 loss_prob: 3.5753 loss_thr: 1.3164 loss_db: 0.9605 2022/11/02 12:17:32 - mmengine - INFO - Epoch(train) [14][60/63] lr: 2.6436e-04 eta: 21:52:33 time: 0.5659 data_time: 0.0111 memory: 14901 loss: 5.7063 loss_prob: 3.4508 loss_thr: 1.2639 loss_db: 0.9916 2022/11/02 12:17:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:17:39 - mmengine - INFO - Epoch(train) [15][5/63] lr: 2.8455e-04 eta: 21:52:33 time: 0.8500 data_time: 0.3083 memory: 14901 loss: 5.5280 loss_prob: 3.2969 loss_thr: 1.2373 loss_db: 0.9938 2022/11/02 12:17:42 - mmengine - INFO - Epoch(train) [15][10/63] lr: 2.8455e-04 eta: 21:45:46 time: 0.9008 data_time: 0.3072 memory: 14901 loss: 5.4030 loss_prob: 3.2028 loss_thr: 1.2024 loss_db: 0.9978 2022/11/02 12:17:45 - mmengine - INFO - Epoch(train) [15][15/63] lr: 2.8455e-04 eta: 21:45:46 time: 0.6122 data_time: 0.0062 memory: 14901 loss: 5.3201 loss_prob: 3.1386 loss_thr: 1.1821 loss_db: 0.9994 2022/11/02 12:17:48 - mmengine - INFO - Epoch(train) [15][20/63] lr: 2.8455e-04 eta: 21:38:31 time: 0.5360 data_time: 0.0046 memory: 14901 loss: 5.2735 loss_prob: 3.0880 loss_thr: 1.1857 loss_db: 0.9997 2022/11/02 12:17:51 - mmengine - INFO - Epoch(train) [15][25/63] lr: 2.8455e-04 eta: 21:38:31 time: 0.5655 data_time: 0.0378 memory: 14901 loss: 5.2434 loss_prob: 3.0330 loss_thr: 1.2106 loss_db: 0.9998 2022/11/02 12:17:53 - mmengine - INFO - Epoch(train) [15][30/63] lr: 2.8455e-04 eta: 21:31:55 time: 0.5728 data_time: 0.0381 memory: 14901 loss: 5.2404 loss_prob: 3.0312 loss_thr: 1.2094 loss_db: 0.9999 2022/11/02 12:17:56 - mmengine - INFO - Epoch(train) [15][35/63] lr: 2.8455e-04 eta: 21:31:55 time: 0.5526 data_time: 0.0046 memory: 14901 loss: 5.2474 loss_prob: 3.0607 loss_thr: 1.1869 loss_db: 0.9999 2022/11/02 12:17:59 - mmengine - INFO - Epoch(train) [15][40/63] lr: 2.8455e-04 eta: 21:25:10 time: 0.5508 data_time: 0.0044 memory: 14901 loss: 5.2411 loss_prob: 3.0579 loss_thr: 1.1833 loss_db: 0.9999 2022/11/02 12:18:01 - mmengine - INFO - Epoch(train) [15][45/63] lr: 2.8455e-04 eta: 21:25:10 time: 0.4962 data_time: 0.0046 memory: 14901 loss: 5.2484 loss_prob: 3.0485 loss_thr: 1.1999 loss_db: 0.9999 2022/11/02 12:18:04 - mmengine - INFO - Epoch(train) [15][50/63] lr: 2.8455e-04 eta: 21:17:52 time: 0.4983 data_time: 0.0208 memory: 14901 loss: 5.2081 loss_prob: 3.0182 loss_thr: 1.1900 loss_db: 0.9999 2022/11/02 12:18:06 - mmengine - INFO - Epoch(train) [15][55/63] lr: 2.8455e-04 eta: 21:17:52 time: 0.4824 data_time: 0.0207 memory: 14901 loss: 5.1403 loss_prob: 2.9740 loss_thr: 1.1663 loss_db: 0.9999 2022/11/02 12:18:09 - mmengine - INFO - Epoch(train) [15][60/63] lr: 2.8455e-04 eta: 21:10:28 time: 0.4790 data_time: 0.0049 memory: 14901 loss: 5.1272 loss_prob: 2.9612 loss_thr: 1.1661 loss_db: 0.9999 2022/11/02 12:18:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:18:16 - mmengine - INFO - Epoch(train) [16][5/63] lr: 3.0473e-04 eta: 21:10:28 time: 0.7793 data_time: 0.2593 memory: 14901 loss: 5.1106 loss_prob: 2.9418 loss_thr: 1.1689 loss_db: 0.9999 2022/11/02 12:18:18 - mmengine - INFO - Epoch(train) [16][10/63] lr: 3.0473e-04 eta: 21:03:17 time: 0.7933 data_time: 0.2608 memory: 14901 loss: 5.0925 loss_prob: 2.9255 loss_thr: 1.1671 loss_db: 0.9999 2022/11/02 12:18:20 - mmengine - INFO - Epoch(train) [16][15/63] lr: 3.0473e-04 eta: 21:03:17 time: 0.4877 data_time: 0.0102 memory: 14901 loss: 5.0780 loss_prob: 2.9141 loss_thr: 1.1639 loss_db: 1.0000 2022/11/02 12:18:23 - mmengine - INFO - Epoch(train) [16][20/63] lr: 3.0473e-04 eta: 20:56:15 time: 0.4827 data_time: 0.0086 memory: 14901 loss: 5.1137 loss_prob: 2.9344 loss_thr: 1.1793 loss_db: 1.0000 2022/11/02 12:18:25 - mmengine - INFO - Epoch(train) [16][25/63] lr: 3.0473e-04 eta: 20:56:15 time: 0.4984 data_time: 0.0282 memory: 14901 loss: 5.2025 loss_prob: 2.9764 loss_thr: 1.2261 loss_db: 1.0000 2022/11/02 12:18:28 - mmengine - INFO - Epoch(train) [16][30/63] lr: 3.0473e-04 eta: 20:50:02 time: 0.5366 data_time: 0.0325 memory: 14901 loss: 5.1923 loss_prob: 2.9800 loss_thr: 1.2124 loss_db: 1.0000 2022/11/02 12:18:31 - mmengine - INFO - Epoch(train) [16][35/63] lr: 3.0473e-04 eta: 20:50:02 time: 0.5097 data_time: 0.0114 memory: 14901 loss: 5.1092 loss_prob: 2.9445 loss_thr: 1.1647 loss_db: 0.9999 2022/11/02 12:18:33 - mmengine - INFO - Epoch(train) [16][40/63] lr: 3.0473e-04 eta: 20:43:32 time: 0.5029 data_time: 0.0112 memory: 14901 loss: 5.0962 loss_prob: 2.9312 loss_thr: 1.1650 loss_db: 0.9999 2022/11/02 12:18:35 - mmengine - INFO - Epoch(train) [16][45/63] lr: 3.0473e-04 eta: 20:43:32 time: 0.4945 data_time: 0.0089 memory: 14901 loss: 5.0913 loss_prob: 2.9311 loss_thr: 1.1602 loss_db: 0.9999 2022/11/02 12:18:38 - mmengine - INFO - Epoch(train) [16][50/63] lr: 3.0473e-04 eta: 20:36:52 time: 0.4795 data_time: 0.0167 memory: 14901 loss: 5.0671 loss_prob: 2.9112 loss_thr: 1.1560 loss_db: 1.0000 2022/11/02 12:18:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:18:40 - mmengine - INFO - Epoch(train) [16][55/63] lr: 3.0473e-04 eta: 20:36:52 time: 0.5033 data_time: 0.0213 memory: 14901 loss: 5.0535 loss_prob: 2.8919 loss_thr: 1.1616 loss_db: 1.0000 2022/11/02 12:18:43 - mmengine - INFO - Epoch(train) [16][60/63] lr: 3.0473e-04 eta: 20:30:35 time: 0.5012 data_time: 0.0108 memory: 14901 loss: 5.0493 loss_prob: 2.8853 loss_thr: 1.1640 loss_db: 1.0000 2022/11/02 12:18:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:18:50 - mmengine - INFO - Epoch(train) [17][5/63] lr: 3.2491e-04 eta: 20:30:35 time: 0.7823 data_time: 0.2204 memory: 14901 loss: 5.0611 loss_prob: 2.9056 loss_thr: 1.1555 loss_db: 1.0000 2022/11/02 12:18:52 - mmengine - INFO - Epoch(train) [17][10/63] lr: 3.2491e-04 eta: 20:24:37 time: 0.8154 data_time: 0.2195 memory: 14901 loss: 5.0919 loss_prob: 2.9348 loss_thr: 1.1571 loss_db: 1.0000 2022/11/02 12:18:55 - mmengine - INFO - Epoch(train) [17][15/63] lr: 3.2491e-04 eta: 20:24:37 time: 0.4691 data_time: 0.0050 memory: 14901 loss: 5.1079 loss_prob: 2.9506 loss_thr: 1.1574 loss_db: 0.9999 2022/11/02 12:18:57 - mmengine - INFO - Epoch(train) [17][20/63] lr: 3.2491e-04 eta: 20:18:19 time: 0.4777 data_time: 0.0050 memory: 14901 loss: 5.0918 loss_prob: 2.9318 loss_thr: 1.1601 loss_db: 0.9999 2022/11/02 12:18:59 - mmengine - INFO - Epoch(train) [17][25/63] lr: 3.2491e-04 eta: 20:18:19 time: 0.4873 data_time: 0.0119 memory: 14901 loss: 5.0656 loss_prob: 2.9069 loss_thr: 1.1588 loss_db: 1.0000 2022/11/02 12:19:02 - mmengine - INFO - Epoch(train) [17][30/63] lr: 3.2491e-04 eta: 20:12:04 time: 0.4714 data_time: 0.0367 memory: 14901 loss: 5.0409 loss_prob: 2.8838 loss_thr: 1.1571 loss_db: 1.0000 2022/11/02 12:19:04 - mmengine - INFO - Epoch(train) [17][35/63] lr: 3.2491e-04 eta: 20:12:04 time: 0.5055 data_time: 0.0297 memory: 14901 loss: 5.0241 loss_prob: 2.8622 loss_thr: 1.1619 loss_db: 1.0000 2022/11/02 12:19:07 - mmengine - INFO - Epoch(train) [17][40/63] lr: 3.2491e-04 eta: 20:06:07 time: 0.4868 data_time: 0.0047 memory: 14901 loss: 5.0290 loss_prob: 2.8702 loss_thr: 1.1588 loss_db: 1.0000 2022/11/02 12:19:09 - mmengine - INFO - Epoch(train) [17][45/63] lr: 3.2491e-04 eta: 20:06:07 time: 0.4570 data_time: 0.0049 memory: 14901 loss: 5.0400 loss_prob: 2.8832 loss_thr: 1.1569 loss_db: 1.0000 2022/11/02 12:19:12 - mmengine - INFO - Epoch(train) [17][50/63] lr: 3.2491e-04 eta: 20:00:13 time: 0.4832 data_time: 0.0121 memory: 14901 loss: 5.0776 loss_prob: 2.9158 loss_thr: 1.1618 loss_db: 1.0000 2022/11/02 12:19:14 - mmengine - INFO - Epoch(train) [17][55/63] lr: 3.2491e-04 eta: 20:00:13 time: 0.5087 data_time: 0.0232 memory: 14901 loss: 5.1105 loss_prob: 2.9513 loss_thr: 1.1593 loss_db: 1.0000 2022/11/02 12:19:16 - mmengine - INFO - Epoch(train) [17][60/63] lr: 3.2491e-04 eta: 19:54:31 time: 0.4889 data_time: 0.0159 memory: 14901 loss: 5.1056 loss_prob: 2.9535 loss_thr: 1.1522 loss_db: 1.0000 2022/11/02 12:19:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:19:22 - mmengine - INFO - Epoch(train) [18][5/63] lr: 3.4509e-04 eta: 19:54:31 time: 0.6783 data_time: 0.1969 memory: 14901 loss: 5.0828 loss_prob: 2.9257 loss_thr: 1.1572 loss_db: 1.0000 2022/11/02 12:19:26 - mmengine - INFO - Epoch(train) [18][10/63] lr: 3.4509e-04 eta: 19:49:13 time: 0.8076 data_time: 0.2104 memory: 14901 loss: 5.0601 loss_prob: 2.9041 loss_thr: 1.1561 loss_db: 1.0000 2022/11/02 12:19:28 - mmengine - INFO - Epoch(train) [18][15/63] lr: 3.4509e-04 eta: 19:49:13 time: 0.5802 data_time: 0.0200 memory: 14901 loss: 5.0396 loss_prob: 2.8862 loss_thr: 1.1535 loss_db: 1.0000 2022/11/02 12:19:31 - mmengine - INFO - Epoch(train) [18][20/63] lr: 3.4509e-04 eta: 19:44:04 time: 0.5188 data_time: 0.0062 memory: 14901 loss: 5.0528 loss_prob: 2.8938 loss_thr: 1.1591 loss_db: 1.0000 2022/11/02 12:19:34 - mmengine - INFO - Epoch(train) [18][25/63] lr: 3.4509e-04 eta: 19:44:04 time: 0.5630 data_time: 0.0094 memory: 14901 loss: 5.0705 loss_prob: 2.9037 loss_thr: 1.1669 loss_db: 1.0000 2022/11/02 12:19:38 - mmengine - INFO - Epoch(train) [18][30/63] lr: 3.4509e-04 eta: 19:40:48 time: 0.6773 data_time: 0.0351 memory: 14901 loss: 5.0687 loss_prob: 2.9034 loss_thr: 1.1653 loss_db: 1.0000 2022/11/02 12:19:41 - mmengine - INFO - Epoch(train) [18][35/63] lr: 3.4509e-04 eta: 19:40:48 time: 0.7121 data_time: 0.0300 memory: 14901 loss: 5.0616 loss_prob: 2.9003 loss_thr: 1.1613 loss_db: 1.0000 2022/11/02 12:19:43 - mmengine - INFO - Epoch(train) [18][40/63] lr: 3.4509e-04 eta: 19:36:25 time: 0.5732 data_time: 0.0064 memory: 14901 loss: 5.0543 loss_prob: 2.8958 loss_thr: 1.1586 loss_db: 1.0000 2022/11/02 12:19:46 - mmengine - INFO - Epoch(train) [18][45/63] lr: 3.4509e-04 eta: 19:36:25 time: 0.4985 data_time: 0.0084 memory: 14901 loss: 5.0381 loss_prob: 2.8840 loss_thr: 1.1541 loss_db: 1.0000 2022/11/02 12:19:50 - mmengine - INFO - Epoch(train) [18][50/63] lr: 3.4509e-04 eta: 19:32:41 time: 0.6244 data_time: 0.0152 memory: 14901 loss: 5.0417 loss_prob: 2.8859 loss_thr: 1.1558 loss_db: 1.0000 2022/11/02 12:19:52 - mmengine - INFO - Epoch(train) [18][55/63] lr: 3.4509e-04 eta: 19:32:41 time: 0.6445 data_time: 0.0261 memory: 14901 loss: 5.0505 loss_prob: 2.8937 loss_thr: 1.1569 loss_db: 1.0000 2022/11/02 12:19:55 - mmengine - INFO - Epoch(train) [18][60/63] lr: 3.4509e-04 eta: 19:27:42 time: 0.5063 data_time: 0.0173 memory: 14901 loss: 5.0557 loss_prob: 2.8940 loss_thr: 1.1617 loss_db: 1.0000 2022/11/02 12:19:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:20:04 - mmengine - INFO - Epoch(train) [19][5/63] lr: 3.6527e-04 eta: 19:27:42 time: 0.9867 data_time: 0.3436 memory: 14901 loss: 5.0680 loss_prob: 2.9133 loss_thr: 1.1547 loss_db: 1.0000 2022/11/02 12:20:07 - mmengine - INFO - Epoch(train) [19][10/63] lr: 3.6527e-04 eta: 19:25:49 time: 1.0671 data_time: 0.3432 memory: 14901 loss: 5.0634 loss_prob: 2.9120 loss_thr: 1.1514 loss_db: 1.0000 2022/11/02 12:20:10 - mmengine - INFO - Epoch(train) [19][15/63] lr: 3.6527e-04 eta: 19:25:49 time: 0.6400 data_time: 0.0079 memory: 14901 loss: 5.0488 loss_prob: 2.8979 loss_thr: 1.1510 loss_db: 1.0000 2022/11/02 12:20:13 - mmengine - INFO - Epoch(train) [19][20/63] lr: 3.6527e-04 eta: 19:22:10 time: 0.6145 data_time: 0.0060 memory: 14901 loss: 5.0442 loss_prob: 2.8879 loss_thr: 1.1563 loss_db: 1.0000 2022/11/02 12:20:16 - mmengine - INFO - Epoch(train) [19][25/63] lr: 3.6527e-04 eta: 19:22:10 time: 0.6091 data_time: 0.0260 memory: 14901 loss: 5.0485 loss_prob: 2.8888 loss_thr: 1.1598 loss_db: 1.0000 2022/11/02 12:20:19 - mmengine - INFO - Epoch(train) [19][30/63] lr: 3.6527e-04 eta: 19:18:53 time: 0.6441 data_time: 0.0256 memory: 14901 loss: 5.0533 loss_prob: 2.8938 loss_thr: 1.1595 loss_db: 1.0000 2022/11/02 12:20:22 - mmengine - INFO - Epoch(train) [19][35/63] lr: 3.6527e-04 eta: 19:18:53 time: 0.5935 data_time: 0.0050 memory: 14901 loss: 5.0781 loss_prob: 2.9083 loss_thr: 1.1699 loss_db: 1.0000 2022/11/02 12:20:25 - mmengine - INFO - Epoch(train) [19][40/63] lr: 3.6527e-04 eta: 19:14:13 time: 0.5072 data_time: 0.0050 memory: 14901 loss: 5.1045 loss_prob: 2.9365 loss_thr: 1.1680 loss_db: 1.0000 2022/11/02 12:20:28 - mmengine - INFO - Epoch(train) [19][45/63] lr: 3.6527e-04 eta: 19:14:13 time: 0.5692 data_time: 0.0048 memory: 14901 loss: 5.1515 loss_prob: 2.9932 loss_thr: 1.1583 loss_db: 1.0000 2022/11/02 12:20:31 - mmengine - INFO - Epoch(train) [19][50/63] lr: 3.6527e-04 eta: 19:11:27 time: 0.6803 data_time: 0.0205 memory: 14901 loss: 5.2653 loss_prob: 3.0905 loss_thr: 1.1748 loss_db: 1.0000 2022/11/02 12:20:34 - mmengine - INFO - Epoch(train) [19][55/63] lr: 3.6527e-04 eta: 19:11:27 time: 0.6073 data_time: 0.0229 memory: 14901 loss: 5.3521 loss_prob: 3.1733 loss_thr: 1.1788 loss_db: 1.0000 2022/11/02 12:20:37 - mmengine - INFO - Epoch(train) [19][60/63] lr: 3.6527e-04 eta: 19:07:24 time: 0.5533 data_time: 0.0071 memory: 14901 loss: 5.3926 loss_prob: 3.1881 loss_thr: 1.2045 loss_db: 1.0000 2022/11/02 12:20:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:20:43 - mmengine - INFO - Epoch(train) [20][5/63] lr: 3.8545e-04 eta: 19:07:24 time: 0.7284 data_time: 0.1904 memory: 14901 loss: 5.3307 loss_prob: 3.1231 loss_thr: 1.2076 loss_db: 1.0000 2022/11/02 12:20:45 - mmengine - INFO - Epoch(train) [20][10/63] lr: 3.8545e-04 eta: 19:02:06 time: 0.7064 data_time: 0.1927 memory: 14901 loss: 5.2078 loss_prob: 3.0386 loss_thr: 1.1693 loss_db: 1.0000 2022/11/02 12:20:48 - mmengine - INFO - Epoch(train) [20][15/63] lr: 3.8545e-04 eta: 19:02:06 time: 0.4760 data_time: 0.0080 memory: 14901 loss: 5.1671 loss_prob: 3.0002 loss_thr: 1.1669 loss_db: 1.0000 2022/11/02 12:20:51 - mmengine - INFO - Epoch(train) [20][20/63] lr: 3.8545e-04 eta: 18:57:50 time: 0.5186 data_time: 0.0060 memory: 14901 loss: 5.1757 loss_prob: 3.0138 loss_thr: 1.1620 loss_db: 1.0000 2022/11/02 12:20:53 - mmengine - INFO - Epoch(train) [20][25/63] lr: 3.8545e-04 eta: 18:57:50 time: 0.5354 data_time: 0.0070 memory: 14901 loss: 5.2353 loss_prob: 3.0540 loss_thr: 1.1814 loss_db: 1.0000 2022/11/02 12:20:56 - mmengine - INFO - Epoch(train) [20][30/63] lr: 3.8545e-04 eta: 18:53:37 time: 0.5155 data_time: 0.0351 memory: 14901 loss: 5.2395 loss_prob: 3.0583 loss_thr: 1.1812 loss_db: 1.0000 2022/11/02 12:20:58 - mmengine - INFO - Epoch(train) [20][35/63] lr: 3.8545e-04 eta: 18:53:37 time: 0.4870 data_time: 0.0332 memory: 14901 loss: 5.1780 loss_prob: 3.0197 loss_thr: 1.1583 loss_db: 1.0000 2022/11/02 12:21:01 - mmengine - INFO - Epoch(train) [20][40/63] lr: 3.8545e-04 eta: 18:49:12 time: 0.4886 data_time: 0.0044 memory: 14901 loss: 5.1689 loss_prob: 2.9988 loss_thr: 1.1701 loss_db: 1.0000 2022/11/02 12:21:03 - mmengine - INFO - Epoch(train) [20][45/63] lr: 3.8545e-04 eta: 18:49:12 time: 0.5097 data_time: 0.0048 memory: 14901 loss: 5.1476 loss_prob: 2.9754 loss_thr: 1.1723 loss_db: 1.0000 2022/11/02 12:21:06 - mmengine - INFO - Epoch(train) [20][50/63] lr: 3.8545e-04 eta: 18:44:59 time: 0.5013 data_time: 0.0219 memory: 14901 loss: 5.1299 loss_prob: 2.9713 loss_thr: 1.1587 loss_db: 1.0000 2022/11/02 12:21:08 - mmengine - INFO - Epoch(train) [20][55/63] lr: 3.8545e-04 eta: 18:44:59 time: 0.5089 data_time: 0.0214 memory: 14901 loss: 5.1189 loss_prob: 2.9622 loss_thr: 1.1567 loss_db: 1.0000 2022/11/02 12:21:11 - mmengine - INFO - Epoch(train) [20][60/63] lr: 3.8545e-04 eta: 18:40:53 time: 0.5074 data_time: 0.0044 memory: 14901 loss: 5.0973 loss_prob: 2.9309 loss_thr: 1.1664 loss_db: 1.0000 2022/11/02 12:21:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:21:12 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/11/02 12:23:27 - mmengine - INFO - Epoch(val) [20][5/500] eta: 18:40:53 time: 26.3208 data_time: 25.0998 memory: 34493 2022/11/02 12:23:27 - mmengine - INFO - Epoch(val) [20][10/500] eta: 1:47:36 time: 13.1769 data_time: 12.5510 memory: 1008 2022/11/02 12:23:27 - mmengine - INFO - Epoch(val) [20][15/500] eta: 1:47:36 time: 0.0334 data_time: 0.0024 memory: 1008 2022/11/02 12:23:27 - mmengine - INFO - Epoch(val) [20][20/500] eta: 0:00:16 time: 0.0339 data_time: 0.0024 memory: 1008 2022/11/02 12:23:28 - mmengine - INFO - Epoch(val) [20][25/500] eta: 0:00:16 time: 0.0340 data_time: 0.0027 memory: 1008 2022/11/02 12:23:28 - mmengine - INFO - Epoch(val) [20][30/500] eta: 0:00:15 time: 0.0337 data_time: 0.0027 memory: 1008 2022/11/02 12:23:28 - mmengine - INFO - Epoch(val) [20][35/500] eta: 0:00:15 time: 0.0330 data_time: 0.0023 memory: 1008 2022/11/02 12:23:28 - mmengine - INFO - Epoch(val) [20][40/500] eta: 0:00:15 time: 0.0345 data_time: 0.0022 memory: 1008 2022/11/02 12:23:28 - mmengine - INFO - Epoch(val) [20][45/500] eta: 0:00:15 time: 0.0338 data_time: 0.0023 memory: 1008 2022/11/02 12:23:28 - mmengine - INFO - Epoch(val) [20][50/500] eta: 0:00:13 time: 0.0303 data_time: 0.0022 memory: 1008 2022/11/02 12:23:29 - mmengine - INFO - Epoch(val) [20][55/500] eta: 0:00:13 time: 0.0296 data_time: 0.0020 memory: 1008 2022/11/02 12:23:29 - mmengine - INFO - Epoch(val) [20][60/500] eta: 0:00:13 time: 0.0298 data_time: 0.0019 memory: 1008 2022/11/02 12:23:29 - mmengine - INFO - Epoch(val) [20][65/500] eta: 0:00:13 time: 0.0299 data_time: 0.0020 memory: 1008 2022/11/02 12:23:29 - mmengine - INFO - Epoch(val) [20][70/500] eta: 0:00:12 time: 0.0298 data_time: 0.0020 memory: 1008 2022/11/02 12:23:29 - mmengine - INFO - Epoch(val) [20][75/500] eta: 0:00:12 time: 0.0304 data_time: 0.0022 memory: 1008 2022/11/02 12:23:29 - mmengine - INFO - Epoch(val) [20][80/500] eta: 0:00:13 time: 0.0315 data_time: 0.0023 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][85/500] eta: 0:00:13 time: 0.0318 data_time: 0.0023 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][90/500] eta: 0:00:12 time: 0.0317 data_time: 0.0024 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][95/500] eta: 0:00:12 time: 0.0315 data_time: 0.0025 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][100/500] eta: 0:00:12 time: 0.0311 data_time: 0.0024 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][105/500] eta: 0:00:12 time: 0.0317 data_time: 0.0023 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][110/500] eta: 0:00:12 time: 0.0317 data_time: 0.0022 memory: 1008 2022/11/02 12:23:30 - mmengine - INFO - Epoch(val) [20][115/500] eta: 0:00:12 time: 0.0308 data_time: 0.0023 memory: 1008 2022/11/02 12:23:31 - mmengine - INFO - Epoch(val) [20][120/500] eta: 0:00:11 time: 0.0307 data_time: 0.0022 memory: 1008 2022/11/02 12:23:31 - mmengine - INFO - Epoch(val) [20][125/500] eta: 0:00:11 time: 0.0305 data_time: 0.0022 memory: 1008 2022/11/02 12:23:31 - mmengine - INFO - Epoch(val) [20][130/500] eta: 0:00:11 time: 0.0307 data_time: 0.0022 memory: 1008 2022/11/02 12:23:31 - mmengine - INFO - Epoch(val) [20][135/500] eta: 0:00:11 time: 0.0318 data_time: 0.0022 memory: 1008 2022/11/02 12:23:31 - mmengine - INFO - Epoch(val) [20][140/500] eta: 0:00:11 time: 0.0325 data_time: 0.0024 memory: 1008 2022/11/02 12:23:31 - mmengine - INFO - Epoch(val) [20][145/500] eta: 0:00:11 time: 0.0325 data_time: 0.0026 memory: 1008 2022/11/02 12:23:32 - mmengine - INFO - Epoch(val) [20][150/500] eta: 0:00:11 time: 0.0328 data_time: 0.0025 memory: 1008 2022/11/02 12:23:32 - mmengine - INFO - Epoch(val) [20][155/500] eta: 0:00:11 time: 0.0313 data_time: 0.0022 memory: 1008 2022/11/02 12:23:32 - mmengine - INFO - Epoch(val) [20][160/500] eta: 0:00:10 time: 0.0298 data_time: 0.0020 memory: 1008 2022/11/02 12:23:32 - mmengine - INFO - Epoch(val) [20][165/500] eta: 0:00:10 time: 0.0300 data_time: 0.0020 memory: 1008 2022/11/02 12:23:32 - mmengine - INFO - Epoch(val) [20][170/500] eta: 0:00:10 time: 0.0313 data_time: 0.0022 memory: 1008 2022/11/02 12:23:32 - mmengine - INFO - Epoch(val) [20][175/500] eta: 0:00:10 time: 0.0317 data_time: 0.0023 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][180/500] eta: 0:00:09 time: 0.0310 data_time: 0.0023 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][185/500] eta: 0:00:09 time: 0.0309 data_time: 0.0023 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][190/500] eta: 0:00:09 time: 0.0307 data_time: 0.0021 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][195/500] eta: 0:00:09 time: 0.0302 data_time: 0.0019 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][200/500] eta: 0:00:08 time: 0.0298 data_time: 0.0019 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][205/500] eta: 0:00:08 time: 0.0300 data_time: 0.0020 memory: 1008 2022/11/02 12:23:33 - mmengine - INFO - Epoch(val) [20][210/500] eta: 0:00:08 time: 0.0304 data_time: 0.0022 memory: 1008 2022/11/02 12:23:34 - mmengine - INFO - Epoch(val) [20][215/500] eta: 0:00:08 time: 0.0307 data_time: 0.0023 memory: 1008 2022/11/02 12:23:34 - mmengine - INFO - Epoch(val) [20][220/500] eta: 0:00:08 time: 0.0307 data_time: 0.0022 memory: 1008 2022/11/02 12:23:34 - mmengine - INFO - Epoch(val) [20][225/500] eta: 0:00:08 time: 0.0316 data_time: 0.0022 memory: 1008 2022/11/02 12:23:34 - mmengine - INFO - Epoch(val) [20][230/500] eta: 0:00:08 time: 0.0325 data_time: 0.0022 memory: 1008 2022/11/02 12:23:34 - mmengine - INFO - Epoch(val) [20][235/500] eta: 0:00:08 time: 0.0317 data_time: 0.0022 memory: 1008 2022/11/02 12:23:34 - mmengine - INFO - Epoch(val) [20][240/500] eta: 0:00:07 time: 0.0307 data_time: 0.0023 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][245/500] eta: 0:00:07 time: 0.0310 data_time: 0.0023 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][250/500] eta: 0:00:07 time: 0.0310 data_time: 0.0023 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][255/500] eta: 0:00:07 time: 0.0307 data_time: 0.0023 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][260/500] eta: 0:00:07 time: 0.0308 data_time: 0.0023 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][265/500] eta: 0:00:07 time: 0.0310 data_time: 0.0023 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][270/500] eta: 0:00:07 time: 0.0311 data_time: 0.0024 memory: 1008 2022/11/02 12:23:35 - mmengine - INFO - Epoch(val) [20][275/500] eta: 0:00:07 time: 0.0310 data_time: 0.0023 memory: 1008 2022/11/02 12:23:36 - mmengine - INFO - Epoch(val) [20][280/500] eta: 0:00:07 time: 0.0329 data_time: 0.0025 memory: 1008 2022/11/02 12:23:36 - mmengine - INFO - Epoch(val) [20][285/500] eta: 0:00:07 time: 0.0332 data_time: 0.0025 memory: 1008 2022/11/02 12:23:36 - mmengine - INFO - Epoch(val) [20][290/500] eta: 0:00:06 time: 0.0309 data_time: 0.0023 memory: 1008 2022/11/02 12:23:36 - mmengine - INFO - Epoch(val) [20][295/500] eta: 0:00:06 time: 0.0306 data_time: 0.0022 memory: 1008 2022/11/02 12:23:36 - mmengine - INFO - Epoch(val) [20][300/500] eta: 0:00:06 time: 0.0307 data_time: 0.0023 memory: 1008 2022/11/02 12:23:36 - mmengine - INFO - Epoch(val) [20][305/500] eta: 0:00:06 time: 0.0308 data_time: 0.0023 memory: 1008 2022/11/02 12:23:37 - mmengine - INFO - Epoch(val) [20][310/500] eta: 0:00:06 time: 0.0333 data_time: 0.0024 memory: 1008 2022/11/02 12:23:37 - mmengine - INFO - Epoch(val) [20][315/500] eta: 0:00:06 time: 0.0335 data_time: 0.0025 memory: 1008 2022/11/02 12:23:37 - mmengine - INFO - Epoch(val) [20][320/500] eta: 0:00:05 time: 0.0318 data_time: 0.0026 memory: 1008 2022/11/02 12:23:37 - mmengine - INFO - Epoch(val) [20][325/500] eta: 0:00:05 time: 0.0319 data_time: 0.0025 memory: 1008 2022/11/02 12:23:37 - mmengine - INFO - Epoch(val) [20][330/500] eta: 0:00:05 time: 0.0311 data_time: 0.0024 memory: 1008 2022/11/02 12:23:37 - mmengine - INFO - Epoch(val) [20][335/500] eta: 0:00:05 time: 0.0306 data_time: 0.0023 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][340/500] eta: 0:00:05 time: 0.0315 data_time: 0.0023 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][345/500] eta: 0:00:05 time: 0.0319 data_time: 0.0024 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][350/500] eta: 0:00:04 time: 0.0313 data_time: 0.0024 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][355/500] eta: 0:00:04 time: 0.0313 data_time: 0.0023 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][360/500] eta: 0:00:04 time: 0.0319 data_time: 0.0023 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][365/500] eta: 0:00:04 time: 0.0318 data_time: 0.0023 memory: 1008 2022/11/02 12:23:38 - mmengine - INFO - Epoch(val) [20][370/500] eta: 0:00:04 time: 0.0308 data_time: 0.0024 memory: 1008 2022/11/02 12:23:39 - mmengine - INFO - Epoch(val) [20][375/500] eta: 0:00:04 time: 0.0309 data_time: 0.0022 memory: 1008 2022/11/02 12:23:39 - mmengine - INFO - Epoch(val) [20][380/500] eta: 0:00:03 time: 0.0323 data_time: 0.0025 memory: 1008 2022/11/02 12:23:39 - mmengine - INFO - Epoch(val) [20][385/500] eta: 0:00:03 time: 0.0324 data_time: 0.0026 memory: 1008 2022/11/02 12:23:39 - mmengine - INFO - Epoch(val) [20][390/500] eta: 0:00:03 time: 0.0311 data_time: 0.0024 memory: 1008 2022/11/02 12:23:39 - mmengine - INFO - Epoch(val) [20][395/500] eta: 0:00:03 time: 0.0311 data_time: 0.0024 memory: 1008 2022/11/02 12:23:39 - mmengine - INFO - Epoch(val) [20][400/500] eta: 0:00:03 time: 0.0307 data_time: 0.0022 memory: 1008 2022/11/02 12:23:40 - mmengine - INFO - Epoch(val) [20][405/500] eta: 0:00:03 time: 0.0310 data_time: 0.0023 memory: 1008 2022/11/02 12:23:40 - mmengine - INFO - Epoch(val) [20][410/500] eta: 0:00:02 time: 0.0315 data_time: 0.0024 memory: 1008 2022/11/02 12:23:40 - mmengine - INFO - Epoch(val) [20][415/500] eta: 0:00:02 time: 0.0314 data_time: 0.0024 memory: 1008 2022/11/02 12:23:40 - mmengine - INFO - Epoch(val) [20][420/500] eta: 0:00:02 time: 0.0327 data_time: 0.0025 memory: 1008 2022/11/02 12:23:40 - mmengine - INFO - Epoch(val) [20][425/500] eta: 0:00:02 time: 0.0330 data_time: 0.0026 memory: 1008 2022/11/02 12:23:40 - mmengine - INFO - Epoch(val) [20][430/500] eta: 0:00:02 time: 0.0320 data_time: 0.0024 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][435/500] eta: 0:00:02 time: 0.0317 data_time: 0.0023 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][440/500] eta: 0:00:01 time: 0.0313 data_time: 0.0023 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][445/500] eta: 0:00:01 time: 0.0310 data_time: 0.0024 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][450/500] eta: 0:00:01 time: 0.0307 data_time: 0.0023 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][455/500] eta: 0:00:01 time: 0.0312 data_time: 0.0024 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][460/500] eta: 0:00:01 time: 0.0316 data_time: 0.0026 memory: 1008 2022/11/02 12:23:41 - mmengine - INFO - Epoch(val) [20][465/500] eta: 0:00:01 time: 0.0308 data_time: 0.0024 memory: 1008 2022/11/02 12:23:42 - mmengine - INFO - Epoch(val) [20][470/500] eta: 0:00:00 time: 0.0307 data_time: 0.0022 memory: 1008 2022/11/02 12:23:42 - mmengine - INFO - Epoch(val) [20][475/500] eta: 0:00:00 time: 0.0306 data_time: 0.0021 memory: 1008 2022/11/02 12:23:42 - mmengine - INFO - Epoch(val) [20][480/500] eta: 0:00:00 time: 0.0313 data_time: 0.0021 memory: 1008 2022/11/02 12:23:42 - mmengine - INFO - Epoch(val) [20][485/500] eta: 0:00:00 time: 0.0318 data_time: 0.0022 memory: 1008 2022/11/02 12:23:42 - mmengine - INFO - Epoch(val) [20][490/500] eta: 0:00:00 time: 0.0349 data_time: 0.0025 memory: 1008 2022/11/02 12:23:42 - mmengine - INFO - Epoch(val) [20][495/500] eta: 0:00:00 time: 0.0371 data_time: 0.0028 memory: 1008 2022/11/02 12:23:43 - mmengine - INFO - Epoch(val) [20][500/500] eta: 0:00:00 time: 0.0328 data_time: 0.0025 memory: 1008 2022/11/02 12:23:43 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:23:43 - mmengine - INFO - Epoch(val) [20][500/500] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/11/02 12:23:47 - mmengine - INFO - Epoch(train) [21][5/63] lr: 4.0564e-04 eta: 0:00:00 time: 0.6973 data_time: 0.1957 memory: 14901 loss: 5.0678 loss_prob: 2.9084 loss_thr: 1.1595 loss_db: 1.0000 2022/11/02 12:23:50 - mmengine - INFO - Epoch(train) [21][10/63] lr: 4.0564e-04 eta: 18:36:02 time: 0.6997 data_time: 0.2000 memory: 14901 loss: 5.0712 loss_prob: 2.9134 loss_thr: 1.1579 loss_db: 1.0000 2022/11/02 12:23:52 - mmengine - INFO - Epoch(train) [21][15/63] lr: 4.0564e-04 eta: 18:36:02 time: 0.4641 data_time: 0.0088 memory: 14901 loss: 5.0765 loss_prob: 2.9169 loss_thr: 1.1596 loss_db: 1.0000 2022/11/02 12:23:54 - mmengine - INFO - Epoch(train) [21][20/63] lr: 4.0564e-04 eta: 18:31:35 time: 0.4559 data_time: 0.0045 memory: 14901 loss: 5.0842 loss_prob: 2.9229 loss_thr: 1.1613 loss_db: 1.0000 2022/11/02 12:23:57 - mmengine - INFO - Epoch(train) [21][25/63] lr: 4.0564e-04 eta: 18:31:35 time: 0.4838 data_time: 0.0183 memory: 14901 loss: 5.0586 loss_prob: 2.9018 loss_thr: 1.1568 loss_db: 1.0000 2022/11/02 12:23:59 - mmengine - INFO - Epoch(train) [21][30/63] lr: 4.0564e-04 eta: 18:27:33 time: 0.4934 data_time: 0.0277 memory: 14901 loss: 5.0559 loss_prob: 2.8929 loss_thr: 1.1630 loss_db: 1.0000 2022/11/02 12:24:02 - mmengine - INFO - Epoch(train) [21][35/63] lr: 4.0564e-04 eta: 18:27:33 time: 0.4719 data_time: 0.0209 memory: 14901 loss: 5.0510 loss_prob: 2.8856 loss_thr: 1.1654 loss_db: 1.0000 2022/11/02 12:24:04 - mmengine - INFO - Epoch(train) [21][40/63] lr: 4.0564e-04 eta: 18:23:22 time: 0.4706 data_time: 0.0117 memory: 14901 loss: 5.0180 loss_prob: 2.8622 loss_thr: 1.1558 loss_db: 1.0000 2022/11/02 12:24:06 - mmengine - INFO - Epoch(train) [21][45/63] lr: 4.0564e-04 eta: 18:23:22 time: 0.4689 data_time: 0.0080 memory: 14901 loss: 5.0205 loss_prob: 2.8659 loss_thr: 1.1546 loss_db: 1.0000 2022/11/02 12:24:09 - mmengine - INFO - Epoch(train) [21][50/63] lr: 4.0564e-04 eta: 18:19:16 time: 0.4722 data_time: 0.0150 memory: 14901 loss: 5.0459 loss_prob: 2.8889 loss_thr: 1.1570 loss_db: 1.0000 2022/11/02 12:24:11 - mmengine - INFO - Epoch(train) [21][55/63] lr: 4.0564e-04 eta: 18:19:16 time: 0.4855 data_time: 0.0179 memory: 14901 loss: 5.0558 loss_prob: 2.8962 loss_thr: 1.1596 loss_db: 1.0000 2022/11/02 12:24:13 - mmengine - INFO - Epoch(train) [21][60/63] lr: 4.0564e-04 eta: 18:15:16 time: 0.4781 data_time: 0.0175 memory: 14901 loss: 5.0514 loss_prob: 2.8950 loss_thr: 1.1564 loss_db: 1.0000 2022/11/02 12:24:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:24:19 - mmengine - INFO - Epoch(train) [22][5/63] lr: 4.2582e-04 eta: 18:15:16 time: 0.6763 data_time: 0.2196 memory: 14901 loss: 5.0613 loss_prob: 2.8981 loss_thr: 1.1632 loss_db: 1.0000 2022/11/02 12:24:22 - mmengine - INFO - Epoch(train) [22][10/63] lr: 4.2582e-04 eta: 18:11:01 time: 0.7136 data_time: 0.2246 memory: 14901 loss: 5.0651 loss_prob: 2.9077 loss_thr: 1.1575 loss_db: 1.0000 2022/11/02 12:24:24 - mmengine - INFO - Epoch(train) [22][15/63] lr: 4.2582e-04 eta: 18:11:01 time: 0.4760 data_time: 0.0091 memory: 14901 loss: 5.0858 loss_prob: 2.9216 loss_thr: 1.1643 loss_db: 1.0000 2022/11/02 12:24:26 - mmengine - INFO - Epoch(train) [22][20/63] lr: 4.2582e-04 eta: 18:06:53 time: 0.4489 data_time: 0.0051 memory: 14901 loss: 5.0851 loss_prob: 2.9221 loss_thr: 1.1631 loss_db: 1.0000 2022/11/02 12:24:29 - mmengine - INFO - Epoch(train) [22][25/63] lr: 4.2582e-04 eta: 18:06:53 time: 0.4552 data_time: 0.0178 memory: 14901 loss: 5.0848 loss_prob: 2.9289 loss_thr: 1.1559 loss_db: 1.0000 2022/11/02 12:24:31 - mmengine - INFO - Epoch(train) [22][30/63] lr: 4.2582e-04 eta: 18:03:13 time: 0.4918 data_time: 0.0345 memory: 14901 loss: 5.0981 loss_prob: 2.9382 loss_thr: 1.1600 loss_db: 1.0000 2022/11/02 12:24:34 - mmengine - INFO - Epoch(train) [22][35/63] lr: 4.2582e-04 eta: 18:03:13 time: 0.5008 data_time: 0.0219 memory: 14901 loss: 5.0799 loss_prob: 2.9186 loss_thr: 1.1614 loss_db: 1.0000 2022/11/02 12:24:36 - mmengine - INFO - Epoch(train) [22][40/63] lr: 4.2582e-04 eta: 17:59:49 time: 0.5172 data_time: 0.0164 memory: 14901 loss: 5.0483 loss_prob: 2.8900 loss_thr: 1.1584 loss_db: 1.0000 2022/11/02 12:24:39 - mmengine - INFO - Epoch(train) [22][45/63] lr: 4.2582e-04 eta: 17:59:49 time: 0.5247 data_time: 0.0164 memory: 14901 loss: 5.0353 loss_prob: 2.8776 loss_thr: 1.1577 loss_db: 1.0000 2022/11/02 12:24:42 - mmengine - INFO - Epoch(train) [22][50/63] lr: 4.2582e-04 eta: 17:56:45 time: 0.5486 data_time: 0.0049 memory: 14901 loss: 5.0283 loss_prob: 2.8694 loss_thr: 1.1590 loss_db: 1.0000 2022/11/02 12:24:44 - mmengine - INFO - Epoch(train) [22][55/63] lr: 4.2582e-04 eta: 17:56:45 time: 0.5353 data_time: 0.0139 memory: 14901 loss: 5.0289 loss_prob: 2.8674 loss_thr: 1.1615 loss_db: 1.0000 2022/11/02 12:24:46 - mmengine - INFO - Epoch(train) [22][60/63] lr: 4.2582e-04 eta: 17:53:01 time: 0.4703 data_time: 0.0139 memory: 14901 loss: 5.0490 loss_prob: 2.8836 loss_thr: 1.1654 loss_db: 1.0000 2022/11/02 12:24:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:24:52 - mmengine - INFO - Epoch(train) [23][5/63] lr: 4.4600e-04 eta: 17:53:01 time: 0.6627 data_time: 0.2080 memory: 14901 loss: 5.0579 loss_prob: 2.8951 loss_thr: 1.1629 loss_db: 1.0000 2022/11/02 12:24:55 - mmengine - INFO - Epoch(train) [23][10/63] lr: 4.4600e-04 eta: 17:48:57 time: 0.6891 data_time: 0.2057 memory: 14901 loss: 5.0345 loss_prob: 2.8766 loss_thr: 1.1580 loss_db: 1.0000 2022/11/02 12:24:57 - mmengine - INFO - Epoch(train) [23][15/63] lr: 4.4600e-04 eta: 17:48:57 time: 0.5024 data_time: 0.0051 memory: 14901 loss: 5.0207 loss_prob: 2.8628 loss_thr: 1.1579 loss_db: 1.0000 2022/11/02 12:24:59 - mmengine - INFO - Epoch(train) [23][20/63] lr: 4.4600e-04 eta: 17:45:31 time: 0.4908 data_time: 0.0048 memory: 14901 loss: 5.0211 loss_prob: 2.8619 loss_thr: 1.1593 loss_db: 1.0000 2022/11/02 12:25:02 - mmengine - INFO - Epoch(train) [23][25/63] lr: 4.4600e-04 eta: 17:45:31 time: 0.5044 data_time: 0.0342 memory: 14901 loss: 5.0081 loss_prob: 2.8500 loss_thr: 1.1581 loss_db: 1.0000 2022/11/02 12:25:05 - mmengine - INFO - Epoch(train) [23][30/63] lr: 4.4600e-04 eta: 17:42:18 time: 0.5090 data_time: 0.0349 memory: 14901 loss: 4.9964 loss_prob: 2.8400 loss_thr: 1.1564 loss_db: 1.0000 2022/11/02 12:25:07 - mmengine - INFO - Epoch(train) [23][35/63] lr: 4.4600e-04 eta: 17:42:18 time: 0.4881 data_time: 0.0065 memory: 14901 loss: 5.0037 loss_prob: 2.8481 loss_thr: 1.1556 loss_db: 1.0000 2022/11/02 12:25:10 - mmengine - INFO - Epoch(train) [23][40/63] lr: 4.4600e-04 eta: 17:39:25 time: 0.5442 data_time: 0.0058 memory: 14901 loss: 5.0221 loss_prob: 2.8693 loss_thr: 1.1528 loss_db: 1.0000 2022/11/02 12:25:14 - mmengine - INFO - Epoch(train) [23][45/63] lr: 4.4600e-04 eta: 17:39:25 time: 0.6477 data_time: 0.0050 memory: 14901 loss: 5.0409 loss_prob: 2.8898 loss_thr: 1.1512 loss_db: 1.0000 2022/11/02 12:25:16 - mmengine - INFO - Epoch(train) [23][50/63] lr: 4.4600e-04 eta: 17:37:06 time: 0.6028 data_time: 0.0241 memory: 14901 loss: 5.0493 loss_prob: 2.8919 loss_thr: 1.1575 loss_db: 1.0000 2022/11/02 12:25:19 - mmengine - INFO - Epoch(train) [23][55/63] lr: 4.4600e-04 eta: 17:37:06 time: 0.5497 data_time: 0.0244 memory: 14901 loss: 5.0467 loss_prob: 2.8787 loss_thr: 1.1680 loss_db: 1.0000 2022/11/02 12:25:21 - mmengine - INFO - Epoch(train) [23][60/63] lr: 4.4600e-04 eta: 17:34:13 time: 0.5359 data_time: 0.0068 memory: 14901 loss: 5.0300 loss_prob: 2.8685 loss_thr: 1.1615 loss_db: 1.0000 2022/11/02 12:25:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:25:28 - mmengine - INFO - Epoch(train) [24][5/63] lr: 4.6618e-04 eta: 17:34:13 time: 0.8009 data_time: 0.2872 memory: 14901 loss: 5.0411 loss_prob: 2.8808 loss_thr: 1.1602 loss_db: 1.0000 2022/11/02 12:25:31 - mmengine - INFO - Epoch(train) [24][10/63] lr: 4.6618e-04 eta: 17:32:03 time: 0.8735 data_time: 0.2818 memory: 14901 loss: 5.0817 loss_prob: 2.9031 loss_thr: 1.1786 loss_db: 1.0000 2022/11/02 12:25:34 - mmengine - INFO - Epoch(train) [24][15/63] lr: 4.6618e-04 eta: 17:32:03 time: 0.5492 data_time: 0.0060 memory: 14901 loss: 5.1354 loss_prob: 2.9520 loss_thr: 1.1834 loss_db: 1.0000 2022/11/02 12:25:37 - mmengine - INFO - Epoch(train) [24][20/63] lr: 4.6618e-04 eta: 17:29:40 time: 0.5860 data_time: 0.0060 memory: 14901 loss: 5.1725 loss_prob: 3.0126 loss_thr: 1.1600 loss_db: 1.0000 2022/11/02 12:25:40 - mmengine - INFO - Epoch(train) [24][25/63] lr: 4.6618e-04 eta: 17:29:40 time: 0.6178 data_time: 0.0340 memory: 14901 loss: 5.1929 loss_prob: 3.0310 loss_thr: 1.1619 loss_db: 1.0000 2022/11/02 12:25:43 - mmengine - INFO - Epoch(train) [24][30/63] lr: 4.6618e-04 eta: 17:27:13 time: 0.5735 data_time: 0.0340 memory: 14901 loss: 5.1742 loss_prob: 2.9987 loss_thr: 1.1755 loss_db: 1.0000 2022/11/02 12:25:46 - mmengine - INFO - Epoch(train) [24][35/63] lr: 4.6618e-04 eta: 17:27:13 time: 0.6337 data_time: 0.0047 memory: 14901 loss: 5.1398 loss_prob: 2.9721 loss_thr: 1.1677 loss_db: 1.0000 2022/11/02 12:25:50 - mmengine - INFO - Epoch(train) [24][40/63] lr: 4.6618e-04 eta: 17:25:47 time: 0.6910 data_time: 0.0053 memory: 14901 loss: 5.1272 loss_prob: 2.9573 loss_thr: 1.1699 loss_db: 1.0000 2022/11/02 12:25:52 - mmengine - INFO - Epoch(train) [24][45/63] lr: 4.6618e-04 eta: 17:25:47 time: 0.5990 data_time: 0.0052 memory: 14901 loss: 5.1095 loss_prob: 2.9382 loss_thr: 1.1713 loss_db: 1.0000 2022/11/02 12:25:56 - mmengine - INFO - Epoch(train) [24][50/63] lr: 4.6618e-04 eta: 17:23:31 time: 0.5892 data_time: 0.0306 memory: 14901 loss: 5.0675 loss_prob: 2.9112 loss_thr: 1.1563 loss_db: 1.0000 2022/11/02 12:25:59 - mmengine - INFO - Epoch(train) [24][55/63] lr: 4.6618e-04 eta: 17:23:31 time: 0.6255 data_time: 0.0310 memory: 14901 loss: 5.0552 loss_prob: 2.9004 loss_thr: 1.1549 loss_db: 1.0000 2022/11/02 12:26:01 - mmengine - INFO - Epoch(train) [24][60/63] lr: 4.6618e-04 eta: 17:21:00 time: 0.5538 data_time: 0.0048 memory: 14901 loss: 5.0500 loss_prob: 2.8947 loss_thr: 1.1553 loss_db: 1.0000 2022/11/02 12:26:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:26:09 - mmengine - INFO - Epoch(train) [25][5/63] lr: 4.8636e-04 eta: 17:21:00 time: 0.8505 data_time: 0.2053 memory: 14901 loss: 5.0338 loss_prob: 2.8763 loss_thr: 1.1575 loss_db: 1.0000 2022/11/02 12:26:12 - mmengine - INFO - Epoch(train) [25][10/63] lr: 4.8636e-04 eta: 17:18:52 time: 0.8562 data_time: 0.2044 memory: 14901 loss: 5.0425 loss_prob: 2.8804 loss_thr: 1.1621 loss_db: 1.0000 2022/11/02 12:26:14 - mmengine - INFO - Epoch(train) [25][15/63] lr: 4.8636e-04 eta: 17:18:52 time: 0.5447 data_time: 0.0107 memory: 14901 loss: 5.0349 loss_prob: 2.8707 loss_thr: 1.1642 loss_db: 1.0000 2022/11/02 12:26:17 - mmengine - INFO - Epoch(train) [25][20/63] lr: 4.8636e-04 eta: 17:16:03 time: 0.5089 data_time: 0.0065 memory: 14901 loss: 5.0272 loss_prob: 2.8695 loss_thr: 1.1577 loss_db: 1.0000 2022/11/02 12:26:19 - mmengine - INFO - Epoch(train) [25][25/63] lr: 4.8636e-04 eta: 17:16:03 time: 0.4748 data_time: 0.0129 memory: 14901 loss: 5.0367 loss_prob: 2.8811 loss_thr: 1.1556 loss_db: 1.0000 2022/11/02 12:26:22 - mmengine - INFO - Epoch(train) [25][30/63] lr: 4.8636e-04 eta: 17:13:10 time: 0.4973 data_time: 0.0310 memory: 14901 loss: 5.0372 loss_prob: 2.8796 loss_thr: 1.1577 loss_db: 1.0000 2022/11/02 12:26:24 - mmengine - INFO - Epoch(train) [25][35/63] lr: 4.8636e-04 eta: 17:13:10 time: 0.4971 data_time: 0.0267 memory: 14901 loss: 5.0302 loss_prob: 2.8737 loss_thr: 1.1565 loss_db: 1.0000 2022/11/02 12:26:27 - mmengine - INFO - Epoch(train) [25][40/63] lr: 4.8636e-04 eta: 17:10:16 time: 0.4897 data_time: 0.0088 memory: 14901 loss: 5.0196 loss_prob: 2.8645 loss_thr: 1.1551 loss_db: 1.0000 2022/11/02 12:26:29 - mmengine - INFO - Epoch(train) [25][45/63] lr: 4.8636e-04 eta: 17:10:16 time: 0.4874 data_time: 0.0048 memory: 14901 loss: 5.0138 loss_prob: 2.8558 loss_thr: 1.1580 loss_db: 1.0000 2022/11/02 12:26:31 - mmengine - INFO - Epoch(train) [25][50/63] lr: 4.8636e-04 eta: 17:07:14 time: 0.4691 data_time: 0.0101 memory: 14901 loss: 5.0059 loss_prob: 2.8492 loss_thr: 1.1567 loss_db: 1.0000 2022/11/02 12:26:34 - mmengine - INFO - Epoch(train) [25][55/63] lr: 4.8636e-04 eta: 17:07:14 time: 0.4876 data_time: 0.0246 memory: 14901 loss: 4.9978 loss_prob: 2.8430 loss_thr: 1.1548 loss_db: 1.0000 2022/11/02 12:26:36 - mmengine - INFO - Epoch(train) [25][60/63] lr: 4.8636e-04 eta: 17:04:25 time: 0.4912 data_time: 0.0198 memory: 14901 loss: 4.9978 loss_prob: 2.8418 loss_thr: 1.1561 loss_db: 1.0000 2022/11/02 12:26:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:26:42 - mmengine - INFO - Epoch(train) [26][5/63] lr: 5.0655e-04 eta: 17:04:25 time: 0.6651 data_time: 0.2295 memory: 14901 loss: 5.0092 loss_prob: 2.8555 loss_thr: 1.1537 loss_db: 1.0000 2022/11/02 12:26:45 - mmengine - INFO - Epoch(train) [26][10/63] lr: 5.0655e-04 eta: 17:01:31 time: 0.7284 data_time: 0.2293 memory: 14901 loss: 5.0173 loss_prob: 2.8622 loss_thr: 1.1551 loss_db: 1.0000 2022/11/02 12:26:47 - mmengine - INFO - Epoch(train) [26][15/63] lr: 5.0655e-04 eta: 17:01:31 time: 0.5258 data_time: 0.0049 memory: 14901 loss: 5.0227 loss_prob: 2.8660 loss_thr: 1.1568 loss_db: 1.0000 2022/11/02 12:26:50 - mmengine - INFO - Epoch(train) [26][20/63] lr: 5.0655e-04 eta: 16:59:10 time: 0.5420 data_time: 0.0049 memory: 14901 loss: 5.0265 loss_prob: 2.8674 loss_thr: 1.1591 loss_db: 1.0000 2022/11/02 12:26:53 - mmengine - INFO - Epoch(train) [26][25/63] lr: 5.0655e-04 eta: 16:59:10 time: 0.5391 data_time: 0.0242 memory: 14901 loss: 5.0191 loss_prob: 2.8605 loss_thr: 1.1586 loss_db: 1.0000 2022/11/02 12:26:55 - mmengine - INFO - Epoch(train) [26][30/63] lr: 5.0655e-04 eta: 16:56:30 time: 0.4981 data_time: 0.0334 memory: 14901 loss: 5.0088 loss_prob: 2.8549 loss_thr: 1.1540 loss_db: 1.0000 2022/11/02 12:26:57 - mmengine - INFO - Epoch(train) [26][35/63] lr: 5.0655e-04 eta: 16:56:30 time: 0.4819 data_time: 0.0140 memory: 14901 loss: 5.0081 loss_prob: 2.8505 loss_thr: 1.1576 loss_db: 1.0000 2022/11/02 12:27:00 - mmengine - INFO - Epoch(train) [26][40/63] lr: 5.0655e-04 eta: 16:53:46 time: 0.4833 data_time: 0.0059 memory: 14901 loss: 5.0061 loss_prob: 2.8485 loss_thr: 1.1577 loss_db: 1.0000 2022/11/02 12:27:02 - mmengine - INFO - Epoch(train) [26][45/63] lr: 5.0655e-04 eta: 16:53:46 time: 0.4824 data_time: 0.0075 memory: 14901 loss: 5.0050 loss_prob: 2.8520 loss_thr: 1.1530 loss_db: 1.0000 2022/11/02 12:27:05 - mmengine - INFO - Epoch(train) [26][50/63] lr: 5.0655e-04 eta: 16:51:28 time: 0.5387 data_time: 0.0269 memory: 14901 loss: 5.0210 loss_prob: 2.8665 loss_thr: 1.1545 loss_db: 1.0000 2022/11/02 12:27:08 - mmengine - INFO - Epoch(train) [26][55/63] lr: 5.0655e-04 eta: 16:51:28 time: 0.5646 data_time: 0.0286 memory: 14901 loss: 5.0398 loss_prob: 2.8841 loss_thr: 1.1557 loss_db: 1.0000 2022/11/02 12:27:11 - mmengine - INFO - Epoch(train) [26][60/63] lr: 5.0655e-04 eta: 16:49:13 time: 0.5402 data_time: 0.0081 memory: 14901 loss: 5.0366 loss_prob: 2.8836 loss_thr: 1.1531 loss_db: 1.0000 2022/11/02 12:27:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:27:17 - mmengine - INFO - Epoch(train) [27][5/63] lr: 5.2673e-04 eta: 16:49:13 time: 0.7102 data_time: 0.2076 memory: 14901 loss: 5.0212 loss_prob: 2.8644 loss_thr: 1.1569 loss_db: 1.0000 2022/11/02 12:27:19 - mmengine - INFO - Epoch(train) [27][10/63] lr: 5.2673e-04 eta: 16:46:30 time: 0.7243 data_time: 0.2176 memory: 14901 loss: 5.0100 loss_prob: 2.8553 loss_thr: 1.1547 loss_db: 1.0000 2022/11/02 12:27:22 - mmengine - INFO - Epoch(train) [27][15/63] lr: 5.2673e-04 eta: 16:46:30 time: 0.4960 data_time: 0.0160 memory: 14901 loss: 5.0044 loss_prob: 2.8492 loss_thr: 1.1553 loss_db: 1.0000 2022/11/02 12:27:24 - mmengine - INFO - Epoch(train) [27][20/63] lr: 5.2673e-04 eta: 16:43:48 time: 0.4706 data_time: 0.0060 memory: 14901 loss: 5.0026 loss_prob: 2.8466 loss_thr: 1.1560 loss_db: 1.0000 2022/11/02 12:27:27 - mmengine - INFO - Epoch(train) [27][25/63] lr: 5.2673e-04 eta: 16:43:48 time: 0.5092 data_time: 0.0225 memory: 14901 loss: 4.9986 loss_prob: 2.8421 loss_thr: 1.1565 loss_db: 1.0000 2022/11/02 12:27:29 - mmengine - INFO - Epoch(train) [27][30/63] lr: 5.2673e-04 eta: 16:41:37 time: 0.5379 data_time: 0.0468 memory: 14901 loss: 4.9987 loss_prob: 2.8403 loss_thr: 1.1584 loss_db: 1.0000 2022/11/02 12:27:32 - mmengine - INFO - Epoch(train) [27][35/63] lr: 5.2673e-04 eta: 16:41:37 time: 0.4950 data_time: 0.0291 memory: 14901 loss: 5.0114 loss_prob: 2.8513 loss_thr: 1.1602 loss_db: 1.0000 2022/11/02 12:27:34 - mmengine - INFO - Epoch(train) [27][40/63] lr: 5.2673e-04 eta: 16:39:06 time: 0.4884 data_time: 0.0056 memory: 14901 loss: 5.0218 loss_prob: 2.8676 loss_thr: 1.1543 loss_db: 1.0000 2022/11/02 12:27:37 - mmengine - INFO - Epoch(train) [27][45/63] lr: 5.2673e-04 eta: 16:39:06 time: 0.4934 data_time: 0.0055 memory: 14901 loss: 5.0233 loss_prob: 2.8706 loss_thr: 1.1528 loss_db: 0.9999 2022/11/02 12:27:39 - mmengine - INFO - Epoch(train) [27][50/63] lr: 5.2673e-04 eta: 16:36:44 time: 0.5048 data_time: 0.0190 memory: 14901 loss: 5.0169 loss_prob: 2.8639 loss_thr: 1.1530 loss_db: 0.9999 2022/11/02 12:27:42 - mmengine - INFO - Epoch(train) [27][55/63] lr: 5.2673e-04 eta: 16:36:44 time: 0.5275 data_time: 0.0240 memory: 14901 loss: 5.0129 loss_prob: 2.8584 loss_thr: 1.1545 loss_db: 1.0000 2022/11/02 12:27:44 - mmengine - INFO - Epoch(train) [27][60/63] lr: 5.2673e-04 eta: 16:34:15 time: 0.4872 data_time: 0.0093 memory: 14901 loss: 5.0107 loss_prob: 2.8544 loss_thr: 1.1563 loss_db: 1.0000 2022/11/02 12:27:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:27:51 - mmengine - INFO - Epoch(train) [28][5/63] lr: 5.4691e-04 eta: 16:34:15 time: 0.7557 data_time: 0.2151 memory: 14901 loss: 5.0074 loss_prob: 2.8504 loss_thr: 1.1570 loss_db: 1.0000 2022/11/02 12:27:53 - mmengine - INFO - Epoch(train) [28][10/63] lr: 5.4691e-04 eta: 16:32:09 time: 0.7819 data_time: 0.2156 memory: 14901 loss: 5.0007 loss_prob: 2.8462 loss_thr: 1.1545 loss_db: 1.0000 2022/11/02 12:27:56 - mmengine - INFO - Epoch(train) [28][15/63] lr: 5.4691e-04 eta: 16:32:09 time: 0.4963 data_time: 0.0069 memory: 14901 loss: 4.9920 loss_prob: 2.8446 loss_thr: 1.1475 loss_db: 1.0000 2022/11/02 12:27:58 - mmengine - INFO - Epoch(train) [28][20/63] lr: 5.4691e-04 eta: 16:29:41 time: 0.4782 data_time: 0.0087 memory: 14901 loss: 4.9966 loss_prob: 2.8457 loss_thr: 1.1510 loss_db: 1.0000 2022/11/02 12:28:01 - mmengine - INFO - Epoch(train) [28][25/63] lr: 5.4691e-04 eta: 16:29:41 time: 0.4867 data_time: 0.0125 memory: 14901 loss: 5.0122 loss_prob: 2.8529 loss_thr: 1.1593 loss_db: 0.9999 2022/11/02 12:28:03 - mmengine - INFO - Epoch(train) [28][30/63] lr: 5.4691e-04 eta: 16:27:29 time: 0.5141 data_time: 0.0275 memory: 14901 loss: 5.0204 loss_prob: 2.8611 loss_thr: 1.1594 loss_db: 0.9999 2022/11/02 12:28:06 - mmengine - INFO - Epoch(train) [28][35/63] lr: 5.4691e-04 eta: 16:27:29 time: 0.5198 data_time: 0.0237 memory: 14901 loss: 5.0179 loss_prob: 2.8589 loss_thr: 1.1590 loss_db: 0.9999 2022/11/02 12:28:08 - mmengine - INFO - Epoch(train) [28][40/63] lr: 5.4691e-04 eta: 16:25:13 time: 0.5007 data_time: 0.0112 memory: 14901 loss: 5.0121 loss_prob: 2.8541 loss_thr: 1.1580 loss_db: 0.9999 2022/11/02 12:28:10 - mmengine - INFO - Epoch(train) [28][45/63] lr: 5.4691e-04 eta: 16:25:13 time: 0.4682 data_time: 0.0135 memory: 14901 loss: 5.0050 loss_prob: 2.8488 loss_thr: 1.1562 loss_db: 0.9999 2022/11/02 12:28:13 - mmengine - INFO - Epoch(train) [28][50/63] lr: 5.4691e-04 eta: 16:22:57 time: 0.4961 data_time: 0.0171 memory: 14901 loss: 4.9999 loss_prob: 2.8434 loss_thr: 1.1566 loss_db: 0.9999 2022/11/02 12:28:16 - mmengine - INFO - Epoch(train) [28][55/63] lr: 5.4691e-04 eta: 16:22:57 time: 0.5292 data_time: 0.0217 memory: 14901 loss: 4.9932 loss_prob: 2.8404 loss_thr: 1.1529 loss_db: 0.9999 2022/11/02 12:28:18 - mmengine - INFO - Epoch(train) [28][60/63] lr: 5.4691e-04 eta: 16:20:44 time: 0.5010 data_time: 0.0117 memory: 14901 loss: 4.9896 loss_prob: 2.8368 loss_thr: 1.1529 loss_db: 0.9999 2022/11/02 12:28:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:28:24 - mmengine - INFO - Epoch(train) [29][5/63] lr: 5.6709e-04 eta: 16:20:44 time: 0.7047 data_time: 0.2235 memory: 14901 loss: 4.9827 loss_prob: 2.8302 loss_thr: 1.1525 loss_db: 0.9999 2022/11/02 12:28:27 - mmengine - INFO - Epoch(train) [29][10/63] lr: 5.6709e-04 eta: 16:18:33 time: 0.7460 data_time: 0.2234 memory: 14901 loss: 4.9769 loss_prob: 2.8267 loss_thr: 1.1502 loss_db: 0.9999 2022/11/02 12:28:29 - mmengine - INFO - Epoch(train) [29][15/63] lr: 5.6709e-04 eta: 16:18:33 time: 0.4962 data_time: 0.0074 memory: 14901 loss: 4.9918 loss_prob: 2.8362 loss_thr: 1.1556 loss_db: 0.9999 2022/11/02 12:28:31 - mmengine - INFO - Epoch(train) [29][20/63] lr: 5.6709e-04 eta: 16:16:14 time: 0.4786 data_time: 0.0092 memory: 14901 loss: 5.0080 loss_prob: 2.8529 loss_thr: 1.1551 loss_db: 0.9999 2022/11/02 12:28:34 - mmengine - INFO - Epoch(train) [29][25/63] lr: 5.6709e-04 eta: 16:16:14 time: 0.4862 data_time: 0.0204 memory: 14901 loss: 5.0079 loss_prob: 2.8592 loss_thr: 1.1487 loss_db: 0.9999 2022/11/02 12:28:37 - mmengine - INFO - Epoch(train) [29][30/63] lr: 5.6709e-04 eta: 16:14:12 time: 0.5162 data_time: 0.0333 memory: 14901 loss: 5.0079 loss_prob: 2.8568 loss_thr: 1.1511 loss_db: 0.9999 2022/11/02 12:28:39 - mmengine - INFO - Epoch(train) [29][35/63] lr: 5.6709e-04 eta: 16:14:12 time: 0.5074 data_time: 0.0201 memory: 14901 loss: 5.0040 loss_prob: 2.8521 loss_thr: 1.1519 loss_db: 1.0000 2022/11/02 12:28:41 - mmengine - INFO - Epoch(train) [29][40/63] lr: 5.6709e-04 eta: 16:11:57 time: 0.4798 data_time: 0.0057 memory: 14901 loss: 4.9972 loss_prob: 2.8439 loss_thr: 1.1534 loss_db: 0.9999 2022/11/02 12:28:44 - mmengine - INFO - Epoch(train) [29][45/63] lr: 5.6709e-04 eta: 16:11:57 time: 0.4830 data_time: 0.0082 memory: 14901 loss: 4.9964 loss_prob: 2.8383 loss_thr: 1.1581 loss_db: 1.0000 2022/11/02 12:28:47 - mmengine - INFO - Epoch(train) [29][50/63] lr: 5.6709e-04 eta: 16:10:01 time: 0.5251 data_time: 0.0242 memory: 14901 loss: 4.9963 loss_prob: 2.8374 loss_thr: 1.1589 loss_db: 1.0000 2022/11/02 12:28:49 - mmengine - INFO - Epoch(train) [29][55/63] lr: 5.6709e-04 eta: 16:10:01 time: 0.5306 data_time: 0.0218 memory: 14901 loss: 4.9894 loss_prob: 2.8341 loss_thr: 1.1554 loss_db: 1.0000 2022/11/02 12:28:52 - mmengine - INFO - Epoch(train) [29][60/63] lr: 5.6709e-04 eta: 16:08:05 time: 0.5214 data_time: 0.0061 memory: 14901 loss: 4.9928 loss_prob: 2.8366 loss_thr: 1.1562 loss_db: 0.9999 2022/11/02 12:28:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:28:59 - mmengine - INFO - Epoch(train) [30][5/63] lr: 5.8727e-04 eta: 16:08:05 time: 0.8180 data_time: 0.2429 memory: 14901 loss: 4.9877 loss_prob: 2.8422 loss_thr: 1.1457 loss_db: 0.9998 2022/11/02 12:29:02 - mmengine - INFO - Epoch(train) [30][10/63] lr: 5.8727e-04 eta: 16:06:37 time: 0.8295 data_time: 0.2427 memory: 14901 loss: 4.9956 loss_prob: 2.8460 loss_thr: 1.1498 loss_db: 0.9998 2022/11/02 12:29:05 - mmengine - INFO - Epoch(train) [30][15/63] lr: 5.8727e-04 eta: 16:06:37 time: 0.5873 data_time: 0.0052 memory: 14901 loss: 4.9932 loss_prob: 2.8411 loss_thr: 1.1522 loss_db: 0.9999 2022/11/02 12:29:08 - mmengine - INFO - Epoch(train) [30][20/63] lr: 5.8727e-04 eta: 16:04:59 time: 0.5624 data_time: 0.0053 memory: 14901 loss: 5.0121 loss_prob: 2.8588 loss_thr: 1.1534 loss_db: 1.0000 2022/11/02 12:29:11 - mmengine - INFO - Epoch(train) [30][25/63] lr: 5.8727e-04 eta: 16:04:59 time: 0.5673 data_time: 0.0082 memory: 14901 loss: 5.0361 loss_prob: 2.8734 loss_thr: 1.1627 loss_db: 1.0000 2022/11/02 12:29:13 - mmengine - INFO - Epoch(train) [30][30/63] lr: 5.8727e-04 eta: 16:03:18 time: 0.5484 data_time: 0.0355 memory: 14901 loss: 5.0758 loss_prob: 2.9123 loss_thr: 1.1636 loss_db: 1.0000 2022/11/02 12:29:16 - mmengine - INFO - Epoch(train) [30][35/63] lr: 5.8727e-04 eta: 16:03:18 time: 0.5285 data_time: 0.0330 memory: 14901 loss: 5.1634 loss_prob: 2.9887 loss_thr: 1.1747 loss_db: 0.9999 2022/11/02 12:29:19 - mmengine - INFO - Epoch(train) [30][40/63] lr: 5.8727e-04 eta: 16:01:36 time: 0.5460 data_time: 0.0053 memory: 14901 loss: 5.2047 loss_prob: 3.0130 loss_thr: 1.1917 loss_db: 1.0000 2022/11/02 12:29:21 - mmengine - INFO - Epoch(train) [30][45/63] lr: 5.8727e-04 eta: 16:01:36 time: 0.5490 data_time: 0.0046 memory: 14901 loss: 5.1927 loss_prob: 3.0183 loss_thr: 1.1744 loss_db: 1.0000 2022/11/02 12:29:24 - mmengine - INFO - Epoch(train) [30][50/63] lr: 5.8727e-04 eta: 16:00:00 time: 0.5590 data_time: 0.0247 memory: 14901 loss: 5.1627 loss_prob: 3.0063 loss_thr: 1.1565 loss_db: 1.0000 2022/11/02 12:29:27 - mmengine - INFO - Epoch(train) [30][55/63] lr: 5.8727e-04 eta: 16:00:00 time: 0.6052 data_time: 0.0249 memory: 14901 loss: 5.1559 loss_prob: 2.9978 loss_thr: 1.1581 loss_db: 1.0000 2022/11/02 12:29:30 - mmengine - INFO - Epoch(train) [30][60/63] lr: 5.8727e-04 eta: 15:58:46 time: 0.6112 data_time: 0.0052 memory: 14901 loss: 5.1660 loss_prob: 3.0046 loss_thr: 1.1615 loss_db: 1.0000 2022/11/02 12:29:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:29:38 - mmengine - INFO - Epoch(train) [31][5/63] lr: 6.0745e-04 eta: 15:58:46 time: 0.8639 data_time: 0.2165 memory: 14901 loss: 5.1335 loss_prob: 2.9671 loss_thr: 1.1664 loss_db: 1.0000 2022/11/02 12:29:40 - mmengine - INFO - Epoch(train) [31][10/63] lr: 6.0745e-04 eta: 15:57:11 time: 0.7965 data_time: 0.2250 memory: 14901 loss: 5.1049 loss_prob: 2.9442 loss_thr: 1.1607 loss_db: 1.0000 2022/11/02 12:29:43 - mmengine - INFO - Epoch(train) [31][15/63] lr: 6.0745e-04 eta: 15:57:11 time: 0.5678 data_time: 0.0149 memory: 14901 loss: 5.0725 loss_prob: 2.9124 loss_thr: 1.1601 loss_db: 1.0000 2022/11/02 12:29:46 - mmengine - INFO - Epoch(train) [31][20/63] lr: 6.0745e-04 eta: 15:56:03 time: 0.6226 data_time: 0.0106 memory: 14901 loss: 5.0783 loss_prob: 2.9147 loss_thr: 1.1637 loss_db: 1.0000 2022/11/02 12:29:49 - mmengine - INFO - Epoch(train) [31][25/63] lr: 6.0745e-04 eta: 15:56:03 time: 0.5576 data_time: 0.0166 memory: 14901 loss: 5.0758 loss_prob: 2.9157 loss_thr: 1.1602 loss_db: 1.0000 2022/11/02 12:29:51 - mmengine - INFO - Epoch(train) [31][30/63] lr: 6.0745e-04 eta: 15:54:08 time: 0.4983 data_time: 0.0236 memory: 14901 loss: 5.0672 loss_prob: 2.9106 loss_thr: 1.1566 loss_db: 1.0000 2022/11/02 12:29:54 - mmengine - INFO - Epoch(train) [31][35/63] lr: 6.0745e-04 eta: 15:54:08 time: 0.4848 data_time: 0.0240 memory: 14901 loss: 5.0748 loss_prob: 2.9131 loss_thr: 1.1617 loss_db: 1.0000 2022/11/02 12:29:56 - mmengine - INFO - Epoch(train) [31][40/63] lr: 6.0745e-04 eta: 15:52:08 time: 0.4850 data_time: 0.0143 memory: 14901 loss: 5.0692 loss_prob: 2.9042 loss_thr: 1.1651 loss_db: 0.9999 2022/11/02 12:29:58 - mmengine - INFO - Epoch(train) [31][45/63] lr: 6.0745e-04 eta: 15:52:08 time: 0.4722 data_time: 0.0075 memory: 14901 loss: 5.0759 loss_prob: 2.9182 loss_thr: 1.1578 loss_db: 1.0000 2022/11/02 12:30:01 - mmengine - INFO - Epoch(train) [31][50/63] lr: 6.0745e-04 eta: 15:50:08 time: 0.4787 data_time: 0.0153 memory: 14901 loss: 5.0724 loss_prob: 2.9190 loss_thr: 1.1534 loss_db: 1.0000 2022/11/02 12:30:03 - mmengine - INFO - Epoch(train) [31][55/63] lr: 6.0745e-04 eta: 15:50:08 time: 0.5006 data_time: 0.0340 memory: 14901 loss: 5.0479 loss_prob: 2.8902 loss_thr: 1.1577 loss_db: 1.0000 2022/11/02 12:30:06 - mmengine - INFO - Epoch(train) [31][60/63] lr: 6.0745e-04 eta: 15:48:16 time: 0.4974 data_time: 0.0262 memory: 14901 loss: 5.0391 loss_prob: 2.8861 loss_thr: 1.1530 loss_db: 1.0000 2022/11/02 12:30:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:30:12 - mmengine - INFO - Epoch(train) [32][5/63] lr: 6.2764e-04 eta: 15:48:16 time: 0.6823 data_time: 0.2012 memory: 14901 loss: 5.0291 loss_prob: 2.8784 loss_thr: 1.1507 loss_db: 0.9999 2022/11/02 12:30:15 - mmengine - INFO - Epoch(train) [32][10/63] lr: 6.2764e-04 eta: 15:46:28 time: 0.7438 data_time: 0.2021 memory: 14901 loss: 5.0151 loss_prob: 2.8623 loss_thr: 1.1528 loss_db: 1.0000 2022/11/02 12:30:17 - mmengine - INFO - Epoch(train) [32][15/63] lr: 6.2764e-04 eta: 15:46:28 time: 0.5416 data_time: 0.0067 memory: 14901 loss: 5.0090 loss_prob: 2.8546 loss_thr: 1.1544 loss_db: 0.9999 2022/11/02 12:30:20 - mmengine - INFO - Epoch(train) [32][20/63] lr: 6.2764e-04 eta: 15:44:57 time: 0.5479 data_time: 0.0048 memory: 14901 loss: 5.0064 loss_prob: 2.8516 loss_thr: 1.1549 loss_db: 0.9999 2022/11/02 12:30:22 - mmengine - INFO - Epoch(train) [32][25/63] lr: 6.2764e-04 eta: 15:44:57 time: 0.5297 data_time: 0.0159 memory: 14901 loss: 5.0004 loss_prob: 2.8414 loss_thr: 1.1590 loss_db: 1.0000 2022/11/02 12:30:25 - mmengine - INFO - Epoch(train) [32][30/63] lr: 6.2764e-04 eta: 15:43:16 time: 0.5184 data_time: 0.0551 memory: 14901 loss: 4.9955 loss_prob: 2.8375 loss_thr: 1.1580 loss_db: 0.9999 2022/11/02 12:30:28 - mmengine - INFO - Epoch(train) [32][35/63] lr: 6.2764e-04 eta: 15:43:16 time: 0.5172 data_time: 0.0441 memory: 14901 loss: 4.9923 loss_prob: 2.8383 loss_thr: 1.1540 loss_db: 0.9999 2022/11/02 12:30:30 - mmengine - INFO - Epoch(train) [32][40/63] lr: 6.2764e-04 eta: 15:41:21 time: 0.4791 data_time: 0.0060 memory: 14901 loss: 4.9914 loss_prob: 2.8387 loss_thr: 1.1528 loss_db: 1.0000 2022/11/02 12:30:33 - mmengine - INFO - Epoch(train) [32][45/63] lr: 6.2764e-04 eta: 15:41:21 time: 0.5073 data_time: 0.0057 memory: 14901 loss: 4.9853 loss_prob: 2.8361 loss_thr: 1.1493 loss_db: 0.9999 2022/11/02 12:30:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:30:35 - mmengine - INFO - Epoch(train) [32][50/63] lr: 6.2764e-04 eta: 15:39:38 time: 0.5078 data_time: 0.0137 memory: 14901 loss: 4.9829 loss_prob: 2.8331 loss_thr: 1.1500 loss_db: 0.9999 2022/11/02 12:30:37 - mmengine - INFO - Epoch(train) [32][55/63] lr: 6.2764e-04 eta: 15:39:38 time: 0.4834 data_time: 0.0253 memory: 14901 loss: 4.9828 loss_prob: 2.8316 loss_thr: 1.1513 loss_db: 0.9999 2022/11/02 12:30:40 - mmengine - INFO - Epoch(train) [32][60/63] lr: 6.2764e-04 eta: 15:37:45 time: 0.4779 data_time: 0.0159 memory: 14901 loss: 4.9779 loss_prob: 2.8291 loss_thr: 1.1488 loss_db: 0.9999 2022/11/02 12:30:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:30:46 - mmengine - INFO - Epoch(train) [33][5/63] lr: 6.4782e-04 eta: 15:37:45 time: 0.6718 data_time: 0.2215 memory: 14901 loss: 4.9729 loss_prob: 2.8291 loss_thr: 1.1439 loss_db: 0.9998 2022/11/02 12:30:48 - mmengine - INFO - Epoch(train) [33][10/63] lr: 6.4782e-04 eta: 15:35:54 time: 0.7156 data_time: 0.2252 memory: 14901 loss: 4.9729 loss_prob: 2.8295 loss_thr: 1.1436 loss_db: 0.9998 2022/11/02 12:30:51 - mmengine - INFO - Epoch(train) [33][15/63] lr: 6.4782e-04 eta: 15:35:54 time: 0.5140 data_time: 0.0080 memory: 14901 loss: 4.9713 loss_prob: 2.8280 loss_thr: 1.1435 loss_db: 0.9998 2022/11/02 12:30:53 - mmengine - INFO - Epoch(train) [33][20/63] lr: 6.4782e-04 eta: 15:34:22 time: 0.5281 data_time: 0.0054 memory: 14901 loss: 4.9724 loss_prob: 2.8280 loss_thr: 1.1448 loss_db: 0.9997 2022/11/02 12:30:56 - mmengine - INFO - Epoch(train) [33][25/63] lr: 6.4782e-04 eta: 15:34:22 time: 0.5483 data_time: 0.0340 memory: 14901 loss: 4.9731 loss_prob: 2.8271 loss_thr: 1.1463 loss_db: 0.9997 2022/11/02 12:30:59 - mmengine - INFO - Epoch(train) [33][30/63] lr: 6.4782e-04 eta: 15:32:49 time: 0.5268 data_time: 0.0329 memory: 14901 loss: 4.9707 loss_prob: 2.8252 loss_thr: 1.1456 loss_db: 0.9999 2022/11/02 12:31:01 - mmengine - INFO - Epoch(train) [33][35/63] lr: 6.4782e-04 eta: 15:32:49 time: 0.4788 data_time: 0.0087 memory: 14901 loss: 4.9753 loss_prob: 2.8270 loss_thr: 1.1484 loss_db: 0.9999 2022/11/02 12:31:04 - mmengine - INFO - Epoch(train) [33][40/63] lr: 6.4782e-04 eta: 15:31:08 time: 0.4988 data_time: 0.0139 memory: 14901 loss: 4.9785 loss_prob: 2.8302 loss_thr: 1.1484 loss_db: 0.9999 2022/11/02 12:31:06 - mmengine - INFO - Epoch(train) [33][45/63] lr: 6.4782e-04 eta: 15:31:08 time: 0.4917 data_time: 0.0097 memory: 14901 loss: 4.9688 loss_prob: 2.8283 loss_thr: 1.1406 loss_db: 0.9999 2022/11/02 12:31:09 - mmengine - INFO - Epoch(train) [33][50/63] lr: 6.4782e-04 eta: 15:29:23 time: 0.4852 data_time: 0.0191 memory: 14901 loss: 4.9653 loss_prob: 2.8248 loss_thr: 1.1407 loss_db: 0.9998 2022/11/02 12:31:11 - mmengine - INFO - Epoch(train) [33][55/63] lr: 6.4782e-04 eta: 15:29:23 time: 0.5245 data_time: 0.0217 memory: 14901 loss: 4.9773 loss_prob: 2.8261 loss_thr: 1.1513 loss_db: 0.9999 2022/11/02 12:31:14 - mmengine - INFO - Epoch(train) [33][60/63] lr: 6.4782e-04 eta: 15:27:50 time: 0.5174 data_time: 0.0071 memory: 14901 loss: 4.9745 loss_prob: 2.8250 loss_thr: 1.1496 loss_db: 0.9999 2022/11/02 12:31:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:31:20 - mmengine - INFO - Epoch(train) [34][5/63] lr: 6.6800e-04 eta: 15:27:50 time: 0.7096 data_time: 0.2211 memory: 14901 loss: 4.9714 loss_prob: 2.8234 loss_thr: 1.1481 loss_db: 0.9999 2022/11/02 12:31:22 - mmengine - INFO - Epoch(train) [34][10/63] lr: 6.6800e-04 eta: 15:26:19 time: 0.7529 data_time: 0.2210 memory: 14901 loss: 4.9642 loss_prob: 2.8220 loss_thr: 1.1423 loss_db: 0.9998 2022/11/02 12:31:26 - mmengine - INFO - Epoch(train) [34][15/63] lr: 6.6800e-04 eta: 15:26:19 time: 0.5787 data_time: 0.0066 memory: 14901 loss: 4.9648 loss_prob: 2.8221 loss_thr: 1.1431 loss_db: 0.9997 2022/11/02 12:31:28 - mmengine - INFO - Epoch(train) [34][20/63] lr: 6.6800e-04 eta: 15:25:09 time: 0.5791 data_time: 0.0093 memory: 14901 loss: 4.9740 loss_prob: 2.8284 loss_thr: 1.1460 loss_db: 0.9996 2022/11/02 12:31:32 - mmengine - INFO - Epoch(train) [34][25/63] lr: 6.6800e-04 eta: 15:25:09 time: 0.6442 data_time: 0.0438 memory: 14901 loss: 4.9738 loss_prob: 2.8325 loss_thr: 1.1417 loss_db: 0.9997 2022/11/02 12:31:36 - mmengine - INFO - Epoch(train) [34][30/63] lr: 6.6800e-04 eta: 15:25:07 time: 0.7720 data_time: 0.0419 memory: 14901 loss: 4.9799 loss_prob: 2.8325 loss_thr: 1.1477 loss_db: 0.9997 2022/11/02 12:31:38 - mmengine - INFO - Epoch(train) [34][35/63] lr: 6.6800e-04 eta: 15:25:07 time: 0.6345 data_time: 0.0081 memory: 14901 loss: 4.9813 loss_prob: 2.8308 loss_thr: 1.1511 loss_db: 0.9994 2022/11/02 12:31:42 - mmengine - INFO - Epoch(train) [34][40/63] lr: 6.6800e-04 eta: 15:23:56 time: 0.5701 data_time: 0.0077 memory: 14901 loss: 4.9708 loss_prob: 2.8268 loss_thr: 1.1445 loss_db: 0.9994 2022/11/02 12:31:44 - mmengine - INFO - Epoch(train) [34][45/63] lr: 6.6800e-04 eta: 15:23:56 time: 0.5907 data_time: 0.0050 memory: 14901 loss: 4.9559 loss_prob: 2.8219 loss_thr: 1.1345 loss_db: 0.9996 2022/11/02 12:31:47 - mmengine - INFO - Epoch(train) [34][50/63] lr: 6.6800e-04 eta: 15:22:40 time: 0.5565 data_time: 0.0205 memory: 14901 loss: 4.9553 loss_prob: 2.8222 loss_thr: 1.1339 loss_db: 0.9992 2022/11/02 12:31:50 - mmengine - INFO - Epoch(train) [34][55/63] lr: 6.6800e-04 eta: 15:22:40 time: 0.5379 data_time: 0.0205 memory: 14901 loss: 4.9696 loss_prob: 2.8252 loss_thr: 1.1453 loss_db: 0.9991 2022/11/02 12:31:52 - mmengine - INFO - Epoch(train) [34][60/63] lr: 6.6800e-04 eta: 15:21:08 time: 0.5096 data_time: 0.0067 memory: 14901 loss: 4.9645 loss_prob: 2.8259 loss_thr: 1.1392 loss_db: 0.9994 2022/11/02 12:31:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:31:59 - mmengine - INFO - Epoch(train) [35][5/63] lr: 6.8818e-04 eta: 15:21:08 time: 0.8032 data_time: 0.2720 memory: 14901 loss: 4.9513 loss_prob: 2.8266 loss_thr: 1.1735 loss_db: 0.9512 2022/11/02 12:32:02 - mmengine - INFO - Epoch(train) [35][10/63] lr: 6.8818e-04 eta: 15:20:16 time: 0.8540 data_time: 0.2700 memory: 14901 loss: 4.9748 loss_prob: 2.8308 loss_thr: 1.1794 loss_db: 0.9646 2022/11/02 12:32:05 - mmengine - INFO - Epoch(train) [35][15/63] lr: 6.8818e-04 eta: 15:20:16 time: 0.5815 data_time: 0.0058 memory: 14901 loss: 5.0183 loss_prob: 2.8485 loss_thr: 1.1702 loss_db: 0.9996 2022/11/02 12:32:08 - mmengine - INFO - Epoch(train) [35][20/63] lr: 6.8818e-04 eta: 15:19:01 time: 0.5510 data_time: 0.0053 memory: 14901 loss: 5.0130 loss_prob: 2.8485 loss_thr: 1.1667 loss_db: 0.9978 2022/11/02 12:32:11 - mmengine - INFO - Epoch(train) [35][25/63] lr: 6.8818e-04 eta: 15:19:01 time: 0.6030 data_time: 0.0360 memory: 14901 loss: 4.9730 loss_prob: 2.8316 loss_thr: 1.1521 loss_db: 0.9893 2022/11/02 12:32:14 - mmengine - INFO - Epoch(train) [35][30/63] lr: 6.8818e-04 eta: 15:18:06 time: 0.6105 data_time: 0.0373 memory: 14901 loss: 4.9695 loss_prob: 2.8313 loss_thr: 1.1640 loss_db: 0.9742 2022/11/02 12:32:16 - mmengine - INFO - Epoch(train) [35][35/63] lr: 6.8818e-04 eta: 15:18:06 time: 0.5342 data_time: 0.0071 memory: 14901 loss: 4.9431 loss_prob: 2.8253 loss_thr: 1.1542 loss_db: 0.9635 2022/11/02 12:32:19 - mmengine - INFO - Epoch(train) [35][40/63] lr: 6.8818e-04 eta: 15:16:45 time: 0.5327 data_time: 0.0052 memory: 14901 loss: 4.9196 loss_prob: 2.8216 loss_thr: 1.1585 loss_db: 0.9394 2022/11/02 12:32:22 - mmengine - INFO - Epoch(train) [35][45/63] lr: 6.8818e-04 eta: 15:16:45 time: 0.5311 data_time: 0.0045 memory: 14901 loss: 4.9249 loss_prob: 2.8333 loss_thr: 1.1842 loss_db: 0.9073 2022/11/02 12:32:24 - mmengine - INFO - Epoch(train) [35][50/63] lr: 6.8818e-04 eta: 15:15:22 time: 0.5255 data_time: 0.0262 memory: 14901 loss: 4.9639 loss_prob: 2.8404 loss_thr: 1.1752 loss_db: 0.9482 2022/11/02 12:32:27 - mmengine - INFO - Epoch(train) [35][55/63] lr: 6.8818e-04 eta: 15:15:22 time: 0.5152 data_time: 0.0266 memory: 14901 loss: 5.0157 loss_prob: 2.8707 loss_thr: 1.1528 loss_db: 0.9921 2022/11/02 12:32:29 - mmengine - INFO - Epoch(train) [35][60/63] lr: 6.8818e-04 eta: 15:13:53 time: 0.5023 data_time: 0.0048 memory: 14901 loss: 5.0244 loss_prob: 2.9171 loss_thr: 1.1663 loss_db: 0.9410 2022/11/02 12:32:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:32:35 - mmengine - INFO - Epoch(train) [36][5/63] lr: 7.0836e-04 eta: 15:13:53 time: 0.6861 data_time: 0.1659 memory: 14901 loss: 4.9575 loss_prob: 2.9210 loss_thr: 1.1883 loss_db: 0.8482 2022/11/02 12:32:38 - mmengine - INFO - Epoch(train) [36][10/63] lr: 7.0836e-04 eta: 15:12:22 time: 0.7245 data_time: 0.1706 memory: 14901 loss: 5.0360 loss_prob: 2.9080 loss_thr: 1.1871 loss_db: 0.9409 2022/11/02 12:32:40 - mmengine - INFO - Epoch(train) [36][15/63] lr: 7.0836e-04 eta: 15:12:22 time: 0.4890 data_time: 0.0093 memory: 14901 loss: 5.0642 loss_prob: 2.8981 loss_thr: 1.1665 loss_db: 0.9996 2022/11/02 12:32:43 - mmengine - INFO - Epoch(train) [36][20/63] lr: 7.0836e-04 eta: 15:10:50 time: 0.4896 data_time: 0.0047 memory: 14901 loss: 5.0377 loss_prob: 2.8822 loss_thr: 1.1557 loss_db: 0.9997 2022/11/02 12:32:45 - mmengine - INFO - Epoch(train) [36][25/63] lr: 7.0836e-04 eta: 15:10:50 time: 0.4992 data_time: 0.0083 memory: 14901 loss: 5.0146 loss_prob: 2.8771 loss_thr: 1.1395 loss_db: 0.9980 2022/11/02 12:32:48 - mmengine - INFO - Epoch(train) [36][30/63] lr: 7.0836e-04 eta: 15:09:29 time: 0.5212 data_time: 0.0346 memory: 14901 loss: 4.9983 loss_prob: 2.8691 loss_thr: 1.1317 loss_db: 0.9975 2022/11/02 12:32:51 - mmengine - INFO - Epoch(train) [36][35/63] lr: 7.0836e-04 eta: 15:09:29 time: 0.5652 data_time: 0.0314 memory: 14901 loss: 4.9743 loss_prob: 2.8624 loss_thr: 1.1321 loss_db: 0.9799 2022/11/02 12:32:54 - mmengine - INFO - Epoch(train) [36][40/63] lr: 7.0836e-04 eta: 15:08:26 time: 0.5750 data_time: 0.0052 memory: 14901 loss: 4.9004 loss_prob: 2.8593 loss_thr: 1.1464 loss_db: 0.8947 2022/11/02 12:32:56 - mmengine - INFO - Epoch(train) [36][45/63] lr: 7.0836e-04 eta: 15:08:26 time: 0.5173 data_time: 0.0047 memory: 14901 loss: 4.8834 loss_prob: 2.8582 loss_thr: 1.1879 loss_db: 0.8373 2022/11/02 12:32:58 - mmengine - INFO - Epoch(train) [36][50/63] lr: 7.0836e-04 eta: 15:06:47 time: 0.4621 data_time: 0.0102 memory: 14901 loss: 4.9185 loss_prob: 2.8540 loss_thr: 1.2086 loss_db: 0.8560 2022/11/02 12:33:01 - mmengine - INFO - Epoch(train) [36][55/63] lr: 7.0836e-04 eta: 15:06:47 time: 0.5165 data_time: 0.0250 memory: 14901 loss: 4.8828 loss_prob: 2.8522 loss_thr: 1.1977 loss_db: 0.8330 2022/11/02 12:33:04 - mmengine - INFO - Epoch(train) [36][60/63] lr: 7.0836e-04 eta: 15:05:37 time: 0.5485 data_time: 0.0194 memory: 14901 loss: 4.8410 loss_prob: 2.8623 loss_thr: 1.1826 loss_db: 0.7961 2022/11/02 12:33:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:33:10 - mmengine - INFO - Epoch(train) [37][5/63] lr: 7.2855e-04 eta: 15:05:37 time: 0.6818 data_time: 0.2213 memory: 14901 loss: 4.8915 loss_prob: 2.8696 loss_thr: 1.1809 loss_db: 0.8410 2022/11/02 12:33:12 - mmengine - INFO - Epoch(train) [37][10/63] lr: 7.2855e-04 eta: 15:04:07 time: 0.7123 data_time: 0.2221 memory: 14901 loss: 4.8124 loss_prob: 2.8403 loss_thr: 1.1557 loss_db: 0.8163 2022/11/02 12:33:15 - mmengine - INFO - Epoch(train) [37][15/63] lr: 7.2855e-04 eta: 15:04:07 time: 0.4970 data_time: 0.0083 memory: 14901 loss: 4.7007 loss_prob: 2.8337 loss_thr: 1.1371 loss_db: 0.7299 2022/11/02 12:33:17 - mmengine - INFO - Epoch(train) [37][20/63] lr: 7.2855e-04 eta: 15:02:45 time: 0.5065 data_time: 0.0087 memory: 14901 loss: 4.7254 loss_prob: 2.8443 loss_thr: 1.1541 loss_db: 0.7270 2022/11/02 12:33:20 - mmengine - INFO - Epoch(train) [37][25/63] lr: 7.2855e-04 eta: 15:02:45 time: 0.5209 data_time: 0.0195 memory: 14901 loss: 4.7268 loss_prob: 2.8411 loss_thr: 1.1657 loss_db: 0.7200 2022/11/02 12:33:23 - mmengine - INFO - Epoch(train) [37][30/63] lr: 7.2855e-04 eta: 15:01:35 time: 0.5446 data_time: 0.0369 memory: 14901 loss: 4.7463 loss_prob: 2.8545 loss_thr: 1.1604 loss_db: 0.7313 2022/11/02 12:33:25 - mmengine - INFO - Epoch(train) [37][35/63] lr: 7.2855e-04 eta: 15:01:35 time: 0.5248 data_time: 0.0233 memory: 14901 loss: 4.7989 loss_prob: 2.8649 loss_thr: 1.1558 loss_db: 0.7782 2022/11/02 12:33:28 - mmengine - INFO - Epoch(train) [37][40/63] lr: 7.2855e-04 eta: 15:00:21 time: 0.5275 data_time: 0.0063 memory: 14901 loss: 4.7960 loss_prob: 2.8425 loss_thr: 1.1534 loss_db: 0.8001 2022/11/02 12:33:30 - mmengine - INFO - Epoch(train) [37][45/63] lr: 7.2855e-04 eta: 15:00:21 time: 0.5236 data_time: 0.0067 memory: 14901 loss: 4.8132 loss_prob: 2.8460 loss_thr: 1.1608 loss_db: 0.8064 2022/11/02 12:33:33 - mmengine - INFO - Epoch(train) [37][50/63] lr: 7.2855e-04 eta: 14:59:05 time: 0.5192 data_time: 0.0227 memory: 14901 loss: 4.7915 loss_prob: 2.8579 loss_thr: 1.1704 loss_db: 0.7632 2022/11/02 12:33:36 - mmengine - INFO - Epoch(train) [37][55/63] lr: 7.2855e-04 eta: 14:59:05 time: 0.5224 data_time: 0.0254 memory: 14901 loss: 4.7936 loss_prob: 2.8624 loss_thr: 1.1993 loss_db: 0.7319 2022/11/02 12:33:38 - mmengine - INFO - Epoch(train) [37][60/63] lr: 7.2855e-04 eta: 14:57:40 time: 0.4898 data_time: 0.0077 memory: 14901 loss: 4.8749 loss_prob: 2.8472 loss_thr: 1.1715 loss_db: 0.8563 2022/11/02 12:33:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:33:44 - mmengine - INFO - Epoch(train) [38][5/63] lr: 7.4873e-04 eta: 14:57:40 time: 0.6821 data_time: 0.1921 memory: 14901 loss: 4.7455 loss_prob: 2.8146 loss_thr: 1.1188 loss_db: 0.8121 2022/11/02 12:33:47 - mmengine - INFO - Epoch(train) [38][10/63] lr: 7.4873e-04 eta: 14:56:26 time: 0.7492 data_time: 0.2283 memory: 14901 loss: 4.7488 loss_prob: 2.8366 loss_thr: 1.1524 loss_db: 0.7598 2022/11/02 12:33:49 - mmengine - INFO - Epoch(train) [38][15/63] lr: 7.4873e-04 eta: 14:56:26 time: 0.5473 data_time: 0.0422 memory: 14901 loss: 4.9235 loss_prob: 2.8519 loss_thr: 1.1737 loss_db: 0.8979 2022/11/02 12:33:52 - mmengine - INFO - Epoch(train) [38][20/63] lr: 7.4873e-04 eta: 14:55:06 time: 0.5011 data_time: 0.0047 memory: 14901 loss: 4.9745 loss_prob: 2.8478 loss_thr: 1.1622 loss_db: 0.9646 2022/11/02 12:33:55 - mmengine - INFO - Epoch(train) [38][25/63] lr: 7.4873e-04 eta: 14:55:06 time: 0.5141 data_time: 0.0086 memory: 14901 loss: 4.9529 loss_prob: 2.8477 loss_thr: 1.1343 loss_db: 0.9710 2022/11/02 12:33:57 - mmengine - INFO - Epoch(train) [38][30/63] lr: 7.4873e-04 eta: 14:54:10 time: 0.5772 data_time: 0.0290 memory: 14901 loss: 4.9428 loss_prob: 2.8665 loss_thr: 1.1349 loss_db: 0.9414 2022/11/02 12:34:00 - mmengine - INFO - Epoch(train) [38][35/63] lr: 7.4873e-04 eta: 14:54:10 time: 0.5617 data_time: 0.0318 memory: 14901 loss: 4.9856 loss_prob: 2.8707 loss_thr: 1.1462 loss_db: 0.9686 2022/11/02 12:34:03 - mmengine - INFO - Epoch(train) [38][40/63] lr: 7.4873e-04 eta: 14:53:16 time: 0.5803 data_time: 0.0111 memory: 14901 loss: 5.0109 loss_prob: 2.8711 loss_thr: 1.1404 loss_db: 0.9994 2022/11/02 12:34:07 - mmengine - INFO - Epoch(train) [38][45/63] lr: 7.4873e-04 eta: 14:53:16 time: 0.6967 data_time: 0.0050 memory: 14901 loss: 4.9956 loss_prob: 2.8926 loss_thr: 1.1530 loss_db: 0.9501 2022/11/02 12:34:11 - mmengine - INFO - Epoch(train) [38][50/63] lr: 7.4873e-04 eta: 14:53:11 time: 0.7388 data_time: 0.0162 memory: 14901 loss: 4.9406 loss_prob: 2.8918 loss_thr: 1.1847 loss_db: 0.8641 2022/11/02 12:34:14 - mmengine - INFO - Epoch(train) [38][55/63] lr: 7.4873e-04 eta: 14:53:11 time: 0.6412 data_time: 0.0195 memory: 14901 loss: 4.8985 loss_prob: 2.8768 loss_thr: 1.1703 loss_db: 0.8514 2022/11/02 12:34:16 - mmengine - INFO - Epoch(train) [38][60/63] lr: 7.4873e-04 eta: 14:52:09 time: 0.5557 data_time: 0.0156 memory: 14901 loss: 4.8666 loss_prob: 2.8724 loss_thr: 1.1716 loss_db: 0.8226 2022/11/02 12:34:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:34:23 - mmengine - INFO - Epoch(train) [39][5/63] lr: 7.6891e-04 eta: 14:52:09 time: 0.7921 data_time: 0.2001 memory: 14901 loss: 4.7489 loss_prob: 2.8795 loss_thr: 1.1406 loss_db: 0.7289 2022/11/02 12:34:26 - mmengine - INFO - Epoch(train) [39][10/63] lr: 7.6891e-04 eta: 14:51:29 time: 0.8483 data_time: 0.2133 memory: 14901 loss: 4.9354 loss_prob: 2.8990 loss_thr: 1.1473 loss_db: 0.8891 2022/11/02 12:34:29 - mmengine - INFO - Epoch(train) [39][15/63] lr: 7.6891e-04 eta: 14:51:29 time: 0.5946 data_time: 0.0180 memory: 14901 loss: 4.8492 loss_prob: 2.8396 loss_thr: 1.1457 loss_db: 0.8639 2022/11/02 12:34:32 - mmengine - INFO - Epoch(train) [39][20/63] lr: 7.6891e-04 eta: 14:50:40 time: 0.5942 data_time: 0.0052 memory: 14901 loss: 4.7750 loss_prob: 2.8325 loss_thr: 1.1893 loss_db: 0.7533 2022/11/02 12:34:35 - mmengine - INFO - Epoch(train) [39][25/63] lr: 7.6891e-04 eta: 14:50:40 time: 0.5692 data_time: 0.0233 memory: 14901 loss: 4.8750 loss_prob: 2.8667 loss_thr: 1.2034 loss_db: 0.8049 2022/11/02 12:34:38 - mmengine - INFO - Epoch(train) [39][30/63] lr: 7.6891e-04 eta: 14:50:02 time: 0.6294 data_time: 0.0232 memory: 14901 loss: 4.8328 loss_prob: 2.8650 loss_thr: 1.2099 loss_db: 0.7579 2022/11/02 12:34:41 - mmengine - INFO - Epoch(train) [39][35/63] lr: 7.6891e-04 eta: 14:50:02 time: 0.5951 data_time: 0.0179 memory: 14901 loss: 4.6877 loss_prob: 2.8405 loss_thr: 1.1731 loss_db: 0.6741 2022/11/02 12:34:43 - mmengine - INFO - Epoch(train) [39][40/63] lr: 7.6891e-04 eta: 14:48:42 time: 0.4857 data_time: 0.0175 memory: 14901 loss: 4.6870 loss_prob: 2.8378 loss_thr: 1.1079 loss_db: 0.7413 2022/11/02 12:34:46 - mmengine - INFO - Epoch(train) [39][45/63] lr: 7.6891e-04 eta: 14:48:42 time: 0.5628 data_time: 0.0043 memory: 14901 loss: 4.7099 loss_prob: 2.8272 loss_thr: 1.1455 loss_db: 0.7371 2022/11/02 12:34:50 - mmengine - INFO - Epoch(train) [39][50/63] lr: 7.6891e-04 eta: 14:48:27 time: 0.7034 data_time: 0.0183 memory: 14901 loss: 4.6560 loss_prob: 2.8246 loss_thr: 1.1595 loss_db: 0.6719 2022/11/02 12:34:53 - mmengine - INFO - Epoch(train) [39][55/63] lr: 7.6891e-04 eta: 14:48:27 time: 0.6869 data_time: 0.0186 memory: 14901 loss: 4.5972 loss_prob: 2.8025 loss_thr: 1.1148 loss_db: 0.6799 2022/11/02 12:34:56 - mmengine - INFO - Epoch(train) [39][60/63] lr: 7.6891e-04 eta: 14:47:33 time: 0.5734 data_time: 0.0085 memory: 14901 loss: 4.5690 loss_prob: 2.7904 loss_thr: 1.1165 loss_db: 0.6620 2022/11/02 12:34:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:35:02 - mmengine - INFO - Epoch(train) [40][5/63] lr: 7.8909e-04 eta: 14:47:33 time: 0.6885 data_time: 0.2178 memory: 14901 loss: 4.6890 loss_prob: 2.8462 loss_thr: 1.1394 loss_db: 0.7034 2022/11/02 12:35:04 - mmengine - INFO - Epoch(train) [40][10/63] lr: 7.8909e-04 eta: 14:46:14 time: 0.7102 data_time: 0.2192 memory: 14901 loss: 4.5794 loss_prob: 2.7921 loss_thr: 1.1009 loss_db: 0.6865 2022/11/02 12:35:07 - mmengine - INFO - Epoch(train) [40][15/63] lr: 7.8909e-04 eta: 14:46:14 time: 0.5294 data_time: 0.0066 memory: 14901 loss: 4.4765 loss_prob: 2.7505 loss_thr: 1.0819 loss_db: 0.6441 2022/11/02 12:35:10 - mmengine - INFO - Epoch(train) [40][20/63] lr: 7.8909e-04 eta: 14:45:12 time: 0.5441 data_time: 0.0097 memory: 14901 loss: 4.3902 loss_prob: 2.7393 loss_thr: 1.0644 loss_db: 0.5865 2022/11/02 12:35:12 - mmengine - INFO - Epoch(train) [40][25/63] lr: 7.8909e-04 eta: 14:45:12 time: 0.4955 data_time: 0.0143 memory: 14901 loss: 4.3858 loss_prob: 2.7222 loss_thr: 1.0521 loss_db: 0.6115 2022/11/02 12:35:14 - mmengine - INFO - Epoch(train) [40][30/63] lr: 7.8909e-04 eta: 14:43:51 time: 0.4754 data_time: 0.0285 memory: 14901 loss: 4.3973 loss_prob: 2.7220 loss_thr: 1.0717 loss_db: 0.6036 2022/11/02 12:35:17 - mmengine - INFO - Epoch(train) [40][35/63] lr: 7.8909e-04 eta: 14:43:51 time: 0.4865 data_time: 0.0236 memory: 14901 loss: 4.2807 loss_prob: 2.6882 loss_thr: 1.0518 loss_db: 0.5407 2022/11/02 12:35:19 - mmengine - INFO - Epoch(train) [40][40/63] lr: 7.8909e-04 eta: 14:42:33 time: 0.4827 data_time: 0.0046 memory: 14901 loss: 4.2465 loss_prob: 2.6722 loss_thr: 1.0315 loss_db: 0.5428 2022/11/02 12:35:22 - mmengine - INFO - Epoch(train) [40][45/63] lr: 7.8909e-04 eta: 14:42:33 time: 0.4866 data_time: 0.0080 memory: 14901 loss: 4.3254 loss_prob: 2.6979 loss_thr: 1.0555 loss_db: 0.5720 2022/11/02 12:35:25 - mmengine - INFO - Epoch(train) [40][50/63] lr: 7.8909e-04 eta: 14:41:31 time: 0.5375 data_time: 0.0201 memory: 14901 loss: 4.2148 loss_prob: 2.6316 loss_thr: 1.0542 loss_db: 0.5289 2022/11/02 12:35:28 - mmengine - INFO - Epoch(train) [40][55/63] lr: 7.8909e-04 eta: 14:41:31 time: 0.6076 data_time: 0.0235 memory: 14901 loss: 4.2255 loss_prob: 2.6599 loss_thr: 1.0450 loss_db: 0.5206 2022/11/02 12:35:30 - mmengine - INFO - Epoch(train) [40][60/63] lr: 7.8909e-04 eta: 14:40:37 time: 0.5607 data_time: 0.0117 memory: 14901 loss: 4.3959 loss_prob: 2.7408 loss_thr: 1.0651 loss_db: 0.5900 2022/11/02 12:35:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:35:32 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/11/02 12:35:35 - mmengine - INFO - Epoch(val) [40][5/500] eta: 14:40:37 time: 0.0564 data_time: 0.0065 memory: 14901 2022/11/02 12:35:36 - mmengine - INFO - Epoch(val) [40][10/500] eta: 0:00:39 time: 0.0815 data_time: 0.0063 memory: 1008 2022/11/02 12:35:36 - mmengine - INFO - Epoch(val) [40][15/500] eta: 0:00:39 time: 0.0865 data_time: 0.0029 memory: 1008 2022/11/02 12:35:37 - mmengine - INFO - Epoch(val) [40][20/500] eta: 0:00:41 time: 0.0868 data_time: 0.0032 memory: 1008 2022/11/02 12:35:37 - mmengine - INFO - Epoch(val) [40][25/500] eta: 0:00:41 time: 0.0687 data_time: 0.0024 memory: 1008 2022/11/02 12:35:37 - mmengine - INFO - Epoch(val) [40][30/500] eta: 0:00:36 time: 0.0780 data_time: 0.0024 memory: 1008 2022/11/02 12:35:38 - mmengine - INFO - Epoch(val) [40][35/500] eta: 0:00:36 time: 0.0964 data_time: 0.0024 memory: 1008 2022/11/02 12:35:39 - mmengine - INFO - Epoch(val) [40][40/500] eta: 0:00:55 time: 0.1201 data_time: 0.0027 memory: 1008 2022/11/02 12:35:39 - mmengine - INFO - Epoch(val) [40][45/500] eta: 0:00:55 time: 0.1340 data_time: 0.0028 memory: 1008 2022/11/02 12:35:40 - mmengine - INFO - Epoch(val) [40][50/500] eta: 0:00:46 time: 0.1034 data_time: 0.0026 memory: 1008 2022/11/02 12:35:40 - mmengine - INFO - Epoch(val) [40][55/500] eta: 0:00:46 time: 0.0753 data_time: 0.0025 memory: 1008 2022/11/02 12:35:40 - mmengine - INFO - Epoch(val) [40][60/500] eta: 0:00:35 time: 0.0814 data_time: 0.0024 memory: 1008 2022/11/02 12:35:41 - mmengine - INFO - Epoch(val) [40][65/500] eta: 0:00:35 time: 0.0840 data_time: 0.0026 memory: 1008 2022/11/02 12:35:41 - mmengine - INFO - Epoch(val) [40][70/500] eta: 0:00:35 time: 0.0828 data_time: 0.0027 memory: 1008 2022/11/02 12:35:42 - mmengine - INFO - Epoch(val) [40][75/500] eta: 0:00:35 time: 0.0855 data_time: 0.0024 memory: 1008 2022/11/02 12:35:42 - mmengine - INFO - Epoch(val) [40][80/500] eta: 0:00:25 time: 0.0597 data_time: 0.0024 memory: 1008 2022/11/02 12:35:42 - mmengine - INFO - Epoch(val) [40][85/500] eta: 0:00:25 time: 0.0555 data_time: 0.0025 memory: 1008 2022/11/02 12:35:43 - mmengine - INFO - Epoch(val) [40][90/500] eta: 0:00:33 time: 0.0828 data_time: 0.0024 memory: 1008 2022/11/02 12:35:43 - mmengine - INFO - Epoch(val) [40][95/500] eta: 0:00:33 time: 0.0823 data_time: 0.0025 memory: 1008 2022/11/02 12:35:43 - mmengine - INFO - Epoch(val) [40][100/500] eta: 0:00:30 time: 0.0760 data_time: 0.0025 memory: 1008 2022/11/02 12:35:44 - mmengine - INFO - Epoch(val) [40][105/500] eta: 0:00:30 time: 0.0801 data_time: 0.0026 memory: 1008 2022/11/02 12:35:44 - mmengine - INFO - Epoch(val) [40][110/500] eta: 0:00:32 time: 0.0829 data_time: 0.0026 memory: 1008 2022/11/02 12:35:45 - mmengine - INFO - Epoch(val) [40][115/500] eta: 0:00:32 time: 0.1004 data_time: 0.0026 memory: 1008 2022/11/02 12:35:45 - mmengine - INFO - Epoch(val) [40][120/500] eta: 0:00:33 time: 0.0879 data_time: 0.0026 memory: 1008 2022/11/02 12:35:46 - mmengine - INFO - Epoch(val) [40][125/500] eta: 0:00:33 time: 0.0682 data_time: 0.0029 memory: 1008 2022/11/02 12:35:46 - mmengine - INFO - Epoch(val) [40][130/500] eta: 0:00:32 time: 0.0878 data_time: 0.0026 memory: 1008 2022/11/02 12:35:46 - mmengine - INFO - Epoch(val) [40][135/500] eta: 0:00:32 time: 0.0845 data_time: 0.0024 memory: 1008 2022/11/02 12:35:47 - mmengine - INFO - Epoch(val) [40][140/500] eta: 0:00:30 time: 0.0841 data_time: 0.0028 memory: 1008 2022/11/02 12:35:47 - mmengine - INFO - Epoch(val) [40][145/500] eta: 0:00:30 time: 0.0988 data_time: 0.0030 memory: 1008 2022/11/02 12:35:48 - mmengine - INFO - Epoch(val) [40][150/500] eta: 0:00:33 time: 0.0958 data_time: 0.0027 memory: 1008 2022/11/02 12:35:48 - mmengine - INFO - Epoch(val) [40][155/500] eta: 0:00:33 time: 0.0915 data_time: 0.0025 memory: 1008 2022/11/02 12:35:49 - mmengine - INFO - Epoch(val) [40][160/500] eta: 0:00:35 time: 0.1046 data_time: 0.0024 memory: 1008 2022/11/02 12:35:50 - mmengine - INFO - Epoch(val) [40][165/500] eta: 0:00:35 time: 0.1343 data_time: 0.0024 memory: 1008 2022/11/02 12:35:50 - mmengine - INFO - Epoch(val) [40][170/500] eta: 0:00:50 time: 0.1520 data_time: 0.0025 memory: 1008 2022/11/02 12:35:51 - mmengine - INFO - Epoch(val) [40][175/500] eta: 0:00:50 time: 0.1140 data_time: 0.0024 memory: 1008 2022/11/02 12:35:51 - mmengine - INFO - Epoch(val) [40][180/500] eta: 0:00:25 time: 0.0785 data_time: 0.0024 memory: 1008 2022/11/02 12:35:51 - mmengine - INFO - Epoch(val) [40][185/500] eta: 0:00:25 time: 0.0735 data_time: 0.0025 memory: 1008 2022/11/02 12:35:52 - mmengine - INFO - Epoch(val) [40][190/500] eta: 0:00:19 time: 0.0640 data_time: 0.0024 memory: 1008 2022/11/02 12:35:52 - mmengine - INFO - Epoch(val) [40][195/500] eta: 0:00:19 time: 0.0675 data_time: 0.0024 memory: 1008 2022/11/02 12:35:53 - mmengine - INFO - Epoch(val) [40][200/500] eta: 0:00:28 time: 0.0952 data_time: 0.0027 memory: 1008 2022/11/02 12:35:53 - mmengine - INFO - Epoch(val) [40][205/500] eta: 0:00:28 time: 0.0989 data_time: 0.0028 memory: 1008 2022/11/02 12:35:54 - mmengine - INFO - Epoch(val) [40][210/500] eta: 0:00:22 time: 0.0784 data_time: 0.0025 memory: 1008 2022/11/02 12:35:54 - mmengine - INFO - Epoch(val) [40][215/500] eta: 0:00:22 time: 0.0886 data_time: 0.0029 memory: 1008 2022/11/02 12:35:54 - mmengine - INFO - Epoch(val) [40][220/500] eta: 0:00:20 time: 0.0749 data_time: 0.0030 memory: 1008 2022/11/02 12:35:55 - mmengine - INFO - Epoch(val) [40][225/500] eta: 0:00:20 time: 0.0815 data_time: 0.0026 memory: 1008 2022/11/02 12:35:55 - mmengine - INFO - Epoch(val) [40][230/500] eta: 0:00:26 time: 0.0969 data_time: 0.0026 memory: 1008 2022/11/02 12:35:56 - mmengine - INFO - Epoch(val) [40][235/500] eta: 0:00:26 time: 0.0846 data_time: 0.0025 memory: 1008 2022/11/02 12:35:56 - mmengine - INFO - Epoch(val) [40][240/500] eta: 0:00:21 time: 0.0823 data_time: 0.0028 memory: 1008 2022/11/02 12:35:57 - mmengine - INFO - Epoch(val) [40][245/500] eta: 0:00:21 time: 0.0848 data_time: 0.0028 memory: 1008 2022/11/02 12:35:57 - mmengine - INFO - Epoch(val) [40][250/500] eta: 0:00:28 time: 0.1142 data_time: 0.0024 memory: 1008 2022/11/02 12:35:58 - mmengine - INFO - Epoch(val) [40][255/500] eta: 0:00:28 time: 0.1094 data_time: 0.0029 memory: 1008 2022/11/02 12:35:58 - mmengine - INFO - Epoch(val) [40][260/500] eta: 0:00:16 time: 0.0699 data_time: 0.0028 memory: 1008 2022/11/02 12:35:59 - mmengine - INFO - Epoch(val) [40][265/500] eta: 0:00:16 time: 0.1080 data_time: 0.0037 memory: 1008 2022/11/02 12:35:59 - mmengine - INFO - Epoch(val) [40][270/500] eta: 0:00:26 time: 0.1156 data_time: 0.0038 memory: 1008 2022/11/02 12:36:00 - mmengine - INFO - Epoch(val) [40][275/500] eta: 0:00:26 time: 0.0769 data_time: 0.0031 memory: 1008 2022/11/02 12:36:00 - mmengine - INFO - Epoch(val) [40][280/500] eta: 0:00:16 time: 0.0755 data_time: 0.0032 memory: 1008 2022/11/02 12:36:00 - mmengine - INFO - Epoch(val) [40][285/500] eta: 0:00:16 time: 0.0685 data_time: 0.0029 memory: 1008 2022/11/02 12:36:01 - mmengine - INFO - Epoch(val) [40][290/500] eta: 0:00:18 time: 0.0879 data_time: 0.0027 memory: 1008 2022/11/02 12:36:01 - mmengine - INFO - Epoch(val) [40][295/500] eta: 0:00:18 time: 0.1065 data_time: 0.0029 memory: 1008 2022/11/02 12:36:02 - mmengine - INFO - Epoch(val) [40][300/500] eta: 0:00:18 time: 0.0903 data_time: 0.0029 memory: 1008 2022/11/02 12:36:02 - mmengine - INFO - Epoch(val) [40][305/500] eta: 0:00:18 time: 0.0978 data_time: 0.0029 memory: 1008 2022/11/02 12:36:03 - mmengine - INFO - Epoch(val) [40][310/500] eta: 0:00:17 time: 0.0925 data_time: 0.0029 memory: 1008 2022/11/02 12:36:03 - mmengine - INFO - Epoch(val) [40][315/500] eta: 0:00:17 time: 0.0728 data_time: 0.0028 memory: 1008 2022/11/02 12:36:03 - mmengine - INFO - Epoch(val) [40][320/500] eta: 0:00:12 time: 0.0681 data_time: 0.0028 memory: 1008 2022/11/02 12:36:04 - mmengine - INFO - Epoch(val) [40][325/500] eta: 0:00:12 time: 0.0895 data_time: 0.0025 memory: 1008 2022/11/02 12:36:04 - mmengine - INFO - Epoch(val) [40][330/500] eta: 0:00:16 time: 0.0980 data_time: 0.0027 memory: 1008 2022/11/02 12:36:04 - mmengine - INFO - Epoch(val) [40][335/500] eta: 0:00:16 time: 0.0640 data_time: 0.0028 memory: 1008 2022/11/02 12:36:05 - mmengine - INFO - Epoch(val) [40][340/500] eta: 0:00:15 time: 0.0966 data_time: 0.0026 memory: 1008 2022/11/02 12:36:06 - mmengine - INFO - Epoch(val) [40][345/500] eta: 0:00:15 time: 0.1033 data_time: 0.0026 memory: 1008 2022/11/02 12:36:06 - mmengine - INFO - Epoch(val) [40][350/500] eta: 0:00:13 time: 0.0882 data_time: 0.0026 memory: 1008 2022/11/02 12:36:06 - mmengine - INFO - Epoch(val) [40][355/500] eta: 0:00:13 time: 0.0935 data_time: 0.0025 memory: 1008 2022/11/02 12:36:07 - mmengine - INFO - Epoch(val) [40][360/500] eta: 0:00:10 time: 0.0752 data_time: 0.0026 memory: 1008 2022/11/02 12:36:07 - mmengine - INFO - Epoch(val) [40][365/500] eta: 0:00:10 time: 0.0850 data_time: 0.0026 memory: 1008 2022/11/02 12:36:08 - mmengine - INFO - Epoch(val) [40][370/500] eta: 0:00:10 time: 0.0814 data_time: 0.0026 memory: 1008 2022/11/02 12:36:08 - mmengine - INFO - Epoch(val) [40][375/500] eta: 0:00:10 time: 0.0767 data_time: 0.0033 memory: 1008 2022/11/02 12:36:09 - mmengine - INFO - Epoch(val) [40][380/500] eta: 0:00:12 time: 0.1003 data_time: 0.0033 memory: 1008 2022/11/02 12:36:09 - mmengine - INFO - Epoch(val) [40][385/500] eta: 0:00:12 time: 0.1016 data_time: 0.0026 memory: 1008 2022/11/02 12:36:10 - mmengine - INFO - Epoch(val) [40][390/500] eta: 0:00:12 time: 0.1160 data_time: 0.0027 memory: 1008 2022/11/02 12:36:10 - mmengine - INFO - Epoch(val) [40][395/500] eta: 0:00:12 time: 0.1202 data_time: 0.0028 memory: 1008 2022/11/02 12:36:11 - mmengine - INFO - Epoch(val) [40][400/500] eta: 0:00:08 time: 0.0871 data_time: 0.0027 memory: 1008 2022/11/02 12:36:11 - mmengine - INFO - Epoch(val) [40][405/500] eta: 0:00:08 time: 0.0904 data_time: 0.0028 memory: 1008 2022/11/02 12:36:12 - mmengine - INFO - Epoch(val) [40][410/500] eta: 0:00:08 time: 0.0915 data_time: 0.0026 memory: 1008 2022/11/02 12:36:12 - mmengine - INFO - Epoch(val) [40][415/500] eta: 0:00:08 time: 0.0775 data_time: 0.0025 memory: 1008 2022/11/02 12:36:13 - mmengine - INFO - Epoch(val) [40][420/500] eta: 0:00:09 time: 0.1136 data_time: 0.0490 memory: 1008 2022/11/02 12:36:13 - mmengine - INFO - Epoch(val) [40][425/500] eta: 0:00:09 time: 0.1364 data_time: 0.0487 memory: 1008 2022/11/02 12:36:14 - mmengine - INFO - Epoch(val) [40][430/500] eta: 0:00:07 time: 0.1061 data_time: 0.0022 memory: 1008 2022/11/02 12:36:14 - mmengine - INFO - Epoch(val) [40][435/500] eta: 0:00:07 time: 0.0751 data_time: 0.0026 memory: 1008 2022/11/02 12:36:14 - mmengine - INFO - Epoch(val) [40][440/500] eta: 0:00:03 time: 0.0574 data_time: 0.0025 memory: 1008 2022/11/02 12:36:15 - mmengine - INFO - Epoch(val) [40][445/500] eta: 0:00:03 time: 0.0703 data_time: 0.0024 memory: 1008 2022/11/02 12:36:15 - mmengine - INFO - Epoch(val) [40][450/500] eta: 0:00:04 time: 0.0874 data_time: 0.0024 memory: 1008 2022/11/02 12:36:16 - mmengine - INFO - Epoch(val) [40][455/500] eta: 0:00:04 time: 0.0876 data_time: 0.0024 memory: 1008 2022/11/02 12:36:16 - mmengine - INFO - Epoch(val) [40][460/500] eta: 0:00:03 time: 0.0759 data_time: 0.0029 memory: 1008 2022/11/02 12:36:17 - mmengine - INFO - Epoch(val) [40][465/500] eta: 0:00:03 time: 0.0834 data_time: 0.0033 memory: 1008 2022/11/02 12:36:17 - mmengine - INFO - Epoch(val) [40][470/500] eta: 0:00:02 time: 0.0892 data_time: 0.0031 memory: 1008 2022/11/02 12:36:17 - mmengine - INFO - Epoch(val) [40][475/500] eta: 0:00:02 time: 0.0691 data_time: 0.0029 memory: 1008 2022/11/02 12:36:18 - mmengine - INFO - Epoch(val) [40][480/500] eta: 0:00:01 time: 0.0783 data_time: 0.0027 memory: 1008 2022/11/02 12:36:18 - mmengine - INFO - Epoch(val) [40][485/500] eta: 0:00:01 time: 0.0896 data_time: 0.0025 memory: 1008 2022/11/02 12:36:19 - mmengine - INFO - Epoch(val) [40][490/500] eta: 0:00:01 time: 0.1153 data_time: 0.0026 memory: 1008 2022/11/02 12:36:19 - mmengine - INFO - Epoch(val) [40][495/500] eta: 0:00:01 time: 0.1164 data_time: 0.0026 memory: 1008 2022/11/02 12:36:20 - mmengine - INFO - Epoch(val) [40][500/500] eta: 0:00:00 time: 0.0791 data_time: 0.0032 memory: 1008 2022/11/02 12:36:20 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.1993, precision: 0.0488, hmean: 0.0784 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0934, precision: 0.5389, hmean: 0.1592 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0029, precision: 0.6000, hmean: 0.0057 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:36:20 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:36:20 - mmengine - INFO - Epoch(val) [40][500/500] icdar/precision: 0.5389 icdar/recall: 0.0934 icdar/hmean: 0.1592 2022/11/02 12:36:25 - mmengine - INFO - Epoch(train) [41][5/63] lr: 8.0927e-04 eta: 0:00:00 time: 0.7648 data_time: 0.1995 memory: 14901 loss: 4.4229 loss_prob: 2.7257 loss_thr: 1.0775 loss_db: 0.6197 2022/11/02 12:36:27 - mmengine - INFO - Epoch(train) [41][10/63] lr: 8.0927e-04 eta: 14:39:34 time: 0.7538 data_time: 0.2022 memory: 14901 loss: 4.3644 loss_prob: 2.6862 loss_thr: 1.0657 loss_db: 0.6125 2022/11/02 12:36:30 - mmengine - INFO - Epoch(train) [41][15/63] lr: 8.0927e-04 eta: 14:39:34 time: 0.4741 data_time: 0.0113 memory: 14901 loss: 4.3063 loss_prob: 2.6457 loss_thr: 1.0681 loss_db: 0.5925 2022/11/02 12:36:32 - mmengine - INFO - Epoch(train) [41][20/63] lr: 8.0927e-04 eta: 14:38:17 time: 0.4807 data_time: 0.0096 memory: 14901 loss: 4.2846 loss_prob: 2.6574 loss_thr: 1.0663 loss_db: 0.5609 2022/11/02 12:36:36 - mmengine - INFO - Epoch(train) [41][25/63] lr: 8.0927e-04 eta: 14:38:17 time: 0.6300 data_time: 0.0346 memory: 14901 loss: 4.2860 loss_prob: 2.6931 loss_thr: 1.0411 loss_db: 0.5518 2022/11/02 12:36:40 - mmengine - INFO - Epoch(train) [41][30/63] lr: 8.0927e-04 eta: 14:38:42 time: 0.8354 data_time: 0.0374 memory: 14901 loss: 4.4211 loss_prob: 2.7287 loss_thr: 1.0494 loss_db: 0.6429 2022/11/02 12:36:43 - mmengine - INFO - Epoch(train) [41][35/63] lr: 8.0927e-04 eta: 14:38:42 time: 0.6992 data_time: 0.0116 memory: 14901 loss: 4.3852 loss_prob: 2.6782 loss_thr: 1.0688 loss_db: 0.6382 2022/11/02 12:36:47 - mmengine - INFO - Epoch(train) [41][40/63] lr: 8.0927e-04 eta: 14:38:12 time: 0.6407 data_time: 0.0110 memory: 14901 loss: 4.1499 loss_prob: 2.5834 loss_thr: 1.0462 loss_db: 0.5204 2022/11/02 12:36:50 - mmengine - INFO - Epoch(train) [41][45/63] lr: 8.0927e-04 eta: 14:38:12 time: 0.7079 data_time: 0.0097 memory: 14901 loss: 4.0464 loss_prob: 2.5363 loss_thr: 1.0231 loss_db: 0.4871 2022/11/02 12:36:53 - mmengine - INFO - Epoch(train) [41][50/63] lr: 8.0927e-04 eta: 14:37:41 time: 0.6371 data_time: 0.0161 memory: 14901 loss: 4.0903 loss_prob: 2.5510 loss_thr: 1.0166 loss_db: 0.5227 2022/11/02 12:36:56 - mmengine - INFO - Epoch(train) [41][55/63] lr: 8.0927e-04 eta: 14:37:41 time: 0.5655 data_time: 0.0185 memory: 14901 loss: 4.1627 loss_prob: 2.5913 loss_thr: 1.0302 loss_db: 0.5412 2022/11/02 12:36:58 - mmengine - INFO - Epoch(train) [41][60/63] lr: 8.0927e-04 eta: 14:36:34 time: 0.5089 data_time: 0.0118 memory: 14901 loss: 4.2201 loss_prob: 2.6268 loss_thr: 1.0416 loss_db: 0.5517 2022/11/02 12:37:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:37:06 - mmengine - INFO - Epoch(train) [42][5/63] lr: 8.2945e-04 eta: 14:36:34 time: 0.8512 data_time: 0.2204 memory: 14901 loss: 3.8167 loss_prob: 2.4045 loss_thr: 0.9652 loss_db: 0.4470 2022/11/02 12:37:08 - mmengine - INFO - Epoch(train) [42][10/63] lr: 8.2945e-04 eta: 14:36:04 time: 0.8640 data_time: 0.2185 memory: 14901 loss: 3.9585 loss_prob: 2.4922 loss_thr: 0.9785 loss_db: 0.4878 2022/11/02 12:37:11 - mmengine - INFO - Epoch(train) [42][15/63] lr: 8.2945e-04 eta: 14:36:04 time: 0.4997 data_time: 0.0051 memory: 14901 loss: 4.1546 loss_prob: 2.6095 loss_thr: 1.0206 loss_db: 0.5246 2022/11/02 12:37:14 - mmengine - INFO - Epoch(train) [42][20/63] lr: 8.2945e-04 eta: 14:35:03 time: 0.5287 data_time: 0.0053 memory: 14901 loss: 4.1581 loss_prob: 2.5904 loss_thr: 1.0353 loss_db: 0.5323 2022/11/02 12:37:17 - mmengine - INFO - Epoch(train) [42][25/63] lr: 8.2945e-04 eta: 14:35:03 time: 0.6173 data_time: 0.0193 memory: 14901 loss: 4.0749 loss_prob: 2.5378 loss_thr: 1.0193 loss_db: 0.5178 2022/11/02 12:37:20 - mmengine - INFO - Epoch(train) [42][30/63] lr: 8.2945e-04 eta: 14:34:25 time: 0.6095 data_time: 0.0379 memory: 14901 loss: 3.9885 loss_prob: 2.4998 loss_thr: 1.0009 loss_db: 0.4878 2022/11/02 12:37:22 - mmengine - INFO - Epoch(train) [42][35/63] lr: 8.2945e-04 eta: 14:34:25 time: 0.5116 data_time: 0.0236 memory: 14901 loss: 3.9000 loss_prob: 2.4514 loss_thr: 0.9745 loss_db: 0.4741 2022/11/02 12:37:25 - mmengine - INFO - Epoch(train) [42][40/63] lr: 8.2945e-04 eta: 14:33:14 time: 0.4881 data_time: 0.0044 memory: 14901 loss: 3.9620 loss_prob: 2.4901 loss_thr: 0.9832 loss_db: 0.4888 2022/11/02 12:37:27 - mmengine - INFO - Epoch(train) [42][45/63] lr: 8.2945e-04 eta: 14:33:14 time: 0.4850 data_time: 0.0041 memory: 14901 loss: 4.0935 loss_prob: 2.5749 loss_thr: 1.0032 loss_db: 0.5155 2022/11/02 12:37:30 - mmengine - INFO - Epoch(train) [42][50/63] lr: 8.2945e-04 eta: 14:32:12 time: 0.5191 data_time: 0.0222 memory: 14901 loss: 3.8569 loss_prob: 2.4386 loss_thr: 0.9691 loss_db: 0.4491 2022/11/02 12:37:32 - mmengine - INFO - Epoch(train) [42][55/63] lr: 8.2945e-04 eta: 14:32:12 time: 0.5378 data_time: 0.0244 memory: 14901 loss: 3.8329 loss_prob: 2.4254 loss_thr: 0.9577 loss_db: 0.4498 2022/11/02 12:37:35 - mmengine - INFO - Epoch(train) [42][60/63] lr: 8.2945e-04 eta: 14:31:08 time: 0.5113 data_time: 0.0066 memory: 14901 loss: 4.0424 loss_prob: 2.5212 loss_thr: 0.9997 loss_db: 0.5215 2022/11/02 12:37:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:37:40 - mmengine - INFO - Epoch(train) [43][5/63] lr: 8.4964e-04 eta: 14:31:08 time: 0.6591 data_time: 0.2105 memory: 14901 loss: 4.1694 loss_prob: 2.6144 loss_thr: 0.9763 loss_db: 0.5787 2022/11/02 12:37:43 - mmengine - INFO - Epoch(train) [43][10/63] lr: 8.4964e-04 eta: 14:29:54 time: 0.6965 data_time: 0.2175 memory: 14901 loss: 4.2718 loss_prob: 2.6947 loss_thr: 1.0054 loss_db: 0.5717 2022/11/02 12:37:45 - mmengine - INFO - Epoch(train) [43][15/63] lr: 8.4964e-04 eta: 14:29:54 time: 0.4990 data_time: 0.0120 memory: 14901 loss: 4.1644 loss_prob: 2.6309 loss_thr: 1.0195 loss_db: 0.5140 2022/11/02 12:37:48 - mmengine - INFO - Epoch(train) [43][20/63] lr: 8.4964e-04 eta: 14:28:46 time: 0.4950 data_time: 0.0054 memory: 14901 loss: 3.9377 loss_prob: 2.4945 loss_thr: 0.9760 loss_db: 0.4672 2022/11/02 12:37:51 - mmengine - INFO - Epoch(train) [43][25/63] lr: 8.4964e-04 eta: 14:28:46 time: 0.5643 data_time: 0.0301 memory: 14901 loss: 3.8591 loss_prob: 2.4422 loss_thr: 0.9570 loss_db: 0.4599 2022/11/02 12:37:54 - mmengine - INFO - Epoch(train) [43][30/63] lr: 8.4964e-04 eta: 14:28:04 time: 0.5843 data_time: 0.0394 memory: 14901 loss: 3.8583 loss_prob: 2.4322 loss_thr: 0.9709 loss_db: 0.4552 2022/11/02 12:37:56 - mmengine - INFO - Epoch(train) [43][35/63] lr: 8.4964e-04 eta: 14:28:04 time: 0.5386 data_time: 0.0155 memory: 14901 loss: 3.7877 loss_prob: 2.3836 loss_thr: 0.9601 loss_db: 0.4440 2022/11/02 12:37:59 - mmengine - INFO - Epoch(train) [43][40/63] lr: 8.4964e-04 eta: 14:27:00 time: 0.5068 data_time: 0.0060 memory: 14901 loss: 3.7337 loss_prob: 2.3567 loss_thr: 0.9434 loss_db: 0.4336 2022/11/02 12:38:01 - mmengine - INFO - Epoch(train) [43][45/63] lr: 8.4964e-04 eta: 14:27:00 time: 0.4908 data_time: 0.0046 memory: 14901 loss: 3.6798 loss_prob: 2.3102 loss_thr: 0.9474 loss_db: 0.4221 2022/11/02 12:38:04 - mmengine - INFO - Epoch(train) [43][50/63] lr: 8.4964e-04 eta: 14:26:00 time: 0.5162 data_time: 0.0185 memory: 14901 loss: 3.6003 loss_prob: 2.2610 loss_thr: 0.9351 loss_db: 0.4043 2022/11/02 12:38:06 - mmengine - INFO - Epoch(train) [43][55/63] lr: 8.4964e-04 eta: 14:26:00 time: 0.4968 data_time: 0.0240 memory: 14901 loss: 3.6423 loss_prob: 2.2926 loss_thr: 0.9412 loss_db: 0.4084 2022/11/02 12:38:09 - mmengine - INFO - Epoch(train) [43][60/63] lr: 8.4964e-04 eta: 14:24:49 time: 0.4785 data_time: 0.0106 memory: 14901 loss: 3.5720 loss_prob: 2.2288 loss_thr: 0.9505 loss_db: 0.3927 2022/11/02 12:38:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:38:14 - mmengine - INFO - Epoch(train) [44][5/63] lr: 8.6982e-04 eta: 14:24:49 time: 0.6383 data_time: 0.1923 memory: 14901 loss: 3.5487 loss_prob: 2.2198 loss_thr: 0.9390 loss_db: 0.3899 2022/11/02 12:38:17 - mmengine - INFO - Epoch(train) [44][10/63] lr: 8.6982e-04 eta: 14:23:38 time: 0.6924 data_time: 0.1933 memory: 14901 loss: 3.6625 loss_prob: 2.2946 loss_thr: 0.9457 loss_db: 0.4222 2022/11/02 12:38:19 - mmengine - INFO - Epoch(train) [44][15/63] lr: 8.6982e-04 eta: 14:23:38 time: 0.5325 data_time: 0.0110 memory: 14901 loss: 3.5562 loss_prob: 2.2265 loss_thr: 0.9376 loss_db: 0.3921 2022/11/02 12:38:22 - mmengine - INFO - Epoch(train) [44][20/63] lr: 8.6982e-04 eta: 14:22:35 time: 0.5026 data_time: 0.0097 memory: 14901 loss: 3.5550 loss_prob: 2.2369 loss_thr: 0.9333 loss_db: 0.3848 2022/11/02 12:38:24 - mmengine - INFO - Epoch(train) [44][25/63] lr: 8.6982e-04 eta: 14:22:35 time: 0.4936 data_time: 0.0282 memory: 14901 loss: 3.7876 loss_prob: 2.3926 loss_thr: 0.9439 loss_db: 0.4511 2022/11/02 12:38:27 - mmengine - INFO - Epoch(train) [44][30/63] lr: 8.6982e-04 eta: 14:21:41 time: 0.5326 data_time: 0.0322 memory: 14901 loss: 4.2113 loss_prob: 2.6155 loss_thr: 0.9807 loss_db: 0.6151 2022/11/02 12:38:30 - mmengine - INFO - Epoch(train) [44][35/63] lr: 8.6982e-04 eta: 14:21:41 time: 0.5562 data_time: 0.0170 memory: 14901 loss: 4.2308 loss_prob: 2.6200 loss_thr: 0.9952 loss_db: 0.6156 2022/11/02 12:38:33 - mmengine - INFO - Epoch(train) [44][40/63] lr: 8.6982e-04 eta: 14:20:52 time: 0.5532 data_time: 0.0132 memory: 14901 loss: 3.9551 loss_prob: 2.4908 loss_thr: 0.9677 loss_db: 0.4967 2022/11/02 12:38:35 - mmengine - INFO - Epoch(train) [44][45/63] lr: 8.6982e-04 eta: 14:20:52 time: 0.4960 data_time: 0.0083 memory: 14901 loss: 3.9157 loss_prob: 2.4848 loss_thr: 0.9488 loss_db: 0.4821 2022/11/02 12:38:38 - mmengine - INFO - Epoch(train) [44][50/63] lr: 8.6982e-04 eta: 14:19:49 time: 0.4978 data_time: 0.0172 memory: 14901 loss: 3.7785 loss_prob: 2.4017 loss_thr: 0.9226 loss_db: 0.4542 2022/11/02 12:38:40 - mmengine - INFO - Epoch(train) [44][55/63] lr: 8.6982e-04 eta: 14:19:49 time: 0.5175 data_time: 0.0168 memory: 14901 loss: 3.7632 loss_prob: 2.3744 loss_thr: 0.9167 loss_db: 0.4721 2022/11/02 12:38:43 - mmengine - INFO - Epoch(train) [44][60/63] lr: 8.6982e-04 eta: 14:18:47 time: 0.4987 data_time: 0.0106 memory: 14901 loss: 3.6760 loss_prob: 2.3156 loss_thr: 0.9183 loss_db: 0.4421 2022/11/02 12:38:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:38:49 - mmengine - INFO - Epoch(train) [45][5/63] lr: 8.9000e-04 eta: 14:18:47 time: 0.7267 data_time: 0.2569 memory: 14901 loss: 3.5715 loss_prob: 2.2651 loss_thr: 0.9022 loss_db: 0.4042 2022/11/02 12:38:52 - mmengine - INFO - Epoch(train) [45][10/63] lr: 8.9000e-04 eta: 14:18:00 time: 0.7747 data_time: 0.2569 memory: 14901 loss: 3.8139 loss_prob: 2.4076 loss_thr: 0.9244 loss_db: 0.4819 2022/11/02 12:38:54 - mmengine - INFO - Epoch(train) [45][15/63] lr: 8.9000e-04 eta: 14:18:00 time: 0.5038 data_time: 0.0058 memory: 14901 loss: 3.9226 loss_prob: 2.4629 loss_thr: 0.9397 loss_db: 0.5200 2022/11/02 12:38:57 - mmengine - INFO - Epoch(train) [45][20/63] lr: 8.9000e-04 eta: 14:17:08 time: 0.5363 data_time: 0.0217 memory: 14901 loss: 3.6952 loss_prob: 2.3416 loss_thr: 0.9195 loss_db: 0.4341 2022/11/02 12:38:59 - mmengine - INFO - Epoch(train) [45][25/63] lr: 8.9000e-04 eta: 14:17:08 time: 0.5197 data_time: 0.0258 memory: 14901 loss: 3.5660 loss_prob: 2.2572 loss_thr: 0.9150 loss_db: 0.3938 2022/11/02 12:39:02 - mmengine - INFO - Epoch(train) [45][30/63] lr: 8.9000e-04 eta: 14:16:04 time: 0.4856 data_time: 0.0175 memory: 14901 loss: 3.5678 loss_prob: 2.2398 loss_thr: 0.9260 loss_db: 0.4020 2022/11/02 12:39:04 - mmengine - INFO - Epoch(train) [45][35/63] lr: 8.9000e-04 eta: 14:16:04 time: 0.5234 data_time: 0.0140 memory: 14901 loss: 3.4569 loss_prob: 2.1668 loss_thr: 0.9151 loss_db: 0.3751 2022/11/02 12:39:07 - mmengine - INFO - Epoch(train) [45][40/63] lr: 8.9000e-04 eta: 14:15:15 time: 0.5436 data_time: 0.0082 memory: 14901 loss: 3.3906 loss_prob: 2.1367 loss_thr: 0.8848 loss_db: 0.3692 2022/11/02 12:39:10 - mmengine - INFO - Epoch(train) [45][45/63] lr: 8.9000e-04 eta: 14:15:15 time: 0.6037 data_time: 0.0169 memory: 14901 loss: 3.2918 loss_prob: 2.0658 loss_thr: 0.8705 loss_db: 0.3555 2022/11/02 12:39:14 - mmengine - INFO - Epoch(train) [45][50/63] lr: 8.9000e-04 eta: 14:14:59 time: 0.6707 data_time: 0.0223 memory: 14901 loss: 3.5680 loss_prob: 2.2605 loss_thr: 0.9028 loss_db: 0.4047 2022/11/02 12:39:17 - mmengine - INFO - Epoch(train) [45][55/63] lr: 8.9000e-04 eta: 14:14:59 time: 0.6797 data_time: 0.0165 memory: 14901 loss: 3.6259 loss_prob: 2.3054 loss_thr: 0.9156 loss_db: 0.4049 2022/11/02 12:39:20 - mmengine - INFO - Epoch(train) [45][60/63] lr: 8.9000e-04 eta: 14:14:30 time: 0.6196 data_time: 0.0104 memory: 14901 loss: 3.4219 loss_prob: 2.1515 loss_thr: 0.8959 loss_db: 0.3746 2022/11/02 12:39:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:39:27 - mmengine - INFO - Epoch(train) [46][5/63] lr: 9.1018e-04 eta: 14:14:30 time: 0.8232 data_time: 0.2322 memory: 14901 loss: 3.5294 loss_prob: 2.2336 loss_thr: 0.8875 loss_db: 0.4082 2022/11/02 12:39:30 - mmengine - INFO - Epoch(train) [46][10/63] lr: 9.1018e-04 eta: 14:13:59 time: 0.8284 data_time: 0.2310 memory: 14901 loss: 3.5895 loss_prob: 2.2820 loss_thr: 0.8909 loss_db: 0.4167 2022/11/02 12:39:33 - mmengine - INFO - Epoch(train) [46][15/63] lr: 9.1018e-04 eta: 14:13:59 time: 0.5953 data_time: 0.0051 memory: 14901 loss: 3.8838 loss_prob: 2.4541 loss_thr: 0.9301 loss_db: 0.4995 2022/11/02 12:39:36 - mmengine - INFO - Epoch(train) [46][20/63] lr: 9.1018e-04 eta: 14:13:23 time: 0.5937 data_time: 0.0046 memory: 14901 loss: 3.9022 loss_prob: 2.4725 loss_thr: 0.9204 loss_db: 0.5093 2022/11/02 12:39:39 - mmengine - INFO - Epoch(train) [46][25/63] lr: 9.1018e-04 eta: 14:13:23 time: 0.6443 data_time: 0.0281 memory: 14901 loss: 3.5956 loss_prob: 2.2853 loss_thr: 0.8893 loss_db: 0.4209 2022/11/02 12:39:42 - mmengine - INFO - Epoch(train) [46][30/63] lr: 9.1018e-04 eta: 14:13:07 time: 0.6681 data_time: 0.0344 memory: 14901 loss: 3.4201 loss_prob: 2.1550 loss_thr: 0.8915 loss_db: 0.3736 2022/11/02 12:39:46 - mmengine - INFO - Epoch(train) [46][35/63] lr: 9.1018e-04 eta: 14:13:07 time: 0.6926 data_time: 0.0117 memory: 14901 loss: 3.5386 loss_prob: 2.2501 loss_thr: 0.8759 loss_db: 0.4126 2022/11/02 12:39:49 - mmengine - INFO - Epoch(train) [46][40/63] lr: 9.1018e-04 eta: 14:12:59 time: 0.7009 data_time: 0.0051 memory: 14901 loss: 3.5232 loss_prob: 2.2466 loss_thr: 0.8700 loss_db: 0.4066 2022/11/02 12:39:52 - mmengine - INFO - Epoch(train) [46][45/63] lr: 9.1018e-04 eta: 14:12:59 time: 0.6147 data_time: 0.0047 memory: 14901 loss: 3.4862 loss_prob: 2.1769 loss_thr: 0.9129 loss_db: 0.3964 2022/11/02 12:39:55 - mmengine - INFO - Epoch(train) [46][50/63] lr: 9.1018e-04 eta: 14:12:21 time: 0.5778 data_time: 0.0237 memory: 14901 loss: 3.6664 loss_prob: 2.2903 loss_thr: 0.9368 loss_db: 0.4393 2022/11/02 12:39:58 - mmengine - INFO - Epoch(train) [46][55/63] lr: 9.1018e-04 eta: 14:12:21 time: 0.5492 data_time: 0.0237 memory: 14901 loss: 3.6914 loss_prob: 2.3149 loss_thr: 0.9298 loss_db: 0.4468 2022/11/02 12:40:01 - mmengine - INFO - Epoch(train) [46][60/63] lr: 9.1018e-04 eta: 14:11:35 time: 0.5480 data_time: 0.0049 memory: 14901 loss: 3.3906 loss_prob: 2.1240 loss_thr: 0.8868 loss_db: 0.3798 2022/11/02 12:40:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:40:07 - mmengine - INFO - Epoch(train) [47][5/63] lr: 9.3036e-04 eta: 14:11:35 time: 0.7859 data_time: 0.2121 memory: 14901 loss: 3.3816 loss_prob: 2.1385 loss_thr: 0.8665 loss_db: 0.3766 2022/11/02 12:40:10 - mmengine - INFO - Epoch(train) [47][10/63] lr: 9.3036e-04 eta: 14:10:52 time: 0.7799 data_time: 0.2123 memory: 14901 loss: 3.5763 loss_prob: 2.2557 loss_thr: 0.9094 loss_db: 0.4112 2022/11/02 12:40:12 - mmengine - INFO - Epoch(train) [47][15/63] lr: 9.3036e-04 eta: 14:10:52 time: 0.4738 data_time: 0.0068 memory: 14901 loss: 3.4649 loss_prob: 2.1674 loss_thr: 0.9070 loss_db: 0.3905 2022/11/02 12:40:15 - mmengine - INFO - Epoch(train) [47][20/63] lr: 9.3036e-04 eta: 14:09:51 time: 0.4843 data_time: 0.0067 memory: 14901 loss: 3.2899 loss_prob: 2.0637 loss_thr: 0.8783 loss_db: 0.3479 2022/11/02 12:40:17 - mmengine - INFO - Epoch(train) [47][25/63] lr: 9.3036e-04 eta: 14:09:51 time: 0.5037 data_time: 0.0103 memory: 14901 loss: 3.2836 loss_prob: 2.0445 loss_thr: 0.8896 loss_db: 0.3495 2022/11/02 12:40:20 - mmengine - INFO - Epoch(train) [47][30/63] lr: 9.3036e-04 eta: 14:09:01 time: 0.5281 data_time: 0.0357 memory: 14901 loss: 3.3502 loss_prob: 2.0849 loss_thr: 0.8908 loss_db: 0.3745 2022/11/02 12:40:23 - mmengine - INFO - Epoch(train) [47][35/63] lr: 9.3036e-04 eta: 14:09:01 time: 0.5403 data_time: 0.0306 memory: 14901 loss: 3.3378 loss_prob: 2.0829 loss_thr: 0.8780 loss_db: 0.3769 2022/11/02 12:40:25 - mmengine - INFO - Epoch(train) [47][40/63] lr: 9.3036e-04 eta: 14:08:12 time: 0.5331 data_time: 0.0053 memory: 14901 loss: 3.3171 loss_prob: 2.0630 loss_thr: 0.8879 loss_db: 0.3661 2022/11/02 12:40:28 - mmengine - INFO - Epoch(train) [47][45/63] lr: 9.3036e-04 eta: 14:08:12 time: 0.5428 data_time: 0.0051 memory: 14901 loss: 3.3534 loss_prob: 2.0841 loss_thr: 0.9002 loss_db: 0.3691 2022/11/02 12:40:31 - mmengine - INFO - Epoch(train) [47][50/63] lr: 9.3036e-04 eta: 14:07:27 time: 0.5455 data_time: 0.0201 memory: 14901 loss: 3.3109 loss_prob: 2.0609 loss_thr: 0.8849 loss_db: 0.3651 2022/11/02 12:40:33 - mmengine - INFO - Epoch(train) [47][55/63] lr: 9.3036e-04 eta: 14:07:27 time: 0.5107 data_time: 0.0210 memory: 14901 loss: 3.4252 loss_prob: 2.1444 loss_thr: 0.8851 loss_db: 0.3956 2022/11/02 12:40:36 - mmengine - INFO - Epoch(train) [47][60/63] lr: 9.3036e-04 eta: 14:06:28 time: 0.4870 data_time: 0.0060 memory: 14901 loss: 3.2678 loss_prob: 2.0378 loss_thr: 0.8694 loss_db: 0.3606 2022/11/02 12:40:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:40:42 - mmengine - INFO - Epoch(train) [48][5/63] lr: 9.5055e-04 eta: 14:06:28 time: 0.6916 data_time: 0.1949 memory: 14901 loss: 3.2394 loss_prob: 2.0285 loss_thr: 0.8543 loss_db: 0.3566 2022/11/02 12:40:44 - mmengine - INFO - Epoch(train) [48][10/63] lr: 9.5055e-04 eta: 14:05:29 time: 0.7048 data_time: 0.2005 memory: 14901 loss: 3.1156 loss_prob: 1.9457 loss_thr: 0.8331 loss_db: 0.3367 2022/11/02 12:40:47 - mmengine - INFO - Epoch(train) [48][15/63] lr: 9.5055e-04 eta: 14:05:29 time: 0.4876 data_time: 0.0114 memory: 14901 loss: 3.0354 loss_prob: 1.8768 loss_thr: 0.8391 loss_db: 0.3195 2022/11/02 12:40:49 - mmengine - INFO - Epoch(train) [48][20/63] lr: 9.5055e-04 eta: 14:04:31 time: 0.4888 data_time: 0.0056 memory: 14901 loss: 3.1051 loss_prob: 1.9360 loss_thr: 0.8453 loss_db: 0.3238 2022/11/02 12:40:51 - mmengine - INFO - Epoch(train) [48][25/63] lr: 9.5055e-04 eta: 14:04:31 time: 0.4901 data_time: 0.0104 memory: 14901 loss: 3.1765 loss_prob: 1.9746 loss_thr: 0.8721 loss_db: 0.3298 2022/11/02 12:40:54 - mmengine - INFO - Epoch(train) [48][30/63] lr: 9.5055e-04 eta: 14:03:38 time: 0.5103 data_time: 0.0316 memory: 14901 loss: 3.1277 loss_prob: 1.9249 loss_thr: 0.8743 loss_db: 0.3286 2022/11/02 12:40:56 - mmengine - INFO - Epoch(train) [48][35/63] lr: 9.5055e-04 eta: 14:03:38 time: 0.4900 data_time: 0.0307 memory: 14901 loss: 3.2576 loss_prob: 2.0373 loss_thr: 0.8674 loss_db: 0.3529 2022/11/02 12:40:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:40:59 - mmengine - INFO - Epoch(train) [48][40/63] lr: 9.5055e-04 eta: 14:02:34 time: 0.4629 data_time: 0.0090 memory: 14901 loss: 3.2291 loss_prob: 2.0169 loss_thr: 0.8622 loss_db: 0.3500 2022/11/02 12:41:01 - mmengine - INFO - Epoch(train) [48][45/63] lr: 9.5055e-04 eta: 14:02:34 time: 0.5082 data_time: 0.0077 memory: 14901 loss: 3.2462 loss_prob: 2.0190 loss_thr: 0.8795 loss_db: 0.3477 2022/11/02 12:41:04 - mmengine - INFO - Epoch(train) [48][50/63] lr: 9.5055e-04 eta: 14:01:50 time: 0.5394 data_time: 0.0168 memory: 14901 loss: 3.2931 loss_prob: 2.0708 loss_thr: 0.8681 loss_db: 0.3543 2022/11/02 12:41:06 - mmengine - INFO - Epoch(train) [48][55/63] lr: 9.5055e-04 eta: 14:01:50 time: 0.5045 data_time: 0.0245 memory: 14901 loss: 3.2880 loss_prob: 2.0697 loss_thr: 0.8529 loss_db: 0.3654 2022/11/02 12:41:09 - mmengine - INFO - Epoch(train) [48][60/63] lr: 9.5055e-04 eta: 14:00:53 time: 0.4904 data_time: 0.0165 memory: 14901 loss: 3.2211 loss_prob: 2.0110 loss_thr: 0.8529 loss_db: 0.3572 2022/11/02 12:41:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:41:15 - mmengine - INFO - Epoch(train) [49][5/63] lr: 9.7073e-04 eta: 14:00:53 time: 0.6740 data_time: 0.1933 memory: 14901 loss: 3.1734 loss_prob: 1.9835 loss_thr: 0.8439 loss_db: 0.3460 2022/11/02 12:41:17 - mmengine - INFO - Epoch(train) [49][10/63] lr: 9.7073e-04 eta: 13:59:59 time: 0.7163 data_time: 0.1964 memory: 14901 loss: 3.3277 loss_prob: 2.0750 loss_thr: 0.8726 loss_db: 0.3800 2022/11/02 12:41:20 - mmengine - INFO - Epoch(train) [49][15/63] lr: 9.7073e-04 eta: 13:59:59 time: 0.5141 data_time: 0.0076 memory: 14901 loss: 3.0940 loss_prob: 1.9281 loss_thr: 0.8323 loss_db: 0.3336 2022/11/02 12:41:22 - mmengine - INFO - Epoch(train) [49][20/63] lr: 9.7073e-04 eta: 13:59:02 time: 0.4812 data_time: 0.0051 memory: 14901 loss: 3.0919 loss_prob: 1.9255 loss_thr: 0.8346 loss_db: 0.3318 2022/11/02 12:41:25 - mmengine - INFO - Epoch(train) [49][25/63] lr: 9.7073e-04 eta: 13:59:02 time: 0.5013 data_time: 0.0309 memory: 14901 loss: 3.0950 loss_prob: 1.9201 loss_thr: 0.8395 loss_db: 0.3353 2022/11/02 12:41:27 - mmengine - INFO - Epoch(train) [49][30/63] lr: 9.7073e-04 eta: 13:58:16 time: 0.5293 data_time: 0.0445 memory: 14901 loss: 2.9437 loss_prob: 1.8125 loss_thr: 0.8316 loss_db: 0.2996 2022/11/02 12:41:30 - mmengine - INFO - Epoch(train) [49][35/63] lr: 9.7073e-04 eta: 13:58:16 time: 0.5174 data_time: 0.0206 memory: 14901 loss: 2.9970 loss_prob: 1.8525 loss_thr: 0.8385 loss_db: 0.3060 2022/11/02 12:41:32 - mmengine - INFO - Epoch(train) [49][40/63] lr: 9.7073e-04 eta: 13:57:20 time: 0.4886 data_time: 0.0065 memory: 14901 loss: 3.1688 loss_prob: 1.9715 loss_thr: 0.8668 loss_db: 0.3306 2022/11/02 12:41:35 - mmengine - INFO - Epoch(train) [49][45/63] lr: 9.7073e-04 eta: 13:57:20 time: 0.4697 data_time: 0.0047 memory: 14901 loss: 3.3985 loss_prob: 2.1510 loss_thr: 0.8777 loss_db: 0.3698 2022/11/02 12:41:37 - mmengine - INFO - Epoch(train) [49][50/63] lr: 9.7073e-04 eta: 13:56:29 time: 0.5044 data_time: 0.0208 memory: 14901 loss: 3.5432 loss_prob: 2.2692 loss_thr: 0.8725 loss_db: 0.4015 2022/11/02 12:41:40 - mmengine - INFO - Epoch(train) [49][55/63] lr: 9.7073e-04 eta: 13:56:29 time: 0.5398 data_time: 0.0258 memory: 14901 loss: 3.6282 loss_prob: 2.2959 loss_thr: 0.8906 loss_db: 0.4416 2022/11/02 12:41:43 - mmengine - INFO - Epoch(train) [49][60/63] lr: 9.7073e-04 eta: 13:55:43 time: 0.5281 data_time: 0.0109 memory: 14901 loss: 3.5510 loss_prob: 2.2346 loss_thr: 0.8925 loss_db: 0.4238 2022/11/02 12:41:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:41:49 - mmengine - INFO - Epoch(train) [50][5/63] lr: 9.9091e-04 eta: 13:55:43 time: 0.7594 data_time: 0.2120 memory: 14901 loss: 3.5388 loss_prob: 2.2266 loss_thr: 0.8987 loss_db: 0.4134 2022/11/02 12:41:53 - mmengine - INFO - Epoch(train) [50][10/63] lr: 9.9091e-04 eta: 13:55:25 time: 0.8573 data_time: 0.2146 memory: 14901 loss: 3.4918 loss_prob: 2.2076 loss_thr: 0.8868 loss_db: 0.3975 2022/11/02 12:41:56 - mmengine - INFO - Epoch(train) [50][15/63] lr: 9.9091e-04 eta: 13:55:25 time: 0.6255 data_time: 0.0078 memory: 14901 loss: 3.3037 loss_prob: 2.0793 loss_thr: 0.8550 loss_db: 0.3694 2022/11/02 12:41:59 - mmengine - INFO - Epoch(train) [50][20/63] lr: 9.9091e-04 eta: 13:54:59 time: 0.6109 data_time: 0.0061 memory: 14901 loss: 3.1769 loss_prob: 1.9941 loss_thr: 0.8424 loss_db: 0.3404 2022/11/02 12:42:02 - mmengine - INFO - Epoch(train) [50][25/63] lr: 9.9091e-04 eta: 13:54:59 time: 0.6080 data_time: 0.0124 memory: 14901 loss: 3.1432 loss_prob: 1.9568 loss_thr: 0.8471 loss_db: 0.3392 2022/11/02 12:42:05 - mmengine - INFO - Epoch(train) [50][30/63] lr: 9.9091e-04 eta: 13:54:41 time: 0.6442 data_time: 0.0343 memory: 14901 loss: 3.2555 loss_prob: 2.0241 loss_thr: 0.8627 loss_db: 0.3687 2022/11/02 12:42:08 - mmengine - INFO - Epoch(train) [50][35/63] lr: 9.9091e-04 eta: 13:54:41 time: 0.6835 data_time: 0.0277 memory: 14901 loss: 3.2222 loss_prob: 2.0044 loss_thr: 0.8534 loss_db: 0.3644 2022/11/02 12:42:11 - mmengine - INFO - Epoch(train) [50][40/63] lr: 9.9091e-04 eta: 13:54:06 time: 0.5703 data_time: 0.0055 memory: 14901 loss: 3.0019 loss_prob: 1.8651 loss_thr: 0.8247 loss_db: 0.3121 2022/11/02 12:42:13 - mmengine - INFO - Epoch(train) [50][45/63] lr: 9.9091e-04 eta: 13:54:06 time: 0.4993 data_time: 0.0058 memory: 14901 loss: 3.0097 loss_prob: 1.8714 loss_thr: 0.8283 loss_db: 0.3100 2022/11/02 12:42:16 - mmengine - INFO - Epoch(train) [50][50/63] lr: 9.9091e-04 eta: 13:53:30 time: 0.5634 data_time: 0.0117 memory: 14901 loss: 2.9697 loss_prob: 1.8383 loss_thr: 0.8136 loss_db: 0.3177 2022/11/02 12:42:19 - mmengine - INFO - Epoch(train) [50][55/63] lr: 9.9091e-04 eta: 13:53:30 time: 0.5888 data_time: 0.0224 memory: 14901 loss: 3.2963 loss_prob: 2.0756 loss_thr: 0.8317 loss_db: 0.3890 2022/11/02 12:42:23 - mmengine - INFO - Epoch(train) [50][60/63] lr: 9.9091e-04 eta: 13:53:18 time: 0.6659 data_time: 0.0162 memory: 14901 loss: 3.5221 loss_prob: 2.2535 loss_thr: 0.8496 loss_db: 0.4190 2022/11/02 12:42:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:42:30 - mmengine - INFO - Epoch(train) [51][5/63] lr: 1.0111e-03 eta: 13:53:18 time: 0.7666 data_time: 0.2345 memory: 14901 loss: 3.6052 loss_prob: 2.2887 loss_thr: 0.8962 loss_db: 0.4203 2022/11/02 12:42:33 - mmengine - INFO - Epoch(train) [51][10/63] lr: 1.0111e-03 eta: 13:52:51 time: 0.8189 data_time: 0.2352 memory: 14901 loss: 3.3042 loss_prob: 2.0705 loss_thr: 0.8680 loss_db: 0.3657 2022/11/02 12:42:35 - mmengine - INFO - Epoch(train) [51][15/63] lr: 1.0111e-03 eta: 13:52:51 time: 0.5274 data_time: 0.0080 memory: 14901 loss: 3.0601 loss_prob: 1.8965 loss_thr: 0.8418 loss_db: 0.3218 2022/11/02 12:42:38 - mmengine - INFO - Epoch(train) [51][20/63] lr: 1.0111e-03 eta: 13:52:02 time: 0.5070 data_time: 0.0073 memory: 14901 loss: 3.0832 loss_prob: 1.9381 loss_thr: 0.8233 loss_db: 0.3219 2022/11/02 12:42:40 - mmengine - INFO - Epoch(train) [51][25/63] lr: 1.0111e-03 eta: 13:52:02 time: 0.5424 data_time: 0.0150 memory: 14901 loss: 3.3183 loss_prob: 2.1084 loss_thr: 0.8347 loss_db: 0.3752 2022/11/02 12:42:43 - mmengine - INFO - Epoch(train) [51][30/63] lr: 1.0111e-03 eta: 13:51:21 time: 0.5381 data_time: 0.0317 memory: 14901 loss: 3.4551 loss_prob: 2.1922 loss_thr: 0.8712 loss_db: 0.3917 2022/11/02 12:42:45 - mmengine - INFO - Epoch(train) [51][35/63] lr: 1.0111e-03 eta: 13:51:21 time: 0.4838 data_time: 0.0231 memory: 14901 loss: 3.2112 loss_prob: 2.0113 loss_thr: 0.8560 loss_db: 0.3439 2022/11/02 12:42:48 - mmengine - INFO - Epoch(train) [51][40/63] lr: 1.0111e-03 eta: 13:50:22 time: 0.4591 data_time: 0.0072 memory: 14901 loss: 3.0985 loss_prob: 1.9324 loss_thr: 0.8302 loss_db: 0.3360 2022/11/02 12:42:50 - mmengine - INFO - Epoch(train) [51][45/63] lr: 1.0111e-03 eta: 13:50:22 time: 0.4640 data_time: 0.0053 memory: 14901 loss: 3.3898 loss_prob: 2.1411 loss_thr: 0.8606 loss_db: 0.3881 2022/11/02 12:42:52 - mmengine - INFO - Epoch(train) [51][50/63] lr: 1.0111e-03 eta: 13:49:27 time: 0.4759 data_time: 0.0184 memory: 14901 loss: 3.2606 loss_prob: 2.0402 loss_thr: 0.8577 loss_db: 0.3626 2022/11/02 12:42:55 - mmengine - INFO - Epoch(train) [51][55/63] lr: 1.0111e-03 eta: 13:49:27 time: 0.4808 data_time: 0.0185 memory: 14901 loss: 2.9686 loss_prob: 1.8450 loss_thr: 0.8139 loss_db: 0.3097 2022/11/02 12:42:57 - mmengine - INFO - Epoch(train) [51][60/63] lr: 1.0111e-03 eta: 13:48:34 time: 0.4815 data_time: 0.0090 memory: 14901 loss: 3.0219 loss_prob: 1.8871 loss_thr: 0.8169 loss_db: 0.3179 2022/11/02 12:42:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:43:03 - mmengine - INFO - Epoch(train) [52][5/63] lr: 1.0313e-03 eta: 13:48:34 time: 0.7099 data_time: 0.1855 memory: 14901 loss: 3.0001 loss_prob: 1.8539 loss_thr: 0.8358 loss_db: 0.3103 2022/11/02 12:43:06 - mmengine - INFO - Epoch(train) [52][10/63] lr: 1.0313e-03 eta: 13:47:40 time: 0.6923 data_time: 0.1808 memory: 14901 loss: 3.1062 loss_prob: 1.9337 loss_thr: 0.8419 loss_db: 0.3306 2022/11/02 12:43:08 - mmengine - INFO - Epoch(train) [52][15/63] lr: 1.0313e-03 eta: 13:47:40 time: 0.5113 data_time: 0.0132 memory: 14901 loss: 3.1590 loss_prob: 1.9571 loss_thr: 0.8568 loss_db: 0.3451 2022/11/02 12:43:11 - mmengine - INFO - Epoch(train) [52][20/63] lr: 1.0313e-03 eta: 13:46:50 time: 0.4957 data_time: 0.0131 memory: 14901 loss: 3.2086 loss_prob: 1.9951 loss_thr: 0.8587 loss_db: 0.3548 2022/11/02 12:43:13 - mmengine - INFO - Epoch(train) [52][25/63] lr: 1.0313e-03 eta: 13:46:50 time: 0.5085 data_time: 0.0190 memory: 14901 loss: 3.2130 loss_prob: 2.0297 loss_thr: 0.8348 loss_db: 0.3485 2022/11/02 12:43:16 - mmengine - INFO - Epoch(train) [52][30/63] lr: 1.0313e-03 eta: 13:46:03 time: 0.5071 data_time: 0.0233 memory: 14901 loss: 3.0133 loss_prob: 1.8857 loss_thr: 0.8130 loss_db: 0.3145 2022/11/02 12:43:18 - mmengine - INFO - Epoch(train) [52][35/63] lr: 1.0313e-03 eta: 13:46:03 time: 0.4610 data_time: 0.0166 memory: 14901 loss: 3.0204 loss_prob: 1.8919 loss_thr: 0.8048 loss_db: 0.3237 2022/11/02 12:43:20 - mmengine - INFO - Epoch(train) [52][40/63] lr: 1.0313e-03 eta: 13:45:10 time: 0.4758 data_time: 0.0132 memory: 14901 loss: 2.9174 loss_prob: 1.8072 loss_thr: 0.8070 loss_db: 0.3032 2022/11/02 12:43:23 - mmengine - INFO - Epoch(train) [52][45/63] lr: 1.0313e-03 eta: 13:45:10 time: 0.4970 data_time: 0.0055 memory: 14901 loss: 2.8300 loss_prob: 1.7296 loss_thr: 0.8123 loss_db: 0.2882 2022/11/02 12:43:26 - mmengine - INFO - Epoch(train) [52][50/63] lr: 1.0313e-03 eta: 13:44:25 time: 0.5105 data_time: 0.0216 memory: 14901 loss: 3.0135 loss_prob: 1.8594 loss_thr: 0.8322 loss_db: 0.3219 2022/11/02 12:43:28 - mmengine - INFO - Epoch(train) [52][55/63] lr: 1.0313e-03 eta: 13:44:25 time: 0.4986 data_time: 0.0247 memory: 14901 loss: 3.1118 loss_prob: 1.9382 loss_thr: 0.8390 loss_db: 0.3346 2022/11/02 12:43:30 - mmengine - INFO - Epoch(train) [52][60/63] lr: 1.0313e-03 eta: 13:43:29 time: 0.4634 data_time: 0.0105 memory: 14901 loss: 3.0532 loss_prob: 1.8993 loss_thr: 0.8276 loss_db: 0.3263 2022/11/02 12:43:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:43:37 - mmengine - INFO - Epoch(train) [53][5/63] lr: 1.0515e-03 eta: 13:43:29 time: 0.7624 data_time: 0.2302 memory: 14901 loss: 2.9457 loss_prob: 1.8256 loss_thr: 0.8060 loss_db: 0.3141 2022/11/02 12:43:39 - mmengine - INFO - Epoch(train) [53][10/63] lr: 1.0515e-03 eta: 13:42:58 time: 0.7891 data_time: 0.2303 memory: 14901 loss: 2.9016 loss_prob: 1.7732 loss_thr: 0.8332 loss_db: 0.2951 2022/11/02 12:43:42 - mmengine - INFO - Epoch(train) [53][15/63] lr: 1.0515e-03 eta: 13:42:58 time: 0.5081 data_time: 0.0084 memory: 14901 loss: 2.9887 loss_prob: 1.8315 loss_thr: 0.8522 loss_db: 0.3049 2022/11/02 12:43:44 - mmengine - INFO - Epoch(train) [53][20/63] lr: 1.0515e-03 eta: 13:42:12 time: 0.5022 data_time: 0.0058 memory: 14901 loss: 2.9335 loss_prob: 1.8037 loss_thr: 0.8244 loss_db: 0.3054 2022/11/02 12:43:47 - mmengine - INFO - Epoch(train) [53][25/63] lr: 1.0515e-03 eta: 13:42:12 time: 0.4993 data_time: 0.0323 memory: 14901 loss: 2.8550 loss_prob: 1.7649 loss_thr: 0.7911 loss_db: 0.2990 2022/11/02 12:43:50 - mmengine - INFO - Epoch(train) [53][30/63] lr: 1.0515e-03 eta: 13:41:34 time: 0.5415 data_time: 0.0347 memory: 14901 loss: 2.9322 loss_prob: 1.8228 loss_thr: 0.7998 loss_db: 0.3095 2022/11/02 12:43:52 - mmengine - INFO - Epoch(train) [53][35/63] lr: 1.0515e-03 eta: 13:41:34 time: 0.5124 data_time: 0.0070 memory: 14901 loss: 3.0154 loss_prob: 1.8826 loss_thr: 0.8117 loss_db: 0.3210 2022/11/02 12:43:54 - mmengine - INFO - Epoch(train) [53][40/63] lr: 1.0515e-03 eta: 13:40:41 time: 0.4687 data_time: 0.0060 memory: 14901 loss: 3.2222 loss_prob: 2.0541 loss_thr: 0.8136 loss_db: 0.3544 2022/11/02 12:43:57 - mmengine - INFO - Epoch(train) [53][45/63] lr: 1.0515e-03 eta: 13:40:41 time: 0.4703 data_time: 0.0078 memory: 14901 loss: 3.2785 loss_prob: 2.0862 loss_thr: 0.8159 loss_db: 0.3765 2022/11/02 12:43:59 - mmengine - INFO - Epoch(train) [53][50/63] lr: 1.0515e-03 eta: 13:39:54 time: 0.4937 data_time: 0.0204 memory: 14901 loss: 3.1340 loss_prob: 1.9737 loss_thr: 0.8091 loss_db: 0.3511 2022/11/02 12:44:02 - mmengine - INFO - Epoch(train) [53][55/63] lr: 1.0515e-03 eta: 13:39:54 time: 0.4962 data_time: 0.0217 memory: 14901 loss: 3.0716 loss_prob: 1.9329 loss_thr: 0.8097 loss_db: 0.3290 2022/11/02 12:44:04 - mmengine - INFO - Epoch(train) [53][60/63] lr: 1.0515e-03 eta: 13:39:04 time: 0.4809 data_time: 0.0092 memory: 14901 loss: 3.0817 loss_prob: 1.9204 loss_thr: 0.8348 loss_db: 0.3264 2022/11/02 12:44:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:44:10 - mmengine - INFO - Epoch(train) [54][5/63] lr: 1.0716e-03 eta: 13:39:04 time: 0.7060 data_time: 0.1991 memory: 14901 loss: 3.1016 loss_prob: 1.9401 loss_thr: 0.8334 loss_db: 0.3281 2022/11/02 12:44:13 - mmengine - INFO - Epoch(train) [54][10/63] lr: 1.0716e-03 eta: 13:38:17 time: 0.7086 data_time: 0.2011 memory: 14901 loss: 3.0816 loss_prob: 1.9258 loss_thr: 0.8267 loss_db: 0.3292 2022/11/02 12:44:16 - mmengine - INFO - Epoch(train) [54][15/63] lr: 1.0716e-03 eta: 13:38:17 time: 0.5344 data_time: 0.0132 memory: 14901 loss: 2.9297 loss_prob: 1.8074 loss_thr: 0.8193 loss_db: 0.3031 2022/11/02 12:44:19 - mmengine - INFO - Epoch(train) [54][20/63] lr: 1.0716e-03 eta: 13:37:53 time: 0.5988 data_time: 0.0115 memory: 14901 loss: 2.8364 loss_prob: 1.7279 loss_thr: 0.8220 loss_db: 0.2865 2022/11/02 12:44:23 - mmengine - INFO - Epoch(train) [54][25/63] lr: 1.0716e-03 eta: 13:37:53 time: 0.7148 data_time: 0.0330 memory: 14901 loss: 2.8896 loss_prob: 1.7746 loss_thr: 0.8191 loss_db: 0.2959 2022/11/02 12:44:26 - mmengine - INFO - Epoch(train) [54][30/63] lr: 1.0716e-03 eta: 13:37:55 time: 0.7219 data_time: 0.0330 memory: 14901 loss: 2.9558 loss_prob: 1.8356 loss_thr: 0.8098 loss_db: 0.3104 2022/11/02 12:44:29 - mmengine - INFO - Epoch(train) [54][35/63] lr: 1.0716e-03 eta: 13:37:55 time: 0.5721 data_time: 0.0053 memory: 14901 loss: 2.8186 loss_prob: 1.7256 loss_thr: 0.8010 loss_db: 0.2920 2022/11/02 12:44:31 - mmengine - INFO - Epoch(train) [54][40/63] lr: 1.0716e-03 eta: 13:37:11 time: 0.5036 data_time: 0.0081 memory: 14901 loss: 2.8886 loss_prob: 1.7811 loss_thr: 0.8073 loss_db: 0.3003 2022/11/02 12:44:34 - mmengine - INFO - Epoch(train) [54][45/63] lr: 1.0716e-03 eta: 13:37:11 time: 0.5087 data_time: 0.0077 memory: 14901 loss: 2.9748 loss_prob: 1.8582 loss_thr: 0.8023 loss_db: 0.3143 2022/11/02 12:44:37 - mmengine - INFO - Epoch(train) [54][50/63] lr: 1.0716e-03 eta: 13:36:54 time: 0.6321 data_time: 0.0571 memory: 14901 loss: 2.8819 loss_prob: 1.7986 loss_thr: 0.7809 loss_db: 0.3024 2022/11/02 12:44:40 - mmengine - INFO - Epoch(train) [54][55/63] lr: 1.0716e-03 eta: 13:36:54 time: 0.6385 data_time: 0.0573 memory: 14901 loss: 2.9601 loss_prob: 1.8507 loss_thr: 0.7978 loss_db: 0.3117 2022/11/02 12:44:43 - mmengine - INFO - Epoch(train) [54][60/63] lr: 1.0716e-03 eta: 13:36:15 time: 0.5264 data_time: 0.0048 memory: 14901 loss: 3.0358 loss_prob: 1.9008 loss_thr: 0.8140 loss_db: 0.3210 2022/11/02 12:44:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:44:50 - mmengine - INFO - Epoch(train) [55][5/63] lr: 1.0918e-03 eta: 13:36:15 time: 0.8501 data_time: 0.2278 memory: 14901 loss: 3.3001 loss_prob: 2.0954 loss_thr: 0.8140 loss_db: 0.3907 2022/11/02 12:44:53 - mmengine - INFO - Epoch(train) [55][10/63] lr: 1.0918e-03 eta: 13:36:10 time: 0.9022 data_time: 0.2289 memory: 14901 loss: 3.3289 loss_prob: 2.1140 loss_thr: 0.8232 loss_db: 0.3917 2022/11/02 12:44:57 - mmengine - INFO - Epoch(train) [55][15/63] lr: 1.0918e-03 eta: 13:36:10 time: 0.7242 data_time: 0.0090 memory: 14901 loss: 3.0003 loss_prob: 1.8919 loss_thr: 0.7938 loss_db: 0.3146 2022/11/02 12:45:00 - mmengine - INFO - Epoch(train) [55][20/63] lr: 1.0918e-03 eta: 13:36:08 time: 0.7005 data_time: 0.0082 memory: 14901 loss: 2.9184 loss_prob: 1.8260 loss_thr: 0.7870 loss_db: 0.3053 2022/11/02 12:45:04 - mmengine - INFO - Epoch(train) [55][25/63] lr: 1.0918e-03 eta: 13:36:08 time: 0.6530 data_time: 0.0355 memory: 14901 loss: 3.2904 loss_prob: 2.0816 loss_thr: 0.8402 loss_db: 0.3686 2022/11/02 12:45:07 - mmengine - INFO - Epoch(train) [55][30/63] lr: 1.0918e-03 eta: 13:36:09 time: 0.7142 data_time: 0.0379 memory: 14901 loss: 3.1731 loss_prob: 1.9949 loss_thr: 0.8310 loss_db: 0.3472 2022/11/02 12:45:10 - mmengine - INFO - Epoch(train) [55][35/63] lr: 1.0918e-03 eta: 13:36:09 time: 0.6090 data_time: 0.0081 memory: 14901 loss: 2.9633 loss_prob: 1.8324 loss_thr: 0.8214 loss_db: 0.3094 2022/11/02 12:45:13 - mmengine - INFO - Epoch(train) [55][40/63] lr: 1.0918e-03 eta: 13:35:56 time: 0.6499 data_time: 0.0046 memory: 14901 loss: 3.0185 loss_prob: 1.8656 loss_thr: 0.8372 loss_db: 0.3156 2022/11/02 12:45:16 - mmengine - INFO - Epoch(train) [55][45/63] lr: 1.0918e-03 eta: 13:35:56 time: 0.6027 data_time: 0.0153 memory: 14901 loss: 2.8120 loss_prob: 1.7327 loss_thr: 0.7938 loss_db: 0.2855 2022/11/02 12:45:19 - mmengine - INFO - Epoch(train) [55][50/63] lr: 1.0918e-03 eta: 13:35:16 time: 0.5182 data_time: 0.0222 memory: 14901 loss: 2.8344 loss_prob: 1.7627 loss_thr: 0.7760 loss_db: 0.2958 2022/11/02 12:45:21 - mmengine - INFO - Epoch(train) [55][55/63] lr: 1.0918e-03 eta: 13:35:16 time: 0.5606 data_time: 0.0116 memory: 14901 loss: 2.9871 loss_prob: 1.8659 loss_thr: 0.8017 loss_db: 0.3195 2022/11/02 12:45:24 - mmengine - INFO - Epoch(train) [55][60/63] lr: 1.0918e-03 eta: 13:34:35 time: 0.5160 data_time: 0.0048 memory: 14901 loss: 2.9568 loss_prob: 1.8380 loss_thr: 0.8102 loss_db: 0.3086 2022/11/02 12:45:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:45:29 - mmengine - INFO - Epoch(train) [56][5/63] lr: 1.1120e-03 eta: 13:34:35 time: 0.6747 data_time: 0.2043 memory: 14901 loss: 2.7822 loss_prob: 1.7181 loss_thr: 0.7715 loss_db: 0.2926 2022/11/02 12:45:32 - mmengine - INFO - Epoch(train) [56][10/63] lr: 1.1120e-03 eta: 13:33:47 time: 0.6906 data_time: 0.2060 memory: 14901 loss: 2.7907 loss_prob: 1.7214 loss_thr: 0.7785 loss_db: 0.2908 2022/11/02 12:45:35 - mmengine - INFO - Epoch(train) [56][15/63] lr: 1.1120e-03 eta: 13:33:47 time: 0.5044 data_time: 0.0074 memory: 14901 loss: 2.7665 loss_prob: 1.7045 loss_thr: 0.7822 loss_db: 0.2798 2022/11/02 12:45:37 - mmengine - INFO - Epoch(train) [56][20/63] lr: 1.1120e-03 eta: 13:33:05 time: 0.5051 data_time: 0.0055 memory: 14901 loss: 2.8595 loss_prob: 1.7786 loss_thr: 0.7803 loss_db: 0.3006 2022/11/02 12:45:40 - mmengine - INFO - Epoch(train) [56][25/63] lr: 1.1120e-03 eta: 13:33:05 time: 0.5714 data_time: 0.0310 memory: 14901 loss: 2.7994 loss_prob: 1.7372 loss_thr: 0.7700 loss_db: 0.2922 2022/11/02 12:45:43 - mmengine - INFO - Epoch(train) [56][30/63] lr: 1.1120e-03 eta: 13:32:46 time: 0.6194 data_time: 0.0403 memory: 14901 loss: 2.7122 loss_prob: 1.6607 loss_thr: 0.7743 loss_db: 0.2772 2022/11/02 12:45:46 - mmengine - INFO - Epoch(train) [56][35/63] lr: 1.1120e-03 eta: 13:32:46 time: 0.5607 data_time: 0.0193 memory: 14901 loss: 2.8025 loss_prob: 1.7149 loss_thr: 0.7951 loss_db: 0.2924 2022/11/02 12:45:48 - mmengine - INFO - Epoch(train) [56][40/63] lr: 1.1120e-03 eta: 13:32:07 time: 0.5178 data_time: 0.0093 memory: 14901 loss: 2.9233 loss_prob: 1.8192 loss_thr: 0.7948 loss_db: 0.3092 2022/11/02 12:45:51 - mmengine - INFO - Epoch(train) [56][45/63] lr: 1.1120e-03 eta: 13:32:07 time: 0.5019 data_time: 0.0062 memory: 14901 loss: 2.9426 loss_prob: 1.8388 loss_thr: 0.7935 loss_db: 0.3103 2022/11/02 12:45:53 - mmengine - INFO - Epoch(train) [56][50/63] lr: 1.1120e-03 eta: 13:31:19 time: 0.4785 data_time: 0.0173 memory: 14901 loss: 2.9461 loss_prob: 1.8287 loss_thr: 0.8093 loss_db: 0.3080 2022/11/02 12:45:55 - mmengine - INFO - Epoch(train) [56][55/63] lr: 1.1120e-03 eta: 13:31:19 time: 0.4640 data_time: 0.0202 memory: 14901 loss: 2.9912 loss_prob: 1.8647 loss_thr: 0.8098 loss_db: 0.3167 2022/11/02 12:45:58 - mmengine - INFO - Epoch(train) [56][60/63] lr: 1.1120e-03 eta: 13:30:30 time: 0.4669 data_time: 0.0090 memory: 14901 loss: 2.8958 loss_prob: 1.7904 loss_thr: 0.8036 loss_db: 0.3018 2022/11/02 12:45:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:46:04 - mmengine - INFO - Epoch(train) [57][5/63] lr: 1.1322e-03 eta: 13:30:30 time: 0.6950 data_time: 0.1879 memory: 14901 loss: 2.8150 loss_prob: 1.7244 loss_thr: 0.7976 loss_db: 0.2931 2022/11/02 12:46:06 - mmengine - INFO - Epoch(train) [57][10/63] lr: 1.1322e-03 eta: 13:29:50 time: 0.7213 data_time: 0.1895 memory: 14901 loss: 2.7663 loss_prob: 1.7002 loss_thr: 0.7845 loss_db: 0.2815 2022/11/02 12:46:09 - mmengine - INFO - Epoch(train) [57][15/63] lr: 1.1322e-03 eta: 13:29:50 time: 0.4987 data_time: 0.0069 memory: 14901 loss: 2.8371 loss_prob: 1.7613 loss_thr: 0.7858 loss_db: 0.2901 2022/11/02 12:46:11 - mmengine - INFO - Epoch(train) [57][20/63] lr: 1.1322e-03 eta: 13:29:06 time: 0.4954 data_time: 0.0063 memory: 14901 loss: 2.8975 loss_prob: 1.7964 loss_thr: 0.8021 loss_db: 0.2990 2022/11/02 12:46:14 - mmengine - INFO - Epoch(train) [57][25/63] lr: 1.1322e-03 eta: 13:29:06 time: 0.5180 data_time: 0.0078 memory: 14901 loss: 3.3469 loss_prob: 2.1367 loss_thr: 0.8393 loss_db: 0.3710 2022/11/02 12:46:17 - mmengine - INFO - Epoch(train) [57][30/63] lr: 1.1322e-03 eta: 13:28:38 time: 0.5650 data_time: 0.0309 memory: 14901 loss: 3.7353 loss_prob: 2.4336 loss_thr: 0.8713 loss_db: 0.4304 2022/11/02 12:46:19 - mmengine - INFO - Epoch(train) [57][35/63] lr: 1.1322e-03 eta: 13:28:38 time: 0.5069 data_time: 0.0312 memory: 14901 loss: 3.4630 loss_prob: 2.2276 loss_thr: 0.8415 loss_db: 0.3939 2022/11/02 12:46:22 - mmengine - INFO - Epoch(train) [57][40/63] lr: 1.1322e-03 eta: 13:27:52 time: 0.4799 data_time: 0.0077 memory: 14901 loss: 3.4175 loss_prob: 2.1708 loss_thr: 0.8384 loss_db: 0.4084 2022/11/02 12:46:24 - mmengine - INFO - Epoch(train) [57][45/63] lr: 1.1322e-03 eta: 13:27:52 time: 0.4927 data_time: 0.0055 memory: 14901 loss: 3.3904 loss_prob: 2.1641 loss_thr: 0.8216 loss_db: 0.4047 2022/11/02 12:46:26 - mmengine - INFO - Epoch(train) [57][50/63] lr: 1.1322e-03 eta: 13:27:06 time: 0.4778 data_time: 0.0070 memory: 14901 loss: 3.1555 loss_prob: 2.0064 loss_thr: 0.7979 loss_db: 0.3512 2022/11/02 12:46:29 - mmengine - INFO - Epoch(train) [57][55/63] lr: 1.1322e-03 eta: 13:27:06 time: 0.4874 data_time: 0.0216 memory: 14901 loss: 3.1870 loss_prob: 2.0135 loss_thr: 0.8295 loss_db: 0.3441 2022/11/02 12:46:31 - mmengine - INFO - Epoch(train) [57][60/63] lr: 1.1322e-03 eta: 13:26:19 time: 0.4732 data_time: 0.0201 memory: 14901 loss: 3.0164 loss_prob: 1.8918 loss_thr: 0.8155 loss_db: 0.3092 2022/11/02 12:46:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:46:38 - mmengine - INFO - Epoch(train) [58][5/63] lr: 1.1524e-03 eta: 13:26:19 time: 0.7241 data_time: 0.2508 memory: 14901 loss: 3.3699 loss_prob: 2.1879 loss_thr: 0.7886 loss_db: 0.3934 2022/11/02 12:46:40 - mmengine - INFO - Epoch(train) [58][10/63] lr: 1.1524e-03 eta: 13:25:46 time: 0.7508 data_time: 0.2488 memory: 14901 loss: 4.0614 loss_prob: 2.6926 loss_thr: 0.8503 loss_db: 0.5185 2022/11/02 12:46:42 - mmengine - INFO - Epoch(train) [58][15/63] lr: 1.1524e-03 eta: 13:25:46 time: 0.4968 data_time: 0.0044 memory: 14901 loss: 4.0673 loss_prob: 2.6590 loss_thr: 0.8757 loss_db: 0.5326 2022/11/02 12:46:45 - mmengine - INFO - Epoch(train) [58][20/63] lr: 1.1524e-03 eta: 13:25:02 time: 0.4847 data_time: 0.0043 memory: 14901 loss: 3.7227 loss_prob: 2.4075 loss_thr: 0.8527 loss_db: 0.4625 2022/11/02 12:46:48 - mmengine - INFO - Epoch(train) [58][25/63] lr: 1.1524e-03 eta: 13:25:02 time: 0.5069 data_time: 0.0322 memory: 14901 loss: 3.5488 loss_prob: 2.2967 loss_thr: 0.8488 loss_db: 0.4033 2022/11/02 12:46:50 - mmengine - INFO - Epoch(train) [58][30/63] lr: 1.1524e-03 eta: 13:24:30 time: 0.5416 data_time: 0.0429 memory: 14901 loss: 3.4253 loss_prob: 2.2024 loss_thr: 0.8432 loss_db: 0.3796 2022/11/02 12:46:53 - mmengine - INFO - Epoch(train) [58][35/63] lr: 1.1524e-03 eta: 13:24:30 time: 0.4970 data_time: 0.0158 memory: 14901 loss: 3.3122 loss_prob: 2.1087 loss_thr: 0.8403 loss_db: 0.3631 2022/11/02 12:46:55 - mmengine - INFO - Epoch(train) [58][40/63] lr: 1.1524e-03 eta: 13:23:48 time: 0.4941 data_time: 0.0050 memory: 14901 loss: 3.1532 loss_prob: 1.9970 loss_thr: 0.8167 loss_db: 0.3395 2022/11/02 12:46:58 - mmengine - INFO - Epoch(train) [58][45/63] lr: 1.1524e-03 eta: 13:23:48 time: 0.5878 data_time: 0.0052 memory: 14901 loss: 3.1479 loss_prob: 1.9881 loss_thr: 0.8122 loss_db: 0.3476 2022/11/02 12:47:01 - mmengine - INFO - Epoch(train) [58][50/63] lr: 1.1524e-03 eta: 13:23:29 time: 0.6108 data_time: 0.0216 memory: 14901 loss: 3.3050 loss_prob: 2.1071 loss_thr: 0.8365 loss_db: 0.3614 2022/11/02 12:47:04 - mmengine - INFO - Epoch(train) [58][55/63] lr: 1.1524e-03 eta: 13:23:29 time: 0.5810 data_time: 0.0230 memory: 14901 loss: 3.3071 loss_prob: 2.1135 loss_thr: 0.8281 loss_db: 0.3654 2022/11/02 12:47:07 - mmengine - INFO - Epoch(train) [58][60/63] lr: 1.1524e-03 eta: 13:22:59 time: 0.5487 data_time: 0.0067 memory: 14901 loss: 3.2692 loss_prob: 2.0752 loss_thr: 0.8271 loss_db: 0.3669 2022/11/02 12:47:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:47:14 - mmengine - INFO - Epoch(train) [59][5/63] lr: 1.1725e-03 eta: 13:22:59 time: 0.8208 data_time: 0.2426 memory: 14901 loss: 3.3072 loss_prob: 2.0971 loss_thr: 0.8360 loss_db: 0.3741 2022/11/02 12:47:17 - mmengine - INFO - Epoch(train) [59][10/63] lr: 1.1725e-03 eta: 13:22:55 time: 0.8965 data_time: 0.2404 memory: 14901 loss: 3.2032 loss_prob: 2.0230 loss_thr: 0.8262 loss_db: 0.3539 2022/11/02 12:47:20 - mmengine - INFO - Epoch(train) [59][15/63] lr: 1.1725e-03 eta: 13:22:55 time: 0.5627 data_time: 0.0049 memory: 14901 loss: 3.0334 loss_prob: 1.9035 loss_thr: 0.8042 loss_db: 0.3257 2022/11/02 12:47:22 - mmengine - INFO - Epoch(train) [59][20/63] lr: 1.1725e-03 eta: 13:22:25 time: 0.5477 data_time: 0.0047 memory: 14901 loss: 3.1089 loss_prob: 1.9558 loss_thr: 0.8160 loss_db: 0.3371 2022/11/02 12:47:25 - mmengine - INFO - Epoch(train) [59][25/63] lr: 1.1725e-03 eta: 13:22:25 time: 0.5486 data_time: 0.0057 memory: 14901 loss: 2.8442 loss_prob: 1.7699 loss_thr: 0.7779 loss_db: 0.2965 2022/11/02 12:47:28 - mmengine - INFO - Epoch(train) [59][30/63] lr: 1.1725e-03 eta: 13:21:54 time: 0.5464 data_time: 0.0214 memory: 14901 loss: 2.7108 loss_prob: 1.6637 loss_thr: 0.7741 loss_db: 0.2730 2022/11/02 12:47:31 - mmengine - INFO - Epoch(train) [59][35/63] lr: 1.1725e-03 eta: 13:21:54 time: 0.5815 data_time: 0.0217 memory: 14901 loss: 2.7803 loss_prob: 1.7040 loss_thr: 0.7955 loss_db: 0.2808 2022/11/02 12:47:35 - mmengine - INFO - Epoch(train) [59][40/63] lr: 1.1725e-03 eta: 13:21:59 time: 0.7273 data_time: 0.0098 memory: 14901 loss: 2.7361 loss_prob: 1.6592 loss_thr: 0.8040 loss_db: 0.2729 2022/11/02 12:47:39 - mmengine - INFO - Epoch(train) [59][45/63] lr: 1.1725e-03 eta: 13:21:59 time: 0.7636 data_time: 0.0087 memory: 14901 loss: 2.6245 loss_prob: 1.5871 loss_thr: 0.7797 loss_db: 0.2577 2022/11/02 12:47:41 - mmengine - INFO - Epoch(train) [59][50/63] lr: 1.1725e-03 eta: 13:21:33 time: 0.5715 data_time: 0.0061 memory: 14901 loss: 2.7059 loss_prob: 1.6556 loss_thr: 0.7780 loss_db: 0.2723 2022/11/02 12:47:44 - mmengine - INFO - Epoch(train) [59][55/63] lr: 1.1725e-03 eta: 13:21:33 time: 0.5243 data_time: 0.0225 memory: 14901 loss: 2.8048 loss_prob: 1.7141 loss_thr: 0.8037 loss_db: 0.2870 2022/11/02 12:47:47 - mmengine - INFO - Epoch(train) [59][60/63] lr: 1.1725e-03 eta: 13:21:11 time: 0.5895 data_time: 0.0211 memory: 14901 loss: 3.1072 loss_prob: 1.9392 loss_thr: 0.8306 loss_db: 0.3374 2022/11/02 12:47:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:47:54 - mmengine - INFO - Epoch(train) [60][5/63] lr: 1.1927e-03 eta: 13:21:11 time: 0.7857 data_time: 0.2265 memory: 14901 loss: 3.0274 loss_prob: 1.8998 loss_thr: 0.8050 loss_db: 0.3225 2022/11/02 12:47:56 - mmengine - INFO - Epoch(train) [60][10/63] lr: 1.1927e-03 eta: 13:20:50 time: 0.8074 data_time: 0.2266 memory: 14901 loss: 2.8817 loss_prob: 1.7731 loss_thr: 0.8114 loss_db: 0.2973 2022/11/02 12:47:59 - mmengine - INFO - Epoch(train) [60][15/63] lr: 1.1927e-03 eta: 13:20:50 time: 0.4939 data_time: 0.0068 memory: 14901 loss: 2.8083 loss_prob: 1.7174 loss_thr: 0.8083 loss_db: 0.2826 2022/11/02 12:48:01 - mmengine - INFO - Epoch(train) [60][20/63] lr: 1.1927e-03 eta: 13:20:09 time: 0.4869 data_time: 0.0066 memory: 14901 loss: 2.7558 loss_prob: 1.6959 loss_thr: 0.7790 loss_db: 0.2809 2022/11/02 12:48:04 - mmengine - INFO - Epoch(train) [60][25/63] lr: 1.1927e-03 eta: 13:20:09 time: 0.5073 data_time: 0.0245 memory: 14901 loss: 2.6334 loss_prob: 1.6086 loss_thr: 0.7619 loss_db: 0.2629 2022/11/02 12:48:06 - mmengine - INFO - Epoch(train) [60][30/63] lr: 1.1927e-03 eta: 13:19:32 time: 0.5094 data_time: 0.0351 memory: 14901 loss: 2.6366 loss_prob: 1.6078 loss_thr: 0.7673 loss_db: 0.2616 2022/11/02 12:48:09 - mmengine - INFO - Epoch(train) [60][35/63] lr: 1.1927e-03 eta: 13:19:32 time: 0.4963 data_time: 0.0152 memory: 14901 loss: 2.7521 loss_prob: 1.6891 loss_thr: 0.7809 loss_db: 0.2821 2022/11/02 12:48:12 - mmengine - INFO - Epoch(train) [60][40/63] lr: 1.1927e-03 eta: 13:19:09 time: 0.5828 data_time: 0.0057 memory: 14901 loss: 2.8542 loss_prob: 1.7666 loss_thr: 0.7907 loss_db: 0.2969 2022/11/02 12:48:14 - mmengine - INFO - Epoch(train) [60][45/63] lr: 1.1927e-03 eta: 13:19:09 time: 0.5867 data_time: 0.0063 memory: 14901 loss: 2.9270 loss_prob: 1.8156 loss_thr: 0.8065 loss_db: 0.3050 2022/11/02 12:48:17 - mmengine - INFO - Epoch(train) [60][50/63] lr: 1.1927e-03 eta: 13:18:30 time: 0.4991 data_time: 0.0192 memory: 14901 loss: 2.7514 loss_prob: 1.6718 loss_thr: 0.8031 loss_db: 0.2765 2022/11/02 12:48:20 - mmengine - INFO - Epoch(train) [60][55/63] lr: 1.1927e-03 eta: 13:18:30 time: 0.5183 data_time: 0.0236 memory: 14901 loss: 2.7866 loss_prob: 1.6995 loss_thr: 0.8019 loss_db: 0.2852 2022/11/02 12:48:22 - mmengine - INFO - Epoch(train) [60][60/63] lr: 1.1927e-03 eta: 13:17:55 time: 0.5167 data_time: 0.0098 memory: 14901 loss: 2.8892 loss_prob: 1.7796 loss_thr: 0.8088 loss_db: 0.3008 2022/11/02 12:48:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:48:23 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/11/02 12:48:27 - mmengine - INFO - Epoch(val) [60][5/500] eta: 13:17:55 time: 0.0630 data_time: 0.0052 memory: 14901 2022/11/02 12:48:27 - mmengine - INFO - Epoch(val) [60][10/500] eta: 0:00:21 time: 0.0445 data_time: 0.0046 memory: 1008 2022/11/02 12:48:27 - mmengine - INFO - Epoch(val) [60][15/500] eta: 0:00:21 time: 0.0389 data_time: 0.0024 memory: 1008 2022/11/02 12:48:27 - mmengine - INFO - Epoch(val) [60][20/500] eta: 0:00:17 time: 0.0364 data_time: 0.0021 memory: 1008 2022/11/02 12:48:27 - mmengine - INFO - Epoch(val) [60][25/500] eta: 0:00:17 time: 0.0360 data_time: 0.0022 memory: 1008 2022/11/02 12:48:28 - mmengine - INFO - Epoch(val) [60][30/500] eta: 0:00:18 time: 0.0393 data_time: 0.0023 memory: 1008 2022/11/02 12:48:28 - mmengine - INFO - Epoch(val) [60][35/500] eta: 0:00:18 time: 0.0405 data_time: 0.0023 memory: 1008 2022/11/02 12:48:28 - mmengine - INFO - Epoch(val) [60][40/500] eta: 0:00:19 time: 0.0432 data_time: 0.0024 memory: 1008 2022/11/02 12:48:28 - mmengine - INFO - Epoch(val) [60][45/500] eta: 0:00:19 time: 0.0506 data_time: 0.0025 memory: 1008 2022/11/02 12:48:29 - mmengine - INFO - Epoch(val) [60][50/500] eta: 0:00:21 time: 0.0487 data_time: 0.0025 memory: 1008 2022/11/02 12:48:29 - mmengine - INFO - Epoch(val) [60][55/500] eta: 0:00:21 time: 0.0405 data_time: 0.0023 memory: 1008 2022/11/02 12:48:29 - mmengine - INFO - Epoch(val) [60][60/500] eta: 0:00:16 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 12:48:29 - mmengine - INFO - Epoch(val) [60][65/500] eta: 0:00:16 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/02 12:48:29 - mmengine - INFO - Epoch(val) [60][70/500] eta: 0:00:17 time: 0.0407 data_time: 0.0023 memory: 1008 2022/11/02 12:48:30 - mmengine - INFO - Epoch(val) [60][75/500] eta: 0:00:17 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 12:48:30 - mmengine - INFO - Epoch(val) [60][80/500] eta: 0:00:15 time: 0.0371 data_time: 0.0026 memory: 1008 2022/11/02 12:48:30 - mmengine - INFO - Epoch(val) [60][85/500] eta: 0:00:15 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/02 12:48:30 - mmengine - INFO - Epoch(val) [60][90/500] eta: 0:00:16 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 12:48:30 - mmengine - INFO - Epoch(val) [60][95/500] eta: 0:00:16 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/02 12:48:30 - mmengine - INFO - Epoch(val) [60][100/500] eta: 0:00:15 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 12:48:31 - mmengine - INFO - Epoch(val) [60][105/500] eta: 0:00:15 time: 0.0389 data_time: 0.0030 memory: 1008 2022/11/02 12:48:31 - mmengine - INFO - Epoch(val) [60][110/500] eta: 0:00:15 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 12:48:31 - mmengine - INFO - Epoch(val) [60][115/500] eta: 0:00:15 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 12:48:31 - mmengine - INFO - Epoch(val) [60][120/500] eta: 0:00:15 time: 0.0404 data_time: 0.0024 memory: 1008 2022/11/02 12:48:32 - mmengine - INFO - Epoch(val) [60][125/500] eta: 0:00:15 time: 0.0410 data_time: 0.0025 memory: 1008 2022/11/02 12:48:32 - mmengine - INFO - Epoch(val) [60][130/500] eta: 0:00:14 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/02 12:48:32 - mmengine - INFO - Epoch(val) [60][135/500] eta: 0:00:14 time: 0.0363 data_time: 0.0022 memory: 1008 2022/11/02 12:48:32 - mmengine - INFO - Epoch(val) [60][140/500] eta: 0:00:13 time: 0.0382 data_time: 0.0023 memory: 1008 2022/11/02 12:48:32 - mmengine - INFO - Epoch(val) [60][145/500] eta: 0:00:13 time: 0.0396 data_time: 0.0023 memory: 1008 2022/11/02 12:48:32 - mmengine - INFO - Epoch(val) [60][150/500] eta: 0:00:14 time: 0.0403 data_time: 0.0024 memory: 1008 2022/11/02 12:48:33 - mmengine - INFO - Epoch(val) [60][155/500] eta: 0:00:14 time: 0.0421 data_time: 0.0025 memory: 1008 2022/11/02 12:48:33 - mmengine - INFO - Epoch(val) [60][160/500] eta: 0:00:14 time: 0.0430 data_time: 0.0024 memory: 1008 2022/11/02 12:48:33 - mmengine - INFO - Epoch(val) [60][165/500] eta: 0:00:14 time: 0.0414 data_time: 0.0023 memory: 1008 2022/11/02 12:48:33 - mmengine - INFO - Epoch(val) [60][170/500] eta: 0:00:13 time: 0.0411 data_time: 0.0023 memory: 1008 2022/11/02 12:48:34 - mmengine - INFO - Epoch(val) [60][175/500] eta: 0:00:13 time: 0.0407 data_time: 0.0023 memory: 1008 2022/11/02 12:48:34 - mmengine - INFO - Epoch(val) [60][180/500] eta: 0:00:12 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/02 12:48:34 - mmengine - INFO - Epoch(val) [60][185/500] eta: 0:00:12 time: 0.0400 data_time: 0.0024 memory: 1008 2022/11/02 12:48:34 - mmengine - INFO - Epoch(val) [60][190/500] eta: 0:00:13 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 12:48:34 - mmengine - INFO - Epoch(val) [60][195/500] eta: 0:00:13 time: 0.0385 data_time: 0.0023 memory: 1008 2022/11/02 12:48:35 - mmengine - INFO - Epoch(val) [60][200/500] eta: 0:00:12 time: 0.0426 data_time: 0.0024 memory: 1008 2022/11/02 12:48:35 - mmengine - INFO - Epoch(val) [60][205/500] eta: 0:00:12 time: 0.0430 data_time: 0.0024 memory: 1008 2022/11/02 12:48:35 - mmengine - INFO - Epoch(val) [60][210/500] eta: 0:00:10 time: 0.0363 data_time: 0.0024 memory: 1008 2022/11/02 12:48:35 - mmengine - INFO - Epoch(val) [60][215/500] eta: 0:00:10 time: 0.0381 data_time: 0.0024 memory: 1008 2022/11/02 12:48:35 - mmengine - INFO - Epoch(val) [60][220/500] eta: 0:00:10 time: 0.0377 data_time: 0.0022 memory: 1008 2022/11/02 12:48:36 - mmengine - INFO - Epoch(val) [60][225/500] eta: 0:00:10 time: 0.0412 data_time: 0.0023 memory: 1008 2022/11/02 12:48:36 - mmengine - INFO - Epoch(val) [60][230/500] eta: 0:00:10 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/02 12:48:36 - mmengine - INFO - Epoch(val) [60][235/500] eta: 0:00:10 time: 0.0355 data_time: 0.0022 memory: 1008 2022/11/02 12:48:36 - mmengine - INFO - Epoch(val) [60][240/500] eta: 0:00:10 time: 0.0394 data_time: 0.0022 memory: 1008 2022/11/02 12:48:36 - mmengine - INFO - Epoch(val) [60][245/500] eta: 0:00:10 time: 0.0372 data_time: 0.0022 memory: 1008 2022/11/02 12:48:36 - mmengine - INFO - Epoch(val) [60][250/500] eta: 0:00:09 time: 0.0362 data_time: 0.0020 memory: 1008 2022/11/02 12:48:37 - mmengine - INFO - Epoch(val) [60][255/500] eta: 0:00:09 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/02 12:48:37 - mmengine - INFO - Epoch(val) [60][260/500] eta: 0:00:08 time: 0.0368 data_time: 0.0023 memory: 1008 2022/11/02 12:48:37 - mmengine - INFO - Epoch(val) [60][265/500] eta: 0:00:08 time: 0.0357 data_time: 0.0023 memory: 1008 2022/11/02 12:48:37 - mmengine - INFO - Epoch(val) [60][270/500] eta: 0:00:10 time: 0.0448 data_time: 0.0070 memory: 1008 2022/11/02 12:48:37 - mmengine - INFO - Epoch(val) [60][275/500] eta: 0:00:10 time: 0.0432 data_time: 0.0066 memory: 1008 2022/11/02 12:48:38 - mmengine - INFO - Epoch(val) [60][280/500] eta: 0:00:09 time: 0.0420 data_time: 0.0024 memory: 1008 2022/11/02 12:48:38 - mmengine - INFO - Epoch(val) [60][285/500] eta: 0:00:09 time: 0.0433 data_time: 0.0026 memory: 1008 2022/11/02 12:48:38 - mmengine - INFO - Epoch(val) [60][290/500] eta: 0:00:08 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 12:48:38 - mmengine - INFO - Epoch(val) [60][295/500] eta: 0:00:08 time: 0.0428 data_time: 0.0027 memory: 1008 2022/11/02 12:48:38 - mmengine - INFO - Epoch(val) [60][300/500] eta: 0:00:07 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 12:48:39 - mmengine - INFO - Epoch(val) [60][305/500] eta: 0:00:07 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/02 12:48:39 - mmengine - INFO - Epoch(val) [60][310/500] eta: 0:00:07 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/02 12:48:39 - mmengine - INFO - Epoch(val) [60][315/500] eta: 0:00:07 time: 0.0416 data_time: 0.0023 memory: 1008 2022/11/02 12:48:39 - mmengine - INFO - Epoch(val) [60][320/500] eta: 0:00:07 time: 0.0414 data_time: 0.0024 memory: 1008 2022/11/02 12:48:40 - mmengine - INFO - Epoch(val) [60][325/500] eta: 0:00:07 time: 0.0511 data_time: 0.0025 memory: 1008 2022/11/02 12:48:40 - mmengine - INFO - Epoch(val) [60][330/500] eta: 0:00:08 time: 0.0492 data_time: 0.0023 memory: 1008 2022/11/02 12:48:40 - mmengine - INFO - Epoch(val) [60][335/500] eta: 0:00:08 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/02 12:48:40 - mmengine - INFO - Epoch(val) [60][340/500] eta: 0:00:08 time: 0.0518 data_time: 0.0025 memory: 1008 2022/11/02 12:48:40 - mmengine - INFO - Epoch(val) [60][345/500] eta: 0:00:08 time: 0.0522 data_time: 0.0024 memory: 1008 2022/11/02 12:48:41 - mmengine - INFO - Epoch(val) [60][350/500] eta: 0:00:06 time: 0.0432 data_time: 0.0023 memory: 1008 2022/11/02 12:48:41 - mmengine - INFO - Epoch(val) [60][355/500] eta: 0:00:06 time: 0.0425 data_time: 0.0023 memory: 1008 2022/11/02 12:48:41 - mmengine - INFO - Epoch(val) [60][360/500] eta: 0:00:05 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 12:48:41 - mmengine - INFO - Epoch(val) [60][365/500] eta: 0:00:05 time: 0.0446 data_time: 0.0029 memory: 1008 2022/11/02 12:48:42 - mmengine - INFO - Epoch(val) [60][370/500] eta: 0:00:05 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 12:48:42 - mmengine - INFO - Epoch(val) [60][375/500] eta: 0:00:05 time: 0.0356 data_time: 0.0023 memory: 1008 2022/11/02 12:48:42 - mmengine - INFO - Epoch(val) [60][380/500] eta: 0:00:04 time: 0.0401 data_time: 0.0025 memory: 1008 2022/11/02 12:48:42 - mmengine - INFO - Epoch(val) [60][385/500] eta: 0:00:04 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 12:48:42 - mmengine - INFO - Epoch(val) [60][390/500] eta: 0:00:04 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/02 12:48:43 - mmengine - INFO - Epoch(val) [60][395/500] eta: 0:00:04 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/02 12:48:43 - mmengine - INFO - Epoch(val) [60][400/500] eta: 0:00:03 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/02 12:48:43 - mmengine - INFO - Epoch(val) [60][405/500] eta: 0:00:03 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 12:48:43 - mmengine - INFO - Epoch(val) [60][410/500] eta: 0:00:03 time: 0.0414 data_time: 0.0025 memory: 1008 2022/11/02 12:48:43 - mmengine - INFO - Epoch(val) [60][415/500] eta: 0:00:03 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/02 12:48:44 - mmengine - INFO - Epoch(val) [60][420/500] eta: 0:00:07 time: 0.0955 data_time: 0.0608 memory: 1008 2022/11/02 12:48:44 - mmengine - INFO - Epoch(val) [60][425/500] eta: 0:00:07 time: 0.0974 data_time: 0.0605 memory: 1008 2022/11/02 12:48:44 - mmengine - INFO - Epoch(val) [60][430/500] eta: 0:00:02 time: 0.0403 data_time: 0.0023 memory: 1008 2022/11/02 12:48:45 - mmengine - INFO - Epoch(val) [60][435/500] eta: 0:00:02 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/02 12:48:45 - mmengine - INFO - Epoch(val) [60][440/500] eta: 0:00:02 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 12:48:45 - mmengine - INFO - Epoch(val) [60][445/500] eta: 0:00:02 time: 0.0452 data_time: 0.0029 memory: 1008 2022/11/02 12:48:45 - mmengine - INFO - Epoch(val) [60][450/500] eta: 0:00:02 time: 0.0477 data_time: 0.0030 memory: 1008 2022/11/02 12:48:46 - mmengine - INFO - Epoch(val) [60][455/500] eta: 0:00:02 time: 0.0452 data_time: 0.0028 memory: 1008 2022/11/02 12:48:46 - mmengine - INFO - Epoch(val) [60][460/500] eta: 0:00:01 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/02 12:48:46 - mmengine - INFO - Epoch(val) [60][465/500] eta: 0:00:01 time: 0.0400 data_time: 0.0028 memory: 1008 2022/11/02 12:48:46 - mmengine - INFO - Epoch(val) [60][470/500] eta: 0:00:01 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 12:48:46 - mmengine - INFO - Epoch(val) [60][475/500] eta: 0:00:01 time: 0.0375 data_time: 0.0029 memory: 1008 2022/11/02 12:48:47 - mmengine - INFO - Epoch(val) [60][480/500] eta: 0:00:00 time: 0.0374 data_time: 0.0031 memory: 1008 2022/11/02 12:48:47 - mmengine - INFO - Epoch(val) [60][485/500] eta: 0:00:00 time: 0.0388 data_time: 0.0028 memory: 1008 2022/11/02 12:48:47 - mmengine - INFO - Epoch(val) [60][490/500] eta: 0:00:00 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 12:48:47 - mmengine - INFO - Epoch(val) [60][495/500] eta: 0:00:00 time: 0.0421 data_time: 0.0024 memory: 1008 2022/11/02 12:48:47 - mmengine - INFO - Epoch(val) [60][500/500] eta: 0:00:00 time: 0.0421 data_time: 0.0027 memory: 1008 2022/11/02 12:48:47 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.6601, precision: 0.5316, hmean: 0.5889 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.6596, precision: 0.6524, hmean: 0.6560 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.6442, precision: 0.7598, hmean: 0.6972 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.5494, precision: 0.8483, hmean: 0.6669 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.2287, precision: 0.9170, hmean: 0.3661 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0014, precision: 0.7500, hmean: 0.0029 2022/11/02 12:48:47 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 12:48:47 - mmengine - INFO - Epoch(val) [60][500/500] icdar/precision: 0.7598 icdar/recall: 0.6442 icdar/hmean: 0.6972 2022/11/02 12:48:52 - mmengine - INFO - Epoch(train) [61][5/63] lr: 1.2129e-03 eta: 0:00:00 time: 0.6782 data_time: 0.2188 memory: 14901 loss: 2.8272 loss_prob: 1.7379 loss_thr: 0.7943 loss_db: 0.2950 2022/11/02 12:48:55 - mmengine - INFO - Epoch(train) [61][10/63] lr: 1.2129e-03 eta: 13:17:20 time: 0.7280 data_time: 0.2191 memory: 14901 loss: 3.1072 loss_prob: 1.9454 loss_thr: 0.8257 loss_db: 0.3360 2022/11/02 12:48:58 - mmengine - INFO - Epoch(train) [61][15/63] lr: 1.2129e-03 eta: 13:17:20 time: 0.5348 data_time: 0.0359 memory: 14901 loss: 3.2231 loss_prob: 2.0395 loss_thr: 0.8233 loss_db: 0.3603 2022/11/02 12:49:00 - mmengine - INFO - Epoch(train) [61][20/63] lr: 1.2129e-03 eta: 13:16:47 time: 0.5257 data_time: 0.0360 memory: 14901 loss: 2.9006 loss_prob: 1.8028 loss_thr: 0.7886 loss_db: 0.3091 2022/11/02 12:49:03 - mmengine - INFO - Epoch(train) [61][25/63] lr: 1.2129e-03 eta: 13:16:47 time: 0.5108 data_time: 0.0049 memory: 14901 loss: 2.8166 loss_prob: 1.7338 loss_thr: 0.7969 loss_db: 0.2860 2022/11/02 12:49:05 - mmengine - INFO - Epoch(train) [61][30/63] lr: 1.2129e-03 eta: 13:16:11 time: 0.5133 data_time: 0.0238 memory: 14901 loss: 2.9106 loss_prob: 1.7934 loss_thr: 0.8116 loss_db: 0.3055 2022/11/02 12:49:08 - mmengine - INFO - Epoch(train) [61][35/63] lr: 1.2129e-03 eta: 13:16:11 time: 0.4926 data_time: 0.0237 memory: 14901 loss: 2.8702 loss_prob: 1.7778 loss_thr: 0.7931 loss_db: 0.2993 2022/11/02 12:49:10 - mmengine - INFO - Epoch(train) [61][40/63] lr: 1.2129e-03 eta: 13:15:38 time: 0.5223 data_time: 0.0232 memory: 14901 loss: 2.9024 loss_prob: 1.8147 loss_thr: 0.7821 loss_db: 0.3055 2022/11/02 12:49:13 - mmengine - INFO - Epoch(train) [61][45/63] lr: 1.2129e-03 eta: 13:15:38 time: 0.5227 data_time: 0.0231 memory: 14901 loss: 2.9737 loss_prob: 1.8721 loss_thr: 0.7855 loss_db: 0.3161 2022/11/02 12:49:15 - mmengine - INFO - Epoch(train) [61][50/63] lr: 1.2129e-03 eta: 13:15:01 time: 0.5028 data_time: 0.0044 memory: 14901 loss: 2.8896 loss_prob: 1.8143 loss_thr: 0.7745 loss_db: 0.3008 2022/11/02 12:49:18 - mmengine - INFO - Epoch(train) [61][55/63] lr: 1.2129e-03 eta: 13:15:01 time: 0.5001 data_time: 0.0073 memory: 14901 loss: 2.7960 loss_prob: 1.7393 loss_thr: 0.7704 loss_db: 0.2863 2022/11/02 12:49:20 - mmengine - INFO - Epoch(train) [61][60/63] lr: 1.2129e-03 eta: 13:14:20 time: 0.4832 data_time: 0.0072 memory: 14901 loss: 2.9508 loss_prob: 1.8467 loss_thr: 0.7863 loss_db: 0.3179 2022/11/02 12:49:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:49:27 - mmengine - INFO - Epoch(train) [62][5/63] lr: 1.2331e-03 eta: 13:14:20 time: 0.7476 data_time: 0.2383 memory: 14901 loss: 2.8626 loss_prob: 1.7727 loss_thr: 0.7853 loss_db: 0.3045 2022/11/02 12:49:30 - mmengine - INFO - Epoch(train) [62][10/63] lr: 1.2331e-03 eta: 13:14:03 time: 0.8203 data_time: 0.2379 memory: 14901 loss: 2.6601 loss_prob: 1.6249 loss_thr: 0.7685 loss_db: 0.2667 2022/11/02 12:49:32 - mmengine - INFO - Epoch(train) [62][15/63] lr: 1.2331e-03 eta: 13:14:03 time: 0.5346 data_time: 0.0095 memory: 14901 loss: 2.7955 loss_prob: 1.7307 loss_thr: 0.7714 loss_db: 0.2934 2022/11/02 12:49:34 - mmengine - INFO - Epoch(train) [62][20/63] lr: 1.2331e-03 eta: 13:13:21 time: 0.4693 data_time: 0.0068 memory: 14901 loss: 2.8120 loss_prob: 1.7278 loss_thr: 0.7927 loss_db: 0.2915 2022/11/02 12:49:37 - mmengine - INFO - Epoch(train) [62][25/63] lr: 1.2331e-03 eta: 13:13:21 time: 0.5291 data_time: 0.0120 memory: 14901 loss: 2.7707 loss_prob: 1.7061 loss_thr: 0.7843 loss_db: 0.2803 2022/11/02 12:49:40 - mmengine - INFO - Epoch(train) [62][30/63] lr: 1.2331e-03 eta: 13:12:58 time: 0.5771 data_time: 0.0353 memory: 14901 loss: 2.7477 loss_prob: 1.7001 loss_thr: 0.7658 loss_db: 0.2818 2022/11/02 12:49:44 - mmengine - INFO - Epoch(train) [62][35/63] lr: 1.2331e-03 eta: 13:12:58 time: 0.6335 data_time: 0.0285 memory: 14901 loss: 2.7006 loss_prob: 1.6572 loss_thr: 0.7670 loss_db: 0.2764 2022/11/02 12:49:47 - mmengine - INFO - Epoch(train) [62][40/63] lr: 1.2331e-03 eta: 13:12:48 time: 0.6445 data_time: 0.0098 memory: 14901 loss: 2.8112 loss_prob: 1.7367 loss_thr: 0.7830 loss_db: 0.2915 2022/11/02 12:49:49 - mmengine - INFO - Epoch(train) [62][45/63] lr: 1.2331e-03 eta: 13:12:48 time: 0.5601 data_time: 0.0091 memory: 14901 loss: 2.9143 loss_prob: 1.8139 loss_thr: 0.7936 loss_db: 0.3069 2022/11/02 12:49:52 - mmengine - INFO - Epoch(train) [62][50/63] lr: 1.2331e-03 eta: 13:12:16 time: 0.5272 data_time: 0.0156 memory: 14901 loss: 2.9711 loss_prob: 1.8522 loss_thr: 0.8050 loss_db: 0.3140 2022/11/02 12:49:55 - mmengine - INFO - Epoch(train) [62][55/63] lr: 1.2331e-03 eta: 13:12:16 time: 0.5428 data_time: 0.0235 memory: 14901 loss: 2.8856 loss_prob: 1.7890 loss_thr: 0.7939 loss_db: 0.3027 2022/11/02 12:49:58 - mmengine - INFO - Epoch(train) [62][60/63] lr: 1.2331e-03 eta: 13:11:55 time: 0.5862 data_time: 0.0130 memory: 14901 loss: 2.9942 loss_prob: 1.8961 loss_thr: 0.7747 loss_db: 0.3233 2022/11/02 12:49:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:50:06 - mmengine - INFO - Epoch(train) [63][5/63] lr: 1.2533e-03 eta: 13:11:55 time: 0.9228 data_time: 0.2180 memory: 14901 loss: 3.3712 loss_prob: 2.1828 loss_thr: 0.8080 loss_db: 0.3804 2022/11/02 12:50:09 - mmengine - INFO - Epoch(train) [63][10/63] lr: 1.2533e-03 eta: 13:12:07 time: 0.9709 data_time: 0.2175 memory: 14901 loss: 3.1882 loss_prob: 2.0296 loss_thr: 0.8023 loss_db: 0.3563 2022/11/02 12:50:12 - mmengine - INFO - Epoch(train) [63][15/63] lr: 1.2533e-03 eta: 13:12:07 time: 0.6166 data_time: 0.0060 memory: 14901 loss: 2.9453 loss_prob: 1.8502 loss_thr: 0.7810 loss_db: 0.3141 2022/11/02 12:50:14 - mmengine - INFO - Epoch(train) [63][20/63] lr: 1.2533e-03 eta: 13:11:37 time: 0.5345 data_time: 0.0055 memory: 14901 loss: 2.9539 loss_prob: 1.8513 loss_thr: 0.7939 loss_db: 0.3087 2022/11/02 12:50:19 - mmengine - INFO - Epoch(train) [63][25/63] lr: 1.2533e-03 eta: 13:11:37 time: 0.6945 data_time: 0.0328 memory: 14901 loss: 3.1915 loss_prob: 2.0117 loss_thr: 0.8228 loss_db: 0.3569 2022/11/02 12:50:23 - mmengine - INFO - Epoch(train) [63][30/63] lr: 1.2533e-03 eta: 13:12:00 time: 0.8260 data_time: 0.0399 memory: 14901 loss: 3.1786 loss_prob: 1.9992 loss_thr: 0.8205 loss_db: 0.3589 2022/11/02 12:50:26 - mmengine - INFO - Epoch(train) [63][35/63] lr: 1.2533e-03 eta: 13:12:00 time: 0.7051 data_time: 0.0117 memory: 14901 loss: 2.8580 loss_prob: 1.7614 loss_thr: 0.8017 loss_db: 0.2949 2022/11/02 12:50:28 - mmengine - INFO - Epoch(train) [63][40/63] lr: 1.2533e-03 eta: 13:11:40 time: 0.5885 data_time: 0.0081 memory: 14901 loss: 3.2246 loss_prob: 2.0092 loss_thr: 0.8577 loss_db: 0.3577 2022/11/02 12:50:31 - mmengine - INFO - Epoch(train) [63][45/63] lr: 1.2533e-03 eta: 13:11:40 time: 0.5024 data_time: 0.0080 memory: 14901 loss: 3.2135 loss_prob: 2.0130 loss_thr: 0.8393 loss_db: 0.3613 2022/11/02 12:50:34 - mmengine - INFO - Epoch(train) [63][50/63] lr: 1.2533e-03 eta: 13:11:18 time: 0.5831 data_time: 0.0195 memory: 14901 loss: 2.9621 loss_prob: 1.8488 loss_thr: 0.7954 loss_db: 0.3179 2022/11/02 12:50:37 - mmengine - INFO - Epoch(train) [63][55/63] lr: 1.2533e-03 eta: 13:11:18 time: 0.6292 data_time: 0.0245 memory: 14901 loss: 3.0890 loss_prob: 1.9547 loss_thr: 0.8012 loss_db: 0.3331 2022/11/02 12:50:40 - mmengine - INFO - Epoch(train) [63][60/63] lr: 1.2533e-03 eta: 13:10:51 time: 0.5459 data_time: 0.0093 memory: 14901 loss: 2.9113 loss_prob: 1.8278 loss_thr: 0.7855 loss_db: 0.2980 2022/11/02 12:50:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:50:46 - mmengine - INFO - Epoch(train) [64][5/63] lr: 1.2735e-03 eta: 13:10:51 time: 0.6945 data_time: 0.1889 memory: 14901 loss: 2.7394 loss_prob: 1.6563 loss_thr: 0.8103 loss_db: 0.2728 2022/11/02 12:50:48 - mmengine - INFO - Epoch(train) [64][10/63] lr: 1.2735e-03 eta: 13:10:18 time: 0.7261 data_time: 0.1986 memory: 14901 loss: 2.6335 loss_prob: 1.5811 loss_thr: 0.7901 loss_db: 0.2623 2022/11/02 12:50:51 - mmengine - INFO - Epoch(train) [64][15/63] lr: 1.2735e-03 eta: 13:10:18 time: 0.4737 data_time: 0.0162 memory: 14901 loss: 2.7832 loss_prob: 1.6957 loss_thr: 0.7989 loss_db: 0.2886 2022/11/02 12:50:53 - mmengine - INFO - Epoch(train) [64][20/63] lr: 1.2735e-03 eta: 13:09:36 time: 0.4671 data_time: 0.0064 memory: 14901 loss: 2.7350 loss_prob: 1.6752 loss_thr: 0.7781 loss_db: 0.2817 2022/11/02 12:50:55 - mmengine - INFO - Epoch(train) [64][25/63] lr: 1.2735e-03 eta: 13:09:36 time: 0.4863 data_time: 0.0209 memory: 14901 loss: 2.8626 loss_prob: 1.7987 loss_thr: 0.7631 loss_db: 0.3008 2022/11/02 12:50:58 - mmengine - INFO - Epoch(train) [64][30/63] lr: 1.2735e-03 eta: 13:08:59 time: 0.4923 data_time: 0.0246 memory: 14901 loss: 3.0983 loss_prob: 1.9607 loss_thr: 0.8034 loss_db: 0.3342 2022/11/02 12:50:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:51:00 - mmengine - INFO - Epoch(train) [64][35/63] lr: 1.2735e-03 eta: 13:08:59 time: 0.4701 data_time: 0.0172 memory: 14901 loss: 2.9367 loss_prob: 1.8221 loss_thr: 0.8020 loss_db: 0.3125 2022/11/02 12:51:02 - mmengine - INFO - Epoch(train) [64][40/63] lr: 1.2735e-03 eta: 13:08:19 time: 0.4723 data_time: 0.0145 memory: 14901 loss: 2.8852 loss_prob: 1.7878 loss_thr: 0.7942 loss_db: 0.3032 2022/11/02 12:51:05 - mmengine - INFO - Epoch(train) [64][45/63] lr: 1.2735e-03 eta: 13:08:19 time: 0.4748 data_time: 0.0063 memory: 14901 loss: 2.8346 loss_prob: 1.7634 loss_thr: 0.7801 loss_db: 0.2911 2022/11/02 12:51:07 - mmengine - INFO - Epoch(train) [64][50/63] lr: 1.2735e-03 eta: 13:07:41 time: 0.4857 data_time: 0.0162 memory: 14901 loss: 2.6417 loss_prob: 1.6332 loss_thr: 0.7441 loss_db: 0.2644 2022/11/02 12:51:10 - mmengine - INFO - Epoch(train) [64][55/63] lr: 1.2735e-03 eta: 13:07:41 time: 0.5028 data_time: 0.0200 memory: 14901 loss: 2.6763 loss_prob: 1.6501 loss_thr: 0.7550 loss_db: 0.2712 2022/11/02 12:51:12 - mmengine - INFO - Epoch(train) [64][60/63] lr: 1.2735e-03 eta: 13:07:06 time: 0.5000 data_time: 0.0114 memory: 14901 loss: 3.0340 loss_prob: 1.9002 loss_thr: 0.8087 loss_db: 0.3250 2022/11/02 12:51:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:51:18 - mmengine - INFO - Epoch(train) [65][5/63] lr: 1.2936e-03 eta: 13:07:06 time: 0.6834 data_time: 0.2156 memory: 14901 loss: 2.9008 loss_prob: 1.7780 loss_thr: 0.8197 loss_db: 0.3030 2022/11/02 12:51:21 - mmengine - INFO - Epoch(train) [65][10/63] lr: 1.2936e-03 eta: 13:06:31 time: 0.7103 data_time: 0.2242 memory: 14901 loss: 2.7855 loss_prob: 1.6979 loss_thr: 0.8113 loss_db: 0.2763 2022/11/02 12:51:24 - mmengine - INFO - Epoch(train) [65][15/63] lr: 1.2936e-03 eta: 13:06:31 time: 0.5325 data_time: 0.0154 memory: 14901 loss: 2.9230 loss_prob: 1.8223 loss_thr: 0.7998 loss_db: 0.3010 2022/11/02 12:51:26 - mmengine - INFO - Epoch(train) [65][20/63] lr: 1.2936e-03 eta: 13:05:59 time: 0.5158 data_time: 0.0054 memory: 14901 loss: 2.9888 loss_prob: 1.8672 loss_thr: 0.8048 loss_db: 0.3168 2022/11/02 12:51:28 - mmengine - INFO - Epoch(train) [65][25/63] lr: 1.2936e-03 eta: 13:05:59 time: 0.4724 data_time: 0.0179 memory: 14901 loss: 2.8396 loss_prob: 1.7675 loss_thr: 0.7775 loss_db: 0.2946 2022/11/02 12:51:31 - mmengine - INFO - Epoch(train) [65][30/63] lr: 1.2936e-03 eta: 13:05:23 time: 0.4916 data_time: 0.0269 memory: 14901 loss: 2.8425 loss_prob: 1.7773 loss_thr: 0.7703 loss_db: 0.2949 2022/11/02 12:51:33 - mmengine - INFO - Epoch(train) [65][35/63] lr: 1.2936e-03 eta: 13:05:23 time: 0.4869 data_time: 0.0221 memory: 14901 loss: 2.7381 loss_prob: 1.6937 loss_thr: 0.7673 loss_db: 0.2770 2022/11/02 12:51:36 - mmengine - INFO - Epoch(train) [65][40/63] lr: 1.2936e-03 eta: 13:04:44 time: 0.4720 data_time: 0.0142 memory: 14901 loss: 2.7681 loss_prob: 1.7088 loss_thr: 0.7780 loss_db: 0.2813 2022/11/02 12:51:38 - mmengine - INFO - Epoch(train) [65][45/63] lr: 1.2936e-03 eta: 13:04:44 time: 0.4854 data_time: 0.0056 memory: 14901 loss: 2.8378 loss_prob: 1.7699 loss_thr: 0.7728 loss_db: 0.2952 2022/11/02 12:51:41 - mmengine - INFO - Epoch(train) [65][50/63] lr: 1.2936e-03 eta: 13:04:12 time: 0.5122 data_time: 0.0135 memory: 14901 loss: 2.7032 loss_prob: 1.6757 loss_thr: 0.7544 loss_db: 0.2731 2022/11/02 12:51:43 - mmengine - INFO - Epoch(train) [65][55/63] lr: 1.2936e-03 eta: 13:04:12 time: 0.5150 data_time: 0.0199 memory: 14901 loss: 2.7182 loss_prob: 1.6825 loss_thr: 0.7606 loss_db: 0.2751 2022/11/02 12:51:46 - mmengine - INFO - Epoch(train) [65][60/63] lr: 1.2936e-03 eta: 13:03:42 time: 0.5257 data_time: 0.0128 memory: 14901 loss: 2.9911 loss_prob: 1.8667 loss_thr: 0.7986 loss_db: 0.3258 2022/11/02 12:51:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:51:53 - mmengine - INFO - Epoch(train) [66][5/63] lr: 1.3138e-03 eta: 13:03:42 time: 0.8189 data_time: 0.2167 memory: 14901 loss: 2.7758 loss_prob: 1.7218 loss_thr: 0.7634 loss_db: 0.2906 2022/11/02 12:51:56 - mmengine - INFO - Epoch(train) [66][10/63] lr: 1.3138e-03 eta: 13:03:32 time: 0.8454 data_time: 0.2231 memory: 14901 loss: 2.7628 loss_prob: 1.6954 loss_thr: 0.7834 loss_db: 0.2840 2022/11/02 12:51:58 - mmengine - INFO - Epoch(train) [66][15/63] lr: 1.3138e-03 eta: 13:03:32 time: 0.5146 data_time: 0.0119 memory: 14901 loss: 2.8800 loss_prob: 1.7813 loss_thr: 0.8008 loss_db: 0.2979 2022/11/02 12:52:01 - mmengine - INFO - Epoch(train) [66][20/63] lr: 1.3138e-03 eta: 13:02:58 time: 0.4980 data_time: 0.0050 memory: 14901 loss: 3.0248 loss_prob: 1.9065 loss_thr: 0.7921 loss_db: 0.3262 2022/11/02 12:52:03 - mmengine - INFO - Epoch(train) [66][25/63] lr: 1.3138e-03 eta: 13:02:58 time: 0.4914 data_time: 0.0182 memory: 14901 loss: 2.9477 loss_prob: 1.8526 loss_thr: 0.7752 loss_db: 0.3199 2022/11/02 12:52:06 - mmengine - INFO - Epoch(train) [66][30/63] lr: 1.3138e-03 eta: 13:02:23 time: 0.4966 data_time: 0.0319 memory: 14901 loss: 2.8816 loss_prob: 1.7965 loss_thr: 0.7804 loss_db: 0.3046 2022/11/02 12:52:08 - mmengine - INFO - Epoch(train) [66][35/63] lr: 1.3138e-03 eta: 13:02:23 time: 0.5077 data_time: 0.0231 memory: 14901 loss: 2.7228 loss_prob: 1.6836 loss_thr: 0.7628 loss_db: 0.2764 2022/11/02 12:52:11 - mmengine - INFO - Epoch(train) [66][40/63] lr: 1.3138e-03 eta: 13:02:05 time: 0.5911 data_time: 0.0097 memory: 14901 loss: 2.6882 loss_prob: 1.6570 loss_thr: 0.7606 loss_db: 0.2705 2022/11/02 12:52:15 - mmengine - INFO - Epoch(train) [66][45/63] lr: 1.3138e-03 eta: 13:02:05 time: 0.6662 data_time: 0.0051 memory: 14901 loss: 2.7573 loss_prob: 1.7150 loss_thr: 0.7619 loss_db: 0.2804 2022/11/02 12:52:18 - mmengine - INFO - Epoch(train) [66][50/63] lr: 1.3138e-03 eta: 13:01:58 time: 0.6505 data_time: 0.0184 memory: 14901 loss: 2.5882 loss_prob: 1.5896 loss_thr: 0.7418 loss_db: 0.2568 2022/11/02 12:52:21 - mmengine - INFO - Epoch(train) [66][55/63] lr: 1.3138e-03 eta: 13:01:58 time: 0.5738 data_time: 0.0217 memory: 14901 loss: 2.5589 loss_prob: 1.5443 loss_thr: 0.7614 loss_db: 0.2532 2022/11/02 12:52:23 - mmengine - INFO - Epoch(train) [66][60/63] lr: 1.3138e-03 eta: 13:01:30 time: 0.5310 data_time: 0.0094 memory: 14901 loss: 2.6759 loss_prob: 1.6317 loss_thr: 0.7744 loss_db: 0.2698 2022/11/02 12:52:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:52:32 - mmengine - INFO - Epoch(train) [67][5/63] lr: 1.3340e-03 eta: 13:01:30 time: 0.9652 data_time: 0.2282 memory: 14901 loss: 2.7962 loss_prob: 1.7194 loss_thr: 0.7850 loss_db: 0.2917 2022/11/02 12:52:35 - mmengine - INFO - Epoch(train) [67][10/63] lr: 1.3340e-03 eta: 13:01:46 time: 1.0012 data_time: 0.2308 memory: 14901 loss: 2.7671 loss_prob: 1.7169 loss_thr: 0.7612 loss_db: 0.2891 2022/11/02 12:52:38 - mmengine - INFO - Epoch(train) [67][15/63] lr: 1.3340e-03 eta: 13:01:46 time: 0.6178 data_time: 0.0072 memory: 14901 loss: 2.8273 loss_prob: 1.7503 loss_thr: 0.7863 loss_db: 0.2907 2022/11/02 12:52:40 - mmengine - INFO - Epoch(train) [67][20/63] lr: 1.3340e-03 eta: 13:01:22 time: 0.5522 data_time: 0.0050 memory: 14901 loss: 2.8450 loss_prob: 1.7434 loss_thr: 0.8134 loss_db: 0.2883 2022/11/02 12:52:43 - mmengine - INFO - Epoch(train) [67][25/63] lr: 1.3340e-03 eta: 13:01:22 time: 0.5227 data_time: 0.0322 memory: 14901 loss: 2.7866 loss_prob: 1.7191 loss_thr: 0.7791 loss_db: 0.2884 2022/11/02 12:52:46 - mmengine - INFO - Epoch(train) [67][30/63] lr: 1.3340e-03 eta: 13:00:52 time: 0.5200 data_time: 0.0328 memory: 14901 loss: 2.8757 loss_prob: 1.7900 loss_thr: 0.7788 loss_db: 0.3068 2022/11/02 12:52:48 - mmengine - INFO - Epoch(train) [67][35/63] lr: 1.3340e-03 eta: 13:00:52 time: 0.5267 data_time: 0.0083 memory: 14901 loss: 2.8250 loss_prob: 1.7505 loss_thr: 0.7744 loss_db: 0.3000 2022/11/02 12:52:51 - mmengine - INFO - Epoch(train) [67][40/63] lr: 1.3340e-03 eta: 13:00:26 time: 0.5437 data_time: 0.0087 memory: 14901 loss: 2.7413 loss_prob: 1.6929 loss_thr: 0.7609 loss_db: 0.2875 2022/11/02 12:52:54 - mmengine - INFO - Epoch(train) [67][45/63] lr: 1.3340e-03 eta: 13:00:26 time: 0.5599 data_time: 0.0074 memory: 14901 loss: 2.8476 loss_prob: 1.7707 loss_thr: 0.7751 loss_db: 0.3018 2022/11/02 12:52:57 - mmengine - INFO - Epoch(train) [67][50/63] lr: 1.3340e-03 eta: 13:00:09 time: 0.5899 data_time: 0.0309 memory: 14901 loss: 2.9941 loss_prob: 1.8677 loss_thr: 0.8021 loss_db: 0.3243 2022/11/02 12:52:59 - mmengine - INFO - Epoch(train) [67][55/63] lr: 1.3340e-03 eta: 13:00:09 time: 0.5389 data_time: 0.0291 memory: 14901 loss: 3.2952 loss_prob: 2.0766 loss_thr: 0.8457 loss_db: 0.3728 2022/11/02 12:53:02 - mmengine - INFO - Epoch(train) [67][60/63] lr: 1.3340e-03 eta: 12:59:42 time: 0.5364 data_time: 0.0080 memory: 14901 loss: 3.1245 loss_prob: 1.9797 loss_thr: 0.7915 loss_db: 0.3533 2022/11/02 12:53:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:53:09 - mmengine - INFO - Epoch(train) [68][5/63] lr: 1.3542e-03 eta: 12:59:42 time: 0.8346 data_time: 0.2178 memory: 14901 loss: 3.0324 loss_prob: 1.9370 loss_thr: 0.7548 loss_db: 0.3406 2022/11/02 12:53:12 - mmengine - INFO - Epoch(train) [68][10/63] lr: 1.3542e-03 eta: 12:59:23 time: 0.7892 data_time: 0.2155 memory: 14901 loss: 3.1199 loss_prob: 1.9920 loss_thr: 0.7790 loss_db: 0.3489 2022/11/02 12:53:15 - mmengine - INFO - Epoch(train) [68][15/63] lr: 1.3542e-03 eta: 12:59:23 time: 0.5292 data_time: 0.0056 memory: 14901 loss: 2.8887 loss_prob: 1.8071 loss_thr: 0.7731 loss_db: 0.3085 2022/11/02 12:53:17 - mmengine - INFO - Epoch(train) [68][20/63] lr: 1.3542e-03 eta: 12:58:55 time: 0.5309 data_time: 0.0057 memory: 14901 loss: 3.0287 loss_prob: 1.9095 loss_thr: 0.7861 loss_db: 0.3330 2022/11/02 12:53:20 - mmengine - INFO - Epoch(train) [68][25/63] lr: 1.3542e-03 eta: 12:58:55 time: 0.5215 data_time: 0.0261 memory: 14901 loss: 3.2563 loss_prob: 2.0693 loss_thr: 0.8243 loss_db: 0.3627 2022/11/02 12:53:22 - mmengine - INFO - Epoch(train) [68][30/63] lr: 1.3542e-03 eta: 12:58:28 time: 0.5333 data_time: 0.0326 memory: 14901 loss: 2.9389 loss_prob: 1.8374 loss_thr: 0.7918 loss_db: 0.3097 2022/11/02 12:53:25 - mmengine - INFO - Epoch(train) [68][35/63] lr: 1.3542e-03 eta: 12:58:28 time: 0.4995 data_time: 0.0166 memory: 14901 loss: 2.6609 loss_prob: 1.6367 loss_thr: 0.7571 loss_db: 0.2671 2022/11/02 12:53:27 - mmengine - INFO - Epoch(train) [68][40/63] lr: 1.3542e-03 eta: 12:57:53 time: 0.4798 data_time: 0.0095 memory: 14901 loss: 2.5431 loss_prob: 1.5454 loss_thr: 0.7516 loss_db: 0.2461 2022/11/02 12:53:30 - mmengine - INFO - Epoch(train) [68][45/63] lr: 1.3542e-03 eta: 12:57:53 time: 0.4775 data_time: 0.0041 memory: 14901 loss: 2.4529 loss_prob: 1.4595 loss_thr: 0.7567 loss_db: 0.2368 2022/11/02 12:53:32 - mmengine - INFO - Epoch(train) [68][50/63] lr: 1.3542e-03 eta: 12:57:24 time: 0.5208 data_time: 0.0223 memory: 14901 loss: 2.6238 loss_prob: 1.5981 loss_thr: 0.7583 loss_db: 0.2675 2022/11/02 12:53:35 - mmengine - INFO - Epoch(train) [68][55/63] lr: 1.3542e-03 eta: 12:57:24 time: 0.5316 data_time: 0.0271 memory: 14901 loss: 2.6257 loss_prob: 1.6226 loss_thr: 0.7325 loss_db: 0.2706 2022/11/02 12:53:37 - mmengine - INFO - Epoch(train) [68][60/63] lr: 1.3542e-03 eta: 12:56:48 time: 0.4813 data_time: 0.0101 memory: 14901 loss: 2.5461 loss_prob: 1.5663 loss_thr: 0.7220 loss_db: 0.2578 2022/11/02 12:53:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:53:44 - mmengine - INFO - Epoch(train) [69][5/63] lr: 1.3744e-03 eta: 12:56:48 time: 0.7609 data_time: 0.1679 memory: 14901 loss: 2.9272 loss_prob: 1.8257 loss_thr: 0.7899 loss_db: 0.3116 2022/11/02 12:53:46 - mmengine - INFO - Epoch(train) [69][10/63] lr: 1.3744e-03 eta: 12:56:30 time: 0.7876 data_time: 0.1832 memory: 14901 loss: 2.7999 loss_prob: 1.7236 loss_thr: 0.7822 loss_db: 0.2941 2022/11/02 12:53:49 - mmengine - INFO - Epoch(train) [69][15/63] lr: 1.3744e-03 eta: 12:56:30 time: 0.5052 data_time: 0.0233 memory: 14901 loss: 2.5803 loss_prob: 1.5634 loss_thr: 0.7575 loss_db: 0.2594 2022/11/02 12:53:51 - mmengine - INFO - Epoch(train) [69][20/63] lr: 1.3744e-03 eta: 12:55:55 time: 0.4845 data_time: 0.0075 memory: 14901 loss: 2.6101 loss_prob: 1.5973 loss_thr: 0.7496 loss_db: 0.2633 2022/11/02 12:53:54 - mmengine - INFO - Epoch(train) [69][25/63] lr: 1.3744e-03 eta: 12:55:55 time: 0.4761 data_time: 0.0109 memory: 14901 loss: 2.6706 loss_prob: 1.6445 loss_thr: 0.7473 loss_db: 0.2788 2022/11/02 12:53:56 - mmengine - INFO - Epoch(train) [69][30/63] lr: 1.3744e-03 eta: 12:55:23 time: 0.4986 data_time: 0.0378 memory: 14901 loss: 2.5978 loss_prob: 1.5735 loss_thr: 0.7629 loss_db: 0.2614 2022/11/02 12:53:59 - mmengine - INFO - Epoch(train) [69][35/63] lr: 1.3744e-03 eta: 12:55:23 time: 0.5124 data_time: 0.0331 memory: 14901 loss: 2.5305 loss_prob: 1.5335 loss_thr: 0.7498 loss_db: 0.2472 2022/11/02 12:54:01 - mmengine - INFO - Epoch(train) [69][40/63] lr: 1.3744e-03 eta: 12:54:49 time: 0.4884 data_time: 0.0071 memory: 14901 loss: 2.6722 loss_prob: 1.6433 loss_thr: 0.7555 loss_db: 0.2733 2022/11/02 12:54:03 - mmengine - INFO - Epoch(train) [69][45/63] lr: 1.3744e-03 eta: 12:54:49 time: 0.4751 data_time: 0.0057 memory: 14901 loss: 2.9424 loss_prob: 1.8379 loss_thr: 0.7883 loss_db: 0.3162 2022/11/02 12:54:06 - mmengine - INFO - Epoch(train) [69][50/63] lr: 1.3744e-03 eta: 12:54:15 time: 0.4839 data_time: 0.0088 memory: 14901 loss: 2.8180 loss_prob: 1.7555 loss_thr: 0.7645 loss_db: 0.2980 2022/11/02 12:54:08 - mmengine - INFO - Epoch(train) [69][55/63] lr: 1.3744e-03 eta: 12:54:15 time: 0.4912 data_time: 0.0187 memory: 14901 loss: 2.5777 loss_prob: 1.5721 loss_thr: 0.7482 loss_db: 0.2574 2022/11/02 12:54:11 - mmengine - INFO - Epoch(train) [69][60/63] lr: 1.3744e-03 eta: 12:53:40 time: 0.4752 data_time: 0.0158 memory: 14901 loss: 2.6306 loss_prob: 1.6212 loss_thr: 0.7445 loss_db: 0.2649 2022/11/02 12:54:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:54:17 - mmengine - INFO - Epoch(train) [70][5/63] lr: 1.3945e-03 eta: 12:53:40 time: 0.7041 data_time: 0.2048 memory: 14901 loss: 2.6999 loss_prob: 1.6571 loss_thr: 0.7678 loss_db: 0.2750 2022/11/02 12:54:20 - mmengine - INFO - Epoch(train) [70][10/63] lr: 1.3945e-03 eta: 12:53:18 time: 0.7642 data_time: 0.2084 memory: 14901 loss: 2.4924 loss_prob: 1.5089 loss_thr: 0.7389 loss_db: 0.2445 2022/11/02 12:54:22 - mmengine - INFO - Epoch(train) [70][15/63] lr: 1.3945e-03 eta: 12:53:18 time: 0.5077 data_time: 0.0103 memory: 14901 loss: 2.5358 loss_prob: 1.5399 loss_thr: 0.7442 loss_db: 0.2518 2022/11/02 12:54:24 - mmengine - INFO - Epoch(train) [70][20/63] lr: 1.3945e-03 eta: 12:52:45 time: 0.4932 data_time: 0.0049 memory: 14901 loss: 2.6072 loss_prob: 1.5991 loss_thr: 0.7481 loss_db: 0.2599 2022/11/02 12:54:27 - mmengine - INFO - Epoch(train) [70][25/63] lr: 1.3945e-03 eta: 12:52:45 time: 0.5190 data_time: 0.0249 memory: 14901 loss: 2.6032 loss_prob: 1.5883 loss_thr: 0.7534 loss_db: 0.2615 2022/11/02 12:54:29 - mmengine - INFO - Epoch(train) [70][30/63] lr: 1.3945e-03 eta: 12:52:14 time: 0.4999 data_time: 0.0354 memory: 14901 loss: 2.6367 loss_prob: 1.6099 loss_thr: 0.7614 loss_db: 0.2655 2022/11/02 12:54:32 - mmengine - INFO - Epoch(train) [70][35/63] lr: 1.3945e-03 eta: 12:52:14 time: 0.4749 data_time: 0.0182 memory: 14901 loss: 2.7782 loss_prob: 1.7327 loss_thr: 0.7596 loss_db: 0.2860 2022/11/02 12:54:34 - mmengine - INFO - Epoch(train) [70][40/63] lr: 1.3945e-03 eta: 12:51:38 time: 0.4691 data_time: 0.0075 memory: 14901 loss: 2.6511 loss_prob: 1.6468 loss_thr: 0.7327 loss_db: 0.2717 2022/11/02 12:54:37 - mmengine - INFO - Epoch(train) [70][45/63] lr: 1.3945e-03 eta: 12:51:38 time: 0.4868 data_time: 0.0044 memory: 14901 loss: 2.5510 loss_prob: 1.5574 loss_thr: 0.7382 loss_db: 0.2554 2022/11/02 12:54:39 - mmengine - INFO - Epoch(train) [70][50/63] lr: 1.3945e-03 eta: 12:51:08 time: 0.5033 data_time: 0.0176 memory: 14901 loss: 2.6350 loss_prob: 1.6228 loss_thr: 0.7406 loss_db: 0.2716 2022/11/02 12:54:42 - mmengine - INFO - Epoch(train) [70][55/63] lr: 1.3945e-03 eta: 12:51:08 time: 0.4838 data_time: 0.0200 memory: 14901 loss: 2.7017 loss_prob: 1.6799 loss_thr: 0.7369 loss_db: 0.2849 2022/11/02 12:54:44 - mmengine - INFO - Epoch(train) [70][60/63] lr: 1.3945e-03 eta: 12:50:35 time: 0.4815 data_time: 0.0080 memory: 14901 loss: 2.8004 loss_prob: 1.7344 loss_thr: 0.7722 loss_db: 0.2938 2022/11/02 12:54:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:54:51 - mmengine - INFO - Epoch(train) [71][5/63] lr: 1.4147e-03 eta: 12:50:35 time: 0.8380 data_time: 0.2075 memory: 14901 loss: 2.5773 loss_prob: 1.5576 loss_thr: 0.7641 loss_db: 0.2556 2022/11/02 12:54:55 - mmengine - INFO - Epoch(train) [71][10/63] lr: 1.4147e-03 eta: 12:50:42 time: 0.9448 data_time: 0.2135 memory: 14901 loss: 2.6191 loss_prob: 1.5891 loss_thr: 0.7677 loss_db: 0.2623 2022/11/02 12:54:57 - mmengine - INFO - Epoch(train) [71][15/63] lr: 1.4147e-03 eta: 12:50:42 time: 0.5934 data_time: 0.0161 memory: 14901 loss: 2.5638 loss_prob: 1.5667 loss_thr: 0.7377 loss_db: 0.2595 2022/11/02 12:55:00 - mmengine - INFO - Epoch(train) [71][20/63] lr: 1.4147e-03 eta: 12:50:13 time: 0.5075 data_time: 0.0111 memory: 14901 loss: 2.5050 loss_prob: 1.5380 loss_thr: 0.7146 loss_db: 0.2524 2022/11/02 12:55:03 - mmengine - INFO - Epoch(train) [71][25/63] lr: 1.4147e-03 eta: 12:50:13 time: 0.5310 data_time: 0.0056 memory: 14901 loss: 2.5602 loss_prob: 1.5710 loss_thr: 0.7340 loss_db: 0.2553 2022/11/02 12:55:05 - mmengine - INFO - Epoch(train) [71][30/63] lr: 1.4147e-03 eta: 12:49:53 time: 0.5625 data_time: 0.0285 memory: 14901 loss: 2.6281 loss_prob: 1.6223 loss_thr: 0.7429 loss_db: 0.2629 2022/11/02 12:55:09 - mmengine - INFO - Epoch(train) [71][35/63] lr: 1.4147e-03 eta: 12:49:53 time: 0.6527 data_time: 0.0327 memory: 14901 loss: 2.6382 loss_prob: 1.6385 loss_thr: 0.7334 loss_db: 0.2664 2022/11/02 12:55:12 - mmengine - INFO - Epoch(train) [71][40/63] lr: 1.4147e-03 eta: 12:49:39 time: 0.6077 data_time: 0.0154 memory: 14901 loss: 2.7163 loss_prob: 1.6906 loss_thr: 0.7432 loss_db: 0.2825 2022/11/02 12:55:16 - mmengine - INFO - Epoch(train) [71][45/63] lr: 1.4147e-03 eta: 12:49:39 time: 0.6592 data_time: 0.0131 memory: 14901 loss: 2.8405 loss_prob: 1.7854 loss_thr: 0.7456 loss_db: 0.3095 2022/11/02 12:55:18 - mmengine - INFO - Epoch(train) [71][50/63] lr: 1.4147e-03 eta: 12:49:37 time: 0.6723 data_time: 0.0197 memory: 14901 loss: 2.9489 loss_prob: 1.8617 loss_thr: 0.7626 loss_db: 0.3245 2022/11/02 12:55:21 - mmengine - INFO - Epoch(train) [71][55/63] lr: 1.4147e-03 eta: 12:49:37 time: 0.5142 data_time: 0.0193 memory: 14901 loss: 2.9338 loss_prob: 1.8413 loss_thr: 0.7780 loss_db: 0.3144 2022/11/02 12:55:24 - mmengine - INFO - Epoch(train) [71][60/63] lr: 1.4147e-03 eta: 12:49:11 time: 0.5308 data_time: 0.0063 memory: 14901 loss: 2.7112 loss_prob: 1.6659 loss_thr: 0.7658 loss_db: 0.2794 2022/11/02 12:55:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:55:31 - mmengine - INFO - Epoch(train) [72][5/63] lr: 1.4349e-03 eta: 12:49:11 time: 0.7899 data_time: 0.2043 memory: 14901 loss: 2.7789 loss_prob: 1.7285 loss_thr: 0.7665 loss_db: 0.2840 2022/11/02 12:55:33 - mmengine - INFO - Epoch(train) [72][10/63] lr: 1.4349e-03 eta: 12:49:07 time: 0.8704 data_time: 0.2059 memory: 14901 loss: 2.9226 loss_prob: 1.8394 loss_thr: 0.7752 loss_db: 0.3080 2022/11/02 12:55:36 - mmengine - INFO - Epoch(train) [72][15/63] lr: 1.4349e-03 eta: 12:49:07 time: 0.5281 data_time: 0.0129 memory: 14901 loss: 2.9722 loss_prob: 1.8675 loss_thr: 0.7843 loss_db: 0.3204 2022/11/02 12:55:39 - mmengine - INFO - Epoch(train) [72][20/63] lr: 1.4349e-03 eta: 12:48:43 time: 0.5361 data_time: 0.0128 memory: 14901 loss: 2.9405 loss_prob: 1.8430 loss_thr: 0.7846 loss_db: 0.3129 2022/11/02 12:55:42 - mmengine - INFO - Epoch(train) [72][25/63] lr: 1.4349e-03 eta: 12:48:43 time: 0.6098 data_time: 0.0244 memory: 14901 loss: 2.7980 loss_prob: 1.7601 loss_thr: 0.7483 loss_db: 0.2896 2022/11/02 12:55:45 - mmengine - INFO - Epoch(train) [72][30/63] lr: 1.4349e-03 eta: 12:48:37 time: 0.6555 data_time: 0.0325 memory: 14901 loss: 2.6799 loss_prob: 1.6677 loss_thr: 0.7377 loss_db: 0.2745 2022/11/02 12:55:48 - mmengine - INFO - Epoch(train) [72][35/63] lr: 1.4349e-03 eta: 12:48:37 time: 0.5815 data_time: 0.0168 memory: 14901 loss: 2.6212 loss_prob: 1.6099 loss_thr: 0.7515 loss_db: 0.2599 2022/11/02 12:55:50 - mmengine - INFO - Epoch(train) [72][40/63] lr: 1.4349e-03 eta: 12:48:04 time: 0.4789 data_time: 0.0108 memory: 14901 loss: 2.5513 loss_prob: 1.5555 loss_thr: 0.7477 loss_db: 0.2481 2022/11/02 12:55:53 - mmengine - INFO - Epoch(train) [72][45/63] lr: 1.4349e-03 eta: 12:48:04 time: 0.4794 data_time: 0.0107 memory: 14901 loss: 2.6017 loss_prob: 1.5921 loss_thr: 0.7493 loss_db: 0.2603 2022/11/02 12:55:55 - mmengine - INFO - Epoch(train) [72][50/63] lr: 1.4349e-03 eta: 12:47:37 time: 0.5192 data_time: 0.0110 memory: 14901 loss: 2.8350 loss_prob: 1.7722 loss_thr: 0.7656 loss_db: 0.2972 2022/11/02 12:55:58 - mmengine - INFO - Epoch(train) [72][55/63] lr: 1.4349e-03 eta: 12:47:37 time: 0.5433 data_time: 0.0193 memory: 14901 loss: 2.7174 loss_prob: 1.6973 loss_thr: 0.7400 loss_db: 0.2801 2022/11/02 12:56:01 - mmengine - INFO - Epoch(train) [72][60/63] lr: 1.4349e-03 eta: 12:47:12 time: 0.5289 data_time: 0.0130 memory: 14901 loss: 2.4078 loss_prob: 1.4648 loss_thr: 0.7098 loss_db: 0.2332 2022/11/02 12:56:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:56:07 - mmengine - INFO - Epoch(train) [73][5/63] lr: 1.4551e-03 eta: 12:47:12 time: 0.7120 data_time: 0.2226 memory: 14901 loss: 2.3909 loss_prob: 1.4371 loss_thr: 0.7203 loss_db: 0.2335 2022/11/02 12:56:09 - mmengine - INFO - Epoch(train) [73][10/63] lr: 1.4551e-03 eta: 12:46:44 time: 0.7156 data_time: 0.2219 memory: 14901 loss: 2.5304 loss_prob: 1.5235 loss_thr: 0.7535 loss_db: 0.2534 2022/11/02 12:56:12 - mmengine - INFO - Epoch(train) [73][15/63] lr: 1.4551e-03 eta: 12:46:44 time: 0.4954 data_time: 0.0110 memory: 14901 loss: 2.6947 loss_prob: 1.6460 loss_thr: 0.7757 loss_db: 0.2731 2022/11/02 12:56:14 - mmengine - INFO - Epoch(train) [73][20/63] lr: 1.4551e-03 eta: 12:46:15 time: 0.5003 data_time: 0.0094 memory: 14901 loss: 2.6821 loss_prob: 1.6718 loss_thr: 0.7423 loss_db: 0.2680 2022/11/02 12:56:17 - mmengine - INFO - Epoch(train) [73][25/63] lr: 1.4551e-03 eta: 12:46:15 time: 0.5127 data_time: 0.0116 memory: 14901 loss: 2.5554 loss_prob: 1.5894 loss_thr: 0.7095 loss_db: 0.2565 2022/11/02 12:56:19 - mmengine - INFO - Epoch(train) [73][30/63] lr: 1.4551e-03 eta: 12:45:50 time: 0.5289 data_time: 0.0276 memory: 14901 loss: 2.4108 loss_prob: 1.4533 loss_thr: 0.7171 loss_db: 0.2404 2022/11/02 12:56:22 - mmengine - INFO - Epoch(train) [73][35/63] lr: 1.4551e-03 eta: 12:45:50 time: 0.4967 data_time: 0.0216 memory: 14901 loss: 2.7969 loss_prob: 1.7199 loss_thr: 0.7875 loss_db: 0.2895 2022/11/02 12:56:25 - mmengine - INFO - Epoch(train) [73][40/63] lr: 1.4551e-03 eta: 12:45:22 time: 0.5122 data_time: 0.0132 memory: 14901 loss: 2.9348 loss_prob: 1.8326 loss_thr: 0.7917 loss_db: 0.3105 2022/11/02 12:56:27 - mmengine - INFO - Epoch(train) [73][45/63] lr: 1.4551e-03 eta: 12:45:22 time: 0.5637 data_time: 0.0122 memory: 14901 loss: 2.7110 loss_prob: 1.6759 loss_thr: 0.7570 loss_db: 0.2780 2022/11/02 12:56:30 - mmengine - INFO - Epoch(train) [73][50/63] lr: 1.4551e-03 eta: 12:44:57 time: 0.5226 data_time: 0.0182 memory: 14901 loss: 2.6231 loss_prob: 1.6080 loss_thr: 0.7518 loss_db: 0.2632 2022/11/02 12:56:33 - mmengine - INFO - Epoch(train) [73][55/63] lr: 1.4551e-03 eta: 12:44:57 time: 0.5110 data_time: 0.0256 memory: 14901 loss: 2.5216 loss_prob: 1.5335 loss_thr: 0.7407 loss_db: 0.2474 2022/11/02 12:56:35 - mmengine - INFO - Epoch(train) [73][60/63] lr: 1.4551e-03 eta: 12:44:33 time: 0.5369 data_time: 0.0147 memory: 14901 loss: 2.5976 loss_prob: 1.5825 loss_thr: 0.7590 loss_db: 0.2561 2022/11/02 12:56:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:56:41 - mmengine - INFO - Epoch(train) [74][5/63] lr: 1.4753e-03 eta: 12:44:33 time: 0.6741 data_time: 0.1929 memory: 14901 loss: 2.4547 loss_prob: 1.5026 loss_thr: 0.7147 loss_db: 0.2374 2022/11/02 12:56:43 - mmengine - INFO - Epoch(train) [74][10/63] lr: 1.4753e-03 eta: 12:44:02 time: 0.6932 data_time: 0.1942 memory: 14901 loss: 2.4889 loss_prob: 1.5241 loss_thr: 0.7172 loss_db: 0.2476 2022/11/02 12:56:46 - mmengine - INFO - Epoch(train) [74][15/63] lr: 1.4753e-03 eta: 12:44:02 time: 0.4961 data_time: 0.0079 memory: 14901 loss: 2.5217 loss_prob: 1.5432 loss_thr: 0.7205 loss_db: 0.2580 2022/11/02 12:56:48 - mmengine - INFO - Epoch(train) [74][20/63] lr: 1.4753e-03 eta: 12:43:29 time: 0.4712 data_time: 0.0062 memory: 14901 loss: 2.7122 loss_prob: 1.6815 loss_thr: 0.7366 loss_db: 0.2941 2022/11/02 12:56:51 - mmengine - INFO - Epoch(train) [74][25/63] lr: 1.4753e-03 eta: 12:43:29 time: 0.4895 data_time: 0.0291 memory: 14901 loss: 2.9194 loss_prob: 1.8436 loss_thr: 0.7526 loss_db: 0.3232 2022/11/02 12:56:53 - mmengine - INFO - Epoch(train) [74][30/63] lr: 1.4753e-03 eta: 12:42:58 time: 0.4860 data_time: 0.0271 memory: 14901 loss: 3.0590 loss_prob: 1.9442 loss_thr: 0.7805 loss_db: 0.3343 2022/11/02 12:56:55 - mmengine - INFO - Epoch(train) [74][35/63] lr: 1.4753e-03 eta: 12:42:58 time: 0.4723 data_time: 0.0082 memory: 14901 loss: 3.1509 loss_prob: 1.9731 loss_thr: 0.8305 loss_db: 0.3472 2022/11/02 12:56:58 - mmengine - INFO - Epoch(train) [74][40/63] lr: 1.4753e-03 eta: 12:42:27 time: 0.4810 data_time: 0.0083 memory: 14901 loss: 3.2397 loss_prob: 2.0545 loss_thr: 0.8188 loss_db: 0.3664 2022/11/02 12:57:00 - mmengine - INFO - Epoch(train) [74][45/63] lr: 1.4753e-03 eta: 12:42:27 time: 0.4805 data_time: 0.0061 memory: 14901 loss: 3.2449 loss_prob: 2.0761 loss_thr: 0.8045 loss_db: 0.3642 2022/11/02 12:57:03 - mmengine - INFO - Epoch(train) [74][50/63] lr: 1.4753e-03 eta: 12:42:05 time: 0.5452 data_time: 0.0215 memory: 14901 loss: 3.1657 loss_prob: 2.0055 loss_thr: 0.8048 loss_db: 0.3554 2022/11/02 12:57:06 - mmengine - INFO - Epoch(train) [74][55/63] lr: 1.4753e-03 eta: 12:42:05 time: 0.5490 data_time: 0.0200 memory: 14901 loss: 3.0384 loss_prob: 1.9132 loss_thr: 0.7897 loss_db: 0.3355 2022/11/02 12:57:08 - mmengine - INFO - Epoch(train) [74][60/63] lr: 1.4753e-03 eta: 12:41:40 time: 0.5213 data_time: 0.0071 memory: 14901 loss: 2.9817 loss_prob: 1.8706 loss_thr: 0.7944 loss_db: 0.3167 2022/11/02 12:57:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:57:14 - mmengine - INFO - Epoch(train) [75][5/63] lr: 1.4955e-03 eta: 12:41:40 time: 0.6828 data_time: 0.2067 memory: 14901 loss: 3.0031 loss_prob: 1.8885 loss_thr: 0.7929 loss_db: 0.3218 2022/11/02 12:57:17 - mmengine - INFO - Epoch(train) [75][10/63] lr: 1.4955e-03 eta: 12:41:12 time: 0.7103 data_time: 0.2092 memory: 14901 loss: 2.9852 loss_prob: 1.8853 loss_thr: 0.7838 loss_db: 0.3161 2022/11/02 12:57:19 - mmengine - INFO - Epoch(train) [75][15/63] lr: 1.4955e-03 eta: 12:41:12 time: 0.4782 data_time: 0.0081 memory: 14901 loss: 2.7157 loss_prob: 1.6976 loss_thr: 0.7438 loss_db: 0.2742 2022/11/02 12:57:22 - mmengine - INFO - Epoch(train) [75][20/63] lr: 1.4955e-03 eta: 12:40:42 time: 0.4888 data_time: 0.0058 memory: 14901 loss: 2.6802 loss_prob: 1.6622 loss_thr: 0.7469 loss_db: 0.2711 2022/11/02 12:57:25 - mmengine - INFO - Epoch(train) [75][25/63] lr: 1.4955e-03 eta: 12:40:42 time: 0.5942 data_time: 0.0328 memory: 14901 loss: 2.7968 loss_prob: 1.7328 loss_thr: 0.7732 loss_db: 0.2908 2022/11/02 12:57:28 - mmengine - INFO - Epoch(train) [75][30/63] lr: 1.4955e-03 eta: 12:40:32 time: 0.6176 data_time: 0.0332 memory: 14901 loss: 2.7350 loss_prob: 1.6893 loss_thr: 0.7594 loss_db: 0.2863 2022/11/02 12:57:30 - mmengine - INFO - Epoch(train) [75][35/63] lr: 1.4955e-03 eta: 12:40:32 time: 0.5328 data_time: 0.0095 memory: 14901 loss: 2.7224 loss_prob: 1.6901 loss_thr: 0.7422 loss_db: 0.2901 2022/11/02 12:57:33 - mmengine - INFO - Epoch(train) [75][40/63] lr: 1.4955e-03 eta: 12:40:08 time: 0.5264 data_time: 0.0083 memory: 14901 loss: 2.9209 loss_prob: 1.8297 loss_thr: 0.7772 loss_db: 0.3140 2022/11/02 12:57:36 - mmengine - INFO - Epoch(train) [75][45/63] lr: 1.4955e-03 eta: 12:40:08 time: 0.5635 data_time: 0.0045 memory: 14901 loss: 2.9574 loss_prob: 1.8641 loss_thr: 0.7823 loss_db: 0.3110 2022/11/02 12:57:39 - mmengine - INFO - Epoch(train) [75][50/63] lr: 1.4955e-03 eta: 12:39:49 time: 0.5625 data_time: 0.0193 memory: 14901 loss: 2.7368 loss_prob: 1.7061 loss_thr: 0.7503 loss_db: 0.2804 2022/11/02 12:57:42 - mmengine - INFO - Epoch(train) [75][55/63] lr: 1.4955e-03 eta: 12:39:49 time: 0.6071 data_time: 0.0205 memory: 14901 loss: 2.5970 loss_prob: 1.5908 loss_thr: 0.7450 loss_db: 0.2612 2022/11/02 12:57:45 - mmengine - INFO - Epoch(train) [75][60/63] lr: 1.4955e-03 eta: 12:39:37 time: 0.6042 data_time: 0.0100 memory: 14901 loss: 2.5011 loss_prob: 1.5117 loss_thr: 0.7423 loss_db: 0.2471 2022/11/02 12:57:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:57:51 - mmengine - INFO - Epoch(train) [76][5/63] lr: 1.5156e-03 eta: 12:39:37 time: 0.7204 data_time: 0.2366 memory: 14901 loss: 2.6103 loss_prob: 1.6168 loss_thr: 0.7216 loss_db: 0.2719 2022/11/02 12:57:54 - mmengine - INFO - Epoch(train) [76][10/63] lr: 1.5156e-03 eta: 12:39:24 time: 0.8092 data_time: 0.2396 memory: 14901 loss: 2.5721 loss_prob: 1.5830 loss_thr: 0.7266 loss_db: 0.2625 2022/11/02 12:57:58 - mmengine - INFO - Epoch(train) [76][15/63] lr: 1.5156e-03 eta: 12:39:24 time: 0.6706 data_time: 0.0117 memory: 14901 loss: 2.7466 loss_prob: 1.7042 loss_thr: 0.7590 loss_db: 0.2834 2022/11/02 12:58:01 - mmengine - INFO - Epoch(train) [76][20/63] lr: 1.5156e-03 eta: 12:39:29 time: 0.7195 data_time: 0.0091 memory: 14901 loss: 2.7328 loss_prob: 1.7003 loss_thr: 0.7473 loss_db: 0.2853 2022/11/02 12:58:04 - mmengine - INFO - Epoch(train) [76][25/63] lr: 1.5156e-03 eta: 12:39:29 time: 0.6349 data_time: 0.0202 memory: 14901 loss: 2.4620 loss_prob: 1.4996 loss_thr: 0.7149 loss_db: 0.2475 2022/11/02 12:58:07 - mmengine - INFO - Epoch(train) [76][30/63] lr: 1.5156e-03 eta: 12:39:09 time: 0.5507 data_time: 0.0302 memory: 14901 loss: 2.5380 loss_prob: 1.5570 loss_thr: 0.7235 loss_db: 0.2575 2022/11/02 12:58:10 - mmengine - INFO - Epoch(train) [76][35/63] lr: 1.5156e-03 eta: 12:39:09 time: 0.5709 data_time: 0.0161 memory: 14901 loss: 2.6194 loss_prob: 1.6191 loss_thr: 0.7306 loss_db: 0.2697 2022/11/02 12:58:13 - mmengine - INFO - Epoch(train) [76][40/63] lr: 1.5156e-03 eta: 12:38:55 time: 0.5870 data_time: 0.0111 memory: 14901 loss: 2.6421 loss_prob: 1.6485 loss_thr: 0.7199 loss_db: 0.2737 2022/11/02 12:58:16 - mmengine - INFO - Epoch(train) [76][45/63] lr: 1.5156e-03 eta: 12:38:55 time: 0.6201 data_time: 0.0105 memory: 14901 loss: 2.8210 loss_prob: 1.7740 loss_thr: 0.7505 loss_db: 0.2965 2022/11/02 12:58:20 - mmengine - INFO - Epoch(train) [76][50/63] lr: 1.5156e-03 eta: 12:38:56 time: 0.6936 data_time: 0.0196 memory: 14901 loss: 2.8656 loss_prob: 1.7884 loss_thr: 0.7791 loss_db: 0.2981 2022/11/02 12:58:22 - mmengine - INFO - Epoch(train) [76][55/63] lr: 1.5156e-03 eta: 12:38:56 time: 0.6374 data_time: 0.0195 memory: 14901 loss: 2.6253 loss_prob: 1.6115 loss_thr: 0.7494 loss_db: 0.2644 2022/11/02 12:58:25 - mmengine - INFO - Epoch(train) [76][60/63] lr: 1.5156e-03 eta: 12:38:31 time: 0.5216 data_time: 0.0070 memory: 14901 loss: 2.5242 loss_prob: 1.5347 loss_thr: 0.7348 loss_db: 0.2547 2022/11/02 12:58:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:58:31 - mmengine - INFO - Epoch(train) [77][5/63] lr: 1.5358e-03 eta: 12:38:31 time: 0.7218 data_time: 0.2290 memory: 14901 loss: 2.3763 loss_prob: 1.4304 loss_thr: 0.7130 loss_db: 0.2329 2022/11/02 12:58:33 - mmengine - INFO - Epoch(train) [77][10/63] lr: 1.5358e-03 eta: 12:38:11 time: 0.7522 data_time: 0.2316 memory: 14901 loss: 2.4639 loss_prob: 1.4937 loss_thr: 0.7255 loss_db: 0.2447 2022/11/02 12:58:36 - mmengine - INFO - Epoch(train) [77][15/63] lr: 1.5358e-03 eta: 12:38:11 time: 0.5312 data_time: 0.0109 memory: 14901 loss: 2.6598 loss_prob: 1.6232 loss_thr: 0.7659 loss_db: 0.2707 2022/11/02 12:58:38 - mmengine - INFO - Epoch(train) [77][20/63] lr: 1.5358e-03 eta: 12:37:44 time: 0.5022 data_time: 0.0105 memory: 14901 loss: 2.6003 loss_prob: 1.5778 loss_thr: 0.7578 loss_db: 0.2647 2022/11/02 12:58:41 - mmengine - INFO - Epoch(train) [77][25/63] lr: 1.5358e-03 eta: 12:37:44 time: 0.5043 data_time: 0.0340 memory: 14901 loss: 2.5698 loss_prob: 1.5659 loss_thr: 0.7420 loss_db: 0.2620 2022/11/02 12:58:44 - mmengine - INFO - Epoch(train) [77][30/63] lr: 1.5358e-03 eta: 12:37:21 time: 0.5317 data_time: 0.0300 memory: 14901 loss: 2.5894 loss_prob: 1.5905 loss_thr: 0.7333 loss_db: 0.2656 2022/11/02 12:58:46 - mmengine - INFO - Epoch(train) [77][35/63] lr: 1.5358e-03 eta: 12:37:21 time: 0.4956 data_time: 0.0043 memory: 14901 loss: 2.5211 loss_prob: 1.5283 loss_thr: 0.7418 loss_db: 0.2510 2022/11/02 12:58:48 - mmengine - INFO - Epoch(train) [77][40/63] lr: 1.5358e-03 eta: 12:36:48 time: 0.4608 data_time: 0.0042 memory: 14901 loss: 2.4255 loss_prob: 1.4578 loss_thr: 0.7281 loss_db: 0.2396 2022/11/02 12:58:51 - mmengine - INFO - Epoch(train) [77][45/63] lr: 1.5358e-03 eta: 12:36:48 time: 0.4668 data_time: 0.0097 memory: 14901 loss: 2.4885 loss_prob: 1.5046 loss_thr: 0.7302 loss_db: 0.2537 2022/11/02 12:58:53 - mmengine - INFO - Epoch(train) [77][50/63] lr: 1.5358e-03 eta: 12:36:18 time: 0.4842 data_time: 0.0242 memory: 14901 loss: 2.6133 loss_prob: 1.5942 loss_thr: 0.7539 loss_db: 0.2651 2022/11/02 12:58:56 - mmengine - INFO - Epoch(train) [77][55/63] lr: 1.5358e-03 eta: 12:36:18 time: 0.4817 data_time: 0.0186 memory: 14901 loss: 2.4556 loss_prob: 1.5075 loss_thr: 0.7014 loss_db: 0.2467 2022/11/02 12:58:58 - mmengine - INFO - Epoch(train) [77][60/63] lr: 1.5358e-03 eta: 12:35:49 time: 0.4831 data_time: 0.0050 memory: 14901 loss: 2.3907 loss_prob: 1.4495 loss_thr: 0.7018 loss_db: 0.2394 2022/11/02 12:59:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:59:05 - mmengine - INFO - Epoch(train) [78][5/63] lr: 1.5560e-03 eta: 12:35:49 time: 0.7466 data_time: 0.2203 memory: 14901 loss: 2.6002 loss_prob: 1.5870 loss_thr: 0.7495 loss_db: 0.2637 2022/11/02 12:59:07 - mmengine - INFO - Epoch(train) [78][10/63] lr: 1.5560e-03 eta: 12:35:22 time: 0.7049 data_time: 0.2183 memory: 14901 loss: 2.5909 loss_prob: 1.6111 loss_thr: 0.7148 loss_db: 0.2650 2022/11/02 12:59:09 - mmengine - INFO - Epoch(train) [78][15/63] lr: 1.5560e-03 eta: 12:35:22 time: 0.4778 data_time: 0.0080 memory: 14901 loss: 2.6180 loss_prob: 1.6323 loss_thr: 0.7166 loss_db: 0.2691 2022/11/02 12:59:12 - mmengine - INFO - Epoch(train) [78][20/63] lr: 1.5560e-03 eta: 12:34:55 time: 0.5022 data_time: 0.0083 memory: 14901 loss: 2.6831 loss_prob: 1.6595 loss_thr: 0.7432 loss_db: 0.2803 2022/11/02 12:59:15 - mmengine - INFO - Epoch(train) [78][25/63] lr: 1.5560e-03 eta: 12:34:55 time: 0.5346 data_time: 0.0302 memory: 14901 loss: 2.6273 loss_prob: 1.5895 loss_thr: 0.7692 loss_db: 0.2685 2022/11/02 12:59:17 - mmengine - INFO - Epoch(train) [78][30/63] lr: 1.5560e-03 eta: 12:34:34 time: 0.5374 data_time: 0.0366 memory: 14901 loss: 2.4782 loss_prob: 1.4879 loss_thr: 0.7417 loss_db: 0.2485 2022/11/02 12:59:20 - mmengine - INFO - Epoch(train) [78][35/63] lr: 1.5560e-03 eta: 12:34:34 time: 0.5202 data_time: 0.0153 memory: 14901 loss: 2.6458 loss_prob: 1.6356 loss_thr: 0.7278 loss_db: 0.2824 2022/11/02 12:59:22 - mmengine - INFO - Epoch(train) [78][40/63] lr: 1.5560e-03 eta: 12:34:06 time: 0.4926 data_time: 0.0086 memory: 14901 loss: 3.1911 loss_prob: 2.0318 loss_thr: 0.7959 loss_db: 0.3635 2022/11/02 12:59:24 - mmengine - INFO - Epoch(train) [78][45/63] lr: 1.5560e-03 eta: 12:34:06 time: 0.4641 data_time: 0.0043 memory: 14901 loss: 3.3606 loss_prob: 2.1662 loss_thr: 0.8065 loss_db: 0.3878 2022/11/02 12:59:27 - mmengine - INFO - Epoch(train) [78][50/63] lr: 1.5560e-03 eta: 12:33:35 time: 0.4640 data_time: 0.0160 memory: 14901 loss: 3.0592 loss_prob: 1.9360 loss_thr: 0.7862 loss_db: 0.3371 2022/11/02 12:59:29 - mmengine - INFO - Epoch(train) [78][55/63] lr: 1.5560e-03 eta: 12:33:35 time: 0.4808 data_time: 0.0224 memory: 14901 loss: 3.0664 loss_prob: 1.9264 loss_thr: 0.8087 loss_db: 0.3312 2022/11/02 12:59:32 - mmengine - INFO - Epoch(train) [78][60/63] lr: 1.5560e-03 eta: 12:33:06 time: 0.4833 data_time: 0.0139 memory: 14901 loss: 3.1127 loss_prob: 1.9709 loss_thr: 0.7976 loss_db: 0.3443 2022/11/02 12:59:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 12:59:39 - mmengine - INFO - Epoch(train) [79][5/63] lr: 1.5762e-03 eta: 12:33:06 time: 0.8007 data_time: 0.2322 memory: 14901 loss: 2.6988 loss_prob: 1.6545 loss_thr: 0.7673 loss_db: 0.2770 2022/11/02 12:59:41 - mmengine - INFO - Epoch(train) [79][10/63] lr: 1.5762e-03 eta: 12:32:57 time: 0.8311 data_time: 0.2323 memory: 14901 loss: 2.8411 loss_prob: 1.7587 loss_thr: 0.7838 loss_db: 0.2987 2022/11/02 12:59:44 - mmengine - INFO - Epoch(train) [79][15/63] lr: 1.5762e-03 eta: 12:32:57 time: 0.4792 data_time: 0.0134 memory: 14901 loss: 2.7733 loss_prob: 1.7138 loss_thr: 0.7746 loss_db: 0.2849 2022/11/02 12:59:46 - mmengine - INFO - Epoch(train) [79][20/63] lr: 1.5762e-03 eta: 12:32:30 time: 0.4939 data_time: 0.0100 memory: 14901 loss: 2.5829 loss_prob: 1.5648 loss_thr: 0.7629 loss_db: 0.2552 2022/11/02 12:59:49 - mmengine - INFO - Epoch(train) [79][25/63] lr: 1.5762e-03 eta: 12:32:30 time: 0.5311 data_time: 0.0123 memory: 14901 loss: 2.6672 loss_prob: 1.6416 loss_thr: 0.7543 loss_db: 0.2712 2022/11/02 12:59:51 - mmengine - INFO - Epoch(train) [79][30/63] lr: 1.5762e-03 eta: 12:32:05 time: 0.5081 data_time: 0.0256 memory: 14901 loss: 3.0425 loss_prob: 1.9196 loss_thr: 0.7929 loss_db: 0.3300 2022/11/02 12:59:54 - mmengine - INFO - Epoch(train) [79][35/63] lr: 1.5762e-03 eta: 12:32:05 time: 0.4928 data_time: 0.0207 memory: 14901 loss: 3.0756 loss_prob: 1.9457 loss_thr: 0.7912 loss_db: 0.3386 2022/11/02 12:59:56 - mmengine - INFO - Epoch(train) [79][40/63] lr: 1.5762e-03 eta: 12:31:41 time: 0.5170 data_time: 0.0109 memory: 14901 loss: 2.8330 loss_prob: 1.7726 loss_thr: 0.7631 loss_db: 0.2973 2022/11/02 12:59:59 - mmengine - INFO - Epoch(train) [79][45/63] lr: 1.5762e-03 eta: 12:31:41 time: 0.5609 data_time: 0.0095 memory: 14901 loss: 2.9924 loss_prob: 1.8865 loss_thr: 0.7805 loss_db: 0.3254 2022/11/02 13:00:03 - mmengine - INFO - Epoch(train) [79][50/63] lr: 1.5762e-03 eta: 12:31:40 time: 0.6753 data_time: 0.0136 memory: 14901 loss: 2.8794 loss_prob: 1.8140 loss_thr: 0.7544 loss_db: 0.3111 2022/11/02 13:00:06 - mmengine - INFO - Epoch(train) [79][55/63] lr: 1.5762e-03 eta: 12:31:40 time: 0.6728 data_time: 0.0201 memory: 14901 loss: 2.7714 loss_prob: 1.7353 loss_thr: 0.7432 loss_db: 0.2929 2022/11/02 13:00:09 - mmengine - INFO - Epoch(train) [79][60/63] lr: 1.5762e-03 eta: 12:31:22 time: 0.5544 data_time: 0.0128 memory: 14901 loss: 2.7942 loss_prob: 1.7393 loss_thr: 0.7623 loss_db: 0.2926 2022/11/02 13:00:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:00:16 - mmengine - INFO - Epoch(train) [80][5/63] lr: 1.5964e-03 eta: 12:31:22 time: 0.8394 data_time: 0.2492 memory: 14901 loss: 2.9380 loss_prob: 1.8317 loss_thr: 0.7801 loss_db: 0.3261 2022/11/02 13:00:19 - mmengine - INFO - Epoch(train) [80][10/63] lr: 1.5964e-03 eta: 12:31:21 time: 0.8826 data_time: 0.2508 memory: 14901 loss: 2.9534 loss_prob: 1.8629 loss_thr: 0.7714 loss_db: 0.3190 2022/11/02 13:00:23 - mmengine - INFO - Epoch(train) [80][15/63] lr: 1.5964e-03 eta: 12:31:21 time: 0.6675 data_time: 0.0090 memory: 14901 loss: 2.9909 loss_prob: 1.9058 loss_thr: 0.7575 loss_db: 0.3277 2022/11/02 13:00:27 - mmengine - INFO - Epoch(train) [80][20/63] lr: 1.5964e-03 eta: 12:31:38 time: 0.8029 data_time: 0.0058 memory: 14901 loss: 2.8422 loss_prob: 1.8013 loss_thr: 0.7379 loss_db: 0.3030 2022/11/02 13:00:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:00:31 - mmengine - INFO - Epoch(train) [80][25/63] lr: 1.5964e-03 eta: 12:31:38 time: 0.7916 data_time: 0.0373 memory: 14901 loss: 2.7582 loss_prob: 1.7331 loss_thr: 0.7314 loss_db: 0.2938 2022/11/02 13:00:33 - mmengine - INFO - Epoch(train) [80][30/63] lr: 1.5964e-03 eta: 12:31:29 time: 0.6192 data_time: 0.0365 memory: 14901 loss: 2.7215 loss_prob: 1.6993 loss_thr: 0.7338 loss_db: 0.2885 2022/11/02 13:00:36 - mmengine - INFO - Epoch(train) [80][35/63] lr: 1.5964e-03 eta: 12:31:29 time: 0.5232 data_time: 0.0046 memory: 14901 loss: 2.7479 loss_prob: 1.7155 loss_thr: 0.7451 loss_db: 0.2873 2022/11/02 13:00:38 - mmengine - INFO - Epoch(train) [80][40/63] lr: 1.5964e-03 eta: 12:31:05 time: 0.5137 data_time: 0.0047 memory: 14901 loss: 2.7415 loss_prob: 1.7161 loss_thr: 0.7430 loss_db: 0.2824 2022/11/02 13:00:41 - mmengine - INFO - Epoch(train) [80][45/63] lr: 1.5964e-03 eta: 12:31:05 time: 0.5212 data_time: 0.0045 memory: 14901 loss: 2.5689 loss_prob: 1.5840 loss_thr: 0.7315 loss_db: 0.2533 2022/11/02 13:00:43 - mmengine - INFO - Epoch(train) [80][50/63] lr: 1.5964e-03 eta: 12:30:41 time: 0.5151 data_time: 0.0230 memory: 14901 loss: 2.6176 loss_prob: 1.6098 loss_thr: 0.7464 loss_db: 0.2614 2022/11/02 13:00:46 - mmengine - INFO - Epoch(train) [80][55/63] lr: 1.5964e-03 eta: 12:30:41 time: 0.5331 data_time: 0.0236 memory: 14901 loss: 2.7161 loss_prob: 1.6753 loss_thr: 0.7662 loss_db: 0.2745 2022/11/02 13:00:49 - mmengine - INFO - Epoch(train) [80][60/63] lr: 1.5964e-03 eta: 12:30:29 time: 0.5973 data_time: 0.0051 memory: 14901 loss: 2.5813 loss_prob: 1.5742 loss_thr: 0.7489 loss_db: 0.2582 2022/11/02 13:00:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:00:51 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/11/02 13:00:54 - mmengine - INFO - Epoch(val) [80][5/500] eta: 12:30:29 time: 0.0455 data_time: 0.0047 memory: 14901 2022/11/02 13:00:55 - mmengine - INFO - Epoch(val) [80][10/500] eta: 0:00:22 time: 0.0452 data_time: 0.0043 memory: 1008 2022/11/02 13:00:55 - mmengine - INFO - Epoch(val) [80][15/500] eta: 0:00:22 time: 0.0400 data_time: 0.0023 memory: 1008 2022/11/02 13:00:55 - mmengine - INFO - Epoch(val) [80][20/500] eta: 0:00:19 time: 0.0399 data_time: 0.0023 memory: 1008 2022/11/02 13:00:55 - mmengine - INFO - Epoch(val) [80][25/500] eta: 0:00:19 time: 0.0392 data_time: 0.0027 memory: 1008 2022/11/02 13:00:55 - mmengine - INFO - Epoch(val) [80][30/500] eta: 0:00:20 time: 0.0439 data_time: 0.0031 memory: 1008 2022/11/02 13:00:56 - mmengine - INFO - Epoch(val) [80][35/500] eta: 0:00:20 time: 0.0431 data_time: 0.0027 memory: 1008 2022/11/02 13:00:56 - mmengine - INFO - Epoch(val) [80][40/500] eta: 0:00:20 time: 0.0456 data_time: 0.0026 memory: 1008 2022/11/02 13:00:56 - mmengine - INFO - Epoch(val) [80][45/500] eta: 0:00:20 time: 0.0501 data_time: 0.0027 memory: 1008 2022/11/02 13:00:56 - mmengine - INFO - Epoch(val) [80][50/500] eta: 0:00:19 time: 0.0435 data_time: 0.0025 memory: 1008 2022/11/02 13:00:57 - mmengine - INFO - Epoch(val) [80][55/500] eta: 0:00:19 time: 0.0412 data_time: 0.0029 memory: 1008 2022/11/02 13:00:57 - mmengine - INFO - Epoch(val) [80][60/500] eta: 0:00:16 time: 0.0382 data_time: 0.0028 memory: 1008 2022/11/02 13:00:57 - mmengine - INFO - Epoch(val) [80][65/500] eta: 0:00:16 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 13:00:57 - mmengine - INFO - Epoch(val) [80][70/500] eta: 0:00:18 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 13:00:57 - mmengine - INFO - Epoch(val) [80][75/500] eta: 0:00:18 time: 0.0400 data_time: 0.0030 memory: 1008 2022/11/02 13:00:58 - mmengine - INFO - Epoch(val) [80][80/500] eta: 0:00:17 time: 0.0417 data_time: 0.0035 memory: 1008 2022/11/02 13:00:58 - mmengine - INFO - Epoch(val) [80][85/500] eta: 0:00:17 time: 0.0417 data_time: 0.0032 memory: 1008 2022/11/02 13:00:58 - mmengine - INFO - Epoch(val) [80][90/500] eta: 0:00:16 time: 0.0408 data_time: 0.0026 memory: 1008 2022/11/02 13:00:58 - mmengine - INFO - Epoch(val) [80][95/500] eta: 0:00:16 time: 0.0450 data_time: 0.0027 memory: 1008 2022/11/02 13:00:58 - mmengine - INFO - Epoch(val) [80][100/500] eta: 0:00:16 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 13:00:59 - mmengine - INFO - Epoch(val) [80][105/500] eta: 0:00:16 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/02 13:00:59 - mmengine - INFO - Epoch(val) [80][110/500] eta: 0:00:15 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 13:00:59 - mmengine - INFO - Epoch(val) [80][115/500] eta: 0:00:15 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 13:00:59 - mmengine - INFO - Epoch(val) [80][120/500] eta: 0:00:15 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 13:00:59 - mmengine - INFO - Epoch(val) [80][125/500] eta: 0:00:15 time: 0.0375 data_time: 0.0023 memory: 1008 2022/11/02 13:01:00 - mmengine - INFO - Epoch(val) [80][130/500] eta: 0:00:14 time: 0.0400 data_time: 0.0033 memory: 1008 2022/11/02 13:01:00 - mmengine - INFO - Epoch(val) [80][135/500] eta: 0:00:14 time: 0.0397 data_time: 0.0035 memory: 1008 2022/11/02 13:01:00 - mmengine - INFO - Epoch(val) [80][140/500] eta: 0:00:14 time: 0.0394 data_time: 0.0033 memory: 1008 2022/11/02 13:01:00 - mmengine - INFO - Epoch(val) [80][145/500] eta: 0:00:14 time: 0.0426 data_time: 0.0033 memory: 1008 2022/11/02 13:01:00 - mmengine - INFO - Epoch(val) [80][150/500] eta: 0:00:15 time: 0.0433 data_time: 0.0025 memory: 1008 2022/11/02 13:01:01 - mmengine - INFO - Epoch(val) [80][155/500] eta: 0:00:15 time: 0.0438 data_time: 0.0025 memory: 1008 2022/11/02 13:01:01 - mmengine - INFO - Epoch(val) [80][160/500] eta: 0:00:14 time: 0.0440 data_time: 0.0025 memory: 1008 2022/11/02 13:01:01 - mmengine - INFO - Epoch(val) [80][165/500] eta: 0:00:14 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 13:01:01 - mmengine - INFO - Epoch(val) [80][170/500] eta: 0:00:14 time: 0.0444 data_time: 0.0028 memory: 1008 2022/11/02 13:01:02 - mmengine - INFO - Epoch(val) [80][175/500] eta: 0:00:14 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 13:01:02 - mmengine - INFO - Epoch(val) [80][180/500] eta: 0:00:12 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/02 13:01:02 - mmengine - INFO - Epoch(val) [80][185/500] eta: 0:00:12 time: 0.0425 data_time: 0.0027 memory: 1008 2022/11/02 13:01:02 - mmengine - INFO - Epoch(val) [80][190/500] eta: 0:00:13 time: 0.0432 data_time: 0.0025 memory: 1008 2022/11/02 13:01:02 - mmengine - INFO - Epoch(val) [80][195/500] eta: 0:00:13 time: 0.0401 data_time: 0.0031 memory: 1008 2022/11/02 13:01:03 - mmengine - INFO - Epoch(val) [80][200/500] eta: 0:00:13 time: 0.0462 data_time: 0.0032 memory: 1008 2022/11/02 13:01:03 - mmengine - INFO - Epoch(val) [80][205/500] eta: 0:00:13 time: 0.0477 data_time: 0.0027 memory: 1008 2022/11/02 13:01:03 - mmengine - INFO - Epoch(val) [80][210/500] eta: 0:00:11 time: 0.0404 data_time: 0.0028 memory: 1008 2022/11/02 13:01:03 - mmengine - INFO - Epoch(val) [80][215/500] eta: 0:00:11 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 13:01:03 - mmengine - INFO - Epoch(val) [80][220/500] eta: 0:00:10 time: 0.0391 data_time: 0.0024 memory: 1008 2022/11/02 13:01:04 - mmengine - INFO - Epoch(val) [80][225/500] eta: 0:00:10 time: 0.0412 data_time: 0.0025 memory: 1008 2022/11/02 13:01:04 - mmengine - INFO - Epoch(val) [80][230/500] eta: 0:00:11 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 13:01:04 - mmengine - INFO - Epoch(val) [80][235/500] eta: 0:00:11 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 13:01:04 - mmengine - INFO - Epoch(val) [80][240/500] eta: 0:00:10 time: 0.0403 data_time: 0.0023 memory: 1008 2022/11/02 13:01:04 - mmengine - INFO - Epoch(val) [80][245/500] eta: 0:00:10 time: 0.0382 data_time: 0.0024 memory: 1008 2022/11/02 13:01:05 - mmengine - INFO - Epoch(val) [80][250/500] eta: 0:00:09 time: 0.0386 data_time: 0.0022 memory: 1008 2022/11/02 13:01:05 - mmengine - INFO - Epoch(val) [80][255/500] eta: 0:00:09 time: 0.0377 data_time: 0.0023 memory: 1008 2022/11/02 13:01:05 - mmengine - INFO - Epoch(val) [80][260/500] eta: 0:00:08 time: 0.0359 data_time: 0.0023 memory: 1008 2022/11/02 13:01:05 - mmengine - INFO - Epoch(val) [80][265/500] eta: 0:00:08 time: 0.0367 data_time: 0.0022 memory: 1008 2022/11/02 13:01:05 - mmengine - INFO - Epoch(val) [80][270/500] eta: 0:00:08 time: 0.0381 data_time: 0.0022 memory: 1008 2022/11/02 13:01:06 - mmengine - INFO - Epoch(val) [80][275/500] eta: 0:00:08 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 13:01:06 - mmengine - INFO - Epoch(val) [80][280/500] eta: 0:00:08 time: 0.0369 data_time: 0.0025 memory: 1008 2022/11/02 13:01:06 - mmengine - INFO - Epoch(val) [80][285/500] eta: 0:00:08 time: 0.0377 data_time: 0.0023 memory: 1008 2022/11/02 13:01:06 - mmengine - INFO - Epoch(val) [80][290/500] eta: 0:00:07 time: 0.0372 data_time: 0.0022 memory: 1008 2022/11/02 13:01:06 - mmengine - INFO - Epoch(val) [80][295/500] eta: 0:00:07 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/02 13:01:06 - mmengine - INFO - Epoch(val) [80][300/500] eta: 0:00:08 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 13:01:07 - mmengine - INFO - Epoch(val) [80][305/500] eta: 0:00:08 time: 0.0411 data_time: 0.0027 memory: 1008 2022/11/02 13:01:07 - mmengine - INFO - Epoch(val) [80][310/500] eta: 0:00:07 time: 0.0409 data_time: 0.0026 memory: 1008 2022/11/02 13:01:07 - mmengine - INFO - Epoch(val) [80][315/500] eta: 0:00:07 time: 0.0418 data_time: 0.0024 memory: 1008 2022/11/02 13:01:07 - mmengine - INFO - Epoch(val) [80][320/500] eta: 0:00:07 time: 0.0397 data_time: 0.0023 memory: 1008 2022/11/02 13:01:08 - mmengine - INFO - Epoch(val) [80][325/500] eta: 0:00:07 time: 0.0487 data_time: 0.0025 memory: 1008 2022/11/02 13:01:08 - mmengine - INFO - Epoch(val) [80][330/500] eta: 0:00:08 time: 0.0491 data_time: 0.0025 memory: 1008 2022/11/02 13:01:08 - mmengine - INFO - Epoch(val) [80][335/500] eta: 0:00:08 time: 0.0387 data_time: 0.0030 memory: 1008 2022/11/02 13:01:08 - mmengine - INFO - Epoch(val) [80][340/500] eta: 0:00:08 time: 0.0512 data_time: 0.0032 memory: 1008 2022/11/02 13:01:08 - mmengine - INFO - Epoch(val) [80][345/500] eta: 0:00:08 time: 0.0512 data_time: 0.0026 memory: 1008 2022/11/02 13:01:09 - mmengine - INFO - Epoch(val) [80][350/500] eta: 0:00:06 time: 0.0458 data_time: 0.0025 memory: 1008 2022/11/02 13:01:09 - mmengine - INFO - Epoch(val) [80][355/500] eta: 0:00:06 time: 0.0441 data_time: 0.0025 memory: 1008 2022/11/02 13:01:09 - mmengine - INFO - Epoch(val) [80][360/500] eta: 0:00:05 time: 0.0404 data_time: 0.0029 memory: 1008 2022/11/02 13:01:09 - mmengine - INFO - Epoch(val) [80][365/500] eta: 0:00:05 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 13:01:10 - mmengine - INFO - Epoch(val) [80][370/500] eta: 0:00:05 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 13:01:10 - mmengine - INFO - Epoch(val) [80][375/500] eta: 0:00:05 time: 0.0356 data_time: 0.0024 memory: 1008 2022/11/02 13:01:10 - mmengine - INFO - Epoch(val) [80][380/500] eta: 0:00:04 time: 0.0375 data_time: 0.0022 memory: 1008 2022/11/02 13:01:10 - mmengine - INFO - Epoch(val) [80][385/500] eta: 0:00:04 time: 0.0378 data_time: 0.0021 memory: 1008 2022/11/02 13:01:10 - mmengine - INFO - Epoch(val) [80][390/500] eta: 0:00:04 time: 0.0369 data_time: 0.0022 memory: 1008 2022/11/02 13:01:10 - mmengine - INFO - Epoch(val) [80][395/500] eta: 0:00:04 time: 0.0392 data_time: 0.0023 memory: 1008 2022/11/02 13:01:11 - mmengine - INFO - Epoch(val) [80][400/500] eta: 0:00:04 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 13:01:11 - mmengine - INFO - Epoch(val) [80][405/500] eta: 0:00:04 time: 0.0428 data_time: 0.0026 memory: 1008 2022/11/02 13:01:11 - mmengine - INFO - Epoch(val) [80][410/500] eta: 0:00:03 time: 0.0434 data_time: 0.0025 memory: 1008 2022/11/02 13:01:11 - mmengine - INFO - Epoch(val) [80][415/500] eta: 0:00:03 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 13:01:11 - mmengine - INFO - Epoch(val) [80][420/500] eta: 0:00:02 time: 0.0358 data_time: 0.0025 memory: 1008 2022/11/02 13:01:12 - mmengine - INFO - Epoch(val) [80][425/500] eta: 0:00:02 time: 0.0374 data_time: 0.0025 memory: 1008 2022/11/02 13:01:12 - mmengine - INFO - Epoch(val) [80][430/500] eta: 0:00:02 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 13:01:12 - mmengine - INFO - Epoch(val) [80][435/500] eta: 0:00:02 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 13:01:12 - mmengine - INFO - Epoch(val) [80][440/500] eta: 0:00:02 time: 0.0416 data_time: 0.0024 memory: 1008 2022/11/02 13:01:13 - mmengine - INFO - Epoch(val) [80][445/500] eta: 0:00:02 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/02 13:01:13 - mmengine - INFO - Epoch(val) [80][450/500] eta: 0:00:02 time: 0.0407 data_time: 0.0023 memory: 1008 2022/11/02 13:01:13 - mmengine - INFO - Epoch(val) [80][455/500] eta: 0:00:02 time: 0.0408 data_time: 0.0024 memory: 1008 2022/11/02 13:01:13 - mmengine - INFO - Epoch(val) [80][460/500] eta: 0:00:01 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/02 13:01:13 - mmengine - INFO - Epoch(val) [80][465/500] eta: 0:00:01 time: 0.0360 data_time: 0.0023 memory: 1008 2022/11/02 13:01:13 - mmengine - INFO - Epoch(val) [80][470/500] eta: 0:00:01 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 13:01:14 - mmengine - INFO - Epoch(val) [80][475/500] eta: 0:00:01 time: 0.0389 data_time: 0.0027 memory: 1008 2022/11/02 13:01:14 - mmengine - INFO - Epoch(val) [80][480/500] eta: 0:00:00 time: 0.0366 data_time: 0.0026 memory: 1008 2022/11/02 13:01:14 - mmengine - INFO - Epoch(val) [80][485/500] eta: 0:00:00 time: 0.0383 data_time: 0.0032 memory: 1008 2022/11/02 13:01:14 - mmengine - INFO - Epoch(val) [80][490/500] eta: 0:00:00 time: 0.0406 data_time: 0.0032 memory: 1008 2022/11/02 13:01:14 - mmengine - INFO - Epoch(val) [80][495/500] eta: 0:00:00 time: 0.0423 data_time: 0.0024 memory: 1008 2022/11/02 13:01:15 - mmengine - INFO - Epoch(val) [80][500/500] eta: 0:00:00 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/02 13:01:15 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7410, precision: 0.5901, hmean: 0.6570 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7405, precision: 0.7010, hmean: 0.7202 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7265, precision: 0.7851, hmean: 0.7547 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.6673, precision: 0.8545, hmean: 0.7494 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.4535, precision: 0.9235, hmean: 0.6083 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0294, precision: 0.9531, hmean: 0.0570 2022/11/02 13:01:15 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 13:01:15 - mmengine - INFO - Epoch(val) [80][500/500] icdar/precision: 0.7851 icdar/recall: 0.7265 icdar/hmean: 0.7547 2022/11/02 13:01:20 - mmengine - INFO - Epoch(train) [81][5/63] lr: 1.6165e-03 eta: 0:00:00 time: 0.7645 data_time: 0.2190 memory: 14901 loss: 2.5941 loss_prob: 1.5841 loss_thr: 0.7470 loss_db: 0.2630 2022/11/02 13:01:23 - mmengine - INFO - Epoch(train) [81][10/63] lr: 1.6165e-03 eta: 12:30:15 time: 0.7883 data_time: 0.2185 memory: 14901 loss: 2.5399 loss_prob: 1.5530 loss_thr: 0.7317 loss_db: 0.2551 2022/11/02 13:01:25 - mmengine - INFO - Epoch(train) [81][15/63] lr: 1.6165e-03 eta: 12:30:15 time: 0.4825 data_time: 0.0046 memory: 14901 loss: 2.5147 loss_prob: 1.5399 loss_thr: 0.7199 loss_db: 0.2550 2022/11/02 13:01:27 - mmengine - INFO - Epoch(train) [81][20/63] lr: 1.6165e-03 eta: 12:29:47 time: 0.4848 data_time: 0.0045 memory: 14901 loss: 2.5502 loss_prob: 1.5618 loss_thr: 0.7302 loss_db: 0.2581 2022/11/02 13:01:30 - mmengine - INFO - Epoch(train) [81][25/63] lr: 1.6165e-03 eta: 12:29:47 time: 0.5005 data_time: 0.0189 memory: 14901 loss: 2.5624 loss_prob: 1.5795 loss_thr: 0.7196 loss_db: 0.2633 2022/11/02 13:01:33 - mmengine - INFO - Epoch(train) [81][30/63] lr: 1.6165e-03 eta: 12:29:24 time: 0.5167 data_time: 0.0327 memory: 14901 loss: 2.5626 loss_prob: 1.5756 loss_thr: 0.7205 loss_db: 0.2665 2022/11/02 13:01:35 - mmengine - INFO - Epoch(train) [81][35/63] lr: 1.6165e-03 eta: 12:29:24 time: 0.5284 data_time: 0.0183 memory: 14901 loss: 2.5705 loss_prob: 1.5713 loss_thr: 0.7340 loss_db: 0.2652 2022/11/02 13:01:38 - mmengine - INFO - Epoch(train) [81][40/63] lr: 1.6165e-03 eta: 12:28:59 time: 0.5058 data_time: 0.0051 memory: 14901 loss: 2.5114 loss_prob: 1.5437 loss_thr: 0.7131 loss_db: 0.2546 2022/11/02 13:01:40 - mmengine - INFO - Epoch(train) [81][45/63] lr: 1.6165e-03 eta: 12:28:59 time: 0.4950 data_time: 0.0060 memory: 14901 loss: 2.4527 loss_prob: 1.5105 loss_thr: 0.6970 loss_db: 0.2452 2022/11/02 13:01:43 - mmengine - INFO - Epoch(train) [81][50/63] lr: 1.6165e-03 eta: 12:28:34 time: 0.5019 data_time: 0.0243 memory: 14901 loss: 2.5566 loss_prob: 1.5775 loss_thr: 0.7206 loss_db: 0.2585 2022/11/02 13:01:45 - mmengine - INFO - Epoch(train) [81][55/63] lr: 1.6165e-03 eta: 12:28:34 time: 0.4939 data_time: 0.0233 memory: 14901 loss: 2.6616 loss_prob: 1.6585 loss_thr: 0.7309 loss_db: 0.2722 2022/11/02 13:01:48 - mmengine - INFO - Epoch(train) [81][60/63] lr: 1.6165e-03 eta: 12:28:08 time: 0.4909 data_time: 0.0046 memory: 14901 loss: 2.5882 loss_prob: 1.5842 loss_thr: 0.7447 loss_db: 0.2593 2022/11/02 13:01:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:01:53 - mmengine - INFO - Epoch(train) [82][5/63] lr: 1.6367e-03 eta: 12:28:08 time: 0.6765 data_time: 0.1927 memory: 14901 loss: 2.4237 loss_prob: 1.4511 loss_thr: 0.7363 loss_db: 0.2362 2022/11/02 13:01:55 - mmengine - INFO - Epoch(train) [82][10/63] lr: 1.6367e-03 eta: 12:27:37 time: 0.6637 data_time: 0.1960 memory: 14901 loss: 2.3859 loss_prob: 1.4451 loss_thr: 0.7092 loss_db: 0.2316 2022/11/02 13:01:58 - mmengine - INFO - Epoch(train) [82][15/63] lr: 1.6367e-03 eta: 12:27:37 time: 0.4580 data_time: 0.0078 memory: 14901 loss: 2.4396 loss_prob: 1.4720 loss_thr: 0.7276 loss_db: 0.2400 2022/11/02 13:02:00 - mmengine - INFO - Epoch(train) [82][20/63] lr: 1.6367e-03 eta: 12:27:11 time: 0.4992 data_time: 0.0050 memory: 14901 loss: 2.4055 loss_prob: 1.4484 loss_thr: 0.7187 loss_db: 0.2384 2022/11/02 13:02:03 - mmengine - INFO - Epoch(train) [82][25/63] lr: 1.6367e-03 eta: 12:27:11 time: 0.5206 data_time: 0.0257 memory: 14901 loss: 2.5495 loss_prob: 1.5790 loss_thr: 0.7118 loss_db: 0.2586 2022/11/02 13:02:05 - mmengine - INFO - Epoch(train) [82][30/63] lr: 1.6367e-03 eta: 12:26:46 time: 0.4978 data_time: 0.0300 memory: 14901 loss: 2.6408 loss_prob: 1.6453 loss_thr: 0.7274 loss_db: 0.2681 2022/11/02 13:02:08 - mmengine - INFO - Epoch(train) [82][35/63] lr: 1.6367e-03 eta: 12:26:46 time: 0.4751 data_time: 0.0124 memory: 14901 loss: 2.3609 loss_prob: 1.4251 loss_thr: 0.7038 loss_db: 0.2320 2022/11/02 13:02:10 - mmengine - INFO - Epoch(train) [82][40/63] lr: 1.6367e-03 eta: 12:26:19 time: 0.4853 data_time: 0.0080 memory: 14901 loss: 2.3588 loss_prob: 1.4360 loss_thr: 0.6865 loss_db: 0.2363 2022/11/02 13:02:13 - mmengine - INFO - Epoch(train) [82][45/63] lr: 1.6367e-03 eta: 12:26:19 time: 0.4854 data_time: 0.0047 memory: 14901 loss: 2.4466 loss_prob: 1.4917 loss_thr: 0.7076 loss_db: 0.2473 2022/11/02 13:02:15 - mmengine - INFO - Epoch(train) [82][50/63] lr: 1.6367e-03 eta: 12:25:55 time: 0.5026 data_time: 0.0228 memory: 14901 loss: 2.4039 loss_prob: 1.4468 loss_thr: 0.7199 loss_db: 0.2372 2022/11/02 13:02:18 - mmengine - INFO - Epoch(train) [82][55/63] lr: 1.6367e-03 eta: 12:25:55 time: 0.4937 data_time: 0.0255 memory: 14901 loss: 2.4650 loss_prob: 1.4899 loss_thr: 0.7325 loss_db: 0.2426 2022/11/02 13:02:20 - mmengine - INFO - Epoch(train) [82][60/63] lr: 1.6367e-03 eta: 12:25:27 time: 0.4784 data_time: 0.0106 memory: 14901 loss: 2.7761 loss_prob: 1.7379 loss_thr: 0.7508 loss_db: 0.2873 2022/11/02 13:02:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:02:26 - mmengine - INFO - Epoch(train) [83][5/63] lr: 1.6569e-03 eta: 12:25:27 time: 0.7060 data_time: 0.2243 memory: 14901 loss: 2.5806 loss_prob: 1.6128 loss_thr: 0.6990 loss_db: 0.2688 2022/11/02 13:02:29 - mmengine - INFO - Epoch(train) [83][10/63] lr: 1.6569e-03 eta: 12:25:04 time: 0.7211 data_time: 0.2243 memory: 14901 loss: 2.7664 loss_prob: 1.7500 loss_thr: 0.7191 loss_db: 0.2973 2022/11/02 13:02:32 - mmengine - INFO - Epoch(train) [83][15/63] lr: 1.6569e-03 eta: 12:25:04 time: 0.5519 data_time: 0.0049 memory: 14901 loss: 2.7910 loss_prob: 1.7382 loss_thr: 0.7578 loss_db: 0.2950 2022/11/02 13:02:35 - mmengine - INFO - Epoch(train) [83][20/63] lr: 1.6569e-03 eta: 12:24:54 time: 0.6021 data_time: 0.0053 memory: 14901 loss: 2.8661 loss_prob: 1.7976 loss_thr: 0.7628 loss_db: 0.3057 2022/11/02 13:02:37 - mmengine - INFO - Epoch(train) [83][25/63] lr: 1.6569e-03 eta: 12:24:54 time: 0.5648 data_time: 0.0358 memory: 14901 loss: 2.9866 loss_prob: 1.8915 loss_thr: 0.7705 loss_db: 0.3246 2022/11/02 13:02:40 - mmengine - INFO - Epoch(train) [83][30/63] lr: 1.6569e-03 eta: 12:24:38 time: 0.5650 data_time: 0.0356 memory: 14901 loss: 2.6714 loss_prob: 1.6457 loss_thr: 0.7504 loss_db: 0.2754 2022/11/02 13:02:43 - mmengine - INFO - Epoch(train) [83][35/63] lr: 1.6569e-03 eta: 12:24:38 time: 0.5630 data_time: 0.0065 memory: 14901 loss: 2.4789 loss_prob: 1.5143 loss_thr: 0.7156 loss_db: 0.2490 2022/11/02 13:02:45 - mmengine - INFO - Epoch(train) [83][40/63] lr: 1.6569e-03 eta: 12:24:16 time: 0.5198 data_time: 0.0063 memory: 14901 loss: 2.5035 loss_prob: 1.5272 loss_thr: 0.7256 loss_db: 0.2507 2022/11/02 13:02:49 - mmengine - INFO - Epoch(train) [83][45/63] lr: 1.6569e-03 eta: 12:24:16 time: 0.6062 data_time: 0.0050 memory: 14901 loss: 2.8528 loss_prob: 1.7874 loss_thr: 0.7729 loss_db: 0.2926 2022/11/02 13:02:52 - mmengine - INFO - Epoch(train) [83][50/63] lr: 1.6569e-03 eta: 12:24:12 time: 0.6515 data_time: 0.0241 memory: 14901 loss: 2.8848 loss_prob: 1.8158 loss_thr: 0.7734 loss_db: 0.2957 2022/11/02 13:02:55 - mmengine - INFO - Epoch(train) [83][55/63] lr: 1.6569e-03 eta: 12:24:12 time: 0.5598 data_time: 0.0291 memory: 14901 loss: 2.6871 loss_prob: 1.6712 loss_thr: 0.7352 loss_db: 0.2807 2022/11/02 13:02:58 - mmengine - INFO - Epoch(train) [83][60/63] lr: 1.6569e-03 eta: 12:23:56 time: 0.5635 data_time: 0.0107 memory: 14901 loss: 2.6170 loss_prob: 1.6277 loss_thr: 0.7154 loss_db: 0.2739 2022/11/02 13:02:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:03:06 - mmengine - INFO - Epoch(train) [84][5/63] lr: 1.6771e-03 eta: 12:23:56 time: 0.9172 data_time: 0.2185 memory: 14901 loss: 2.7209 loss_prob: 1.6878 loss_thr: 0.7556 loss_db: 0.2775 2022/11/02 13:03:08 - mmengine - INFO - Epoch(train) [84][10/63] lr: 1.6771e-03 eta: 12:23:53 time: 0.8628 data_time: 0.2274 memory: 14901 loss: 2.7388 loss_prob: 1.7034 loss_thr: 0.7530 loss_db: 0.2824 2022/11/02 13:03:11 - mmengine - INFO - Epoch(train) [84][15/63] lr: 1.6771e-03 eta: 12:23:53 time: 0.5182 data_time: 0.0154 memory: 14901 loss: 2.5810 loss_prob: 1.5944 loss_thr: 0.7217 loss_db: 0.2650 2022/11/02 13:03:13 - mmengine - INFO - Epoch(train) [84][20/63] lr: 1.6771e-03 eta: 12:23:29 time: 0.5021 data_time: 0.0072 memory: 14901 loss: 2.5050 loss_prob: 1.5067 loss_thr: 0.7484 loss_db: 0.2500 2022/11/02 13:03:16 - mmengine - INFO - Epoch(train) [84][25/63] lr: 1.6771e-03 eta: 12:23:29 time: 0.5476 data_time: 0.0212 memory: 14901 loss: 2.6673 loss_prob: 1.6173 loss_thr: 0.7727 loss_db: 0.2773 2022/11/02 13:03:19 - mmengine - INFO - Epoch(train) [84][30/63] lr: 1.6771e-03 eta: 12:23:14 time: 0.5684 data_time: 0.0229 memory: 14901 loss: 2.7023 loss_prob: 1.6675 loss_thr: 0.7527 loss_db: 0.2821 2022/11/02 13:03:21 - mmengine - INFO - Epoch(train) [84][35/63] lr: 1.6771e-03 eta: 12:23:14 time: 0.5275 data_time: 0.0164 memory: 14901 loss: 2.5882 loss_prob: 1.5993 loss_thr: 0.7244 loss_db: 0.2644 2022/11/02 13:03:24 - mmengine - INFO - Epoch(train) [84][40/63] lr: 1.6771e-03 eta: 12:22:50 time: 0.5065 data_time: 0.0135 memory: 14901 loss: 2.6047 loss_prob: 1.6051 loss_thr: 0.7276 loss_db: 0.2720 2022/11/02 13:03:27 - mmengine - INFO - Epoch(train) [84][45/63] lr: 1.6771e-03 eta: 12:22:50 time: 0.5714 data_time: 0.0056 memory: 14901 loss: 2.6434 loss_prob: 1.6308 loss_thr: 0.7356 loss_db: 0.2770 2022/11/02 13:03:30 - mmengine - INFO - Epoch(train) [84][50/63] lr: 1.6771e-03 eta: 12:22:47 time: 0.6552 data_time: 0.0219 memory: 14901 loss: 2.6622 loss_prob: 1.6519 loss_thr: 0.7341 loss_db: 0.2763 2022/11/02 13:03:33 - mmengine - INFO - Epoch(train) [84][55/63] lr: 1.6771e-03 eta: 12:22:47 time: 0.5952 data_time: 0.0240 memory: 14901 loss: 2.6088 loss_prob: 1.6038 loss_thr: 0.7362 loss_db: 0.2688 2022/11/02 13:03:36 - mmengine - INFO - Epoch(train) [84][60/63] lr: 1.6771e-03 eta: 12:22:25 time: 0.5185 data_time: 0.0116 memory: 14901 loss: 2.4614 loss_prob: 1.4952 loss_thr: 0.7144 loss_db: 0.2519 2022/11/02 13:03:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:03:42 - mmengine - INFO - Epoch(train) [85][5/63] lr: 1.6973e-03 eta: 12:22:25 time: 0.6850 data_time: 0.2141 memory: 14901 loss: 2.5375 loss_prob: 1.5562 loss_thr: 0.7250 loss_db: 0.2563 2022/11/02 13:03:44 - mmengine - INFO - Epoch(train) [85][10/63] lr: 1.6973e-03 eta: 12:22:00 time: 0.6992 data_time: 0.2209 memory: 14901 loss: 2.7261 loss_prob: 1.6931 loss_thr: 0.7512 loss_db: 0.2819 2022/11/02 13:03:47 - mmengine - INFO - Epoch(train) [85][15/63] lr: 1.6973e-03 eta: 12:22:00 time: 0.5166 data_time: 0.0126 memory: 14901 loss: 2.6698 loss_prob: 1.6504 loss_thr: 0.7429 loss_db: 0.2766 2022/11/02 13:03:49 - mmengine - INFO - Epoch(train) [85][20/63] lr: 1.6973e-03 eta: 12:21:38 time: 0.5086 data_time: 0.0057 memory: 14901 loss: 2.4745 loss_prob: 1.5076 loss_thr: 0.7217 loss_db: 0.2453 2022/11/02 13:03:52 - mmengine - INFO - Epoch(train) [85][25/63] lr: 1.6973e-03 eta: 12:21:38 time: 0.4963 data_time: 0.0336 memory: 14901 loss: 2.4797 loss_prob: 1.5169 loss_thr: 0.7126 loss_db: 0.2502 2022/11/02 13:03:54 - mmengine - INFO - Epoch(train) [85][30/63] lr: 1.6973e-03 eta: 12:21:11 time: 0.4806 data_time: 0.0366 memory: 14901 loss: 2.4895 loss_prob: 1.5205 loss_thr: 0.7144 loss_db: 0.2546 2022/11/02 13:03:56 - mmengine - INFO - Epoch(train) [85][35/63] lr: 1.6973e-03 eta: 12:21:11 time: 0.4632 data_time: 0.0121 memory: 14901 loss: 2.3491 loss_prob: 1.4159 loss_thr: 0.7019 loss_db: 0.2312 2022/11/02 13:03:59 - mmengine - INFO - Epoch(train) [85][40/63] lr: 1.6973e-03 eta: 12:20:44 time: 0.4763 data_time: 0.0100 memory: 14901 loss: 2.3491 loss_prob: 1.4284 loss_thr: 0.6912 loss_db: 0.2295 2022/11/02 13:04:01 - mmengine - INFO - Epoch(train) [85][45/63] lr: 1.6973e-03 eta: 12:20:44 time: 0.4789 data_time: 0.0051 memory: 14901 loss: 2.6975 loss_prob: 1.6704 loss_thr: 0.7527 loss_db: 0.2745 2022/11/02 13:04:04 - mmengine - INFO - Epoch(train) [85][50/63] lr: 1.6973e-03 eta: 12:20:20 time: 0.4931 data_time: 0.0192 memory: 14901 loss: 2.6892 loss_prob: 1.6453 loss_thr: 0.7708 loss_db: 0.2730 2022/11/02 13:04:06 - mmengine - INFO - Epoch(train) [85][55/63] lr: 1.6973e-03 eta: 12:20:20 time: 0.4795 data_time: 0.0195 memory: 14901 loss: 2.4851 loss_prob: 1.5035 loss_thr: 0.7314 loss_db: 0.2502 2022/11/02 13:04:08 - mmengine - INFO - Epoch(train) [85][60/63] lr: 1.6973e-03 eta: 12:19:52 time: 0.4736 data_time: 0.0063 memory: 14901 loss: 2.5965 loss_prob: 1.6081 loss_thr: 0.7256 loss_db: 0.2628 2022/11/02 13:04:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:04:14 - mmengine - INFO - Epoch(train) [86][5/63] lr: 1.7175e-03 eta: 12:19:52 time: 0.6916 data_time: 0.2398 memory: 14901 loss: 2.7018 loss_prob: 1.6965 loss_thr: 0.7248 loss_db: 0.2805 2022/11/02 13:04:17 - mmengine - INFO - Epoch(train) [86][10/63] lr: 1.7175e-03 eta: 12:19:31 time: 0.7218 data_time: 0.2384 memory: 14901 loss: 2.8263 loss_prob: 1.7667 loss_thr: 0.7459 loss_db: 0.3136 2022/11/02 13:04:19 - mmengine - INFO - Epoch(train) [86][15/63] lr: 1.7175e-03 eta: 12:19:31 time: 0.4840 data_time: 0.0047 memory: 14901 loss: 2.6909 loss_prob: 1.6809 loss_thr: 0.7140 loss_db: 0.2959 2022/11/02 13:04:21 - mmengine - INFO - Epoch(train) [86][20/63] lr: 1.7175e-03 eta: 12:19:05 time: 0.4830 data_time: 0.0060 memory: 14901 loss: 2.5789 loss_prob: 1.5980 loss_thr: 0.7105 loss_db: 0.2703 2022/11/02 13:04:24 - mmengine - INFO - Epoch(train) [86][25/63] lr: 1.7175e-03 eta: 12:19:05 time: 0.4930 data_time: 0.0325 memory: 14901 loss: 2.6371 loss_prob: 1.6319 loss_thr: 0.7286 loss_db: 0.2766 2022/11/02 13:04:27 - mmengine - INFO - Epoch(train) [86][30/63] lr: 1.7175e-03 eta: 12:18:45 time: 0.5214 data_time: 0.0345 memory: 14901 loss: 2.6310 loss_prob: 1.6336 loss_thr: 0.7269 loss_db: 0.2705 2022/11/02 13:04:29 - mmengine - INFO - Epoch(train) [86][35/63] lr: 1.7175e-03 eta: 12:18:45 time: 0.5198 data_time: 0.0142 memory: 14901 loss: 2.5838 loss_prob: 1.5884 loss_thr: 0.7324 loss_db: 0.2629 2022/11/02 13:04:32 - mmengine - INFO - Epoch(train) [86][40/63] lr: 1.7175e-03 eta: 12:18:23 time: 0.5166 data_time: 0.0112 memory: 14901 loss: 2.6518 loss_prob: 1.6424 loss_thr: 0.7378 loss_db: 0.2716 2022/11/02 13:04:34 - mmengine - INFO - Epoch(train) [86][45/63] lr: 1.7175e-03 eta: 12:18:23 time: 0.5178 data_time: 0.0078 memory: 14901 loss: 2.7528 loss_prob: 1.7295 loss_thr: 0.7362 loss_db: 0.2872 2022/11/02 13:04:37 - mmengine - INFO - Epoch(train) [86][50/63] lr: 1.7175e-03 eta: 12:18:06 time: 0.5473 data_time: 0.0235 memory: 14901 loss: 2.8617 loss_prob: 1.8190 loss_thr: 0.7372 loss_db: 0.3054 2022/11/02 13:04:40 - mmengine - INFO - Epoch(train) [86][55/63] lr: 1.7175e-03 eta: 12:18:06 time: 0.5579 data_time: 0.0231 memory: 14901 loss: 2.8344 loss_prob: 1.7945 loss_thr: 0.7366 loss_db: 0.3033 2022/11/02 13:04:42 - mmengine - INFO - Epoch(train) [86][60/63] lr: 1.7175e-03 eta: 12:17:43 time: 0.4984 data_time: 0.0070 memory: 14901 loss: 2.7241 loss_prob: 1.6934 loss_thr: 0.7433 loss_db: 0.2874 2022/11/02 13:04:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:04:49 - mmengine - INFO - Epoch(train) [87][5/63] lr: 1.7376e-03 eta: 12:17:43 time: 0.7113 data_time: 0.2018 memory: 14901 loss: 2.8757 loss_prob: 1.8155 loss_thr: 0.7552 loss_db: 0.3050 2022/11/02 13:04:51 - mmengine - INFO - Epoch(train) [87][10/63] lr: 1.7376e-03 eta: 12:17:24 time: 0.7367 data_time: 0.2018 memory: 14901 loss: 2.7945 loss_prob: 1.7490 loss_thr: 0.7533 loss_db: 0.2921 2022/11/02 13:04:54 - mmengine - INFO - Epoch(train) [87][15/63] lr: 1.7376e-03 eta: 12:17:24 time: 0.5037 data_time: 0.0054 memory: 14901 loss: 2.5974 loss_prob: 1.6087 loss_thr: 0.7267 loss_db: 0.2620 2022/11/02 13:04:56 - mmengine - INFO - Epoch(train) [87][20/63] lr: 1.7376e-03 eta: 12:17:01 time: 0.5018 data_time: 0.0057 memory: 14901 loss: 2.6689 loss_prob: 1.6680 loss_thr: 0.7278 loss_db: 0.2732 2022/11/02 13:04:58 - mmengine - INFO - Epoch(train) [87][25/63] lr: 1.7376e-03 eta: 12:17:01 time: 0.4814 data_time: 0.0158 memory: 14901 loss: 2.6789 loss_prob: 1.6678 loss_thr: 0.7339 loss_db: 0.2772 2022/11/02 13:05:01 - mmengine - INFO - Epoch(train) [87][30/63] lr: 1.7376e-03 eta: 12:16:35 time: 0.4808 data_time: 0.0318 memory: 14901 loss: 3.0227 loss_prob: 1.9247 loss_thr: 0.7605 loss_db: 0.3375 2022/11/02 13:05:03 - mmengine - INFO - Epoch(train) [87][35/63] lr: 1.7376e-03 eta: 12:16:35 time: 0.4854 data_time: 0.0210 memory: 14901 loss: 3.0585 loss_prob: 1.9639 loss_thr: 0.7527 loss_db: 0.3419 2022/11/02 13:05:06 - mmengine - INFO - Epoch(train) [87][40/63] lr: 1.7376e-03 eta: 12:16:12 time: 0.4954 data_time: 0.0048 memory: 14901 loss: 2.6513 loss_prob: 1.6603 loss_thr: 0.7203 loss_db: 0.2707 2022/11/02 13:05:09 - mmengine - INFO - Epoch(train) [87][45/63] lr: 1.7376e-03 eta: 12:16:12 time: 0.5473 data_time: 0.0064 memory: 14901 loss: 2.6424 loss_prob: 1.6326 loss_thr: 0.7387 loss_db: 0.2711 2022/11/02 13:05:11 - mmengine - INFO - Epoch(train) [87][50/63] lr: 1.7376e-03 eta: 12:15:56 time: 0.5533 data_time: 0.0193 memory: 14901 loss: 2.6242 loss_prob: 1.5945 loss_thr: 0.7552 loss_db: 0.2745 2022/11/02 13:05:14 - mmengine - INFO - Epoch(train) [87][55/63] lr: 1.7376e-03 eta: 12:15:56 time: 0.5081 data_time: 0.0256 memory: 14901 loss: 2.5956 loss_prob: 1.5717 loss_thr: 0.7606 loss_db: 0.2632 2022/11/02 13:05:17 - mmengine - INFO - Epoch(train) [87][60/63] lr: 1.7376e-03 eta: 12:15:38 time: 0.5401 data_time: 0.0127 memory: 14901 loss: 2.4274 loss_prob: 1.4680 loss_thr: 0.7236 loss_db: 0.2358 2022/11/02 13:05:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:05:23 - mmengine - INFO - Epoch(train) [88][5/63] lr: 1.7578e-03 eta: 12:15:38 time: 0.7687 data_time: 0.2395 memory: 14901 loss: 2.3475 loss_prob: 1.4041 loss_thr: 0.7149 loss_db: 0.2284 2022/11/02 13:05:26 - mmengine - INFO - Epoch(train) [88][10/63] lr: 1.7578e-03 eta: 12:15:31 time: 0.8260 data_time: 0.2406 memory: 14901 loss: 2.3657 loss_prob: 1.4262 loss_thr: 0.7061 loss_db: 0.2334 2022/11/02 13:05:30 - mmengine - INFO - Epoch(train) [88][15/63] lr: 1.7578e-03 eta: 12:15:31 time: 0.6787 data_time: 0.0065 memory: 14901 loss: 2.3311 loss_prob: 1.4085 loss_thr: 0.6917 loss_db: 0.2308 2022/11/02 13:05:33 - mmengine - INFO - Epoch(train) [88][20/63] lr: 1.7578e-03 eta: 12:15:28 time: 0.6579 data_time: 0.0048 memory: 14901 loss: 2.4404 loss_prob: 1.4848 loss_thr: 0.7124 loss_db: 0.2431 2022/11/02 13:05:36 - mmengine - INFO - Epoch(train) [88][25/63] lr: 1.7578e-03 eta: 12:15:28 time: 0.6340 data_time: 0.0272 memory: 14901 loss: 2.6023 loss_prob: 1.5807 loss_thr: 0.7618 loss_db: 0.2598 2022/11/02 13:05:39 - mmengine - INFO - Epoch(train) [88][30/63] lr: 1.7578e-03 eta: 12:15:19 time: 0.6053 data_time: 0.0357 memory: 14901 loss: 2.6235 loss_prob: 1.5912 loss_thr: 0.7742 loss_db: 0.2580 2022/11/02 13:05:42 - mmengine - INFO - Epoch(train) [88][35/63] lr: 1.7578e-03 eta: 12:15:19 time: 0.5242 data_time: 0.0177 memory: 14901 loss: 2.6133 loss_prob: 1.5997 loss_thr: 0.7514 loss_db: 0.2621 2022/11/02 13:05:44 - mmengine - INFO - Epoch(train) [88][40/63] lr: 1.7578e-03 eta: 12:14:59 time: 0.5261 data_time: 0.0092 memory: 14901 loss: 2.6795 loss_prob: 1.6432 loss_thr: 0.7614 loss_db: 0.2749 2022/11/02 13:05:47 - mmengine - INFO - Epoch(train) [88][45/63] lr: 1.7578e-03 eta: 12:14:59 time: 0.5390 data_time: 0.0047 memory: 14901 loss: 2.7031 loss_prob: 1.6537 loss_thr: 0.7742 loss_db: 0.2751 2022/11/02 13:05:50 - mmengine - INFO - Epoch(train) [88][50/63] lr: 1.7578e-03 eta: 12:14:49 time: 0.5986 data_time: 0.0173 memory: 14901 loss: 2.5914 loss_prob: 1.5786 loss_thr: 0.7517 loss_db: 0.2610 2022/11/02 13:05:55 - mmengine - INFO - Epoch(train) [88][55/63] lr: 1.7578e-03 eta: 12:14:49 time: 0.7785 data_time: 0.0365 memory: 14901 loss: 2.5725 loss_prob: 1.5756 loss_thr: 0.7324 loss_db: 0.2645 2022/11/02 13:05:58 - mmengine - INFO - Epoch(train) [88][60/63] lr: 1.7578e-03 eta: 12:15:03 time: 0.7853 data_time: 0.0244 memory: 14901 loss: 2.5988 loss_prob: 1.5971 loss_thr: 0.7354 loss_db: 0.2663 2022/11/02 13:05:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:06:05 - mmengine - INFO - Epoch(train) [89][5/63] lr: 1.7780e-03 eta: 12:15:03 time: 0.8029 data_time: 0.2179 memory: 14901 loss: 2.5000 loss_prob: 1.5588 loss_thr: 0.6884 loss_db: 0.2528 2022/11/02 13:06:07 - mmengine - INFO - Epoch(train) [89][10/63] lr: 1.7780e-03 eta: 12:14:58 time: 0.8480 data_time: 0.2176 memory: 14901 loss: 2.6643 loss_prob: 1.6714 loss_thr: 0.7223 loss_db: 0.2706 2022/11/02 13:06:10 - mmengine - INFO - Epoch(train) [89][15/63] lr: 1.7780e-03 eta: 12:14:58 time: 0.5336 data_time: 0.0053 memory: 14901 loss: 2.7865 loss_prob: 1.7659 loss_thr: 0.7268 loss_db: 0.2938 2022/11/02 13:06:12 - mmengine - INFO - Epoch(train) [89][20/63] lr: 1.7780e-03 eta: 12:14:36 time: 0.5005 data_time: 0.0044 memory: 14901 loss: 2.8106 loss_prob: 1.7790 loss_thr: 0.7310 loss_db: 0.3006 2022/11/02 13:06:15 - mmengine - INFO - Epoch(train) [89][25/63] lr: 1.7780e-03 eta: 12:14:36 time: 0.4897 data_time: 0.0176 memory: 14901 loss: 2.7177 loss_prob: 1.6946 loss_thr: 0.7419 loss_db: 0.2812 2022/11/02 13:06:17 - mmengine - INFO - Epoch(train) [89][30/63] lr: 1.7780e-03 eta: 12:14:10 time: 0.4768 data_time: 0.0309 memory: 14901 loss: 2.5523 loss_prob: 1.5865 loss_thr: 0.7067 loss_db: 0.2591 2022/11/02 13:06:20 - mmengine - INFO - Epoch(train) [89][35/63] lr: 1.7780e-03 eta: 12:14:10 time: 0.5078 data_time: 0.0181 memory: 14901 loss: 2.6324 loss_prob: 1.6384 loss_thr: 0.7177 loss_db: 0.2764 2022/11/02 13:06:22 - mmengine - INFO - Epoch(train) [89][40/63] lr: 1.7780e-03 eta: 12:13:49 time: 0.5123 data_time: 0.0049 memory: 14901 loss: 2.7679 loss_prob: 1.7194 loss_thr: 0.7513 loss_db: 0.2972 2022/11/02 13:06:25 - mmengine - INFO - Epoch(train) [89][45/63] lr: 1.7780e-03 eta: 12:13:49 time: 0.4993 data_time: 0.0060 memory: 14901 loss: 2.7343 loss_prob: 1.6764 loss_thr: 0.7724 loss_db: 0.2855 2022/11/02 13:06:28 - mmengine - INFO - Epoch(train) [89][50/63] lr: 1.7780e-03 eta: 12:13:31 time: 0.5317 data_time: 0.0134 memory: 14901 loss: 2.6689 loss_prob: 1.6371 loss_thr: 0.7595 loss_db: 0.2723 2022/11/02 13:06:30 - mmengine - INFO - Epoch(train) [89][55/63] lr: 1.7780e-03 eta: 12:13:31 time: 0.5275 data_time: 0.0268 memory: 14901 loss: 2.5603 loss_prob: 1.5751 loss_thr: 0.7301 loss_db: 0.2550 2022/11/02 13:06:33 - mmengine - INFO - Epoch(train) [89][60/63] lr: 1.7780e-03 eta: 12:13:08 time: 0.4977 data_time: 0.0202 memory: 14901 loss: 2.5005 loss_prob: 1.5213 loss_thr: 0.7323 loss_db: 0.2469 2022/11/02 13:06:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:06:39 - mmengine - INFO - Epoch(train) [90][5/63] lr: 1.7982e-03 eta: 12:13:08 time: 0.7400 data_time: 0.2119 memory: 14901 loss: 2.5863 loss_prob: 1.5927 loss_thr: 0.7284 loss_db: 0.2653 2022/11/02 13:06:42 - mmengine - INFO - Epoch(train) [90][10/63] lr: 1.7982e-03 eta: 12:12:54 time: 0.7718 data_time: 0.2107 memory: 14901 loss: 2.7174 loss_prob: 1.6781 loss_thr: 0.7606 loss_db: 0.2787 2022/11/02 13:06:44 - mmengine - INFO - Epoch(train) [90][15/63] lr: 1.7982e-03 eta: 12:12:54 time: 0.5001 data_time: 0.0122 memory: 14901 loss: 2.6088 loss_prob: 1.6129 loss_thr: 0.7296 loss_db: 0.2663 2022/11/02 13:06:46 - mmengine - INFO - Epoch(train) [90][20/63] lr: 1.7982e-03 eta: 12:12:29 time: 0.4748 data_time: 0.0122 memory: 14901 loss: 2.5135 loss_prob: 1.5489 loss_thr: 0.7094 loss_db: 0.2552 2022/11/02 13:06:49 - mmengine - INFO - Epoch(train) [90][25/63] lr: 1.7982e-03 eta: 12:12:29 time: 0.5013 data_time: 0.0204 memory: 14901 loss: 2.5498 loss_prob: 1.5746 loss_thr: 0.7171 loss_db: 0.2580 2022/11/02 13:06:51 - mmengine - INFO - Epoch(train) [90][30/63] lr: 1.7982e-03 eta: 12:12:07 time: 0.5028 data_time: 0.0275 memory: 14901 loss: 2.5626 loss_prob: 1.5814 loss_thr: 0.7227 loss_db: 0.2586 2022/11/02 13:06:54 - mmengine - INFO - Epoch(train) [90][35/63] lr: 1.7982e-03 eta: 12:12:07 time: 0.4728 data_time: 0.0133 memory: 14901 loss: 2.6067 loss_prob: 1.6041 loss_thr: 0.7434 loss_db: 0.2592 2022/11/02 13:06:56 - mmengine - INFO - Epoch(train) [90][40/63] lr: 1.7982e-03 eta: 12:11:46 time: 0.5075 data_time: 0.0265 memory: 14901 loss: 2.6445 loss_prob: 1.6342 loss_thr: 0.7451 loss_db: 0.2652 2022/11/02 13:06:59 - mmengine - INFO - Epoch(train) [90][45/63] lr: 1.7982e-03 eta: 12:11:46 time: 0.5096 data_time: 0.0259 memory: 14901 loss: 2.5746 loss_prob: 1.5904 loss_thr: 0.7216 loss_db: 0.2625 2022/11/02 13:07:01 - mmengine - INFO - Epoch(train) [90][50/63] lr: 1.7982e-03 eta: 12:11:21 time: 0.4807 data_time: 0.0164 memory: 14901 loss: 2.5517 loss_prob: 1.5731 loss_thr: 0.7190 loss_db: 0.2596 2022/11/02 13:07:04 - mmengine - INFO - Epoch(train) [90][55/63] lr: 1.7982e-03 eta: 12:11:21 time: 0.4779 data_time: 0.0189 memory: 14901 loss: 2.6046 loss_prob: 1.6224 loss_thr: 0.7137 loss_db: 0.2685 2022/11/02 13:07:06 - mmengine - INFO - Epoch(train) [90][60/63] lr: 1.7982e-03 eta: 12:10:57 time: 0.4764 data_time: 0.0107 memory: 14901 loss: 2.5012 loss_prob: 1.5410 loss_thr: 0.7080 loss_db: 0.2522 2022/11/02 13:07:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:07:13 - mmengine - INFO - Epoch(train) [91][5/63] lr: 1.8184e-03 eta: 12:10:57 time: 0.8173 data_time: 0.3313 memory: 14901 loss: 2.3552 loss_prob: 1.4107 loss_thr: 0.7177 loss_db: 0.2267 2022/11/02 13:07:16 - mmengine - INFO - Epoch(train) [91][10/63] lr: 1.8184e-03 eta: 12:10:47 time: 0.8046 data_time: 0.3278 memory: 14901 loss: 2.2908 loss_prob: 1.3636 loss_thr: 0.7080 loss_db: 0.2192 2022/11/02 13:07:18 - mmengine - INFO - Epoch(train) [91][15/63] lr: 1.8184e-03 eta: 12:10:47 time: 0.4857 data_time: 0.0048 memory: 14901 loss: 2.3060 loss_prob: 1.3944 loss_thr: 0.6866 loss_db: 0.2250 2022/11/02 13:07:21 - mmengine - INFO - Epoch(train) [91][20/63] lr: 1.8184e-03 eta: 12:10:25 time: 0.4955 data_time: 0.0056 memory: 14901 loss: 2.4536 loss_prob: 1.5095 loss_thr: 0.6985 loss_db: 0.2456 2022/11/02 13:07:23 - mmengine - INFO - Epoch(train) [91][25/63] lr: 1.8184e-03 eta: 12:10:25 time: 0.5069 data_time: 0.0266 memory: 14901 loss: 2.3580 loss_prob: 1.4376 loss_thr: 0.6852 loss_db: 0.2352 2022/11/02 13:07:26 - mmengine - INFO - Epoch(train) [91][30/63] lr: 1.8184e-03 eta: 12:10:05 time: 0.5191 data_time: 0.0261 memory: 14901 loss: 2.4565 loss_prob: 1.5049 loss_thr: 0.7062 loss_db: 0.2454 2022/11/02 13:07:28 - mmengine - INFO - Epoch(train) [91][35/63] lr: 1.8184e-03 eta: 12:10:05 time: 0.5238 data_time: 0.0098 memory: 14901 loss: 2.5172 loss_prob: 1.5463 loss_thr: 0.7211 loss_db: 0.2497 2022/11/02 13:07:31 - mmengine - INFO - Epoch(train) [91][40/63] lr: 1.8184e-03 eta: 12:09:42 time: 0.4897 data_time: 0.0099 memory: 14901 loss: 2.4102 loss_prob: 1.4432 loss_thr: 0.7318 loss_db: 0.2352 2022/11/02 13:07:33 - mmengine - INFO - Epoch(train) [91][45/63] lr: 1.8184e-03 eta: 12:09:42 time: 0.4833 data_time: 0.0109 memory: 14901 loss: 2.3824 loss_prob: 1.4231 loss_thr: 0.7251 loss_db: 0.2342 2022/11/02 13:07:36 - mmengine - INFO - Epoch(train) [91][50/63] lr: 1.8184e-03 eta: 12:09:20 time: 0.4964 data_time: 0.0269 memory: 14901 loss: 2.4724 loss_prob: 1.5102 loss_thr: 0.7126 loss_db: 0.2496 2022/11/02 13:07:38 - mmengine - INFO - Epoch(train) [91][55/63] lr: 1.8184e-03 eta: 12:09:20 time: 0.4710 data_time: 0.0210 memory: 14901 loss: 2.4659 loss_prob: 1.5044 loss_thr: 0.7153 loss_db: 0.2462 2022/11/02 13:07:40 - mmengine - INFO - Epoch(train) [91][60/63] lr: 1.8184e-03 eta: 12:08:53 time: 0.4591 data_time: 0.0063 memory: 14901 loss: 2.5264 loss_prob: 1.5485 loss_thr: 0.7213 loss_db: 0.2565 2022/11/02 13:07:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:07:47 - mmengine - INFO - Epoch(train) [92][5/63] lr: 1.8385e-03 eta: 12:08:53 time: 0.7885 data_time: 0.2937 memory: 14901 loss: 2.7824 loss_prob: 1.7497 loss_thr: 0.7388 loss_db: 0.2939 2022/11/02 13:07:52 - mmengine - INFO - Epoch(train) [92][10/63] lr: 1.8385e-03 eta: 12:09:09 time: 1.0109 data_time: 0.2964 memory: 14901 loss: 2.7339 loss_prob: 1.7153 loss_thr: 0.7335 loss_db: 0.2851 2022/11/02 13:07:55 - mmengine - INFO - Epoch(train) [92][15/63] lr: 1.8385e-03 eta: 12:09:09 time: 0.7471 data_time: 0.0075 memory: 14901 loss: 2.6433 loss_prob: 1.6362 loss_thr: 0.7343 loss_db: 0.2728 2022/11/02 13:07:58 - mmengine - INFO - Epoch(train) [92][20/63] lr: 1.8385e-03 eta: 12:09:03 time: 0.6295 data_time: 0.0054 memory: 14901 loss: 2.7112 loss_prob: 1.6672 loss_thr: 0.7588 loss_db: 0.2853 2022/11/02 13:08:01 - mmengine - INFO - Epoch(train) [92][25/63] lr: 1.8385e-03 eta: 12:09:03 time: 0.6300 data_time: 0.0310 memory: 14901 loss: 2.6483 loss_prob: 1.6218 loss_thr: 0.7467 loss_db: 0.2797 2022/11/02 13:08:04 - mmengine - INFO - Epoch(train) [92][30/63] lr: 1.8385e-03 eta: 12:08:55 time: 0.6099 data_time: 0.0317 memory: 14901 loss: 2.5859 loss_prob: 1.6025 loss_thr: 0.7148 loss_db: 0.2686 2022/11/02 13:08:07 - mmengine - INFO - Epoch(train) [92][35/63] lr: 1.8385e-03 eta: 12:08:55 time: 0.5491 data_time: 0.0077 memory: 14901 loss: 2.6866 loss_prob: 1.6877 loss_thr: 0.7202 loss_db: 0.2788 2022/11/02 13:08:10 - mmengine - INFO - Epoch(train) [92][40/63] lr: 1.8385e-03 eta: 12:08:44 time: 0.5905 data_time: 0.0067 memory: 14901 loss: 2.6143 loss_prob: 1.6219 loss_thr: 0.7239 loss_db: 0.2684 2022/11/02 13:08:13 - mmengine - INFO - Epoch(train) [92][45/63] lr: 1.8385e-03 eta: 12:08:44 time: 0.6159 data_time: 0.0074 memory: 14901 loss: 2.6275 loss_prob: 1.6255 loss_thr: 0.7313 loss_db: 0.2707 2022/11/02 13:08:15 - mmengine - INFO - Epoch(train) [92][50/63] lr: 1.8385e-03 eta: 12:08:29 time: 0.5476 data_time: 0.0227 memory: 14901 loss: 2.6902 loss_prob: 1.6739 loss_thr: 0.7376 loss_db: 0.2787 2022/11/02 13:08:19 - mmengine - INFO - Epoch(train) [92][55/63] lr: 1.8385e-03 eta: 12:08:29 time: 0.5811 data_time: 0.0223 memory: 14901 loss: 2.5672 loss_prob: 1.5863 loss_thr: 0.7256 loss_db: 0.2554 2022/11/02 13:08:22 - mmengine - INFO - Epoch(train) [92][60/63] lr: 1.8385e-03 eta: 12:08:24 time: 0.6360 data_time: 0.0078 memory: 14901 loss: 2.5613 loss_prob: 1.5798 loss_thr: 0.7270 loss_db: 0.2545 2022/11/02 13:08:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:08:31 - mmengine - INFO - Epoch(train) [93][5/63] lr: 1.8587e-03 eta: 12:08:24 time: 0.9887 data_time: 0.2632 memory: 14901 loss: 2.5019 loss_prob: 1.5315 loss_thr: 0.7147 loss_db: 0.2557 2022/11/02 13:08:34 - mmengine - INFO - Epoch(train) [93][10/63] lr: 1.8587e-03 eta: 12:08:40 time: 1.0161 data_time: 0.2629 memory: 14901 loss: 2.3364 loss_prob: 1.4064 loss_thr: 0.6960 loss_db: 0.2340 2022/11/02 13:08:37 - mmengine - INFO - Epoch(train) [93][15/63] lr: 1.8587e-03 eta: 12:08:40 time: 0.6368 data_time: 0.0078 memory: 14901 loss: 2.2230 loss_prob: 1.3100 loss_thr: 0.6973 loss_db: 0.2157 2022/11/02 13:08:39 - mmengine - INFO - Epoch(train) [93][20/63] lr: 1.8587e-03 eta: 12:08:27 time: 0.5744 data_time: 0.0088 memory: 14901 loss: 2.4929 loss_prob: 1.5083 loss_thr: 0.7326 loss_db: 0.2520 2022/11/02 13:08:42 - mmengine - INFO - Epoch(train) [93][25/63] lr: 1.8587e-03 eta: 12:08:27 time: 0.5178 data_time: 0.0101 memory: 14901 loss: 2.5283 loss_prob: 1.5447 loss_thr: 0.7278 loss_db: 0.2558 2022/11/02 13:08:45 - mmengine - INFO - Epoch(train) [93][30/63] lr: 1.8587e-03 eta: 12:08:12 time: 0.5540 data_time: 0.0364 memory: 14901 loss: 2.4871 loss_prob: 1.5235 loss_thr: 0.7101 loss_db: 0.2535 2022/11/02 13:08:48 - mmengine - INFO - Epoch(train) [93][35/63] lr: 1.8587e-03 eta: 12:08:12 time: 0.5440 data_time: 0.0329 memory: 14901 loss: 2.5873 loss_prob: 1.5937 loss_thr: 0.7270 loss_db: 0.2666 2022/11/02 13:08:50 - mmengine - INFO - Epoch(train) [93][40/63] lr: 1.8587e-03 eta: 12:07:51 time: 0.5018 data_time: 0.0047 memory: 14901 loss: 2.6496 loss_prob: 1.6339 loss_thr: 0.7449 loss_db: 0.2708 2022/11/02 13:08:52 - mmengine - INFO - Epoch(train) [93][45/63] lr: 1.8587e-03 eta: 12:07:51 time: 0.4657 data_time: 0.0075 memory: 14901 loss: 2.6505 loss_prob: 1.6432 loss_thr: 0.7350 loss_db: 0.2723 2022/11/02 13:08:55 - mmengine - INFO - Epoch(train) [93][50/63] lr: 1.8587e-03 eta: 12:07:33 time: 0.5246 data_time: 0.0244 memory: 14901 loss: 2.4871 loss_prob: 1.5313 loss_thr: 0.7003 loss_db: 0.2555 2022/11/02 13:08:58 - mmengine - INFO - Epoch(train) [93][55/63] lr: 1.8587e-03 eta: 12:07:33 time: 0.5347 data_time: 0.0218 memory: 14901 loss: 2.5251 loss_prob: 1.5709 loss_thr: 0.6908 loss_db: 0.2634 2022/11/02 13:09:00 - mmengine - INFO - Epoch(train) [93][60/63] lr: 1.8587e-03 eta: 12:07:08 time: 0.4726 data_time: 0.0049 memory: 14901 loss: 2.6057 loss_prob: 1.6188 loss_thr: 0.7167 loss_db: 0.2702 2022/11/02 13:09:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:09:06 - mmengine - INFO - Epoch(train) [94][5/63] lr: 1.8789e-03 eta: 12:07:08 time: 0.6957 data_time: 0.1964 memory: 14901 loss: 2.4105 loss_prob: 1.4464 loss_thr: 0.7236 loss_db: 0.2405 2022/11/02 13:09:09 - mmengine - INFO - Epoch(train) [94][10/63] lr: 1.8789e-03 eta: 12:06:59 time: 0.8019 data_time: 0.2080 memory: 14901 loss: 2.3791 loss_prob: 1.4324 loss_thr: 0.7145 loss_db: 0.2322 2022/11/02 13:09:11 - mmengine - INFO - Epoch(train) [94][15/63] lr: 1.8789e-03 eta: 12:06:59 time: 0.5489 data_time: 0.0165 memory: 14901 loss: 2.4514 loss_prob: 1.4850 loss_thr: 0.7269 loss_db: 0.2394 2022/11/02 13:09:14 - mmengine - INFO - Epoch(train) [94][20/63] lr: 1.8789e-03 eta: 12:06:36 time: 0.4867 data_time: 0.0051 memory: 14901 loss: 2.4382 loss_prob: 1.4773 loss_thr: 0.7180 loss_db: 0.2429 2022/11/02 13:09:17 - mmengine - INFO - Epoch(train) [94][25/63] lr: 1.8789e-03 eta: 12:06:36 time: 0.5414 data_time: 0.0198 memory: 14901 loss: 2.4987 loss_prob: 1.5087 loss_thr: 0.7369 loss_db: 0.2531 2022/11/02 13:09:19 - mmengine - INFO - Epoch(train) [94][30/63] lr: 1.8789e-03 eta: 12:06:18 time: 0.5220 data_time: 0.0203 memory: 14901 loss: 2.5334 loss_prob: 1.5396 loss_thr: 0.7365 loss_db: 0.2573 2022/11/02 13:09:22 - mmengine - INFO - Epoch(train) [94][35/63] lr: 1.8789e-03 eta: 12:06:18 time: 0.4972 data_time: 0.0189 memory: 14901 loss: 2.8395 loss_prob: 1.7837 loss_thr: 0.7600 loss_db: 0.2958 2022/11/02 13:09:24 - mmengine - INFO - Epoch(train) [94][40/63] lr: 1.8789e-03 eta: 12:05:55 time: 0.4872 data_time: 0.0179 memory: 14901 loss: 3.1340 loss_prob: 1.9945 loss_thr: 0.8107 loss_db: 0.3288 2022/11/02 13:09:26 - mmengine - INFO - Epoch(train) [94][45/63] lr: 1.8789e-03 eta: 12:05:55 time: 0.4713 data_time: 0.0044 memory: 14901 loss: 2.9372 loss_prob: 1.8504 loss_thr: 0.7875 loss_db: 0.2993 2022/11/02 13:09:29 - mmengine - INFO - Epoch(train) [94][50/63] lr: 1.8789e-03 eta: 12:05:32 time: 0.4796 data_time: 0.0145 memory: 14901 loss: 2.7100 loss_prob: 1.6971 loss_thr: 0.7322 loss_db: 0.2807 2022/11/02 13:09:31 - mmengine - INFO - Epoch(train) [94][55/63] lr: 1.8789e-03 eta: 12:05:32 time: 0.4988 data_time: 0.0191 memory: 14901 loss: 2.7712 loss_prob: 1.7223 loss_thr: 0.7462 loss_db: 0.3028 2022/11/02 13:09:34 - mmengine - INFO - Epoch(train) [94][60/63] lr: 1.8789e-03 eta: 12:05:09 time: 0.4853 data_time: 0.0132 memory: 14901 loss: 3.0663 loss_prob: 1.9575 loss_thr: 0.7608 loss_db: 0.3480 2022/11/02 13:09:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:09:39 - mmengine - INFO - Epoch(train) [95][5/63] lr: 1.8991e-03 eta: 12:05:09 time: 0.6509 data_time: 0.1926 memory: 14901 loss: 3.2111 loss_prob: 2.0301 loss_thr: 0.8307 loss_db: 0.3503 2022/11/02 13:09:42 - mmengine - INFO - Epoch(train) [95][10/63] lr: 1.8991e-03 eta: 12:04:53 time: 0.7463 data_time: 0.1924 memory: 14901 loss: 3.2160 loss_prob: 2.0317 loss_thr: 0.8214 loss_db: 0.3629 2022/11/02 13:09:45 - mmengine - INFO - Epoch(train) [95][15/63] lr: 1.8991e-03 eta: 12:04:53 time: 0.5488 data_time: 0.0070 memory: 14901 loss: 3.0939 loss_prob: 1.9807 loss_thr: 0.7609 loss_db: 0.3522 2022/11/02 13:09:47 - mmengine - INFO - Epoch(train) [95][20/63] lr: 1.8991e-03 eta: 12:04:31 time: 0.4854 data_time: 0.0068 memory: 14901 loss: 2.8518 loss_prob: 1.8059 loss_thr: 0.7322 loss_db: 0.3137 2022/11/02 13:09:50 - mmengine - INFO - Epoch(train) [95][25/63] lr: 1.8991e-03 eta: 12:04:31 time: 0.5042 data_time: 0.0080 memory: 14901 loss: 2.9305 loss_prob: 1.8512 loss_thr: 0.7632 loss_db: 0.3160 2022/11/02 13:09:52 - mmengine - INFO - Epoch(train) [95][30/63] lr: 1.8991e-03 eta: 12:04:13 time: 0.5226 data_time: 0.0366 memory: 14901 loss: 2.8911 loss_prob: 1.8244 loss_thr: 0.7607 loss_db: 0.3060 2022/11/02 13:09:55 - mmengine - INFO - Epoch(train) [95][35/63] lr: 1.8991e-03 eta: 12:04:13 time: 0.4984 data_time: 0.0343 memory: 14901 loss: 2.5966 loss_prob: 1.6104 loss_thr: 0.7257 loss_db: 0.2604 2022/11/02 13:09:57 - mmengine - INFO - Epoch(train) [95][40/63] lr: 1.8991e-03 eta: 12:03:50 time: 0.4816 data_time: 0.0046 memory: 14901 loss: 2.7627 loss_prob: 1.7335 loss_thr: 0.7445 loss_db: 0.2847 2022/11/02 13:10:00 - mmengine - INFO - Epoch(train) [95][45/63] lr: 1.8991e-03 eta: 12:03:50 time: 0.4865 data_time: 0.0070 memory: 14901 loss: 2.6894 loss_prob: 1.6567 loss_thr: 0.7617 loss_db: 0.2711 2022/11/02 13:10:02 - mmengine - INFO - Epoch(train) [95][50/63] lr: 1.8991e-03 eta: 12:03:28 time: 0.4907 data_time: 0.0214 memory: 14901 loss: 2.3878 loss_prob: 1.4325 loss_thr: 0.7237 loss_db: 0.2316 2022/11/02 13:10:04 - mmengine - INFO - Epoch(train) [95][55/63] lr: 1.8991e-03 eta: 12:03:28 time: 0.4838 data_time: 0.0300 memory: 14901 loss: 2.3895 loss_prob: 1.4623 loss_thr: 0.6881 loss_db: 0.2390 2022/11/02 13:10:07 - mmengine - INFO - Epoch(train) [95][60/63] lr: 1.8991e-03 eta: 12:03:08 time: 0.5070 data_time: 0.0158 memory: 14901 loss: 2.3897 loss_prob: 1.4635 loss_thr: 0.6847 loss_db: 0.2416 2022/11/02 13:10:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:10:13 - mmengine - INFO - Epoch(train) [96][5/63] lr: 1.9193e-03 eta: 12:03:08 time: 0.7126 data_time: 0.2207 memory: 14901 loss: 2.3866 loss_prob: 1.4752 loss_thr: 0.6721 loss_db: 0.2392 2022/11/02 13:10:15 - mmengine - INFO - Epoch(train) [96][10/63] lr: 1.9193e-03 eta: 12:02:46 time: 0.6877 data_time: 0.2210 memory: 14901 loss: 2.5783 loss_prob: 1.6130 loss_thr: 0.6949 loss_db: 0.2704 2022/11/02 13:10:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:10:18 - mmengine - INFO - Epoch(train) [96][15/63] lr: 1.9193e-03 eta: 12:02:46 time: 0.5059 data_time: 0.0049 memory: 14901 loss: 2.5858 loss_prob: 1.5884 loss_thr: 0.7300 loss_db: 0.2674 2022/11/02 13:10:21 - mmengine - INFO - Epoch(train) [96][20/63] lr: 1.9193e-03 eta: 12:02:30 time: 0.5427 data_time: 0.0076 memory: 14901 loss: 2.6342 loss_prob: 1.6267 loss_thr: 0.7391 loss_db: 0.2684 2022/11/02 13:10:24 - mmengine - INFO - Epoch(train) [96][25/63] lr: 1.9193e-03 eta: 12:02:30 time: 0.5967 data_time: 0.0428 memory: 14901 loss: 2.5940 loss_prob: 1.6090 loss_thr: 0.7225 loss_db: 0.2625 2022/11/02 13:10:28 - mmengine - INFO - Epoch(train) [96][30/63] lr: 1.9193e-03 eta: 12:02:30 time: 0.6741 data_time: 0.0398 memory: 14901 loss: 2.4620 loss_prob: 1.5065 loss_thr: 0.7078 loss_db: 0.2478 2022/11/02 13:10:30 - mmengine - INFO - Epoch(train) [96][35/63] lr: 1.9193e-03 eta: 12:02:30 time: 0.5827 data_time: 0.0045 memory: 14901 loss: 2.5307 loss_prob: 1.5448 loss_thr: 0.7289 loss_db: 0.2570 2022/11/02 13:10:33 - mmengine - INFO - Epoch(train) [96][40/63] lr: 1.9193e-03 eta: 12:02:16 time: 0.5553 data_time: 0.0050 memory: 14901 loss: 2.6976 loss_prob: 1.6774 loss_thr: 0.7417 loss_db: 0.2785 2022/11/02 13:10:36 - mmengine - INFO - Epoch(train) [96][45/63] lr: 1.9193e-03 eta: 12:02:16 time: 0.5643 data_time: 0.0053 memory: 14901 loss: 2.6433 loss_prob: 1.6543 loss_thr: 0.7153 loss_db: 0.2737 2022/11/02 13:10:38 - mmengine - INFO - Epoch(train) [96][50/63] lr: 1.9193e-03 eta: 12:01:59 time: 0.5328 data_time: 0.0241 memory: 14901 loss: 2.4294 loss_prob: 1.4756 loss_thr: 0.7129 loss_db: 0.2409 2022/11/02 13:10:41 - mmengine - INFO - Epoch(train) [96][55/63] lr: 1.9193e-03 eta: 12:01:59 time: 0.5539 data_time: 0.0238 memory: 14901 loss: 2.5000 loss_prob: 1.5074 loss_thr: 0.7396 loss_db: 0.2530 2022/11/02 13:10:44 - mmengine - INFO - Epoch(train) [96][60/63] lr: 1.9193e-03 eta: 12:01:42 time: 0.5233 data_time: 0.0054 memory: 14901 loss: 2.5250 loss_prob: 1.5424 loss_thr: 0.7251 loss_db: 0.2575 2022/11/02 13:10:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:10:51 - mmengine - INFO - Epoch(train) [97][5/63] lr: 1.9395e-03 eta: 12:01:42 time: 0.8038 data_time: 0.2235 memory: 14901 loss: 2.6313 loss_prob: 1.6362 loss_thr: 0.7230 loss_db: 0.2721 2022/11/02 13:10:53 - mmengine - INFO - Epoch(train) [97][10/63] lr: 1.9395e-03 eta: 12:01:32 time: 0.7964 data_time: 0.2321 memory: 14901 loss: 2.5684 loss_prob: 1.5916 loss_thr: 0.7141 loss_db: 0.2626 2022/11/02 13:10:56 - mmengine - INFO - Epoch(train) [97][15/63] lr: 1.9395e-03 eta: 12:01:32 time: 0.5394 data_time: 0.0151 memory: 14901 loss: 2.3870 loss_prob: 1.4481 loss_thr: 0.7013 loss_db: 0.2375 2022/11/02 13:11:00 - mmengine - INFO - Epoch(train) [97][20/63] lr: 1.9395e-03 eta: 12:01:30 time: 0.6538 data_time: 0.0068 memory: 14901 loss: 2.5229 loss_prob: 1.5485 loss_thr: 0.7174 loss_db: 0.2570 2022/11/02 13:11:03 - mmengine - INFO - Epoch(train) [97][25/63] lr: 1.9395e-03 eta: 12:01:30 time: 0.7299 data_time: 0.0207 memory: 14901 loss: 2.6312 loss_prob: 1.6323 loss_thr: 0.7260 loss_db: 0.2729 2022/11/02 13:11:07 - mmengine - INFO - Epoch(train) [97][30/63] lr: 1.9395e-03 eta: 12:01:33 time: 0.7052 data_time: 0.0275 memory: 14901 loss: 2.5905 loss_prob: 1.6069 loss_thr: 0.7165 loss_db: 0.2671 2022/11/02 13:11:10 - mmengine - INFO - Epoch(train) [97][35/63] lr: 1.9395e-03 eta: 12:01:33 time: 0.6153 data_time: 0.0199 memory: 14901 loss: 2.4291 loss_prob: 1.4860 loss_thr: 0.6965 loss_db: 0.2467 2022/11/02 13:11:12 - mmengine - INFO - Epoch(train) [97][40/63] lr: 1.9395e-03 eta: 12:01:15 time: 0.5224 data_time: 0.0121 memory: 14901 loss: 2.4245 loss_prob: 1.4863 loss_thr: 0.6917 loss_db: 0.2464 2022/11/02 13:11:15 - mmengine - INFO - Epoch(train) [97][45/63] lr: 1.9395e-03 eta: 12:01:15 time: 0.5053 data_time: 0.0047 memory: 14901 loss: 2.5858 loss_prob: 1.6097 loss_thr: 0.7085 loss_db: 0.2676 2022/11/02 13:11:17 - mmengine - INFO - Epoch(train) [97][50/63] lr: 1.9395e-03 eta: 12:00:58 time: 0.5307 data_time: 0.0142 memory: 14901 loss: 2.5573 loss_prob: 1.5669 loss_thr: 0.7268 loss_db: 0.2636 2022/11/02 13:11:20 - mmengine - INFO - Epoch(train) [97][55/63] lr: 1.9395e-03 eta: 12:00:58 time: 0.5108 data_time: 0.0188 memory: 14901 loss: 2.4004 loss_prob: 1.4619 loss_thr: 0.7014 loss_db: 0.2370 2022/11/02 13:11:22 - mmengine - INFO - Epoch(train) [97][60/63] lr: 1.9395e-03 eta: 12:00:37 time: 0.4858 data_time: 0.0136 memory: 14901 loss: 2.3927 loss_prob: 1.4636 loss_thr: 0.6946 loss_db: 0.2345 2022/11/02 13:11:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:11:28 - mmengine - INFO - Epoch(train) [98][5/63] lr: 1.9596e-03 eta: 12:00:37 time: 0.7008 data_time: 0.2318 memory: 14901 loss: 2.3822 loss_prob: 1.4438 loss_thr: 0.6977 loss_db: 0.2407 2022/11/02 13:11:31 - mmengine - INFO - Epoch(train) [98][10/63] lr: 1.9596e-03 eta: 12:00:20 time: 0.7293 data_time: 0.2298 memory: 14901 loss: 2.4352 loss_prob: 1.4769 loss_thr: 0.7123 loss_db: 0.2460 2022/11/02 13:11:33 - mmengine - INFO - Epoch(train) [98][15/63] lr: 1.9596e-03 eta: 12:00:20 time: 0.5127 data_time: 0.0045 memory: 14901 loss: 2.5364 loss_prob: 1.5787 loss_thr: 0.6976 loss_db: 0.2600 2022/11/02 13:11:36 - mmengine - INFO - Epoch(train) [98][20/63] lr: 1.9596e-03 eta: 12:00:01 time: 0.5164 data_time: 0.0068 memory: 14901 loss: 2.5211 loss_prob: 1.5801 loss_thr: 0.6863 loss_db: 0.2547 2022/11/02 13:11:39 - mmengine - INFO - Epoch(train) [98][25/63] lr: 1.9596e-03 eta: 12:00:01 time: 0.5195 data_time: 0.0327 memory: 14901 loss: 2.4701 loss_prob: 1.5219 loss_thr: 0.7027 loss_db: 0.2455 2022/11/02 13:11:41 - mmengine - INFO - Epoch(train) [98][30/63] lr: 1.9596e-03 eta: 11:59:45 time: 0.5296 data_time: 0.0379 memory: 14901 loss: 2.4317 loss_prob: 1.4769 loss_thr: 0.7099 loss_db: 0.2448 2022/11/02 13:11:44 - mmengine - INFO - Epoch(train) [98][35/63] lr: 1.9596e-03 eta: 11:59:45 time: 0.4955 data_time: 0.0121 memory: 14901 loss: 2.6054 loss_prob: 1.6162 loss_thr: 0.7209 loss_db: 0.2683 2022/11/02 13:11:46 - mmengine - INFO - Epoch(train) [98][40/63] lr: 1.9596e-03 eta: 11:59:24 time: 0.4936 data_time: 0.0042 memory: 14901 loss: 2.6818 loss_prob: 1.6646 loss_thr: 0.7410 loss_db: 0.2763 2022/11/02 13:11:48 - mmengine - INFO - Epoch(train) [98][45/63] lr: 1.9596e-03 eta: 11:59:24 time: 0.4775 data_time: 0.0067 memory: 14901 loss: 2.5025 loss_prob: 1.5157 loss_thr: 0.7371 loss_db: 0.2497 2022/11/02 13:11:51 - mmengine - INFO - Epoch(train) [98][50/63] lr: 1.9596e-03 eta: 11:59:03 time: 0.4912 data_time: 0.0236 memory: 14901 loss: 2.3590 loss_prob: 1.4329 loss_thr: 0.6937 loss_db: 0.2324 2022/11/02 13:11:53 - mmengine - INFO - Epoch(train) [98][55/63] lr: 1.9596e-03 eta: 11:59:03 time: 0.5162 data_time: 0.0268 memory: 14901 loss: 2.3327 loss_prob: 1.4116 loss_thr: 0.6925 loss_db: 0.2286 2022/11/02 13:11:56 - mmengine - INFO - Epoch(train) [98][60/63] lr: 1.9596e-03 eta: 11:58:44 time: 0.5045 data_time: 0.0103 memory: 14901 loss: 2.4848 loss_prob: 1.5179 loss_thr: 0.7182 loss_db: 0.2487 2022/11/02 13:11:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:12:02 - mmengine - INFO - Epoch(train) [99][5/63] lr: 1.9798e-03 eta: 11:58:44 time: 0.7071 data_time: 0.1995 memory: 14901 loss: 2.4599 loss_prob: 1.5016 loss_thr: 0.7099 loss_db: 0.2483 2022/11/02 13:12:04 - mmengine - INFO - Epoch(train) [99][10/63] lr: 1.9798e-03 eta: 11:58:27 time: 0.7332 data_time: 0.1988 memory: 14901 loss: 2.2635 loss_prob: 1.3651 loss_thr: 0.6764 loss_db: 0.2220 2022/11/02 13:12:07 - mmengine - INFO - Epoch(train) [99][15/63] lr: 1.9798e-03 eta: 11:58:27 time: 0.4776 data_time: 0.0078 memory: 14901 loss: 2.1877 loss_prob: 1.3109 loss_thr: 0.6621 loss_db: 0.2147 2022/11/02 13:12:09 - mmengine - INFO - Epoch(train) [99][20/63] lr: 1.9798e-03 eta: 11:58:05 time: 0.4745 data_time: 0.0091 memory: 14901 loss: 2.3053 loss_prob: 1.3941 loss_thr: 0.6848 loss_db: 0.2264 2022/11/02 13:12:12 - mmengine - INFO - Epoch(train) [99][25/63] lr: 1.9798e-03 eta: 11:58:05 time: 0.4783 data_time: 0.0208 memory: 14901 loss: 2.4254 loss_prob: 1.4694 loss_thr: 0.7171 loss_db: 0.2390 2022/11/02 13:12:14 - mmengine - INFO - Epoch(train) [99][30/63] lr: 1.9798e-03 eta: 11:57:44 time: 0.4892 data_time: 0.0306 memory: 14901 loss: 2.3229 loss_prob: 1.3968 loss_thr: 0.6985 loss_db: 0.2277 2022/11/02 13:12:17 - mmengine - INFO - Epoch(train) [99][35/63] lr: 1.9798e-03 eta: 11:57:44 time: 0.5392 data_time: 0.0183 memory: 14901 loss: 2.2579 loss_prob: 1.3538 loss_thr: 0.6814 loss_db: 0.2228 2022/11/02 13:12:19 - mmengine - INFO - Epoch(train) [99][40/63] lr: 1.9798e-03 eta: 11:57:28 time: 0.5332 data_time: 0.0080 memory: 14901 loss: 2.3174 loss_prob: 1.3917 loss_thr: 0.6930 loss_db: 0.2328 2022/11/02 13:12:22 - mmengine - INFO - Epoch(train) [99][45/63] lr: 1.9798e-03 eta: 11:57:28 time: 0.5099 data_time: 0.0064 memory: 14901 loss: 2.4030 loss_prob: 1.4594 loss_thr: 0.7023 loss_db: 0.2414 2022/11/02 13:12:25 - mmengine - INFO - Epoch(train) [99][50/63] lr: 1.9798e-03 eta: 11:57:15 time: 0.5650 data_time: 0.0238 memory: 14901 loss: 2.5208 loss_prob: 1.5544 loss_thr: 0.7151 loss_db: 0.2513 2022/11/02 13:12:28 - mmengine - INFO - Epoch(train) [99][55/63] lr: 1.9798e-03 eta: 11:57:15 time: 0.5848 data_time: 0.0234 memory: 14901 loss: 2.4893 loss_prob: 1.5264 loss_thr: 0.7125 loss_db: 0.2504 2022/11/02 13:12:31 - mmengine - INFO - Epoch(train) [99][60/63] lr: 1.9798e-03 eta: 11:57:01 time: 0.5456 data_time: 0.0061 memory: 14901 loss: 2.5746 loss_prob: 1.5720 loss_thr: 0.7337 loss_db: 0.2689 2022/11/02 13:12:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:12:37 - mmengine - INFO - Epoch(train) [100][5/63] lr: 2.0000e-03 eta: 11:57:01 time: 0.7654 data_time: 0.2374 memory: 14901 loss: 2.5772 loss_prob: 1.5808 loss_thr: 0.7413 loss_db: 0.2552 2022/11/02 13:12:39 - mmengine - INFO - Epoch(train) [100][10/63] lr: 2.0000e-03 eta: 11:56:46 time: 0.7458 data_time: 0.2357 memory: 14901 loss: 2.6708 loss_prob: 1.6663 loss_thr: 0.7365 loss_db: 0.2680 2022/11/02 13:12:42 - mmengine - INFO - Epoch(train) [100][15/63] lr: 2.0000e-03 eta: 11:56:46 time: 0.4999 data_time: 0.0064 memory: 14901 loss: 2.5861 loss_prob: 1.6080 loss_thr: 0.7127 loss_db: 0.2654 2022/11/02 13:12:44 - mmengine - INFO - Epoch(train) [100][20/63] lr: 2.0000e-03 eta: 11:56:28 time: 0.5124 data_time: 0.0062 memory: 14901 loss: 2.4709 loss_prob: 1.5279 loss_thr: 0.6888 loss_db: 0.2542 2022/11/02 13:12:47 - mmengine - INFO - Epoch(train) [100][25/63] lr: 2.0000e-03 eta: 11:56:28 time: 0.4927 data_time: 0.0276 memory: 14901 loss: 2.7793 loss_prob: 1.7670 loss_thr: 0.7262 loss_db: 0.2860 2022/11/02 13:12:49 - mmengine - INFO - Epoch(train) [100][30/63] lr: 2.0000e-03 eta: 11:56:06 time: 0.4806 data_time: 0.0297 memory: 14901 loss: 3.0767 loss_prob: 2.0095 loss_thr: 0.7376 loss_db: 0.3295 2022/11/02 13:12:52 - mmengine - INFO - Epoch(train) [100][35/63] lr: 2.0000e-03 eta: 11:56:06 time: 0.4665 data_time: 0.0074 memory: 14901 loss: 2.8187 loss_prob: 1.8227 loss_thr: 0.6936 loss_db: 0.3023 2022/11/02 13:12:54 - mmengine - INFO - Epoch(train) [100][40/63] lr: 2.0000e-03 eta: 11:55:45 time: 0.4865 data_time: 0.0078 memory: 14901 loss: 2.6690 loss_prob: 1.6677 loss_thr: 0.7272 loss_db: 0.2741 2022/11/02 13:12:57 - mmengine - INFO - Epoch(train) [100][45/63] lr: 2.0000e-03 eta: 11:55:45 time: 0.4964 data_time: 0.0080 memory: 14901 loss: 2.4726 loss_prob: 1.5066 loss_thr: 0.7218 loss_db: 0.2442 2022/11/02 13:13:01 - mmengine - INFO - Epoch(train) [100][50/63] lr: 2.0000e-03 eta: 11:55:45 time: 0.6682 data_time: 0.0229 memory: 14901 loss: 2.5254 loss_prob: 1.5544 loss_thr: 0.7134 loss_db: 0.2576 2022/11/02 13:13:04 - mmengine - INFO - Epoch(train) [100][55/63] lr: 2.0000e-03 eta: 11:55:45 time: 0.7403 data_time: 0.0266 memory: 14901 loss: 2.6892 loss_prob: 1.6560 loss_thr: 0.7576 loss_db: 0.2756 2022/11/02 13:13:07 - mmengine - INFO - Epoch(train) [100][60/63] lr: 2.0000e-03 eta: 11:55:43 time: 0.6572 data_time: 0.0092 memory: 14901 loss: 2.4227 loss_prob: 1.4659 loss_thr: 0.7154 loss_db: 0.2414 2022/11/02 13:13:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:13:09 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/11/02 13:13:12 - mmengine - INFO - Epoch(val) [100][5/500] eta: 11:55:43 time: 0.0460 data_time: 0.0048 memory: 14901 2022/11/02 13:13:13 - mmengine - INFO - Epoch(val) [100][10/500] eta: 0:00:24 time: 0.0491 data_time: 0.0050 memory: 1008 2022/11/02 13:13:13 - mmengine - INFO - Epoch(val) [100][15/500] eta: 0:00:24 time: 0.0447 data_time: 0.0031 memory: 1008 2022/11/02 13:13:13 - mmengine - INFO - Epoch(val) [100][20/500] eta: 0:00:20 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/02 13:13:13 - mmengine - INFO - Epoch(val) [100][25/500] eta: 0:00:20 time: 0.0371 data_time: 0.0027 memory: 1008 2022/11/02 13:13:13 - mmengine - INFO - Epoch(val) [100][30/500] eta: 0:00:18 time: 0.0396 data_time: 0.0025 memory: 1008 2022/11/02 13:13:14 - mmengine - INFO - Epoch(val) [100][35/500] eta: 0:00:18 time: 0.0443 data_time: 0.0046 memory: 1008 2022/11/02 13:13:14 - mmengine - INFO - Epoch(val) [100][40/500] eta: 0:00:21 time: 0.0457 data_time: 0.0047 memory: 1008 2022/11/02 13:13:14 - mmengine - INFO - Epoch(val) [100][45/500] eta: 0:00:21 time: 0.0414 data_time: 0.0024 memory: 1008 2022/11/02 13:13:14 - mmengine - INFO - Epoch(val) [100][50/500] eta: 0:00:18 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 13:13:15 - mmengine - INFO - Epoch(val) [100][55/500] eta: 0:00:18 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/02 13:13:15 - mmengine - INFO - Epoch(val) [100][60/500] eta: 0:00:17 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 13:13:15 - mmengine - INFO - Epoch(val) [100][65/500] eta: 0:00:17 time: 0.0404 data_time: 0.0033 memory: 1008 2022/11/02 13:13:15 - mmengine - INFO - Epoch(val) [100][70/500] eta: 0:00:17 time: 0.0414 data_time: 0.0034 memory: 1008 2022/11/02 13:13:15 - mmengine - INFO - Epoch(val) [100][75/500] eta: 0:00:17 time: 0.0431 data_time: 0.0039 memory: 1008 2022/11/02 13:13:16 - mmengine - INFO - Epoch(val) [100][80/500] eta: 0:00:45 time: 0.1085 data_time: 0.0713 memory: 1008 2022/11/02 13:13:16 - mmengine - INFO - Epoch(val) [100][85/500] eta: 0:00:45 time: 0.1025 data_time: 0.0695 memory: 1008 2022/11/02 13:13:17 - mmengine - INFO - Epoch(val) [100][90/500] eta: 0:00:15 time: 0.0372 data_time: 0.0020 memory: 1008 2022/11/02 13:13:17 - mmengine - INFO - Epoch(val) [100][95/500] eta: 0:00:15 time: 0.0423 data_time: 0.0027 memory: 1008 2022/11/02 13:13:17 - mmengine - INFO - Epoch(val) [100][100/500] eta: 0:00:18 time: 0.0452 data_time: 0.0034 memory: 1008 2022/11/02 13:13:17 - mmengine - INFO - Epoch(val) [100][105/500] eta: 0:00:18 time: 0.0413 data_time: 0.0032 memory: 1008 2022/11/02 13:13:17 - mmengine - INFO - Epoch(val) [100][110/500] eta: 0:00:15 time: 0.0386 data_time: 0.0026 memory: 1008 2022/11/02 13:13:18 - mmengine - INFO - Epoch(val) [100][115/500] eta: 0:00:15 time: 0.0410 data_time: 0.0024 memory: 1008 2022/11/02 13:13:18 - mmengine - INFO - Epoch(val) [100][120/500] eta: 0:00:16 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 13:13:18 - mmengine - INFO - Epoch(val) [100][125/500] eta: 0:00:16 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 13:13:18 - mmengine - INFO - Epoch(val) [100][130/500] eta: 0:00:13 time: 0.0364 data_time: 0.0023 memory: 1008 2022/11/02 13:13:18 - mmengine - INFO - Epoch(val) [100][135/500] eta: 0:00:13 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 13:13:19 - mmengine - INFO - Epoch(val) [100][140/500] eta: 0:00:15 time: 0.0421 data_time: 0.0031 memory: 1008 2022/11/02 13:13:19 - mmengine - INFO - Epoch(val) [100][145/500] eta: 0:00:15 time: 0.0401 data_time: 0.0029 memory: 1008 2022/11/02 13:13:19 - mmengine - INFO - Epoch(val) [100][150/500] eta: 0:00:13 time: 0.0397 data_time: 0.0023 memory: 1008 2022/11/02 13:13:20 - mmengine - INFO - Epoch(val) [100][155/500] eta: 0:00:13 time: 0.0698 data_time: 0.0286 memory: 1008 2022/11/02 13:13:20 - mmengine - INFO - Epoch(val) [100][160/500] eta: 0:00:23 time: 0.0684 data_time: 0.0283 memory: 1008 2022/11/02 13:13:20 - mmengine - INFO - Epoch(val) [100][165/500] eta: 0:00:23 time: 0.0388 data_time: 0.0020 memory: 1008 2022/11/02 13:13:20 - mmengine - INFO - Epoch(val) [100][170/500] eta: 0:00:14 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 13:13:20 - mmengine - INFO - Epoch(val) [100][175/500] eta: 0:00:14 time: 0.0450 data_time: 0.0040 memory: 1008 2022/11/02 13:13:21 - mmengine - INFO - Epoch(val) [100][180/500] eta: 0:00:13 time: 0.0426 data_time: 0.0037 memory: 1008 2022/11/02 13:13:21 - mmengine - INFO - Epoch(val) [100][185/500] eta: 0:00:13 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/02 13:13:21 - mmengine - INFO - Epoch(val) [100][190/500] eta: 0:00:13 time: 0.0451 data_time: 0.0028 memory: 1008 2022/11/02 13:13:21 - mmengine - INFO - Epoch(val) [100][195/500] eta: 0:00:13 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 13:13:22 - mmengine - INFO - Epoch(val) [100][200/500] eta: 0:00:13 time: 0.0456 data_time: 0.0027 memory: 1008 2022/11/02 13:13:22 - mmengine - INFO - Epoch(val) [100][205/500] eta: 0:00:13 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 13:13:22 - mmengine - INFO - Epoch(val) [100][210/500] eta: 0:00:10 time: 0.0379 data_time: 0.0025 memory: 1008 2022/11/02 13:13:22 - mmengine - INFO - Epoch(val) [100][215/500] eta: 0:00:10 time: 0.0438 data_time: 0.0032 memory: 1008 2022/11/02 13:13:22 - mmengine - INFO - Epoch(val) [100][220/500] eta: 0:00:12 time: 0.0436 data_time: 0.0031 memory: 1008 2022/11/02 13:13:23 - mmengine - INFO - Epoch(val) [100][225/500] eta: 0:00:12 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 13:13:23 - mmengine - INFO - Epoch(val) [100][230/500] eta: 0:00:10 time: 0.0380 data_time: 0.0026 memory: 1008 2022/11/02 13:13:23 - mmengine - INFO - Epoch(val) [100][235/500] eta: 0:00:10 time: 0.0394 data_time: 0.0029 memory: 1008 2022/11/02 13:13:23 - mmengine - INFO - Epoch(val) [100][240/500] eta: 0:00:11 time: 0.0448 data_time: 0.0029 memory: 1008 2022/11/02 13:13:23 - mmengine - INFO - Epoch(val) [100][245/500] eta: 0:00:11 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 13:13:24 - mmengine - INFO - Epoch(val) [100][250/500] eta: 0:00:10 time: 0.0400 data_time: 0.0024 memory: 1008 2022/11/02 13:13:24 - mmengine - INFO - Epoch(val) [100][255/500] eta: 0:00:10 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/02 13:13:24 - mmengine - INFO - Epoch(val) [100][260/500] eta: 0:00:09 time: 0.0405 data_time: 0.0031 memory: 1008 2022/11/02 13:13:24 - mmengine - INFO - Epoch(val) [100][265/500] eta: 0:00:09 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 13:13:24 - mmengine - INFO - Epoch(val) [100][270/500] eta: 0:00:09 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/02 13:13:25 - mmengine - INFO - Epoch(val) [100][275/500] eta: 0:00:09 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 13:13:25 - mmengine - INFO - Epoch(val) [100][280/500] eta: 0:00:10 time: 0.0461 data_time: 0.0026 memory: 1008 2022/11/02 13:13:25 - mmengine - INFO - Epoch(val) [100][285/500] eta: 0:00:10 time: 0.0431 data_time: 0.0024 memory: 1008 2022/11/02 13:13:25 - mmengine - INFO - Epoch(val) [100][290/500] eta: 0:00:08 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/02 13:13:25 - mmengine - INFO - Epoch(val) [100][295/500] eta: 0:00:08 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/02 13:13:26 - mmengine - INFO - Epoch(val) [100][300/500] eta: 0:00:07 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 13:13:26 - mmengine - INFO - Epoch(val) [100][305/500] eta: 0:00:07 time: 0.0384 data_time: 0.0033 memory: 1008 2022/11/02 13:13:26 - mmengine - INFO - Epoch(val) [100][310/500] eta: 0:00:07 time: 0.0382 data_time: 0.0032 memory: 1008 2022/11/02 13:13:26 - mmengine - INFO - Epoch(val) [100][315/500] eta: 0:00:07 time: 0.0441 data_time: 0.0026 memory: 1008 2022/11/02 13:13:26 - mmengine - INFO - Epoch(val) [100][320/500] eta: 0:00:08 time: 0.0466 data_time: 0.0035 memory: 1008 2022/11/02 13:13:27 - mmengine - INFO - Epoch(val) [100][325/500] eta: 0:00:08 time: 0.0577 data_time: 0.0034 memory: 1008 2022/11/02 13:13:27 - mmengine - INFO - Epoch(val) [100][330/500] eta: 0:00:09 time: 0.0543 data_time: 0.0032 memory: 1008 2022/11/02 13:13:27 - mmengine - INFO - Epoch(val) [100][335/500] eta: 0:00:09 time: 0.0346 data_time: 0.0031 memory: 1008 2022/11/02 13:13:27 - mmengine - INFO - Epoch(val) [100][340/500] eta: 0:00:07 time: 0.0483 data_time: 0.0023 memory: 1008 2022/11/02 13:13:28 - mmengine - INFO - Epoch(val) [100][345/500] eta: 0:00:07 time: 0.0494 data_time: 0.0022 memory: 1008 2022/11/02 13:13:28 - mmengine - INFO - Epoch(val) [100][350/500] eta: 0:00:06 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/02 13:13:28 - mmengine - INFO - Epoch(val) [100][355/500] eta: 0:00:06 time: 0.0464 data_time: 0.0027 memory: 1008 2022/11/02 13:13:28 - mmengine - INFO - Epoch(val) [100][360/500] eta: 0:00:05 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 13:13:29 - mmengine - INFO - Epoch(val) [100][365/500] eta: 0:00:05 time: 0.0416 data_time: 0.0030 memory: 1008 2022/11/02 13:13:29 - mmengine - INFO - Epoch(val) [100][370/500] eta: 0:00:05 time: 0.0394 data_time: 0.0030 memory: 1008 2022/11/02 13:13:29 - mmengine - INFO - Epoch(val) [100][375/500] eta: 0:00:05 time: 0.0363 data_time: 0.0023 memory: 1008 2022/11/02 13:13:29 - mmengine - INFO - Epoch(val) [100][380/500] eta: 0:00:05 time: 0.0436 data_time: 0.0034 memory: 1008 2022/11/02 13:13:29 - mmengine - INFO - Epoch(val) [100][385/500] eta: 0:00:05 time: 0.0457 data_time: 0.0037 memory: 1008 2022/11/02 13:13:30 - mmengine - INFO - Epoch(val) [100][390/500] eta: 0:00:04 time: 0.0454 data_time: 0.0030 memory: 1008 2022/11/02 13:13:30 - mmengine - INFO - Epoch(val) [100][395/500] eta: 0:00:04 time: 0.0486 data_time: 0.0033 memory: 1008 2022/11/02 13:13:30 - mmengine - INFO - Epoch(val) [100][400/500] eta: 0:00:04 time: 0.0464 data_time: 0.0034 memory: 1008 2022/11/02 13:13:30 - mmengine - INFO - Epoch(val) [100][405/500] eta: 0:00:04 time: 0.0426 data_time: 0.0028 memory: 1008 2022/11/02 13:13:31 - mmengine - INFO - Epoch(val) [100][410/500] eta: 0:00:04 time: 0.0521 data_time: 0.0037 memory: 1008 2022/11/02 13:13:31 - mmengine - INFO - Epoch(val) [100][415/500] eta: 0:00:04 time: 0.0628 data_time: 0.0087 memory: 1008 2022/11/02 13:13:31 - mmengine - INFO - Epoch(val) [100][420/500] eta: 0:00:04 time: 0.0559 data_time: 0.0108 memory: 1008 2022/11/02 13:13:31 - mmengine - INFO - Epoch(val) [100][425/500] eta: 0:00:04 time: 0.0450 data_time: 0.0060 memory: 1008 2022/11/02 13:13:32 - mmengine - INFO - Epoch(val) [100][430/500] eta: 0:00:02 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 13:13:32 - mmengine - INFO - Epoch(val) [100][435/500] eta: 0:00:02 time: 0.0406 data_time: 0.0040 memory: 1008 2022/11/02 13:13:32 - mmengine - INFO - Epoch(val) [100][440/500] eta: 0:00:02 time: 0.0461 data_time: 0.0044 memory: 1008 2022/11/02 13:13:32 - mmengine - INFO - Epoch(val) [100][445/500] eta: 0:00:02 time: 0.0517 data_time: 0.0046 memory: 1008 2022/11/02 13:13:32 - mmengine - INFO - Epoch(val) [100][450/500] eta: 0:00:02 time: 0.0496 data_time: 0.0049 memory: 1008 2022/11/02 13:13:33 - mmengine - INFO - Epoch(val) [100][455/500] eta: 0:00:02 time: 0.0474 data_time: 0.0038 memory: 1008 2022/11/02 13:13:33 - mmengine - INFO - Epoch(val) [100][460/500] eta: 0:00:01 time: 0.0430 data_time: 0.0031 memory: 1008 2022/11/02 13:13:33 - mmengine - INFO - Epoch(val) [100][465/500] eta: 0:00:01 time: 0.0362 data_time: 0.0026 memory: 1008 2022/11/02 13:13:33 - mmengine - INFO - Epoch(val) [100][470/500] eta: 0:00:01 time: 0.0367 data_time: 0.0024 memory: 1008 2022/11/02 13:13:33 - mmengine - INFO - Epoch(val) [100][475/500] eta: 0:00:01 time: 0.0366 data_time: 0.0024 memory: 1008 2022/11/02 13:13:34 - mmengine - INFO - Epoch(val) [100][480/500] eta: 0:00:00 time: 0.0383 data_time: 0.0038 memory: 1008 2022/11/02 13:13:34 - mmengine - INFO - Epoch(val) [100][485/500] eta: 0:00:00 time: 0.0398 data_time: 0.0035 memory: 1008 2022/11/02 13:13:34 - mmengine - INFO - Epoch(val) [100][490/500] eta: 0:00:00 time: 0.0386 data_time: 0.0020 memory: 1008 2022/11/02 13:13:34 - mmengine - INFO - Epoch(val) [100][495/500] eta: 0:00:00 time: 0.0423 data_time: 0.0024 memory: 1008 2022/11/02 13:13:34 - mmengine - INFO - Epoch(val) [100][500/500] eta: 0:00:00 time: 0.0422 data_time: 0.0031 memory: 1008 2022/11/02 13:13:34 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7188, precision: 0.6768, hmean: 0.6972 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7174, precision: 0.7888, hmean: 0.7514 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7044, precision: 0.8452, hmean: 0.7684 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.6394, precision: 0.8895, hmean: 0.7440 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.4338, precision: 0.9366, hmean: 0.5930 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0255, precision: 0.9464, hmean: 0.0497 2022/11/02 13:13:35 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 13:13:35 - mmengine - INFO - Epoch(val) [100][500/500] icdar/precision: 0.8452 icdar/recall: 0.7044 icdar/hmean: 0.7684 2022/11/02 13:13:41 - mmengine - INFO - Epoch(train) [101][5/63] lr: 2.0000e-03 eta: 0:00:00 time: 0.8934 data_time: 0.2492 memory: 14901 loss: 2.3203 loss_prob: 1.3946 loss_thr: 0.6986 loss_db: 0.2271 2022/11/02 13:13:44 - mmengine - INFO - Epoch(train) [101][10/63] lr: 2.0000e-03 eta: 11:55:53 time: 0.9734 data_time: 0.2505 memory: 14901 loss: 2.5264 loss_prob: 1.5569 loss_thr: 0.7164 loss_db: 0.2531 2022/11/02 13:13:48 - mmengine - INFO - Epoch(train) [101][15/63] lr: 2.0000e-03 eta: 11:55:53 time: 0.6411 data_time: 0.0150 memory: 14901 loss: 2.5360 loss_prob: 1.5662 loss_thr: 0.7198 loss_db: 0.2500 2022/11/02 13:13:50 - mmengine - INFO - Epoch(train) [101][20/63] lr: 2.0000e-03 eta: 11:55:47 time: 0.6215 data_time: 0.0133 memory: 14901 loss: 2.4899 loss_prob: 1.5267 loss_thr: 0.7179 loss_db: 0.2454 2022/11/02 13:13:53 - mmengine - INFO - Epoch(train) [101][25/63] lr: 2.0000e-03 eta: 11:55:47 time: 0.5416 data_time: 0.0047 memory: 14901 loss: 2.4769 loss_prob: 1.5080 loss_thr: 0.7210 loss_db: 0.2480 2022/11/02 13:13:56 - mmengine - INFO - Epoch(train) [101][30/63] lr: 2.0000e-03 eta: 11:55:30 time: 0.5204 data_time: 0.0253 memory: 14901 loss: 2.3911 loss_prob: 1.4428 loss_thr: 0.7150 loss_db: 0.2332 2022/11/02 13:13:58 - mmengine - INFO - Epoch(train) [101][35/63] lr: 2.0000e-03 eta: 11:55:30 time: 0.4881 data_time: 0.0267 memory: 14901 loss: 2.2739 loss_prob: 1.3581 loss_thr: 0.6940 loss_db: 0.2218 2022/11/02 13:14:01 - mmengine - INFO - Epoch(train) [101][40/63] lr: 2.0000e-03 eta: 11:55:11 time: 0.4995 data_time: 0.0136 memory: 14901 loss: 2.1834 loss_prob: 1.2995 loss_thr: 0.6659 loss_db: 0.2180 2022/11/02 13:14:03 - mmengine - INFO - Epoch(train) [101][45/63] lr: 2.0000e-03 eta: 11:55:11 time: 0.5035 data_time: 0.0121 memory: 14901 loss: 2.3654 loss_prob: 1.4436 loss_thr: 0.6816 loss_db: 0.2402 2022/11/02 13:14:05 - mmengine - INFO - Epoch(train) [101][50/63] lr: 2.0000e-03 eta: 11:54:48 time: 0.4695 data_time: 0.0144 memory: 14901 loss: 2.4333 loss_prob: 1.4984 loss_thr: 0.6890 loss_db: 0.2458 2022/11/02 13:14:08 - mmengine - INFO - Epoch(train) [101][55/63] lr: 2.0000e-03 eta: 11:54:48 time: 0.4713 data_time: 0.0147 memory: 14901 loss: 2.6820 loss_prob: 1.6826 loss_thr: 0.7173 loss_db: 0.2821 2022/11/02 13:14:10 - mmengine - INFO - Epoch(train) [101][60/63] lr: 2.0000e-03 eta: 11:54:28 time: 0.4915 data_time: 0.0059 memory: 14901 loss: 2.7857 loss_prob: 1.7358 loss_thr: 0.7576 loss_db: 0.2923 2022/11/02 13:14:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:14:17 - mmengine - INFO - Epoch(train) [102][5/63] lr: 1.9984e-03 eta: 11:54:28 time: 0.7541 data_time: 0.2565 memory: 14901 loss: 2.9031 loss_prob: 1.8359 loss_thr: 0.7516 loss_db: 0.3156 2022/11/02 13:14:19 - mmengine - INFO - Epoch(train) [102][10/63] lr: 1.9984e-03 eta: 11:54:16 time: 0.7707 data_time: 0.2616 memory: 14901 loss: 2.7169 loss_prob: 1.6976 loss_thr: 0.7313 loss_db: 0.2879 2022/11/02 13:14:22 - mmengine - INFO - Epoch(train) [102][15/63] lr: 1.9984e-03 eta: 11:54:16 time: 0.5296 data_time: 0.0121 memory: 14901 loss: 2.5126 loss_prob: 1.5562 loss_thr: 0.6979 loss_db: 0.2585 2022/11/02 13:14:25 - mmengine - INFO - Epoch(train) [102][20/63] lr: 1.9984e-03 eta: 11:53:58 time: 0.5120 data_time: 0.0051 memory: 14901 loss: 2.3412 loss_prob: 1.4102 loss_thr: 0.7031 loss_db: 0.2279 2022/11/02 13:14:27 - mmengine - INFO - Epoch(train) [102][25/63] lr: 1.9984e-03 eta: 11:53:58 time: 0.5354 data_time: 0.0282 memory: 14901 loss: 2.2673 loss_prob: 1.3658 loss_thr: 0.6838 loss_db: 0.2177 2022/11/02 13:14:30 - mmengine - INFO - Epoch(train) [102][30/63] lr: 1.9984e-03 eta: 11:53:44 time: 0.5421 data_time: 0.0430 memory: 14901 loss: 2.3479 loss_prob: 1.4412 loss_thr: 0.6769 loss_db: 0.2298 2022/11/02 13:14:32 - mmengine - INFO - Epoch(train) [102][35/63] lr: 1.9984e-03 eta: 11:53:44 time: 0.4882 data_time: 0.0195 memory: 14901 loss: 2.3001 loss_prob: 1.3913 loss_thr: 0.6839 loss_db: 0.2249 2022/11/02 13:14:35 - mmengine - INFO - Epoch(train) [102][40/63] lr: 1.9984e-03 eta: 11:53:21 time: 0.4610 data_time: 0.0063 memory: 14901 loss: 2.1910 loss_prob: 1.3143 loss_thr: 0.6628 loss_db: 0.2139 2022/11/02 13:14:37 - mmengine - INFO - Epoch(train) [102][45/63] lr: 1.9984e-03 eta: 11:53:21 time: 0.4854 data_time: 0.0061 memory: 14901 loss: 2.2713 loss_prob: 1.3733 loss_thr: 0.6775 loss_db: 0.2205 2022/11/02 13:14:40 - mmengine - INFO - Epoch(train) [102][50/63] lr: 1.9984e-03 eta: 11:53:03 time: 0.5100 data_time: 0.0198 memory: 14901 loss: 2.2226 loss_prob: 1.3248 loss_thr: 0.6870 loss_db: 0.2108 2022/11/02 13:14:42 - mmengine - INFO - Epoch(train) [102][55/63] lr: 1.9984e-03 eta: 11:53:03 time: 0.4831 data_time: 0.0231 memory: 14901 loss: 2.1938 loss_prob: 1.3012 loss_thr: 0.6794 loss_db: 0.2132 2022/11/02 13:14:45 - mmengine - INFO - Epoch(train) [102][60/63] lr: 1.9984e-03 eta: 11:52:42 time: 0.4810 data_time: 0.0082 memory: 14901 loss: 2.5730 loss_prob: 1.5968 loss_thr: 0.7171 loss_db: 0.2592 2022/11/02 13:14:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:14:51 - mmengine - INFO - Epoch(train) [103][5/63] lr: 1.9967e-03 eta: 11:52:42 time: 0.7986 data_time: 0.2400 memory: 14901 loss: 2.5000 loss_prob: 1.5373 loss_thr: 0.7109 loss_db: 0.2519 2022/11/02 13:14:54 - mmengine - INFO - Epoch(train) [103][10/63] lr: 1.9967e-03 eta: 11:52:34 time: 0.8049 data_time: 0.2419 memory: 14901 loss: 2.2510 loss_prob: 1.3474 loss_thr: 0.6806 loss_db: 0.2230 2022/11/02 13:14:56 - mmengine - INFO - Epoch(train) [103][15/63] lr: 1.9967e-03 eta: 11:52:34 time: 0.4778 data_time: 0.0072 memory: 14901 loss: 2.2981 loss_prob: 1.3815 loss_thr: 0.6931 loss_db: 0.2236 2022/11/02 13:14:59 - mmengine - INFO - Epoch(train) [103][20/63] lr: 1.9967e-03 eta: 11:52:12 time: 0.4748 data_time: 0.0050 memory: 14901 loss: 2.3587 loss_prob: 1.4146 loss_thr: 0.7108 loss_db: 0.2334 2022/11/02 13:15:01 - mmengine - INFO - Epoch(train) [103][25/63] lr: 1.9967e-03 eta: 11:52:12 time: 0.4934 data_time: 0.0246 memory: 14901 loss: 2.2657 loss_prob: 1.3505 loss_thr: 0.6938 loss_db: 0.2214 2022/11/02 13:15:04 - mmengine - INFO - Epoch(train) [103][30/63] lr: 1.9967e-03 eta: 11:51:55 time: 0.5112 data_time: 0.0310 memory: 14901 loss: 2.3952 loss_prob: 1.4637 loss_thr: 0.6920 loss_db: 0.2395 2022/11/02 13:15:06 - mmengine - INFO - Epoch(train) [103][35/63] lr: 1.9967e-03 eta: 11:51:55 time: 0.4928 data_time: 0.0149 memory: 14901 loss: 2.5035 loss_prob: 1.5427 loss_thr: 0.7108 loss_db: 0.2500 2022/11/02 13:15:09 - mmengine - INFO - Epoch(train) [103][40/63] lr: 1.9967e-03 eta: 11:51:33 time: 0.4774 data_time: 0.0079 memory: 14901 loss: 2.3714 loss_prob: 1.4156 loss_thr: 0.7295 loss_db: 0.2262 2022/11/02 13:15:11 - mmengine - INFO - Epoch(train) [103][45/63] lr: 1.9967e-03 eta: 11:51:33 time: 0.4730 data_time: 0.0054 memory: 14901 loss: 2.5489 loss_prob: 1.5477 loss_thr: 0.7472 loss_db: 0.2540 2022/11/02 13:15:14 - mmengine - INFO - Epoch(train) [103][50/63] lr: 1.9967e-03 eta: 11:51:15 time: 0.5022 data_time: 0.0210 memory: 14901 loss: 2.6936 loss_prob: 1.6743 loss_thr: 0.7409 loss_db: 0.2785 2022/11/02 13:15:16 - mmengine - INFO - Epoch(train) [103][55/63] lr: 1.9967e-03 eta: 11:51:15 time: 0.4969 data_time: 0.0209 memory: 14901 loss: 2.6107 loss_prob: 1.6190 loss_thr: 0.7228 loss_db: 0.2690 2022/11/02 13:15:18 - mmengine - INFO - Epoch(train) [103][60/63] lr: 1.9967e-03 eta: 11:50:52 time: 0.4569 data_time: 0.0055 memory: 14901 loss: 2.6309 loss_prob: 1.6336 loss_thr: 0.7257 loss_db: 0.2716 2022/11/02 13:15:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:15:24 - mmengine - INFO - Epoch(train) [104][5/63] lr: 1.9951e-03 eta: 11:50:52 time: 0.6576 data_time: 0.2166 memory: 14901 loss: 2.2904 loss_prob: 1.3781 loss_thr: 0.6802 loss_db: 0.2321 2022/11/02 13:15:27 - mmengine - INFO - Epoch(train) [104][10/63] lr: 1.9951e-03 eta: 11:50:37 time: 0.7352 data_time: 0.2174 memory: 14901 loss: 2.6400 loss_prob: 1.6375 loss_thr: 0.7222 loss_db: 0.2803 2022/11/02 13:15:29 - mmengine - INFO - Epoch(train) [104][15/63] lr: 1.9951e-03 eta: 11:50:37 time: 0.5248 data_time: 0.0082 memory: 14901 loss: 2.7491 loss_prob: 1.7113 loss_thr: 0.7551 loss_db: 0.2827 2022/11/02 13:15:32 - mmengine - INFO - Epoch(train) [104][20/63] lr: 1.9951e-03 eta: 11:50:17 time: 0.4885 data_time: 0.0076 memory: 14901 loss: 2.4258 loss_prob: 1.4778 loss_thr: 0.7067 loss_db: 0.2413 2022/11/02 13:15:35 - mmengine - INFO - Epoch(train) [104][25/63] lr: 1.9951e-03 eta: 11:50:17 time: 0.5828 data_time: 0.0284 memory: 14901 loss: 2.2654 loss_prob: 1.3754 loss_thr: 0.6674 loss_db: 0.2226 2022/11/02 13:15:38 - mmengine - INFO - Epoch(train) [104][30/63] lr: 1.9951e-03 eta: 11:50:13 time: 0.6381 data_time: 0.0334 memory: 14901 loss: 2.1978 loss_prob: 1.3176 loss_thr: 0.6730 loss_db: 0.2072 2022/11/02 13:15:41 - mmengine - INFO - Epoch(train) [104][35/63] lr: 1.9951e-03 eta: 11:50:13 time: 0.5769 data_time: 0.0106 memory: 14901 loss: 2.2481 loss_prob: 1.3446 loss_thr: 0.6862 loss_db: 0.2173 2022/11/02 13:15:44 - mmengine - INFO - Epoch(train) [104][40/63] lr: 1.9951e-03 eta: 11:50:02 time: 0.5732 data_time: 0.0059 memory: 14901 loss: 2.3371 loss_prob: 1.3885 loss_thr: 0.7181 loss_db: 0.2305 2022/11/02 13:15:47 - mmengine - INFO - Epoch(train) [104][45/63] lr: 1.9951e-03 eta: 11:50:02 time: 0.5801 data_time: 0.0054 memory: 14901 loss: 2.2768 loss_prob: 1.3403 loss_thr: 0.7155 loss_db: 0.2210 2022/11/02 13:15:49 - mmengine - INFO - Epoch(train) [104][50/63] lr: 1.9951e-03 eta: 11:49:47 time: 0.5330 data_time: 0.0167 memory: 14901 loss: 2.2001 loss_prob: 1.3261 loss_thr: 0.6593 loss_db: 0.2147 2022/11/02 13:15:52 - mmengine - INFO - Epoch(train) [104][55/63] lr: 1.9951e-03 eta: 11:49:47 time: 0.5029 data_time: 0.0207 memory: 14901 loss: 2.2387 loss_prob: 1.3574 loss_thr: 0.6613 loss_db: 0.2200 2022/11/02 13:15:54 - mmengine - INFO - Epoch(train) [104][60/63] lr: 1.9951e-03 eta: 11:49:28 time: 0.4923 data_time: 0.0088 memory: 14901 loss: 2.3610 loss_prob: 1.4358 loss_thr: 0.6919 loss_db: 0.2333 2022/11/02 13:15:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:16:00 - mmengine - INFO - Epoch(train) [105][5/63] lr: 1.9934e-03 eta: 11:49:28 time: 0.7203 data_time: 0.2083 memory: 14901 loss: 2.3204 loss_prob: 1.4219 loss_thr: 0.6704 loss_db: 0.2280 2022/11/02 13:16:03 - mmengine - INFO - Epoch(train) [105][10/63] lr: 1.9934e-03 eta: 11:49:17 time: 0.7787 data_time: 0.2172 memory: 14901 loss: 2.4406 loss_prob: 1.5056 loss_thr: 0.6924 loss_db: 0.2426 2022/11/02 13:16:06 - mmengine - INFO - Epoch(train) [105][15/63] lr: 1.9934e-03 eta: 11:49:17 time: 0.6049 data_time: 0.0143 memory: 14901 loss: 2.4369 loss_prob: 1.4959 loss_thr: 0.6981 loss_db: 0.2430 2022/11/02 13:16:09 - mmengine - INFO - Epoch(train) [105][20/63] lr: 1.9934e-03 eta: 11:49:08 time: 0.5904 data_time: 0.0063 memory: 14901 loss: 2.5126 loss_prob: 1.5482 loss_thr: 0.7122 loss_db: 0.2521 2022/11/02 13:16:13 - mmengine - INFO - Epoch(train) [105][25/63] lr: 1.9934e-03 eta: 11:49:08 time: 0.6452 data_time: 0.0314 memory: 14901 loss: 2.6492 loss_prob: 1.6397 loss_thr: 0.7445 loss_db: 0.2649 2022/11/02 13:16:16 - mmengine - INFO - Epoch(train) [105][30/63] lr: 1.9934e-03 eta: 11:49:12 time: 0.7109 data_time: 0.0304 memory: 14901 loss: 2.5634 loss_prob: 1.5782 loss_thr: 0.7252 loss_db: 0.2600 2022/11/02 13:16:19 - mmengine - INFO - Epoch(train) [105][35/63] lr: 1.9934e-03 eta: 11:49:12 time: 0.6225 data_time: 0.0082 memory: 14901 loss: 2.5418 loss_prob: 1.5637 loss_thr: 0.7129 loss_db: 0.2652 2022/11/02 13:16:22 - mmengine - INFO - Epoch(train) [105][40/63] lr: 1.9934e-03 eta: 11:49:02 time: 0.5744 data_time: 0.0079 memory: 14901 loss: 2.5180 loss_prob: 1.5538 loss_thr: 0.7046 loss_db: 0.2595 2022/11/02 13:16:24 - mmengine - INFO - Epoch(train) [105][45/63] lr: 1.9934e-03 eta: 11:49:02 time: 0.5044 data_time: 0.0042 memory: 14901 loss: 2.5078 loss_prob: 1.5415 loss_thr: 0.7096 loss_db: 0.2567 2022/11/02 13:16:26 - mmengine - INFO - Epoch(train) [105][50/63] lr: 1.9934e-03 eta: 11:48:40 time: 0.4677 data_time: 0.0176 memory: 14901 loss: 2.4354 loss_prob: 1.4848 loss_thr: 0.7037 loss_db: 0.2469 2022/11/02 13:16:29 - mmengine - INFO - Epoch(train) [105][55/63] lr: 1.9934e-03 eta: 11:48:40 time: 0.5152 data_time: 0.0176 memory: 14901 loss: 2.4525 loss_prob: 1.5067 loss_thr: 0.6882 loss_db: 0.2576 2022/11/02 13:16:32 - mmengine - INFO - Epoch(train) [105][60/63] lr: 1.9934e-03 eta: 11:48:25 time: 0.5350 data_time: 0.0070 memory: 14901 loss: 2.4735 loss_prob: 1.5124 loss_thr: 0.7011 loss_db: 0.2600 2022/11/02 13:16:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:16:38 - mmengine - INFO - Epoch(train) [106][5/63] lr: 1.9918e-03 eta: 11:48:25 time: 0.7162 data_time: 0.2124 memory: 14901 loss: 2.3691 loss_prob: 1.4353 loss_thr: 0.7005 loss_db: 0.2334 2022/11/02 13:16:40 - mmengine - INFO - Epoch(train) [106][10/63] lr: 1.9918e-03 eta: 11:48:14 time: 0.7700 data_time: 0.2138 memory: 14901 loss: 2.4110 loss_prob: 1.4501 loss_thr: 0.7270 loss_db: 0.2339 2022/11/02 13:16:43 - mmengine - INFO - Epoch(train) [106][15/63] lr: 1.9918e-03 eta: 11:48:14 time: 0.5246 data_time: 0.0117 memory: 14901 loss: 2.3242 loss_prob: 1.4000 loss_thr: 0.6952 loss_db: 0.2290 2022/11/02 13:16:46 - mmengine - INFO - Epoch(train) [106][20/63] lr: 1.9918e-03 eta: 11:48:01 time: 0.5467 data_time: 0.0134 memory: 14901 loss: 2.3149 loss_prob: 1.4038 loss_thr: 0.6791 loss_db: 0.2319 2022/11/02 13:16:49 - mmengine - INFO - Epoch(train) [106][25/63] lr: 1.9918e-03 eta: 11:48:01 time: 0.5439 data_time: 0.0303 memory: 14901 loss: 2.3456 loss_prob: 1.4273 loss_thr: 0.6845 loss_db: 0.2338 2022/11/02 13:16:51 - mmengine - INFO - Epoch(train) [106][30/63] lr: 1.9918e-03 eta: 11:47:42 time: 0.4965 data_time: 0.0302 memory: 14901 loss: 2.4816 loss_prob: 1.5284 loss_thr: 0.7005 loss_db: 0.2527 2022/11/02 13:16:53 - mmengine - INFO - Epoch(train) [106][35/63] lr: 1.9918e-03 eta: 11:47:42 time: 0.4690 data_time: 0.0095 memory: 14901 loss: 2.5966 loss_prob: 1.6139 loss_thr: 0.7150 loss_db: 0.2678 2022/11/02 13:16:56 - mmengine - INFO - Epoch(train) [106][40/63] lr: 1.9918e-03 eta: 11:47:23 time: 0.4899 data_time: 0.0063 memory: 14901 loss: 2.5419 loss_prob: 1.5789 loss_thr: 0.7006 loss_db: 0.2623 2022/11/02 13:16:58 - mmengine - INFO - Epoch(train) [106][45/63] lr: 1.9918e-03 eta: 11:47:23 time: 0.5124 data_time: 0.0042 memory: 14901 loss: 2.3853 loss_prob: 1.4605 loss_thr: 0.6805 loss_db: 0.2443 2022/11/02 13:17:01 - mmengine - INFO - Epoch(train) [106][50/63] lr: 1.9918e-03 eta: 11:47:06 time: 0.5122 data_time: 0.0180 memory: 14901 loss: 2.3809 loss_prob: 1.4462 loss_thr: 0.6953 loss_db: 0.2395 2022/11/02 13:17:03 - mmengine - INFO - Epoch(train) [106][55/63] lr: 1.9918e-03 eta: 11:47:06 time: 0.4702 data_time: 0.0179 memory: 14901 loss: 2.4963 loss_prob: 1.5130 loss_thr: 0.7333 loss_db: 0.2501 2022/11/02 13:17:06 - mmengine - INFO - Epoch(train) [106][60/63] lr: 1.9918e-03 eta: 11:46:44 time: 0.4630 data_time: 0.0048 memory: 14901 loss: 2.4527 loss_prob: 1.4867 loss_thr: 0.7227 loss_db: 0.2434 2022/11/02 13:17:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:17:12 - mmengine - INFO - Epoch(train) [107][5/63] lr: 1.9902e-03 eta: 11:46:44 time: 0.7038 data_time: 0.2012 memory: 14901 loss: 2.3227 loss_prob: 1.3864 loss_thr: 0.7141 loss_db: 0.2222 2022/11/02 13:17:14 - mmengine - INFO - Epoch(train) [107][10/63] lr: 1.9902e-03 eta: 11:46:29 time: 0.7301 data_time: 0.2039 memory: 14901 loss: 2.2322 loss_prob: 1.3158 loss_thr: 0.7080 loss_db: 0.2084 2022/11/02 13:17:17 - mmengine - INFO - Epoch(train) [107][15/63] lr: 1.9902e-03 eta: 11:46:29 time: 0.4885 data_time: 0.0092 memory: 14901 loss: 2.2335 loss_prob: 1.3320 loss_thr: 0.6864 loss_db: 0.2151 2022/11/02 13:17:19 - mmengine - INFO - Epoch(train) [107][20/63] lr: 1.9902e-03 eta: 11:46:09 time: 0.4814 data_time: 0.0092 memory: 14901 loss: 2.2032 loss_prob: 1.3148 loss_thr: 0.6760 loss_db: 0.2124 2022/11/02 13:17:21 - mmengine - INFO - Epoch(train) [107][25/63] lr: 1.9902e-03 eta: 11:46:09 time: 0.4843 data_time: 0.0242 memory: 14901 loss: 2.4223 loss_prob: 1.4875 loss_thr: 0.6952 loss_db: 0.2396 2022/11/02 13:17:24 - mmengine - INFO - Epoch(train) [107][30/63] lr: 1.9902e-03 eta: 11:45:50 time: 0.4885 data_time: 0.0300 memory: 14901 loss: 2.4352 loss_prob: 1.4951 loss_thr: 0.6980 loss_db: 0.2421 2022/11/02 13:17:26 - mmengine - INFO - Epoch(train) [107][35/63] lr: 1.9902e-03 eta: 11:45:50 time: 0.4880 data_time: 0.0149 memory: 14901 loss: 2.1969 loss_prob: 1.3130 loss_thr: 0.6682 loss_db: 0.2157 2022/11/02 13:17:29 - mmengine - INFO - Epoch(train) [107][40/63] lr: 1.9902e-03 eta: 11:45:29 time: 0.4725 data_time: 0.0065 memory: 14901 loss: 2.1681 loss_prob: 1.2948 loss_thr: 0.6594 loss_db: 0.2139 2022/11/02 13:17:31 - mmengine - INFO - Epoch(train) [107][45/63] lr: 1.9902e-03 eta: 11:45:29 time: 0.4558 data_time: 0.0054 memory: 14901 loss: 2.4360 loss_prob: 1.4787 loss_thr: 0.7155 loss_db: 0.2418 2022/11/02 13:17:34 - mmengine - INFO - Epoch(train) [107][50/63] lr: 1.9902e-03 eta: 11:45:12 time: 0.5067 data_time: 0.0291 memory: 14901 loss: 2.4985 loss_prob: 1.5297 loss_thr: 0.7226 loss_db: 0.2462 2022/11/02 13:17:36 - mmengine - INFO - Epoch(train) [107][55/63] lr: 1.9902e-03 eta: 11:45:12 time: 0.5216 data_time: 0.0350 memory: 14901 loss: 2.3380 loss_prob: 1.4231 loss_thr: 0.6840 loss_db: 0.2309 2022/11/02 13:17:39 - mmengine - INFO - Epoch(train) [107][60/63] lr: 1.9902e-03 eta: 11:44:53 time: 0.4894 data_time: 0.0149 memory: 14901 loss: 2.3676 loss_prob: 1.4525 loss_thr: 0.6752 loss_db: 0.2399 2022/11/02 13:17:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:17:44 - mmengine - INFO - Epoch(train) [108][5/63] lr: 1.9885e-03 eta: 11:44:53 time: 0.6668 data_time: 0.1955 memory: 14901 loss: 2.4456 loss_prob: 1.4815 loss_thr: 0.7225 loss_db: 0.2416 2022/11/02 13:17:47 - mmengine - INFO - Epoch(train) [108][10/63] lr: 1.9885e-03 eta: 11:44:36 time: 0.7080 data_time: 0.2000 memory: 14901 loss: 2.5499 loss_prob: 1.5545 loss_thr: 0.7342 loss_db: 0.2612 2022/11/02 13:17:50 - mmengine - INFO - Epoch(train) [108][15/63] lr: 1.9885e-03 eta: 11:44:36 time: 0.5471 data_time: 0.0178 memory: 14901 loss: 2.8256 loss_prob: 1.7801 loss_thr: 0.7384 loss_db: 0.3071 2022/11/02 13:17:52 - mmengine - INFO - Epoch(train) [108][20/63] lr: 1.9885e-03 eta: 11:44:20 time: 0.5195 data_time: 0.0116 memory: 14901 loss: 2.7950 loss_prob: 1.7602 loss_thr: 0.7380 loss_db: 0.2968 2022/11/02 13:17:54 - mmengine - INFO - Epoch(train) [108][25/63] lr: 1.9885e-03 eta: 11:44:20 time: 0.4664 data_time: 0.0077 memory: 14901 loss: 2.7431 loss_prob: 1.7041 loss_thr: 0.7501 loss_db: 0.2888 2022/11/02 13:17:57 - mmengine - INFO - Epoch(train) [108][30/63] lr: 1.9885e-03 eta: 11:44:01 time: 0.4847 data_time: 0.0298 memory: 14901 loss: 2.7729 loss_prob: 1.7297 loss_thr: 0.7449 loss_db: 0.2984 2022/11/02 13:17:59 - mmengine - INFO - Epoch(train) [108][35/63] lr: 1.9885e-03 eta: 11:44:01 time: 0.4971 data_time: 0.0322 memory: 14901 loss: 2.6886 loss_prob: 1.6849 loss_thr: 0.7137 loss_db: 0.2900 2022/11/02 13:18:02 - mmengine - INFO - Epoch(train) [108][40/63] lr: 1.9885e-03 eta: 11:43:44 time: 0.5064 data_time: 0.0146 memory: 14901 loss: 2.5315 loss_prob: 1.5607 loss_thr: 0.7088 loss_db: 0.2620 2022/11/02 13:18:04 - mmengine - INFO - Epoch(train) [108][45/63] lr: 1.9885e-03 eta: 11:43:44 time: 0.4803 data_time: 0.0089 memory: 14901 loss: 2.3014 loss_prob: 1.3880 loss_thr: 0.6859 loss_db: 0.2274 2022/11/02 13:18:07 - mmengine - INFO - Epoch(train) [108][50/63] lr: 1.9885e-03 eta: 11:43:28 time: 0.5191 data_time: 0.0100 memory: 14901 loss: 2.2132 loss_prob: 1.3425 loss_thr: 0.6535 loss_db: 0.2173 2022/11/02 13:18:10 - mmengine - INFO - Epoch(train) [108][55/63] lr: 1.9885e-03 eta: 11:43:28 time: 0.5744 data_time: 0.0157 memory: 14901 loss: 2.2251 loss_prob: 1.3474 loss_thr: 0.6600 loss_db: 0.2177 2022/11/02 13:18:14 - mmengine - INFO - Epoch(train) [108][60/63] lr: 1.9885e-03 eta: 11:43:26 time: 0.6523 data_time: 0.0138 memory: 14901 loss: 2.4323 loss_prob: 1.4885 loss_thr: 0.7030 loss_db: 0.2408 2022/11/02 13:18:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:18:23 - mmengine - INFO - Epoch(train) [109][5/63] lr: 1.9869e-03 eta: 11:43:26 time: 1.1239 data_time: 0.2476 memory: 14901 loss: 2.4425 loss_prob: 1.4735 loss_thr: 0.7235 loss_db: 0.2455 2022/11/02 13:18:26 - mmengine - INFO - Epoch(train) [109][10/63] lr: 1.9869e-03 eta: 11:43:40 time: 1.0195 data_time: 0.2469 memory: 14901 loss: 2.5662 loss_prob: 1.5753 loss_thr: 0.7340 loss_db: 0.2569 2022/11/02 13:18:30 - mmengine - INFO - Epoch(train) [109][15/63] lr: 1.9869e-03 eta: 11:43:40 time: 0.6770 data_time: 0.0289 memory: 14901 loss: 2.5831 loss_prob: 1.5997 loss_thr: 0.7229 loss_db: 0.2606 2022/11/02 13:18:33 - mmengine - INFO - Epoch(train) [109][20/63] lr: 1.9869e-03 eta: 11:43:43 time: 0.7048 data_time: 0.0286 memory: 14901 loss: 2.4580 loss_prob: 1.5094 loss_thr: 0.7023 loss_db: 0.2462 2022/11/02 13:18:36 - mmengine - INFO - Epoch(train) [109][25/63] lr: 1.9869e-03 eta: 11:43:43 time: 0.5769 data_time: 0.0069 memory: 14901 loss: 2.4388 loss_prob: 1.4902 loss_thr: 0.7068 loss_db: 0.2418 2022/11/02 13:18:38 - mmengine - INFO - Epoch(train) [109][30/63] lr: 1.9869e-03 eta: 11:43:29 time: 0.5311 data_time: 0.0104 memory: 14901 loss: 2.2902 loss_prob: 1.3873 loss_thr: 0.6815 loss_db: 0.2214 2022/11/02 13:18:41 - mmengine - INFO - Epoch(train) [109][35/63] lr: 1.9869e-03 eta: 11:43:29 time: 0.5258 data_time: 0.0097 memory: 14901 loss: 2.2397 loss_prob: 1.3529 loss_thr: 0.6702 loss_db: 0.2165 2022/11/02 13:18:45 - mmengine - INFO - Epoch(train) [109][40/63] lr: 1.9869e-03 eta: 11:43:28 time: 0.6673 data_time: 0.0177 memory: 14901 loss: 2.2158 loss_prob: 1.3242 loss_thr: 0.6768 loss_db: 0.2149 2022/11/02 13:18:47 - mmengine - INFO - Epoch(train) [109][45/63] lr: 1.9869e-03 eta: 11:43:28 time: 0.6524 data_time: 0.0162 memory: 14901 loss: 2.1318 loss_prob: 1.2664 loss_thr: 0.6586 loss_db: 0.2067 2022/11/02 13:18:51 - mmengine - INFO - Epoch(train) [109][50/63] lr: 1.9869e-03 eta: 11:43:19 time: 0.5857 data_time: 0.0105 memory: 14901 loss: 2.2693 loss_prob: 1.3808 loss_thr: 0.6640 loss_db: 0.2245 2022/11/02 13:18:53 - mmengine - INFO - Epoch(train) [109][55/63] lr: 1.9869e-03 eta: 11:43:19 time: 0.5712 data_time: 0.0105 memory: 14901 loss: 2.3564 loss_prob: 1.4353 loss_thr: 0.6930 loss_db: 0.2281 2022/11/02 13:18:56 - mmengine - INFO - Epoch(train) [109][60/63] lr: 1.9869e-03 eta: 11:43:10 time: 0.5798 data_time: 0.0044 memory: 14901 loss: 2.4111 loss_prob: 1.4685 loss_thr: 0.7050 loss_db: 0.2375 2022/11/02 13:18:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:19:04 - mmengine - INFO - Epoch(train) [110][5/63] lr: 1.9853e-03 eta: 11:43:10 time: 0.9076 data_time: 0.1909 memory: 14901 loss: 2.2616 loss_prob: 1.3589 loss_thr: 0.6820 loss_db: 0.2206 2022/11/02 13:19:07 - mmengine - INFO - Epoch(train) [110][10/63] lr: 1.9853e-03 eta: 11:43:13 time: 0.9079 data_time: 0.1980 memory: 14901 loss: 2.4201 loss_prob: 1.4706 loss_thr: 0.7101 loss_db: 0.2394 2022/11/02 13:19:09 - mmengine - INFO - Epoch(train) [110][15/63] lr: 1.9853e-03 eta: 11:43:13 time: 0.4840 data_time: 0.0132 memory: 14901 loss: 2.5311 loss_prob: 1.5323 loss_thr: 0.7454 loss_db: 0.2534 2022/11/02 13:19:12 - mmengine - INFO - Epoch(train) [110][20/63] lr: 1.9853e-03 eta: 11:42:53 time: 0.4838 data_time: 0.0052 memory: 14901 loss: 2.3395 loss_prob: 1.3837 loss_thr: 0.7260 loss_db: 0.2298 2022/11/02 13:19:15 - mmengine - INFO - Epoch(train) [110][25/63] lr: 1.9853e-03 eta: 11:42:53 time: 0.5604 data_time: 0.0239 memory: 14901 loss: 2.1511 loss_prob: 1.2787 loss_thr: 0.6650 loss_db: 0.2073 2022/11/02 13:19:17 - mmengine - INFO - Epoch(train) [110][30/63] lr: 1.9853e-03 eta: 11:42:42 time: 0.5609 data_time: 0.0336 memory: 14901 loss: 2.1842 loss_prob: 1.2991 loss_thr: 0.6746 loss_db: 0.2105 2022/11/02 13:19:20 - mmengine - INFO - Epoch(train) [110][35/63] lr: 1.9853e-03 eta: 11:42:42 time: 0.4778 data_time: 0.0159 memory: 14901 loss: 2.1812 loss_prob: 1.2899 loss_thr: 0.6838 loss_db: 0.2075 2022/11/02 13:19:22 - mmengine - INFO - Epoch(train) [110][40/63] lr: 1.9853e-03 eta: 11:42:23 time: 0.4818 data_time: 0.0067 memory: 14901 loss: 2.2497 loss_prob: 1.3563 loss_thr: 0.6749 loss_db: 0.2184 2022/11/02 13:19:25 - mmengine - INFO - Epoch(train) [110][45/63] lr: 1.9853e-03 eta: 11:42:23 time: 0.5202 data_time: 0.0069 memory: 14901 loss: 2.4179 loss_prob: 1.4745 loss_thr: 0.6971 loss_db: 0.2463 2022/11/02 13:19:27 - mmengine - INFO - Epoch(train) [110][50/63] lr: 1.9853e-03 eta: 11:42:08 time: 0.5307 data_time: 0.0168 memory: 14901 loss: 2.5221 loss_prob: 1.5482 loss_thr: 0.7133 loss_db: 0.2606 2022/11/02 13:19:30 - mmengine - INFO - Epoch(train) [110][55/63] lr: 1.9853e-03 eta: 11:42:08 time: 0.5085 data_time: 0.0248 memory: 14901 loss: 2.4844 loss_prob: 1.5243 loss_thr: 0.7075 loss_db: 0.2526 2022/11/02 13:19:32 - mmengine - INFO - Epoch(train) [110][60/63] lr: 1.9853e-03 eta: 11:41:51 time: 0.4992 data_time: 0.0152 memory: 14901 loss: 2.4112 loss_prob: 1.4699 loss_thr: 0.6957 loss_db: 0.2456 2022/11/02 13:19:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:19:38 - mmengine - INFO - Epoch(train) [111][5/63] lr: 1.9836e-03 eta: 11:41:51 time: 0.7075 data_time: 0.1933 memory: 14901 loss: 2.3723 loss_prob: 1.4380 loss_thr: 0.6931 loss_db: 0.2412 2022/11/02 13:19:41 - mmengine - INFO - Epoch(train) [111][10/63] lr: 1.9836e-03 eta: 11:41:35 time: 0.7117 data_time: 0.2037 memory: 14901 loss: 2.1784 loss_prob: 1.2941 loss_thr: 0.6658 loss_db: 0.2185 2022/11/02 13:19:44 - mmengine - INFO - Epoch(train) [111][15/63] lr: 1.9836e-03 eta: 11:41:35 time: 0.5162 data_time: 0.0194 memory: 14901 loss: 2.3630 loss_prob: 1.4404 loss_thr: 0.6889 loss_db: 0.2337 2022/11/02 13:19:46 - mmengine - INFO - Epoch(train) [111][20/63] lr: 1.9836e-03 eta: 11:41:18 time: 0.5083 data_time: 0.0096 memory: 14901 loss: 2.4161 loss_prob: 1.4972 loss_thr: 0.6752 loss_db: 0.2437 2022/11/02 13:19:49 - mmengine - INFO - Epoch(train) [111][25/63] lr: 1.9836e-03 eta: 11:41:18 time: 0.4976 data_time: 0.0169 memory: 14901 loss: 2.2420 loss_prob: 1.3739 loss_thr: 0.6368 loss_db: 0.2313 2022/11/02 13:19:51 - mmengine - INFO - Epoch(train) [111][30/63] lr: 1.9836e-03 eta: 11:41:04 time: 0.5361 data_time: 0.0314 memory: 14901 loss: 2.2558 loss_prob: 1.3686 loss_thr: 0.6595 loss_db: 0.2277 2022/11/02 13:19:54 - mmengine - INFO - Epoch(train) [111][35/63] lr: 1.9836e-03 eta: 11:41:04 time: 0.5550 data_time: 0.0222 memory: 14901 loss: 2.3569 loss_prob: 1.4137 loss_thr: 0.7122 loss_db: 0.2310 2022/11/02 13:19:57 - mmengine - INFO - Epoch(train) [111][40/63] lr: 1.9836e-03 eta: 11:40:49 time: 0.5192 data_time: 0.0092 memory: 14901 loss: 2.2384 loss_prob: 1.3365 loss_thr: 0.6844 loss_db: 0.2175 2022/11/02 13:19:59 - mmengine - INFO - Epoch(train) [111][45/63] lr: 1.9836e-03 eta: 11:40:49 time: 0.4812 data_time: 0.0071 memory: 14901 loss: 2.1708 loss_prob: 1.2898 loss_thr: 0.6740 loss_db: 0.2070 2022/11/02 13:20:01 - mmengine - INFO - Epoch(train) [111][50/63] lr: 1.9836e-03 eta: 11:40:31 time: 0.4938 data_time: 0.0186 memory: 14901 loss: 2.3269 loss_prob: 1.3966 loss_thr: 0.7025 loss_db: 0.2278 2022/11/02 13:20:04 - mmengine - INFO - Epoch(train) [111][55/63] lr: 1.9836e-03 eta: 11:40:31 time: 0.5022 data_time: 0.0230 memory: 14901 loss: 2.4145 loss_prob: 1.4766 loss_thr: 0.6951 loss_db: 0.2428 2022/11/02 13:20:07 - mmengine - INFO - Epoch(train) [111][60/63] lr: 1.9836e-03 eta: 11:40:15 time: 0.5115 data_time: 0.0116 memory: 14901 loss: 2.4406 loss_prob: 1.4929 loss_thr: 0.6998 loss_db: 0.2479 2022/11/02 13:20:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:20:12 - mmengine - INFO - Epoch(train) [112][5/63] lr: 1.9820e-03 eta: 11:40:15 time: 0.6922 data_time: 0.2127 memory: 14901 loss: 2.3366 loss_prob: 1.4108 loss_thr: 0.6948 loss_db: 0.2311 2022/11/02 13:20:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:20:15 - mmengine - INFO - Epoch(train) [112][10/63] lr: 1.9820e-03 eta: 11:40:00 time: 0.7186 data_time: 0.2110 memory: 14901 loss: 2.3400 loss_prob: 1.4082 loss_thr: 0.7034 loss_db: 0.2284 2022/11/02 13:20:17 - mmengine - INFO - Epoch(train) [112][15/63] lr: 1.9820e-03 eta: 11:40:00 time: 0.4922 data_time: 0.0073 memory: 14901 loss: 2.3322 loss_prob: 1.4131 loss_thr: 0.6846 loss_db: 0.2345 2022/11/02 13:20:20 - mmengine - INFO - Epoch(train) [112][20/63] lr: 1.9820e-03 eta: 11:39:41 time: 0.4875 data_time: 0.0083 memory: 14901 loss: 2.3763 loss_prob: 1.4703 loss_thr: 0.6618 loss_db: 0.2442 2022/11/02 13:20:22 - mmengine - INFO - Epoch(train) [112][25/63] lr: 1.9820e-03 eta: 11:39:41 time: 0.4776 data_time: 0.0145 memory: 14901 loss: 2.2822 loss_prob: 1.3776 loss_thr: 0.6799 loss_db: 0.2247 2022/11/02 13:20:25 - mmengine - INFO - Epoch(train) [112][30/63] lr: 1.9820e-03 eta: 11:39:26 time: 0.5143 data_time: 0.0306 memory: 14901 loss: 2.2491 loss_prob: 1.3480 loss_thr: 0.6792 loss_db: 0.2219 2022/11/02 13:20:28 - mmengine - INFO - Epoch(train) [112][35/63] lr: 1.9820e-03 eta: 11:39:26 time: 0.5744 data_time: 0.0256 memory: 14901 loss: 2.3028 loss_prob: 1.4036 loss_thr: 0.6706 loss_db: 0.2286 2022/11/02 13:20:30 - mmengine - INFO - Epoch(train) [112][40/63] lr: 1.9820e-03 eta: 11:39:13 time: 0.5455 data_time: 0.0094 memory: 14901 loss: 2.4420 loss_prob: 1.4875 loss_thr: 0.7102 loss_db: 0.2443 2022/11/02 13:20:33 - mmengine - INFO - Epoch(train) [112][45/63] lr: 1.9820e-03 eta: 11:39:13 time: 0.4838 data_time: 0.0054 memory: 14901 loss: 2.4072 loss_prob: 1.4380 loss_thr: 0.7345 loss_db: 0.2347 2022/11/02 13:20:35 - mmengine - INFO - Epoch(train) [112][50/63] lr: 1.9820e-03 eta: 11:38:54 time: 0.4787 data_time: 0.0107 memory: 14901 loss: 2.4278 loss_prob: 1.4684 loss_thr: 0.7168 loss_db: 0.2426 2022/11/02 13:20:38 - mmengine - INFO - Epoch(train) [112][55/63] lr: 1.9820e-03 eta: 11:38:54 time: 0.4862 data_time: 0.0208 memory: 14901 loss: 2.3832 loss_prob: 1.4363 loss_thr: 0.7054 loss_db: 0.2415 2022/11/02 13:20:40 - mmengine - INFO - Epoch(train) [112][60/63] lr: 1.9820e-03 eta: 11:38:34 time: 0.4661 data_time: 0.0156 memory: 14901 loss: 2.4286 loss_prob: 1.4686 loss_thr: 0.7190 loss_db: 0.2410 2022/11/02 13:20:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:20:46 - mmengine - INFO - Epoch(train) [113][5/63] lr: 1.9803e-03 eta: 11:38:34 time: 0.7125 data_time: 0.2097 memory: 14901 loss: 2.3678 loss_prob: 1.4339 loss_thr: 0.7075 loss_db: 0.2264 2022/11/02 13:20:49 - mmengine - INFO - Epoch(train) [113][10/63] lr: 1.9803e-03 eta: 11:38:23 time: 0.7702 data_time: 0.2089 memory: 14901 loss: 2.7038 loss_prob: 1.7005 loss_thr: 0.7339 loss_db: 0.2694 2022/11/02 13:20:51 - mmengine - INFO - Epoch(train) [113][15/63] lr: 1.9803e-03 eta: 11:38:23 time: 0.5232 data_time: 0.0076 memory: 14901 loss: 2.5624 loss_prob: 1.6005 loss_thr: 0.7005 loss_db: 0.2614 2022/11/02 13:20:54 - mmengine - INFO - Epoch(train) [113][20/63] lr: 1.9803e-03 eta: 11:38:07 time: 0.5062 data_time: 0.0076 memory: 14901 loss: 2.3149 loss_prob: 1.4028 loss_thr: 0.6844 loss_db: 0.2277 2022/11/02 13:20:57 - mmengine - INFO - Epoch(train) [113][25/63] lr: 1.9803e-03 eta: 11:38:07 time: 0.5654 data_time: 0.0588 memory: 14901 loss: 2.3144 loss_prob: 1.4062 loss_thr: 0.6809 loss_db: 0.2274 2022/11/02 13:21:00 - mmengine - INFO - Epoch(train) [113][30/63] lr: 1.9803e-03 eta: 11:37:57 time: 0.5742 data_time: 0.0588 memory: 14901 loss: 2.2953 loss_prob: 1.3986 loss_thr: 0.6704 loss_db: 0.2263 2022/11/02 13:21:02 - mmengine - INFO - Epoch(train) [113][35/63] lr: 1.9803e-03 eta: 11:37:57 time: 0.5117 data_time: 0.0071 memory: 14901 loss: 2.4115 loss_prob: 1.4796 loss_thr: 0.6937 loss_db: 0.2382 2022/11/02 13:21:05 - mmengine - INFO - Epoch(train) [113][40/63] lr: 1.9803e-03 eta: 11:37:49 time: 0.5877 data_time: 0.0098 memory: 14901 loss: 2.6182 loss_prob: 1.6173 loss_thr: 0.7294 loss_db: 0.2715 2022/11/02 13:21:09 - mmengine - INFO - Epoch(train) [113][45/63] lr: 1.9803e-03 eta: 11:37:49 time: 0.6611 data_time: 0.0089 memory: 14901 loss: 2.6886 loss_prob: 1.6802 loss_thr: 0.7232 loss_db: 0.2852 2022/11/02 13:21:12 - mmengine - INFO - Epoch(train) [113][50/63] lr: 1.9803e-03 eta: 11:37:51 time: 0.6945 data_time: 0.0264 memory: 14901 loss: 2.4787 loss_prob: 1.5463 loss_thr: 0.6841 loss_db: 0.2483 2022/11/02 13:21:16 - mmengine - INFO - Epoch(train) [113][55/63] lr: 1.9803e-03 eta: 11:37:51 time: 0.6780 data_time: 0.0266 memory: 14901 loss: 2.4993 loss_prob: 1.5601 loss_thr: 0.6888 loss_db: 0.2504 2022/11/02 13:21:19 - mmengine - INFO - Epoch(train) [113][60/63] lr: 1.9803e-03 eta: 11:37:47 time: 0.6367 data_time: 0.0064 memory: 14901 loss: 2.5300 loss_prob: 1.5696 loss_thr: 0.7008 loss_db: 0.2596 2022/11/02 13:21:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:21:26 - mmengine - INFO - Epoch(train) [114][5/63] lr: 1.9787e-03 eta: 11:37:47 time: 0.7882 data_time: 0.2484 memory: 14901 loss: 2.5605 loss_prob: 1.5763 loss_thr: 0.7223 loss_db: 0.2620 2022/11/02 13:21:29 - mmengine - INFO - Epoch(train) [114][10/63] lr: 1.9787e-03 eta: 11:37:43 time: 0.8340 data_time: 0.2486 memory: 14901 loss: 2.8673 loss_prob: 1.8073 loss_thr: 0.7639 loss_db: 0.2961 2022/11/02 13:21:31 - mmengine - INFO - Epoch(train) [114][15/63] lr: 1.9787e-03 eta: 11:37:43 time: 0.5845 data_time: 0.0057 memory: 14901 loss: 2.9140 loss_prob: 1.8697 loss_thr: 0.7398 loss_db: 0.3045 2022/11/02 13:21:34 - mmengine - INFO - Epoch(train) [114][20/63] lr: 1.9787e-03 eta: 11:37:32 time: 0.5559 data_time: 0.0065 memory: 14901 loss: 2.5200 loss_prob: 1.5644 loss_thr: 0.7031 loss_db: 0.2524 2022/11/02 13:21:37 - mmengine - INFO - Epoch(train) [114][25/63] lr: 1.9787e-03 eta: 11:37:32 time: 0.5659 data_time: 0.0063 memory: 14901 loss: 2.3318 loss_prob: 1.4136 loss_thr: 0.6925 loss_db: 0.2257 2022/11/02 13:21:40 - mmengine - INFO - Epoch(train) [114][30/63] lr: 1.9787e-03 eta: 11:37:24 time: 0.5917 data_time: 0.0313 memory: 14901 loss: 2.5235 loss_prob: 1.5710 loss_thr: 0.6983 loss_db: 0.2542 2022/11/02 13:21:43 - mmengine - INFO - Epoch(train) [114][35/63] lr: 1.9787e-03 eta: 11:37:24 time: 0.6290 data_time: 0.0354 memory: 14901 loss: 2.5875 loss_prob: 1.5896 loss_thr: 0.7328 loss_db: 0.2651 2022/11/02 13:21:46 - mmengine - INFO - Epoch(train) [114][40/63] lr: 1.9787e-03 eta: 11:37:17 time: 0.6091 data_time: 0.0086 memory: 14901 loss: 2.5793 loss_prob: 1.5848 loss_thr: 0.7295 loss_db: 0.2650 2022/11/02 13:21:49 - mmengine - INFO - Epoch(train) [114][45/63] lr: 1.9787e-03 eta: 11:37:17 time: 0.6000 data_time: 0.0046 memory: 14901 loss: 2.4857 loss_prob: 1.5400 loss_thr: 0.6914 loss_db: 0.2543 2022/11/02 13:21:52 - mmengine - INFO - Epoch(train) [114][50/63] lr: 1.9787e-03 eta: 11:37:06 time: 0.5566 data_time: 0.0149 memory: 14901 loss: 2.3147 loss_prob: 1.4073 loss_thr: 0.6744 loss_db: 0.2330 2022/11/02 13:21:54 - mmengine - INFO - Epoch(train) [114][55/63] lr: 1.9787e-03 eta: 11:37:06 time: 0.4706 data_time: 0.0210 memory: 14901 loss: 2.4140 loss_prob: 1.4810 loss_thr: 0.6873 loss_db: 0.2456 2022/11/02 13:21:57 - mmengine - INFO - Epoch(train) [114][60/63] lr: 1.9787e-03 eta: 11:36:47 time: 0.4819 data_time: 0.0112 memory: 14901 loss: 2.4283 loss_prob: 1.4815 loss_thr: 0.7012 loss_db: 0.2456 2022/11/02 13:21:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:22:03 - mmengine - INFO - Epoch(train) [115][5/63] lr: 1.9771e-03 eta: 11:36:47 time: 0.7366 data_time: 0.1930 memory: 14901 loss: 2.5100 loss_prob: 1.5320 loss_thr: 0.7228 loss_db: 0.2552 2022/11/02 13:22:05 - mmengine - INFO - Epoch(train) [115][10/63] lr: 1.9771e-03 eta: 11:36:34 time: 0.7355 data_time: 0.1930 memory: 14901 loss: 2.3823 loss_prob: 1.4320 loss_thr: 0.7146 loss_db: 0.2357 2022/11/02 13:22:08 - mmengine - INFO - Epoch(train) [115][15/63] lr: 1.9771e-03 eta: 11:36:34 time: 0.5190 data_time: 0.0051 memory: 14901 loss: 2.4300 loss_prob: 1.4682 loss_thr: 0.7213 loss_db: 0.2405 2022/11/02 13:22:11 - mmengine - INFO - Epoch(train) [115][20/63] lr: 1.9771e-03 eta: 11:36:21 time: 0.5436 data_time: 0.0051 memory: 14901 loss: 2.7053 loss_prob: 1.6918 loss_thr: 0.7298 loss_db: 0.2837 2022/11/02 13:22:13 - mmengine - INFO - Epoch(train) [115][25/63] lr: 1.9771e-03 eta: 11:36:21 time: 0.4742 data_time: 0.0083 memory: 14901 loss: 2.5448 loss_prob: 1.5823 loss_thr: 0.7005 loss_db: 0.2620 2022/11/02 13:22:16 - mmengine - INFO - Epoch(train) [115][30/63] lr: 1.9771e-03 eta: 11:36:04 time: 0.4870 data_time: 0.0340 memory: 14901 loss: 2.4630 loss_prob: 1.5087 loss_thr: 0.7029 loss_db: 0.2513 2022/11/02 13:22:18 - mmengine - INFO - Epoch(train) [115][35/63] lr: 1.9771e-03 eta: 11:36:04 time: 0.5000 data_time: 0.0306 memory: 14901 loss: 2.4585 loss_prob: 1.5205 loss_thr: 0.6854 loss_db: 0.2526 2022/11/02 13:22:20 - mmengine - INFO - Epoch(train) [115][40/63] lr: 1.9771e-03 eta: 11:35:45 time: 0.4795 data_time: 0.0047 memory: 14901 loss: 2.3094 loss_prob: 1.4184 loss_thr: 0.6654 loss_db: 0.2256 2022/11/02 13:22:23 - mmengine - INFO - Epoch(train) [115][45/63] lr: 1.9771e-03 eta: 11:35:45 time: 0.4786 data_time: 0.0044 memory: 14901 loss: 2.3366 loss_prob: 1.4255 loss_thr: 0.6781 loss_db: 0.2331 2022/11/02 13:22:25 - mmengine - INFO - Epoch(train) [115][50/63] lr: 1.9771e-03 eta: 11:35:29 time: 0.5070 data_time: 0.0114 memory: 14901 loss: 2.3790 loss_prob: 1.4565 loss_thr: 0.6798 loss_db: 0.2427 2022/11/02 13:22:28 - mmengine - INFO - Epoch(train) [115][55/63] lr: 1.9771e-03 eta: 11:35:29 time: 0.5371 data_time: 0.0228 memory: 14901 loss: 2.3888 loss_prob: 1.4565 loss_thr: 0.6881 loss_db: 0.2443 2022/11/02 13:22:30 - mmengine - INFO - Epoch(train) [115][60/63] lr: 1.9771e-03 eta: 11:35:11 time: 0.4857 data_time: 0.0157 memory: 14901 loss: 2.4082 loss_prob: 1.4664 loss_thr: 0.6952 loss_db: 0.2467 2022/11/02 13:22:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:22:36 - mmengine - INFO - Epoch(train) [116][5/63] lr: 1.9754e-03 eta: 11:35:11 time: 0.6711 data_time: 0.2130 memory: 14901 loss: 2.3866 loss_prob: 1.4591 loss_thr: 0.6885 loss_db: 0.2391 2022/11/02 13:22:38 - mmengine - INFO - Epoch(train) [116][10/63] lr: 1.9754e-03 eta: 11:34:53 time: 0.6858 data_time: 0.2140 memory: 14901 loss: 2.2025 loss_prob: 1.3324 loss_thr: 0.6522 loss_db: 0.2180 2022/11/02 13:22:41 - mmengine - INFO - Epoch(train) [116][15/63] lr: 1.9754e-03 eta: 11:34:53 time: 0.4600 data_time: 0.0069 memory: 14901 loss: 2.2776 loss_prob: 1.3898 loss_thr: 0.6594 loss_db: 0.2283 2022/11/02 13:22:43 - mmengine - INFO - Epoch(train) [116][20/63] lr: 1.9754e-03 eta: 11:34:35 time: 0.4809 data_time: 0.0059 memory: 14901 loss: 2.5066 loss_prob: 1.5589 loss_thr: 0.6885 loss_db: 0.2591 2022/11/02 13:22:46 - mmengine - INFO - Epoch(train) [116][25/63] lr: 1.9754e-03 eta: 11:34:35 time: 0.4918 data_time: 0.0217 memory: 14901 loss: 2.5276 loss_prob: 1.5682 loss_thr: 0.7024 loss_db: 0.2570 2022/11/02 13:22:48 - mmengine - INFO - Epoch(train) [116][30/63] lr: 1.9754e-03 eta: 11:34:16 time: 0.4746 data_time: 0.0351 memory: 14901 loss: 2.3959 loss_prob: 1.4659 loss_thr: 0.6889 loss_db: 0.2410 2022/11/02 13:22:50 - mmengine - INFO - Epoch(train) [116][35/63] lr: 1.9754e-03 eta: 11:34:16 time: 0.4777 data_time: 0.0182 memory: 14901 loss: 2.4282 loss_prob: 1.4993 loss_thr: 0.6810 loss_db: 0.2479 2022/11/02 13:22:53 - mmengine - INFO - Epoch(train) [116][40/63] lr: 1.9754e-03 eta: 11:33:57 time: 0.4748 data_time: 0.0057 memory: 14901 loss: 2.4659 loss_prob: 1.5141 loss_thr: 0.6996 loss_db: 0.2522 2022/11/02 13:22:55 - mmengine - INFO - Epoch(train) [116][45/63] lr: 1.9754e-03 eta: 11:33:57 time: 0.4947 data_time: 0.0054 memory: 14901 loss: 2.6072 loss_prob: 1.6177 loss_thr: 0.7177 loss_db: 0.2718 2022/11/02 13:22:58 - mmengine - INFO - Epoch(train) [116][50/63] lr: 1.9754e-03 eta: 11:33:45 time: 0.5402 data_time: 0.0123 memory: 14901 loss: 2.5915 loss_prob: 1.6045 loss_thr: 0.7216 loss_db: 0.2654 2022/11/02 13:23:01 - mmengine - INFO - Epoch(train) [116][55/63] lr: 1.9754e-03 eta: 11:33:45 time: 0.5405 data_time: 0.0217 memory: 14901 loss: 2.5563 loss_prob: 1.5649 loss_thr: 0.7231 loss_db: 0.2683 2022/11/02 13:23:03 - mmengine - INFO - Epoch(train) [116][60/63] lr: 1.9754e-03 eta: 11:33:32 time: 0.5354 data_time: 0.0144 memory: 14901 loss: 2.6658 loss_prob: 1.6580 loss_thr: 0.7194 loss_db: 0.2884 2022/11/02 13:23:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:23:09 - mmengine - INFO - Epoch(train) [117][5/63] lr: 1.9738e-03 eta: 11:33:32 time: 0.6703 data_time: 0.1914 memory: 14901 loss: 2.3741 loss_prob: 1.4420 loss_thr: 0.6877 loss_db: 0.2444 2022/11/02 13:23:12 - mmengine - INFO - Epoch(train) [117][10/63] lr: 1.9738e-03 eta: 11:33:14 time: 0.6898 data_time: 0.1914 memory: 14901 loss: 2.4325 loss_prob: 1.4970 loss_thr: 0.6827 loss_db: 0.2527 2022/11/02 13:23:14 - mmengine - INFO - Epoch(train) [117][15/63] lr: 1.9738e-03 eta: 11:33:14 time: 0.4986 data_time: 0.0060 memory: 14901 loss: 2.6618 loss_prob: 1.6394 loss_thr: 0.7431 loss_db: 0.2793 2022/11/02 13:23:17 - mmengine - INFO - Epoch(train) [117][20/63] lr: 1.9738e-03 eta: 11:33:00 time: 0.5182 data_time: 0.0047 memory: 14901 loss: 2.5187 loss_prob: 1.5206 loss_thr: 0.7422 loss_db: 0.2559 2022/11/02 13:23:20 - mmengine - INFO - Epoch(train) [117][25/63] lr: 1.9738e-03 eta: 11:33:00 time: 0.5467 data_time: 0.0210 memory: 14901 loss: 2.4142 loss_prob: 1.4599 loss_thr: 0.7141 loss_db: 0.2402 2022/11/02 13:23:22 - mmengine - INFO - Epoch(train) [117][30/63] lr: 1.9738e-03 eta: 11:32:48 time: 0.5474 data_time: 0.0307 memory: 14901 loss: 2.3756 loss_prob: 1.4323 loss_thr: 0.7074 loss_db: 0.2359 2022/11/02 13:23:25 - mmengine - INFO - Epoch(train) [117][35/63] lr: 1.9738e-03 eta: 11:32:48 time: 0.5899 data_time: 0.0156 memory: 14901 loss: 2.4016 loss_prob: 1.4486 loss_thr: 0.7133 loss_db: 0.2398 2022/11/02 13:23:29 - mmengine - INFO - Epoch(train) [117][40/63] lr: 1.9738e-03 eta: 11:32:44 time: 0.6322 data_time: 0.0062 memory: 14901 loss: 2.2439 loss_prob: 1.3309 loss_thr: 0.6962 loss_db: 0.2168 2022/11/02 13:23:31 - mmengine - INFO - Epoch(train) [117][45/63] lr: 1.9738e-03 eta: 11:32:44 time: 0.5793 data_time: 0.0048 memory: 14901 loss: 2.1974 loss_prob: 1.2955 loss_thr: 0.6939 loss_db: 0.2080 2022/11/02 13:23:34 - mmengine - INFO - Epoch(train) [117][50/63] lr: 1.9738e-03 eta: 11:32:31 time: 0.5292 data_time: 0.0190 memory: 14901 loss: 2.2281 loss_prob: 1.3253 loss_thr: 0.6908 loss_db: 0.2120 2022/11/02 13:23:37 - mmengine - INFO - Epoch(train) [117][55/63] lr: 1.9738e-03 eta: 11:32:31 time: 0.5487 data_time: 0.0222 memory: 14901 loss: 2.2754 loss_prob: 1.3614 loss_thr: 0.6939 loss_db: 0.2201 2022/11/02 13:23:40 - mmengine - INFO - Epoch(train) [117][60/63] lr: 1.9738e-03 eta: 11:32:26 time: 0.6226 data_time: 0.0083 memory: 14901 loss: 2.3210 loss_prob: 1.3971 loss_thr: 0.6913 loss_db: 0.2327 2022/11/02 13:23:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:23:47 - mmengine - INFO - Epoch(train) [118][5/63] lr: 1.9721e-03 eta: 11:32:26 time: 0.8332 data_time: 0.2319 memory: 14901 loss: 2.1986 loss_prob: 1.3012 loss_thr: 0.6816 loss_db: 0.2157 2022/11/02 13:23:50 - mmengine - INFO - Epoch(train) [118][10/63] lr: 1.9721e-03 eta: 11:32:20 time: 0.8112 data_time: 0.2440 memory: 14901 loss: 2.1903 loss_prob: 1.3086 loss_thr: 0.6623 loss_db: 0.2194 2022/11/02 13:23:53 - mmengine - INFO - Epoch(train) [118][15/63] lr: 1.9721e-03 eta: 11:32:20 time: 0.6076 data_time: 0.0215 memory: 14901 loss: 2.1625 loss_prob: 1.2807 loss_thr: 0.6683 loss_db: 0.2136 2022/11/02 13:23:55 - mmengine - INFO - Epoch(train) [118][20/63] lr: 1.9721e-03 eta: 11:32:09 time: 0.5563 data_time: 0.0093 memory: 14901 loss: 2.1173 loss_prob: 1.2382 loss_thr: 0.6773 loss_db: 0.2018 2022/11/02 13:23:58 - mmengine - INFO - Epoch(train) [118][25/63] lr: 1.9721e-03 eta: 11:32:09 time: 0.4986 data_time: 0.0113 memory: 14901 loss: 2.0701 loss_prob: 1.2176 loss_thr: 0.6562 loss_db: 0.1962 2022/11/02 13:24:01 - mmengine - INFO - Epoch(train) [118][30/63] lr: 1.9721e-03 eta: 11:32:00 time: 0.5803 data_time: 0.0267 memory: 14901 loss: 2.0383 loss_prob: 1.1982 loss_thr: 0.6449 loss_db: 0.1952 2022/11/02 13:24:04 - mmengine - INFO - Epoch(train) [118][35/63] lr: 1.9721e-03 eta: 11:32:00 time: 0.6091 data_time: 0.0292 memory: 14901 loss: 2.0815 loss_prob: 1.2362 loss_thr: 0.6405 loss_db: 0.2048 2022/11/02 13:24:06 - mmengine - INFO - Epoch(train) [118][40/63] lr: 1.9721e-03 eta: 11:31:48 time: 0.5407 data_time: 0.0137 memory: 14901 loss: 2.0761 loss_prob: 1.2396 loss_thr: 0.6337 loss_db: 0.2029 2022/11/02 13:24:09 - mmengine - INFO - Epoch(train) [118][45/63] lr: 1.9721e-03 eta: 11:31:48 time: 0.5272 data_time: 0.0066 memory: 14901 loss: 2.2138 loss_prob: 1.3409 loss_thr: 0.6563 loss_db: 0.2166 2022/11/02 13:24:12 - mmengine - INFO - Epoch(train) [118][50/63] lr: 1.9721e-03 eta: 11:31:35 time: 0.5337 data_time: 0.0166 memory: 14901 loss: 2.2842 loss_prob: 1.3779 loss_thr: 0.6792 loss_db: 0.2271 2022/11/02 13:24:15 - mmengine - INFO - Epoch(train) [118][55/63] lr: 1.9721e-03 eta: 11:31:35 time: 0.5616 data_time: 0.0180 memory: 14901 loss: 2.2075 loss_prob: 1.3045 loss_thr: 0.6848 loss_db: 0.2182 2022/11/02 13:24:17 - mmengine - INFO - Epoch(train) [118][60/63] lr: 1.9721e-03 eta: 11:31:24 time: 0.5633 data_time: 0.0121 memory: 14901 loss: 2.3136 loss_prob: 1.3958 loss_thr: 0.6851 loss_db: 0.2327 2022/11/02 13:24:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:24:25 - mmengine - INFO - Epoch(train) [119][5/63] lr: 1.9705e-03 eta: 11:31:24 time: 0.8429 data_time: 0.2689 memory: 14901 loss: 2.2566 loss_prob: 1.3659 loss_thr: 0.6679 loss_db: 0.2228 2022/11/02 13:24:27 - mmengine - INFO - Epoch(train) [119][10/63] lr: 1.9705e-03 eta: 11:31:18 time: 0.8056 data_time: 0.2703 memory: 14901 loss: 2.3244 loss_prob: 1.4027 loss_thr: 0.6915 loss_db: 0.2302 2022/11/02 13:24:29 - mmengine - INFO - Epoch(train) [119][15/63] lr: 1.9705e-03 eta: 11:31:18 time: 0.4721 data_time: 0.0123 memory: 14901 loss: 2.3608 loss_prob: 1.4453 loss_thr: 0.6794 loss_db: 0.2361 2022/11/02 13:24:32 - mmengine - INFO - Epoch(train) [119][20/63] lr: 1.9705e-03 eta: 11:30:59 time: 0.4732 data_time: 0.0107 memory: 14901 loss: 2.4128 loss_prob: 1.4901 loss_thr: 0.6763 loss_db: 0.2463 2022/11/02 13:24:34 - mmengine - INFO - Epoch(train) [119][25/63] lr: 1.9705e-03 eta: 11:30:59 time: 0.4866 data_time: 0.0268 memory: 14901 loss: 2.4113 loss_prob: 1.4927 loss_thr: 0.6710 loss_db: 0.2476 2022/11/02 13:24:37 - mmengine - INFO - Epoch(train) [119][30/63] lr: 1.9705e-03 eta: 11:30:44 time: 0.5114 data_time: 0.0266 memory: 14901 loss: 2.2729 loss_prob: 1.3821 loss_thr: 0.6636 loss_db: 0.2272 2022/11/02 13:24:39 - mmengine - INFO - Epoch(train) [119][35/63] lr: 1.9705e-03 eta: 11:30:44 time: 0.4960 data_time: 0.0056 memory: 14901 loss: 2.2092 loss_prob: 1.3200 loss_thr: 0.6703 loss_db: 0.2190 2022/11/02 13:24:42 - mmengine - INFO - Epoch(train) [119][40/63] lr: 1.9705e-03 eta: 11:30:26 time: 0.4765 data_time: 0.0107 memory: 14901 loss: 2.3928 loss_prob: 1.4728 loss_thr: 0.6795 loss_db: 0.2405 2022/11/02 13:24:44 - mmengine - INFO - Epoch(train) [119][45/63] lr: 1.9705e-03 eta: 11:30:26 time: 0.4884 data_time: 0.0099 memory: 14901 loss: 2.3951 loss_prob: 1.4820 loss_thr: 0.6734 loss_db: 0.2397 2022/11/02 13:24:47 - mmengine - INFO - Epoch(train) [119][50/63] lr: 1.9705e-03 eta: 11:30:14 time: 0.5356 data_time: 0.0198 memory: 14901 loss: 2.2221 loss_prob: 1.3404 loss_thr: 0.6612 loss_db: 0.2206 2022/11/02 13:24:49 - mmengine - INFO - Epoch(train) [119][55/63] lr: 1.9705e-03 eta: 11:30:14 time: 0.5095 data_time: 0.0197 memory: 14901 loss: 2.2906 loss_prob: 1.3541 loss_thr: 0.7115 loss_db: 0.2249 2022/11/02 13:24:52 - mmengine - INFO - Epoch(train) [119][60/63] lr: 1.9705e-03 eta: 11:29:56 time: 0.4835 data_time: 0.0061 memory: 14901 loss: 2.3809 loss_prob: 1.4240 loss_thr: 0.7201 loss_db: 0.2368 2022/11/02 13:24:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:24:59 - mmengine - INFO - Epoch(train) [120][5/63] lr: 1.9689e-03 eta: 11:29:56 time: 0.7619 data_time: 0.2225 memory: 14901 loss: 2.4716 loss_prob: 1.5105 loss_thr: 0.7067 loss_db: 0.2544 2022/11/02 13:25:01 - mmengine - INFO - Epoch(train) [120][10/63] lr: 1.9689e-03 eta: 11:29:50 time: 0.8111 data_time: 0.2159 memory: 14901 loss: 2.2421 loss_prob: 1.3473 loss_thr: 0.6706 loss_db: 0.2242 2022/11/02 13:25:04 - mmengine - INFO - Epoch(train) [120][15/63] lr: 1.9689e-03 eta: 11:29:50 time: 0.5451 data_time: 0.0060 memory: 14901 loss: 2.3376 loss_prob: 1.4097 loss_thr: 0.6932 loss_db: 0.2347 2022/11/02 13:25:07 - mmengine - INFO - Epoch(train) [120][20/63] lr: 1.9689e-03 eta: 11:29:38 time: 0.5357 data_time: 0.0051 memory: 14901 loss: 2.2790 loss_prob: 1.3558 loss_thr: 0.7007 loss_db: 0.2224 2022/11/02 13:25:09 - mmengine - INFO - Epoch(train) [120][25/63] lr: 1.9689e-03 eta: 11:29:38 time: 0.5172 data_time: 0.0235 memory: 14901 loss: 2.3592 loss_prob: 1.4197 loss_thr: 0.7068 loss_db: 0.2327 2022/11/02 13:25:12 - mmengine - INFO - Epoch(train) [120][30/63] lr: 1.9689e-03 eta: 11:29:23 time: 0.5130 data_time: 0.0315 memory: 14901 loss: 2.3930 loss_prob: 1.4724 loss_thr: 0.6764 loss_db: 0.2441 2022/11/02 13:25:14 - mmengine - INFO - Epoch(train) [120][35/63] lr: 1.9689e-03 eta: 11:29:23 time: 0.4819 data_time: 0.0127 memory: 14901 loss: 2.2956 loss_prob: 1.4015 loss_thr: 0.6580 loss_db: 0.2362 2022/11/02 13:25:16 - mmengine - INFO - Epoch(train) [120][40/63] lr: 1.9689e-03 eta: 11:29:03 time: 0.4574 data_time: 0.0045 memory: 14901 loss: 2.3041 loss_prob: 1.4138 loss_thr: 0.6568 loss_db: 0.2335 2022/11/02 13:25:19 - mmengine - INFO - Epoch(train) [120][45/63] lr: 1.9689e-03 eta: 11:29:03 time: 0.4807 data_time: 0.0044 memory: 14901 loss: 2.5028 loss_prob: 1.5618 loss_thr: 0.6829 loss_db: 0.2580 2022/11/02 13:25:22 - mmengine - INFO - Epoch(train) [120][50/63] lr: 1.9689e-03 eta: 11:28:49 time: 0.5212 data_time: 0.0218 memory: 14901 loss: 2.4371 loss_prob: 1.5036 loss_thr: 0.6899 loss_db: 0.2436 2022/11/02 13:25:24 - mmengine - INFO - Epoch(train) [120][55/63] lr: 1.9689e-03 eta: 11:28:49 time: 0.5080 data_time: 0.0217 memory: 14901 loss: 2.2898 loss_prob: 1.3860 loss_thr: 0.6810 loss_db: 0.2228 2022/11/02 13:25:26 - mmengine - INFO - Epoch(train) [120][60/63] lr: 1.9689e-03 eta: 11:28:32 time: 0.4810 data_time: 0.0045 memory: 14901 loss: 2.1935 loss_prob: 1.3048 loss_thr: 0.6729 loss_db: 0.2158 2022/11/02 13:25:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:25:28 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/11/02 13:25:31 - mmengine - INFO - Epoch(val) [120][5/500] eta: 11:28:32 time: 0.0455 data_time: 0.0050 memory: 14901 2022/11/02 13:25:31 - mmengine - INFO - Epoch(val) [120][10/500] eta: 0:00:21 time: 0.0444 data_time: 0.0042 memory: 1008 2022/11/02 13:25:32 - mmengine - INFO - Epoch(val) [120][15/500] eta: 0:00:21 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/02 13:25:32 - mmengine - INFO - Epoch(val) [120][20/500] eta: 0:00:17 time: 0.0360 data_time: 0.0023 memory: 1008 2022/11/02 13:25:32 - mmengine - INFO - Epoch(val) [120][25/500] eta: 0:00:17 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 13:25:32 - mmengine - INFO - Epoch(val) [120][30/500] eta: 0:00:19 time: 0.0422 data_time: 0.0032 memory: 1008 2022/11/02 13:25:32 - mmengine - INFO - Epoch(val) [120][35/500] eta: 0:00:19 time: 0.0449 data_time: 0.0032 memory: 1008 2022/11/02 13:25:33 - mmengine - INFO - Epoch(val) [120][40/500] eta: 0:00:22 time: 0.0484 data_time: 0.0030 memory: 1008 2022/11/02 13:25:33 - mmengine - INFO - Epoch(val) [120][45/500] eta: 0:00:22 time: 0.0508 data_time: 0.0034 memory: 1008 2022/11/02 13:25:33 - mmengine - INFO - Epoch(val) [120][50/500] eta: 0:00:22 time: 0.0490 data_time: 0.0033 memory: 1008 2022/11/02 13:25:33 - mmengine - INFO - Epoch(val) [120][55/500] eta: 0:00:22 time: 0.0483 data_time: 0.0030 memory: 1008 2022/11/02 13:25:34 - mmengine - INFO - Epoch(val) [120][60/500] eta: 0:00:20 time: 0.0458 data_time: 0.0034 memory: 1008 2022/11/02 13:25:34 - mmengine - INFO - Epoch(val) [120][65/500] eta: 0:00:20 time: 0.0501 data_time: 0.0040 memory: 1008 2022/11/02 13:25:34 - mmengine - INFO - Epoch(val) [120][70/500] eta: 0:00:21 time: 0.0498 data_time: 0.0037 memory: 1008 2022/11/02 13:25:34 - mmengine - INFO - Epoch(val) [120][75/500] eta: 0:00:21 time: 0.0433 data_time: 0.0032 memory: 1008 2022/11/02 13:25:35 - mmengine - INFO - Epoch(val) [120][80/500] eta: 0:00:16 time: 0.0400 data_time: 0.0029 memory: 1008 2022/11/02 13:25:35 - mmengine - INFO - Epoch(val) [120][85/500] eta: 0:00:16 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/02 13:25:35 - mmengine - INFO - Epoch(val) [120][90/500] eta: 0:00:17 time: 0.0435 data_time: 0.0026 memory: 1008 2022/11/02 13:25:35 - mmengine - INFO - Epoch(val) [120][95/500] eta: 0:00:17 time: 0.0451 data_time: 0.0028 memory: 1008 2022/11/02 13:25:35 - mmengine - INFO - Epoch(val) [120][100/500] eta: 0:00:15 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 13:25:36 - mmengine - INFO - Epoch(val) [120][105/500] eta: 0:00:15 time: 0.0375 data_time: 0.0028 memory: 1008 2022/11/02 13:25:36 - mmengine - INFO - Epoch(val) [120][110/500] eta: 0:00:15 time: 0.0396 data_time: 0.0028 memory: 1008 2022/11/02 13:25:36 - mmengine - INFO - Epoch(val) [120][115/500] eta: 0:00:15 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/02 13:25:36 - mmengine - INFO - Epoch(val) [120][120/500] eta: 0:00:16 time: 0.0430 data_time: 0.0025 memory: 1008 2022/11/02 13:25:36 - mmengine - INFO - Epoch(val) [120][125/500] eta: 0:00:16 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/02 13:25:37 - mmengine - INFO - Epoch(val) [120][130/500] eta: 0:00:15 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/02 13:25:37 - mmengine - INFO - Epoch(val) [120][135/500] eta: 0:00:15 time: 0.0461 data_time: 0.0029 memory: 1008 2022/11/02 13:25:37 - mmengine - INFO - Epoch(val) [120][140/500] eta: 0:00:14 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 13:25:37 - mmengine - INFO - Epoch(val) [120][145/500] eta: 0:00:14 time: 0.0402 data_time: 0.0023 memory: 1008 2022/11/02 13:25:37 - mmengine - INFO - Epoch(val) [120][150/500] eta: 0:00:14 time: 0.0405 data_time: 0.0023 memory: 1008 2022/11/02 13:25:38 - mmengine - INFO - Epoch(val) [120][155/500] eta: 0:00:14 time: 0.0422 data_time: 0.0025 memory: 1008 2022/11/02 13:25:38 - mmengine - INFO - Epoch(val) [120][160/500] eta: 0:00:14 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/02 13:25:38 - mmengine - INFO - Epoch(val) [120][165/500] eta: 0:00:14 time: 0.0392 data_time: 0.0023 memory: 1008 2022/11/02 13:25:38 - mmengine - INFO - Epoch(val) [120][170/500] eta: 0:00:13 time: 0.0411 data_time: 0.0024 memory: 1008 2022/11/02 13:25:38 - mmengine - INFO - Epoch(val) [120][175/500] eta: 0:00:13 time: 0.0424 data_time: 0.0027 memory: 1008 2022/11/02 13:25:39 - mmengine - INFO - Epoch(val) [120][180/500] eta: 0:00:12 time: 0.0404 data_time: 0.0025 memory: 1008 2022/11/02 13:25:39 - mmengine - INFO - Epoch(val) [120][185/500] eta: 0:00:12 time: 0.0409 data_time: 0.0023 memory: 1008 2022/11/02 13:25:39 - mmengine - INFO - Epoch(val) [120][190/500] eta: 0:00:12 time: 0.0411 data_time: 0.0024 memory: 1008 2022/11/02 13:25:39 - mmengine - INFO - Epoch(val) [120][195/500] eta: 0:00:12 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/02 13:25:40 - mmengine - INFO - Epoch(val) [120][200/500] eta: 0:00:13 time: 0.0448 data_time: 0.0024 memory: 1008 2022/11/02 13:25:40 - mmengine - INFO - Epoch(val) [120][205/500] eta: 0:00:13 time: 0.0444 data_time: 0.0023 memory: 1008 2022/11/02 13:25:40 - mmengine - INFO - Epoch(val) [120][210/500] eta: 0:00:10 time: 0.0355 data_time: 0.0023 memory: 1008 2022/11/02 13:25:40 - mmengine - INFO - Epoch(val) [120][215/500] eta: 0:00:10 time: 0.0366 data_time: 0.0023 memory: 1008 2022/11/02 13:25:40 - mmengine - INFO - Epoch(val) [120][220/500] eta: 0:00:10 time: 0.0387 data_time: 0.0025 memory: 1008 2022/11/02 13:25:40 - mmengine - INFO - Epoch(val) [120][225/500] eta: 0:00:10 time: 0.0407 data_time: 0.0023 memory: 1008 2022/11/02 13:25:41 - mmengine - INFO - Epoch(val) [120][230/500] eta: 0:00:10 time: 0.0375 data_time: 0.0023 memory: 1008 2022/11/02 13:25:41 - mmengine - INFO - Epoch(val) [120][235/500] eta: 0:00:10 time: 0.0370 data_time: 0.0024 memory: 1008 2022/11/02 13:25:41 - mmengine - INFO - Epoch(val) [120][240/500] eta: 0:00:10 time: 0.0409 data_time: 0.0025 memory: 1008 2022/11/02 13:25:41 - mmengine - INFO - Epoch(val) [120][245/500] eta: 0:00:10 time: 0.0405 data_time: 0.0028 memory: 1008 2022/11/02 13:25:41 - mmengine - INFO - Epoch(val) [120][250/500] eta: 0:00:10 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 13:25:42 - mmengine - INFO - Epoch(val) [120][255/500] eta: 0:00:10 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 13:25:42 - mmengine - INFO - Epoch(val) [120][260/500] eta: 0:00:08 time: 0.0365 data_time: 0.0022 memory: 1008 2022/11/02 13:25:42 - mmengine - INFO - Epoch(val) [120][265/500] eta: 0:00:08 time: 0.0373 data_time: 0.0023 memory: 1008 2022/11/02 13:25:42 - mmengine - INFO - Epoch(val) [120][270/500] eta: 0:00:08 time: 0.0372 data_time: 0.0024 memory: 1008 2022/11/02 13:25:42 - mmengine - INFO - Epoch(val) [120][275/500] eta: 0:00:08 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 13:25:43 - mmengine - INFO - Epoch(val) [120][280/500] eta: 0:00:08 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/02 13:25:43 - mmengine - INFO - Epoch(val) [120][285/500] eta: 0:00:08 time: 0.0381 data_time: 0.0024 memory: 1008 2022/11/02 13:25:43 - mmengine - INFO - Epoch(val) [120][290/500] eta: 0:00:08 time: 0.0392 data_time: 0.0023 memory: 1008 2022/11/02 13:25:43 - mmengine - INFO - Epoch(val) [120][295/500] eta: 0:00:08 time: 0.0396 data_time: 0.0023 memory: 1008 2022/11/02 13:25:43 - mmengine - INFO - Epoch(val) [120][300/500] eta: 0:00:07 time: 0.0361 data_time: 0.0022 memory: 1008 2022/11/02 13:25:44 - mmengine - INFO - Epoch(val) [120][305/500] eta: 0:00:07 time: 0.0388 data_time: 0.0023 memory: 1008 2022/11/02 13:25:44 - mmengine - INFO - Epoch(val) [120][310/500] eta: 0:00:07 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 13:25:44 - mmengine - INFO - Epoch(val) [120][315/500] eta: 0:00:07 time: 0.0373 data_time: 0.0023 memory: 1008 2022/11/02 13:25:44 - mmengine - INFO - Epoch(val) [120][320/500] eta: 0:00:07 time: 0.0391 data_time: 0.0025 memory: 1008 2022/11/02 13:25:44 - mmengine - INFO - Epoch(val) [120][325/500] eta: 0:00:07 time: 0.0534 data_time: 0.0027 memory: 1008 2022/11/02 13:25:45 - mmengine - INFO - Epoch(val) [120][330/500] eta: 0:00:08 time: 0.0515 data_time: 0.0025 memory: 1008 2022/11/02 13:25:45 - mmengine - INFO - Epoch(val) [120][335/500] eta: 0:00:08 time: 0.0344 data_time: 0.0023 memory: 1008 2022/11/02 13:25:45 - mmengine - INFO - Epoch(val) [120][340/500] eta: 0:00:07 time: 0.0473 data_time: 0.0024 memory: 1008 2022/11/02 13:25:45 - mmengine - INFO - Epoch(val) [120][345/500] eta: 0:00:07 time: 0.0499 data_time: 0.0025 memory: 1008 2022/11/02 13:25:46 - mmengine - INFO - Epoch(val) [120][350/500] eta: 0:00:06 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 13:25:46 - mmengine - INFO - Epoch(val) [120][355/500] eta: 0:00:06 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/02 13:25:46 - mmengine - INFO - Epoch(val) [120][360/500] eta: 0:00:05 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/02 13:25:46 - mmengine - INFO - Epoch(val) [120][365/500] eta: 0:00:05 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 13:25:46 - mmengine - INFO - Epoch(val) [120][370/500] eta: 0:00:04 time: 0.0377 data_time: 0.0027 memory: 1008 2022/11/02 13:25:46 - mmengine - INFO - Epoch(val) [120][375/500] eta: 0:00:04 time: 0.0350 data_time: 0.0026 memory: 1008 2022/11/02 13:25:47 - mmengine - INFO - Epoch(val) [120][380/500] eta: 0:00:04 time: 0.0383 data_time: 0.0023 memory: 1008 2022/11/02 13:25:47 - mmengine - INFO - Epoch(val) [120][385/500] eta: 0:00:04 time: 0.0404 data_time: 0.0024 memory: 1008 2022/11/02 13:25:47 - mmengine - INFO - Epoch(val) [120][390/500] eta: 0:00:04 time: 0.0388 data_time: 0.0023 memory: 1008 2022/11/02 13:25:47 - mmengine - INFO - Epoch(val) [120][395/500] eta: 0:00:04 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 13:25:47 - mmengine - INFO - Epoch(val) [120][400/500] eta: 0:00:03 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 13:25:48 - mmengine - INFO - Epoch(val) [120][405/500] eta: 0:00:03 time: 0.0391 data_time: 0.0024 memory: 1008 2022/11/02 13:25:48 - mmengine - INFO - Epoch(val) [120][410/500] eta: 0:00:03 time: 0.0411 data_time: 0.0024 memory: 1008 2022/11/02 13:25:48 - mmengine - INFO - Epoch(val) [120][415/500] eta: 0:00:03 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/02 13:25:48 - mmengine - INFO - Epoch(val) [120][420/500] eta: 0:00:02 time: 0.0353 data_time: 0.0026 memory: 1008 2022/11/02 13:25:48 - mmengine - INFO - Epoch(val) [120][425/500] eta: 0:00:02 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 13:25:49 - mmengine - INFO - Epoch(val) [120][430/500] eta: 0:00:02 time: 0.0404 data_time: 0.0024 memory: 1008 2022/11/02 13:25:49 - mmengine - INFO - Epoch(val) [120][435/500] eta: 0:00:02 time: 0.0366 data_time: 0.0023 memory: 1008 2022/11/02 13:25:49 - mmengine - INFO - Epoch(val) [120][440/500] eta: 0:00:02 time: 0.0382 data_time: 0.0022 memory: 1008 2022/11/02 13:25:49 - mmengine - INFO - Epoch(val) [120][445/500] eta: 0:00:02 time: 0.0391 data_time: 0.0022 memory: 1008 2022/11/02 13:25:49 - mmengine - INFO - Epoch(val) [120][450/500] eta: 0:00:01 time: 0.0396 data_time: 0.0022 memory: 1008 2022/11/02 13:25:50 - mmengine - INFO - Epoch(val) [120][455/500] eta: 0:00:01 time: 0.0391 data_time: 0.0022 memory: 1008 2022/11/02 13:25:50 - mmengine - INFO - Epoch(val) [120][460/500] eta: 0:00:01 time: 0.0353 data_time: 0.0021 memory: 1008 2022/11/02 13:25:50 - mmengine - INFO - Epoch(val) [120][465/500] eta: 0:00:01 time: 0.0365 data_time: 0.0023 memory: 1008 2022/11/02 13:25:50 - mmengine - INFO - Epoch(val) [120][470/500] eta: 0:00:01 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 13:25:50 - mmengine - INFO - Epoch(val) [120][475/500] eta: 0:00:01 time: 0.0340 data_time: 0.0022 memory: 1008 2022/11/02 13:25:51 - mmengine - INFO - Epoch(val) [120][480/500] eta: 0:00:00 time: 0.0354 data_time: 0.0022 memory: 1008 2022/11/02 13:25:51 - mmengine - INFO - Epoch(val) [120][485/500] eta: 0:00:00 time: 0.0368 data_time: 0.0022 memory: 1008 2022/11/02 13:25:51 - mmengine - INFO - Epoch(val) [120][490/500] eta: 0:00:00 time: 0.0425 data_time: 0.0023 memory: 1008 2022/11/02 13:25:51 - mmengine - INFO - Epoch(val) [120][495/500] eta: 0:00:00 time: 0.0477 data_time: 0.0026 memory: 1008 2022/11/02 13:25:51 - mmengine - INFO - Epoch(val) [120][500/500] eta: 0:00:00 time: 0.0401 data_time: 0.0024 memory: 1008 2022/11/02 13:25:51 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7737, precision: 0.6741, hmean: 0.7205 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7737, precision: 0.7634, hmean: 0.7685 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7675, precision: 0.8242, hmean: 0.7948 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7386, precision: 0.8771, hmean: 0.8019 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6057, precision: 0.9182, hmean: 0.7299 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1526, precision: 0.9694, hmean: 0.2637 2022/11/02 13:25:51 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 13:25:51 - mmengine - INFO - Epoch(val) [120][500/500] icdar/precision: 0.8771 icdar/recall: 0.7386 icdar/hmean: 0.8019 2022/11/02 13:25:56 - mmengine - INFO - Epoch(train) [121][5/63] lr: 1.9672e-03 eta: 0:00:00 time: 0.7006 data_time: 0.1929 memory: 14901 loss: 2.0111 loss_prob: 1.1805 loss_thr: 0.6363 loss_db: 0.1942 2022/11/02 13:25:59 - mmengine - INFO - Epoch(train) [121][10/63] lr: 1.9672e-03 eta: 11:28:21 time: 0.7599 data_time: 0.1931 memory: 14901 loss: 2.1155 loss_prob: 1.2615 loss_thr: 0.6447 loss_db: 0.2093 2022/11/02 13:26:02 - mmengine - INFO - Epoch(train) [121][15/63] lr: 1.9672e-03 eta: 11:28:21 time: 0.5741 data_time: 0.0050 memory: 14901 loss: 2.1614 loss_prob: 1.2864 loss_thr: 0.6652 loss_db: 0.2098 2022/11/02 13:26:05 - mmengine - INFO - Epoch(train) [121][20/63] lr: 1.9672e-03 eta: 11:28:13 time: 0.5823 data_time: 0.0051 memory: 14901 loss: 2.3351 loss_prob: 1.4131 loss_thr: 0.6873 loss_db: 0.2347 2022/11/02 13:26:08 - mmengine - INFO - Epoch(train) [121][25/63] lr: 1.9672e-03 eta: 11:28:13 time: 0.5907 data_time: 0.0202 memory: 14901 loss: 2.4241 loss_prob: 1.4738 loss_thr: 0.7013 loss_db: 0.2490 2022/11/02 13:26:11 - mmengine - INFO - Epoch(train) [121][30/63] lr: 1.9672e-03 eta: 11:28:08 time: 0.6138 data_time: 0.0347 memory: 14901 loss: 2.5640 loss_prob: 1.5766 loss_thr: 0.7197 loss_db: 0.2677 2022/11/02 13:26:15 - mmengine - INFO - Epoch(train) [121][35/63] lr: 1.9672e-03 eta: 11:28:08 time: 0.7176 data_time: 0.0299 memory: 14901 loss: 2.6353 loss_prob: 1.6339 loss_thr: 0.7266 loss_db: 0.2749 2022/11/02 13:26:18 - mmengine - INFO - Epoch(train) [121][40/63] lr: 1.9672e-03 eta: 11:28:07 time: 0.6653 data_time: 0.0152 memory: 14901 loss: 2.5065 loss_prob: 1.5588 loss_thr: 0.6899 loss_db: 0.2578 2022/11/02 13:26:20 - mmengine - INFO - Epoch(train) [121][45/63] lr: 1.9672e-03 eta: 11:28:07 time: 0.5080 data_time: 0.0047 memory: 14901 loss: 2.5655 loss_prob: 1.5979 loss_thr: 0.7096 loss_db: 0.2581 2022/11/02 13:26:24 - mmengine - INFO - Epoch(train) [121][50/63] lr: 1.9672e-03 eta: 11:28:00 time: 0.5998 data_time: 0.0112 memory: 14901 loss: 2.3935 loss_prob: 1.4501 loss_thr: 0.7116 loss_db: 0.2318 2022/11/02 13:26:26 - mmengine - INFO - Epoch(train) [121][55/63] lr: 1.9672e-03 eta: 11:28:00 time: 0.5997 data_time: 0.0174 memory: 14901 loss: 2.3313 loss_prob: 1.3961 loss_thr: 0.7042 loss_db: 0.2310 2022/11/02 13:26:29 - mmengine - INFO - Epoch(train) [121][60/63] lr: 1.9672e-03 eta: 11:27:48 time: 0.5425 data_time: 0.0163 memory: 14901 loss: 2.3084 loss_prob: 1.3732 loss_thr: 0.7090 loss_db: 0.2263 2022/11/02 13:26:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:26:37 - mmengine - INFO - Epoch(train) [122][5/63] lr: 1.9656e-03 eta: 11:27:48 time: 0.8836 data_time: 0.2381 memory: 14901 loss: 2.3818 loss_prob: 1.4766 loss_thr: 0.6613 loss_db: 0.2439 2022/11/02 13:26:40 - mmengine - INFO - Epoch(train) [122][10/63] lr: 1.9656e-03 eta: 11:27:55 time: 0.9506 data_time: 0.2369 memory: 14901 loss: 2.3854 loss_prob: 1.4611 loss_thr: 0.6824 loss_db: 0.2419 2022/11/02 13:26:45 - mmengine - INFO - Epoch(train) [122][15/63] lr: 1.9656e-03 eta: 11:27:55 time: 0.7957 data_time: 0.0044 memory: 14901 loss: 2.3653 loss_prob: 1.4377 loss_thr: 0.6913 loss_db: 0.2363 2022/11/02 13:26:47 - mmengine - INFO - Epoch(train) [122][20/63] lr: 1.9656e-03 eta: 11:27:53 time: 0.6598 data_time: 0.0043 memory: 14901 loss: 2.3970 loss_prob: 1.4648 loss_thr: 0.6887 loss_db: 0.2436 2022/11/02 13:26:51 - mmengine - INFO - Epoch(train) [122][25/63] lr: 1.9656e-03 eta: 11:27:53 time: 0.6108 data_time: 0.0262 memory: 14901 loss: 2.5219 loss_prob: 1.5516 loss_thr: 0.7118 loss_db: 0.2585 2022/11/02 13:26:53 - mmengine - INFO - Epoch(train) [122][30/63] lr: 1.9656e-03 eta: 11:27:52 time: 0.6568 data_time: 0.0337 memory: 14901 loss: 2.4792 loss_prob: 1.5320 loss_thr: 0.6996 loss_db: 0.2476 2022/11/02 13:26:57 - mmengine - INFO - Epoch(train) [122][35/63] lr: 1.9656e-03 eta: 11:27:52 time: 0.5968 data_time: 0.0125 memory: 14901 loss: 2.2753 loss_prob: 1.3836 loss_thr: 0.6699 loss_db: 0.2219 2022/11/02 13:27:00 - mmengine - INFO - Epoch(train) [122][40/63] lr: 1.9656e-03 eta: 11:27:45 time: 0.6038 data_time: 0.0056 memory: 14901 loss: 2.1979 loss_prob: 1.3270 loss_thr: 0.6549 loss_db: 0.2160 2022/11/02 13:27:02 - mmengine - INFO - Epoch(train) [122][45/63] lr: 1.9656e-03 eta: 11:27:45 time: 0.5226 data_time: 0.0069 memory: 14901 loss: 2.1933 loss_prob: 1.3321 loss_thr: 0.6403 loss_db: 0.2210 2022/11/02 13:27:04 - mmengine - INFO - Epoch(train) [122][50/63] lr: 1.9656e-03 eta: 11:27:28 time: 0.4863 data_time: 0.0236 memory: 14901 loss: 2.2638 loss_prob: 1.3656 loss_thr: 0.6723 loss_db: 0.2259 2022/11/02 13:27:07 - mmengine - INFO - Epoch(train) [122][55/63] lr: 1.9656e-03 eta: 11:27:28 time: 0.5099 data_time: 0.0242 memory: 14901 loss: 2.3154 loss_prob: 1.3821 loss_thr: 0.7103 loss_db: 0.2229 2022/11/02 13:27:09 - mmengine - INFO - Epoch(train) [122][60/63] lr: 1.9656e-03 eta: 11:27:13 time: 0.5020 data_time: 0.0071 memory: 14901 loss: 2.2358 loss_prob: 1.3147 loss_thr: 0.7055 loss_db: 0.2156 2022/11/02 13:27:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:27:15 - mmengine - INFO - Epoch(train) [123][5/63] lr: 1.9639e-03 eta: 11:27:13 time: 0.6842 data_time: 0.1976 memory: 14901 loss: 2.1682 loss_prob: 1.2896 loss_thr: 0.6713 loss_db: 0.2073 2022/11/02 13:27:18 - mmengine - INFO - Epoch(train) [123][10/63] lr: 1.9639e-03 eta: 11:27:02 time: 0.7512 data_time: 0.2058 memory: 14901 loss: 2.2052 loss_prob: 1.3247 loss_thr: 0.6665 loss_db: 0.2141 2022/11/02 13:27:21 - mmengine - INFO - Epoch(train) [123][15/63] lr: 1.9639e-03 eta: 11:27:02 time: 0.5564 data_time: 0.0153 memory: 14901 loss: 2.3729 loss_prob: 1.4570 loss_thr: 0.6751 loss_db: 0.2408 2022/11/02 13:27:23 - mmengine - INFO - Epoch(train) [123][20/63] lr: 1.9639e-03 eta: 11:26:48 time: 0.5178 data_time: 0.0073 memory: 14901 loss: 2.3506 loss_prob: 1.4317 loss_thr: 0.6814 loss_db: 0.2374 2022/11/02 13:27:26 - mmengine - INFO - Epoch(train) [123][25/63] lr: 1.9639e-03 eta: 11:26:48 time: 0.4942 data_time: 0.0066 memory: 14901 loss: 2.4160 loss_prob: 1.4464 loss_thr: 0.7306 loss_db: 0.2389 2022/11/02 13:27:28 - mmengine - INFO - Epoch(train) [123][30/63] lr: 1.9639e-03 eta: 11:26:34 time: 0.5165 data_time: 0.0290 memory: 14901 loss: 2.3736 loss_prob: 1.4297 loss_thr: 0.7102 loss_db: 0.2338 2022/11/02 13:27:31 - mmengine - INFO - Epoch(train) [123][35/63] lr: 1.9639e-03 eta: 11:26:34 time: 0.5304 data_time: 0.0295 memory: 14901 loss: 2.2594 loss_prob: 1.3799 loss_thr: 0.6541 loss_db: 0.2254 2022/11/02 13:27:34 - mmengine - INFO - Epoch(train) [123][40/63] lr: 1.9639e-03 eta: 11:26:20 time: 0.5161 data_time: 0.0097 memory: 14901 loss: 2.4484 loss_prob: 1.5176 loss_thr: 0.6762 loss_db: 0.2546 2022/11/02 13:27:36 - mmengine - INFO - Epoch(train) [123][45/63] lr: 1.9639e-03 eta: 11:26:20 time: 0.5125 data_time: 0.0101 memory: 14901 loss: 2.3414 loss_prob: 1.4233 loss_thr: 0.6784 loss_db: 0.2397 2022/11/02 13:27:39 - mmengine - INFO - Epoch(train) [123][50/63] lr: 1.9639e-03 eta: 11:26:05 time: 0.5048 data_time: 0.0192 memory: 14901 loss: 2.0835 loss_prob: 1.2273 loss_thr: 0.6563 loss_db: 0.1999 2022/11/02 13:27:41 - mmengine - INFO - Epoch(train) [123][55/63] lr: 1.9639e-03 eta: 11:26:05 time: 0.4823 data_time: 0.0176 memory: 14901 loss: 2.1788 loss_prob: 1.3006 loss_thr: 0.6644 loss_db: 0.2138 2022/11/02 13:27:43 - mmengine - INFO - Epoch(train) [123][60/63] lr: 1.9639e-03 eta: 11:25:48 time: 0.4803 data_time: 0.0116 memory: 14901 loss: 2.1667 loss_prob: 1.3055 loss_thr: 0.6488 loss_db: 0.2124 2022/11/02 13:27:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:27:50 - mmengine - INFO - Epoch(train) [124][5/63] lr: 1.9623e-03 eta: 11:25:48 time: 0.7316 data_time: 0.2130 memory: 14901 loss: 2.2661 loss_prob: 1.3649 loss_thr: 0.6806 loss_db: 0.2206 2022/11/02 13:27:52 - mmengine - INFO - Epoch(train) [124][10/63] lr: 1.9623e-03 eta: 11:25:37 time: 0.7521 data_time: 0.2099 memory: 14901 loss: 2.1045 loss_prob: 1.2255 loss_thr: 0.6741 loss_db: 0.2049 2022/11/02 13:27:55 - mmengine - INFO - Epoch(train) [124][15/63] lr: 1.9623e-03 eta: 11:25:37 time: 0.4847 data_time: 0.0088 memory: 14901 loss: 2.2657 loss_prob: 1.3549 loss_thr: 0.6890 loss_db: 0.2219 2022/11/02 13:27:57 - mmengine - INFO - Epoch(train) [124][20/63] lr: 1.9623e-03 eta: 11:25:19 time: 0.4706 data_time: 0.0081 memory: 14901 loss: 2.3459 loss_prob: 1.4333 loss_thr: 0.6797 loss_db: 0.2329 2022/11/02 13:28:00 - mmengine - INFO - Epoch(train) [124][25/63] lr: 1.9623e-03 eta: 11:25:19 time: 0.5082 data_time: 0.0197 memory: 14901 loss: 2.2074 loss_prob: 1.3383 loss_thr: 0.6572 loss_db: 0.2118 2022/11/02 13:28:02 - mmengine - INFO - Epoch(train) [124][30/63] lr: 1.9623e-03 eta: 11:25:06 time: 0.5313 data_time: 0.0451 memory: 14901 loss: 2.1846 loss_prob: 1.3163 loss_thr: 0.6588 loss_db: 0.2095 2022/11/02 13:28:05 - mmengine - INFO - Epoch(train) [124][35/63] lr: 1.9623e-03 eta: 11:25:06 time: 0.5016 data_time: 0.0298 memory: 14901 loss: 2.2426 loss_prob: 1.3625 loss_thr: 0.6603 loss_db: 0.2197 2022/11/02 13:28:07 - mmengine - INFO - Epoch(train) [124][40/63] lr: 1.9623e-03 eta: 11:24:50 time: 0.4927 data_time: 0.0053 memory: 14901 loss: 2.3413 loss_prob: 1.4256 loss_thr: 0.6821 loss_db: 0.2337 2022/11/02 13:28:10 - mmengine - INFO - Epoch(train) [124][45/63] lr: 1.9623e-03 eta: 11:24:50 time: 0.5732 data_time: 0.0058 memory: 14901 loss: 2.3582 loss_prob: 1.4376 loss_thr: 0.6790 loss_db: 0.2417 2022/11/02 13:28:13 - mmengine - INFO - Epoch(train) [124][50/63] lr: 1.9623e-03 eta: 11:24:42 time: 0.5818 data_time: 0.0145 memory: 14901 loss: 2.5207 loss_prob: 1.5534 loss_thr: 0.7033 loss_db: 0.2640 2022/11/02 13:28:16 - mmengine - INFO - Epoch(train) [124][55/63] lr: 1.9623e-03 eta: 11:24:42 time: 0.5075 data_time: 0.0209 memory: 14901 loss: 2.9650 loss_prob: 1.8995 loss_thr: 0.7460 loss_db: 0.3195 2022/11/02 13:28:18 - mmengine - INFO - Epoch(train) [124][60/63] lr: 1.9623e-03 eta: 11:24:25 time: 0.4826 data_time: 0.0122 memory: 14901 loss: 3.1216 loss_prob: 2.0265 loss_thr: 0.7559 loss_db: 0.3392 2022/11/02 13:28:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:28:24 - mmengine - INFO - Epoch(train) [125][5/63] lr: 1.9607e-03 eta: 11:24:25 time: 0.6778 data_time: 0.2250 memory: 14901 loss: 2.6234 loss_prob: 1.6272 loss_thr: 0.7215 loss_db: 0.2747 2022/11/02 13:28:26 - mmengine - INFO - Epoch(train) [125][10/63] lr: 1.9607e-03 eta: 11:24:11 time: 0.7151 data_time: 0.2232 memory: 14901 loss: 2.4449 loss_prob: 1.5144 loss_thr: 0.6773 loss_db: 0.2532 2022/11/02 13:28:29 - mmengine - INFO - Epoch(train) [125][15/63] lr: 1.9607e-03 eta: 11:24:11 time: 0.4898 data_time: 0.0061 memory: 14901 loss: 2.3412 loss_prob: 1.4407 loss_thr: 0.6650 loss_db: 0.2356 2022/11/02 13:28:31 - mmengine - INFO - Epoch(train) [125][20/63] lr: 1.9607e-03 eta: 11:23:54 time: 0.4745 data_time: 0.0056 memory: 14901 loss: 2.3384 loss_prob: 1.4207 loss_thr: 0.6852 loss_db: 0.2325 2022/11/02 13:28:34 - mmengine - INFO - Epoch(train) [125][25/63] lr: 1.9607e-03 eta: 11:23:54 time: 0.5098 data_time: 0.0347 memory: 14901 loss: 2.4138 loss_prob: 1.4620 loss_thr: 0.7099 loss_db: 0.2420 2022/11/02 13:28:37 - mmengine - INFO - Epoch(train) [125][30/63] lr: 1.9607e-03 eta: 11:23:44 time: 0.5661 data_time: 0.0360 memory: 14901 loss: 2.2773 loss_prob: 1.3743 loss_thr: 0.6798 loss_db: 0.2232 2022/11/02 13:28:40 - mmengine - INFO - Epoch(train) [125][35/63] lr: 1.9607e-03 eta: 11:23:44 time: 0.6550 data_time: 0.0061 memory: 14901 loss: 2.1099 loss_prob: 1.2546 loss_thr: 0.6523 loss_db: 0.2030 2022/11/02 13:28:43 - mmengine - INFO - Epoch(train) [125][40/63] lr: 1.9607e-03 eta: 11:23:40 time: 0.6235 data_time: 0.0046 memory: 14901 loss: 2.2164 loss_prob: 1.3118 loss_thr: 0.6893 loss_db: 0.2154 2022/11/02 13:28:46 - mmengine - INFO - Epoch(train) [125][45/63] lr: 1.9607e-03 eta: 11:23:40 time: 0.5790 data_time: 0.0063 memory: 14901 loss: 2.2454 loss_prob: 1.3431 loss_thr: 0.6827 loss_db: 0.2196 2022/11/02 13:28:50 - mmengine - INFO - Epoch(train) [125][50/63] lr: 1.9607e-03 eta: 11:23:47 time: 0.7586 data_time: 0.0244 memory: 14901 loss: 2.3350 loss_prob: 1.4124 loss_thr: 0.6891 loss_db: 0.2335 2022/11/02 13:28:54 - mmengine - INFO - Epoch(train) [125][55/63] lr: 1.9607e-03 eta: 11:23:47 time: 0.7675 data_time: 0.0242 memory: 14901 loss: 2.5523 loss_prob: 1.5731 loss_thr: 0.7154 loss_db: 0.2638 2022/11/02 13:28:56 - mmengine - INFO - Epoch(train) [125][60/63] lr: 1.9607e-03 eta: 11:23:39 time: 0.5817 data_time: 0.0066 memory: 14901 loss: 2.3889 loss_prob: 1.4714 loss_thr: 0.6737 loss_db: 0.2438 2022/11/02 13:28:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:29:04 - mmengine - INFO - Epoch(train) [126][5/63] lr: 1.9590e-03 eta: 11:23:39 time: 0.8428 data_time: 0.1998 memory: 14901 loss: 2.4313 loss_prob: 1.4913 loss_thr: 0.6947 loss_db: 0.2453 2022/11/02 13:29:06 - mmengine - INFO - Epoch(train) [126][10/63] lr: 1.9590e-03 eta: 11:23:33 time: 0.8106 data_time: 0.2011 memory: 14901 loss: 2.4451 loss_prob: 1.5070 loss_thr: 0.6916 loss_db: 0.2466 2022/11/02 13:29:09 - mmengine - INFO - Epoch(train) [126][15/63] lr: 1.9590e-03 eta: 11:23:33 time: 0.5085 data_time: 0.0075 memory: 14901 loss: 2.3047 loss_prob: 1.3988 loss_thr: 0.6811 loss_db: 0.2248 2022/11/02 13:29:12 - mmengine - INFO - Epoch(train) [126][20/63] lr: 1.9590e-03 eta: 11:23:29 time: 0.6305 data_time: 0.0053 memory: 14901 loss: 2.1917 loss_prob: 1.3209 loss_thr: 0.6581 loss_db: 0.2126 2022/11/02 13:29:16 - mmengine - INFO - Epoch(train) [126][25/63] lr: 1.9590e-03 eta: 11:23:29 time: 0.6821 data_time: 0.0156 memory: 14901 loss: 2.2369 loss_prob: 1.3523 loss_thr: 0.6669 loss_db: 0.2177 2022/11/02 13:29:19 - mmengine - INFO - Epoch(train) [126][30/63] lr: 1.9590e-03 eta: 11:23:25 time: 0.6341 data_time: 0.0331 memory: 14901 loss: 2.3451 loss_prob: 1.4187 loss_thr: 0.6942 loss_db: 0.2322 2022/11/02 13:29:22 - mmengine - INFO - Epoch(train) [126][35/63] lr: 1.9590e-03 eta: 11:23:25 time: 0.6387 data_time: 0.0222 memory: 14901 loss: 2.3163 loss_prob: 1.3992 loss_thr: 0.6882 loss_db: 0.2290 2022/11/02 13:29:25 - mmengine - INFO - Epoch(train) [126][40/63] lr: 1.9590e-03 eta: 11:23:17 time: 0.5778 data_time: 0.0068 memory: 14901 loss: 2.2898 loss_prob: 1.3783 loss_thr: 0.6846 loss_db: 0.2270 2022/11/02 13:29:27 - mmengine - INFO - Epoch(train) [126][45/63] lr: 1.9590e-03 eta: 11:23:17 time: 0.5138 data_time: 0.0068 memory: 14901 loss: 2.2363 loss_prob: 1.3361 loss_thr: 0.6786 loss_db: 0.2217 2022/11/02 13:29:31 - mmengine - INFO - Epoch(train) [126][50/63] lr: 1.9590e-03 eta: 11:23:13 time: 0.6363 data_time: 0.0173 memory: 14901 loss: 2.2743 loss_prob: 1.3767 loss_thr: 0.6755 loss_db: 0.2222 2022/11/02 13:29:34 - mmengine - INFO - Epoch(train) [126][55/63] lr: 1.9590e-03 eta: 11:23:13 time: 0.7106 data_time: 0.0246 memory: 14901 loss: 2.2111 loss_prob: 1.3158 loss_thr: 0.6823 loss_db: 0.2129 2022/11/02 13:29:37 - mmengine - INFO - Epoch(train) [126][60/63] lr: 1.9590e-03 eta: 11:23:05 time: 0.5811 data_time: 0.0124 memory: 14901 loss: 2.1759 loss_prob: 1.2867 loss_thr: 0.6794 loss_db: 0.2097 2022/11/02 13:29:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:29:43 - mmengine - INFO - Epoch(train) [127][5/63] lr: 1.9574e-03 eta: 11:23:05 time: 0.7661 data_time: 0.2637 memory: 14901 loss: 2.3790 loss_prob: 1.4566 loss_thr: 0.6910 loss_db: 0.2314 2022/11/02 13:29:46 - mmengine - INFO - Epoch(train) [127][10/63] lr: 1.9574e-03 eta: 11:23:00 time: 0.8196 data_time: 0.2632 memory: 14901 loss: 2.3356 loss_prob: 1.4092 loss_thr: 0.7007 loss_db: 0.2257 2022/11/02 13:29:49 - mmengine - INFO - Epoch(train) [127][15/63] lr: 1.9574e-03 eta: 11:23:00 time: 0.5227 data_time: 0.0054 memory: 14901 loss: 2.4047 loss_prob: 1.4424 loss_thr: 0.7201 loss_db: 0.2422 2022/11/02 13:29:51 - mmengine - INFO - Epoch(train) [127][20/63] lr: 1.9574e-03 eta: 11:22:43 time: 0.4782 data_time: 0.0061 memory: 14901 loss: 2.3198 loss_prob: 1.3961 loss_thr: 0.6885 loss_db: 0.2351 2022/11/02 13:29:54 - mmengine - INFO - Epoch(train) [127][25/63] lr: 1.9574e-03 eta: 11:22:43 time: 0.4864 data_time: 0.0118 memory: 14901 loss: 2.3565 loss_prob: 1.4499 loss_thr: 0.6695 loss_db: 0.2371 2022/11/02 13:29:56 - mmengine - INFO - Epoch(train) [127][30/63] lr: 1.9574e-03 eta: 11:22:32 time: 0.5490 data_time: 0.0272 memory: 14901 loss: 2.3957 loss_prob: 1.4695 loss_thr: 0.6847 loss_db: 0.2415 2022/11/02 13:29:59 - mmengine - INFO - Epoch(train) [127][35/63] lr: 1.9574e-03 eta: 11:22:32 time: 0.5276 data_time: 0.0268 memory: 14901 loss: 2.1710 loss_prob: 1.2933 loss_thr: 0.6709 loss_db: 0.2069 2022/11/02 13:30:01 - mmengine - INFO - Epoch(train) [127][40/63] lr: 1.9574e-03 eta: 11:22:18 time: 0.5019 data_time: 0.0118 memory: 14901 loss: 2.3383 loss_prob: 1.4231 loss_thr: 0.6858 loss_db: 0.2294 2022/11/02 13:30:04 - mmengine - INFO - Epoch(train) [127][45/63] lr: 1.9574e-03 eta: 11:22:18 time: 0.4922 data_time: 0.0056 memory: 14901 loss: 2.3624 loss_prob: 1.4392 loss_thr: 0.6847 loss_db: 0.2385 2022/11/02 13:30:06 - mmengine - INFO - Epoch(train) [127][50/63] lr: 1.9574e-03 eta: 11:22:03 time: 0.5079 data_time: 0.0229 memory: 14901 loss: 2.0855 loss_prob: 1.2426 loss_thr: 0.6414 loss_db: 0.2015 2022/11/02 13:30:09 - mmengine - INFO - Epoch(train) [127][55/63] lr: 1.9574e-03 eta: 11:22:03 time: 0.5587 data_time: 0.0243 memory: 14901 loss: 2.0721 loss_prob: 1.2220 loss_thr: 0.6540 loss_db: 0.1961 2022/11/02 13:30:12 - mmengine - INFO - Epoch(train) [127][60/63] lr: 1.9574e-03 eta: 11:21:54 time: 0.5647 data_time: 0.0076 memory: 14901 loss: 2.3381 loss_prob: 1.4252 loss_thr: 0.6765 loss_db: 0.2364 2022/11/02 13:30:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:30:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:30:18 - mmengine - INFO - Epoch(train) [128][5/63] lr: 1.9557e-03 eta: 11:21:54 time: 0.7331 data_time: 0.2150 memory: 14901 loss: 2.1568 loss_prob: 1.2976 loss_thr: 0.6459 loss_db: 0.2133 2022/11/02 13:30:21 - mmengine - INFO - Epoch(train) [128][10/63] lr: 1.9557e-03 eta: 11:21:46 time: 0.7899 data_time: 0.2150 memory: 14901 loss: 2.3149 loss_prob: 1.4094 loss_thr: 0.6752 loss_db: 0.2302 2022/11/02 13:30:24 - mmengine - INFO - Epoch(train) [128][15/63] lr: 1.9557e-03 eta: 11:21:46 time: 0.5281 data_time: 0.0049 memory: 14901 loss: 2.2982 loss_prob: 1.3949 loss_thr: 0.6780 loss_db: 0.2253 2022/11/02 13:30:26 - mmengine - INFO - Epoch(train) [128][20/63] lr: 1.9557e-03 eta: 11:21:30 time: 0.4899 data_time: 0.0051 memory: 14901 loss: 2.1454 loss_prob: 1.2764 loss_thr: 0.6653 loss_db: 0.2037 2022/11/02 13:30:28 - mmengine - INFO - Epoch(train) [128][25/63] lr: 1.9557e-03 eta: 11:21:30 time: 0.4766 data_time: 0.0160 memory: 14901 loss: 2.2290 loss_prob: 1.3310 loss_thr: 0.6853 loss_db: 0.2128 2022/11/02 13:30:31 - mmengine - INFO - Epoch(train) [128][30/63] lr: 1.9557e-03 eta: 11:21:14 time: 0.4834 data_time: 0.0367 memory: 14901 loss: 2.3074 loss_prob: 1.4068 loss_thr: 0.6760 loss_db: 0.2246 2022/11/02 13:30:33 - mmengine - INFO - Epoch(train) [128][35/63] lr: 1.9557e-03 eta: 11:21:14 time: 0.5039 data_time: 0.0278 memory: 14901 loss: 2.4137 loss_prob: 1.4956 loss_thr: 0.6803 loss_db: 0.2378 2022/11/02 13:30:36 - mmengine - INFO - Epoch(train) [128][40/63] lr: 1.9557e-03 eta: 11:21:01 time: 0.5218 data_time: 0.0071 memory: 14901 loss: 2.5015 loss_prob: 1.5257 loss_thr: 0.7273 loss_db: 0.2484 2022/11/02 13:30:38 - mmengine - INFO - Epoch(train) [128][45/63] lr: 1.9557e-03 eta: 11:21:01 time: 0.5106 data_time: 0.0049 memory: 14901 loss: 2.2760 loss_prob: 1.3540 loss_thr: 0.6991 loss_db: 0.2229 2022/11/02 13:30:41 - mmengine - INFO - Epoch(train) [128][50/63] lr: 1.9557e-03 eta: 11:20:47 time: 0.5127 data_time: 0.0283 memory: 14901 loss: 2.1371 loss_prob: 1.2755 loss_thr: 0.6583 loss_db: 0.2034 2022/11/02 13:30:44 - mmengine - INFO - Epoch(train) [128][55/63] lr: 1.9557e-03 eta: 11:20:47 time: 0.5368 data_time: 0.0336 memory: 14901 loss: 2.2015 loss_prob: 1.3163 loss_thr: 0.6736 loss_db: 0.2116 2022/11/02 13:30:46 - mmengine - INFO - Epoch(train) [128][60/63] lr: 1.9557e-03 eta: 11:20:32 time: 0.4929 data_time: 0.0097 memory: 14901 loss: 2.4065 loss_prob: 1.4660 loss_thr: 0.7004 loss_db: 0.2402 2022/11/02 13:30:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:30:52 - mmengine - INFO - Epoch(train) [129][5/63] lr: 1.9541e-03 eta: 11:20:32 time: 0.6942 data_time: 0.1993 memory: 14901 loss: 2.3648 loss_prob: 1.4533 loss_thr: 0.6716 loss_db: 0.2399 2022/11/02 13:30:55 - mmengine - INFO - Epoch(train) [129][10/63] lr: 1.9541e-03 eta: 11:20:18 time: 0.7176 data_time: 0.2007 memory: 14901 loss: 2.2218 loss_prob: 1.3315 loss_thr: 0.6682 loss_db: 0.2221 2022/11/02 13:30:57 - mmengine - INFO - Epoch(train) [129][15/63] lr: 1.9541e-03 eta: 11:20:18 time: 0.4708 data_time: 0.0091 memory: 14901 loss: 2.2256 loss_prob: 1.3250 loss_thr: 0.6846 loss_db: 0.2160 2022/11/02 13:30:59 - mmengine - INFO - Epoch(train) [129][20/63] lr: 1.9541e-03 eta: 11:20:01 time: 0.4657 data_time: 0.0101 memory: 14901 loss: 2.2561 loss_prob: 1.3541 loss_thr: 0.6836 loss_db: 0.2183 2022/11/02 13:31:02 - mmengine - INFO - Epoch(train) [129][25/63] lr: 1.9541e-03 eta: 11:20:01 time: 0.4849 data_time: 0.0229 memory: 14901 loss: 2.2992 loss_prob: 1.3903 loss_thr: 0.6860 loss_db: 0.2229 2022/11/02 13:31:04 - mmengine - INFO - Epoch(train) [129][30/63] lr: 1.9541e-03 eta: 11:19:45 time: 0.4919 data_time: 0.0281 memory: 14901 loss: 2.2288 loss_prob: 1.3413 loss_thr: 0.6715 loss_db: 0.2160 2022/11/02 13:31:06 - mmengine - INFO - Epoch(train) [129][35/63] lr: 1.9541e-03 eta: 11:19:45 time: 0.4757 data_time: 0.0124 memory: 14901 loss: 2.2245 loss_prob: 1.3304 loss_thr: 0.6759 loss_db: 0.2182 2022/11/02 13:31:09 - mmengine - INFO - Epoch(train) [129][40/63] lr: 1.9541e-03 eta: 11:19:29 time: 0.4787 data_time: 0.0087 memory: 14901 loss: 2.3465 loss_prob: 1.4128 loss_thr: 0.7019 loss_db: 0.2317 2022/11/02 13:31:11 - mmengine - INFO - Epoch(train) [129][45/63] lr: 1.9541e-03 eta: 11:19:29 time: 0.4834 data_time: 0.0082 memory: 14901 loss: 2.2971 loss_prob: 1.3630 loss_thr: 0.7092 loss_db: 0.2249 2022/11/02 13:31:16 - mmengine - INFO - Epoch(train) [129][50/63] lr: 1.9541e-03 eta: 11:19:31 time: 0.7015 data_time: 0.0197 memory: 14901 loss: 2.1768 loss_prob: 1.2917 loss_thr: 0.6757 loss_db: 0.2093 2022/11/02 13:31:19 - mmengine - INFO - Epoch(train) [129][55/63] lr: 1.9541e-03 eta: 11:19:31 time: 0.7830 data_time: 0.0261 memory: 14901 loss: 2.2376 loss_prob: 1.3528 loss_thr: 0.6647 loss_db: 0.2202 2022/11/02 13:31:22 - mmengine - INFO - Epoch(train) [129][60/63] lr: 1.9541e-03 eta: 11:19:26 time: 0.6219 data_time: 0.0108 memory: 14901 loss: 2.2955 loss_prob: 1.3806 loss_thr: 0.6874 loss_db: 0.2274 2022/11/02 13:31:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:31:31 - mmengine - INFO - Epoch(train) [130][5/63] lr: 1.9524e-03 eta: 11:19:26 time: 0.9506 data_time: 0.2483 memory: 14901 loss: 2.2965 loss_prob: 1.3618 loss_thr: 0.7130 loss_db: 0.2217 2022/11/02 13:31:34 - mmengine - INFO - Epoch(train) [130][10/63] lr: 1.9524e-03 eta: 11:19:31 time: 0.9334 data_time: 0.2434 memory: 14901 loss: 2.2479 loss_prob: 1.3333 loss_thr: 0.6967 loss_db: 0.2179 2022/11/02 13:31:36 - mmengine - INFO - Epoch(train) [130][15/63] lr: 1.9524e-03 eta: 11:19:31 time: 0.5605 data_time: 0.0051 memory: 14901 loss: 2.2992 loss_prob: 1.3896 loss_thr: 0.6841 loss_db: 0.2255 2022/11/02 13:31:39 - mmengine - INFO - Epoch(train) [130][20/63] lr: 1.9524e-03 eta: 11:19:18 time: 0.5286 data_time: 0.0048 memory: 14901 loss: 2.2394 loss_prob: 1.3316 loss_thr: 0.6933 loss_db: 0.2145 2022/11/02 13:31:41 - mmengine - INFO - Epoch(train) [130][25/63] lr: 1.9524e-03 eta: 11:19:18 time: 0.5255 data_time: 0.0141 memory: 14901 loss: 2.1578 loss_prob: 1.2686 loss_thr: 0.6786 loss_db: 0.2106 2022/11/02 13:31:45 - mmengine - INFO - Epoch(train) [130][30/63] lr: 1.9524e-03 eta: 11:19:17 time: 0.6607 data_time: 0.0348 memory: 14901 loss: 2.1121 loss_prob: 1.2529 loss_thr: 0.6517 loss_db: 0.2076 2022/11/02 13:31:48 - mmengine - INFO - Epoch(train) [130][35/63] lr: 1.9524e-03 eta: 11:19:17 time: 0.6498 data_time: 0.0253 memory: 14901 loss: 2.1842 loss_prob: 1.2940 loss_thr: 0.6827 loss_db: 0.2076 2022/11/02 13:31:50 - mmengine - INFO - Epoch(train) [130][40/63] lr: 1.9524e-03 eta: 11:19:00 time: 0.4754 data_time: 0.0043 memory: 14901 loss: 2.2674 loss_prob: 1.3597 loss_thr: 0.6922 loss_db: 0.2155 2022/11/02 13:31:53 - mmengine - INFO - Epoch(train) [130][45/63] lr: 1.9524e-03 eta: 11:19:00 time: 0.5313 data_time: 0.0072 memory: 14901 loss: 2.3965 loss_prob: 1.4621 loss_thr: 0.7045 loss_db: 0.2300 2022/11/02 13:31:57 - mmengine - INFO - Epoch(train) [130][50/63] lr: 1.9524e-03 eta: 11:18:59 time: 0.6595 data_time: 0.0267 memory: 14901 loss: 2.3782 loss_prob: 1.4402 loss_thr: 0.7033 loss_db: 0.2348 2022/11/02 13:32:00 - mmengine - INFO - Epoch(train) [130][55/63] lr: 1.9524e-03 eta: 11:18:59 time: 0.7128 data_time: 0.0243 memory: 14901 loss: 2.1381 loss_prob: 1.2609 loss_thr: 0.6693 loss_db: 0.2079 2022/11/02 13:32:04 - mmengine - INFO - Epoch(train) [130][60/63] lr: 1.9524e-03 eta: 11:19:03 time: 0.7339 data_time: 0.0056 memory: 14901 loss: 2.2583 loss_prob: 1.3660 loss_thr: 0.6682 loss_db: 0.2242 2022/11/02 13:32:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:32:11 - mmengine - INFO - Epoch(train) [131][5/63] lr: 1.9508e-03 eta: 11:19:03 time: 0.8337 data_time: 0.2293 memory: 14901 loss: 2.2031 loss_prob: 1.3395 loss_thr: 0.6436 loss_db: 0.2199 2022/11/02 13:32:14 - mmengine - INFO - Epoch(train) [131][10/63] lr: 1.9508e-03 eta: 11:19:00 time: 0.8413 data_time: 0.2295 memory: 14901 loss: 2.2059 loss_prob: 1.3155 loss_thr: 0.6754 loss_db: 0.2150 2022/11/02 13:32:17 - mmengine - INFO - Epoch(train) [131][15/63] lr: 1.9508e-03 eta: 11:19:00 time: 0.5395 data_time: 0.0063 memory: 14901 loss: 2.1983 loss_prob: 1.3140 loss_thr: 0.6696 loss_db: 0.2148 2022/11/02 13:32:19 - mmengine - INFO - Epoch(train) [131][20/63] lr: 1.9508e-03 eta: 11:18:49 time: 0.5388 data_time: 0.0068 memory: 14901 loss: 2.2292 loss_prob: 1.3277 loss_thr: 0.6837 loss_db: 0.2178 2022/11/02 13:32:22 - mmengine - INFO - Epoch(train) [131][25/63] lr: 1.9508e-03 eta: 11:18:49 time: 0.5037 data_time: 0.0286 memory: 14901 loss: 2.3849 loss_prob: 1.4476 loss_thr: 0.6998 loss_db: 0.2375 2022/11/02 13:32:24 - mmengine - INFO - Epoch(train) [131][30/63] lr: 1.9508e-03 eta: 11:18:33 time: 0.4855 data_time: 0.0324 memory: 14901 loss: 2.2996 loss_prob: 1.4020 loss_thr: 0.6721 loss_db: 0.2256 2022/11/02 13:32:26 - mmengine - INFO - Epoch(train) [131][35/63] lr: 1.9508e-03 eta: 11:18:33 time: 0.4677 data_time: 0.0092 memory: 14901 loss: 2.1439 loss_prob: 1.2679 loss_thr: 0.6718 loss_db: 0.2042 2022/11/02 13:32:29 - mmengine - INFO - Epoch(train) [131][40/63] lr: 1.9508e-03 eta: 11:18:17 time: 0.4772 data_time: 0.0057 memory: 14901 loss: 2.2691 loss_prob: 1.3665 loss_thr: 0.6785 loss_db: 0.2241 2022/11/02 13:32:31 - mmengine - INFO - Epoch(train) [131][45/63] lr: 1.9508e-03 eta: 11:18:17 time: 0.5059 data_time: 0.0055 memory: 14901 loss: 2.2870 loss_prob: 1.3805 loss_thr: 0.6797 loss_db: 0.2268 2022/11/02 13:32:34 - mmengine - INFO - Epoch(train) [131][50/63] lr: 1.9508e-03 eta: 11:18:08 time: 0.5743 data_time: 0.0164 memory: 14901 loss: 2.2382 loss_prob: 1.3407 loss_thr: 0.6761 loss_db: 0.2214 2022/11/02 13:32:38 - mmengine - INFO - Epoch(train) [131][55/63] lr: 1.9508e-03 eta: 11:18:08 time: 0.6188 data_time: 0.0205 memory: 14901 loss: 2.1399 loss_prob: 1.2783 loss_thr: 0.6543 loss_db: 0.2073 2022/11/02 13:32:40 - mmengine - INFO - Epoch(train) [131][60/63] lr: 1.9508e-03 eta: 11:18:02 time: 0.5988 data_time: 0.0089 memory: 14901 loss: 2.2688 loss_prob: 1.4041 loss_thr: 0.6426 loss_db: 0.2221 2022/11/02 13:32:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:32:47 - mmengine - INFO - Epoch(train) [132][5/63] lr: 1.9492e-03 eta: 11:18:02 time: 0.7696 data_time: 0.2345 memory: 14901 loss: 2.2711 loss_prob: 1.4033 loss_thr: 0.6467 loss_db: 0.2212 2022/11/02 13:32:50 - mmengine - INFO - Epoch(train) [132][10/63] lr: 1.9492e-03 eta: 11:17:51 time: 0.7459 data_time: 0.2367 memory: 14901 loss: 2.2123 loss_prob: 1.3392 loss_thr: 0.6571 loss_db: 0.2159 2022/11/02 13:32:52 - mmengine - INFO - Epoch(train) [132][15/63] lr: 1.9492e-03 eta: 11:17:51 time: 0.4813 data_time: 0.0079 memory: 14901 loss: 2.3495 loss_prob: 1.4328 loss_thr: 0.6877 loss_db: 0.2289 2022/11/02 13:32:54 - mmengine - INFO - Epoch(train) [132][20/63] lr: 1.9492e-03 eta: 11:17:35 time: 0.4881 data_time: 0.0054 memory: 14901 loss: 2.3187 loss_prob: 1.4063 loss_thr: 0.6892 loss_db: 0.2233 2022/11/02 13:32:57 - mmengine - INFO - Epoch(train) [132][25/63] lr: 1.9492e-03 eta: 11:17:35 time: 0.5014 data_time: 0.0167 memory: 14901 loss: 2.1858 loss_prob: 1.3058 loss_thr: 0.6640 loss_db: 0.2160 2022/11/02 13:33:00 - mmengine - INFO - Epoch(train) [132][30/63] lr: 1.9492e-03 eta: 11:17:22 time: 0.5211 data_time: 0.0273 memory: 14901 loss: 2.1734 loss_prob: 1.2988 loss_thr: 0.6614 loss_db: 0.2132 2022/11/02 13:33:02 - mmengine - INFO - Epoch(train) [132][35/63] lr: 1.9492e-03 eta: 11:17:22 time: 0.5569 data_time: 0.0204 memory: 14901 loss: 2.1552 loss_prob: 1.2928 loss_thr: 0.6522 loss_db: 0.2101 2022/11/02 13:33:05 - mmengine - INFO - Epoch(train) [132][40/63] lr: 1.9492e-03 eta: 11:17:10 time: 0.5280 data_time: 0.0105 memory: 14901 loss: 2.1003 loss_prob: 1.2480 loss_thr: 0.6477 loss_db: 0.2045 2022/11/02 13:33:07 - mmengine - INFO - Epoch(train) [132][45/63] lr: 1.9492e-03 eta: 11:17:10 time: 0.4803 data_time: 0.0090 memory: 14901 loss: 2.0844 loss_prob: 1.2226 loss_thr: 0.6597 loss_db: 0.2021 2022/11/02 13:33:10 - mmengine - INFO - Epoch(train) [132][50/63] lr: 1.9492e-03 eta: 11:16:55 time: 0.4912 data_time: 0.0194 memory: 14901 loss: 2.0616 loss_prob: 1.2091 loss_thr: 0.6552 loss_db: 0.1973 2022/11/02 13:33:13 - mmengine - INFO - Epoch(train) [132][55/63] lr: 1.9492e-03 eta: 11:16:55 time: 0.5230 data_time: 0.0189 memory: 14901 loss: 2.1003 loss_prob: 1.2273 loss_thr: 0.6738 loss_db: 0.1993 2022/11/02 13:33:15 - mmengine - INFO - Epoch(train) [132][60/63] lr: 1.9492e-03 eta: 11:16:43 time: 0.5289 data_time: 0.0106 memory: 14901 loss: 2.1697 loss_prob: 1.2764 loss_thr: 0.6792 loss_db: 0.2141 2022/11/02 13:33:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:33:21 - mmengine - INFO - Epoch(train) [133][5/63] lr: 1.9475e-03 eta: 11:16:43 time: 0.7189 data_time: 0.2352 memory: 14901 loss: 2.2361 loss_prob: 1.3299 loss_thr: 0.6788 loss_db: 0.2274 2022/11/02 13:33:24 - mmengine - INFO - Epoch(train) [133][10/63] lr: 1.9475e-03 eta: 11:16:31 time: 0.7373 data_time: 0.2447 memory: 14901 loss: 2.4229 loss_prob: 1.4678 loss_thr: 0.7079 loss_db: 0.2472 2022/11/02 13:33:26 - mmengine - INFO - Epoch(train) [133][15/63] lr: 1.9475e-03 eta: 11:16:31 time: 0.4998 data_time: 0.0200 memory: 14901 loss: 2.5062 loss_prob: 1.5263 loss_thr: 0.7290 loss_db: 0.2509 2022/11/02 13:33:29 - mmengine - INFO - Epoch(train) [133][20/63] lr: 1.9475e-03 eta: 11:16:18 time: 0.5124 data_time: 0.0135 memory: 14901 loss: 2.5565 loss_prob: 1.5531 loss_thr: 0.7466 loss_db: 0.2568 2022/11/02 13:33:32 - mmengine - INFO - Epoch(train) [133][25/63] lr: 1.9475e-03 eta: 11:16:18 time: 0.5582 data_time: 0.0392 memory: 14901 loss: 2.8499 loss_prob: 1.8026 loss_thr: 0.7555 loss_db: 0.2918 2022/11/02 13:33:34 - mmengine - INFO - Epoch(train) [133][30/63] lr: 1.9475e-03 eta: 11:16:08 time: 0.5620 data_time: 0.0506 memory: 14901 loss: 2.8141 loss_prob: 1.7889 loss_thr: 0.7381 loss_db: 0.2872 2022/11/02 13:33:37 - mmengine - INFO - Epoch(train) [133][35/63] lr: 1.9475e-03 eta: 11:16:08 time: 0.5013 data_time: 0.0221 memory: 14901 loss: 2.4377 loss_prob: 1.4903 loss_thr: 0.7029 loss_db: 0.2445 2022/11/02 13:33:39 - mmengine - INFO - Epoch(train) [133][40/63] lr: 1.9475e-03 eta: 11:15:52 time: 0.4778 data_time: 0.0046 memory: 14901 loss: 2.2320 loss_prob: 1.3394 loss_thr: 0.6761 loss_db: 0.2164 2022/11/02 13:33:42 - mmengine - INFO - Epoch(train) [133][45/63] lr: 1.9475e-03 eta: 11:15:52 time: 0.4795 data_time: 0.0045 memory: 14901 loss: 2.2238 loss_prob: 1.3341 loss_thr: 0.6702 loss_db: 0.2196 2022/11/02 13:33:44 - mmengine - INFO - Epoch(train) [133][50/63] lr: 1.9475e-03 eta: 11:15:40 time: 0.5182 data_time: 0.0155 memory: 14901 loss: 2.2708 loss_prob: 1.3615 loss_thr: 0.6817 loss_db: 0.2275 2022/11/02 13:33:47 - mmengine - INFO - Epoch(train) [133][55/63] lr: 1.9475e-03 eta: 11:15:40 time: 0.5252 data_time: 0.0243 memory: 14901 loss: 2.2205 loss_prob: 1.3458 loss_thr: 0.6565 loss_db: 0.2182 2022/11/02 13:33:49 - mmengine - INFO - Epoch(train) [133][60/63] lr: 1.9475e-03 eta: 11:15:25 time: 0.5030 data_time: 0.0140 memory: 14901 loss: 2.3105 loss_prob: 1.4083 loss_thr: 0.6758 loss_db: 0.2264 2022/11/02 13:33:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:33:58 - mmengine - INFO - Epoch(train) [134][5/63] lr: 1.9459e-03 eta: 11:15:25 time: 0.9886 data_time: 0.2509 memory: 14901 loss: 2.1130 loss_prob: 1.2655 loss_thr: 0.6426 loss_db: 0.2049 2022/11/02 13:34:02 - mmengine - INFO - Epoch(train) [134][10/63] lr: 1.9459e-03 eta: 11:15:39 time: 1.0463 data_time: 0.2515 memory: 14901 loss: 2.1722 loss_prob: 1.3093 loss_thr: 0.6507 loss_db: 0.2123 2022/11/02 13:34:05 - mmengine - INFO - Epoch(train) [134][15/63] lr: 1.9459e-03 eta: 11:15:39 time: 0.6522 data_time: 0.0092 memory: 14901 loss: 2.1830 loss_prob: 1.2949 loss_thr: 0.6747 loss_db: 0.2134 2022/11/02 13:34:08 - mmengine - INFO - Epoch(train) [134][20/63] lr: 1.9459e-03 eta: 11:15:35 time: 0.6334 data_time: 0.0079 memory: 14901 loss: 2.1469 loss_prob: 1.2577 loss_thr: 0.6792 loss_db: 0.2100 2022/11/02 13:34:10 - mmengine - INFO - Epoch(train) [134][25/63] lr: 1.9459e-03 eta: 11:15:35 time: 0.5670 data_time: 0.0254 memory: 14901 loss: 2.1160 loss_prob: 1.2392 loss_thr: 0.6686 loss_db: 0.2082 2022/11/02 13:34:13 - mmengine - INFO - Epoch(train) [134][30/63] lr: 1.9459e-03 eta: 11:15:23 time: 0.5260 data_time: 0.0280 memory: 14901 loss: 2.1437 loss_prob: 1.2710 loss_thr: 0.6633 loss_db: 0.2094 2022/11/02 13:34:16 - mmengine - INFO - Epoch(train) [134][35/63] lr: 1.9459e-03 eta: 11:15:23 time: 0.5203 data_time: 0.0203 memory: 14901 loss: 2.1606 loss_prob: 1.3120 loss_thr: 0.6357 loss_db: 0.2130 2022/11/02 13:34:19 - mmengine - INFO - Epoch(train) [134][40/63] lr: 1.9459e-03 eta: 11:15:12 time: 0.5406 data_time: 0.0196 memory: 14901 loss: 2.1336 loss_prob: 1.2927 loss_thr: 0.6310 loss_db: 0.2099 2022/11/02 13:34:21 - mmengine - INFO - Epoch(train) [134][45/63] lr: 1.9459e-03 eta: 11:15:12 time: 0.5555 data_time: 0.0068 memory: 14901 loss: 2.2131 loss_prob: 1.3455 loss_thr: 0.6533 loss_db: 0.2143 2022/11/02 13:34:24 - mmengine - INFO - Epoch(train) [134][50/63] lr: 1.9459e-03 eta: 11:15:05 time: 0.5878 data_time: 0.0175 memory: 14901 loss: 2.3468 loss_prob: 1.4269 loss_thr: 0.6925 loss_db: 0.2274 2022/11/02 13:34:27 - mmengine - INFO - Epoch(train) [134][55/63] lr: 1.9459e-03 eta: 11:15:05 time: 0.6045 data_time: 0.0196 memory: 14901 loss: 2.3580 loss_prob: 1.4192 loss_thr: 0.7079 loss_db: 0.2309 2022/11/02 13:34:30 - mmengine - INFO - Epoch(train) [134][60/63] lr: 1.9459e-03 eta: 11:14:55 time: 0.5630 data_time: 0.0085 memory: 14901 loss: 2.2040 loss_prob: 1.3183 loss_thr: 0.6754 loss_db: 0.2102 2022/11/02 13:34:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:34:36 - mmengine - INFO - Epoch(train) [135][5/63] lr: 1.9442e-03 eta: 11:14:55 time: 0.7564 data_time: 0.1978 memory: 14901 loss: 2.0174 loss_prob: 1.1890 loss_thr: 0.6371 loss_db: 0.1914 2022/11/02 13:34:39 - mmengine - INFO - Epoch(train) [135][10/63] lr: 1.9442e-03 eta: 11:14:47 time: 0.7779 data_time: 0.2042 memory: 14901 loss: 2.1285 loss_prob: 1.2657 loss_thr: 0.6570 loss_db: 0.2058 2022/11/02 13:34:42 - mmengine - INFO - Epoch(train) [135][15/63] lr: 1.9442e-03 eta: 11:14:47 time: 0.5685 data_time: 0.0171 memory: 14901 loss: 2.2452 loss_prob: 1.3486 loss_thr: 0.6799 loss_db: 0.2167 2022/11/02 13:34:44 - mmengine - INFO - Epoch(train) [135][20/63] lr: 1.9442e-03 eta: 11:14:36 time: 0.5344 data_time: 0.0079 memory: 14901 loss: 2.2940 loss_prob: 1.3782 loss_thr: 0.6910 loss_db: 0.2249 2022/11/02 13:34:48 - mmengine - INFO - Epoch(train) [135][25/63] lr: 1.9442e-03 eta: 11:14:36 time: 0.6082 data_time: 0.0145 memory: 14901 loss: 2.2552 loss_prob: 1.3451 loss_thr: 0.6910 loss_db: 0.2190 2022/11/02 13:34:51 - mmengine - INFO - Epoch(train) [135][30/63] lr: 1.9442e-03 eta: 11:14:34 time: 0.6546 data_time: 0.0254 memory: 14901 loss: 2.3337 loss_prob: 1.4144 loss_thr: 0.6907 loss_db: 0.2286 2022/11/02 13:34:54 - mmengine - INFO - Epoch(train) [135][35/63] lr: 1.9442e-03 eta: 11:14:34 time: 0.5640 data_time: 0.0221 memory: 14901 loss: 2.2595 loss_prob: 1.3707 loss_thr: 0.6665 loss_db: 0.2223 2022/11/02 13:34:56 - mmengine - INFO - Epoch(train) [135][40/63] lr: 1.9442e-03 eta: 11:14:21 time: 0.5198 data_time: 0.0127 memory: 14901 loss: 2.1070 loss_prob: 1.2484 loss_thr: 0.6549 loss_db: 0.2037 2022/11/02 13:34:59 - mmengine - INFO - Epoch(train) [135][45/63] lr: 1.9442e-03 eta: 11:14:21 time: 0.4918 data_time: 0.0064 memory: 14901 loss: 2.3327 loss_prob: 1.4197 loss_thr: 0.6859 loss_db: 0.2271 2022/11/02 13:35:01 - mmengine - INFO - Epoch(train) [135][50/63] lr: 1.9442e-03 eta: 11:14:06 time: 0.4920 data_time: 0.0106 memory: 14901 loss: 2.3826 loss_prob: 1.4775 loss_thr: 0.6704 loss_db: 0.2347 2022/11/02 13:35:04 - mmengine - INFO - Epoch(train) [135][55/63] lr: 1.9442e-03 eta: 11:14:06 time: 0.5019 data_time: 0.0158 memory: 14901 loss: 2.2181 loss_prob: 1.3294 loss_thr: 0.6747 loss_db: 0.2141 2022/11/02 13:35:06 - mmengine - INFO - Epoch(train) [135][60/63] lr: 1.9442e-03 eta: 11:13:50 time: 0.4782 data_time: 0.0123 memory: 14901 loss: 2.1362 loss_prob: 1.2530 loss_thr: 0.6798 loss_db: 0.2034 2022/11/02 13:35:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:35:12 - mmengine - INFO - Epoch(train) [136][5/63] lr: 1.9426e-03 eta: 11:13:50 time: 0.7231 data_time: 0.2257 memory: 14901 loss: 2.0040 loss_prob: 1.1646 loss_thr: 0.6468 loss_db: 0.1925 2022/11/02 13:35:15 - mmengine - INFO - Epoch(train) [136][10/63] lr: 1.9426e-03 eta: 11:13:41 time: 0.7616 data_time: 0.2222 memory: 14901 loss: 2.1612 loss_prob: 1.2957 loss_thr: 0.6518 loss_db: 0.2137 2022/11/02 13:35:17 - mmengine - INFO - Epoch(train) [136][15/63] lr: 1.9426e-03 eta: 11:13:41 time: 0.5196 data_time: 0.0070 memory: 14901 loss: 2.2027 loss_prob: 1.3341 loss_thr: 0.6497 loss_db: 0.2190 2022/11/02 13:35:20 - mmengine - INFO - Epoch(train) [136][20/63] lr: 1.9426e-03 eta: 11:13:29 time: 0.5348 data_time: 0.0060 memory: 14901 loss: 2.0608 loss_prob: 1.2082 loss_thr: 0.6522 loss_db: 0.2003 2022/11/02 13:35:23 - mmengine - INFO - Epoch(train) [136][25/63] lr: 1.9426e-03 eta: 11:13:29 time: 0.5190 data_time: 0.0289 memory: 14901 loss: 2.1217 loss_prob: 1.2682 loss_thr: 0.6453 loss_db: 0.2082 2022/11/02 13:35:25 - mmengine - INFO - Epoch(train) [136][30/63] lr: 1.9426e-03 eta: 11:13:15 time: 0.4976 data_time: 0.0332 memory: 14901 loss: 2.1063 loss_prob: 1.2579 loss_thr: 0.6423 loss_db: 0.2061 2022/11/02 13:35:27 - mmengine - INFO - Epoch(train) [136][35/63] lr: 1.9426e-03 eta: 11:13:15 time: 0.4742 data_time: 0.0125 memory: 14901 loss: 1.9606 loss_prob: 1.1373 loss_thr: 0.6337 loss_db: 0.1897 2022/11/02 13:35:30 - mmengine - INFO - Epoch(train) [136][40/63] lr: 1.9426e-03 eta: 11:13:01 time: 0.4923 data_time: 0.0083 memory: 14901 loss: 2.1321 loss_prob: 1.2719 loss_thr: 0.6482 loss_db: 0.2120 2022/11/02 13:35:32 - mmengine - INFO - Epoch(train) [136][45/63] lr: 1.9426e-03 eta: 11:13:01 time: 0.4836 data_time: 0.0052 memory: 14901 loss: 2.3291 loss_prob: 1.4193 loss_thr: 0.6809 loss_db: 0.2289 2022/11/02 13:35:35 - mmengine - INFO - Epoch(train) [136][50/63] lr: 1.9426e-03 eta: 11:12:44 time: 0.4724 data_time: 0.0155 memory: 14901 loss: 2.2230 loss_prob: 1.3284 loss_thr: 0.6789 loss_db: 0.2157 2022/11/02 13:35:37 - mmengine - INFO - Epoch(train) [136][55/63] lr: 1.9426e-03 eta: 11:12:44 time: 0.4808 data_time: 0.0200 memory: 14901 loss: 2.3333 loss_prob: 1.4102 loss_thr: 0.6871 loss_db: 0.2360 2022/11/02 13:35:40 - mmengine - INFO - Epoch(train) [136][60/63] lr: 1.9426e-03 eta: 11:12:32 time: 0.5154 data_time: 0.0097 memory: 14901 loss: 2.2626 loss_prob: 1.3728 loss_thr: 0.6648 loss_db: 0.2250 2022/11/02 13:35:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:35:46 - mmengine - INFO - Epoch(train) [137][5/63] lr: 1.9409e-03 eta: 11:12:32 time: 0.7241 data_time: 0.2210 memory: 14901 loss: 2.0501 loss_prob: 1.2233 loss_thr: 0.6259 loss_db: 0.2009 2022/11/02 13:35:48 - mmengine - INFO - Epoch(train) [137][10/63] lr: 1.9409e-03 eta: 11:12:20 time: 0.7315 data_time: 0.2211 memory: 14901 loss: 1.9719 loss_prob: 1.1621 loss_thr: 0.6212 loss_db: 0.1886 2022/11/02 13:35:51 - mmengine - INFO - Epoch(train) [137][15/63] lr: 1.9409e-03 eta: 11:12:20 time: 0.4936 data_time: 0.0077 memory: 14901 loss: 1.9787 loss_prob: 1.1533 loss_thr: 0.6329 loss_db: 0.1925 2022/11/02 13:35:54 - mmengine - INFO - Epoch(train) [137][20/63] lr: 1.9409e-03 eta: 11:12:08 time: 0.5315 data_time: 0.0097 memory: 14901 loss: 1.8813 loss_prob: 1.0850 loss_thr: 0.6171 loss_db: 0.1793 2022/11/02 13:35:56 - mmengine - INFO - Epoch(train) [137][25/63] lr: 1.9409e-03 eta: 11:12:08 time: 0.5288 data_time: 0.0168 memory: 14901 loss: 1.9412 loss_prob: 1.1337 loss_thr: 0.6226 loss_db: 0.1848 2022/11/02 13:35:59 - mmengine - INFO - Epoch(train) [137][30/63] lr: 1.9409e-03 eta: 11:11:54 time: 0.4925 data_time: 0.0278 memory: 14901 loss: 2.0871 loss_prob: 1.2371 loss_thr: 0.6492 loss_db: 0.2008 2022/11/02 13:36:01 - mmengine - INFO - Epoch(train) [137][35/63] lr: 1.9409e-03 eta: 11:11:54 time: 0.4821 data_time: 0.0236 memory: 14901 loss: 2.0692 loss_prob: 1.2111 loss_thr: 0.6618 loss_db: 0.1964 2022/11/02 13:36:03 - mmengine - INFO - Epoch(train) [137][40/63] lr: 1.9409e-03 eta: 11:11:38 time: 0.4771 data_time: 0.0134 memory: 14901 loss: 2.0661 loss_prob: 1.2067 loss_thr: 0.6631 loss_db: 0.1964 2022/11/02 13:36:06 - mmengine - INFO - Epoch(train) [137][45/63] lr: 1.9409e-03 eta: 11:11:38 time: 0.4785 data_time: 0.0075 memory: 14901 loss: 2.0519 loss_prob: 1.2118 loss_thr: 0.6444 loss_db: 0.1957 2022/11/02 13:36:08 - mmengine - INFO - Epoch(train) [137][50/63] lr: 1.9409e-03 eta: 11:11:23 time: 0.4865 data_time: 0.0156 memory: 14901 loss: 2.0066 loss_prob: 1.1752 loss_thr: 0.6371 loss_db: 0.1943 2022/11/02 13:36:11 - mmengine - INFO - Epoch(train) [137][55/63] lr: 1.9409e-03 eta: 11:11:23 time: 0.4900 data_time: 0.0203 memory: 14901 loss: 2.0842 loss_prob: 1.2080 loss_thr: 0.6718 loss_db: 0.2043 2022/11/02 13:36:13 - mmengine - INFO - Epoch(train) [137][60/63] lr: 1.9409e-03 eta: 11:11:08 time: 0.4789 data_time: 0.0114 memory: 14901 loss: 2.2044 loss_prob: 1.3067 loss_thr: 0.6829 loss_db: 0.2149 2022/11/02 13:36:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:36:19 - mmengine - INFO - Epoch(train) [138][5/63] lr: 1.9393e-03 eta: 11:11:08 time: 0.6839 data_time: 0.2155 memory: 14901 loss: 2.1913 loss_prob: 1.3094 loss_thr: 0.6709 loss_db: 0.2111 2022/11/02 13:36:21 - mmengine - INFO - Epoch(train) [138][10/63] lr: 1.9393e-03 eta: 11:10:55 time: 0.7189 data_time: 0.2129 memory: 14901 loss: 2.0425 loss_prob: 1.1916 loss_thr: 0.6582 loss_db: 0.1927 2022/11/02 13:36:24 - mmengine - INFO - Epoch(train) [138][15/63] lr: 1.9393e-03 eta: 11:10:55 time: 0.4868 data_time: 0.0077 memory: 14901 loss: 1.9860 loss_prob: 1.1581 loss_thr: 0.6389 loss_db: 0.1890 2022/11/02 13:36:26 - mmengine - INFO - Epoch(train) [138][20/63] lr: 1.9393e-03 eta: 11:10:42 time: 0.5131 data_time: 0.0077 memory: 14901 loss: 2.0007 loss_prob: 1.1713 loss_thr: 0.6374 loss_db: 0.1920 2022/11/02 13:36:31 - mmengine - INFO - Epoch(train) [138][25/63] lr: 1.9393e-03 eta: 11:10:42 time: 0.7407 data_time: 0.0547 memory: 14901 loss: 1.9432 loss_prob: 1.1331 loss_thr: 0.6264 loss_db: 0.1837 2022/11/02 13:36:34 - mmengine - INFO - Epoch(train) [138][30/63] lr: 1.9393e-03 eta: 11:10:51 time: 0.7943 data_time: 0.0604 memory: 14901 loss: 2.1576 loss_prob: 1.2815 loss_thr: 0.6653 loss_db: 0.2108 2022/11/02 13:36:37 - mmengine - INFO - Epoch(train) [138][35/63] lr: 1.9393e-03 eta: 11:10:51 time: 0.6023 data_time: 0.0107 memory: 14901 loss: 2.1629 loss_prob: 1.2868 loss_thr: 0.6601 loss_db: 0.2160 2022/11/02 13:36:40 - mmengine - INFO - Epoch(train) [138][40/63] lr: 1.9393e-03 eta: 11:10:44 time: 0.5940 data_time: 0.0064 memory: 14901 loss: 2.0832 loss_prob: 1.2208 loss_thr: 0.6614 loss_db: 0.2010 2022/11/02 13:36:44 - mmengine - INFO - Epoch(train) [138][45/63] lr: 1.9393e-03 eta: 11:10:44 time: 0.6623 data_time: 0.0062 memory: 14901 loss: 2.1978 loss_prob: 1.3053 loss_thr: 0.6836 loss_db: 0.2089 2022/11/02 13:36:47 - mmengine - INFO - Epoch(train) [138][50/63] lr: 1.9393e-03 eta: 11:10:42 time: 0.6509 data_time: 0.0207 memory: 14901 loss: 2.1939 loss_prob: 1.3075 loss_thr: 0.6766 loss_db: 0.2098 2022/11/02 13:36:50 - mmengine - INFO - Epoch(train) [138][55/63] lr: 1.9393e-03 eta: 11:10:42 time: 0.6158 data_time: 0.0271 memory: 14901 loss: 2.4324 loss_prob: 1.4897 loss_thr: 0.6985 loss_db: 0.2442 2022/11/02 13:36:54 - mmengine - INFO - Epoch(train) [138][60/63] lr: 1.9393e-03 eta: 11:10:41 time: 0.6694 data_time: 0.0108 memory: 14901 loss: 2.5797 loss_prob: 1.6235 loss_thr: 0.6823 loss_db: 0.2739 2022/11/02 13:36:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:37:01 - mmengine - INFO - Epoch(train) [139][5/63] lr: 1.9377e-03 eta: 11:10:41 time: 0.8643 data_time: 0.2445 memory: 14901 loss: 2.4245 loss_prob: 1.4976 loss_thr: 0.6902 loss_db: 0.2366 2022/11/02 13:37:04 - mmengine - INFO - Epoch(train) [139][10/63] lr: 1.9377e-03 eta: 11:10:41 time: 0.8779 data_time: 0.2444 memory: 14901 loss: 2.2880 loss_prob: 1.3850 loss_thr: 0.6826 loss_db: 0.2204 2022/11/02 13:37:07 - mmengine - INFO - Epoch(train) [139][15/63] lr: 1.9377e-03 eta: 11:10:41 time: 0.5969 data_time: 0.0047 memory: 14901 loss: 2.3451 loss_prob: 1.4205 loss_thr: 0.6953 loss_db: 0.2293 2022/11/02 13:37:10 - mmengine - INFO - Epoch(train) [139][20/63] lr: 1.9377e-03 eta: 11:10:37 time: 0.6228 data_time: 0.0049 memory: 14901 loss: 2.3967 loss_prob: 1.4661 loss_thr: 0.6930 loss_db: 0.2376 2022/11/02 13:37:13 - mmengine - INFO - Epoch(train) [139][25/63] lr: 1.9377e-03 eta: 11:10:37 time: 0.5864 data_time: 0.0220 memory: 14901 loss: 2.2370 loss_prob: 1.3588 loss_thr: 0.6521 loss_db: 0.2261 2022/11/02 13:37:16 - mmengine - INFO - Epoch(train) [139][30/63] lr: 1.9377e-03 eta: 11:10:35 time: 0.6616 data_time: 0.0451 memory: 14901 loss: 2.6440 loss_prob: 1.6683 loss_thr: 0.6963 loss_db: 0.2794 2022/11/02 13:37:20 - mmengine - INFO - Epoch(train) [139][35/63] lr: 1.9377e-03 eta: 11:10:35 time: 0.6696 data_time: 0.0284 memory: 14901 loss: 2.7323 loss_prob: 1.7232 loss_thr: 0.7206 loss_db: 0.2886 2022/11/02 13:37:23 - mmengine - INFO - Epoch(train) [139][40/63] lr: 1.9377e-03 eta: 11:10:30 time: 0.6140 data_time: 0.0051 memory: 14901 loss: 2.3215 loss_prob: 1.4099 loss_thr: 0.6788 loss_db: 0.2328 2022/11/02 13:37:25 - mmengine - INFO - Epoch(train) [139][45/63] lr: 1.9377e-03 eta: 11:10:30 time: 0.5607 data_time: 0.0045 memory: 14901 loss: 2.3058 loss_prob: 1.4096 loss_thr: 0.6718 loss_db: 0.2245 2022/11/02 13:37:28 - mmengine - INFO - Epoch(train) [139][50/63] lr: 1.9377e-03 eta: 11:10:19 time: 0.5396 data_time: 0.0193 memory: 14901 loss: 2.2723 loss_prob: 1.3867 loss_thr: 0.6618 loss_db: 0.2238 2022/11/02 13:37:30 - mmengine - INFO - Epoch(train) [139][55/63] lr: 1.9377e-03 eta: 11:10:19 time: 0.5195 data_time: 0.0207 memory: 14901 loss: 2.1352 loss_prob: 1.2612 loss_thr: 0.6671 loss_db: 0.2068 2022/11/02 13:37:33 - mmengine - INFO - Epoch(train) [139][60/63] lr: 1.9377e-03 eta: 11:10:03 time: 0.4720 data_time: 0.0056 memory: 14901 loss: 2.1815 loss_prob: 1.3009 loss_thr: 0.6725 loss_db: 0.2081 2022/11/02 13:37:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:37:39 - mmengine - INFO - Epoch(train) [140][5/63] lr: 1.9360e-03 eta: 11:10:03 time: 0.7071 data_time: 0.1969 memory: 14901 loss: 2.2107 loss_prob: 1.3262 loss_thr: 0.6666 loss_db: 0.2179 2022/11/02 13:37:41 - mmengine - INFO - Epoch(train) [140][10/63] lr: 1.9360e-03 eta: 11:09:52 time: 0.7300 data_time: 0.2015 memory: 14901 loss: 2.1478 loss_prob: 1.2749 loss_thr: 0.6693 loss_db: 0.2035 2022/11/02 13:37:44 - mmengine - INFO - Epoch(train) [140][15/63] lr: 1.9360e-03 eta: 11:09:52 time: 0.4920 data_time: 0.0094 memory: 14901 loss: 2.1519 loss_prob: 1.2791 loss_thr: 0.6668 loss_db: 0.2060 2022/11/02 13:37:46 - mmengine - INFO - Epoch(train) [140][20/63] lr: 1.9360e-03 eta: 11:09:39 time: 0.5109 data_time: 0.0067 memory: 14901 loss: 2.2235 loss_prob: 1.3231 loss_thr: 0.6855 loss_db: 0.2149 2022/11/02 13:37:49 - mmengine - INFO - Epoch(train) [140][25/63] lr: 1.9360e-03 eta: 11:09:39 time: 0.5062 data_time: 0.0114 memory: 14901 loss: 2.0259 loss_prob: 1.1892 loss_thr: 0.6449 loss_db: 0.1918 2022/11/02 13:37:51 - mmengine - INFO - Epoch(train) [140][30/63] lr: 1.9360e-03 eta: 11:09:26 time: 0.5085 data_time: 0.0297 memory: 14901 loss: 1.9237 loss_prob: 1.1225 loss_thr: 0.6203 loss_db: 0.1808 2022/11/02 13:37:54 - mmengine - INFO - Epoch(train) [140][35/63] lr: 1.9360e-03 eta: 11:09:26 time: 0.5152 data_time: 0.0289 memory: 14901 loss: 2.2093 loss_prob: 1.3272 loss_thr: 0.6676 loss_db: 0.2145 2022/11/02 13:37:56 - mmengine - INFO - Epoch(train) [140][40/63] lr: 1.9360e-03 eta: 11:09:12 time: 0.5028 data_time: 0.0085 memory: 14901 loss: 2.1991 loss_prob: 1.3327 loss_thr: 0.6543 loss_db: 0.2121 2022/11/02 13:37:59 - mmengine - INFO - Epoch(train) [140][45/63] lr: 1.9360e-03 eta: 11:09:12 time: 0.4974 data_time: 0.0100 memory: 14901 loss: 2.0239 loss_prob: 1.1972 loss_thr: 0.6360 loss_db: 0.1908 2022/11/02 13:38:01 - mmengine - INFO - Epoch(train) [140][50/63] lr: 1.9360e-03 eta: 11:08:57 time: 0.4825 data_time: 0.0170 memory: 14901 loss: 2.3265 loss_prob: 1.4209 loss_thr: 0.6747 loss_db: 0.2308 2022/11/02 13:38:04 - mmengine - INFO - Epoch(train) [140][55/63] lr: 1.9360e-03 eta: 11:08:57 time: 0.4686 data_time: 0.0179 memory: 14901 loss: 2.3583 loss_prob: 1.4389 loss_thr: 0.6855 loss_db: 0.2339 2022/11/02 13:38:06 - mmengine - INFO - Epoch(train) [140][60/63] lr: 1.9360e-03 eta: 11:08:41 time: 0.4643 data_time: 0.0129 memory: 14901 loss: 2.1343 loss_prob: 1.2594 loss_thr: 0.6681 loss_db: 0.2068 2022/11/02 13:38:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:38:07 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/11/02 13:38:11 - mmengine - INFO - Epoch(val) [140][5/500] eta: 11:08:41 time: 0.0413 data_time: 0.0042 memory: 14901 2022/11/02 13:38:11 - mmengine - INFO - Epoch(val) [140][10/500] eta: 0:00:23 time: 0.0472 data_time: 0.0043 memory: 1008 2022/11/02 13:38:11 - mmengine - INFO - Epoch(val) [140][15/500] eta: 0:00:23 time: 0.0414 data_time: 0.0023 memory: 1008 2022/11/02 13:38:11 - mmengine - INFO - Epoch(val) [140][20/500] eta: 0:00:19 time: 0.0397 data_time: 0.0024 memory: 1008 2022/11/02 13:38:12 - mmengine - INFO - Epoch(val) [140][25/500] eta: 0:00:19 time: 0.0414 data_time: 0.0024 memory: 1008 2022/11/02 13:38:12 - mmengine - INFO - Epoch(val) [140][30/500] eta: 0:00:19 time: 0.0412 data_time: 0.0024 memory: 1008 2022/11/02 13:38:12 - mmengine - INFO - Epoch(val) [140][35/500] eta: 0:00:19 time: 0.0390 data_time: 0.0023 memory: 1008 2022/11/02 13:38:12 - mmengine - INFO - Epoch(val) [140][40/500] eta: 0:00:20 time: 0.0436 data_time: 0.0038 memory: 1008 2022/11/02 13:38:12 - mmengine - INFO - Epoch(val) [140][45/500] eta: 0:00:20 time: 0.0446 data_time: 0.0040 memory: 1008 2022/11/02 13:38:13 - mmengine - INFO - Epoch(val) [140][50/500] eta: 0:00:18 time: 0.0411 data_time: 0.0028 memory: 1008 2022/11/02 13:38:13 - mmengine - INFO - Epoch(val) [140][55/500] eta: 0:00:18 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 13:38:13 - mmengine - INFO - Epoch(val) [140][60/500] eta: 0:00:16 time: 0.0371 data_time: 0.0021 memory: 1008 2022/11/02 13:38:13 - mmengine - INFO - Epoch(val) [140][65/500] eta: 0:00:16 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/02 13:38:13 - mmengine - INFO - Epoch(val) [140][70/500] eta: 0:00:18 time: 0.0422 data_time: 0.0024 memory: 1008 2022/11/02 13:38:14 - mmengine - INFO - Epoch(val) [140][75/500] eta: 0:00:18 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 13:38:14 - mmengine - INFO - Epoch(val) [140][80/500] eta: 0:00:32 time: 0.0773 data_time: 0.0424 memory: 1008 2022/11/02 13:38:14 - mmengine - INFO - Epoch(val) [140][85/500] eta: 0:00:32 time: 0.0758 data_time: 0.0422 memory: 1008 2022/11/02 13:38:15 - mmengine - INFO - Epoch(val) [140][90/500] eta: 0:00:15 time: 0.0376 data_time: 0.0021 memory: 1008 2022/11/02 13:38:15 - mmengine - INFO - Epoch(val) [140][95/500] eta: 0:00:15 time: 0.0425 data_time: 0.0022 memory: 1008 2022/11/02 13:38:15 - mmengine - INFO - Epoch(val) [140][100/500] eta: 0:00:15 time: 0.0394 data_time: 0.0022 memory: 1008 2022/11/02 13:38:15 - mmengine - INFO - Epoch(val) [140][105/500] eta: 0:00:15 time: 0.0359 data_time: 0.0023 memory: 1008 2022/11/02 13:38:15 - mmengine - INFO - Epoch(val) [140][110/500] eta: 0:00:14 time: 0.0363 data_time: 0.0023 memory: 1008 2022/11/02 13:38:15 - mmengine - INFO - Epoch(val) [140][115/500] eta: 0:00:14 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/02 13:38:16 - mmengine - INFO - Epoch(val) [140][120/500] eta: 0:00:15 time: 0.0420 data_time: 0.0025 memory: 1008 2022/11/02 13:38:16 - mmengine - INFO - Epoch(val) [140][125/500] eta: 0:00:15 time: 0.0397 data_time: 0.0024 memory: 1008 2022/11/02 13:38:16 - mmengine - INFO - Epoch(val) [140][130/500] eta: 0:00:14 time: 0.0381 data_time: 0.0023 memory: 1008 2022/11/02 13:38:16 - mmengine - INFO - Epoch(val) [140][135/500] eta: 0:00:14 time: 0.0389 data_time: 0.0024 memory: 1008 2022/11/02 13:38:16 - mmengine - INFO - Epoch(val) [140][140/500] eta: 0:00:13 time: 0.0387 data_time: 0.0023 memory: 1008 2022/11/02 13:38:17 - mmengine - INFO - Epoch(val) [140][145/500] eta: 0:00:13 time: 0.0414 data_time: 0.0023 memory: 1008 2022/11/02 13:38:17 - mmengine - INFO - Epoch(val) [140][150/500] eta: 0:00:14 time: 0.0416 data_time: 0.0023 memory: 1008 2022/11/02 13:38:17 - mmengine - INFO - Epoch(val) [140][155/500] eta: 0:00:14 time: 0.0708 data_time: 0.0306 memory: 1008 2022/11/02 13:38:18 - mmengine - INFO - Epoch(val) [140][160/500] eta: 0:00:24 time: 0.0723 data_time: 0.0302 memory: 1008 2022/11/02 13:38:18 - mmengine - INFO - Epoch(val) [140][165/500] eta: 0:00:24 time: 0.0432 data_time: 0.0020 memory: 1008 2022/11/02 13:38:18 - mmengine - INFO - Epoch(val) [140][170/500] eta: 0:00:14 time: 0.0433 data_time: 0.0024 memory: 1008 2022/11/02 13:38:18 - mmengine - INFO - Epoch(val) [140][175/500] eta: 0:00:14 time: 0.0388 data_time: 0.0023 memory: 1008 2022/11/02 13:38:18 - mmengine - INFO - Epoch(val) [140][180/500] eta: 0:00:12 time: 0.0375 data_time: 0.0023 memory: 1008 2022/11/02 13:38:19 - mmengine - INFO - Epoch(val) [140][185/500] eta: 0:00:12 time: 0.0400 data_time: 0.0024 memory: 1008 2022/11/02 13:38:19 - mmengine - INFO - Epoch(val) [140][190/500] eta: 0:00:12 time: 0.0407 data_time: 0.0023 memory: 1008 2022/11/02 13:38:19 - mmengine - INFO - Epoch(val) [140][195/500] eta: 0:00:12 time: 0.0396 data_time: 0.0023 memory: 1008 2022/11/02 13:38:19 - mmengine - INFO - Epoch(val) [140][200/500] eta: 0:00:13 time: 0.0440 data_time: 0.0022 memory: 1008 2022/11/02 13:38:19 - mmengine - INFO - Epoch(val) [140][205/500] eta: 0:00:13 time: 0.0482 data_time: 0.0037 memory: 1008 2022/11/02 13:38:20 - mmengine - INFO - Epoch(val) [140][210/500] eta: 0:00:11 time: 0.0409 data_time: 0.0037 memory: 1008 2022/11/02 13:38:20 - mmengine - INFO - Epoch(val) [140][215/500] eta: 0:00:11 time: 0.0374 data_time: 0.0022 memory: 1008 2022/11/02 13:38:20 - mmengine - INFO - Epoch(val) [140][220/500] eta: 0:00:23 time: 0.0830 data_time: 0.0451 memory: 1008 2022/11/02 13:38:21 - mmengine - INFO - Epoch(val) [140][225/500] eta: 0:00:23 time: 0.0823 data_time: 0.0447 memory: 1008 2022/11/02 13:38:21 - mmengine - INFO - Epoch(val) [140][230/500] eta: 0:00:09 time: 0.0353 data_time: 0.0016 memory: 1008 2022/11/02 13:38:21 - mmengine - INFO - Epoch(val) [140][235/500] eta: 0:00:09 time: 0.0380 data_time: 0.0020 memory: 1008 2022/11/02 13:38:21 - mmengine - INFO - Epoch(val) [140][240/500] eta: 0:00:10 time: 0.0418 data_time: 0.0023 memory: 1008 2022/11/02 13:38:21 - mmengine - INFO - Epoch(val) [140][245/500] eta: 0:00:10 time: 0.0382 data_time: 0.0024 memory: 1008 2022/11/02 13:38:22 - mmengine - INFO - Epoch(val) [140][250/500] eta: 0:00:10 time: 0.0411 data_time: 0.0032 memory: 1008 2022/11/02 13:38:22 - mmengine - INFO - Epoch(val) [140][255/500] eta: 0:00:10 time: 0.0407 data_time: 0.0031 memory: 1008 2022/11/02 13:38:22 - mmengine - INFO - Epoch(val) [140][260/500] eta: 0:00:08 time: 0.0372 data_time: 0.0024 memory: 1008 2022/11/02 13:38:22 - mmengine - INFO - Epoch(val) [140][265/500] eta: 0:00:08 time: 0.0376 data_time: 0.0025 memory: 1008 2022/11/02 13:38:22 - mmengine - INFO - Epoch(val) [140][270/500] eta: 0:00:08 time: 0.0379 data_time: 0.0024 memory: 1008 2022/11/02 13:38:23 - mmengine - INFO - Epoch(val) [140][275/500] eta: 0:00:08 time: 0.0400 data_time: 0.0032 memory: 1008 2022/11/02 13:38:23 - mmengine - INFO - Epoch(val) [140][280/500] eta: 0:00:09 time: 0.0422 data_time: 0.0032 memory: 1008 2022/11/02 13:38:23 - mmengine - INFO - Epoch(val) [140][285/500] eta: 0:00:09 time: 0.0400 data_time: 0.0024 memory: 1008 2022/11/02 13:38:23 - mmengine - INFO - Epoch(val) [140][290/500] eta: 0:00:08 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 13:38:23 - mmengine - INFO - Epoch(val) [140][295/500] eta: 0:00:08 time: 0.0413 data_time: 0.0026 memory: 1008 2022/11/02 13:38:24 - mmengine - INFO - Epoch(val) [140][300/500] eta: 0:00:07 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/02 13:38:24 - mmengine - INFO - Epoch(val) [140][305/500] eta: 0:00:07 time: 0.0375 data_time: 0.0024 memory: 1008 2022/11/02 13:38:24 - mmengine - INFO - Epoch(val) [140][310/500] eta: 0:00:07 time: 0.0370 data_time: 0.0023 memory: 1008 2022/11/02 13:38:24 - mmengine - INFO - Epoch(val) [140][315/500] eta: 0:00:07 time: 0.0411 data_time: 0.0023 memory: 1008 2022/11/02 13:38:24 - mmengine - INFO - Epoch(val) [140][320/500] eta: 0:00:07 time: 0.0411 data_time: 0.0024 memory: 1008 2022/11/02 13:38:25 - mmengine - INFO - Epoch(val) [140][325/500] eta: 0:00:07 time: 0.0531 data_time: 0.0026 memory: 1008 2022/11/02 13:38:25 - mmengine - INFO - Epoch(val) [140][330/500] eta: 0:00:09 time: 0.0541 data_time: 0.0028 memory: 1008 2022/11/02 13:38:25 - mmengine - INFO - Epoch(val) [140][335/500] eta: 0:00:09 time: 0.0419 data_time: 0.0031 memory: 1008 2022/11/02 13:38:26 - mmengine - INFO - Epoch(val) [140][340/500] eta: 0:00:08 time: 0.0539 data_time: 0.0031 memory: 1008 2022/11/02 13:38:26 - mmengine - INFO - Epoch(val) [140][345/500] eta: 0:00:08 time: 0.0517 data_time: 0.0028 memory: 1008 2022/11/02 13:38:26 - mmengine - INFO - Epoch(val) [140][350/500] eta: 0:00:07 time: 0.0478 data_time: 0.0029 memory: 1008 2022/11/02 13:38:26 - mmengine - INFO - Epoch(val) [140][355/500] eta: 0:00:07 time: 0.0484 data_time: 0.0031 memory: 1008 2022/11/02 13:38:26 - mmengine - INFO - Epoch(val) [140][360/500] eta: 0:00:06 time: 0.0436 data_time: 0.0031 memory: 1008 2022/11/02 13:38:27 - mmengine - INFO - Epoch(val) [140][365/500] eta: 0:00:06 time: 0.0448 data_time: 0.0031 memory: 1008 2022/11/02 13:38:27 - mmengine - INFO - Epoch(val) [140][370/500] eta: 0:00:05 time: 0.0397 data_time: 0.0029 memory: 1008 2022/11/02 13:38:27 - mmengine - INFO - Epoch(val) [140][375/500] eta: 0:00:05 time: 0.0368 data_time: 0.0029 memory: 1008 2022/11/02 13:38:27 - mmengine - INFO - Epoch(val) [140][380/500] eta: 0:00:05 time: 0.0455 data_time: 0.0031 memory: 1008 2022/11/02 13:38:27 - mmengine - INFO - Epoch(val) [140][385/500] eta: 0:00:05 time: 0.0471 data_time: 0.0030 memory: 1008 2022/11/02 13:38:28 - mmengine - INFO - Epoch(val) [140][390/500] eta: 0:00:04 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/02 13:38:28 - mmengine - INFO - Epoch(val) [140][395/500] eta: 0:00:04 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 13:38:28 - mmengine - INFO - Epoch(val) [140][400/500] eta: 0:00:04 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 13:38:28 - mmengine - INFO - Epoch(val) [140][405/500] eta: 0:00:04 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/02 13:38:29 - mmengine - INFO - Epoch(val) [140][410/500] eta: 0:00:03 time: 0.0420 data_time: 0.0023 memory: 1008 2022/11/02 13:38:29 - mmengine - INFO - Epoch(val) [140][415/500] eta: 0:00:03 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/02 13:38:29 - mmengine - INFO - Epoch(val) [140][420/500] eta: 0:00:02 time: 0.0348 data_time: 0.0023 memory: 1008 2022/11/02 13:38:29 - mmengine - INFO - Epoch(val) [140][425/500] eta: 0:00:02 time: 0.0381 data_time: 0.0024 memory: 1008 2022/11/02 13:38:29 - mmengine - INFO - Epoch(val) [140][430/500] eta: 0:00:02 time: 0.0389 data_time: 0.0023 memory: 1008 2022/11/02 13:38:29 - mmengine - INFO - Epoch(val) [140][435/500] eta: 0:00:02 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 13:38:30 - mmengine - INFO - Epoch(val) [140][440/500] eta: 0:00:02 time: 0.0391 data_time: 0.0024 memory: 1008 2022/11/02 13:38:30 - mmengine - INFO - Epoch(val) [140][445/500] eta: 0:00:02 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/02 13:38:30 - mmengine - INFO - Epoch(val) [140][450/500] eta: 0:00:02 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 13:38:30 - mmengine - INFO - Epoch(val) [140][455/500] eta: 0:00:02 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 13:38:30 - mmengine - INFO - Epoch(val) [140][460/500] eta: 0:00:01 time: 0.0366 data_time: 0.0027 memory: 1008 2022/11/02 13:38:31 - mmengine - INFO - Epoch(val) [140][465/500] eta: 0:00:01 time: 0.0369 data_time: 0.0029 memory: 1008 2022/11/02 13:38:31 - mmengine - INFO - Epoch(val) [140][470/500] eta: 0:00:01 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 13:38:31 - mmengine - INFO - Epoch(val) [140][475/500] eta: 0:00:01 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 13:38:31 - mmengine - INFO - Epoch(val) [140][480/500] eta: 0:00:00 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/02 13:38:31 - mmengine - INFO - Epoch(val) [140][485/500] eta: 0:00:00 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 13:38:32 - mmengine - INFO - Epoch(val) [140][490/500] eta: 0:00:00 time: 0.0408 data_time: 0.0024 memory: 1008 2022/11/02 13:38:32 - mmengine - INFO - Epoch(val) [140][495/500] eta: 0:00:00 time: 0.0450 data_time: 0.0026 memory: 1008 2022/11/02 13:38:32 - mmengine - INFO - Epoch(val) [140][500/500] eta: 0:00:00 time: 0.0400 data_time: 0.0025 memory: 1008 2022/11/02 13:38:32 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7896, precision: 0.6600, hmean: 0.7190 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7896, precision: 0.7441, hmean: 0.7662 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7843, precision: 0.7985, hmean: 0.7914 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7617, precision: 0.8428, hmean: 0.8002 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6740, precision: 0.8946, hmean: 0.7688 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2374, precision: 0.9667, hmean: 0.3811 2022/11/02 13:38:32 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/02 13:38:32 - mmengine - INFO - Epoch(val) [140][500/500] icdar/precision: 0.8428 icdar/recall: 0.7617 icdar/hmean: 0.8002 2022/11/02 13:38:38 - mmengine - INFO - Epoch(train) [141][5/63] lr: 1.9344e-03 eta: 0:00:00 time: 0.7598 data_time: 0.2255 memory: 14901 loss: 2.2836 loss_prob: 1.3721 loss_thr: 0.6866 loss_db: 0.2249 2022/11/02 13:38:40 - mmengine - INFO - Epoch(train) [141][10/63] lr: 1.9344e-03 eta: 11:08:33 time: 0.7853 data_time: 0.2236 memory: 14901 loss: 2.2399 loss_prob: 1.3411 loss_thr: 0.6786 loss_db: 0.2202 2022/11/02 13:38:42 - mmengine - INFO - Epoch(train) [141][15/63] lr: 1.9344e-03 eta: 11:08:33 time: 0.4790 data_time: 0.0044 memory: 14901 loss: 2.1202 loss_prob: 1.2573 loss_thr: 0.6528 loss_db: 0.2101 2022/11/02 13:38:45 - mmengine - INFO - Epoch(train) [141][20/63] lr: 1.9344e-03 eta: 11:08:18 time: 0.4727 data_time: 0.0048 memory: 14901 loss: 2.1425 loss_prob: 1.2694 loss_thr: 0.6638 loss_db: 0.2093 2022/11/02 13:38:47 - mmengine - INFO - Epoch(train) [141][25/63] lr: 1.9344e-03 eta: 11:08:18 time: 0.5023 data_time: 0.0365 memory: 14901 loss: 2.0957 loss_prob: 1.2439 loss_thr: 0.6508 loss_db: 0.2010 2022/11/02 13:38:50 - mmengine - INFO - Epoch(train) [141][30/63] lr: 1.9344e-03 eta: 11:08:06 time: 0.5241 data_time: 0.0360 memory: 14901 loss: 2.1403 loss_prob: 1.3013 loss_thr: 0.6259 loss_db: 0.2131 2022/11/02 13:38:52 - mmengine - INFO - Epoch(train) [141][35/63] lr: 1.9344e-03 eta: 11:08:06 time: 0.4797 data_time: 0.0040 memory: 14901 loss: 2.2026 loss_prob: 1.3342 loss_thr: 0.6491 loss_db: 0.2194 2022/11/02 13:38:54 - mmengine - INFO - Epoch(train) [141][40/63] lr: 1.9344e-03 eta: 11:07:49 time: 0.4505 data_time: 0.0041 memory: 14901 loss: 2.2130 loss_prob: 1.3297 loss_thr: 0.6670 loss_db: 0.2164 2022/11/02 13:38:57 - mmengine - INFO - Epoch(train) [141][45/63] lr: 1.9344e-03 eta: 11:07:49 time: 0.4689 data_time: 0.0041 memory: 14901 loss: 2.1937 loss_prob: 1.3346 loss_thr: 0.6402 loss_db: 0.2189 2022/11/02 13:38:59 - mmengine - INFO - Epoch(train) [141][50/63] lr: 1.9344e-03 eta: 11:07:35 time: 0.4959 data_time: 0.0199 memory: 14901 loss: 2.0912 loss_prob: 1.2614 loss_thr: 0.6241 loss_db: 0.2057 2022/11/02 13:39:02 - mmengine - INFO - Epoch(train) [141][55/63] lr: 1.9344e-03 eta: 11:07:35 time: 0.5201 data_time: 0.0205 memory: 14901 loss: 2.1774 loss_prob: 1.3111 loss_thr: 0.6546 loss_db: 0.2117 2022/11/02 13:39:06 - mmengine - INFO - Epoch(train) [141][60/63] lr: 1.9344e-03 eta: 11:07:32 time: 0.6501 data_time: 0.0058 memory: 14901 loss: 2.1592 loss_prob: 1.2795 loss_thr: 0.6720 loss_db: 0.2077 2022/11/02 13:39:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:39:13 - mmengine - INFO - Epoch(train) [142][5/63] lr: 1.9327e-03 eta: 11:07:32 time: 0.8321 data_time: 0.2652 memory: 14901 loss: 2.1629 loss_prob: 1.2913 loss_thr: 0.6668 loss_db: 0.2047 2022/11/02 13:39:16 - mmengine - INFO - Epoch(train) [142][10/63] lr: 1.9327e-03 eta: 11:07:30 time: 0.8575 data_time: 0.2651 memory: 14901 loss: 2.2548 loss_prob: 1.3669 loss_thr: 0.6709 loss_db: 0.2170 2022/11/02 13:39:19 - mmengine - INFO - Epoch(train) [142][15/63] lr: 1.9327e-03 eta: 11:07:30 time: 0.5947 data_time: 0.0057 memory: 14901 loss: 2.0879 loss_prob: 1.2426 loss_thr: 0.6414 loss_db: 0.2039 2022/11/02 13:39:21 - mmengine - INFO - Epoch(train) [142][20/63] lr: 1.9327e-03 eta: 11:07:20 time: 0.5349 data_time: 0.0056 memory: 14901 loss: 2.1574 loss_prob: 1.2971 loss_thr: 0.6486 loss_db: 0.2117 2022/11/02 13:39:26 - mmengine - INFO - Epoch(train) [142][25/63] lr: 1.9327e-03 eta: 11:07:20 time: 0.6544 data_time: 0.0315 memory: 14901 loss: 2.1751 loss_prob: 1.3004 loss_thr: 0.6665 loss_db: 0.2082 2022/11/02 13:39:28 - mmengine - INFO - Epoch(train) [142][30/63] lr: 1.9327e-03 eta: 11:07:20 time: 0.6926 data_time: 0.0352 memory: 14901 loss: 2.1092 loss_prob: 1.2372 loss_thr: 0.6720 loss_db: 0.2000 2022/11/02 13:39:32 - mmengine - INFO - Epoch(train) [142][35/63] lr: 1.9327e-03 eta: 11:07:20 time: 0.6131 data_time: 0.0093 memory: 14901 loss: 2.0976 loss_prob: 1.2467 loss_thr: 0.6453 loss_db: 0.2056 2022/11/02 13:39:35 - mmengine - INFO - Epoch(train) [142][40/63] lr: 1.9327e-03 eta: 11:07:15 time: 0.6136 data_time: 0.0044 memory: 14901 loss: 2.2200 loss_prob: 1.3362 loss_thr: 0.6657 loss_db: 0.2181 2022/11/02 13:39:38 - mmengine - INFO - Epoch(train) [142][45/63] lr: 1.9327e-03 eta: 11:07:15 time: 0.6045 data_time: 0.0044 memory: 14901 loss: 2.2395 loss_prob: 1.3452 loss_thr: 0.6773 loss_db: 0.2170 2022/11/02 13:39:41 - mmengine - INFO - Epoch(train) [142][50/63] lr: 1.9327e-03 eta: 11:07:13 time: 0.6494 data_time: 0.0199 memory: 14901 loss: 2.2045 loss_prob: 1.3238 loss_thr: 0.6634 loss_db: 0.2174 2022/11/02 13:39:44 - mmengine - INFO - Epoch(train) [142][55/63] lr: 1.9327e-03 eta: 11:07:13 time: 0.6408 data_time: 0.0208 memory: 14901 loss: 2.3647 loss_prob: 1.4232 loss_thr: 0.6988 loss_db: 0.2427 2022/11/02 13:39:48 - mmengine - INFO - Epoch(train) [142][60/63] lr: 1.9327e-03 eta: 11:07:16 time: 0.7181 data_time: 0.0068 memory: 14901 loss: 2.3818 loss_prob: 1.4415 loss_thr: 0.6977 loss_db: 0.2426 2022/11/02 13:39:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:39:55 - mmengine - INFO - Epoch(train) [143][5/63] lr: 1.9311e-03 eta: 11:07:16 time: 0.9306 data_time: 0.2200 memory: 14901 loss: 2.0335 loss_prob: 1.1992 loss_thr: 0.6370 loss_db: 0.1973 2022/11/02 13:39:58 - mmengine - INFO - Epoch(train) [143][10/63] lr: 1.9311e-03 eta: 11:07:14 time: 0.8645 data_time: 0.2193 memory: 14901 loss: 2.1034 loss_prob: 1.2417 loss_thr: 0.6580 loss_db: 0.2036 2022/11/02 13:40:01 - mmengine - INFO - Epoch(train) [143][15/63] lr: 1.9311e-03 eta: 11:07:14 time: 0.5977 data_time: 0.0057 memory: 14901 loss: 2.2096 loss_prob: 1.3142 loss_thr: 0.6782 loss_db: 0.2171 2022/11/02 13:40:04 - mmengine - INFO - Epoch(train) [143][20/63] lr: 1.9311e-03 eta: 11:07:05 time: 0.5541 data_time: 0.0061 memory: 14901 loss: 2.1580 loss_prob: 1.2793 loss_thr: 0.6685 loss_db: 0.2101 2022/11/02 13:40:06 - mmengine - INFO - Epoch(train) [143][25/63] lr: 1.9311e-03 eta: 11:07:05 time: 0.5216 data_time: 0.0201 memory: 14901 loss: 1.9897 loss_prob: 1.1797 loss_thr: 0.6150 loss_db: 0.1949 2022/11/02 13:40:09 - mmengine - INFO - Epoch(train) [143][30/63] lr: 1.9311e-03 eta: 11:06:52 time: 0.5105 data_time: 0.0326 memory: 14901 loss: 2.0369 loss_prob: 1.2190 loss_thr: 0.6145 loss_db: 0.2033 2022/11/02 13:40:11 - mmengine - INFO - Epoch(train) [143][35/63] lr: 1.9311e-03 eta: 11:06:52 time: 0.4968 data_time: 0.0173 memory: 14901 loss: 2.1994 loss_prob: 1.3071 loss_thr: 0.6782 loss_db: 0.2140 2022/11/02 13:40:14 - mmengine - INFO - Epoch(train) [143][40/63] lr: 1.9311e-03 eta: 11:06:36 time: 0.4636 data_time: 0.0079 memory: 14901 loss: 2.3259 loss_prob: 1.3993 loss_thr: 0.6991 loss_db: 0.2275 2022/11/02 13:40:16 - mmengine - INFO - Epoch(train) [143][45/63] lr: 1.9311e-03 eta: 11:06:36 time: 0.4782 data_time: 0.0084 memory: 14901 loss: 2.3093 loss_prob: 1.4297 loss_thr: 0.6484 loss_db: 0.2312 2022/11/02 13:40:19 - mmengine - INFO - Epoch(train) [143][50/63] lr: 1.9311e-03 eta: 11:06:22 time: 0.4889 data_time: 0.0159 memory: 14901 loss: 2.2265 loss_prob: 1.3650 loss_thr: 0.6426 loss_db: 0.2189 2022/11/02 13:40:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:40:21 - mmengine - INFO - Epoch(train) [143][55/63] lr: 1.9311e-03 eta: 11:06:22 time: 0.4846 data_time: 0.0230 memory: 14901 loss: 2.6483 loss_prob: 1.6677 loss_thr: 0.7199 loss_db: 0.2607 2022/11/02 13:40:24 - mmengine - INFO - Epoch(train) [143][60/63] lr: 1.9311e-03 eta: 11:06:11 time: 0.5320 data_time: 0.0117 memory: 14901 loss: 2.7513 loss_prob: 1.7294 loss_thr: 0.7503 loss_db: 0.2716 2022/11/02 13:40:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:40:31 - mmengine - INFO - Epoch(train) [144][5/63] lr: 1.9294e-03 eta: 11:06:11 time: 0.8021 data_time: 0.2283 memory: 14901 loss: 2.7211 loss_prob: 1.6903 loss_thr: 0.7333 loss_db: 0.2975 2022/11/02 13:40:34 - mmengine - INFO - Epoch(train) [144][10/63] lr: 1.9294e-03 eta: 11:06:09 time: 0.8697 data_time: 0.2324 memory: 14901 loss: 2.6096 loss_prob: 1.6105 loss_thr: 0.7181 loss_db: 0.2810 2022/11/02 13:40:37 - mmengine - INFO - Epoch(train) [144][15/63] lr: 1.9294e-03 eta: 11:06:09 time: 0.5824 data_time: 0.0138 memory: 14901 loss: 2.5940 loss_prob: 1.6051 loss_thr: 0.7190 loss_db: 0.2698 2022/11/02 13:40:39 - mmengine - INFO - Epoch(train) [144][20/63] lr: 1.9294e-03 eta: 11:05:56 time: 0.4983 data_time: 0.0096 memory: 14901 loss: 2.4981 loss_prob: 1.5403 loss_thr: 0.6989 loss_db: 0.2589 2022/11/02 13:40:41 - mmengine - INFO - Epoch(train) [144][25/63] lr: 1.9294e-03 eta: 11:05:56 time: 0.4835 data_time: 0.0117 memory: 14901 loss: 2.3862 loss_prob: 1.4659 loss_thr: 0.6837 loss_db: 0.2366 2022/11/02 13:40:44 - mmengine - INFO - Epoch(train) [144][30/63] lr: 1.9294e-03 eta: 11:05:48 time: 0.5703 data_time: 0.0277 memory: 14901 loss: 2.3587 loss_prob: 1.4510 loss_thr: 0.6755 loss_db: 0.2322 2022/11/02 13:40:47 - mmengine - INFO - Epoch(train) [144][35/63] lr: 1.9294e-03 eta: 11:05:48 time: 0.5655 data_time: 0.0253 memory: 14901 loss: 2.1905 loss_prob: 1.3374 loss_thr: 0.6368 loss_db: 0.2163 2022/11/02 13:40:50 - mmengine - INFO - Epoch(train) [144][40/63] lr: 1.9294e-03 eta: 11:05:35 time: 0.5071 data_time: 0.0248 memory: 14901 loss: 2.1784 loss_prob: 1.3109 loss_thr: 0.6540 loss_db: 0.2136 2022/11/02 13:40:52 - mmengine - INFO - Epoch(train) [144][45/63] lr: 1.9294e-03 eta: 11:05:35 time: 0.4977 data_time: 0.0243 memory: 14901 loss: 2.1385 loss_prob: 1.2864 loss_thr: 0.6435 loss_db: 0.2086 2022/11/02 13:40:54 - mmengine - INFO - Epoch(train) [144][50/63] lr: 1.9294e-03 eta: 11:05:21 time: 0.4968 data_time: 0.0173 memory: 14901 loss: 2.0807 loss_prob: 1.2534 loss_thr: 0.6215 loss_db: 0.2057 2022/11/02 13:40:57 - mmengine - INFO - Epoch(train) [144][55/63] lr: 1.9294e-03 eta: 11:05:21 time: 0.4836 data_time: 0.0206 memory: 14901 loss: 2.1290 loss_prob: 1.2619 loss_thr: 0.6597 loss_db: 0.2074 2022/11/02 13:40:59 - mmengine - INFO - Epoch(train) [144][60/63] lr: 1.9294e-03 eta: 11:05:06 time: 0.4717 data_time: 0.0126 memory: 14901 loss: 2.1781 loss_prob: 1.2934 loss_thr: 0.6697 loss_db: 0.2151 2022/11/02 13:41:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:41:06 - mmengine - INFO - Epoch(train) [145][5/63] lr: 1.9278e-03 eta: 11:05:06 time: 0.7635 data_time: 0.2225 memory: 14901 loss: 2.2760 loss_prob: 1.3717 loss_thr: 0.6685 loss_db: 0.2358 2022/11/02 13:41:08 - mmengine - INFO - Epoch(train) [145][10/63] lr: 1.9278e-03 eta: 11:04:59 time: 0.7958 data_time: 0.2185 memory: 14901 loss: 2.2577 loss_prob: 1.3628 loss_thr: 0.6648 loss_db: 0.2301 2022/11/02 13:41:11 - mmengine - INFO - Epoch(train) [145][15/63] lr: 1.9278e-03 eta: 11:04:59 time: 0.4836 data_time: 0.0051 memory: 14901 loss: 2.3072 loss_prob: 1.3927 loss_thr: 0.6865 loss_db: 0.2280 2022/11/02 13:41:14 - mmengine - INFO - Epoch(train) [145][20/63] lr: 1.9278e-03 eta: 11:04:50 time: 0.5506 data_time: 0.0076 memory: 14901 loss: 2.1989 loss_prob: 1.3030 loss_thr: 0.6860 loss_db: 0.2099 2022/11/02 13:41:16 - mmengine - INFO - Epoch(train) [145][25/63] lr: 1.9278e-03 eta: 11:04:50 time: 0.5649 data_time: 0.0314 memory: 14901 loss: 2.1650 loss_prob: 1.2838 loss_thr: 0.6741 loss_db: 0.2071 2022/11/02 13:41:19 - mmengine - INFO - Epoch(train) [145][30/63] lr: 1.9278e-03 eta: 11:04:37 time: 0.5035 data_time: 0.0347 memory: 14901 loss: 2.1523 loss_prob: 1.2870 loss_thr: 0.6526 loss_db: 0.2127 2022/11/02 13:41:21 - mmengine - INFO - Epoch(train) [145][35/63] lr: 1.9278e-03 eta: 11:04:37 time: 0.4802 data_time: 0.0175 memory: 14901 loss: 2.0748 loss_prob: 1.2298 loss_thr: 0.6430 loss_db: 0.2020 2022/11/02 13:41:23 - mmengine - INFO - Epoch(train) [145][40/63] lr: 1.9278e-03 eta: 11:04:21 time: 0.4644 data_time: 0.0117 memory: 14901 loss: 2.2105 loss_prob: 1.3280 loss_thr: 0.6665 loss_db: 0.2160 2022/11/02 13:41:26 - mmengine - INFO - Epoch(train) [145][45/63] lr: 1.9278e-03 eta: 11:04:21 time: 0.4895 data_time: 0.0045 memory: 14901 loss: 2.2637 loss_prob: 1.3537 loss_thr: 0.6887 loss_db: 0.2212 2022/11/02 13:41:29 - mmengine - INFO - Epoch(train) [145][50/63] lr: 1.9278e-03 eta: 11:04:11 time: 0.5469 data_time: 0.0127 memory: 14901 loss: 2.2318 loss_prob: 1.3332 loss_thr: 0.6784 loss_db: 0.2202 2022/11/02 13:41:31 - mmengine - INFO - Epoch(train) [145][55/63] lr: 1.9278e-03 eta: 11:04:11 time: 0.5039 data_time: 0.0146 memory: 14901 loss: 2.2004 loss_prob: 1.3302 loss_thr: 0.6517 loss_db: 0.2184 2022/11/02 13:41:33 - mmengine - INFO - Epoch(train) [145][60/63] lr: 1.9278e-03 eta: 11:03:54 time: 0.4473 data_time: 0.0076 memory: 14901 loss: 2.0249 loss_prob: 1.1914 loss_thr: 0.6410 loss_db: 0.1925 2022/11/02 13:41:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:41:40 - mmengine - INFO - Epoch(train) [146][5/63] lr: 1.9261e-03 eta: 11:03:54 time: 0.7335 data_time: 0.2326 memory: 14901 loss: 2.2729 loss_prob: 1.3729 loss_thr: 0.6632 loss_db: 0.2368 2022/11/02 13:41:44 - mmengine - INFO - Epoch(train) [146][10/63] lr: 1.9261e-03 eta: 11:03:53 time: 0.8816 data_time: 0.2325 memory: 14901 loss: 2.1696 loss_prob: 1.3006 loss_thr: 0.6497 loss_db: 0.2193 2022/11/02 13:41:47 - mmengine - INFO - Epoch(train) [146][15/63] lr: 1.9261e-03 eta: 11:03:53 time: 0.6994 data_time: 0.0055 memory: 14901 loss: 2.1669 loss_prob: 1.2960 loss_thr: 0.6570 loss_db: 0.2139 2022/11/02 13:41:50 - mmengine - INFO - Epoch(train) [146][20/63] lr: 1.9261e-03 eta: 11:03:51 time: 0.6419 data_time: 0.0172 memory: 14901 loss: 2.2071 loss_prob: 1.3072 loss_thr: 0.6823 loss_db: 0.2176 2022/11/02 13:41:53 - mmengine - INFO - Epoch(train) [146][25/63] lr: 1.9261e-03 eta: 11:03:51 time: 0.6186 data_time: 0.0379 memory: 14901 loss: 2.2320 loss_prob: 1.3199 loss_thr: 0.6958 loss_db: 0.2163 2022/11/02 13:41:56 - mmengine - INFO - Epoch(train) [146][30/63] lr: 1.9261e-03 eta: 11:03:43 time: 0.5769 data_time: 0.0251 memory: 14901 loss: 2.0999 loss_prob: 1.2407 loss_thr: 0.6591 loss_db: 0.2001 2022/11/02 13:41:59 - mmengine - INFO - Epoch(train) [146][35/63] lr: 1.9261e-03 eta: 11:03:43 time: 0.5514 data_time: 0.0043 memory: 14901 loss: 2.0333 loss_prob: 1.1931 loss_thr: 0.6432 loss_db: 0.1971 2022/11/02 13:42:02 - mmengine - INFO - Epoch(train) [146][40/63] lr: 1.9261e-03 eta: 11:03:39 time: 0.6250 data_time: 0.0046 memory: 14901 loss: 2.0029 loss_prob: 1.1735 loss_thr: 0.6356 loss_db: 0.1938 2022/11/02 13:42:05 - mmengine - INFO - Epoch(train) [146][45/63] lr: 1.9261e-03 eta: 11:03:39 time: 0.6335 data_time: 0.0102 memory: 14901 loss: 2.0739 loss_prob: 1.2353 loss_thr: 0.6387 loss_db: 0.1999 2022/11/02 13:42:08 - mmengine - INFO - Epoch(train) [146][50/63] lr: 1.9261e-03 eta: 11:03:35 time: 0.6330 data_time: 0.0232 memory: 14901 loss: 2.1400 loss_prob: 1.2857 loss_thr: 0.6477 loss_db: 0.2067 2022/11/02 13:42:12 - mmengine - INFO - Epoch(train) [146][55/63] lr: 1.9261e-03 eta: 11:03:35 time: 0.6864 data_time: 0.0175 memory: 14901 loss: 2.1388 loss_prob: 1.2784 loss_thr: 0.6581 loss_db: 0.2022 2022/11/02 13:42:14 - mmengine - INFO - Epoch(train) [146][60/63] lr: 1.9261e-03 eta: 11:03:29 time: 0.5985 data_time: 0.0042 memory: 14901 loss: 2.2330 loss_prob: 1.3402 loss_thr: 0.6783 loss_db: 0.2145 2022/11/02 13:42:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:42:22 - mmengine - INFO - Epoch(train) [147][5/63] lr: 1.9245e-03 eta: 11:03:29 time: 0.8281 data_time: 0.2622 memory: 14901 loss: 2.0387 loss_prob: 1.2209 loss_thr: 0.6226 loss_db: 0.1952 2022/11/02 13:42:25 - mmengine - INFO - Epoch(train) [147][10/63] lr: 1.9245e-03 eta: 11:03:30 time: 0.8969 data_time: 0.2634 memory: 14901 loss: 2.0211 loss_prob: 1.1874 loss_thr: 0.6436 loss_db: 0.1901 2022/11/02 13:42:29 - mmengine - INFO - Epoch(train) [147][15/63] lr: 1.9245e-03 eta: 11:03:30 time: 0.6912 data_time: 0.0062 memory: 14901 loss: 1.9316 loss_prob: 1.1114 loss_thr: 0.6387 loss_db: 0.1815 2022/11/02 13:42:31 - mmengine - INFO - Epoch(train) [147][20/63] lr: 1.9245e-03 eta: 11:03:26 time: 0.6367 data_time: 0.0054 memory: 14901 loss: 2.0090 loss_prob: 1.1863 loss_thr: 0.6259 loss_db: 0.1967 2022/11/02 13:42:34 - mmengine - INFO - Epoch(train) [147][25/63] lr: 1.9245e-03 eta: 11:03:26 time: 0.5530 data_time: 0.0053 memory: 14901 loss: 2.1058 loss_prob: 1.2712 loss_thr: 0.6324 loss_db: 0.2022 2022/11/02 13:42:38 - mmengine - INFO - Epoch(train) [147][30/63] lr: 1.9245e-03 eta: 11:03:24 time: 0.6526 data_time: 0.0190 memory: 14901 loss: 2.2598 loss_prob: 1.3916 loss_thr: 0.6532 loss_db: 0.2149 2022/11/02 13:42:40 - mmengine - INFO - Epoch(train) [147][35/63] lr: 1.9245e-03 eta: 11:03:24 time: 0.6039 data_time: 0.0184 memory: 14901 loss: 2.3893 loss_prob: 1.4800 loss_thr: 0.6712 loss_db: 0.2381 2022/11/02 13:42:43 - mmengine - INFO - Epoch(train) [147][40/63] lr: 1.9245e-03 eta: 11:03:09 time: 0.4735 data_time: 0.0049 memory: 14901 loss: 2.3380 loss_prob: 1.4322 loss_thr: 0.6694 loss_db: 0.2364 2022/11/02 13:42:45 - mmengine - INFO - Epoch(train) [147][45/63] lr: 1.9245e-03 eta: 11:03:09 time: 0.4888 data_time: 0.0049 memory: 14901 loss: 2.2418 loss_prob: 1.3611 loss_thr: 0.6579 loss_db: 0.2227 2022/11/02 13:42:48 - mmengine - INFO - Epoch(train) [147][50/63] lr: 1.9245e-03 eta: 11:02:57 time: 0.5167 data_time: 0.0042 memory: 14901 loss: 2.1847 loss_prob: 1.3069 loss_thr: 0.6610 loss_db: 0.2168 2022/11/02 13:42:50 - mmengine - INFO - Epoch(train) [147][55/63] lr: 1.9245e-03 eta: 11:02:57 time: 0.5121 data_time: 0.0182 memory: 14901 loss: 2.1982 loss_prob: 1.3188 loss_thr: 0.6618 loss_db: 0.2175 2022/11/02 13:42:52 - mmengine - INFO - Epoch(train) [147][60/63] lr: 1.9245e-03 eta: 11:02:43 time: 0.4786 data_time: 0.0202 memory: 14901 loss: 2.0902 loss_prob: 1.2525 loss_thr: 0.6328 loss_db: 0.2050 2022/11/02 13:42:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:42:58 - mmengine - INFO - Epoch(train) [148][5/63] lr: 1.9229e-03 eta: 11:02:43 time: 0.6646 data_time: 0.1864 memory: 14901 loss: 1.9948 loss_prob: 1.1781 loss_thr: 0.6196 loss_db: 0.1970 2022/11/02 13:43:01 - mmengine - INFO - Epoch(train) [148][10/63] lr: 1.9229e-03 eta: 11:02:29 time: 0.6912 data_time: 0.1869 memory: 14901 loss: 2.0959 loss_prob: 1.2451 loss_thr: 0.6430 loss_db: 0.2079 2022/11/02 13:43:03 - mmengine - INFO - Epoch(train) [148][15/63] lr: 1.9229e-03 eta: 11:02:29 time: 0.4646 data_time: 0.0055 memory: 14901 loss: 2.1294 loss_prob: 1.2743 loss_thr: 0.6410 loss_db: 0.2140 2022/11/02 13:43:06 - mmengine - INFO - Epoch(train) [148][20/63] lr: 1.9229e-03 eta: 11:02:17 time: 0.5259 data_time: 0.0072 memory: 14901 loss: 2.0478 loss_prob: 1.2095 loss_thr: 0.6334 loss_db: 0.2049 2022/11/02 13:43:09 - mmengine - INFO - Epoch(train) [148][25/63] lr: 1.9229e-03 eta: 11:02:17 time: 0.5844 data_time: 0.0165 memory: 14901 loss: 2.1094 loss_prob: 1.2447 loss_thr: 0.6597 loss_db: 0.2050 2022/11/02 13:43:11 - mmengine - INFO - Epoch(train) [148][30/63] lr: 1.9229e-03 eta: 11:02:09 time: 0.5662 data_time: 0.0315 memory: 14901 loss: 2.0854 loss_prob: 1.2196 loss_thr: 0.6684 loss_db: 0.1974 2022/11/02 13:43:14 - mmengine - INFO - Epoch(train) [148][35/63] lr: 1.9229e-03 eta: 11:02:09 time: 0.5085 data_time: 0.0215 memory: 14901 loss: 1.9314 loss_prob: 1.1043 loss_thr: 0.6452 loss_db: 0.1819 2022/11/02 13:43:16 - mmengine - INFO - Epoch(train) [148][40/63] lr: 1.9229e-03 eta: 11:01:54 time: 0.4666 data_time: 0.0058 memory: 14901 loss: 1.9613 loss_prob: 1.1417 loss_thr: 0.6340 loss_db: 0.1856 2022/11/02 13:43:19 - mmengine - INFO - Epoch(train) [148][45/63] lr: 1.9229e-03 eta: 11:01:54 time: 0.4715 data_time: 0.0061 memory: 14901 loss: 2.0861 loss_prob: 1.2500 loss_thr: 0.6331 loss_db: 0.2030 2022/11/02 13:43:21 - mmengine - INFO - Epoch(train) [148][50/63] lr: 1.9229e-03 eta: 11:01:39 time: 0.4783 data_time: 0.0108 memory: 14901 loss: 2.1850 loss_prob: 1.2999 loss_thr: 0.6752 loss_db: 0.2100 2022/11/02 13:43:24 - mmengine - INFO - Epoch(train) [148][55/63] lr: 1.9229e-03 eta: 11:01:39 time: 0.5076 data_time: 0.0331 memory: 14901 loss: 2.2092 loss_prob: 1.2948 loss_thr: 0.7046 loss_db: 0.2098 2022/11/02 13:43:26 - mmengine - INFO - Epoch(train) [148][60/63] lr: 1.9229e-03 eta: 11:01:27 time: 0.5168 data_time: 0.0267 memory: 14901 loss: 2.2761 loss_prob: 1.3553 loss_thr: 0.6974 loss_db: 0.2235 2022/11/02 13:43:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:43:32 - mmengine - INFO - Epoch(train) [149][5/63] lr: 1.9212e-03 eta: 11:01:27 time: 0.6941 data_time: 0.2075 memory: 14901 loss: 2.1652 loss_prob: 1.3043 loss_thr: 0.6524 loss_db: 0.2085 2022/11/02 13:43:35 - mmengine - INFO - Epoch(train) [149][10/63] lr: 1.9212e-03 eta: 11:01:16 time: 0.7308 data_time: 0.2044 memory: 14901 loss: 2.1399 loss_prob: 1.2672 loss_thr: 0.6654 loss_db: 0.2073 2022/11/02 13:43:37 - mmengine - INFO - Epoch(train) [149][15/63] lr: 1.9212e-03 eta: 11:01:16 time: 0.4998 data_time: 0.0048 memory: 14901 loss: 2.1244 loss_prob: 1.2483 loss_thr: 0.6722 loss_db: 0.2039 2022/11/02 13:43:39 - mmengine - INFO - Epoch(train) [149][20/63] lr: 1.9212e-03 eta: 11:01:02 time: 0.4869 data_time: 0.0053 memory: 14901 loss: 2.1403 loss_prob: 1.2558 loss_thr: 0.6815 loss_db: 0.2029 2022/11/02 13:43:42 - mmengine - INFO - Epoch(train) [149][25/63] lr: 1.9212e-03 eta: 11:01:02 time: 0.5248 data_time: 0.0189 memory: 14901 loss: 2.1451 loss_prob: 1.2653 loss_thr: 0.6767 loss_db: 0.2031 2022/11/02 13:43:45 - mmengine - INFO - Epoch(train) [149][30/63] lr: 1.9212e-03 eta: 11:00:52 time: 0.5346 data_time: 0.0375 memory: 14901 loss: 2.1713 loss_prob: 1.2933 loss_thr: 0.6660 loss_db: 0.2120 2022/11/02 13:43:47 - mmengine - INFO - Epoch(train) [149][35/63] lr: 1.9212e-03 eta: 11:00:52 time: 0.5119 data_time: 0.0234 memory: 14901 loss: 2.1362 loss_prob: 1.2750 loss_thr: 0.6521 loss_db: 0.2091 2022/11/02 13:43:50 - mmengine - INFO - Epoch(train) [149][40/63] lr: 1.9212e-03 eta: 11:00:40 time: 0.5257 data_time: 0.0044 memory: 14901 loss: 2.0412 loss_prob: 1.2121 loss_thr: 0.6302 loss_db: 0.1989 2022/11/02 13:43:52 - mmengine - INFO - Epoch(train) [149][45/63] lr: 1.9212e-03 eta: 11:00:40 time: 0.4981 data_time: 0.0042 memory: 14901 loss: 2.0792 loss_prob: 1.2386 loss_thr: 0.6279 loss_db: 0.2126 2022/11/02 13:43:55 - mmengine - INFO - Epoch(train) [149][50/63] lr: 1.9212e-03 eta: 11:00:27 time: 0.4971 data_time: 0.0161 memory: 14901 loss: 2.1876 loss_prob: 1.3113 loss_thr: 0.6540 loss_db: 0.2223 2022/11/02 13:43:57 - mmengine - INFO - Epoch(train) [149][55/63] lr: 1.9212e-03 eta: 11:00:27 time: 0.4926 data_time: 0.0216 memory: 14901 loss: 2.2010 loss_prob: 1.3184 loss_thr: 0.6639 loss_db: 0.2187 2022/11/02 13:44:00 - mmengine - INFO - Epoch(train) [149][60/63] lr: 1.9212e-03 eta: 11:00:12 time: 0.4732 data_time: 0.0099 memory: 14901 loss: 2.2333 loss_prob: 1.3394 loss_thr: 0.6703 loss_db: 0.2236 2022/11/02 13:44:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:44:05 - mmengine - INFO - Epoch(train) [150][5/63] lr: 1.9196e-03 eta: 11:00:12 time: 0.6512 data_time: 0.2010 memory: 14901 loss: 2.1187 loss_prob: 1.2771 loss_thr: 0.6313 loss_db: 0.2104 2022/11/02 13:44:08 - mmengine - INFO - Epoch(train) [150][10/63] lr: 1.9196e-03 eta: 11:00:00 time: 0.7070 data_time: 0.2026 memory: 14901 loss: 2.2827 loss_prob: 1.3981 loss_thr: 0.6619 loss_db: 0.2227 2022/11/02 13:44:11 - mmengine - INFO - Epoch(train) [150][15/63] lr: 1.9196e-03 eta: 11:00:00 time: 0.5437 data_time: 0.0063 memory: 14901 loss: 2.4804 loss_prob: 1.5561 loss_thr: 0.6738 loss_db: 0.2504 2022/11/02 13:44:13 - mmengine - INFO - Epoch(train) [150][20/63] lr: 1.9196e-03 eta: 10:59:48 time: 0.5179 data_time: 0.0071 memory: 14901 loss: 2.4007 loss_prob: 1.5001 loss_thr: 0.6621 loss_db: 0.2386 2022/11/02 13:44:16 - mmengine - INFO - Epoch(train) [150][25/63] lr: 1.9196e-03 eta: 10:59:48 time: 0.5012 data_time: 0.0335 memory: 14901 loss: 2.2654 loss_prob: 1.3841 loss_thr: 0.6625 loss_db: 0.2188 2022/11/02 13:44:18 - mmengine - INFO - Epoch(train) [150][30/63] lr: 1.9196e-03 eta: 10:59:36 time: 0.5162 data_time: 0.0312 memory: 14901 loss: 2.0922 loss_prob: 1.2411 loss_thr: 0.6529 loss_db: 0.1982 2022/11/02 13:44:21 - mmengine - INFO - Epoch(train) [150][35/63] lr: 1.9196e-03 eta: 10:59:36 time: 0.5110 data_time: 0.0062 memory: 14901 loss: 2.3470 loss_prob: 1.4068 loss_thr: 0.7072 loss_db: 0.2330 2022/11/02 13:44:23 - mmengine - INFO - Epoch(train) [150][40/63] lr: 1.9196e-03 eta: 10:59:24 time: 0.5091 data_time: 0.0064 memory: 14901 loss: 2.4049 loss_prob: 1.4507 loss_thr: 0.7118 loss_db: 0.2425 2022/11/02 13:44:26 - mmengine - INFO - Epoch(train) [150][45/63] lr: 1.9196e-03 eta: 10:59:24 time: 0.5136 data_time: 0.0059 memory: 14901 loss: 2.1166 loss_prob: 1.2561 loss_thr: 0.6505 loss_db: 0.2100 2022/11/02 13:44:29 - mmengine - INFO - Epoch(train) [150][50/63] lr: 1.9196e-03 eta: 10:59:14 time: 0.5346 data_time: 0.0279 memory: 14901 loss: 2.2269 loss_prob: 1.3343 loss_thr: 0.6683 loss_db: 0.2244 2022/11/02 13:44:31 - mmengine - INFO - Epoch(train) [150][55/63] lr: 1.9196e-03 eta: 10:59:14 time: 0.5330 data_time: 0.0266 memory: 14901 loss: 2.2772 loss_prob: 1.3754 loss_thr: 0.6738 loss_db: 0.2280 2022/11/02 13:44:34 - mmengine - INFO - Epoch(train) [150][60/63] lr: 1.9196e-03 eta: 10:59:02 time: 0.5204 data_time: 0.0045 memory: 14901 loss: 2.1579 loss_prob: 1.3029 loss_thr: 0.6429 loss_db: 0.2121 2022/11/02 13:44:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:44:41 - mmengine - INFO - Epoch(train) [151][5/63] lr: 1.9179e-03 eta: 10:59:02 time: 0.7675 data_time: 0.2545 memory: 14901 loss: 2.3056 loss_prob: 1.4067 loss_thr: 0.6702 loss_db: 0.2286 2022/11/02 13:44:43 - mmengine - INFO - Epoch(train) [151][10/63] lr: 1.9179e-03 eta: 10:58:58 time: 0.8228 data_time: 0.2552 memory: 14901 loss: 2.2110 loss_prob: 1.3329 loss_thr: 0.6606 loss_db: 0.2175 2022/11/02 13:44:48 - mmengine - INFO - Epoch(train) [151][15/63] lr: 1.9179e-03 eta: 10:58:58 time: 0.7126 data_time: 0.0071 memory: 14901 loss: 2.0958 loss_prob: 1.2396 loss_thr: 0.6521 loss_db: 0.2040 2022/11/02 13:44:51 - mmengine - INFO - Epoch(train) [151][20/63] lr: 1.9179e-03 eta: 10:59:02 time: 0.7400 data_time: 0.0065 memory: 14901 loss: 2.0228 loss_prob: 1.1672 loss_thr: 0.6651 loss_db: 0.1906 2022/11/02 13:44:54 - mmengine - INFO - Epoch(train) [151][25/63] lr: 1.9179e-03 eta: 10:59:02 time: 0.5977 data_time: 0.0366 memory: 14901 loss: 1.9623 loss_prob: 1.1377 loss_thr: 0.6416 loss_db: 0.1830 2022/11/02 13:44:57 - mmengine - INFO - Epoch(train) [151][30/63] lr: 1.9179e-03 eta: 10:58:54 time: 0.5694 data_time: 0.0383 memory: 14901 loss: 1.9628 loss_prob: 1.1444 loss_thr: 0.6298 loss_db: 0.1885 2022/11/02 13:45:00 - mmengine - INFO - Epoch(train) [151][35/63] lr: 1.9179e-03 eta: 10:58:54 time: 0.6250 data_time: 0.0063 memory: 14901 loss: 2.0322 loss_prob: 1.1978 loss_thr: 0.6343 loss_db: 0.2001 2022/11/02 13:45:03 - mmengine - INFO - Epoch(train) [151][40/63] lr: 1.9179e-03 eta: 10:58:49 time: 0.6122 data_time: 0.0044 memory: 14901 loss: 1.9779 loss_prob: 1.1594 loss_thr: 0.6263 loss_db: 0.1922 2022/11/02 13:45:06 - mmengine - INFO - Epoch(train) [151][45/63] lr: 1.9179e-03 eta: 10:58:49 time: 0.5973 data_time: 0.0045 memory: 14901 loss: 1.9935 loss_prob: 1.1517 loss_thr: 0.6495 loss_db: 0.1924 2022/11/02 13:45:09 - mmengine - INFO - Epoch(train) [151][50/63] lr: 1.9179e-03 eta: 10:58:44 time: 0.6236 data_time: 0.0241 memory: 14901 loss: 2.1670 loss_prob: 1.2887 loss_thr: 0.6620 loss_db: 0.2163 2022/11/02 13:45:11 - mmengine - INFO - Epoch(train) [151][55/63] lr: 1.9179e-03 eta: 10:58:44 time: 0.5597 data_time: 0.0251 memory: 14901 loss: 2.2978 loss_prob: 1.4023 loss_thr: 0.6659 loss_db: 0.2296 2022/11/02 13:45:14 - mmengine - INFO - Epoch(train) [151][60/63] lr: 1.9179e-03 eta: 10:58:31 time: 0.4844 data_time: 0.0051 memory: 14901 loss: 2.1841 loss_prob: 1.3103 loss_thr: 0.6646 loss_db: 0.2092 2022/11/02 13:45:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:45:20 - mmengine - INFO - Epoch(train) [152][5/63] lr: 1.9163e-03 eta: 10:58:31 time: 0.7513 data_time: 0.2338 memory: 14901 loss: 2.3397 loss_prob: 1.4410 loss_thr: 0.6637 loss_db: 0.2350 2022/11/02 13:45:23 - mmengine - INFO - Epoch(train) [152][10/63] lr: 1.9163e-03 eta: 10:58:23 time: 0.7862 data_time: 0.2385 memory: 14901 loss: 2.2872 loss_prob: 1.3845 loss_thr: 0.6744 loss_db: 0.2283 2022/11/02 13:45:26 - mmengine - INFO - Epoch(train) [152][15/63] lr: 1.9163e-03 eta: 10:58:23 time: 0.5627 data_time: 0.0100 memory: 14901 loss: 2.2156 loss_prob: 1.3235 loss_thr: 0.6789 loss_db: 0.2132 2022/11/02 13:45:29 - mmengine - INFO - Epoch(train) [152][20/63] lr: 1.9163e-03 eta: 10:58:16 time: 0.5710 data_time: 0.0094 memory: 14901 loss: 2.2661 loss_prob: 1.3545 loss_thr: 0.6888 loss_db: 0.2228 2022/11/02 13:45:31 - mmengine - INFO - Epoch(train) [152][25/63] lr: 1.9163e-03 eta: 10:58:16 time: 0.5130 data_time: 0.0295 memory: 14901 loss: 2.3718 loss_prob: 1.4465 loss_thr: 0.6830 loss_db: 0.2423 2022/11/02 13:45:34 - mmengine - INFO - Epoch(train) [152][30/63] lr: 1.9163e-03 eta: 10:58:03 time: 0.5020 data_time: 0.0343 memory: 14901 loss: 2.3213 loss_prob: 1.4227 loss_thr: 0.6667 loss_db: 0.2320 2022/11/02 13:45:36 - mmengine - INFO - Epoch(train) [152][35/63] lr: 1.9163e-03 eta: 10:58:03 time: 0.4928 data_time: 0.0143 memory: 14901 loss: 2.2723 loss_prob: 1.3833 loss_thr: 0.6693 loss_db: 0.2197 2022/11/02 13:45:39 - mmengine - INFO - Epoch(train) [152][40/63] lr: 1.9163e-03 eta: 10:57:50 time: 0.4948 data_time: 0.0055 memory: 14901 loss: 2.1642 loss_prob: 1.3011 loss_thr: 0.6540 loss_db: 0.2091 2022/11/02 13:45:41 - mmengine - INFO - Epoch(train) [152][45/63] lr: 1.9163e-03 eta: 10:57:50 time: 0.4978 data_time: 0.0045 memory: 14901 loss: 2.1066 loss_prob: 1.2527 loss_thr: 0.6523 loss_db: 0.2015 2022/11/02 13:45:44 - mmengine - INFO - Epoch(train) [152][50/63] lr: 1.9163e-03 eta: 10:57:37 time: 0.5009 data_time: 0.0175 memory: 14901 loss: 1.9882 loss_prob: 1.1698 loss_thr: 0.6320 loss_db: 0.1864 2022/11/02 13:45:46 - mmengine - INFO - Epoch(train) [152][55/63] lr: 1.9163e-03 eta: 10:57:37 time: 0.4924 data_time: 0.0222 memory: 14901 loss: 1.9574 loss_prob: 1.1274 loss_thr: 0.6418 loss_db: 0.1882 2022/11/02 13:45:48 - mmengine - INFO - Epoch(train) [152][60/63] lr: 1.9163e-03 eta: 10:57:24 time: 0.4961 data_time: 0.0106 memory: 14901 loss: 1.9795 loss_prob: 1.1346 loss_thr: 0.6529 loss_db: 0.1920 2022/11/02 13:45:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:45:55 - mmengine - INFO - Epoch(train) [153][5/63] lr: 1.9146e-03 eta: 10:57:24 time: 0.7117 data_time: 0.1874 memory: 14901 loss: 2.2464 loss_prob: 1.3694 loss_thr: 0.6487 loss_db: 0.2282 2022/11/02 13:45:57 - mmengine - INFO - Epoch(train) [153][10/63] lr: 1.9146e-03 eta: 10:57:11 time: 0.6970 data_time: 0.1926 memory: 14901 loss: 2.3536 loss_prob: 1.4426 loss_thr: 0.6658 loss_db: 0.2453 2022/11/02 13:45:59 - mmengine - INFO - Epoch(train) [153][15/63] lr: 1.9146e-03 eta: 10:57:11 time: 0.4667 data_time: 0.0129 memory: 14901 loss: 2.5258 loss_prob: 1.5622 loss_thr: 0.7044 loss_db: 0.2592 2022/11/02 13:46:02 - mmengine - INFO - Epoch(train) [153][20/63] lr: 1.9146e-03 eta: 10:57:00 time: 0.5289 data_time: 0.0083 memory: 14901 loss: 2.2549 loss_prob: 1.3557 loss_thr: 0.6784 loss_db: 0.2209 2022/11/02 13:46:05 - mmengine - INFO - Epoch(train) [153][25/63] lr: 1.9146e-03 eta: 10:57:00 time: 0.5467 data_time: 0.0249 memory: 14901 loss: 2.1324 loss_prob: 1.2672 loss_thr: 0.6594 loss_db: 0.2058 2022/11/02 13:46:08 - mmengine - INFO - Epoch(train) [153][30/63] lr: 1.9146e-03 eta: 10:56:51 time: 0.5451 data_time: 0.0297 memory: 14901 loss: 2.2577 loss_prob: 1.3736 loss_thr: 0.6625 loss_db: 0.2216 2022/11/02 13:46:10 - mmengine - INFO - Epoch(train) [153][35/63] lr: 1.9146e-03 eta: 10:56:51 time: 0.5408 data_time: 0.0159 memory: 14901 loss: 2.2869 loss_prob: 1.3987 loss_thr: 0.6629 loss_db: 0.2253 2022/11/02 13:46:12 - mmengine - INFO - Epoch(train) [153][40/63] lr: 1.9146e-03 eta: 10:56:36 time: 0.4748 data_time: 0.0123 memory: 14901 loss: 2.3292 loss_prob: 1.4110 loss_thr: 0.6910 loss_db: 0.2272 2022/11/02 13:46:15 - mmengine - INFO - Epoch(train) [153][45/63] lr: 1.9146e-03 eta: 10:56:36 time: 0.4610 data_time: 0.0063 memory: 14901 loss: 2.1374 loss_prob: 1.2619 loss_thr: 0.6694 loss_db: 0.2060 2022/11/02 13:46:17 - mmengine - INFO - Epoch(train) [153][50/63] lr: 1.9146e-03 eta: 10:56:24 time: 0.5064 data_time: 0.0127 memory: 14901 loss: 2.0012 loss_prob: 1.1688 loss_thr: 0.6373 loss_db: 0.1951 2022/11/02 13:46:20 - mmengine - INFO - Epoch(train) [153][55/63] lr: 1.9146e-03 eta: 10:56:24 time: 0.5327 data_time: 0.0288 memory: 14901 loss: 2.0059 loss_prob: 1.1798 loss_thr: 0.6306 loss_db: 0.1955 2022/11/02 13:46:22 - mmengine - INFO - Epoch(train) [153][60/63] lr: 1.9146e-03 eta: 10:56:12 time: 0.5071 data_time: 0.0217 memory: 14901 loss: 2.0839 loss_prob: 1.2384 loss_thr: 0.6442 loss_db: 0.2013 2022/11/02 13:46:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:46:29 - mmengine - INFO - Epoch(train) [154][5/63] lr: 1.9130e-03 eta: 10:56:12 time: 0.7230 data_time: 0.1968 memory: 14901 loss: 2.2539 loss_prob: 1.3769 loss_thr: 0.6524 loss_db: 0.2245 2022/11/02 13:46:31 - mmengine - INFO - Epoch(train) [154][10/63] lr: 1.9130e-03 eta: 10:56:02 time: 0.7363 data_time: 0.1951 memory: 14901 loss: 2.1424 loss_prob: 1.2941 loss_thr: 0.6360 loss_db: 0.2123 2022/11/02 13:46:34 - mmengine - INFO - Epoch(train) [154][15/63] lr: 1.9130e-03 eta: 10:56:02 time: 0.5171 data_time: 0.0082 memory: 14901 loss: 2.1430 loss_prob: 1.2856 loss_thr: 0.6483 loss_db: 0.2092 2022/11/02 13:46:36 - mmengine - INFO - Epoch(train) [154][20/63] lr: 1.9130e-03 eta: 10:55:51 time: 0.5306 data_time: 0.0107 memory: 14901 loss: 2.1902 loss_prob: 1.3225 loss_thr: 0.6542 loss_db: 0.2135 2022/11/02 13:46:39 - mmengine - INFO - Epoch(train) [154][25/63] lr: 1.9130e-03 eta: 10:55:51 time: 0.5184 data_time: 0.0175 memory: 14901 loss: 2.0595 loss_prob: 1.2076 loss_thr: 0.6539 loss_db: 0.1979 2022/11/02 13:46:42 - mmengine - INFO - Epoch(train) [154][30/63] lr: 1.9130e-03 eta: 10:55:43 time: 0.5605 data_time: 0.0301 memory: 14901 loss: 2.0397 loss_prob: 1.1843 loss_thr: 0.6612 loss_db: 0.1941 2022/11/02 13:46:44 - mmengine - INFO - Epoch(train) [154][35/63] lr: 1.9130e-03 eta: 10:55:43 time: 0.5290 data_time: 0.0242 memory: 14901 loss: 1.9942 loss_prob: 1.1656 loss_thr: 0.6377 loss_db: 0.1908 2022/11/02 13:46:47 - mmengine - INFO - Epoch(train) [154][40/63] lr: 1.9130e-03 eta: 10:55:29 time: 0.4796 data_time: 0.0091 memory: 14901 loss: 2.0269 loss_prob: 1.1921 loss_thr: 0.6379 loss_db: 0.1968 2022/11/02 13:46:49 - mmengine - INFO - Epoch(train) [154][45/63] lr: 1.9130e-03 eta: 10:55:29 time: 0.5021 data_time: 0.0063 memory: 14901 loss: 2.0265 loss_prob: 1.1940 loss_thr: 0.6353 loss_db: 0.1972 2022/11/02 13:46:52 - mmengine - INFO - Epoch(train) [154][50/63] lr: 1.9130e-03 eta: 10:55:20 time: 0.5535 data_time: 0.0139 memory: 14901 loss: 2.1415 loss_prob: 1.2865 loss_thr: 0.6451 loss_db: 0.2099 2022/11/02 13:46:55 - mmengine - INFO - Epoch(train) [154][55/63] lr: 1.9130e-03 eta: 10:55:20 time: 0.5889 data_time: 0.0229 memory: 14901 loss: 2.1527 loss_prob: 1.2839 loss_thr: 0.6598 loss_db: 0.2090 2022/11/02 13:46:58 - mmengine - INFO - Epoch(train) [154][60/63] lr: 1.9130e-03 eta: 10:55:13 time: 0.5876 data_time: 0.0163 memory: 14901 loss: 2.0116 loss_prob: 1.1825 loss_thr: 0.6373 loss_db: 0.1918 2022/11/02 13:47:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:47:07 - mmengine - INFO - Epoch(train) [155][5/63] lr: 1.9113e-03 eta: 10:55:13 time: 0.9843 data_time: 0.2498 memory: 14901 loss: 2.5393 loss_prob: 1.5811 loss_thr: 0.6972 loss_db: 0.2610 2022/11/02 13:47:09 - mmengine - INFO - Epoch(train) [155][10/63] lr: 1.9113e-03 eta: 10:55:17 time: 0.9500 data_time: 0.2478 memory: 14901 loss: 2.1454 loss_prob: 1.2830 loss_thr: 0.6458 loss_db: 0.2166 2022/11/02 13:47:12 - mmengine - INFO - Epoch(train) [155][15/63] lr: 1.9113e-03 eta: 10:55:17 time: 0.5261 data_time: 0.0044 memory: 14901 loss: 2.0686 loss_prob: 1.2309 loss_thr: 0.6380 loss_db: 0.1997 2022/11/02 13:47:14 - mmengine - INFO - Epoch(train) [155][20/63] lr: 1.9113e-03 eta: 10:55:06 time: 0.5207 data_time: 0.0048 memory: 14901 loss: 2.0419 loss_prob: 1.2118 loss_thr: 0.6371 loss_db: 0.1930 2022/11/02 13:47:17 - mmengine - INFO - Epoch(train) [155][25/63] lr: 1.9113e-03 eta: 10:55:06 time: 0.5544 data_time: 0.0289 memory: 14901 loss: 2.2008 loss_prob: 1.3147 loss_thr: 0.6724 loss_db: 0.2138 2022/11/02 13:47:21 - mmengine - INFO - Epoch(train) [155][30/63] lr: 1.9113e-03 eta: 10:55:01 time: 0.6046 data_time: 0.0432 memory: 14901 loss: 2.1998 loss_prob: 1.3049 loss_thr: 0.6801 loss_db: 0.2148 2022/11/02 13:47:24 - mmengine - INFO - Epoch(train) [155][35/63] lr: 1.9113e-03 eta: 10:55:01 time: 0.6808 data_time: 0.0192 memory: 14901 loss: 2.1364 loss_prob: 1.2631 loss_thr: 0.6646 loss_db: 0.2087 2022/11/02 13:47:27 - mmengine - INFO - Epoch(train) [155][40/63] lr: 1.9113e-03 eta: 10:54:58 time: 0.6438 data_time: 0.0044 memory: 14901 loss: 2.0697 loss_prob: 1.2346 loss_thr: 0.6309 loss_db: 0.2042 2022/11/02 13:47:30 - mmengine - INFO - Epoch(train) [155][45/63] lr: 1.9113e-03 eta: 10:54:58 time: 0.6101 data_time: 0.0050 memory: 14901 loss: 2.0600 loss_prob: 1.2314 loss_thr: 0.6302 loss_db: 0.1984 2022/11/02 13:47:34 - mmengine - INFO - Epoch(train) [155][50/63] lr: 1.9113e-03 eta: 10:54:56 time: 0.6598 data_time: 0.0152 memory: 14901 loss: 2.1499 loss_prob: 1.2908 loss_thr: 0.6507 loss_db: 0.2084 2022/11/02 13:47:37 - mmengine - INFO - Epoch(train) [155][55/63] lr: 1.9113e-03 eta: 10:54:56 time: 0.6709 data_time: 0.0220 memory: 14901 loss: 2.0770 loss_prob: 1.2347 loss_thr: 0.6403 loss_db: 0.2020 2022/11/02 13:47:40 - mmengine - INFO - Epoch(train) [155][60/63] lr: 1.9113e-03 eta: 10:54:53 time: 0.6347 data_time: 0.0117 memory: 14901 loss: 1.9611 loss_prob: 1.1403 loss_thr: 0.6355 loss_db: 0.1852 2022/11/02 13:47:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:47:46 - mmengine - INFO - Epoch(train) [156][5/63] lr: 1.9097e-03 eta: 10:54:53 time: 0.7359 data_time: 0.2048 memory: 14901 loss: 2.3773 loss_prob: 1.4397 loss_thr: 0.7019 loss_db: 0.2357 2022/11/02 13:47:49 - mmengine - INFO - Epoch(train) [156][10/63] lr: 1.9097e-03 eta: 10:54:45 time: 0.7728 data_time: 0.2072 memory: 14901 loss: 2.1244 loss_prob: 1.2437 loss_thr: 0.6769 loss_db: 0.2038 2022/11/02 13:47:52 - mmengine - INFO - Epoch(train) [156][15/63] lr: 1.9097e-03 eta: 10:54:45 time: 0.5557 data_time: 0.0078 memory: 14901 loss: 2.0407 loss_prob: 1.2093 loss_thr: 0.6338 loss_db: 0.1977 2022/11/02 13:47:54 - mmengine - INFO - Epoch(train) [156][20/63] lr: 1.9097e-03 eta: 10:54:35 time: 0.5410 data_time: 0.0083 memory: 14901 loss: 1.9655 loss_prob: 1.1661 loss_thr: 0.6128 loss_db: 0.1866 2022/11/02 13:47:57 - mmengine - INFO - Epoch(train) [156][25/63] lr: 1.9097e-03 eta: 10:54:35 time: 0.4878 data_time: 0.0173 memory: 14901 loss: 2.0530 loss_prob: 1.2049 loss_thr: 0.6544 loss_db: 0.1937 2022/11/02 13:47:59 - mmengine - INFO - Epoch(train) [156][30/63] lr: 1.9097e-03 eta: 10:54:22 time: 0.4908 data_time: 0.0293 memory: 14901 loss: 2.1411 loss_prob: 1.2548 loss_thr: 0.6763 loss_db: 0.2099 2022/11/02 13:48:02 - mmengine - INFO - Epoch(train) [156][35/63] lr: 1.9097e-03 eta: 10:54:22 time: 0.5068 data_time: 0.0225 memory: 14901 loss: 2.0969 loss_prob: 1.2307 loss_thr: 0.6643 loss_db: 0.2019 2022/11/02 13:48:05 - mmengine - INFO - Epoch(train) [156][40/63] lr: 1.9097e-03 eta: 10:54:12 time: 0.5382 data_time: 0.0109 memory: 14901 loss: 1.9975 loss_prob: 1.1510 loss_thr: 0.6588 loss_db: 0.1877 2022/11/02 13:48:07 - mmengine - INFO - Epoch(train) [156][45/63] lr: 1.9097e-03 eta: 10:54:12 time: 0.5226 data_time: 0.0077 memory: 14901 loss: 2.0909 loss_prob: 1.2114 loss_thr: 0.6764 loss_db: 0.2031 2022/11/02 13:48:10 - mmengine - INFO - Epoch(train) [156][50/63] lr: 1.9097e-03 eta: 10:54:01 time: 0.5133 data_time: 0.0143 memory: 14901 loss: 2.0978 loss_prob: 1.2308 loss_thr: 0.6621 loss_db: 0.2049 2022/11/02 13:48:12 - mmengine - INFO - Epoch(train) [156][55/63] lr: 1.9097e-03 eta: 10:54:01 time: 0.5185 data_time: 0.0197 memory: 14901 loss: 2.0862 loss_prob: 1.2361 loss_thr: 0.6532 loss_db: 0.1969 2022/11/02 13:48:15 - mmengine - INFO - Epoch(train) [156][60/63] lr: 1.9097e-03 eta: 10:53:48 time: 0.4989 data_time: 0.0123 memory: 14901 loss: 2.3807 loss_prob: 1.4522 loss_thr: 0.6968 loss_db: 0.2317 2022/11/02 13:48:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:48:21 - mmengine - INFO - Epoch(train) [157][5/63] lr: 1.9080e-03 eta: 10:53:48 time: 0.7486 data_time: 0.2821 memory: 14901 loss: 2.3360 loss_prob: 1.4276 loss_thr: 0.6712 loss_db: 0.2372 2022/11/02 13:48:24 - mmengine - INFO - Epoch(train) [157][10/63] lr: 1.9080e-03 eta: 10:53:40 time: 0.7613 data_time: 0.2812 memory: 14901 loss: 2.1483 loss_prob: 1.3121 loss_thr: 0.6260 loss_db: 0.2102 2022/11/02 13:48:26 - mmengine - INFO - Epoch(train) [157][15/63] lr: 1.9080e-03 eta: 10:53:40 time: 0.4894 data_time: 0.0052 memory: 14901 loss: 2.1318 loss_prob: 1.2711 loss_thr: 0.6562 loss_db: 0.2045 2022/11/02 13:48:29 - mmengine - INFO - Epoch(train) [157][20/63] lr: 1.9080e-03 eta: 10:53:28 time: 0.5053 data_time: 0.0079 memory: 14901 loss: 2.0586 loss_prob: 1.1901 loss_thr: 0.6724 loss_db: 0.1962 2022/11/02 13:48:31 - mmengine - INFO - Epoch(train) [157][25/63] lr: 1.9080e-03 eta: 10:53:28 time: 0.5268 data_time: 0.0304 memory: 14901 loss: 2.2408 loss_prob: 1.3393 loss_thr: 0.6704 loss_db: 0.2310 2022/11/02 13:48:34 - mmengine - INFO - Epoch(train) [157][30/63] lr: 1.9080e-03 eta: 10:53:17 time: 0.5217 data_time: 0.0270 memory: 14901 loss: 2.4434 loss_prob: 1.4940 loss_thr: 0.6896 loss_db: 0.2598 2022/11/02 13:48:36 - mmengine - INFO - Epoch(train) [157][35/63] lr: 1.9080e-03 eta: 10:53:17 time: 0.5071 data_time: 0.0051 memory: 14901 loss: 2.2434 loss_prob: 1.3506 loss_thr: 0.6674 loss_db: 0.2254 2022/11/02 13:48:39 - mmengine - INFO - Epoch(train) [157][40/63] lr: 1.9080e-03 eta: 10:53:04 time: 0.4955 data_time: 0.0058 memory: 14901 loss: 2.1027 loss_prob: 1.2397 loss_thr: 0.6599 loss_db: 0.2032 2022/11/02 13:48:41 - mmengine - INFO - Epoch(train) [157][45/63] lr: 1.9080e-03 eta: 10:53:04 time: 0.4831 data_time: 0.0046 memory: 14901 loss: 2.2000 loss_prob: 1.3164 loss_thr: 0.6678 loss_db: 0.2158 2022/11/02 13:48:44 - mmengine - INFO - Epoch(train) [157][50/63] lr: 1.9080e-03 eta: 10:52:51 time: 0.4893 data_time: 0.0212 memory: 14901 loss: 2.2611 loss_prob: 1.3715 loss_thr: 0.6618 loss_db: 0.2278 2022/11/02 13:48:46 - mmengine - INFO - Epoch(train) [157][55/63] lr: 1.9080e-03 eta: 10:52:51 time: 0.4897 data_time: 0.0226 memory: 14901 loss: 2.1873 loss_prob: 1.3094 loss_thr: 0.6570 loss_db: 0.2209 2022/11/02 13:48:49 - mmengine - INFO - Epoch(train) [157][60/63] lr: 1.9080e-03 eta: 10:52:38 time: 0.4907 data_time: 0.0056 memory: 14901 loss: 2.0768 loss_prob: 1.2280 loss_thr: 0.6458 loss_db: 0.2030 2022/11/02 13:48:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:48:55 - mmengine - INFO - Epoch(train) [158][5/63] lr: 1.9064e-03 eta: 10:52:38 time: 0.6928 data_time: 0.2176 memory: 14901 loss: 2.2341 loss_prob: 1.3465 loss_thr: 0.6684 loss_db: 0.2193 2022/11/02 13:48:57 - mmengine - INFO - Epoch(train) [158][10/63] lr: 1.9064e-03 eta: 10:52:26 time: 0.7098 data_time: 0.2174 memory: 14901 loss: 2.2260 loss_prob: 1.3448 loss_thr: 0.6623 loss_db: 0.2188 2022/11/02 13:48:59 - mmengine - INFO - Epoch(train) [158][15/63] lr: 1.9064e-03 eta: 10:52:26 time: 0.4564 data_time: 0.0042 memory: 14901 loss: 2.0584 loss_prob: 1.2132 loss_thr: 0.6455 loss_db: 0.1997 2022/11/02 13:49:02 - mmengine - INFO - Epoch(train) [158][20/63] lr: 1.9064e-03 eta: 10:52:11 time: 0.4689 data_time: 0.0041 memory: 14901 loss: 2.0524 loss_prob: 1.2054 loss_thr: 0.6461 loss_db: 0.2009 2022/11/02 13:49:04 - mmengine - INFO - Epoch(train) [158][25/63] lr: 1.9064e-03 eta: 10:52:11 time: 0.4977 data_time: 0.0209 memory: 14901 loss: 2.0902 loss_prob: 1.2301 loss_thr: 0.6562 loss_db: 0.2039 2022/11/02 13:49:07 - mmengine - INFO - Epoch(train) [158][30/63] lr: 1.9064e-03 eta: 10:51:59 time: 0.4952 data_time: 0.0310 memory: 14901 loss: 2.0792 loss_prob: 1.2267 loss_thr: 0.6499 loss_db: 0.2026 2022/11/02 13:49:09 - mmengine - INFO - Epoch(train) [158][35/63] lr: 1.9064e-03 eta: 10:51:59 time: 0.4953 data_time: 0.0150 memory: 14901 loss: 2.2790 loss_prob: 1.3816 loss_thr: 0.6711 loss_db: 0.2263 2022/11/02 13:49:12 - mmengine - INFO - Epoch(train) [158][40/63] lr: 1.9064e-03 eta: 10:51:48 time: 0.5197 data_time: 0.0054 memory: 14901 loss: 2.3036 loss_prob: 1.4084 loss_thr: 0.6646 loss_db: 0.2306 2022/11/02 13:49:14 - mmengine - INFO - Epoch(train) [158][45/63] lr: 1.9064e-03 eta: 10:51:48 time: 0.4953 data_time: 0.0074 memory: 14901 loss: 2.0656 loss_prob: 1.2277 loss_thr: 0.6380 loss_db: 0.1999 2022/11/02 13:49:17 - mmengine - INFO - Epoch(train) [158][50/63] lr: 1.9064e-03 eta: 10:51:35 time: 0.4888 data_time: 0.0216 memory: 14901 loss: 2.1950 loss_prob: 1.3049 loss_thr: 0.6752 loss_db: 0.2149 2022/11/02 13:49:19 - mmengine - INFO - Epoch(train) [158][55/63] lr: 1.9064e-03 eta: 10:51:35 time: 0.5294 data_time: 0.0263 memory: 14901 loss: 2.5972 loss_prob: 1.6279 loss_thr: 0.7040 loss_db: 0.2653 2022/11/02 13:49:22 - mmengine - INFO - Epoch(train) [158][60/63] lr: 1.9064e-03 eta: 10:51:22 time: 0.4856 data_time: 0.0119 memory: 14901 loss: 2.4970 loss_prob: 1.5709 loss_thr: 0.6767 loss_db: 0.2494 2022/11/02 13:49:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:49:29 - mmengine - INFO - Epoch(train) [159][5/63] lr: 1.9048e-03 eta: 10:51:22 time: 0.8282 data_time: 0.2343 memory: 14901 loss: 2.3623 loss_prob: 1.4372 loss_thr: 0.6942 loss_db: 0.2309 2022/11/02 13:49:33 - mmengine - INFO - Epoch(train) [159][10/63] lr: 1.9048e-03 eta: 10:51:26 time: 0.9589 data_time: 0.2380 memory: 14901 loss: 2.2905 loss_prob: 1.3984 loss_thr: 0.6671 loss_db: 0.2249 2022/11/02 13:49:35 - mmengine - INFO - Epoch(train) [159][15/63] lr: 1.9048e-03 eta: 10:51:26 time: 0.6055 data_time: 0.0079 memory: 14901 loss: 2.1675 loss_prob: 1.3035 loss_thr: 0.6473 loss_db: 0.2167 2022/11/02 13:49:39 - mmengine - INFO - Epoch(train) [159][20/63] lr: 1.9048e-03 eta: 10:51:21 time: 0.6010 data_time: 0.0042 memory: 14901 loss: 2.2648 loss_prob: 1.3634 loss_thr: 0.6737 loss_db: 0.2277 2022/11/02 13:49:41 - mmengine - INFO - Epoch(train) [159][25/63] lr: 1.9048e-03 eta: 10:51:21 time: 0.5831 data_time: 0.0173 memory: 14901 loss: 2.1269 loss_prob: 1.2695 loss_thr: 0.6533 loss_db: 0.2041 2022/11/02 13:49:44 - mmengine - INFO - Epoch(train) [159][30/63] lr: 1.9048e-03 eta: 10:51:08 time: 0.5027 data_time: 0.0334 memory: 14901 loss: 2.0525 loss_prob: 1.2020 loss_thr: 0.6562 loss_db: 0.1944 2022/11/02 13:49:47 - mmengine - INFO - Epoch(train) [159][35/63] lr: 1.9048e-03 eta: 10:51:08 time: 0.6001 data_time: 0.0202 memory: 14901 loss: 1.9669 loss_prob: 1.1267 loss_thr: 0.6531 loss_db: 0.1871 2022/11/02 13:49:49 - mmengine - INFO - Epoch(train) [159][40/63] lr: 1.9048e-03 eta: 10:51:02 time: 0.5858 data_time: 0.0047 memory: 14901 loss: 1.9014 loss_prob: 1.0989 loss_thr: 0.6232 loss_db: 0.1793 2022/11/02 13:49:53 - mmengine - INFO - Epoch(train) [159][45/63] lr: 1.9048e-03 eta: 10:51:02 time: 0.6176 data_time: 0.0055 memory: 14901 loss: 2.0631 loss_prob: 1.2218 loss_thr: 0.6433 loss_db: 0.1981 2022/11/02 13:49:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:49:56 - mmengine - INFO - Epoch(train) [159][50/63] lr: 1.9048e-03 eta: 10:51:01 time: 0.6778 data_time: 0.0313 memory: 14901 loss: 2.2949 loss_prob: 1.3887 loss_thr: 0.6774 loss_db: 0.2288 2022/11/02 13:49:59 - mmengine - INFO - Epoch(train) [159][55/63] lr: 1.9048e-03 eta: 10:51:01 time: 0.6059 data_time: 0.0317 memory: 14901 loss: 2.2824 loss_prob: 1.3862 loss_thr: 0.6686 loss_db: 0.2277 2022/11/02 13:50:02 - mmengine - INFO - Epoch(train) [159][60/63] lr: 1.9048e-03 eta: 10:50:52 time: 0.5507 data_time: 0.0062 memory: 14901 loss: 2.0958 loss_prob: 1.2569 loss_thr: 0.6341 loss_db: 0.2048 2022/11/02 13:50:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:50:08 - mmengine - INFO - Epoch(train) [160][5/63] lr: 1.9031e-03 eta: 10:50:52 time: 0.7393 data_time: 0.2394 memory: 14901 loss: 2.1852 loss_prob: 1.3238 loss_thr: 0.6454 loss_db: 0.2161 2022/11/02 13:50:11 - mmengine - INFO - Epoch(train) [160][10/63] lr: 1.9031e-03 eta: 10:50:46 time: 0.8016 data_time: 0.2361 memory: 14901 loss: 2.2059 loss_prob: 1.3405 loss_thr: 0.6514 loss_db: 0.2140 2022/11/02 13:50:14 - mmengine - INFO - Epoch(train) [160][15/63] lr: 1.9031e-03 eta: 10:50:46 time: 0.6032 data_time: 0.0053 memory: 14901 loss: 2.1831 loss_prob: 1.3149 loss_thr: 0.6511 loss_db: 0.2171 2022/11/02 13:50:17 - mmengine - INFO - Epoch(train) [160][20/63] lr: 1.9031e-03 eta: 10:50:39 time: 0.5656 data_time: 0.0060 memory: 14901 loss: 2.4485 loss_prob: 1.5213 loss_thr: 0.6843 loss_db: 0.2429 2022/11/02 13:50:19 - mmengine - INFO - Epoch(train) [160][25/63] lr: 1.9031e-03 eta: 10:50:39 time: 0.5207 data_time: 0.0186 memory: 14901 loss: 2.3799 loss_prob: 1.4549 loss_thr: 0.6948 loss_db: 0.2301 2022/11/02 13:50:24 - mmengine - INFO - Epoch(train) [160][30/63] lr: 1.9031e-03 eta: 10:50:42 time: 0.7407 data_time: 0.0321 memory: 14901 loss: 2.1821 loss_prob: 1.2990 loss_thr: 0.6684 loss_db: 0.2147 2022/11/02 13:50:27 - mmengine - INFO - Epoch(train) [160][35/63] lr: 1.9031e-03 eta: 10:50:42 time: 0.7574 data_time: 0.0186 memory: 14901 loss: 2.1191 loss_prob: 1.2630 loss_thr: 0.6473 loss_db: 0.2088 2022/11/02 13:50:29 - mmengine - INFO - Epoch(train) [160][40/63] lr: 1.9031e-03 eta: 10:50:30 time: 0.5035 data_time: 0.0041 memory: 14901 loss: 2.0242 loss_prob: 1.1915 loss_thr: 0.6362 loss_db: 0.1965 2022/11/02 13:50:32 - mmengine - INFO - Epoch(train) [160][45/63] lr: 1.9031e-03 eta: 10:50:30 time: 0.4766 data_time: 0.0041 memory: 14901 loss: 2.1285 loss_prob: 1.2678 loss_thr: 0.6536 loss_db: 0.2071 2022/11/02 13:50:34 - mmengine - INFO - Epoch(train) [160][50/63] lr: 1.9031e-03 eta: 10:50:18 time: 0.5080 data_time: 0.0168 memory: 14901 loss: 2.1882 loss_prob: 1.3228 loss_thr: 0.6534 loss_db: 0.2119 2022/11/02 13:50:37 - mmengine - INFO - Epoch(train) [160][55/63] lr: 1.9031e-03 eta: 10:50:18 time: 0.5024 data_time: 0.0253 memory: 14901 loss: 2.1808 loss_prob: 1.3250 loss_thr: 0.6460 loss_db: 0.2097 2022/11/02 13:50:39 - mmengine - INFO - Epoch(train) [160][60/63] lr: 1.9031e-03 eta: 10:50:05 time: 0.4848 data_time: 0.0130 memory: 14901 loss: 2.0668 loss_prob: 1.2340 loss_thr: 0.6343 loss_db: 0.1985 2022/11/02 13:50:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:50:40 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/11/02 13:50:44 - mmengine - INFO - Epoch(val) [160][5/500] eta: 10:50:05 time: 0.0453 data_time: 0.0049 memory: 14901 2022/11/02 13:50:44 - mmengine - INFO - Epoch(val) [160][10/500] eta: 0:00:22 time: 0.0457 data_time: 0.0046 memory: 1008 2022/11/02 13:50:44 - mmengine - INFO - Epoch(val) [160][15/500] eta: 0:00:22 time: 0.0373 data_time: 0.0020 memory: 1008 2022/11/02 13:50:44 - mmengine - INFO - Epoch(val) [160][20/500] eta: 0:00:18 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 13:50:45 - mmengine - INFO - Epoch(val) [160][25/500] eta: 0:00:18 time: 0.0375 data_time: 0.0028 memory: 1008 2022/11/02 13:50:45 - mmengine - INFO - Epoch(val) [160][30/500] eta: 0:00:19 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 13:50:45 - mmengine - INFO - Epoch(val) [160][35/500] eta: 0:00:19 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 13:50:45 - mmengine - INFO - Epoch(val) [160][40/500] eta: 0:00:20 time: 0.0446 data_time: 0.0029 memory: 1008 2022/11/02 13:50:46 - mmengine - INFO - Epoch(val) [160][45/500] eta: 0:00:20 time: 0.0445 data_time: 0.0028 memory: 1008 2022/11/02 13:50:46 - mmengine - INFO - Epoch(val) [160][50/500] eta: 0:00:18 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/02 13:50:46 - mmengine - INFO - Epoch(val) [160][55/500] eta: 0:00:18 time: 0.0432 data_time: 0.0025 memory: 1008 2022/11/02 13:50:46 - mmengine - INFO - Epoch(val) [160][60/500] eta: 0:00:18 time: 0.0417 data_time: 0.0023 memory: 1008 2022/11/02 13:50:46 - mmengine - INFO - Epoch(val) [160][65/500] eta: 0:00:18 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 13:50:47 - mmengine - INFO - Epoch(val) [160][70/500] eta: 0:00:17 time: 0.0417 data_time: 0.0024 memory: 1008 2022/11/02 13:50:47 - mmengine - INFO - Epoch(val) [160][75/500] eta: 0:00:17 time: 0.0424 data_time: 0.0028 memory: 1008 2022/11/02 13:50:47 - mmengine - INFO - Epoch(val) [160][80/500] eta: 0:00:16 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 13:50:47 - mmengine - INFO - Epoch(val) [160][85/500] eta: 0:00:16 time: 0.0363 data_time: 0.0024 memory: 1008 2022/11/02 13:50:47 - mmengine - INFO - Epoch(val) [160][90/500] eta: 0:00:16 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 13:50:48 - mmengine - INFO - Epoch(val) [160][95/500] eta: 0:00:16 time: 0.0425 data_time: 0.0026 memory: 1008 2022/11/02 13:50:48 - mmengine - INFO - Epoch(val) [160][100/500] eta: 0:00:15 time: 0.0392 data_time: 0.0029 memory: 1008 2022/11/02 13:50:48 - mmengine - INFO - Epoch(val) [160][105/500] eta: 0:00:15 time: 0.0369 data_time: 0.0027 memory: 1008 2022/11/02 13:50:48 - mmengine - INFO - Epoch(val) [160][110/500] eta: 0:00:14 time: 0.0363 data_time: 0.0022 memory: 1008 2022/11/02 13:50:48 - mmengine - INFO - Epoch(val) [160][115/500] eta: 0:00:14 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 13:50:49 - mmengine - INFO - Epoch(val) [160][120/500] eta: 0:00:15 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/02 13:50:49 - mmengine - INFO - Epoch(val) [160][125/500] eta: 0:00:15 time: 0.0385 data_time: 0.0024 memory: 1008 2022/11/02 13:50:49 - mmengine - INFO - Epoch(val) [160][130/500] eta: 0:00:13 time: 0.0367 data_time: 0.0024 memory: 1008 2022/11/02 13:50:49 - mmengine - INFO - Epoch(val) [160][135/500] eta: 0:00:13 time: 0.0364 data_time: 0.0024 memory: 1008 2022/11/02 13:50:49 - mmengine - INFO - Epoch(val) [160][140/500] eta: 0:00:13 time: 0.0381 data_time: 0.0024 memory: 1008 2022/11/02 13:50:50 - mmengine - INFO - Epoch(val) [160][145/500] eta: 0:00:13 time: 0.0451 data_time: 0.0025 memory: 1008 2022/11/02 13:50:50 - mmengine - INFO - Epoch(val) [160][150/500] eta: 0:00:16 time: 0.0463 data_time: 0.0025 memory: 1008 2022/11/02 13:50:50 - mmengine - INFO - Epoch(val) [160][155/500] eta: 0:00:16 time: 0.0441 data_time: 0.0024 memory: 1008 2022/11/02 13:50:50 - mmengine - INFO - Epoch(val) [160][160/500] eta: 0:00:14 time: 0.0438 data_time: 0.0024 memory: 1008 2022/11/02 13:50:50 - mmengine - INFO - Epoch(val) [160][165/500] eta: 0:00:14 time: 0.0422 data_time: 0.0025 memory: 1008 2022/11/02 13:50:51 - mmengine - INFO - Epoch(val) [160][170/500] eta: 0:00:14 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/02 13:50:51 - mmengine - INFO - Epoch(val) [160][175/500] eta: 0:00:14 time: 0.0419 data_time: 0.0041 memory: 1008 2022/11/02 13:50:51 - mmengine - INFO - Epoch(val) [160][180/500] eta: 0:00:12 time: 0.0391 data_time: 0.0036 memory: 1008 2022/11/02 13:50:51 - mmengine - INFO - Epoch(val) [160][185/500] eta: 0:00:12 time: 0.0424 data_time: 0.0023 memory: 1008 2022/11/02 13:50:51 - mmengine - INFO - Epoch(val) [160][190/500] eta: 0:00:14 time: 0.0459 data_time: 0.0026 memory: 1008 2022/11/02 13:50:52 - mmengine - INFO - Epoch(val) [160][195/500] eta: 0:00:14 time: 0.0414 data_time: 0.0025 memory: 1008 2022/11/02 13:50:52 - mmengine - INFO - Epoch(val) [160][200/500] eta: 0:00:13 time: 0.0458 data_time: 0.0025 memory: 1008 2022/11/02 13:50:52 - mmengine - INFO - Epoch(val) [160][205/500] eta: 0:00:13 time: 0.0450 data_time: 0.0025 memory: 1008 2022/11/02 13:50:52 - mmengine - INFO - Epoch(val) [160][210/500] eta: 0:00:10 time: 0.0374 data_time: 0.0024 memory: 1008 2022/11/02 13:50:53 - mmengine - INFO - Epoch(val) [160][215/500] eta: 0:00:10 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/02 13:50:53 - mmengine - INFO - Epoch(val) [160][220/500] eta: 0:00:12 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 13:50:53 - mmengine - INFO - Epoch(val) [160][225/500] eta: 0:00:12 time: 0.0416 data_time: 0.0026 memory: 1008 2022/11/02 13:50:53 - mmengine - INFO - Epoch(val) [160][230/500] eta: 0:00:10 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 13:50:53 - mmengine - INFO - Epoch(val) [160][235/500] eta: 0:00:10 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/02 13:50:54 - mmengine - INFO - Epoch(val) [160][240/500] eta: 0:00:10 time: 0.0403 data_time: 0.0024 memory: 1008 2022/11/02 13:50:54 - mmengine - INFO - Epoch(val) [160][245/500] eta: 0:00:10 time: 0.0387 data_time: 0.0024 memory: 1008 2022/11/02 13:50:54 - mmengine - INFO - Epoch(val) [160][250/500] eta: 0:00:09 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 13:50:54 - mmengine - INFO - Epoch(val) [160][255/500] eta: 0:00:09 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/02 13:50:54 - mmengine - INFO - Epoch(val) [160][260/500] eta: 0:00:08 time: 0.0359 data_time: 0.0024 memory: 1008 2022/11/02 13:50:55 - mmengine - INFO - Epoch(val) [160][265/500] eta: 0:00:08 time: 0.0431 data_time: 0.0062 memory: 1008 2022/11/02 13:50:55 - mmengine - INFO - Epoch(val) [160][270/500] eta: 0:00:10 time: 0.0440 data_time: 0.0062 memory: 1008 2022/11/02 13:50:55 - mmengine - INFO - Epoch(val) [160][275/500] eta: 0:00:10 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 13:50:55 - mmengine - INFO - Epoch(val) [160][280/500] eta: 0:00:09 time: 0.0415 data_time: 0.0034 memory: 1008 2022/11/02 13:50:55 - mmengine - INFO - Epoch(val) [160][285/500] eta: 0:00:09 time: 0.0411 data_time: 0.0036 memory: 1008 2022/11/02 13:50:56 - mmengine - INFO - Epoch(val) [160][290/500] eta: 0:00:07 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 13:50:56 - mmengine - INFO - Epoch(val) [160][295/500] eta: 0:00:07 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 13:50:56 - mmengine - INFO - Epoch(val) [160][300/500] eta: 0:00:07 time: 0.0395 data_time: 0.0029 memory: 1008 2022/11/02 13:50:56 - mmengine - INFO - Epoch(val) [160][305/500] eta: 0:00:07 time: 0.0360 data_time: 0.0022 memory: 1008 2022/11/02 13:50:56 - mmengine - INFO - Epoch(val) [160][310/500] eta: 0:00:06 time: 0.0353 data_time: 0.0021 memory: 1008 2022/11/02 13:50:57 - mmengine - INFO - Epoch(val) [160][315/500] eta: 0:00:06 time: 0.0439 data_time: 0.0025 memory: 1008 2022/11/02 13:50:57 - mmengine - INFO - Epoch(val) [160][320/500] eta: 0:00:08 time: 0.0471 data_time: 0.0029 memory: 1008 2022/11/02 13:50:57 - mmengine - INFO - Epoch(val) [160][325/500] eta: 0:00:08 time: 0.0567 data_time: 0.0027 memory: 1008 2022/11/02 13:50:57 - mmengine - INFO - Epoch(val) [160][330/500] eta: 0:00:09 time: 0.0550 data_time: 0.0026 memory: 1008 2022/11/02 13:50:57 - mmengine - INFO - Epoch(val) [160][335/500] eta: 0:00:09 time: 0.0366 data_time: 0.0024 memory: 1008 2022/11/02 13:50:58 - mmengine - INFO - Epoch(val) [160][340/500] eta: 0:00:07 time: 0.0461 data_time: 0.0024 memory: 1008 2022/11/02 13:50:58 - mmengine - INFO - Epoch(val) [160][345/500] eta: 0:00:07 time: 0.0476 data_time: 0.0024 memory: 1008 2022/11/02 13:50:58 - mmengine - INFO - Epoch(val) [160][350/500] eta: 0:00:06 time: 0.0425 data_time: 0.0024 memory: 1008 2022/11/02 13:50:58 - mmengine - INFO - Epoch(val) [160][355/500] eta: 0:00:06 time: 0.0446 data_time: 0.0024 memory: 1008 2022/11/02 13:50:59 - mmengine - INFO - Epoch(val) [160][360/500] eta: 0:00:05 time: 0.0412 data_time: 0.0024 memory: 1008 2022/11/02 13:50:59 - mmengine - INFO - Epoch(val) [160][365/500] eta: 0:00:05 time: 0.0430 data_time: 0.0026 memory: 1008 2022/11/02 13:50:59 - mmengine - INFO - Epoch(val) [160][370/500] eta: 0:00:05 time: 0.0420 data_time: 0.0035 memory: 1008 2022/11/02 13:50:59 - mmengine - INFO - Epoch(val) [160][375/500] eta: 0:00:05 time: 0.0370 data_time: 0.0031 memory: 1008 2022/11/02 13:50:59 - mmengine - INFO - Epoch(val) [160][380/500] eta: 0:00:05 time: 0.0423 data_time: 0.0024 memory: 1008 2022/11/02 13:51:00 - mmengine - INFO - Epoch(val) [160][385/500] eta: 0:00:05 time: 0.0438 data_time: 0.0027 memory: 1008 2022/11/02 13:51:00 - mmengine - INFO - Epoch(val) [160][390/500] eta: 0:00:04 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 13:51:00 - mmengine - INFO - Epoch(val) [160][395/500] eta: 0:00:04 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 13:51:00 - mmengine - INFO - Epoch(val) [160][400/500] eta: 0:00:04 time: 0.0401 data_time: 0.0024 memory: 1008 2022/11/02 13:51:00 - mmengine - INFO - Epoch(val) [160][405/500] eta: 0:00:04 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/02 13:51:01 - mmengine - INFO - Epoch(val) [160][410/500] eta: 0:00:03 time: 0.0412 data_time: 0.0024 memory: 1008 2022/11/02 13:51:01 - mmengine - INFO - Epoch(val) [160][415/500] eta: 0:00:03 time: 0.0399 data_time: 0.0023 memory: 1008 2022/11/02 13:51:01 - mmengine - INFO - Epoch(val) [160][420/500] eta: 0:00:02 time: 0.0354 data_time: 0.0024 memory: 1008 2022/11/02 13:51:01 - mmengine - INFO - Epoch(val) [160][425/500] eta: 0:00:02 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/02 13:51:01 - mmengine - INFO - Epoch(val) [160][430/500] eta: 0:00:02 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 13:51:02 - mmengine - INFO - Epoch(val) [160][435/500] eta: 0:00:02 time: 0.0385 data_time: 0.0023 memory: 1008 2022/11/02 13:51:02 - mmengine - INFO - Epoch(val) [160][440/500] eta: 0:00:02 time: 0.0391 data_time: 0.0024 memory: 1008 2022/11/02 13:51:02 - mmengine - INFO - Epoch(val) [160][445/500] eta: 0:00:02 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/02 13:51:02 - mmengine - INFO - Epoch(val) [160][450/500] eta: 0:00:02 time: 0.0463 data_time: 0.0042 memory: 1008 2022/11/02 13:51:02 - mmengine - INFO - Epoch(val) [160][455/500] eta: 0:00:02 time: 0.0442 data_time: 0.0041 memory: 1008 2022/11/02 13:51:03 - mmengine - INFO - Epoch(val) [160][460/500] eta: 0:00:01 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/02 13:51:03 - mmengine - INFO - Epoch(val) [160][465/500] eta: 0:00:01 time: 0.0355 data_time: 0.0023 memory: 1008 2022/11/02 13:51:03 - mmengine - INFO - Epoch(val) [160][470/500] eta: 0:00:01 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/02 13:51:03 - mmengine - INFO - Epoch(val) [160][475/500] eta: 0:00:01 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 13:51:03 - mmengine - INFO - Epoch(val) [160][480/500] eta: 0:00:00 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 13:51:04 - mmengine - INFO - Epoch(val) [160][485/500] eta: 0:00:00 time: 0.0394 data_time: 0.0026 memory: 1008 2022/11/02 13:51:04 - mmengine - INFO - Epoch(val) [160][490/500] eta: 0:00:00 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/02 13:51:04 - mmengine - INFO - Epoch(val) [160][495/500] eta: 0:00:00 time: 0.0421 data_time: 0.0025 memory: 1008 2022/11/02 13:51:04 - mmengine - INFO - Epoch(val) [160][500/500] eta: 0:00:00 time: 0.0375 data_time: 0.0024 memory: 1008 2022/11/02 13:51:04 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8098, precision: 0.6474, hmean: 0.7196 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8098, precision: 0.7269, hmean: 0.7661 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8065, precision: 0.7842, hmean: 0.7952 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7853, precision: 0.8429, hmean: 0.8131 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6875, precision: 0.9119, hmean: 0.7840 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1974, precision: 0.9535, hmean: 0.3271 2022/11/02 13:51:04 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0010, precision: 1.0000, hmean: 0.0019 2022/11/02 13:51:04 - mmengine - INFO - Epoch(val) [160][500/500] icdar/precision: 0.8429 icdar/recall: 0.7853 icdar/hmean: 0.8131 2022/11/02 13:51:09 - mmengine - INFO - Epoch(train) [161][5/63] lr: 1.9015e-03 eta: 0:00:00 time: 0.7435 data_time: 0.2079 memory: 14901 loss: 1.9386 loss_prob: 1.1364 loss_thr: 0.6155 loss_db: 0.1868 2022/11/02 13:51:12 - mmengine - INFO - Epoch(train) [161][10/63] lr: 1.9015e-03 eta: 10:49:56 time: 0.7540 data_time: 0.2086 memory: 14901 loss: 1.8914 loss_prob: 1.0974 loss_thr: 0.6178 loss_db: 0.1762 2022/11/02 13:51:14 - mmengine - INFO - Epoch(train) [161][15/63] lr: 1.9015e-03 eta: 10:49:56 time: 0.4845 data_time: 0.0085 memory: 14901 loss: 1.8821 loss_prob: 1.0929 loss_thr: 0.6103 loss_db: 0.1788 2022/11/02 13:51:17 - mmengine - INFO - Epoch(train) [161][20/63] lr: 1.9015e-03 eta: 10:49:43 time: 0.4813 data_time: 0.0079 memory: 14901 loss: 1.9884 loss_prob: 1.1724 loss_thr: 0.6212 loss_db: 0.1948 2022/11/02 13:51:19 - mmengine - INFO - Epoch(train) [161][25/63] lr: 1.9015e-03 eta: 10:49:43 time: 0.4825 data_time: 0.0148 memory: 14901 loss: 2.0063 loss_prob: 1.1748 loss_thr: 0.6384 loss_db: 0.1931 2022/11/02 13:51:22 - mmengine - INFO - Epoch(train) [161][30/63] lr: 1.9015e-03 eta: 10:49:31 time: 0.5002 data_time: 0.0366 memory: 14901 loss: 1.9663 loss_prob: 1.1467 loss_thr: 0.6295 loss_db: 0.1901 2022/11/02 13:51:24 - mmengine - INFO - Epoch(train) [161][35/63] lr: 1.9015e-03 eta: 10:49:31 time: 0.4980 data_time: 0.0266 memory: 14901 loss: 2.1138 loss_prob: 1.2490 loss_thr: 0.6570 loss_db: 0.2078 2022/11/02 13:51:27 - mmengine - INFO - Epoch(train) [161][40/63] lr: 1.9015e-03 eta: 10:49:18 time: 0.4952 data_time: 0.0042 memory: 14901 loss: 2.2533 loss_prob: 1.3613 loss_thr: 0.6724 loss_db: 0.2195 2022/11/02 13:51:29 - mmengine - INFO - Epoch(train) [161][45/63] lr: 1.9015e-03 eta: 10:49:18 time: 0.4846 data_time: 0.0067 memory: 14901 loss: 2.1098 loss_prob: 1.2687 loss_thr: 0.6355 loss_db: 0.2056 2022/11/02 13:51:31 - mmengine - INFO - Epoch(train) [161][50/63] lr: 1.9015e-03 eta: 10:49:06 time: 0.4884 data_time: 0.0189 memory: 14901 loss: 2.0478 loss_prob: 1.2122 loss_thr: 0.6331 loss_db: 0.2025 2022/11/02 13:51:34 - mmengine - INFO - Epoch(train) [161][55/63] lr: 1.9015e-03 eta: 10:49:06 time: 0.4952 data_time: 0.0262 memory: 14901 loss: 2.2120 loss_prob: 1.3320 loss_thr: 0.6626 loss_db: 0.2174 2022/11/02 13:51:36 - mmengine - INFO - Epoch(train) [161][60/63] lr: 1.9015e-03 eta: 10:48:52 time: 0.4736 data_time: 0.0145 memory: 14901 loss: 2.2532 loss_prob: 1.3528 loss_thr: 0.6847 loss_db: 0.2157 2022/11/02 13:51:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:51:42 - mmengine - INFO - Epoch(train) [162][5/63] lr: 1.8998e-03 eta: 10:48:52 time: 0.6803 data_time: 0.2112 memory: 14901 loss: 2.1123 loss_prob: 1.2569 loss_thr: 0.6476 loss_db: 0.2078 2022/11/02 13:51:45 - mmengine - INFO - Epoch(train) [162][10/63] lr: 1.8998e-03 eta: 10:48:40 time: 0.7082 data_time: 0.2138 memory: 14901 loss: 2.1167 loss_prob: 1.2393 loss_thr: 0.6731 loss_db: 0.2042 2022/11/02 13:51:47 - mmengine - INFO - Epoch(train) [162][15/63] lr: 1.8998e-03 eta: 10:48:40 time: 0.5321 data_time: 0.0112 memory: 14901 loss: 1.9923 loss_prob: 1.1618 loss_thr: 0.6412 loss_db: 0.1893 2022/11/02 13:51:50 - mmengine - INFO - Epoch(train) [162][20/63] lr: 1.8998e-03 eta: 10:48:28 time: 0.4974 data_time: 0.0087 memory: 14901 loss: 1.9423 loss_prob: 1.1374 loss_thr: 0.6194 loss_db: 0.1855 2022/11/02 13:51:52 - mmengine - INFO - Epoch(train) [162][25/63] lr: 1.8998e-03 eta: 10:48:28 time: 0.5143 data_time: 0.0370 memory: 14901 loss: 2.0694 loss_prob: 1.2343 loss_thr: 0.6294 loss_db: 0.2056 2022/11/02 13:51:55 - mmengine - INFO - Epoch(train) [162][30/63] lr: 1.8998e-03 eta: 10:48:17 time: 0.5178 data_time: 0.0378 memory: 14901 loss: 2.2766 loss_prob: 1.3917 loss_thr: 0.6533 loss_db: 0.2317 2022/11/02 13:51:57 - mmengine - INFO - Epoch(train) [162][35/63] lr: 1.8998e-03 eta: 10:48:17 time: 0.4594 data_time: 0.0061 memory: 14901 loss: 2.1350 loss_prob: 1.2730 loss_thr: 0.6560 loss_db: 0.2060 2022/11/02 13:51:59 - mmengine - INFO - Epoch(train) [162][40/63] lr: 1.8998e-03 eta: 10:48:03 time: 0.4717 data_time: 0.0072 memory: 14901 loss: 1.9422 loss_prob: 1.1198 loss_thr: 0.6415 loss_db: 0.1809 2022/11/02 13:52:02 - mmengine - INFO - Epoch(train) [162][45/63] lr: 1.8998e-03 eta: 10:48:03 time: 0.4876 data_time: 0.0072 memory: 14901 loss: 1.9701 loss_prob: 1.1504 loss_thr: 0.6300 loss_db: 0.1896 2022/11/02 13:52:05 - mmengine - INFO - Epoch(train) [162][50/63] lr: 1.8998e-03 eta: 10:47:52 time: 0.5182 data_time: 0.0229 memory: 14901 loss: 1.9752 loss_prob: 1.1790 loss_thr: 0.6019 loss_db: 0.1944 2022/11/02 13:52:07 - mmengine - INFO - Epoch(train) [162][55/63] lr: 1.8998e-03 eta: 10:47:52 time: 0.5283 data_time: 0.0245 memory: 14901 loss: 2.1931 loss_prob: 1.3349 loss_thr: 0.6429 loss_db: 0.2154 2022/11/02 13:52:10 - mmengine - INFO - Epoch(train) [162][60/63] lr: 1.8998e-03 eta: 10:47:41 time: 0.5176 data_time: 0.0069 memory: 14901 loss: 2.1472 loss_prob: 1.2831 loss_thr: 0.6572 loss_db: 0.2069 2022/11/02 13:52:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:52:17 - mmengine - INFO - Epoch(train) [163][5/63] lr: 1.8982e-03 eta: 10:47:41 time: 0.7873 data_time: 0.2499 memory: 14901 loss: 1.9953 loss_prob: 1.2007 loss_thr: 0.6030 loss_db: 0.1916 2022/11/02 13:52:20 - mmengine - INFO - Epoch(train) [163][10/63] lr: 1.8982e-03 eta: 10:47:39 time: 0.8631 data_time: 0.2506 memory: 14901 loss: 1.8570 loss_prob: 1.0819 loss_thr: 0.6065 loss_db: 0.1686 2022/11/02 13:52:23 - mmengine - INFO - Epoch(train) [163][15/63] lr: 1.8982e-03 eta: 10:47:39 time: 0.6211 data_time: 0.0077 memory: 14901 loss: 1.8359 loss_prob: 1.0558 loss_thr: 0.6098 loss_db: 0.1703 2022/11/02 13:52:26 - mmengine - INFO - Epoch(train) [163][20/63] lr: 1.8982e-03 eta: 10:47:37 time: 0.6508 data_time: 0.0070 memory: 14901 loss: 1.9544 loss_prob: 1.1378 loss_thr: 0.6270 loss_db: 0.1896 2022/11/02 13:52:29 - mmengine - INFO - Epoch(train) [163][25/63] lr: 1.8982e-03 eta: 10:47:37 time: 0.5896 data_time: 0.0153 memory: 14901 loss: 2.1014 loss_prob: 1.2402 loss_thr: 0.6542 loss_db: 0.2069 2022/11/02 13:52:33 - mmengine - INFO - Epoch(train) [163][30/63] lr: 1.8982e-03 eta: 10:47:34 time: 0.6358 data_time: 0.0334 memory: 14901 loss: 2.1207 loss_prob: 1.2738 loss_thr: 0.6405 loss_db: 0.2064 2022/11/02 13:52:35 - mmengine - INFO - Epoch(train) [163][35/63] lr: 1.8982e-03 eta: 10:47:34 time: 0.6569 data_time: 0.0244 memory: 14901 loss: 2.0832 loss_prob: 1.2456 loss_thr: 0.6364 loss_db: 0.2012 2022/11/02 13:52:38 - mmengine - INFO - Epoch(train) [163][40/63] lr: 1.8982e-03 eta: 10:47:26 time: 0.5613 data_time: 0.0059 memory: 14901 loss: 2.1750 loss_prob: 1.2756 loss_thr: 0.6880 loss_db: 0.2113 2022/11/02 13:52:42 - mmengine - INFO - Epoch(train) [163][45/63] lr: 1.8982e-03 eta: 10:47:26 time: 0.6542 data_time: 0.0059 memory: 14901 loss: 2.1518 loss_prob: 1.2626 loss_thr: 0.6822 loss_db: 0.2070 2022/11/02 13:52:45 - mmengine - INFO - Epoch(train) [163][50/63] lr: 1.8982e-03 eta: 10:47:22 time: 0.6296 data_time: 0.0210 memory: 14901 loss: 2.0008 loss_prob: 1.1634 loss_thr: 0.6469 loss_db: 0.1905 2022/11/02 13:52:48 - mmengine - INFO - Epoch(train) [163][55/63] lr: 1.8982e-03 eta: 10:47:22 time: 0.6350 data_time: 0.0209 memory: 14901 loss: 1.9595 loss_prob: 1.1271 loss_thr: 0.6467 loss_db: 0.1857 2022/11/02 13:52:51 - mmengine - INFO - Epoch(train) [163][60/63] lr: 1.8982e-03 eta: 10:47:22 time: 0.6830 data_time: 0.0048 memory: 14901 loss: 1.9706 loss_prob: 1.1478 loss_thr: 0.6331 loss_db: 0.1896 2022/11/02 13:52:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:52:58 - mmengine - INFO - Epoch(train) [164][5/63] lr: 1.8965e-03 eta: 10:47:22 time: 0.8463 data_time: 0.2397 memory: 14901 loss: 1.8499 loss_prob: 1.0565 loss_thr: 0.6166 loss_db: 0.1768 2022/11/02 13:53:01 - mmengine - INFO - Epoch(train) [164][10/63] lr: 1.8965e-03 eta: 10:47:15 time: 0.7964 data_time: 0.2401 memory: 14901 loss: 1.8778 loss_prob: 1.0741 loss_thr: 0.6283 loss_db: 0.1753 2022/11/02 13:53:04 - mmengine - INFO - Epoch(train) [164][15/63] lr: 1.8965e-03 eta: 10:47:15 time: 0.5582 data_time: 0.0069 memory: 14901 loss: 1.8605 loss_prob: 1.0819 loss_thr: 0.6033 loss_db: 0.1754 2022/11/02 13:53:07 - mmengine - INFO - Epoch(train) [164][20/63] lr: 1.8965e-03 eta: 10:47:10 time: 0.5953 data_time: 0.0067 memory: 14901 loss: 1.9705 loss_prob: 1.1764 loss_thr: 0.6058 loss_db: 0.1883 2022/11/02 13:53:09 - mmengine - INFO - Epoch(train) [164][25/63] lr: 1.8965e-03 eta: 10:47:10 time: 0.5244 data_time: 0.0119 memory: 14901 loss: 2.1162 loss_prob: 1.2754 loss_thr: 0.6373 loss_db: 0.2035 2022/11/02 13:53:12 - mmengine - INFO - Epoch(train) [164][30/63] lr: 1.8965e-03 eta: 10:46:58 time: 0.5093 data_time: 0.0443 memory: 14901 loss: 1.9389 loss_prob: 1.1394 loss_thr: 0.6127 loss_db: 0.1868 2022/11/02 13:53:14 - mmengine - INFO - Epoch(train) [164][35/63] lr: 1.8965e-03 eta: 10:46:58 time: 0.5143 data_time: 0.0371 memory: 14901 loss: 2.0509 loss_prob: 1.2177 loss_thr: 0.6350 loss_db: 0.1982 2022/11/02 13:53:17 - mmengine - INFO - Epoch(train) [164][40/63] lr: 1.8965e-03 eta: 10:46:45 time: 0.4865 data_time: 0.0045 memory: 14901 loss: 2.1884 loss_prob: 1.3085 loss_thr: 0.6664 loss_db: 0.2136 2022/11/02 13:53:19 - mmengine - INFO - Epoch(train) [164][45/63] lr: 1.8965e-03 eta: 10:46:45 time: 0.4867 data_time: 0.0046 memory: 14901 loss: 2.0725 loss_prob: 1.2219 loss_thr: 0.6470 loss_db: 0.2036 2022/11/02 13:53:21 - mmengine - INFO - Epoch(train) [164][50/63] lr: 1.8965e-03 eta: 10:46:32 time: 0.4836 data_time: 0.0198 memory: 14901 loss: 1.8663 loss_prob: 1.0854 loss_thr: 0.6012 loss_db: 0.1797 2022/11/02 13:53:24 - mmengine - INFO - Epoch(train) [164][55/63] lr: 1.8965e-03 eta: 10:46:32 time: 0.4745 data_time: 0.0210 memory: 14901 loss: 1.7859 loss_prob: 1.0335 loss_thr: 0.5844 loss_db: 0.1680 2022/11/02 13:53:26 - mmengine - INFO - Epoch(train) [164][60/63] lr: 1.8965e-03 eta: 10:46:19 time: 0.4742 data_time: 0.0061 memory: 14901 loss: 2.0426 loss_prob: 1.2047 loss_thr: 0.6451 loss_db: 0.1927 2022/11/02 13:53:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:53:32 - mmengine - INFO - Epoch(train) [165][5/63] lr: 1.8949e-03 eta: 10:46:19 time: 0.7071 data_time: 0.2223 memory: 14901 loss: 2.0553 loss_prob: 1.2124 loss_thr: 0.6416 loss_db: 0.2014 2022/11/02 13:53:35 - mmengine - INFO - Epoch(train) [165][10/63] lr: 1.8949e-03 eta: 10:46:07 time: 0.7067 data_time: 0.2270 memory: 14901 loss: 2.1420 loss_prob: 1.2943 loss_thr: 0.6343 loss_db: 0.2134 2022/11/02 13:53:37 - mmengine - INFO - Epoch(train) [165][15/63] lr: 1.8949e-03 eta: 10:46:07 time: 0.4815 data_time: 0.0093 memory: 14901 loss: 2.4237 loss_prob: 1.5017 loss_thr: 0.6825 loss_db: 0.2396 2022/11/02 13:53:40 - mmengine - INFO - Epoch(train) [165][20/63] lr: 1.8949e-03 eta: 10:45:55 time: 0.4936 data_time: 0.0049 memory: 14901 loss: 2.4205 loss_prob: 1.5089 loss_thr: 0.6696 loss_db: 0.2419 2022/11/02 13:53:43 - mmengine - INFO - Epoch(train) [165][25/63] lr: 1.8949e-03 eta: 10:45:55 time: 0.5416 data_time: 0.0304 memory: 14901 loss: 2.2844 loss_prob: 1.3971 loss_thr: 0.6566 loss_db: 0.2307 2022/11/02 13:53:45 - mmengine - INFO - Epoch(train) [165][30/63] lr: 1.8949e-03 eta: 10:45:45 time: 0.5276 data_time: 0.0316 memory: 14901 loss: 2.0823 loss_prob: 1.2457 loss_thr: 0.6336 loss_db: 0.2030 2022/11/02 13:53:47 - mmengine - INFO - Epoch(train) [165][35/63] lr: 1.8949e-03 eta: 10:45:45 time: 0.4735 data_time: 0.0084 memory: 14901 loss: 2.0178 loss_prob: 1.2026 loss_thr: 0.6203 loss_db: 0.1950 2022/11/02 13:53:50 - mmengine - INFO - Epoch(train) [165][40/63] lr: 1.8949e-03 eta: 10:45:32 time: 0.4860 data_time: 0.0072 memory: 14901 loss: 2.1877 loss_prob: 1.3041 loss_thr: 0.6712 loss_db: 0.2123 2022/11/02 13:53:52 - mmengine - INFO - Epoch(train) [165][45/63] lr: 1.8949e-03 eta: 10:45:32 time: 0.4976 data_time: 0.0047 memory: 14901 loss: 2.0820 loss_prob: 1.2102 loss_thr: 0.6736 loss_db: 0.1981 2022/11/02 13:53:55 - mmengine - INFO - Epoch(train) [165][50/63] lr: 1.8949e-03 eta: 10:45:21 time: 0.5114 data_time: 0.0185 memory: 14901 loss: 2.0462 loss_prob: 1.1916 loss_thr: 0.6568 loss_db: 0.1979 2022/11/02 13:53:57 - mmengine - INFO - Epoch(train) [165][55/63] lr: 1.8949e-03 eta: 10:45:21 time: 0.5107 data_time: 0.0227 memory: 14901 loss: 2.4320 loss_prob: 1.5033 loss_thr: 0.6770 loss_db: 0.2517 2022/11/02 13:54:00 - mmengine - INFO - Epoch(train) [165][60/63] lr: 1.8949e-03 eta: 10:45:08 time: 0.4839 data_time: 0.0091 memory: 14901 loss: 2.3696 loss_prob: 1.4741 loss_thr: 0.6515 loss_db: 0.2439 2022/11/02 13:54:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:54:06 - mmengine - INFO - Epoch(train) [166][5/63] lr: 1.8932e-03 eta: 10:45:08 time: 0.7288 data_time: 0.1796 memory: 14901 loss: 2.2025 loss_prob: 1.3413 loss_thr: 0.6447 loss_db: 0.2166 2022/11/02 13:54:08 - mmengine - INFO - Epoch(train) [166][10/63] lr: 1.8932e-03 eta: 10:44:58 time: 0.7386 data_time: 0.1842 memory: 14901 loss: 2.1990 loss_prob: 1.3375 loss_thr: 0.6424 loss_db: 0.2192 2022/11/02 13:54:11 - mmengine - INFO - Epoch(train) [166][15/63] lr: 1.8932e-03 eta: 10:44:58 time: 0.4994 data_time: 0.0135 memory: 14901 loss: 2.1497 loss_prob: 1.3122 loss_thr: 0.6231 loss_db: 0.2144 2022/11/02 13:54:14 - mmengine - INFO - Epoch(train) [166][20/63] lr: 1.8932e-03 eta: 10:44:47 time: 0.5115 data_time: 0.0120 memory: 14901 loss: 2.2358 loss_prob: 1.3613 loss_thr: 0.6498 loss_db: 0.2247 2022/11/02 13:54:16 - mmengine - INFO - Epoch(train) [166][25/63] lr: 1.8932e-03 eta: 10:44:47 time: 0.4964 data_time: 0.0210 memory: 14901 loss: 2.2906 loss_prob: 1.3941 loss_thr: 0.6595 loss_db: 0.2370 2022/11/02 13:54:19 - mmengine - INFO - Epoch(train) [166][30/63] lr: 1.8932e-03 eta: 10:44:38 time: 0.5367 data_time: 0.0265 memory: 14901 loss: 2.2495 loss_prob: 1.3719 loss_thr: 0.6486 loss_db: 0.2290 2022/11/02 13:54:22 - mmengine - INFO - Epoch(train) [166][35/63] lr: 1.8932e-03 eta: 10:44:38 time: 0.5554 data_time: 0.0146 memory: 14901 loss: 2.2549 loss_prob: 1.3722 loss_thr: 0.6595 loss_db: 0.2233 2022/11/02 13:54:24 - mmengine - INFO - Epoch(train) [166][40/63] lr: 1.8932e-03 eta: 10:44:28 time: 0.5292 data_time: 0.0124 memory: 14901 loss: 2.3096 loss_prob: 1.3965 loss_thr: 0.6826 loss_db: 0.2306 2022/11/02 13:54:27 - mmengine - INFO - Epoch(train) [166][45/63] lr: 1.8932e-03 eta: 10:44:28 time: 0.5016 data_time: 0.0111 memory: 14901 loss: 2.1292 loss_prob: 1.2592 loss_thr: 0.6643 loss_db: 0.2056 2022/11/02 13:54:29 - mmengine - INFO - Epoch(train) [166][50/63] lr: 1.8932e-03 eta: 10:44:15 time: 0.4902 data_time: 0.0101 memory: 14901 loss: 2.1017 loss_prob: 1.2412 loss_thr: 0.6593 loss_db: 0.2012 2022/11/02 13:54:32 - mmengine - INFO - Epoch(train) [166][55/63] lr: 1.8932e-03 eta: 10:44:15 time: 0.5132 data_time: 0.0189 memory: 14901 loss: 2.2612 loss_prob: 1.3580 loss_thr: 0.6870 loss_db: 0.2162 2022/11/02 13:54:34 - mmengine - INFO - Epoch(train) [166][60/63] lr: 1.8932e-03 eta: 10:44:05 time: 0.5264 data_time: 0.0172 memory: 14901 loss: 2.2019 loss_prob: 1.3142 loss_thr: 0.6709 loss_db: 0.2168 2022/11/02 13:54:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:54:42 - mmengine - INFO - Epoch(train) [167][5/63] lr: 1.8916e-03 eta: 10:44:05 time: 0.8426 data_time: 0.2112 memory: 14901 loss: 2.0043 loss_prob: 1.1908 loss_thr: 0.6187 loss_db: 0.1948 2022/11/02 13:54:44 - mmengine - INFO - Epoch(train) [167][10/63] lr: 1.8916e-03 eta: 10:44:05 time: 0.8863 data_time: 0.2077 memory: 14901 loss: 1.9585 loss_prob: 1.1328 loss_thr: 0.6407 loss_db: 0.1850 2022/11/02 13:54:48 - mmengine - INFO - Epoch(train) [167][15/63] lr: 1.8916e-03 eta: 10:44:05 time: 0.5873 data_time: 0.0049 memory: 14901 loss: 1.9892 loss_prob: 1.1723 loss_thr: 0.6251 loss_db: 0.1918 2022/11/02 13:54:50 - mmengine - INFO - Epoch(train) [167][20/63] lr: 1.8916e-03 eta: 10:43:59 time: 0.5918 data_time: 0.0054 memory: 14901 loss: 2.1755 loss_prob: 1.3336 loss_thr: 0.6234 loss_db: 0.2185 2022/11/02 13:54:53 - mmengine - INFO - Epoch(train) [167][25/63] lr: 1.8916e-03 eta: 10:43:59 time: 0.5340 data_time: 0.0148 memory: 14901 loss: 2.2829 loss_prob: 1.3967 loss_thr: 0.6542 loss_db: 0.2320 2022/11/02 13:54:56 - mmengine - INFO - Epoch(train) [167][30/63] lr: 1.8916e-03 eta: 10:43:50 time: 0.5518 data_time: 0.0335 memory: 14901 loss: 2.1082 loss_prob: 1.2585 loss_thr: 0.6440 loss_db: 0.2057 2022/11/02 13:54:59 - mmengine - INFO - Epoch(train) [167][35/63] lr: 1.8916e-03 eta: 10:43:50 time: 0.6045 data_time: 0.0247 memory: 14901 loss: 2.1479 loss_prob: 1.2696 loss_thr: 0.6738 loss_db: 0.2045 2022/11/02 13:55:02 - mmengine - INFO - Epoch(train) [167][40/63] lr: 1.8916e-03 eta: 10:43:42 time: 0.5600 data_time: 0.0054 memory: 14901 loss: 2.0628 loss_prob: 1.2066 loss_thr: 0.6570 loss_db: 0.1992 2022/11/02 13:55:05 - mmengine - INFO - Epoch(train) [167][45/63] lr: 1.8916e-03 eta: 10:43:42 time: 0.5476 data_time: 0.0047 memory: 14901 loss: 2.0263 loss_prob: 1.1958 loss_thr: 0.6305 loss_db: 0.2001 2022/11/02 13:55:08 - mmengine - INFO - Epoch(train) [167][50/63] lr: 1.8916e-03 eta: 10:43:37 time: 0.6045 data_time: 0.0148 memory: 14901 loss: 1.9327 loss_prob: 1.1366 loss_thr: 0.6103 loss_db: 0.1857 2022/11/02 13:55:11 - mmengine - INFO - Epoch(train) [167][55/63] lr: 1.8916e-03 eta: 10:43:37 time: 0.5931 data_time: 0.0258 memory: 14901 loss: 1.7923 loss_prob: 1.0275 loss_thr: 0.5980 loss_db: 0.1668 2022/11/02 13:55:14 - mmengine - INFO - Epoch(train) [167][60/63] lr: 1.8916e-03 eta: 10:43:32 time: 0.6033 data_time: 0.0205 memory: 14901 loss: 1.9025 loss_prob: 1.0787 loss_thr: 0.6454 loss_db: 0.1784 2022/11/02 13:55:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:55:20 - mmengine - INFO - Epoch(train) [168][5/63] lr: 1.8899e-03 eta: 10:43:32 time: 0.8295 data_time: 0.2390 memory: 14901 loss: 1.8721 loss_prob: 1.0813 loss_thr: 0.6145 loss_db: 0.1763 2022/11/02 13:55:24 - mmengine - INFO - Epoch(train) [168][10/63] lr: 1.8899e-03 eta: 10:43:32 time: 0.8991 data_time: 0.2421 memory: 14901 loss: 1.9586 loss_prob: 1.1605 loss_thr: 0.6049 loss_db: 0.1932 2022/11/02 13:55:27 - mmengine - INFO - Epoch(train) [168][15/63] lr: 1.8899e-03 eta: 10:43:32 time: 0.6337 data_time: 0.0079 memory: 14901 loss: 2.0099 loss_prob: 1.1903 loss_thr: 0.6237 loss_db: 0.1959 2022/11/02 13:55:29 - mmengine - INFO - Epoch(train) [168][20/63] lr: 1.8899e-03 eta: 10:43:24 time: 0.5631 data_time: 0.0049 memory: 14901 loss: 2.0203 loss_prob: 1.1819 loss_thr: 0.6480 loss_db: 0.1904 2022/11/02 13:55:32 - mmengine - INFO - Epoch(train) [168][25/63] lr: 1.8899e-03 eta: 10:43:24 time: 0.5651 data_time: 0.0283 memory: 14901 loss: 2.0737 loss_prob: 1.2165 loss_thr: 0.6547 loss_db: 0.2025 2022/11/02 13:55:35 - mmengine - INFO - Epoch(train) [168][30/63] lr: 1.8899e-03 eta: 10:43:16 time: 0.5573 data_time: 0.0286 memory: 14901 loss: 1.9544 loss_prob: 1.1452 loss_thr: 0.6203 loss_db: 0.1888 2022/11/02 13:55:38 - mmengine - INFO - Epoch(train) [168][35/63] lr: 1.8899e-03 eta: 10:43:16 time: 0.5337 data_time: 0.0091 memory: 14901 loss: 1.8836 loss_prob: 1.1020 loss_thr: 0.6032 loss_db: 0.1784 2022/11/02 13:55:41 - mmengine - INFO - Epoch(train) [168][40/63] lr: 1.8899e-03 eta: 10:43:07 time: 0.5497 data_time: 0.0091 memory: 14901 loss: 1.9455 loss_prob: 1.1322 loss_thr: 0.6298 loss_db: 0.1835 2022/11/02 13:55:43 - mmengine - INFO - Epoch(train) [168][45/63] lr: 1.8899e-03 eta: 10:43:07 time: 0.5438 data_time: 0.0049 memory: 14901 loss: 2.1859 loss_prob: 1.3033 loss_thr: 0.6765 loss_db: 0.2061 2022/11/02 13:55:46 - mmengine - INFO - Epoch(train) [168][50/63] lr: 1.8899e-03 eta: 10:42:59 time: 0.5625 data_time: 0.0176 memory: 14901 loss: 2.3491 loss_prob: 1.4266 loss_thr: 0.6925 loss_db: 0.2301 2022/11/02 13:55:49 - mmengine - INFO - Epoch(train) [168][55/63] lr: 1.8899e-03 eta: 10:42:59 time: 0.5676 data_time: 0.0186 memory: 14901 loss: 2.3872 loss_prob: 1.4915 loss_thr: 0.6605 loss_db: 0.2352 2022/11/02 13:55:51 - mmengine - INFO - Epoch(train) [168][60/63] lr: 1.8899e-03 eta: 10:42:48 time: 0.5066 data_time: 0.0090 memory: 14901 loss: 2.3807 loss_prob: 1.5082 loss_thr: 0.6400 loss_db: 0.2325 2022/11/02 13:55:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:55:58 - mmengine - INFO - Epoch(train) [169][5/63] lr: 1.8883e-03 eta: 10:42:48 time: 0.7218 data_time: 0.2168 memory: 14901 loss: 2.4048 loss_prob: 1.4745 loss_thr: 0.6836 loss_db: 0.2467 2022/11/02 13:56:00 - mmengine - INFO - Epoch(train) [169][10/63] lr: 1.8883e-03 eta: 10:42:38 time: 0.7346 data_time: 0.2169 memory: 14901 loss: 2.2236 loss_prob: 1.3562 loss_thr: 0.6463 loss_db: 0.2210 2022/11/02 13:56:02 - mmengine - INFO - Epoch(train) [169][15/63] lr: 1.8883e-03 eta: 10:42:38 time: 0.4865 data_time: 0.0057 memory: 14901 loss: 2.1512 loss_prob: 1.2981 loss_thr: 0.6457 loss_db: 0.2074 2022/11/02 13:56:05 - mmengine - INFO - Epoch(train) [169][20/63] lr: 1.8883e-03 eta: 10:42:25 time: 0.4795 data_time: 0.0051 memory: 14901 loss: 2.1061 loss_prob: 1.2516 loss_thr: 0.6470 loss_db: 0.2075 2022/11/02 13:56:07 - mmengine - INFO - Epoch(train) [169][25/63] lr: 1.8883e-03 eta: 10:42:25 time: 0.4978 data_time: 0.0083 memory: 14901 loss: 1.9916 loss_prob: 1.1730 loss_thr: 0.6274 loss_db: 0.1912 2022/11/02 13:56:10 - mmengine - INFO - Epoch(train) [169][30/63] lr: 1.8883e-03 eta: 10:42:16 time: 0.5363 data_time: 0.0310 memory: 14901 loss: 2.0322 loss_prob: 1.2111 loss_thr: 0.6276 loss_db: 0.1935 2022/11/02 13:56:12 - mmengine - INFO - Epoch(train) [169][35/63] lr: 1.8883e-03 eta: 10:42:16 time: 0.5084 data_time: 0.0308 memory: 14901 loss: 2.0118 loss_prob: 1.2094 loss_thr: 0.6067 loss_db: 0.1957 2022/11/02 13:56:15 - mmengine - INFO - Epoch(train) [169][40/63] lr: 1.8883e-03 eta: 10:42:03 time: 0.4828 data_time: 0.0078 memory: 14901 loss: 2.1146 loss_prob: 1.2783 loss_thr: 0.6273 loss_db: 0.2090 2022/11/02 13:56:18 - mmengine - INFO - Epoch(train) [169][45/63] lr: 1.8883e-03 eta: 10:42:03 time: 0.5084 data_time: 0.0045 memory: 14901 loss: 2.1568 loss_prob: 1.2858 loss_thr: 0.6575 loss_db: 0.2135 2022/11/02 13:56:20 - mmengine - INFO - Epoch(train) [169][50/63] lr: 1.8883e-03 eta: 10:41:55 time: 0.5603 data_time: 0.0134 memory: 14901 loss: 2.0821 loss_prob: 1.2203 loss_thr: 0.6589 loss_db: 0.2030 2022/11/02 13:56:24 - mmengine - INFO - Epoch(train) [169][55/63] lr: 1.8883e-03 eta: 10:41:55 time: 0.6010 data_time: 0.0210 memory: 14901 loss: 2.1672 loss_prob: 1.2852 loss_thr: 0.6727 loss_db: 0.2093 2022/11/02 13:56:26 - mmengine - INFO - Epoch(train) [169][60/63] lr: 1.8883e-03 eta: 10:41:48 time: 0.5774 data_time: 0.0133 memory: 14901 loss: 2.1081 loss_prob: 1.2534 loss_thr: 0.6523 loss_db: 0.2024 2022/11/02 13:56:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:56:32 - mmengine - INFO - Epoch(train) [170][5/63] lr: 1.8866e-03 eta: 10:41:48 time: 0.6639 data_time: 0.1959 memory: 14901 loss: 2.1628 loss_prob: 1.3069 loss_thr: 0.6439 loss_db: 0.2121 2022/11/02 13:56:35 - mmengine - INFO - Epoch(train) [170][10/63] lr: 1.8866e-03 eta: 10:41:38 time: 0.7272 data_time: 0.1969 memory: 14901 loss: 2.2356 loss_prob: 1.3707 loss_thr: 0.6397 loss_db: 0.2253 2022/11/02 13:56:38 - mmengine - INFO - Epoch(train) [170][15/63] lr: 1.8866e-03 eta: 10:41:38 time: 0.5635 data_time: 0.0078 memory: 14901 loss: 2.0194 loss_prob: 1.1961 loss_thr: 0.6252 loss_db: 0.1981 2022/11/02 13:56:40 - mmengine - INFO - Epoch(train) [170][20/63] lr: 1.8866e-03 eta: 10:41:29 time: 0.5358 data_time: 0.0091 memory: 14901 loss: 1.9782 loss_prob: 1.1507 loss_thr: 0.6424 loss_db: 0.1851 2022/11/02 13:56:42 - mmengine - INFO - Epoch(train) [170][25/63] lr: 1.8866e-03 eta: 10:41:29 time: 0.4991 data_time: 0.0107 memory: 14901 loss: 1.8839 loss_prob: 1.0867 loss_thr: 0.6218 loss_db: 0.1754 2022/11/02 13:56:45 - mmengine - INFO - Epoch(train) [170][30/63] lr: 1.8866e-03 eta: 10:41:19 time: 0.5275 data_time: 0.0482 memory: 14901 loss: 2.0015 loss_prob: 1.2027 loss_thr: 0.6059 loss_db: 0.1929 2022/11/02 13:56:48 - mmengine - INFO - Epoch(train) [170][35/63] lr: 1.8866e-03 eta: 10:41:19 time: 0.5062 data_time: 0.0442 memory: 14901 loss: 2.3461 loss_prob: 1.4585 loss_thr: 0.6535 loss_db: 0.2342 2022/11/02 13:56:50 - mmengine - INFO - Epoch(train) [170][40/63] lr: 1.8866e-03 eta: 10:41:07 time: 0.5036 data_time: 0.0060 memory: 14901 loss: 2.3400 loss_prob: 1.4223 loss_thr: 0.6872 loss_db: 0.2305 2022/11/02 13:56:53 - mmengine - INFO - Epoch(train) [170][45/63] lr: 1.8866e-03 eta: 10:41:07 time: 0.5356 data_time: 0.0102 memory: 14901 loss: 2.1347 loss_prob: 1.2625 loss_thr: 0.6646 loss_db: 0.2077 2022/11/02 13:56:55 - mmengine - INFO - Epoch(train) [170][50/63] lr: 1.8866e-03 eta: 10:40:57 time: 0.5244 data_time: 0.0257 memory: 14901 loss: 2.1158 loss_prob: 1.2384 loss_thr: 0.6705 loss_db: 0.2069 2022/11/02 13:56:58 - mmengine - INFO - Epoch(train) [170][55/63] lr: 1.8866e-03 eta: 10:40:57 time: 0.4991 data_time: 0.0223 memory: 14901 loss: 2.0970 loss_prob: 1.2266 loss_thr: 0.6663 loss_db: 0.2041 2022/11/02 13:57:01 - mmengine - INFO - Epoch(train) [170][60/63] lr: 1.8866e-03 eta: 10:40:47 time: 0.5196 data_time: 0.0067 memory: 14901 loss: 1.9720 loss_prob: 1.1703 loss_thr: 0.6108 loss_db: 0.1909 2022/11/02 13:57:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:57:07 - mmengine - INFO - Epoch(train) [171][5/63] lr: 1.8850e-03 eta: 10:40:47 time: 0.6879 data_time: 0.2132 memory: 14901 loss: 1.9456 loss_prob: 1.1313 loss_thr: 0.6315 loss_db: 0.1828 2022/11/02 13:57:09 - mmengine - INFO - Epoch(train) [171][10/63] lr: 1.8850e-03 eta: 10:40:35 time: 0.7046 data_time: 0.2122 memory: 14901 loss: 1.9231 loss_prob: 1.1088 loss_thr: 0.6359 loss_db: 0.1783 2022/11/02 13:57:12 - mmengine - INFO - Epoch(train) [171][15/63] lr: 1.8850e-03 eta: 10:40:35 time: 0.5023 data_time: 0.0048 memory: 14901 loss: 1.8376 loss_prob: 1.0674 loss_thr: 0.5953 loss_db: 0.1748 2022/11/02 13:57:14 - mmengine - INFO - Epoch(train) [171][20/63] lr: 1.8850e-03 eta: 10:40:23 time: 0.4939 data_time: 0.0052 memory: 14901 loss: 1.9466 loss_prob: 1.1619 loss_thr: 0.5938 loss_db: 0.1909 2022/11/02 13:57:17 - mmengine - INFO - Epoch(train) [171][25/63] lr: 1.8850e-03 eta: 10:40:23 time: 0.5186 data_time: 0.0151 memory: 14901 loss: 1.9097 loss_prob: 1.1243 loss_thr: 0.6056 loss_db: 0.1798 2022/11/02 13:57:19 - mmengine - INFO - Epoch(train) [171][30/63] lr: 1.8850e-03 eta: 10:40:15 time: 0.5549 data_time: 0.0414 memory: 14901 loss: 1.9150 loss_prob: 1.1116 loss_thr: 0.6254 loss_db: 0.1780 2022/11/02 13:57:22 - mmengine - INFO - Epoch(train) [171][35/63] lr: 1.8850e-03 eta: 10:40:15 time: 0.5740 data_time: 0.0398 memory: 14901 loss: 2.0190 loss_prob: 1.1670 loss_thr: 0.6600 loss_db: 0.1919 2022/11/02 13:57:26 - mmengine - INFO - Epoch(train) [171][40/63] lr: 1.8850e-03 eta: 10:40:11 time: 0.6161 data_time: 0.0152 memory: 14901 loss: 1.9327 loss_prob: 1.1186 loss_thr: 0.6286 loss_db: 0.1854 2022/11/02 13:57:29 - mmengine - INFO - Epoch(train) [171][45/63] lr: 1.8850e-03 eta: 10:40:11 time: 0.6781 data_time: 0.0081 memory: 14901 loss: 1.8782 loss_prob: 1.0943 loss_thr: 0.6038 loss_db: 0.1801 2022/11/02 13:57:32 - mmengine - INFO - Epoch(train) [171][50/63] lr: 1.8850e-03 eta: 10:40:07 time: 0.6341 data_time: 0.0166 memory: 14901 loss: 2.0502 loss_prob: 1.2183 loss_thr: 0.6339 loss_db: 0.1980 2022/11/02 13:57:34 - mmengine - INFO - Epoch(train) [171][55/63] lr: 1.8850e-03 eta: 10:40:07 time: 0.5186 data_time: 0.0202 memory: 14901 loss: 2.1588 loss_prob: 1.2883 loss_thr: 0.6622 loss_db: 0.2084 2022/11/02 13:57:37 - mmengine - INFO - Epoch(train) [171][60/63] lr: 1.8850e-03 eta: 10:39:55 time: 0.4811 data_time: 0.0114 memory: 14901 loss: 2.1122 loss_prob: 1.2524 loss_thr: 0.6558 loss_db: 0.2039 2022/11/02 13:57:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:57:43 - mmengine - INFO - Epoch(train) [172][5/63] lr: 1.8833e-03 eta: 10:39:55 time: 0.7428 data_time: 0.2428 memory: 14901 loss: 1.8907 loss_prob: 1.0661 loss_thr: 0.6483 loss_db: 0.1763 2022/11/02 13:57:46 - mmengine - INFO - Epoch(train) [172][10/63] lr: 1.8833e-03 eta: 10:39:48 time: 0.7796 data_time: 0.2424 memory: 14901 loss: 2.0542 loss_prob: 1.2094 loss_thr: 0.6525 loss_db: 0.1923 2022/11/02 13:57:49 - mmengine - INFO - Epoch(train) [172][15/63] lr: 1.8833e-03 eta: 10:39:48 time: 0.5310 data_time: 0.0061 memory: 14901 loss: 2.0034 loss_prob: 1.1787 loss_thr: 0.6361 loss_db: 0.1886 2022/11/02 13:57:51 - mmengine - INFO - Epoch(train) [172][20/63] lr: 1.8833e-03 eta: 10:39:37 time: 0.5074 data_time: 0.0051 memory: 14901 loss: 1.8690 loss_prob: 1.0703 loss_thr: 0.6238 loss_db: 0.1749 2022/11/02 13:57:54 - mmengine - INFO - Epoch(train) [172][25/63] lr: 1.8833e-03 eta: 10:39:37 time: 0.5234 data_time: 0.0346 memory: 14901 loss: 1.8518 loss_prob: 1.0567 loss_thr: 0.6237 loss_db: 0.1714 2022/11/02 13:57:56 - mmengine - INFO - Epoch(train) [172][30/63] lr: 1.8833e-03 eta: 10:39:27 time: 0.5285 data_time: 0.0378 memory: 14901 loss: 1.7704 loss_prob: 1.0037 loss_thr: 0.6004 loss_db: 0.1663 2022/11/02 13:57:59 - mmengine - INFO - Epoch(train) [172][35/63] lr: 1.8833e-03 eta: 10:39:27 time: 0.5059 data_time: 0.0080 memory: 14901 loss: 1.8467 loss_prob: 1.0691 loss_thr: 0.6003 loss_db: 0.1773 2022/11/02 13:58:02 - mmengine - INFO - Epoch(train) [172][40/63] lr: 1.8833e-03 eta: 10:39:21 time: 0.5976 data_time: 0.0056 memory: 14901 loss: 1.9426 loss_prob: 1.1390 loss_thr: 0.6191 loss_db: 0.1845 2022/11/02 13:58:06 - mmengine - INFO - Epoch(train) [172][45/63] lr: 1.8833e-03 eta: 10:39:21 time: 0.6849 data_time: 0.0084 memory: 14901 loss: 2.0374 loss_prob: 1.2170 loss_thr: 0.6240 loss_db: 0.1964 2022/11/02 13:58:09 - mmengine - INFO - Epoch(train) [172][50/63] lr: 1.8833e-03 eta: 10:39:21 time: 0.6794 data_time: 0.0257 memory: 14901 loss: 1.9657 loss_prob: 1.1751 loss_thr: 0.6023 loss_db: 0.1883 2022/11/02 13:58:12 - mmengine - INFO - Epoch(train) [172][55/63] lr: 1.8833e-03 eta: 10:39:21 time: 0.5988 data_time: 0.0245 memory: 14901 loss: 1.9301 loss_prob: 1.1560 loss_thr: 0.5866 loss_db: 0.1874 2022/11/02 13:58:14 - mmengine - INFO - Epoch(train) [172][60/63] lr: 1.8833e-03 eta: 10:39:09 time: 0.4999 data_time: 0.0061 memory: 14901 loss: 2.0891 loss_prob: 1.2643 loss_thr: 0.6175 loss_db: 0.2073 2022/11/02 13:58:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:58:20 - mmengine - INFO - Epoch(train) [173][5/63] lr: 1.8817e-03 eta: 10:39:09 time: 0.6624 data_time: 0.1990 memory: 14901 loss: 2.0672 loss_prob: 1.2181 loss_thr: 0.6423 loss_db: 0.2068 2022/11/02 13:58:22 - mmengine - INFO - Epoch(train) [173][10/63] lr: 1.8817e-03 eta: 10:38:58 time: 0.7098 data_time: 0.2030 memory: 14901 loss: 2.2057 loss_prob: 1.3278 loss_thr: 0.6607 loss_db: 0.2172 2022/11/02 13:58:25 - mmengine - INFO - Epoch(train) [173][15/63] lr: 1.8817e-03 eta: 10:38:58 time: 0.4898 data_time: 0.0086 memory: 14901 loss: 2.0761 loss_prob: 1.2215 loss_thr: 0.6545 loss_db: 0.2001 2022/11/02 13:58:27 - mmengine - INFO - Epoch(train) [173][20/63] lr: 1.8817e-03 eta: 10:38:44 time: 0.4621 data_time: 0.0057 memory: 14901 loss: 2.0282 loss_prob: 1.1898 loss_thr: 0.6459 loss_db: 0.1926 2022/11/02 13:58:29 - mmengine - INFO - Epoch(train) [173][25/63] lr: 1.8817e-03 eta: 10:38:44 time: 0.4727 data_time: 0.0072 memory: 14901 loss: 2.1118 loss_prob: 1.2661 loss_thr: 0.6405 loss_db: 0.2052 2022/11/02 13:58:32 - mmengine - INFO - Epoch(train) [173][30/63] lr: 1.8817e-03 eta: 10:38:33 time: 0.4979 data_time: 0.0283 memory: 14901 loss: 2.0781 loss_prob: 1.2460 loss_thr: 0.6336 loss_db: 0.1985 2022/11/02 13:58:34 - mmengine - INFO - Epoch(train) [173][35/63] lr: 1.8817e-03 eta: 10:38:33 time: 0.5128 data_time: 0.0325 memory: 14901 loss: 2.0432 loss_prob: 1.2056 loss_thr: 0.6445 loss_db: 0.1932 2022/11/02 13:58:37 - mmengine - INFO - Epoch(train) [173][40/63] lr: 1.8817e-03 eta: 10:38:21 time: 0.4884 data_time: 0.0104 memory: 14901 loss: 2.1407 loss_prob: 1.2620 loss_thr: 0.6713 loss_db: 0.2073 2022/11/02 13:58:39 - mmengine - INFO - Epoch(train) [173][45/63] lr: 1.8817e-03 eta: 10:38:21 time: 0.4906 data_time: 0.0058 memory: 14901 loss: 2.1851 loss_prob: 1.3103 loss_thr: 0.6617 loss_db: 0.2131 2022/11/02 13:58:42 - mmengine - INFO - Epoch(train) [173][50/63] lr: 1.8817e-03 eta: 10:38:11 time: 0.5246 data_time: 0.0144 memory: 14901 loss: 2.0021 loss_prob: 1.1852 loss_thr: 0.6238 loss_db: 0.1931 2022/11/02 13:58:45 - mmengine - INFO - Epoch(train) [173][55/63] lr: 1.8817e-03 eta: 10:38:11 time: 0.5212 data_time: 0.0190 memory: 14901 loss: 1.9740 loss_prob: 1.1442 loss_thr: 0.6437 loss_db: 0.1860 2022/11/02 13:58:47 - mmengine - INFO - Epoch(train) [173][60/63] lr: 1.8817e-03 eta: 10:37:59 time: 0.4926 data_time: 0.0122 memory: 14901 loss: 1.9568 loss_prob: 1.1291 loss_thr: 0.6399 loss_db: 0.1879 2022/11/02 13:58:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:58:53 - mmengine - INFO - Epoch(train) [174][5/63] lr: 1.8800e-03 eta: 10:37:59 time: 0.7376 data_time: 0.1712 memory: 14901 loss: 2.0834 loss_prob: 1.2319 loss_thr: 0.6489 loss_db: 0.2026 2022/11/02 13:58:56 - mmengine - INFO - Epoch(train) [174][10/63] lr: 1.8800e-03 eta: 10:37:50 time: 0.7524 data_time: 0.1714 memory: 14901 loss: 2.0804 loss_prob: 1.2301 loss_thr: 0.6466 loss_db: 0.2037 2022/11/02 13:58:58 - mmengine - INFO - Epoch(train) [174][15/63] lr: 1.8800e-03 eta: 10:37:50 time: 0.4834 data_time: 0.0090 memory: 14901 loss: 1.8989 loss_prob: 1.1006 loss_thr: 0.6178 loss_db: 0.1805 2022/11/02 13:59:01 - mmengine - INFO - Epoch(train) [174][20/63] lr: 1.8800e-03 eta: 10:37:38 time: 0.4893 data_time: 0.0100 memory: 14901 loss: 1.9489 loss_prob: 1.1383 loss_thr: 0.6246 loss_db: 0.1860 2022/11/02 13:59:03 - mmengine - INFO - Epoch(train) [174][25/63] lr: 1.8800e-03 eta: 10:37:38 time: 0.5134 data_time: 0.0080 memory: 14901 loss: 1.9737 loss_prob: 1.1623 loss_thr: 0.6216 loss_db: 0.1899 2022/11/02 13:59:06 - mmengine - INFO - Epoch(train) [174][30/63] lr: 1.8800e-03 eta: 10:37:28 time: 0.5240 data_time: 0.0311 memory: 14901 loss: 1.9236 loss_prob: 1.1298 loss_thr: 0.6107 loss_db: 0.1831 2022/11/02 13:59:08 - mmengine - INFO - Epoch(train) [174][35/63] lr: 1.8800e-03 eta: 10:37:28 time: 0.4910 data_time: 0.0309 memory: 14901 loss: 1.9345 loss_prob: 1.1247 loss_thr: 0.6259 loss_db: 0.1838 2022/11/02 13:59:10 - mmengine - INFO - Epoch(train) [174][40/63] lr: 1.8800e-03 eta: 10:37:14 time: 0.4501 data_time: 0.0065 memory: 14901 loss: 1.9299 loss_prob: 1.1170 loss_thr: 0.6301 loss_db: 0.1827 2022/11/02 13:59:13 - mmengine - INFO - Epoch(train) [174][45/63] lr: 1.8800e-03 eta: 10:37:14 time: 0.4810 data_time: 0.0060 memory: 14901 loss: 2.0201 loss_prob: 1.1902 loss_thr: 0.6377 loss_db: 0.1921 2022/11/02 13:59:15 - mmengine - INFO - Epoch(train) [174][50/63] lr: 1.8800e-03 eta: 10:37:03 time: 0.4983 data_time: 0.0110 memory: 14901 loss: 2.0316 loss_prob: 1.1938 loss_thr: 0.6453 loss_db: 0.1925 2022/11/02 13:59:19 - mmengine - INFO - Epoch(train) [174][55/63] lr: 1.8800e-03 eta: 10:37:03 time: 0.5834 data_time: 0.0217 memory: 14901 loss: 1.9703 loss_prob: 1.1255 loss_thr: 0.6601 loss_db: 0.1846 2022/11/02 13:59:22 - mmengine - INFO - Epoch(train) [174][60/63] lr: 1.8800e-03 eta: 10:36:59 time: 0.6319 data_time: 0.0197 memory: 14901 loss: 1.9940 loss_prob: 1.1488 loss_thr: 0.6565 loss_db: 0.1887 2022/11/02 13:59:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:59:28 - mmengine - INFO - Epoch(train) [175][5/63] lr: 1.8784e-03 eta: 10:36:59 time: 0.7369 data_time: 0.2386 memory: 14901 loss: 2.1222 loss_prob: 1.2656 loss_thr: 0.6484 loss_db: 0.2082 2022/11/02 13:59:30 - mmengine - INFO - Epoch(train) [175][10/63] lr: 1.8784e-03 eta: 10:36:50 time: 0.7469 data_time: 0.2358 memory: 14901 loss: 2.0102 loss_prob: 1.1817 loss_thr: 0.6356 loss_db: 0.1929 2022/11/02 13:59:33 - mmengine - INFO - Epoch(train) [175][15/63] lr: 1.8784e-03 eta: 10:36:50 time: 0.4996 data_time: 0.0049 memory: 14901 loss: 1.9657 loss_prob: 1.1244 loss_thr: 0.6569 loss_db: 0.1843 2022/11/02 13:59:35 - mmengine - INFO - Epoch(train) [175][20/63] lr: 1.8784e-03 eta: 10:36:37 time: 0.4741 data_time: 0.0056 memory: 14901 loss: 2.0181 loss_prob: 1.1720 loss_thr: 0.6565 loss_db: 0.1895 2022/11/02 13:59:38 - mmengine - INFO - Epoch(train) [175][25/63] lr: 1.8784e-03 eta: 10:36:37 time: 0.4921 data_time: 0.0094 memory: 14901 loss: 1.9135 loss_prob: 1.1126 loss_thr: 0.6202 loss_db: 0.1807 2022/11/02 13:59:40 - mmengine - INFO - Epoch(train) [175][30/63] lr: 1.8784e-03 eta: 10:36:26 time: 0.5056 data_time: 0.0198 memory: 14901 loss: 1.8168 loss_prob: 1.0310 loss_thr: 0.6165 loss_db: 0.1692 2022/11/02 13:59:43 - mmengine - INFO - Epoch(train) [175][35/63] lr: 1.8784e-03 eta: 10:36:26 time: 0.5113 data_time: 0.0178 memory: 14901 loss: 1.9139 loss_prob: 1.0981 loss_thr: 0.6315 loss_db: 0.1843 2022/11/02 13:59:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 13:59:45 - mmengine - INFO - Epoch(train) [175][40/63] lr: 1.8784e-03 eta: 10:36:15 time: 0.4933 data_time: 0.0065 memory: 14901 loss: 1.9473 loss_prob: 1.1182 loss_thr: 0.6391 loss_db: 0.1900 2022/11/02 13:59:48 - mmengine - INFO - Epoch(train) [175][45/63] lr: 1.8784e-03 eta: 10:36:15 time: 0.5109 data_time: 0.0053 memory: 14901 loss: 1.9063 loss_prob: 1.0777 loss_thr: 0.6483 loss_db: 0.1804 2022/11/02 13:59:51 - mmengine - INFO - Epoch(train) [175][50/63] lr: 1.8784e-03 eta: 10:36:11 time: 0.6206 data_time: 0.0170 memory: 14901 loss: 1.9547 loss_prob: 1.1395 loss_thr: 0.6263 loss_db: 0.1889 2022/11/02 13:59:55 - mmengine - INFO - Epoch(train) [175][55/63] lr: 1.8784e-03 eta: 10:36:11 time: 0.7147 data_time: 0.0216 memory: 14901 loss: 2.0369 loss_prob: 1.2318 loss_thr: 0.6006 loss_db: 0.2045 2022/11/02 13:59:58 - mmengine - INFO - Epoch(train) [175][60/63] lr: 1.8784e-03 eta: 10:36:09 time: 0.6656 data_time: 0.0106 memory: 14901 loss: 2.0666 loss_prob: 1.2305 loss_thr: 0.6341 loss_db: 0.2020 2022/11/02 13:59:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:00:06 - mmengine - INFO - Epoch(train) [176][5/63] lr: 1.8767e-03 eta: 10:36:09 time: 0.8820 data_time: 0.2264 memory: 14901 loss: 2.0231 loss_prob: 1.2036 loss_thr: 0.6257 loss_db: 0.1938 2022/11/02 14:00:09 - mmengine - INFO - Epoch(train) [176][10/63] lr: 1.8767e-03 eta: 10:36:13 time: 0.9687 data_time: 0.2350 memory: 14901 loss: 2.0662 loss_prob: 1.2222 loss_thr: 0.6425 loss_db: 0.2015 2022/11/02 14:00:11 - mmengine - INFO - Epoch(train) [176][15/63] lr: 1.8767e-03 eta: 10:36:13 time: 0.5316 data_time: 0.0131 memory: 14901 loss: 2.1580 loss_prob: 1.2945 loss_thr: 0.6489 loss_db: 0.2146 2022/11/02 14:00:15 - mmengine - INFO - Epoch(train) [176][20/63] lr: 1.8767e-03 eta: 10:36:08 time: 0.5992 data_time: 0.0056 memory: 14901 loss: 2.2930 loss_prob: 1.4129 loss_thr: 0.6461 loss_db: 0.2339 2022/11/02 14:00:18 - mmengine - INFO - Epoch(train) [176][25/63] lr: 1.8767e-03 eta: 10:36:08 time: 0.6766 data_time: 0.0218 memory: 14901 loss: 2.2478 loss_prob: 1.3798 loss_thr: 0.6411 loss_db: 0.2269 2022/11/02 14:00:22 - mmengine - INFO - Epoch(train) [176][30/63] lr: 1.8767e-03 eta: 10:36:08 time: 0.7057 data_time: 0.0223 memory: 14901 loss: 2.1529 loss_prob: 1.2971 loss_thr: 0.6421 loss_db: 0.2138 2022/11/02 14:00:25 - mmengine - INFO - Epoch(train) [176][35/63] lr: 1.8767e-03 eta: 10:36:08 time: 0.7335 data_time: 0.0156 memory: 14901 loss: 2.2487 loss_prob: 1.3639 loss_thr: 0.6534 loss_db: 0.2314 2022/11/02 14:00:28 - mmengine - INFO - Epoch(train) [176][40/63] lr: 1.8767e-03 eta: 10:36:03 time: 0.6070 data_time: 0.0136 memory: 14901 loss: 2.2937 loss_prob: 1.3938 loss_thr: 0.6661 loss_db: 0.2339 2022/11/02 14:00:31 - mmengine - INFO - Epoch(train) [176][45/63] lr: 1.8767e-03 eta: 10:36:03 time: 0.5426 data_time: 0.0040 memory: 14901 loss: 2.2569 loss_prob: 1.3641 loss_thr: 0.6742 loss_db: 0.2187 2022/11/02 14:00:33 - mmengine - INFO - Epoch(train) [176][50/63] lr: 1.8767e-03 eta: 10:35:54 time: 0.5274 data_time: 0.0177 memory: 14901 loss: 2.1854 loss_prob: 1.3196 loss_thr: 0.6576 loss_db: 0.2082 2022/11/02 14:00:36 - mmengine - INFO - Epoch(train) [176][55/63] lr: 1.8767e-03 eta: 10:35:54 time: 0.5705 data_time: 0.0260 memory: 14901 loss: 1.9956 loss_prob: 1.1679 loss_thr: 0.6386 loss_db: 0.1890 2022/11/02 14:00:40 - mmengine - INFO - Epoch(train) [176][60/63] lr: 1.8767e-03 eta: 10:35:53 time: 0.6766 data_time: 0.0131 memory: 14901 loss: 1.9383 loss_prob: 1.1190 loss_thr: 0.6381 loss_db: 0.1812 2022/11/02 14:00:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:00:47 - mmengine - INFO - Epoch(train) [177][5/63] lr: 1.8751e-03 eta: 10:35:53 time: 0.8368 data_time: 0.2440 memory: 14901 loss: 2.2151 loss_prob: 1.3237 loss_thr: 0.6658 loss_db: 0.2256 2022/11/02 14:00:50 - mmengine - INFO - Epoch(train) [177][10/63] lr: 1.8751e-03 eta: 10:35:46 time: 0.7856 data_time: 0.2436 memory: 14901 loss: 2.4683 loss_prob: 1.5179 loss_thr: 0.6867 loss_db: 0.2637 2022/11/02 14:00:52 - mmengine - INFO - Epoch(train) [177][15/63] lr: 1.8751e-03 eta: 10:35:46 time: 0.4906 data_time: 0.0053 memory: 14901 loss: 2.4458 loss_prob: 1.5118 loss_thr: 0.6803 loss_db: 0.2536 2022/11/02 14:00:55 - mmengine - INFO - Epoch(train) [177][20/63] lr: 1.8751e-03 eta: 10:35:33 time: 0.4730 data_time: 0.0057 memory: 14901 loss: 2.2890 loss_prob: 1.3885 loss_thr: 0.6785 loss_db: 0.2220 2022/11/02 14:00:57 - mmengine - INFO - Epoch(train) [177][25/63] lr: 1.8751e-03 eta: 10:35:33 time: 0.4827 data_time: 0.0178 memory: 14901 loss: 2.1912 loss_prob: 1.3052 loss_thr: 0.6764 loss_db: 0.2096 2022/11/02 14:01:00 - mmengine - INFO - Epoch(train) [177][30/63] lr: 1.8751e-03 eta: 10:35:23 time: 0.5105 data_time: 0.0330 memory: 14901 loss: 2.0845 loss_prob: 1.2253 loss_thr: 0.6612 loss_db: 0.1979 2022/11/02 14:01:02 - mmengine - INFO - Epoch(train) [177][35/63] lr: 1.8751e-03 eta: 10:35:23 time: 0.4938 data_time: 0.0202 memory: 14901 loss: 2.1328 loss_prob: 1.2493 loss_thr: 0.6760 loss_db: 0.2075 2022/11/02 14:01:04 - mmengine - INFO - Epoch(train) [177][40/63] lr: 1.8751e-03 eta: 10:35:10 time: 0.4763 data_time: 0.0043 memory: 14901 loss: 2.0121 loss_prob: 1.1527 loss_thr: 0.6666 loss_db: 0.1928 2022/11/02 14:01:07 - mmengine - INFO - Epoch(train) [177][45/63] lr: 1.8751e-03 eta: 10:35:10 time: 0.4817 data_time: 0.0059 memory: 14901 loss: 1.8866 loss_prob: 1.0897 loss_thr: 0.6198 loss_db: 0.1771 2022/11/02 14:01:10 - mmengine - INFO - Epoch(train) [177][50/63] lr: 1.8751e-03 eta: 10:35:00 time: 0.5248 data_time: 0.0186 memory: 14901 loss: 1.9348 loss_prob: 1.1524 loss_thr: 0.5974 loss_db: 0.1850 2022/11/02 14:01:12 - mmengine - INFO - Epoch(train) [177][55/63] lr: 1.8751e-03 eta: 10:35:00 time: 0.5279 data_time: 0.0204 memory: 14901 loss: 1.9803 loss_prob: 1.1814 loss_thr: 0.6061 loss_db: 0.1928 2022/11/02 14:01:14 - mmengine - INFO - Epoch(train) [177][60/63] lr: 1.8751e-03 eta: 10:34:48 time: 0.4783 data_time: 0.0076 memory: 14901 loss: 1.8127 loss_prob: 1.0629 loss_thr: 0.5745 loss_db: 0.1752 2022/11/02 14:01:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:01:22 - mmengine - INFO - Epoch(train) [178][5/63] lr: 1.8734e-03 eta: 10:34:48 time: 0.8230 data_time: 0.3589 memory: 14901 loss: 2.1930 loss_prob: 1.3341 loss_thr: 0.6473 loss_db: 0.2116 2022/11/02 14:01:24 - mmengine - INFO - Epoch(train) [178][10/63] lr: 1.8734e-03 eta: 10:34:47 time: 0.8849 data_time: 0.3584 memory: 14901 loss: 2.2898 loss_prob: 1.4079 loss_thr: 0.6588 loss_db: 0.2231 2022/11/02 14:01:27 - mmengine - INFO - Epoch(train) [178][15/63] lr: 1.8734e-03 eta: 10:34:47 time: 0.5102 data_time: 0.0047 memory: 14901 loss: 1.9464 loss_prob: 1.1399 loss_thr: 0.6179 loss_db: 0.1887 2022/11/02 14:01:29 - mmengine - INFO - Epoch(train) [178][20/63] lr: 1.8734e-03 eta: 10:34:35 time: 0.4919 data_time: 0.0051 memory: 14901 loss: 1.9708 loss_prob: 1.1486 loss_thr: 0.6329 loss_db: 0.1893 2022/11/02 14:01:32 - mmengine - INFO - Epoch(train) [178][25/63] lr: 1.8734e-03 eta: 10:34:35 time: 0.5342 data_time: 0.0223 memory: 14901 loss: 2.0849 loss_prob: 1.2390 loss_thr: 0.6453 loss_db: 0.2006 2022/11/02 14:01:35 - mmengine - INFO - Epoch(train) [178][30/63] lr: 1.8734e-03 eta: 10:34:25 time: 0.5139 data_time: 0.0220 memory: 14901 loss: 2.1417 loss_prob: 1.2683 loss_thr: 0.6671 loss_db: 0.2063 2022/11/02 14:01:37 - mmengine - INFO - Epoch(train) [178][35/63] lr: 1.8734e-03 eta: 10:34:25 time: 0.4831 data_time: 0.0043 memory: 14901 loss: 2.0843 loss_prob: 1.2202 loss_thr: 0.6618 loss_db: 0.2023 2022/11/02 14:01:39 - mmengine - INFO - Epoch(train) [178][40/63] lr: 1.8734e-03 eta: 10:34:13 time: 0.4821 data_time: 0.0045 memory: 14901 loss: 1.9786 loss_prob: 1.1669 loss_thr: 0.6197 loss_db: 0.1919 2022/11/02 14:01:42 - mmengine - INFO - Epoch(train) [178][45/63] lr: 1.8734e-03 eta: 10:34:13 time: 0.4988 data_time: 0.0044 memory: 14901 loss: 2.0262 loss_prob: 1.1931 loss_thr: 0.6376 loss_db: 0.1955 2022/11/02 14:01:45 - mmengine - INFO - Epoch(train) [178][50/63] lr: 1.8734e-03 eta: 10:34:03 time: 0.5278 data_time: 0.0232 memory: 14901 loss: 2.0084 loss_prob: 1.1734 loss_thr: 0.6405 loss_db: 0.1945 2022/11/02 14:01:47 - mmengine - INFO - Epoch(train) [178][55/63] lr: 1.8734e-03 eta: 10:34:03 time: 0.5055 data_time: 0.0233 memory: 14901 loss: 1.9554 loss_prob: 1.1349 loss_thr: 0.6350 loss_db: 0.1855 2022/11/02 14:01:49 - mmengine - INFO - Epoch(train) [178][60/63] lr: 1.8734e-03 eta: 10:33:51 time: 0.4757 data_time: 0.0065 memory: 14901 loss: 1.9292 loss_prob: 1.1136 loss_thr: 0.6327 loss_db: 0.1829 2022/11/02 14:01:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:01:56 - mmengine - INFO - Epoch(train) [179][5/63] lr: 1.8718e-03 eta: 10:33:51 time: 0.7446 data_time: 0.2171 memory: 14901 loss: 2.1118 loss_prob: 1.2608 loss_thr: 0.6448 loss_db: 0.2063 2022/11/02 14:01:58 - mmengine - INFO - Epoch(train) [179][10/63] lr: 1.8718e-03 eta: 10:33:43 time: 0.7631 data_time: 0.2216 memory: 14901 loss: 2.1789 loss_prob: 1.3276 loss_thr: 0.6383 loss_db: 0.2130 2022/11/02 14:02:01 - mmengine - INFO - Epoch(train) [179][15/63] lr: 1.8718e-03 eta: 10:33:43 time: 0.5077 data_time: 0.0106 memory: 14901 loss: 2.0934 loss_prob: 1.2585 loss_thr: 0.6294 loss_db: 0.2055 2022/11/02 14:02:04 - mmengine - INFO - Epoch(train) [179][20/63] lr: 1.8718e-03 eta: 10:33:33 time: 0.5286 data_time: 0.0059 memory: 14901 loss: 2.1727 loss_prob: 1.3175 loss_thr: 0.6414 loss_db: 0.2138 2022/11/02 14:02:06 - mmengine - INFO - Epoch(train) [179][25/63] lr: 1.8718e-03 eta: 10:33:33 time: 0.4936 data_time: 0.0075 memory: 14901 loss: 2.2475 loss_prob: 1.3893 loss_thr: 0.6324 loss_db: 0.2258 2022/11/02 14:02:09 - mmengine - INFO - Epoch(train) [179][30/63] lr: 1.8718e-03 eta: 10:33:23 time: 0.5067 data_time: 0.0499 memory: 14901 loss: 2.2508 loss_prob: 1.3921 loss_thr: 0.6272 loss_db: 0.2314 2022/11/02 14:02:12 - mmengine - INFO - Epoch(train) [179][35/63] lr: 1.8718e-03 eta: 10:33:23 time: 0.5635 data_time: 0.0523 memory: 14901 loss: 2.1996 loss_prob: 1.3356 loss_thr: 0.6423 loss_db: 0.2218 2022/11/02 14:02:14 - mmengine - INFO - Epoch(train) [179][40/63] lr: 1.8718e-03 eta: 10:33:13 time: 0.5269 data_time: 0.0110 memory: 14901 loss: 2.0943 loss_prob: 1.2518 loss_thr: 0.6331 loss_db: 0.2095 2022/11/02 14:02:16 - mmengine - INFO - Epoch(train) [179][45/63] lr: 1.8718e-03 eta: 10:33:13 time: 0.4782 data_time: 0.0057 memory: 14901 loss: 2.1933 loss_prob: 1.3317 loss_thr: 0.6444 loss_db: 0.2172 2022/11/02 14:02:19 - mmengine - INFO - Epoch(train) [179][50/63] lr: 1.8718e-03 eta: 10:33:02 time: 0.5025 data_time: 0.0134 memory: 14901 loss: 2.3058 loss_prob: 1.3926 loss_thr: 0.6849 loss_db: 0.2283 2022/11/02 14:02:22 - mmengine - INFO - Epoch(train) [179][55/63] lr: 1.8718e-03 eta: 10:33:02 time: 0.5416 data_time: 0.0252 memory: 14901 loss: 2.1795 loss_prob: 1.2899 loss_thr: 0.6747 loss_db: 0.2149 2022/11/02 14:02:24 - mmengine - INFO - Epoch(train) [179][60/63] lr: 1.8718e-03 eta: 10:32:53 time: 0.5281 data_time: 0.0186 memory: 14901 loss: 2.0120 loss_prob: 1.1779 loss_thr: 0.6449 loss_db: 0.1893 2022/11/02 14:02:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:02:32 - mmengine - INFO - Epoch(train) [180][5/63] lr: 1.8701e-03 eta: 10:32:53 time: 0.8456 data_time: 0.2099 memory: 14901 loss: 2.1740 loss_prob: 1.3051 loss_thr: 0.6608 loss_db: 0.2080 2022/11/02 14:02:36 - mmengine - INFO - Epoch(train) [180][10/63] lr: 1.8701e-03 eta: 10:32:58 time: 0.9910 data_time: 0.2226 memory: 14901 loss: 2.0051 loss_prob: 1.1861 loss_thr: 0.6270 loss_db: 0.1919 2022/11/02 14:02:38 - mmengine - INFO - Epoch(train) [180][15/63] lr: 1.8701e-03 eta: 10:32:58 time: 0.6404 data_time: 0.0177 memory: 14901 loss: 1.9834 loss_prob: 1.1520 loss_thr: 0.6396 loss_db: 0.1917 2022/11/02 14:02:41 - mmengine - INFO - Epoch(train) [180][20/63] lr: 1.8701e-03 eta: 10:32:48 time: 0.5150 data_time: 0.0062 memory: 14901 loss: 2.0285 loss_prob: 1.1775 loss_thr: 0.6559 loss_db: 0.1951 2022/11/02 14:02:45 - mmengine - INFO - Epoch(train) [180][25/63] lr: 1.8701e-03 eta: 10:32:48 time: 0.7200 data_time: 0.0381 memory: 14901 loss: 2.0956 loss_prob: 1.2444 loss_thr: 0.6481 loss_db: 0.2031 2022/11/02 14:02:48 - mmengine - INFO - Epoch(train) [180][30/63] lr: 1.8701e-03 eta: 10:32:51 time: 0.7538 data_time: 0.0415 memory: 14901 loss: 2.0442 loss_prob: 1.2211 loss_thr: 0.6208 loss_db: 0.2023 2022/11/02 14:02:52 - mmengine - INFO - Epoch(train) [180][35/63] lr: 1.8701e-03 eta: 10:32:51 time: 0.6190 data_time: 0.0114 memory: 14901 loss: 1.9852 loss_prob: 1.1662 loss_thr: 0.6249 loss_db: 0.1942 2022/11/02 14:02:55 - mmengine - INFO - Epoch(train) [180][40/63] lr: 1.8701e-03 eta: 10:32:47 time: 0.6301 data_time: 0.0064 memory: 14901 loss: 1.9510 loss_prob: 1.1291 loss_thr: 0.6376 loss_db: 0.1843 2022/11/02 14:02:58 - mmengine - INFO - Epoch(train) [180][45/63] lr: 1.8701e-03 eta: 10:32:47 time: 0.6112 data_time: 0.0062 memory: 14901 loss: 1.8816 loss_prob: 1.0898 loss_thr: 0.6130 loss_db: 0.1788 2022/11/02 14:03:02 - mmengine - INFO - Epoch(train) [180][50/63] lr: 1.8701e-03 eta: 10:32:49 time: 0.7252 data_time: 0.0272 memory: 14901 loss: 1.7627 loss_prob: 1.0116 loss_thr: 0.5854 loss_db: 0.1657 2022/11/02 14:03:04 - mmengine - INFO - Epoch(train) [180][55/63] lr: 1.8701e-03 eta: 10:32:49 time: 0.6777 data_time: 0.0314 memory: 14901 loss: 1.7588 loss_prob: 1.0100 loss_thr: 0.5835 loss_db: 0.1654 2022/11/02 14:03:08 - mmengine - INFO - Epoch(train) [180][60/63] lr: 1.8701e-03 eta: 10:32:43 time: 0.5792 data_time: 0.0115 memory: 14901 loss: 1.8543 loss_prob: 1.0738 loss_thr: 0.6035 loss_db: 0.1769 2022/11/02 14:03:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:03:09 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/11/02 14:03:13 - mmengine - INFO - Epoch(val) [180][5/500] eta: 10:32:43 time: 0.0459 data_time: 0.0050 memory: 14901 2022/11/02 14:03:13 - mmengine - INFO - Epoch(val) [180][10/500] eta: 0:00:25 time: 0.0510 data_time: 0.0058 memory: 1008 2022/11/02 14:03:13 - mmengine - INFO - Epoch(val) [180][15/500] eta: 0:00:25 time: 0.0471 data_time: 0.0038 memory: 1008 2022/11/02 14:03:13 - mmengine - INFO - Epoch(val) [180][20/500] eta: 0:00:23 time: 0.0483 data_time: 0.0038 memory: 1008 2022/11/02 14:03:14 - mmengine - INFO - Epoch(val) [180][25/500] eta: 0:00:23 time: 0.0473 data_time: 0.0041 memory: 1008 2022/11/02 14:03:14 - mmengine - INFO - Epoch(val) [180][30/500] eta: 0:00:23 time: 0.0491 data_time: 0.0038 memory: 1008 2022/11/02 14:03:14 - mmengine - INFO - Epoch(val) [180][35/500] eta: 0:00:23 time: 0.0466 data_time: 0.0033 memory: 1008 2022/11/02 14:03:14 - mmengine - INFO - Epoch(val) [180][40/500] eta: 0:00:23 time: 0.0501 data_time: 0.0036 memory: 1008 2022/11/02 14:03:15 - mmengine - INFO - Epoch(val) [180][45/500] eta: 0:00:23 time: 0.0554 data_time: 0.0034 memory: 1008 2022/11/02 14:03:15 - mmengine - INFO - Epoch(val) [180][50/500] eta: 0:00:27 time: 0.0601 data_time: 0.0062 memory: 1008 2022/11/02 14:03:15 - mmengine - INFO - Epoch(val) [180][55/500] eta: 0:00:27 time: 0.0649 data_time: 0.0066 memory: 1008 2022/11/02 14:03:15 - mmengine - INFO - Epoch(val) [180][60/500] eta: 0:00:22 time: 0.0523 data_time: 0.0033 memory: 1008 2022/11/02 14:03:16 - mmengine - INFO - Epoch(val) [180][65/500] eta: 0:00:22 time: 0.0469 data_time: 0.0029 memory: 1008 2022/11/02 14:03:16 - mmengine - INFO - Epoch(val) [180][70/500] eta: 0:00:21 time: 0.0506 data_time: 0.0028 memory: 1008 2022/11/02 14:03:16 - mmengine - INFO - Epoch(val) [180][75/500] eta: 0:00:21 time: 0.0433 data_time: 0.0025 memory: 1008 2022/11/02 14:03:16 - mmengine - INFO - Epoch(val) [180][80/500] eta: 0:00:17 time: 0.0413 data_time: 0.0025 memory: 1008 2022/11/02 14:03:17 - mmengine - INFO - Epoch(val) [180][85/500] eta: 0:00:17 time: 0.0419 data_time: 0.0024 memory: 1008 2022/11/02 14:03:17 - mmengine - INFO - Epoch(val) [180][90/500] eta: 0:00:16 time: 0.0410 data_time: 0.0022 memory: 1008 2022/11/02 14:03:17 - mmengine - INFO - Epoch(val) [180][95/500] eta: 0:00:16 time: 0.0448 data_time: 0.0025 memory: 1008 2022/11/02 14:03:17 - mmengine - INFO - Epoch(val) [180][100/500] eta: 0:00:16 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 14:03:17 - mmengine - INFO - Epoch(val) [180][105/500] eta: 0:00:16 time: 0.0404 data_time: 0.0024 memory: 1008 2022/11/02 14:03:18 - mmengine - INFO - Epoch(val) [180][110/500] eta: 0:00:17 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/02 14:03:18 - mmengine - INFO - Epoch(val) [180][115/500] eta: 0:00:17 time: 0.0432 data_time: 0.0031 memory: 1008 2022/11/02 14:03:18 - mmengine - INFO - Epoch(val) [180][120/500] eta: 0:00:15 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 14:03:18 - mmengine - INFO - Epoch(val) [180][125/500] eta: 0:00:15 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 14:03:19 - mmengine - INFO - Epoch(val) [180][130/500] eta: 0:00:16 time: 0.0442 data_time: 0.0042 memory: 1008 2022/11/02 14:03:19 - mmengine - INFO - Epoch(val) [180][135/500] eta: 0:00:16 time: 0.0472 data_time: 0.0056 memory: 1008 2022/11/02 14:03:19 - mmengine - INFO - Epoch(val) [180][140/500] eta: 0:00:16 time: 0.0461 data_time: 0.0039 memory: 1008 2022/11/02 14:03:19 - mmengine - INFO - Epoch(val) [180][145/500] eta: 0:00:16 time: 0.0544 data_time: 0.0040 memory: 1008 2022/11/02 14:03:20 - mmengine - INFO - Epoch(val) [180][150/500] eta: 0:00:18 time: 0.0522 data_time: 0.0041 memory: 1008 2022/11/02 14:03:20 - mmengine - INFO - Epoch(val) [180][155/500] eta: 0:00:18 time: 0.0491 data_time: 0.0027 memory: 1008 2022/11/02 14:03:20 - mmengine - INFO - Epoch(val) [180][160/500] eta: 0:00:17 time: 0.0511 data_time: 0.0026 memory: 1008 2022/11/02 14:03:20 - mmengine - INFO - Epoch(val) [180][165/500] eta: 0:00:17 time: 0.0451 data_time: 0.0026 memory: 1008 2022/11/02 14:03:20 - mmengine - INFO - Epoch(val) [180][170/500] eta: 0:00:14 time: 0.0441 data_time: 0.0026 memory: 1008 2022/11/02 14:03:21 - mmengine - INFO - Epoch(val) [180][175/500] eta: 0:00:14 time: 0.0400 data_time: 0.0023 memory: 1008 2022/11/02 14:03:21 - mmengine - INFO - Epoch(val) [180][180/500] eta: 0:00:14 time: 0.0438 data_time: 0.0031 memory: 1008 2022/11/02 14:03:21 - mmengine - INFO - Epoch(val) [180][185/500] eta: 0:00:14 time: 0.0472 data_time: 0.0031 memory: 1008 2022/11/02 14:03:21 - mmengine - INFO - Epoch(val) [180][190/500] eta: 0:00:14 time: 0.0453 data_time: 0.0024 memory: 1008 2022/11/02 14:03:22 - mmengine - INFO - Epoch(val) [180][195/500] eta: 0:00:14 time: 0.0420 data_time: 0.0024 memory: 1008 2022/11/02 14:03:22 - mmengine - INFO - Epoch(val) [180][200/500] eta: 0:00:14 time: 0.0483 data_time: 0.0028 memory: 1008 2022/11/02 14:03:22 - mmengine - INFO - Epoch(val) [180][205/500] eta: 0:00:14 time: 0.0490 data_time: 0.0029 memory: 1008 2022/11/02 14:03:22 - mmengine - INFO - Epoch(val) [180][210/500] eta: 0:00:11 time: 0.0413 data_time: 0.0026 memory: 1008 2022/11/02 14:03:22 - mmengine - INFO - Epoch(val) [180][215/500] eta: 0:00:11 time: 0.0446 data_time: 0.0026 memory: 1008 2022/11/02 14:03:23 - mmengine - INFO - Epoch(val) [180][220/500] eta: 0:00:12 time: 0.0463 data_time: 0.0029 memory: 1008 2022/11/02 14:03:23 - mmengine - INFO - Epoch(val) [180][225/500] eta: 0:00:12 time: 0.0447 data_time: 0.0025 memory: 1008 2022/11/02 14:03:23 - mmengine - INFO - Epoch(val) [180][230/500] eta: 0:00:10 time: 0.0391 data_time: 0.0020 memory: 1008 2022/11/02 14:03:23 - mmengine - INFO - Epoch(val) [180][235/500] eta: 0:00:10 time: 0.0429 data_time: 0.0034 memory: 1008 2022/11/02 14:03:24 - mmengine - INFO - Epoch(val) [180][240/500] eta: 0:00:11 time: 0.0459 data_time: 0.0035 memory: 1008 2022/11/02 14:03:24 - mmengine - INFO - Epoch(val) [180][245/500] eta: 0:00:11 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 14:03:24 - mmengine - INFO - Epoch(val) [180][250/500] eta: 0:00:10 time: 0.0436 data_time: 0.0025 memory: 1008 2022/11/02 14:03:24 - mmengine - INFO - Epoch(val) [180][255/500] eta: 0:00:10 time: 0.0433 data_time: 0.0025 memory: 1008 2022/11/02 14:03:24 - mmengine - INFO - Epoch(val) [180][260/500] eta: 0:00:09 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/02 14:03:25 - mmengine - INFO - Epoch(val) [180][265/500] eta: 0:00:09 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/02 14:03:25 - mmengine - INFO - Epoch(val) [180][270/500] eta: 0:00:09 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 14:03:25 - mmengine - INFO - Epoch(val) [180][275/500] eta: 0:00:09 time: 0.0383 data_time: 0.0027 memory: 1008 2022/11/02 14:03:25 - mmengine - INFO - Epoch(val) [180][280/500] eta: 0:00:09 time: 0.0415 data_time: 0.0023 memory: 1008 2022/11/02 14:03:25 - mmengine - INFO - Epoch(val) [180][285/500] eta: 0:00:09 time: 0.0406 data_time: 0.0020 memory: 1008 2022/11/02 14:03:26 - mmengine - INFO - Epoch(val) [180][290/500] eta: 0:00:08 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/02 14:03:26 - mmengine - INFO - Epoch(val) [180][295/500] eta: 0:00:08 time: 0.0444 data_time: 0.0026 memory: 1008 2022/11/02 14:03:26 - mmengine - INFO - Epoch(val) [180][300/500] eta: 0:00:08 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 14:03:26 - mmengine - INFO - Epoch(val) [180][305/500] eta: 0:00:08 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 14:03:26 - mmengine - INFO - Epoch(val) [180][310/500] eta: 0:00:07 time: 0.0386 data_time: 0.0025 memory: 1008 2022/11/02 14:03:27 - mmengine - INFO - Epoch(val) [180][315/500] eta: 0:00:07 time: 0.0422 data_time: 0.0025 memory: 1008 2022/11/02 14:03:27 - mmengine - INFO - Epoch(val) [180][320/500] eta: 0:00:07 time: 0.0425 data_time: 0.0025 memory: 1008 2022/11/02 14:03:27 - mmengine - INFO - Epoch(val) [180][325/500] eta: 0:00:07 time: 0.0510 data_time: 0.0025 memory: 1008 2022/11/02 14:03:27 - mmengine - INFO - Epoch(val) [180][330/500] eta: 0:00:08 time: 0.0494 data_time: 0.0022 memory: 1008 2022/11/02 14:03:27 - mmengine - INFO - Epoch(val) [180][335/500] eta: 0:00:08 time: 0.0343 data_time: 0.0021 memory: 1008 2022/11/02 14:03:28 - mmengine - INFO - Epoch(val) [180][340/500] eta: 0:00:07 time: 0.0493 data_time: 0.0022 memory: 1008 2022/11/02 14:03:28 - mmengine - INFO - Epoch(val) [180][345/500] eta: 0:00:07 time: 0.0510 data_time: 0.0023 memory: 1008 2022/11/02 14:03:28 - mmengine - INFO - Epoch(val) [180][350/500] eta: 0:00:06 time: 0.0426 data_time: 0.0025 memory: 1008 2022/11/02 14:03:28 - mmengine - INFO - Epoch(val) [180][355/500] eta: 0:00:06 time: 0.0414 data_time: 0.0024 memory: 1008 2022/11/02 14:03:29 - mmengine - INFO - Epoch(val) [180][360/500] eta: 0:00:04 time: 0.0355 data_time: 0.0022 memory: 1008 2022/11/02 14:03:29 - mmengine - INFO - Epoch(val) [180][365/500] eta: 0:00:04 time: 0.0399 data_time: 0.0022 memory: 1008 2022/11/02 14:03:29 - mmengine - INFO - Epoch(val) [180][370/500] eta: 0:00:04 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/02 14:03:29 - mmengine - INFO - Epoch(val) [180][375/500] eta: 0:00:04 time: 0.0352 data_time: 0.0023 memory: 1008 2022/11/02 14:03:29 - mmengine - INFO - Epoch(val) [180][380/500] eta: 0:00:04 time: 0.0413 data_time: 0.0022 memory: 1008 2022/11/02 14:03:30 - mmengine - INFO - Epoch(val) [180][385/500] eta: 0:00:04 time: 0.0415 data_time: 0.0023 memory: 1008 2022/11/02 14:03:30 - mmengine - INFO - Epoch(val) [180][390/500] eta: 0:00:04 time: 0.0379 data_time: 0.0023 memory: 1008 2022/11/02 14:03:30 - mmengine - INFO - Epoch(val) [180][395/500] eta: 0:00:04 time: 0.0401 data_time: 0.0024 memory: 1008 2022/11/02 14:03:30 - mmengine - INFO - Epoch(val) [180][400/500] eta: 0:00:04 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/02 14:03:30 - mmengine - INFO - Epoch(val) [180][405/500] eta: 0:00:04 time: 0.0410 data_time: 0.0023 memory: 1008 2022/11/02 14:03:31 - mmengine - INFO - Epoch(val) [180][410/500] eta: 0:00:03 time: 0.0405 data_time: 0.0022 memory: 1008 2022/11/02 14:03:31 - mmengine - INFO - Epoch(val) [180][415/500] eta: 0:00:03 time: 0.0397 data_time: 0.0023 memory: 1008 2022/11/02 14:03:31 - mmengine - INFO - Epoch(val) [180][420/500] eta: 0:00:02 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/02 14:03:31 - mmengine - INFO - Epoch(val) [180][425/500] eta: 0:00:02 time: 0.0348 data_time: 0.0022 memory: 1008 2022/11/02 14:03:31 - mmengine - INFO - Epoch(val) [180][430/500] eta: 0:00:02 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 14:03:32 - mmengine - INFO - Epoch(val) [180][435/500] eta: 0:00:02 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/02 14:03:32 - mmengine - INFO - Epoch(val) [180][440/500] eta: 0:00:02 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/02 14:03:32 - mmengine - INFO - Epoch(val) [180][445/500] eta: 0:00:02 time: 0.0411 data_time: 0.0025 memory: 1008 2022/11/02 14:03:32 - mmengine - INFO - Epoch(val) [180][450/500] eta: 0:00:02 time: 0.0409 data_time: 0.0022 memory: 1008 2022/11/02 14:03:32 - mmengine - INFO - Epoch(val) [180][455/500] eta: 0:00:02 time: 0.0406 data_time: 0.0022 memory: 1008 2022/11/02 14:03:33 - mmengine - INFO - Epoch(val) [180][460/500] eta: 0:00:01 time: 0.0378 data_time: 0.0022 memory: 1008 2022/11/02 14:03:33 - mmengine - INFO - Epoch(val) [180][465/500] eta: 0:00:01 time: 0.0359 data_time: 0.0023 memory: 1008 2022/11/02 14:03:33 - mmengine - INFO - Epoch(val) [180][470/500] eta: 0:00:01 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 14:03:33 - mmengine - INFO - Epoch(val) [180][475/500] eta: 0:00:01 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 14:03:33 - mmengine - INFO - Epoch(val) [180][480/500] eta: 0:00:00 time: 0.0355 data_time: 0.0021 memory: 1008 2022/11/02 14:03:33 - mmengine - INFO - Epoch(val) [180][485/500] eta: 0:00:00 time: 0.0378 data_time: 0.0022 memory: 1008 2022/11/02 14:03:34 - mmengine - INFO - Epoch(val) [180][490/500] eta: 0:00:00 time: 0.0398 data_time: 0.0022 memory: 1008 2022/11/02 14:03:34 - mmengine - INFO - Epoch(val) [180][495/500] eta: 0:00:00 time: 0.0441 data_time: 0.0023 memory: 1008 2022/11/02 14:03:34 - mmengine - INFO - Epoch(val) [180][500/500] eta: 0:00:00 time: 0.0424 data_time: 0.0024 memory: 1008 2022/11/02 14:03:34 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8228, precision: 0.5748, hmean: 0.6768 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8228, precision: 0.6803, hmean: 0.7448 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8199, precision: 0.7414, hmean: 0.7787 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8050, precision: 0.8019, hmean: 0.8035 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7357, precision: 0.8827, hmean: 0.8025 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3028, precision: 0.9632, hmean: 0.4608 2022/11/02 14:03:34 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0010, precision: 1.0000, hmean: 0.0019 2022/11/02 14:03:34 - mmengine - INFO - Epoch(val) [180][500/500] icdar/precision: 0.8019 icdar/recall: 0.8050 icdar/hmean: 0.8035 2022/11/02 14:03:39 - mmengine - INFO - Epoch(train) [181][5/63] lr: 1.8685e-03 eta: 0:00:00 time: 0.7865 data_time: 0.1780 memory: 14901 loss: 2.0057 loss_prob: 1.1636 loss_thr: 0.6523 loss_db: 0.1898 2022/11/02 14:03:42 - mmengine - INFO - Epoch(train) [181][10/63] lr: 1.8685e-03 eta: 10:32:38 time: 0.8159 data_time: 0.1837 memory: 14901 loss: 2.0035 loss_prob: 1.1666 loss_thr: 0.6453 loss_db: 0.1915 2022/11/02 14:03:45 - mmengine - INFO - Epoch(train) [181][15/63] lr: 1.8685e-03 eta: 10:32:38 time: 0.5388 data_time: 0.0105 memory: 14901 loss: 1.8820 loss_prob: 1.1041 loss_thr: 0.5967 loss_db: 0.1812 2022/11/02 14:03:47 - mmengine - INFO - Epoch(train) [181][20/63] lr: 1.8685e-03 eta: 10:32:26 time: 0.4895 data_time: 0.0052 memory: 14901 loss: 1.9479 loss_prob: 1.1443 loss_thr: 0.6199 loss_db: 0.1837 2022/11/02 14:03:50 - mmengine - INFO - Epoch(train) [181][25/63] lr: 1.8685e-03 eta: 10:32:26 time: 0.4784 data_time: 0.0065 memory: 14901 loss: 2.1978 loss_prob: 1.3223 loss_thr: 0.6629 loss_db: 0.2125 2022/11/02 14:03:53 - mmengine - INFO - Epoch(train) [181][30/63] lr: 1.8685e-03 eta: 10:32:17 time: 0.5426 data_time: 0.0613 memory: 14901 loss: 2.1929 loss_prob: 1.3147 loss_thr: 0.6625 loss_db: 0.2156 2022/11/02 14:03:55 - mmengine - INFO - Epoch(train) [181][35/63] lr: 1.8685e-03 eta: 10:32:17 time: 0.5488 data_time: 0.0649 memory: 14901 loss: 2.0395 loss_prob: 1.1860 loss_thr: 0.6583 loss_db: 0.1952 2022/11/02 14:03:58 - mmengine - INFO - Epoch(train) [181][40/63] lr: 1.8685e-03 eta: 10:32:07 time: 0.5096 data_time: 0.0097 memory: 14901 loss: 1.9963 loss_prob: 1.1486 loss_thr: 0.6581 loss_db: 0.1895 2022/11/02 14:04:00 - mmengine - INFO - Epoch(train) [181][45/63] lr: 1.8685e-03 eta: 10:32:07 time: 0.4775 data_time: 0.0046 memory: 14901 loss: 2.0353 loss_prob: 1.2006 loss_thr: 0.6353 loss_db: 0.1994 2022/11/02 14:04:02 - mmengine - INFO - Epoch(train) [181][50/63] lr: 1.8685e-03 eta: 10:31:53 time: 0.4566 data_time: 0.0081 memory: 14901 loss: 2.0280 loss_prob: 1.2179 loss_thr: 0.6134 loss_db: 0.1966 2022/11/02 14:04:05 - mmengine - INFO - Epoch(train) [181][55/63] lr: 1.8685e-03 eta: 10:31:53 time: 0.4991 data_time: 0.0203 memory: 14901 loss: 1.9632 loss_prob: 1.1518 loss_thr: 0.6292 loss_db: 0.1822 2022/11/02 14:04:07 - mmengine - INFO - Epoch(train) [181][60/63] lr: 1.8685e-03 eta: 10:31:41 time: 0.4842 data_time: 0.0189 memory: 14901 loss: 1.9907 loss_prob: 1.1623 loss_thr: 0.6365 loss_db: 0.1918 2022/11/02 14:04:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:04:14 - mmengine - INFO - Epoch(train) [182][5/63] lr: 1.8668e-03 eta: 10:31:41 time: 0.7294 data_time: 0.2241 memory: 14901 loss: 2.0421 loss_prob: 1.2011 loss_thr: 0.6453 loss_db: 0.1956 2022/11/02 14:04:16 - mmengine - INFO - Epoch(train) [182][10/63] lr: 1.8668e-03 eta: 10:31:31 time: 0.7265 data_time: 0.2241 memory: 14901 loss: 2.1049 loss_prob: 1.2405 loss_thr: 0.6641 loss_db: 0.2003 2022/11/02 14:04:18 - mmengine - INFO - Epoch(train) [182][15/63] lr: 1.8668e-03 eta: 10:31:31 time: 0.4804 data_time: 0.0050 memory: 14901 loss: 1.9144 loss_prob: 1.1141 loss_thr: 0.6171 loss_db: 0.1832 2022/11/02 14:04:21 - mmengine - INFO - Epoch(train) [182][20/63] lr: 1.8668e-03 eta: 10:31:23 time: 0.5426 data_time: 0.0355 memory: 14901 loss: 1.8327 loss_prob: 1.0589 loss_thr: 0.5983 loss_db: 0.1755 2022/11/02 14:04:24 - mmengine - INFO - Epoch(train) [182][25/63] lr: 1.8668e-03 eta: 10:31:23 time: 0.5701 data_time: 0.0353 memory: 14901 loss: 1.9129 loss_prob: 1.1154 loss_thr: 0.6165 loss_db: 0.1810 2022/11/02 14:04:27 - mmengine - INFO - Epoch(train) [182][30/63] lr: 1.8668e-03 eta: 10:31:14 time: 0.5421 data_time: 0.0052 memory: 14901 loss: 2.0098 loss_prob: 1.1789 loss_thr: 0.6341 loss_db: 0.1968 2022/11/02 14:04:30 - mmengine - INFO - Epoch(train) [182][35/63] lr: 1.8668e-03 eta: 10:31:14 time: 0.5742 data_time: 0.0054 memory: 14901 loss: 2.0655 loss_prob: 1.2263 loss_thr: 0.6387 loss_db: 0.2005 2022/11/02 14:04:32 - mmengine - INFO - Epoch(train) [182][40/63] lr: 1.8668e-03 eta: 10:31:06 time: 0.5483 data_time: 0.0052 memory: 14901 loss: 1.9331 loss_prob: 1.1392 loss_thr: 0.6101 loss_db: 0.1837 2022/11/02 14:04:35 - mmengine - INFO - Epoch(train) [182][45/63] lr: 1.8668e-03 eta: 10:31:06 time: 0.5496 data_time: 0.0259 memory: 14901 loss: 1.7582 loss_prob: 1.0066 loss_thr: 0.5825 loss_db: 0.1690 2022/11/02 14:04:38 - mmengine - INFO - Epoch(train) [182][50/63] lr: 1.8668e-03 eta: 10:30:58 time: 0.5463 data_time: 0.0281 memory: 14901 loss: 1.8361 loss_prob: 1.0540 loss_thr: 0.6092 loss_db: 0.1729 2022/11/02 14:04:40 - mmengine - INFO - Epoch(train) [182][55/63] lr: 1.8668e-03 eta: 10:30:58 time: 0.4799 data_time: 0.0082 memory: 14901 loss: 1.8515 loss_prob: 1.0623 loss_thr: 0.6181 loss_db: 0.1711 2022/11/02 14:04:43 - mmengine - INFO - Epoch(train) [182][60/63] lr: 1.8668e-03 eta: 10:30:47 time: 0.5118 data_time: 0.0058 memory: 14901 loss: 1.9188 loss_prob: 1.1170 loss_thr: 0.6222 loss_db: 0.1797 2022/11/02 14:04:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:04:49 - mmengine - INFO - Epoch(train) [183][5/63] lr: 1.8652e-03 eta: 10:30:47 time: 0.7193 data_time: 0.2095 memory: 14901 loss: 2.0045 loss_prob: 1.1718 loss_thr: 0.6396 loss_db: 0.1931 2022/11/02 14:04:51 - mmengine - INFO - Epoch(train) [183][10/63] lr: 1.8652e-03 eta: 10:30:37 time: 0.7195 data_time: 0.2118 memory: 14901 loss: 1.9118 loss_prob: 1.1327 loss_thr: 0.5955 loss_db: 0.1836 2022/11/02 14:04:54 - mmengine - INFO - Epoch(train) [183][15/63] lr: 1.8652e-03 eta: 10:30:37 time: 0.4905 data_time: 0.0070 memory: 14901 loss: 1.9365 loss_prob: 1.1337 loss_thr: 0.6197 loss_db: 0.1830 2022/11/02 14:04:56 - mmengine - INFO - Epoch(train) [183][20/63] lr: 1.8652e-03 eta: 10:30:26 time: 0.4972 data_time: 0.0047 memory: 14901 loss: 2.0374 loss_prob: 1.1755 loss_thr: 0.6685 loss_db: 0.1934 2022/11/02 14:04:59 - mmengine - INFO - Epoch(train) [183][25/63] lr: 1.8652e-03 eta: 10:30:26 time: 0.4820 data_time: 0.0077 memory: 14901 loss: 1.9713 loss_prob: 1.1267 loss_thr: 0.6585 loss_db: 0.1861 2022/11/02 14:05:02 - mmengine - INFO - Epoch(train) [183][30/63] lr: 1.8652e-03 eta: 10:30:19 time: 0.5620 data_time: 0.0308 memory: 14901 loss: 1.8150 loss_prob: 1.0303 loss_thr: 0.6180 loss_db: 0.1667 2022/11/02 14:05:05 - mmengine - INFO - Epoch(train) [183][35/63] lr: 1.8652e-03 eta: 10:30:19 time: 0.6574 data_time: 0.0291 memory: 14901 loss: 1.8068 loss_prob: 1.0240 loss_thr: 0.6128 loss_db: 0.1700 2022/11/02 14:05:08 - mmengine - INFO - Epoch(train) [183][40/63] lr: 1.8652e-03 eta: 10:30:14 time: 0.6229 data_time: 0.0070 memory: 14901 loss: 1.8113 loss_prob: 1.0214 loss_thr: 0.6157 loss_db: 0.1742 2022/11/02 14:05:11 - mmengine - INFO - Epoch(train) [183][45/63] lr: 1.8652e-03 eta: 10:30:14 time: 0.5902 data_time: 0.0056 memory: 14901 loss: 1.8551 loss_prob: 1.0714 loss_thr: 0.6075 loss_db: 0.1761 2022/11/02 14:05:14 - mmengine - INFO - Epoch(train) [183][50/63] lr: 1.8652e-03 eta: 10:30:08 time: 0.5836 data_time: 0.0115 memory: 14901 loss: 1.9797 loss_prob: 1.1570 loss_thr: 0.6363 loss_db: 0.1865 2022/11/02 14:05:17 - mmengine - INFO - Epoch(train) [183][55/63] lr: 1.8652e-03 eta: 10:30:08 time: 0.6379 data_time: 0.0233 memory: 14901 loss: 1.9838 loss_prob: 1.1456 loss_thr: 0.6517 loss_db: 0.1865 2022/11/02 14:05:21 - mmengine - INFO - Epoch(train) [183][60/63] lr: 1.8652e-03 eta: 10:30:07 time: 0.6781 data_time: 0.0170 memory: 14901 loss: 1.9922 loss_prob: 1.1575 loss_thr: 0.6424 loss_db: 0.1924 2022/11/02 14:05:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:05:28 - mmengine - INFO - Epoch(train) [184][5/63] lr: 1.8635e-03 eta: 10:30:07 time: 0.8169 data_time: 0.2302 memory: 14901 loss: 1.8084 loss_prob: 1.0308 loss_thr: 0.6115 loss_db: 0.1661 2022/11/02 14:05:31 - mmengine - INFO - Epoch(train) [184][10/63] lr: 1.8635e-03 eta: 10:30:06 time: 0.8871 data_time: 0.2295 memory: 14901 loss: 1.8555 loss_prob: 1.0704 loss_thr: 0.6098 loss_db: 0.1753 2022/11/02 14:05:34 - mmengine - INFO - Epoch(train) [184][15/63] lr: 1.8635e-03 eta: 10:30:06 time: 0.5743 data_time: 0.0127 memory: 14901 loss: 1.9063 loss_prob: 1.0998 loss_thr: 0.6243 loss_db: 0.1822 2022/11/02 14:05:36 - mmengine - INFO - Epoch(train) [184][20/63] lr: 1.8635e-03 eta: 10:29:58 time: 0.5525 data_time: 0.0134 memory: 14901 loss: 1.8955 loss_prob: 1.0899 loss_thr: 0.6273 loss_db: 0.1783 2022/11/02 14:05:39 - mmengine - INFO - Epoch(train) [184][25/63] lr: 1.8635e-03 eta: 10:29:58 time: 0.5303 data_time: 0.0155 memory: 14901 loss: 1.9058 loss_prob: 1.1116 loss_thr: 0.6162 loss_db: 0.1780 2022/11/02 14:05:42 - mmengine - INFO - Epoch(train) [184][30/63] lr: 1.8635e-03 eta: 10:29:51 time: 0.5611 data_time: 0.0316 memory: 14901 loss: 1.8487 loss_prob: 1.0677 loss_thr: 0.6087 loss_db: 0.1723 2022/11/02 14:05:45 - mmengine - INFO - Epoch(train) [184][35/63] lr: 1.8635e-03 eta: 10:29:51 time: 0.5690 data_time: 0.0221 memory: 14901 loss: 2.0229 loss_prob: 1.1861 loss_thr: 0.6415 loss_db: 0.1953 2022/11/02 14:05:48 - mmengine - INFO - Epoch(train) [184][40/63] lr: 1.8635e-03 eta: 10:29:46 time: 0.6155 data_time: 0.0107 memory: 14901 loss: 1.9744 loss_prob: 1.1613 loss_thr: 0.6227 loss_db: 0.1904 2022/11/02 14:05:51 - mmengine - INFO - Epoch(train) [184][45/63] lr: 1.8635e-03 eta: 10:29:46 time: 0.6353 data_time: 0.0100 memory: 14901 loss: 1.8828 loss_prob: 1.1018 loss_thr: 0.6027 loss_db: 0.1784 2022/11/02 14:05:54 - mmengine - INFO - Epoch(train) [184][50/63] lr: 1.8635e-03 eta: 10:29:38 time: 0.5526 data_time: 0.0110 memory: 14901 loss: 2.0471 loss_prob: 1.2322 loss_thr: 0.6220 loss_db: 0.1929 2022/11/02 14:05:57 - mmengine - INFO - Epoch(train) [184][55/63] lr: 1.8635e-03 eta: 10:29:38 time: 0.6362 data_time: 0.0185 memory: 14901 loss: 1.9180 loss_prob: 1.1418 loss_thr: 0.5942 loss_db: 0.1820 2022/11/02 14:06:02 - mmengine - INFO - Epoch(train) [184][60/63] lr: 1.8635e-03 eta: 10:29:44 time: 0.7934 data_time: 0.0151 memory: 14901 loss: 1.8473 loss_prob: 1.0847 loss_thr: 0.5798 loss_db: 0.1828 2022/11/02 14:06:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:06:08 - mmengine - INFO - Epoch(train) [185][5/63] lr: 1.8619e-03 eta: 10:29:44 time: 0.7168 data_time: 0.1785 memory: 14901 loss: 1.9098 loss_prob: 1.1224 loss_thr: 0.6034 loss_db: 0.1840 2022/11/02 14:06:10 - mmengine - INFO - Epoch(train) [185][10/63] lr: 1.8619e-03 eta: 10:29:34 time: 0.7255 data_time: 0.1758 memory: 14901 loss: 1.8436 loss_prob: 1.0764 loss_thr: 0.5899 loss_db: 0.1773 2022/11/02 14:06:12 - mmengine - INFO - Epoch(train) [185][15/63] lr: 1.8619e-03 eta: 10:29:34 time: 0.4863 data_time: 0.0047 memory: 14901 loss: 1.7912 loss_prob: 1.0344 loss_thr: 0.5846 loss_db: 0.1722 2022/11/02 14:06:15 - mmengine - INFO - Epoch(train) [185][20/63] lr: 1.8619e-03 eta: 10:29:21 time: 0.4734 data_time: 0.0051 memory: 14901 loss: 1.9096 loss_prob: 1.1125 loss_thr: 0.6147 loss_db: 0.1824 2022/11/02 14:06:18 - mmengine - INFO - Epoch(train) [185][25/63] lr: 1.8619e-03 eta: 10:29:21 time: 0.5294 data_time: 0.0113 memory: 14901 loss: 1.9404 loss_prob: 1.1303 loss_thr: 0.6289 loss_db: 0.1811 2022/11/02 14:06:20 - mmengine - INFO - Epoch(train) [185][30/63] lr: 1.8619e-03 eta: 10:29:12 time: 0.5331 data_time: 0.0311 memory: 14901 loss: 1.8769 loss_prob: 1.0774 loss_thr: 0.6222 loss_db: 0.1772 2022/11/02 14:06:23 - mmengine - INFO - Epoch(train) [185][35/63] lr: 1.8619e-03 eta: 10:29:12 time: 0.4881 data_time: 0.0251 memory: 14901 loss: 1.9355 loss_prob: 1.1151 loss_thr: 0.6354 loss_db: 0.1850 2022/11/02 14:06:25 - mmengine - INFO - Epoch(train) [185][40/63] lr: 1.8619e-03 eta: 10:29:01 time: 0.4948 data_time: 0.0049 memory: 14901 loss: 1.9398 loss_prob: 1.1194 loss_thr: 0.6356 loss_db: 0.1848 2022/11/02 14:06:28 - mmengine - INFO - Epoch(train) [185][45/63] lr: 1.8619e-03 eta: 10:29:01 time: 0.5001 data_time: 0.0048 memory: 14901 loss: 2.0148 loss_prob: 1.1760 loss_thr: 0.6476 loss_db: 0.1912 2022/11/02 14:06:31 - mmengine - INFO - Epoch(train) [185][50/63] lr: 1.8619e-03 eta: 10:28:52 time: 0.5366 data_time: 0.0221 memory: 14901 loss: 2.0672 loss_prob: 1.2185 loss_thr: 0.6514 loss_db: 0.1973 2022/11/02 14:06:33 - mmengine - INFO - Epoch(train) [185][55/63] lr: 1.8619e-03 eta: 10:28:52 time: 0.5272 data_time: 0.0231 memory: 14901 loss: 1.9852 loss_prob: 1.1615 loss_thr: 0.6319 loss_db: 0.1917 2022/11/02 14:06:35 - mmengine - INFO - Epoch(train) [185][60/63] lr: 1.8619e-03 eta: 10:28:40 time: 0.4714 data_time: 0.0061 memory: 14901 loss: 1.9146 loss_prob: 1.1048 loss_thr: 0.6297 loss_db: 0.1800 2022/11/02 14:06:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:06:41 - mmengine - INFO - Epoch(train) [186][5/63] lr: 1.8602e-03 eta: 10:28:40 time: 0.6986 data_time: 0.2084 memory: 14901 loss: 1.8405 loss_prob: 1.0587 loss_thr: 0.6053 loss_db: 0.1765 2022/11/02 14:06:44 - mmengine - INFO - Epoch(train) [186][10/63] lr: 1.8602e-03 eta: 10:28:29 time: 0.7097 data_time: 0.2085 memory: 14901 loss: 1.8260 loss_prob: 1.0419 loss_thr: 0.6129 loss_db: 0.1711 2022/11/02 14:06:46 - mmengine - INFO - Epoch(train) [186][15/63] lr: 1.8602e-03 eta: 10:28:29 time: 0.4731 data_time: 0.0054 memory: 14901 loss: 1.8274 loss_prob: 1.0484 loss_thr: 0.6106 loss_db: 0.1684 2022/11/02 14:06:48 - mmengine - INFO - Epoch(train) [186][20/63] lr: 1.8602e-03 eta: 10:28:17 time: 0.4802 data_time: 0.0049 memory: 14901 loss: 1.8552 loss_prob: 1.0681 loss_thr: 0.6157 loss_db: 0.1715 2022/11/02 14:06:51 - mmengine - INFO - Epoch(train) [186][25/63] lr: 1.8602e-03 eta: 10:28:17 time: 0.5023 data_time: 0.0182 memory: 14901 loss: 1.9608 loss_prob: 1.1422 loss_thr: 0.6339 loss_db: 0.1847 2022/11/02 14:06:54 - mmengine - INFO - Epoch(train) [186][30/63] lr: 1.8602e-03 eta: 10:28:07 time: 0.5179 data_time: 0.0456 memory: 14901 loss: 1.9384 loss_prob: 1.1421 loss_thr: 0.6115 loss_db: 0.1849 2022/11/02 14:06:56 - mmengine - INFO - Epoch(train) [186][35/63] lr: 1.8602e-03 eta: 10:28:07 time: 0.5051 data_time: 0.0321 memory: 14901 loss: 1.8304 loss_prob: 1.0647 loss_thr: 0.5919 loss_db: 0.1738 2022/11/02 14:06:59 - mmengine - INFO - Epoch(train) [186][40/63] lr: 1.8602e-03 eta: 10:27:56 time: 0.4985 data_time: 0.0048 memory: 14901 loss: 1.8015 loss_prob: 1.0359 loss_thr: 0.5944 loss_db: 0.1712 2022/11/02 14:07:01 - mmengine - INFO - Epoch(train) [186][45/63] lr: 1.8602e-03 eta: 10:27:56 time: 0.4974 data_time: 0.0049 memory: 14901 loss: 1.9133 loss_prob: 1.1103 loss_thr: 0.6147 loss_db: 0.1883 2022/11/02 14:07:04 - mmengine - INFO - Epoch(train) [186][50/63] lr: 1.8602e-03 eta: 10:27:48 time: 0.5459 data_time: 0.0201 memory: 14901 loss: 1.9973 loss_prob: 1.1452 loss_thr: 0.6590 loss_db: 0.1931 2022/11/02 14:07:06 - mmengine - INFO - Epoch(train) [186][55/63] lr: 1.8602e-03 eta: 10:27:48 time: 0.5318 data_time: 0.0261 memory: 14901 loss: 1.8291 loss_prob: 1.0264 loss_thr: 0.6356 loss_db: 0.1671 2022/11/02 14:07:09 - mmengine - INFO - Epoch(train) [186][60/63] lr: 1.8602e-03 eta: 10:27:37 time: 0.4914 data_time: 0.0124 memory: 14901 loss: 1.8873 loss_prob: 1.1015 loss_thr: 0.6104 loss_db: 0.1754 2022/11/02 14:07:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:07:15 - mmengine - INFO - Epoch(train) [187][5/63] lr: 1.8586e-03 eta: 10:27:37 time: 0.7137 data_time: 0.2044 memory: 14901 loss: 1.9247 loss_prob: 1.1080 loss_thr: 0.6351 loss_db: 0.1817 2022/11/02 14:07:17 - mmengine - INFO - Epoch(train) [187][10/63] lr: 1.8586e-03 eta: 10:27:27 time: 0.7329 data_time: 0.2043 memory: 14901 loss: 1.7386 loss_prob: 0.9706 loss_thr: 0.6074 loss_db: 0.1605 2022/11/02 14:07:20 - mmengine - INFO - Epoch(train) [187][15/63] lr: 1.8586e-03 eta: 10:27:27 time: 0.4804 data_time: 0.0049 memory: 14901 loss: 1.7758 loss_prob: 1.0084 loss_thr: 0.6019 loss_db: 0.1655 2022/11/02 14:07:22 - mmengine - INFO - Epoch(train) [187][20/63] lr: 1.8586e-03 eta: 10:27:15 time: 0.4788 data_time: 0.0077 memory: 14901 loss: 1.9321 loss_prob: 1.1230 loss_thr: 0.6261 loss_db: 0.1831 2022/11/02 14:07:25 - mmengine - INFO - Epoch(train) [187][25/63] lr: 1.8586e-03 eta: 10:27:15 time: 0.5047 data_time: 0.0297 memory: 14901 loss: 1.9302 loss_prob: 1.1241 loss_thr: 0.6236 loss_db: 0.1825 2022/11/02 14:07:27 - mmengine - INFO - Epoch(train) [187][30/63] lr: 1.8586e-03 eta: 10:27:05 time: 0.5043 data_time: 0.0322 memory: 14901 loss: 1.9946 loss_prob: 1.1803 loss_thr: 0.6220 loss_db: 0.1923 2022/11/02 14:07:30 - mmengine - INFO - Epoch(train) [187][35/63] lr: 1.8586e-03 eta: 10:27:05 time: 0.4881 data_time: 0.0099 memory: 14901 loss: 1.9153 loss_prob: 1.1109 loss_thr: 0.6221 loss_db: 0.1823 2022/11/02 14:07:32 - mmengine - INFO - Epoch(train) [187][40/63] lr: 1.8586e-03 eta: 10:26:54 time: 0.4983 data_time: 0.0046 memory: 14901 loss: 1.8595 loss_prob: 1.0670 loss_thr: 0.6156 loss_db: 0.1770 2022/11/02 14:07:35 - mmengine - INFO - Epoch(train) [187][45/63] lr: 1.8586e-03 eta: 10:26:54 time: 0.5029 data_time: 0.0045 memory: 14901 loss: 1.9403 loss_prob: 1.1451 loss_thr: 0.6037 loss_db: 0.1915 2022/11/02 14:07:38 - mmengine - INFO - Epoch(train) [187][50/63] lr: 1.8586e-03 eta: 10:26:48 time: 0.5839 data_time: 0.0267 memory: 14901 loss: 1.9105 loss_prob: 1.1221 loss_thr: 0.5992 loss_db: 0.1892 2022/11/02 14:07:42 - mmengine - INFO - Epoch(train) [187][55/63] lr: 1.8586e-03 eta: 10:26:48 time: 0.6921 data_time: 0.0278 memory: 14901 loss: 1.9143 loss_prob: 1.1176 loss_thr: 0.6113 loss_db: 0.1854 2022/11/02 14:07:46 - mmengine - INFO - Epoch(train) [187][60/63] lr: 1.8586e-03 eta: 10:26:51 time: 0.7582 data_time: 0.0060 memory: 14901 loss: 1.9551 loss_prob: 1.1478 loss_thr: 0.6173 loss_db: 0.1900 2022/11/02 14:07:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:07:53 - mmengine - INFO - Epoch(train) [188][5/63] lr: 1.8569e-03 eta: 10:26:51 time: 0.8994 data_time: 0.2295 memory: 14901 loss: 1.9221 loss_prob: 1.1224 loss_thr: 0.6136 loss_db: 0.1861 2022/11/02 14:07:56 - mmengine - INFO - Epoch(train) [188][10/63] lr: 1.8569e-03 eta: 10:26:46 time: 0.8194 data_time: 0.2326 memory: 14901 loss: 1.9498 loss_prob: 1.1449 loss_thr: 0.6189 loss_db: 0.1860 2022/11/02 14:07:58 - mmengine - INFO - Epoch(train) [188][15/63] lr: 1.8569e-03 eta: 10:26:46 time: 0.5192 data_time: 0.0080 memory: 14901 loss: 2.1966 loss_prob: 1.3316 loss_thr: 0.6508 loss_db: 0.2142 2022/11/02 14:08:01 - mmengine - INFO - Epoch(train) [188][20/63] lr: 1.8569e-03 eta: 10:26:36 time: 0.5061 data_time: 0.0063 memory: 14901 loss: 2.2928 loss_prob: 1.4082 loss_thr: 0.6588 loss_db: 0.2258 2022/11/02 14:08:05 - mmengine - INFO - Epoch(train) [188][25/63] lr: 1.8569e-03 eta: 10:26:36 time: 0.6386 data_time: 0.0269 memory: 14901 loss: 2.0249 loss_prob: 1.2046 loss_thr: 0.6263 loss_db: 0.1940 2022/11/02 14:08:08 - mmengine - INFO - Epoch(train) [188][30/63] lr: 1.8569e-03 eta: 10:26:37 time: 0.7112 data_time: 0.0308 memory: 14901 loss: 1.7858 loss_prob: 1.0361 loss_thr: 0.5826 loss_db: 0.1671 2022/11/02 14:08:11 - mmengine - INFO - Epoch(train) [188][35/63] lr: 1.8569e-03 eta: 10:26:37 time: 0.6433 data_time: 0.0135 memory: 14901 loss: 1.8921 loss_prob: 1.1125 loss_thr: 0.5983 loss_db: 0.1814 2022/11/02 14:08:14 - mmengine - INFO - Epoch(train) [188][40/63] lr: 1.8569e-03 eta: 10:26:29 time: 0.5628 data_time: 0.0125 memory: 14901 loss: 1.9109 loss_prob: 1.1178 loss_thr: 0.6109 loss_db: 0.1823 2022/11/02 14:08:17 - mmengine - INFO - Epoch(train) [188][45/63] lr: 1.8569e-03 eta: 10:26:29 time: 0.5836 data_time: 0.0109 memory: 14901 loss: 1.8708 loss_prob: 1.0776 loss_thr: 0.6153 loss_db: 0.1779 2022/11/02 14:08:20 - mmengine - INFO - Epoch(train) [188][50/63] lr: 1.8569e-03 eta: 10:26:26 time: 0.6434 data_time: 0.0164 memory: 14901 loss: 1.9874 loss_prob: 1.1697 loss_thr: 0.6229 loss_db: 0.1947 2022/11/02 14:08:23 - mmengine - INFO - Epoch(train) [188][55/63] lr: 1.8569e-03 eta: 10:26:26 time: 0.5811 data_time: 0.0209 memory: 14901 loss: 1.9525 loss_prob: 1.1601 loss_thr: 0.6027 loss_db: 0.1896 2022/11/02 14:08:26 - mmengine - INFO - Epoch(train) [188][60/63] lr: 1.8569e-03 eta: 10:26:22 time: 0.6208 data_time: 0.0149 memory: 14901 loss: 1.8329 loss_prob: 1.0676 loss_thr: 0.5952 loss_db: 0.1701 2022/11/02 14:08:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:08:33 - mmengine - INFO - Epoch(train) [189][5/63] lr: 1.8553e-03 eta: 10:26:22 time: 0.8491 data_time: 0.2334 memory: 14901 loss: 1.7927 loss_prob: 1.0226 loss_thr: 0.6012 loss_db: 0.1689 2022/11/02 14:08:36 - mmengine - INFO - Epoch(train) [189][10/63] lr: 1.8553e-03 eta: 10:26:19 time: 0.8561 data_time: 0.2416 memory: 14901 loss: 1.7820 loss_prob: 1.0106 loss_thr: 0.6055 loss_db: 0.1659 2022/11/02 14:08:39 - mmengine - INFO - Epoch(train) [189][15/63] lr: 1.8553e-03 eta: 10:26:19 time: 0.5160 data_time: 0.0144 memory: 14901 loss: 1.7867 loss_prob: 1.0156 loss_thr: 0.6059 loss_db: 0.1652 2022/11/02 14:08:41 - mmengine - INFO - Epoch(train) [189][20/63] lr: 1.8553e-03 eta: 10:26:08 time: 0.4911 data_time: 0.0054 memory: 14901 loss: 1.8474 loss_prob: 1.0774 loss_thr: 0.5941 loss_db: 0.1759 2022/11/02 14:08:44 - mmengine - INFO - Epoch(train) [189][25/63] lr: 1.8553e-03 eta: 10:26:08 time: 0.5222 data_time: 0.0234 memory: 14901 loss: 1.8813 loss_prob: 1.0922 loss_thr: 0.6103 loss_db: 0.1789 2022/11/02 14:08:46 - mmengine - INFO - Epoch(train) [189][30/63] lr: 1.8553e-03 eta: 10:25:59 time: 0.5263 data_time: 0.0323 memory: 14901 loss: 1.7766 loss_prob: 1.0155 loss_thr: 0.5923 loss_db: 0.1688 2022/11/02 14:08:49 - mmengine - INFO - Epoch(train) [189][35/63] lr: 1.8553e-03 eta: 10:25:59 time: 0.4985 data_time: 0.0213 memory: 14901 loss: 1.9143 loss_prob: 1.1185 loss_thr: 0.6143 loss_db: 0.1816 2022/11/02 14:08:51 - mmengine - INFO - Epoch(train) [189][40/63] lr: 1.8553e-03 eta: 10:25:50 time: 0.5272 data_time: 0.0148 memory: 14901 loss: 2.0102 loss_prob: 1.1708 loss_thr: 0.6515 loss_db: 0.1879 2022/11/02 14:08:54 - mmengine - INFO - Epoch(train) [189][45/63] lr: 1.8553e-03 eta: 10:25:50 time: 0.5629 data_time: 0.0077 memory: 14901 loss: 1.9033 loss_prob: 1.0834 loss_thr: 0.6393 loss_db: 0.1806 2022/11/02 14:08:57 - mmengine - INFO - Epoch(train) [189][50/63] lr: 1.8553e-03 eta: 10:25:41 time: 0.5347 data_time: 0.0165 memory: 14901 loss: 1.8745 loss_prob: 1.0638 loss_thr: 0.6345 loss_db: 0.1762 2022/11/02 14:08:59 - mmengine - INFO - Epoch(train) [189][55/63] lr: 1.8553e-03 eta: 10:25:41 time: 0.4772 data_time: 0.0210 memory: 14901 loss: 1.9954 loss_prob: 1.1611 loss_thr: 0.6432 loss_db: 0.1911 2022/11/02 14:09:02 - mmengine - INFO - Epoch(train) [189][60/63] lr: 1.8553e-03 eta: 10:25:29 time: 0.4836 data_time: 0.0110 memory: 14901 loss: 1.9833 loss_prob: 1.1718 loss_thr: 0.6206 loss_db: 0.1909 2022/11/02 14:09:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:09:07 - mmengine - INFO - Epoch(train) [190][5/63] lr: 1.8536e-03 eta: 10:25:29 time: 0.6781 data_time: 0.2116 memory: 14901 loss: 2.1089 loss_prob: 1.2808 loss_thr: 0.6255 loss_db: 0.2026 2022/11/02 14:09:10 - mmengine - INFO - Epoch(train) [190][10/63] lr: 1.8536e-03 eta: 10:25:20 time: 0.7261 data_time: 0.2173 memory: 14901 loss: 2.2561 loss_prob: 1.3870 loss_thr: 0.6491 loss_db: 0.2199 2022/11/02 14:09:13 - mmengine - INFO - Epoch(train) [190][15/63] lr: 1.8536e-03 eta: 10:25:20 time: 0.5183 data_time: 0.0138 memory: 14901 loss: 2.3900 loss_prob: 1.4922 loss_thr: 0.6567 loss_db: 0.2412 2022/11/02 14:09:15 - mmengine - INFO - Epoch(train) [190][20/63] lr: 1.8536e-03 eta: 10:25:09 time: 0.5052 data_time: 0.0101 memory: 14901 loss: 2.3418 loss_prob: 1.4703 loss_thr: 0.6380 loss_db: 0.2336 2022/11/02 14:09:18 - mmengine - INFO - Epoch(train) [190][25/63] lr: 1.8536e-03 eta: 10:25:09 time: 0.5038 data_time: 0.0300 memory: 14901 loss: 2.0434 loss_prob: 1.2271 loss_thr: 0.6132 loss_db: 0.2031 2022/11/02 14:09:20 - mmengine - INFO - Epoch(train) [190][30/63] lr: 1.8536e-03 eta: 10:24:59 time: 0.5104 data_time: 0.0270 memory: 14901 loss: 1.8872 loss_prob: 1.0879 loss_thr: 0.6182 loss_db: 0.1811 2022/11/02 14:09:23 - mmengine - INFO - Epoch(train) [190][35/63] lr: 1.8536e-03 eta: 10:24:59 time: 0.5005 data_time: 0.0109 memory: 14901 loss: 1.9007 loss_prob: 1.0929 loss_thr: 0.6346 loss_db: 0.1732 2022/11/02 14:09:25 - mmengine - INFO - Epoch(train) [190][40/63] lr: 1.8536e-03 eta: 10:24:48 time: 0.4939 data_time: 0.0156 memory: 14901 loss: 1.8722 loss_prob: 1.0951 loss_thr: 0.6008 loss_db: 0.1764 2022/11/02 14:09:27 - mmengine - INFO - Epoch(train) [190][45/63] lr: 1.8536e-03 eta: 10:24:48 time: 0.4704 data_time: 0.0089 memory: 14901 loss: 1.8459 loss_prob: 1.0782 loss_thr: 0.5900 loss_db: 0.1778 2022/11/02 14:09:30 - mmengine - INFO - Epoch(train) [190][50/63] lr: 1.8536e-03 eta: 10:24:37 time: 0.4825 data_time: 0.0152 memory: 14901 loss: 1.7598 loss_prob: 1.0105 loss_thr: 0.5859 loss_db: 0.1634 2022/11/02 14:09:32 - mmengine - INFO - Epoch(train) [190][55/63] lr: 1.8536e-03 eta: 10:24:37 time: 0.4985 data_time: 0.0150 memory: 14901 loss: 1.7747 loss_prob: 1.0110 loss_thr: 0.5969 loss_db: 0.1668 2022/11/02 14:09:35 - mmengine - INFO - Epoch(train) [190][60/63] lr: 1.8536e-03 eta: 10:24:24 time: 0.4682 data_time: 0.0088 memory: 14901 loss: 1.8467 loss_prob: 1.0581 loss_thr: 0.6123 loss_db: 0.1763 2022/11/02 14:09:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:09:42 - mmengine - INFO - Epoch(train) [191][5/63] lr: 1.8520e-03 eta: 10:24:24 time: 0.8393 data_time: 0.2423 memory: 14901 loss: 1.8700 loss_prob: 1.1009 loss_thr: 0.5882 loss_db: 0.1809 2022/11/02 14:09:45 - mmengine - INFO - Epoch(train) [191][10/63] lr: 1.8520e-03 eta: 10:24:23 time: 0.8881 data_time: 0.2410 memory: 14901 loss: 1.6841 loss_prob: 0.9560 loss_thr: 0.5700 loss_db: 0.1581 2022/11/02 14:09:47 - mmengine - INFO - Epoch(train) [191][15/63] lr: 1.8520e-03 eta: 10:24:23 time: 0.5213 data_time: 0.0044 memory: 14901 loss: 1.7553 loss_prob: 0.9996 loss_thr: 0.5866 loss_db: 0.1692 2022/11/02 14:09:50 - mmengine - INFO - Epoch(train) [191][20/63] lr: 1.8520e-03 eta: 10:24:12 time: 0.4912 data_time: 0.0056 memory: 14901 loss: 1.9029 loss_prob: 1.1193 loss_thr: 0.6007 loss_db: 0.1829 2022/11/02 14:09:53 - mmengine - INFO - Epoch(train) [191][25/63] lr: 1.8520e-03 eta: 10:24:12 time: 0.5242 data_time: 0.0269 memory: 14901 loss: 1.9514 loss_prob: 1.1592 loss_thr: 0.6084 loss_db: 0.1838 2022/11/02 14:09:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:09:55 - mmengine - INFO - Epoch(train) [191][30/63] lr: 1.8520e-03 eta: 10:24:04 time: 0.5551 data_time: 0.0464 memory: 14901 loss: 1.8445 loss_prob: 1.0729 loss_thr: 0.5967 loss_db: 0.1750 2022/11/02 14:09:58 - mmengine - INFO - Epoch(train) [191][35/63] lr: 1.8520e-03 eta: 10:24:04 time: 0.5100 data_time: 0.0251 memory: 14901 loss: 1.8574 loss_prob: 1.0821 loss_thr: 0.5975 loss_db: 0.1778 2022/11/02 14:10:00 - mmengine - INFO - Epoch(train) [191][40/63] lr: 1.8520e-03 eta: 10:23:54 time: 0.4971 data_time: 0.0047 memory: 14901 loss: 1.8729 loss_prob: 1.0866 loss_thr: 0.6108 loss_db: 0.1755 2022/11/02 14:10:03 - mmengine - INFO - Epoch(train) [191][45/63] lr: 1.8520e-03 eta: 10:23:54 time: 0.4912 data_time: 0.0053 memory: 14901 loss: 1.7825 loss_prob: 1.0178 loss_thr: 0.5970 loss_db: 0.1677 2022/11/02 14:10:05 - mmengine - INFO - Epoch(train) [191][50/63] lr: 1.8520e-03 eta: 10:23:41 time: 0.4641 data_time: 0.0163 memory: 14901 loss: 1.8983 loss_prob: 1.1019 loss_thr: 0.6163 loss_db: 0.1801 2022/11/02 14:10:07 - mmengine - INFO - Epoch(train) [191][55/63] lr: 1.8520e-03 eta: 10:23:41 time: 0.4798 data_time: 0.0213 memory: 14901 loss: 2.0518 loss_prob: 1.2027 loss_thr: 0.6528 loss_db: 0.1963 2022/11/02 14:10:10 - mmengine - INFO - Epoch(train) [191][60/63] lr: 1.8520e-03 eta: 10:23:29 time: 0.4660 data_time: 0.0102 memory: 14901 loss: 2.1239 loss_prob: 1.2491 loss_thr: 0.6705 loss_db: 0.2043 2022/11/02 14:10:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:10:16 - mmengine - INFO - Epoch(train) [192][5/63] lr: 1.8503e-03 eta: 10:23:29 time: 0.7209 data_time: 0.2330 memory: 14901 loss: 1.8656 loss_prob: 1.0682 loss_thr: 0.6183 loss_db: 0.1791 2022/11/02 14:10:19 - mmengine - INFO - Epoch(train) [192][10/63] lr: 1.8503e-03 eta: 10:23:25 time: 0.8365 data_time: 0.2344 memory: 14901 loss: 1.9897 loss_prob: 1.1837 loss_thr: 0.6042 loss_db: 0.2019 2022/11/02 14:10:22 - mmengine - INFO - Epoch(train) [192][15/63] lr: 1.8503e-03 eta: 10:23:25 time: 0.6016 data_time: 0.0064 memory: 14901 loss: 2.0647 loss_prob: 1.2555 loss_thr: 0.6014 loss_db: 0.2078 2022/11/02 14:10:24 - mmengine - INFO - Epoch(train) [192][20/63] lr: 1.8503e-03 eta: 10:23:16 time: 0.5283 data_time: 0.0054 memory: 14901 loss: 2.0298 loss_prob: 1.2128 loss_thr: 0.6188 loss_db: 0.1983 2022/11/02 14:10:27 - mmengine - INFO - Epoch(train) [192][25/63] lr: 1.8503e-03 eta: 10:23:16 time: 0.5113 data_time: 0.0158 memory: 14901 loss: 2.0395 loss_prob: 1.1945 loss_thr: 0.6460 loss_db: 0.1989 2022/11/02 14:10:30 - mmengine - INFO - Epoch(train) [192][30/63] lr: 1.8503e-03 eta: 10:23:06 time: 0.5121 data_time: 0.0376 memory: 14901 loss: 2.1677 loss_prob: 1.2977 loss_thr: 0.6583 loss_db: 0.2118 2022/11/02 14:10:32 - mmengine - INFO - Epoch(train) [192][35/63] lr: 1.8503e-03 eta: 10:23:06 time: 0.5387 data_time: 0.0275 memory: 14901 loss: 2.1811 loss_prob: 1.3254 loss_thr: 0.6443 loss_db: 0.2114 2022/11/02 14:10:35 - mmengine - INFO - Epoch(train) [192][40/63] lr: 1.8503e-03 eta: 10:22:57 time: 0.5347 data_time: 0.0058 memory: 14901 loss: 1.9203 loss_prob: 1.1290 loss_thr: 0.6087 loss_db: 0.1826 2022/11/02 14:10:38 - mmengine - INFO - Epoch(train) [192][45/63] lr: 1.8503e-03 eta: 10:22:57 time: 0.5496 data_time: 0.0057 memory: 14901 loss: 1.8049 loss_prob: 1.0324 loss_thr: 0.6027 loss_db: 0.1698 2022/11/02 14:10:41 - mmengine - INFO - Epoch(train) [192][50/63] lr: 1.8503e-03 eta: 10:22:51 time: 0.5821 data_time: 0.0215 memory: 14901 loss: 2.0550 loss_prob: 1.2147 loss_thr: 0.6422 loss_db: 0.1981 2022/11/02 14:10:43 - mmengine - INFO - Epoch(train) [192][55/63] lr: 1.8503e-03 eta: 10:22:51 time: 0.5130 data_time: 0.0232 memory: 14901 loss: 2.1723 loss_prob: 1.2998 loss_thr: 0.6626 loss_db: 0.2099 2022/11/02 14:10:46 - mmengine - INFO - Epoch(train) [192][60/63] lr: 1.8503e-03 eta: 10:22:41 time: 0.5166 data_time: 0.0071 memory: 14901 loss: 2.0369 loss_prob: 1.1902 loss_thr: 0.6547 loss_db: 0.1920 2022/11/02 14:10:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:10:57 - mmengine - INFO - Epoch(train) [193][5/63] lr: 1.8487e-03 eta: 10:22:41 time: 1.2482 data_time: 0.2453 memory: 14901 loss: 1.8608 loss_prob: 1.0783 loss_thr: 0.6046 loss_db: 0.1779 2022/11/02 14:11:00 - mmengine - INFO - Epoch(train) [193][10/63] lr: 1.8487e-03 eta: 10:23:00 time: 1.2685 data_time: 0.2515 memory: 14901 loss: 1.8634 loss_prob: 1.0794 loss_thr: 0.6047 loss_db: 0.1792 2022/11/02 14:11:04 - mmengine - INFO - Epoch(train) [193][15/63] lr: 1.8487e-03 eta: 10:23:00 time: 0.7035 data_time: 0.0159 memory: 14901 loss: 1.8004 loss_prob: 1.0263 loss_thr: 0.6027 loss_db: 0.1714 2022/11/02 14:11:07 - mmengine - INFO - Epoch(train) [193][20/63] lr: 1.8487e-03 eta: 10:22:58 time: 0.6553 data_time: 0.0130 memory: 14901 loss: 1.9369 loss_prob: 1.1218 loss_thr: 0.6299 loss_db: 0.1852 2022/11/02 14:11:10 - mmengine - INFO - Epoch(train) [193][25/63] lr: 1.8487e-03 eta: 10:22:58 time: 0.5828 data_time: 0.0206 memory: 14901 loss: 1.9794 loss_prob: 1.1377 loss_thr: 0.6531 loss_db: 0.1885 2022/11/02 14:11:13 - mmengine - INFO - Epoch(train) [193][30/63] lr: 1.8487e-03 eta: 10:22:51 time: 0.5723 data_time: 0.0410 memory: 14901 loss: 1.8511 loss_prob: 1.0459 loss_thr: 0.6307 loss_db: 0.1745 2022/11/02 14:11:16 - mmengine - INFO - Epoch(train) [193][35/63] lr: 1.8487e-03 eta: 10:22:51 time: 0.5791 data_time: 0.0300 memory: 14901 loss: 1.9165 loss_prob: 1.1052 loss_thr: 0.6290 loss_db: 0.1824 2022/11/02 14:11:18 - mmengine - INFO - Epoch(train) [193][40/63] lr: 1.8487e-03 eta: 10:22:45 time: 0.5853 data_time: 0.0096 memory: 14901 loss: 1.9982 loss_prob: 1.1636 loss_thr: 0.6428 loss_db: 0.1918 2022/11/02 14:11:22 - mmengine - INFO - Epoch(train) [193][45/63] lr: 1.8487e-03 eta: 10:22:45 time: 0.5866 data_time: 0.0157 memory: 14901 loss: 1.9394 loss_prob: 1.1335 loss_thr: 0.6187 loss_db: 0.1871 2022/11/02 14:11:25 - mmengine - INFO - Epoch(train) [193][50/63] lr: 1.8487e-03 eta: 10:22:41 time: 0.6224 data_time: 0.0399 memory: 14901 loss: 1.7841 loss_prob: 1.0173 loss_thr: 0.6007 loss_db: 0.1661 2022/11/02 14:11:28 - mmengine - INFO - Epoch(train) [193][55/63] lr: 1.8487e-03 eta: 10:22:41 time: 0.6029 data_time: 0.0399 memory: 14901 loss: 1.7531 loss_prob: 0.9834 loss_thr: 0.6083 loss_db: 0.1615 2022/11/02 14:11:30 - mmengine - INFO - Epoch(train) [193][60/63] lr: 1.8487e-03 eta: 10:22:34 time: 0.5675 data_time: 0.0169 memory: 14901 loss: 1.7981 loss_prob: 1.0242 loss_thr: 0.6041 loss_db: 0.1698 2022/11/02 14:11:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:11:41 - mmengine - INFO - Epoch(train) [194][5/63] lr: 1.8470e-03 eta: 10:22:34 time: 1.1638 data_time: 0.2466 memory: 14901 loss: 1.9119 loss_prob: 1.0985 loss_thr: 0.6317 loss_db: 0.1816 2022/11/02 14:11:45 - mmengine - INFO - Epoch(train) [194][10/63] lr: 1.8470e-03 eta: 10:22:53 time: 1.2897 data_time: 0.2596 memory: 14901 loss: 1.9580 loss_prob: 1.1348 loss_thr: 0.6378 loss_db: 0.1854 2022/11/02 14:11:48 - mmengine - INFO - Epoch(train) [194][15/63] lr: 1.8470e-03 eta: 10:22:53 time: 0.7341 data_time: 0.0361 memory: 14901 loss: 1.8393 loss_prob: 1.0585 loss_thr: 0.6096 loss_db: 0.1712 2022/11/02 14:11:51 - mmengine - INFO - Epoch(train) [194][20/63] lr: 1.8470e-03 eta: 10:22:49 time: 0.6250 data_time: 0.0200 memory: 14901 loss: 1.8020 loss_prob: 1.0384 loss_thr: 0.5982 loss_db: 0.1654 2022/11/02 14:11:55 - mmengine - INFO - Epoch(train) [194][25/63] lr: 1.8470e-03 eta: 10:22:49 time: 0.6258 data_time: 0.0135 memory: 14901 loss: 1.7985 loss_prob: 1.0277 loss_thr: 0.6029 loss_db: 0.1680 2022/11/02 14:11:59 - mmengine - INFO - Epoch(train) [194][30/63] lr: 1.8470e-03 eta: 10:22:54 time: 0.7839 data_time: 0.0312 memory: 14901 loss: 1.8353 loss_prob: 1.0539 loss_thr: 0.6044 loss_db: 0.1770 2022/11/02 14:12:02 - mmengine - INFO - Epoch(train) [194][35/63] lr: 1.8470e-03 eta: 10:22:54 time: 0.7768 data_time: 0.0495 memory: 14901 loss: 2.1056 loss_prob: 1.2578 loss_thr: 0.6439 loss_db: 0.2039 2022/11/02 14:12:06 - mmengine - INFO - Epoch(train) [194][40/63] lr: 1.8470e-03 eta: 10:22:55 time: 0.7281 data_time: 0.0336 memory: 14901 loss: 2.1860 loss_prob: 1.3034 loss_thr: 0.6696 loss_db: 0.2129 2022/11/02 14:12:10 - mmengine - INFO - Epoch(train) [194][45/63] lr: 1.8470e-03 eta: 10:22:55 time: 0.7829 data_time: 0.0122 memory: 14901 loss: 2.0273 loss_prob: 1.1862 loss_thr: 0.6393 loss_db: 0.2018 2022/11/02 14:12:13 - mmengine - INFO - Epoch(train) [194][50/63] lr: 1.8470e-03 eta: 10:22:55 time: 0.7023 data_time: 0.0202 memory: 14901 loss: 2.0663 loss_prob: 1.2294 loss_thr: 0.6337 loss_db: 0.2032 2022/11/02 14:12:17 - mmengine - INFO - Epoch(train) [194][55/63] lr: 1.8470e-03 eta: 10:22:55 time: 0.7085 data_time: 0.0324 memory: 14901 loss: 2.2286 loss_prob: 1.3535 loss_thr: 0.6597 loss_db: 0.2154 2022/11/02 14:12:21 - mmengine - INFO - Epoch(train) [194][60/63] lr: 1.8470e-03 eta: 10:22:57 time: 0.7420 data_time: 0.0234 memory: 14901 loss: 2.1945 loss_prob: 1.3261 loss_thr: 0.6530 loss_db: 0.2154 2022/11/02 14:12:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:12:30 - mmengine - INFO - Epoch(train) [195][5/63] lr: 1.8454e-03 eta: 10:22:57 time: 1.0785 data_time: 0.2399 memory: 14901 loss: 2.1522 loss_prob: 1.2981 loss_thr: 0.6455 loss_db: 0.2087 2022/11/02 14:12:33 - mmengine - INFO - Epoch(train) [195][10/63] lr: 1.8454e-03 eta: 10:23:05 time: 1.0635 data_time: 0.2416 memory: 14901 loss: 2.2603 loss_prob: 1.3854 loss_thr: 0.6517 loss_db: 0.2232 2022/11/02 14:12:36 - mmengine - INFO - Epoch(train) [195][15/63] lr: 1.8454e-03 eta: 10:23:05 time: 0.6453 data_time: 0.0175 memory: 14901 loss: 2.1226 loss_prob: 1.2793 loss_thr: 0.6374 loss_db: 0.2059 2022/11/02 14:12:39 - mmengine - INFO - Epoch(train) [195][20/63] lr: 1.8454e-03 eta: 10:23:00 time: 0.6226 data_time: 0.0154 memory: 14901 loss: 2.0038 loss_prob: 1.1802 loss_thr: 0.6346 loss_db: 0.1890 2022/11/02 14:12:42 - mmengine - INFO - Epoch(train) [195][25/63] lr: 1.8454e-03 eta: 10:23:00 time: 0.5483 data_time: 0.0138 memory: 14901 loss: 1.9917 loss_prob: 1.1753 loss_thr: 0.6259 loss_db: 0.1904 2022/11/02 14:12:45 - mmengine - INFO - Epoch(train) [195][30/63] lr: 1.8454e-03 eta: 10:22:55 time: 0.5952 data_time: 0.0417 memory: 14901 loss: 1.9354 loss_prob: 1.1155 loss_thr: 0.6402 loss_db: 0.1797 2022/11/02 14:12:48 - mmengine - INFO - Epoch(train) [195][35/63] lr: 1.8454e-03 eta: 10:22:55 time: 0.6000 data_time: 0.0370 memory: 14901 loss: 1.8312 loss_prob: 1.0367 loss_thr: 0.6270 loss_db: 0.1675 2022/11/02 14:12:51 - mmengine - INFO - Epoch(train) [195][40/63] lr: 1.8454e-03 eta: 10:22:48 time: 0.5752 data_time: 0.0107 memory: 14901 loss: 1.7692 loss_prob: 1.0017 loss_thr: 0.6034 loss_db: 0.1641 2022/11/02 14:12:54 - mmengine - INFO - Epoch(train) [195][45/63] lr: 1.8454e-03 eta: 10:22:48 time: 0.6009 data_time: 0.0125 memory: 14901 loss: 1.7661 loss_prob: 0.9921 loss_thr: 0.6085 loss_db: 0.1655 2022/11/02 14:12:57 - mmengine - INFO - Epoch(train) [195][50/63] lr: 1.8454e-03 eta: 10:22:44 time: 0.6166 data_time: 0.0146 memory: 14901 loss: 1.8070 loss_prob: 1.0201 loss_thr: 0.6161 loss_db: 0.1709 2022/11/02 14:13:00 - mmengine - INFO - Epoch(train) [195][55/63] lr: 1.8454e-03 eta: 10:22:44 time: 0.6393 data_time: 0.0233 memory: 14901 loss: 1.8945 loss_prob: 1.1049 loss_thr: 0.6055 loss_db: 0.1841 2022/11/02 14:13:03 - mmengine - INFO - Epoch(train) [195][60/63] lr: 1.8454e-03 eta: 10:22:36 time: 0.5656 data_time: 0.0166 memory: 14901 loss: 2.1639 loss_prob: 1.3209 loss_thr: 0.6356 loss_db: 0.2074 2022/11/02 14:13:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:13:10 - mmengine - INFO - Epoch(train) [196][5/63] lr: 1.8437e-03 eta: 10:22:36 time: 0.8379 data_time: 0.2489 memory: 14901 loss: 1.9033 loss_prob: 1.1246 loss_thr: 0.5926 loss_db: 0.1861 2022/11/02 14:13:13 - mmengine - INFO - Epoch(train) [196][10/63] lr: 1.8437e-03 eta: 10:22:36 time: 0.9057 data_time: 0.2466 memory: 14901 loss: 1.8997 loss_prob: 1.0917 loss_thr: 0.6250 loss_db: 0.1829 2022/11/02 14:13:16 - mmengine - INFO - Epoch(train) [196][15/63] lr: 1.8437e-03 eta: 10:22:36 time: 0.5746 data_time: 0.0066 memory: 14901 loss: 1.9975 loss_prob: 1.1638 loss_thr: 0.6477 loss_db: 0.1860 2022/11/02 14:13:19 - mmengine - INFO - Epoch(train) [196][20/63] lr: 1.8437e-03 eta: 10:22:27 time: 0.5352 data_time: 0.0114 memory: 14901 loss: 1.9387 loss_prob: 1.1438 loss_thr: 0.6124 loss_db: 0.1825 2022/11/02 14:13:21 - mmengine - INFO - Epoch(train) [196][25/63] lr: 1.8437e-03 eta: 10:22:27 time: 0.5414 data_time: 0.0402 memory: 14901 loss: 1.8597 loss_prob: 1.0829 loss_thr: 0.5999 loss_db: 0.1769 2022/11/02 14:13:24 - mmengine - INFO - Epoch(train) [196][30/63] lr: 1.8437e-03 eta: 10:22:20 time: 0.5662 data_time: 0.0652 memory: 14901 loss: 1.8142 loss_prob: 1.0379 loss_thr: 0.6049 loss_db: 0.1715 2022/11/02 14:13:27 - mmengine - INFO - Epoch(train) [196][35/63] lr: 1.8437e-03 eta: 10:22:20 time: 0.5479 data_time: 0.0368 memory: 14901 loss: 1.9300 loss_prob: 1.1113 loss_thr: 0.6323 loss_db: 0.1864 2022/11/02 14:13:30 - mmengine - INFO - Epoch(train) [196][40/63] lr: 1.8437e-03 eta: 10:22:12 time: 0.5400 data_time: 0.0100 memory: 14901 loss: 1.9229 loss_prob: 1.1129 loss_thr: 0.6248 loss_db: 0.1851 2022/11/02 14:13:32 - mmengine - INFO - Epoch(train) [196][45/63] lr: 1.8437e-03 eta: 10:22:12 time: 0.5197 data_time: 0.0135 memory: 14901 loss: 1.8069 loss_prob: 1.0378 loss_thr: 0.5984 loss_db: 0.1707 2022/11/02 14:13:35 - mmengine - INFO - Epoch(train) [196][50/63] lr: 1.8437e-03 eta: 10:22:01 time: 0.4984 data_time: 0.0229 memory: 14901 loss: 1.8706 loss_prob: 1.0780 loss_thr: 0.6138 loss_db: 0.1788 2022/11/02 14:13:38 - mmengine - INFO - Epoch(train) [196][55/63] lr: 1.8437e-03 eta: 10:22:01 time: 0.5521 data_time: 0.0306 memory: 14901 loss: 1.7886 loss_prob: 1.0196 loss_thr: 0.5985 loss_db: 0.1706 2022/11/02 14:13:40 - mmengine - INFO - Epoch(train) [196][60/63] lr: 1.8437e-03 eta: 10:21:54 time: 0.5614 data_time: 0.0176 memory: 14901 loss: 1.7612 loss_prob: 1.0202 loss_thr: 0.5718 loss_db: 0.1692 2022/11/02 14:13:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:13:47 - mmengine - INFO - Epoch(train) [197][5/63] lr: 1.8421e-03 eta: 10:21:54 time: 0.7888 data_time: 0.2292 memory: 14901 loss: 1.7938 loss_prob: 1.0165 loss_thr: 0.6118 loss_db: 0.1655 2022/11/02 14:13:51 - mmengine - INFO - Epoch(train) [197][10/63] lr: 1.8421e-03 eta: 10:21:53 time: 0.9045 data_time: 0.2438 memory: 14901 loss: 1.8316 loss_prob: 1.0459 loss_thr: 0.6175 loss_db: 0.1682 2022/11/02 14:13:53 - mmengine - INFO - Epoch(train) [197][15/63] lr: 1.8421e-03 eta: 10:21:53 time: 0.6064 data_time: 0.0237 memory: 14901 loss: 1.8491 loss_prob: 1.0805 loss_thr: 0.5978 loss_db: 0.1708 2022/11/02 14:13:56 - mmengine - INFO - Epoch(train) [197][20/63] lr: 1.8421e-03 eta: 10:21:46 time: 0.5636 data_time: 0.0101 memory: 14901 loss: 1.8055 loss_prob: 1.0560 loss_thr: 0.5801 loss_db: 0.1694 2022/11/02 14:13:59 - mmengine - INFO - Epoch(train) [197][25/63] lr: 1.8421e-03 eta: 10:21:46 time: 0.5971 data_time: 0.0159 memory: 14901 loss: 1.7786 loss_prob: 1.0104 loss_thr: 0.6002 loss_db: 0.1679 2022/11/02 14:14:02 - mmengine - INFO - Epoch(train) [197][30/63] lr: 1.8421e-03 eta: 10:21:39 time: 0.5740 data_time: 0.0337 memory: 14901 loss: 2.1337 loss_prob: 1.2911 loss_thr: 0.6318 loss_db: 0.2108 2022/11/02 14:14:05 - mmengine - INFO - Epoch(train) [197][35/63] lr: 1.8421e-03 eta: 10:21:39 time: 0.5556 data_time: 0.0345 memory: 14901 loss: 2.2015 loss_prob: 1.3627 loss_thr: 0.6209 loss_db: 0.2179 2022/11/02 14:14:08 - mmengine - INFO - Epoch(train) [197][40/63] lr: 1.8421e-03 eta: 10:21:31 time: 0.5538 data_time: 0.0154 memory: 14901 loss: 1.9683 loss_prob: 1.1694 loss_thr: 0.6163 loss_db: 0.1826 2022/11/02 14:14:10 - mmengine - INFO - Epoch(train) [197][45/63] lr: 1.8421e-03 eta: 10:21:31 time: 0.5266 data_time: 0.0079 memory: 14901 loss: 1.9365 loss_prob: 1.1261 loss_thr: 0.6290 loss_db: 0.1814 2022/11/02 14:14:13 - mmengine - INFO - Epoch(train) [197][50/63] lr: 1.8421e-03 eta: 10:21:22 time: 0.5268 data_time: 0.0239 memory: 14901 loss: 1.8645 loss_prob: 1.0713 loss_thr: 0.6151 loss_db: 0.1782 2022/11/02 14:14:15 - mmengine - INFO - Epoch(train) [197][55/63] lr: 1.8421e-03 eta: 10:21:22 time: 0.5362 data_time: 0.0277 memory: 14901 loss: 1.8935 loss_prob: 1.0983 loss_thr: 0.6143 loss_db: 0.1809 2022/11/02 14:14:18 - mmengine - INFO - Epoch(train) [197][60/63] lr: 1.8421e-03 eta: 10:21:14 time: 0.5453 data_time: 0.0143 memory: 14901 loss: 1.8618 loss_prob: 1.0740 loss_thr: 0.6105 loss_db: 0.1773 2022/11/02 14:14:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:14:25 - mmengine - INFO - Epoch(train) [198][5/63] lr: 1.8404e-03 eta: 10:21:14 time: 0.8283 data_time: 0.3011 memory: 14901 loss: 1.9192 loss_prob: 1.0910 loss_thr: 0.6481 loss_db: 0.1800 2022/11/02 14:14:28 - mmengine - INFO - Epoch(train) [198][10/63] lr: 1.8404e-03 eta: 10:21:11 time: 0.8643 data_time: 0.2983 memory: 14901 loss: 1.8972 loss_prob: 1.0673 loss_thr: 0.6558 loss_db: 0.1741 2022/11/02 14:14:31 - mmengine - INFO - Epoch(train) [198][15/63] lr: 1.8404e-03 eta: 10:21:11 time: 0.5845 data_time: 0.0104 memory: 14901 loss: 1.8036 loss_prob: 1.0351 loss_thr: 0.5954 loss_db: 0.1731 2022/11/02 14:14:34 - mmengine - INFO - Epoch(train) [198][20/63] lr: 1.8404e-03 eta: 10:21:07 time: 0.6244 data_time: 0.0190 memory: 14901 loss: 1.8900 loss_prob: 1.1094 loss_thr: 0.5975 loss_db: 0.1831 2022/11/02 14:14:38 - mmengine - INFO - Epoch(train) [198][25/63] lr: 1.8404e-03 eta: 10:21:07 time: 0.6553 data_time: 0.0458 memory: 14901 loss: 1.8278 loss_prob: 1.0683 loss_thr: 0.5874 loss_db: 0.1721 2022/11/02 14:14:41 - mmengine - INFO - Epoch(train) [198][30/63] lr: 1.8404e-03 eta: 10:21:02 time: 0.6053 data_time: 0.0355 memory: 14901 loss: 1.8008 loss_prob: 1.0379 loss_thr: 0.5919 loss_db: 0.1710 2022/11/02 14:14:43 - mmengine - INFO - Epoch(train) [198][35/63] lr: 1.8404e-03 eta: 10:21:02 time: 0.5366 data_time: 0.0075 memory: 14901 loss: 1.9093 loss_prob: 1.0954 loss_thr: 0.6334 loss_db: 0.1806 2022/11/02 14:14:46 - mmengine - INFO - Epoch(train) [198][40/63] lr: 1.8404e-03 eta: 10:20:53 time: 0.5258 data_time: 0.0105 memory: 14901 loss: 1.9268 loss_prob: 1.1110 loss_thr: 0.6321 loss_db: 0.1837 2022/11/02 14:14:48 - mmengine - INFO - Epoch(train) [198][45/63] lr: 1.8404e-03 eta: 10:20:53 time: 0.5029 data_time: 0.0184 memory: 14901 loss: 1.8610 loss_prob: 1.0654 loss_thr: 0.6201 loss_db: 0.1755 2022/11/02 14:14:51 - mmengine - INFO - Epoch(train) [198][50/63] lr: 1.8404e-03 eta: 10:20:45 time: 0.5503 data_time: 0.0292 memory: 14901 loss: 1.8218 loss_prob: 1.0234 loss_thr: 0.6281 loss_db: 0.1704 2022/11/02 14:14:54 - mmengine - INFO - Epoch(train) [198][55/63] lr: 1.8404e-03 eta: 10:20:45 time: 0.5810 data_time: 0.0222 memory: 14901 loss: 1.9328 loss_prob: 1.1207 loss_thr: 0.6240 loss_db: 0.1882 2022/11/02 14:14:57 - mmengine - INFO - Epoch(train) [198][60/63] lr: 1.8404e-03 eta: 10:20:38 time: 0.5617 data_time: 0.0104 memory: 14901 loss: 2.0287 loss_prob: 1.2145 loss_thr: 0.6123 loss_db: 0.2019 2022/11/02 14:14:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:15:03 - mmengine - INFO - Epoch(train) [199][5/63] lr: 1.8388e-03 eta: 10:20:38 time: 0.7242 data_time: 0.2456 memory: 14901 loss: 1.9457 loss_prob: 1.1494 loss_thr: 0.6176 loss_db: 0.1787 2022/11/02 14:15:06 - mmengine - INFO - Epoch(train) [199][10/63] lr: 1.8388e-03 eta: 10:20:30 time: 0.7575 data_time: 0.2475 memory: 14901 loss: 2.0479 loss_prob: 1.1894 loss_thr: 0.6682 loss_db: 0.1903 2022/11/02 14:15:09 - mmengine - INFO - Epoch(train) [199][15/63] lr: 1.8388e-03 eta: 10:20:30 time: 0.6409 data_time: 0.0117 memory: 14901 loss: 2.0675 loss_prob: 1.2121 loss_thr: 0.6546 loss_db: 0.2008 2022/11/02 14:15:12 - mmengine - INFO - Epoch(train) [199][20/63] lr: 1.8388e-03 eta: 10:20:25 time: 0.6241 data_time: 0.0083 memory: 14901 loss: 2.0680 loss_prob: 1.2229 loss_thr: 0.6454 loss_db: 0.1998 2022/11/02 14:15:15 - mmengine - INFO - Epoch(train) [199][25/63] lr: 1.8388e-03 eta: 10:20:25 time: 0.5377 data_time: 0.0109 memory: 14901 loss: 1.9758 loss_prob: 1.1508 loss_thr: 0.6388 loss_db: 0.1862 2022/11/02 14:15:18 - mmengine - INFO - Epoch(train) [199][30/63] lr: 1.8388e-03 eta: 10:20:19 time: 0.5730 data_time: 0.0349 memory: 14901 loss: 1.9437 loss_prob: 1.1311 loss_thr: 0.6264 loss_db: 0.1863 2022/11/02 14:15:20 - mmengine - INFO - Epoch(train) [199][35/63] lr: 1.8388e-03 eta: 10:20:19 time: 0.5344 data_time: 0.0306 memory: 14901 loss: 1.9190 loss_prob: 1.1151 loss_thr: 0.6200 loss_db: 0.1839 2022/11/02 14:15:23 - mmengine - INFO - Epoch(train) [199][40/63] lr: 1.8388e-03 eta: 10:20:09 time: 0.5139 data_time: 0.0098 memory: 14901 loss: 2.0555 loss_prob: 1.2286 loss_thr: 0.6307 loss_db: 0.1962 2022/11/02 14:15:25 - mmengine - INFO - Epoch(train) [199][45/63] lr: 1.8388e-03 eta: 10:20:09 time: 0.5252 data_time: 0.0103 memory: 14901 loss: 2.1755 loss_prob: 1.3197 loss_thr: 0.6437 loss_db: 0.2120 2022/11/02 14:15:28 - mmengine - INFO - Epoch(train) [199][50/63] lr: 1.8388e-03 eta: 10:20:01 time: 0.5599 data_time: 0.0264 memory: 14901 loss: 1.9153 loss_prob: 1.1255 loss_thr: 0.6018 loss_db: 0.1880 2022/11/02 14:15:31 - mmengine - INFO - Epoch(train) [199][55/63] lr: 1.8388e-03 eta: 10:20:01 time: 0.5707 data_time: 0.0330 memory: 14901 loss: 1.7758 loss_prob: 1.0273 loss_thr: 0.5810 loss_db: 0.1675 2022/11/02 14:15:34 - mmengine - INFO - Epoch(train) [199][60/63] lr: 1.8388e-03 eta: 10:19:55 time: 0.5705 data_time: 0.0152 memory: 14901 loss: 1.8258 loss_prob: 1.0722 loss_thr: 0.5795 loss_db: 0.1740 2022/11/02 14:15:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:15:41 - mmengine - INFO - Epoch(train) [200][5/63] lr: 1.8371e-03 eta: 10:19:55 time: 0.7682 data_time: 0.2284 memory: 14901 loss: 1.7906 loss_prob: 1.0224 loss_thr: 0.5981 loss_db: 0.1701 2022/11/02 14:15:43 - mmengine - INFO - Epoch(train) [200][10/63] lr: 1.8371e-03 eta: 10:19:46 time: 0.7560 data_time: 0.2365 memory: 14901 loss: 1.9343 loss_prob: 1.1201 loss_thr: 0.6329 loss_db: 0.1813 2022/11/02 14:15:46 - mmengine - INFO - Epoch(train) [200][15/63] lr: 1.8371e-03 eta: 10:19:46 time: 0.5600 data_time: 0.0205 memory: 14901 loss: 1.9286 loss_prob: 1.1203 loss_thr: 0.6238 loss_db: 0.1845 2022/11/02 14:15:50 - mmengine - INFO - Epoch(train) [200][20/63] lr: 1.8371e-03 eta: 10:19:43 time: 0.6414 data_time: 0.0106 memory: 14901 loss: 1.9027 loss_prob: 1.0934 loss_thr: 0.6315 loss_db: 0.1778 2022/11/02 14:15:52 - mmengine - INFO - Epoch(train) [200][25/63] lr: 1.8371e-03 eta: 10:19:43 time: 0.5944 data_time: 0.0163 memory: 14901 loss: 1.9391 loss_prob: 1.1271 loss_thr: 0.6315 loss_db: 0.1805 2022/11/02 14:15:55 - mmengine - INFO - Epoch(train) [200][30/63] lr: 1.8371e-03 eta: 10:19:35 time: 0.5375 data_time: 0.0441 memory: 14901 loss: 1.8822 loss_prob: 1.1022 loss_thr: 0.6015 loss_db: 0.1786 2022/11/02 14:15:58 - mmengine - INFO - Epoch(train) [200][35/63] lr: 1.8371e-03 eta: 10:19:35 time: 0.5439 data_time: 0.0363 memory: 14901 loss: 1.8226 loss_prob: 1.0604 loss_thr: 0.5898 loss_db: 0.1724 2022/11/02 14:16:00 - mmengine - INFO - Epoch(train) [200][40/63] lr: 1.8371e-03 eta: 10:19:26 time: 0.5297 data_time: 0.0104 memory: 14901 loss: 1.8623 loss_prob: 1.0731 loss_thr: 0.6124 loss_db: 0.1768 2022/11/02 14:16:03 - mmengine - INFO - Epoch(train) [200][45/63] lr: 1.8371e-03 eta: 10:19:26 time: 0.5441 data_time: 0.0132 memory: 14901 loss: 1.9072 loss_prob: 1.1036 loss_thr: 0.6203 loss_db: 0.1833 2022/11/02 14:16:05 - mmengine - INFO - Epoch(train) [200][50/63] lr: 1.8371e-03 eta: 10:19:16 time: 0.5179 data_time: 0.0173 memory: 14901 loss: 1.8296 loss_prob: 1.0559 loss_thr: 0.6007 loss_db: 0.1729 2022/11/02 14:16:08 - mmengine - INFO - Epoch(train) [200][55/63] lr: 1.8371e-03 eta: 10:19:16 time: 0.5061 data_time: 0.0236 memory: 14901 loss: 1.7577 loss_prob: 1.0111 loss_thr: 0.5799 loss_db: 0.1668 2022/11/02 14:16:11 - mmengine - INFO - Epoch(train) [200][60/63] lr: 1.8371e-03 eta: 10:19:07 time: 0.5269 data_time: 0.0205 memory: 14901 loss: 1.8048 loss_prob: 1.0345 loss_thr: 0.5991 loss_db: 0.1712 2022/11/02 14:16:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:16:12 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/11/02 14:16:16 - mmengine - INFO - Epoch(val) [200][5/500] eta: 10:19:07 time: 0.0467 data_time: 0.0053 memory: 14901 2022/11/02 14:16:16 - mmengine - INFO - Epoch(val) [200][10/500] eta: 0:00:22 time: 0.0459 data_time: 0.0051 memory: 1008 2022/11/02 14:16:16 - mmengine - INFO - Epoch(val) [200][15/500] eta: 0:00:22 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/02 14:16:16 - mmengine - INFO - Epoch(val) [200][20/500] eta: 0:00:18 time: 0.0388 data_time: 0.0025 memory: 1008 2022/11/02 14:16:17 - mmengine - INFO - Epoch(val) [200][25/500] eta: 0:00:18 time: 0.0362 data_time: 0.0025 memory: 1008 2022/11/02 14:16:17 - mmengine - INFO - Epoch(val) [200][30/500] eta: 0:00:18 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 14:16:17 - mmengine - INFO - Epoch(val) [200][35/500] eta: 0:00:18 time: 0.0410 data_time: 0.0024 memory: 1008 2022/11/02 14:16:17 - mmengine - INFO - Epoch(val) [200][40/500] eta: 0:00:18 time: 0.0412 data_time: 0.0023 memory: 1008 2022/11/02 14:16:17 - mmengine - INFO - Epoch(val) [200][45/500] eta: 0:00:18 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 14:16:18 - mmengine - INFO - Epoch(val) [200][50/500] eta: 0:00:18 time: 0.0410 data_time: 0.0025 memory: 1008 2022/11/02 14:16:18 - mmengine - INFO - Epoch(val) [200][55/500] eta: 0:00:18 time: 0.0458 data_time: 0.0027 memory: 1008 2022/11/02 14:16:18 - mmengine - INFO - Epoch(val) [200][60/500] eta: 0:00:19 time: 0.0446 data_time: 0.0030 memory: 1008 2022/11/02 14:16:18 - mmengine - INFO - Epoch(val) [200][65/500] eta: 0:00:19 time: 0.0416 data_time: 0.0029 memory: 1008 2022/11/02 14:16:18 - mmengine - INFO - Epoch(val) [200][70/500] eta: 0:00:18 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 14:16:19 - mmengine - INFO - Epoch(val) [200][75/500] eta: 0:00:18 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 14:16:19 - mmengine - INFO - Epoch(val) [200][80/500] eta: 0:00:33 time: 0.0792 data_time: 0.0408 memory: 1008 2022/11/02 14:16:19 - mmengine - INFO - Epoch(val) [200][85/500] eta: 0:00:33 time: 0.0759 data_time: 0.0403 memory: 1008 2022/11/02 14:16:20 - mmengine - INFO - Epoch(val) [200][90/500] eta: 0:00:16 time: 0.0400 data_time: 0.0022 memory: 1008 2022/11/02 14:16:20 - mmengine - INFO - Epoch(val) [200][95/500] eta: 0:00:16 time: 0.0442 data_time: 0.0027 memory: 1008 2022/11/02 14:16:20 - mmengine - INFO - Epoch(val) [200][100/500] eta: 0:00:16 time: 0.0425 data_time: 0.0030 memory: 1008 2022/11/02 14:16:20 - mmengine - INFO - Epoch(val) [200][105/500] eta: 0:00:16 time: 0.0400 data_time: 0.0029 memory: 1008 2022/11/02 14:16:20 - mmengine - INFO - Epoch(val) [200][110/500] eta: 0:00:15 time: 0.0385 data_time: 0.0026 memory: 1008 2022/11/02 14:16:21 - mmengine - INFO - Epoch(val) [200][115/500] eta: 0:00:15 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 14:16:21 - mmengine - INFO - Epoch(val) [200][120/500] eta: 0:00:16 time: 0.0426 data_time: 0.0031 memory: 1008 2022/11/02 14:16:21 - mmengine - INFO - Epoch(val) [200][125/500] eta: 0:00:16 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 14:16:21 - mmengine - INFO - Epoch(val) [200][130/500] eta: 0:00:14 time: 0.0397 data_time: 0.0028 memory: 1008 2022/11/02 14:16:21 - mmengine - INFO - Epoch(val) [200][135/500] eta: 0:00:14 time: 0.0389 data_time: 0.0028 memory: 1008 2022/11/02 14:16:22 - mmengine - INFO - Epoch(val) [200][140/500] eta: 0:00:14 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/02 14:16:22 - mmengine - INFO - Epoch(val) [200][145/500] eta: 0:00:14 time: 0.0458 data_time: 0.0029 memory: 1008 2022/11/02 14:16:22 - mmengine - INFO - Epoch(val) [200][150/500] eta: 0:00:15 time: 0.0448 data_time: 0.0026 memory: 1008 2022/11/02 14:16:22 - mmengine - INFO - Epoch(val) [200][155/500] eta: 0:00:15 time: 0.0450 data_time: 0.0026 memory: 1008 2022/11/02 14:16:23 - mmengine - INFO - Epoch(val) [200][160/500] eta: 0:00:15 time: 0.0458 data_time: 0.0027 memory: 1008 2022/11/02 14:16:23 - mmengine - INFO - Epoch(val) [200][165/500] eta: 0:00:15 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 14:16:23 - mmengine - INFO - Epoch(val) [200][170/500] eta: 0:00:14 time: 0.0431 data_time: 0.0028 memory: 1008 2022/11/02 14:16:23 - mmengine - INFO - Epoch(val) [200][175/500] eta: 0:00:14 time: 0.0419 data_time: 0.0030 memory: 1008 2022/11/02 14:16:23 - mmengine - INFO - Epoch(val) [200][180/500] eta: 0:00:12 time: 0.0402 data_time: 0.0031 memory: 1008 2022/11/02 14:16:24 - mmengine - INFO - Epoch(val) [200][185/500] eta: 0:00:12 time: 0.0423 data_time: 0.0030 memory: 1008 2022/11/02 14:16:24 - mmengine - INFO - Epoch(val) [200][190/500] eta: 0:00:13 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/02 14:16:24 - mmengine - INFO - Epoch(val) [200][195/500] eta: 0:00:13 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 14:16:24 - mmengine - INFO - Epoch(val) [200][200/500] eta: 0:00:12 time: 0.0426 data_time: 0.0030 memory: 1008 2022/11/02 14:16:25 - mmengine - INFO - Epoch(val) [200][205/500] eta: 0:00:12 time: 0.0439 data_time: 0.0030 memory: 1008 2022/11/02 14:16:25 - mmengine - INFO - Epoch(val) [200][210/500] eta: 0:00:11 time: 0.0407 data_time: 0.0030 memory: 1008 2022/11/02 14:16:25 - mmengine - INFO - Epoch(val) [200][215/500] eta: 0:00:11 time: 0.0427 data_time: 0.0033 memory: 1008 2022/11/02 14:16:25 - mmengine - INFO - Epoch(val) [200][220/500] eta: 0:00:12 time: 0.0437 data_time: 0.0031 memory: 1008 2022/11/02 14:16:25 - mmengine - INFO - Epoch(val) [200][225/500] eta: 0:00:12 time: 0.0478 data_time: 0.0030 memory: 1008 2022/11/02 14:16:26 - mmengine - INFO - Epoch(val) [200][230/500] eta: 0:00:12 time: 0.0457 data_time: 0.0032 memory: 1008 2022/11/02 14:16:26 - mmengine - INFO - Epoch(val) [200][235/500] eta: 0:00:12 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/02 14:16:26 - mmengine - INFO - Epoch(val) [200][240/500] eta: 0:00:12 time: 0.0468 data_time: 0.0034 memory: 1008 2022/11/02 14:16:26 - mmengine - INFO - Epoch(val) [200][245/500] eta: 0:00:12 time: 0.0445 data_time: 0.0035 memory: 1008 2022/11/02 14:16:27 - mmengine - INFO - Epoch(val) [200][250/500] eta: 0:00:10 time: 0.0424 data_time: 0.0029 memory: 1008 2022/11/02 14:16:27 - mmengine - INFO - Epoch(val) [200][255/500] eta: 0:00:10 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 14:16:27 - mmengine - INFO - Epoch(val) [200][260/500] eta: 0:00:08 time: 0.0372 data_time: 0.0024 memory: 1008 2022/11/02 14:16:27 - mmengine - INFO - Epoch(val) [200][265/500] eta: 0:00:08 time: 0.0419 data_time: 0.0031 memory: 1008 2022/11/02 14:16:27 - mmengine - INFO - Epoch(val) [200][270/500] eta: 0:00:10 time: 0.0469 data_time: 0.0037 memory: 1008 2022/11/02 14:16:28 - mmengine - INFO - Epoch(val) [200][275/500] eta: 0:00:10 time: 0.0433 data_time: 0.0032 memory: 1008 2022/11/02 14:16:28 - mmengine - INFO - Epoch(val) [200][280/500] eta: 0:00:09 time: 0.0411 data_time: 0.0029 memory: 1008 2022/11/02 14:16:28 - mmengine - INFO - Epoch(val) [200][285/500] eta: 0:00:09 time: 0.0393 data_time: 0.0026 memory: 1008 2022/11/02 14:16:28 - mmengine - INFO - Epoch(val) [200][290/500] eta: 0:00:08 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/02 14:16:28 - mmengine - INFO - Epoch(val) [200][295/500] eta: 0:00:08 time: 0.0429 data_time: 0.0025 memory: 1008 2022/11/02 14:16:29 - mmengine - INFO - Epoch(val) [200][300/500] eta: 0:00:07 time: 0.0400 data_time: 0.0025 memory: 1008 2022/11/02 14:16:29 - mmengine - INFO - Epoch(val) [200][305/500] eta: 0:00:07 time: 0.0392 data_time: 0.0028 memory: 1008 2022/11/02 14:16:29 - mmengine - INFO - Epoch(val) [200][310/500] eta: 0:00:08 time: 0.0458 data_time: 0.0035 memory: 1008 2022/11/02 14:16:29 - mmengine - INFO - Epoch(val) [200][315/500] eta: 0:00:08 time: 0.0505 data_time: 0.0034 memory: 1008 2022/11/02 14:16:29 - mmengine - INFO - Epoch(val) [200][320/500] eta: 0:00:08 time: 0.0447 data_time: 0.0027 memory: 1008 2022/11/02 14:16:30 - mmengine - INFO - Epoch(val) [200][325/500] eta: 0:00:08 time: 0.0556 data_time: 0.0024 memory: 1008 2022/11/02 14:16:30 - mmengine - INFO - Epoch(val) [200][330/500] eta: 0:00:09 time: 0.0549 data_time: 0.0024 memory: 1008 2022/11/02 14:16:30 - mmengine - INFO - Epoch(val) [200][335/500] eta: 0:00:09 time: 0.0367 data_time: 0.0026 memory: 1008 2022/11/02 14:16:31 - mmengine - INFO - Epoch(val) [200][340/500] eta: 0:00:09 time: 0.0583 data_time: 0.0030 memory: 1008 2022/11/02 14:16:31 - mmengine - INFO - Epoch(val) [200][345/500] eta: 0:00:09 time: 0.0610 data_time: 0.0033 memory: 1008 2022/11/02 14:16:31 - mmengine - INFO - Epoch(val) [200][350/500] eta: 0:00:07 time: 0.0479 data_time: 0.0034 memory: 1008 2022/11/02 14:16:31 - mmengine - INFO - Epoch(val) [200][355/500] eta: 0:00:07 time: 0.0460 data_time: 0.0031 memory: 1008 2022/11/02 14:16:31 - mmengine - INFO - Epoch(val) [200][360/500] eta: 0:00:05 time: 0.0394 data_time: 0.0031 memory: 1008 2022/11/02 14:16:32 - mmengine - INFO - Epoch(val) [200][365/500] eta: 0:00:05 time: 0.0428 data_time: 0.0037 memory: 1008 2022/11/02 14:16:32 - mmengine - INFO - Epoch(val) [200][370/500] eta: 0:00:05 time: 0.0394 data_time: 0.0033 memory: 1008 2022/11/02 14:16:32 - mmengine - INFO - Epoch(val) [200][375/500] eta: 0:00:05 time: 0.0372 data_time: 0.0027 memory: 1008 2022/11/02 14:16:32 - mmengine - INFO - Epoch(val) [200][380/500] eta: 0:00:05 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 14:16:32 - mmengine - INFO - Epoch(val) [200][385/500] eta: 0:00:05 time: 0.0423 data_time: 0.0026 memory: 1008 2022/11/02 14:16:33 - mmengine - INFO - Epoch(val) [200][390/500] eta: 0:00:04 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 14:16:33 - mmengine - INFO - Epoch(val) [200][395/500] eta: 0:00:04 time: 0.0430 data_time: 0.0031 memory: 1008 2022/11/02 14:16:33 - mmengine - INFO - Epoch(val) [200][400/500] eta: 0:00:04 time: 0.0463 data_time: 0.0039 memory: 1008 2022/11/02 14:16:33 - mmengine - INFO - Epoch(val) [200][405/500] eta: 0:00:04 time: 0.0457 data_time: 0.0036 memory: 1008 2022/11/02 14:16:34 - mmengine - INFO - Epoch(val) [200][410/500] eta: 0:00:04 time: 0.0449 data_time: 0.0029 memory: 1008 2022/11/02 14:16:34 - mmengine - INFO - Epoch(val) [200][415/500] eta: 0:00:04 time: 0.0425 data_time: 0.0028 memory: 1008 2022/11/02 14:16:34 - mmengine - INFO - Epoch(val) [200][420/500] eta: 0:00:06 time: 0.0771 data_time: 0.0446 memory: 1008 2022/11/02 14:16:35 - mmengine - INFO - Epoch(val) [200][425/500] eta: 0:00:06 time: 0.0804 data_time: 0.0443 memory: 1008 2022/11/02 14:16:35 - mmengine - INFO - Epoch(val) [200][430/500] eta: 0:00:02 time: 0.0413 data_time: 0.0024 memory: 1008 2022/11/02 14:16:35 - mmengine - INFO - Epoch(val) [200][435/500] eta: 0:00:02 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/02 14:16:35 - mmengine - INFO - Epoch(val) [200][440/500] eta: 0:00:02 time: 0.0405 data_time: 0.0024 memory: 1008 2022/11/02 14:16:35 - mmengine - INFO - Epoch(val) [200][445/500] eta: 0:00:02 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 14:16:36 - mmengine - INFO - Epoch(val) [200][450/500] eta: 0:00:02 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 14:16:36 - mmengine - INFO - Epoch(val) [200][455/500] eta: 0:00:02 time: 0.0439 data_time: 0.0026 memory: 1008 2022/11/02 14:16:36 - mmengine - INFO - Epoch(val) [200][460/500] eta: 0:00:01 time: 0.0413 data_time: 0.0028 memory: 1008 2022/11/02 14:16:36 - mmengine - INFO - Epoch(val) [200][465/500] eta: 0:00:01 time: 0.0367 data_time: 0.0028 memory: 1008 2022/11/02 14:16:36 - mmengine - INFO - Epoch(val) [200][470/500] eta: 0:00:01 time: 0.0382 data_time: 0.0029 memory: 1008 2022/11/02 14:16:37 - mmengine - INFO - Epoch(val) [200][475/500] eta: 0:00:01 time: 0.0374 data_time: 0.0029 memory: 1008 2022/11/02 14:16:37 - mmengine - INFO - Epoch(val) [200][480/500] eta: 0:00:00 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 14:16:37 - mmengine - INFO - Epoch(val) [200][485/500] eta: 0:00:00 time: 0.0397 data_time: 0.0028 memory: 1008 2022/11/02 14:16:37 - mmengine - INFO - Epoch(val) [200][490/500] eta: 0:00:00 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 14:16:37 - mmengine - INFO - Epoch(val) [200][495/500] eta: 0:00:00 time: 0.0418 data_time: 0.0024 memory: 1008 2022/11/02 14:16:38 - mmengine - INFO - Epoch(val) [200][500/500] eta: 0:00:00 time: 0.0407 data_time: 0.0027 memory: 1008 2022/11/02 14:16:38 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8117, precision: 0.6379, hmean: 0.7144 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8113, precision: 0.7161, hmean: 0.7607 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8103, precision: 0.7650, hmean: 0.7870 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7978, precision: 0.8099, hmean: 0.8038 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7328, precision: 0.8702, hmean: 0.7956 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3447, precision: 0.9446, hmean: 0.5051 2022/11/02 14:16:38 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0010, precision: 1.0000, hmean: 0.0019 2022/11/02 14:16:38 - mmengine - INFO - Epoch(val) [200][500/500] icdar/precision: 0.8099 icdar/recall: 0.7978 icdar/hmean: 0.8038 2022/11/02 14:16:44 - mmengine - INFO - Epoch(train) [201][5/63] lr: 1.8355e-03 eta: 0:00:00 time: 0.8107 data_time: 0.2384 memory: 14901 loss: 1.9507 loss_prob: 1.1391 loss_thr: 0.6239 loss_db: 0.1877 2022/11/02 14:16:47 - mmengine - INFO - Epoch(train) [201][10/63] lr: 1.8355e-03 eta: 10:19:05 time: 0.8850 data_time: 0.2456 memory: 14901 loss: 1.9479 loss_prob: 1.1553 loss_thr: 0.6071 loss_db: 0.1854 2022/11/02 14:16:49 - mmengine - INFO - Epoch(train) [201][15/63] lr: 1.8355e-03 eta: 10:19:05 time: 0.5750 data_time: 0.0144 memory: 14901 loss: 1.8436 loss_prob: 1.0643 loss_thr: 0.6054 loss_db: 0.1739 2022/11/02 14:16:52 - mmengine - INFO - Epoch(train) [201][20/63] lr: 1.8355e-03 eta: 10:18:58 time: 0.5685 data_time: 0.0076 memory: 14901 loss: 1.7739 loss_prob: 1.0011 loss_thr: 0.6045 loss_db: 0.1682 2022/11/02 14:16:55 - mmengine - INFO - Epoch(train) [201][25/63] lr: 1.8355e-03 eta: 10:18:58 time: 0.5594 data_time: 0.0206 memory: 14901 loss: 1.9241 loss_prob: 1.1208 loss_thr: 0.6209 loss_db: 0.1824 2022/11/02 14:16:58 - mmengine - INFO - Epoch(train) [201][30/63] lr: 1.8355e-03 eta: 10:18:50 time: 0.5345 data_time: 0.0282 memory: 14901 loss: 1.8926 loss_prob: 1.1119 loss_thr: 0.6011 loss_db: 0.1796 2022/11/02 14:17:00 - mmengine - INFO - Epoch(train) [201][35/63] lr: 1.8355e-03 eta: 10:18:50 time: 0.5254 data_time: 0.0230 memory: 14901 loss: 1.8252 loss_prob: 1.0615 loss_thr: 0.5876 loss_db: 0.1762 2022/11/02 14:17:03 - mmengine - INFO - Epoch(train) [201][40/63] lr: 1.8355e-03 eta: 10:18:40 time: 0.5095 data_time: 0.0134 memory: 14901 loss: 1.9431 loss_prob: 1.1329 loss_thr: 0.6248 loss_db: 0.1854 2022/11/02 14:17:05 - mmengine - INFO - Epoch(train) [201][45/63] lr: 1.8355e-03 eta: 10:18:40 time: 0.5277 data_time: 0.0081 memory: 14901 loss: 1.8356 loss_prob: 1.0580 loss_thr: 0.6062 loss_db: 0.1713 2022/11/02 14:17:08 - mmengine - INFO - Epoch(train) [201][50/63] lr: 1.8355e-03 eta: 10:18:33 time: 0.5663 data_time: 0.0231 memory: 14901 loss: 1.8958 loss_prob: 1.1142 loss_thr: 0.5985 loss_db: 0.1831 2022/11/02 14:17:11 - mmengine - INFO - Epoch(train) [201][55/63] lr: 1.8355e-03 eta: 10:18:33 time: 0.5924 data_time: 0.0324 memory: 14901 loss: 1.9986 loss_prob: 1.1874 loss_thr: 0.6158 loss_db: 0.1953 2022/11/02 14:17:14 - mmengine - INFO - Epoch(train) [201][60/63] lr: 1.8355e-03 eta: 10:18:25 time: 0.5412 data_time: 0.0211 memory: 14901 loss: 2.1046 loss_prob: 1.2695 loss_thr: 0.6323 loss_db: 0.2028 2022/11/02 14:17:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:17:20 - mmengine - INFO - Epoch(train) [202][5/63] lr: 1.8338e-03 eta: 10:18:25 time: 0.7720 data_time: 0.2195 memory: 14901 loss: 2.0198 loss_prob: 1.1914 loss_thr: 0.6355 loss_db: 0.1929 2022/11/02 14:17:24 - mmengine - INFO - Epoch(train) [202][10/63] lr: 1.8338e-03 eta: 10:18:21 time: 0.8553 data_time: 0.2286 memory: 14901 loss: 1.8320 loss_prob: 1.0584 loss_thr: 0.6034 loss_db: 0.1702 2022/11/02 14:17:26 - mmengine - INFO - Epoch(train) [202][15/63] lr: 1.8338e-03 eta: 10:18:21 time: 0.5688 data_time: 0.0199 memory: 14901 loss: 1.7639 loss_prob: 1.0154 loss_thr: 0.5861 loss_db: 0.1624 2022/11/02 14:17:29 - mmengine - INFO - Epoch(train) [202][20/63] lr: 1.8338e-03 eta: 10:18:12 time: 0.5161 data_time: 0.0085 memory: 14901 loss: 1.8317 loss_prob: 1.0582 loss_thr: 0.5990 loss_db: 0.1745 2022/11/02 14:17:31 - mmengine - INFO - Epoch(train) [202][25/63] lr: 1.8338e-03 eta: 10:18:12 time: 0.5317 data_time: 0.0342 memory: 14901 loss: 1.8135 loss_prob: 1.0457 loss_thr: 0.5963 loss_db: 0.1714 2022/11/02 14:17:34 - mmengine - INFO - Epoch(train) [202][30/63] lr: 1.8338e-03 eta: 10:18:02 time: 0.5173 data_time: 0.0324 memory: 14901 loss: 1.9369 loss_prob: 1.1286 loss_thr: 0.6274 loss_db: 0.1809 2022/11/02 14:17:37 - mmengine - INFO - Epoch(train) [202][35/63] lr: 1.8338e-03 eta: 10:18:02 time: 0.5266 data_time: 0.0141 memory: 14901 loss: 1.9983 loss_prob: 1.1794 loss_thr: 0.6273 loss_db: 0.1915 2022/11/02 14:17:39 - mmengine - INFO - Epoch(train) [202][40/63] lr: 1.8338e-03 eta: 10:17:53 time: 0.5196 data_time: 0.0140 memory: 14901 loss: 1.9314 loss_prob: 1.1270 loss_thr: 0.6195 loss_db: 0.1850 2022/11/02 14:17:42 - mmengine - INFO - Epoch(train) [202][45/63] lr: 1.8338e-03 eta: 10:17:53 time: 0.5210 data_time: 0.0052 memory: 14901 loss: 1.8770 loss_prob: 1.0717 loss_thr: 0.6300 loss_db: 0.1753 2022/11/02 14:17:45 - mmengine - INFO - Epoch(train) [202][50/63] lr: 1.8338e-03 eta: 10:17:46 time: 0.5665 data_time: 0.0243 memory: 14901 loss: 1.8380 loss_prob: 1.0510 loss_thr: 0.6118 loss_db: 0.1752 2022/11/02 14:17:47 - mmengine - INFO - Epoch(train) [202][55/63] lr: 1.8338e-03 eta: 10:17:46 time: 0.5375 data_time: 0.0289 memory: 14901 loss: 1.7070 loss_prob: 0.9678 loss_thr: 0.5779 loss_db: 0.1612 2022/11/02 14:17:50 - mmengine - INFO - Epoch(train) [202][60/63] lr: 1.8338e-03 eta: 10:17:37 time: 0.5370 data_time: 0.0114 memory: 14901 loss: 1.7626 loss_prob: 1.0097 loss_thr: 0.5869 loss_db: 0.1660 2022/11/02 14:17:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:17:57 - mmengine - INFO - Epoch(train) [203][5/63] lr: 1.8321e-03 eta: 10:17:37 time: 0.7513 data_time: 0.2582 memory: 14901 loss: 1.7445 loss_prob: 0.9817 loss_thr: 0.5946 loss_db: 0.1682 2022/11/02 14:18:00 - mmengine - INFO - Epoch(train) [203][10/63] lr: 1.8321e-03 eta: 10:17:33 time: 0.8220 data_time: 0.2623 memory: 14901 loss: 1.7552 loss_prob: 0.9842 loss_thr: 0.6064 loss_db: 0.1646 2022/11/02 14:18:02 - mmengine - INFO - Epoch(train) [203][15/63] lr: 1.8321e-03 eta: 10:17:33 time: 0.5758 data_time: 0.0151 memory: 14901 loss: 1.7685 loss_prob: 1.0003 loss_thr: 0.6029 loss_db: 0.1653 2022/11/02 14:18:05 - mmengine - INFO - Epoch(train) [203][20/63] lr: 1.8321e-03 eta: 10:17:23 time: 0.5132 data_time: 0.0099 memory: 14901 loss: 1.7223 loss_prob: 0.9772 loss_thr: 0.5830 loss_db: 0.1621 2022/11/02 14:18:08 - mmengine - INFO - Epoch(train) [203][25/63] lr: 1.8321e-03 eta: 10:17:23 time: 0.5285 data_time: 0.0343 memory: 14901 loss: 1.8261 loss_prob: 1.0375 loss_thr: 0.6156 loss_db: 0.1730 2022/11/02 14:18:10 - mmengine - INFO - Epoch(train) [203][30/63] lr: 1.8321e-03 eta: 10:17:14 time: 0.5353 data_time: 0.0409 memory: 14901 loss: 1.9089 loss_prob: 1.0965 loss_thr: 0.6302 loss_db: 0.1822 2022/11/02 14:18:13 - mmengine - INFO - Epoch(train) [203][35/63] lr: 1.8321e-03 eta: 10:17:14 time: 0.5592 data_time: 0.0159 memory: 14901 loss: 1.8253 loss_prob: 1.0495 loss_thr: 0.6057 loss_db: 0.1702 2022/11/02 14:18:16 - mmengine - INFO - Epoch(train) [203][40/63] lr: 1.8321e-03 eta: 10:17:07 time: 0.5607 data_time: 0.0105 memory: 14901 loss: 1.7470 loss_prob: 0.9878 loss_thr: 0.6001 loss_db: 0.1592 2022/11/02 14:18:19 - mmengine - INFO - Epoch(train) [203][45/63] lr: 1.8321e-03 eta: 10:17:07 time: 0.5342 data_time: 0.0137 memory: 14901 loss: 1.7855 loss_prob: 1.0166 loss_thr: 0.6011 loss_db: 0.1679 2022/11/02 14:18:21 - mmengine - INFO - Epoch(train) [203][50/63] lr: 1.8321e-03 eta: 10:16:59 time: 0.5478 data_time: 0.0275 memory: 14901 loss: 1.9125 loss_prob: 1.1246 loss_thr: 0.6052 loss_db: 0.1826 2022/11/02 14:18:24 - mmengine - INFO - Epoch(train) [203][55/63] lr: 1.8321e-03 eta: 10:16:59 time: 0.5219 data_time: 0.0253 memory: 14901 loss: 1.9156 loss_prob: 1.1314 loss_thr: 0.6029 loss_db: 0.1814 2022/11/02 14:18:27 - mmengine - INFO - Epoch(train) [203][60/63] lr: 1.8321e-03 eta: 10:16:54 time: 0.6103 data_time: 0.0153 memory: 14901 loss: 1.8994 loss_prob: 1.0943 loss_thr: 0.6245 loss_db: 0.1806 2022/11/02 14:18:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:18:35 - mmengine - INFO - Epoch(train) [204][5/63] lr: 1.8305e-03 eta: 10:16:54 time: 0.9930 data_time: 0.2514 memory: 14901 loss: 1.8432 loss_prob: 1.0490 loss_thr: 0.6236 loss_db: 0.1706 2022/11/02 14:18:38 - mmengine - INFO - Epoch(train) [204][10/63] lr: 1.8305e-03 eta: 10:16:52 time: 0.8829 data_time: 0.2524 memory: 14901 loss: 1.8681 loss_prob: 1.0775 loss_thr: 0.6153 loss_db: 0.1754 2022/11/02 14:18:41 - mmengine - INFO - Epoch(train) [204][15/63] lr: 1.8305e-03 eta: 10:16:52 time: 0.5477 data_time: 0.0137 memory: 14901 loss: 1.8512 loss_prob: 1.0592 loss_thr: 0.6121 loss_db: 0.1799 2022/11/02 14:18:44 - mmengine - INFO - Epoch(train) [204][20/63] lr: 1.8305e-03 eta: 10:16:45 time: 0.5581 data_time: 0.0108 memory: 14901 loss: 1.7854 loss_prob: 1.0201 loss_thr: 0.5960 loss_db: 0.1692 2022/11/02 14:18:47 - mmengine - INFO - Epoch(train) [204][25/63] lr: 1.8305e-03 eta: 10:16:45 time: 0.5782 data_time: 0.0318 memory: 14901 loss: 1.7031 loss_prob: 0.9964 loss_thr: 0.5478 loss_db: 0.1589 2022/11/02 14:18:49 - mmengine - INFO - Epoch(train) [204][30/63] lr: 1.8305e-03 eta: 10:16:39 time: 0.5867 data_time: 0.0387 memory: 14901 loss: 1.6840 loss_prob: 0.9894 loss_thr: 0.5365 loss_db: 0.1581 2022/11/02 14:18:52 - mmengine - INFO - Epoch(train) [204][35/63] lr: 1.8305e-03 eta: 10:16:39 time: 0.5892 data_time: 0.0162 memory: 14901 loss: 1.7677 loss_prob: 1.0138 loss_thr: 0.5879 loss_db: 0.1660 2022/11/02 14:18:55 - mmengine - INFO - Epoch(train) [204][40/63] lr: 1.8305e-03 eta: 10:16:31 time: 0.5432 data_time: 0.0098 memory: 14901 loss: 1.7187 loss_prob: 0.9736 loss_thr: 0.5842 loss_db: 0.1609 2022/11/02 14:18:58 - mmengine - INFO - Epoch(train) [204][45/63] lr: 1.8305e-03 eta: 10:16:31 time: 0.5048 data_time: 0.0066 memory: 14901 loss: 1.8172 loss_prob: 1.0645 loss_thr: 0.5821 loss_db: 0.1705 2022/11/02 14:19:00 - mmengine - INFO - Epoch(train) [204][50/63] lr: 1.8305e-03 eta: 10:16:22 time: 0.5235 data_time: 0.0183 memory: 14901 loss: 2.0241 loss_prob: 1.2054 loss_thr: 0.6268 loss_db: 0.1919 2022/11/02 14:19:03 - mmengine - INFO - Epoch(train) [204][55/63] lr: 1.8305e-03 eta: 10:16:22 time: 0.5334 data_time: 0.0273 memory: 14901 loss: 1.9484 loss_prob: 1.1342 loss_thr: 0.6260 loss_db: 0.1882 2022/11/02 14:19:06 - mmengine - INFO - Epoch(train) [204][60/63] lr: 1.8305e-03 eta: 10:16:14 time: 0.5585 data_time: 0.0183 memory: 14901 loss: 1.9264 loss_prob: 1.1146 loss_thr: 0.6241 loss_db: 0.1877 2022/11/02 14:19:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:19:15 - mmengine - INFO - Epoch(train) [205][5/63] lr: 1.8288e-03 eta: 10:16:14 time: 1.0264 data_time: 0.2518 memory: 14901 loss: 1.7878 loss_prob: 1.0324 loss_thr: 0.5909 loss_db: 0.1645 2022/11/02 14:19:17 - mmengine - INFO - Epoch(train) [205][10/63] lr: 1.8288e-03 eta: 10:16:19 time: 1.0217 data_time: 0.2555 memory: 14901 loss: 1.8547 loss_prob: 1.0742 loss_thr: 0.6029 loss_db: 0.1777 2022/11/02 14:19:20 - mmengine - INFO - Epoch(train) [205][15/63] lr: 1.8288e-03 eta: 10:16:19 time: 0.5636 data_time: 0.0164 memory: 14901 loss: 1.9529 loss_prob: 1.1360 loss_thr: 0.6297 loss_db: 0.1871 2022/11/02 14:19:23 - mmengine - INFO - Epoch(train) [205][20/63] lr: 1.8288e-03 eta: 10:16:13 time: 0.5799 data_time: 0.0104 memory: 14901 loss: 1.8907 loss_prob: 1.0939 loss_thr: 0.6214 loss_db: 0.1754 2022/11/02 14:19:26 - mmengine - INFO - Epoch(train) [205][25/63] lr: 1.8288e-03 eta: 10:16:13 time: 0.5944 data_time: 0.0382 memory: 14901 loss: 1.8536 loss_prob: 1.0716 loss_thr: 0.6077 loss_db: 0.1743 2022/11/02 14:19:29 - mmengine - INFO - Epoch(train) [205][30/63] lr: 1.8288e-03 eta: 10:16:04 time: 0.5415 data_time: 0.0397 memory: 14901 loss: 1.7639 loss_prob: 1.0070 loss_thr: 0.5898 loss_db: 0.1671 2022/11/02 14:19:31 - mmengine - INFO - Epoch(train) [205][35/63] lr: 1.8288e-03 eta: 10:16:04 time: 0.5011 data_time: 0.0114 memory: 14901 loss: 1.7835 loss_prob: 1.0221 loss_thr: 0.5936 loss_db: 0.1677 2022/11/02 14:19:34 - mmengine - INFO - Epoch(train) [205][40/63] lr: 1.8288e-03 eta: 10:15:54 time: 0.4951 data_time: 0.0120 memory: 14901 loss: 1.8157 loss_prob: 1.0466 loss_thr: 0.5954 loss_db: 0.1737 2022/11/02 14:19:36 - mmengine - INFO - Epoch(train) [205][45/63] lr: 1.8288e-03 eta: 10:15:54 time: 0.5007 data_time: 0.0086 memory: 14901 loss: 1.7549 loss_prob: 1.0035 loss_thr: 0.5815 loss_db: 0.1699 2022/11/02 14:19:39 - mmengine - INFO - Epoch(train) [205][50/63] lr: 1.8288e-03 eta: 10:15:44 time: 0.5061 data_time: 0.0233 memory: 14901 loss: 1.7392 loss_prob: 0.9940 loss_thr: 0.5766 loss_db: 0.1686 2022/11/02 14:19:41 - mmengine - INFO - Epoch(train) [205][55/63] lr: 1.8288e-03 eta: 10:15:44 time: 0.5055 data_time: 0.0239 memory: 14901 loss: 1.8012 loss_prob: 1.0297 loss_thr: 0.5998 loss_db: 0.1717 2022/11/02 14:19:44 - mmengine - INFO - Epoch(train) [205][60/63] lr: 1.8288e-03 eta: 10:15:34 time: 0.5128 data_time: 0.0073 memory: 14901 loss: 1.8967 loss_prob: 1.0915 loss_thr: 0.6259 loss_db: 0.1793 2022/11/02 14:19:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:19:50 - mmengine - INFO - Epoch(train) [206][5/63] lr: 1.8272e-03 eta: 10:15:34 time: 0.7707 data_time: 0.2525 memory: 14901 loss: 1.7669 loss_prob: 0.9874 loss_thr: 0.6139 loss_db: 0.1656 2022/11/02 14:19:53 - mmengine - INFO - Epoch(train) [206][10/63] lr: 1.8272e-03 eta: 10:15:27 time: 0.7792 data_time: 0.2484 memory: 14901 loss: 1.6453 loss_prob: 0.9188 loss_thr: 0.5748 loss_db: 0.1517 2022/11/02 14:19:56 - mmengine - INFO - Epoch(train) [206][15/63] lr: 1.8272e-03 eta: 10:15:27 time: 0.5914 data_time: 0.0097 memory: 14901 loss: 1.6648 loss_prob: 0.9313 loss_thr: 0.5779 loss_db: 0.1556 2022/11/02 14:19:59 - mmengine - INFO - Epoch(train) [206][20/63] lr: 1.8272e-03 eta: 10:15:21 time: 0.5844 data_time: 0.0108 memory: 14901 loss: 1.7127 loss_prob: 0.9668 loss_thr: 0.5847 loss_db: 0.1611 2022/11/02 14:20:02 - mmengine - INFO - Epoch(train) [206][25/63] lr: 1.8272e-03 eta: 10:15:21 time: 0.5363 data_time: 0.0321 memory: 14901 loss: 1.7662 loss_prob: 1.0083 loss_thr: 0.5922 loss_db: 0.1656 2022/11/02 14:20:05 - mmengine - INFO - Epoch(train) [206][30/63] lr: 1.8272e-03 eta: 10:15:15 time: 0.5887 data_time: 0.0439 memory: 14901 loss: 1.7302 loss_prob: 0.9794 loss_thr: 0.5895 loss_db: 0.1613 2022/11/02 14:20:07 - mmengine - INFO - Epoch(train) [206][35/63] lr: 1.8272e-03 eta: 10:15:15 time: 0.5580 data_time: 0.0252 memory: 14901 loss: 1.7140 loss_prob: 0.9546 loss_thr: 0.5998 loss_db: 0.1595 2022/11/02 14:20:10 - mmengine - INFO - Epoch(train) [206][40/63] lr: 1.8272e-03 eta: 10:15:06 time: 0.5179 data_time: 0.0133 memory: 14901 loss: 1.7527 loss_prob: 0.9770 loss_thr: 0.6145 loss_db: 0.1612 2022/11/02 14:20:13 - mmengine - INFO - Epoch(train) [206][45/63] lr: 1.8272e-03 eta: 10:15:06 time: 0.5667 data_time: 0.0123 memory: 14901 loss: 1.7608 loss_prob: 0.9818 loss_thr: 0.6160 loss_db: 0.1630 2022/11/02 14:20:16 - mmengine - INFO - Epoch(train) [206][50/63] lr: 1.8272e-03 eta: 10:15:01 time: 0.6045 data_time: 0.0225 memory: 14901 loss: 1.9278 loss_prob: 1.1156 loss_thr: 0.6228 loss_db: 0.1894 2022/11/02 14:20:18 - mmengine - INFO - Epoch(train) [206][55/63] lr: 1.8272e-03 eta: 10:15:01 time: 0.5440 data_time: 0.0218 memory: 14901 loss: 1.9143 loss_prob: 1.1304 loss_thr: 0.5951 loss_db: 0.1888 2022/11/02 14:20:21 - mmengine - INFO - Epoch(train) [206][60/63] lr: 1.8272e-03 eta: 10:14:52 time: 0.5340 data_time: 0.0131 memory: 14901 loss: 1.7204 loss_prob: 1.0001 loss_thr: 0.5577 loss_db: 0.1627 2022/11/02 14:20:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:20:28 - mmengine - INFO - Epoch(train) [207][5/63] lr: 1.8255e-03 eta: 10:14:52 time: 0.8312 data_time: 0.2620 memory: 14901 loss: 1.9396 loss_prob: 1.1500 loss_thr: 0.6080 loss_db: 0.1816 2022/11/02 14:20:31 - mmengine - INFO - Epoch(train) [207][10/63] lr: 1.8255e-03 eta: 10:14:48 time: 0.8330 data_time: 0.2664 memory: 14901 loss: 2.0969 loss_prob: 1.2593 loss_thr: 0.6325 loss_db: 0.2052 2022/11/02 14:20:34 - mmengine - INFO - Epoch(train) [207][15/63] lr: 1.8255e-03 eta: 10:14:48 time: 0.5348 data_time: 0.0178 memory: 14901 loss: 2.1442 loss_prob: 1.2910 loss_thr: 0.6377 loss_db: 0.2155 2022/11/02 14:20:36 - mmengine - INFO - Epoch(train) [207][20/63] lr: 1.8255e-03 eta: 10:14:39 time: 0.5232 data_time: 0.0127 memory: 14901 loss: 2.2447 loss_prob: 1.3761 loss_thr: 0.6414 loss_db: 0.2272 2022/11/02 14:20:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:20:39 - mmengine - INFO - Epoch(train) [207][25/63] lr: 1.8255e-03 eta: 10:14:39 time: 0.5409 data_time: 0.0149 memory: 14901 loss: 2.5821 loss_prob: 1.6371 loss_thr: 0.6700 loss_db: 0.2750 2022/11/02 14:20:42 - mmengine - INFO - Epoch(train) [207][30/63] lr: 1.8255e-03 eta: 10:14:35 time: 0.6245 data_time: 0.0385 memory: 14901 loss: 2.7363 loss_prob: 1.7651 loss_thr: 0.6812 loss_db: 0.2901 2022/11/02 14:20:46 - mmengine - INFO - Epoch(train) [207][35/63] lr: 1.8255e-03 eta: 10:14:35 time: 0.6662 data_time: 0.0310 memory: 14901 loss: 2.3276 loss_prob: 1.4419 loss_thr: 0.6494 loss_db: 0.2363 2022/11/02 14:20:48 - mmengine - INFO - Epoch(train) [207][40/63] lr: 1.8255e-03 eta: 10:14:30 time: 0.6085 data_time: 0.0049 memory: 14901 loss: 2.1987 loss_prob: 1.3550 loss_thr: 0.6282 loss_db: 0.2154 2022/11/02 14:20:51 - mmengine - INFO - Epoch(train) [207][45/63] lr: 1.8255e-03 eta: 10:14:30 time: 0.5363 data_time: 0.0054 memory: 14901 loss: 2.2161 loss_prob: 1.3605 loss_thr: 0.6437 loss_db: 0.2119 2022/11/02 14:20:54 - mmengine - INFO - Epoch(train) [207][50/63] lr: 1.8255e-03 eta: 10:14:21 time: 0.5267 data_time: 0.0145 memory: 14901 loss: 2.2376 loss_prob: 1.3387 loss_thr: 0.6807 loss_db: 0.2182 2022/11/02 14:20:56 - mmengine - INFO - Epoch(train) [207][55/63] lr: 1.8255e-03 eta: 10:14:21 time: 0.5226 data_time: 0.0252 memory: 14901 loss: 2.2373 loss_prob: 1.3589 loss_thr: 0.6552 loss_db: 0.2231 2022/11/02 14:20:59 - mmengine - INFO - Epoch(train) [207][60/63] lr: 1.8255e-03 eta: 10:14:12 time: 0.5288 data_time: 0.0160 memory: 14901 loss: 2.1720 loss_prob: 1.3143 loss_thr: 0.6406 loss_db: 0.2171 2022/11/02 14:21:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:21:06 - mmengine - INFO - Epoch(train) [208][5/63] lr: 1.8239e-03 eta: 10:14:12 time: 0.8463 data_time: 0.2780 memory: 14901 loss: 2.0363 loss_prob: 1.2138 loss_thr: 0.6232 loss_db: 0.1993 2022/11/02 14:21:09 - mmengine - INFO - Epoch(train) [208][10/63] lr: 1.8239e-03 eta: 10:14:09 time: 0.8668 data_time: 0.2832 memory: 14901 loss: 1.7981 loss_prob: 1.0402 loss_thr: 0.5906 loss_db: 0.1673 2022/11/02 14:21:12 - mmengine - INFO - Epoch(train) [208][15/63] lr: 1.8239e-03 eta: 10:14:09 time: 0.5599 data_time: 0.0145 memory: 14901 loss: 1.8987 loss_prob: 1.0913 loss_thr: 0.6242 loss_db: 0.1831 2022/11/02 14:21:14 - mmengine - INFO - Epoch(train) [208][20/63] lr: 1.8239e-03 eta: 10:14:01 time: 0.5330 data_time: 0.0103 memory: 14901 loss: 2.3789 loss_prob: 1.4873 loss_thr: 0.6513 loss_db: 0.2402 2022/11/02 14:21:17 - mmengine - INFO - Epoch(train) [208][25/63] lr: 1.8239e-03 eta: 10:14:01 time: 0.4997 data_time: 0.0261 memory: 14901 loss: 2.8783 loss_prob: 1.8994 loss_thr: 0.6950 loss_db: 0.2839 2022/11/02 14:21:20 - mmengine - INFO - Epoch(train) [208][30/63] lr: 1.8239e-03 eta: 10:13:54 time: 0.5785 data_time: 0.0393 memory: 14901 loss: 2.3227 loss_prob: 1.4576 loss_thr: 0.6487 loss_db: 0.2164 2022/11/02 14:21:23 - mmengine - INFO - Epoch(train) [208][35/63] lr: 1.8239e-03 eta: 10:13:54 time: 0.6069 data_time: 0.0201 memory: 14901 loss: 1.8719 loss_prob: 1.0907 loss_thr: 0.6039 loss_db: 0.1773 2022/11/02 14:21:26 - mmengine - INFO - Epoch(train) [208][40/63] lr: 1.8239e-03 eta: 10:13:46 time: 0.5512 data_time: 0.0084 memory: 14901 loss: 2.2092 loss_prob: 1.3117 loss_thr: 0.6802 loss_db: 0.2173 2022/11/02 14:21:28 - mmengine - INFO - Epoch(train) [208][45/63] lr: 1.8239e-03 eta: 10:13:46 time: 0.5205 data_time: 0.0110 memory: 14901 loss: 2.2223 loss_prob: 1.3210 loss_thr: 0.6848 loss_db: 0.2165 2022/11/02 14:21:31 - mmengine - INFO - Epoch(train) [208][50/63] lr: 1.8239e-03 eta: 10:13:38 time: 0.5388 data_time: 0.0214 memory: 14901 loss: 2.0135 loss_prob: 1.1926 loss_thr: 0.6258 loss_db: 0.1950 2022/11/02 14:21:34 - mmengine - INFO - Epoch(train) [208][55/63] lr: 1.8239e-03 eta: 10:13:38 time: 0.5736 data_time: 0.0262 memory: 14901 loss: 1.9582 loss_prob: 1.1467 loss_thr: 0.6214 loss_db: 0.1901 2022/11/02 14:21:36 - mmengine - INFO - Epoch(train) [208][60/63] lr: 1.8239e-03 eta: 10:13:30 time: 0.5368 data_time: 0.0129 memory: 14901 loss: 1.9289 loss_prob: 1.1419 loss_thr: 0.6015 loss_db: 0.1855 2022/11/02 14:21:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:21:43 - mmengine - INFO - Epoch(train) [209][5/63] lr: 1.8222e-03 eta: 10:13:30 time: 0.7891 data_time: 0.2158 memory: 14901 loss: 1.8382 loss_prob: 1.0667 loss_thr: 0.5968 loss_db: 0.1746 2022/11/02 14:21:46 - mmengine - INFO - Epoch(train) [209][10/63] lr: 1.8222e-03 eta: 10:13:24 time: 0.8002 data_time: 0.2165 memory: 14901 loss: 1.9047 loss_prob: 1.1114 loss_thr: 0.6111 loss_db: 0.1821 2022/11/02 14:21:49 - mmengine - INFO - Epoch(train) [209][15/63] lr: 1.8222e-03 eta: 10:13:24 time: 0.5360 data_time: 0.0163 memory: 14901 loss: 1.9048 loss_prob: 1.1064 loss_thr: 0.6165 loss_db: 0.1819 2022/11/02 14:21:51 - mmengine - INFO - Epoch(train) [209][20/63] lr: 1.8222e-03 eta: 10:13:16 time: 0.5383 data_time: 0.0163 memory: 14901 loss: 1.8447 loss_prob: 1.0907 loss_thr: 0.5761 loss_db: 0.1779 2022/11/02 14:21:54 - mmengine - INFO - Epoch(train) [209][25/63] lr: 1.8222e-03 eta: 10:13:16 time: 0.5486 data_time: 0.0373 memory: 14901 loss: 2.0271 loss_prob: 1.2187 loss_thr: 0.6056 loss_db: 0.2028 2022/11/02 14:21:57 - mmengine - INFO - Epoch(train) [209][30/63] lr: 1.8222e-03 eta: 10:13:08 time: 0.5499 data_time: 0.0378 memory: 14901 loss: 2.1495 loss_prob: 1.2807 loss_thr: 0.6510 loss_db: 0.2179 2022/11/02 14:21:59 - mmengine - INFO - Epoch(train) [209][35/63] lr: 1.8222e-03 eta: 10:13:08 time: 0.4968 data_time: 0.0080 memory: 14901 loss: 2.3161 loss_prob: 1.3979 loss_thr: 0.6832 loss_db: 0.2350 2022/11/02 14:22:02 - mmengine - INFO - Epoch(train) [209][40/63] lr: 1.8222e-03 eta: 10:12:59 time: 0.5341 data_time: 0.0064 memory: 14901 loss: 2.3006 loss_prob: 1.4001 loss_thr: 0.6700 loss_db: 0.2306 2022/11/02 14:22:05 - mmengine - INFO - Epoch(train) [209][45/63] lr: 1.8222e-03 eta: 10:12:59 time: 0.5990 data_time: 0.0159 memory: 14901 loss: 2.2148 loss_prob: 1.3508 loss_thr: 0.6455 loss_db: 0.2185 2022/11/02 14:22:08 - mmengine - INFO - Epoch(train) [209][50/63] lr: 1.8222e-03 eta: 10:12:52 time: 0.5651 data_time: 0.0338 memory: 14901 loss: 2.1947 loss_prob: 1.3183 loss_thr: 0.6616 loss_db: 0.2148 2022/11/02 14:22:10 - mmengine - INFO - Epoch(train) [209][55/63] lr: 1.8222e-03 eta: 10:12:52 time: 0.5222 data_time: 0.0270 memory: 14901 loss: 2.1020 loss_prob: 1.2399 loss_thr: 0.6578 loss_db: 0.2043 2022/11/02 14:22:13 - mmengine - INFO - Epoch(train) [209][60/63] lr: 1.8222e-03 eta: 10:12:44 time: 0.5473 data_time: 0.0098 memory: 14901 loss: 2.1109 loss_prob: 1.2523 loss_thr: 0.6502 loss_db: 0.2084 2022/11/02 14:22:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:22:20 - mmengine - INFO - Epoch(train) [210][5/63] lr: 1.8206e-03 eta: 10:12:44 time: 0.8059 data_time: 0.2772 memory: 14901 loss: 2.1514 loss_prob: 1.2852 loss_thr: 0.6583 loss_db: 0.2080 2022/11/02 14:22:23 - mmengine - INFO - Epoch(train) [210][10/63] lr: 1.8206e-03 eta: 10:12:39 time: 0.8150 data_time: 0.2802 memory: 14901 loss: 2.1113 loss_prob: 1.2513 loss_thr: 0.6536 loss_db: 0.2064 2022/11/02 14:22:25 - mmengine - INFO - Epoch(train) [210][15/63] lr: 1.8206e-03 eta: 10:12:39 time: 0.5470 data_time: 0.0088 memory: 14901 loss: 2.0109 loss_prob: 1.1793 loss_thr: 0.6292 loss_db: 0.2024 2022/11/02 14:22:28 - mmengine - INFO - Epoch(train) [210][20/63] lr: 1.8206e-03 eta: 10:12:33 time: 0.5811 data_time: 0.0108 memory: 14901 loss: 1.9505 loss_prob: 1.1619 loss_thr: 0.5976 loss_db: 0.1910 2022/11/02 14:22:31 - mmengine - INFO - Epoch(train) [210][25/63] lr: 1.8206e-03 eta: 10:12:33 time: 0.5918 data_time: 0.0492 memory: 14901 loss: 2.0800 loss_prob: 1.2396 loss_thr: 0.6381 loss_db: 0.2023 2022/11/02 14:22:34 - mmengine - INFO - Epoch(train) [210][30/63] lr: 1.8206e-03 eta: 10:12:25 time: 0.5388 data_time: 0.0463 memory: 14901 loss: 2.1257 loss_prob: 1.2560 loss_thr: 0.6582 loss_db: 0.2115 2022/11/02 14:22:37 - mmengine - INFO - Epoch(train) [210][35/63] lr: 1.8206e-03 eta: 10:12:25 time: 0.5220 data_time: 0.0114 memory: 14901 loss: 1.9564 loss_prob: 1.1398 loss_thr: 0.6248 loss_db: 0.1918 2022/11/02 14:22:39 - mmengine - INFO - Epoch(train) [210][40/63] lr: 1.8206e-03 eta: 10:12:16 time: 0.5239 data_time: 0.0090 memory: 14901 loss: 1.9317 loss_prob: 1.1318 loss_thr: 0.6096 loss_db: 0.1902 2022/11/02 14:22:42 - mmengine - INFO - Epoch(train) [210][45/63] lr: 1.8206e-03 eta: 10:12:16 time: 0.5561 data_time: 0.0077 memory: 14901 loss: 2.0234 loss_prob: 1.2060 loss_thr: 0.6126 loss_db: 0.2048 2022/11/02 14:22:45 - mmengine - INFO - Epoch(train) [210][50/63] lr: 1.8206e-03 eta: 10:12:08 time: 0.5565 data_time: 0.0276 memory: 14901 loss: 2.0813 loss_prob: 1.2444 loss_thr: 0.6269 loss_db: 0.2100 2022/11/02 14:22:47 - mmengine - INFO - Epoch(train) [210][55/63] lr: 1.8206e-03 eta: 10:12:08 time: 0.4891 data_time: 0.0266 memory: 14901 loss: 2.1387 loss_prob: 1.3032 loss_thr: 0.6222 loss_db: 0.2133 2022/11/02 14:22:50 - mmengine - INFO - Epoch(train) [210][60/63] lr: 1.8206e-03 eta: 10:11:59 time: 0.5148 data_time: 0.0092 memory: 14901 loss: 2.1561 loss_prob: 1.3197 loss_thr: 0.6202 loss_db: 0.2162 2022/11/02 14:22:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:22:57 - mmengine - INFO - Epoch(train) [211][5/63] lr: 1.8189e-03 eta: 10:11:59 time: 0.8020 data_time: 0.2617 memory: 14901 loss: 1.9300 loss_prob: 1.1420 loss_thr: 0.5999 loss_db: 0.1880 2022/11/02 14:22:59 - mmengine - INFO - Epoch(train) [211][10/63] lr: 1.8189e-03 eta: 10:11:52 time: 0.7788 data_time: 0.2655 memory: 14901 loss: 1.8185 loss_prob: 1.0529 loss_thr: 0.5901 loss_db: 0.1754 2022/11/02 14:23:01 - mmengine - INFO - Epoch(train) [211][15/63] lr: 1.8189e-03 eta: 10:11:52 time: 0.4893 data_time: 0.0132 memory: 14901 loss: 1.9541 loss_prob: 1.1482 loss_thr: 0.6170 loss_db: 0.1890 2022/11/02 14:23:04 - mmengine - INFO - Epoch(train) [211][20/63] lr: 1.8189e-03 eta: 10:11:42 time: 0.5123 data_time: 0.0095 memory: 14901 loss: 2.0896 loss_prob: 1.2371 loss_thr: 0.6507 loss_db: 0.2018 2022/11/02 14:23:07 - mmengine - INFO - Epoch(train) [211][25/63] lr: 1.8189e-03 eta: 10:11:42 time: 0.5541 data_time: 0.0305 memory: 14901 loss: 1.9559 loss_prob: 1.1331 loss_thr: 0.6384 loss_db: 0.1844 2022/11/02 14:23:10 - mmengine - INFO - Epoch(train) [211][30/63] lr: 1.8189e-03 eta: 10:11:35 time: 0.5607 data_time: 0.0405 memory: 14901 loss: 1.7878 loss_prob: 1.0155 loss_thr: 0.6090 loss_db: 0.1633 2022/11/02 14:23:12 - mmengine - INFO - Epoch(train) [211][35/63] lr: 1.8189e-03 eta: 10:11:35 time: 0.5277 data_time: 0.0204 memory: 14901 loss: 1.8277 loss_prob: 1.0482 loss_thr: 0.6101 loss_db: 0.1693 2022/11/02 14:23:15 - mmengine - INFO - Epoch(train) [211][40/63] lr: 1.8189e-03 eta: 10:11:25 time: 0.4940 data_time: 0.0109 memory: 14901 loss: 1.8811 loss_prob: 1.0838 loss_thr: 0.6180 loss_db: 0.1793 2022/11/02 14:23:17 - mmengine - INFO - Epoch(train) [211][45/63] lr: 1.8189e-03 eta: 10:11:25 time: 0.4937 data_time: 0.0065 memory: 14901 loss: 1.9864 loss_prob: 1.1724 loss_thr: 0.6231 loss_db: 0.1909 2022/11/02 14:23:20 - mmengine - INFO - Epoch(train) [211][50/63] lr: 1.8189e-03 eta: 10:11:18 time: 0.5778 data_time: 0.0197 memory: 14901 loss: 2.0396 loss_prob: 1.2025 loss_thr: 0.6450 loss_db: 0.1921 2022/11/02 14:23:24 - mmengine - INFO - Epoch(train) [211][55/63] lr: 1.8189e-03 eta: 10:11:18 time: 0.6512 data_time: 0.0301 memory: 14901 loss: 1.9659 loss_prob: 1.1339 loss_thr: 0.6462 loss_db: 0.1859 2022/11/02 14:23:26 - mmengine - INFO - Epoch(train) [211][60/63] lr: 1.8189e-03 eta: 10:11:12 time: 0.5840 data_time: 0.0203 memory: 14901 loss: 2.0427 loss_prob: 1.2130 loss_thr: 0.6263 loss_db: 0.2034 2022/11/02 14:23:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:23:33 - mmengine - INFO - Epoch(train) [212][5/63] lr: 1.8173e-03 eta: 10:11:12 time: 0.7493 data_time: 0.2651 memory: 14901 loss: 2.1872 loss_prob: 1.3265 loss_thr: 0.6351 loss_db: 0.2256 2022/11/02 14:23:35 - mmengine - INFO - Epoch(train) [212][10/63] lr: 1.8173e-03 eta: 10:11:05 time: 0.7800 data_time: 0.2602 memory: 14901 loss: 2.0773 loss_prob: 1.2446 loss_thr: 0.6275 loss_db: 0.2052 2022/11/02 14:23:38 - mmengine - INFO - Epoch(train) [212][15/63] lr: 1.8173e-03 eta: 10:11:05 time: 0.5351 data_time: 0.0086 memory: 14901 loss: 2.1520 loss_prob: 1.2900 loss_thr: 0.6536 loss_db: 0.2084 2022/11/02 14:23:41 - mmengine - INFO - Epoch(train) [212][20/63] lr: 1.8173e-03 eta: 10:10:57 time: 0.5307 data_time: 0.0094 memory: 14901 loss: 2.1034 loss_prob: 1.2525 loss_thr: 0.6454 loss_db: 0.2055 2022/11/02 14:23:44 - mmengine - INFO - Epoch(train) [212][25/63] lr: 1.8173e-03 eta: 10:10:57 time: 0.5708 data_time: 0.0324 memory: 14901 loss: 1.9624 loss_prob: 1.1473 loss_thr: 0.6272 loss_db: 0.1879 2022/11/02 14:23:47 - mmengine - INFO - Epoch(train) [212][30/63] lr: 1.8173e-03 eta: 10:10:51 time: 0.5924 data_time: 0.0475 memory: 14901 loss: 2.0766 loss_prob: 1.2410 loss_thr: 0.6361 loss_db: 0.1995 2022/11/02 14:23:49 - mmengine - INFO - Epoch(train) [212][35/63] lr: 1.8173e-03 eta: 10:10:51 time: 0.5589 data_time: 0.0237 memory: 14901 loss: 2.1312 loss_prob: 1.2798 loss_thr: 0.6403 loss_db: 0.2111 2022/11/02 14:23:52 - mmengine - INFO - Epoch(train) [212][40/63] lr: 1.8173e-03 eta: 10:10:43 time: 0.5362 data_time: 0.0079 memory: 14901 loss: 2.0118 loss_prob: 1.1764 loss_thr: 0.6370 loss_db: 0.1983 2022/11/02 14:23:54 - mmengine - INFO - Epoch(train) [212][45/63] lr: 1.8173e-03 eta: 10:10:43 time: 0.4984 data_time: 0.0058 memory: 14901 loss: 1.8418 loss_prob: 1.0519 loss_thr: 0.6142 loss_db: 0.1757 2022/11/02 14:23:57 - mmengine - INFO - Epoch(train) [212][50/63] lr: 1.8173e-03 eta: 10:10:35 time: 0.5515 data_time: 0.0189 memory: 14901 loss: 1.8336 loss_prob: 1.0634 loss_thr: 0.5965 loss_db: 0.1738 2022/11/02 14:24:00 - mmengine - INFO - Epoch(train) [212][55/63] lr: 1.8173e-03 eta: 10:10:35 time: 0.5779 data_time: 0.0272 memory: 14901 loss: 1.9205 loss_prob: 1.1185 loss_thr: 0.6166 loss_db: 0.1854 2022/11/02 14:24:04 - mmengine - INFO - Epoch(train) [212][60/63] lr: 1.8173e-03 eta: 10:10:31 time: 0.6232 data_time: 0.0145 memory: 14901 loss: 1.8181 loss_prob: 1.0414 loss_thr: 0.6044 loss_db: 0.1723 2022/11/02 14:24:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:24:11 - mmengine - INFO - Epoch(train) [213][5/63] lr: 1.8156e-03 eta: 10:10:31 time: 0.9058 data_time: 0.2550 memory: 14901 loss: 1.8380 loss_prob: 1.0435 loss_thr: 0.6190 loss_db: 0.1755 2022/11/02 14:24:13 - mmengine - INFO - Epoch(train) [213][10/63] lr: 1.8156e-03 eta: 10:10:27 time: 0.8489 data_time: 0.2747 memory: 14901 loss: 1.9489 loss_prob: 1.1283 loss_thr: 0.6311 loss_db: 0.1895 2022/11/02 14:24:16 - mmengine - INFO - Epoch(train) [213][15/63] lr: 1.8156e-03 eta: 10:10:27 time: 0.5265 data_time: 0.0301 memory: 14901 loss: 2.0299 loss_prob: 1.1998 loss_thr: 0.6337 loss_db: 0.1963 2022/11/02 14:24:19 - mmengine - INFO - Epoch(train) [213][20/63] lr: 1.8156e-03 eta: 10:10:18 time: 0.5273 data_time: 0.0103 memory: 14901 loss: 2.0035 loss_prob: 1.1754 loss_thr: 0.6368 loss_db: 0.1914 2022/11/02 14:24:22 - mmengine - INFO - Epoch(train) [213][25/63] lr: 1.8156e-03 eta: 10:10:18 time: 0.5726 data_time: 0.0274 memory: 14901 loss: 1.9564 loss_prob: 1.1500 loss_thr: 0.6192 loss_db: 0.1872 2022/11/02 14:24:25 - mmengine - INFO - Epoch(train) [213][30/63] lr: 1.8156e-03 eta: 10:10:15 time: 0.6422 data_time: 0.0346 memory: 14901 loss: 1.9027 loss_prob: 1.1239 loss_thr: 0.5966 loss_db: 0.1822 2022/11/02 14:24:28 - mmengine - INFO - Epoch(train) [213][35/63] lr: 1.8156e-03 eta: 10:10:15 time: 0.5964 data_time: 0.0194 memory: 14901 loss: 1.9692 loss_prob: 1.1659 loss_thr: 0.6120 loss_db: 0.1913 2022/11/02 14:24:30 - mmengine - INFO - Epoch(train) [213][40/63] lr: 1.8156e-03 eta: 10:10:06 time: 0.5252 data_time: 0.0142 memory: 14901 loss: 1.9069 loss_prob: 1.1161 loss_thr: 0.6075 loss_db: 0.1833 2022/11/02 14:24:33 - mmengine - INFO - Epoch(train) [213][45/63] lr: 1.8156e-03 eta: 10:10:06 time: 0.5134 data_time: 0.0113 memory: 14901 loss: 1.8341 loss_prob: 1.0610 loss_thr: 0.5966 loss_db: 0.1765 2022/11/02 14:24:36 - mmengine - INFO - Epoch(train) [213][50/63] lr: 1.8156e-03 eta: 10:09:57 time: 0.5176 data_time: 0.0199 memory: 14901 loss: 1.9420 loss_prob: 1.1342 loss_thr: 0.6226 loss_db: 0.1851 2022/11/02 14:24:38 - mmengine - INFO - Epoch(train) [213][55/63] lr: 1.8156e-03 eta: 10:09:57 time: 0.5421 data_time: 0.0278 memory: 14901 loss: 1.9782 loss_prob: 1.1579 loss_thr: 0.6331 loss_db: 0.1872 2022/11/02 14:24:41 - mmengine - INFO - Epoch(train) [213][60/63] lr: 1.8156e-03 eta: 10:09:49 time: 0.5465 data_time: 0.0193 memory: 14901 loss: 2.2620 loss_prob: 1.3891 loss_thr: 0.6535 loss_db: 0.2194 2022/11/02 14:24:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:24:50 - mmengine - INFO - Epoch(train) [214][5/63] lr: 1.8139e-03 eta: 10:09:49 time: 0.9851 data_time: 0.2422 memory: 14901 loss: 1.7648 loss_prob: 1.0152 loss_thr: 0.5822 loss_db: 0.1674 2022/11/02 14:24:52 - mmengine - INFO - Epoch(train) [214][10/63] lr: 1.8139e-03 eta: 10:09:54 time: 1.0253 data_time: 0.2405 memory: 14901 loss: 1.8119 loss_prob: 1.0295 loss_thr: 0.6142 loss_db: 0.1683 2022/11/02 14:24:55 - mmengine - INFO - Epoch(train) [214][15/63] lr: 1.8139e-03 eta: 10:09:54 time: 0.5497 data_time: 0.0081 memory: 14901 loss: 1.9558 loss_prob: 1.1292 loss_thr: 0.6385 loss_db: 0.1881 2022/11/02 14:24:58 - mmengine - INFO - Epoch(train) [214][20/63] lr: 1.8139e-03 eta: 10:09:45 time: 0.5389 data_time: 0.0107 memory: 14901 loss: 2.0145 loss_prob: 1.1989 loss_thr: 0.6205 loss_db: 0.1951 2022/11/02 14:25:01 - mmengine - INFO - Epoch(train) [214][25/63] lr: 1.8139e-03 eta: 10:09:45 time: 0.5502 data_time: 0.0185 memory: 14901 loss: 1.8944 loss_prob: 1.1109 loss_thr: 0.6038 loss_db: 0.1798 2022/11/02 14:25:04 - mmengine - INFO - Epoch(train) [214][30/63] lr: 1.8139e-03 eta: 10:09:40 time: 0.5899 data_time: 0.0410 memory: 14901 loss: 1.8237 loss_prob: 1.0326 loss_thr: 0.6172 loss_db: 0.1739 2022/11/02 14:25:06 - mmengine - INFO - Epoch(train) [214][35/63] lr: 1.8139e-03 eta: 10:09:40 time: 0.5597 data_time: 0.0341 memory: 14901 loss: 1.7922 loss_prob: 1.0199 loss_thr: 0.5990 loss_db: 0.1734 2022/11/02 14:25:09 - mmengine - INFO - Epoch(train) [214][40/63] lr: 1.8139e-03 eta: 10:09:33 time: 0.5733 data_time: 0.0102 memory: 14901 loss: 1.7140 loss_prob: 0.9831 loss_thr: 0.5675 loss_db: 0.1633 2022/11/02 14:25:12 - mmengine - INFO - Epoch(train) [214][45/63] lr: 1.8139e-03 eta: 10:09:33 time: 0.5893 data_time: 0.0108 memory: 14901 loss: 1.7994 loss_prob: 1.0277 loss_thr: 0.6025 loss_db: 0.1692 2022/11/02 14:25:15 - mmengine - INFO - Epoch(train) [214][50/63] lr: 1.8139e-03 eta: 10:09:25 time: 0.5337 data_time: 0.0196 memory: 14901 loss: 1.8400 loss_prob: 1.0417 loss_thr: 0.6238 loss_db: 0.1744 2022/11/02 14:25:17 - mmengine - INFO - Epoch(train) [214][55/63] lr: 1.8139e-03 eta: 10:09:25 time: 0.5293 data_time: 0.0266 memory: 14901 loss: 1.9350 loss_prob: 1.1288 loss_thr: 0.6166 loss_db: 0.1896 2022/11/02 14:25:20 - mmengine - INFO - Epoch(train) [214][60/63] lr: 1.8139e-03 eta: 10:09:15 time: 0.5106 data_time: 0.0162 memory: 14901 loss: 2.0589 loss_prob: 1.2228 loss_thr: 0.6340 loss_db: 0.2021 2022/11/02 14:25:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:25:26 - mmengine - INFO - Epoch(train) [215][5/63] lr: 1.8123e-03 eta: 10:09:15 time: 0.7436 data_time: 0.2425 memory: 14901 loss: 1.9524 loss_prob: 1.1371 loss_thr: 0.6268 loss_db: 0.1886 2022/11/02 14:25:29 - mmengine - INFO - Epoch(train) [215][10/63] lr: 1.8123e-03 eta: 10:09:08 time: 0.7762 data_time: 0.2475 memory: 14901 loss: 1.9502 loss_prob: 1.1443 loss_thr: 0.6174 loss_db: 0.1885 2022/11/02 14:25:32 - mmengine - INFO - Epoch(train) [215][15/63] lr: 1.8123e-03 eta: 10:09:08 time: 0.5170 data_time: 0.0155 memory: 14901 loss: 1.9040 loss_prob: 1.1045 loss_thr: 0.6186 loss_db: 0.1809 2022/11/02 14:25:34 - mmengine - INFO - Epoch(train) [215][20/63] lr: 1.8123e-03 eta: 10:08:59 time: 0.5134 data_time: 0.0103 memory: 14901 loss: 1.8426 loss_prob: 1.0532 loss_thr: 0.6163 loss_db: 0.1731 2022/11/02 14:25:37 - mmengine - INFO - Epoch(train) [215][25/63] lr: 1.8123e-03 eta: 10:08:59 time: 0.5340 data_time: 0.0355 memory: 14901 loss: 1.8494 loss_prob: 1.0666 loss_thr: 0.6098 loss_db: 0.1729 2022/11/02 14:25:40 - mmengine - INFO - Epoch(train) [215][30/63] lr: 1.8123e-03 eta: 10:08:51 time: 0.5601 data_time: 0.0384 memory: 14901 loss: 1.8550 loss_prob: 1.0804 loss_thr: 0.6040 loss_db: 0.1705 2022/11/02 14:25:42 - mmengine - INFO - Epoch(train) [215][35/63] lr: 1.8123e-03 eta: 10:08:51 time: 0.5488 data_time: 0.0213 memory: 14901 loss: 1.8926 loss_prob: 1.0952 loss_thr: 0.6224 loss_db: 0.1750 2022/11/02 14:25:45 - mmengine - INFO - Epoch(train) [215][40/63] lr: 1.8123e-03 eta: 10:08:43 time: 0.5339 data_time: 0.0194 memory: 14901 loss: 1.8441 loss_prob: 1.0497 loss_thr: 0.6209 loss_db: 0.1734 2022/11/02 14:25:47 - mmengine - INFO - Epoch(train) [215][45/63] lr: 1.8123e-03 eta: 10:08:43 time: 0.5075 data_time: 0.0123 memory: 14901 loss: 1.8088 loss_prob: 1.0341 loss_thr: 0.6037 loss_db: 0.1710 2022/11/02 14:25:50 - mmengine - INFO - Epoch(train) [215][50/63] lr: 1.8123e-03 eta: 10:08:33 time: 0.4949 data_time: 0.0235 memory: 14901 loss: 1.9635 loss_prob: 1.1591 loss_thr: 0.6094 loss_db: 0.1951 2022/11/02 14:25:53 - mmengine - INFO - Epoch(train) [215][55/63] lr: 1.8123e-03 eta: 10:08:33 time: 0.5137 data_time: 0.0234 memory: 14901 loss: 2.1719 loss_prob: 1.3277 loss_thr: 0.6201 loss_db: 0.2241 2022/11/02 14:25:55 - mmengine - INFO - Epoch(train) [215][60/63] lr: 1.8123e-03 eta: 10:08:25 time: 0.5353 data_time: 0.0125 memory: 14901 loss: 2.4007 loss_prob: 1.5039 loss_thr: 0.6451 loss_db: 0.2517 2022/11/02 14:25:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:26:03 - mmengine - INFO - Epoch(train) [216][5/63] lr: 1.8106e-03 eta: 10:08:25 time: 0.8664 data_time: 0.2431 memory: 14901 loss: 2.4323 loss_prob: 1.5147 loss_thr: 0.6629 loss_db: 0.2548 2022/11/02 14:26:06 - mmengine - INFO - Epoch(train) [216][10/63] lr: 1.8106e-03 eta: 10:08:23 time: 0.9084 data_time: 0.2443 memory: 14901 loss: 2.1684 loss_prob: 1.3161 loss_thr: 0.6358 loss_db: 0.2166 2022/11/02 14:26:09 - mmengine - INFO - Epoch(train) [216][15/63] lr: 1.8106e-03 eta: 10:08:23 time: 0.6193 data_time: 0.0192 memory: 14901 loss: 2.0272 loss_prob: 1.2056 loss_thr: 0.6223 loss_db: 0.1993 2022/11/02 14:26:12 - mmengine - INFO - Epoch(train) [216][20/63] lr: 1.8106e-03 eta: 10:08:17 time: 0.5815 data_time: 0.0167 memory: 14901 loss: 2.1593 loss_prob: 1.3148 loss_thr: 0.6325 loss_db: 0.2121 2022/11/02 14:26:15 - mmengine - INFO - Epoch(train) [216][25/63] lr: 1.8106e-03 eta: 10:08:17 time: 0.5209 data_time: 0.0174 memory: 14901 loss: 2.2474 loss_prob: 1.3913 loss_thr: 0.6352 loss_db: 0.2209 2022/11/02 14:26:17 - mmengine - INFO - Epoch(train) [216][30/63] lr: 1.8106e-03 eta: 10:08:09 time: 0.5380 data_time: 0.0315 memory: 14901 loss: 2.0598 loss_prob: 1.2297 loss_thr: 0.6313 loss_db: 0.1988 2022/11/02 14:26:20 - mmengine - INFO - Epoch(train) [216][35/63] lr: 1.8106e-03 eta: 10:08:09 time: 0.5262 data_time: 0.0287 memory: 14901 loss: 2.0476 loss_prob: 1.2169 loss_thr: 0.6323 loss_db: 0.1984 2022/11/02 14:26:23 - mmengine - INFO - Epoch(train) [216][40/63] lr: 1.8106e-03 eta: 10:08:02 time: 0.5518 data_time: 0.0175 memory: 14901 loss: 2.0970 loss_prob: 1.2400 loss_thr: 0.6544 loss_db: 0.2026 2022/11/02 14:26:25 - mmengine - INFO - Epoch(train) [216][45/63] lr: 1.8106e-03 eta: 10:08:02 time: 0.5491 data_time: 0.0126 memory: 14901 loss: 1.9119 loss_prob: 1.0927 loss_thr: 0.6397 loss_db: 0.1795 2022/11/02 14:26:28 - mmengine - INFO - Epoch(train) [216][50/63] lr: 1.8106e-03 eta: 10:07:53 time: 0.5240 data_time: 0.0213 memory: 14901 loss: 1.9712 loss_prob: 1.1501 loss_thr: 0.6317 loss_db: 0.1895 2022/11/02 14:26:31 - mmengine - INFO - Epoch(train) [216][55/63] lr: 1.8106e-03 eta: 10:07:53 time: 0.5441 data_time: 0.0198 memory: 14901 loss: 2.1273 loss_prob: 1.2625 loss_thr: 0.6574 loss_db: 0.2074 2022/11/02 14:26:33 - mmengine - INFO - Epoch(train) [216][60/63] lr: 1.8106e-03 eta: 10:07:45 time: 0.5494 data_time: 0.0118 memory: 14901 loss: 2.0055 loss_prob: 1.1760 loss_thr: 0.6365 loss_db: 0.1931 2022/11/02 14:26:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:26:41 - mmengine - INFO - Epoch(train) [217][5/63] lr: 1.8090e-03 eta: 10:07:45 time: 0.9006 data_time: 0.2113 memory: 14901 loss: 2.0785 loss_prob: 1.2555 loss_thr: 0.6216 loss_db: 0.2013 2022/11/02 14:26:44 - mmengine - INFO - Epoch(train) [217][10/63] lr: 1.8090e-03 eta: 10:07:46 time: 0.9537 data_time: 0.2097 memory: 14901 loss: 2.0434 loss_prob: 1.2226 loss_thr: 0.6236 loss_db: 0.1971 2022/11/02 14:26:47 - mmengine - INFO - Epoch(train) [217][15/63] lr: 1.8090e-03 eta: 10:07:46 time: 0.5530 data_time: 0.0089 memory: 14901 loss: 1.9822 loss_prob: 1.1680 loss_thr: 0.6218 loss_db: 0.1924 2022/11/02 14:26:49 - mmengine - INFO - Epoch(train) [217][20/63] lr: 1.8090e-03 eta: 10:07:37 time: 0.5278 data_time: 0.0121 memory: 14901 loss: 1.8796 loss_prob: 1.0863 loss_thr: 0.6114 loss_db: 0.1819 2022/11/02 14:26:52 - mmengine - INFO - Epoch(train) [217][25/63] lr: 1.8090e-03 eta: 10:07:37 time: 0.5133 data_time: 0.0173 memory: 14901 loss: 1.9615 loss_prob: 1.1227 loss_thr: 0.6524 loss_db: 0.1864 2022/11/02 14:26:55 - mmengine - INFO - Epoch(train) [217][30/63] lr: 1.8090e-03 eta: 10:07:29 time: 0.5379 data_time: 0.0401 memory: 14901 loss: 2.0602 loss_prob: 1.1939 loss_thr: 0.6607 loss_db: 0.2055 2022/11/02 14:26:58 - mmengine - INFO - Epoch(train) [217][35/63] lr: 1.8090e-03 eta: 10:07:29 time: 0.5905 data_time: 0.0366 memory: 14901 loss: 2.0916 loss_prob: 1.2516 loss_thr: 0.6313 loss_db: 0.2087 2022/11/02 14:27:00 - mmengine - INFO - Epoch(train) [217][40/63] lr: 1.8090e-03 eta: 10:07:23 time: 0.5703 data_time: 0.0122 memory: 14901 loss: 2.0220 loss_prob: 1.1932 loss_thr: 0.6402 loss_db: 0.1886 2022/11/02 14:27:03 - mmengine - INFO - Epoch(train) [217][45/63] lr: 1.8090e-03 eta: 10:07:23 time: 0.5516 data_time: 0.0094 memory: 14901 loss: 2.0373 loss_prob: 1.1988 loss_thr: 0.6420 loss_db: 0.1965 2022/11/02 14:27:06 - mmengine - INFO - Epoch(train) [217][50/63] lr: 1.8090e-03 eta: 10:07:15 time: 0.5512 data_time: 0.0163 memory: 14901 loss: 2.0951 loss_prob: 1.2671 loss_thr: 0.6234 loss_db: 0.2045 2022/11/02 14:27:09 - mmengine - INFO - Epoch(train) [217][55/63] lr: 1.8090e-03 eta: 10:07:15 time: 0.5676 data_time: 0.0295 memory: 14901 loss: 2.0905 loss_prob: 1.2565 loss_thr: 0.6276 loss_db: 0.2063 2022/11/02 14:27:12 - mmengine - INFO - Epoch(train) [217][60/63] lr: 1.8090e-03 eta: 10:07:09 time: 0.5840 data_time: 0.0246 memory: 14901 loss: 2.0076 loss_prob: 1.2058 loss_thr: 0.5929 loss_db: 0.2089 2022/11/02 14:27:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:27:19 - mmengine - INFO - Epoch(train) [218][5/63] lr: 1.8073e-03 eta: 10:07:09 time: 0.8013 data_time: 0.2260 memory: 14901 loss: 2.0937 loss_prob: 1.2485 loss_thr: 0.6425 loss_db: 0.2027 2022/11/02 14:27:21 - mmengine - INFO - Epoch(train) [218][10/63] lr: 1.8073e-03 eta: 10:07:03 time: 0.8086 data_time: 0.2278 memory: 14901 loss: 2.1128 loss_prob: 1.2635 loss_thr: 0.6368 loss_db: 0.2126 2022/11/02 14:27:25 - mmengine - INFO - Epoch(train) [218][15/63] lr: 1.8073e-03 eta: 10:07:03 time: 0.5962 data_time: 0.0121 memory: 14901 loss: 2.1307 loss_prob: 1.2786 loss_thr: 0.6368 loss_db: 0.2153 2022/11/02 14:27:27 - mmengine - INFO - Epoch(train) [218][20/63] lr: 1.8073e-03 eta: 10:06:56 time: 0.5653 data_time: 0.0109 memory: 14901 loss: 2.0619 loss_prob: 1.2148 loss_thr: 0.6473 loss_db: 0.1997 2022/11/02 14:27:30 - mmengine - INFO - Epoch(train) [218][25/63] lr: 1.8073e-03 eta: 10:06:56 time: 0.5309 data_time: 0.0278 memory: 14901 loss: 1.9303 loss_prob: 1.1232 loss_thr: 0.6219 loss_db: 0.1852 2022/11/02 14:27:33 - mmengine - INFO - Epoch(train) [218][30/63] lr: 1.8073e-03 eta: 10:06:50 time: 0.5887 data_time: 0.0522 memory: 14901 loss: 1.9572 loss_prob: 1.1537 loss_thr: 0.6176 loss_db: 0.1859 2022/11/02 14:27:36 - mmengine - INFO - Epoch(train) [218][35/63] lr: 1.8073e-03 eta: 10:06:50 time: 0.5631 data_time: 0.0390 memory: 14901 loss: 1.9419 loss_prob: 1.1360 loss_thr: 0.6190 loss_db: 0.1870 2022/11/02 14:27:38 - mmengine - INFO - Epoch(train) [218][40/63] lr: 1.8073e-03 eta: 10:06:42 time: 0.5407 data_time: 0.0137 memory: 14901 loss: 1.8960 loss_prob: 1.0888 loss_thr: 0.6254 loss_db: 0.1818 2022/11/02 14:27:41 - mmengine - INFO - Epoch(train) [218][45/63] lr: 1.8073e-03 eta: 10:06:42 time: 0.5508 data_time: 0.0168 memory: 14901 loss: 1.9122 loss_prob: 1.1210 loss_thr: 0.6080 loss_db: 0.1832 2022/11/02 14:27:44 - mmengine - INFO - Epoch(train) [218][50/63] lr: 1.8073e-03 eta: 10:06:36 time: 0.5821 data_time: 0.0353 memory: 14901 loss: 1.8730 loss_prob: 1.1008 loss_thr: 0.5923 loss_db: 0.1799 2022/11/02 14:27:47 - mmengine - INFO - Epoch(train) [218][55/63] lr: 1.8073e-03 eta: 10:06:36 time: 0.6000 data_time: 0.0268 memory: 14901 loss: 2.0086 loss_prob: 1.1876 loss_thr: 0.6257 loss_db: 0.1953 2022/11/02 14:27:50 - mmengine - INFO - Epoch(train) [218][60/63] lr: 1.8073e-03 eta: 10:06:29 time: 0.5664 data_time: 0.0078 memory: 14901 loss: 2.0599 loss_prob: 1.2362 loss_thr: 0.6205 loss_db: 0.2031 2022/11/02 14:27:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:27:57 - mmengine - INFO - Epoch(train) [219][5/63] lr: 1.8057e-03 eta: 10:06:29 time: 0.8190 data_time: 0.2233 memory: 14901 loss: 1.9005 loss_prob: 1.1260 loss_thr: 0.5964 loss_db: 0.1782 2022/11/02 14:28:00 - mmengine - INFO - Epoch(train) [219][10/63] lr: 1.8057e-03 eta: 10:06:26 time: 0.8524 data_time: 0.2286 memory: 14901 loss: 1.7891 loss_prob: 1.0248 loss_thr: 0.5966 loss_db: 0.1677 2022/11/02 14:28:03 - mmengine - INFO - Epoch(train) [219][15/63] lr: 1.8057e-03 eta: 10:06:26 time: 0.5869 data_time: 0.0136 memory: 14901 loss: 1.9321 loss_prob: 1.1264 loss_thr: 0.6199 loss_db: 0.1859 2022/11/02 14:28:05 - mmengine - INFO - Epoch(train) [219][20/63] lr: 1.8057e-03 eta: 10:06:17 time: 0.5323 data_time: 0.0111 memory: 14901 loss: 1.9588 loss_prob: 1.1467 loss_thr: 0.6261 loss_db: 0.1859 2022/11/02 14:28:09 - mmengine - INFO - Epoch(train) [219][25/63] lr: 1.8057e-03 eta: 10:06:17 time: 0.6218 data_time: 0.0227 memory: 14901 loss: 1.9750 loss_prob: 1.1515 loss_thr: 0.6359 loss_db: 0.1876 2022/11/02 14:28:13 - mmengine - INFO - Epoch(train) [219][30/63] lr: 1.8057e-03 eta: 10:06:18 time: 0.7325 data_time: 0.0440 memory: 14901 loss: 1.9021 loss_prob: 1.1079 loss_thr: 0.6167 loss_db: 0.1775 2022/11/02 14:28:15 - mmengine - INFO - Epoch(train) [219][35/63] lr: 1.8057e-03 eta: 10:06:18 time: 0.6200 data_time: 0.0334 memory: 14901 loss: 1.6940 loss_prob: 0.9648 loss_thr: 0.5737 loss_db: 0.1555 2022/11/02 14:28:18 - mmengine - INFO - Epoch(train) [219][40/63] lr: 1.8057e-03 eta: 10:06:10 time: 0.5414 data_time: 0.0137 memory: 14901 loss: 1.7788 loss_prob: 1.0298 loss_thr: 0.5783 loss_db: 0.1707 2022/11/02 14:28:21 - mmengine - INFO - Epoch(train) [219][45/63] lr: 1.8057e-03 eta: 10:06:10 time: 0.5690 data_time: 0.0140 memory: 14901 loss: 1.8923 loss_prob: 1.1227 loss_thr: 0.5845 loss_db: 0.1850 2022/11/02 14:28:24 - mmengine - INFO - Epoch(train) [219][50/63] lr: 1.8057e-03 eta: 10:06:03 time: 0.5690 data_time: 0.0158 memory: 14901 loss: 1.8347 loss_prob: 1.0683 loss_thr: 0.5923 loss_db: 0.1740 2022/11/02 14:28:27 - mmengine - INFO - Epoch(train) [219][55/63] lr: 1.8057e-03 eta: 10:06:03 time: 0.6109 data_time: 0.0270 memory: 14901 loss: 1.8054 loss_prob: 1.0224 loss_thr: 0.6143 loss_db: 0.1687 2022/11/02 14:28:29 - mmengine - INFO - Epoch(train) [219][60/63] lr: 1.8057e-03 eta: 10:05:56 time: 0.5602 data_time: 0.0210 memory: 14901 loss: 1.8887 loss_prob: 1.0766 loss_thr: 0.6308 loss_db: 0.1814 2022/11/02 14:28:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:28:36 - mmengine - INFO - Epoch(train) [220][5/63] lr: 1.8040e-03 eta: 10:05:56 time: 0.7788 data_time: 0.2283 memory: 14901 loss: 1.9529 loss_prob: 1.1372 loss_thr: 0.6280 loss_db: 0.1877 2022/11/02 14:28:39 - mmengine - INFO - Epoch(train) [220][10/63] lr: 1.8040e-03 eta: 10:05:50 time: 0.8002 data_time: 0.2288 memory: 14901 loss: 1.8994 loss_prob: 1.0999 loss_thr: 0.6168 loss_db: 0.1827 2022/11/02 14:28:41 - mmengine - INFO - Epoch(train) [220][15/63] lr: 1.8040e-03 eta: 10:05:50 time: 0.4913 data_time: 0.0063 memory: 14901 loss: 1.8446 loss_prob: 1.0516 loss_thr: 0.6186 loss_db: 0.1744 2022/11/02 14:28:44 - mmengine - INFO - Epoch(train) [220][20/63] lr: 1.8040e-03 eta: 10:05:40 time: 0.5066 data_time: 0.0103 memory: 14901 loss: 1.7816 loss_prob: 1.0042 loss_thr: 0.6103 loss_db: 0.1670 2022/11/02 14:28:47 - mmengine - INFO - Epoch(train) [220][25/63] lr: 1.8040e-03 eta: 10:05:40 time: 0.5906 data_time: 0.0493 memory: 14901 loss: 2.1321 loss_prob: 1.3012 loss_thr: 0.6268 loss_db: 0.2041 2022/11/02 14:28:50 - mmengine - INFO - Epoch(train) [220][30/63] lr: 1.8040e-03 eta: 10:05:35 time: 0.5908 data_time: 0.0460 memory: 14901 loss: 2.2965 loss_prob: 1.4326 loss_thr: 0.6425 loss_db: 0.2214 2022/11/02 14:28:52 - mmengine - INFO - Epoch(train) [220][35/63] lr: 1.8040e-03 eta: 10:05:35 time: 0.5593 data_time: 0.0083 memory: 14901 loss: 1.9392 loss_prob: 1.1458 loss_thr: 0.6088 loss_db: 0.1845 2022/11/02 14:28:55 - mmengine - INFO - Epoch(train) [220][40/63] lr: 1.8040e-03 eta: 10:05:27 time: 0.5378 data_time: 0.0073 memory: 14901 loss: 1.8066 loss_prob: 1.0524 loss_thr: 0.5891 loss_db: 0.1651 2022/11/02 14:28:58 - mmengine - INFO - Epoch(train) [220][45/63] lr: 1.8040e-03 eta: 10:05:27 time: 0.5290 data_time: 0.0067 memory: 14901 loss: 1.8298 loss_prob: 1.0604 loss_thr: 0.6006 loss_db: 0.1689 2022/11/02 14:29:01 - mmengine - INFO - Epoch(train) [220][50/63] lr: 1.8040e-03 eta: 10:05:21 time: 0.5915 data_time: 0.0270 memory: 14901 loss: 1.7916 loss_prob: 1.0245 loss_thr: 0.5966 loss_db: 0.1706 2022/11/02 14:29:04 - mmengine - INFO - Epoch(train) [220][55/63] lr: 1.8040e-03 eta: 10:05:21 time: 0.6172 data_time: 0.0264 memory: 14901 loss: 1.8362 loss_prob: 1.0565 loss_thr: 0.6070 loss_db: 0.1727 2022/11/02 14:29:06 - mmengine - INFO - Epoch(train) [220][60/63] lr: 1.8040e-03 eta: 10:05:13 time: 0.5531 data_time: 0.0114 memory: 14901 loss: 1.8344 loss_prob: 1.0525 loss_thr: 0.6120 loss_db: 0.1699 2022/11/02 14:29:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:29:08 - mmengine - INFO - Saving checkpoint at 220 epochs 2022/11/02 14:29:12 - mmengine - INFO - Epoch(val) [220][5/500] eta: 10:05:13 time: 0.0460 data_time: 0.0069 memory: 14901 2022/11/02 14:29:12 - mmengine - INFO - Epoch(val) [220][10/500] eta: 0:00:23 time: 0.0486 data_time: 0.0065 memory: 1008 2022/11/02 14:29:12 - mmengine - INFO - Epoch(val) [220][15/500] eta: 0:00:23 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 14:29:12 - mmengine - INFO - Epoch(val) [220][20/500] eta: 0:00:18 time: 0.0391 data_time: 0.0031 memory: 1008 2022/11/02 14:29:12 - mmengine - INFO - Epoch(val) [220][25/500] eta: 0:00:18 time: 0.0408 data_time: 0.0036 memory: 1008 2022/11/02 14:29:13 - mmengine - INFO - Epoch(val) [220][30/500] eta: 0:00:20 time: 0.0447 data_time: 0.0039 memory: 1008 2022/11/02 14:29:13 - mmengine - INFO - Epoch(val) [220][35/500] eta: 0:00:20 time: 0.0420 data_time: 0.0032 memory: 1008 2022/11/02 14:29:13 - mmengine - INFO - Epoch(val) [220][40/500] eta: 0:00:20 time: 0.0441 data_time: 0.0028 memory: 1008 2022/11/02 14:29:13 - mmengine - INFO - Epoch(val) [220][45/500] eta: 0:00:20 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 14:29:14 - mmengine - INFO - Epoch(val) [220][50/500] eta: 0:00:18 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/02 14:29:14 - mmengine - INFO - Epoch(val) [220][55/500] eta: 0:00:18 time: 0.0451 data_time: 0.0032 memory: 1008 2022/11/02 14:29:14 - mmengine - INFO - Epoch(val) [220][60/500] eta: 0:00:17 time: 0.0403 data_time: 0.0033 memory: 1008 2022/11/02 14:29:14 - mmengine - INFO - Epoch(val) [220][65/500] eta: 0:00:17 time: 0.0408 data_time: 0.0024 memory: 1008 2022/11/02 14:29:14 - mmengine - INFO - Epoch(val) [220][70/500] eta: 0:00:18 time: 0.0431 data_time: 0.0024 memory: 1008 2022/11/02 14:29:15 - mmengine - INFO - Epoch(val) [220][75/500] eta: 0:00:18 time: 0.0401 data_time: 0.0030 memory: 1008 2022/11/02 14:29:15 - mmengine - INFO - Epoch(val) [220][80/500] eta: 0:00:16 time: 0.0391 data_time: 0.0033 memory: 1008 2022/11/02 14:29:15 - mmengine - INFO - Epoch(val) [220][85/500] eta: 0:00:16 time: 0.0364 data_time: 0.0027 memory: 1008 2022/11/02 14:29:15 - mmengine - INFO - Epoch(val) [220][90/500] eta: 0:00:16 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 14:29:15 - mmengine - INFO - Epoch(val) [220][95/500] eta: 0:00:16 time: 0.0452 data_time: 0.0027 memory: 1008 2022/11/02 14:29:16 - mmengine - INFO - Epoch(val) [220][100/500] eta: 0:00:17 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/02 14:29:16 - mmengine - INFO - Epoch(val) [220][105/500] eta: 0:00:17 time: 0.0416 data_time: 0.0039 memory: 1008 2022/11/02 14:29:16 - mmengine - INFO - Epoch(val) [220][110/500] eta: 0:00:15 time: 0.0396 data_time: 0.0037 memory: 1008 2022/11/02 14:29:16 - mmengine - INFO - Epoch(val) [220][115/500] eta: 0:00:15 time: 0.0365 data_time: 0.0023 memory: 1008 2022/11/02 14:29:16 - mmengine - INFO - Epoch(val) [220][120/500] eta: 0:00:15 time: 0.0404 data_time: 0.0032 memory: 1008 2022/11/02 14:29:17 - mmengine - INFO - Epoch(val) [220][125/500] eta: 0:00:15 time: 0.0396 data_time: 0.0034 memory: 1008 2022/11/02 14:29:17 - mmengine - INFO - Epoch(val) [220][130/500] eta: 0:00:12 time: 0.0348 data_time: 0.0023 memory: 1008 2022/11/02 14:29:17 - mmengine - INFO - Epoch(val) [220][135/500] eta: 0:00:12 time: 0.0413 data_time: 0.0024 memory: 1008 2022/11/02 14:29:17 - mmengine - INFO - Epoch(val) [220][140/500] eta: 0:00:15 time: 0.0421 data_time: 0.0024 memory: 1008 2022/11/02 14:29:17 - mmengine - INFO - Epoch(val) [220][145/500] eta: 0:00:15 time: 0.0407 data_time: 0.0023 memory: 1008 2022/11/02 14:29:18 - mmengine - INFO - Epoch(val) [220][150/500] eta: 0:00:15 time: 0.0449 data_time: 0.0026 memory: 1008 2022/11/02 14:29:18 - mmengine - INFO - Epoch(val) [220][155/500] eta: 0:00:15 time: 0.0476 data_time: 0.0028 memory: 1008 2022/11/02 14:29:18 - mmengine - INFO - Epoch(val) [220][160/500] eta: 0:00:15 time: 0.0465 data_time: 0.0028 memory: 1008 2022/11/02 14:29:18 - mmengine - INFO - Epoch(val) [220][165/500] eta: 0:00:15 time: 0.0427 data_time: 0.0030 memory: 1008 2022/11/02 14:29:18 - mmengine - INFO - Epoch(val) [220][170/500] eta: 0:00:13 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 14:29:19 - mmengine - INFO - Epoch(val) [220][175/500] eta: 0:00:13 time: 0.0376 data_time: 0.0025 memory: 1008 2022/11/02 14:29:19 - mmengine - INFO - Epoch(val) [220][180/500] eta: 0:00:13 time: 0.0435 data_time: 0.0041 memory: 1008 2022/11/02 14:29:19 - mmengine - INFO - Epoch(val) [220][185/500] eta: 0:00:13 time: 0.0466 data_time: 0.0042 memory: 1008 2022/11/02 14:29:19 - mmengine - INFO - Epoch(val) [220][190/500] eta: 0:00:12 time: 0.0413 data_time: 0.0025 memory: 1008 2022/11/02 14:29:19 - mmengine - INFO - Epoch(val) [220][195/500] eta: 0:00:12 time: 0.0378 data_time: 0.0025 memory: 1008 2022/11/02 14:29:20 - mmengine - INFO - Epoch(val) [220][200/500] eta: 0:00:12 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 14:29:20 - mmengine - INFO - Epoch(val) [220][205/500] eta: 0:00:12 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/02 14:29:20 - mmengine - INFO - Epoch(val) [220][210/500] eta: 0:00:11 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 14:29:20 - mmengine - INFO - Epoch(val) [220][215/500] eta: 0:00:11 time: 0.0433 data_time: 0.0033 memory: 1008 2022/11/02 14:29:21 - mmengine - INFO - Epoch(val) [220][220/500] eta: 0:00:12 time: 0.0459 data_time: 0.0033 memory: 1008 2022/11/02 14:29:21 - mmengine - INFO - Epoch(val) [220][225/500] eta: 0:00:12 time: 0.0434 data_time: 0.0027 memory: 1008 2022/11/02 14:29:21 - mmengine - INFO - Epoch(val) [220][230/500] eta: 0:00:10 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 14:29:21 - mmengine - INFO - Epoch(val) [220][235/500] eta: 0:00:10 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/02 14:29:21 - mmengine - INFO - Epoch(val) [220][240/500] eta: 0:00:11 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 14:29:22 - mmengine - INFO - Epoch(val) [220][245/500] eta: 0:00:11 time: 0.0440 data_time: 0.0041 memory: 1008 2022/11/02 14:29:22 - mmengine - INFO - Epoch(val) [220][250/500] eta: 0:00:11 time: 0.0442 data_time: 0.0040 memory: 1008 2022/11/02 14:29:22 - mmengine - INFO - Epoch(val) [220][255/500] eta: 0:00:11 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/02 14:29:22 - mmengine - INFO - Epoch(val) [220][260/500] eta: 0:00:08 time: 0.0348 data_time: 0.0023 memory: 1008 2022/11/02 14:29:22 - mmengine - INFO - Epoch(val) [220][265/500] eta: 0:00:08 time: 0.0368 data_time: 0.0024 memory: 1008 2022/11/02 14:29:23 - mmengine - INFO - Epoch(val) [220][270/500] eta: 0:00:09 time: 0.0397 data_time: 0.0028 memory: 1008 2022/11/02 14:29:23 - mmengine - INFO - Epoch(val) [220][275/500] eta: 0:00:09 time: 0.0381 data_time: 0.0028 memory: 1008 2022/11/02 14:29:23 - mmengine - INFO - Epoch(val) [220][280/500] eta: 0:00:08 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 14:29:23 - mmengine - INFO - Epoch(val) [220][285/500] eta: 0:00:08 time: 0.0391 data_time: 0.0024 memory: 1008 2022/11/02 14:29:23 - mmengine - INFO - Epoch(val) [220][290/500] eta: 0:00:08 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 14:29:24 - mmengine - INFO - Epoch(val) [220][295/500] eta: 0:00:08 time: 0.0446 data_time: 0.0028 memory: 1008 2022/11/02 14:29:24 - mmengine - INFO - Epoch(val) [220][300/500] eta: 0:00:08 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/02 14:29:24 - mmengine - INFO - Epoch(val) [220][305/500] eta: 0:00:08 time: 0.0416 data_time: 0.0031 memory: 1008 2022/11/02 14:29:24 - mmengine - INFO - Epoch(val) [220][310/500] eta: 0:00:08 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/02 14:29:24 - mmengine - INFO - Epoch(val) [220][315/500] eta: 0:00:08 time: 0.0477 data_time: 0.0034 memory: 1008 2022/11/02 14:29:25 - mmengine - INFO - Epoch(val) [220][320/500] eta: 0:00:08 time: 0.0483 data_time: 0.0035 memory: 1008 2022/11/02 14:29:25 - mmengine - INFO - Epoch(val) [220][325/500] eta: 0:00:08 time: 0.0539 data_time: 0.0028 memory: 1008 2022/11/02 14:29:25 - mmengine - INFO - Epoch(val) [220][330/500] eta: 0:00:09 time: 0.0536 data_time: 0.0028 memory: 1008 2022/11/02 14:29:25 - mmengine - INFO - Epoch(val) [220][335/500] eta: 0:00:09 time: 0.0404 data_time: 0.0031 memory: 1008 2022/11/02 14:29:26 - mmengine - INFO - Epoch(val) [220][340/500] eta: 0:00:07 time: 0.0498 data_time: 0.0030 memory: 1008 2022/11/02 14:29:26 - mmengine - INFO - Epoch(val) [220][345/500] eta: 0:00:07 time: 0.0528 data_time: 0.0030 memory: 1008 2022/11/02 14:29:26 - mmengine - INFO - Epoch(val) [220][350/500] eta: 0:00:07 time: 0.0479 data_time: 0.0031 memory: 1008 2022/11/02 14:29:26 - mmengine - INFO - Epoch(val) [220][355/500] eta: 0:00:07 time: 0.0472 data_time: 0.0030 memory: 1008 2022/11/02 14:29:27 - mmengine - INFO - Epoch(val) [220][360/500] eta: 0:00:05 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/02 14:29:27 - mmengine - INFO - Epoch(val) [220][365/500] eta: 0:00:05 time: 0.0448 data_time: 0.0028 memory: 1008 2022/11/02 14:29:27 - mmengine - INFO - Epoch(val) [220][370/500] eta: 0:00:05 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/02 14:29:27 - mmengine - INFO - Epoch(val) [220][375/500] eta: 0:00:05 time: 0.0400 data_time: 0.0033 memory: 1008 2022/11/02 14:29:28 - mmengine - INFO - Epoch(val) [220][380/500] eta: 0:00:05 time: 0.0480 data_time: 0.0035 memory: 1008 2022/11/02 14:29:28 - mmengine - INFO - Epoch(val) [220][385/500] eta: 0:00:05 time: 0.0489 data_time: 0.0032 memory: 1008 2022/11/02 14:29:28 - mmengine - INFO - Epoch(val) [220][390/500] eta: 0:00:04 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 14:29:28 - mmengine - INFO - Epoch(val) [220][395/500] eta: 0:00:04 time: 0.0396 data_time: 0.0028 memory: 1008 2022/11/02 14:29:28 - mmengine - INFO - Epoch(val) [220][400/500] eta: 0:00:04 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 14:29:29 - mmengine - INFO - Epoch(val) [220][405/500] eta: 0:00:04 time: 0.0456 data_time: 0.0031 memory: 1008 2022/11/02 14:29:29 - mmengine - INFO - Epoch(val) [220][410/500] eta: 0:00:04 time: 0.0491 data_time: 0.0035 memory: 1008 2022/11/02 14:29:29 - mmengine - INFO - Epoch(val) [220][415/500] eta: 0:00:04 time: 0.0467 data_time: 0.0035 memory: 1008 2022/11/02 14:29:30 - mmengine - INFO - Epoch(val) [220][420/500] eta: 0:00:05 time: 0.0654 data_time: 0.0241 memory: 1008 2022/11/02 14:29:30 - mmengine - INFO - Epoch(val) [220][425/500] eta: 0:00:05 time: 0.0671 data_time: 0.0236 memory: 1008 2022/11/02 14:29:30 - mmengine - INFO - Epoch(val) [220][430/500] eta: 0:00:02 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 14:29:30 - mmengine - INFO - Epoch(val) [220][435/500] eta: 0:00:02 time: 0.0419 data_time: 0.0034 memory: 1008 2022/11/02 14:29:30 - mmengine - INFO - Epoch(val) [220][440/500] eta: 0:00:03 time: 0.0507 data_time: 0.0045 memory: 1008 2022/11/02 14:29:31 - mmengine - INFO - Epoch(val) [220][445/500] eta: 0:00:03 time: 0.0561 data_time: 0.0043 memory: 1008 2022/11/02 14:29:31 - mmengine - INFO - Epoch(val) [220][450/500] eta: 0:00:02 time: 0.0476 data_time: 0.0032 memory: 1008 2022/11/02 14:29:31 - mmengine - INFO - Epoch(val) [220][455/500] eta: 0:00:02 time: 0.0382 data_time: 0.0029 memory: 1008 2022/11/02 14:29:31 - mmengine - INFO - Epoch(val) [220][460/500] eta: 0:00:01 time: 0.0353 data_time: 0.0024 memory: 1008 2022/11/02 14:29:31 - mmengine - INFO - Epoch(val) [220][465/500] eta: 0:00:01 time: 0.0359 data_time: 0.0021 memory: 1008 2022/11/02 14:29:32 - mmengine - INFO - Epoch(val) [220][470/500] eta: 0:00:01 time: 0.0375 data_time: 0.0023 memory: 1008 2022/11/02 14:29:32 - mmengine - INFO - Epoch(val) [220][475/500] eta: 0:00:01 time: 0.0367 data_time: 0.0027 memory: 1008 2022/11/02 14:29:32 - mmengine - INFO - Epoch(val) [220][480/500] eta: 0:00:00 time: 0.0401 data_time: 0.0035 memory: 1008 2022/11/02 14:29:32 - mmengine - INFO - Epoch(val) [220][485/500] eta: 0:00:00 time: 0.0405 data_time: 0.0035 memory: 1008 2022/11/02 14:29:32 - mmengine - INFO - Epoch(val) [220][490/500] eta: 0:00:00 time: 0.0411 data_time: 0.0033 memory: 1008 2022/11/02 14:29:33 - mmengine - INFO - Epoch(val) [220][495/500] eta: 0:00:00 time: 0.0452 data_time: 0.0055 memory: 1008 2022/11/02 14:29:33 - mmengine - INFO - Epoch(val) [220][500/500] eta: 0:00:00 time: 0.0397 data_time: 0.0047 memory: 1008 2022/11/02 14:29:33 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8142, precision: 0.6916, hmean: 0.7479 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8142, precision: 0.7707, hmean: 0.7919 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8065, precision: 0.8191, hmean: 0.8127 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7872, precision: 0.8623, hmean: 0.8231 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7116, precision: 0.9129, hmean: 0.7998 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2898, precision: 0.9663, hmean: 0.4459 2022/11/02 14:29:33 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0005, precision: 1.0000, hmean: 0.0010 2022/11/02 14:29:33 - mmengine - INFO - Epoch(val) [220][500/500] icdar/precision: 0.8623 icdar/recall: 0.7872 icdar/hmean: 0.8231 2022/11/02 14:29:40 - mmengine - INFO - Epoch(train) [221][5/63] lr: 1.8023e-03 eta: 0:00:00 time: 0.8885 data_time: 0.2381 memory: 14901 loss: 1.7302 loss_prob: 0.9787 loss_thr: 0.5864 loss_db: 0.1652 2022/11/02 14:29:42 - mmengine - INFO - Epoch(train) [221][10/63] lr: 1.8023e-03 eta: 10:05:14 time: 0.9442 data_time: 0.2381 memory: 14901 loss: 1.8591 loss_prob: 1.0944 loss_thr: 0.5960 loss_db: 0.1687 2022/11/02 14:29:46 - mmengine - INFO - Epoch(train) [221][15/63] lr: 1.8023e-03 eta: 10:05:14 time: 0.5876 data_time: 0.0085 memory: 14901 loss: 1.8474 loss_prob: 1.0920 loss_thr: 0.5860 loss_db: 0.1694 2022/11/02 14:29:48 - mmengine - INFO - Epoch(train) [221][20/63] lr: 1.8023e-03 eta: 10:05:07 time: 0.5724 data_time: 0.0094 memory: 14901 loss: 1.7947 loss_prob: 1.0245 loss_thr: 0.6010 loss_db: 0.1693 2022/11/02 14:29:51 - mmengine - INFO - Epoch(train) [221][25/63] lr: 1.8023e-03 eta: 10:05:07 time: 0.5302 data_time: 0.0113 memory: 14901 loss: 1.7381 loss_prob: 0.9869 loss_thr: 0.5884 loss_db: 0.1629 2022/11/02 14:29:54 - mmengine - INFO - Epoch(train) [221][30/63] lr: 1.8023e-03 eta: 10:05:00 time: 0.5503 data_time: 0.0371 memory: 14901 loss: 1.6672 loss_prob: 0.9485 loss_thr: 0.5600 loss_db: 0.1587 2022/11/02 14:29:57 - mmengine - INFO - Epoch(train) [221][35/63] lr: 1.8023e-03 eta: 10:05:00 time: 0.5986 data_time: 0.0342 memory: 14901 loss: 1.8513 loss_prob: 1.0804 loss_thr: 0.5946 loss_db: 0.1763 2022/11/02 14:29:59 - mmengine - INFO - Epoch(train) [221][40/63] lr: 1.8023e-03 eta: 10:04:53 time: 0.5654 data_time: 0.0124 memory: 14901 loss: 1.9430 loss_prob: 1.1421 loss_thr: 0.6139 loss_db: 0.1870 2022/11/02 14:30:02 - mmengine - INFO - Epoch(train) [221][45/63] lr: 1.8023e-03 eta: 10:04:53 time: 0.5504 data_time: 0.0124 memory: 14901 loss: 1.9012 loss_prob: 1.1121 loss_thr: 0.6048 loss_db: 0.1842 2022/11/02 14:30:05 - mmengine - INFO - Epoch(train) [221][50/63] lr: 1.8023e-03 eta: 10:04:45 time: 0.5542 data_time: 0.0167 memory: 14901 loss: 1.8949 loss_prob: 1.0994 loss_thr: 0.6155 loss_db: 0.1799 2022/11/02 14:30:08 - mmengine - INFO - Epoch(train) [221][55/63] lr: 1.8023e-03 eta: 10:04:45 time: 0.5317 data_time: 0.0309 memory: 14901 loss: 1.8913 loss_prob: 1.0833 loss_thr: 0.6295 loss_db: 0.1786 2022/11/02 14:30:10 - mmengine - INFO - Epoch(train) [221][60/63] lr: 1.8023e-03 eta: 10:04:37 time: 0.5232 data_time: 0.0225 memory: 14901 loss: 1.8784 loss_prob: 1.0791 loss_thr: 0.6192 loss_db: 0.1801 2022/11/02 14:30:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:30:18 - mmengine - INFO - Epoch(train) [222][5/63] lr: 1.8007e-03 eta: 10:04:37 time: 0.9392 data_time: 0.2551 memory: 14901 loss: 1.9006 loss_prob: 1.0947 loss_thr: 0.6243 loss_db: 0.1817 2022/11/02 14:30:21 - mmengine - INFO - Epoch(train) [222][10/63] lr: 1.8007e-03 eta: 10:04:39 time: 0.9996 data_time: 0.2555 memory: 14901 loss: 1.8616 loss_prob: 1.0626 loss_thr: 0.6250 loss_db: 0.1739 2022/11/02 14:30:24 - mmengine - INFO - Epoch(train) [222][15/63] lr: 1.8007e-03 eta: 10:04:39 time: 0.5578 data_time: 0.0067 memory: 14901 loss: 1.9394 loss_prob: 1.1323 loss_thr: 0.6212 loss_db: 0.1860 2022/11/02 14:30:27 - mmengine - INFO - Epoch(train) [222][20/63] lr: 1.8007e-03 eta: 10:04:32 time: 0.5614 data_time: 0.0081 memory: 14901 loss: 2.0433 loss_prob: 1.2141 loss_thr: 0.6346 loss_db: 0.1946 2022/11/02 14:30:29 - mmengine - INFO - Epoch(train) [222][25/63] lr: 1.8007e-03 eta: 10:04:32 time: 0.5468 data_time: 0.0199 memory: 14901 loss: 1.8826 loss_prob: 1.0883 loss_thr: 0.6174 loss_db: 0.1769 2022/11/02 14:30:33 - mmengine - INFO - Epoch(train) [222][30/63] lr: 1.8007e-03 eta: 10:04:26 time: 0.5748 data_time: 0.0407 memory: 14901 loss: 1.7258 loss_prob: 0.9715 loss_thr: 0.5916 loss_db: 0.1627 2022/11/02 14:30:35 - mmengine - INFO - Epoch(train) [222][35/63] lr: 1.8007e-03 eta: 10:04:26 time: 0.5797 data_time: 0.0299 memory: 14901 loss: 1.7219 loss_prob: 0.9814 loss_thr: 0.5812 loss_db: 0.1592 2022/11/02 14:30:38 - mmengine - INFO - Epoch(train) [222][40/63] lr: 1.8007e-03 eta: 10:04:17 time: 0.5224 data_time: 0.0086 memory: 14901 loss: 1.7274 loss_prob: 0.9839 loss_thr: 0.5853 loss_db: 0.1582 2022/11/02 14:30:41 - mmengine - INFO - Epoch(train) [222][45/63] lr: 1.8007e-03 eta: 10:04:17 time: 0.5354 data_time: 0.0074 memory: 14901 loss: 1.7849 loss_prob: 1.0188 loss_thr: 0.5960 loss_db: 0.1701 2022/11/02 14:30:43 - mmengine - INFO - Epoch(train) [222][50/63] lr: 1.8007e-03 eta: 10:04:09 time: 0.5403 data_time: 0.0126 memory: 14901 loss: 1.8054 loss_prob: 1.0383 loss_thr: 0.5903 loss_db: 0.1768 2022/11/02 14:30:46 - mmengine - INFO - Epoch(train) [222][55/63] lr: 1.8007e-03 eta: 10:04:09 time: 0.5366 data_time: 0.0286 memory: 14901 loss: 1.7876 loss_prob: 1.0236 loss_thr: 0.5892 loss_db: 0.1749 2022/11/02 14:30:49 - mmengine - INFO - Epoch(train) [222][60/63] lr: 1.8007e-03 eta: 10:04:02 time: 0.5700 data_time: 0.0236 memory: 14901 loss: 1.7900 loss_prob: 1.0264 loss_thr: 0.5907 loss_db: 0.1730 2022/11/02 14:30:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:30:55 - mmengine - INFO - Epoch(train) [223][5/63] lr: 1.7990e-03 eta: 10:04:02 time: 0.7384 data_time: 0.2123 memory: 14901 loss: 1.9755 loss_prob: 1.1513 loss_thr: 0.6373 loss_db: 0.1869 2022/11/02 14:30:59 - mmengine - INFO - Epoch(train) [223][10/63] lr: 1.7990e-03 eta: 10:03:57 time: 0.8295 data_time: 0.2370 memory: 14901 loss: 1.9426 loss_prob: 1.1167 loss_thr: 0.6414 loss_db: 0.1845 2022/11/02 14:31:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:31:02 - mmengine - INFO - Epoch(train) [223][15/63] lr: 1.7990e-03 eta: 10:03:57 time: 0.6266 data_time: 0.0543 memory: 14901 loss: 1.8338 loss_prob: 1.0436 loss_thr: 0.6163 loss_db: 0.1739 2022/11/02 14:31:04 - mmengine - INFO - Epoch(train) [223][20/63] lr: 1.7990e-03 eta: 10:03:51 time: 0.5813 data_time: 0.0311 memory: 14901 loss: 1.9661 loss_prob: 1.1683 loss_thr: 0.6058 loss_db: 0.1919 2022/11/02 14:31:07 - mmengine - INFO - Epoch(train) [223][25/63] lr: 1.7990e-03 eta: 10:03:51 time: 0.5387 data_time: 0.0073 memory: 14901 loss: 1.9617 loss_prob: 1.1520 loss_thr: 0.6197 loss_db: 0.1900 2022/11/02 14:31:09 - mmengine - INFO - Epoch(train) [223][30/63] lr: 1.7990e-03 eta: 10:03:41 time: 0.4992 data_time: 0.0066 memory: 14901 loss: 1.9453 loss_prob: 1.1144 loss_thr: 0.6422 loss_db: 0.1887 2022/11/02 14:31:12 - mmengine - INFO - Epoch(train) [223][35/63] lr: 1.7990e-03 eta: 10:03:41 time: 0.5421 data_time: 0.0215 memory: 14901 loss: 2.0016 loss_prob: 1.1847 loss_thr: 0.6212 loss_db: 0.1957 2022/11/02 14:31:15 - mmengine - INFO - Epoch(train) [223][40/63] lr: 1.7990e-03 eta: 10:03:35 time: 0.5702 data_time: 0.0317 memory: 14901 loss: 1.9502 loss_prob: 1.1520 loss_thr: 0.6067 loss_db: 0.1916 2022/11/02 14:31:18 - mmengine - INFO - Epoch(train) [223][45/63] lr: 1.7990e-03 eta: 10:03:35 time: 0.5223 data_time: 0.0213 memory: 14901 loss: 1.9005 loss_prob: 1.0989 loss_thr: 0.6118 loss_db: 0.1898 2022/11/02 14:31:20 - mmengine - INFO - Epoch(train) [223][50/63] lr: 1.7990e-03 eta: 10:03:26 time: 0.5240 data_time: 0.0149 memory: 14901 loss: 1.8042 loss_prob: 1.0364 loss_thr: 0.5942 loss_db: 0.1736 2022/11/02 14:31:23 - mmengine - INFO - Epoch(train) [223][55/63] lr: 1.7990e-03 eta: 10:03:26 time: 0.5224 data_time: 0.0247 memory: 14901 loss: 1.8683 loss_prob: 1.0924 loss_thr: 0.5971 loss_db: 0.1788 2022/11/02 14:31:25 - mmengine - INFO - Epoch(train) [223][60/63] lr: 1.7990e-03 eta: 10:03:17 time: 0.5199 data_time: 0.0217 memory: 14901 loss: 1.8970 loss_prob: 1.1177 loss_thr: 0.5920 loss_db: 0.1872 2022/11/02 14:31:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:31:33 - mmengine - INFO - Epoch(train) [224][5/63] lr: 1.7974e-03 eta: 10:03:17 time: 0.8194 data_time: 0.2217 memory: 14901 loss: 1.8574 loss_prob: 1.0613 loss_thr: 0.6199 loss_db: 0.1762 2022/11/02 14:31:35 - mmengine - INFO - Epoch(train) [224][10/63] lr: 1.7974e-03 eta: 10:03:13 time: 0.8332 data_time: 0.2194 memory: 14901 loss: 1.9437 loss_prob: 1.1445 loss_thr: 0.6119 loss_db: 0.1873 2022/11/02 14:31:38 - mmengine - INFO - Epoch(train) [224][15/63] lr: 1.7974e-03 eta: 10:03:13 time: 0.5281 data_time: 0.0121 memory: 14901 loss: 1.9896 loss_prob: 1.1816 loss_thr: 0.6107 loss_db: 0.1973 2022/11/02 14:31:41 - mmengine - INFO - Epoch(train) [224][20/63] lr: 1.7974e-03 eta: 10:03:06 time: 0.5764 data_time: 0.0115 memory: 14901 loss: 2.0058 loss_prob: 1.1891 loss_thr: 0.6238 loss_db: 0.1929 2022/11/02 14:31:44 - mmengine - INFO - Epoch(train) [224][25/63] lr: 1.7974e-03 eta: 10:03:06 time: 0.6395 data_time: 0.0588 memory: 14901 loss: 1.9582 loss_prob: 1.1600 loss_thr: 0.6135 loss_db: 0.1847 2022/11/02 14:31:47 - mmengine - INFO - Epoch(train) [224][30/63] lr: 1.7974e-03 eta: 10:03:01 time: 0.5965 data_time: 0.0621 memory: 14901 loss: 2.0406 loss_prob: 1.2373 loss_thr: 0.6056 loss_db: 0.1976 2022/11/02 14:31:50 - mmengine - INFO - Epoch(train) [224][35/63] lr: 1.7974e-03 eta: 10:03:01 time: 0.5512 data_time: 0.0095 memory: 14901 loss: 2.0700 loss_prob: 1.2523 loss_thr: 0.6085 loss_db: 0.2093 2022/11/02 14:31:53 - mmengine - INFO - Epoch(train) [224][40/63] lr: 1.7974e-03 eta: 10:02:53 time: 0.5565 data_time: 0.0072 memory: 14901 loss: 2.2346 loss_prob: 1.3798 loss_thr: 0.6345 loss_db: 0.2204 2022/11/02 14:31:55 - mmengine - INFO - Epoch(train) [224][45/63] lr: 1.7974e-03 eta: 10:02:53 time: 0.5509 data_time: 0.0135 memory: 14901 loss: 2.1195 loss_prob: 1.3026 loss_thr: 0.6157 loss_db: 0.2012 2022/11/02 14:31:58 - mmengine - INFO - Epoch(train) [224][50/63] lr: 1.7974e-03 eta: 10:02:46 time: 0.5445 data_time: 0.0315 memory: 14901 loss: 1.7429 loss_prob: 1.0098 loss_thr: 0.5675 loss_db: 0.1656 2022/11/02 14:32:01 - mmengine - INFO - Epoch(train) [224][55/63] lr: 1.7974e-03 eta: 10:02:46 time: 0.5220 data_time: 0.0309 memory: 14901 loss: 1.8371 loss_prob: 1.0953 loss_thr: 0.5638 loss_db: 0.1780 2022/11/02 14:32:03 - mmengine - INFO - Epoch(train) [224][60/63] lr: 1.7974e-03 eta: 10:02:37 time: 0.5238 data_time: 0.0127 memory: 14901 loss: 1.8949 loss_prob: 1.1239 loss_thr: 0.5882 loss_db: 0.1828 2022/11/02 14:32:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:32:10 - mmengine - INFO - Epoch(train) [225][5/63] lr: 1.7957e-03 eta: 10:02:37 time: 0.7982 data_time: 0.2351 memory: 14901 loss: 2.0695 loss_prob: 1.2264 loss_thr: 0.6395 loss_db: 0.2035 2022/11/02 14:32:12 - mmengine - INFO - Epoch(train) [225][10/63] lr: 1.7957e-03 eta: 10:02:30 time: 0.7835 data_time: 0.2368 memory: 14901 loss: 1.9870 loss_prob: 1.1510 loss_thr: 0.6430 loss_db: 0.1930 2022/11/02 14:32:15 - mmengine - INFO - Epoch(train) [225][15/63] lr: 1.7957e-03 eta: 10:02:30 time: 0.4913 data_time: 0.0097 memory: 14901 loss: 1.7645 loss_prob: 1.0028 loss_thr: 0.5960 loss_db: 0.1657 2022/11/02 14:32:17 - mmengine - INFO - Epoch(train) [225][20/63] lr: 1.7957e-03 eta: 10:02:21 time: 0.5062 data_time: 0.0093 memory: 14901 loss: 1.7654 loss_prob: 1.0280 loss_thr: 0.5704 loss_db: 0.1669 2022/11/02 14:32:20 - mmengine - INFO - Epoch(train) [225][25/63] lr: 1.7957e-03 eta: 10:02:21 time: 0.5573 data_time: 0.0388 memory: 14901 loss: 1.7263 loss_prob: 0.9906 loss_thr: 0.5739 loss_db: 0.1618 2022/11/02 14:32:23 - mmengine - INFO - Epoch(train) [225][30/63] lr: 1.7957e-03 eta: 10:02:15 time: 0.5853 data_time: 0.0382 memory: 14901 loss: 1.7527 loss_prob: 0.9946 loss_thr: 0.5945 loss_db: 0.1636 2022/11/02 14:32:26 - mmengine - INFO - Epoch(train) [225][35/63] lr: 1.7957e-03 eta: 10:02:15 time: 0.5650 data_time: 0.0100 memory: 14901 loss: 1.8465 loss_prob: 1.0721 loss_thr: 0.6001 loss_db: 0.1744 2022/11/02 14:32:29 - mmengine - INFO - Epoch(train) [225][40/63] lr: 1.7957e-03 eta: 10:02:06 time: 0.5310 data_time: 0.0153 memory: 14901 loss: 1.8155 loss_prob: 1.0628 loss_thr: 0.5825 loss_db: 0.1702 2022/11/02 14:32:31 - mmengine - INFO - Epoch(train) [225][45/63] lr: 1.7957e-03 eta: 10:02:06 time: 0.5168 data_time: 0.0149 memory: 14901 loss: 1.8469 loss_prob: 1.0645 loss_thr: 0.6048 loss_db: 0.1776 2022/11/02 14:32:34 - mmengine - INFO - Epoch(train) [225][50/63] lr: 1.7957e-03 eta: 10:01:58 time: 0.5412 data_time: 0.0247 memory: 14901 loss: 1.8692 loss_prob: 1.0611 loss_thr: 0.6278 loss_db: 0.1804 2022/11/02 14:32:37 - mmengine - INFO - Epoch(train) [225][55/63] lr: 1.7957e-03 eta: 10:01:58 time: 0.5295 data_time: 0.0252 memory: 14901 loss: 1.8083 loss_prob: 1.0355 loss_thr: 0.6028 loss_db: 0.1700 2022/11/02 14:32:40 - mmengine - INFO - Epoch(train) [225][60/63] lr: 1.7957e-03 eta: 10:01:52 time: 0.5740 data_time: 0.0103 memory: 14901 loss: 1.8334 loss_prob: 1.0528 loss_thr: 0.6083 loss_db: 0.1722 2022/11/02 14:32:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:32:47 - mmengine - INFO - Epoch(train) [226][5/63] lr: 1.7941e-03 eta: 10:01:52 time: 0.9065 data_time: 0.2300 memory: 14901 loss: 1.9087 loss_prob: 1.1044 loss_thr: 0.6199 loss_db: 0.1844 2022/11/02 14:32:51 - mmengine - INFO - Epoch(train) [226][10/63] lr: 1.7941e-03 eta: 10:01:52 time: 0.9406 data_time: 0.2281 memory: 14901 loss: 1.8812 loss_prob: 1.1112 loss_thr: 0.5862 loss_db: 0.1838 2022/11/02 14:32:54 - mmengine - INFO - Epoch(train) [226][15/63] lr: 1.7941e-03 eta: 10:01:52 time: 0.6825 data_time: 0.0351 memory: 14901 loss: 1.7207 loss_prob: 0.9997 loss_thr: 0.5580 loss_db: 0.1630 2022/11/02 14:32:57 - mmengine - INFO - Epoch(train) [226][20/63] lr: 1.7941e-03 eta: 10:01:49 time: 0.6486 data_time: 0.0336 memory: 14901 loss: 1.7951 loss_prob: 1.0477 loss_thr: 0.5708 loss_db: 0.1766 2022/11/02 14:33:00 - mmengine - INFO - Epoch(train) [226][25/63] lr: 1.7941e-03 eta: 10:01:49 time: 0.5554 data_time: 0.0069 memory: 14901 loss: 1.8848 loss_prob: 1.1031 loss_thr: 0.5948 loss_db: 0.1869 2022/11/02 14:33:03 - mmengine - INFO - Epoch(train) [226][30/63] lr: 1.7941e-03 eta: 10:01:42 time: 0.5687 data_time: 0.0231 memory: 14901 loss: 1.8069 loss_prob: 1.0521 loss_thr: 0.5790 loss_db: 0.1758 2022/11/02 14:33:06 - mmengine - INFO - Epoch(train) [226][35/63] lr: 1.7941e-03 eta: 10:01:42 time: 0.6457 data_time: 0.0305 memory: 14901 loss: 1.8470 loss_prob: 1.0750 loss_thr: 0.5931 loss_db: 0.1788 2022/11/02 14:33:09 - mmengine - INFO - Epoch(train) [226][40/63] lr: 1.7941e-03 eta: 10:01:37 time: 0.6090 data_time: 0.0145 memory: 14901 loss: 1.8424 loss_prob: 1.0475 loss_thr: 0.6228 loss_db: 0.1722 2022/11/02 14:33:11 - mmengine - INFO - Epoch(train) [226][45/63] lr: 1.7941e-03 eta: 10:01:37 time: 0.5150 data_time: 0.0085 memory: 14901 loss: 1.7038 loss_prob: 0.9566 loss_thr: 0.5859 loss_db: 0.1613 2022/11/02 14:33:14 - mmengine - INFO - Epoch(train) [226][50/63] lr: 1.7941e-03 eta: 10:01:29 time: 0.5462 data_time: 0.0074 memory: 14901 loss: 1.8178 loss_prob: 1.0567 loss_thr: 0.5867 loss_db: 0.1743 2022/11/02 14:33:17 - mmengine - INFO - Epoch(train) [226][55/63] lr: 1.7941e-03 eta: 10:01:29 time: 0.5962 data_time: 0.0202 memory: 14901 loss: 1.7985 loss_prob: 1.0448 loss_thr: 0.5849 loss_db: 0.1687 2022/11/02 14:33:20 - mmengine - INFO - Epoch(train) [226][60/63] lr: 1.7941e-03 eta: 10:01:21 time: 0.5357 data_time: 0.0227 memory: 14901 loss: 1.7183 loss_prob: 0.9838 loss_thr: 0.5716 loss_db: 0.1630 2022/11/02 14:33:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:33:27 - mmengine - INFO - Epoch(train) [227][5/63] lr: 1.7924e-03 eta: 10:01:21 time: 0.8288 data_time: 0.2392 memory: 14901 loss: 1.8609 loss_prob: 1.0574 loss_thr: 0.6278 loss_db: 0.1757 2022/11/02 14:33:30 - mmengine - INFO - Epoch(train) [227][10/63] lr: 1.7924e-03 eta: 10:01:16 time: 0.8308 data_time: 0.2410 memory: 14901 loss: 1.8465 loss_prob: 1.0383 loss_thr: 0.6348 loss_db: 0.1735 2022/11/02 14:33:33 - mmengine - INFO - Epoch(train) [227][15/63] lr: 1.7924e-03 eta: 10:01:16 time: 0.5605 data_time: 0.0098 memory: 14901 loss: 1.7460 loss_prob: 0.9869 loss_thr: 0.5978 loss_db: 0.1614 2022/11/02 14:33:35 - mmengine - INFO - Epoch(train) [227][20/63] lr: 1.7924e-03 eta: 10:01:09 time: 0.5498 data_time: 0.0066 memory: 14901 loss: 1.7975 loss_prob: 1.0169 loss_thr: 0.6119 loss_db: 0.1687 2022/11/02 14:33:38 - mmengine - INFO - Epoch(train) [227][25/63] lr: 1.7924e-03 eta: 10:01:09 time: 0.5162 data_time: 0.0354 memory: 14901 loss: 1.8052 loss_prob: 1.0213 loss_thr: 0.6132 loss_db: 0.1707 2022/11/02 14:33:40 - mmengine - INFO - Epoch(train) [227][30/63] lr: 1.7924e-03 eta: 10:01:00 time: 0.5202 data_time: 0.0428 memory: 14901 loss: 1.7072 loss_prob: 0.9753 loss_thr: 0.5710 loss_db: 0.1608 2022/11/02 14:33:43 - mmengine - INFO - Epoch(train) [227][35/63] lr: 1.7924e-03 eta: 10:01:00 time: 0.5059 data_time: 0.0150 memory: 14901 loss: 1.7098 loss_prob: 0.9800 loss_thr: 0.5681 loss_db: 0.1616 2022/11/02 14:33:45 - mmengine - INFO - Epoch(train) [227][40/63] lr: 1.7924e-03 eta: 10:00:50 time: 0.4967 data_time: 0.0095 memory: 14901 loss: 1.8304 loss_prob: 1.0758 loss_thr: 0.5796 loss_db: 0.1750 2022/11/02 14:33:48 - mmengine - INFO - Epoch(train) [227][45/63] lr: 1.7924e-03 eta: 10:00:50 time: 0.5531 data_time: 0.0081 memory: 14901 loss: 1.8497 loss_prob: 1.1071 loss_thr: 0.5672 loss_db: 0.1754 2022/11/02 14:33:52 - mmengine - INFO - Epoch(train) [227][50/63] lr: 1.7924e-03 eta: 10:00:47 time: 0.6409 data_time: 0.0216 memory: 14901 loss: 1.7607 loss_prob: 1.0291 loss_thr: 0.5673 loss_db: 0.1643 2022/11/02 14:33:55 - mmengine - INFO - Epoch(train) [227][55/63] lr: 1.7924e-03 eta: 10:00:47 time: 0.6161 data_time: 0.0264 memory: 14901 loss: 1.7613 loss_prob: 1.0030 loss_thr: 0.5920 loss_db: 0.1664 2022/11/02 14:33:57 - mmengine - INFO - Epoch(train) [227][60/63] lr: 1.7924e-03 eta: 10:00:39 time: 0.5532 data_time: 0.0140 memory: 14901 loss: 1.8566 loss_prob: 1.0750 loss_thr: 0.6043 loss_db: 0.1773 2022/11/02 14:33:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:34:04 - mmengine - INFO - Epoch(train) [228][5/63] lr: 1.7907e-03 eta: 10:00:39 time: 0.8290 data_time: 0.2089 memory: 14901 loss: 1.7551 loss_prob: 1.0060 loss_thr: 0.5819 loss_db: 0.1672 2022/11/02 14:34:07 - mmengine - INFO - Epoch(train) [228][10/63] lr: 1.7907e-03 eta: 10:00:35 time: 0.8517 data_time: 0.2170 memory: 14901 loss: 1.9576 loss_prob: 1.1494 loss_thr: 0.6174 loss_db: 0.1907 2022/11/02 14:34:10 - mmengine - INFO - Epoch(train) [228][15/63] lr: 1.7907e-03 eta: 10:00:35 time: 0.5270 data_time: 0.0188 memory: 14901 loss: 2.0310 loss_prob: 1.2127 loss_thr: 0.6180 loss_db: 0.2002 2022/11/02 14:34:12 - mmengine - INFO - Epoch(train) [228][20/63] lr: 1.7907e-03 eta: 10:00:27 time: 0.5245 data_time: 0.0311 memory: 14901 loss: 1.9248 loss_prob: 1.1233 loss_thr: 0.6151 loss_db: 0.1864 2022/11/02 14:34:15 - mmengine - INFO - Epoch(train) [228][25/63] lr: 1.7907e-03 eta: 10:00:27 time: 0.5270 data_time: 0.0276 memory: 14901 loss: 1.8327 loss_prob: 1.0455 loss_thr: 0.6143 loss_db: 0.1729 2022/11/02 14:34:18 - mmengine - INFO - Epoch(train) [228][30/63] lr: 1.7907e-03 eta: 10:00:18 time: 0.5173 data_time: 0.0185 memory: 14901 loss: 1.7944 loss_prob: 1.0273 loss_thr: 0.5946 loss_db: 0.1725 2022/11/02 14:34:20 - mmengine - INFO - Epoch(train) [228][35/63] lr: 1.7907e-03 eta: 10:00:18 time: 0.5057 data_time: 0.0227 memory: 14901 loss: 1.8258 loss_prob: 1.0605 loss_thr: 0.5864 loss_db: 0.1789 2022/11/02 14:34:22 - mmengine - INFO - Epoch(train) [228][40/63] lr: 1.7907e-03 eta: 10:00:08 time: 0.4920 data_time: 0.0142 memory: 14901 loss: 1.8053 loss_prob: 1.0447 loss_thr: 0.5891 loss_db: 0.1715 2022/11/02 14:34:26 - mmengine - INFO - Epoch(train) [228][45/63] lr: 1.7907e-03 eta: 10:00:08 time: 0.5815 data_time: 0.0232 memory: 14901 loss: 1.7705 loss_prob: 1.0119 loss_thr: 0.5929 loss_db: 0.1658 2022/11/02 14:34:29 - mmengine - INFO - Epoch(train) [228][50/63] lr: 1.7907e-03 eta: 10:00:03 time: 0.6195 data_time: 0.0200 memory: 14901 loss: 1.7366 loss_prob: 0.9890 loss_thr: 0.5839 loss_db: 0.1637 2022/11/02 14:34:32 - mmengine - INFO - Epoch(train) [228][55/63] lr: 1.7907e-03 eta: 10:00:03 time: 0.6095 data_time: 0.0149 memory: 14901 loss: 1.6507 loss_prob: 0.9327 loss_thr: 0.5641 loss_db: 0.1539 2022/11/02 14:34:35 - mmengine - INFO - Epoch(train) [228][60/63] lr: 1.7907e-03 eta: 9:59:58 time: 0.5916 data_time: 0.0160 memory: 14901 loss: 1.6834 loss_prob: 0.9529 loss_thr: 0.5720 loss_db: 0.1585 2022/11/02 14:34:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:34:42 - mmengine - INFO - Epoch(train) [229][5/63] lr: 1.7891e-03 eta: 9:59:58 time: 0.8357 data_time: 0.2460 memory: 14901 loss: 1.8832 loss_prob: 1.0873 loss_thr: 0.6201 loss_db: 0.1758 2022/11/02 14:34:45 - mmengine - INFO - Epoch(train) [229][10/63] lr: 1.7891e-03 eta: 9:59:56 time: 0.8975 data_time: 0.2440 memory: 14901 loss: 1.8180 loss_prob: 1.0339 loss_thr: 0.6140 loss_db: 0.1701 2022/11/02 14:34:48 - mmengine - INFO - Epoch(train) [229][15/63] lr: 1.7891e-03 eta: 9:59:56 time: 0.5924 data_time: 0.0073 memory: 14901 loss: 1.7692 loss_prob: 0.9973 loss_thr: 0.6087 loss_db: 0.1632 2022/11/02 14:34:50 - mmengine - INFO - Epoch(train) [229][20/63] lr: 1.7891e-03 eta: 9:59:47 time: 0.5295 data_time: 0.0075 memory: 14901 loss: 1.7059 loss_prob: 0.9464 loss_thr: 0.6036 loss_db: 0.1559 2022/11/02 14:34:53 - mmengine - INFO - Epoch(train) [229][25/63] lr: 1.7891e-03 eta: 9:59:47 time: 0.5347 data_time: 0.0120 memory: 14901 loss: 1.7001 loss_prob: 0.9535 loss_thr: 0.5866 loss_db: 0.1600 2022/11/02 14:34:56 - mmengine - INFO - Epoch(train) [229][30/63] lr: 1.7891e-03 eta: 9:59:40 time: 0.5581 data_time: 0.0622 memory: 14901 loss: 1.7151 loss_prob: 0.9800 loss_thr: 0.5720 loss_db: 0.1631 2022/11/02 14:34:59 - mmengine - INFO - Epoch(train) [229][35/63] lr: 1.7891e-03 eta: 9:59:40 time: 0.5613 data_time: 0.0570 memory: 14901 loss: 1.7279 loss_prob: 0.9884 loss_thr: 0.5760 loss_db: 0.1635 2022/11/02 14:35:01 - mmengine - INFO - Epoch(train) [229][40/63] lr: 1.7891e-03 eta: 9:59:32 time: 0.5332 data_time: 0.0072 memory: 14901 loss: 1.7297 loss_prob: 0.9936 loss_thr: 0.5733 loss_db: 0.1627 2022/11/02 14:35:04 - mmengine - INFO - Epoch(train) [229][45/63] lr: 1.7891e-03 eta: 9:59:32 time: 0.5239 data_time: 0.0097 memory: 14901 loss: 1.7822 loss_prob: 1.0311 loss_thr: 0.5855 loss_db: 0.1656 2022/11/02 14:35:06 - mmengine - INFO - Epoch(train) [229][50/63] lr: 1.7891e-03 eta: 9:59:23 time: 0.5090 data_time: 0.0140 memory: 14901 loss: 1.8746 loss_prob: 1.0755 loss_thr: 0.6210 loss_db: 0.1781 2022/11/02 14:35:09 - mmengine - INFO - Epoch(train) [229][55/63] lr: 1.7891e-03 eta: 9:59:23 time: 0.5533 data_time: 0.0311 memory: 14901 loss: 1.8790 loss_prob: 1.0686 loss_thr: 0.6321 loss_db: 0.1783 2022/11/02 14:35:12 - mmengine - INFO - Epoch(train) [229][60/63] lr: 1.7891e-03 eta: 9:59:15 time: 0.5442 data_time: 0.0301 memory: 14901 loss: 1.9438 loss_prob: 1.1198 loss_thr: 0.6362 loss_db: 0.1878 2022/11/02 14:35:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:35:19 - mmengine - INFO - Epoch(train) [230][5/63] lr: 1.7874e-03 eta: 9:59:15 time: 0.7483 data_time: 0.2578 memory: 14901 loss: 2.9819 loss_prob: 1.9623 loss_thr: 0.7018 loss_db: 0.3178 2022/11/02 14:35:21 - mmengine - INFO - Epoch(train) [230][10/63] lr: 1.7874e-03 eta: 9:59:10 time: 0.8186 data_time: 0.2612 memory: 14901 loss: 2.9240 loss_prob: 1.9500 loss_thr: 0.6608 loss_db: 0.3132 2022/11/02 14:35:24 - mmengine - INFO - Epoch(train) [230][15/63] lr: 1.7874e-03 eta: 9:59:10 time: 0.5853 data_time: 0.0118 memory: 14901 loss: 2.7419 loss_prob: 1.7914 loss_thr: 0.6588 loss_db: 0.2917 2022/11/02 14:35:27 - mmengine - INFO - Epoch(train) [230][20/63] lr: 1.7874e-03 eta: 9:59:04 time: 0.5942 data_time: 0.0077 memory: 14901 loss: 2.6182 loss_prob: 1.6665 loss_thr: 0.6777 loss_db: 0.2740 2022/11/02 14:35:30 - mmengine - INFO - Epoch(train) [230][25/63] lr: 1.7874e-03 eta: 9:59:04 time: 0.5972 data_time: 0.0234 memory: 14901 loss: 2.4995 loss_prob: 1.5600 loss_thr: 0.6854 loss_db: 0.2541 2022/11/02 14:35:33 - mmengine - INFO - Epoch(train) [230][30/63] lr: 1.7874e-03 eta: 9:58:59 time: 0.5991 data_time: 0.0390 memory: 14901 loss: 2.2342 loss_prob: 1.3668 loss_thr: 0.6478 loss_db: 0.2196 2022/11/02 14:35:36 - mmengine - INFO - Epoch(train) [230][35/63] lr: 1.7874e-03 eta: 9:58:59 time: 0.5521 data_time: 0.0237 memory: 14901 loss: 2.1668 loss_prob: 1.3290 loss_thr: 0.6263 loss_db: 0.2115 2022/11/02 14:35:39 - mmengine - INFO - Epoch(train) [230][40/63] lr: 1.7874e-03 eta: 9:58:50 time: 0.5257 data_time: 0.0120 memory: 14901 loss: 2.0927 loss_prob: 1.2700 loss_thr: 0.6188 loss_db: 0.2039 2022/11/02 14:35:41 - mmengine - INFO - Epoch(train) [230][45/63] lr: 1.7874e-03 eta: 9:58:50 time: 0.5377 data_time: 0.0146 memory: 14901 loss: 2.1417 loss_prob: 1.2982 loss_thr: 0.6309 loss_db: 0.2127 2022/11/02 14:35:44 - mmengine - INFO - Epoch(train) [230][50/63] lr: 1.7874e-03 eta: 9:58:42 time: 0.5332 data_time: 0.0255 memory: 14901 loss: 2.2345 loss_prob: 1.3530 loss_thr: 0.6617 loss_db: 0.2199 2022/11/02 14:35:47 - mmengine - INFO - Epoch(train) [230][55/63] lr: 1.7874e-03 eta: 9:58:42 time: 0.5334 data_time: 0.0314 memory: 14901 loss: 2.0727 loss_prob: 1.2252 loss_thr: 0.6502 loss_db: 0.1973 2022/11/02 14:35:49 - mmengine - INFO - Epoch(train) [230][60/63] lr: 1.7874e-03 eta: 9:58:34 time: 0.5364 data_time: 0.0171 memory: 14901 loss: 1.8898 loss_prob: 1.0969 loss_thr: 0.6137 loss_db: 0.1792 2022/11/02 14:35:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:35:57 - mmengine - INFO - Epoch(train) [231][5/63] lr: 1.7858e-03 eta: 9:58:34 time: 0.8863 data_time: 0.2035 memory: 14901 loss: 1.8159 loss_prob: 1.0516 loss_thr: 0.5930 loss_db: 0.1713 2022/11/02 14:36:00 - mmengine - INFO - Epoch(train) [231][10/63] lr: 1.7858e-03 eta: 9:58:31 time: 0.8791 data_time: 0.2112 memory: 14901 loss: 1.7683 loss_prob: 1.0187 loss_thr: 0.5825 loss_db: 0.1670 2022/11/02 14:36:02 - mmengine - INFO - Epoch(train) [231][15/63] lr: 1.7858e-03 eta: 9:58:31 time: 0.5383 data_time: 0.0248 memory: 14901 loss: 1.7899 loss_prob: 1.0326 loss_thr: 0.5873 loss_db: 0.1699 2022/11/02 14:36:05 - mmengine - INFO - Epoch(train) [231][20/63] lr: 1.7858e-03 eta: 9:58:23 time: 0.5271 data_time: 0.0159 memory: 14901 loss: 1.8876 loss_prob: 1.1004 loss_thr: 0.6100 loss_db: 0.1772 2022/11/02 14:36:08 - mmengine - INFO - Epoch(train) [231][25/63] lr: 1.7858e-03 eta: 9:58:23 time: 0.5882 data_time: 0.0236 memory: 14901 loss: 2.0254 loss_prob: 1.2199 loss_thr: 0.6129 loss_db: 0.1925 2022/11/02 14:36:11 - mmengine - INFO - Epoch(train) [231][30/63] lr: 1.7858e-03 eta: 9:58:17 time: 0.5973 data_time: 0.0284 memory: 14901 loss: 1.9890 loss_prob: 1.1782 loss_thr: 0.6200 loss_db: 0.1908 2022/11/02 14:36:14 - mmengine - INFO - Epoch(train) [231][35/63] lr: 1.7858e-03 eta: 9:58:17 time: 0.5265 data_time: 0.0200 memory: 14901 loss: 1.7970 loss_prob: 1.0282 loss_thr: 0.6013 loss_db: 0.1675 2022/11/02 14:36:17 - mmengine - INFO - Epoch(train) [231][40/63] lr: 1.7858e-03 eta: 9:58:11 time: 0.5728 data_time: 0.0265 memory: 14901 loss: 1.8304 loss_prob: 1.0671 loss_thr: 0.5935 loss_db: 0.1698 2022/11/02 14:36:19 - mmengine - INFO - Epoch(train) [231][45/63] lr: 1.7858e-03 eta: 9:58:11 time: 0.5863 data_time: 0.0180 memory: 14901 loss: 1.8886 loss_prob: 1.0914 loss_thr: 0.6190 loss_db: 0.1781 2022/11/02 14:36:22 - mmengine - INFO - Epoch(train) [231][50/63] lr: 1.7858e-03 eta: 9:58:03 time: 0.5525 data_time: 0.0219 memory: 14901 loss: 1.7957 loss_prob: 1.0287 loss_thr: 0.5982 loss_db: 0.1688 2022/11/02 14:36:25 - mmengine - INFO - Epoch(train) [231][55/63] lr: 1.7858e-03 eta: 9:58:03 time: 0.5525 data_time: 0.0216 memory: 14901 loss: 1.8303 loss_prob: 1.0527 loss_thr: 0.6082 loss_db: 0.1694 2022/11/02 14:36:28 - mmengine - INFO - Epoch(train) [231][60/63] lr: 1.7858e-03 eta: 9:57:55 time: 0.5369 data_time: 0.0120 memory: 14901 loss: 1.8338 loss_prob: 1.0477 loss_thr: 0.6169 loss_db: 0.1691 2022/11/02 14:36:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:36:35 - mmengine - INFO - Epoch(train) [232][5/63] lr: 1.7841e-03 eta: 9:57:55 time: 0.8214 data_time: 0.2283 memory: 14901 loss: 1.7685 loss_prob: 1.0121 loss_thr: 0.5911 loss_db: 0.1653 2022/11/02 14:36:39 - mmengine - INFO - Epoch(train) [232][10/63] lr: 1.7841e-03 eta: 9:57:57 time: 0.9832 data_time: 0.2329 memory: 14901 loss: 1.6963 loss_prob: 0.9530 loss_thr: 0.5863 loss_db: 0.1570 2022/11/02 14:36:42 - mmengine - INFO - Epoch(train) [232][15/63] lr: 1.7841e-03 eta: 9:57:57 time: 0.7027 data_time: 0.0169 memory: 14901 loss: 1.7571 loss_prob: 1.0031 loss_thr: 0.5901 loss_db: 0.1639 2022/11/02 14:36:44 - mmengine - INFO - Epoch(train) [232][20/63] lr: 1.7841e-03 eta: 9:57:51 time: 0.5778 data_time: 0.0092 memory: 14901 loss: 1.8061 loss_prob: 1.0437 loss_thr: 0.5935 loss_db: 0.1689 2022/11/02 14:36:48 - mmengine - INFO - Epoch(train) [232][25/63] lr: 1.7841e-03 eta: 9:57:51 time: 0.5701 data_time: 0.0118 memory: 14901 loss: 1.8447 loss_prob: 1.0726 loss_thr: 0.5955 loss_db: 0.1766 2022/11/02 14:36:50 - mmengine - INFO - Epoch(train) [232][30/63] lr: 1.7841e-03 eta: 9:57:45 time: 0.6024 data_time: 0.0322 memory: 14901 loss: 1.9254 loss_prob: 1.1182 loss_thr: 0.6220 loss_db: 0.1851 2022/11/02 14:36:53 - mmengine - INFO - Epoch(train) [232][35/63] lr: 1.7841e-03 eta: 9:57:45 time: 0.5615 data_time: 0.0354 memory: 14901 loss: 1.8964 loss_prob: 1.0966 loss_thr: 0.6211 loss_db: 0.1786 2022/11/02 14:36:56 - mmengine - INFO - Epoch(train) [232][40/63] lr: 1.7841e-03 eta: 9:57:37 time: 0.5192 data_time: 0.0143 memory: 14901 loss: 1.9501 loss_prob: 1.1397 loss_thr: 0.6195 loss_db: 0.1908 2022/11/02 14:36:59 - mmengine - INFO - Epoch(train) [232][45/63] lr: 1.7841e-03 eta: 9:57:37 time: 0.5381 data_time: 0.0077 memory: 14901 loss: 1.9840 loss_prob: 1.1710 loss_thr: 0.6228 loss_db: 0.1902 2022/11/02 14:37:01 - mmengine - INFO - Epoch(train) [232][50/63] lr: 1.7841e-03 eta: 9:57:29 time: 0.5425 data_time: 0.0182 memory: 14901 loss: 1.8155 loss_prob: 1.0583 loss_thr: 0.5898 loss_db: 0.1674 2022/11/02 14:37:04 - mmengine - INFO - Epoch(train) [232][55/63] lr: 1.7841e-03 eta: 9:57:29 time: 0.5105 data_time: 0.0298 memory: 14901 loss: 1.9466 loss_prob: 1.1702 loss_thr: 0.5877 loss_db: 0.1887 2022/11/02 14:37:06 - mmengine - INFO - Epoch(train) [232][60/63] lr: 1.7841e-03 eta: 9:57:19 time: 0.5012 data_time: 0.0251 memory: 14901 loss: 2.1400 loss_prob: 1.3373 loss_thr: 0.6000 loss_db: 0.2027 2022/11/02 14:37:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:37:12 - mmengine - INFO - Epoch(train) [233][5/63] lr: 1.7825e-03 eta: 9:57:19 time: 0.7417 data_time: 0.2106 memory: 14901 loss: 1.9256 loss_prob: 1.1452 loss_thr: 0.5969 loss_db: 0.1835 2022/11/02 14:37:15 - mmengine - INFO - Epoch(train) [233][10/63] lr: 1.7825e-03 eta: 9:57:12 time: 0.7701 data_time: 0.2268 memory: 14901 loss: 1.9139 loss_prob: 1.1177 loss_thr: 0.6152 loss_db: 0.1810 2022/11/02 14:37:19 - mmengine - INFO - Epoch(train) [233][15/63] lr: 1.7825e-03 eta: 9:57:12 time: 0.6340 data_time: 0.0274 memory: 14901 loss: 1.7430 loss_prob: 0.9899 loss_thr: 0.5903 loss_db: 0.1628 2022/11/02 14:37:22 - mmengine - INFO - Epoch(train) [233][20/63] lr: 1.7825e-03 eta: 9:57:11 time: 0.7131 data_time: 0.0088 memory: 14901 loss: 1.7482 loss_prob: 0.9969 loss_thr: 0.5895 loss_db: 0.1618 2022/11/02 14:37:25 - mmengine - INFO - Epoch(train) [233][25/63] lr: 1.7825e-03 eta: 9:57:11 time: 0.6376 data_time: 0.0182 memory: 14901 loss: 1.8657 loss_prob: 1.0612 loss_thr: 0.6314 loss_db: 0.1731 2022/11/02 14:37:28 - mmengine - INFO - Epoch(train) [233][30/63] lr: 1.7825e-03 eta: 9:57:04 time: 0.5534 data_time: 0.0485 memory: 14901 loss: 1.8033 loss_prob: 1.0126 loss_thr: 0.6217 loss_db: 0.1689 2022/11/02 14:37:31 - mmengine - INFO - Epoch(train) [233][35/63] lr: 1.7825e-03 eta: 9:57:04 time: 0.5845 data_time: 0.0366 memory: 14901 loss: 1.7439 loss_prob: 0.9886 loss_thr: 0.5916 loss_db: 0.1638 2022/11/02 14:37:34 - mmengine - INFO - Epoch(train) [233][40/63] lr: 1.7825e-03 eta: 9:56:58 time: 0.5794 data_time: 0.0065 memory: 14901 loss: 1.9509 loss_prob: 1.1469 loss_thr: 0.6162 loss_db: 0.1877 2022/11/02 14:37:37 - mmengine - INFO - Epoch(train) [233][45/63] lr: 1.7825e-03 eta: 9:56:58 time: 0.5607 data_time: 0.0091 memory: 14901 loss: 1.9503 loss_prob: 1.1398 loss_thr: 0.6218 loss_db: 0.1887 2022/11/02 14:37:39 - mmengine - INFO - Epoch(train) [233][50/63] lr: 1.7825e-03 eta: 9:56:51 time: 0.5612 data_time: 0.0194 memory: 14901 loss: 1.9008 loss_prob: 1.1152 loss_thr: 0.6047 loss_db: 0.1810 2022/11/02 14:37:42 - mmengine - INFO - Epoch(train) [233][55/63] lr: 1.7825e-03 eta: 9:56:51 time: 0.5361 data_time: 0.0294 memory: 14901 loss: 2.0450 loss_prob: 1.2261 loss_thr: 0.6188 loss_db: 0.2000 2022/11/02 14:37:45 - mmengine - INFO - Epoch(train) [233][60/63] lr: 1.7825e-03 eta: 9:56:42 time: 0.5258 data_time: 0.0226 memory: 14901 loss: 1.8919 loss_prob: 1.0963 loss_thr: 0.6123 loss_db: 0.1833 2022/11/02 14:37:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:37:52 - mmengine - INFO - Epoch(train) [234][5/63] lr: 1.7808e-03 eta: 9:56:42 time: 0.8043 data_time: 0.2317 memory: 14901 loss: 1.8445 loss_prob: 1.0886 loss_thr: 0.5824 loss_db: 0.1735 2022/11/02 14:37:55 - mmengine - INFO - Epoch(train) [234][10/63] lr: 1.7808e-03 eta: 9:56:40 time: 0.8951 data_time: 0.2352 memory: 14901 loss: 1.9556 loss_prob: 1.1722 loss_thr: 0.5969 loss_db: 0.1865 2022/11/02 14:37:58 - mmengine - INFO - Epoch(train) [234][15/63] lr: 1.7808e-03 eta: 9:56:40 time: 0.6099 data_time: 0.0116 memory: 14901 loss: 1.7636 loss_prob: 1.0226 loss_thr: 0.5727 loss_db: 0.1683 2022/11/02 14:38:01 - mmengine - INFO - Epoch(train) [234][20/63] lr: 1.7808e-03 eta: 9:56:34 time: 0.5893 data_time: 0.0105 memory: 14901 loss: 1.7417 loss_prob: 0.9908 loss_thr: 0.5921 loss_db: 0.1589 2022/11/02 14:38:04 - mmengine - INFO - Epoch(train) [234][25/63] lr: 1.7808e-03 eta: 9:56:34 time: 0.5929 data_time: 0.0123 memory: 14901 loss: 1.7449 loss_prob: 0.9872 loss_thr: 0.5975 loss_db: 0.1601 2022/11/02 14:38:07 - mmengine - INFO - Epoch(train) [234][30/63] lr: 1.7808e-03 eta: 9:56:32 time: 0.6589 data_time: 0.0447 memory: 14901 loss: 1.7366 loss_prob: 0.9971 loss_thr: 0.5762 loss_db: 0.1634 2022/11/02 14:38:10 - mmengine - INFO - Epoch(train) [234][35/63] lr: 1.7808e-03 eta: 9:56:32 time: 0.6347 data_time: 0.0424 memory: 14901 loss: 1.7997 loss_prob: 1.0380 loss_thr: 0.5943 loss_db: 0.1673 2022/11/02 14:38:13 - mmengine - INFO - Epoch(train) [234][40/63] lr: 1.7808e-03 eta: 9:56:24 time: 0.5426 data_time: 0.0107 memory: 14901 loss: 1.7618 loss_prob: 0.9950 loss_thr: 0.5977 loss_db: 0.1690 2022/11/02 14:38:15 - mmengine - INFO - Epoch(train) [234][45/63] lr: 1.7808e-03 eta: 9:56:24 time: 0.5247 data_time: 0.0098 memory: 14901 loss: 1.9403 loss_prob: 1.1439 loss_thr: 0.6127 loss_db: 0.1838 2022/11/02 14:38:18 - mmengine - INFO - Epoch(train) [234][50/63] lr: 1.7808e-03 eta: 9:56:14 time: 0.4885 data_time: 0.0143 memory: 14901 loss: 1.9149 loss_prob: 1.1348 loss_thr: 0.6010 loss_db: 0.1791 2022/11/02 14:38:21 - mmengine - INFO - Epoch(train) [234][55/63] lr: 1.7808e-03 eta: 9:56:14 time: 0.5147 data_time: 0.0250 memory: 14901 loss: 1.6965 loss_prob: 0.9538 loss_thr: 0.5815 loss_db: 0.1612 2022/11/02 14:38:23 - mmengine - INFO - Epoch(train) [234][60/63] lr: 1.7808e-03 eta: 9:56:05 time: 0.5154 data_time: 0.0181 memory: 14901 loss: 1.7605 loss_prob: 1.0010 loss_thr: 0.5907 loss_db: 0.1687 2022/11/02 14:38:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:38:29 - mmengine - INFO - Epoch(train) [235][5/63] lr: 1.7791e-03 eta: 9:56:05 time: 0.6932 data_time: 0.2370 memory: 14901 loss: 1.8737 loss_prob: 1.0859 loss_thr: 0.6064 loss_db: 0.1815 2022/11/02 14:38:32 - mmengine - INFO - Epoch(train) [235][10/63] lr: 1.7791e-03 eta: 9:55:57 time: 0.7454 data_time: 0.2381 memory: 14901 loss: 1.8585 loss_prob: 1.0862 loss_thr: 0.5956 loss_db: 0.1766 2022/11/02 14:38:35 - mmengine - INFO - Epoch(train) [235][15/63] lr: 1.7791e-03 eta: 9:55:57 time: 0.5573 data_time: 0.0094 memory: 14901 loss: 1.9791 loss_prob: 1.1646 loss_thr: 0.6234 loss_db: 0.1912 2022/11/02 14:38:37 - mmengine - INFO - Epoch(train) [235][20/63] lr: 1.7791e-03 eta: 9:55:51 time: 0.5841 data_time: 0.0089 memory: 14901 loss: 1.9063 loss_prob: 1.1086 loss_thr: 0.6147 loss_db: 0.1830 2022/11/02 14:38:40 - mmengine - INFO - Epoch(train) [235][25/63] lr: 1.7791e-03 eta: 9:55:51 time: 0.5768 data_time: 0.0357 memory: 14901 loss: 1.7965 loss_prob: 1.0335 loss_thr: 0.5934 loss_db: 0.1696 2022/11/02 14:38:43 - mmengine - INFO - Epoch(train) [235][30/63] lr: 1.7791e-03 eta: 9:55:44 time: 0.5615 data_time: 0.0436 memory: 14901 loss: 1.7912 loss_prob: 1.0224 loss_thr: 0.5953 loss_db: 0.1735 2022/11/02 14:38:46 - mmengine - INFO - Epoch(train) [235][35/63] lr: 1.7791e-03 eta: 9:55:44 time: 0.5844 data_time: 0.0138 memory: 14901 loss: 1.7962 loss_prob: 1.0243 loss_thr: 0.5990 loss_db: 0.1729 2022/11/02 14:38:49 - mmengine - INFO - Epoch(train) [235][40/63] lr: 1.7791e-03 eta: 9:55:39 time: 0.6171 data_time: 0.0062 memory: 14901 loss: 1.7208 loss_prob: 0.9822 loss_thr: 0.5773 loss_db: 0.1612 2022/11/02 14:38:52 - mmengine - INFO - Epoch(train) [235][45/63] lr: 1.7791e-03 eta: 9:55:39 time: 0.5640 data_time: 0.0085 memory: 14901 loss: 1.7927 loss_prob: 1.0450 loss_thr: 0.5795 loss_db: 0.1683 2022/11/02 14:38:55 - mmengine - INFO - Epoch(train) [235][50/63] lr: 1.7791e-03 eta: 9:55:31 time: 0.5373 data_time: 0.0264 memory: 14901 loss: 1.8346 loss_prob: 1.0759 loss_thr: 0.5852 loss_db: 0.1735 2022/11/02 14:38:58 - mmengine - INFO - Epoch(train) [235][55/63] lr: 1.7791e-03 eta: 9:55:31 time: 0.5719 data_time: 0.0297 memory: 14901 loss: 1.6831 loss_prob: 0.9547 loss_thr: 0.5706 loss_db: 0.1578 2022/11/02 14:39:00 - mmengine - INFO - Epoch(train) [235][60/63] lr: 1.7791e-03 eta: 9:55:24 time: 0.5617 data_time: 0.0144 memory: 14901 loss: 1.7426 loss_prob: 0.9877 loss_thr: 0.5918 loss_db: 0.1631 2022/11/02 14:39:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:39:07 - mmengine - INFO - Epoch(train) [236][5/63] lr: 1.7775e-03 eta: 9:55:24 time: 0.8108 data_time: 0.2100 memory: 14901 loss: 1.7827 loss_prob: 1.0323 loss_thr: 0.5849 loss_db: 0.1655 2022/11/02 14:39:10 - mmengine - INFO - Epoch(train) [236][10/63] lr: 1.7775e-03 eta: 9:55:19 time: 0.8284 data_time: 0.2123 memory: 14901 loss: 1.7656 loss_prob: 1.0015 loss_thr: 0.5998 loss_db: 0.1643 2022/11/02 14:39:12 - mmengine - INFO - Epoch(train) [236][15/63] lr: 1.7775e-03 eta: 9:55:19 time: 0.5201 data_time: 0.0115 memory: 14901 loss: 1.7420 loss_prob: 0.9799 loss_thr: 0.5987 loss_db: 0.1634 2022/11/02 14:39:15 - mmengine - INFO - Epoch(train) [236][20/63] lr: 1.7775e-03 eta: 9:55:11 time: 0.5443 data_time: 0.0070 memory: 14901 loss: 1.6624 loss_prob: 0.9351 loss_thr: 0.5742 loss_db: 0.1532 2022/11/02 14:39:18 - mmengine - INFO - Epoch(train) [236][25/63] lr: 1.7775e-03 eta: 9:55:11 time: 0.5703 data_time: 0.0134 memory: 14901 loss: 1.6819 loss_prob: 0.9447 loss_thr: 0.5800 loss_db: 0.1571 2022/11/02 14:39:21 - mmengine - INFO - Epoch(train) [236][30/63] lr: 1.7775e-03 eta: 9:55:04 time: 0.5527 data_time: 0.0422 memory: 14901 loss: 1.7070 loss_prob: 0.9501 loss_thr: 0.5975 loss_db: 0.1593 2022/11/02 14:39:23 - mmengine - INFO - Epoch(train) [236][35/63] lr: 1.7775e-03 eta: 9:55:04 time: 0.5270 data_time: 0.0352 memory: 14901 loss: 1.7354 loss_prob: 0.9686 loss_thr: 0.6040 loss_db: 0.1628 2022/11/02 14:39:26 - mmengine - INFO - Epoch(train) [236][40/63] lr: 1.7775e-03 eta: 9:54:57 time: 0.5472 data_time: 0.0103 memory: 14901 loss: 1.7945 loss_prob: 1.0194 loss_thr: 0.6052 loss_db: 0.1699 2022/11/02 14:39:29 - mmengine - INFO - Epoch(train) [236][45/63] lr: 1.7775e-03 eta: 9:54:57 time: 0.5553 data_time: 0.0127 memory: 14901 loss: 1.7825 loss_prob: 1.0234 loss_thr: 0.5890 loss_db: 0.1701 2022/11/02 14:39:32 - mmengine - INFO - Epoch(train) [236][50/63] lr: 1.7775e-03 eta: 9:54:49 time: 0.5475 data_time: 0.0169 memory: 14901 loss: 1.7218 loss_prob: 0.9739 loss_thr: 0.5837 loss_db: 0.1642 2022/11/02 14:39:35 - mmengine - INFO - Epoch(train) [236][55/63] lr: 1.7775e-03 eta: 9:54:49 time: 0.6331 data_time: 0.0301 memory: 14901 loss: 1.6381 loss_prob: 0.9218 loss_thr: 0.5647 loss_db: 0.1516 2022/11/02 14:39:38 - mmengine - INFO - Epoch(train) [236][60/63] lr: 1.7775e-03 eta: 9:54:44 time: 0.6110 data_time: 0.0225 memory: 14901 loss: 1.5638 loss_prob: 0.8869 loss_thr: 0.5318 loss_db: 0.1451 2022/11/02 14:39:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:39:46 - mmengine - INFO - Epoch(train) [237][5/63] lr: 1.7758e-03 eta: 9:54:44 time: 0.9226 data_time: 0.2701 memory: 14901 loss: 1.7475 loss_prob: 0.9974 loss_thr: 0.5852 loss_db: 0.1649 2022/11/02 14:39:49 - mmengine - INFO - Epoch(train) [237][10/63] lr: 1.7758e-03 eta: 9:54:43 time: 0.9342 data_time: 0.2770 memory: 14901 loss: 1.7908 loss_prob: 1.0174 loss_thr: 0.6079 loss_db: 0.1655 2022/11/02 14:39:52 - mmengine - INFO - Epoch(train) [237][15/63] lr: 1.7758e-03 eta: 9:54:43 time: 0.5796 data_time: 0.0195 memory: 14901 loss: 1.7850 loss_prob: 1.0237 loss_thr: 0.5936 loss_db: 0.1677 2022/11/02 14:39:54 - mmengine - INFO - Epoch(train) [237][20/63] lr: 1.7758e-03 eta: 9:54:37 time: 0.5650 data_time: 0.0131 memory: 14901 loss: 1.8703 loss_prob: 1.0861 loss_thr: 0.6004 loss_db: 0.1838 2022/11/02 14:39:58 - mmengine - INFO - Epoch(train) [237][25/63] lr: 1.7758e-03 eta: 9:54:37 time: 0.5799 data_time: 0.0362 memory: 14901 loss: 1.8163 loss_prob: 1.0403 loss_thr: 0.6028 loss_db: 0.1731 2022/11/02 14:40:01 - mmengine - INFO - Epoch(train) [237][30/63] lr: 1.7758e-03 eta: 9:54:33 time: 0.6391 data_time: 0.0414 memory: 14901 loss: 1.6838 loss_prob: 0.9452 loss_thr: 0.5856 loss_db: 0.1529 2022/11/02 14:40:03 - mmengine - INFO - Epoch(train) [237][35/63] lr: 1.7758e-03 eta: 9:54:33 time: 0.5777 data_time: 0.0133 memory: 14901 loss: 1.6174 loss_prob: 0.9054 loss_thr: 0.5629 loss_db: 0.1490 2022/11/02 14:40:06 - mmengine - INFO - Epoch(train) [237][40/63] lr: 1.7758e-03 eta: 9:54:26 time: 0.5544 data_time: 0.0054 memory: 14901 loss: 1.6447 loss_prob: 0.9288 loss_thr: 0.5628 loss_db: 0.1531 2022/11/02 14:40:09 - mmengine - INFO - Epoch(train) [237][45/63] lr: 1.7758e-03 eta: 9:54:26 time: 0.5455 data_time: 0.0055 memory: 14901 loss: 1.8133 loss_prob: 1.0438 loss_thr: 0.6001 loss_db: 0.1694 2022/11/02 14:40:11 - mmengine - INFO - Epoch(train) [237][50/63] lr: 1.7758e-03 eta: 9:54:16 time: 0.5002 data_time: 0.0226 memory: 14901 loss: 1.8606 loss_prob: 1.0792 loss_thr: 0.6035 loss_db: 0.1780 2022/11/02 14:40:14 - mmengine - INFO - Epoch(train) [237][55/63] lr: 1.7758e-03 eta: 9:54:16 time: 0.4875 data_time: 0.0266 memory: 14901 loss: 1.8614 loss_prob: 1.0717 loss_thr: 0.6050 loss_db: 0.1847 2022/11/02 14:40:16 - mmengine - INFO - Epoch(train) [237][60/63] lr: 1.7758e-03 eta: 9:54:06 time: 0.4916 data_time: 0.0110 memory: 14901 loss: 2.0178 loss_prob: 1.1976 loss_thr: 0.6231 loss_db: 0.1972 2022/11/02 14:40:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:40:23 - mmengine - INFO - Epoch(train) [238][5/63] lr: 1.7742e-03 eta: 9:54:06 time: 0.7388 data_time: 0.2437 memory: 14901 loss: 1.9399 loss_prob: 1.1460 loss_thr: 0.6146 loss_db: 0.1793 2022/11/02 14:40:25 - mmengine - INFO - Epoch(train) [238][10/63] lr: 1.7742e-03 eta: 9:54:00 time: 0.8001 data_time: 0.2514 memory: 14901 loss: 1.8096 loss_prob: 1.0369 loss_thr: 0.6026 loss_db: 0.1701 2022/11/02 14:40:28 - mmengine - INFO - Epoch(train) [238][15/63] lr: 1.7742e-03 eta: 9:54:00 time: 0.5237 data_time: 0.0184 memory: 14901 loss: 1.8639 loss_prob: 1.0832 loss_thr: 0.6013 loss_db: 0.1794 2022/11/02 14:40:30 - mmengine - INFO - Epoch(train) [238][20/63] lr: 1.7742e-03 eta: 9:53:51 time: 0.5037 data_time: 0.0112 memory: 14901 loss: 1.7550 loss_prob: 1.0022 loss_thr: 0.5881 loss_db: 0.1648 2022/11/02 14:40:33 - mmengine - INFO - Epoch(train) [238][25/63] lr: 1.7742e-03 eta: 9:53:51 time: 0.5195 data_time: 0.0167 memory: 14901 loss: 1.7805 loss_prob: 1.0179 loss_thr: 0.5961 loss_db: 0.1664 2022/11/02 14:40:36 - mmengine - INFO - Epoch(train) [238][30/63] lr: 1.7742e-03 eta: 9:53:42 time: 0.5183 data_time: 0.0359 memory: 14901 loss: 1.8016 loss_prob: 1.0326 loss_thr: 0.5978 loss_db: 0.1712 2022/11/02 14:40:38 - mmengine - INFO - Epoch(train) [238][35/63] lr: 1.7742e-03 eta: 9:53:42 time: 0.5174 data_time: 0.0309 memory: 14901 loss: 1.7064 loss_prob: 0.9582 loss_thr: 0.5883 loss_db: 0.1599 2022/11/02 14:40:41 - mmengine - INFO - Epoch(train) [238][40/63] lr: 1.7742e-03 eta: 9:53:34 time: 0.5257 data_time: 0.0116 memory: 14901 loss: 1.7816 loss_prob: 1.0049 loss_thr: 0.6101 loss_db: 0.1667 2022/11/02 14:40:44 - mmengine - INFO - Epoch(train) [238][45/63] lr: 1.7742e-03 eta: 9:53:34 time: 0.6090 data_time: 0.0097 memory: 14901 loss: 1.7472 loss_prob: 0.9930 loss_thr: 0.5880 loss_db: 0.1662 2022/11/02 14:40:47 - mmengine - INFO - Epoch(train) [238][50/63] lr: 1.7742e-03 eta: 9:53:30 time: 0.6301 data_time: 0.0198 memory: 14901 loss: 1.6813 loss_prob: 0.9534 loss_thr: 0.5697 loss_db: 0.1582 2022/11/02 14:40:50 - mmengine - INFO - Epoch(train) [238][55/63] lr: 1.7742e-03 eta: 9:53:30 time: 0.5760 data_time: 0.0279 memory: 14901 loss: 1.8106 loss_prob: 1.0381 loss_thr: 0.6032 loss_db: 0.1693 2022/11/02 14:40:53 - mmengine - INFO - Epoch(train) [238][60/63] lr: 1.7742e-03 eta: 9:53:23 time: 0.5655 data_time: 0.0201 memory: 14901 loss: 1.8453 loss_prob: 1.0673 loss_thr: 0.6032 loss_db: 0.1748 2022/11/02 14:40:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:40:59 - mmengine - INFO - Epoch(train) [239][5/63] lr: 1.7725e-03 eta: 9:53:23 time: 0.7344 data_time: 0.2465 memory: 14901 loss: 1.6239 loss_prob: 0.9156 loss_thr: 0.5577 loss_db: 0.1506 2022/11/02 14:41:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:41:02 - mmengine - INFO - Epoch(train) [239][10/63] lr: 1.7725e-03 eta: 9:53:18 time: 0.8241 data_time: 0.2604 memory: 14901 loss: 1.5781 loss_prob: 0.8814 loss_thr: 0.5515 loss_db: 0.1451 2022/11/02 14:41:05 - mmengine - INFO - Epoch(train) [239][15/63] lr: 1.7725e-03 eta: 9:53:18 time: 0.5772 data_time: 0.0222 memory: 14901 loss: 1.6642 loss_prob: 0.9249 loss_thr: 0.5821 loss_db: 0.1572 2022/11/02 14:41:07 - mmengine - INFO - Epoch(train) [239][20/63] lr: 1.7725e-03 eta: 9:53:09 time: 0.5138 data_time: 0.0078 memory: 14901 loss: 1.6471 loss_prob: 0.9240 loss_thr: 0.5681 loss_db: 0.1550 2022/11/02 14:41:10 - mmengine - INFO - Epoch(train) [239][25/63] lr: 1.7725e-03 eta: 9:53:09 time: 0.5365 data_time: 0.0373 memory: 14901 loss: 1.7380 loss_prob: 0.9863 loss_thr: 0.5910 loss_db: 0.1607 2022/11/02 14:41:13 - mmengine - INFO - Epoch(train) [239][30/63] lr: 1.7725e-03 eta: 9:53:02 time: 0.5507 data_time: 0.0385 memory: 14901 loss: 1.7862 loss_prob: 1.0210 loss_thr: 0.5967 loss_db: 0.1685 2022/11/02 14:41:16 - mmengine - INFO - Epoch(train) [239][35/63] lr: 1.7725e-03 eta: 9:53:02 time: 0.5513 data_time: 0.0132 memory: 14901 loss: 1.7327 loss_prob: 0.9930 loss_thr: 0.5745 loss_db: 0.1652 2022/11/02 14:41:19 - mmengine - INFO - Epoch(train) [239][40/63] lr: 1.7725e-03 eta: 9:52:58 time: 0.6417 data_time: 0.0143 memory: 14901 loss: 1.8442 loss_prob: 1.0608 loss_thr: 0.6066 loss_db: 0.1768 2022/11/02 14:41:22 - mmengine - INFO - Epoch(train) [239][45/63] lr: 1.7725e-03 eta: 9:52:58 time: 0.6052 data_time: 0.0082 memory: 14901 loss: 1.8101 loss_prob: 1.0416 loss_thr: 0.5961 loss_db: 0.1724 2022/11/02 14:41:25 - mmengine - INFO - Epoch(train) [239][50/63] lr: 1.7725e-03 eta: 9:52:50 time: 0.5356 data_time: 0.0199 memory: 14901 loss: 1.8424 loss_prob: 1.0649 loss_thr: 0.6055 loss_db: 0.1720 2022/11/02 14:41:29 - mmengine - INFO - Epoch(train) [239][55/63] lr: 1.7725e-03 eta: 9:52:50 time: 0.6837 data_time: 0.0220 memory: 14901 loss: 1.8149 loss_prob: 1.0379 loss_thr: 0.6063 loss_db: 0.1708 2022/11/02 14:41:32 - mmengine - INFO - Epoch(train) [239][60/63] lr: 1.7725e-03 eta: 9:52:49 time: 0.7150 data_time: 0.0104 memory: 14901 loss: 1.7663 loss_prob: 0.9950 loss_thr: 0.6035 loss_db: 0.1678 2022/11/02 14:41:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:41:39 - mmengine - INFO - Epoch(train) [240][5/63] lr: 1.7708e-03 eta: 9:52:49 time: 0.8252 data_time: 0.2495 memory: 14901 loss: 1.7503 loss_prob: 0.9930 loss_thr: 0.5931 loss_db: 0.1642 2022/11/02 14:41:42 - mmengine - INFO - Epoch(train) [240][10/63] lr: 1.7708e-03 eta: 9:52:44 time: 0.8124 data_time: 0.2472 memory: 14901 loss: 1.7301 loss_prob: 0.9702 loss_thr: 0.6001 loss_db: 0.1598 2022/11/02 14:41:44 - mmengine - INFO - Epoch(train) [240][15/63] lr: 1.7708e-03 eta: 9:52:44 time: 0.4949 data_time: 0.0078 memory: 14901 loss: 1.6376 loss_prob: 0.9090 loss_thr: 0.5764 loss_db: 0.1522 2022/11/02 14:41:47 - mmengine - INFO - Epoch(train) [240][20/63] lr: 1.7708e-03 eta: 9:52:34 time: 0.5020 data_time: 0.0103 memory: 14901 loss: 1.7253 loss_prob: 0.9736 loss_thr: 0.5879 loss_db: 0.1639 2022/11/02 14:41:50 - mmengine - INFO - Epoch(train) [240][25/63] lr: 1.7708e-03 eta: 9:52:34 time: 0.5733 data_time: 0.0341 memory: 14901 loss: 1.8202 loss_prob: 1.0267 loss_thr: 0.6236 loss_db: 0.1699 2022/11/02 14:41:53 - mmengine - INFO - Epoch(train) [240][30/63] lr: 1.7708e-03 eta: 9:52:30 time: 0.6383 data_time: 0.0368 memory: 14901 loss: 1.7698 loss_prob: 0.9905 loss_thr: 0.6142 loss_db: 0.1651 2022/11/02 14:41:55 - mmengine - INFO - Epoch(train) [240][35/63] lr: 1.7708e-03 eta: 9:52:30 time: 0.5772 data_time: 0.0171 memory: 14901 loss: 1.7367 loss_prob: 0.9783 loss_thr: 0.5937 loss_db: 0.1647 2022/11/02 14:41:58 - mmengine - INFO - Epoch(train) [240][40/63] lr: 1.7708e-03 eta: 9:52:22 time: 0.5246 data_time: 0.0132 memory: 14901 loss: 1.6828 loss_prob: 0.9522 loss_thr: 0.5744 loss_db: 0.1563 2022/11/02 14:42:01 - mmengine - INFO - Epoch(train) [240][45/63] lr: 1.7708e-03 eta: 9:52:22 time: 0.5404 data_time: 0.0085 memory: 14901 loss: 1.6216 loss_prob: 0.9078 loss_thr: 0.5668 loss_db: 0.1471 2022/11/02 14:42:04 - mmengine - INFO - Epoch(train) [240][50/63] lr: 1.7708e-03 eta: 9:52:14 time: 0.5353 data_time: 0.0279 memory: 14901 loss: 1.7205 loss_prob: 0.9732 loss_thr: 0.5858 loss_db: 0.1615 2022/11/02 14:42:06 - mmengine - INFO - Epoch(train) [240][55/63] lr: 1.7708e-03 eta: 9:52:14 time: 0.5058 data_time: 0.0293 memory: 14901 loss: 1.7539 loss_prob: 1.0003 loss_thr: 0.5854 loss_db: 0.1682 2022/11/02 14:42:08 - mmengine - INFO - Epoch(train) [240][60/63] lr: 1.7708e-03 eta: 9:52:04 time: 0.4873 data_time: 0.0109 memory: 14901 loss: 1.6729 loss_prob: 0.9443 loss_thr: 0.5750 loss_db: 0.1535 2022/11/02 14:42:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:42:11 - mmengine - INFO - Saving checkpoint at 240 epochs 2022/11/02 14:42:15 - mmengine - INFO - Epoch(val) [240][5/500] eta: 9:52:04 time: 0.0424 data_time: 0.0058 memory: 14901 2022/11/02 14:42:15 - mmengine - INFO - Epoch(val) [240][10/500] eta: 0:00:21 time: 0.0444 data_time: 0.0059 memory: 1008 2022/11/02 14:42:15 - mmengine - INFO - Epoch(val) [240][15/500] eta: 0:00:21 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 14:42:15 - mmengine - INFO - Epoch(val) [240][20/500] eta: 0:00:16 time: 0.0353 data_time: 0.0023 memory: 1008 2022/11/02 14:42:16 - mmengine - INFO - Epoch(val) [240][25/500] eta: 0:00:16 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/02 14:42:16 - mmengine - INFO - Epoch(val) [240][30/500] eta: 0:00:19 time: 0.0424 data_time: 0.0029 memory: 1008 2022/11/02 14:42:16 - mmengine - INFO - Epoch(val) [240][35/500] eta: 0:00:19 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/02 14:42:16 - mmengine - INFO - Epoch(val) [240][40/500] eta: 0:00:19 time: 0.0430 data_time: 0.0032 memory: 1008 2022/11/02 14:42:16 - mmengine - INFO - Epoch(val) [240][45/500] eta: 0:00:19 time: 0.0457 data_time: 0.0033 memory: 1008 2022/11/02 14:42:17 - mmengine - INFO - Epoch(val) [240][50/500] eta: 0:00:39 time: 0.0878 data_time: 0.0493 memory: 1008 2022/11/02 14:42:17 - mmengine - INFO - Epoch(val) [240][55/500] eta: 0:00:39 time: 0.0885 data_time: 0.0488 memory: 1008 2022/11/02 14:42:18 - mmengine - INFO - Epoch(val) [240][60/500] eta: 0:00:17 time: 0.0405 data_time: 0.0019 memory: 1008 2022/11/02 14:42:18 - mmengine - INFO - Epoch(val) [240][65/500] eta: 0:00:17 time: 0.0409 data_time: 0.0023 memory: 1008 2022/11/02 14:42:18 - mmengine - INFO - Epoch(val) [240][70/500] eta: 0:00:17 time: 0.0417 data_time: 0.0026 memory: 1008 2022/11/02 14:42:18 - mmengine - INFO - Epoch(val) [240][75/500] eta: 0:00:17 time: 0.0382 data_time: 0.0024 memory: 1008 2022/11/02 14:42:19 - mmengine - INFO - Epoch(val) [240][80/500] eta: 0:00:25 time: 0.0597 data_time: 0.0268 memory: 1008 2022/11/02 14:42:19 - mmengine - INFO - Epoch(val) [240][85/500] eta: 0:00:25 time: 0.0580 data_time: 0.0265 memory: 1008 2022/11/02 14:42:19 - mmengine - INFO - Epoch(val) [240][90/500] eta: 0:00:15 time: 0.0390 data_time: 0.0023 memory: 1008 2022/11/02 14:42:19 - mmengine - INFO - Epoch(val) [240][95/500] eta: 0:00:15 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 14:42:19 - mmengine - INFO - Epoch(val) [240][100/500] eta: 0:00:15 time: 0.0386 data_time: 0.0029 memory: 1008 2022/11/02 14:42:20 - mmengine - INFO - Epoch(val) [240][105/500] eta: 0:00:15 time: 0.0378 data_time: 0.0028 memory: 1008 2022/11/02 14:42:20 - mmengine - INFO - Epoch(val) [240][110/500] eta: 0:00:13 time: 0.0353 data_time: 0.0024 memory: 1008 2022/11/02 14:42:20 - mmengine - INFO - Epoch(val) [240][115/500] eta: 0:00:13 time: 0.0362 data_time: 0.0025 memory: 1008 2022/11/02 14:42:20 - mmengine - INFO - Epoch(val) [240][120/500] eta: 0:00:14 time: 0.0393 data_time: 0.0029 memory: 1008 2022/11/02 14:42:20 - mmengine - INFO - Epoch(val) [240][125/500] eta: 0:00:14 time: 0.0367 data_time: 0.0026 memory: 1008 2022/11/02 14:42:20 - mmengine - INFO - Epoch(val) [240][130/500] eta: 0:00:13 time: 0.0357 data_time: 0.0023 memory: 1008 2022/11/02 14:42:21 - mmengine - INFO - Epoch(val) [240][135/500] eta: 0:00:13 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/02 14:42:21 - mmengine - INFO - Epoch(val) [240][140/500] eta: 0:00:13 time: 0.0386 data_time: 0.0023 memory: 1008 2022/11/02 14:42:21 - mmengine - INFO - Epoch(val) [240][145/500] eta: 0:00:13 time: 0.0481 data_time: 0.0034 memory: 1008 2022/11/02 14:42:21 - mmengine - INFO - Epoch(val) [240][150/500] eta: 0:00:16 time: 0.0465 data_time: 0.0036 memory: 1008 2022/11/02 14:42:22 - mmengine - INFO - Epoch(val) [240][155/500] eta: 0:00:16 time: 0.0425 data_time: 0.0024 memory: 1008 2022/11/02 14:42:22 - mmengine - INFO - Epoch(val) [240][160/500] eta: 0:00:14 time: 0.0428 data_time: 0.0025 memory: 1008 2022/11/02 14:42:22 - mmengine - INFO - Epoch(val) [240][165/500] eta: 0:00:14 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 14:42:22 - mmengine - INFO - Epoch(val) [240][170/500] eta: 0:00:13 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/02 14:42:22 - mmengine - INFO - Epoch(val) [240][175/500] eta: 0:00:13 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 14:42:23 - mmengine - INFO - Epoch(val) [240][180/500] eta: 0:00:11 time: 0.0374 data_time: 0.0027 memory: 1008 2022/11/02 14:42:23 - mmengine - INFO - Epoch(val) [240][185/500] eta: 0:00:11 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 14:42:23 - mmengine - INFO - Epoch(val) [240][190/500] eta: 0:00:12 time: 0.0417 data_time: 0.0027 memory: 1008 2022/11/02 14:42:23 - mmengine - INFO - Epoch(val) [240][195/500] eta: 0:00:12 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/02 14:42:23 - mmengine - INFO - Epoch(val) [240][200/500] eta: 0:00:13 time: 0.0453 data_time: 0.0026 memory: 1008 2022/11/02 14:42:24 - mmengine - INFO - Epoch(val) [240][205/500] eta: 0:00:13 time: 0.0448 data_time: 0.0026 memory: 1008 2022/11/02 14:42:24 - mmengine - INFO - Epoch(val) [240][210/500] eta: 0:00:10 time: 0.0348 data_time: 0.0025 memory: 1008 2022/11/02 14:42:24 - mmengine - INFO - Epoch(val) [240][215/500] eta: 0:00:10 time: 0.0374 data_time: 0.0024 memory: 1008 2022/11/02 14:42:24 - mmengine - INFO - Epoch(val) [240][220/500] eta: 0:00:11 time: 0.0418 data_time: 0.0062 memory: 1008 2022/11/02 14:42:24 - mmengine - INFO - Epoch(val) [240][225/500] eta: 0:00:11 time: 0.0414 data_time: 0.0058 memory: 1008 2022/11/02 14:42:25 - mmengine - INFO - Epoch(val) [240][230/500] eta: 0:00:09 time: 0.0364 data_time: 0.0018 memory: 1008 2022/11/02 14:42:25 - mmengine - INFO - Epoch(val) [240][235/500] eta: 0:00:09 time: 0.0348 data_time: 0.0021 memory: 1008 2022/11/02 14:42:25 - mmengine - INFO - Epoch(val) [240][240/500] eta: 0:00:10 time: 0.0399 data_time: 0.0028 memory: 1008 2022/11/02 14:42:25 - mmengine - INFO - Epoch(val) [240][245/500] eta: 0:00:10 time: 0.0404 data_time: 0.0030 memory: 1008 2022/11/02 14:42:25 - mmengine - INFO - Epoch(val) [240][250/500] eta: 0:00:09 time: 0.0371 data_time: 0.0025 memory: 1008 2022/11/02 14:42:25 - mmengine - INFO - Epoch(val) [240][255/500] eta: 0:00:09 time: 0.0350 data_time: 0.0023 memory: 1008 2022/11/02 14:42:26 - mmengine - INFO - Epoch(val) [240][260/500] eta: 0:00:08 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 14:42:26 - mmengine - INFO - Epoch(val) [240][265/500] eta: 0:00:08 time: 0.0414 data_time: 0.0036 memory: 1008 2022/11/02 14:42:26 - mmengine - INFO - Epoch(val) [240][270/500] eta: 0:00:09 time: 0.0426 data_time: 0.0035 memory: 1008 2022/11/02 14:42:26 - mmengine - INFO - Epoch(val) [240][275/500] eta: 0:00:09 time: 0.0402 data_time: 0.0026 memory: 1008 2022/11/02 14:42:26 - mmengine - INFO - Epoch(val) [240][280/500] eta: 0:00:08 time: 0.0387 data_time: 0.0024 memory: 1008 2022/11/02 14:42:27 - mmengine - INFO - Epoch(val) [240][285/500] eta: 0:00:08 time: 0.0365 data_time: 0.0022 memory: 1008 2022/11/02 14:42:27 - mmengine - INFO - Epoch(val) [240][290/500] eta: 0:00:07 time: 0.0377 data_time: 0.0022 memory: 1008 2022/11/02 14:42:27 - mmengine - INFO - Epoch(val) [240][295/500] eta: 0:00:07 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 14:42:27 - mmengine - INFO - Epoch(val) [240][300/500] eta: 0:00:07 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 14:42:27 - mmengine - INFO - Epoch(val) [240][305/500] eta: 0:00:07 time: 0.0349 data_time: 0.0023 memory: 1008 2022/11/02 14:42:28 - mmengine - INFO - Epoch(val) [240][310/500] eta: 0:00:07 time: 0.0374 data_time: 0.0024 memory: 1008 2022/11/02 14:42:28 - mmengine - INFO - Epoch(val) [240][315/500] eta: 0:00:07 time: 0.0394 data_time: 0.0022 memory: 1008 2022/11/02 14:42:28 - mmengine - INFO - Epoch(val) [240][320/500] eta: 0:00:06 time: 0.0371 data_time: 0.0022 memory: 1008 2022/11/02 14:42:28 - mmengine - INFO - Epoch(val) [240][325/500] eta: 0:00:06 time: 0.0476 data_time: 0.0024 memory: 1008 2022/11/02 14:42:28 - mmengine - INFO - Epoch(val) [240][330/500] eta: 0:00:08 time: 0.0489 data_time: 0.0024 memory: 1008 2022/11/02 14:42:29 - mmengine - INFO - Epoch(val) [240][335/500] eta: 0:00:08 time: 0.0359 data_time: 0.0024 memory: 1008 2022/11/02 14:42:29 - mmengine - INFO - Epoch(val) [240][340/500] eta: 0:00:07 time: 0.0454 data_time: 0.0025 memory: 1008 2022/11/02 14:42:29 - mmengine - INFO - Epoch(val) [240][345/500] eta: 0:00:07 time: 0.0478 data_time: 0.0026 memory: 1008 2022/11/02 14:42:29 - mmengine - INFO - Epoch(val) [240][350/500] eta: 0:00:06 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 14:42:30 - mmengine - INFO - Epoch(val) [240][355/500] eta: 0:00:06 time: 0.0410 data_time: 0.0024 memory: 1008 2022/11/02 14:42:30 - mmengine - INFO - Epoch(val) [240][360/500] eta: 0:00:05 time: 0.0396 data_time: 0.0024 memory: 1008 2022/11/02 14:42:30 - mmengine - INFO - Epoch(val) [240][365/500] eta: 0:00:05 time: 0.0423 data_time: 0.0028 memory: 1008 2022/11/02 14:42:30 - mmengine - INFO - Epoch(val) [240][370/500] eta: 0:00:04 time: 0.0369 data_time: 0.0027 memory: 1008 2022/11/02 14:42:30 - mmengine - INFO - Epoch(val) [240][375/500] eta: 0:00:04 time: 0.0347 data_time: 0.0025 memory: 1008 2022/11/02 14:42:30 - mmengine - INFO - Epoch(val) [240][380/500] eta: 0:00:04 time: 0.0374 data_time: 0.0025 memory: 1008 2022/11/02 14:42:31 - mmengine - INFO - Epoch(val) [240][385/500] eta: 0:00:04 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 14:42:31 - mmengine - INFO - Epoch(val) [240][390/500] eta: 0:00:04 time: 0.0414 data_time: 0.0024 memory: 1008 2022/11/02 14:42:31 - mmengine - INFO - Epoch(val) [240][395/500] eta: 0:00:04 time: 0.0410 data_time: 0.0023 memory: 1008 2022/11/02 14:42:31 - mmengine - INFO - Epoch(val) [240][400/500] eta: 0:00:03 time: 0.0346 data_time: 0.0021 memory: 1008 2022/11/02 14:42:31 - mmengine - INFO - Epoch(val) [240][405/500] eta: 0:00:03 time: 0.0368 data_time: 0.0022 memory: 1008 2022/11/02 14:42:32 - mmengine - INFO - Epoch(val) [240][410/500] eta: 0:00:03 time: 0.0387 data_time: 0.0023 memory: 1008 2022/11/02 14:42:32 - mmengine - INFO - Epoch(val) [240][415/500] eta: 0:00:03 time: 0.0364 data_time: 0.0021 memory: 1008 2022/11/02 14:42:33 - mmengine - INFO - Epoch(val) [240][420/500] eta: 0:00:08 time: 0.1081 data_time: 0.0774 memory: 1008 2022/11/02 14:42:33 - mmengine - INFO - Epoch(val) [240][425/500] eta: 0:00:08 time: 0.1103 data_time: 0.0774 memory: 1008 2022/11/02 14:42:33 - mmengine - INFO - Epoch(val) [240][430/500] eta: 0:00:02 time: 0.0385 data_time: 0.0023 memory: 1008 2022/11/02 14:42:33 - mmengine - INFO - Epoch(val) [240][435/500] eta: 0:00:02 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 14:42:33 - mmengine - INFO - Epoch(val) [240][440/500] eta: 0:00:02 time: 0.0367 data_time: 0.0023 memory: 1008 2022/11/02 14:42:34 - mmengine - INFO - Epoch(val) [240][445/500] eta: 0:00:02 time: 0.0396 data_time: 0.0025 memory: 1008 2022/11/02 14:42:34 - mmengine - INFO - Epoch(val) [240][450/500] eta: 0:00:01 time: 0.0396 data_time: 0.0025 memory: 1008 2022/11/02 14:42:34 - mmengine - INFO - Epoch(val) [240][455/500] eta: 0:00:01 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 14:42:34 - mmengine - INFO - Epoch(val) [240][460/500] eta: 0:00:01 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/02 14:42:34 - mmengine - INFO - Epoch(val) [240][465/500] eta: 0:00:01 time: 0.0386 data_time: 0.0030 memory: 1008 2022/11/02 14:42:35 - mmengine - INFO - Epoch(val) [240][470/500] eta: 0:00:01 time: 0.0361 data_time: 0.0025 memory: 1008 2022/11/02 14:42:35 - mmengine - INFO - Epoch(val) [240][475/500] eta: 0:00:01 time: 0.0374 data_time: 0.0027 memory: 1008 2022/11/02 14:42:35 - mmengine - INFO - Epoch(val) [240][480/500] eta: 0:00:00 time: 0.0369 data_time: 0.0027 memory: 1008 2022/11/02 14:42:35 - mmengine - INFO - Epoch(val) [240][485/500] eta: 0:00:00 time: 0.0347 data_time: 0.0023 memory: 1008 2022/11/02 14:42:35 - mmengine - INFO - Epoch(val) [240][490/500] eta: 0:00:00 time: 0.0383 data_time: 0.0023 memory: 1008 2022/11/02 14:42:36 - mmengine - INFO - Epoch(val) [240][495/500] eta: 0:00:00 time: 0.0449 data_time: 0.0026 memory: 1008 2022/11/02 14:42:36 - mmengine - INFO - Epoch(val) [240][500/500] eta: 0:00:00 time: 0.0406 data_time: 0.0027 memory: 1008 2022/11/02 14:42:36 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7944, precision: 0.7346, hmean: 0.7634 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7939, precision: 0.8005, hmean: 0.7972 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7906, precision: 0.8360, hmean: 0.8127 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7727, precision: 0.8718, hmean: 0.8193 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7053, precision: 0.9043, hmean: 0.7925 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3394, precision: 0.9527, hmean: 0.5005 2022/11/02 14:42:36 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0019, precision: 1.0000, hmean: 0.0038 2022/11/02 14:42:36 - mmengine - INFO - Epoch(val) [240][500/500] icdar/precision: 0.8718 icdar/recall: 0.7727 icdar/hmean: 0.8193 2022/11/02 14:42:42 - mmengine - INFO - Epoch(train) [241][5/63] lr: 1.7692e-03 eta: 0:00:00 time: 0.9738 data_time: 0.2153 memory: 14901 loss: 1.6316 loss_prob: 0.9139 loss_thr: 0.5639 loss_db: 0.1538 2022/11/02 14:42:45 - mmengine - INFO - Epoch(train) [241][10/63] lr: 1.7692e-03 eta: 9:52:00 time: 0.8628 data_time: 0.2241 memory: 14901 loss: 1.6892 loss_prob: 0.9606 loss_thr: 0.5667 loss_db: 0.1619 2022/11/02 14:42:47 - mmengine - INFO - Epoch(train) [241][15/63] lr: 1.7692e-03 eta: 9:52:00 time: 0.5247 data_time: 0.0169 memory: 14901 loss: 1.7937 loss_prob: 1.0439 loss_thr: 0.5812 loss_db: 0.1687 2022/11/02 14:42:50 - mmengine - INFO - Epoch(train) [241][20/63] lr: 1.7692e-03 eta: 9:51:52 time: 0.5304 data_time: 0.0094 memory: 14901 loss: 1.7984 loss_prob: 1.0484 loss_thr: 0.5848 loss_db: 0.1652 2022/11/02 14:42:53 - mmengine - INFO - Epoch(train) [241][25/63] lr: 1.7692e-03 eta: 9:51:52 time: 0.6111 data_time: 0.0202 memory: 14901 loss: 1.7080 loss_prob: 0.9781 loss_thr: 0.5718 loss_db: 0.1581 2022/11/02 14:42:56 - mmengine - INFO - Epoch(train) [241][30/63] lr: 1.7692e-03 eta: 9:51:48 time: 0.6165 data_time: 0.0406 memory: 14901 loss: 1.7049 loss_prob: 0.9683 loss_thr: 0.5774 loss_db: 0.1592 2022/11/02 14:42:59 - mmengine - INFO - Epoch(train) [241][35/63] lr: 1.7692e-03 eta: 9:51:48 time: 0.5621 data_time: 0.0330 memory: 14901 loss: 1.7714 loss_prob: 1.0098 loss_thr: 0.5934 loss_db: 0.1682 2022/11/02 14:43:01 - mmengine - INFO - Epoch(train) [241][40/63] lr: 1.7692e-03 eta: 9:51:39 time: 0.5303 data_time: 0.0092 memory: 14901 loss: 1.6939 loss_prob: 0.9605 loss_thr: 0.5726 loss_db: 0.1607 2022/11/02 14:43:04 - mmengine - INFO - Epoch(train) [241][45/63] lr: 1.7692e-03 eta: 9:51:39 time: 0.5224 data_time: 0.0095 memory: 14901 loss: 1.6106 loss_prob: 0.9113 loss_thr: 0.5488 loss_db: 0.1506 2022/11/02 14:43:07 - mmengine - INFO - Epoch(train) [241][50/63] lr: 1.7692e-03 eta: 9:51:33 time: 0.5637 data_time: 0.0197 memory: 14901 loss: 1.7330 loss_prob: 0.9761 loss_thr: 0.5972 loss_db: 0.1597 2022/11/02 14:43:10 - mmengine - INFO - Epoch(train) [241][55/63] lr: 1.7692e-03 eta: 9:51:33 time: 0.5819 data_time: 0.0230 memory: 14901 loss: 1.7408 loss_prob: 0.9779 loss_thr: 0.6021 loss_db: 0.1608 2022/11/02 14:43:13 - mmengine - INFO - Epoch(train) [241][60/63] lr: 1.7692e-03 eta: 9:51:26 time: 0.5692 data_time: 0.0158 memory: 14901 loss: 1.6801 loss_prob: 0.9468 loss_thr: 0.5755 loss_db: 0.1578 2022/11/02 14:43:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:43:20 - mmengine - INFO - Epoch(train) [242][5/63] lr: 1.7675e-03 eta: 9:51:26 time: 0.8291 data_time: 0.2141 memory: 14901 loss: 1.8138 loss_prob: 1.0384 loss_thr: 0.6054 loss_db: 0.1699 2022/11/02 14:43:22 - mmengine - INFO - Epoch(train) [242][10/63] lr: 1.7675e-03 eta: 9:51:21 time: 0.8407 data_time: 0.2205 memory: 14901 loss: 1.8713 loss_prob: 1.0892 loss_thr: 0.6043 loss_db: 0.1778 2022/11/02 14:43:25 - mmengine - INFO - Epoch(train) [242][15/63] lr: 1.7675e-03 eta: 9:51:21 time: 0.5517 data_time: 0.0134 memory: 14901 loss: 1.8910 loss_prob: 1.1043 loss_thr: 0.6031 loss_db: 0.1837 2022/11/02 14:43:28 - mmengine - INFO - Epoch(train) [242][20/63] lr: 1.7675e-03 eta: 9:51:13 time: 0.5343 data_time: 0.0061 memory: 14901 loss: 1.7904 loss_prob: 1.0389 loss_thr: 0.5779 loss_db: 0.1736 2022/11/02 14:43:31 - mmengine - INFO - Epoch(train) [242][25/63] lr: 1.7675e-03 eta: 9:51:13 time: 0.5907 data_time: 0.0275 memory: 14901 loss: 1.8151 loss_prob: 1.0432 loss_thr: 0.5972 loss_db: 0.1747 2022/11/02 14:43:35 - mmengine - INFO - Epoch(train) [242][30/63] lr: 1.7675e-03 eta: 9:51:14 time: 0.7390 data_time: 0.0367 memory: 14901 loss: 1.7775 loss_prob: 1.0135 loss_thr: 0.5954 loss_db: 0.1686 2022/11/02 14:43:38 - mmengine - INFO - Epoch(train) [242][35/63] lr: 1.7675e-03 eta: 9:51:14 time: 0.6816 data_time: 0.0254 memory: 14901 loss: 1.5724 loss_prob: 0.8694 loss_thr: 0.5588 loss_db: 0.1443 2022/11/02 14:43:41 - mmengine - INFO - Epoch(train) [242][40/63] lr: 1.7675e-03 eta: 9:51:07 time: 0.5725 data_time: 0.0190 memory: 14901 loss: 1.6122 loss_prob: 0.8989 loss_thr: 0.5657 loss_db: 0.1477 2022/11/02 14:43:44 - mmengine - INFO - Epoch(train) [242][45/63] lr: 1.7675e-03 eta: 9:51:07 time: 0.5745 data_time: 0.0088 memory: 14901 loss: 1.8110 loss_prob: 1.0423 loss_thr: 0.5971 loss_db: 0.1716 2022/11/02 14:43:46 - mmengine - INFO - Epoch(train) [242][50/63] lr: 1.7675e-03 eta: 9:51:00 time: 0.5654 data_time: 0.0141 memory: 14901 loss: 1.8541 loss_prob: 1.0884 loss_thr: 0.5877 loss_db: 0.1780 2022/11/02 14:43:49 - mmengine - INFO - Epoch(train) [242][55/63] lr: 1.7675e-03 eta: 9:51:00 time: 0.5529 data_time: 0.0210 memory: 14901 loss: 1.7493 loss_prob: 1.0013 loss_thr: 0.5844 loss_db: 0.1636 2022/11/02 14:43:52 - mmengine - INFO - Epoch(train) [242][60/63] lr: 1.7675e-03 eta: 9:50:53 time: 0.5510 data_time: 0.0190 memory: 14901 loss: 1.7773 loss_prob: 1.0014 loss_thr: 0.6088 loss_db: 0.1671 2022/11/02 14:43:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:43:59 - mmengine - INFO - Epoch(train) [243][5/63] lr: 1.7659e-03 eta: 9:50:53 time: 0.8676 data_time: 0.2412 memory: 14901 loss: 1.7066 loss_prob: 0.9668 loss_thr: 0.5817 loss_db: 0.1581 2022/11/02 14:44:02 - mmengine - INFO - Epoch(train) [243][10/63] lr: 1.7659e-03 eta: 9:50:50 time: 0.8883 data_time: 0.2714 memory: 14901 loss: 1.6462 loss_prob: 0.9287 loss_thr: 0.5640 loss_db: 0.1536 2022/11/02 14:44:05 - mmengine - INFO - Epoch(train) [243][15/63] lr: 1.7659e-03 eta: 9:50:50 time: 0.5685 data_time: 0.0404 memory: 14901 loss: 1.6313 loss_prob: 0.9135 loss_thr: 0.5654 loss_db: 0.1524 2022/11/02 14:44:08 - mmengine - INFO - Epoch(train) [243][20/63] lr: 1.7659e-03 eta: 9:50:43 time: 0.5429 data_time: 0.0080 memory: 14901 loss: 1.7794 loss_prob: 1.0153 loss_thr: 0.5947 loss_db: 0.1694 2022/11/02 14:44:10 - mmengine - INFO - Epoch(train) [243][25/63] lr: 1.7659e-03 eta: 9:50:43 time: 0.5319 data_time: 0.0077 memory: 14901 loss: 1.8669 loss_prob: 1.0713 loss_thr: 0.6201 loss_db: 0.1755 2022/11/02 14:44:13 - mmengine - INFO - Epoch(train) [243][30/63] lr: 1.7659e-03 eta: 9:50:36 time: 0.5616 data_time: 0.0213 memory: 14901 loss: 1.7756 loss_prob: 1.0083 loss_thr: 0.5991 loss_db: 0.1682 2022/11/02 14:44:16 - mmengine - INFO - Epoch(train) [243][35/63] lr: 1.7659e-03 eta: 9:50:36 time: 0.5734 data_time: 0.0342 memory: 14901 loss: 1.6621 loss_prob: 0.9332 loss_thr: 0.5721 loss_db: 0.1568 2022/11/02 14:44:20 - mmengine - INFO - Epoch(train) [243][40/63] lr: 1.7659e-03 eta: 9:50:32 time: 0.6310 data_time: 0.0203 memory: 14901 loss: 1.6220 loss_prob: 0.9016 loss_thr: 0.5672 loss_db: 0.1532 2022/11/02 14:44:23 - mmengine - INFO - Epoch(train) [243][45/63] lr: 1.7659e-03 eta: 9:50:32 time: 0.6551 data_time: 0.0069 memory: 14901 loss: 1.7847 loss_prob: 1.0273 loss_thr: 0.5852 loss_db: 0.1721 2022/11/02 14:44:26 - mmengine - INFO - Epoch(train) [243][50/63] lr: 1.7659e-03 eta: 9:50:28 time: 0.6440 data_time: 0.0219 memory: 14901 loss: 1.8133 loss_prob: 1.0557 loss_thr: 0.5841 loss_db: 0.1735 2022/11/02 14:44:29 - mmengine - INFO - Epoch(train) [243][55/63] lr: 1.7659e-03 eta: 9:50:28 time: 0.6096 data_time: 0.0242 memory: 14901 loss: 1.6938 loss_prob: 0.9646 loss_thr: 0.5681 loss_db: 0.1610 2022/11/02 14:44:31 - mmengine - INFO - Epoch(train) [243][60/63] lr: 1.7659e-03 eta: 9:50:21 time: 0.5447 data_time: 0.0146 memory: 14901 loss: 1.8440 loss_prob: 1.0573 loss_thr: 0.6106 loss_db: 0.1761 2022/11/02 14:44:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:44:39 - mmengine - INFO - Epoch(train) [244][5/63] lr: 1.7642e-03 eta: 9:50:21 time: 0.8708 data_time: 0.2410 memory: 14901 loss: 1.8344 loss_prob: 1.0291 loss_thr: 0.6323 loss_db: 0.1729 2022/11/02 14:44:42 - mmengine - INFO - Epoch(train) [244][10/63] lr: 1.7642e-03 eta: 9:50:18 time: 0.8883 data_time: 0.2465 memory: 14901 loss: 1.8231 loss_prob: 1.0242 loss_thr: 0.6332 loss_db: 0.1657 2022/11/02 14:44:45 - mmengine - INFO - Epoch(train) [244][15/63] lr: 1.7642e-03 eta: 9:50:18 time: 0.5389 data_time: 0.0143 memory: 14901 loss: 1.6983 loss_prob: 0.9488 loss_thr: 0.5901 loss_db: 0.1593 2022/11/02 14:44:47 - mmengine - INFO - Epoch(train) [244][20/63] lr: 1.7642e-03 eta: 9:50:10 time: 0.5492 data_time: 0.0084 memory: 14901 loss: 1.8640 loss_prob: 1.0787 loss_thr: 0.6011 loss_db: 0.1841 2022/11/02 14:44:50 - mmengine - INFO - Epoch(train) [244][25/63] lr: 1.7642e-03 eta: 9:50:10 time: 0.5398 data_time: 0.0292 memory: 14901 loss: 1.9696 loss_prob: 1.1736 loss_thr: 0.6021 loss_db: 0.1939 2022/11/02 14:44:53 - mmengine - INFO - Epoch(train) [244][30/63] lr: 1.7642e-03 eta: 9:50:03 time: 0.5465 data_time: 0.0380 memory: 14901 loss: 1.8512 loss_prob: 1.0920 loss_thr: 0.5803 loss_db: 0.1789 2022/11/02 14:44:55 - mmengine - INFO - Epoch(train) [244][35/63] lr: 1.7642e-03 eta: 9:50:03 time: 0.5489 data_time: 0.0187 memory: 14901 loss: 1.7984 loss_prob: 1.0446 loss_thr: 0.5810 loss_db: 0.1728 2022/11/02 14:44:58 - mmengine - INFO - Epoch(train) [244][40/63] lr: 1.7642e-03 eta: 9:49:56 time: 0.5619 data_time: 0.0110 memory: 14901 loss: 1.8133 loss_prob: 1.0554 loss_thr: 0.5846 loss_db: 0.1733 2022/11/02 14:45:01 - mmengine - INFO - Epoch(train) [244][45/63] lr: 1.7642e-03 eta: 9:49:56 time: 0.6008 data_time: 0.0125 memory: 14901 loss: 1.7690 loss_prob: 1.0243 loss_thr: 0.5758 loss_db: 0.1689 2022/11/02 14:45:05 - mmengine - INFO - Epoch(train) [244][50/63] lr: 1.7642e-03 eta: 9:49:53 time: 0.6564 data_time: 0.0223 memory: 14901 loss: 1.7116 loss_prob: 0.9769 loss_thr: 0.5718 loss_db: 0.1629 2022/11/02 14:45:08 - mmengine - INFO - Epoch(train) [244][55/63] lr: 1.7642e-03 eta: 9:49:53 time: 0.6237 data_time: 0.0211 memory: 14901 loss: 1.7618 loss_prob: 1.0090 loss_thr: 0.5870 loss_db: 0.1657 2022/11/02 14:45:10 - mmengine - INFO - Epoch(train) [244][60/63] lr: 1.7642e-03 eta: 9:49:46 time: 0.5523 data_time: 0.0132 memory: 14901 loss: 1.8567 loss_prob: 1.0627 loss_thr: 0.6204 loss_db: 0.1736 2022/11/02 14:45:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:45:18 - mmengine - INFO - Epoch(train) [245][5/63] lr: 1.7625e-03 eta: 9:49:46 time: 0.8482 data_time: 0.2296 memory: 14901 loss: 1.8152 loss_prob: 1.0576 loss_thr: 0.5874 loss_db: 0.1702 2022/11/02 14:45:21 - mmengine - INFO - Epoch(train) [245][10/63] lr: 1.7625e-03 eta: 9:49:44 time: 0.9073 data_time: 0.2561 memory: 14901 loss: 1.7498 loss_prob: 0.9985 loss_thr: 0.5860 loss_db: 0.1652 2022/11/02 14:45:24 - mmengine - INFO - Epoch(train) [245][15/63] lr: 1.7625e-03 eta: 9:49:44 time: 0.5730 data_time: 0.0348 memory: 14901 loss: 1.6796 loss_prob: 0.9423 loss_thr: 0.5799 loss_db: 0.1573 2022/11/02 14:45:27 - mmengine - INFO - Epoch(train) [245][20/63] lr: 1.7625e-03 eta: 9:49:37 time: 0.5641 data_time: 0.0110 memory: 14901 loss: 1.7517 loss_prob: 0.9945 loss_thr: 0.5932 loss_db: 0.1639 2022/11/02 14:45:29 - mmengine - INFO - Epoch(train) [245][25/63] lr: 1.7625e-03 eta: 9:49:37 time: 0.5495 data_time: 0.0114 memory: 14901 loss: 1.8572 loss_prob: 1.0535 loss_thr: 0.6296 loss_db: 0.1741 2022/11/02 14:45:32 - mmengine - INFO - Epoch(train) [245][30/63] lr: 1.7625e-03 eta: 9:49:30 time: 0.5708 data_time: 0.0261 memory: 14901 loss: 1.7483 loss_prob: 0.9759 loss_thr: 0.6092 loss_db: 0.1631 2022/11/02 14:45:35 - mmengine - INFO - Epoch(train) [245][35/63] lr: 1.7625e-03 eta: 9:49:30 time: 0.6044 data_time: 0.0294 memory: 14901 loss: 1.6337 loss_prob: 0.9129 loss_thr: 0.5660 loss_db: 0.1547 2022/11/02 14:45:38 - mmengine - INFO - Epoch(train) [245][40/63] lr: 1.7625e-03 eta: 9:49:24 time: 0.5675 data_time: 0.0118 memory: 14901 loss: 1.6515 loss_prob: 0.9190 loss_thr: 0.5752 loss_db: 0.1573 2022/11/02 14:45:41 - mmengine - INFO - Epoch(train) [245][45/63] lr: 1.7625e-03 eta: 9:49:24 time: 0.5550 data_time: 0.0079 memory: 14901 loss: 1.7110 loss_prob: 0.9642 loss_thr: 0.5847 loss_db: 0.1620 2022/11/02 14:45:44 - mmengine - INFO - Epoch(train) [245][50/63] lr: 1.7625e-03 eta: 9:49:16 time: 0.5529 data_time: 0.0083 memory: 14901 loss: 1.6913 loss_prob: 0.9663 loss_thr: 0.5699 loss_db: 0.1551 2022/11/02 14:45:47 - mmengine - INFO - Epoch(train) [245][55/63] lr: 1.7625e-03 eta: 9:49:16 time: 0.5966 data_time: 0.0254 memory: 14901 loss: 1.7180 loss_prob: 0.9713 loss_thr: 0.5911 loss_db: 0.1555 2022/11/02 14:45:49 - mmengine - INFO - Epoch(train) [245][60/63] lr: 1.7625e-03 eta: 9:49:10 time: 0.5663 data_time: 0.0235 memory: 14901 loss: 1.7842 loss_prob: 1.0048 loss_thr: 0.6161 loss_db: 0.1633 2022/11/02 14:45:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:45:57 - mmengine - INFO - Epoch(train) [246][5/63] lr: 1.7609e-03 eta: 9:49:10 time: 0.8433 data_time: 0.2186 memory: 14901 loss: 1.8414 loss_prob: 1.0544 loss_thr: 0.6153 loss_db: 0.1717 2022/11/02 14:45:59 - mmengine - INFO - Epoch(train) [246][10/63] lr: 1.7609e-03 eta: 9:49:06 time: 0.8681 data_time: 0.2185 memory: 14901 loss: 1.6960 loss_prob: 0.9579 loss_thr: 0.5783 loss_db: 0.1597 2022/11/02 14:46:02 - mmengine - INFO - Epoch(train) [246][15/63] lr: 1.7609e-03 eta: 9:49:06 time: 0.5449 data_time: 0.0056 memory: 14901 loss: 1.7278 loss_prob: 0.9713 loss_thr: 0.5938 loss_db: 0.1627 2022/11/02 14:46:05 - mmengine - INFO - Epoch(train) [246][20/63] lr: 1.7609e-03 eta: 9:48:59 time: 0.5481 data_time: 0.0076 memory: 14901 loss: 1.6577 loss_prob: 0.9330 loss_thr: 0.5688 loss_db: 0.1558 2022/11/02 14:46:08 - mmengine - INFO - Epoch(train) [246][25/63] lr: 1.7609e-03 eta: 9:48:59 time: 0.5532 data_time: 0.0287 memory: 14901 loss: 1.6390 loss_prob: 0.9175 loss_thr: 0.5699 loss_db: 0.1516 2022/11/02 14:46:10 - mmengine - INFO - Epoch(train) [246][30/63] lr: 1.7609e-03 eta: 9:48:50 time: 0.5251 data_time: 0.0369 memory: 14901 loss: 1.7661 loss_prob: 1.0035 loss_thr: 0.5985 loss_db: 0.1641 2022/11/02 14:46:13 - mmengine - INFO - Epoch(train) [246][35/63] lr: 1.7609e-03 eta: 9:48:50 time: 0.5018 data_time: 0.0171 memory: 14901 loss: 1.7675 loss_prob: 1.0149 loss_thr: 0.5879 loss_db: 0.1647 2022/11/02 14:46:15 - mmengine - INFO - Epoch(train) [246][40/63] lr: 1.7609e-03 eta: 9:48:42 time: 0.5289 data_time: 0.0070 memory: 14901 loss: 1.7407 loss_prob: 1.0070 loss_thr: 0.5649 loss_db: 0.1688 2022/11/02 14:46:18 - mmengine - INFO - Epoch(train) [246][45/63] lr: 1.7609e-03 eta: 9:48:42 time: 0.5644 data_time: 0.0075 memory: 14901 loss: 1.8247 loss_prob: 1.0571 loss_thr: 0.5886 loss_db: 0.1790 2022/11/02 14:46:21 - mmengine - INFO - Epoch(train) [246][50/63] lr: 1.7609e-03 eta: 9:48:35 time: 0.5511 data_time: 0.0202 memory: 14901 loss: 1.8670 loss_prob: 1.0829 loss_thr: 0.6086 loss_db: 0.1755 2022/11/02 14:46:23 - mmengine - INFO - Epoch(train) [246][55/63] lr: 1.7609e-03 eta: 9:48:35 time: 0.5217 data_time: 0.0289 memory: 14901 loss: 1.8345 loss_prob: 1.0610 loss_thr: 0.6043 loss_db: 0.1692 2022/11/02 14:46:26 - mmengine - INFO - Epoch(train) [246][60/63] lr: 1.7609e-03 eta: 9:48:27 time: 0.5263 data_time: 0.0179 memory: 14901 loss: 1.7128 loss_prob: 0.9633 loss_thr: 0.5865 loss_db: 0.1630 2022/11/02 14:46:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:46:32 - mmengine - INFO - Epoch(train) [247][5/63] lr: 1.7592e-03 eta: 9:48:27 time: 0.7161 data_time: 0.2249 memory: 14901 loss: 1.7410 loss_prob: 0.9993 loss_thr: 0.5726 loss_db: 0.1691 2022/11/02 14:46:35 - mmengine - INFO - Epoch(train) [247][10/63] lr: 1.7592e-03 eta: 9:48:19 time: 0.7603 data_time: 0.2410 memory: 14901 loss: 1.7831 loss_prob: 1.0257 loss_thr: 0.5822 loss_db: 0.1751 2022/11/02 14:46:38 - mmengine - INFO - Epoch(train) [247][15/63] lr: 1.7592e-03 eta: 9:48:19 time: 0.5795 data_time: 0.0235 memory: 14901 loss: 2.2488 loss_prob: 1.3967 loss_thr: 0.6200 loss_db: 0.2321 2022/11/02 14:46:40 - mmengine - INFO - Epoch(train) [247][20/63] lr: 1.7592e-03 eta: 9:48:11 time: 0.5461 data_time: 0.0073 memory: 14901 loss: 2.4133 loss_prob: 1.5140 loss_thr: 0.6527 loss_db: 0.2466 2022/11/02 14:46:43 - mmengine - INFO - Epoch(train) [247][25/63] lr: 1.7592e-03 eta: 9:48:11 time: 0.5455 data_time: 0.0259 memory: 14901 loss: 2.2796 loss_prob: 1.3555 loss_thr: 0.6964 loss_db: 0.2277 2022/11/02 14:46:46 - mmengine - INFO - Epoch(train) [247][30/63] lr: 1.7592e-03 eta: 9:48:04 time: 0.5593 data_time: 0.0332 memory: 14901 loss: 2.3347 loss_prob: 1.3990 loss_thr: 0.7018 loss_db: 0.2339 2022/11/02 14:46:49 - mmengine - INFO - Epoch(train) [247][35/63] lr: 1.7592e-03 eta: 9:48:04 time: 0.5133 data_time: 0.0255 memory: 14901 loss: 2.0944 loss_prob: 1.2534 loss_thr: 0.6387 loss_db: 0.2023 2022/11/02 14:46:51 - mmengine - INFO - Epoch(train) [247][40/63] lr: 1.7592e-03 eta: 9:47:57 time: 0.5342 data_time: 0.0187 memory: 14901 loss: 2.4912 loss_prob: 1.5591 loss_thr: 0.6834 loss_db: 0.2487 2022/11/02 14:46:54 - mmengine - INFO - Epoch(train) [247][45/63] lr: 1.7592e-03 eta: 9:47:57 time: 0.5682 data_time: 0.0087 memory: 14901 loss: 2.5986 loss_prob: 1.6263 loss_thr: 0.7138 loss_db: 0.2585 2022/11/02 14:46:57 - mmengine - INFO - Epoch(train) [247][50/63] lr: 1.7592e-03 eta: 9:47:51 time: 0.5975 data_time: 0.0174 memory: 14901 loss: 2.0148 loss_prob: 1.1809 loss_thr: 0.6448 loss_db: 0.1891 2022/11/02 14:47:00 - mmengine - INFO - Epoch(train) [247][55/63] lr: 1.7592e-03 eta: 9:47:51 time: 0.5873 data_time: 0.0257 memory: 14901 loss: 2.0165 loss_prob: 1.1693 loss_thr: 0.6616 loss_db: 0.1856 2022/11/02 14:47:03 - mmengine - INFO - Epoch(train) [247][60/63] lr: 1.7592e-03 eta: 9:47:46 time: 0.6129 data_time: 0.0253 memory: 14901 loss: 1.9626 loss_prob: 1.1417 loss_thr: 0.6412 loss_db: 0.1797 2022/11/02 14:47:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:47:10 - mmengine - INFO - Epoch(train) [248][5/63] lr: 1.7576e-03 eta: 9:47:46 time: 0.7631 data_time: 0.2452 memory: 14901 loss: 1.8218 loss_prob: 1.0494 loss_thr: 0.6009 loss_db: 0.1715 2022/11/02 14:47:14 - mmengine - INFO - Epoch(train) [248][10/63] lr: 1.7576e-03 eta: 9:47:46 time: 0.9517 data_time: 0.2498 memory: 14901 loss: 1.8542 loss_prob: 1.0749 loss_thr: 0.6030 loss_db: 0.1763 2022/11/02 14:47:17 - mmengine - INFO - Epoch(train) [248][15/63] lr: 1.7576e-03 eta: 9:47:46 time: 0.7250 data_time: 0.0105 memory: 14901 loss: 1.8145 loss_prob: 1.0437 loss_thr: 0.6003 loss_db: 0.1706 2022/11/02 14:47:20 - mmengine - INFO - Epoch(train) [248][20/63] lr: 1.7576e-03 eta: 9:47:42 time: 0.6340 data_time: 0.0123 memory: 14901 loss: 1.8455 loss_prob: 1.0679 loss_thr: 0.6030 loss_db: 0.1746 2022/11/02 14:47:24 - mmengine - INFO - Epoch(train) [248][25/63] lr: 1.7576e-03 eta: 9:47:42 time: 0.6720 data_time: 0.0450 memory: 14901 loss: 1.8818 loss_prob: 1.1072 loss_thr: 0.5977 loss_db: 0.1768 2022/11/02 14:47:27 - mmengine - INFO - Epoch(train) [248][30/63] lr: 1.7576e-03 eta: 9:47:37 time: 0.6175 data_time: 0.0391 memory: 14901 loss: 1.8401 loss_prob: 1.0784 loss_thr: 0.5866 loss_db: 0.1751 2022/11/02 14:47:29 - mmengine - INFO - Epoch(train) [248][35/63] lr: 1.7576e-03 eta: 9:47:37 time: 0.5188 data_time: 0.0110 memory: 14901 loss: 1.7743 loss_prob: 1.0288 loss_thr: 0.5757 loss_db: 0.1699 2022/11/02 14:47:32 - mmengine - INFO - Epoch(train) [248][40/63] lr: 1.7576e-03 eta: 9:47:28 time: 0.5050 data_time: 0.0129 memory: 14901 loss: 1.8135 loss_prob: 1.0578 loss_thr: 0.5841 loss_db: 0.1716 2022/11/02 14:47:34 - mmengine - INFO - Epoch(train) [248][45/63] lr: 1.7576e-03 eta: 9:47:28 time: 0.5179 data_time: 0.0113 memory: 14901 loss: 1.8995 loss_prob: 1.1115 loss_thr: 0.6061 loss_db: 0.1819 2022/11/02 14:47:37 - mmengine - INFO - Epoch(train) [248][50/63] lr: 1.7576e-03 eta: 9:47:20 time: 0.5299 data_time: 0.0237 memory: 14901 loss: 2.0007 loss_prob: 1.1941 loss_thr: 0.6110 loss_db: 0.1955 2022/11/02 14:47:40 - mmengine - INFO - Epoch(train) [248][55/63] lr: 1.7576e-03 eta: 9:47:20 time: 0.5477 data_time: 0.0213 memory: 14901 loss: 1.9060 loss_prob: 1.1157 loss_thr: 0.6064 loss_db: 0.1839 2022/11/02 14:47:42 - mmengine - INFO - Epoch(train) [248][60/63] lr: 1.7576e-03 eta: 9:47:12 time: 0.5357 data_time: 0.0101 memory: 14901 loss: 1.7554 loss_prob: 0.9847 loss_thr: 0.6036 loss_db: 0.1671 2022/11/02 14:47:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:47:50 - mmengine - INFO - Epoch(train) [249][5/63] lr: 1.7559e-03 eta: 9:47:12 time: 0.8242 data_time: 0.2014 memory: 14901 loss: 1.7497 loss_prob: 1.0072 loss_thr: 0.5736 loss_db: 0.1689 2022/11/02 14:47:52 - mmengine - INFO - Epoch(train) [249][10/63] lr: 1.7559e-03 eta: 9:47:08 time: 0.8526 data_time: 0.2045 memory: 14901 loss: 1.7403 loss_prob: 0.9976 loss_thr: 0.5778 loss_db: 0.1648 2022/11/02 14:47:55 - mmengine - INFO - Epoch(train) [249][15/63] lr: 1.7559e-03 eta: 9:47:08 time: 0.5673 data_time: 0.0153 memory: 14901 loss: 2.1983 loss_prob: 1.3428 loss_thr: 0.6403 loss_db: 0.2152 2022/11/02 14:47:58 - mmengine - INFO - Epoch(train) [249][20/63] lr: 1.7559e-03 eta: 9:47:00 time: 0.5506 data_time: 0.0169 memory: 14901 loss: 2.4574 loss_prob: 1.5208 loss_thr: 0.6951 loss_db: 0.2415 2022/11/02 14:48:01 - mmengine - INFO - Epoch(train) [249][25/63] lr: 1.7559e-03 eta: 9:47:00 time: 0.5391 data_time: 0.0174 memory: 14901 loss: 2.0162 loss_prob: 1.1951 loss_thr: 0.6280 loss_db: 0.1931 2022/11/02 14:48:04 - mmengine - INFO - Epoch(train) [249][30/63] lr: 1.7559e-03 eta: 9:46:54 time: 0.5675 data_time: 0.0327 memory: 14901 loss: 1.7468 loss_prob: 1.0026 loss_thr: 0.5777 loss_db: 0.1665 2022/11/02 14:48:07 - mmengine - INFO - Epoch(train) [249][35/63] lr: 1.7559e-03 eta: 9:46:54 time: 0.6177 data_time: 0.0358 memory: 14901 loss: 1.9365 loss_prob: 1.1354 loss_thr: 0.6126 loss_db: 0.1885 2022/11/02 14:48:10 - mmengine - INFO - Epoch(train) [249][40/63] lr: 1.7559e-03 eta: 9:46:48 time: 0.6011 data_time: 0.0151 memory: 14901 loss: 1.8888 loss_prob: 1.1074 loss_thr: 0.6006 loss_db: 0.1808 2022/11/02 14:48:12 - mmengine - INFO - Epoch(train) [249][45/63] lr: 1.7559e-03 eta: 9:46:48 time: 0.5250 data_time: 0.0103 memory: 14901 loss: 1.8084 loss_prob: 1.0507 loss_thr: 0.5858 loss_db: 0.1719 2022/11/02 14:48:15 - mmengine - INFO - Epoch(train) [249][50/63] lr: 1.7559e-03 eta: 9:46:40 time: 0.5279 data_time: 0.0159 memory: 14901 loss: 2.0856 loss_prob: 1.2470 loss_thr: 0.6349 loss_db: 0.2036 2022/11/02 14:48:18 - mmengine - INFO - Epoch(train) [249][55/63] lr: 1.7559e-03 eta: 9:46:40 time: 0.5407 data_time: 0.0247 memory: 14901 loss: 2.0244 loss_prob: 1.2040 loss_thr: 0.6226 loss_db: 0.1978 2022/11/02 14:48:21 - mmengine - INFO - Epoch(train) [249][60/63] lr: 1.7559e-03 eta: 9:46:34 time: 0.5817 data_time: 0.0250 memory: 14901 loss: 1.9270 loss_prob: 1.1297 loss_thr: 0.6081 loss_db: 0.1892 2022/11/02 14:48:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:48:28 - mmengine - INFO - Epoch(train) [250][5/63] lr: 1.7542e-03 eta: 9:46:34 time: 0.8458 data_time: 0.2415 memory: 14901 loss: 1.8699 loss_prob: 1.0910 loss_thr: 0.5998 loss_db: 0.1792 2022/11/02 14:48:31 - mmengine - INFO - Epoch(train) [250][10/63] lr: 1.7542e-03 eta: 9:46:31 time: 0.8780 data_time: 0.2474 memory: 14901 loss: 1.8509 loss_prob: 1.0765 loss_thr: 0.5980 loss_db: 0.1764 2022/11/02 14:48:33 - mmengine - INFO - Epoch(train) [250][15/63] lr: 1.7542e-03 eta: 9:46:31 time: 0.5506 data_time: 0.0215 memory: 14901 loss: 1.7940 loss_prob: 1.0230 loss_thr: 0.5997 loss_db: 0.1713 2022/11/02 14:48:36 - mmengine - INFO - Epoch(train) [250][20/63] lr: 1.7542e-03 eta: 9:46:23 time: 0.5377 data_time: 0.0108 memory: 14901 loss: 1.8201 loss_prob: 1.0528 loss_thr: 0.5937 loss_db: 0.1737 2022/11/02 14:48:39 - mmengine - INFO - Epoch(train) [250][25/63] lr: 1.7542e-03 eta: 9:46:23 time: 0.5307 data_time: 0.0098 memory: 14901 loss: 1.7957 loss_prob: 1.0396 loss_thr: 0.5848 loss_db: 0.1714 2022/11/02 14:48:43 - mmengine - INFO - Epoch(train) [250][30/63] lr: 1.7542e-03 eta: 9:46:21 time: 0.6772 data_time: 0.0467 memory: 14901 loss: 1.7935 loss_prob: 1.0224 loss_thr: 0.6018 loss_db: 0.1693 2022/11/02 14:48:46 - mmengine - INFO - Epoch(train) [250][35/63] lr: 1.7542e-03 eta: 9:46:21 time: 0.7391 data_time: 0.0454 memory: 14901 loss: 1.8328 loss_prob: 1.0515 loss_thr: 0.6097 loss_db: 0.1716 2022/11/02 14:48:49 - mmengine - INFO - Epoch(train) [250][40/63] lr: 1.7542e-03 eta: 9:46:15 time: 0.5903 data_time: 0.0112 memory: 14901 loss: 1.7522 loss_prob: 1.0044 loss_thr: 0.5820 loss_db: 0.1658 2022/11/02 14:48:52 - mmengine - INFO - Epoch(train) [250][45/63] lr: 1.7542e-03 eta: 9:46:15 time: 0.5455 data_time: 0.0091 memory: 14901 loss: 1.7237 loss_prob: 0.9666 loss_thr: 0.5953 loss_db: 0.1618 2022/11/02 14:48:55 - mmengine - INFO - Epoch(train) [250][50/63] lr: 1.7542e-03 eta: 9:46:09 time: 0.5811 data_time: 0.0228 memory: 14901 loss: 1.8142 loss_prob: 1.0201 loss_thr: 0.6264 loss_db: 0.1678 2022/11/02 14:48:57 - mmengine - INFO - Epoch(train) [250][55/63] lr: 1.7542e-03 eta: 9:46:09 time: 0.5607 data_time: 0.0282 memory: 14901 loss: 1.8381 loss_prob: 1.0510 loss_thr: 0.6145 loss_db: 0.1725 2022/11/02 14:49:00 - mmengine - INFO - Epoch(train) [250][60/63] lr: 1.7542e-03 eta: 9:46:01 time: 0.5287 data_time: 0.0170 memory: 14901 loss: 1.7472 loss_prob: 0.9987 loss_thr: 0.5826 loss_db: 0.1659 2022/11/02 14:49:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:49:08 - mmengine - INFO - Epoch(train) [251][5/63] lr: 1.7526e-03 eta: 9:46:01 time: 0.9139 data_time: 0.2490 memory: 14901 loss: 1.6598 loss_prob: 0.9237 loss_thr: 0.5845 loss_db: 0.1516 2022/11/02 14:49:10 - mmengine - INFO - Epoch(train) [251][10/63] lr: 1.7526e-03 eta: 9:45:58 time: 0.9053 data_time: 0.2514 memory: 14901 loss: 1.7365 loss_prob: 0.9671 loss_thr: 0.6075 loss_db: 0.1620 2022/11/02 14:49:13 - mmengine - INFO - Epoch(train) [251][15/63] lr: 1.7526e-03 eta: 9:45:58 time: 0.5300 data_time: 0.0131 memory: 14901 loss: 1.7690 loss_prob: 0.9959 loss_thr: 0.6051 loss_db: 0.1680 2022/11/02 14:49:16 - mmengine - INFO - Epoch(train) [251][20/63] lr: 1.7526e-03 eta: 9:45:53 time: 0.5847 data_time: 0.0124 memory: 14901 loss: 1.7650 loss_prob: 0.9891 loss_thr: 0.6123 loss_db: 0.1636 2022/11/02 14:49:19 - mmengine - INFO - Epoch(train) [251][25/63] lr: 1.7526e-03 eta: 9:45:53 time: 0.5546 data_time: 0.0167 memory: 14901 loss: 1.7377 loss_prob: 0.9747 loss_thr: 0.5986 loss_db: 0.1644 2022/11/02 14:49:22 - mmengine - INFO - Epoch(train) [251][30/63] lr: 1.7526e-03 eta: 9:45:46 time: 0.5767 data_time: 0.0393 memory: 14901 loss: 1.7809 loss_prob: 1.0285 loss_thr: 0.5794 loss_db: 0.1730 2022/11/02 14:49:24 - mmengine - INFO - Epoch(train) [251][35/63] lr: 1.7526e-03 eta: 9:45:46 time: 0.5725 data_time: 0.0330 memory: 14901 loss: 1.7423 loss_prob: 1.0056 loss_thr: 0.5701 loss_db: 0.1666 2022/11/02 14:49:27 - mmengine - INFO - Epoch(train) [251][40/63] lr: 1.7526e-03 eta: 9:45:37 time: 0.5103 data_time: 0.0101 memory: 14901 loss: 1.6800 loss_prob: 0.9489 loss_thr: 0.5724 loss_db: 0.1587 2022/11/02 14:49:31 - mmengine - INFO - Epoch(train) [251][45/63] lr: 1.7526e-03 eta: 9:45:37 time: 0.6579 data_time: 0.0105 memory: 14901 loss: 1.6450 loss_prob: 0.9225 loss_thr: 0.5699 loss_db: 0.1527 2022/11/02 14:49:34 - mmengine - INFO - Epoch(train) [251][50/63] lr: 1.7526e-03 eta: 9:45:36 time: 0.7090 data_time: 0.0259 memory: 14901 loss: 1.5970 loss_prob: 0.8894 loss_thr: 0.5601 loss_db: 0.1475 2022/11/02 14:49:37 - mmengine - INFO - Epoch(train) [251][55/63] lr: 1.7526e-03 eta: 9:45:36 time: 0.5814 data_time: 0.0266 memory: 14901 loss: 1.6088 loss_prob: 0.9056 loss_thr: 0.5523 loss_db: 0.1509 2022/11/02 14:49:40 - mmengine - INFO - Epoch(train) [251][60/63] lr: 1.7526e-03 eta: 9:45:28 time: 0.5320 data_time: 0.0135 memory: 14901 loss: 1.5877 loss_prob: 0.8985 loss_thr: 0.5431 loss_db: 0.1461 2022/11/02 14:49:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:49:46 - mmengine - INFO - Epoch(train) [252][5/63] lr: 1.7509e-03 eta: 9:45:28 time: 0.7843 data_time: 0.2544 memory: 14901 loss: 1.7102 loss_prob: 0.9685 loss_thr: 0.5832 loss_db: 0.1585 2022/11/02 14:49:49 - mmengine - INFO - Epoch(train) [252][10/63] lr: 1.7509e-03 eta: 9:45:23 time: 0.8327 data_time: 0.2529 memory: 14901 loss: 1.7051 loss_prob: 0.9685 loss_thr: 0.5790 loss_db: 0.1575 2022/11/02 14:49:52 - mmengine - INFO - Epoch(train) [252][15/63] lr: 1.7509e-03 eta: 9:45:23 time: 0.5325 data_time: 0.0102 memory: 14901 loss: 1.6376 loss_prob: 0.9228 loss_thr: 0.5630 loss_db: 0.1518 2022/11/02 14:49:55 - mmengine - INFO - Epoch(train) [252][20/63] lr: 1.7509e-03 eta: 9:45:15 time: 0.5340 data_time: 0.0102 memory: 14901 loss: 1.6812 loss_prob: 0.9597 loss_thr: 0.5671 loss_db: 0.1544 2022/11/02 14:49:58 - mmengine - INFO - Epoch(train) [252][25/63] lr: 1.7509e-03 eta: 9:45:15 time: 0.5958 data_time: 0.0408 memory: 14901 loss: 1.6817 loss_prob: 0.9616 loss_thr: 0.5651 loss_db: 0.1550 2022/11/02 14:50:01 - mmengine - INFO - Epoch(train) [252][30/63] lr: 1.7509e-03 eta: 9:45:10 time: 0.6084 data_time: 0.0408 memory: 14901 loss: 1.6149 loss_prob: 0.9095 loss_thr: 0.5529 loss_db: 0.1525 2022/11/02 14:50:04 - mmengine - INFO - Epoch(train) [252][35/63] lr: 1.7509e-03 eta: 9:45:10 time: 0.5828 data_time: 0.0098 memory: 14901 loss: 1.7167 loss_prob: 0.9902 loss_thr: 0.5611 loss_db: 0.1653 2022/11/02 14:50:06 - mmengine - INFO - Epoch(train) [252][40/63] lr: 1.7509e-03 eta: 9:45:04 time: 0.5718 data_time: 0.0128 memory: 14901 loss: 1.6876 loss_prob: 0.9590 loss_thr: 0.5695 loss_db: 0.1592 2022/11/02 14:50:09 - mmengine - INFO - Epoch(train) [252][45/63] lr: 1.7509e-03 eta: 9:45:04 time: 0.5597 data_time: 0.0104 memory: 14901 loss: 1.6287 loss_prob: 0.8993 loss_thr: 0.5816 loss_db: 0.1479 2022/11/02 14:50:12 - mmengine - INFO - Epoch(train) [252][50/63] lr: 1.7509e-03 eta: 9:44:57 time: 0.5653 data_time: 0.0226 memory: 14901 loss: 1.6779 loss_prob: 0.9298 loss_thr: 0.5943 loss_db: 0.1539 2022/11/02 14:50:15 - mmengine - INFO - Epoch(train) [252][55/63] lr: 1.7509e-03 eta: 9:44:57 time: 0.5853 data_time: 0.0225 memory: 14901 loss: 1.6291 loss_prob: 0.9028 loss_thr: 0.5759 loss_db: 0.1504 2022/11/02 14:50:18 - mmengine - INFO - Epoch(train) [252][60/63] lr: 1.7509e-03 eta: 9:44:51 time: 0.5800 data_time: 0.0097 memory: 14901 loss: 1.6066 loss_prob: 0.8894 loss_thr: 0.5679 loss_db: 0.1493 2022/11/02 14:50:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:50:26 - mmengine - INFO - Epoch(train) [253][5/63] lr: 1.7492e-03 eta: 9:44:51 time: 0.8997 data_time: 0.2254 memory: 14901 loss: 1.6444 loss_prob: 0.9088 loss_thr: 0.5811 loss_db: 0.1545 2022/11/02 14:50:29 - mmengine - INFO - Epoch(train) [253][10/63] lr: 1.7492e-03 eta: 9:44:49 time: 0.9243 data_time: 0.2396 memory: 14901 loss: 1.6331 loss_prob: 0.8952 loss_thr: 0.5856 loss_db: 0.1523 2022/11/02 14:50:31 - mmengine - INFO - Epoch(train) [253][15/63] lr: 1.7492e-03 eta: 9:44:49 time: 0.5850 data_time: 0.0250 memory: 14901 loss: 1.5749 loss_prob: 0.8696 loss_thr: 0.5602 loss_db: 0.1452 2022/11/02 14:50:34 - mmengine - INFO - Epoch(train) [253][20/63] lr: 1.7492e-03 eta: 9:44:41 time: 0.5140 data_time: 0.0082 memory: 14901 loss: 1.5597 loss_prob: 0.8868 loss_thr: 0.5263 loss_db: 0.1465 2022/11/02 14:50:37 - mmengine - INFO - Epoch(train) [253][25/63] lr: 1.7492e-03 eta: 9:44:41 time: 0.5071 data_time: 0.0192 memory: 14901 loss: 1.6882 loss_prob: 0.9717 loss_thr: 0.5526 loss_db: 0.1639 2022/11/02 14:50:39 - mmengine - INFO - Epoch(train) [253][30/63] lr: 1.7492e-03 eta: 9:44:32 time: 0.5255 data_time: 0.0399 memory: 14901 loss: 1.8033 loss_prob: 1.0378 loss_thr: 0.5936 loss_db: 0.1719 2022/11/02 14:50:42 - mmengine - INFO - Epoch(train) [253][35/63] lr: 1.7492e-03 eta: 9:44:32 time: 0.5393 data_time: 0.0356 memory: 14901 loss: 1.7404 loss_prob: 0.9961 loss_thr: 0.5818 loss_db: 0.1625 2022/11/02 14:50:44 - mmengine - INFO - Epoch(train) [253][40/63] lr: 1.7492e-03 eta: 9:44:24 time: 0.5214 data_time: 0.0159 memory: 14901 loss: 1.7886 loss_prob: 1.0407 loss_thr: 0.5761 loss_db: 0.1718 2022/11/02 14:50:47 - mmengine - INFO - Epoch(train) [253][45/63] lr: 1.7492e-03 eta: 9:44:24 time: 0.5163 data_time: 0.0111 memory: 14901 loss: 1.8885 loss_prob: 1.1042 loss_thr: 0.6023 loss_db: 0.1820 2022/11/02 14:50:51 - mmengine - INFO - Epoch(train) [253][50/63] lr: 1.7492e-03 eta: 9:44:20 time: 0.6265 data_time: 0.0238 memory: 14901 loss: 1.7622 loss_prob: 0.9980 loss_thr: 0.5954 loss_db: 0.1687 2022/11/02 14:50:53 - mmengine - INFO - Epoch(train) [253][55/63] lr: 1.7492e-03 eta: 9:44:20 time: 0.6367 data_time: 0.0265 memory: 14901 loss: 1.6786 loss_prob: 0.9462 loss_thr: 0.5727 loss_db: 0.1597 2022/11/02 14:50:56 - mmengine - INFO - Epoch(train) [253][60/63] lr: 1.7492e-03 eta: 9:44:12 time: 0.5287 data_time: 0.0141 memory: 14901 loss: 1.7204 loss_prob: 0.9735 loss_thr: 0.5867 loss_db: 0.1602 2022/11/02 14:50:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:51:03 - mmengine - INFO - Epoch(train) [254][5/63] lr: 1.7476e-03 eta: 9:44:12 time: 0.7866 data_time: 0.2337 memory: 14901 loss: 1.6846 loss_prob: 0.9550 loss_thr: 0.5702 loss_db: 0.1594 2022/11/02 14:51:06 - mmengine - INFO - Epoch(train) [254][10/63] lr: 1.7476e-03 eta: 9:44:08 time: 0.8738 data_time: 0.2534 memory: 14901 loss: 1.6955 loss_prob: 0.9676 loss_thr: 0.5679 loss_db: 0.1601 2022/11/02 14:51:09 - mmengine - INFO - Epoch(train) [254][15/63] lr: 1.7476e-03 eta: 9:44:08 time: 0.6265 data_time: 0.0291 memory: 14901 loss: 1.7130 loss_prob: 0.9709 loss_thr: 0.5862 loss_db: 0.1558 2022/11/02 14:51:12 - mmengine - INFO - Epoch(train) [254][20/63] lr: 1.7476e-03 eta: 9:44:02 time: 0.5771 data_time: 0.0086 memory: 14901 loss: 1.7279 loss_prob: 0.9877 loss_thr: 0.5790 loss_db: 0.1612 2022/11/02 14:51:14 - mmengine - INFO - Epoch(train) [254][25/63] lr: 1.7476e-03 eta: 9:44:02 time: 0.5397 data_time: 0.0118 memory: 14901 loss: 1.6447 loss_prob: 0.9323 loss_thr: 0.5595 loss_db: 0.1529 2022/11/02 14:51:17 - mmengine - INFO - Epoch(train) [254][30/63] lr: 1.7476e-03 eta: 9:43:55 time: 0.5625 data_time: 0.0393 memory: 14901 loss: 1.6563 loss_prob: 0.9174 loss_thr: 0.5903 loss_db: 0.1486 2022/11/02 14:51:20 - mmengine - INFO - Epoch(train) [254][35/63] lr: 1.7476e-03 eta: 9:43:55 time: 0.6060 data_time: 0.0334 memory: 14901 loss: 1.7363 loss_prob: 0.9539 loss_thr: 0.6249 loss_db: 0.1576 2022/11/02 14:51:23 - mmengine - INFO - Epoch(train) [254][40/63] lr: 1.7476e-03 eta: 9:43:49 time: 0.5831 data_time: 0.0081 memory: 14901 loss: 1.6950 loss_prob: 0.9366 loss_thr: 0.5987 loss_db: 0.1596 2022/11/02 14:51:26 - mmengine - INFO - Epoch(train) [254][45/63] lr: 1.7476e-03 eta: 9:43:49 time: 0.5232 data_time: 0.0098 memory: 14901 loss: 1.7109 loss_prob: 0.9640 loss_thr: 0.5858 loss_db: 0.1611 2022/11/02 14:51:29 - mmengine - INFO - Epoch(train) [254][50/63] lr: 1.7476e-03 eta: 9:43:41 time: 0.5392 data_time: 0.0163 memory: 14901 loss: 1.7993 loss_prob: 1.0145 loss_thr: 0.6201 loss_db: 0.1647 2022/11/02 14:51:31 - mmengine - INFO - Epoch(train) [254][55/63] lr: 1.7476e-03 eta: 9:43:41 time: 0.5596 data_time: 0.0347 memory: 14901 loss: 1.7676 loss_prob: 0.9912 loss_thr: 0.6109 loss_db: 0.1655 2022/11/02 14:51:34 - mmengine - INFO - Epoch(train) [254][60/63] lr: 1.7476e-03 eta: 9:43:34 time: 0.5462 data_time: 0.0263 memory: 14901 loss: 1.6936 loss_prob: 0.9533 loss_thr: 0.5810 loss_db: 0.1592 2022/11/02 14:51:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:51:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:51:40 - mmengine - INFO - Epoch(train) [255][5/63] lr: 1.7459e-03 eta: 9:43:34 time: 0.7367 data_time: 0.2456 memory: 14901 loss: 1.6553 loss_prob: 0.9313 loss_thr: 0.5711 loss_db: 0.1529 2022/11/02 14:51:44 - mmengine - INFO - Epoch(train) [255][10/63] lr: 1.7459e-03 eta: 9:43:32 time: 0.9165 data_time: 0.2658 memory: 14901 loss: 1.7040 loss_prob: 0.9617 loss_thr: 0.5835 loss_db: 0.1588 2022/11/02 14:51:47 - mmengine - INFO - Epoch(train) [255][15/63] lr: 1.7459e-03 eta: 9:43:32 time: 0.6656 data_time: 0.0261 memory: 14901 loss: 1.6110 loss_prob: 0.8992 loss_thr: 0.5615 loss_db: 0.1503 2022/11/02 14:51:50 - mmengine - INFO - Epoch(train) [255][20/63] lr: 1.7459e-03 eta: 9:43:24 time: 0.5470 data_time: 0.0071 memory: 14901 loss: 1.5459 loss_prob: 0.8533 loss_thr: 0.5493 loss_db: 0.1432 2022/11/02 14:51:53 - mmengine - INFO - Epoch(train) [255][25/63] lr: 1.7459e-03 eta: 9:43:24 time: 0.5619 data_time: 0.0172 memory: 14901 loss: 1.7159 loss_prob: 0.9723 loss_thr: 0.5805 loss_db: 0.1631 2022/11/02 14:51:56 - mmengine - INFO - Epoch(train) [255][30/63] lr: 1.7459e-03 eta: 9:43:19 time: 0.6051 data_time: 0.0383 memory: 14901 loss: 1.8016 loss_prob: 1.0300 loss_thr: 0.6003 loss_db: 0.1714 2022/11/02 14:51:58 - mmengine - INFO - Epoch(train) [255][35/63] lr: 1.7459e-03 eta: 9:43:19 time: 0.5693 data_time: 0.0319 memory: 14901 loss: 1.9940 loss_prob: 1.2085 loss_thr: 0.5999 loss_db: 0.1856 2022/11/02 14:52:01 - mmengine - INFO - Epoch(train) [255][40/63] lr: 1.7459e-03 eta: 9:43:11 time: 0.5239 data_time: 0.0093 memory: 14901 loss: 2.0471 loss_prob: 1.2471 loss_thr: 0.6106 loss_db: 0.1894 2022/11/02 14:52:04 - mmengine - INFO - Epoch(train) [255][45/63] lr: 1.7459e-03 eta: 9:43:11 time: 0.5551 data_time: 0.0096 memory: 14901 loss: 1.9299 loss_prob: 1.1416 loss_thr: 0.6071 loss_db: 0.1812 2022/11/02 14:52:07 - mmengine - INFO - Epoch(train) [255][50/63] lr: 1.7459e-03 eta: 9:43:03 time: 0.5342 data_time: 0.0220 memory: 14901 loss: 1.9013 loss_prob: 1.1347 loss_thr: 0.5803 loss_db: 0.1863 2022/11/02 14:52:09 - mmengine - INFO - Epoch(train) [255][55/63] lr: 1.7459e-03 eta: 9:43:03 time: 0.5434 data_time: 0.0283 memory: 14901 loss: 1.8117 loss_prob: 1.0508 loss_thr: 0.5836 loss_db: 0.1774 2022/11/02 14:52:12 - mmengine - INFO - Epoch(train) [255][60/63] lr: 1.7459e-03 eta: 9:42:56 time: 0.5476 data_time: 0.0204 memory: 14901 loss: 1.7541 loss_prob: 0.9890 loss_thr: 0.5986 loss_db: 0.1664 2022/11/02 14:52:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:52:19 - mmengine - INFO - Epoch(train) [256][5/63] lr: 1.7443e-03 eta: 9:42:56 time: 0.8181 data_time: 0.2618 memory: 14901 loss: 1.7458 loss_prob: 0.9897 loss_thr: 0.5902 loss_db: 0.1659 2022/11/02 14:52:22 - mmengine - INFO - Epoch(train) [256][10/63] lr: 1.7443e-03 eta: 9:42:51 time: 0.8334 data_time: 0.2634 memory: 14901 loss: 1.8012 loss_prob: 1.0189 loss_thr: 0.6104 loss_db: 0.1720 2022/11/02 14:52:24 - mmengine - INFO - Epoch(train) [256][15/63] lr: 1.7443e-03 eta: 9:42:51 time: 0.5287 data_time: 0.0286 memory: 14901 loss: 1.7652 loss_prob: 0.9904 loss_thr: 0.6097 loss_db: 0.1651 2022/11/02 14:52:28 - mmengine - INFO - Epoch(train) [256][20/63] lr: 1.7443e-03 eta: 9:42:48 time: 0.6601 data_time: 0.0289 memory: 14901 loss: 1.7197 loss_prob: 0.9656 loss_thr: 0.5934 loss_db: 0.1606 2022/11/02 14:52:31 - mmengine - INFO - Epoch(train) [256][25/63] lr: 1.7443e-03 eta: 9:42:48 time: 0.6796 data_time: 0.0082 memory: 14901 loss: 1.6395 loss_prob: 0.9096 loss_thr: 0.5779 loss_db: 0.1520 2022/11/02 14:52:35 - mmengine - INFO - Epoch(train) [256][30/63] lr: 1.7443e-03 eta: 9:42:43 time: 0.6334 data_time: 0.0258 memory: 14901 loss: 1.5946 loss_prob: 0.8915 loss_thr: 0.5537 loss_db: 0.1494 2022/11/02 14:52:37 - mmengine - INFO - Epoch(train) [256][35/63] lr: 1.7443e-03 eta: 9:42:43 time: 0.5943 data_time: 0.0253 memory: 14901 loss: 1.7066 loss_prob: 0.9640 loss_thr: 0.5811 loss_db: 0.1615 2022/11/02 14:52:40 - mmengine - INFO - Epoch(train) [256][40/63] lr: 1.7443e-03 eta: 9:42:35 time: 0.5157 data_time: 0.0124 memory: 14901 loss: 1.6821 loss_prob: 0.9265 loss_thr: 0.5990 loss_db: 0.1566 2022/11/02 14:52:42 - mmengine - INFO - Epoch(train) [256][45/63] lr: 1.7443e-03 eta: 9:42:35 time: 0.5298 data_time: 0.0158 memory: 14901 loss: 1.8149 loss_prob: 1.0189 loss_thr: 0.6263 loss_db: 0.1697 2022/11/02 14:52:45 - mmengine - INFO - Epoch(train) [256][50/63] lr: 1.7443e-03 eta: 9:42:27 time: 0.5473 data_time: 0.0209 memory: 14901 loss: 2.0200 loss_prob: 1.2247 loss_thr: 0.5917 loss_db: 0.2036 2022/11/02 14:52:48 - mmengine - INFO - Epoch(train) [256][55/63] lr: 1.7443e-03 eta: 9:42:27 time: 0.5493 data_time: 0.0211 memory: 14901 loss: 3.7791 loss_prob: 2.6954 loss_thr: 0.6954 loss_db: 0.3883 2022/11/02 14:52:51 - mmengine - INFO - Epoch(train) [256][60/63] lr: 1.7443e-03 eta: 9:42:21 time: 0.5614 data_time: 0.0088 memory: 14901 loss: 4.6506 loss_prob: 3.3164 loss_thr: 0.8488 loss_db: 0.4853 2022/11/02 14:52:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:52:58 - mmengine - INFO - Epoch(train) [257][5/63] lr: 1.7426e-03 eta: 9:42:21 time: 0.8320 data_time: 0.2310 memory: 14901 loss: 3.2603 loss_prob: 2.1466 loss_thr: 0.7510 loss_db: 0.3627 2022/11/02 14:53:01 - mmengine - INFO - Epoch(train) [257][10/63] lr: 1.7426e-03 eta: 9:42:16 time: 0.8358 data_time: 0.2284 memory: 14901 loss: 2.8645 loss_prob: 1.8150 loss_thr: 0.7510 loss_db: 0.2985 2022/11/02 14:53:03 - mmengine - INFO - Epoch(train) [257][15/63] lr: 1.7426e-03 eta: 9:42:16 time: 0.5487 data_time: 0.0112 memory: 14901 loss: 2.6177 loss_prob: 1.6274 loss_thr: 0.7278 loss_db: 0.2626 2022/11/02 14:53:06 - mmengine - INFO - Epoch(train) [257][20/63] lr: 1.7426e-03 eta: 9:42:08 time: 0.5453 data_time: 0.0138 memory: 14901 loss: 2.4892 loss_prob: 1.5622 loss_thr: 0.6767 loss_db: 0.2503 2022/11/02 14:53:09 - mmengine - INFO - Epoch(train) [257][25/63] lr: 1.7426e-03 eta: 9:42:08 time: 0.5724 data_time: 0.0162 memory: 14901 loss: 2.5192 loss_prob: 1.5711 loss_thr: 0.6904 loss_db: 0.2577 2022/11/02 14:53:12 - mmengine - INFO - Epoch(train) [257][30/63] lr: 1.7426e-03 eta: 9:42:02 time: 0.5777 data_time: 0.0434 memory: 14901 loss: 2.6065 loss_prob: 1.6202 loss_thr: 0.7154 loss_db: 0.2709 2022/11/02 14:53:15 - mmengine - INFO - Epoch(train) [257][35/63] lr: 1.7426e-03 eta: 9:42:02 time: 0.5570 data_time: 0.0395 memory: 14901 loss: 2.5256 loss_prob: 1.5592 loss_thr: 0.7047 loss_db: 0.2618 2022/11/02 14:53:17 - mmengine - INFO - Epoch(train) [257][40/63] lr: 1.7426e-03 eta: 9:41:54 time: 0.5253 data_time: 0.0073 memory: 14901 loss: 2.3333 loss_prob: 1.4253 loss_thr: 0.6729 loss_db: 0.2351 2022/11/02 14:53:19 - mmengine - INFO - Epoch(train) [257][45/63] lr: 1.7426e-03 eta: 9:41:54 time: 0.4791 data_time: 0.0054 memory: 14901 loss: 2.2559 loss_prob: 1.3924 loss_thr: 0.6391 loss_db: 0.2244 2022/11/02 14:53:23 - mmengine - INFO - Epoch(train) [257][50/63] lr: 1.7426e-03 eta: 9:41:49 time: 0.6133 data_time: 0.0309 memory: 14901 loss: 2.2184 loss_prob: 1.3694 loss_thr: 0.6339 loss_db: 0.2151 2022/11/02 14:53:26 - mmengine - INFO - Epoch(train) [257][55/63] lr: 1.7426e-03 eta: 9:41:49 time: 0.6378 data_time: 0.0317 memory: 14901 loss: 2.1899 loss_prob: 1.3338 loss_thr: 0.6484 loss_db: 0.2077 2022/11/02 14:53:29 - mmengine - INFO - Epoch(train) [257][60/63] lr: 1.7426e-03 eta: 9:41:42 time: 0.5479 data_time: 0.0119 memory: 14901 loss: 2.1289 loss_prob: 1.2829 loss_thr: 0.6386 loss_db: 0.2074 2022/11/02 14:53:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:53:37 - mmengine - INFO - Epoch(train) [258][5/63] lr: 1.7409e-03 eta: 9:41:42 time: 0.8867 data_time: 0.2740 memory: 14901 loss: 2.1367 loss_prob: 1.2596 loss_thr: 0.6728 loss_db: 0.2043 2022/11/02 14:53:39 - mmengine - INFO - Epoch(train) [258][10/63] lr: 1.7409e-03 eta: 9:41:39 time: 0.8931 data_time: 0.2829 memory: 14901 loss: 2.2038 loss_prob: 1.3149 loss_thr: 0.6798 loss_db: 0.2090 2022/11/02 14:53:42 - mmengine - INFO - Epoch(train) [258][15/63] lr: 1.7409e-03 eta: 9:41:39 time: 0.5385 data_time: 0.0155 memory: 14901 loss: 2.2113 loss_prob: 1.3451 loss_thr: 0.6558 loss_db: 0.2104 2022/11/02 14:53:45 - mmengine - INFO - Epoch(train) [258][20/63] lr: 1.7409e-03 eta: 9:41:32 time: 0.5613 data_time: 0.0080 memory: 14901 loss: 2.1346 loss_prob: 1.2953 loss_thr: 0.6378 loss_db: 0.2014 2022/11/02 14:53:48 - mmengine - INFO - Epoch(train) [258][25/63] lr: 1.7409e-03 eta: 9:41:32 time: 0.5685 data_time: 0.0332 memory: 14901 loss: 2.1025 loss_prob: 1.2676 loss_thr: 0.6331 loss_db: 0.2018 2022/11/02 14:53:51 - mmengine - INFO - Epoch(train) [258][30/63] lr: 1.7409e-03 eta: 9:41:28 time: 0.6367 data_time: 0.0321 memory: 14901 loss: 1.9289 loss_prob: 1.1269 loss_thr: 0.6147 loss_db: 0.1872 2022/11/02 14:53:54 - mmengine - INFO - Epoch(train) [258][35/63] lr: 1.7409e-03 eta: 9:41:28 time: 0.6055 data_time: 0.0093 memory: 14901 loss: 1.8262 loss_prob: 1.0518 loss_thr: 0.6041 loss_db: 0.1704 2022/11/02 14:53:57 - mmengine - INFO - Epoch(train) [258][40/63] lr: 1.7409e-03 eta: 9:41:22 time: 0.6042 data_time: 0.0084 memory: 14901 loss: 1.8712 loss_prob: 1.0998 loss_thr: 0.5942 loss_db: 0.1772 2022/11/02 14:54:01 - mmengine - INFO - Epoch(train) [258][45/63] lr: 1.7409e-03 eta: 9:41:22 time: 0.7006 data_time: 0.0059 memory: 14901 loss: 1.9962 loss_prob: 1.1919 loss_thr: 0.6105 loss_db: 0.1937 2022/11/02 14:54:03 - mmengine - INFO - Epoch(train) [258][50/63] lr: 1.7409e-03 eta: 9:41:17 time: 0.5988 data_time: 0.0204 memory: 14901 loss: 2.0001 loss_prob: 1.2008 loss_thr: 0.6045 loss_db: 0.1948 2022/11/02 14:54:06 - mmengine - INFO - Epoch(train) [258][55/63] lr: 1.7409e-03 eta: 9:41:17 time: 0.5158 data_time: 0.0221 memory: 14901 loss: 1.9741 loss_prob: 1.1685 loss_thr: 0.6130 loss_db: 0.1925 2022/11/02 14:54:09 - mmengine - INFO - Epoch(train) [258][60/63] lr: 1.7409e-03 eta: 9:41:09 time: 0.5423 data_time: 0.0129 memory: 14901 loss: 1.9989 loss_prob: 1.1796 loss_thr: 0.6254 loss_db: 0.1939 2022/11/02 14:54:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:54:16 - mmengine - INFO - Epoch(train) [259][5/63] lr: 1.7393e-03 eta: 9:41:09 time: 0.9020 data_time: 0.2406 memory: 14901 loss: 1.8354 loss_prob: 1.0556 loss_thr: 0.6031 loss_db: 0.1767 2022/11/02 14:54:19 - mmengine - INFO - Epoch(train) [259][10/63] lr: 1.7393e-03 eta: 9:41:06 time: 0.8825 data_time: 0.2417 memory: 14901 loss: 2.0644 loss_prob: 1.2397 loss_thr: 0.6211 loss_db: 0.2036 2022/11/02 14:54:22 - mmengine - INFO - Epoch(train) [259][15/63] lr: 1.7393e-03 eta: 9:41:06 time: 0.5761 data_time: 0.0122 memory: 14901 loss: 2.1710 loss_prob: 1.3183 loss_thr: 0.6353 loss_db: 0.2174 2022/11/02 14:54:25 - mmengine - INFO - Epoch(train) [259][20/63] lr: 1.7393e-03 eta: 9:41:00 time: 0.5931 data_time: 0.0127 memory: 14901 loss: 2.0858 loss_prob: 1.2449 loss_thr: 0.6373 loss_db: 0.2035 2022/11/02 14:54:28 - mmengine - INFO - Epoch(train) [259][25/63] lr: 1.7393e-03 eta: 9:41:00 time: 0.5625 data_time: 0.0198 memory: 14901 loss: 2.0771 loss_prob: 1.2450 loss_thr: 0.6345 loss_db: 0.1976 2022/11/02 14:54:31 - mmengine - INFO - Epoch(train) [259][30/63] lr: 1.7393e-03 eta: 9:40:54 time: 0.5708 data_time: 0.0542 memory: 14901 loss: 1.8043 loss_prob: 1.0416 loss_thr: 0.5965 loss_db: 0.1661 2022/11/02 14:54:33 - mmengine - INFO - Epoch(train) [259][35/63] lr: 1.7393e-03 eta: 9:40:54 time: 0.5730 data_time: 0.0448 memory: 14901 loss: 1.7413 loss_prob: 0.9944 loss_thr: 0.5836 loss_db: 0.1634 2022/11/02 14:54:36 - mmengine - INFO - Epoch(train) [259][40/63] lr: 1.7393e-03 eta: 9:40:48 time: 0.5715 data_time: 0.0134 memory: 14901 loss: 1.9330 loss_prob: 1.1418 loss_thr: 0.6042 loss_db: 0.1870 2022/11/02 14:54:39 - mmengine - INFO - Epoch(train) [259][45/63] lr: 1.7393e-03 eta: 9:40:48 time: 0.5560 data_time: 0.0125 memory: 14901 loss: 1.9404 loss_prob: 1.1353 loss_thr: 0.6198 loss_db: 0.1853 2022/11/02 14:54:42 - mmengine - INFO - Epoch(train) [259][50/63] lr: 1.7393e-03 eta: 9:40:43 time: 0.6130 data_time: 0.0195 memory: 14901 loss: 1.9178 loss_prob: 1.1103 loss_thr: 0.6267 loss_db: 0.1808 2022/11/02 14:54:45 - mmengine - INFO - Epoch(train) [259][55/63] lr: 1.7393e-03 eta: 9:40:43 time: 0.6016 data_time: 0.0239 memory: 14901 loss: 1.9567 loss_prob: 1.1460 loss_thr: 0.6250 loss_db: 0.1857 2022/11/02 14:54:48 - mmengine - INFO - Epoch(train) [259][60/63] lr: 1.7393e-03 eta: 9:40:36 time: 0.5661 data_time: 0.0133 memory: 14901 loss: 1.9731 loss_prob: 1.1594 loss_thr: 0.6241 loss_db: 0.1897 2022/11/02 14:54:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:54:55 - mmengine - INFO - Epoch(train) [260][5/63] lr: 1.7376e-03 eta: 9:40:36 time: 0.8390 data_time: 0.3169 memory: 14901 loss: 1.8556 loss_prob: 1.0803 loss_thr: 0.6035 loss_db: 0.1718 2022/11/02 14:54:57 - mmengine - INFO - Epoch(train) [260][10/63] lr: 1.7376e-03 eta: 9:40:30 time: 0.8164 data_time: 0.3129 memory: 14901 loss: 1.7936 loss_prob: 1.0454 loss_thr: 0.5803 loss_db: 0.1679 2022/11/02 14:55:00 - mmengine - INFO - Epoch(train) [260][15/63] lr: 1.7376e-03 eta: 9:40:30 time: 0.5319 data_time: 0.0101 memory: 14901 loss: 1.8725 loss_prob: 1.0997 loss_thr: 0.5982 loss_db: 0.1746 2022/11/02 14:55:03 - mmengine - INFO - Epoch(train) [260][20/63] lr: 1.7376e-03 eta: 9:40:24 time: 0.5720 data_time: 0.0118 memory: 14901 loss: 1.8629 loss_prob: 1.0838 loss_thr: 0.6018 loss_db: 0.1773 2022/11/02 14:55:06 - mmengine - INFO - Epoch(train) [260][25/63] lr: 1.7376e-03 eta: 9:40:24 time: 0.5841 data_time: 0.0495 memory: 14901 loss: 1.8997 loss_prob: 1.1049 loss_thr: 0.6116 loss_db: 0.1832 2022/11/02 14:55:09 - mmengine - INFO - Epoch(train) [260][30/63] lr: 1.7376e-03 eta: 9:40:16 time: 0.5406 data_time: 0.0489 memory: 14901 loss: 1.9123 loss_prob: 1.1273 loss_thr: 0.6028 loss_db: 0.1822 2022/11/02 14:55:11 - mmengine - INFO - Epoch(train) [260][35/63] lr: 1.7376e-03 eta: 9:40:16 time: 0.4950 data_time: 0.0079 memory: 14901 loss: 1.8212 loss_prob: 1.0565 loss_thr: 0.5934 loss_db: 0.1713 2022/11/02 14:55:14 - mmengine - INFO - Epoch(train) [260][40/63] lr: 1.7376e-03 eta: 9:40:08 time: 0.5373 data_time: 0.0068 memory: 14901 loss: 1.9104 loss_prob: 1.1125 loss_thr: 0.6161 loss_db: 0.1818 2022/11/02 14:55:17 - mmengine - INFO - Epoch(train) [260][45/63] lr: 1.7376e-03 eta: 9:40:08 time: 0.5622 data_time: 0.0088 memory: 14901 loss: 1.8593 loss_prob: 1.0833 loss_thr: 0.5985 loss_db: 0.1775 2022/11/02 14:55:19 - mmengine - INFO - Epoch(train) [260][50/63] lr: 1.7376e-03 eta: 9:40:01 time: 0.5406 data_time: 0.0280 memory: 14901 loss: 1.6906 loss_prob: 0.9643 loss_thr: 0.5662 loss_db: 0.1602 2022/11/02 14:55:22 - mmengine - INFO - Epoch(train) [260][55/63] lr: 1.7376e-03 eta: 9:40:01 time: 0.4940 data_time: 0.0311 memory: 14901 loss: 1.7532 loss_prob: 0.9932 loss_thr: 0.5976 loss_db: 0.1624 2022/11/02 14:55:24 - mmengine - INFO - Epoch(train) [260][60/63] lr: 1.7376e-03 eta: 9:39:51 time: 0.4714 data_time: 0.0128 memory: 14901 loss: 1.8501 loss_prob: 1.0486 loss_thr: 0.6327 loss_db: 0.1688 2022/11/02 14:55:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:55:25 - mmengine - INFO - Saving checkpoint at 260 epochs 2022/11/02 14:55:29 - mmengine - INFO - Epoch(val) [260][5/500] eta: 9:39:51 time: 0.0463 data_time: 0.0062 memory: 14901 2022/11/02 14:55:29 - mmengine - INFO - Epoch(val) [260][10/500] eta: 0:00:23 time: 0.0472 data_time: 0.0058 memory: 1008 2022/11/02 14:55:29 - mmengine - INFO - Epoch(val) [260][15/500] eta: 0:00:23 time: 0.0373 data_time: 0.0020 memory: 1008 2022/11/02 14:55:29 - mmengine - INFO - Epoch(val) [260][20/500] eta: 0:00:17 time: 0.0374 data_time: 0.0022 memory: 1008 2022/11/02 14:55:30 - mmengine - INFO - Epoch(val) [260][25/500] eta: 0:00:17 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/02 14:55:30 - mmengine - INFO - Epoch(val) [260][30/500] eta: 0:00:19 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 14:55:30 - mmengine - INFO - Epoch(val) [260][35/500] eta: 0:00:19 time: 0.0439 data_time: 0.0030 memory: 1008 2022/11/02 14:55:30 - mmengine - INFO - Epoch(val) [260][40/500] eta: 0:00:21 time: 0.0460 data_time: 0.0030 memory: 1008 2022/11/02 14:55:31 - mmengine - INFO - Epoch(val) [260][45/500] eta: 0:00:21 time: 0.0452 data_time: 0.0030 memory: 1008 2022/11/02 14:55:32 - mmengine - INFO - Epoch(val) [260][50/500] eta: 0:00:50 time: 0.1127 data_time: 0.0751 memory: 1008 2022/11/02 14:55:32 - mmengine - INFO - Epoch(val) [260][55/500] eta: 0:00:50 time: 0.1123 data_time: 0.0744 memory: 1008 2022/11/02 14:55:32 - mmengine - INFO - Epoch(val) [260][60/500] eta: 0:00:16 time: 0.0372 data_time: 0.0018 memory: 1008 2022/11/02 14:55:32 - mmengine - INFO - Epoch(val) [260][65/500] eta: 0:00:16 time: 0.0389 data_time: 0.0021 memory: 1008 2022/11/02 14:55:32 - mmengine - INFO - Epoch(val) [260][70/500] eta: 0:00:17 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 14:55:32 - mmengine - INFO - Epoch(val) [260][75/500] eta: 0:00:17 time: 0.0381 data_time: 0.0024 memory: 1008 2022/11/02 14:55:33 - mmengine - INFO - Epoch(val) [260][80/500] eta: 0:00:46 time: 0.1107 data_time: 0.0757 memory: 1008 2022/11/02 14:55:34 - mmengine - INFO - Epoch(val) [260][85/500] eta: 0:00:46 time: 0.1081 data_time: 0.0754 memory: 1008 2022/11/02 14:55:34 - mmengine - INFO - Epoch(val) [260][90/500] eta: 0:00:16 time: 0.0413 data_time: 0.0023 memory: 1008 2022/11/02 14:55:34 - mmengine - INFO - Epoch(val) [260][95/500] eta: 0:00:16 time: 0.0445 data_time: 0.0027 memory: 1008 2022/11/02 14:55:34 - mmengine - INFO - Epoch(val) [260][100/500] eta: 0:00:15 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 14:55:34 - mmengine - INFO - Epoch(val) [260][105/500] eta: 0:00:15 time: 0.0369 data_time: 0.0025 memory: 1008 2022/11/02 14:55:35 - mmengine - INFO - Epoch(val) [260][110/500] eta: 0:00:15 time: 0.0385 data_time: 0.0031 memory: 1008 2022/11/02 14:55:35 - mmengine - INFO - Epoch(val) [260][115/500] eta: 0:00:15 time: 0.0388 data_time: 0.0030 memory: 1008 2022/11/02 14:55:35 - mmengine - INFO - Epoch(val) [260][120/500] eta: 0:00:14 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/02 14:55:35 - mmengine - INFO - Epoch(val) [260][125/500] eta: 0:00:14 time: 0.0363 data_time: 0.0025 memory: 1008 2022/11/02 14:55:35 - mmengine - INFO - Epoch(val) [260][130/500] eta: 0:00:13 time: 0.0359 data_time: 0.0024 memory: 1008 2022/11/02 14:55:35 - mmengine - INFO - Epoch(val) [260][135/500] eta: 0:00:13 time: 0.0359 data_time: 0.0023 memory: 1008 2022/11/02 14:55:36 - mmengine - INFO - Epoch(val) [260][140/500] eta: 0:00:12 time: 0.0360 data_time: 0.0022 memory: 1008 2022/11/02 14:55:36 - mmengine - INFO - Epoch(val) [260][145/500] eta: 0:00:12 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/02 14:55:36 - mmengine - INFO - Epoch(val) [260][150/500] eta: 0:00:14 time: 0.0419 data_time: 0.0027 memory: 1008 2022/11/02 14:55:36 - mmengine - INFO - Epoch(val) [260][155/500] eta: 0:00:14 time: 0.0430 data_time: 0.0025 memory: 1008 2022/11/02 14:55:36 - mmengine - INFO - Epoch(val) [260][160/500] eta: 0:00:14 time: 0.0416 data_time: 0.0022 memory: 1008 2022/11/02 14:55:37 - mmengine - INFO - Epoch(val) [260][165/500] eta: 0:00:14 time: 0.0393 data_time: 0.0023 memory: 1008 2022/11/02 14:55:37 - mmengine - INFO - Epoch(val) [260][170/500] eta: 0:00:12 time: 0.0390 data_time: 0.0023 memory: 1008 2022/11/02 14:55:37 - mmengine - INFO - Epoch(val) [260][175/500] eta: 0:00:12 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/02 14:55:37 - mmengine - INFO - Epoch(val) [260][180/500] eta: 0:00:10 time: 0.0343 data_time: 0.0022 memory: 1008 2022/11/02 14:55:37 - mmengine - INFO - Epoch(val) [260][185/500] eta: 0:00:10 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 14:55:38 - mmengine - INFO - Epoch(val) [260][190/500] eta: 0:00:12 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 14:55:38 - mmengine - INFO - Epoch(val) [260][195/500] eta: 0:00:12 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/02 14:55:38 - mmengine - INFO - Epoch(val) [260][200/500] eta: 0:00:13 time: 0.0443 data_time: 0.0026 memory: 1008 2022/11/02 14:55:38 - mmengine - INFO - Epoch(val) [260][205/500] eta: 0:00:13 time: 0.0443 data_time: 0.0026 memory: 1008 2022/11/02 14:55:38 - mmengine - INFO - Epoch(val) [260][210/500] eta: 0:00:10 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 14:55:39 - mmengine - INFO - Epoch(val) [260][215/500] eta: 0:00:10 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 14:55:39 - mmengine - INFO - Epoch(val) [260][220/500] eta: 0:00:11 time: 0.0427 data_time: 0.0030 memory: 1008 2022/11/02 14:55:39 - mmengine - INFO - Epoch(val) [260][225/500] eta: 0:00:11 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 14:55:39 - mmengine - INFO - Epoch(val) [260][230/500] eta: 0:00:10 time: 0.0379 data_time: 0.0025 memory: 1008 2022/11/02 14:55:39 - mmengine - INFO - Epoch(val) [260][235/500] eta: 0:00:10 time: 0.0374 data_time: 0.0024 memory: 1008 2022/11/02 14:55:40 - mmengine - INFO - Epoch(val) [260][240/500] eta: 0:00:10 time: 0.0387 data_time: 0.0024 memory: 1008 2022/11/02 14:55:40 - mmengine - INFO - Epoch(val) [260][245/500] eta: 0:00:10 time: 0.0371 data_time: 0.0023 memory: 1008 2022/11/02 14:55:40 - mmengine - INFO - Epoch(val) [260][250/500] eta: 0:00:09 time: 0.0379 data_time: 0.0024 memory: 1008 2022/11/02 14:55:40 - mmengine - INFO - Epoch(val) [260][255/500] eta: 0:00:09 time: 0.0367 data_time: 0.0024 memory: 1008 2022/11/02 14:55:40 - mmengine - INFO - Epoch(val) [260][260/500] eta: 0:00:08 time: 0.0359 data_time: 0.0023 memory: 1008 2022/11/02 14:55:41 - mmengine - INFO - Epoch(val) [260][265/500] eta: 0:00:08 time: 0.0357 data_time: 0.0022 memory: 1008 2022/11/02 14:55:43 - mmengine - INFO - Epoch(val) [260][270/500] eta: 0:00:49 time: 0.2149 data_time: 0.1781 memory: 1008 2022/11/02 14:55:43 - mmengine - INFO - Epoch(val) [260][275/500] eta: 0:00:49 time: 0.2188 data_time: 0.1781 memory: 1008 2022/11/02 14:55:43 - mmengine - INFO - Epoch(val) [260][280/500] eta: 0:00:09 time: 0.0426 data_time: 0.0026 memory: 1008 2022/11/02 14:55:43 - mmengine - INFO - Epoch(val) [260][285/500] eta: 0:00:09 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/02 14:55:43 - mmengine - INFO - Epoch(val) [260][290/500] eta: 0:00:08 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 14:55:44 - mmengine - INFO - Epoch(val) [260][295/500] eta: 0:00:08 time: 0.0414 data_time: 0.0024 memory: 1008 2022/11/02 14:55:44 - mmengine - INFO - Epoch(val) [260][300/500] eta: 0:00:07 time: 0.0381 data_time: 0.0023 memory: 1008 2022/11/02 14:55:44 - mmengine - INFO - Epoch(val) [260][305/500] eta: 0:00:07 time: 0.0360 data_time: 0.0023 memory: 1008 2022/11/02 14:55:44 - mmengine - INFO - Epoch(val) [260][310/500] eta: 0:00:07 time: 0.0372 data_time: 0.0023 memory: 1008 2022/11/02 14:55:44 - mmengine - INFO - Epoch(val) [260][315/500] eta: 0:00:07 time: 0.0422 data_time: 0.0024 memory: 1008 2022/11/02 14:55:45 - mmengine - INFO - Epoch(val) [260][320/500] eta: 0:00:07 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 14:55:45 - mmengine - INFO - Epoch(val) [260][325/500] eta: 0:00:07 time: 0.0482 data_time: 0.0027 memory: 1008 2022/11/02 14:55:45 - mmengine - INFO - Epoch(val) [260][330/500] eta: 0:00:08 time: 0.0481 data_time: 0.0026 memory: 1008 2022/11/02 14:55:45 - mmengine - INFO - Epoch(val) [260][335/500] eta: 0:00:08 time: 0.0377 data_time: 0.0026 memory: 1008 2022/11/02 14:55:46 - mmengine - INFO - Epoch(val) [260][340/500] eta: 0:00:07 time: 0.0492 data_time: 0.0027 memory: 1008 2022/11/02 14:55:46 - mmengine - INFO - Epoch(val) [260][345/500] eta: 0:00:07 time: 0.0490 data_time: 0.0026 memory: 1008 2022/11/02 14:55:46 - mmengine - INFO - Epoch(val) [260][350/500] eta: 0:00:06 time: 0.0452 data_time: 0.0032 memory: 1008 2022/11/02 14:55:46 - mmengine - INFO - Epoch(val) [260][355/500] eta: 0:00:06 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 14:55:46 - mmengine - INFO - Epoch(val) [260][360/500] eta: 0:00:04 time: 0.0356 data_time: 0.0021 memory: 1008 2022/11/02 14:55:47 - mmengine - INFO - Epoch(val) [260][365/500] eta: 0:00:04 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/02 14:55:47 - mmengine - INFO - Epoch(val) [260][370/500] eta: 0:00:04 time: 0.0374 data_time: 0.0026 memory: 1008 2022/11/02 14:55:47 - mmengine - INFO - Epoch(val) [260][375/500] eta: 0:00:04 time: 0.0346 data_time: 0.0028 memory: 1008 2022/11/02 14:55:47 - mmengine - INFO - Epoch(val) [260][380/500] eta: 0:00:04 time: 0.0391 data_time: 0.0028 memory: 1008 2022/11/02 14:55:47 - mmengine - INFO - Epoch(val) [260][385/500] eta: 0:00:04 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 14:55:47 - mmengine - INFO - Epoch(val) [260][390/500] eta: 0:00:04 time: 0.0367 data_time: 0.0025 memory: 1008 2022/11/02 14:55:48 - mmengine - INFO - Epoch(val) [260][395/500] eta: 0:00:04 time: 0.0371 data_time: 0.0025 memory: 1008 2022/11/02 14:55:48 - mmengine - INFO - Epoch(val) [260][400/500] eta: 0:00:03 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/02 14:55:48 - mmengine - INFO - Epoch(val) [260][405/500] eta: 0:00:03 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 14:55:48 - mmengine - INFO - Epoch(val) [260][410/500] eta: 0:00:03 time: 0.0393 data_time: 0.0026 memory: 1008 2022/11/02 14:55:48 - mmengine - INFO - Epoch(val) [260][415/500] eta: 0:00:03 time: 0.0390 data_time: 0.0029 memory: 1008 2022/11/02 14:55:49 - mmengine - INFO - Epoch(val) [260][420/500] eta: 0:00:03 time: 0.0466 data_time: 0.0142 memory: 1008 2022/11/02 14:55:49 - mmengine - INFO - Epoch(val) [260][425/500] eta: 0:00:03 time: 0.0459 data_time: 0.0136 memory: 1008 2022/11/02 14:55:49 - mmengine - INFO - Epoch(val) [260][430/500] eta: 0:00:02 time: 0.0357 data_time: 0.0020 memory: 1008 2022/11/02 14:55:49 - mmengine - INFO - Epoch(val) [260][435/500] eta: 0:00:02 time: 0.0348 data_time: 0.0022 memory: 1008 2022/11/02 14:55:49 - mmengine - INFO - Epoch(val) [260][440/500] eta: 0:00:02 time: 0.0358 data_time: 0.0021 memory: 1008 2022/11/02 14:55:50 - mmengine - INFO - Epoch(val) [260][445/500] eta: 0:00:02 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/02 14:55:50 - mmengine - INFO - Epoch(val) [260][450/500] eta: 0:00:02 time: 0.0402 data_time: 0.0026 memory: 1008 2022/11/02 14:55:50 - mmengine - INFO - Epoch(val) [260][455/500] eta: 0:00:02 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 14:55:50 - mmengine - INFO - Epoch(val) [260][460/500] eta: 0:00:01 time: 0.0401 data_time: 0.0028 memory: 1008 2022/11/02 14:55:50 - mmengine - INFO - Epoch(val) [260][465/500] eta: 0:00:01 time: 0.0387 data_time: 0.0030 memory: 1008 2022/11/02 14:55:51 - mmengine - INFO - Epoch(val) [260][470/500] eta: 0:00:01 time: 0.0404 data_time: 0.0028 memory: 1008 2022/11/02 14:55:51 - mmengine - INFO - Epoch(val) [260][475/500] eta: 0:00:01 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 14:55:51 - mmengine - INFO - Epoch(val) [260][480/500] eta: 0:00:00 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 14:55:51 - mmengine - INFO - Epoch(val) [260][485/500] eta: 0:00:00 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 14:55:51 - mmengine - INFO - Epoch(val) [260][490/500] eta: 0:00:00 time: 0.0408 data_time: 0.0024 memory: 1008 2022/11/02 14:55:52 - mmengine - INFO - Epoch(val) [260][495/500] eta: 0:00:00 time: 0.0503 data_time: 0.0038 memory: 1008 2022/11/02 14:55:52 - mmengine - INFO - Epoch(val) [260][500/500] eta: 0:00:00 time: 0.0527 data_time: 0.0068 memory: 1008 2022/11/02 14:55:52 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7944, precision: 0.7060, hmean: 0.7476 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7944, precision: 0.7674, hmean: 0.7807 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7896, precision: 0.8147, hmean: 0.8020 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7732, precision: 0.8543, hmean: 0.8117 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7025, precision: 0.8940, hmean: 0.7867 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3115, precision: 0.9529, hmean: 0.4695 2022/11/02 14:55:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0005, precision: 1.0000, hmean: 0.0010 2022/11/02 14:55:52 - mmengine - INFO - Epoch(val) [260][500/500] icdar/precision: 0.8543 icdar/recall: 0.7732 icdar/hmean: 0.8117 2022/11/02 14:55:58 - mmengine - INFO - Epoch(train) [261][5/63] lr: 1.7359e-03 eta: 0:00:00 time: 0.8805 data_time: 0.2805 memory: 14901 loss: 1.6661 loss_prob: 0.9250 loss_thr: 0.5895 loss_db: 0.1517 2022/11/02 14:56:01 - mmengine - INFO - Epoch(train) [261][10/63] lr: 1.7359e-03 eta: 9:39:50 time: 0.9433 data_time: 0.2801 memory: 14901 loss: 1.6444 loss_prob: 0.9290 loss_thr: 0.5625 loss_db: 0.1529 2022/11/02 14:56:04 - mmengine - INFO - Epoch(train) [261][15/63] lr: 1.7359e-03 eta: 9:39:50 time: 0.5784 data_time: 0.0075 memory: 14901 loss: 1.7546 loss_prob: 0.9949 loss_thr: 0.5948 loss_db: 0.1650 2022/11/02 14:56:07 - mmengine - INFO - Epoch(train) [261][20/63] lr: 1.7359e-03 eta: 9:39:42 time: 0.5345 data_time: 0.0071 memory: 14901 loss: 1.7190 loss_prob: 0.9701 loss_thr: 0.5873 loss_db: 0.1616 2022/11/02 14:56:10 - mmengine - INFO - Epoch(train) [261][25/63] lr: 1.7359e-03 eta: 9:39:42 time: 0.5491 data_time: 0.0387 memory: 14901 loss: 1.6336 loss_prob: 0.9110 loss_thr: 0.5732 loss_db: 0.1495 2022/11/02 14:56:12 - mmengine - INFO - Epoch(train) [261][30/63] lr: 1.7359e-03 eta: 9:39:34 time: 0.5370 data_time: 0.0375 memory: 14901 loss: 1.7155 loss_prob: 0.9737 loss_thr: 0.5816 loss_db: 0.1601 2022/11/02 14:56:15 - mmengine - INFO - Epoch(train) [261][35/63] lr: 1.7359e-03 eta: 9:39:34 time: 0.4929 data_time: 0.0130 memory: 14901 loss: 1.7029 loss_prob: 0.9643 loss_thr: 0.5788 loss_db: 0.1598 2022/11/02 14:56:17 - mmengine - INFO - Epoch(train) [261][40/63] lr: 1.7359e-03 eta: 9:39:26 time: 0.5234 data_time: 0.0140 memory: 14901 loss: 1.8069 loss_prob: 1.0490 loss_thr: 0.5879 loss_db: 0.1701 2022/11/02 14:56:20 - mmengine - INFO - Epoch(train) [261][45/63] lr: 1.7359e-03 eta: 9:39:26 time: 0.5314 data_time: 0.0074 memory: 14901 loss: 1.9658 loss_prob: 1.1758 loss_thr: 0.6010 loss_db: 0.1890 2022/11/02 14:56:23 - mmengine - INFO - Epoch(train) [261][50/63] lr: 1.7359e-03 eta: 9:39:19 time: 0.5644 data_time: 0.0222 memory: 14901 loss: 1.9882 loss_prob: 1.1735 loss_thr: 0.6206 loss_db: 0.1942 2022/11/02 14:56:26 - mmengine - INFO - Epoch(train) [261][55/63] lr: 1.7359e-03 eta: 9:39:19 time: 0.5601 data_time: 0.0245 memory: 14901 loss: 1.8899 loss_prob: 1.0966 loss_thr: 0.6097 loss_db: 0.1836 2022/11/02 14:56:29 - mmengine - INFO - Epoch(train) [261][60/63] lr: 1.7359e-03 eta: 9:39:12 time: 0.5516 data_time: 0.0124 memory: 14901 loss: 1.8495 loss_prob: 1.0760 loss_thr: 0.5957 loss_db: 0.1777 2022/11/02 14:56:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:56:35 - mmengine - INFO - Epoch(train) [262][5/63] lr: 1.7343e-03 eta: 9:39:12 time: 0.7702 data_time: 0.2134 memory: 14901 loss: 1.9717 loss_prob: 1.1597 loss_thr: 0.6218 loss_db: 0.1902 2022/11/02 14:56:38 - mmengine - INFO - Epoch(train) [262][10/63] lr: 1.7343e-03 eta: 9:39:07 time: 0.8404 data_time: 0.2218 memory: 14901 loss: 1.8745 loss_prob: 1.0891 loss_thr: 0.6057 loss_db: 0.1797 2022/11/02 14:56:41 - mmengine - INFO - Epoch(train) [262][15/63] lr: 1.7343e-03 eta: 9:39:07 time: 0.5698 data_time: 0.0166 memory: 14901 loss: 1.7135 loss_prob: 0.9896 loss_thr: 0.5613 loss_db: 0.1627 2022/11/02 14:56:43 - mmengine - INFO - Epoch(train) [262][20/63] lr: 1.7343e-03 eta: 9:38:59 time: 0.5125 data_time: 0.0123 memory: 14901 loss: 1.6974 loss_prob: 0.9814 loss_thr: 0.5541 loss_db: 0.1619 2022/11/02 14:56:46 - mmengine - INFO - Epoch(train) [262][25/63] lr: 1.7343e-03 eta: 9:38:59 time: 0.5320 data_time: 0.0410 memory: 14901 loss: 1.9283 loss_prob: 1.1303 loss_thr: 0.6118 loss_db: 0.1862 2022/11/02 14:56:49 - mmengine - INFO - Epoch(train) [262][30/63] lr: 1.7343e-03 eta: 9:38:51 time: 0.5319 data_time: 0.0448 memory: 14901 loss: 1.9597 loss_prob: 1.1497 loss_thr: 0.6182 loss_db: 0.1919 2022/11/02 14:56:51 - mmengine - INFO - Epoch(train) [262][35/63] lr: 1.7343e-03 eta: 9:38:51 time: 0.5304 data_time: 0.0178 memory: 14901 loss: 1.6832 loss_prob: 0.9499 loss_thr: 0.5732 loss_db: 0.1600 2022/11/02 14:56:54 - mmengine - INFO - Epoch(train) [262][40/63] lr: 1.7343e-03 eta: 9:38:43 time: 0.5441 data_time: 0.0087 memory: 14901 loss: 1.6597 loss_prob: 0.9236 loss_thr: 0.5836 loss_db: 0.1525 2022/11/02 14:56:56 - mmengine - INFO - Epoch(train) [262][45/63] lr: 1.7343e-03 eta: 9:38:43 time: 0.5077 data_time: 0.0078 memory: 14901 loss: 1.7198 loss_prob: 0.9757 loss_thr: 0.5806 loss_db: 0.1635 2022/11/02 14:56:59 - mmengine - INFO - Epoch(train) [262][50/63] lr: 1.7343e-03 eta: 9:38:34 time: 0.4831 data_time: 0.0226 memory: 14901 loss: 1.6600 loss_prob: 0.9351 loss_thr: 0.5694 loss_db: 0.1556 2022/11/02 14:57:01 - mmengine - INFO - Epoch(train) [262][55/63] lr: 1.7343e-03 eta: 9:38:34 time: 0.4848 data_time: 0.0211 memory: 14901 loss: 1.7759 loss_prob: 1.0191 loss_thr: 0.5937 loss_db: 0.1632 2022/11/02 14:57:04 - mmengine - INFO - Epoch(train) [262][60/63] lr: 1.7343e-03 eta: 9:38:25 time: 0.5056 data_time: 0.0098 memory: 14901 loss: 1.8574 loss_prob: 1.0831 loss_thr: 0.5968 loss_db: 0.1775 2022/11/02 14:57:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:57:11 - mmengine - INFO - Epoch(train) [263][5/63] lr: 1.7326e-03 eta: 9:38:25 time: 0.7998 data_time: 0.2200 memory: 14901 loss: 2.0703 loss_prob: 1.2668 loss_thr: 0.6035 loss_db: 0.2000 2022/11/02 14:57:14 - mmengine - INFO - Epoch(train) [263][10/63] lr: 1.7326e-03 eta: 9:38:21 time: 0.8522 data_time: 0.2213 memory: 14901 loss: 2.1488 loss_prob: 1.3320 loss_thr: 0.6059 loss_db: 0.2109 2022/11/02 14:57:16 - mmengine - INFO - Epoch(train) [263][15/63] lr: 1.7326e-03 eta: 9:38:21 time: 0.5270 data_time: 0.0111 memory: 14901 loss: 1.8649 loss_prob: 1.1044 loss_thr: 0.5811 loss_db: 0.1795 2022/11/02 14:57:19 - mmengine - INFO - Epoch(train) [263][20/63] lr: 1.7326e-03 eta: 9:38:15 time: 0.5836 data_time: 0.0104 memory: 14901 loss: 1.8408 loss_prob: 1.0696 loss_thr: 0.5968 loss_db: 0.1743 2022/11/02 14:57:22 - mmengine - INFO - Epoch(train) [263][25/63] lr: 1.7326e-03 eta: 9:38:15 time: 0.5958 data_time: 0.0215 memory: 14901 loss: 1.7762 loss_prob: 1.0219 loss_thr: 0.5857 loss_db: 0.1685 2022/11/02 14:57:25 - mmengine - INFO - Epoch(train) [263][30/63] lr: 1.7326e-03 eta: 9:38:07 time: 0.5496 data_time: 0.0410 memory: 14901 loss: 1.7595 loss_prob: 1.0115 loss_thr: 0.5784 loss_db: 0.1696 2022/11/02 14:57:27 - mmengine - INFO - Epoch(train) [263][35/63] lr: 1.7326e-03 eta: 9:38:07 time: 0.5398 data_time: 0.0252 memory: 14901 loss: 1.8657 loss_prob: 1.0874 loss_thr: 0.5987 loss_db: 0.1795 2022/11/02 14:57:30 - mmengine - INFO - Epoch(train) [263][40/63] lr: 1.7326e-03 eta: 9:37:59 time: 0.5169 data_time: 0.0086 memory: 14901 loss: 1.8775 loss_prob: 1.1047 loss_thr: 0.5903 loss_db: 0.1824 2022/11/02 14:57:32 - mmengine - INFO - Epoch(train) [263][45/63] lr: 1.7326e-03 eta: 9:37:59 time: 0.5014 data_time: 0.0094 memory: 14901 loss: 1.8440 loss_prob: 1.0772 loss_thr: 0.5839 loss_db: 0.1830 2022/11/02 14:57:35 - mmengine - INFO - Epoch(train) [263][50/63] lr: 1.7326e-03 eta: 9:37:49 time: 0.4857 data_time: 0.0152 memory: 14901 loss: 1.8481 loss_prob: 1.0805 loss_thr: 0.5860 loss_db: 0.1815 2022/11/02 14:57:38 - mmengine - INFO - Epoch(train) [263][55/63] lr: 1.7326e-03 eta: 9:37:49 time: 0.5286 data_time: 0.0286 memory: 14901 loss: 2.2238 loss_prob: 1.3725 loss_thr: 0.6340 loss_db: 0.2173 2022/11/02 14:57:40 - mmengine - INFO - Epoch(train) [263][60/63] lr: 1.7326e-03 eta: 9:37:42 time: 0.5447 data_time: 0.0221 memory: 14901 loss: 2.2439 loss_prob: 1.3782 loss_thr: 0.6466 loss_db: 0.2191 2022/11/02 14:57:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:57:47 - mmengine - INFO - Epoch(train) [264][5/63] lr: 1.7309e-03 eta: 9:37:42 time: 0.7635 data_time: 0.2226 memory: 14901 loss: 2.1417 loss_prob: 1.3347 loss_thr: 0.5913 loss_db: 0.2157 2022/11/02 14:57:50 - mmengine - INFO - Epoch(train) [264][10/63] lr: 1.7309e-03 eta: 9:37:36 time: 0.8117 data_time: 0.2257 memory: 14901 loss: 2.2736 loss_prob: 1.4442 loss_thr: 0.6035 loss_db: 0.2259 2022/11/02 14:57:53 - mmengine - INFO - Epoch(train) [264][15/63] lr: 1.7309e-03 eta: 9:37:36 time: 0.5666 data_time: 0.0231 memory: 14901 loss: 2.1549 loss_prob: 1.3236 loss_thr: 0.6192 loss_db: 0.2121 2022/11/02 14:57:55 - mmengine - INFO - Epoch(train) [264][20/63] lr: 1.7309e-03 eta: 9:37:28 time: 0.5225 data_time: 0.0178 memory: 14901 loss: 2.0988 loss_prob: 1.2518 loss_thr: 0.6436 loss_db: 0.2034 2022/11/02 14:57:58 - mmengine - INFO - Epoch(train) [264][25/63] lr: 1.7309e-03 eta: 9:37:28 time: 0.4983 data_time: 0.0092 memory: 14901 loss: 2.0805 loss_prob: 1.2324 loss_thr: 0.6442 loss_db: 0.2039 2022/11/02 14:58:01 - mmengine - INFO - Epoch(train) [264][30/63] lr: 1.7309e-03 eta: 9:37:23 time: 0.6065 data_time: 0.0398 memory: 14901 loss: 2.0742 loss_prob: 1.2493 loss_thr: 0.6111 loss_db: 0.2138 2022/11/02 14:58:03 - mmengine - INFO - Epoch(train) [264][35/63] lr: 1.7309e-03 eta: 9:37:23 time: 0.5650 data_time: 0.0357 memory: 14901 loss: 2.0607 loss_prob: 1.2318 loss_thr: 0.6264 loss_db: 0.2024 2022/11/02 14:58:06 - mmengine - INFO - Epoch(train) [264][40/63] lr: 1.7309e-03 eta: 9:37:13 time: 0.4888 data_time: 0.0066 memory: 14901 loss: 2.0422 loss_prob: 1.2001 loss_thr: 0.6495 loss_db: 0.1926 2022/11/02 14:58:09 - mmengine - INFO - Epoch(train) [264][45/63] lr: 1.7309e-03 eta: 9:37:13 time: 0.5550 data_time: 0.0116 memory: 14901 loss: 2.0625 loss_prob: 1.2115 loss_thr: 0.6514 loss_db: 0.1996 2022/11/02 14:58:11 - mmengine - INFO - Epoch(train) [264][50/63] lr: 1.7309e-03 eta: 9:37:06 time: 0.5376 data_time: 0.0174 memory: 14901 loss: 1.8534 loss_prob: 1.0668 loss_thr: 0.6121 loss_db: 0.1745 2022/11/02 14:58:14 - mmengine - INFO - Epoch(train) [264][55/63] lr: 1.7309e-03 eta: 9:37:06 time: 0.5015 data_time: 0.0250 memory: 14901 loss: 1.7401 loss_prob: 1.0158 loss_thr: 0.5657 loss_db: 0.1587 2022/11/02 14:58:16 - mmengine - INFO - Epoch(train) [264][60/63] lr: 1.7309e-03 eta: 9:36:57 time: 0.4964 data_time: 0.0207 memory: 14901 loss: 1.8129 loss_prob: 1.0608 loss_thr: 0.5830 loss_db: 0.1692 2022/11/02 14:58:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:58:22 - mmengine - INFO - Epoch(train) [265][5/63] lr: 1.7293e-03 eta: 9:36:57 time: 0.7189 data_time: 0.2218 memory: 14901 loss: 1.8364 loss_prob: 1.0455 loss_thr: 0.6168 loss_db: 0.1742 2022/11/02 14:58:26 - mmengine - INFO - Epoch(train) [265][10/63] lr: 1.7293e-03 eta: 9:36:51 time: 0.8091 data_time: 0.2241 memory: 14901 loss: 1.8431 loss_prob: 1.0539 loss_thr: 0.6178 loss_db: 0.1714 2022/11/02 14:58:28 - mmengine - INFO - Epoch(train) [265][15/63] lr: 1.7293e-03 eta: 9:36:51 time: 0.5572 data_time: 0.0085 memory: 14901 loss: 1.9801 loss_prob: 1.1548 loss_thr: 0.6370 loss_db: 0.1884 2022/11/02 14:58:31 - mmengine - INFO - Epoch(train) [265][20/63] lr: 1.7293e-03 eta: 9:36:42 time: 0.5105 data_time: 0.0070 memory: 14901 loss: 1.9532 loss_prob: 1.1297 loss_thr: 0.6315 loss_db: 0.1921 2022/11/02 14:58:34 - mmengine - INFO - Epoch(train) [265][25/63] lr: 1.7293e-03 eta: 9:36:42 time: 0.5823 data_time: 0.0424 memory: 14901 loss: 1.8060 loss_prob: 1.0296 loss_thr: 0.6040 loss_db: 0.1724 2022/11/02 14:58:37 - mmengine - INFO - Epoch(train) [265][30/63] lr: 1.7293e-03 eta: 9:36:36 time: 0.5846 data_time: 0.0401 memory: 14901 loss: 1.7771 loss_prob: 1.0219 loss_thr: 0.5912 loss_db: 0.1640 2022/11/02 14:58:39 - mmengine - INFO - Epoch(train) [265][35/63] lr: 1.7293e-03 eta: 9:36:36 time: 0.5023 data_time: 0.0069 memory: 14901 loss: 1.7615 loss_prob: 1.0177 loss_thr: 0.5790 loss_db: 0.1649 2022/11/02 14:58:42 - mmengine - INFO - Epoch(train) [265][40/63] lr: 1.7293e-03 eta: 9:36:30 time: 0.5894 data_time: 0.0072 memory: 14901 loss: 1.6735 loss_prob: 0.9598 loss_thr: 0.5567 loss_db: 0.1570 2022/11/02 14:58:45 - mmengine - INFO - Epoch(train) [265][45/63] lr: 1.7293e-03 eta: 9:36:30 time: 0.6329 data_time: 0.0123 memory: 14901 loss: 1.7468 loss_prob: 1.0068 loss_thr: 0.5719 loss_db: 0.1681 2022/11/02 14:58:48 - mmengine - INFO - Epoch(train) [265][50/63] lr: 1.7293e-03 eta: 9:36:23 time: 0.5462 data_time: 0.0316 memory: 14901 loss: 1.8120 loss_prob: 1.0572 loss_thr: 0.5793 loss_db: 0.1755 2022/11/02 14:58:51 - mmengine - INFO - Epoch(train) [265][55/63] lr: 1.7293e-03 eta: 9:36:23 time: 0.5675 data_time: 0.0243 memory: 14901 loss: 1.8733 loss_prob: 1.0855 loss_thr: 0.6108 loss_db: 0.1770 2022/11/02 14:58:54 - mmengine - INFO - Epoch(train) [265][60/63] lr: 1.7293e-03 eta: 9:36:18 time: 0.6104 data_time: 0.0087 memory: 14901 loss: 1.9693 loss_prob: 1.1417 loss_thr: 0.6397 loss_db: 0.1879 2022/11/02 14:58:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:59:00 - mmengine - INFO - Epoch(train) [266][5/63] lr: 1.7276e-03 eta: 9:36:18 time: 0.7378 data_time: 0.2060 memory: 14901 loss: 1.8660 loss_prob: 1.0859 loss_thr: 0.6012 loss_db: 0.1789 2022/11/02 14:59:04 - mmengine - INFO - Epoch(train) [266][10/63] lr: 1.7276e-03 eta: 9:36:13 time: 0.8491 data_time: 0.2489 memory: 14901 loss: 1.7465 loss_prob: 1.0093 loss_thr: 0.5709 loss_db: 0.1663 2022/11/02 14:59:07 - mmengine - INFO - Epoch(train) [266][15/63] lr: 1.7276e-03 eta: 9:36:13 time: 0.6317 data_time: 0.0483 memory: 14901 loss: 1.7782 loss_prob: 1.0256 loss_thr: 0.5844 loss_db: 0.1682 2022/11/02 14:59:09 - mmengine - INFO - Epoch(train) [266][20/63] lr: 1.7276e-03 eta: 9:36:07 time: 0.5809 data_time: 0.0082 memory: 14901 loss: 1.8736 loss_prob: 1.0998 loss_thr: 0.5905 loss_db: 0.1833 2022/11/02 14:59:12 - mmengine - INFO - Epoch(train) [266][25/63] lr: 1.7276e-03 eta: 9:36:07 time: 0.5511 data_time: 0.0094 memory: 14901 loss: 1.8195 loss_prob: 1.0569 loss_thr: 0.5888 loss_db: 0.1738 2022/11/02 14:59:15 - mmengine - INFO - Epoch(train) [266][30/63] lr: 1.7276e-03 eta: 9:36:00 time: 0.5505 data_time: 0.0148 memory: 14901 loss: 1.7883 loss_prob: 1.0246 loss_thr: 0.6006 loss_db: 0.1632 2022/11/02 14:59:17 - mmengine - INFO - Epoch(train) [266][35/63] lr: 1.7276e-03 eta: 9:36:00 time: 0.5149 data_time: 0.0132 memory: 14901 loss: 1.9401 loss_prob: 1.1411 loss_thr: 0.6160 loss_db: 0.1829 2022/11/02 14:59:20 - mmengine - INFO - Epoch(train) [266][40/63] lr: 1.7276e-03 eta: 9:35:50 time: 0.4765 data_time: 0.0047 memory: 14901 loss: 1.8399 loss_prob: 1.0709 loss_thr: 0.5929 loss_db: 0.1762 2022/11/02 14:59:23 - mmengine - INFO - Epoch(train) [266][45/63] lr: 1.7276e-03 eta: 9:35:50 time: 0.5116 data_time: 0.0070 memory: 14901 loss: 1.6636 loss_prob: 0.9487 loss_thr: 0.5585 loss_db: 0.1565 2022/11/02 14:59:26 - mmengine - INFO - Epoch(train) [266][50/63] lr: 1.7276e-03 eta: 9:35:47 time: 0.6561 data_time: 0.0102 memory: 14901 loss: 1.7045 loss_prob: 0.9745 loss_thr: 0.5691 loss_db: 0.1609 2022/11/02 14:59:29 - mmengine - INFO - Epoch(train) [266][55/63] lr: 1.7276e-03 eta: 9:35:47 time: 0.6551 data_time: 0.0403 memory: 14901 loss: 1.7699 loss_prob: 1.0023 loss_thr: 0.5964 loss_db: 0.1712 2022/11/02 14:59:32 - mmengine - INFO - Epoch(train) [266][60/63] lr: 1.7276e-03 eta: 9:35:41 time: 0.5704 data_time: 0.0396 memory: 14901 loss: 1.7287 loss_prob: 0.9752 loss_thr: 0.5880 loss_db: 0.1655 2022/11/02 14:59:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 14:59:40 - mmengine - INFO - Epoch(train) [267][5/63] lr: 1.7260e-03 eta: 9:35:41 time: 0.9102 data_time: 0.2647 memory: 14901 loss: 1.6662 loss_prob: 0.9547 loss_thr: 0.5532 loss_db: 0.1583 2022/11/02 14:59:43 - mmengine - INFO - Epoch(train) [267][10/63] lr: 1.7260e-03 eta: 9:35:37 time: 0.8730 data_time: 0.2669 memory: 14901 loss: 1.6613 loss_prob: 0.9423 loss_thr: 0.5618 loss_db: 0.1571 2022/11/02 14:59:46 - mmengine - INFO - Epoch(train) [267][15/63] lr: 1.7260e-03 eta: 9:35:37 time: 0.5668 data_time: 0.0081 memory: 14901 loss: 1.6973 loss_prob: 0.9605 loss_thr: 0.5795 loss_db: 0.1574 2022/11/02 14:59:49 - mmengine - INFO - Epoch(train) [267][20/63] lr: 1.7260e-03 eta: 9:35:31 time: 0.5946 data_time: 0.0076 memory: 14901 loss: 1.7317 loss_prob: 1.0036 loss_thr: 0.5707 loss_db: 0.1573 2022/11/02 14:59:51 - mmengine - INFO - Epoch(train) [267][25/63] lr: 1.7260e-03 eta: 9:35:31 time: 0.5544 data_time: 0.0318 memory: 14901 loss: 1.6513 loss_prob: 0.9518 loss_thr: 0.5483 loss_db: 0.1512 2022/11/02 14:59:54 - mmengine - INFO - Epoch(train) [267][30/63] lr: 1.7260e-03 eta: 9:35:24 time: 0.5443 data_time: 0.0473 memory: 14901 loss: 1.6192 loss_prob: 0.9171 loss_thr: 0.5504 loss_db: 0.1517 2022/11/02 14:59:57 - mmengine - INFO - Epoch(train) [267][35/63] lr: 1.7260e-03 eta: 9:35:24 time: 0.5254 data_time: 0.0272 memory: 14901 loss: 1.6262 loss_prob: 0.9277 loss_thr: 0.5487 loss_db: 0.1497 2022/11/02 14:59:59 - mmengine - INFO - Epoch(train) [267][40/63] lr: 1.7260e-03 eta: 9:35:16 time: 0.5277 data_time: 0.0128 memory: 14901 loss: 1.7362 loss_prob: 1.0075 loss_thr: 0.5720 loss_db: 0.1567 2022/11/02 15:00:02 - mmengine - INFO - Epoch(train) [267][45/63] lr: 1.7260e-03 eta: 9:35:16 time: 0.5092 data_time: 0.0085 memory: 14901 loss: 1.8296 loss_prob: 1.0580 loss_thr: 0.6033 loss_db: 0.1683 2022/11/02 15:00:04 - mmengine - INFO - Epoch(train) [267][50/63] lr: 1.7260e-03 eta: 9:35:08 time: 0.5195 data_time: 0.0211 memory: 14901 loss: 1.7028 loss_prob: 0.9651 loss_thr: 0.5775 loss_db: 0.1601 2022/11/02 15:00:07 - mmengine - INFO - Epoch(train) [267][55/63] lr: 1.7260e-03 eta: 9:35:08 time: 0.5403 data_time: 0.0243 memory: 14901 loss: 1.7090 loss_prob: 0.9712 loss_thr: 0.5794 loss_db: 0.1585 2022/11/02 15:00:11 - mmengine - INFO - Epoch(train) [267][60/63] lr: 1.7260e-03 eta: 9:35:02 time: 0.6068 data_time: 0.0094 memory: 14901 loss: 1.6803 loss_prob: 0.9503 loss_thr: 0.5727 loss_db: 0.1573 2022/11/02 15:00:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:00:18 - mmengine - INFO - Epoch(train) [268][5/63] lr: 1.7243e-03 eta: 9:35:02 time: 0.8875 data_time: 0.2427 memory: 14901 loss: 1.6962 loss_prob: 0.9635 loss_thr: 0.5750 loss_db: 0.1578 2022/11/02 15:00:21 - mmengine - INFO - Epoch(train) [268][10/63] lr: 1.7243e-03 eta: 9:35:00 time: 0.9089 data_time: 0.2443 memory: 14901 loss: 1.7937 loss_prob: 1.0541 loss_thr: 0.5712 loss_db: 0.1683 2022/11/02 15:00:24 - mmengine - INFO - Epoch(train) [268][15/63] lr: 1.7243e-03 eta: 9:35:00 time: 0.5706 data_time: 0.0157 memory: 14901 loss: 1.6738 loss_prob: 0.9690 loss_thr: 0.5495 loss_db: 0.1553 2022/11/02 15:00:26 - mmengine - INFO - Epoch(train) [268][20/63] lr: 1.7243e-03 eta: 9:34:52 time: 0.5332 data_time: 0.0165 memory: 14901 loss: 1.5459 loss_prob: 0.8515 loss_thr: 0.5547 loss_db: 0.1396 2022/11/02 15:00:29 - mmengine - INFO - Epoch(train) [268][25/63] lr: 1.7243e-03 eta: 9:34:52 time: 0.5262 data_time: 0.0378 memory: 14901 loss: 1.6401 loss_prob: 0.9170 loss_thr: 0.5694 loss_db: 0.1536 2022/11/02 15:00:32 - mmengine - INFO - Epoch(train) [268][30/63] lr: 1.7243e-03 eta: 9:34:45 time: 0.5602 data_time: 0.0394 memory: 14901 loss: 1.7061 loss_prob: 0.9703 loss_thr: 0.5703 loss_db: 0.1655 2022/11/02 15:00:34 - mmengine - INFO - Epoch(train) [268][35/63] lr: 1.7243e-03 eta: 9:34:45 time: 0.5422 data_time: 0.0147 memory: 14901 loss: 1.6856 loss_prob: 0.9610 loss_thr: 0.5644 loss_db: 0.1603 2022/11/02 15:00:37 - mmengine - INFO - Epoch(train) [268][40/63] lr: 1.7243e-03 eta: 9:34:37 time: 0.5194 data_time: 0.0097 memory: 14901 loss: 1.7272 loss_prob: 0.9882 loss_thr: 0.5779 loss_db: 0.1611 2022/11/02 15:00:40 - mmengine - INFO - Epoch(train) [268][45/63] lr: 1.7243e-03 eta: 9:34:37 time: 0.5220 data_time: 0.0071 memory: 14901 loss: 1.8897 loss_prob: 1.1032 loss_thr: 0.6063 loss_db: 0.1802 2022/11/02 15:00:42 - mmengine - INFO - Epoch(train) [268][50/63] lr: 1.7243e-03 eta: 9:34:29 time: 0.5340 data_time: 0.0233 memory: 14901 loss: 1.8691 loss_prob: 1.0881 loss_thr: 0.6034 loss_db: 0.1777 2022/11/02 15:00:45 - mmengine - INFO - Epoch(train) [268][55/63] lr: 1.7243e-03 eta: 9:34:29 time: 0.5450 data_time: 0.0233 memory: 14901 loss: 1.8590 loss_prob: 1.0763 loss_thr: 0.6105 loss_db: 0.1722 2022/11/02 15:00:48 - mmengine - INFO - Epoch(train) [268][60/63] lr: 1.7243e-03 eta: 9:34:23 time: 0.5777 data_time: 0.0073 memory: 14901 loss: 2.0516 loss_prob: 1.2175 loss_thr: 0.6485 loss_db: 0.1856 2022/11/02 15:00:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:00:57 - mmengine - INFO - Epoch(train) [269][5/63] lr: 1.7226e-03 eta: 9:34:23 time: 1.0106 data_time: 0.2327 memory: 14901 loss: 2.2933 loss_prob: 1.4136 loss_thr: 0.6575 loss_db: 0.2223 2022/11/02 15:01:00 - mmengine - INFO - Epoch(train) [269][10/63] lr: 1.7226e-03 eta: 9:34:25 time: 1.0281 data_time: 0.2353 memory: 14901 loss: 2.3880 loss_prob: 1.5283 loss_thr: 0.6275 loss_db: 0.2322 2022/11/02 15:01:03 - mmengine - INFO - Epoch(train) [269][15/63] lr: 1.7226e-03 eta: 9:34:25 time: 0.5875 data_time: 0.0113 memory: 14901 loss: 1.9502 loss_prob: 1.1537 loss_thr: 0.6097 loss_db: 0.1867 2022/11/02 15:01:05 - mmengine - INFO - Epoch(train) [269][20/63] lr: 1.7226e-03 eta: 9:34:17 time: 0.5431 data_time: 0.0067 memory: 14901 loss: 1.8227 loss_prob: 1.0387 loss_thr: 0.6074 loss_db: 0.1767 2022/11/02 15:01:09 - mmengine - INFO - Epoch(train) [269][25/63] lr: 1.7226e-03 eta: 9:34:17 time: 0.6282 data_time: 0.0166 memory: 14901 loss: 1.8221 loss_prob: 1.0427 loss_thr: 0.6077 loss_db: 0.1718 2022/11/02 15:01:12 - mmengine - INFO - Epoch(train) [269][30/63] lr: 1.7226e-03 eta: 9:34:14 time: 0.6546 data_time: 0.0403 memory: 14901 loss: 1.8151 loss_prob: 1.0386 loss_thr: 0.6055 loss_db: 0.1710 2022/11/02 15:01:15 - mmengine - INFO - Epoch(train) [269][35/63] lr: 1.7226e-03 eta: 9:34:14 time: 0.5431 data_time: 0.0341 memory: 14901 loss: 1.7477 loss_prob: 0.9951 loss_thr: 0.5897 loss_db: 0.1628 2022/11/02 15:01:17 - mmengine - INFO - Epoch(train) [269][40/63] lr: 1.7226e-03 eta: 9:34:05 time: 0.5119 data_time: 0.0104 memory: 14901 loss: 1.7112 loss_prob: 0.9676 loss_thr: 0.5853 loss_db: 0.1583 2022/11/02 15:01:20 - mmengine - INFO - Epoch(train) [269][45/63] lr: 1.7226e-03 eta: 9:34:05 time: 0.5089 data_time: 0.0085 memory: 14901 loss: 1.8544 loss_prob: 1.0625 loss_thr: 0.6107 loss_db: 0.1812 2022/11/02 15:01:23 - mmengine - INFO - Epoch(train) [269][50/63] lr: 1.7226e-03 eta: 9:33:59 time: 0.5652 data_time: 0.0215 memory: 14901 loss: 1.8641 loss_prob: 1.0684 loss_thr: 0.6130 loss_db: 0.1828 2022/11/02 15:01:26 - mmengine - INFO - Epoch(train) [269][55/63] lr: 1.7226e-03 eta: 9:33:59 time: 0.5963 data_time: 0.0292 memory: 14901 loss: 1.7767 loss_prob: 1.0170 loss_thr: 0.5923 loss_db: 0.1674 2022/11/02 15:01:28 - mmengine - INFO - Epoch(train) [269][60/63] lr: 1.7226e-03 eta: 9:33:52 time: 0.5512 data_time: 0.0185 memory: 14901 loss: 1.7130 loss_prob: 0.9822 loss_thr: 0.5734 loss_db: 0.1574 2022/11/02 15:01:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:01:35 - mmengine - INFO - Epoch(train) [270][5/63] lr: 1.7210e-03 eta: 9:33:52 time: 0.7795 data_time: 0.2246 memory: 14901 loss: 1.7969 loss_prob: 1.0346 loss_thr: 0.5918 loss_db: 0.1704 2022/11/02 15:01:38 - mmengine - INFO - Epoch(train) [270][10/63] lr: 1.7210e-03 eta: 9:33:46 time: 0.8116 data_time: 0.2286 memory: 14901 loss: 1.8053 loss_prob: 1.0355 loss_thr: 0.5980 loss_db: 0.1719 2022/11/02 15:01:41 - mmengine - INFO - Epoch(train) [270][15/63] lr: 1.7210e-03 eta: 9:33:46 time: 0.5766 data_time: 0.0190 memory: 14901 loss: 1.7070 loss_prob: 0.9716 loss_thr: 0.5766 loss_db: 0.1588 2022/11/02 15:01:44 - mmengine - INFO - Epoch(train) [270][20/63] lr: 1.7210e-03 eta: 9:33:40 time: 0.5952 data_time: 0.0216 memory: 14901 loss: 1.7906 loss_prob: 1.0255 loss_thr: 0.5955 loss_db: 0.1696 2022/11/02 15:01:47 - mmengine - INFO - Epoch(train) [270][25/63] lr: 1.7210e-03 eta: 9:33:40 time: 0.6537 data_time: 0.0379 memory: 14901 loss: 1.9341 loss_prob: 1.1281 loss_thr: 0.6151 loss_db: 0.1908 2022/11/02 15:01:50 - mmengine - INFO - Epoch(train) [270][30/63] lr: 1.7210e-03 eta: 9:33:35 time: 0.6231 data_time: 0.0340 memory: 14901 loss: 1.6493 loss_prob: 0.9341 loss_thr: 0.5576 loss_db: 0.1575 2022/11/02 15:01:53 - mmengine - INFO - Epoch(train) [270][35/63] lr: 1.7210e-03 eta: 9:33:35 time: 0.5360 data_time: 0.0085 memory: 14901 loss: 1.5976 loss_prob: 0.8926 loss_thr: 0.5604 loss_db: 0.1447 2022/11/02 15:01:56 - mmengine - INFO - Epoch(train) [270][40/63] lr: 1.7210e-03 eta: 9:33:29 time: 0.5655 data_time: 0.0130 memory: 14901 loss: 1.7054 loss_prob: 0.9725 loss_thr: 0.5745 loss_db: 0.1584 2022/11/02 15:01:59 - mmengine - INFO - Epoch(train) [270][45/63] lr: 1.7210e-03 eta: 9:33:29 time: 0.5807 data_time: 0.0130 memory: 14901 loss: 1.7565 loss_prob: 1.0090 loss_thr: 0.5809 loss_db: 0.1666 2022/11/02 15:02:02 - mmengine - INFO - Epoch(train) [270][50/63] lr: 1.7210e-03 eta: 9:33:23 time: 0.5996 data_time: 0.0211 memory: 14901 loss: 1.7902 loss_prob: 1.0194 loss_thr: 0.6044 loss_db: 0.1663 2022/11/02 15:02:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:02:04 - mmengine - INFO - Epoch(train) [270][55/63] lr: 1.7210e-03 eta: 9:33:23 time: 0.5771 data_time: 0.0218 memory: 14901 loss: 1.6850 loss_prob: 0.9400 loss_thr: 0.5888 loss_db: 0.1561 2022/11/02 15:02:08 - mmengine - INFO - Epoch(train) [270][60/63] lr: 1.7210e-03 eta: 9:33:18 time: 0.6019 data_time: 0.0066 memory: 14901 loss: 1.7014 loss_prob: 0.9636 loss_thr: 0.5756 loss_db: 0.1622 2022/11/02 15:02:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:02:15 - mmengine - INFO - Epoch(train) [271][5/63] lr: 1.7193e-03 eta: 9:33:18 time: 0.8205 data_time: 0.2280 memory: 14901 loss: 2.0443 loss_prob: 1.2355 loss_thr: 0.6128 loss_db: 0.1960 2022/11/02 15:02:18 - mmengine - INFO - Epoch(train) [271][10/63] lr: 1.7193e-03 eta: 9:33:13 time: 0.8357 data_time: 0.2335 memory: 14901 loss: 2.0345 loss_prob: 1.2272 loss_thr: 0.6184 loss_db: 0.1889 2022/11/02 15:02:20 - mmengine - INFO - Epoch(train) [271][15/63] lr: 1.7193e-03 eta: 9:33:13 time: 0.5595 data_time: 0.0159 memory: 14901 loss: 1.7100 loss_prob: 0.9703 loss_thr: 0.5818 loss_db: 0.1578 2022/11/02 15:02:23 - mmengine - INFO - Epoch(train) [271][20/63] lr: 1.7193e-03 eta: 9:33:06 time: 0.5425 data_time: 0.0070 memory: 14901 loss: 1.7526 loss_prob: 0.9854 loss_thr: 0.6028 loss_db: 0.1644 2022/11/02 15:02:27 - mmengine - INFO - Epoch(train) [271][25/63] lr: 1.7193e-03 eta: 9:33:06 time: 0.6691 data_time: 0.0291 memory: 14901 loss: 1.7336 loss_prob: 0.9737 loss_thr: 0.5966 loss_db: 0.1632 2022/11/02 15:02:30 - mmengine - INFO - Epoch(train) [271][30/63] lr: 1.7193e-03 eta: 9:33:02 time: 0.6630 data_time: 0.0382 memory: 14901 loss: 1.6972 loss_prob: 0.9666 loss_thr: 0.5695 loss_db: 0.1612 2022/11/02 15:02:32 - mmengine - INFO - Epoch(train) [271][35/63] lr: 1.7193e-03 eta: 9:33:02 time: 0.4906 data_time: 0.0232 memory: 14901 loss: 1.7344 loss_prob: 0.9941 loss_thr: 0.5749 loss_db: 0.1654 2022/11/02 15:02:36 - mmengine - INFO - Epoch(train) [271][40/63] lr: 1.7193e-03 eta: 9:32:57 time: 0.5906 data_time: 0.0159 memory: 14901 loss: 1.9354 loss_prob: 1.1475 loss_thr: 0.5947 loss_db: 0.1932 2022/11/02 15:02:38 - mmengine - INFO - Epoch(train) [271][45/63] lr: 1.7193e-03 eta: 9:32:57 time: 0.6466 data_time: 0.0075 memory: 14901 loss: 2.0344 loss_prob: 1.2267 loss_thr: 0.5996 loss_db: 0.2081 2022/11/02 15:02:41 - mmengine - INFO - Epoch(train) [271][50/63] lr: 1.7193e-03 eta: 9:32:50 time: 0.5593 data_time: 0.0185 memory: 14901 loss: 1.8821 loss_prob: 1.1078 loss_thr: 0.5916 loss_db: 0.1826 2022/11/02 15:02:44 - mmengine - INFO - Epoch(train) [271][55/63] lr: 1.7193e-03 eta: 9:32:50 time: 0.5235 data_time: 0.0285 memory: 14901 loss: 1.7478 loss_prob: 1.0013 loss_thr: 0.5836 loss_db: 0.1630 2022/11/02 15:02:47 - mmengine - INFO - Epoch(train) [271][60/63] lr: 1.7193e-03 eta: 9:32:43 time: 0.5567 data_time: 0.0167 memory: 14901 loss: 1.7548 loss_prob: 0.9969 loss_thr: 0.5904 loss_db: 0.1675 2022/11/02 15:02:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:02:53 - mmengine - INFO - Epoch(train) [272][5/63] lr: 1.7176e-03 eta: 9:32:43 time: 0.7259 data_time: 0.1978 memory: 14901 loss: 2.0258 loss_prob: 1.2099 loss_thr: 0.6204 loss_db: 0.1956 2022/11/02 15:02:56 - mmengine - INFO - Epoch(train) [272][10/63] lr: 1.7176e-03 eta: 9:32:35 time: 0.7577 data_time: 0.2138 memory: 14901 loss: 1.9723 loss_prob: 1.1722 loss_thr: 0.6076 loss_db: 0.1925 2022/11/02 15:02:58 - mmengine - INFO - Epoch(train) [272][15/63] lr: 1.7176e-03 eta: 9:32:35 time: 0.5532 data_time: 0.0241 memory: 14901 loss: 1.8016 loss_prob: 1.0505 loss_thr: 0.5784 loss_db: 0.1727 2022/11/02 15:03:01 - mmengine - INFO - Epoch(train) [272][20/63] lr: 1.7176e-03 eta: 9:32:28 time: 0.5669 data_time: 0.0107 memory: 14901 loss: 1.6929 loss_prob: 0.9473 loss_thr: 0.5889 loss_db: 0.1567 2022/11/02 15:03:04 - mmengine - INFO - Epoch(train) [272][25/63] lr: 1.7176e-03 eta: 9:32:28 time: 0.5442 data_time: 0.0170 memory: 14901 loss: 1.8316 loss_prob: 1.0550 loss_thr: 0.6013 loss_db: 0.1752 2022/11/02 15:03:07 - mmengine - INFO - Epoch(train) [272][30/63] lr: 1.7176e-03 eta: 9:32:21 time: 0.5413 data_time: 0.0395 memory: 14901 loss: 1.7729 loss_prob: 1.0347 loss_thr: 0.5662 loss_db: 0.1720 2022/11/02 15:03:09 - mmengine - INFO - Epoch(train) [272][35/63] lr: 1.7176e-03 eta: 9:32:21 time: 0.5480 data_time: 0.0385 memory: 14901 loss: 1.7702 loss_prob: 1.0431 loss_thr: 0.5626 loss_db: 0.1645 2022/11/02 15:03:12 - mmengine - INFO - Epoch(train) [272][40/63] lr: 1.7176e-03 eta: 9:32:15 time: 0.5803 data_time: 0.0127 memory: 14901 loss: 1.8176 loss_prob: 1.0804 loss_thr: 0.5689 loss_db: 0.1682 2022/11/02 15:03:16 - mmengine - INFO - Epoch(train) [272][45/63] lr: 1.7176e-03 eta: 9:32:15 time: 0.6369 data_time: 0.0101 memory: 14901 loss: 1.7122 loss_prob: 0.9796 loss_thr: 0.5700 loss_db: 0.1626 2022/11/02 15:03:18 - mmengine - INFO - Epoch(train) [272][50/63] lr: 1.7176e-03 eta: 9:32:09 time: 0.5740 data_time: 0.0269 memory: 14901 loss: 1.6669 loss_prob: 0.9324 loss_thr: 0.5786 loss_db: 0.1560 2022/11/02 15:03:21 - mmengine - INFO - Epoch(train) [272][55/63] lr: 1.7176e-03 eta: 9:32:09 time: 0.5241 data_time: 0.0350 memory: 14901 loss: 2.0150 loss_prob: 1.1938 loss_thr: 0.6266 loss_db: 0.1946 2022/11/02 15:03:23 - mmengine - INFO - Epoch(train) [272][60/63] lr: 1.7176e-03 eta: 9:32:00 time: 0.5203 data_time: 0.0225 memory: 14901 loss: 2.0217 loss_prob: 1.2142 loss_thr: 0.6082 loss_db: 0.1994 2022/11/02 15:03:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:03:30 - mmengine - INFO - Epoch(train) [273][5/63] lr: 1.7160e-03 eta: 9:32:00 time: 0.7676 data_time: 0.2378 memory: 14901 loss: 1.7928 loss_prob: 1.0345 loss_thr: 0.5856 loss_db: 0.1727 2022/11/02 15:03:34 - mmengine - INFO - Epoch(train) [273][10/63] lr: 1.7160e-03 eta: 9:31:58 time: 0.9068 data_time: 0.3158 memory: 14901 loss: 1.8206 loss_prob: 1.0533 loss_thr: 0.5923 loss_db: 0.1750 2022/11/02 15:03:37 - mmengine - INFO - Epoch(train) [273][15/63] lr: 1.7160e-03 eta: 9:31:58 time: 0.6673 data_time: 0.0888 memory: 14901 loss: 1.7136 loss_prob: 0.9642 loss_thr: 0.5924 loss_db: 0.1570 2022/11/02 15:03:39 - mmengine - INFO - Epoch(train) [273][20/63] lr: 1.7160e-03 eta: 9:31:51 time: 0.5506 data_time: 0.0119 memory: 14901 loss: 1.7357 loss_prob: 0.9814 loss_thr: 0.5945 loss_db: 0.1599 2022/11/02 15:03:42 - mmengine - INFO - Epoch(train) [273][25/63] lr: 1.7160e-03 eta: 9:31:51 time: 0.4964 data_time: 0.0071 memory: 14901 loss: 1.7991 loss_prob: 1.0336 loss_thr: 0.5926 loss_db: 0.1729 2022/11/02 15:03:44 - mmengine - INFO - Epoch(train) [273][30/63] lr: 1.7160e-03 eta: 9:31:41 time: 0.4904 data_time: 0.0063 memory: 14901 loss: 1.7389 loss_prob: 0.9930 loss_thr: 0.5781 loss_db: 0.1677 2022/11/02 15:03:47 - mmengine - INFO - Epoch(train) [273][35/63] lr: 1.7160e-03 eta: 9:31:41 time: 0.5105 data_time: 0.0094 memory: 14901 loss: 1.6775 loss_prob: 0.9385 loss_thr: 0.5811 loss_db: 0.1578 2022/11/02 15:03:50 - mmengine - INFO - Epoch(train) [273][40/63] lr: 1.7160e-03 eta: 9:31:34 time: 0.5374 data_time: 0.0129 memory: 14901 loss: 1.7587 loss_prob: 0.9875 loss_thr: 0.6070 loss_db: 0.1642 2022/11/02 15:03:52 - mmengine - INFO - Epoch(train) [273][45/63] lr: 1.7160e-03 eta: 9:31:34 time: 0.5126 data_time: 0.0091 memory: 14901 loss: 1.8314 loss_prob: 1.0615 loss_thr: 0.6013 loss_db: 0.1687 2022/11/02 15:03:54 - mmengine - INFO - Epoch(train) [273][50/63] lr: 1.7160e-03 eta: 9:31:24 time: 0.4715 data_time: 0.0068 memory: 14901 loss: 1.9019 loss_prob: 1.1181 loss_thr: 0.6047 loss_db: 0.1791 2022/11/02 15:03:57 - mmengine - INFO - Epoch(train) [273][55/63] lr: 1.7160e-03 eta: 9:31:24 time: 0.5242 data_time: 0.0134 memory: 14901 loss: 1.7747 loss_prob: 1.0060 loss_thr: 0.6030 loss_db: 0.1658 2022/11/02 15:04:00 - mmengine - INFO - Epoch(train) [273][60/63] lr: 1.7160e-03 eta: 9:31:17 time: 0.5540 data_time: 0.0199 memory: 14901 loss: 1.5983 loss_prob: 0.8854 loss_thr: 0.5644 loss_db: 0.1485 2022/11/02 15:04:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:04:06 - mmengine - INFO - Epoch(train) [274][5/63] lr: 1.7143e-03 eta: 9:31:17 time: 0.7439 data_time: 0.2377 memory: 14901 loss: 1.7901 loss_prob: 1.0322 loss_thr: 0.5900 loss_db: 0.1679 2022/11/02 15:04:09 - mmengine - INFO - Epoch(train) [274][10/63] lr: 1.7143e-03 eta: 9:31:11 time: 0.8136 data_time: 0.2302 memory: 14901 loss: 1.7266 loss_prob: 0.9754 loss_thr: 0.5869 loss_db: 0.1643 2022/11/02 15:04:12 - mmengine - INFO - Epoch(train) [274][15/63] lr: 1.7143e-03 eta: 9:31:11 time: 0.6019 data_time: 0.0067 memory: 14901 loss: 1.7033 loss_prob: 0.9617 loss_thr: 0.5805 loss_db: 0.1610 2022/11/02 15:04:15 - mmengine - INFO - Epoch(train) [274][20/63] lr: 1.7143e-03 eta: 9:31:04 time: 0.5534 data_time: 0.0099 memory: 14901 loss: 1.6963 loss_prob: 0.9721 loss_thr: 0.5630 loss_db: 0.1613 2022/11/02 15:04:19 - mmengine - INFO - Epoch(train) [274][25/63] lr: 1.7143e-03 eta: 9:31:04 time: 0.6265 data_time: 0.0326 memory: 14901 loss: 1.6904 loss_prob: 0.9674 loss_thr: 0.5652 loss_db: 0.1578 2022/11/02 15:04:21 - mmengine - INFO - Epoch(train) [274][30/63] lr: 1.7143e-03 eta: 9:30:59 time: 0.6184 data_time: 0.0395 memory: 14901 loss: 1.7147 loss_prob: 0.9788 loss_thr: 0.5768 loss_db: 0.1591 2022/11/02 15:04:24 - mmengine - INFO - Epoch(train) [274][35/63] lr: 1.7143e-03 eta: 9:30:59 time: 0.5535 data_time: 0.0161 memory: 14901 loss: 1.7702 loss_prob: 1.0130 loss_thr: 0.5897 loss_db: 0.1675 2022/11/02 15:04:27 - mmengine - INFO - Epoch(train) [274][40/63] lr: 1.7143e-03 eta: 9:30:52 time: 0.5443 data_time: 0.0092 memory: 14901 loss: 1.7437 loss_prob: 0.9943 loss_thr: 0.5801 loss_db: 0.1694 2022/11/02 15:04:30 - mmengine - INFO - Epoch(train) [274][45/63] lr: 1.7143e-03 eta: 9:30:52 time: 0.5760 data_time: 0.0166 memory: 14901 loss: 1.7961 loss_prob: 1.0404 loss_thr: 0.5814 loss_db: 0.1743 2022/11/02 15:04:32 - mmengine - INFO - Epoch(train) [274][50/63] lr: 1.7143e-03 eta: 9:30:46 time: 0.5794 data_time: 0.0283 memory: 14901 loss: 1.8820 loss_prob: 1.1140 loss_thr: 0.5863 loss_db: 0.1817 2022/11/02 15:04:35 - mmengine - INFO - Epoch(train) [274][55/63] lr: 1.7143e-03 eta: 9:30:46 time: 0.5241 data_time: 0.0292 memory: 14901 loss: 1.7493 loss_prob: 1.0218 loss_thr: 0.5559 loss_db: 0.1716 2022/11/02 15:04:38 - mmengine - INFO - Epoch(train) [274][60/63] lr: 1.7143e-03 eta: 9:30:40 time: 0.5969 data_time: 0.0143 memory: 14901 loss: 1.6619 loss_prob: 0.9506 loss_thr: 0.5517 loss_db: 0.1596 2022/11/02 15:04:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:04:47 - mmengine - INFO - Epoch(train) [275][5/63] lr: 1.7126e-03 eta: 9:30:40 time: 0.9127 data_time: 0.2851 memory: 14901 loss: 1.7908 loss_prob: 1.0538 loss_thr: 0.5670 loss_db: 0.1699 2022/11/02 15:04:49 - mmengine - INFO - Epoch(train) [275][10/63] lr: 1.7126e-03 eta: 9:30:38 time: 0.9296 data_time: 0.2878 memory: 14901 loss: 1.8652 loss_prob: 1.1007 loss_thr: 0.5823 loss_db: 0.1821 2022/11/02 15:04:52 - mmengine - INFO - Epoch(train) [275][15/63] lr: 1.7126e-03 eta: 9:30:38 time: 0.5009 data_time: 0.0103 memory: 14901 loss: 1.8312 loss_prob: 1.0755 loss_thr: 0.5763 loss_db: 0.1793 2022/11/02 15:04:54 - mmengine - INFO - Epoch(train) [275][20/63] lr: 1.7126e-03 eta: 9:30:30 time: 0.5207 data_time: 0.0060 memory: 14901 loss: 1.7321 loss_prob: 0.9986 loss_thr: 0.5711 loss_db: 0.1624 2022/11/02 15:04:57 - mmengine - INFO - Epoch(train) [275][25/63] lr: 1.7126e-03 eta: 9:30:30 time: 0.5745 data_time: 0.0397 memory: 14901 loss: 1.8336 loss_prob: 1.0779 loss_thr: 0.5836 loss_db: 0.1722 2022/11/02 15:05:00 - mmengine - INFO - Epoch(train) [275][30/63] lr: 1.7126e-03 eta: 9:30:23 time: 0.5387 data_time: 0.0399 memory: 14901 loss: 1.7704 loss_prob: 1.0270 loss_thr: 0.5770 loss_db: 0.1664 2022/11/02 15:05:02 - mmengine - INFO - Epoch(train) [275][35/63] lr: 1.7126e-03 eta: 9:30:23 time: 0.5025 data_time: 0.0127 memory: 14901 loss: 1.8525 loss_prob: 1.0825 loss_thr: 0.5954 loss_db: 0.1745 2022/11/02 15:05:05 - mmengine - INFO - Epoch(train) [275][40/63] lr: 1.7126e-03 eta: 9:30:15 time: 0.5227 data_time: 0.0117 memory: 14901 loss: 1.9040 loss_prob: 1.1304 loss_thr: 0.5935 loss_db: 0.1801 2022/11/02 15:05:08 - mmengine - INFO - Epoch(train) [275][45/63] lr: 1.7126e-03 eta: 9:30:15 time: 0.5136 data_time: 0.0057 memory: 14901 loss: 1.8264 loss_prob: 1.0690 loss_thr: 0.5796 loss_db: 0.1778 2022/11/02 15:05:10 - mmengine - INFO - Epoch(train) [275][50/63] lr: 1.7126e-03 eta: 9:30:07 time: 0.5258 data_time: 0.0225 memory: 14901 loss: 2.0407 loss_prob: 1.2596 loss_thr: 0.5873 loss_db: 0.1938 2022/11/02 15:05:13 - mmengine - INFO - Epoch(train) [275][55/63] lr: 1.7126e-03 eta: 9:30:07 time: 0.5542 data_time: 0.0232 memory: 14901 loss: 1.9838 loss_prob: 1.2196 loss_thr: 0.5850 loss_db: 0.1792 2022/11/02 15:05:16 - mmengine - INFO - Epoch(train) [275][60/63] lr: 1.7126e-03 eta: 9:30:00 time: 0.5711 data_time: 0.0111 memory: 14901 loss: 1.6314 loss_prob: 0.9222 loss_thr: 0.5577 loss_db: 0.1515 2022/11/02 15:05:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:05:24 - mmengine - INFO - Epoch(train) [276][5/63] lr: 1.7110e-03 eta: 9:30:00 time: 0.9232 data_time: 0.2645 memory: 14901 loss: 1.9771 loss_prob: 1.1902 loss_thr: 0.5909 loss_db: 0.1959 2022/11/02 15:05:27 - mmengine - INFO - Epoch(train) [276][10/63] lr: 1.7110e-03 eta: 9:29:57 time: 0.8998 data_time: 0.2721 memory: 14901 loss: 2.0308 loss_prob: 1.2276 loss_thr: 0.6049 loss_db: 0.1983 2022/11/02 15:05:29 - mmengine - INFO - Epoch(train) [276][15/63] lr: 1.7110e-03 eta: 9:29:57 time: 0.5116 data_time: 0.0159 memory: 14901 loss: 1.9248 loss_prob: 1.1140 loss_thr: 0.6319 loss_db: 0.1789 2022/11/02 15:05:32 - mmengine - INFO - Epoch(train) [276][20/63] lr: 1.7110e-03 eta: 9:29:49 time: 0.5121 data_time: 0.0079 memory: 14901 loss: 2.0143 loss_prob: 1.1774 loss_thr: 0.6431 loss_db: 0.1938 2022/11/02 15:05:35 - mmengine - INFO - Epoch(train) [276][25/63] lr: 1.7110e-03 eta: 9:29:49 time: 0.5449 data_time: 0.0150 memory: 14901 loss: 2.0824 loss_prob: 1.2614 loss_thr: 0.6150 loss_db: 0.2060 2022/11/02 15:05:37 - mmengine - INFO - Epoch(train) [276][30/63] lr: 1.7110e-03 eta: 9:29:41 time: 0.5338 data_time: 0.0326 memory: 14901 loss: 1.8191 loss_prob: 1.0783 loss_thr: 0.5706 loss_db: 0.1702 2022/11/02 15:05:40 - mmengine - INFO - Epoch(train) [276][35/63] lr: 1.7110e-03 eta: 9:29:41 time: 0.5270 data_time: 0.0265 memory: 14901 loss: 1.5835 loss_prob: 0.8896 loss_thr: 0.5478 loss_db: 0.1461 2022/11/02 15:05:42 - mmengine - INFO - Epoch(train) [276][40/63] lr: 1.7110e-03 eta: 9:29:33 time: 0.5180 data_time: 0.0102 memory: 14901 loss: 1.6911 loss_prob: 0.9644 loss_thr: 0.5665 loss_db: 0.1602 2022/11/02 15:05:46 - mmengine - INFO - Epoch(train) [276][45/63] lr: 1.7110e-03 eta: 9:29:33 time: 0.5866 data_time: 0.0090 memory: 14901 loss: 1.7014 loss_prob: 0.9701 loss_thr: 0.5740 loss_db: 0.1573 2022/11/02 15:05:49 - mmengine - INFO - Epoch(train) [276][50/63] lr: 1.7110e-03 eta: 9:29:31 time: 0.6910 data_time: 0.0296 memory: 14901 loss: 1.7213 loss_prob: 0.9839 loss_thr: 0.5778 loss_db: 0.1595 2022/11/02 15:05:52 - mmengine - INFO - Epoch(train) [276][55/63] lr: 1.7110e-03 eta: 9:29:31 time: 0.6127 data_time: 0.0322 memory: 14901 loss: 1.9032 loss_prob: 1.1257 loss_thr: 0.5963 loss_db: 0.1812 2022/11/02 15:05:55 - mmengine - INFO - Epoch(train) [276][60/63] lr: 1.7110e-03 eta: 9:29:23 time: 0.5369 data_time: 0.0121 memory: 14901 loss: 2.0040 loss_prob: 1.2195 loss_thr: 0.5872 loss_db: 0.1973 2022/11/02 15:05:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:06:02 - mmengine - INFO - Epoch(train) [277][5/63] lr: 1.7093e-03 eta: 9:29:23 time: 0.7965 data_time: 0.2366 memory: 14901 loss: 1.6931 loss_prob: 0.9974 loss_thr: 0.5331 loss_db: 0.1627 2022/11/02 15:06:05 - mmengine - INFO - Epoch(train) [277][10/63] lr: 1.7093e-03 eta: 9:29:19 time: 0.8611 data_time: 0.2344 memory: 14901 loss: 1.6780 loss_prob: 0.9476 loss_thr: 0.5755 loss_db: 0.1550 2022/11/02 15:06:08 - mmengine - INFO - Epoch(train) [277][15/63] lr: 1.7093e-03 eta: 9:29:19 time: 0.5939 data_time: 0.0110 memory: 14901 loss: 1.7458 loss_prob: 0.9863 loss_thr: 0.5987 loss_db: 0.1607 2022/11/02 15:06:10 - mmengine - INFO - Epoch(train) [277][20/63] lr: 1.7093e-03 eta: 9:29:12 time: 0.5638 data_time: 0.0261 memory: 14901 loss: 1.8079 loss_prob: 1.0393 loss_thr: 0.6002 loss_db: 0.1684 2022/11/02 15:06:13 - mmengine - INFO - Epoch(train) [277][25/63] lr: 1.7093e-03 eta: 9:29:12 time: 0.5656 data_time: 0.0216 memory: 14901 loss: 1.7564 loss_prob: 1.0113 loss_thr: 0.5798 loss_db: 0.1653 2022/11/02 15:06:16 - mmengine - INFO - Epoch(train) [277][30/63] lr: 1.7093e-03 eta: 9:29:06 time: 0.5869 data_time: 0.0309 memory: 14901 loss: 1.7190 loss_prob: 0.9684 loss_thr: 0.5901 loss_db: 0.1605 2022/11/02 15:06:19 - mmengine - INFO - Epoch(train) [277][35/63] lr: 1.7093e-03 eta: 9:29:06 time: 0.5627 data_time: 0.0316 memory: 14901 loss: 1.7071 loss_prob: 0.9503 loss_thr: 0.5981 loss_db: 0.1587 2022/11/02 15:06:21 - mmengine - INFO - Epoch(train) [277][40/63] lr: 1.7093e-03 eta: 9:28:58 time: 0.5255 data_time: 0.0130 memory: 14901 loss: 1.5579 loss_prob: 0.8718 loss_thr: 0.5408 loss_db: 0.1453 2022/11/02 15:06:25 - mmengine - INFO - Epoch(train) [277][45/63] lr: 1.7093e-03 eta: 9:28:58 time: 0.5813 data_time: 0.0122 memory: 14901 loss: 1.5736 loss_prob: 0.8811 loss_thr: 0.5480 loss_db: 0.1445 2022/11/02 15:06:27 - mmengine - INFO - Epoch(train) [277][50/63] lr: 1.7093e-03 eta: 9:28:53 time: 0.5916 data_time: 0.0212 memory: 14901 loss: 1.6827 loss_prob: 0.9392 loss_thr: 0.5869 loss_db: 0.1567 2022/11/02 15:06:30 - mmengine - INFO - Epoch(train) [277][55/63] lr: 1.7093e-03 eta: 9:28:53 time: 0.5377 data_time: 0.0222 memory: 14901 loss: 1.8201 loss_prob: 1.0243 loss_thr: 0.6259 loss_db: 0.1699 2022/11/02 15:06:33 - mmengine - INFO - Epoch(train) [277][60/63] lr: 1.7093e-03 eta: 9:28:45 time: 0.5311 data_time: 0.0082 memory: 14901 loss: 1.7312 loss_prob: 0.9766 loss_thr: 0.5941 loss_db: 0.1606 2022/11/02 15:06:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:06:39 - mmengine - INFO - Epoch(train) [278][5/63] lr: 1.7076e-03 eta: 9:28:45 time: 0.7383 data_time: 0.2413 memory: 14901 loss: 1.7906 loss_prob: 1.0349 loss_thr: 0.5820 loss_db: 0.1736 2022/11/02 15:06:42 - mmengine - INFO - Epoch(train) [278][10/63] lr: 1.7076e-03 eta: 9:28:39 time: 0.8236 data_time: 0.2413 memory: 14901 loss: 1.8108 loss_prob: 1.0586 loss_thr: 0.5804 loss_db: 0.1717 2022/11/02 15:06:45 - mmengine - INFO - Epoch(train) [278][15/63] lr: 1.7076e-03 eta: 9:28:39 time: 0.6082 data_time: 0.0074 memory: 14901 loss: 1.6153 loss_prob: 0.9192 loss_thr: 0.5441 loss_db: 0.1520 2022/11/02 15:06:48 - mmengine - INFO - Epoch(train) [278][20/63] lr: 1.7076e-03 eta: 9:28:34 time: 0.5887 data_time: 0.0117 memory: 14901 loss: 1.5919 loss_prob: 0.8896 loss_thr: 0.5540 loss_db: 0.1484 2022/11/02 15:06:51 - mmengine - INFO - Epoch(train) [278][25/63] lr: 1.7076e-03 eta: 9:28:34 time: 0.5834 data_time: 0.0368 memory: 14901 loss: 1.6926 loss_prob: 0.9561 loss_thr: 0.5827 loss_db: 0.1539 2022/11/02 15:06:54 - mmengine - INFO - Epoch(train) [278][30/63] lr: 1.7076e-03 eta: 9:28:27 time: 0.5585 data_time: 0.0377 memory: 14901 loss: 1.6860 loss_prob: 0.9619 loss_thr: 0.5689 loss_db: 0.1553 2022/11/02 15:06:57 - mmengine - INFO - Epoch(train) [278][35/63] lr: 1.7076e-03 eta: 9:28:27 time: 0.5703 data_time: 0.0130 memory: 14901 loss: 1.7313 loss_prob: 0.9995 loss_thr: 0.5634 loss_db: 0.1684 2022/11/02 15:06:59 - mmengine - INFO - Epoch(train) [278][40/63] lr: 1.7076e-03 eta: 9:28:19 time: 0.5424 data_time: 0.0084 memory: 14901 loss: 1.7709 loss_prob: 1.0270 loss_thr: 0.5710 loss_db: 0.1729 2022/11/02 15:07:02 - mmengine - INFO - Epoch(train) [278][45/63] lr: 1.7076e-03 eta: 9:28:19 time: 0.5841 data_time: 0.0100 memory: 14901 loss: 1.7315 loss_prob: 0.9977 loss_thr: 0.5697 loss_db: 0.1640 2022/11/02 15:07:05 - mmengine - INFO - Epoch(train) [278][50/63] lr: 1.7076e-03 eta: 9:28:15 time: 0.6227 data_time: 0.0324 memory: 14901 loss: 1.6840 loss_prob: 0.9601 loss_thr: 0.5647 loss_db: 0.1592 2022/11/02 15:07:08 - mmengine - INFO - Epoch(train) [278][55/63] lr: 1.7076e-03 eta: 9:28:15 time: 0.5526 data_time: 0.0321 memory: 14901 loss: 1.6828 loss_prob: 0.9598 loss_thr: 0.5621 loss_db: 0.1609 2022/11/02 15:07:11 - mmengine - INFO - Epoch(train) [278][60/63] lr: 1.7076e-03 eta: 9:28:08 time: 0.5510 data_time: 0.0116 memory: 14901 loss: 1.7525 loss_prob: 1.0155 loss_thr: 0.5698 loss_db: 0.1673 2022/11/02 15:07:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:07:18 - mmengine - INFO - Epoch(train) [279][5/63] lr: 1.7060e-03 eta: 9:28:08 time: 0.8308 data_time: 0.2371 memory: 14901 loss: 2.0014 loss_prob: 1.1940 loss_thr: 0.6141 loss_db: 0.1933 2022/11/02 15:07:21 - mmengine - INFO - Epoch(train) [279][10/63] lr: 1.7060e-03 eta: 9:28:03 time: 0.8535 data_time: 0.2372 memory: 14901 loss: 1.9062 loss_prob: 1.1215 loss_thr: 0.5997 loss_db: 0.1850 2022/11/02 15:07:24 - mmengine - INFO - Epoch(train) [279][15/63] lr: 1.7060e-03 eta: 9:28:03 time: 0.5525 data_time: 0.0077 memory: 14901 loss: 1.6731 loss_prob: 0.9449 loss_thr: 0.5728 loss_db: 0.1554 2022/11/02 15:07:26 - mmengine - INFO - Epoch(train) [279][20/63] lr: 1.7060e-03 eta: 9:27:57 time: 0.5730 data_time: 0.0132 memory: 14901 loss: 1.7936 loss_prob: 1.0373 loss_thr: 0.5849 loss_db: 0.1714 2022/11/02 15:07:29 - mmengine - INFO - Epoch(train) [279][25/63] lr: 1.7060e-03 eta: 9:27:57 time: 0.5755 data_time: 0.0408 memory: 14901 loss: 1.7284 loss_prob: 0.9913 loss_thr: 0.5760 loss_db: 0.1611 2022/11/02 15:07:33 - mmengine - INFO - Epoch(train) [279][30/63] lr: 1.7060e-03 eta: 9:27:53 time: 0.6474 data_time: 0.0424 memory: 14901 loss: 1.6921 loss_prob: 0.9533 loss_thr: 0.5850 loss_db: 0.1538 2022/11/02 15:07:36 - mmengine - INFO - Epoch(train) [279][35/63] lr: 1.7060e-03 eta: 9:27:53 time: 0.6284 data_time: 0.0209 memory: 14901 loss: 1.9109 loss_prob: 1.1352 loss_thr: 0.5919 loss_db: 0.1838 2022/11/02 15:07:38 - mmengine - INFO - Epoch(train) [279][40/63] lr: 1.7060e-03 eta: 9:27:46 time: 0.5506 data_time: 0.0136 memory: 14901 loss: 1.8589 loss_prob: 1.1052 loss_thr: 0.5757 loss_db: 0.1780 2022/11/02 15:07:41 - mmengine - INFO - Epoch(train) [279][45/63] lr: 1.7060e-03 eta: 9:27:46 time: 0.5269 data_time: 0.0099 memory: 14901 loss: 1.7477 loss_prob: 0.9979 loss_thr: 0.5917 loss_db: 0.1582 2022/11/02 15:07:44 - mmengine - INFO - Epoch(train) [279][50/63] lr: 1.7060e-03 eta: 9:27:39 time: 0.5683 data_time: 0.0235 memory: 14901 loss: 1.7670 loss_prob: 1.0006 loss_thr: 0.6043 loss_db: 0.1621 2022/11/02 15:07:47 - mmengine - INFO - Epoch(train) [279][55/63] lr: 1.7060e-03 eta: 9:27:39 time: 0.5790 data_time: 0.0236 memory: 14901 loss: 1.8345 loss_prob: 1.0549 loss_thr: 0.6068 loss_db: 0.1728 2022/11/02 15:07:49 - mmengine - INFO - Epoch(train) [279][60/63] lr: 1.7060e-03 eta: 9:27:31 time: 0.5089 data_time: 0.0120 memory: 14901 loss: 1.9078 loss_prob: 1.1098 loss_thr: 0.6191 loss_db: 0.1789 2022/11/02 15:07:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:07:56 - mmengine - INFO - Epoch(train) [280][5/63] lr: 1.7043e-03 eta: 9:27:31 time: 0.7741 data_time: 0.1963 memory: 14901 loss: 1.6753 loss_prob: 0.9477 loss_thr: 0.5785 loss_db: 0.1491 2022/11/02 15:07:58 - mmengine - INFO - Epoch(train) [280][10/63] lr: 1.7043e-03 eta: 9:27:24 time: 0.7913 data_time: 0.1966 memory: 14901 loss: 1.8270 loss_prob: 1.0411 loss_thr: 0.6145 loss_db: 0.1714 2022/11/02 15:08:01 - mmengine - INFO - Epoch(train) [280][15/63] lr: 1.7043e-03 eta: 9:27:24 time: 0.4969 data_time: 0.0113 memory: 14901 loss: 1.7560 loss_prob: 0.9934 loss_thr: 0.5953 loss_db: 0.1673 2022/11/02 15:08:03 - mmengine - INFO - Epoch(train) [280][20/63] lr: 1.7043e-03 eta: 9:27:16 time: 0.5021 data_time: 0.0147 memory: 14901 loss: 1.6678 loss_prob: 0.9330 loss_thr: 0.5759 loss_db: 0.1589 2022/11/02 15:08:06 - mmengine - INFO - Epoch(train) [280][25/63] lr: 1.7043e-03 eta: 9:27:16 time: 0.5107 data_time: 0.0276 memory: 14901 loss: 1.7566 loss_prob: 0.9928 loss_thr: 0.5972 loss_db: 0.1665 2022/11/02 15:08:09 - mmengine - INFO - Epoch(train) [280][30/63] lr: 1.7043e-03 eta: 9:27:07 time: 0.5144 data_time: 0.0305 memory: 14901 loss: 1.8651 loss_prob: 1.0780 loss_thr: 0.6096 loss_db: 0.1775 2022/11/02 15:08:11 - mmengine - INFO - Epoch(train) [280][35/63] lr: 1.7043e-03 eta: 9:27:07 time: 0.4958 data_time: 0.0193 memory: 14901 loss: 1.8222 loss_prob: 1.0583 loss_thr: 0.5897 loss_db: 0.1741 2022/11/02 15:08:13 - mmengine - INFO - Epoch(train) [280][40/63] lr: 1.7043e-03 eta: 9:26:58 time: 0.4950 data_time: 0.0239 memory: 14901 loss: 1.7671 loss_prob: 1.0182 loss_thr: 0.5771 loss_db: 0.1718 2022/11/02 15:08:16 - mmengine - INFO - Epoch(train) [280][45/63] lr: 1.7043e-03 eta: 9:26:58 time: 0.5099 data_time: 0.0235 memory: 14901 loss: 1.8864 loss_prob: 1.1060 loss_thr: 0.6031 loss_db: 0.1772 2022/11/02 15:08:19 - mmengine - INFO - Epoch(train) [280][50/63] lr: 1.7043e-03 eta: 9:26:51 time: 0.5291 data_time: 0.0226 memory: 14901 loss: 1.8992 loss_prob: 1.1077 loss_thr: 0.6158 loss_db: 0.1757 2022/11/02 15:08:21 - mmengine - INFO - Epoch(train) [280][55/63] lr: 1.7043e-03 eta: 9:26:51 time: 0.5437 data_time: 0.0221 memory: 14901 loss: 1.8584 loss_prob: 1.0648 loss_thr: 0.6169 loss_db: 0.1767 2022/11/02 15:08:24 - mmengine - INFO - Epoch(train) [280][60/63] lr: 1.7043e-03 eta: 9:26:43 time: 0.5279 data_time: 0.0198 memory: 14901 loss: 2.0122 loss_prob: 1.2037 loss_thr: 0.6165 loss_db: 0.1920 2022/11/02 15:08:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:08:25 - mmengine - INFO - Saving checkpoint at 280 epochs 2022/11/02 15:08:29 - mmengine - INFO - Epoch(val) [280][5/500] eta: 9:26:43 time: 0.0497 data_time: 0.0078 memory: 14901 2022/11/02 15:08:29 - mmengine - INFO - Epoch(val) [280][10/500] eta: 0:00:21 time: 0.0448 data_time: 0.0046 memory: 1008 2022/11/02 15:08:29 - mmengine - INFO - Epoch(val) [280][15/500] eta: 0:00:21 time: 0.0387 data_time: 0.0021 memory: 1008 2022/11/02 15:08:30 - mmengine - INFO - Epoch(val) [280][20/500] eta: 0:00:18 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 15:08:30 - mmengine - INFO - Epoch(val) [280][25/500] eta: 0:00:18 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 15:08:30 - mmengine - INFO - Epoch(val) [280][30/500] eta: 0:00:20 time: 0.0442 data_time: 0.0025 memory: 1008 2022/11/02 15:08:30 - mmengine - INFO - Epoch(val) [280][35/500] eta: 0:00:20 time: 0.0427 data_time: 0.0024 memory: 1008 2022/11/02 15:08:30 - mmengine - INFO - Epoch(val) [280][40/500] eta: 0:00:19 time: 0.0415 data_time: 0.0024 memory: 1008 2022/11/02 15:08:31 - mmengine - INFO - Epoch(val) [280][45/500] eta: 0:00:19 time: 0.0433 data_time: 0.0024 memory: 1008 2022/11/02 15:08:31 - mmengine - INFO - Epoch(val) [280][50/500] eta: 0:00:44 time: 0.0986 data_time: 0.0606 memory: 1008 2022/11/02 15:08:32 - mmengine - INFO - Epoch(val) [280][55/500] eta: 0:00:44 time: 0.1005 data_time: 0.0602 memory: 1008 2022/11/02 15:08:32 - mmengine - INFO - Epoch(val) [280][60/500] eta: 0:00:17 time: 0.0393 data_time: 0.0017 memory: 1008 2022/11/02 15:08:32 - mmengine - INFO - Epoch(val) [280][65/500] eta: 0:00:17 time: 0.0430 data_time: 0.0024 memory: 1008 2022/11/02 15:08:32 - mmengine - INFO - Epoch(val) [280][70/500] eta: 0:00:20 time: 0.0466 data_time: 0.0029 memory: 1008 2022/11/02 15:08:32 - mmengine - INFO - Epoch(val) [280][75/500] eta: 0:00:20 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 15:08:33 - mmengine - INFO - Epoch(val) [280][80/500] eta: 0:00:15 time: 0.0357 data_time: 0.0025 memory: 1008 2022/11/02 15:08:33 - mmengine - INFO - Epoch(val) [280][85/500] eta: 0:00:15 time: 0.0346 data_time: 0.0025 memory: 1008 2022/11/02 15:08:33 - mmengine - INFO - Epoch(val) [280][90/500] eta: 0:00:16 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 15:08:33 - mmengine - INFO - Epoch(val) [280][95/500] eta: 0:00:16 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 15:08:33 - mmengine - INFO - Epoch(val) [280][100/500] eta: 0:00:15 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/02 15:08:34 - mmengine - INFO - Epoch(val) [280][105/500] eta: 0:00:15 time: 0.0373 data_time: 0.0028 memory: 1008 2022/11/02 15:08:34 - mmengine - INFO - Epoch(val) [280][110/500] eta: 0:00:15 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 15:08:34 - mmengine - INFO - Epoch(val) [280][115/500] eta: 0:00:15 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/02 15:08:34 - mmengine - INFO - Epoch(val) [280][120/500] eta: 0:00:15 time: 0.0413 data_time: 0.0024 memory: 1008 2022/11/02 15:08:34 - mmengine - INFO - Epoch(val) [280][125/500] eta: 0:00:15 time: 0.0386 data_time: 0.0023 memory: 1008 2022/11/02 15:08:35 - mmengine - INFO - Epoch(val) [280][130/500] eta: 0:00:12 time: 0.0348 data_time: 0.0023 memory: 1008 2022/11/02 15:08:35 - mmengine - INFO - Epoch(val) [280][135/500] eta: 0:00:12 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 15:08:35 - mmengine - INFO - Epoch(val) [280][140/500] eta: 0:00:14 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/02 15:08:35 - mmengine - INFO - Epoch(val) [280][145/500] eta: 0:00:14 time: 0.0403 data_time: 0.0023 memory: 1008 2022/11/02 15:08:35 - mmengine - INFO - Epoch(val) [280][150/500] eta: 0:00:15 time: 0.0437 data_time: 0.0025 memory: 1008 2022/11/02 15:08:36 - mmengine - INFO - Epoch(val) [280][155/500] eta: 0:00:15 time: 0.0483 data_time: 0.0025 memory: 1008 2022/11/02 15:08:36 - mmengine - INFO - Epoch(val) [280][160/500] eta: 0:00:16 time: 0.0489 data_time: 0.0025 memory: 1008 2022/11/02 15:08:36 - mmengine - INFO - Epoch(val) [280][165/500] eta: 0:00:16 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 15:08:36 - mmengine - INFO - Epoch(val) [280][170/500] eta: 0:00:14 time: 0.0427 data_time: 0.0023 memory: 1008 2022/11/02 15:08:37 - mmengine - INFO - Epoch(val) [280][175/500] eta: 0:00:14 time: 0.0430 data_time: 0.0026 memory: 1008 2022/11/02 15:08:37 - mmengine - INFO - Epoch(val) [280][180/500] eta: 0:00:12 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 15:08:37 - mmengine - INFO - Epoch(val) [280][185/500] eta: 0:00:12 time: 0.0400 data_time: 0.0023 memory: 1008 2022/11/02 15:08:37 - mmengine - INFO - Epoch(val) [280][190/500] eta: 0:00:12 time: 0.0408 data_time: 0.0023 memory: 1008 2022/11/02 15:08:37 - mmengine - INFO - Epoch(val) [280][195/500] eta: 0:00:12 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/02 15:08:38 - mmengine - INFO - Epoch(val) [280][200/500] eta: 0:00:13 time: 0.0441 data_time: 0.0023 memory: 1008 2022/11/02 15:08:38 - mmengine - INFO - Epoch(val) [280][205/500] eta: 0:00:13 time: 0.0426 data_time: 0.0021 memory: 1008 2022/11/02 15:08:38 - mmengine - INFO - Epoch(val) [280][210/500] eta: 0:00:11 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/02 15:08:38 - mmengine - INFO - Epoch(val) [280][215/500] eta: 0:00:11 time: 0.0407 data_time: 0.0028 memory: 1008 2022/11/02 15:08:38 - mmengine - INFO - Epoch(val) [280][220/500] eta: 0:00:10 time: 0.0377 data_time: 0.0026 memory: 1008 2022/11/02 15:08:39 - mmengine - INFO - Epoch(val) [280][225/500] eta: 0:00:10 time: 0.0392 data_time: 0.0021 memory: 1008 2022/11/02 15:08:39 - mmengine - INFO - Epoch(val) [280][230/500] eta: 0:00:10 time: 0.0377 data_time: 0.0022 memory: 1008 2022/11/02 15:08:39 - mmengine - INFO - Epoch(val) [280][235/500] eta: 0:00:10 time: 0.0366 data_time: 0.0022 memory: 1008 2022/11/02 15:08:39 - mmengine - INFO - Epoch(val) [280][240/500] eta: 0:00:10 time: 0.0398 data_time: 0.0023 memory: 1008 2022/11/02 15:08:39 - mmengine - INFO - Epoch(val) [280][245/500] eta: 0:00:10 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/02 15:08:40 - mmengine - INFO - Epoch(val) [280][250/500] eta: 0:00:09 time: 0.0380 data_time: 0.0020 memory: 1008 2022/11/02 15:08:40 - mmengine - INFO - Epoch(val) [280][255/500] eta: 0:00:09 time: 0.0391 data_time: 0.0021 memory: 1008 2022/11/02 15:08:40 - mmengine - INFO - Epoch(val) [280][260/500] eta: 0:00:08 time: 0.0368 data_time: 0.0023 memory: 1008 2022/11/02 15:08:40 - mmengine - INFO - Epoch(val) [280][265/500] eta: 0:00:08 time: 0.0413 data_time: 0.0024 memory: 1008 2022/11/02 15:08:40 - mmengine - INFO - Epoch(val) [280][270/500] eta: 0:00:09 time: 0.0424 data_time: 0.0025 memory: 1008 2022/11/02 15:08:40 - mmengine - INFO - Epoch(val) [280][275/500] eta: 0:00:09 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 15:08:41 - mmengine - INFO - Epoch(val) [280][280/500] eta: 0:00:08 time: 0.0388 data_time: 0.0023 memory: 1008 2022/11/02 15:08:41 - mmengine - INFO - Epoch(val) [280][285/500] eta: 0:00:08 time: 0.0394 data_time: 0.0023 memory: 1008 2022/11/02 15:08:41 - mmengine - INFO - Epoch(val) [280][290/500] eta: 0:00:08 time: 0.0392 data_time: 0.0023 memory: 1008 2022/11/02 15:08:41 - mmengine - INFO - Epoch(val) [280][295/500] eta: 0:00:08 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 15:08:41 - mmengine - INFO - Epoch(val) [280][300/500] eta: 0:00:08 time: 0.0406 data_time: 0.0030 memory: 1008 2022/11/02 15:08:42 - mmengine - INFO - Epoch(val) [280][305/500] eta: 0:00:08 time: 0.0381 data_time: 0.0027 memory: 1008 2022/11/02 15:08:42 - mmengine - INFO - Epoch(val) [280][310/500] eta: 0:00:07 time: 0.0420 data_time: 0.0031 memory: 1008 2022/11/02 15:08:42 - mmengine - INFO - Epoch(val) [280][315/500] eta: 0:00:07 time: 0.0457 data_time: 0.0031 memory: 1008 2022/11/02 15:08:42 - mmengine - INFO - Epoch(val) [280][320/500] eta: 0:00:07 time: 0.0414 data_time: 0.0025 memory: 1008 2022/11/02 15:08:43 - mmengine - INFO - Epoch(val) [280][325/500] eta: 0:00:07 time: 0.0549 data_time: 0.0024 memory: 1008 2022/11/02 15:08:43 - mmengine - INFO - Epoch(val) [280][330/500] eta: 0:00:09 time: 0.0540 data_time: 0.0025 memory: 1008 2022/11/02 15:08:43 - mmengine - INFO - Epoch(val) [280][335/500] eta: 0:00:09 time: 0.0364 data_time: 0.0026 memory: 1008 2022/11/02 15:08:43 - mmengine - INFO - Epoch(val) [280][340/500] eta: 0:00:08 time: 0.0536 data_time: 0.0026 memory: 1008 2022/11/02 15:08:44 - mmengine - INFO - Epoch(val) [280][345/500] eta: 0:00:08 time: 0.0558 data_time: 0.0025 memory: 1008 2022/11/02 15:08:44 - mmengine - INFO - Epoch(val) [280][350/500] eta: 0:00:07 time: 0.0498 data_time: 0.0027 memory: 1008 2022/11/02 15:08:44 - mmengine - INFO - Epoch(val) [280][355/500] eta: 0:00:07 time: 0.0490 data_time: 0.0026 memory: 1008 2022/11/02 15:08:44 - mmengine - INFO - Epoch(val) [280][360/500] eta: 0:00:06 time: 0.0440 data_time: 0.0027 memory: 1008 2022/11/02 15:08:45 - mmengine - INFO - Epoch(val) [280][365/500] eta: 0:00:06 time: 0.0471 data_time: 0.0031 memory: 1008 2022/11/02 15:08:45 - mmengine - INFO - Epoch(val) [280][370/500] eta: 0:00:05 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/02 15:08:45 - mmengine - INFO - Epoch(val) [280][375/500] eta: 0:00:05 time: 0.0355 data_time: 0.0024 memory: 1008 2022/11/02 15:08:45 - mmengine - INFO - Epoch(val) [280][380/500] eta: 0:00:04 time: 0.0377 data_time: 0.0023 memory: 1008 2022/11/02 15:08:45 - mmengine - INFO - Epoch(val) [280][385/500] eta: 0:00:04 time: 0.0401 data_time: 0.0023 memory: 1008 2022/11/02 15:08:46 - mmengine - INFO - Epoch(val) [280][390/500] eta: 0:00:04 time: 0.0394 data_time: 0.0023 memory: 1008 2022/11/02 15:08:46 - mmengine - INFO - Epoch(val) [280][395/500] eta: 0:00:04 time: 0.0375 data_time: 0.0022 memory: 1008 2022/11/02 15:08:46 - mmengine - INFO - Epoch(val) [280][400/500] eta: 0:00:03 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 15:08:46 - mmengine - INFO - Epoch(val) [280][405/500] eta: 0:00:03 time: 0.0383 data_time: 0.0023 memory: 1008 2022/11/02 15:08:46 - mmengine - INFO - Epoch(val) [280][410/500] eta: 0:00:03 time: 0.0403 data_time: 0.0022 memory: 1008 2022/11/02 15:08:46 - mmengine - INFO - Epoch(val) [280][415/500] eta: 0:00:03 time: 0.0394 data_time: 0.0023 memory: 1008 2022/11/02 15:08:47 - mmengine - INFO - Epoch(val) [280][420/500] eta: 0:00:08 time: 0.1096 data_time: 0.0766 memory: 1008 2022/11/02 15:08:48 - mmengine - INFO - Epoch(val) [280][425/500] eta: 0:00:08 time: 0.1118 data_time: 0.0764 memory: 1008 2022/11/02 15:08:48 - mmengine - INFO - Epoch(val) [280][430/500] eta: 0:00:02 time: 0.0390 data_time: 0.0021 memory: 1008 2022/11/02 15:08:48 - mmengine - INFO - Epoch(val) [280][435/500] eta: 0:00:02 time: 0.0389 data_time: 0.0023 memory: 1008 2022/11/02 15:08:48 - mmengine - INFO - Epoch(val) [280][440/500] eta: 0:00:02 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 15:08:48 - mmengine - INFO - Epoch(val) [280][445/500] eta: 0:00:02 time: 0.0404 data_time: 0.0027 memory: 1008 2022/11/02 15:08:49 - mmengine - INFO - Epoch(val) [280][450/500] eta: 0:00:02 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 15:08:49 - mmengine - INFO - Epoch(val) [280][455/500] eta: 0:00:02 time: 0.0424 data_time: 0.0029 memory: 1008 2022/11/02 15:08:49 - mmengine - INFO - Epoch(val) [280][460/500] eta: 0:00:01 time: 0.0436 data_time: 0.0032 memory: 1008 2022/11/02 15:08:49 - mmengine - INFO - Epoch(val) [280][465/500] eta: 0:00:01 time: 0.0413 data_time: 0.0036 memory: 1008 2022/11/02 15:08:49 - mmengine - INFO - Epoch(val) [280][470/500] eta: 0:00:01 time: 0.0411 data_time: 0.0033 memory: 1008 2022/11/02 15:08:50 - mmengine - INFO - Epoch(val) [280][475/500] eta: 0:00:01 time: 0.0432 data_time: 0.0030 memory: 1008 2022/11/02 15:08:50 - mmengine - INFO - Epoch(val) [280][480/500] eta: 0:00:00 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/02 15:08:50 - mmengine - INFO - Epoch(val) [280][485/500] eta: 0:00:00 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 15:08:50 - mmengine - INFO - Epoch(val) [280][490/500] eta: 0:00:00 time: 0.0400 data_time: 0.0022 memory: 1008 2022/11/02 15:08:50 - mmengine - INFO - Epoch(val) [280][495/500] eta: 0:00:00 time: 0.0434 data_time: 0.0024 memory: 1008 2022/11/02 15:08:51 - mmengine - INFO - Epoch(val) [280][500/500] eta: 0:00:00 time: 0.0390 data_time: 0.0023 memory: 1008 2022/11/02 15:08:51 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8166, precision: 0.5342, hmean: 0.6458 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8166, precision: 0.6350, hmean: 0.7144 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8151, precision: 0.7060, hmean: 0.7566 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8031, precision: 0.7805, hmean: 0.7916 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7626, precision: 0.8539, hmean: 0.8057 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4242, precision: 0.9402, hmean: 0.5846 2022/11/02 15:08:51 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0014, precision: 0.7500, hmean: 0.0029 2022/11/02 15:08:51 - mmengine - INFO - Epoch(val) [280][500/500] icdar/precision: 0.8539 icdar/recall: 0.7626 icdar/hmean: 0.8057 2022/11/02 15:08:56 - mmengine - INFO - Epoch(train) [281][5/63] lr: 1.7026e-03 eta: 0:00:00 time: 0.7368 data_time: 0.2182 memory: 14901 loss: 2.1322 loss_prob: 1.2990 loss_thr: 0.6234 loss_db: 0.2098 2022/11/02 15:08:58 - mmengine - INFO - Epoch(train) [281][10/63] lr: 1.7026e-03 eta: 9:26:35 time: 0.7577 data_time: 0.2145 memory: 14901 loss: 1.8069 loss_prob: 1.0273 loss_thr: 0.6119 loss_db: 0.1677 2022/11/02 15:09:01 - mmengine - INFO - Epoch(train) [281][15/63] lr: 1.7026e-03 eta: 9:26:35 time: 0.4761 data_time: 0.0103 memory: 14901 loss: 1.8302 loss_prob: 1.0538 loss_thr: 0.6064 loss_db: 0.1700 2022/11/02 15:09:03 - mmengine - INFO - Epoch(train) [281][20/63] lr: 1.7026e-03 eta: 9:26:25 time: 0.4725 data_time: 0.0103 memory: 14901 loss: 1.9062 loss_prob: 1.1048 loss_thr: 0.6221 loss_db: 0.1793 2022/11/02 15:09:06 - mmengine - INFO - Epoch(train) [281][25/63] lr: 1.7026e-03 eta: 9:26:25 time: 0.5243 data_time: 0.0130 memory: 14901 loss: 1.8310 loss_prob: 1.0614 loss_thr: 0.5956 loss_db: 0.1740 2022/11/02 15:09:09 - mmengine - INFO - Epoch(train) [281][30/63] lr: 1.7026e-03 eta: 9:26:19 time: 0.5663 data_time: 0.0420 memory: 14901 loss: 1.7553 loss_prob: 1.0169 loss_thr: 0.5709 loss_db: 0.1675 2022/11/02 15:09:11 - mmengine - INFO - Epoch(train) [281][35/63] lr: 1.7026e-03 eta: 9:26:19 time: 0.5364 data_time: 0.0339 memory: 14901 loss: 1.7823 loss_prob: 1.0108 loss_thr: 0.6042 loss_db: 0.1673 2022/11/02 15:09:14 - mmengine - INFO - Epoch(train) [281][40/63] lr: 1.7026e-03 eta: 9:26:10 time: 0.5015 data_time: 0.0051 memory: 14901 loss: 1.7765 loss_prob: 1.0087 loss_thr: 0.6003 loss_db: 0.1675 2022/11/02 15:09:16 - mmengine - INFO - Epoch(train) [281][45/63] lr: 1.7026e-03 eta: 9:26:10 time: 0.5116 data_time: 0.0091 memory: 14901 loss: 1.6617 loss_prob: 0.9385 loss_thr: 0.5689 loss_db: 0.1543 2022/11/02 15:09:19 - mmengine - INFO - Epoch(train) [281][50/63] lr: 1.7026e-03 eta: 9:26:02 time: 0.5200 data_time: 0.0187 memory: 14901 loss: 1.6967 loss_prob: 0.9589 loss_thr: 0.5819 loss_db: 0.1560 2022/11/02 15:09:22 - mmengine - INFO - Epoch(train) [281][55/63] lr: 1.7026e-03 eta: 9:26:02 time: 0.5742 data_time: 0.0261 memory: 14901 loss: 1.7173 loss_prob: 0.9788 loss_thr: 0.5776 loss_db: 0.1610 2022/11/02 15:09:24 - mmengine - INFO - Epoch(train) [281][60/63] lr: 1.7026e-03 eta: 9:25:55 time: 0.5529 data_time: 0.0207 memory: 14901 loss: 1.6282 loss_prob: 0.9120 loss_thr: 0.5673 loss_db: 0.1488 2022/11/02 15:09:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:09:32 - mmengine - INFO - Epoch(train) [282][5/63] lr: 1.7010e-03 eta: 9:25:55 time: 0.8457 data_time: 0.2537 memory: 14901 loss: 1.7147 loss_prob: 0.9557 loss_thr: 0.6001 loss_db: 0.1589 2022/11/02 15:09:35 - mmengine - INFO - Epoch(train) [282][10/63] lr: 1.7010e-03 eta: 9:25:52 time: 0.8828 data_time: 0.2552 memory: 14901 loss: 1.5876 loss_prob: 0.8909 loss_thr: 0.5510 loss_db: 0.1456 2022/11/02 15:09:37 - mmengine - INFO - Epoch(train) [282][15/63] lr: 1.7010e-03 eta: 9:25:52 time: 0.5144 data_time: 0.0112 memory: 14901 loss: 1.6448 loss_prob: 0.9289 loss_thr: 0.5642 loss_db: 0.1517 2022/11/02 15:09:40 - mmengine - INFO - Epoch(train) [282][20/63] lr: 1.7010e-03 eta: 9:25:45 time: 0.5728 data_time: 0.0173 memory: 14901 loss: 1.6643 loss_prob: 0.9331 loss_thr: 0.5782 loss_db: 0.1530 2022/11/02 15:09:43 - mmengine - INFO - Epoch(train) [282][25/63] lr: 1.7010e-03 eta: 9:25:45 time: 0.5533 data_time: 0.0192 memory: 14901 loss: 1.5940 loss_prob: 0.8883 loss_thr: 0.5571 loss_db: 0.1486 2022/11/02 15:09:45 - mmengine - INFO - Epoch(train) [282][30/63] lr: 1.7010e-03 eta: 9:25:37 time: 0.5207 data_time: 0.0281 memory: 14901 loss: 1.5357 loss_prob: 0.8572 loss_thr: 0.5335 loss_db: 0.1450 2022/11/02 15:09:48 - mmengine - INFO - Epoch(train) [282][35/63] lr: 1.7010e-03 eta: 9:25:37 time: 0.5191 data_time: 0.0229 memory: 14901 loss: 1.6902 loss_prob: 0.9673 loss_thr: 0.5633 loss_db: 0.1597 2022/11/02 15:09:50 - mmengine - INFO - Epoch(train) [282][40/63] lr: 1.7010e-03 eta: 9:25:28 time: 0.4881 data_time: 0.0114 memory: 14901 loss: 1.8754 loss_prob: 1.0841 loss_thr: 0.6122 loss_db: 0.1791 2022/11/02 15:09:53 - mmengine - INFO - Epoch(train) [282][45/63] lr: 1.7010e-03 eta: 9:25:28 time: 0.4918 data_time: 0.0138 memory: 14901 loss: 1.7914 loss_prob: 1.0273 loss_thr: 0.5939 loss_db: 0.1701 2022/11/02 15:09:56 - mmengine - INFO - Epoch(train) [282][50/63] lr: 1.7010e-03 eta: 9:25:21 time: 0.5404 data_time: 0.0224 memory: 14901 loss: 1.7368 loss_prob: 0.9911 loss_thr: 0.5814 loss_db: 0.1643 2022/11/02 15:09:59 - mmengine - INFO - Epoch(train) [282][55/63] lr: 1.7010e-03 eta: 9:25:21 time: 0.5807 data_time: 0.0207 memory: 14901 loss: 1.7121 loss_prob: 0.9710 loss_thr: 0.5774 loss_db: 0.1637 2022/11/02 15:10:01 - mmengine - INFO - Epoch(train) [282][60/63] lr: 1.7010e-03 eta: 9:25:13 time: 0.5256 data_time: 0.0100 memory: 14901 loss: 1.7536 loss_prob: 1.0136 loss_thr: 0.5716 loss_db: 0.1684 2022/11/02 15:10:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:10:07 - mmengine - INFO - Epoch(train) [283][5/63] lr: 1.6993e-03 eta: 9:25:13 time: 0.6530 data_time: 0.2082 memory: 14901 loss: 1.7306 loss_prob: 0.9844 loss_thr: 0.5829 loss_db: 0.1633 2022/11/02 15:10:09 - mmengine - INFO - Epoch(train) [283][10/63] lr: 1.6993e-03 eta: 9:25:02 time: 0.6625 data_time: 0.2046 memory: 14901 loss: 1.7926 loss_prob: 1.0490 loss_thr: 0.5740 loss_db: 0.1697 2022/11/02 15:10:11 - mmengine - INFO - Epoch(train) [283][15/63] lr: 1.6993e-03 eta: 9:25:02 time: 0.4660 data_time: 0.0096 memory: 14901 loss: 1.6970 loss_prob: 0.9763 loss_thr: 0.5596 loss_db: 0.1611 2022/11/02 15:10:14 - mmengine - INFO - Epoch(train) [283][20/63] lr: 1.6993e-03 eta: 9:24:54 time: 0.5056 data_time: 0.0107 memory: 14901 loss: 1.6528 loss_prob: 0.9252 loss_thr: 0.5701 loss_db: 0.1576 2022/11/02 15:10:18 - mmengine - INFO - Epoch(train) [283][25/63] lr: 1.6993e-03 eta: 9:24:54 time: 0.6298 data_time: 0.0201 memory: 14901 loss: 1.5899 loss_prob: 0.8789 loss_thr: 0.5626 loss_db: 0.1485 2022/11/02 15:10:20 - mmengine - INFO - Epoch(train) [283][30/63] lr: 1.6993e-03 eta: 9:24:49 time: 0.6145 data_time: 0.0397 memory: 14901 loss: 1.7048 loss_prob: 0.9800 loss_thr: 0.5674 loss_db: 0.1574 2022/11/02 15:10:22 - mmengine - INFO - Epoch(train) [283][35/63] lr: 1.6993e-03 eta: 9:24:49 time: 0.4932 data_time: 0.0256 memory: 14901 loss: 1.9409 loss_prob: 1.1631 loss_thr: 0.5986 loss_db: 0.1792 2022/11/02 15:10:25 - mmengine - INFO - Epoch(train) [283][40/63] lr: 1.6993e-03 eta: 9:24:39 time: 0.4787 data_time: 0.0110 memory: 14901 loss: 1.8153 loss_prob: 1.0575 loss_thr: 0.5894 loss_db: 0.1684 2022/11/02 15:10:27 - mmengine - INFO - Epoch(train) [283][45/63] lr: 1.6993e-03 eta: 9:24:39 time: 0.4687 data_time: 0.0140 memory: 14901 loss: 1.7501 loss_prob: 0.9980 loss_thr: 0.5857 loss_db: 0.1664 2022/11/02 15:10:30 - mmengine - INFO - Epoch(train) [283][50/63] lr: 1.6993e-03 eta: 9:24:30 time: 0.4754 data_time: 0.0149 memory: 14901 loss: 1.8796 loss_prob: 1.0896 loss_thr: 0.6084 loss_db: 0.1816 2022/11/02 15:10:32 - mmengine - INFO - Epoch(train) [283][55/63] lr: 1.6993e-03 eta: 9:24:30 time: 0.5005 data_time: 0.0291 memory: 14901 loss: 1.7381 loss_prob: 0.9967 loss_thr: 0.5758 loss_db: 0.1656 2022/11/02 15:10:35 - mmengine - INFO - Epoch(train) [283][60/63] lr: 1.6993e-03 eta: 9:24:21 time: 0.5008 data_time: 0.0249 memory: 14901 loss: 1.6563 loss_prob: 0.9292 loss_thr: 0.5710 loss_db: 0.1562 2022/11/02 15:10:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:10:41 - mmengine - INFO - Epoch(train) [284][5/63] lr: 1.6976e-03 eta: 9:24:21 time: 0.7294 data_time: 0.2655 memory: 14901 loss: 1.7448 loss_prob: 0.9889 loss_thr: 0.5945 loss_db: 0.1613 2022/11/02 15:10:43 - mmengine - INFO - Epoch(train) [284][10/63] lr: 1.6976e-03 eta: 9:24:14 time: 0.7676 data_time: 0.2717 memory: 14901 loss: 1.6661 loss_prob: 0.9397 loss_thr: 0.5742 loss_db: 0.1523 2022/11/02 15:10:46 - mmengine - INFO - Epoch(train) [284][15/63] lr: 1.6976e-03 eta: 9:24:14 time: 0.5412 data_time: 0.0113 memory: 14901 loss: 1.7585 loss_prob: 0.9948 loss_thr: 0.5981 loss_db: 0.1656 2022/11/02 15:10:49 - mmengine - INFO - Epoch(train) [284][20/63] lr: 1.6976e-03 eta: 9:24:06 time: 0.5364 data_time: 0.0078 memory: 14901 loss: 1.8385 loss_prob: 1.0559 loss_thr: 0.6089 loss_db: 0.1736 2022/11/02 15:10:53 - mmengine - INFO - Epoch(train) [284][25/63] lr: 1.6976e-03 eta: 9:24:06 time: 0.6375 data_time: 0.0148 memory: 14901 loss: 1.8151 loss_prob: 1.0562 loss_thr: 0.5871 loss_db: 0.1718 2022/11/02 15:10:56 - mmengine - INFO - Epoch(train) [284][30/63] lr: 1.6976e-03 eta: 9:24:04 time: 0.7058 data_time: 0.0410 memory: 14901 loss: 1.7553 loss_prob: 1.0093 loss_thr: 0.5775 loss_db: 0.1685 2022/11/02 15:10:59 - mmengine - INFO - Epoch(train) [284][35/63] lr: 1.6976e-03 eta: 9:24:04 time: 0.6001 data_time: 0.0365 memory: 14901 loss: 1.6626 loss_prob: 0.9349 loss_thr: 0.5701 loss_db: 0.1576 2022/11/02 15:11:01 - mmengine - INFO - Epoch(train) [284][40/63] lr: 1.6976e-03 eta: 9:23:57 time: 0.5358 data_time: 0.0118 memory: 14901 loss: 1.6358 loss_prob: 0.9204 loss_thr: 0.5613 loss_db: 0.1541 2022/11/02 15:11:04 - mmengine - INFO - Epoch(train) [284][45/63] lr: 1.6976e-03 eta: 9:23:57 time: 0.4857 data_time: 0.0100 memory: 14901 loss: 1.8063 loss_prob: 1.0452 loss_thr: 0.5859 loss_db: 0.1752 2022/11/02 15:11:07 - mmengine - INFO - Epoch(train) [284][50/63] lr: 1.6976e-03 eta: 9:23:49 time: 0.5229 data_time: 0.0207 memory: 14901 loss: 1.8101 loss_prob: 1.0474 loss_thr: 0.5876 loss_db: 0.1751 2022/11/02 15:11:10 - mmengine - INFO - Epoch(train) [284][55/63] lr: 1.6976e-03 eta: 9:23:49 time: 0.6432 data_time: 0.0227 memory: 14901 loss: 1.6886 loss_prob: 0.9640 loss_thr: 0.5632 loss_db: 0.1614 2022/11/02 15:11:13 - mmengine - INFO - Epoch(train) [284][60/63] lr: 1.6976e-03 eta: 9:23:45 time: 0.6453 data_time: 0.0120 memory: 14901 loss: 1.7368 loss_prob: 0.9930 loss_thr: 0.5837 loss_db: 0.1602 2022/11/02 15:11:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:11:20 - mmengine - INFO - Epoch(train) [285][5/63] lr: 1.6960e-03 eta: 9:23:45 time: 0.7568 data_time: 0.2440 memory: 14901 loss: 1.6746 loss_prob: 0.9316 loss_thr: 0.5916 loss_db: 0.1514 2022/11/02 15:11:22 - mmengine - INFO - Epoch(train) [285][10/63] lr: 1.6960e-03 eta: 9:23:37 time: 0.7506 data_time: 0.2405 memory: 14901 loss: 1.7367 loss_prob: 0.9736 loss_thr: 0.6033 loss_db: 0.1597 2022/11/02 15:11:25 - mmengine - INFO - Epoch(train) [285][15/63] lr: 1.6960e-03 eta: 9:23:37 time: 0.5338 data_time: 0.0061 memory: 14901 loss: 1.8622 loss_prob: 1.0825 loss_thr: 0.6091 loss_db: 0.1706 2022/11/02 15:11:28 - mmengine - INFO - Epoch(train) [285][20/63] lr: 1.6960e-03 eta: 9:23:32 time: 0.6187 data_time: 0.0098 memory: 14901 loss: 1.8053 loss_prob: 1.0520 loss_thr: 0.5839 loss_db: 0.1694 2022/11/02 15:11:31 - mmengine - INFO - Epoch(train) [285][25/63] lr: 1.6960e-03 eta: 9:23:32 time: 0.6399 data_time: 0.0469 memory: 14901 loss: 1.8225 loss_prob: 1.0526 loss_thr: 0.5964 loss_db: 0.1736 2022/11/02 15:11:34 - mmengine - INFO - Epoch(train) [285][30/63] lr: 1.6960e-03 eta: 9:23:25 time: 0.5418 data_time: 0.0448 memory: 14901 loss: 1.7428 loss_prob: 0.9965 loss_thr: 0.5829 loss_db: 0.1635 2022/11/02 15:11:37 - mmengine - INFO - Epoch(train) [285][35/63] lr: 1.6960e-03 eta: 9:23:25 time: 0.5256 data_time: 0.0073 memory: 14901 loss: 1.5909 loss_prob: 0.8768 loss_thr: 0.5693 loss_db: 0.1448 2022/11/02 15:11:39 - mmengine - INFO - Epoch(train) [285][40/63] lr: 1.6960e-03 eta: 9:23:17 time: 0.5086 data_time: 0.0097 memory: 14901 loss: 1.6391 loss_prob: 0.9216 loss_thr: 0.5680 loss_db: 0.1495 2022/11/02 15:11:42 - mmengine - INFO - Epoch(train) [285][45/63] lr: 1.6960e-03 eta: 9:23:17 time: 0.5048 data_time: 0.0105 memory: 14901 loss: 1.7274 loss_prob: 0.9932 loss_thr: 0.5688 loss_db: 0.1653 2022/11/02 15:11:44 - mmengine - INFO - Epoch(train) [285][50/63] lr: 1.6960e-03 eta: 9:23:08 time: 0.5155 data_time: 0.0245 memory: 14901 loss: 1.7455 loss_prob: 0.9991 loss_thr: 0.5791 loss_db: 0.1673 2022/11/02 15:11:47 - mmengine - INFO - Epoch(train) [285][55/63] lr: 1.6960e-03 eta: 9:23:08 time: 0.4972 data_time: 0.0242 memory: 14901 loss: 1.7541 loss_prob: 1.0101 loss_thr: 0.5797 loss_db: 0.1643 2022/11/02 15:11:49 - mmengine - INFO - Epoch(train) [285][60/63] lr: 1.6960e-03 eta: 9:22:59 time: 0.4719 data_time: 0.0060 memory: 14901 loss: 1.6522 loss_prob: 0.9440 loss_thr: 0.5530 loss_db: 0.1552 2022/11/02 15:11:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:11:56 - mmengine - INFO - Epoch(train) [286][5/63] lr: 1.6943e-03 eta: 9:22:59 time: 0.7579 data_time: 0.2408 memory: 14901 loss: 1.6646 loss_prob: 0.9438 loss_thr: 0.5630 loss_db: 0.1578 2022/11/02 15:11:58 - mmengine - INFO - Epoch(train) [286][10/63] lr: 1.6943e-03 eta: 9:22:53 time: 0.8099 data_time: 0.2451 memory: 14901 loss: 1.7018 loss_prob: 0.9586 loss_thr: 0.5809 loss_db: 0.1623 2022/11/02 15:12:01 - mmengine - INFO - Epoch(train) [286][15/63] lr: 1.6943e-03 eta: 9:22:53 time: 0.5205 data_time: 0.0108 memory: 14901 loss: 1.7971 loss_prob: 1.0271 loss_thr: 0.5971 loss_db: 0.1729 2022/11/02 15:12:03 - mmengine - INFO - Epoch(train) [286][20/63] lr: 1.6943e-03 eta: 9:22:44 time: 0.4912 data_time: 0.0063 memory: 14901 loss: 1.8632 loss_prob: 1.0858 loss_thr: 0.5999 loss_db: 0.1775 2022/11/02 15:12:06 - mmengine - INFO - Epoch(train) [286][25/63] lr: 1.6943e-03 eta: 9:22:44 time: 0.5718 data_time: 0.0295 memory: 14901 loss: 1.7616 loss_prob: 1.0167 loss_thr: 0.5785 loss_db: 0.1664 2022/11/02 15:12:09 - mmengine - INFO - Epoch(train) [286][30/63] lr: 1.6943e-03 eta: 9:22:38 time: 0.5816 data_time: 0.0439 memory: 14901 loss: 1.6994 loss_prob: 0.9754 loss_thr: 0.5591 loss_db: 0.1649 2022/11/02 15:12:12 - mmengine - INFO - Epoch(train) [286][35/63] lr: 1.6943e-03 eta: 9:22:38 time: 0.5019 data_time: 0.0217 memory: 14901 loss: 1.7079 loss_prob: 0.9768 loss_thr: 0.5678 loss_db: 0.1633 2022/11/02 15:12:14 - mmengine - INFO - Epoch(train) [286][40/63] lr: 1.6943e-03 eta: 9:22:30 time: 0.5203 data_time: 0.0115 memory: 14901 loss: 1.7687 loss_prob: 1.0202 loss_thr: 0.5849 loss_db: 0.1636 2022/11/02 15:12:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:12:17 - mmengine - INFO - Epoch(train) [286][45/63] lr: 1.6943e-03 eta: 9:22:30 time: 0.5283 data_time: 0.0093 memory: 14901 loss: 1.7998 loss_prob: 1.0602 loss_thr: 0.5649 loss_db: 0.1747 2022/11/02 15:12:20 - mmengine - INFO - Epoch(train) [286][50/63] lr: 1.6943e-03 eta: 9:22:23 time: 0.5431 data_time: 0.0252 memory: 14901 loss: 1.6933 loss_prob: 0.9886 loss_thr: 0.5372 loss_db: 0.1676 2022/11/02 15:12:22 - mmengine - INFO - Epoch(train) [286][55/63] lr: 1.6943e-03 eta: 9:22:23 time: 0.5315 data_time: 0.0280 memory: 14901 loss: 1.6162 loss_prob: 0.9262 loss_thr: 0.5378 loss_db: 0.1521 2022/11/02 15:12:25 - mmengine - INFO - Epoch(train) [286][60/63] lr: 1.6943e-03 eta: 9:22:14 time: 0.4944 data_time: 0.0091 memory: 14901 loss: 1.6765 loss_prob: 0.9521 loss_thr: 0.5709 loss_db: 0.1535 2022/11/02 15:12:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:12:32 - mmengine - INFO - Epoch(train) [287][5/63] lr: 1.6926e-03 eta: 9:22:14 time: 0.8556 data_time: 0.2776 memory: 14901 loss: 1.6716 loss_prob: 0.9433 loss_thr: 0.5705 loss_db: 0.1578 2022/11/02 15:12:35 - mmengine - INFO - Epoch(train) [287][10/63] lr: 1.6926e-03 eta: 9:22:10 time: 0.8843 data_time: 0.2810 memory: 14901 loss: 1.6072 loss_prob: 0.9024 loss_thr: 0.5566 loss_db: 0.1482 2022/11/02 15:12:37 - mmengine - INFO - Epoch(train) [287][15/63] lr: 1.6926e-03 eta: 9:22:10 time: 0.5194 data_time: 0.0111 memory: 14901 loss: 1.6517 loss_prob: 0.9383 loss_thr: 0.5579 loss_db: 0.1556 2022/11/02 15:12:40 - mmengine - INFO - Epoch(train) [287][20/63] lr: 1.6926e-03 eta: 9:22:02 time: 0.5099 data_time: 0.0106 memory: 14901 loss: 1.6075 loss_prob: 0.9041 loss_thr: 0.5500 loss_db: 0.1533 2022/11/02 15:12:43 - mmengine - INFO - Epoch(train) [287][25/63] lr: 1.6926e-03 eta: 9:22:02 time: 0.5260 data_time: 0.0399 memory: 14901 loss: 1.6253 loss_prob: 0.8983 loss_thr: 0.5754 loss_db: 0.1517 2022/11/02 15:12:45 - mmengine - INFO - Epoch(train) [287][30/63] lr: 1.6926e-03 eta: 9:21:54 time: 0.5316 data_time: 0.0376 memory: 14901 loss: 1.6479 loss_prob: 0.9139 loss_thr: 0.5815 loss_db: 0.1525 2022/11/02 15:12:48 - mmengine - INFO - Epoch(train) [287][35/63] lr: 1.6926e-03 eta: 9:21:54 time: 0.5557 data_time: 0.0062 memory: 14901 loss: 1.6783 loss_prob: 0.9439 loss_thr: 0.5790 loss_db: 0.1554 2022/11/02 15:12:51 - mmengine - INFO - Epoch(train) [287][40/63] lr: 1.6926e-03 eta: 9:21:49 time: 0.5974 data_time: 0.0086 memory: 14901 loss: 1.7465 loss_prob: 0.9884 loss_thr: 0.5945 loss_db: 0.1635 2022/11/02 15:12:54 - mmengine - INFO - Epoch(train) [287][45/63] lr: 1.6926e-03 eta: 9:21:49 time: 0.5499 data_time: 0.0092 memory: 14901 loss: 1.7912 loss_prob: 1.0349 loss_thr: 0.5870 loss_db: 0.1693 2022/11/02 15:12:56 - mmengine - INFO - Epoch(train) [287][50/63] lr: 1.6926e-03 eta: 9:21:42 time: 0.5448 data_time: 0.0231 memory: 14901 loss: 1.7334 loss_prob: 0.9971 loss_thr: 0.5714 loss_db: 0.1649 2022/11/02 15:12:59 - mmengine - INFO - Epoch(train) [287][55/63] lr: 1.6926e-03 eta: 9:21:42 time: 0.5371 data_time: 0.0252 memory: 14901 loss: 1.6676 loss_prob: 0.9637 loss_thr: 0.5476 loss_db: 0.1562 2022/11/02 15:13:02 - mmengine - INFO - Epoch(train) [287][60/63] lr: 1.6926e-03 eta: 9:21:35 time: 0.5604 data_time: 0.0097 memory: 14901 loss: 1.6334 loss_prob: 0.9354 loss_thr: 0.5460 loss_db: 0.1521 2022/11/02 15:13:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:13:09 - mmengine - INFO - Epoch(train) [288][5/63] lr: 1.6910e-03 eta: 9:21:35 time: 0.7736 data_time: 0.2247 memory: 14901 loss: 1.4628 loss_prob: 0.7995 loss_thr: 0.5280 loss_db: 0.1353 2022/11/02 15:13:12 - mmengine - INFO - Epoch(train) [288][10/63] lr: 1.6910e-03 eta: 9:21:30 time: 0.8297 data_time: 0.2264 memory: 14901 loss: 1.5043 loss_prob: 0.8268 loss_thr: 0.5390 loss_db: 0.1385 2022/11/02 15:13:14 - mmengine - INFO - Epoch(train) [288][15/63] lr: 1.6910e-03 eta: 9:21:30 time: 0.5195 data_time: 0.0115 memory: 14901 loss: 1.5720 loss_prob: 0.8724 loss_thr: 0.5526 loss_db: 0.1469 2022/11/02 15:13:16 - mmengine - INFO - Epoch(train) [288][20/63] lr: 1.6910e-03 eta: 9:21:21 time: 0.4934 data_time: 0.0078 memory: 14901 loss: 1.4512 loss_prob: 0.7950 loss_thr: 0.5229 loss_db: 0.1333 2022/11/02 15:13:19 - mmengine - INFO - Epoch(train) [288][25/63] lr: 1.6910e-03 eta: 9:21:21 time: 0.4994 data_time: 0.0236 memory: 14901 loss: 1.5021 loss_prob: 0.8431 loss_thr: 0.5170 loss_db: 0.1419 2022/11/02 15:13:22 - mmengine - INFO - Epoch(train) [288][30/63] lr: 1.6910e-03 eta: 9:21:13 time: 0.5312 data_time: 0.0403 memory: 14901 loss: 1.7346 loss_prob: 1.0084 loss_thr: 0.5606 loss_db: 0.1656 2022/11/02 15:13:25 - mmengine - INFO - Epoch(train) [288][35/63] lr: 1.6910e-03 eta: 9:21:13 time: 0.6145 data_time: 0.0251 memory: 14901 loss: 1.7347 loss_prob: 0.9915 loss_thr: 0.5790 loss_db: 0.1641 2022/11/02 15:13:28 - mmengine - INFO - Epoch(train) [288][40/63] lr: 1.6910e-03 eta: 9:21:09 time: 0.6366 data_time: 0.0063 memory: 14901 loss: 1.7510 loss_prob: 0.9960 loss_thr: 0.5881 loss_db: 0.1669 2022/11/02 15:13:31 - mmengine - INFO - Epoch(train) [288][45/63] lr: 1.6910e-03 eta: 9:21:09 time: 0.5408 data_time: 0.0071 memory: 14901 loss: 1.7714 loss_prob: 1.0134 loss_thr: 0.5928 loss_db: 0.1652 2022/11/02 15:13:33 - mmengine - INFO - Epoch(train) [288][50/63] lr: 1.6910e-03 eta: 9:21:01 time: 0.5209 data_time: 0.0170 memory: 14901 loss: 1.6662 loss_prob: 0.9366 loss_thr: 0.5769 loss_db: 0.1527 2022/11/02 15:13:36 - mmengine - INFO - Epoch(train) [288][55/63] lr: 1.6910e-03 eta: 9:21:01 time: 0.5707 data_time: 0.0273 memory: 14901 loss: 1.6829 loss_prob: 0.9500 loss_thr: 0.5813 loss_db: 0.1516 2022/11/02 15:13:39 - mmengine - INFO - Epoch(train) [288][60/63] lr: 1.6910e-03 eta: 9:20:54 time: 0.5474 data_time: 0.0177 memory: 14901 loss: 1.7179 loss_prob: 0.9764 loss_thr: 0.5845 loss_db: 0.1570 2022/11/02 15:13:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:13:46 - mmengine - INFO - Epoch(train) [289][5/63] lr: 1.6893e-03 eta: 9:20:54 time: 0.8467 data_time: 0.2327 memory: 14901 loss: 1.7193 loss_prob: 0.9897 loss_thr: 0.5631 loss_db: 0.1665 2022/11/02 15:13:50 - mmengine - INFO - Epoch(train) [289][10/63] lr: 1.6893e-03 eta: 9:20:52 time: 0.9526 data_time: 0.2324 memory: 14901 loss: 1.6083 loss_prob: 0.9134 loss_thr: 0.5452 loss_db: 0.1497 2022/11/02 15:13:52 - mmengine - INFO - Epoch(train) [289][15/63] lr: 1.6893e-03 eta: 9:20:52 time: 0.5880 data_time: 0.0070 memory: 14901 loss: 1.6994 loss_prob: 0.9730 loss_thr: 0.5664 loss_db: 0.1600 2022/11/02 15:13:55 - mmengine - INFO - Epoch(train) [289][20/63] lr: 1.6893e-03 eta: 9:20:44 time: 0.5035 data_time: 0.0055 memory: 14901 loss: 1.7631 loss_prob: 1.0072 loss_thr: 0.5927 loss_db: 0.1632 2022/11/02 15:13:58 - mmengine - INFO - Epoch(train) [289][25/63] lr: 1.6893e-03 eta: 9:20:44 time: 0.5370 data_time: 0.0297 memory: 14901 loss: 1.6872 loss_prob: 0.9447 loss_thr: 0.5856 loss_db: 0.1570 2022/11/02 15:14:01 - mmengine - INFO - Epoch(train) [289][30/63] lr: 1.6893e-03 eta: 9:20:40 time: 0.6481 data_time: 0.0456 memory: 14901 loss: 1.6855 loss_prob: 0.9393 loss_thr: 0.5881 loss_db: 0.1581 2022/11/02 15:14:04 - mmengine - INFO - Epoch(train) [289][35/63] lr: 1.6893e-03 eta: 9:20:40 time: 0.6141 data_time: 0.0239 memory: 14901 loss: 1.6996 loss_prob: 0.9502 loss_thr: 0.5918 loss_db: 0.1575 2022/11/02 15:14:06 - mmengine - INFO - Epoch(train) [289][40/63] lr: 1.6893e-03 eta: 9:20:32 time: 0.5079 data_time: 0.0077 memory: 14901 loss: 1.6467 loss_prob: 0.9153 loss_thr: 0.5771 loss_db: 0.1543 2022/11/02 15:14:08 - mmengine - INFO - Epoch(train) [289][45/63] lr: 1.6893e-03 eta: 9:20:32 time: 0.4693 data_time: 0.0049 memory: 14901 loss: 1.6784 loss_prob: 0.9434 loss_thr: 0.5745 loss_db: 0.1605 2022/11/02 15:14:11 - mmengine - INFO - Epoch(train) [289][50/63] lr: 1.6893e-03 eta: 9:20:23 time: 0.5015 data_time: 0.0193 memory: 14901 loss: 1.7318 loss_prob: 0.9880 loss_thr: 0.5795 loss_db: 0.1643 2022/11/02 15:14:14 - mmengine - INFO - Epoch(train) [289][55/63] lr: 1.6893e-03 eta: 9:20:23 time: 0.5410 data_time: 0.0309 memory: 14901 loss: 1.7218 loss_prob: 0.9719 loss_thr: 0.5894 loss_db: 0.1605 2022/11/02 15:14:16 - mmengine - INFO - Epoch(train) [289][60/63] lr: 1.6893e-03 eta: 9:20:15 time: 0.5109 data_time: 0.0192 memory: 14901 loss: 1.6398 loss_prob: 0.9143 loss_thr: 0.5736 loss_db: 0.1519 2022/11/02 15:14:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:14:24 - mmengine - INFO - Epoch(train) [290][5/63] lr: 1.6876e-03 eta: 9:20:15 time: 0.8482 data_time: 0.2227 memory: 14901 loss: 1.5858 loss_prob: 0.8835 loss_thr: 0.5526 loss_db: 0.1497 2022/11/02 15:14:26 - mmengine - INFO - Epoch(train) [290][10/63] lr: 1.6876e-03 eta: 9:20:11 time: 0.8824 data_time: 0.2296 memory: 14901 loss: 1.5965 loss_prob: 0.8951 loss_thr: 0.5505 loss_db: 0.1509 2022/11/02 15:14:29 - mmengine - INFO - Epoch(train) [290][15/63] lr: 1.6876e-03 eta: 9:20:11 time: 0.5326 data_time: 0.0151 memory: 14901 loss: 1.5829 loss_prob: 0.8783 loss_thr: 0.5574 loss_db: 0.1472 2022/11/02 15:14:32 - mmengine - INFO - Epoch(train) [290][20/63] lr: 1.6876e-03 eta: 9:20:03 time: 0.5126 data_time: 0.0106 memory: 14901 loss: 1.6368 loss_prob: 0.9135 loss_thr: 0.5723 loss_db: 0.1510 2022/11/02 15:14:34 - mmengine - INFO - Epoch(train) [290][25/63] lr: 1.6876e-03 eta: 9:20:03 time: 0.5238 data_time: 0.0273 memory: 14901 loss: 1.6403 loss_prob: 0.9164 loss_thr: 0.5721 loss_db: 0.1518 2022/11/02 15:14:38 - mmengine - INFO - Epoch(train) [290][30/63] lr: 1.6876e-03 eta: 9:19:58 time: 0.5984 data_time: 0.0418 memory: 14901 loss: 1.7072 loss_prob: 0.9880 loss_thr: 0.5572 loss_db: 0.1620 2022/11/02 15:14:40 - mmengine - INFO - Epoch(train) [290][35/63] lr: 1.6876e-03 eta: 9:19:58 time: 0.5481 data_time: 0.0218 memory: 14901 loss: 1.7183 loss_prob: 0.9963 loss_thr: 0.5572 loss_db: 0.1648 2022/11/02 15:14:43 - mmengine - INFO - Epoch(train) [290][40/63] lr: 1.6876e-03 eta: 9:19:50 time: 0.5349 data_time: 0.0081 memory: 14901 loss: 1.5934 loss_prob: 0.8925 loss_thr: 0.5525 loss_db: 0.1484 2022/11/02 15:14:45 - mmengine - INFO - Epoch(train) [290][45/63] lr: 1.6876e-03 eta: 9:19:50 time: 0.5339 data_time: 0.0097 memory: 14901 loss: 1.7143 loss_prob: 0.9747 loss_thr: 0.5820 loss_db: 0.1577 2022/11/02 15:14:48 - mmengine - INFO - Epoch(train) [290][50/63] lr: 1.6876e-03 eta: 9:19:41 time: 0.4923 data_time: 0.0194 memory: 14901 loss: 1.7723 loss_prob: 1.0092 loss_thr: 0.5952 loss_db: 0.1679 2022/11/02 15:14:50 - mmengine - INFO - Epoch(train) [290][55/63] lr: 1.6876e-03 eta: 9:19:41 time: 0.5138 data_time: 0.0375 memory: 14901 loss: 1.7297 loss_prob: 0.9862 loss_thr: 0.5750 loss_db: 0.1685 2022/11/02 15:14:53 - mmengine - INFO - Epoch(train) [290][60/63] lr: 1.6876e-03 eta: 9:19:34 time: 0.5218 data_time: 0.0276 memory: 14901 loss: 1.7707 loss_prob: 1.0085 loss_thr: 0.5923 loss_db: 0.1700 2022/11/02 15:14:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:15:02 - mmengine - INFO - Epoch(train) [291][5/63] lr: 1.6859e-03 eta: 9:19:34 time: 0.9841 data_time: 0.2108 memory: 14901 loss: 1.6932 loss_prob: 0.9599 loss_thr: 0.5756 loss_db: 0.1577 2022/11/02 15:15:05 - mmengine - INFO - Epoch(train) [291][10/63] lr: 1.6859e-03 eta: 9:19:36 time: 1.0758 data_time: 0.2262 memory: 14901 loss: 1.5898 loss_prob: 0.8859 loss_thr: 0.5542 loss_db: 0.1498 2022/11/02 15:15:09 - mmengine - INFO - Epoch(train) [291][15/63] lr: 1.6859e-03 eta: 9:19:36 time: 0.6710 data_time: 0.0249 memory: 14901 loss: 1.5809 loss_prob: 0.8749 loss_thr: 0.5587 loss_db: 0.1473 2022/11/02 15:15:11 - mmengine - INFO - Epoch(train) [291][20/63] lr: 1.6859e-03 eta: 9:19:30 time: 0.5826 data_time: 0.0099 memory: 14901 loss: 1.5872 loss_prob: 0.8825 loss_thr: 0.5593 loss_db: 0.1454 2022/11/02 15:15:14 - mmengine - INFO - Epoch(train) [291][25/63] lr: 1.6859e-03 eta: 9:19:30 time: 0.4983 data_time: 0.0277 memory: 14901 loss: 1.7178 loss_prob: 0.9762 loss_thr: 0.5841 loss_db: 0.1575 2022/11/02 15:15:16 - mmengine - INFO - Epoch(train) [291][30/63] lr: 1.6859e-03 eta: 9:19:22 time: 0.5226 data_time: 0.0301 memory: 14901 loss: 1.7861 loss_prob: 1.0267 loss_thr: 0.5909 loss_db: 0.1685 2022/11/02 15:15:19 - mmengine - INFO - Epoch(train) [291][35/63] lr: 1.6859e-03 eta: 9:19:22 time: 0.5104 data_time: 0.0193 memory: 14901 loss: 1.6818 loss_prob: 0.9602 loss_thr: 0.5622 loss_db: 0.1594 2022/11/02 15:15:22 - mmengine - INFO - Epoch(train) [291][40/63] lr: 1.6859e-03 eta: 9:19:15 time: 0.5625 data_time: 0.0163 memory: 14901 loss: 1.6749 loss_prob: 0.9456 loss_thr: 0.5746 loss_db: 0.1547 2022/11/02 15:15:24 - mmengine - INFO - Epoch(train) [291][45/63] lr: 1.6859e-03 eta: 9:19:15 time: 0.5447 data_time: 0.0073 memory: 14901 loss: 1.6418 loss_prob: 0.9056 loss_thr: 0.5861 loss_db: 0.1500 2022/11/02 15:15:27 - mmengine - INFO - Epoch(train) [291][50/63] lr: 1.6859e-03 eta: 9:19:08 time: 0.5474 data_time: 0.0199 memory: 14901 loss: 1.7026 loss_prob: 0.9450 loss_thr: 0.5984 loss_db: 0.1592 2022/11/02 15:15:30 - mmengine - INFO - Epoch(train) [291][55/63] lr: 1.6859e-03 eta: 9:19:08 time: 0.5539 data_time: 0.0211 memory: 14901 loss: 1.7474 loss_prob: 0.9897 loss_thr: 0.5934 loss_db: 0.1644 2022/11/02 15:15:32 - mmengine - INFO - Epoch(train) [291][60/63] lr: 1.6859e-03 eta: 9:19:00 time: 0.5079 data_time: 0.0139 memory: 14901 loss: 1.7098 loss_prob: 0.9644 loss_thr: 0.5853 loss_db: 0.1601 2022/11/02 15:15:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:15:39 - mmengine - INFO - Epoch(train) [292][5/63] lr: 1.6843e-03 eta: 9:19:00 time: 0.7738 data_time: 0.2025 memory: 14901 loss: 1.7684 loss_prob: 1.0097 loss_thr: 0.5896 loss_db: 0.1691 2022/11/02 15:15:42 - mmengine - INFO - Epoch(train) [292][10/63] lr: 1.6843e-03 eta: 9:18:56 time: 0.8637 data_time: 0.2044 memory: 14901 loss: 1.6678 loss_prob: 0.9530 loss_thr: 0.5594 loss_db: 0.1554 2022/11/02 15:15:45 - mmengine - INFO - Epoch(train) [292][15/63] lr: 1.6843e-03 eta: 9:18:56 time: 0.5889 data_time: 0.0156 memory: 14901 loss: 1.5722 loss_prob: 0.8904 loss_thr: 0.5370 loss_db: 0.1448 2022/11/02 15:15:48 - mmengine - INFO - Epoch(train) [292][20/63] lr: 1.6843e-03 eta: 9:18:49 time: 0.5563 data_time: 0.0095 memory: 14901 loss: 1.6200 loss_prob: 0.9137 loss_thr: 0.5550 loss_db: 0.1513 2022/11/02 15:15:51 - mmengine - INFO - Epoch(train) [292][25/63] lr: 1.6843e-03 eta: 9:18:49 time: 0.5563 data_time: 0.0185 memory: 14901 loss: 1.6238 loss_prob: 0.9076 loss_thr: 0.5646 loss_db: 0.1516 2022/11/02 15:15:53 - mmengine - INFO - Epoch(train) [292][30/63] lr: 1.6843e-03 eta: 9:18:41 time: 0.5121 data_time: 0.0304 memory: 14901 loss: 1.5544 loss_prob: 0.8674 loss_thr: 0.5428 loss_db: 0.1442 2022/11/02 15:15:56 - mmengine - INFO - Epoch(train) [292][35/63] lr: 1.6843e-03 eta: 9:18:41 time: 0.5059 data_time: 0.0255 memory: 14901 loss: 1.7079 loss_prob: 0.9968 loss_thr: 0.5534 loss_db: 0.1576 2022/11/02 15:15:58 - mmengine - INFO - Epoch(train) [292][40/63] lr: 1.6843e-03 eta: 9:18:33 time: 0.5408 data_time: 0.0141 memory: 14901 loss: 1.7732 loss_prob: 1.0453 loss_thr: 0.5617 loss_db: 0.1662 2022/11/02 15:16:01 - mmengine - INFO - Epoch(train) [292][45/63] lr: 1.6843e-03 eta: 9:18:33 time: 0.5135 data_time: 0.0059 memory: 14901 loss: 1.7008 loss_prob: 0.9879 loss_thr: 0.5500 loss_db: 0.1629 2022/11/02 15:16:04 - mmengine - INFO - Epoch(train) [292][50/63] lr: 1.6843e-03 eta: 9:18:26 time: 0.5315 data_time: 0.0185 memory: 14901 loss: 1.6645 loss_prob: 0.9353 loss_thr: 0.5738 loss_db: 0.1554 2022/11/02 15:16:06 - mmengine - INFO - Epoch(train) [292][55/63] lr: 1.6843e-03 eta: 9:18:26 time: 0.5636 data_time: 0.0276 memory: 14901 loss: 1.6830 loss_prob: 0.9279 loss_thr: 0.6007 loss_db: 0.1544 2022/11/02 15:16:09 - mmengine - INFO - Epoch(train) [292][60/63] lr: 1.6843e-03 eta: 9:18:18 time: 0.5254 data_time: 0.0177 memory: 14901 loss: 1.6055 loss_prob: 0.8971 loss_thr: 0.5581 loss_db: 0.1503 2022/11/02 15:16:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:16:17 - mmengine - INFO - Epoch(train) [293][5/63] lr: 1.6826e-03 eta: 9:18:18 time: 0.8462 data_time: 0.2268 memory: 14901 loss: 1.5618 loss_prob: 0.8671 loss_thr: 0.5512 loss_db: 0.1436 2022/11/02 15:16:19 - mmengine - INFO - Epoch(train) [293][10/63] lr: 1.6826e-03 eta: 9:18:15 time: 0.9133 data_time: 0.2291 memory: 14901 loss: 1.5490 loss_prob: 0.8654 loss_thr: 0.5421 loss_db: 0.1415 2022/11/02 15:16:23 - mmengine - INFO - Epoch(train) [293][15/63] lr: 1.6826e-03 eta: 9:18:15 time: 0.6028 data_time: 0.0115 memory: 14901 loss: 1.6241 loss_prob: 0.9110 loss_thr: 0.5613 loss_db: 0.1518 2022/11/02 15:16:25 - mmengine - INFO - Epoch(train) [293][20/63] lr: 1.6826e-03 eta: 9:18:11 time: 0.6210 data_time: 0.0076 memory: 14901 loss: 1.6422 loss_prob: 0.9352 loss_thr: 0.5512 loss_db: 0.1558 2022/11/02 15:16:28 - mmengine - INFO - Epoch(train) [293][25/63] lr: 1.6826e-03 eta: 9:18:11 time: 0.5652 data_time: 0.0228 memory: 14901 loss: 1.6598 loss_prob: 0.9524 loss_thr: 0.5509 loss_db: 0.1565 2022/11/02 15:16:31 - mmengine - INFO - Epoch(train) [293][30/63] lr: 1.6826e-03 eta: 9:18:03 time: 0.5382 data_time: 0.0416 memory: 14901 loss: 1.6763 loss_prob: 0.9573 loss_thr: 0.5615 loss_db: 0.1576 2022/11/02 15:16:33 - mmengine - INFO - Epoch(train) [293][35/63] lr: 1.6826e-03 eta: 9:18:03 time: 0.5015 data_time: 0.0282 memory: 14901 loss: 1.6631 loss_prob: 0.9403 loss_thr: 0.5669 loss_db: 0.1559 2022/11/02 15:16:35 - mmengine - INFO - Epoch(train) [293][40/63] lr: 1.6826e-03 eta: 9:17:53 time: 0.4607 data_time: 0.0090 memory: 14901 loss: 1.7884 loss_prob: 1.0231 loss_thr: 0.5998 loss_db: 0.1655 2022/11/02 15:16:38 - mmengine - INFO - Epoch(train) [293][45/63] lr: 1.6826e-03 eta: 9:17:53 time: 0.5095 data_time: 0.0100 memory: 14901 loss: 1.7659 loss_prob: 1.0105 loss_thr: 0.5941 loss_db: 0.1613 2022/11/02 15:16:42 - mmengine - INFO - Epoch(train) [293][50/63] lr: 1.6826e-03 eta: 9:17:48 time: 0.6039 data_time: 0.0196 memory: 14901 loss: 1.7087 loss_prob: 0.9779 loss_thr: 0.5710 loss_db: 0.1598 2022/11/02 15:16:44 - mmengine - INFO - Epoch(train) [293][55/63] lr: 1.6826e-03 eta: 9:17:48 time: 0.5557 data_time: 0.0265 memory: 14901 loss: 1.6722 loss_prob: 0.9507 loss_thr: 0.5647 loss_db: 0.1568 2022/11/02 15:16:46 - mmengine - INFO - Epoch(train) [293][60/63] lr: 1.6826e-03 eta: 9:17:39 time: 0.4767 data_time: 0.0178 memory: 14901 loss: 1.6427 loss_prob: 0.9188 loss_thr: 0.5740 loss_db: 0.1499 2022/11/02 15:16:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:16:52 - mmengine - INFO - Epoch(train) [294][5/63] lr: 1.6809e-03 eta: 9:17:39 time: 0.6895 data_time: 0.2122 memory: 14901 loss: 1.7154 loss_prob: 0.9700 loss_thr: 0.5834 loss_db: 0.1620 2022/11/02 15:16:55 - mmengine - INFO - Epoch(train) [294][10/63] lr: 1.6809e-03 eta: 9:17:32 time: 0.7772 data_time: 0.2125 memory: 14901 loss: 1.6724 loss_prob: 0.9506 loss_thr: 0.5657 loss_db: 0.1562 2022/11/02 15:16:58 - mmengine - INFO - Epoch(train) [294][15/63] lr: 1.6809e-03 eta: 9:17:32 time: 0.5396 data_time: 0.0133 memory: 14901 loss: 1.6576 loss_prob: 0.9427 loss_thr: 0.5576 loss_db: 0.1574 2022/11/02 15:17:01 - mmengine - INFO - Epoch(train) [294][20/63] lr: 1.6809e-03 eta: 9:17:25 time: 0.5427 data_time: 0.0133 memory: 14901 loss: 1.6301 loss_prob: 0.9208 loss_thr: 0.5526 loss_db: 0.1567 2022/11/02 15:17:03 - mmengine - INFO - Epoch(train) [294][25/63] lr: 1.6809e-03 eta: 9:17:25 time: 0.5521 data_time: 0.0156 memory: 14901 loss: 1.6267 loss_prob: 0.9138 loss_thr: 0.5604 loss_db: 0.1525 2022/11/02 15:17:07 - mmengine - INFO - Epoch(train) [294][30/63] lr: 1.6809e-03 eta: 9:17:20 time: 0.6377 data_time: 0.0323 memory: 14901 loss: 1.7263 loss_prob: 0.9676 loss_thr: 0.5949 loss_db: 0.1638 2022/11/02 15:17:09 - mmengine - INFO - Epoch(train) [294][35/63] lr: 1.6809e-03 eta: 9:17:20 time: 0.6257 data_time: 0.0232 memory: 14901 loss: 1.6856 loss_prob: 0.9431 loss_thr: 0.5836 loss_db: 0.1588 2022/11/02 15:17:13 - mmengine - INFO - Epoch(train) [294][40/63] lr: 1.6809e-03 eta: 9:17:15 time: 0.6040 data_time: 0.0141 memory: 14901 loss: 1.5910 loss_prob: 0.8912 loss_thr: 0.5536 loss_db: 0.1463 2022/11/02 15:17:16 - mmengine - INFO - Epoch(train) [294][45/63] lr: 1.6809e-03 eta: 9:17:15 time: 0.6593 data_time: 0.0146 memory: 14901 loss: 1.6316 loss_prob: 0.9094 loss_thr: 0.5715 loss_db: 0.1507 2022/11/02 15:17:19 - mmengine - INFO - Epoch(train) [294][50/63] lr: 1.6809e-03 eta: 9:17:08 time: 0.5469 data_time: 0.0132 memory: 14901 loss: 1.6645 loss_prob: 0.9252 loss_thr: 0.5831 loss_db: 0.1562 2022/11/02 15:17:21 - mmengine - INFO - Epoch(train) [294][55/63] lr: 1.6809e-03 eta: 9:17:08 time: 0.5097 data_time: 0.0255 memory: 14901 loss: 1.5980 loss_prob: 0.8940 loss_thr: 0.5565 loss_db: 0.1475 2022/11/02 15:17:24 - mmengine - INFO - Epoch(train) [294][60/63] lr: 1.6809e-03 eta: 9:17:00 time: 0.5153 data_time: 0.0186 memory: 14901 loss: 1.5997 loss_prob: 0.8945 loss_thr: 0.5586 loss_db: 0.1466 2022/11/02 15:17:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:17:31 - mmengine - INFO - Epoch(train) [295][5/63] lr: 1.6793e-03 eta: 9:17:00 time: 0.8250 data_time: 0.2201 memory: 14901 loss: 1.6816 loss_prob: 0.9545 loss_thr: 0.5719 loss_db: 0.1553 2022/11/02 15:17:34 - mmengine - INFO - Epoch(train) [295][10/63] lr: 1.6793e-03 eta: 9:16:55 time: 0.8407 data_time: 0.2211 memory: 14901 loss: 1.7245 loss_prob: 0.9835 loss_thr: 0.5806 loss_db: 0.1604 2022/11/02 15:17:36 - mmengine - INFO - Epoch(train) [295][15/63] lr: 1.6793e-03 eta: 9:16:55 time: 0.5391 data_time: 0.0177 memory: 14901 loss: 1.6688 loss_prob: 0.9446 loss_thr: 0.5646 loss_db: 0.1595 2022/11/02 15:17:39 - mmengine - INFO - Epoch(train) [295][20/63] lr: 1.6793e-03 eta: 9:16:47 time: 0.5095 data_time: 0.0115 memory: 14901 loss: 1.6288 loss_prob: 0.9164 loss_thr: 0.5587 loss_db: 0.1537 2022/11/02 15:17:42 - mmengine - INFO - Epoch(train) [295][25/63] lr: 1.6793e-03 eta: 9:16:47 time: 0.5097 data_time: 0.0215 memory: 14901 loss: 1.6059 loss_prob: 0.8950 loss_thr: 0.5615 loss_db: 0.1493 2022/11/02 15:17:44 - mmengine - INFO - Epoch(train) [295][30/63] lr: 1.6793e-03 eta: 9:16:40 time: 0.5511 data_time: 0.0345 memory: 14901 loss: 1.7350 loss_prob: 1.0029 loss_thr: 0.5702 loss_db: 0.1619 2022/11/02 15:17:48 - mmengine - INFO - Epoch(train) [295][35/63] lr: 1.6793e-03 eta: 9:16:40 time: 0.6110 data_time: 0.0248 memory: 14901 loss: 1.7008 loss_prob: 0.9766 loss_thr: 0.5664 loss_db: 0.1578 2022/11/02 15:17:50 - mmengine - INFO - Epoch(train) [295][40/63] lr: 1.6793e-03 eta: 9:16:33 time: 0.5556 data_time: 0.0175 memory: 14901 loss: 1.8467 loss_prob: 1.0799 loss_thr: 0.5869 loss_db: 0.1798 2022/11/02 15:17:53 - mmengine - INFO - Epoch(train) [295][45/63] lr: 1.6793e-03 eta: 9:16:33 time: 0.5001 data_time: 0.0124 memory: 14901 loss: 1.8452 loss_prob: 1.0819 loss_thr: 0.5853 loss_db: 0.1780 2022/11/02 15:17:56 - mmengine - INFO - Epoch(train) [295][50/63] lr: 1.6793e-03 eta: 9:16:27 time: 0.5760 data_time: 0.0200 memory: 14901 loss: 1.5943 loss_prob: 0.8979 loss_thr: 0.5479 loss_db: 0.1485 2022/11/02 15:17:58 - mmengine - INFO - Epoch(train) [295][55/63] lr: 1.6793e-03 eta: 9:16:27 time: 0.5607 data_time: 0.0236 memory: 14901 loss: 1.7595 loss_prob: 1.0089 loss_thr: 0.5815 loss_db: 0.1691 2022/11/02 15:18:01 - mmengine - INFO - Epoch(train) [295][60/63] lr: 1.6793e-03 eta: 9:16:20 time: 0.5425 data_time: 0.0121 memory: 14901 loss: 1.7293 loss_prob: 0.9825 loss_thr: 0.5811 loss_db: 0.1657 2022/11/02 15:18:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:18:09 - mmengine - INFO - Epoch(train) [296][5/63] lr: 1.6776e-03 eta: 9:16:20 time: 0.8247 data_time: 0.2343 memory: 14901 loss: 1.6581 loss_prob: 0.9319 loss_thr: 0.5733 loss_db: 0.1529 2022/11/02 15:18:11 - mmengine - INFO - Epoch(train) [296][10/63] lr: 1.6776e-03 eta: 9:16:14 time: 0.8265 data_time: 0.2333 memory: 14901 loss: 1.6112 loss_prob: 0.8967 loss_thr: 0.5676 loss_db: 0.1470 2022/11/02 15:18:14 - mmengine - INFO - Epoch(train) [296][15/63] lr: 1.6776e-03 eta: 9:16:14 time: 0.5301 data_time: 0.0121 memory: 14901 loss: 1.6171 loss_prob: 0.8974 loss_thr: 0.5698 loss_db: 0.1499 2022/11/02 15:18:17 - mmengine - INFO - Epoch(train) [296][20/63] lr: 1.6776e-03 eta: 9:16:08 time: 0.5825 data_time: 0.0218 memory: 14901 loss: 1.6563 loss_prob: 0.9234 loss_thr: 0.5769 loss_db: 0.1560 2022/11/02 15:18:20 - mmengine - INFO - Epoch(train) [296][25/63] lr: 1.6776e-03 eta: 9:16:08 time: 0.5912 data_time: 0.0328 memory: 14901 loss: 1.6663 loss_prob: 0.9318 loss_thr: 0.5770 loss_db: 0.1575 2022/11/02 15:18:22 - mmengine - INFO - Epoch(train) [296][30/63] lr: 1.6776e-03 eta: 9:16:01 time: 0.5292 data_time: 0.0421 memory: 14901 loss: 1.8602 loss_prob: 1.0800 loss_thr: 0.6076 loss_db: 0.1726 2022/11/02 15:18:25 - mmengine - INFO - Epoch(train) [296][35/63] lr: 1.6776e-03 eta: 9:16:01 time: 0.5264 data_time: 0.0395 memory: 14901 loss: 1.8311 loss_prob: 1.0720 loss_thr: 0.5894 loss_db: 0.1697 2022/11/02 15:18:28 - mmengine - INFO - Epoch(train) [296][40/63] lr: 1.6776e-03 eta: 9:15:53 time: 0.5386 data_time: 0.0195 memory: 14901 loss: 1.6067 loss_prob: 0.9070 loss_thr: 0.5511 loss_db: 0.1486 2022/11/02 15:18:30 - mmengine - INFO - Epoch(train) [296][45/63] lr: 1.6776e-03 eta: 9:15:53 time: 0.5196 data_time: 0.0125 memory: 14901 loss: 1.6990 loss_prob: 0.9542 loss_thr: 0.5857 loss_db: 0.1591 2022/11/02 15:18:33 - mmengine - INFO - Epoch(train) [296][50/63] lr: 1.6776e-03 eta: 9:15:45 time: 0.5186 data_time: 0.0163 memory: 14901 loss: 1.8010 loss_prob: 1.0260 loss_thr: 0.6022 loss_db: 0.1727 2022/11/02 15:18:37 - mmengine - INFO - Epoch(train) [296][55/63] lr: 1.6776e-03 eta: 9:15:45 time: 0.6379 data_time: 0.0242 memory: 14901 loss: 1.6787 loss_prob: 0.9538 loss_thr: 0.5630 loss_db: 0.1619 2022/11/02 15:18:39 - mmengine - INFO - Epoch(train) [296][60/63] lr: 1.6776e-03 eta: 9:15:41 time: 0.6315 data_time: 0.0161 memory: 14901 loss: 1.5824 loss_prob: 0.8860 loss_thr: 0.5470 loss_db: 0.1495 2022/11/02 15:18:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:18:46 - mmengine - INFO - Epoch(train) [297][5/63] lr: 1.6759e-03 eta: 9:15:41 time: 0.8534 data_time: 0.2646 memory: 14901 loss: 1.5980 loss_prob: 0.8922 loss_thr: 0.5578 loss_db: 0.1480 2022/11/02 15:18:49 - mmengine - INFO - Epoch(train) [297][10/63] lr: 1.6759e-03 eta: 9:15:36 time: 0.8635 data_time: 0.2697 memory: 14901 loss: 1.7228 loss_prob: 0.9825 loss_thr: 0.5786 loss_db: 0.1618 2022/11/02 15:18:52 - mmengine - INFO - Epoch(train) [297][15/63] lr: 1.6759e-03 eta: 9:15:36 time: 0.5144 data_time: 0.0147 memory: 14901 loss: 1.7625 loss_prob: 1.0138 loss_thr: 0.5842 loss_db: 0.1645 2022/11/02 15:18:55 - mmengine - INFO - Epoch(train) [297][20/63] lr: 1.6759e-03 eta: 9:15:29 time: 0.5369 data_time: 0.0054 memory: 14901 loss: 1.6760 loss_prob: 0.9451 loss_thr: 0.5764 loss_db: 0.1545 2022/11/02 15:18:57 - mmengine - INFO - Epoch(train) [297][25/63] lr: 1.6759e-03 eta: 9:15:29 time: 0.5769 data_time: 0.0281 memory: 14901 loss: 1.5706 loss_prob: 0.8767 loss_thr: 0.5473 loss_db: 0.1466 2022/11/02 15:19:00 - mmengine - INFO - Epoch(train) [297][30/63] lr: 1.6759e-03 eta: 9:15:22 time: 0.5487 data_time: 0.0475 memory: 14901 loss: 1.5687 loss_prob: 0.8863 loss_thr: 0.5362 loss_db: 0.1462 2022/11/02 15:19:03 - mmengine - INFO - Epoch(train) [297][35/63] lr: 1.6759e-03 eta: 9:15:22 time: 0.5307 data_time: 0.0277 memory: 14901 loss: 1.5547 loss_prob: 0.8659 loss_thr: 0.5471 loss_db: 0.1418 2022/11/02 15:19:06 - mmengine - INFO - Epoch(train) [297][40/63] lr: 1.6759e-03 eta: 9:15:16 time: 0.5705 data_time: 0.0113 memory: 14901 loss: 1.5329 loss_prob: 0.8405 loss_thr: 0.5525 loss_db: 0.1399 2022/11/02 15:19:08 - mmengine - INFO - Epoch(train) [297][45/63] lr: 1.6759e-03 eta: 9:15:16 time: 0.5594 data_time: 0.0102 memory: 14901 loss: 1.5256 loss_prob: 0.8360 loss_thr: 0.5501 loss_db: 0.1394 2022/11/02 15:19:11 - mmengine - INFO - Epoch(train) [297][50/63] lr: 1.6759e-03 eta: 9:15:07 time: 0.4973 data_time: 0.0244 memory: 14901 loss: 1.6124 loss_prob: 0.8903 loss_thr: 0.5710 loss_db: 0.1511 2022/11/02 15:19:14 - mmengine - INFO - Epoch(train) [297][55/63] lr: 1.6759e-03 eta: 9:15:07 time: 0.5391 data_time: 0.0261 memory: 14901 loss: 1.6204 loss_prob: 0.9085 loss_thr: 0.5578 loss_db: 0.1541 2022/11/02 15:19:16 - mmengine - INFO - Epoch(train) [297][60/63] lr: 1.6759e-03 eta: 9:15:00 time: 0.5349 data_time: 0.0106 memory: 14901 loss: 1.5887 loss_prob: 0.9071 loss_thr: 0.5340 loss_db: 0.1477 2022/11/02 15:19:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:19:23 - mmengine - INFO - Epoch(train) [298][5/63] lr: 1.6743e-03 eta: 9:15:00 time: 0.8311 data_time: 0.2397 memory: 14901 loss: 1.6159 loss_prob: 0.9081 loss_thr: 0.5611 loss_db: 0.1468 2022/11/02 15:19:26 - mmengine - INFO - Epoch(train) [298][10/63] lr: 1.6743e-03 eta: 9:14:54 time: 0.8057 data_time: 0.2452 memory: 14901 loss: 1.6062 loss_prob: 0.9005 loss_thr: 0.5523 loss_db: 0.1534 2022/11/02 15:19:29 - mmengine - INFO - Epoch(train) [298][15/63] lr: 1.6743e-03 eta: 9:14:54 time: 0.5228 data_time: 0.0161 memory: 14901 loss: 1.6439 loss_prob: 0.9390 loss_thr: 0.5479 loss_db: 0.1570 2022/11/02 15:19:31 - mmengine - INFO - Epoch(train) [298][20/63] lr: 1.6743e-03 eta: 9:14:46 time: 0.5331 data_time: 0.0141 memory: 14901 loss: 1.6013 loss_prob: 0.8999 loss_thr: 0.5515 loss_db: 0.1498 2022/11/02 15:19:34 - mmengine - INFO - Epoch(train) [298][25/63] lr: 1.6743e-03 eta: 9:14:46 time: 0.5772 data_time: 0.0160 memory: 14901 loss: 1.6843 loss_prob: 0.9683 loss_thr: 0.5620 loss_db: 0.1541 2022/11/02 15:19:38 - mmengine - INFO - Epoch(train) [298][30/63] lr: 1.6743e-03 eta: 9:14:43 time: 0.6646 data_time: 0.0384 memory: 14901 loss: 1.6993 loss_prob: 0.9809 loss_thr: 0.5630 loss_db: 0.1553 2022/11/02 15:19:41 - mmengine - INFO - Epoch(train) [298][35/63] lr: 1.6743e-03 eta: 9:14:43 time: 0.6161 data_time: 0.0366 memory: 14901 loss: 1.5897 loss_prob: 0.8830 loss_thr: 0.5562 loss_db: 0.1505 2022/11/02 15:19:43 - mmengine - INFO - Epoch(train) [298][40/63] lr: 1.6743e-03 eta: 9:14:36 time: 0.5459 data_time: 0.0137 memory: 14901 loss: 1.5795 loss_prob: 0.8803 loss_thr: 0.5526 loss_db: 0.1466 2022/11/02 15:19:46 - mmengine - INFO - Epoch(train) [298][45/63] lr: 1.6743e-03 eta: 9:14:36 time: 0.5544 data_time: 0.0118 memory: 14901 loss: 1.5960 loss_prob: 0.8952 loss_thr: 0.5562 loss_db: 0.1446 2022/11/02 15:19:49 - mmengine - INFO - Epoch(train) [298][50/63] lr: 1.6743e-03 eta: 9:14:28 time: 0.5315 data_time: 0.0232 memory: 14901 loss: 1.6212 loss_prob: 0.9093 loss_thr: 0.5621 loss_db: 0.1498 2022/11/02 15:19:51 - mmengine - INFO - Epoch(train) [298][55/63] lr: 1.6743e-03 eta: 9:14:28 time: 0.5349 data_time: 0.0205 memory: 14901 loss: 1.7003 loss_prob: 0.9802 loss_thr: 0.5590 loss_db: 0.1611 2022/11/02 15:19:54 - mmengine - INFO - Epoch(train) [298][60/63] lr: 1.6743e-03 eta: 9:14:21 time: 0.5445 data_time: 0.0093 memory: 14901 loss: 1.6604 loss_prob: 0.9401 loss_thr: 0.5664 loss_db: 0.1539 2022/11/02 15:19:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:20:02 - mmengine - INFO - Epoch(train) [299][5/63] lr: 1.6726e-03 eta: 9:14:21 time: 0.8664 data_time: 0.2152 memory: 14901 loss: 1.6021 loss_prob: 0.9007 loss_thr: 0.5557 loss_db: 0.1457 2022/11/02 15:20:05 - mmengine - INFO - Epoch(train) [299][10/63] lr: 1.6726e-03 eta: 9:14:20 time: 0.9690 data_time: 0.2161 memory: 14901 loss: 1.6121 loss_prob: 0.8999 loss_thr: 0.5628 loss_db: 0.1495 2022/11/02 15:20:08 - mmengine - INFO - Epoch(train) [299][15/63] lr: 1.6726e-03 eta: 9:14:20 time: 0.6297 data_time: 0.0086 memory: 14901 loss: 1.6005 loss_prob: 0.8828 loss_thr: 0.5631 loss_db: 0.1546 2022/11/02 15:20:11 - mmengine - INFO - Epoch(train) [299][20/63] lr: 1.6726e-03 eta: 9:14:12 time: 0.5355 data_time: 0.0092 memory: 14901 loss: 1.5812 loss_prob: 0.8791 loss_thr: 0.5529 loss_db: 0.1492 2022/11/02 15:20:13 - mmengine - INFO - Epoch(train) [299][25/63] lr: 1.6726e-03 eta: 9:14:12 time: 0.5391 data_time: 0.0097 memory: 14901 loss: 1.7057 loss_prob: 0.9832 loss_thr: 0.5638 loss_db: 0.1587 2022/11/02 15:20:17 - mmengine - INFO - Epoch(train) [299][30/63] lr: 1.6726e-03 eta: 9:14:07 time: 0.5978 data_time: 0.0350 memory: 14901 loss: 1.7466 loss_prob: 1.0033 loss_thr: 0.5771 loss_db: 0.1662 2022/11/02 15:20:19 - mmengine - INFO - Epoch(train) [299][35/63] lr: 1.6726e-03 eta: 9:14:07 time: 0.5743 data_time: 0.0398 memory: 14901 loss: 1.5844 loss_prob: 0.8858 loss_thr: 0.5502 loss_db: 0.1484 2022/11/02 15:20:22 - mmengine - INFO - Epoch(train) [299][40/63] lr: 1.6726e-03 eta: 9:13:59 time: 0.5290 data_time: 0.0120 memory: 14901 loss: 1.6516 loss_prob: 0.9241 loss_thr: 0.5745 loss_db: 0.1531 2022/11/02 15:20:25 - mmengine - INFO - Epoch(train) [299][45/63] lr: 1.6726e-03 eta: 9:13:59 time: 0.5504 data_time: 0.0108 memory: 14901 loss: 1.6031 loss_prob: 0.8875 loss_thr: 0.5636 loss_db: 0.1520 2022/11/02 15:20:27 - mmengine - INFO - Epoch(train) [299][50/63] lr: 1.6726e-03 eta: 9:13:53 time: 0.5558 data_time: 0.0252 memory: 14901 loss: 1.6104 loss_prob: 0.9000 loss_thr: 0.5585 loss_db: 0.1519 2022/11/02 15:20:30 - mmengine - INFO - Epoch(train) [299][55/63] lr: 1.6726e-03 eta: 9:13:53 time: 0.5271 data_time: 0.0204 memory: 14901 loss: 1.6628 loss_prob: 0.9230 loss_thr: 0.5875 loss_db: 0.1523 2022/11/02 15:20:33 - mmengine - INFO - Epoch(train) [299][60/63] lr: 1.6726e-03 eta: 9:13:46 time: 0.5479 data_time: 0.0125 memory: 14901 loss: 1.5771 loss_prob: 0.8724 loss_thr: 0.5628 loss_db: 0.1418 2022/11/02 15:20:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:20:40 - mmengine - INFO - Epoch(train) [300][5/63] lr: 1.6709e-03 eta: 9:13:46 time: 0.7958 data_time: 0.2522 memory: 14901 loss: 1.6831 loss_prob: 0.9477 loss_thr: 0.5767 loss_db: 0.1587 2022/11/02 15:20:43 - mmengine - INFO - Epoch(train) [300][10/63] lr: 1.6709e-03 eta: 9:13:40 time: 0.8134 data_time: 0.2521 memory: 14901 loss: 1.7374 loss_prob: 0.9867 loss_thr: 0.5912 loss_db: 0.1596 2022/11/02 15:20:45 - mmengine - INFO - Epoch(train) [300][15/63] lr: 1.6709e-03 eta: 9:13:40 time: 0.5548 data_time: 0.0089 memory: 14901 loss: 1.6137 loss_prob: 0.9243 loss_thr: 0.5425 loss_db: 0.1469 2022/11/02 15:20:49 - mmengine - INFO - Epoch(train) [300][20/63] lr: 1.6709e-03 eta: 9:13:35 time: 0.6214 data_time: 0.0097 memory: 14901 loss: 1.4965 loss_prob: 0.8267 loss_thr: 0.5313 loss_db: 0.1385 2022/11/02 15:20:51 - mmengine - INFO - Epoch(train) [300][25/63] lr: 1.6709e-03 eta: 9:13:35 time: 0.6108 data_time: 0.0135 memory: 14901 loss: 1.5299 loss_prob: 0.8539 loss_thr: 0.5331 loss_db: 0.1429 2022/11/02 15:20:55 - mmengine - INFO - Epoch(train) [300][30/63] lr: 1.6709e-03 eta: 9:13:29 time: 0.5871 data_time: 0.0396 memory: 14901 loss: 1.6093 loss_prob: 0.9030 loss_thr: 0.5579 loss_db: 0.1484 2022/11/02 15:20:57 - mmengine - INFO - Epoch(train) [300][35/63] lr: 1.6709e-03 eta: 9:13:29 time: 0.5625 data_time: 0.0326 memory: 14901 loss: 1.6934 loss_prob: 0.9380 loss_thr: 0.5996 loss_db: 0.1558 2022/11/02 15:20:59 - mmengine - INFO - Epoch(train) [300][40/63] lr: 1.6709e-03 eta: 9:13:20 time: 0.4787 data_time: 0.0054 memory: 14901 loss: 1.7464 loss_prob: 0.9797 loss_thr: 0.5995 loss_db: 0.1672 2022/11/02 15:21:02 - mmengine - INFO - Epoch(train) [300][45/63] lr: 1.6709e-03 eta: 9:13:20 time: 0.4977 data_time: 0.0087 memory: 14901 loss: 1.6386 loss_prob: 0.9215 loss_thr: 0.5623 loss_db: 0.1547 2022/11/02 15:21:05 - mmengine - INFO - Epoch(train) [300][50/63] lr: 1.6709e-03 eta: 9:13:12 time: 0.5265 data_time: 0.0180 memory: 14901 loss: 1.6309 loss_prob: 0.9229 loss_thr: 0.5552 loss_db: 0.1528 2022/11/02 15:21:07 - mmengine - INFO - Epoch(train) [300][55/63] lr: 1.6709e-03 eta: 9:13:12 time: 0.5146 data_time: 0.0235 memory: 14901 loss: 1.5768 loss_prob: 0.8840 loss_thr: 0.5453 loss_db: 0.1474 2022/11/02 15:21:10 - mmengine - INFO - Epoch(train) [300][60/63] lr: 1.6709e-03 eta: 9:13:05 time: 0.5333 data_time: 0.0171 memory: 14901 loss: 1.5569 loss_prob: 0.8595 loss_thr: 0.5530 loss_db: 0.1444 2022/11/02 15:21:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:21:11 - mmengine - INFO - Saving checkpoint at 300 epochs 2022/11/02 15:21:15 - mmengine - INFO - Epoch(val) [300][5/500] eta: 9:13:05 time: 0.0429 data_time: 0.0046 memory: 14901 2022/11/02 15:21:15 - mmengine - INFO - Epoch(val) [300][10/500] eta: 0:00:22 time: 0.0466 data_time: 0.0058 memory: 1008 2022/11/02 15:21:16 - mmengine - INFO - Epoch(val) [300][15/500] eta: 0:00:22 time: 0.0387 data_time: 0.0034 memory: 1008 2022/11/02 15:21:16 - mmengine - INFO - Epoch(val) [300][20/500] eta: 0:00:16 time: 0.0351 data_time: 0.0021 memory: 1008 2022/11/02 15:21:16 - mmengine - INFO - Epoch(val) [300][25/500] eta: 0:00:16 time: 0.0388 data_time: 0.0031 memory: 1008 2022/11/02 15:21:16 - mmengine - INFO - Epoch(val) [300][30/500] eta: 0:00:19 time: 0.0417 data_time: 0.0033 memory: 1008 2022/11/02 15:21:16 - mmengine - INFO - Epoch(val) [300][35/500] eta: 0:00:19 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 15:21:17 - mmengine - INFO - Epoch(val) [300][40/500] eta: 0:00:19 time: 0.0422 data_time: 0.0026 memory: 1008 2022/11/02 15:21:17 - mmengine - INFO - Epoch(val) [300][45/500] eta: 0:00:19 time: 0.0413 data_time: 0.0024 memory: 1008 2022/11/02 15:21:17 - mmengine - INFO - Epoch(val) [300][50/500] eta: 0:00:18 time: 0.0418 data_time: 0.0035 memory: 1008 2022/11/02 15:21:17 - mmengine - INFO - Epoch(val) [300][55/500] eta: 0:00:18 time: 0.0439 data_time: 0.0040 memory: 1008 2022/11/02 15:21:17 - mmengine - INFO - Epoch(val) [300][60/500] eta: 0:00:16 time: 0.0386 data_time: 0.0028 memory: 1008 2022/11/02 15:21:18 - mmengine - INFO - Epoch(val) [300][65/500] eta: 0:00:16 time: 0.0420 data_time: 0.0026 memory: 1008 2022/11/02 15:21:18 - mmengine - INFO - Epoch(val) [300][70/500] eta: 0:00:18 time: 0.0431 data_time: 0.0027 memory: 1008 2022/11/02 15:21:18 - mmengine - INFO - Epoch(val) [300][75/500] eta: 0:00:18 time: 0.0377 data_time: 0.0027 memory: 1008 2022/11/02 15:21:18 - mmengine - INFO - Epoch(val) [300][80/500] eta: 0:00:22 time: 0.0525 data_time: 0.0205 memory: 1008 2022/11/02 15:21:19 - mmengine - INFO - Epoch(val) [300][85/500] eta: 0:00:22 time: 0.0538 data_time: 0.0201 memory: 1008 2022/11/02 15:21:19 - mmengine - INFO - Epoch(val) [300][90/500] eta: 0:00:17 time: 0.0433 data_time: 0.0025 memory: 1008 2022/11/02 15:21:19 - mmengine - INFO - Epoch(val) [300][95/500] eta: 0:00:17 time: 0.0452 data_time: 0.0029 memory: 1008 2022/11/02 15:21:19 - mmengine - INFO - Epoch(val) [300][100/500] eta: 0:00:15 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 15:21:19 - mmengine - INFO - Epoch(val) [300][105/500] eta: 0:00:15 time: 0.0420 data_time: 0.0031 memory: 1008 2022/11/02 15:21:20 - mmengine - INFO - Epoch(val) [300][110/500] eta: 0:00:16 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 15:21:20 - mmengine - INFO - Epoch(val) [300][115/500] eta: 0:00:16 time: 0.0404 data_time: 0.0025 memory: 1008 2022/11/02 15:21:20 - mmengine - INFO - Epoch(val) [300][120/500] eta: 0:00:15 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 15:21:20 - mmengine - INFO - Epoch(val) [300][125/500] eta: 0:00:15 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/02 15:21:20 - mmengine - INFO - Epoch(val) [300][130/500] eta: 0:00:13 time: 0.0369 data_time: 0.0025 memory: 1008 2022/11/02 15:21:21 - mmengine - INFO - Epoch(val) [300][135/500] eta: 0:00:13 time: 0.0390 data_time: 0.0029 memory: 1008 2022/11/02 15:21:21 - mmengine - INFO - Epoch(val) [300][140/500] eta: 0:00:14 time: 0.0392 data_time: 0.0028 memory: 1008 2022/11/02 15:21:21 - mmengine - INFO - Epoch(val) [300][145/500] eta: 0:00:14 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 15:21:21 - mmengine - INFO - Epoch(val) [300][150/500] eta: 0:00:15 time: 0.0439 data_time: 0.0028 memory: 1008 2022/11/02 15:21:21 - mmengine - INFO - Epoch(val) [300][155/500] eta: 0:00:15 time: 0.0475 data_time: 0.0030 memory: 1008 2022/11/02 15:21:22 - mmengine - INFO - Epoch(val) [300][160/500] eta: 0:00:16 time: 0.0483 data_time: 0.0028 memory: 1008 2022/11/02 15:21:22 - mmengine - INFO - Epoch(val) [300][165/500] eta: 0:00:16 time: 0.0455 data_time: 0.0027 memory: 1008 2022/11/02 15:21:22 - mmengine - INFO - Epoch(val) [300][170/500] eta: 0:00:15 time: 0.0485 data_time: 0.0029 memory: 1008 2022/11/02 15:21:22 - mmengine - INFO - Epoch(val) [300][175/500] eta: 0:00:15 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 15:21:23 - mmengine - INFO - Epoch(val) [300][180/500] eta: 0:00:11 time: 0.0360 data_time: 0.0024 memory: 1008 2022/11/02 15:21:23 - mmengine - INFO - Epoch(val) [300][185/500] eta: 0:00:11 time: 0.0389 data_time: 0.0024 memory: 1008 2022/11/02 15:21:23 - mmengine - INFO - Epoch(val) [300][190/500] eta: 0:00:12 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 15:21:23 - mmengine - INFO - Epoch(val) [300][195/500] eta: 0:00:12 time: 0.0373 data_time: 0.0026 memory: 1008 2022/11/02 15:21:23 - mmengine - INFO - Epoch(val) [300][200/500] eta: 0:00:14 time: 0.0483 data_time: 0.0028 memory: 1008 2022/11/02 15:21:24 - mmengine - INFO - Epoch(val) [300][205/500] eta: 0:00:14 time: 0.0486 data_time: 0.0033 memory: 1008 2022/11/02 15:21:24 - mmengine - INFO - Epoch(val) [300][210/500] eta: 0:00:10 time: 0.0377 data_time: 0.0029 memory: 1008 2022/11/02 15:21:24 - mmengine - INFO - Epoch(val) [300][215/500] eta: 0:00:10 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 15:21:24 - mmengine - INFO - Epoch(val) [300][220/500] eta: 0:00:11 time: 0.0404 data_time: 0.0030 memory: 1008 2022/11/02 15:21:24 - mmengine - INFO - Epoch(val) [300][225/500] eta: 0:00:11 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 15:21:25 - mmengine - INFO - Epoch(val) [300][230/500] eta: 0:00:10 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/02 15:21:25 - mmengine - INFO - Epoch(val) [300][235/500] eta: 0:00:10 time: 0.0365 data_time: 0.0021 memory: 1008 2022/11/02 15:21:25 - mmengine - INFO - Epoch(val) [300][240/500] eta: 0:00:09 time: 0.0377 data_time: 0.0023 memory: 1008 2022/11/02 15:21:25 - mmengine - INFO - Epoch(val) [300][245/500] eta: 0:00:09 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/02 15:21:25 - mmengine - INFO - Epoch(val) [300][250/500] eta: 0:00:08 time: 0.0355 data_time: 0.0024 memory: 1008 2022/11/02 15:21:26 - mmengine - INFO - Epoch(val) [300][255/500] eta: 0:00:08 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 15:21:26 - mmengine - INFO - Epoch(val) [300][260/500] eta: 0:00:10 time: 0.0433 data_time: 0.0033 memory: 1008 2022/11/02 15:21:26 - mmengine - INFO - Epoch(val) [300][265/500] eta: 0:00:10 time: 0.0473 data_time: 0.0033 memory: 1008 2022/11/02 15:21:26 - mmengine - INFO - Epoch(val) [300][270/500] eta: 0:00:10 time: 0.0465 data_time: 0.0031 memory: 1008 2022/11/02 15:21:26 - mmengine - INFO - Epoch(val) [300][275/500] eta: 0:00:10 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 15:21:27 - mmengine - INFO - Epoch(val) [300][280/500] eta: 0:00:09 time: 0.0447 data_time: 0.0027 memory: 1008 2022/11/02 15:21:27 - mmengine - INFO - Epoch(val) [300][285/500] eta: 0:00:09 time: 0.0427 data_time: 0.0028 memory: 1008 2022/11/02 15:21:27 - mmengine - INFO - Epoch(val) [300][290/500] eta: 0:00:09 time: 0.0456 data_time: 0.0028 memory: 1008 2022/11/02 15:21:27 - mmengine - INFO - Epoch(val) [300][295/500] eta: 0:00:09 time: 0.0522 data_time: 0.0031 memory: 1008 2022/11/02 15:21:28 - mmengine - INFO - Epoch(val) [300][300/500] eta: 0:00:10 time: 0.0549 data_time: 0.0038 memory: 1008 2022/11/02 15:21:28 - mmengine - INFO - Epoch(val) [300][305/500] eta: 0:00:10 time: 0.0499 data_time: 0.0041 memory: 1008 2022/11/02 15:21:28 - mmengine - INFO - Epoch(val) [300][310/500] eta: 0:00:08 time: 0.0432 data_time: 0.0032 memory: 1008 2022/11/02 15:21:28 - mmengine - INFO - Epoch(val) [300][315/500] eta: 0:00:08 time: 0.0455 data_time: 0.0026 memory: 1008 2022/11/02 15:21:29 - mmengine - INFO - Epoch(val) [300][320/500] eta: 0:00:08 time: 0.0446 data_time: 0.0028 memory: 1008 2022/11/02 15:21:29 - mmengine - INFO - Epoch(val) [300][325/500] eta: 0:00:08 time: 0.0546 data_time: 0.0027 memory: 1008 2022/11/02 15:21:29 - mmengine - INFO - Epoch(val) [300][330/500] eta: 0:00:08 time: 0.0525 data_time: 0.0025 memory: 1008 2022/11/02 15:21:29 - mmengine - INFO - Epoch(val) [300][335/500] eta: 0:00:08 time: 0.0364 data_time: 0.0026 memory: 1008 2022/11/02 15:21:30 - mmengine - INFO - Epoch(val) [300][340/500] eta: 0:00:09 time: 0.0618 data_time: 0.0032 memory: 1008 2022/11/02 15:21:30 - mmengine - INFO - Epoch(val) [300][345/500] eta: 0:00:09 time: 0.0648 data_time: 0.0030 memory: 1008 2022/11/02 15:21:30 - mmengine - INFO - Epoch(val) [300][350/500] eta: 0:00:06 time: 0.0434 data_time: 0.0022 memory: 1008 2022/11/02 15:21:30 - mmengine - INFO - Epoch(val) [300][355/500] eta: 0:00:06 time: 0.0411 data_time: 0.0023 memory: 1008 2022/11/02 15:21:31 - mmengine - INFO - Epoch(val) [300][360/500] eta: 0:00:05 time: 0.0422 data_time: 0.0027 memory: 1008 2022/11/02 15:21:31 - mmengine - INFO - Epoch(val) [300][365/500] eta: 0:00:05 time: 0.0447 data_time: 0.0031 memory: 1008 2022/11/02 15:21:31 - mmengine - INFO - Epoch(val) [300][370/500] eta: 0:00:04 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 15:21:31 - mmengine - INFO - Epoch(val) [300][375/500] eta: 0:00:04 time: 0.0396 data_time: 0.0033 memory: 1008 2022/11/02 15:21:31 - mmengine - INFO - Epoch(val) [300][380/500] eta: 0:00:05 time: 0.0425 data_time: 0.0034 memory: 1008 2022/11/02 15:21:32 - mmengine - INFO - Epoch(val) [300][385/500] eta: 0:00:05 time: 0.0420 data_time: 0.0025 memory: 1008 2022/11/02 15:21:32 - mmengine - INFO - Epoch(val) [300][390/500] eta: 0:00:05 time: 0.0493 data_time: 0.0044 memory: 1008 2022/11/02 15:21:32 - mmengine - INFO - Epoch(val) [300][395/500] eta: 0:00:05 time: 0.0460 data_time: 0.0045 memory: 1008 2022/11/02 15:21:32 - mmengine - INFO - Epoch(val) [300][400/500] eta: 0:00:04 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/02 15:21:32 - mmengine - INFO - Epoch(val) [300][405/500] eta: 0:00:04 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 15:21:33 - mmengine - INFO - Epoch(val) [300][410/500] eta: 0:00:03 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/02 15:21:33 - mmengine - INFO - Epoch(val) [300][415/500] eta: 0:00:03 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 15:21:33 - mmengine - INFO - Epoch(val) [300][420/500] eta: 0:00:03 time: 0.0404 data_time: 0.0029 memory: 1008 2022/11/02 15:21:33 - mmengine - INFO - Epoch(val) [300][425/500] eta: 0:00:03 time: 0.0411 data_time: 0.0029 memory: 1008 2022/11/02 15:21:33 - mmengine - INFO - Epoch(val) [300][430/500] eta: 0:00:02 time: 0.0382 data_time: 0.0025 memory: 1008 2022/11/02 15:21:34 - mmengine - INFO - Epoch(val) [300][435/500] eta: 0:00:02 time: 0.0379 data_time: 0.0028 memory: 1008 2022/11/02 15:21:34 - mmengine - INFO - Epoch(val) [300][440/500] eta: 0:00:02 time: 0.0390 data_time: 0.0029 memory: 1008 2022/11/02 15:21:34 - mmengine - INFO - Epoch(val) [300][445/500] eta: 0:00:02 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/02 15:21:34 - mmengine - INFO - Epoch(val) [300][450/500] eta: 0:00:02 time: 0.0401 data_time: 0.0024 memory: 1008 2022/11/02 15:21:34 - mmengine - INFO - Epoch(val) [300][455/500] eta: 0:00:02 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 15:21:35 - mmengine - INFO - Epoch(val) [300][460/500] eta: 0:00:01 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 15:21:35 - mmengine - INFO - Epoch(val) [300][465/500] eta: 0:00:01 time: 0.0352 data_time: 0.0023 memory: 1008 2022/11/02 15:21:35 - mmengine - INFO - Epoch(val) [300][470/500] eta: 0:00:01 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/02 15:21:35 - mmengine - INFO - Epoch(val) [300][475/500] eta: 0:00:01 time: 0.0356 data_time: 0.0025 memory: 1008 2022/11/02 15:21:35 - mmengine - INFO - Epoch(val) [300][480/500] eta: 0:00:00 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 15:21:36 - mmengine - INFO - Epoch(val) [300][485/500] eta: 0:00:00 time: 0.0379 data_time: 0.0024 memory: 1008 2022/11/02 15:21:36 - mmengine - INFO - Epoch(val) [300][490/500] eta: 0:00:00 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 15:21:36 - mmengine - INFO - Epoch(val) [300][495/500] eta: 0:00:00 time: 0.0439 data_time: 0.0027 memory: 1008 2022/11/02 15:21:36 - mmengine - INFO - Epoch(val) [300][500/500] eta: 0:00:00 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 15:21:36 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8146, precision: 0.7154, hmean: 0.7618 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8146, precision: 0.7779, hmean: 0.7959 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8122, precision: 0.8134, hmean: 0.8128 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8021, precision: 0.8544, hmean: 0.8274 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7713, precision: 0.8950, hmean: 0.8285 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4627, precision: 0.9496, hmean: 0.6222 2022/11/02 15:21:36 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0077, precision: 1.0000, hmean: 0.0153 2022/11/02 15:21:36 - mmengine - INFO - Epoch(val) [300][500/500] icdar/precision: 0.8950 icdar/recall: 0.7713 icdar/hmean: 0.8285 2022/11/02 15:21:43 - mmengine - INFO - Epoch(train) [301][5/63] lr: 1.6692e-03 eta: 0:00:00 time: 0.8664 data_time: 0.2546 memory: 14901 loss: 1.4024 loss_prob: 0.7669 loss_thr: 0.5056 loss_db: 0.1300 2022/11/02 15:21:45 - mmengine - INFO - Epoch(train) [301][10/63] lr: 1.6692e-03 eta: 9:13:01 time: 0.8859 data_time: 0.2533 memory: 14901 loss: 1.4850 loss_prob: 0.8304 loss_thr: 0.5147 loss_db: 0.1398 2022/11/02 15:21:48 - mmengine - INFO - Epoch(train) [301][15/63] lr: 1.6692e-03 eta: 9:13:01 time: 0.5711 data_time: 0.0078 memory: 14901 loss: 1.5149 loss_prob: 0.8495 loss_thr: 0.5273 loss_db: 0.1382 2022/11/02 15:21:51 - mmengine - INFO - Epoch(train) [301][20/63] lr: 1.6692e-03 eta: 9:12:56 time: 0.6173 data_time: 0.0111 memory: 14901 loss: 1.5266 loss_prob: 0.8439 loss_thr: 0.5421 loss_db: 0.1406 2022/11/02 15:21:54 - mmengine - INFO - Epoch(train) [301][25/63] lr: 1.6692e-03 eta: 9:12:56 time: 0.5929 data_time: 0.0421 memory: 14901 loss: 1.4331 loss_prob: 0.7707 loss_thr: 0.5309 loss_db: 0.1316 2022/11/02 15:21:57 - mmengine - INFO - Epoch(train) [301][30/63] lr: 1.6692e-03 eta: 9:12:50 time: 0.5715 data_time: 0.0532 memory: 14901 loss: 1.4127 loss_prob: 0.7674 loss_thr: 0.5139 loss_db: 0.1314 2022/11/02 15:22:00 - mmengine - INFO - Epoch(train) [301][35/63] lr: 1.6692e-03 eta: 9:12:50 time: 0.6164 data_time: 0.0235 memory: 14901 loss: 1.5354 loss_prob: 0.8502 loss_thr: 0.5390 loss_db: 0.1462 2022/11/02 15:22:03 - mmengine - INFO - Epoch(train) [301][40/63] lr: 1.6692e-03 eta: 9:12:44 time: 0.5817 data_time: 0.0112 memory: 14901 loss: 1.5161 loss_prob: 0.8364 loss_thr: 0.5375 loss_db: 0.1422 2022/11/02 15:22:06 - mmengine - INFO - Epoch(train) [301][45/63] lr: 1.6692e-03 eta: 9:12:44 time: 0.5453 data_time: 0.0077 memory: 14901 loss: 1.6971 loss_prob: 0.9606 loss_thr: 0.5771 loss_db: 0.1594 2022/11/02 15:22:09 - mmengine - INFO - Epoch(train) [301][50/63] lr: 1.6692e-03 eta: 9:12:38 time: 0.5744 data_time: 0.0248 memory: 14901 loss: 1.8023 loss_prob: 1.0409 loss_thr: 0.5915 loss_db: 0.1699 2022/11/02 15:22:11 - mmengine - INFO - Epoch(train) [301][55/63] lr: 1.6692e-03 eta: 9:12:38 time: 0.5302 data_time: 0.0271 memory: 14901 loss: 1.8091 loss_prob: 1.0598 loss_thr: 0.5827 loss_db: 0.1666 2022/11/02 15:22:15 - mmengine - INFO - Epoch(train) [301][60/63] lr: 1.6692e-03 eta: 9:12:33 time: 0.6107 data_time: 0.0080 memory: 14901 loss: 1.7358 loss_prob: 1.0018 loss_thr: 0.5741 loss_db: 0.1598 2022/11/02 15:22:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:22:23 - mmengine - INFO - Epoch(train) [302][5/63] lr: 1.6676e-03 eta: 9:12:33 time: 0.9007 data_time: 0.3027 memory: 14901 loss: 1.6522 loss_prob: 0.9253 loss_thr: 0.5722 loss_db: 0.1547 2022/11/02 15:22:25 - mmengine - INFO - Epoch(train) [302][10/63] lr: 1.6676e-03 eta: 9:12:30 time: 0.9376 data_time: 0.3021 memory: 14901 loss: 1.6053 loss_prob: 0.8950 loss_thr: 0.5623 loss_db: 0.1480 2022/11/02 15:22:28 - mmengine - INFO - Epoch(train) [302][15/63] lr: 1.6676e-03 eta: 9:12:30 time: 0.5275 data_time: 0.0085 memory: 14901 loss: 1.7173 loss_prob: 0.9898 loss_thr: 0.5678 loss_db: 0.1597 2022/11/02 15:22:31 - mmengine - INFO - Epoch(train) [302][20/63] lr: 1.6676e-03 eta: 9:12:22 time: 0.5032 data_time: 0.0105 memory: 14901 loss: 1.8106 loss_prob: 1.0437 loss_thr: 0.6012 loss_db: 0.1658 2022/11/02 15:22:33 - mmengine - INFO - Epoch(train) [302][25/63] lr: 1.6676e-03 eta: 9:12:22 time: 0.5432 data_time: 0.0411 memory: 14901 loss: 1.7501 loss_prob: 0.9737 loss_thr: 0.6166 loss_db: 0.1598 2022/11/02 15:22:36 - mmengine - INFO - Epoch(train) [302][30/63] lr: 1.6676e-03 eta: 9:12:16 time: 0.5741 data_time: 0.0415 memory: 14901 loss: 1.7082 loss_prob: 0.9677 loss_thr: 0.5808 loss_db: 0.1597 2022/11/02 15:22:39 - mmengine - INFO - Epoch(train) [302][35/63] lr: 1.6676e-03 eta: 9:12:16 time: 0.5797 data_time: 0.0100 memory: 14901 loss: 1.6129 loss_prob: 0.9123 loss_thr: 0.5501 loss_db: 0.1505 2022/11/02 15:22:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:22:42 - mmengine - INFO - Epoch(train) [302][40/63] lr: 1.6676e-03 eta: 9:12:10 time: 0.5779 data_time: 0.0088 memory: 14901 loss: 1.5967 loss_prob: 0.8763 loss_thr: 0.5733 loss_db: 0.1471 2022/11/02 15:22:45 - mmengine - INFO - Epoch(train) [302][45/63] lr: 1.6676e-03 eta: 9:12:10 time: 0.5473 data_time: 0.0101 memory: 14901 loss: 1.5871 loss_prob: 0.8686 loss_thr: 0.5733 loss_db: 0.1452 2022/11/02 15:22:47 - mmengine - INFO - Epoch(train) [302][50/63] lr: 1.6676e-03 eta: 9:12:03 time: 0.5405 data_time: 0.0260 memory: 14901 loss: 1.5465 loss_prob: 0.8603 loss_thr: 0.5431 loss_db: 0.1431 2022/11/02 15:22:50 - mmengine - INFO - Epoch(train) [302][55/63] lr: 1.6676e-03 eta: 9:12:03 time: 0.5213 data_time: 0.0263 memory: 14901 loss: 1.6853 loss_prob: 0.9695 loss_thr: 0.5598 loss_db: 0.1560 2022/11/02 15:22:52 - mmengine - INFO - Epoch(train) [302][60/63] lr: 1.6676e-03 eta: 9:11:54 time: 0.4980 data_time: 0.0117 memory: 14901 loss: 1.6250 loss_prob: 0.9088 loss_thr: 0.5653 loss_db: 0.1508 2022/11/02 15:22:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:23:01 - mmengine - INFO - Epoch(train) [303][5/63] lr: 1.6659e-03 eta: 9:11:54 time: 0.9645 data_time: 0.2790 memory: 14901 loss: 1.6435 loss_prob: 0.9250 loss_thr: 0.5641 loss_db: 0.1543 2022/11/02 15:23:05 - mmengine - INFO - Epoch(train) [303][10/63] lr: 1.6659e-03 eta: 9:11:56 time: 1.0779 data_time: 0.2820 memory: 14901 loss: 1.6520 loss_prob: 0.9326 loss_thr: 0.5647 loss_db: 0.1547 2022/11/02 15:23:07 - mmengine - INFO - Epoch(train) [303][15/63] lr: 1.6659e-03 eta: 9:11:56 time: 0.6208 data_time: 0.0093 memory: 14901 loss: 1.5800 loss_prob: 0.8842 loss_thr: 0.5471 loss_db: 0.1488 2022/11/02 15:23:10 - mmengine - INFO - Epoch(train) [303][20/63] lr: 1.6659e-03 eta: 9:11:49 time: 0.5541 data_time: 0.0079 memory: 14901 loss: 1.8204 loss_prob: 1.0877 loss_thr: 0.5589 loss_db: 0.1738 2022/11/02 15:23:13 - mmengine - INFO - Epoch(train) [303][25/63] lr: 1.6659e-03 eta: 9:11:49 time: 0.6108 data_time: 0.0500 memory: 14901 loss: 1.9076 loss_prob: 1.1560 loss_thr: 0.5733 loss_db: 0.1783 2022/11/02 15:23:16 - mmengine - INFO - Epoch(train) [303][30/63] lr: 1.6659e-03 eta: 9:11:44 time: 0.6214 data_time: 0.0521 memory: 14901 loss: 2.0443 loss_prob: 1.2504 loss_thr: 0.5883 loss_db: 0.2056 2022/11/02 15:23:19 - mmengine - INFO - Epoch(train) [303][35/63] lr: 1.6659e-03 eta: 9:11:44 time: 0.5542 data_time: 0.0124 memory: 14901 loss: 2.0795 loss_prob: 1.2688 loss_thr: 0.5986 loss_db: 0.2120 2022/11/02 15:23:22 - mmengine - INFO - Epoch(train) [303][40/63] lr: 1.6659e-03 eta: 9:11:37 time: 0.5430 data_time: 0.0095 memory: 14901 loss: 1.9608 loss_prob: 1.1611 loss_thr: 0.6165 loss_db: 0.1832 2022/11/02 15:23:24 - mmengine - INFO - Epoch(train) [303][45/63] lr: 1.6659e-03 eta: 9:11:37 time: 0.5344 data_time: 0.0062 memory: 14901 loss: 2.0833 loss_prob: 1.2461 loss_thr: 0.6385 loss_db: 0.1987 2022/11/02 15:23:27 - mmengine - INFO - Epoch(train) [303][50/63] lr: 1.6659e-03 eta: 9:11:30 time: 0.5512 data_time: 0.0250 memory: 14901 loss: 1.9181 loss_prob: 1.1121 loss_thr: 0.6220 loss_db: 0.1840 2022/11/02 15:23:30 - mmengine - INFO - Epoch(train) [303][55/63] lr: 1.6659e-03 eta: 9:11:30 time: 0.5412 data_time: 0.0280 memory: 14901 loss: 1.7560 loss_prob: 0.9847 loss_thr: 0.6048 loss_db: 0.1665 2022/11/02 15:23:33 - mmengine - INFO - Epoch(train) [303][60/63] lr: 1.6659e-03 eta: 9:11:24 time: 0.5592 data_time: 0.0106 memory: 14901 loss: 1.7601 loss_prob: 0.9823 loss_thr: 0.6141 loss_db: 0.1637 2022/11/02 15:23:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:23:40 - mmengine - INFO - Epoch(train) [304][5/63] lr: 1.6642e-03 eta: 9:11:24 time: 0.8797 data_time: 0.2222 memory: 14901 loss: 1.7892 loss_prob: 1.0313 loss_thr: 0.5877 loss_db: 0.1701 2022/11/02 15:23:44 - mmengine - INFO - Epoch(train) [304][10/63] lr: 1.6642e-03 eta: 9:11:23 time: 0.9998 data_time: 0.2229 memory: 14901 loss: 1.7404 loss_prob: 0.9889 loss_thr: 0.5909 loss_db: 0.1607 2022/11/02 15:23:47 - mmengine - INFO - Epoch(train) [304][15/63] lr: 1.6642e-03 eta: 9:11:23 time: 0.6673 data_time: 0.0127 memory: 14901 loss: 1.9550 loss_prob: 1.1575 loss_thr: 0.6083 loss_db: 0.1891 2022/11/02 15:23:50 - mmengine - INFO - Epoch(train) [304][20/63] lr: 1.6642e-03 eta: 9:11:15 time: 0.5168 data_time: 0.0132 memory: 14901 loss: 1.9620 loss_prob: 1.1592 loss_thr: 0.6106 loss_db: 0.1922 2022/11/02 15:23:52 - mmengine - INFO - Epoch(train) [304][25/63] lr: 1.6642e-03 eta: 9:11:15 time: 0.5326 data_time: 0.0162 memory: 14901 loss: 1.7598 loss_prob: 0.9952 loss_thr: 0.6023 loss_db: 0.1622 2022/11/02 15:23:56 - mmengine - INFO - Epoch(train) [304][30/63] lr: 1.6642e-03 eta: 9:11:10 time: 0.6073 data_time: 0.0362 memory: 14901 loss: 1.8055 loss_prob: 1.0247 loss_thr: 0.6153 loss_db: 0.1655 2022/11/02 15:23:58 - mmengine - INFO - Epoch(train) [304][35/63] lr: 1.6642e-03 eta: 9:11:10 time: 0.5634 data_time: 0.0279 memory: 14901 loss: 1.8069 loss_prob: 1.0242 loss_thr: 0.6133 loss_db: 0.1694 2022/11/02 15:24:01 - mmengine - INFO - Epoch(train) [304][40/63] lr: 1.6642e-03 eta: 9:11:03 time: 0.5279 data_time: 0.0077 memory: 14901 loss: 1.7313 loss_prob: 0.9772 loss_thr: 0.5913 loss_db: 0.1627 2022/11/02 15:24:03 - mmengine - INFO - Epoch(train) [304][45/63] lr: 1.6642e-03 eta: 9:11:03 time: 0.5300 data_time: 0.0082 memory: 14901 loss: 1.7282 loss_prob: 0.9938 loss_thr: 0.5689 loss_db: 0.1654 2022/11/02 15:24:06 - mmengine - INFO - Epoch(train) [304][50/63] lr: 1.6642e-03 eta: 9:10:56 time: 0.5565 data_time: 0.0142 memory: 14901 loss: 1.6957 loss_prob: 0.9684 loss_thr: 0.5654 loss_db: 0.1619 2022/11/02 15:24:09 - mmengine - INFO - Epoch(train) [304][55/63] lr: 1.6642e-03 eta: 9:10:56 time: 0.5500 data_time: 0.0260 memory: 14901 loss: 1.6425 loss_prob: 0.9166 loss_thr: 0.5727 loss_db: 0.1532 2022/11/02 15:24:11 - mmengine - INFO - Epoch(train) [304][60/63] lr: 1.6642e-03 eta: 9:10:48 time: 0.5017 data_time: 0.0183 memory: 14901 loss: 1.6069 loss_prob: 0.8892 loss_thr: 0.5681 loss_db: 0.1496 2022/11/02 15:24:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:24:18 - mmengine - INFO - Epoch(train) [305][5/63] lr: 1.6626e-03 eta: 9:10:48 time: 0.7712 data_time: 0.2473 memory: 14901 loss: 1.6983 loss_prob: 0.9546 loss_thr: 0.5852 loss_db: 0.1585 2022/11/02 15:24:21 - mmengine - INFO - Epoch(train) [305][10/63] lr: 1.6626e-03 eta: 9:10:43 time: 0.8528 data_time: 0.2518 memory: 14901 loss: 1.7030 loss_prob: 0.9775 loss_thr: 0.5632 loss_db: 0.1623 2022/11/02 15:24:24 - mmengine - INFO - Epoch(train) [305][15/63] lr: 1.6626e-03 eta: 9:10:43 time: 0.5634 data_time: 0.0154 memory: 14901 loss: 1.6916 loss_prob: 0.9651 loss_thr: 0.5709 loss_db: 0.1556 2022/11/02 15:24:27 - mmengine - INFO - Epoch(train) [305][20/63] lr: 1.6626e-03 eta: 9:10:35 time: 0.5190 data_time: 0.0072 memory: 14901 loss: 1.7980 loss_prob: 1.0391 loss_thr: 0.5892 loss_db: 0.1698 2022/11/02 15:24:29 - mmengine - INFO - Epoch(train) [305][25/63] lr: 1.6626e-03 eta: 9:10:35 time: 0.5515 data_time: 0.0254 memory: 14901 loss: 1.8301 loss_prob: 1.0639 loss_thr: 0.5889 loss_db: 0.1773 2022/11/02 15:24:32 - mmengine - INFO - Epoch(train) [305][30/63] lr: 1.6626e-03 eta: 9:10:29 time: 0.5700 data_time: 0.0384 memory: 14901 loss: 1.7210 loss_prob: 0.9831 loss_thr: 0.5742 loss_db: 0.1637 2022/11/02 15:24:35 - mmengine - INFO - Epoch(train) [305][35/63] lr: 1.6626e-03 eta: 9:10:29 time: 0.6019 data_time: 0.0258 memory: 14901 loss: 1.7028 loss_prob: 0.9669 loss_thr: 0.5758 loss_db: 0.1601 2022/11/02 15:24:38 - mmengine - INFO - Epoch(train) [305][40/63] lr: 1.6626e-03 eta: 9:10:22 time: 0.5554 data_time: 0.0144 memory: 14901 loss: 1.5930 loss_prob: 0.8875 loss_thr: 0.5559 loss_db: 0.1495 2022/11/02 15:24:40 - mmengine - INFO - Epoch(train) [305][45/63] lr: 1.6626e-03 eta: 9:10:22 time: 0.5210 data_time: 0.0090 memory: 14901 loss: 1.5989 loss_prob: 0.9004 loss_thr: 0.5485 loss_db: 0.1500 2022/11/02 15:24:43 - mmengine - INFO - Epoch(train) [305][50/63] lr: 1.6626e-03 eta: 9:10:15 time: 0.5382 data_time: 0.0222 memory: 14901 loss: 1.7016 loss_prob: 0.9654 loss_thr: 0.5781 loss_db: 0.1581 2022/11/02 15:24:46 - mmengine - INFO - Epoch(train) [305][55/63] lr: 1.6626e-03 eta: 9:10:15 time: 0.5365 data_time: 0.0301 memory: 14901 loss: 1.6176 loss_prob: 0.8995 loss_thr: 0.5699 loss_db: 0.1482 2022/11/02 15:24:49 - mmengine - INFO - Epoch(train) [305][60/63] lr: 1.6626e-03 eta: 9:10:08 time: 0.5584 data_time: 0.0151 memory: 14901 loss: 1.5126 loss_prob: 0.8332 loss_thr: 0.5440 loss_db: 0.1354 2022/11/02 15:24:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:24:56 - mmengine - INFO - Epoch(train) [306][5/63] lr: 1.6609e-03 eta: 9:10:08 time: 0.8332 data_time: 0.2604 memory: 14901 loss: 1.4678 loss_prob: 0.8038 loss_thr: 0.5272 loss_db: 0.1368 2022/11/02 15:24:59 - mmengine - INFO - Epoch(train) [306][10/63] lr: 1.6609e-03 eta: 9:10:04 time: 0.8713 data_time: 0.2619 memory: 14901 loss: 1.5263 loss_prob: 0.8453 loss_thr: 0.5410 loss_db: 0.1400 2022/11/02 15:25:02 - mmengine - INFO - Epoch(train) [306][15/63] lr: 1.6609e-03 eta: 9:10:04 time: 0.5877 data_time: 0.0134 memory: 14901 loss: 1.6311 loss_prob: 0.9280 loss_thr: 0.5529 loss_db: 0.1501 2022/11/02 15:25:05 - mmengine - INFO - Epoch(train) [306][20/63] lr: 1.6609e-03 eta: 9:09:58 time: 0.5872 data_time: 0.0138 memory: 14901 loss: 1.5615 loss_prob: 0.8691 loss_thr: 0.5473 loss_db: 0.1452 2022/11/02 15:25:08 - mmengine - INFO - Epoch(train) [306][25/63] lr: 1.6609e-03 eta: 9:09:58 time: 0.5560 data_time: 0.0274 memory: 14901 loss: 1.5335 loss_prob: 0.8371 loss_thr: 0.5588 loss_db: 0.1376 2022/11/02 15:25:10 - mmengine - INFO - Epoch(train) [306][30/63] lr: 1.6609e-03 eta: 9:09:51 time: 0.5444 data_time: 0.0356 memory: 14901 loss: 1.4836 loss_prob: 0.8069 loss_thr: 0.5440 loss_db: 0.1327 2022/11/02 15:25:13 - mmengine - INFO - Epoch(train) [306][35/63] lr: 1.6609e-03 eta: 9:09:51 time: 0.5117 data_time: 0.0190 memory: 14901 loss: 1.4911 loss_prob: 0.8213 loss_thr: 0.5292 loss_db: 0.1406 2022/11/02 15:25:15 - mmengine - INFO - Epoch(train) [306][40/63] lr: 1.6609e-03 eta: 9:09:43 time: 0.5115 data_time: 0.0058 memory: 14901 loss: 1.5734 loss_prob: 0.8837 loss_thr: 0.5424 loss_db: 0.1473 2022/11/02 15:25:18 - mmengine - INFO - Epoch(train) [306][45/63] lr: 1.6609e-03 eta: 9:09:43 time: 0.4971 data_time: 0.0072 memory: 14901 loss: 1.6320 loss_prob: 0.9353 loss_thr: 0.5418 loss_db: 0.1549 2022/11/02 15:25:20 - mmengine - INFO - Epoch(train) [306][50/63] lr: 1.6609e-03 eta: 9:09:34 time: 0.5017 data_time: 0.0309 memory: 14901 loss: 1.6133 loss_prob: 0.9209 loss_thr: 0.5412 loss_db: 0.1513 2022/11/02 15:25:23 - mmengine - INFO - Epoch(train) [306][55/63] lr: 1.6609e-03 eta: 9:09:34 time: 0.4874 data_time: 0.0299 memory: 14901 loss: 1.8762 loss_prob: 1.1214 loss_thr: 0.5844 loss_db: 0.1705 2022/11/02 15:25:25 - mmengine - INFO - Epoch(train) [306][60/63] lr: 1.6609e-03 eta: 9:09:26 time: 0.4834 data_time: 0.0065 memory: 14901 loss: 2.0322 loss_prob: 1.2425 loss_thr: 0.5980 loss_db: 0.1917 2022/11/02 15:25:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:25:31 - mmengine - INFO - Epoch(train) [307][5/63] lr: 1.6592e-03 eta: 9:09:26 time: 0.7262 data_time: 0.2428 memory: 14901 loss: 2.6916 loss_prob: 1.7701 loss_thr: 0.6444 loss_db: 0.2770 2022/11/02 15:25:34 - mmengine - INFO - Epoch(train) [307][10/63] lr: 1.6592e-03 eta: 9:09:17 time: 0.7360 data_time: 0.2386 memory: 14901 loss: 2.9604 loss_prob: 1.9543 loss_thr: 0.7056 loss_db: 0.3005 2022/11/02 15:25:37 - mmengine - INFO - Epoch(train) [307][15/63] lr: 1.6592e-03 eta: 9:09:17 time: 0.5275 data_time: 0.0132 memory: 14901 loss: 2.5850 loss_prob: 1.6398 loss_thr: 0.6900 loss_db: 0.2553 2022/11/02 15:25:40 - mmengine - INFO - Epoch(train) [307][20/63] lr: 1.6592e-03 eta: 9:09:12 time: 0.6014 data_time: 0.0130 memory: 14901 loss: 2.1756 loss_prob: 1.3227 loss_thr: 0.6448 loss_db: 0.2081 2022/11/02 15:25:43 - mmengine - INFO - Epoch(train) [307][25/63] lr: 1.6592e-03 eta: 9:09:12 time: 0.6002 data_time: 0.0265 memory: 14901 loss: 2.0862 loss_prob: 1.2597 loss_thr: 0.6187 loss_db: 0.2078 2022/11/02 15:25:46 - mmengine - INFO - Epoch(train) [307][30/63] lr: 1.6592e-03 eta: 9:09:06 time: 0.5871 data_time: 0.0405 memory: 14901 loss: 1.9647 loss_prob: 1.1695 loss_thr: 0.6046 loss_db: 0.1906 2022/11/02 15:25:48 - mmengine - INFO - Epoch(train) [307][35/63] lr: 1.6592e-03 eta: 9:09:06 time: 0.5693 data_time: 0.0212 memory: 14901 loss: 2.0846 loss_prob: 1.2482 loss_thr: 0.6382 loss_db: 0.1981 2022/11/02 15:25:51 - mmengine - INFO - Epoch(train) [307][40/63] lr: 1.6592e-03 eta: 9:09:00 time: 0.5620 data_time: 0.0105 memory: 14901 loss: 2.1112 loss_prob: 1.2701 loss_thr: 0.6363 loss_db: 0.2048 2022/11/02 15:25:54 - mmengine - INFO - Epoch(train) [307][45/63] lr: 1.6592e-03 eta: 9:09:00 time: 0.5992 data_time: 0.0119 memory: 14901 loss: 2.0697 loss_prob: 1.2597 loss_thr: 0.6130 loss_db: 0.1971 2022/11/02 15:25:57 - mmengine - INFO - Epoch(train) [307][50/63] lr: 1.6592e-03 eta: 9:08:55 time: 0.6244 data_time: 0.0283 memory: 14901 loss: 2.0796 loss_prob: 1.2657 loss_thr: 0.6182 loss_db: 0.1957 2022/11/02 15:26:00 - mmengine - INFO - Epoch(train) [307][55/63] lr: 1.6592e-03 eta: 9:08:55 time: 0.5695 data_time: 0.0274 memory: 14901 loss: 1.9941 loss_prob: 1.1838 loss_thr: 0.6190 loss_db: 0.1912 2022/11/02 15:26:03 - mmengine - INFO - Epoch(train) [307][60/63] lr: 1.6592e-03 eta: 9:08:48 time: 0.5457 data_time: 0.0070 memory: 14901 loss: 1.7256 loss_prob: 0.9924 loss_thr: 0.5715 loss_db: 0.1617 2022/11/02 15:26:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:26:09 - mmengine - INFO - Epoch(train) [308][5/63] lr: 1.6575e-03 eta: 9:08:48 time: 0.7328 data_time: 0.2208 memory: 14901 loss: 1.8353 loss_prob: 1.0802 loss_thr: 0.5831 loss_db: 0.1721 2022/11/02 15:26:12 - mmengine - INFO - Epoch(train) [308][10/63] lr: 1.6575e-03 eta: 9:08:41 time: 0.7861 data_time: 0.2197 memory: 14901 loss: 1.7938 loss_prob: 1.0344 loss_thr: 0.5948 loss_db: 0.1646 2022/11/02 15:26:15 - mmengine - INFO - Epoch(train) [308][15/63] lr: 1.6575e-03 eta: 9:08:41 time: 0.5444 data_time: 0.0097 memory: 14901 loss: 1.7561 loss_prob: 1.0058 loss_thr: 0.5882 loss_db: 0.1621 2022/11/02 15:26:18 - mmengine - INFO - Epoch(train) [308][20/63] lr: 1.6575e-03 eta: 9:08:34 time: 0.5477 data_time: 0.0072 memory: 14901 loss: 1.6868 loss_prob: 0.9541 loss_thr: 0.5753 loss_db: 0.1574 2022/11/02 15:26:20 - mmengine - INFO - Epoch(train) [308][25/63] lr: 1.6575e-03 eta: 9:08:34 time: 0.5541 data_time: 0.0280 memory: 14901 loss: 1.7345 loss_prob: 0.9753 loss_thr: 0.5992 loss_db: 0.1601 2022/11/02 15:26:23 - mmengine - INFO - Epoch(train) [308][30/63] lr: 1.6575e-03 eta: 9:08:27 time: 0.5441 data_time: 0.0514 memory: 14901 loss: 1.7238 loss_prob: 0.9747 loss_thr: 0.5852 loss_db: 0.1640 2022/11/02 15:26:25 - mmengine - INFO - Epoch(train) [308][35/63] lr: 1.6575e-03 eta: 9:08:27 time: 0.5293 data_time: 0.0296 memory: 14901 loss: 1.6846 loss_prob: 0.9482 loss_thr: 0.5782 loss_db: 0.1581 2022/11/02 15:26:28 - mmengine - INFO - Epoch(train) [308][40/63] lr: 1.6575e-03 eta: 9:08:19 time: 0.5225 data_time: 0.0056 memory: 14901 loss: 1.6941 loss_prob: 0.9558 loss_thr: 0.5824 loss_db: 0.1559 2022/11/02 15:26:31 - mmengine - INFO - Epoch(train) [308][45/63] lr: 1.6575e-03 eta: 9:08:19 time: 0.5645 data_time: 0.0091 memory: 14901 loss: 1.6288 loss_prob: 0.9236 loss_thr: 0.5528 loss_db: 0.1524 2022/11/02 15:26:34 - mmengine - INFO - Epoch(train) [308][50/63] lr: 1.6575e-03 eta: 9:08:13 time: 0.5798 data_time: 0.0200 memory: 14901 loss: 1.5238 loss_prob: 0.8537 loss_thr: 0.5292 loss_db: 0.1409 2022/11/02 15:26:37 - mmengine - INFO - Epoch(train) [308][55/63] lr: 1.6575e-03 eta: 9:08:13 time: 0.5801 data_time: 0.0262 memory: 14901 loss: 1.6175 loss_prob: 0.9140 loss_thr: 0.5524 loss_db: 0.1512 2022/11/02 15:26:40 - mmengine - INFO - Epoch(train) [308][60/63] lr: 1.6575e-03 eta: 9:08:07 time: 0.5793 data_time: 0.0235 memory: 14901 loss: 1.6521 loss_prob: 0.9395 loss_thr: 0.5572 loss_db: 0.1554 2022/11/02 15:26:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:26:48 - mmengine - INFO - Epoch(train) [309][5/63] lr: 1.6559e-03 eta: 9:08:07 time: 0.9169 data_time: 0.2116 memory: 14901 loss: 1.6731 loss_prob: 0.9402 loss_thr: 0.5773 loss_db: 0.1556 2022/11/02 15:26:50 - mmengine - INFO - Epoch(train) [309][10/63] lr: 1.6559e-03 eta: 9:08:04 time: 0.9122 data_time: 0.2122 memory: 14901 loss: 1.6294 loss_prob: 0.9184 loss_thr: 0.5567 loss_db: 0.1543 2022/11/02 15:26:53 - mmengine - INFO - Epoch(train) [309][15/63] lr: 1.6559e-03 eta: 9:08:04 time: 0.5399 data_time: 0.0153 memory: 14901 loss: 1.6370 loss_prob: 0.9313 loss_thr: 0.5504 loss_db: 0.1553 2022/11/02 15:26:56 - mmengine - INFO - Epoch(train) [309][20/63] lr: 1.6559e-03 eta: 9:07:57 time: 0.5357 data_time: 0.0153 memory: 14901 loss: 1.6431 loss_prob: 0.9224 loss_thr: 0.5649 loss_db: 0.1558 2022/11/02 15:26:59 - mmengine - INFO - Epoch(train) [309][25/63] lr: 1.6559e-03 eta: 9:07:57 time: 0.5812 data_time: 0.0173 memory: 14901 loss: 1.5845 loss_prob: 0.8794 loss_thr: 0.5532 loss_db: 0.1519 2022/11/02 15:27:02 - mmengine - INFO - Epoch(train) [309][30/63] lr: 1.6559e-03 eta: 9:07:51 time: 0.5844 data_time: 0.0456 memory: 14901 loss: 1.6620 loss_prob: 0.9447 loss_thr: 0.5577 loss_db: 0.1596 2022/11/02 15:27:05 - mmengine - INFO - Epoch(train) [309][35/63] lr: 1.6559e-03 eta: 9:07:51 time: 0.6004 data_time: 0.0421 memory: 14901 loss: 1.8382 loss_prob: 1.0682 loss_thr: 0.5980 loss_db: 0.1720 2022/11/02 15:27:07 - mmengine - INFO - Epoch(train) [309][40/63] lr: 1.6559e-03 eta: 9:07:44 time: 0.5654 data_time: 0.0160 memory: 14901 loss: 1.9369 loss_prob: 1.1509 loss_thr: 0.6071 loss_db: 0.1789 2022/11/02 15:27:11 - mmengine - INFO - Epoch(train) [309][45/63] lr: 1.6559e-03 eta: 9:07:44 time: 0.5856 data_time: 0.0081 memory: 14901 loss: 1.8141 loss_prob: 1.0570 loss_thr: 0.5897 loss_db: 0.1675 2022/11/02 15:27:14 - mmengine - INFO - Epoch(train) [309][50/63] lr: 1.6559e-03 eta: 9:07:40 time: 0.6348 data_time: 0.0137 memory: 14901 loss: 1.6073 loss_prob: 0.8995 loss_thr: 0.5591 loss_db: 0.1487 2022/11/02 15:27:17 - mmengine - INFO - Epoch(train) [309][55/63] lr: 1.6559e-03 eta: 9:07:40 time: 0.5840 data_time: 0.0298 memory: 14901 loss: 1.5291 loss_prob: 0.8512 loss_thr: 0.5337 loss_db: 0.1441 2022/11/02 15:27:19 - mmengine - INFO - Epoch(train) [309][60/63] lr: 1.6559e-03 eta: 9:07:33 time: 0.5594 data_time: 0.0235 memory: 14901 loss: 1.5322 loss_prob: 0.8562 loss_thr: 0.5314 loss_db: 0.1446 2022/11/02 15:27:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:27:26 - mmengine - INFO - Epoch(train) [310][5/63] lr: 1.6542e-03 eta: 9:07:33 time: 0.7728 data_time: 0.2659 memory: 14901 loss: 1.5586 loss_prob: 0.8784 loss_thr: 0.5342 loss_db: 0.1460 2022/11/02 15:27:29 - mmengine - INFO - Epoch(train) [310][10/63] lr: 1.6542e-03 eta: 9:07:27 time: 0.7936 data_time: 0.2640 memory: 14901 loss: 1.6722 loss_prob: 0.9577 loss_thr: 0.5578 loss_db: 0.1568 2022/11/02 15:27:31 - mmengine - INFO - Epoch(train) [310][15/63] lr: 1.6542e-03 eta: 9:07:27 time: 0.5252 data_time: 0.0123 memory: 14901 loss: 1.6753 loss_prob: 0.9428 loss_thr: 0.5792 loss_db: 0.1533 2022/11/02 15:27:34 - mmengine - INFO - Epoch(train) [310][20/63] lr: 1.6542e-03 eta: 9:07:19 time: 0.5180 data_time: 0.0077 memory: 14901 loss: 1.6508 loss_prob: 0.9131 loss_thr: 0.5865 loss_db: 0.1512 2022/11/02 15:27:36 - mmengine - INFO - Epoch(train) [310][25/63] lr: 1.6542e-03 eta: 9:07:19 time: 0.5151 data_time: 0.0211 memory: 14901 loss: 1.6762 loss_prob: 0.9378 loss_thr: 0.5824 loss_db: 0.1560 2022/11/02 15:27:39 - mmengine - INFO - Epoch(train) [310][30/63] lr: 1.6542e-03 eta: 9:07:12 time: 0.5509 data_time: 0.0371 memory: 14901 loss: 1.7219 loss_prob: 0.9908 loss_thr: 0.5715 loss_db: 0.1596 2022/11/02 15:27:42 - mmengine - INFO - Epoch(train) [310][35/63] lr: 1.6542e-03 eta: 9:07:12 time: 0.5691 data_time: 0.0251 memory: 14901 loss: 1.7059 loss_prob: 0.9867 loss_thr: 0.5609 loss_db: 0.1583 2022/11/02 15:27:44 - mmengine - INFO - Epoch(train) [310][40/63] lr: 1.6542e-03 eta: 9:07:04 time: 0.5005 data_time: 0.0092 memory: 14901 loss: 1.6321 loss_prob: 0.9167 loss_thr: 0.5633 loss_db: 0.1520 2022/11/02 15:27:47 - mmengine - INFO - Epoch(train) [310][45/63] lr: 1.6542e-03 eta: 9:07:04 time: 0.5316 data_time: 0.0089 memory: 14901 loss: 1.6639 loss_prob: 0.9399 loss_thr: 0.5687 loss_db: 0.1553 2022/11/02 15:27:51 - mmengine - INFO - Epoch(train) [310][50/63] lr: 1.6542e-03 eta: 9:07:00 time: 0.6664 data_time: 0.0211 memory: 14901 loss: 1.6654 loss_prob: 0.9408 loss_thr: 0.5696 loss_db: 0.1549 2022/11/02 15:27:54 - mmengine - INFO - Epoch(train) [310][55/63] lr: 1.6542e-03 eta: 9:07:00 time: 0.7059 data_time: 0.0255 memory: 14901 loss: 1.6115 loss_prob: 0.8994 loss_thr: 0.5638 loss_db: 0.1484 2022/11/02 15:27:57 - mmengine - INFO - Epoch(train) [310][60/63] lr: 1.6542e-03 eta: 9:06:56 time: 0.6244 data_time: 0.0157 memory: 14901 loss: 1.6808 loss_prob: 0.9643 loss_thr: 0.5592 loss_db: 0.1573 2022/11/02 15:27:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:28:05 - mmengine - INFO - Epoch(train) [311][5/63] lr: 1.6525e-03 eta: 9:06:56 time: 0.8650 data_time: 0.2411 memory: 14901 loss: 1.6435 loss_prob: 0.9289 loss_thr: 0.5629 loss_db: 0.1517 2022/11/02 15:28:07 - mmengine - INFO - Epoch(train) [311][10/63] lr: 1.6525e-03 eta: 9:06:51 time: 0.8683 data_time: 0.2474 memory: 14901 loss: 1.6065 loss_prob: 0.9012 loss_thr: 0.5525 loss_db: 0.1528 2022/11/02 15:28:10 - mmengine - INFO - Epoch(train) [311][15/63] lr: 1.6525e-03 eta: 9:06:51 time: 0.5604 data_time: 0.0172 memory: 14901 loss: 1.7172 loss_prob: 0.9702 loss_thr: 0.5836 loss_db: 0.1633 2022/11/02 15:28:13 - mmengine - INFO - Epoch(train) [311][20/63] lr: 1.6525e-03 eta: 9:06:44 time: 0.5414 data_time: 0.0105 memory: 14901 loss: 1.6890 loss_prob: 0.9616 loss_thr: 0.5704 loss_db: 0.1569 2022/11/02 15:28:16 - mmengine - INFO - Epoch(train) [311][25/63] lr: 1.6525e-03 eta: 9:06:44 time: 0.5449 data_time: 0.0316 memory: 14901 loss: 1.5938 loss_prob: 0.9077 loss_thr: 0.5397 loss_db: 0.1463 2022/11/02 15:28:18 - mmengine - INFO - Epoch(train) [311][30/63] lr: 1.6525e-03 eta: 9:06:36 time: 0.5265 data_time: 0.0368 memory: 14901 loss: 1.6750 loss_prob: 0.9707 loss_thr: 0.5447 loss_db: 0.1596 2022/11/02 15:28:21 - mmengine - INFO - Epoch(train) [311][35/63] lr: 1.6525e-03 eta: 9:06:36 time: 0.4891 data_time: 0.0208 memory: 14901 loss: 1.7314 loss_prob: 0.9995 loss_thr: 0.5665 loss_db: 0.1654 2022/11/02 15:28:23 - mmengine - INFO - Epoch(train) [311][40/63] lr: 1.6525e-03 eta: 9:06:29 time: 0.5293 data_time: 0.0142 memory: 14901 loss: 1.6298 loss_prob: 0.9025 loss_thr: 0.5748 loss_db: 0.1524 2022/11/02 15:28:26 - mmengine - INFO - Epoch(train) [311][45/63] lr: 1.6525e-03 eta: 9:06:29 time: 0.5484 data_time: 0.0081 memory: 14901 loss: 1.6774 loss_prob: 0.9376 loss_thr: 0.5846 loss_db: 0.1552 2022/11/02 15:28:29 - mmengine - INFO - Epoch(train) [311][50/63] lr: 1.6525e-03 eta: 9:06:22 time: 0.5361 data_time: 0.0260 memory: 14901 loss: 1.6485 loss_prob: 0.9330 loss_thr: 0.5646 loss_db: 0.1509 2022/11/02 15:28:31 - mmengine - INFO - Epoch(train) [311][55/63] lr: 1.6525e-03 eta: 9:06:22 time: 0.5425 data_time: 0.0294 memory: 14901 loss: 1.7425 loss_prob: 0.9945 loss_thr: 0.5817 loss_db: 0.1664 2022/11/02 15:28:34 - mmengine - INFO - Epoch(train) [311][60/63] lr: 1.6525e-03 eta: 9:06:14 time: 0.5304 data_time: 0.0139 memory: 14901 loss: 1.8067 loss_prob: 1.0293 loss_thr: 0.6022 loss_db: 0.1752 2022/11/02 15:28:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:28:42 - mmengine - INFO - Epoch(train) [312][5/63] lr: 1.6509e-03 eta: 9:06:14 time: 0.9304 data_time: 0.2380 memory: 14901 loss: 1.6148 loss_prob: 0.9260 loss_thr: 0.5351 loss_db: 0.1537 2022/11/02 15:28:45 - mmengine - INFO - Epoch(train) [312][10/63] lr: 1.6509e-03 eta: 9:06:11 time: 0.9004 data_time: 0.2384 memory: 14901 loss: 1.6116 loss_prob: 0.9114 loss_thr: 0.5498 loss_db: 0.1504 2022/11/02 15:28:48 - mmengine - INFO - Epoch(train) [312][15/63] lr: 1.6509e-03 eta: 9:06:11 time: 0.5844 data_time: 0.0098 memory: 14901 loss: 1.6561 loss_prob: 0.9274 loss_thr: 0.5750 loss_db: 0.1536 2022/11/02 15:28:51 - mmengine - INFO - Epoch(train) [312][20/63] lr: 1.6509e-03 eta: 9:06:04 time: 0.5401 data_time: 0.0085 memory: 14901 loss: 1.6051 loss_prob: 0.9014 loss_thr: 0.5523 loss_db: 0.1514 2022/11/02 15:28:53 - mmengine - INFO - Epoch(train) [312][25/63] lr: 1.6509e-03 eta: 9:06:04 time: 0.5239 data_time: 0.0127 memory: 14901 loss: 1.5847 loss_prob: 0.8845 loss_thr: 0.5535 loss_db: 0.1467 2022/11/02 15:28:57 - mmengine - INFO - Epoch(train) [312][30/63] lr: 1.6509e-03 eta: 9:05:58 time: 0.5980 data_time: 0.0399 memory: 14901 loss: 1.5718 loss_prob: 0.8792 loss_thr: 0.5472 loss_db: 0.1453 2022/11/02 15:28:59 - mmengine - INFO - Epoch(train) [312][35/63] lr: 1.6509e-03 eta: 9:05:58 time: 0.5931 data_time: 0.0329 memory: 14901 loss: 1.5724 loss_prob: 0.8802 loss_thr: 0.5480 loss_db: 0.1443 2022/11/02 15:29:02 - mmengine - INFO - Epoch(train) [312][40/63] lr: 1.6509e-03 eta: 9:05:50 time: 0.5126 data_time: 0.0057 memory: 14901 loss: 1.6309 loss_prob: 0.9202 loss_thr: 0.5578 loss_db: 0.1528 2022/11/02 15:29:04 - mmengine - INFO - Epoch(train) [312][45/63] lr: 1.6509e-03 eta: 9:05:50 time: 0.5050 data_time: 0.0087 memory: 14901 loss: 1.6708 loss_prob: 0.9474 loss_thr: 0.5650 loss_db: 0.1584 2022/11/02 15:29:07 - mmengine - INFO - Epoch(train) [312][50/63] lr: 1.6509e-03 eta: 9:05:43 time: 0.5553 data_time: 0.0319 memory: 14901 loss: 1.7412 loss_prob: 0.9881 loss_thr: 0.5884 loss_db: 0.1647 2022/11/02 15:29:10 - mmengine - INFO - Epoch(train) [312][55/63] lr: 1.6509e-03 eta: 9:05:43 time: 0.5716 data_time: 0.0339 memory: 14901 loss: 1.8736 loss_prob: 1.0938 loss_thr: 0.6019 loss_db: 0.1779 2022/11/02 15:29:13 - mmengine - INFO - Epoch(train) [312][60/63] lr: 1.6509e-03 eta: 9:05:36 time: 0.5408 data_time: 0.0141 memory: 14901 loss: 2.0019 loss_prob: 1.2011 loss_thr: 0.6082 loss_db: 0.1925 2022/11/02 15:29:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:29:22 - mmengine - INFO - Epoch(train) [313][5/63] lr: 1.6492e-03 eta: 9:05:36 time: 0.9913 data_time: 0.2461 memory: 14901 loss: 1.8948 loss_prob: 1.1018 loss_thr: 0.6118 loss_db: 0.1812 2022/11/02 15:29:24 - mmengine - INFO - Epoch(train) [313][10/63] lr: 1.6492e-03 eta: 9:05:35 time: 0.9673 data_time: 0.2488 memory: 14901 loss: 1.8649 loss_prob: 1.0969 loss_thr: 0.5842 loss_db: 0.1838 2022/11/02 15:29:27 - mmengine - INFO - Epoch(train) [313][15/63] lr: 1.6492e-03 eta: 9:05:35 time: 0.5614 data_time: 0.0149 memory: 14901 loss: 1.9304 loss_prob: 1.1429 loss_thr: 0.5961 loss_db: 0.1914 2022/11/02 15:29:31 - mmengine - INFO - Epoch(train) [313][20/63] lr: 1.6492e-03 eta: 9:05:31 time: 0.6535 data_time: 0.0148 memory: 14901 loss: 2.0076 loss_prob: 1.1854 loss_thr: 0.6310 loss_db: 0.1912 2022/11/02 15:29:33 - mmengine - INFO - Epoch(train) [313][25/63] lr: 1.6492e-03 eta: 9:05:31 time: 0.6025 data_time: 0.0326 memory: 14901 loss: 1.9868 loss_prob: 1.1721 loss_thr: 0.6275 loss_db: 0.1871 2022/11/02 15:29:36 - mmengine - INFO - Epoch(train) [313][30/63] lr: 1.6492e-03 eta: 9:05:24 time: 0.5650 data_time: 0.0482 memory: 14901 loss: 1.9984 loss_prob: 1.2012 loss_thr: 0.6015 loss_db: 0.1956 2022/11/02 15:29:39 - mmengine - INFO - Epoch(train) [313][35/63] lr: 1.6492e-03 eta: 9:05:24 time: 0.5421 data_time: 0.0255 memory: 14901 loss: 1.9710 loss_prob: 1.1823 loss_thr: 0.5979 loss_db: 0.1907 2022/11/02 15:29:42 - mmengine - INFO - Epoch(train) [313][40/63] lr: 1.6492e-03 eta: 9:05:17 time: 0.5354 data_time: 0.0067 memory: 14901 loss: 1.8850 loss_prob: 1.1009 loss_thr: 0.6025 loss_db: 0.1817 2022/11/02 15:29:44 - mmengine - INFO - Epoch(train) [313][45/63] lr: 1.6492e-03 eta: 9:05:17 time: 0.5549 data_time: 0.0131 memory: 14901 loss: 1.7634 loss_prob: 1.0122 loss_thr: 0.5763 loss_db: 0.1750 2022/11/02 15:29:47 - mmengine - INFO - Epoch(train) [313][50/63] lr: 1.6492e-03 eta: 9:05:10 time: 0.5315 data_time: 0.0263 memory: 14901 loss: 1.6643 loss_prob: 0.9503 loss_thr: 0.5535 loss_db: 0.1605 2022/11/02 15:29:50 - mmengine - INFO - Epoch(train) [313][55/63] lr: 1.6492e-03 eta: 9:05:10 time: 0.5277 data_time: 0.0230 memory: 14901 loss: 1.6068 loss_prob: 0.9049 loss_thr: 0.5558 loss_db: 0.1461 2022/11/02 15:29:52 - mmengine - INFO - Epoch(train) [313][60/63] lr: 1.6492e-03 eta: 9:05:02 time: 0.5406 data_time: 0.0099 memory: 14901 loss: 1.6739 loss_prob: 0.9369 loss_thr: 0.5826 loss_db: 0.1543 2022/11/02 15:29:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:30:00 - mmengine - INFO - Epoch(train) [314][5/63] lr: 1.6475e-03 eta: 9:05:02 time: 0.8534 data_time: 0.2576 memory: 14901 loss: 1.6834 loss_prob: 0.9473 loss_thr: 0.5801 loss_db: 0.1560 2022/11/02 15:30:03 - mmengine - INFO - Epoch(train) [314][10/63] lr: 1.6475e-03 eta: 9:04:59 time: 0.8904 data_time: 0.2602 memory: 14901 loss: 1.7152 loss_prob: 0.9760 loss_thr: 0.5803 loss_db: 0.1590 2022/11/02 15:30:06 - mmengine - INFO - Epoch(train) [314][15/63] lr: 1.6475e-03 eta: 9:04:59 time: 0.6326 data_time: 0.0106 memory: 14901 loss: 1.6892 loss_prob: 0.9517 loss_thr: 0.5810 loss_db: 0.1565 2022/11/02 15:30:09 - mmengine - INFO - Epoch(train) [314][20/63] lr: 1.6475e-03 eta: 9:04:54 time: 0.6467 data_time: 0.0079 memory: 14901 loss: 1.5776 loss_prob: 0.8840 loss_thr: 0.5422 loss_db: 0.1513 2022/11/02 15:30:12 - mmengine - INFO - Epoch(train) [314][25/63] lr: 1.6475e-03 eta: 9:04:54 time: 0.6265 data_time: 0.0421 memory: 14901 loss: 1.5395 loss_prob: 0.8544 loss_thr: 0.5393 loss_db: 0.1458 2022/11/02 15:30:15 - mmengine - INFO - Epoch(train) [314][30/63] lr: 1.6475e-03 eta: 9:04:50 time: 0.6483 data_time: 0.0472 memory: 14901 loss: 1.5907 loss_prob: 0.8728 loss_thr: 0.5766 loss_db: 0.1413 2022/11/02 15:30:18 - mmengine - INFO - Epoch(train) [314][35/63] lr: 1.6475e-03 eta: 9:04:50 time: 0.5745 data_time: 0.0106 memory: 14901 loss: 1.6791 loss_prob: 0.9355 loss_thr: 0.5901 loss_db: 0.1535 2022/11/02 15:30:21 - mmengine - INFO - Epoch(train) [314][40/63] lr: 1.6475e-03 eta: 9:04:43 time: 0.5441 data_time: 0.0086 memory: 14901 loss: 1.6378 loss_prob: 0.9192 loss_thr: 0.5643 loss_db: 0.1543 2022/11/02 15:30:24 - mmengine - INFO - Epoch(train) [314][45/63] lr: 1.6475e-03 eta: 9:04:43 time: 0.5341 data_time: 0.0086 memory: 14901 loss: 1.5667 loss_prob: 0.8660 loss_thr: 0.5534 loss_db: 0.1474 2022/11/02 15:30:26 - mmengine - INFO - Epoch(train) [314][50/63] lr: 1.6475e-03 eta: 9:04:35 time: 0.5121 data_time: 0.0228 memory: 14901 loss: 1.5743 loss_prob: 0.8714 loss_thr: 0.5559 loss_db: 0.1470 2022/11/02 15:30:28 - mmengine - INFO - Epoch(train) [314][55/63] lr: 1.6475e-03 eta: 9:04:35 time: 0.4848 data_time: 0.0248 memory: 14901 loss: 1.5314 loss_prob: 0.8518 loss_thr: 0.5389 loss_db: 0.1407 2022/11/02 15:30:31 - mmengine - INFO - Epoch(train) [314][60/63] lr: 1.6475e-03 eta: 9:04:26 time: 0.4689 data_time: 0.0066 memory: 14901 loss: 1.8909 loss_prob: 1.1269 loss_thr: 0.5761 loss_db: 0.1878 2022/11/02 15:30:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:30:37 - mmengine - INFO - Epoch(train) [315][5/63] lr: 1.6458e-03 eta: 9:04:26 time: 0.6715 data_time: 0.2208 memory: 14901 loss: 1.8243 loss_prob: 1.0758 loss_thr: 0.5769 loss_db: 0.1715 2022/11/02 15:30:39 - mmengine - INFO - Epoch(train) [315][10/63] lr: 1.6458e-03 eta: 9:04:17 time: 0.7048 data_time: 0.2214 memory: 14901 loss: 1.7941 loss_prob: 1.0484 loss_thr: 0.5748 loss_db: 0.1709 2022/11/02 15:30:42 - mmengine - INFO - Epoch(train) [315][15/63] lr: 1.6458e-03 eta: 9:04:17 time: 0.5182 data_time: 0.0058 memory: 14901 loss: 1.7447 loss_prob: 1.0038 loss_thr: 0.5735 loss_db: 0.1674 2022/11/02 15:30:44 - mmengine - INFO - Epoch(train) [315][20/63] lr: 1.6458e-03 eta: 9:04:10 time: 0.5435 data_time: 0.0093 memory: 14901 loss: 1.8001 loss_prob: 1.0459 loss_thr: 0.5782 loss_db: 0.1761 2022/11/02 15:30:47 - mmengine - INFO - Epoch(train) [315][25/63] lr: 1.6458e-03 eta: 9:04:10 time: 0.5455 data_time: 0.0441 memory: 14901 loss: 1.9402 loss_prob: 1.1456 loss_thr: 0.6068 loss_db: 0.1877 2022/11/02 15:30:50 - mmengine - INFO - Epoch(train) [315][30/63] lr: 1.6458e-03 eta: 9:04:04 time: 0.5603 data_time: 0.0647 memory: 14901 loss: 1.8316 loss_prob: 1.0602 loss_thr: 0.5981 loss_db: 0.1733 2022/11/02 15:30:52 - mmengine - INFO - Epoch(train) [315][35/63] lr: 1.6458e-03 eta: 9:04:04 time: 0.5121 data_time: 0.0327 memory: 14901 loss: 1.6838 loss_prob: 0.9503 loss_thr: 0.5718 loss_db: 0.1616 2022/11/02 15:30:55 - mmengine - INFO - Epoch(train) [315][40/63] lr: 1.6458e-03 eta: 9:03:55 time: 0.4964 data_time: 0.0163 memory: 14901 loss: 1.7283 loss_prob: 0.9889 loss_thr: 0.5774 loss_db: 0.1620 2022/11/02 15:30:58 - mmengine - INFO - Epoch(train) [315][45/63] lr: 1.6458e-03 eta: 9:03:55 time: 0.5396 data_time: 0.0137 memory: 14901 loss: 1.8386 loss_prob: 1.0741 loss_thr: 0.5930 loss_db: 0.1715 2022/11/02 15:31:00 - mmengine - INFO - Epoch(train) [315][50/63] lr: 1.6458e-03 eta: 9:03:48 time: 0.5302 data_time: 0.0226 memory: 14901 loss: 1.7497 loss_prob: 1.0025 loss_thr: 0.5820 loss_db: 0.1652 2022/11/02 15:31:03 - mmengine - INFO - Epoch(train) [315][55/63] lr: 1.6458e-03 eta: 9:03:48 time: 0.5432 data_time: 0.0276 memory: 14901 loss: 1.6738 loss_prob: 0.9391 loss_thr: 0.5771 loss_db: 0.1577 2022/11/02 15:31:06 - mmengine - INFO - Epoch(train) [315][60/63] lr: 1.6458e-03 eta: 9:03:41 time: 0.5373 data_time: 0.0129 memory: 14901 loss: 1.6940 loss_prob: 0.9648 loss_thr: 0.5682 loss_db: 0.1609 2022/11/02 15:31:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:31:12 - mmengine - INFO - Epoch(train) [316][5/63] lr: 1.6442e-03 eta: 9:03:41 time: 0.7569 data_time: 0.2458 memory: 14901 loss: 1.6504 loss_prob: 0.9313 loss_thr: 0.5630 loss_db: 0.1561 2022/11/02 15:31:15 - mmengine - INFO - Epoch(train) [316][10/63] lr: 1.6442e-03 eta: 9:03:34 time: 0.8070 data_time: 0.2438 memory: 14901 loss: 1.5792 loss_prob: 0.8911 loss_thr: 0.5432 loss_db: 0.1449 2022/11/02 15:31:18 - mmengine - INFO - Epoch(train) [316][15/63] lr: 1.6442e-03 eta: 9:03:34 time: 0.5887 data_time: 0.0113 memory: 14901 loss: 1.6451 loss_prob: 0.9429 loss_thr: 0.5475 loss_db: 0.1546 2022/11/02 15:31:22 - mmengine - INFO - Epoch(train) [316][20/63] lr: 1.6442e-03 eta: 9:03:30 time: 0.6560 data_time: 0.0378 memory: 14901 loss: 1.6980 loss_prob: 0.9667 loss_thr: 0.5741 loss_db: 0.1572 2022/11/02 15:31:24 - mmengine - INFO - Epoch(train) [316][25/63] lr: 1.6442e-03 eta: 9:03:30 time: 0.6303 data_time: 0.0565 memory: 14901 loss: 1.6487 loss_prob: 0.9251 loss_thr: 0.5751 loss_db: 0.1485 2022/11/02 15:31:27 - mmengine - INFO - Epoch(train) [316][30/63] lr: 1.6442e-03 eta: 9:03:24 time: 0.5657 data_time: 0.0390 memory: 14901 loss: 1.6192 loss_prob: 0.9088 loss_thr: 0.5578 loss_db: 0.1526 2022/11/02 15:31:30 - mmengine - INFO - Epoch(train) [316][35/63] lr: 1.6442e-03 eta: 9:03:24 time: 0.5449 data_time: 0.0191 memory: 14901 loss: 1.5125 loss_prob: 0.8280 loss_thr: 0.5437 loss_db: 0.1408 2022/11/02 15:31:32 - mmengine - INFO - Epoch(train) [316][40/63] lr: 1.6442e-03 eta: 9:03:16 time: 0.5104 data_time: 0.0100 memory: 14901 loss: 1.5058 loss_prob: 0.8366 loss_thr: 0.5343 loss_db: 0.1350 2022/11/02 15:31:35 - mmengine - INFO - Epoch(train) [316][45/63] lr: 1.6442e-03 eta: 9:03:16 time: 0.4997 data_time: 0.0345 memory: 14901 loss: 1.6824 loss_prob: 0.9619 loss_thr: 0.5661 loss_db: 0.1544 2022/11/02 15:31:38 - mmengine - INFO - Epoch(train) [316][50/63] lr: 1.6442e-03 eta: 9:03:09 time: 0.5508 data_time: 0.0481 memory: 14901 loss: 1.8006 loss_prob: 1.0463 loss_thr: 0.5835 loss_db: 0.1707 2022/11/02 15:31:41 - mmengine - INFO - Epoch(train) [316][55/63] lr: 1.6442e-03 eta: 9:03:09 time: 0.5624 data_time: 0.0271 memory: 14901 loss: 1.7254 loss_prob: 0.9946 loss_thr: 0.5662 loss_db: 0.1645 2022/11/02 15:31:43 - mmengine - INFO - Epoch(train) [316][60/63] lr: 1.6442e-03 eta: 9:03:01 time: 0.5160 data_time: 0.0114 memory: 14901 loss: 1.6856 loss_prob: 0.9570 loss_thr: 0.5709 loss_db: 0.1577 2022/11/02 15:31:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:31:49 - mmengine - INFO - Epoch(train) [317][5/63] lr: 1.6425e-03 eta: 9:03:01 time: 0.7125 data_time: 0.2364 memory: 14901 loss: 1.5767 loss_prob: 0.8808 loss_thr: 0.5447 loss_db: 0.1512 2022/11/02 15:31:52 - mmengine - INFO - Epoch(train) [317][10/63] lr: 1.6425e-03 eta: 9:02:54 time: 0.7695 data_time: 0.2406 memory: 14901 loss: 1.6873 loss_prob: 0.9522 loss_thr: 0.5736 loss_db: 0.1614 2022/11/02 15:31:54 - mmengine - INFO - Epoch(train) [317][15/63] lr: 1.6425e-03 eta: 9:02:54 time: 0.5173 data_time: 0.0143 memory: 14901 loss: 1.7556 loss_prob: 0.9923 loss_thr: 0.5948 loss_db: 0.1685 2022/11/02 15:31:57 - mmengine - INFO - Epoch(train) [317][20/63] lr: 1.6425e-03 eta: 9:02:46 time: 0.5217 data_time: 0.0148 memory: 14901 loss: 1.6866 loss_prob: 0.9374 loss_thr: 0.5903 loss_db: 0.1590 2022/11/02 15:32:00 - mmengine - INFO - Epoch(train) [317][25/63] lr: 1.6425e-03 eta: 9:02:46 time: 0.5550 data_time: 0.0360 memory: 14901 loss: 1.5240 loss_prob: 0.8448 loss_thr: 0.5391 loss_db: 0.1401 2022/11/02 15:32:03 - mmengine - INFO - Epoch(train) [317][30/63] lr: 1.6425e-03 eta: 9:02:40 time: 0.5459 data_time: 0.0434 memory: 14901 loss: 1.5314 loss_prob: 0.8513 loss_thr: 0.5384 loss_db: 0.1417 2022/11/02 15:32:05 - mmengine - INFO - Epoch(train) [317][35/63] lr: 1.6425e-03 eta: 9:02:40 time: 0.5306 data_time: 0.0273 memory: 14901 loss: 1.5325 loss_prob: 0.8449 loss_thr: 0.5469 loss_db: 0.1407 2022/11/02 15:32:09 - mmengine - INFO - Epoch(train) [317][40/63] lr: 1.6425e-03 eta: 9:02:35 time: 0.6146 data_time: 0.0196 memory: 14901 loss: 1.4902 loss_prob: 0.8250 loss_thr: 0.5307 loss_db: 0.1345 2022/11/02 15:32:11 - mmengine - INFO - Epoch(train) [317][45/63] lr: 1.6425e-03 eta: 9:02:35 time: 0.5965 data_time: 0.0120 memory: 14901 loss: 1.8543 loss_prob: 1.1082 loss_thr: 0.5784 loss_db: 0.1677 2022/11/02 15:32:14 - mmengine - INFO - Epoch(train) [317][50/63] lr: 1.6425e-03 eta: 9:02:28 time: 0.5589 data_time: 0.0184 memory: 14901 loss: 1.8680 loss_prob: 1.1034 loss_thr: 0.5935 loss_db: 0.1711 2022/11/02 15:32:17 - mmengine - INFO - Epoch(train) [317][55/63] lr: 1.6425e-03 eta: 9:02:28 time: 0.5509 data_time: 0.0267 memory: 14901 loss: 1.5833 loss_prob: 0.8808 loss_thr: 0.5530 loss_db: 0.1495 2022/11/02 15:32:20 - mmengine - INFO - Epoch(train) [317][60/63] lr: 1.6425e-03 eta: 9:02:21 time: 0.5510 data_time: 0.0164 memory: 14901 loss: 1.6249 loss_prob: 0.9286 loss_thr: 0.5389 loss_db: 0.1574 2022/11/02 15:32:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:32:27 - mmengine - INFO - Epoch(train) [318][5/63] lr: 1.6408e-03 eta: 9:02:21 time: 0.8037 data_time: 0.2315 memory: 14901 loss: 1.6484 loss_prob: 0.9288 loss_thr: 0.5585 loss_db: 0.1611 2022/11/02 15:32:29 - mmengine - INFO - Epoch(train) [318][10/63] lr: 1.6408e-03 eta: 9:02:15 time: 0.8219 data_time: 0.2269 memory: 14901 loss: 1.5862 loss_prob: 0.8866 loss_thr: 0.5502 loss_db: 0.1494 2022/11/02 15:32:33 - mmengine - INFO - Epoch(train) [318][15/63] lr: 1.6408e-03 eta: 9:02:15 time: 0.5953 data_time: 0.0078 memory: 14901 loss: 1.6044 loss_prob: 0.9042 loss_thr: 0.5515 loss_db: 0.1488 2022/11/02 15:32:35 - mmengine - INFO - Epoch(train) [318][20/63] lr: 1.6408e-03 eta: 9:02:09 time: 0.5799 data_time: 0.0078 memory: 14901 loss: 1.5749 loss_prob: 0.8857 loss_thr: 0.5440 loss_db: 0.1452 2022/11/02 15:32:38 - mmengine - INFO - Epoch(train) [318][25/63] lr: 1.6408e-03 eta: 9:02:09 time: 0.5349 data_time: 0.0178 memory: 14901 loss: 1.5992 loss_prob: 0.8887 loss_thr: 0.5618 loss_db: 0.1488 2022/11/02 15:32:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:32:41 - mmengine - INFO - Epoch(train) [318][30/63] lr: 1.6408e-03 eta: 9:02:03 time: 0.5674 data_time: 0.0386 memory: 14901 loss: 1.6929 loss_prob: 0.9387 loss_thr: 0.5948 loss_db: 0.1594 2022/11/02 15:32:43 - mmengine - INFO - Epoch(train) [318][35/63] lr: 1.6408e-03 eta: 9:02:03 time: 0.5467 data_time: 0.0288 memory: 14901 loss: 1.6809 loss_prob: 0.9557 loss_thr: 0.5661 loss_db: 0.1591 2022/11/02 15:32:46 - mmengine - INFO - Epoch(train) [318][40/63] lr: 1.6408e-03 eta: 9:01:56 time: 0.5409 data_time: 0.0099 memory: 14901 loss: 1.6631 loss_prob: 0.9524 loss_thr: 0.5541 loss_db: 0.1567 2022/11/02 15:32:49 - mmengine - INFO - Epoch(train) [318][45/63] lr: 1.6408e-03 eta: 9:01:56 time: 0.5176 data_time: 0.0108 memory: 14901 loss: 1.6834 loss_prob: 0.9404 loss_thr: 0.5876 loss_db: 0.1554 2022/11/02 15:32:51 - mmengine - INFO - Epoch(train) [318][50/63] lr: 1.6408e-03 eta: 9:01:48 time: 0.5072 data_time: 0.0230 memory: 14901 loss: 1.6782 loss_prob: 0.9393 loss_thr: 0.5802 loss_db: 0.1587 2022/11/02 15:32:54 - mmengine - INFO - Epoch(train) [318][55/63] lr: 1.6408e-03 eta: 9:01:48 time: 0.5799 data_time: 0.0561 memory: 14901 loss: 1.6529 loss_prob: 0.9350 loss_thr: 0.5599 loss_db: 0.1580 2022/11/02 15:32:57 - mmengine - INFO - Epoch(train) [318][60/63] lr: 1.6408e-03 eta: 9:01:42 time: 0.5729 data_time: 0.0446 memory: 14901 loss: 1.7890 loss_prob: 1.0323 loss_thr: 0.5917 loss_db: 0.1649 2022/11/02 15:32:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:33:04 - mmengine - INFO - Epoch(train) [319][5/63] lr: 1.6391e-03 eta: 9:01:42 time: 0.8361 data_time: 0.2116 memory: 14901 loss: 1.6437 loss_prob: 0.9118 loss_thr: 0.5791 loss_db: 0.1529 2022/11/02 15:33:07 - mmengine - INFO - Epoch(train) [319][10/63] lr: 1.6391e-03 eta: 9:01:38 time: 0.8852 data_time: 0.2136 memory: 14901 loss: 1.6765 loss_prob: 0.9486 loss_thr: 0.5680 loss_db: 0.1599 2022/11/02 15:33:10 - mmengine - INFO - Epoch(train) [319][15/63] lr: 1.6391e-03 eta: 9:01:38 time: 0.5474 data_time: 0.0159 memory: 14901 loss: 1.7282 loss_prob: 1.0095 loss_thr: 0.5609 loss_db: 0.1579 2022/11/02 15:33:13 - mmengine - INFO - Epoch(train) [319][20/63] lr: 1.6391e-03 eta: 9:01:30 time: 0.5355 data_time: 0.0167 memory: 14901 loss: 1.7418 loss_prob: 1.0167 loss_thr: 0.5644 loss_db: 0.1607 2022/11/02 15:33:16 - mmengine - INFO - Epoch(train) [319][25/63] lr: 1.6391e-03 eta: 9:01:30 time: 0.6041 data_time: 0.0174 memory: 14901 loss: 1.6159 loss_prob: 0.8993 loss_thr: 0.5638 loss_db: 0.1528 2022/11/02 15:33:19 - mmengine - INFO - Epoch(train) [319][30/63] lr: 1.6391e-03 eta: 9:01:25 time: 0.6125 data_time: 0.0311 memory: 14901 loss: 1.5152 loss_prob: 0.8299 loss_thr: 0.5463 loss_db: 0.1390 2022/11/02 15:33:22 - mmengine - INFO - Epoch(train) [319][35/63] lr: 1.6391e-03 eta: 9:01:25 time: 0.6060 data_time: 0.0365 memory: 14901 loss: 1.4741 loss_prob: 0.8154 loss_thr: 0.5239 loss_db: 0.1348 2022/11/02 15:33:25 - mmengine - INFO - Epoch(train) [319][40/63] lr: 1.6391e-03 eta: 9:01:19 time: 0.5812 data_time: 0.0325 memory: 14901 loss: 1.5414 loss_prob: 0.8700 loss_thr: 0.5286 loss_db: 0.1428 2022/11/02 15:33:27 - mmengine - INFO - Epoch(train) [319][45/63] lr: 1.6391e-03 eta: 9:01:19 time: 0.5501 data_time: 0.0214 memory: 14901 loss: 1.6530 loss_prob: 0.9369 loss_thr: 0.5620 loss_db: 0.1540 2022/11/02 15:33:30 - mmengine - INFO - Epoch(train) [319][50/63] lr: 1.6391e-03 eta: 9:01:12 time: 0.5439 data_time: 0.0088 memory: 14901 loss: 1.7086 loss_prob: 0.9603 loss_thr: 0.5875 loss_db: 0.1607 2022/11/02 15:33:33 - mmengine - INFO - Epoch(train) [319][55/63] lr: 1.6391e-03 eta: 9:01:12 time: 0.5586 data_time: 0.0115 memory: 14901 loss: 1.6736 loss_prob: 0.9393 loss_thr: 0.5743 loss_db: 0.1600 2022/11/02 15:33:36 - mmengine - INFO - Epoch(train) [319][60/63] lr: 1.6391e-03 eta: 9:01:08 time: 0.6238 data_time: 0.0085 memory: 14901 loss: 1.7594 loss_prob: 1.0175 loss_thr: 0.5718 loss_db: 0.1701 2022/11/02 15:33:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:33:45 - mmengine - INFO - Epoch(train) [320][5/63] lr: 1.6375e-03 eta: 9:01:08 time: 0.9958 data_time: 0.2601 memory: 14901 loss: 1.6124 loss_prob: 0.9169 loss_thr: 0.5465 loss_db: 0.1490 2022/11/02 15:33:47 - mmengine - INFO - Epoch(train) [320][10/63] lr: 1.6375e-03 eta: 9:01:04 time: 0.8906 data_time: 0.2584 memory: 14901 loss: 1.5410 loss_prob: 0.8639 loss_thr: 0.5330 loss_db: 0.1441 2022/11/02 15:33:50 - mmengine - INFO - Epoch(train) [320][15/63] lr: 1.6375e-03 eta: 9:01:04 time: 0.5805 data_time: 0.0128 memory: 14901 loss: 1.5882 loss_prob: 0.8917 loss_thr: 0.5491 loss_db: 0.1474 2022/11/02 15:33:53 - mmengine - INFO - Epoch(train) [320][20/63] lr: 1.6375e-03 eta: 9:00:58 time: 0.5946 data_time: 0.0119 memory: 14901 loss: 1.4941 loss_prob: 0.8265 loss_thr: 0.5312 loss_db: 0.1365 2022/11/02 15:33:56 - mmengine - INFO - Epoch(train) [320][25/63] lr: 1.6375e-03 eta: 9:00:58 time: 0.5958 data_time: 0.0273 memory: 14901 loss: 1.4800 loss_prob: 0.8232 loss_thr: 0.5179 loss_db: 0.1389 2022/11/02 15:33:59 - mmengine - INFO - Epoch(train) [320][30/63] lr: 1.6375e-03 eta: 9:00:52 time: 0.5724 data_time: 0.0271 memory: 14901 loss: 1.6248 loss_prob: 0.9148 loss_thr: 0.5604 loss_db: 0.1496 2022/11/02 15:34:02 - mmengine - INFO - Epoch(train) [320][35/63] lr: 1.6375e-03 eta: 9:00:52 time: 0.5191 data_time: 0.0168 memory: 14901 loss: 1.5901 loss_prob: 0.8881 loss_thr: 0.5563 loss_db: 0.1457 2022/11/02 15:34:04 - mmengine - INFO - Epoch(train) [320][40/63] lr: 1.6375e-03 eta: 9:00:45 time: 0.5440 data_time: 0.0182 memory: 14901 loss: 1.4896 loss_prob: 0.8230 loss_thr: 0.5270 loss_db: 0.1396 2022/11/02 15:34:07 - mmengine - INFO - Epoch(train) [320][45/63] lr: 1.6375e-03 eta: 9:00:45 time: 0.5670 data_time: 0.0076 memory: 14901 loss: 1.5465 loss_prob: 0.8653 loss_thr: 0.5355 loss_db: 0.1457 2022/11/02 15:34:10 - mmengine - INFO - Epoch(train) [320][50/63] lr: 1.6375e-03 eta: 9:00:38 time: 0.5515 data_time: 0.0262 memory: 14901 loss: 1.5893 loss_prob: 0.8886 loss_thr: 0.5517 loss_db: 0.1490 2022/11/02 15:34:13 - mmengine - INFO - Epoch(train) [320][55/63] lr: 1.6375e-03 eta: 9:00:38 time: 0.5293 data_time: 0.0279 memory: 14901 loss: 1.5406 loss_prob: 0.8527 loss_thr: 0.5451 loss_db: 0.1428 2022/11/02 15:34:15 - mmengine - INFO - Epoch(train) [320][60/63] lr: 1.6375e-03 eta: 9:00:31 time: 0.5393 data_time: 0.0108 memory: 14901 loss: 1.5136 loss_prob: 0.8324 loss_thr: 0.5419 loss_db: 0.1393 2022/11/02 15:34:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:34:17 - mmengine - INFO - Saving checkpoint at 320 epochs 2022/11/02 15:34:20 - mmengine - INFO - Epoch(val) [320][5/500] eta: 9:00:31 time: 0.0443 data_time: 0.0058 memory: 14901 2022/11/02 15:34:21 - mmengine - INFO - Epoch(val) [320][10/500] eta: 0:00:25 time: 0.0516 data_time: 0.0066 memory: 1008 2022/11/02 15:34:21 - mmengine - INFO - Epoch(val) [320][15/500] eta: 0:00:25 time: 0.0448 data_time: 0.0036 memory: 1008 2022/11/02 15:34:21 - mmengine - INFO - Epoch(val) [320][20/500] eta: 0:00:19 time: 0.0400 data_time: 0.0029 memory: 1008 2022/11/02 15:34:21 - mmengine - INFO - Epoch(val) [320][25/500] eta: 0:00:19 time: 0.0417 data_time: 0.0035 memory: 1008 2022/11/02 15:34:22 - mmengine - INFO - Epoch(val) [320][30/500] eta: 0:00:21 time: 0.0449 data_time: 0.0036 memory: 1008 2022/11/02 15:34:22 - mmengine - INFO - Epoch(val) [320][35/500] eta: 0:00:21 time: 0.0409 data_time: 0.0026 memory: 1008 2022/11/02 15:34:22 - mmengine - INFO - Epoch(val) [320][40/500] eta: 0:00:18 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 15:34:22 - mmengine - INFO - Epoch(val) [320][45/500] eta: 0:00:18 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/02 15:34:22 - mmengine - INFO - Epoch(val) [320][50/500] eta: 0:00:19 time: 0.0425 data_time: 0.0029 memory: 1008 2022/11/02 15:34:23 - mmengine - INFO - Epoch(val) [320][55/500] eta: 0:00:19 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 15:34:23 - mmengine - INFO - Epoch(val) [320][60/500] eta: 0:00:16 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 15:34:23 - mmengine - INFO - Epoch(val) [320][65/500] eta: 0:00:16 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 15:34:23 - mmengine - INFO - Epoch(val) [320][70/500] eta: 0:00:17 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 15:34:23 - mmengine - INFO - Epoch(val) [320][75/500] eta: 0:00:17 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 15:34:24 - mmengine - INFO - Epoch(val) [320][80/500] eta: 0:00:46 time: 0.1103 data_time: 0.0735 memory: 1008 2022/11/02 15:34:24 - mmengine - INFO - Epoch(val) [320][85/500] eta: 0:00:46 time: 0.1074 data_time: 0.0733 memory: 1008 2022/11/02 15:34:25 - mmengine - INFO - Epoch(val) [320][90/500] eta: 0:00:17 time: 0.0430 data_time: 0.0039 memory: 1008 2022/11/02 15:34:25 - mmengine - INFO - Epoch(val) [320][95/500] eta: 0:00:17 time: 0.0428 data_time: 0.0040 memory: 1008 2022/11/02 15:34:25 - mmengine - INFO - Epoch(val) [320][100/500] eta: 0:00:15 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 15:34:25 - mmengine - INFO - Epoch(val) [320][105/500] eta: 0:00:15 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 15:34:25 - mmengine - INFO - Epoch(val) [320][110/500] eta: 0:00:14 time: 0.0360 data_time: 0.0027 memory: 1008 2022/11/02 15:34:26 - mmengine - INFO - Epoch(val) [320][115/500] eta: 0:00:14 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 15:34:26 - mmengine - INFO - Epoch(val) [320][120/500] eta: 0:00:17 time: 0.0460 data_time: 0.0031 memory: 1008 2022/11/02 15:34:26 - mmengine - INFO - Epoch(val) [320][125/500] eta: 0:00:17 time: 0.0397 data_time: 0.0029 memory: 1008 2022/11/02 15:34:26 - mmengine - INFO - Epoch(val) [320][130/500] eta: 0:00:13 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 15:34:26 - mmengine - INFO - Epoch(val) [320][135/500] eta: 0:00:13 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 15:34:27 - mmengine - INFO - Epoch(val) [320][140/500] eta: 0:00:14 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 15:34:27 - mmengine - INFO - Epoch(val) [320][145/500] eta: 0:00:14 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 15:34:27 - mmengine - INFO - Epoch(val) [320][150/500] eta: 0:00:15 time: 0.0456 data_time: 0.0029 memory: 1008 2022/11/02 15:34:28 - mmengine - INFO - Epoch(val) [320][155/500] eta: 0:00:15 time: 0.0984 data_time: 0.0587 memory: 1008 2022/11/02 15:34:28 - mmengine - INFO - Epoch(val) [320][160/500] eta: 0:00:33 time: 0.0985 data_time: 0.0582 memory: 1008 2022/11/02 15:34:28 - mmengine - INFO - Epoch(val) [320][165/500] eta: 0:00:33 time: 0.0385 data_time: 0.0021 memory: 1008 2022/11/02 15:34:28 - mmengine - INFO - Epoch(val) [320][170/500] eta: 0:00:12 time: 0.0386 data_time: 0.0021 memory: 1008 2022/11/02 15:34:29 - mmengine - INFO - Epoch(val) [320][175/500] eta: 0:00:12 time: 0.0374 data_time: 0.0024 memory: 1008 2022/11/02 15:34:29 - mmengine - INFO - Epoch(val) [320][180/500] eta: 0:00:11 time: 0.0375 data_time: 0.0027 memory: 1008 2022/11/02 15:34:29 - mmengine - INFO - Epoch(val) [320][185/500] eta: 0:00:11 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 15:34:29 - mmengine - INFO - Epoch(val) [320][190/500] eta: 0:00:13 time: 0.0437 data_time: 0.0026 memory: 1008 2022/11/02 15:34:29 - mmengine - INFO - Epoch(val) [320][195/500] eta: 0:00:13 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/02 15:34:30 - mmengine - INFO - Epoch(val) [320][200/500] eta: 0:00:13 time: 0.0444 data_time: 0.0024 memory: 1008 2022/11/02 15:34:30 - mmengine - INFO - Epoch(val) [320][205/500] eta: 0:00:13 time: 0.0418 data_time: 0.0023 memory: 1008 2022/11/02 15:34:30 - mmengine - INFO - Epoch(val) [320][210/500] eta: 0:00:10 time: 0.0364 data_time: 0.0025 memory: 1008 2022/11/02 15:34:30 - mmengine - INFO - Epoch(val) [320][215/500] eta: 0:00:10 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 15:34:31 - mmengine - INFO - Epoch(val) [320][220/500] eta: 0:00:19 time: 0.0698 data_time: 0.0280 memory: 1008 2022/11/02 15:34:31 - mmengine - INFO - Epoch(val) [320][225/500] eta: 0:00:19 time: 0.0713 data_time: 0.0277 memory: 1008 2022/11/02 15:34:31 - mmengine - INFO - Epoch(val) [320][230/500] eta: 0:00:10 time: 0.0403 data_time: 0.0021 memory: 1008 2022/11/02 15:34:31 - mmengine - INFO - Epoch(val) [320][235/500] eta: 0:00:10 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 15:34:32 - mmengine - INFO - Epoch(val) [320][240/500] eta: 0:00:10 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 15:34:32 - mmengine - INFO - Epoch(val) [320][245/500] eta: 0:00:10 time: 0.0424 data_time: 0.0029 memory: 1008 2022/11/02 15:34:32 - mmengine - INFO - Epoch(val) [320][250/500] eta: 0:00:09 time: 0.0382 data_time: 0.0027 memory: 1008 2022/11/02 15:34:32 - mmengine - INFO - Epoch(val) [320][255/500] eta: 0:00:09 time: 0.0377 data_time: 0.0029 memory: 1008 2022/11/02 15:34:32 - mmengine - INFO - Epoch(val) [320][260/500] eta: 0:00:09 time: 0.0383 data_time: 0.0027 memory: 1008 2022/11/02 15:34:33 - mmengine - INFO - Epoch(val) [320][265/500] eta: 0:00:09 time: 0.0371 data_time: 0.0023 memory: 1008 2022/11/02 15:34:33 - mmengine - INFO - Epoch(val) [320][270/500] eta: 0:00:08 time: 0.0373 data_time: 0.0024 memory: 1008 2022/11/02 15:34:33 - mmengine - INFO - Epoch(val) [320][275/500] eta: 0:00:08 time: 0.0374 data_time: 0.0024 memory: 1008 2022/11/02 15:34:33 - mmengine - INFO - Epoch(val) [320][280/500] eta: 0:00:08 time: 0.0384 data_time: 0.0023 memory: 1008 2022/11/02 15:34:33 - mmengine - INFO - Epoch(val) [320][285/500] eta: 0:00:08 time: 0.0402 data_time: 0.0027 memory: 1008 2022/11/02 15:34:34 - mmengine - INFO - Epoch(val) [320][290/500] eta: 0:00:08 time: 0.0401 data_time: 0.0029 memory: 1008 2022/11/02 15:34:34 - mmengine - INFO - Epoch(val) [320][295/500] eta: 0:00:08 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 15:34:34 - mmengine - INFO - Epoch(val) [320][300/500] eta: 0:00:08 time: 0.0418 data_time: 0.0032 memory: 1008 2022/11/02 15:34:34 - mmengine - INFO - Epoch(val) [320][305/500] eta: 0:00:08 time: 0.0430 data_time: 0.0032 memory: 1008 2022/11/02 15:34:34 - mmengine - INFO - Epoch(val) [320][310/500] eta: 0:00:07 time: 0.0414 data_time: 0.0029 memory: 1008 2022/11/02 15:34:35 - mmengine - INFO - Epoch(val) [320][315/500] eta: 0:00:07 time: 0.0435 data_time: 0.0028 memory: 1008 2022/11/02 15:34:35 - mmengine - INFO - Epoch(val) [320][320/500] eta: 0:00:07 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 15:34:35 - mmengine - INFO - Epoch(val) [320][325/500] eta: 0:00:07 time: 0.0455 data_time: 0.0025 memory: 1008 2022/11/02 15:34:35 - mmengine - INFO - Epoch(val) [320][330/500] eta: 0:00:08 time: 0.0476 data_time: 0.0027 memory: 1008 2022/11/02 15:34:35 - mmengine - INFO - Epoch(val) [320][335/500] eta: 0:00:08 time: 0.0392 data_time: 0.0036 memory: 1008 2022/11/02 15:34:36 - mmengine - INFO - Epoch(val) [320][340/500] eta: 0:00:07 time: 0.0465 data_time: 0.0034 memory: 1008 2022/11/02 15:34:36 - mmengine - INFO - Epoch(val) [320][345/500] eta: 0:00:07 time: 0.0462 data_time: 0.0026 memory: 1008 2022/11/02 15:34:36 - mmengine - INFO - Epoch(val) [320][350/500] eta: 0:00:06 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 15:34:36 - mmengine - INFO - Epoch(val) [320][355/500] eta: 0:00:06 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 15:34:36 - mmengine - INFO - Epoch(val) [320][360/500] eta: 0:00:05 time: 0.0360 data_time: 0.0023 memory: 1008 2022/11/02 15:34:37 - mmengine - INFO - Epoch(val) [320][365/500] eta: 0:00:05 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 15:34:37 - mmengine - INFO - Epoch(val) [320][370/500] eta: 0:00:05 time: 0.0390 data_time: 0.0028 memory: 1008 2022/11/02 15:34:37 - mmengine - INFO - Epoch(val) [320][375/500] eta: 0:00:05 time: 0.0343 data_time: 0.0032 memory: 1008 2022/11/02 15:34:37 - mmengine - INFO - Epoch(val) [320][380/500] eta: 0:00:04 time: 0.0375 data_time: 0.0028 memory: 1008 2022/11/02 15:34:37 - mmengine - INFO - Epoch(val) [320][385/500] eta: 0:00:04 time: 0.0373 data_time: 0.0021 memory: 1008 2022/11/02 15:34:38 - mmengine - INFO - Epoch(val) [320][390/500] eta: 0:00:03 time: 0.0350 data_time: 0.0023 memory: 1008 2022/11/02 15:34:38 - mmengine - INFO - Epoch(val) [320][395/500] eta: 0:00:03 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 15:34:38 - mmengine - INFO - Epoch(val) [320][400/500] eta: 0:00:03 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 15:34:38 - mmengine - INFO - Epoch(val) [320][405/500] eta: 0:00:03 time: 0.0365 data_time: 0.0022 memory: 1008 2022/11/02 15:34:38 - mmengine - INFO - Epoch(val) [320][410/500] eta: 0:00:03 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/02 15:34:39 - mmengine - INFO - Epoch(val) [320][415/500] eta: 0:00:03 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/02 15:34:39 - mmengine - INFO - Epoch(val) [320][420/500] eta: 0:00:02 time: 0.0357 data_time: 0.0044 memory: 1008 2022/11/02 15:34:39 - mmengine - INFO - Epoch(val) [320][425/500] eta: 0:00:02 time: 0.0381 data_time: 0.0041 memory: 1008 2022/11/02 15:34:39 - mmengine - INFO - Epoch(val) [320][430/500] eta: 0:00:02 time: 0.0380 data_time: 0.0021 memory: 1008 2022/11/02 15:34:39 - mmengine - INFO - Epoch(val) [320][435/500] eta: 0:00:02 time: 0.0359 data_time: 0.0025 memory: 1008 2022/11/02 15:34:40 - mmengine - INFO - Epoch(val) [320][440/500] eta: 0:00:02 time: 0.0394 data_time: 0.0029 memory: 1008 2022/11/02 15:34:40 - mmengine - INFO - Epoch(val) [320][445/500] eta: 0:00:02 time: 0.0453 data_time: 0.0032 memory: 1008 2022/11/02 15:34:40 - mmengine - INFO - Epoch(val) [320][450/500] eta: 0:00:02 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/02 15:34:40 - mmengine - INFO - Epoch(val) [320][455/500] eta: 0:00:02 time: 0.0400 data_time: 0.0025 memory: 1008 2022/11/02 15:34:40 - mmengine - INFO - Epoch(val) [320][460/500] eta: 0:00:01 time: 0.0365 data_time: 0.0027 memory: 1008 2022/11/02 15:34:40 - mmengine - INFO - Epoch(val) [320][465/500] eta: 0:00:01 time: 0.0339 data_time: 0.0026 memory: 1008 2022/11/02 15:34:41 - mmengine - INFO - Epoch(val) [320][470/500] eta: 0:00:01 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 15:34:41 - mmengine - INFO - Epoch(val) [320][475/500] eta: 0:00:01 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 15:34:41 - mmengine - INFO - Epoch(val) [320][480/500] eta: 0:00:00 time: 0.0381 data_time: 0.0030 memory: 1008 2022/11/02 15:34:41 - mmengine - INFO - Epoch(val) [320][485/500] eta: 0:00:00 time: 0.0396 data_time: 0.0029 memory: 1008 2022/11/02 15:34:41 - mmengine - INFO - Epoch(val) [320][490/500] eta: 0:00:00 time: 0.0402 data_time: 0.0026 memory: 1008 2022/11/02 15:34:42 - mmengine - INFO - Epoch(val) [320][495/500] eta: 0:00:00 time: 0.0424 data_time: 0.0027 memory: 1008 2022/11/02 15:34:42 - mmengine - INFO - Epoch(val) [320][500/500] eta: 0:00:00 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 15:34:42 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7949, precision: 0.7629, hmean: 0.7786 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7949, precision: 0.8165, hmean: 0.8056 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7906, precision: 0.8517, hmean: 0.8200 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7756, precision: 0.8789, hmean: 0.8240 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7198, precision: 0.9083, hmean: 0.8031 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4295, precision: 0.9350, hmean: 0.5886 2022/11/02 15:34:42 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0048, precision: 0.9091, hmean: 0.0096 2022/11/02 15:34:42 - mmengine - INFO - Epoch(val) [320][500/500] icdar/precision: 0.8789 icdar/recall: 0.7756 icdar/hmean: 0.8240 2022/11/02 15:34:48 - mmengine - INFO - Epoch(train) [321][5/63] lr: 1.6358e-03 eta: 0:00:00 time: 0.8837 data_time: 0.2377 memory: 14901 loss: 1.5483 loss_prob: 0.8620 loss_thr: 0.5428 loss_db: 0.1436 2022/11/02 15:34:51 - mmengine - INFO - Epoch(train) [321][10/63] lr: 1.6358e-03 eta: 9:00:27 time: 0.8849 data_time: 0.2305 memory: 14901 loss: 1.5551 loss_prob: 0.8644 loss_thr: 0.5456 loss_db: 0.1452 2022/11/02 15:34:53 - mmengine - INFO - Epoch(train) [321][15/63] lr: 1.6358e-03 eta: 9:00:27 time: 0.5008 data_time: 0.0061 memory: 14901 loss: 1.6747 loss_prob: 0.9386 loss_thr: 0.5793 loss_db: 0.1568 2022/11/02 15:34:56 - mmengine - INFO - Epoch(train) [321][20/63] lr: 1.6358e-03 eta: 9:00:19 time: 0.5295 data_time: 0.0101 memory: 14901 loss: 1.6468 loss_prob: 0.9209 loss_thr: 0.5713 loss_db: 0.1546 2022/11/02 15:34:59 - mmengine - INFO - Epoch(train) [321][25/63] lr: 1.6358e-03 eta: 9:00:19 time: 0.5518 data_time: 0.0317 memory: 14901 loss: 1.5652 loss_prob: 0.8663 loss_thr: 0.5528 loss_db: 0.1461 2022/11/02 15:35:02 - mmengine - INFO - Epoch(train) [321][30/63] lr: 1.6358e-03 eta: 9:00:14 time: 0.6221 data_time: 0.0438 memory: 14901 loss: 1.6592 loss_prob: 0.9255 loss_thr: 0.5772 loss_db: 0.1564 2022/11/02 15:35:05 - mmengine - INFO - Epoch(train) [321][35/63] lr: 1.6358e-03 eta: 9:00:14 time: 0.6067 data_time: 0.0258 memory: 14901 loss: 1.6184 loss_prob: 0.9010 loss_thr: 0.5660 loss_db: 0.1514 2022/11/02 15:35:08 - mmengine - INFO - Epoch(train) [321][40/63] lr: 1.6358e-03 eta: 9:00:08 time: 0.5580 data_time: 0.0088 memory: 14901 loss: 1.5885 loss_prob: 0.8899 loss_thr: 0.5528 loss_db: 0.1458 2022/11/02 15:35:10 - mmengine - INFO - Epoch(train) [321][45/63] lr: 1.6358e-03 eta: 9:00:08 time: 0.5367 data_time: 0.0101 memory: 14901 loss: 1.6090 loss_prob: 0.9024 loss_thr: 0.5567 loss_db: 0.1498 2022/11/02 15:35:14 - mmengine - INFO - Epoch(train) [321][50/63] lr: 1.6358e-03 eta: 9:00:02 time: 0.5745 data_time: 0.0233 memory: 14901 loss: 1.5722 loss_prob: 0.8725 loss_thr: 0.5524 loss_db: 0.1473 2022/11/02 15:35:17 - mmengine - INFO - Epoch(train) [321][55/63] lr: 1.6358e-03 eta: 9:00:02 time: 0.6487 data_time: 0.0260 memory: 14901 loss: 1.5928 loss_prob: 0.8830 loss_thr: 0.5633 loss_db: 0.1466 2022/11/02 15:35:20 - mmengine - INFO - Epoch(train) [321][60/63] lr: 1.6358e-03 eta: 8:59:56 time: 0.5977 data_time: 0.0129 memory: 14901 loss: 1.5421 loss_prob: 0.8566 loss_thr: 0.5473 loss_db: 0.1383 2022/11/02 15:35:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:35:26 - mmengine - INFO - Epoch(train) [322][5/63] lr: 1.6341e-03 eta: 8:59:56 time: 0.7994 data_time: 0.2604 memory: 14901 loss: 1.6070 loss_prob: 0.9044 loss_thr: 0.5522 loss_db: 0.1504 2022/11/02 15:35:29 - mmengine - INFO - Epoch(train) [322][10/63] lr: 1.6341e-03 eta: 8:59:50 time: 0.8072 data_time: 0.2609 memory: 14901 loss: 1.8751 loss_prob: 1.1152 loss_thr: 0.5851 loss_db: 0.1747 2022/11/02 15:35:31 - mmengine - INFO - Epoch(train) [322][15/63] lr: 1.6341e-03 eta: 8:59:50 time: 0.4986 data_time: 0.0058 memory: 14901 loss: 1.8834 loss_prob: 1.1291 loss_thr: 0.5785 loss_db: 0.1757 2022/11/02 15:35:34 - mmengine - INFO - Epoch(train) [322][20/63] lr: 1.6341e-03 eta: 8:59:43 time: 0.5388 data_time: 0.0055 memory: 14901 loss: 1.5523 loss_prob: 0.8732 loss_thr: 0.5344 loss_db: 0.1447 2022/11/02 15:35:37 - mmengine - INFO - Epoch(train) [322][25/63] lr: 1.6341e-03 eta: 8:59:43 time: 0.5682 data_time: 0.0343 memory: 14901 loss: 1.5765 loss_prob: 0.8896 loss_thr: 0.5392 loss_db: 0.1478 2022/11/02 15:35:40 - mmengine - INFO - Epoch(train) [322][30/63] lr: 1.6341e-03 eta: 8:59:36 time: 0.5661 data_time: 0.0414 memory: 14901 loss: 1.6581 loss_prob: 0.9339 loss_thr: 0.5673 loss_db: 0.1570 2022/11/02 15:35:43 - mmengine - INFO - Epoch(train) [322][35/63] lr: 1.6341e-03 eta: 8:59:36 time: 0.5735 data_time: 0.0152 memory: 14901 loss: 1.6286 loss_prob: 0.9044 loss_thr: 0.5718 loss_db: 0.1524 2022/11/02 15:35:45 - mmengine - INFO - Epoch(train) [322][40/63] lr: 1.6341e-03 eta: 8:59:29 time: 0.5194 data_time: 0.0094 memory: 14901 loss: 1.5012 loss_prob: 0.8321 loss_thr: 0.5295 loss_db: 0.1396 2022/11/02 15:35:49 - mmengine - INFO - Epoch(train) [322][45/63] lr: 1.6341e-03 eta: 8:59:29 time: 0.5835 data_time: 0.0068 memory: 14901 loss: 1.4886 loss_prob: 0.8166 loss_thr: 0.5345 loss_db: 0.1375 2022/11/02 15:35:51 - mmengine - INFO - Epoch(train) [322][50/63] lr: 1.6341e-03 eta: 8:59:24 time: 0.6166 data_time: 0.0239 memory: 14901 loss: 1.5483 loss_prob: 0.8555 loss_thr: 0.5501 loss_db: 0.1426 2022/11/02 15:35:54 - mmengine - INFO - Epoch(train) [322][55/63] lr: 1.6341e-03 eta: 8:59:24 time: 0.5850 data_time: 0.0284 memory: 14901 loss: 1.5965 loss_prob: 0.8993 loss_thr: 0.5496 loss_db: 0.1476 2022/11/02 15:35:57 - mmengine - INFO - Epoch(train) [322][60/63] lr: 1.6341e-03 eta: 8:59:18 time: 0.5745 data_time: 0.0107 memory: 14901 loss: 1.6936 loss_prob: 0.9536 loss_thr: 0.5843 loss_db: 0.1557 2022/11/02 15:35:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:36:04 - mmengine - INFO - Epoch(train) [323][5/63] lr: 1.6324e-03 eta: 8:59:18 time: 0.7623 data_time: 0.1979 memory: 14901 loss: 1.5744 loss_prob: 0.8834 loss_thr: 0.5427 loss_db: 0.1483 2022/11/02 15:36:06 - mmengine - INFO - Epoch(train) [323][10/63] lr: 1.6324e-03 eta: 8:59:11 time: 0.7991 data_time: 0.2045 memory: 14901 loss: 1.4898 loss_prob: 0.8269 loss_thr: 0.5273 loss_db: 0.1356 2022/11/02 15:36:09 - mmengine - INFO - Epoch(train) [323][15/63] lr: 1.6324e-03 eta: 8:59:11 time: 0.5781 data_time: 0.0315 memory: 14901 loss: 1.6074 loss_prob: 0.8987 loss_thr: 0.5632 loss_db: 0.1456 2022/11/02 15:36:12 - mmengine - INFO - Epoch(train) [323][20/63] lr: 1.6324e-03 eta: 8:59:05 time: 0.5752 data_time: 0.0293 memory: 14901 loss: 1.6696 loss_prob: 0.9363 loss_thr: 0.5793 loss_db: 0.1540 2022/11/02 15:36:15 - mmengine - INFO - Epoch(train) [323][25/63] lr: 1.6324e-03 eta: 8:59:05 time: 0.5350 data_time: 0.0130 memory: 14901 loss: 1.6145 loss_prob: 0.8976 loss_thr: 0.5668 loss_db: 0.1501 2022/11/02 15:36:18 - mmengine - INFO - Epoch(train) [323][30/63] lr: 1.6324e-03 eta: 8:58:59 time: 0.5880 data_time: 0.0204 memory: 14901 loss: 1.5894 loss_prob: 0.8854 loss_thr: 0.5564 loss_db: 0.1476 2022/11/02 15:36:21 - mmengine - INFO - Epoch(train) [323][35/63] lr: 1.6324e-03 eta: 8:58:59 time: 0.6179 data_time: 0.0351 memory: 14901 loss: 1.4955 loss_prob: 0.8260 loss_thr: 0.5319 loss_db: 0.1375 2022/11/02 15:36:24 - mmengine - INFO - Epoch(train) [323][40/63] lr: 1.6324e-03 eta: 8:58:54 time: 0.6030 data_time: 0.0278 memory: 14901 loss: 1.4997 loss_prob: 0.8281 loss_thr: 0.5332 loss_db: 0.1384 2022/11/02 15:36:27 - mmengine - INFO - Epoch(train) [323][45/63] lr: 1.6324e-03 eta: 8:58:54 time: 0.5762 data_time: 0.0102 memory: 14901 loss: 1.6131 loss_prob: 0.8990 loss_thr: 0.5640 loss_db: 0.1501 2022/11/02 15:36:29 - mmengine - INFO - Epoch(train) [323][50/63] lr: 1.6324e-03 eta: 8:58:46 time: 0.5204 data_time: 0.0097 memory: 14901 loss: 1.4720 loss_prob: 0.8115 loss_thr: 0.5261 loss_db: 0.1343 2022/11/02 15:36:32 - mmengine - INFO - Epoch(train) [323][55/63] lr: 1.6324e-03 eta: 8:58:46 time: 0.5353 data_time: 0.0242 memory: 14901 loss: 1.4386 loss_prob: 0.7821 loss_thr: 0.5274 loss_db: 0.1291 2022/11/02 15:36:35 - mmengine - INFO - Epoch(train) [323][60/63] lr: 1.6324e-03 eta: 8:58:41 time: 0.6077 data_time: 0.0270 memory: 14901 loss: 1.5522 loss_prob: 0.8582 loss_thr: 0.5523 loss_db: 0.1418 2022/11/02 15:36:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:36:43 - mmengine - INFO - Epoch(train) [324][5/63] lr: 1.6308e-03 eta: 8:58:41 time: 0.8691 data_time: 0.2506 memory: 14901 loss: 1.5308 loss_prob: 0.8478 loss_thr: 0.5396 loss_db: 0.1434 2022/11/02 15:36:45 - mmengine - INFO - Epoch(train) [324][10/63] lr: 1.6308e-03 eta: 8:58:35 time: 0.8309 data_time: 0.2426 memory: 14901 loss: 1.4532 loss_prob: 0.8025 loss_thr: 0.5189 loss_db: 0.1318 2022/11/02 15:36:48 - mmengine - INFO - Epoch(train) [324][15/63] lr: 1.6308e-03 eta: 8:58:35 time: 0.5232 data_time: 0.0073 memory: 14901 loss: 1.5831 loss_prob: 0.8892 loss_thr: 0.5481 loss_db: 0.1457 2022/11/02 15:36:51 - mmengine - INFO - Epoch(train) [324][20/63] lr: 1.6308e-03 eta: 8:58:29 time: 0.5636 data_time: 0.0102 memory: 14901 loss: 1.6763 loss_prob: 0.9529 loss_thr: 0.5622 loss_db: 0.1612 2022/11/02 15:36:54 - mmengine - INFO - Epoch(train) [324][25/63] lr: 1.6308e-03 eta: 8:58:29 time: 0.5815 data_time: 0.0264 memory: 14901 loss: 1.6311 loss_prob: 0.9275 loss_thr: 0.5479 loss_db: 0.1557 2022/11/02 15:36:57 - mmengine - INFO - Epoch(train) [324][30/63] lr: 1.6308e-03 eta: 8:58:24 time: 0.6013 data_time: 0.0420 memory: 14901 loss: 1.5696 loss_prob: 0.8789 loss_thr: 0.5443 loss_db: 0.1463 2022/11/02 15:37:00 - mmengine - INFO - Epoch(train) [324][35/63] lr: 1.6308e-03 eta: 8:58:24 time: 0.5637 data_time: 0.0304 memory: 14901 loss: 1.6174 loss_prob: 0.9119 loss_thr: 0.5516 loss_db: 0.1539 2022/11/02 15:37:02 - mmengine - INFO - Epoch(train) [324][40/63] lr: 1.6308e-03 eta: 8:58:16 time: 0.5264 data_time: 0.0162 memory: 14901 loss: 1.6584 loss_prob: 0.9403 loss_thr: 0.5601 loss_db: 0.1580 2022/11/02 15:37:05 - mmengine - INFO - Epoch(train) [324][45/63] lr: 1.6308e-03 eta: 8:58:16 time: 0.5534 data_time: 0.0133 memory: 14901 loss: 1.6322 loss_prob: 0.9149 loss_thr: 0.5624 loss_db: 0.1549 2022/11/02 15:37:08 - mmengine - INFO - Epoch(train) [324][50/63] lr: 1.6308e-03 eta: 8:58:10 time: 0.5614 data_time: 0.0210 memory: 14901 loss: 1.7033 loss_prob: 0.9668 loss_thr: 0.5745 loss_db: 0.1620 2022/11/02 15:37:11 - mmengine - INFO - Epoch(train) [324][55/63] lr: 1.6308e-03 eta: 8:58:10 time: 0.5454 data_time: 0.0268 memory: 14901 loss: 1.8245 loss_prob: 1.0592 loss_thr: 0.5944 loss_db: 0.1709 2022/11/02 15:37:13 - mmengine - INFO - Epoch(train) [324][60/63] lr: 1.6308e-03 eta: 8:58:03 time: 0.5473 data_time: 0.0149 memory: 14901 loss: 1.6591 loss_prob: 0.9449 loss_thr: 0.5630 loss_db: 0.1513 2022/11/02 15:37:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:37:21 - mmengine - INFO - Epoch(train) [325][5/63] lr: 1.6291e-03 eta: 8:58:03 time: 0.9167 data_time: 0.2496 memory: 14901 loss: 1.6369 loss_prob: 0.9212 loss_thr: 0.5620 loss_db: 0.1536 2022/11/02 15:37:25 - mmengine - INFO - Epoch(train) [325][10/63] lr: 1.6291e-03 eta: 8:58:02 time: 1.0067 data_time: 0.2478 memory: 14901 loss: 1.6632 loss_prob: 0.9519 loss_thr: 0.5519 loss_db: 0.1595 2022/11/02 15:37:27 - mmengine - INFO - Epoch(train) [325][15/63] lr: 1.6291e-03 eta: 8:58:02 time: 0.5793 data_time: 0.0077 memory: 14901 loss: 1.6858 loss_prob: 0.9682 loss_thr: 0.5555 loss_db: 0.1620 2022/11/02 15:37:30 - mmengine - INFO - Epoch(train) [325][20/63] lr: 1.6291e-03 eta: 8:57:54 time: 0.5247 data_time: 0.0098 memory: 14901 loss: 1.7259 loss_prob: 0.9834 loss_thr: 0.5778 loss_db: 0.1647 2022/11/02 15:37:33 - mmengine - INFO - Epoch(train) [325][25/63] lr: 1.6291e-03 eta: 8:57:54 time: 0.5396 data_time: 0.0227 memory: 14901 loss: 1.7328 loss_prob: 0.9873 loss_thr: 0.5804 loss_db: 0.1651 2022/11/02 15:37:35 - mmengine - INFO - Epoch(train) [325][30/63] lr: 1.6291e-03 eta: 8:57:48 time: 0.5653 data_time: 0.0410 memory: 14901 loss: 1.7117 loss_prob: 0.9712 loss_thr: 0.5772 loss_db: 0.1633 2022/11/02 15:37:38 - mmengine - INFO - Epoch(train) [325][35/63] lr: 1.6291e-03 eta: 8:57:48 time: 0.5423 data_time: 0.0283 memory: 14901 loss: 1.6895 loss_prob: 0.9654 loss_thr: 0.5623 loss_db: 0.1618 2022/11/02 15:37:41 - mmengine - INFO - Epoch(train) [325][40/63] lr: 1.6291e-03 eta: 8:57:40 time: 0.5188 data_time: 0.0083 memory: 14901 loss: 1.6593 loss_prob: 0.9582 loss_thr: 0.5400 loss_db: 0.1611 2022/11/02 15:37:44 - mmengine - INFO - Epoch(train) [325][45/63] lr: 1.6291e-03 eta: 8:57:40 time: 0.5558 data_time: 0.0057 memory: 14901 loss: 1.7247 loss_prob: 1.0211 loss_thr: 0.5410 loss_db: 0.1626 2022/11/02 15:37:47 - mmengine - INFO - Epoch(train) [325][50/63] lr: 1.6291e-03 eta: 8:57:37 time: 0.6644 data_time: 0.0439 memory: 14901 loss: 1.8178 loss_prob: 1.0813 loss_thr: 0.5651 loss_db: 0.1714 2022/11/02 15:37:50 - mmengine - INFO - Epoch(train) [325][55/63] lr: 1.6291e-03 eta: 8:57:37 time: 0.6633 data_time: 0.0477 memory: 14901 loss: 1.8974 loss_prob: 1.1172 loss_thr: 0.5917 loss_db: 0.1885 2022/11/02 15:37:53 - mmengine - INFO - Epoch(train) [325][60/63] lr: 1.6291e-03 eta: 8:57:30 time: 0.5537 data_time: 0.0089 memory: 14901 loss: 1.9485 loss_prob: 1.1562 loss_thr: 0.5941 loss_db: 0.1981 2022/11/02 15:37:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:38:01 - mmengine - INFO - Epoch(train) [326][5/63] lr: 1.6274e-03 eta: 8:57:30 time: 0.8854 data_time: 0.2153 memory: 14901 loss: 1.7804 loss_prob: 1.0308 loss_thr: 0.5756 loss_db: 0.1740 2022/11/02 15:38:03 - mmengine - INFO - Epoch(train) [326][10/63] lr: 1.6274e-03 eta: 8:57:25 time: 0.8685 data_time: 0.2191 memory: 14901 loss: 1.5670 loss_prob: 0.8620 loss_thr: 0.5623 loss_db: 0.1427 2022/11/02 15:38:06 - mmengine - INFO - Epoch(train) [326][15/63] lr: 1.6274e-03 eta: 8:57:25 time: 0.5047 data_time: 0.0109 memory: 14901 loss: 1.7358 loss_prob: 0.9916 loss_thr: 0.5828 loss_db: 0.1615 2022/11/02 15:38:09 - mmengine - INFO - Epoch(train) [326][20/63] lr: 1.6274e-03 eta: 8:57:19 time: 0.5748 data_time: 0.0103 memory: 14901 loss: 1.7714 loss_prob: 1.0354 loss_thr: 0.5671 loss_db: 0.1689 2022/11/02 15:38:11 - mmengine - INFO - Epoch(train) [326][25/63] lr: 1.6274e-03 eta: 8:57:19 time: 0.5830 data_time: 0.0174 memory: 14901 loss: 1.6810 loss_prob: 0.9701 loss_thr: 0.5520 loss_db: 0.1590 2022/11/02 15:38:14 - mmengine - INFO - Epoch(train) [326][30/63] lr: 1.6274e-03 eta: 8:57:13 time: 0.5613 data_time: 0.0373 memory: 14901 loss: 1.5969 loss_prob: 0.8935 loss_thr: 0.5550 loss_db: 0.1483 2022/11/02 15:38:18 - mmengine - INFO - Epoch(train) [326][35/63] lr: 1.6274e-03 eta: 8:57:13 time: 0.6206 data_time: 0.0370 memory: 14901 loss: 1.6493 loss_prob: 0.9224 loss_thr: 0.5715 loss_db: 0.1555 2022/11/02 15:38:20 - mmengine - INFO - Epoch(train) [326][40/63] lr: 1.6274e-03 eta: 8:57:07 time: 0.6112 data_time: 0.0152 memory: 14901 loss: 1.9621 loss_prob: 1.1527 loss_thr: 0.6209 loss_db: 0.1886 2022/11/02 15:38:23 - mmengine - INFO - Epoch(train) [326][45/63] lr: 1.6274e-03 eta: 8:57:07 time: 0.5267 data_time: 0.0063 memory: 14901 loss: 1.8895 loss_prob: 1.0965 loss_thr: 0.6129 loss_db: 0.1801 2022/11/02 15:38:25 - mmengine - INFO - Epoch(train) [326][50/63] lr: 1.6274e-03 eta: 8:56:59 time: 0.4785 data_time: 0.0086 memory: 14901 loss: 1.6221 loss_prob: 0.9082 loss_thr: 0.5620 loss_db: 0.1518 2022/11/02 15:38:28 - mmengine - INFO - Epoch(train) [326][55/63] lr: 1.6274e-03 eta: 8:56:59 time: 0.5268 data_time: 0.0250 memory: 14901 loss: 1.7615 loss_prob: 1.0245 loss_thr: 0.5730 loss_db: 0.1640 2022/11/02 15:38:31 - mmengine - INFO - Epoch(train) [326][60/63] lr: 1.6274e-03 eta: 8:56:52 time: 0.5584 data_time: 0.0226 memory: 14901 loss: 1.6875 loss_prob: 0.9685 loss_thr: 0.5658 loss_db: 0.1532 2022/11/02 15:38:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:38:39 - mmengine - INFO - Epoch(train) [327][5/63] lr: 1.6257e-03 eta: 8:56:52 time: 0.9115 data_time: 0.2770 memory: 14901 loss: 1.6561 loss_prob: 0.9270 loss_thr: 0.5743 loss_db: 0.1548 2022/11/02 15:38:41 - mmengine - INFO - Epoch(train) [327][10/63] lr: 1.6257e-03 eta: 8:56:49 time: 0.9185 data_time: 0.2716 memory: 14901 loss: 1.7909 loss_prob: 1.0250 loss_thr: 0.5949 loss_db: 0.1710 2022/11/02 15:38:45 - mmengine - INFO - Epoch(train) [327][15/63] lr: 1.6257e-03 eta: 8:56:49 time: 0.6001 data_time: 0.0093 memory: 14901 loss: 1.7396 loss_prob: 0.9843 loss_thr: 0.5928 loss_db: 0.1624 2022/11/02 15:38:47 - mmengine - INFO - Epoch(train) [327][20/63] lr: 1.6257e-03 eta: 8:56:43 time: 0.6068 data_time: 0.0097 memory: 14901 loss: 1.6289 loss_prob: 0.9077 loss_thr: 0.5699 loss_db: 0.1513 2022/11/02 15:38:50 - mmengine - INFO - Epoch(train) [327][25/63] lr: 1.6257e-03 eta: 8:56:43 time: 0.5324 data_time: 0.0208 memory: 14901 loss: 1.7793 loss_prob: 1.0492 loss_thr: 0.5516 loss_db: 0.1785 2022/11/02 15:38:54 - mmengine - INFO - Epoch(train) [327][30/63] lr: 1.6257e-03 eta: 8:56:40 time: 0.6859 data_time: 0.0417 memory: 14901 loss: 1.9035 loss_prob: 1.1276 loss_thr: 0.5900 loss_db: 0.1860 2022/11/02 15:38:57 - mmengine - INFO - Epoch(train) [327][35/63] lr: 1.6257e-03 eta: 8:56:40 time: 0.6683 data_time: 0.0272 memory: 14901 loss: 2.0477 loss_prob: 1.2292 loss_thr: 0.6260 loss_db: 0.1924 2022/11/02 15:39:00 - mmengine - INFO - Epoch(train) [327][40/63] lr: 1.6257e-03 eta: 8:56:33 time: 0.5330 data_time: 0.0092 memory: 14901 loss: 2.2256 loss_prob: 1.3566 loss_thr: 0.6575 loss_db: 0.2115 2022/11/02 15:39:02 - mmengine - INFO - Epoch(train) [327][45/63] lr: 1.6257e-03 eta: 8:56:33 time: 0.5427 data_time: 0.0111 memory: 14901 loss: 2.1047 loss_prob: 1.2471 loss_thr: 0.6567 loss_db: 0.2010 2022/11/02 15:39:05 - mmengine - INFO - Epoch(train) [327][50/63] lr: 1.6257e-03 eta: 8:56:26 time: 0.5469 data_time: 0.0268 memory: 14901 loss: 1.9366 loss_prob: 1.1462 loss_thr: 0.6029 loss_db: 0.1875 2022/11/02 15:39:08 - mmengine - INFO - Epoch(train) [327][55/63] lr: 1.6257e-03 eta: 8:56:26 time: 0.5650 data_time: 0.0251 memory: 14901 loss: 1.8355 loss_prob: 1.0680 loss_thr: 0.5908 loss_db: 0.1766 2022/11/02 15:39:11 - mmengine - INFO - Epoch(train) [327][60/63] lr: 1.6257e-03 eta: 8:56:20 time: 0.5762 data_time: 0.0081 memory: 14901 loss: 1.8952 loss_prob: 1.1108 loss_thr: 0.6050 loss_db: 0.1795 2022/11/02 15:39:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:39:18 - mmengine - INFO - Epoch(train) [328][5/63] lr: 1.6241e-03 eta: 8:56:20 time: 0.7914 data_time: 0.2117 memory: 14901 loss: 2.0023 loss_prob: 1.1943 loss_thr: 0.6208 loss_db: 0.1873 2022/11/02 15:39:20 - mmengine - INFO - Epoch(train) [328][10/63] lr: 1.6241e-03 eta: 8:56:14 time: 0.8254 data_time: 0.2206 memory: 14901 loss: 1.8929 loss_prob: 1.1095 loss_thr: 0.6003 loss_db: 0.1831 2022/11/02 15:39:23 - mmengine - INFO - Epoch(train) [328][15/63] lr: 1.6241e-03 eta: 8:56:14 time: 0.5604 data_time: 0.0263 memory: 14901 loss: 1.7712 loss_prob: 1.0231 loss_thr: 0.5772 loss_db: 0.1709 2022/11/02 15:39:26 - mmengine - INFO - Epoch(train) [328][20/63] lr: 1.6241e-03 eta: 8:56:08 time: 0.5705 data_time: 0.0149 memory: 14901 loss: 1.6104 loss_prob: 0.9073 loss_thr: 0.5536 loss_db: 0.1494 2022/11/02 15:39:29 - mmengine - INFO - Epoch(train) [328][25/63] lr: 1.6241e-03 eta: 8:56:08 time: 0.5668 data_time: 0.0236 memory: 14901 loss: 1.5638 loss_prob: 0.8763 loss_thr: 0.5448 loss_db: 0.1427 2022/11/02 15:39:32 - mmengine - INFO - Epoch(train) [328][30/63] lr: 1.6241e-03 eta: 8:56:01 time: 0.5451 data_time: 0.0217 memory: 14901 loss: 1.5915 loss_prob: 0.8919 loss_thr: 0.5515 loss_db: 0.1481 2022/11/02 15:39:34 - mmengine - INFO - Epoch(train) [328][35/63] lr: 1.6241e-03 eta: 8:56:01 time: 0.5157 data_time: 0.0200 memory: 14901 loss: 1.6772 loss_prob: 0.9480 loss_thr: 0.5694 loss_db: 0.1598 2022/11/02 15:39:37 - mmengine - INFO - Epoch(train) [328][40/63] lr: 1.6241e-03 eta: 8:55:54 time: 0.5301 data_time: 0.0238 memory: 14901 loss: 1.6705 loss_prob: 0.9489 loss_thr: 0.5653 loss_db: 0.1563 2022/11/02 15:39:40 - mmengine - INFO - Epoch(train) [328][45/63] lr: 1.6241e-03 eta: 8:55:54 time: 0.5282 data_time: 0.0114 memory: 14901 loss: 1.6721 loss_prob: 0.9477 loss_thr: 0.5671 loss_db: 0.1573 2022/11/02 15:39:42 - mmengine - INFO - Epoch(train) [328][50/63] lr: 1.6241e-03 eta: 8:55:46 time: 0.5263 data_time: 0.0180 memory: 14901 loss: 1.7354 loss_prob: 0.9735 loss_thr: 0.5987 loss_db: 0.1632 2022/11/02 15:39:45 - mmengine - INFO - Epoch(train) [328][55/63] lr: 1.6241e-03 eta: 8:55:46 time: 0.5333 data_time: 0.0315 memory: 14901 loss: 1.6869 loss_prob: 0.9320 loss_thr: 0.5948 loss_db: 0.1601 2022/11/02 15:39:48 - mmengine - INFO - Epoch(train) [328][60/63] lr: 1.6241e-03 eta: 8:55:39 time: 0.5351 data_time: 0.0194 memory: 14901 loss: 1.6367 loss_prob: 0.9164 loss_thr: 0.5650 loss_db: 0.1553 2022/11/02 15:39:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:39:55 - mmengine - INFO - Epoch(train) [329][5/63] lr: 1.6224e-03 eta: 8:55:39 time: 0.7967 data_time: 0.2602 memory: 14901 loss: 1.5928 loss_prob: 0.8826 loss_thr: 0.5646 loss_db: 0.1456 2022/11/02 15:39:58 - mmengine - INFO - Epoch(train) [329][10/63] lr: 1.6224e-03 eta: 8:55:35 time: 0.8764 data_time: 0.2547 memory: 14901 loss: 1.5115 loss_prob: 0.8320 loss_thr: 0.5367 loss_db: 0.1428 2022/11/02 15:40:00 - mmengine - INFO - Epoch(train) [329][15/63] lr: 1.6224e-03 eta: 8:55:35 time: 0.5695 data_time: 0.0082 memory: 14901 loss: 1.5947 loss_prob: 0.9028 loss_thr: 0.5403 loss_db: 0.1516 2022/11/02 15:40:03 - mmengine - INFO - Epoch(train) [329][20/63] lr: 1.6224e-03 eta: 8:55:27 time: 0.5183 data_time: 0.0111 memory: 14901 loss: 1.6145 loss_prob: 0.9093 loss_thr: 0.5548 loss_db: 0.1505 2022/11/02 15:40:06 - mmengine - INFO - Epoch(train) [329][25/63] lr: 1.6224e-03 eta: 8:55:27 time: 0.5297 data_time: 0.0397 memory: 14901 loss: 1.6241 loss_prob: 0.9045 loss_thr: 0.5646 loss_db: 0.1551 2022/11/02 15:40:08 - mmengine - INFO - Epoch(train) [329][30/63] lr: 1.6224e-03 eta: 8:55:20 time: 0.5452 data_time: 0.0429 memory: 14901 loss: 1.6180 loss_prob: 0.8954 loss_thr: 0.5714 loss_db: 0.1512 2022/11/02 15:40:11 - mmengine - INFO - Epoch(train) [329][35/63] lr: 1.6224e-03 eta: 8:55:20 time: 0.5464 data_time: 0.0146 memory: 14901 loss: 1.5744 loss_prob: 0.8653 loss_thr: 0.5660 loss_db: 0.1432 2022/11/02 15:40:14 - mmengine - INFO - Epoch(train) [329][40/63] lr: 1.6224e-03 eta: 8:55:13 time: 0.5359 data_time: 0.0091 memory: 14901 loss: 1.6387 loss_prob: 0.8981 loss_thr: 0.5880 loss_db: 0.1526 2022/11/02 15:40:17 - mmengine - INFO - Epoch(train) [329][45/63] lr: 1.6224e-03 eta: 8:55:13 time: 0.5881 data_time: 0.0095 memory: 14901 loss: 1.7025 loss_prob: 0.9497 loss_thr: 0.5911 loss_db: 0.1617 2022/11/02 15:40:20 - mmengine - INFO - Epoch(train) [329][50/63] lr: 1.6224e-03 eta: 8:55:07 time: 0.5935 data_time: 0.0216 memory: 14901 loss: 1.7039 loss_prob: 0.9643 loss_thr: 0.5811 loss_db: 0.1585 2022/11/02 15:40:22 - mmengine - INFO - Epoch(train) [329][55/63] lr: 1.6224e-03 eta: 8:55:07 time: 0.5251 data_time: 0.0328 memory: 14901 loss: 1.6349 loss_prob: 0.9086 loss_thr: 0.5751 loss_db: 0.1511 2022/11/02 15:40:25 - mmengine - INFO - Epoch(train) [329][60/63] lr: 1.6224e-03 eta: 8:55:00 time: 0.5227 data_time: 0.0214 memory: 14901 loss: 1.8330 loss_prob: 1.0539 loss_thr: 0.6049 loss_db: 0.1743 2022/11/02 15:40:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:40:31 - mmengine - INFO - Epoch(train) [330][5/63] lr: 1.6207e-03 eta: 8:55:00 time: 0.7306 data_time: 0.2520 memory: 14901 loss: 1.6483 loss_prob: 0.9236 loss_thr: 0.5693 loss_db: 0.1554 2022/11/02 15:40:33 - mmengine - INFO - Epoch(train) [330][10/63] lr: 1.6207e-03 eta: 8:54:51 time: 0.7293 data_time: 0.2483 memory: 14901 loss: 1.6128 loss_prob: 0.9114 loss_thr: 0.5514 loss_db: 0.1500 2022/11/02 15:40:36 - mmengine - INFO - Epoch(train) [330][15/63] lr: 1.6207e-03 eta: 8:54:51 time: 0.4896 data_time: 0.0101 memory: 14901 loss: 1.7870 loss_prob: 1.0458 loss_thr: 0.5731 loss_db: 0.1682 2022/11/02 15:40:38 - mmengine - INFO - Epoch(train) [330][20/63] lr: 1.6207e-03 eta: 8:54:43 time: 0.4995 data_time: 0.0079 memory: 14901 loss: 1.7155 loss_prob: 0.9865 loss_thr: 0.5678 loss_db: 0.1612 2022/11/02 15:40:41 - mmengine - INFO - Epoch(train) [330][25/63] lr: 1.6207e-03 eta: 8:54:43 time: 0.5287 data_time: 0.0389 memory: 14901 loss: 1.5720 loss_prob: 0.8747 loss_thr: 0.5500 loss_db: 0.1474 2022/11/02 15:40:44 - mmengine - INFO - Epoch(train) [330][30/63] lr: 1.6207e-03 eta: 8:54:36 time: 0.5306 data_time: 0.0435 memory: 14901 loss: 1.6052 loss_prob: 0.8933 loss_thr: 0.5635 loss_db: 0.1483 2022/11/02 15:40:46 - mmengine - INFO - Epoch(train) [330][35/63] lr: 1.6207e-03 eta: 8:54:36 time: 0.4886 data_time: 0.0114 memory: 14901 loss: 1.5499 loss_prob: 0.8632 loss_thr: 0.5442 loss_db: 0.1425 2022/11/02 15:40:49 - mmengine - INFO - Epoch(train) [330][40/63] lr: 1.6207e-03 eta: 8:54:28 time: 0.4878 data_time: 0.0108 memory: 14901 loss: 1.5208 loss_prob: 0.8536 loss_thr: 0.5266 loss_db: 0.1406 2022/11/02 15:40:51 - mmengine - INFO - Epoch(train) [330][45/63] lr: 1.6207e-03 eta: 8:54:28 time: 0.5207 data_time: 0.0106 memory: 14901 loss: 1.5510 loss_prob: 0.8683 loss_thr: 0.5395 loss_db: 0.1433 2022/11/02 15:40:54 - mmengine - INFO - Epoch(train) [330][50/63] lr: 1.6207e-03 eta: 8:54:21 time: 0.5597 data_time: 0.0281 memory: 14901 loss: 1.6124 loss_prob: 0.9003 loss_thr: 0.5611 loss_db: 0.1510 2022/11/02 15:40:57 - mmengine - INFO - Epoch(train) [330][55/63] lr: 1.6207e-03 eta: 8:54:21 time: 0.5499 data_time: 0.0338 memory: 14901 loss: 1.5971 loss_prob: 0.8894 loss_thr: 0.5607 loss_db: 0.1470 2022/11/02 15:41:00 - mmengine - INFO - Epoch(train) [330][60/63] lr: 1.6207e-03 eta: 8:54:15 time: 0.5872 data_time: 0.0131 memory: 14901 loss: 1.4570 loss_prob: 0.8014 loss_thr: 0.5237 loss_db: 0.1320 2022/11/02 15:41:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:41:07 - mmengine - INFO - Epoch(train) [331][5/63] lr: 1.6190e-03 eta: 8:54:15 time: 0.8113 data_time: 0.2636 memory: 14901 loss: 1.6036 loss_prob: 0.8914 loss_thr: 0.5616 loss_db: 0.1506 2022/11/02 15:41:10 - mmengine - INFO - Epoch(train) [331][10/63] lr: 1.6190e-03 eta: 8:54:10 time: 0.8379 data_time: 0.2621 memory: 14901 loss: 1.5231 loss_prob: 0.8336 loss_thr: 0.5479 loss_db: 0.1416 2022/11/02 15:41:13 - mmengine - INFO - Epoch(train) [331][15/63] lr: 1.6190e-03 eta: 8:54:10 time: 0.5714 data_time: 0.0082 memory: 14901 loss: 1.7113 loss_prob: 0.9865 loss_thr: 0.5591 loss_db: 0.1657 2022/11/02 15:41:15 - mmengine - INFO - Epoch(train) [331][20/63] lr: 1.6190e-03 eta: 8:54:03 time: 0.5430 data_time: 0.0106 memory: 14901 loss: 1.8938 loss_prob: 1.1285 loss_thr: 0.5764 loss_db: 0.1889 2022/11/02 15:41:18 - mmengine - INFO - Epoch(train) [331][25/63] lr: 1.6190e-03 eta: 8:54:03 time: 0.5710 data_time: 0.0307 memory: 14901 loss: 1.9899 loss_prob: 1.1874 loss_thr: 0.6040 loss_db: 0.1985 2022/11/02 15:41:21 - mmengine - INFO - Epoch(train) [331][30/63] lr: 1.6190e-03 eta: 8:53:57 time: 0.5741 data_time: 0.0391 memory: 14901 loss: 2.1402 loss_prob: 1.2907 loss_thr: 0.6381 loss_db: 0.2114 2022/11/02 15:41:23 - mmengine - INFO - Epoch(train) [331][35/63] lr: 1.6190e-03 eta: 8:53:57 time: 0.4856 data_time: 0.0194 memory: 14901 loss: 2.3154 loss_prob: 1.4559 loss_thr: 0.6304 loss_db: 0.2291 2022/11/02 15:41:26 - mmengine - INFO - Epoch(train) [331][40/63] lr: 1.6190e-03 eta: 8:53:49 time: 0.5060 data_time: 0.0109 memory: 14901 loss: 2.2929 loss_prob: 1.4413 loss_thr: 0.6211 loss_db: 0.2304 2022/11/02 15:41:29 - mmengine - INFO - Epoch(train) [331][45/63] lr: 1.6190e-03 eta: 8:53:49 time: 0.5342 data_time: 0.0108 memory: 14901 loss: 2.3168 loss_prob: 1.4423 loss_thr: 0.6346 loss_db: 0.2399 2022/11/02 15:41:32 - mmengine - INFO - Epoch(train) [331][50/63] lr: 1.6190e-03 eta: 8:53:42 time: 0.5430 data_time: 0.0210 memory: 14901 loss: 2.3181 loss_prob: 1.4491 loss_thr: 0.6379 loss_db: 0.2311 2022/11/02 15:41:34 - mmengine - INFO - Epoch(train) [331][55/63] lr: 1.6190e-03 eta: 8:53:42 time: 0.5835 data_time: 0.0280 memory: 14901 loss: 2.0902 loss_prob: 1.2685 loss_thr: 0.6202 loss_db: 0.2015 2022/11/02 15:41:38 - mmengine - INFO - Epoch(train) [331][60/63] lr: 1.6190e-03 eta: 8:53:37 time: 0.6096 data_time: 0.0187 memory: 14901 loss: 1.9692 loss_prob: 1.1801 loss_thr: 0.5923 loss_db: 0.1968 2022/11/02 15:41:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:41:44 - mmengine - INFO - Epoch(train) [332][5/63] lr: 1.6174e-03 eta: 8:53:37 time: 0.7165 data_time: 0.1770 memory: 14901 loss: 1.8667 loss_prob: 1.0803 loss_thr: 0.6090 loss_db: 0.1774 2022/11/02 15:41:46 - mmengine - INFO - Epoch(train) [332][10/63] lr: 1.6174e-03 eta: 8:53:29 time: 0.7562 data_time: 0.1892 memory: 14901 loss: 1.7961 loss_prob: 1.0200 loss_thr: 0.6068 loss_db: 0.1693 2022/11/02 15:41:49 - mmengine - INFO - Epoch(train) [332][15/63] lr: 1.6174e-03 eta: 8:53:29 time: 0.5591 data_time: 0.0281 memory: 14901 loss: 1.8658 loss_prob: 1.0802 loss_thr: 0.6095 loss_db: 0.1761 2022/11/02 15:41:52 - mmengine - INFO - Epoch(train) [332][20/63] lr: 1.6174e-03 eta: 8:53:22 time: 0.5497 data_time: 0.0196 memory: 14901 loss: 1.9193 loss_prob: 1.1306 loss_thr: 0.6094 loss_db: 0.1793 2022/11/02 15:41:55 - mmengine - INFO - Epoch(train) [332][25/63] lr: 1.6174e-03 eta: 8:53:22 time: 0.5442 data_time: 0.0272 memory: 14901 loss: 1.8105 loss_prob: 1.0478 loss_thr: 0.5941 loss_db: 0.1685 2022/11/02 15:41:57 - mmengine - INFO - Epoch(train) [332][30/63] lr: 1.6174e-03 eta: 8:53:15 time: 0.5292 data_time: 0.0348 memory: 14901 loss: 1.6609 loss_prob: 0.9464 loss_thr: 0.5565 loss_db: 0.1580 2022/11/02 15:42:00 - mmengine - INFO - Epoch(train) [332][35/63] lr: 1.6174e-03 eta: 8:53:15 time: 0.4947 data_time: 0.0228 memory: 14901 loss: 1.5907 loss_prob: 0.9115 loss_thr: 0.5304 loss_db: 0.1488 2022/11/02 15:42:02 - mmengine - INFO - Epoch(train) [332][40/63] lr: 1.6174e-03 eta: 8:53:08 time: 0.5337 data_time: 0.0137 memory: 14901 loss: 1.6359 loss_prob: 0.9297 loss_thr: 0.5541 loss_db: 0.1522 2022/11/02 15:42:05 - mmengine - INFO - Epoch(train) [332][45/63] lr: 1.6174e-03 eta: 8:53:08 time: 0.5287 data_time: 0.0102 memory: 14901 loss: 1.6646 loss_prob: 0.9333 loss_thr: 0.5712 loss_db: 0.1601 2022/11/02 15:42:08 - mmengine - INFO - Epoch(train) [332][50/63] lr: 1.6174e-03 eta: 8:53:01 time: 0.5579 data_time: 0.0250 memory: 14901 loss: 1.6930 loss_prob: 0.9636 loss_thr: 0.5668 loss_db: 0.1626 2022/11/02 15:42:12 - mmengine - INFO - Epoch(train) [332][55/63] lr: 1.6174e-03 eta: 8:53:01 time: 0.6794 data_time: 0.0349 memory: 14901 loss: 1.6433 loss_prob: 0.9437 loss_thr: 0.5469 loss_db: 0.1528 2022/11/02 15:42:14 - mmengine - INFO - Epoch(train) [332][60/63] lr: 1.6174e-03 eta: 8:52:56 time: 0.6166 data_time: 0.0194 memory: 14901 loss: 1.5424 loss_prob: 0.8713 loss_thr: 0.5292 loss_db: 0.1419 2022/11/02 15:42:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:42:21 - mmengine - INFO - Epoch(train) [333][5/63] lr: 1.6157e-03 eta: 8:52:56 time: 0.8096 data_time: 0.2445 memory: 14901 loss: 1.5398 loss_prob: 0.8396 loss_thr: 0.5585 loss_db: 0.1417 2022/11/02 15:42:24 - mmengine - INFO - Epoch(train) [333][10/63] lr: 1.6157e-03 eta: 8:52:50 time: 0.8199 data_time: 0.2385 memory: 14901 loss: 1.5849 loss_prob: 0.8806 loss_thr: 0.5649 loss_db: 0.1394 2022/11/02 15:42:27 - mmengine - INFO - Epoch(train) [333][15/63] lr: 1.6157e-03 eta: 8:52:50 time: 0.5553 data_time: 0.0077 memory: 14901 loss: 1.5991 loss_prob: 0.9037 loss_thr: 0.5469 loss_db: 0.1485 2022/11/02 15:42:30 - mmengine - INFO - Epoch(train) [333][20/63] lr: 1.6157e-03 eta: 8:52:45 time: 0.6024 data_time: 0.0092 memory: 14901 loss: 1.5909 loss_prob: 0.8878 loss_thr: 0.5523 loss_db: 0.1508 2022/11/02 15:42:32 - mmengine - INFO - Epoch(train) [333][25/63] lr: 1.6157e-03 eta: 8:52:45 time: 0.5566 data_time: 0.0297 memory: 14901 loss: 1.6571 loss_prob: 0.9417 loss_thr: 0.5624 loss_db: 0.1530 2022/11/02 15:42:35 - mmengine - INFO - Epoch(train) [333][30/63] lr: 1.6157e-03 eta: 8:52:37 time: 0.5242 data_time: 0.0391 memory: 14901 loss: 1.5832 loss_prob: 0.8965 loss_thr: 0.5388 loss_db: 0.1478 2022/11/02 15:42:38 - mmengine - INFO - Epoch(train) [333][35/63] lr: 1.6157e-03 eta: 8:52:37 time: 0.5399 data_time: 0.0235 memory: 14901 loss: 1.6184 loss_prob: 0.9088 loss_thr: 0.5596 loss_db: 0.1500 2022/11/02 15:42:40 - mmengine - INFO - Epoch(train) [333][40/63] lr: 1.6157e-03 eta: 8:52:30 time: 0.5253 data_time: 0.0127 memory: 14901 loss: 1.6495 loss_prob: 0.9235 loss_thr: 0.5732 loss_db: 0.1528 2022/11/02 15:42:43 - mmengine - INFO - Epoch(train) [333][45/63] lr: 1.6157e-03 eta: 8:52:30 time: 0.4842 data_time: 0.0088 memory: 14901 loss: 1.6906 loss_prob: 0.9802 loss_thr: 0.5550 loss_db: 0.1554 2022/11/02 15:42:45 - mmengine - INFO - Epoch(train) [333][50/63] lr: 1.6157e-03 eta: 8:52:23 time: 0.5279 data_time: 0.0224 memory: 14901 loss: 1.6933 loss_prob: 0.9826 loss_thr: 0.5558 loss_db: 0.1549 2022/11/02 15:42:48 - mmengine - INFO - Epoch(train) [333][55/63] lr: 1.6157e-03 eta: 8:52:23 time: 0.5683 data_time: 0.0339 memory: 14901 loss: 1.6596 loss_prob: 0.9310 loss_thr: 0.5727 loss_db: 0.1559 2022/11/02 15:42:51 - mmengine - INFO - Epoch(train) [333][60/63] lr: 1.6157e-03 eta: 8:52:16 time: 0.5567 data_time: 0.0183 memory: 14901 loss: 1.7885 loss_prob: 1.0239 loss_thr: 0.5950 loss_db: 0.1696 2022/11/02 15:42:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:42:59 - mmengine - INFO - Epoch(train) [334][5/63] lr: 1.6140e-03 eta: 8:52:16 time: 0.8769 data_time: 0.2928 memory: 14901 loss: 1.6772 loss_prob: 0.9483 loss_thr: 0.5716 loss_db: 0.1574 2022/11/02 15:43:02 - mmengine - INFO - Epoch(train) [334][10/63] lr: 1.6140e-03 eta: 8:52:14 time: 0.9668 data_time: 0.2898 memory: 14901 loss: 1.7389 loss_prob: 1.0009 loss_thr: 0.5719 loss_db: 0.1661 2022/11/02 15:43:05 - mmengine - INFO - Epoch(train) [334][15/63] lr: 1.6140e-03 eta: 8:52:14 time: 0.6409 data_time: 0.0117 memory: 14901 loss: 1.6986 loss_prob: 0.9718 loss_thr: 0.5678 loss_db: 0.1590 2022/11/02 15:43:07 - mmengine - INFO - Epoch(train) [334][20/63] lr: 1.6140e-03 eta: 8:52:06 time: 0.5304 data_time: 0.0084 memory: 14901 loss: 1.6232 loss_prob: 0.9171 loss_thr: 0.5561 loss_db: 0.1500 2022/11/02 15:43:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:43:11 - mmengine - INFO - Epoch(train) [334][25/63] lr: 1.6140e-03 eta: 8:52:06 time: 0.5398 data_time: 0.0418 memory: 14901 loss: 1.6911 loss_prob: 0.9656 loss_thr: 0.5653 loss_db: 0.1603 2022/11/02 15:43:13 - mmengine - INFO - Epoch(train) [334][30/63] lr: 1.6140e-03 eta: 8:52:00 time: 0.5669 data_time: 0.0469 memory: 14901 loss: 1.7005 loss_prob: 0.9778 loss_thr: 0.5631 loss_db: 0.1595 2022/11/02 15:43:16 - mmengine - INFO - Epoch(train) [334][35/63] lr: 1.6140e-03 eta: 8:52:00 time: 0.5549 data_time: 0.0108 memory: 14901 loss: 1.7056 loss_prob: 0.9702 loss_thr: 0.5800 loss_db: 0.1555 2022/11/02 15:43:19 - mmengine - INFO - Epoch(train) [334][40/63] lr: 1.6140e-03 eta: 8:51:55 time: 0.6034 data_time: 0.0090 memory: 14901 loss: 1.6726 loss_prob: 0.9376 loss_thr: 0.5804 loss_db: 0.1545 2022/11/02 15:43:22 - mmengine - INFO - Epoch(train) [334][45/63] lr: 1.6140e-03 eta: 8:51:55 time: 0.5891 data_time: 0.0086 memory: 14901 loss: 1.6477 loss_prob: 0.9356 loss_thr: 0.5570 loss_db: 0.1550 2022/11/02 15:43:26 - mmengine - INFO - Epoch(train) [334][50/63] lr: 1.6140e-03 eta: 8:51:50 time: 0.6368 data_time: 0.0371 memory: 14901 loss: 1.7065 loss_prob: 0.9724 loss_thr: 0.5737 loss_db: 0.1604 2022/11/02 15:43:29 - mmengine - INFO - Epoch(train) [334][55/63] lr: 1.6140e-03 eta: 8:51:50 time: 0.6535 data_time: 0.0404 memory: 14901 loss: 1.6976 loss_prob: 0.9568 loss_thr: 0.5824 loss_db: 0.1584 2022/11/02 15:43:31 - mmengine - INFO - Epoch(train) [334][60/63] lr: 1.6140e-03 eta: 8:51:44 time: 0.5738 data_time: 0.0092 memory: 14901 loss: 1.5476 loss_prob: 0.8609 loss_thr: 0.5443 loss_db: 0.1423 2022/11/02 15:43:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:43:40 - mmengine - INFO - Epoch(train) [335][5/63] lr: 1.6123e-03 eta: 8:51:44 time: 0.9342 data_time: 0.1874 memory: 14901 loss: 1.4954 loss_prob: 0.8259 loss_thr: 0.5293 loss_db: 0.1401 2022/11/02 15:43:43 - mmengine - INFO - Epoch(train) [335][10/63] lr: 1.6123e-03 eta: 8:51:42 time: 0.9582 data_time: 0.1943 memory: 14901 loss: 1.6232 loss_prob: 0.9111 loss_thr: 0.5598 loss_db: 0.1522 2022/11/02 15:43:46 - mmengine - INFO - Epoch(train) [335][15/63] lr: 1.6123e-03 eta: 8:51:42 time: 0.6801 data_time: 0.0134 memory: 14901 loss: 1.6476 loss_prob: 0.9307 loss_thr: 0.5632 loss_db: 0.1537 2022/11/02 15:43:49 - mmengine - INFO - Epoch(train) [335][20/63] lr: 1.6123e-03 eta: 8:51:37 time: 0.6235 data_time: 0.0092 memory: 14901 loss: 1.5183 loss_prob: 0.8467 loss_thr: 0.5281 loss_db: 0.1436 2022/11/02 15:43:52 - mmengine - INFO - Epoch(train) [335][25/63] lr: 1.6123e-03 eta: 8:51:37 time: 0.5651 data_time: 0.0116 memory: 14901 loss: 1.4884 loss_prob: 0.8348 loss_thr: 0.5132 loss_db: 0.1404 2022/11/02 15:43:55 - mmengine - INFO - Epoch(train) [335][30/63] lr: 1.6123e-03 eta: 8:51:31 time: 0.5986 data_time: 0.0385 memory: 14901 loss: 1.5230 loss_prob: 0.8539 loss_thr: 0.5278 loss_db: 0.1412 2022/11/02 15:43:58 - mmengine - INFO - Epoch(train) [335][35/63] lr: 1.6123e-03 eta: 8:51:31 time: 0.6356 data_time: 0.0431 memory: 14901 loss: 1.5476 loss_prob: 0.8629 loss_thr: 0.5395 loss_db: 0.1452 2022/11/02 15:44:01 - mmengine - INFO - Epoch(train) [335][40/63] lr: 1.6123e-03 eta: 8:51:25 time: 0.5596 data_time: 0.0159 memory: 14901 loss: 1.5728 loss_prob: 0.8744 loss_thr: 0.5499 loss_db: 0.1485 2022/11/02 15:44:03 - mmengine - INFO - Epoch(train) [335][45/63] lr: 1.6123e-03 eta: 8:51:25 time: 0.4936 data_time: 0.0081 memory: 14901 loss: 1.5991 loss_prob: 0.8804 loss_thr: 0.5703 loss_db: 0.1484 2022/11/02 15:44:06 - mmengine - INFO - Epoch(train) [335][50/63] lr: 1.6123e-03 eta: 8:51:17 time: 0.5229 data_time: 0.0143 memory: 14901 loss: 1.5738 loss_prob: 0.8651 loss_thr: 0.5670 loss_db: 0.1417 2022/11/02 15:44:09 - mmengine - INFO - Epoch(train) [335][55/63] lr: 1.6123e-03 eta: 8:51:17 time: 0.5929 data_time: 0.0386 memory: 14901 loss: 1.5896 loss_prob: 0.9055 loss_thr: 0.5386 loss_db: 0.1455 2022/11/02 15:44:12 - mmengine - INFO - Epoch(train) [335][60/63] lr: 1.6123e-03 eta: 8:51:11 time: 0.5694 data_time: 0.0314 memory: 14901 loss: 1.6185 loss_prob: 0.9304 loss_thr: 0.5365 loss_db: 0.1516 2022/11/02 15:44:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:44:22 - mmengine - INFO - Epoch(train) [336][5/63] lr: 1.6106e-03 eta: 8:51:11 time: 1.0972 data_time: 0.2334 memory: 14901 loss: 1.4678 loss_prob: 0.7992 loss_thr: 0.5344 loss_db: 0.1342 2022/11/02 15:44:25 - mmengine - INFO - Epoch(train) [336][10/63] lr: 1.6106e-03 eta: 8:51:10 time: 1.0055 data_time: 0.2330 memory: 14901 loss: 1.5412 loss_prob: 0.8553 loss_thr: 0.5422 loss_db: 0.1437 2022/11/02 15:44:28 - mmengine - INFO - Epoch(train) [336][15/63] lr: 1.6106e-03 eta: 8:51:10 time: 0.6637 data_time: 0.0120 memory: 14901 loss: 1.6908 loss_prob: 0.9471 loss_thr: 0.5839 loss_db: 0.1599 2022/11/02 15:44:32 - mmengine - INFO - Epoch(train) [336][20/63] lr: 1.6106e-03 eta: 8:51:08 time: 0.7353 data_time: 0.0094 memory: 14901 loss: 1.6054 loss_prob: 0.8988 loss_thr: 0.5558 loss_db: 0.1508 2022/11/02 15:44:36 - mmengine - INFO - Epoch(train) [336][25/63] lr: 1.6106e-03 eta: 8:51:08 time: 0.7488 data_time: 0.0334 memory: 14901 loss: 1.5984 loss_prob: 0.9058 loss_thr: 0.5386 loss_db: 0.1540 2022/11/02 15:44:38 - mmengine - INFO - Epoch(train) [336][30/63] lr: 1.6106e-03 eta: 8:51:03 time: 0.6344 data_time: 0.0398 memory: 14901 loss: 1.5941 loss_prob: 0.8935 loss_thr: 0.5493 loss_db: 0.1513 2022/11/02 15:44:42 - mmengine - INFO - Epoch(train) [336][35/63] lr: 1.6106e-03 eta: 8:51:03 time: 0.5996 data_time: 0.0150 memory: 14901 loss: 1.5311 loss_prob: 0.8383 loss_thr: 0.5513 loss_db: 0.1415 2022/11/02 15:44:45 - mmengine - INFO - Epoch(train) [336][40/63] lr: 1.6106e-03 eta: 8:50:59 time: 0.6335 data_time: 0.0146 memory: 14901 loss: 1.5665 loss_prob: 0.8634 loss_thr: 0.5593 loss_db: 0.1438 2022/11/02 15:44:47 - mmengine - INFO - Epoch(train) [336][45/63] lr: 1.6106e-03 eta: 8:50:59 time: 0.5664 data_time: 0.0115 memory: 14901 loss: 1.5231 loss_prob: 0.8417 loss_thr: 0.5417 loss_db: 0.1396 2022/11/02 15:44:51 - mmengine - INFO - Epoch(train) [336][50/63] lr: 1.6106e-03 eta: 8:50:54 time: 0.6166 data_time: 0.0244 memory: 14901 loss: 1.7112 loss_prob: 0.9923 loss_thr: 0.5567 loss_db: 0.1622 2022/11/02 15:44:54 - mmengine - INFO - Epoch(train) [336][55/63] lr: 1.6106e-03 eta: 8:50:54 time: 0.7064 data_time: 0.0325 memory: 14901 loss: 1.7728 loss_prob: 1.0302 loss_thr: 0.5716 loss_db: 0.1710 2022/11/02 15:44:58 - mmengine - INFO - Epoch(train) [336][60/63] lr: 1.6106e-03 eta: 8:50:50 time: 0.6778 data_time: 0.0182 memory: 14901 loss: 1.6771 loss_prob: 0.9671 loss_thr: 0.5471 loss_db: 0.1629 2022/11/02 15:45:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:45:08 - mmengine - INFO - Epoch(train) [337][5/63] lr: 1.6090e-03 eta: 8:50:50 time: 1.1015 data_time: 0.2954 memory: 14901 loss: 1.5674 loss_prob: 0.8961 loss_thr: 0.5254 loss_db: 0.1459 2022/11/02 15:45:10 - mmengine - INFO - Epoch(train) [337][10/63] lr: 1.6090e-03 eta: 8:50:49 time: 0.9998 data_time: 0.2980 memory: 14901 loss: 1.4814 loss_prob: 0.8242 loss_thr: 0.5175 loss_db: 0.1397 2022/11/02 15:45:14 - mmengine - INFO - Epoch(train) [337][15/63] lr: 1.6090e-03 eta: 8:50:49 time: 0.6259 data_time: 0.0110 memory: 14901 loss: 1.6230 loss_prob: 0.9158 loss_thr: 0.5535 loss_db: 0.1536 2022/11/02 15:45:16 - mmengine - INFO - Epoch(train) [337][20/63] lr: 1.6090e-03 eta: 8:50:44 time: 0.6174 data_time: 0.0111 memory: 14901 loss: 1.8237 loss_prob: 1.0656 loss_thr: 0.5831 loss_db: 0.1750 2022/11/02 15:45:20 - mmengine - INFO - Epoch(train) [337][25/63] lr: 1.6090e-03 eta: 8:50:44 time: 0.6529 data_time: 0.0432 memory: 14901 loss: 1.7290 loss_prob: 0.9909 loss_thr: 0.5712 loss_db: 0.1669 2022/11/02 15:45:24 - mmengine - INFO - Epoch(train) [337][30/63] lr: 1.6090e-03 eta: 8:50:42 time: 0.7361 data_time: 0.0493 memory: 14901 loss: 1.5985 loss_prob: 0.8902 loss_thr: 0.5600 loss_db: 0.1483 2022/11/02 15:45:26 - mmengine - INFO - Epoch(train) [337][35/63] lr: 1.6090e-03 eta: 8:50:42 time: 0.6164 data_time: 0.0190 memory: 14901 loss: 1.6100 loss_prob: 0.8949 loss_thr: 0.5670 loss_db: 0.1481 2022/11/02 15:45:29 - mmengine - INFO - Epoch(train) [337][40/63] lr: 1.6090e-03 eta: 8:50:34 time: 0.5268 data_time: 0.0130 memory: 14901 loss: 1.6899 loss_prob: 0.9504 loss_thr: 0.5792 loss_db: 0.1603 2022/11/02 15:45:32 - mmengine - INFO - Epoch(train) [337][45/63] lr: 1.6090e-03 eta: 8:50:34 time: 0.5090 data_time: 0.0146 memory: 14901 loss: 1.6711 loss_prob: 0.9460 loss_thr: 0.5648 loss_db: 0.1604 2022/11/02 15:45:35 - mmengine - INFO - Epoch(train) [337][50/63] lr: 1.6090e-03 eta: 8:50:28 time: 0.5723 data_time: 0.0266 memory: 14901 loss: 1.6719 loss_prob: 0.9403 loss_thr: 0.5712 loss_db: 0.1603 2022/11/02 15:45:38 - mmengine - INFO - Epoch(train) [337][55/63] lr: 1.6090e-03 eta: 8:50:28 time: 0.6304 data_time: 0.0299 memory: 14901 loss: 1.7312 loss_prob: 0.9827 loss_thr: 0.5813 loss_db: 0.1671 2022/11/02 15:45:41 - mmengine - INFO - Epoch(train) [337][60/63] lr: 1.6090e-03 eta: 8:50:24 time: 0.6626 data_time: 0.0158 memory: 14901 loss: 1.7551 loss_prob: 1.0057 loss_thr: 0.5814 loss_db: 0.1680 2022/11/02 15:45:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:45:50 - mmengine - INFO - Epoch(train) [338][5/63] lr: 1.6073e-03 eta: 8:50:24 time: 0.9876 data_time: 0.2720 memory: 14901 loss: 1.6917 loss_prob: 0.9737 loss_thr: 0.5546 loss_db: 0.1634 2022/11/02 15:45:53 - mmengine - INFO - Epoch(train) [338][10/63] lr: 1.6073e-03 eta: 8:50:24 time: 1.0415 data_time: 0.2710 memory: 14901 loss: 1.6377 loss_prob: 0.9298 loss_thr: 0.5530 loss_db: 0.1549 2022/11/02 15:45:56 - mmengine - INFO - Epoch(train) [338][15/63] lr: 1.6073e-03 eta: 8:50:24 time: 0.6895 data_time: 0.0142 memory: 14901 loss: 1.6811 loss_prob: 0.9421 loss_thr: 0.5793 loss_db: 0.1597 2022/11/02 15:45:59 - mmengine - INFO - Epoch(train) [338][20/63] lr: 1.6073e-03 eta: 8:50:19 time: 0.6053 data_time: 0.0153 memory: 14901 loss: 1.7012 loss_prob: 0.9550 loss_thr: 0.5860 loss_db: 0.1602 2022/11/02 15:46:02 - mmengine - INFO - Epoch(train) [338][25/63] lr: 1.6073e-03 eta: 8:50:19 time: 0.5553 data_time: 0.0362 memory: 14901 loss: 1.6010 loss_prob: 0.8947 loss_thr: 0.5580 loss_db: 0.1483 2022/11/02 15:46:05 - mmengine - INFO - Epoch(train) [338][30/63] lr: 1.6073e-03 eta: 8:50:12 time: 0.5419 data_time: 0.0444 memory: 14901 loss: 1.5656 loss_prob: 0.8713 loss_thr: 0.5465 loss_db: 0.1477 2022/11/02 15:46:08 - mmengine - INFO - Epoch(train) [338][35/63] lr: 1.6073e-03 eta: 8:50:12 time: 0.5631 data_time: 0.0189 memory: 14901 loss: 1.6771 loss_prob: 0.9584 loss_thr: 0.5584 loss_db: 0.1603 2022/11/02 15:46:10 - mmengine - INFO - Epoch(train) [338][40/63] lr: 1.6073e-03 eta: 8:50:06 time: 0.5907 data_time: 0.0132 memory: 14901 loss: 1.6334 loss_prob: 0.9310 loss_thr: 0.5478 loss_db: 0.1546 2022/11/02 15:46:14 - mmengine - INFO - Epoch(train) [338][45/63] lr: 1.6073e-03 eta: 8:50:06 time: 0.6019 data_time: 0.0112 memory: 14901 loss: 1.5666 loss_prob: 0.8777 loss_thr: 0.5434 loss_db: 0.1455 2022/11/02 15:46:17 - mmengine - INFO - Epoch(train) [338][50/63] lr: 1.6073e-03 eta: 8:50:01 time: 0.6226 data_time: 0.0286 memory: 14901 loss: 1.6420 loss_prob: 0.9303 loss_thr: 0.5619 loss_db: 0.1498 2022/11/02 15:46:20 - mmengine - INFO - Epoch(train) [338][55/63] lr: 1.6073e-03 eta: 8:50:01 time: 0.6353 data_time: 0.0345 memory: 14901 loss: 1.5362 loss_prob: 0.8586 loss_thr: 0.5361 loss_db: 0.1416 2022/11/02 15:46:24 - mmengine - INFO - Epoch(train) [338][60/63] lr: 1.6073e-03 eta: 8:49:58 time: 0.6913 data_time: 0.0128 memory: 14901 loss: 1.4820 loss_prob: 0.8215 loss_thr: 0.5216 loss_db: 0.1389 2022/11/02 15:46:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:46:33 - mmengine - INFO - Epoch(train) [339][5/63] lr: 1.6056e-03 eta: 8:49:58 time: 1.0527 data_time: 0.2662 memory: 14901 loss: 1.7395 loss_prob: 1.0303 loss_thr: 0.5518 loss_db: 0.1575 2022/11/02 15:46:36 - mmengine - INFO - Epoch(train) [339][10/63] lr: 1.6056e-03 eta: 8:49:57 time: 1.0094 data_time: 0.2656 memory: 14901 loss: 1.7464 loss_prob: 1.0161 loss_thr: 0.5719 loss_db: 0.1583 2022/11/02 15:46:39 - mmengine - INFO - Epoch(train) [339][15/63] lr: 1.6056e-03 eta: 8:49:57 time: 0.6490 data_time: 0.0056 memory: 14901 loss: 1.5494 loss_prob: 0.8499 loss_thr: 0.5555 loss_db: 0.1440 2022/11/02 15:46:42 - mmengine - INFO - Epoch(train) [339][20/63] lr: 1.6056e-03 eta: 8:49:51 time: 0.5975 data_time: 0.0059 memory: 14901 loss: 1.6216 loss_prob: 0.9049 loss_thr: 0.5642 loss_db: 0.1524 2022/11/02 15:46:45 - mmengine - INFO - Epoch(train) [339][25/63] lr: 1.6056e-03 eta: 8:49:51 time: 0.5465 data_time: 0.0350 memory: 14901 loss: 1.6016 loss_prob: 0.9046 loss_thr: 0.5427 loss_db: 0.1544 2022/11/02 15:46:47 - mmengine - INFO - Epoch(train) [339][30/63] lr: 1.6056e-03 eta: 8:49:45 time: 0.5702 data_time: 0.0436 memory: 14901 loss: 1.5776 loss_prob: 0.8960 loss_thr: 0.5288 loss_db: 0.1528 2022/11/02 15:46:50 - mmengine - INFO - Epoch(train) [339][35/63] lr: 1.6056e-03 eta: 8:49:45 time: 0.5278 data_time: 0.0150 memory: 14901 loss: 1.8492 loss_prob: 1.1041 loss_thr: 0.5732 loss_db: 0.1719 2022/11/02 15:46:53 - mmengine - INFO - Epoch(train) [339][40/63] lr: 1.6056e-03 eta: 8:49:39 time: 0.5731 data_time: 0.0086 memory: 14901 loss: 1.8571 loss_prob: 1.0946 loss_thr: 0.5923 loss_db: 0.1702 2022/11/02 15:46:56 - mmengine - INFO - Epoch(train) [339][45/63] lr: 1.6056e-03 eta: 8:49:39 time: 0.6219 data_time: 0.0076 memory: 14901 loss: 1.7445 loss_prob: 0.9951 loss_thr: 0.5834 loss_db: 0.1660 2022/11/02 15:46:59 - mmengine - INFO - Epoch(train) [339][50/63] lr: 1.6056e-03 eta: 8:49:34 time: 0.6456 data_time: 0.0274 memory: 14901 loss: 1.7396 loss_prob: 1.0145 loss_thr: 0.5593 loss_db: 0.1657 2022/11/02 15:47:02 - mmengine - INFO - Epoch(train) [339][55/63] lr: 1.6056e-03 eta: 8:49:34 time: 0.5995 data_time: 0.0331 memory: 14901 loss: 1.6595 loss_prob: 0.9519 loss_thr: 0.5530 loss_db: 0.1546 2022/11/02 15:47:06 - mmengine - INFO - Epoch(train) [339][60/63] lr: 1.6056e-03 eta: 8:49:30 time: 0.6350 data_time: 0.0118 memory: 14901 loss: 1.6466 loss_prob: 0.9300 loss_thr: 0.5591 loss_db: 0.1575 2022/11/02 15:47:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:47:14 - mmengine - INFO - Epoch(train) [340][5/63] lr: 1.6039e-03 eta: 8:49:30 time: 1.0254 data_time: 0.2547 memory: 14901 loss: 1.5763 loss_prob: 0.8727 loss_thr: 0.5547 loss_db: 0.1488 2022/11/02 15:47:17 - mmengine - INFO - Epoch(train) [340][10/63] lr: 1.6039e-03 eta: 8:49:27 time: 0.9680 data_time: 0.2619 memory: 14901 loss: 1.5626 loss_prob: 0.8709 loss_thr: 0.5457 loss_db: 0.1459 2022/11/02 15:47:20 - mmengine - INFO - Epoch(train) [340][15/63] lr: 1.6039e-03 eta: 8:49:27 time: 0.5187 data_time: 0.0167 memory: 14901 loss: 1.4695 loss_prob: 0.8052 loss_thr: 0.5279 loss_db: 0.1365 2022/11/02 15:47:22 - mmengine - INFO - Epoch(train) [340][20/63] lr: 1.6039e-03 eta: 8:49:20 time: 0.5164 data_time: 0.0103 memory: 14901 loss: 1.4921 loss_prob: 0.8256 loss_thr: 0.5289 loss_db: 0.1376 2022/11/02 15:47:25 - mmengine - INFO - Epoch(train) [340][25/63] lr: 1.6039e-03 eta: 8:49:20 time: 0.5796 data_time: 0.0334 memory: 14901 loss: 1.6876 loss_prob: 0.9799 loss_thr: 0.5511 loss_db: 0.1566 2022/11/02 15:47:29 - mmengine - INFO - Epoch(train) [340][30/63] lr: 1.6039e-03 eta: 8:49:16 time: 0.6701 data_time: 0.0413 memory: 14901 loss: 1.7179 loss_prob: 0.9828 loss_thr: 0.5754 loss_db: 0.1597 2022/11/02 15:47:33 - mmengine - INFO - Epoch(train) [340][35/63] lr: 1.6039e-03 eta: 8:49:16 time: 0.7219 data_time: 0.0197 memory: 14901 loss: 1.6603 loss_prob: 0.9343 loss_thr: 0.5671 loss_db: 0.1589 2022/11/02 15:47:36 - mmengine - INFO - Epoch(train) [340][40/63] lr: 1.6039e-03 eta: 8:49:13 time: 0.7150 data_time: 0.0147 memory: 14901 loss: 1.6576 loss_prob: 0.9530 loss_thr: 0.5435 loss_db: 0.1611 2022/11/02 15:47:39 - mmengine - INFO - Epoch(train) [340][45/63] lr: 1.6039e-03 eta: 8:49:13 time: 0.6189 data_time: 0.0128 memory: 14901 loss: 1.7051 loss_prob: 0.9805 loss_thr: 0.5638 loss_db: 0.1608 2022/11/02 15:47:42 - mmengine - INFO - Epoch(train) [340][50/63] lr: 1.6039e-03 eta: 8:49:07 time: 0.5644 data_time: 0.0262 memory: 14901 loss: 1.6992 loss_prob: 0.9642 loss_thr: 0.5764 loss_db: 0.1585 2022/11/02 15:47:45 - mmengine - INFO - Epoch(train) [340][55/63] lr: 1.6039e-03 eta: 8:49:07 time: 0.6624 data_time: 0.0270 memory: 14901 loss: 1.5943 loss_prob: 0.8816 loss_thr: 0.5648 loss_db: 0.1479 2022/11/02 15:47:49 - mmengine - INFO - Epoch(train) [340][60/63] lr: 1.6039e-03 eta: 8:49:05 time: 0.7388 data_time: 0.0097 memory: 14901 loss: 1.7230 loss_prob: 0.9824 loss_thr: 0.5752 loss_db: 0.1655 2022/11/02 15:47:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:47:51 - mmengine - INFO - Saving checkpoint at 340 epochs 2022/11/02 15:47:55 - mmengine - INFO - Epoch(val) [340][5/500] eta: 8:49:05 time: 0.0458 data_time: 0.0061 memory: 14901 2022/11/02 15:47:56 - mmengine - INFO - Epoch(val) [340][10/500] eta: 0:00:24 time: 0.0502 data_time: 0.0065 memory: 1008 2022/11/02 15:47:56 - mmengine - INFO - Epoch(val) [340][15/500] eta: 0:00:24 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 15:47:56 - mmengine - INFO - Epoch(val) [340][20/500] eta: 0:00:19 time: 0.0415 data_time: 0.0027 memory: 1008 2022/11/02 15:47:56 - mmengine - INFO - Epoch(val) [340][25/500] eta: 0:00:19 time: 0.0386 data_time: 0.0027 memory: 1008 2022/11/02 15:47:56 - mmengine - INFO - Epoch(val) [340][30/500] eta: 0:00:20 time: 0.0429 data_time: 0.0028 memory: 1008 2022/11/02 15:47:57 - mmengine - INFO - Epoch(val) [340][35/500] eta: 0:00:20 time: 0.0428 data_time: 0.0027 memory: 1008 2022/11/02 15:47:57 - mmengine - INFO - Epoch(val) [340][40/500] eta: 0:00:22 time: 0.0489 data_time: 0.0030 memory: 1008 2022/11/02 15:47:57 - mmengine - INFO - Epoch(val) [340][45/500] eta: 0:00:22 time: 0.0521 data_time: 0.0031 memory: 1008 2022/11/02 15:47:58 - mmengine - INFO - Epoch(val) [340][50/500] eta: 0:00:43 time: 0.0975 data_time: 0.0537 memory: 1008 2022/11/02 15:47:58 - mmengine - INFO - Epoch(val) [340][55/500] eta: 0:00:43 time: 0.0988 data_time: 0.0532 memory: 1008 2022/11/02 15:47:58 - mmengine - INFO - Epoch(val) [340][60/500] eta: 0:00:19 time: 0.0434 data_time: 0.0020 memory: 1008 2022/11/02 15:47:59 - mmengine - INFO - Epoch(val) [340][65/500] eta: 0:00:19 time: 0.0440 data_time: 0.0026 memory: 1008 2022/11/02 15:47:59 - mmengine - INFO - Epoch(val) [340][70/500] eta: 0:00:19 time: 0.0448 data_time: 0.0031 memory: 1008 2022/11/02 15:47:59 - mmengine - INFO - Epoch(val) [340][75/500] eta: 0:00:19 time: 0.0396 data_time: 0.0029 memory: 1008 2022/11/02 15:47:59 - mmengine - INFO - Epoch(val) [340][80/500] eta: 0:00:17 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/02 15:47:59 - mmengine - INFO - Epoch(val) [340][85/500] eta: 0:00:17 time: 0.0413 data_time: 0.0030 memory: 1008 2022/11/02 15:48:00 - mmengine - INFO - Epoch(val) [340][90/500] eta: 0:00:18 time: 0.0442 data_time: 0.0029 memory: 1008 2022/11/02 15:48:00 - mmengine - INFO - Epoch(val) [340][95/500] eta: 0:00:18 time: 0.0504 data_time: 0.0032 memory: 1008 2022/11/02 15:48:00 - mmengine - INFO - Epoch(val) [340][100/500] eta: 0:00:17 time: 0.0436 data_time: 0.0030 memory: 1008 2022/11/02 15:48:00 - mmengine - INFO - Epoch(val) [340][105/500] eta: 0:00:17 time: 0.0452 data_time: 0.0054 memory: 1008 2022/11/02 15:48:00 - mmengine - INFO - Epoch(val) [340][110/500] eta: 0:00:17 time: 0.0453 data_time: 0.0054 memory: 1008 2022/11/02 15:48:01 - mmengine - INFO - Epoch(val) [340][115/500] eta: 0:00:17 time: 0.0455 data_time: 0.0031 memory: 1008 2022/11/02 15:48:01 - mmengine - INFO - Epoch(val) [340][120/500] eta: 0:00:17 time: 0.0468 data_time: 0.0032 memory: 1008 2022/11/02 15:48:01 - mmengine - INFO - Epoch(val) [340][125/500] eta: 0:00:17 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/02 15:48:01 - mmengine - INFO - Epoch(val) [340][130/500] eta: 0:00:15 time: 0.0418 data_time: 0.0031 memory: 1008 2022/11/02 15:48:02 - mmengine - INFO - Epoch(val) [340][135/500] eta: 0:00:15 time: 0.0440 data_time: 0.0030 memory: 1008 2022/11/02 15:48:02 - mmengine - INFO - Epoch(val) [340][140/500] eta: 0:00:16 time: 0.0470 data_time: 0.0030 memory: 1008 2022/11/02 15:48:02 - mmengine - INFO - Epoch(val) [340][145/500] eta: 0:00:16 time: 0.0562 data_time: 0.0037 memory: 1008 2022/11/02 15:48:02 - mmengine - INFO - Epoch(val) [340][150/500] eta: 0:00:20 time: 0.0578 data_time: 0.0039 memory: 1008 2022/11/02 15:48:03 - mmengine - INFO - Epoch(val) [340][155/500] eta: 0:00:20 time: 0.0590 data_time: 0.0038 memory: 1008 2022/11/02 15:48:03 - mmengine - INFO - Epoch(val) [340][160/500] eta: 0:00:20 time: 0.0592 data_time: 0.0035 memory: 1008 2022/11/02 15:48:03 - mmengine - INFO - Epoch(val) [340][165/500] eta: 0:00:20 time: 0.0508 data_time: 0.0031 memory: 1008 2022/11/02 15:48:04 - mmengine - INFO - Epoch(val) [340][170/500] eta: 0:00:16 time: 0.0502 data_time: 0.0032 memory: 1008 2022/11/02 15:48:04 - mmengine - INFO - Epoch(val) [340][175/500] eta: 0:00:16 time: 0.0457 data_time: 0.0030 memory: 1008 2022/11/02 15:48:04 - mmengine - INFO - Epoch(val) [340][180/500] eta: 0:00:14 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 15:48:04 - mmengine - INFO - Epoch(val) [340][185/500] eta: 0:00:14 time: 0.0462 data_time: 0.0028 memory: 1008 2022/11/02 15:48:04 - mmengine - INFO - Epoch(val) [340][190/500] eta: 0:00:14 time: 0.0469 data_time: 0.0029 memory: 1008 2022/11/02 15:48:05 - mmengine - INFO - Epoch(val) [340][195/500] eta: 0:00:14 time: 0.0471 data_time: 0.0034 memory: 1008 2022/11/02 15:48:05 - mmengine - INFO - Epoch(val) [340][200/500] eta: 0:00:16 time: 0.0540 data_time: 0.0038 memory: 1008 2022/11/02 15:48:05 - mmengine - INFO - Epoch(val) [340][205/500] eta: 0:00:16 time: 0.0506 data_time: 0.0033 memory: 1008 2022/11/02 15:48:05 - mmengine - INFO - Epoch(val) [340][210/500] eta: 0:00:12 time: 0.0426 data_time: 0.0028 memory: 1008 2022/11/02 15:48:06 - mmengine - INFO - Epoch(val) [340][215/500] eta: 0:00:12 time: 0.0438 data_time: 0.0027 memory: 1008 2022/11/02 15:48:06 - mmengine - INFO - Epoch(val) [340][220/500] eta: 0:00:11 time: 0.0416 data_time: 0.0029 memory: 1008 2022/11/02 15:48:06 - mmengine - INFO - Epoch(val) [340][225/500] eta: 0:00:11 time: 0.0454 data_time: 0.0027 memory: 1008 2022/11/02 15:48:06 - mmengine - INFO - Epoch(val) [340][230/500] eta: 0:00:12 time: 0.0447 data_time: 0.0023 memory: 1008 2022/11/02 15:48:07 - mmengine - INFO - Epoch(val) [340][235/500] eta: 0:00:12 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 15:48:07 - mmengine - INFO - Epoch(val) [340][240/500] eta: 0:00:12 time: 0.0465 data_time: 0.0032 memory: 1008 2022/11/02 15:48:07 - mmengine - INFO - Epoch(val) [340][245/500] eta: 0:00:12 time: 0.0478 data_time: 0.0036 memory: 1008 2022/11/02 15:48:07 - mmengine - INFO - Epoch(val) [340][250/500] eta: 0:00:12 time: 0.0490 data_time: 0.0035 memory: 1008 2022/11/02 15:48:07 - mmengine - INFO - Epoch(val) [340][255/500] eta: 0:00:12 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/02 15:48:08 - mmengine - INFO - Epoch(val) [340][260/500] eta: 0:00:09 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 15:48:08 - mmengine - INFO - Epoch(val) [340][265/500] eta: 0:00:09 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 15:48:09 - mmengine - INFO - Epoch(val) [340][270/500] eta: 0:00:26 time: 0.1166 data_time: 0.0750 memory: 1008 2022/11/02 15:48:09 - mmengine - INFO - Epoch(val) [340][275/500] eta: 0:00:26 time: 0.1162 data_time: 0.0746 memory: 1008 2022/11/02 15:48:09 - mmengine - INFO - Epoch(val) [340][280/500] eta: 0:00:10 time: 0.0466 data_time: 0.0036 memory: 1008 2022/11/02 15:48:09 - mmengine - INFO - Epoch(val) [340][285/500] eta: 0:00:10 time: 0.0472 data_time: 0.0039 memory: 1008 2022/11/02 15:48:10 - mmengine - INFO - Epoch(val) [340][290/500] eta: 0:00:08 time: 0.0409 data_time: 0.0029 memory: 1008 2022/11/02 15:48:10 - mmengine - INFO - Epoch(val) [340][295/500] eta: 0:00:08 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/02 15:48:10 - mmengine - INFO - Epoch(val) [340][300/500] eta: 0:00:08 time: 0.0432 data_time: 0.0032 memory: 1008 2022/11/02 15:48:10 - mmengine - INFO - Epoch(val) [340][305/500] eta: 0:00:08 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/02 15:48:11 - mmengine - INFO - Epoch(val) [340][310/500] eta: 0:00:08 time: 0.0459 data_time: 0.0034 memory: 1008 2022/11/02 15:48:11 - mmengine - INFO - Epoch(val) [340][315/500] eta: 0:00:08 time: 0.0557 data_time: 0.0035 memory: 1008 2022/11/02 15:48:11 - mmengine - INFO - Epoch(val) [340][320/500] eta: 0:00:09 time: 0.0506 data_time: 0.0027 memory: 1008 2022/11/02 15:48:11 - mmengine - INFO - Epoch(val) [340][325/500] eta: 0:00:09 time: 0.0629 data_time: 0.0028 memory: 1008 2022/11/02 15:48:12 - mmengine - INFO - Epoch(val) [340][330/500] eta: 0:00:10 time: 0.0625 data_time: 0.0028 memory: 1008 2022/11/02 15:48:12 - mmengine - INFO - Epoch(val) [340][335/500] eta: 0:00:10 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 15:48:12 - mmengine - INFO - Epoch(val) [340][340/500] eta: 0:00:09 time: 0.0597 data_time: 0.0033 memory: 1008 2022/11/02 15:48:13 - mmengine - INFO - Epoch(val) [340][345/500] eta: 0:00:09 time: 0.0596 data_time: 0.0032 memory: 1008 2022/11/02 15:48:13 - mmengine - INFO - Epoch(val) [340][350/500] eta: 0:00:07 time: 0.0510 data_time: 0.0036 memory: 1008 2022/11/02 15:48:13 - mmengine - INFO - Epoch(val) [340][355/500] eta: 0:00:07 time: 0.0497 data_time: 0.0033 memory: 1008 2022/11/02 15:48:13 - mmengine - INFO - Epoch(val) [340][360/500] eta: 0:00:06 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 15:48:13 - mmengine - INFO - Epoch(val) [340][365/500] eta: 0:00:06 time: 0.0493 data_time: 0.0033 memory: 1008 2022/11/02 15:48:14 - mmengine - INFO - Epoch(val) [340][370/500] eta: 0:00:06 time: 0.0474 data_time: 0.0045 memory: 1008 2022/11/02 15:48:14 - mmengine - INFO - Epoch(val) [340][375/500] eta: 0:00:06 time: 0.0455 data_time: 0.0041 memory: 1008 2022/11/02 15:48:14 - mmengine - INFO - Epoch(val) [340][380/500] eta: 0:00:05 time: 0.0466 data_time: 0.0028 memory: 1008 2022/11/02 15:48:14 - mmengine - INFO - Epoch(val) [340][385/500] eta: 0:00:05 time: 0.0471 data_time: 0.0027 memory: 1008 2022/11/02 15:48:15 - mmengine - INFO - Epoch(val) [340][390/500] eta: 0:00:05 time: 0.0464 data_time: 0.0029 memory: 1008 2022/11/02 15:48:15 - mmengine - INFO - Epoch(val) [340][395/500] eta: 0:00:05 time: 0.0468 data_time: 0.0033 memory: 1008 2022/11/02 15:48:15 - mmengine - INFO - Epoch(val) [340][400/500] eta: 0:00:04 time: 0.0481 data_time: 0.0035 memory: 1008 2022/11/02 15:48:15 - mmengine - INFO - Epoch(val) [340][405/500] eta: 0:00:04 time: 0.0457 data_time: 0.0033 memory: 1008 2022/11/02 15:48:16 - mmengine - INFO - Epoch(val) [340][410/500] eta: 0:00:04 time: 0.0446 data_time: 0.0029 memory: 1008 2022/11/02 15:48:16 - mmengine - INFO - Epoch(val) [340][415/500] eta: 0:00:04 time: 0.0435 data_time: 0.0028 memory: 1008 2022/11/02 15:48:16 - mmengine - INFO - Epoch(val) [340][420/500] eta: 0:00:03 time: 0.0377 data_time: 0.0027 memory: 1008 2022/11/02 15:48:16 - mmengine - INFO - Epoch(val) [340][425/500] eta: 0:00:03 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/02 15:48:16 - mmengine - INFO - Epoch(val) [340][430/500] eta: 0:00:03 time: 0.0465 data_time: 0.0034 memory: 1008 2022/11/02 15:48:17 - mmengine - INFO - Epoch(val) [340][435/500] eta: 0:00:03 time: 0.0441 data_time: 0.0032 memory: 1008 2022/11/02 15:48:17 - mmengine - INFO - Epoch(val) [340][440/500] eta: 0:00:02 time: 0.0422 data_time: 0.0029 memory: 1008 2022/11/02 15:48:17 - mmengine - INFO - Epoch(val) [340][445/500] eta: 0:00:02 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 15:48:17 - mmengine - INFO - Epoch(val) [340][450/500] eta: 0:00:02 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/02 15:48:18 - mmengine - INFO - Epoch(val) [340][455/500] eta: 0:00:02 time: 0.0453 data_time: 0.0028 memory: 1008 2022/11/02 15:48:18 - mmengine - INFO - Epoch(val) [340][460/500] eta: 0:00:01 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/02 15:48:18 - mmengine - INFO - Epoch(val) [340][465/500] eta: 0:00:01 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/02 15:48:18 - mmengine - INFO - Epoch(val) [340][470/500] eta: 0:00:01 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 15:48:18 - mmengine - INFO - Epoch(val) [340][475/500] eta: 0:00:01 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 15:48:19 - mmengine - INFO - Epoch(val) [340][480/500] eta: 0:00:00 time: 0.0452 data_time: 0.0030 memory: 1008 2022/11/02 15:48:19 - mmengine - INFO - Epoch(val) [340][485/500] eta: 0:00:00 time: 0.0451 data_time: 0.0030 memory: 1008 2022/11/02 15:48:19 - mmengine - INFO - Epoch(val) [340][490/500] eta: 0:00:00 time: 0.0490 data_time: 0.0048 memory: 1008 2022/11/02 15:48:19 - mmengine - INFO - Epoch(val) [340][495/500] eta: 0:00:00 time: 0.0518 data_time: 0.0047 memory: 1008 2022/11/02 15:48:20 - mmengine - INFO - Epoch(val) [340][500/500] eta: 0:00:00 time: 0.0440 data_time: 0.0027 memory: 1008 2022/11/02 15:48:20 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8440, precision: 0.5565, hmean: 0.6707 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8440, precision: 0.6402, hmean: 0.7281 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8411, precision: 0.7042, hmean: 0.7666 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8247, precision: 0.7741, hmean: 0.7986 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7573, precision: 0.8633, hmean: 0.8069 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4198, precision: 0.9468, hmean: 0.5817 2022/11/02 15:48:20 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0034, precision: 1.0000, hmean: 0.0067 2022/11/02 15:48:20 - mmengine - INFO - Epoch(val) [340][500/500] icdar/precision: 0.8633 icdar/recall: 0.7573 icdar/hmean: 0.8069 2022/11/02 15:48:26 - mmengine - INFO - Epoch(train) [341][5/63] lr: 1.6023e-03 eta: 0:00:00 time: 0.9255 data_time: 0.2742 memory: 14901 loss: 1.8546 loss_prob: 1.0771 loss_thr: 0.6008 loss_db: 0.1767 2022/11/02 15:48:29 - mmengine - INFO - Epoch(train) [341][10/63] lr: 1.6023e-03 eta: 8:49:02 time: 0.9420 data_time: 0.2921 memory: 14901 loss: 1.8507 loss_prob: 1.0823 loss_thr: 0.5934 loss_db: 0.1750 2022/11/02 15:48:32 - mmengine - INFO - Epoch(train) [341][15/63] lr: 1.6023e-03 eta: 8:49:02 time: 0.5810 data_time: 0.0264 memory: 14901 loss: 1.8649 loss_prob: 1.1141 loss_thr: 0.5744 loss_db: 0.1764 2022/11/02 15:48:34 - mmengine - INFO - Epoch(train) [341][20/63] lr: 1.6023e-03 eta: 8:48:54 time: 0.4986 data_time: 0.0050 memory: 14901 loss: 1.8217 loss_prob: 1.0705 loss_thr: 0.5716 loss_db: 0.1796 2022/11/02 15:48:37 - mmengine - INFO - Epoch(train) [341][25/63] lr: 1.6023e-03 eta: 8:48:54 time: 0.5011 data_time: 0.0124 memory: 14901 loss: 1.7478 loss_prob: 1.0090 loss_thr: 0.5705 loss_db: 0.1684 2022/11/02 15:48:39 - mmengine - INFO - Epoch(train) [341][30/63] lr: 1.6023e-03 eta: 8:48:47 time: 0.5299 data_time: 0.0330 memory: 14901 loss: 1.7534 loss_prob: 1.0123 loss_thr: 0.5826 loss_db: 0.1585 2022/11/02 15:48:42 - mmengine - INFO - Epoch(train) [341][35/63] lr: 1.6023e-03 eta: 8:48:47 time: 0.5440 data_time: 0.0272 memory: 14901 loss: 1.7985 loss_prob: 1.0412 loss_thr: 0.5911 loss_db: 0.1662 2022/11/02 15:48:44 - mmengine - INFO - Epoch(train) [341][40/63] lr: 1.6023e-03 eta: 8:48:39 time: 0.5140 data_time: 0.0071 memory: 14901 loss: 1.7616 loss_prob: 1.0137 loss_thr: 0.5805 loss_db: 0.1673 2022/11/02 15:48:47 - mmengine - INFO - Epoch(train) [341][45/63] lr: 1.6023e-03 eta: 8:48:39 time: 0.4794 data_time: 0.0056 memory: 14901 loss: 1.8032 loss_prob: 1.0504 loss_thr: 0.5804 loss_db: 0.1724 2022/11/02 15:48:50 - mmengine - INFO - Epoch(train) [341][50/63] lr: 1.6023e-03 eta: 8:48:32 time: 0.5445 data_time: 0.0130 memory: 14901 loss: 1.8038 loss_prob: 1.0499 loss_thr: 0.5814 loss_db: 0.1725 2022/11/02 15:48:53 - mmengine - INFO - Epoch(train) [341][55/63] lr: 1.6023e-03 eta: 8:48:32 time: 0.5735 data_time: 0.0251 memory: 14901 loss: 1.6660 loss_prob: 0.9419 loss_thr: 0.5653 loss_db: 0.1589 2022/11/02 15:48:56 - mmengine - INFO - Epoch(train) [341][60/63] lr: 1.6023e-03 eta: 8:48:26 time: 0.5750 data_time: 0.0194 memory: 14901 loss: 1.6015 loss_prob: 0.8921 loss_thr: 0.5596 loss_db: 0.1499 2022/11/02 15:48:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:49:03 - mmengine - INFO - Epoch(train) [342][5/63] lr: 1.6006e-03 eta: 8:48:26 time: 0.8328 data_time: 0.3328 memory: 14901 loss: 1.5425 loss_prob: 0.8555 loss_thr: 0.5455 loss_db: 0.1416 2022/11/02 15:49:07 - mmengine - INFO - Epoch(train) [342][10/63] lr: 1.6006e-03 eta: 8:48:25 time: 1.0174 data_time: 0.3351 memory: 14901 loss: 1.5979 loss_prob: 0.8991 loss_thr: 0.5468 loss_db: 0.1520 2022/11/02 15:49:10 - mmengine - INFO - Epoch(train) [342][15/63] lr: 1.6006e-03 eta: 8:48:25 time: 0.7009 data_time: 0.0120 memory: 14901 loss: 1.6463 loss_prob: 0.9275 loss_thr: 0.5612 loss_db: 0.1575 2022/11/02 15:49:12 - mmengine - INFO - Epoch(train) [342][20/63] lr: 1.6006e-03 eta: 8:48:17 time: 0.5264 data_time: 0.0098 memory: 14901 loss: 1.5993 loss_prob: 0.8952 loss_thr: 0.5554 loss_db: 0.1486 2022/11/02 15:49:15 - mmengine - INFO - Epoch(train) [342][25/63] lr: 1.6006e-03 eta: 8:48:17 time: 0.5478 data_time: 0.0369 memory: 14901 loss: 1.5619 loss_prob: 0.8778 loss_thr: 0.5396 loss_db: 0.1445 2022/11/02 15:49:18 - mmengine - INFO - Epoch(train) [342][30/63] lr: 1.6006e-03 eta: 8:48:10 time: 0.5451 data_time: 0.0366 memory: 14901 loss: 1.6072 loss_prob: 0.9186 loss_thr: 0.5336 loss_db: 0.1551 2022/11/02 15:49:20 - mmengine - INFO - Epoch(train) [342][35/63] lr: 1.6006e-03 eta: 8:48:10 time: 0.4761 data_time: 0.0047 memory: 14901 loss: 1.6014 loss_prob: 0.9045 loss_thr: 0.5446 loss_db: 0.1523 2022/11/02 15:49:23 - mmengine - INFO - Epoch(train) [342][40/63] lr: 1.6006e-03 eta: 8:48:02 time: 0.4726 data_time: 0.0046 memory: 14901 loss: 1.6261 loss_prob: 0.9032 loss_thr: 0.5710 loss_db: 0.1519 2022/11/02 15:49:25 - mmengine - INFO - Epoch(train) [342][45/63] lr: 1.6006e-03 eta: 8:48:02 time: 0.5077 data_time: 0.0047 memory: 14901 loss: 1.5665 loss_prob: 0.8747 loss_thr: 0.5473 loss_db: 0.1444 2022/11/02 15:49:28 - mmengine - INFO - Epoch(train) [342][50/63] lr: 1.6006e-03 eta: 8:47:55 time: 0.5454 data_time: 0.0314 memory: 14901 loss: 1.5777 loss_prob: 0.8795 loss_thr: 0.5523 loss_db: 0.1459 2022/11/02 15:49:31 - mmengine - INFO - Epoch(train) [342][55/63] lr: 1.6006e-03 eta: 8:47:55 time: 0.5730 data_time: 0.0355 memory: 14901 loss: 1.5869 loss_prob: 0.8831 loss_thr: 0.5502 loss_db: 0.1536 2022/11/02 15:49:34 - mmengine - INFO - Epoch(train) [342][60/63] lr: 1.6006e-03 eta: 8:47:50 time: 0.6400 data_time: 0.0153 memory: 14901 loss: 1.4546 loss_prob: 0.8001 loss_thr: 0.5186 loss_db: 0.1358 2022/11/02 15:49:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:49:41 - mmengine - INFO - Epoch(train) [343][5/63] lr: 1.5989e-03 eta: 8:47:50 time: 0.8429 data_time: 0.2604 memory: 14901 loss: 1.5497 loss_prob: 0.8613 loss_thr: 0.5460 loss_db: 0.1424 2022/11/02 15:49:45 - mmengine - INFO - Epoch(train) [343][10/63] lr: 1.5989e-03 eta: 8:47:48 time: 0.9525 data_time: 0.2647 memory: 14901 loss: 1.4800 loss_prob: 0.8160 loss_thr: 0.5227 loss_db: 0.1413 2022/11/02 15:49:49 - mmengine - INFO - Epoch(train) [343][15/63] lr: 1.5989e-03 eta: 8:47:48 time: 0.7535 data_time: 0.0119 memory: 14901 loss: 1.6497 loss_prob: 0.9386 loss_thr: 0.5574 loss_db: 0.1537 2022/11/02 15:49:52 - mmengine - INFO - Epoch(train) [343][20/63] lr: 1.5989e-03 eta: 8:47:43 time: 0.6339 data_time: 0.0111 memory: 14901 loss: 1.6126 loss_prob: 0.9166 loss_thr: 0.5510 loss_db: 0.1450 2022/11/02 15:49:55 - mmengine - INFO - Epoch(train) [343][25/63] lr: 1.5989e-03 eta: 8:47:43 time: 0.5609 data_time: 0.0339 memory: 14901 loss: 1.4944 loss_prob: 0.8176 loss_thr: 0.5391 loss_db: 0.1377 2022/11/02 15:49:58 - mmengine - INFO - Epoch(train) [343][30/63] lr: 1.5989e-03 eta: 8:47:37 time: 0.5877 data_time: 0.0457 memory: 14901 loss: 1.6252 loss_prob: 0.9091 loss_thr: 0.5607 loss_db: 0.1554 2022/11/02 15:50:00 - mmengine - INFO - Epoch(train) [343][35/63] lr: 1.5989e-03 eta: 8:47:37 time: 0.5846 data_time: 0.0266 memory: 14901 loss: 1.6127 loss_prob: 0.9022 loss_thr: 0.5601 loss_db: 0.1504 2022/11/02 15:50:03 - mmengine - INFO - Epoch(train) [343][40/63] lr: 1.5989e-03 eta: 8:47:31 time: 0.5739 data_time: 0.0146 memory: 14901 loss: 1.5245 loss_prob: 0.8416 loss_thr: 0.5459 loss_db: 0.1370 2022/11/02 15:50:07 - mmengine - INFO - Epoch(train) [343][45/63] lr: 1.5989e-03 eta: 8:47:31 time: 0.6293 data_time: 0.0126 memory: 14901 loss: 1.5636 loss_prob: 0.8745 loss_thr: 0.5457 loss_db: 0.1434 2022/11/02 15:50:10 - mmengine - INFO - Epoch(train) [343][50/63] lr: 1.5989e-03 eta: 8:47:26 time: 0.6332 data_time: 0.0241 memory: 14901 loss: 1.5541 loss_prob: 0.8713 loss_thr: 0.5385 loss_db: 0.1442 2022/11/02 15:50:12 - mmengine - INFO - Epoch(train) [343][55/63] lr: 1.5989e-03 eta: 8:47:26 time: 0.5665 data_time: 0.0265 memory: 14901 loss: 1.4788 loss_prob: 0.8250 loss_thr: 0.5184 loss_db: 0.1354 2022/11/02 15:50:15 - mmengine - INFO - Epoch(train) [343][60/63] lr: 1.5989e-03 eta: 8:47:19 time: 0.5263 data_time: 0.0155 memory: 14901 loss: 1.5122 loss_prob: 0.8398 loss_thr: 0.5349 loss_db: 0.1375 2022/11/02 15:50:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:50:24 - mmengine - INFO - Epoch(train) [344][5/63] lr: 1.5972e-03 eta: 8:47:19 time: 0.9612 data_time: 0.3156 memory: 14901 loss: 1.6108 loss_prob: 0.9086 loss_thr: 0.5536 loss_db: 0.1486 2022/11/02 15:50:26 - mmengine - INFO - Epoch(train) [344][10/63] lr: 1.5972e-03 eta: 8:47:17 time: 1.0066 data_time: 0.3112 memory: 14901 loss: 1.5007 loss_prob: 0.8299 loss_thr: 0.5357 loss_db: 0.1351 2022/11/02 15:50:30 - mmengine - INFO - Epoch(train) [344][15/63] lr: 1.5972e-03 eta: 8:47:17 time: 0.6638 data_time: 0.0127 memory: 14901 loss: 1.5722 loss_prob: 0.8650 loss_thr: 0.5644 loss_db: 0.1428 2022/11/02 15:50:33 - mmengine - INFO - Epoch(train) [344][20/63] lr: 1.5972e-03 eta: 8:47:13 time: 0.6402 data_time: 0.0117 memory: 14901 loss: 1.6101 loss_prob: 0.8937 loss_thr: 0.5624 loss_db: 0.1539 2022/11/02 15:50:35 - mmengine - INFO - Epoch(train) [344][25/63] lr: 1.5972e-03 eta: 8:47:13 time: 0.5241 data_time: 0.0204 memory: 14901 loss: 1.6788 loss_prob: 0.9735 loss_thr: 0.5453 loss_db: 0.1600 2022/11/02 15:50:38 - mmengine - INFO - Epoch(train) [344][30/63] lr: 1.5972e-03 eta: 8:47:05 time: 0.5118 data_time: 0.0288 memory: 14901 loss: 1.7329 loss_prob: 1.0196 loss_thr: 0.5522 loss_db: 0.1612 2022/11/02 15:50:40 - mmengine - INFO - Epoch(train) [344][35/63] lr: 1.5972e-03 eta: 8:47:05 time: 0.4960 data_time: 0.0150 memory: 14901 loss: 1.6001 loss_prob: 0.9162 loss_thr: 0.5346 loss_db: 0.1493 2022/11/02 15:50:43 - mmengine - INFO - Epoch(train) [344][40/63] lr: 1.5972e-03 eta: 8:46:58 time: 0.5212 data_time: 0.0065 memory: 14901 loss: 1.5587 loss_prob: 0.8666 loss_thr: 0.5449 loss_db: 0.1472 2022/11/02 15:50:46 - mmengine - INFO - Epoch(train) [344][45/63] lr: 1.5972e-03 eta: 8:46:58 time: 0.5264 data_time: 0.0059 memory: 14901 loss: 1.5908 loss_prob: 0.8732 loss_thr: 0.5700 loss_db: 0.1476 2022/11/02 15:50:48 - mmengine - INFO - Epoch(train) [344][50/63] lr: 1.5972e-03 eta: 8:46:50 time: 0.5315 data_time: 0.0170 memory: 14901 loss: 1.5673 loss_prob: 0.8605 loss_thr: 0.5642 loss_db: 0.1426 2022/11/02 15:50:51 - mmengine - INFO - Epoch(train) [344][55/63] lr: 1.5972e-03 eta: 8:46:50 time: 0.5659 data_time: 0.0261 memory: 14901 loss: 1.6144 loss_prob: 0.9026 loss_thr: 0.5604 loss_db: 0.1514 2022/11/02 15:50:54 - mmengine - INFO - Epoch(train) [344][60/63] lr: 1.5972e-03 eta: 8:46:44 time: 0.5664 data_time: 0.0162 memory: 14901 loss: 1.6891 loss_prob: 0.9546 loss_thr: 0.5739 loss_db: 0.1606 2022/11/02 15:50:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:51:01 - mmengine - INFO - Epoch(train) [345][5/63] lr: 1.5955e-03 eta: 8:46:44 time: 0.8137 data_time: 0.2109 memory: 14901 loss: 1.5028 loss_prob: 0.8398 loss_thr: 0.5245 loss_db: 0.1384 2022/11/02 15:51:04 - mmengine - INFO - Epoch(train) [345][10/63] lr: 1.5955e-03 eta: 8:46:38 time: 0.8114 data_time: 0.2214 memory: 14901 loss: 1.5487 loss_prob: 0.8674 loss_thr: 0.5380 loss_db: 0.1433 2022/11/02 15:51:07 - mmengine - INFO - Epoch(train) [345][15/63] lr: 1.5955e-03 eta: 8:46:38 time: 0.5738 data_time: 0.0288 memory: 14901 loss: 1.6079 loss_prob: 0.9132 loss_thr: 0.5425 loss_db: 0.1522 2022/11/02 15:51:09 - mmengine - INFO - Epoch(train) [345][20/63] lr: 1.5955e-03 eta: 8:46:31 time: 0.5563 data_time: 0.0172 memory: 14901 loss: 1.4707 loss_prob: 0.8251 loss_thr: 0.5088 loss_db: 0.1369 2022/11/02 15:51:13 - mmengine - INFO - Epoch(train) [345][25/63] lr: 1.5955e-03 eta: 8:46:31 time: 0.5941 data_time: 0.0161 memory: 14901 loss: 1.4507 loss_prob: 0.8081 loss_thr: 0.5103 loss_db: 0.1323 2022/11/02 15:51:15 - mmengine - INFO - Epoch(train) [345][30/63] lr: 1.5955e-03 eta: 8:46:26 time: 0.6135 data_time: 0.0377 memory: 14901 loss: 1.5262 loss_prob: 0.8396 loss_thr: 0.5473 loss_db: 0.1393 2022/11/02 15:51:19 - mmengine - INFO - Epoch(train) [345][35/63] lr: 1.5955e-03 eta: 8:46:26 time: 0.5787 data_time: 0.0309 memory: 14901 loss: 1.5456 loss_prob: 0.8369 loss_thr: 0.5673 loss_db: 0.1414 2022/11/02 15:51:22 - mmengine - INFO - Epoch(train) [345][40/63] lr: 1.5955e-03 eta: 8:46:21 time: 0.6151 data_time: 0.0142 memory: 14901 loss: 1.4748 loss_prob: 0.8066 loss_thr: 0.5306 loss_db: 0.1376 2022/11/02 15:51:24 - mmengine - INFO - Epoch(train) [345][45/63] lr: 1.5955e-03 eta: 8:46:21 time: 0.5496 data_time: 0.0152 memory: 14901 loss: 1.4978 loss_prob: 0.8301 loss_thr: 0.5302 loss_db: 0.1375 2022/11/02 15:51:27 - mmengine - INFO - Epoch(train) [345][50/63] lr: 1.5955e-03 eta: 8:46:13 time: 0.4899 data_time: 0.0152 memory: 14901 loss: 1.5717 loss_prob: 0.8718 loss_thr: 0.5572 loss_db: 0.1428 2022/11/02 15:51:29 - mmengine - INFO - Epoch(train) [345][55/63] lr: 1.5955e-03 eta: 8:46:13 time: 0.5233 data_time: 0.0250 memory: 14901 loss: 1.6007 loss_prob: 0.9028 loss_thr: 0.5469 loss_db: 0.1511 2022/11/02 15:51:32 - mmengine - INFO - Epoch(train) [345][60/63] lr: 1.5955e-03 eta: 8:46:05 time: 0.5296 data_time: 0.0203 memory: 14901 loss: 1.6696 loss_prob: 0.9605 loss_thr: 0.5524 loss_db: 0.1567 2022/11/02 15:51:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:51:39 - mmengine - INFO - Epoch(train) [346][5/63] lr: 1.5939e-03 eta: 8:46:05 time: 0.7939 data_time: 0.2313 memory: 14901 loss: 1.5763 loss_prob: 0.8823 loss_thr: 0.5474 loss_db: 0.1466 2022/11/02 15:51:42 - mmengine - INFO - Epoch(train) [346][10/63] lr: 1.5939e-03 eta: 8:46:01 time: 0.8803 data_time: 0.2342 memory: 14901 loss: 1.4388 loss_prob: 0.7787 loss_thr: 0.5261 loss_db: 0.1340 2022/11/02 15:51:45 - mmengine - INFO - Epoch(train) [346][15/63] lr: 1.5939e-03 eta: 8:46:01 time: 0.5833 data_time: 0.0103 memory: 14901 loss: 1.4308 loss_prob: 0.7741 loss_thr: 0.5265 loss_db: 0.1301 2022/11/02 15:51:47 - mmengine - INFO - Epoch(train) [346][20/63] lr: 1.5939e-03 eta: 8:45:53 time: 0.5369 data_time: 0.0082 memory: 14901 loss: 1.5164 loss_prob: 0.8309 loss_thr: 0.5489 loss_db: 0.1366 2022/11/02 15:51:51 - mmengine - INFO - Epoch(train) [346][25/63] lr: 1.5939e-03 eta: 8:45:53 time: 0.5850 data_time: 0.0350 memory: 14901 loss: 1.6228 loss_prob: 0.9117 loss_thr: 0.5631 loss_db: 0.1480 2022/11/02 15:51:53 - mmengine - INFO - Epoch(train) [346][30/63] lr: 1.5939e-03 eta: 8:45:48 time: 0.5930 data_time: 0.0424 memory: 14901 loss: 1.5501 loss_prob: 0.8749 loss_thr: 0.5309 loss_db: 0.1443 2022/11/02 15:51:57 - mmengine - INFO - Epoch(train) [346][35/63] lr: 1.5939e-03 eta: 8:45:48 time: 0.5910 data_time: 0.0144 memory: 14901 loss: 1.8122 loss_prob: 1.0834 loss_thr: 0.5601 loss_db: 0.1686 2022/11/02 15:52:00 - mmengine - INFO - Epoch(train) [346][40/63] lr: 1.5939e-03 eta: 8:45:44 time: 0.6502 data_time: 0.0102 memory: 14901 loss: 2.0430 loss_prob: 1.2608 loss_thr: 0.5865 loss_db: 0.1957 2022/11/02 15:52:02 - mmengine - INFO - Epoch(train) [346][45/63] lr: 1.5939e-03 eta: 8:45:44 time: 0.5898 data_time: 0.0125 memory: 14901 loss: 1.8124 loss_prob: 1.0799 loss_thr: 0.5605 loss_db: 0.1720 2022/11/02 15:52:06 - mmengine - INFO - Epoch(train) [346][50/63] lr: 1.5939e-03 eta: 8:45:37 time: 0.5777 data_time: 0.0213 memory: 14901 loss: 1.5861 loss_prob: 0.9008 loss_thr: 0.5424 loss_db: 0.1429 2022/11/02 15:52:09 - mmengine - INFO - Epoch(train) [346][55/63] lr: 1.5939e-03 eta: 8:45:37 time: 0.6152 data_time: 0.0269 memory: 14901 loss: 1.6080 loss_prob: 0.9228 loss_thr: 0.5321 loss_db: 0.1531 2022/11/02 15:52:11 - mmengine - INFO - Epoch(train) [346][60/63] lr: 1.5939e-03 eta: 8:45:30 time: 0.5352 data_time: 0.0132 memory: 14901 loss: 1.6368 loss_prob: 0.9526 loss_thr: 0.5248 loss_db: 0.1594 2022/11/02 15:52:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:52:17 - mmengine - INFO - Epoch(train) [347][5/63] lr: 1.5922e-03 eta: 8:45:30 time: 0.7227 data_time: 0.2187 memory: 14901 loss: 1.6309 loss_prob: 0.9447 loss_thr: 0.5302 loss_db: 0.1561 2022/11/02 15:52:20 - mmengine - INFO - Epoch(train) [347][10/63] lr: 1.5922e-03 eta: 8:45:22 time: 0.7462 data_time: 0.2192 memory: 14901 loss: 1.5148 loss_prob: 0.8389 loss_thr: 0.5323 loss_db: 0.1436 2022/11/02 15:52:23 - mmengine - INFO - Epoch(train) [347][15/63] lr: 1.5922e-03 eta: 8:45:22 time: 0.5416 data_time: 0.0175 memory: 14901 loss: 1.5507 loss_prob: 0.8464 loss_thr: 0.5578 loss_db: 0.1465 2022/11/02 15:52:26 - mmengine - INFO - Epoch(train) [347][20/63] lr: 1.5922e-03 eta: 8:45:17 time: 0.5952 data_time: 0.0234 memory: 14901 loss: 1.6993 loss_prob: 0.9579 loss_thr: 0.5812 loss_db: 0.1602 2022/11/02 15:52:28 - mmengine - INFO - Epoch(train) [347][25/63] lr: 1.5922e-03 eta: 8:45:17 time: 0.5767 data_time: 0.0323 memory: 14901 loss: 1.7229 loss_prob: 0.9675 loss_thr: 0.5989 loss_db: 0.1565 2022/11/02 15:52:31 - mmengine - INFO - Epoch(train) [347][30/63] lr: 1.5922e-03 eta: 8:45:10 time: 0.5715 data_time: 0.0364 memory: 14901 loss: 1.6128 loss_prob: 0.8881 loss_thr: 0.5773 loss_db: 0.1474 2022/11/02 15:52:34 - mmengine - INFO - Epoch(train) [347][35/63] lr: 1.5922e-03 eta: 8:45:10 time: 0.5820 data_time: 0.0243 memory: 14901 loss: 1.6878 loss_prob: 0.9640 loss_thr: 0.5617 loss_db: 0.1621 2022/11/02 15:52:37 - mmengine - INFO - Epoch(train) [347][40/63] lr: 1.5922e-03 eta: 8:45:04 time: 0.5618 data_time: 0.0161 memory: 14901 loss: 1.7268 loss_prob: 0.9974 loss_thr: 0.5628 loss_db: 0.1666 2022/11/02 15:52:41 - mmengine - INFO - Epoch(train) [347][45/63] lr: 1.5922e-03 eta: 8:45:04 time: 0.6255 data_time: 0.0083 memory: 14901 loss: 1.5688 loss_prob: 0.8782 loss_thr: 0.5438 loss_db: 0.1468 2022/11/02 15:52:44 - mmengine - INFO - Epoch(train) [347][50/63] lr: 1.5922e-03 eta: 8:45:00 time: 0.6747 data_time: 0.0232 memory: 14901 loss: 1.6434 loss_prob: 0.9301 loss_thr: 0.5566 loss_db: 0.1567 2022/11/02 15:52:46 - mmengine - INFO - Epoch(train) [347][55/63] lr: 1.5922e-03 eta: 8:45:00 time: 0.5913 data_time: 0.0248 memory: 14901 loss: 1.6643 loss_prob: 0.9487 loss_thr: 0.5539 loss_db: 0.1617 2022/11/02 15:52:49 - mmengine - INFO - Epoch(train) [347][60/63] lr: 1.5922e-03 eta: 8:44:53 time: 0.5302 data_time: 0.0112 memory: 14901 loss: 1.6167 loss_prob: 0.9167 loss_thr: 0.5459 loss_db: 0.1540 2022/11/02 15:52:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:52:55 - mmengine - INFO - Epoch(train) [348][5/63] lr: 1.5905e-03 eta: 8:44:53 time: 0.7228 data_time: 0.2430 memory: 14901 loss: 1.6294 loss_prob: 0.9072 loss_thr: 0.5736 loss_db: 0.1486 2022/11/02 15:52:58 - mmengine - INFO - Epoch(train) [348][10/63] lr: 1.5905e-03 eta: 8:44:45 time: 0.7392 data_time: 0.2405 memory: 14901 loss: 1.5371 loss_prob: 0.8465 loss_thr: 0.5506 loss_db: 0.1399 2022/11/02 15:53:00 - mmengine - INFO - Epoch(train) [348][15/63] lr: 1.5905e-03 eta: 8:44:45 time: 0.5225 data_time: 0.0067 memory: 14901 loss: 1.5775 loss_prob: 0.8926 loss_thr: 0.5302 loss_db: 0.1547 2022/11/02 15:53:03 - mmengine - INFO - Epoch(train) [348][20/63] lr: 1.5905e-03 eta: 8:44:37 time: 0.5090 data_time: 0.0062 memory: 14901 loss: 1.6539 loss_prob: 0.9374 loss_thr: 0.5565 loss_db: 0.1600 2022/11/02 15:53:05 - mmengine - INFO - Epoch(train) [348][25/63] lr: 1.5905e-03 eta: 8:44:37 time: 0.4944 data_time: 0.0187 memory: 14901 loss: 1.6571 loss_prob: 0.9275 loss_thr: 0.5775 loss_db: 0.1520 2022/11/02 15:53:08 - mmengine - INFO - Epoch(train) [348][30/63] lr: 1.5905e-03 eta: 8:44:30 time: 0.5276 data_time: 0.0433 memory: 14901 loss: 1.5935 loss_prob: 0.8919 loss_thr: 0.5542 loss_db: 0.1475 2022/11/02 15:53:11 - mmengine - INFO - Epoch(train) [348][35/63] lr: 1.5905e-03 eta: 8:44:30 time: 0.5330 data_time: 0.0356 memory: 14901 loss: 1.5502 loss_prob: 0.8600 loss_thr: 0.5461 loss_db: 0.1441 2022/11/02 15:53:13 - mmengine - INFO - Epoch(train) [348][40/63] lr: 1.5905e-03 eta: 8:44:23 time: 0.5436 data_time: 0.0097 memory: 14901 loss: 1.5863 loss_prob: 0.8761 loss_thr: 0.5642 loss_db: 0.1460 2022/11/02 15:53:16 - mmengine - INFO - Epoch(train) [348][45/63] lr: 1.5905e-03 eta: 8:44:23 time: 0.5103 data_time: 0.0064 memory: 14901 loss: 1.5328 loss_prob: 0.8602 loss_thr: 0.5286 loss_db: 0.1440 2022/11/02 15:53:18 - mmengine - INFO - Epoch(train) [348][50/63] lr: 1.5905e-03 eta: 8:44:15 time: 0.5086 data_time: 0.0235 memory: 14901 loss: 1.6093 loss_prob: 0.9299 loss_thr: 0.5255 loss_db: 0.1539 2022/11/02 15:53:22 - mmengine - INFO - Epoch(train) [348][55/63] lr: 1.5905e-03 eta: 8:44:15 time: 0.6419 data_time: 0.0234 memory: 14901 loss: 1.6970 loss_prob: 0.9885 loss_thr: 0.5444 loss_db: 0.1641 2022/11/02 15:53:25 - mmengine - INFO - Epoch(train) [348][60/63] lr: 1.5905e-03 eta: 8:44:11 time: 0.6438 data_time: 0.0111 memory: 14901 loss: 2.0257 loss_prob: 1.2170 loss_thr: 0.6036 loss_db: 0.2051 2022/11/02 15:53:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:53:32 - mmengine - INFO - Epoch(train) [349][5/63] lr: 1.5888e-03 eta: 8:44:11 time: 0.7766 data_time: 0.2222 memory: 14901 loss: 2.1128 loss_prob: 1.3121 loss_thr: 0.6068 loss_db: 0.1940 2022/11/02 15:53:34 - mmengine - INFO - Epoch(train) [349][10/63] lr: 1.5888e-03 eta: 8:44:04 time: 0.7854 data_time: 0.2268 memory: 14901 loss: 2.0901 loss_prob: 1.2899 loss_thr: 0.6074 loss_db: 0.1928 2022/11/02 15:53:37 - mmengine - INFO - Epoch(train) [349][15/63] lr: 1.5888e-03 eta: 8:44:04 time: 0.5192 data_time: 0.0140 memory: 14901 loss: 1.6889 loss_prob: 0.9545 loss_thr: 0.5765 loss_db: 0.1579 2022/11/02 15:53:40 - mmengine - INFO - Epoch(train) [349][20/63] lr: 1.5888e-03 eta: 8:43:58 time: 0.5989 data_time: 0.0089 memory: 14901 loss: 1.7416 loss_prob: 1.0052 loss_thr: 0.5764 loss_db: 0.1599 2022/11/02 15:53:43 - mmengine - INFO - Epoch(train) [349][25/63] lr: 1.5888e-03 eta: 8:43:58 time: 0.6207 data_time: 0.0326 memory: 14901 loss: 1.6916 loss_prob: 0.9747 loss_thr: 0.5595 loss_db: 0.1574 2022/11/02 15:53:46 - mmengine - INFO - Epoch(train) [349][30/63] lr: 1.5888e-03 eta: 8:43:51 time: 0.5340 data_time: 0.0370 memory: 14901 loss: 1.6575 loss_prob: 0.9447 loss_thr: 0.5573 loss_db: 0.1555 2022/11/02 15:53:48 - mmengine - INFO - Epoch(train) [349][35/63] lr: 1.5888e-03 eta: 8:43:51 time: 0.5044 data_time: 0.0134 memory: 14901 loss: 1.7092 loss_prob: 0.9855 loss_thr: 0.5639 loss_db: 0.1597 2022/11/02 15:53:51 - mmengine - INFO - Epoch(train) [349][40/63] lr: 1.5888e-03 eta: 8:43:44 time: 0.5479 data_time: 0.0108 memory: 14901 loss: 1.6993 loss_prob: 0.9715 loss_thr: 0.5660 loss_db: 0.1618 2022/11/02 15:53:54 - mmengine - INFO - Epoch(train) [349][45/63] lr: 1.5888e-03 eta: 8:43:44 time: 0.5625 data_time: 0.0074 memory: 14901 loss: 1.6932 loss_prob: 0.9507 loss_thr: 0.5803 loss_db: 0.1622 2022/11/02 15:53:56 - mmengine - INFO - Epoch(train) [349][50/63] lr: 1.5888e-03 eta: 8:43:37 time: 0.5126 data_time: 0.0263 memory: 14901 loss: 1.6640 loss_prob: 0.9287 loss_thr: 0.5754 loss_db: 0.1598 2022/11/02 15:53:59 - mmengine - INFO - Epoch(train) [349][55/63] lr: 1.5888e-03 eta: 8:43:37 time: 0.5284 data_time: 0.0316 memory: 14901 loss: 1.6777 loss_prob: 0.9367 loss_thr: 0.5809 loss_db: 0.1601 2022/11/02 15:54:02 - mmengine - INFO - Epoch(train) [349][60/63] lr: 1.5888e-03 eta: 8:43:29 time: 0.5293 data_time: 0.0104 memory: 14901 loss: 1.6937 loss_prob: 0.9450 loss_thr: 0.5889 loss_db: 0.1599 2022/11/02 15:54:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:54:09 - mmengine - INFO - Epoch(train) [350][5/63] lr: 1.5871e-03 eta: 8:43:29 time: 0.8782 data_time: 0.2654 memory: 14901 loss: 1.5524 loss_prob: 0.8624 loss_thr: 0.5438 loss_db: 0.1462 2022/11/02 15:54:13 - mmengine - INFO - Epoch(train) [350][10/63] lr: 1.5871e-03 eta: 8:43:26 time: 0.9413 data_time: 0.2685 memory: 14901 loss: 1.6050 loss_prob: 0.8946 loss_thr: 0.5608 loss_db: 0.1495 2022/11/02 15:54:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:54:15 - mmengine - INFO - Epoch(train) [350][15/63] lr: 1.5871e-03 eta: 8:43:26 time: 0.5677 data_time: 0.0169 memory: 14901 loss: 1.5158 loss_prob: 0.8295 loss_thr: 0.5464 loss_db: 0.1399 2022/11/02 15:54:18 - mmengine - INFO - Epoch(train) [350][20/63] lr: 1.5871e-03 eta: 8:43:19 time: 0.5117 data_time: 0.0113 memory: 14901 loss: 1.5488 loss_prob: 0.8493 loss_thr: 0.5558 loss_db: 0.1437 2022/11/02 15:54:20 - mmengine - INFO - Epoch(train) [350][25/63] lr: 1.5871e-03 eta: 8:43:19 time: 0.5028 data_time: 0.0083 memory: 14901 loss: 1.7126 loss_prob: 0.9657 loss_thr: 0.5884 loss_db: 0.1585 2022/11/02 15:54:23 - mmengine - INFO - Epoch(train) [350][30/63] lr: 1.5871e-03 eta: 8:43:11 time: 0.5217 data_time: 0.0348 memory: 14901 loss: 1.6646 loss_prob: 0.9381 loss_thr: 0.5714 loss_db: 0.1551 2022/11/02 15:54:25 - mmengine - INFO - Epoch(train) [350][35/63] lr: 1.5871e-03 eta: 8:43:11 time: 0.5413 data_time: 0.0353 memory: 14901 loss: 1.6535 loss_prob: 0.9312 loss_thr: 0.5666 loss_db: 0.1556 2022/11/02 15:54:28 - mmengine - INFO - Epoch(train) [350][40/63] lr: 1.5871e-03 eta: 8:43:04 time: 0.5203 data_time: 0.0119 memory: 14901 loss: 1.6631 loss_prob: 0.9370 loss_thr: 0.5710 loss_db: 0.1551 2022/11/02 15:54:31 - mmengine - INFO - Epoch(train) [350][45/63] lr: 1.5871e-03 eta: 8:43:04 time: 0.5330 data_time: 0.0162 memory: 14901 loss: 1.5857 loss_prob: 0.9043 loss_thr: 0.5368 loss_db: 0.1446 2022/11/02 15:54:34 - mmengine - INFO - Epoch(train) [350][50/63] lr: 1.5871e-03 eta: 8:42:58 time: 0.5890 data_time: 0.0280 memory: 14901 loss: 1.5412 loss_prob: 0.8719 loss_thr: 0.5291 loss_db: 0.1402 2022/11/02 15:54:36 - mmengine - INFO - Epoch(train) [350][55/63] lr: 1.5871e-03 eta: 8:42:58 time: 0.5687 data_time: 0.0294 memory: 14901 loss: 1.4817 loss_prob: 0.8085 loss_thr: 0.5351 loss_db: 0.1381 2022/11/02 15:54:39 - mmengine - INFO - Epoch(train) [350][60/63] lr: 1.5871e-03 eta: 8:42:51 time: 0.5339 data_time: 0.0159 memory: 14901 loss: 1.6066 loss_prob: 0.9122 loss_thr: 0.5501 loss_db: 0.1443 2022/11/02 15:54:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:54:46 - mmengine - INFO - Epoch(train) [351][5/63] lr: 1.5855e-03 eta: 8:42:51 time: 0.7287 data_time: 0.2488 memory: 14901 loss: 1.7339 loss_prob: 1.0095 loss_thr: 0.5627 loss_db: 0.1617 2022/11/02 15:54:48 - mmengine - INFO - Epoch(train) [351][10/63] lr: 1.5855e-03 eta: 8:42:43 time: 0.7424 data_time: 0.2512 memory: 14901 loss: 1.5969 loss_prob: 0.8835 loss_thr: 0.5636 loss_db: 0.1497 2022/11/02 15:54:50 - mmengine - INFO - Epoch(train) [351][15/63] lr: 1.5855e-03 eta: 8:42:43 time: 0.4825 data_time: 0.0130 memory: 14901 loss: 1.5120 loss_prob: 0.8215 loss_thr: 0.5528 loss_db: 0.1376 2022/11/02 15:54:53 - mmengine - INFO - Epoch(train) [351][20/63] lr: 1.5855e-03 eta: 8:42:35 time: 0.5134 data_time: 0.0170 memory: 14901 loss: 1.6243 loss_prob: 0.9070 loss_thr: 0.5671 loss_db: 0.1502 2022/11/02 15:54:56 - mmengine - INFO - Epoch(train) [351][25/63] lr: 1.5855e-03 eta: 8:42:35 time: 0.5276 data_time: 0.0428 memory: 14901 loss: 1.5653 loss_prob: 0.8722 loss_thr: 0.5479 loss_db: 0.1451 2022/11/02 15:54:58 - mmengine - INFO - Epoch(train) [351][30/63] lr: 1.5855e-03 eta: 8:42:28 time: 0.5177 data_time: 0.0353 memory: 14901 loss: 1.3584 loss_prob: 0.7241 loss_thr: 0.5113 loss_db: 0.1231 2022/11/02 15:55:01 - mmengine - INFO - Epoch(train) [351][35/63] lr: 1.5855e-03 eta: 8:42:28 time: 0.4939 data_time: 0.0068 memory: 14901 loss: 1.5171 loss_prob: 0.8321 loss_thr: 0.5433 loss_db: 0.1416 2022/11/02 15:55:03 - mmengine - INFO - Epoch(train) [351][40/63] lr: 1.5855e-03 eta: 8:42:20 time: 0.4950 data_time: 0.0112 memory: 14901 loss: 1.5260 loss_prob: 0.8479 loss_thr: 0.5368 loss_db: 0.1413 2022/11/02 15:55:06 - mmengine - INFO - Epoch(train) [351][45/63] lr: 1.5855e-03 eta: 8:42:20 time: 0.5166 data_time: 0.0190 memory: 14901 loss: 1.4011 loss_prob: 0.7667 loss_thr: 0.5067 loss_db: 0.1276 2022/11/02 15:55:08 - mmengine - INFO - Epoch(train) [351][50/63] lr: 1.5855e-03 eta: 8:42:12 time: 0.5127 data_time: 0.0324 memory: 14901 loss: 1.5489 loss_prob: 0.8536 loss_thr: 0.5536 loss_db: 0.1417 2022/11/02 15:55:11 - mmengine - INFO - Epoch(train) [351][55/63] lr: 1.5855e-03 eta: 8:42:12 time: 0.5142 data_time: 0.0249 memory: 14901 loss: 1.6592 loss_prob: 0.9337 loss_thr: 0.5726 loss_db: 0.1529 2022/11/02 15:55:13 - mmengine - INFO - Epoch(train) [351][60/63] lr: 1.5855e-03 eta: 8:42:04 time: 0.5004 data_time: 0.0089 memory: 14901 loss: 1.5472 loss_prob: 0.8704 loss_thr: 0.5330 loss_db: 0.1438 2022/11/02 15:55:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:55:21 - mmengine - INFO - Epoch(train) [352][5/63] lr: 1.5838e-03 eta: 8:42:04 time: 0.8430 data_time: 0.2550 memory: 14901 loss: 1.5543 loss_prob: 0.8550 loss_thr: 0.5553 loss_db: 0.1439 2022/11/02 15:55:24 - mmengine - INFO - Epoch(train) [352][10/63] lr: 1.5838e-03 eta: 8:42:01 time: 0.9430 data_time: 0.2875 memory: 14901 loss: 1.5316 loss_prob: 0.8397 loss_thr: 0.5472 loss_db: 0.1447 2022/11/02 15:55:27 - mmengine - INFO - Epoch(train) [352][15/63] lr: 1.5838e-03 eta: 8:42:01 time: 0.6275 data_time: 0.0420 memory: 14901 loss: 1.5742 loss_prob: 0.8840 loss_thr: 0.5471 loss_db: 0.1432 2022/11/02 15:55:30 - mmengine - INFO - Epoch(train) [352][20/63] lr: 1.5838e-03 eta: 8:41:54 time: 0.5472 data_time: 0.0093 memory: 14901 loss: 1.5667 loss_prob: 0.8980 loss_thr: 0.5237 loss_db: 0.1449 2022/11/02 15:55:32 - mmengine - INFO - Epoch(train) [352][25/63] lr: 1.5838e-03 eta: 8:41:54 time: 0.5294 data_time: 0.0088 memory: 14901 loss: 1.4980 loss_prob: 0.8431 loss_thr: 0.5126 loss_db: 0.1423 2022/11/02 15:55:35 - mmengine - INFO - Epoch(train) [352][30/63] lr: 1.5838e-03 eta: 8:41:47 time: 0.5597 data_time: 0.0238 memory: 14901 loss: 1.4936 loss_prob: 0.8226 loss_thr: 0.5351 loss_db: 0.1359 2022/11/02 15:55:38 - mmengine - INFO - Epoch(train) [352][35/63] lr: 1.5838e-03 eta: 8:41:47 time: 0.5717 data_time: 0.0341 memory: 14901 loss: 1.5275 loss_prob: 0.8370 loss_thr: 0.5509 loss_db: 0.1397 2022/11/02 15:55:41 - mmengine - INFO - Epoch(train) [352][40/63] lr: 1.5838e-03 eta: 8:41:41 time: 0.5508 data_time: 0.0189 memory: 14901 loss: 1.5329 loss_prob: 0.8444 loss_thr: 0.5444 loss_db: 0.1441 2022/11/02 15:55:44 - mmengine - INFO - Epoch(train) [352][45/63] lr: 1.5838e-03 eta: 8:41:41 time: 0.5367 data_time: 0.0113 memory: 14901 loss: 1.5491 loss_prob: 0.8649 loss_thr: 0.5393 loss_db: 0.1449 2022/11/02 15:55:46 - mmengine - INFO - Epoch(train) [352][50/63] lr: 1.5838e-03 eta: 8:41:34 time: 0.5294 data_time: 0.0134 memory: 14901 loss: 1.5800 loss_prob: 0.8783 loss_thr: 0.5564 loss_db: 0.1452 2022/11/02 15:55:49 - mmengine - INFO - Epoch(train) [352][55/63] lr: 1.5838e-03 eta: 8:41:34 time: 0.5498 data_time: 0.0218 memory: 14901 loss: 1.5938 loss_prob: 0.8731 loss_thr: 0.5742 loss_db: 0.1465 2022/11/02 15:55:52 - mmengine - INFO - Epoch(train) [352][60/63] lr: 1.5838e-03 eta: 8:41:27 time: 0.5556 data_time: 0.0252 memory: 14901 loss: 1.5477 loss_prob: 0.8443 loss_thr: 0.5595 loss_db: 0.1439 2022/11/02 15:55:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:55:58 - mmengine - INFO - Epoch(train) [353][5/63] lr: 1.5821e-03 eta: 8:41:27 time: 0.7502 data_time: 0.2462 memory: 14901 loss: 1.6676 loss_prob: 0.9470 loss_thr: 0.5669 loss_db: 0.1536 2022/11/02 15:56:02 - mmengine - INFO - Epoch(train) [353][10/63] lr: 1.5821e-03 eta: 8:41:23 time: 0.9192 data_time: 0.2479 memory: 14901 loss: 1.6036 loss_prob: 0.9021 loss_thr: 0.5544 loss_db: 0.1471 2022/11/02 15:56:06 - mmengine - INFO - Epoch(train) [353][15/63] lr: 1.5821e-03 eta: 8:41:23 time: 0.7334 data_time: 0.0088 memory: 14901 loss: 1.5317 loss_prob: 0.8380 loss_thr: 0.5527 loss_db: 0.1411 2022/11/02 15:56:08 - mmengine - INFO - Epoch(train) [353][20/63] lr: 1.5821e-03 eta: 8:41:17 time: 0.5874 data_time: 0.0079 memory: 14901 loss: 1.4520 loss_prob: 0.7976 loss_thr: 0.5211 loss_db: 0.1333 2022/11/02 15:56:11 - mmengine - INFO - Epoch(train) [353][25/63] lr: 1.5821e-03 eta: 8:41:17 time: 0.5316 data_time: 0.0332 memory: 14901 loss: 1.7809 loss_prob: 1.0759 loss_thr: 0.5436 loss_db: 0.1614 2022/11/02 15:56:14 - mmengine - INFO - Epoch(train) [353][30/63] lr: 1.5821e-03 eta: 8:41:11 time: 0.5731 data_time: 0.0537 memory: 14901 loss: 1.8850 loss_prob: 1.1316 loss_thr: 0.5821 loss_db: 0.1713 2022/11/02 15:56:17 - mmengine - INFO - Epoch(train) [353][35/63] lr: 1.5821e-03 eta: 8:41:11 time: 0.5818 data_time: 0.0287 memory: 14901 loss: 1.5567 loss_prob: 0.8525 loss_thr: 0.5616 loss_db: 0.1426 2022/11/02 15:56:20 - mmengine - INFO - Epoch(train) [353][40/63] lr: 1.5821e-03 eta: 8:41:05 time: 0.5792 data_time: 0.0093 memory: 14901 loss: 1.7068 loss_prob: 0.9612 loss_thr: 0.5860 loss_db: 0.1596 2022/11/02 15:56:22 - mmengine - INFO - Epoch(train) [353][45/63] lr: 1.5821e-03 eta: 8:41:05 time: 0.5250 data_time: 0.0106 memory: 14901 loss: 1.5716 loss_prob: 0.8817 loss_thr: 0.5426 loss_db: 0.1473 2022/11/02 15:56:25 - mmengine - INFO - Epoch(train) [353][50/63] lr: 1.5821e-03 eta: 8:40:58 time: 0.5278 data_time: 0.0245 memory: 14901 loss: 1.3911 loss_prob: 0.7557 loss_thr: 0.5073 loss_db: 0.1280 2022/11/02 15:56:28 - mmengine - INFO - Epoch(train) [353][55/63] lr: 1.5821e-03 eta: 8:40:58 time: 0.6217 data_time: 0.0281 memory: 14901 loss: 1.4621 loss_prob: 0.7973 loss_thr: 0.5306 loss_db: 0.1342 2022/11/02 15:56:31 - mmengine - INFO - Epoch(train) [353][60/63] lr: 1.5821e-03 eta: 8:40:52 time: 0.5892 data_time: 0.0125 memory: 14901 loss: 1.4927 loss_prob: 0.8116 loss_thr: 0.5430 loss_db: 0.1381 2022/11/02 15:56:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:56:37 - mmengine - INFO - Epoch(train) [354][5/63] lr: 1.5804e-03 eta: 8:40:52 time: 0.7462 data_time: 0.2276 memory: 14901 loss: 1.5120 loss_prob: 0.8569 loss_thr: 0.5110 loss_db: 0.1441 2022/11/02 15:56:40 - mmengine - INFO - Epoch(train) [354][10/63] lr: 1.5804e-03 eta: 8:40:46 time: 0.8087 data_time: 0.2296 memory: 14901 loss: 1.5263 loss_prob: 0.8592 loss_thr: 0.5281 loss_db: 0.1390 2022/11/02 15:56:42 - mmengine - INFO - Epoch(train) [354][15/63] lr: 1.5804e-03 eta: 8:40:46 time: 0.5094 data_time: 0.0092 memory: 14901 loss: 1.4593 loss_prob: 0.7992 loss_thr: 0.5292 loss_db: 0.1309 2022/11/02 15:56:46 - mmengine - INFO - Epoch(train) [354][20/63] lr: 1.5804e-03 eta: 8:40:40 time: 0.5804 data_time: 0.0089 memory: 14901 loss: 1.6052 loss_prob: 0.8895 loss_thr: 0.5677 loss_db: 0.1481 2022/11/02 15:56:49 - mmengine - INFO - Epoch(train) [354][25/63] lr: 1.5804e-03 eta: 8:40:40 time: 0.6219 data_time: 0.0373 memory: 14901 loss: 1.5953 loss_prob: 0.8759 loss_thr: 0.5746 loss_db: 0.1448 2022/11/02 15:56:51 - mmengine - INFO - Epoch(train) [354][30/63] lr: 1.5804e-03 eta: 8:40:33 time: 0.5481 data_time: 0.0412 memory: 14901 loss: 1.4339 loss_prob: 0.7746 loss_thr: 0.5290 loss_db: 0.1302 2022/11/02 15:56:54 - mmengine - INFO - Epoch(train) [354][35/63] lr: 1.5804e-03 eta: 8:40:33 time: 0.5253 data_time: 0.0111 memory: 14901 loss: 1.5725 loss_prob: 0.8899 loss_thr: 0.5325 loss_db: 0.1501 2022/11/02 15:56:56 - mmengine - INFO - Epoch(train) [354][40/63] lr: 1.5804e-03 eta: 8:40:25 time: 0.5094 data_time: 0.0079 memory: 14901 loss: 1.6969 loss_prob: 0.9876 loss_thr: 0.5510 loss_db: 0.1583 2022/11/02 15:56:59 - mmengine - INFO - Epoch(train) [354][45/63] lr: 1.5804e-03 eta: 8:40:25 time: 0.5289 data_time: 0.0119 memory: 14901 loss: 1.5949 loss_prob: 0.9024 loss_thr: 0.5485 loss_db: 0.1440 2022/11/02 15:57:02 - mmengine - INFO - Epoch(train) [354][50/63] lr: 1.5804e-03 eta: 8:40:18 time: 0.5314 data_time: 0.0275 memory: 14901 loss: 1.6411 loss_prob: 0.9398 loss_thr: 0.5498 loss_db: 0.1515 2022/11/02 15:57:04 - mmengine - INFO - Epoch(train) [354][55/63] lr: 1.5804e-03 eta: 8:40:18 time: 0.4959 data_time: 0.0249 memory: 14901 loss: 1.7567 loss_prob: 1.0289 loss_thr: 0.5654 loss_db: 0.1624 2022/11/02 15:57:07 - mmengine - INFO - Epoch(train) [354][60/63] lr: 1.5804e-03 eta: 8:40:12 time: 0.5740 data_time: 0.0066 memory: 14901 loss: 1.6976 loss_prob: 0.9686 loss_thr: 0.5713 loss_db: 0.1577 2022/11/02 15:57:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:57:15 - mmengine - INFO - Epoch(train) [355][5/63] lr: 1.5787e-03 eta: 8:40:12 time: 0.8295 data_time: 0.2249 memory: 14901 loss: 1.6996 loss_prob: 0.9678 loss_thr: 0.5716 loss_db: 0.1601 2022/11/02 15:57:18 - mmengine - INFO - Epoch(train) [355][10/63] lr: 1.5787e-03 eta: 8:40:08 time: 0.9114 data_time: 0.2303 memory: 14901 loss: 1.5152 loss_prob: 0.8355 loss_thr: 0.5390 loss_db: 0.1407 2022/11/02 15:57:21 - mmengine - INFO - Epoch(train) [355][15/63] lr: 1.5787e-03 eta: 8:40:08 time: 0.6000 data_time: 0.0114 memory: 14901 loss: 1.5124 loss_prob: 0.8430 loss_thr: 0.5301 loss_db: 0.1393 2022/11/02 15:57:23 - mmengine - INFO - Epoch(train) [355][20/63] lr: 1.5787e-03 eta: 8:40:01 time: 0.5559 data_time: 0.0100 memory: 14901 loss: 1.6183 loss_prob: 0.9098 loss_thr: 0.5597 loss_db: 0.1488 2022/11/02 15:57:26 - mmengine - INFO - Epoch(train) [355][25/63] lr: 1.5787e-03 eta: 8:40:01 time: 0.5048 data_time: 0.0206 memory: 14901 loss: 1.6398 loss_prob: 0.9207 loss_thr: 0.5658 loss_db: 0.1533 2022/11/02 15:57:29 - mmengine - INFO - Epoch(train) [355][30/63] lr: 1.5787e-03 eta: 8:39:55 time: 0.5541 data_time: 0.0580 memory: 14901 loss: 1.5748 loss_prob: 0.8745 loss_thr: 0.5548 loss_db: 0.1455 2022/11/02 15:57:31 - mmengine - INFO - Epoch(train) [355][35/63] lr: 1.5787e-03 eta: 8:39:55 time: 0.5387 data_time: 0.0492 memory: 14901 loss: 1.4748 loss_prob: 0.7998 loss_thr: 0.5413 loss_db: 0.1337 2022/11/02 15:57:34 - mmengine - INFO - Epoch(train) [355][40/63] lr: 1.5787e-03 eta: 8:39:46 time: 0.4818 data_time: 0.0074 memory: 14901 loss: 1.4576 loss_prob: 0.7907 loss_thr: 0.5341 loss_db: 0.1328 2022/11/02 15:57:36 - mmengine - INFO - Epoch(train) [355][45/63] lr: 1.5787e-03 eta: 8:39:46 time: 0.4949 data_time: 0.0046 memory: 14901 loss: 1.4970 loss_prob: 0.8183 loss_thr: 0.5439 loss_db: 0.1348 2022/11/02 15:57:39 - mmengine - INFO - Epoch(train) [355][50/63] lr: 1.5787e-03 eta: 8:39:39 time: 0.5127 data_time: 0.0222 memory: 14901 loss: 1.5133 loss_prob: 0.8219 loss_thr: 0.5562 loss_db: 0.1352 2022/11/02 15:57:41 - mmengine - INFO - Epoch(train) [355][55/63] lr: 1.5787e-03 eta: 8:39:39 time: 0.5032 data_time: 0.0253 memory: 14901 loss: 1.4890 loss_prob: 0.8160 loss_thr: 0.5383 loss_db: 0.1346 2022/11/02 15:57:44 - mmengine - INFO - Epoch(train) [355][60/63] lr: 1.5787e-03 eta: 8:39:31 time: 0.4907 data_time: 0.0077 memory: 14901 loss: 1.5278 loss_prob: 0.8494 loss_thr: 0.5393 loss_db: 0.1391 2022/11/02 15:57:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:57:51 - mmengine - INFO - Epoch(train) [356][5/63] lr: 1.5771e-03 eta: 8:39:31 time: 0.7892 data_time: 0.2569 memory: 14901 loss: 1.6703 loss_prob: 0.9410 loss_thr: 0.5710 loss_db: 0.1583 2022/11/02 15:57:53 - mmengine - INFO - Epoch(train) [356][10/63] lr: 1.5771e-03 eta: 8:39:25 time: 0.8383 data_time: 0.2567 memory: 14901 loss: 1.8748 loss_prob: 1.1312 loss_thr: 0.5623 loss_db: 0.1814 2022/11/02 15:57:57 - mmengine - INFO - Epoch(train) [356][15/63] lr: 1.5771e-03 eta: 8:39:25 time: 0.5806 data_time: 0.0092 memory: 14901 loss: 1.8204 loss_prob: 1.1064 loss_thr: 0.5442 loss_db: 0.1699 2022/11/02 15:57:59 - mmengine - INFO - Epoch(train) [356][20/63] lr: 1.5771e-03 eta: 8:39:19 time: 0.5748 data_time: 0.0106 memory: 14901 loss: 1.6869 loss_prob: 0.9788 loss_thr: 0.5496 loss_db: 0.1585 2022/11/02 15:58:02 - mmengine - INFO - Epoch(train) [356][25/63] lr: 1.5771e-03 eta: 8:39:19 time: 0.5273 data_time: 0.0317 memory: 14901 loss: 1.7149 loss_prob: 0.9854 loss_thr: 0.5612 loss_db: 0.1683 2022/11/02 15:58:04 - mmengine - INFO - Epoch(train) [356][30/63] lr: 1.5771e-03 eta: 8:39:12 time: 0.5229 data_time: 0.0375 memory: 14901 loss: 1.8403 loss_prob: 1.0787 loss_thr: 0.5852 loss_db: 0.1765 2022/11/02 15:58:07 - mmengine - INFO - Epoch(train) [356][35/63] lr: 1.5771e-03 eta: 8:39:12 time: 0.5607 data_time: 0.0139 memory: 14901 loss: 1.8372 loss_prob: 1.0750 loss_thr: 0.5851 loss_db: 0.1771 2022/11/02 15:58:10 - mmengine - INFO - Epoch(train) [356][40/63] lr: 1.5771e-03 eta: 8:39:05 time: 0.5748 data_time: 0.0079 memory: 14901 loss: 1.6350 loss_prob: 0.9305 loss_thr: 0.5482 loss_db: 0.1563 2022/11/02 15:58:13 - mmengine - INFO - Epoch(train) [356][45/63] lr: 1.5771e-03 eta: 8:39:05 time: 0.5615 data_time: 0.0104 memory: 14901 loss: 1.5576 loss_prob: 0.8787 loss_thr: 0.5377 loss_db: 0.1412 2022/11/02 15:58:16 - mmengine - INFO - Epoch(train) [356][50/63] lr: 1.5771e-03 eta: 8:38:58 time: 0.5369 data_time: 0.0296 memory: 14901 loss: 1.6422 loss_prob: 0.9242 loss_thr: 0.5685 loss_db: 0.1495 2022/11/02 15:58:18 - mmengine - INFO - Epoch(train) [356][55/63] lr: 1.5771e-03 eta: 8:38:58 time: 0.5051 data_time: 0.0282 memory: 14901 loss: 1.7362 loss_prob: 0.9925 loss_thr: 0.5772 loss_db: 0.1666 2022/11/02 15:58:21 - mmengine - INFO - Epoch(train) [356][60/63] lr: 1.5771e-03 eta: 8:38:51 time: 0.5412 data_time: 0.0109 memory: 14901 loss: 1.6388 loss_prob: 0.9341 loss_thr: 0.5461 loss_db: 0.1587 2022/11/02 15:58:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:58:28 - mmengine - INFO - Epoch(train) [357][5/63] lr: 1.5754e-03 eta: 8:38:51 time: 0.8012 data_time: 0.2644 memory: 14901 loss: 1.4703 loss_prob: 0.8021 loss_thr: 0.5323 loss_db: 0.1359 2022/11/02 15:58:31 - mmengine - INFO - Epoch(train) [357][10/63] lr: 1.5754e-03 eta: 8:38:45 time: 0.8210 data_time: 0.2596 memory: 14901 loss: 1.5155 loss_prob: 0.8494 loss_thr: 0.5234 loss_db: 0.1427 2022/11/02 15:58:34 - mmengine - INFO - Epoch(train) [357][15/63] lr: 1.5754e-03 eta: 8:38:45 time: 0.5713 data_time: 0.0083 memory: 14901 loss: 1.5853 loss_prob: 0.8981 loss_thr: 0.5388 loss_db: 0.1484 2022/11/02 15:58:36 - mmengine - INFO - Epoch(train) [357][20/63] lr: 1.5754e-03 eta: 8:38:38 time: 0.5330 data_time: 0.0085 memory: 14901 loss: 1.6902 loss_prob: 0.9719 loss_thr: 0.5615 loss_db: 0.1568 2022/11/02 15:58:39 - mmengine - INFO - Epoch(train) [357][25/63] lr: 1.5754e-03 eta: 8:38:38 time: 0.5436 data_time: 0.0329 memory: 14901 loss: 1.6414 loss_prob: 0.9338 loss_thr: 0.5578 loss_db: 0.1498 2022/11/02 15:58:42 - mmengine - INFO - Epoch(train) [357][30/63] lr: 1.5754e-03 eta: 8:38:32 time: 0.5786 data_time: 0.0504 memory: 14901 loss: 1.5434 loss_prob: 0.8641 loss_thr: 0.5333 loss_db: 0.1460 2022/11/02 15:58:44 - mmengine - INFO - Epoch(train) [357][35/63] lr: 1.5754e-03 eta: 8:38:32 time: 0.5125 data_time: 0.0233 memory: 14901 loss: 1.4809 loss_prob: 0.8344 loss_thr: 0.5059 loss_db: 0.1406 2022/11/02 15:58:47 - mmengine - INFO - Epoch(train) [357][40/63] lr: 1.5754e-03 eta: 8:38:24 time: 0.5074 data_time: 0.0058 memory: 14901 loss: 1.5435 loss_prob: 0.8654 loss_thr: 0.5334 loss_db: 0.1447 2022/11/02 15:58:50 - mmengine - INFO - Epoch(train) [357][45/63] lr: 1.5754e-03 eta: 8:38:24 time: 0.5346 data_time: 0.0115 memory: 14901 loss: 1.6610 loss_prob: 0.9292 loss_thr: 0.5749 loss_db: 0.1569 2022/11/02 15:58:53 - mmengine - INFO - Epoch(train) [357][50/63] lr: 1.5754e-03 eta: 8:38:19 time: 0.5924 data_time: 0.0279 memory: 14901 loss: 1.6199 loss_prob: 0.9056 loss_thr: 0.5593 loss_db: 0.1550 2022/11/02 15:58:55 - mmengine - INFO - Epoch(train) [357][55/63] lr: 1.5754e-03 eta: 8:38:19 time: 0.5814 data_time: 0.0278 memory: 14901 loss: 1.6050 loss_prob: 0.9080 loss_thr: 0.5419 loss_db: 0.1551 2022/11/02 15:58:59 - mmengine - INFO - Epoch(train) [357][60/63] lr: 1.5754e-03 eta: 8:38:13 time: 0.5962 data_time: 0.0161 memory: 14901 loss: 1.6331 loss_prob: 0.9457 loss_thr: 0.5365 loss_db: 0.1508 2022/11/02 15:59:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:59:05 - mmengine - INFO - Epoch(train) [358][5/63] lr: 1.5737e-03 eta: 8:38:13 time: 0.8465 data_time: 0.2275 memory: 14901 loss: 1.6557 loss_prob: 0.9473 loss_thr: 0.5558 loss_db: 0.1526 2022/11/02 15:59:08 - mmengine - INFO - Epoch(train) [358][10/63] lr: 1.5737e-03 eta: 8:38:06 time: 0.7943 data_time: 0.2309 memory: 14901 loss: 1.4930 loss_prob: 0.8205 loss_thr: 0.5347 loss_db: 0.1378 2022/11/02 15:59:11 - mmengine - INFO - Epoch(train) [358][15/63] lr: 1.5737e-03 eta: 8:38:06 time: 0.5301 data_time: 0.0089 memory: 14901 loss: 1.5173 loss_prob: 0.8479 loss_thr: 0.5276 loss_db: 0.1418 2022/11/02 15:59:13 - mmengine - INFO - Epoch(train) [358][20/63] lr: 1.5737e-03 eta: 8:37:59 time: 0.5339 data_time: 0.0098 memory: 14901 loss: 1.5163 loss_prob: 0.8449 loss_thr: 0.5294 loss_db: 0.1420 2022/11/02 15:59:16 - mmengine - INFO - Epoch(train) [358][25/63] lr: 1.5737e-03 eta: 8:37:59 time: 0.5215 data_time: 0.0141 memory: 14901 loss: 1.6624 loss_prob: 0.9573 loss_thr: 0.5474 loss_db: 0.1578 2022/11/02 15:59:19 - mmengine - INFO - Epoch(train) [358][30/63] lr: 1.5737e-03 eta: 8:37:53 time: 0.5456 data_time: 0.0500 memory: 14901 loss: 1.7306 loss_prob: 1.0005 loss_thr: 0.5686 loss_db: 0.1616 2022/11/02 15:59:22 - mmengine - INFO - Epoch(train) [358][35/63] lr: 1.5737e-03 eta: 8:37:53 time: 0.5695 data_time: 0.0515 memory: 14901 loss: 1.6588 loss_prob: 0.9403 loss_thr: 0.5634 loss_db: 0.1551 2022/11/02 15:59:24 - mmengine - INFO - Epoch(train) [358][40/63] lr: 1.5737e-03 eta: 8:37:46 time: 0.5457 data_time: 0.0113 memory: 14901 loss: 1.6391 loss_prob: 0.9246 loss_thr: 0.5629 loss_db: 0.1516 2022/11/02 15:59:27 - mmengine - INFO - Epoch(train) [358][45/63] lr: 1.5737e-03 eta: 8:37:46 time: 0.5438 data_time: 0.0103 memory: 14901 loss: 1.5960 loss_prob: 0.8789 loss_thr: 0.5739 loss_db: 0.1431 2022/11/02 15:59:30 - mmengine - INFO - Epoch(train) [358][50/63] lr: 1.5737e-03 eta: 8:37:40 time: 0.5770 data_time: 0.0256 memory: 14901 loss: 1.5357 loss_prob: 0.8307 loss_thr: 0.5668 loss_db: 0.1381 2022/11/02 15:59:33 - mmengine - INFO - Epoch(train) [358][55/63] lr: 1.5737e-03 eta: 8:37:40 time: 0.5761 data_time: 0.0335 memory: 14901 loss: 1.6567 loss_prob: 0.9213 loss_thr: 0.5819 loss_db: 0.1534 2022/11/02 15:59:36 - mmengine - INFO - Epoch(train) [358][60/63] lr: 1.5737e-03 eta: 8:37:34 time: 0.5968 data_time: 0.0193 memory: 14901 loss: 1.7089 loss_prob: 0.9797 loss_thr: 0.5675 loss_db: 0.1617 2022/11/02 15:59:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 15:59:43 - mmengine - INFO - Epoch(train) [359][5/63] lr: 1.5720e-03 eta: 8:37:34 time: 0.8118 data_time: 0.2406 memory: 14901 loss: 1.5206 loss_prob: 0.8565 loss_thr: 0.5226 loss_db: 0.1415 2022/11/02 15:59:46 - mmengine - INFO - Epoch(train) [359][10/63] lr: 1.5720e-03 eta: 8:37:30 time: 0.9127 data_time: 0.2410 memory: 14901 loss: 1.4952 loss_prob: 0.8289 loss_thr: 0.5265 loss_db: 0.1398 2022/11/02 15:59:49 - mmengine - INFO - Epoch(train) [359][15/63] lr: 1.5720e-03 eta: 8:37:30 time: 0.5705 data_time: 0.0167 memory: 14901 loss: 1.5749 loss_prob: 0.8853 loss_thr: 0.5410 loss_db: 0.1486 2022/11/02 15:59:51 - mmengine - INFO - Epoch(train) [359][20/63] lr: 1.5720e-03 eta: 8:37:23 time: 0.5204 data_time: 0.0173 memory: 14901 loss: 1.6653 loss_prob: 0.9427 loss_thr: 0.5633 loss_db: 0.1592 2022/11/02 15:59:55 - mmengine - INFO - Epoch(train) [359][25/63] lr: 1.5720e-03 eta: 8:37:23 time: 0.5827 data_time: 0.0379 memory: 14901 loss: 1.6508 loss_prob: 0.9313 loss_thr: 0.5645 loss_db: 0.1551 2022/11/02 15:59:57 - mmengine - INFO - Epoch(train) [359][30/63] lr: 1.5720e-03 eta: 8:37:16 time: 0.5709 data_time: 0.0410 memory: 14901 loss: 1.6106 loss_prob: 0.9215 loss_thr: 0.5368 loss_db: 0.1523 2022/11/02 16:00:00 - mmengine - INFO - Epoch(train) [359][35/63] lr: 1.5720e-03 eta: 8:37:16 time: 0.5050 data_time: 0.0155 memory: 14901 loss: 1.7582 loss_prob: 1.0260 loss_thr: 0.5628 loss_db: 0.1695 2022/11/02 16:00:03 - mmengine - INFO - Epoch(train) [359][40/63] lr: 1.5720e-03 eta: 8:37:10 time: 0.5405 data_time: 0.0149 memory: 14901 loss: 1.7089 loss_prob: 0.9714 loss_thr: 0.5717 loss_db: 0.1658 2022/11/02 16:00:05 - mmengine - INFO - Epoch(train) [359][45/63] lr: 1.5720e-03 eta: 8:37:10 time: 0.5543 data_time: 0.0112 memory: 14901 loss: 1.5302 loss_prob: 0.8343 loss_thr: 0.5528 loss_db: 0.1431 2022/11/02 16:00:08 - mmengine - INFO - Epoch(train) [359][50/63] lr: 1.5720e-03 eta: 8:37:03 time: 0.5602 data_time: 0.0281 memory: 14901 loss: 1.5930 loss_prob: 0.8862 loss_thr: 0.5603 loss_db: 0.1465 2022/11/02 16:00:11 - mmengine - INFO - Epoch(train) [359][55/63] lr: 1.5720e-03 eta: 8:37:03 time: 0.6093 data_time: 0.0260 memory: 14901 loss: 1.5932 loss_prob: 0.8888 loss_thr: 0.5625 loss_db: 0.1419 2022/11/02 16:00:14 - mmengine - INFO - Epoch(train) [359][60/63] lr: 1.5720e-03 eta: 8:36:57 time: 0.5864 data_time: 0.0095 memory: 14901 loss: 1.4761 loss_prob: 0.8101 loss_thr: 0.5343 loss_db: 0.1317 2022/11/02 16:00:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:00:23 - mmengine - INFO - Epoch(train) [360][5/63] lr: 1.5703e-03 eta: 8:36:57 time: 0.9677 data_time: 0.3093 memory: 14901 loss: 1.5145 loss_prob: 0.8273 loss_thr: 0.5461 loss_db: 0.1410 2022/11/02 16:00:26 - mmengine - INFO - Epoch(train) [360][10/63] lr: 1.5703e-03 eta: 8:36:56 time: 1.0471 data_time: 0.3055 memory: 14901 loss: 1.4990 loss_prob: 0.8209 loss_thr: 0.5407 loss_db: 0.1374 2022/11/02 16:00:29 - mmengine - INFO - Epoch(train) [360][15/63] lr: 1.5703e-03 eta: 8:36:56 time: 0.6070 data_time: 0.0070 memory: 14901 loss: 1.4862 loss_prob: 0.8242 loss_thr: 0.5254 loss_db: 0.1366 2022/11/02 16:00:31 - mmengine - INFO - Epoch(train) [360][20/63] lr: 1.5703e-03 eta: 8:36:50 time: 0.5646 data_time: 0.0085 memory: 14901 loss: 1.3901 loss_prob: 0.7697 loss_thr: 0.4927 loss_db: 0.1277 2022/11/02 16:00:34 - mmengine - INFO - Epoch(train) [360][25/63] lr: 1.5703e-03 eta: 8:36:50 time: 0.5774 data_time: 0.0412 memory: 14901 loss: 1.4259 loss_prob: 0.7785 loss_thr: 0.5173 loss_db: 0.1301 2022/11/02 16:00:37 - mmengine - INFO - Epoch(train) [360][30/63] lr: 1.5703e-03 eta: 8:36:43 time: 0.5401 data_time: 0.0421 memory: 14901 loss: 1.4257 loss_prob: 0.7690 loss_thr: 0.5266 loss_db: 0.1301 2022/11/02 16:00:39 - mmengine - INFO - Epoch(train) [360][35/63] lr: 1.5703e-03 eta: 8:36:43 time: 0.4936 data_time: 0.0091 memory: 14901 loss: 1.5055 loss_prob: 0.8313 loss_thr: 0.5361 loss_db: 0.1381 2022/11/02 16:00:42 - mmengine - INFO - Epoch(train) [360][40/63] lr: 1.5703e-03 eta: 8:36:35 time: 0.4928 data_time: 0.0049 memory: 14901 loss: 1.6136 loss_prob: 0.9097 loss_thr: 0.5575 loss_db: 0.1463 2022/11/02 16:00:44 - mmengine - INFO - Epoch(train) [360][45/63] lr: 1.5703e-03 eta: 8:36:35 time: 0.5139 data_time: 0.0107 memory: 14901 loss: 1.5324 loss_prob: 0.8483 loss_thr: 0.5437 loss_db: 0.1404 2022/11/02 16:00:47 - mmengine - INFO - Epoch(train) [360][50/63] lr: 1.5703e-03 eta: 8:36:29 time: 0.5560 data_time: 0.0288 memory: 14901 loss: 1.4485 loss_prob: 0.7840 loss_thr: 0.5317 loss_db: 0.1328 2022/11/02 16:00:50 - mmengine - INFO - Epoch(train) [360][55/63] lr: 1.5703e-03 eta: 8:36:29 time: 0.5679 data_time: 0.0269 memory: 14901 loss: 1.4452 loss_prob: 0.7829 loss_thr: 0.5311 loss_db: 0.1311 2022/11/02 16:00:53 - mmengine - INFO - Epoch(train) [360][60/63] lr: 1.5703e-03 eta: 8:36:21 time: 0.5289 data_time: 0.0097 memory: 14901 loss: 1.5814 loss_prob: 0.8813 loss_thr: 0.5537 loss_db: 0.1464 2022/11/02 16:00:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:00:54 - mmengine - INFO - Saving checkpoint at 360 epochs 2022/11/02 16:00:59 - mmengine - INFO - Epoch(val) [360][5/500] eta: 8:36:21 time: 0.0487 data_time: 0.0059 memory: 14901 2022/11/02 16:00:59 - mmengine - INFO - Epoch(val) [360][10/500] eta: 0:00:23 time: 0.0479 data_time: 0.0056 memory: 1008 2022/11/02 16:00:59 - mmengine - INFO - Epoch(val) [360][15/500] eta: 0:00:23 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 16:01:00 - mmengine - INFO - Epoch(val) [360][20/500] eta: 0:00:20 time: 0.0433 data_time: 0.0031 memory: 1008 2022/11/02 16:01:00 - mmengine - INFO - Epoch(val) [360][25/500] eta: 0:00:20 time: 0.0435 data_time: 0.0030 memory: 1008 2022/11/02 16:01:00 - mmengine - INFO - Epoch(val) [360][30/500] eta: 0:00:21 time: 0.0451 data_time: 0.0029 memory: 1008 2022/11/02 16:01:00 - mmengine - INFO - Epoch(val) [360][35/500] eta: 0:00:21 time: 0.0431 data_time: 0.0027 memory: 1008 2022/11/02 16:01:00 - mmengine - INFO - Epoch(val) [360][40/500] eta: 0:00:19 time: 0.0421 data_time: 0.0026 memory: 1008 2022/11/02 16:01:01 - mmengine - INFO - Epoch(val) [360][45/500] eta: 0:00:19 time: 0.0468 data_time: 0.0027 memory: 1008 2022/11/02 16:01:01 - mmengine - INFO - Epoch(val) [360][50/500] eta: 0:00:21 time: 0.0480 data_time: 0.0031 memory: 1008 2022/11/02 16:01:01 - mmengine - INFO - Epoch(val) [360][55/500] eta: 0:00:21 time: 0.0514 data_time: 0.0032 memory: 1008 2022/11/02 16:01:01 - mmengine - INFO - Epoch(val) [360][60/500] eta: 0:00:22 time: 0.0516 data_time: 0.0034 memory: 1008 2022/11/02 16:01:02 - mmengine - INFO - Epoch(val) [360][65/500] eta: 0:00:22 time: 0.0487 data_time: 0.0032 memory: 1008 2022/11/02 16:01:02 - mmengine - INFO - Epoch(val) [360][70/500] eta: 0:00:21 time: 0.0489 data_time: 0.0030 memory: 1008 2022/11/02 16:01:02 - mmengine - INFO - Epoch(val) [360][75/500] eta: 0:00:21 time: 0.0460 data_time: 0.0035 memory: 1008 2022/11/02 16:01:02 - mmengine - INFO - Epoch(val) [360][80/500] eta: 0:00:19 time: 0.0455 data_time: 0.0036 memory: 1008 2022/11/02 16:01:03 - mmengine - INFO - Epoch(val) [360][85/500] eta: 0:00:19 time: 0.0466 data_time: 0.0038 memory: 1008 2022/11/02 16:01:03 - mmengine - INFO - Epoch(val) [360][90/500] eta: 0:00:18 time: 0.0454 data_time: 0.0034 memory: 1008 2022/11/02 16:01:03 - mmengine - INFO - Epoch(val) [360][95/500] eta: 0:00:18 time: 0.0456 data_time: 0.0028 memory: 1008 2022/11/02 16:01:03 - mmengine - INFO - Epoch(val) [360][100/500] eta: 0:00:16 time: 0.0422 data_time: 0.0028 memory: 1008 2022/11/02 16:01:03 - mmengine - INFO - Epoch(val) [360][105/500] eta: 0:00:16 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 16:01:04 - mmengine - INFO - Epoch(val) [360][110/500] eta: 0:00:16 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/02 16:01:04 - mmengine - INFO - Epoch(val) [360][115/500] eta: 0:00:16 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/02 16:01:04 - mmengine - INFO - Epoch(val) [360][120/500] eta: 0:00:17 time: 0.0447 data_time: 0.0028 memory: 1008 2022/11/02 16:01:04 - mmengine - INFO - Epoch(val) [360][125/500] eta: 0:00:17 time: 0.0391 data_time: 0.0028 memory: 1008 2022/11/02 16:01:05 - mmengine - INFO - Epoch(val) [360][130/500] eta: 0:00:14 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/02 16:01:05 - mmengine - INFO - Epoch(val) [360][135/500] eta: 0:00:14 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 16:01:05 - mmengine - INFO - Epoch(val) [360][140/500] eta: 0:00:13 time: 0.0384 data_time: 0.0026 memory: 1008 2022/11/02 16:01:05 - mmengine - INFO - Epoch(val) [360][145/500] eta: 0:00:13 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 16:01:05 - mmengine - INFO - Epoch(val) [360][150/500] eta: 0:00:14 time: 0.0423 data_time: 0.0025 memory: 1008 2022/11/02 16:01:06 - mmengine - INFO - Epoch(val) [360][155/500] eta: 0:00:14 time: 0.0416 data_time: 0.0024 memory: 1008 2022/11/02 16:01:06 - mmengine - INFO - Epoch(val) [360][160/500] eta: 0:00:14 time: 0.0431 data_time: 0.0028 memory: 1008 2022/11/02 16:01:06 - mmengine - INFO - Epoch(val) [360][165/500] eta: 0:00:14 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 16:01:06 - mmengine - INFO - Epoch(val) [360][170/500] eta: 0:00:13 time: 0.0397 data_time: 0.0021 memory: 1008 2022/11/02 16:01:06 - mmengine - INFO - Epoch(val) [360][175/500] eta: 0:00:13 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 16:01:07 - mmengine - INFO - Epoch(val) [360][180/500] eta: 0:00:13 time: 0.0415 data_time: 0.0030 memory: 1008 2022/11/02 16:01:07 - mmengine - INFO - Epoch(val) [360][185/500] eta: 0:00:13 time: 0.0465 data_time: 0.0032 memory: 1008 2022/11/02 16:01:07 - mmengine - INFO - Epoch(val) [360][190/500] eta: 0:00:13 time: 0.0448 data_time: 0.0028 memory: 1008 2022/11/02 16:01:07 - mmengine - INFO - Epoch(val) [360][195/500] eta: 0:00:13 time: 0.0388 data_time: 0.0025 memory: 1008 2022/11/02 16:01:07 - mmengine - INFO - Epoch(val) [360][200/500] eta: 0:00:13 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 16:01:08 - mmengine - INFO - Epoch(val) [360][205/500] eta: 0:00:13 time: 0.0445 data_time: 0.0029 memory: 1008 2022/11/02 16:01:08 - mmengine - INFO - Epoch(val) [360][210/500] eta: 0:00:10 time: 0.0362 data_time: 0.0031 memory: 1008 2022/11/02 16:01:08 - mmengine - INFO - Epoch(val) [360][215/500] eta: 0:00:10 time: 0.0381 data_time: 0.0030 memory: 1008 2022/11/02 16:01:09 - mmengine - INFO - Epoch(val) [360][220/500] eta: 0:00:20 time: 0.0749 data_time: 0.0359 memory: 1008 2022/11/02 16:01:09 - mmengine - INFO - Epoch(val) [360][225/500] eta: 0:00:20 time: 0.0771 data_time: 0.0356 memory: 1008 2022/11/02 16:01:09 - mmengine - INFO - Epoch(val) [360][230/500] eta: 0:00:11 time: 0.0408 data_time: 0.0021 memory: 1008 2022/11/02 16:01:09 - mmengine - INFO - Epoch(val) [360][235/500] eta: 0:00:11 time: 0.0398 data_time: 0.0026 memory: 1008 2022/11/02 16:01:09 - mmengine - INFO - Epoch(val) [360][240/500] eta: 0:00:11 time: 0.0444 data_time: 0.0029 memory: 1008 2022/11/02 16:01:10 - mmengine - INFO - Epoch(val) [360][245/500] eta: 0:00:11 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 16:01:10 - mmengine - INFO - Epoch(val) [360][250/500] eta: 0:00:09 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/02 16:01:10 - mmengine - INFO - Epoch(val) [360][255/500] eta: 0:00:09 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 16:01:10 - mmengine - INFO - Epoch(val) [360][260/500] eta: 0:00:08 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 16:01:10 - mmengine - INFO - Epoch(val) [360][265/500] eta: 0:00:08 time: 0.0413 data_time: 0.0031 memory: 1008 2022/11/02 16:01:11 - mmengine - INFO - Epoch(val) [360][270/500] eta: 0:00:10 time: 0.0471 data_time: 0.0080 memory: 1008 2022/11/02 16:01:11 - mmengine - INFO - Epoch(val) [360][275/500] eta: 0:00:10 time: 0.0436 data_time: 0.0072 memory: 1008 2022/11/02 16:01:11 - mmengine - INFO - Epoch(val) [360][280/500] eta: 0:00:08 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 16:01:11 - mmengine - INFO - Epoch(val) [360][285/500] eta: 0:00:08 time: 0.0404 data_time: 0.0029 memory: 1008 2022/11/02 16:01:11 - mmengine - INFO - Epoch(val) [360][290/500] eta: 0:00:08 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 16:01:12 - mmengine - INFO - Epoch(val) [360][295/500] eta: 0:00:08 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/02 16:01:12 - mmengine - INFO - Epoch(val) [360][300/500] eta: 0:00:09 time: 0.0460 data_time: 0.0037 memory: 1008 2022/11/02 16:01:12 - mmengine - INFO - Epoch(val) [360][305/500] eta: 0:00:09 time: 0.0420 data_time: 0.0034 memory: 1008 2022/11/02 16:01:12 - mmengine - INFO - Epoch(val) [360][310/500] eta: 0:00:07 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 16:01:13 - mmengine - INFO - Epoch(val) [360][315/500] eta: 0:00:07 time: 0.0443 data_time: 0.0027 memory: 1008 2022/11/02 16:01:13 - mmengine - INFO - Epoch(val) [360][320/500] eta: 0:00:07 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 16:01:13 - mmengine - INFO - Epoch(val) [360][325/500] eta: 0:00:07 time: 0.0554 data_time: 0.0026 memory: 1008 2022/11/02 16:01:13 - mmengine - INFO - Epoch(val) [360][330/500] eta: 0:00:09 time: 0.0561 data_time: 0.0027 memory: 1008 2022/11/02 16:01:13 - mmengine - INFO - Epoch(val) [360][335/500] eta: 0:00:09 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 16:01:14 - mmengine - INFO - Epoch(val) [360][340/500] eta: 0:00:07 time: 0.0489 data_time: 0.0030 memory: 1008 2022/11/02 16:01:14 - mmengine - INFO - Epoch(val) [360][345/500] eta: 0:00:07 time: 0.0531 data_time: 0.0031 memory: 1008 2022/11/02 16:01:14 - mmengine - INFO - Epoch(val) [360][350/500] eta: 0:00:07 time: 0.0516 data_time: 0.0030 memory: 1008 2022/11/02 16:01:14 - mmengine - INFO - Epoch(val) [360][355/500] eta: 0:00:07 time: 0.0475 data_time: 0.0028 memory: 1008 2022/11/02 16:01:15 - mmengine - INFO - Epoch(val) [360][360/500] eta: 0:00:05 time: 0.0381 data_time: 0.0026 memory: 1008 2022/11/02 16:01:15 - mmengine - INFO - Epoch(val) [360][365/500] eta: 0:00:05 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 16:01:15 - mmengine - INFO - Epoch(val) [360][370/500] eta: 0:00:05 time: 0.0391 data_time: 0.0029 memory: 1008 2022/11/02 16:01:15 - mmengine - INFO - Epoch(val) [360][375/500] eta: 0:00:05 time: 0.0366 data_time: 0.0028 memory: 1008 2022/11/02 16:01:15 - mmengine - INFO - Epoch(val) [360][380/500] eta: 0:00:04 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 16:01:16 - mmengine - INFO - Epoch(val) [360][385/500] eta: 0:00:04 time: 0.0402 data_time: 0.0026 memory: 1008 2022/11/02 16:01:16 - mmengine - INFO - Epoch(val) [360][390/500] eta: 0:00:04 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/02 16:01:16 - mmengine - INFO - Epoch(val) [360][395/500] eta: 0:00:04 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/02 16:01:16 - mmengine - INFO - Epoch(val) [360][400/500] eta: 0:00:03 time: 0.0363 data_time: 0.0022 memory: 1008 2022/11/02 16:01:16 - mmengine - INFO - Epoch(val) [360][405/500] eta: 0:00:03 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 16:01:17 - mmengine - INFO - Epoch(val) [360][410/500] eta: 0:00:03 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 16:01:17 - mmengine - INFO - Epoch(val) [360][415/500] eta: 0:00:03 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 16:01:18 - mmengine - INFO - Epoch(val) [360][420/500] eta: 0:00:08 time: 0.1091 data_time: 0.0767 memory: 1008 2022/11/02 16:01:18 - mmengine - INFO - Epoch(val) [360][425/500] eta: 0:00:08 time: 0.1094 data_time: 0.0764 memory: 1008 2022/11/02 16:01:18 - mmengine - INFO - Epoch(val) [360][430/500] eta: 0:00:02 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 16:01:18 - mmengine - INFO - Epoch(val) [360][435/500] eta: 0:00:02 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/02 16:01:19 - mmengine - INFO - Epoch(val) [360][440/500] eta: 0:00:02 time: 0.0394 data_time: 0.0030 memory: 1008 2022/11/02 16:01:19 - mmengine - INFO - Epoch(val) [360][445/500] eta: 0:00:02 time: 0.0437 data_time: 0.0029 memory: 1008 2022/11/02 16:01:19 - mmengine - INFO - Epoch(val) [360][450/500] eta: 0:00:02 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 16:01:19 - mmengine - INFO - Epoch(val) [360][455/500] eta: 0:00:02 time: 0.0402 data_time: 0.0028 memory: 1008 2022/11/02 16:01:19 - mmengine - INFO - Epoch(val) [360][460/500] eta: 0:00:01 time: 0.0371 data_time: 0.0026 memory: 1008 2022/11/02 16:01:20 - mmengine - INFO - Epoch(val) [360][465/500] eta: 0:00:01 time: 0.0392 data_time: 0.0043 memory: 1008 2022/11/02 16:01:20 - mmengine - INFO - Epoch(val) [360][470/500] eta: 0:00:01 time: 0.0398 data_time: 0.0043 memory: 1008 2022/11/02 16:01:20 - mmengine - INFO - Epoch(val) [360][475/500] eta: 0:00:01 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 16:01:20 - mmengine - INFO - Epoch(val) [360][480/500] eta: 0:00:00 time: 0.0375 data_time: 0.0026 memory: 1008 2022/11/02 16:01:20 - mmengine - INFO - Epoch(val) [360][485/500] eta: 0:00:00 time: 0.0381 data_time: 0.0023 memory: 1008 2022/11/02 16:01:21 - mmengine - INFO - Epoch(val) [360][490/500] eta: 0:00:00 time: 0.0426 data_time: 0.0029 memory: 1008 2022/11/02 16:01:21 - mmengine - INFO - Epoch(val) [360][495/500] eta: 0:00:00 time: 0.0430 data_time: 0.0031 memory: 1008 2022/11/02 16:01:21 - mmengine - INFO - Epoch(val) [360][500/500] eta: 0:00:00 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 16:01:21 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8257, precision: 0.7182, hmean: 0.7682 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8257, precision: 0.7806, hmean: 0.8025 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8238, precision: 0.8144, hmean: 0.8191 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8132, precision: 0.8578, hmean: 0.8349 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7703, precision: 0.8949, hmean: 0.8279 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4540, precision: 0.9439, hmean: 0.6131 2022/11/02 16:01:21 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0082, precision: 0.8500, hmean: 0.0162 2022/11/02 16:01:21 - mmengine - INFO - Epoch(val) [360][500/500] icdar/precision: 0.8578 icdar/recall: 0.8132 icdar/hmean: 0.8349 2022/11/02 16:01:27 - mmengine - INFO - Epoch(train) [361][5/63] lr: 1.5686e-03 eta: 0:00:00 time: 0.8504 data_time: 0.2806 memory: 14901 loss: 1.5159 loss_prob: 0.8426 loss_thr: 0.5318 loss_db: 0.1414 2022/11/02 16:01:30 - mmengine - INFO - Epoch(train) [361][10/63] lr: 1.5686e-03 eta: 8:36:18 time: 0.9320 data_time: 0.2748 memory: 14901 loss: 1.4196 loss_prob: 0.7798 loss_thr: 0.5088 loss_db: 0.1309 2022/11/02 16:01:33 - mmengine - INFO - Epoch(train) [361][15/63] lr: 1.5686e-03 eta: 8:36:18 time: 0.6204 data_time: 0.0063 memory: 14901 loss: 1.4845 loss_prob: 0.8104 loss_thr: 0.5380 loss_db: 0.1360 2022/11/02 16:01:36 - mmengine - INFO - Epoch(train) [361][20/63] lr: 1.5686e-03 eta: 8:36:12 time: 0.6053 data_time: 0.0065 memory: 14901 loss: 1.5370 loss_prob: 0.8430 loss_thr: 0.5527 loss_db: 0.1413 2022/11/02 16:01:39 - mmengine - INFO - Epoch(train) [361][25/63] lr: 1.5686e-03 eta: 8:36:12 time: 0.6143 data_time: 0.0403 memory: 14901 loss: 1.5620 loss_prob: 0.8695 loss_thr: 0.5444 loss_db: 0.1480 2022/11/02 16:01:42 - mmengine - INFO - Epoch(train) [361][30/63] lr: 1.5686e-03 eta: 8:36:06 time: 0.5622 data_time: 0.0405 memory: 14901 loss: 1.6059 loss_prob: 0.9111 loss_thr: 0.5459 loss_db: 0.1489 2022/11/02 16:01:46 - mmengine - INFO - Epoch(train) [361][35/63] lr: 1.5686e-03 eta: 8:36:06 time: 0.6357 data_time: 0.0213 memory: 14901 loss: 1.5853 loss_prob: 0.9036 loss_thr: 0.5360 loss_db: 0.1457 2022/11/02 16:01:49 - mmengine - INFO - Epoch(train) [361][40/63] lr: 1.5686e-03 eta: 8:36:02 time: 0.6666 data_time: 0.0237 memory: 14901 loss: 1.5038 loss_prob: 0.8378 loss_thr: 0.5247 loss_db: 0.1413 2022/11/02 16:01:52 - mmengine - INFO - Epoch(train) [361][45/63] lr: 1.5686e-03 eta: 8:36:02 time: 0.5825 data_time: 0.0085 memory: 14901 loss: 1.5185 loss_prob: 0.8361 loss_thr: 0.5408 loss_db: 0.1417 2022/11/02 16:01:54 - mmengine - INFO - Epoch(train) [361][50/63] lr: 1.5686e-03 eta: 8:35:55 time: 0.5452 data_time: 0.0091 memory: 14901 loss: 1.5043 loss_prob: 0.8298 loss_thr: 0.5328 loss_db: 0.1417 2022/11/02 16:01:57 - mmengine - INFO - Epoch(train) [361][55/63] lr: 1.5686e-03 eta: 8:35:55 time: 0.4940 data_time: 0.0088 memory: 14901 loss: 1.4921 loss_prob: 0.8246 loss_thr: 0.5271 loss_db: 0.1403 2022/11/02 16:01:59 - mmengine - INFO - Epoch(train) [361][60/63] lr: 1.5686e-03 eta: 8:35:47 time: 0.4944 data_time: 0.0290 memory: 14901 loss: 1.5147 loss_prob: 0.8459 loss_thr: 0.5265 loss_db: 0.1423 2022/11/02 16:02:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:02:06 - mmengine - INFO - Epoch(train) [362][5/63] lr: 1.5670e-03 eta: 8:35:47 time: 0.7583 data_time: 0.2183 memory: 14901 loss: 1.4495 loss_prob: 0.7932 loss_thr: 0.5229 loss_db: 0.1333 2022/11/02 16:02:08 - mmengine - INFO - Epoch(train) [362][10/63] lr: 1.5670e-03 eta: 8:35:41 time: 0.8067 data_time: 0.2178 memory: 14901 loss: 1.4803 loss_prob: 0.8170 loss_thr: 0.5224 loss_db: 0.1409 2022/11/02 16:02:11 - mmengine - INFO - Epoch(train) [362][15/63] lr: 1.5670e-03 eta: 8:35:41 time: 0.4974 data_time: 0.0056 memory: 14901 loss: 1.4849 loss_prob: 0.8264 loss_thr: 0.5202 loss_db: 0.1384 2022/11/02 16:02:13 - mmengine - INFO - Epoch(train) [362][20/63] lr: 1.5670e-03 eta: 8:35:33 time: 0.4910 data_time: 0.0065 memory: 14901 loss: 1.4467 loss_prob: 0.7921 loss_thr: 0.5247 loss_db: 0.1299 2022/11/02 16:02:16 - mmengine - INFO - Epoch(train) [362][25/63] lr: 1.5670e-03 eta: 8:35:33 time: 0.5450 data_time: 0.0149 memory: 14901 loss: 1.4849 loss_prob: 0.8261 loss_thr: 0.5227 loss_db: 0.1361 2022/11/02 16:02:19 - mmengine - INFO - Epoch(train) [362][30/63] lr: 1.5670e-03 eta: 8:35:26 time: 0.5404 data_time: 0.0350 memory: 14901 loss: 1.4894 loss_prob: 0.8467 loss_thr: 0.5014 loss_db: 0.1413 2022/11/02 16:02:21 - mmengine - INFO - Epoch(train) [362][35/63] lr: 1.5670e-03 eta: 8:35:26 time: 0.5091 data_time: 0.0258 memory: 14901 loss: 1.5234 loss_prob: 0.8616 loss_thr: 0.5195 loss_db: 0.1422 2022/11/02 16:02:24 - mmengine - INFO - Epoch(train) [362][40/63] lr: 1.5670e-03 eta: 8:35:20 time: 0.5786 data_time: 0.0197 memory: 14901 loss: 1.4964 loss_prob: 0.8312 loss_thr: 0.5262 loss_db: 0.1390 2022/11/02 16:02:27 - mmengine - INFO - Epoch(train) [362][45/63] lr: 1.5670e-03 eta: 8:35:20 time: 0.5815 data_time: 0.0230 memory: 14901 loss: 1.4906 loss_prob: 0.8197 loss_thr: 0.5294 loss_db: 0.1415 2022/11/02 16:02:30 - mmengine - INFO - Epoch(train) [362][50/63] lr: 1.5670e-03 eta: 8:35:13 time: 0.5577 data_time: 0.0163 memory: 14901 loss: 1.4992 loss_prob: 0.8228 loss_thr: 0.5377 loss_db: 0.1387 2022/11/02 16:02:33 - mmengine - INFO - Epoch(train) [362][55/63] lr: 1.5670e-03 eta: 8:35:13 time: 0.5654 data_time: 0.0153 memory: 14901 loss: 1.5626 loss_prob: 0.8675 loss_thr: 0.5492 loss_db: 0.1459 2022/11/02 16:02:36 - mmengine - INFO - Epoch(train) [362][60/63] lr: 1.5670e-03 eta: 8:35:07 time: 0.5671 data_time: 0.0125 memory: 14901 loss: 1.6366 loss_prob: 0.9198 loss_thr: 0.5604 loss_db: 0.1564 2022/11/02 16:02:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:02:42 - mmengine - INFO - Epoch(train) [363][5/63] lr: 1.5653e-03 eta: 8:35:07 time: 0.7103 data_time: 0.2093 memory: 14901 loss: 1.6520 loss_prob: 0.9288 loss_thr: 0.5656 loss_db: 0.1576 2022/11/02 16:02:44 - mmengine - INFO - Epoch(train) [363][10/63] lr: 1.5653e-03 eta: 8:34:58 time: 0.6932 data_time: 0.2087 memory: 14901 loss: 1.5674 loss_prob: 0.8814 loss_thr: 0.5367 loss_db: 0.1493 2022/11/02 16:02:47 - mmengine - INFO - Epoch(train) [363][15/63] lr: 1.5653e-03 eta: 8:34:58 time: 0.5025 data_time: 0.0055 memory: 14901 loss: 1.5657 loss_prob: 0.8719 loss_thr: 0.5476 loss_db: 0.1462 2022/11/02 16:02:49 - mmengine - INFO - Epoch(train) [363][20/63] lr: 1.5653e-03 eta: 8:34:51 time: 0.5540 data_time: 0.0064 memory: 14901 loss: 1.5261 loss_prob: 0.8349 loss_thr: 0.5500 loss_db: 0.1412 2022/11/02 16:02:52 - mmengine - INFO - Epoch(train) [363][25/63] lr: 1.5653e-03 eta: 8:34:51 time: 0.5599 data_time: 0.0224 memory: 14901 loss: 1.4300 loss_prob: 0.7742 loss_thr: 0.5223 loss_db: 0.1335 2022/11/02 16:02:55 - mmengine - INFO - Epoch(train) [363][30/63] lr: 1.5653e-03 eta: 8:34:45 time: 0.5907 data_time: 0.0409 memory: 14901 loss: 1.5302 loss_prob: 0.8594 loss_thr: 0.5235 loss_db: 0.1473 2022/11/02 16:02:58 - mmengine - INFO - Epoch(train) [363][35/63] lr: 1.5653e-03 eta: 8:34:45 time: 0.5812 data_time: 0.0289 memory: 14901 loss: 1.5856 loss_prob: 0.8962 loss_thr: 0.5391 loss_db: 0.1503 2022/11/02 16:03:01 - mmengine - INFO - Epoch(train) [363][40/63] lr: 1.5653e-03 eta: 8:34:39 time: 0.5550 data_time: 0.0111 memory: 14901 loss: 1.5066 loss_prob: 0.8329 loss_thr: 0.5358 loss_db: 0.1379 2022/11/02 16:03:04 - mmengine - INFO - Epoch(train) [363][45/63] lr: 1.5653e-03 eta: 8:34:39 time: 0.6233 data_time: 0.0167 memory: 14901 loss: 1.5201 loss_prob: 0.8407 loss_thr: 0.5397 loss_db: 0.1397 2022/11/02 16:03:07 - mmengine - INFO - Epoch(train) [363][50/63] lr: 1.5653e-03 eta: 8:34:34 time: 0.6118 data_time: 0.0299 memory: 14901 loss: 1.7602 loss_prob: 1.0200 loss_thr: 0.5733 loss_db: 0.1669 2022/11/02 16:03:10 - mmengine - INFO - Epoch(train) [363][55/63] lr: 1.5653e-03 eta: 8:34:34 time: 0.5644 data_time: 0.0276 memory: 14901 loss: 1.7602 loss_prob: 1.0372 loss_thr: 0.5540 loss_db: 0.1690 2022/11/02 16:03:13 - mmengine - INFO - Epoch(train) [363][60/63] lr: 1.5653e-03 eta: 8:34:28 time: 0.5734 data_time: 0.0184 memory: 14901 loss: 1.5344 loss_prob: 0.8637 loss_thr: 0.5276 loss_db: 0.1431 2022/11/02 16:03:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:03:19 - mmengine - INFO - Epoch(train) [364][5/63] lr: 1.5636e-03 eta: 8:34:28 time: 0.7305 data_time: 0.2380 memory: 14901 loss: 1.8314 loss_prob: 1.0725 loss_thr: 0.5878 loss_db: 0.1711 2022/11/02 16:03:22 - mmengine - INFO - Epoch(train) [364][10/63] lr: 1.5636e-03 eta: 8:34:21 time: 0.7978 data_time: 0.2424 memory: 14901 loss: 1.7010 loss_prob: 0.9745 loss_thr: 0.5694 loss_db: 0.1572 2022/11/02 16:03:26 - mmengine - INFO - Epoch(train) [364][15/63] lr: 1.5636e-03 eta: 8:34:21 time: 0.6691 data_time: 0.0143 memory: 14901 loss: 1.5777 loss_prob: 0.8784 loss_thr: 0.5516 loss_db: 0.1476 2022/11/02 16:03:29 - mmengine - INFO - Epoch(train) [364][20/63] lr: 1.5636e-03 eta: 8:34:18 time: 0.7088 data_time: 0.0113 memory: 14901 loss: 1.5578 loss_prob: 0.8602 loss_thr: 0.5536 loss_db: 0.1440 2022/11/02 16:03:32 - mmengine - INFO - Epoch(train) [364][25/63] lr: 1.5636e-03 eta: 8:34:18 time: 0.6370 data_time: 0.0263 memory: 14901 loss: 1.5406 loss_prob: 0.8505 loss_thr: 0.5479 loss_db: 0.1422 2022/11/02 16:03:36 - mmengine - INFO - Epoch(train) [364][30/63] lr: 1.5636e-03 eta: 8:34:14 time: 0.6628 data_time: 0.0397 memory: 14901 loss: 1.5737 loss_prob: 0.8797 loss_thr: 0.5487 loss_db: 0.1453 2022/11/02 16:03:39 - mmengine - INFO - Epoch(train) [364][35/63] lr: 1.5636e-03 eta: 8:34:14 time: 0.6661 data_time: 0.0235 memory: 14901 loss: 1.6520 loss_prob: 0.9459 loss_thr: 0.5528 loss_db: 0.1533 2022/11/02 16:03:42 - mmengine - INFO - Epoch(train) [364][40/63] lr: 1.5636e-03 eta: 8:34:08 time: 0.5992 data_time: 0.0107 memory: 14901 loss: 1.6008 loss_prob: 0.9052 loss_thr: 0.5479 loss_db: 0.1477 2022/11/02 16:03:44 - mmengine - INFO - Epoch(train) [364][45/63] lr: 1.5636e-03 eta: 8:34:08 time: 0.5679 data_time: 0.0117 memory: 14901 loss: 1.5315 loss_prob: 0.8444 loss_thr: 0.5449 loss_db: 0.1422 2022/11/02 16:03:49 - mmengine - INFO - Epoch(train) [364][50/63] lr: 1.5636e-03 eta: 8:34:05 time: 0.6990 data_time: 0.0296 memory: 14901 loss: 1.5103 loss_prob: 0.8373 loss_thr: 0.5311 loss_db: 0.1419 2022/11/02 16:03:52 - mmengine - INFO - Epoch(train) [364][55/63] lr: 1.5636e-03 eta: 8:34:05 time: 0.7698 data_time: 0.0273 memory: 14901 loss: 1.4836 loss_prob: 0.8128 loss_thr: 0.5341 loss_db: 0.1366 2022/11/02 16:03:55 - mmengine - INFO - Epoch(train) [364][60/63] lr: 1.5636e-03 eta: 8:33:59 time: 0.5921 data_time: 0.0081 memory: 14901 loss: 1.4549 loss_prob: 0.7923 loss_thr: 0.5286 loss_db: 0.1341 2022/11/02 16:03:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:04:02 - mmengine - INFO - Epoch(train) [365][5/63] lr: 1.5619e-03 eta: 8:33:59 time: 0.8562 data_time: 0.2926 memory: 14901 loss: 1.4916 loss_prob: 0.8147 loss_thr: 0.5426 loss_db: 0.1344 2022/11/02 16:04:05 - mmengine - INFO - Epoch(train) [365][10/63] lr: 1.5619e-03 eta: 8:33:55 time: 0.9283 data_time: 0.2922 memory: 14901 loss: 1.4158 loss_prob: 0.7719 loss_thr: 0.5154 loss_db: 0.1285 2022/11/02 16:04:08 - mmengine - INFO - Epoch(train) [365][15/63] lr: 1.5619e-03 eta: 8:33:55 time: 0.5795 data_time: 0.0118 memory: 14901 loss: 1.4326 loss_prob: 0.7820 loss_thr: 0.5173 loss_db: 0.1333 2022/11/02 16:04:11 - mmengine - INFO - Epoch(train) [365][20/63] lr: 1.5619e-03 eta: 8:33:49 time: 0.5516 data_time: 0.0114 memory: 14901 loss: 1.4591 loss_prob: 0.7978 loss_thr: 0.5257 loss_db: 0.1355 2022/11/02 16:04:14 - mmengine - INFO - Epoch(train) [365][25/63] lr: 1.5619e-03 eta: 8:33:49 time: 0.6144 data_time: 0.0320 memory: 14901 loss: 1.4727 loss_prob: 0.8237 loss_thr: 0.5168 loss_db: 0.1321 2022/11/02 16:04:18 - mmengine - INFO - Epoch(train) [365][30/63] lr: 1.5619e-03 eta: 8:33:45 time: 0.6844 data_time: 0.0362 memory: 14901 loss: 1.5336 loss_prob: 0.8673 loss_thr: 0.5272 loss_db: 0.1391 2022/11/02 16:04:21 - mmengine - INFO - Epoch(train) [365][35/63] lr: 1.5619e-03 eta: 8:33:45 time: 0.6697 data_time: 0.0162 memory: 14901 loss: 1.5768 loss_prob: 0.8792 loss_thr: 0.5497 loss_db: 0.1479 2022/11/02 16:04:24 - mmengine - INFO - Epoch(train) [365][40/63] lr: 1.5619e-03 eta: 8:33:40 time: 0.6113 data_time: 0.0145 memory: 14901 loss: 1.5563 loss_prob: 0.8589 loss_thr: 0.5524 loss_db: 0.1449 2022/11/02 16:04:27 - mmengine - INFO - Epoch(train) [365][45/63] lr: 1.5619e-03 eta: 8:33:40 time: 0.5890 data_time: 0.0116 memory: 14901 loss: 1.4917 loss_prob: 0.8171 loss_thr: 0.5382 loss_db: 0.1363 2022/11/02 16:04:30 - mmengine - INFO - Epoch(train) [365][50/63] lr: 1.5619e-03 eta: 8:33:34 time: 0.5786 data_time: 0.0269 memory: 14901 loss: 1.4483 loss_prob: 0.7909 loss_thr: 0.5248 loss_db: 0.1326 2022/11/02 16:04:34 - mmengine - INFO - Epoch(train) [365][55/63] lr: 1.5619e-03 eta: 8:33:34 time: 0.6802 data_time: 0.0283 memory: 14901 loss: 1.8070 loss_prob: 1.0852 loss_thr: 0.5637 loss_db: 0.1580 2022/11/02 16:04:36 - mmengine - INFO - Epoch(train) [365][60/63] lr: 1.5619e-03 eta: 8:33:30 time: 0.6787 data_time: 0.0117 memory: 14901 loss: 1.8745 loss_prob: 1.1396 loss_thr: 0.5683 loss_db: 0.1665 2022/11/02 16:04:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:04:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:04:44 - mmengine - INFO - Epoch(train) [366][5/63] lr: 1.5602e-03 eta: 8:33:30 time: 0.8540 data_time: 0.2838 memory: 14901 loss: 1.4629 loss_prob: 0.8099 loss_thr: 0.5166 loss_db: 0.1363 2022/11/02 16:04:47 - mmengine - INFO - Epoch(train) [366][10/63] lr: 1.5602e-03 eta: 8:33:26 time: 0.8908 data_time: 0.2880 memory: 14901 loss: 1.4522 loss_prob: 0.8074 loss_thr: 0.5115 loss_db: 0.1333 2022/11/02 16:04:49 - mmengine - INFO - Epoch(train) [366][15/63] lr: 1.5602e-03 eta: 8:33:26 time: 0.5103 data_time: 0.0122 memory: 14901 loss: 1.4565 loss_prob: 0.8053 loss_thr: 0.5178 loss_db: 0.1334 2022/11/02 16:04:52 - mmengine - INFO - Epoch(train) [366][20/63] lr: 1.5602e-03 eta: 8:33:19 time: 0.5349 data_time: 0.0056 memory: 14901 loss: 1.4663 loss_prob: 0.8060 loss_thr: 0.5232 loss_db: 0.1372 2022/11/02 16:04:55 - mmengine - INFO - Epoch(train) [366][25/63] lr: 1.5602e-03 eta: 8:33:19 time: 0.5887 data_time: 0.0334 memory: 14901 loss: 1.5765 loss_prob: 0.8738 loss_thr: 0.5541 loss_db: 0.1486 2022/11/02 16:04:57 - mmengine - INFO - Epoch(train) [366][30/63] lr: 1.5602e-03 eta: 8:33:11 time: 0.5195 data_time: 0.0329 memory: 14901 loss: 1.6532 loss_prob: 0.9309 loss_thr: 0.5655 loss_db: 0.1569 2022/11/02 16:05:00 - mmengine - INFO - Epoch(train) [366][35/63] lr: 1.5602e-03 eta: 8:33:11 time: 0.4643 data_time: 0.0077 memory: 14901 loss: 1.5386 loss_prob: 0.8595 loss_thr: 0.5354 loss_db: 0.1436 2022/11/02 16:05:02 - mmengine - INFO - Epoch(train) [366][40/63] lr: 1.5602e-03 eta: 8:33:04 time: 0.5121 data_time: 0.0079 memory: 14901 loss: 1.4430 loss_prob: 0.7904 loss_thr: 0.5189 loss_db: 0.1337 2022/11/02 16:05:05 - mmengine - INFO - Epoch(train) [366][45/63] lr: 1.5602e-03 eta: 8:33:04 time: 0.5110 data_time: 0.0047 memory: 14901 loss: 1.4566 loss_prob: 0.7956 loss_thr: 0.5254 loss_db: 0.1357 2022/11/02 16:05:07 - mmengine - INFO - Epoch(train) [366][50/63] lr: 1.5602e-03 eta: 8:32:56 time: 0.4978 data_time: 0.0201 memory: 14901 loss: 1.4486 loss_prob: 0.7935 loss_thr: 0.5230 loss_db: 0.1322 2022/11/02 16:05:10 - mmengine - INFO - Epoch(train) [366][55/63] lr: 1.5602e-03 eta: 8:32:56 time: 0.5135 data_time: 0.0233 memory: 14901 loss: 1.4731 loss_prob: 0.8206 loss_thr: 0.5184 loss_db: 0.1342 2022/11/02 16:05:12 - mmengine - INFO - Epoch(train) [366][60/63] lr: 1.5602e-03 eta: 8:32:48 time: 0.5005 data_time: 0.0085 memory: 14901 loss: 1.5810 loss_prob: 0.8941 loss_thr: 0.5406 loss_db: 0.1464 2022/11/02 16:05:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:05:19 - mmengine - INFO - Epoch(train) [367][5/63] lr: 1.5585e-03 eta: 8:32:48 time: 0.7649 data_time: 0.2491 memory: 14901 loss: 1.5618 loss_prob: 0.8683 loss_thr: 0.5520 loss_db: 0.1415 2022/11/02 16:05:22 - mmengine - INFO - Epoch(train) [367][10/63] lr: 1.5585e-03 eta: 8:32:41 time: 0.7993 data_time: 0.2515 memory: 14901 loss: 1.4606 loss_prob: 0.7955 loss_thr: 0.5333 loss_db: 0.1318 2022/11/02 16:05:24 - mmengine - INFO - Epoch(train) [367][15/63] lr: 1.5585e-03 eta: 8:32:41 time: 0.5035 data_time: 0.0086 memory: 14901 loss: 1.4934 loss_prob: 0.8204 loss_thr: 0.5379 loss_db: 0.1350 2022/11/02 16:05:27 - mmengine - INFO - Epoch(train) [367][20/63] lr: 1.5585e-03 eta: 8:32:34 time: 0.5054 data_time: 0.0057 memory: 14901 loss: 1.5015 loss_prob: 0.8182 loss_thr: 0.5438 loss_db: 0.1395 2022/11/02 16:05:29 - mmengine - INFO - Epoch(train) [367][25/63] lr: 1.5585e-03 eta: 8:32:34 time: 0.5141 data_time: 0.0328 memory: 14901 loss: 1.5250 loss_prob: 0.8226 loss_thr: 0.5619 loss_db: 0.1405 2022/11/02 16:05:32 - mmengine - INFO - Epoch(train) [367][30/63] lr: 1.5585e-03 eta: 8:32:26 time: 0.5121 data_time: 0.0342 memory: 14901 loss: 1.5268 loss_prob: 0.8334 loss_thr: 0.5568 loss_db: 0.1366 2022/11/02 16:05:34 - mmengine - INFO - Epoch(train) [367][35/63] lr: 1.5585e-03 eta: 8:32:26 time: 0.4954 data_time: 0.0073 memory: 14901 loss: 1.5116 loss_prob: 0.8406 loss_thr: 0.5339 loss_db: 0.1371 2022/11/02 16:05:37 - mmengine - INFO - Epoch(train) [367][40/63] lr: 1.5585e-03 eta: 8:32:19 time: 0.5204 data_time: 0.0057 memory: 14901 loss: 1.5045 loss_prob: 0.8352 loss_thr: 0.5298 loss_db: 0.1395 2022/11/02 16:05:39 - mmengine - INFO - Epoch(train) [367][45/63] lr: 1.5585e-03 eta: 8:32:19 time: 0.4992 data_time: 0.0044 memory: 14901 loss: 1.4782 loss_prob: 0.8189 loss_thr: 0.5220 loss_db: 0.1373 2022/11/02 16:05:42 - mmengine - INFO - Epoch(train) [367][50/63] lr: 1.5585e-03 eta: 8:32:11 time: 0.5048 data_time: 0.0203 memory: 14901 loss: 1.6209 loss_prob: 0.9205 loss_thr: 0.5486 loss_db: 0.1517 2022/11/02 16:05:45 - mmengine - INFO - Epoch(train) [367][55/63] lr: 1.5585e-03 eta: 8:32:11 time: 0.5464 data_time: 0.0220 memory: 14901 loss: 1.8422 loss_prob: 1.0921 loss_thr: 0.5732 loss_db: 0.1769 2022/11/02 16:05:48 - mmengine - INFO - Epoch(train) [367][60/63] lr: 1.5585e-03 eta: 8:32:05 time: 0.5724 data_time: 0.0111 memory: 14901 loss: 1.8237 loss_prob: 1.0916 loss_thr: 0.5581 loss_db: 0.1740 2022/11/02 16:05:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:05:55 - mmengine - INFO - Epoch(train) [368][5/63] lr: 1.5569e-03 eta: 8:32:05 time: 0.8801 data_time: 0.2598 memory: 14901 loss: 1.6783 loss_prob: 0.9426 loss_thr: 0.5792 loss_db: 0.1565 2022/11/02 16:05:58 - mmengine - INFO - Epoch(train) [368][10/63] lr: 1.5569e-03 eta: 8:31:59 time: 0.8247 data_time: 0.2566 memory: 14901 loss: 1.8331 loss_prob: 1.0469 loss_thr: 0.6070 loss_db: 0.1792 2022/11/02 16:06:01 - mmengine - INFO - Epoch(train) [368][15/63] lr: 1.5569e-03 eta: 8:31:59 time: 0.5524 data_time: 0.0116 memory: 14901 loss: 1.7914 loss_prob: 1.0289 loss_thr: 0.5863 loss_db: 0.1763 2022/11/02 16:06:03 - mmengine - INFO - Epoch(train) [368][20/63] lr: 1.5569e-03 eta: 8:31:52 time: 0.5295 data_time: 0.0107 memory: 14901 loss: 1.7138 loss_prob: 0.9673 loss_thr: 0.5904 loss_db: 0.1561 2022/11/02 16:06:05 - mmengine - INFO - Epoch(train) [368][25/63] lr: 1.5569e-03 eta: 8:31:52 time: 0.4891 data_time: 0.0203 memory: 14901 loss: 1.7843 loss_prob: 1.0173 loss_thr: 0.6074 loss_db: 0.1596 2022/11/02 16:06:08 - mmengine - INFO - Epoch(train) [368][30/63] lr: 1.5569e-03 eta: 8:31:44 time: 0.5099 data_time: 0.0388 memory: 14901 loss: 1.6951 loss_prob: 0.9733 loss_thr: 0.5649 loss_db: 0.1569 2022/11/02 16:06:11 - mmengine - INFO - Epoch(train) [368][35/63] lr: 1.5569e-03 eta: 8:31:44 time: 0.5434 data_time: 0.0302 memory: 14901 loss: 1.8274 loss_prob: 1.0746 loss_thr: 0.5810 loss_db: 0.1719 2022/11/02 16:06:14 - mmengine - INFO - Epoch(train) [368][40/63] lr: 1.5569e-03 eta: 8:31:37 time: 0.5519 data_time: 0.0143 memory: 14901 loss: 1.8283 loss_prob: 1.0652 loss_thr: 0.5944 loss_db: 0.1687 2022/11/02 16:06:16 - mmengine - INFO - Epoch(train) [368][45/63] lr: 1.5569e-03 eta: 8:31:37 time: 0.5113 data_time: 0.0092 memory: 14901 loss: 1.7824 loss_prob: 1.0435 loss_thr: 0.5720 loss_db: 0.1670 2022/11/02 16:06:19 - mmengine - INFO - Epoch(train) [368][50/63] lr: 1.5569e-03 eta: 8:31:30 time: 0.5147 data_time: 0.0291 memory: 14901 loss: 1.8518 loss_prob: 1.1003 loss_thr: 0.5742 loss_db: 0.1773 2022/11/02 16:06:21 - mmengine - INFO - Epoch(train) [368][55/63] lr: 1.5569e-03 eta: 8:31:30 time: 0.5383 data_time: 0.0337 memory: 14901 loss: 1.6555 loss_prob: 0.9528 loss_thr: 0.5475 loss_db: 0.1552 2022/11/02 16:06:24 - mmengine - INFO - Epoch(train) [368][60/63] lr: 1.5569e-03 eta: 8:31:22 time: 0.5094 data_time: 0.0107 memory: 14901 loss: 1.5302 loss_prob: 0.8576 loss_thr: 0.5329 loss_db: 0.1398 2022/11/02 16:06:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:06:31 - mmengine - INFO - Epoch(train) [369][5/63] lr: 1.5552e-03 eta: 8:31:22 time: 0.7827 data_time: 0.2917 memory: 14901 loss: 1.5022 loss_prob: 0.8274 loss_thr: 0.5374 loss_db: 0.1374 2022/11/02 16:06:33 - mmengine - INFO - Epoch(train) [369][10/63] lr: 1.5552e-03 eta: 8:31:16 time: 0.8009 data_time: 0.2915 memory: 14901 loss: 1.5647 loss_prob: 0.8699 loss_thr: 0.5494 loss_db: 0.1454 2022/11/02 16:06:36 - mmengine - INFO - Epoch(train) [369][15/63] lr: 1.5552e-03 eta: 8:31:16 time: 0.4993 data_time: 0.0054 memory: 14901 loss: 1.5222 loss_prob: 0.8405 loss_thr: 0.5416 loss_db: 0.1401 2022/11/02 16:06:38 - mmengine - INFO - Epoch(train) [369][20/63] lr: 1.5552e-03 eta: 8:31:08 time: 0.5097 data_time: 0.0053 memory: 14901 loss: 1.6409 loss_prob: 0.9479 loss_thr: 0.5455 loss_db: 0.1476 2022/11/02 16:06:41 - mmengine - INFO - Epoch(train) [369][25/63] lr: 1.5552e-03 eta: 8:31:08 time: 0.5684 data_time: 0.0585 memory: 14901 loss: 1.6155 loss_prob: 0.9343 loss_thr: 0.5317 loss_db: 0.1495 2022/11/02 16:06:44 - mmengine - INFO - Epoch(train) [369][30/63] lr: 1.5552e-03 eta: 8:31:02 time: 0.5903 data_time: 0.0584 memory: 14901 loss: 1.5514 loss_prob: 0.8551 loss_thr: 0.5540 loss_db: 0.1423 2022/11/02 16:06:47 - mmengine - INFO - Epoch(train) [369][35/63] lr: 1.5552e-03 eta: 8:31:02 time: 0.5186 data_time: 0.0067 memory: 14901 loss: 1.5649 loss_prob: 0.8679 loss_thr: 0.5558 loss_db: 0.1412 2022/11/02 16:06:49 - mmengine - INFO - Epoch(train) [369][40/63] lr: 1.5552e-03 eta: 8:30:55 time: 0.5170 data_time: 0.0069 memory: 14901 loss: 1.4847 loss_prob: 0.8141 loss_thr: 0.5342 loss_db: 0.1363 2022/11/02 16:06:52 - mmengine - INFO - Epoch(train) [369][45/63] lr: 1.5552e-03 eta: 8:30:55 time: 0.5309 data_time: 0.0069 memory: 14901 loss: 1.4827 loss_prob: 0.8026 loss_thr: 0.5464 loss_db: 0.1337 2022/11/02 16:06:55 - mmengine - INFO - Epoch(train) [369][50/63] lr: 1.5552e-03 eta: 8:30:49 time: 0.5670 data_time: 0.0487 memory: 14901 loss: 1.5030 loss_prob: 0.8327 loss_thr: 0.5349 loss_db: 0.1354 2022/11/02 16:06:58 - mmengine - INFO - Epoch(train) [369][55/63] lr: 1.5552e-03 eta: 8:30:49 time: 0.5630 data_time: 0.0473 memory: 14901 loss: 1.4979 loss_prob: 0.8356 loss_thr: 0.5253 loss_db: 0.1370 2022/11/02 16:07:00 - mmengine - INFO - Epoch(train) [369][60/63] lr: 1.5552e-03 eta: 8:30:41 time: 0.5265 data_time: 0.0074 memory: 14901 loss: 1.4690 loss_prob: 0.8208 loss_thr: 0.5113 loss_db: 0.1369 2022/11/02 16:07:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:07:08 - mmengine - INFO - Epoch(train) [370][5/63] lr: 1.5535e-03 eta: 8:30:41 time: 0.8986 data_time: 0.3695 memory: 14901 loss: 1.3830 loss_prob: 0.7557 loss_thr: 0.5016 loss_db: 0.1257 2022/11/02 16:07:11 - mmengine - INFO - Epoch(train) [370][10/63] lr: 1.5535e-03 eta: 8:30:38 time: 0.9306 data_time: 0.3691 memory: 14901 loss: 1.4151 loss_prob: 0.7764 loss_thr: 0.5085 loss_db: 0.1302 2022/11/02 16:07:14 - mmengine - INFO - Epoch(train) [370][15/63] lr: 1.5535e-03 eta: 8:30:38 time: 0.5421 data_time: 0.0108 memory: 14901 loss: 1.5280 loss_prob: 0.8618 loss_thr: 0.5222 loss_db: 0.1440 2022/11/02 16:07:16 - mmengine - INFO - Epoch(train) [370][20/63] lr: 1.5535e-03 eta: 8:30:30 time: 0.5257 data_time: 0.0091 memory: 14901 loss: 1.5851 loss_prob: 0.8904 loss_thr: 0.5438 loss_db: 0.1509 2022/11/02 16:07:19 - mmengine - INFO - Epoch(train) [370][25/63] lr: 1.5535e-03 eta: 8:30:30 time: 0.5559 data_time: 0.0376 memory: 14901 loss: 1.5090 loss_prob: 0.8279 loss_thr: 0.5408 loss_db: 0.1403 2022/11/02 16:07:23 - mmengine - INFO - Epoch(train) [370][30/63] lr: 1.5535e-03 eta: 8:30:28 time: 0.7208 data_time: 0.0463 memory: 14901 loss: 1.4079 loss_prob: 0.7608 loss_thr: 0.5167 loss_db: 0.1303 2022/11/02 16:07:26 - mmengine - INFO - Epoch(train) [370][35/63] lr: 1.5535e-03 eta: 8:30:28 time: 0.6923 data_time: 0.0141 memory: 14901 loss: 1.4230 loss_prob: 0.7744 loss_thr: 0.5178 loss_db: 0.1309 2022/11/02 16:07:29 - mmengine - INFO - Epoch(train) [370][40/63] lr: 1.5535e-03 eta: 8:30:22 time: 0.5773 data_time: 0.0063 memory: 14901 loss: 1.4056 loss_prob: 0.7616 loss_thr: 0.5178 loss_db: 0.1263 2022/11/02 16:07:32 - mmengine - INFO - Epoch(train) [370][45/63] lr: 1.5535e-03 eta: 8:30:22 time: 0.5972 data_time: 0.0098 memory: 14901 loss: 1.4005 loss_prob: 0.7528 loss_thr: 0.5210 loss_db: 0.1267 2022/11/02 16:07:35 - mmengine - INFO - Epoch(train) [370][50/63] lr: 1.5535e-03 eta: 8:30:17 time: 0.6377 data_time: 0.0298 memory: 14901 loss: 1.4514 loss_prob: 0.7859 loss_thr: 0.5341 loss_db: 0.1314 2022/11/02 16:07:39 - mmengine - INFO - Epoch(train) [370][55/63] lr: 1.5535e-03 eta: 8:30:17 time: 0.6704 data_time: 0.0319 memory: 14901 loss: 1.4595 loss_prob: 0.8010 loss_thr: 0.5268 loss_db: 0.1316 2022/11/02 16:07:41 - mmengine - INFO - Epoch(train) [370][60/63] lr: 1.5535e-03 eta: 8:30:11 time: 0.5736 data_time: 0.0142 memory: 14901 loss: 1.4438 loss_prob: 0.7928 loss_thr: 0.5178 loss_db: 0.1332 2022/11/02 16:07:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:07:49 - mmengine - INFO - Epoch(train) [371][5/63] lr: 1.5518e-03 eta: 8:30:11 time: 0.8921 data_time: 0.2969 memory: 14901 loss: 1.5067 loss_prob: 0.8326 loss_thr: 0.5358 loss_db: 0.1383 2022/11/02 16:07:53 - mmengine - INFO - Epoch(train) [371][10/63] lr: 1.5518e-03 eta: 8:30:09 time: 1.0279 data_time: 0.2911 memory: 14901 loss: 1.4254 loss_prob: 0.7757 loss_thr: 0.5176 loss_db: 0.1321 2022/11/02 16:07:55 - mmengine - INFO - Epoch(train) [371][15/63] lr: 1.5518e-03 eta: 8:30:09 time: 0.6375 data_time: 0.0089 memory: 14901 loss: 1.4481 loss_prob: 0.7789 loss_thr: 0.5339 loss_db: 0.1354 2022/11/02 16:07:58 - mmengine - INFO - Epoch(train) [371][20/63] lr: 1.5518e-03 eta: 8:30:03 time: 0.5504 data_time: 0.0095 memory: 14901 loss: 1.4378 loss_prob: 0.7757 loss_thr: 0.5280 loss_db: 0.1341 2022/11/02 16:08:01 - mmengine - INFO - Epoch(train) [371][25/63] lr: 1.5518e-03 eta: 8:30:03 time: 0.5978 data_time: 0.0086 memory: 14901 loss: 1.5413 loss_prob: 0.8662 loss_thr: 0.5311 loss_db: 0.1440 2022/11/02 16:08:05 - mmengine - INFO - Epoch(train) [371][30/63] lr: 1.5518e-03 eta: 8:29:58 time: 0.6200 data_time: 0.0227 memory: 14901 loss: 1.5673 loss_prob: 0.8807 loss_thr: 0.5405 loss_db: 0.1462 2022/11/02 16:08:07 - mmengine - INFO - Epoch(train) [371][35/63] lr: 1.5518e-03 eta: 8:29:58 time: 0.6033 data_time: 0.0243 memory: 14901 loss: 1.5311 loss_prob: 0.8449 loss_thr: 0.5440 loss_db: 0.1423 2022/11/02 16:08:10 - mmengine - INFO - Epoch(train) [371][40/63] lr: 1.5518e-03 eta: 8:29:51 time: 0.5388 data_time: 0.0093 memory: 14901 loss: 1.4586 loss_prob: 0.8020 loss_thr: 0.5223 loss_db: 0.1343 2022/11/02 16:08:13 - mmengine - INFO - Epoch(train) [371][45/63] lr: 1.5518e-03 eta: 8:29:51 time: 0.5650 data_time: 0.0139 memory: 14901 loss: 1.4389 loss_prob: 0.7992 loss_thr: 0.5077 loss_db: 0.1321 2022/11/02 16:08:16 - mmengine - INFO - Epoch(train) [371][50/63] lr: 1.5518e-03 eta: 8:29:44 time: 0.5682 data_time: 0.0130 memory: 14901 loss: 1.6165 loss_prob: 0.9192 loss_thr: 0.5474 loss_db: 0.1499 2022/11/02 16:08:18 - mmengine - INFO - Epoch(train) [371][55/63] lr: 1.5518e-03 eta: 8:29:44 time: 0.5386 data_time: 0.0240 memory: 14901 loss: 1.6289 loss_prob: 0.9195 loss_thr: 0.5557 loss_db: 0.1536 2022/11/02 16:08:22 - mmengine - INFO - Epoch(train) [371][60/63] lr: 1.5518e-03 eta: 8:29:39 time: 0.5909 data_time: 0.0249 memory: 14901 loss: 1.4838 loss_prob: 0.8157 loss_thr: 0.5304 loss_db: 0.1378 2022/11/02 16:08:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:08:29 - mmengine - INFO - Epoch(train) [372][5/63] lr: 1.5501e-03 eta: 8:29:39 time: 0.8957 data_time: 0.2485 memory: 14901 loss: 1.6275 loss_prob: 0.9252 loss_thr: 0.5458 loss_db: 0.1566 2022/11/02 16:08:32 - mmengine - INFO - Epoch(train) [372][10/63] lr: 1.5501e-03 eta: 8:29:34 time: 0.9040 data_time: 0.2560 memory: 14901 loss: 1.5717 loss_prob: 0.8847 loss_thr: 0.5368 loss_db: 0.1501 2022/11/02 16:08:36 - mmengine - INFO - Epoch(train) [372][15/63] lr: 1.5501e-03 eta: 8:29:34 time: 0.6446 data_time: 0.0208 memory: 14901 loss: 1.5201 loss_prob: 0.8525 loss_thr: 0.5233 loss_db: 0.1444 2022/11/02 16:08:39 - mmengine - INFO - Epoch(train) [372][20/63] lr: 1.5501e-03 eta: 8:29:30 time: 0.6393 data_time: 0.0134 memory: 14901 loss: 1.4569 loss_prob: 0.8038 loss_thr: 0.5165 loss_db: 0.1367 2022/11/02 16:08:42 - mmengine - INFO - Epoch(train) [372][25/63] lr: 1.5501e-03 eta: 8:29:30 time: 0.6087 data_time: 0.0433 memory: 14901 loss: 1.4785 loss_prob: 0.8075 loss_thr: 0.5364 loss_db: 0.1345 2022/11/02 16:08:44 - mmengine - INFO - Epoch(train) [372][30/63] lr: 1.5501e-03 eta: 8:29:24 time: 0.5812 data_time: 0.0435 memory: 14901 loss: 1.8733 loss_prob: 1.0737 loss_thr: 0.6216 loss_db: 0.1779 2022/11/02 16:08:47 - mmengine - INFO - Epoch(train) [372][35/63] lr: 1.5501e-03 eta: 8:29:24 time: 0.5635 data_time: 0.0228 memory: 14901 loss: 2.4253 loss_prob: 1.5417 loss_thr: 0.6300 loss_db: 0.2537 2022/11/02 16:08:50 - mmengine - INFO - Epoch(train) [372][40/63] lr: 1.5501e-03 eta: 8:29:18 time: 0.5825 data_time: 0.0233 memory: 14901 loss: 2.2630 loss_prob: 1.4514 loss_thr: 0.5717 loss_db: 0.2400 2022/11/02 16:08:53 - mmengine - INFO - Epoch(train) [372][45/63] lr: 1.5501e-03 eta: 8:29:18 time: 0.5793 data_time: 0.0105 memory: 14901 loss: 1.8783 loss_prob: 1.1001 loss_thr: 0.5930 loss_db: 0.1852 2022/11/02 16:08:57 - mmengine - INFO - Epoch(train) [372][50/63] lr: 1.5501e-03 eta: 8:29:13 time: 0.6362 data_time: 0.0223 memory: 14901 loss: 1.8007 loss_prob: 1.0327 loss_thr: 0.5969 loss_db: 0.1711 2022/11/02 16:08:59 - mmengine - INFO - Epoch(train) [372][55/63] lr: 1.5501e-03 eta: 8:29:13 time: 0.5857 data_time: 0.0221 memory: 14901 loss: 1.7029 loss_prob: 0.9745 loss_thr: 0.5668 loss_db: 0.1615 2022/11/02 16:09:02 - mmengine - INFO - Epoch(train) [372][60/63] lr: 1.5501e-03 eta: 8:29:07 time: 0.5658 data_time: 0.0173 memory: 14901 loss: 1.6422 loss_prob: 0.9339 loss_thr: 0.5505 loss_db: 0.1578 2022/11/02 16:09:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:09:09 - mmengine - INFO - Epoch(train) [373][5/63] lr: 1.5484e-03 eta: 8:29:07 time: 0.8001 data_time: 0.2451 memory: 14901 loss: 1.5856 loss_prob: 0.8897 loss_thr: 0.5461 loss_db: 0.1498 2022/11/02 16:09:12 - mmengine - INFO - Epoch(train) [373][10/63] lr: 1.5484e-03 eta: 8:29:02 time: 0.8889 data_time: 0.2455 memory: 14901 loss: 1.5244 loss_prob: 0.8517 loss_thr: 0.5263 loss_db: 0.1465 2022/11/02 16:09:15 - mmengine - INFO - Epoch(train) [373][15/63] lr: 1.5484e-03 eta: 8:29:02 time: 0.5812 data_time: 0.0102 memory: 14901 loss: 1.7443 loss_prob: 1.0213 loss_thr: 0.5565 loss_db: 0.1665 2022/11/02 16:09:17 - mmengine - INFO - Epoch(train) [373][20/63] lr: 1.5484e-03 eta: 8:28:54 time: 0.5092 data_time: 0.0104 memory: 14901 loss: 1.7811 loss_prob: 1.0571 loss_thr: 0.5555 loss_db: 0.1685 2022/11/02 16:09:20 - mmengine - INFO - Epoch(train) [373][25/63] lr: 1.5484e-03 eta: 8:28:54 time: 0.5341 data_time: 0.0162 memory: 14901 loss: 1.5224 loss_prob: 0.8475 loss_thr: 0.5331 loss_db: 0.1419 2022/11/02 16:09:23 - mmengine - INFO - Epoch(train) [373][30/63] lr: 1.5484e-03 eta: 8:28:48 time: 0.5642 data_time: 0.0366 memory: 14901 loss: 1.5802 loss_prob: 0.8886 loss_thr: 0.5405 loss_db: 0.1511 2022/11/02 16:09:26 - mmengine - INFO - Epoch(train) [373][35/63] lr: 1.5484e-03 eta: 8:28:48 time: 0.5329 data_time: 0.0298 memory: 14901 loss: 1.7253 loss_prob: 0.9951 loss_thr: 0.5642 loss_db: 0.1660 2022/11/02 16:09:28 - mmengine - INFO - Epoch(train) [373][40/63] lr: 1.5484e-03 eta: 8:28:40 time: 0.4934 data_time: 0.0050 memory: 14901 loss: 1.7326 loss_prob: 0.9916 loss_thr: 0.5789 loss_db: 0.1622 2022/11/02 16:09:31 - mmengine - INFO - Epoch(train) [373][45/63] lr: 1.5484e-03 eta: 8:28:40 time: 0.5194 data_time: 0.0132 memory: 14901 loss: 1.9937 loss_prob: 1.2130 loss_thr: 0.5934 loss_db: 0.1873 2022/11/02 16:09:34 - mmengine - INFO - Epoch(train) [373][50/63] lr: 1.5484e-03 eta: 8:28:34 time: 0.5563 data_time: 0.0258 memory: 14901 loss: 1.9926 loss_prob: 1.2004 loss_thr: 0.6068 loss_db: 0.1855 2022/11/02 16:09:36 - mmengine - INFO - Epoch(train) [373][55/63] lr: 1.5484e-03 eta: 8:28:34 time: 0.5619 data_time: 0.0282 memory: 14901 loss: 1.7844 loss_prob: 1.0441 loss_thr: 0.5807 loss_db: 0.1597 2022/11/02 16:09:39 - mmengine - INFO - Epoch(train) [373][60/63] lr: 1.5484e-03 eta: 8:28:27 time: 0.5620 data_time: 0.0228 memory: 14901 loss: 1.7616 loss_prob: 1.0495 loss_thr: 0.5522 loss_db: 0.1599 2022/11/02 16:09:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:09:46 - mmengine - INFO - Epoch(train) [374][5/63] lr: 1.5468e-03 eta: 8:28:27 time: 0.7708 data_time: 0.2413 memory: 14901 loss: 1.6428 loss_prob: 0.9399 loss_thr: 0.5494 loss_db: 0.1534 2022/11/02 16:09:50 - mmengine - INFO - Epoch(train) [374][10/63] lr: 1.5468e-03 eta: 8:28:24 time: 0.9736 data_time: 0.2608 memory: 14901 loss: 1.5838 loss_prob: 0.8726 loss_thr: 0.5655 loss_db: 0.1456 2022/11/02 16:09:53 - mmengine - INFO - Epoch(train) [374][15/63] lr: 1.5468e-03 eta: 8:28:24 time: 0.7005 data_time: 0.0273 memory: 14901 loss: 1.6268 loss_prob: 0.9059 loss_thr: 0.5667 loss_db: 0.1541 2022/11/02 16:09:56 - mmengine - INFO - Epoch(train) [374][20/63] lr: 1.5468e-03 eta: 8:28:18 time: 0.5622 data_time: 0.0073 memory: 14901 loss: 1.5348 loss_prob: 0.8652 loss_thr: 0.5275 loss_db: 0.1421 2022/11/02 16:09:59 - mmengine - INFO - Epoch(train) [374][25/63] lr: 1.5468e-03 eta: 8:28:18 time: 0.6542 data_time: 0.0245 memory: 14901 loss: 1.5261 loss_prob: 0.8546 loss_thr: 0.5331 loss_db: 0.1384 2022/11/02 16:10:02 - mmengine - INFO - Epoch(train) [374][30/63] lr: 1.5468e-03 eta: 8:28:14 time: 0.6571 data_time: 0.0328 memory: 14901 loss: 1.5713 loss_prob: 0.8852 loss_thr: 0.5385 loss_db: 0.1475 2022/11/02 16:10:05 - mmengine - INFO - Epoch(train) [374][35/63] lr: 1.5468e-03 eta: 8:28:14 time: 0.6239 data_time: 0.0213 memory: 14901 loss: 1.6007 loss_prob: 0.9066 loss_thr: 0.5445 loss_db: 0.1497 2022/11/02 16:10:08 - mmengine - INFO - Epoch(train) [374][40/63] lr: 1.5468e-03 eta: 8:28:07 time: 0.5547 data_time: 0.0121 memory: 14901 loss: 1.5625 loss_prob: 0.8699 loss_thr: 0.5466 loss_db: 0.1460 2022/11/02 16:10:11 - mmengine - INFO - Epoch(train) [374][45/63] lr: 1.5468e-03 eta: 8:28:07 time: 0.5252 data_time: 0.0078 memory: 14901 loss: 1.8547 loss_prob: 1.0957 loss_thr: 0.5792 loss_db: 0.1799 2022/11/02 16:10:14 - mmengine - INFO - Epoch(train) [374][50/63] lr: 1.5468e-03 eta: 8:28:01 time: 0.5708 data_time: 0.0257 memory: 14901 loss: 1.8152 loss_prob: 1.0751 loss_thr: 0.5670 loss_db: 0.1732 2022/11/02 16:10:16 - mmengine - INFO - Epoch(train) [374][55/63] lr: 1.5468e-03 eta: 8:28:01 time: 0.5593 data_time: 0.0426 memory: 14901 loss: 1.5140 loss_prob: 0.8510 loss_thr: 0.5222 loss_db: 0.1408 2022/11/02 16:10:20 - mmengine - INFO - Epoch(train) [374][60/63] lr: 1.5468e-03 eta: 8:27:57 time: 0.6535 data_time: 0.0257 memory: 14901 loss: 1.5871 loss_prob: 0.9028 loss_thr: 0.5349 loss_db: 0.1493 2022/11/02 16:10:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:10:28 - mmengine - INFO - Epoch(train) [375][5/63] lr: 1.5451e-03 eta: 8:27:57 time: 0.8941 data_time: 0.2095 memory: 14901 loss: 1.5487 loss_prob: 0.8660 loss_thr: 0.5348 loss_db: 0.1478 2022/11/02 16:10:31 - mmengine - INFO - Epoch(train) [375][10/63] lr: 1.5451e-03 eta: 8:27:54 time: 0.9795 data_time: 0.2186 memory: 14901 loss: 1.4703 loss_prob: 0.8215 loss_thr: 0.5118 loss_db: 0.1370 2022/11/02 16:10:35 - mmengine - INFO - Epoch(train) [375][15/63] lr: 1.5451e-03 eta: 8:27:54 time: 0.7377 data_time: 0.0171 memory: 14901 loss: 1.4882 loss_prob: 0.8474 loss_thr: 0.5009 loss_db: 0.1399 2022/11/02 16:10:38 - mmengine - INFO - Epoch(train) [375][20/63] lr: 1.5451e-03 eta: 8:27:50 time: 0.6706 data_time: 0.0115 memory: 14901 loss: 1.5891 loss_prob: 0.8933 loss_thr: 0.5481 loss_db: 0.1477 2022/11/02 16:10:42 - mmengine - INFO - Epoch(train) [375][25/63] lr: 1.5451e-03 eta: 8:27:50 time: 0.6394 data_time: 0.0553 memory: 14901 loss: 1.6118 loss_prob: 0.8986 loss_thr: 0.5618 loss_db: 0.1513 2022/11/02 16:10:45 - mmengine - INFO - Epoch(train) [375][30/63] lr: 1.5451e-03 eta: 8:27:46 time: 0.6688 data_time: 0.0505 memory: 14901 loss: 1.5899 loss_prob: 0.8984 loss_thr: 0.5361 loss_db: 0.1554 2022/11/02 16:10:47 - mmengine - INFO - Epoch(train) [375][35/63] lr: 1.5451e-03 eta: 8:27:46 time: 0.5531 data_time: 0.0059 memory: 14901 loss: 1.5857 loss_prob: 0.9069 loss_thr: 0.5274 loss_db: 0.1514 2022/11/02 16:10:50 - mmengine - INFO - Epoch(train) [375][40/63] lr: 1.5451e-03 eta: 8:27:38 time: 0.5067 data_time: 0.0085 memory: 14901 loss: 1.5492 loss_prob: 0.8843 loss_thr: 0.5206 loss_db: 0.1443 2022/11/02 16:10:53 - mmengine - INFO - Epoch(train) [375][45/63] lr: 1.5451e-03 eta: 8:27:38 time: 0.5554 data_time: 0.0094 memory: 14901 loss: 1.4803 loss_prob: 0.8290 loss_thr: 0.5173 loss_db: 0.1340 2022/11/02 16:10:56 - mmengine - INFO - Epoch(train) [375][50/63] lr: 1.5451e-03 eta: 8:27:32 time: 0.5768 data_time: 0.0234 memory: 14901 loss: 1.5071 loss_prob: 0.8375 loss_thr: 0.5296 loss_db: 0.1400 2022/11/02 16:10:58 - mmengine - INFO - Epoch(train) [375][55/63] lr: 1.5451e-03 eta: 8:27:32 time: 0.5568 data_time: 0.0243 memory: 14901 loss: 1.5663 loss_prob: 0.8724 loss_thr: 0.5461 loss_db: 0.1478 2022/11/02 16:11:01 - mmengine - INFO - Epoch(train) [375][60/63] lr: 1.5451e-03 eta: 8:27:25 time: 0.5224 data_time: 0.0072 memory: 14901 loss: 1.7104 loss_prob: 0.9856 loss_thr: 0.5711 loss_db: 0.1537 2022/11/02 16:11:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:11:08 - mmengine - INFO - Epoch(train) [376][5/63] lr: 1.5434e-03 eta: 8:27:25 time: 0.7890 data_time: 0.2691 memory: 14901 loss: 1.9256 loss_prob: 1.1563 loss_thr: 0.5879 loss_db: 0.1814 2022/11/02 16:11:11 - mmengine - INFO - Epoch(train) [376][10/63] lr: 1.5434e-03 eta: 8:27:20 time: 0.8968 data_time: 0.2644 memory: 14901 loss: 2.0133 loss_prob: 1.2195 loss_thr: 0.6028 loss_db: 0.1909 2022/11/02 16:11:14 - mmengine - INFO - Epoch(train) [376][15/63] lr: 1.5434e-03 eta: 8:27:20 time: 0.6682 data_time: 0.0133 memory: 14901 loss: 1.8424 loss_prob: 1.0763 loss_thr: 0.5836 loss_db: 0.1826 2022/11/02 16:11:18 - mmengine - INFO - Epoch(train) [376][20/63] lr: 1.5434e-03 eta: 8:27:16 time: 0.6550 data_time: 0.0111 memory: 14901 loss: 1.7364 loss_prob: 1.0141 loss_thr: 0.5500 loss_db: 0.1723 2022/11/02 16:11:21 - mmengine - INFO - Epoch(train) [376][25/63] lr: 1.5434e-03 eta: 8:27:16 time: 0.6886 data_time: 0.0519 memory: 14901 loss: 1.7804 loss_prob: 1.0670 loss_thr: 0.5439 loss_db: 0.1694 2022/11/02 16:11:24 - mmengine - INFO - Epoch(train) [376][30/63] lr: 1.5434e-03 eta: 8:27:11 time: 0.6151 data_time: 0.0527 memory: 14901 loss: 1.9435 loss_prob: 1.1909 loss_thr: 0.5635 loss_db: 0.1891 2022/11/02 16:11:27 - mmengine - INFO - Epoch(train) [376][35/63] lr: 1.5434e-03 eta: 8:27:11 time: 0.5707 data_time: 0.0141 memory: 14901 loss: 1.8692 loss_prob: 1.0814 loss_thr: 0.6105 loss_db: 0.1773 2022/11/02 16:11:30 - mmengine - INFO - Epoch(train) [376][40/63] lr: 1.5434e-03 eta: 8:27:04 time: 0.5627 data_time: 0.0136 memory: 14901 loss: 1.7300 loss_prob: 0.9753 loss_thr: 0.5939 loss_db: 0.1608 2022/11/02 16:11:33 - mmengine - INFO - Epoch(train) [376][45/63] lr: 1.5434e-03 eta: 8:27:04 time: 0.5872 data_time: 0.0071 memory: 14901 loss: 1.6338 loss_prob: 0.9315 loss_thr: 0.5499 loss_db: 0.1523 2022/11/02 16:11:36 - mmengine - INFO - Epoch(train) [376][50/63] lr: 1.5434e-03 eta: 8:26:59 time: 0.6259 data_time: 0.0285 memory: 14901 loss: 1.7061 loss_prob: 0.9727 loss_thr: 0.5746 loss_db: 0.1588 2022/11/02 16:11:39 - mmengine - INFO - Epoch(train) [376][55/63] lr: 1.5434e-03 eta: 8:26:59 time: 0.6236 data_time: 0.0288 memory: 14901 loss: 1.7129 loss_prob: 0.9852 loss_thr: 0.5617 loss_db: 0.1659 2022/11/02 16:11:42 - mmengine - INFO - Epoch(train) [376][60/63] lr: 1.5434e-03 eta: 8:26:54 time: 0.5992 data_time: 0.0107 memory: 14901 loss: 1.6331 loss_prob: 0.9412 loss_thr: 0.5335 loss_db: 0.1584 2022/11/02 16:11:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:11:49 - mmengine - INFO - Epoch(train) [377][5/63] lr: 1.5417e-03 eta: 8:26:54 time: 0.8663 data_time: 0.2249 memory: 14901 loss: 1.6366 loss_prob: 0.9261 loss_thr: 0.5525 loss_db: 0.1579 2022/11/02 16:11:52 - mmengine - INFO - Epoch(train) [377][10/63] lr: 1.5417e-03 eta: 8:26:49 time: 0.8739 data_time: 0.2383 memory: 14901 loss: 1.5725 loss_prob: 0.8720 loss_thr: 0.5496 loss_db: 0.1509 2022/11/02 16:11:55 - mmengine - INFO - Epoch(train) [377][15/63] lr: 1.5417e-03 eta: 8:26:49 time: 0.5641 data_time: 0.0251 memory: 14901 loss: 1.6211 loss_prob: 0.9058 loss_thr: 0.5627 loss_db: 0.1525 2022/11/02 16:11:58 - mmengine - INFO - Epoch(train) [377][20/63] lr: 1.5417e-03 eta: 8:26:42 time: 0.5344 data_time: 0.0098 memory: 14901 loss: 1.6980 loss_prob: 0.9672 loss_thr: 0.5713 loss_db: 0.1595 2022/11/02 16:12:01 - mmengine - INFO - Epoch(train) [377][25/63] lr: 1.5417e-03 eta: 8:26:42 time: 0.6216 data_time: 0.0126 memory: 14901 loss: 1.5605 loss_prob: 0.8640 loss_thr: 0.5496 loss_db: 0.1468 2022/11/02 16:12:04 - mmengine - INFO - Epoch(train) [377][30/63] lr: 1.5417e-03 eta: 8:26:37 time: 0.6519 data_time: 0.0455 memory: 14901 loss: 1.5403 loss_prob: 0.8540 loss_thr: 0.5407 loss_db: 0.1456 2022/11/02 16:12:08 - mmengine - INFO - Epoch(train) [377][35/63] lr: 1.5417e-03 eta: 8:26:37 time: 0.6355 data_time: 0.0500 memory: 14901 loss: 1.5190 loss_prob: 0.8522 loss_thr: 0.5251 loss_db: 0.1417 2022/11/02 16:12:10 - mmengine - INFO - Epoch(train) [377][40/63] lr: 1.5417e-03 eta: 8:26:32 time: 0.6196 data_time: 0.0162 memory: 14901 loss: 1.4639 loss_prob: 0.8064 loss_thr: 0.5238 loss_db: 0.1337 2022/11/02 16:12:14 - mmengine - INFO - Epoch(train) [377][45/63] lr: 1.5417e-03 eta: 8:26:32 time: 0.6002 data_time: 0.0095 memory: 14901 loss: 1.5404 loss_prob: 0.8576 loss_thr: 0.5389 loss_db: 0.1438 2022/11/02 16:12:16 - mmengine - INFO - Epoch(train) [377][50/63] lr: 1.5417e-03 eta: 8:26:26 time: 0.5806 data_time: 0.0174 memory: 14901 loss: 1.6513 loss_prob: 0.9393 loss_thr: 0.5502 loss_db: 0.1617 2022/11/02 16:12:19 - mmengine - INFO - Epoch(train) [377][55/63] lr: 1.5417e-03 eta: 8:26:26 time: 0.5778 data_time: 0.0249 memory: 14901 loss: 1.5787 loss_prob: 0.8942 loss_thr: 0.5315 loss_db: 0.1529 2022/11/02 16:12:23 - mmengine - INFO - Epoch(train) [377][60/63] lr: 1.5417e-03 eta: 8:26:22 time: 0.6489 data_time: 0.0244 memory: 14901 loss: 1.5521 loss_prob: 0.8637 loss_thr: 0.5442 loss_db: 0.1442 2022/11/02 16:12:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:12:30 - mmengine - INFO - Epoch(train) [378][5/63] lr: 1.5400e-03 eta: 8:26:22 time: 0.9000 data_time: 0.2587 memory: 14901 loss: 1.5304 loss_prob: 0.8492 loss_thr: 0.5377 loss_db: 0.1435 2022/11/02 16:12:33 - mmengine - INFO - Epoch(train) [378][10/63] lr: 1.5400e-03 eta: 8:26:17 time: 0.8978 data_time: 0.2569 memory: 14901 loss: 1.5404 loss_prob: 0.8596 loss_thr: 0.5380 loss_db: 0.1429 2022/11/02 16:12:36 - mmengine - INFO - Epoch(train) [378][15/63] lr: 1.5400e-03 eta: 8:26:17 time: 0.5518 data_time: 0.0102 memory: 14901 loss: 1.5648 loss_prob: 0.8650 loss_thr: 0.5569 loss_db: 0.1429 2022/11/02 16:12:39 - mmengine - INFO - Epoch(train) [378][20/63] lr: 1.5400e-03 eta: 8:26:11 time: 0.5601 data_time: 0.0127 memory: 14901 loss: 1.6349 loss_prob: 0.9019 loss_thr: 0.5809 loss_db: 0.1521 2022/11/02 16:12:42 - mmengine - INFO - Epoch(train) [378][25/63] lr: 1.5400e-03 eta: 8:26:11 time: 0.6100 data_time: 0.0581 memory: 14901 loss: 1.6207 loss_prob: 0.8926 loss_thr: 0.5775 loss_db: 0.1506 2022/11/02 16:12:45 - mmengine - INFO - Epoch(train) [378][30/63] lr: 1.5400e-03 eta: 8:26:06 time: 0.6559 data_time: 0.0553 memory: 14901 loss: 1.4520 loss_prob: 0.7860 loss_thr: 0.5332 loss_db: 0.1328 2022/11/02 16:12:48 - mmengine - INFO - Epoch(train) [378][35/63] lr: 1.5400e-03 eta: 8:26:06 time: 0.6441 data_time: 0.0079 memory: 14901 loss: 1.4337 loss_prob: 0.7819 loss_thr: 0.5192 loss_db: 0.1326 2022/11/02 16:12:51 - mmengine - INFO - Epoch(train) [378][40/63] lr: 1.5400e-03 eta: 8:26:01 time: 0.5980 data_time: 0.0078 memory: 14901 loss: 1.4967 loss_prob: 0.8201 loss_thr: 0.5385 loss_db: 0.1381 2022/11/02 16:12:54 - mmengine - INFO - Epoch(train) [378][45/63] lr: 1.5400e-03 eta: 8:26:01 time: 0.5860 data_time: 0.0164 memory: 14901 loss: 1.4392 loss_prob: 0.7873 loss_thr: 0.5201 loss_db: 0.1318 2022/11/02 16:12:57 - mmengine - INFO - Epoch(train) [378][50/63] lr: 1.5400e-03 eta: 8:25:55 time: 0.6028 data_time: 0.0347 memory: 14901 loss: 1.4110 loss_prob: 0.7763 loss_thr: 0.5042 loss_db: 0.1305 2022/11/02 16:13:00 - mmengine - INFO - Epoch(train) [378][55/63] lr: 1.5400e-03 eta: 8:25:55 time: 0.6119 data_time: 0.0271 memory: 14901 loss: 1.4316 loss_prob: 0.8030 loss_thr: 0.4952 loss_db: 0.1334 2022/11/02 16:13:03 - mmengine - INFO - Epoch(train) [378][60/63] lr: 1.5400e-03 eta: 8:25:50 time: 0.6097 data_time: 0.0074 memory: 14901 loss: 1.4856 loss_prob: 0.8342 loss_thr: 0.5128 loss_db: 0.1385 2022/11/02 16:13:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:13:11 - mmengine - INFO - Epoch(train) [379][5/63] lr: 1.5383e-03 eta: 8:25:50 time: 0.8819 data_time: 0.2550 memory: 14901 loss: 1.5161 loss_prob: 0.8221 loss_thr: 0.5538 loss_db: 0.1403 2022/11/02 16:13:14 - mmengine - INFO - Epoch(train) [379][10/63] lr: 1.5383e-03 eta: 8:25:44 time: 0.8688 data_time: 0.2549 memory: 14901 loss: 1.4380 loss_prob: 0.7827 loss_thr: 0.5221 loss_db: 0.1332 2022/11/02 16:13:16 - mmengine - INFO - Epoch(train) [379][15/63] lr: 1.5383e-03 eta: 8:25:44 time: 0.5247 data_time: 0.0104 memory: 14901 loss: 1.3798 loss_prob: 0.7478 loss_thr: 0.5054 loss_db: 0.1266 2022/11/02 16:13:19 - mmengine - INFO - Epoch(train) [379][20/63] lr: 1.5383e-03 eta: 8:25:37 time: 0.4978 data_time: 0.0103 memory: 14901 loss: 1.3901 loss_prob: 0.7570 loss_thr: 0.5073 loss_db: 0.1258 2022/11/02 16:13:21 - mmengine - INFO - Epoch(train) [379][25/63] lr: 1.5383e-03 eta: 8:25:37 time: 0.5190 data_time: 0.0241 memory: 14901 loss: 1.4073 loss_prob: 0.7685 loss_thr: 0.5120 loss_db: 0.1269 2022/11/02 16:13:25 - mmengine - INFO - Epoch(train) [379][30/63] lr: 1.5383e-03 eta: 8:25:32 time: 0.6527 data_time: 0.0512 memory: 14901 loss: 1.4691 loss_prob: 0.8165 loss_thr: 0.5167 loss_db: 0.1359 2022/11/02 16:13:28 - mmengine - INFO - Epoch(train) [379][35/63] lr: 1.5383e-03 eta: 8:25:32 time: 0.6846 data_time: 0.0350 memory: 14901 loss: 1.5228 loss_prob: 0.8620 loss_thr: 0.5187 loss_db: 0.1421 2022/11/02 16:13:31 - mmengine - INFO - Epoch(train) [379][40/63] lr: 1.5383e-03 eta: 8:25:27 time: 0.6152 data_time: 0.0093 memory: 14901 loss: 1.5995 loss_prob: 0.9112 loss_thr: 0.5365 loss_db: 0.1518 2022/11/02 16:13:34 - mmengine - INFO - Epoch(train) [379][45/63] lr: 1.5383e-03 eta: 8:25:27 time: 0.5629 data_time: 0.0136 memory: 14901 loss: 1.6065 loss_prob: 0.9155 loss_thr: 0.5363 loss_db: 0.1548 2022/11/02 16:13:36 - mmengine - INFO - Epoch(train) [379][50/63] lr: 1.5383e-03 eta: 8:25:20 time: 0.5083 data_time: 0.0168 memory: 14901 loss: 1.5853 loss_prob: 0.8870 loss_thr: 0.5512 loss_db: 0.1471 2022/11/02 16:13:39 - mmengine - INFO - Epoch(train) [379][55/63] lr: 1.5383e-03 eta: 8:25:20 time: 0.5535 data_time: 0.0285 memory: 14901 loss: 1.4796 loss_prob: 0.7974 loss_thr: 0.5518 loss_db: 0.1304 2022/11/02 16:13:42 - mmengine - INFO - Epoch(train) [379][60/63] lr: 1.5383e-03 eta: 8:25:13 time: 0.5680 data_time: 0.0244 memory: 14901 loss: 1.4640 loss_prob: 0.7995 loss_thr: 0.5318 loss_db: 0.1328 2022/11/02 16:13:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:13:48 - mmengine - INFO - Epoch(train) [380][5/63] lr: 1.5366e-03 eta: 8:25:13 time: 0.7007 data_time: 0.2376 memory: 14901 loss: 1.4777 loss_prob: 0.8279 loss_thr: 0.5083 loss_db: 0.1416 2022/11/02 16:13:51 - mmengine - INFO - Epoch(train) [380][10/63] lr: 1.5366e-03 eta: 8:25:05 time: 0.7440 data_time: 0.2410 memory: 14901 loss: 1.5116 loss_prob: 0.8352 loss_thr: 0.5389 loss_db: 0.1376 2022/11/02 16:13:54 - mmengine - INFO - Epoch(train) [380][15/63] lr: 1.5366e-03 eta: 8:25:05 time: 0.5236 data_time: 0.0124 memory: 14901 loss: 1.5317 loss_prob: 0.8539 loss_thr: 0.5386 loss_db: 0.1392 2022/11/02 16:13:56 - mmengine - INFO - Epoch(train) [380][20/63] lr: 1.5366e-03 eta: 8:24:58 time: 0.5136 data_time: 0.0093 memory: 14901 loss: 1.5104 loss_prob: 0.8607 loss_thr: 0.5060 loss_db: 0.1437 2022/11/02 16:13:59 - mmengine - INFO - Epoch(train) [380][25/63] lr: 1.5366e-03 eta: 8:24:58 time: 0.5304 data_time: 0.0323 memory: 14901 loss: 1.4679 loss_prob: 0.8213 loss_thr: 0.5076 loss_db: 0.1390 2022/11/02 16:14:02 - mmengine - INFO - Epoch(train) [380][30/63] lr: 1.5366e-03 eta: 8:24:52 time: 0.5793 data_time: 0.0519 memory: 14901 loss: 1.4762 loss_prob: 0.8167 loss_thr: 0.5231 loss_db: 0.1363 2022/11/02 16:14:04 - mmengine - INFO - Epoch(train) [380][35/63] lr: 1.5366e-03 eta: 8:24:52 time: 0.5621 data_time: 0.0294 memory: 14901 loss: 1.6201 loss_prob: 0.9043 loss_thr: 0.5666 loss_db: 0.1493 2022/11/02 16:14:07 - mmengine - INFO - Epoch(train) [380][40/63] lr: 1.5366e-03 eta: 8:24:45 time: 0.5595 data_time: 0.0132 memory: 14901 loss: 1.5962 loss_prob: 0.8895 loss_thr: 0.5597 loss_db: 0.1469 2022/11/02 16:14:11 - mmengine - INFO - Epoch(train) [380][45/63] lr: 1.5366e-03 eta: 8:24:45 time: 0.6155 data_time: 0.0095 memory: 14901 loss: 1.4741 loss_prob: 0.8124 loss_thr: 0.5260 loss_db: 0.1357 2022/11/02 16:14:13 - mmengine - INFO - Epoch(train) [380][50/63] lr: 1.5366e-03 eta: 8:24:40 time: 0.5867 data_time: 0.0185 memory: 14901 loss: 1.4187 loss_prob: 0.7774 loss_thr: 0.5128 loss_db: 0.1286 2022/11/02 16:14:16 - mmengine - INFO - Epoch(train) [380][55/63] lr: 1.5366e-03 eta: 8:24:40 time: 0.5711 data_time: 0.0271 memory: 14901 loss: 1.4945 loss_prob: 0.8200 loss_thr: 0.5406 loss_db: 0.1340 2022/11/02 16:14:20 - mmengine - INFO - Epoch(train) [380][60/63] lr: 1.5366e-03 eta: 8:24:35 time: 0.6367 data_time: 0.0237 memory: 14901 loss: 1.5207 loss_prob: 0.8377 loss_thr: 0.5435 loss_db: 0.1396 2022/11/02 16:14:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:14:21 - mmengine - INFO - Saving checkpoint at 380 epochs 2022/11/02 16:14:25 - mmengine - INFO - Epoch(val) [380][5/500] eta: 8:24:35 time: 0.0492 data_time: 0.0057 memory: 14901 2022/11/02 16:14:25 - mmengine - INFO - Epoch(val) [380][10/500] eta: 0:00:24 time: 0.0509 data_time: 0.0056 memory: 1008 2022/11/02 16:14:25 - mmengine - INFO - Epoch(val) [380][15/500] eta: 0:00:24 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/02 16:14:25 - mmengine - INFO - Epoch(val) [380][20/500] eta: 0:00:19 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 16:14:26 - mmengine - INFO - Epoch(val) [380][25/500] eta: 0:00:19 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 16:14:26 - mmengine - INFO - Epoch(val) [380][30/500] eta: 0:00:20 time: 0.0431 data_time: 0.0026 memory: 1008 2022/11/02 16:14:26 - mmengine - INFO - Epoch(val) [380][35/500] eta: 0:00:20 time: 0.0444 data_time: 0.0029 memory: 1008 2022/11/02 16:14:26 - mmengine - INFO - Epoch(val) [380][40/500] eta: 0:00:19 time: 0.0426 data_time: 0.0029 memory: 1008 2022/11/02 16:14:26 - mmengine - INFO - Epoch(val) [380][45/500] eta: 0:00:19 time: 0.0437 data_time: 0.0026 memory: 1008 2022/11/02 16:14:27 - mmengine - INFO - Epoch(val) [380][50/500] eta: 0:00:20 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 16:14:27 - mmengine - INFO - Epoch(val) [380][55/500] eta: 0:00:20 time: 0.0495 data_time: 0.0035 memory: 1008 2022/11/02 16:14:27 - mmengine - INFO - Epoch(val) [380][60/500] eta: 0:00:19 time: 0.0450 data_time: 0.0041 memory: 1008 2022/11/02 16:14:27 - mmengine - INFO - Epoch(val) [380][65/500] eta: 0:00:19 time: 0.0448 data_time: 0.0037 memory: 1008 2022/11/02 16:14:28 - mmengine - INFO - Epoch(val) [380][70/500] eta: 0:00:20 time: 0.0466 data_time: 0.0028 memory: 1008 2022/11/02 16:14:28 - mmengine - INFO - Epoch(val) [380][75/500] eta: 0:00:20 time: 0.0436 data_time: 0.0030 memory: 1008 2022/11/02 16:14:28 - mmengine - INFO - Epoch(val) [380][80/500] eta: 0:00:17 time: 0.0408 data_time: 0.0031 memory: 1008 2022/11/02 16:14:28 - mmengine - INFO - Epoch(val) [380][85/500] eta: 0:00:17 time: 0.0366 data_time: 0.0029 memory: 1008 2022/11/02 16:14:28 - mmengine - INFO - Epoch(val) [380][90/500] eta: 0:00:16 time: 0.0407 data_time: 0.0029 memory: 1008 2022/11/02 16:14:29 - mmengine - INFO - Epoch(val) [380][95/500] eta: 0:00:16 time: 0.0430 data_time: 0.0029 memory: 1008 2022/11/02 16:14:29 - mmengine - INFO - Epoch(val) [380][100/500] eta: 0:00:15 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 16:14:29 - mmengine - INFO - Epoch(val) [380][105/500] eta: 0:00:15 time: 0.0379 data_time: 0.0027 memory: 1008 2022/11/02 16:14:29 - mmengine - INFO - Epoch(val) [380][110/500] eta: 0:00:15 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 16:14:29 - mmengine - INFO - Epoch(val) [380][115/500] eta: 0:00:15 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 16:14:30 - mmengine - INFO - Epoch(val) [380][120/500] eta: 0:00:16 time: 0.0432 data_time: 0.0029 memory: 1008 2022/11/02 16:14:30 - mmengine - INFO - Epoch(val) [380][125/500] eta: 0:00:16 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 16:14:30 - mmengine - INFO - Epoch(val) [380][130/500] eta: 0:00:13 time: 0.0377 data_time: 0.0031 memory: 1008 2022/11/02 16:14:30 - mmengine - INFO - Epoch(val) [380][135/500] eta: 0:00:13 time: 0.0397 data_time: 0.0032 memory: 1008 2022/11/02 16:14:30 - mmengine - INFO - Epoch(val) [380][140/500] eta: 0:00:15 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/02 16:14:31 - mmengine - INFO - Epoch(val) [380][145/500] eta: 0:00:15 time: 0.0438 data_time: 0.0031 memory: 1008 2022/11/02 16:14:31 - mmengine - INFO - Epoch(val) [380][150/500] eta: 0:00:16 time: 0.0473 data_time: 0.0030 memory: 1008 2022/11/02 16:14:31 - mmengine - INFO - Epoch(val) [380][155/500] eta: 0:00:16 time: 0.0482 data_time: 0.0029 memory: 1008 2022/11/02 16:14:31 - mmengine - INFO - Epoch(val) [380][160/500] eta: 0:00:14 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 16:14:32 - mmengine - INFO - Epoch(val) [380][165/500] eta: 0:00:14 time: 0.0417 data_time: 0.0027 memory: 1008 2022/11/02 16:14:32 - mmengine - INFO - Epoch(val) [380][170/500] eta: 0:00:15 time: 0.0475 data_time: 0.0031 memory: 1008 2022/11/02 16:14:32 - mmengine - INFO - Epoch(val) [380][175/500] eta: 0:00:15 time: 0.0463 data_time: 0.0034 memory: 1008 2022/11/02 16:14:32 - mmengine - INFO - Epoch(val) [380][180/500] eta: 0:00:13 time: 0.0425 data_time: 0.0032 memory: 1008 2022/11/02 16:14:32 - mmengine - INFO - Epoch(val) [380][185/500] eta: 0:00:13 time: 0.0427 data_time: 0.0030 memory: 1008 2022/11/02 16:14:33 - mmengine - INFO - Epoch(val) [380][190/500] eta: 0:00:13 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/02 16:14:33 - mmengine - INFO - Epoch(val) [380][195/500] eta: 0:00:13 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 16:14:33 - mmengine - INFO - Epoch(val) [380][200/500] eta: 0:00:13 time: 0.0437 data_time: 0.0025 memory: 1008 2022/11/02 16:14:33 - mmengine - INFO - Epoch(val) [380][205/500] eta: 0:00:13 time: 0.0459 data_time: 0.0025 memory: 1008 2022/11/02 16:14:34 - mmengine - INFO - Epoch(val) [380][210/500] eta: 0:00:10 time: 0.0372 data_time: 0.0025 memory: 1008 2022/11/02 16:14:34 - mmengine - INFO - Epoch(val) [380][215/500] eta: 0:00:10 time: 0.0399 data_time: 0.0031 memory: 1008 2022/11/02 16:14:34 - mmengine - INFO - Epoch(val) [380][220/500] eta: 0:00:11 time: 0.0423 data_time: 0.0036 memory: 1008 2022/11/02 16:14:34 - mmengine - INFO - Epoch(val) [380][225/500] eta: 0:00:11 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/02 16:14:34 - mmengine - INFO - Epoch(val) [380][230/500] eta: 0:00:11 time: 0.0437 data_time: 0.0026 memory: 1008 2022/11/02 16:14:35 - mmengine - INFO - Epoch(val) [380][235/500] eta: 0:00:11 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/02 16:14:35 - mmengine - INFO - Epoch(val) [380][240/500] eta: 0:00:10 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/02 16:14:35 - mmengine - INFO - Epoch(val) [380][245/500] eta: 0:00:10 time: 0.0419 data_time: 0.0031 memory: 1008 2022/11/02 16:14:35 - mmengine - INFO - Epoch(val) [380][250/500] eta: 0:00:10 time: 0.0432 data_time: 0.0033 memory: 1008 2022/11/02 16:14:35 - mmengine - INFO - Epoch(val) [380][255/500] eta: 0:00:10 time: 0.0436 data_time: 0.0030 memory: 1008 2022/11/02 16:14:36 - mmengine - INFO - Epoch(val) [380][260/500] eta: 0:00:09 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 16:14:36 - mmengine - INFO - Epoch(val) [380][265/500] eta: 0:00:09 time: 0.0398 data_time: 0.0026 memory: 1008 2022/11/02 16:14:36 - mmengine - INFO - Epoch(val) [380][270/500] eta: 0:00:11 time: 0.0492 data_time: 0.0095 memory: 1008 2022/11/02 16:14:36 - mmengine - INFO - Epoch(val) [380][275/500] eta: 0:00:11 time: 0.0465 data_time: 0.0092 memory: 1008 2022/11/02 16:14:37 - mmengine - INFO - Epoch(val) [380][280/500] eta: 0:00:09 time: 0.0451 data_time: 0.0029 memory: 1008 2022/11/02 16:14:37 - mmengine - INFO - Epoch(val) [380][285/500] eta: 0:00:09 time: 0.0456 data_time: 0.0034 memory: 1008 2022/11/02 16:14:37 - mmengine - INFO - Epoch(val) [380][290/500] eta: 0:00:09 time: 0.0435 data_time: 0.0032 memory: 1008 2022/11/02 16:14:37 - mmengine - INFO - Epoch(val) [380][295/500] eta: 0:00:09 time: 0.0465 data_time: 0.0037 memory: 1008 2022/11/02 16:14:37 - mmengine - INFO - Epoch(val) [380][300/500] eta: 0:00:08 time: 0.0439 data_time: 0.0039 memory: 1008 2022/11/02 16:14:38 - mmengine - INFO - Epoch(val) [380][305/500] eta: 0:00:08 time: 0.0411 data_time: 0.0033 memory: 1008 2022/11/02 16:14:38 - mmengine - INFO - Epoch(val) [380][310/500] eta: 0:00:07 time: 0.0412 data_time: 0.0032 memory: 1008 2022/11/02 16:14:38 - mmengine - INFO - Epoch(val) [380][315/500] eta: 0:00:07 time: 0.0458 data_time: 0.0036 memory: 1008 2022/11/02 16:14:38 - mmengine - INFO - Epoch(val) [380][320/500] eta: 0:00:08 time: 0.0452 data_time: 0.0031 memory: 1008 2022/11/02 16:14:39 - mmengine - INFO - Epoch(val) [380][325/500] eta: 0:00:08 time: 0.0580 data_time: 0.0032 memory: 1008 2022/11/02 16:14:39 - mmengine - INFO - Epoch(val) [380][330/500] eta: 0:00:10 time: 0.0598 data_time: 0.0035 memory: 1008 2022/11/02 16:14:39 - mmengine - INFO - Epoch(val) [380][335/500] eta: 0:00:10 time: 0.0420 data_time: 0.0034 memory: 1008 2022/11/02 16:14:39 - mmengine - INFO - Epoch(val) [380][340/500] eta: 0:00:07 time: 0.0483 data_time: 0.0032 memory: 1008 2022/11/02 16:14:40 - mmengine - INFO - Epoch(val) [380][345/500] eta: 0:00:07 time: 0.0496 data_time: 0.0028 memory: 1008 2022/11/02 16:14:40 - mmengine - INFO - Epoch(val) [380][350/500] eta: 0:00:06 time: 0.0442 data_time: 0.0027 memory: 1008 2022/11/02 16:14:40 - mmengine - INFO - Epoch(val) [380][355/500] eta: 0:00:06 time: 0.0431 data_time: 0.0029 memory: 1008 2022/11/02 16:14:40 - mmengine - INFO - Epoch(val) [380][360/500] eta: 0:00:06 time: 0.0433 data_time: 0.0032 memory: 1008 2022/11/02 16:14:40 - mmengine - INFO - Epoch(val) [380][365/500] eta: 0:00:06 time: 0.0491 data_time: 0.0034 memory: 1008 2022/11/02 16:14:41 - mmengine - INFO - Epoch(val) [380][370/500] eta: 0:00:05 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/02 16:14:41 - mmengine - INFO - Epoch(val) [380][375/500] eta: 0:00:05 time: 0.0389 data_time: 0.0029 memory: 1008 2022/11/02 16:14:41 - mmengine - INFO - Epoch(val) [380][380/500] eta: 0:00:04 time: 0.0413 data_time: 0.0028 memory: 1008 2022/11/02 16:14:41 - mmengine - INFO - Epoch(val) [380][385/500] eta: 0:00:04 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/02 16:14:42 - mmengine - INFO - Epoch(val) [380][390/500] eta: 0:00:04 time: 0.0454 data_time: 0.0042 memory: 1008 2022/11/02 16:14:42 - mmengine - INFO - Epoch(val) [380][395/500] eta: 0:00:04 time: 0.0516 data_time: 0.0066 memory: 1008 2022/11/02 16:14:42 - mmengine - INFO - Epoch(val) [380][400/500] eta: 0:00:04 time: 0.0477 data_time: 0.0052 memory: 1008 2022/11/02 16:14:42 - mmengine - INFO - Epoch(val) [380][405/500] eta: 0:00:04 time: 0.0419 data_time: 0.0031 memory: 1008 2022/11/02 16:14:42 - mmengine - INFO - Epoch(val) [380][410/500] eta: 0:00:03 time: 0.0409 data_time: 0.0032 memory: 1008 2022/11/02 16:14:43 - mmengine - INFO - Epoch(val) [380][415/500] eta: 0:00:03 time: 0.0415 data_time: 0.0034 memory: 1008 2022/11/02 16:14:43 - mmengine - INFO - Epoch(val) [380][420/500] eta: 0:00:03 time: 0.0379 data_time: 0.0029 memory: 1008 2022/11/02 16:14:43 - mmengine - INFO - Epoch(val) [380][425/500] eta: 0:00:03 time: 0.0396 data_time: 0.0030 memory: 1008 2022/11/02 16:14:43 - mmengine - INFO - Epoch(val) [380][430/500] eta: 0:00:03 time: 0.0435 data_time: 0.0032 memory: 1008 2022/11/02 16:14:43 - mmengine - INFO - Epoch(val) [380][435/500] eta: 0:00:03 time: 0.0396 data_time: 0.0029 memory: 1008 2022/11/02 16:14:44 - mmengine - INFO - Epoch(val) [380][440/500] eta: 0:00:02 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 16:14:44 - mmengine - INFO - Epoch(val) [380][445/500] eta: 0:00:02 time: 0.0491 data_time: 0.0032 memory: 1008 2022/11/02 16:14:44 - mmengine - INFO - Epoch(val) [380][450/500] eta: 0:00:02 time: 0.0466 data_time: 0.0036 memory: 1008 2022/11/02 16:14:44 - mmengine - INFO - Epoch(val) [380][455/500] eta: 0:00:02 time: 0.0424 data_time: 0.0036 memory: 1008 2022/11/02 16:14:45 - mmengine - INFO - Epoch(val) [380][460/500] eta: 0:00:01 time: 0.0389 data_time: 0.0031 memory: 1008 2022/11/02 16:14:45 - mmengine - INFO - Epoch(val) [380][465/500] eta: 0:00:01 time: 0.0365 data_time: 0.0029 memory: 1008 2022/11/02 16:14:45 - mmengine - INFO - Epoch(val) [380][470/500] eta: 0:00:01 time: 0.0408 data_time: 0.0029 memory: 1008 2022/11/02 16:14:45 - mmengine - INFO - Epoch(val) [380][475/500] eta: 0:00:01 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 16:14:45 - mmengine - INFO - Epoch(val) [380][480/500] eta: 0:00:00 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 16:14:46 - mmengine - INFO - Epoch(val) [380][485/500] eta: 0:00:00 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/02 16:14:46 - mmengine - INFO - Epoch(val) [380][490/500] eta: 0:00:00 time: 0.0441 data_time: 0.0032 memory: 1008 2022/11/02 16:14:46 - mmengine - INFO - Epoch(val) [380][495/500] eta: 0:00:00 time: 0.0504 data_time: 0.0047 memory: 1008 2022/11/02 16:14:46 - mmengine - INFO - Epoch(val) [380][500/500] eta: 0:00:00 time: 0.0456 data_time: 0.0041 memory: 1008 2022/11/02 16:14:46 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8113, precision: 0.7590, hmean: 0.7843 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8113, precision: 0.8047, hmean: 0.8080 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8079, precision: 0.8352, hmean: 0.8213 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7959, precision: 0.8583, hmean: 0.8259 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7424, precision: 0.8898, hmean: 0.8094 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4343, precision: 0.9270, hmean: 0.5915 2022/11/02 16:14:46 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0067, precision: 0.8750, hmean: 0.0134 2022/11/02 16:14:46 - mmengine - INFO - Epoch(val) [380][500/500] icdar/precision: 0.8583 icdar/recall: 0.7959 icdar/hmean: 0.8259 2022/11/02 16:14:53 - mmengine - INFO - Epoch(train) [381][5/63] lr: 1.5349e-03 eta: 0:00:00 time: 0.8949 data_time: 0.2407 memory: 14901 loss: 1.4489 loss_prob: 0.7901 loss_thr: 0.5272 loss_db: 0.1316 2022/11/02 16:14:56 - mmengine - INFO - Epoch(train) [381][10/63] lr: 1.5349e-03 eta: 8:24:31 time: 0.9579 data_time: 0.2389 memory: 14901 loss: 1.5435 loss_prob: 0.8579 loss_thr: 0.5412 loss_db: 0.1444 2022/11/02 16:14:59 - mmengine - INFO - Epoch(train) [381][15/63] lr: 1.5349e-03 eta: 8:24:31 time: 0.6321 data_time: 0.0120 memory: 14901 loss: 1.5771 loss_prob: 0.8923 loss_thr: 0.5339 loss_db: 0.1509 2022/11/02 16:15:02 - mmengine - INFO - Epoch(train) [381][20/63] lr: 1.5349e-03 eta: 8:24:25 time: 0.5774 data_time: 0.0081 memory: 14901 loss: 1.4891 loss_prob: 0.8222 loss_thr: 0.5286 loss_db: 0.1383 2022/11/02 16:15:05 - mmengine - INFO - Epoch(train) [381][25/63] lr: 1.5349e-03 eta: 8:24:25 time: 0.6322 data_time: 0.0347 memory: 14901 loss: 1.4234 loss_prob: 0.7772 loss_thr: 0.5159 loss_db: 0.1303 2022/11/02 16:15:08 - mmengine - INFO - Epoch(train) [381][30/63] lr: 1.5349e-03 eta: 8:24:21 time: 0.6686 data_time: 0.0385 memory: 14901 loss: 1.3929 loss_prob: 0.7612 loss_thr: 0.5014 loss_db: 0.1303 2022/11/02 16:15:12 - mmengine - INFO - Epoch(train) [381][35/63] lr: 1.5349e-03 eta: 8:24:21 time: 0.6460 data_time: 0.0121 memory: 14901 loss: 1.3525 loss_prob: 0.7324 loss_thr: 0.4942 loss_db: 0.1259 2022/11/02 16:15:14 - mmengine - INFO - Epoch(train) [381][40/63] lr: 1.5349e-03 eta: 8:24:16 time: 0.6129 data_time: 0.0116 memory: 14901 loss: 1.4771 loss_prob: 0.8234 loss_thr: 0.5178 loss_db: 0.1358 2022/11/02 16:15:17 - mmengine - INFO - Epoch(train) [381][45/63] lr: 1.5349e-03 eta: 8:24:16 time: 0.5868 data_time: 0.0144 memory: 14901 loss: 1.5531 loss_prob: 0.8791 loss_thr: 0.5307 loss_db: 0.1433 2022/11/02 16:15:21 - mmengine - INFO - Epoch(train) [381][50/63] lr: 1.5349e-03 eta: 8:24:11 time: 0.6169 data_time: 0.0307 memory: 14901 loss: 1.4444 loss_prob: 0.8029 loss_thr: 0.5068 loss_db: 0.1347 2022/11/02 16:15:24 - mmengine - INFO - Epoch(train) [381][55/63] lr: 1.5349e-03 eta: 8:24:11 time: 0.6048 data_time: 0.0283 memory: 14901 loss: 1.5085 loss_prob: 0.8387 loss_thr: 0.5286 loss_db: 0.1411 2022/11/02 16:15:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:15:27 - mmengine - INFO - Epoch(train) [381][60/63] lr: 1.5349e-03 eta: 8:24:06 time: 0.6473 data_time: 0.0111 memory: 14901 loss: 1.5732 loss_prob: 0.8818 loss_thr: 0.5460 loss_db: 0.1454 2022/11/02 16:15:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:15:35 - mmengine - INFO - Epoch(train) [382][5/63] lr: 1.5333e-03 eta: 8:24:06 time: 1.0194 data_time: 0.2547 memory: 14901 loss: 1.4323 loss_prob: 0.7901 loss_thr: 0.5094 loss_db: 0.1328 2022/11/02 16:15:39 - mmengine - INFO - Epoch(train) [382][10/63] lr: 1.5333e-03 eta: 8:24:05 time: 1.0532 data_time: 0.2579 memory: 14901 loss: 1.4640 loss_prob: 0.8127 loss_thr: 0.5121 loss_db: 0.1392 2022/11/02 16:15:43 - mmengine - INFO - Epoch(train) [382][15/63] lr: 1.5333e-03 eta: 8:24:05 time: 0.7363 data_time: 0.0161 memory: 14901 loss: 1.5000 loss_prob: 0.8306 loss_thr: 0.5284 loss_db: 0.1410 2022/11/02 16:15:45 - mmengine - INFO - Epoch(train) [382][20/63] lr: 1.5333e-03 eta: 8:24:00 time: 0.6151 data_time: 0.0122 memory: 14901 loss: 1.5084 loss_prob: 0.8360 loss_thr: 0.5285 loss_db: 0.1440 2022/11/02 16:15:48 - mmengine - INFO - Epoch(train) [382][25/63] lr: 1.5333e-03 eta: 8:24:00 time: 0.5468 data_time: 0.0296 memory: 14901 loss: 1.6579 loss_prob: 0.9638 loss_thr: 0.5407 loss_db: 0.1534 2022/11/02 16:15:51 - mmengine - INFO - Epoch(train) [382][30/63] lr: 1.5333e-03 eta: 8:23:54 time: 0.5829 data_time: 0.0389 memory: 14901 loss: 1.6763 loss_prob: 0.9797 loss_thr: 0.5455 loss_db: 0.1512 2022/11/02 16:15:53 - mmengine - INFO - Epoch(train) [382][35/63] lr: 1.5333e-03 eta: 8:23:54 time: 0.5229 data_time: 0.0175 memory: 14901 loss: 1.6533 loss_prob: 0.9306 loss_thr: 0.5688 loss_db: 0.1539 2022/11/02 16:15:56 - mmengine - INFO - Epoch(train) [382][40/63] lr: 1.5333e-03 eta: 8:23:47 time: 0.5388 data_time: 0.0093 memory: 14901 loss: 1.6013 loss_prob: 0.8948 loss_thr: 0.5587 loss_db: 0.1477 2022/11/02 16:15:59 - mmengine - INFO - Epoch(train) [382][45/63] lr: 1.5333e-03 eta: 8:23:47 time: 0.5610 data_time: 0.0084 memory: 14901 loss: 1.5144 loss_prob: 0.8488 loss_thr: 0.5241 loss_db: 0.1415 2022/11/02 16:16:02 - mmengine - INFO - Epoch(train) [382][50/63] lr: 1.5333e-03 eta: 8:23:39 time: 0.5143 data_time: 0.0196 memory: 14901 loss: 1.5386 loss_prob: 0.8694 loss_thr: 0.5222 loss_db: 0.1470 2022/11/02 16:16:04 - mmengine - INFO - Epoch(train) [382][55/63] lr: 1.5333e-03 eta: 8:23:39 time: 0.5261 data_time: 0.0190 memory: 14901 loss: 1.6163 loss_prob: 0.9090 loss_thr: 0.5542 loss_db: 0.1531 2022/11/02 16:16:07 - mmengine - INFO - Epoch(train) [382][60/63] lr: 1.5333e-03 eta: 8:23:34 time: 0.5871 data_time: 0.0126 memory: 14901 loss: 1.5626 loss_prob: 0.8651 loss_thr: 0.5530 loss_db: 0.1445 2022/11/02 16:16:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:16:15 - mmengine - INFO - Epoch(train) [383][5/63] lr: 1.5316e-03 eta: 8:23:34 time: 0.9083 data_time: 0.2923 memory: 14901 loss: 1.6130 loss_prob: 0.9078 loss_thr: 0.5544 loss_db: 0.1508 2022/11/02 16:16:18 - mmengine - INFO - Epoch(train) [383][10/63] lr: 1.5316e-03 eta: 8:23:28 time: 0.8811 data_time: 0.2856 memory: 14901 loss: 1.6576 loss_prob: 0.9401 loss_thr: 0.5609 loss_db: 0.1567 2022/11/02 16:16:21 - mmengine - INFO - Epoch(train) [383][15/63] lr: 1.5316e-03 eta: 8:23:28 time: 0.5465 data_time: 0.0067 memory: 14901 loss: 1.8685 loss_prob: 1.1113 loss_thr: 0.5730 loss_db: 0.1841 2022/11/02 16:16:23 - mmengine - INFO - Epoch(train) [383][20/63] lr: 1.5316e-03 eta: 8:23:21 time: 0.5313 data_time: 0.0096 memory: 14901 loss: 2.2182 loss_prob: 1.3825 loss_thr: 0.6232 loss_db: 0.2126 2022/11/02 16:16:26 - mmengine - INFO - Epoch(train) [383][25/63] lr: 1.5316e-03 eta: 8:23:21 time: 0.5249 data_time: 0.0084 memory: 14901 loss: 2.2608 loss_prob: 1.4151 loss_thr: 0.6288 loss_db: 0.2169 2022/11/02 16:16:29 - mmengine - INFO - Epoch(train) [383][30/63] lr: 1.5316e-03 eta: 8:23:15 time: 0.5381 data_time: 0.0265 memory: 14901 loss: 2.3086 loss_prob: 1.4405 loss_thr: 0.6400 loss_db: 0.2281 2022/11/02 16:16:31 - mmengine - INFO - Epoch(train) [383][35/63] lr: 1.5316e-03 eta: 8:23:15 time: 0.5441 data_time: 0.0268 memory: 14901 loss: 2.0376 loss_prob: 1.2428 loss_thr: 0.6006 loss_db: 0.1942 2022/11/02 16:16:34 - mmengine - INFO - Epoch(train) [383][40/63] lr: 1.5316e-03 eta: 8:23:07 time: 0.5277 data_time: 0.0102 memory: 14901 loss: 1.7838 loss_prob: 1.0495 loss_thr: 0.5641 loss_db: 0.1703 2022/11/02 16:16:37 - mmengine - INFO - Epoch(train) [383][45/63] lr: 1.5316e-03 eta: 8:23:07 time: 0.5814 data_time: 0.0141 memory: 14901 loss: 2.1444 loss_prob: 1.3382 loss_thr: 0.5802 loss_db: 0.2259 2022/11/02 16:16:40 - mmengine - INFO - Epoch(train) [383][50/63] lr: 1.5316e-03 eta: 8:23:02 time: 0.5900 data_time: 0.0183 memory: 14901 loss: 2.1262 loss_prob: 1.3220 loss_thr: 0.5831 loss_db: 0.2212 2022/11/02 16:16:43 - mmengine - INFO - Epoch(train) [383][55/63] lr: 1.5316e-03 eta: 8:23:02 time: 0.5367 data_time: 0.0343 memory: 14901 loss: 1.8455 loss_prob: 1.0816 loss_thr: 0.5911 loss_db: 0.1728 2022/11/02 16:16:46 - mmengine - INFO - Epoch(train) [383][60/63] lr: 1.5316e-03 eta: 8:22:56 time: 0.6092 data_time: 0.0282 memory: 14901 loss: 1.9326 loss_prob: 1.1221 loss_thr: 0.6299 loss_db: 0.1806 2022/11/02 16:16:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:16:54 - mmengine - INFO - Epoch(train) [384][5/63] lr: 1.5299e-03 eta: 8:22:56 time: 0.9647 data_time: 0.2687 memory: 14901 loss: 1.8970 loss_prob: 1.1071 loss_thr: 0.6094 loss_db: 0.1806 2022/11/02 16:16:57 - mmengine - INFO - Epoch(train) [384][10/63] lr: 1.5299e-03 eta: 8:22:53 time: 0.9708 data_time: 0.2686 memory: 14901 loss: 2.0638 loss_prob: 1.2512 loss_thr: 0.6040 loss_db: 0.2086 2022/11/02 16:17:00 - mmengine - INFO - Epoch(train) [384][15/63] lr: 1.5299e-03 eta: 8:22:53 time: 0.5485 data_time: 0.0084 memory: 14901 loss: 2.3391 loss_prob: 1.4779 loss_thr: 0.6146 loss_db: 0.2466 2022/11/02 16:17:03 - mmengine - INFO - Epoch(train) [384][20/63] lr: 1.5299e-03 eta: 8:22:47 time: 0.5811 data_time: 0.0089 memory: 14901 loss: 2.3804 loss_prob: 1.5102 loss_thr: 0.6234 loss_db: 0.2467 2022/11/02 16:17:06 - mmengine - INFO - Epoch(train) [384][25/63] lr: 1.5299e-03 eta: 8:22:47 time: 0.6042 data_time: 0.0170 memory: 14901 loss: 2.1615 loss_prob: 1.3331 loss_thr: 0.6099 loss_db: 0.2186 2022/11/02 16:17:09 - mmengine - INFO - Epoch(train) [384][30/63] lr: 1.5299e-03 eta: 8:22:42 time: 0.5988 data_time: 0.0436 memory: 14901 loss: 1.9580 loss_prob: 1.1693 loss_thr: 0.5990 loss_db: 0.1897 2022/11/02 16:17:11 - mmengine - INFO - Epoch(train) [384][35/63] lr: 1.5299e-03 eta: 8:22:42 time: 0.5459 data_time: 0.0339 memory: 14901 loss: 1.9021 loss_prob: 1.1342 loss_thr: 0.5851 loss_db: 0.1827 2022/11/02 16:17:14 - mmengine - INFO - Epoch(train) [384][40/63] lr: 1.5299e-03 eta: 8:22:35 time: 0.5510 data_time: 0.0053 memory: 14901 loss: 1.8288 loss_prob: 1.0725 loss_thr: 0.5816 loss_db: 0.1747 2022/11/02 16:17:17 - mmengine - INFO - Epoch(train) [384][45/63] lr: 1.5299e-03 eta: 8:22:35 time: 0.5718 data_time: 0.0071 memory: 14901 loss: 1.9124 loss_prob: 1.1324 loss_thr: 0.5852 loss_db: 0.1948 2022/11/02 16:17:20 - mmengine - INFO - Epoch(train) [384][50/63] lr: 1.5299e-03 eta: 8:22:29 time: 0.5794 data_time: 0.0208 memory: 14901 loss: 2.0180 loss_prob: 1.2141 loss_thr: 0.5919 loss_db: 0.2120 2022/11/02 16:17:23 - mmengine - INFO - Epoch(train) [384][55/63] lr: 1.5299e-03 eta: 8:22:29 time: 0.6311 data_time: 0.0291 memory: 14901 loss: 1.9963 loss_prob: 1.1762 loss_thr: 0.6210 loss_db: 0.1990 2022/11/02 16:17:26 - mmengine - INFO - Epoch(train) [384][60/63] lr: 1.5299e-03 eta: 8:22:23 time: 0.5688 data_time: 0.0172 memory: 14901 loss: 1.8070 loss_prob: 1.0253 loss_thr: 0.6107 loss_db: 0.1711 2022/11/02 16:17:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:17:35 - mmengine - INFO - Epoch(train) [385][5/63] lr: 1.5282e-03 eta: 8:22:23 time: 1.0135 data_time: 0.2674 memory: 14901 loss: 1.8650 loss_prob: 1.0887 loss_thr: 0.5948 loss_db: 0.1815 2022/11/02 16:17:38 - mmengine - INFO - Epoch(train) [385][10/63] lr: 1.5282e-03 eta: 8:22:22 time: 1.0702 data_time: 0.2963 memory: 14901 loss: 1.8662 loss_prob: 1.1007 loss_thr: 0.5842 loss_db: 0.1813 2022/11/02 16:17:41 - mmengine - INFO - Epoch(train) [385][15/63] lr: 1.5282e-03 eta: 8:22:22 time: 0.6062 data_time: 0.0431 memory: 14901 loss: 1.7558 loss_prob: 1.0223 loss_thr: 0.5694 loss_db: 0.1642 2022/11/02 16:17:44 - mmengine - INFO - Epoch(train) [385][20/63] lr: 1.5282e-03 eta: 8:22:15 time: 0.5408 data_time: 0.0088 memory: 14901 loss: 1.9916 loss_prob: 1.2070 loss_thr: 0.5887 loss_db: 0.1959 2022/11/02 16:17:46 - mmengine - INFO - Epoch(train) [385][25/63] lr: 1.5282e-03 eta: 8:22:15 time: 0.5292 data_time: 0.0078 memory: 14901 loss: 2.0694 loss_prob: 1.2618 loss_thr: 0.6034 loss_db: 0.2042 2022/11/02 16:17:49 - mmengine - INFO - Epoch(train) [385][30/63] lr: 1.5282e-03 eta: 8:22:08 time: 0.5591 data_time: 0.0082 memory: 14901 loss: 1.8755 loss_prob: 1.1042 loss_thr: 0.5981 loss_db: 0.1732 2022/11/02 16:17:52 - mmengine - INFO - Epoch(train) [385][35/63] lr: 1.5282e-03 eta: 8:22:08 time: 0.5487 data_time: 0.0201 memory: 14901 loss: 1.9248 loss_prob: 1.1300 loss_thr: 0.6120 loss_db: 0.1828 2022/11/02 16:17:54 - mmengine - INFO - Epoch(train) [385][40/63] lr: 1.5282e-03 eta: 8:22:00 time: 0.4941 data_time: 0.0192 memory: 14901 loss: 1.7720 loss_prob: 1.0241 loss_thr: 0.5779 loss_db: 0.1701 2022/11/02 16:17:57 - mmengine - INFO - Epoch(train) [385][45/63] lr: 1.5282e-03 eta: 8:22:00 time: 0.5294 data_time: 0.0102 memory: 14901 loss: 1.7034 loss_prob: 0.9677 loss_thr: 0.5768 loss_db: 0.1588 2022/11/02 16:18:00 - mmengine - INFO - Epoch(train) [385][50/63] lr: 1.5282e-03 eta: 8:21:54 time: 0.5534 data_time: 0.0123 memory: 14901 loss: 1.7435 loss_prob: 0.9877 loss_thr: 0.5942 loss_db: 0.1616 2022/11/02 16:18:03 - mmengine - INFO - Epoch(train) [385][55/63] lr: 1.5282e-03 eta: 8:21:54 time: 0.5277 data_time: 0.0210 memory: 14901 loss: 1.7995 loss_prob: 1.0380 loss_thr: 0.5909 loss_db: 0.1706 2022/11/02 16:18:05 - mmengine - INFO - Epoch(train) [385][60/63] lr: 1.5282e-03 eta: 8:21:46 time: 0.5119 data_time: 0.0222 memory: 14901 loss: 1.8702 loss_prob: 1.1008 loss_thr: 0.5881 loss_db: 0.1813 2022/11/02 16:18:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:18:12 - mmengine - INFO - Epoch(train) [386][5/63] lr: 1.5265e-03 eta: 8:21:46 time: 0.7422 data_time: 0.2171 memory: 14901 loss: 1.9509 loss_prob: 1.1494 loss_thr: 0.6063 loss_db: 0.1952 2022/11/02 16:18:14 - mmengine - INFO - Epoch(train) [386][10/63] lr: 1.5265e-03 eta: 8:21:39 time: 0.7908 data_time: 0.2281 memory: 14901 loss: 1.8107 loss_prob: 1.0451 loss_thr: 0.5886 loss_db: 0.1770 2022/11/02 16:18:18 - mmengine - INFO - Epoch(train) [386][15/63] lr: 1.5265e-03 eta: 8:21:39 time: 0.6195 data_time: 0.0347 memory: 14901 loss: 1.7075 loss_prob: 0.9865 loss_thr: 0.5622 loss_db: 0.1588 2022/11/02 16:18:21 - mmengine - INFO - Epoch(train) [386][20/63] lr: 1.5265e-03 eta: 8:21:34 time: 0.6241 data_time: 0.0230 memory: 14901 loss: 1.7365 loss_prob: 1.0086 loss_thr: 0.5621 loss_db: 0.1658 2022/11/02 16:18:24 - mmengine - INFO - Epoch(train) [386][25/63] lr: 1.5265e-03 eta: 8:21:34 time: 0.6055 data_time: 0.0380 memory: 14901 loss: 1.7067 loss_prob: 0.9805 loss_thr: 0.5609 loss_db: 0.1652 2022/11/02 16:18:26 - mmengine - INFO - Epoch(train) [386][30/63] lr: 1.5265e-03 eta: 8:21:29 time: 0.5901 data_time: 0.0498 memory: 14901 loss: 1.7487 loss_prob: 1.0142 loss_thr: 0.5684 loss_db: 0.1661 2022/11/02 16:18:29 - mmengine - INFO - Epoch(train) [386][35/63] lr: 1.5265e-03 eta: 8:21:29 time: 0.5630 data_time: 0.0282 memory: 14901 loss: 1.6410 loss_prob: 0.9313 loss_thr: 0.5540 loss_db: 0.1557 2022/11/02 16:18:32 - mmengine - INFO - Epoch(train) [386][40/63] lr: 1.5265e-03 eta: 8:21:23 time: 0.5784 data_time: 0.0236 memory: 14901 loss: 1.5315 loss_prob: 0.8520 loss_thr: 0.5356 loss_db: 0.1438 2022/11/02 16:18:35 - mmengine - INFO - Epoch(train) [386][45/63] lr: 1.5265e-03 eta: 8:21:23 time: 0.5613 data_time: 0.0127 memory: 14901 loss: 1.6615 loss_prob: 0.9389 loss_thr: 0.5660 loss_db: 0.1567 2022/11/02 16:18:38 - mmengine - INFO - Epoch(train) [386][50/63] lr: 1.5265e-03 eta: 8:21:16 time: 0.5647 data_time: 0.0185 memory: 14901 loss: 1.6444 loss_prob: 0.9200 loss_thr: 0.5693 loss_db: 0.1551 2022/11/02 16:18:40 - mmengine - INFO - Epoch(train) [386][55/63] lr: 1.5265e-03 eta: 8:21:16 time: 0.5389 data_time: 0.0191 memory: 14901 loss: 1.7241 loss_prob: 1.0084 loss_thr: 0.5473 loss_db: 0.1684 2022/11/02 16:18:43 - mmengine - INFO - Epoch(train) [386][60/63] lr: 1.5265e-03 eta: 8:21:10 time: 0.5543 data_time: 0.0124 memory: 14901 loss: 1.6952 loss_prob: 0.9914 loss_thr: 0.5415 loss_db: 0.1624 2022/11/02 16:18:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:18:51 - mmengine - INFO - Epoch(train) [387][5/63] lr: 1.5248e-03 eta: 8:21:10 time: 0.9374 data_time: 0.2249 memory: 14901 loss: 1.7725 loss_prob: 1.0331 loss_thr: 0.5728 loss_db: 0.1666 2022/11/02 16:18:54 - mmengine - INFO - Epoch(train) [387][10/63] lr: 1.5248e-03 eta: 8:21:06 time: 0.9368 data_time: 0.2260 memory: 14901 loss: 1.7254 loss_prob: 1.0111 loss_thr: 0.5490 loss_db: 0.1653 2022/11/02 16:18:57 - mmengine - INFO - Epoch(train) [387][15/63] lr: 1.5248e-03 eta: 8:21:06 time: 0.5813 data_time: 0.0126 memory: 14901 loss: 1.7130 loss_prob: 0.9815 loss_thr: 0.5692 loss_db: 0.1623 2022/11/02 16:19:00 - mmengine - INFO - Epoch(train) [387][20/63] lr: 1.5248e-03 eta: 8:20:59 time: 0.5492 data_time: 0.0098 memory: 14901 loss: 1.6924 loss_prob: 0.9755 loss_thr: 0.5562 loss_db: 0.1607 2022/11/02 16:19:03 - mmengine - INFO - Epoch(train) [387][25/63] lr: 1.5248e-03 eta: 8:20:59 time: 0.5909 data_time: 0.0280 memory: 14901 loss: 1.6702 loss_prob: 0.9673 loss_thr: 0.5403 loss_db: 0.1627 2022/11/02 16:19:06 - mmengine - INFO - Epoch(train) [387][30/63] lr: 1.5248e-03 eta: 8:20:54 time: 0.6321 data_time: 0.0391 memory: 14901 loss: 1.6439 loss_prob: 0.9410 loss_thr: 0.5442 loss_db: 0.1587 2022/11/02 16:19:09 - mmengine - INFO - Epoch(train) [387][35/63] lr: 1.5248e-03 eta: 8:20:54 time: 0.5875 data_time: 0.0263 memory: 14901 loss: 1.6913 loss_prob: 0.9671 loss_thr: 0.5622 loss_db: 0.1620 2022/11/02 16:19:12 - mmengine - INFO - Epoch(train) [387][40/63] lr: 1.5248e-03 eta: 8:20:49 time: 0.6211 data_time: 0.0132 memory: 14901 loss: 1.7476 loss_prob: 0.9966 loss_thr: 0.5847 loss_db: 0.1663 2022/11/02 16:19:15 - mmengine - INFO - Epoch(train) [387][45/63] lr: 1.5248e-03 eta: 8:20:49 time: 0.6286 data_time: 0.0071 memory: 14901 loss: 1.6504 loss_prob: 0.9356 loss_thr: 0.5558 loss_db: 0.1590 2022/11/02 16:19:18 - mmengine - INFO - Epoch(train) [387][50/63] lr: 1.5248e-03 eta: 8:20:43 time: 0.5689 data_time: 0.0249 memory: 14901 loss: 1.5201 loss_prob: 0.8728 loss_thr: 0.5014 loss_db: 0.1459 2022/11/02 16:19:21 - mmengine - INFO - Epoch(train) [387][55/63] lr: 1.5248e-03 eta: 8:20:43 time: 0.5326 data_time: 0.0307 memory: 14901 loss: 1.4527 loss_prob: 0.8188 loss_thr: 0.5005 loss_db: 0.1334 2022/11/02 16:19:23 - mmengine - INFO - Epoch(train) [387][60/63] lr: 1.5248e-03 eta: 8:20:36 time: 0.5162 data_time: 0.0121 memory: 14901 loss: 1.5386 loss_prob: 0.8552 loss_thr: 0.5406 loss_db: 0.1429 2022/11/02 16:19:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:19:31 - mmengine - INFO - Epoch(train) [388][5/63] lr: 1.5231e-03 eta: 8:20:36 time: 0.8689 data_time: 0.2201 memory: 14901 loss: 1.6774 loss_prob: 0.9599 loss_thr: 0.5571 loss_db: 0.1604 2022/11/02 16:19:34 - mmengine - INFO - Epoch(train) [388][10/63] lr: 1.5231e-03 eta: 8:20:31 time: 0.9332 data_time: 0.2209 memory: 14901 loss: 1.5993 loss_prob: 0.9147 loss_thr: 0.5325 loss_db: 0.1520 2022/11/02 16:19:37 - mmengine - INFO - Epoch(train) [388][15/63] lr: 1.5231e-03 eta: 8:20:31 time: 0.5694 data_time: 0.0120 memory: 14901 loss: 1.5538 loss_prob: 0.8818 loss_thr: 0.5262 loss_db: 0.1458 2022/11/02 16:19:39 - mmengine - INFO - Epoch(train) [388][20/63] lr: 1.5231e-03 eta: 8:20:25 time: 0.5351 data_time: 0.0093 memory: 14901 loss: 1.5811 loss_prob: 0.8957 loss_thr: 0.5386 loss_db: 0.1468 2022/11/02 16:19:42 - mmengine - INFO - Epoch(train) [388][25/63] lr: 1.5231e-03 eta: 8:20:25 time: 0.5742 data_time: 0.0092 memory: 14901 loss: 1.5821 loss_prob: 0.8940 loss_thr: 0.5391 loss_db: 0.1489 2022/11/02 16:19:45 - mmengine - INFO - Epoch(train) [388][30/63] lr: 1.5231e-03 eta: 8:20:19 time: 0.6072 data_time: 0.0444 memory: 14901 loss: 1.5362 loss_prob: 0.8579 loss_thr: 0.5326 loss_db: 0.1458 2022/11/02 16:19:50 - mmengine - INFO - Epoch(train) [388][35/63] lr: 1.5231e-03 eta: 8:20:19 time: 0.7602 data_time: 0.0434 memory: 14901 loss: 1.4654 loss_prob: 0.8118 loss_thr: 0.5196 loss_db: 0.1340 2022/11/02 16:19:53 - mmengine - INFO - Epoch(train) [388][40/63] lr: 1.5231e-03 eta: 8:20:16 time: 0.7023 data_time: 0.0080 memory: 14901 loss: 1.4809 loss_prob: 0.8117 loss_thr: 0.5352 loss_db: 0.1340 2022/11/02 16:19:55 - mmengine - INFO - Epoch(train) [388][45/63] lr: 1.5231e-03 eta: 8:20:16 time: 0.4953 data_time: 0.0087 memory: 14901 loss: 1.5574 loss_prob: 0.8623 loss_thr: 0.5524 loss_db: 0.1427 2022/11/02 16:19:58 - mmengine - INFO - Epoch(train) [388][50/63] lr: 1.5231e-03 eta: 8:20:09 time: 0.5317 data_time: 0.0231 memory: 14901 loss: 1.6372 loss_prob: 0.9325 loss_thr: 0.5546 loss_db: 0.1501 2022/11/02 16:20:01 - mmengine - INFO - Epoch(train) [388][55/63] lr: 1.5231e-03 eta: 8:20:09 time: 0.6134 data_time: 0.0267 memory: 14901 loss: 1.6000 loss_prob: 0.8990 loss_thr: 0.5541 loss_db: 0.1469 2022/11/02 16:20:04 - mmengine - INFO - Epoch(train) [388][60/63] lr: 1.5231e-03 eta: 8:20:03 time: 0.5830 data_time: 0.0138 memory: 14901 loss: 1.5328 loss_prob: 0.8415 loss_thr: 0.5493 loss_db: 0.1420 2022/11/02 16:20:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:20:11 - mmengine - INFO - Epoch(train) [389][5/63] lr: 1.5214e-03 eta: 8:20:03 time: 0.7883 data_time: 0.2281 memory: 14901 loss: 1.5383 loss_prob: 0.8478 loss_thr: 0.5494 loss_db: 0.1411 2022/11/02 16:20:14 - mmengine - INFO - Epoch(train) [389][10/63] lr: 1.5214e-03 eta: 8:19:57 time: 0.8700 data_time: 0.2386 memory: 14901 loss: 1.5693 loss_prob: 0.8688 loss_thr: 0.5509 loss_db: 0.1496 2022/11/02 16:20:17 - mmengine - INFO - Epoch(train) [389][15/63] lr: 1.5214e-03 eta: 8:19:57 time: 0.6780 data_time: 0.0202 memory: 14901 loss: 1.6360 loss_prob: 0.9281 loss_thr: 0.5514 loss_db: 0.1566 2022/11/02 16:20:20 - mmengine - INFO - Epoch(train) [389][20/63] lr: 1.5214e-03 eta: 8:19:53 time: 0.6681 data_time: 0.0096 memory: 14901 loss: 1.6935 loss_prob: 0.9669 loss_thr: 0.5638 loss_db: 0.1628 2022/11/02 16:20:24 - mmengine - INFO - Epoch(train) [389][25/63] lr: 1.5214e-03 eta: 8:19:53 time: 0.6385 data_time: 0.0380 memory: 14901 loss: 1.7557 loss_prob: 1.0174 loss_thr: 0.5706 loss_db: 0.1677 2022/11/02 16:20:27 - mmengine - INFO - Epoch(train) [389][30/63] lr: 1.5214e-03 eta: 8:19:49 time: 0.6457 data_time: 0.0369 memory: 14901 loss: 1.7757 loss_prob: 1.0432 loss_thr: 0.5723 loss_db: 0.1602 2022/11/02 16:20:29 - mmengine - INFO - Epoch(train) [389][35/63] lr: 1.5214e-03 eta: 8:19:49 time: 0.5614 data_time: 0.0106 memory: 14901 loss: 1.8569 loss_prob: 1.1004 loss_thr: 0.5856 loss_db: 0.1709 2022/11/02 16:20:32 - mmengine - INFO - Epoch(train) [389][40/63] lr: 1.5214e-03 eta: 8:19:42 time: 0.5479 data_time: 0.0118 memory: 14901 loss: 1.7923 loss_prob: 1.0395 loss_thr: 0.5857 loss_db: 0.1672 2022/11/02 16:20:36 - mmengine - INFO - Epoch(train) [389][45/63] lr: 1.5214e-03 eta: 8:19:42 time: 0.7091 data_time: 0.0100 memory: 14901 loss: 1.6832 loss_prob: 0.9573 loss_thr: 0.5675 loss_db: 0.1584 2022/11/02 16:20:40 - mmengine - INFO - Epoch(train) [389][50/63] lr: 1.5214e-03 eta: 8:19:39 time: 0.7228 data_time: 0.0256 memory: 14901 loss: 1.6457 loss_prob: 0.9453 loss_thr: 0.5456 loss_db: 0.1548 2022/11/02 16:20:43 - mmengine - INFO - Epoch(train) [389][55/63] lr: 1.5214e-03 eta: 8:19:39 time: 0.6119 data_time: 0.0252 memory: 14901 loss: 1.5606 loss_prob: 0.8864 loss_thr: 0.5284 loss_db: 0.1458 2022/11/02 16:20:45 - mmengine - INFO - Epoch(train) [389][60/63] lr: 1.5214e-03 eta: 8:19:33 time: 0.5745 data_time: 0.0125 memory: 14901 loss: 1.5070 loss_prob: 0.8421 loss_thr: 0.5205 loss_db: 0.1444 2022/11/02 16:20:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:20:52 - mmengine - INFO - Epoch(train) [390][5/63] lr: 1.5198e-03 eta: 8:19:33 time: 0.8055 data_time: 0.2463 memory: 14901 loss: 1.4545 loss_prob: 0.8044 loss_thr: 0.5140 loss_db: 0.1361 2022/11/02 16:20:55 - mmengine - INFO - Epoch(train) [390][10/63] lr: 1.5198e-03 eta: 8:19:26 time: 0.8265 data_time: 0.2467 memory: 14901 loss: 1.4600 loss_prob: 0.8092 loss_thr: 0.5155 loss_db: 0.1353 2022/11/02 16:20:58 - mmengine - INFO - Epoch(train) [390][15/63] lr: 1.5198e-03 eta: 8:19:26 time: 0.5353 data_time: 0.0076 memory: 14901 loss: 1.4589 loss_prob: 0.8099 loss_thr: 0.5118 loss_db: 0.1373 2022/11/02 16:21:01 - mmengine - INFO - Epoch(train) [390][20/63] lr: 1.5198e-03 eta: 8:19:21 time: 0.5890 data_time: 0.0103 memory: 14901 loss: 1.3795 loss_prob: 0.7490 loss_thr: 0.5048 loss_db: 0.1256 2022/11/02 16:21:04 - mmengine - INFO - Epoch(train) [390][25/63] lr: 1.5198e-03 eta: 8:19:21 time: 0.5926 data_time: 0.0170 memory: 14901 loss: 1.4637 loss_prob: 0.8109 loss_thr: 0.5171 loss_db: 0.1356 2022/11/02 16:21:06 - mmengine - INFO - Epoch(train) [390][30/63] lr: 1.5198e-03 eta: 8:19:14 time: 0.5451 data_time: 0.0378 memory: 14901 loss: 1.5853 loss_prob: 0.8857 loss_thr: 0.5478 loss_db: 0.1518 2022/11/02 16:21:09 - mmengine - INFO - Epoch(train) [390][35/63] lr: 1.5198e-03 eta: 8:19:14 time: 0.5395 data_time: 0.0351 memory: 14901 loss: 1.6705 loss_prob: 0.9410 loss_thr: 0.5710 loss_db: 0.1585 2022/11/02 16:21:12 - mmengine - INFO - Epoch(train) [390][40/63] lr: 1.5198e-03 eta: 8:19:07 time: 0.5276 data_time: 0.0134 memory: 14901 loss: 1.5893 loss_prob: 0.8908 loss_thr: 0.5511 loss_db: 0.1474 2022/11/02 16:21:14 - mmengine - INFO - Epoch(train) [390][45/63] lr: 1.5198e-03 eta: 8:19:07 time: 0.5119 data_time: 0.0129 memory: 14901 loss: 1.4839 loss_prob: 0.8190 loss_thr: 0.5301 loss_db: 0.1349 2022/11/02 16:21:17 - mmengine - INFO - Epoch(train) [390][50/63] lr: 1.5198e-03 eta: 8:19:00 time: 0.5392 data_time: 0.0261 memory: 14901 loss: 1.5682 loss_prob: 0.8726 loss_thr: 0.5480 loss_db: 0.1476 2022/11/02 16:21:20 - mmengine - INFO - Epoch(train) [390][55/63] lr: 1.5198e-03 eta: 8:19:00 time: 0.5539 data_time: 0.0266 memory: 14901 loss: 1.5513 loss_prob: 0.8543 loss_thr: 0.5483 loss_db: 0.1487 2022/11/02 16:21:23 - mmengine - INFO - Epoch(train) [390][60/63] lr: 1.5198e-03 eta: 8:18:54 time: 0.5726 data_time: 0.0132 memory: 14901 loss: 1.6735 loss_prob: 0.9383 loss_thr: 0.5764 loss_db: 0.1588 2022/11/02 16:21:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:21:30 - mmengine - INFO - Epoch(train) [391][5/63] lr: 1.5181e-03 eta: 8:18:54 time: 0.8769 data_time: 0.2239 memory: 14901 loss: 1.6842 loss_prob: 0.9461 loss_thr: 0.5843 loss_db: 0.1538 2022/11/02 16:21:34 - mmengine - INFO - Epoch(train) [391][10/63] lr: 1.5181e-03 eta: 8:18:49 time: 0.9087 data_time: 0.2342 memory: 14901 loss: 1.7025 loss_prob: 0.9660 loss_thr: 0.5715 loss_db: 0.1650 2022/11/02 16:21:36 - mmengine - INFO - Epoch(train) [391][15/63] lr: 1.5181e-03 eta: 8:18:49 time: 0.6021 data_time: 0.0194 memory: 14901 loss: 1.7768 loss_prob: 1.0262 loss_thr: 0.5773 loss_db: 0.1733 2022/11/02 16:21:39 - mmengine - INFO - Epoch(train) [391][20/63] lr: 1.5181e-03 eta: 8:18:42 time: 0.5232 data_time: 0.0098 memory: 14901 loss: 1.7350 loss_prob: 0.9917 loss_thr: 0.5840 loss_db: 0.1593 2022/11/02 16:21:41 - mmengine - INFO - Epoch(train) [391][25/63] lr: 1.5181e-03 eta: 8:18:42 time: 0.4975 data_time: 0.0241 memory: 14901 loss: 1.5853 loss_prob: 0.8875 loss_thr: 0.5499 loss_db: 0.1480 2022/11/02 16:21:44 - mmengine - INFO - Epoch(train) [391][30/63] lr: 1.5181e-03 eta: 8:18:35 time: 0.5386 data_time: 0.0446 memory: 14901 loss: 1.6094 loss_prob: 0.9139 loss_thr: 0.5435 loss_db: 0.1519 2022/11/02 16:21:47 - mmengine - INFO - Epoch(train) [391][35/63] lr: 1.5181e-03 eta: 8:18:35 time: 0.5626 data_time: 0.0373 memory: 14901 loss: 1.6147 loss_prob: 0.9199 loss_thr: 0.5442 loss_db: 0.1506 2022/11/02 16:21:50 - mmengine - INFO - Epoch(train) [391][40/63] lr: 1.5181e-03 eta: 8:18:30 time: 0.6039 data_time: 0.0192 memory: 14901 loss: 1.5611 loss_prob: 0.8767 loss_thr: 0.5371 loss_db: 0.1473 2022/11/02 16:21:53 - mmengine - INFO - Epoch(train) [391][45/63] lr: 1.5181e-03 eta: 8:18:30 time: 0.5933 data_time: 0.0127 memory: 14901 loss: 1.5355 loss_prob: 0.8486 loss_thr: 0.5415 loss_db: 0.1454 2022/11/02 16:21:55 - mmengine - INFO - Epoch(train) [391][50/63] lr: 1.5181e-03 eta: 8:18:23 time: 0.5307 data_time: 0.0143 memory: 14901 loss: 1.4786 loss_prob: 0.8222 loss_thr: 0.5192 loss_db: 0.1372 2022/11/02 16:21:58 - mmengine - INFO - Epoch(train) [391][55/63] lr: 1.5181e-03 eta: 8:18:23 time: 0.5362 data_time: 0.0190 memory: 14901 loss: 1.4383 loss_prob: 0.7966 loss_thr: 0.5119 loss_db: 0.1297 2022/11/02 16:22:01 - mmengine - INFO - Epoch(train) [391][60/63] lr: 1.5181e-03 eta: 8:18:16 time: 0.5435 data_time: 0.0140 memory: 14901 loss: 1.5002 loss_prob: 0.8232 loss_thr: 0.5409 loss_db: 0.1361 2022/11/02 16:22:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:22:09 - mmengine - INFO - Epoch(train) [392][5/63] lr: 1.5164e-03 eta: 8:18:16 time: 0.9000 data_time: 0.3123 memory: 14901 loss: 1.6637 loss_prob: 0.9371 loss_thr: 0.5718 loss_db: 0.1548 2022/11/02 16:22:11 - mmengine - INFO - Epoch(train) [392][10/63] lr: 1.5164e-03 eta: 8:18:11 time: 0.9093 data_time: 0.3103 memory: 14901 loss: 1.6111 loss_prob: 0.9063 loss_thr: 0.5548 loss_db: 0.1500 2022/11/02 16:22:14 - mmengine - INFO - Epoch(train) [392][15/63] lr: 1.5164e-03 eta: 8:18:11 time: 0.5198 data_time: 0.0115 memory: 14901 loss: 1.6312 loss_prob: 0.9278 loss_thr: 0.5512 loss_db: 0.1522 2022/11/02 16:22:17 - mmengine - INFO - Epoch(train) [392][20/63] lr: 1.5164e-03 eta: 8:18:05 time: 0.5513 data_time: 0.0125 memory: 14901 loss: 1.6455 loss_prob: 0.9324 loss_thr: 0.5585 loss_db: 0.1546 2022/11/02 16:22:20 - mmengine - INFO - Epoch(train) [392][25/63] lr: 1.5164e-03 eta: 8:18:05 time: 0.5627 data_time: 0.0411 memory: 14901 loss: 1.6081 loss_prob: 0.9108 loss_thr: 0.5466 loss_db: 0.1507 2022/11/02 16:22:22 - mmengine - INFO - Epoch(train) [392][30/63] lr: 1.5164e-03 eta: 8:17:58 time: 0.5492 data_time: 0.0453 memory: 14901 loss: 1.5693 loss_prob: 0.8915 loss_thr: 0.5323 loss_db: 0.1455 2022/11/02 16:22:25 - mmengine - INFO - Epoch(train) [392][35/63] lr: 1.5164e-03 eta: 8:17:58 time: 0.5334 data_time: 0.0159 memory: 14901 loss: 1.5861 loss_prob: 0.9078 loss_thr: 0.5323 loss_db: 0.1460 2022/11/02 16:22:28 - mmengine - INFO - Epoch(train) [392][40/63] lr: 1.5164e-03 eta: 8:17:51 time: 0.5494 data_time: 0.0133 memory: 14901 loss: 1.5149 loss_prob: 0.8564 loss_thr: 0.5197 loss_db: 0.1389 2022/11/02 16:22:31 - mmengine - INFO - Epoch(train) [392][45/63] lr: 1.5164e-03 eta: 8:17:51 time: 0.5682 data_time: 0.0110 memory: 14901 loss: 1.5768 loss_prob: 0.8834 loss_thr: 0.5493 loss_db: 0.1441 2022/11/02 16:22:33 - mmengine - INFO - Epoch(train) [392][50/63] lr: 1.5164e-03 eta: 8:17:45 time: 0.5408 data_time: 0.0198 memory: 14901 loss: 1.5586 loss_prob: 0.8587 loss_thr: 0.5585 loss_db: 0.1414 2022/11/02 16:22:36 - mmengine - INFO - Epoch(train) [392][55/63] lr: 1.5164e-03 eta: 8:17:45 time: 0.5394 data_time: 0.0272 memory: 14901 loss: 1.4964 loss_prob: 0.8223 loss_thr: 0.5379 loss_db: 0.1362 2022/11/02 16:22:39 - mmengine - INFO - Epoch(train) [392][60/63] lr: 1.5164e-03 eta: 8:17:39 time: 0.6009 data_time: 0.0148 memory: 14901 loss: 1.6442 loss_prob: 0.9251 loss_thr: 0.5656 loss_db: 0.1534 2022/11/02 16:22:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:22:46 - mmengine - INFO - Epoch(train) [393][5/63] lr: 1.5147e-03 eta: 8:17:39 time: 0.7824 data_time: 0.2246 memory: 14901 loss: 1.4869 loss_prob: 0.8090 loss_thr: 0.5446 loss_db: 0.1333 2022/11/02 16:22:50 - mmengine - INFO - Epoch(train) [393][10/63] lr: 1.5147e-03 eta: 8:17:35 time: 0.9245 data_time: 0.2256 memory: 14901 loss: 1.4289 loss_prob: 0.7829 loss_thr: 0.5150 loss_db: 0.1310 2022/11/02 16:22:52 - mmengine - INFO - Epoch(train) [393][15/63] lr: 1.5147e-03 eta: 8:17:35 time: 0.6240 data_time: 0.0103 memory: 14901 loss: 1.5760 loss_prob: 0.8799 loss_thr: 0.5490 loss_db: 0.1470 2022/11/02 16:22:55 - mmengine - INFO - Epoch(train) [393][20/63] lr: 1.5147e-03 eta: 8:17:28 time: 0.5277 data_time: 0.0060 memory: 14901 loss: 1.6143 loss_prob: 0.8963 loss_thr: 0.5662 loss_db: 0.1518 2022/11/02 16:22:58 - mmengine - INFO - Epoch(train) [393][25/63] lr: 1.5147e-03 eta: 8:17:28 time: 0.5664 data_time: 0.0116 memory: 14901 loss: 1.4960 loss_prob: 0.8305 loss_thr: 0.5267 loss_db: 0.1388 2022/11/02 16:23:01 - mmengine - INFO - Epoch(train) [393][30/63] lr: 1.5147e-03 eta: 8:17:23 time: 0.6236 data_time: 0.0407 memory: 14901 loss: 1.5114 loss_prob: 0.8381 loss_thr: 0.5350 loss_db: 0.1383 2022/11/02 16:23:04 - mmengine - INFO - Epoch(train) [393][35/63] lr: 1.5147e-03 eta: 8:17:23 time: 0.5727 data_time: 0.0390 memory: 14901 loss: 1.5015 loss_prob: 0.8206 loss_thr: 0.5422 loss_db: 0.1387 2022/11/02 16:23:06 - mmengine - INFO - Epoch(train) [393][40/63] lr: 1.5147e-03 eta: 8:17:15 time: 0.4943 data_time: 0.0095 memory: 14901 loss: 1.4391 loss_prob: 0.7877 loss_thr: 0.5194 loss_db: 0.1321 2022/11/02 16:23:09 - mmengine - INFO - Epoch(train) [393][45/63] lr: 1.5147e-03 eta: 8:17:15 time: 0.5261 data_time: 0.0113 memory: 14901 loss: 1.4136 loss_prob: 0.7695 loss_thr: 0.5171 loss_db: 0.1271 2022/11/02 16:23:12 - mmengine - INFO - Epoch(train) [393][50/63] lr: 1.5147e-03 eta: 8:17:08 time: 0.5350 data_time: 0.0208 memory: 14901 loss: 1.4538 loss_prob: 0.7975 loss_thr: 0.5248 loss_db: 0.1314 2022/11/02 16:23:14 - mmengine - INFO - Epoch(train) [393][55/63] lr: 1.5147e-03 eta: 8:17:08 time: 0.5176 data_time: 0.0266 memory: 14901 loss: 1.4480 loss_prob: 0.7974 loss_thr: 0.5186 loss_db: 0.1320 2022/11/02 16:23:17 - mmengine - INFO - Epoch(train) [393][60/63] lr: 1.5147e-03 eta: 8:17:01 time: 0.5354 data_time: 0.0219 memory: 14901 loss: 1.4900 loss_prob: 0.8176 loss_thr: 0.5343 loss_db: 0.1381 2022/11/02 16:23:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:23:24 - mmengine - INFO - Epoch(train) [394][5/63] lr: 1.5130e-03 eta: 8:17:01 time: 0.8166 data_time: 0.2374 memory: 14901 loss: 1.6831 loss_prob: 0.9870 loss_thr: 0.5471 loss_db: 0.1490 2022/11/02 16:23:26 - mmengine - INFO - Epoch(train) [394][10/63] lr: 1.5130e-03 eta: 8:16:54 time: 0.8087 data_time: 0.2378 memory: 14901 loss: 1.6387 loss_prob: 0.9608 loss_thr: 0.5311 loss_db: 0.1469 2022/11/02 16:23:29 - mmengine - INFO - Epoch(train) [394][15/63] lr: 1.5130e-03 eta: 8:16:54 time: 0.5278 data_time: 0.0089 memory: 14901 loss: 1.5280 loss_prob: 0.8441 loss_thr: 0.5398 loss_db: 0.1441 2022/11/02 16:23:33 - mmengine - INFO - Epoch(train) [394][20/63] lr: 1.5130e-03 eta: 8:16:50 time: 0.6578 data_time: 0.0092 memory: 14901 loss: 1.4853 loss_prob: 0.8160 loss_thr: 0.5311 loss_db: 0.1383 2022/11/02 16:23:36 - mmengine - INFO - Epoch(train) [394][25/63] lr: 1.5130e-03 eta: 8:16:50 time: 0.6714 data_time: 0.0305 memory: 14901 loss: 1.4346 loss_prob: 0.7805 loss_thr: 0.5239 loss_db: 0.1303 2022/11/02 16:23:39 - mmengine - INFO - Epoch(train) [394][30/63] lr: 1.5130e-03 eta: 8:16:44 time: 0.5669 data_time: 0.0429 memory: 14901 loss: 1.5103 loss_prob: 0.8364 loss_thr: 0.5320 loss_db: 0.1419 2022/11/02 16:23:41 - mmengine - INFO - Epoch(train) [394][35/63] lr: 1.5130e-03 eta: 8:16:44 time: 0.5265 data_time: 0.0209 memory: 14901 loss: 1.6107 loss_prob: 0.8974 loss_thr: 0.5612 loss_db: 0.1521 2022/11/02 16:23:44 - mmengine - INFO - Epoch(train) [394][40/63] lr: 1.5130e-03 eta: 8:16:36 time: 0.4844 data_time: 0.0116 memory: 14901 loss: 1.5776 loss_prob: 0.8799 loss_thr: 0.5553 loss_db: 0.1424 2022/11/02 16:23:46 - mmengine - INFO - Epoch(train) [394][45/63] lr: 1.5130e-03 eta: 8:16:36 time: 0.5087 data_time: 0.0123 memory: 14901 loss: 1.4849 loss_prob: 0.8408 loss_thr: 0.5096 loss_db: 0.1345 2022/11/02 16:23:49 - mmengine - INFO - Epoch(train) [394][50/63] lr: 1.5130e-03 eta: 8:16:28 time: 0.5100 data_time: 0.0220 memory: 14901 loss: 1.4841 loss_prob: 0.8304 loss_thr: 0.5158 loss_db: 0.1379 2022/11/02 16:23:52 - mmengine - INFO - Epoch(train) [394][55/63] lr: 1.5130e-03 eta: 8:16:28 time: 0.5291 data_time: 0.0234 memory: 14901 loss: 1.4955 loss_prob: 0.8247 loss_thr: 0.5322 loss_db: 0.1385 2022/11/02 16:23:55 - mmengine - INFO - Epoch(train) [394][60/63] lr: 1.5130e-03 eta: 8:16:23 time: 0.5943 data_time: 0.0108 memory: 14901 loss: 1.5409 loss_prob: 0.8612 loss_thr: 0.5385 loss_db: 0.1412 2022/11/02 16:23:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:24:01 - mmengine - INFO - Epoch(train) [395][5/63] lr: 1.5113e-03 eta: 8:16:23 time: 0.8175 data_time: 0.2174 memory: 14901 loss: 1.4049 loss_prob: 0.7676 loss_thr: 0.5087 loss_db: 0.1286 2022/11/02 16:24:04 - mmengine - INFO - Epoch(train) [395][10/63] lr: 1.5113e-03 eta: 8:16:16 time: 0.8385 data_time: 0.2470 memory: 14901 loss: 1.4025 loss_prob: 0.7619 loss_thr: 0.5119 loss_db: 0.1288 2022/11/02 16:24:07 - mmengine - INFO - Epoch(train) [395][15/63] lr: 1.5113e-03 eta: 8:16:16 time: 0.5615 data_time: 0.0363 memory: 14901 loss: 1.4155 loss_prob: 0.7763 loss_thr: 0.5085 loss_db: 0.1307 2022/11/02 16:24:10 - mmengine - INFO - Epoch(train) [395][20/63] lr: 1.5113e-03 eta: 8:16:10 time: 0.5401 data_time: 0.0104 memory: 14901 loss: 1.4040 loss_prob: 0.7792 loss_thr: 0.4952 loss_db: 0.1296 2022/11/02 16:24:13 - mmengine - INFO - Epoch(train) [395][25/63] lr: 1.5113e-03 eta: 8:16:10 time: 0.5594 data_time: 0.0136 memory: 14901 loss: 1.4268 loss_prob: 0.7862 loss_thr: 0.5075 loss_db: 0.1331 2022/11/02 16:24:15 - mmengine - INFO - Epoch(train) [395][30/63] lr: 1.5113e-03 eta: 8:16:02 time: 0.5240 data_time: 0.0123 memory: 14901 loss: 1.4625 loss_prob: 0.7946 loss_thr: 0.5309 loss_db: 0.1369 2022/11/02 16:24:18 - mmengine - INFO - Epoch(train) [395][35/63] lr: 1.5113e-03 eta: 8:16:02 time: 0.5034 data_time: 0.0213 memory: 14901 loss: 1.4475 loss_prob: 0.7842 loss_thr: 0.5300 loss_db: 0.1333 2022/11/02 16:24:20 - mmengine - INFO - Epoch(train) [395][40/63] lr: 1.5113e-03 eta: 8:15:55 time: 0.5101 data_time: 0.0211 memory: 14901 loss: 1.4987 loss_prob: 0.8255 loss_thr: 0.5335 loss_db: 0.1397 2022/11/02 16:24:23 - mmengine - INFO - Epoch(train) [395][45/63] lr: 1.5113e-03 eta: 8:15:55 time: 0.5027 data_time: 0.0090 memory: 14901 loss: 1.5133 loss_prob: 0.8328 loss_thr: 0.5416 loss_db: 0.1388 2022/11/02 16:24:25 - mmengine - INFO - Epoch(train) [395][50/63] lr: 1.5113e-03 eta: 8:15:48 time: 0.5038 data_time: 0.0064 memory: 14901 loss: 1.4412 loss_prob: 0.7790 loss_thr: 0.5321 loss_db: 0.1301 2022/11/02 16:24:28 - mmengine - INFO - Epoch(train) [395][55/63] lr: 1.5113e-03 eta: 8:15:48 time: 0.5431 data_time: 0.0290 memory: 14901 loss: 1.4421 loss_prob: 0.7886 loss_thr: 0.5229 loss_db: 0.1307 2022/11/02 16:24:31 - mmengine - INFO - Epoch(train) [395][60/63] lr: 1.5113e-03 eta: 8:15:41 time: 0.5319 data_time: 0.0291 memory: 14901 loss: 1.4192 loss_prob: 0.7960 loss_thr: 0.4931 loss_db: 0.1301 2022/11/02 16:24:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:24:37 - mmengine - INFO - Epoch(train) [396][5/63] lr: 1.5096e-03 eta: 8:15:41 time: 0.7102 data_time: 0.2373 memory: 14901 loss: 1.5350 loss_prob: 0.8604 loss_thr: 0.5256 loss_db: 0.1491 2022/11/02 16:24:39 - mmengine - INFO - Epoch(train) [396][10/63] lr: 1.5096e-03 eta: 8:15:32 time: 0.7235 data_time: 0.2366 memory: 14901 loss: 1.4753 loss_prob: 0.8137 loss_thr: 0.5234 loss_db: 0.1382 2022/11/02 16:24:42 - mmengine - INFO - Epoch(train) [396][15/63] lr: 1.5096e-03 eta: 8:15:32 time: 0.5162 data_time: 0.0135 memory: 14901 loss: 1.4739 loss_prob: 0.8176 loss_thr: 0.5208 loss_db: 0.1355 2022/11/02 16:24:45 - mmengine - INFO - Epoch(train) [396][20/63] lr: 1.5096e-03 eta: 8:15:27 time: 0.6316 data_time: 0.0122 memory: 14901 loss: 1.3965 loss_prob: 0.7664 loss_thr: 0.4984 loss_db: 0.1317 2022/11/02 16:24:48 - mmengine - INFO - Epoch(train) [396][25/63] lr: 1.5096e-03 eta: 8:15:27 time: 0.6152 data_time: 0.0119 memory: 14901 loss: 1.3929 loss_prob: 0.7557 loss_thr: 0.5060 loss_db: 0.1312 2022/11/02 16:24:51 - mmengine - INFO - Epoch(train) [396][30/63] lr: 1.5096e-03 eta: 8:15:20 time: 0.5452 data_time: 0.0447 memory: 14901 loss: 1.4562 loss_prob: 0.7957 loss_thr: 0.5287 loss_db: 0.1318 2022/11/02 16:24:54 - mmengine - INFO - Epoch(train) [396][35/63] lr: 1.5096e-03 eta: 8:15:20 time: 0.5984 data_time: 0.0396 memory: 14901 loss: 1.4274 loss_prob: 0.7897 loss_thr: 0.5058 loss_db: 0.1319 2022/11/02 16:24:57 - mmengine - INFO - Epoch(train) [396][40/63] lr: 1.5096e-03 eta: 8:15:15 time: 0.6016 data_time: 0.0105 memory: 14901 loss: 1.4405 loss_prob: 0.7980 loss_thr: 0.5050 loss_db: 0.1375 2022/11/02 16:24:59 - mmengine - INFO - Epoch(train) [396][45/63] lr: 1.5096e-03 eta: 8:15:15 time: 0.5376 data_time: 0.0114 memory: 14901 loss: 1.4579 loss_prob: 0.8071 loss_thr: 0.5133 loss_db: 0.1375 2022/11/02 16:25:03 - mmengine - INFO - Epoch(train) [396][50/63] lr: 1.5096e-03 eta: 8:15:09 time: 0.5780 data_time: 0.0162 memory: 14901 loss: 1.3987 loss_prob: 0.7732 loss_thr: 0.4950 loss_db: 0.1305 2022/11/02 16:25:06 - mmengine - INFO - Epoch(train) [396][55/63] lr: 1.5096e-03 eta: 8:15:09 time: 0.6137 data_time: 0.0266 memory: 14901 loss: 1.3323 loss_prob: 0.7184 loss_thr: 0.4926 loss_db: 0.1213 2022/11/02 16:25:08 - mmengine - INFO - Epoch(train) [396][60/63] lr: 1.5096e-03 eta: 8:15:02 time: 0.5267 data_time: 0.0168 memory: 14901 loss: 1.4076 loss_prob: 0.7623 loss_thr: 0.5184 loss_db: 0.1269 2022/11/02 16:25:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:25:15 - mmengine - INFO - Epoch(train) [397][5/63] lr: 1.5079e-03 eta: 8:15:02 time: 0.8285 data_time: 0.2586 memory: 14901 loss: 1.4829 loss_prob: 0.8104 loss_thr: 0.5374 loss_db: 0.1350 2022/11/02 16:25:18 - mmengine - INFO - Epoch(train) [397][10/63] lr: 1.5079e-03 eta: 8:14:56 time: 0.8559 data_time: 0.2598 memory: 14901 loss: 1.5073 loss_prob: 0.8405 loss_thr: 0.5307 loss_db: 0.1361 2022/11/02 16:25:21 - mmengine - INFO - Epoch(train) [397][15/63] lr: 1.5079e-03 eta: 8:14:56 time: 0.5368 data_time: 0.0151 memory: 14901 loss: 1.4664 loss_prob: 0.8184 loss_thr: 0.5122 loss_db: 0.1357 2022/11/02 16:25:23 - mmengine - INFO - Epoch(train) [397][20/63] lr: 1.5079e-03 eta: 8:14:50 time: 0.5594 data_time: 0.0429 memory: 14901 loss: 1.3765 loss_prob: 0.7534 loss_thr: 0.4951 loss_db: 0.1280 2022/11/02 16:25:26 - mmengine - INFO - Epoch(train) [397][25/63] lr: 1.5079e-03 eta: 8:14:50 time: 0.5099 data_time: 0.0396 memory: 14901 loss: 1.4278 loss_prob: 0.7851 loss_thr: 0.5104 loss_db: 0.1323 2022/11/02 16:25:29 - mmengine - INFO - Epoch(train) [397][30/63] lr: 1.5079e-03 eta: 8:14:43 time: 0.5411 data_time: 0.0099 memory: 14901 loss: 1.4600 loss_prob: 0.8070 loss_thr: 0.5163 loss_db: 0.1367 2022/11/02 16:25:32 - mmengine - INFO - Epoch(train) [397][35/63] lr: 1.5079e-03 eta: 8:14:43 time: 0.5880 data_time: 0.0195 memory: 14901 loss: 1.4396 loss_prob: 0.7997 loss_thr: 0.5108 loss_db: 0.1290 2022/11/02 16:25:34 - mmengine - INFO - Epoch(train) [397][40/63] lr: 1.5079e-03 eta: 8:14:36 time: 0.5425 data_time: 0.0152 memory: 14901 loss: 1.4938 loss_prob: 0.8278 loss_thr: 0.5345 loss_db: 0.1315 2022/11/02 16:25:37 - mmengine - INFO - Epoch(train) [397][45/63] lr: 1.5079e-03 eta: 8:14:36 time: 0.5835 data_time: 0.0321 memory: 14901 loss: 1.4668 loss_prob: 0.7936 loss_thr: 0.5403 loss_db: 0.1328 2022/11/02 16:25:40 - mmengine - INFO - Epoch(train) [397][50/63] lr: 1.5079e-03 eta: 8:14:30 time: 0.5601 data_time: 0.0336 memory: 14901 loss: 1.4542 loss_prob: 0.7900 loss_thr: 0.5299 loss_db: 0.1342 2022/11/02 16:25:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:25:42 - mmengine - INFO - Epoch(train) [397][55/63] lr: 1.5079e-03 eta: 8:14:30 time: 0.4839 data_time: 0.0110 memory: 14901 loss: 1.4930 loss_prob: 0.8225 loss_thr: 0.5332 loss_db: 0.1373 2022/11/02 16:25:45 - mmengine - INFO - Epoch(train) [397][60/63] lr: 1.5079e-03 eta: 8:14:22 time: 0.5148 data_time: 0.0152 memory: 14901 loss: 1.5437 loss_prob: 0.8549 loss_thr: 0.5464 loss_db: 0.1424 2022/11/02 16:25:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:25:52 - mmengine - INFO - Epoch(train) [398][5/63] lr: 1.5062e-03 eta: 8:14:22 time: 0.7876 data_time: 0.2074 memory: 14901 loss: 1.6219 loss_prob: 0.9162 loss_thr: 0.5511 loss_db: 0.1545 2022/11/02 16:25:55 - mmengine - INFO - Epoch(train) [398][10/63] lr: 1.5062e-03 eta: 8:14:16 time: 0.8143 data_time: 0.2158 memory: 14901 loss: 1.6209 loss_prob: 0.8968 loss_thr: 0.5751 loss_db: 0.1490 2022/11/02 16:25:57 - mmengine - INFO - Epoch(train) [398][15/63] lr: 1.5062e-03 eta: 8:14:16 time: 0.5400 data_time: 0.0147 memory: 14901 loss: 1.5500 loss_prob: 0.8529 loss_thr: 0.5556 loss_db: 0.1415 2022/11/02 16:26:00 - mmengine - INFO - Epoch(train) [398][20/63] lr: 1.5062e-03 eta: 8:14:09 time: 0.5363 data_time: 0.0106 memory: 14901 loss: 1.3463 loss_prob: 0.7273 loss_thr: 0.4930 loss_db: 0.1260 2022/11/02 16:26:03 - mmengine - INFO - Epoch(train) [398][25/63] lr: 1.5062e-03 eta: 8:14:09 time: 0.5583 data_time: 0.0456 memory: 14901 loss: 1.4166 loss_prob: 0.7807 loss_thr: 0.5048 loss_db: 0.1311 2022/11/02 16:26:06 - mmengine - INFO - Epoch(train) [398][30/63] lr: 1.5062e-03 eta: 8:14:03 time: 0.5616 data_time: 0.0476 memory: 14901 loss: 1.5664 loss_prob: 0.8816 loss_thr: 0.5375 loss_db: 0.1474 2022/11/02 16:26:10 - mmengine - INFO - Epoch(train) [398][35/63] lr: 1.5062e-03 eta: 8:14:03 time: 0.6854 data_time: 0.0132 memory: 14901 loss: 1.7080 loss_prob: 0.9796 loss_thr: 0.5638 loss_db: 0.1646 2022/11/02 16:26:13 - mmengine - INFO - Epoch(train) [398][40/63] lr: 1.5062e-03 eta: 8:13:59 time: 0.7078 data_time: 0.0097 memory: 14901 loss: 1.7004 loss_prob: 0.9865 loss_thr: 0.5521 loss_db: 0.1618 2022/11/02 16:26:15 - mmengine - INFO - Epoch(train) [398][45/63] lr: 1.5062e-03 eta: 8:13:59 time: 0.5399 data_time: 0.0096 memory: 14901 loss: 1.7097 loss_prob: 0.9922 loss_thr: 0.5523 loss_db: 0.1652 2022/11/02 16:26:18 - mmengine - INFO - Epoch(train) [398][50/63] lr: 1.5062e-03 eta: 8:13:53 time: 0.5605 data_time: 0.0247 memory: 14901 loss: 1.8240 loss_prob: 1.0678 loss_thr: 0.5736 loss_db: 0.1826 2022/11/02 16:26:21 - mmengine - INFO - Epoch(train) [398][55/63] lr: 1.5062e-03 eta: 8:13:53 time: 0.6248 data_time: 0.0316 memory: 14901 loss: 1.6966 loss_prob: 0.9792 loss_thr: 0.5544 loss_db: 0.1630 2022/11/02 16:26:24 - mmengine - INFO - Epoch(train) [398][60/63] lr: 1.5062e-03 eta: 8:13:47 time: 0.5748 data_time: 0.0168 memory: 14901 loss: 1.4721 loss_prob: 0.8235 loss_thr: 0.5121 loss_db: 0.1366 2022/11/02 16:26:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:26:32 - mmengine - INFO - Epoch(train) [399][5/63] lr: 1.5046e-03 eta: 8:13:47 time: 0.8784 data_time: 0.2787 memory: 14901 loss: 1.4758 loss_prob: 0.8262 loss_thr: 0.5102 loss_db: 0.1394 2022/11/02 16:26:34 - mmengine - INFO - Epoch(train) [399][10/63] lr: 1.5046e-03 eta: 8:13:42 time: 0.9109 data_time: 0.2764 memory: 14901 loss: 1.5831 loss_prob: 0.8958 loss_thr: 0.5400 loss_db: 0.1473 2022/11/02 16:26:37 - mmengine - INFO - Epoch(train) [399][15/63] lr: 1.5046e-03 eta: 8:13:42 time: 0.5606 data_time: 0.0137 memory: 14901 loss: 1.5194 loss_prob: 0.8474 loss_thr: 0.5315 loss_db: 0.1405 2022/11/02 16:26:40 - mmengine - INFO - Epoch(train) [399][20/63] lr: 1.5046e-03 eta: 8:13:35 time: 0.5214 data_time: 0.0117 memory: 14901 loss: 1.4882 loss_prob: 0.8134 loss_thr: 0.5388 loss_db: 0.1361 2022/11/02 16:26:43 - mmengine - INFO - Epoch(train) [399][25/63] lr: 1.5046e-03 eta: 8:13:35 time: 0.5441 data_time: 0.0430 memory: 14901 loss: 1.4572 loss_prob: 0.7893 loss_thr: 0.5332 loss_db: 0.1347 2022/11/02 16:26:45 - mmengine - INFO - Epoch(train) [399][30/63] lr: 1.5046e-03 eta: 8:13:29 time: 0.5719 data_time: 0.0437 memory: 14901 loss: 1.4550 loss_prob: 0.7900 loss_thr: 0.5282 loss_db: 0.1368 2022/11/02 16:26:48 - mmengine - INFO - Epoch(train) [399][35/63] lr: 1.5046e-03 eta: 8:13:29 time: 0.5512 data_time: 0.0101 memory: 14901 loss: 1.4582 loss_prob: 0.7953 loss_thr: 0.5280 loss_db: 0.1349 2022/11/02 16:26:51 - mmengine - INFO - Epoch(train) [399][40/63] lr: 1.5046e-03 eta: 8:13:22 time: 0.5307 data_time: 0.0155 memory: 14901 loss: 1.4901 loss_prob: 0.8152 loss_thr: 0.5393 loss_db: 0.1356 2022/11/02 16:26:53 - mmengine - INFO - Epoch(train) [399][45/63] lr: 1.5046e-03 eta: 8:13:22 time: 0.4899 data_time: 0.0122 memory: 14901 loss: 1.5055 loss_prob: 0.8271 loss_thr: 0.5410 loss_db: 0.1374 2022/11/02 16:26:57 - mmengine - INFO - Epoch(train) [399][50/63] lr: 1.5046e-03 eta: 8:13:17 time: 0.6344 data_time: 0.0210 memory: 14901 loss: 1.4849 loss_prob: 0.8207 loss_thr: 0.5272 loss_db: 0.1369 2022/11/02 16:27:00 - mmengine - INFO - Epoch(train) [399][55/63] lr: 1.5046e-03 eta: 8:13:17 time: 0.6614 data_time: 0.0246 memory: 14901 loss: 1.4778 loss_prob: 0.8179 loss_thr: 0.5217 loss_db: 0.1382 2022/11/02 16:27:02 - mmengine - INFO - Epoch(train) [399][60/63] lr: 1.5046e-03 eta: 8:13:10 time: 0.5263 data_time: 0.0101 memory: 14901 loss: 1.4549 loss_prob: 0.8084 loss_thr: 0.5079 loss_db: 0.1386 2022/11/02 16:27:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:27:10 - mmengine - INFO - Epoch(train) [400][5/63] lr: 1.5029e-03 eta: 8:13:10 time: 0.8292 data_time: 0.2944 memory: 14901 loss: 1.6053 loss_prob: 0.8885 loss_thr: 0.5675 loss_db: 0.1492 2022/11/02 16:27:12 - mmengine - INFO - Epoch(train) [400][10/63] lr: 1.5029e-03 eta: 8:13:05 time: 0.8824 data_time: 0.2935 memory: 14901 loss: 1.5313 loss_prob: 0.8531 loss_thr: 0.5347 loss_db: 0.1434 2022/11/02 16:27:15 - mmengine - INFO - Epoch(train) [400][15/63] lr: 1.5029e-03 eta: 8:13:05 time: 0.5457 data_time: 0.0107 memory: 14901 loss: 1.3505 loss_prob: 0.7376 loss_thr: 0.4884 loss_db: 0.1245 2022/11/02 16:27:18 - mmengine - INFO - Epoch(train) [400][20/63] lr: 1.5029e-03 eta: 8:12:58 time: 0.5345 data_time: 0.0073 memory: 14901 loss: 1.3892 loss_prob: 0.7555 loss_thr: 0.5056 loss_db: 0.1281 2022/11/02 16:27:22 - mmengine - INFO - Epoch(train) [400][25/63] lr: 1.5029e-03 eta: 8:12:58 time: 0.6473 data_time: 0.0437 memory: 14901 loss: 1.4877 loss_prob: 0.8157 loss_thr: 0.5344 loss_db: 0.1376 2022/11/02 16:27:24 - mmengine - INFO - Epoch(train) [400][30/63] lr: 1.5029e-03 eta: 8:12:53 time: 0.6244 data_time: 0.0450 memory: 14901 loss: 1.4694 loss_prob: 0.8048 loss_thr: 0.5282 loss_db: 0.1364 2022/11/02 16:27:27 - mmengine - INFO - Epoch(train) [400][35/63] lr: 1.5029e-03 eta: 8:12:53 time: 0.5110 data_time: 0.0066 memory: 14901 loss: 1.3941 loss_prob: 0.7602 loss_thr: 0.5036 loss_db: 0.1303 2022/11/02 16:27:30 - mmengine - INFO - Epoch(train) [400][40/63] lr: 1.5029e-03 eta: 8:12:46 time: 0.5663 data_time: 0.0103 memory: 14901 loss: 1.3721 loss_prob: 0.7425 loss_thr: 0.5037 loss_db: 0.1259 2022/11/02 16:27:33 - mmengine - INFO - Epoch(train) [400][45/63] lr: 1.5029e-03 eta: 8:12:46 time: 0.6156 data_time: 0.0109 memory: 14901 loss: 1.4040 loss_prob: 0.7551 loss_thr: 0.5210 loss_db: 0.1280 2022/11/02 16:27:36 - mmengine - INFO - Epoch(train) [400][50/63] lr: 1.5029e-03 eta: 8:12:41 time: 0.6327 data_time: 0.0356 memory: 14901 loss: 1.4241 loss_prob: 0.7681 loss_thr: 0.5248 loss_db: 0.1312 2022/11/02 16:27:38 - mmengine - INFO - Epoch(train) [400][55/63] lr: 1.5029e-03 eta: 8:12:41 time: 0.5514 data_time: 0.0360 memory: 14901 loss: 1.4262 loss_prob: 0.7837 loss_thr: 0.5089 loss_db: 0.1336 2022/11/02 16:27:41 - mmengine - INFO - Epoch(train) [400][60/63] lr: 1.5029e-03 eta: 8:12:34 time: 0.5327 data_time: 0.0061 memory: 14901 loss: 1.4788 loss_prob: 0.8253 loss_thr: 0.5153 loss_db: 0.1382 2022/11/02 16:27:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:27:43 - mmengine - INFO - Saving checkpoint at 400 epochs 2022/11/02 16:27:47 - mmengine - INFO - Epoch(val) [400][5/500] eta: 8:12:34 time: 0.0456 data_time: 0.0054 memory: 14901 2022/11/02 16:27:47 - mmengine - INFO - Epoch(val) [400][10/500] eta: 0:00:21 time: 0.0445 data_time: 0.0055 memory: 1008 2022/11/02 16:27:47 - mmengine - INFO - Epoch(val) [400][15/500] eta: 0:00:21 time: 0.0425 data_time: 0.0036 memory: 1008 2022/11/02 16:27:47 - mmengine - INFO - Epoch(val) [400][20/500] eta: 0:00:22 time: 0.0462 data_time: 0.0036 memory: 1008 2022/11/02 16:27:47 - mmengine - INFO - Epoch(val) [400][25/500] eta: 0:00:22 time: 0.0390 data_time: 0.0025 memory: 1008 2022/11/02 16:27:48 - mmengine - INFO - Epoch(val) [400][30/500] eta: 0:00:18 time: 0.0394 data_time: 0.0023 memory: 1008 2022/11/02 16:27:48 - mmengine - INFO - Epoch(val) [400][35/500] eta: 0:00:18 time: 0.0398 data_time: 0.0022 memory: 1008 2022/11/02 16:27:48 - mmengine - INFO - Epoch(val) [400][40/500] eta: 0:00:19 time: 0.0419 data_time: 0.0045 memory: 1008 2022/11/02 16:27:48 - mmengine - INFO - Epoch(val) [400][45/500] eta: 0:00:19 time: 0.0434 data_time: 0.0047 memory: 1008 2022/11/02 16:27:49 - mmengine - INFO - Epoch(val) [400][50/500] eta: 0:00:50 time: 0.1127 data_time: 0.0758 memory: 1008 2022/11/02 16:27:49 - mmengine - INFO - Epoch(val) [400][55/500] eta: 0:00:50 time: 0.1150 data_time: 0.0754 memory: 1008 2022/11/02 16:27:50 - mmengine - INFO - Epoch(val) [400][60/500] eta: 0:00:17 time: 0.0392 data_time: 0.0019 memory: 1008 2022/11/02 16:27:50 - mmengine - INFO - Epoch(val) [400][65/500] eta: 0:00:17 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 16:27:50 - mmengine - INFO - Epoch(val) [400][70/500] eta: 0:00:17 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 16:27:50 - mmengine - INFO - Epoch(val) [400][75/500] eta: 0:00:17 time: 0.0451 data_time: 0.0052 memory: 1008 2022/11/02 16:27:50 - mmengine - INFO - Epoch(val) [400][80/500] eta: 0:00:17 time: 0.0426 data_time: 0.0052 memory: 1008 2022/11/02 16:27:51 - mmengine - INFO - Epoch(val) [400][85/500] eta: 0:00:17 time: 0.0334 data_time: 0.0024 memory: 1008 2022/11/02 16:27:51 - mmengine - INFO - Epoch(val) [400][90/500] eta: 0:00:15 time: 0.0368 data_time: 0.0023 memory: 1008 2022/11/02 16:27:51 - mmengine - INFO - Epoch(val) [400][95/500] eta: 0:00:15 time: 0.0401 data_time: 0.0024 memory: 1008 2022/11/02 16:27:51 - mmengine - INFO - Epoch(val) [400][100/500] eta: 0:00:15 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 16:27:51 - mmengine - INFO - Epoch(val) [400][105/500] eta: 0:00:15 time: 0.0404 data_time: 0.0027 memory: 1008 2022/11/02 16:27:51 - mmengine - INFO - Epoch(val) [400][110/500] eta: 0:00:14 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/02 16:27:52 - mmengine - INFO - Epoch(val) [400][115/500] eta: 0:00:14 time: 0.0363 data_time: 0.0023 memory: 1008 2022/11/02 16:27:52 - mmengine - INFO - Epoch(val) [400][120/500] eta: 0:00:14 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/02 16:27:52 - mmengine - INFO - Epoch(val) [400][125/500] eta: 0:00:14 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/02 16:27:52 - mmengine - INFO - Epoch(val) [400][130/500] eta: 0:00:12 time: 0.0350 data_time: 0.0022 memory: 1008 2022/11/02 16:27:52 - mmengine - INFO - Epoch(val) [400][135/500] eta: 0:00:12 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/02 16:27:53 - mmengine - INFO - Epoch(val) [400][140/500] eta: 0:00:14 time: 0.0411 data_time: 0.0029 memory: 1008 2022/11/02 16:27:53 - mmengine - INFO - Epoch(val) [400][145/500] eta: 0:00:14 time: 0.0392 data_time: 0.0023 memory: 1008 2022/11/02 16:27:53 - mmengine - INFO - Epoch(val) [400][150/500] eta: 0:00:14 time: 0.0419 data_time: 0.0022 memory: 1008 2022/11/02 16:27:53 - mmengine - INFO - Epoch(val) [400][155/500] eta: 0:00:14 time: 0.0432 data_time: 0.0022 memory: 1008 2022/11/02 16:27:53 - mmengine - INFO - Epoch(val) [400][160/500] eta: 0:00:13 time: 0.0411 data_time: 0.0021 memory: 1008 2022/11/02 16:27:54 - mmengine - INFO - Epoch(val) [400][165/500] eta: 0:00:13 time: 0.0404 data_time: 0.0024 memory: 1008 2022/11/02 16:27:54 - mmengine - INFO - Epoch(val) [400][170/500] eta: 0:00:15 time: 0.0470 data_time: 0.0028 memory: 1008 2022/11/02 16:27:54 - mmengine - INFO - Epoch(val) [400][175/500] eta: 0:00:15 time: 0.0447 data_time: 0.0030 memory: 1008 2022/11/02 16:27:54 - mmengine - INFO - Epoch(val) [400][180/500] eta: 0:00:12 time: 0.0390 data_time: 0.0029 memory: 1008 2022/11/02 16:27:55 - mmengine - INFO - Epoch(val) [400][185/500] eta: 0:00:12 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/02 16:27:55 - mmengine - INFO - Epoch(val) [400][190/500] eta: 0:00:13 time: 0.0424 data_time: 0.0025 memory: 1008 2022/11/02 16:27:55 - mmengine - INFO - Epoch(val) [400][195/500] eta: 0:00:13 time: 0.0421 data_time: 0.0025 memory: 1008 2022/11/02 16:27:55 - mmengine - INFO - Epoch(val) [400][200/500] eta: 0:00:14 time: 0.0468 data_time: 0.0025 memory: 1008 2022/11/02 16:27:55 - mmengine - INFO - Epoch(val) [400][205/500] eta: 0:00:14 time: 0.0447 data_time: 0.0028 memory: 1008 2022/11/02 16:27:56 - mmengine - INFO - Epoch(val) [400][210/500] eta: 0:00:10 time: 0.0354 data_time: 0.0027 memory: 1008 2022/11/02 16:27:56 - mmengine - INFO - Epoch(val) [400][215/500] eta: 0:00:10 time: 0.0375 data_time: 0.0027 memory: 1008 2022/11/02 16:27:56 - mmengine - INFO - Epoch(val) [400][220/500] eta: 0:00:11 time: 0.0406 data_time: 0.0028 memory: 1008 2022/11/02 16:27:56 - mmengine - INFO - Epoch(val) [400][225/500] eta: 0:00:11 time: 0.0427 data_time: 0.0028 memory: 1008 2022/11/02 16:27:56 - mmengine - INFO - Epoch(val) [400][230/500] eta: 0:00:10 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 16:27:57 - mmengine - INFO - Epoch(val) [400][235/500] eta: 0:00:10 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 16:27:57 - mmengine - INFO - Epoch(val) [400][240/500] eta: 0:00:11 time: 0.0432 data_time: 0.0024 memory: 1008 2022/11/02 16:27:57 - mmengine - INFO - Epoch(val) [400][245/500] eta: 0:00:11 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 16:27:57 - mmengine - INFO - Epoch(val) [400][250/500] eta: 0:00:09 time: 0.0368 data_time: 0.0024 memory: 1008 2022/11/02 16:27:57 - mmengine - INFO - Epoch(val) [400][255/500] eta: 0:00:09 time: 0.0391 data_time: 0.0025 memory: 1008 2022/11/02 16:27:58 - mmengine - INFO - Epoch(val) [400][260/500] eta: 0:00:09 time: 0.0380 data_time: 0.0028 memory: 1008 2022/11/02 16:27:58 - mmengine - INFO - Epoch(val) [400][265/500] eta: 0:00:09 time: 0.0374 data_time: 0.0029 memory: 1008 2022/11/02 16:27:59 - mmengine - INFO - Epoch(val) [400][270/500] eta: 0:00:29 time: 0.1261 data_time: 0.0907 memory: 1008 2022/11/02 16:27:59 - mmengine - INFO - Epoch(val) [400][275/500] eta: 0:00:29 time: 0.1259 data_time: 0.0902 memory: 1008 2022/11/02 16:27:59 - mmengine - INFO - Epoch(val) [400][280/500] eta: 0:00:08 time: 0.0403 data_time: 0.0023 memory: 1008 2022/11/02 16:27:59 - mmengine - INFO - Epoch(val) [400][285/500] eta: 0:00:08 time: 0.0446 data_time: 0.0031 memory: 1008 2022/11/02 16:28:00 - mmengine - INFO - Epoch(val) [400][290/500] eta: 0:00:09 time: 0.0470 data_time: 0.0034 memory: 1008 2022/11/02 16:28:00 - mmengine - INFO - Epoch(val) [400][295/500] eta: 0:00:09 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 16:28:00 - mmengine - INFO - Epoch(val) [400][300/500] eta: 0:00:07 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 16:28:00 - mmengine - INFO - Epoch(val) [400][305/500] eta: 0:00:07 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/02 16:28:00 - mmengine - INFO - Epoch(val) [400][310/500] eta: 0:00:07 time: 0.0414 data_time: 0.0034 memory: 1008 2022/11/02 16:28:01 - mmengine - INFO - Epoch(val) [400][315/500] eta: 0:00:07 time: 0.0422 data_time: 0.0031 memory: 1008 2022/11/02 16:28:01 - mmengine - INFO - Epoch(val) [400][320/500] eta: 0:00:07 time: 0.0436 data_time: 0.0032 memory: 1008 2022/11/02 16:28:01 - mmengine - INFO - Epoch(val) [400][325/500] eta: 0:00:07 time: 0.0571 data_time: 0.0032 memory: 1008 2022/11/02 16:28:02 - mmengine - INFO - Epoch(val) [400][330/500] eta: 0:00:09 time: 0.0583 data_time: 0.0028 memory: 1008 2022/11/02 16:28:02 - mmengine - INFO - Epoch(val) [400][335/500] eta: 0:00:09 time: 0.0411 data_time: 0.0027 memory: 1008 2022/11/02 16:28:02 - mmengine - INFO - Epoch(val) [400][340/500] eta: 0:00:08 time: 0.0536 data_time: 0.0029 memory: 1008 2022/11/02 16:28:02 - mmengine - INFO - Epoch(val) [400][345/500] eta: 0:00:08 time: 0.0537 data_time: 0.0027 memory: 1008 2022/11/02 16:28:02 - mmengine - INFO - Epoch(val) [400][350/500] eta: 0:00:06 time: 0.0418 data_time: 0.0024 memory: 1008 2022/11/02 16:28:03 - mmengine - INFO - Epoch(val) [400][355/500] eta: 0:00:06 time: 0.0433 data_time: 0.0037 memory: 1008 2022/11/02 16:28:03 - mmengine - INFO - Epoch(val) [400][360/500] eta: 0:00:05 time: 0.0384 data_time: 0.0036 memory: 1008 2022/11/02 16:28:03 - mmengine - INFO - Epoch(val) [400][365/500] eta: 0:00:05 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 16:28:03 - mmengine - INFO - Epoch(val) [400][370/500] eta: 0:00:04 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 16:28:03 - mmengine - INFO - Epoch(val) [400][375/500] eta: 0:00:04 time: 0.0365 data_time: 0.0028 memory: 1008 2022/11/02 16:28:04 - mmengine - INFO - Epoch(val) [400][380/500] eta: 0:00:05 time: 0.0443 data_time: 0.0028 memory: 1008 2022/11/02 16:28:04 - mmengine - INFO - Epoch(val) [400][385/500] eta: 0:00:05 time: 0.0435 data_time: 0.0027 memory: 1008 2022/11/02 16:28:04 - mmengine - INFO - Epoch(val) [400][390/500] eta: 0:00:04 time: 0.0381 data_time: 0.0026 memory: 1008 2022/11/02 16:28:04 - mmengine - INFO - Epoch(val) [400][395/500] eta: 0:00:04 time: 0.0392 data_time: 0.0028 memory: 1008 2022/11/02 16:28:04 - mmengine - INFO - Epoch(val) [400][400/500] eta: 0:00:03 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 16:28:05 - mmengine - INFO - Epoch(val) [400][405/500] eta: 0:00:03 time: 0.0416 data_time: 0.0029 memory: 1008 2022/11/02 16:28:05 - mmengine - INFO - Epoch(val) [400][410/500] eta: 0:00:04 time: 0.0445 data_time: 0.0031 memory: 1008 2022/11/02 16:28:05 - mmengine - INFO - Epoch(val) [400][415/500] eta: 0:00:04 time: 0.0445 data_time: 0.0040 memory: 1008 2022/11/02 16:28:05 - mmengine - INFO - Epoch(val) [400][420/500] eta: 0:00:03 time: 0.0382 data_time: 0.0039 memory: 1008 2022/11/02 16:28:05 - mmengine - INFO - Epoch(val) [400][425/500] eta: 0:00:03 time: 0.0355 data_time: 0.0024 memory: 1008 2022/11/02 16:28:06 - mmengine - INFO - Epoch(val) [400][430/500] eta: 0:00:02 time: 0.0393 data_time: 0.0029 memory: 1008 2022/11/02 16:28:06 - mmengine - INFO - Epoch(val) [400][435/500] eta: 0:00:02 time: 0.0416 data_time: 0.0035 memory: 1008 2022/11/02 16:28:06 - mmengine - INFO - Epoch(val) [400][440/500] eta: 0:00:02 time: 0.0405 data_time: 0.0031 memory: 1008 2022/11/02 16:28:06 - mmengine - INFO - Epoch(val) [400][445/500] eta: 0:00:02 time: 0.0410 data_time: 0.0029 memory: 1008 2022/11/02 16:28:07 - mmengine - INFO - Epoch(val) [400][450/500] eta: 0:00:02 time: 0.0467 data_time: 0.0040 memory: 1008 2022/11/02 16:28:07 - mmengine - INFO - Epoch(val) [400][455/500] eta: 0:00:02 time: 0.0482 data_time: 0.0042 memory: 1008 2022/11/02 16:28:07 - mmengine - INFO - Epoch(val) [400][460/500] eta: 0:00:01 time: 0.0407 data_time: 0.0030 memory: 1008 2022/11/02 16:28:07 - mmengine - INFO - Epoch(val) [400][465/500] eta: 0:00:01 time: 0.0345 data_time: 0.0025 memory: 1008 2022/11/02 16:28:07 - mmengine - INFO - Epoch(val) [400][470/500] eta: 0:00:01 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 16:28:08 - mmengine - INFO - Epoch(val) [400][475/500] eta: 0:00:01 time: 0.0390 data_time: 0.0029 memory: 1008 2022/11/02 16:28:08 - mmengine - INFO - Epoch(val) [400][480/500] eta: 0:00:00 time: 0.0391 data_time: 0.0029 memory: 1008 2022/11/02 16:28:08 - mmengine - INFO - Epoch(val) [400][485/500] eta: 0:00:00 time: 0.0426 data_time: 0.0031 memory: 1008 2022/11/02 16:28:08 - mmengine - INFO - Epoch(val) [400][490/500] eta: 0:00:00 time: 0.0425 data_time: 0.0032 memory: 1008 2022/11/02 16:28:08 - mmengine - INFO - Epoch(val) [400][495/500] eta: 0:00:00 time: 0.0439 data_time: 0.0032 memory: 1008 2022/11/02 16:28:09 - mmengine - INFO - Epoch(val) [400][500/500] eta: 0:00:00 time: 0.0411 data_time: 0.0031 memory: 1008 2022/11/02 16:28:09 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8305, precision: 0.7190, hmean: 0.7708 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8300, precision: 0.7794, hmean: 0.8039 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8286, precision: 0.8145, hmean: 0.8215 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8209, precision: 0.8500, hmean: 0.8352 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7862, precision: 0.8909, hmean: 0.8353 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5161, precision: 0.9428, hmean: 0.6671 2022/11/02 16:28:09 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0144, precision: 0.8824, hmean: 0.0284 2022/11/02 16:28:09 - mmengine - INFO - Epoch(val) [400][500/500] icdar/precision: 0.8909 icdar/recall: 0.7862 icdar/hmean: 0.8353 2022/11/02 16:28:15 - mmengine - INFO - Epoch(train) [401][5/63] lr: 1.5012e-03 eta: 0:00:00 time: 0.8408 data_time: 0.2528 memory: 14901 loss: 1.4769 loss_prob: 0.8078 loss_thr: 0.5341 loss_db: 0.1350 2022/11/02 16:28:18 - mmengine - INFO - Epoch(train) [401][10/63] lr: 1.5012e-03 eta: 8:12:31 time: 0.9791 data_time: 0.2503 memory: 14901 loss: 1.4829 loss_prob: 0.8122 loss_thr: 0.5351 loss_db: 0.1357 2022/11/02 16:28:21 - mmengine - INFO - Epoch(train) [401][15/63] lr: 1.5012e-03 eta: 8:12:31 time: 0.6384 data_time: 0.0148 memory: 14901 loss: 1.4745 loss_prob: 0.8016 loss_thr: 0.5391 loss_db: 0.1338 2022/11/02 16:28:24 - mmengine - INFO - Epoch(train) [401][20/63] lr: 1.5012e-03 eta: 8:12:25 time: 0.5564 data_time: 0.0150 memory: 14901 loss: 1.3696 loss_prob: 0.7289 loss_thr: 0.5183 loss_db: 0.1223 2022/11/02 16:28:27 - mmengine - INFO - Epoch(train) [401][25/63] lr: 1.5012e-03 eta: 8:12:25 time: 0.6251 data_time: 0.0392 memory: 14901 loss: 1.4234 loss_prob: 0.7852 loss_thr: 0.5061 loss_db: 0.1321 2022/11/02 16:28:30 - mmengine - INFO - Epoch(train) [401][30/63] lr: 1.5012e-03 eta: 8:12:19 time: 0.5931 data_time: 0.0465 memory: 14901 loss: 1.6474 loss_prob: 0.9444 loss_thr: 0.5493 loss_db: 0.1537 2022/11/02 16:28:33 - mmengine - INFO - Epoch(train) [401][35/63] lr: 1.5012e-03 eta: 8:12:19 time: 0.5448 data_time: 0.0169 memory: 14901 loss: 1.5873 loss_prob: 0.9057 loss_thr: 0.5343 loss_db: 0.1474 2022/11/02 16:28:36 - mmengine - INFO - Epoch(train) [401][40/63] lr: 1.5012e-03 eta: 8:12:13 time: 0.5588 data_time: 0.0117 memory: 14901 loss: 1.5253 loss_prob: 0.8630 loss_thr: 0.5198 loss_db: 0.1425 2022/11/02 16:28:38 - mmengine - INFO - Epoch(train) [401][45/63] lr: 1.5012e-03 eta: 8:12:13 time: 0.5621 data_time: 0.0120 memory: 14901 loss: 1.4520 loss_prob: 0.8058 loss_thr: 0.5122 loss_db: 0.1340 2022/11/02 16:28:41 - mmengine - INFO - Epoch(train) [401][50/63] lr: 1.5012e-03 eta: 8:12:06 time: 0.5708 data_time: 0.0276 memory: 14901 loss: 1.4173 loss_prob: 0.7684 loss_thr: 0.5171 loss_db: 0.1318 2022/11/02 16:28:44 - mmengine - INFO - Epoch(train) [401][55/63] lr: 1.5012e-03 eta: 8:12:06 time: 0.5609 data_time: 0.0265 memory: 14901 loss: 1.4988 loss_prob: 0.8189 loss_thr: 0.5396 loss_db: 0.1404 2022/11/02 16:28:47 - mmengine - INFO - Epoch(train) [401][60/63] lr: 1.5012e-03 eta: 8:12:01 time: 0.5945 data_time: 0.0149 memory: 14901 loss: 1.4704 loss_prob: 0.7943 loss_thr: 0.5405 loss_db: 0.1356 2022/11/02 16:28:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:28:54 - mmengine - INFO - Epoch(train) [402][5/63] lr: 1.4995e-03 eta: 8:12:01 time: 0.8091 data_time: 0.2878 memory: 14901 loss: 1.3877 loss_prob: 0.7579 loss_thr: 0.5035 loss_db: 0.1263 2022/11/02 16:28:57 - mmengine - INFO - Epoch(train) [402][10/63] lr: 1.4995e-03 eta: 8:11:54 time: 0.8104 data_time: 0.2833 memory: 14901 loss: 1.3631 loss_prob: 0.7390 loss_thr: 0.4971 loss_db: 0.1270 2022/11/02 16:29:00 - mmengine - INFO - Epoch(train) [402][15/63] lr: 1.4995e-03 eta: 8:11:54 time: 0.6322 data_time: 0.0070 memory: 14901 loss: 1.4695 loss_prob: 0.8161 loss_thr: 0.5159 loss_db: 0.1375 2022/11/02 16:29:03 - mmengine - INFO - Epoch(train) [402][20/63] lr: 1.4995e-03 eta: 8:11:50 time: 0.6700 data_time: 0.0248 memory: 14901 loss: 1.4603 loss_prob: 0.8050 loss_thr: 0.5190 loss_db: 0.1363 2022/11/02 16:29:06 - mmengine - INFO - Epoch(train) [402][25/63] lr: 1.4995e-03 eta: 8:11:50 time: 0.6046 data_time: 0.0697 memory: 14901 loss: 1.4330 loss_prob: 0.7796 loss_thr: 0.5202 loss_db: 0.1333 2022/11/02 16:29:09 - mmengine - INFO - Epoch(train) [402][30/63] lr: 1.4995e-03 eta: 8:11:44 time: 0.5899 data_time: 0.0524 memory: 14901 loss: 1.4296 loss_prob: 0.7801 loss_thr: 0.5179 loss_db: 0.1316 2022/11/02 16:29:12 - mmengine - INFO - Epoch(train) [402][35/63] lr: 1.4995e-03 eta: 8:11:44 time: 0.5261 data_time: 0.0075 memory: 14901 loss: 1.4563 loss_prob: 0.8060 loss_thr: 0.5168 loss_db: 0.1336 2022/11/02 16:29:14 - mmengine - INFO - Epoch(train) [402][40/63] lr: 1.4995e-03 eta: 8:11:37 time: 0.5234 data_time: 0.0099 memory: 14901 loss: 1.4560 loss_prob: 0.8116 loss_thr: 0.5083 loss_db: 0.1361 2022/11/02 16:29:17 - mmengine - INFO - Epoch(train) [402][45/63] lr: 1.4995e-03 eta: 8:11:37 time: 0.5496 data_time: 0.0220 memory: 14901 loss: 1.4214 loss_prob: 0.7849 loss_thr: 0.5020 loss_db: 0.1345 2022/11/02 16:29:20 - mmengine - INFO - Epoch(train) [402][50/63] lr: 1.4995e-03 eta: 8:11:30 time: 0.5517 data_time: 0.0266 memory: 14901 loss: 1.4159 loss_prob: 0.7676 loss_thr: 0.5192 loss_db: 0.1291 2022/11/02 16:29:23 - mmengine - INFO - Epoch(train) [402][55/63] lr: 1.4995e-03 eta: 8:11:30 time: 0.6026 data_time: 0.0136 memory: 14901 loss: 1.3914 loss_prob: 0.7445 loss_thr: 0.5200 loss_db: 0.1268 2022/11/02 16:29:26 - mmengine - INFO - Epoch(train) [402][60/63] lr: 1.4995e-03 eta: 8:11:24 time: 0.5804 data_time: 0.0060 memory: 14901 loss: 1.5242 loss_prob: 0.8325 loss_thr: 0.5515 loss_db: 0.1401 2022/11/02 16:29:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:29:32 - mmengine - INFO - Epoch(train) [403][5/63] lr: 1.4978e-03 eta: 8:11:24 time: 0.7986 data_time: 0.2427 memory: 14901 loss: 1.4653 loss_prob: 0.7956 loss_thr: 0.5359 loss_db: 0.1338 2022/11/02 16:29:35 - mmengine - INFO - Epoch(train) [403][10/63] lr: 1.4978e-03 eta: 8:11:18 time: 0.8340 data_time: 0.2426 memory: 14901 loss: 1.3816 loss_prob: 0.7450 loss_thr: 0.5116 loss_db: 0.1250 2022/11/02 16:29:38 - mmengine - INFO - Epoch(train) [403][15/63] lr: 1.4978e-03 eta: 8:11:18 time: 0.5366 data_time: 0.0086 memory: 14901 loss: 1.3802 loss_prob: 0.7505 loss_thr: 0.5036 loss_db: 0.1262 2022/11/02 16:29:41 - mmengine - INFO - Epoch(train) [403][20/63] lr: 1.4978e-03 eta: 8:11:11 time: 0.5275 data_time: 0.0145 memory: 14901 loss: 1.4187 loss_prob: 0.7765 loss_thr: 0.5092 loss_db: 0.1330 2022/11/02 16:29:45 - mmengine - INFO - Epoch(train) [403][25/63] lr: 1.4978e-03 eta: 8:11:11 time: 0.6816 data_time: 0.0223 memory: 14901 loss: 1.4378 loss_prob: 0.7955 loss_thr: 0.5094 loss_db: 0.1329 2022/11/02 16:29:48 - mmengine - INFO - Epoch(train) [403][30/63] lr: 1.4978e-03 eta: 8:11:07 time: 0.6890 data_time: 0.0474 memory: 14901 loss: 1.4909 loss_prob: 0.8246 loss_thr: 0.5306 loss_db: 0.1356 2022/11/02 16:29:50 - mmengine - INFO - Epoch(train) [403][35/63] lr: 1.4978e-03 eta: 8:11:07 time: 0.5202 data_time: 0.0363 memory: 14901 loss: 1.4045 loss_prob: 0.7544 loss_thr: 0.5229 loss_db: 0.1272 2022/11/02 16:29:53 - mmengine - INFO - Epoch(train) [403][40/63] lr: 1.4978e-03 eta: 8:11:01 time: 0.5399 data_time: 0.0055 memory: 14901 loss: 1.3487 loss_prob: 0.7310 loss_thr: 0.4963 loss_db: 0.1214 2022/11/02 16:29:55 - mmengine - INFO - Epoch(train) [403][45/63] lr: 1.4978e-03 eta: 8:11:01 time: 0.5579 data_time: 0.0105 memory: 14901 loss: 1.4546 loss_prob: 0.8046 loss_thr: 0.5180 loss_db: 0.1320 2022/11/02 16:29:58 - mmengine - INFO - Epoch(train) [403][50/63] lr: 1.4978e-03 eta: 8:10:53 time: 0.5281 data_time: 0.0257 memory: 14901 loss: 1.4494 loss_prob: 0.7837 loss_thr: 0.5355 loss_db: 0.1302 2022/11/02 16:30:01 - mmengine - INFO - Epoch(train) [403][55/63] lr: 1.4978e-03 eta: 8:10:53 time: 0.5121 data_time: 0.0244 memory: 14901 loss: 1.3743 loss_prob: 0.7411 loss_thr: 0.5065 loss_db: 0.1267 2022/11/02 16:30:03 - mmengine - INFO - Epoch(train) [403][60/63] lr: 1.4978e-03 eta: 8:10:46 time: 0.5167 data_time: 0.0135 memory: 14901 loss: 1.4189 loss_prob: 0.7907 loss_thr: 0.4928 loss_db: 0.1354 2022/11/02 16:30:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:30:10 - mmengine - INFO - Epoch(train) [404][5/63] lr: 1.4961e-03 eta: 8:10:46 time: 0.7988 data_time: 0.1966 memory: 14901 loss: 1.3686 loss_prob: 0.7391 loss_thr: 0.5026 loss_db: 0.1269 2022/11/02 16:30:13 - mmengine - INFO - Epoch(train) [404][10/63] lr: 1.4961e-03 eta: 8:10:40 time: 0.8525 data_time: 0.2031 memory: 14901 loss: 1.3997 loss_prob: 0.7477 loss_thr: 0.5247 loss_db: 0.1273 2022/11/02 16:30:16 - mmengine - INFO - Epoch(train) [404][15/63] lr: 1.4961e-03 eta: 8:10:40 time: 0.5495 data_time: 0.0278 memory: 14901 loss: 1.4721 loss_prob: 0.8030 loss_thr: 0.5303 loss_db: 0.1388 2022/11/02 16:30:18 - mmengine - INFO - Epoch(train) [404][20/63] lr: 1.4961e-03 eta: 8:10:33 time: 0.5314 data_time: 0.0207 memory: 14901 loss: 1.4326 loss_prob: 0.7863 loss_thr: 0.5138 loss_db: 0.1325 2022/11/02 16:30:22 - mmengine - INFO - Epoch(train) [404][25/63] lr: 1.4961e-03 eta: 8:10:33 time: 0.6241 data_time: 0.0106 memory: 14901 loss: 1.4915 loss_prob: 0.8385 loss_thr: 0.5144 loss_db: 0.1386 2022/11/02 16:30:26 - mmengine - INFO - Epoch(train) [404][30/63] lr: 1.4961e-03 eta: 8:10:30 time: 0.7204 data_time: 0.0379 memory: 14901 loss: 1.4712 loss_prob: 0.8235 loss_thr: 0.5091 loss_db: 0.1386 2022/11/02 16:30:29 - mmengine - INFO - Epoch(train) [404][35/63] lr: 1.4961e-03 eta: 8:10:30 time: 0.7436 data_time: 0.0382 memory: 14901 loss: 1.4533 loss_prob: 0.8072 loss_thr: 0.5101 loss_db: 0.1359 2022/11/02 16:30:32 - mmengine - INFO - Epoch(train) [404][40/63] lr: 1.4961e-03 eta: 8:10:25 time: 0.6410 data_time: 0.0152 memory: 14901 loss: 1.4975 loss_prob: 0.8246 loss_thr: 0.5338 loss_db: 0.1391 2022/11/02 16:30:35 - mmengine - INFO - Epoch(train) [404][45/63] lr: 1.4961e-03 eta: 8:10:25 time: 0.5253 data_time: 0.0149 memory: 14901 loss: 1.4013 loss_prob: 0.7579 loss_thr: 0.5142 loss_db: 0.1292 2022/11/02 16:30:37 - mmengine - INFO - Epoch(train) [404][50/63] lr: 1.4961e-03 eta: 8:10:18 time: 0.5238 data_time: 0.0145 memory: 14901 loss: 1.3600 loss_prob: 0.7314 loss_thr: 0.5048 loss_db: 0.1237 2022/11/02 16:30:41 - mmengine - INFO - Epoch(train) [404][55/63] lr: 1.4961e-03 eta: 8:10:18 time: 0.5824 data_time: 0.0284 memory: 14901 loss: 1.4063 loss_prob: 0.7537 loss_thr: 0.5256 loss_db: 0.1270 2022/11/02 16:30:43 - mmengine - INFO - Epoch(train) [404][60/63] lr: 1.4961e-03 eta: 8:10:12 time: 0.5761 data_time: 0.0266 memory: 14901 loss: 1.5144 loss_prob: 0.8382 loss_thr: 0.5349 loss_db: 0.1413 2022/11/02 16:30:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:30:50 - mmengine - INFO - Epoch(train) [405][5/63] lr: 1.4944e-03 eta: 8:10:12 time: 0.7744 data_time: 0.2704 memory: 14901 loss: 1.3929 loss_prob: 0.7513 loss_thr: 0.5166 loss_db: 0.1250 2022/11/02 16:30:53 - mmengine - INFO - Epoch(train) [405][10/63] lr: 1.4944e-03 eta: 8:10:06 time: 0.8224 data_time: 0.2647 memory: 14901 loss: 1.5745 loss_prob: 0.8731 loss_thr: 0.5546 loss_db: 0.1468 2022/11/02 16:30:55 - mmengine - INFO - Epoch(train) [405][15/63] lr: 1.4944e-03 eta: 8:10:06 time: 0.5405 data_time: 0.0116 memory: 14901 loss: 1.6498 loss_prob: 0.9316 loss_thr: 0.5640 loss_db: 0.1542 2022/11/02 16:30:58 - mmengine - INFO - Epoch(train) [405][20/63] lr: 1.4944e-03 eta: 8:09:59 time: 0.5344 data_time: 0.0168 memory: 14901 loss: 1.5364 loss_prob: 0.8583 loss_thr: 0.5358 loss_db: 0.1423 2022/11/02 16:31:01 - mmengine - INFO - Epoch(train) [405][25/63] lr: 1.4944e-03 eta: 8:09:59 time: 0.5397 data_time: 0.0382 memory: 14901 loss: 1.3913 loss_prob: 0.7574 loss_thr: 0.5080 loss_db: 0.1260 2022/11/02 16:31:03 - mmengine - INFO - Epoch(train) [405][30/63] lr: 1.4944e-03 eta: 8:09:52 time: 0.5474 data_time: 0.0359 memory: 14901 loss: 1.4012 loss_prob: 0.7644 loss_thr: 0.5085 loss_db: 0.1282 2022/11/02 16:31:07 - mmengine - INFO - Epoch(train) [405][35/63] lr: 1.4944e-03 eta: 8:09:52 time: 0.5917 data_time: 0.0100 memory: 14901 loss: 1.5089 loss_prob: 0.8495 loss_thr: 0.5171 loss_db: 0.1424 2022/11/02 16:31:09 - mmengine - INFO - Epoch(train) [405][40/63] lr: 1.4944e-03 eta: 8:09:46 time: 0.5881 data_time: 0.0118 memory: 14901 loss: 1.4895 loss_prob: 0.8345 loss_thr: 0.5141 loss_db: 0.1409 2022/11/02 16:31:12 - mmengine - INFO - Epoch(train) [405][45/63] lr: 1.4944e-03 eta: 8:09:46 time: 0.5334 data_time: 0.0116 memory: 14901 loss: 1.6354 loss_prob: 0.9637 loss_thr: 0.5233 loss_db: 0.1485 2022/11/02 16:31:15 - mmengine - INFO - Epoch(train) [405][50/63] lr: 1.4944e-03 eta: 8:09:41 time: 0.6040 data_time: 0.0283 memory: 14901 loss: 1.7605 loss_prob: 1.0555 loss_thr: 0.5428 loss_db: 0.1622 2022/11/02 16:31:18 - mmengine - INFO - Epoch(train) [405][55/63] lr: 1.4944e-03 eta: 8:09:41 time: 0.5888 data_time: 0.0275 memory: 14901 loss: 2.2212 loss_prob: 1.4010 loss_thr: 0.5982 loss_db: 0.2221 2022/11/02 16:31:20 - mmengine - INFO - Epoch(train) [405][60/63] lr: 1.4944e-03 eta: 8:09:33 time: 0.5009 data_time: 0.0127 memory: 14901 loss: 2.4576 loss_prob: 1.5897 loss_thr: 0.6131 loss_db: 0.2547 2022/11/02 16:31:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:31:27 - mmengine - INFO - Epoch(train) [406][5/63] lr: 1.4927e-03 eta: 8:09:33 time: 0.7988 data_time: 0.2803 memory: 14901 loss: 2.1357 loss_prob: 1.3138 loss_thr: 0.5976 loss_db: 0.2243 2022/11/02 16:31:31 - mmengine - INFO - Epoch(train) [406][10/63] lr: 1.4927e-03 eta: 8:09:28 time: 0.8569 data_time: 0.2841 memory: 14901 loss: 1.9283 loss_prob: 1.1502 loss_thr: 0.5867 loss_db: 0.1915 2022/11/02 16:31:33 - mmengine - INFO - Epoch(train) [406][15/63] lr: 1.4927e-03 eta: 8:09:28 time: 0.5937 data_time: 0.0142 memory: 14901 loss: 1.9318 loss_prob: 1.1342 loss_thr: 0.6113 loss_db: 0.1862 2022/11/02 16:31:36 - mmengine - INFO - Epoch(train) [406][20/63] lr: 1.4927e-03 eta: 8:09:21 time: 0.5275 data_time: 0.0089 memory: 14901 loss: 1.9947 loss_prob: 1.1754 loss_thr: 0.6246 loss_db: 0.1947 2022/11/02 16:31:39 - mmengine - INFO - Epoch(train) [406][25/63] lr: 1.4927e-03 eta: 8:09:21 time: 0.5424 data_time: 0.0424 memory: 14901 loss: 1.8319 loss_prob: 1.0681 loss_thr: 0.5890 loss_db: 0.1747 2022/11/02 16:31:41 - mmengine - INFO - Epoch(train) [406][30/63] lr: 1.4927e-03 eta: 8:09:14 time: 0.5254 data_time: 0.0409 memory: 14901 loss: 1.7174 loss_prob: 0.9913 loss_thr: 0.5609 loss_db: 0.1652 2022/11/02 16:31:44 - mmengine - INFO - Epoch(train) [406][35/63] lr: 1.4927e-03 eta: 8:09:14 time: 0.5284 data_time: 0.0101 memory: 14901 loss: 1.8064 loss_prob: 1.0647 loss_thr: 0.5676 loss_db: 0.1740 2022/11/02 16:31:47 - mmengine - INFO - Epoch(train) [406][40/63] lr: 1.4927e-03 eta: 8:09:07 time: 0.5366 data_time: 0.0126 memory: 14901 loss: 1.7179 loss_prob: 0.9896 loss_thr: 0.5675 loss_db: 0.1608 2022/11/02 16:31:49 - mmengine - INFO - Epoch(train) [406][45/63] lr: 1.4927e-03 eta: 8:09:07 time: 0.5235 data_time: 0.0075 memory: 14901 loss: 1.4735 loss_prob: 0.8058 loss_thr: 0.5332 loss_db: 0.1345 2022/11/02 16:31:52 - mmengine - INFO - Epoch(train) [406][50/63] lr: 1.4927e-03 eta: 8:09:01 time: 0.5714 data_time: 0.0263 memory: 14901 loss: 1.4757 loss_prob: 0.8175 loss_thr: 0.5225 loss_db: 0.1358 2022/11/02 16:31:56 - mmengine - INFO - Epoch(train) [406][55/63] lr: 1.4927e-03 eta: 8:09:01 time: 0.6967 data_time: 0.0291 memory: 14901 loss: 1.5768 loss_prob: 0.8789 loss_thr: 0.5489 loss_db: 0.1491 2022/11/02 16:31:59 - mmengine - INFO - Epoch(train) [406][60/63] lr: 1.4927e-03 eta: 8:08:56 time: 0.6570 data_time: 0.0105 memory: 14901 loss: 1.5340 loss_prob: 0.8466 loss_thr: 0.5468 loss_db: 0.1406 2022/11/02 16:32:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:32:07 - mmengine - INFO - Epoch(train) [407][5/63] lr: 1.4910e-03 eta: 8:08:56 time: 0.9470 data_time: 0.2701 memory: 14901 loss: 1.5358 loss_prob: 0.8490 loss_thr: 0.5440 loss_db: 0.1428 2022/11/02 16:32:10 - mmengine - INFO - Epoch(train) [407][10/63] lr: 1.4910e-03 eta: 8:08:51 time: 0.9172 data_time: 0.2693 memory: 14901 loss: 1.5406 loss_prob: 0.8552 loss_thr: 0.5415 loss_db: 0.1439 2022/11/02 16:32:12 - mmengine - INFO - Epoch(train) [407][15/63] lr: 1.4910e-03 eta: 8:08:51 time: 0.5307 data_time: 0.0114 memory: 14901 loss: 1.6040 loss_prob: 0.9000 loss_thr: 0.5537 loss_db: 0.1503 2022/11/02 16:32:16 - mmengine - INFO - Epoch(train) [407][20/63] lr: 1.4910e-03 eta: 8:08:46 time: 0.6075 data_time: 0.0105 memory: 14901 loss: 1.6047 loss_prob: 0.9021 loss_thr: 0.5530 loss_db: 0.1496 2022/11/02 16:32:19 - mmengine - INFO - Epoch(train) [407][25/63] lr: 1.4910e-03 eta: 8:08:46 time: 0.6398 data_time: 0.0294 memory: 14901 loss: 1.5061 loss_prob: 0.8287 loss_thr: 0.5371 loss_db: 0.1403 2022/11/02 16:32:22 - mmengine - INFO - Epoch(train) [407][30/63] lr: 1.4910e-03 eta: 8:08:40 time: 0.5928 data_time: 0.0604 memory: 14901 loss: 1.6004 loss_prob: 0.8992 loss_thr: 0.5502 loss_db: 0.1510 2022/11/02 16:32:25 - mmengine - INFO - Epoch(train) [407][35/63] lr: 1.4910e-03 eta: 8:08:40 time: 0.5982 data_time: 0.0394 memory: 14901 loss: 1.6354 loss_prob: 0.9348 loss_thr: 0.5485 loss_db: 0.1521 2022/11/02 16:32:27 - mmengine - INFO - Epoch(train) [407][40/63] lr: 1.4910e-03 eta: 8:08:34 time: 0.5728 data_time: 0.0090 memory: 14901 loss: 1.6313 loss_prob: 0.9396 loss_thr: 0.5401 loss_db: 0.1517 2022/11/02 16:32:30 - mmengine - INFO - Epoch(train) [407][45/63] lr: 1.4910e-03 eta: 8:08:34 time: 0.5242 data_time: 0.0061 memory: 14901 loss: 1.5183 loss_prob: 0.8535 loss_thr: 0.5236 loss_db: 0.1412 2022/11/02 16:32:33 - mmengine - INFO - Epoch(train) [407][50/63] lr: 1.4910e-03 eta: 8:08:27 time: 0.5239 data_time: 0.0263 memory: 14901 loss: 1.4955 loss_prob: 0.8172 loss_thr: 0.5421 loss_db: 0.1362 2022/11/02 16:32:35 - mmengine - INFO - Epoch(train) [407][55/63] lr: 1.4910e-03 eta: 8:08:27 time: 0.5102 data_time: 0.0272 memory: 14901 loss: 1.5913 loss_prob: 0.8897 loss_thr: 0.5582 loss_db: 0.1434 2022/11/02 16:32:38 - mmengine - INFO - Epoch(train) [407][60/63] lr: 1.4910e-03 eta: 8:08:19 time: 0.4990 data_time: 0.0083 memory: 14901 loss: 1.4263 loss_prob: 0.7844 loss_thr: 0.5118 loss_db: 0.1301 2022/11/02 16:32:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:32:46 - mmengine - INFO - Epoch(train) [408][5/63] lr: 1.4893e-03 eta: 8:08:19 time: 0.8813 data_time: 0.2726 memory: 14901 loss: 1.4619 loss_prob: 0.8068 loss_thr: 0.5181 loss_db: 0.1370 2022/11/02 16:32:49 - mmengine - INFO - Epoch(train) [408][10/63] lr: 1.4893e-03 eta: 8:08:17 time: 1.0408 data_time: 0.2713 memory: 14901 loss: 1.4400 loss_prob: 0.7993 loss_thr: 0.5093 loss_db: 0.1315 2022/11/02 16:32:53 - mmengine - INFO - Epoch(train) [408][15/63] lr: 1.4893e-03 eta: 8:08:17 time: 0.7110 data_time: 0.0109 memory: 14901 loss: 1.4238 loss_prob: 0.7886 loss_thr: 0.5031 loss_db: 0.1322 2022/11/02 16:32:55 - mmengine - INFO - Epoch(train) [408][20/63] lr: 1.4893e-03 eta: 8:08:11 time: 0.5637 data_time: 0.0106 memory: 14901 loss: 1.4661 loss_prob: 0.8079 loss_thr: 0.5190 loss_db: 0.1392 2022/11/02 16:32:58 - mmengine - INFO - Epoch(train) [408][25/63] lr: 1.4893e-03 eta: 8:08:11 time: 0.5145 data_time: 0.0104 memory: 14901 loss: 1.5028 loss_prob: 0.8297 loss_thr: 0.5316 loss_db: 0.1415 2022/11/02 16:33:01 - mmengine - INFO - Epoch(train) [408][30/63] lr: 1.4893e-03 eta: 8:08:05 time: 0.5732 data_time: 0.0392 memory: 14901 loss: 1.4565 loss_prob: 0.7934 loss_thr: 0.5322 loss_db: 0.1309 2022/11/02 16:33:03 - mmengine - INFO - Epoch(train) [408][35/63] lr: 1.4893e-03 eta: 8:08:05 time: 0.5582 data_time: 0.0391 memory: 14901 loss: 1.4279 loss_prob: 0.7764 loss_thr: 0.5231 loss_db: 0.1284 2022/11/02 16:33:06 - mmengine - INFO - Epoch(train) [408][40/63] lr: 1.4893e-03 eta: 8:07:58 time: 0.5129 data_time: 0.0124 memory: 14901 loss: 1.4303 loss_prob: 0.7915 loss_thr: 0.5064 loss_db: 0.1325 2022/11/02 16:33:09 - mmengine - INFO - Epoch(train) [408][45/63] lr: 1.4893e-03 eta: 8:07:58 time: 0.5508 data_time: 0.0097 memory: 14901 loss: 1.5222 loss_prob: 0.8578 loss_thr: 0.5198 loss_db: 0.1446 2022/11/02 16:33:12 - mmengine - INFO - Epoch(train) [408][50/63] lr: 1.4893e-03 eta: 8:07:51 time: 0.5586 data_time: 0.0211 memory: 14901 loss: 1.4936 loss_prob: 0.8412 loss_thr: 0.5096 loss_db: 0.1427 2022/11/02 16:33:15 - mmengine - INFO - Epoch(train) [408][55/63] lr: 1.4893e-03 eta: 8:07:51 time: 0.5659 data_time: 0.0220 memory: 14901 loss: 1.4681 loss_prob: 0.8200 loss_thr: 0.5089 loss_db: 0.1392 2022/11/02 16:33:17 - mmengine - INFO - Epoch(train) [408][60/63] lr: 1.4893e-03 eta: 8:07:45 time: 0.5794 data_time: 0.0146 memory: 14901 loss: 1.4939 loss_prob: 0.8271 loss_thr: 0.5273 loss_db: 0.1395 2022/11/02 16:33:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:33:24 - mmengine - INFO - Epoch(train) [409][5/63] lr: 1.4876e-03 eta: 8:07:45 time: 0.7447 data_time: 0.2435 memory: 14901 loss: 1.5537 loss_prob: 0.8616 loss_thr: 0.5461 loss_db: 0.1459 2022/11/02 16:33:26 - mmengine - INFO - Epoch(train) [409][10/63] lr: 1.4876e-03 eta: 8:07:38 time: 0.7761 data_time: 0.2411 memory: 14901 loss: 1.5195 loss_prob: 0.8357 loss_thr: 0.5423 loss_db: 0.1415 2022/11/02 16:33:29 - mmengine - INFO - Epoch(train) [409][15/63] lr: 1.4876e-03 eta: 8:07:38 time: 0.5590 data_time: 0.0111 memory: 14901 loss: 1.4148 loss_prob: 0.7752 loss_thr: 0.5071 loss_db: 0.1324 2022/11/02 16:33:32 - mmengine - INFO - Epoch(train) [409][20/63] lr: 1.4876e-03 eta: 8:07:32 time: 0.5661 data_time: 0.0114 memory: 14901 loss: 1.3741 loss_prob: 0.7532 loss_thr: 0.4941 loss_db: 0.1268 2022/11/02 16:33:36 - mmengine - INFO - Epoch(train) [409][25/63] lr: 1.4876e-03 eta: 8:07:32 time: 0.6302 data_time: 0.0101 memory: 14901 loss: 1.5086 loss_prob: 0.8184 loss_thr: 0.5525 loss_db: 0.1376 2022/11/02 16:33:39 - mmengine - INFO - Epoch(train) [409][30/63] lr: 1.4876e-03 eta: 8:07:27 time: 0.6680 data_time: 0.0420 memory: 14901 loss: 1.5201 loss_prob: 0.8185 loss_thr: 0.5630 loss_db: 0.1386 2022/11/02 16:33:42 - mmengine - INFO - Epoch(train) [409][35/63] lr: 1.4876e-03 eta: 8:07:27 time: 0.6325 data_time: 0.0412 memory: 14901 loss: 1.4822 loss_prob: 0.8087 loss_thr: 0.5378 loss_db: 0.1357 2022/11/02 16:33:45 - mmengine - INFO - Epoch(train) [409][40/63] lr: 1.4876e-03 eta: 8:07:22 time: 0.6062 data_time: 0.0157 memory: 14901 loss: 1.4617 loss_prob: 0.8002 loss_thr: 0.5265 loss_db: 0.1351 2022/11/02 16:33:47 - mmengine - INFO - Epoch(train) [409][45/63] lr: 1.4876e-03 eta: 8:07:22 time: 0.5456 data_time: 0.0129 memory: 14901 loss: 1.4135 loss_prob: 0.7777 loss_thr: 0.5040 loss_db: 0.1318 2022/11/02 16:33:50 - mmengine - INFO - Epoch(train) [409][50/63] lr: 1.4876e-03 eta: 8:07:15 time: 0.5463 data_time: 0.0157 memory: 14901 loss: 1.3804 loss_prob: 0.7590 loss_thr: 0.4920 loss_db: 0.1293 2022/11/02 16:33:53 - mmengine - INFO - Epoch(train) [409][55/63] lr: 1.4876e-03 eta: 8:07:15 time: 0.5306 data_time: 0.0266 memory: 14901 loss: 1.4011 loss_prob: 0.7681 loss_thr: 0.5024 loss_db: 0.1306 2022/11/02 16:33:55 - mmengine - INFO - Epoch(train) [409][60/63] lr: 1.4876e-03 eta: 8:07:08 time: 0.5058 data_time: 0.0205 memory: 14901 loss: 1.3827 loss_prob: 0.7472 loss_thr: 0.5098 loss_db: 0.1257 2022/11/02 16:33:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:34:02 - mmengine - INFO - Epoch(train) [410][5/63] lr: 1.4859e-03 eta: 8:07:08 time: 0.8246 data_time: 0.2437 memory: 14901 loss: 1.5141 loss_prob: 0.8293 loss_thr: 0.5444 loss_db: 0.1404 2022/11/02 16:34:05 - mmengine - INFO - Epoch(train) [410][10/63] lr: 1.4859e-03 eta: 8:07:02 time: 0.8499 data_time: 0.2752 memory: 14901 loss: 1.6399 loss_prob: 0.9356 loss_thr: 0.5489 loss_db: 0.1554 2022/11/02 16:34:08 - mmengine - INFO - Epoch(train) [410][15/63] lr: 1.4859e-03 eta: 8:07:02 time: 0.5840 data_time: 0.0460 memory: 14901 loss: 1.7261 loss_prob: 1.0166 loss_thr: 0.5447 loss_db: 0.1648 2022/11/02 16:34:11 - mmengine - INFO - Epoch(train) [410][20/63] lr: 1.4859e-03 eta: 8:06:56 time: 0.5692 data_time: 0.0076 memory: 14901 loss: 1.7865 loss_prob: 1.0611 loss_thr: 0.5542 loss_db: 0.1712 2022/11/02 16:34:14 - mmengine - INFO - Epoch(train) [410][25/63] lr: 1.4859e-03 eta: 8:06:56 time: 0.5336 data_time: 0.0146 memory: 14901 loss: 1.8290 loss_prob: 1.0667 loss_thr: 0.5870 loss_db: 0.1753 2022/11/02 16:34:16 - mmengine - INFO - Epoch(train) [410][30/63] lr: 1.4859e-03 eta: 8:06:49 time: 0.5651 data_time: 0.0164 memory: 14901 loss: 1.8089 loss_prob: 1.0441 loss_thr: 0.5934 loss_db: 0.1714 2022/11/02 16:34:19 - mmengine - INFO - Epoch(train) [410][35/63] lr: 1.4859e-03 eta: 8:06:49 time: 0.5639 data_time: 0.0199 memory: 14901 loss: 1.7566 loss_prob: 1.0155 loss_thr: 0.5728 loss_db: 0.1683 2022/11/02 16:34:22 - mmengine - INFO - Epoch(train) [410][40/63] lr: 1.4859e-03 eta: 8:06:42 time: 0.5340 data_time: 0.0205 memory: 14901 loss: 1.6544 loss_prob: 0.9419 loss_thr: 0.5515 loss_db: 0.1610 2022/11/02 16:34:26 - mmengine - INFO - Epoch(train) [410][45/63] lr: 1.4859e-03 eta: 8:06:42 time: 0.6319 data_time: 0.0099 memory: 14901 loss: 1.5946 loss_prob: 0.9071 loss_thr: 0.5373 loss_db: 0.1502 2022/11/02 16:34:29 - mmengine - INFO - Epoch(train) [410][50/63] lr: 1.4859e-03 eta: 8:06:38 time: 0.6832 data_time: 0.0189 memory: 14901 loss: 1.5934 loss_prob: 0.9005 loss_thr: 0.5457 loss_db: 0.1472 2022/11/02 16:34:31 - mmengine - INFO - Epoch(train) [410][55/63] lr: 1.4859e-03 eta: 8:06:38 time: 0.5912 data_time: 0.0199 memory: 14901 loss: 1.5704 loss_prob: 0.8683 loss_thr: 0.5521 loss_db: 0.1500 2022/11/02 16:34:34 - mmengine - INFO - Epoch(train) [410][60/63] lr: 1.4859e-03 eta: 8:06:32 time: 0.5538 data_time: 0.0109 memory: 14901 loss: 1.5596 loss_prob: 0.8575 loss_thr: 0.5572 loss_db: 0.1448 2022/11/02 16:34:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:34:42 - mmengine - INFO - Epoch(train) [411][5/63] lr: 1.4843e-03 eta: 8:06:32 time: 0.8422 data_time: 0.2476 memory: 14901 loss: 1.4645 loss_prob: 0.8137 loss_thr: 0.5178 loss_db: 0.1329 2022/11/02 16:34:44 - mmengine - INFO - Epoch(train) [411][10/63] lr: 1.4843e-03 eta: 8:06:26 time: 0.8688 data_time: 0.2457 memory: 14901 loss: 1.4605 loss_prob: 0.7879 loss_thr: 0.5385 loss_db: 0.1340 2022/11/02 16:34:47 - mmengine - INFO - Epoch(train) [411][15/63] lr: 1.4843e-03 eta: 8:06:26 time: 0.5464 data_time: 0.0093 memory: 14901 loss: 1.4718 loss_prob: 0.7909 loss_thr: 0.5476 loss_db: 0.1333 2022/11/02 16:34:50 - mmengine - INFO - Epoch(train) [411][20/63] lr: 1.4843e-03 eta: 8:06:20 time: 0.5500 data_time: 0.0108 memory: 14901 loss: 1.5863 loss_prob: 0.8876 loss_thr: 0.5517 loss_db: 0.1470 2022/11/02 16:34:53 - mmengine - INFO - Epoch(train) [411][25/63] lr: 1.4843e-03 eta: 8:06:20 time: 0.5547 data_time: 0.0212 memory: 14901 loss: 1.6466 loss_prob: 0.9326 loss_thr: 0.5586 loss_db: 0.1555 2022/11/02 16:34:56 - mmengine - INFO - Epoch(train) [411][30/63] lr: 1.4843e-03 eta: 8:06:14 time: 0.5959 data_time: 0.0438 memory: 14901 loss: 1.4494 loss_prob: 0.8014 loss_thr: 0.5148 loss_db: 0.1332 2022/11/02 16:34:59 - mmengine - INFO - Epoch(train) [411][35/63] lr: 1.4843e-03 eta: 8:06:14 time: 0.6447 data_time: 0.0298 memory: 14901 loss: 1.4878 loss_prob: 0.8329 loss_thr: 0.5158 loss_db: 0.1391 2022/11/02 16:35:02 - mmengine - INFO - Epoch(train) [411][40/63] lr: 1.4843e-03 eta: 8:06:09 time: 0.6053 data_time: 0.0058 memory: 14901 loss: 1.6168 loss_prob: 0.9218 loss_thr: 0.5401 loss_db: 0.1549 2022/11/02 16:35:04 - mmengine - INFO - Epoch(train) [411][45/63] lr: 1.4843e-03 eta: 8:06:09 time: 0.5253 data_time: 0.0058 memory: 14901 loss: 1.6373 loss_prob: 0.9334 loss_thr: 0.5503 loss_db: 0.1536 2022/11/02 16:35:07 - mmengine - INFO - Epoch(train) [411][50/63] lr: 1.4843e-03 eta: 8:06:02 time: 0.5466 data_time: 0.0136 memory: 14901 loss: 1.6100 loss_prob: 0.9089 loss_thr: 0.5526 loss_db: 0.1485 2022/11/02 16:35:11 - mmengine - INFO - Epoch(train) [411][55/63] lr: 1.4843e-03 eta: 8:06:02 time: 0.6024 data_time: 0.0260 memory: 14901 loss: 1.6156 loss_prob: 0.9087 loss_thr: 0.5551 loss_db: 0.1518 2022/11/02 16:35:13 - mmengine - INFO - Epoch(train) [411][60/63] lr: 1.4843e-03 eta: 8:05:56 time: 0.5831 data_time: 0.0217 memory: 14901 loss: 1.6805 loss_prob: 0.9686 loss_thr: 0.5539 loss_db: 0.1580 2022/11/02 16:35:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:35:20 - mmengine - INFO - Epoch(train) [412][5/63] lr: 1.4826e-03 eta: 8:05:56 time: 0.8213 data_time: 0.2372 memory: 14901 loss: 1.6791 loss_prob: 0.9660 loss_thr: 0.5619 loss_db: 0.1512 2022/11/02 16:35:23 - mmengine - INFO - Epoch(train) [412][10/63] lr: 1.4826e-03 eta: 8:05:51 time: 0.8763 data_time: 0.2347 memory: 14901 loss: 1.6097 loss_prob: 0.9138 loss_thr: 0.5453 loss_db: 0.1505 2022/11/02 16:35:26 - mmengine - INFO - Epoch(train) [412][15/63] lr: 1.4826e-03 eta: 8:05:51 time: 0.5545 data_time: 0.0080 memory: 14901 loss: 1.5325 loss_prob: 0.8551 loss_thr: 0.5324 loss_db: 0.1451 2022/11/02 16:35:28 - mmengine - INFO - Epoch(train) [412][20/63] lr: 1.4826e-03 eta: 8:05:43 time: 0.5158 data_time: 0.0135 memory: 14901 loss: 1.4286 loss_prob: 0.7899 loss_thr: 0.5088 loss_db: 0.1299 2022/11/02 16:35:31 - mmengine - INFO - Epoch(train) [412][25/63] lr: 1.4826e-03 eta: 8:05:43 time: 0.5416 data_time: 0.0236 memory: 14901 loss: 1.4685 loss_prob: 0.8112 loss_thr: 0.5233 loss_db: 0.1340 2022/11/02 16:35:34 - mmengine - INFO - Epoch(train) [412][30/63] lr: 1.4826e-03 eta: 8:05:37 time: 0.5472 data_time: 0.0531 memory: 14901 loss: 1.4922 loss_prob: 0.8251 loss_thr: 0.5281 loss_db: 0.1390 2022/11/02 16:35:36 - mmengine - INFO - Epoch(train) [412][35/63] lr: 1.4826e-03 eta: 8:05:37 time: 0.5100 data_time: 0.0441 memory: 14901 loss: 1.4803 loss_prob: 0.8233 loss_thr: 0.5186 loss_db: 0.1385 2022/11/02 16:35:39 - mmengine - INFO - Epoch(train) [412][40/63] lr: 1.4826e-03 eta: 8:05:29 time: 0.4939 data_time: 0.0084 memory: 14901 loss: 1.4693 loss_prob: 0.8074 loss_thr: 0.5277 loss_db: 0.1342 2022/11/02 16:35:42 - mmengine - INFO - Epoch(train) [412][45/63] lr: 1.4826e-03 eta: 8:05:29 time: 0.5532 data_time: 0.0064 memory: 14901 loss: 1.4507 loss_prob: 0.7887 loss_thr: 0.5297 loss_db: 0.1323 2022/11/02 16:35:45 - mmengine - INFO - Epoch(train) [412][50/63] lr: 1.4826e-03 eta: 8:05:23 time: 0.5983 data_time: 0.0183 memory: 14901 loss: 1.5611 loss_prob: 0.8695 loss_thr: 0.5469 loss_db: 0.1448 2022/11/02 16:35:48 - mmengine - INFO - Epoch(train) [412][55/63] lr: 1.4826e-03 eta: 8:05:23 time: 0.6234 data_time: 0.0297 memory: 14901 loss: 1.5443 loss_prob: 0.8554 loss_thr: 0.5460 loss_db: 0.1428 2022/11/02 16:35:51 - mmengine - INFO - Epoch(train) [412][60/63] lr: 1.4826e-03 eta: 8:05:18 time: 0.6175 data_time: 0.0177 memory: 14901 loss: 1.4917 loss_prob: 0.8277 loss_thr: 0.5250 loss_db: 0.1389 2022/11/02 16:35:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:35:58 - mmengine - INFO - Epoch(train) [413][5/63] lr: 1.4809e-03 eta: 8:05:18 time: 0.8706 data_time: 0.2254 memory: 14901 loss: 1.4951 loss_prob: 0.8347 loss_thr: 0.5201 loss_db: 0.1403 2022/11/02 16:36:01 - mmengine - INFO - Epoch(train) [413][10/63] lr: 1.4809e-03 eta: 8:05:13 time: 0.8765 data_time: 0.2271 memory: 14901 loss: 1.5474 loss_prob: 0.8731 loss_thr: 0.5330 loss_db: 0.1413 2022/11/02 16:36:04 - mmengine - INFO - Epoch(train) [413][15/63] lr: 1.4809e-03 eta: 8:05:13 time: 0.5732 data_time: 0.0165 memory: 14901 loss: 1.5031 loss_prob: 0.8289 loss_thr: 0.5349 loss_db: 0.1392 2022/11/02 16:36:07 - mmengine - INFO - Epoch(train) [413][20/63] lr: 1.4809e-03 eta: 8:05:06 time: 0.5209 data_time: 0.0090 memory: 14901 loss: 1.5366 loss_prob: 0.8557 loss_thr: 0.5352 loss_db: 0.1457 2022/11/02 16:36:10 - mmengine - INFO - Epoch(train) [413][25/63] lr: 1.4809e-03 eta: 8:05:06 time: 0.5477 data_time: 0.0129 memory: 14901 loss: 1.4451 loss_prob: 0.8000 loss_thr: 0.5129 loss_db: 0.1322 2022/11/02 16:36:13 - mmengine - INFO - Epoch(train) [413][30/63] lr: 1.4809e-03 eta: 8:05:00 time: 0.6245 data_time: 0.0462 memory: 14901 loss: 1.4445 loss_prob: 0.7831 loss_thr: 0.5310 loss_db: 0.1304 2022/11/02 16:36:15 - mmengine - INFO - Epoch(train) [413][35/63] lr: 1.4809e-03 eta: 8:05:00 time: 0.5627 data_time: 0.0387 memory: 14901 loss: 1.5714 loss_prob: 0.8643 loss_thr: 0.5615 loss_db: 0.1457 2022/11/02 16:36:18 - mmengine - INFO - Epoch(train) [413][40/63] lr: 1.4809e-03 eta: 8:04:54 time: 0.5383 data_time: 0.0067 memory: 14901 loss: 1.5719 loss_prob: 0.8692 loss_thr: 0.5570 loss_db: 0.1456 2022/11/02 16:36:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:36:21 - mmengine - INFO - Epoch(train) [413][45/63] lr: 1.4809e-03 eta: 8:04:54 time: 0.5678 data_time: 0.0078 memory: 14901 loss: 1.4732 loss_prob: 0.8041 loss_thr: 0.5363 loss_db: 0.1328 2022/11/02 16:36:24 - mmengine - INFO - Epoch(train) [413][50/63] lr: 1.4809e-03 eta: 8:04:47 time: 0.5522 data_time: 0.0184 memory: 14901 loss: 1.4197 loss_prob: 0.7670 loss_thr: 0.5207 loss_db: 0.1320 2022/11/02 16:36:26 - mmengine - INFO - Epoch(train) [413][55/63] lr: 1.4809e-03 eta: 8:04:47 time: 0.5424 data_time: 0.0275 memory: 14901 loss: 1.4269 loss_prob: 0.7737 loss_thr: 0.5200 loss_db: 0.1332 2022/11/02 16:36:29 - mmengine - INFO - Epoch(train) [413][60/63] lr: 1.4809e-03 eta: 8:04:40 time: 0.5320 data_time: 0.0206 memory: 14901 loss: 1.3117 loss_prob: 0.7092 loss_thr: 0.4849 loss_db: 0.1175 2022/11/02 16:36:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:36:36 - mmengine - INFO - Epoch(train) [414][5/63] lr: 1.4792e-03 eta: 8:04:40 time: 0.8274 data_time: 0.2895 memory: 14901 loss: 1.4507 loss_prob: 0.8143 loss_thr: 0.5040 loss_db: 0.1325 2022/11/02 16:36:39 - mmengine - INFO - Epoch(train) [414][10/63] lr: 1.4792e-03 eta: 8:04:36 time: 0.9149 data_time: 0.2896 memory: 14901 loss: 1.5332 loss_prob: 0.8582 loss_thr: 0.5315 loss_db: 0.1434 2022/11/02 16:36:43 - mmengine - INFO - Epoch(train) [414][15/63] lr: 1.4792e-03 eta: 8:04:36 time: 0.6255 data_time: 0.0118 memory: 14901 loss: 1.5567 loss_prob: 0.8811 loss_thr: 0.5295 loss_db: 0.1461 2022/11/02 16:36:46 - mmengine - INFO - Epoch(train) [414][20/63] lr: 1.4792e-03 eta: 8:04:30 time: 0.6072 data_time: 0.0091 memory: 14901 loss: 1.5450 loss_prob: 0.8674 loss_thr: 0.5352 loss_db: 0.1423 2022/11/02 16:36:49 - mmengine - INFO - Epoch(train) [414][25/63] lr: 1.4792e-03 eta: 8:04:30 time: 0.5935 data_time: 0.0293 memory: 14901 loss: 1.4443 loss_prob: 0.8011 loss_thr: 0.5092 loss_db: 0.1340 2022/11/02 16:36:51 - mmengine - INFO - Epoch(train) [414][30/63] lr: 1.4792e-03 eta: 8:04:24 time: 0.5742 data_time: 0.0414 memory: 14901 loss: 1.4466 loss_prob: 0.8020 loss_thr: 0.5110 loss_db: 0.1335 2022/11/02 16:36:54 - mmengine - INFO - Epoch(train) [414][35/63] lr: 1.4792e-03 eta: 8:04:24 time: 0.5480 data_time: 0.0224 memory: 14901 loss: 1.5528 loss_prob: 0.8717 loss_thr: 0.5353 loss_db: 0.1459 2022/11/02 16:36:57 - mmengine - INFO - Epoch(train) [414][40/63] lr: 1.4792e-03 eta: 8:04:18 time: 0.5616 data_time: 0.0099 memory: 14901 loss: 1.6149 loss_prob: 0.9232 loss_thr: 0.5401 loss_db: 0.1516 2022/11/02 16:37:00 - mmengine - INFO - Epoch(train) [414][45/63] lr: 1.4792e-03 eta: 8:04:18 time: 0.5819 data_time: 0.0061 memory: 14901 loss: 1.5195 loss_prob: 0.8582 loss_thr: 0.5232 loss_db: 0.1381 2022/11/02 16:37:02 - mmengine - INFO - Epoch(train) [414][50/63] lr: 1.4792e-03 eta: 8:04:11 time: 0.5585 data_time: 0.0213 memory: 14901 loss: 1.4320 loss_prob: 0.7909 loss_thr: 0.5082 loss_db: 0.1329 2022/11/02 16:37:05 - mmengine - INFO - Epoch(train) [414][55/63] lr: 1.4792e-03 eta: 8:04:11 time: 0.5492 data_time: 0.0316 memory: 14901 loss: 1.5105 loss_prob: 0.8454 loss_thr: 0.5212 loss_db: 0.1439 2022/11/02 16:37:08 - mmengine - INFO - Epoch(train) [414][60/63] lr: 1.4792e-03 eta: 8:04:05 time: 0.5667 data_time: 0.0183 memory: 14901 loss: 1.4561 loss_prob: 0.8184 loss_thr: 0.5022 loss_db: 0.1355 2022/11/02 16:37:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:37:17 - mmengine - INFO - Epoch(train) [415][5/63] lr: 1.4775e-03 eta: 8:04:05 time: 1.0251 data_time: 0.2946 memory: 14901 loss: 1.3553 loss_prob: 0.7336 loss_thr: 0.4983 loss_db: 0.1235 2022/11/02 16:37:21 - mmengine - INFO - Epoch(train) [415][10/63] lr: 1.4775e-03 eta: 8:04:03 time: 1.0863 data_time: 0.2930 memory: 14901 loss: 1.4576 loss_prob: 0.8069 loss_thr: 0.5140 loss_db: 0.1367 2022/11/02 16:37:25 - mmengine - INFO - Epoch(train) [415][15/63] lr: 1.4775e-03 eta: 8:04:03 time: 0.7308 data_time: 0.0071 memory: 14901 loss: 1.4205 loss_prob: 0.7803 loss_thr: 0.5116 loss_db: 0.1286 2022/11/02 16:37:27 - mmengine - INFO - Epoch(train) [415][20/63] lr: 1.4775e-03 eta: 8:03:59 time: 0.6684 data_time: 0.0079 memory: 14901 loss: 1.3933 loss_prob: 0.7580 loss_thr: 0.5081 loss_db: 0.1271 2022/11/02 16:37:31 - mmengine - INFO - Epoch(train) [415][25/63] lr: 1.4775e-03 eta: 8:03:59 time: 0.6145 data_time: 0.0466 memory: 14901 loss: 1.3517 loss_prob: 0.7285 loss_thr: 0.4958 loss_db: 0.1273 2022/11/02 16:37:33 - mmengine - INFO - Epoch(train) [415][30/63] lr: 1.4775e-03 eta: 8:03:53 time: 0.5908 data_time: 0.0440 memory: 14901 loss: 1.4345 loss_prob: 0.7823 loss_thr: 0.5202 loss_db: 0.1320 2022/11/02 16:37:36 - mmengine - INFO - Epoch(train) [415][35/63] lr: 1.4775e-03 eta: 8:03:53 time: 0.5048 data_time: 0.0051 memory: 14901 loss: 1.6831 loss_prob: 0.9720 loss_thr: 0.5569 loss_db: 0.1541 2022/11/02 16:37:38 - mmengine - INFO - Epoch(train) [415][40/63] lr: 1.4775e-03 eta: 8:03:46 time: 0.5170 data_time: 0.0123 memory: 14901 loss: 1.7360 loss_prob: 1.0075 loss_thr: 0.5721 loss_db: 0.1564 2022/11/02 16:37:42 - mmengine - INFO - Epoch(train) [415][45/63] lr: 1.4775e-03 eta: 8:03:46 time: 0.5585 data_time: 0.0132 memory: 14901 loss: 1.6473 loss_prob: 0.9338 loss_thr: 0.5638 loss_db: 0.1498 2022/11/02 16:37:44 - mmengine - INFO - Epoch(train) [415][50/63] lr: 1.4775e-03 eta: 8:03:41 time: 0.5987 data_time: 0.0246 memory: 14901 loss: 1.5371 loss_prob: 0.8580 loss_thr: 0.5352 loss_db: 0.1439 2022/11/02 16:37:47 - mmengine - INFO - Epoch(train) [415][55/63] lr: 1.4775e-03 eta: 8:03:41 time: 0.5450 data_time: 0.0246 memory: 14901 loss: 1.4879 loss_prob: 0.8096 loss_thr: 0.5415 loss_db: 0.1368 2022/11/02 16:37:49 - mmengine - INFO - Epoch(train) [415][60/63] lr: 1.4775e-03 eta: 8:03:33 time: 0.5028 data_time: 0.0057 memory: 14901 loss: 1.4868 loss_prob: 0.8108 loss_thr: 0.5406 loss_db: 0.1353 2022/11/02 16:37:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:37:56 - mmengine - INFO - Epoch(train) [416][5/63] lr: 1.4758e-03 eta: 8:03:33 time: 0.7572 data_time: 0.2585 memory: 14901 loss: 1.4861 loss_prob: 0.8285 loss_thr: 0.5178 loss_db: 0.1398 2022/11/02 16:37:59 - mmengine - INFO - Epoch(train) [416][10/63] lr: 1.4758e-03 eta: 8:03:26 time: 0.7888 data_time: 0.2607 memory: 14901 loss: 1.3946 loss_prob: 0.7663 loss_thr: 0.4993 loss_db: 0.1291 2022/11/02 16:38:02 - mmengine - INFO - Epoch(train) [416][15/63] lr: 1.4758e-03 eta: 8:03:26 time: 0.6035 data_time: 0.0099 memory: 14901 loss: 1.3803 loss_prob: 0.7618 loss_thr: 0.4898 loss_db: 0.1287 2022/11/02 16:38:05 - mmengine - INFO - Epoch(train) [416][20/63] lr: 1.4758e-03 eta: 8:03:22 time: 0.6668 data_time: 0.0085 memory: 14901 loss: 1.4042 loss_prob: 0.7695 loss_thr: 0.5046 loss_db: 0.1300 2022/11/02 16:38:09 - mmengine - INFO - Epoch(train) [416][25/63] lr: 1.4758e-03 eta: 8:03:22 time: 0.6726 data_time: 0.0398 memory: 14901 loss: 1.3660 loss_prob: 0.7426 loss_thr: 0.4975 loss_db: 0.1259 2022/11/02 16:38:12 - mmengine - INFO - Epoch(train) [416][30/63] lr: 1.4758e-03 eta: 8:03:17 time: 0.6633 data_time: 0.0440 memory: 14901 loss: 1.4407 loss_prob: 0.7890 loss_thr: 0.5192 loss_db: 0.1325 2022/11/02 16:38:15 - mmengine - INFO - Epoch(train) [416][35/63] lr: 1.4758e-03 eta: 8:03:17 time: 0.5949 data_time: 0.0123 memory: 14901 loss: 1.4414 loss_prob: 0.7874 loss_thr: 0.5220 loss_db: 0.1320 2022/11/02 16:38:17 - mmengine - INFO - Epoch(train) [416][40/63] lr: 1.4758e-03 eta: 8:03:10 time: 0.5407 data_time: 0.0073 memory: 14901 loss: 1.4241 loss_prob: 0.7824 loss_thr: 0.5123 loss_db: 0.1295 2022/11/02 16:38:21 - mmengine - INFO - Epoch(train) [416][45/63] lr: 1.4758e-03 eta: 8:03:10 time: 0.5781 data_time: 0.0081 memory: 14901 loss: 1.6077 loss_prob: 0.9250 loss_thr: 0.5370 loss_db: 0.1457 2022/11/02 16:38:23 - mmengine - INFO - Epoch(train) [416][50/63] lr: 1.4758e-03 eta: 8:03:05 time: 0.5882 data_time: 0.0296 memory: 14901 loss: 1.6044 loss_prob: 0.9206 loss_thr: 0.5359 loss_db: 0.1479 2022/11/02 16:38:26 - mmengine - INFO - Epoch(train) [416][55/63] lr: 1.4758e-03 eta: 8:03:05 time: 0.5582 data_time: 0.0304 memory: 14901 loss: 1.4887 loss_prob: 0.8207 loss_thr: 0.5300 loss_db: 0.1380 2022/11/02 16:38:29 - mmengine - INFO - Epoch(train) [416][60/63] lr: 1.4758e-03 eta: 8:02:58 time: 0.5436 data_time: 0.0170 memory: 14901 loss: 1.4230 loss_prob: 0.7784 loss_thr: 0.5146 loss_db: 0.1300 2022/11/02 16:38:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:38:35 - mmengine - INFO - Epoch(train) [417][5/63] lr: 1.4741e-03 eta: 8:02:58 time: 0.7645 data_time: 0.2463 memory: 14901 loss: 1.4109 loss_prob: 0.7731 loss_thr: 0.5090 loss_db: 0.1288 2022/11/02 16:38:38 - mmengine - INFO - Epoch(train) [417][10/63] lr: 1.4741e-03 eta: 8:02:51 time: 0.8150 data_time: 0.2496 memory: 14901 loss: 1.3810 loss_prob: 0.7525 loss_thr: 0.5019 loss_db: 0.1266 2022/11/02 16:38:41 - mmengine - INFO - Epoch(train) [417][15/63] lr: 1.4741e-03 eta: 8:02:51 time: 0.5738 data_time: 0.0110 memory: 14901 loss: 1.2769 loss_prob: 0.6819 loss_thr: 0.4798 loss_db: 0.1152 2022/11/02 16:38:44 - mmengine - INFO - Epoch(train) [417][20/63] lr: 1.4741e-03 eta: 8:02:45 time: 0.5716 data_time: 0.0113 memory: 14901 loss: 1.2540 loss_prob: 0.6712 loss_thr: 0.4701 loss_db: 0.1126 2022/11/02 16:38:48 - mmengine - INFO - Epoch(train) [417][25/63] lr: 1.4741e-03 eta: 8:02:45 time: 0.7176 data_time: 0.0150 memory: 14901 loss: 1.2629 loss_prob: 0.6922 loss_thr: 0.4540 loss_db: 0.1167 2022/11/02 16:38:51 - mmengine - INFO - Epoch(train) [417][30/63] lr: 1.4741e-03 eta: 8:02:42 time: 0.7158 data_time: 0.0459 memory: 14901 loss: 1.3692 loss_prob: 0.7606 loss_thr: 0.4799 loss_db: 0.1287 2022/11/02 16:38:54 - mmengine - INFO - Epoch(train) [417][35/63] lr: 1.4741e-03 eta: 8:02:42 time: 0.5933 data_time: 0.0411 memory: 14901 loss: 1.4579 loss_prob: 0.8071 loss_thr: 0.5138 loss_db: 0.1369 2022/11/02 16:38:57 - mmengine - INFO - Epoch(train) [417][40/63] lr: 1.4741e-03 eta: 8:02:36 time: 0.6058 data_time: 0.0072 memory: 14901 loss: 1.5052 loss_prob: 0.8524 loss_thr: 0.5137 loss_db: 0.1391 2022/11/02 16:39:00 - mmengine - INFO - Epoch(train) [417][45/63] lr: 1.4741e-03 eta: 8:02:36 time: 0.6045 data_time: 0.0107 memory: 14901 loss: 1.5474 loss_prob: 0.8797 loss_thr: 0.5265 loss_db: 0.1411 2022/11/02 16:39:04 - mmengine - INFO - Epoch(train) [417][50/63] lr: 1.4741e-03 eta: 8:02:31 time: 0.6358 data_time: 0.0303 memory: 14901 loss: 1.4872 loss_prob: 0.8219 loss_thr: 0.5282 loss_db: 0.1371 2022/11/02 16:39:07 - mmengine - INFO - Epoch(train) [417][55/63] lr: 1.4741e-03 eta: 8:02:31 time: 0.6307 data_time: 0.0269 memory: 14901 loss: 1.5076 loss_prob: 0.8270 loss_thr: 0.5420 loss_db: 0.1385 2022/11/02 16:39:09 - mmengine - INFO - Epoch(train) [417][60/63] lr: 1.4741e-03 eta: 8:02:25 time: 0.5725 data_time: 0.0107 memory: 14901 loss: 1.5242 loss_prob: 0.8387 loss_thr: 0.5448 loss_db: 0.1408 2022/11/02 16:39:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:39:17 - mmengine - INFO - Epoch(train) [418][5/63] lr: 1.4724e-03 eta: 8:02:25 time: 0.8283 data_time: 0.2483 memory: 14901 loss: 1.3576 loss_prob: 0.7282 loss_thr: 0.5031 loss_db: 0.1264 2022/11/02 16:39:19 - mmengine - INFO - Epoch(train) [418][10/63] lr: 1.4724e-03 eta: 8:02:19 time: 0.8550 data_time: 0.2539 memory: 14901 loss: 1.4063 loss_prob: 0.7611 loss_thr: 0.5176 loss_db: 0.1276 2022/11/02 16:39:22 - mmengine - INFO - Epoch(train) [418][15/63] lr: 1.4724e-03 eta: 8:02:19 time: 0.5446 data_time: 0.0202 memory: 14901 loss: 1.4364 loss_prob: 0.7789 loss_thr: 0.5280 loss_db: 0.1295 2022/11/02 16:39:24 - mmengine - INFO - Epoch(train) [418][20/63] lr: 1.4724e-03 eta: 8:02:12 time: 0.5086 data_time: 0.0107 memory: 14901 loss: 1.4287 loss_prob: 0.7665 loss_thr: 0.5326 loss_db: 0.1296 2022/11/02 16:39:27 - mmengine - INFO - Epoch(train) [418][25/63] lr: 1.4724e-03 eta: 8:02:12 time: 0.5345 data_time: 0.0471 memory: 14901 loss: 1.4950 loss_prob: 0.8262 loss_thr: 0.5321 loss_db: 0.1368 2022/11/02 16:39:30 - mmengine - INFO - Epoch(train) [418][30/63] lr: 1.4724e-03 eta: 8:02:05 time: 0.5486 data_time: 0.0480 memory: 14901 loss: 1.4196 loss_prob: 0.7882 loss_thr: 0.5002 loss_db: 0.1311 2022/11/02 16:39:32 - mmengine - INFO - Epoch(train) [418][35/63] lr: 1.4724e-03 eta: 8:02:05 time: 0.4988 data_time: 0.0074 memory: 14901 loss: 1.3568 loss_prob: 0.7323 loss_thr: 0.4993 loss_db: 0.1252 2022/11/02 16:39:35 - mmengine - INFO - Epoch(train) [418][40/63] lr: 1.4724e-03 eta: 8:01:58 time: 0.4934 data_time: 0.0076 memory: 14901 loss: 1.4178 loss_prob: 0.7676 loss_thr: 0.5206 loss_db: 0.1296 2022/11/02 16:39:37 - mmengine - INFO - Epoch(train) [418][45/63] lr: 1.4724e-03 eta: 8:01:58 time: 0.4865 data_time: 0.0063 memory: 14901 loss: 1.3533 loss_prob: 0.7361 loss_thr: 0.4935 loss_db: 0.1238 2022/11/02 16:39:40 - mmengine - INFO - Epoch(train) [418][50/63] lr: 1.4724e-03 eta: 8:01:50 time: 0.5102 data_time: 0.0190 memory: 14901 loss: 1.2994 loss_prob: 0.7030 loss_thr: 0.4785 loss_db: 0.1179 2022/11/02 16:39:42 - mmengine - INFO - Epoch(train) [418][55/63] lr: 1.4724e-03 eta: 8:01:50 time: 0.5120 data_time: 0.0190 memory: 14901 loss: 1.4003 loss_prob: 0.7724 loss_thr: 0.4989 loss_db: 0.1290 2022/11/02 16:39:45 - mmengine - INFO - Epoch(train) [418][60/63] lr: 1.4724e-03 eta: 8:01:42 time: 0.4693 data_time: 0.0055 memory: 14901 loss: 1.4570 loss_prob: 0.7980 loss_thr: 0.5263 loss_db: 0.1328 2022/11/02 16:39:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:39:51 - mmengine - INFO - Epoch(train) [419][5/63] lr: 1.4707e-03 eta: 8:01:42 time: 0.7137 data_time: 0.2456 memory: 14901 loss: 1.6437 loss_prob: 0.9524 loss_thr: 0.5321 loss_db: 0.1592 2022/11/02 16:39:53 - mmengine - INFO - Epoch(train) [419][10/63] lr: 1.4707e-03 eta: 8:01:34 time: 0.7478 data_time: 0.2486 memory: 14901 loss: 1.5432 loss_prob: 0.8744 loss_thr: 0.5200 loss_db: 0.1488 2022/11/02 16:39:56 - mmengine - INFO - Epoch(train) [419][15/63] lr: 1.4707e-03 eta: 8:01:34 time: 0.5018 data_time: 0.0198 memory: 14901 loss: 1.4594 loss_prob: 0.8078 loss_thr: 0.5228 loss_db: 0.1288 2022/11/02 16:39:58 - mmengine - INFO - Epoch(train) [419][20/63] lr: 1.4707e-03 eta: 8:01:27 time: 0.5109 data_time: 0.0170 memory: 14901 loss: 1.4986 loss_prob: 0.8216 loss_thr: 0.5428 loss_db: 0.1342 2022/11/02 16:40:01 - mmengine - INFO - Epoch(train) [419][25/63] lr: 1.4707e-03 eta: 8:01:27 time: 0.5472 data_time: 0.0262 memory: 14901 loss: 1.4397 loss_prob: 0.7799 loss_thr: 0.5265 loss_db: 0.1333 2022/11/02 16:40:04 - mmengine - INFO - Epoch(train) [419][30/63] lr: 1.4707e-03 eta: 8:01:21 time: 0.5656 data_time: 0.0336 memory: 14901 loss: 1.4555 loss_prob: 0.8022 loss_thr: 0.5204 loss_db: 0.1329 2022/11/02 16:40:07 - mmengine - INFO - Epoch(train) [419][35/63] lr: 1.4707e-03 eta: 8:01:21 time: 0.5429 data_time: 0.0208 memory: 14901 loss: 1.5015 loss_prob: 0.8386 loss_thr: 0.5248 loss_db: 0.1381 2022/11/02 16:40:10 - mmengine - INFO - Epoch(train) [419][40/63] lr: 1.4707e-03 eta: 8:01:14 time: 0.5454 data_time: 0.0143 memory: 14901 loss: 1.4446 loss_prob: 0.8011 loss_thr: 0.5085 loss_db: 0.1351 2022/11/02 16:40:12 - mmengine - INFO - Epoch(train) [419][45/63] lr: 1.4707e-03 eta: 8:01:14 time: 0.5613 data_time: 0.0102 memory: 14901 loss: 1.4200 loss_prob: 0.7670 loss_thr: 0.5210 loss_db: 0.1321 2022/11/02 16:40:15 - mmengine - INFO - Epoch(train) [419][50/63] lr: 1.4707e-03 eta: 8:01:08 time: 0.5456 data_time: 0.0296 memory: 14901 loss: 1.4523 loss_prob: 0.7926 loss_thr: 0.5262 loss_db: 0.1334 2022/11/02 16:40:18 - mmengine - INFO - Epoch(train) [419][55/63] lr: 1.4707e-03 eta: 8:01:08 time: 0.5300 data_time: 0.0289 memory: 14901 loss: 1.4610 loss_prob: 0.8172 loss_thr: 0.5112 loss_db: 0.1327 2022/11/02 16:40:20 - mmengine - INFO - Epoch(train) [419][60/63] lr: 1.4707e-03 eta: 8:01:00 time: 0.5109 data_time: 0.0125 memory: 14901 loss: 1.4895 loss_prob: 0.8357 loss_thr: 0.5145 loss_db: 0.1393 2022/11/02 16:40:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:40:27 - mmengine - INFO - Epoch(train) [420][5/63] lr: 1.4690e-03 eta: 8:01:00 time: 0.7869 data_time: 0.2196 memory: 14901 loss: 1.4986 loss_prob: 0.8309 loss_thr: 0.5273 loss_db: 0.1404 2022/11/02 16:40:30 - mmengine - INFO - Epoch(train) [420][10/63] lr: 1.4690e-03 eta: 8:00:54 time: 0.8257 data_time: 0.2258 memory: 14901 loss: 1.4289 loss_prob: 0.7895 loss_thr: 0.5039 loss_db: 0.1355 2022/11/02 16:40:33 - mmengine - INFO - Epoch(train) [420][15/63] lr: 1.4690e-03 eta: 8:00:54 time: 0.5552 data_time: 0.0174 memory: 14901 loss: 1.4157 loss_prob: 0.7733 loss_thr: 0.5106 loss_db: 0.1318 2022/11/02 16:40:35 - mmengine - INFO - Epoch(train) [420][20/63] lr: 1.4690e-03 eta: 8:00:47 time: 0.5200 data_time: 0.0093 memory: 14901 loss: 1.4532 loss_prob: 0.7919 loss_thr: 0.5282 loss_db: 0.1332 2022/11/02 16:40:38 - mmengine - INFO - Epoch(train) [420][25/63] lr: 1.4690e-03 eta: 8:00:47 time: 0.5185 data_time: 0.0155 memory: 14901 loss: 1.4541 loss_prob: 0.8042 loss_thr: 0.5149 loss_db: 0.1350 2022/11/02 16:40:41 - mmengine - INFO - Epoch(train) [420][30/63] lr: 1.4690e-03 eta: 8:00:41 time: 0.5957 data_time: 0.0423 memory: 14901 loss: 1.4495 loss_prob: 0.8025 loss_thr: 0.5111 loss_db: 0.1359 2022/11/02 16:40:44 - mmengine - INFO - Epoch(train) [420][35/63] lr: 1.4690e-03 eta: 8:00:41 time: 0.5906 data_time: 0.0353 memory: 14901 loss: 1.3903 loss_prob: 0.7523 loss_thr: 0.5117 loss_db: 0.1263 2022/11/02 16:40:46 - mmengine - INFO - Epoch(train) [420][40/63] lr: 1.4690e-03 eta: 8:00:35 time: 0.5615 data_time: 0.0085 memory: 14901 loss: 1.3820 loss_prob: 0.7321 loss_thr: 0.5256 loss_db: 0.1243 2022/11/02 16:40:49 - mmengine - INFO - Epoch(train) [420][45/63] lr: 1.4690e-03 eta: 8:00:35 time: 0.5828 data_time: 0.0105 memory: 14901 loss: 1.4270 loss_prob: 0.7574 loss_thr: 0.5399 loss_db: 0.1296 2022/11/02 16:40:52 - mmengine - INFO - Epoch(train) [420][50/63] lr: 1.4690e-03 eta: 8:00:28 time: 0.5482 data_time: 0.0148 memory: 14901 loss: 1.3591 loss_prob: 0.7291 loss_thr: 0.5051 loss_db: 0.1249 2022/11/02 16:40:55 - mmengine - INFO - Epoch(train) [420][55/63] lr: 1.4690e-03 eta: 8:00:28 time: 0.5378 data_time: 0.0268 memory: 14901 loss: 1.4391 loss_prob: 0.7930 loss_thr: 0.5130 loss_db: 0.1332 2022/11/02 16:40:57 - mmengine - INFO - Epoch(train) [420][60/63] lr: 1.4690e-03 eta: 8:00:22 time: 0.5431 data_time: 0.0252 memory: 14901 loss: 1.5358 loss_prob: 0.8390 loss_thr: 0.5584 loss_db: 0.1384 2022/11/02 16:40:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:40:59 - mmengine - INFO - Saving checkpoint at 420 epochs 2022/11/02 16:41:03 - mmengine - INFO - Epoch(val) [420][5/500] eta: 8:00:22 time: 0.0530 data_time: 0.0077 memory: 14901 2022/11/02 16:41:03 - mmengine - INFO - Epoch(val) [420][10/500] eta: 0:00:26 time: 0.0546 data_time: 0.0074 memory: 1008 2022/11/02 16:41:03 - mmengine - INFO - Epoch(val) [420][15/500] eta: 0:00:26 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 16:41:03 - mmengine - INFO - Epoch(val) [420][20/500] eta: 0:00:20 time: 0.0417 data_time: 0.0029 memory: 1008 2022/11/02 16:41:04 - mmengine - INFO - Epoch(val) [420][25/500] eta: 0:00:20 time: 0.0410 data_time: 0.0031 memory: 1008 2022/11/02 16:41:04 - mmengine - INFO - Epoch(val) [420][30/500] eta: 0:00:21 time: 0.0460 data_time: 0.0033 memory: 1008 2022/11/02 16:41:04 - mmengine - INFO - Epoch(val) [420][35/500] eta: 0:00:21 time: 0.0455 data_time: 0.0030 memory: 1008 2022/11/02 16:41:04 - mmengine - INFO - Epoch(val) [420][40/500] eta: 0:00:20 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 16:41:05 - mmengine - INFO - Epoch(val) [420][45/500] eta: 0:00:20 time: 0.0438 data_time: 0.0026 memory: 1008 2022/11/02 16:41:05 - mmengine - INFO - Epoch(val) [420][50/500] eta: 0:00:18 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 16:41:05 - mmengine - INFO - Epoch(val) [420][55/500] eta: 0:00:18 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/02 16:41:05 - mmengine - INFO - Epoch(val) [420][60/500] eta: 0:00:17 time: 0.0393 data_time: 0.0023 memory: 1008 2022/11/02 16:41:05 - mmengine - INFO - Epoch(val) [420][65/500] eta: 0:00:17 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/02 16:41:06 - mmengine - INFO - Epoch(val) [420][70/500] eta: 0:00:18 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 16:41:06 - mmengine - INFO - Epoch(val) [420][75/500] eta: 0:00:18 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 16:41:07 - mmengine - INFO - Epoch(val) [420][80/500] eta: 0:00:45 time: 0.1083 data_time: 0.0743 memory: 1008 2022/11/02 16:41:07 - mmengine - INFO - Epoch(val) [420][85/500] eta: 0:00:45 time: 0.1076 data_time: 0.0736 memory: 1008 2022/11/02 16:41:07 - mmengine - INFO - Epoch(val) [420][90/500] eta: 0:00:16 time: 0.0403 data_time: 0.0020 memory: 1008 2022/11/02 16:41:07 - mmengine - INFO - Epoch(val) [420][95/500] eta: 0:00:16 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/02 16:41:07 - mmengine - INFO - Epoch(val) [420][100/500] eta: 0:00:15 time: 0.0384 data_time: 0.0031 memory: 1008 2022/11/02 16:41:08 - mmengine - INFO - Epoch(val) [420][105/500] eta: 0:00:15 time: 0.0369 data_time: 0.0031 memory: 1008 2022/11/02 16:41:08 - mmengine - INFO - Epoch(val) [420][110/500] eta: 0:00:14 time: 0.0359 data_time: 0.0023 memory: 1008 2022/11/02 16:41:08 - mmengine - INFO - Epoch(val) [420][115/500] eta: 0:00:14 time: 0.0390 data_time: 0.0022 memory: 1008 2022/11/02 16:41:08 - mmengine - INFO - Epoch(val) [420][120/500] eta: 0:00:16 time: 0.0422 data_time: 0.0024 memory: 1008 2022/11/02 16:41:08 - mmengine - INFO - Epoch(val) [420][125/500] eta: 0:00:16 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/02 16:41:09 - mmengine - INFO - Epoch(val) [420][130/500] eta: 0:00:13 time: 0.0358 data_time: 0.0026 memory: 1008 2022/11/02 16:41:09 - mmengine - INFO - Epoch(val) [420][135/500] eta: 0:00:13 time: 0.0364 data_time: 0.0024 memory: 1008 2022/11/02 16:41:09 - mmengine - INFO - Epoch(val) [420][140/500] eta: 0:00:13 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 16:41:09 - mmengine - INFO - Epoch(val) [420][145/500] eta: 0:00:13 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/02 16:41:09 - mmengine - INFO - Epoch(val) [420][150/500] eta: 0:00:15 time: 0.0455 data_time: 0.0029 memory: 1008 2022/11/02 16:41:10 - mmengine - INFO - Epoch(val) [420][155/500] eta: 0:00:15 time: 0.0466 data_time: 0.0030 memory: 1008 2022/11/02 16:41:10 - mmengine - INFO - Epoch(val) [420][160/500] eta: 0:00:14 time: 0.0433 data_time: 0.0026 memory: 1008 2022/11/02 16:41:10 - mmengine - INFO - Epoch(val) [420][165/500] eta: 0:00:14 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 16:41:10 - mmengine - INFO - Epoch(val) [420][170/500] eta: 0:00:13 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 16:41:10 - mmengine - INFO - Epoch(val) [420][175/500] eta: 0:00:13 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 16:41:11 - mmengine - INFO - Epoch(val) [420][180/500] eta: 0:00:12 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 16:41:11 - mmengine - INFO - Epoch(val) [420][185/500] eta: 0:00:12 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 16:41:11 - mmengine - INFO - Epoch(val) [420][190/500] eta: 0:00:12 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/02 16:41:11 - mmengine - INFO - Epoch(val) [420][195/500] eta: 0:00:12 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 16:41:12 - mmengine - INFO - Epoch(val) [420][200/500] eta: 0:00:13 time: 0.0446 data_time: 0.0025 memory: 1008 2022/11/02 16:41:12 - mmengine - INFO - Epoch(val) [420][205/500] eta: 0:00:13 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 16:41:12 - mmengine - INFO - Epoch(val) [420][210/500] eta: 0:00:10 time: 0.0371 data_time: 0.0025 memory: 1008 2022/11/02 16:41:12 - mmengine - INFO - Epoch(val) [420][215/500] eta: 0:00:10 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 16:41:12 - mmengine - INFO - Epoch(val) [420][220/500] eta: 0:00:10 time: 0.0377 data_time: 0.0023 memory: 1008 2022/11/02 16:41:12 - mmengine - INFO - Epoch(val) [420][225/500] eta: 0:00:10 time: 0.0398 data_time: 0.0026 memory: 1008 2022/11/02 16:41:13 - mmengine - INFO - Epoch(val) [420][230/500] eta: 0:00:10 time: 0.0384 data_time: 0.0029 memory: 1008 2022/11/02 16:41:13 - mmengine - INFO - Epoch(val) [420][235/500] eta: 0:00:10 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 16:41:13 - mmengine - INFO - Epoch(val) [420][240/500] eta: 0:00:11 time: 0.0423 data_time: 0.0024 memory: 1008 2022/11/02 16:41:13 - mmengine - INFO - Epoch(val) [420][245/500] eta: 0:00:11 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/02 16:41:13 - mmengine - INFO - Epoch(val) [420][250/500] eta: 0:00:09 time: 0.0382 data_time: 0.0024 memory: 1008 2022/11/02 16:41:14 - mmengine - INFO - Epoch(val) [420][255/500] eta: 0:00:09 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 16:41:14 - mmengine - INFO - Epoch(val) [420][260/500] eta: 0:00:09 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 16:41:14 - mmengine - INFO - Epoch(val) [420][265/500] eta: 0:00:09 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 16:41:14 - mmengine - INFO - Epoch(val) [420][270/500] eta: 0:00:10 time: 0.0436 data_time: 0.0047 memory: 1008 2022/11/02 16:41:14 - mmengine - INFO - Epoch(val) [420][275/500] eta: 0:00:10 time: 0.0405 data_time: 0.0044 memory: 1008 2022/11/02 16:41:15 - mmengine - INFO - Epoch(val) [420][280/500] eta: 0:00:08 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/02 16:41:15 - mmengine - INFO - Epoch(val) [420][285/500] eta: 0:00:08 time: 0.0443 data_time: 0.0030 memory: 1008 2022/11/02 16:41:15 - mmengine - INFO - Epoch(val) [420][290/500] eta: 0:00:09 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/02 16:41:15 - mmengine - INFO - Epoch(val) [420][295/500] eta: 0:00:09 time: 0.0439 data_time: 0.0030 memory: 1008 2022/11/02 16:41:16 - mmengine - INFO - Epoch(val) [420][300/500] eta: 0:00:08 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/02 16:41:16 - mmengine - INFO - Epoch(val) [420][305/500] eta: 0:00:08 time: 0.0396 data_time: 0.0028 memory: 1008 2022/11/02 16:41:16 - mmengine - INFO - Epoch(val) [420][310/500] eta: 0:00:07 time: 0.0413 data_time: 0.0028 memory: 1008 2022/11/02 16:41:16 - mmengine - INFO - Epoch(val) [420][315/500] eta: 0:00:07 time: 0.0446 data_time: 0.0030 memory: 1008 2022/11/02 16:41:16 - mmengine - INFO - Epoch(val) [420][320/500] eta: 0:00:07 time: 0.0411 data_time: 0.0028 memory: 1008 2022/11/02 16:41:17 - mmengine - INFO - Epoch(val) [420][325/500] eta: 0:00:07 time: 0.0532 data_time: 0.0027 memory: 1008 2022/11/02 16:41:17 - mmengine - INFO - Epoch(val) [420][330/500] eta: 0:00:08 time: 0.0522 data_time: 0.0027 memory: 1008 2022/11/02 16:41:17 - mmengine - INFO - Epoch(val) [420][335/500] eta: 0:00:08 time: 0.0376 data_time: 0.0026 memory: 1008 2022/11/02 16:41:17 - mmengine - INFO - Epoch(val) [420][340/500] eta: 0:00:08 time: 0.0513 data_time: 0.0026 memory: 1008 2022/11/02 16:41:18 - mmengine - INFO - Epoch(val) [420][345/500] eta: 0:00:08 time: 0.0515 data_time: 0.0026 memory: 1008 2022/11/02 16:41:18 - mmengine - INFO - Epoch(val) [420][350/500] eta: 0:00:07 time: 0.0500 data_time: 0.0032 memory: 1008 2022/11/02 16:41:18 - mmengine - INFO - Epoch(val) [420][355/500] eta: 0:00:07 time: 0.0500 data_time: 0.0034 memory: 1008 2022/11/02 16:41:18 - mmengine - INFO - Epoch(val) [420][360/500] eta: 0:00:05 time: 0.0393 data_time: 0.0029 memory: 1008 2022/11/02 16:41:19 - mmengine - INFO - Epoch(val) [420][365/500] eta: 0:00:05 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/02 16:41:19 - mmengine - INFO - Epoch(val) [420][370/500] eta: 0:00:05 time: 0.0394 data_time: 0.0031 memory: 1008 2022/11/02 16:41:19 - mmengine - INFO - Epoch(val) [420][375/500] eta: 0:00:05 time: 0.0359 data_time: 0.0029 memory: 1008 2022/11/02 16:41:19 - mmengine - INFO - Epoch(val) [420][380/500] eta: 0:00:04 time: 0.0391 data_time: 0.0024 memory: 1008 2022/11/02 16:41:19 - mmengine - INFO - Epoch(val) [420][385/500] eta: 0:00:04 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/02 16:41:20 - mmengine - INFO - Epoch(val) [420][390/500] eta: 0:00:04 time: 0.0419 data_time: 0.0032 memory: 1008 2022/11/02 16:41:20 - mmengine - INFO - Epoch(val) [420][395/500] eta: 0:00:04 time: 0.0416 data_time: 0.0034 memory: 1008 2022/11/02 16:41:20 - mmengine - INFO - Epoch(val) [420][400/500] eta: 0:00:04 time: 0.0411 data_time: 0.0031 memory: 1008 2022/11/02 16:41:20 - mmengine - INFO - Epoch(val) [420][405/500] eta: 0:00:04 time: 0.0440 data_time: 0.0029 memory: 1008 2022/11/02 16:41:20 - mmengine - INFO - Epoch(val) [420][410/500] eta: 0:00:04 time: 0.0451 data_time: 0.0028 memory: 1008 2022/11/02 16:41:21 - mmengine - INFO - Epoch(val) [420][415/500] eta: 0:00:04 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 16:41:21 - mmengine - INFO - Epoch(val) [420][420/500] eta: 0:00:02 time: 0.0355 data_time: 0.0029 memory: 1008 2022/11/02 16:41:21 - mmengine - INFO - Epoch(val) [420][425/500] eta: 0:00:02 time: 0.0364 data_time: 0.0028 memory: 1008 2022/11/02 16:41:21 - mmengine - INFO - Epoch(val) [420][430/500] eta: 0:00:02 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 16:41:21 - mmengine - INFO - Epoch(val) [420][435/500] eta: 0:00:02 time: 0.0437 data_time: 0.0029 memory: 1008 2022/11/02 16:41:22 - mmengine - INFO - Epoch(val) [420][440/500] eta: 0:00:02 time: 0.0465 data_time: 0.0031 memory: 1008 2022/11/02 16:41:22 - mmengine - INFO - Epoch(val) [420][445/500] eta: 0:00:02 time: 0.0517 data_time: 0.0034 memory: 1008 2022/11/02 16:41:22 - mmengine - INFO - Epoch(val) [420][450/500] eta: 0:00:02 time: 0.0500 data_time: 0.0036 memory: 1008 2022/11/02 16:41:22 - mmengine - INFO - Epoch(val) [420][455/500] eta: 0:00:02 time: 0.0463 data_time: 0.0042 memory: 1008 2022/11/02 16:41:23 - mmengine - INFO - Epoch(val) [420][460/500] eta: 0:00:01 time: 0.0425 data_time: 0.0037 memory: 1008 2022/11/02 16:41:23 - mmengine - INFO - Epoch(val) [420][465/500] eta: 0:00:01 time: 0.0370 data_time: 0.0025 memory: 1008 2022/11/02 16:41:23 - mmengine - INFO - Epoch(val) [420][470/500] eta: 0:00:01 time: 0.0365 data_time: 0.0024 memory: 1008 2022/11/02 16:41:23 - mmengine - INFO - Epoch(val) [420][475/500] eta: 0:00:01 time: 0.0372 data_time: 0.0026 memory: 1008 2022/11/02 16:41:23 - mmengine - INFO - Epoch(val) [420][480/500] eta: 0:00:00 time: 0.0369 data_time: 0.0025 memory: 1008 2022/11/02 16:41:24 - mmengine - INFO - Epoch(val) [420][485/500] eta: 0:00:00 time: 0.0401 data_time: 0.0025 memory: 1008 2022/11/02 16:41:24 - mmengine - INFO - Epoch(val) [420][490/500] eta: 0:00:00 time: 0.0430 data_time: 0.0025 memory: 1008 2022/11/02 16:41:24 - mmengine - INFO - Epoch(val) [420][495/500] eta: 0:00:00 time: 0.0490 data_time: 0.0037 memory: 1008 2022/11/02 16:41:24 - mmengine - INFO - Epoch(val) [420][500/500] eta: 0:00:00 time: 0.0455 data_time: 0.0036 memory: 1008 2022/11/02 16:41:24 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8127, precision: 0.6820, hmean: 0.7417 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8122, precision: 0.7661, hmean: 0.7885 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8108, precision: 0.8004, hmean: 0.8055 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8021, precision: 0.8330, hmean: 0.8173 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7723, precision: 0.8708, hmean: 0.8186 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5729, precision: 0.9232, hmean: 0.7071 2022/11/02 16:41:24 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0221, precision: 0.9200, hmean: 0.0433 2022/11/02 16:41:24 - mmengine - INFO - Epoch(val) [420][500/500] icdar/precision: 0.8708 icdar/recall: 0.7723 icdar/hmean: 0.8186 2022/11/02 16:41:30 - mmengine - INFO - Epoch(train) [421][5/63] lr: 1.4673e-03 eta: 0:00:00 time: 0.8101 data_time: 0.2330 memory: 14901 loss: 1.3518 loss_prob: 0.7219 loss_thr: 0.5069 loss_db: 0.1231 2022/11/02 16:41:33 - mmengine - INFO - Epoch(train) [421][10/63] lr: 1.4673e-03 eta: 8:00:15 time: 0.8384 data_time: 0.2416 memory: 14901 loss: 1.3923 loss_prob: 0.7582 loss_thr: 0.5046 loss_db: 0.1295 2022/11/02 16:41:35 - mmengine - INFO - Epoch(train) [421][15/63] lr: 1.4673e-03 eta: 8:00:15 time: 0.5351 data_time: 0.0148 memory: 14901 loss: 1.4181 loss_prob: 0.7821 loss_thr: 0.5036 loss_db: 0.1325 2022/11/02 16:41:38 - mmengine - INFO - Epoch(train) [421][20/63] lr: 1.4673e-03 eta: 8:00:09 time: 0.5398 data_time: 0.0052 memory: 14901 loss: 1.4509 loss_prob: 0.8068 loss_thr: 0.5081 loss_db: 0.1360 2022/11/02 16:41:41 - mmengine - INFO - Epoch(train) [421][25/63] lr: 1.4673e-03 eta: 8:00:09 time: 0.5866 data_time: 0.0245 memory: 14901 loss: 1.4421 loss_prob: 0.7880 loss_thr: 0.5193 loss_db: 0.1348 2022/11/02 16:41:44 - mmengine - INFO - Epoch(train) [421][30/63] lr: 1.4673e-03 eta: 8:00:02 time: 0.5734 data_time: 0.0361 memory: 14901 loss: 1.3895 loss_prob: 0.7475 loss_thr: 0.5153 loss_db: 0.1267 2022/11/02 16:41:46 - mmengine - INFO - Epoch(train) [421][35/63] lr: 1.4673e-03 eta: 8:00:02 time: 0.5078 data_time: 0.0202 memory: 14901 loss: 1.4891 loss_prob: 0.8229 loss_thr: 0.5251 loss_db: 0.1412 2022/11/02 16:41:49 - mmengine - INFO - Epoch(train) [421][40/63] lr: 1.4673e-03 eta: 7:59:56 time: 0.5376 data_time: 0.0124 memory: 14901 loss: 1.5074 loss_prob: 0.8397 loss_thr: 0.5245 loss_db: 0.1431 2022/11/02 16:41:52 - mmengine - INFO - Epoch(train) [421][45/63] lr: 1.4673e-03 eta: 7:59:56 time: 0.5434 data_time: 0.0097 memory: 14901 loss: 1.4481 loss_prob: 0.7972 loss_thr: 0.5164 loss_db: 0.1345 2022/11/02 16:41:55 - mmengine - INFO - Epoch(train) [421][50/63] lr: 1.4673e-03 eta: 7:59:49 time: 0.5360 data_time: 0.0150 memory: 14901 loss: 1.4823 loss_prob: 0.8162 loss_thr: 0.5270 loss_db: 0.1390 2022/11/02 16:41:57 - mmengine - INFO - Epoch(train) [421][55/63] lr: 1.4673e-03 eta: 7:59:49 time: 0.5224 data_time: 0.0239 memory: 14901 loss: 1.4707 loss_prob: 0.8077 loss_thr: 0.5273 loss_db: 0.1357 2022/11/02 16:41:59 - mmengine - INFO - Epoch(train) [421][60/63] lr: 1.4673e-03 eta: 7:59:41 time: 0.4779 data_time: 0.0194 memory: 14901 loss: 1.3869 loss_prob: 0.7641 loss_thr: 0.4925 loss_db: 0.1303 2022/11/02 16:42:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:42:07 - mmengine - INFO - Epoch(train) [422][5/63] lr: 1.4656e-03 eta: 7:59:41 time: 0.8470 data_time: 0.2196 memory: 14901 loss: 1.4504 loss_prob: 0.8164 loss_thr: 0.4988 loss_db: 0.1352 2022/11/02 16:42:10 - mmengine - INFO - Epoch(train) [422][10/63] lr: 1.4656e-03 eta: 7:59:37 time: 0.9468 data_time: 0.2266 memory: 14901 loss: 1.4029 loss_prob: 0.7848 loss_thr: 0.4890 loss_db: 0.1291 2022/11/02 16:42:13 - mmengine - INFO - Epoch(train) [422][15/63] lr: 1.4656e-03 eta: 7:59:37 time: 0.6067 data_time: 0.0153 memory: 14901 loss: 1.3413 loss_prob: 0.7362 loss_thr: 0.4830 loss_db: 0.1221 2022/11/02 16:42:16 - mmengine - INFO - Epoch(train) [422][20/63] lr: 1.4656e-03 eta: 7:59:31 time: 0.5703 data_time: 0.0130 memory: 14901 loss: 1.3557 loss_prob: 0.7586 loss_thr: 0.4744 loss_db: 0.1227 2022/11/02 16:42:19 - mmengine - INFO - Epoch(train) [422][25/63] lr: 1.4656e-03 eta: 7:59:31 time: 0.6208 data_time: 0.0350 memory: 14901 loss: 1.3849 loss_prob: 0.7780 loss_thr: 0.4787 loss_db: 0.1282 2022/11/02 16:42:22 - mmengine - INFO - Epoch(train) [422][30/63] lr: 1.4656e-03 eta: 7:59:26 time: 0.6290 data_time: 0.0374 memory: 14901 loss: 1.3336 loss_prob: 0.7163 loss_thr: 0.4941 loss_db: 0.1232 2022/11/02 16:42:24 - mmengine - INFO - Epoch(train) [422][35/63] lr: 1.4656e-03 eta: 7:59:26 time: 0.5142 data_time: 0.0138 memory: 14901 loss: 1.3508 loss_prob: 0.7256 loss_thr: 0.5021 loss_db: 0.1231 2022/11/02 16:42:28 - mmengine - INFO - Epoch(train) [422][40/63] lr: 1.4656e-03 eta: 7:59:19 time: 0.5604 data_time: 0.0093 memory: 14901 loss: 1.4331 loss_prob: 0.7859 loss_thr: 0.5167 loss_db: 0.1305 2022/11/02 16:42:31 - mmengine - INFO - Epoch(train) [422][45/63] lr: 1.4656e-03 eta: 7:59:19 time: 0.6701 data_time: 0.0106 memory: 14901 loss: 1.3882 loss_prob: 0.7547 loss_thr: 0.5074 loss_db: 0.1261 2022/11/02 16:42:34 - mmengine - INFO - Epoch(train) [422][50/63] lr: 1.4656e-03 eta: 7:59:14 time: 0.6317 data_time: 0.0228 memory: 14901 loss: 1.4009 loss_prob: 0.7682 loss_thr: 0.5056 loss_db: 0.1271 2022/11/02 16:42:37 - mmengine - INFO - Epoch(train) [422][55/63] lr: 1.4656e-03 eta: 7:59:14 time: 0.5418 data_time: 0.0274 memory: 14901 loss: 1.4278 loss_prob: 0.7869 loss_thr: 0.5092 loss_db: 0.1316 2022/11/02 16:42:39 - mmengine - INFO - Epoch(train) [422][60/63] lr: 1.4656e-03 eta: 7:59:07 time: 0.5278 data_time: 0.0137 memory: 14901 loss: 1.3782 loss_prob: 0.7446 loss_thr: 0.5047 loss_db: 0.1289 2022/11/02 16:42:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:42:48 - mmengine - INFO - Epoch(train) [423][5/63] lr: 1.4639e-03 eta: 7:59:07 time: 0.9838 data_time: 0.3091 memory: 14901 loss: 1.6363 loss_prob: 0.9634 loss_thr: 0.5218 loss_db: 0.1511 2022/11/02 16:42:52 - mmengine - INFO - Epoch(train) [423][10/63] lr: 1.4639e-03 eta: 7:59:06 time: 1.1047 data_time: 0.3089 memory: 14901 loss: 1.6633 loss_prob: 0.9886 loss_thr: 0.5220 loss_db: 0.1527 2022/11/02 16:42:55 - mmengine - INFO - Epoch(train) [423][15/63] lr: 1.4639e-03 eta: 7:59:06 time: 0.6709 data_time: 0.0130 memory: 14901 loss: 1.3394 loss_prob: 0.7341 loss_thr: 0.4820 loss_db: 0.1233 2022/11/02 16:42:58 - mmengine - INFO - Epoch(train) [423][20/63] lr: 1.4639e-03 eta: 7:59:01 time: 0.6133 data_time: 0.0153 memory: 14901 loss: 1.4832 loss_prob: 0.8274 loss_thr: 0.5176 loss_db: 0.1382 2022/11/02 16:43:01 - mmengine - INFO - Epoch(train) [423][25/63] lr: 1.4639e-03 eta: 7:59:01 time: 0.5723 data_time: 0.0424 memory: 14901 loss: 1.5861 loss_prob: 0.9053 loss_thr: 0.5324 loss_db: 0.1484 2022/11/02 16:43:03 - mmengine - INFO - Epoch(train) [423][30/63] lr: 1.4639e-03 eta: 7:58:54 time: 0.5443 data_time: 0.0402 memory: 14901 loss: 1.4542 loss_prob: 0.7942 loss_thr: 0.5280 loss_db: 0.1320 2022/11/02 16:43:06 - mmengine - INFO - Epoch(train) [423][35/63] lr: 1.4639e-03 eta: 7:58:54 time: 0.5372 data_time: 0.0104 memory: 14901 loss: 1.4171 loss_prob: 0.7578 loss_thr: 0.5299 loss_db: 0.1293 2022/11/02 16:43:09 - mmengine - INFO - Epoch(train) [423][40/63] lr: 1.4639e-03 eta: 7:58:48 time: 0.5626 data_time: 0.0095 memory: 14901 loss: 1.5109 loss_prob: 0.8386 loss_thr: 0.5293 loss_db: 0.1429 2022/11/02 16:43:12 - mmengine - INFO - Epoch(train) [423][45/63] lr: 1.4639e-03 eta: 7:58:48 time: 0.5835 data_time: 0.0117 memory: 14901 loss: 1.5302 loss_prob: 0.8559 loss_thr: 0.5305 loss_db: 0.1438 2022/11/02 16:43:14 - mmengine - INFO - Epoch(train) [423][50/63] lr: 1.4639e-03 eta: 7:58:41 time: 0.5471 data_time: 0.0276 memory: 14901 loss: 1.5536 loss_prob: 0.8778 loss_thr: 0.5288 loss_db: 0.1470 2022/11/02 16:43:17 - mmengine - INFO - Epoch(train) [423][55/63] lr: 1.4639e-03 eta: 7:58:41 time: 0.5489 data_time: 0.0241 memory: 14901 loss: 1.5669 loss_prob: 0.8817 loss_thr: 0.5392 loss_db: 0.1461 2022/11/02 16:43:20 - mmengine - INFO - Epoch(train) [423][60/63] lr: 1.4639e-03 eta: 7:58:35 time: 0.5771 data_time: 0.0087 memory: 14901 loss: 1.4876 loss_prob: 0.8177 loss_thr: 0.5338 loss_db: 0.1361 2022/11/02 16:43:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:43:27 - mmengine - INFO - Epoch(train) [424][5/63] lr: 1.4622e-03 eta: 7:58:35 time: 0.8565 data_time: 0.2256 memory: 14901 loss: 1.4629 loss_prob: 0.8020 loss_thr: 0.5238 loss_db: 0.1372 2022/11/02 16:43:32 - mmengine - INFO - Epoch(train) [424][10/63] lr: 1.4622e-03 eta: 7:58:32 time: 1.0085 data_time: 0.2257 memory: 14901 loss: 1.5610 loss_prob: 0.8700 loss_thr: 0.5417 loss_db: 0.1493 2022/11/02 16:43:35 - mmengine - INFO - Epoch(train) [424][15/63] lr: 1.4622e-03 eta: 7:58:32 time: 0.7119 data_time: 0.0072 memory: 14901 loss: 1.4922 loss_prob: 0.8267 loss_thr: 0.5263 loss_db: 0.1392 2022/11/02 16:43:37 - mmengine - INFO - Epoch(train) [424][20/63] lr: 1.4622e-03 eta: 7:58:26 time: 0.5679 data_time: 0.0062 memory: 14901 loss: 1.4875 loss_prob: 0.8414 loss_thr: 0.5052 loss_db: 0.1408 2022/11/02 16:43:40 - mmengine - INFO - Epoch(train) [424][25/63] lr: 1.4622e-03 eta: 7:58:26 time: 0.5694 data_time: 0.0257 memory: 14901 loss: 1.4865 loss_prob: 0.8460 loss_thr: 0.4992 loss_db: 0.1413 2022/11/02 16:43:43 - mmengine - INFO - Epoch(train) [424][30/63] lr: 1.4622e-03 eta: 7:58:20 time: 0.5839 data_time: 0.0494 memory: 14901 loss: 1.4215 loss_prob: 0.7875 loss_thr: 0.5022 loss_db: 0.1319 2022/11/02 16:43:46 - mmengine - INFO - Epoch(train) [424][35/63] lr: 1.4622e-03 eta: 7:58:20 time: 0.5452 data_time: 0.0307 memory: 14901 loss: 1.5233 loss_prob: 0.8505 loss_thr: 0.5318 loss_db: 0.1410 2022/11/02 16:43:48 - mmengine - INFO - Epoch(train) [424][40/63] lr: 1.4622e-03 eta: 7:58:13 time: 0.5303 data_time: 0.0079 memory: 14901 loss: 1.6070 loss_prob: 0.9030 loss_thr: 0.5525 loss_db: 0.1514 2022/11/02 16:43:51 - mmengine - INFO - Epoch(train) [424][45/63] lr: 1.4622e-03 eta: 7:58:13 time: 0.5260 data_time: 0.0076 memory: 14901 loss: 1.6448 loss_prob: 0.9281 loss_thr: 0.5586 loss_db: 0.1581 2022/11/02 16:43:54 - mmengine - INFO - Epoch(train) [424][50/63] lr: 1.4622e-03 eta: 7:58:07 time: 0.5728 data_time: 0.0134 memory: 14901 loss: 1.5290 loss_prob: 0.8587 loss_thr: 0.5294 loss_db: 0.1409 2022/11/02 16:43:57 - mmengine - INFO - Epoch(train) [424][55/63] lr: 1.4622e-03 eta: 7:58:07 time: 0.5769 data_time: 0.0340 memory: 14901 loss: 1.3574 loss_prob: 0.7469 loss_thr: 0.4878 loss_db: 0.1227 2022/11/02 16:44:00 - mmengine - INFO - Epoch(train) [424][60/63] lr: 1.4622e-03 eta: 7:58:00 time: 0.5575 data_time: 0.0301 memory: 14901 loss: 1.4180 loss_prob: 0.7798 loss_thr: 0.5058 loss_db: 0.1324 2022/11/02 16:44:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:44:06 - mmengine - INFO - Epoch(train) [425][5/63] lr: 1.4605e-03 eta: 7:58:00 time: 0.7881 data_time: 0.2287 memory: 14901 loss: 1.7001 loss_prob: 1.0033 loss_thr: 0.5377 loss_db: 0.1592 2022/11/02 16:44:09 - mmengine - INFO - Epoch(train) [425][10/63] lr: 1.4605e-03 eta: 7:57:54 time: 0.8270 data_time: 0.2393 memory: 14901 loss: 1.4474 loss_prob: 0.8036 loss_thr: 0.5100 loss_db: 0.1339 2022/11/02 16:44:13 - mmengine - INFO - Epoch(train) [425][15/63] lr: 1.4605e-03 eta: 7:57:54 time: 0.7007 data_time: 0.0209 memory: 14901 loss: 1.4546 loss_prob: 0.7945 loss_thr: 0.5279 loss_db: 0.1322 2022/11/02 16:44:16 - mmengine - INFO - Epoch(train) [425][20/63] lr: 1.4605e-03 eta: 7:57:49 time: 0.6526 data_time: 0.0082 memory: 14901 loss: 1.4848 loss_prob: 0.8126 loss_thr: 0.5380 loss_db: 0.1341 2022/11/02 16:44:19 - mmengine - INFO - Epoch(train) [425][25/63] lr: 1.4605e-03 eta: 7:57:49 time: 0.6149 data_time: 0.0321 memory: 14901 loss: 1.4627 loss_prob: 0.7970 loss_thr: 0.5334 loss_db: 0.1323 2022/11/02 16:44:22 - mmengine - INFO - Epoch(train) [425][30/63] lr: 1.4605e-03 eta: 7:57:45 time: 0.6513 data_time: 0.0338 memory: 14901 loss: 1.4309 loss_prob: 0.7887 loss_thr: 0.5089 loss_db: 0.1333 2022/11/02 16:44:25 - mmengine - INFO - Epoch(train) [425][35/63] lr: 1.4605e-03 eta: 7:57:45 time: 0.5879 data_time: 0.0212 memory: 14901 loss: 1.4298 loss_prob: 0.8027 loss_thr: 0.4928 loss_db: 0.1343 2022/11/02 16:44:28 - mmengine - INFO - Epoch(train) [425][40/63] lr: 1.4605e-03 eta: 7:57:38 time: 0.5686 data_time: 0.0198 memory: 14901 loss: 1.6175 loss_prob: 0.9201 loss_thr: 0.5438 loss_db: 0.1536 2022/11/02 16:44:31 - mmengine - INFO - Epoch(train) [425][45/63] lr: 1.4605e-03 eta: 7:57:38 time: 0.5489 data_time: 0.0088 memory: 14901 loss: 1.6075 loss_prob: 0.9084 loss_thr: 0.5455 loss_db: 0.1537 2022/11/02 16:44:34 - mmengine - INFO - Epoch(train) [425][50/63] lr: 1.4605e-03 eta: 7:57:32 time: 0.5753 data_time: 0.0232 memory: 14901 loss: 1.4017 loss_prob: 0.7770 loss_thr: 0.4937 loss_db: 0.1310 2022/11/02 16:44:37 - mmengine - INFO - Epoch(train) [425][55/63] lr: 1.4605e-03 eta: 7:57:32 time: 0.5920 data_time: 0.0244 memory: 14901 loss: 1.3679 loss_prob: 0.7520 loss_thr: 0.4874 loss_db: 0.1285 2022/11/02 16:44:40 - mmengine - INFO - Epoch(train) [425][60/63] lr: 1.4605e-03 eta: 7:57:26 time: 0.5755 data_time: 0.0159 memory: 14901 loss: 1.3917 loss_prob: 0.7649 loss_thr: 0.4978 loss_db: 0.1290 2022/11/02 16:44:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:44:46 - mmengine - INFO - Epoch(train) [426][5/63] lr: 1.4588e-03 eta: 7:57:26 time: 0.7314 data_time: 0.2330 memory: 14901 loss: 1.3212 loss_prob: 0.7057 loss_thr: 0.4938 loss_db: 0.1216 2022/11/02 16:44:49 - mmengine - INFO - Epoch(train) [426][10/63] lr: 1.4588e-03 eta: 7:57:19 time: 0.7606 data_time: 0.2406 memory: 14901 loss: 1.4030 loss_prob: 0.7596 loss_thr: 0.5167 loss_db: 0.1268 2022/11/02 16:44:52 - mmengine - INFO - Epoch(train) [426][15/63] lr: 1.4588e-03 eta: 7:57:19 time: 0.5689 data_time: 0.0198 memory: 14901 loss: 1.4056 loss_prob: 0.7682 loss_thr: 0.5111 loss_db: 0.1263 2022/11/02 16:44:55 - mmengine - INFO - Epoch(train) [426][20/63] lr: 1.4588e-03 eta: 7:57:14 time: 0.6700 data_time: 0.0101 memory: 14901 loss: 1.3469 loss_prob: 0.7225 loss_thr: 0.5009 loss_db: 0.1236 2022/11/02 16:44:59 - mmengine - INFO - Epoch(train) [426][25/63] lr: 1.4588e-03 eta: 7:57:14 time: 0.7020 data_time: 0.0273 memory: 14901 loss: 1.3604 loss_prob: 0.7304 loss_thr: 0.5034 loss_db: 0.1266 2022/11/02 16:45:01 - mmengine - INFO - Epoch(train) [426][30/63] lr: 1.4588e-03 eta: 7:57:09 time: 0.6111 data_time: 0.0322 memory: 14901 loss: 1.3574 loss_prob: 0.7443 loss_thr: 0.4861 loss_db: 0.1270 2022/11/02 16:45:04 - mmengine - INFO - Epoch(train) [426][35/63] lr: 1.4588e-03 eta: 7:57:09 time: 0.5385 data_time: 0.0251 memory: 14901 loss: 1.3365 loss_prob: 0.7376 loss_thr: 0.4748 loss_db: 0.1241 2022/11/02 16:45:07 - mmengine - INFO - Epoch(train) [426][40/63] lr: 1.4588e-03 eta: 7:57:02 time: 0.5353 data_time: 0.0217 memory: 14901 loss: 1.3295 loss_prob: 0.7206 loss_thr: 0.4884 loss_db: 0.1205 2022/11/02 16:45:10 - mmengine - INFO - Epoch(train) [426][45/63] lr: 1.4588e-03 eta: 7:57:02 time: 0.5488 data_time: 0.0105 memory: 14901 loss: 1.3259 loss_prob: 0.7189 loss_thr: 0.4848 loss_db: 0.1222 2022/11/02 16:45:12 - mmengine - INFO - Epoch(train) [426][50/63] lr: 1.4588e-03 eta: 7:56:55 time: 0.5372 data_time: 0.0223 memory: 14901 loss: 1.2802 loss_prob: 0.6903 loss_thr: 0.4714 loss_db: 0.1185 2022/11/02 16:45:15 - mmengine - INFO - Epoch(train) [426][55/63] lr: 1.4588e-03 eta: 7:56:55 time: 0.5273 data_time: 0.0286 memory: 14901 loss: 1.2574 loss_prob: 0.6682 loss_thr: 0.4749 loss_db: 0.1144 2022/11/02 16:45:17 - mmengine - INFO - Epoch(train) [426][60/63] lr: 1.4588e-03 eta: 7:56:48 time: 0.5181 data_time: 0.0184 memory: 14901 loss: 1.3844 loss_prob: 0.7495 loss_thr: 0.5085 loss_db: 0.1264 2022/11/02 16:45:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:45:26 - mmengine - INFO - Epoch(train) [427][5/63] lr: 1.4571e-03 eta: 7:56:48 time: 0.9149 data_time: 0.2931 memory: 14901 loss: 1.3452 loss_prob: 0.7208 loss_thr: 0.5004 loss_db: 0.1240 2022/11/02 16:45:29 - mmengine - INFO - Epoch(train) [427][10/63] lr: 1.4571e-03 eta: 7:56:45 time: 1.0116 data_time: 0.3176 memory: 14901 loss: 1.1926 loss_prob: 0.6312 loss_thr: 0.4538 loss_db: 0.1076 2022/11/02 16:45:32 - mmengine - INFO - Epoch(train) [427][15/63] lr: 1.4571e-03 eta: 7:56:45 time: 0.6624 data_time: 0.0332 memory: 14901 loss: 1.3947 loss_prob: 0.7660 loss_thr: 0.4966 loss_db: 0.1321 2022/11/02 16:45:36 - mmengine - INFO - Epoch(train) [427][20/63] lr: 1.4571e-03 eta: 7:56:41 time: 0.7038 data_time: 0.0094 memory: 14901 loss: 1.5542 loss_prob: 0.8754 loss_thr: 0.5293 loss_db: 0.1495 2022/11/02 16:45:39 - mmengine - INFO - Epoch(train) [427][25/63] lr: 1.4571e-03 eta: 7:56:41 time: 0.6827 data_time: 0.0279 memory: 14901 loss: 1.5505 loss_prob: 0.8752 loss_thr: 0.5306 loss_db: 0.1446 2022/11/02 16:45:42 - mmengine - INFO - Epoch(train) [427][30/63] lr: 1.4571e-03 eta: 7:56:36 time: 0.6350 data_time: 0.0269 memory: 14901 loss: 1.5899 loss_prob: 0.9054 loss_thr: 0.5412 loss_db: 0.1433 2022/11/02 16:45:45 - mmengine - INFO - Epoch(train) [427][35/63] lr: 1.4571e-03 eta: 7:56:36 time: 0.6196 data_time: 0.0103 memory: 14901 loss: 1.5631 loss_prob: 0.8797 loss_thr: 0.5400 loss_db: 0.1434 2022/11/02 16:45:48 - mmengine - INFO - Epoch(train) [427][40/63] lr: 1.4571e-03 eta: 7:56:31 time: 0.6012 data_time: 0.0139 memory: 14901 loss: 1.5248 loss_prob: 0.8364 loss_thr: 0.5455 loss_db: 0.1429 2022/11/02 16:45:51 - mmengine - INFO - Epoch(train) [427][45/63] lr: 1.4571e-03 eta: 7:56:31 time: 0.6002 data_time: 0.0089 memory: 14901 loss: 1.4695 loss_prob: 0.8038 loss_thr: 0.5322 loss_db: 0.1335 2022/11/02 16:45:55 - mmengine - INFO - Epoch(train) [427][50/63] lr: 1.4571e-03 eta: 7:56:26 time: 0.6689 data_time: 0.0251 memory: 14901 loss: 1.5142 loss_prob: 0.8347 loss_thr: 0.5403 loss_db: 0.1393 2022/11/02 16:45:58 - mmengine - INFO - Epoch(train) [427][55/63] lr: 1.4571e-03 eta: 7:56:26 time: 0.6413 data_time: 0.0274 memory: 14901 loss: 1.4855 loss_prob: 0.8206 loss_thr: 0.5245 loss_db: 0.1404 2022/11/02 16:46:01 - mmengine - INFO - Epoch(train) [427][60/63] lr: 1.4571e-03 eta: 7:56:20 time: 0.5818 data_time: 0.0102 memory: 14901 loss: 1.3998 loss_prob: 0.7691 loss_thr: 0.5002 loss_db: 0.1305 2022/11/02 16:46:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:46:08 - mmengine - INFO - Epoch(train) [428][5/63] lr: 1.4554e-03 eta: 7:56:20 time: 0.9070 data_time: 0.2300 memory: 14901 loss: 1.6250 loss_prob: 0.9055 loss_thr: 0.5702 loss_db: 0.1493 2022/11/02 16:46:12 - mmengine - INFO - Epoch(train) [428][10/63] lr: 1.4554e-03 eta: 7:56:16 time: 0.9731 data_time: 0.2611 memory: 14901 loss: 1.5682 loss_prob: 0.8699 loss_thr: 0.5540 loss_db: 0.1444 2022/11/02 16:46:15 - mmengine - INFO - Epoch(train) [428][15/63] lr: 1.4554e-03 eta: 7:56:16 time: 0.6778 data_time: 0.0373 memory: 14901 loss: 1.4338 loss_prob: 0.7879 loss_thr: 0.5125 loss_db: 0.1334 2022/11/02 16:46:20 - mmengine - INFO - Epoch(train) [428][20/63] lr: 1.4554e-03 eta: 7:56:15 time: 0.8286 data_time: 0.0099 memory: 14901 loss: 1.3313 loss_prob: 0.7269 loss_thr: 0.4806 loss_db: 0.1239 2022/11/02 16:46:23 - mmengine - INFO - Epoch(train) [428][25/63] lr: 1.4554e-03 eta: 7:56:15 time: 0.7677 data_time: 0.0138 memory: 14901 loss: 1.3332 loss_prob: 0.7229 loss_thr: 0.4851 loss_db: 0.1253 2022/11/02 16:46:26 - mmengine - INFO - Epoch(train) [428][30/63] lr: 1.4554e-03 eta: 7:56:09 time: 0.5965 data_time: 0.0180 memory: 14901 loss: 1.5140 loss_prob: 0.8489 loss_thr: 0.5236 loss_db: 0.1415 2022/11/02 16:46:30 - mmengine - INFO - Epoch(train) [428][35/63] lr: 1.4554e-03 eta: 7:56:09 time: 0.6690 data_time: 0.0242 memory: 14901 loss: 1.5131 loss_prob: 0.8489 loss_thr: 0.5260 loss_db: 0.1381 2022/11/02 16:46:33 - mmengine - INFO - Epoch(train) [428][40/63] lr: 1.4554e-03 eta: 7:56:06 time: 0.7078 data_time: 0.0183 memory: 14901 loss: 1.5882 loss_prob: 0.9141 loss_thr: 0.5306 loss_db: 0.1435 2022/11/02 16:46:36 - mmengine - INFO - Epoch(train) [428][45/63] lr: 1.4554e-03 eta: 7:56:06 time: 0.6488 data_time: 0.0102 memory: 14901 loss: 1.6177 loss_prob: 0.9447 loss_thr: 0.5213 loss_db: 0.1517 2022/11/02 16:46:39 - mmengine - INFO - Epoch(train) [428][50/63] lr: 1.4554e-03 eta: 7:56:00 time: 0.6123 data_time: 0.0098 memory: 14901 loss: 1.5429 loss_prob: 0.8902 loss_thr: 0.5097 loss_db: 0.1430 2022/11/02 16:46:42 - mmengine - INFO - Epoch(train) [428][55/63] lr: 1.4554e-03 eta: 7:56:00 time: 0.6012 data_time: 0.0223 memory: 14901 loss: 1.5044 loss_prob: 0.8583 loss_thr: 0.5101 loss_db: 0.1360 2022/11/02 16:46:46 - mmengine - INFO - Epoch(train) [428][60/63] lr: 1.4554e-03 eta: 7:55:56 time: 0.6848 data_time: 0.0245 memory: 14901 loss: 1.3623 loss_prob: 0.7421 loss_thr: 0.4919 loss_db: 0.1283 2022/11/02 16:46:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:46:54 - mmengine - INFO - Epoch(train) [429][5/63] lr: 1.4537e-03 eta: 7:55:56 time: 0.9117 data_time: 0.2196 memory: 14901 loss: 1.4436 loss_prob: 0.7890 loss_thr: 0.5217 loss_db: 0.1329 2022/11/02 16:46:58 - mmengine - INFO - Epoch(train) [429][10/63] lr: 1.4537e-03 eta: 7:55:53 time: 1.0453 data_time: 0.2233 memory: 14901 loss: 1.4354 loss_prob: 0.7916 loss_thr: 0.5125 loss_db: 0.1313 2022/11/02 16:47:01 - mmengine - INFO - Epoch(train) [429][15/63] lr: 1.4537e-03 eta: 7:55:53 time: 0.6723 data_time: 0.0118 memory: 14901 loss: 1.4088 loss_prob: 0.7774 loss_thr: 0.5003 loss_db: 0.1311 2022/11/02 16:47:04 - mmengine - INFO - Epoch(train) [429][20/63] lr: 1.4537e-03 eta: 7:55:48 time: 0.6159 data_time: 0.0076 memory: 14901 loss: 1.3866 loss_prob: 0.7584 loss_thr: 0.5006 loss_db: 0.1277 2022/11/02 16:47:07 - mmengine - INFO - Epoch(train) [429][25/63] lr: 1.4537e-03 eta: 7:55:48 time: 0.6653 data_time: 0.0246 memory: 14901 loss: 1.3498 loss_prob: 0.7375 loss_thr: 0.4875 loss_db: 0.1248 2022/11/02 16:47:10 - mmengine - INFO - Epoch(train) [429][30/63] lr: 1.4537e-03 eta: 7:55:43 time: 0.6293 data_time: 0.0600 memory: 14901 loss: 1.3672 loss_prob: 0.7488 loss_thr: 0.4896 loss_db: 0.1288 2022/11/02 16:47:13 - mmengine - INFO - Epoch(train) [429][35/63] lr: 1.4537e-03 eta: 7:55:43 time: 0.5961 data_time: 0.0472 memory: 14901 loss: 1.4052 loss_prob: 0.7746 loss_thr: 0.5008 loss_db: 0.1298 2022/11/02 16:47:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:47:17 - mmengine - INFO - Epoch(train) [429][40/63] lr: 1.4537e-03 eta: 7:55:38 time: 0.6459 data_time: 0.0119 memory: 14901 loss: 1.4549 loss_prob: 0.8034 loss_thr: 0.5152 loss_db: 0.1364 2022/11/02 16:47:19 - mmengine - INFO - Epoch(train) [429][45/63] lr: 1.4537e-03 eta: 7:55:38 time: 0.6089 data_time: 0.0108 memory: 14901 loss: 1.5360 loss_prob: 0.8527 loss_thr: 0.5384 loss_db: 0.1448 2022/11/02 16:47:23 - mmengine - INFO - Epoch(train) [429][50/63] lr: 1.4537e-03 eta: 7:55:32 time: 0.5963 data_time: 0.0313 memory: 14901 loss: 1.4719 loss_prob: 0.8178 loss_thr: 0.5192 loss_db: 0.1349 2022/11/02 16:47:26 - mmengine - INFO - Epoch(train) [429][55/63] lr: 1.4537e-03 eta: 7:55:32 time: 0.6256 data_time: 0.0286 memory: 14901 loss: 1.3625 loss_prob: 0.7446 loss_thr: 0.4933 loss_db: 0.1245 2022/11/02 16:47:28 - mmengine - INFO - Epoch(train) [429][60/63] lr: 1.4537e-03 eta: 7:55:26 time: 0.5261 data_time: 0.0074 memory: 14901 loss: 1.4957 loss_prob: 0.8307 loss_thr: 0.5263 loss_db: 0.1387 2022/11/02 16:47:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:47:35 - mmengine - INFO - Epoch(train) [430][5/63] lr: 1.4521e-03 eta: 7:55:26 time: 0.8194 data_time: 0.2458 memory: 14901 loss: 1.5312 loss_prob: 0.8625 loss_thr: 0.5238 loss_db: 0.1448 2022/11/02 16:47:38 - mmengine - INFO - Epoch(train) [430][10/63] lr: 1.4521e-03 eta: 7:55:20 time: 0.8987 data_time: 0.2607 memory: 14901 loss: 1.5027 loss_prob: 0.8463 loss_thr: 0.5134 loss_db: 0.1431 2022/11/02 16:47:41 - mmengine - INFO - Epoch(train) [430][15/63] lr: 1.4521e-03 eta: 7:55:20 time: 0.6063 data_time: 0.0269 memory: 14901 loss: 1.4859 loss_prob: 0.8042 loss_thr: 0.5435 loss_db: 0.1382 2022/11/02 16:47:45 - mmengine - INFO - Epoch(train) [430][20/63] lr: 1.4521e-03 eta: 7:55:15 time: 0.6368 data_time: 0.0139 memory: 14901 loss: 1.5777 loss_prob: 0.8853 loss_thr: 0.5450 loss_db: 0.1475 2022/11/02 16:47:48 - mmengine - INFO - Epoch(train) [430][25/63] lr: 1.4521e-03 eta: 7:55:15 time: 0.7138 data_time: 0.0097 memory: 14901 loss: 1.6712 loss_prob: 0.9727 loss_thr: 0.5384 loss_db: 0.1601 2022/11/02 16:47:52 - mmengine - INFO - Epoch(train) [430][30/63] lr: 1.4521e-03 eta: 7:55:12 time: 0.7094 data_time: 0.0286 memory: 14901 loss: 1.6175 loss_prob: 0.9190 loss_thr: 0.5494 loss_db: 0.1491 2022/11/02 16:47:55 - mmengine - INFO - Epoch(train) [430][35/63] lr: 1.4521e-03 eta: 7:55:12 time: 0.6131 data_time: 0.0280 memory: 14901 loss: 1.4847 loss_prob: 0.8172 loss_thr: 0.5320 loss_db: 0.1354 2022/11/02 16:47:58 - mmengine - INFO - Epoch(train) [430][40/63] lr: 1.4521e-03 eta: 7:55:06 time: 0.5981 data_time: 0.0095 memory: 14901 loss: 1.5138 loss_prob: 0.8288 loss_thr: 0.5392 loss_db: 0.1458 2022/11/02 16:48:01 - mmengine - INFO - Epoch(train) [430][45/63] lr: 1.4521e-03 eta: 7:55:06 time: 0.6076 data_time: 0.0124 memory: 14901 loss: 1.6504 loss_prob: 0.9283 loss_thr: 0.5635 loss_db: 0.1586 2022/11/02 16:48:05 - mmengine - INFO - Epoch(train) [430][50/63] lr: 1.4521e-03 eta: 7:55:02 time: 0.6710 data_time: 0.0240 memory: 14901 loss: 1.6596 loss_prob: 0.9500 loss_thr: 0.5526 loss_db: 0.1570 2022/11/02 16:48:08 - mmengine - INFO - Epoch(train) [430][55/63] lr: 1.4521e-03 eta: 7:55:02 time: 0.6973 data_time: 0.0302 memory: 14901 loss: 1.5129 loss_prob: 0.8535 loss_thr: 0.5171 loss_db: 0.1424 2022/11/02 16:48:11 - mmengine - INFO - Epoch(train) [430][60/63] lr: 1.4521e-03 eta: 7:54:57 time: 0.6550 data_time: 0.0190 memory: 14901 loss: 1.4696 loss_prob: 0.8196 loss_thr: 0.5135 loss_db: 0.1365 2022/11/02 16:48:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:48:19 - mmengine - INFO - Epoch(train) [431][5/63] lr: 1.4504e-03 eta: 7:54:57 time: 0.9109 data_time: 0.2152 memory: 14901 loss: 1.4982 loss_prob: 0.8308 loss_thr: 0.5282 loss_db: 0.1392 2022/11/02 16:48:23 - mmengine - INFO - Epoch(train) [431][10/63] lr: 1.4504e-03 eta: 7:54:54 time: 1.0118 data_time: 0.2424 memory: 14901 loss: 1.4019 loss_prob: 0.7682 loss_thr: 0.5022 loss_db: 0.1316 2022/11/02 16:48:25 - mmengine - INFO - Epoch(train) [431][15/63] lr: 1.4504e-03 eta: 7:54:54 time: 0.6829 data_time: 0.0385 memory: 14901 loss: 1.5269 loss_prob: 0.8453 loss_thr: 0.5390 loss_db: 0.1426 2022/11/02 16:48:29 - mmengine - INFO - Epoch(train) [431][20/63] lr: 1.4504e-03 eta: 7:54:48 time: 0.6069 data_time: 0.0099 memory: 14901 loss: 1.6451 loss_prob: 0.9328 loss_thr: 0.5584 loss_db: 0.1539 2022/11/02 16:48:32 - mmengine - INFO - Epoch(train) [431][25/63] lr: 1.4504e-03 eta: 7:54:48 time: 0.6796 data_time: 0.0091 memory: 14901 loss: 1.3450 loss_prob: 0.7502 loss_thr: 0.4681 loss_db: 0.1267 2022/11/02 16:48:35 - mmengine - INFO - Epoch(train) [431][30/63] lr: 1.4504e-03 eta: 7:54:43 time: 0.6146 data_time: 0.0294 memory: 14901 loss: 1.2477 loss_prob: 0.6737 loss_thr: 0.4584 loss_db: 0.1156 2022/11/02 16:48:38 - mmengine - INFO - Epoch(train) [431][35/63] lr: 1.4504e-03 eta: 7:54:43 time: 0.5674 data_time: 0.0289 memory: 14901 loss: 1.4535 loss_prob: 0.8031 loss_thr: 0.5145 loss_db: 0.1358 2022/11/02 16:48:41 - mmengine - INFO - Epoch(train) [431][40/63] lr: 1.4504e-03 eta: 7:54:36 time: 0.5538 data_time: 0.0080 memory: 14901 loss: 1.6290 loss_prob: 0.9166 loss_thr: 0.5611 loss_db: 0.1513 2022/11/02 16:48:43 - mmengine - INFO - Epoch(train) [431][45/63] lr: 1.4504e-03 eta: 7:54:36 time: 0.5135 data_time: 0.0050 memory: 14901 loss: 1.5570 loss_prob: 0.8699 loss_thr: 0.5437 loss_db: 0.1434 2022/11/02 16:48:45 - mmengine - INFO - Epoch(train) [431][50/63] lr: 1.4504e-03 eta: 7:54:29 time: 0.4864 data_time: 0.0087 memory: 14901 loss: 1.3975 loss_prob: 0.7682 loss_thr: 0.4990 loss_db: 0.1303 2022/11/02 16:48:48 - mmengine - INFO - Epoch(train) [431][55/63] lr: 1.4504e-03 eta: 7:54:29 time: 0.5117 data_time: 0.0286 memory: 14901 loss: 1.3422 loss_prob: 0.7262 loss_thr: 0.4949 loss_db: 0.1211 2022/11/02 16:48:51 - mmengine - INFO - Epoch(train) [431][60/63] lr: 1.4504e-03 eta: 7:54:22 time: 0.5339 data_time: 0.0245 memory: 14901 loss: 1.3912 loss_prob: 0.7728 loss_thr: 0.4908 loss_db: 0.1275 2022/11/02 16:48:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:48:59 - mmengine - INFO - Epoch(train) [432][5/63] lr: 1.4487e-03 eta: 7:54:22 time: 0.9278 data_time: 0.2904 memory: 14901 loss: 1.7266 loss_prob: 1.0071 loss_thr: 0.5587 loss_db: 0.1608 2022/11/02 16:49:02 - mmengine - INFO - Epoch(train) [432][10/63] lr: 1.4487e-03 eta: 7:54:18 time: 0.9737 data_time: 0.2873 memory: 14901 loss: 1.7766 loss_prob: 1.0357 loss_thr: 0.5810 loss_db: 0.1600 2022/11/02 16:49:06 - mmengine - INFO - Epoch(train) [432][15/63] lr: 1.4487e-03 eta: 7:54:18 time: 0.6662 data_time: 0.0345 memory: 14901 loss: 1.6666 loss_prob: 0.9435 loss_thr: 0.5694 loss_db: 0.1537 2022/11/02 16:49:08 - mmengine - INFO - Epoch(train) [432][20/63] lr: 1.4487e-03 eta: 7:54:13 time: 0.6258 data_time: 0.0353 memory: 14901 loss: 1.6814 loss_prob: 0.9711 loss_thr: 0.5476 loss_db: 0.1627 2022/11/02 16:49:12 - mmengine - INFO - Epoch(train) [432][25/63] lr: 1.4487e-03 eta: 7:54:13 time: 0.6740 data_time: 0.0138 memory: 14901 loss: 1.7003 loss_prob: 1.0064 loss_thr: 0.5308 loss_db: 0.1631 2022/11/02 16:49:15 - mmengine - INFO - Epoch(train) [432][30/63] lr: 1.4487e-03 eta: 7:54:09 time: 0.6879 data_time: 0.0223 memory: 14901 loss: 1.6659 loss_prob: 0.9746 loss_thr: 0.5356 loss_db: 0.1557 2022/11/02 16:49:18 - mmengine - INFO - Epoch(train) [432][35/63] lr: 1.4487e-03 eta: 7:54:09 time: 0.5998 data_time: 0.0223 memory: 14901 loss: 1.6261 loss_prob: 0.9119 loss_thr: 0.5600 loss_db: 0.1542 2022/11/02 16:49:21 - mmengine - INFO - Epoch(train) [432][40/63] lr: 1.4487e-03 eta: 7:54:03 time: 0.5951 data_time: 0.0263 memory: 14901 loss: 1.6175 loss_prob: 0.9015 loss_thr: 0.5600 loss_db: 0.1560 2022/11/02 16:49:24 - mmengine - INFO - Epoch(train) [432][45/63] lr: 1.4487e-03 eta: 7:54:03 time: 0.5606 data_time: 0.0221 memory: 14901 loss: 1.4837 loss_prob: 0.8275 loss_thr: 0.5196 loss_db: 0.1367 2022/11/02 16:49:27 - mmengine - INFO - Epoch(train) [432][50/63] lr: 1.4487e-03 eta: 7:53:56 time: 0.5564 data_time: 0.0190 memory: 14901 loss: 1.4444 loss_prob: 0.7910 loss_thr: 0.5228 loss_db: 0.1307 2022/11/02 16:49:29 - mmengine - INFO - Epoch(train) [432][55/63] lr: 1.4487e-03 eta: 7:53:56 time: 0.5429 data_time: 0.0210 memory: 14901 loss: 1.4021 loss_prob: 0.7495 loss_thr: 0.5253 loss_db: 0.1272 2022/11/02 16:49:32 - mmengine - INFO - Epoch(train) [432][60/63] lr: 1.4487e-03 eta: 7:53:50 time: 0.5579 data_time: 0.0143 memory: 14901 loss: 1.3862 loss_prob: 0.7537 loss_thr: 0.5070 loss_db: 0.1255 2022/11/02 16:49:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:49:39 - mmengine - INFO - Epoch(train) [433][5/63] lr: 1.4470e-03 eta: 7:53:50 time: 0.8455 data_time: 0.2695 memory: 14901 loss: 1.4721 loss_prob: 0.8031 loss_thr: 0.5385 loss_db: 0.1305 2022/11/02 16:49:43 - mmengine - INFO - Epoch(train) [433][10/63] lr: 1.4470e-03 eta: 7:53:44 time: 0.8711 data_time: 0.2685 memory: 14901 loss: 1.4519 loss_prob: 0.7920 loss_thr: 0.5257 loss_db: 0.1343 2022/11/02 16:49:45 - mmengine - INFO - Epoch(train) [433][15/63] lr: 1.4470e-03 eta: 7:53:44 time: 0.5923 data_time: 0.0128 memory: 14901 loss: 1.4693 loss_prob: 0.8076 loss_thr: 0.5231 loss_db: 0.1386 2022/11/02 16:49:48 - mmengine - INFO - Epoch(train) [433][20/63] lr: 1.4470e-03 eta: 7:53:37 time: 0.5331 data_time: 0.0115 memory: 14901 loss: 1.6086 loss_prob: 0.9072 loss_thr: 0.5478 loss_db: 0.1536 2022/11/02 16:49:51 - mmengine - INFO - Epoch(train) [433][25/63] lr: 1.4470e-03 eta: 7:53:37 time: 0.5486 data_time: 0.0130 memory: 14901 loss: 1.5819 loss_prob: 0.8937 loss_thr: 0.5391 loss_db: 0.1492 2022/11/02 16:49:54 - mmengine - INFO - Epoch(train) [433][30/63] lr: 1.4470e-03 eta: 7:53:32 time: 0.6069 data_time: 0.0345 memory: 14901 loss: 1.4563 loss_prob: 0.7973 loss_thr: 0.5259 loss_db: 0.1331 2022/11/02 16:49:57 - mmengine - INFO - Epoch(train) [433][35/63] lr: 1.4470e-03 eta: 7:53:32 time: 0.5731 data_time: 0.0331 memory: 14901 loss: 1.4826 loss_prob: 0.8220 loss_thr: 0.5230 loss_db: 0.1376 2022/11/02 16:49:59 - mmengine - INFO - Epoch(train) [433][40/63] lr: 1.4470e-03 eta: 7:53:25 time: 0.5377 data_time: 0.0104 memory: 14901 loss: 1.5690 loss_prob: 0.8819 loss_thr: 0.5412 loss_db: 0.1459 2022/11/02 16:50:02 - mmengine - INFO - Epoch(train) [433][45/63] lr: 1.4470e-03 eta: 7:53:25 time: 0.5139 data_time: 0.0070 memory: 14901 loss: 1.4847 loss_prob: 0.8180 loss_thr: 0.5309 loss_db: 0.1358 2022/11/02 16:50:05 - mmengine - INFO - Epoch(train) [433][50/63] lr: 1.4470e-03 eta: 7:53:18 time: 0.5249 data_time: 0.0065 memory: 14901 loss: 1.3982 loss_prob: 0.7600 loss_thr: 0.5090 loss_db: 0.1293 2022/11/02 16:50:07 - mmengine - INFO - Epoch(train) [433][55/63] lr: 1.4470e-03 eta: 7:53:18 time: 0.5682 data_time: 0.0216 memory: 14901 loss: 1.3393 loss_prob: 0.7222 loss_thr: 0.4912 loss_db: 0.1259 2022/11/02 16:50:10 - mmengine - INFO - Epoch(train) [433][60/63] lr: 1.4470e-03 eta: 7:53:11 time: 0.5304 data_time: 0.0214 memory: 14901 loss: 1.3150 loss_prob: 0.7094 loss_thr: 0.4842 loss_db: 0.1214 2022/11/02 16:50:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:50:17 - mmengine - INFO - Epoch(train) [434][5/63] lr: 1.4453e-03 eta: 7:53:11 time: 0.7701 data_time: 0.2353 memory: 14901 loss: 1.3708 loss_prob: 0.7375 loss_thr: 0.5087 loss_db: 0.1245 2022/11/02 16:50:20 - mmengine - INFO - Epoch(train) [434][10/63] lr: 1.4453e-03 eta: 7:53:04 time: 0.8018 data_time: 0.2414 memory: 14901 loss: 1.3805 loss_prob: 0.7486 loss_thr: 0.5027 loss_db: 0.1292 2022/11/02 16:50:22 - mmengine - INFO - Epoch(train) [434][15/63] lr: 1.4453e-03 eta: 7:53:04 time: 0.5487 data_time: 0.0244 memory: 14901 loss: 1.3699 loss_prob: 0.7467 loss_thr: 0.4961 loss_db: 0.1271 2022/11/02 16:50:25 - mmengine - INFO - Epoch(train) [434][20/63] lr: 1.4453e-03 eta: 7:52:58 time: 0.5369 data_time: 0.0143 memory: 14901 loss: 1.3568 loss_prob: 0.7368 loss_thr: 0.4962 loss_db: 0.1237 2022/11/02 16:50:28 - mmengine - INFO - Epoch(train) [434][25/63] lr: 1.4453e-03 eta: 7:52:58 time: 0.5448 data_time: 0.0295 memory: 14901 loss: 1.4949 loss_prob: 0.8359 loss_thr: 0.5240 loss_db: 0.1350 2022/11/02 16:50:30 - mmengine - INFO - Epoch(train) [434][30/63] lr: 1.4453e-03 eta: 7:52:51 time: 0.5511 data_time: 0.0432 memory: 14901 loss: 1.4507 loss_prob: 0.8069 loss_thr: 0.5118 loss_db: 0.1320 2022/11/02 16:50:33 - mmengine - INFO - Epoch(train) [434][35/63] lr: 1.4453e-03 eta: 7:52:51 time: 0.5881 data_time: 0.0229 memory: 14901 loss: 1.2977 loss_prob: 0.6975 loss_thr: 0.4808 loss_db: 0.1194 2022/11/02 16:50:36 - mmengine - INFO - Epoch(train) [434][40/63] lr: 1.4453e-03 eta: 7:52:45 time: 0.5619 data_time: 0.0138 memory: 14901 loss: 1.3290 loss_prob: 0.7214 loss_thr: 0.4872 loss_db: 0.1204 2022/11/02 16:50:39 - mmengine - INFO - Epoch(train) [434][45/63] lr: 1.4453e-03 eta: 7:52:45 time: 0.5156 data_time: 0.0116 memory: 14901 loss: 1.3574 loss_prob: 0.7291 loss_thr: 0.5063 loss_db: 0.1221 2022/11/02 16:50:42 - mmengine - INFO - Epoch(train) [434][50/63] lr: 1.4453e-03 eta: 7:52:39 time: 0.5909 data_time: 0.0301 memory: 14901 loss: 1.3273 loss_prob: 0.6956 loss_thr: 0.5115 loss_db: 0.1202 2022/11/02 16:50:45 - mmengine - INFO - Epoch(train) [434][55/63] lr: 1.4453e-03 eta: 7:52:39 time: 0.6327 data_time: 0.0348 memory: 14901 loss: 1.3394 loss_prob: 0.7111 loss_thr: 0.5071 loss_db: 0.1212 2022/11/02 16:50:48 - mmengine - INFO - Epoch(train) [434][60/63] lr: 1.4453e-03 eta: 7:52:33 time: 0.5581 data_time: 0.0130 memory: 14901 loss: 1.4262 loss_prob: 0.7968 loss_thr: 0.4982 loss_db: 0.1312 2022/11/02 16:50:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:50:56 - mmengine - INFO - Epoch(train) [435][5/63] lr: 1.4436e-03 eta: 7:52:33 time: 0.9242 data_time: 0.3833 memory: 14901 loss: 1.4790 loss_prob: 0.8181 loss_thr: 0.5267 loss_db: 0.1342 2022/11/02 16:50:58 - mmengine - INFO - Epoch(train) [435][10/63] lr: 1.4436e-03 eta: 7:52:28 time: 0.9165 data_time: 0.3808 memory: 14901 loss: 1.4167 loss_prob: 0.7564 loss_thr: 0.5280 loss_db: 0.1323 2022/11/02 16:51:01 - mmengine - INFO - Epoch(train) [435][15/63] lr: 1.4436e-03 eta: 7:52:28 time: 0.5671 data_time: 0.0087 memory: 14901 loss: 1.4003 loss_prob: 0.7584 loss_thr: 0.5095 loss_db: 0.1324 2022/11/02 16:51:04 - mmengine - INFO - Epoch(train) [435][20/63] lr: 1.4436e-03 eta: 7:52:21 time: 0.5553 data_time: 0.0124 memory: 14901 loss: 1.3579 loss_prob: 0.7407 loss_thr: 0.4920 loss_db: 0.1253 2022/11/02 16:51:07 - mmengine - INFO - Epoch(train) [435][25/63] lr: 1.4436e-03 eta: 7:52:21 time: 0.5331 data_time: 0.0285 memory: 14901 loss: 1.4661 loss_prob: 0.8323 loss_thr: 0.5012 loss_db: 0.1325 2022/11/02 16:51:09 - mmengine - INFO - Epoch(train) [435][30/63] lr: 1.4436e-03 eta: 7:52:14 time: 0.5430 data_time: 0.0224 memory: 14901 loss: 1.3837 loss_prob: 0.7763 loss_thr: 0.4822 loss_db: 0.1252 2022/11/02 16:51:12 - mmengine - INFO - Epoch(train) [435][35/63] lr: 1.4436e-03 eta: 7:52:14 time: 0.5276 data_time: 0.0067 memory: 14901 loss: 1.2915 loss_prob: 0.6878 loss_thr: 0.4862 loss_db: 0.1175 2022/11/02 16:51:17 - mmengine - INFO - Epoch(train) [435][40/63] lr: 1.4436e-03 eta: 7:52:11 time: 0.7480 data_time: 0.0071 memory: 14901 loss: 1.3853 loss_prob: 0.7317 loss_thr: 0.5272 loss_db: 0.1264 2022/11/02 16:51:20 - mmengine - INFO - Epoch(train) [435][45/63] lr: 1.4436e-03 eta: 7:52:11 time: 0.8189 data_time: 0.0083 memory: 14901 loss: 1.3483 loss_prob: 0.7163 loss_thr: 0.5101 loss_db: 0.1218 2022/11/02 16:51:23 - mmengine - INFO - Epoch(train) [435][50/63] lr: 1.4436e-03 eta: 7:52:06 time: 0.6275 data_time: 0.0315 memory: 14901 loss: 1.4003 loss_prob: 0.7641 loss_thr: 0.5075 loss_db: 0.1287 2022/11/02 16:51:26 - mmengine - INFO - Epoch(train) [435][55/63] lr: 1.4436e-03 eta: 7:52:06 time: 0.5748 data_time: 0.0311 memory: 14901 loss: 1.4146 loss_prob: 0.7714 loss_thr: 0.5117 loss_db: 0.1315 2022/11/02 16:51:28 - mmengine - INFO - Epoch(train) [435][60/63] lr: 1.4436e-03 eta: 7:52:00 time: 0.5449 data_time: 0.0084 memory: 14901 loss: 1.3682 loss_prob: 0.7435 loss_thr: 0.4998 loss_db: 0.1249 2022/11/02 16:51:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:51:36 - mmengine - INFO - Epoch(train) [436][5/63] lr: 1.4419e-03 eta: 7:52:00 time: 0.8804 data_time: 0.3715 memory: 14901 loss: 1.5389 loss_prob: 0.8549 loss_thr: 0.5391 loss_db: 0.1450 2022/11/02 16:51:39 - mmengine - INFO - Epoch(train) [436][10/63] lr: 1.4419e-03 eta: 7:51:55 time: 0.9372 data_time: 0.3722 memory: 14901 loss: 1.4423 loss_prob: 0.7828 loss_thr: 0.5226 loss_db: 0.1370 2022/11/02 16:51:42 - mmengine - INFO - Epoch(train) [436][15/63] lr: 1.4419e-03 eta: 7:51:55 time: 0.6136 data_time: 0.0107 memory: 14901 loss: 1.3648 loss_prob: 0.7530 loss_thr: 0.4867 loss_db: 0.1252 2022/11/02 16:51:45 - mmengine - INFO - Epoch(train) [436][20/63] lr: 1.4419e-03 eta: 7:51:49 time: 0.5767 data_time: 0.0124 memory: 14901 loss: 1.4102 loss_prob: 0.7761 loss_thr: 0.5041 loss_db: 0.1300 2022/11/02 16:51:48 - mmengine - INFO - Epoch(train) [436][25/63] lr: 1.4419e-03 eta: 7:51:49 time: 0.5363 data_time: 0.0262 memory: 14901 loss: 1.4571 loss_prob: 0.7921 loss_thr: 0.5299 loss_db: 0.1351 2022/11/02 16:51:50 - mmengine - INFO - Epoch(train) [436][30/63] lr: 1.4419e-03 eta: 7:51:42 time: 0.5475 data_time: 0.0234 memory: 14901 loss: 1.3898 loss_prob: 0.7545 loss_thr: 0.5095 loss_db: 0.1259 2022/11/02 16:51:53 - mmengine - INFO - Epoch(train) [436][35/63] lr: 1.4419e-03 eta: 7:51:42 time: 0.5565 data_time: 0.0123 memory: 14901 loss: 1.3739 loss_prob: 0.7473 loss_thr: 0.5003 loss_db: 0.1263 2022/11/02 16:51:56 - mmengine - INFO - Epoch(train) [436][40/63] lr: 1.4419e-03 eta: 7:51:35 time: 0.5212 data_time: 0.0098 memory: 14901 loss: 1.4263 loss_prob: 0.7877 loss_thr: 0.5043 loss_db: 0.1343 2022/11/02 16:51:58 - mmengine - INFO - Epoch(train) [436][45/63] lr: 1.4419e-03 eta: 7:51:35 time: 0.4842 data_time: 0.0055 memory: 14901 loss: 1.4144 loss_prob: 0.7838 loss_thr: 0.4990 loss_db: 0.1317 2022/11/02 16:52:02 - mmengine - INFO - Epoch(train) [436][50/63] lr: 1.4419e-03 eta: 7:51:30 time: 0.6404 data_time: 0.0341 memory: 14901 loss: 1.4099 loss_prob: 0.7661 loss_thr: 0.5147 loss_db: 0.1292 2022/11/02 16:52:05 - mmengine - INFO - Epoch(train) [436][55/63] lr: 1.4419e-03 eta: 7:51:30 time: 0.6858 data_time: 0.0344 memory: 14901 loss: 1.4650 loss_prob: 0.8106 loss_thr: 0.5208 loss_db: 0.1336 2022/11/02 16:52:08 - mmengine - INFO - Epoch(train) [436][60/63] lr: 1.4419e-03 eta: 7:51:24 time: 0.5538 data_time: 0.0068 memory: 14901 loss: 1.3782 loss_prob: 0.7585 loss_thr: 0.4961 loss_db: 0.1236 2022/11/02 16:52:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:52:14 - mmengine - INFO - Epoch(train) [437][5/63] lr: 1.4402e-03 eta: 7:51:24 time: 0.7853 data_time: 0.2411 memory: 14901 loss: 1.4210 loss_prob: 0.7872 loss_thr: 0.5013 loss_db: 0.1325 2022/11/02 16:52:17 - mmengine - INFO - Epoch(train) [437][10/63] lr: 1.4402e-03 eta: 7:51:17 time: 0.7894 data_time: 0.2491 memory: 14901 loss: 1.4452 loss_prob: 0.8053 loss_thr: 0.5077 loss_db: 0.1322 2022/11/02 16:52:20 - mmengine - INFO - Epoch(train) [437][15/63] lr: 1.4402e-03 eta: 7:51:17 time: 0.5515 data_time: 0.0168 memory: 14901 loss: 1.3973 loss_prob: 0.7712 loss_thr: 0.4989 loss_db: 0.1272 2022/11/02 16:52:23 - mmengine - INFO - Epoch(train) [437][20/63] lr: 1.4402e-03 eta: 7:51:11 time: 0.6119 data_time: 0.0406 memory: 14901 loss: 1.4944 loss_prob: 0.8333 loss_thr: 0.5228 loss_db: 0.1383 2022/11/02 16:52:26 - mmengine - INFO - Epoch(train) [437][25/63] lr: 1.4402e-03 eta: 7:51:11 time: 0.5877 data_time: 0.0400 memory: 14901 loss: 1.4481 loss_prob: 0.7978 loss_thr: 0.5160 loss_db: 0.1344 2022/11/02 16:52:28 - mmengine - INFO - Epoch(train) [437][30/63] lr: 1.4402e-03 eta: 7:51:05 time: 0.5489 data_time: 0.0078 memory: 14901 loss: 1.4164 loss_prob: 0.7778 loss_thr: 0.5073 loss_db: 0.1313 2022/11/02 16:52:31 - mmengine - INFO - Epoch(train) [437][35/63] lr: 1.4402e-03 eta: 7:51:05 time: 0.5192 data_time: 0.0125 memory: 14901 loss: 1.4196 loss_prob: 0.7850 loss_thr: 0.5043 loss_db: 0.1303 2022/11/02 16:52:34 - mmengine - INFO - Epoch(train) [437][40/63] lr: 1.4402e-03 eta: 7:50:59 time: 0.5855 data_time: 0.0330 memory: 14901 loss: 1.3553 loss_prob: 0.7401 loss_thr: 0.4909 loss_db: 0.1243 2022/11/02 16:52:37 - mmengine - INFO - Epoch(train) [437][45/63] lr: 1.4402e-03 eta: 7:50:59 time: 0.5840 data_time: 0.0302 memory: 14901 loss: 1.4148 loss_prob: 0.7714 loss_thr: 0.5122 loss_db: 0.1312 2022/11/02 16:52:39 - mmengine - INFO - Epoch(train) [437][50/63] lr: 1.4402e-03 eta: 7:50:52 time: 0.5160 data_time: 0.0085 memory: 14901 loss: 1.4548 loss_prob: 0.8002 loss_thr: 0.5190 loss_db: 0.1355 2022/11/02 16:52:43 - mmengine - INFO - Epoch(train) [437][55/63] lr: 1.4402e-03 eta: 7:50:52 time: 0.5985 data_time: 0.0096 memory: 14901 loss: 1.4036 loss_prob: 0.7644 loss_thr: 0.5089 loss_db: 0.1304 2022/11/02 16:52:45 - mmengine - INFO - Epoch(train) [437][60/63] lr: 1.4402e-03 eta: 7:50:46 time: 0.5849 data_time: 0.0117 memory: 14901 loss: 1.3018 loss_prob: 0.6975 loss_thr: 0.4843 loss_db: 0.1199 2022/11/02 16:52:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:52:53 - mmengine - INFO - Epoch(train) [438][5/63] lr: 1.4385e-03 eta: 7:50:46 time: 0.9146 data_time: 0.2680 memory: 14901 loss: 1.3297 loss_prob: 0.7167 loss_thr: 0.4911 loss_db: 0.1219 2022/11/02 16:52:56 - mmengine - INFO - Epoch(train) [438][10/63] lr: 1.4385e-03 eta: 7:50:40 time: 0.8758 data_time: 0.2653 memory: 14901 loss: 1.3077 loss_prob: 0.7047 loss_thr: 0.4822 loss_db: 0.1208 2022/11/02 16:52:59 - mmengine - INFO - Epoch(train) [438][15/63] lr: 1.4385e-03 eta: 7:50:40 time: 0.5590 data_time: 0.0094 memory: 14901 loss: 1.3666 loss_prob: 0.7421 loss_thr: 0.4996 loss_db: 0.1249 2022/11/02 16:53:01 - mmengine - INFO - Epoch(train) [438][20/63] lr: 1.4385e-03 eta: 7:50:33 time: 0.5420 data_time: 0.0110 memory: 14901 loss: 1.3993 loss_prob: 0.7656 loss_thr: 0.5059 loss_db: 0.1278 2022/11/02 16:53:04 - mmengine - INFO - Epoch(train) [438][25/63] lr: 1.4385e-03 eta: 7:50:33 time: 0.5419 data_time: 0.0298 memory: 14901 loss: 1.3646 loss_prob: 0.7482 loss_thr: 0.4913 loss_db: 0.1251 2022/11/02 16:53:07 - mmengine - INFO - Epoch(train) [438][30/63] lr: 1.4385e-03 eta: 7:50:27 time: 0.5599 data_time: 0.0420 memory: 14901 loss: 1.3866 loss_prob: 0.7541 loss_thr: 0.5057 loss_db: 0.1267 2022/11/02 16:53:10 - mmengine - INFO - Epoch(train) [438][35/63] lr: 1.4385e-03 eta: 7:50:27 time: 0.5214 data_time: 0.0206 memory: 14901 loss: 1.4154 loss_prob: 0.7637 loss_thr: 0.5205 loss_db: 0.1312 2022/11/02 16:53:12 - mmengine - INFO - Epoch(train) [438][40/63] lr: 1.4385e-03 eta: 7:50:20 time: 0.5372 data_time: 0.0096 memory: 14901 loss: 1.3873 loss_prob: 0.7557 loss_thr: 0.5032 loss_db: 0.1284 2022/11/02 16:53:15 - mmengine - INFO - Epoch(train) [438][45/63] lr: 1.4385e-03 eta: 7:50:20 time: 0.5141 data_time: 0.0117 memory: 14901 loss: 1.3642 loss_prob: 0.7456 loss_thr: 0.4925 loss_db: 0.1261 2022/11/02 16:53:17 - mmengine - INFO - Epoch(train) [438][50/63] lr: 1.4385e-03 eta: 7:50:13 time: 0.4952 data_time: 0.0210 memory: 14901 loss: 1.3351 loss_prob: 0.7155 loss_thr: 0.4971 loss_db: 0.1226 2022/11/02 16:53:20 - mmengine - INFO - Epoch(train) [438][55/63] lr: 1.4385e-03 eta: 7:50:13 time: 0.5258 data_time: 0.0259 memory: 14901 loss: 1.2755 loss_prob: 0.6695 loss_thr: 0.4924 loss_db: 0.1135 2022/11/02 16:53:23 - mmengine - INFO - Epoch(train) [438][60/63] lr: 1.4385e-03 eta: 7:50:06 time: 0.5406 data_time: 0.0132 memory: 14901 loss: 1.3799 loss_prob: 0.7405 loss_thr: 0.5134 loss_db: 0.1260 2022/11/02 16:53:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:53:31 - mmengine - INFO - Epoch(train) [439][5/63] lr: 1.4368e-03 eta: 7:50:06 time: 0.9608 data_time: 0.2661 memory: 14901 loss: 1.3051 loss_prob: 0.7019 loss_thr: 0.4863 loss_db: 0.1168 2022/11/02 16:53:35 - mmengine - INFO - Epoch(train) [439][10/63] lr: 1.4368e-03 eta: 7:50:03 time: 1.0277 data_time: 0.2729 memory: 14901 loss: 1.2635 loss_prob: 0.6755 loss_thr: 0.4744 loss_db: 0.1135 2022/11/02 16:53:37 - mmengine - INFO - Epoch(train) [439][15/63] lr: 1.4368e-03 eta: 7:50:03 time: 0.6145 data_time: 0.0145 memory: 14901 loss: 1.4456 loss_prob: 0.7985 loss_thr: 0.5133 loss_db: 0.1338 2022/11/02 16:53:40 - mmengine - INFO - Epoch(train) [439][20/63] lr: 1.4368e-03 eta: 7:49:56 time: 0.5262 data_time: 0.0075 memory: 14901 loss: 1.4791 loss_prob: 0.8198 loss_thr: 0.5238 loss_db: 0.1355 2022/11/02 16:53:43 - mmengine - INFO - Epoch(train) [439][25/63] lr: 1.4368e-03 eta: 7:49:56 time: 0.5280 data_time: 0.0254 memory: 14901 loss: 1.3527 loss_prob: 0.7394 loss_thr: 0.4906 loss_db: 0.1228 2022/11/02 16:53:46 - mmengine - INFO - Epoch(train) [439][30/63] lr: 1.4368e-03 eta: 7:49:50 time: 0.5790 data_time: 0.0425 memory: 14901 loss: 1.3405 loss_prob: 0.7265 loss_thr: 0.4904 loss_db: 0.1236 2022/11/02 16:53:48 - mmengine - INFO - Epoch(train) [439][35/63] lr: 1.4368e-03 eta: 7:49:50 time: 0.5773 data_time: 0.0287 memory: 14901 loss: 1.4855 loss_prob: 0.8289 loss_thr: 0.5120 loss_db: 0.1446 2022/11/02 16:53:51 - mmengine - INFO - Epoch(train) [439][40/63] lr: 1.4368e-03 eta: 7:49:43 time: 0.4999 data_time: 0.0122 memory: 14901 loss: 1.6168 loss_prob: 0.9376 loss_thr: 0.5270 loss_db: 0.1522 2022/11/02 16:53:54 - mmengine - INFO - Epoch(train) [439][45/63] lr: 1.4368e-03 eta: 7:49:43 time: 0.5264 data_time: 0.0131 memory: 14901 loss: 1.5126 loss_prob: 0.8566 loss_thr: 0.5185 loss_db: 0.1375 2022/11/02 16:53:56 - mmengine - INFO - Epoch(train) [439][50/63] lr: 1.4368e-03 eta: 7:49:37 time: 0.5773 data_time: 0.0272 memory: 14901 loss: 1.4851 loss_prob: 0.8390 loss_thr: 0.5045 loss_db: 0.1416 2022/11/02 16:53:59 - mmengine - INFO - Epoch(train) [439][55/63] lr: 1.4368e-03 eta: 7:49:37 time: 0.5413 data_time: 0.0221 memory: 14901 loss: 1.5558 loss_prob: 0.8938 loss_thr: 0.5132 loss_db: 0.1488 2022/11/02 16:54:02 - mmengine - INFO - Epoch(train) [439][60/63] lr: 1.4368e-03 eta: 7:49:30 time: 0.5450 data_time: 0.0114 memory: 14901 loss: 1.4734 loss_prob: 0.8296 loss_thr: 0.5046 loss_db: 0.1392 2022/11/02 16:54:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:54:09 - mmengine - INFO - Epoch(train) [440][5/63] lr: 1.4351e-03 eta: 7:49:30 time: 0.7927 data_time: 0.2677 memory: 14901 loss: 1.4614 loss_prob: 0.8146 loss_thr: 0.5101 loss_db: 0.1366 2022/11/02 16:54:11 - mmengine - INFO - Epoch(train) [440][10/63] lr: 1.4351e-03 eta: 7:49:23 time: 0.7841 data_time: 0.2669 memory: 14901 loss: 1.5309 loss_prob: 0.8494 loss_thr: 0.5389 loss_db: 0.1426 2022/11/02 16:54:13 - mmengine - INFO - Epoch(train) [440][15/63] lr: 1.4351e-03 eta: 7:49:23 time: 0.4811 data_time: 0.0051 memory: 14901 loss: 1.6761 loss_prob: 0.9506 loss_thr: 0.5694 loss_db: 0.1561 2022/11/02 16:54:16 - mmengine - INFO - Epoch(train) [440][20/63] lr: 1.4351e-03 eta: 7:49:16 time: 0.5104 data_time: 0.0088 memory: 14901 loss: 1.6588 loss_prob: 0.9746 loss_thr: 0.5268 loss_db: 0.1574 2022/11/02 16:54:19 - mmengine - INFO - Epoch(train) [440][25/63] lr: 1.4351e-03 eta: 7:49:16 time: 0.5399 data_time: 0.0348 memory: 14901 loss: 1.5130 loss_prob: 0.8723 loss_thr: 0.4969 loss_db: 0.1439 2022/11/02 16:54:21 - mmengine - INFO - Epoch(train) [440][30/63] lr: 1.4351e-03 eta: 7:49:09 time: 0.5272 data_time: 0.0340 memory: 14901 loss: 1.5105 loss_prob: 0.8500 loss_thr: 0.5207 loss_db: 0.1398 2022/11/02 16:54:24 - mmengine - INFO - Epoch(train) [440][35/63] lr: 1.4351e-03 eta: 7:49:09 time: 0.5085 data_time: 0.0109 memory: 14901 loss: 1.7133 loss_prob: 0.9910 loss_thr: 0.5567 loss_db: 0.1657 2022/11/02 16:54:27 - mmengine - INFO - Epoch(train) [440][40/63] lr: 1.4351e-03 eta: 7:49:02 time: 0.5451 data_time: 0.0127 memory: 14901 loss: 1.6773 loss_prob: 0.9481 loss_thr: 0.5684 loss_db: 0.1608 2022/11/02 16:54:29 - mmengine - INFO - Epoch(train) [440][45/63] lr: 1.4351e-03 eta: 7:49:02 time: 0.5458 data_time: 0.0097 memory: 14901 loss: 1.5080 loss_prob: 0.8264 loss_thr: 0.5427 loss_db: 0.1389 2022/11/02 16:54:32 - mmengine - INFO - Epoch(train) [440][50/63] lr: 1.4351e-03 eta: 7:48:55 time: 0.5330 data_time: 0.0207 memory: 14901 loss: 1.8623 loss_prob: 1.1359 loss_thr: 0.5606 loss_db: 0.1658 2022/11/02 16:54:35 - mmengine - INFO - Epoch(train) [440][55/63] lr: 1.4351e-03 eta: 7:48:55 time: 0.5433 data_time: 0.0276 memory: 14901 loss: 1.9185 loss_prob: 1.1803 loss_thr: 0.5629 loss_db: 0.1752 2022/11/02 16:54:37 - mmengine - INFO - Epoch(train) [440][60/63] lr: 1.4351e-03 eta: 7:48:48 time: 0.5221 data_time: 0.0156 memory: 14901 loss: 1.5814 loss_prob: 0.8925 loss_thr: 0.5386 loss_db: 0.1503 2022/11/02 16:54:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:54:39 - mmengine - INFO - Saving checkpoint at 440 epochs 2022/11/02 16:54:44 - mmengine - INFO - Epoch(val) [440][5/500] eta: 7:48:48 time: 0.0465 data_time: 0.0053 memory: 14901 2022/11/02 16:54:44 - mmengine - INFO - Epoch(val) [440][10/500] eta: 0:00:23 time: 0.0482 data_time: 0.0050 memory: 1008 2022/11/02 16:54:44 - mmengine - INFO - Epoch(val) [440][15/500] eta: 0:00:23 time: 0.0400 data_time: 0.0022 memory: 1008 2022/11/02 16:54:44 - mmengine - INFO - Epoch(val) [440][20/500] eta: 0:00:19 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 16:54:44 - mmengine - INFO - Epoch(val) [440][25/500] eta: 0:00:19 time: 0.0405 data_time: 0.0033 memory: 1008 2022/11/02 16:54:45 - mmengine - INFO - Epoch(val) [440][30/500] eta: 0:00:20 time: 0.0432 data_time: 0.0039 memory: 1008 2022/11/02 16:54:45 - mmengine - INFO - Epoch(val) [440][35/500] eta: 0:00:20 time: 0.0429 data_time: 0.0035 memory: 1008 2022/11/02 16:54:45 - mmengine - INFO - Epoch(val) [440][40/500] eta: 0:00:20 time: 0.0447 data_time: 0.0031 memory: 1008 2022/11/02 16:54:45 - mmengine - INFO - Epoch(val) [440][45/500] eta: 0:00:20 time: 0.0449 data_time: 0.0030 memory: 1008 2022/11/02 16:54:46 - mmengine - INFO - Epoch(val) [440][50/500] eta: 0:00:17 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 16:54:46 - mmengine - INFO - Epoch(val) [440][55/500] eta: 0:00:17 time: 0.0416 data_time: 0.0026 memory: 1008 2022/11/02 16:54:46 - mmengine - INFO - Epoch(val) [440][60/500] eta: 0:00:18 time: 0.0431 data_time: 0.0031 memory: 1008 2022/11/02 16:54:46 - mmengine - INFO - Epoch(val) [440][65/500] eta: 0:00:18 time: 0.0480 data_time: 0.0034 memory: 1008 2022/11/02 16:54:46 - mmengine - INFO - Epoch(val) [440][70/500] eta: 0:00:21 time: 0.0507 data_time: 0.0033 memory: 1008 2022/11/02 16:54:47 - mmengine - INFO - Epoch(val) [440][75/500] eta: 0:00:21 time: 0.0475 data_time: 0.0039 memory: 1008 2022/11/02 16:54:48 - mmengine - INFO - Epoch(val) [440][80/500] eta: 0:00:46 time: 0.1109 data_time: 0.0698 memory: 1008 2022/11/02 16:54:48 - mmengine - INFO - Epoch(val) [440][85/500] eta: 0:00:46 time: 0.1135 data_time: 0.0706 memory: 1008 2022/11/02 16:54:48 - mmengine - INFO - Epoch(val) [440][90/500] eta: 0:00:19 time: 0.0468 data_time: 0.0044 memory: 1008 2022/11/02 16:54:48 - mmengine - INFO - Epoch(val) [440][95/500] eta: 0:00:19 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 16:54:48 - mmengine - INFO - Epoch(val) [440][100/500] eta: 0:00:15 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 16:54:49 - mmengine - INFO - Epoch(val) [440][105/500] eta: 0:00:15 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 16:54:49 - mmengine - INFO - Epoch(val) [440][110/500] eta: 0:00:16 time: 0.0424 data_time: 0.0028 memory: 1008 2022/11/02 16:54:49 - mmengine - INFO - Epoch(val) [440][115/500] eta: 0:00:16 time: 0.0412 data_time: 0.0025 memory: 1008 2022/11/02 16:54:49 - mmengine - INFO - Epoch(val) [440][120/500] eta: 0:00:14 time: 0.0391 data_time: 0.0025 memory: 1008 2022/11/02 16:54:49 - mmengine - INFO - Epoch(val) [440][125/500] eta: 0:00:14 time: 0.0373 data_time: 0.0024 memory: 1008 2022/11/02 16:54:50 - mmengine - INFO - Epoch(val) [440][130/500] eta: 0:00:14 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 16:54:50 - mmengine - INFO - Epoch(val) [440][135/500] eta: 0:00:14 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/02 16:54:50 - mmengine - INFO - Epoch(val) [440][140/500] eta: 0:00:15 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 16:54:50 - mmengine - INFO - Epoch(val) [440][145/500] eta: 0:00:15 time: 0.0454 data_time: 0.0029 memory: 1008 2022/11/02 16:54:51 - mmengine - INFO - Epoch(val) [440][150/500] eta: 0:00:15 time: 0.0438 data_time: 0.0027 memory: 1008 2022/11/02 16:54:51 - mmengine - INFO - Epoch(val) [440][155/500] eta: 0:00:15 time: 0.0500 data_time: 0.0027 memory: 1008 2022/11/02 16:54:51 - mmengine - INFO - Epoch(val) [440][160/500] eta: 0:00:17 time: 0.0506 data_time: 0.0026 memory: 1008 2022/11/02 16:54:51 - mmengine - INFO - Epoch(val) [440][165/500] eta: 0:00:17 time: 0.0391 data_time: 0.0022 memory: 1008 2022/11/02 16:54:51 - mmengine - INFO - Epoch(val) [440][170/500] eta: 0:00:13 time: 0.0403 data_time: 0.0021 memory: 1008 2022/11/02 16:54:52 - mmengine - INFO - Epoch(val) [440][175/500] eta: 0:00:13 time: 0.0403 data_time: 0.0024 memory: 1008 2022/11/02 16:54:52 - mmengine - INFO - Epoch(val) [440][180/500] eta: 0:00:11 time: 0.0372 data_time: 0.0025 memory: 1008 2022/11/02 16:54:52 - mmengine - INFO - Epoch(val) [440][185/500] eta: 0:00:11 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 16:54:52 - mmengine - INFO - Epoch(val) [440][190/500] eta: 0:00:13 time: 0.0432 data_time: 0.0027 memory: 1008 2022/11/02 16:54:52 - mmengine - INFO - Epoch(val) [440][195/500] eta: 0:00:13 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 16:54:53 - mmengine - INFO - Epoch(val) [440][200/500] eta: 0:00:14 time: 0.0494 data_time: 0.0027 memory: 1008 2022/11/02 16:54:53 - mmengine - INFO - Epoch(val) [440][205/500] eta: 0:00:14 time: 0.0503 data_time: 0.0029 memory: 1008 2022/11/02 16:54:53 - mmengine - INFO - Epoch(val) [440][210/500] eta: 0:00:10 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/02 16:54:53 - mmengine - INFO - Epoch(val) [440][215/500] eta: 0:00:10 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 16:54:54 - mmengine - INFO - Epoch(val) [440][220/500] eta: 0:00:12 time: 0.0448 data_time: 0.0028 memory: 1008 2022/11/02 16:54:54 - mmengine - INFO - Epoch(val) [440][225/500] eta: 0:00:12 time: 0.0409 data_time: 0.0026 memory: 1008 2022/11/02 16:54:54 - mmengine - INFO - Epoch(val) [440][230/500] eta: 0:00:11 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 16:54:54 - mmengine - INFO - Epoch(val) [440][235/500] eta: 0:00:11 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 16:54:54 - mmengine - INFO - Epoch(val) [440][240/500] eta: 0:00:10 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/02 16:54:55 - mmengine - INFO - Epoch(val) [440][245/500] eta: 0:00:10 time: 0.0414 data_time: 0.0037 memory: 1008 2022/11/02 16:54:55 - mmengine - INFO - Epoch(val) [440][250/500] eta: 0:00:11 time: 0.0442 data_time: 0.0041 memory: 1008 2022/11/02 16:54:55 - mmengine - INFO - Epoch(val) [440][255/500] eta: 0:00:11 time: 0.0465 data_time: 0.0043 memory: 1008 2022/11/02 16:54:55 - mmengine - INFO - Epoch(val) [440][260/500] eta: 0:00:11 time: 0.0475 data_time: 0.0045 memory: 1008 2022/11/02 16:54:56 - mmengine - INFO - Epoch(val) [440][265/500] eta: 0:00:11 time: 0.0446 data_time: 0.0033 memory: 1008 2022/11/02 16:54:56 - mmengine - INFO - Epoch(val) [440][270/500] eta: 0:00:10 time: 0.0452 data_time: 0.0033 memory: 1008 2022/11/02 16:54:56 - mmengine - INFO - Epoch(val) [440][275/500] eta: 0:00:10 time: 0.0457 data_time: 0.0037 memory: 1008 2022/11/02 16:54:56 - mmengine - INFO - Epoch(val) [440][280/500] eta: 0:00:10 time: 0.0482 data_time: 0.0045 memory: 1008 2022/11/02 16:54:56 - mmengine - INFO - Epoch(val) [440][285/500] eta: 0:00:10 time: 0.0470 data_time: 0.0041 memory: 1008 2022/11/02 16:54:57 - mmengine - INFO - Epoch(val) [440][290/500] eta: 0:00:08 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 16:54:57 - mmengine - INFO - Epoch(val) [440][295/500] eta: 0:00:08 time: 0.0451 data_time: 0.0027 memory: 1008 2022/11/02 16:54:57 - mmengine - INFO - Epoch(val) [440][300/500] eta: 0:00:08 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/02 16:54:57 - mmengine - INFO - Epoch(val) [440][305/500] eta: 0:00:08 time: 0.0378 data_time: 0.0024 memory: 1008 2022/11/02 16:54:57 - mmengine - INFO - Epoch(val) [440][310/500] eta: 0:00:07 time: 0.0372 data_time: 0.0024 memory: 1008 2022/11/02 16:54:58 - mmengine - INFO - Epoch(val) [440][315/500] eta: 0:00:07 time: 0.0404 data_time: 0.0025 memory: 1008 2022/11/02 16:54:58 - mmengine - INFO - Epoch(val) [440][320/500] eta: 0:00:07 time: 0.0416 data_time: 0.0024 memory: 1008 2022/11/02 16:54:58 - mmengine - INFO - Epoch(val) [440][325/500] eta: 0:00:07 time: 0.0497 data_time: 0.0024 memory: 1008 2022/11/02 16:54:58 - mmengine - INFO - Epoch(val) [440][330/500] eta: 0:00:08 time: 0.0473 data_time: 0.0023 memory: 1008 2022/11/02 16:54:59 - mmengine - INFO - Epoch(val) [440][335/500] eta: 0:00:08 time: 0.0358 data_time: 0.0022 memory: 1008 2022/11/02 16:54:59 - mmengine - INFO - Epoch(val) [440][340/500] eta: 0:00:08 time: 0.0517 data_time: 0.0023 memory: 1008 2022/11/02 16:54:59 - mmengine - INFO - Epoch(val) [440][345/500] eta: 0:00:08 time: 0.0526 data_time: 0.0023 memory: 1008 2022/11/02 16:54:59 - mmengine - INFO - Epoch(val) [440][350/500] eta: 0:00:06 time: 0.0416 data_time: 0.0023 memory: 1008 2022/11/02 16:54:59 - mmengine - INFO - Epoch(val) [440][355/500] eta: 0:00:06 time: 0.0405 data_time: 0.0024 memory: 1008 2022/11/02 16:55:00 - mmengine - INFO - Epoch(val) [440][360/500] eta: 0:00:05 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 16:55:00 - mmengine - INFO - Epoch(val) [440][365/500] eta: 0:00:05 time: 0.0467 data_time: 0.0029 memory: 1008 2022/11/02 16:55:00 - mmengine - INFO - Epoch(val) [440][370/500] eta: 0:00:05 time: 0.0416 data_time: 0.0029 memory: 1008 2022/11/02 16:55:00 - mmengine - INFO - Epoch(val) [440][375/500] eta: 0:00:05 time: 0.0362 data_time: 0.0025 memory: 1008 2022/11/02 16:55:01 - mmengine - INFO - Epoch(val) [440][380/500] eta: 0:00:04 time: 0.0410 data_time: 0.0023 memory: 1008 2022/11/02 16:55:01 - mmengine - INFO - Epoch(val) [440][385/500] eta: 0:00:04 time: 0.0476 data_time: 0.0036 memory: 1008 2022/11/02 16:55:01 - mmengine - INFO - Epoch(val) [440][390/500] eta: 0:00:05 time: 0.0456 data_time: 0.0041 memory: 1008 2022/11/02 16:55:01 - mmengine - INFO - Epoch(val) [440][395/500] eta: 0:00:05 time: 0.0414 data_time: 0.0033 memory: 1008 2022/11/02 16:55:01 - mmengine - INFO - Epoch(val) [440][400/500] eta: 0:00:04 time: 0.0421 data_time: 0.0033 memory: 1008 2022/11/02 16:55:02 - mmengine - INFO - Epoch(val) [440][405/500] eta: 0:00:04 time: 0.0417 data_time: 0.0030 memory: 1008 2022/11/02 16:55:02 - mmengine - INFO - Epoch(val) [440][410/500] eta: 0:00:03 time: 0.0442 data_time: 0.0029 memory: 1008 2022/11/02 16:55:02 - mmengine - INFO - Epoch(val) [440][415/500] eta: 0:00:03 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/02 16:55:03 - mmengine - INFO - Epoch(val) [440][420/500] eta: 0:00:08 time: 0.1087 data_time: 0.0728 memory: 1008 2022/11/02 16:55:03 - mmengine - INFO - Epoch(val) [440][425/500] eta: 0:00:08 time: 0.1085 data_time: 0.0723 memory: 1008 2022/11/02 16:55:03 - mmengine - INFO - Epoch(val) [440][430/500] eta: 0:00:02 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 16:55:04 - mmengine - INFO - Epoch(val) [440][435/500] eta: 0:00:02 time: 0.0361 data_time: 0.0027 memory: 1008 2022/11/02 16:55:04 - mmengine - INFO - Epoch(val) [440][440/500] eta: 0:00:02 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 16:55:04 - mmengine - INFO - Epoch(val) [440][445/500] eta: 0:00:02 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 16:55:04 - mmengine - INFO - Epoch(val) [440][450/500] eta: 0:00:02 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/02 16:55:04 - mmengine - INFO - Epoch(val) [440][455/500] eta: 0:00:02 time: 0.0428 data_time: 0.0030 memory: 1008 2022/11/02 16:55:05 - mmengine - INFO - Epoch(val) [440][460/500] eta: 0:00:01 time: 0.0386 data_time: 0.0028 memory: 1008 2022/11/02 16:55:05 - mmengine - INFO - Epoch(val) [440][465/500] eta: 0:00:01 time: 0.0361 data_time: 0.0027 memory: 1008 2022/11/02 16:55:05 - mmengine - INFO - Epoch(val) [440][470/500] eta: 0:00:01 time: 0.0362 data_time: 0.0028 memory: 1008 2022/11/02 16:55:05 - mmengine - INFO - Epoch(val) [440][475/500] eta: 0:00:01 time: 0.0348 data_time: 0.0027 memory: 1008 2022/11/02 16:55:05 - mmengine - INFO - Epoch(val) [440][480/500] eta: 0:00:00 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 16:55:05 - mmengine - INFO - Epoch(val) [440][485/500] eta: 0:00:00 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 16:55:06 - mmengine - INFO - Epoch(val) [440][490/500] eta: 0:00:00 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 16:55:06 - mmengine - INFO - Epoch(val) [440][495/500] eta: 0:00:00 time: 0.0415 data_time: 0.0023 memory: 1008 2022/11/02 16:55:06 - mmengine - INFO - Epoch(val) [440][500/500] eta: 0:00:00 time: 0.0387 data_time: 0.0023 memory: 1008 2022/11/02 16:55:06 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8060, precision: 0.6672, hmean: 0.7300 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8060, precision: 0.7819, hmean: 0.7937 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8045, precision: 0.8203, hmean: 0.8123 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7915, precision: 0.8465, hmean: 0.8181 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7443, precision: 0.8880, hmean: 0.8098 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4357, precision: 0.9388, hmean: 0.5952 2022/11/02 16:55:06 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0164, precision: 0.9714, hmean: 0.0322 2022/11/02 16:55:06 - mmengine - INFO - Epoch(val) [440][500/500] icdar/precision: 0.8465 icdar/recall: 0.7915 icdar/hmean: 0.8181 2022/11/02 16:55:12 - mmengine - INFO - Epoch(train) [441][5/63] lr: 1.4334e-03 eta: 0:00:00 time: 0.7785 data_time: 0.2404 memory: 14901 loss: 1.4386 loss_prob: 0.7964 loss_thr: 0.5079 loss_db: 0.1343 2022/11/02 16:55:14 - mmengine - INFO - Epoch(train) [441][10/63] lr: 1.4334e-03 eta: 7:48:41 time: 0.8137 data_time: 0.2331 memory: 14901 loss: 1.5207 loss_prob: 0.8449 loss_thr: 0.5355 loss_db: 0.1403 2022/11/02 16:55:17 - mmengine - INFO - Epoch(train) [441][15/63] lr: 1.4334e-03 eta: 7:48:41 time: 0.5475 data_time: 0.0124 memory: 14901 loss: 1.5626 loss_prob: 0.8761 loss_thr: 0.5433 loss_db: 0.1432 2022/11/02 16:55:21 - mmengine - INFO - Epoch(train) [441][20/63] lr: 1.4334e-03 eta: 7:48:37 time: 0.6962 data_time: 0.0142 memory: 14901 loss: 1.5071 loss_prob: 0.8338 loss_thr: 0.5348 loss_db: 0.1385 2022/11/02 16:55:24 - mmengine - INFO - Epoch(train) [441][25/63] lr: 1.4334e-03 eta: 7:48:37 time: 0.7023 data_time: 0.0296 memory: 14901 loss: 1.4189 loss_prob: 0.7699 loss_thr: 0.5149 loss_db: 0.1341 2022/11/02 16:55:27 - mmengine - INFO - Epoch(train) [441][30/63] lr: 1.4334e-03 eta: 7:48:31 time: 0.5514 data_time: 0.0447 memory: 14901 loss: 1.3135 loss_prob: 0.7061 loss_thr: 0.4866 loss_db: 0.1208 2022/11/02 16:55:30 - mmengine - INFO - Epoch(train) [441][35/63] lr: 1.4334e-03 eta: 7:48:31 time: 0.5681 data_time: 0.0254 memory: 14901 loss: 1.3503 loss_prob: 0.7362 loss_thr: 0.4919 loss_db: 0.1222 2022/11/02 16:55:33 - mmengine - INFO - Epoch(train) [441][40/63] lr: 1.4334e-03 eta: 7:48:25 time: 0.5754 data_time: 0.0085 memory: 14901 loss: 1.3874 loss_prob: 0.7649 loss_thr: 0.4948 loss_db: 0.1277 2022/11/02 16:55:35 - mmengine - INFO - Epoch(train) [441][45/63] lr: 1.4334e-03 eta: 7:48:25 time: 0.5670 data_time: 0.0097 memory: 14901 loss: 1.3224 loss_prob: 0.7259 loss_thr: 0.4707 loss_db: 0.1259 2022/11/02 16:55:38 - mmengine - INFO - Epoch(train) [441][50/63] lr: 1.4334e-03 eta: 7:48:19 time: 0.5761 data_time: 0.0220 memory: 14901 loss: 1.3648 loss_prob: 0.7600 loss_thr: 0.4722 loss_db: 0.1326 2022/11/02 16:55:42 - mmengine - INFO - Epoch(train) [441][55/63] lr: 1.4334e-03 eta: 7:48:19 time: 0.6273 data_time: 0.0291 memory: 14901 loss: 1.4034 loss_prob: 0.7811 loss_thr: 0.4928 loss_db: 0.1295 2022/11/02 16:55:45 - mmengine - INFO - Epoch(train) [441][60/63] lr: 1.4334e-03 eta: 7:48:14 time: 0.6254 data_time: 0.0181 memory: 14901 loss: 1.4680 loss_prob: 0.8264 loss_thr: 0.5051 loss_db: 0.1365 2022/11/02 16:55:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:55:52 - mmengine - INFO - Epoch(train) [442][5/63] lr: 1.4317e-03 eta: 7:48:14 time: 0.8321 data_time: 0.3109 memory: 14901 loss: 1.5202 loss_prob: 0.8567 loss_thr: 0.5225 loss_db: 0.1410 2022/11/02 16:55:55 - mmengine - INFO - Epoch(train) [442][10/63] lr: 1.4317e-03 eta: 7:48:08 time: 0.8925 data_time: 0.3105 memory: 14901 loss: 1.4893 loss_prob: 0.8282 loss_thr: 0.5230 loss_db: 0.1381 2022/11/02 16:55:58 - mmengine - INFO - Epoch(train) [442][15/63] lr: 1.4317e-03 eta: 7:48:08 time: 0.6605 data_time: 0.0103 memory: 14901 loss: 1.4160 loss_prob: 0.7703 loss_thr: 0.5175 loss_db: 0.1282 2022/11/02 16:56:01 - mmengine - INFO - Epoch(train) [442][20/63] lr: 1.4317e-03 eta: 7:48:04 time: 0.6627 data_time: 0.0087 memory: 14901 loss: 1.3800 loss_prob: 0.7511 loss_thr: 0.5030 loss_db: 0.1258 2022/11/02 16:56:05 - mmengine - INFO - Epoch(train) [442][25/63] lr: 1.4317e-03 eta: 7:48:04 time: 0.6430 data_time: 0.0427 memory: 14901 loss: 1.4327 loss_prob: 0.7888 loss_thr: 0.5109 loss_db: 0.1330 2022/11/02 16:56:08 - mmengine - INFO - Epoch(train) [442][30/63] lr: 1.4317e-03 eta: 7:47:59 time: 0.6793 data_time: 0.0462 memory: 14901 loss: 1.4692 loss_prob: 0.8063 loss_thr: 0.5267 loss_db: 0.1362 2022/11/02 16:56:11 - mmengine - INFO - Epoch(train) [442][35/63] lr: 1.4317e-03 eta: 7:47:59 time: 0.6510 data_time: 0.0120 memory: 14901 loss: 1.4453 loss_prob: 0.7937 loss_thr: 0.5154 loss_db: 0.1362 2022/11/02 16:56:14 - mmengine - INFO - Epoch(train) [442][40/63] lr: 1.4317e-03 eta: 7:47:54 time: 0.6220 data_time: 0.0079 memory: 14901 loss: 1.3648 loss_prob: 0.7455 loss_thr: 0.4928 loss_db: 0.1265 2022/11/02 16:56:17 - mmengine - INFO - Epoch(train) [442][45/63] lr: 1.4317e-03 eta: 7:47:54 time: 0.6039 data_time: 0.0073 memory: 14901 loss: 1.3898 loss_prob: 0.7498 loss_thr: 0.5159 loss_db: 0.1241 2022/11/02 16:56:20 - mmengine - INFO - Epoch(train) [442][50/63] lr: 1.4317e-03 eta: 7:47:48 time: 0.5844 data_time: 0.0269 memory: 14901 loss: 1.3493 loss_prob: 0.7239 loss_thr: 0.5007 loss_db: 0.1248 2022/11/02 16:56:23 - mmengine - INFO - Epoch(train) [442][55/63] lr: 1.4317e-03 eta: 7:47:48 time: 0.5862 data_time: 0.0310 memory: 14901 loss: 1.3346 loss_prob: 0.7195 loss_thr: 0.4933 loss_db: 0.1218 2022/11/02 16:56:26 - mmengine - INFO - Epoch(train) [442][60/63] lr: 1.4317e-03 eta: 7:47:42 time: 0.5508 data_time: 0.0133 memory: 14901 loss: 1.4086 loss_prob: 0.7681 loss_thr: 0.5165 loss_db: 0.1240 2022/11/02 16:56:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:56:34 - mmengine - INFO - Epoch(train) [443][5/63] lr: 1.4300e-03 eta: 7:47:42 time: 0.8849 data_time: 0.2264 memory: 14901 loss: 1.4584 loss_prob: 0.8172 loss_thr: 0.5054 loss_db: 0.1358 2022/11/02 16:56:37 - mmengine - INFO - Epoch(train) [443][10/63] lr: 1.4300e-03 eta: 7:47:38 time: 0.9867 data_time: 0.2324 memory: 14901 loss: 1.4698 loss_prob: 0.8274 loss_thr: 0.5043 loss_db: 0.1380 2022/11/02 16:56:40 - mmengine - INFO - Epoch(train) [443][15/63] lr: 1.4300e-03 eta: 7:47:38 time: 0.6321 data_time: 0.0188 memory: 14901 loss: 1.3543 loss_prob: 0.7429 loss_thr: 0.4906 loss_db: 0.1208 2022/11/02 16:56:43 - mmengine - INFO - Epoch(train) [443][20/63] lr: 1.4300e-03 eta: 7:47:32 time: 0.5733 data_time: 0.0128 memory: 14901 loss: 1.3034 loss_prob: 0.7005 loss_thr: 0.4860 loss_db: 0.1169 2022/11/02 16:56:47 - mmengine - INFO - Epoch(train) [443][25/63] lr: 1.4300e-03 eta: 7:47:32 time: 0.7453 data_time: 0.0220 memory: 14901 loss: 1.3249 loss_prob: 0.7164 loss_thr: 0.4840 loss_db: 0.1246 2022/11/02 16:56:50 - mmengine - INFO - Epoch(train) [443][30/63] lr: 1.4300e-03 eta: 7:47:28 time: 0.7347 data_time: 0.0469 memory: 14901 loss: 1.3545 loss_prob: 0.7180 loss_thr: 0.5133 loss_db: 0.1233 2022/11/02 16:56:53 - mmengine - INFO - Epoch(train) [443][35/63] lr: 1.4300e-03 eta: 7:47:28 time: 0.5414 data_time: 0.0337 memory: 14901 loss: 1.4265 loss_prob: 0.7587 loss_thr: 0.5394 loss_db: 0.1284 2022/11/02 16:56:55 - mmengine - INFO - Epoch(train) [443][40/63] lr: 1.4300e-03 eta: 7:47:21 time: 0.5309 data_time: 0.0091 memory: 14901 loss: 1.3694 loss_prob: 0.7445 loss_thr: 0.5007 loss_db: 0.1243 2022/11/02 16:56:58 - mmengine - INFO - Epoch(train) [443][45/63] lr: 1.4300e-03 eta: 7:47:21 time: 0.5235 data_time: 0.0080 memory: 14901 loss: 1.3197 loss_prob: 0.7121 loss_thr: 0.4868 loss_db: 0.1209 2022/11/02 16:57:01 - mmengine - INFO - Epoch(train) [443][50/63] lr: 1.4300e-03 eta: 7:47:15 time: 0.5478 data_time: 0.0212 memory: 14901 loss: 1.4242 loss_prob: 0.7900 loss_thr: 0.5030 loss_db: 0.1313 2022/11/02 16:57:03 - mmengine - INFO - Epoch(train) [443][55/63] lr: 1.4300e-03 eta: 7:47:15 time: 0.5489 data_time: 0.0342 memory: 14901 loss: 1.5622 loss_prob: 0.8904 loss_thr: 0.5269 loss_db: 0.1449 2022/11/02 16:57:06 - mmengine - INFO - Epoch(train) [443][60/63] lr: 1.4300e-03 eta: 7:47:07 time: 0.4969 data_time: 0.0181 memory: 14901 loss: 1.5185 loss_prob: 0.8414 loss_thr: 0.5364 loss_db: 0.1407 2022/11/02 16:57:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:57:14 - mmengine - INFO - Epoch(train) [444][5/63] lr: 1.4283e-03 eta: 7:47:07 time: 0.9060 data_time: 0.2408 memory: 14901 loss: 1.3283 loss_prob: 0.7187 loss_thr: 0.4900 loss_db: 0.1196 2022/11/02 16:57:17 - mmengine - INFO - Epoch(train) [444][10/63] lr: 1.4283e-03 eta: 7:47:02 time: 0.8951 data_time: 0.2436 memory: 14901 loss: 1.2908 loss_prob: 0.7015 loss_thr: 0.4724 loss_db: 0.1168 2022/11/02 16:57:20 - mmengine - INFO - Epoch(train) [444][15/63] lr: 1.4283e-03 eta: 7:47:02 time: 0.5886 data_time: 0.0146 memory: 14901 loss: 1.4148 loss_prob: 0.7786 loss_thr: 0.5070 loss_db: 0.1292 2022/11/02 16:57:23 - mmengine - INFO - Epoch(train) [444][20/63] lr: 1.4283e-03 eta: 7:46:57 time: 0.6477 data_time: 0.0141 memory: 14901 loss: 1.5526 loss_prob: 0.8661 loss_thr: 0.5420 loss_db: 0.1444 2022/11/02 16:57:27 - mmengine - INFO - Epoch(train) [444][25/63] lr: 1.4283e-03 eta: 7:46:57 time: 0.7156 data_time: 0.0259 memory: 14901 loss: 1.4892 loss_prob: 0.8233 loss_thr: 0.5273 loss_db: 0.1386 2022/11/02 16:57:31 - mmengine - INFO - Epoch(train) [444][30/63] lr: 1.4283e-03 eta: 7:46:55 time: 0.7799 data_time: 0.0329 memory: 14901 loss: 1.3688 loss_prob: 0.7438 loss_thr: 0.4984 loss_db: 0.1265 2022/11/02 16:57:33 - mmengine - INFO - Epoch(train) [444][35/63] lr: 1.4283e-03 eta: 7:46:55 time: 0.6456 data_time: 0.0187 memory: 14901 loss: 1.4366 loss_prob: 0.8006 loss_thr: 0.5032 loss_db: 0.1329 2022/11/02 16:57:36 - mmengine - INFO - Epoch(train) [444][40/63] lr: 1.4283e-03 eta: 7:46:48 time: 0.5551 data_time: 0.0100 memory: 14901 loss: 1.4452 loss_prob: 0.8105 loss_thr: 0.5008 loss_db: 0.1339 2022/11/02 16:57:39 - mmengine - INFO - Epoch(train) [444][45/63] lr: 1.4283e-03 eta: 7:46:48 time: 0.5448 data_time: 0.0103 memory: 14901 loss: 1.3991 loss_prob: 0.7709 loss_thr: 0.4975 loss_db: 0.1307 2022/11/02 16:57:42 - mmengine - INFO - Epoch(train) [444][50/63] lr: 1.4283e-03 eta: 7:46:41 time: 0.5389 data_time: 0.0219 memory: 14901 loss: 1.3276 loss_prob: 0.7183 loss_thr: 0.4878 loss_db: 0.1215 2022/11/02 16:57:44 - mmengine - INFO - Epoch(train) [444][55/63] lr: 1.4283e-03 eta: 7:46:41 time: 0.5523 data_time: 0.0235 memory: 14901 loss: 1.3400 loss_prob: 0.7276 loss_thr: 0.4903 loss_db: 0.1221 2022/11/02 16:57:48 - mmengine - INFO - Epoch(train) [444][60/63] lr: 1.4283e-03 eta: 7:46:36 time: 0.6019 data_time: 0.0207 memory: 14901 loss: 1.3425 loss_prob: 0.7225 loss_thr: 0.4985 loss_db: 0.1215 2022/11/02 16:57:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:57:56 - mmengine - INFO - Epoch(train) [445][5/63] lr: 1.4266e-03 eta: 7:46:36 time: 0.9098 data_time: 0.2132 memory: 14901 loss: 1.3919 loss_prob: 0.7765 loss_thr: 0.4905 loss_db: 0.1249 2022/11/02 16:57:59 - mmengine - INFO - Epoch(train) [445][10/63] lr: 1.4266e-03 eta: 7:46:32 time: 0.9810 data_time: 0.2133 memory: 14901 loss: 1.6107 loss_prob: 0.9393 loss_thr: 0.5229 loss_db: 0.1485 2022/11/02 16:58:02 - mmengine - INFO - Epoch(train) [445][15/63] lr: 1.4266e-03 eta: 7:46:32 time: 0.6552 data_time: 0.0059 memory: 14901 loss: 1.5171 loss_prob: 0.8607 loss_thr: 0.5180 loss_db: 0.1384 2022/11/02 16:58:06 - mmengine - INFO - Epoch(train) [445][20/63] lr: 1.4266e-03 eta: 7:46:27 time: 0.6556 data_time: 0.0134 memory: 14901 loss: 1.4215 loss_prob: 0.7725 loss_thr: 0.5219 loss_db: 0.1271 2022/11/02 16:58:09 - mmengine - INFO - Epoch(train) [445][25/63] lr: 1.4266e-03 eta: 7:46:27 time: 0.6814 data_time: 0.0306 memory: 14901 loss: 1.3767 loss_prob: 0.7366 loss_thr: 0.5147 loss_db: 0.1254 2022/11/02 16:58:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:58:12 - mmengine - INFO - Epoch(train) [445][30/63] lr: 1.4266e-03 eta: 7:46:22 time: 0.6279 data_time: 0.0488 memory: 14901 loss: 1.3759 loss_prob: 0.7400 loss_thr: 0.5097 loss_db: 0.1262 2022/11/02 16:58:14 - mmengine - INFO - Epoch(train) [445][35/63] lr: 1.4266e-03 eta: 7:46:22 time: 0.5318 data_time: 0.0347 memory: 14901 loss: 1.4554 loss_prob: 0.7960 loss_thr: 0.5262 loss_db: 0.1332 2022/11/02 16:58:17 - mmengine - INFO - Epoch(train) [445][40/63] lr: 1.4266e-03 eta: 7:46:15 time: 0.5199 data_time: 0.0118 memory: 14901 loss: 1.4481 loss_prob: 0.8013 loss_thr: 0.5188 loss_db: 0.1281 2022/11/02 16:58:21 - mmengine - INFO - Epoch(train) [445][45/63] lr: 1.4266e-03 eta: 7:46:15 time: 0.6802 data_time: 0.0136 memory: 14901 loss: 1.4872 loss_prob: 0.8399 loss_thr: 0.5161 loss_db: 0.1311 2022/11/02 16:58:25 - mmengine - INFO - Epoch(train) [445][50/63] lr: 1.4266e-03 eta: 7:46:12 time: 0.7668 data_time: 0.0284 memory: 14901 loss: 1.5204 loss_prob: 0.8619 loss_thr: 0.5212 loss_db: 0.1373 2022/11/02 16:58:27 - mmengine - INFO - Epoch(train) [445][55/63] lr: 1.4266e-03 eta: 7:46:12 time: 0.6230 data_time: 0.0262 memory: 14901 loss: 1.4644 loss_prob: 0.8186 loss_thr: 0.5088 loss_db: 0.1369 2022/11/02 16:58:30 - mmengine - INFO - Epoch(train) [445][60/63] lr: 1.4266e-03 eta: 7:46:05 time: 0.5322 data_time: 0.0097 memory: 14901 loss: 1.3865 loss_prob: 0.7661 loss_thr: 0.4890 loss_db: 0.1314 2022/11/02 16:58:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:58:37 - mmengine - INFO - Epoch(train) [446][5/63] lr: 1.4249e-03 eta: 7:46:05 time: 0.8253 data_time: 0.2694 memory: 14901 loss: 1.3921 loss_prob: 0.7600 loss_thr: 0.5072 loss_db: 0.1249 2022/11/02 16:58:40 - mmengine - INFO - Epoch(train) [446][10/63] lr: 1.4249e-03 eta: 7:46:00 time: 0.9025 data_time: 0.2692 memory: 14901 loss: 1.3574 loss_prob: 0.7425 loss_thr: 0.4901 loss_db: 0.1248 2022/11/02 16:58:44 - mmengine - INFO - Epoch(train) [446][15/63] lr: 1.4249e-03 eta: 7:46:00 time: 0.6438 data_time: 0.0087 memory: 14901 loss: 1.4059 loss_prob: 0.7756 loss_thr: 0.4972 loss_db: 0.1331 2022/11/02 16:58:47 - mmengine - INFO - Epoch(train) [446][20/63] lr: 1.4249e-03 eta: 7:45:55 time: 0.6369 data_time: 0.0110 memory: 14901 loss: 1.3610 loss_prob: 0.7454 loss_thr: 0.4906 loss_db: 0.1250 2022/11/02 16:58:50 - mmengine - INFO - Epoch(train) [446][25/63] lr: 1.4249e-03 eta: 7:45:55 time: 0.6636 data_time: 0.0144 memory: 14901 loss: 1.2734 loss_prob: 0.6827 loss_thr: 0.4764 loss_db: 0.1143 2022/11/02 16:58:53 - mmengine - INFO - Epoch(train) [446][30/63] lr: 1.4249e-03 eta: 7:45:50 time: 0.6441 data_time: 0.0426 memory: 14901 loss: 1.3268 loss_prob: 0.7251 loss_thr: 0.4806 loss_db: 0.1211 2022/11/02 16:58:56 - mmengine - INFO - Epoch(train) [446][35/63] lr: 1.4249e-03 eta: 7:45:50 time: 0.5140 data_time: 0.0359 memory: 14901 loss: 1.3548 loss_prob: 0.7353 loss_thr: 0.4952 loss_db: 0.1244 2022/11/02 16:58:58 - mmengine - INFO - Epoch(train) [446][40/63] lr: 1.4249e-03 eta: 7:45:43 time: 0.5047 data_time: 0.0049 memory: 14901 loss: 1.3322 loss_prob: 0.7070 loss_thr: 0.5050 loss_db: 0.1203 2022/11/02 16:59:02 - mmengine - INFO - Epoch(train) [446][45/63] lr: 1.4249e-03 eta: 7:45:43 time: 0.5974 data_time: 0.0110 memory: 14901 loss: 1.3860 loss_prob: 0.7511 loss_thr: 0.5109 loss_db: 0.1240 2022/11/02 16:59:04 - mmengine - INFO - Epoch(train) [446][50/63] lr: 1.4249e-03 eta: 7:45:37 time: 0.5806 data_time: 0.0246 memory: 14901 loss: 1.3436 loss_prob: 0.7243 loss_thr: 0.4969 loss_db: 0.1225 2022/11/02 16:59:07 - mmengine - INFO - Epoch(train) [446][55/63] lr: 1.4249e-03 eta: 7:45:37 time: 0.5172 data_time: 0.0314 memory: 14901 loss: 1.4052 loss_prob: 0.7716 loss_thr: 0.5045 loss_db: 0.1291 2022/11/02 16:59:09 - mmengine - INFO - Epoch(train) [446][60/63] lr: 1.4249e-03 eta: 7:45:30 time: 0.5271 data_time: 0.0215 memory: 14901 loss: 1.4976 loss_prob: 0.8328 loss_thr: 0.5242 loss_db: 0.1405 2022/11/02 16:59:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 16:59:17 - mmengine - INFO - Epoch(train) [447][5/63] lr: 1.4232e-03 eta: 7:45:30 time: 0.8493 data_time: 0.2442 memory: 14901 loss: 1.4805 loss_prob: 0.8243 loss_thr: 0.5179 loss_db: 0.1383 2022/11/02 16:59:20 - mmengine - INFO - Epoch(train) [447][10/63] lr: 1.4232e-03 eta: 7:45:25 time: 0.9339 data_time: 0.2496 memory: 14901 loss: 1.4898 loss_prob: 0.8406 loss_thr: 0.5118 loss_db: 0.1374 2022/11/02 16:59:23 - mmengine - INFO - Epoch(train) [447][15/63] lr: 1.4232e-03 eta: 7:45:25 time: 0.6440 data_time: 0.0109 memory: 14901 loss: 1.5283 loss_prob: 0.8518 loss_thr: 0.5344 loss_db: 0.1422 2022/11/02 16:59:27 - mmengine - INFO - Epoch(train) [447][20/63] lr: 1.4232e-03 eta: 7:45:20 time: 0.6613 data_time: 0.0106 memory: 14901 loss: 1.5771 loss_prob: 0.8744 loss_thr: 0.5531 loss_db: 0.1496 2022/11/02 16:59:31 - mmengine - INFO - Epoch(train) [447][25/63] lr: 1.4232e-03 eta: 7:45:20 time: 0.7292 data_time: 0.0276 memory: 14901 loss: 1.5559 loss_prob: 0.8673 loss_thr: 0.5426 loss_db: 0.1459 2022/11/02 16:59:34 - mmengine - INFO - Epoch(train) [447][30/63] lr: 1.4232e-03 eta: 7:45:17 time: 0.7334 data_time: 0.0373 memory: 14901 loss: 1.5296 loss_prob: 0.8530 loss_thr: 0.5333 loss_db: 0.1433 2022/11/02 16:59:37 - mmengine - INFO - Epoch(train) [447][35/63] lr: 1.4232e-03 eta: 7:45:17 time: 0.6734 data_time: 0.0265 memory: 14901 loss: 1.4518 loss_prob: 0.8040 loss_thr: 0.5105 loss_db: 0.1373 2022/11/02 16:59:40 - mmengine - INFO - Epoch(train) [447][40/63] lr: 1.4232e-03 eta: 7:45:12 time: 0.6543 data_time: 0.0140 memory: 14901 loss: 1.3532 loss_prob: 0.7386 loss_thr: 0.4885 loss_db: 0.1262 2022/11/02 16:59:43 - mmengine - INFO - Epoch(train) [447][45/63] lr: 1.4232e-03 eta: 7:45:12 time: 0.5965 data_time: 0.0114 memory: 14901 loss: 1.2989 loss_prob: 0.7014 loss_thr: 0.4763 loss_db: 0.1212 2022/11/02 16:59:46 - mmengine - INFO - Epoch(train) [447][50/63] lr: 1.4232e-03 eta: 7:45:06 time: 0.5816 data_time: 0.0214 memory: 14901 loss: 1.3476 loss_prob: 0.7376 loss_thr: 0.4845 loss_db: 0.1255 2022/11/02 16:59:49 - mmengine - INFO - Epoch(train) [447][55/63] lr: 1.4232e-03 eta: 7:45:06 time: 0.6265 data_time: 0.0254 memory: 14901 loss: 1.4236 loss_prob: 0.7667 loss_thr: 0.5283 loss_db: 0.1285 2022/11/02 16:59:53 - mmengine - INFO - Epoch(train) [447][60/63] lr: 1.4232e-03 eta: 7:45:02 time: 0.6733 data_time: 0.0169 memory: 14901 loss: 1.3691 loss_prob: 0.7332 loss_thr: 0.5109 loss_db: 0.1250 2022/11/02 16:59:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:00:01 - mmengine - INFO - Epoch(train) [448][5/63] lr: 1.4215e-03 eta: 7:45:02 time: 0.9279 data_time: 0.2923 memory: 14901 loss: 1.3878 loss_prob: 0.7484 loss_thr: 0.5125 loss_db: 0.1269 2022/11/02 17:00:04 - mmengine - INFO - Epoch(train) [448][10/63] lr: 1.4215e-03 eta: 7:44:57 time: 0.9338 data_time: 0.2939 memory: 14901 loss: 1.3673 loss_prob: 0.7383 loss_thr: 0.5055 loss_db: 0.1235 2022/11/02 17:00:07 - mmengine - INFO - Epoch(train) [448][15/63] lr: 1.4215e-03 eta: 7:44:57 time: 0.5829 data_time: 0.0125 memory: 14901 loss: 1.2625 loss_prob: 0.6771 loss_thr: 0.4709 loss_db: 0.1145 2022/11/02 17:00:09 - mmengine - INFO - Epoch(train) [448][20/63] lr: 1.4215e-03 eta: 7:44:50 time: 0.5306 data_time: 0.0140 memory: 14901 loss: 1.4140 loss_prob: 0.7679 loss_thr: 0.5183 loss_db: 0.1278 2022/11/02 17:00:13 - mmengine - INFO - Epoch(train) [448][25/63] lr: 1.4215e-03 eta: 7:44:50 time: 0.6274 data_time: 0.0170 memory: 14901 loss: 1.4633 loss_prob: 0.7926 loss_thr: 0.5404 loss_db: 0.1303 2022/11/02 17:00:17 - mmengine - INFO - Epoch(train) [448][30/63] lr: 1.4215e-03 eta: 7:44:47 time: 0.7372 data_time: 0.0456 memory: 14901 loss: 1.3448 loss_prob: 0.7180 loss_thr: 0.5067 loss_db: 0.1202 2022/11/02 17:00:20 - mmengine - INFO - Epoch(train) [448][35/63] lr: 1.4215e-03 eta: 7:44:47 time: 0.6744 data_time: 0.0377 memory: 14901 loss: 1.2887 loss_prob: 0.6883 loss_thr: 0.4831 loss_db: 0.1172 2022/11/02 17:00:23 - mmengine - INFO - Epoch(train) [448][40/63] lr: 1.4215e-03 eta: 7:44:42 time: 0.6391 data_time: 0.0072 memory: 14901 loss: 1.2883 loss_prob: 0.6982 loss_thr: 0.4717 loss_db: 0.1183 2022/11/02 17:00:26 - mmengine - INFO - Epoch(train) [448][45/63] lr: 1.4215e-03 eta: 7:44:42 time: 0.6558 data_time: 0.0069 memory: 14901 loss: 1.4117 loss_prob: 0.7746 loss_thr: 0.5070 loss_db: 0.1301 2022/11/02 17:00:29 - mmengine - INFO - Epoch(train) [448][50/63] lr: 1.4215e-03 eta: 7:44:36 time: 0.6235 data_time: 0.0338 memory: 14901 loss: 1.4159 loss_prob: 0.7698 loss_thr: 0.5139 loss_db: 0.1322 2022/11/02 17:00:32 - mmengine - INFO - Epoch(train) [448][55/63] lr: 1.4215e-03 eta: 7:44:36 time: 0.5431 data_time: 0.0333 memory: 14901 loss: 1.4357 loss_prob: 0.8009 loss_thr: 0.5004 loss_db: 0.1345 2022/11/02 17:00:35 - mmengine - INFO - Epoch(train) [448][60/63] lr: 1.4215e-03 eta: 7:44:29 time: 0.5254 data_time: 0.0051 memory: 14901 loss: 1.5173 loss_prob: 0.8584 loss_thr: 0.5181 loss_db: 0.1408 2022/11/02 17:00:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:00:42 - mmengine - INFO - Epoch(train) [449][5/63] lr: 1.4198e-03 eta: 7:44:29 time: 0.8001 data_time: 0.2589 memory: 14901 loss: 1.5114 loss_prob: 0.8318 loss_thr: 0.5416 loss_db: 0.1381 2022/11/02 17:00:44 - mmengine - INFO - Epoch(train) [449][10/63] lr: 1.4198e-03 eta: 7:44:22 time: 0.7933 data_time: 0.2583 memory: 14901 loss: 1.5884 loss_prob: 0.8994 loss_thr: 0.5375 loss_db: 0.1515 2022/11/02 17:00:47 - mmengine - INFO - Epoch(train) [449][15/63] lr: 1.4198e-03 eta: 7:44:22 time: 0.5277 data_time: 0.0123 memory: 14901 loss: 1.5804 loss_prob: 0.8968 loss_thr: 0.5353 loss_db: 0.1483 2022/11/02 17:00:50 - mmengine - INFO - Epoch(train) [449][20/63] lr: 1.4198e-03 eta: 7:44:16 time: 0.5957 data_time: 0.0098 memory: 14901 loss: 1.4688 loss_prob: 0.8061 loss_thr: 0.5295 loss_db: 0.1333 2022/11/02 17:00:53 - mmengine - INFO - Epoch(train) [449][25/63] lr: 1.4198e-03 eta: 7:44:16 time: 0.5873 data_time: 0.0097 memory: 14901 loss: 1.4179 loss_prob: 0.7589 loss_thr: 0.5331 loss_db: 0.1258 2022/11/02 17:00:56 - mmengine - INFO - Epoch(train) [449][30/63] lr: 1.4198e-03 eta: 7:44:11 time: 0.6278 data_time: 0.0704 memory: 14901 loss: 1.4665 loss_prob: 0.8033 loss_thr: 0.5313 loss_db: 0.1320 2022/11/02 17:00:59 - mmengine - INFO - Epoch(train) [449][35/63] lr: 1.4198e-03 eta: 7:44:11 time: 0.6497 data_time: 0.0783 memory: 14901 loss: 1.4198 loss_prob: 0.7841 loss_thr: 0.5048 loss_db: 0.1309 2022/11/02 17:01:02 - mmengine - INFO - Epoch(train) [449][40/63] lr: 1.4198e-03 eta: 7:44:04 time: 0.5332 data_time: 0.0183 memory: 14901 loss: 1.3624 loss_prob: 0.7320 loss_thr: 0.5067 loss_db: 0.1236 2022/11/02 17:01:04 - mmengine - INFO - Epoch(train) [449][45/63] lr: 1.4198e-03 eta: 7:44:04 time: 0.5010 data_time: 0.0072 memory: 14901 loss: 1.4936 loss_prob: 0.8309 loss_thr: 0.5240 loss_db: 0.1388 2022/11/02 17:01:07 - mmengine - INFO - Epoch(train) [449][50/63] lr: 1.4198e-03 eta: 7:43:58 time: 0.5318 data_time: 0.0322 memory: 14901 loss: 1.4900 loss_prob: 0.8278 loss_thr: 0.5229 loss_db: 0.1393 2022/11/02 17:01:10 - mmengine - INFO - Epoch(train) [449][55/63] lr: 1.4198e-03 eta: 7:43:58 time: 0.5487 data_time: 0.0342 memory: 14901 loss: 1.3923 loss_prob: 0.7525 loss_thr: 0.5135 loss_db: 0.1263 2022/11/02 17:01:13 - mmengine - INFO - Epoch(train) [449][60/63] lr: 1.4198e-03 eta: 7:43:52 time: 0.6099 data_time: 0.0101 memory: 14901 loss: 1.3799 loss_prob: 0.7505 loss_thr: 0.5053 loss_db: 0.1242 2022/11/02 17:01:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:01:20 - mmengine - INFO - Epoch(train) [450][5/63] lr: 1.4181e-03 eta: 7:43:52 time: 0.8615 data_time: 0.2535 memory: 14901 loss: 1.5865 loss_prob: 0.9332 loss_thr: 0.5040 loss_db: 0.1492 2022/11/02 17:01:23 - mmengine - INFO - Epoch(train) [450][10/63] lr: 1.4181e-03 eta: 7:43:46 time: 0.8498 data_time: 0.2577 memory: 14901 loss: 1.7571 loss_prob: 1.0574 loss_thr: 0.5283 loss_db: 0.1714 2022/11/02 17:01:26 - mmengine - INFO - Epoch(train) [450][15/63] lr: 1.4181e-03 eta: 7:43:46 time: 0.5957 data_time: 0.0224 memory: 14901 loss: 1.6989 loss_prob: 0.9852 loss_thr: 0.5493 loss_db: 0.1643 2022/11/02 17:01:29 - mmengine - INFO - Epoch(train) [450][20/63] lr: 1.4181e-03 eta: 7:43:39 time: 0.5475 data_time: 0.0156 memory: 14901 loss: 1.5099 loss_prob: 0.8320 loss_thr: 0.5360 loss_db: 0.1419 2022/11/02 17:01:32 - mmengine - INFO - Epoch(train) [450][25/63] lr: 1.4181e-03 eta: 7:43:39 time: 0.5718 data_time: 0.0324 memory: 14901 loss: 1.4916 loss_prob: 0.8236 loss_thr: 0.5279 loss_db: 0.1401 2022/11/02 17:01:35 - mmengine - INFO - Epoch(train) [450][30/63] lr: 1.4181e-03 eta: 7:43:34 time: 0.6214 data_time: 0.0376 memory: 14901 loss: 1.5386 loss_prob: 0.8512 loss_thr: 0.5466 loss_db: 0.1408 2022/11/02 17:01:38 - mmengine - INFO - Epoch(train) [450][35/63] lr: 1.4181e-03 eta: 7:43:34 time: 0.6095 data_time: 0.0149 memory: 14901 loss: 1.5157 loss_prob: 0.8315 loss_thr: 0.5467 loss_db: 0.1374 2022/11/02 17:01:41 - mmengine - INFO - Epoch(train) [450][40/63] lr: 1.4181e-03 eta: 7:43:29 time: 0.6388 data_time: 0.0229 memory: 14901 loss: 1.5236 loss_prob: 0.8395 loss_thr: 0.5453 loss_db: 0.1389 2022/11/02 17:01:44 - mmengine - INFO - Epoch(train) [450][45/63] lr: 1.4181e-03 eta: 7:43:29 time: 0.5948 data_time: 0.0207 memory: 14901 loss: 1.5659 loss_prob: 0.8696 loss_thr: 0.5516 loss_db: 0.1447 2022/11/02 17:01:47 - mmengine - INFO - Epoch(train) [450][50/63] lr: 1.4181e-03 eta: 7:43:22 time: 0.5549 data_time: 0.0224 memory: 14901 loss: 1.5585 loss_prob: 0.8741 loss_thr: 0.5381 loss_db: 0.1463 2022/11/02 17:01:50 - mmengine - INFO - Epoch(train) [450][55/63] lr: 1.4181e-03 eta: 7:43:22 time: 0.5452 data_time: 0.0218 memory: 14901 loss: 1.5217 loss_prob: 0.8449 loss_thr: 0.5350 loss_db: 0.1418 2022/11/02 17:01:52 - mmengine - INFO - Epoch(train) [450][60/63] lr: 1.4181e-03 eta: 7:43:16 time: 0.5291 data_time: 0.0142 memory: 14901 loss: 1.5105 loss_prob: 0.8233 loss_thr: 0.5483 loss_db: 0.1389 2022/11/02 17:01:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:01:59 - mmengine - INFO - Epoch(train) [451][5/63] lr: 1.4164e-03 eta: 7:43:16 time: 0.8112 data_time: 0.2114 memory: 14901 loss: 1.4669 loss_prob: 0.8080 loss_thr: 0.5217 loss_db: 0.1371 2022/11/02 17:02:02 - mmengine - INFO - Epoch(train) [451][10/63] lr: 1.4164e-03 eta: 7:43:09 time: 0.8273 data_time: 0.2117 memory: 14901 loss: 1.4977 loss_prob: 0.8251 loss_thr: 0.5341 loss_db: 0.1385 2022/11/02 17:02:05 - mmengine - INFO - Epoch(train) [451][15/63] lr: 1.4164e-03 eta: 7:43:09 time: 0.5307 data_time: 0.0126 memory: 14901 loss: 1.5026 loss_prob: 0.8357 loss_thr: 0.5288 loss_db: 0.1381 2022/11/02 17:02:07 - mmengine - INFO - Epoch(train) [451][20/63] lr: 1.4164e-03 eta: 7:43:02 time: 0.5178 data_time: 0.0088 memory: 14901 loss: 1.4289 loss_prob: 0.7828 loss_thr: 0.5133 loss_db: 0.1328 2022/11/02 17:02:10 - mmengine - INFO - Epoch(train) [451][25/63] lr: 1.4164e-03 eta: 7:43:02 time: 0.5020 data_time: 0.0227 memory: 14901 loss: 1.4384 loss_prob: 0.7963 loss_thr: 0.5062 loss_db: 0.1359 2022/11/02 17:02:13 - mmengine - INFO - Epoch(train) [451][30/63] lr: 1.4164e-03 eta: 7:42:56 time: 0.5573 data_time: 0.0457 memory: 14901 loss: 1.4241 loss_prob: 0.7962 loss_thr: 0.4942 loss_db: 0.1336 2022/11/02 17:02:15 - mmengine - INFO - Epoch(train) [451][35/63] lr: 1.4164e-03 eta: 7:42:56 time: 0.5608 data_time: 0.0317 memory: 14901 loss: 1.3821 loss_prob: 0.7583 loss_thr: 0.4982 loss_db: 0.1256 2022/11/02 17:02:18 - mmengine - INFO - Epoch(train) [451][40/63] lr: 1.4164e-03 eta: 7:42:48 time: 0.5093 data_time: 0.0076 memory: 14901 loss: 1.3873 loss_prob: 0.7569 loss_thr: 0.5057 loss_db: 0.1247 2022/11/02 17:02:21 - mmengine - INFO - Epoch(train) [451][45/63] lr: 1.4164e-03 eta: 7:42:48 time: 0.5553 data_time: 0.0110 memory: 14901 loss: 1.4056 loss_prob: 0.7787 loss_thr: 0.5012 loss_db: 0.1257 2022/11/02 17:02:24 - mmengine - INFO - Epoch(train) [451][50/63] lr: 1.4164e-03 eta: 7:42:43 time: 0.5955 data_time: 0.0288 memory: 14901 loss: 1.3981 loss_prob: 0.7750 loss_thr: 0.4975 loss_db: 0.1256 2022/11/02 17:02:27 - mmengine - INFO - Epoch(train) [451][55/63] lr: 1.4164e-03 eta: 7:42:43 time: 0.6061 data_time: 0.0365 memory: 14901 loss: 1.5381 loss_prob: 0.8590 loss_thr: 0.5368 loss_db: 0.1423 2022/11/02 17:02:30 - mmengine - INFO - Epoch(train) [451][60/63] lr: 1.4164e-03 eta: 7:42:38 time: 0.6450 data_time: 0.0174 memory: 14901 loss: 1.6334 loss_prob: 0.9248 loss_thr: 0.5552 loss_db: 0.1534 2022/11/02 17:02:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:02:37 - mmengine - INFO - Epoch(train) [452][5/63] lr: 1.4147e-03 eta: 7:42:38 time: 0.7835 data_time: 0.2662 memory: 14901 loss: 1.5915 loss_prob: 0.9139 loss_thr: 0.5276 loss_db: 0.1500 2022/11/02 17:02:40 - mmengine - INFO - Epoch(train) [452][10/63] lr: 1.4147e-03 eta: 7:42:32 time: 0.8672 data_time: 0.2626 memory: 14901 loss: 1.5021 loss_prob: 0.8545 loss_thr: 0.5069 loss_db: 0.1407 2022/11/02 17:02:43 - mmengine - INFO - Epoch(train) [452][15/63] lr: 1.4147e-03 eta: 7:42:32 time: 0.5722 data_time: 0.0120 memory: 14901 loss: 1.5039 loss_prob: 0.8367 loss_thr: 0.5241 loss_db: 0.1431 2022/11/02 17:02:46 - mmengine - INFO - Epoch(train) [452][20/63] lr: 1.4147e-03 eta: 7:42:26 time: 0.5781 data_time: 0.0118 memory: 14901 loss: 1.5194 loss_prob: 0.8421 loss_thr: 0.5335 loss_db: 0.1438 2022/11/02 17:02:49 - mmengine - INFO - Epoch(train) [452][25/63] lr: 1.4147e-03 eta: 7:42:26 time: 0.5923 data_time: 0.0463 memory: 14901 loss: 1.4642 loss_prob: 0.8012 loss_thr: 0.5273 loss_db: 0.1356 2022/11/02 17:02:51 - mmengine - INFO - Epoch(train) [452][30/63] lr: 1.4147e-03 eta: 7:42:19 time: 0.5484 data_time: 0.0451 memory: 14901 loss: 1.3412 loss_prob: 0.7238 loss_thr: 0.4962 loss_db: 0.1212 2022/11/02 17:02:54 - mmengine - INFO - Epoch(train) [452][35/63] lr: 1.4147e-03 eta: 7:42:19 time: 0.5104 data_time: 0.0073 memory: 14901 loss: 1.2553 loss_prob: 0.6707 loss_thr: 0.4698 loss_db: 0.1148 2022/11/02 17:02:57 - mmengine - INFO - Epoch(train) [452][40/63] lr: 1.4147e-03 eta: 7:42:13 time: 0.5846 data_time: 0.0078 memory: 14901 loss: 1.1957 loss_prob: 0.6237 loss_thr: 0.4649 loss_db: 0.1071 2022/11/02 17:03:00 - mmengine - INFO - Epoch(train) [452][45/63] lr: 1.4147e-03 eta: 7:42:13 time: 0.5956 data_time: 0.0100 memory: 14901 loss: 1.2329 loss_prob: 0.6465 loss_thr: 0.4768 loss_db: 0.1096 2022/11/02 17:03:03 - mmengine - INFO - Epoch(train) [452][50/63] lr: 1.4147e-03 eta: 7:42:07 time: 0.5526 data_time: 0.0349 memory: 14901 loss: 1.3634 loss_prob: 0.7305 loss_thr: 0.5058 loss_db: 0.1271 2022/11/02 17:03:06 - mmengine - INFO - Epoch(train) [452][55/63] lr: 1.4147e-03 eta: 7:42:07 time: 0.6302 data_time: 0.0343 memory: 14901 loss: 1.4928 loss_prob: 0.8411 loss_thr: 0.5133 loss_db: 0.1384 2022/11/02 17:03:09 - mmengine - INFO - Epoch(train) [452][60/63] lr: 1.4147e-03 eta: 7:42:02 time: 0.6494 data_time: 0.0090 memory: 14901 loss: 1.5126 loss_prob: 0.8770 loss_thr: 0.4980 loss_db: 0.1375 2022/11/02 17:03:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:03:16 - mmengine - INFO - Epoch(train) [453][5/63] lr: 1.4130e-03 eta: 7:42:02 time: 0.8589 data_time: 0.1903 memory: 14901 loss: 1.4093 loss_prob: 0.7830 loss_thr: 0.4981 loss_db: 0.1282 2022/11/02 17:03:19 - mmengine - INFO - Epoch(train) [453][10/63] lr: 1.4130e-03 eta: 7:41:56 time: 0.8587 data_time: 0.1982 memory: 14901 loss: 1.3508 loss_prob: 0.7306 loss_thr: 0.4970 loss_db: 0.1231 2022/11/02 17:03:22 - mmengine - INFO - Epoch(train) [453][15/63] lr: 1.4130e-03 eta: 7:41:56 time: 0.5401 data_time: 0.0201 memory: 14901 loss: 1.2876 loss_prob: 0.6793 loss_thr: 0.4941 loss_db: 0.1142 2022/11/02 17:03:24 - mmengine - INFO - Epoch(train) [453][20/63] lr: 1.4130e-03 eta: 7:41:49 time: 0.5351 data_time: 0.0118 memory: 14901 loss: 1.4454 loss_prob: 0.7913 loss_thr: 0.5222 loss_db: 0.1319 2022/11/02 17:03:27 - mmengine - INFO - Epoch(train) [453][25/63] lr: 1.4130e-03 eta: 7:41:49 time: 0.5495 data_time: 0.0195 memory: 14901 loss: 1.5540 loss_prob: 0.8652 loss_thr: 0.5449 loss_db: 0.1439 2022/11/02 17:03:30 - mmengine - INFO - Epoch(train) [453][30/63] lr: 1.4130e-03 eta: 7:41:43 time: 0.5677 data_time: 0.0432 memory: 14901 loss: 1.4250 loss_prob: 0.7792 loss_thr: 0.5142 loss_db: 0.1316 2022/11/02 17:03:33 - mmengine - INFO - Epoch(train) [453][35/63] lr: 1.4130e-03 eta: 7:41:43 time: 0.5627 data_time: 0.0299 memory: 14901 loss: 1.3287 loss_prob: 0.7231 loss_thr: 0.4819 loss_db: 0.1237 2022/11/02 17:03:36 - mmengine - INFO - Epoch(train) [453][40/63] lr: 1.4130e-03 eta: 7:41:36 time: 0.5567 data_time: 0.0151 memory: 14901 loss: 1.5403 loss_prob: 0.8851 loss_thr: 0.5033 loss_db: 0.1520 2022/11/02 17:03:38 - mmengine - INFO - Epoch(train) [453][45/63] lr: 1.4130e-03 eta: 7:41:36 time: 0.5337 data_time: 0.0149 memory: 14901 loss: 1.5458 loss_prob: 0.8770 loss_thr: 0.5202 loss_db: 0.1486 2022/11/02 17:03:41 - mmengine - INFO - Epoch(train) [453][50/63] lr: 1.4130e-03 eta: 7:41:30 time: 0.5342 data_time: 0.0125 memory: 14901 loss: 1.4051 loss_prob: 0.7659 loss_thr: 0.5121 loss_db: 0.1271 2022/11/02 17:03:44 - mmengine - INFO - Epoch(train) [453][55/63] lr: 1.4130e-03 eta: 7:41:30 time: 0.5677 data_time: 0.0264 memory: 14901 loss: 1.6111 loss_prob: 0.9204 loss_thr: 0.5377 loss_db: 0.1529 2022/11/02 17:03:46 - mmengine - INFO - Epoch(train) [453][60/63] lr: 1.4130e-03 eta: 7:41:23 time: 0.5428 data_time: 0.0209 memory: 14901 loss: 1.6906 loss_prob: 0.9788 loss_thr: 0.5518 loss_db: 0.1600 2022/11/02 17:03:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:03:55 - mmengine - INFO - Epoch(train) [454][5/63] lr: 1.4113e-03 eta: 7:41:23 time: 0.9400 data_time: 0.2602 memory: 14901 loss: 1.6023 loss_prob: 0.9080 loss_thr: 0.5456 loss_db: 0.1487 2022/11/02 17:03:58 - mmengine - INFO - Epoch(train) [454][10/63] lr: 1.4113e-03 eta: 7:41:19 time: 1.0085 data_time: 0.2552 memory: 14901 loss: 1.5006 loss_prob: 0.8391 loss_thr: 0.5195 loss_db: 0.1421 2022/11/02 17:04:00 - mmengine - INFO - Epoch(train) [454][15/63] lr: 1.4113e-03 eta: 7:41:19 time: 0.5769 data_time: 0.0110 memory: 14901 loss: 1.5213 loss_prob: 0.8597 loss_thr: 0.5192 loss_db: 0.1423 2022/11/02 17:04:03 - mmengine - INFO - Epoch(train) [454][20/63] lr: 1.4113e-03 eta: 7:41:13 time: 0.5399 data_time: 0.0129 memory: 14901 loss: 1.4668 loss_prob: 0.8104 loss_thr: 0.5228 loss_db: 0.1336 2022/11/02 17:04:07 - mmengine - INFO - Epoch(train) [454][25/63] lr: 1.4113e-03 eta: 7:41:13 time: 0.6395 data_time: 0.0319 memory: 14901 loss: 1.4109 loss_prob: 0.7683 loss_thr: 0.5136 loss_db: 0.1290 2022/11/02 17:04:10 - mmengine - INFO - Epoch(train) [454][30/63] lr: 1.4113e-03 eta: 7:41:08 time: 0.6547 data_time: 0.0445 memory: 14901 loss: 1.4684 loss_prob: 0.8144 loss_thr: 0.5154 loss_db: 0.1386 2022/11/02 17:04:13 - mmengine - INFO - Epoch(train) [454][35/63] lr: 1.4113e-03 eta: 7:41:08 time: 0.5881 data_time: 0.0290 memory: 14901 loss: 1.5031 loss_prob: 0.8400 loss_thr: 0.5191 loss_db: 0.1440 2022/11/02 17:04:16 - mmengine - INFO - Epoch(train) [454][40/63] lr: 1.4113e-03 eta: 7:41:02 time: 0.6004 data_time: 0.0134 memory: 14901 loss: 1.4398 loss_prob: 0.8034 loss_thr: 0.5011 loss_db: 0.1353 2022/11/02 17:04:19 - mmengine - INFO - Epoch(train) [454][45/63] lr: 1.4113e-03 eta: 7:41:02 time: 0.6098 data_time: 0.0137 memory: 14901 loss: 1.3536 loss_prob: 0.7415 loss_thr: 0.4863 loss_db: 0.1258 2022/11/02 17:04:21 - mmengine - INFO - Epoch(train) [454][50/63] lr: 1.4113e-03 eta: 7:40:56 time: 0.5529 data_time: 0.0203 memory: 14901 loss: 1.3944 loss_prob: 0.7654 loss_thr: 0.4983 loss_db: 0.1307 2022/11/02 17:04:25 - mmengine - INFO - Epoch(train) [454][55/63] lr: 1.4113e-03 eta: 7:40:56 time: 0.5917 data_time: 0.0231 memory: 14901 loss: 1.5024 loss_prob: 0.8314 loss_thr: 0.5320 loss_db: 0.1390 2022/11/02 17:04:28 - mmengine - INFO - Epoch(train) [454][60/63] lr: 1.4113e-03 eta: 7:40:51 time: 0.6632 data_time: 0.0167 memory: 14901 loss: 1.5551 loss_prob: 0.8436 loss_thr: 0.5705 loss_db: 0.1410 2022/11/02 17:04:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:04:35 - mmengine - INFO - Epoch(train) [455][5/63] lr: 1.4096e-03 eta: 7:40:51 time: 0.7935 data_time: 0.2345 memory: 14901 loss: 1.4318 loss_prob: 0.7797 loss_thr: 0.5181 loss_db: 0.1340 2022/11/02 17:04:40 - mmengine - INFO - Epoch(train) [455][10/63] lr: 1.4096e-03 eta: 7:40:47 time: 1.0058 data_time: 0.2391 memory: 14901 loss: 1.3874 loss_prob: 0.7555 loss_thr: 0.5005 loss_db: 0.1313 2022/11/02 17:04:42 - mmengine - INFO - Epoch(train) [455][15/63] lr: 1.4096e-03 eta: 7:40:47 time: 0.7536 data_time: 0.0144 memory: 14901 loss: 1.3843 loss_prob: 0.7507 loss_thr: 0.5053 loss_db: 0.1283 2022/11/02 17:04:45 - mmengine - INFO - Epoch(train) [455][20/63] lr: 1.4096e-03 eta: 7:40:41 time: 0.5676 data_time: 0.0074 memory: 14901 loss: 1.4033 loss_prob: 0.7563 loss_thr: 0.5190 loss_db: 0.1281 2022/11/02 17:04:48 - mmengine - INFO - Epoch(train) [455][25/63] lr: 1.4096e-03 eta: 7:40:41 time: 0.5815 data_time: 0.0443 memory: 14901 loss: 1.4781 loss_prob: 0.8041 loss_thr: 0.5369 loss_db: 0.1371 2022/11/02 17:04:51 - mmengine - INFO - Epoch(train) [455][30/63] lr: 1.4096e-03 eta: 7:40:35 time: 0.5770 data_time: 0.0434 memory: 14901 loss: 1.5136 loss_prob: 0.8282 loss_thr: 0.5425 loss_db: 0.1429 2022/11/02 17:04:54 - mmengine - INFO - Epoch(train) [455][35/63] lr: 1.4096e-03 eta: 7:40:35 time: 0.5538 data_time: 0.0109 memory: 14901 loss: 1.3924 loss_prob: 0.7541 loss_thr: 0.5100 loss_db: 0.1283 2022/11/02 17:04:57 - mmengine - INFO - Epoch(train) [455][40/63] lr: 1.4096e-03 eta: 7:40:29 time: 0.5631 data_time: 0.0102 memory: 14901 loss: 1.3892 loss_prob: 0.7548 loss_thr: 0.5077 loss_db: 0.1268 2022/11/02 17:04:59 - mmengine - INFO - Epoch(train) [455][45/63] lr: 1.4096e-03 eta: 7:40:29 time: 0.5524 data_time: 0.0075 memory: 14901 loss: 1.4773 loss_prob: 0.8143 loss_thr: 0.5251 loss_db: 0.1379 2022/11/02 17:05:02 - mmengine - INFO - Epoch(train) [455][50/63] lr: 1.4096e-03 eta: 7:40:22 time: 0.5179 data_time: 0.0248 memory: 14901 loss: 1.3909 loss_prob: 0.7580 loss_thr: 0.5051 loss_db: 0.1277 2022/11/02 17:05:05 - mmengine - INFO - Epoch(train) [455][55/63] lr: 1.4096e-03 eta: 7:40:22 time: 0.5413 data_time: 0.0263 memory: 14901 loss: 1.3907 loss_prob: 0.7769 loss_thr: 0.4845 loss_db: 0.1292 2022/11/02 17:05:07 - mmengine - INFO - Epoch(train) [455][60/63] lr: 1.4096e-03 eta: 7:40:15 time: 0.5166 data_time: 0.0135 memory: 14901 loss: 1.5934 loss_prob: 0.9346 loss_thr: 0.5126 loss_db: 0.1462 2022/11/02 17:05:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:05:14 - mmengine - INFO - Epoch(train) [456][5/63] lr: 1.4079e-03 eta: 7:40:15 time: 0.8012 data_time: 0.2136 memory: 14901 loss: 1.4031 loss_prob: 0.7696 loss_thr: 0.5032 loss_db: 0.1303 2022/11/02 17:05:17 - mmengine - INFO - Epoch(train) [456][10/63] lr: 1.4079e-03 eta: 7:40:09 time: 0.8597 data_time: 0.2193 memory: 14901 loss: 1.4394 loss_prob: 0.7903 loss_thr: 0.5172 loss_db: 0.1319 2022/11/02 17:05:20 - mmengine - INFO - Epoch(train) [456][15/63] lr: 1.4079e-03 eta: 7:40:09 time: 0.5949 data_time: 0.0151 memory: 14901 loss: 1.4730 loss_prob: 0.8048 loss_thr: 0.5359 loss_db: 0.1323 2022/11/02 17:05:23 - mmengine - INFO - Epoch(train) [456][20/63] lr: 1.4079e-03 eta: 7:40:03 time: 0.6010 data_time: 0.0109 memory: 14901 loss: 1.4843 loss_prob: 0.8165 loss_thr: 0.5294 loss_db: 0.1383 2022/11/02 17:05:26 - mmengine - INFO - Epoch(train) [456][25/63] lr: 1.4079e-03 eta: 7:40:03 time: 0.5853 data_time: 0.0086 memory: 14901 loss: 1.5337 loss_prob: 0.8464 loss_thr: 0.5428 loss_db: 0.1445 2022/11/02 17:05:29 - mmengine - INFO - Epoch(train) [456][30/63] lr: 1.4079e-03 eta: 7:39:57 time: 0.5664 data_time: 0.0347 memory: 14901 loss: 1.5064 loss_prob: 0.8197 loss_thr: 0.5448 loss_db: 0.1418 2022/11/02 17:05:31 - mmengine - INFO - Epoch(train) [456][35/63] lr: 1.4079e-03 eta: 7:39:57 time: 0.5503 data_time: 0.0377 memory: 14901 loss: 1.4468 loss_prob: 0.7838 loss_thr: 0.5287 loss_db: 0.1343 2022/11/02 17:05:34 - mmengine - INFO - Epoch(train) [456][40/63] lr: 1.4079e-03 eta: 7:39:49 time: 0.4935 data_time: 0.0094 memory: 14901 loss: 1.3417 loss_prob: 0.7113 loss_thr: 0.5112 loss_db: 0.1191 2022/11/02 17:05:37 - mmengine - INFO - Epoch(train) [456][45/63] lr: 1.4079e-03 eta: 7:39:49 time: 0.5231 data_time: 0.0121 memory: 14901 loss: 1.4193 loss_prob: 0.7727 loss_thr: 0.5145 loss_db: 0.1322 2022/11/02 17:05:39 - mmengine - INFO - Epoch(train) [456][50/63] lr: 1.4079e-03 eta: 7:39:43 time: 0.5654 data_time: 0.0179 memory: 14901 loss: 1.4615 loss_prob: 0.8124 loss_thr: 0.5116 loss_db: 0.1376 2022/11/02 17:05:42 - mmengine - INFO - Epoch(train) [456][55/63] lr: 1.4079e-03 eta: 7:39:43 time: 0.5459 data_time: 0.0250 memory: 14901 loss: 1.3712 loss_prob: 0.7563 loss_thr: 0.4908 loss_db: 0.1241 2022/11/02 17:05:46 - mmengine - INFO - Epoch(train) [456][60/63] lr: 1.4079e-03 eta: 7:39:38 time: 0.6284 data_time: 0.0229 memory: 14901 loss: 1.3811 loss_prob: 0.7563 loss_thr: 0.5018 loss_db: 0.1230 2022/11/02 17:05:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:05:53 - mmengine - INFO - Epoch(train) [457][5/63] lr: 1.4061e-03 eta: 7:39:38 time: 0.9333 data_time: 0.2509 memory: 14901 loss: 1.4988 loss_prob: 0.8337 loss_thr: 0.5245 loss_db: 0.1406 2022/11/02 17:05:56 - mmengine - INFO - Epoch(train) [457][10/63] lr: 1.4061e-03 eta: 7:39:32 time: 0.8523 data_time: 0.2543 memory: 14901 loss: 1.5159 loss_prob: 0.8437 loss_thr: 0.5309 loss_db: 0.1413 2022/11/02 17:05:59 - mmengine - INFO - Epoch(train) [457][15/63] lr: 1.4061e-03 eta: 7:39:32 time: 0.5526 data_time: 0.0133 memory: 14901 loss: 1.4788 loss_prob: 0.8070 loss_thr: 0.5364 loss_db: 0.1354 2022/11/02 17:06:01 - mmengine - INFO - Epoch(train) [457][20/63] lr: 1.4061e-03 eta: 7:39:25 time: 0.5738 data_time: 0.0080 memory: 14901 loss: 1.3920 loss_prob: 0.7502 loss_thr: 0.5143 loss_db: 0.1276 2022/11/02 17:06:04 - mmengine - INFO - Epoch(train) [457][25/63] lr: 1.4061e-03 eta: 7:39:25 time: 0.5453 data_time: 0.0228 memory: 14901 loss: 1.3800 loss_prob: 0.7645 loss_thr: 0.4881 loss_db: 0.1274 2022/11/02 17:06:08 - mmengine - INFO - Epoch(train) [457][30/63] lr: 1.4061e-03 eta: 7:39:21 time: 0.6681 data_time: 0.0473 memory: 14901 loss: 1.4140 loss_prob: 0.7846 loss_thr: 0.5001 loss_db: 0.1293 2022/11/02 17:06:11 - mmengine - INFO - Epoch(train) [457][35/63] lr: 1.4061e-03 eta: 7:39:21 time: 0.6745 data_time: 0.0326 memory: 14901 loss: 1.3289 loss_prob: 0.7138 loss_thr: 0.4937 loss_db: 0.1215 2022/11/02 17:06:14 - mmengine - INFO - Epoch(train) [457][40/63] lr: 1.4061e-03 eta: 7:39:15 time: 0.5919 data_time: 0.0066 memory: 14901 loss: 1.2889 loss_prob: 0.6791 loss_thr: 0.4943 loss_db: 0.1155 2022/11/02 17:06:17 - mmengine - INFO - Epoch(train) [457][45/63] lr: 1.4061e-03 eta: 7:39:15 time: 0.6017 data_time: 0.0065 memory: 14901 loss: 1.3160 loss_prob: 0.6922 loss_thr: 0.5060 loss_db: 0.1178 2022/11/02 17:06:20 - mmengine - INFO - Epoch(train) [457][50/63] lr: 1.4061e-03 eta: 7:39:08 time: 0.5419 data_time: 0.0234 memory: 14901 loss: 1.3612 loss_prob: 0.7407 loss_thr: 0.4967 loss_db: 0.1238 2022/11/02 17:06:22 - mmengine - INFO - Epoch(train) [457][55/63] lr: 1.4061e-03 eta: 7:39:08 time: 0.5416 data_time: 0.0290 memory: 14901 loss: 1.3398 loss_prob: 0.7282 loss_thr: 0.4910 loss_db: 0.1205 2022/11/02 17:06:25 - mmengine - INFO - Epoch(train) [457][60/63] lr: 1.4061e-03 eta: 7:39:02 time: 0.5910 data_time: 0.0115 memory: 14901 loss: 1.3065 loss_prob: 0.6965 loss_thr: 0.4929 loss_db: 0.1172 2022/11/02 17:06:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:06:33 - mmengine - INFO - Epoch(train) [458][5/63] lr: 1.4044e-03 eta: 7:39:02 time: 0.8491 data_time: 0.2759 memory: 14901 loss: 1.3639 loss_prob: 0.7441 loss_thr: 0.4911 loss_db: 0.1287 2022/11/02 17:06:36 - mmengine - INFO - Epoch(train) [458][10/63] lr: 1.4044e-03 eta: 7:38:57 time: 0.9281 data_time: 0.2743 memory: 14901 loss: 1.3968 loss_prob: 0.7690 loss_thr: 0.5015 loss_db: 0.1264 2022/11/02 17:06:39 - mmengine - INFO - Epoch(train) [458][15/63] lr: 1.4044e-03 eta: 7:38:57 time: 0.5774 data_time: 0.0106 memory: 14901 loss: 1.3765 loss_prob: 0.7556 loss_thr: 0.4974 loss_db: 0.1235 2022/11/02 17:06:42 - mmengine - INFO - Epoch(train) [458][20/63] lr: 1.4044e-03 eta: 7:38:51 time: 0.5621 data_time: 0.0093 memory: 14901 loss: 1.3588 loss_prob: 0.7378 loss_thr: 0.4963 loss_db: 0.1248 2022/11/02 17:06:45 - mmengine - INFO - Epoch(train) [458][25/63] lr: 1.4044e-03 eta: 7:38:51 time: 0.6155 data_time: 0.0241 memory: 14901 loss: 1.3204 loss_prob: 0.7050 loss_thr: 0.4957 loss_db: 0.1197 2022/11/02 17:06:48 - mmengine - INFO - Epoch(train) [458][30/63] lr: 1.4044e-03 eta: 7:38:46 time: 0.6057 data_time: 0.0477 memory: 14901 loss: 1.3502 loss_prob: 0.7313 loss_thr: 0.4973 loss_db: 0.1217 2022/11/02 17:06:51 - mmengine - INFO - Epoch(train) [458][35/63] lr: 1.4044e-03 eta: 7:38:46 time: 0.5713 data_time: 0.0314 memory: 14901 loss: 1.2863 loss_prob: 0.6912 loss_thr: 0.4789 loss_db: 0.1162 2022/11/02 17:06:54 - mmengine - INFO - Epoch(train) [458][40/63] lr: 1.4044e-03 eta: 7:38:40 time: 0.6366 data_time: 0.0071 memory: 14901 loss: 1.3340 loss_prob: 0.7130 loss_thr: 0.4980 loss_db: 0.1230 2022/11/02 17:06:57 - mmengine - INFO - Epoch(train) [458][45/63] lr: 1.4044e-03 eta: 7:38:40 time: 0.5989 data_time: 0.0074 memory: 14901 loss: 1.4188 loss_prob: 0.7741 loss_thr: 0.5114 loss_db: 0.1333 2022/11/02 17:07:00 - mmengine - INFO - Epoch(train) [458][50/63] lr: 1.4044e-03 eta: 7:38:34 time: 0.5558 data_time: 0.0250 memory: 14901 loss: 1.3651 loss_prob: 0.7462 loss_thr: 0.4919 loss_db: 0.1270 2022/11/02 17:07:03 - mmengine - INFO - Epoch(train) [458][55/63] lr: 1.4044e-03 eta: 7:38:34 time: 0.5892 data_time: 0.0310 memory: 14901 loss: 1.3124 loss_prob: 0.7077 loss_thr: 0.4846 loss_db: 0.1202 2022/11/02 17:07:06 - mmengine - INFO - Epoch(train) [458][60/63] lr: 1.4044e-03 eta: 7:38:28 time: 0.5946 data_time: 0.0135 memory: 14901 loss: 1.2593 loss_prob: 0.6636 loss_thr: 0.4818 loss_db: 0.1139 2022/11/02 17:07:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:07:14 - mmengine - INFO - Epoch(train) [459][5/63] lr: 1.4027e-03 eta: 7:38:28 time: 0.9158 data_time: 0.2590 memory: 14901 loss: 1.4099 loss_prob: 0.7692 loss_thr: 0.5124 loss_db: 0.1283 2022/11/02 17:07:16 - mmengine - INFO - Epoch(train) [459][10/63] lr: 1.4027e-03 eta: 7:38:23 time: 0.9412 data_time: 0.2580 memory: 14901 loss: 1.3848 loss_prob: 0.7588 loss_thr: 0.5007 loss_db: 0.1252 2022/11/02 17:07:19 - mmengine - INFO - Epoch(train) [459][15/63] lr: 1.4027e-03 eta: 7:38:23 time: 0.5550 data_time: 0.0119 memory: 14901 loss: 1.3009 loss_prob: 0.7058 loss_thr: 0.4755 loss_db: 0.1196 2022/11/02 17:07:22 - mmengine - INFO - Epoch(train) [459][20/63] lr: 1.4027e-03 eta: 7:38:17 time: 0.5506 data_time: 0.0169 memory: 14901 loss: 1.2734 loss_prob: 0.6821 loss_thr: 0.4761 loss_db: 0.1153 2022/11/02 17:07:25 - mmengine - INFO - Epoch(train) [459][25/63] lr: 1.4027e-03 eta: 7:38:17 time: 0.6070 data_time: 0.0249 memory: 14901 loss: 1.2405 loss_prob: 0.6590 loss_thr: 0.4695 loss_db: 0.1120 2022/11/02 17:07:28 - mmengine - INFO - Epoch(train) [459][30/63] lr: 1.4027e-03 eta: 7:38:12 time: 0.6576 data_time: 0.0311 memory: 14901 loss: 1.2651 loss_prob: 0.6810 loss_thr: 0.4667 loss_db: 0.1175 2022/11/02 17:07:32 - mmengine - INFO - Epoch(train) [459][35/63] lr: 1.4027e-03 eta: 7:38:12 time: 0.6368 data_time: 0.0204 memory: 14901 loss: 1.3473 loss_prob: 0.7337 loss_thr: 0.4887 loss_db: 0.1249 2022/11/02 17:07:34 - mmengine - INFO - Epoch(train) [459][40/63] lr: 1.4027e-03 eta: 7:38:06 time: 0.5720 data_time: 0.0116 memory: 14901 loss: 1.3605 loss_prob: 0.7426 loss_thr: 0.4970 loss_db: 0.1209 2022/11/02 17:07:37 - mmengine - INFO - Epoch(train) [459][45/63] lr: 1.4027e-03 eta: 7:38:06 time: 0.5465 data_time: 0.0115 memory: 14901 loss: 1.4038 loss_prob: 0.7539 loss_thr: 0.5263 loss_db: 0.1236 2022/11/02 17:07:40 - mmengine - INFO - Epoch(train) [459][50/63] lr: 1.4027e-03 eta: 7:38:00 time: 0.6010 data_time: 0.0279 memory: 14901 loss: 1.4314 loss_prob: 0.7748 loss_thr: 0.5255 loss_db: 0.1311 2022/11/02 17:07:43 - mmengine - INFO - Epoch(train) [459][55/63] lr: 1.4027e-03 eta: 7:38:00 time: 0.6226 data_time: 0.0314 memory: 14901 loss: 1.3112 loss_prob: 0.7115 loss_thr: 0.4781 loss_db: 0.1216 2022/11/02 17:07:46 - mmengine - INFO - Epoch(train) [459][60/63] lr: 1.4027e-03 eta: 7:37:54 time: 0.5773 data_time: 0.0128 memory: 14901 loss: 1.2951 loss_prob: 0.6935 loss_thr: 0.4835 loss_db: 0.1181 2022/11/02 17:07:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:07:53 - mmengine - INFO - Epoch(train) [460][5/63] lr: 1.4010e-03 eta: 7:37:54 time: 0.8044 data_time: 0.2316 memory: 14901 loss: 1.2938 loss_prob: 0.6816 loss_thr: 0.4925 loss_db: 0.1198 2022/11/02 17:07:56 - mmengine - INFO - Epoch(train) [460][10/63] lr: 1.4010e-03 eta: 7:37:48 time: 0.8635 data_time: 0.2390 memory: 14901 loss: 1.2638 loss_prob: 0.6584 loss_thr: 0.4915 loss_db: 0.1139 2022/11/02 17:07:59 - mmengine - INFO - Epoch(train) [460][15/63] lr: 1.4010e-03 eta: 7:37:48 time: 0.5860 data_time: 0.0170 memory: 14901 loss: 1.3015 loss_prob: 0.6916 loss_thr: 0.4910 loss_db: 0.1189 2022/11/02 17:08:02 - mmengine - INFO - Epoch(train) [460][20/63] lr: 1.4010e-03 eta: 7:37:42 time: 0.5804 data_time: 0.0085 memory: 14901 loss: 1.2906 loss_prob: 0.6985 loss_thr: 0.4711 loss_db: 0.1210 2022/11/02 17:08:04 - mmengine - INFO - Epoch(train) [460][25/63] lr: 1.4010e-03 eta: 7:37:42 time: 0.5412 data_time: 0.0220 memory: 14901 loss: 1.2804 loss_prob: 0.6994 loss_thr: 0.4638 loss_db: 0.1172 2022/11/02 17:08:07 - mmengine - INFO - Epoch(train) [460][30/63] lr: 1.4010e-03 eta: 7:37:35 time: 0.5257 data_time: 0.0279 memory: 14901 loss: 1.3702 loss_prob: 0.7521 loss_thr: 0.4926 loss_db: 0.1255 2022/11/02 17:08:09 - mmengine - INFO - Epoch(train) [460][35/63] lr: 1.4010e-03 eta: 7:37:35 time: 0.5230 data_time: 0.0196 memory: 14901 loss: 1.3204 loss_prob: 0.7043 loss_thr: 0.4950 loss_db: 0.1211 2022/11/02 17:08:12 - mmengine - INFO - Epoch(train) [460][40/63] lr: 1.4010e-03 eta: 7:37:29 time: 0.5478 data_time: 0.0126 memory: 14901 loss: 1.4050 loss_prob: 0.7721 loss_thr: 0.5008 loss_db: 0.1321 2022/11/02 17:08:15 - mmengine - INFO - Epoch(train) [460][45/63] lr: 1.4010e-03 eta: 7:37:29 time: 0.5855 data_time: 0.0061 memory: 14901 loss: 1.4428 loss_prob: 0.8053 loss_thr: 0.5018 loss_db: 0.1357 2022/11/02 17:08:19 - mmengine - INFO - Epoch(train) [460][50/63] lr: 1.4010e-03 eta: 7:37:24 time: 0.6356 data_time: 0.0268 memory: 14901 loss: 1.3613 loss_prob: 0.7315 loss_thr: 0.5070 loss_db: 0.1229 2022/11/02 17:08:21 - mmengine - INFO - Epoch(train) [460][55/63] lr: 1.4010e-03 eta: 7:37:24 time: 0.6177 data_time: 0.0286 memory: 14901 loss: 1.4927 loss_prob: 0.8120 loss_thr: 0.5423 loss_db: 0.1384 2022/11/02 17:08:24 - mmengine - INFO - Epoch(train) [460][60/63] lr: 1.4010e-03 eta: 7:37:17 time: 0.5641 data_time: 0.0133 memory: 14901 loss: 1.5294 loss_prob: 0.8364 loss_thr: 0.5497 loss_db: 0.1433 2022/11/02 17:08:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:08:27 - mmengine - INFO - Saving checkpoint at 460 epochs 2022/11/02 17:08:31 - mmengine - INFO - Epoch(val) [460][5/500] eta: 7:37:17 time: 0.0434 data_time: 0.0055 memory: 14901 2022/11/02 17:08:31 - mmengine - INFO - Epoch(val) [460][10/500] eta: 0:00:22 time: 0.0465 data_time: 0.0061 memory: 1008 2022/11/02 17:08:31 - mmengine - INFO - Epoch(val) [460][15/500] eta: 0:00:22 time: 0.0443 data_time: 0.0033 memory: 1008 2022/11/02 17:08:31 - mmengine - INFO - Epoch(val) [460][20/500] eta: 0:00:20 time: 0.0427 data_time: 0.0029 memory: 1008 2022/11/02 17:08:31 - mmengine - INFO - Epoch(val) [460][25/500] eta: 0:00:20 time: 0.0370 data_time: 0.0027 memory: 1008 2022/11/02 17:08:32 - mmengine - INFO - Epoch(val) [460][30/500] eta: 0:00:20 time: 0.0427 data_time: 0.0040 memory: 1008 2022/11/02 17:08:32 - mmengine - INFO - Epoch(val) [460][35/500] eta: 0:00:20 time: 0.0472 data_time: 0.0042 memory: 1008 2022/11/02 17:08:32 - mmengine - INFO - Epoch(val) [460][40/500] eta: 0:00:23 time: 0.0515 data_time: 0.0058 memory: 1008 2022/11/02 17:08:32 - mmengine - INFO - Epoch(val) [460][45/500] eta: 0:00:23 time: 0.0502 data_time: 0.0062 memory: 1008 2022/11/02 17:08:33 - mmengine - INFO - Epoch(val) [460][50/500] eta: 0:00:18 time: 0.0410 data_time: 0.0040 memory: 1008 2022/11/02 17:08:33 - mmengine - INFO - Epoch(val) [460][55/500] eta: 0:00:18 time: 0.0431 data_time: 0.0034 memory: 1008 2022/11/02 17:08:33 - mmengine - INFO - Epoch(val) [460][60/500] eta: 0:00:18 time: 0.0428 data_time: 0.0026 memory: 1008 2022/11/02 17:08:33 - mmengine - INFO - Epoch(val) [460][65/500] eta: 0:00:18 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 17:08:33 - mmengine - INFO - Epoch(val) [460][70/500] eta: 0:00:17 time: 0.0408 data_time: 0.0023 memory: 1008 2022/11/02 17:08:34 - mmengine - INFO - Epoch(val) [460][75/500] eta: 0:00:17 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/02 17:08:34 - mmengine - INFO - Epoch(val) [460][80/500] eta: 0:00:14 time: 0.0353 data_time: 0.0027 memory: 1008 2022/11/02 17:08:34 - mmengine - INFO - Epoch(val) [460][85/500] eta: 0:00:14 time: 0.0363 data_time: 0.0028 memory: 1008 2022/11/02 17:08:34 - mmengine - INFO - Epoch(val) [460][90/500] eta: 0:00:16 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/02 17:08:34 - mmengine - INFO - Epoch(val) [460][95/500] eta: 0:00:16 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 17:08:35 - mmengine - INFO - Epoch(val) [460][100/500] eta: 0:00:16 time: 0.0400 data_time: 0.0025 memory: 1008 2022/11/02 17:08:35 - mmengine - INFO - Epoch(val) [460][105/500] eta: 0:00:16 time: 0.0357 data_time: 0.0022 memory: 1008 2022/11/02 17:08:35 - mmengine - INFO - Epoch(val) [460][110/500] eta: 0:00:14 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/02 17:08:35 - mmengine - INFO - Epoch(val) [460][115/500] eta: 0:00:14 time: 0.0429 data_time: 0.0028 memory: 1008 2022/11/02 17:08:35 - mmengine - INFO - Epoch(val) [460][120/500] eta: 0:00:16 time: 0.0438 data_time: 0.0032 memory: 1008 2022/11/02 17:08:36 - mmengine - INFO - Epoch(val) [460][125/500] eta: 0:00:16 time: 0.0392 data_time: 0.0030 memory: 1008 2022/11/02 17:08:36 - mmengine - INFO - Epoch(val) [460][130/500] eta: 0:00:13 time: 0.0375 data_time: 0.0027 memory: 1008 2022/11/02 17:08:36 - mmengine - INFO - Epoch(val) [460][135/500] eta: 0:00:13 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 17:08:36 - mmengine - INFO - Epoch(val) [460][140/500] eta: 0:00:14 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 17:08:36 - mmengine - INFO - Epoch(val) [460][145/500] eta: 0:00:14 time: 0.0461 data_time: 0.0030 memory: 1008 2022/11/02 17:08:37 - mmengine - INFO - Epoch(val) [460][150/500] eta: 0:00:16 time: 0.0472 data_time: 0.0033 memory: 1008 2022/11/02 17:08:37 - mmengine - INFO - Epoch(val) [460][155/500] eta: 0:00:16 time: 0.0476 data_time: 0.0031 memory: 1008 2022/11/02 17:08:37 - mmengine - INFO - Epoch(val) [460][160/500] eta: 0:00:15 time: 0.0452 data_time: 0.0026 memory: 1008 2022/11/02 17:08:37 - mmengine - INFO - Epoch(val) [460][165/500] eta: 0:00:15 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 17:08:38 - mmengine - INFO - Epoch(val) [460][170/500] eta: 0:00:14 time: 0.0437 data_time: 0.0026 memory: 1008 2022/11/02 17:08:38 - mmengine - INFO - Epoch(val) [460][175/500] eta: 0:00:14 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 17:08:38 - mmengine - INFO - Epoch(val) [460][180/500] eta: 0:00:12 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 17:08:38 - mmengine - INFO - Epoch(val) [460][185/500] eta: 0:00:12 time: 0.0488 data_time: 0.0059 memory: 1008 2022/11/02 17:08:38 - mmengine - INFO - Epoch(val) [460][190/500] eta: 0:00:14 time: 0.0471 data_time: 0.0055 memory: 1008 2022/11/02 17:08:39 - mmengine - INFO - Epoch(val) [460][195/500] eta: 0:00:14 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 17:08:39 - mmengine - INFO - Epoch(val) [460][200/500] eta: 0:00:14 time: 0.0492 data_time: 0.0039 memory: 1008 2022/11/02 17:08:39 - mmengine - INFO - Epoch(val) [460][205/500] eta: 0:00:14 time: 0.0481 data_time: 0.0040 memory: 1008 2022/11/02 17:08:39 - mmengine - INFO - Epoch(val) [460][210/500] eta: 0:00:11 time: 0.0393 data_time: 0.0031 memory: 1008 2022/11/02 17:08:40 - mmengine - INFO - Epoch(val) [460][215/500] eta: 0:00:11 time: 0.0426 data_time: 0.0031 memory: 1008 2022/11/02 17:08:40 - mmengine - INFO - Epoch(val) [460][220/500] eta: 0:00:11 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 17:08:40 - mmengine - INFO - Epoch(val) [460][225/500] eta: 0:00:11 time: 0.0400 data_time: 0.0024 memory: 1008 2022/11/02 17:08:40 - mmengine - INFO - Epoch(val) [460][230/500] eta: 0:00:10 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/02 17:08:40 - mmengine - INFO - Epoch(val) [460][235/500] eta: 0:00:10 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 17:08:40 - mmengine - INFO - Epoch(val) [460][240/500] eta: 0:00:10 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 17:08:41 - mmengine - INFO - Epoch(val) [460][245/500] eta: 0:00:10 time: 0.0375 data_time: 0.0027 memory: 1008 2022/11/02 17:08:41 - mmengine - INFO - Epoch(val) [460][250/500] eta: 0:00:10 time: 0.0423 data_time: 0.0047 memory: 1008 2022/11/02 17:08:41 - mmengine - INFO - Epoch(val) [460][255/500] eta: 0:00:10 time: 0.0424 data_time: 0.0045 memory: 1008 2022/11/02 17:08:41 - mmengine - INFO - Epoch(val) [460][260/500] eta: 0:00:08 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/02 17:08:41 - mmengine - INFO - Epoch(val) [460][265/500] eta: 0:00:08 time: 0.0368 data_time: 0.0023 memory: 1008 2022/11/02 17:08:42 - mmengine - INFO - Epoch(val) [460][270/500] eta: 0:00:09 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 17:08:42 - mmengine - INFO - Epoch(val) [460][275/500] eta: 0:00:09 time: 0.0393 data_time: 0.0029 memory: 1008 2022/11/02 17:08:42 - mmengine - INFO - Epoch(val) [460][280/500] eta: 0:00:08 time: 0.0393 data_time: 0.0026 memory: 1008 2022/11/02 17:08:42 - mmengine - INFO - Epoch(val) [460][285/500] eta: 0:00:08 time: 0.0397 data_time: 0.0022 memory: 1008 2022/11/02 17:08:42 - mmengine - INFO - Epoch(val) [460][290/500] eta: 0:00:08 time: 0.0384 data_time: 0.0022 memory: 1008 2022/11/02 17:08:43 - mmengine - INFO - Epoch(val) [460][295/500] eta: 0:00:08 time: 0.0385 data_time: 0.0022 memory: 1008 2022/11/02 17:08:43 - mmengine - INFO - Epoch(val) [460][300/500] eta: 0:00:07 time: 0.0375 data_time: 0.0023 memory: 1008 2022/11/02 17:08:43 - mmengine - INFO - Epoch(val) [460][305/500] eta: 0:00:07 time: 0.0357 data_time: 0.0023 memory: 1008 2022/11/02 17:08:43 - mmengine - INFO - Epoch(val) [460][310/500] eta: 0:00:07 time: 0.0389 data_time: 0.0023 memory: 1008 2022/11/02 17:08:43 - mmengine - INFO - Epoch(val) [460][315/500] eta: 0:00:07 time: 0.0422 data_time: 0.0024 memory: 1008 2022/11/02 17:08:44 - mmengine - INFO - Epoch(val) [460][320/500] eta: 0:00:06 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/02 17:08:44 - mmengine - INFO - Epoch(val) [460][325/500] eta: 0:00:06 time: 0.0473 data_time: 0.0023 memory: 1008 2022/11/02 17:08:44 - mmengine - INFO - Epoch(val) [460][330/500] eta: 0:00:08 time: 0.0471 data_time: 0.0022 memory: 1008 2022/11/02 17:08:44 - mmengine - INFO - Epoch(val) [460][335/500] eta: 0:00:08 time: 0.0351 data_time: 0.0022 memory: 1008 2022/11/02 17:08:45 - mmengine - INFO - Epoch(val) [460][340/500] eta: 0:00:07 time: 0.0485 data_time: 0.0023 memory: 1008 2022/11/02 17:08:45 - mmengine - INFO - Epoch(val) [460][345/500] eta: 0:00:07 time: 0.0506 data_time: 0.0021 memory: 1008 2022/11/02 17:08:45 - mmengine - INFO - Epoch(val) [460][350/500] eta: 0:00:06 time: 0.0440 data_time: 0.0023 memory: 1008 2022/11/02 17:08:45 - mmengine - INFO - Epoch(val) [460][355/500] eta: 0:00:06 time: 0.0413 data_time: 0.0025 memory: 1008 2022/11/02 17:08:45 - mmengine - INFO - Epoch(val) [460][360/500] eta: 0:00:05 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/02 17:08:46 - mmengine - INFO - Epoch(val) [460][365/500] eta: 0:00:05 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/02 17:08:46 - mmengine - INFO - Epoch(val) [460][370/500] eta: 0:00:04 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 17:08:46 - mmengine - INFO - Epoch(val) [460][375/500] eta: 0:00:04 time: 0.0376 data_time: 0.0029 memory: 1008 2022/11/02 17:08:46 - mmengine - INFO - Epoch(val) [460][380/500] eta: 0:00:04 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 17:08:46 - mmengine - INFO - Epoch(val) [460][385/500] eta: 0:00:04 time: 0.0391 data_time: 0.0023 memory: 1008 2022/11/02 17:08:47 - mmengine - INFO - Epoch(val) [460][390/500] eta: 0:00:04 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/02 17:08:47 - mmengine - INFO - Epoch(val) [460][395/500] eta: 0:00:04 time: 0.0382 data_time: 0.0022 memory: 1008 2022/11/02 17:08:47 - mmengine - INFO - Epoch(val) [460][400/500] eta: 0:00:04 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 17:08:47 - mmengine - INFO - Epoch(val) [460][405/500] eta: 0:00:04 time: 0.0430 data_time: 0.0029 memory: 1008 2022/11/02 17:08:47 - mmengine - INFO - Epoch(val) [460][410/500] eta: 0:00:03 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 17:08:48 - mmengine - INFO - Epoch(val) [460][415/500] eta: 0:00:03 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/02 17:08:48 - mmengine - INFO - Epoch(val) [460][420/500] eta: 0:00:03 time: 0.0382 data_time: 0.0027 memory: 1008 2022/11/02 17:08:48 - mmengine - INFO - Epoch(val) [460][425/500] eta: 0:00:03 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 17:08:48 - mmengine - INFO - Epoch(val) [460][430/500] eta: 0:00:02 time: 0.0401 data_time: 0.0027 memory: 1008 2022/11/02 17:08:48 - mmengine - INFO - Epoch(val) [460][435/500] eta: 0:00:02 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/02 17:08:49 - mmengine - INFO - Epoch(val) [460][440/500] eta: 0:00:02 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/02 17:08:49 - mmengine - INFO - Epoch(val) [460][445/500] eta: 0:00:02 time: 0.0459 data_time: 0.0037 memory: 1008 2022/11/02 17:08:49 - mmengine - INFO - Epoch(val) [460][450/500] eta: 0:00:02 time: 0.0493 data_time: 0.0039 memory: 1008 2022/11/02 17:08:49 - mmengine - INFO - Epoch(val) [460][455/500] eta: 0:00:02 time: 0.0449 data_time: 0.0031 memory: 1008 2022/11/02 17:08:49 - mmengine - INFO - Epoch(val) [460][460/500] eta: 0:00:01 time: 0.0402 data_time: 0.0032 memory: 1008 2022/11/02 17:08:50 - mmengine - INFO - Epoch(val) [460][465/500] eta: 0:00:01 time: 0.0376 data_time: 0.0030 memory: 1008 2022/11/02 17:08:50 - mmengine - INFO - Epoch(val) [460][470/500] eta: 0:00:01 time: 0.0389 data_time: 0.0027 memory: 1008 2022/11/02 17:08:50 - mmengine - INFO - Epoch(val) [460][475/500] eta: 0:00:01 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/02 17:08:50 - mmengine - INFO - Epoch(val) [460][480/500] eta: 0:00:00 time: 0.0381 data_time: 0.0027 memory: 1008 2022/11/02 17:08:50 - mmengine - INFO - Epoch(val) [460][485/500] eta: 0:00:00 time: 0.0375 data_time: 0.0024 memory: 1008 2022/11/02 17:08:51 - mmengine - INFO - Epoch(val) [460][490/500] eta: 0:00:00 time: 0.0420 data_time: 0.0026 memory: 1008 2022/11/02 17:08:51 - mmengine - INFO - Epoch(val) [460][495/500] eta: 0:00:00 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 17:08:51 - mmengine - INFO - Epoch(val) [460][500/500] eta: 0:00:00 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/02 17:08:51 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8247, precision: 0.6882, hmean: 0.7503 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8247, precision: 0.7425, hmean: 0.7815 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8233, precision: 0.7848, hmean: 0.8036 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8180, precision: 0.8224, hmean: 0.8202 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7824, precision: 0.8648, hmean: 0.8215 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5185, precision: 0.9253, hmean: 0.6646 2022/11/02 17:08:51 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0246, precision: 0.9273, hmean: 0.0478 2022/11/02 17:08:51 - mmengine - INFO - Epoch(val) [460][500/500] icdar/precision: 0.8648 icdar/recall: 0.7824 icdar/hmean: 0.8215 2022/11/02 17:08:57 - mmengine - INFO - Epoch(train) [461][5/63] lr: 1.3993e-03 eta: 0:00:00 time: 0.9397 data_time: 0.2147 memory: 14901 loss: 1.4823 loss_prob: 0.8098 loss_thr: 0.5369 loss_db: 0.1356 2022/11/02 17:09:00 - mmengine - INFO - Epoch(train) [461][10/63] lr: 1.3993e-03 eta: 7:37:12 time: 0.8930 data_time: 0.2139 memory: 14901 loss: 1.3673 loss_prob: 0.7358 loss_thr: 0.5075 loss_db: 0.1240 2022/11/02 17:09:03 - mmengine - INFO - Epoch(train) [461][15/63] lr: 1.3993e-03 eta: 7:37:12 time: 0.5969 data_time: 0.0119 memory: 14901 loss: 1.3525 loss_prob: 0.7205 loss_thr: 0.5086 loss_db: 0.1235 2022/11/02 17:09:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:09:06 - mmengine - INFO - Epoch(train) [461][20/63] lr: 1.3993e-03 eta: 7:37:06 time: 0.5885 data_time: 0.0137 memory: 14901 loss: 1.3660 loss_prob: 0.7354 loss_thr: 0.5050 loss_db: 0.1256 2022/11/02 17:09:08 - mmengine - INFO - Epoch(train) [461][25/63] lr: 1.3993e-03 eta: 7:37:06 time: 0.5519 data_time: 0.0317 memory: 14901 loss: 1.4752 loss_prob: 0.8063 loss_thr: 0.5340 loss_db: 0.1349 2022/11/02 17:09:11 - mmengine - INFO - Epoch(train) [461][30/63] lr: 1.3993e-03 eta: 7:36:59 time: 0.5288 data_time: 0.0370 memory: 14901 loss: 1.5308 loss_prob: 0.8599 loss_thr: 0.5336 loss_db: 0.1372 2022/11/02 17:09:14 - mmengine - INFO - Epoch(train) [461][35/63] lr: 1.3993e-03 eta: 7:36:59 time: 0.5398 data_time: 0.0170 memory: 14901 loss: 1.3445 loss_prob: 0.7457 loss_thr: 0.4776 loss_db: 0.1212 2022/11/02 17:09:16 - mmengine - INFO - Epoch(train) [461][40/63] lr: 1.3993e-03 eta: 7:36:52 time: 0.5087 data_time: 0.0116 memory: 14901 loss: 1.6823 loss_prob: 1.0254 loss_thr: 0.5060 loss_db: 0.1508 2022/11/02 17:09:19 - mmengine - INFO - Epoch(train) [461][45/63] lr: 1.3993e-03 eta: 7:36:52 time: 0.4911 data_time: 0.0113 memory: 14901 loss: 1.7910 loss_prob: 1.0916 loss_thr: 0.5369 loss_db: 0.1625 2022/11/02 17:09:21 - mmengine - INFO - Epoch(train) [461][50/63] lr: 1.3993e-03 eta: 7:36:45 time: 0.5148 data_time: 0.0259 memory: 14901 loss: 1.3792 loss_prob: 0.7500 loss_thr: 0.4989 loss_db: 0.1304 2022/11/02 17:09:24 - mmengine - INFO - Epoch(train) [461][55/63] lr: 1.3993e-03 eta: 7:36:45 time: 0.5023 data_time: 0.0278 memory: 14901 loss: 1.3335 loss_prob: 0.7216 loss_thr: 0.4860 loss_db: 0.1260 2022/11/02 17:09:26 - mmengine - INFO - Epoch(train) [461][60/63] lr: 1.3993e-03 eta: 7:36:37 time: 0.4756 data_time: 0.0132 memory: 14901 loss: 1.3581 loss_prob: 0.7394 loss_thr: 0.4925 loss_db: 0.1263 2022/11/02 17:09:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:09:32 - mmengine - INFO - Epoch(train) [462][5/63] lr: 1.3976e-03 eta: 7:36:37 time: 0.7038 data_time: 0.2406 memory: 14901 loss: 1.3200 loss_prob: 0.7208 loss_thr: 0.4813 loss_db: 0.1178 2022/11/02 17:09:36 - mmengine - INFO - Epoch(train) [462][10/63] lr: 1.3976e-03 eta: 7:36:31 time: 0.8288 data_time: 0.2408 memory: 14901 loss: 1.4046 loss_prob: 0.7834 loss_thr: 0.4946 loss_db: 0.1266 2022/11/02 17:09:39 - mmengine - INFO - Epoch(train) [462][15/63] lr: 1.3976e-03 eta: 7:36:31 time: 0.6508 data_time: 0.0151 memory: 14901 loss: 1.3519 loss_prob: 0.7448 loss_thr: 0.4832 loss_db: 0.1240 2022/11/02 17:09:42 - mmengine - INFO - Epoch(train) [462][20/63] lr: 1.3976e-03 eta: 7:36:26 time: 0.6802 data_time: 0.0149 memory: 14901 loss: 1.3661 loss_prob: 0.7490 loss_thr: 0.4918 loss_db: 0.1252 2022/11/02 17:09:45 - mmengine - INFO - Epoch(train) [462][25/63] lr: 1.3976e-03 eta: 7:36:26 time: 0.6555 data_time: 0.0393 memory: 14901 loss: 1.3691 loss_prob: 0.7585 loss_thr: 0.4859 loss_db: 0.1247 2022/11/02 17:09:48 - mmengine - INFO - Epoch(train) [462][30/63] lr: 1.3976e-03 eta: 7:36:20 time: 0.5519 data_time: 0.0454 memory: 14901 loss: 1.3405 loss_prob: 0.7291 loss_thr: 0.4896 loss_db: 0.1217 2022/11/02 17:09:50 - mmengine - INFO - Epoch(train) [462][35/63] lr: 1.3976e-03 eta: 7:36:20 time: 0.5123 data_time: 0.0175 memory: 14901 loss: 1.2990 loss_prob: 0.6943 loss_thr: 0.4869 loss_db: 0.1178 2022/11/02 17:09:53 - mmengine - INFO - Epoch(train) [462][40/63] lr: 1.3976e-03 eta: 7:36:12 time: 0.5025 data_time: 0.0097 memory: 14901 loss: 1.2149 loss_prob: 0.6384 loss_thr: 0.4677 loss_db: 0.1088 2022/11/02 17:09:56 - mmengine - INFO - Epoch(train) [462][45/63] lr: 1.3976e-03 eta: 7:36:12 time: 0.5222 data_time: 0.0136 memory: 14901 loss: 1.2540 loss_prob: 0.6634 loss_thr: 0.4804 loss_db: 0.1103 2022/11/02 17:09:58 - mmengine - INFO - Epoch(train) [462][50/63] lr: 1.3976e-03 eta: 7:36:06 time: 0.5339 data_time: 0.0273 memory: 14901 loss: 1.2899 loss_prob: 0.6938 loss_thr: 0.4809 loss_db: 0.1153 2022/11/02 17:10:01 - mmengine - INFO - Epoch(train) [462][55/63] lr: 1.3976e-03 eta: 7:36:06 time: 0.5683 data_time: 0.0272 memory: 14901 loss: 1.3475 loss_prob: 0.7497 loss_thr: 0.4756 loss_db: 0.1222 2022/11/02 17:10:04 - mmengine - INFO - Epoch(train) [462][60/63] lr: 1.3976e-03 eta: 7:35:59 time: 0.5539 data_time: 0.0119 memory: 14901 loss: 1.3726 loss_prob: 0.7670 loss_thr: 0.4796 loss_db: 0.1259 2022/11/02 17:10:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:10:11 - mmengine - INFO - Epoch(train) [463][5/63] lr: 1.3959e-03 eta: 7:35:59 time: 0.8402 data_time: 0.2516 memory: 14901 loss: 1.3697 loss_prob: 0.7396 loss_thr: 0.5043 loss_db: 0.1258 2022/11/02 17:10:14 - mmengine - INFO - Epoch(train) [463][10/63] lr: 1.3959e-03 eta: 7:35:53 time: 0.8790 data_time: 0.2550 memory: 14901 loss: 1.3309 loss_prob: 0.7163 loss_thr: 0.4945 loss_db: 0.1201 2022/11/02 17:10:17 - mmengine - INFO - Epoch(train) [463][15/63] lr: 1.3959e-03 eta: 7:35:53 time: 0.5723 data_time: 0.0143 memory: 14901 loss: 1.2723 loss_prob: 0.6869 loss_thr: 0.4702 loss_db: 0.1152 2022/11/02 17:10:21 - mmengine - INFO - Epoch(train) [463][20/63] lr: 1.3959e-03 eta: 7:35:49 time: 0.7107 data_time: 0.0108 memory: 14901 loss: 1.3076 loss_prob: 0.7059 loss_thr: 0.4812 loss_db: 0.1205 2022/11/02 17:10:24 - mmengine - INFO - Epoch(train) [463][25/63] lr: 1.3959e-03 eta: 7:35:49 time: 0.7392 data_time: 0.0295 memory: 14901 loss: 1.3853 loss_prob: 0.7306 loss_thr: 0.5286 loss_db: 0.1261 2022/11/02 17:10:28 - mmengine - INFO - Epoch(train) [463][30/63] lr: 1.3959e-03 eta: 7:35:44 time: 0.6302 data_time: 0.0384 memory: 14901 loss: 1.4048 loss_prob: 0.7499 loss_thr: 0.5261 loss_db: 0.1287 2022/11/02 17:10:30 - mmengine - INFO - Epoch(train) [463][35/63] lr: 1.3959e-03 eta: 7:35:44 time: 0.6082 data_time: 0.0197 memory: 14901 loss: 1.4388 loss_prob: 0.7919 loss_thr: 0.5128 loss_db: 0.1341 2022/11/02 17:10:33 - mmengine - INFO - Epoch(train) [463][40/63] lr: 1.3959e-03 eta: 7:35:37 time: 0.5263 data_time: 0.0119 memory: 14901 loss: 1.5311 loss_prob: 0.8573 loss_thr: 0.5317 loss_db: 0.1421 2022/11/02 17:10:35 - mmengine - INFO - Epoch(train) [463][45/63] lr: 1.3959e-03 eta: 7:35:37 time: 0.5017 data_time: 0.0101 memory: 14901 loss: 1.3997 loss_prob: 0.7708 loss_thr: 0.5013 loss_db: 0.1276 2022/11/02 17:10:39 - mmengine - INFO - Epoch(train) [463][50/63] lr: 1.3959e-03 eta: 7:35:32 time: 0.5970 data_time: 0.0242 memory: 14901 loss: 1.2774 loss_prob: 0.6881 loss_thr: 0.4751 loss_db: 0.1141 2022/11/02 17:10:41 - mmengine - INFO - Epoch(train) [463][55/63] lr: 1.3959e-03 eta: 7:35:32 time: 0.6132 data_time: 0.0256 memory: 14901 loss: 1.3208 loss_prob: 0.7115 loss_thr: 0.4921 loss_db: 0.1172 2022/11/02 17:10:44 - mmengine - INFO - Epoch(train) [463][60/63] lr: 1.3959e-03 eta: 7:35:25 time: 0.5577 data_time: 0.0141 memory: 14901 loss: 1.2728 loss_prob: 0.6789 loss_thr: 0.4781 loss_db: 0.1158 2022/11/02 17:10:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:10:52 - mmengine - INFO - Epoch(train) [464][5/63] lr: 1.3942e-03 eta: 7:35:25 time: 0.8466 data_time: 0.2556 memory: 14901 loss: 1.2591 loss_prob: 0.6767 loss_thr: 0.4671 loss_db: 0.1153 2022/11/02 17:10:54 - mmengine - INFO - Epoch(train) [464][10/63] lr: 1.3942e-03 eta: 7:35:19 time: 0.8433 data_time: 0.2553 memory: 14901 loss: 1.3186 loss_prob: 0.7092 loss_thr: 0.4888 loss_db: 0.1205 2022/11/02 17:10:57 - mmengine - INFO - Epoch(train) [464][15/63] lr: 1.3942e-03 eta: 7:35:19 time: 0.5486 data_time: 0.0084 memory: 14901 loss: 1.4209 loss_prob: 0.7754 loss_thr: 0.5110 loss_db: 0.1346 2022/11/02 17:11:00 - mmengine - INFO - Epoch(train) [464][20/63] lr: 1.3942e-03 eta: 7:35:12 time: 0.5257 data_time: 0.0083 memory: 14901 loss: 1.3664 loss_prob: 0.7383 loss_thr: 0.5013 loss_db: 0.1268 2022/11/02 17:11:03 - mmengine - INFO - Epoch(train) [464][25/63] lr: 1.3942e-03 eta: 7:35:12 time: 0.5522 data_time: 0.0423 memory: 14901 loss: 1.3129 loss_prob: 0.7036 loss_thr: 0.4937 loss_db: 0.1156 2022/11/02 17:11:05 - mmengine - INFO - Epoch(train) [464][30/63] lr: 1.3942e-03 eta: 7:35:06 time: 0.5670 data_time: 0.0465 memory: 14901 loss: 1.3182 loss_prob: 0.7119 loss_thr: 0.4878 loss_db: 0.1185 2022/11/02 17:11:09 - mmengine - INFO - Epoch(train) [464][35/63] lr: 1.3942e-03 eta: 7:35:06 time: 0.6467 data_time: 0.0100 memory: 14901 loss: 1.3917 loss_prob: 0.7545 loss_thr: 0.5076 loss_db: 0.1296 2022/11/02 17:11:12 - mmengine - INFO - Epoch(train) [464][40/63] lr: 1.3942e-03 eta: 7:35:02 time: 0.6971 data_time: 0.0080 memory: 14901 loss: 1.4093 loss_prob: 0.7655 loss_thr: 0.5119 loss_db: 0.1319 2022/11/02 17:11:15 - mmengine - INFO - Epoch(train) [464][45/63] lr: 1.3942e-03 eta: 7:35:02 time: 0.6229 data_time: 0.0113 memory: 14901 loss: 1.3626 loss_prob: 0.7353 loss_thr: 0.5007 loss_db: 0.1265 2022/11/02 17:11:18 - mmengine - INFO - Epoch(train) [464][50/63] lr: 1.3942e-03 eta: 7:34:56 time: 0.6107 data_time: 0.0440 memory: 14901 loss: 1.3456 loss_prob: 0.7232 loss_thr: 0.4979 loss_db: 0.1245 2022/11/02 17:11:21 - mmengine - INFO - Epoch(train) [464][55/63] lr: 1.3942e-03 eta: 7:34:56 time: 0.6146 data_time: 0.0431 memory: 14901 loss: 1.4127 loss_prob: 0.7822 loss_thr: 0.4991 loss_db: 0.1313 2022/11/02 17:11:24 - mmengine - INFO - Epoch(train) [464][60/63] lr: 1.3942e-03 eta: 7:34:50 time: 0.5600 data_time: 0.0113 memory: 14901 loss: 1.5267 loss_prob: 0.8463 loss_thr: 0.5362 loss_db: 0.1443 2022/11/02 17:11:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:11:30 - mmengine - INFO - Epoch(train) [465][5/63] lr: 1.3925e-03 eta: 7:34:50 time: 0.7420 data_time: 0.2650 memory: 14901 loss: 1.4403 loss_prob: 0.7878 loss_thr: 0.5219 loss_db: 0.1306 2022/11/02 17:11:33 - mmengine - INFO - Epoch(train) [465][10/63] lr: 1.3925e-03 eta: 7:34:42 time: 0.7732 data_time: 0.2650 memory: 14901 loss: 1.3447 loss_prob: 0.7314 loss_thr: 0.4906 loss_db: 0.1228 2022/11/02 17:11:36 - mmengine - INFO - Epoch(train) [465][15/63] lr: 1.3925e-03 eta: 7:34:42 time: 0.5213 data_time: 0.0059 memory: 14901 loss: 1.4599 loss_prob: 0.8123 loss_thr: 0.5079 loss_db: 0.1398 2022/11/02 17:11:39 - mmengine - INFO - Epoch(train) [465][20/63] lr: 1.3925e-03 eta: 7:34:36 time: 0.5593 data_time: 0.0095 memory: 14901 loss: 1.5288 loss_prob: 0.8616 loss_thr: 0.5231 loss_db: 0.1441 2022/11/02 17:11:41 - mmengine - INFO - Epoch(train) [465][25/63] lr: 1.3925e-03 eta: 7:34:36 time: 0.5573 data_time: 0.0293 memory: 14901 loss: 1.4286 loss_prob: 0.7932 loss_thr: 0.5076 loss_db: 0.1278 2022/11/02 17:11:44 - mmengine - INFO - Epoch(train) [465][30/63] lr: 1.3925e-03 eta: 7:34:29 time: 0.5609 data_time: 0.0352 memory: 14901 loss: 1.4066 loss_prob: 0.7718 loss_thr: 0.5080 loss_db: 0.1268 2022/11/02 17:11:47 - mmengine - INFO - Epoch(train) [465][35/63] lr: 1.3925e-03 eta: 7:34:29 time: 0.5647 data_time: 0.0213 memory: 14901 loss: 1.3581 loss_prob: 0.7366 loss_thr: 0.4943 loss_db: 0.1273 2022/11/02 17:11:50 - mmengine - INFO - Epoch(train) [465][40/63] lr: 1.3925e-03 eta: 7:34:24 time: 0.6148 data_time: 0.0125 memory: 14901 loss: 1.4029 loss_prob: 0.7557 loss_thr: 0.5183 loss_db: 0.1289 2022/11/02 17:11:54 - mmengine - INFO - Epoch(train) [465][45/63] lr: 1.3925e-03 eta: 7:34:24 time: 0.7193 data_time: 0.0080 memory: 14901 loss: 1.4373 loss_prob: 0.7851 loss_thr: 0.5191 loss_db: 0.1331 2022/11/02 17:11:57 - mmengine - INFO - Epoch(train) [465][50/63] lr: 1.3925e-03 eta: 7:34:19 time: 0.6246 data_time: 0.0203 memory: 14901 loss: 1.4339 loss_prob: 0.7920 loss_thr: 0.5059 loss_db: 0.1360 2022/11/02 17:11:59 - mmengine - INFO - Epoch(train) [465][55/63] lr: 1.3925e-03 eta: 7:34:19 time: 0.5073 data_time: 0.0238 memory: 14901 loss: 1.4108 loss_prob: 0.7783 loss_thr: 0.5018 loss_db: 0.1307 2022/11/02 17:12:02 - mmengine - INFO - Epoch(train) [465][60/63] lr: 1.3925e-03 eta: 7:34:12 time: 0.5444 data_time: 0.0165 memory: 14901 loss: 1.3528 loss_prob: 0.7467 loss_thr: 0.4823 loss_db: 0.1238 2022/11/02 17:12:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:12:10 - mmengine - INFO - Epoch(train) [466][5/63] lr: 1.3908e-03 eta: 7:34:12 time: 0.8551 data_time: 0.2731 memory: 14901 loss: 1.3299 loss_prob: 0.7270 loss_thr: 0.4775 loss_db: 0.1254 2022/11/02 17:12:13 - mmengine - INFO - Epoch(train) [466][10/63] lr: 1.3908e-03 eta: 7:34:08 time: 0.9617 data_time: 0.2735 memory: 14901 loss: 1.3563 loss_prob: 0.7427 loss_thr: 0.4893 loss_db: 0.1242 2022/11/02 17:12:16 - mmengine - INFO - Epoch(train) [466][15/63] lr: 1.3908e-03 eta: 7:34:08 time: 0.6027 data_time: 0.0107 memory: 14901 loss: 1.3421 loss_prob: 0.7308 loss_thr: 0.4886 loss_db: 0.1226 2022/11/02 17:12:19 - mmengine - INFO - Epoch(train) [466][20/63] lr: 1.3908e-03 eta: 7:34:02 time: 0.6068 data_time: 0.0116 memory: 14901 loss: 1.3150 loss_prob: 0.6973 loss_thr: 0.4982 loss_db: 0.1196 2022/11/02 17:12:22 - mmengine - INFO - Epoch(train) [466][25/63] lr: 1.3908e-03 eta: 7:34:02 time: 0.5924 data_time: 0.0242 memory: 14901 loss: 1.3552 loss_prob: 0.7202 loss_thr: 0.5118 loss_db: 0.1233 2022/11/02 17:12:25 - mmengine - INFO - Epoch(train) [466][30/63] lr: 1.3908e-03 eta: 7:33:56 time: 0.5651 data_time: 0.0352 memory: 14901 loss: 1.3614 loss_prob: 0.7429 loss_thr: 0.4916 loss_db: 0.1269 2022/11/02 17:12:27 - mmengine - INFO - Epoch(train) [466][35/63] lr: 1.3908e-03 eta: 7:33:56 time: 0.5818 data_time: 0.0209 memory: 14901 loss: 1.3342 loss_prob: 0.7369 loss_thr: 0.4729 loss_db: 0.1244 2022/11/02 17:12:30 - mmengine - INFO - Epoch(train) [466][40/63] lr: 1.3908e-03 eta: 7:33:49 time: 0.5687 data_time: 0.0082 memory: 14901 loss: 1.4223 loss_prob: 0.7865 loss_thr: 0.5037 loss_db: 0.1321 2022/11/02 17:12:33 - mmengine - INFO - Epoch(train) [466][45/63] lr: 1.3908e-03 eta: 7:33:49 time: 0.5148 data_time: 0.0078 memory: 14901 loss: 1.4641 loss_prob: 0.7908 loss_thr: 0.5365 loss_db: 0.1367 2022/11/02 17:12:35 - mmengine - INFO - Epoch(train) [466][50/63] lr: 1.3908e-03 eta: 7:33:42 time: 0.5050 data_time: 0.0234 memory: 14901 loss: 1.5197 loss_prob: 0.8630 loss_thr: 0.5068 loss_db: 0.1498 2022/11/02 17:12:38 - mmengine - INFO - Epoch(train) [466][55/63] lr: 1.3908e-03 eta: 7:33:42 time: 0.5675 data_time: 0.0256 memory: 14901 loss: 1.5427 loss_prob: 0.8901 loss_thr: 0.5030 loss_db: 0.1497 2022/11/02 17:12:41 - mmengine - INFO - Epoch(train) [466][60/63] lr: 1.3908e-03 eta: 7:33:36 time: 0.5427 data_time: 0.0103 memory: 14901 loss: 1.4905 loss_prob: 0.8244 loss_thr: 0.5283 loss_db: 0.1378 2022/11/02 17:12:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:12:48 - mmengine - INFO - Epoch(train) [467][5/63] lr: 1.3891e-03 eta: 7:33:36 time: 0.8540 data_time: 0.2770 memory: 14901 loss: 1.5980 loss_prob: 0.9045 loss_thr: 0.5423 loss_db: 0.1512 2022/11/02 17:12:51 - mmengine - INFO - Epoch(train) [467][10/63] lr: 1.3891e-03 eta: 7:33:31 time: 0.9259 data_time: 0.2825 memory: 14901 loss: 1.4728 loss_prob: 0.8034 loss_thr: 0.5332 loss_db: 0.1361 2022/11/02 17:12:54 - mmengine - INFO - Epoch(train) [467][15/63] lr: 1.3891e-03 eta: 7:33:31 time: 0.5682 data_time: 0.0174 memory: 14901 loss: 1.6323 loss_prob: 0.9302 loss_thr: 0.5537 loss_db: 0.1484 2022/11/02 17:12:57 - mmengine - INFO - Epoch(train) [467][20/63] lr: 1.3891e-03 eta: 7:33:24 time: 0.5345 data_time: 0.0094 memory: 14901 loss: 1.5101 loss_prob: 0.8487 loss_thr: 0.5253 loss_db: 0.1360 2022/11/02 17:13:00 - mmengine - INFO - Epoch(train) [467][25/63] lr: 1.3891e-03 eta: 7:33:24 time: 0.6005 data_time: 0.0304 memory: 14901 loss: 1.3270 loss_prob: 0.7075 loss_thr: 0.5006 loss_db: 0.1190 2022/11/02 17:13:03 - mmengine - INFO - Epoch(train) [467][30/63] lr: 1.3891e-03 eta: 7:33:18 time: 0.6003 data_time: 0.0402 memory: 14901 loss: 1.4798 loss_prob: 0.8180 loss_thr: 0.5249 loss_db: 0.1368 2022/11/02 17:13:05 - mmengine - INFO - Epoch(train) [467][35/63] lr: 1.3891e-03 eta: 7:33:18 time: 0.5217 data_time: 0.0167 memory: 14901 loss: 1.5225 loss_prob: 0.8556 loss_thr: 0.5240 loss_db: 0.1430 2022/11/02 17:13:08 - mmengine - INFO - Epoch(train) [467][40/63] lr: 1.3891e-03 eta: 7:33:11 time: 0.5352 data_time: 0.0067 memory: 14901 loss: 1.4618 loss_prob: 0.8145 loss_thr: 0.5123 loss_db: 0.1350 2022/11/02 17:13:11 - mmengine - INFO - Epoch(train) [467][45/63] lr: 1.3891e-03 eta: 7:33:11 time: 0.5580 data_time: 0.0080 memory: 14901 loss: 1.3992 loss_prob: 0.7661 loss_thr: 0.5052 loss_db: 0.1279 2022/11/02 17:13:14 - mmengine - INFO - Epoch(train) [467][50/63] lr: 1.3891e-03 eta: 7:33:05 time: 0.5587 data_time: 0.0267 memory: 14901 loss: 1.4394 loss_prob: 0.8019 loss_thr: 0.5023 loss_db: 0.1352 2022/11/02 17:13:17 - mmengine - INFO - Epoch(train) [467][55/63] lr: 1.3891e-03 eta: 7:33:05 time: 0.5844 data_time: 0.0295 memory: 14901 loss: 1.4975 loss_prob: 0.8500 loss_thr: 0.5032 loss_db: 0.1443 2022/11/02 17:13:19 - mmengine - INFO - Epoch(train) [467][60/63] lr: 1.3891e-03 eta: 7:32:59 time: 0.5543 data_time: 0.0104 memory: 14901 loss: 1.4686 loss_prob: 0.8255 loss_thr: 0.5056 loss_db: 0.1375 2022/11/02 17:13:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:13:27 - mmengine - INFO - Epoch(train) [468][5/63] lr: 1.3874e-03 eta: 7:32:59 time: 0.9267 data_time: 0.2014 memory: 14901 loss: 1.4190 loss_prob: 0.7716 loss_thr: 0.5155 loss_db: 0.1319 2022/11/02 17:13:30 - mmengine - INFO - Epoch(train) [468][10/63] lr: 1.3874e-03 eta: 7:32:53 time: 0.9059 data_time: 0.2045 memory: 14901 loss: 1.3605 loss_prob: 0.7466 loss_thr: 0.4870 loss_db: 0.1269 2022/11/02 17:13:33 - mmengine - INFO - Epoch(train) [468][15/63] lr: 1.3874e-03 eta: 7:32:53 time: 0.6041 data_time: 0.0170 memory: 14901 loss: 1.4494 loss_prob: 0.8181 loss_thr: 0.5009 loss_db: 0.1305 2022/11/02 17:13:36 - mmengine - INFO - Epoch(train) [468][20/63] lr: 1.3874e-03 eta: 7:32:47 time: 0.5537 data_time: 0.0113 memory: 14901 loss: 1.6023 loss_prob: 0.9383 loss_thr: 0.5217 loss_db: 0.1423 2022/11/02 17:13:39 - mmengine - INFO - Epoch(train) [468][25/63] lr: 1.3874e-03 eta: 7:32:47 time: 0.5754 data_time: 0.0223 memory: 14901 loss: 1.5544 loss_prob: 0.8987 loss_thr: 0.5104 loss_db: 0.1453 2022/11/02 17:13:42 - mmengine - INFO - Epoch(train) [468][30/63] lr: 1.3874e-03 eta: 7:32:41 time: 0.5863 data_time: 0.0426 memory: 14901 loss: 1.4954 loss_prob: 0.8262 loss_thr: 0.5286 loss_db: 0.1407 2022/11/02 17:13:45 - mmengine - INFO - Epoch(train) [468][35/63] lr: 1.3874e-03 eta: 7:32:41 time: 0.5519 data_time: 0.0296 memory: 14901 loss: 1.5083 loss_prob: 0.8236 loss_thr: 0.5469 loss_db: 0.1378 2022/11/02 17:13:48 - mmengine - INFO - Epoch(train) [468][40/63] lr: 1.3874e-03 eta: 7:32:35 time: 0.5808 data_time: 0.0125 memory: 14901 loss: 1.5011 loss_prob: 0.8269 loss_thr: 0.5354 loss_db: 0.1388 2022/11/02 17:13:50 - mmengine - INFO - Epoch(train) [468][45/63] lr: 1.3874e-03 eta: 7:32:35 time: 0.5421 data_time: 0.0087 memory: 14901 loss: 1.5743 loss_prob: 0.8903 loss_thr: 0.5376 loss_db: 0.1463 2022/11/02 17:13:53 - mmengine - INFO - Epoch(train) [468][50/63] lr: 1.3874e-03 eta: 7:32:29 time: 0.5723 data_time: 0.0195 memory: 14901 loss: 1.5621 loss_prob: 0.8828 loss_thr: 0.5329 loss_db: 0.1464 2022/11/02 17:13:56 - mmengine - INFO - Epoch(train) [468][55/63] lr: 1.3874e-03 eta: 7:32:29 time: 0.6025 data_time: 0.0303 memory: 14901 loss: 1.4793 loss_prob: 0.8174 loss_thr: 0.5241 loss_db: 0.1378 2022/11/02 17:13:59 - mmengine - INFO - Epoch(train) [468][60/63] lr: 1.3874e-03 eta: 7:32:23 time: 0.5743 data_time: 0.0187 memory: 14901 loss: 1.4601 loss_prob: 0.7937 loss_thr: 0.5322 loss_db: 0.1343 2022/11/02 17:14:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:14:06 - mmengine - INFO - Epoch(train) [469][5/63] lr: 1.3857e-03 eta: 7:32:23 time: 0.8392 data_time: 0.2456 memory: 14901 loss: 1.4061 loss_prob: 0.7704 loss_thr: 0.5038 loss_db: 0.1318 2022/11/02 17:14:10 - mmengine - INFO - Epoch(train) [469][10/63] lr: 1.3857e-03 eta: 7:32:17 time: 0.9236 data_time: 0.2538 memory: 14901 loss: 1.4215 loss_prob: 0.7852 loss_thr: 0.5053 loss_db: 0.1310 2022/11/02 17:14:13 - mmengine - INFO - Epoch(train) [469][15/63] lr: 1.3857e-03 eta: 7:32:17 time: 0.6232 data_time: 0.0208 memory: 14901 loss: 1.4945 loss_prob: 0.8214 loss_thr: 0.5361 loss_db: 0.1371 2022/11/02 17:14:16 - mmengine - INFO - Epoch(train) [469][20/63] lr: 1.3857e-03 eta: 7:32:12 time: 0.5917 data_time: 0.0120 memory: 14901 loss: 1.4500 loss_prob: 0.7958 loss_thr: 0.5191 loss_db: 0.1351 2022/11/02 17:14:18 - mmengine - INFO - Epoch(train) [469][25/63] lr: 1.3857e-03 eta: 7:32:12 time: 0.5388 data_time: 0.0214 memory: 14901 loss: 1.3592 loss_prob: 0.7481 loss_thr: 0.4831 loss_db: 0.1280 2022/11/02 17:14:21 - mmengine - INFO - Epoch(train) [469][30/63] lr: 1.3857e-03 eta: 7:32:05 time: 0.5387 data_time: 0.0380 memory: 14901 loss: 1.3480 loss_prob: 0.7355 loss_thr: 0.4864 loss_db: 0.1260 2022/11/02 17:14:24 - mmengine - INFO - Epoch(train) [469][35/63] lr: 1.3857e-03 eta: 7:32:05 time: 0.5506 data_time: 0.0307 memory: 14901 loss: 1.3294 loss_prob: 0.7297 loss_thr: 0.4754 loss_db: 0.1243 2022/11/02 17:14:26 - mmengine - INFO - Epoch(train) [469][40/63] lr: 1.3857e-03 eta: 7:31:58 time: 0.5357 data_time: 0.0168 memory: 14901 loss: 1.4169 loss_prob: 0.8039 loss_thr: 0.4793 loss_db: 0.1338 2022/11/02 17:14:30 - mmengine - INFO - Epoch(train) [469][45/63] lr: 1.3857e-03 eta: 7:31:58 time: 0.6129 data_time: 0.0121 memory: 14901 loss: 1.4730 loss_prob: 0.8281 loss_thr: 0.5054 loss_db: 0.1394 2022/11/02 17:14:33 - mmengine - INFO - Epoch(train) [469][50/63] lr: 1.3857e-03 eta: 7:31:53 time: 0.6620 data_time: 0.0228 memory: 14901 loss: 1.5404 loss_prob: 0.8861 loss_thr: 0.5104 loss_db: 0.1439 2022/11/02 17:14:35 - mmengine - INFO - Epoch(train) [469][55/63] lr: 1.3857e-03 eta: 7:31:53 time: 0.5598 data_time: 0.0214 memory: 14901 loss: 1.4629 loss_prob: 0.8353 loss_thr: 0.4950 loss_db: 0.1327 2022/11/02 17:14:38 - mmengine - INFO - Epoch(train) [469][60/63] lr: 1.3857e-03 eta: 7:31:47 time: 0.5324 data_time: 0.0108 memory: 14901 loss: 1.3859 loss_prob: 0.7599 loss_thr: 0.5001 loss_db: 0.1258 2022/11/02 17:14:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:14:45 - mmengine - INFO - Epoch(train) [470][5/63] lr: 1.3840e-03 eta: 7:31:47 time: 0.8309 data_time: 0.2399 memory: 14901 loss: 1.4519 loss_prob: 0.7967 loss_thr: 0.5216 loss_db: 0.1335 2022/11/02 17:14:48 - mmengine - INFO - Epoch(train) [470][10/63] lr: 1.3840e-03 eta: 7:31:39 time: 0.7886 data_time: 0.2442 memory: 14901 loss: 1.5112 loss_prob: 0.8444 loss_thr: 0.5307 loss_db: 0.1361 2022/11/02 17:14:51 - mmengine - INFO - Epoch(train) [470][15/63] lr: 1.3840e-03 eta: 7:31:39 time: 0.5381 data_time: 0.0178 memory: 14901 loss: 1.5299 loss_prob: 0.8563 loss_thr: 0.5342 loss_db: 0.1394 2022/11/02 17:14:54 - mmengine - INFO - Epoch(train) [470][20/63] lr: 1.3840e-03 eta: 7:31:34 time: 0.6110 data_time: 0.0148 memory: 14901 loss: 1.4259 loss_prob: 0.7780 loss_thr: 0.5140 loss_db: 0.1339 2022/11/02 17:14:57 - mmengine - INFO - Epoch(train) [470][25/63] lr: 1.3840e-03 eta: 7:31:34 time: 0.6478 data_time: 0.0376 memory: 14901 loss: 1.7389 loss_prob: 1.0370 loss_thr: 0.5301 loss_db: 0.1718 2022/11/02 17:15:00 - mmengine - INFO - Epoch(train) [470][30/63] lr: 1.3840e-03 eta: 7:31:28 time: 0.5708 data_time: 0.0442 memory: 14901 loss: 1.8521 loss_prob: 1.1186 loss_thr: 0.5527 loss_db: 0.1809 2022/11/02 17:15:03 - mmengine - INFO - Epoch(train) [470][35/63] lr: 1.3840e-03 eta: 7:31:28 time: 0.5485 data_time: 0.0232 memory: 14901 loss: 1.6472 loss_prob: 0.9429 loss_thr: 0.5514 loss_db: 0.1529 2022/11/02 17:15:05 - mmengine - INFO - Epoch(train) [470][40/63] lr: 1.3840e-03 eta: 7:31:21 time: 0.5400 data_time: 0.0149 memory: 14901 loss: 1.5977 loss_prob: 0.9181 loss_thr: 0.5317 loss_db: 0.1479 2022/11/02 17:15:08 - mmengine - INFO - Epoch(train) [470][45/63] lr: 1.3840e-03 eta: 7:31:21 time: 0.5082 data_time: 0.0121 memory: 14901 loss: 1.5229 loss_prob: 0.8514 loss_thr: 0.5294 loss_db: 0.1420 2022/11/02 17:15:10 - mmengine - INFO - Epoch(train) [470][50/63] lr: 1.3840e-03 eta: 7:31:14 time: 0.4994 data_time: 0.0251 memory: 14901 loss: 1.6839 loss_prob: 0.9578 loss_thr: 0.5636 loss_db: 0.1625 2022/11/02 17:15:13 - mmengine - INFO - Epoch(train) [470][55/63] lr: 1.3840e-03 eta: 7:31:14 time: 0.5114 data_time: 0.0255 memory: 14901 loss: 1.6663 loss_prob: 0.9480 loss_thr: 0.5560 loss_db: 0.1623 2022/11/02 17:15:16 - mmengine - INFO - Epoch(train) [470][60/63] lr: 1.3840e-03 eta: 7:31:07 time: 0.5360 data_time: 0.0171 memory: 14901 loss: 1.4902 loss_prob: 0.8215 loss_thr: 0.5282 loss_db: 0.1405 2022/11/02 17:15:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:15:22 - mmengine - INFO - Epoch(train) [471][5/63] lr: 1.3823e-03 eta: 7:31:07 time: 0.7754 data_time: 0.2458 memory: 14901 loss: 1.5647 loss_prob: 0.8666 loss_thr: 0.5526 loss_db: 0.1454 2022/11/02 17:15:25 - mmengine - INFO - Epoch(train) [471][10/63] lr: 1.3823e-03 eta: 7:31:00 time: 0.8080 data_time: 0.2460 memory: 14901 loss: 1.5152 loss_prob: 0.8400 loss_thr: 0.5368 loss_db: 0.1384 2022/11/02 17:15:28 - mmengine - INFO - Epoch(train) [471][15/63] lr: 1.3823e-03 eta: 7:31:00 time: 0.5836 data_time: 0.0083 memory: 14901 loss: 1.4980 loss_prob: 0.8287 loss_thr: 0.5296 loss_db: 0.1396 2022/11/02 17:15:31 - mmengine - INFO - Epoch(train) [471][20/63] lr: 1.3823e-03 eta: 7:30:54 time: 0.5973 data_time: 0.0077 memory: 14901 loss: 1.4791 loss_prob: 0.8106 loss_thr: 0.5316 loss_db: 0.1369 2022/11/02 17:15:34 - mmengine - INFO - Epoch(train) [471][25/63] lr: 1.3823e-03 eta: 7:30:54 time: 0.5522 data_time: 0.0268 memory: 14901 loss: 1.5192 loss_prob: 0.8370 loss_thr: 0.5428 loss_db: 0.1394 2022/11/02 17:15:37 - mmengine - INFO - Epoch(train) [471][30/63] lr: 1.3823e-03 eta: 7:30:49 time: 0.5963 data_time: 0.0320 memory: 14901 loss: 1.4503 loss_prob: 0.7957 loss_thr: 0.5220 loss_db: 0.1326 2022/11/02 17:15:40 - mmengine - INFO - Epoch(train) [471][35/63] lr: 1.3823e-03 eta: 7:30:49 time: 0.6090 data_time: 0.0191 memory: 14901 loss: 1.3331 loss_prob: 0.7223 loss_thr: 0.4899 loss_db: 0.1209 2022/11/02 17:15:42 - mmengine - INFO - Epoch(train) [471][40/63] lr: 1.3823e-03 eta: 7:30:42 time: 0.5403 data_time: 0.0112 memory: 14901 loss: 1.4819 loss_prob: 0.8242 loss_thr: 0.5191 loss_db: 0.1386 2022/11/02 17:15:45 - mmengine - INFO - Epoch(train) [471][45/63] lr: 1.3823e-03 eta: 7:30:42 time: 0.5257 data_time: 0.0104 memory: 14901 loss: 1.5386 loss_prob: 0.8598 loss_thr: 0.5353 loss_db: 0.1434 2022/11/02 17:15:49 - mmengine - INFO - Epoch(train) [471][50/63] lr: 1.3823e-03 eta: 7:30:37 time: 0.6211 data_time: 0.0273 memory: 14901 loss: 1.4155 loss_prob: 0.7729 loss_thr: 0.5129 loss_db: 0.1297 2022/11/02 17:15:51 - mmengine - INFO - Epoch(train) [471][55/63] lr: 1.3823e-03 eta: 7:30:37 time: 0.6032 data_time: 0.0256 memory: 14901 loss: 1.4209 loss_prob: 0.7772 loss_thr: 0.5117 loss_db: 0.1320 2022/11/02 17:15:54 - mmengine - INFO - Epoch(train) [471][60/63] lr: 1.3823e-03 eta: 7:30:29 time: 0.5005 data_time: 0.0116 memory: 14901 loss: 1.4393 loss_prob: 0.7909 loss_thr: 0.5147 loss_db: 0.1336 2022/11/02 17:15:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:16:01 - mmengine - INFO - Epoch(train) [472][5/63] lr: 1.3806e-03 eta: 7:30:29 time: 0.8352 data_time: 0.2293 memory: 14901 loss: 1.4262 loss_prob: 0.7783 loss_thr: 0.5150 loss_db: 0.1329 2022/11/02 17:16:03 - mmengine - INFO - Epoch(train) [472][10/63] lr: 1.3806e-03 eta: 7:30:23 time: 0.8545 data_time: 0.2310 memory: 14901 loss: 1.3765 loss_prob: 0.7622 loss_thr: 0.4813 loss_db: 0.1330 2022/11/02 17:16:07 - mmengine - INFO - Epoch(train) [472][15/63] lr: 1.3806e-03 eta: 7:30:23 time: 0.5629 data_time: 0.0142 memory: 14901 loss: 1.5409 loss_prob: 0.8944 loss_thr: 0.5041 loss_db: 0.1424 2022/11/02 17:16:09 - mmengine - INFO - Epoch(train) [472][20/63] lr: 1.3806e-03 eta: 7:30:17 time: 0.5913 data_time: 0.0145 memory: 14901 loss: 1.5559 loss_prob: 0.8923 loss_thr: 0.5227 loss_db: 0.1409 2022/11/02 17:16:12 - mmengine - INFO - Epoch(train) [472][25/63] lr: 1.3806e-03 eta: 7:30:17 time: 0.5529 data_time: 0.0346 memory: 14901 loss: 1.4701 loss_prob: 0.8243 loss_thr: 0.5038 loss_db: 0.1420 2022/11/02 17:16:15 - mmengine - INFO - Epoch(train) [472][30/63] lr: 1.3806e-03 eta: 7:30:10 time: 0.5219 data_time: 0.0383 memory: 14901 loss: 1.4562 loss_prob: 0.8138 loss_thr: 0.5037 loss_db: 0.1387 2022/11/02 17:16:17 - mmengine - INFO - Epoch(train) [472][35/63] lr: 1.3806e-03 eta: 7:30:10 time: 0.4990 data_time: 0.0128 memory: 14901 loss: 1.3774 loss_prob: 0.7546 loss_thr: 0.4968 loss_db: 0.1260 2022/11/02 17:16:21 - mmengine - INFO - Epoch(train) [472][40/63] lr: 1.3806e-03 eta: 7:30:05 time: 0.6085 data_time: 0.0165 memory: 14901 loss: 1.4197 loss_prob: 0.7750 loss_thr: 0.5095 loss_db: 0.1352 2022/11/02 17:16:23 - mmengine - INFO - Epoch(train) [472][45/63] lr: 1.3806e-03 eta: 7:30:05 time: 0.5884 data_time: 0.0150 memory: 14901 loss: 1.5128 loss_prob: 0.8394 loss_thr: 0.5277 loss_db: 0.1457 2022/11/02 17:16:26 - mmengine - INFO - Epoch(train) [472][50/63] lr: 1.3806e-03 eta: 7:29:58 time: 0.5149 data_time: 0.0219 memory: 14901 loss: 1.4996 loss_prob: 0.8365 loss_thr: 0.5223 loss_db: 0.1408 2022/11/02 17:16:29 - mmengine - INFO - Epoch(train) [472][55/63] lr: 1.3806e-03 eta: 7:29:58 time: 0.6089 data_time: 0.0275 memory: 14901 loss: 1.3442 loss_prob: 0.7265 loss_thr: 0.4939 loss_db: 0.1239 2022/11/02 17:16:32 - mmengine - INFO - Epoch(train) [472][60/63] lr: 1.3806e-03 eta: 7:29:52 time: 0.5759 data_time: 0.0154 memory: 14901 loss: 1.3904 loss_prob: 0.7550 loss_thr: 0.5050 loss_db: 0.1305 2022/11/02 17:16:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:16:38 - mmengine - INFO - Epoch(train) [473][5/63] lr: 1.3789e-03 eta: 7:29:52 time: 0.7904 data_time: 0.2350 memory: 14901 loss: 1.3453 loss_prob: 0.7362 loss_thr: 0.4869 loss_db: 0.1222 2022/11/02 17:16:41 - mmengine - INFO - Epoch(train) [473][10/63] lr: 1.3789e-03 eta: 7:29:45 time: 0.8436 data_time: 0.2323 memory: 14901 loss: 1.2873 loss_prob: 0.6961 loss_thr: 0.4729 loss_db: 0.1184 2022/11/02 17:16:44 - mmengine - INFO - Epoch(train) [473][15/63] lr: 1.3789e-03 eta: 7:29:45 time: 0.5536 data_time: 0.0078 memory: 14901 loss: 1.3771 loss_prob: 0.7592 loss_thr: 0.4887 loss_db: 0.1292 2022/11/02 17:16:46 - mmengine - INFO - Epoch(train) [473][20/63] lr: 1.3789e-03 eta: 7:29:38 time: 0.5039 data_time: 0.0058 memory: 14901 loss: 1.3384 loss_prob: 0.7354 loss_thr: 0.4792 loss_db: 0.1238 2022/11/02 17:16:49 - mmengine - INFO - Epoch(train) [473][25/63] lr: 1.3789e-03 eta: 7:29:38 time: 0.5065 data_time: 0.0090 memory: 14901 loss: 1.3601 loss_prob: 0.7373 loss_thr: 0.4991 loss_db: 0.1237 2022/11/02 17:16:52 - mmengine - INFO - Epoch(train) [473][30/63] lr: 1.3789e-03 eta: 7:29:31 time: 0.5330 data_time: 0.0330 memory: 14901 loss: 1.5003 loss_prob: 0.8287 loss_thr: 0.5308 loss_db: 0.1407 2022/11/02 17:16:55 - mmengine - INFO - Epoch(train) [473][35/63] lr: 1.3789e-03 eta: 7:29:31 time: 0.5574 data_time: 0.0334 memory: 14901 loss: 1.4495 loss_prob: 0.7985 loss_thr: 0.5177 loss_db: 0.1333 2022/11/02 17:16:57 - mmengine - INFO - Epoch(train) [473][40/63] lr: 1.3789e-03 eta: 7:29:24 time: 0.5164 data_time: 0.0107 memory: 14901 loss: 1.3166 loss_prob: 0.7210 loss_thr: 0.4796 loss_db: 0.1160 2022/11/02 17:17:00 - mmengine - INFO - Epoch(train) [473][45/63] lr: 1.3789e-03 eta: 7:29:24 time: 0.5003 data_time: 0.0113 memory: 14901 loss: 1.4511 loss_prob: 0.8175 loss_thr: 0.4972 loss_db: 0.1364 2022/11/02 17:17:02 - mmengine - INFO - Epoch(train) [473][50/63] lr: 1.3789e-03 eta: 7:29:17 time: 0.5253 data_time: 0.0136 memory: 14901 loss: 1.6031 loss_prob: 0.9201 loss_thr: 0.5290 loss_db: 0.1541 2022/11/02 17:17:05 - mmengine - INFO - Epoch(train) [473][55/63] lr: 1.3789e-03 eta: 7:29:17 time: 0.5632 data_time: 0.0269 memory: 14901 loss: 1.4898 loss_prob: 0.8385 loss_thr: 0.5119 loss_db: 0.1393 2022/11/02 17:17:08 - mmengine - INFO - Epoch(train) [473][60/63] lr: 1.3789e-03 eta: 7:29:11 time: 0.5514 data_time: 0.0254 memory: 14901 loss: 1.5573 loss_prob: 0.8831 loss_thr: 0.5316 loss_db: 0.1426 2022/11/02 17:17:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:17:14 - mmengine - INFO - Epoch(train) [474][5/63] lr: 1.3772e-03 eta: 7:29:11 time: 0.7420 data_time: 0.2326 memory: 14901 loss: 1.4078 loss_prob: 0.7759 loss_thr: 0.5035 loss_db: 0.1284 2022/11/02 17:17:17 - mmengine - INFO - Epoch(train) [474][10/63] lr: 1.3772e-03 eta: 7:29:04 time: 0.7999 data_time: 0.2405 memory: 14901 loss: 1.3715 loss_prob: 0.7525 loss_thr: 0.4910 loss_db: 0.1280 2022/11/02 17:17:20 - mmengine - INFO - Epoch(train) [474][15/63] lr: 1.3772e-03 eta: 7:29:04 time: 0.5882 data_time: 0.0220 memory: 14901 loss: 1.3239 loss_prob: 0.7126 loss_thr: 0.4903 loss_db: 0.1210 2022/11/02 17:17:23 - mmengine - INFO - Epoch(train) [474][20/63] lr: 1.3772e-03 eta: 7:28:57 time: 0.5507 data_time: 0.0176 memory: 14901 loss: 1.3319 loss_prob: 0.7244 loss_thr: 0.4861 loss_db: 0.1215 2022/11/02 17:17:25 - mmengine - INFO - Epoch(train) [474][25/63] lr: 1.3772e-03 eta: 7:28:57 time: 0.5202 data_time: 0.0140 memory: 14901 loss: 1.2901 loss_prob: 0.7056 loss_thr: 0.4645 loss_db: 0.1199 2022/11/02 17:17:28 - mmengine - INFO - Epoch(train) [474][30/63] lr: 1.3772e-03 eta: 7:28:51 time: 0.5455 data_time: 0.0382 memory: 14901 loss: 1.4525 loss_prob: 0.8258 loss_thr: 0.4946 loss_db: 0.1322 2022/11/02 17:17:31 - mmengine - INFO - Epoch(train) [474][35/63] lr: 1.3772e-03 eta: 7:28:51 time: 0.5577 data_time: 0.0417 memory: 14901 loss: 1.4993 loss_prob: 0.8403 loss_thr: 0.5267 loss_db: 0.1322 2022/11/02 17:17:34 - mmengine - INFO - Epoch(train) [474][40/63] lr: 1.3772e-03 eta: 7:28:44 time: 0.5523 data_time: 0.0143 memory: 14901 loss: 1.3241 loss_prob: 0.7062 loss_thr: 0.4993 loss_db: 0.1186 2022/11/02 17:17:37 - mmengine - INFO - Epoch(train) [474][45/63] lr: 1.3772e-03 eta: 7:28:44 time: 0.5883 data_time: 0.0096 memory: 14901 loss: 1.3073 loss_prob: 0.7100 loss_thr: 0.4766 loss_db: 0.1207 2022/11/02 17:17:39 - mmengine - INFO - Epoch(train) [474][50/63] lr: 1.3772e-03 eta: 7:28:38 time: 0.5610 data_time: 0.0212 memory: 14901 loss: 1.3372 loss_prob: 0.7355 loss_thr: 0.4807 loss_db: 0.1211 2022/11/02 17:17:42 - mmengine - INFO - Epoch(train) [474][55/63] lr: 1.3772e-03 eta: 7:28:38 time: 0.5337 data_time: 0.0259 memory: 14901 loss: 1.3394 loss_prob: 0.7345 loss_thr: 0.4845 loss_db: 0.1204 2022/11/02 17:17:45 - mmengine - INFO - Epoch(train) [474][60/63] lr: 1.3772e-03 eta: 7:28:31 time: 0.5236 data_time: 0.0190 memory: 14901 loss: 1.4577 loss_prob: 0.8140 loss_thr: 0.5095 loss_db: 0.1343 2022/11/02 17:17:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:17:52 - mmengine - INFO - Epoch(train) [475][5/63] lr: 1.3755e-03 eta: 7:28:31 time: 0.8844 data_time: 0.2370 memory: 14901 loss: 1.4710 loss_prob: 0.8071 loss_thr: 0.5253 loss_db: 0.1387 2022/11/02 17:17:55 - mmengine - INFO - Epoch(train) [475][10/63] lr: 1.3755e-03 eta: 7:28:25 time: 0.8699 data_time: 0.2340 memory: 14901 loss: 1.3011 loss_prob: 0.7097 loss_thr: 0.4706 loss_db: 0.1208 2022/11/02 17:17:58 - mmengine - INFO - Epoch(train) [475][15/63] lr: 1.3755e-03 eta: 7:28:25 time: 0.5514 data_time: 0.0075 memory: 14901 loss: 1.3113 loss_prob: 0.7094 loss_thr: 0.4810 loss_db: 0.1208 2022/11/02 17:18:01 - mmengine - INFO - Epoch(train) [475][20/63] lr: 1.3755e-03 eta: 7:28:19 time: 0.5865 data_time: 0.0115 memory: 14901 loss: 1.3557 loss_prob: 0.7345 loss_thr: 0.4975 loss_db: 0.1237 2022/11/02 17:18:04 - mmengine - INFO - Epoch(train) [475][25/63] lr: 1.3755e-03 eta: 7:28:19 time: 0.5884 data_time: 0.0215 memory: 14901 loss: 1.3238 loss_prob: 0.7113 loss_thr: 0.4922 loss_db: 0.1203 2022/11/02 17:18:07 - mmengine - INFO - Epoch(train) [475][30/63] lr: 1.3755e-03 eta: 7:28:13 time: 0.5789 data_time: 0.0375 memory: 14901 loss: 1.4152 loss_prob: 0.7671 loss_thr: 0.5180 loss_db: 0.1301 2022/11/02 17:18:09 - mmengine - INFO - Epoch(train) [475][35/63] lr: 1.3755e-03 eta: 7:28:13 time: 0.5598 data_time: 0.0252 memory: 14901 loss: 1.3843 loss_prob: 0.7523 loss_thr: 0.5056 loss_db: 0.1264 2022/11/02 17:18:12 - mmengine - INFO - Epoch(train) [475][40/63] lr: 1.3755e-03 eta: 7:28:06 time: 0.5305 data_time: 0.0100 memory: 14901 loss: 1.3077 loss_prob: 0.7009 loss_thr: 0.4875 loss_db: 0.1193 2022/11/02 17:18:15 - mmengine - INFO - Epoch(train) [475][45/63] lr: 1.3755e-03 eta: 7:28:06 time: 0.5395 data_time: 0.0165 memory: 14901 loss: 1.3423 loss_prob: 0.7351 loss_thr: 0.4831 loss_db: 0.1241 2022/11/02 17:18:18 - mmengine - INFO - Epoch(train) [475][50/63] lr: 1.3755e-03 eta: 7:28:00 time: 0.5771 data_time: 0.0242 memory: 14901 loss: 1.3347 loss_prob: 0.7361 loss_thr: 0.4733 loss_db: 0.1253 2022/11/02 17:18:21 - mmengine - INFO - Epoch(train) [475][55/63] lr: 1.3755e-03 eta: 7:28:00 time: 0.5742 data_time: 0.0309 memory: 14901 loss: 1.2877 loss_prob: 0.6944 loss_thr: 0.4732 loss_db: 0.1201 2022/11/02 17:18:23 - mmengine - INFO - Epoch(train) [475][60/63] lr: 1.3755e-03 eta: 7:27:54 time: 0.5305 data_time: 0.0185 memory: 14901 loss: 1.3250 loss_prob: 0.7173 loss_thr: 0.4856 loss_db: 0.1221 2022/11/02 17:18:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:18:32 - mmengine - INFO - Epoch(train) [476][5/63] lr: 1.3737e-03 eta: 7:27:54 time: 0.9516 data_time: 0.2297 memory: 14901 loss: 1.4096 loss_prob: 0.7715 loss_thr: 0.5070 loss_db: 0.1311 2022/11/02 17:18:35 - mmengine - INFO - Epoch(train) [476][10/63] lr: 1.3737e-03 eta: 7:27:51 time: 1.0878 data_time: 0.2334 memory: 14901 loss: 1.5005 loss_prob: 0.8429 loss_thr: 0.5210 loss_db: 0.1366 2022/11/02 17:18:38 - mmengine - INFO - Epoch(train) [476][15/63] lr: 1.3737e-03 eta: 7:27:51 time: 0.6535 data_time: 0.0484 memory: 14901 loss: 1.4892 loss_prob: 0.8305 loss_thr: 0.5252 loss_db: 0.1335 2022/11/02 17:18:41 - mmengine - INFO - Epoch(train) [476][20/63] lr: 1.3737e-03 eta: 7:27:45 time: 0.5765 data_time: 0.0460 memory: 14901 loss: 1.4895 loss_prob: 0.8183 loss_thr: 0.5353 loss_db: 0.1359 2022/11/02 17:18:44 - mmengine - INFO - Epoch(train) [476][25/63] lr: 1.3737e-03 eta: 7:27:45 time: 0.5529 data_time: 0.0243 memory: 14901 loss: 1.4640 loss_prob: 0.8062 loss_thr: 0.5216 loss_db: 0.1361 2022/11/02 17:18:47 - mmengine - INFO - Epoch(train) [476][30/63] lr: 1.3737e-03 eta: 7:27:39 time: 0.5620 data_time: 0.0365 memory: 14901 loss: 1.2128 loss_prob: 0.6358 loss_thr: 0.4676 loss_db: 0.1093 2022/11/02 17:18:49 - mmengine - INFO - Epoch(train) [476][35/63] lr: 1.3737e-03 eta: 7:27:39 time: 0.5606 data_time: 0.0301 memory: 14901 loss: 1.2459 loss_prob: 0.6579 loss_thr: 0.4767 loss_db: 0.1113 2022/11/02 17:18:52 - mmengine - INFO - Epoch(train) [476][40/63] lr: 1.3737e-03 eta: 7:27:33 time: 0.5793 data_time: 0.0170 memory: 14901 loss: 1.3109 loss_prob: 0.7052 loss_thr: 0.4871 loss_db: 0.1186 2022/11/02 17:18:55 - mmengine - INFO - Epoch(train) [476][45/63] lr: 1.3737e-03 eta: 7:27:33 time: 0.6013 data_time: 0.0116 memory: 14901 loss: 1.3127 loss_prob: 0.7098 loss_thr: 0.4821 loss_db: 0.1208 2022/11/02 17:18:59 - mmengine - INFO - Epoch(train) [476][50/63] lr: 1.3737e-03 eta: 7:27:27 time: 0.6170 data_time: 0.0139 memory: 14901 loss: 1.3369 loss_prob: 0.7290 loss_thr: 0.4814 loss_db: 0.1264 2022/11/02 17:19:01 - mmengine - INFO - Epoch(train) [476][55/63] lr: 1.3737e-03 eta: 7:27:27 time: 0.6082 data_time: 0.0282 memory: 14901 loss: 1.4213 loss_prob: 0.7830 loss_thr: 0.5071 loss_db: 0.1312 2022/11/02 17:19:04 - mmengine - INFO - Epoch(train) [476][60/63] lr: 1.3737e-03 eta: 7:27:21 time: 0.5749 data_time: 0.0244 memory: 14901 loss: 1.4677 loss_prob: 0.8051 loss_thr: 0.5300 loss_db: 0.1326 2022/11/02 17:19:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:19:12 - mmengine - INFO - Epoch(train) [477][5/63] lr: 1.3720e-03 eta: 7:27:21 time: 0.8898 data_time: 0.2744 memory: 14901 loss: 1.3968 loss_prob: 0.7547 loss_thr: 0.5127 loss_db: 0.1294 2022/11/02 17:19:15 - mmengine - INFO - Epoch(train) [477][10/63] lr: 1.3720e-03 eta: 7:27:15 time: 0.8983 data_time: 0.2706 memory: 14901 loss: 1.3108 loss_prob: 0.7114 loss_thr: 0.4782 loss_db: 0.1212 2022/11/02 17:19:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:19:18 - mmengine - INFO - Epoch(train) [477][15/63] lr: 1.3720e-03 eta: 7:27:15 time: 0.6313 data_time: 0.0071 memory: 14901 loss: 1.5135 loss_prob: 0.8700 loss_thr: 0.5045 loss_db: 0.1390 2022/11/02 17:19:21 - mmengine - INFO - Epoch(train) [477][20/63] lr: 1.3720e-03 eta: 7:27:10 time: 0.6267 data_time: 0.0074 memory: 14901 loss: 1.5362 loss_prob: 0.8758 loss_thr: 0.5175 loss_db: 0.1429 2022/11/02 17:19:25 - mmengine - INFO - Epoch(train) [477][25/63] lr: 1.3720e-03 eta: 7:27:10 time: 0.6354 data_time: 0.0316 memory: 14901 loss: 1.5683 loss_prob: 0.8906 loss_thr: 0.5287 loss_db: 0.1490 2022/11/02 17:19:27 - mmengine - INFO - Epoch(train) [477][30/63] lr: 1.3720e-03 eta: 7:27:05 time: 0.6248 data_time: 0.0411 memory: 14901 loss: 1.7882 loss_prob: 1.0601 loss_thr: 0.5598 loss_db: 0.1682 2022/11/02 17:19:30 - mmengine - INFO - Epoch(train) [477][35/63] lr: 1.3720e-03 eta: 7:27:05 time: 0.5891 data_time: 0.0176 memory: 14901 loss: 1.6711 loss_prob: 0.9635 loss_thr: 0.5451 loss_db: 0.1626 2022/11/02 17:19:33 - mmengine - INFO - Epoch(train) [477][40/63] lr: 1.3720e-03 eta: 7:26:59 time: 0.6164 data_time: 0.0087 memory: 14901 loss: 1.7078 loss_prob: 0.9917 loss_thr: 0.5447 loss_db: 0.1715 2022/11/02 17:19:36 - mmengine - INFO - Epoch(train) [477][45/63] lr: 1.3720e-03 eta: 7:26:59 time: 0.5539 data_time: 0.0094 memory: 14901 loss: 1.8643 loss_prob: 1.1132 loss_thr: 0.5705 loss_db: 0.1806 2022/11/02 17:19:39 - mmengine - INFO - Epoch(train) [477][50/63] lr: 1.3720e-03 eta: 7:26:53 time: 0.5567 data_time: 0.0300 memory: 14901 loss: 1.7618 loss_prob: 1.0244 loss_thr: 0.5685 loss_db: 0.1690 2022/11/02 17:19:42 - mmengine - INFO - Epoch(train) [477][55/63] lr: 1.3720e-03 eta: 7:26:53 time: 0.5731 data_time: 0.0266 memory: 14901 loss: 1.5819 loss_prob: 0.8963 loss_thr: 0.5337 loss_db: 0.1520 2022/11/02 17:19:44 - mmengine - INFO - Epoch(train) [477][60/63] lr: 1.3720e-03 eta: 7:26:46 time: 0.5347 data_time: 0.0086 memory: 14901 loss: 1.5630 loss_prob: 0.9024 loss_thr: 0.5165 loss_db: 0.1440 2022/11/02 17:19:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:19:51 - mmengine - INFO - Epoch(train) [478][5/63] lr: 1.3703e-03 eta: 7:26:46 time: 0.7600 data_time: 0.2458 memory: 14901 loss: 1.5152 loss_prob: 0.8504 loss_thr: 0.5242 loss_db: 0.1406 2022/11/02 17:19:54 - mmengine - INFO - Epoch(train) [478][10/63] lr: 1.3703e-03 eta: 7:26:39 time: 0.7855 data_time: 0.2452 memory: 14901 loss: 1.5023 loss_prob: 0.8442 loss_thr: 0.5146 loss_db: 0.1435 2022/11/02 17:19:56 - mmengine - INFO - Epoch(train) [478][15/63] lr: 1.3703e-03 eta: 7:26:39 time: 0.5524 data_time: 0.0068 memory: 14901 loss: 1.5807 loss_prob: 0.9190 loss_thr: 0.5197 loss_db: 0.1420 2022/11/02 17:19:59 - mmengine - INFO - Epoch(train) [478][20/63] lr: 1.3703e-03 eta: 7:26:33 time: 0.5703 data_time: 0.0070 memory: 14901 loss: 1.5840 loss_prob: 0.9100 loss_thr: 0.5321 loss_db: 0.1420 2022/11/02 17:20:02 - mmengine - INFO - Epoch(train) [478][25/63] lr: 1.3703e-03 eta: 7:26:33 time: 0.6031 data_time: 0.0457 memory: 14901 loss: 1.5087 loss_prob: 0.8332 loss_thr: 0.5318 loss_db: 0.1437 2022/11/02 17:20:05 - mmengine - INFO - Epoch(train) [478][30/63] lr: 1.3703e-03 eta: 7:26:27 time: 0.5784 data_time: 0.0477 memory: 14901 loss: 1.5636 loss_prob: 0.8708 loss_thr: 0.5456 loss_db: 0.1472 2022/11/02 17:20:08 - mmengine - INFO - Epoch(train) [478][35/63] lr: 1.3703e-03 eta: 7:26:27 time: 0.5349 data_time: 0.0080 memory: 14901 loss: 1.4943 loss_prob: 0.8445 loss_thr: 0.5091 loss_db: 0.1407 2022/11/02 17:20:11 - mmengine - INFO - Epoch(train) [478][40/63] lr: 1.3703e-03 eta: 7:26:20 time: 0.5537 data_time: 0.0106 memory: 14901 loss: 1.4024 loss_prob: 0.7923 loss_thr: 0.4777 loss_db: 0.1323 2022/11/02 17:20:14 - mmengine - INFO - Epoch(train) [478][45/63] lr: 1.3703e-03 eta: 7:26:20 time: 0.5776 data_time: 0.0160 memory: 14901 loss: 1.5210 loss_prob: 0.8751 loss_thr: 0.5066 loss_db: 0.1393 2022/11/02 17:20:16 - mmengine - INFO - Epoch(train) [478][50/63] lr: 1.3703e-03 eta: 7:26:14 time: 0.5661 data_time: 0.0296 memory: 14901 loss: 1.5276 loss_prob: 0.8829 loss_thr: 0.5024 loss_db: 0.1423 2022/11/02 17:20:19 - mmengine - INFO - Epoch(train) [478][55/63] lr: 1.3703e-03 eta: 7:26:14 time: 0.5302 data_time: 0.0278 memory: 14901 loss: 1.3528 loss_prob: 0.7417 loss_thr: 0.4848 loss_db: 0.1262 2022/11/02 17:20:22 - mmengine - INFO - Epoch(train) [478][60/63] lr: 1.3703e-03 eta: 7:26:07 time: 0.5301 data_time: 0.0102 memory: 14901 loss: 1.3635 loss_prob: 0.7409 loss_thr: 0.4972 loss_db: 0.1254 2022/11/02 17:20:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:20:29 - mmengine - INFO - Epoch(train) [479][5/63] lr: 1.3686e-03 eta: 7:26:07 time: 0.8382 data_time: 0.2486 memory: 14901 loss: 1.4242 loss_prob: 0.7761 loss_thr: 0.5151 loss_db: 0.1331 2022/11/02 17:20:32 - mmengine - INFO - Epoch(train) [479][10/63] lr: 1.3686e-03 eta: 7:26:02 time: 0.9083 data_time: 0.2444 memory: 14901 loss: 1.3752 loss_prob: 0.7391 loss_thr: 0.5109 loss_db: 0.1252 2022/11/02 17:20:35 - mmengine - INFO - Epoch(train) [479][15/63] lr: 1.3686e-03 eta: 7:26:02 time: 0.6080 data_time: 0.0091 memory: 14901 loss: 1.3558 loss_prob: 0.7318 loss_thr: 0.4992 loss_db: 0.1248 2022/11/02 17:20:38 - mmengine - INFO - Epoch(train) [479][20/63] lr: 1.3686e-03 eta: 7:25:56 time: 0.5963 data_time: 0.0101 memory: 14901 loss: 1.3770 loss_prob: 0.7531 loss_thr: 0.4948 loss_db: 0.1290 2022/11/02 17:20:41 - mmengine - INFO - Epoch(train) [479][25/63] lr: 1.3686e-03 eta: 7:25:56 time: 0.5576 data_time: 0.0289 memory: 14901 loss: 1.3726 loss_prob: 0.7378 loss_thr: 0.5102 loss_db: 0.1246 2022/11/02 17:20:43 - mmengine - INFO - Epoch(train) [479][30/63] lr: 1.3686e-03 eta: 7:25:49 time: 0.5252 data_time: 0.0394 memory: 14901 loss: 1.3918 loss_prob: 0.7537 loss_thr: 0.5109 loss_db: 0.1273 2022/11/02 17:20:46 - mmengine - INFO - Epoch(train) [479][35/63] lr: 1.3686e-03 eta: 7:25:49 time: 0.4974 data_time: 0.0208 memory: 14901 loss: 1.4511 loss_prob: 0.8151 loss_thr: 0.4980 loss_db: 0.1379 2022/11/02 17:20:49 - mmengine - INFO - Epoch(train) [479][40/63] lr: 1.3686e-03 eta: 7:25:43 time: 0.5548 data_time: 0.0137 memory: 14901 loss: 1.4985 loss_prob: 0.8427 loss_thr: 0.5159 loss_db: 0.1399 2022/11/02 17:20:52 - mmengine - INFO - Epoch(train) [479][45/63] lr: 1.3686e-03 eta: 7:25:43 time: 0.6402 data_time: 0.0104 memory: 14901 loss: 1.3835 loss_prob: 0.7616 loss_thr: 0.4935 loss_db: 0.1284 2022/11/02 17:20:55 - mmengine - INFO - Epoch(train) [479][50/63] lr: 1.3686e-03 eta: 7:25:37 time: 0.5991 data_time: 0.0179 memory: 14901 loss: 1.2713 loss_prob: 0.6891 loss_thr: 0.4626 loss_db: 0.1197 2022/11/02 17:20:58 - mmengine - INFO - Epoch(train) [479][55/63] lr: 1.3686e-03 eta: 7:25:37 time: 0.5828 data_time: 0.0277 memory: 14901 loss: 1.2425 loss_prob: 0.6678 loss_thr: 0.4613 loss_db: 0.1133 2022/11/02 17:21:01 - mmengine - INFO - Epoch(train) [479][60/63] lr: 1.3686e-03 eta: 7:25:31 time: 0.5835 data_time: 0.0186 memory: 14901 loss: 1.2815 loss_prob: 0.6856 loss_thr: 0.4817 loss_db: 0.1143 2022/11/02 17:21:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:21:07 - mmengine - INFO - Epoch(train) [480][5/63] lr: 1.3669e-03 eta: 7:25:31 time: 0.7877 data_time: 0.2198 memory: 14901 loss: 1.2581 loss_prob: 0.6699 loss_thr: 0.4749 loss_db: 0.1133 2022/11/02 17:21:11 - mmengine - INFO - Epoch(train) [480][10/63] lr: 1.3669e-03 eta: 7:25:25 time: 0.8669 data_time: 0.2206 memory: 14901 loss: 1.3106 loss_prob: 0.7112 loss_thr: 0.4789 loss_db: 0.1205 2022/11/02 17:21:13 - mmengine - INFO - Epoch(train) [480][15/63] lr: 1.3669e-03 eta: 7:25:25 time: 0.5974 data_time: 0.0150 memory: 14901 loss: 1.3615 loss_prob: 0.7463 loss_thr: 0.4899 loss_db: 0.1253 2022/11/02 17:21:16 - mmengine - INFO - Epoch(train) [480][20/63] lr: 1.3669e-03 eta: 7:25:19 time: 0.5933 data_time: 0.0138 memory: 14901 loss: 1.3444 loss_prob: 0.7301 loss_thr: 0.4904 loss_db: 0.1240 2022/11/02 17:21:19 - mmengine - INFO - Epoch(train) [480][25/63] lr: 1.3669e-03 eta: 7:25:19 time: 0.6050 data_time: 0.0205 memory: 14901 loss: 1.3349 loss_prob: 0.7160 loss_thr: 0.4961 loss_db: 0.1228 2022/11/02 17:21:22 - mmengine - INFO - Epoch(train) [480][30/63] lr: 1.3669e-03 eta: 7:25:13 time: 0.5910 data_time: 0.0404 memory: 14901 loss: 1.2672 loss_prob: 0.6746 loss_thr: 0.4810 loss_db: 0.1117 2022/11/02 17:21:26 - mmengine - INFO - Epoch(train) [480][35/63] lr: 1.3669e-03 eta: 7:25:13 time: 0.6425 data_time: 0.0331 memory: 14901 loss: 1.3290 loss_prob: 0.7196 loss_thr: 0.4902 loss_db: 0.1192 2022/11/02 17:21:28 - mmengine - INFO - Epoch(train) [480][40/63] lr: 1.3669e-03 eta: 7:25:08 time: 0.5933 data_time: 0.0153 memory: 14901 loss: 1.3856 loss_prob: 0.7479 loss_thr: 0.5099 loss_db: 0.1278 2022/11/02 17:21:31 - mmengine - INFO - Epoch(train) [480][45/63] lr: 1.3669e-03 eta: 7:25:08 time: 0.5077 data_time: 0.0084 memory: 14901 loss: 1.3604 loss_prob: 0.7303 loss_thr: 0.5072 loss_db: 0.1229 2022/11/02 17:21:34 - mmengine - INFO - Epoch(train) [480][50/63] lr: 1.3669e-03 eta: 7:25:02 time: 0.6047 data_time: 0.0210 memory: 14901 loss: 1.4026 loss_prob: 0.7645 loss_thr: 0.5098 loss_db: 0.1284 2022/11/02 17:21:37 - mmengine - INFO - Epoch(train) [480][55/63] lr: 1.3669e-03 eta: 7:25:02 time: 0.6573 data_time: 0.0266 memory: 14901 loss: 1.4115 loss_prob: 0.7739 loss_thr: 0.5065 loss_db: 0.1311 2022/11/02 17:21:40 - mmengine - INFO - Epoch(train) [480][60/63] lr: 1.3669e-03 eta: 7:24:56 time: 0.5598 data_time: 0.0126 memory: 14901 loss: 1.4176 loss_prob: 0.7711 loss_thr: 0.5179 loss_db: 0.1286 2022/11/02 17:21:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:21:41 - mmengine - INFO - Saving checkpoint at 480 epochs 2022/11/02 17:21:45 - mmengine - INFO - Epoch(val) [480][5/500] eta: 7:24:56 time: 0.0450 data_time: 0.0061 memory: 14901 2022/11/02 17:21:45 - mmengine - INFO - Epoch(val) [480][10/500] eta: 0:00:25 time: 0.0519 data_time: 0.0069 memory: 1008 2022/11/02 17:21:45 - mmengine - INFO - Epoch(val) [480][15/500] eta: 0:00:25 time: 0.0446 data_time: 0.0033 memory: 1008 2022/11/02 17:21:46 - mmengine - INFO - Epoch(val) [480][20/500] eta: 0:00:18 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/02 17:21:46 - mmengine - INFO - Epoch(val) [480][25/500] eta: 0:00:18 time: 0.0352 data_time: 0.0023 memory: 1008 2022/11/02 17:21:46 - mmengine - INFO - Epoch(val) [480][30/500] eta: 0:00:19 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 17:21:46 - mmengine - INFO - Epoch(val) [480][35/500] eta: 0:00:19 time: 0.0435 data_time: 0.0033 memory: 1008 2022/11/02 17:21:47 - mmengine - INFO - Epoch(val) [480][40/500] eta: 0:00:20 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 17:21:47 - mmengine - INFO - Epoch(val) [480][45/500] eta: 0:00:20 time: 0.0458 data_time: 0.0030 memory: 1008 2022/11/02 17:21:47 - mmengine - INFO - Epoch(val) [480][50/500] eta: 0:00:18 time: 0.0418 data_time: 0.0030 memory: 1008 2022/11/02 17:21:47 - mmengine - INFO - Epoch(val) [480][55/500] eta: 0:00:18 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 17:21:47 - mmengine - INFO - Epoch(val) [480][60/500] eta: 0:00:18 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/02 17:21:48 - mmengine - INFO - Epoch(val) [480][65/500] eta: 0:00:18 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 17:21:48 - mmengine - INFO - Epoch(val) [480][70/500] eta: 0:00:18 time: 0.0426 data_time: 0.0027 memory: 1008 2022/11/02 17:21:48 - mmengine - INFO - Epoch(val) [480][75/500] eta: 0:00:18 time: 0.0435 data_time: 0.0027 memory: 1008 2022/11/02 17:21:48 - mmengine - INFO - Epoch(val) [480][80/500] eta: 0:00:17 time: 0.0408 data_time: 0.0038 memory: 1008 2022/11/02 17:21:48 - mmengine - INFO - Epoch(val) [480][85/500] eta: 0:00:17 time: 0.0380 data_time: 0.0035 memory: 1008 2022/11/02 17:21:49 - mmengine - INFO - Epoch(val) [480][90/500] eta: 0:00:16 time: 0.0408 data_time: 0.0024 memory: 1008 2022/11/02 17:21:49 - mmengine - INFO - Epoch(val) [480][95/500] eta: 0:00:16 time: 0.0431 data_time: 0.0026 memory: 1008 2022/11/02 17:21:49 - mmengine - INFO - Epoch(val) [480][100/500] eta: 0:00:15 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 17:21:49 - mmengine - INFO - Epoch(val) [480][105/500] eta: 0:00:15 time: 0.0385 data_time: 0.0031 memory: 1008 2022/11/02 17:21:49 - mmengine - INFO - Epoch(val) [480][110/500] eta: 0:00:16 time: 0.0413 data_time: 0.0044 memory: 1008 2022/11/02 17:21:50 - mmengine - INFO - Epoch(val) [480][115/500] eta: 0:00:16 time: 0.0409 data_time: 0.0038 memory: 1008 2022/11/02 17:21:50 - mmengine - INFO - Epoch(val) [480][120/500] eta: 0:00:15 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/02 17:21:50 - mmengine - INFO - Epoch(val) [480][125/500] eta: 0:00:15 time: 0.0407 data_time: 0.0039 memory: 1008 2022/11/02 17:21:50 - mmengine - INFO - Epoch(val) [480][130/500] eta: 0:00:14 time: 0.0385 data_time: 0.0043 memory: 1008 2022/11/02 17:21:50 - mmengine - INFO - Epoch(val) [480][135/500] eta: 0:00:14 time: 0.0351 data_time: 0.0030 memory: 1008 2022/11/02 17:21:51 - mmengine - INFO - Epoch(val) [480][140/500] eta: 0:00:13 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 17:21:51 - mmengine - INFO - Epoch(val) [480][145/500] eta: 0:00:13 time: 0.0433 data_time: 0.0027 memory: 1008 2022/11/02 17:21:51 - mmengine - INFO - Epoch(val) [480][150/500] eta: 0:00:14 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 17:21:51 - mmengine - INFO - Epoch(val) [480][155/500] eta: 0:00:14 time: 0.0452 data_time: 0.0026 memory: 1008 2022/11/02 17:21:51 - mmengine - INFO - Epoch(val) [480][160/500] eta: 0:00:16 time: 0.0484 data_time: 0.0030 memory: 1008 2022/11/02 17:21:52 - mmengine - INFO - Epoch(val) [480][165/500] eta: 0:00:16 time: 0.0425 data_time: 0.0032 memory: 1008 2022/11/02 17:21:52 - mmengine - INFO - Epoch(val) [480][170/500] eta: 0:00:14 time: 0.0446 data_time: 0.0034 memory: 1008 2022/11/02 17:21:52 - mmengine - INFO - Epoch(val) [480][175/500] eta: 0:00:14 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 17:21:52 - mmengine - INFO - Epoch(val) [480][180/500] eta: 0:00:12 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 17:21:53 - mmengine - INFO - Epoch(val) [480][185/500] eta: 0:00:12 time: 0.0444 data_time: 0.0027 memory: 1008 2022/11/02 17:21:53 - mmengine - INFO - Epoch(val) [480][190/500] eta: 0:00:13 time: 0.0442 data_time: 0.0027 memory: 1008 2022/11/02 17:21:53 - mmengine - INFO - Epoch(val) [480][195/500] eta: 0:00:13 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 17:21:53 - mmengine - INFO - Epoch(val) [480][200/500] eta: 0:00:12 time: 0.0427 data_time: 0.0025 memory: 1008 2022/11/02 17:21:53 - mmengine - INFO - Epoch(val) [480][205/500] eta: 0:00:12 time: 0.0428 data_time: 0.0026 memory: 1008 2022/11/02 17:21:54 - mmengine - INFO - Epoch(val) [480][210/500] eta: 0:00:11 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/02 17:21:54 - mmengine - INFO - Epoch(val) [480][215/500] eta: 0:00:11 time: 0.0425 data_time: 0.0033 memory: 1008 2022/11/02 17:21:54 - mmengine - INFO - Epoch(val) [480][220/500] eta: 0:00:11 time: 0.0405 data_time: 0.0031 memory: 1008 2022/11/02 17:21:54 - mmengine - INFO - Epoch(val) [480][225/500] eta: 0:00:11 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 17:21:54 - mmengine - INFO - Epoch(val) [480][230/500] eta: 0:00:10 time: 0.0407 data_time: 0.0028 memory: 1008 2022/11/02 17:21:55 - mmengine - INFO - Epoch(val) [480][235/500] eta: 0:00:10 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 17:21:55 - mmengine - INFO - Epoch(val) [480][240/500] eta: 0:00:11 time: 0.0425 data_time: 0.0031 memory: 1008 2022/11/02 17:21:55 - mmengine - INFO - Epoch(val) [480][245/500] eta: 0:00:11 time: 0.0384 data_time: 0.0030 memory: 1008 2022/11/02 17:21:55 - mmengine - INFO - Epoch(val) [480][250/500] eta: 0:00:09 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 17:21:55 - mmengine - INFO - Epoch(val) [480][255/500] eta: 0:00:09 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 17:21:56 - mmengine - INFO - Epoch(val) [480][260/500] eta: 0:00:09 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 17:21:56 - mmengine - INFO - Epoch(val) [480][265/500] eta: 0:00:09 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 17:21:56 - mmengine - INFO - Epoch(val) [480][270/500] eta: 0:00:08 time: 0.0389 data_time: 0.0023 memory: 1008 2022/11/02 17:21:56 - mmengine - INFO - Epoch(val) [480][275/500] eta: 0:00:08 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/02 17:21:56 - mmengine - INFO - Epoch(val) [480][280/500] eta: 0:00:08 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 17:21:57 - mmengine - INFO - Epoch(val) [480][285/500] eta: 0:00:08 time: 0.0409 data_time: 0.0027 memory: 1008 2022/11/02 17:21:57 - mmengine - INFO - Epoch(val) [480][290/500] eta: 0:00:09 time: 0.0435 data_time: 0.0031 memory: 1008 2022/11/02 17:21:57 - mmengine - INFO - Epoch(val) [480][295/500] eta: 0:00:09 time: 0.0425 data_time: 0.0029 memory: 1008 2022/11/02 17:21:57 - mmengine - INFO - Epoch(val) [480][300/500] eta: 0:00:07 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/02 17:21:57 - mmengine - INFO - Epoch(val) [480][305/500] eta: 0:00:07 time: 0.0412 data_time: 0.0032 memory: 1008 2022/11/02 17:21:58 - mmengine - INFO - Epoch(val) [480][310/500] eta: 0:00:07 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/02 17:21:58 - mmengine - INFO - Epoch(val) [480][315/500] eta: 0:00:07 time: 0.0403 data_time: 0.0022 memory: 1008 2022/11/02 17:21:58 - mmengine - INFO - Epoch(val) [480][320/500] eta: 0:00:07 time: 0.0432 data_time: 0.0037 memory: 1008 2022/11/02 17:21:58 - mmengine - INFO - Epoch(val) [480][325/500] eta: 0:00:07 time: 0.0519 data_time: 0.0039 memory: 1008 2022/11/02 17:21:59 - mmengine - INFO - Epoch(val) [480][330/500] eta: 0:00:08 time: 0.0509 data_time: 0.0027 memory: 1008 2022/11/02 17:21:59 - mmengine - INFO - Epoch(val) [480][335/500] eta: 0:00:08 time: 0.0373 data_time: 0.0026 memory: 1008 2022/11/02 17:21:59 - mmengine - INFO - Epoch(val) [480][340/500] eta: 0:00:08 time: 0.0529 data_time: 0.0023 memory: 1008 2022/11/02 17:21:59 - mmengine - INFO - Epoch(val) [480][345/500] eta: 0:00:08 time: 0.0559 data_time: 0.0026 memory: 1008 2022/11/02 17:21:59 - mmengine - INFO - Epoch(val) [480][350/500] eta: 0:00:06 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/02 17:22:00 - mmengine - INFO - Epoch(val) [480][355/500] eta: 0:00:06 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 17:22:00 - mmengine - INFO - Epoch(val) [480][360/500] eta: 0:00:05 time: 0.0384 data_time: 0.0026 memory: 1008 2022/11/02 17:22:00 - mmengine - INFO - Epoch(val) [480][365/500] eta: 0:00:05 time: 0.0425 data_time: 0.0027 memory: 1008 2022/11/02 17:22:00 - mmengine - INFO - Epoch(val) [480][370/500] eta: 0:00:05 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 17:22:00 - mmengine - INFO - Epoch(val) [480][375/500] eta: 0:00:05 time: 0.0346 data_time: 0.0022 memory: 1008 2022/11/02 17:22:01 - mmengine - INFO - Epoch(val) [480][380/500] eta: 0:00:04 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 17:22:01 - mmengine - INFO - Epoch(val) [480][385/500] eta: 0:00:04 time: 0.0413 data_time: 0.0030 memory: 1008 2022/11/02 17:22:01 - mmengine - INFO - Epoch(val) [480][390/500] eta: 0:00:04 time: 0.0398 data_time: 0.0026 memory: 1008 2022/11/02 17:22:01 - mmengine - INFO - Epoch(val) [480][395/500] eta: 0:00:04 time: 0.0387 data_time: 0.0023 memory: 1008 2022/11/02 17:22:01 - mmengine - INFO - Epoch(val) [480][400/500] eta: 0:00:03 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 17:22:02 - mmengine - INFO - Epoch(val) [480][405/500] eta: 0:00:03 time: 0.0378 data_time: 0.0025 memory: 1008 2022/11/02 17:22:02 - mmengine - INFO - Epoch(val) [480][410/500] eta: 0:00:03 time: 0.0430 data_time: 0.0024 memory: 1008 2022/11/02 17:22:02 - mmengine - INFO - Epoch(val) [480][415/500] eta: 0:00:03 time: 0.0439 data_time: 0.0024 memory: 1008 2022/11/02 17:22:02 - mmengine - INFO - Epoch(val) [480][420/500] eta: 0:00:02 time: 0.0365 data_time: 0.0023 memory: 1008 2022/11/02 17:22:02 - mmengine - INFO - Epoch(val) [480][425/500] eta: 0:00:02 time: 0.0421 data_time: 0.0035 memory: 1008 2022/11/02 17:22:03 - mmengine - INFO - Epoch(val) [480][430/500] eta: 0:00:03 time: 0.0456 data_time: 0.0038 memory: 1008 2022/11/02 17:22:03 - mmengine - INFO - Epoch(val) [480][435/500] eta: 0:00:03 time: 0.0377 data_time: 0.0026 memory: 1008 2022/11/02 17:22:03 - mmengine - INFO - Epoch(val) [480][440/500] eta: 0:00:02 time: 0.0382 data_time: 0.0024 memory: 1008 2022/11/02 17:22:03 - mmengine - INFO - Epoch(val) [480][445/500] eta: 0:00:02 time: 0.0438 data_time: 0.0038 memory: 1008 2022/11/02 17:22:04 - mmengine - INFO - Epoch(val) [480][450/500] eta: 0:00:02 time: 0.0486 data_time: 0.0043 memory: 1008 2022/11/02 17:22:04 - mmengine - INFO - Epoch(val) [480][455/500] eta: 0:00:02 time: 0.0484 data_time: 0.0033 memory: 1008 2022/11/02 17:22:04 - mmengine - INFO - Epoch(val) [480][460/500] eta: 0:00:01 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 17:22:04 - mmengine - INFO - Epoch(val) [480][465/500] eta: 0:00:01 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/02 17:22:04 - mmengine - INFO - Epoch(val) [480][470/500] eta: 0:00:01 time: 0.0385 data_time: 0.0027 memory: 1008 2022/11/02 17:22:05 - mmengine - INFO - Epoch(val) [480][475/500] eta: 0:00:01 time: 0.0376 data_time: 0.0028 memory: 1008 2022/11/02 17:22:05 - mmengine - INFO - Epoch(val) [480][480/500] eta: 0:00:00 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 17:22:05 - mmengine - INFO - Epoch(val) [480][485/500] eta: 0:00:00 time: 0.0402 data_time: 0.0026 memory: 1008 2022/11/02 17:22:05 - mmengine - INFO - Epoch(val) [480][490/500] eta: 0:00:00 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/02 17:22:05 - mmengine - INFO - Epoch(val) [480][495/500] eta: 0:00:00 time: 0.0449 data_time: 0.0031 memory: 1008 2022/11/02 17:22:06 - mmengine - INFO - Epoch(val) [480][500/500] eta: 0:00:00 time: 0.0397 data_time: 0.0029 memory: 1008 2022/11/02 17:22:06 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8257, precision: 0.6969, hmean: 0.7558 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8257, precision: 0.7542, hmean: 0.7883 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8252, precision: 0.7954, hmean: 0.8100 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8190, precision: 0.8326, hmean: 0.8257 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7910, precision: 0.8753, hmean: 0.8311 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5888, precision: 0.9357, hmean: 0.7228 2022/11/02 17:22:06 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0284, precision: 0.9833, hmean: 0.0552 2022/11/02 17:22:06 - mmengine - INFO - Epoch(val) [480][500/500] icdar/precision: 0.8753 icdar/recall: 0.7910 icdar/hmean: 0.8311 2022/11/02 17:22:11 - mmengine - INFO - Epoch(train) [481][5/63] lr: 1.3652e-03 eta: 0:00:00 time: 0.8189 data_time: 0.2377 memory: 14901 loss: 1.3560 loss_prob: 0.7308 loss_thr: 0.5044 loss_db: 0.1208 2022/11/02 17:22:14 - mmengine - INFO - Epoch(train) [481][10/63] lr: 1.3652e-03 eta: 7:24:49 time: 0.8243 data_time: 0.2360 memory: 14901 loss: 1.4001 loss_prob: 0.7674 loss_thr: 0.5013 loss_db: 0.1314 2022/11/02 17:22:18 - mmengine - INFO - Epoch(train) [481][15/63] lr: 1.3652e-03 eta: 7:24:49 time: 0.6170 data_time: 0.0106 memory: 14901 loss: 1.5891 loss_prob: 0.9040 loss_thr: 0.5371 loss_db: 0.1480 2022/11/02 17:22:20 - mmengine - INFO - Epoch(train) [481][20/63] lr: 1.3652e-03 eta: 7:24:43 time: 0.6257 data_time: 0.0081 memory: 14901 loss: 1.5575 loss_prob: 0.8883 loss_thr: 0.5247 loss_db: 0.1446 2022/11/02 17:22:23 - mmengine - INFO - Epoch(train) [481][25/63] lr: 1.3652e-03 eta: 7:24:43 time: 0.5150 data_time: 0.0195 memory: 14901 loss: 1.4499 loss_prob: 0.8065 loss_thr: 0.5087 loss_db: 0.1346 2022/11/02 17:22:26 - mmengine - INFO - Epoch(train) [481][30/63] lr: 1.3652e-03 eta: 7:24:37 time: 0.5811 data_time: 0.0373 memory: 14901 loss: 1.4241 loss_prob: 0.7794 loss_thr: 0.5131 loss_db: 0.1316 2022/11/02 17:22:28 - mmengine - INFO - Epoch(train) [481][35/63] lr: 1.3652e-03 eta: 7:24:37 time: 0.5726 data_time: 0.0238 memory: 14901 loss: 1.3463 loss_prob: 0.7254 loss_thr: 0.4990 loss_db: 0.1218 2022/11/02 17:22:31 - mmengine - INFO - Epoch(train) [481][40/63] lr: 1.3652e-03 eta: 7:24:31 time: 0.5172 data_time: 0.0092 memory: 14901 loss: 1.4456 loss_prob: 0.8043 loss_thr: 0.5091 loss_db: 0.1322 2022/11/02 17:22:34 - mmengine - INFO - Epoch(train) [481][45/63] lr: 1.3652e-03 eta: 7:24:31 time: 0.5800 data_time: 0.0114 memory: 14901 loss: 1.4180 loss_prob: 0.7866 loss_thr: 0.4977 loss_db: 0.1338 2022/11/02 17:22:38 - mmengine - INFO - Epoch(train) [481][50/63] lr: 1.3652e-03 eta: 7:24:26 time: 0.6503 data_time: 0.0269 memory: 14901 loss: 1.3846 loss_prob: 0.7669 loss_thr: 0.4887 loss_db: 0.1290 2022/11/02 17:22:40 - mmengine - INFO - Epoch(train) [481][55/63] lr: 1.3652e-03 eta: 7:24:26 time: 0.6115 data_time: 0.0293 memory: 14901 loss: 1.4223 loss_prob: 0.7869 loss_thr: 0.5032 loss_db: 0.1322 2022/11/02 17:22:43 - mmengine - INFO - Epoch(train) [481][60/63] lr: 1.3652e-03 eta: 7:24:19 time: 0.5490 data_time: 0.0144 memory: 14901 loss: 1.4003 loss_prob: 0.7617 loss_thr: 0.5068 loss_db: 0.1318 2022/11/02 17:22:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:22:49 - mmengine - INFO - Epoch(train) [482][5/63] lr: 1.3635e-03 eta: 7:24:19 time: 0.7458 data_time: 0.2368 memory: 14901 loss: 1.3713 loss_prob: 0.7527 loss_thr: 0.4900 loss_db: 0.1285 2022/11/02 17:22:52 - mmengine - INFO - Epoch(train) [482][10/63] lr: 1.3635e-03 eta: 7:24:12 time: 0.8107 data_time: 0.2491 memory: 14901 loss: 1.3590 loss_prob: 0.7374 loss_thr: 0.4961 loss_db: 0.1255 2022/11/02 17:22:55 - mmengine - INFO - Epoch(train) [482][15/63] lr: 1.3635e-03 eta: 7:24:12 time: 0.5763 data_time: 0.0231 memory: 14901 loss: 1.3194 loss_prob: 0.7176 loss_thr: 0.4790 loss_db: 0.1229 2022/11/02 17:22:58 - mmengine - INFO - Epoch(train) [482][20/63] lr: 1.3635e-03 eta: 7:24:06 time: 0.5552 data_time: 0.0142 memory: 14901 loss: 1.3049 loss_prob: 0.7126 loss_thr: 0.4696 loss_db: 0.1227 2022/11/02 17:23:02 - mmengine - INFO - Epoch(train) [482][25/63] lr: 1.3635e-03 eta: 7:24:06 time: 0.6625 data_time: 0.0316 memory: 14901 loss: 1.4052 loss_prob: 0.7665 loss_thr: 0.5100 loss_db: 0.1287 2022/11/02 17:23:05 - mmengine - INFO - Epoch(train) [482][30/63] lr: 1.3635e-03 eta: 7:24:02 time: 0.7367 data_time: 0.0358 memory: 14901 loss: 1.4252 loss_prob: 0.7813 loss_thr: 0.5104 loss_db: 0.1335 2022/11/02 17:23:09 - mmengine - INFO - Epoch(train) [482][35/63] lr: 1.3635e-03 eta: 7:24:02 time: 0.6850 data_time: 0.0251 memory: 14901 loss: 1.3709 loss_prob: 0.7507 loss_thr: 0.4919 loss_db: 0.1283 2022/11/02 17:23:12 - mmengine - INFO - Epoch(train) [482][40/63] lr: 1.3635e-03 eta: 7:23:57 time: 0.6237 data_time: 0.0198 memory: 14901 loss: 1.4081 loss_prob: 0.7679 loss_thr: 0.5138 loss_db: 0.1264 2022/11/02 17:23:15 - mmengine - INFO - Epoch(train) [482][45/63] lr: 1.3635e-03 eta: 7:23:57 time: 0.5900 data_time: 0.0110 memory: 14901 loss: 1.3900 loss_prob: 0.7582 loss_thr: 0.5054 loss_db: 0.1263 2022/11/02 17:23:17 - mmengine - INFO - Epoch(train) [482][50/63] lr: 1.3635e-03 eta: 7:23:51 time: 0.5880 data_time: 0.0192 memory: 14901 loss: 1.3284 loss_prob: 0.7195 loss_thr: 0.4860 loss_db: 0.1229 2022/11/02 17:23:21 - mmengine - INFO - Epoch(train) [482][55/63] lr: 1.3635e-03 eta: 7:23:51 time: 0.6071 data_time: 0.0214 memory: 14901 loss: 1.2946 loss_prob: 0.6854 loss_thr: 0.4925 loss_db: 0.1168 2022/11/02 17:23:23 - mmengine - INFO - Epoch(train) [482][60/63] lr: 1.3635e-03 eta: 7:23:45 time: 0.5895 data_time: 0.0140 memory: 14901 loss: 1.3264 loss_prob: 0.7074 loss_thr: 0.5004 loss_db: 0.1186 2022/11/02 17:23:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:23:31 - mmengine - INFO - Epoch(train) [483][5/63] lr: 1.3618e-03 eta: 7:23:45 time: 0.8354 data_time: 0.2347 memory: 14901 loss: 1.4009 loss_prob: 0.7503 loss_thr: 0.5241 loss_db: 0.1264 2022/11/02 17:23:34 - mmengine - INFO - Epoch(train) [483][10/63] lr: 1.3618e-03 eta: 7:23:39 time: 0.8864 data_time: 0.2315 memory: 14901 loss: 1.3242 loss_prob: 0.6974 loss_thr: 0.5099 loss_db: 0.1169 2022/11/02 17:23:36 - mmengine - INFO - Epoch(train) [483][15/63] lr: 1.3618e-03 eta: 7:23:39 time: 0.5703 data_time: 0.0104 memory: 14901 loss: 1.3418 loss_prob: 0.7115 loss_thr: 0.5122 loss_db: 0.1180 2022/11/02 17:23:39 - mmengine - INFO - Epoch(train) [483][20/63] lr: 1.3618e-03 eta: 7:23:33 time: 0.5693 data_time: 0.0136 memory: 14901 loss: 1.3433 loss_prob: 0.7191 loss_thr: 0.5025 loss_db: 0.1217 2022/11/02 17:23:43 - mmengine - INFO - Epoch(train) [483][25/63] lr: 1.3618e-03 eta: 7:23:33 time: 0.6202 data_time: 0.0218 memory: 14901 loss: 1.3235 loss_prob: 0.7128 loss_thr: 0.4888 loss_db: 0.1219 2022/11/02 17:23:46 - mmengine - INFO - Epoch(train) [483][30/63] lr: 1.3618e-03 eta: 7:23:27 time: 0.6063 data_time: 0.0381 memory: 14901 loss: 1.4647 loss_prob: 0.7967 loss_thr: 0.5351 loss_db: 0.1329 2022/11/02 17:23:48 - mmengine - INFO - Epoch(train) [483][35/63] lr: 1.3618e-03 eta: 7:23:27 time: 0.5352 data_time: 0.0243 memory: 14901 loss: 1.4437 loss_prob: 0.7727 loss_thr: 0.5396 loss_db: 0.1314 2022/11/02 17:23:52 - mmengine - INFO - Epoch(train) [483][40/63] lr: 1.3618e-03 eta: 7:23:23 time: 0.6683 data_time: 0.0080 memory: 14901 loss: 1.3263 loss_prob: 0.7063 loss_thr: 0.4980 loss_db: 0.1220 2022/11/02 17:23:55 - mmengine - INFO - Epoch(train) [483][45/63] lr: 1.3618e-03 eta: 7:23:23 time: 0.7081 data_time: 0.0091 memory: 14901 loss: 1.3472 loss_prob: 0.7259 loss_thr: 0.4967 loss_db: 0.1246 2022/11/02 17:23:58 - mmengine - INFO - Epoch(train) [483][50/63] lr: 1.3618e-03 eta: 7:23:17 time: 0.5949 data_time: 0.0188 memory: 14901 loss: 1.3954 loss_prob: 0.7580 loss_thr: 0.5087 loss_db: 0.1287 2022/11/02 17:24:01 - mmengine - INFO - Epoch(train) [483][55/63] lr: 1.3618e-03 eta: 7:23:17 time: 0.5658 data_time: 0.0287 memory: 14901 loss: 1.4122 loss_prob: 0.7762 loss_thr: 0.5048 loss_db: 0.1312 2022/11/02 17:24:03 - mmengine - INFO - Epoch(train) [483][60/63] lr: 1.3618e-03 eta: 7:23:10 time: 0.5024 data_time: 0.0186 memory: 14901 loss: 1.3659 loss_prob: 0.7527 loss_thr: 0.4836 loss_db: 0.1297 2022/11/02 17:24:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:24:11 - mmengine - INFO - Epoch(train) [484][5/63] lr: 1.3601e-03 eta: 7:23:10 time: 0.8402 data_time: 0.2445 memory: 14901 loss: 1.4613 loss_prob: 0.8056 loss_thr: 0.5195 loss_db: 0.1362 2022/11/02 17:24:13 - mmengine - INFO - Epoch(train) [484][10/63] lr: 1.3601e-03 eta: 7:23:04 time: 0.8954 data_time: 0.2456 memory: 14901 loss: 1.4122 loss_prob: 0.7788 loss_thr: 0.5017 loss_db: 0.1317 2022/11/02 17:24:16 - mmengine - INFO - Epoch(train) [484][15/63] lr: 1.3601e-03 eta: 7:23:04 time: 0.5559 data_time: 0.0135 memory: 14901 loss: 1.4404 loss_prob: 0.8111 loss_thr: 0.4993 loss_db: 0.1301 2022/11/02 17:24:19 - mmengine - INFO - Epoch(train) [484][20/63] lr: 1.3601e-03 eta: 7:22:58 time: 0.5639 data_time: 0.0133 memory: 14901 loss: 1.4640 loss_prob: 0.8281 loss_thr: 0.5036 loss_db: 0.1322 2022/11/02 17:24:22 - mmengine - INFO - Epoch(train) [484][25/63] lr: 1.3601e-03 eta: 7:22:58 time: 0.5929 data_time: 0.0219 memory: 14901 loss: 1.3479 loss_prob: 0.7374 loss_thr: 0.4848 loss_db: 0.1256 2022/11/02 17:24:25 - mmengine - INFO - Epoch(train) [484][30/63] lr: 1.3601e-03 eta: 7:22:52 time: 0.6107 data_time: 0.0404 memory: 14901 loss: 1.3742 loss_prob: 0.7478 loss_thr: 0.4981 loss_db: 0.1283 2022/11/02 17:24:28 - mmengine - INFO - Epoch(train) [484][35/63] lr: 1.3601e-03 eta: 7:22:52 time: 0.6181 data_time: 0.0271 memory: 14901 loss: 1.3243 loss_prob: 0.7153 loss_thr: 0.4858 loss_db: 0.1232 2022/11/02 17:24:31 - mmengine - INFO - Epoch(train) [484][40/63] lr: 1.3601e-03 eta: 7:22:46 time: 0.5827 data_time: 0.0126 memory: 14901 loss: 1.3822 loss_prob: 0.7581 loss_thr: 0.4933 loss_db: 0.1308 2022/11/02 17:24:34 - mmengine - INFO - Epoch(train) [484][45/63] lr: 1.3601e-03 eta: 7:22:46 time: 0.5701 data_time: 0.0121 memory: 14901 loss: 1.4894 loss_prob: 0.8186 loss_thr: 0.5315 loss_db: 0.1392 2022/11/02 17:24:37 - mmengine - INFO - Epoch(train) [484][50/63] lr: 1.3601e-03 eta: 7:22:40 time: 0.5612 data_time: 0.0133 memory: 14901 loss: 1.4163 loss_prob: 0.7792 loss_thr: 0.5074 loss_db: 0.1297 2022/11/02 17:24:39 - mmengine - INFO - Epoch(train) [484][55/63] lr: 1.3601e-03 eta: 7:22:40 time: 0.5275 data_time: 0.0262 memory: 14901 loss: 1.3555 loss_prob: 0.7498 loss_thr: 0.4812 loss_db: 0.1245 2022/11/02 17:24:42 - mmengine - INFO - Epoch(train) [484][60/63] lr: 1.3601e-03 eta: 7:22:33 time: 0.5038 data_time: 0.0206 memory: 14901 loss: 1.4382 loss_prob: 0.7984 loss_thr: 0.5065 loss_db: 0.1332 2022/11/02 17:24:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:24:48 - mmengine - INFO - Epoch(train) [485][5/63] lr: 1.3584e-03 eta: 7:22:33 time: 0.6875 data_time: 0.2094 memory: 14901 loss: 1.3320 loss_prob: 0.7143 loss_thr: 0.4952 loss_db: 0.1225 2022/11/02 17:24:50 - mmengine - INFO - Epoch(train) [485][10/63] lr: 1.3584e-03 eta: 7:22:24 time: 0.7140 data_time: 0.2143 memory: 14901 loss: 1.3413 loss_prob: 0.7318 loss_thr: 0.4888 loss_db: 0.1206 2022/11/02 17:24:53 - mmengine - INFO - Epoch(train) [485][15/63] lr: 1.3584e-03 eta: 7:22:24 time: 0.4922 data_time: 0.0150 memory: 14901 loss: 1.3934 loss_prob: 0.7702 loss_thr: 0.4955 loss_db: 0.1277 2022/11/02 17:24:55 - mmengine - INFO - Epoch(train) [485][20/63] lr: 1.3584e-03 eta: 7:22:17 time: 0.5007 data_time: 0.0123 memory: 14901 loss: 1.3062 loss_prob: 0.6970 loss_thr: 0.4907 loss_db: 0.1186 2022/11/02 17:24:58 - mmengine - INFO - Epoch(train) [485][25/63] lr: 1.3584e-03 eta: 7:22:17 time: 0.5096 data_time: 0.0254 memory: 14901 loss: 1.3114 loss_prob: 0.6940 loss_thr: 0.4987 loss_db: 0.1186 2022/11/02 17:25:00 - mmengine - INFO - Epoch(train) [485][30/63] lr: 1.3584e-03 eta: 7:22:10 time: 0.5232 data_time: 0.0373 memory: 14901 loss: 1.3203 loss_prob: 0.7050 loss_thr: 0.4961 loss_db: 0.1192 2022/11/02 17:25:03 - mmengine - INFO - Epoch(train) [485][35/63] lr: 1.3584e-03 eta: 7:22:10 time: 0.5131 data_time: 0.0261 memory: 14901 loss: 1.3496 loss_prob: 0.7233 loss_thr: 0.5045 loss_db: 0.1218 2022/11/02 17:25:05 - mmengine - INFO - Epoch(train) [485][40/63] lr: 1.3584e-03 eta: 7:22:03 time: 0.5124 data_time: 0.0111 memory: 14901 loss: 1.2891 loss_prob: 0.6932 loss_thr: 0.4775 loss_db: 0.1184 2022/11/02 17:25:08 - mmengine - INFO - Epoch(train) [485][45/63] lr: 1.3584e-03 eta: 7:22:03 time: 0.5507 data_time: 0.0089 memory: 14901 loss: 1.3266 loss_prob: 0.7212 loss_thr: 0.4822 loss_db: 0.1232 2022/11/02 17:25:11 - mmengine - INFO - Epoch(train) [485][50/63] lr: 1.3584e-03 eta: 7:21:57 time: 0.5564 data_time: 0.0183 memory: 14901 loss: 1.4104 loss_prob: 0.7793 loss_thr: 0.4981 loss_db: 0.1329 2022/11/02 17:25:14 - mmengine - INFO - Epoch(train) [485][55/63] lr: 1.3584e-03 eta: 7:21:57 time: 0.5549 data_time: 0.0282 memory: 14901 loss: 1.4268 loss_prob: 0.7930 loss_thr: 0.4989 loss_db: 0.1350 2022/11/02 17:25:17 - mmengine - INFO - Epoch(train) [485][60/63] lr: 1.3584e-03 eta: 7:21:51 time: 0.5662 data_time: 0.0162 memory: 14901 loss: 1.3926 loss_prob: 0.7697 loss_thr: 0.4953 loss_db: 0.1276 2022/11/02 17:25:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:25:24 - mmengine - INFO - Epoch(train) [486][5/63] lr: 1.3567e-03 eta: 7:21:51 time: 0.7814 data_time: 0.1986 memory: 14901 loss: 1.3617 loss_prob: 0.7390 loss_thr: 0.4983 loss_db: 0.1244 2022/11/02 17:25:26 - mmengine - INFO - Epoch(train) [486][10/63] lr: 1.3567e-03 eta: 7:21:44 time: 0.8032 data_time: 0.2095 memory: 14901 loss: 1.3357 loss_prob: 0.7112 loss_thr: 0.5019 loss_db: 0.1226 2022/11/02 17:25:29 - mmengine - INFO - Epoch(train) [486][15/63] lr: 1.3567e-03 eta: 7:21:44 time: 0.5293 data_time: 0.0165 memory: 14901 loss: 1.2747 loss_prob: 0.6755 loss_thr: 0.4828 loss_db: 0.1164 2022/11/02 17:25:31 - mmengine - INFO - Epoch(train) [486][20/63] lr: 1.3567e-03 eta: 7:21:37 time: 0.5229 data_time: 0.0076 memory: 14901 loss: 1.2811 loss_prob: 0.6796 loss_thr: 0.4849 loss_db: 0.1166 2022/11/02 17:25:34 - mmengine - INFO - Epoch(train) [486][25/63] lr: 1.3567e-03 eta: 7:21:37 time: 0.5513 data_time: 0.0120 memory: 14901 loss: 1.2756 loss_prob: 0.6783 loss_thr: 0.4819 loss_db: 0.1153 2022/11/02 17:25:38 - mmengine - INFO - Epoch(train) [486][30/63] lr: 1.3567e-03 eta: 7:21:32 time: 0.6516 data_time: 0.0359 memory: 14901 loss: 1.2375 loss_prob: 0.6617 loss_thr: 0.4644 loss_db: 0.1115 2022/11/02 17:25:41 - mmengine - INFO - Epoch(train) [486][35/63] lr: 1.3567e-03 eta: 7:21:32 time: 0.6313 data_time: 0.0403 memory: 14901 loss: 1.3600 loss_prob: 0.7433 loss_thr: 0.4896 loss_db: 0.1270 2022/11/02 17:25:44 - mmengine - INFO - Epoch(train) [486][40/63] lr: 1.3567e-03 eta: 7:21:25 time: 0.5561 data_time: 0.0147 memory: 14901 loss: 1.4430 loss_prob: 0.7915 loss_thr: 0.5158 loss_db: 0.1357 2022/11/02 17:25:46 - mmengine - INFO - Epoch(train) [486][45/63] lr: 1.3567e-03 eta: 7:21:25 time: 0.5435 data_time: 0.0062 memory: 14901 loss: 1.3028 loss_prob: 0.7044 loss_thr: 0.4802 loss_db: 0.1183 2022/11/02 17:25:49 - mmengine - INFO - Epoch(train) [486][50/63] lr: 1.3567e-03 eta: 7:21:19 time: 0.5414 data_time: 0.0100 memory: 14901 loss: 1.2484 loss_prob: 0.6752 loss_thr: 0.4599 loss_db: 0.1134 2022/11/02 17:25:52 - mmengine - INFO - Epoch(train) [486][55/63] lr: 1.3567e-03 eta: 7:21:19 time: 0.6201 data_time: 0.0212 memory: 14901 loss: 1.2898 loss_prob: 0.7008 loss_thr: 0.4675 loss_db: 0.1216 2022/11/02 17:25:55 - mmengine - INFO - Epoch(train) [486][60/63] lr: 1.3567e-03 eta: 7:21:13 time: 0.6047 data_time: 0.0219 memory: 14901 loss: 1.3746 loss_prob: 0.7540 loss_thr: 0.4910 loss_db: 0.1296 2022/11/02 17:25:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:26:03 - mmengine - INFO - Epoch(train) [487][5/63] lr: 1.3549e-03 eta: 7:21:13 time: 0.8879 data_time: 0.2928 memory: 14901 loss: 1.4324 loss_prob: 0.7780 loss_thr: 0.5214 loss_db: 0.1330 2022/11/02 17:26:06 - mmengine - INFO - Epoch(train) [487][10/63] lr: 1.3549e-03 eta: 7:21:07 time: 0.8968 data_time: 0.2965 memory: 14901 loss: 1.4442 loss_prob: 0.7842 loss_thr: 0.5259 loss_db: 0.1341 2022/11/02 17:26:08 - mmengine - INFO - Epoch(train) [487][15/63] lr: 1.3549e-03 eta: 7:21:07 time: 0.5524 data_time: 0.0122 memory: 14901 loss: 1.3054 loss_prob: 0.7053 loss_thr: 0.4807 loss_db: 0.1193 2022/11/02 17:26:11 - mmengine - INFO - Epoch(train) [487][20/63] lr: 1.3549e-03 eta: 7:21:01 time: 0.5177 data_time: 0.0104 memory: 14901 loss: 1.3160 loss_prob: 0.7193 loss_thr: 0.4764 loss_db: 0.1203 2022/11/02 17:26:13 - mmengine - INFO - Epoch(train) [487][25/63] lr: 1.3549e-03 eta: 7:21:01 time: 0.4968 data_time: 0.0107 memory: 14901 loss: 1.4520 loss_prob: 0.8023 loss_thr: 0.5146 loss_db: 0.1351 2022/11/02 17:26:16 - mmengine - INFO - Epoch(train) [487][30/63] lr: 1.3549e-03 eta: 7:20:54 time: 0.5411 data_time: 0.0568 memory: 14901 loss: 1.4676 loss_prob: 0.8096 loss_thr: 0.5221 loss_db: 0.1360 2022/11/02 17:26:19 - mmengine - INFO - Epoch(train) [487][35/63] lr: 1.3549e-03 eta: 7:20:54 time: 0.5347 data_time: 0.0565 memory: 14901 loss: 1.3411 loss_prob: 0.7246 loss_thr: 0.4933 loss_db: 0.1233 2022/11/02 17:26:21 - mmengine - INFO - Epoch(train) [487][40/63] lr: 1.3549e-03 eta: 7:20:47 time: 0.4938 data_time: 0.0092 memory: 14901 loss: 1.2516 loss_prob: 0.6591 loss_thr: 0.4792 loss_db: 0.1133 2022/11/02 17:26:24 - mmengine - INFO - Epoch(train) [487][45/63] lr: 1.3549e-03 eta: 7:20:47 time: 0.4813 data_time: 0.0073 memory: 14901 loss: 1.5341 loss_prob: 0.8998 loss_thr: 0.5009 loss_db: 0.1334 2022/11/02 17:26:26 - mmengine - INFO - Epoch(train) [487][50/63] lr: 1.3549e-03 eta: 7:20:40 time: 0.5153 data_time: 0.0235 memory: 14901 loss: 1.6647 loss_prob: 0.9849 loss_thr: 0.5316 loss_db: 0.1482 2022/11/02 17:26:30 - mmengine - INFO - Epoch(train) [487][55/63] lr: 1.3549e-03 eta: 7:20:40 time: 0.5950 data_time: 0.0322 memory: 14901 loss: 1.4388 loss_prob: 0.7889 loss_thr: 0.5199 loss_db: 0.1301 2022/11/02 17:26:32 - mmengine - INFO - Epoch(train) [487][60/63] lr: 1.3549e-03 eta: 7:20:33 time: 0.5642 data_time: 0.0142 memory: 14901 loss: 1.4593 loss_prob: 0.8065 loss_thr: 0.5220 loss_db: 0.1307 2022/11/02 17:26:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:26:39 - mmengine - INFO - Epoch(train) [488][5/63] lr: 1.3532e-03 eta: 7:20:33 time: 0.8004 data_time: 0.2940 memory: 14901 loss: 1.4673 loss_prob: 0.7988 loss_thr: 0.5322 loss_db: 0.1363 2022/11/02 17:26:42 - mmengine - INFO - Epoch(train) [488][10/63] lr: 1.3532e-03 eta: 7:20:27 time: 0.8585 data_time: 0.2898 memory: 14901 loss: 1.3772 loss_prob: 0.7444 loss_thr: 0.5080 loss_db: 0.1248 2022/11/02 17:26:45 - mmengine - INFO - Epoch(train) [488][15/63] lr: 1.3532e-03 eta: 7:20:27 time: 0.6226 data_time: 0.0076 memory: 14901 loss: 1.3380 loss_prob: 0.7170 loss_thr: 0.5012 loss_db: 0.1199 2022/11/02 17:26:49 - mmengine - INFO - Epoch(train) [488][20/63] lr: 1.3532e-03 eta: 7:20:22 time: 0.6399 data_time: 0.0106 memory: 14901 loss: 1.4178 loss_prob: 0.7744 loss_thr: 0.5115 loss_db: 0.1319 2022/11/02 17:26:51 - mmengine - INFO - Epoch(train) [488][25/63] lr: 1.3532e-03 eta: 7:20:22 time: 0.6222 data_time: 0.0491 memory: 14901 loss: 1.3537 loss_prob: 0.7382 loss_thr: 0.4881 loss_db: 0.1273 2022/11/02 17:26:54 - mmengine - INFO - Epoch(train) [488][30/63] lr: 1.3532e-03 eta: 7:20:16 time: 0.5678 data_time: 0.0535 memory: 14901 loss: 1.3208 loss_prob: 0.7205 loss_thr: 0.4793 loss_db: 0.1211 2022/11/02 17:26:57 - mmengine - INFO - Epoch(train) [488][35/63] lr: 1.3532e-03 eta: 7:20:16 time: 0.5792 data_time: 0.0129 memory: 14901 loss: 1.4322 loss_prob: 0.7923 loss_thr: 0.5094 loss_db: 0.1306 2022/11/02 17:27:00 - mmengine - INFO - Epoch(train) [488][40/63] lr: 1.3532e-03 eta: 7:20:10 time: 0.5587 data_time: 0.0077 memory: 14901 loss: 1.3512 loss_prob: 0.7365 loss_thr: 0.4914 loss_db: 0.1233 2022/11/02 17:27:02 - mmengine - INFO - Epoch(train) [488][45/63] lr: 1.3532e-03 eta: 7:20:10 time: 0.5007 data_time: 0.0081 memory: 14901 loss: 1.4174 loss_prob: 0.8018 loss_thr: 0.4822 loss_db: 0.1334 2022/11/02 17:27:05 - mmengine - INFO - Epoch(train) [488][50/63] lr: 1.3532e-03 eta: 7:20:03 time: 0.5215 data_time: 0.0258 memory: 14901 loss: 1.5541 loss_prob: 0.8972 loss_thr: 0.5096 loss_db: 0.1473 2022/11/02 17:27:08 - mmengine - INFO - Epoch(train) [488][55/63] lr: 1.3532e-03 eta: 7:20:03 time: 0.5452 data_time: 0.0279 memory: 14901 loss: 1.4747 loss_prob: 0.8242 loss_thr: 0.5139 loss_db: 0.1366 2022/11/02 17:27:11 - mmengine - INFO - Epoch(train) [488][60/63] lr: 1.3532e-03 eta: 7:19:56 time: 0.5609 data_time: 0.0082 memory: 14901 loss: 1.5406 loss_prob: 0.8580 loss_thr: 0.5411 loss_db: 0.1415 2022/11/02 17:27:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:27:17 - mmengine - INFO - Epoch(train) [489][5/63] lr: 1.3515e-03 eta: 7:19:56 time: 0.7856 data_time: 0.2646 memory: 14901 loss: 1.4031 loss_prob: 0.7601 loss_thr: 0.5121 loss_db: 0.1309 2022/11/02 17:27:20 - mmengine - INFO - Epoch(train) [489][10/63] lr: 1.3515e-03 eta: 7:19:50 time: 0.8229 data_time: 0.2603 memory: 14901 loss: 1.3863 loss_prob: 0.7478 loss_thr: 0.5091 loss_db: 0.1293 2022/11/02 17:27:23 - mmengine - INFO - Epoch(train) [489][15/63] lr: 1.3515e-03 eta: 7:19:50 time: 0.5780 data_time: 0.0060 memory: 14901 loss: 1.2821 loss_prob: 0.6846 loss_thr: 0.4823 loss_db: 0.1151 2022/11/02 17:27:26 - mmengine - INFO - Epoch(train) [489][20/63] lr: 1.3515e-03 eta: 7:19:43 time: 0.5493 data_time: 0.0092 memory: 14901 loss: 1.3286 loss_prob: 0.7231 loss_thr: 0.4846 loss_db: 0.1209 2022/11/02 17:27:29 - mmengine - INFO - Epoch(train) [489][25/63] lr: 1.3515e-03 eta: 7:19:43 time: 0.5444 data_time: 0.0148 memory: 14901 loss: 1.4316 loss_prob: 0.8099 loss_thr: 0.4915 loss_db: 0.1302 2022/11/02 17:27:31 - mmengine - INFO - Epoch(train) [489][30/63] lr: 1.3515e-03 eta: 7:19:37 time: 0.5756 data_time: 0.0332 memory: 14901 loss: 1.4089 loss_prob: 0.7950 loss_thr: 0.4880 loss_db: 0.1260 2022/11/02 17:27:34 - mmengine - INFO - Epoch(train) [489][35/63] lr: 1.3515e-03 eta: 7:19:37 time: 0.5808 data_time: 0.0383 memory: 14901 loss: 1.3169 loss_prob: 0.7259 loss_thr: 0.4698 loss_db: 0.1212 2022/11/02 17:27:37 - mmengine - INFO - Epoch(train) [489][40/63] lr: 1.3515e-03 eta: 7:19:31 time: 0.5526 data_time: 0.0186 memory: 14901 loss: 1.2835 loss_prob: 0.7026 loss_thr: 0.4587 loss_db: 0.1222 2022/11/02 17:27:39 - mmengine - INFO - Epoch(train) [489][45/63] lr: 1.3515e-03 eta: 7:19:31 time: 0.5051 data_time: 0.0091 memory: 14901 loss: 1.3674 loss_prob: 0.7566 loss_thr: 0.4816 loss_db: 0.1292 2022/11/02 17:27:43 - mmengine - INFO - Epoch(train) [489][50/63] lr: 1.3515e-03 eta: 7:19:25 time: 0.5791 data_time: 0.0273 memory: 14901 loss: 1.4517 loss_prob: 0.8082 loss_thr: 0.5060 loss_db: 0.1375 2022/11/02 17:27:45 - mmengine - INFO - Epoch(train) [489][55/63] lr: 1.3515e-03 eta: 7:19:25 time: 0.5985 data_time: 0.0295 memory: 14901 loss: 1.3966 loss_prob: 0.7649 loss_thr: 0.4964 loss_db: 0.1353 2022/11/02 17:27:48 - mmengine - INFO - Epoch(train) [489][60/63] lr: 1.3515e-03 eta: 7:19:17 time: 0.4983 data_time: 0.0111 memory: 14901 loss: 1.3235 loss_prob: 0.7258 loss_thr: 0.4737 loss_db: 0.1240 2022/11/02 17:27:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:27:55 - mmengine - INFO - Epoch(train) [490][5/63] lr: 1.3498e-03 eta: 7:19:17 time: 0.8223 data_time: 0.2318 memory: 14901 loss: 1.4172 loss_prob: 0.7973 loss_thr: 0.4887 loss_db: 0.1311 2022/11/02 17:27:58 - mmengine - INFO - Epoch(train) [490][10/63] lr: 1.3498e-03 eta: 7:19:12 time: 0.8934 data_time: 0.2311 memory: 14901 loss: 1.4333 loss_prob: 0.8068 loss_thr: 0.4936 loss_db: 0.1329 2022/11/02 17:28:01 - mmengine - INFO - Epoch(train) [490][15/63] lr: 1.3498e-03 eta: 7:19:12 time: 0.5689 data_time: 0.0082 memory: 14901 loss: 1.2970 loss_prob: 0.6973 loss_thr: 0.4814 loss_db: 0.1182 2022/11/02 17:28:04 - mmengine - INFO - Epoch(train) [490][20/63] lr: 1.3498e-03 eta: 7:19:05 time: 0.5628 data_time: 0.0094 memory: 14901 loss: 1.2602 loss_prob: 0.6743 loss_thr: 0.4717 loss_db: 0.1142 2022/11/02 17:28:07 - mmengine - INFO - Epoch(train) [490][25/63] lr: 1.3498e-03 eta: 7:19:05 time: 0.6120 data_time: 0.0116 memory: 14901 loss: 1.2437 loss_prob: 0.6645 loss_thr: 0.4648 loss_db: 0.1143 2022/11/02 17:28:10 - mmengine - INFO - Epoch(train) [490][30/63] lr: 1.3498e-03 eta: 7:18:59 time: 0.5736 data_time: 0.0409 memory: 14901 loss: 1.3210 loss_prob: 0.7108 loss_thr: 0.4886 loss_db: 0.1216 2022/11/02 17:28:12 - mmengine - INFO - Epoch(train) [490][35/63] lr: 1.3498e-03 eta: 7:18:59 time: 0.5615 data_time: 0.0380 memory: 14901 loss: 1.3174 loss_prob: 0.7121 loss_thr: 0.4844 loss_db: 0.1208 2022/11/02 17:28:15 - mmengine - INFO - Epoch(train) [490][40/63] lr: 1.3498e-03 eta: 7:18:53 time: 0.5723 data_time: 0.0083 memory: 14901 loss: 1.2913 loss_prob: 0.6908 loss_thr: 0.4819 loss_db: 0.1186 2022/11/02 17:28:18 - mmengine - INFO - Epoch(train) [490][45/63] lr: 1.3498e-03 eta: 7:18:53 time: 0.5284 data_time: 0.0083 memory: 14901 loss: 1.3437 loss_prob: 0.7299 loss_thr: 0.4911 loss_db: 0.1227 2022/11/02 17:28:21 - mmengine - INFO - Epoch(train) [490][50/63] lr: 1.3498e-03 eta: 7:18:47 time: 0.5517 data_time: 0.0162 memory: 14901 loss: 1.2956 loss_prob: 0.7016 loss_thr: 0.4755 loss_db: 0.1184 2022/11/02 17:28:24 - mmengine - INFO - Epoch(train) [490][55/63] lr: 1.3498e-03 eta: 7:18:47 time: 0.5747 data_time: 0.0307 memory: 14901 loss: 1.7237 loss_prob: 1.0460 loss_thr: 0.5192 loss_db: 0.1586 2022/11/02 17:28:27 - mmengine - INFO - Epoch(train) [490][60/63] lr: 1.3498e-03 eta: 7:18:41 time: 0.5846 data_time: 0.0263 memory: 14901 loss: 1.8652 loss_prob: 1.1377 loss_thr: 0.5535 loss_db: 0.1740 2022/11/02 17:28:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:28:33 - mmengine - INFO - Epoch(train) [491][5/63] lr: 1.3481e-03 eta: 7:18:41 time: 0.7952 data_time: 0.2430 memory: 14901 loss: 1.5602 loss_prob: 0.8741 loss_thr: 0.5373 loss_db: 0.1488 2022/11/02 17:28:36 - mmengine - INFO - Epoch(train) [491][10/63] lr: 1.3481e-03 eta: 7:18:34 time: 0.8312 data_time: 0.2449 memory: 14901 loss: 1.5103 loss_prob: 0.8394 loss_thr: 0.5344 loss_db: 0.1366 2022/11/02 17:28:39 - mmengine - INFO - Epoch(train) [491][15/63] lr: 1.3481e-03 eta: 7:18:34 time: 0.6064 data_time: 0.0080 memory: 14901 loss: 1.4361 loss_prob: 0.7970 loss_thr: 0.5080 loss_db: 0.1311 2022/11/02 17:28:43 - mmengine - INFO - Epoch(train) [491][20/63] lr: 1.3481e-03 eta: 7:18:29 time: 0.6608 data_time: 0.0092 memory: 14901 loss: 1.3831 loss_prob: 0.7642 loss_thr: 0.4912 loss_db: 0.1277 2022/11/02 17:28:46 - mmengine - INFO - Epoch(train) [491][25/63] lr: 1.3481e-03 eta: 7:18:29 time: 0.6434 data_time: 0.0480 memory: 14901 loss: 1.3876 loss_prob: 0.7596 loss_thr: 0.4983 loss_db: 0.1298 2022/11/02 17:28:49 - mmengine - INFO - Epoch(train) [491][30/63] lr: 1.3481e-03 eta: 7:18:24 time: 0.6533 data_time: 0.0637 memory: 14901 loss: 1.3964 loss_prob: 0.7738 loss_thr: 0.4926 loss_db: 0.1299 2022/11/02 17:28:52 - mmengine - INFO - Epoch(train) [491][35/63] lr: 1.3481e-03 eta: 7:18:24 time: 0.6607 data_time: 0.0274 memory: 14901 loss: 1.3244 loss_prob: 0.7452 loss_thr: 0.4523 loss_db: 0.1270 2022/11/02 17:28:55 - mmengine - INFO - Epoch(train) [491][40/63] lr: 1.3481e-03 eta: 7:18:19 time: 0.5943 data_time: 0.0107 memory: 14901 loss: 1.4013 loss_prob: 0.7951 loss_thr: 0.4712 loss_db: 0.1351 2022/11/02 17:28:58 - mmengine - INFO - Epoch(train) [491][45/63] lr: 1.3481e-03 eta: 7:18:19 time: 0.5668 data_time: 0.0088 memory: 14901 loss: 1.4007 loss_prob: 0.7818 loss_thr: 0.4917 loss_db: 0.1273 2022/11/02 17:29:01 - mmengine - INFO - Epoch(train) [491][50/63] lr: 1.3481e-03 eta: 7:18:12 time: 0.5541 data_time: 0.0238 memory: 14901 loss: 1.3208 loss_prob: 0.7138 loss_thr: 0.4888 loss_db: 0.1182 2022/11/02 17:29:04 - mmengine - INFO - Epoch(train) [491][55/63] lr: 1.3481e-03 eta: 7:18:12 time: 0.5545 data_time: 0.0300 memory: 14901 loss: 1.4071 loss_prob: 0.7655 loss_thr: 0.5138 loss_db: 0.1279 2022/11/02 17:29:06 - mmengine - INFO - Epoch(train) [491][60/63] lr: 1.3481e-03 eta: 7:18:06 time: 0.5532 data_time: 0.0143 memory: 14901 loss: 1.4063 loss_prob: 0.7683 loss_thr: 0.5097 loss_db: 0.1282 2022/11/02 17:29:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:29:14 - mmengine - INFO - Epoch(train) [492][5/63] lr: 1.3464e-03 eta: 7:18:06 time: 0.8457 data_time: 0.2431 memory: 14901 loss: 1.3285 loss_prob: 0.7128 loss_thr: 0.4960 loss_db: 0.1196 2022/11/02 17:29:16 - mmengine - INFO - Epoch(train) [492][10/63] lr: 1.3464e-03 eta: 7:17:59 time: 0.8118 data_time: 0.2446 memory: 14901 loss: 1.4153 loss_prob: 0.7820 loss_thr: 0.5021 loss_db: 0.1312 2022/11/02 17:29:19 - mmengine - INFO - Epoch(train) [492][15/63] lr: 1.3464e-03 eta: 7:17:59 time: 0.5714 data_time: 0.0132 memory: 14901 loss: 1.4788 loss_prob: 0.8284 loss_thr: 0.5110 loss_db: 0.1395 2022/11/02 17:29:22 - mmengine - INFO - Epoch(train) [492][20/63] lr: 1.3464e-03 eta: 7:17:53 time: 0.6133 data_time: 0.0103 memory: 14901 loss: 1.4885 loss_prob: 0.8241 loss_thr: 0.5238 loss_db: 0.1406 2022/11/02 17:29:26 - mmengine - INFO - Epoch(train) [492][25/63] lr: 1.3464e-03 eta: 7:17:53 time: 0.6421 data_time: 0.0330 memory: 14901 loss: 1.4260 loss_prob: 0.7822 loss_thr: 0.5098 loss_db: 0.1340 2022/11/02 17:29:29 - mmengine - INFO - Epoch(train) [492][30/63] lr: 1.3464e-03 eta: 7:17:48 time: 0.6556 data_time: 0.0322 memory: 14901 loss: 1.3615 loss_prob: 0.7578 loss_thr: 0.4806 loss_db: 0.1231 2022/11/02 17:29:33 - mmengine - INFO - Epoch(train) [492][35/63] lr: 1.3464e-03 eta: 7:17:48 time: 0.7194 data_time: 0.0176 memory: 14901 loss: 1.3701 loss_prob: 0.7629 loss_thr: 0.4819 loss_db: 0.1253 2022/11/02 17:29:36 - mmengine - INFO - Epoch(train) [492][40/63] lr: 1.3464e-03 eta: 7:17:44 time: 0.6900 data_time: 0.0184 memory: 14901 loss: 1.4523 loss_prob: 0.8143 loss_thr: 0.5037 loss_db: 0.1342 2022/11/02 17:29:39 - mmengine - INFO - Epoch(train) [492][45/63] lr: 1.3464e-03 eta: 7:17:44 time: 0.5587 data_time: 0.0129 memory: 14901 loss: 1.4552 loss_prob: 0.8201 loss_thr: 0.5023 loss_db: 0.1328 2022/11/02 17:29:42 - mmengine - INFO - Epoch(train) [492][50/63] lr: 1.3464e-03 eta: 7:17:38 time: 0.5737 data_time: 0.0285 memory: 14901 loss: 1.3391 loss_prob: 0.7347 loss_thr: 0.4810 loss_db: 0.1234 2022/11/02 17:29:44 - mmengine - INFO - Epoch(train) [492][55/63] lr: 1.3464e-03 eta: 7:17:38 time: 0.5713 data_time: 0.0344 memory: 14901 loss: 1.3703 loss_prob: 0.7494 loss_thr: 0.4925 loss_db: 0.1284 2022/11/02 17:29:47 - mmengine - INFO - Epoch(train) [492][60/63] lr: 1.3464e-03 eta: 7:17:32 time: 0.5754 data_time: 0.0175 memory: 14901 loss: 1.4096 loss_prob: 0.7761 loss_thr: 0.5032 loss_db: 0.1304 2022/11/02 17:29:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:29:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:29:54 - mmengine - INFO - Epoch(train) [493][5/63] lr: 1.3447e-03 eta: 7:17:32 time: 0.7408 data_time: 0.2026 memory: 14901 loss: 1.3139 loss_prob: 0.7185 loss_thr: 0.4776 loss_db: 0.1178 2022/11/02 17:29:56 - mmengine - INFO - Epoch(train) [493][10/63] lr: 1.3447e-03 eta: 7:17:24 time: 0.7521 data_time: 0.2219 memory: 14901 loss: 1.2411 loss_prob: 0.6586 loss_thr: 0.4699 loss_db: 0.1126 2022/11/02 17:29:59 - mmengine - INFO - Epoch(train) [493][15/63] lr: 1.3447e-03 eta: 7:17:24 time: 0.5489 data_time: 0.0290 memory: 14901 loss: 1.2152 loss_prob: 0.6364 loss_thr: 0.4663 loss_db: 0.1125 2022/11/02 17:30:02 - mmengine - INFO - Epoch(train) [493][20/63] lr: 1.3447e-03 eta: 7:17:18 time: 0.6067 data_time: 0.0096 memory: 14901 loss: 1.2058 loss_prob: 0.6410 loss_thr: 0.4543 loss_db: 0.1105 2022/11/02 17:30:05 - mmengine - INFO - Epoch(train) [493][25/63] lr: 1.3447e-03 eta: 7:17:18 time: 0.6164 data_time: 0.0187 memory: 14901 loss: 1.2574 loss_prob: 0.6771 loss_thr: 0.4657 loss_db: 0.1146 2022/11/02 17:30:09 - mmengine - INFO - Epoch(train) [493][30/63] lr: 1.3447e-03 eta: 7:17:13 time: 0.6290 data_time: 0.0313 memory: 14901 loss: 1.3355 loss_prob: 0.7241 loss_thr: 0.4885 loss_db: 0.1230 2022/11/02 17:30:12 - mmengine - INFO - Epoch(train) [493][35/63] lr: 1.3447e-03 eta: 7:17:13 time: 0.6477 data_time: 0.0340 memory: 14901 loss: 1.3617 loss_prob: 0.7427 loss_thr: 0.4922 loss_db: 0.1268 2022/11/02 17:30:15 - mmengine - INFO - Epoch(train) [493][40/63] lr: 1.3447e-03 eta: 7:17:07 time: 0.5821 data_time: 0.0183 memory: 14901 loss: 1.3522 loss_prob: 0.7277 loss_thr: 0.4995 loss_db: 0.1250 2022/11/02 17:30:18 - mmengine - INFO - Epoch(train) [493][45/63] lr: 1.3447e-03 eta: 7:17:07 time: 0.6366 data_time: 0.0074 memory: 14901 loss: 1.3737 loss_prob: 0.7290 loss_thr: 0.5201 loss_db: 0.1245 2022/11/02 17:30:21 - mmengine - INFO - Epoch(train) [493][50/63] lr: 1.3447e-03 eta: 7:17:02 time: 0.6260 data_time: 0.0197 memory: 14901 loss: 1.4567 loss_prob: 0.7968 loss_thr: 0.5246 loss_db: 0.1353 2022/11/02 17:30:24 - mmengine - INFO - Epoch(train) [493][55/63] lr: 1.3447e-03 eta: 7:17:02 time: 0.5615 data_time: 0.0288 memory: 14901 loss: 1.4787 loss_prob: 0.8275 loss_thr: 0.5108 loss_db: 0.1404 2022/11/02 17:30:27 - mmengine - INFO - Epoch(train) [493][60/63] lr: 1.3447e-03 eta: 7:16:55 time: 0.5655 data_time: 0.0242 memory: 14901 loss: 1.4209 loss_prob: 0.7804 loss_thr: 0.5083 loss_db: 0.1322 2022/11/02 17:30:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:30:34 - mmengine - INFO - Epoch(train) [494][5/63] lr: 1.3430e-03 eta: 7:16:55 time: 0.8676 data_time: 0.2174 memory: 14901 loss: 1.3280 loss_prob: 0.7224 loss_thr: 0.4855 loss_db: 0.1201 2022/11/02 17:30:36 - mmengine - INFO - Epoch(train) [494][10/63] lr: 1.3430e-03 eta: 7:16:49 time: 0.8350 data_time: 0.2149 memory: 14901 loss: 1.3316 loss_prob: 0.7277 loss_thr: 0.4816 loss_db: 0.1223 2022/11/02 17:30:39 - mmengine - INFO - Epoch(train) [494][15/63] lr: 1.3430e-03 eta: 7:16:49 time: 0.5325 data_time: 0.0109 memory: 14901 loss: 1.3482 loss_prob: 0.7391 loss_thr: 0.4853 loss_db: 0.1239 2022/11/02 17:30:42 - mmengine - INFO - Epoch(train) [494][20/63] lr: 1.3430e-03 eta: 7:16:42 time: 0.5553 data_time: 0.0121 memory: 14901 loss: 1.4603 loss_prob: 0.8015 loss_thr: 0.5274 loss_db: 0.1314 2022/11/02 17:30:45 - mmengine - INFO - Epoch(train) [494][25/63] lr: 1.3430e-03 eta: 7:16:42 time: 0.5869 data_time: 0.0092 memory: 14901 loss: 1.4329 loss_prob: 0.7782 loss_thr: 0.5245 loss_db: 0.1302 2022/11/02 17:30:49 - mmengine - INFO - Epoch(train) [494][30/63] lr: 1.3430e-03 eta: 7:16:38 time: 0.6632 data_time: 0.0379 memory: 14901 loss: 1.3633 loss_prob: 0.7398 loss_thr: 0.4982 loss_db: 0.1253 2022/11/02 17:30:52 - mmengine - INFO - Epoch(train) [494][35/63] lr: 1.3430e-03 eta: 7:16:38 time: 0.6542 data_time: 0.0399 memory: 14901 loss: 1.3574 loss_prob: 0.7278 loss_thr: 0.5058 loss_db: 0.1239 2022/11/02 17:30:55 - mmengine - INFO - Epoch(train) [494][40/63] lr: 1.3430e-03 eta: 7:16:32 time: 0.6159 data_time: 0.0144 memory: 14901 loss: 1.3221 loss_prob: 0.7136 loss_thr: 0.4862 loss_db: 0.1224 2022/11/02 17:30:58 - mmengine - INFO - Epoch(train) [494][45/63] lr: 1.3430e-03 eta: 7:16:32 time: 0.6160 data_time: 0.0139 memory: 14901 loss: 1.3076 loss_prob: 0.7015 loss_thr: 0.4884 loss_db: 0.1177 2022/11/02 17:31:00 - mmengine - INFO - Epoch(train) [494][50/63] lr: 1.3430e-03 eta: 7:16:26 time: 0.5676 data_time: 0.0228 memory: 14901 loss: 1.2667 loss_prob: 0.6723 loss_thr: 0.4803 loss_db: 0.1141 2022/11/02 17:31:04 - mmengine - INFO - Epoch(train) [494][55/63] lr: 1.3430e-03 eta: 7:16:26 time: 0.5746 data_time: 0.0266 memory: 14901 loss: 1.3452 loss_prob: 0.7458 loss_thr: 0.4715 loss_db: 0.1279 2022/11/02 17:31:06 - mmengine - INFO - Epoch(train) [494][60/63] lr: 1.3430e-03 eta: 7:16:20 time: 0.5899 data_time: 0.0149 memory: 14901 loss: 1.3379 loss_prob: 0.7400 loss_thr: 0.4724 loss_db: 0.1255 2022/11/02 17:31:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:31:13 - mmengine - INFO - Epoch(train) [495][5/63] lr: 1.3413e-03 eta: 7:16:20 time: 0.8103 data_time: 0.1929 memory: 14901 loss: 1.3312 loss_prob: 0.7306 loss_thr: 0.4786 loss_db: 0.1220 2022/11/02 17:31:16 - mmengine - INFO - Epoch(train) [495][10/63] lr: 1.3413e-03 eta: 7:16:13 time: 0.8356 data_time: 0.2050 memory: 14901 loss: 1.2812 loss_prob: 0.6962 loss_thr: 0.4661 loss_db: 0.1189 2022/11/02 17:31:19 - mmengine - INFO - Epoch(train) [495][15/63] lr: 1.3413e-03 eta: 7:16:13 time: 0.5456 data_time: 0.0272 memory: 14901 loss: 1.2962 loss_prob: 0.7036 loss_thr: 0.4700 loss_db: 0.1226 2022/11/02 17:31:22 - mmengine - INFO - Epoch(train) [495][20/63] lr: 1.3413e-03 eta: 7:16:07 time: 0.5544 data_time: 0.0228 memory: 14901 loss: 1.3449 loss_prob: 0.7342 loss_thr: 0.4843 loss_db: 0.1263 2022/11/02 17:31:25 - mmengine - INFO - Epoch(train) [495][25/63] lr: 1.3413e-03 eta: 7:16:07 time: 0.5808 data_time: 0.0225 memory: 14901 loss: 1.2756 loss_prob: 0.6853 loss_thr: 0.4765 loss_db: 0.1138 2022/11/02 17:31:28 - mmengine - INFO - Epoch(train) [495][30/63] lr: 1.3413e-03 eta: 7:16:02 time: 0.6793 data_time: 0.0347 memory: 14901 loss: 1.2810 loss_prob: 0.6781 loss_thr: 0.4886 loss_db: 0.1143 2022/11/02 17:31:31 - mmengine - INFO - Epoch(train) [495][35/63] lr: 1.3413e-03 eta: 7:16:02 time: 0.6284 data_time: 0.0343 memory: 14901 loss: 1.2883 loss_prob: 0.6831 loss_thr: 0.4866 loss_db: 0.1185 2022/11/02 17:31:34 - mmengine - INFO - Epoch(train) [495][40/63] lr: 1.3413e-03 eta: 7:15:56 time: 0.5583 data_time: 0.0196 memory: 14901 loss: 1.2351 loss_prob: 0.6610 loss_thr: 0.4626 loss_db: 0.1115 2022/11/02 17:31:37 - mmengine - INFO - Epoch(train) [495][45/63] lr: 1.3413e-03 eta: 7:15:56 time: 0.5930 data_time: 0.0144 memory: 14901 loss: 1.2506 loss_prob: 0.6680 loss_thr: 0.4705 loss_db: 0.1122 2022/11/02 17:31:39 - mmengine - INFO - Epoch(train) [495][50/63] lr: 1.3413e-03 eta: 7:15:50 time: 0.5459 data_time: 0.0133 memory: 14901 loss: 1.3239 loss_prob: 0.7061 loss_thr: 0.4986 loss_db: 0.1192 2022/11/02 17:31:42 - mmengine - INFO - Epoch(train) [495][55/63] lr: 1.3413e-03 eta: 7:15:50 time: 0.5343 data_time: 0.0290 memory: 14901 loss: 1.4115 loss_prob: 0.7700 loss_thr: 0.5147 loss_db: 0.1267 2022/11/02 17:31:45 - mmengine - INFO - Epoch(train) [495][60/63] lr: 1.3413e-03 eta: 7:15:44 time: 0.5954 data_time: 0.0312 memory: 14901 loss: 1.4466 loss_prob: 0.8038 loss_thr: 0.5095 loss_db: 0.1333 2022/11/02 17:31:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:31:53 - mmengine - INFO - Epoch(train) [496][5/63] lr: 1.3395e-03 eta: 7:15:44 time: 0.9246 data_time: 0.2439 memory: 14901 loss: 1.2286 loss_prob: 0.6582 loss_thr: 0.4586 loss_db: 0.1119 2022/11/02 17:31:56 - mmengine - INFO - Epoch(train) [496][10/63] lr: 1.3395e-03 eta: 7:15:38 time: 0.9199 data_time: 0.2387 memory: 14901 loss: 1.2581 loss_prob: 0.6729 loss_thr: 0.4710 loss_db: 0.1143 2022/11/02 17:31:59 - mmengine - INFO - Epoch(train) [496][15/63] lr: 1.3395e-03 eta: 7:15:38 time: 0.5287 data_time: 0.0124 memory: 14901 loss: 1.3415 loss_prob: 0.7216 loss_thr: 0.4950 loss_db: 0.1249 2022/11/02 17:32:02 - mmengine - INFO - Epoch(train) [496][20/63] lr: 1.3395e-03 eta: 7:15:32 time: 0.5688 data_time: 0.0148 memory: 14901 loss: 1.3288 loss_prob: 0.7126 loss_thr: 0.4945 loss_db: 0.1217 2022/11/02 17:32:04 - mmengine - INFO - Epoch(train) [496][25/63] lr: 1.3395e-03 eta: 7:15:32 time: 0.5597 data_time: 0.0295 memory: 14901 loss: 1.3268 loss_prob: 0.7270 loss_thr: 0.4739 loss_db: 0.1259 2022/11/02 17:32:07 - mmengine - INFO - Epoch(train) [496][30/63] lr: 1.3395e-03 eta: 7:15:26 time: 0.5729 data_time: 0.0466 memory: 14901 loss: 1.3313 loss_prob: 0.7302 loss_thr: 0.4719 loss_db: 0.1292 2022/11/02 17:32:10 - mmengine - INFO - Epoch(train) [496][35/63] lr: 1.3395e-03 eta: 7:15:26 time: 0.5758 data_time: 0.0262 memory: 14901 loss: 1.2932 loss_prob: 0.7007 loss_thr: 0.4738 loss_db: 0.1188 2022/11/02 17:32:13 - mmengine - INFO - Epoch(train) [496][40/63] lr: 1.3395e-03 eta: 7:15:20 time: 0.5422 data_time: 0.0095 memory: 14901 loss: 1.2678 loss_prob: 0.6802 loss_thr: 0.4731 loss_db: 0.1145 2022/11/02 17:32:15 - mmengine - INFO - Epoch(train) [496][45/63] lr: 1.3395e-03 eta: 7:15:20 time: 0.5259 data_time: 0.0110 memory: 14901 loss: 1.3887 loss_prob: 0.7745 loss_thr: 0.4814 loss_db: 0.1329 2022/11/02 17:32:18 - mmengine - INFO - Epoch(train) [496][50/63] lr: 1.3395e-03 eta: 7:15:13 time: 0.5066 data_time: 0.0207 memory: 14901 loss: 1.5670 loss_prob: 0.8963 loss_thr: 0.5211 loss_db: 0.1496 2022/11/02 17:32:21 - mmengine - INFO - Epoch(train) [496][55/63] lr: 1.3395e-03 eta: 7:15:13 time: 0.5241 data_time: 0.0322 memory: 14901 loss: 1.5266 loss_prob: 0.8555 loss_thr: 0.5300 loss_db: 0.1412 2022/11/02 17:32:23 - mmengine - INFO - Epoch(train) [496][60/63] lr: 1.3395e-03 eta: 7:15:06 time: 0.5685 data_time: 0.0206 memory: 14901 loss: 1.3782 loss_prob: 0.7546 loss_thr: 0.4933 loss_db: 0.1303 2022/11/02 17:32:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:32:32 - mmengine - INFO - Epoch(train) [497][5/63] lr: 1.3378e-03 eta: 7:15:06 time: 0.9488 data_time: 0.2979 memory: 14901 loss: 1.4214 loss_prob: 0.7806 loss_thr: 0.5040 loss_db: 0.1368 2022/11/02 17:32:35 - mmengine - INFO - Epoch(train) [497][10/63] lr: 1.3378e-03 eta: 7:15:02 time: 0.9743 data_time: 0.3037 memory: 14901 loss: 1.4334 loss_prob: 0.7835 loss_thr: 0.5169 loss_db: 0.1330 2022/11/02 17:32:37 - mmengine - INFO - Epoch(train) [497][15/63] lr: 1.3378e-03 eta: 7:15:02 time: 0.5658 data_time: 0.0163 memory: 14901 loss: 1.3150 loss_prob: 0.7102 loss_thr: 0.4818 loss_db: 0.1231 2022/11/02 17:32:40 - mmengine - INFO - Epoch(train) [497][20/63] lr: 1.3378e-03 eta: 7:14:55 time: 0.5314 data_time: 0.0055 memory: 14901 loss: 1.4353 loss_prob: 0.8160 loss_thr: 0.4806 loss_db: 0.1387 2022/11/02 17:32:43 - mmengine - INFO - Epoch(train) [497][25/63] lr: 1.3378e-03 eta: 7:14:55 time: 0.5789 data_time: 0.0362 memory: 14901 loss: 1.5048 loss_prob: 0.8635 loss_thr: 0.4982 loss_db: 0.1431 2022/11/02 17:32:46 - mmengine - INFO - Epoch(train) [497][30/63] lr: 1.3378e-03 eta: 7:14:49 time: 0.5527 data_time: 0.0371 memory: 14901 loss: 1.3882 loss_prob: 0.7605 loss_thr: 0.4991 loss_db: 0.1286 2022/11/02 17:32:49 - mmengine - INFO - Epoch(train) [497][35/63] lr: 1.3378e-03 eta: 7:14:49 time: 0.5773 data_time: 0.0146 memory: 14901 loss: 1.3512 loss_prob: 0.7382 loss_thr: 0.4891 loss_db: 0.1239 2022/11/02 17:32:52 - mmengine - INFO - Epoch(train) [497][40/63] lr: 1.3378e-03 eta: 7:14:42 time: 0.5721 data_time: 0.0143 memory: 14901 loss: 1.3783 loss_prob: 0.7548 loss_thr: 0.4991 loss_db: 0.1244 2022/11/02 17:32:54 - mmengine - INFO - Epoch(train) [497][45/63] lr: 1.3378e-03 eta: 7:14:42 time: 0.5332 data_time: 0.0073 memory: 14901 loss: 1.3878 loss_prob: 0.7625 loss_thr: 0.4960 loss_db: 0.1294 2022/11/02 17:32:57 - mmengine - INFO - Epoch(train) [497][50/63] lr: 1.3378e-03 eta: 7:14:36 time: 0.5782 data_time: 0.0235 memory: 14901 loss: 1.3375 loss_prob: 0.7312 loss_thr: 0.4837 loss_db: 0.1227 2022/11/02 17:33:00 - mmengine - INFO - Epoch(train) [497][55/63] lr: 1.3378e-03 eta: 7:14:36 time: 0.5627 data_time: 0.0281 memory: 14901 loss: 1.2603 loss_prob: 0.6702 loss_thr: 0.4782 loss_db: 0.1120 2022/11/02 17:33:03 - mmengine - INFO - Epoch(train) [497][60/63] lr: 1.3378e-03 eta: 7:14:30 time: 0.5367 data_time: 0.0126 memory: 14901 loss: 1.3367 loss_prob: 0.7308 loss_thr: 0.4837 loss_db: 0.1222 2022/11/02 17:33:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:33:12 - mmengine - INFO - Epoch(train) [498][5/63] lr: 1.3361e-03 eta: 7:14:30 time: 0.9939 data_time: 0.2568 memory: 14901 loss: 1.4373 loss_prob: 0.8098 loss_thr: 0.4951 loss_db: 0.1324 2022/11/02 17:33:14 - mmengine - INFO - Epoch(train) [498][10/63] lr: 1.3361e-03 eta: 7:14:26 time: 1.0036 data_time: 0.2601 memory: 14901 loss: 1.3666 loss_prob: 0.7480 loss_thr: 0.4920 loss_db: 0.1266 2022/11/02 17:33:17 - mmengine - INFO - Epoch(train) [498][15/63] lr: 1.3361e-03 eta: 7:14:26 time: 0.5625 data_time: 0.0136 memory: 14901 loss: 1.3461 loss_prob: 0.7327 loss_thr: 0.4885 loss_db: 0.1250 2022/11/02 17:33:20 - mmengine - INFO - Epoch(train) [498][20/63] lr: 1.3361e-03 eta: 7:14:19 time: 0.5692 data_time: 0.0142 memory: 14901 loss: 1.3771 loss_prob: 0.7526 loss_thr: 0.4984 loss_db: 0.1260 2022/11/02 17:33:23 - mmengine - INFO - Epoch(train) [498][25/63] lr: 1.3361e-03 eta: 7:14:19 time: 0.5635 data_time: 0.0216 memory: 14901 loss: 1.3489 loss_prob: 0.7333 loss_thr: 0.4934 loss_db: 0.1221 2022/11/02 17:33:26 - mmengine - INFO - Epoch(train) [498][30/63] lr: 1.3361e-03 eta: 7:14:14 time: 0.6336 data_time: 0.0400 memory: 14901 loss: 1.2656 loss_prob: 0.6772 loss_thr: 0.4719 loss_db: 0.1165 2022/11/02 17:33:29 - mmengine - INFO - Epoch(train) [498][35/63] lr: 1.3361e-03 eta: 7:14:14 time: 0.6189 data_time: 0.0356 memory: 14901 loss: 1.4489 loss_prob: 0.8126 loss_thr: 0.4993 loss_db: 0.1370 2022/11/02 17:33:32 - mmengine - INFO - Epoch(train) [498][40/63] lr: 1.3361e-03 eta: 7:14:08 time: 0.5656 data_time: 0.0145 memory: 14901 loss: 1.5218 loss_prob: 0.8743 loss_thr: 0.5036 loss_db: 0.1439 2022/11/02 17:33:35 - mmengine - INFO - Epoch(train) [498][45/63] lr: 1.3361e-03 eta: 7:14:08 time: 0.5611 data_time: 0.0080 memory: 14901 loss: 1.3619 loss_prob: 0.7518 loss_thr: 0.4827 loss_db: 0.1273 2022/11/02 17:33:38 - mmengine - INFO - Epoch(train) [498][50/63] lr: 1.3361e-03 eta: 7:14:02 time: 0.5523 data_time: 0.0192 memory: 14901 loss: 1.3554 loss_prob: 0.7432 loss_thr: 0.4843 loss_db: 0.1279 2022/11/02 17:33:40 - mmengine - INFO - Epoch(train) [498][55/63] lr: 1.3361e-03 eta: 7:14:02 time: 0.5551 data_time: 0.0284 memory: 14901 loss: 1.3480 loss_prob: 0.7386 loss_thr: 0.4863 loss_db: 0.1231 2022/11/02 17:33:43 - mmengine - INFO - Epoch(train) [498][60/63] lr: 1.3361e-03 eta: 7:13:56 time: 0.5853 data_time: 0.0225 memory: 14901 loss: 1.2790 loss_prob: 0.6919 loss_thr: 0.4710 loss_db: 0.1161 2022/11/02 17:33:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:33:52 - mmengine - INFO - Epoch(train) [499][5/63] lr: 1.3344e-03 eta: 7:13:56 time: 0.9821 data_time: 0.2263 memory: 14901 loss: 1.3131 loss_prob: 0.6964 loss_thr: 0.5001 loss_db: 0.1166 2022/11/02 17:33:55 - mmengine - INFO - Epoch(train) [499][10/63] lr: 1.3344e-03 eta: 7:13:51 time: 0.9839 data_time: 0.2267 memory: 14901 loss: 1.3111 loss_prob: 0.6882 loss_thr: 0.5031 loss_db: 0.1198 2022/11/02 17:33:58 - mmengine - INFO - Epoch(train) [499][15/63] lr: 1.3344e-03 eta: 7:13:51 time: 0.5878 data_time: 0.0140 memory: 14901 loss: 1.2930 loss_prob: 0.6858 loss_thr: 0.4897 loss_db: 0.1176 2022/11/02 17:34:01 - mmengine - INFO - Epoch(train) [499][20/63] lr: 1.3344e-03 eta: 7:13:46 time: 0.6164 data_time: 0.0117 memory: 14901 loss: 1.2318 loss_prob: 0.6544 loss_thr: 0.4664 loss_db: 0.1111 2022/11/02 17:34:04 - mmengine - INFO - Epoch(train) [499][25/63] lr: 1.3344e-03 eta: 7:13:46 time: 0.6072 data_time: 0.0164 memory: 14901 loss: 1.2977 loss_prob: 0.6922 loss_thr: 0.4863 loss_db: 0.1191 2022/11/02 17:34:07 - mmengine - INFO - Epoch(train) [499][30/63] lr: 1.3344e-03 eta: 7:13:40 time: 0.6354 data_time: 0.0390 memory: 14901 loss: 1.3186 loss_prob: 0.7116 loss_thr: 0.4875 loss_db: 0.1195 2022/11/02 17:34:10 - mmengine - INFO - Epoch(train) [499][35/63] lr: 1.3344e-03 eta: 7:13:40 time: 0.6425 data_time: 0.0346 memory: 14901 loss: 1.3033 loss_prob: 0.7136 loss_thr: 0.4707 loss_db: 0.1189 2022/11/02 17:34:13 - mmengine - INFO - Epoch(train) [499][40/63] lr: 1.3344e-03 eta: 7:13:34 time: 0.5774 data_time: 0.0109 memory: 14901 loss: 1.3228 loss_prob: 0.7321 loss_thr: 0.4698 loss_db: 0.1209 2022/11/02 17:34:16 - mmengine - INFO - Epoch(train) [499][45/63] lr: 1.3344e-03 eta: 7:13:34 time: 0.5305 data_time: 0.0081 memory: 14901 loss: 1.3328 loss_prob: 0.7344 loss_thr: 0.4746 loss_db: 0.1237 2022/11/02 17:34:19 - mmengine - INFO - Epoch(train) [499][50/63] lr: 1.3344e-03 eta: 7:13:28 time: 0.5577 data_time: 0.0128 memory: 14901 loss: 1.4004 loss_prob: 0.7736 loss_thr: 0.4960 loss_db: 0.1308 2022/11/02 17:34:22 - mmengine - INFO - Epoch(train) [499][55/63] lr: 1.3344e-03 eta: 7:13:28 time: 0.6267 data_time: 0.0259 memory: 14901 loss: 1.3089 loss_prob: 0.7101 loss_thr: 0.4807 loss_db: 0.1181 2022/11/02 17:34:25 - mmengine - INFO - Epoch(train) [499][60/63] lr: 1.3344e-03 eta: 7:13:22 time: 0.5809 data_time: 0.0250 memory: 14901 loss: 1.3007 loss_prob: 0.7079 loss_thr: 0.4713 loss_db: 0.1216 2022/11/02 17:34:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:34:32 - mmengine - INFO - Epoch(train) [500][5/63] lr: 1.3327e-03 eta: 7:13:22 time: 0.8805 data_time: 0.2632 memory: 14901 loss: 1.2649 loss_prob: 0.6830 loss_thr: 0.4651 loss_db: 0.1167 2022/11/02 17:34:35 - mmengine - INFO - Epoch(train) [500][10/63] lr: 1.3327e-03 eta: 7:13:17 time: 0.9320 data_time: 0.2627 memory: 14901 loss: 1.4240 loss_prob: 0.8000 loss_thr: 0.4953 loss_db: 0.1287 2022/11/02 17:34:38 - mmengine - INFO - Epoch(train) [500][15/63] lr: 1.3327e-03 eta: 7:13:17 time: 0.5768 data_time: 0.0164 memory: 14901 loss: 1.3768 loss_prob: 0.7603 loss_thr: 0.4931 loss_db: 0.1235 2022/11/02 17:34:41 - mmengine - INFO - Epoch(train) [500][20/63] lr: 1.3327e-03 eta: 7:13:10 time: 0.5422 data_time: 0.0156 memory: 14901 loss: 1.3914 loss_prob: 0.7751 loss_thr: 0.4897 loss_db: 0.1265 2022/11/02 17:34:44 - mmengine - INFO - Epoch(train) [500][25/63] lr: 1.3327e-03 eta: 7:13:10 time: 0.5511 data_time: 0.0247 memory: 14901 loss: 1.5975 loss_prob: 0.9283 loss_thr: 0.5148 loss_db: 0.1545 2022/11/02 17:34:47 - mmengine - INFO - Epoch(train) [500][30/63] lr: 1.3327e-03 eta: 7:13:05 time: 0.6443 data_time: 0.0293 memory: 14901 loss: 1.5545 loss_prob: 0.8926 loss_thr: 0.5120 loss_db: 0.1499 2022/11/02 17:34:50 - mmengine - INFO - Epoch(train) [500][35/63] lr: 1.3327e-03 eta: 7:13:05 time: 0.6453 data_time: 0.0208 memory: 14901 loss: 1.3932 loss_prob: 0.7865 loss_thr: 0.4793 loss_db: 0.1274 2022/11/02 17:34:53 - mmengine - INFO - Epoch(train) [500][40/63] lr: 1.3327e-03 eta: 7:12:59 time: 0.5632 data_time: 0.0171 memory: 14901 loss: 1.2534 loss_prob: 0.6859 loss_thr: 0.4520 loss_db: 0.1155 2022/11/02 17:34:56 - mmengine - INFO - Epoch(train) [500][45/63] lr: 1.3327e-03 eta: 7:12:59 time: 0.5425 data_time: 0.0084 memory: 14901 loss: 1.4047 loss_prob: 0.7873 loss_thr: 0.4891 loss_db: 0.1283 2022/11/02 17:34:59 - mmengine - INFO - Epoch(train) [500][50/63] lr: 1.3327e-03 eta: 7:12:53 time: 0.5939 data_time: 0.0196 memory: 14901 loss: 1.4343 loss_prob: 0.7965 loss_thr: 0.5066 loss_db: 0.1311 2022/11/02 17:35:02 - mmengine - INFO - Epoch(train) [500][55/63] lr: 1.3327e-03 eta: 7:12:53 time: 0.6319 data_time: 0.0233 memory: 14901 loss: 1.3296 loss_prob: 0.7203 loss_thr: 0.4860 loss_db: 0.1233 2022/11/02 17:35:05 - mmengine - INFO - Epoch(train) [500][60/63] lr: 1.3327e-03 eta: 7:12:47 time: 0.5756 data_time: 0.0170 memory: 14901 loss: 1.4054 loss_prob: 0.7737 loss_thr: 0.4981 loss_db: 0.1336 2022/11/02 17:35:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:35:06 - mmengine - INFO - Saving checkpoint at 500 epochs 2022/11/02 17:35:10 - mmengine - INFO - Epoch(val) [500][5/500] eta: 7:12:47 time: 0.0468 data_time: 0.0055 memory: 14901 2022/11/02 17:35:10 - mmengine - INFO - Epoch(val) [500][10/500] eta: 0:00:24 time: 0.0507 data_time: 0.0057 memory: 1008 2022/11/02 17:35:10 - mmengine - INFO - Epoch(val) [500][15/500] eta: 0:00:24 time: 0.0426 data_time: 0.0033 memory: 1008 2022/11/02 17:35:10 - mmengine - INFO - Epoch(val) [500][20/500] eta: 0:00:20 time: 0.0423 data_time: 0.0035 memory: 1008 2022/11/02 17:35:11 - mmengine - INFO - Epoch(val) [500][25/500] eta: 0:00:20 time: 0.0421 data_time: 0.0032 memory: 1008 2022/11/02 17:35:11 - mmengine - INFO - Epoch(val) [500][30/500] eta: 0:00:19 time: 0.0423 data_time: 0.0028 memory: 1008 2022/11/02 17:35:11 - mmengine - INFO - Epoch(val) [500][35/500] eta: 0:00:19 time: 0.0421 data_time: 0.0027 memory: 1008 2022/11/02 17:35:11 - mmengine - INFO - Epoch(val) [500][40/500] eta: 0:00:22 time: 0.0480 data_time: 0.0032 memory: 1008 2022/11/02 17:35:12 - mmengine - INFO - Epoch(val) [500][45/500] eta: 0:00:22 time: 0.0534 data_time: 0.0037 memory: 1008 2022/11/02 17:35:12 - mmengine - INFO - Epoch(val) [500][50/500] eta: 0:00:21 time: 0.0487 data_time: 0.0036 memory: 1008 2022/11/02 17:35:12 - mmengine - INFO - Epoch(val) [500][55/500] eta: 0:00:21 time: 0.0504 data_time: 0.0033 memory: 1008 2022/11/02 17:35:12 - mmengine - INFO - Epoch(val) [500][60/500] eta: 0:00:21 time: 0.0498 data_time: 0.0039 memory: 1008 2022/11/02 17:35:13 - mmengine - INFO - Epoch(val) [500][65/500] eta: 0:00:21 time: 0.0536 data_time: 0.0047 memory: 1008 2022/11/02 17:35:13 - mmengine - INFO - Epoch(val) [500][70/500] eta: 0:00:22 time: 0.0531 data_time: 0.0037 memory: 1008 2022/11/02 17:35:13 - mmengine - INFO - Epoch(val) [500][75/500] eta: 0:00:22 time: 0.0429 data_time: 0.0028 memory: 1008 2022/11/02 17:35:13 - mmengine - INFO - Epoch(val) [500][80/500] eta: 0:00:16 time: 0.0396 data_time: 0.0030 memory: 1008 2022/11/02 17:35:13 - mmengine - INFO - Epoch(val) [500][85/500] eta: 0:00:16 time: 0.0405 data_time: 0.0029 memory: 1008 2022/11/02 17:35:14 - mmengine - INFO - Epoch(val) [500][90/500] eta: 0:00:18 time: 0.0462 data_time: 0.0032 memory: 1008 2022/11/02 17:35:14 - mmengine - INFO - Epoch(val) [500][95/500] eta: 0:00:18 time: 0.0551 data_time: 0.0037 memory: 1008 2022/11/02 17:35:14 - mmengine - INFO - Epoch(val) [500][100/500] eta: 0:00:22 time: 0.0565 data_time: 0.0052 memory: 1008 2022/11/02 17:35:15 - mmengine - INFO - Epoch(val) [500][105/500] eta: 0:00:22 time: 0.0492 data_time: 0.0048 memory: 1008 2022/11/02 17:35:15 - mmengine - INFO - Epoch(val) [500][110/500] eta: 0:00:18 time: 0.0479 data_time: 0.0034 memory: 1008 2022/11/02 17:35:15 - mmengine - INFO - Epoch(val) [500][115/500] eta: 0:00:18 time: 0.0471 data_time: 0.0032 memory: 1008 2022/11/02 17:35:15 - mmengine - INFO - Epoch(val) [500][120/500] eta: 0:00:15 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 17:35:15 - mmengine - INFO - Epoch(val) [500][125/500] eta: 0:00:15 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 17:35:16 - mmengine - INFO - Epoch(val) [500][130/500] eta: 0:00:15 time: 0.0410 data_time: 0.0031 memory: 1008 2022/11/02 17:35:16 - mmengine - INFO - Epoch(val) [500][135/500] eta: 0:00:15 time: 0.0442 data_time: 0.0038 memory: 1008 2022/11/02 17:35:16 - mmengine - INFO - Epoch(val) [500][140/500] eta: 0:00:16 time: 0.0448 data_time: 0.0038 memory: 1008 2022/11/02 17:35:16 - mmengine - INFO - Epoch(val) [500][145/500] eta: 0:00:16 time: 0.0444 data_time: 0.0029 memory: 1008 2022/11/02 17:35:16 - mmengine - INFO - Epoch(val) [500][150/500] eta: 0:00:14 time: 0.0424 data_time: 0.0025 memory: 1008 2022/11/02 17:35:17 - mmengine - INFO - Epoch(val) [500][155/500] eta: 0:00:14 time: 0.0487 data_time: 0.0029 memory: 1008 2022/11/02 17:35:17 - mmengine - INFO - Epoch(val) [500][160/500] eta: 0:00:18 time: 0.0540 data_time: 0.0045 memory: 1008 2022/11/02 17:35:17 - mmengine - INFO - Epoch(val) [500][165/500] eta: 0:00:18 time: 0.0472 data_time: 0.0043 memory: 1008 2022/11/02 17:35:17 - mmengine - INFO - Epoch(val) [500][170/500] eta: 0:00:14 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/02 17:35:18 - mmengine - INFO - Epoch(val) [500][175/500] eta: 0:00:14 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 17:35:18 - mmengine - INFO - Epoch(val) [500][180/500] eta: 0:00:13 time: 0.0424 data_time: 0.0032 memory: 1008 2022/11/02 17:35:18 - mmengine - INFO - Epoch(val) [500][185/500] eta: 0:00:13 time: 0.0443 data_time: 0.0031 memory: 1008 2022/11/02 17:35:18 - mmengine - INFO - Epoch(val) [500][190/500] eta: 0:00:14 time: 0.0453 data_time: 0.0028 memory: 1008 2022/11/02 17:35:19 - mmengine - INFO - Epoch(val) [500][195/500] eta: 0:00:14 time: 0.0427 data_time: 0.0030 memory: 1008 2022/11/02 17:35:19 - mmengine - INFO - Epoch(val) [500][200/500] eta: 0:00:14 time: 0.0474 data_time: 0.0032 memory: 1008 2022/11/02 17:35:19 - mmengine - INFO - Epoch(val) [500][205/500] eta: 0:00:14 time: 0.0451 data_time: 0.0029 memory: 1008 2022/11/02 17:35:19 - mmengine - INFO - Epoch(val) [500][210/500] eta: 0:00:11 time: 0.0411 data_time: 0.0032 memory: 1008 2022/11/02 17:35:19 - mmengine - INFO - Epoch(val) [500][215/500] eta: 0:00:11 time: 0.0446 data_time: 0.0032 memory: 1008 2022/11/02 17:35:20 - mmengine - INFO - Epoch(val) [500][220/500] eta: 0:00:12 time: 0.0451 data_time: 0.0029 memory: 1008 2022/11/02 17:35:20 - mmengine - INFO - Epoch(val) [500][225/500] eta: 0:00:12 time: 0.0488 data_time: 0.0033 memory: 1008 2022/11/02 17:35:20 - mmengine - INFO - Epoch(val) [500][230/500] eta: 0:00:11 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/02 17:35:20 - mmengine - INFO - Epoch(val) [500][235/500] eta: 0:00:11 time: 0.0417 data_time: 0.0031 memory: 1008 2022/11/02 17:35:21 - mmengine - INFO - Epoch(val) [500][240/500] eta: 0:00:11 time: 0.0449 data_time: 0.0032 memory: 1008 2022/11/02 17:35:21 - mmengine - INFO - Epoch(val) [500][245/500] eta: 0:00:11 time: 0.0453 data_time: 0.0043 memory: 1008 2022/11/02 17:35:21 - mmengine - INFO - Epoch(val) [500][250/500] eta: 0:00:12 time: 0.0481 data_time: 0.0044 memory: 1008 2022/11/02 17:35:21 - mmengine - INFO - Epoch(val) [500][255/500] eta: 0:00:12 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/02 17:35:21 - mmengine - INFO - Epoch(val) [500][260/500] eta: 0:00:09 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 17:35:22 - mmengine - INFO - Epoch(val) [500][265/500] eta: 0:00:09 time: 0.0396 data_time: 0.0028 memory: 1008 2022/11/02 17:35:22 - mmengine - INFO - Epoch(val) [500][270/500] eta: 0:00:09 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/02 17:35:22 - mmengine - INFO - Epoch(val) [500][275/500] eta: 0:00:09 time: 0.0426 data_time: 0.0029 memory: 1008 2022/11/02 17:35:22 - mmengine - INFO - Epoch(val) [500][280/500] eta: 0:00:10 time: 0.0474 data_time: 0.0028 memory: 1008 2022/11/02 17:35:23 - mmengine - INFO - Epoch(val) [500][285/500] eta: 0:00:10 time: 0.0471 data_time: 0.0033 memory: 1008 2022/11/02 17:35:23 - mmengine - INFO - Epoch(val) [500][290/500] eta: 0:00:09 time: 0.0435 data_time: 0.0035 memory: 1008 2022/11/02 17:35:23 - mmengine - INFO - Epoch(val) [500][295/500] eta: 0:00:09 time: 0.0450 data_time: 0.0029 memory: 1008 2022/11/02 17:35:23 - mmengine - INFO - Epoch(val) [500][300/500] eta: 0:00:09 time: 0.0450 data_time: 0.0031 memory: 1008 2022/11/02 17:35:23 - mmengine - INFO - Epoch(val) [500][305/500] eta: 0:00:09 time: 0.0406 data_time: 0.0029 memory: 1008 2022/11/02 17:35:24 - mmengine - INFO - Epoch(val) [500][310/500] eta: 0:00:07 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 17:35:24 - mmengine - INFO - Epoch(val) [500][315/500] eta: 0:00:07 time: 0.0435 data_time: 0.0025 memory: 1008 2022/11/02 17:35:24 - mmengine - INFO - Epoch(val) [500][320/500] eta: 0:00:07 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/02 17:35:24 - mmengine - INFO - Epoch(val) [500][325/500] eta: 0:00:07 time: 0.0653 data_time: 0.0027 memory: 1008 2022/11/02 17:35:25 - mmengine - INFO - Epoch(val) [500][330/500] eta: 0:00:10 time: 0.0641 data_time: 0.0026 memory: 1008 2022/11/02 17:35:25 - mmengine - INFO - Epoch(val) [500][335/500] eta: 0:00:10 time: 0.0392 data_time: 0.0027 memory: 1008 2022/11/02 17:35:25 - mmengine - INFO - Epoch(val) [500][340/500] eta: 0:00:10 time: 0.0645 data_time: 0.0029 memory: 1008 2022/11/02 17:35:26 - mmengine - INFO - Epoch(val) [500][345/500] eta: 0:00:10 time: 0.0663 data_time: 0.0028 memory: 1008 2022/11/02 17:35:26 - mmengine - INFO - Epoch(val) [500][350/500] eta: 0:00:06 time: 0.0447 data_time: 0.0028 memory: 1008 2022/11/02 17:35:26 - mmengine - INFO - Epoch(val) [500][355/500] eta: 0:00:06 time: 0.0434 data_time: 0.0029 memory: 1008 2022/11/02 17:35:26 - mmengine - INFO - Epoch(val) [500][360/500] eta: 0:00:05 time: 0.0406 data_time: 0.0027 memory: 1008 2022/11/02 17:35:26 - mmengine - INFO - Epoch(val) [500][365/500] eta: 0:00:05 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/02 17:35:27 - mmengine - INFO - Epoch(val) [500][370/500] eta: 0:00:04 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 17:35:27 - mmengine - INFO - Epoch(val) [500][375/500] eta: 0:00:04 time: 0.0364 data_time: 0.0027 memory: 1008 2022/11/02 17:35:27 - mmengine - INFO - Epoch(val) [500][380/500] eta: 0:00:05 time: 0.0448 data_time: 0.0032 memory: 1008 2022/11/02 17:35:27 - mmengine - INFO - Epoch(val) [500][385/500] eta: 0:00:05 time: 0.0472 data_time: 0.0033 memory: 1008 2022/11/02 17:35:27 - mmengine - INFO - Epoch(val) [500][390/500] eta: 0:00:04 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 17:35:28 - mmengine - INFO - Epoch(val) [500][395/500] eta: 0:00:04 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 17:35:28 - mmengine - INFO - Epoch(val) [500][400/500] eta: 0:00:04 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/02 17:35:28 - mmengine - INFO - Epoch(val) [500][405/500] eta: 0:00:04 time: 0.0423 data_time: 0.0031 memory: 1008 2022/11/02 17:35:28 - mmengine - INFO - Epoch(val) [500][410/500] eta: 0:00:04 time: 0.0449 data_time: 0.0032 memory: 1008 2022/11/02 17:35:28 - mmengine - INFO - Epoch(val) [500][415/500] eta: 0:00:04 time: 0.0424 data_time: 0.0030 memory: 1008 2022/11/02 17:35:29 - mmengine - INFO - Epoch(val) [500][420/500] eta: 0:00:02 time: 0.0369 data_time: 0.0029 memory: 1008 2022/11/02 17:35:29 - mmengine - INFO - Epoch(val) [500][425/500] eta: 0:00:02 time: 0.0387 data_time: 0.0029 memory: 1008 2022/11/02 17:35:29 - mmengine - INFO - Epoch(val) [500][430/500] eta: 0:00:02 time: 0.0404 data_time: 0.0031 memory: 1008 2022/11/02 17:35:29 - mmengine - INFO - Epoch(val) [500][435/500] eta: 0:00:02 time: 0.0387 data_time: 0.0029 memory: 1008 2022/11/02 17:35:29 - mmengine - INFO - Epoch(val) [500][440/500] eta: 0:00:02 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 17:35:30 - mmengine - INFO - Epoch(val) [500][445/500] eta: 0:00:02 time: 0.0398 data_time: 0.0024 memory: 1008 2022/11/02 17:35:30 - mmengine - INFO - Epoch(val) [500][450/500] eta: 0:00:02 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/02 17:35:30 - mmengine - INFO - Epoch(val) [500][455/500] eta: 0:00:02 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 17:35:30 - mmengine - INFO - Epoch(val) [500][460/500] eta: 0:00:01 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 17:35:30 - mmengine - INFO - Epoch(val) [500][465/500] eta: 0:00:01 time: 0.0375 data_time: 0.0028 memory: 1008 2022/11/02 17:35:31 - mmengine - INFO - Epoch(val) [500][470/500] eta: 0:00:01 time: 0.0384 data_time: 0.0028 memory: 1008 2022/11/02 17:35:31 - mmengine - INFO - Epoch(val) [500][475/500] eta: 0:00:01 time: 0.0356 data_time: 0.0023 memory: 1008 2022/11/02 17:35:31 - mmengine - INFO - Epoch(val) [500][480/500] eta: 0:00:00 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/02 17:35:31 - mmengine - INFO - Epoch(val) [500][485/500] eta: 0:00:00 time: 0.0373 data_time: 0.0023 memory: 1008 2022/11/02 17:35:31 - mmengine - INFO - Epoch(val) [500][490/500] eta: 0:00:00 time: 0.0400 data_time: 0.0023 memory: 1008 2022/11/02 17:35:32 - mmengine - INFO - Epoch(val) [500][495/500] eta: 0:00:00 time: 0.0419 data_time: 0.0023 memory: 1008 2022/11/02 17:35:32 - mmengine - INFO - Epoch(val) [500][500/500] eta: 0:00:00 time: 0.0365 data_time: 0.0022 memory: 1008 2022/11/02 17:35:32 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8296, precision: 0.6733, hmean: 0.7433 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8296, precision: 0.7661, hmean: 0.7966 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8291, precision: 0.8013, hmean: 0.8150 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8214, precision: 0.8400, hmean: 0.8306 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7925, precision: 0.8741, hmean: 0.8313 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5339, precision: 0.9335, hmean: 0.6793 2022/11/02 17:35:32 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0178, precision: 0.9737, hmean: 0.0350 2022/11/02 17:35:32 - mmengine - INFO - Epoch(val) [500][500/500] icdar/precision: 0.8741 icdar/recall: 0.7925 icdar/hmean: 0.8313 2022/11/02 17:35:38 - mmengine - INFO - Epoch(train) [501][5/63] lr: 1.3310e-03 eta: 0:00:00 time: 0.8304 data_time: 0.2157 memory: 14901 loss: 1.3446 loss_prob: 0.7252 loss_thr: 0.4948 loss_db: 0.1247 2022/11/02 17:35:40 - mmengine - INFO - Epoch(train) [501][10/63] lr: 1.3310e-03 eta: 7:12:40 time: 0.8441 data_time: 0.2177 memory: 14901 loss: 1.4242 loss_prob: 0.7817 loss_thr: 0.5116 loss_db: 0.1309 2022/11/02 17:35:43 - mmengine - INFO - Epoch(train) [501][15/63] lr: 1.3310e-03 eta: 7:12:40 time: 0.5680 data_time: 0.0120 memory: 14901 loss: 1.3788 loss_prob: 0.7558 loss_thr: 0.4966 loss_db: 0.1263 2022/11/02 17:35:47 - mmengine - INFO - Epoch(train) [501][20/63] lr: 1.3310e-03 eta: 7:12:36 time: 0.6764 data_time: 0.0085 memory: 14901 loss: 1.4412 loss_prob: 0.8222 loss_thr: 0.4834 loss_db: 0.1355 2022/11/02 17:35:50 - mmengine - INFO - Epoch(train) [501][25/63] lr: 1.3310e-03 eta: 7:12:36 time: 0.6566 data_time: 0.0313 memory: 14901 loss: 1.6385 loss_prob: 0.9523 loss_thr: 0.5286 loss_db: 0.1576 2022/11/02 17:35:54 - mmengine - INFO - Epoch(train) [501][30/63] lr: 1.3310e-03 eta: 7:12:31 time: 0.6503 data_time: 0.0466 memory: 14901 loss: 1.5066 loss_prob: 0.8259 loss_thr: 0.5419 loss_db: 0.1388 2022/11/02 17:35:56 - mmengine - INFO - Epoch(train) [501][35/63] lr: 1.3310e-03 eta: 7:12:31 time: 0.6305 data_time: 0.0243 memory: 14901 loss: 1.4450 loss_prob: 0.7812 loss_thr: 0.5329 loss_db: 0.1309 2022/11/02 17:35:59 - mmengine - INFO - Epoch(train) [501][40/63] lr: 1.3310e-03 eta: 7:12:24 time: 0.5639 data_time: 0.0090 memory: 14901 loss: 1.4047 loss_prob: 0.7705 loss_thr: 0.5020 loss_db: 0.1322 2022/11/02 17:36:02 - mmengine - INFO - Epoch(train) [501][45/63] lr: 1.3310e-03 eta: 7:12:24 time: 0.5658 data_time: 0.0094 memory: 14901 loss: 1.4955 loss_prob: 0.8375 loss_thr: 0.5132 loss_db: 0.1449 2022/11/02 17:36:05 - mmengine - INFO - Epoch(train) [501][50/63] lr: 1.3310e-03 eta: 7:12:18 time: 0.5791 data_time: 0.0240 memory: 14901 loss: 1.5521 loss_prob: 0.8736 loss_thr: 0.5291 loss_db: 0.1494 2022/11/02 17:36:08 - mmengine - INFO - Epoch(train) [501][55/63] lr: 1.3310e-03 eta: 7:12:18 time: 0.6085 data_time: 0.0290 memory: 14901 loss: 1.4636 loss_prob: 0.8211 loss_thr: 0.5062 loss_db: 0.1363 2022/11/02 17:36:11 - mmengine - INFO - Epoch(train) [501][60/63] lr: 1.3310e-03 eta: 7:12:12 time: 0.5754 data_time: 0.0118 memory: 14901 loss: 1.4206 loss_prob: 0.7933 loss_thr: 0.4947 loss_db: 0.1326 2022/11/02 17:36:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:36:18 - mmengine - INFO - Epoch(train) [502][5/63] lr: 1.3293e-03 eta: 7:12:12 time: 0.7940 data_time: 0.2622 memory: 14901 loss: 1.2778 loss_prob: 0.6828 loss_thr: 0.4784 loss_db: 0.1166 2022/11/02 17:36:21 - mmengine - INFO - Epoch(train) [502][10/63] lr: 1.3293e-03 eta: 7:12:07 time: 0.9199 data_time: 0.2641 memory: 14901 loss: 1.2339 loss_prob: 0.6583 loss_thr: 0.4621 loss_db: 0.1135 2022/11/02 17:36:24 - mmengine - INFO - Epoch(train) [502][15/63] lr: 1.3293e-03 eta: 7:12:07 time: 0.6381 data_time: 0.0106 memory: 14901 loss: 1.3104 loss_prob: 0.7193 loss_thr: 0.4719 loss_db: 0.1192 2022/11/02 17:36:27 - mmengine - INFO - Epoch(train) [502][20/63] lr: 1.3293e-03 eta: 7:12:00 time: 0.5255 data_time: 0.0063 memory: 14901 loss: 1.3633 loss_prob: 0.7513 loss_thr: 0.4875 loss_db: 0.1245 2022/11/02 17:36:29 - mmengine - INFO - Epoch(train) [502][25/63] lr: 1.3293e-03 eta: 7:12:00 time: 0.5011 data_time: 0.0099 memory: 14901 loss: 1.2875 loss_prob: 0.6893 loss_thr: 0.4803 loss_db: 0.1179 2022/11/02 17:36:32 - mmengine - INFO - Epoch(train) [502][30/63] lr: 1.3293e-03 eta: 7:11:53 time: 0.5261 data_time: 0.0349 memory: 14901 loss: 1.2861 loss_prob: 0.6854 loss_thr: 0.4833 loss_db: 0.1174 2022/11/02 17:36:35 - mmengine - INFO - Epoch(train) [502][35/63] lr: 1.3293e-03 eta: 7:11:53 time: 0.5502 data_time: 0.0361 memory: 14901 loss: 1.2956 loss_prob: 0.6932 loss_thr: 0.4837 loss_db: 0.1186 2022/11/02 17:36:38 - mmengine - INFO - Epoch(train) [502][40/63] lr: 1.3293e-03 eta: 7:11:47 time: 0.5848 data_time: 0.0128 memory: 14901 loss: 1.3053 loss_prob: 0.7012 loss_thr: 0.4840 loss_db: 0.1201 2022/11/02 17:36:40 - mmengine - INFO - Epoch(train) [502][45/63] lr: 1.3293e-03 eta: 7:11:47 time: 0.5577 data_time: 0.0115 memory: 14901 loss: 1.2813 loss_prob: 0.6920 loss_thr: 0.4714 loss_db: 0.1179 2022/11/02 17:36:43 - mmengine - INFO - Epoch(train) [502][50/63] lr: 1.3293e-03 eta: 7:11:40 time: 0.4957 data_time: 0.0154 memory: 14901 loss: 1.2824 loss_prob: 0.6907 loss_thr: 0.4746 loss_db: 0.1170 2022/11/02 17:36:46 - mmengine - INFO - Epoch(train) [502][55/63] lr: 1.3293e-03 eta: 7:11:40 time: 0.5252 data_time: 0.0332 memory: 14901 loss: 1.4195 loss_prob: 0.7773 loss_thr: 0.5096 loss_db: 0.1325 2022/11/02 17:36:49 - mmengine - INFO - Epoch(train) [502][60/63] lr: 1.3293e-03 eta: 7:11:35 time: 0.6631 data_time: 0.0301 memory: 14901 loss: 1.4242 loss_prob: 0.7858 loss_thr: 0.5046 loss_db: 0.1337 2022/11/02 17:36:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:36:59 - mmengine - INFO - Epoch(train) [503][5/63] lr: 1.3276e-03 eta: 7:11:35 time: 1.1003 data_time: 0.3235 memory: 14901 loss: 1.3164 loss_prob: 0.7049 loss_thr: 0.4913 loss_db: 0.1202 2022/11/02 17:37:03 - mmengine - INFO - Epoch(train) [503][10/63] lr: 1.3276e-03 eta: 7:11:33 time: 1.1493 data_time: 0.3283 memory: 14901 loss: 1.3243 loss_prob: 0.7119 loss_thr: 0.4891 loss_db: 0.1233 2022/11/02 17:37:06 - mmengine - INFO - Epoch(train) [503][15/63] lr: 1.3276e-03 eta: 7:11:33 time: 0.7601 data_time: 0.0138 memory: 14901 loss: 1.3394 loss_prob: 0.7278 loss_thr: 0.4885 loss_db: 0.1230 2022/11/02 17:37:10 - mmengine - INFO - Epoch(train) [503][20/63] lr: 1.3276e-03 eta: 7:11:29 time: 0.7080 data_time: 0.0087 memory: 14901 loss: 1.3115 loss_prob: 0.7031 loss_thr: 0.4914 loss_db: 0.1170 2022/11/02 17:37:13 - mmengine - INFO - Epoch(train) [503][25/63] lr: 1.3276e-03 eta: 7:11:29 time: 0.6846 data_time: 0.0413 memory: 14901 loss: 1.2388 loss_prob: 0.6562 loss_thr: 0.4704 loss_db: 0.1122 2022/11/02 17:37:17 - mmengine - INFO - Epoch(train) [503][30/63] lr: 1.3276e-03 eta: 7:11:25 time: 0.7406 data_time: 0.0536 memory: 14901 loss: 1.2731 loss_prob: 0.6920 loss_thr: 0.4663 loss_db: 0.1149 2022/11/02 17:37:21 - mmengine - INFO - Epoch(train) [503][35/63] lr: 1.3276e-03 eta: 7:11:25 time: 0.8039 data_time: 0.0200 memory: 14901 loss: 1.3468 loss_prob: 0.7393 loss_thr: 0.4848 loss_db: 0.1227 2022/11/02 17:37:24 - mmengine - INFO - Epoch(train) [503][40/63] lr: 1.3276e-03 eta: 7:11:20 time: 0.6648 data_time: 0.0071 memory: 14901 loss: 1.3863 loss_prob: 0.7586 loss_thr: 0.4994 loss_db: 0.1284 2022/11/02 17:37:26 - mmengine - INFO - Epoch(train) [503][45/63] lr: 1.3276e-03 eta: 7:11:20 time: 0.5295 data_time: 0.0055 memory: 14901 loss: 1.6068 loss_prob: 0.9162 loss_thr: 0.5442 loss_db: 0.1464 2022/11/02 17:37:30 - mmengine - INFO - Epoch(train) [503][50/63] lr: 1.3276e-03 eta: 7:11:14 time: 0.5713 data_time: 0.0278 memory: 14901 loss: 1.6223 loss_prob: 0.9304 loss_thr: 0.5378 loss_db: 0.1540 2022/11/02 17:37:32 - mmengine - INFO - Epoch(train) [503][55/63] lr: 1.3276e-03 eta: 7:11:14 time: 0.5690 data_time: 0.0365 memory: 14901 loss: 1.4307 loss_prob: 0.7937 loss_thr: 0.4975 loss_db: 0.1395 2022/11/02 17:37:35 - mmengine - INFO - Epoch(train) [503][60/63] lr: 1.3276e-03 eta: 7:11:07 time: 0.5163 data_time: 0.0171 memory: 14901 loss: 1.5583 loss_prob: 0.8864 loss_thr: 0.5230 loss_db: 0.1488 2022/11/02 17:37:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:37:43 - mmengine - INFO - Epoch(train) [504][5/63] lr: 1.3258e-03 eta: 7:11:07 time: 0.9398 data_time: 0.2322 memory: 14901 loss: 2.0863 loss_prob: 1.3112 loss_thr: 0.5758 loss_db: 0.1993 2022/11/02 17:37:47 - mmengine - INFO - Epoch(train) [504][10/63] lr: 1.3258e-03 eta: 7:11:04 time: 1.1259 data_time: 0.2338 memory: 14901 loss: 2.4949 loss_prob: 1.6378 loss_thr: 0.5948 loss_db: 0.2623 2022/11/02 17:37:51 - mmengine - INFO - Epoch(train) [504][15/63] lr: 1.3258e-03 eta: 7:11:04 time: 0.7528 data_time: 0.0105 memory: 14901 loss: 1.9177 loss_prob: 1.1733 loss_thr: 0.5464 loss_db: 0.1980 2022/11/02 17:37:54 - mmengine - INFO - Epoch(train) [504][20/63] lr: 1.3258e-03 eta: 7:11:00 time: 0.6884 data_time: 0.0084 memory: 14901 loss: 1.6980 loss_prob: 1.0005 loss_thr: 0.5375 loss_db: 0.1600 2022/11/02 17:37:58 - mmengine - INFO - Epoch(train) [504][25/63] lr: 1.3258e-03 eta: 7:11:00 time: 0.7086 data_time: 0.0108 memory: 14901 loss: 2.0427 loss_prob: 1.2615 loss_thr: 0.5804 loss_db: 0.2008 2022/11/02 17:38:01 - mmengine - INFO - Epoch(train) [504][30/63] lr: 1.3258e-03 eta: 7:10:55 time: 0.6499 data_time: 0.0395 memory: 14901 loss: 2.0329 loss_prob: 1.2372 loss_thr: 0.5953 loss_db: 0.2004 2022/11/02 17:38:03 - mmengine - INFO - Epoch(train) [504][35/63] lr: 1.3258e-03 eta: 7:10:55 time: 0.5613 data_time: 0.0360 memory: 14901 loss: 1.6884 loss_prob: 0.9647 loss_thr: 0.5617 loss_db: 0.1620 2022/11/02 17:38:06 - mmengine - INFO - Epoch(train) [504][40/63] lr: 1.3258e-03 eta: 7:10:48 time: 0.5061 data_time: 0.0112 memory: 14901 loss: 1.6340 loss_prob: 0.9294 loss_thr: 0.5526 loss_db: 0.1520 2022/11/02 17:38:08 - mmengine - INFO - Epoch(train) [504][45/63] lr: 1.3258e-03 eta: 7:10:48 time: 0.4895 data_time: 0.0118 memory: 14901 loss: 1.6162 loss_prob: 0.9238 loss_thr: 0.5403 loss_db: 0.1520 2022/11/02 17:38:11 - mmengine - INFO - Epoch(train) [504][50/63] lr: 1.3258e-03 eta: 7:10:42 time: 0.5721 data_time: 0.0310 memory: 14901 loss: 1.4517 loss_prob: 0.8123 loss_thr: 0.5048 loss_db: 0.1346 2022/11/02 17:38:14 - mmengine - INFO - Epoch(train) [504][55/63] lr: 1.3258e-03 eta: 7:10:42 time: 0.6315 data_time: 0.0354 memory: 14901 loss: 1.4751 loss_prob: 0.8209 loss_thr: 0.5193 loss_db: 0.1349 2022/11/02 17:38:18 - mmengine - INFO - Epoch(train) [504][60/63] lr: 1.3258e-03 eta: 7:10:37 time: 0.6493 data_time: 0.0132 memory: 14901 loss: 1.4621 loss_prob: 0.8013 loss_thr: 0.5225 loss_db: 0.1383 2022/11/02 17:38:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:38:26 - mmengine - INFO - Epoch(train) [505][5/63] lr: 1.3241e-03 eta: 7:10:37 time: 0.9324 data_time: 0.2852 memory: 14901 loss: 1.4024 loss_prob: 0.7686 loss_thr: 0.5077 loss_db: 0.1261 2022/11/02 17:38:31 - mmengine - INFO - Epoch(train) [505][10/63] lr: 1.3241e-03 eta: 7:10:34 time: 1.1167 data_time: 0.2838 memory: 14901 loss: 1.4005 loss_prob: 0.7743 loss_thr: 0.5006 loss_db: 0.1256 2022/11/02 17:38:34 - mmengine - INFO - Epoch(train) [505][15/63] lr: 1.3241e-03 eta: 7:10:34 time: 0.8291 data_time: 0.0080 memory: 14901 loss: 1.3364 loss_prob: 0.7309 loss_thr: 0.4849 loss_db: 0.1206 2022/11/02 17:38:37 - mmengine - INFO - Epoch(train) [505][20/63] lr: 1.3241e-03 eta: 7:10:29 time: 0.6796 data_time: 0.0071 memory: 14901 loss: 1.2990 loss_prob: 0.7115 loss_thr: 0.4685 loss_db: 0.1190 2022/11/02 17:38:41 - mmengine - INFO - Epoch(train) [505][25/63] lr: 1.3241e-03 eta: 7:10:29 time: 0.6966 data_time: 0.0700 memory: 14901 loss: 1.4279 loss_prob: 0.7978 loss_thr: 0.4975 loss_db: 0.1326 2022/11/02 17:38:45 - mmengine - INFO - Epoch(train) [505][30/63] lr: 1.3241e-03 eta: 7:10:25 time: 0.7557 data_time: 0.0685 memory: 14901 loss: 1.4689 loss_prob: 0.8180 loss_thr: 0.5148 loss_db: 0.1362 2022/11/02 17:38:48 - mmengine - INFO - Epoch(train) [505][35/63] lr: 1.3241e-03 eta: 7:10:25 time: 0.7063 data_time: 0.0072 memory: 14901 loss: 1.4394 loss_prob: 0.7899 loss_thr: 0.5138 loss_db: 0.1357 2022/11/02 17:38:52 - mmengine - INFO - Epoch(train) [505][40/63] lr: 1.3241e-03 eta: 7:10:21 time: 0.7275 data_time: 0.0068 memory: 14901 loss: 1.5492 loss_prob: 0.8851 loss_thr: 0.5198 loss_db: 0.1443 2022/11/02 17:38:55 - mmengine - INFO - Epoch(train) [505][45/63] lr: 1.3241e-03 eta: 7:10:21 time: 0.6864 data_time: 0.0101 memory: 14901 loss: 1.5606 loss_prob: 0.8829 loss_thr: 0.5353 loss_db: 0.1424 2022/11/02 17:38:58 - mmengine - INFO - Epoch(train) [505][50/63] lr: 1.3241e-03 eta: 7:10:16 time: 0.6077 data_time: 0.0378 memory: 14901 loss: 1.4768 loss_prob: 0.8001 loss_thr: 0.5400 loss_db: 0.1367 2022/11/02 17:39:01 - mmengine - INFO - Epoch(train) [505][55/63] lr: 1.3241e-03 eta: 7:10:16 time: 0.6153 data_time: 0.0330 memory: 14901 loss: 1.4710 loss_prob: 0.8113 loss_thr: 0.5251 loss_db: 0.1346 2022/11/02 17:39:05 - mmengine - INFO - Epoch(train) [505][60/63] lr: 1.3241e-03 eta: 7:10:11 time: 0.6368 data_time: 0.0085 memory: 14901 loss: 1.4677 loss_prob: 0.8186 loss_thr: 0.5136 loss_db: 0.1355 2022/11/02 17:39:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:39:13 - mmengine - INFO - Epoch(train) [506][5/63] lr: 1.3224e-03 eta: 7:10:11 time: 0.9093 data_time: 0.2892 memory: 14901 loss: 1.3219 loss_prob: 0.7094 loss_thr: 0.4892 loss_db: 0.1233 2022/11/02 17:39:16 - mmengine - INFO - Epoch(train) [506][10/63] lr: 1.3224e-03 eta: 7:10:06 time: 1.0135 data_time: 0.2951 memory: 14901 loss: 1.3801 loss_prob: 0.7517 loss_thr: 0.5023 loss_db: 0.1261 2022/11/02 17:39:19 - mmengine - INFO - Epoch(train) [506][15/63] lr: 1.3224e-03 eta: 7:10:06 time: 0.6404 data_time: 0.0125 memory: 14901 loss: 1.3417 loss_prob: 0.7337 loss_thr: 0.4863 loss_db: 0.1217 2022/11/02 17:39:22 - mmengine - INFO - Epoch(train) [506][20/63] lr: 1.3224e-03 eta: 7:10:00 time: 0.5623 data_time: 0.0062 memory: 14901 loss: 1.3420 loss_prob: 0.7367 loss_thr: 0.4818 loss_db: 0.1236 2022/11/02 17:39:24 - mmengine - INFO - Epoch(train) [506][25/63] lr: 1.3224e-03 eta: 7:10:00 time: 0.5474 data_time: 0.0331 memory: 14901 loss: 1.3928 loss_prob: 0.7620 loss_thr: 0.5058 loss_db: 0.1250 2022/11/02 17:39:27 - mmengine - INFO - Epoch(train) [506][30/63] lr: 1.3224e-03 eta: 7:09:54 time: 0.5564 data_time: 0.0381 memory: 14901 loss: 1.4413 loss_prob: 0.8141 loss_thr: 0.4941 loss_db: 0.1331 2022/11/02 17:39:30 - mmengine - INFO - Epoch(train) [506][35/63] lr: 1.3224e-03 eta: 7:09:54 time: 0.5639 data_time: 0.0163 memory: 14901 loss: 1.4048 loss_prob: 0.7786 loss_thr: 0.4952 loss_db: 0.1311 2022/11/02 17:39:33 - mmengine - INFO - Epoch(train) [506][40/63] lr: 1.3224e-03 eta: 7:09:47 time: 0.5558 data_time: 0.0143 memory: 14901 loss: 1.3731 loss_prob: 0.7438 loss_thr: 0.5055 loss_db: 0.1237 2022/11/02 17:39:36 - mmengine - INFO - Epoch(train) [506][45/63] lr: 1.3224e-03 eta: 7:09:47 time: 0.5597 data_time: 0.0111 memory: 14901 loss: 1.4455 loss_prob: 0.8099 loss_thr: 0.5040 loss_db: 0.1316 2022/11/02 17:39:39 - mmengine - INFO - Epoch(train) [506][50/63] lr: 1.3224e-03 eta: 7:09:41 time: 0.5908 data_time: 0.0194 memory: 14901 loss: 1.3679 loss_prob: 0.7513 loss_thr: 0.4919 loss_db: 0.1248 2022/11/02 17:39:41 - mmengine - INFO - Epoch(train) [506][55/63] lr: 1.3224e-03 eta: 7:09:41 time: 0.5633 data_time: 0.0244 memory: 14901 loss: 1.3288 loss_prob: 0.7146 loss_thr: 0.4909 loss_db: 0.1233 2022/11/02 17:39:44 - mmengine - INFO - Epoch(train) [506][60/63] lr: 1.3224e-03 eta: 7:09:35 time: 0.5236 data_time: 0.0163 memory: 14901 loss: 1.3302 loss_prob: 0.7219 loss_thr: 0.4855 loss_db: 0.1227 2022/11/02 17:39:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:39:52 - mmengine - INFO - Epoch(train) [507][5/63] lr: 1.3207e-03 eta: 7:09:35 time: 0.9443 data_time: 0.2448 memory: 14901 loss: 1.2249 loss_prob: 0.6516 loss_thr: 0.4650 loss_db: 0.1082 2022/11/02 17:39:55 - mmengine - INFO - Epoch(train) [507][10/63] lr: 1.3207e-03 eta: 7:09:29 time: 0.9420 data_time: 0.2511 memory: 14901 loss: 1.3402 loss_prob: 0.7339 loss_thr: 0.4839 loss_db: 0.1225 2022/11/02 17:39:58 - mmengine - INFO - Epoch(train) [507][15/63] lr: 1.3207e-03 eta: 7:09:29 time: 0.5274 data_time: 0.0168 memory: 14901 loss: 1.4379 loss_prob: 0.8064 loss_thr: 0.4996 loss_db: 0.1319 2022/11/02 17:40:00 - mmengine - INFO - Epoch(train) [507][20/63] lr: 1.3207e-03 eta: 7:09:23 time: 0.5418 data_time: 0.0107 memory: 14901 loss: 1.4382 loss_prob: 0.7887 loss_thr: 0.5163 loss_db: 0.1332 2022/11/02 17:40:03 - mmengine - INFO - Epoch(train) [507][25/63] lr: 1.3207e-03 eta: 7:09:23 time: 0.5306 data_time: 0.0091 memory: 14901 loss: 1.5326 loss_prob: 0.8719 loss_thr: 0.5211 loss_db: 0.1396 2022/11/02 17:40:06 - mmengine - INFO - Epoch(train) [507][30/63] lr: 1.3207e-03 eta: 7:09:16 time: 0.5331 data_time: 0.0432 memory: 14901 loss: 1.4938 loss_prob: 0.8530 loss_thr: 0.5072 loss_db: 0.1337 2022/11/02 17:40:09 - mmengine - INFO - Epoch(train) [507][35/63] lr: 1.3207e-03 eta: 7:09:16 time: 0.5870 data_time: 0.0416 memory: 14901 loss: 1.2634 loss_prob: 0.6821 loss_thr: 0.4677 loss_db: 0.1136 2022/11/02 17:40:12 - mmengine - INFO - Epoch(train) [507][40/63] lr: 1.3207e-03 eta: 7:09:11 time: 0.6539 data_time: 0.0065 memory: 14901 loss: 1.2602 loss_prob: 0.6780 loss_thr: 0.4673 loss_db: 0.1149 2022/11/02 17:40:15 - mmengine - INFO - Epoch(train) [507][45/63] lr: 1.3207e-03 eta: 7:09:11 time: 0.6072 data_time: 0.0093 memory: 14901 loss: 1.2989 loss_prob: 0.6845 loss_thr: 0.4974 loss_db: 0.1170 2022/11/02 17:40:17 - mmengine - INFO - Epoch(train) [507][50/63] lr: 1.3207e-03 eta: 7:09:04 time: 0.5223 data_time: 0.0128 memory: 14901 loss: 1.2748 loss_prob: 0.6708 loss_thr: 0.4881 loss_db: 0.1158 2022/11/02 17:40:21 - mmengine - INFO - Epoch(train) [507][55/63] lr: 1.3207e-03 eta: 7:09:04 time: 0.5877 data_time: 0.0372 memory: 14901 loss: 1.3198 loss_prob: 0.7118 loss_thr: 0.4877 loss_db: 0.1203 2022/11/02 17:40:24 - mmengine - INFO - Epoch(train) [507][60/63] lr: 1.3207e-03 eta: 7:08:59 time: 0.6581 data_time: 0.0331 memory: 14901 loss: 1.3724 loss_prob: 0.7497 loss_thr: 0.4983 loss_db: 0.1244 2022/11/02 17:40:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:40:34 - mmengine - INFO - Epoch(train) [508][5/63] lr: 1.3190e-03 eta: 7:08:59 time: 1.1413 data_time: 0.2902 memory: 14901 loss: 1.4054 loss_prob: 0.7712 loss_thr: 0.5003 loss_db: 0.1340 2022/11/02 17:40:37 - mmengine - INFO - Epoch(train) [508][10/63] lr: 1.3190e-03 eta: 7:08:56 time: 1.0757 data_time: 0.2887 memory: 14901 loss: 1.3538 loss_prob: 0.7414 loss_thr: 0.4876 loss_db: 0.1248 2022/11/02 17:40:39 - mmengine - INFO - Epoch(train) [508][15/63] lr: 1.3190e-03 eta: 7:08:56 time: 0.5280 data_time: 0.0072 memory: 14901 loss: 1.4191 loss_prob: 0.7867 loss_thr: 0.5014 loss_db: 0.1310 2022/11/02 17:40:42 - mmengine - INFO - Epoch(train) [508][20/63] lr: 1.3190e-03 eta: 7:08:49 time: 0.4850 data_time: 0.0046 memory: 14901 loss: 1.4819 loss_prob: 0.8127 loss_thr: 0.5301 loss_db: 0.1391 2022/11/02 17:40:45 - mmengine - INFO - Epoch(train) [508][25/63] lr: 1.3190e-03 eta: 7:08:49 time: 0.5180 data_time: 0.0202 memory: 14901 loss: 1.4952 loss_prob: 0.8304 loss_thr: 0.5242 loss_db: 0.1406 2022/11/02 17:40:48 - mmengine - INFO - Epoch(train) [508][30/63] lr: 1.3190e-03 eta: 7:08:43 time: 0.6109 data_time: 0.0656 memory: 14901 loss: 1.5599 loss_prob: 0.9024 loss_thr: 0.5057 loss_db: 0.1517 2022/11/02 17:40:50 - mmengine - INFO - Epoch(train) [508][35/63] lr: 1.3190e-03 eta: 7:08:43 time: 0.5692 data_time: 0.0499 memory: 14901 loss: 1.5353 loss_prob: 0.9019 loss_thr: 0.4891 loss_db: 0.1443 2022/11/02 17:40:53 - mmengine - INFO - Epoch(train) [508][40/63] lr: 1.3190e-03 eta: 7:08:36 time: 0.4895 data_time: 0.0048 memory: 14901 loss: 1.4127 loss_prob: 0.8065 loss_thr: 0.4776 loss_db: 0.1286 2022/11/02 17:40:56 - mmengine - INFO - Epoch(train) [508][45/63] lr: 1.3190e-03 eta: 7:08:36 time: 0.5376 data_time: 0.0076 memory: 14901 loss: 1.3345 loss_prob: 0.7216 loss_thr: 0.4877 loss_db: 0.1253 2022/11/02 17:40:59 - mmengine - INFO - Epoch(train) [508][50/63] lr: 1.3190e-03 eta: 7:08:31 time: 0.6434 data_time: 0.0177 memory: 14901 loss: 1.4013 loss_prob: 0.7603 loss_thr: 0.5077 loss_db: 0.1333 2022/11/02 17:41:02 - mmengine - INFO - Epoch(train) [508][55/63] lr: 1.3190e-03 eta: 7:08:31 time: 0.6441 data_time: 0.0388 memory: 14901 loss: 1.3618 loss_prob: 0.7482 loss_thr: 0.4848 loss_db: 0.1288 2022/11/02 17:41:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:41:05 - mmengine - INFO - Epoch(train) [508][60/63] lr: 1.3190e-03 eta: 7:08:24 time: 0.5591 data_time: 0.0301 memory: 14901 loss: 1.3513 loss_prob: 0.7283 loss_thr: 0.5025 loss_db: 0.1205 2022/11/02 17:41:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:41:14 - mmengine - INFO - Epoch(train) [509][5/63] lr: 1.3173e-03 eta: 7:08:24 time: 1.0485 data_time: 0.2814 memory: 14901 loss: 1.3272 loss_prob: 0.7090 loss_thr: 0.4955 loss_db: 0.1228 2022/11/02 17:41:18 - mmengine - INFO - Epoch(train) [509][10/63] lr: 1.3173e-03 eta: 7:08:22 time: 1.1240 data_time: 0.2828 memory: 14901 loss: 1.3218 loss_prob: 0.7123 loss_thr: 0.4882 loss_db: 0.1214 2022/11/02 17:41:21 - mmengine - INFO - Epoch(train) [509][15/63] lr: 1.3173e-03 eta: 7:08:22 time: 0.6846 data_time: 0.0123 memory: 14901 loss: 1.3073 loss_prob: 0.7162 loss_thr: 0.4714 loss_db: 0.1197 2022/11/02 17:41:25 - mmengine - INFO - Epoch(train) [509][20/63] lr: 1.3173e-03 eta: 7:08:17 time: 0.6948 data_time: 0.0088 memory: 14901 loss: 1.3994 loss_prob: 0.7877 loss_thr: 0.4778 loss_db: 0.1339 2022/11/02 17:41:28 - mmengine - INFO - Epoch(train) [509][25/63] lr: 1.3173e-03 eta: 7:08:17 time: 0.6400 data_time: 0.0278 memory: 14901 loss: 1.3318 loss_prob: 0.7287 loss_thr: 0.4797 loss_db: 0.1234 2022/11/02 17:41:31 - mmengine - INFO - Epoch(train) [509][30/63] lr: 1.3173e-03 eta: 7:08:11 time: 0.6017 data_time: 0.0360 memory: 14901 loss: 1.4145 loss_prob: 0.7753 loss_thr: 0.5115 loss_db: 0.1276 2022/11/02 17:41:34 - mmengine - INFO - Epoch(train) [509][35/63] lr: 1.3173e-03 eta: 7:08:11 time: 0.6186 data_time: 0.0176 memory: 14901 loss: 1.4840 loss_prob: 0.8137 loss_thr: 0.5339 loss_db: 0.1364 2022/11/02 17:41:37 - mmengine - INFO - Epoch(train) [509][40/63] lr: 1.3173e-03 eta: 7:08:06 time: 0.5975 data_time: 0.0105 memory: 14901 loss: 1.3597 loss_prob: 0.7276 loss_thr: 0.5078 loss_db: 0.1243 2022/11/02 17:41:40 - mmengine - INFO - Epoch(train) [509][45/63] lr: 1.3173e-03 eta: 7:08:06 time: 0.5806 data_time: 0.0088 memory: 14901 loss: 1.3663 loss_prob: 0.7545 loss_thr: 0.4852 loss_db: 0.1265 2022/11/02 17:41:42 - mmengine - INFO - Epoch(train) [509][50/63] lr: 1.3173e-03 eta: 7:08:00 time: 0.5859 data_time: 0.0173 memory: 14901 loss: 1.3631 loss_prob: 0.7532 loss_thr: 0.4824 loss_db: 0.1275 2022/11/02 17:41:46 - mmengine - INFO - Epoch(train) [509][55/63] lr: 1.3173e-03 eta: 7:08:00 time: 0.6935 data_time: 0.0259 memory: 14901 loss: 1.3187 loss_prob: 0.7169 loss_thr: 0.4796 loss_db: 0.1223 2022/11/02 17:41:51 - mmengine - INFO - Epoch(train) [509][60/63] lr: 1.3173e-03 eta: 7:07:57 time: 0.8425 data_time: 0.0216 memory: 14901 loss: 1.3561 loss_prob: 0.7511 loss_thr: 0.4810 loss_db: 0.1241 2022/11/02 17:41:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:42:00 - mmengine - INFO - Epoch(train) [510][5/63] lr: 1.3156e-03 eta: 7:07:57 time: 1.0703 data_time: 0.2514 memory: 14901 loss: 1.2951 loss_prob: 0.7033 loss_thr: 0.4687 loss_db: 0.1231 2022/11/02 17:42:03 - mmengine - INFO - Epoch(train) [510][10/63] lr: 1.3156e-03 eta: 7:07:52 time: 0.9731 data_time: 0.2505 memory: 14901 loss: 1.4003 loss_prob: 0.7665 loss_thr: 0.5031 loss_db: 0.1307 2022/11/02 17:42:05 - mmengine - INFO - Epoch(train) [510][15/63] lr: 1.3156e-03 eta: 7:07:52 time: 0.5379 data_time: 0.0080 memory: 14901 loss: 1.4495 loss_prob: 0.7971 loss_thr: 0.5190 loss_db: 0.1335 2022/11/02 17:42:08 - mmengine - INFO - Epoch(train) [510][20/63] lr: 1.3156e-03 eta: 7:07:46 time: 0.5594 data_time: 0.0090 memory: 14901 loss: 1.3668 loss_prob: 0.7482 loss_thr: 0.4943 loss_db: 0.1243 2022/11/02 17:42:12 - mmengine - INFO - Epoch(train) [510][25/63] lr: 1.3156e-03 eta: 7:07:46 time: 0.6870 data_time: 0.0327 memory: 14901 loss: 1.3235 loss_prob: 0.7089 loss_thr: 0.4953 loss_db: 0.1194 2022/11/02 17:42:15 - mmengine - INFO - Epoch(train) [510][30/63] lr: 1.3156e-03 eta: 7:07:41 time: 0.6968 data_time: 0.0467 memory: 14901 loss: 1.3173 loss_prob: 0.7076 loss_thr: 0.4892 loss_db: 0.1204 2022/11/02 17:42:18 - mmengine - INFO - Epoch(train) [510][35/63] lr: 1.3156e-03 eta: 7:07:41 time: 0.5999 data_time: 0.0218 memory: 14901 loss: 1.3153 loss_prob: 0.7114 loss_thr: 0.4816 loss_db: 0.1223 2022/11/02 17:42:21 - mmengine - INFO - Epoch(train) [510][40/63] lr: 1.3156e-03 eta: 7:07:36 time: 0.6018 data_time: 0.0083 memory: 14901 loss: 1.2618 loss_prob: 0.6781 loss_thr: 0.4678 loss_db: 0.1158 2022/11/02 17:42:24 - mmengine - INFO - Epoch(train) [510][45/63] lr: 1.3156e-03 eta: 7:07:36 time: 0.5400 data_time: 0.0073 memory: 14901 loss: 1.2342 loss_prob: 0.6668 loss_thr: 0.4556 loss_db: 0.1118 2022/11/02 17:42:26 - mmengine - INFO - Epoch(train) [510][50/63] lr: 1.3156e-03 eta: 7:07:29 time: 0.5229 data_time: 0.0236 memory: 14901 loss: 1.2576 loss_prob: 0.6802 loss_thr: 0.4609 loss_db: 0.1165 2022/11/02 17:42:29 - mmengine - INFO - Epoch(train) [510][55/63] lr: 1.3156e-03 eta: 7:07:29 time: 0.5633 data_time: 0.0314 memory: 14901 loss: 1.3149 loss_prob: 0.7131 loss_thr: 0.4810 loss_db: 0.1208 2022/11/02 17:42:32 - mmengine - INFO - Epoch(train) [510][60/63] lr: 1.3156e-03 eta: 7:07:23 time: 0.5988 data_time: 0.0125 memory: 14901 loss: 1.4792 loss_prob: 0.8244 loss_thr: 0.5208 loss_db: 0.1339 2022/11/02 17:42:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:42:41 - mmengine - INFO - Epoch(train) [511][5/63] lr: 1.3138e-03 eta: 7:07:23 time: 1.0191 data_time: 0.2833 memory: 14901 loss: 1.4767 loss_prob: 0.8294 loss_thr: 0.5149 loss_db: 0.1324 2022/11/02 17:42:45 - mmengine - INFO - Epoch(train) [511][10/63] lr: 1.3138e-03 eta: 7:07:20 time: 1.0979 data_time: 0.2837 memory: 14901 loss: 1.3667 loss_prob: 0.7628 loss_thr: 0.4787 loss_db: 0.1252 2022/11/02 17:42:48 - mmengine - INFO - Epoch(train) [511][15/63] lr: 1.3138e-03 eta: 7:07:20 time: 0.6963 data_time: 0.0081 memory: 14901 loss: 1.3438 loss_prob: 0.7406 loss_thr: 0.4783 loss_db: 0.1250 2022/11/02 17:42:51 - mmengine - INFO - Epoch(train) [511][20/63] lr: 1.3138e-03 eta: 7:07:14 time: 0.5805 data_time: 0.0081 memory: 14901 loss: 1.4239 loss_prob: 0.7863 loss_thr: 0.5078 loss_db: 0.1298 2022/11/02 17:42:54 - mmengine - INFO - Epoch(train) [511][25/63] lr: 1.3138e-03 eta: 7:07:14 time: 0.5608 data_time: 0.0282 memory: 14901 loss: 1.4268 loss_prob: 0.7822 loss_thr: 0.5155 loss_db: 0.1292 2022/11/02 17:42:56 - mmengine - INFO - Epoch(train) [511][30/63] lr: 1.3138e-03 eta: 7:07:08 time: 0.5709 data_time: 0.0470 memory: 14901 loss: 1.3683 loss_prob: 0.7444 loss_thr: 0.4980 loss_db: 0.1260 2022/11/02 17:42:59 - mmengine - INFO - Epoch(train) [511][35/63] lr: 1.3138e-03 eta: 7:07:08 time: 0.5415 data_time: 0.0279 memory: 14901 loss: 1.3507 loss_prob: 0.7369 loss_thr: 0.4882 loss_db: 0.1256 2022/11/02 17:43:03 - mmengine - INFO - Epoch(train) [511][40/63] lr: 1.3138e-03 eta: 7:07:02 time: 0.6179 data_time: 0.0074 memory: 14901 loss: 1.4215 loss_prob: 0.7930 loss_thr: 0.4928 loss_db: 0.1357 2022/11/02 17:43:05 - mmengine - INFO - Epoch(train) [511][45/63] lr: 1.3138e-03 eta: 7:07:02 time: 0.5907 data_time: 0.0056 memory: 14901 loss: 1.3421 loss_prob: 0.7412 loss_thr: 0.4736 loss_db: 0.1274 2022/11/02 17:43:07 - mmengine - INFO - Epoch(train) [511][50/63] lr: 1.3138e-03 eta: 7:06:55 time: 0.4820 data_time: 0.0162 memory: 14901 loss: 1.2850 loss_prob: 0.6891 loss_thr: 0.4771 loss_db: 0.1188 2022/11/02 17:43:10 - mmengine - INFO - Epoch(train) [511][55/63] lr: 1.3138e-03 eta: 7:06:55 time: 0.5015 data_time: 0.0229 memory: 14901 loss: 1.3585 loss_prob: 0.7401 loss_thr: 0.4911 loss_db: 0.1272 2022/11/02 17:43:12 - mmengine - INFO - Epoch(train) [511][60/63] lr: 1.3138e-03 eta: 7:06:48 time: 0.4949 data_time: 0.0111 memory: 14901 loss: 1.3501 loss_prob: 0.7357 loss_thr: 0.4883 loss_db: 0.1262 2022/11/02 17:43:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:43:19 - mmengine - INFO - Epoch(train) [512][5/63] lr: 1.3121e-03 eta: 7:06:48 time: 0.7333 data_time: 0.1973 memory: 14901 loss: 1.4654 loss_prob: 0.8205 loss_thr: 0.5067 loss_db: 0.1382 2022/11/02 17:43:21 - mmengine - INFO - Epoch(train) [512][10/63] lr: 1.3121e-03 eta: 7:06:40 time: 0.7733 data_time: 0.1957 memory: 14901 loss: 1.4028 loss_prob: 0.7733 loss_thr: 0.5030 loss_db: 0.1266 2022/11/02 17:43:24 - mmengine - INFO - Epoch(train) [512][15/63] lr: 1.3121e-03 eta: 7:06:40 time: 0.4773 data_time: 0.0061 memory: 14901 loss: 1.4006 loss_prob: 0.7678 loss_thr: 0.5080 loss_db: 0.1248 2022/11/02 17:43:26 - mmengine - INFO - Epoch(train) [512][20/63] lr: 1.3121e-03 eta: 7:06:33 time: 0.4813 data_time: 0.0063 memory: 14901 loss: 1.4067 loss_prob: 0.7656 loss_thr: 0.5127 loss_db: 0.1284 2022/11/02 17:43:29 - mmengine - INFO - Epoch(train) [512][25/63] lr: 1.3121e-03 eta: 7:06:33 time: 0.5289 data_time: 0.0189 memory: 14901 loss: 1.3569 loss_prob: 0.7340 loss_thr: 0.4991 loss_db: 0.1238 2022/11/02 17:43:31 - mmengine - INFO - Epoch(train) [512][30/63] lr: 1.3121e-03 eta: 7:06:26 time: 0.5209 data_time: 0.0315 memory: 14901 loss: 1.2963 loss_prob: 0.6957 loss_thr: 0.4811 loss_db: 0.1195 2022/11/02 17:43:34 - mmengine - INFO - Epoch(train) [512][35/63] lr: 1.3121e-03 eta: 7:06:26 time: 0.4737 data_time: 0.0184 memory: 14901 loss: 1.3047 loss_prob: 0.7010 loss_thr: 0.4845 loss_db: 0.1192 2022/11/02 17:43:36 - mmengine - INFO - Epoch(train) [512][40/63] lr: 1.3121e-03 eta: 7:06:19 time: 0.4854 data_time: 0.0045 memory: 14901 loss: 1.3748 loss_prob: 0.7481 loss_thr: 0.5004 loss_db: 0.1263 2022/11/02 17:43:39 - mmengine - INFO - Epoch(train) [512][45/63] lr: 1.3121e-03 eta: 7:06:19 time: 0.5065 data_time: 0.0058 memory: 14901 loss: 1.3840 loss_prob: 0.7567 loss_thr: 0.4988 loss_db: 0.1284 2022/11/02 17:43:41 - mmengine - INFO - Epoch(train) [512][50/63] lr: 1.3121e-03 eta: 7:06:12 time: 0.5000 data_time: 0.0177 memory: 14901 loss: 1.3294 loss_prob: 0.7254 loss_thr: 0.4824 loss_db: 0.1217 2022/11/02 17:43:44 - mmengine - INFO - Epoch(train) [512][55/63] lr: 1.3121e-03 eta: 7:06:12 time: 0.4956 data_time: 0.0210 memory: 14901 loss: 1.2990 loss_prob: 0.7092 loss_thr: 0.4704 loss_db: 0.1194 2022/11/02 17:43:46 - mmengine - INFO - Epoch(train) [512][60/63] lr: 1.3121e-03 eta: 7:06:04 time: 0.5002 data_time: 0.0089 memory: 14901 loss: 1.3493 loss_prob: 0.7493 loss_thr: 0.4719 loss_db: 0.1281 2022/11/02 17:43:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:43:53 - mmengine - INFO - Epoch(train) [513][5/63] lr: 1.3104e-03 eta: 7:06:04 time: 0.7484 data_time: 0.2328 memory: 14901 loss: 1.3541 loss_prob: 0.7437 loss_thr: 0.4880 loss_db: 0.1225 2022/11/02 17:43:56 - mmengine - INFO - Epoch(train) [513][10/63] lr: 1.3104e-03 eta: 7:05:58 time: 0.8389 data_time: 0.2338 memory: 14901 loss: 1.3096 loss_prob: 0.7087 loss_thr: 0.4792 loss_db: 0.1217 2022/11/02 17:43:58 - mmengine - INFO - Epoch(train) [513][15/63] lr: 1.3104e-03 eta: 7:05:58 time: 0.5496 data_time: 0.0058 memory: 14901 loss: 1.3023 loss_prob: 0.7045 loss_thr: 0.4740 loss_db: 0.1238 2022/11/02 17:44:01 - mmengine - INFO - Epoch(train) [513][20/63] lr: 1.3104e-03 eta: 7:05:50 time: 0.4842 data_time: 0.0050 memory: 14901 loss: 1.3239 loss_prob: 0.7176 loss_thr: 0.4840 loss_db: 0.1223 2022/11/02 17:44:03 - mmengine - INFO - Epoch(train) [513][25/63] lr: 1.3104e-03 eta: 7:05:50 time: 0.4930 data_time: 0.0058 memory: 14901 loss: 1.3822 loss_prob: 0.7554 loss_thr: 0.5000 loss_db: 0.1268 2022/11/02 17:44:06 - mmengine - INFO - Epoch(train) [513][30/63] lr: 1.3104e-03 eta: 7:05:44 time: 0.5205 data_time: 0.0289 memory: 14901 loss: 1.3030 loss_prob: 0.6976 loss_thr: 0.4877 loss_db: 0.1177 2022/11/02 17:44:08 - mmengine - INFO - Epoch(train) [513][35/63] lr: 1.3104e-03 eta: 7:05:44 time: 0.4995 data_time: 0.0277 memory: 14901 loss: 1.2997 loss_prob: 0.7031 loss_thr: 0.4768 loss_db: 0.1198 2022/11/02 17:44:10 - mmengine - INFO - Epoch(train) [513][40/63] lr: 1.3104e-03 eta: 7:05:36 time: 0.4698 data_time: 0.0055 memory: 14901 loss: 1.4264 loss_prob: 0.7931 loss_thr: 0.5000 loss_db: 0.1333 2022/11/02 17:44:13 - mmengine - INFO - Epoch(train) [513][45/63] lr: 1.3104e-03 eta: 7:05:36 time: 0.4906 data_time: 0.0059 memory: 14901 loss: 1.2925 loss_prob: 0.7010 loss_thr: 0.4743 loss_db: 0.1172 2022/11/02 17:44:16 - mmengine - INFO - Epoch(train) [513][50/63] lr: 1.3104e-03 eta: 7:05:30 time: 0.5960 data_time: 0.0236 memory: 14901 loss: 1.1909 loss_prob: 0.6365 loss_thr: 0.4477 loss_db: 0.1067 2022/11/02 17:44:19 - mmengine - INFO - Epoch(train) [513][55/63] lr: 1.3104e-03 eta: 7:05:30 time: 0.6067 data_time: 0.0267 memory: 14901 loss: 1.2868 loss_prob: 0.6924 loss_thr: 0.4763 loss_db: 0.1182 2022/11/02 17:44:22 - mmengine - INFO - Epoch(train) [513][60/63] lr: 1.3104e-03 eta: 7:05:24 time: 0.5268 data_time: 0.0109 memory: 14901 loss: 1.3760 loss_prob: 0.7430 loss_thr: 0.5052 loss_db: 0.1278 2022/11/02 17:44:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:44:29 - mmengine - INFO - Epoch(train) [514][5/63] lr: 1.3087e-03 eta: 7:05:24 time: 0.8308 data_time: 0.2189 memory: 14901 loss: 1.3093 loss_prob: 0.7177 loss_thr: 0.4732 loss_db: 0.1183 2022/11/02 17:44:34 - mmengine - INFO - Epoch(train) [514][10/63] lr: 1.3087e-03 eta: 7:05:20 time: 1.0915 data_time: 0.2217 memory: 14901 loss: 1.2887 loss_prob: 0.6997 loss_thr: 0.4719 loss_db: 0.1172 2022/11/02 17:44:39 - mmengine - INFO - Epoch(train) [514][15/63] lr: 1.3087e-03 eta: 7:05:20 time: 0.9903 data_time: 0.0134 memory: 14901 loss: 1.3586 loss_prob: 0.7326 loss_thr: 0.5017 loss_db: 0.1243 2022/11/02 17:44:42 - mmengine - INFO - Epoch(train) [514][20/63] lr: 1.3087e-03 eta: 7:05:18 time: 0.8300 data_time: 0.0143 memory: 14901 loss: 1.2419 loss_prob: 0.6526 loss_thr: 0.4772 loss_db: 0.1121 2022/11/02 17:44:47 - mmengine - INFO - Epoch(train) [514][25/63] lr: 1.3087e-03 eta: 7:05:18 time: 0.7692 data_time: 0.0440 memory: 14901 loss: 1.2187 loss_prob: 0.6518 loss_thr: 0.4546 loss_db: 0.1123 2022/11/02 17:44:50 - mmengine - INFO - Epoch(train) [514][30/63] lr: 1.3087e-03 eta: 7:05:14 time: 0.7725 data_time: 0.0467 memory: 14901 loss: 1.2494 loss_prob: 0.6730 loss_thr: 0.4605 loss_db: 0.1159 2022/11/02 17:44:53 - mmengine - INFO - Epoch(train) [514][35/63] lr: 1.3087e-03 eta: 7:05:14 time: 0.6372 data_time: 0.0156 memory: 14901 loss: 1.2006 loss_prob: 0.6323 loss_thr: 0.4584 loss_db: 0.1099 2022/11/02 17:44:56 - mmengine - INFO - Epoch(train) [514][40/63] lr: 1.3087e-03 eta: 7:05:08 time: 0.5688 data_time: 0.0114 memory: 14901 loss: 1.2611 loss_prob: 0.6743 loss_thr: 0.4698 loss_db: 0.1170 2022/11/02 17:44:58 - mmengine - INFO - Epoch(train) [514][45/63] lr: 1.3087e-03 eta: 7:05:08 time: 0.5248 data_time: 0.0095 memory: 14901 loss: 1.3669 loss_prob: 0.7472 loss_thr: 0.4903 loss_db: 0.1294 2022/11/02 17:45:01 - mmengine - INFO - Epoch(train) [514][50/63] lr: 1.3087e-03 eta: 7:05:01 time: 0.5422 data_time: 0.0192 memory: 14901 loss: 1.4001 loss_prob: 0.7686 loss_thr: 0.4980 loss_db: 0.1335 2022/11/02 17:45:03 - mmengine - INFO - Epoch(train) [514][55/63] lr: 1.3087e-03 eta: 7:05:01 time: 0.5148 data_time: 0.0195 memory: 14901 loss: 1.3012 loss_prob: 0.7035 loss_thr: 0.4768 loss_db: 0.1209 2022/11/02 17:45:06 - mmengine - INFO - Epoch(train) [514][60/63] lr: 1.3087e-03 eta: 7:04:54 time: 0.4603 data_time: 0.0066 memory: 14901 loss: 1.3189 loss_prob: 0.7181 loss_thr: 0.4811 loss_db: 0.1197 2022/11/02 17:45:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:45:13 - mmengine - INFO - Epoch(train) [515][5/63] lr: 1.3070e-03 eta: 7:04:54 time: 0.8204 data_time: 0.2543 memory: 14901 loss: 1.4772 loss_prob: 0.8246 loss_thr: 0.5183 loss_db: 0.1342 2022/11/02 17:45:17 - mmengine - INFO - Epoch(train) [515][10/63] lr: 1.3070e-03 eta: 7:04:50 time: 1.0318 data_time: 0.2555 memory: 14901 loss: 1.4686 loss_prob: 0.8234 loss_thr: 0.5093 loss_db: 0.1359 2022/11/02 17:45:21 - mmengine - INFO - Epoch(train) [515][15/63] lr: 1.3070e-03 eta: 7:04:50 time: 0.7630 data_time: 0.0117 memory: 14901 loss: 1.3143 loss_prob: 0.7075 loss_thr: 0.4851 loss_db: 0.1217 2022/11/02 17:45:24 - mmengine - INFO - Epoch(train) [515][20/63] lr: 1.3070e-03 eta: 7:04:45 time: 0.6585 data_time: 0.0125 memory: 14901 loss: 1.3252 loss_prob: 0.7186 loss_thr: 0.4862 loss_db: 0.1204 2022/11/02 17:45:27 - mmengine - INFO - Epoch(train) [515][25/63] lr: 1.3070e-03 eta: 7:04:45 time: 0.6495 data_time: 0.0318 memory: 14901 loss: 1.3149 loss_prob: 0.7119 loss_thr: 0.4813 loss_db: 0.1218 2022/11/02 17:45:31 - mmengine - INFO - Epoch(train) [515][30/63] lr: 1.3070e-03 eta: 7:04:40 time: 0.6723 data_time: 0.0381 memory: 14901 loss: 1.2889 loss_prob: 0.6843 loss_thr: 0.4866 loss_db: 0.1180 2022/11/02 17:45:34 - mmengine - INFO - Epoch(train) [515][35/63] lr: 1.3070e-03 eta: 7:04:40 time: 0.6649 data_time: 0.0214 memory: 14901 loss: 1.2873 loss_prob: 0.6801 loss_thr: 0.4932 loss_db: 0.1140 2022/11/02 17:45:37 - mmengine - INFO - Epoch(train) [515][40/63] lr: 1.3070e-03 eta: 7:04:34 time: 0.6281 data_time: 0.0140 memory: 14901 loss: 1.3642 loss_prob: 0.7336 loss_thr: 0.5086 loss_db: 0.1220 2022/11/02 17:45:40 - mmengine - INFO - Epoch(train) [515][45/63] lr: 1.3070e-03 eta: 7:04:34 time: 0.6301 data_time: 0.0102 memory: 14901 loss: 1.3907 loss_prob: 0.7581 loss_thr: 0.5047 loss_db: 0.1279 2022/11/02 17:45:43 - mmengine - INFO - Epoch(train) [515][50/63] lr: 1.3070e-03 eta: 7:04:28 time: 0.5820 data_time: 0.0256 memory: 14901 loss: 1.3279 loss_prob: 0.7155 loss_thr: 0.4929 loss_db: 0.1195 2022/11/02 17:45:46 - mmengine - INFO - Epoch(train) [515][55/63] lr: 1.3070e-03 eta: 7:04:28 time: 0.5977 data_time: 0.0283 memory: 14901 loss: 1.2999 loss_prob: 0.6995 loss_thr: 0.4834 loss_db: 0.1170 2022/11/02 17:45:49 - mmengine - INFO - Epoch(train) [515][60/63] lr: 1.3070e-03 eta: 7:04:23 time: 0.6293 data_time: 0.0147 memory: 14901 loss: 1.2716 loss_prob: 0.6829 loss_thr: 0.4735 loss_db: 0.1153 2022/11/02 17:45:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:45:57 - mmengine - INFO - Epoch(train) [516][5/63] lr: 1.3053e-03 eta: 7:04:23 time: 0.8981 data_time: 0.2465 memory: 14901 loss: 1.3484 loss_prob: 0.7206 loss_thr: 0.5018 loss_db: 0.1261 2022/11/02 17:46:02 - mmengine - INFO - Epoch(train) [516][10/63] lr: 1.3053e-03 eta: 7:04:20 time: 1.1459 data_time: 0.2436 memory: 14901 loss: 1.2643 loss_prob: 0.6635 loss_thr: 0.4859 loss_db: 0.1149 2022/11/02 17:46:05 - mmengine - INFO - Epoch(train) [516][15/63] lr: 1.3053e-03 eta: 7:04:20 time: 0.7720 data_time: 0.0155 memory: 14901 loss: 1.2372 loss_prob: 0.6657 loss_thr: 0.4579 loss_db: 0.1137 2022/11/02 17:46:09 - mmengine - INFO - Epoch(train) [516][20/63] lr: 1.3053e-03 eta: 7:04:16 time: 0.6825 data_time: 0.0133 memory: 14901 loss: 1.3423 loss_prob: 0.7300 loss_thr: 0.4874 loss_db: 0.1249 2022/11/02 17:46:11 - mmengine - INFO - Epoch(train) [516][25/63] lr: 1.3053e-03 eta: 7:04:16 time: 0.6599 data_time: 0.0221 memory: 14901 loss: 1.3410 loss_prob: 0.7181 loss_thr: 0.4993 loss_db: 0.1236 2022/11/02 17:46:14 - mmengine - INFO - Epoch(train) [516][30/63] lr: 1.3053e-03 eta: 7:04:10 time: 0.5743 data_time: 0.0404 memory: 14901 loss: 1.3397 loss_prob: 0.7174 loss_thr: 0.4978 loss_db: 0.1245 2022/11/02 17:46:18 - mmengine - INFO - Epoch(train) [516][35/63] lr: 1.3053e-03 eta: 7:04:10 time: 0.6889 data_time: 0.0264 memory: 14901 loss: 1.3234 loss_prob: 0.7102 loss_thr: 0.4917 loss_db: 0.1216 2022/11/02 17:46:22 - mmengine - INFO - Epoch(train) [516][40/63] lr: 1.3053e-03 eta: 7:04:06 time: 0.7582 data_time: 0.0156 memory: 14901 loss: 1.3258 loss_prob: 0.7229 loss_thr: 0.4832 loss_db: 0.1197 2022/11/02 17:46:25 - mmengine - INFO - Epoch(train) [516][45/63] lr: 1.3053e-03 eta: 7:04:06 time: 0.6205 data_time: 0.0159 memory: 14901 loss: 1.2520 loss_prob: 0.6777 loss_thr: 0.4607 loss_db: 0.1135 2022/11/02 17:46:27 - mmengine - INFO - Epoch(train) [516][50/63] lr: 1.3053e-03 eta: 7:03:59 time: 0.5261 data_time: 0.0204 memory: 14901 loss: 1.2054 loss_prob: 0.6417 loss_thr: 0.4520 loss_db: 0.1117 2022/11/02 17:46:32 - mmengine - INFO - Epoch(train) [516][55/63] lr: 1.3053e-03 eta: 7:03:59 time: 0.7322 data_time: 0.0279 memory: 14901 loss: 1.2328 loss_prob: 0.6625 loss_thr: 0.4583 loss_db: 0.1120 2022/11/02 17:46:35 - mmengine - INFO - Epoch(train) [516][60/63] lr: 1.3053e-03 eta: 7:03:56 time: 0.7871 data_time: 0.0186 memory: 14901 loss: 1.2704 loss_prob: 0.6930 loss_thr: 0.4628 loss_db: 0.1146 2022/11/02 17:46:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:46:42 - mmengine - INFO - Epoch(train) [517][5/63] lr: 1.3035e-03 eta: 7:03:56 time: 0.7888 data_time: 0.2558 memory: 14901 loss: 1.2951 loss_prob: 0.6956 loss_thr: 0.4815 loss_db: 0.1180 2022/11/02 17:46:46 - mmengine - INFO - Epoch(train) [517][10/63] lr: 1.3035e-03 eta: 7:03:51 time: 0.9527 data_time: 0.2551 memory: 14901 loss: 1.2683 loss_prob: 0.6821 loss_thr: 0.4725 loss_db: 0.1138 2022/11/02 17:46:49 - mmengine - INFO - Epoch(train) [517][15/63] lr: 1.3035e-03 eta: 7:03:51 time: 0.7293 data_time: 0.0120 memory: 14901 loss: 1.2251 loss_prob: 0.6666 loss_thr: 0.4459 loss_db: 0.1127 2022/11/02 17:46:52 - mmengine - INFO - Epoch(train) [517][20/63] lr: 1.3035e-03 eta: 7:03:44 time: 0.5647 data_time: 0.0111 memory: 14901 loss: 1.2430 loss_prob: 0.6752 loss_thr: 0.4519 loss_db: 0.1158 2022/11/02 17:46:55 - mmengine - INFO - Epoch(train) [517][25/63] lr: 1.3035e-03 eta: 7:03:44 time: 0.5849 data_time: 0.0317 memory: 14901 loss: 1.3292 loss_prob: 0.7132 loss_thr: 0.4944 loss_db: 0.1217 2022/11/02 17:46:58 - mmengine - INFO - Epoch(train) [517][30/63] lr: 1.3035e-03 eta: 7:03:38 time: 0.5866 data_time: 0.0427 memory: 14901 loss: 1.3128 loss_prob: 0.7100 loss_thr: 0.4814 loss_db: 0.1214 2022/11/02 17:47:01 - mmengine - INFO - Epoch(train) [517][35/63] lr: 1.3035e-03 eta: 7:03:38 time: 0.5548 data_time: 0.0217 memory: 14901 loss: 1.2789 loss_prob: 0.6980 loss_thr: 0.4613 loss_db: 0.1196 2022/11/02 17:47:04 - mmengine - INFO - Epoch(train) [517][40/63] lr: 1.3035e-03 eta: 7:03:33 time: 0.6526 data_time: 0.0100 memory: 14901 loss: 1.2599 loss_prob: 0.6802 loss_thr: 0.4648 loss_db: 0.1149 2022/11/02 17:47:07 - mmengine - INFO - Epoch(train) [517][45/63] lr: 1.3035e-03 eta: 7:03:33 time: 0.6229 data_time: 0.0113 memory: 14901 loss: 1.2717 loss_prob: 0.6778 loss_thr: 0.4795 loss_db: 0.1145 2022/11/02 17:47:10 - mmengine - INFO - Epoch(train) [517][50/63] lr: 1.3035e-03 eta: 7:03:28 time: 0.6072 data_time: 0.0329 memory: 14901 loss: 1.2583 loss_prob: 0.6683 loss_thr: 0.4751 loss_db: 0.1149 2022/11/02 17:47:13 - mmengine - INFO - Epoch(train) [517][55/63] lr: 1.3035e-03 eta: 7:03:28 time: 0.6117 data_time: 0.0385 memory: 14901 loss: 1.2680 loss_prob: 0.6794 loss_thr: 0.4739 loss_db: 0.1147 2022/11/02 17:47:16 - mmengine - INFO - Epoch(train) [517][60/63] lr: 1.3035e-03 eta: 7:03:22 time: 0.5732 data_time: 0.0188 memory: 14901 loss: 1.2998 loss_prob: 0.7037 loss_thr: 0.4772 loss_db: 0.1189 2022/11/02 17:47:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:47:23 - mmengine - INFO - Epoch(train) [518][5/63] lr: 1.3018e-03 eta: 7:03:22 time: 0.8538 data_time: 0.2605 memory: 14901 loss: 1.3591 loss_prob: 0.7299 loss_thr: 0.5058 loss_db: 0.1235 2022/11/02 17:47:27 - mmengine - INFO - Epoch(train) [518][10/63] lr: 1.3018e-03 eta: 7:03:17 time: 0.9905 data_time: 0.2656 memory: 14901 loss: 1.5161 loss_prob: 0.8442 loss_thr: 0.5305 loss_db: 0.1414 2022/11/02 17:47:30 - mmengine - INFO - Epoch(train) [518][15/63] lr: 1.3018e-03 eta: 7:03:17 time: 0.7027 data_time: 0.0124 memory: 14901 loss: 1.4836 loss_prob: 0.8501 loss_thr: 0.4885 loss_db: 0.1450 2022/11/02 17:47:33 - mmengine - INFO - Epoch(train) [518][20/63] lr: 1.3018e-03 eta: 7:03:11 time: 0.5605 data_time: 0.0091 memory: 14901 loss: 1.4350 loss_prob: 0.8016 loss_thr: 0.4985 loss_db: 0.1349 2022/11/02 17:47:36 - mmengine - INFO - Epoch(train) [518][25/63] lr: 1.3018e-03 eta: 7:03:11 time: 0.5405 data_time: 0.0317 memory: 14901 loss: 1.3756 loss_prob: 0.7549 loss_thr: 0.4971 loss_db: 0.1235 2022/11/02 17:47:39 - mmengine - INFO - Epoch(train) [518][30/63] lr: 1.3018e-03 eta: 7:03:04 time: 0.5755 data_time: 0.0432 memory: 14901 loss: 1.3564 loss_prob: 0.7407 loss_thr: 0.4904 loss_db: 0.1252 2022/11/02 17:47:42 - mmengine - INFO - Epoch(train) [518][35/63] lr: 1.3018e-03 eta: 7:03:04 time: 0.5912 data_time: 0.0215 memory: 14901 loss: 1.3521 loss_prob: 0.7327 loss_thr: 0.4930 loss_db: 0.1264 2022/11/02 17:47:45 - mmengine - INFO - Epoch(train) [518][40/63] lr: 1.3018e-03 eta: 7:02:59 time: 0.6233 data_time: 0.0098 memory: 14901 loss: 1.2105 loss_prob: 0.6473 loss_thr: 0.4535 loss_db: 0.1097 2022/11/02 17:47:48 - mmengine - INFO - Epoch(train) [518][45/63] lr: 1.3018e-03 eta: 7:02:59 time: 0.5923 data_time: 0.0110 memory: 14901 loss: 1.2736 loss_prob: 0.6889 loss_thr: 0.4685 loss_db: 0.1161 2022/11/02 17:47:51 - mmengine - INFO - Epoch(train) [518][50/63] lr: 1.3018e-03 eta: 7:02:53 time: 0.5908 data_time: 0.0249 memory: 14901 loss: 1.3281 loss_prob: 0.7137 loss_thr: 0.4951 loss_db: 0.1193 2022/11/02 17:47:54 - mmengine - INFO - Epoch(train) [518][55/63] lr: 1.3018e-03 eta: 7:02:53 time: 0.6073 data_time: 0.0297 memory: 14901 loss: 1.3491 loss_prob: 0.7228 loss_thr: 0.5041 loss_db: 0.1221 2022/11/02 17:47:57 - mmengine - INFO - Epoch(train) [518][60/63] lr: 1.3018e-03 eta: 7:02:47 time: 0.5942 data_time: 0.0156 memory: 14901 loss: 1.3628 loss_prob: 0.7259 loss_thr: 0.5096 loss_db: 0.1273 2022/11/02 17:47:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:48:05 - mmengine - INFO - Epoch(train) [519][5/63] lr: 1.3001e-03 eta: 7:02:47 time: 0.9762 data_time: 0.2334 memory: 14901 loss: 1.2518 loss_prob: 0.6647 loss_thr: 0.4745 loss_db: 0.1126 2022/11/02 17:48:10 - mmengine - INFO - Epoch(train) [519][10/63] lr: 1.3001e-03 eta: 7:02:44 time: 1.0908 data_time: 0.2496 memory: 14901 loss: 1.3685 loss_prob: 0.7569 loss_thr: 0.4841 loss_db: 0.1275 2022/11/02 17:48:12 - mmengine - INFO - Epoch(train) [519][15/63] lr: 1.3001e-03 eta: 7:02:44 time: 0.6783 data_time: 0.0256 memory: 14901 loss: 1.3800 loss_prob: 0.7726 loss_thr: 0.4781 loss_db: 0.1293 2022/11/02 17:48:16 - mmengine - INFO - Epoch(train) [519][20/63] lr: 1.3001e-03 eta: 7:02:38 time: 0.6238 data_time: 0.0091 memory: 14901 loss: 1.3320 loss_prob: 0.7237 loss_thr: 0.4852 loss_db: 0.1230 2022/11/02 17:48:18 - mmengine - INFO - Epoch(train) [519][25/63] lr: 1.3001e-03 eta: 7:02:38 time: 0.6262 data_time: 0.0070 memory: 14901 loss: 1.3713 loss_prob: 0.7449 loss_thr: 0.4972 loss_db: 0.1292 2022/11/02 17:48:21 - mmengine - INFO - Epoch(train) [519][30/63] lr: 1.3001e-03 eta: 7:02:32 time: 0.5641 data_time: 0.0363 memory: 14901 loss: 1.2800 loss_prob: 0.6824 loss_thr: 0.4788 loss_db: 0.1188 2022/11/02 17:48:25 - mmengine - INFO - Epoch(train) [519][35/63] lr: 1.3001e-03 eta: 7:02:32 time: 0.6447 data_time: 0.0414 memory: 14901 loss: 1.3211 loss_prob: 0.7137 loss_thr: 0.4862 loss_db: 0.1212 2022/11/02 17:48:28 - mmengine - INFO - Epoch(train) [519][40/63] lr: 1.3001e-03 eta: 7:02:27 time: 0.6867 data_time: 0.0159 memory: 14901 loss: 1.3358 loss_prob: 0.7334 loss_thr: 0.4805 loss_db: 0.1219 2022/11/02 17:48:31 - mmengine - INFO - Epoch(train) [519][45/63] lr: 1.3001e-03 eta: 7:02:27 time: 0.6441 data_time: 0.0114 memory: 14901 loss: 1.2376 loss_prob: 0.6614 loss_thr: 0.4676 loss_db: 0.1086 2022/11/02 17:48:34 - mmengine - INFO - Epoch(train) [519][50/63] lr: 1.3001e-03 eta: 7:02:22 time: 0.6131 data_time: 0.0239 memory: 14901 loss: 1.2728 loss_prob: 0.6768 loss_thr: 0.4815 loss_db: 0.1145 2022/11/02 17:48:37 - mmengine - INFO - Epoch(train) [519][55/63] lr: 1.3001e-03 eta: 7:02:22 time: 0.6200 data_time: 0.0262 memory: 14901 loss: 1.3112 loss_prob: 0.7042 loss_thr: 0.4862 loss_db: 0.1208 2022/11/02 17:48:41 - mmengine - INFO - Epoch(train) [519][60/63] lr: 1.3001e-03 eta: 7:02:17 time: 0.6419 data_time: 0.0137 memory: 14901 loss: 1.2862 loss_prob: 0.6920 loss_thr: 0.4771 loss_db: 0.1171 2022/11/02 17:48:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:48:48 - mmengine - INFO - Epoch(train) [520][5/63] lr: 1.2984e-03 eta: 7:02:17 time: 0.8277 data_time: 0.1921 memory: 14901 loss: 1.2996 loss_prob: 0.6994 loss_thr: 0.4804 loss_db: 0.1198 2022/11/02 17:48:52 - mmengine - INFO - Epoch(train) [520][10/63] lr: 1.2984e-03 eta: 7:02:12 time: 0.9794 data_time: 0.2014 memory: 14901 loss: 1.3521 loss_prob: 0.7407 loss_thr: 0.4859 loss_db: 0.1255 2022/11/02 17:48:55 - mmengine - INFO - Epoch(train) [520][15/63] lr: 1.2984e-03 eta: 7:02:12 time: 0.7496 data_time: 0.0271 memory: 14901 loss: 1.3110 loss_prob: 0.7161 loss_thr: 0.4749 loss_db: 0.1200 2022/11/02 17:48:59 - mmengine - INFO - Epoch(train) [520][20/63] lr: 1.2984e-03 eta: 7:02:07 time: 0.6884 data_time: 0.0169 memory: 14901 loss: 1.2685 loss_prob: 0.6822 loss_thr: 0.4702 loss_db: 0.1160 2022/11/02 17:49:02 - mmengine - INFO - Epoch(train) [520][25/63] lr: 1.2984e-03 eta: 7:02:07 time: 0.6425 data_time: 0.0132 memory: 14901 loss: 1.3513 loss_prob: 0.7481 loss_thr: 0.4754 loss_db: 0.1278 2022/11/02 17:49:05 - mmengine - INFO - Epoch(train) [520][30/63] lr: 1.2984e-03 eta: 7:02:01 time: 0.6111 data_time: 0.0267 memory: 14901 loss: 1.2979 loss_prob: 0.7151 loss_thr: 0.4615 loss_db: 0.1214 2022/11/02 17:49:08 - mmengine - INFO - Epoch(train) [520][35/63] lr: 1.2984e-03 eta: 7:02:01 time: 0.5766 data_time: 0.0313 memory: 14901 loss: 1.2644 loss_prob: 0.6803 loss_thr: 0.4682 loss_db: 0.1158 2022/11/02 17:49:10 - mmengine - INFO - Epoch(train) [520][40/63] lr: 1.2984e-03 eta: 7:01:55 time: 0.5324 data_time: 0.0236 memory: 14901 loss: 1.2324 loss_prob: 0.6562 loss_thr: 0.4628 loss_db: 0.1134 2022/11/02 17:49:13 - mmengine - INFO - Epoch(train) [520][45/63] lr: 1.2984e-03 eta: 7:01:55 time: 0.5069 data_time: 0.0168 memory: 14901 loss: 1.2195 loss_prob: 0.6417 loss_thr: 0.4671 loss_db: 0.1108 2022/11/02 17:49:15 - mmengine - INFO - Epoch(train) [520][50/63] lr: 1.2984e-03 eta: 7:01:48 time: 0.5106 data_time: 0.0164 memory: 14901 loss: 1.3434 loss_prob: 0.7081 loss_thr: 0.5141 loss_db: 0.1212 2022/11/02 17:49:18 - mmengine - INFO - Epoch(train) [520][55/63] lr: 1.2984e-03 eta: 7:01:48 time: 0.5098 data_time: 0.0231 memory: 14901 loss: 1.3234 loss_prob: 0.6981 loss_thr: 0.5046 loss_db: 0.1206 2022/11/02 17:49:20 - mmengine - INFO - Epoch(train) [520][60/63] lr: 1.2984e-03 eta: 7:01:41 time: 0.4930 data_time: 0.0196 memory: 14901 loss: 1.2470 loss_prob: 0.6767 loss_thr: 0.4541 loss_db: 0.1163 2022/11/02 17:49:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:49:22 - mmengine - INFO - Saving checkpoint at 520 epochs 2022/11/02 17:49:25 - mmengine - INFO - Epoch(val) [520][5/500] eta: 7:01:41 time: 0.0451 data_time: 0.0055 memory: 14901 2022/11/02 17:49:25 - mmengine - INFO - Epoch(val) [520][10/500] eta: 0:00:24 time: 0.0507 data_time: 0.0062 memory: 1008 2022/11/02 17:49:26 - mmengine - INFO - Epoch(val) [520][15/500] eta: 0:00:24 time: 0.0455 data_time: 0.0037 memory: 1008 2022/11/02 17:49:26 - mmengine - INFO - Epoch(val) [520][20/500] eta: 0:00:21 time: 0.0455 data_time: 0.0037 memory: 1008 2022/11/02 17:49:26 - mmengine - INFO - Epoch(val) [520][25/500] eta: 0:00:21 time: 0.0426 data_time: 0.0034 memory: 1008 2022/11/02 17:49:26 - mmengine - INFO - Epoch(val) [520][30/500] eta: 0:00:21 time: 0.0461 data_time: 0.0035 memory: 1008 2022/11/02 17:49:27 - mmengine - INFO - Epoch(val) [520][35/500] eta: 0:00:21 time: 0.0468 data_time: 0.0034 memory: 1008 2022/11/02 17:49:27 - mmengine - INFO - Epoch(val) [520][40/500] eta: 0:00:21 time: 0.0466 data_time: 0.0031 memory: 1008 2022/11/02 17:49:27 - mmengine - INFO - Epoch(val) [520][45/500] eta: 0:00:21 time: 0.0511 data_time: 0.0035 memory: 1008 2022/11/02 17:49:27 - mmengine - INFO - Epoch(val) [520][50/500] eta: 0:00:23 time: 0.0513 data_time: 0.0042 memory: 1008 2022/11/02 17:49:28 - mmengine - INFO - Epoch(val) [520][55/500] eta: 0:00:23 time: 0.0519 data_time: 0.0040 memory: 1008 2022/11/02 17:49:28 - mmengine - INFO - Epoch(val) [520][60/500] eta: 0:00:20 time: 0.0465 data_time: 0.0037 memory: 1008 2022/11/02 17:49:28 - mmengine - INFO - Epoch(val) [520][65/500] eta: 0:00:20 time: 0.0429 data_time: 0.0034 memory: 1008 2022/11/02 17:49:28 - mmengine - INFO - Epoch(val) [520][70/500] eta: 0:00:20 time: 0.0466 data_time: 0.0028 memory: 1008 2022/11/02 17:49:28 - mmengine - INFO - Epoch(val) [520][75/500] eta: 0:00:20 time: 0.0428 data_time: 0.0031 memory: 1008 2022/11/02 17:49:29 - mmengine - INFO - Epoch(val) [520][80/500] eta: 0:00:15 time: 0.0364 data_time: 0.0030 memory: 1008 2022/11/02 17:49:29 - mmengine - INFO - Epoch(val) [520][85/500] eta: 0:00:15 time: 0.0352 data_time: 0.0025 memory: 1008 2022/11/02 17:49:29 - mmengine - INFO - Epoch(val) [520][90/500] eta: 0:00:16 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 17:49:29 - mmengine - INFO - Epoch(val) [520][95/500] eta: 0:00:16 time: 0.0446 data_time: 0.0028 memory: 1008 2022/11/02 17:49:29 - mmengine - INFO - Epoch(val) [520][100/500] eta: 0:00:15 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 17:49:30 - mmengine - INFO - Epoch(val) [520][105/500] eta: 0:00:15 time: 0.0363 data_time: 0.0026 memory: 1008 2022/11/02 17:49:30 - mmengine - INFO - Epoch(val) [520][110/500] eta: 0:00:15 time: 0.0385 data_time: 0.0027 memory: 1008 2022/11/02 17:49:30 - mmengine - INFO - Epoch(val) [520][115/500] eta: 0:00:15 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 17:49:30 - mmengine - INFO - Epoch(val) [520][120/500] eta: 0:00:16 time: 0.0445 data_time: 0.0029 memory: 1008 2022/11/02 17:49:30 - mmengine - INFO - Epoch(val) [520][125/500] eta: 0:00:16 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/02 17:49:31 - mmengine - INFO - Epoch(val) [520][130/500] eta: 0:00:13 time: 0.0374 data_time: 0.0027 memory: 1008 2022/11/02 17:49:31 - mmengine - INFO - Epoch(val) [520][135/500] eta: 0:00:13 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 17:49:31 - mmengine - INFO - Epoch(val) [520][140/500] eta: 0:00:14 time: 0.0401 data_time: 0.0028 memory: 1008 2022/11/02 17:49:31 - mmengine - INFO - Epoch(val) [520][145/500] eta: 0:00:14 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 17:49:31 - mmengine - INFO - Epoch(val) [520][150/500] eta: 0:00:14 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/02 17:49:32 - mmengine - INFO - Epoch(val) [520][155/500] eta: 0:00:14 time: 0.0420 data_time: 0.0024 memory: 1008 2022/11/02 17:49:32 - mmengine - INFO - Epoch(val) [520][160/500] eta: 0:00:15 time: 0.0456 data_time: 0.0029 memory: 1008 2022/11/02 17:49:32 - mmengine - INFO - Epoch(val) [520][165/500] eta: 0:00:15 time: 0.0446 data_time: 0.0032 memory: 1008 2022/11/02 17:49:32 - mmengine - INFO - Epoch(val) [520][170/500] eta: 0:00:14 time: 0.0436 data_time: 0.0029 memory: 1008 2022/11/02 17:49:33 - mmengine - INFO - Epoch(val) [520][175/500] eta: 0:00:14 time: 0.0437 data_time: 0.0034 memory: 1008 2022/11/02 17:49:33 - mmengine - INFO - Epoch(val) [520][180/500] eta: 0:00:12 time: 0.0404 data_time: 0.0032 memory: 1008 2022/11/02 17:49:33 - mmengine - INFO - Epoch(val) [520][185/500] eta: 0:00:12 time: 0.0419 data_time: 0.0025 memory: 1008 2022/11/02 17:49:33 - mmengine - INFO - Epoch(val) [520][190/500] eta: 0:00:13 time: 0.0450 data_time: 0.0028 memory: 1008 2022/11/02 17:49:33 - mmengine - INFO - Epoch(val) [520][195/500] eta: 0:00:13 time: 0.0413 data_time: 0.0032 memory: 1008 2022/11/02 17:49:34 - mmengine - INFO - Epoch(val) [520][200/500] eta: 0:00:13 time: 0.0453 data_time: 0.0031 memory: 1008 2022/11/02 17:49:34 - mmengine - INFO - Epoch(val) [520][205/500] eta: 0:00:13 time: 0.0445 data_time: 0.0026 memory: 1008 2022/11/02 17:49:34 - mmengine - INFO - Epoch(val) [520][210/500] eta: 0:00:10 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 17:49:34 - mmengine - INFO - Epoch(val) [520][215/500] eta: 0:00:10 time: 0.0378 data_time: 0.0027 memory: 1008 2022/11/02 17:49:34 - mmengine - INFO - Epoch(val) [520][220/500] eta: 0:00:10 time: 0.0372 data_time: 0.0026 memory: 1008 2022/11/02 17:49:35 - mmengine - INFO - Epoch(val) [520][225/500] eta: 0:00:10 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/02 17:49:35 - mmengine - INFO - Epoch(val) [520][230/500] eta: 0:00:10 time: 0.0402 data_time: 0.0030 memory: 1008 2022/11/02 17:49:35 - mmengine - INFO - Epoch(val) [520][235/500] eta: 0:00:10 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 17:49:35 - mmengine - INFO - Epoch(val) [520][240/500] eta: 0:00:12 time: 0.0462 data_time: 0.0031 memory: 1008 2022/11/02 17:49:35 - mmengine - INFO - Epoch(val) [520][245/500] eta: 0:00:12 time: 0.0425 data_time: 0.0030 memory: 1008 2022/11/02 17:49:36 - mmengine - INFO - Epoch(val) [520][250/500] eta: 0:00:10 time: 0.0407 data_time: 0.0028 memory: 1008 2022/11/02 17:49:36 - mmengine - INFO - Epoch(val) [520][255/500] eta: 0:00:10 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 17:49:36 - mmengine - INFO - Epoch(val) [520][260/500] eta: 0:00:09 time: 0.0383 data_time: 0.0026 memory: 1008 2022/11/02 17:49:36 - mmengine - INFO - Epoch(val) [520][265/500] eta: 0:00:09 time: 0.0401 data_time: 0.0026 memory: 1008 2022/11/02 17:49:36 - mmengine - INFO - Epoch(val) [520][270/500] eta: 0:00:09 time: 0.0401 data_time: 0.0026 memory: 1008 2022/11/02 17:49:37 - mmengine - INFO - Epoch(val) [520][275/500] eta: 0:00:09 time: 0.0398 data_time: 0.0026 memory: 1008 2022/11/02 17:49:37 - mmengine - INFO - Epoch(val) [520][280/500] eta: 0:00:09 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 17:49:37 - mmengine - INFO - Epoch(val) [520][285/500] eta: 0:00:09 time: 0.0419 data_time: 0.0027 memory: 1008 2022/11/02 17:49:37 - mmengine - INFO - Epoch(val) [520][290/500] eta: 0:00:09 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/02 17:49:37 - mmengine - INFO - Epoch(val) [520][295/500] eta: 0:00:09 time: 0.0439 data_time: 0.0030 memory: 1008 2022/11/02 17:49:38 - mmengine - INFO - Epoch(val) [520][300/500] eta: 0:00:08 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/02 17:49:38 - mmengine - INFO - Epoch(val) [520][305/500] eta: 0:00:08 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 17:49:38 - mmengine - INFO - Epoch(val) [520][310/500] eta: 0:00:07 time: 0.0385 data_time: 0.0024 memory: 1008 2022/11/02 17:49:38 - mmengine - INFO - Epoch(val) [520][315/500] eta: 0:00:07 time: 0.0432 data_time: 0.0027 memory: 1008 2022/11/02 17:49:39 - mmengine - INFO - Epoch(val) [520][320/500] eta: 0:00:07 time: 0.0422 data_time: 0.0028 memory: 1008 2022/11/02 17:49:39 - mmengine - INFO - Epoch(val) [520][325/500] eta: 0:00:07 time: 0.0562 data_time: 0.0029 memory: 1008 2022/11/02 17:49:39 - mmengine - INFO - Epoch(val) [520][330/500] eta: 0:00:09 time: 0.0570 data_time: 0.0029 memory: 1008 2022/11/02 17:49:39 - mmengine - INFO - Epoch(val) [520][335/500] eta: 0:00:09 time: 0.0391 data_time: 0.0031 memory: 1008 2022/11/02 17:49:40 - mmengine - INFO - Epoch(val) [520][340/500] eta: 0:00:07 time: 0.0458 data_time: 0.0025 memory: 1008 2022/11/02 17:49:40 - mmengine - INFO - Epoch(val) [520][345/500] eta: 0:00:07 time: 0.0482 data_time: 0.0022 memory: 1008 2022/11/02 17:49:40 - mmengine - INFO - Epoch(val) [520][350/500] eta: 0:00:06 time: 0.0447 data_time: 0.0029 memory: 1008 2022/11/02 17:49:40 - mmengine - INFO - Epoch(val) [520][355/500] eta: 0:00:06 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 17:49:40 - mmengine - INFO - Epoch(val) [520][360/500] eta: 0:00:05 time: 0.0386 data_time: 0.0027 memory: 1008 2022/11/02 17:49:41 - mmengine - INFO - Epoch(val) [520][365/500] eta: 0:00:05 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 17:49:41 - mmengine - INFO - Epoch(val) [520][370/500] eta: 0:00:04 time: 0.0372 data_time: 0.0026 memory: 1008 2022/11/02 17:49:41 - mmengine - INFO - Epoch(val) [520][375/500] eta: 0:00:04 time: 0.0373 data_time: 0.0030 memory: 1008 2022/11/02 17:49:41 - mmengine - INFO - Epoch(val) [520][380/500] eta: 0:00:05 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/02 17:49:41 - mmengine - INFO - Epoch(val) [520][385/500] eta: 0:00:05 time: 0.0425 data_time: 0.0028 memory: 1008 2022/11/02 17:49:42 - mmengine - INFO - Epoch(val) [520][390/500] eta: 0:00:04 time: 0.0421 data_time: 0.0029 memory: 1008 2022/11/02 17:49:42 - mmengine - INFO - Epoch(val) [520][395/500] eta: 0:00:04 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/02 17:49:42 - mmengine - INFO - Epoch(val) [520][400/500] eta: 0:00:03 time: 0.0391 data_time: 0.0028 memory: 1008 2022/11/02 17:49:42 - mmengine - INFO - Epoch(val) [520][405/500] eta: 0:00:03 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 17:49:42 - mmengine - INFO - Epoch(val) [520][410/500] eta: 0:00:03 time: 0.0401 data_time: 0.0025 memory: 1008 2022/11/02 17:49:43 - mmengine - INFO - Epoch(val) [520][415/500] eta: 0:00:03 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 17:49:43 - mmengine - INFO - Epoch(val) [520][420/500] eta: 0:00:03 time: 0.0381 data_time: 0.0028 memory: 1008 2022/11/02 17:49:43 - mmengine - INFO - Epoch(val) [520][425/500] eta: 0:00:03 time: 0.0387 data_time: 0.0028 memory: 1008 2022/11/02 17:49:43 - mmengine - INFO - Epoch(val) [520][430/500] eta: 0:00:02 time: 0.0409 data_time: 0.0029 memory: 1008 2022/11/02 17:49:43 - mmengine - INFO - Epoch(val) [520][435/500] eta: 0:00:02 time: 0.0383 data_time: 0.0029 memory: 1008 2022/11/02 17:49:44 - mmengine - INFO - Epoch(val) [520][440/500] eta: 0:00:02 time: 0.0425 data_time: 0.0030 memory: 1008 2022/11/02 17:49:44 - mmengine - INFO - Epoch(val) [520][445/500] eta: 0:00:02 time: 0.0485 data_time: 0.0032 memory: 1008 2022/11/02 17:49:44 - mmengine - INFO - Epoch(val) [520][450/500] eta: 0:00:02 time: 0.0445 data_time: 0.0029 memory: 1008 2022/11/02 17:49:44 - mmengine - INFO - Epoch(val) [520][455/500] eta: 0:00:02 time: 0.0415 data_time: 0.0027 memory: 1008 2022/11/02 17:49:44 - mmengine - INFO - Epoch(val) [520][460/500] eta: 0:00:01 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 17:49:45 - mmengine - INFO - Epoch(val) [520][465/500] eta: 0:00:01 time: 0.0377 data_time: 0.0033 memory: 1008 2022/11/02 17:49:45 - mmengine - INFO - Epoch(val) [520][470/500] eta: 0:00:01 time: 0.0467 data_time: 0.0039 memory: 1008 2022/11/02 17:49:45 - mmengine - INFO - Epoch(val) [520][475/500] eta: 0:00:01 time: 0.0437 data_time: 0.0032 memory: 1008 2022/11/02 17:49:45 - mmengine - INFO - Epoch(val) [520][480/500] eta: 0:00:00 time: 0.0383 data_time: 0.0027 memory: 1008 2022/11/02 17:49:45 - mmengine - INFO - Epoch(val) [520][485/500] eta: 0:00:00 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 17:49:46 - mmengine - INFO - Epoch(val) [520][490/500] eta: 0:00:00 time: 0.0390 data_time: 0.0025 memory: 1008 2022/11/02 17:49:46 - mmengine - INFO - Epoch(val) [520][495/500] eta: 0:00:00 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 17:49:46 - mmengine - INFO - Epoch(val) [520][500/500] eta: 0:00:00 time: 0.0367 data_time: 0.0025 memory: 1008 2022/11/02 17:49:46 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7944, precision: 0.7269, hmean: 0.7591 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7944, precision: 0.7838, hmean: 0.7891 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7935, precision: 0.8183, hmean: 0.8057 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7848, precision: 0.8481, hmean: 0.8152 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7520, precision: 0.8820, hmean: 0.8119 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5234, precision: 0.9228, hmean: 0.6679 2022/11/02 17:49:46 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0351, precision: 0.9241, hmean: 0.0677 2022/11/02 17:49:46 - mmengine - INFO - Epoch(val) [520][500/500] icdar/precision: 0.8481 icdar/recall: 0.7848 icdar/hmean: 0.8152 2022/11/02 17:49:52 - mmengine - INFO - Epoch(train) [521][5/63] lr: 1.2967e-03 eta: 0:00:00 time: 0.7745 data_time: 0.2047 memory: 14901 loss: 1.2411 loss_prob: 0.6588 loss_thr: 0.4699 loss_db: 0.1123 2022/11/02 17:49:55 - mmengine - INFO - Epoch(train) [521][10/63] lr: 1.2967e-03 eta: 7:01:34 time: 0.8534 data_time: 0.2154 memory: 14901 loss: 1.2405 loss_prob: 0.6592 loss_thr: 0.4697 loss_db: 0.1116 2022/11/02 17:49:57 - mmengine - INFO - Epoch(train) [521][15/63] lr: 1.2967e-03 eta: 7:01:34 time: 0.5793 data_time: 0.0223 memory: 14901 loss: 1.3818 loss_prob: 0.7603 loss_thr: 0.4934 loss_db: 0.1282 2022/11/02 17:50:01 - mmengine - INFO - Epoch(train) [521][20/63] lr: 1.2967e-03 eta: 7:01:29 time: 0.6429 data_time: 0.0103 memory: 14901 loss: 1.4188 loss_prob: 0.7767 loss_thr: 0.5093 loss_db: 0.1328 2022/11/02 17:50:04 - mmengine - INFO - Epoch(train) [521][25/63] lr: 1.2967e-03 eta: 7:01:29 time: 0.6862 data_time: 0.0093 memory: 14901 loss: 1.3780 loss_prob: 0.7486 loss_thr: 0.5033 loss_db: 0.1261 2022/11/02 17:50:10 - mmengine - INFO - Epoch(train) [521][30/63] lr: 1.2967e-03 eta: 7:01:26 time: 0.8424 data_time: 0.0337 memory: 14901 loss: 1.3768 loss_prob: 0.7567 loss_thr: 0.4953 loss_db: 0.1248 2022/11/02 17:50:13 - mmengine - INFO - Epoch(train) [521][35/63] lr: 1.2967e-03 eta: 7:01:26 time: 0.8783 data_time: 0.0476 memory: 14901 loss: 1.3358 loss_prob: 0.7307 loss_thr: 0.4812 loss_db: 0.1239 2022/11/02 17:50:16 - mmengine - INFO - Epoch(train) [521][40/63] lr: 1.2967e-03 eta: 7:01:21 time: 0.6124 data_time: 0.0222 memory: 14901 loss: 1.2665 loss_prob: 0.6729 loss_thr: 0.4780 loss_db: 0.1155 2022/11/02 17:50:19 - mmengine - INFO - Epoch(train) [521][45/63] lr: 1.2967e-03 eta: 7:01:21 time: 0.5845 data_time: 0.0083 memory: 14901 loss: 1.2600 loss_prob: 0.6687 loss_thr: 0.4771 loss_db: 0.1142 2022/11/02 17:50:22 - mmengine - INFO - Epoch(train) [521][50/63] lr: 1.2967e-03 eta: 7:01:15 time: 0.6284 data_time: 0.0173 memory: 14901 loss: 1.2638 loss_prob: 0.6755 loss_thr: 0.4729 loss_db: 0.1154 2022/11/02 17:50:25 - mmengine - INFO - Epoch(train) [521][55/63] lr: 1.2967e-03 eta: 7:01:15 time: 0.6256 data_time: 0.0214 memory: 14901 loss: 1.2994 loss_prob: 0.6931 loss_thr: 0.4861 loss_db: 0.1201 2022/11/02 17:50:28 - mmengine - INFO - Epoch(train) [521][60/63] lr: 1.2967e-03 eta: 7:01:10 time: 0.6262 data_time: 0.0148 memory: 14901 loss: 1.2973 loss_prob: 0.7021 loss_thr: 0.4765 loss_db: 0.1187 2022/11/02 17:50:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:50:36 - mmengine - INFO - Epoch(train) [522][5/63] lr: 1.2949e-03 eta: 7:01:10 time: 0.8866 data_time: 0.2622 memory: 14901 loss: 1.1649 loss_prob: 0.6135 loss_thr: 0.4456 loss_db: 0.1057 2022/11/02 17:50:40 - mmengine - INFO - Epoch(train) [522][10/63] lr: 1.2949e-03 eta: 7:01:06 time: 1.0405 data_time: 0.2629 memory: 14901 loss: 1.2823 loss_prob: 0.7043 loss_thr: 0.4578 loss_db: 0.1202 2022/11/02 17:50:43 - mmengine - INFO - Epoch(train) [522][15/63] lr: 1.2949e-03 eta: 7:01:06 time: 0.6625 data_time: 0.0111 memory: 14901 loss: 1.3456 loss_prob: 0.7435 loss_thr: 0.4770 loss_db: 0.1251 2022/11/02 17:50:45 - mmengine - INFO - Epoch(train) [522][20/63] lr: 1.2949e-03 eta: 7:00:59 time: 0.5078 data_time: 0.0112 memory: 14901 loss: 1.2985 loss_prob: 0.7054 loss_thr: 0.4695 loss_db: 0.1236 2022/11/02 17:50:48 - mmengine - INFO - Epoch(train) [522][25/63] lr: 1.2949e-03 eta: 7:00:59 time: 0.5280 data_time: 0.0164 memory: 14901 loss: 1.4367 loss_prob: 0.8178 loss_thr: 0.4764 loss_db: 0.1424 2022/11/02 17:50:52 - mmengine - INFO - Epoch(train) [522][30/63] lr: 1.2949e-03 eta: 7:00:54 time: 0.6532 data_time: 0.0574 memory: 14901 loss: 1.4006 loss_prob: 0.7954 loss_thr: 0.4687 loss_db: 0.1365 2022/11/02 17:50:54 - mmengine - INFO - Epoch(train) [522][35/63] lr: 1.2949e-03 eta: 7:00:54 time: 0.6431 data_time: 0.0515 memory: 14901 loss: 1.3898 loss_prob: 0.7689 loss_thr: 0.4907 loss_db: 0.1302 2022/11/02 17:50:57 - mmengine - INFO - Epoch(train) [522][40/63] lr: 1.2949e-03 eta: 7:00:47 time: 0.5584 data_time: 0.0099 memory: 14901 loss: 1.4151 loss_prob: 0.7604 loss_thr: 0.5258 loss_db: 0.1289 2022/11/02 17:51:00 - mmengine - INFO - Epoch(train) [522][45/63] lr: 1.2949e-03 eta: 7:00:47 time: 0.5570 data_time: 0.0102 memory: 14901 loss: 1.3660 loss_prob: 0.7297 loss_thr: 0.5081 loss_db: 0.1283 2022/11/02 17:51:03 - mmengine - INFO - Epoch(train) [522][50/63] lr: 1.2949e-03 eta: 7:00:41 time: 0.5575 data_time: 0.0243 memory: 14901 loss: 1.4480 loss_prob: 0.7929 loss_thr: 0.5196 loss_db: 0.1355 2022/11/02 17:51:06 - mmengine - INFO - Epoch(train) [522][55/63] lr: 1.2949e-03 eta: 7:00:41 time: 0.6052 data_time: 0.0294 memory: 14901 loss: 1.4540 loss_prob: 0.7884 loss_thr: 0.5346 loss_db: 0.1310 2022/11/02 17:51:09 - mmengine - INFO - Epoch(train) [522][60/63] lr: 1.2949e-03 eta: 7:00:35 time: 0.6150 data_time: 0.0161 memory: 14901 loss: 1.3930 loss_prob: 0.7499 loss_thr: 0.5151 loss_db: 0.1280 2022/11/02 17:51:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:51:16 - mmengine - INFO - Epoch(train) [523][5/63] lr: 1.2932e-03 eta: 7:00:35 time: 0.8089 data_time: 0.2550 memory: 14901 loss: 1.5080 loss_prob: 0.8411 loss_thr: 0.5313 loss_db: 0.1356 2022/11/02 17:51:19 - mmengine - INFO - Epoch(train) [523][10/63] lr: 1.2932e-03 eta: 7:00:29 time: 0.9025 data_time: 0.2525 memory: 14901 loss: 1.8913 loss_prob: 1.2180 loss_thr: 0.5048 loss_db: 0.1685 2022/11/02 17:51:22 - mmengine - INFO - Epoch(train) [523][15/63] lr: 1.2932e-03 eta: 7:00:29 time: 0.5522 data_time: 0.0092 memory: 14901 loss: 1.8241 loss_prob: 1.1653 loss_thr: 0.4953 loss_db: 0.1635 2022/11/02 17:51:24 - mmengine - INFO - Epoch(train) [523][20/63] lr: 1.2932e-03 eta: 7:00:22 time: 0.5028 data_time: 0.0102 memory: 14901 loss: 1.3772 loss_prob: 0.7712 loss_thr: 0.4797 loss_db: 0.1263 2022/11/02 17:51:28 - mmengine - INFO - Epoch(train) [523][25/63] lr: 1.2932e-03 eta: 7:00:22 time: 0.6522 data_time: 0.0389 memory: 14901 loss: 1.3300 loss_prob: 0.7324 loss_thr: 0.4742 loss_db: 0.1235 2022/11/02 17:51:31 - mmengine - INFO - Epoch(train) [523][30/63] lr: 1.2932e-03 eta: 7:00:18 time: 0.6840 data_time: 0.0462 memory: 14901 loss: 1.3256 loss_prob: 0.7219 loss_thr: 0.4802 loss_db: 0.1236 2022/11/02 17:51:34 - mmengine - INFO - Epoch(train) [523][35/63] lr: 1.2932e-03 eta: 7:00:18 time: 0.5867 data_time: 0.0170 memory: 14901 loss: 1.4669 loss_prob: 0.8175 loss_thr: 0.5131 loss_db: 0.1362 2022/11/02 17:51:37 - mmengine - INFO - Epoch(train) [523][40/63] lr: 1.2932e-03 eta: 7:00:12 time: 0.5869 data_time: 0.0080 memory: 14901 loss: 1.4174 loss_prob: 0.7795 loss_thr: 0.5098 loss_db: 0.1282 2022/11/02 17:51:40 - mmengine - INFO - Epoch(train) [523][45/63] lr: 1.2932e-03 eta: 7:00:12 time: 0.6190 data_time: 0.0103 memory: 14901 loss: 1.3600 loss_prob: 0.7382 loss_thr: 0.4982 loss_db: 0.1236 2022/11/02 17:51:43 - mmengine - INFO - Epoch(train) [523][50/63] lr: 1.2932e-03 eta: 7:00:06 time: 0.6286 data_time: 0.0332 memory: 14901 loss: 1.3309 loss_prob: 0.7148 loss_thr: 0.4921 loss_db: 0.1239 2022/11/02 17:51:46 - mmengine - INFO - Epoch(train) [523][55/63] lr: 1.2932e-03 eta: 7:00:06 time: 0.6078 data_time: 0.0334 memory: 14901 loss: 1.3194 loss_prob: 0.7069 loss_thr: 0.4914 loss_db: 0.1211 2022/11/02 17:51:49 - mmengine - INFO - Epoch(train) [523][60/63] lr: 1.2932e-03 eta: 7:00:00 time: 0.5580 data_time: 0.0131 memory: 14901 loss: 1.3468 loss_prob: 0.7239 loss_thr: 0.5008 loss_db: 0.1222 2022/11/02 17:51:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:51:57 - mmengine - INFO - Epoch(train) [524][5/63] lr: 1.2915e-03 eta: 7:00:00 time: 0.8690 data_time: 0.2208 memory: 14901 loss: 1.3081 loss_prob: 0.6989 loss_thr: 0.4906 loss_db: 0.1186 2022/11/02 17:51:59 - mmengine - INFO - Epoch(train) [524][10/63] lr: 1.2915e-03 eta: 6:59:54 time: 0.8956 data_time: 0.2281 memory: 14901 loss: 1.3542 loss_prob: 0.7367 loss_thr: 0.4931 loss_db: 0.1244 2022/11/02 17:52:02 - mmengine - INFO - Epoch(train) [524][15/63] lr: 1.2915e-03 eta: 6:59:54 time: 0.5736 data_time: 0.0175 memory: 14901 loss: 1.3987 loss_prob: 0.7824 loss_thr: 0.4823 loss_db: 0.1340 2022/11/02 17:52:05 - mmengine - INFO - Epoch(train) [524][20/63] lr: 1.2915e-03 eta: 6:59:48 time: 0.5903 data_time: 0.0090 memory: 14901 loss: 1.3299 loss_prob: 0.7331 loss_thr: 0.4708 loss_db: 0.1260 2022/11/02 17:52:08 - mmengine - INFO - Epoch(train) [524][25/63] lr: 1.2915e-03 eta: 6:59:48 time: 0.5851 data_time: 0.0108 memory: 14901 loss: 1.2151 loss_prob: 0.6517 loss_thr: 0.4519 loss_db: 0.1114 2022/11/02 17:52:11 - mmengine - INFO - Epoch(train) [524][30/63] lr: 1.2915e-03 eta: 6:59:43 time: 0.6323 data_time: 0.0519 memory: 14901 loss: 1.2791 loss_prob: 0.6831 loss_thr: 0.4789 loss_db: 0.1171 2022/11/02 17:52:14 - mmengine - INFO - Epoch(train) [524][35/63] lr: 1.2915e-03 eta: 6:59:43 time: 0.6156 data_time: 0.0555 memory: 14901 loss: 1.3498 loss_prob: 0.7261 loss_thr: 0.5014 loss_db: 0.1223 2022/11/02 17:52:17 - mmengine - INFO - Epoch(train) [524][40/63] lr: 1.2915e-03 eta: 6:59:37 time: 0.5963 data_time: 0.0159 memory: 14901 loss: 1.3393 loss_prob: 0.7262 loss_thr: 0.4901 loss_db: 0.1230 2022/11/02 17:52:21 - mmengine - INFO - Epoch(train) [524][45/63] lr: 1.2915e-03 eta: 6:59:37 time: 0.7158 data_time: 0.0100 memory: 14901 loss: 1.3759 loss_prob: 0.7564 loss_thr: 0.4908 loss_db: 0.1287 2022/11/02 17:52:25 - mmengine - INFO - Epoch(train) [524][50/63] lr: 1.2915e-03 eta: 6:59:33 time: 0.7309 data_time: 0.0100 memory: 14901 loss: 1.3731 loss_prob: 0.7500 loss_thr: 0.4966 loss_db: 0.1265 2022/11/02 17:52:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:52:27 - mmengine - INFO - Epoch(train) [524][55/63] lr: 1.2915e-03 eta: 6:59:33 time: 0.5735 data_time: 0.0239 memory: 14901 loss: 1.2703 loss_prob: 0.6781 loss_thr: 0.4756 loss_db: 0.1167 2022/11/02 17:52:31 - mmengine - INFO - Epoch(train) [524][60/63] lr: 1.2915e-03 eta: 6:59:27 time: 0.5866 data_time: 0.0267 memory: 14901 loss: 1.2683 loss_prob: 0.6789 loss_thr: 0.4743 loss_db: 0.1151 2022/11/02 17:52:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:52:39 - mmengine - INFO - Epoch(train) [525][5/63] lr: 1.2898e-03 eta: 6:59:27 time: 0.9491 data_time: 0.2242 memory: 14901 loss: 1.2366 loss_prob: 0.6674 loss_thr: 0.4541 loss_db: 0.1151 2022/11/02 17:52:42 - mmengine - INFO - Epoch(train) [525][10/63] lr: 1.2898e-03 eta: 6:59:21 time: 0.9317 data_time: 0.2248 memory: 14901 loss: 1.2243 loss_prob: 0.6615 loss_thr: 0.4480 loss_db: 0.1148 2022/11/02 17:52:45 - mmengine - INFO - Epoch(train) [525][15/63] lr: 1.2898e-03 eta: 6:59:21 time: 0.5869 data_time: 0.0142 memory: 14901 loss: 1.3421 loss_prob: 0.7555 loss_thr: 0.4611 loss_db: 0.1256 2022/11/02 17:52:47 - mmengine - INFO - Epoch(train) [525][20/63] lr: 1.2898e-03 eta: 6:59:15 time: 0.5806 data_time: 0.0165 memory: 14901 loss: 1.3930 loss_prob: 0.7870 loss_thr: 0.4740 loss_db: 0.1319 2022/11/02 17:52:51 - mmengine - INFO - Epoch(train) [525][25/63] lr: 1.2898e-03 eta: 6:59:15 time: 0.6054 data_time: 0.0163 memory: 14901 loss: 1.3627 loss_prob: 0.7587 loss_thr: 0.4764 loss_db: 0.1276 2022/11/02 17:52:54 - mmengine - INFO - Epoch(train) [525][30/63] lr: 1.2898e-03 eta: 6:59:11 time: 0.7023 data_time: 0.0560 memory: 14901 loss: 1.3128 loss_prob: 0.7057 loss_thr: 0.4913 loss_db: 0.1158 2022/11/02 17:52:57 - mmengine - INFO - Epoch(train) [525][35/63] lr: 1.2898e-03 eta: 6:59:11 time: 0.6425 data_time: 0.0539 memory: 14901 loss: 1.3271 loss_prob: 0.7042 loss_thr: 0.5050 loss_db: 0.1179 2022/11/02 17:53:00 - mmengine - INFO - Epoch(train) [525][40/63] lr: 1.2898e-03 eta: 6:59:04 time: 0.5523 data_time: 0.0105 memory: 14901 loss: 1.3948 loss_prob: 0.7685 loss_thr: 0.4931 loss_db: 0.1332 2022/11/02 17:53:03 - mmengine - INFO - Epoch(train) [525][45/63] lr: 1.2898e-03 eta: 6:59:04 time: 0.5635 data_time: 0.0129 memory: 14901 loss: 1.3946 loss_prob: 0.7637 loss_thr: 0.4988 loss_db: 0.1321 2022/11/02 17:53:06 - mmengine - INFO - Epoch(train) [525][50/63] lr: 1.2898e-03 eta: 6:58:59 time: 0.6272 data_time: 0.0287 memory: 14901 loss: 1.3955 loss_prob: 0.7659 loss_thr: 0.4982 loss_db: 0.1314 2022/11/02 17:53:09 - mmengine - INFO - Epoch(train) [525][55/63] lr: 1.2898e-03 eta: 6:58:59 time: 0.6262 data_time: 0.0270 memory: 14901 loss: 1.2629 loss_prob: 0.6852 loss_thr: 0.4591 loss_db: 0.1185 2022/11/02 17:53:12 - mmengine - INFO - Epoch(train) [525][60/63] lr: 1.2898e-03 eta: 6:58:53 time: 0.6072 data_time: 0.0131 memory: 14901 loss: 1.2429 loss_prob: 0.6610 loss_thr: 0.4700 loss_db: 0.1119 2022/11/02 17:53:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:53:21 - mmengine - INFO - Epoch(train) [526][5/63] lr: 1.2881e-03 eta: 6:58:53 time: 0.9369 data_time: 0.2438 memory: 14901 loss: 1.2912 loss_prob: 0.7004 loss_thr: 0.4717 loss_db: 0.1192 2022/11/02 17:53:24 - mmengine - INFO - Epoch(train) [526][10/63] lr: 1.2881e-03 eta: 6:58:49 time: 1.0172 data_time: 0.2657 memory: 14901 loss: 1.2970 loss_prob: 0.7056 loss_thr: 0.4740 loss_db: 0.1175 2022/11/02 17:53:28 - mmengine - INFO - Epoch(train) [526][15/63] lr: 1.2881e-03 eta: 6:58:49 time: 0.7084 data_time: 0.0319 memory: 14901 loss: 1.3259 loss_prob: 0.7212 loss_thr: 0.4834 loss_db: 0.1212 2022/11/02 17:53:31 - mmengine - INFO - Epoch(train) [526][20/63] lr: 1.2881e-03 eta: 6:58:44 time: 0.6907 data_time: 0.0113 memory: 14901 loss: 1.2896 loss_prob: 0.6902 loss_thr: 0.4811 loss_db: 0.1183 2022/11/02 17:53:34 - mmengine - INFO - Epoch(train) [526][25/63] lr: 1.2881e-03 eta: 6:58:44 time: 0.6259 data_time: 0.0328 memory: 14901 loss: 1.2629 loss_prob: 0.6719 loss_thr: 0.4734 loss_db: 0.1176 2022/11/02 17:53:37 - mmengine - INFO - Epoch(train) [526][30/63] lr: 1.2881e-03 eta: 6:58:38 time: 0.5542 data_time: 0.0295 memory: 14901 loss: 1.2601 loss_prob: 0.6702 loss_thr: 0.4740 loss_db: 0.1158 2022/11/02 17:53:39 - mmengine - INFO - Epoch(train) [526][35/63] lr: 1.2881e-03 eta: 6:58:38 time: 0.5288 data_time: 0.0175 memory: 14901 loss: 1.2259 loss_prob: 0.6579 loss_thr: 0.4566 loss_db: 0.1113 2022/11/02 17:53:42 - mmengine - INFO - Epoch(train) [526][40/63] lr: 1.2881e-03 eta: 6:58:31 time: 0.5158 data_time: 0.0181 memory: 14901 loss: 1.2635 loss_prob: 0.6842 loss_thr: 0.4627 loss_db: 0.1166 2022/11/02 17:53:44 - mmengine - INFO - Epoch(train) [526][45/63] lr: 1.2881e-03 eta: 6:58:31 time: 0.5259 data_time: 0.0124 memory: 14901 loss: 1.3815 loss_prob: 0.7597 loss_thr: 0.4947 loss_db: 0.1271 2022/11/02 17:53:47 - mmengine - INFO - Epoch(train) [526][50/63] lr: 1.2881e-03 eta: 6:58:24 time: 0.5430 data_time: 0.0274 memory: 14901 loss: 1.3117 loss_prob: 0.7104 loss_thr: 0.4820 loss_db: 0.1193 2022/11/02 17:53:50 - mmengine - INFO - Epoch(train) [526][55/63] lr: 1.2881e-03 eta: 6:58:24 time: 0.5852 data_time: 0.0286 memory: 14901 loss: 1.2138 loss_prob: 0.6327 loss_thr: 0.4719 loss_db: 0.1093 2022/11/02 17:53:53 - mmengine - INFO - Epoch(train) [526][60/63] lr: 1.2881e-03 eta: 6:58:18 time: 0.5559 data_time: 0.0148 memory: 14901 loss: 1.3148 loss_prob: 0.7147 loss_thr: 0.4777 loss_db: 0.1224 2022/11/02 17:53:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:54:02 - mmengine - INFO - Epoch(train) [527][5/63] lr: 1.2863e-03 eta: 6:58:18 time: 0.9917 data_time: 0.2656 memory: 14901 loss: 1.3900 loss_prob: 0.7655 loss_thr: 0.4989 loss_db: 0.1256 2022/11/02 17:54:06 - mmengine - INFO - Epoch(train) [527][10/63] lr: 1.2863e-03 eta: 6:58:15 time: 1.1624 data_time: 0.2670 memory: 14901 loss: 1.6807 loss_prob: 0.9810 loss_thr: 0.5279 loss_db: 0.1718 2022/11/02 17:54:10 - mmengine - INFO - Epoch(train) [527][15/63] lr: 1.2863e-03 eta: 6:58:15 time: 0.8210 data_time: 0.0118 memory: 14901 loss: 1.8306 loss_prob: 1.1097 loss_thr: 0.5285 loss_db: 0.1924 2022/11/02 17:54:14 - mmengine - INFO - Epoch(train) [527][20/63] lr: 1.2863e-03 eta: 6:58:12 time: 0.7998 data_time: 0.0108 memory: 14901 loss: 1.5855 loss_prob: 0.9202 loss_thr: 0.5174 loss_db: 0.1479 2022/11/02 17:54:17 - mmengine - INFO - Epoch(train) [527][25/63] lr: 1.2863e-03 eta: 6:58:12 time: 0.6712 data_time: 0.0373 memory: 14901 loss: 1.7216 loss_prob: 1.0206 loss_thr: 0.5486 loss_db: 0.1525 2022/11/02 17:54:19 - mmengine - INFO - Epoch(train) [527][30/63] lr: 1.2863e-03 eta: 6:58:06 time: 0.5670 data_time: 0.0424 memory: 14901 loss: 1.6762 loss_prob: 0.9912 loss_thr: 0.5324 loss_db: 0.1526 2022/11/02 17:54:22 - mmengine - INFO - Epoch(train) [527][35/63] lr: 1.2863e-03 eta: 6:58:06 time: 0.5356 data_time: 0.0138 memory: 14901 loss: 1.5719 loss_prob: 0.8947 loss_thr: 0.5293 loss_db: 0.1480 2022/11/02 17:54:25 - mmengine - INFO - Epoch(train) [527][40/63] lr: 1.2863e-03 eta: 6:57:59 time: 0.5177 data_time: 0.0071 memory: 14901 loss: 1.5951 loss_prob: 0.9056 loss_thr: 0.5399 loss_db: 0.1496 2022/11/02 17:54:28 - mmengine - INFO - Epoch(train) [527][45/63] lr: 1.2863e-03 eta: 6:57:59 time: 0.5532 data_time: 0.0102 memory: 14901 loss: 1.3879 loss_prob: 0.7512 loss_thr: 0.5088 loss_db: 0.1279 2022/11/02 17:54:31 - mmengine - INFO - Epoch(train) [527][50/63] lr: 1.2863e-03 eta: 6:57:53 time: 0.6134 data_time: 0.0305 memory: 14901 loss: 1.3543 loss_prob: 0.7358 loss_thr: 0.4923 loss_db: 0.1262 2022/11/02 17:54:34 - mmengine - INFO - Epoch(train) [527][55/63] lr: 1.2863e-03 eta: 6:57:53 time: 0.5965 data_time: 0.0296 memory: 14901 loss: 1.4036 loss_prob: 0.7703 loss_thr: 0.5025 loss_db: 0.1308 2022/11/02 17:54:36 - mmengine - INFO - Epoch(train) [527][60/63] lr: 1.2863e-03 eta: 6:57:46 time: 0.5160 data_time: 0.0105 memory: 14901 loss: 1.6701 loss_prob: 0.9779 loss_thr: 0.5394 loss_db: 0.1528 2022/11/02 17:54:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:54:44 - mmengine - INFO - Epoch(train) [528][5/63] lr: 1.2846e-03 eta: 6:57:46 time: 0.9199 data_time: 0.2409 memory: 14901 loss: 1.3928 loss_prob: 0.7606 loss_thr: 0.5027 loss_db: 0.1295 2022/11/02 17:54:47 - mmengine - INFO - Epoch(train) [528][10/63] lr: 1.2846e-03 eta: 6:57:41 time: 0.9848 data_time: 0.2450 memory: 14901 loss: 1.5649 loss_prob: 0.8800 loss_thr: 0.5326 loss_db: 0.1523 2022/11/02 17:54:51 - mmengine - INFO - Epoch(train) [528][15/63] lr: 1.2846e-03 eta: 6:57:41 time: 0.6534 data_time: 0.0162 memory: 14901 loss: 1.6642 loss_prob: 0.9658 loss_thr: 0.5319 loss_db: 0.1665 2022/11/02 17:54:53 - mmengine - INFO - Epoch(train) [528][20/63] lr: 1.2846e-03 eta: 6:57:36 time: 0.6124 data_time: 0.0084 memory: 14901 loss: 1.4683 loss_prob: 0.8323 loss_thr: 0.4975 loss_db: 0.1385 2022/11/02 17:54:56 - mmengine - INFO - Epoch(train) [528][25/63] lr: 1.2846e-03 eta: 6:57:36 time: 0.5569 data_time: 0.0262 memory: 14901 loss: 1.3839 loss_prob: 0.7513 loss_thr: 0.5096 loss_db: 0.1230 2022/11/02 17:54:59 - mmengine - INFO - Epoch(train) [528][30/63] lr: 1.2846e-03 eta: 6:57:29 time: 0.5564 data_time: 0.0328 memory: 14901 loss: 1.4152 loss_prob: 0.7662 loss_thr: 0.5206 loss_db: 0.1285 2022/11/02 17:55:02 - mmengine - INFO - Epoch(train) [528][35/63] lr: 1.2846e-03 eta: 6:57:29 time: 0.5324 data_time: 0.0232 memory: 14901 loss: 1.3717 loss_prob: 0.7517 loss_thr: 0.4916 loss_db: 0.1284 2022/11/02 17:55:04 - mmengine - INFO - Epoch(train) [528][40/63] lr: 1.2846e-03 eta: 6:57:23 time: 0.5211 data_time: 0.0187 memory: 14901 loss: 1.4139 loss_prob: 0.7875 loss_thr: 0.4919 loss_db: 0.1345 2022/11/02 17:55:07 - mmengine - INFO - Epoch(train) [528][45/63] lr: 1.2846e-03 eta: 6:57:23 time: 0.5832 data_time: 0.0125 memory: 14901 loss: 1.4177 loss_prob: 0.7812 loss_thr: 0.5055 loss_db: 0.1310 2022/11/02 17:55:10 - mmengine - INFO - Epoch(train) [528][50/63] lr: 1.2846e-03 eta: 6:57:17 time: 0.6111 data_time: 0.0231 memory: 14901 loss: 1.2412 loss_prob: 0.6697 loss_thr: 0.4599 loss_db: 0.1117 2022/11/02 17:55:13 - mmengine - INFO - Epoch(train) [528][55/63] lr: 1.2846e-03 eta: 6:57:17 time: 0.5789 data_time: 0.0244 memory: 14901 loss: 1.2567 loss_prob: 0.6728 loss_thr: 0.4697 loss_db: 0.1142 2022/11/02 17:55:16 - mmengine - INFO - Epoch(train) [528][60/63] lr: 1.2846e-03 eta: 6:57:10 time: 0.5416 data_time: 0.0181 memory: 14901 loss: 1.3534 loss_prob: 0.7337 loss_thr: 0.4935 loss_db: 0.1262 2022/11/02 17:55:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:55:26 - mmengine - INFO - Epoch(train) [529][5/63] lr: 1.2829e-03 eta: 6:57:10 time: 1.0907 data_time: 0.2497 memory: 14901 loss: 1.3286 loss_prob: 0.7145 loss_thr: 0.4935 loss_db: 0.1206 2022/11/02 17:55:29 - mmengine - INFO - Epoch(train) [529][10/63] lr: 1.2829e-03 eta: 6:57:07 time: 1.1054 data_time: 0.2681 memory: 14901 loss: 1.2634 loss_prob: 0.6743 loss_thr: 0.4730 loss_db: 0.1161 2022/11/02 17:55:31 - mmengine - INFO - Epoch(train) [529][15/63] lr: 1.2829e-03 eta: 6:57:07 time: 0.5642 data_time: 0.0279 memory: 14901 loss: 1.2861 loss_prob: 0.6913 loss_thr: 0.4752 loss_db: 0.1196 2022/11/02 17:55:34 - mmengine - INFO - Epoch(train) [529][20/63] lr: 1.2829e-03 eta: 6:57:00 time: 0.5335 data_time: 0.0103 memory: 14901 loss: 1.3395 loss_prob: 0.7238 loss_thr: 0.4909 loss_db: 0.1247 2022/11/02 17:55:37 - mmengine - INFO - Epoch(train) [529][25/63] lr: 1.2829e-03 eta: 6:57:00 time: 0.5354 data_time: 0.0158 memory: 14901 loss: 1.2815 loss_prob: 0.6958 loss_thr: 0.4667 loss_db: 0.1190 2022/11/02 17:55:39 - mmengine - INFO - Epoch(train) [529][30/63] lr: 1.2829e-03 eta: 6:56:54 time: 0.5457 data_time: 0.0310 memory: 14901 loss: 1.3075 loss_prob: 0.7199 loss_thr: 0.4669 loss_db: 0.1207 2022/11/02 17:55:42 - mmengine - INFO - Epoch(train) [529][35/63] lr: 1.2829e-03 eta: 6:56:54 time: 0.5423 data_time: 0.0409 memory: 14901 loss: 1.3697 loss_prob: 0.7466 loss_thr: 0.4976 loss_db: 0.1255 2022/11/02 17:55:45 - mmengine - INFO - Epoch(train) [529][40/63] lr: 1.2829e-03 eta: 6:56:47 time: 0.5339 data_time: 0.0288 memory: 14901 loss: 1.3160 loss_prob: 0.7176 loss_thr: 0.4764 loss_db: 0.1220 2022/11/02 17:55:48 - mmengine - INFO - Epoch(train) [529][45/63] lr: 1.2829e-03 eta: 6:56:47 time: 0.5523 data_time: 0.0138 memory: 14901 loss: 1.2575 loss_prob: 0.6899 loss_thr: 0.4505 loss_db: 0.1171 2022/11/02 17:55:50 - mmengine - INFO - Epoch(train) [529][50/63] lr: 1.2829e-03 eta: 6:56:41 time: 0.5722 data_time: 0.0227 memory: 14901 loss: 1.5548 loss_prob: 0.9287 loss_thr: 0.4859 loss_db: 0.1401 2022/11/02 17:55:54 - mmengine - INFO - Epoch(train) [529][55/63] lr: 1.2829e-03 eta: 6:56:41 time: 0.5973 data_time: 0.0292 memory: 14901 loss: 1.6658 loss_prob: 0.9997 loss_thr: 0.5129 loss_db: 0.1533 2022/11/02 17:55:56 - mmengine - INFO - Epoch(train) [529][60/63] lr: 1.2829e-03 eta: 6:56:35 time: 0.5749 data_time: 0.0198 memory: 14901 loss: 1.5262 loss_prob: 0.8826 loss_thr: 0.5027 loss_db: 0.1408 2022/11/02 17:55:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:56:04 - mmengine - INFO - Epoch(train) [530][5/63] lr: 1.2812e-03 eta: 6:56:35 time: 0.8837 data_time: 0.2548 memory: 14901 loss: 1.5336 loss_prob: 0.8928 loss_thr: 0.5021 loss_db: 0.1388 2022/11/02 17:56:07 - mmengine - INFO - Epoch(train) [530][10/63] lr: 1.2812e-03 eta: 6:56:30 time: 0.9555 data_time: 0.2622 memory: 14901 loss: 1.3986 loss_prob: 0.7616 loss_thr: 0.5093 loss_db: 0.1276 2022/11/02 17:56:10 - mmengine - INFO - Epoch(train) [530][15/63] lr: 1.2812e-03 eta: 6:56:30 time: 0.6531 data_time: 0.0178 memory: 14901 loss: 1.3654 loss_prob: 0.7417 loss_thr: 0.4989 loss_db: 0.1248 2022/11/02 17:56:13 - mmengine - INFO - Epoch(train) [530][20/63] lr: 1.2812e-03 eta: 6:56:24 time: 0.6196 data_time: 0.0093 memory: 14901 loss: 1.3317 loss_prob: 0.7245 loss_thr: 0.4852 loss_db: 0.1220 2022/11/02 17:56:16 - mmengine - INFO - Epoch(train) [530][25/63] lr: 1.2812e-03 eta: 6:56:24 time: 0.5544 data_time: 0.0303 memory: 14901 loss: 1.2532 loss_prob: 0.6650 loss_thr: 0.4714 loss_db: 0.1167 2022/11/02 17:56:19 - mmengine - INFO - Epoch(train) [530][30/63] lr: 1.2812e-03 eta: 6:56:18 time: 0.5629 data_time: 0.0419 memory: 14901 loss: 1.2215 loss_prob: 0.6485 loss_thr: 0.4596 loss_db: 0.1134 2022/11/02 17:56:22 - mmengine - INFO - Epoch(train) [530][35/63] lr: 1.2812e-03 eta: 6:56:18 time: 0.5497 data_time: 0.0238 memory: 14901 loss: 1.1945 loss_prob: 0.6355 loss_thr: 0.4499 loss_db: 0.1091 2022/11/02 17:56:25 - mmengine - INFO - Epoch(train) [530][40/63] lr: 1.2812e-03 eta: 6:56:12 time: 0.6208 data_time: 0.0173 memory: 14901 loss: 1.2822 loss_prob: 0.6896 loss_thr: 0.4721 loss_db: 0.1205 2022/11/02 17:56:28 - mmengine - INFO - Epoch(train) [530][45/63] lr: 1.2812e-03 eta: 6:56:12 time: 0.6505 data_time: 0.0154 memory: 14901 loss: 1.3118 loss_prob: 0.7124 loss_thr: 0.4770 loss_db: 0.1223 2022/11/02 17:56:31 - mmengine - INFO - Epoch(train) [530][50/63] lr: 1.2812e-03 eta: 6:56:06 time: 0.5632 data_time: 0.0204 memory: 14901 loss: 1.3461 loss_prob: 0.7346 loss_thr: 0.4884 loss_db: 0.1231 2022/11/02 17:56:33 - mmengine - INFO - Epoch(train) [530][55/63] lr: 1.2812e-03 eta: 6:56:06 time: 0.5372 data_time: 0.0196 memory: 14901 loss: 1.3322 loss_prob: 0.7170 loss_thr: 0.4932 loss_db: 0.1220 2022/11/02 17:56:36 - mmengine - INFO - Epoch(train) [530][60/63] lr: 1.2812e-03 eta: 6:56:00 time: 0.5551 data_time: 0.0153 memory: 14901 loss: 1.1921 loss_prob: 0.6226 loss_thr: 0.4605 loss_db: 0.1090 2022/11/02 17:56:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:56:45 - mmengine - INFO - Epoch(train) [531][5/63] lr: 1.2795e-03 eta: 6:56:00 time: 1.0248 data_time: 0.2388 memory: 14901 loss: 1.1426 loss_prob: 0.5912 loss_thr: 0.4510 loss_db: 0.1003 2022/11/02 17:56:48 - mmengine - INFO - Epoch(train) [531][10/63] lr: 1.2795e-03 eta: 6:55:55 time: 1.0427 data_time: 0.2427 memory: 14901 loss: 1.2053 loss_prob: 0.6518 loss_thr: 0.4452 loss_db: 0.1084 2022/11/02 17:56:51 - mmengine - INFO - Epoch(train) [531][15/63] lr: 1.2795e-03 eta: 6:55:55 time: 0.5997 data_time: 0.0141 memory: 14901 loss: 1.2537 loss_prob: 0.6741 loss_thr: 0.4673 loss_db: 0.1123 2022/11/02 17:56:54 - mmengine - INFO - Epoch(train) [531][20/63] lr: 1.2795e-03 eta: 6:55:50 time: 0.6086 data_time: 0.0078 memory: 14901 loss: 1.1890 loss_prob: 0.6266 loss_thr: 0.4538 loss_db: 0.1086 2022/11/02 17:56:57 - mmengine - INFO - Epoch(train) [531][25/63] lr: 1.2795e-03 eta: 6:55:50 time: 0.6079 data_time: 0.0208 memory: 14901 loss: 1.1224 loss_prob: 0.5946 loss_thr: 0.4265 loss_db: 0.1012 2022/11/02 17:57:01 - mmengine - INFO - Epoch(train) [531][30/63] lr: 1.2795e-03 eta: 6:55:44 time: 0.6353 data_time: 0.0398 memory: 14901 loss: 1.1862 loss_prob: 0.6256 loss_thr: 0.4543 loss_db: 0.1064 2022/11/02 17:57:03 - mmengine - INFO - Epoch(train) [531][35/63] lr: 1.2795e-03 eta: 6:55:44 time: 0.5953 data_time: 0.0296 memory: 14901 loss: 1.2184 loss_prob: 0.6447 loss_thr: 0.4631 loss_db: 0.1105 2022/11/02 17:57:06 - mmengine - INFO - Epoch(train) [531][40/63] lr: 1.2795e-03 eta: 6:55:38 time: 0.5352 data_time: 0.0137 memory: 14901 loss: 1.2156 loss_prob: 0.6476 loss_thr: 0.4601 loss_db: 0.1080 2022/11/02 17:57:10 - mmengine - INFO - Epoch(train) [531][45/63] lr: 1.2795e-03 eta: 6:55:38 time: 0.6140 data_time: 0.0087 memory: 14901 loss: 1.1770 loss_prob: 0.6246 loss_thr: 0.4457 loss_db: 0.1068 2022/11/02 17:57:13 - mmengine - INFO - Epoch(train) [531][50/63] lr: 1.2795e-03 eta: 6:55:33 time: 0.6802 data_time: 0.0262 memory: 14901 loss: 1.1607 loss_prob: 0.6177 loss_thr: 0.4339 loss_db: 0.1091 2022/11/02 17:57:16 - mmengine - INFO - Epoch(train) [531][55/63] lr: 1.2795e-03 eta: 6:55:33 time: 0.6411 data_time: 0.0289 memory: 14901 loss: 1.3120 loss_prob: 0.7042 loss_thr: 0.4863 loss_db: 0.1216 2022/11/02 17:57:18 - mmengine - INFO - Epoch(train) [531][60/63] lr: 1.2795e-03 eta: 6:55:27 time: 0.5638 data_time: 0.0111 memory: 14901 loss: 1.4434 loss_prob: 0.7948 loss_thr: 0.5167 loss_db: 0.1319 2022/11/02 17:57:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:57:28 - mmengine - INFO - Epoch(train) [532][5/63] lr: 1.2777e-03 eta: 6:55:27 time: 1.0092 data_time: 0.2355 memory: 14901 loss: 1.2716 loss_prob: 0.6796 loss_thr: 0.4748 loss_db: 0.1173 2022/11/02 17:57:31 - mmengine - INFO - Epoch(train) [532][10/63] lr: 1.2777e-03 eta: 6:55:23 time: 1.0660 data_time: 0.2425 memory: 14901 loss: 1.2896 loss_prob: 0.6960 loss_thr: 0.4737 loss_db: 0.1200 2022/11/02 17:57:34 - mmengine - INFO - Epoch(train) [532][15/63] lr: 1.2777e-03 eta: 6:55:23 time: 0.5914 data_time: 0.0162 memory: 14901 loss: 1.3494 loss_prob: 0.7457 loss_thr: 0.4783 loss_db: 0.1253 2022/11/02 17:57:36 - mmengine - INFO - Epoch(train) [532][20/63] lr: 1.2777e-03 eta: 6:55:17 time: 0.5714 data_time: 0.0103 memory: 14901 loss: 1.2383 loss_prob: 0.6640 loss_thr: 0.4627 loss_db: 0.1115 2022/11/02 17:57:39 - mmengine - INFO - Epoch(train) [532][25/63] lr: 1.2777e-03 eta: 6:55:17 time: 0.5554 data_time: 0.0187 memory: 14901 loss: 1.2188 loss_prob: 0.6443 loss_thr: 0.4635 loss_db: 0.1110 2022/11/02 17:57:42 - mmengine - INFO - Epoch(train) [532][30/63] lr: 1.2777e-03 eta: 6:55:11 time: 0.5881 data_time: 0.0432 memory: 14901 loss: 1.2685 loss_prob: 0.6781 loss_thr: 0.4735 loss_db: 0.1170 2022/11/02 17:57:45 - mmengine - INFO - Epoch(train) [532][35/63] lr: 1.2777e-03 eta: 6:55:11 time: 0.5847 data_time: 0.0334 memory: 14901 loss: 1.2342 loss_prob: 0.6564 loss_thr: 0.4647 loss_db: 0.1131 2022/11/02 17:57:48 - mmengine - INFO - Epoch(train) [532][40/63] lr: 1.2777e-03 eta: 6:55:04 time: 0.5560 data_time: 0.0080 memory: 14901 loss: 1.2540 loss_prob: 0.6708 loss_thr: 0.4669 loss_db: 0.1163 2022/11/02 17:57:50 - mmengine - INFO - Epoch(train) [532][45/63] lr: 1.2777e-03 eta: 6:55:04 time: 0.5198 data_time: 0.0125 memory: 14901 loss: 1.2281 loss_prob: 0.6584 loss_thr: 0.4538 loss_db: 0.1160 2022/11/02 17:57:53 - mmengine - INFO - Epoch(train) [532][50/63] lr: 1.2777e-03 eta: 6:54:57 time: 0.5176 data_time: 0.0226 memory: 14901 loss: 1.2118 loss_prob: 0.6602 loss_thr: 0.4376 loss_db: 0.1141 2022/11/02 17:57:56 - mmengine - INFO - Epoch(train) [532][55/63] lr: 1.2777e-03 eta: 6:54:57 time: 0.5411 data_time: 0.0242 memory: 14901 loss: 1.2175 loss_prob: 0.6612 loss_thr: 0.4453 loss_db: 0.1110 2022/11/02 17:57:58 - mmengine - INFO - Epoch(train) [532][60/63] lr: 1.2777e-03 eta: 6:54:51 time: 0.5242 data_time: 0.0156 memory: 14901 loss: 1.2076 loss_prob: 0.6514 loss_thr: 0.4473 loss_db: 0.1089 2022/11/02 17:58:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:58:06 - mmengine - INFO - Epoch(train) [533][5/63] lr: 1.2760e-03 eta: 6:54:51 time: 0.9047 data_time: 0.2927 memory: 14901 loss: 1.2112 loss_prob: 0.6471 loss_thr: 0.4574 loss_db: 0.1067 2022/11/02 17:58:09 - mmengine - INFO - Epoch(train) [533][10/63] lr: 1.2760e-03 eta: 6:54:45 time: 0.9171 data_time: 0.2920 memory: 14901 loss: 1.2072 loss_prob: 0.6463 loss_thr: 0.4511 loss_db: 0.1098 2022/11/02 17:58:11 - mmengine - INFO - Epoch(train) [533][15/63] lr: 1.2760e-03 eta: 6:54:45 time: 0.5316 data_time: 0.0130 memory: 14901 loss: 1.2379 loss_prob: 0.6640 loss_thr: 0.4610 loss_db: 0.1129 2022/11/02 17:58:14 - mmengine - INFO - Epoch(train) [533][20/63] lr: 1.2760e-03 eta: 6:54:38 time: 0.5378 data_time: 0.0127 memory: 14901 loss: 1.2206 loss_prob: 0.6545 loss_thr: 0.4564 loss_db: 0.1098 2022/11/02 17:58:17 - mmengine - INFO - Epoch(train) [533][25/63] lr: 1.2760e-03 eta: 6:54:38 time: 0.5572 data_time: 0.0329 memory: 14901 loss: 1.2567 loss_prob: 0.6767 loss_thr: 0.4649 loss_db: 0.1151 2022/11/02 17:58:20 - mmengine - INFO - Epoch(train) [533][30/63] lr: 1.2760e-03 eta: 6:54:32 time: 0.5534 data_time: 0.0354 memory: 14901 loss: 1.3343 loss_prob: 0.7262 loss_thr: 0.4875 loss_db: 0.1206 2022/11/02 17:58:23 - mmengine - INFO - Epoch(train) [533][35/63] lr: 1.2760e-03 eta: 6:54:32 time: 0.5666 data_time: 0.0119 memory: 14901 loss: 1.2590 loss_prob: 0.6823 loss_thr: 0.4612 loss_db: 0.1155 2022/11/02 17:58:26 - mmengine - INFO - Epoch(train) [533][40/63] lr: 1.2760e-03 eta: 6:54:26 time: 0.5854 data_time: 0.0119 memory: 14901 loss: 1.2072 loss_prob: 0.6403 loss_thr: 0.4559 loss_db: 0.1110 2022/11/02 17:58:28 - mmengine - INFO - Epoch(train) [533][45/63] lr: 1.2760e-03 eta: 6:54:26 time: 0.5780 data_time: 0.0096 memory: 14901 loss: 1.2046 loss_prob: 0.6295 loss_thr: 0.4683 loss_db: 0.1068 2022/11/02 17:58:31 - mmengine - INFO - Epoch(train) [533][50/63] lr: 1.2760e-03 eta: 6:54:20 time: 0.5667 data_time: 0.0246 memory: 14901 loss: 1.2787 loss_prob: 0.6927 loss_thr: 0.4696 loss_db: 0.1163 2022/11/02 17:58:34 - mmengine - INFO - Epoch(train) [533][55/63] lr: 1.2760e-03 eta: 6:54:20 time: 0.5373 data_time: 0.0293 memory: 14901 loss: 1.2795 loss_prob: 0.7035 loss_thr: 0.4591 loss_db: 0.1169 2022/11/02 17:58:37 - mmengine - INFO - Epoch(train) [533][60/63] lr: 1.2760e-03 eta: 6:54:13 time: 0.5400 data_time: 0.0140 memory: 14901 loss: 1.2797 loss_prob: 0.6941 loss_thr: 0.4715 loss_db: 0.1140 2022/11/02 17:58:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:58:47 - mmengine - INFO - Epoch(train) [534][5/63] lr: 1.2743e-03 eta: 6:54:13 time: 1.1366 data_time: 0.2634 memory: 14901 loss: 1.2233 loss_prob: 0.6587 loss_thr: 0.4517 loss_db: 0.1130 2022/11/02 17:58:50 - mmengine - INFO - Epoch(train) [534][10/63] lr: 1.2743e-03 eta: 6:54:10 time: 1.1775 data_time: 0.2632 memory: 14901 loss: 1.2109 loss_prob: 0.6468 loss_thr: 0.4547 loss_db: 0.1094 2022/11/02 17:58:54 - mmengine - INFO - Epoch(train) [534][15/63] lr: 1.2743e-03 eta: 6:54:10 time: 0.6927 data_time: 0.0159 memory: 14901 loss: 1.2659 loss_prob: 0.6787 loss_thr: 0.4721 loss_db: 0.1151 2022/11/02 17:58:57 - mmengine - INFO - Epoch(train) [534][20/63] lr: 1.2743e-03 eta: 6:54:05 time: 0.6526 data_time: 0.0133 memory: 14901 loss: 1.3091 loss_prob: 0.7116 loss_thr: 0.4768 loss_db: 0.1207 2022/11/02 17:59:01 - mmengine - INFO - Epoch(train) [534][25/63] lr: 1.2743e-03 eta: 6:54:05 time: 0.6922 data_time: 0.0382 memory: 14901 loss: 1.3881 loss_prob: 0.7681 loss_thr: 0.4931 loss_db: 0.1269 2022/11/02 17:59:03 - mmengine - INFO - Epoch(train) [534][30/63] lr: 1.2743e-03 eta: 6:54:00 time: 0.6474 data_time: 0.0435 memory: 14901 loss: 1.3777 loss_prob: 0.7600 loss_thr: 0.4896 loss_db: 0.1281 2022/11/02 17:59:06 - mmengine - INFO - Epoch(train) [534][35/63] lr: 1.2743e-03 eta: 6:54:00 time: 0.5656 data_time: 0.0128 memory: 14901 loss: 1.2824 loss_prob: 0.6902 loss_thr: 0.4735 loss_db: 0.1187 2022/11/02 17:59:09 - mmengine - INFO - Epoch(train) [534][40/63] lr: 1.2743e-03 eta: 6:53:54 time: 0.5937 data_time: 0.0100 memory: 14901 loss: 1.1942 loss_prob: 0.6307 loss_thr: 0.4574 loss_db: 0.1060 2022/11/02 17:59:12 - mmengine - INFO - Epoch(train) [534][45/63] lr: 1.2743e-03 eta: 6:53:54 time: 0.5590 data_time: 0.0118 memory: 14901 loss: 1.3169 loss_prob: 0.7050 loss_thr: 0.4912 loss_db: 0.1206 2022/11/02 17:59:15 - mmengine - INFO - Epoch(train) [534][50/63] lr: 1.2743e-03 eta: 6:53:49 time: 0.6118 data_time: 0.0208 memory: 14901 loss: 1.3116 loss_prob: 0.7012 loss_thr: 0.4884 loss_db: 0.1220 2022/11/02 17:59:19 - mmengine - INFO - Epoch(train) [534][55/63] lr: 1.2743e-03 eta: 6:53:49 time: 0.6930 data_time: 0.0234 memory: 14901 loss: 1.2593 loss_prob: 0.6709 loss_thr: 0.4751 loss_db: 0.1132 2022/11/02 17:59:22 - mmengine - INFO - Epoch(train) [534][60/63] lr: 1.2743e-03 eta: 6:53:43 time: 0.6419 data_time: 0.0139 memory: 14901 loss: 1.3497 loss_prob: 0.7252 loss_thr: 0.5015 loss_db: 0.1229 2022/11/02 17:59:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 17:59:29 - mmengine - INFO - Epoch(train) [535][5/63] lr: 1.2726e-03 eta: 6:53:43 time: 0.8496 data_time: 0.1966 memory: 14901 loss: 1.2032 loss_prob: 0.6368 loss_thr: 0.4566 loss_db: 0.1098 2022/11/02 17:59:32 - mmengine - INFO - Epoch(train) [535][10/63] lr: 1.2726e-03 eta: 6:53:37 time: 0.8981 data_time: 0.2021 memory: 14901 loss: 1.1855 loss_prob: 0.6387 loss_thr: 0.4382 loss_db: 0.1086 2022/11/02 17:59:36 - mmengine - INFO - Epoch(train) [535][15/63] lr: 1.2726e-03 eta: 6:53:37 time: 0.6350 data_time: 0.0188 memory: 14901 loss: 1.2689 loss_prob: 0.6764 loss_thr: 0.4789 loss_db: 0.1136 2022/11/02 17:59:38 - mmengine - INFO - Epoch(train) [535][20/63] lr: 1.2726e-03 eta: 6:53:32 time: 0.6182 data_time: 0.0122 memory: 14901 loss: 1.3704 loss_prob: 0.7318 loss_thr: 0.5120 loss_db: 0.1266 2022/11/02 17:59:41 - mmengine - INFO - Epoch(train) [535][25/63] lr: 1.2726e-03 eta: 6:53:32 time: 0.5187 data_time: 0.0148 memory: 14901 loss: 1.3538 loss_prob: 0.7238 loss_thr: 0.5043 loss_db: 0.1257 2022/11/02 17:59:44 - mmengine - INFO - Epoch(train) [535][30/63] lr: 1.2726e-03 eta: 6:53:25 time: 0.5468 data_time: 0.0377 memory: 14901 loss: 1.3462 loss_prob: 0.7291 loss_thr: 0.4972 loss_db: 0.1199 2022/11/02 17:59:46 - mmengine - INFO - Epoch(train) [535][35/63] lr: 1.2726e-03 eta: 6:53:25 time: 0.5623 data_time: 0.0323 memory: 14901 loss: 1.3263 loss_prob: 0.7208 loss_thr: 0.4874 loss_db: 0.1180 2022/11/02 17:59:49 - mmengine - INFO - Epoch(train) [535][40/63] lr: 1.2726e-03 eta: 6:53:19 time: 0.5598 data_time: 0.0120 memory: 14901 loss: 1.2576 loss_prob: 0.6738 loss_thr: 0.4680 loss_db: 0.1158 2022/11/02 17:59:53 - mmengine - INFO - Epoch(train) [535][45/63] lr: 1.2726e-03 eta: 6:53:19 time: 0.6650 data_time: 0.0137 memory: 14901 loss: 1.2722 loss_prob: 0.6815 loss_thr: 0.4728 loss_db: 0.1179 2022/11/02 17:59:57 - mmengine - INFO - Epoch(train) [535][50/63] lr: 1.2726e-03 eta: 6:53:14 time: 0.7049 data_time: 0.0187 memory: 14901 loss: 1.2578 loss_prob: 0.6631 loss_thr: 0.4787 loss_db: 0.1160 2022/11/02 18:00:00 - mmengine - INFO - Epoch(train) [535][55/63] lr: 1.2726e-03 eta: 6:53:14 time: 0.6616 data_time: 0.0279 memory: 14901 loss: 1.2205 loss_prob: 0.6549 loss_thr: 0.4504 loss_db: 0.1152 2022/11/02 18:00:02 - mmengine - INFO - Epoch(train) [535][60/63] lr: 1.2726e-03 eta: 6:53:08 time: 0.5687 data_time: 0.0223 memory: 14901 loss: 1.2259 loss_prob: 0.6617 loss_thr: 0.4498 loss_db: 0.1143 2022/11/02 18:00:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:00:11 - mmengine - INFO - Epoch(train) [536][5/63] lr: 1.2709e-03 eta: 6:53:08 time: 1.0044 data_time: 0.3409 memory: 14901 loss: 1.6143 loss_prob: 0.9655 loss_thr: 0.4861 loss_db: 0.1628 2022/11/02 18:00:15 - mmengine - INFO - Epoch(train) [536][10/63] lr: 1.2709e-03 eta: 6:53:05 time: 1.1459 data_time: 0.3426 memory: 14901 loss: 1.8719 loss_prob: 1.1463 loss_thr: 0.5527 loss_db: 0.1729 2022/11/02 18:00:19 - mmengine - INFO - Epoch(train) [536][15/63] lr: 1.2709e-03 eta: 6:53:05 time: 0.7779 data_time: 0.0110 memory: 14901 loss: 1.8823 loss_prob: 1.1486 loss_thr: 0.5683 loss_db: 0.1654 2022/11/02 18:00:22 - mmengine - INFO - Epoch(train) [536][20/63] lr: 1.2709e-03 eta: 6:53:00 time: 0.6497 data_time: 0.0101 memory: 14901 loss: 1.8054 loss_prob: 1.0707 loss_thr: 0.5657 loss_db: 0.1689 2022/11/02 18:00:25 - mmengine - INFO - Epoch(train) [536][25/63] lr: 1.2709e-03 eta: 6:53:00 time: 0.5545 data_time: 0.0204 memory: 14901 loss: 1.8643 loss_prob: 1.1036 loss_thr: 0.5743 loss_db: 0.1864 2022/11/02 18:00:27 - mmengine - INFO - Epoch(train) [536][30/63] lr: 1.2709e-03 eta: 6:52:54 time: 0.5793 data_time: 0.0379 memory: 14901 loss: 1.8935 loss_prob: 1.1273 loss_thr: 0.5678 loss_db: 0.1984 2022/11/02 18:00:31 - mmengine - INFO - Epoch(train) [536][35/63] lr: 1.2709e-03 eta: 6:52:54 time: 0.6404 data_time: 0.0309 memory: 14901 loss: 1.9319 loss_prob: 1.1503 loss_thr: 0.5911 loss_db: 0.1905 2022/11/02 18:00:34 - mmengine - INFO - Epoch(train) [536][40/63] lr: 1.2709e-03 eta: 6:52:49 time: 0.6625 data_time: 0.0173 memory: 14901 loss: 1.8060 loss_prob: 1.0641 loss_thr: 0.5681 loss_db: 0.1738 2022/11/02 18:00:37 - mmengine - INFO - Epoch(train) [536][45/63] lr: 1.2709e-03 eta: 6:52:49 time: 0.6363 data_time: 0.0130 memory: 14901 loss: 1.7184 loss_prob: 0.9958 loss_thr: 0.5556 loss_db: 0.1670 2022/11/02 18:00:40 - mmengine - INFO - Epoch(train) [536][50/63] lr: 1.2709e-03 eta: 6:52:43 time: 0.5977 data_time: 0.0344 memory: 14901 loss: 1.5975 loss_prob: 0.9025 loss_thr: 0.5454 loss_db: 0.1497 2022/11/02 18:00:43 - mmengine - INFO - Epoch(train) [536][55/63] lr: 1.2709e-03 eta: 6:52:43 time: 0.5692 data_time: 0.0334 memory: 14901 loss: 1.6129 loss_prob: 0.9164 loss_thr: 0.5464 loss_db: 0.1501 2022/11/02 18:00:46 - mmengine - INFO - Epoch(train) [536][60/63] lr: 1.2709e-03 eta: 6:52:37 time: 0.5775 data_time: 0.0054 memory: 14901 loss: 1.7370 loss_prob: 1.0150 loss_thr: 0.5583 loss_db: 0.1636 2022/11/02 18:00:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:00:55 - mmengine - INFO - Epoch(train) [537][5/63] lr: 1.2691e-03 eta: 6:52:37 time: 1.0576 data_time: 0.2594 memory: 14901 loss: 1.6431 loss_prob: 0.9492 loss_thr: 0.5346 loss_db: 0.1593 2022/11/02 18:00:59 - mmengine - INFO - Epoch(train) [537][10/63] lr: 1.2691e-03 eta: 6:52:34 time: 1.1454 data_time: 0.2579 memory: 14901 loss: 1.5308 loss_prob: 0.8601 loss_thr: 0.5268 loss_db: 0.1439 2022/11/02 18:01:03 - mmengine - INFO - Epoch(train) [537][15/63] lr: 1.2691e-03 eta: 6:52:34 time: 0.8185 data_time: 0.0108 memory: 14901 loss: 1.4587 loss_prob: 0.8121 loss_thr: 0.5100 loss_db: 0.1366 2022/11/02 18:01:07 - mmengine - INFO - Epoch(train) [537][20/63] lr: 1.2691e-03 eta: 6:52:31 time: 0.8448 data_time: 0.0100 memory: 14901 loss: 1.4277 loss_prob: 0.7957 loss_thr: 0.4951 loss_db: 0.1369 2022/11/02 18:01:11 - mmengine - INFO - Epoch(train) [537][25/63] lr: 1.2691e-03 eta: 6:52:31 time: 0.7353 data_time: 0.0325 memory: 14901 loss: 1.3597 loss_prob: 0.7424 loss_thr: 0.4908 loss_db: 0.1266 2022/11/02 18:01:14 - mmengine - INFO - Epoch(train) [537][30/63] lr: 1.2691e-03 eta: 6:52:27 time: 0.7233 data_time: 0.0475 memory: 14901 loss: 1.4107 loss_prob: 0.7661 loss_thr: 0.5150 loss_db: 0.1295 2022/11/02 18:01:18 - mmengine - INFO - Epoch(train) [537][35/63] lr: 1.2691e-03 eta: 6:52:27 time: 0.7120 data_time: 0.0256 memory: 14901 loss: 1.4931 loss_prob: 0.8423 loss_thr: 0.5160 loss_db: 0.1348 2022/11/02 18:01:20 - mmengine - INFO - Epoch(train) [537][40/63] lr: 1.2691e-03 eta: 6:52:21 time: 0.6044 data_time: 0.0123 memory: 14901 loss: 1.4814 loss_prob: 0.8524 loss_thr: 0.4954 loss_db: 0.1336 2022/11/02 18:01:24 - mmengine - INFO - Epoch(train) [537][45/63] lr: 1.2691e-03 eta: 6:52:21 time: 0.5872 data_time: 0.0124 memory: 14901 loss: 1.3842 loss_prob: 0.7660 loss_thr: 0.4897 loss_db: 0.1286 2022/11/02 18:01:28 - mmengine - INFO - Epoch(train) [537][50/63] lr: 1.2691e-03 eta: 6:52:17 time: 0.7208 data_time: 0.0281 memory: 14901 loss: 1.3588 loss_prob: 0.7432 loss_thr: 0.4894 loss_db: 0.1263 2022/11/02 18:01:30 - mmengine - INFO - Epoch(train) [537][55/63] lr: 1.2691e-03 eta: 6:52:17 time: 0.6807 data_time: 0.0307 memory: 14901 loss: 1.2818 loss_prob: 0.6901 loss_thr: 0.4736 loss_db: 0.1181 2022/11/02 18:01:33 - mmengine - INFO - Epoch(train) [537][60/63] lr: 1.2691e-03 eta: 6:52:10 time: 0.5337 data_time: 0.0153 memory: 14901 loss: 1.3107 loss_prob: 0.7049 loss_thr: 0.4850 loss_db: 0.1209 2022/11/02 18:01:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:01:42 - mmengine - INFO - Epoch(train) [538][5/63] lr: 1.2674e-03 eta: 6:52:10 time: 1.0324 data_time: 0.2679 memory: 14901 loss: 1.3352 loss_prob: 0.7284 loss_thr: 0.4843 loss_db: 0.1225 2022/11/02 18:01:46 - mmengine - INFO - Epoch(train) [538][10/63] lr: 1.2674e-03 eta: 6:52:07 time: 1.1324 data_time: 0.2711 memory: 14901 loss: 1.3693 loss_prob: 0.7451 loss_thr: 0.4961 loss_db: 0.1281 2022/11/02 18:01:50 - mmengine - INFO - Epoch(train) [538][15/63] lr: 1.2674e-03 eta: 6:52:07 time: 0.7164 data_time: 0.0162 memory: 14901 loss: 1.3553 loss_prob: 0.7312 loss_thr: 0.4979 loss_db: 0.1262 2022/11/02 18:01:53 - mmengine - INFO - Epoch(train) [538][20/63] lr: 1.2674e-03 eta: 6:52:02 time: 0.6725 data_time: 0.0143 memory: 14901 loss: 1.4536 loss_prob: 0.8023 loss_thr: 0.5171 loss_db: 0.1342 2022/11/02 18:01:56 - mmengine - INFO - Epoch(train) [538][25/63] lr: 1.2674e-03 eta: 6:52:02 time: 0.6648 data_time: 0.0296 memory: 14901 loss: 1.5341 loss_prob: 0.8784 loss_thr: 0.5135 loss_db: 0.1422 2022/11/02 18:01:59 - mmengine - INFO - Epoch(train) [538][30/63] lr: 1.2674e-03 eta: 6:51:56 time: 0.6250 data_time: 0.0419 memory: 14901 loss: 1.4370 loss_prob: 0.8182 loss_thr: 0.4865 loss_db: 0.1323 2022/11/02 18:02:02 - mmengine - INFO - Epoch(train) [538][35/63] lr: 1.2674e-03 eta: 6:51:56 time: 0.5325 data_time: 0.0299 memory: 14901 loss: 1.3907 loss_prob: 0.7724 loss_thr: 0.4893 loss_db: 0.1290 2022/11/02 18:02:04 - mmengine - INFO - Epoch(train) [538][40/63] lr: 1.2674e-03 eta: 6:51:50 time: 0.5605 data_time: 0.0227 memory: 14901 loss: 1.3894 loss_prob: 0.7719 loss_thr: 0.4843 loss_db: 0.1332 2022/11/02 18:02:07 - mmengine - INFO - Epoch(train) [538][45/63] lr: 1.2674e-03 eta: 6:51:50 time: 0.5553 data_time: 0.0219 memory: 14901 loss: 1.3913 loss_prob: 0.7743 loss_thr: 0.4827 loss_db: 0.1343 2022/11/02 18:02:10 - mmengine - INFO - Epoch(train) [538][50/63] lr: 1.2674e-03 eta: 6:51:44 time: 0.5598 data_time: 0.0332 memory: 14901 loss: 1.4367 loss_prob: 0.8051 loss_thr: 0.4973 loss_db: 0.1343 2022/11/02 18:02:13 - mmengine - INFO - Epoch(train) [538][55/63] lr: 1.2674e-03 eta: 6:51:44 time: 0.5912 data_time: 0.0297 memory: 14901 loss: 1.4201 loss_prob: 0.7961 loss_thr: 0.4931 loss_db: 0.1309 2022/11/02 18:02:16 - mmengine - INFO - Epoch(train) [538][60/63] lr: 1.2674e-03 eta: 6:51:38 time: 0.6121 data_time: 0.0140 memory: 14901 loss: 1.3072 loss_prob: 0.7192 loss_thr: 0.4647 loss_db: 0.1232 2022/11/02 18:02:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:02:25 - mmengine - INFO - Epoch(train) [539][5/63] lr: 1.2657e-03 eta: 6:51:38 time: 0.9742 data_time: 0.2898 memory: 14901 loss: 1.2317 loss_prob: 0.6588 loss_thr: 0.4620 loss_db: 0.1110 2022/11/02 18:02:27 - mmengine - INFO - Epoch(train) [539][10/63] lr: 1.2657e-03 eta: 6:51:33 time: 0.9761 data_time: 0.2926 memory: 14901 loss: 1.3443 loss_prob: 0.7328 loss_thr: 0.4882 loss_db: 0.1233 2022/11/02 18:02:30 - mmengine - INFO - Epoch(train) [539][15/63] lr: 1.2657e-03 eta: 6:51:33 time: 0.5831 data_time: 0.0121 memory: 14901 loss: 1.4057 loss_prob: 0.7752 loss_thr: 0.4983 loss_db: 0.1321 2022/11/02 18:02:34 - mmengine - INFO - Epoch(train) [539][20/63] lr: 1.2657e-03 eta: 6:51:28 time: 0.6532 data_time: 0.0121 memory: 14901 loss: 1.3234 loss_prob: 0.7255 loss_thr: 0.4748 loss_db: 0.1231 2022/11/02 18:02:37 - mmengine - INFO - Epoch(train) [539][25/63] lr: 1.2657e-03 eta: 6:51:28 time: 0.6239 data_time: 0.0225 memory: 14901 loss: 1.3388 loss_prob: 0.7393 loss_thr: 0.4725 loss_db: 0.1270 2022/11/02 18:02:40 - mmengine - INFO - Epoch(train) [539][30/63] lr: 1.2657e-03 eta: 6:51:21 time: 0.5701 data_time: 0.0407 memory: 14901 loss: 1.3129 loss_prob: 0.7118 loss_thr: 0.4797 loss_db: 0.1214 2022/11/02 18:02:42 - mmengine - INFO - Epoch(train) [539][35/63] lr: 1.2657e-03 eta: 6:51:21 time: 0.5793 data_time: 0.0331 memory: 14901 loss: 1.2506 loss_prob: 0.6683 loss_thr: 0.4736 loss_db: 0.1087 2022/11/02 18:02:45 - mmengine - INFO - Epoch(train) [539][40/63] lr: 1.2657e-03 eta: 6:51:15 time: 0.5410 data_time: 0.0139 memory: 14901 loss: 1.2659 loss_prob: 0.6836 loss_thr: 0.4652 loss_db: 0.1171 2022/11/02 18:02:48 - mmengine - INFO - Epoch(train) [539][45/63] lr: 1.2657e-03 eta: 6:51:15 time: 0.5398 data_time: 0.0133 memory: 14901 loss: 1.2715 loss_prob: 0.6868 loss_thr: 0.4652 loss_db: 0.1195 2022/11/02 18:02:51 - mmengine - INFO - Epoch(train) [539][50/63] lr: 1.2657e-03 eta: 6:51:09 time: 0.5554 data_time: 0.0240 memory: 14901 loss: 1.3440 loss_prob: 0.7380 loss_thr: 0.4823 loss_db: 0.1237 2022/11/02 18:02:53 - mmengine - INFO - Epoch(train) [539][55/63] lr: 1.2657e-03 eta: 6:51:09 time: 0.5518 data_time: 0.0305 memory: 14901 loss: 1.3088 loss_prob: 0.7185 loss_thr: 0.4673 loss_db: 0.1229 2022/11/02 18:02:56 - mmengine - INFO - Epoch(train) [539][60/63] lr: 1.2657e-03 eta: 6:51:02 time: 0.5299 data_time: 0.0205 memory: 14901 loss: 1.2714 loss_prob: 0.6742 loss_thr: 0.4820 loss_db: 0.1152 2022/11/02 18:02:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:03:05 - mmengine - INFO - Epoch(train) [540][5/63] lr: 1.2640e-03 eta: 6:51:02 time: 1.0415 data_time: 0.2123 memory: 14901 loss: 1.3845 loss_prob: 0.7637 loss_thr: 0.4949 loss_db: 0.1259 2022/11/02 18:03:09 - mmengine - INFO - Epoch(train) [540][10/63] lr: 1.2640e-03 eta: 6:50:59 time: 1.1924 data_time: 0.2304 memory: 14901 loss: 1.3105 loss_prob: 0.7281 loss_thr: 0.4630 loss_db: 0.1194 2022/11/02 18:03:13 - mmengine - INFO - Epoch(train) [540][15/63] lr: 1.2640e-03 eta: 6:50:59 time: 0.7566 data_time: 0.0319 memory: 14901 loss: 1.2304 loss_prob: 0.6625 loss_thr: 0.4548 loss_db: 0.1131 2022/11/02 18:03:15 - mmengine - INFO - Epoch(train) [540][20/63] lr: 1.2640e-03 eta: 6:50:53 time: 0.5950 data_time: 0.0129 memory: 14901 loss: 1.2997 loss_prob: 0.6918 loss_thr: 0.4911 loss_db: 0.1168 2022/11/02 18:03:18 - mmengine - INFO - Epoch(train) [540][25/63] lr: 1.2640e-03 eta: 6:50:53 time: 0.5353 data_time: 0.0195 memory: 14901 loss: 1.3950 loss_prob: 0.7684 loss_thr: 0.5009 loss_db: 0.1256 2022/11/02 18:03:22 - mmengine - INFO - Epoch(train) [540][30/63] lr: 1.2640e-03 eta: 6:50:48 time: 0.6629 data_time: 0.0371 memory: 14901 loss: 1.4330 loss_prob: 0.8022 loss_thr: 0.5007 loss_db: 0.1300 2022/11/02 18:03:25 - mmengine - INFO - Epoch(train) [540][35/63] lr: 1.2640e-03 eta: 6:50:48 time: 0.6582 data_time: 0.0403 memory: 14901 loss: 1.4555 loss_prob: 0.8003 loss_thr: 0.5213 loss_db: 0.1339 2022/11/02 18:03:28 - mmengine - INFO - Epoch(train) [540][40/63] lr: 1.2640e-03 eta: 6:50:42 time: 0.5847 data_time: 0.0230 memory: 14901 loss: 1.8268 loss_prob: 1.1405 loss_thr: 0.5171 loss_db: 0.1691 2022/11/02 18:03:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:03:32 - mmengine - INFO - Epoch(train) [540][45/63] lr: 1.2640e-03 eta: 6:50:42 time: 0.6823 data_time: 0.0088 memory: 14901 loss: 1.9377 loss_prob: 1.2148 loss_thr: 0.5398 loss_db: 0.1831 2022/11/02 18:03:34 - mmengine - INFO - Epoch(train) [540][50/63] lr: 1.2640e-03 eta: 6:50:37 time: 0.6332 data_time: 0.0150 memory: 14901 loss: 1.5383 loss_prob: 0.8669 loss_thr: 0.5252 loss_db: 0.1463 2022/11/02 18:03:37 - mmengine - INFO - Epoch(train) [540][55/63] lr: 1.2640e-03 eta: 6:50:37 time: 0.5312 data_time: 0.0278 memory: 14901 loss: 1.3889 loss_prob: 0.7697 loss_thr: 0.4911 loss_db: 0.1281 2022/11/02 18:03:39 - mmengine - INFO - Epoch(train) [540][60/63] lr: 1.2640e-03 eta: 6:50:30 time: 0.5104 data_time: 0.0240 memory: 14901 loss: 1.5457 loss_prob: 0.8784 loss_thr: 0.5254 loss_db: 0.1419 2022/11/02 18:03:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:03:41 - mmengine - INFO - Saving checkpoint at 540 epochs 2022/11/02 18:03:45 - mmengine - INFO - Epoch(val) [540][5/500] eta: 6:50:30 time: 0.0479 data_time: 0.0055 memory: 14901 2022/11/02 18:03:45 - mmengine - INFO - Epoch(val) [540][10/500] eta: 0:00:27 time: 0.0552 data_time: 0.0057 memory: 1008 2022/11/02 18:03:45 - mmengine - INFO - Epoch(val) [540][15/500] eta: 0:00:27 time: 0.0463 data_time: 0.0031 memory: 1008 2022/11/02 18:03:45 - mmengine - INFO - Epoch(val) [540][20/500] eta: 0:00:19 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/02 18:03:45 - mmengine - INFO - Epoch(val) [540][25/500] eta: 0:00:19 time: 0.0403 data_time: 0.0029 memory: 1008 2022/11/02 18:03:46 - mmengine - INFO - Epoch(val) [540][30/500] eta: 0:00:20 time: 0.0435 data_time: 0.0030 memory: 1008 2022/11/02 18:03:46 - mmengine - INFO - Epoch(val) [540][35/500] eta: 0:00:20 time: 0.0460 data_time: 0.0029 memory: 1008 2022/11/02 18:03:46 - mmengine - INFO - Epoch(val) [540][40/500] eta: 0:00:21 time: 0.0473 data_time: 0.0027 memory: 1008 2022/11/02 18:03:46 - mmengine - INFO - Epoch(val) [540][45/500] eta: 0:00:21 time: 0.0436 data_time: 0.0024 memory: 1008 2022/11/02 18:03:47 - mmengine - INFO - Epoch(val) [540][50/500] eta: 0:00:18 time: 0.0402 data_time: 0.0027 memory: 1008 2022/11/02 18:03:47 - mmengine - INFO - Epoch(val) [540][55/500] eta: 0:00:18 time: 0.0417 data_time: 0.0029 memory: 1008 2022/11/02 18:03:47 - mmengine - INFO - Epoch(val) [540][60/500] eta: 0:00:18 time: 0.0417 data_time: 0.0031 memory: 1008 2022/11/02 18:03:47 - mmengine - INFO - Epoch(val) [540][65/500] eta: 0:00:18 time: 0.0427 data_time: 0.0029 memory: 1008 2022/11/02 18:03:47 - mmengine - INFO - Epoch(val) [540][70/500] eta: 0:00:19 time: 0.0461 data_time: 0.0029 memory: 1008 2022/11/02 18:03:48 - mmengine - INFO - Epoch(val) [540][75/500] eta: 0:00:19 time: 0.0431 data_time: 0.0029 memory: 1008 2022/11/02 18:03:48 - mmengine - INFO - Epoch(val) [540][80/500] eta: 0:00:15 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/02 18:03:48 - mmengine - INFO - Epoch(val) [540][85/500] eta: 0:00:15 time: 0.0389 data_time: 0.0029 memory: 1008 2022/11/02 18:03:48 - mmengine - INFO - Epoch(val) [540][90/500] eta: 0:00:18 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 18:03:48 - mmengine - INFO - Epoch(val) [540][95/500] eta: 0:00:18 time: 0.0518 data_time: 0.0032 memory: 1008 2022/11/02 18:03:49 - mmengine - INFO - Epoch(val) [540][100/500] eta: 0:00:19 time: 0.0482 data_time: 0.0033 memory: 1008 2022/11/02 18:03:49 - mmengine - INFO - Epoch(val) [540][105/500] eta: 0:00:19 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/02 18:03:49 - mmengine - INFO - Epoch(val) [540][110/500] eta: 0:00:16 time: 0.0420 data_time: 0.0030 memory: 1008 2022/11/02 18:03:49 - mmengine - INFO - Epoch(val) [540][115/500] eta: 0:00:16 time: 0.0453 data_time: 0.0031 memory: 1008 2022/11/02 18:03:50 - mmengine - INFO - Epoch(val) [540][120/500] eta: 0:00:17 time: 0.0451 data_time: 0.0029 memory: 1008 2022/11/02 18:03:50 - mmengine - INFO - Epoch(val) [540][125/500] eta: 0:00:17 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 18:03:50 - mmengine - INFO - Epoch(val) [540][130/500] eta: 0:00:16 time: 0.0444 data_time: 0.0040 memory: 1008 2022/11/02 18:03:50 - mmengine - INFO - Epoch(val) [540][135/500] eta: 0:00:16 time: 0.0482 data_time: 0.0043 memory: 1008 2022/11/02 18:03:50 - mmengine - INFO - Epoch(val) [540][140/500] eta: 0:00:16 time: 0.0468 data_time: 0.0036 memory: 1008 2022/11/02 18:03:51 - mmengine - INFO - Epoch(val) [540][145/500] eta: 0:00:16 time: 0.0477 data_time: 0.0033 memory: 1008 2022/11/02 18:03:51 - mmengine - INFO - Epoch(val) [540][150/500] eta: 0:00:17 time: 0.0495 data_time: 0.0040 memory: 1008 2022/11/02 18:03:51 - mmengine - INFO - Epoch(val) [540][155/500] eta: 0:00:17 time: 0.0545 data_time: 0.0044 memory: 1008 2022/11/02 18:03:51 - mmengine - INFO - Epoch(val) [540][160/500] eta: 0:00:16 time: 0.0490 data_time: 0.0030 memory: 1008 2022/11/02 18:03:52 - mmengine - INFO - Epoch(val) [540][165/500] eta: 0:00:16 time: 0.0501 data_time: 0.0033 memory: 1008 2022/11/02 18:03:52 - mmengine - INFO - Epoch(val) [540][170/500] eta: 0:00:17 time: 0.0539 data_time: 0.0034 memory: 1008 2022/11/02 18:03:52 - mmengine - INFO - Epoch(val) [540][175/500] eta: 0:00:17 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/02 18:03:52 - mmengine - INFO - Epoch(val) [540][180/500] eta: 0:00:13 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/02 18:03:53 - mmengine - INFO - Epoch(val) [540][185/500] eta: 0:00:13 time: 0.0435 data_time: 0.0027 memory: 1008 2022/11/02 18:03:53 - mmengine - INFO - Epoch(val) [540][190/500] eta: 0:00:13 time: 0.0424 data_time: 0.0025 memory: 1008 2022/11/02 18:03:53 - mmengine - INFO - Epoch(val) [540][195/500] eta: 0:00:13 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 18:03:53 - mmengine - INFO - Epoch(val) [540][200/500] eta: 0:00:14 time: 0.0487 data_time: 0.0028 memory: 1008 2022/11/02 18:03:54 - mmengine - INFO - Epoch(val) [540][205/500] eta: 0:00:14 time: 0.0494 data_time: 0.0026 memory: 1008 2022/11/02 18:03:54 - mmengine - INFO - Epoch(val) [540][210/500] eta: 0:00:11 time: 0.0399 data_time: 0.0030 memory: 1008 2022/11/02 18:03:54 - mmengine - INFO - Epoch(val) [540][215/500] eta: 0:00:11 time: 0.0401 data_time: 0.0031 memory: 1008 2022/11/02 18:03:54 - mmengine - INFO - Epoch(val) [540][220/500] eta: 0:00:10 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/02 18:03:54 - mmengine - INFO - Epoch(val) [540][225/500] eta: 0:00:10 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/02 18:03:55 - mmengine - INFO - Epoch(val) [540][230/500] eta: 0:00:11 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 18:03:55 - mmengine - INFO - Epoch(val) [540][235/500] eta: 0:00:11 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 18:03:55 - mmengine - INFO - Epoch(val) [540][240/500] eta: 0:00:13 time: 0.0508 data_time: 0.0030 memory: 1008 2022/11/02 18:03:55 - mmengine - INFO - Epoch(val) [540][245/500] eta: 0:00:13 time: 0.0485 data_time: 0.0033 memory: 1008 2022/11/02 18:03:55 - mmengine - INFO - Epoch(val) [540][250/500] eta: 0:00:10 time: 0.0420 data_time: 0.0030 memory: 1008 2022/11/02 18:03:56 - mmengine - INFO - Epoch(val) [540][255/500] eta: 0:00:10 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 18:03:56 - mmengine - INFO - Epoch(val) [540][260/500] eta: 0:00:09 time: 0.0378 data_time: 0.0025 memory: 1008 2022/11/02 18:03:56 - mmengine - INFO - Epoch(val) [540][265/500] eta: 0:00:09 time: 0.0383 data_time: 0.0026 memory: 1008 2022/11/02 18:03:56 - mmengine - INFO - Epoch(val) [540][270/500] eta: 0:00:09 time: 0.0432 data_time: 0.0032 memory: 1008 2022/11/02 18:03:56 - mmengine - INFO - Epoch(val) [540][275/500] eta: 0:00:09 time: 0.0419 data_time: 0.0032 memory: 1008 2022/11/02 18:03:57 - mmengine - INFO - Epoch(val) [540][280/500] eta: 0:00:08 time: 0.0392 data_time: 0.0029 memory: 1008 2022/11/02 18:03:57 - mmengine - INFO - Epoch(val) [540][285/500] eta: 0:00:08 time: 0.0428 data_time: 0.0029 memory: 1008 2022/11/02 18:03:57 - mmengine - INFO - Epoch(val) [540][290/500] eta: 0:00:09 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 18:03:57 - mmengine - INFO - Epoch(val) [540][295/500] eta: 0:00:09 time: 0.0428 data_time: 0.0028 memory: 1008 2022/11/02 18:03:58 - mmengine - INFO - Epoch(val) [540][300/500] eta: 0:00:08 time: 0.0441 data_time: 0.0033 memory: 1008 2022/11/02 18:03:58 - mmengine - INFO - Epoch(val) [540][305/500] eta: 0:00:08 time: 0.0415 data_time: 0.0034 memory: 1008 2022/11/02 18:03:58 - mmengine - INFO - Epoch(val) [540][310/500] eta: 0:00:07 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/02 18:03:58 - mmengine - INFO - Epoch(val) [540][315/500] eta: 0:00:07 time: 0.0448 data_time: 0.0023 memory: 1008 2022/11/02 18:03:58 - mmengine - INFO - Epoch(val) [540][320/500] eta: 0:00:08 time: 0.0451 data_time: 0.0027 memory: 1008 2022/11/02 18:03:59 - mmengine - INFO - Epoch(val) [540][325/500] eta: 0:00:08 time: 0.0605 data_time: 0.0032 memory: 1008 2022/11/02 18:03:59 - mmengine - INFO - Epoch(val) [540][330/500] eta: 0:00:10 time: 0.0628 data_time: 0.0036 memory: 1008 2022/11/02 18:03:59 - mmengine - INFO - Epoch(val) [540][335/500] eta: 0:00:10 time: 0.0431 data_time: 0.0033 memory: 1008 2022/11/02 18:04:00 - mmengine - INFO - Epoch(val) [540][340/500] eta: 0:00:09 time: 0.0587 data_time: 0.0028 memory: 1008 2022/11/02 18:04:00 - mmengine - INFO - Epoch(val) [540][345/500] eta: 0:00:09 time: 0.0578 data_time: 0.0027 memory: 1008 2022/11/02 18:04:00 - mmengine - INFO - Epoch(val) [540][350/500] eta: 0:00:06 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/02 18:04:00 - mmengine - INFO - Epoch(val) [540][355/500] eta: 0:00:06 time: 0.0454 data_time: 0.0027 memory: 1008 2022/11/02 18:04:01 - mmengine - INFO - Epoch(val) [540][360/500] eta: 0:00:05 time: 0.0415 data_time: 0.0027 memory: 1008 2022/11/02 18:04:01 - mmengine - INFO - Epoch(val) [540][365/500] eta: 0:00:05 time: 0.0416 data_time: 0.0026 memory: 1008 2022/11/02 18:04:01 - mmengine - INFO - Epoch(val) [540][370/500] eta: 0:00:05 time: 0.0390 data_time: 0.0025 memory: 1008 2022/11/02 18:04:01 - mmengine - INFO - Epoch(val) [540][375/500] eta: 0:00:05 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 18:04:01 - mmengine - INFO - Epoch(val) [540][380/500] eta: 0:00:05 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/02 18:04:02 - mmengine - INFO - Epoch(val) [540][385/500] eta: 0:00:05 time: 0.0439 data_time: 0.0027 memory: 1008 2022/11/02 18:04:02 - mmengine - INFO - Epoch(val) [540][390/500] eta: 0:00:05 time: 0.0466 data_time: 0.0035 memory: 1008 2022/11/02 18:04:02 - mmengine - INFO - Epoch(val) [540][395/500] eta: 0:00:05 time: 0.0489 data_time: 0.0037 memory: 1008 2022/11/02 18:04:02 - mmengine - INFO - Epoch(val) [540][400/500] eta: 0:00:04 time: 0.0437 data_time: 0.0034 memory: 1008 2022/11/02 18:04:02 - mmengine - INFO - Epoch(val) [540][405/500] eta: 0:00:04 time: 0.0444 data_time: 0.0033 memory: 1008 2022/11/02 18:04:03 - mmengine - INFO - Epoch(val) [540][410/500] eta: 0:00:04 time: 0.0467 data_time: 0.0029 memory: 1008 2022/11/02 18:04:03 - mmengine - INFO - Epoch(val) [540][415/500] eta: 0:00:04 time: 0.0461 data_time: 0.0032 memory: 1008 2022/11/02 18:04:03 - mmengine - INFO - Epoch(val) [540][420/500] eta: 0:00:03 time: 0.0419 data_time: 0.0036 memory: 1008 2022/11/02 18:04:03 - mmengine - INFO - Epoch(val) [540][425/500] eta: 0:00:03 time: 0.0389 data_time: 0.0029 memory: 1008 2022/11/02 18:04:04 - mmengine - INFO - Epoch(val) [540][430/500] eta: 0:00:02 time: 0.0404 data_time: 0.0025 memory: 1008 2022/11/02 18:04:04 - mmengine - INFO - Epoch(val) [540][435/500] eta: 0:00:02 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 18:04:04 - mmengine - INFO - Epoch(val) [540][440/500] eta: 0:00:02 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 18:04:04 - mmengine - INFO - Epoch(val) [540][445/500] eta: 0:00:02 time: 0.0423 data_time: 0.0027 memory: 1008 2022/11/02 18:04:04 - mmengine - INFO - Epoch(val) [540][450/500] eta: 0:00:02 time: 0.0428 data_time: 0.0028 memory: 1008 2022/11/02 18:04:05 - mmengine - INFO - Epoch(val) [540][455/500] eta: 0:00:02 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/02 18:04:05 - mmengine - INFO - Epoch(val) [540][460/500] eta: 0:00:01 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 18:04:05 - mmengine - INFO - Epoch(val) [540][465/500] eta: 0:00:01 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 18:04:05 - mmengine - INFO - Epoch(val) [540][470/500] eta: 0:00:01 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 18:04:05 - mmengine - INFO - Epoch(val) [540][475/500] eta: 0:00:01 time: 0.0392 data_time: 0.0029 memory: 1008 2022/11/02 18:04:06 - mmengine - INFO - Epoch(val) [540][480/500] eta: 0:00:00 time: 0.0415 data_time: 0.0030 memory: 1008 2022/11/02 18:04:06 - mmengine - INFO - Epoch(val) [540][485/500] eta: 0:00:00 time: 0.0411 data_time: 0.0027 memory: 1008 2022/11/02 18:04:06 - mmengine - INFO - Epoch(val) [540][490/500] eta: 0:00:00 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 18:04:06 - mmengine - INFO - Epoch(val) [540][495/500] eta: 0:00:00 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 18:04:06 - mmengine - INFO - Epoch(val) [540][500/500] eta: 0:00:00 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 18:04:06 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8156, precision: 0.6869, hmean: 0.7458 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8156, precision: 0.7519, hmean: 0.7824 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8113, precision: 0.7959, hmean: 0.8035 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8016, precision: 0.8375, hmean: 0.8192 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7535, precision: 0.8812, hmean: 0.8124 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4357, precision: 0.9546, hmean: 0.5983 2022/11/02 18:04:06 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0111, precision: 0.9200, hmean: 0.0219 2022/11/02 18:04:06 - mmengine - INFO - Epoch(val) [540][500/500] icdar/precision: 0.8375 icdar/recall: 0.8016 icdar/hmean: 0.8192 2022/11/02 18:04:12 - mmengine - INFO - Epoch(train) [541][5/63] lr: 1.2622e-03 eta: 0:00:00 time: 0.8062 data_time: 0.2784 memory: 14901 loss: 1.5680 loss_prob: 0.8876 loss_thr: 0.5363 loss_db: 0.1441 2022/11/02 18:04:15 - mmengine - INFO - Epoch(train) [541][10/63] lr: 1.2622e-03 eta: 6:50:24 time: 0.8709 data_time: 0.2768 memory: 14901 loss: 1.4385 loss_prob: 0.7939 loss_thr: 0.5089 loss_db: 0.1358 2022/11/02 18:04:18 - mmengine - INFO - Epoch(train) [541][15/63] lr: 1.2622e-03 eta: 6:50:24 time: 0.5560 data_time: 0.0093 memory: 14901 loss: 1.4962 loss_prob: 0.8304 loss_thr: 0.5236 loss_db: 0.1423 2022/11/02 18:04:20 - mmengine - INFO - Epoch(train) [541][20/63] lr: 1.2622e-03 eta: 6:50:17 time: 0.5294 data_time: 0.0146 memory: 14901 loss: 1.4370 loss_prob: 0.8020 loss_thr: 0.5003 loss_db: 0.1348 2022/11/02 18:04:24 - mmengine - INFO - Epoch(train) [541][25/63] lr: 1.2622e-03 eta: 6:50:17 time: 0.6631 data_time: 0.0510 memory: 14901 loss: 1.3293 loss_prob: 0.7313 loss_thr: 0.4757 loss_db: 0.1223 2022/11/02 18:04:28 - mmengine - INFO - Epoch(train) [541][30/63] lr: 1.2622e-03 eta: 6:50:13 time: 0.7343 data_time: 0.0479 memory: 14901 loss: 1.3078 loss_prob: 0.6990 loss_thr: 0.4880 loss_db: 0.1207 2022/11/02 18:04:30 - mmengine - INFO - Epoch(train) [541][35/63] lr: 1.2622e-03 eta: 6:50:13 time: 0.5997 data_time: 0.0104 memory: 14901 loss: 1.3324 loss_prob: 0.7174 loss_thr: 0.4900 loss_db: 0.1249 2022/11/02 18:04:33 - mmengine - INFO - Epoch(train) [541][40/63] lr: 1.2622e-03 eta: 6:50:06 time: 0.5033 data_time: 0.0082 memory: 14901 loss: 1.4334 loss_prob: 0.7923 loss_thr: 0.5099 loss_db: 0.1312 2022/11/02 18:04:35 - mmengine - INFO - Epoch(train) [541][45/63] lr: 1.2622e-03 eta: 6:50:06 time: 0.5012 data_time: 0.0088 memory: 14901 loss: 1.4758 loss_prob: 0.8156 loss_thr: 0.5252 loss_db: 0.1350 2022/11/02 18:04:39 - mmengine - INFO - Epoch(train) [541][50/63] lr: 1.2622e-03 eta: 6:50:00 time: 0.5724 data_time: 0.0332 memory: 14901 loss: 1.3735 loss_prob: 0.7500 loss_thr: 0.4985 loss_db: 0.1249 2022/11/02 18:04:42 - mmengine - INFO - Epoch(train) [541][55/63] lr: 1.2622e-03 eta: 6:50:00 time: 0.6079 data_time: 0.0303 memory: 14901 loss: 1.2646 loss_prob: 0.6829 loss_thr: 0.4672 loss_db: 0.1145 2022/11/02 18:04:45 - mmengine - INFO - Epoch(train) [541][60/63] lr: 1.2622e-03 eta: 6:49:54 time: 0.5939 data_time: 0.0101 memory: 14901 loss: 1.2526 loss_prob: 0.6717 loss_thr: 0.4638 loss_db: 0.1171 2022/11/02 18:04:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:04:52 - mmengine - INFO - Epoch(train) [542][5/63] lr: 1.2605e-03 eta: 6:49:54 time: 0.8278 data_time: 0.2661 memory: 14901 loss: 1.5921 loss_prob: 0.9429 loss_thr: 0.5007 loss_db: 0.1485 2022/11/02 18:04:54 - mmengine - INFO - Epoch(train) [542][10/63] lr: 1.2605e-03 eta: 6:49:47 time: 0.8529 data_time: 0.2703 memory: 14901 loss: 1.5549 loss_prob: 0.9095 loss_thr: 0.5024 loss_db: 0.1430 2022/11/02 18:04:58 - mmengine - INFO - Epoch(train) [542][15/63] lr: 1.2605e-03 eta: 6:49:47 time: 0.5862 data_time: 0.0160 memory: 14901 loss: 1.3617 loss_prob: 0.7446 loss_thr: 0.4940 loss_db: 0.1231 2022/11/02 18:05:00 - mmengine - INFO - Epoch(train) [542][20/63] lr: 1.2605e-03 eta: 6:49:41 time: 0.5994 data_time: 0.0115 memory: 14901 loss: 1.3546 loss_prob: 0.7377 loss_thr: 0.4921 loss_db: 0.1247 2022/11/02 18:05:04 - mmengine - INFO - Epoch(train) [542][25/63] lr: 1.2605e-03 eta: 6:49:41 time: 0.6560 data_time: 0.0361 memory: 14901 loss: 1.3308 loss_prob: 0.7216 loss_thr: 0.4860 loss_db: 0.1232 2022/11/02 18:05:07 - mmengine - INFO - Epoch(train) [542][30/63] lr: 1.2605e-03 eta: 6:49:36 time: 0.6614 data_time: 0.0481 memory: 14901 loss: 1.4348 loss_prob: 0.8072 loss_thr: 0.4900 loss_db: 0.1375 2022/11/02 18:05:10 - mmengine - INFO - Epoch(train) [542][35/63] lr: 1.2605e-03 eta: 6:49:36 time: 0.5586 data_time: 0.0295 memory: 14901 loss: 1.4216 loss_prob: 0.7951 loss_thr: 0.4913 loss_db: 0.1352 2022/11/02 18:05:12 - mmengine - INFO - Epoch(train) [542][40/63] lr: 1.2605e-03 eta: 6:49:30 time: 0.5472 data_time: 0.0170 memory: 14901 loss: 1.2510 loss_prob: 0.6680 loss_thr: 0.4695 loss_db: 0.1136 2022/11/02 18:05:15 - mmengine - INFO - Epoch(train) [542][45/63] lr: 1.2605e-03 eta: 6:49:30 time: 0.5216 data_time: 0.0106 memory: 14901 loss: 1.2675 loss_prob: 0.6776 loss_thr: 0.4744 loss_db: 0.1155 2022/11/02 18:05:19 - mmengine - INFO - Epoch(train) [542][50/63] lr: 1.2605e-03 eta: 6:49:24 time: 0.6092 data_time: 0.0264 memory: 14901 loss: 1.3526 loss_prob: 0.7368 loss_thr: 0.4916 loss_db: 0.1243 2022/11/02 18:05:22 - mmengine - INFO - Epoch(train) [542][55/63] lr: 1.2605e-03 eta: 6:49:24 time: 0.7277 data_time: 0.0252 memory: 14901 loss: 1.4556 loss_prob: 0.7992 loss_thr: 0.5252 loss_db: 0.1312 2022/11/02 18:05:25 - mmengine - INFO - Epoch(train) [542][60/63] lr: 1.2605e-03 eta: 6:49:19 time: 0.6738 data_time: 0.0147 memory: 14901 loss: 1.5019 loss_prob: 0.8239 loss_thr: 0.5423 loss_db: 0.1358 2022/11/02 18:05:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:05:33 - mmengine - INFO - Epoch(train) [543][5/63] lr: 1.2588e-03 eta: 6:49:19 time: 0.9127 data_time: 0.2679 memory: 14901 loss: 1.4353 loss_prob: 0.7927 loss_thr: 0.5078 loss_db: 0.1348 2022/11/02 18:05:36 - mmengine - INFO - Epoch(train) [543][10/63] lr: 1.2588e-03 eta: 6:49:13 time: 0.9531 data_time: 0.2674 memory: 14901 loss: 1.3933 loss_prob: 0.7539 loss_thr: 0.5130 loss_db: 0.1264 2022/11/02 18:05:39 - mmengine - INFO - Epoch(train) [543][15/63] lr: 1.2588e-03 eta: 6:49:13 time: 0.5275 data_time: 0.0108 memory: 14901 loss: 1.3938 loss_prob: 0.7566 loss_thr: 0.5100 loss_db: 0.1272 2022/11/02 18:05:41 - mmengine - INFO - Epoch(train) [543][20/63] lr: 1.2588e-03 eta: 6:49:07 time: 0.5311 data_time: 0.0083 memory: 14901 loss: 1.4097 loss_prob: 0.7791 loss_thr: 0.4974 loss_db: 0.1331 2022/11/02 18:05:46 - mmengine - INFO - Epoch(train) [543][25/63] lr: 1.2588e-03 eta: 6:49:07 time: 0.7119 data_time: 0.0239 memory: 14901 loss: 1.3652 loss_prob: 0.7556 loss_thr: 0.4802 loss_db: 0.1294 2022/11/02 18:05:49 - mmengine - INFO - Epoch(train) [543][30/63] lr: 1.2588e-03 eta: 6:49:03 time: 0.7995 data_time: 0.0451 memory: 14901 loss: 1.3507 loss_prob: 0.7450 loss_thr: 0.4781 loss_db: 0.1275 2022/11/02 18:05:52 - mmengine - INFO - Epoch(train) [543][35/63] lr: 1.2588e-03 eta: 6:49:03 time: 0.6617 data_time: 0.0292 memory: 14901 loss: 1.2407 loss_prob: 0.6682 loss_thr: 0.4587 loss_db: 0.1138 2022/11/02 18:05:55 - mmengine - INFO - Epoch(train) [543][40/63] lr: 1.2588e-03 eta: 6:48:57 time: 0.5447 data_time: 0.0103 memory: 14901 loss: 1.1789 loss_prob: 0.6257 loss_thr: 0.4476 loss_db: 0.1056 2022/11/02 18:05:57 - mmengine - INFO - Epoch(train) [543][45/63] lr: 1.2588e-03 eta: 6:48:57 time: 0.5136 data_time: 0.0115 memory: 14901 loss: 1.3604 loss_prob: 0.7453 loss_thr: 0.4898 loss_db: 0.1254 2022/11/02 18:06:01 - mmengine - INFO - Epoch(train) [543][50/63] lr: 1.2588e-03 eta: 6:48:51 time: 0.6139 data_time: 0.0317 memory: 14901 loss: 1.4260 loss_prob: 0.7756 loss_thr: 0.5195 loss_db: 0.1308 2022/11/02 18:06:04 - mmengine - INFO - Epoch(train) [543][55/63] lr: 1.2588e-03 eta: 6:48:51 time: 0.6478 data_time: 0.0328 memory: 14901 loss: 1.3346 loss_prob: 0.7102 loss_thr: 0.5044 loss_db: 0.1199 2022/11/02 18:06:07 - mmengine - INFO - Epoch(train) [543][60/63] lr: 1.2588e-03 eta: 6:48:45 time: 0.5544 data_time: 0.0123 memory: 14901 loss: 1.2653 loss_prob: 0.6721 loss_thr: 0.4784 loss_db: 0.1148 2022/11/02 18:06:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:06:15 - mmengine - INFO - Epoch(train) [544][5/63] lr: 1.2571e-03 eta: 6:48:45 time: 0.9235 data_time: 0.2265 memory: 14901 loss: 1.2469 loss_prob: 0.6751 loss_thr: 0.4562 loss_db: 0.1157 2022/11/02 18:06:18 - mmengine - INFO - Epoch(train) [544][10/63] lr: 1.2571e-03 eta: 6:48:39 time: 0.9563 data_time: 0.2264 memory: 14901 loss: 1.2889 loss_prob: 0.6937 loss_thr: 0.4789 loss_db: 0.1164 2022/11/02 18:06:21 - mmengine - INFO - Epoch(train) [544][15/63] lr: 1.2571e-03 eta: 6:48:39 time: 0.5838 data_time: 0.0120 memory: 14901 loss: 1.2723 loss_prob: 0.6848 loss_thr: 0.4729 loss_db: 0.1146 2022/11/02 18:06:24 - mmengine - INFO - Epoch(train) [544][20/63] lr: 1.2571e-03 eta: 6:48:34 time: 0.6520 data_time: 0.0130 memory: 14901 loss: 1.2373 loss_prob: 0.6535 loss_thr: 0.4695 loss_db: 0.1144 2022/11/02 18:06:28 - mmengine - INFO - Epoch(train) [544][25/63] lr: 1.2571e-03 eta: 6:48:34 time: 0.7266 data_time: 0.0237 memory: 14901 loss: 1.2535 loss_prob: 0.6562 loss_thr: 0.4831 loss_db: 0.1143 2022/11/02 18:06:31 - mmengine - INFO - Epoch(train) [544][30/63] lr: 1.2571e-03 eta: 6:48:29 time: 0.6260 data_time: 0.0391 memory: 14901 loss: 1.1933 loss_prob: 0.6314 loss_thr: 0.4546 loss_db: 0.1073 2022/11/02 18:06:33 - mmengine - INFO - Epoch(train) [544][35/63] lr: 1.2571e-03 eta: 6:48:29 time: 0.5187 data_time: 0.0258 memory: 14901 loss: 1.1870 loss_prob: 0.6363 loss_thr: 0.4408 loss_db: 0.1098 2022/11/02 18:06:36 - mmengine - INFO - Epoch(train) [544][40/63] lr: 1.2571e-03 eta: 6:48:22 time: 0.5131 data_time: 0.0157 memory: 14901 loss: 1.2373 loss_prob: 0.6693 loss_thr: 0.4519 loss_db: 0.1161 2022/11/02 18:06:39 - mmengine - INFO - Epoch(train) [544][45/63] lr: 1.2571e-03 eta: 6:48:22 time: 0.5681 data_time: 0.0170 memory: 14901 loss: 1.3016 loss_prob: 0.7032 loss_thr: 0.4787 loss_db: 0.1198 2022/11/02 18:06:41 - mmengine - INFO - Epoch(train) [544][50/63] lr: 1.2571e-03 eta: 6:48:15 time: 0.5518 data_time: 0.0252 memory: 14901 loss: 1.3022 loss_prob: 0.7064 loss_thr: 0.4762 loss_db: 0.1196 2022/11/02 18:06:44 - mmengine - INFO - Epoch(train) [544][55/63] lr: 1.2571e-03 eta: 6:48:15 time: 0.5266 data_time: 0.0277 memory: 14901 loss: 1.2121 loss_prob: 0.6518 loss_thr: 0.4479 loss_db: 0.1123 2022/11/02 18:06:48 - mmengine - INFO - Epoch(train) [544][60/63] lr: 1.2571e-03 eta: 6:48:10 time: 0.6390 data_time: 0.0173 memory: 14901 loss: 1.1360 loss_prob: 0.5989 loss_thr: 0.4350 loss_db: 0.1022 2022/11/02 18:06:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:06:56 - mmengine - INFO - Epoch(train) [545][5/63] lr: 1.2553e-03 eta: 6:48:10 time: 1.0009 data_time: 0.2645 memory: 14901 loss: 1.1921 loss_prob: 0.6309 loss_thr: 0.4534 loss_db: 0.1078 2022/11/02 18:07:01 - mmengine - INFO - Epoch(train) [545][10/63] lr: 1.2553e-03 eta: 6:48:06 time: 1.0921 data_time: 0.2648 memory: 14901 loss: 1.2073 loss_prob: 0.6445 loss_thr: 0.4512 loss_db: 0.1117 2022/11/02 18:07:04 - mmengine - INFO - Epoch(train) [545][15/63] lr: 1.2553e-03 eta: 6:48:06 time: 0.8093 data_time: 0.0148 memory: 14901 loss: 1.2487 loss_prob: 0.6680 loss_thr: 0.4662 loss_db: 0.1146 2022/11/02 18:07:08 - mmengine - INFO - Epoch(train) [545][20/63] lr: 1.2553e-03 eta: 6:48:02 time: 0.7488 data_time: 0.0125 memory: 14901 loss: 1.2688 loss_prob: 0.6906 loss_thr: 0.4611 loss_db: 0.1171 2022/11/02 18:07:11 - mmengine - INFO - Epoch(train) [545][25/63] lr: 1.2553e-03 eta: 6:48:02 time: 0.6799 data_time: 0.0339 memory: 14901 loss: 1.2289 loss_prob: 0.6645 loss_thr: 0.4539 loss_db: 0.1106 2022/11/02 18:07:14 - mmengine - INFO - Epoch(train) [545][30/63] lr: 1.2553e-03 eta: 6:47:56 time: 0.5571 data_time: 0.0387 memory: 14901 loss: 1.2198 loss_prob: 0.6494 loss_thr: 0.4628 loss_db: 0.1077 2022/11/02 18:07:17 - mmengine - INFO - Epoch(train) [545][35/63] lr: 1.2553e-03 eta: 6:47:56 time: 0.5391 data_time: 0.0207 memory: 14901 loss: 1.2293 loss_prob: 0.6447 loss_thr: 0.4765 loss_db: 0.1082 2022/11/02 18:07:19 - mmengine - INFO - Epoch(train) [545][40/63] lr: 1.2553e-03 eta: 6:47:49 time: 0.5514 data_time: 0.0160 memory: 14901 loss: 1.1652 loss_prob: 0.5971 loss_thr: 0.4678 loss_db: 0.1004 2022/11/02 18:07:24 - mmengine - INFO - Epoch(train) [545][45/63] lr: 1.2553e-03 eta: 6:47:49 time: 0.7045 data_time: 0.0125 memory: 14901 loss: 1.2059 loss_prob: 0.6355 loss_thr: 0.4627 loss_db: 0.1078 2022/11/02 18:07:27 - mmengine - INFO - Epoch(train) [545][50/63] lr: 1.2553e-03 eta: 6:47:46 time: 0.8063 data_time: 0.0220 memory: 14901 loss: 1.2762 loss_prob: 0.6809 loss_thr: 0.4801 loss_db: 0.1152 2022/11/02 18:07:31 - mmengine - INFO - Epoch(train) [545][55/63] lr: 1.2553e-03 eta: 6:47:46 time: 0.7039 data_time: 0.0265 memory: 14901 loss: 1.1920 loss_prob: 0.6261 loss_thr: 0.4590 loss_db: 0.1069 2022/11/02 18:07:33 - mmengine - INFO - Epoch(train) [545][60/63] lr: 1.2553e-03 eta: 6:47:40 time: 0.5756 data_time: 0.0190 memory: 14901 loss: 1.2329 loss_prob: 0.6583 loss_thr: 0.4624 loss_db: 0.1122 2022/11/02 18:07:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:07:41 - mmengine - INFO - Epoch(train) [546][5/63] lr: 1.2536e-03 eta: 6:47:40 time: 0.9041 data_time: 0.2610 memory: 14901 loss: 1.3106 loss_prob: 0.7020 loss_thr: 0.4937 loss_db: 0.1150 2022/11/02 18:07:44 - mmengine - INFO - Epoch(train) [546][10/63] lr: 1.2536e-03 eta: 6:47:34 time: 0.9689 data_time: 0.2628 memory: 14901 loss: 1.3916 loss_prob: 0.7778 loss_thr: 0.4932 loss_db: 0.1206 2022/11/02 18:07:47 - mmengine - INFO - Epoch(train) [546][15/63] lr: 1.2536e-03 eta: 6:47:34 time: 0.5728 data_time: 0.0144 memory: 14901 loss: 1.4228 loss_prob: 0.7973 loss_thr: 0.5011 loss_db: 0.1245 2022/11/02 18:07:50 - mmengine - INFO - Epoch(train) [546][20/63] lr: 1.2536e-03 eta: 6:47:28 time: 0.5516 data_time: 0.0123 memory: 14901 loss: 1.3201 loss_prob: 0.7048 loss_thr: 0.4952 loss_db: 0.1201 2022/11/02 18:07:53 - mmengine - INFO - Epoch(train) [546][25/63] lr: 1.2536e-03 eta: 6:47:28 time: 0.5757 data_time: 0.0384 memory: 14901 loss: 1.2331 loss_prob: 0.6549 loss_thr: 0.4642 loss_db: 0.1139 2022/11/02 18:07:55 - mmengine - INFO - Epoch(train) [546][30/63] lr: 1.2536e-03 eta: 6:47:22 time: 0.5637 data_time: 0.0398 memory: 14901 loss: 1.2040 loss_prob: 0.6475 loss_thr: 0.4453 loss_db: 0.1112 2022/11/02 18:07:58 - mmengine - INFO - Epoch(train) [546][35/63] lr: 1.2536e-03 eta: 6:47:22 time: 0.5403 data_time: 0.0172 memory: 14901 loss: 1.2136 loss_prob: 0.6467 loss_thr: 0.4537 loss_db: 0.1131 2022/11/02 18:08:01 - mmengine - INFO - Epoch(train) [546][40/63] lr: 1.2536e-03 eta: 6:47:15 time: 0.5472 data_time: 0.0161 memory: 14901 loss: 1.2423 loss_prob: 0.6628 loss_thr: 0.4664 loss_db: 0.1132 2022/11/02 18:08:04 - mmengine - INFO - Epoch(train) [546][45/63] lr: 1.2536e-03 eta: 6:47:15 time: 0.5522 data_time: 0.0157 memory: 14901 loss: 1.3512 loss_prob: 0.7450 loss_thr: 0.4844 loss_db: 0.1217 2022/11/02 18:08:06 - mmengine - INFO - Epoch(train) [546][50/63] lr: 1.2536e-03 eta: 6:47:09 time: 0.5461 data_time: 0.0292 memory: 14901 loss: 1.3686 loss_prob: 0.7385 loss_thr: 0.5062 loss_db: 0.1240 2022/11/02 18:08:09 - mmengine - INFO - Epoch(train) [546][55/63] lr: 1.2536e-03 eta: 6:47:09 time: 0.5508 data_time: 0.0263 memory: 14901 loss: 1.3115 loss_prob: 0.6950 loss_thr: 0.4943 loss_db: 0.1223 2022/11/02 18:08:12 - mmengine - INFO - Epoch(train) [546][60/63] lr: 1.2536e-03 eta: 6:47:02 time: 0.5265 data_time: 0.0138 memory: 14901 loss: 1.2656 loss_prob: 0.6832 loss_thr: 0.4630 loss_db: 0.1195 2022/11/02 18:08:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:08:21 - mmengine - INFO - Epoch(train) [547][5/63] lr: 1.2519e-03 eta: 6:47:02 time: 1.0244 data_time: 0.2856 memory: 14901 loss: 1.2787 loss_prob: 0.6983 loss_thr: 0.4677 loss_db: 0.1127 2022/11/02 18:08:24 - mmengine - INFO - Epoch(train) [547][10/63] lr: 1.2519e-03 eta: 6:46:58 time: 1.0445 data_time: 0.2845 memory: 14901 loss: 1.1991 loss_prob: 0.6485 loss_thr: 0.4399 loss_db: 0.1107 2022/11/02 18:08:27 - mmengine - INFO - Epoch(train) [547][15/63] lr: 1.2519e-03 eta: 6:46:58 time: 0.5836 data_time: 0.0161 memory: 14901 loss: 1.3056 loss_prob: 0.7153 loss_thr: 0.4705 loss_db: 0.1198 2022/11/02 18:08:29 - mmengine - INFO - Epoch(train) [547][20/63] lr: 1.2519e-03 eta: 6:46:51 time: 0.5256 data_time: 0.0135 memory: 14901 loss: 1.3758 loss_prob: 0.7570 loss_thr: 0.4959 loss_db: 0.1230 2022/11/02 18:08:32 - mmengine - INFO - Epoch(train) [547][25/63] lr: 1.2519e-03 eta: 6:46:51 time: 0.5878 data_time: 0.0320 memory: 14901 loss: 1.3140 loss_prob: 0.7068 loss_thr: 0.4879 loss_db: 0.1193 2022/11/02 18:08:35 - mmengine - INFO - Epoch(train) [547][30/63] lr: 1.2519e-03 eta: 6:46:45 time: 0.6001 data_time: 0.0350 memory: 14901 loss: 1.3498 loss_prob: 0.7387 loss_thr: 0.4850 loss_db: 0.1262 2022/11/02 18:08:38 - mmengine - INFO - Epoch(train) [547][35/63] lr: 1.2519e-03 eta: 6:46:45 time: 0.5385 data_time: 0.0175 memory: 14901 loss: 1.3330 loss_prob: 0.7277 loss_thr: 0.4823 loss_db: 0.1229 2022/11/02 18:08:41 - mmengine - INFO - Epoch(train) [547][40/63] lr: 1.2519e-03 eta: 6:46:38 time: 0.5330 data_time: 0.0172 memory: 14901 loss: 1.2152 loss_prob: 0.6459 loss_thr: 0.4595 loss_db: 0.1098 2022/11/02 18:08:43 - mmengine - INFO - Epoch(train) [547][45/63] lr: 1.2519e-03 eta: 6:46:38 time: 0.5377 data_time: 0.0131 memory: 14901 loss: 1.1997 loss_prob: 0.6245 loss_thr: 0.4640 loss_db: 0.1112 2022/11/02 18:08:47 - mmengine - INFO - Epoch(train) [547][50/63] lr: 1.2519e-03 eta: 6:46:33 time: 0.6258 data_time: 0.0220 memory: 14901 loss: 1.2905 loss_prob: 0.6845 loss_thr: 0.4881 loss_db: 0.1178 2022/11/02 18:08:51 - mmengine - INFO - Epoch(train) [547][55/63] lr: 1.2519e-03 eta: 6:46:33 time: 0.7277 data_time: 0.0243 memory: 14901 loss: 1.3815 loss_prob: 0.7544 loss_thr: 0.5015 loss_db: 0.1256 2022/11/02 18:08:53 - mmengine - INFO - Epoch(train) [547][60/63] lr: 1.2519e-03 eta: 6:46:28 time: 0.6495 data_time: 0.0171 memory: 14901 loss: 1.3270 loss_prob: 0.7223 loss_thr: 0.4829 loss_db: 0.1218 2022/11/02 18:08:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:09:01 - mmengine - INFO - Epoch(train) [548][5/63] lr: 1.2502e-03 eta: 6:46:28 time: 0.9032 data_time: 0.2453 memory: 14901 loss: 1.2984 loss_prob: 0.6940 loss_thr: 0.4848 loss_db: 0.1197 2022/11/02 18:09:04 - mmengine - INFO - Epoch(train) [548][10/63] lr: 1.2502e-03 eta: 6:46:22 time: 0.9330 data_time: 0.2460 memory: 14901 loss: 1.3043 loss_prob: 0.7116 loss_thr: 0.4728 loss_db: 0.1200 2022/11/02 18:09:07 - mmengine - INFO - Epoch(train) [548][15/63] lr: 1.2502e-03 eta: 6:46:22 time: 0.5260 data_time: 0.0091 memory: 14901 loss: 1.2772 loss_prob: 0.6827 loss_thr: 0.4784 loss_db: 0.1161 2022/11/02 18:09:09 - mmengine - INFO - Epoch(train) [548][20/63] lr: 1.2502e-03 eta: 6:46:15 time: 0.5230 data_time: 0.0106 memory: 14901 loss: 1.3692 loss_prob: 0.7331 loss_thr: 0.5110 loss_db: 0.1251 2022/11/02 18:09:12 - mmengine - INFO - Epoch(train) [548][25/63] lr: 1.2502e-03 eta: 6:46:15 time: 0.5916 data_time: 0.0221 memory: 14901 loss: 1.3264 loss_prob: 0.7107 loss_thr: 0.4947 loss_db: 0.1210 2022/11/02 18:09:16 - mmengine - INFO - Epoch(train) [548][30/63] lr: 1.2502e-03 eta: 6:46:10 time: 0.6238 data_time: 0.0550 memory: 14901 loss: 1.3044 loss_prob: 0.7066 loss_thr: 0.4777 loss_db: 0.1201 2022/11/02 18:09:18 - mmengine - INFO - Epoch(train) [548][35/63] lr: 1.2502e-03 eta: 6:46:10 time: 0.5932 data_time: 0.0460 memory: 14901 loss: 1.3558 loss_prob: 0.7402 loss_thr: 0.4898 loss_db: 0.1257 2022/11/02 18:09:22 - mmengine - INFO - Epoch(train) [548][40/63] lr: 1.2502e-03 eta: 6:46:04 time: 0.6593 data_time: 0.0086 memory: 14901 loss: 1.3319 loss_prob: 0.7154 loss_thr: 0.4967 loss_db: 0.1199 2022/11/02 18:09:26 - mmengine - INFO - Epoch(train) [548][45/63] lr: 1.2502e-03 eta: 6:46:04 time: 0.7453 data_time: 0.0103 memory: 14901 loss: 1.3137 loss_prob: 0.7108 loss_thr: 0.4826 loss_db: 0.1203 2022/11/02 18:09:28 - mmengine - INFO - Epoch(train) [548][50/63] lr: 1.2502e-03 eta: 6:45:59 time: 0.6328 data_time: 0.0215 memory: 14901 loss: 1.2242 loss_prob: 0.6576 loss_thr: 0.4552 loss_db: 0.1114 2022/11/02 18:09:31 - mmengine - INFO - Epoch(train) [548][55/63] lr: 1.2502e-03 eta: 6:45:59 time: 0.5351 data_time: 0.0303 memory: 14901 loss: 1.1736 loss_prob: 0.6215 loss_thr: 0.4476 loss_db: 0.1045 2022/11/02 18:09:34 - mmengine - INFO - Epoch(train) [548][60/63] lr: 1.2502e-03 eta: 6:45:53 time: 0.5942 data_time: 0.0208 memory: 14901 loss: 1.2600 loss_prob: 0.6723 loss_thr: 0.4723 loss_db: 0.1153 2022/11/02 18:09:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:09:44 - mmengine - INFO - Epoch(train) [549][5/63] lr: 1.2484e-03 eta: 6:45:53 time: 1.0696 data_time: 0.2780 memory: 14901 loss: 1.3794 loss_prob: 0.7695 loss_thr: 0.4821 loss_db: 0.1278 2022/11/02 18:09:48 - mmengine - INFO - Epoch(train) [549][10/63] lr: 1.2484e-03 eta: 6:45:49 time: 1.0804 data_time: 0.2762 memory: 14901 loss: 1.3811 loss_prob: 0.7880 loss_thr: 0.4601 loss_db: 0.1330 2022/11/02 18:09:50 - mmengine - INFO - Epoch(train) [549][15/63] lr: 1.2484e-03 eta: 6:45:49 time: 0.6498 data_time: 0.0141 memory: 14901 loss: 1.4537 loss_prob: 0.8257 loss_thr: 0.4886 loss_db: 0.1394 2022/11/02 18:09:53 - mmengine - INFO - Epoch(train) [549][20/63] lr: 1.2484e-03 eta: 6:45:42 time: 0.5403 data_time: 0.0144 memory: 14901 loss: 1.5217 loss_prob: 0.8575 loss_thr: 0.5207 loss_db: 0.1435 2022/11/02 18:09:56 - mmengine - INFO - Epoch(train) [549][25/63] lr: 1.2484e-03 eta: 6:45:42 time: 0.5968 data_time: 0.0452 memory: 14901 loss: 1.6084 loss_prob: 0.9069 loss_thr: 0.5482 loss_db: 0.1533 2022/11/02 18:09:59 - mmengine - INFO - Epoch(train) [549][30/63] lr: 1.2484e-03 eta: 6:45:37 time: 0.6293 data_time: 0.0441 memory: 14901 loss: 1.6326 loss_prob: 0.9199 loss_thr: 0.5573 loss_db: 0.1554 2022/11/02 18:10:02 - mmengine - INFO - Epoch(train) [549][35/63] lr: 1.2484e-03 eta: 6:45:37 time: 0.5655 data_time: 0.0102 memory: 14901 loss: 1.4729 loss_prob: 0.8085 loss_thr: 0.5264 loss_db: 0.1380 2022/11/02 18:10:04 - mmengine - INFO - Epoch(train) [549][40/63] lr: 1.2484e-03 eta: 6:45:30 time: 0.4969 data_time: 0.0117 memory: 14901 loss: 1.3890 loss_prob: 0.7621 loss_thr: 0.4964 loss_db: 0.1305 2022/11/02 18:10:08 - mmengine - INFO - Epoch(train) [549][45/63] lr: 1.2484e-03 eta: 6:45:30 time: 0.5489 data_time: 0.0120 memory: 14901 loss: 1.3866 loss_prob: 0.7657 loss_thr: 0.4915 loss_db: 0.1294 2022/11/02 18:10:11 - mmengine - INFO - Epoch(train) [549][50/63] lr: 1.2484e-03 eta: 6:45:24 time: 0.6093 data_time: 0.0392 memory: 14901 loss: 1.4033 loss_prob: 0.7788 loss_thr: 0.4949 loss_db: 0.1296 2022/11/02 18:10:14 - mmengine - INFO - Epoch(train) [549][55/63] lr: 1.2484e-03 eta: 6:45:24 time: 0.6349 data_time: 0.0384 memory: 14901 loss: 1.3807 loss_prob: 0.7574 loss_thr: 0.4958 loss_db: 0.1274 2022/11/02 18:10:17 - mmengine - INFO - Epoch(train) [549][60/63] lr: 1.2484e-03 eta: 6:45:19 time: 0.6305 data_time: 0.0106 memory: 14901 loss: 1.3444 loss_prob: 0.7139 loss_thr: 0.5077 loss_db: 0.1227 2022/11/02 18:10:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:10:27 - mmengine - INFO - Epoch(train) [550][5/63] lr: 1.2467e-03 eta: 6:45:19 time: 1.1425 data_time: 0.2853 memory: 14901 loss: 1.3378 loss_prob: 0.7367 loss_thr: 0.4837 loss_db: 0.1173 2022/11/02 18:10:31 - mmengine - INFO - Epoch(train) [550][10/63] lr: 1.2467e-03 eta: 6:45:15 time: 1.1048 data_time: 0.2867 memory: 14901 loss: 1.4020 loss_prob: 0.7725 loss_thr: 0.4992 loss_db: 0.1303 2022/11/02 18:10:34 - mmengine - INFO - Epoch(train) [550][15/63] lr: 1.2467e-03 eta: 6:45:15 time: 0.7231 data_time: 0.0130 memory: 14901 loss: 1.3276 loss_prob: 0.7234 loss_thr: 0.4807 loss_db: 0.1235 2022/11/02 18:10:37 - mmengine - INFO - Epoch(train) [550][20/63] lr: 1.2467e-03 eta: 6:45:10 time: 0.6399 data_time: 0.0113 memory: 14901 loss: 1.2986 loss_prob: 0.7010 loss_thr: 0.4785 loss_db: 0.1190 2022/11/02 18:10:40 - mmengine - INFO - Epoch(train) [550][25/63] lr: 1.2467e-03 eta: 6:45:10 time: 0.5678 data_time: 0.0328 memory: 14901 loss: 1.2731 loss_prob: 0.6850 loss_thr: 0.4705 loss_db: 0.1177 2022/11/02 18:10:43 - mmengine - INFO - Epoch(train) [550][30/63] lr: 1.2467e-03 eta: 6:45:03 time: 0.5539 data_time: 0.0445 memory: 14901 loss: 1.2386 loss_prob: 0.6736 loss_thr: 0.4493 loss_db: 0.1157 2022/11/02 18:10:45 - mmengine - INFO - Epoch(train) [550][35/63] lr: 1.2467e-03 eta: 6:45:03 time: 0.5193 data_time: 0.0221 memory: 14901 loss: 1.2307 loss_prob: 0.6645 loss_thr: 0.4540 loss_db: 0.1123 2022/11/02 18:10:48 - mmengine - INFO - Epoch(train) [550][40/63] lr: 1.2467e-03 eta: 6:44:57 time: 0.5349 data_time: 0.0095 memory: 14901 loss: 1.2819 loss_prob: 0.6908 loss_thr: 0.4753 loss_db: 0.1158 2022/11/02 18:10:52 - mmengine - INFO - Epoch(train) [550][45/63] lr: 1.2467e-03 eta: 6:44:57 time: 0.7271 data_time: 0.0105 memory: 14901 loss: 1.3955 loss_prob: 0.7647 loss_thr: 0.5000 loss_db: 0.1308 2022/11/02 18:10:56 - mmengine - INFO - Epoch(train) [550][50/63] lr: 1.2467e-03 eta: 6:44:54 time: 0.8405 data_time: 0.0288 memory: 14901 loss: 1.3530 loss_prob: 0.7382 loss_thr: 0.4876 loss_db: 0.1272 2022/11/02 18:10:59 - mmengine - INFO - Epoch(train) [550][55/63] lr: 1.2467e-03 eta: 6:44:54 time: 0.6983 data_time: 0.0311 memory: 14901 loss: 1.2611 loss_prob: 0.6729 loss_thr: 0.4736 loss_db: 0.1146 2022/11/02 18:11:02 - mmengine - INFO - Epoch(train) [550][60/63] lr: 1.2467e-03 eta: 6:44:48 time: 0.5934 data_time: 0.0153 memory: 14901 loss: 1.3166 loss_prob: 0.7134 loss_thr: 0.4815 loss_db: 0.1217 2022/11/02 18:11:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:11:11 - mmengine - INFO - Epoch(train) [551][5/63] lr: 1.2450e-03 eta: 6:44:48 time: 0.9415 data_time: 0.2174 memory: 14901 loss: 1.3316 loss_prob: 0.7365 loss_thr: 0.4722 loss_db: 0.1229 2022/11/02 18:11:13 - mmengine - INFO - Epoch(train) [551][10/63] lr: 1.2450e-03 eta: 6:44:42 time: 0.9116 data_time: 0.2187 memory: 14901 loss: 1.1916 loss_prob: 0.6380 loss_thr: 0.4457 loss_db: 0.1078 2022/11/02 18:11:16 - mmengine - INFO - Epoch(train) [551][15/63] lr: 1.2450e-03 eta: 6:44:42 time: 0.5349 data_time: 0.0159 memory: 14901 loss: 1.2687 loss_prob: 0.6893 loss_thr: 0.4616 loss_db: 0.1178 2022/11/02 18:11:19 - mmengine - INFO - Epoch(train) [551][20/63] lr: 1.2450e-03 eta: 6:44:35 time: 0.5582 data_time: 0.0177 memory: 14901 loss: 1.3613 loss_prob: 0.7487 loss_thr: 0.4891 loss_db: 0.1235 2022/11/02 18:11:22 - mmengine - INFO - Epoch(train) [551][25/63] lr: 1.2450e-03 eta: 6:44:35 time: 0.5726 data_time: 0.0156 memory: 14901 loss: 1.3107 loss_prob: 0.7098 loss_thr: 0.4815 loss_db: 0.1194 2022/11/02 18:11:24 - mmengine - INFO - Epoch(train) [551][30/63] lr: 1.2450e-03 eta: 6:44:29 time: 0.5494 data_time: 0.0357 memory: 14901 loss: 1.3043 loss_prob: 0.6963 loss_thr: 0.4864 loss_db: 0.1216 2022/11/02 18:11:27 - mmengine - INFO - Epoch(train) [551][35/63] lr: 1.2450e-03 eta: 6:44:29 time: 0.5157 data_time: 0.0333 memory: 14901 loss: 1.2453 loss_prob: 0.6612 loss_thr: 0.4688 loss_db: 0.1153 2022/11/02 18:11:30 - mmengine - INFO - Epoch(train) [551][40/63] lr: 1.2450e-03 eta: 6:44:22 time: 0.5354 data_time: 0.0152 memory: 14901 loss: 1.2372 loss_prob: 0.6652 loss_thr: 0.4574 loss_db: 0.1146 2022/11/02 18:11:32 - mmengine - INFO - Epoch(train) [551][45/63] lr: 1.2450e-03 eta: 6:44:22 time: 0.5202 data_time: 0.0154 memory: 14901 loss: 1.2249 loss_prob: 0.6510 loss_thr: 0.4626 loss_db: 0.1113 2022/11/02 18:11:35 - mmengine - INFO - Epoch(train) [551][50/63] lr: 1.2450e-03 eta: 6:44:16 time: 0.5330 data_time: 0.0138 memory: 14901 loss: 1.2846 loss_prob: 0.6938 loss_thr: 0.4747 loss_db: 0.1160 2022/11/02 18:11:38 - mmengine - INFO - Epoch(train) [551][55/63] lr: 1.2450e-03 eta: 6:44:16 time: 0.6024 data_time: 0.0269 memory: 14901 loss: 1.4058 loss_prob: 0.7759 loss_thr: 0.5044 loss_db: 0.1255 2022/11/02 18:11:41 - mmengine - INFO - Epoch(train) [551][60/63] lr: 1.2450e-03 eta: 6:44:09 time: 0.5783 data_time: 0.0239 memory: 14901 loss: 1.3006 loss_prob: 0.7111 loss_thr: 0.4717 loss_db: 0.1178 2022/11/02 18:11:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:11:50 - mmengine - INFO - Epoch(train) [552][5/63] lr: 1.2433e-03 eta: 6:44:09 time: 0.9775 data_time: 0.2708 memory: 14901 loss: 1.3772 loss_prob: 0.7610 loss_thr: 0.4908 loss_db: 0.1254 2022/11/02 18:11:54 - mmengine - INFO - Epoch(train) [552][10/63] lr: 1.2433e-03 eta: 6:44:05 time: 1.0870 data_time: 0.2687 memory: 14901 loss: 1.4392 loss_prob: 0.8024 loss_thr: 0.5041 loss_db: 0.1327 2022/11/02 18:11:56 - mmengine - INFO - Epoch(train) [552][15/63] lr: 1.2433e-03 eta: 6:44:05 time: 0.6685 data_time: 0.0090 memory: 14901 loss: 1.3875 loss_prob: 0.7529 loss_thr: 0.5075 loss_db: 0.1272 2022/11/02 18:11:59 - mmengine - INFO - Epoch(train) [552][20/63] lr: 1.2433e-03 eta: 6:43:59 time: 0.5642 data_time: 0.0116 memory: 14901 loss: 1.3332 loss_prob: 0.7170 loss_thr: 0.4967 loss_db: 0.1195 2022/11/02 18:12:03 - mmengine - INFO - Epoch(train) [552][25/63] lr: 1.2433e-03 eta: 6:43:59 time: 0.6765 data_time: 0.0450 memory: 14901 loss: 1.3212 loss_prob: 0.7140 loss_thr: 0.4892 loss_db: 0.1179 2022/11/02 18:12:06 - mmengine - INFO - Epoch(train) [552][30/63] lr: 1.2433e-03 eta: 6:43:54 time: 0.6491 data_time: 0.0454 memory: 14901 loss: 1.3602 loss_prob: 0.7448 loss_thr: 0.4882 loss_db: 0.1272 2022/11/02 18:12:09 - mmengine - INFO - Epoch(train) [552][35/63] lr: 1.2433e-03 eta: 6:43:54 time: 0.5652 data_time: 0.0103 memory: 14901 loss: 1.3033 loss_prob: 0.7082 loss_thr: 0.4718 loss_db: 0.1233 2022/11/02 18:12:11 - mmengine - INFO - Epoch(train) [552][40/63] lr: 1.2433e-03 eta: 6:43:47 time: 0.5346 data_time: 0.0101 memory: 14901 loss: 1.2465 loss_prob: 0.6625 loss_thr: 0.4711 loss_db: 0.1129 2022/11/02 18:12:14 - mmengine - INFO - Epoch(train) [552][45/63] lr: 1.2433e-03 eta: 6:43:47 time: 0.5266 data_time: 0.0093 memory: 14901 loss: 1.3417 loss_prob: 0.7261 loss_thr: 0.4929 loss_db: 0.1227 2022/11/02 18:12:17 - mmengine - INFO - Epoch(train) [552][50/63] lr: 1.2433e-03 eta: 6:43:41 time: 0.5990 data_time: 0.0250 memory: 14901 loss: 1.3727 loss_prob: 0.7533 loss_thr: 0.4897 loss_db: 0.1297 2022/11/02 18:12:20 - mmengine - INFO - Epoch(train) [552][55/63] lr: 1.2433e-03 eta: 6:43:41 time: 0.5922 data_time: 0.0264 memory: 14901 loss: 1.3071 loss_prob: 0.7173 loss_thr: 0.4683 loss_db: 0.1215 2022/11/02 18:12:23 - mmengine - INFO - Epoch(train) [552][60/63] lr: 1.2433e-03 eta: 6:43:35 time: 0.5339 data_time: 0.0112 memory: 14901 loss: 1.3911 loss_prob: 0.7823 loss_thr: 0.4820 loss_db: 0.1268 2022/11/02 18:12:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:12:31 - mmengine - INFO - Epoch(train) [553][5/63] lr: 1.2415e-03 eta: 6:43:35 time: 0.9432 data_time: 0.2518 memory: 14901 loss: 1.4778 loss_prob: 0.8379 loss_thr: 0.5022 loss_db: 0.1377 2022/11/02 18:12:35 - mmengine - INFO - Epoch(train) [553][10/63] lr: 1.2415e-03 eta: 6:43:30 time: 1.0296 data_time: 0.2532 memory: 14901 loss: 1.3772 loss_prob: 0.7709 loss_thr: 0.4748 loss_db: 0.1315 2022/11/02 18:12:38 - mmengine - INFO - Epoch(train) [553][15/63] lr: 1.2415e-03 eta: 6:43:30 time: 0.6828 data_time: 0.0123 memory: 14901 loss: 1.3161 loss_prob: 0.7219 loss_thr: 0.4729 loss_db: 0.1213 2022/11/02 18:12:41 - mmengine - INFO - Epoch(train) [553][20/63] lr: 1.2415e-03 eta: 6:43:24 time: 0.6130 data_time: 0.0110 memory: 14901 loss: 1.2741 loss_prob: 0.6840 loss_thr: 0.4738 loss_db: 0.1164 2022/11/02 18:12:44 - mmengine - INFO - Epoch(train) [553][25/63] lr: 1.2415e-03 eta: 6:43:24 time: 0.6487 data_time: 0.0179 memory: 14901 loss: 1.4026 loss_prob: 0.7752 loss_thr: 0.4978 loss_db: 0.1295 2022/11/02 18:12:47 - mmengine - INFO - Epoch(train) [553][30/63] lr: 1.2415e-03 eta: 6:43:19 time: 0.6135 data_time: 0.0414 memory: 14901 loss: 1.3386 loss_prob: 0.7375 loss_thr: 0.4804 loss_db: 0.1208 2022/11/02 18:12:50 - mmengine - INFO - Epoch(train) [553][35/63] lr: 1.2415e-03 eta: 6:43:19 time: 0.5389 data_time: 0.0355 memory: 14901 loss: 1.2758 loss_prob: 0.6883 loss_thr: 0.4714 loss_db: 0.1160 2022/11/02 18:12:55 - mmengine - INFO - Epoch(train) [553][40/63] lr: 1.2415e-03 eta: 6:43:15 time: 0.7628 data_time: 0.0122 memory: 14901 loss: 1.3410 loss_prob: 0.7226 loss_thr: 0.4947 loss_db: 0.1237 2022/11/02 18:12:58 - mmengine - INFO - Epoch(train) [553][45/63] lr: 1.2415e-03 eta: 6:43:15 time: 0.8574 data_time: 0.0119 memory: 14901 loss: 1.2603 loss_prob: 0.6643 loss_thr: 0.4819 loss_db: 0.1142 2022/11/02 18:13:02 - mmengine - INFO - Epoch(train) [553][50/63] lr: 1.2415e-03 eta: 6:43:10 time: 0.7211 data_time: 0.0231 memory: 14901 loss: 1.3063 loss_prob: 0.6996 loss_thr: 0.4851 loss_db: 0.1216 2022/11/02 18:13:05 - mmengine - INFO - Epoch(train) [553][55/63] lr: 1.2415e-03 eta: 6:43:10 time: 0.6534 data_time: 0.0453 memory: 14901 loss: 1.2583 loss_prob: 0.6708 loss_thr: 0.4701 loss_db: 0.1174 2022/11/02 18:13:08 - mmengine - INFO - Epoch(train) [553][60/63] lr: 1.2415e-03 eta: 6:43:04 time: 0.5909 data_time: 0.0345 memory: 14901 loss: 1.2267 loss_prob: 0.6590 loss_thr: 0.4561 loss_db: 0.1117 2022/11/02 18:13:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:13:17 - mmengine - INFO - Epoch(train) [554][5/63] lr: 1.2398e-03 eta: 6:43:04 time: 1.0350 data_time: 0.2781 memory: 14901 loss: 1.2451 loss_prob: 0.6591 loss_thr: 0.4740 loss_db: 0.1120 2022/11/02 18:13:20 - mmengine - INFO - Epoch(train) [554][10/63] lr: 1.2398e-03 eta: 6:42:59 time: 1.0073 data_time: 0.2755 memory: 14901 loss: 1.2651 loss_prob: 0.6760 loss_thr: 0.4750 loss_db: 0.1140 2022/11/02 18:13:23 - mmengine - INFO - Epoch(train) [554][15/63] lr: 1.2398e-03 eta: 6:42:59 time: 0.5938 data_time: 0.0104 memory: 14901 loss: 1.2592 loss_prob: 0.6847 loss_thr: 0.4573 loss_db: 0.1172 2022/11/02 18:13:26 - mmengine - INFO - Epoch(train) [554][20/63] lr: 1.2398e-03 eta: 6:42:54 time: 0.6396 data_time: 0.0111 memory: 14901 loss: 1.2046 loss_prob: 0.6460 loss_thr: 0.4488 loss_db: 0.1098 2022/11/02 18:13:29 - mmengine - INFO - Epoch(train) [554][25/63] lr: 1.2398e-03 eta: 6:42:54 time: 0.6147 data_time: 0.0202 memory: 14901 loss: 1.2579 loss_prob: 0.6730 loss_thr: 0.4724 loss_db: 0.1126 2022/11/02 18:13:33 - mmengine - INFO - Epoch(train) [554][30/63] lr: 1.2398e-03 eta: 6:42:48 time: 0.6260 data_time: 0.0437 memory: 14901 loss: 1.1849 loss_prob: 0.6265 loss_thr: 0.4515 loss_db: 0.1069 2022/11/02 18:13:36 - mmengine - INFO - Epoch(train) [554][35/63] lr: 1.2398e-03 eta: 6:42:48 time: 0.6925 data_time: 0.0342 memory: 14901 loss: 1.1622 loss_prob: 0.6091 loss_thr: 0.4482 loss_db: 0.1048 2022/11/02 18:13:39 - mmengine - INFO - Epoch(train) [554][40/63] lr: 1.2398e-03 eta: 6:42:44 time: 0.6804 data_time: 0.0102 memory: 14901 loss: 1.2856 loss_prob: 0.6903 loss_thr: 0.4789 loss_db: 0.1164 2022/11/02 18:13:42 - mmengine - INFO - Epoch(train) [554][45/63] lr: 1.2398e-03 eta: 6:42:44 time: 0.6107 data_time: 0.0098 memory: 14901 loss: 1.3198 loss_prob: 0.7111 loss_thr: 0.4875 loss_db: 0.1213 2022/11/02 18:13:45 - mmengine - INFO - Epoch(train) [554][50/63] lr: 1.2398e-03 eta: 6:42:37 time: 0.5280 data_time: 0.0251 memory: 14901 loss: 1.3659 loss_prob: 0.7484 loss_thr: 0.4921 loss_db: 0.1254 2022/11/02 18:13:48 - mmengine - INFO - Epoch(train) [554][55/63] lr: 1.2398e-03 eta: 6:42:37 time: 0.6140 data_time: 0.0335 memory: 14901 loss: 1.3385 loss_prob: 0.7378 loss_thr: 0.4810 loss_db: 0.1197 2022/11/02 18:13:52 - mmengine - INFO - Epoch(train) [554][60/63] lr: 1.2398e-03 eta: 6:42:32 time: 0.7137 data_time: 0.0195 memory: 14901 loss: 1.2416 loss_prob: 0.6670 loss_thr: 0.4634 loss_db: 0.1112 2022/11/02 18:13:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:14:02 - mmengine - INFO - Epoch(train) [555][5/63] lr: 1.2381e-03 eta: 6:42:32 time: 1.1789 data_time: 0.2727 memory: 14901 loss: 1.2987 loss_prob: 0.6901 loss_thr: 0.4894 loss_db: 0.1193 2022/11/02 18:14:05 - mmengine - INFO - Epoch(train) [555][10/63] lr: 1.2381e-03 eta: 6:42:28 time: 1.0504 data_time: 0.2712 memory: 14901 loss: 1.3183 loss_prob: 0.7223 loss_thr: 0.4714 loss_db: 0.1245 2022/11/02 18:14:08 - mmengine - INFO - Epoch(train) [555][15/63] lr: 1.2381e-03 eta: 6:42:28 time: 0.5982 data_time: 0.0098 memory: 14901 loss: 1.2767 loss_prob: 0.7054 loss_thr: 0.4517 loss_db: 0.1195 2022/11/02 18:14:12 - mmengine - INFO - Epoch(train) [555][20/63] lr: 1.2381e-03 eta: 6:42:23 time: 0.6766 data_time: 0.0121 memory: 14901 loss: 1.2487 loss_prob: 0.6833 loss_thr: 0.4534 loss_db: 0.1119 2022/11/02 18:14:15 - mmengine - INFO - Epoch(train) [555][25/63] lr: 1.2381e-03 eta: 6:42:23 time: 0.7397 data_time: 0.0376 memory: 14901 loss: 1.3297 loss_prob: 0.7331 loss_thr: 0.4738 loss_db: 0.1227 2022/11/02 18:14:18 - mmengine - INFO - Epoch(train) [555][30/63] lr: 1.2381e-03 eta: 6:42:17 time: 0.6280 data_time: 0.0379 memory: 14901 loss: 1.3390 loss_prob: 0.7490 loss_thr: 0.4634 loss_db: 0.1266 2022/11/02 18:14:21 - mmengine - INFO - Epoch(train) [555][35/63] lr: 1.2381e-03 eta: 6:42:17 time: 0.5198 data_time: 0.0153 memory: 14901 loss: 1.2397 loss_prob: 0.6847 loss_thr: 0.4417 loss_db: 0.1133 2022/11/02 18:14:23 - mmengine - INFO - Epoch(train) [555][40/63] lr: 1.2381e-03 eta: 6:42:10 time: 0.5119 data_time: 0.0138 memory: 14901 loss: 1.2821 loss_prob: 0.6876 loss_thr: 0.4773 loss_db: 0.1172 2022/11/02 18:14:26 - mmengine - INFO - Epoch(train) [555][45/63] lr: 1.2381e-03 eta: 6:42:10 time: 0.4999 data_time: 0.0103 memory: 14901 loss: 1.2858 loss_prob: 0.6939 loss_thr: 0.4694 loss_db: 0.1225 2022/11/02 18:14:28 - mmengine - INFO - Epoch(train) [555][50/63] lr: 1.2381e-03 eta: 6:42:04 time: 0.5055 data_time: 0.0235 memory: 14901 loss: 1.2027 loss_prob: 0.6508 loss_thr: 0.4406 loss_db: 0.1114 2022/11/02 18:14:31 - mmengine - INFO - Epoch(train) [555][55/63] lr: 1.2381e-03 eta: 6:42:04 time: 0.5093 data_time: 0.0262 memory: 14901 loss: 1.2051 loss_prob: 0.6478 loss_thr: 0.4479 loss_db: 0.1095 2022/11/02 18:14:34 - mmengine - INFO - Epoch(train) [555][60/63] lr: 1.2381e-03 eta: 6:41:57 time: 0.5575 data_time: 0.0152 memory: 14901 loss: 1.2014 loss_prob: 0.6391 loss_thr: 0.4528 loss_db: 0.1096 2022/11/02 18:14:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:14:43 - mmengine - INFO - Epoch(train) [556][5/63] lr: 1.2364e-03 eta: 6:41:57 time: 1.0471 data_time: 0.2585 memory: 14901 loss: 1.2745 loss_prob: 0.6825 loss_thr: 0.4761 loss_db: 0.1160 2022/11/02 18:14:46 - mmengine - INFO - Epoch(train) [556][10/63] lr: 1.2364e-03 eta: 6:41:52 time: 0.9696 data_time: 0.2596 memory: 14901 loss: 1.2142 loss_prob: 0.6407 loss_thr: 0.4636 loss_db: 0.1099 2022/11/02 18:14:49 - mmengine - INFO - Epoch(train) [556][15/63] lr: 1.2364e-03 eta: 6:41:52 time: 0.5774 data_time: 0.0099 memory: 14901 loss: 1.2839 loss_prob: 0.6940 loss_thr: 0.4721 loss_db: 0.1177 2022/11/02 18:14:51 - mmengine - INFO - Epoch(train) [556][20/63] lr: 1.2364e-03 eta: 6:41:45 time: 0.5226 data_time: 0.0111 memory: 14901 loss: 1.4544 loss_prob: 0.8394 loss_thr: 0.4814 loss_db: 0.1336 2022/11/02 18:14:55 - mmengine - INFO - Epoch(train) [556][25/63] lr: 1.2364e-03 eta: 6:41:45 time: 0.6282 data_time: 0.0247 memory: 14901 loss: 1.4599 loss_prob: 0.8470 loss_thr: 0.4799 loss_db: 0.1330 2022/11/02 18:14:58 - mmengine - INFO - Epoch(train) [556][30/63] lr: 1.2364e-03 eta: 6:41:40 time: 0.6415 data_time: 0.0422 memory: 14901 loss: 1.2786 loss_prob: 0.7008 loss_thr: 0.4595 loss_db: 0.1184 2022/11/02 18:15:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:15:01 - mmengine - INFO - Epoch(train) [556][35/63] lr: 1.2364e-03 eta: 6:41:40 time: 0.6033 data_time: 0.0319 memory: 14901 loss: 1.4611 loss_prob: 0.8537 loss_thr: 0.4715 loss_db: 0.1358 2022/11/02 18:15:04 - mmengine - INFO - Epoch(train) [556][40/63] lr: 1.2364e-03 eta: 6:41:34 time: 0.5931 data_time: 0.0129 memory: 14901 loss: 1.4830 loss_prob: 0.8662 loss_thr: 0.4802 loss_db: 0.1367 2022/11/02 18:15:06 - mmengine - INFO - Epoch(train) [556][45/63] lr: 1.2364e-03 eta: 6:41:34 time: 0.5415 data_time: 0.0103 memory: 14901 loss: 1.3534 loss_prob: 0.7443 loss_thr: 0.4837 loss_db: 0.1253 2022/11/02 18:15:09 - mmengine - INFO - Epoch(train) [556][50/63] lr: 1.2364e-03 eta: 6:41:28 time: 0.5837 data_time: 0.0227 memory: 14901 loss: 1.3791 loss_prob: 0.7622 loss_thr: 0.4919 loss_db: 0.1251 2022/11/02 18:15:12 - mmengine - INFO - Epoch(train) [556][55/63] lr: 1.2364e-03 eta: 6:41:28 time: 0.5885 data_time: 0.0275 memory: 14901 loss: 1.2834 loss_prob: 0.6878 loss_thr: 0.4788 loss_db: 0.1168 2022/11/02 18:15:15 - mmengine - INFO - Epoch(train) [556][60/63] lr: 1.2364e-03 eta: 6:41:21 time: 0.5774 data_time: 0.0182 memory: 14901 loss: 1.3510 loss_prob: 0.7244 loss_thr: 0.5040 loss_db: 0.1227 2022/11/02 18:15:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:15:25 - mmengine - INFO - Epoch(train) [557][5/63] lr: 1.2346e-03 eta: 6:41:21 time: 1.1073 data_time: 0.2414 memory: 14901 loss: 1.2970 loss_prob: 0.6935 loss_thr: 0.4864 loss_db: 0.1171 2022/11/02 18:15:28 - mmengine - INFO - Epoch(train) [557][10/63] lr: 1.2346e-03 eta: 6:41:17 time: 1.0724 data_time: 0.2411 memory: 14901 loss: 1.2772 loss_prob: 0.6798 loss_thr: 0.4811 loss_db: 0.1163 2022/11/02 18:15:32 - mmengine - INFO - Epoch(train) [557][15/63] lr: 1.2346e-03 eta: 6:41:17 time: 0.6556 data_time: 0.0096 memory: 14901 loss: 1.3041 loss_prob: 0.7012 loss_thr: 0.4881 loss_db: 0.1148 2022/11/02 18:15:35 - mmengine - INFO - Epoch(train) [557][20/63] lr: 1.2346e-03 eta: 6:41:12 time: 0.6727 data_time: 0.0161 memory: 14901 loss: 1.2937 loss_prob: 0.6863 loss_thr: 0.4913 loss_db: 0.1160 2022/11/02 18:15:37 - mmengine - INFO - Epoch(train) [557][25/63] lr: 1.2346e-03 eta: 6:41:12 time: 0.5633 data_time: 0.0212 memory: 14901 loss: 1.3056 loss_prob: 0.6862 loss_thr: 0.5002 loss_db: 0.1192 2022/11/02 18:15:41 - mmengine - INFO - Epoch(train) [557][30/63] lr: 1.2346e-03 eta: 6:41:07 time: 0.6127 data_time: 0.0359 memory: 14901 loss: 1.3018 loss_prob: 0.6836 loss_thr: 0.5012 loss_db: 0.1170 2022/11/02 18:15:44 - mmengine - INFO - Epoch(train) [557][35/63] lr: 1.2346e-03 eta: 6:41:07 time: 0.6293 data_time: 0.0291 memory: 14901 loss: 1.2000 loss_prob: 0.6272 loss_thr: 0.4664 loss_db: 0.1063 2022/11/02 18:15:46 - mmengine - INFO - Epoch(train) [557][40/63] lr: 1.2346e-03 eta: 6:41:00 time: 0.5661 data_time: 0.0086 memory: 14901 loss: 1.3393 loss_prob: 0.7407 loss_thr: 0.4732 loss_db: 0.1254 2022/11/02 18:15:50 - mmengine - INFO - Epoch(train) [557][45/63] lr: 1.2346e-03 eta: 6:41:00 time: 0.6354 data_time: 0.0111 memory: 14901 loss: 1.4368 loss_prob: 0.8075 loss_thr: 0.4932 loss_db: 0.1360 2022/11/02 18:15:54 - mmengine - INFO - Epoch(train) [557][50/63] lr: 1.2346e-03 eta: 6:40:56 time: 0.7283 data_time: 0.0213 memory: 14901 loss: 1.3264 loss_prob: 0.7193 loss_thr: 0.4852 loss_db: 0.1219 2022/11/02 18:15:57 - mmengine - INFO - Epoch(train) [557][55/63] lr: 1.2346e-03 eta: 6:40:56 time: 0.7392 data_time: 0.0282 memory: 14901 loss: 1.3784 loss_prob: 0.7627 loss_thr: 0.4909 loss_db: 0.1248 2022/11/02 18:16:00 - mmengine - INFO - Epoch(train) [557][60/63] lr: 1.2346e-03 eta: 6:40:50 time: 0.6191 data_time: 0.0204 memory: 14901 loss: 1.4290 loss_prob: 0.7980 loss_thr: 0.4996 loss_db: 0.1314 2022/11/02 18:16:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:16:08 - mmengine - INFO - Epoch(train) [558][5/63] lr: 1.2329e-03 eta: 6:40:50 time: 0.9203 data_time: 0.2950 memory: 14901 loss: 1.3094 loss_prob: 0.7186 loss_thr: 0.4723 loss_db: 0.1185 2022/11/02 18:16:11 - mmengine - INFO - Epoch(train) [558][10/63] lr: 1.2329e-03 eta: 6:40:44 time: 0.9231 data_time: 0.2955 memory: 14901 loss: 1.2145 loss_prob: 0.6527 loss_thr: 0.4582 loss_db: 0.1037 2022/11/02 18:16:14 - mmengine - INFO - Epoch(train) [558][15/63] lr: 1.2329e-03 eta: 6:40:44 time: 0.6063 data_time: 0.0112 memory: 14901 loss: 1.2216 loss_prob: 0.6548 loss_thr: 0.4556 loss_db: 0.1112 2022/11/02 18:16:17 - mmengine - INFO - Epoch(train) [558][20/63] lr: 1.2329e-03 eta: 6:40:38 time: 0.6002 data_time: 0.0125 memory: 14901 loss: 1.3194 loss_prob: 0.7039 loss_thr: 0.4913 loss_db: 0.1243 2022/11/02 18:16:20 - mmengine - INFO - Epoch(train) [558][25/63] lr: 1.2329e-03 eta: 6:40:38 time: 0.5774 data_time: 0.0191 memory: 14901 loss: 1.3184 loss_prob: 0.6984 loss_thr: 0.5005 loss_db: 0.1194 2022/11/02 18:16:23 - mmengine - INFO - Epoch(train) [558][30/63] lr: 1.2329e-03 eta: 6:40:32 time: 0.5343 data_time: 0.0366 memory: 14901 loss: 1.3094 loss_prob: 0.7016 loss_thr: 0.4923 loss_db: 0.1156 2022/11/02 18:16:25 - mmengine - INFO - Epoch(train) [558][35/63] lr: 1.2329e-03 eta: 6:40:32 time: 0.5623 data_time: 0.0308 memory: 14901 loss: 1.2804 loss_prob: 0.6874 loss_thr: 0.4760 loss_db: 0.1170 2022/11/02 18:16:29 - mmengine - INFO - Epoch(train) [558][40/63] lr: 1.2329e-03 eta: 6:40:26 time: 0.5979 data_time: 0.0171 memory: 14901 loss: 1.2604 loss_prob: 0.6714 loss_thr: 0.4711 loss_db: 0.1179 2022/11/02 18:16:33 - mmengine - INFO - Epoch(train) [558][45/63] lr: 1.2329e-03 eta: 6:40:26 time: 0.7479 data_time: 0.0144 memory: 14901 loss: 1.2827 loss_prob: 0.6869 loss_thr: 0.4832 loss_db: 0.1127 2022/11/02 18:16:37 - mmengine - INFO - Epoch(train) [558][50/63] lr: 1.2329e-03 eta: 6:40:22 time: 0.8043 data_time: 0.0246 memory: 14901 loss: 1.3732 loss_prob: 0.7592 loss_thr: 0.4916 loss_db: 0.1224 2022/11/02 18:16:39 - mmengine - INFO - Epoch(train) [558][55/63] lr: 1.2329e-03 eta: 6:40:22 time: 0.6566 data_time: 0.0249 memory: 14901 loss: 1.3422 loss_prob: 0.7395 loss_thr: 0.4786 loss_db: 0.1241 2022/11/02 18:16:43 - mmengine - INFO - Epoch(train) [558][60/63] lr: 1.2329e-03 eta: 6:40:16 time: 0.5937 data_time: 0.0147 memory: 14901 loss: 1.2553 loss_prob: 0.6750 loss_thr: 0.4656 loss_db: 0.1147 2022/11/02 18:16:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:16:52 - mmengine - INFO - Epoch(train) [559][5/63] lr: 1.2312e-03 eta: 6:40:16 time: 1.0889 data_time: 0.2966 memory: 14901 loss: 1.2934 loss_prob: 0.6984 loss_thr: 0.4785 loss_db: 0.1165 2022/11/02 18:16:55 - mmengine - INFO - Epoch(train) [559][10/63] lr: 1.2312e-03 eta: 6:40:12 time: 1.0801 data_time: 0.2944 memory: 14901 loss: 1.1623 loss_prob: 0.6173 loss_thr: 0.4394 loss_db: 0.1056 2022/11/02 18:16:58 - mmengine - INFO - Epoch(train) [559][15/63] lr: 1.2312e-03 eta: 6:40:12 time: 0.5559 data_time: 0.0111 memory: 14901 loss: 1.1773 loss_prob: 0.6272 loss_thr: 0.4431 loss_db: 0.1070 2022/11/02 18:17:01 - mmengine - INFO - Epoch(train) [559][20/63] lr: 1.2312e-03 eta: 6:40:06 time: 0.5441 data_time: 0.0130 memory: 14901 loss: 1.1897 loss_prob: 0.6338 loss_thr: 0.4486 loss_db: 0.1074 2022/11/02 18:17:05 - mmengine - INFO - Epoch(train) [559][25/63] lr: 1.2312e-03 eta: 6:40:06 time: 0.6872 data_time: 0.0342 memory: 14901 loss: 1.1567 loss_prob: 0.6145 loss_thr: 0.4366 loss_db: 0.1055 2022/11/02 18:17:08 - mmengine - INFO - Epoch(train) [559][30/63] lr: 1.2312e-03 eta: 6:40:01 time: 0.7127 data_time: 0.0441 memory: 14901 loss: 1.1171 loss_prob: 0.5885 loss_thr: 0.4275 loss_db: 0.1011 2022/11/02 18:17:11 - mmengine - INFO - Epoch(train) [559][35/63] lr: 1.2312e-03 eta: 6:40:01 time: 0.6649 data_time: 0.0240 memory: 14901 loss: 1.2229 loss_prob: 0.6506 loss_thr: 0.4625 loss_db: 0.1099 2022/11/02 18:17:14 - mmengine - INFO - Epoch(train) [559][40/63] lr: 1.2312e-03 eta: 6:39:55 time: 0.5984 data_time: 0.0145 memory: 14901 loss: 1.2556 loss_prob: 0.6742 loss_thr: 0.4662 loss_db: 0.1152 2022/11/02 18:17:17 - mmengine - INFO - Epoch(train) [559][45/63] lr: 1.2312e-03 eta: 6:39:55 time: 0.5543 data_time: 0.0134 memory: 14901 loss: 1.2637 loss_prob: 0.6847 loss_thr: 0.4613 loss_db: 0.1177 2022/11/02 18:17:21 - mmengine - INFO - Epoch(train) [559][50/63] lr: 1.2312e-03 eta: 6:39:51 time: 0.6962 data_time: 0.0284 memory: 14901 loss: 1.3193 loss_prob: 0.7144 loss_thr: 0.4831 loss_db: 0.1219 2022/11/02 18:17:24 - mmengine - INFO - Epoch(train) [559][55/63] lr: 1.2312e-03 eta: 6:39:51 time: 0.6779 data_time: 0.0309 memory: 14901 loss: 1.3087 loss_prob: 0.7226 loss_thr: 0.4660 loss_db: 0.1200 2022/11/02 18:17:27 - mmengine - INFO - Epoch(train) [559][60/63] lr: 1.2312e-03 eta: 6:39:45 time: 0.6460 data_time: 0.0130 memory: 14901 loss: 1.3627 loss_prob: 0.7655 loss_thr: 0.4710 loss_db: 0.1262 2022/11/02 18:17:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:17:36 - mmengine - INFO - Epoch(train) [560][5/63] lr: 1.2294e-03 eta: 6:39:45 time: 1.0833 data_time: 0.3007 memory: 14901 loss: 1.3216 loss_prob: 0.7121 loss_thr: 0.4870 loss_db: 0.1226 2022/11/02 18:17:39 - mmengine - INFO - Epoch(train) [560][10/63] lr: 1.2294e-03 eta: 6:39:41 time: 1.0498 data_time: 0.2999 memory: 14901 loss: 1.2735 loss_prob: 0.6788 loss_thr: 0.4776 loss_db: 0.1171 2022/11/02 18:17:42 - mmengine - INFO - Epoch(train) [560][15/63] lr: 1.2294e-03 eta: 6:39:41 time: 0.5785 data_time: 0.0086 memory: 14901 loss: 1.2396 loss_prob: 0.6690 loss_thr: 0.4562 loss_db: 0.1143 2022/11/02 18:17:46 - mmengine - INFO - Epoch(train) [560][20/63] lr: 1.2294e-03 eta: 6:39:35 time: 0.6026 data_time: 0.0112 memory: 14901 loss: 1.2491 loss_prob: 0.6704 loss_thr: 0.4650 loss_db: 0.1137 2022/11/02 18:17:49 - mmengine - INFO - Epoch(train) [560][25/63] lr: 1.2294e-03 eta: 6:39:35 time: 0.6530 data_time: 0.0367 memory: 14901 loss: 1.2663 loss_prob: 0.6752 loss_thr: 0.4750 loss_db: 0.1161 2022/11/02 18:17:52 - mmengine - INFO - Epoch(train) [560][30/63] lr: 1.2294e-03 eta: 6:39:29 time: 0.6132 data_time: 0.0440 memory: 14901 loss: 1.2237 loss_prob: 0.6507 loss_thr: 0.4594 loss_db: 0.1135 2022/11/02 18:17:54 - mmengine - INFO - Epoch(train) [560][35/63] lr: 1.2294e-03 eta: 6:39:29 time: 0.5585 data_time: 0.0207 memory: 14901 loss: 1.1983 loss_prob: 0.6401 loss_thr: 0.4485 loss_db: 0.1097 2022/11/02 18:17:58 - mmengine - INFO - Epoch(train) [560][40/63] lr: 1.2294e-03 eta: 6:39:23 time: 0.6180 data_time: 0.0100 memory: 14901 loss: 1.1993 loss_prob: 0.6352 loss_thr: 0.4543 loss_db: 0.1098 2022/11/02 18:18:02 - mmengine - INFO - Epoch(train) [560][45/63] lr: 1.2294e-03 eta: 6:39:23 time: 0.7568 data_time: 0.0151 memory: 14901 loss: 1.2211 loss_prob: 0.6434 loss_thr: 0.4659 loss_db: 0.1117 2022/11/02 18:18:05 - mmengine - INFO - Epoch(train) [560][50/63] lr: 1.2294e-03 eta: 6:39:19 time: 0.6993 data_time: 0.0280 memory: 14901 loss: 1.1812 loss_prob: 0.6229 loss_thr: 0.4504 loss_db: 0.1080 2022/11/02 18:18:07 - mmengine - INFO - Epoch(train) [560][55/63] lr: 1.2294e-03 eta: 6:39:19 time: 0.5717 data_time: 0.0286 memory: 14901 loss: 1.1415 loss_prob: 0.5941 loss_thr: 0.4452 loss_db: 0.1022 2022/11/02 18:18:11 - mmengine - INFO - Epoch(train) [560][60/63] lr: 1.2294e-03 eta: 6:39:13 time: 0.6238 data_time: 0.0164 memory: 14901 loss: 1.2339 loss_prob: 0.6452 loss_thr: 0.4779 loss_db: 0.1108 2022/11/02 18:18:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:18:13 - mmengine - INFO - Saving checkpoint at 560 epochs 2022/11/02 18:18:17 - mmengine - INFO - Epoch(val) [560][5/500] eta: 6:39:13 time: 0.0490 data_time: 0.0061 memory: 14901 2022/11/02 18:18:17 - mmengine - INFO - Epoch(val) [560][10/500] eta: 0:00:24 time: 0.0491 data_time: 0.0056 memory: 1008 2022/11/02 18:18:17 - mmengine - INFO - Epoch(val) [560][15/500] eta: 0:00:24 time: 0.0425 data_time: 0.0024 memory: 1008 2022/11/02 18:18:17 - mmengine - INFO - Epoch(val) [560][20/500] eta: 0:00:19 time: 0.0400 data_time: 0.0028 memory: 1008 2022/11/02 18:18:17 - mmengine - INFO - Epoch(val) [560][25/500] eta: 0:00:19 time: 0.0404 data_time: 0.0028 memory: 1008 2022/11/02 18:18:18 - mmengine - INFO - Epoch(val) [560][30/500] eta: 0:00:20 time: 0.0426 data_time: 0.0029 memory: 1008 2022/11/02 18:18:18 - mmengine - INFO - Epoch(val) [560][35/500] eta: 0:00:20 time: 0.0435 data_time: 0.0029 memory: 1008 2022/11/02 18:18:18 - mmengine - INFO - Epoch(val) [560][40/500] eta: 0:00:20 time: 0.0439 data_time: 0.0029 memory: 1008 2022/11/02 18:18:18 - mmengine - INFO - Epoch(val) [560][45/500] eta: 0:00:20 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/02 18:18:19 - mmengine - INFO - Epoch(val) [560][50/500] eta: 0:00:21 time: 0.0472 data_time: 0.0040 memory: 1008 2022/11/02 18:18:19 - mmengine - INFO - Epoch(val) [560][55/500] eta: 0:00:21 time: 0.0478 data_time: 0.0040 memory: 1008 2022/11/02 18:18:19 - mmengine - INFO - Epoch(val) [560][60/500] eta: 0:00:18 time: 0.0422 data_time: 0.0028 memory: 1008 2022/11/02 18:18:19 - mmengine - INFO - Epoch(val) [560][65/500] eta: 0:00:18 time: 0.0467 data_time: 0.0033 memory: 1008 2022/11/02 18:18:19 - mmengine - INFO - Epoch(val) [560][70/500] eta: 0:00:21 time: 0.0489 data_time: 0.0033 memory: 1008 2022/11/02 18:18:20 - mmengine - INFO - Epoch(val) [560][75/500] eta: 0:00:21 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/02 18:18:20 - mmengine - INFO - Epoch(val) [560][80/500] eta: 0:00:15 time: 0.0365 data_time: 0.0028 memory: 1008 2022/11/02 18:18:20 - mmengine - INFO - Epoch(val) [560][85/500] eta: 0:00:15 time: 0.0404 data_time: 0.0029 memory: 1008 2022/11/02 18:18:20 - mmengine - INFO - Epoch(val) [560][90/500] eta: 0:00:18 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/02 18:18:21 - mmengine - INFO - Epoch(val) [560][95/500] eta: 0:00:18 time: 0.0460 data_time: 0.0030 memory: 1008 2022/11/02 18:18:21 - mmengine - INFO - Epoch(val) [560][100/500] eta: 0:00:18 time: 0.0453 data_time: 0.0032 memory: 1008 2022/11/02 18:18:21 - mmengine - INFO - Epoch(val) [560][105/500] eta: 0:00:18 time: 0.0408 data_time: 0.0031 memory: 1008 2022/11/02 18:18:21 - mmengine - INFO - Epoch(val) [560][110/500] eta: 0:00:14 time: 0.0376 data_time: 0.0026 memory: 1008 2022/11/02 18:18:21 - mmengine - INFO - Epoch(val) [560][115/500] eta: 0:00:14 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 18:18:22 - mmengine - INFO - Epoch(val) [560][120/500] eta: 0:00:14 time: 0.0389 data_time: 0.0024 memory: 1008 2022/11/02 18:18:22 - mmengine - INFO - Epoch(val) [560][125/500] eta: 0:00:14 time: 0.0367 data_time: 0.0028 memory: 1008 2022/11/02 18:18:22 - mmengine - INFO - Epoch(val) [560][130/500] eta: 0:00:14 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 18:18:22 - mmengine - INFO - Epoch(val) [560][135/500] eta: 0:00:14 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 18:18:22 - mmengine - INFO - Epoch(val) [560][140/500] eta: 0:00:13 time: 0.0372 data_time: 0.0026 memory: 1008 2022/11/02 18:18:23 - mmengine - INFO - Epoch(val) [560][145/500] eta: 0:00:13 time: 0.0421 data_time: 0.0025 memory: 1008 2022/11/02 18:18:23 - mmengine - INFO - Epoch(val) [560][150/500] eta: 0:00:16 time: 0.0461 data_time: 0.0029 memory: 1008 2022/11/02 18:18:23 - mmengine - INFO - Epoch(val) [560][155/500] eta: 0:00:16 time: 0.0497 data_time: 0.0030 memory: 1008 2022/11/02 18:18:23 - mmengine - INFO - Epoch(val) [560][160/500] eta: 0:00:15 time: 0.0462 data_time: 0.0026 memory: 1008 2022/11/02 18:18:23 - mmengine - INFO - Epoch(val) [560][165/500] eta: 0:00:15 time: 0.0383 data_time: 0.0026 memory: 1008 2022/11/02 18:18:24 - mmengine - INFO - Epoch(val) [560][170/500] eta: 0:00:13 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 18:18:24 - mmengine - INFO - Epoch(val) [560][175/500] eta: 0:00:13 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 18:18:24 - mmengine - INFO - Epoch(val) [560][180/500] eta: 0:00:12 time: 0.0403 data_time: 0.0030 memory: 1008 2022/11/02 18:18:24 - mmengine - INFO - Epoch(val) [560][185/500] eta: 0:00:12 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/02 18:18:24 - mmengine - INFO - Epoch(val) [560][190/500] eta: 0:00:13 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 18:18:25 - mmengine - INFO - Epoch(val) [560][195/500] eta: 0:00:13 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 18:18:25 - mmengine - INFO - Epoch(val) [560][200/500] eta: 0:00:13 time: 0.0450 data_time: 0.0026 memory: 1008 2022/11/02 18:18:25 - mmengine - INFO - Epoch(val) [560][205/500] eta: 0:00:13 time: 0.0479 data_time: 0.0034 memory: 1008 2022/11/02 18:18:25 - mmengine - INFO - Epoch(val) [560][210/500] eta: 0:00:11 time: 0.0390 data_time: 0.0034 memory: 1008 2022/11/02 18:18:25 - mmengine - INFO - Epoch(val) [560][215/500] eta: 0:00:11 time: 0.0382 data_time: 0.0027 memory: 1008 2022/11/02 18:18:26 - mmengine - INFO - Epoch(val) [560][220/500] eta: 0:00:11 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 18:18:26 - mmengine - INFO - Epoch(val) [560][225/500] eta: 0:00:11 time: 0.0415 data_time: 0.0031 memory: 1008 2022/11/02 18:18:26 - mmengine - INFO - Epoch(val) [560][230/500] eta: 0:00:11 time: 0.0409 data_time: 0.0034 memory: 1008 2022/11/02 18:18:26 - mmengine - INFO - Epoch(val) [560][235/500] eta: 0:00:11 time: 0.0409 data_time: 0.0034 memory: 1008 2022/11/02 18:18:27 - mmengine - INFO - Epoch(val) [560][240/500] eta: 0:00:11 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/02 18:18:27 - mmengine - INFO - Epoch(val) [560][245/500] eta: 0:00:11 time: 0.0450 data_time: 0.0029 memory: 1008 2022/11/02 18:18:27 - mmengine - INFO - Epoch(val) [560][250/500] eta: 0:00:10 time: 0.0414 data_time: 0.0029 memory: 1008 2022/11/02 18:18:27 - mmengine - INFO - Epoch(val) [560][255/500] eta: 0:00:10 time: 0.0407 data_time: 0.0029 memory: 1008 2022/11/02 18:18:27 - mmengine - INFO - Epoch(val) [560][260/500] eta: 0:00:09 time: 0.0407 data_time: 0.0028 memory: 1008 2022/11/02 18:18:28 - mmengine - INFO - Epoch(val) [560][265/500] eta: 0:00:09 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 18:18:28 - mmengine - INFO - Epoch(val) [560][270/500] eta: 0:00:09 time: 0.0418 data_time: 0.0032 memory: 1008 2022/11/02 18:18:28 - mmengine - INFO - Epoch(val) [560][275/500] eta: 0:00:09 time: 0.0409 data_time: 0.0031 memory: 1008 2022/11/02 18:18:28 - mmengine - INFO - Epoch(val) [560][280/500] eta: 0:00:08 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 18:18:28 - mmengine - INFO - Epoch(val) [560][285/500] eta: 0:00:08 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 18:18:29 - mmengine - INFO - Epoch(val) [560][290/500] eta: 0:00:09 time: 0.0446 data_time: 0.0027 memory: 1008 2022/11/02 18:18:29 - mmengine - INFO - Epoch(val) [560][295/500] eta: 0:00:09 time: 0.0491 data_time: 0.0030 memory: 1008 2022/11/02 18:18:29 - mmengine - INFO - Epoch(val) [560][300/500] eta: 0:00:08 time: 0.0449 data_time: 0.0033 memory: 1008 2022/11/02 18:18:29 - mmengine - INFO - Epoch(val) [560][305/500] eta: 0:00:08 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 18:18:29 - mmengine - INFO - Epoch(val) [560][310/500] eta: 0:00:07 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/02 18:18:30 - mmengine - INFO - Epoch(val) [560][315/500] eta: 0:00:07 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 18:18:30 - mmengine - INFO - Epoch(val) [560][320/500] eta: 0:00:07 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/02 18:18:30 - mmengine - INFO - Epoch(val) [560][325/500] eta: 0:00:07 time: 0.0705 data_time: 0.0028 memory: 1008 2022/11/02 18:18:31 - mmengine - INFO - Epoch(val) [560][330/500] eta: 0:00:11 time: 0.0676 data_time: 0.0030 memory: 1008 2022/11/02 18:18:31 - mmengine - INFO - Epoch(val) [560][335/500] eta: 0:00:11 time: 0.0373 data_time: 0.0027 memory: 1008 2022/11/02 18:18:31 - mmengine - INFO - Epoch(val) [560][340/500] eta: 0:00:07 time: 0.0487 data_time: 0.0028 memory: 1008 2022/11/02 18:18:31 - mmengine - INFO - Epoch(val) [560][345/500] eta: 0:00:07 time: 0.0501 data_time: 0.0031 memory: 1008 2022/11/02 18:18:32 - mmengine - INFO - Epoch(val) [560][350/500] eta: 0:00:06 time: 0.0428 data_time: 0.0027 memory: 1008 2022/11/02 18:18:32 - mmengine - INFO - Epoch(val) [560][355/500] eta: 0:00:06 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 18:18:32 - mmengine - INFO - Epoch(val) [560][360/500] eta: 0:00:05 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 18:18:32 - mmengine - INFO - Epoch(val) [560][365/500] eta: 0:00:05 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 18:18:32 - mmengine - INFO - Epoch(val) [560][370/500] eta: 0:00:05 time: 0.0386 data_time: 0.0028 memory: 1008 2022/11/02 18:18:32 - mmengine - INFO - Epoch(val) [560][375/500] eta: 0:00:05 time: 0.0357 data_time: 0.0028 memory: 1008 2022/11/02 18:18:33 - mmengine - INFO - Epoch(val) [560][380/500] eta: 0:00:04 time: 0.0402 data_time: 0.0027 memory: 1008 2022/11/02 18:18:33 - mmengine - INFO - Epoch(val) [560][385/500] eta: 0:00:04 time: 0.0431 data_time: 0.0026 memory: 1008 2022/11/02 18:18:33 - mmengine - INFO - Epoch(val) [560][390/500] eta: 0:00:04 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/02 18:18:33 - mmengine - INFO - Epoch(val) [560][395/500] eta: 0:00:04 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 18:18:34 - mmengine - INFO - Epoch(val) [560][400/500] eta: 0:00:04 time: 0.0431 data_time: 0.0026 memory: 1008 2022/11/02 18:18:34 - mmengine - INFO - Epoch(val) [560][405/500] eta: 0:00:04 time: 0.0432 data_time: 0.0026 memory: 1008 2022/11/02 18:18:34 - mmengine - INFO - Epoch(val) [560][410/500] eta: 0:00:03 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/02 18:18:34 - mmengine - INFO - Epoch(val) [560][415/500] eta: 0:00:03 time: 0.0411 data_time: 0.0027 memory: 1008 2022/11/02 18:18:34 - mmengine - INFO - Epoch(val) [560][420/500] eta: 0:00:03 time: 0.0376 data_time: 0.0025 memory: 1008 2022/11/02 18:18:35 - mmengine - INFO - Epoch(val) [560][425/500] eta: 0:00:03 time: 0.0375 data_time: 0.0024 memory: 1008 2022/11/02 18:18:35 - mmengine - INFO - Epoch(val) [560][430/500] eta: 0:00:02 time: 0.0423 data_time: 0.0024 memory: 1008 2022/11/02 18:18:35 - mmengine - INFO - Epoch(val) [560][435/500] eta: 0:00:02 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 18:18:35 - mmengine - INFO - Epoch(val) [560][440/500] eta: 0:00:02 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 18:18:35 - mmengine - INFO - Epoch(val) [560][445/500] eta: 0:00:02 time: 0.0412 data_time: 0.0025 memory: 1008 2022/11/02 18:18:36 - mmengine - INFO - Epoch(val) [560][450/500] eta: 0:00:02 time: 0.0458 data_time: 0.0027 memory: 1008 2022/11/02 18:18:36 - mmengine - INFO - Epoch(val) [560][455/500] eta: 0:00:02 time: 0.0453 data_time: 0.0028 memory: 1008 2022/11/02 18:18:36 - mmengine - INFO - Epoch(val) [560][460/500] eta: 0:00:01 time: 0.0384 data_time: 0.0026 memory: 1008 2022/11/02 18:18:36 - mmengine - INFO - Epoch(val) [560][465/500] eta: 0:00:01 time: 0.0353 data_time: 0.0025 memory: 1008 2022/11/02 18:18:36 - mmengine - INFO - Epoch(val) [560][470/500] eta: 0:00:01 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/02 18:18:37 - mmengine - INFO - Epoch(val) [560][475/500] eta: 0:00:01 time: 0.0399 data_time: 0.0028 memory: 1008 2022/11/02 18:18:37 - mmengine - INFO - Epoch(val) [560][480/500] eta: 0:00:00 time: 0.0370 data_time: 0.0028 memory: 1008 2022/11/02 18:18:37 - mmengine - INFO - Epoch(val) [560][485/500] eta: 0:00:00 time: 0.0400 data_time: 0.0024 memory: 1008 2022/11/02 18:18:37 - mmengine - INFO - Epoch(val) [560][490/500] eta: 0:00:00 time: 0.0419 data_time: 0.0022 memory: 1008 2022/11/02 18:18:37 - mmengine - INFO - Epoch(val) [560][495/500] eta: 0:00:00 time: 0.0416 data_time: 0.0024 memory: 1008 2022/11/02 18:18:38 - mmengine - INFO - Epoch(val) [560][500/500] eta: 0:00:00 time: 0.0407 data_time: 0.0024 memory: 1008 2022/11/02 18:18:38 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8161, precision: 0.7464, hmean: 0.7797 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8161, precision: 0.7928, hmean: 0.8043 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8146, precision: 0.8198, hmean: 0.8172 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8108, precision: 0.8471, hmean: 0.8285 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7829, precision: 0.8813, hmean: 0.8292 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5888, precision: 0.9307, hmean: 0.7213 2022/11/02 18:18:38 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0327, precision: 0.9577, hmean: 0.0633 2022/11/02 18:18:38 - mmengine - INFO - Epoch(val) [560][500/500] icdar/precision: 0.8813 icdar/recall: 0.7829 icdar/hmean: 0.8292 2022/11/02 18:18:43 - mmengine - INFO - Epoch(train) [561][5/63] lr: 1.2277e-03 eta: 0:00:00 time: 0.8830 data_time: 0.2675 memory: 14901 loss: 1.2738 loss_prob: 0.6919 loss_thr: 0.4643 loss_db: 0.1176 2022/11/02 18:18:47 - mmengine - INFO - Epoch(train) [561][10/63] lr: 1.2277e-03 eta: 6:39:07 time: 0.8997 data_time: 0.2678 memory: 14901 loss: 1.2201 loss_prob: 0.6551 loss_thr: 0.4524 loss_db: 0.1126 2022/11/02 18:18:51 - mmengine - INFO - Epoch(train) [561][15/63] lr: 1.2277e-03 eta: 6:39:07 time: 0.8020 data_time: 0.0127 memory: 14901 loss: 1.2755 loss_prob: 0.6833 loss_thr: 0.4758 loss_db: 0.1164 2022/11/02 18:18:54 - mmengine - INFO - Epoch(train) [561][20/63] lr: 1.2277e-03 eta: 6:39:03 time: 0.7727 data_time: 0.0122 memory: 14901 loss: 1.3515 loss_prob: 0.7433 loss_thr: 0.4870 loss_db: 0.1212 2022/11/02 18:18:58 - mmengine - INFO - Epoch(train) [561][25/63] lr: 1.2277e-03 eta: 6:39:03 time: 0.6886 data_time: 0.0489 memory: 14901 loss: 1.2990 loss_prob: 0.7032 loss_thr: 0.4815 loss_db: 0.1143 2022/11/02 18:19:01 - mmengine - INFO - Epoch(train) [561][30/63] lr: 1.2277e-03 eta: 6:38:58 time: 0.6958 data_time: 0.0497 memory: 14901 loss: 1.2705 loss_prob: 0.6718 loss_thr: 0.4847 loss_db: 0.1139 2022/11/02 18:19:05 - mmengine - INFO - Epoch(train) [561][35/63] lr: 1.2277e-03 eta: 6:38:58 time: 0.6854 data_time: 0.0119 memory: 14901 loss: 1.2375 loss_prob: 0.6642 loss_thr: 0.4606 loss_db: 0.1127 2022/11/02 18:19:08 - mmengine - INFO - Epoch(train) [561][40/63] lr: 1.2277e-03 eta: 6:38:52 time: 0.6172 data_time: 0.0095 memory: 14901 loss: 1.2498 loss_prob: 0.6633 loss_thr: 0.4715 loss_db: 0.1150 2022/11/02 18:19:11 - mmengine - INFO - Epoch(train) [561][45/63] lr: 1.2277e-03 eta: 6:38:52 time: 0.5808 data_time: 0.0118 memory: 14901 loss: 1.3091 loss_prob: 0.7046 loss_thr: 0.4822 loss_db: 0.1223 2022/11/02 18:19:14 - mmengine - INFO - Epoch(train) [561][50/63] lr: 1.2277e-03 eta: 6:38:47 time: 0.6758 data_time: 0.0328 memory: 14901 loss: 1.2508 loss_prob: 0.6716 loss_thr: 0.4642 loss_db: 0.1150 2022/11/02 18:19:17 - mmengine - INFO - Epoch(train) [561][55/63] lr: 1.2277e-03 eta: 6:38:47 time: 0.6382 data_time: 0.0302 memory: 14901 loss: 1.1978 loss_prob: 0.6277 loss_thr: 0.4601 loss_db: 0.1100 2022/11/02 18:19:20 - mmengine - INFO - Epoch(train) [561][60/63] lr: 1.2277e-03 eta: 6:38:41 time: 0.5484 data_time: 0.0097 memory: 14901 loss: 1.1725 loss_prob: 0.6186 loss_thr: 0.4446 loss_db: 0.1093 2022/11/02 18:19:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:19:28 - mmengine - INFO - Epoch(train) [562][5/63] lr: 1.2260e-03 eta: 6:38:41 time: 0.9334 data_time: 0.2307 memory: 14901 loss: 1.2403 loss_prob: 0.6636 loss_thr: 0.4648 loss_db: 0.1119 2022/11/02 18:19:31 - mmengine - INFO - Epoch(train) [562][10/63] lr: 1.2260e-03 eta: 6:38:36 time: 0.9904 data_time: 0.2270 memory: 14901 loss: 1.2897 loss_prob: 0.6903 loss_thr: 0.4811 loss_db: 0.1183 2022/11/02 18:19:35 - mmengine - INFO - Epoch(train) [562][15/63] lr: 1.2260e-03 eta: 6:38:36 time: 0.7501 data_time: 0.0069 memory: 14901 loss: 1.3631 loss_prob: 0.7382 loss_thr: 0.4946 loss_db: 0.1302 2022/11/02 18:19:40 - mmengine - INFO - Epoch(train) [562][20/63] lr: 1.2260e-03 eta: 6:38:33 time: 0.8450 data_time: 0.0103 memory: 14901 loss: 1.2632 loss_prob: 0.6758 loss_thr: 0.4714 loss_db: 0.1160 2022/11/02 18:19:42 - mmengine - INFO - Epoch(train) [562][25/63] lr: 1.2260e-03 eta: 6:38:33 time: 0.6903 data_time: 0.0133 memory: 14901 loss: 1.2135 loss_prob: 0.6497 loss_thr: 0.4554 loss_db: 0.1084 2022/11/02 18:19:46 - mmengine - INFO - Epoch(train) [562][30/63] lr: 1.2260e-03 eta: 6:38:27 time: 0.6198 data_time: 0.0418 memory: 14901 loss: 1.2441 loss_prob: 0.6723 loss_thr: 0.4539 loss_db: 0.1179 2022/11/02 18:19:49 - mmengine - INFO - Epoch(train) [562][35/63] lr: 1.2260e-03 eta: 6:38:27 time: 0.6747 data_time: 0.0399 memory: 14901 loss: 1.2911 loss_prob: 0.6995 loss_thr: 0.4722 loss_db: 0.1193 2022/11/02 18:19:52 - mmengine - INFO - Epoch(train) [562][40/63] lr: 1.2260e-03 eta: 6:38:21 time: 0.5817 data_time: 0.0118 memory: 14901 loss: 1.3310 loss_prob: 0.7262 loss_thr: 0.4846 loss_db: 0.1203 2022/11/02 18:19:55 - mmengine - INFO - Epoch(train) [562][45/63] lr: 1.2260e-03 eta: 6:38:21 time: 0.5775 data_time: 0.0152 memory: 14901 loss: 1.3139 loss_prob: 0.6988 loss_thr: 0.4967 loss_db: 0.1184 2022/11/02 18:19:58 - mmengine - INFO - Epoch(train) [562][50/63] lr: 1.2260e-03 eta: 6:38:15 time: 0.6352 data_time: 0.0307 memory: 14901 loss: 1.2371 loss_prob: 0.6469 loss_thr: 0.4792 loss_db: 0.1110 2022/11/02 18:20:01 - mmengine - INFO - Epoch(train) [562][55/63] lr: 1.2260e-03 eta: 6:38:15 time: 0.6445 data_time: 0.0289 memory: 14901 loss: 1.2054 loss_prob: 0.6353 loss_thr: 0.4602 loss_db: 0.1099 2022/11/02 18:20:04 - mmengine - INFO - Epoch(train) [562][60/63] lr: 1.2260e-03 eta: 6:38:10 time: 0.6325 data_time: 0.0123 memory: 14901 loss: 1.2664 loss_prob: 0.6643 loss_thr: 0.4885 loss_db: 0.1136 2022/11/02 18:20:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:20:13 - mmengine - INFO - Epoch(train) [563][5/63] lr: 1.2243e-03 eta: 6:38:10 time: 0.9179 data_time: 0.2931 memory: 14901 loss: 1.3594 loss_prob: 0.7416 loss_thr: 0.4928 loss_db: 0.1250 2022/11/02 18:20:16 - mmengine - INFO - Epoch(train) [563][10/63] lr: 1.2243e-03 eta: 6:38:04 time: 0.9317 data_time: 0.2918 memory: 14901 loss: 1.2069 loss_prob: 0.6465 loss_thr: 0.4486 loss_db: 0.1118 2022/11/02 18:20:20 - mmengine - INFO - Epoch(train) [563][15/63] lr: 1.2243e-03 eta: 6:38:04 time: 0.7095 data_time: 0.0097 memory: 14901 loss: 1.1871 loss_prob: 0.6328 loss_thr: 0.4447 loss_db: 0.1096 2022/11/02 18:20:23 - mmengine - INFO - Epoch(train) [563][20/63] lr: 1.2243e-03 eta: 6:37:59 time: 0.6932 data_time: 0.0113 memory: 14901 loss: 1.3580 loss_prob: 0.7462 loss_thr: 0.4882 loss_db: 0.1235 2022/11/02 18:20:26 - mmengine - INFO - Epoch(train) [563][25/63] lr: 1.2243e-03 eta: 6:37:59 time: 0.5931 data_time: 0.0373 memory: 14901 loss: 1.3437 loss_prob: 0.7412 loss_thr: 0.4810 loss_db: 0.1215 2022/11/02 18:20:29 - mmengine - INFO - Epoch(train) [563][30/63] lr: 1.2243e-03 eta: 6:37:54 time: 0.6277 data_time: 0.0473 memory: 14901 loss: 1.1716 loss_prob: 0.6255 loss_thr: 0.4390 loss_db: 0.1070 2022/11/02 18:20:32 - mmengine - INFO - Epoch(train) [563][35/63] lr: 1.2243e-03 eta: 6:37:54 time: 0.6446 data_time: 0.0230 memory: 14901 loss: 1.1463 loss_prob: 0.5945 loss_thr: 0.4478 loss_db: 0.1040 2022/11/02 18:20:35 - mmengine - INFO - Epoch(train) [563][40/63] lr: 1.2243e-03 eta: 6:37:48 time: 0.5923 data_time: 0.0100 memory: 14901 loss: 1.1614 loss_prob: 0.6118 loss_thr: 0.4445 loss_db: 0.1050 2022/11/02 18:20:38 - mmengine - INFO - Epoch(train) [563][45/63] lr: 1.2243e-03 eta: 6:37:48 time: 0.6166 data_time: 0.0105 memory: 14901 loss: 1.1793 loss_prob: 0.6315 loss_thr: 0.4410 loss_db: 0.1068 2022/11/02 18:20:41 - mmengine - INFO - Epoch(train) [563][50/63] lr: 1.2243e-03 eta: 6:37:42 time: 0.6378 data_time: 0.0357 memory: 14901 loss: 1.1853 loss_prob: 0.6322 loss_thr: 0.4459 loss_db: 0.1073 2022/11/02 18:20:44 - mmengine - INFO - Epoch(train) [563][55/63] lr: 1.2243e-03 eta: 6:37:42 time: 0.5697 data_time: 0.0308 memory: 14901 loss: 1.1848 loss_prob: 0.6285 loss_thr: 0.4472 loss_db: 0.1092 2022/11/02 18:20:47 - mmengine - INFO - Epoch(train) [563][60/63] lr: 1.2243e-03 eta: 6:37:36 time: 0.5815 data_time: 0.0086 memory: 14901 loss: 1.2261 loss_prob: 0.6595 loss_thr: 0.4524 loss_db: 0.1142 2022/11/02 18:20:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:20:54 - mmengine - INFO - Epoch(train) [564][5/63] lr: 1.2225e-03 eta: 6:37:36 time: 0.7597 data_time: 0.2563 memory: 14901 loss: 1.2921 loss_prob: 0.7084 loss_thr: 0.4657 loss_db: 0.1180 2022/11/02 18:20:57 - mmengine - INFO - Epoch(train) [564][10/63] lr: 1.2225e-03 eta: 6:37:29 time: 0.8477 data_time: 0.2574 memory: 14901 loss: 1.2404 loss_prob: 0.6544 loss_thr: 0.4725 loss_db: 0.1136 2022/11/02 18:21:01 - mmengine - INFO - Epoch(train) [564][15/63] lr: 1.2225e-03 eta: 6:37:29 time: 0.7000 data_time: 0.0113 memory: 14901 loss: 1.1906 loss_prob: 0.6166 loss_thr: 0.4669 loss_db: 0.1071 2022/11/02 18:21:03 - mmengine - INFO - Epoch(train) [564][20/63] lr: 1.2225e-03 eta: 6:37:24 time: 0.6509 data_time: 0.0072 memory: 14901 loss: 1.1990 loss_prob: 0.6368 loss_thr: 0.4546 loss_db: 0.1076 2022/11/02 18:21:07 - mmengine - INFO - Epoch(train) [564][25/63] lr: 1.2225e-03 eta: 6:37:24 time: 0.6664 data_time: 0.0182 memory: 14901 loss: 1.2178 loss_prob: 0.6552 loss_thr: 0.4500 loss_db: 0.1125 2022/11/02 18:21:10 - mmengine - INFO - Epoch(train) [564][30/63] lr: 1.2225e-03 eta: 6:37:19 time: 0.6787 data_time: 0.0484 memory: 14901 loss: 1.2820 loss_prob: 0.7025 loss_thr: 0.4615 loss_db: 0.1181 2022/11/02 18:21:13 - mmengine - INFO - Epoch(train) [564][35/63] lr: 1.2225e-03 eta: 6:37:19 time: 0.5621 data_time: 0.0391 memory: 14901 loss: 1.3267 loss_prob: 0.7249 loss_thr: 0.4825 loss_db: 0.1192 2022/11/02 18:21:16 - mmengine - INFO - Epoch(train) [564][40/63] lr: 1.2225e-03 eta: 6:37:13 time: 0.5763 data_time: 0.0121 memory: 14901 loss: 1.2786 loss_prob: 0.6868 loss_thr: 0.4760 loss_db: 0.1159 2022/11/02 18:21:19 - mmengine - INFO - Epoch(train) [564][45/63] lr: 1.2225e-03 eta: 6:37:13 time: 0.5643 data_time: 0.0121 memory: 14901 loss: 1.2668 loss_prob: 0.6807 loss_thr: 0.4717 loss_db: 0.1145 2022/11/02 18:21:22 - mmengine - INFO - Epoch(train) [564][50/63] lr: 1.2225e-03 eta: 6:37:07 time: 0.5695 data_time: 0.0342 memory: 14901 loss: 1.2705 loss_prob: 0.6740 loss_thr: 0.4823 loss_db: 0.1142 2022/11/02 18:21:25 - mmengine - INFO - Epoch(train) [564][55/63] lr: 1.2225e-03 eta: 6:37:07 time: 0.6512 data_time: 0.0343 memory: 14901 loss: 1.1854 loss_prob: 0.6234 loss_thr: 0.4555 loss_db: 0.1065 2022/11/02 18:21:28 - mmengine - INFO - Epoch(train) [564][60/63] lr: 1.2225e-03 eta: 6:37:02 time: 0.6927 data_time: 0.0110 memory: 14901 loss: 1.1365 loss_prob: 0.5974 loss_thr: 0.4378 loss_db: 0.1013 2022/11/02 18:21:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:21:36 - mmengine - INFO - Epoch(train) [565][5/63] lr: 1.2208e-03 eta: 6:37:02 time: 0.9008 data_time: 0.2175 memory: 14901 loss: 1.2249 loss_prob: 0.6642 loss_thr: 0.4453 loss_db: 0.1154 2022/11/02 18:21:41 - mmengine - INFO - Epoch(train) [565][10/63] lr: 1.2208e-03 eta: 6:36:57 time: 1.0368 data_time: 0.2317 memory: 14901 loss: 1.1639 loss_prob: 0.6300 loss_thr: 0.4257 loss_db: 0.1081 2022/11/02 18:21:44 - mmengine - INFO - Epoch(train) [565][15/63] lr: 1.2208e-03 eta: 6:36:57 time: 0.8222 data_time: 0.0244 memory: 14901 loss: 1.2103 loss_prob: 0.6438 loss_thr: 0.4586 loss_db: 0.1079 2022/11/02 18:21:48 - mmengine - INFO - Epoch(train) [565][20/63] lr: 1.2208e-03 eta: 6:36:52 time: 0.7228 data_time: 0.0114 memory: 14901 loss: 1.2535 loss_prob: 0.6708 loss_thr: 0.4673 loss_db: 0.1154 2022/11/02 18:21:52 - mmengine - INFO - Epoch(train) [565][25/63] lr: 1.2208e-03 eta: 6:36:52 time: 0.7761 data_time: 0.0259 memory: 14901 loss: 1.1571 loss_prob: 0.6136 loss_thr: 0.4376 loss_db: 0.1058 2022/11/02 18:21:56 - mmengine - INFO - Epoch(train) [565][30/63] lr: 1.2208e-03 eta: 6:36:49 time: 0.7776 data_time: 0.0595 memory: 14901 loss: 1.1949 loss_prob: 0.6203 loss_thr: 0.4682 loss_db: 0.1064 2022/11/02 18:21:59 - mmengine - INFO - Epoch(train) [565][35/63] lr: 1.2208e-03 eta: 6:36:49 time: 0.7239 data_time: 0.0449 memory: 14901 loss: 1.2332 loss_prob: 0.6399 loss_thr: 0.4830 loss_db: 0.1102 2022/11/02 18:22:02 - mmengine - INFO - Epoch(train) [565][40/63] lr: 1.2208e-03 eta: 6:36:43 time: 0.6447 data_time: 0.0094 memory: 14901 loss: 1.1718 loss_prob: 0.6099 loss_thr: 0.4559 loss_db: 0.1060 2022/11/02 18:22:05 - mmengine - INFO - Epoch(train) [565][45/63] lr: 1.2208e-03 eta: 6:36:43 time: 0.5672 data_time: 0.0103 memory: 14901 loss: 1.2333 loss_prob: 0.6579 loss_thr: 0.4647 loss_db: 0.1107 2022/11/02 18:22:08 - mmengine - INFO - Epoch(train) [565][50/63] lr: 1.2208e-03 eta: 6:36:38 time: 0.6530 data_time: 0.0247 memory: 14901 loss: 1.2798 loss_prob: 0.6839 loss_thr: 0.4823 loss_db: 0.1136 2022/11/02 18:22:11 - mmengine - INFO - Epoch(train) [565][55/63] lr: 1.2208e-03 eta: 6:36:38 time: 0.5855 data_time: 0.0264 memory: 14901 loss: 1.2837 loss_prob: 0.6985 loss_thr: 0.4658 loss_db: 0.1194 2022/11/02 18:22:14 - mmengine - INFO - Epoch(train) [565][60/63] lr: 1.2208e-03 eta: 6:36:31 time: 0.5409 data_time: 0.0111 memory: 14901 loss: 1.3020 loss_prob: 0.7247 loss_thr: 0.4540 loss_db: 0.1233 2022/11/02 18:22:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:22:21 - mmengine - INFO - Epoch(train) [566][5/63] lr: 1.2191e-03 eta: 6:36:31 time: 0.8797 data_time: 0.2122 memory: 14901 loss: 1.3484 loss_prob: 0.7478 loss_thr: 0.4775 loss_db: 0.1231 2022/11/02 18:22:24 - mmengine - INFO - Epoch(train) [566][10/63] lr: 1.2191e-03 eta: 6:36:25 time: 0.9150 data_time: 0.2152 memory: 14901 loss: 1.4177 loss_prob: 0.8067 loss_thr: 0.4771 loss_db: 0.1339 2022/11/02 18:22:27 - mmengine - INFO - Epoch(train) [566][15/63] lr: 1.2191e-03 eta: 6:36:25 time: 0.5683 data_time: 0.0162 memory: 14901 loss: 1.3489 loss_prob: 0.7476 loss_thr: 0.4745 loss_db: 0.1268 2022/11/02 18:22:30 - mmengine - INFO - Epoch(train) [566][20/63] lr: 1.2191e-03 eta: 6:36:19 time: 0.5362 data_time: 0.0102 memory: 14901 loss: 1.3388 loss_prob: 0.7157 loss_thr: 0.5012 loss_db: 0.1219 2022/11/02 18:22:32 - mmengine - INFO - Epoch(train) [566][25/63] lr: 1.2191e-03 eta: 6:36:19 time: 0.5272 data_time: 0.0183 memory: 14901 loss: 1.4169 loss_prob: 0.7770 loss_thr: 0.5087 loss_db: 0.1313 2022/11/02 18:22:35 - mmengine - INFO - Epoch(train) [566][30/63] lr: 1.2191e-03 eta: 6:36:12 time: 0.5575 data_time: 0.0375 memory: 14901 loss: 1.5472 loss_prob: 0.9027 loss_thr: 0.4973 loss_db: 0.1471 2022/11/02 18:22:38 - mmengine - INFO - Epoch(train) [566][35/63] lr: 1.2191e-03 eta: 6:36:12 time: 0.5567 data_time: 0.0292 memory: 14901 loss: 1.4441 loss_prob: 0.8309 loss_thr: 0.4772 loss_db: 0.1359 2022/11/02 18:22:41 - mmengine - INFO - Epoch(train) [566][40/63] lr: 1.2191e-03 eta: 6:36:06 time: 0.5538 data_time: 0.0094 memory: 14901 loss: 1.3752 loss_prob: 0.7741 loss_thr: 0.4755 loss_db: 0.1255 2022/11/02 18:22:44 - mmengine - INFO - Epoch(train) [566][45/63] lr: 1.2191e-03 eta: 6:36:06 time: 0.5611 data_time: 0.0101 memory: 14901 loss: 1.3451 loss_prob: 0.7526 loss_thr: 0.4693 loss_db: 0.1231 2022/11/02 18:22:46 - mmengine - INFO - Epoch(train) [566][50/63] lr: 1.2191e-03 eta: 6:36:00 time: 0.5662 data_time: 0.0291 memory: 14901 loss: 1.2823 loss_prob: 0.6832 loss_thr: 0.4784 loss_db: 0.1207 2022/11/02 18:22:49 - mmengine - INFO - Epoch(train) [566][55/63] lr: 1.2191e-03 eta: 6:36:00 time: 0.5516 data_time: 0.0323 memory: 14901 loss: 1.4875 loss_prob: 0.8369 loss_thr: 0.5122 loss_db: 0.1384 2022/11/02 18:22:52 - mmengine - INFO - Epoch(train) [566][60/63] lr: 1.2191e-03 eta: 6:35:53 time: 0.5796 data_time: 0.0189 memory: 14901 loss: 1.4438 loss_prob: 0.8028 loss_thr: 0.5120 loss_db: 0.1289 2022/11/02 18:22:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:23:01 - mmengine - INFO - Epoch(train) [567][5/63] lr: 1.2173e-03 eta: 6:35:53 time: 1.0480 data_time: 0.2656 memory: 14901 loss: 1.3688 loss_prob: 0.7277 loss_thr: 0.5159 loss_db: 0.1252 2022/11/02 18:23:04 - mmengine - INFO - Epoch(train) [567][10/63] lr: 1.2173e-03 eta: 6:35:48 time: 0.9589 data_time: 0.2737 memory: 14901 loss: 1.3767 loss_prob: 0.7420 loss_thr: 0.5068 loss_db: 0.1280 2022/11/02 18:23:07 - mmengine - INFO - Epoch(train) [567][15/63] lr: 1.2173e-03 eta: 6:35:48 time: 0.5677 data_time: 0.0194 memory: 14901 loss: 1.3427 loss_prob: 0.7427 loss_thr: 0.4759 loss_db: 0.1241 2022/11/02 18:23:11 - mmengine - INFO - Epoch(train) [567][20/63] lr: 1.2173e-03 eta: 6:35:43 time: 0.6551 data_time: 0.0132 memory: 14901 loss: 1.2976 loss_prob: 0.7151 loss_thr: 0.4658 loss_db: 0.1167 2022/11/02 18:23:14 - mmengine - INFO - Epoch(train) [567][25/63] lr: 1.2173e-03 eta: 6:35:43 time: 0.7251 data_time: 0.0177 memory: 14901 loss: 1.3340 loss_prob: 0.7126 loss_thr: 0.5002 loss_db: 0.1212 2022/11/02 18:23:18 - mmengine - INFO - Epoch(train) [567][30/63] lr: 1.2173e-03 eta: 6:35:38 time: 0.7043 data_time: 0.0320 memory: 14901 loss: 1.3983 loss_prob: 0.7580 loss_thr: 0.5075 loss_db: 0.1328 2022/11/02 18:23:21 - mmengine - INFO - Epoch(train) [567][35/63] lr: 1.2173e-03 eta: 6:35:38 time: 0.6176 data_time: 0.0358 memory: 14901 loss: 1.2520 loss_prob: 0.6735 loss_thr: 0.4612 loss_db: 0.1172 2022/11/02 18:23:23 - mmengine - INFO - Epoch(train) [567][40/63] lr: 1.2173e-03 eta: 6:35:31 time: 0.5446 data_time: 0.0204 memory: 14901 loss: 1.1738 loss_prob: 0.6174 loss_thr: 0.4531 loss_db: 0.1032 2022/11/02 18:23:26 - mmengine - INFO - Epoch(train) [567][45/63] lr: 1.2173e-03 eta: 6:35:31 time: 0.5280 data_time: 0.0114 memory: 14901 loss: 1.2139 loss_prob: 0.6450 loss_thr: 0.4602 loss_db: 0.1087 2022/11/02 18:23:29 - mmengine - INFO - Epoch(train) [567][50/63] lr: 1.2173e-03 eta: 6:35:25 time: 0.6070 data_time: 0.0163 memory: 14901 loss: 1.2783 loss_prob: 0.6879 loss_thr: 0.4710 loss_db: 0.1195 2022/11/02 18:23:32 - mmengine - INFO - Epoch(train) [567][55/63] lr: 1.2173e-03 eta: 6:35:25 time: 0.6372 data_time: 0.0301 memory: 14901 loss: 1.2902 loss_prob: 0.6943 loss_thr: 0.4785 loss_db: 0.1174 2022/11/02 18:23:36 - mmengine - INFO - Epoch(train) [567][60/63] lr: 1.2173e-03 eta: 6:35:20 time: 0.6638 data_time: 0.0299 memory: 14901 loss: 1.2420 loss_prob: 0.6710 loss_thr: 0.4608 loss_db: 0.1102 2022/11/02 18:23:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:23:44 - mmengine - INFO - Epoch(train) [568][5/63] lr: 1.2156e-03 eta: 6:35:20 time: 0.9664 data_time: 0.2575 memory: 14901 loss: 1.2831 loss_prob: 0.6945 loss_thr: 0.4695 loss_db: 0.1191 2022/11/02 18:23:46 - mmengine - INFO - Epoch(train) [568][10/63] lr: 1.2156e-03 eta: 6:35:14 time: 0.8943 data_time: 0.2569 memory: 14901 loss: 1.1507 loss_prob: 0.5981 loss_thr: 0.4462 loss_db: 0.1064 2022/11/02 18:23:49 - mmengine - INFO - Epoch(train) [568][15/63] lr: 1.2156e-03 eta: 6:35:14 time: 0.5297 data_time: 0.0109 memory: 14901 loss: 1.2788 loss_prob: 0.6908 loss_thr: 0.4725 loss_db: 0.1155 2022/11/02 18:23:51 - mmengine - INFO - Epoch(train) [568][20/63] lr: 1.2156e-03 eta: 6:35:07 time: 0.4969 data_time: 0.0102 memory: 14901 loss: 1.3450 loss_prob: 0.7383 loss_thr: 0.4824 loss_db: 0.1243 2022/11/02 18:23:54 - mmengine - INFO - Epoch(train) [568][25/63] lr: 1.2156e-03 eta: 6:35:07 time: 0.5297 data_time: 0.0382 memory: 14901 loss: 1.3028 loss_prob: 0.7005 loss_thr: 0.4803 loss_db: 0.1221 2022/11/02 18:23:57 - mmengine - INFO - Epoch(train) [568][30/63] lr: 1.2156e-03 eta: 6:35:00 time: 0.5471 data_time: 0.0410 memory: 14901 loss: 1.4042 loss_prob: 0.7710 loss_thr: 0.5026 loss_db: 0.1306 2022/11/02 18:24:00 - mmengine - INFO - Epoch(train) [568][35/63] lr: 1.2156e-03 eta: 6:35:00 time: 0.5252 data_time: 0.0160 memory: 14901 loss: 1.4634 loss_prob: 0.8120 loss_thr: 0.5159 loss_db: 0.1355 2022/11/02 18:24:02 - mmengine - INFO - Epoch(train) [568][40/63] lr: 1.2156e-03 eta: 6:34:54 time: 0.5576 data_time: 0.0123 memory: 14901 loss: 1.3050 loss_prob: 0.7044 loss_thr: 0.4811 loss_db: 0.1195 2022/11/02 18:24:05 - mmengine - INFO - Epoch(train) [568][45/63] lr: 1.2156e-03 eta: 6:34:54 time: 0.5236 data_time: 0.0097 memory: 14901 loss: 1.1856 loss_prob: 0.6255 loss_thr: 0.4515 loss_db: 0.1087 2022/11/02 18:24:07 - mmengine - INFO - Epoch(train) [568][50/63] lr: 1.2156e-03 eta: 6:34:47 time: 0.5030 data_time: 0.0300 memory: 14901 loss: 1.2117 loss_prob: 0.6448 loss_thr: 0.4543 loss_db: 0.1126 2022/11/02 18:24:10 - mmengine - INFO - Epoch(train) [568][55/63] lr: 1.2156e-03 eta: 6:34:47 time: 0.5112 data_time: 0.0340 memory: 14901 loss: 1.2863 loss_prob: 0.7144 loss_thr: 0.4552 loss_db: 0.1168 2022/11/02 18:24:13 - mmengine - INFO - Epoch(train) [568][60/63] lr: 1.2156e-03 eta: 6:34:40 time: 0.5336 data_time: 0.0145 memory: 14901 loss: 1.2393 loss_prob: 0.6733 loss_thr: 0.4566 loss_db: 0.1094 2022/11/02 18:24:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:24:20 - mmengine - INFO - Epoch(train) [569][5/63] lr: 1.2139e-03 eta: 6:34:40 time: 0.8837 data_time: 0.2060 memory: 14901 loss: 1.1967 loss_prob: 0.6347 loss_thr: 0.4520 loss_db: 0.1101 2022/11/02 18:24:24 - mmengine - INFO - Epoch(train) [569][10/63] lr: 1.2139e-03 eta: 6:34:35 time: 0.9360 data_time: 0.2125 memory: 14901 loss: 1.2832 loss_prob: 0.7031 loss_thr: 0.4625 loss_db: 0.1177 2022/11/02 18:24:26 - mmengine - INFO - Epoch(train) [569][15/63] lr: 1.2139e-03 eta: 6:34:35 time: 0.5815 data_time: 0.0122 memory: 14901 loss: 1.2725 loss_prob: 0.6843 loss_thr: 0.4749 loss_db: 0.1133 2022/11/02 18:24:29 - mmengine - INFO - Epoch(train) [569][20/63] lr: 1.2139e-03 eta: 6:34:28 time: 0.5310 data_time: 0.0086 memory: 14901 loss: 1.3103 loss_prob: 0.6931 loss_thr: 0.4994 loss_db: 0.1178 2022/11/02 18:24:32 - mmengine - INFO - Epoch(train) [569][25/63] lr: 1.2139e-03 eta: 6:34:28 time: 0.5688 data_time: 0.0264 memory: 14901 loss: 1.2726 loss_prob: 0.6695 loss_thr: 0.4854 loss_db: 0.1177 2022/11/02 18:24:35 - mmengine - INFO - Epoch(train) [569][30/63] lr: 1.2139e-03 eta: 6:34:22 time: 0.6067 data_time: 0.0412 memory: 14901 loss: 1.2346 loss_prob: 0.6497 loss_thr: 0.4717 loss_db: 0.1132 2022/11/02 18:24:38 - mmengine - INFO - Epoch(train) [569][35/63] lr: 1.2139e-03 eta: 6:34:22 time: 0.5673 data_time: 0.0235 memory: 14901 loss: 1.2541 loss_prob: 0.6661 loss_thr: 0.4753 loss_db: 0.1128 2022/11/02 18:24:40 - mmengine - INFO - Epoch(train) [569][40/63] lr: 1.2139e-03 eta: 6:34:16 time: 0.5560 data_time: 0.0080 memory: 14901 loss: 1.2733 loss_prob: 0.6884 loss_thr: 0.4683 loss_db: 0.1166 2022/11/02 18:24:43 - mmengine - INFO - Epoch(train) [569][45/63] lr: 1.2139e-03 eta: 6:34:16 time: 0.5836 data_time: 0.0115 memory: 14901 loss: 1.2092 loss_prob: 0.6466 loss_thr: 0.4543 loss_db: 0.1082 2022/11/02 18:24:46 - mmengine - INFO - Epoch(train) [569][50/63] lr: 1.2139e-03 eta: 6:34:10 time: 0.6006 data_time: 0.0167 memory: 14901 loss: 1.1226 loss_prob: 0.5819 loss_thr: 0.4427 loss_db: 0.0980 2022/11/02 18:24:49 - mmengine - INFO - Epoch(train) [569][55/63] lr: 1.2139e-03 eta: 6:34:10 time: 0.6009 data_time: 0.0279 memory: 14901 loss: 1.1453 loss_prob: 0.5965 loss_thr: 0.4449 loss_db: 0.1039 2022/11/02 18:24:52 - mmengine - INFO - Epoch(train) [569][60/63] lr: 1.2139e-03 eta: 6:34:04 time: 0.5830 data_time: 0.0242 memory: 14901 loss: 1.2646 loss_prob: 0.6845 loss_thr: 0.4634 loss_db: 0.1167 2022/11/02 18:24:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:25:00 - mmengine - INFO - Epoch(train) [570][5/63] lr: 1.2121e-03 eta: 6:34:04 time: 0.8838 data_time: 0.2823 memory: 14901 loss: 1.3172 loss_prob: 0.7226 loss_thr: 0.4747 loss_db: 0.1198 2022/11/02 18:25:03 - mmengine - INFO - Epoch(train) [570][10/63] lr: 1.2121e-03 eta: 6:33:57 time: 0.8815 data_time: 0.2847 memory: 14901 loss: 1.2839 loss_prob: 0.7005 loss_thr: 0.4660 loss_db: 0.1174 2022/11/02 18:25:05 - mmengine - INFO - Epoch(train) [570][15/63] lr: 1.2121e-03 eta: 6:33:57 time: 0.5489 data_time: 0.0120 memory: 14901 loss: 1.2500 loss_prob: 0.6707 loss_thr: 0.4619 loss_db: 0.1174 2022/11/02 18:25:08 - mmengine - INFO - Epoch(train) [570][20/63] lr: 1.2121e-03 eta: 6:33:51 time: 0.5614 data_time: 0.0093 memory: 14901 loss: 1.2214 loss_prob: 0.6443 loss_thr: 0.4640 loss_db: 0.1131 2022/11/02 18:25:11 - mmengine - INFO - Epoch(train) [570][25/63] lr: 1.2121e-03 eta: 6:33:51 time: 0.5605 data_time: 0.0193 memory: 14901 loss: 1.2343 loss_prob: 0.6520 loss_thr: 0.4715 loss_db: 0.1107 2022/11/02 18:25:14 - mmengine - INFO - Epoch(train) [570][30/63] lr: 1.2121e-03 eta: 6:33:45 time: 0.5691 data_time: 0.0438 memory: 14901 loss: 1.2802 loss_prob: 0.6945 loss_thr: 0.4678 loss_db: 0.1179 2022/11/02 18:25:17 - mmengine - INFO - Epoch(train) [570][35/63] lr: 1.2121e-03 eta: 6:33:45 time: 0.5953 data_time: 0.0325 memory: 14901 loss: 1.2568 loss_prob: 0.6871 loss_thr: 0.4506 loss_db: 0.1192 2022/11/02 18:25:20 - mmengine - INFO - Epoch(train) [570][40/63] lr: 1.2121e-03 eta: 6:33:39 time: 0.6177 data_time: 0.0100 memory: 14901 loss: 1.2159 loss_prob: 0.6542 loss_thr: 0.4496 loss_db: 0.1121 2022/11/02 18:25:23 - mmengine - INFO - Epoch(train) [570][45/63] lr: 1.2121e-03 eta: 6:33:39 time: 0.5650 data_time: 0.0111 memory: 14901 loss: 1.1781 loss_prob: 0.6256 loss_thr: 0.4458 loss_db: 0.1067 2022/11/02 18:25:26 - mmengine - INFO - Epoch(train) [570][50/63] lr: 1.2121e-03 eta: 6:33:33 time: 0.5661 data_time: 0.0503 memory: 14901 loss: 1.1712 loss_prob: 0.6184 loss_thr: 0.4467 loss_db: 0.1060 2022/11/02 18:25:28 - mmengine - INFO - Epoch(train) [570][55/63] lr: 1.2121e-03 eta: 6:33:33 time: 0.5538 data_time: 0.0502 memory: 14901 loss: 1.2610 loss_prob: 0.6932 loss_thr: 0.4575 loss_db: 0.1103 2022/11/02 18:25:31 - mmengine - INFO - Epoch(train) [570][60/63] lr: 1.2121e-03 eta: 6:33:26 time: 0.4837 data_time: 0.0102 memory: 14901 loss: 1.3222 loss_prob: 0.7247 loss_thr: 0.4824 loss_db: 0.1151 2022/11/02 18:25:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:25:39 - mmengine - INFO - Epoch(train) [571][5/63] lr: 1.2104e-03 eta: 6:33:26 time: 0.9072 data_time: 0.2573 memory: 14901 loss: 1.5188 loss_prob: 0.8886 loss_thr: 0.4795 loss_db: 0.1507 2022/11/02 18:25:41 - mmengine - INFO - Epoch(train) [571][10/63] lr: 1.2104e-03 eta: 6:33:19 time: 0.8651 data_time: 0.2568 memory: 14901 loss: 1.4570 loss_prob: 0.8436 loss_thr: 0.4719 loss_db: 0.1416 2022/11/02 18:25:44 - mmengine - INFO - Epoch(train) [571][15/63] lr: 1.2104e-03 eta: 6:33:19 time: 0.5239 data_time: 0.0114 memory: 14901 loss: 1.5373 loss_prob: 0.8824 loss_thr: 0.5107 loss_db: 0.1443 2022/11/02 18:25:47 - mmengine - INFO - Epoch(train) [571][20/63] lr: 1.2104e-03 eta: 6:33:12 time: 0.5527 data_time: 0.0135 memory: 14901 loss: 1.4340 loss_prob: 0.8073 loss_thr: 0.4943 loss_db: 0.1324 2022/11/02 18:25:50 - mmengine - INFO - Epoch(train) [571][25/63] lr: 1.2104e-03 eta: 6:33:12 time: 0.5918 data_time: 0.0195 memory: 14901 loss: 1.3389 loss_prob: 0.7447 loss_thr: 0.4681 loss_db: 0.1261 2022/11/02 18:25:53 - mmengine - INFO - Epoch(train) [571][30/63] lr: 1.2104e-03 eta: 6:33:07 time: 0.6140 data_time: 0.0430 memory: 14901 loss: 1.3984 loss_prob: 0.7611 loss_thr: 0.5070 loss_db: 0.1303 2022/11/02 18:25:55 - mmengine - INFO - Epoch(train) [571][35/63] lr: 1.2104e-03 eta: 6:33:07 time: 0.5670 data_time: 0.0353 memory: 14901 loss: 1.4058 loss_prob: 0.7683 loss_thr: 0.5063 loss_db: 0.1312 2022/11/02 18:25:59 - mmengine - INFO - Epoch(train) [571][40/63] lr: 1.2104e-03 eta: 6:33:00 time: 0.5544 data_time: 0.0102 memory: 14901 loss: 1.3461 loss_prob: 0.7320 loss_thr: 0.4900 loss_db: 0.1240 2022/11/02 18:26:01 - mmengine - INFO - Epoch(train) [571][45/63] lr: 1.2104e-03 eta: 6:33:00 time: 0.5936 data_time: 0.0119 memory: 14901 loss: 1.2168 loss_prob: 0.6369 loss_thr: 0.4714 loss_db: 0.1086 2022/11/02 18:26:04 - mmengine - INFO - Epoch(train) [571][50/63] lr: 1.2104e-03 eta: 6:32:54 time: 0.5639 data_time: 0.0274 memory: 14901 loss: 1.1320 loss_prob: 0.5949 loss_thr: 0.4323 loss_db: 0.1048 2022/11/02 18:26:07 - mmengine - INFO - Epoch(train) [571][55/63] lr: 1.2104e-03 eta: 6:32:54 time: 0.5348 data_time: 0.0337 memory: 14901 loss: 1.2846 loss_prob: 0.7078 loss_thr: 0.4600 loss_db: 0.1168 2022/11/02 18:26:09 - mmengine - INFO - Epoch(train) [571][60/63] lr: 1.2104e-03 eta: 6:32:47 time: 0.5100 data_time: 0.0170 memory: 14901 loss: 1.3803 loss_prob: 0.7608 loss_thr: 0.4961 loss_db: 0.1234 2022/11/02 18:26:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:26:18 - mmengine - INFO - Epoch(train) [572][5/63] lr: 1.2087e-03 eta: 6:32:47 time: 0.9410 data_time: 0.2299 memory: 14901 loss: 1.3732 loss_prob: 0.7464 loss_thr: 0.4997 loss_db: 0.1270 2022/11/02 18:26:20 - mmengine - INFO - Epoch(train) [572][10/63] lr: 1.2087e-03 eta: 6:32:42 time: 0.9777 data_time: 0.2274 memory: 14901 loss: 1.3367 loss_prob: 0.7228 loss_thr: 0.4922 loss_db: 0.1217 2022/11/02 18:26:23 - mmengine - INFO - Epoch(train) [572][15/63] lr: 1.2087e-03 eta: 6:32:42 time: 0.5167 data_time: 0.0099 memory: 14901 loss: 1.3559 loss_prob: 0.7373 loss_thr: 0.4966 loss_db: 0.1220 2022/11/02 18:26:26 - mmengine - INFO - Epoch(train) [572][20/63] lr: 1.2087e-03 eta: 6:32:35 time: 0.5621 data_time: 0.0117 memory: 14901 loss: 1.3469 loss_prob: 0.7325 loss_thr: 0.4907 loss_db: 0.1237 2022/11/02 18:26:29 - mmengine - INFO - Epoch(train) [572][25/63] lr: 1.2087e-03 eta: 6:32:35 time: 0.5618 data_time: 0.0176 memory: 14901 loss: 1.3584 loss_prob: 0.7441 loss_thr: 0.4889 loss_db: 0.1254 2022/11/02 18:26:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:26:31 - mmengine - INFO - Epoch(train) [572][30/63] lr: 1.2087e-03 eta: 6:32:29 time: 0.5434 data_time: 0.0444 memory: 14901 loss: 1.3260 loss_prob: 0.7222 loss_thr: 0.4838 loss_db: 0.1200 2022/11/02 18:26:34 - mmengine - INFO - Epoch(train) [572][35/63] lr: 1.2087e-03 eta: 6:32:29 time: 0.5908 data_time: 0.0369 memory: 14901 loss: 1.3710 loss_prob: 0.7526 loss_thr: 0.4920 loss_db: 0.1263 2022/11/02 18:26:38 - mmengine - INFO - Epoch(train) [572][40/63] lr: 1.2087e-03 eta: 6:32:23 time: 0.6204 data_time: 0.0081 memory: 14901 loss: 1.4393 loss_prob: 0.8041 loss_thr: 0.4996 loss_db: 0.1356 2022/11/02 18:26:41 - mmengine - INFO - Epoch(train) [572][45/63] lr: 1.2087e-03 eta: 6:32:23 time: 0.6230 data_time: 0.0083 memory: 14901 loss: 1.3620 loss_prob: 0.7554 loss_thr: 0.4796 loss_db: 0.1270 2022/11/02 18:26:44 - mmengine - INFO - Epoch(train) [572][50/63] lr: 1.2087e-03 eta: 6:32:17 time: 0.6085 data_time: 0.0249 memory: 14901 loss: 1.3982 loss_prob: 0.7792 loss_thr: 0.4897 loss_db: 0.1293 2022/11/02 18:26:46 - mmengine - INFO - Epoch(train) [572][55/63] lr: 1.2087e-03 eta: 6:32:17 time: 0.5771 data_time: 0.0290 memory: 14901 loss: 1.3669 loss_prob: 0.7511 loss_thr: 0.4886 loss_db: 0.1272 2022/11/02 18:26:50 - mmengine - INFO - Epoch(train) [572][60/63] lr: 1.2087e-03 eta: 6:32:11 time: 0.5855 data_time: 0.0140 memory: 14901 loss: 1.2706 loss_prob: 0.6843 loss_thr: 0.4673 loss_db: 0.1190 2022/11/02 18:26:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:26:58 - mmengine - INFO - Epoch(train) [573][5/63] lr: 1.2069e-03 eta: 6:32:11 time: 0.9580 data_time: 0.2944 memory: 14901 loss: 1.1944 loss_prob: 0.6462 loss_thr: 0.4376 loss_db: 0.1106 2022/11/02 18:27:01 - mmengine - INFO - Epoch(train) [573][10/63] lr: 1.2069e-03 eta: 6:32:06 time: 0.9768 data_time: 0.2923 memory: 14901 loss: 1.2701 loss_prob: 0.6879 loss_thr: 0.4648 loss_db: 0.1174 2022/11/02 18:27:03 - mmengine - INFO - Epoch(train) [573][15/63] lr: 1.2069e-03 eta: 6:32:06 time: 0.5419 data_time: 0.0113 memory: 14901 loss: 1.2574 loss_prob: 0.6722 loss_thr: 0.4671 loss_db: 0.1182 2022/11/02 18:27:06 - mmengine - INFO - Epoch(train) [573][20/63] lr: 1.2069e-03 eta: 6:31:59 time: 0.5378 data_time: 0.0161 memory: 14901 loss: 1.1811 loss_prob: 0.6243 loss_thr: 0.4505 loss_db: 0.1063 2022/11/02 18:27:09 - mmengine - INFO - Epoch(train) [573][25/63] lr: 1.2069e-03 eta: 6:31:59 time: 0.6143 data_time: 0.0505 memory: 14901 loss: 1.2653 loss_prob: 0.6826 loss_thr: 0.4689 loss_db: 0.1138 2022/11/02 18:27:12 - mmengine - INFO - Epoch(train) [573][30/63] lr: 1.2069e-03 eta: 6:31:53 time: 0.6147 data_time: 0.0465 memory: 14901 loss: 1.3261 loss_prob: 0.7171 loss_thr: 0.4853 loss_db: 0.1236 2022/11/02 18:27:15 - mmengine - INFO - Epoch(train) [573][35/63] lr: 1.2069e-03 eta: 6:31:53 time: 0.5164 data_time: 0.0112 memory: 14901 loss: 1.2478 loss_prob: 0.6696 loss_thr: 0.4624 loss_db: 0.1158 2022/11/02 18:27:18 - mmengine - INFO - Epoch(train) [573][40/63] lr: 1.2069e-03 eta: 6:31:47 time: 0.5389 data_time: 0.0127 memory: 14901 loss: 1.1950 loss_prob: 0.6396 loss_thr: 0.4467 loss_db: 0.1087 2022/11/02 18:27:20 - mmengine - INFO - Epoch(train) [573][45/63] lr: 1.2069e-03 eta: 6:31:47 time: 0.5670 data_time: 0.0134 memory: 14901 loss: 1.1794 loss_prob: 0.6278 loss_thr: 0.4433 loss_db: 0.1082 2022/11/02 18:27:24 - mmengine - INFO - Epoch(train) [573][50/63] lr: 1.2069e-03 eta: 6:31:41 time: 0.6164 data_time: 0.0320 memory: 14901 loss: 1.2807 loss_prob: 0.6913 loss_thr: 0.4711 loss_db: 0.1183 2022/11/02 18:27:27 - mmengine - INFO - Epoch(train) [573][55/63] lr: 1.2069e-03 eta: 6:31:41 time: 0.6478 data_time: 0.0316 memory: 14901 loss: 1.2505 loss_prob: 0.6712 loss_thr: 0.4661 loss_db: 0.1132 2022/11/02 18:27:31 - mmengine - INFO - Epoch(train) [573][60/63] lr: 1.2069e-03 eta: 6:31:36 time: 0.6822 data_time: 0.0107 memory: 14901 loss: 1.2634 loss_prob: 0.6722 loss_thr: 0.4776 loss_db: 0.1136 2022/11/02 18:27:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:27:39 - mmengine - INFO - Epoch(train) [574][5/63] lr: 1.2052e-03 eta: 6:31:36 time: 1.0575 data_time: 0.2840 memory: 14901 loss: 1.2850 loss_prob: 0.6889 loss_thr: 0.4786 loss_db: 0.1175 2022/11/02 18:27:43 - mmengine - INFO - Epoch(train) [574][10/63] lr: 1.2052e-03 eta: 6:31:32 time: 1.0543 data_time: 0.2815 memory: 14901 loss: 1.2208 loss_prob: 0.6523 loss_thr: 0.4574 loss_db: 0.1112 2022/11/02 18:27:46 - mmengine - INFO - Epoch(train) [574][15/63] lr: 1.2052e-03 eta: 6:31:32 time: 0.6294 data_time: 0.0091 memory: 14901 loss: 1.2282 loss_prob: 0.6561 loss_thr: 0.4586 loss_db: 0.1135 2022/11/02 18:27:49 - mmengine - INFO - Epoch(train) [574][20/63] lr: 1.2052e-03 eta: 6:31:27 time: 0.6863 data_time: 0.0116 memory: 14901 loss: 1.1770 loss_prob: 0.6216 loss_thr: 0.4488 loss_db: 0.1066 2022/11/02 18:27:52 - mmengine - INFO - Epoch(train) [574][25/63] lr: 1.2052e-03 eta: 6:31:27 time: 0.6681 data_time: 0.0429 memory: 14901 loss: 1.2113 loss_prob: 0.6450 loss_thr: 0.4570 loss_db: 0.1093 2022/11/02 18:27:55 - mmengine - INFO - Epoch(train) [574][30/63] lr: 1.2052e-03 eta: 6:31:21 time: 0.5792 data_time: 0.0484 memory: 14901 loss: 1.3347 loss_prob: 0.7356 loss_thr: 0.4754 loss_db: 0.1238 2022/11/02 18:27:58 - mmengine - INFO - Epoch(train) [574][35/63] lr: 1.2052e-03 eta: 6:31:21 time: 0.5928 data_time: 0.0178 memory: 14901 loss: 1.3020 loss_prob: 0.7112 loss_thr: 0.4716 loss_db: 0.1192 2022/11/02 18:28:01 - mmengine - INFO - Epoch(train) [574][40/63] lr: 1.2052e-03 eta: 6:31:14 time: 0.5885 data_time: 0.0130 memory: 14901 loss: 1.2608 loss_prob: 0.6720 loss_thr: 0.4737 loss_db: 0.1151 2022/11/02 18:28:04 - mmengine - INFO - Epoch(train) [574][45/63] lr: 1.2052e-03 eta: 6:31:14 time: 0.5919 data_time: 0.0106 memory: 14901 loss: 1.3457 loss_prob: 0.7330 loss_thr: 0.4905 loss_db: 0.1223 2022/11/02 18:28:07 - mmengine - INFO - Epoch(train) [574][50/63] lr: 1.2052e-03 eta: 6:31:09 time: 0.6308 data_time: 0.0355 memory: 14901 loss: 1.2702 loss_prob: 0.6808 loss_thr: 0.4733 loss_db: 0.1160 2022/11/02 18:28:11 - mmengine - INFO - Epoch(train) [574][55/63] lr: 1.2052e-03 eta: 6:31:09 time: 0.6272 data_time: 0.0368 memory: 14901 loss: 1.2189 loss_prob: 0.6380 loss_thr: 0.4700 loss_db: 0.1110 2022/11/02 18:28:14 - mmengine - INFO - Epoch(train) [574][60/63] lr: 1.2052e-03 eta: 6:31:03 time: 0.6344 data_time: 0.0102 memory: 14901 loss: 1.3250 loss_prob: 0.7155 loss_thr: 0.4888 loss_db: 0.1206 2022/11/02 18:28:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:28:24 - mmengine - INFO - Epoch(train) [575][5/63] lr: 1.2035e-03 eta: 6:31:03 time: 1.1245 data_time: 0.3262 memory: 14901 loss: 1.3062 loss_prob: 0.7112 loss_thr: 0.4745 loss_db: 0.1205 2022/11/02 18:28:27 - mmengine - INFO - Epoch(train) [575][10/63] lr: 1.2035e-03 eta: 6:30:59 time: 1.0729 data_time: 0.3240 memory: 14901 loss: 1.2182 loss_prob: 0.6447 loss_thr: 0.4597 loss_db: 0.1138 2022/11/02 18:28:30 - mmengine - INFO - Epoch(train) [575][15/63] lr: 1.2035e-03 eta: 6:30:59 time: 0.5651 data_time: 0.0086 memory: 14901 loss: 1.2261 loss_prob: 0.6565 loss_thr: 0.4582 loss_db: 0.1114 2022/11/02 18:28:33 - mmengine - INFO - Epoch(train) [575][20/63] lr: 1.2035e-03 eta: 6:30:53 time: 0.6094 data_time: 0.0114 memory: 14901 loss: 1.2065 loss_prob: 0.6445 loss_thr: 0.4536 loss_db: 0.1084 2022/11/02 18:28:35 - mmengine - INFO - Epoch(train) [575][25/63] lr: 1.2035e-03 eta: 6:30:53 time: 0.5803 data_time: 0.0398 memory: 14901 loss: 1.2231 loss_prob: 0.6576 loss_thr: 0.4538 loss_db: 0.1118 2022/11/02 18:28:38 - mmengine - INFO - Epoch(train) [575][30/63] lr: 1.2035e-03 eta: 6:30:47 time: 0.5589 data_time: 0.0432 memory: 14901 loss: 1.2225 loss_prob: 0.6620 loss_thr: 0.4500 loss_db: 0.1105 2022/11/02 18:28:42 - mmengine - INFO - Epoch(train) [575][35/63] lr: 1.2035e-03 eta: 6:30:47 time: 0.6354 data_time: 0.0175 memory: 14901 loss: 1.2527 loss_prob: 0.6806 loss_thr: 0.4574 loss_db: 0.1147 2022/11/02 18:28:45 - mmengine - INFO - Epoch(train) [575][40/63] lr: 1.2035e-03 eta: 6:30:41 time: 0.6325 data_time: 0.0107 memory: 14901 loss: 1.2757 loss_prob: 0.6941 loss_thr: 0.4638 loss_db: 0.1178 2022/11/02 18:28:47 - mmengine - INFO - Epoch(train) [575][45/63] lr: 1.2035e-03 eta: 6:30:41 time: 0.5589 data_time: 0.0089 memory: 14901 loss: 1.2589 loss_prob: 0.6731 loss_thr: 0.4714 loss_db: 0.1143 2022/11/02 18:28:50 - mmengine - INFO - Epoch(train) [575][50/63] lr: 1.2035e-03 eta: 6:30:35 time: 0.5563 data_time: 0.0281 memory: 14901 loss: 1.2331 loss_prob: 0.6628 loss_thr: 0.4566 loss_db: 0.1137 2022/11/02 18:28:53 - mmengine - INFO - Epoch(train) [575][55/63] lr: 1.2035e-03 eta: 6:30:35 time: 0.5394 data_time: 0.0270 memory: 14901 loss: 1.4284 loss_prob: 0.8279 loss_thr: 0.4608 loss_db: 0.1396 2022/11/02 18:28:56 - mmengine - INFO - Epoch(train) [575][60/63] lr: 1.2035e-03 eta: 6:30:28 time: 0.5432 data_time: 0.0118 memory: 14901 loss: 1.4169 loss_prob: 0.8152 loss_thr: 0.4698 loss_db: 0.1319 2022/11/02 18:28:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:29:04 - mmengine - INFO - Epoch(train) [576][5/63] lr: 1.2017e-03 eta: 6:30:28 time: 0.9959 data_time: 0.2599 memory: 14901 loss: 1.2896 loss_prob: 0.6980 loss_thr: 0.4726 loss_db: 0.1190 2022/11/02 18:29:08 - mmengine - INFO - Epoch(train) [576][10/63] lr: 1.2017e-03 eta: 6:30:25 time: 1.1288 data_time: 0.2664 memory: 14901 loss: 1.3826 loss_prob: 0.7657 loss_thr: 0.4885 loss_db: 0.1284 2022/11/02 18:29:12 - mmengine - INFO - Epoch(train) [576][15/63] lr: 1.2017e-03 eta: 6:30:25 time: 0.7254 data_time: 0.0176 memory: 14901 loss: 1.4576 loss_prob: 0.8080 loss_thr: 0.5167 loss_db: 0.1330 2022/11/02 18:29:14 - mmengine - INFO - Epoch(train) [576][20/63] lr: 1.2017e-03 eta: 6:30:19 time: 0.6270 data_time: 0.0146 memory: 14901 loss: 1.3550 loss_prob: 0.7358 loss_thr: 0.4960 loss_db: 0.1232 2022/11/02 18:29:17 - mmengine - INFO - Epoch(train) [576][25/63] lr: 1.2017e-03 eta: 6:30:19 time: 0.5635 data_time: 0.0241 memory: 14901 loss: 1.2848 loss_prob: 0.6900 loss_thr: 0.4763 loss_db: 0.1185 2022/11/02 18:29:21 - mmengine - INFO - Epoch(train) [576][30/63] lr: 1.2017e-03 eta: 6:30:13 time: 0.6427 data_time: 0.0349 memory: 14901 loss: 1.2375 loss_prob: 0.6594 loss_thr: 0.4638 loss_db: 0.1143 2022/11/02 18:29:24 - mmengine - INFO - Epoch(train) [576][35/63] lr: 1.2017e-03 eta: 6:30:13 time: 0.6641 data_time: 0.0306 memory: 14901 loss: 1.2240 loss_prob: 0.6579 loss_thr: 0.4552 loss_db: 0.1110 2022/11/02 18:29:26 - mmengine - INFO - Epoch(train) [576][40/63] lr: 1.2017e-03 eta: 6:30:07 time: 0.5573 data_time: 0.0210 memory: 14901 loss: 1.2360 loss_prob: 0.6588 loss_thr: 0.4641 loss_db: 0.1131 2022/11/02 18:29:29 - mmengine - INFO - Epoch(train) [576][45/63] lr: 1.2017e-03 eta: 6:30:07 time: 0.5338 data_time: 0.0164 memory: 14901 loss: 1.2331 loss_prob: 0.6456 loss_thr: 0.4757 loss_db: 0.1118 2022/11/02 18:29:33 - mmengine - INFO - Epoch(train) [576][50/63] lr: 1.2017e-03 eta: 6:30:02 time: 0.6304 data_time: 0.0223 memory: 14901 loss: 1.2706 loss_prob: 0.6832 loss_thr: 0.4732 loss_db: 0.1142 2022/11/02 18:29:36 - mmengine - INFO - Epoch(train) [576][55/63] lr: 1.2017e-03 eta: 6:30:02 time: 0.7045 data_time: 0.0275 memory: 14901 loss: 1.2631 loss_prob: 0.6924 loss_thr: 0.4549 loss_db: 0.1158 2022/11/02 18:29:39 - mmengine - INFO - Epoch(train) [576][60/63] lr: 1.2017e-03 eta: 6:29:56 time: 0.6453 data_time: 0.0200 memory: 14901 loss: 1.2057 loss_prob: 0.6469 loss_thr: 0.4477 loss_db: 0.1110 2022/11/02 18:29:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:29:47 - mmengine - INFO - Epoch(train) [577][5/63] lr: 1.2000e-03 eta: 6:29:56 time: 0.9158 data_time: 0.2181 memory: 14901 loss: 1.2438 loss_prob: 0.6640 loss_thr: 0.4679 loss_db: 0.1119 2022/11/02 18:29:50 - mmengine - INFO - Epoch(train) [577][10/63] lr: 1.2000e-03 eta: 6:29:50 time: 0.9265 data_time: 0.2188 memory: 14901 loss: 1.2076 loss_prob: 0.6400 loss_thr: 0.4609 loss_db: 0.1067 2022/11/02 18:29:53 - mmengine - INFO - Epoch(train) [577][15/63] lr: 1.2000e-03 eta: 6:29:50 time: 0.5689 data_time: 0.0096 memory: 14901 loss: 1.1208 loss_prob: 0.5980 loss_thr: 0.4236 loss_db: 0.0993 2022/11/02 18:29:56 - mmengine - INFO - Epoch(train) [577][20/63] lr: 1.2000e-03 eta: 6:29:44 time: 0.5911 data_time: 0.0147 memory: 14901 loss: 1.2003 loss_prob: 0.6396 loss_thr: 0.4508 loss_db: 0.1099 2022/11/02 18:29:58 - mmengine - INFO - Epoch(train) [577][25/63] lr: 1.2000e-03 eta: 6:29:44 time: 0.5610 data_time: 0.0299 memory: 14901 loss: 1.3640 loss_prob: 0.7475 loss_thr: 0.4926 loss_db: 0.1240 2022/11/02 18:30:02 - mmengine - INFO - Epoch(train) [577][30/63] lr: 1.2000e-03 eta: 6:29:38 time: 0.5650 data_time: 0.0432 memory: 14901 loss: 1.2443 loss_prob: 0.6708 loss_thr: 0.4651 loss_db: 0.1084 2022/11/02 18:30:05 - mmengine - INFO - Epoch(train) [577][35/63] lr: 1.2000e-03 eta: 6:29:38 time: 0.6219 data_time: 0.0286 memory: 14901 loss: 1.0973 loss_prob: 0.5739 loss_thr: 0.4274 loss_db: 0.0959 2022/11/02 18:30:08 - mmengine - INFO - Epoch(train) [577][40/63] lr: 1.2000e-03 eta: 6:29:32 time: 0.6013 data_time: 0.0118 memory: 14901 loss: 1.3698 loss_prob: 0.7783 loss_thr: 0.4601 loss_db: 0.1313 2022/11/02 18:30:10 - mmengine - INFO - Epoch(train) [577][45/63] lr: 1.2000e-03 eta: 6:29:32 time: 0.5412 data_time: 0.0086 memory: 14901 loss: 1.4302 loss_prob: 0.8053 loss_thr: 0.4868 loss_db: 0.1381 2022/11/02 18:30:13 - mmengine - INFO - Epoch(train) [577][50/63] lr: 1.2000e-03 eta: 6:29:25 time: 0.5470 data_time: 0.0254 memory: 14901 loss: 1.2907 loss_prob: 0.6923 loss_thr: 0.4797 loss_db: 0.1187 2022/11/02 18:30:17 - mmengine - INFO - Epoch(train) [577][55/63] lr: 1.2000e-03 eta: 6:29:25 time: 0.6417 data_time: 0.0349 memory: 14901 loss: 1.3266 loss_prob: 0.7198 loss_thr: 0.4862 loss_db: 0.1206 2022/11/02 18:30:19 - mmengine - INFO - Epoch(train) [577][60/63] lr: 1.2000e-03 eta: 6:29:20 time: 0.6469 data_time: 0.0214 memory: 14901 loss: 1.2730 loss_prob: 0.6904 loss_thr: 0.4661 loss_db: 0.1164 2022/11/02 18:30:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:30:27 - mmengine - INFO - Epoch(train) [578][5/63] lr: 1.1983e-03 eta: 6:29:20 time: 0.8872 data_time: 0.2644 memory: 14901 loss: 1.2099 loss_prob: 0.6438 loss_thr: 0.4558 loss_db: 0.1103 2022/11/02 18:30:31 - mmengine - INFO - Epoch(train) [578][10/63] lr: 1.1983e-03 eta: 6:29:14 time: 0.9350 data_time: 0.2832 memory: 14901 loss: 1.2461 loss_prob: 0.6715 loss_thr: 0.4582 loss_db: 0.1164 2022/11/02 18:30:34 - mmengine - INFO - Epoch(train) [578][15/63] lr: 1.1983e-03 eta: 6:29:14 time: 0.6508 data_time: 0.0262 memory: 14901 loss: 1.2450 loss_prob: 0.6743 loss_thr: 0.4529 loss_db: 0.1178 2022/11/02 18:30:37 - mmengine - INFO - Epoch(train) [578][20/63] lr: 1.1983e-03 eta: 6:29:08 time: 0.6012 data_time: 0.0092 memory: 14901 loss: 1.2497 loss_prob: 0.6748 loss_thr: 0.4603 loss_db: 0.1145 2022/11/02 18:30:40 - mmengine - INFO - Epoch(train) [578][25/63] lr: 1.1983e-03 eta: 6:29:08 time: 0.5876 data_time: 0.0351 memory: 14901 loss: 1.6654 loss_prob: 1.0247 loss_thr: 0.4945 loss_db: 0.1462 2022/11/02 18:30:43 - mmengine - INFO - Epoch(train) [578][30/63] lr: 1.1983e-03 eta: 6:29:02 time: 0.6047 data_time: 0.0434 memory: 14901 loss: 1.6737 loss_prob: 1.0268 loss_thr: 0.5014 loss_db: 0.1455 2022/11/02 18:30:46 - mmengine - INFO - Epoch(train) [578][35/63] lr: 1.1983e-03 eta: 6:29:02 time: 0.5807 data_time: 0.0244 memory: 14901 loss: 1.4133 loss_prob: 0.8027 loss_thr: 0.4752 loss_db: 0.1353 2022/11/02 18:30:48 - mmengine - INFO - Epoch(train) [578][40/63] lr: 1.1983e-03 eta: 6:28:56 time: 0.5639 data_time: 0.0148 memory: 14901 loss: 1.4885 loss_prob: 0.8517 loss_thr: 0.4908 loss_db: 0.1459 2022/11/02 18:30:51 - mmengine - INFO - Epoch(train) [578][45/63] lr: 1.1983e-03 eta: 6:28:56 time: 0.5394 data_time: 0.0106 memory: 14901 loss: 1.4784 loss_prob: 0.8130 loss_thr: 0.5287 loss_db: 0.1367 2022/11/02 18:30:55 - mmengine - INFO - Epoch(train) [578][50/63] lr: 1.1983e-03 eta: 6:28:50 time: 0.6280 data_time: 0.0230 memory: 14901 loss: 1.4982 loss_prob: 0.8333 loss_thr: 0.5264 loss_db: 0.1385 2022/11/02 18:30:57 - mmengine - INFO - Epoch(train) [578][55/63] lr: 1.1983e-03 eta: 6:28:50 time: 0.6266 data_time: 0.0269 memory: 14901 loss: 1.4077 loss_prob: 0.7740 loss_thr: 0.5013 loss_db: 0.1323 2022/11/02 18:31:00 - mmengine - INFO - Epoch(train) [578][60/63] lr: 1.1983e-03 eta: 6:28:44 time: 0.5262 data_time: 0.0210 memory: 14901 loss: 1.3498 loss_prob: 0.7326 loss_thr: 0.4928 loss_db: 0.1243 2022/11/02 18:31:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:31:07 - mmengine - INFO - Epoch(train) [579][5/63] lr: 1.1965e-03 eta: 6:28:44 time: 0.8216 data_time: 0.2323 memory: 14901 loss: 1.4811 loss_prob: 0.8397 loss_thr: 0.5013 loss_db: 0.1401 2022/11/02 18:31:10 - mmengine - INFO - Epoch(train) [579][10/63] lr: 1.1965e-03 eta: 6:28:37 time: 0.8944 data_time: 0.2376 memory: 14901 loss: 1.4783 loss_prob: 0.8262 loss_thr: 0.5110 loss_db: 0.1410 2022/11/02 18:31:14 - mmengine - INFO - Epoch(train) [579][15/63] lr: 1.1965e-03 eta: 6:28:37 time: 0.6427 data_time: 0.0134 memory: 14901 loss: 1.4081 loss_prob: 0.7686 loss_thr: 0.5084 loss_db: 0.1311 2022/11/02 18:31:17 - mmengine - INFO - Epoch(train) [579][20/63] lr: 1.1965e-03 eta: 6:28:32 time: 0.6497 data_time: 0.0093 memory: 14901 loss: 1.4748 loss_prob: 0.8115 loss_thr: 0.5240 loss_db: 0.1393 2022/11/02 18:31:20 - mmengine - INFO - Epoch(train) [579][25/63] lr: 1.1965e-03 eta: 6:28:32 time: 0.6122 data_time: 0.0253 memory: 14901 loss: 1.4285 loss_prob: 0.7819 loss_thr: 0.5119 loss_db: 0.1347 2022/11/02 18:31:23 - mmengine - INFO - Epoch(train) [579][30/63] lr: 1.1965e-03 eta: 6:28:26 time: 0.5680 data_time: 0.0431 memory: 14901 loss: 1.3068 loss_prob: 0.7093 loss_thr: 0.4810 loss_db: 0.1165 2022/11/02 18:31:25 - mmengine - INFO - Epoch(train) [579][35/63] lr: 1.1965e-03 eta: 6:28:26 time: 0.5357 data_time: 0.0307 memory: 14901 loss: 1.2907 loss_prob: 0.7071 loss_thr: 0.4669 loss_db: 0.1166 2022/11/02 18:31:28 - mmengine - INFO - Epoch(train) [579][40/63] lr: 1.1965e-03 eta: 6:28:19 time: 0.5322 data_time: 0.0110 memory: 14901 loss: 1.1933 loss_prob: 0.6364 loss_thr: 0.4494 loss_db: 0.1075 2022/11/02 18:31:31 - mmengine - INFO - Epoch(train) [579][45/63] lr: 1.1965e-03 eta: 6:28:19 time: 0.5696 data_time: 0.0096 memory: 14901 loss: 1.3513 loss_prob: 0.7597 loss_thr: 0.4690 loss_db: 0.1227 2022/11/02 18:31:34 - mmengine - INFO - Epoch(train) [579][50/63] lr: 1.1965e-03 eta: 6:28:14 time: 0.6367 data_time: 0.0306 memory: 14901 loss: 1.4485 loss_prob: 0.8271 loss_thr: 0.4891 loss_db: 0.1324 2022/11/02 18:31:37 - mmengine - INFO - Epoch(train) [579][55/63] lr: 1.1965e-03 eta: 6:28:14 time: 0.6172 data_time: 0.0311 memory: 14901 loss: 1.3291 loss_prob: 0.7275 loss_thr: 0.4788 loss_db: 0.1228 2022/11/02 18:31:40 - mmengine - INFO - Epoch(train) [579][60/63] lr: 1.1965e-03 eta: 6:28:07 time: 0.5296 data_time: 0.0115 memory: 14901 loss: 1.2813 loss_prob: 0.6867 loss_thr: 0.4764 loss_db: 0.1182 2022/11/02 18:31:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:31:47 - mmengine - INFO - Epoch(train) [580][5/63] lr: 1.1948e-03 eta: 6:28:07 time: 0.8108 data_time: 0.2322 memory: 14901 loss: 1.3316 loss_prob: 0.7229 loss_thr: 0.4861 loss_db: 0.1225 2022/11/02 18:31:50 - mmengine - INFO - Epoch(train) [580][10/63] lr: 1.1948e-03 eta: 6:28:00 time: 0.8724 data_time: 0.2383 memory: 14901 loss: 1.2383 loss_prob: 0.6680 loss_thr: 0.4588 loss_db: 0.1115 2022/11/02 18:31:54 - mmengine - INFO - Epoch(train) [580][15/63] lr: 1.1948e-03 eta: 6:28:00 time: 0.6989 data_time: 0.0201 memory: 14901 loss: 1.2343 loss_prob: 0.6718 loss_thr: 0.4481 loss_db: 0.1144 2022/11/02 18:31:57 - mmengine - INFO - Epoch(train) [580][20/63] lr: 1.1948e-03 eta: 6:27:56 time: 0.7540 data_time: 0.0151 memory: 14901 loss: 1.2654 loss_prob: 0.6787 loss_thr: 0.4697 loss_db: 0.1170 2022/11/02 18:32:01 - mmengine - INFO - Epoch(train) [580][25/63] lr: 1.1948e-03 eta: 6:27:56 time: 0.7169 data_time: 0.0365 memory: 14901 loss: 1.2605 loss_prob: 0.6678 loss_thr: 0.4775 loss_db: 0.1152 2022/11/02 18:32:04 - mmengine - INFO - Epoch(train) [580][30/63] lr: 1.1948e-03 eta: 6:27:51 time: 0.7117 data_time: 0.0429 memory: 14901 loss: 1.4223 loss_prob: 0.7838 loss_thr: 0.5053 loss_db: 0.1332 2022/11/02 18:32:07 - mmengine - INFO - Epoch(train) [580][35/63] lr: 1.1948e-03 eta: 6:27:51 time: 0.5989 data_time: 0.0183 memory: 14901 loss: 1.3825 loss_prob: 0.7639 loss_thr: 0.4913 loss_db: 0.1274 2022/11/02 18:32:10 - mmengine - INFO - Epoch(train) [580][40/63] lr: 1.1948e-03 eta: 6:27:45 time: 0.5397 data_time: 0.0092 memory: 14901 loss: 1.1975 loss_prob: 0.6391 loss_thr: 0.4490 loss_db: 0.1094 2022/11/02 18:32:13 - mmengine - INFO - Epoch(train) [580][45/63] lr: 1.1948e-03 eta: 6:27:45 time: 0.5853 data_time: 0.0140 memory: 14901 loss: 1.1703 loss_prob: 0.6121 loss_thr: 0.4507 loss_db: 0.1075 2022/11/02 18:32:15 - mmengine - INFO - Epoch(train) [580][50/63] lr: 1.1948e-03 eta: 6:27:38 time: 0.5534 data_time: 0.0310 memory: 14901 loss: 1.1928 loss_prob: 0.6314 loss_thr: 0.4526 loss_db: 0.1088 2022/11/02 18:32:18 - mmengine - INFO - Epoch(train) [580][55/63] lr: 1.1948e-03 eta: 6:27:38 time: 0.5344 data_time: 0.0357 memory: 14901 loss: 1.3027 loss_prob: 0.7062 loss_thr: 0.4758 loss_db: 0.1206 2022/11/02 18:32:21 - mmengine - INFO - Epoch(train) [580][60/63] lr: 1.1948e-03 eta: 6:27:32 time: 0.5800 data_time: 0.0173 memory: 14901 loss: 1.3327 loss_prob: 0.7205 loss_thr: 0.4859 loss_db: 0.1263 2022/11/02 18:32:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:32:22 - mmengine - INFO - Saving checkpoint at 580 epochs 2022/11/02 18:32:26 - mmengine - INFO - Epoch(val) [580][5/500] eta: 6:27:32 time: 0.0492 data_time: 0.0051 memory: 14901 2022/11/02 18:32:26 - mmengine - INFO - Epoch(val) [580][10/500] eta: 0:00:24 time: 0.0503 data_time: 0.0054 memory: 1008 2022/11/02 18:32:26 - mmengine - INFO - Epoch(val) [580][15/500] eta: 0:00:24 time: 0.0408 data_time: 0.0030 memory: 1008 2022/11/02 18:32:27 - mmengine - INFO - Epoch(val) [580][20/500] eta: 0:00:18 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/02 18:32:27 - mmengine - INFO - Epoch(val) [580][25/500] eta: 0:00:18 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 18:32:27 - mmengine - INFO - Epoch(val) [580][30/500] eta: 0:00:21 time: 0.0453 data_time: 0.0031 memory: 1008 2022/11/02 18:32:27 - mmengine - INFO - Epoch(val) [580][35/500] eta: 0:00:21 time: 0.0465 data_time: 0.0035 memory: 1008 2022/11/02 18:32:28 - mmengine - INFO - Epoch(val) [580][40/500] eta: 0:00:23 time: 0.0509 data_time: 0.0035 memory: 1008 2022/11/02 18:32:28 - mmengine - INFO - Epoch(val) [580][45/500] eta: 0:00:23 time: 0.0550 data_time: 0.0037 memory: 1008 2022/11/02 18:32:28 - mmengine - INFO - Epoch(val) [580][50/500] eta: 0:00:23 time: 0.0527 data_time: 0.0037 memory: 1008 2022/11/02 18:32:28 - mmengine - INFO - Epoch(val) [580][55/500] eta: 0:00:23 time: 0.0504 data_time: 0.0032 memory: 1008 2022/11/02 18:32:29 - mmengine - INFO - Epoch(val) [580][60/500] eta: 0:00:20 time: 0.0467 data_time: 0.0030 memory: 1008 2022/11/02 18:32:29 - mmengine - INFO - Epoch(val) [580][65/500] eta: 0:00:20 time: 0.0512 data_time: 0.0036 memory: 1008 2022/11/02 18:32:29 - mmengine - INFO - Epoch(val) [580][70/500] eta: 0:00:21 time: 0.0496 data_time: 0.0036 memory: 1008 2022/11/02 18:32:29 - mmengine - INFO - Epoch(val) [580][75/500] eta: 0:00:21 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 18:32:29 - mmengine - INFO - Epoch(val) [580][80/500] eta: 0:00:15 time: 0.0373 data_time: 0.0029 memory: 1008 2022/11/02 18:32:30 - mmengine - INFO - Epoch(val) [580][85/500] eta: 0:00:15 time: 0.0356 data_time: 0.0027 memory: 1008 2022/11/02 18:32:30 - mmengine - INFO - Epoch(val) [580][90/500] eta: 0:00:16 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 18:32:30 - mmengine - INFO - Epoch(val) [580][95/500] eta: 0:00:16 time: 0.0421 data_time: 0.0025 memory: 1008 2022/11/02 18:32:30 - mmengine - INFO - Epoch(val) [580][100/500] eta: 0:00:16 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/02 18:32:30 - mmengine - INFO - Epoch(val) [580][105/500] eta: 0:00:16 time: 0.0432 data_time: 0.0037 memory: 1008 2022/11/02 18:32:31 - mmengine - INFO - Epoch(val) [580][110/500] eta: 0:00:16 time: 0.0433 data_time: 0.0039 memory: 1008 2022/11/02 18:32:31 - mmengine - INFO - Epoch(val) [580][115/500] eta: 0:00:16 time: 0.0420 data_time: 0.0034 memory: 1008 2022/11/02 18:32:31 - mmengine - INFO - Epoch(val) [580][120/500] eta: 0:00:15 time: 0.0409 data_time: 0.0031 memory: 1008 2022/11/02 18:32:31 - mmengine - INFO - Epoch(val) [580][125/500] eta: 0:00:15 time: 0.0381 data_time: 0.0028 memory: 1008 2022/11/02 18:32:31 - mmengine - INFO - Epoch(val) [580][130/500] eta: 0:00:13 time: 0.0375 data_time: 0.0027 memory: 1008 2022/11/02 18:32:32 - mmengine - INFO - Epoch(val) [580][135/500] eta: 0:00:13 time: 0.0380 data_time: 0.0031 memory: 1008 2022/11/02 18:32:32 - mmengine - INFO - Epoch(val) [580][140/500] eta: 0:00:14 time: 0.0413 data_time: 0.0034 memory: 1008 2022/11/02 18:32:32 - mmengine - INFO - Epoch(val) [580][145/500] eta: 0:00:14 time: 0.0534 data_time: 0.0036 memory: 1008 2022/11/02 18:32:32 - mmengine - INFO - Epoch(val) [580][150/500] eta: 0:00:19 time: 0.0568 data_time: 0.0050 memory: 1008 2022/11/02 18:32:33 - mmengine - INFO - Epoch(val) [580][155/500] eta: 0:00:19 time: 0.0516 data_time: 0.0049 memory: 1008 2022/11/02 18:32:33 - mmengine - INFO - Epoch(val) [580][160/500] eta: 0:00:17 time: 0.0515 data_time: 0.0039 memory: 1008 2022/11/02 18:32:33 - mmengine - INFO - Epoch(val) [580][165/500] eta: 0:00:17 time: 0.0537 data_time: 0.0043 memory: 1008 2022/11/02 18:32:34 - mmengine - INFO - Epoch(val) [580][170/500] eta: 0:00:17 time: 0.0533 data_time: 0.0043 memory: 1008 2022/11/02 18:32:34 - mmengine - INFO - Epoch(val) [580][175/500] eta: 0:00:17 time: 0.0448 data_time: 0.0037 memory: 1008 2022/11/02 18:32:34 - mmengine - INFO - Epoch(val) [580][180/500] eta: 0:00:14 time: 0.0459 data_time: 0.0043 memory: 1008 2022/11/02 18:32:34 - mmengine - INFO - Epoch(val) [580][185/500] eta: 0:00:14 time: 0.0491 data_time: 0.0042 memory: 1008 2022/11/02 18:32:34 - mmengine - INFO - Epoch(val) [580][190/500] eta: 0:00:13 time: 0.0424 data_time: 0.0028 memory: 1008 2022/11/02 18:32:35 - mmengine - INFO - Epoch(val) [580][195/500] eta: 0:00:13 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 18:32:35 - mmengine - INFO - Epoch(val) [580][200/500] eta: 0:00:13 time: 0.0466 data_time: 0.0028 memory: 1008 2022/11/02 18:32:35 - mmengine - INFO - Epoch(val) [580][205/500] eta: 0:00:13 time: 0.0451 data_time: 0.0030 memory: 1008 2022/11/02 18:32:35 - mmengine - INFO - Epoch(val) [580][210/500] eta: 0:00:10 time: 0.0374 data_time: 0.0027 memory: 1008 2022/11/02 18:32:35 - mmengine - INFO - Epoch(val) [580][215/500] eta: 0:00:10 time: 0.0417 data_time: 0.0027 memory: 1008 2022/11/02 18:32:36 - mmengine - INFO - Epoch(val) [580][220/500] eta: 0:00:12 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/02 18:32:36 - mmengine - INFO - Epoch(val) [580][225/500] eta: 0:00:12 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 18:32:36 - mmengine - INFO - Epoch(val) [580][230/500] eta: 0:00:11 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/02 18:32:36 - mmengine - INFO - Epoch(val) [580][235/500] eta: 0:00:11 time: 0.0416 data_time: 0.0036 memory: 1008 2022/11/02 18:32:37 - mmengine - INFO - Epoch(val) [580][240/500] eta: 0:00:10 time: 0.0420 data_time: 0.0034 memory: 1008 2022/11/02 18:32:37 - mmengine - INFO - Epoch(val) [580][245/500] eta: 0:00:10 time: 0.0382 data_time: 0.0028 memory: 1008 2022/11/02 18:32:37 - mmengine - INFO - Epoch(val) [580][250/500] eta: 0:00:09 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 18:32:37 - mmengine - INFO - Epoch(val) [580][255/500] eta: 0:00:09 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/02 18:32:37 - mmengine - INFO - Epoch(val) [580][260/500] eta: 0:00:09 time: 0.0396 data_time: 0.0030 memory: 1008 2022/11/02 18:32:38 - mmengine - INFO - Epoch(val) [580][265/500] eta: 0:00:09 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 18:32:38 - mmengine - INFO - Epoch(val) [580][270/500] eta: 0:00:10 time: 0.0463 data_time: 0.0040 memory: 1008 2022/11/02 18:32:38 - mmengine - INFO - Epoch(val) [580][275/500] eta: 0:00:10 time: 0.0452 data_time: 0.0043 memory: 1008 2022/11/02 18:32:38 - mmengine - INFO - Epoch(val) [580][280/500] eta: 0:00:09 time: 0.0446 data_time: 0.0030 memory: 1008 2022/11/02 18:32:38 - mmengine - INFO - Epoch(val) [580][285/500] eta: 0:00:09 time: 0.0461 data_time: 0.0039 memory: 1008 2022/11/02 18:32:39 - mmengine - INFO - Epoch(val) [580][290/500] eta: 0:00:08 time: 0.0416 data_time: 0.0035 memory: 1008 2022/11/02 18:32:39 - mmengine - INFO - Epoch(val) [580][295/500] eta: 0:00:08 time: 0.0443 data_time: 0.0028 memory: 1008 2022/11/02 18:32:39 - mmengine - INFO - Epoch(val) [580][300/500] eta: 0:00:08 time: 0.0436 data_time: 0.0029 memory: 1008 2022/11/02 18:32:39 - mmengine - INFO - Epoch(val) [580][305/500] eta: 0:00:08 time: 0.0401 data_time: 0.0029 memory: 1008 2022/11/02 18:32:40 - mmengine - INFO - Epoch(val) [580][310/500] eta: 0:00:08 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/02 18:32:40 - mmengine - INFO - Epoch(val) [580][315/500] eta: 0:00:08 time: 0.0481 data_time: 0.0032 memory: 1008 2022/11/02 18:32:40 - mmengine - INFO - Epoch(val) [580][320/500] eta: 0:00:08 time: 0.0449 data_time: 0.0032 memory: 1008 2022/11/02 18:32:40 - mmengine - INFO - Epoch(val) [580][325/500] eta: 0:00:08 time: 0.0583 data_time: 0.0031 memory: 1008 2022/11/02 18:32:41 - mmengine - INFO - Epoch(val) [580][330/500] eta: 0:00:09 time: 0.0568 data_time: 0.0028 memory: 1008 2022/11/02 18:32:41 - mmengine - INFO - Epoch(val) [580][335/500] eta: 0:00:09 time: 0.0373 data_time: 0.0026 memory: 1008 2022/11/02 18:32:41 - mmengine - INFO - Epoch(val) [580][340/500] eta: 0:00:08 time: 0.0538 data_time: 0.0029 memory: 1008 2022/11/02 18:32:41 - mmengine - INFO - Epoch(val) [580][345/500] eta: 0:00:08 time: 0.0558 data_time: 0.0031 memory: 1008 2022/11/02 18:32:42 - mmengine - INFO - Epoch(val) [580][350/500] eta: 0:00:07 time: 0.0482 data_time: 0.0030 memory: 1008 2022/11/02 18:32:42 - mmengine - INFO - Epoch(val) [580][355/500] eta: 0:00:07 time: 0.0455 data_time: 0.0028 memory: 1008 2022/11/02 18:32:42 - mmengine - INFO - Epoch(val) [580][360/500] eta: 0:00:05 time: 0.0367 data_time: 0.0025 memory: 1008 2022/11/02 18:32:42 - mmengine - INFO - Epoch(val) [580][365/500] eta: 0:00:05 time: 0.0426 data_time: 0.0028 memory: 1008 2022/11/02 18:32:42 - mmengine - INFO - Epoch(val) [580][370/500] eta: 0:00:05 time: 0.0430 data_time: 0.0038 memory: 1008 2022/11/02 18:32:43 - mmengine - INFO - Epoch(val) [580][375/500] eta: 0:00:05 time: 0.0368 data_time: 0.0034 memory: 1008 2022/11/02 18:32:43 - mmengine - INFO - Epoch(val) [580][380/500] eta: 0:00:04 time: 0.0409 data_time: 0.0026 memory: 1008 2022/11/02 18:32:43 - mmengine - INFO - Epoch(val) [580][385/500] eta: 0:00:04 time: 0.0429 data_time: 0.0032 memory: 1008 2022/11/02 18:32:43 - mmengine - INFO - Epoch(val) [580][390/500] eta: 0:00:04 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/02 18:32:43 - mmengine - INFO - Epoch(val) [580][395/500] eta: 0:00:04 time: 0.0393 data_time: 0.0022 memory: 1008 2022/11/02 18:32:44 - mmengine - INFO - Epoch(val) [580][400/500] eta: 0:00:03 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 18:32:44 - mmengine - INFO - Epoch(val) [580][405/500] eta: 0:00:03 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/02 18:32:44 - mmengine - INFO - Epoch(val) [580][410/500] eta: 0:00:04 time: 0.0472 data_time: 0.0037 memory: 1008 2022/11/02 18:32:44 - mmengine - INFO - Epoch(val) [580][415/500] eta: 0:00:04 time: 0.0435 data_time: 0.0034 memory: 1008 2022/11/02 18:32:44 - mmengine - INFO - Epoch(val) [580][420/500] eta: 0:00:02 time: 0.0374 data_time: 0.0029 memory: 1008 2022/11/02 18:32:45 - mmengine - INFO - Epoch(val) [580][425/500] eta: 0:00:02 time: 0.0389 data_time: 0.0030 memory: 1008 2022/11/02 18:32:45 - mmengine - INFO - Epoch(val) [580][430/500] eta: 0:00:02 time: 0.0418 data_time: 0.0030 memory: 1008 2022/11/02 18:32:45 - mmengine - INFO - Epoch(val) [580][435/500] eta: 0:00:02 time: 0.0426 data_time: 0.0030 memory: 1008 2022/11/02 18:32:45 - mmengine - INFO - Epoch(val) [580][440/500] eta: 0:00:02 time: 0.0411 data_time: 0.0028 memory: 1008 2022/11/02 18:32:45 - mmengine - INFO - Epoch(val) [580][445/500] eta: 0:00:02 time: 0.0409 data_time: 0.0029 memory: 1008 2022/11/02 18:32:46 - mmengine - INFO - Epoch(val) [580][450/500] eta: 0:00:02 time: 0.0432 data_time: 0.0031 memory: 1008 2022/11/02 18:32:46 - mmengine - INFO - Epoch(val) [580][455/500] eta: 0:00:02 time: 0.0460 data_time: 0.0035 memory: 1008 2022/11/02 18:32:46 - mmengine - INFO - Epoch(val) [580][460/500] eta: 0:00:01 time: 0.0454 data_time: 0.0037 memory: 1008 2022/11/02 18:32:46 - mmengine - INFO - Epoch(val) [580][465/500] eta: 0:00:01 time: 0.0451 data_time: 0.0034 memory: 1008 2022/11/02 18:32:47 - mmengine - INFO - Epoch(val) [580][470/500] eta: 0:00:01 time: 0.0444 data_time: 0.0033 memory: 1008 2022/11/02 18:32:47 - mmengine - INFO - Epoch(val) [580][475/500] eta: 0:00:01 time: 0.0384 data_time: 0.0028 memory: 1008 2022/11/02 18:32:47 - mmengine - INFO - Epoch(val) [580][480/500] eta: 0:00:00 time: 0.0389 data_time: 0.0028 memory: 1008 2022/11/02 18:32:47 - mmengine - INFO - Epoch(val) [580][485/500] eta: 0:00:00 time: 0.0403 data_time: 0.0030 memory: 1008 2022/11/02 18:32:47 - mmengine - INFO - Epoch(val) [580][490/500] eta: 0:00:00 time: 0.0406 data_time: 0.0027 memory: 1008 2022/11/02 18:32:48 - mmengine - INFO - Epoch(val) [580][495/500] eta: 0:00:00 time: 0.0445 data_time: 0.0030 memory: 1008 2022/11/02 18:32:48 - mmengine - INFO - Epoch(val) [580][500/500] eta: 0:00:00 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 18:32:48 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8334, precision: 0.7138, hmean: 0.7690 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8334, precision: 0.7714, hmean: 0.8012 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8325, precision: 0.8046, hmean: 0.8183 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8257, precision: 0.8325, hmean: 0.8291 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7992, precision: 0.8668, hmean: 0.8317 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5782, precision: 0.9260, hmean: 0.7119 2022/11/02 18:32:48 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0481, precision: 0.9434, hmean: 0.0916 2022/11/02 18:32:48 - mmengine - INFO - Epoch(val) [580][500/500] icdar/precision: 0.8668 icdar/recall: 0.7992 icdar/hmean: 0.8317 2022/11/02 18:32:54 - mmengine - INFO - Epoch(train) [581][5/63] lr: 1.1931e-03 eta: 0:00:00 time: 0.8711 data_time: 0.2767 memory: 14901 loss: 1.3519 loss_prob: 0.7340 loss_thr: 0.4966 loss_db: 0.1213 2022/11/02 18:32:57 - mmengine - INFO - Epoch(train) [581][10/63] lr: 1.1931e-03 eta: 6:27:26 time: 0.9034 data_time: 0.2805 memory: 14901 loss: 1.2443 loss_prob: 0.6577 loss_thr: 0.4730 loss_db: 0.1136 2022/11/02 18:33:00 - mmengine - INFO - Epoch(train) [581][15/63] lr: 1.1931e-03 eta: 6:27:26 time: 0.5436 data_time: 0.0151 memory: 14901 loss: 1.2188 loss_prob: 0.6553 loss_thr: 0.4471 loss_db: 0.1165 2022/11/02 18:33:02 - mmengine - INFO - Epoch(train) [581][20/63] lr: 1.1931e-03 eta: 6:27:19 time: 0.5505 data_time: 0.0120 memory: 14901 loss: 1.2405 loss_prob: 0.6805 loss_thr: 0.4421 loss_db: 0.1178 2022/11/02 18:33:06 - mmengine - INFO - Epoch(train) [581][25/63] lr: 1.1931e-03 eta: 6:27:19 time: 0.5969 data_time: 0.0593 memory: 14901 loss: 1.3077 loss_prob: 0.7305 loss_thr: 0.4562 loss_db: 0.1210 2022/11/02 18:33:08 - mmengine - INFO - Epoch(train) [581][30/63] lr: 1.1931e-03 eta: 6:27:13 time: 0.5980 data_time: 0.0691 memory: 14901 loss: 1.3532 loss_prob: 0.7513 loss_thr: 0.4776 loss_db: 0.1244 2022/11/02 18:33:11 - mmengine - INFO - Epoch(train) [581][35/63] lr: 1.1931e-03 eta: 6:27:13 time: 0.5348 data_time: 0.0211 memory: 14901 loss: 1.3227 loss_prob: 0.7115 loss_thr: 0.4897 loss_db: 0.1215 2022/11/02 18:33:15 - mmengine - INFO - Epoch(train) [581][40/63] lr: 1.1931e-03 eta: 6:27:08 time: 0.6368 data_time: 0.0107 memory: 14901 loss: 1.2382 loss_prob: 0.6565 loss_thr: 0.4673 loss_db: 0.1144 2022/11/02 18:33:18 - mmengine - INFO - Epoch(train) [581][45/63] lr: 1.1931e-03 eta: 6:27:08 time: 0.6914 data_time: 0.0104 memory: 14901 loss: 1.2375 loss_prob: 0.6580 loss_thr: 0.4679 loss_db: 0.1117 2022/11/02 18:33:21 - mmengine - INFO - Epoch(train) [581][50/63] lr: 1.1931e-03 eta: 6:27:02 time: 0.6195 data_time: 0.0248 memory: 14901 loss: 1.2147 loss_prob: 0.6371 loss_thr: 0.4717 loss_db: 0.1059 2022/11/02 18:33:24 - mmengine - INFO - Epoch(train) [581][55/63] lr: 1.1931e-03 eta: 6:27:02 time: 0.5921 data_time: 0.0293 memory: 14901 loss: 1.2324 loss_prob: 0.6487 loss_thr: 0.4711 loss_db: 0.1126 2022/11/02 18:33:27 - mmengine - INFO - Epoch(train) [581][60/63] lr: 1.1931e-03 eta: 6:26:56 time: 0.6006 data_time: 0.0155 memory: 14901 loss: 1.3425 loss_prob: 0.7195 loss_thr: 0.4982 loss_db: 0.1248 2022/11/02 18:33:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:33:34 - mmengine - INFO - Epoch(train) [582][5/63] lr: 1.1913e-03 eta: 6:26:56 time: 0.8550 data_time: 0.2479 memory: 14901 loss: 1.3209 loss_prob: 0.7199 loss_thr: 0.4770 loss_db: 0.1240 2022/11/02 18:33:38 - mmengine - INFO - Epoch(train) [582][10/63] lr: 1.1913e-03 eta: 6:26:50 time: 0.9112 data_time: 0.2529 memory: 14901 loss: 1.3595 loss_prob: 0.7395 loss_thr: 0.4929 loss_db: 0.1272 2022/11/02 18:33:40 - mmengine - INFO - Epoch(train) [582][15/63] lr: 1.1913e-03 eta: 6:26:50 time: 0.5874 data_time: 0.0148 memory: 14901 loss: 1.3257 loss_prob: 0.7169 loss_thr: 0.4861 loss_db: 0.1227 2022/11/02 18:33:43 - mmengine - INFO - Epoch(train) [582][20/63] lr: 1.1913e-03 eta: 6:26:44 time: 0.5408 data_time: 0.0121 memory: 14901 loss: 1.2151 loss_prob: 0.6534 loss_thr: 0.4517 loss_db: 0.1101 2022/11/02 18:33:46 - mmengine - INFO - Epoch(train) [582][25/63] lr: 1.1913e-03 eta: 6:26:44 time: 0.5640 data_time: 0.0486 memory: 14901 loss: 1.2222 loss_prob: 0.6556 loss_thr: 0.4571 loss_db: 0.1094 2022/11/02 18:33:49 - mmengine - INFO - Epoch(train) [582][30/63] lr: 1.1913e-03 eta: 6:26:37 time: 0.5582 data_time: 0.0471 memory: 14901 loss: 1.2105 loss_prob: 0.6438 loss_thr: 0.4564 loss_db: 0.1103 2022/11/02 18:33:51 - mmengine - INFO - Epoch(train) [582][35/63] lr: 1.1913e-03 eta: 6:26:37 time: 0.5410 data_time: 0.0141 memory: 14901 loss: 1.1952 loss_prob: 0.6453 loss_thr: 0.4394 loss_db: 0.1105 2022/11/02 18:33:54 - mmengine - INFO - Epoch(train) [582][40/63] lr: 1.1913e-03 eta: 6:26:31 time: 0.5451 data_time: 0.0145 memory: 14901 loss: 1.2331 loss_prob: 0.6678 loss_thr: 0.4506 loss_db: 0.1147 2022/11/02 18:33:57 - mmengine - INFO - Epoch(train) [582][45/63] lr: 1.1913e-03 eta: 6:26:31 time: 0.5841 data_time: 0.0100 memory: 14901 loss: 1.2244 loss_prob: 0.6590 loss_thr: 0.4534 loss_db: 0.1121 2022/11/02 18:34:00 - mmengine - INFO - Epoch(train) [582][50/63] lr: 1.1913e-03 eta: 6:26:25 time: 0.6150 data_time: 0.0306 memory: 14901 loss: 1.3051 loss_prob: 0.7155 loss_thr: 0.4712 loss_db: 0.1183 2022/11/02 18:34:04 - mmengine - INFO - Epoch(train) [582][55/63] lr: 1.1913e-03 eta: 6:26:25 time: 0.6518 data_time: 0.0313 memory: 14901 loss: 1.3164 loss_prob: 0.7027 loss_thr: 0.4957 loss_db: 0.1180 2022/11/02 18:34:07 - mmengine - INFO - Epoch(train) [582][60/63] lr: 1.1913e-03 eta: 6:26:20 time: 0.6491 data_time: 0.0101 memory: 14901 loss: 1.2819 loss_prob: 0.6760 loss_thr: 0.4918 loss_db: 0.1141 2022/11/02 18:34:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:34:14 - mmengine - INFO - Epoch(train) [583][5/63] lr: 1.1896e-03 eta: 6:26:20 time: 0.8461 data_time: 0.2506 memory: 14901 loss: 1.2054 loss_prob: 0.6357 loss_thr: 0.4577 loss_db: 0.1119 2022/11/02 18:34:17 - mmengine - INFO - Epoch(train) [583][10/63] lr: 1.1896e-03 eta: 6:26:13 time: 0.8506 data_time: 0.2506 memory: 14901 loss: 1.1770 loss_prob: 0.6132 loss_thr: 0.4554 loss_db: 0.1084 2022/11/02 18:34:19 - mmengine - INFO - Epoch(train) [583][15/63] lr: 1.1896e-03 eta: 6:26:13 time: 0.5368 data_time: 0.0181 memory: 14901 loss: 1.2284 loss_prob: 0.6556 loss_thr: 0.4605 loss_db: 0.1122 2022/11/02 18:34:22 - mmengine - INFO - Epoch(train) [583][20/63] lr: 1.1896e-03 eta: 6:26:06 time: 0.5536 data_time: 0.0168 memory: 14901 loss: 1.1731 loss_prob: 0.6304 loss_thr: 0.4347 loss_db: 0.1080 2022/11/02 18:34:25 - mmengine - INFO - Epoch(train) [583][25/63] lr: 1.1896e-03 eta: 6:26:06 time: 0.5569 data_time: 0.0323 memory: 14901 loss: 1.1771 loss_prob: 0.6316 loss_thr: 0.4399 loss_db: 0.1055 2022/11/02 18:34:28 - mmengine - INFO - Epoch(train) [583][30/63] lr: 1.1896e-03 eta: 6:26:00 time: 0.5602 data_time: 0.0340 memory: 14901 loss: 1.2474 loss_prob: 0.6688 loss_thr: 0.4707 loss_db: 0.1079 2022/11/02 18:34:30 - mmengine - INFO - Epoch(train) [583][35/63] lr: 1.1896e-03 eta: 6:26:00 time: 0.5473 data_time: 0.0160 memory: 14901 loss: 1.2887 loss_prob: 0.6894 loss_thr: 0.4822 loss_db: 0.1170 2022/11/02 18:34:34 - mmengine - INFO - Epoch(train) [583][40/63] lr: 1.1896e-03 eta: 6:25:54 time: 0.6050 data_time: 0.0165 memory: 14901 loss: 1.2932 loss_prob: 0.7014 loss_thr: 0.4703 loss_db: 0.1215 2022/11/02 18:34:37 - mmengine - INFO - Epoch(train) [583][45/63] lr: 1.1896e-03 eta: 6:25:54 time: 0.6800 data_time: 0.0131 memory: 14901 loss: 1.2359 loss_prob: 0.6627 loss_thr: 0.4593 loss_db: 0.1139 2022/11/02 18:34:40 - mmengine - INFO - Epoch(train) [583][50/63] lr: 1.1896e-03 eta: 6:25:49 time: 0.6416 data_time: 0.0272 memory: 14901 loss: 1.3789 loss_prob: 0.7459 loss_thr: 0.5050 loss_db: 0.1280 2022/11/02 18:34:43 - mmengine - INFO - Epoch(train) [583][55/63] lr: 1.1896e-03 eta: 6:25:49 time: 0.5649 data_time: 0.0254 memory: 14901 loss: 1.4115 loss_prob: 0.7554 loss_thr: 0.5253 loss_db: 0.1308 2022/11/02 18:34:46 - mmengine - INFO - Epoch(train) [583][60/63] lr: 1.1896e-03 eta: 6:25:43 time: 0.6163 data_time: 0.0146 memory: 14901 loss: 1.2863 loss_prob: 0.6690 loss_thr: 0.5001 loss_db: 0.1172 2022/11/02 18:34:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:34:54 - mmengine - INFO - Epoch(train) [584][5/63] lr: 1.1879e-03 eta: 6:25:43 time: 0.9465 data_time: 0.2483 memory: 14901 loss: 1.2440 loss_prob: 0.6484 loss_thr: 0.4846 loss_db: 0.1110 2022/11/02 18:34:57 - mmengine - INFO - Epoch(train) [584][10/63] lr: 1.1879e-03 eta: 6:25:36 time: 0.8856 data_time: 0.2463 memory: 14901 loss: 1.2863 loss_prob: 0.6848 loss_thr: 0.4836 loss_db: 0.1179 2022/11/02 18:35:00 - mmengine - INFO - Epoch(train) [584][15/63] lr: 1.1879e-03 eta: 6:25:36 time: 0.6032 data_time: 0.0138 memory: 14901 loss: 1.3060 loss_prob: 0.7104 loss_thr: 0.4734 loss_db: 0.1222 2022/11/02 18:35:02 - mmengine - INFO - Epoch(train) [584][20/63] lr: 1.1879e-03 eta: 6:25:30 time: 0.5628 data_time: 0.0096 memory: 14901 loss: 1.3750 loss_prob: 0.7704 loss_thr: 0.4757 loss_db: 0.1289 2022/11/02 18:35:06 - mmengine - INFO - Epoch(train) [584][25/63] lr: 1.1879e-03 eta: 6:25:30 time: 0.5512 data_time: 0.0209 memory: 14901 loss: 1.3001 loss_prob: 0.7155 loss_thr: 0.4636 loss_db: 0.1210 2022/11/02 18:35:09 - mmengine - INFO - Epoch(train) [584][30/63] lr: 1.1879e-03 eta: 6:25:25 time: 0.6862 data_time: 0.0420 memory: 14901 loss: 1.3000 loss_prob: 0.6942 loss_thr: 0.4857 loss_db: 0.1201 2022/11/02 18:35:13 - mmengine - INFO - Epoch(train) [584][35/63] lr: 1.1879e-03 eta: 6:25:25 time: 0.7123 data_time: 0.0273 memory: 14901 loss: 1.3345 loss_prob: 0.7105 loss_thr: 0.5048 loss_db: 0.1192 2022/11/02 18:35:16 - mmengine - INFO - Epoch(train) [584][40/63] lr: 1.1879e-03 eta: 6:25:20 time: 0.6344 data_time: 0.0064 memory: 14901 loss: 1.2587 loss_prob: 0.6670 loss_thr: 0.4768 loss_db: 0.1149 2022/11/02 18:35:19 - mmengine - INFO - Epoch(train) [584][45/63] lr: 1.1879e-03 eta: 6:25:20 time: 0.5789 data_time: 0.0104 memory: 14901 loss: 1.2552 loss_prob: 0.6716 loss_thr: 0.4662 loss_db: 0.1173 2022/11/02 18:35:22 - mmengine - INFO - Epoch(train) [584][50/63] lr: 1.1879e-03 eta: 6:25:14 time: 0.6327 data_time: 0.0375 memory: 14901 loss: 1.3141 loss_prob: 0.7278 loss_thr: 0.4619 loss_db: 0.1244 2022/11/02 18:35:26 - mmengine - INFO - Epoch(train) [584][55/63] lr: 1.1879e-03 eta: 6:25:14 time: 0.7437 data_time: 0.0335 memory: 14901 loss: 1.3370 loss_prob: 0.7406 loss_thr: 0.4735 loss_db: 0.1229 2022/11/02 18:35:29 - mmengine - INFO - Epoch(train) [584][60/63] lr: 1.1879e-03 eta: 6:25:09 time: 0.7186 data_time: 0.0097 memory: 14901 loss: 1.2568 loss_prob: 0.6805 loss_thr: 0.4623 loss_db: 0.1140 2022/11/02 18:35:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:35:37 - mmengine - INFO - Epoch(train) [585][5/63] lr: 1.1861e-03 eta: 6:25:09 time: 0.9025 data_time: 0.2607 memory: 14901 loss: 1.2498 loss_prob: 0.6795 loss_thr: 0.4488 loss_db: 0.1216 2022/11/02 18:35:40 - mmengine - INFO - Epoch(train) [585][10/63] lr: 1.1861e-03 eta: 6:25:03 time: 0.8727 data_time: 0.2609 memory: 14901 loss: 1.3314 loss_prob: 0.7335 loss_thr: 0.4723 loss_db: 0.1257 2022/11/02 18:35:42 - mmengine - INFO - Epoch(train) [585][15/63] lr: 1.1861e-03 eta: 6:25:03 time: 0.5545 data_time: 0.0095 memory: 14901 loss: 1.3245 loss_prob: 0.7236 loss_thr: 0.4796 loss_db: 0.1214 2022/11/02 18:35:45 - mmengine - INFO - Epoch(train) [585][20/63] lr: 1.1861e-03 eta: 6:24:56 time: 0.5741 data_time: 0.0118 memory: 14901 loss: 1.4077 loss_prob: 0.7894 loss_thr: 0.4867 loss_db: 0.1316 2022/11/02 18:35:49 - mmengine - INFO - Epoch(train) [585][25/63] lr: 1.1861e-03 eta: 6:24:56 time: 0.6616 data_time: 0.0462 memory: 14901 loss: 1.4492 loss_prob: 0.8089 loss_thr: 0.5067 loss_db: 0.1336 2022/11/02 18:35:51 - mmengine - INFO - Epoch(train) [585][30/63] lr: 1.1861e-03 eta: 6:24:51 time: 0.6089 data_time: 0.0463 memory: 14901 loss: 1.2665 loss_prob: 0.6782 loss_thr: 0.4757 loss_db: 0.1127 2022/11/02 18:35:54 - mmengine - INFO - Epoch(train) [585][35/63] lr: 1.1861e-03 eta: 6:24:51 time: 0.5377 data_time: 0.0120 memory: 14901 loss: 1.2238 loss_prob: 0.6511 loss_thr: 0.4616 loss_db: 0.1110 2022/11/02 18:35:57 - mmengine - INFO - Epoch(train) [585][40/63] lr: 1.1861e-03 eta: 6:24:45 time: 0.5840 data_time: 0.0080 memory: 14901 loss: 1.2655 loss_prob: 0.6770 loss_thr: 0.4701 loss_db: 0.1183 2022/11/02 18:36:00 - mmengine - INFO - Epoch(train) [585][45/63] lr: 1.1861e-03 eta: 6:24:45 time: 0.5501 data_time: 0.0124 memory: 14901 loss: 1.3634 loss_prob: 0.7507 loss_thr: 0.4850 loss_db: 0.1277 2022/11/02 18:36:04 - mmengine - INFO - Epoch(train) [585][50/63] lr: 1.1861e-03 eta: 6:24:40 time: 0.6945 data_time: 0.0393 memory: 14901 loss: 1.3554 loss_prob: 0.7485 loss_thr: 0.4836 loss_db: 0.1233 2022/11/02 18:36:07 - mmengine - INFO - Epoch(train) [585][55/63] lr: 1.1861e-03 eta: 6:24:40 time: 0.7000 data_time: 0.0320 memory: 14901 loss: 1.2564 loss_prob: 0.6734 loss_thr: 0.4698 loss_db: 0.1133 2022/11/02 18:36:10 - mmengine - INFO - Epoch(train) [585][60/63] lr: 1.1861e-03 eta: 6:24:33 time: 0.5462 data_time: 0.0075 memory: 14901 loss: 1.2467 loss_prob: 0.6653 loss_thr: 0.4653 loss_db: 0.1161 2022/11/02 18:36:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:36:19 - mmengine - INFO - Epoch(train) [586][5/63] lr: 1.1844e-03 eta: 6:24:33 time: 1.0257 data_time: 0.2821 memory: 14901 loss: 1.1433 loss_prob: 0.5983 loss_thr: 0.4459 loss_db: 0.0991 2022/11/02 18:36:22 - mmengine - INFO - Epoch(train) [586][10/63] lr: 1.1844e-03 eta: 6:24:28 time: 1.0283 data_time: 0.2808 memory: 14901 loss: 1.2285 loss_prob: 0.6501 loss_thr: 0.4697 loss_db: 0.1087 2022/11/02 18:36:24 - mmengine - INFO - Epoch(train) [586][15/63] lr: 1.1844e-03 eta: 6:24:28 time: 0.5829 data_time: 0.0128 memory: 14901 loss: 1.3055 loss_prob: 0.6974 loss_thr: 0.4902 loss_db: 0.1179 2022/11/02 18:36:27 - mmengine - INFO - Epoch(train) [586][20/63] lr: 1.1844e-03 eta: 6:24:22 time: 0.5729 data_time: 0.0148 memory: 14901 loss: 1.2102 loss_prob: 0.6420 loss_thr: 0.4581 loss_db: 0.1101 2022/11/02 18:36:31 - mmengine - INFO - Epoch(train) [586][25/63] lr: 1.1844e-03 eta: 6:24:22 time: 0.6510 data_time: 0.0505 memory: 14901 loss: 1.1697 loss_prob: 0.6225 loss_thr: 0.4396 loss_db: 0.1076 2022/11/02 18:36:34 - mmengine - INFO - Epoch(train) [586][30/63] lr: 1.1844e-03 eta: 6:24:16 time: 0.6149 data_time: 0.0562 memory: 14901 loss: 1.2588 loss_prob: 0.6785 loss_thr: 0.4635 loss_db: 0.1168 2022/11/02 18:36:36 - mmengine - INFO - Epoch(train) [586][35/63] lr: 1.1844e-03 eta: 6:24:16 time: 0.5179 data_time: 0.0148 memory: 14901 loss: 1.3250 loss_prob: 0.7163 loss_thr: 0.4858 loss_db: 0.1228 2022/11/02 18:36:39 - mmengine - INFO - Epoch(train) [586][40/63] lr: 1.1844e-03 eta: 6:24:09 time: 0.5078 data_time: 0.0066 memory: 14901 loss: 1.1870 loss_prob: 0.6137 loss_thr: 0.4657 loss_db: 0.1076 2022/11/02 18:36:41 - mmengine - INFO - Epoch(train) [586][45/63] lr: 1.1844e-03 eta: 6:24:09 time: 0.4991 data_time: 0.0115 memory: 14901 loss: 1.1018 loss_prob: 0.5664 loss_thr: 0.4376 loss_db: 0.0978 2022/11/02 18:36:44 - mmengine - INFO - Epoch(train) [586][50/63] lr: 1.1844e-03 eta: 6:24:02 time: 0.5108 data_time: 0.0252 memory: 14901 loss: 1.1632 loss_prob: 0.6104 loss_thr: 0.4496 loss_db: 0.1032 2022/11/02 18:36:46 - mmengine - INFO - Epoch(train) [586][55/63] lr: 1.1844e-03 eta: 6:24:02 time: 0.5087 data_time: 0.0268 memory: 14901 loss: 1.1851 loss_prob: 0.6246 loss_thr: 0.4536 loss_db: 0.1069 2022/11/02 18:36:49 - mmengine - INFO - Epoch(train) [586][60/63] lr: 1.1844e-03 eta: 6:23:55 time: 0.4856 data_time: 0.0121 memory: 14901 loss: 1.1704 loss_prob: 0.6221 loss_thr: 0.4410 loss_db: 0.1073 2022/11/02 18:36:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:36:55 - mmengine - INFO - Epoch(train) [587][5/63] lr: 1.1827e-03 eta: 6:23:55 time: 0.7637 data_time: 0.2333 memory: 14901 loss: 1.1547 loss_prob: 0.6174 loss_thr: 0.4304 loss_db: 0.1068 2022/11/02 18:36:58 - mmengine - INFO - Epoch(train) [587][10/63] lr: 1.1827e-03 eta: 6:23:48 time: 0.7892 data_time: 0.2281 memory: 14901 loss: 1.2699 loss_prob: 0.6851 loss_thr: 0.4700 loss_db: 0.1148 2022/11/02 18:37:01 - mmengine - INFO - Epoch(train) [587][15/63] lr: 1.1827e-03 eta: 6:23:48 time: 0.5295 data_time: 0.0096 memory: 14901 loss: 1.2703 loss_prob: 0.6766 loss_thr: 0.4804 loss_db: 0.1134 2022/11/02 18:37:03 - mmengine - INFO - Epoch(train) [587][20/63] lr: 1.1827e-03 eta: 6:23:41 time: 0.5281 data_time: 0.0138 memory: 14901 loss: 1.3308 loss_prob: 0.7704 loss_thr: 0.4454 loss_db: 0.1149 2022/11/02 18:37:06 - mmengine - INFO - Epoch(train) [587][25/63] lr: 1.1827e-03 eta: 6:23:41 time: 0.5109 data_time: 0.0142 memory: 14901 loss: 1.2832 loss_prob: 0.7451 loss_thr: 0.4272 loss_db: 0.1109 2022/11/02 18:37:08 - mmengine - INFO - Epoch(train) [587][30/63] lr: 1.1827e-03 eta: 6:23:34 time: 0.5133 data_time: 0.0288 memory: 14901 loss: 1.2120 loss_prob: 0.6451 loss_thr: 0.4574 loss_db: 0.1095 2022/11/02 18:37:11 - mmengine - INFO - Epoch(train) [587][35/63] lr: 1.1827e-03 eta: 6:23:34 time: 0.5468 data_time: 0.0332 memory: 14901 loss: 1.2329 loss_prob: 0.6612 loss_thr: 0.4591 loss_db: 0.1126 2022/11/02 18:37:14 - mmengine - INFO - Epoch(train) [587][40/63] lr: 1.1827e-03 eta: 6:23:28 time: 0.5452 data_time: 0.0215 memory: 14901 loss: 1.2175 loss_prob: 0.6569 loss_thr: 0.4474 loss_db: 0.1132 2022/11/02 18:37:17 - mmengine - INFO - Epoch(train) [587][45/63] lr: 1.1827e-03 eta: 6:23:28 time: 0.5456 data_time: 0.0132 memory: 14901 loss: 1.2479 loss_prob: 0.6781 loss_thr: 0.4534 loss_db: 0.1163 2022/11/02 18:37:20 - mmengine - INFO - Epoch(train) [587][50/63] lr: 1.1827e-03 eta: 6:23:22 time: 0.6358 data_time: 0.0143 memory: 14901 loss: 1.2853 loss_prob: 0.7000 loss_thr: 0.4660 loss_db: 0.1193 2022/11/02 18:37:23 - mmengine - INFO - Epoch(train) [587][55/63] lr: 1.1827e-03 eta: 6:23:22 time: 0.6405 data_time: 0.0331 memory: 14901 loss: 1.2741 loss_prob: 0.6969 loss_thr: 0.4605 loss_db: 0.1167 2022/11/02 18:37:27 - mmengine - INFO - Epoch(train) [587][60/63] lr: 1.1827e-03 eta: 6:23:17 time: 0.6557 data_time: 0.0297 memory: 14901 loss: 1.1830 loss_prob: 0.6451 loss_thr: 0.4303 loss_db: 0.1076 2022/11/02 18:37:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:37:35 - mmengine - INFO - Epoch(train) [588][5/63] lr: 1.1809e-03 eta: 6:23:17 time: 0.9572 data_time: 0.2445 memory: 14901 loss: 1.4017 loss_prob: 0.7722 loss_thr: 0.5019 loss_db: 0.1275 2022/11/02 18:37:38 - mmengine - INFO - Epoch(train) [588][10/63] lr: 1.1809e-03 eta: 6:23:11 time: 0.9157 data_time: 0.2461 memory: 14901 loss: 1.4291 loss_prob: 0.8005 loss_thr: 0.4972 loss_db: 0.1314 2022/11/02 18:37:40 - mmengine - INFO - Epoch(train) [588][15/63] lr: 1.1809e-03 eta: 6:23:11 time: 0.5309 data_time: 0.0210 memory: 14901 loss: 1.3055 loss_prob: 0.7223 loss_thr: 0.4545 loss_db: 0.1287 2022/11/02 18:37:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:37:43 - mmengine - INFO - Epoch(train) [588][20/63] lr: 1.1809e-03 eta: 6:23:04 time: 0.5521 data_time: 0.0134 memory: 14901 loss: 1.1819 loss_prob: 0.6306 loss_thr: 0.4389 loss_db: 0.1124 2022/11/02 18:37:46 - mmengine - INFO - Epoch(train) [588][25/63] lr: 1.1809e-03 eta: 6:23:04 time: 0.5919 data_time: 0.0209 memory: 14901 loss: 1.2455 loss_prob: 0.6625 loss_thr: 0.4698 loss_db: 0.1131 2022/11/02 18:37:49 - mmengine - INFO - Epoch(train) [588][30/63] lr: 1.1809e-03 eta: 6:22:58 time: 0.5851 data_time: 0.0290 memory: 14901 loss: 1.3470 loss_prob: 0.7292 loss_thr: 0.4923 loss_db: 0.1256 2022/11/02 18:37:53 - mmengine - INFO - Epoch(train) [588][35/63] lr: 1.1809e-03 eta: 6:22:58 time: 0.7197 data_time: 0.0326 memory: 14901 loss: 1.2209 loss_prob: 0.6557 loss_thr: 0.4534 loss_db: 0.1118 2022/11/02 18:37:56 - mmengine - INFO - Epoch(train) [588][40/63] lr: 1.1809e-03 eta: 6:22:54 time: 0.7488 data_time: 0.0309 memory: 14901 loss: 1.1566 loss_prob: 0.6144 loss_thr: 0.4366 loss_db: 0.1056 2022/11/02 18:37:59 - mmengine - INFO - Epoch(train) [588][45/63] lr: 1.1809e-03 eta: 6:22:54 time: 0.6010 data_time: 0.0168 memory: 14901 loss: 1.2133 loss_prob: 0.6464 loss_thr: 0.4583 loss_db: 0.1086 2022/11/02 18:38:02 - mmengine - INFO - Epoch(train) [588][50/63] lr: 1.1809e-03 eta: 6:22:48 time: 0.6018 data_time: 0.0193 memory: 14901 loss: 1.2358 loss_prob: 0.6630 loss_thr: 0.4606 loss_db: 0.1122 2022/11/02 18:38:05 - mmengine - INFO - Epoch(train) [588][55/63] lr: 1.1809e-03 eta: 6:22:48 time: 0.6057 data_time: 0.0272 memory: 14901 loss: 1.1971 loss_prob: 0.6372 loss_thr: 0.4498 loss_db: 0.1100 2022/11/02 18:38:08 - mmengine - INFO - Epoch(train) [588][60/63] lr: 1.1809e-03 eta: 6:22:42 time: 0.5607 data_time: 0.0254 memory: 14901 loss: 1.1892 loss_prob: 0.6397 loss_thr: 0.4392 loss_db: 0.1103 2022/11/02 18:38:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:38:16 - mmengine - INFO - Epoch(train) [589][5/63] lr: 1.1792e-03 eta: 6:22:42 time: 0.9167 data_time: 0.2301 memory: 14901 loss: 1.3373 loss_prob: 0.7301 loss_thr: 0.4833 loss_db: 0.1238 2022/11/02 18:38:20 - mmengine - INFO - Epoch(train) [589][10/63] lr: 1.1792e-03 eta: 6:22:37 time: 1.0955 data_time: 0.2326 memory: 14901 loss: 1.2726 loss_prob: 0.6844 loss_thr: 0.4723 loss_db: 0.1160 2022/11/02 18:38:23 - mmengine - INFO - Epoch(train) [589][15/63] lr: 1.1792e-03 eta: 6:22:37 time: 0.7282 data_time: 0.0170 memory: 14901 loss: 1.2441 loss_prob: 0.6704 loss_thr: 0.4584 loss_db: 0.1153 2022/11/02 18:38:27 - mmengine - INFO - Epoch(train) [589][20/63] lr: 1.1792e-03 eta: 6:22:32 time: 0.6569 data_time: 0.0132 memory: 14901 loss: 1.2775 loss_prob: 0.6879 loss_thr: 0.4745 loss_db: 0.1151 2022/11/02 18:38:31 - mmengine - INFO - Epoch(train) [589][25/63] lr: 1.1792e-03 eta: 6:22:32 time: 0.7203 data_time: 0.0240 memory: 14901 loss: 1.2854 loss_prob: 0.6896 loss_thr: 0.4813 loss_db: 0.1146 2022/11/02 18:38:33 - mmengine - INFO - Epoch(train) [589][30/63] lr: 1.1792e-03 eta: 6:22:27 time: 0.6581 data_time: 0.0346 memory: 14901 loss: 1.1655 loss_prob: 0.6123 loss_thr: 0.4488 loss_db: 0.1043 2022/11/02 18:38:37 - mmengine - INFO - Epoch(train) [589][35/63] lr: 1.1792e-03 eta: 6:22:27 time: 0.6531 data_time: 0.0303 memory: 14901 loss: 1.1546 loss_prob: 0.6033 loss_thr: 0.4474 loss_db: 0.1039 2022/11/02 18:38:40 - mmengine - INFO - Epoch(train) [589][40/63] lr: 1.1792e-03 eta: 6:22:22 time: 0.6967 data_time: 0.0202 memory: 14901 loss: 1.2618 loss_prob: 0.6778 loss_thr: 0.4706 loss_db: 0.1135 2022/11/02 18:38:43 - mmengine - INFO - Epoch(train) [589][45/63] lr: 1.1792e-03 eta: 6:22:22 time: 0.5857 data_time: 0.0141 memory: 14901 loss: 1.2517 loss_prob: 0.6798 loss_thr: 0.4576 loss_db: 0.1143 2022/11/02 18:38:46 - mmengine - INFO - Epoch(train) [589][50/63] lr: 1.1792e-03 eta: 6:22:15 time: 0.5748 data_time: 0.0289 memory: 14901 loss: 1.1820 loss_prob: 0.6312 loss_thr: 0.4419 loss_db: 0.1089 2022/11/02 18:38:49 - mmengine - INFO - Epoch(train) [589][55/63] lr: 1.1792e-03 eta: 6:22:15 time: 0.5718 data_time: 0.0291 memory: 14901 loss: 1.1622 loss_prob: 0.6117 loss_thr: 0.4460 loss_db: 0.1045 2022/11/02 18:38:52 - mmengine - INFO - Epoch(train) [589][60/63] lr: 1.1792e-03 eta: 6:22:09 time: 0.5371 data_time: 0.0171 memory: 14901 loss: 1.2022 loss_prob: 0.6480 loss_thr: 0.4461 loss_db: 0.1081 2022/11/02 18:38:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:38:59 - mmengine - INFO - Epoch(train) [590][5/63] lr: 1.1775e-03 eta: 6:22:09 time: 0.8733 data_time: 0.2325 memory: 14901 loss: 1.1861 loss_prob: 0.6310 loss_thr: 0.4457 loss_db: 0.1094 2022/11/02 18:39:02 - mmengine - INFO - Epoch(train) [590][10/63] lr: 1.1775e-03 eta: 6:22:02 time: 0.8861 data_time: 0.2287 memory: 14901 loss: 1.1633 loss_prob: 0.6182 loss_thr: 0.4403 loss_db: 0.1048 2022/11/02 18:39:05 - mmengine - INFO - Epoch(train) [590][15/63] lr: 1.1775e-03 eta: 6:22:02 time: 0.5440 data_time: 0.0101 memory: 14901 loss: 1.2258 loss_prob: 0.6678 loss_thr: 0.4450 loss_db: 0.1130 2022/11/02 18:39:07 - mmengine - INFO - Epoch(train) [590][20/63] lr: 1.1775e-03 eta: 6:21:56 time: 0.5227 data_time: 0.0095 memory: 14901 loss: 1.1180 loss_prob: 0.5943 loss_thr: 0.4216 loss_db: 0.1020 2022/11/02 18:39:10 - mmengine - INFO - Epoch(train) [590][25/63] lr: 1.1775e-03 eta: 6:21:56 time: 0.5341 data_time: 0.0145 memory: 14901 loss: 1.0751 loss_prob: 0.5675 loss_thr: 0.4099 loss_db: 0.0976 2022/11/02 18:39:13 - mmengine - INFO - Epoch(train) [590][30/63] lr: 1.1775e-03 eta: 6:21:50 time: 0.5963 data_time: 0.0429 memory: 14901 loss: 1.1654 loss_prob: 0.6251 loss_thr: 0.4326 loss_db: 0.1077 2022/11/02 18:39:17 - mmengine - INFO - Epoch(train) [590][35/63] lr: 1.1775e-03 eta: 6:21:50 time: 0.7087 data_time: 0.0391 memory: 14901 loss: 1.1891 loss_prob: 0.6402 loss_thr: 0.4393 loss_db: 0.1097 2022/11/02 18:39:19 - mmengine - INFO - Epoch(train) [590][40/63] lr: 1.1775e-03 eta: 6:21:44 time: 0.6364 data_time: 0.0123 memory: 14901 loss: 1.1589 loss_prob: 0.6184 loss_thr: 0.4340 loss_db: 0.1066 2022/11/02 18:39:22 - mmengine - INFO - Epoch(train) [590][45/63] lr: 1.1775e-03 eta: 6:21:44 time: 0.5126 data_time: 0.0107 memory: 14901 loss: 1.1708 loss_prob: 0.6157 loss_thr: 0.4492 loss_db: 0.1059 2022/11/02 18:39:25 - mmengine - INFO - Epoch(train) [590][50/63] lr: 1.1775e-03 eta: 6:21:38 time: 0.5407 data_time: 0.0272 memory: 14901 loss: 1.2232 loss_prob: 0.6549 loss_thr: 0.4606 loss_db: 0.1077 2022/11/02 18:39:28 - mmengine - INFO - Epoch(train) [590][55/63] lr: 1.1775e-03 eta: 6:21:38 time: 0.5809 data_time: 0.0305 memory: 14901 loss: 1.2641 loss_prob: 0.6880 loss_thr: 0.4618 loss_db: 0.1143 2022/11/02 18:39:30 - mmengine - INFO - Epoch(train) [590][60/63] lr: 1.1775e-03 eta: 6:21:31 time: 0.5582 data_time: 0.0131 memory: 14901 loss: 1.2777 loss_prob: 0.6926 loss_thr: 0.4664 loss_db: 0.1187 2022/11/02 18:39:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:39:38 - mmengine - INFO - Epoch(train) [591][5/63] lr: 1.1757e-03 eta: 6:21:31 time: 0.8982 data_time: 0.2386 memory: 14901 loss: 1.0574 loss_prob: 0.5533 loss_thr: 0.4096 loss_db: 0.0944 2022/11/02 18:39:41 - mmengine - INFO - Epoch(train) [591][10/63] lr: 1.1757e-03 eta: 6:21:26 time: 0.9697 data_time: 0.2390 memory: 14901 loss: 1.0795 loss_prob: 0.5483 loss_thr: 0.4382 loss_db: 0.0930 2022/11/02 18:39:44 - mmengine - INFO - Epoch(train) [591][15/63] lr: 1.1757e-03 eta: 6:21:26 time: 0.5796 data_time: 0.0146 memory: 14901 loss: 1.2461 loss_prob: 0.6556 loss_thr: 0.4782 loss_db: 0.1122 2022/11/02 18:39:47 - mmengine - INFO - Epoch(train) [591][20/63] lr: 1.1757e-03 eta: 6:21:19 time: 0.5326 data_time: 0.0141 memory: 14901 loss: 1.2327 loss_prob: 0.6619 loss_thr: 0.4562 loss_db: 0.1146 2022/11/02 18:39:50 - mmengine - INFO - Epoch(train) [591][25/63] lr: 1.1757e-03 eta: 6:21:19 time: 0.5485 data_time: 0.0406 memory: 14901 loss: 1.3067 loss_prob: 0.7116 loss_thr: 0.4772 loss_db: 0.1179 2022/11/02 18:39:53 - mmengine - INFO - Epoch(train) [591][30/63] lr: 1.1757e-03 eta: 6:21:13 time: 0.5941 data_time: 0.0387 memory: 14901 loss: 1.2728 loss_prob: 0.6866 loss_thr: 0.4754 loss_db: 0.1108 2022/11/02 18:39:57 - mmengine - INFO - Epoch(train) [591][35/63] lr: 1.1757e-03 eta: 6:21:13 time: 0.7454 data_time: 0.0081 memory: 14901 loss: 1.1778 loss_prob: 0.6170 loss_thr: 0.4566 loss_db: 0.1042 2022/11/02 18:40:01 - mmengine - INFO - Epoch(train) [591][40/63] lr: 1.1757e-03 eta: 6:21:10 time: 0.8546 data_time: 0.0112 memory: 14901 loss: 1.2769 loss_prob: 0.6767 loss_thr: 0.4850 loss_db: 0.1152 2022/11/02 18:40:05 - mmengine - INFO - Epoch(train) [591][45/63] lr: 1.1757e-03 eta: 6:21:10 time: 0.7487 data_time: 0.0083 memory: 14901 loss: 1.2852 loss_prob: 0.6753 loss_thr: 0.4947 loss_db: 0.1152 2022/11/02 18:40:08 - mmengine - INFO - Epoch(train) [591][50/63] lr: 1.1757e-03 eta: 6:21:05 time: 0.6742 data_time: 0.0528 memory: 14901 loss: 1.2436 loss_prob: 0.6563 loss_thr: 0.4757 loss_db: 0.1116 2022/11/02 18:40:12 - mmengine - INFO - Epoch(train) [591][55/63] lr: 1.1757e-03 eta: 6:21:05 time: 0.7013 data_time: 0.0555 memory: 14901 loss: 1.1793 loss_prob: 0.6258 loss_thr: 0.4475 loss_db: 0.1060 2022/11/02 18:40:15 - mmengine - INFO - Epoch(train) [591][60/63] lr: 1.1757e-03 eta: 6:20:59 time: 0.6692 data_time: 0.0092 memory: 14901 loss: 1.1361 loss_prob: 0.5869 loss_thr: 0.4478 loss_db: 0.1014 2022/11/02 18:40:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:40:22 - mmengine - INFO - Epoch(train) [592][5/63] lr: 1.1740e-03 eta: 6:20:59 time: 0.8640 data_time: 0.2446 memory: 14901 loss: 1.2284 loss_prob: 0.6389 loss_thr: 0.4800 loss_db: 0.1095 2022/11/02 18:40:25 - mmengine - INFO - Epoch(train) [592][10/63] lr: 1.1740e-03 eta: 6:20:53 time: 0.9081 data_time: 0.2406 memory: 14901 loss: 1.1314 loss_prob: 0.5925 loss_thr: 0.4356 loss_db: 0.1033 2022/11/02 18:40:28 - mmengine - INFO - Epoch(train) [592][15/63] lr: 1.1740e-03 eta: 6:20:53 time: 0.5748 data_time: 0.0093 memory: 14901 loss: 1.1833 loss_prob: 0.6337 loss_thr: 0.4408 loss_db: 0.1088 2022/11/02 18:40:31 - mmengine - INFO - Epoch(train) [592][20/63] lr: 1.1740e-03 eta: 6:20:46 time: 0.5440 data_time: 0.0111 memory: 14901 loss: 1.2570 loss_prob: 0.6792 loss_thr: 0.4628 loss_db: 0.1150 2022/11/02 18:40:34 - mmengine - INFO - Epoch(train) [592][25/63] lr: 1.1740e-03 eta: 6:20:46 time: 0.5909 data_time: 0.0115 memory: 14901 loss: 1.2187 loss_prob: 0.6573 loss_thr: 0.4483 loss_db: 0.1131 2022/11/02 18:40:38 - mmengine - INFO - Epoch(train) [592][30/63] lr: 1.1740e-03 eta: 6:20:42 time: 0.7254 data_time: 0.0414 memory: 14901 loss: 1.1757 loss_prob: 0.6316 loss_thr: 0.4372 loss_db: 0.1069 2022/11/02 18:40:41 - mmengine - INFO - Epoch(train) [592][35/63] lr: 1.1740e-03 eta: 6:20:42 time: 0.6783 data_time: 0.0404 memory: 14901 loss: 1.2603 loss_prob: 0.6818 loss_thr: 0.4641 loss_db: 0.1145 2022/11/02 18:40:44 - mmengine - INFO - Epoch(train) [592][40/63] lr: 1.1740e-03 eta: 6:20:37 time: 0.6694 data_time: 0.0076 memory: 14901 loss: 1.2814 loss_prob: 0.7023 loss_thr: 0.4571 loss_db: 0.1219 2022/11/02 18:40:47 - mmengine - INFO - Epoch(train) [592][45/63] lr: 1.1740e-03 eta: 6:20:37 time: 0.6672 data_time: 0.0070 memory: 14901 loss: 1.4163 loss_prob: 0.8139 loss_thr: 0.4636 loss_db: 0.1387 2022/11/02 18:40:50 - mmengine - INFO - Epoch(train) [592][50/63] lr: 1.1740e-03 eta: 6:20:31 time: 0.5833 data_time: 0.0313 memory: 14901 loss: 1.4561 loss_prob: 0.8377 loss_thr: 0.4834 loss_db: 0.1350 2022/11/02 18:40:54 - mmengine - INFO - Epoch(train) [592][55/63] lr: 1.1740e-03 eta: 6:20:31 time: 0.6678 data_time: 0.0307 memory: 14901 loss: 1.3519 loss_prob: 0.7504 loss_thr: 0.4808 loss_db: 0.1207 2022/11/02 18:40:57 - mmengine - INFO - Epoch(train) [592][60/63] lr: 1.1740e-03 eta: 6:20:25 time: 0.6366 data_time: 0.0106 memory: 14901 loss: 1.4137 loss_prob: 0.7723 loss_thr: 0.5095 loss_db: 0.1319 2022/11/02 18:40:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:41:05 - mmengine - INFO - Epoch(train) [593][5/63] lr: 1.1722e-03 eta: 6:20:25 time: 0.9259 data_time: 0.2812 memory: 14901 loss: 1.3085 loss_prob: 0.7131 loss_thr: 0.4744 loss_db: 0.1210 2022/11/02 18:41:08 - mmengine - INFO - Epoch(train) [593][10/63] lr: 1.1722e-03 eta: 6:20:19 time: 0.9674 data_time: 0.2820 memory: 14901 loss: 1.2655 loss_prob: 0.6887 loss_thr: 0.4627 loss_db: 0.1141 2022/11/02 18:41:11 - mmengine - INFO - Epoch(train) [593][15/63] lr: 1.1722e-03 eta: 6:20:19 time: 0.6582 data_time: 0.0117 memory: 14901 loss: 1.2420 loss_prob: 0.6765 loss_thr: 0.4506 loss_db: 0.1149 2022/11/02 18:41:14 - mmengine - INFO - Epoch(train) [593][20/63] lr: 1.1722e-03 eta: 6:20:14 time: 0.6636 data_time: 0.0134 memory: 14901 loss: 1.2475 loss_prob: 0.6725 loss_thr: 0.4612 loss_db: 0.1137 2022/11/02 18:41:17 - mmengine - INFO - Epoch(train) [593][25/63] lr: 1.1722e-03 eta: 6:20:14 time: 0.5916 data_time: 0.0405 memory: 14901 loss: 1.3093 loss_prob: 0.7036 loss_thr: 0.4880 loss_db: 0.1178 2022/11/02 18:41:21 - mmengine - INFO - Epoch(train) [593][30/63] lr: 1.1722e-03 eta: 6:20:09 time: 0.7109 data_time: 0.0387 memory: 14901 loss: 1.2707 loss_prob: 0.6705 loss_thr: 0.4819 loss_db: 0.1182 2022/11/02 18:41:24 - mmengine - INFO - Epoch(train) [593][35/63] lr: 1.1722e-03 eta: 6:20:09 time: 0.6869 data_time: 0.0074 memory: 14901 loss: 1.2283 loss_prob: 0.6429 loss_thr: 0.4725 loss_db: 0.1130 2022/11/02 18:41:28 - mmengine - INFO - Epoch(train) [593][40/63] lr: 1.1722e-03 eta: 6:20:04 time: 0.6412 data_time: 0.0106 memory: 14901 loss: 1.2288 loss_prob: 0.6418 loss_thr: 0.4775 loss_db: 0.1095 2022/11/02 18:41:31 - mmengine - INFO - Epoch(train) [593][45/63] lr: 1.1722e-03 eta: 6:20:04 time: 0.6526 data_time: 0.0136 memory: 14901 loss: 1.2267 loss_prob: 0.6396 loss_thr: 0.4783 loss_db: 0.1088 2022/11/02 18:41:34 - mmengine - INFO - Epoch(train) [593][50/63] lr: 1.1722e-03 eta: 6:19:58 time: 0.5921 data_time: 0.0291 memory: 14901 loss: 1.1901 loss_prob: 0.6322 loss_thr: 0.4499 loss_db: 0.1079 2022/11/02 18:41:37 - mmengine - INFO - Epoch(train) [593][55/63] lr: 1.1722e-03 eta: 6:19:58 time: 0.5905 data_time: 0.0293 memory: 14901 loss: 1.1515 loss_prob: 0.6119 loss_thr: 0.4347 loss_db: 0.1048 2022/11/02 18:41:41 - mmengine - INFO - Epoch(train) [593][60/63] lr: 1.1722e-03 eta: 6:19:53 time: 0.7133 data_time: 0.0105 memory: 14901 loss: 1.1782 loss_prob: 0.6211 loss_thr: 0.4498 loss_db: 0.1073 2022/11/02 18:41:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:41:48 - mmengine - INFO - Epoch(train) [594][5/63] lr: 1.1705e-03 eta: 6:19:53 time: 0.9604 data_time: 0.2377 memory: 14901 loss: 1.1990 loss_prob: 0.6391 loss_thr: 0.4498 loss_db: 0.1101 2022/11/02 18:41:51 - mmengine - INFO - Epoch(train) [594][10/63] lr: 1.1705e-03 eta: 6:19:47 time: 0.9039 data_time: 0.2401 memory: 14901 loss: 1.1368 loss_prob: 0.5977 loss_thr: 0.4397 loss_db: 0.0994 2022/11/02 18:41:54 - mmengine - INFO - Epoch(train) [594][15/63] lr: 1.1705e-03 eta: 6:19:47 time: 0.5807 data_time: 0.0154 memory: 14901 loss: 1.1755 loss_prob: 0.6212 loss_thr: 0.4498 loss_db: 0.1046 2022/11/02 18:41:58 - mmengine - INFO - Epoch(train) [594][20/63] lr: 1.1705e-03 eta: 6:19:42 time: 0.6972 data_time: 0.0113 memory: 14901 loss: 1.1928 loss_prob: 0.6329 loss_thr: 0.4504 loss_db: 0.1094 2022/11/02 18:42:01 - mmengine - INFO - Epoch(train) [594][25/63] lr: 1.1705e-03 eta: 6:19:42 time: 0.7004 data_time: 0.0388 memory: 14901 loss: 1.2219 loss_prob: 0.6515 loss_thr: 0.4585 loss_db: 0.1120 2022/11/02 18:42:06 - mmengine - INFO - Epoch(train) [594][30/63] lr: 1.1705e-03 eta: 6:19:38 time: 0.8249 data_time: 0.0488 memory: 14901 loss: 1.2488 loss_prob: 0.6744 loss_thr: 0.4596 loss_db: 0.1148 2022/11/02 18:42:10 - mmengine - INFO - Epoch(train) [594][35/63] lr: 1.1705e-03 eta: 6:19:38 time: 0.8648 data_time: 0.0169 memory: 14901 loss: 1.2346 loss_prob: 0.6688 loss_thr: 0.4527 loss_db: 0.1131 2022/11/02 18:42:13 - mmengine - INFO - Epoch(train) [594][40/63] lr: 1.1705e-03 eta: 6:19:32 time: 0.6205 data_time: 0.0107 memory: 14901 loss: 1.1747 loss_prob: 0.6282 loss_thr: 0.4410 loss_db: 0.1055 2022/11/02 18:42:15 - mmengine - INFO - Epoch(train) [594][45/63] lr: 1.1705e-03 eta: 6:19:32 time: 0.5479 data_time: 0.0125 memory: 14901 loss: 1.1574 loss_prob: 0.6088 loss_thr: 0.4442 loss_db: 0.1044 2022/11/02 18:42:18 - mmengine - INFO - Epoch(train) [594][50/63] lr: 1.1705e-03 eta: 6:19:26 time: 0.5295 data_time: 0.0231 memory: 14901 loss: 1.2248 loss_prob: 0.6501 loss_thr: 0.4623 loss_db: 0.1124 2022/11/02 18:42:21 - mmengine - INFO - Epoch(train) [594][55/63] lr: 1.1705e-03 eta: 6:19:26 time: 0.5863 data_time: 0.0254 memory: 14901 loss: 1.2165 loss_prob: 0.6480 loss_thr: 0.4561 loss_db: 0.1124 2022/11/02 18:42:24 - mmengine - INFO - Epoch(train) [594][60/63] lr: 1.1705e-03 eta: 6:19:20 time: 0.6074 data_time: 0.0142 memory: 14901 loss: 1.2137 loss_prob: 0.6478 loss_thr: 0.4556 loss_db: 0.1103 2022/11/02 18:42:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:42:31 - mmengine - INFO - Epoch(train) [595][5/63] lr: 1.1688e-03 eta: 6:19:20 time: 0.8044 data_time: 0.2537 memory: 14901 loss: 1.1281 loss_prob: 0.5979 loss_thr: 0.4272 loss_db: 0.1030 2022/11/02 18:42:34 - mmengine - INFO - Epoch(train) [595][10/63] lr: 1.1688e-03 eta: 6:19:13 time: 0.8547 data_time: 0.2527 memory: 14901 loss: 1.1502 loss_prob: 0.6069 loss_thr: 0.4379 loss_db: 0.1054 2022/11/02 18:42:37 - mmengine - INFO - Epoch(train) [595][15/63] lr: 1.1688e-03 eta: 6:19:13 time: 0.5769 data_time: 0.0118 memory: 14901 loss: 1.0744 loss_prob: 0.5675 loss_thr: 0.4093 loss_db: 0.0977 2022/11/02 18:42:39 - mmengine - INFO - Epoch(train) [595][20/63] lr: 1.1688e-03 eta: 6:19:06 time: 0.5473 data_time: 0.0139 memory: 14901 loss: 1.0638 loss_prob: 0.5597 loss_thr: 0.4089 loss_db: 0.0952 2022/11/02 18:42:43 - mmengine - INFO - Epoch(train) [595][25/63] lr: 1.1688e-03 eta: 6:19:06 time: 0.5917 data_time: 0.0576 memory: 14901 loss: 1.2400 loss_prob: 0.6648 loss_thr: 0.4636 loss_db: 0.1116 2022/11/02 18:42:46 - mmengine - INFO - Epoch(train) [595][30/63] lr: 1.1688e-03 eta: 6:19:01 time: 0.6856 data_time: 0.0550 memory: 14901 loss: 1.2846 loss_prob: 0.6988 loss_thr: 0.4672 loss_db: 0.1185 2022/11/02 18:42:49 - mmengine - INFO - Epoch(train) [595][35/63] lr: 1.1688e-03 eta: 6:19:01 time: 0.6224 data_time: 0.0086 memory: 14901 loss: 1.2326 loss_prob: 0.6711 loss_thr: 0.4482 loss_db: 0.1133 2022/11/02 18:42:51 - mmengine - INFO - Epoch(train) [595][40/63] lr: 1.1688e-03 eta: 6:18:55 time: 0.5184 data_time: 0.0056 memory: 14901 loss: 1.2179 loss_prob: 0.6628 loss_thr: 0.4439 loss_db: 0.1112 2022/11/02 18:42:54 - mmengine - INFO - Epoch(train) [595][45/63] lr: 1.1688e-03 eta: 6:18:55 time: 0.4971 data_time: 0.0083 memory: 14901 loss: 1.2308 loss_prob: 0.6620 loss_thr: 0.4561 loss_db: 0.1127 2022/11/02 18:42:58 - mmengine - INFO - Epoch(train) [595][50/63] lr: 1.1688e-03 eta: 6:18:49 time: 0.6088 data_time: 0.0286 memory: 14901 loss: 1.2241 loss_prob: 0.6570 loss_thr: 0.4551 loss_db: 0.1120 2022/11/02 18:43:00 - mmengine - INFO - Epoch(train) [595][55/63] lr: 1.1688e-03 eta: 6:18:49 time: 0.6372 data_time: 0.0280 memory: 14901 loss: 1.2143 loss_prob: 0.6504 loss_thr: 0.4534 loss_db: 0.1105 2022/11/02 18:43:03 - mmengine - INFO - Epoch(train) [595][60/63] lr: 1.1688e-03 eta: 6:18:42 time: 0.5066 data_time: 0.0098 memory: 14901 loss: 1.2783 loss_prob: 0.6855 loss_thr: 0.4762 loss_db: 0.1166 2022/11/02 18:43:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:43:09 - mmengine - INFO - Epoch(train) [596][5/63] lr: 1.1670e-03 eta: 6:18:42 time: 0.7224 data_time: 0.2273 memory: 14901 loss: 1.3369 loss_prob: 0.7396 loss_thr: 0.4727 loss_db: 0.1247 2022/11/02 18:43:12 - mmengine - INFO - Epoch(train) [596][10/63] lr: 1.1670e-03 eta: 6:18:34 time: 0.7747 data_time: 0.2302 memory: 14901 loss: 1.2422 loss_prob: 0.6739 loss_thr: 0.4536 loss_db: 0.1147 2022/11/02 18:43:14 - mmengine - INFO - Epoch(train) [596][15/63] lr: 1.1670e-03 eta: 6:18:34 time: 0.5192 data_time: 0.0135 memory: 14901 loss: 1.3315 loss_prob: 0.7231 loss_thr: 0.4845 loss_db: 0.1239 2022/11/02 18:43:17 - mmengine - INFO - Epoch(train) [596][20/63] lr: 1.1670e-03 eta: 6:18:27 time: 0.5208 data_time: 0.0116 memory: 14901 loss: 1.2398 loss_prob: 0.6479 loss_thr: 0.4811 loss_db: 0.1108 2022/11/02 18:43:19 - mmengine - INFO - Epoch(train) [596][25/63] lr: 1.1670e-03 eta: 6:18:27 time: 0.5264 data_time: 0.0148 memory: 14901 loss: 1.1454 loss_prob: 0.5851 loss_thr: 0.4594 loss_db: 0.1009 2022/11/02 18:43:23 - mmengine - INFO - Epoch(train) [596][30/63] lr: 1.1670e-03 eta: 6:18:22 time: 0.6141 data_time: 0.0480 memory: 14901 loss: 1.2131 loss_prob: 0.6402 loss_thr: 0.4615 loss_db: 0.1114 2022/11/02 18:43:26 - mmengine - INFO - Epoch(train) [596][35/63] lr: 1.1670e-03 eta: 6:18:22 time: 0.6906 data_time: 0.0463 memory: 14901 loss: 1.2427 loss_prob: 0.6621 loss_thr: 0.4666 loss_db: 0.1141 2022/11/02 18:43:29 - mmengine - INFO - Epoch(train) [596][40/63] lr: 1.1670e-03 eta: 6:18:16 time: 0.6487 data_time: 0.0135 memory: 14901 loss: 1.2804 loss_prob: 0.6874 loss_thr: 0.4750 loss_db: 0.1180 2022/11/02 18:43:32 - mmengine - INFO - Epoch(train) [596][45/63] lr: 1.1670e-03 eta: 6:18:16 time: 0.5624 data_time: 0.0087 memory: 14901 loss: 1.1747 loss_prob: 0.6238 loss_thr: 0.4438 loss_db: 0.1071 2022/11/02 18:43:35 - mmengine - INFO - Epoch(train) [596][50/63] lr: 1.1670e-03 eta: 6:18:10 time: 0.5718 data_time: 0.0209 memory: 14901 loss: 1.1404 loss_prob: 0.5932 loss_thr: 0.4448 loss_db: 0.1025 2022/11/02 18:43:38 - mmengine - INFO - Epoch(train) [596][55/63] lr: 1.1670e-03 eta: 6:18:10 time: 0.6075 data_time: 0.0235 memory: 14901 loss: 1.2298 loss_prob: 0.6474 loss_thr: 0.4740 loss_db: 0.1084 2022/11/02 18:43:41 - mmengine - INFO - Epoch(train) [596][60/63] lr: 1.1670e-03 eta: 6:18:03 time: 0.5400 data_time: 0.0130 memory: 14901 loss: 1.1961 loss_prob: 0.6340 loss_thr: 0.4566 loss_db: 0.1056 2022/11/02 18:43:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:43:48 - mmengine - INFO - Epoch(train) [597][5/63] lr: 1.1653e-03 eta: 6:18:03 time: 0.7902 data_time: 0.2068 memory: 14901 loss: 1.1968 loss_prob: 0.6332 loss_thr: 0.4552 loss_db: 0.1084 2022/11/02 18:43:51 - mmengine - INFO - Epoch(train) [597][10/63] lr: 1.1653e-03 eta: 6:17:57 time: 0.9413 data_time: 0.2297 memory: 14901 loss: 1.2704 loss_prob: 0.6754 loss_thr: 0.4802 loss_db: 0.1148 2022/11/02 18:43:55 - mmengine - INFO - Epoch(train) [597][15/63] lr: 1.1653e-03 eta: 6:17:57 time: 0.7408 data_time: 0.0343 memory: 14901 loss: 1.3016 loss_prob: 0.7054 loss_thr: 0.4754 loss_db: 0.1208 2022/11/02 18:43:58 - mmengine - INFO - Epoch(train) [597][20/63] lr: 1.1653e-03 eta: 6:17:52 time: 0.6563 data_time: 0.0103 memory: 14901 loss: 1.2483 loss_prob: 0.6835 loss_thr: 0.4464 loss_db: 0.1184 2022/11/02 18:44:01 - mmengine - INFO - Epoch(train) [597][25/63] lr: 1.1653e-03 eta: 6:17:52 time: 0.6118 data_time: 0.0294 memory: 14901 loss: 1.2643 loss_prob: 0.7130 loss_thr: 0.4323 loss_db: 0.1190 2022/11/02 18:44:05 - mmengine - INFO - Epoch(train) [597][30/63] lr: 1.1653e-03 eta: 6:17:47 time: 0.7181 data_time: 0.0477 memory: 14901 loss: 1.2280 loss_prob: 0.6838 loss_thr: 0.4325 loss_db: 0.1118 2022/11/02 18:44:10 - mmengine - INFO - Epoch(train) [597][35/63] lr: 1.1653e-03 eta: 6:17:47 time: 0.8478 data_time: 0.0277 memory: 14901 loss: 1.1679 loss_prob: 0.6228 loss_thr: 0.4407 loss_db: 0.1043 2022/11/02 18:44:13 - mmengine - INFO - Epoch(train) [597][40/63] lr: 1.1653e-03 eta: 6:17:43 time: 0.7760 data_time: 0.0100 memory: 14901 loss: 1.1816 loss_prob: 0.6296 loss_thr: 0.4432 loss_db: 0.1088 2022/11/02 18:44:16 - mmengine - INFO - Epoch(train) [597][45/63] lr: 1.1653e-03 eta: 6:17:43 time: 0.6385 data_time: 0.0108 memory: 14901 loss: 1.2694 loss_prob: 0.6830 loss_thr: 0.4688 loss_db: 0.1176 2022/11/02 18:44:19 - mmengine - INFO - Epoch(train) [597][50/63] lr: 1.1653e-03 eta: 6:17:38 time: 0.6433 data_time: 0.0205 memory: 14901 loss: 1.2703 loss_prob: 0.6864 loss_thr: 0.4674 loss_db: 0.1165 2022/11/02 18:44:22 - mmengine - INFO - Epoch(train) [597][55/63] lr: 1.1653e-03 eta: 6:17:38 time: 0.6134 data_time: 0.0332 memory: 14901 loss: 1.2079 loss_prob: 0.6429 loss_thr: 0.4554 loss_db: 0.1096 2022/11/02 18:44:25 - mmengine - INFO - Epoch(train) [597][60/63] lr: 1.1653e-03 eta: 6:17:31 time: 0.5363 data_time: 0.0242 memory: 14901 loss: 1.2298 loss_prob: 0.6660 loss_thr: 0.4556 loss_db: 0.1082 2022/11/02 18:44:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:44:32 - mmengine - INFO - Epoch(train) [598][5/63] lr: 1.1635e-03 eta: 6:17:31 time: 0.8835 data_time: 0.2960 memory: 14901 loss: 1.2024 loss_prob: 0.6438 loss_thr: 0.4465 loss_db: 0.1121 2022/11/02 18:44:36 - mmengine - INFO - Epoch(train) [598][10/63] lr: 1.1635e-03 eta: 6:17:25 time: 0.9778 data_time: 0.3028 memory: 14901 loss: 1.3923 loss_prob: 0.8090 loss_thr: 0.4618 loss_db: 0.1216 2022/11/02 18:44:38 - mmengine - INFO - Epoch(train) [598][15/63] lr: 1.1635e-03 eta: 6:17:25 time: 0.6060 data_time: 0.0167 memory: 14901 loss: 1.4200 loss_prob: 0.8230 loss_thr: 0.4736 loss_db: 0.1233 2022/11/02 18:44:42 - mmengine - INFO - Epoch(train) [598][20/63] lr: 1.1635e-03 eta: 6:17:20 time: 0.6147 data_time: 0.0099 memory: 14901 loss: 1.2621 loss_prob: 0.6743 loss_thr: 0.4688 loss_db: 0.1190 2022/11/02 18:44:46 - mmengine - INFO - Epoch(train) [598][25/63] lr: 1.1635e-03 eta: 6:17:20 time: 0.7571 data_time: 0.0327 memory: 14901 loss: 1.3104 loss_prob: 0.7192 loss_thr: 0.4670 loss_db: 0.1243 2022/11/02 18:44:49 - mmengine - INFO - Epoch(train) [598][30/63] lr: 1.1635e-03 eta: 6:17:15 time: 0.7229 data_time: 0.0394 memory: 14901 loss: 1.3274 loss_prob: 0.7339 loss_thr: 0.4692 loss_db: 0.1243 2022/11/02 18:44:52 - mmengine - INFO - Epoch(train) [598][35/63] lr: 1.1635e-03 eta: 6:17:15 time: 0.6208 data_time: 0.0265 memory: 14901 loss: 1.3075 loss_prob: 0.7024 loss_thr: 0.4840 loss_db: 0.1211 2022/11/02 18:44:55 - mmengine - INFO - Epoch(train) [598][40/63] lr: 1.1635e-03 eta: 6:17:09 time: 0.5882 data_time: 0.0208 memory: 14901 loss: 1.2154 loss_prob: 0.6522 loss_thr: 0.4511 loss_db: 0.1121 2022/11/02 18:44:58 - mmengine - INFO - Epoch(train) [598][45/63] lr: 1.1635e-03 eta: 6:17:09 time: 0.5903 data_time: 0.0115 memory: 14901 loss: 1.2270 loss_prob: 0.6779 loss_thr: 0.4373 loss_db: 0.1118 2022/11/02 18:45:01 - mmengine - INFO - Epoch(train) [598][50/63] lr: 1.1635e-03 eta: 6:17:03 time: 0.6427 data_time: 0.0174 memory: 14901 loss: 1.3438 loss_prob: 0.7454 loss_thr: 0.4773 loss_db: 0.1211 2022/11/02 18:45:04 - mmengine - INFO - Epoch(train) [598][55/63] lr: 1.1635e-03 eta: 6:17:03 time: 0.5869 data_time: 0.0221 memory: 14901 loss: 1.1982 loss_prob: 0.6447 loss_thr: 0.4441 loss_db: 0.1094 2022/11/02 18:45:07 - mmengine - INFO - Epoch(train) [598][60/63] lr: 1.1635e-03 eta: 6:16:57 time: 0.5373 data_time: 0.0202 memory: 14901 loss: 1.0736 loss_prob: 0.5632 loss_thr: 0.4162 loss_db: 0.0942 2022/11/02 18:45:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:45:15 - mmengine - INFO - Epoch(train) [599][5/63] lr: 1.1618e-03 eta: 6:16:57 time: 0.9318 data_time: 0.2827 memory: 14901 loss: 1.1521 loss_prob: 0.6062 loss_thr: 0.4442 loss_db: 0.1017 2022/11/02 18:45:17 - mmengine - INFO - Epoch(train) [599][10/63] lr: 1.1618e-03 eta: 6:16:50 time: 0.8988 data_time: 0.2785 memory: 14901 loss: 1.2090 loss_prob: 0.6470 loss_thr: 0.4504 loss_db: 0.1116 2022/11/02 18:45:20 - mmengine - INFO - Epoch(train) [599][15/63] lr: 1.1618e-03 eta: 6:16:50 time: 0.5285 data_time: 0.0088 memory: 14901 loss: 1.2619 loss_prob: 0.6917 loss_thr: 0.4540 loss_db: 0.1162 2022/11/02 18:45:23 - mmengine - INFO - Epoch(train) [599][20/63] lr: 1.1618e-03 eta: 6:16:44 time: 0.5107 data_time: 0.0122 memory: 14901 loss: 1.2591 loss_prob: 0.6917 loss_thr: 0.4544 loss_db: 0.1130 2022/11/02 18:45:26 - mmengine - INFO - Epoch(train) [599][25/63] lr: 1.1618e-03 eta: 6:16:44 time: 0.6295 data_time: 0.0413 memory: 14901 loss: 1.2012 loss_prob: 0.6427 loss_thr: 0.4469 loss_db: 0.1117 2022/11/02 18:45:30 - mmengine - INFO - Epoch(train) [599][30/63] lr: 1.1618e-03 eta: 6:16:39 time: 0.7715 data_time: 0.0564 memory: 14901 loss: 1.1916 loss_prob: 0.6285 loss_thr: 0.4515 loss_db: 0.1116 2022/11/02 18:45:34 - mmengine - INFO - Epoch(train) [599][35/63] lr: 1.1618e-03 eta: 6:16:39 time: 0.7892 data_time: 0.0243 memory: 14901 loss: 1.2298 loss_prob: 0.6605 loss_thr: 0.4572 loss_db: 0.1122 2022/11/02 18:45:38 - mmengine - INFO - Epoch(train) [599][40/63] lr: 1.1618e-03 eta: 6:16:35 time: 0.7356 data_time: 0.0085 memory: 14901 loss: 1.1940 loss_prob: 0.6395 loss_thr: 0.4488 loss_db: 0.1057 2022/11/02 18:45:40 - mmengine - INFO - Epoch(train) [599][45/63] lr: 1.1618e-03 eta: 6:16:35 time: 0.5928 data_time: 0.0086 memory: 14901 loss: 1.1477 loss_prob: 0.5996 loss_thr: 0.4452 loss_db: 0.1029 2022/11/02 18:45:43 - mmengine - INFO - Epoch(train) [599][50/63] lr: 1.1618e-03 eta: 6:16:28 time: 0.5507 data_time: 0.0294 memory: 14901 loss: 1.1925 loss_prob: 0.6261 loss_thr: 0.4561 loss_db: 0.1102 2022/11/02 18:45:46 - mmengine - INFO - Epoch(train) [599][55/63] lr: 1.1618e-03 eta: 6:16:28 time: 0.5327 data_time: 0.0303 memory: 14901 loss: 1.2225 loss_prob: 0.6491 loss_thr: 0.4617 loss_db: 0.1118 2022/11/02 18:45:48 - mmengine - INFO - Epoch(train) [599][60/63] lr: 1.1618e-03 eta: 6:16:22 time: 0.5215 data_time: 0.0096 memory: 14901 loss: 1.2351 loss_prob: 0.6571 loss_thr: 0.4683 loss_db: 0.1097 2022/11/02 18:45:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:45:56 - mmengine - INFO - Epoch(train) [600][5/63] lr: 1.1601e-03 eta: 6:16:22 time: 0.8593 data_time: 0.2379 memory: 14901 loss: 1.1872 loss_prob: 0.6259 loss_thr: 0.4533 loss_db: 0.1080 2022/11/02 18:45:59 - mmengine - INFO - Epoch(train) [600][10/63] lr: 1.1601e-03 eta: 6:16:15 time: 0.8678 data_time: 0.2398 memory: 14901 loss: 1.1737 loss_prob: 0.6288 loss_thr: 0.4345 loss_db: 0.1104 2022/11/02 18:46:02 - mmengine - INFO - Epoch(train) [600][15/63] lr: 1.1601e-03 eta: 6:16:15 time: 0.6065 data_time: 0.0100 memory: 14901 loss: 1.1608 loss_prob: 0.6231 loss_thr: 0.4324 loss_db: 0.1053 2022/11/02 18:46:05 - mmengine - INFO - Epoch(train) [600][20/63] lr: 1.1601e-03 eta: 6:16:09 time: 0.6542 data_time: 0.0112 memory: 14901 loss: 1.1598 loss_prob: 0.6165 loss_thr: 0.4387 loss_db: 0.1047 2022/11/02 18:46:09 - mmengine - INFO - Epoch(train) [600][25/63] lr: 1.1601e-03 eta: 6:16:09 time: 0.6885 data_time: 0.0205 memory: 14901 loss: 1.1741 loss_prob: 0.6260 loss_thr: 0.4397 loss_db: 0.1083 2022/11/02 18:46:13 - mmengine - INFO - Epoch(train) [600][30/63] lr: 1.1601e-03 eta: 6:16:05 time: 0.7521 data_time: 0.0438 memory: 14901 loss: 1.1959 loss_prob: 0.6380 loss_thr: 0.4489 loss_db: 0.1090 2022/11/02 18:46:15 - mmengine - INFO - Epoch(train) [600][35/63] lr: 1.1601e-03 eta: 6:16:05 time: 0.6577 data_time: 0.0345 memory: 14901 loss: 1.2226 loss_prob: 0.6567 loss_thr: 0.4555 loss_db: 0.1103 2022/11/02 18:46:18 - mmengine - INFO - Epoch(train) [600][40/63] lr: 1.1601e-03 eta: 6:15:58 time: 0.5156 data_time: 0.0082 memory: 14901 loss: 1.2167 loss_prob: 0.6562 loss_thr: 0.4491 loss_db: 0.1114 2022/11/02 18:46:21 - mmengine - INFO - Epoch(train) [600][45/63] lr: 1.1601e-03 eta: 6:15:58 time: 0.5785 data_time: 0.0047 memory: 14901 loss: 1.2206 loss_prob: 0.6497 loss_thr: 0.4576 loss_db: 0.1133 2022/11/02 18:46:24 - mmengine - INFO - Epoch(train) [600][50/63] lr: 1.1601e-03 eta: 6:15:52 time: 0.5963 data_time: 0.0172 memory: 14901 loss: 1.2038 loss_prob: 0.6395 loss_thr: 0.4553 loss_db: 0.1089 2022/11/02 18:46:26 - mmengine - INFO - Epoch(train) [600][55/63] lr: 1.1601e-03 eta: 6:15:52 time: 0.5339 data_time: 0.0307 memory: 14901 loss: 1.2500 loss_prob: 0.6838 loss_thr: 0.4543 loss_db: 0.1118 2022/11/02 18:46:29 - mmengine - INFO - Epoch(train) [600][60/63] lr: 1.1601e-03 eta: 6:15:46 time: 0.5276 data_time: 0.0186 memory: 14901 loss: 1.1752 loss_prob: 0.6351 loss_thr: 0.4322 loss_db: 0.1079 2022/11/02 18:46:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:46:31 - mmengine - INFO - Saving checkpoint at 600 epochs 2022/11/02 18:46:34 - mmengine - INFO - Epoch(val) [600][5/500] eta: 6:15:46 time: 0.0457 data_time: 0.0067 memory: 14901 2022/11/02 18:46:35 - mmengine - INFO - Epoch(val) [600][10/500] eta: 0:00:22 time: 0.0461 data_time: 0.0062 memory: 1008 2022/11/02 18:46:35 - mmengine - INFO - Epoch(val) [600][15/500] eta: 0:00:22 time: 0.0386 data_time: 0.0022 memory: 1008 2022/11/02 18:46:35 - mmengine - INFO - Epoch(val) [600][20/500] eta: 0:00:18 time: 0.0382 data_time: 0.0025 memory: 1008 2022/11/02 18:46:35 - mmengine - INFO - Epoch(val) [600][25/500] eta: 0:00:18 time: 0.0360 data_time: 0.0028 memory: 1008 2022/11/02 18:46:35 - mmengine - INFO - Epoch(val) [600][30/500] eta: 0:00:20 time: 0.0435 data_time: 0.0034 memory: 1008 2022/11/02 18:46:36 - mmengine - INFO - Epoch(val) [600][35/500] eta: 0:00:20 time: 0.0447 data_time: 0.0032 memory: 1008 2022/11/02 18:46:36 - mmengine - INFO - Epoch(val) [600][40/500] eta: 0:00:20 time: 0.0443 data_time: 0.0026 memory: 1008 2022/11/02 18:46:36 - mmengine - INFO - Epoch(val) [600][45/500] eta: 0:00:20 time: 0.0467 data_time: 0.0027 memory: 1008 2022/11/02 18:46:36 - mmengine - INFO - Epoch(val) [600][50/500] eta: 0:00:18 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/02 18:46:37 - mmengine - INFO - Epoch(val) [600][55/500] eta: 0:00:18 time: 0.0476 data_time: 0.0030 memory: 1008 2022/11/02 18:46:37 - mmengine - INFO - Epoch(val) [600][60/500] eta: 0:00:20 time: 0.0455 data_time: 0.0029 memory: 1008 2022/11/02 18:46:37 - mmengine - INFO - Epoch(val) [600][65/500] eta: 0:00:20 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 18:46:37 - mmengine - INFO - Epoch(val) [600][70/500] eta: 0:00:19 time: 0.0448 data_time: 0.0027 memory: 1008 2022/11/02 18:46:37 - mmengine - INFO - Epoch(val) [600][75/500] eta: 0:00:19 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 18:46:38 - mmengine - INFO - Epoch(val) [600][80/500] eta: 0:00:17 time: 0.0424 data_time: 0.0027 memory: 1008 2022/11/02 18:46:38 - mmengine - INFO - Epoch(val) [600][85/500] eta: 0:00:17 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 18:46:38 - mmengine - INFO - Epoch(val) [600][90/500] eta: 0:00:16 time: 0.0413 data_time: 0.0025 memory: 1008 2022/11/02 18:46:38 - mmengine - INFO - Epoch(val) [600][95/500] eta: 0:00:16 time: 0.0504 data_time: 0.0035 memory: 1008 2022/11/02 18:46:39 - mmengine - INFO - Epoch(val) [600][100/500] eta: 0:00:20 time: 0.0507 data_time: 0.0036 memory: 1008 2022/11/02 18:46:39 - mmengine - INFO - Epoch(val) [600][105/500] eta: 0:00:20 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/02 18:46:39 - mmengine - INFO - Epoch(val) [600][110/500] eta: 0:00:16 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 18:46:39 - mmengine - INFO - Epoch(val) [600][115/500] eta: 0:00:16 time: 0.0430 data_time: 0.0029 memory: 1008 2022/11/02 18:46:39 - mmengine - INFO - Epoch(val) [600][120/500] eta: 0:00:16 time: 0.0429 data_time: 0.0025 memory: 1008 2022/11/02 18:46:40 - mmengine - INFO - Epoch(val) [600][125/500] eta: 0:00:16 time: 0.0414 data_time: 0.0023 memory: 1008 2022/11/02 18:46:40 - mmengine - INFO - Epoch(val) [600][130/500] eta: 0:00:14 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/02 18:46:40 - mmengine - INFO - Epoch(val) [600][135/500] eta: 0:00:14 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 18:46:40 - mmengine - INFO - Epoch(val) [600][140/500] eta: 0:00:15 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 18:46:40 - mmengine - INFO - Epoch(val) [600][145/500] eta: 0:00:15 time: 0.0471 data_time: 0.0030 memory: 1008 2022/11/02 18:46:41 - mmengine - INFO - Epoch(val) [600][150/500] eta: 0:00:16 time: 0.0459 data_time: 0.0030 memory: 1008 2022/11/02 18:46:41 - mmengine - INFO - Epoch(val) [600][155/500] eta: 0:00:16 time: 0.0477 data_time: 0.0029 memory: 1008 2022/11/02 18:46:41 - mmengine - INFO - Epoch(val) [600][160/500] eta: 0:00:15 time: 0.0468 data_time: 0.0028 memory: 1008 2022/11/02 18:46:41 - mmengine - INFO - Epoch(val) [600][165/500] eta: 0:00:15 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 18:46:42 - mmengine - INFO - Epoch(val) [600][170/500] eta: 0:00:13 time: 0.0417 data_time: 0.0026 memory: 1008 2022/11/02 18:46:42 - mmengine - INFO - Epoch(val) [600][175/500] eta: 0:00:13 time: 0.0404 data_time: 0.0027 memory: 1008 2022/11/02 18:46:42 - mmengine - INFO - Epoch(val) [600][180/500] eta: 0:00:13 time: 0.0417 data_time: 0.0026 memory: 1008 2022/11/02 18:46:42 - mmengine - INFO - Epoch(val) [600][185/500] eta: 0:00:13 time: 0.0444 data_time: 0.0025 memory: 1008 2022/11/02 18:46:42 - mmengine - INFO - Epoch(val) [600][190/500] eta: 0:00:13 time: 0.0431 data_time: 0.0027 memory: 1008 2022/11/02 18:46:43 - mmengine - INFO - Epoch(val) [600][195/500] eta: 0:00:13 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 18:46:43 - mmengine - INFO - Epoch(val) [600][200/500] eta: 0:00:13 time: 0.0457 data_time: 0.0027 memory: 1008 2022/11/02 18:46:43 - mmengine - INFO - Epoch(val) [600][205/500] eta: 0:00:13 time: 0.0449 data_time: 0.0026 memory: 1008 2022/11/02 18:46:43 - mmengine - INFO - Epoch(val) [600][210/500] eta: 0:00:11 time: 0.0383 data_time: 0.0026 memory: 1008 2022/11/02 18:46:43 - mmengine - INFO - Epoch(val) [600][215/500] eta: 0:00:11 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 18:46:44 - mmengine - INFO - Epoch(val) [600][220/500] eta: 0:00:11 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 18:46:44 - mmengine - INFO - Epoch(val) [600][225/500] eta: 0:00:11 time: 0.0406 data_time: 0.0028 memory: 1008 2022/11/02 18:46:44 - mmengine - INFO - Epoch(val) [600][230/500] eta: 0:00:10 time: 0.0386 data_time: 0.0026 memory: 1008 2022/11/02 18:46:44 - mmengine - INFO - Epoch(val) [600][235/500] eta: 0:00:10 time: 0.0411 data_time: 0.0029 memory: 1008 2022/11/02 18:46:45 - mmengine - INFO - Epoch(val) [600][240/500] eta: 0:00:12 time: 0.0477 data_time: 0.0033 memory: 1008 2022/11/02 18:46:45 - mmengine - INFO - Epoch(val) [600][245/500] eta: 0:00:12 time: 0.0458 data_time: 0.0033 memory: 1008 2022/11/02 18:46:45 - mmengine - INFO - Epoch(val) [600][250/500] eta: 0:00:10 time: 0.0437 data_time: 0.0033 memory: 1008 2022/11/02 18:46:45 - mmengine - INFO - Epoch(val) [600][255/500] eta: 0:00:10 time: 0.0455 data_time: 0.0038 memory: 1008 2022/11/02 18:46:45 - mmengine - INFO - Epoch(val) [600][260/500] eta: 0:00:10 time: 0.0432 data_time: 0.0038 memory: 1008 2022/11/02 18:46:46 - mmengine - INFO - Epoch(val) [600][265/500] eta: 0:00:10 time: 0.0449 data_time: 0.0035 memory: 1008 2022/11/02 18:46:46 - mmengine - INFO - Epoch(val) [600][270/500] eta: 0:00:10 time: 0.0458 data_time: 0.0032 memory: 1008 2022/11/02 18:46:46 - mmengine - INFO - Epoch(val) [600][275/500] eta: 0:00:10 time: 0.0455 data_time: 0.0031 memory: 1008 2022/11/02 18:46:46 - mmengine - INFO - Epoch(val) [600][280/500] eta: 0:00:12 time: 0.0568 data_time: 0.0036 memory: 1008 2022/11/02 18:46:47 - mmengine - INFO - Epoch(val) [600][285/500] eta: 0:00:12 time: 0.0571 data_time: 0.0038 memory: 1008 2022/11/02 18:46:47 - mmengine - INFO - Epoch(val) [600][290/500] eta: 0:00:10 time: 0.0498 data_time: 0.0035 memory: 1008 2022/11/02 18:46:47 - mmengine - INFO - Epoch(val) [600][295/500] eta: 0:00:10 time: 0.0540 data_time: 0.0035 memory: 1008 2022/11/02 18:46:47 - mmengine - INFO - Epoch(val) [600][300/500] eta: 0:00:10 time: 0.0542 data_time: 0.0036 memory: 1008 2022/11/02 18:46:48 - mmengine - INFO - Epoch(val) [600][305/500] eta: 0:00:10 time: 0.0476 data_time: 0.0033 memory: 1008 2022/11/02 18:46:48 - mmengine - INFO - Epoch(val) [600][310/500] eta: 0:00:07 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 18:46:48 - mmengine - INFO - Epoch(val) [600][315/500] eta: 0:00:07 time: 0.0424 data_time: 0.0026 memory: 1008 2022/11/02 18:46:48 - mmengine - INFO - Epoch(val) [600][320/500] eta: 0:00:07 time: 0.0425 data_time: 0.0026 memory: 1008 2022/11/02 18:46:49 - mmengine - INFO - Epoch(val) [600][325/500] eta: 0:00:07 time: 0.0531 data_time: 0.0025 memory: 1008 2022/11/02 18:46:49 - mmengine - INFO - Epoch(val) [600][330/500] eta: 0:00:08 time: 0.0529 data_time: 0.0025 memory: 1008 2022/11/02 18:46:49 - mmengine - INFO - Epoch(val) [600][335/500] eta: 0:00:08 time: 0.0370 data_time: 0.0026 memory: 1008 2022/11/02 18:46:49 - mmengine - INFO - Epoch(val) [600][340/500] eta: 0:00:08 time: 0.0550 data_time: 0.0028 memory: 1008 2022/11/02 18:46:50 - mmengine - INFO - Epoch(val) [600][345/500] eta: 0:00:08 time: 0.0566 data_time: 0.0028 memory: 1008 2022/11/02 18:46:50 - mmengine - INFO - Epoch(val) [600][350/500] eta: 0:00:07 time: 0.0486 data_time: 0.0027 memory: 1008 2022/11/02 18:46:50 - mmengine - INFO - Epoch(val) [600][355/500] eta: 0:00:07 time: 0.0480 data_time: 0.0030 memory: 1008 2022/11/02 18:46:50 - mmengine - INFO - Epoch(val) [600][360/500] eta: 0:00:05 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/02 18:46:50 - mmengine - INFO - Epoch(val) [600][365/500] eta: 0:00:05 time: 0.0453 data_time: 0.0027 memory: 1008 2022/11/02 18:46:51 - mmengine - INFO - Epoch(val) [600][370/500] eta: 0:00:05 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 18:46:51 - mmengine - INFO - Epoch(val) [600][375/500] eta: 0:00:05 time: 0.0389 data_time: 0.0028 memory: 1008 2022/11/02 18:46:51 - mmengine - INFO - Epoch(val) [600][380/500] eta: 0:00:05 time: 0.0418 data_time: 0.0028 memory: 1008 2022/11/02 18:46:51 - mmengine - INFO - Epoch(val) [600][385/500] eta: 0:00:05 time: 0.0401 data_time: 0.0024 memory: 1008 2022/11/02 18:46:51 - mmengine - INFO - Epoch(val) [600][390/500] eta: 0:00:04 time: 0.0383 data_time: 0.0023 memory: 1008 2022/11/02 18:46:52 - mmengine - INFO - Epoch(val) [600][395/500] eta: 0:00:04 time: 0.0398 data_time: 0.0024 memory: 1008 2022/11/02 18:46:52 - mmengine - INFO - Epoch(val) [600][400/500] eta: 0:00:04 time: 0.0400 data_time: 0.0025 memory: 1008 2022/11/02 18:46:52 - mmengine - INFO - Epoch(val) [600][405/500] eta: 0:00:04 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 18:46:52 - mmengine - INFO - Epoch(val) [600][410/500] eta: 0:00:03 time: 0.0431 data_time: 0.0025 memory: 1008 2022/11/02 18:46:53 - mmengine - INFO - Epoch(val) [600][415/500] eta: 0:00:03 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/02 18:46:53 - mmengine - INFO - Epoch(val) [600][420/500] eta: 0:00:02 time: 0.0347 data_time: 0.0025 memory: 1008 2022/11/02 18:46:53 - mmengine - INFO - Epoch(val) [600][425/500] eta: 0:00:02 time: 0.0358 data_time: 0.0023 memory: 1008 2022/11/02 18:46:53 - mmengine - INFO - Epoch(val) [600][430/500] eta: 0:00:02 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 18:46:53 - mmengine - INFO - Epoch(val) [600][435/500] eta: 0:00:02 time: 0.0369 data_time: 0.0024 memory: 1008 2022/11/02 18:46:53 - mmengine - INFO - Epoch(val) [600][440/500] eta: 0:00:02 time: 0.0436 data_time: 0.0026 memory: 1008 2022/11/02 18:46:54 - mmengine - INFO - Epoch(val) [600][445/500] eta: 0:00:02 time: 0.0487 data_time: 0.0031 memory: 1008 2022/11/02 18:46:54 - mmengine - INFO - Epoch(val) [600][450/500] eta: 0:00:02 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/02 18:46:54 - mmengine - INFO - Epoch(val) [600][455/500] eta: 0:00:02 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 18:46:54 - mmengine - INFO - Epoch(val) [600][460/500] eta: 0:00:01 time: 0.0385 data_time: 0.0028 memory: 1008 2022/11/02 18:46:55 - mmengine - INFO - Epoch(val) [600][465/500] eta: 0:00:01 time: 0.0395 data_time: 0.0031 memory: 1008 2022/11/02 18:46:55 - mmengine - INFO - Epoch(val) [600][470/500] eta: 0:00:01 time: 0.0390 data_time: 0.0028 memory: 1008 2022/11/02 18:46:55 - mmengine - INFO - Epoch(val) [600][475/500] eta: 0:00:01 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 18:46:55 - mmengine - INFO - Epoch(val) [600][480/500] eta: 0:00:00 time: 0.0406 data_time: 0.0031 memory: 1008 2022/11/02 18:46:55 - mmengine - INFO - Epoch(val) [600][485/500] eta: 0:00:00 time: 0.0590 data_time: 0.0207 memory: 1008 2022/11/02 18:46:56 - mmengine - INFO - Epoch(val) [600][490/500] eta: 0:00:00 time: 0.0622 data_time: 0.0200 memory: 1008 2022/11/02 18:46:56 - mmengine - INFO - Epoch(val) [600][495/500] eta: 0:00:00 time: 0.0462 data_time: 0.0026 memory: 1008 2022/11/02 18:46:56 - mmengine - INFO - Epoch(val) [600][500/500] eta: 0:00:00 time: 0.0414 data_time: 0.0031 memory: 1008 2022/11/02 18:46:56 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8402, precision: 0.7464, hmean: 0.7905 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8402, precision: 0.7957, hmean: 0.8173 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8402, precision: 0.8235, hmean: 0.8317 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8320, precision: 0.8500, hmean: 0.8409 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8065, precision: 0.8788, hmean: 0.8411 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6225, precision: 0.9289, hmean: 0.7455 2022/11/02 18:46:56 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0688, precision: 0.9470, hmean: 0.1284 2022/11/02 18:46:56 - mmengine - INFO - Epoch(val) [600][500/500] icdar/precision: 0.8788 icdar/recall: 0.8065 icdar/hmean: 0.8411 2022/11/02 18:47:02 - mmengine - INFO - Epoch(train) [601][5/63] lr: 1.1583e-03 eta: 0:00:00 time: 0.8133 data_time: 0.2370 memory: 14901 loss: 1.0118 loss_prob: 0.5256 loss_thr: 0.3948 loss_db: 0.0914 2022/11/02 18:47:05 - mmengine - INFO - Epoch(train) [601][10/63] lr: 1.1583e-03 eta: 6:15:39 time: 0.8514 data_time: 0.2377 memory: 14901 loss: 1.1100 loss_prob: 0.5892 loss_thr: 0.4218 loss_db: 0.0991 2022/11/02 18:47:07 - mmengine - INFO - Epoch(train) [601][15/63] lr: 1.1583e-03 eta: 6:15:39 time: 0.5649 data_time: 0.0106 memory: 14901 loss: 1.1888 loss_prob: 0.6379 loss_thr: 0.4448 loss_db: 0.1061 2022/11/02 18:47:11 - mmengine - INFO - Epoch(train) [601][20/63] lr: 1.1583e-03 eta: 6:15:33 time: 0.6170 data_time: 0.0084 memory: 14901 loss: 1.1842 loss_prob: 0.6278 loss_thr: 0.4489 loss_db: 0.1075 2022/11/02 18:47:14 - mmengine - INFO - Epoch(train) [601][25/63] lr: 1.1583e-03 eta: 6:15:33 time: 0.6695 data_time: 0.0176 memory: 14901 loss: 1.2154 loss_prob: 0.6375 loss_thr: 0.4651 loss_db: 0.1129 2022/11/02 18:47:18 - mmengine - INFO - Epoch(train) [601][30/63] lr: 1.1583e-03 eta: 6:15:28 time: 0.6930 data_time: 0.0422 memory: 14901 loss: 1.2033 loss_prob: 0.6341 loss_thr: 0.4581 loss_db: 0.1111 2022/11/02 18:47:21 - mmengine - INFO - Epoch(train) [601][35/63] lr: 1.1583e-03 eta: 6:15:28 time: 0.6632 data_time: 0.0366 memory: 14901 loss: 1.1805 loss_prob: 0.6226 loss_thr: 0.4514 loss_db: 0.1065 2022/11/02 18:47:24 - mmengine - INFO - Epoch(train) [601][40/63] lr: 1.1583e-03 eta: 6:15:22 time: 0.6152 data_time: 0.0133 memory: 14901 loss: 1.2236 loss_prob: 0.6661 loss_thr: 0.4460 loss_db: 0.1115 2022/11/02 18:47:27 - mmengine - INFO - Epoch(train) [601][45/63] lr: 1.1583e-03 eta: 6:15:22 time: 0.6402 data_time: 0.0084 memory: 14901 loss: 1.2050 loss_prob: 0.6602 loss_thr: 0.4337 loss_db: 0.1111 2022/11/02 18:47:30 - mmengine - INFO - Epoch(train) [601][50/63] lr: 1.1583e-03 eta: 6:15:17 time: 0.6342 data_time: 0.0166 memory: 14901 loss: 1.2150 loss_prob: 0.6694 loss_thr: 0.4334 loss_db: 0.1122 2022/11/02 18:47:34 - mmengine - INFO - Epoch(train) [601][55/63] lr: 1.1583e-03 eta: 6:15:17 time: 0.6966 data_time: 0.0279 memory: 14901 loss: 1.2637 loss_prob: 0.7003 loss_thr: 0.4466 loss_db: 0.1168 2022/11/02 18:47:38 - mmengine - INFO - Epoch(train) [601][60/63] lr: 1.1583e-03 eta: 6:15:12 time: 0.7194 data_time: 0.0222 memory: 14901 loss: 1.2730 loss_prob: 0.7114 loss_thr: 0.4437 loss_db: 0.1179 2022/11/02 18:47:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:47:45 - mmengine - INFO - Epoch(train) [602][5/63] lr: 1.1566e-03 eta: 6:15:12 time: 0.9265 data_time: 0.2160 memory: 14901 loss: 1.2316 loss_prob: 0.6793 loss_thr: 0.4390 loss_db: 0.1134 2022/11/02 18:47:49 - mmengine - INFO - Epoch(train) [602][10/63] lr: 1.1566e-03 eta: 6:15:06 time: 0.9688 data_time: 0.2149 memory: 14901 loss: 1.1647 loss_prob: 0.6199 loss_thr: 0.4352 loss_db: 0.1096 2022/11/02 18:47:52 - mmengine - INFO - Epoch(train) [602][15/63] lr: 1.1566e-03 eta: 6:15:06 time: 0.6902 data_time: 0.0131 memory: 14901 loss: 1.1781 loss_prob: 0.6313 loss_thr: 0.4363 loss_db: 0.1104 2022/11/02 18:47:55 - mmengine - INFO - Epoch(train) [602][20/63] lr: 1.1566e-03 eta: 6:15:00 time: 0.6113 data_time: 0.0139 memory: 14901 loss: 1.1529 loss_prob: 0.6088 loss_thr: 0.4390 loss_db: 0.1051 2022/11/02 18:47:58 - mmengine - INFO - Epoch(train) [602][25/63] lr: 1.1566e-03 eta: 6:15:00 time: 0.5997 data_time: 0.0142 memory: 14901 loss: 1.1751 loss_prob: 0.6183 loss_thr: 0.4499 loss_db: 0.1070 2022/11/02 18:48:01 - mmengine - INFO - Epoch(train) [602][30/63] lr: 1.1566e-03 eta: 6:14:54 time: 0.5910 data_time: 0.0442 memory: 14901 loss: 1.2521 loss_prob: 0.6777 loss_thr: 0.4582 loss_db: 0.1162 2022/11/02 18:48:04 - mmengine - INFO - Epoch(train) [602][35/63] lr: 1.1566e-03 eta: 6:14:54 time: 0.5560 data_time: 0.0401 memory: 14901 loss: 1.2699 loss_prob: 0.6908 loss_thr: 0.4604 loss_db: 0.1187 2022/11/02 18:48:06 - mmengine - INFO - Epoch(train) [602][40/63] lr: 1.1566e-03 eta: 6:14:47 time: 0.5223 data_time: 0.0110 memory: 14901 loss: 1.2996 loss_prob: 0.7205 loss_thr: 0.4580 loss_db: 0.1211 2022/11/02 18:48:09 - mmengine - INFO - Epoch(train) [602][45/63] lr: 1.1566e-03 eta: 6:14:47 time: 0.5661 data_time: 0.0120 memory: 14901 loss: 1.3165 loss_prob: 0.7296 loss_thr: 0.4658 loss_db: 0.1211 2022/11/02 18:48:14 - mmengine - INFO - Epoch(train) [602][50/63] lr: 1.1566e-03 eta: 6:14:44 time: 0.8192 data_time: 0.0206 memory: 14901 loss: 1.1849 loss_prob: 0.6209 loss_thr: 0.4600 loss_db: 0.1039 2022/11/02 18:48:17 - mmengine - INFO - Epoch(train) [602][55/63] lr: 1.1566e-03 eta: 6:14:44 time: 0.7931 data_time: 0.0244 memory: 14901 loss: 1.1686 loss_prob: 0.6052 loss_thr: 0.4599 loss_db: 0.1036 2022/11/02 18:48:20 - mmengine - INFO - Epoch(train) [602][60/63] lr: 1.1566e-03 eta: 6:14:37 time: 0.5481 data_time: 0.0168 memory: 14901 loss: 1.2089 loss_prob: 0.6387 loss_thr: 0.4593 loss_db: 0.1109 2022/11/02 18:48:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:48:28 - mmengine - INFO - Epoch(train) [603][5/63] lr: 1.1548e-03 eta: 6:14:37 time: 0.9238 data_time: 0.2197 memory: 14901 loss: 1.1917 loss_prob: 0.6355 loss_thr: 0.4450 loss_db: 0.1113 2022/11/02 18:48:31 - mmengine - INFO - Epoch(train) [603][10/63] lr: 1.1548e-03 eta: 6:14:31 time: 0.8897 data_time: 0.2220 memory: 14901 loss: 1.1421 loss_prob: 0.5989 loss_thr: 0.4380 loss_db: 0.1052 2022/11/02 18:48:33 - mmengine - INFO - Epoch(train) [603][15/63] lr: 1.1548e-03 eta: 6:14:31 time: 0.5136 data_time: 0.0175 memory: 14901 loss: 1.1909 loss_prob: 0.6332 loss_thr: 0.4491 loss_db: 0.1086 2022/11/02 18:48:36 - mmengine - INFO - Epoch(train) [603][20/63] lr: 1.1548e-03 eta: 6:14:24 time: 0.5395 data_time: 0.0131 memory: 14901 loss: 1.2155 loss_prob: 0.6537 loss_thr: 0.4507 loss_db: 0.1110 2022/11/02 18:48:39 - mmengine - INFO - Epoch(train) [603][25/63] lr: 1.1548e-03 eta: 6:14:24 time: 0.6210 data_time: 0.0298 memory: 14901 loss: 1.1100 loss_prob: 0.5910 loss_thr: 0.4160 loss_db: 0.1029 2022/11/02 18:48:43 - mmengine - INFO - Epoch(train) [603][30/63] lr: 1.1548e-03 eta: 6:14:19 time: 0.6703 data_time: 0.0360 memory: 14901 loss: 1.2081 loss_prob: 0.6559 loss_thr: 0.4397 loss_db: 0.1124 2022/11/02 18:48:46 - mmengine - INFO - Epoch(train) [603][35/63] lr: 1.1548e-03 eta: 6:14:19 time: 0.6431 data_time: 0.0192 memory: 14901 loss: 1.3258 loss_prob: 0.7218 loss_thr: 0.4816 loss_db: 0.1224 2022/11/02 18:48:49 - mmengine - INFO - Epoch(train) [603][40/63] lr: 1.1548e-03 eta: 6:14:13 time: 0.6219 data_time: 0.0139 memory: 14901 loss: 1.2703 loss_prob: 0.6880 loss_thr: 0.4651 loss_db: 0.1173 2022/11/02 18:48:52 - mmengine - INFO - Epoch(train) [603][45/63] lr: 1.1548e-03 eta: 6:14:13 time: 0.6349 data_time: 0.0114 memory: 14901 loss: 1.1923 loss_prob: 0.6426 loss_thr: 0.4413 loss_db: 0.1084 2022/11/02 18:48:56 - mmengine - INFO - Epoch(train) [603][50/63] lr: 1.1548e-03 eta: 6:14:08 time: 0.7213 data_time: 0.0317 memory: 14901 loss: 1.1915 loss_prob: 0.6422 loss_thr: 0.4399 loss_db: 0.1094 2022/11/02 18:48:59 - mmengine - INFO - Epoch(train) [603][55/63] lr: 1.1548e-03 eta: 6:14:08 time: 0.7276 data_time: 0.0330 memory: 14901 loss: 1.2507 loss_prob: 0.6675 loss_thr: 0.4693 loss_db: 0.1139 2022/11/02 18:49:02 - mmengine - INFO - Epoch(train) [603][60/63] lr: 1.1548e-03 eta: 6:14:03 time: 0.6322 data_time: 0.0144 memory: 14901 loss: 1.3420 loss_prob: 0.7188 loss_thr: 0.5017 loss_db: 0.1215 2022/11/02 18:49:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:49:10 - mmengine - INFO - Epoch(train) [604][5/63] lr: 1.1531e-03 eta: 6:14:03 time: 0.9404 data_time: 0.2731 memory: 14901 loss: 1.2471 loss_prob: 0.6728 loss_thr: 0.4586 loss_db: 0.1157 2022/11/02 18:49:13 - mmengine - INFO - Epoch(train) [604][10/63] lr: 1.1531e-03 eta: 6:13:56 time: 0.8609 data_time: 0.2706 memory: 14901 loss: 1.2027 loss_prob: 0.6375 loss_thr: 0.4555 loss_db: 0.1097 2022/11/02 18:49:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:49:16 - mmengine - INFO - Epoch(train) [604][15/63] lr: 1.1531e-03 eta: 6:13:56 time: 0.5438 data_time: 0.0134 memory: 14901 loss: 1.2281 loss_prob: 0.6639 loss_thr: 0.4531 loss_db: 0.1112 2022/11/02 18:49:19 - mmengine - INFO - Epoch(train) [604][20/63] lr: 1.1531e-03 eta: 6:13:51 time: 0.6631 data_time: 0.0097 memory: 14901 loss: 1.2951 loss_prob: 0.7071 loss_thr: 0.4691 loss_db: 0.1189 2022/11/02 18:49:23 - mmengine - INFO - Epoch(train) [604][25/63] lr: 1.1531e-03 eta: 6:13:51 time: 0.7214 data_time: 0.0420 memory: 14901 loss: 1.1999 loss_prob: 0.6405 loss_thr: 0.4497 loss_db: 0.1096 2022/11/02 18:49:26 - mmengine - INFO - Epoch(train) [604][30/63] lr: 1.1531e-03 eta: 6:13:45 time: 0.6599 data_time: 0.0544 memory: 14901 loss: 1.2543 loss_prob: 0.6710 loss_thr: 0.4676 loss_db: 0.1157 2022/11/02 18:49:29 - mmengine - INFO - Epoch(train) [604][35/63] lr: 1.1531e-03 eta: 6:13:45 time: 0.6027 data_time: 0.0240 memory: 14901 loss: 1.2565 loss_prob: 0.6747 loss_thr: 0.4645 loss_db: 0.1173 2022/11/02 18:49:32 - mmengine - INFO - Epoch(train) [604][40/63] lr: 1.1531e-03 eta: 6:13:39 time: 0.5785 data_time: 0.0170 memory: 14901 loss: 1.2011 loss_prob: 0.6458 loss_thr: 0.4466 loss_db: 0.1086 2022/11/02 18:49:36 - mmengine - INFO - Epoch(train) [604][45/63] lr: 1.1531e-03 eta: 6:13:39 time: 0.6846 data_time: 0.0137 memory: 14901 loss: 1.2747 loss_prob: 0.6906 loss_thr: 0.4684 loss_db: 0.1157 2022/11/02 18:49:39 - mmengine - INFO - Epoch(train) [604][50/63] lr: 1.1531e-03 eta: 6:13:34 time: 0.7095 data_time: 0.0172 memory: 14901 loss: 1.2541 loss_prob: 0.6759 loss_thr: 0.4622 loss_db: 0.1159 2022/11/02 18:49:42 - mmengine - INFO - Epoch(train) [604][55/63] lr: 1.1531e-03 eta: 6:13:34 time: 0.5941 data_time: 0.0187 memory: 14901 loss: 1.2175 loss_prob: 0.6541 loss_thr: 0.4508 loss_db: 0.1126 2022/11/02 18:49:45 - mmengine - INFO - Epoch(train) [604][60/63] lr: 1.1531e-03 eta: 6:13:28 time: 0.5571 data_time: 0.0145 memory: 14901 loss: 1.2564 loss_prob: 0.6931 loss_thr: 0.4491 loss_db: 0.1142 2022/11/02 18:49:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:49:52 - mmengine - INFO - Epoch(train) [605][5/63] lr: 1.1514e-03 eta: 6:13:28 time: 0.8064 data_time: 0.2566 memory: 14901 loss: 1.1977 loss_prob: 0.6385 loss_thr: 0.4504 loss_db: 0.1088 2022/11/02 18:49:54 - mmengine - INFO - Epoch(train) [605][10/63] lr: 1.1514e-03 eta: 6:13:20 time: 0.7778 data_time: 0.2531 memory: 14901 loss: 1.3163 loss_prob: 0.7111 loss_thr: 0.4873 loss_db: 0.1180 2022/11/02 18:49:57 - mmengine - INFO - Epoch(train) [605][15/63] lr: 1.1514e-03 eta: 6:13:20 time: 0.5073 data_time: 0.0124 memory: 14901 loss: 1.3755 loss_prob: 0.7519 loss_thr: 0.4971 loss_db: 0.1266 2022/11/02 18:49:59 - mmengine - INFO - Epoch(train) [605][20/63] lr: 1.1514e-03 eta: 6:13:13 time: 0.5199 data_time: 0.0136 memory: 14901 loss: 1.2979 loss_prob: 0.6965 loss_thr: 0.4796 loss_db: 0.1218 2022/11/02 18:50:03 - mmengine - INFO - Epoch(train) [605][25/63] lr: 1.1514e-03 eta: 6:13:13 time: 0.6375 data_time: 0.0399 memory: 14901 loss: 1.2650 loss_prob: 0.6793 loss_thr: 0.4693 loss_db: 0.1165 2022/11/02 18:50:06 - mmengine - INFO - Epoch(train) [605][30/63] lr: 1.1514e-03 eta: 6:13:08 time: 0.6944 data_time: 0.0425 memory: 14901 loss: 1.2150 loss_prob: 0.6542 loss_thr: 0.4494 loss_db: 0.1114 2022/11/02 18:50:09 - mmengine - INFO - Epoch(train) [605][35/63] lr: 1.1514e-03 eta: 6:13:08 time: 0.5781 data_time: 0.0147 memory: 14901 loss: 1.1389 loss_prob: 0.6069 loss_thr: 0.4270 loss_db: 0.1049 2022/11/02 18:50:11 - mmengine - INFO - Epoch(train) [605][40/63] lr: 1.1514e-03 eta: 6:13:02 time: 0.5212 data_time: 0.0112 memory: 14901 loss: 1.1761 loss_prob: 0.6215 loss_thr: 0.4464 loss_db: 0.1082 2022/11/02 18:50:14 - mmengine - INFO - Epoch(train) [605][45/63] lr: 1.1514e-03 eta: 6:13:02 time: 0.5468 data_time: 0.0152 memory: 14901 loss: 1.2972 loss_prob: 0.6978 loss_thr: 0.4805 loss_db: 0.1188 2022/11/02 18:50:18 - mmengine - INFO - Epoch(train) [605][50/63] lr: 1.1514e-03 eta: 6:12:57 time: 0.6843 data_time: 0.0343 memory: 14901 loss: 1.3068 loss_prob: 0.7073 loss_thr: 0.4807 loss_db: 0.1188 2022/11/02 18:50:21 - mmengine - INFO - Epoch(train) [605][55/63] lr: 1.1514e-03 eta: 6:12:57 time: 0.6595 data_time: 0.0289 memory: 14901 loss: 1.1788 loss_prob: 0.6237 loss_thr: 0.4466 loss_db: 0.1085 2022/11/02 18:50:24 - mmengine - INFO - Epoch(train) [605][60/63] lr: 1.1514e-03 eta: 6:12:50 time: 0.5250 data_time: 0.0089 memory: 14901 loss: 1.1341 loss_prob: 0.6003 loss_thr: 0.4288 loss_db: 0.1049 2022/11/02 18:50:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:50:31 - mmengine - INFO - Epoch(train) [606][5/63] lr: 1.1496e-03 eta: 6:12:50 time: 0.8040 data_time: 0.2558 memory: 14901 loss: 1.1437 loss_prob: 0.5962 loss_thr: 0.4462 loss_db: 0.1013 2022/11/02 18:50:34 - mmengine - INFO - Epoch(train) [606][10/63] lr: 1.1496e-03 eta: 6:12:43 time: 0.8518 data_time: 0.2609 memory: 14901 loss: 1.1216 loss_prob: 0.5733 loss_thr: 0.4470 loss_db: 0.1013 2022/11/02 18:50:36 - mmengine - INFO - Epoch(train) [606][15/63] lr: 1.1496e-03 eta: 6:12:43 time: 0.5842 data_time: 0.0178 memory: 14901 loss: 1.1658 loss_prob: 0.6065 loss_thr: 0.4541 loss_db: 0.1052 2022/11/02 18:50:39 - mmengine - INFO - Epoch(train) [606][20/63] lr: 1.1496e-03 eta: 6:12:36 time: 0.5294 data_time: 0.0099 memory: 14901 loss: 1.2576 loss_prob: 0.6870 loss_thr: 0.4605 loss_db: 0.1101 2022/11/02 18:50:42 - mmengine - INFO - Epoch(train) [606][25/63] lr: 1.1496e-03 eta: 6:12:36 time: 0.5168 data_time: 0.0178 memory: 14901 loss: 1.2852 loss_prob: 0.7053 loss_thr: 0.4657 loss_db: 0.1143 2022/11/02 18:50:45 - mmengine - INFO - Epoch(train) [606][30/63] lr: 1.1496e-03 eta: 6:12:31 time: 0.6400 data_time: 0.0473 memory: 14901 loss: 1.2480 loss_prob: 0.6657 loss_thr: 0.4692 loss_db: 0.1130 2022/11/02 18:50:49 - mmengine - INFO - Epoch(train) [606][35/63] lr: 1.1496e-03 eta: 6:12:31 time: 0.7821 data_time: 0.0353 memory: 14901 loss: 1.2500 loss_prob: 0.6661 loss_thr: 0.4706 loss_db: 0.1133 2022/11/02 18:50:53 - mmengine - INFO - Epoch(train) [606][40/63] lr: 1.1496e-03 eta: 6:12:26 time: 0.7523 data_time: 0.0076 memory: 14901 loss: 1.2185 loss_prob: 0.6440 loss_thr: 0.4641 loss_db: 0.1104 2022/11/02 18:50:55 - mmengine - INFO - Epoch(train) [606][45/63] lr: 1.1496e-03 eta: 6:12:26 time: 0.6065 data_time: 0.0101 memory: 14901 loss: 1.1524 loss_prob: 0.6025 loss_thr: 0.4447 loss_db: 0.1052 2022/11/02 18:50:58 - mmengine - INFO - Epoch(train) [606][50/63] lr: 1.1496e-03 eta: 6:12:20 time: 0.5360 data_time: 0.0192 memory: 14901 loss: 1.1619 loss_prob: 0.6300 loss_thr: 0.4235 loss_db: 0.1084 2022/11/02 18:51:01 - mmengine - INFO - Epoch(train) [606][55/63] lr: 1.1496e-03 eta: 6:12:20 time: 0.5431 data_time: 0.0266 memory: 14901 loss: 1.1345 loss_prob: 0.6171 loss_thr: 0.4112 loss_db: 0.1062 2022/11/02 18:51:04 - mmengine - INFO - Epoch(train) [606][60/63] lr: 1.1496e-03 eta: 6:12:13 time: 0.5395 data_time: 0.0181 memory: 14901 loss: 1.2109 loss_prob: 0.6508 loss_thr: 0.4450 loss_db: 0.1151 2022/11/02 18:51:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:51:11 - mmengine - INFO - Epoch(train) [607][5/63] lr: 1.1479e-03 eta: 6:12:13 time: 0.8135 data_time: 0.2515 memory: 14901 loss: 1.2763 loss_prob: 0.6927 loss_thr: 0.4664 loss_db: 0.1172 2022/11/02 18:51:13 - mmengine - INFO - Epoch(train) [607][10/63] lr: 1.1479e-03 eta: 6:12:06 time: 0.8549 data_time: 0.2553 memory: 14901 loss: 1.2415 loss_prob: 0.6708 loss_thr: 0.4593 loss_db: 0.1114 2022/11/02 18:51:16 - mmengine - INFO - Epoch(train) [607][15/63] lr: 1.1479e-03 eta: 6:12:06 time: 0.5676 data_time: 0.0183 memory: 14901 loss: 1.2168 loss_prob: 0.6513 loss_thr: 0.4558 loss_db: 0.1097 2022/11/02 18:51:19 - mmengine - INFO - Epoch(train) [607][20/63] lr: 1.1479e-03 eta: 6:12:00 time: 0.5531 data_time: 0.0125 memory: 14901 loss: 1.1786 loss_prob: 0.6358 loss_thr: 0.4345 loss_db: 0.1083 2022/11/02 18:51:23 - mmengine - INFO - Epoch(train) [607][25/63] lr: 1.1479e-03 eta: 6:12:00 time: 0.6982 data_time: 0.0331 memory: 14901 loss: 1.3004 loss_prob: 0.7268 loss_thr: 0.4553 loss_db: 0.1182 2022/11/02 18:51:27 - mmengine - INFO - Epoch(train) [607][30/63] lr: 1.1479e-03 eta: 6:11:55 time: 0.7608 data_time: 0.0341 memory: 14901 loss: 1.2988 loss_prob: 0.7033 loss_thr: 0.4799 loss_db: 0.1156 2022/11/02 18:51:30 - mmengine - INFO - Epoch(train) [607][35/63] lr: 1.1479e-03 eta: 6:11:55 time: 0.6488 data_time: 0.0152 memory: 14901 loss: 1.1178 loss_prob: 0.5741 loss_thr: 0.4431 loss_db: 0.1006 2022/11/02 18:51:33 - mmengine - INFO - Epoch(train) [607][40/63] lr: 1.1479e-03 eta: 6:11:50 time: 0.6907 data_time: 0.0176 memory: 14901 loss: 1.1737 loss_prob: 0.6172 loss_thr: 0.4489 loss_db: 0.1076 2022/11/02 18:51:37 - mmengine - INFO - Epoch(train) [607][45/63] lr: 1.1479e-03 eta: 6:11:50 time: 0.6792 data_time: 0.0155 memory: 14901 loss: 1.1814 loss_prob: 0.6250 loss_thr: 0.4487 loss_db: 0.1077 2022/11/02 18:51:39 - mmengine - INFO - Epoch(train) [607][50/63] lr: 1.1479e-03 eta: 6:11:44 time: 0.5890 data_time: 0.0283 memory: 14901 loss: 1.1909 loss_prob: 0.6349 loss_thr: 0.4476 loss_db: 0.1084 2022/11/02 18:51:42 - mmengine - INFO - Epoch(train) [607][55/63] lr: 1.1479e-03 eta: 6:11:44 time: 0.5709 data_time: 0.0279 memory: 14901 loss: 1.2493 loss_prob: 0.6688 loss_thr: 0.4678 loss_db: 0.1126 2022/11/02 18:51:46 - mmengine - INFO - Epoch(train) [607][60/63] lr: 1.1479e-03 eta: 6:11:39 time: 0.7017 data_time: 0.0131 memory: 14901 loss: 1.1840 loss_prob: 0.6310 loss_thr: 0.4462 loss_db: 0.1069 2022/11/02 18:51:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:51:54 - mmengine - INFO - Epoch(train) [608][5/63] lr: 1.1461e-03 eta: 6:11:39 time: 0.8554 data_time: 0.2410 memory: 14901 loss: 1.1585 loss_prob: 0.6113 loss_thr: 0.4413 loss_db: 0.1059 2022/11/02 18:51:56 - mmengine - INFO - Epoch(train) [608][10/63] lr: 1.1461e-03 eta: 6:11:33 time: 0.8926 data_time: 0.2446 memory: 14901 loss: 1.2462 loss_prob: 0.6620 loss_thr: 0.4707 loss_db: 0.1135 2022/11/02 18:52:00 - mmengine - INFO - Epoch(train) [608][15/63] lr: 1.1461e-03 eta: 6:11:33 time: 0.5997 data_time: 0.0177 memory: 14901 loss: 1.2902 loss_prob: 0.6994 loss_thr: 0.4753 loss_db: 0.1155 2022/11/02 18:52:03 - mmengine - INFO - Epoch(train) [608][20/63] lr: 1.1461e-03 eta: 6:11:28 time: 0.6724 data_time: 0.0176 memory: 14901 loss: 1.1991 loss_prob: 0.6430 loss_thr: 0.4485 loss_db: 0.1076 2022/11/02 18:52:07 - mmengine - INFO - Epoch(train) [608][25/63] lr: 1.1461e-03 eta: 6:11:28 time: 0.7546 data_time: 0.0206 memory: 14901 loss: 1.1430 loss_prob: 0.6095 loss_thr: 0.4288 loss_db: 0.1047 2022/11/02 18:52:10 - mmengine - INFO - Epoch(train) [608][30/63] lr: 1.1461e-03 eta: 6:11:23 time: 0.7117 data_time: 0.0384 memory: 14901 loss: 1.2064 loss_prob: 0.6563 loss_thr: 0.4408 loss_db: 0.1093 2022/11/02 18:52:15 - mmengine - INFO - Epoch(train) [608][35/63] lr: 1.1461e-03 eta: 6:11:23 time: 0.7744 data_time: 0.0356 memory: 14901 loss: 1.2161 loss_prob: 0.6552 loss_thr: 0.4521 loss_db: 0.1088 2022/11/02 18:52:18 - mmengine - INFO - Epoch(train) [608][40/63] lr: 1.1461e-03 eta: 6:11:18 time: 0.7520 data_time: 0.0176 memory: 14901 loss: 1.1381 loss_prob: 0.6057 loss_thr: 0.4293 loss_db: 0.1032 2022/11/02 18:52:21 - mmengine - INFO - Epoch(train) [608][45/63] lr: 1.1461e-03 eta: 6:11:18 time: 0.6396 data_time: 0.0122 memory: 14901 loss: 1.1618 loss_prob: 0.6174 loss_thr: 0.4380 loss_db: 0.1065 2022/11/02 18:52:24 - mmengine - INFO - Epoch(train) [608][50/63] lr: 1.1461e-03 eta: 6:11:13 time: 0.6443 data_time: 0.0128 memory: 14901 loss: 1.1968 loss_prob: 0.6369 loss_thr: 0.4531 loss_db: 0.1068 2022/11/02 18:52:27 - mmengine - INFO - Epoch(train) [608][55/63] lr: 1.1461e-03 eta: 6:11:13 time: 0.5815 data_time: 0.0262 memory: 14901 loss: 1.1944 loss_prob: 0.6334 loss_thr: 0.4545 loss_db: 0.1065 2022/11/02 18:52:30 - mmengine - INFO - Epoch(train) [608][60/63] lr: 1.1461e-03 eta: 6:11:07 time: 0.5880 data_time: 0.0233 memory: 14901 loss: 1.2089 loss_prob: 0.6434 loss_thr: 0.4533 loss_db: 0.1123 2022/11/02 18:52:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:52:38 - mmengine - INFO - Epoch(train) [609][5/63] lr: 1.1444e-03 eta: 6:11:07 time: 0.8419 data_time: 0.2608 memory: 14901 loss: 1.1687 loss_prob: 0.6205 loss_thr: 0.4426 loss_db: 0.1056 2022/11/02 18:52:40 - mmengine - INFO - Epoch(train) [609][10/63] lr: 1.1444e-03 eta: 6:11:00 time: 0.8886 data_time: 0.2562 memory: 14901 loss: 1.1858 loss_prob: 0.6252 loss_thr: 0.4563 loss_db: 0.1043 2022/11/02 18:52:43 - mmengine - INFO - Epoch(train) [609][15/63] lr: 1.1444e-03 eta: 6:11:00 time: 0.5635 data_time: 0.0151 memory: 14901 loss: 1.1794 loss_prob: 0.6210 loss_thr: 0.4536 loss_db: 0.1047 2022/11/02 18:52:46 - mmengine - INFO - Epoch(train) [609][20/63] lr: 1.1444e-03 eta: 6:10:54 time: 0.5798 data_time: 0.0154 memory: 14901 loss: 1.1890 loss_prob: 0.6304 loss_thr: 0.4501 loss_db: 0.1085 2022/11/02 18:52:50 - mmengine - INFO - Epoch(train) [609][25/63] lr: 1.1444e-03 eta: 6:10:54 time: 0.7140 data_time: 0.0289 memory: 14901 loss: 1.1637 loss_prob: 0.6117 loss_thr: 0.4467 loss_db: 0.1054 2022/11/02 18:52:54 - mmengine - INFO - Epoch(train) [609][30/63] lr: 1.1444e-03 eta: 6:10:50 time: 0.8277 data_time: 0.0401 memory: 14901 loss: 1.2346 loss_prob: 0.6675 loss_thr: 0.4536 loss_db: 0.1136 2022/11/02 18:52:58 - mmengine - INFO - Epoch(train) [609][35/63] lr: 1.1444e-03 eta: 6:10:50 time: 0.7599 data_time: 0.0221 memory: 14901 loss: 1.3031 loss_prob: 0.7103 loss_thr: 0.4726 loss_db: 0.1201 2022/11/02 18:53:01 - mmengine - INFO - Epoch(train) [609][40/63] lr: 1.1444e-03 eta: 6:10:44 time: 0.6109 data_time: 0.0107 memory: 14901 loss: 1.2483 loss_prob: 0.6701 loss_thr: 0.4645 loss_db: 0.1136 2022/11/02 18:53:04 - mmengine - INFO - Epoch(train) [609][45/63] lr: 1.1444e-03 eta: 6:10:44 time: 0.5640 data_time: 0.0113 memory: 14901 loss: 1.1968 loss_prob: 0.6392 loss_thr: 0.4493 loss_db: 0.1082 2022/11/02 18:53:07 - mmengine - INFO - Epoch(train) [609][50/63] lr: 1.1444e-03 eta: 6:10:39 time: 0.6428 data_time: 0.0258 memory: 14901 loss: 1.1844 loss_prob: 0.6228 loss_thr: 0.4540 loss_db: 0.1076 2022/11/02 18:53:11 - mmengine - INFO - Epoch(train) [609][55/63] lr: 1.1444e-03 eta: 6:10:39 time: 0.6994 data_time: 0.0355 memory: 14901 loss: 1.2092 loss_prob: 0.6430 loss_thr: 0.4542 loss_db: 0.1119 2022/11/02 18:53:14 - mmengine - INFO - Epoch(train) [609][60/63] lr: 1.1444e-03 eta: 6:10:33 time: 0.6650 data_time: 0.0218 memory: 14901 loss: 1.1840 loss_prob: 0.6217 loss_thr: 0.4564 loss_db: 0.1059 2022/11/02 18:53:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:53:22 - mmengine - INFO - Epoch(train) [610][5/63] lr: 1.1427e-03 eta: 6:10:33 time: 0.9032 data_time: 0.2720 memory: 14901 loss: 1.2691 loss_prob: 0.6841 loss_thr: 0.4700 loss_db: 0.1149 2022/11/02 18:53:25 - mmengine - INFO - Epoch(train) [610][10/63] lr: 1.1427e-03 eta: 6:10:27 time: 0.8758 data_time: 0.2719 memory: 14901 loss: 1.2879 loss_prob: 0.7027 loss_thr: 0.4665 loss_db: 0.1187 2022/11/02 18:53:28 - mmengine - INFO - Epoch(train) [610][15/63] lr: 1.1427e-03 eta: 6:10:27 time: 0.6938 data_time: 0.0109 memory: 14901 loss: 1.1876 loss_prob: 0.6343 loss_thr: 0.4440 loss_db: 0.1094 2022/11/02 18:53:32 - mmengine - INFO - Epoch(train) [610][20/63] lr: 1.1427e-03 eta: 6:10:22 time: 0.7121 data_time: 0.0126 memory: 14901 loss: 1.1748 loss_prob: 0.6127 loss_thr: 0.4581 loss_db: 0.1040 2022/11/02 18:53:35 - mmengine - INFO - Epoch(train) [610][25/63] lr: 1.1427e-03 eta: 6:10:22 time: 0.6763 data_time: 0.0372 memory: 14901 loss: 1.1689 loss_prob: 0.6124 loss_thr: 0.4533 loss_db: 0.1033 2022/11/02 18:53:38 - mmengine - INFO - Epoch(train) [610][30/63] lr: 1.1427e-03 eta: 6:10:16 time: 0.6080 data_time: 0.0360 memory: 14901 loss: 1.2270 loss_prob: 0.6743 loss_thr: 0.4388 loss_db: 0.1139 2022/11/02 18:53:41 - mmengine - INFO - Epoch(train) [610][35/63] lr: 1.1427e-03 eta: 6:10:16 time: 0.5446 data_time: 0.0156 memory: 14901 loss: 1.2996 loss_prob: 0.7275 loss_thr: 0.4499 loss_db: 0.1223 2022/11/02 18:53:44 - mmengine - INFO - Epoch(train) [610][40/63] lr: 1.1427e-03 eta: 6:10:10 time: 0.5706 data_time: 0.0165 memory: 14901 loss: 1.3029 loss_prob: 0.7044 loss_thr: 0.4779 loss_db: 0.1206 2022/11/02 18:53:47 - mmengine - INFO - Epoch(train) [610][45/63] lr: 1.1427e-03 eta: 6:10:10 time: 0.5962 data_time: 0.0116 memory: 14901 loss: 1.2355 loss_prob: 0.6379 loss_thr: 0.4899 loss_db: 0.1078 2022/11/02 18:53:50 - mmengine - INFO - Epoch(train) [610][50/63] lr: 1.1427e-03 eta: 6:10:04 time: 0.5945 data_time: 0.0273 memory: 14901 loss: 1.2747 loss_prob: 0.6688 loss_thr: 0.4924 loss_db: 0.1135 2022/11/02 18:53:52 - mmengine - INFO - Epoch(train) [610][55/63] lr: 1.1427e-03 eta: 6:10:04 time: 0.5425 data_time: 0.0316 memory: 14901 loss: 1.3081 loss_prob: 0.7129 loss_thr: 0.4718 loss_db: 0.1234 2022/11/02 18:53:55 - mmengine - INFO - Epoch(train) [610][60/63] lr: 1.1427e-03 eta: 6:09:57 time: 0.4991 data_time: 0.0153 memory: 14901 loss: 1.2681 loss_prob: 0.6875 loss_thr: 0.4626 loss_db: 0.1180 2022/11/02 18:53:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:54:02 - mmengine - INFO - Epoch(train) [611][5/63] lr: 1.1409e-03 eta: 6:09:57 time: 0.8067 data_time: 0.2244 memory: 14901 loss: 1.2792 loss_prob: 0.6846 loss_thr: 0.4775 loss_db: 0.1172 2022/11/02 18:54:06 - mmengine - INFO - Epoch(train) [611][10/63] lr: 1.1409e-03 eta: 6:09:51 time: 1.0188 data_time: 0.2222 memory: 14901 loss: 1.2563 loss_prob: 0.6670 loss_thr: 0.4735 loss_db: 0.1159 2022/11/02 18:54:09 - mmengine - INFO - Epoch(train) [611][15/63] lr: 1.1409e-03 eta: 6:09:51 time: 0.7653 data_time: 0.0114 memory: 14901 loss: 1.1594 loss_prob: 0.6106 loss_thr: 0.4419 loss_db: 0.1069 2022/11/02 18:54:12 - mmengine - INFO - Epoch(train) [611][20/63] lr: 1.1409e-03 eta: 6:09:45 time: 0.6079 data_time: 0.0116 memory: 14901 loss: 1.2478 loss_prob: 0.6748 loss_thr: 0.4574 loss_db: 0.1156 2022/11/02 18:54:17 - mmengine - INFO - Epoch(train) [611][25/63] lr: 1.1409e-03 eta: 6:09:45 time: 0.7342 data_time: 0.0161 memory: 14901 loss: 1.2346 loss_prob: 0.6695 loss_thr: 0.4519 loss_db: 0.1132 2022/11/02 18:54:20 - mmengine - INFO - Epoch(train) [611][30/63] lr: 1.1409e-03 eta: 6:09:41 time: 0.7436 data_time: 0.0367 memory: 14901 loss: 1.1975 loss_prob: 0.6452 loss_thr: 0.4439 loss_db: 0.1085 2022/11/02 18:54:22 - mmengine - INFO - Epoch(train) [611][35/63] lr: 1.1409e-03 eta: 6:09:41 time: 0.5857 data_time: 0.0401 memory: 14901 loss: 1.1742 loss_prob: 0.6238 loss_thr: 0.4440 loss_db: 0.1064 2022/11/02 18:54:25 - mmengine - INFO - Epoch(train) [611][40/63] lr: 1.1409e-03 eta: 6:09:34 time: 0.5395 data_time: 0.0177 memory: 14901 loss: 1.1597 loss_prob: 0.6158 loss_thr: 0.4375 loss_db: 0.1063 2022/11/02 18:54:28 - mmengine - INFO - Epoch(train) [611][45/63] lr: 1.1409e-03 eta: 6:09:34 time: 0.5765 data_time: 0.0104 memory: 14901 loss: 1.1919 loss_prob: 0.6406 loss_thr: 0.4404 loss_db: 0.1110 2022/11/02 18:54:32 - mmengine - INFO - Epoch(train) [611][50/63] lr: 1.1409e-03 eta: 6:09:29 time: 0.6808 data_time: 0.0179 memory: 14901 loss: 1.1814 loss_prob: 0.6386 loss_thr: 0.4342 loss_db: 0.1086 2022/11/02 18:54:35 - mmengine - INFO - Epoch(train) [611][55/63] lr: 1.1409e-03 eta: 6:09:29 time: 0.6551 data_time: 0.0240 memory: 14901 loss: 1.1393 loss_prob: 0.6126 loss_thr: 0.4244 loss_db: 0.1022 2022/11/02 18:54:37 - mmengine - INFO - Epoch(train) [611][60/63] lr: 1.1409e-03 eta: 6:09:23 time: 0.5617 data_time: 0.0172 memory: 14901 loss: 1.1796 loss_prob: 0.6344 loss_thr: 0.4412 loss_db: 0.1039 2022/11/02 18:54:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:54:45 - mmengine - INFO - Epoch(train) [612][5/63] lr: 1.1392e-03 eta: 6:09:23 time: 0.8569 data_time: 0.2105 memory: 14901 loss: 1.2432 loss_prob: 0.6624 loss_thr: 0.4698 loss_db: 0.1110 2022/11/02 18:54:49 - mmengine - INFO - Epoch(train) [612][10/63] lr: 1.1392e-03 eta: 6:09:17 time: 1.0056 data_time: 0.2165 memory: 14901 loss: 1.1345 loss_prob: 0.5931 loss_thr: 0.4407 loss_db: 0.1007 2022/11/02 18:54:52 - mmengine - INFO - Epoch(train) [612][15/63] lr: 1.1392e-03 eta: 6:09:17 time: 0.7054 data_time: 0.0156 memory: 14901 loss: 1.0722 loss_prob: 0.5675 loss_thr: 0.4068 loss_db: 0.0980 2022/11/02 18:54:56 - mmengine - INFO - Epoch(train) [612][20/63] lr: 1.1392e-03 eta: 6:09:12 time: 0.6596 data_time: 0.0084 memory: 14901 loss: 1.1450 loss_prob: 0.6134 loss_thr: 0.4266 loss_db: 0.1050 2022/11/02 18:54:59 - mmengine - INFO - Epoch(train) [612][25/63] lr: 1.1392e-03 eta: 6:09:12 time: 0.7120 data_time: 0.0219 memory: 14901 loss: 1.2155 loss_prob: 0.6555 loss_thr: 0.4495 loss_db: 0.1105 2022/11/02 18:55:02 - mmengine - INFO - Epoch(train) [612][30/63] lr: 1.1392e-03 eta: 6:09:06 time: 0.6155 data_time: 0.0392 memory: 14901 loss: 1.2772 loss_prob: 0.6865 loss_thr: 0.4720 loss_db: 0.1187 2022/11/02 18:55:04 - mmengine - INFO - Epoch(train) [612][35/63] lr: 1.1392e-03 eta: 6:09:06 time: 0.5212 data_time: 0.0353 memory: 14901 loss: 1.2889 loss_prob: 0.6942 loss_thr: 0.4770 loss_db: 0.1177 2022/11/02 18:55:07 - mmengine - INFO - Epoch(train) [612][40/63] lr: 1.1392e-03 eta: 6:09:00 time: 0.5463 data_time: 0.0195 memory: 14901 loss: 1.2320 loss_prob: 0.6734 loss_thr: 0.4476 loss_db: 0.1110 2022/11/02 18:55:10 - mmengine - INFO - Epoch(train) [612][45/63] lr: 1.1392e-03 eta: 6:09:00 time: 0.5260 data_time: 0.0107 memory: 14901 loss: 1.2661 loss_prob: 0.6971 loss_thr: 0.4544 loss_db: 0.1146 2022/11/02 18:55:12 - mmengine - INFO - Epoch(train) [612][50/63] lr: 1.1392e-03 eta: 6:08:53 time: 0.5243 data_time: 0.0156 memory: 14901 loss: 1.2465 loss_prob: 0.6775 loss_thr: 0.4566 loss_db: 0.1124 2022/11/02 18:55:16 - mmengine - INFO - Epoch(train) [612][55/63] lr: 1.1392e-03 eta: 6:08:53 time: 0.6272 data_time: 0.0193 memory: 14901 loss: 1.1243 loss_prob: 0.6027 loss_thr: 0.4173 loss_db: 0.1043 2022/11/02 18:55:19 - mmengine - INFO - Epoch(train) [612][60/63] lr: 1.1392e-03 eta: 6:08:47 time: 0.6285 data_time: 0.0194 memory: 14901 loss: 1.1859 loss_prob: 0.6379 loss_thr: 0.4383 loss_db: 0.1097 2022/11/02 18:55:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:55:27 - mmengine - INFO - Epoch(train) [613][5/63] lr: 1.1374e-03 eta: 6:08:47 time: 0.8998 data_time: 0.2409 memory: 14901 loss: 1.1951 loss_prob: 0.6262 loss_thr: 0.4602 loss_db: 0.1087 2022/11/02 18:55:30 - mmengine - INFO - Epoch(train) [613][10/63] lr: 1.1374e-03 eta: 6:08:42 time: 1.0122 data_time: 0.2512 memory: 14901 loss: 1.1759 loss_prob: 0.6151 loss_thr: 0.4551 loss_db: 0.1058 2022/11/02 18:55:35 - mmengine - INFO - Epoch(train) [613][15/63] lr: 1.1374e-03 eta: 6:08:42 time: 0.8057 data_time: 0.0182 memory: 14901 loss: 1.2186 loss_prob: 0.6568 loss_thr: 0.4496 loss_db: 0.1122 2022/11/02 18:55:38 - mmengine - INFO - Epoch(train) [613][20/63] lr: 1.1374e-03 eta: 6:08:37 time: 0.7447 data_time: 0.0077 memory: 14901 loss: 1.2501 loss_prob: 0.6831 loss_thr: 0.4535 loss_db: 0.1135 2022/11/02 18:55:41 - mmengine - INFO - Epoch(train) [613][25/63] lr: 1.1374e-03 eta: 6:08:37 time: 0.6017 data_time: 0.0293 memory: 14901 loss: 1.1296 loss_prob: 0.6072 loss_thr: 0.4201 loss_db: 0.1023 2022/11/02 18:55:44 - mmengine - INFO - Epoch(train) [613][30/63] lr: 1.1374e-03 eta: 6:08:32 time: 0.6704 data_time: 0.0464 memory: 14901 loss: 1.1683 loss_prob: 0.6192 loss_thr: 0.4395 loss_db: 0.1096 2022/11/02 18:55:47 - mmengine - INFO - Epoch(train) [613][35/63] lr: 1.1374e-03 eta: 6:08:32 time: 0.6738 data_time: 0.0260 memory: 14901 loss: 1.2965 loss_prob: 0.7025 loss_thr: 0.4726 loss_db: 0.1214 2022/11/02 18:55:50 - mmengine - INFO - Epoch(train) [613][40/63] lr: 1.1374e-03 eta: 6:08:26 time: 0.5602 data_time: 0.0064 memory: 14901 loss: 1.2447 loss_prob: 0.6716 loss_thr: 0.4590 loss_db: 0.1141 2022/11/02 18:55:53 - mmengine - INFO - Epoch(train) [613][45/63] lr: 1.1374e-03 eta: 6:08:26 time: 0.5308 data_time: 0.0069 memory: 14901 loss: 1.1315 loss_prob: 0.5931 loss_thr: 0.4359 loss_db: 0.1026 2022/11/02 18:55:55 - mmengine - INFO - Epoch(train) [613][50/63] lr: 1.1374e-03 eta: 6:08:19 time: 0.5337 data_time: 0.0188 memory: 14901 loss: 1.1489 loss_prob: 0.6094 loss_thr: 0.4353 loss_db: 0.1042 2022/11/02 18:55:58 - mmengine - INFO - Epoch(train) [613][55/63] lr: 1.1374e-03 eta: 6:08:19 time: 0.5312 data_time: 0.0277 memory: 14901 loss: 1.1825 loss_prob: 0.6241 loss_thr: 0.4533 loss_db: 0.1051 2022/11/02 18:56:01 - mmengine - INFO - Epoch(train) [613][60/63] lr: 1.1374e-03 eta: 6:08:13 time: 0.5593 data_time: 0.0166 memory: 14901 loss: 1.2120 loss_prob: 0.6390 loss_thr: 0.4636 loss_db: 0.1094 2022/11/02 18:56:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:56:10 - mmengine - INFO - Epoch(train) [614][5/63] lr: 1.1357e-03 eta: 6:08:13 time: 0.9989 data_time: 0.2374 memory: 14901 loss: 1.2672 loss_prob: 0.6970 loss_thr: 0.4569 loss_db: 0.1134 2022/11/02 18:56:13 - mmengine - INFO - Epoch(train) [614][10/63] lr: 1.1357e-03 eta: 6:08:08 time: 1.1117 data_time: 0.2377 memory: 14901 loss: 1.2055 loss_prob: 0.6365 loss_thr: 0.4597 loss_db: 0.1093 2022/11/02 18:56:17 - mmengine - INFO - Epoch(train) [614][15/63] lr: 1.1357e-03 eta: 6:08:08 time: 0.7180 data_time: 0.0114 memory: 14901 loss: 1.2064 loss_prob: 0.6448 loss_thr: 0.4518 loss_db: 0.1097 2022/11/02 18:56:21 - mmengine - INFO - Epoch(train) [614][20/63] lr: 1.1357e-03 eta: 6:08:04 time: 0.7569 data_time: 0.0125 memory: 14901 loss: 1.2561 loss_prob: 0.6853 loss_thr: 0.4552 loss_db: 0.1156 2022/11/02 18:56:24 - mmengine - INFO - Epoch(train) [614][25/63] lr: 1.1357e-03 eta: 6:08:04 time: 0.7153 data_time: 0.0576 memory: 14901 loss: 1.2043 loss_prob: 0.6576 loss_thr: 0.4361 loss_db: 0.1106 2022/11/02 18:56:27 - mmengine - INFO - Epoch(train) [614][30/63] lr: 1.1357e-03 eta: 6:07:58 time: 0.5696 data_time: 0.0534 memory: 14901 loss: 1.0837 loss_prob: 0.5811 loss_thr: 0.4070 loss_db: 0.0956 2022/11/02 18:56:29 - mmengine - INFO - Epoch(train) [614][35/63] lr: 1.1357e-03 eta: 6:07:58 time: 0.5407 data_time: 0.0099 memory: 14901 loss: 1.1192 loss_prob: 0.5938 loss_thr: 0.4246 loss_db: 0.1008 2022/11/02 18:56:32 - mmengine - INFO - Epoch(train) [614][40/63] lr: 1.1357e-03 eta: 6:07:51 time: 0.5846 data_time: 0.0123 memory: 14901 loss: 1.2749 loss_prob: 0.7049 loss_thr: 0.4540 loss_db: 0.1161 2022/11/02 18:56:35 - mmengine - INFO - Epoch(train) [614][45/63] lr: 1.1357e-03 eta: 6:07:51 time: 0.5676 data_time: 0.0131 memory: 14901 loss: 1.3440 loss_prob: 0.7493 loss_thr: 0.4752 loss_db: 0.1195 2022/11/02 18:56:38 - mmengine - INFO - Epoch(train) [614][50/63] lr: 1.1357e-03 eta: 6:07:45 time: 0.5248 data_time: 0.0281 memory: 14901 loss: 1.2296 loss_prob: 0.6637 loss_thr: 0.4548 loss_db: 0.1111 2022/11/02 18:56:40 - mmengine - INFO - Epoch(train) [614][55/63] lr: 1.1357e-03 eta: 6:07:45 time: 0.5217 data_time: 0.0237 memory: 14901 loss: 1.1724 loss_prob: 0.6275 loss_thr: 0.4386 loss_db: 0.1063 2022/11/02 18:56:43 - mmengine - INFO - Epoch(train) [614][60/63] lr: 1.1357e-03 eta: 6:07:38 time: 0.5652 data_time: 0.0123 memory: 14901 loss: 1.1634 loss_prob: 0.6076 loss_thr: 0.4522 loss_db: 0.1036 2022/11/02 18:56:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:56:50 - mmengine - INFO - Epoch(train) [615][5/63] lr: 1.1339e-03 eta: 6:07:38 time: 0.8011 data_time: 0.2426 memory: 14901 loss: 1.1095 loss_prob: 0.5763 loss_thr: 0.4345 loss_db: 0.0988 2022/11/02 18:56:53 - mmengine - INFO - Epoch(train) [615][10/63] lr: 1.1339e-03 eta: 6:07:31 time: 0.8240 data_time: 0.2435 memory: 14901 loss: 1.1040 loss_prob: 0.5727 loss_thr: 0.4347 loss_db: 0.0967 2022/11/02 18:56:56 - mmengine - INFO - Epoch(train) [615][15/63] lr: 1.1339e-03 eta: 6:07:31 time: 0.5495 data_time: 0.0101 memory: 14901 loss: 1.1838 loss_prob: 0.6275 loss_thr: 0.4489 loss_db: 0.1074 2022/11/02 18:57:00 - mmengine - INFO - Epoch(train) [615][20/63] lr: 1.1339e-03 eta: 6:07:26 time: 0.6636 data_time: 0.0098 memory: 14901 loss: 1.2361 loss_prob: 0.6638 loss_thr: 0.4582 loss_db: 0.1141 2022/11/02 18:57:03 - mmengine - INFO - Epoch(train) [615][25/63] lr: 1.1339e-03 eta: 6:07:26 time: 0.7178 data_time: 0.0394 memory: 14901 loss: 1.1861 loss_prob: 0.6360 loss_thr: 0.4406 loss_db: 0.1095 2022/11/02 18:57:06 - mmengine - INFO - Epoch(train) [615][30/63] lr: 1.1339e-03 eta: 6:07:20 time: 0.5907 data_time: 0.0393 memory: 14901 loss: 1.1909 loss_prob: 0.6418 loss_thr: 0.4398 loss_db: 0.1092 2022/11/02 18:57:08 - mmengine - INFO - Epoch(train) [615][35/63] lr: 1.1339e-03 eta: 6:07:20 time: 0.5390 data_time: 0.0132 memory: 14901 loss: 1.2771 loss_prob: 0.6994 loss_thr: 0.4620 loss_db: 0.1157 2022/11/02 18:57:12 - mmengine - INFO - Epoch(train) [615][40/63] lr: 1.1339e-03 eta: 6:07:14 time: 0.6128 data_time: 0.0166 memory: 14901 loss: 1.3406 loss_prob: 0.7336 loss_thr: 0.4841 loss_db: 0.1229 2022/11/02 18:57:14 - mmengine - INFO - Epoch(train) [615][45/63] lr: 1.1339e-03 eta: 6:07:14 time: 0.5803 data_time: 0.0101 memory: 14901 loss: 1.2759 loss_prob: 0.6804 loss_thr: 0.4772 loss_db: 0.1183 2022/11/02 18:57:17 - mmengine - INFO - Epoch(train) [615][50/63] lr: 1.1339e-03 eta: 6:07:07 time: 0.5081 data_time: 0.0228 memory: 14901 loss: 1.1777 loss_prob: 0.6139 loss_thr: 0.4587 loss_db: 0.1051 2022/11/02 18:57:20 - mmengine - INFO - Epoch(train) [615][55/63] lr: 1.1339e-03 eta: 6:07:07 time: 0.6040 data_time: 0.0259 memory: 14901 loss: 1.1254 loss_prob: 0.5865 loss_thr: 0.4412 loss_db: 0.0977 2022/11/02 18:57:23 - mmengine - INFO - Epoch(train) [615][60/63] lr: 1.1339e-03 eta: 6:07:01 time: 0.6107 data_time: 0.0110 memory: 14901 loss: 1.1683 loss_prob: 0.6123 loss_thr: 0.4516 loss_db: 0.1044 2022/11/02 18:57:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:57:31 - mmengine - INFO - Epoch(train) [616][5/63] lr: 1.1322e-03 eta: 6:07:01 time: 0.8750 data_time: 0.2198 memory: 14901 loss: 1.0596 loss_prob: 0.5445 loss_thr: 0.4217 loss_db: 0.0934 2022/11/02 18:57:34 - mmengine - INFO - Epoch(train) [616][10/63] lr: 1.1322e-03 eta: 6:06:55 time: 0.9806 data_time: 0.2264 memory: 14901 loss: 1.1123 loss_prob: 0.5894 loss_thr: 0.4244 loss_db: 0.0985 2022/11/02 18:57:37 - mmengine - INFO - Epoch(train) [616][15/63] lr: 1.1322e-03 eta: 6:06:55 time: 0.6779 data_time: 0.0139 memory: 14901 loss: 1.1471 loss_prob: 0.6098 loss_thr: 0.4343 loss_db: 0.1030 2022/11/02 18:57:40 - mmengine - INFO - Epoch(train) [616][20/63] lr: 1.1322e-03 eta: 6:06:50 time: 0.6288 data_time: 0.0072 memory: 14901 loss: 1.1462 loss_prob: 0.6006 loss_thr: 0.4414 loss_db: 0.1042 2022/11/02 18:57:45 - mmengine - INFO - Epoch(train) [616][25/63] lr: 1.1322e-03 eta: 6:06:50 time: 0.7134 data_time: 0.0133 memory: 14901 loss: 1.1549 loss_prob: 0.6114 loss_thr: 0.4379 loss_db: 0.1056 2022/11/02 18:57:48 - mmengine - INFO - Epoch(train) [616][30/63] lr: 1.1322e-03 eta: 6:06:45 time: 0.7596 data_time: 0.0478 memory: 14901 loss: 1.2160 loss_prob: 0.6566 loss_thr: 0.4485 loss_db: 0.1110 2022/11/02 18:57:51 - mmengine - INFO - Epoch(train) [616][35/63] lr: 1.1322e-03 eta: 6:06:45 time: 0.6320 data_time: 0.0496 memory: 14901 loss: 1.1914 loss_prob: 0.6369 loss_thr: 0.4458 loss_db: 0.1087 2022/11/02 18:57:54 - mmengine - INFO - Epoch(train) [616][40/63] lr: 1.1322e-03 eta: 6:06:39 time: 0.5659 data_time: 0.0179 memory: 14901 loss: 1.1524 loss_prob: 0.6121 loss_thr: 0.4341 loss_db: 0.1062 2022/11/02 18:57:58 - mmengine - INFO - Epoch(train) [616][45/63] lr: 1.1322e-03 eta: 6:06:39 time: 0.6898 data_time: 0.0117 memory: 14901 loss: 1.3644 loss_prob: 0.7692 loss_thr: 0.4721 loss_db: 0.1231 2022/11/02 18:58:01 - mmengine - INFO - Epoch(train) [616][50/63] lr: 1.1322e-03 eta: 6:06:35 time: 0.7895 data_time: 0.0246 memory: 14901 loss: 1.3750 loss_prob: 0.7676 loss_thr: 0.4835 loss_db: 0.1240 2022/11/02 18:58:05 - mmengine - INFO - Epoch(train) [616][55/63] lr: 1.1322e-03 eta: 6:06:35 time: 0.6832 data_time: 0.0277 memory: 14901 loss: 1.1786 loss_prob: 0.6202 loss_thr: 0.4509 loss_db: 0.1075 2022/11/02 18:58:07 - mmengine - INFO - Epoch(train) [616][60/63] lr: 1.1322e-03 eta: 6:06:29 time: 0.5897 data_time: 0.0118 memory: 14901 loss: 1.2884 loss_prob: 0.7124 loss_thr: 0.4526 loss_db: 0.1234 2022/11/02 18:58:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:58:16 - mmengine - INFO - Epoch(train) [617][5/63] lr: 1.1304e-03 eta: 6:06:29 time: 0.9381 data_time: 0.2369 memory: 14901 loss: 1.2958 loss_prob: 0.6902 loss_thr: 0.4884 loss_db: 0.1172 2022/11/02 18:58:19 - mmengine - INFO - Epoch(train) [617][10/63] lr: 1.1304e-03 eta: 6:06:23 time: 0.9453 data_time: 0.2351 memory: 14901 loss: 1.5890 loss_prob: 0.9393 loss_thr: 0.5110 loss_db: 0.1387 2022/11/02 18:58:21 - mmengine - INFO - Epoch(train) [617][15/63] lr: 1.1304e-03 eta: 6:06:23 time: 0.5704 data_time: 0.0107 memory: 14901 loss: 1.6950 loss_prob: 1.0401 loss_thr: 0.5050 loss_db: 0.1499 2022/11/02 18:58:24 - mmengine - INFO - Epoch(train) [617][20/63] lr: 1.1304e-03 eta: 6:06:16 time: 0.5534 data_time: 0.0226 memory: 14901 loss: 1.4076 loss_prob: 0.8017 loss_thr: 0.4769 loss_db: 0.1289 2022/11/02 18:58:27 - mmengine - INFO - Epoch(train) [617][25/63] lr: 1.1304e-03 eta: 6:06:16 time: 0.5679 data_time: 0.0365 memory: 14901 loss: 1.3292 loss_prob: 0.7252 loss_thr: 0.4823 loss_db: 0.1217 2022/11/02 18:58:30 - mmengine - INFO - Epoch(train) [617][30/63] lr: 1.1304e-03 eta: 6:06:10 time: 0.5488 data_time: 0.0363 memory: 14901 loss: 1.3686 loss_prob: 0.7638 loss_thr: 0.4788 loss_db: 0.1260 2022/11/02 18:58:32 - mmengine - INFO - Epoch(train) [617][35/63] lr: 1.1304e-03 eta: 6:06:10 time: 0.5365 data_time: 0.0225 memory: 14901 loss: 1.3981 loss_prob: 0.7840 loss_thr: 0.4834 loss_db: 0.1307 2022/11/02 18:58:35 - mmengine - INFO - Epoch(train) [617][40/63] lr: 1.1304e-03 eta: 6:06:04 time: 0.5628 data_time: 0.0132 memory: 14901 loss: 1.3197 loss_prob: 0.7146 loss_thr: 0.4843 loss_db: 0.1207 2022/11/02 18:58:38 - mmengine - INFO - Epoch(train) [617][45/63] lr: 1.1304e-03 eta: 6:06:04 time: 0.5451 data_time: 0.0203 memory: 14901 loss: 1.2703 loss_prob: 0.6846 loss_thr: 0.4718 loss_db: 0.1139 2022/11/02 18:58:41 - mmengine - INFO - Epoch(train) [617][50/63] lr: 1.1304e-03 eta: 6:05:57 time: 0.5425 data_time: 0.0366 memory: 14901 loss: 1.2317 loss_prob: 0.6623 loss_thr: 0.4571 loss_db: 0.1123 2022/11/02 18:58:43 - mmengine - INFO - Epoch(train) [617][55/63] lr: 1.1304e-03 eta: 6:05:57 time: 0.5461 data_time: 0.0302 memory: 14901 loss: 1.2452 loss_prob: 0.6649 loss_thr: 0.4657 loss_db: 0.1146 2022/11/02 18:58:47 - mmengine - INFO - Epoch(train) [617][60/63] lr: 1.1304e-03 eta: 6:05:51 time: 0.6035 data_time: 0.0116 memory: 14901 loss: 1.1945 loss_prob: 0.6407 loss_thr: 0.4432 loss_db: 0.1107 2022/11/02 18:58:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:58:54 - mmengine - INFO - Epoch(train) [618][5/63] lr: 1.1287e-03 eta: 6:05:51 time: 0.9130 data_time: 0.3035 memory: 14901 loss: 1.2313 loss_prob: 0.6636 loss_thr: 0.4534 loss_db: 0.1143 2022/11/02 18:58:57 - mmengine - INFO - Epoch(train) [618][10/63] lr: 1.1287e-03 eta: 6:05:44 time: 0.8739 data_time: 0.2999 memory: 14901 loss: 1.3186 loss_prob: 0.7273 loss_thr: 0.4699 loss_db: 0.1214 2022/11/02 18:58:59 - mmengine - INFO - Epoch(train) [618][15/63] lr: 1.1287e-03 eta: 6:05:44 time: 0.5028 data_time: 0.0104 memory: 14901 loss: 1.3170 loss_prob: 0.7251 loss_thr: 0.4716 loss_db: 0.1203 2022/11/02 18:59:02 - mmengine - INFO - Epoch(train) [618][20/63] lr: 1.1287e-03 eta: 6:05:38 time: 0.5367 data_time: 0.0111 memory: 14901 loss: 1.2549 loss_prob: 0.6618 loss_thr: 0.4807 loss_db: 0.1124 2022/11/02 18:59:06 - mmengine - INFO - Epoch(train) [618][25/63] lr: 1.1287e-03 eta: 6:05:38 time: 0.7037 data_time: 0.0508 memory: 14901 loss: 1.2093 loss_prob: 0.6331 loss_thr: 0.4676 loss_db: 0.1085 2022/11/02 18:59:09 - mmengine - INFO - Epoch(train) [618][30/63] lr: 1.1287e-03 eta: 6:05:32 time: 0.6736 data_time: 0.0502 memory: 14901 loss: 1.2350 loss_prob: 0.6576 loss_thr: 0.4632 loss_db: 0.1142 2022/11/02 18:59:12 - mmengine - INFO - Epoch(train) [618][35/63] lr: 1.1287e-03 eta: 6:05:32 time: 0.5448 data_time: 0.0115 memory: 14901 loss: 1.2590 loss_prob: 0.6741 loss_thr: 0.4680 loss_db: 0.1169 2022/11/02 18:59:15 - mmengine - INFO - Epoch(train) [618][40/63] lr: 1.1287e-03 eta: 6:05:26 time: 0.5738 data_time: 0.0111 memory: 14901 loss: 1.2196 loss_prob: 0.6486 loss_thr: 0.4611 loss_db: 0.1099 2022/11/02 18:59:18 - mmengine - INFO - Epoch(train) [618][45/63] lr: 1.1287e-03 eta: 6:05:26 time: 0.5836 data_time: 0.0108 memory: 14901 loss: 1.2012 loss_prob: 0.6383 loss_thr: 0.4533 loss_db: 0.1096 2022/11/02 18:59:21 - mmengine - INFO - Epoch(train) [618][50/63] lr: 1.1287e-03 eta: 6:05:20 time: 0.6057 data_time: 0.0304 memory: 14901 loss: 1.2419 loss_prob: 0.6686 loss_thr: 0.4594 loss_db: 0.1138 2022/11/02 18:59:24 - mmengine - INFO - Epoch(train) [618][55/63] lr: 1.1287e-03 eta: 6:05:20 time: 0.6348 data_time: 0.0331 memory: 14901 loss: 1.2621 loss_prob: 0.6802 loss_thr: 0.4667 loss_db: 0.1152 2022/11/02 18:59:27 - mmengine - INFO - Epoch(train) [618][60/63] lr: 1.1287e-03 eta: 6:05:15 time: 0.6327 data_time: 0.0150 memory: 14901 loss: 1.1948 loss_prob: 0.6397 loss_thr: 0.4457 loss_db: 0.1093 2022/11/02 18:59:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 18:59:35 - mmengine - INFO - Epoch(train) [619][5/63] lr: 1.1270e-03 eta: 6:05:15 time: 0.8953 data_time: 0.2063 memory: 14901 loss: 1.2154 loss_prob: 0.6553 loss_thr: 0.4504 loss_db: 0.1097 2022/11/02 18:59:38 - mmengine - INFO - Epoch(train) [619][10/63] lr: 1.1270e-03 eta: 6:05:08 time: 0.8586 data_time: 0.2234 memory: 14901 loss: 1.2253 loss_prob: 0.6562 loss_thr: 0.4590 loss_db: 0.1101 2022/11/02 18:59:41 - mmengine - INFO - Epoch(train) [619][15/63] lr: 1.1270e-03 eta: 6:05:08 time: 0.5932 data_time: 0.0285 memory: 14901 loss: 1.2045 loss_prob: 0.6401 loss_thr: 0.4555 loss_db: 0.1089 2022/11/02 18:59:43 - mmengine - INFO - Epoch(train) [619][20/63] lr: 1.1270e-03 eta: 6:05:01 time: 0.5541 data_time: 0.0123 memory: 14901 loss: 1.0812 loss_prob: 0.5712 loss_thr: 0.4105 loss_db: 0.0996 2022/11/02 18:59:46 - mmengine - INFO - Epoch(train) [619][25/63] lr: 1.1270e-03 eta: 6:05:01 time: 0.5631 data_time: 0.0296 memory: 14901 loss: 1.1549 loss_prob: 0.6106 loss_thr: 0.4405 loss_db: 0.1038 2022/11/02 18:59:50 - mmengine - INFO - Epoch(train) [619][30/63] lr: 1.1270e-03 eta: 6:04:56 time: 0.7001 data_time: 0.0344 memory: 14901 loss: 1.2411 loss_prob: 0.6621 loss_thr: 0.4685 loss_db: 0.1104 2022/11/02 18:59:53 - mmengine - INFO - Epoch(train) [619][35/63] lr: 1.1270e-03 eta: 6:04:56 time: 0.6575 data_time: 0.0234 memory: 14901 loss: 1.2560 loss_prob: 0.6783 loss_thr: 0.4641 loss_db: 0.1135 2022/11/02 18:59:55 - mmengine - INFO - Epoch(train) [619][40/63] lr: 1.1270e-03 eta: 6:04:50 time: 0.5304 data_time: 0.0186 memory: 14901 loss: 1.2048 loss_prob: 0.6342 loss_thr: 0.4625 loss_db: 0.1082 2022/11/02 18:59:58 - mmengine - INFO - Epoch(train) [619][45/63] lr: 1.1270e-03 eta: 6:04:50 time: 0.5269 data_time: 0.0091 memory: 14901 loss: 1.2503 loss_prob: 0.6854 loss_thr: 0.4506 loss_db: 0.1143 2022/11/02 19:00:01 - mmengine - INFO - Epoch(train) [619][50/63] lr: 1.1270e-03 eta: 6:04:44 time: 0.5786 data_time: 0.0236 memory: 14901 loss: 1.3283 loss_prob: 0.7478 loss_thr: 0.4577 loss_db: 0.1227 2022/11/02 19:00:04 - mmengine - INFO - Epoch(train) [619][55/63] lr: 1.1270e-03 eta: 6:04:44 time: 0.5694 data_time: 0.0306 memory: 14901 loss: 1.2522 loss_prob: 0.6763 loss_thr: 0.4628 loss_db: 0.1131 2022/11/02 19:00:06 - mmengine - INFO - Epoch(train) [619][60/63] lr: 1.1270e-03 eta: 6:04:37 time: 0.5057 data_time: 0.0165 memory: 14901 loss: 1.2379 loss_prob: 0.6512 loss_thr: 0.4755 loss_db: 0.1112 2022/11/02 19:00:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:00:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:00:13 - mmengine - INFO - Epoch(train) [620][5/63] lr: 1.1252e-03 eta: 6:04:37 time: 0.7644 data_time: 0.2390 memory: 14901 loss: 1.1842 loss_prob: 0.6337 loss_thr: 0.4406 loss_db: 0.1099 2022/11/02 19:00:16 - mmengine - INFO - Epoch(train) [620][10/63] lr: 1.1252e-03 eta: 6:04:29 time: 0.8039 data_time: 0.2448 memory: 14901 loss: 1.1168 loss_prob: 0.5885 loss_thr: 0.4266 loss_db: 0.1016 2022/11/02 19:00:19 - mmengine - INFO - Epoch(train) [620][15/63] lr: 1.1252e-03 eta: 6:04:29 time: 0.5673 data_time: 0.0174 memory: 14901 loss: 1.1216 loss_prob: 0.5942 loss_thr: 0.4256 loss_db: 0.1018 2022/11/02 19:00:21 - mmengine - INFO - Epoch(train) [620][20/63] lr: 1.1252e-03 eta: 6:04:23 time: 0.5649 data_time: 0.0089 memory: 14901 loss: 1.1964 loss_prob: 0.6354 loss_thr: 0.4521 loss_db: 0.1088 2022/11/02 19:00:25 - mmengine - INFO - Epoch(train) [620][25/63] lr: 1.1252e-03 eta: 6:04:23 time: 0.6300 data_time: 0.0086 memory: 14901 loss: 1.1779 loss_prob: 0.6160 loss_thr: 0.4532 loss_db: 0.1086 2022/11/02 19:00:28 - mmengine - INFO - Epoch(train) [620][30/63] lr: 1.1252e-03 eta: 6:04:17 time: 0.6578 data_time: 0.0571 memory: 14901 loss: 1.2176 loss_prob: 0.6466 loss_thr: 0.4571 loss_db: 0.1139 2022/11/02 19:00:31 - mmengine - INFO - Epoch(train) [620][35/63] lr: 1.1252e-03 eta: 6:04:17 time: 0.5603 data_time: 0.0540 memory: 14901 loss: 1.2749 loss_prob: 0.6771 loss_thr: 0.4826 loss_db: 0.1152 2022/11/02 19:00:33 - mmengine - INFO - Epoch(train) [620][40/63] lr: 1.1252e-03 eta: 6:04:11 time: 0.5172 data_time: 0.0086 memory: 14901 loss: 1.2616 loss_prob: 0.6738 loss_thr: 0.4750 loss_db: 0.1128 2022/11/02 19:00:36 - mmengine - INFO - Epoch(train) [620][45/63] lr: 1.1252e-03 eta: 6:04:11 time: 0.5483 data_time: 0.0115 memory: 14901 loss: 1.2627 loss_prob: 0.6822 loss_thr: 0.4627 loss_db: 0.1179 2022/11/02 19:00:39 - mmengine - INFO - Epoch(train) [620][50/63] lr: 1.1252e-03 eta: 6:04:05 time: 0.6052 data_time: 0.0225 memory: 14901 loss: 1.1366 loss_prob: 0.6005 loss_thr: 0.4316 loss_db: 0.1045 2022/11/02 19:00:42 - mmengine - INFO - Epoch(train) [620][55/63] lr: 1.1252e-03 eta: 6:04:05 time: 0.5634 data_time: 0.0250 memory: 14901 loss: 1.5088 loss_prob: 0.9239 loss_thr: 0.4584 loss_db: 0.1266 2022/11/02 19:00:44 - mmengine - INFO - Epoch(train) [620][60/63] lr: 1.1252e-03 eta: 6:03:58 time: 0.5364 data_time: 0.0168 memory: 14901 loss: 1.6466 loss_prob: 1.0203 loss_thr: 0.4853 loss_db: 0.1411 2022/11/02 19:00:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:00:46 - mmengine - INFO - Saving checkpoint at 620 epochs 2022/11/02 19:00:49 - mmengine - INFO - Epoch(val) [620][5/500] eta: 6:03:58 time: 0.0484 data_time: 0.0052 memory: 14901 2022/11/02 19:00:50 - mmengine - INFO - Epoch(val) [620][10/500] eta: 0:00:23 time: 0.0481 data_time: 0.0047 memory: 1008 2022/11/02 19:00:50 - mmengine - INFO - Epoch(val) [620][15/500] eta: 0:00:23 time: 0.0409 data_time: 0.0026 memory: 1008 2022/11/02 19:00:50 - mmengine - INFO - Epoch(val) [620][20/500] eta: 0:00:22 time: 0.0471 data_time: 0.0033 memory: 1008 2022/11/02 19:00:50 - mmengine - INFO - Epoch(val) [620][25/500] eta: 0:00:22 time: 0.0453 data_time: 0.0031 memory: 1008 2022/11/02 19:00:50 - mmengine - INFO - Epoch(val) [620][30/500] eta: 0:00:21 time: 0.0457 data_time: 0.0032 memory: 1008 2022/11/02 19:00:51 - mmengine - INFO - Epoch(val) [620][35/500] eta: 0:00:21 time: 0.0455 data_time: 0.0033 memory: 1008 2022/11/02 19:00:51 - mmengine - INFO - Epoch(val) [620][40/500] eta: 0:00:19 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 19:00:51 - mmengine - INFO - Epoch(val) [620][45/500] eta: 0:00:19 time: 0.0437 data_time: 0.0025 memory: 1008 2022/11/02 19:00:51 - mmengine - INFO - Epoch(val) [620][50/500] eta: 0:00:19 time: 0.0424 data_time: 0.0026 memory: 1008 2022/11/02 19:00:52 - mmengine - INFO - Epoch(val) [620][55/500] eta: 0:00:19 time: 0.0443 data_time: 0.0028 memory: 1008 2022/11/02 19:00:52 - mmengine - INFO - Epoch(val) [620][60/500] eta: 0:00:18 time: 0.0424 data_time: 0.0029 memory: 1008 2022/11/02 19:00:52 - mmengine - INFO - Epoch(val) [620][65/500] eta: 0:00:18 time: 0.0477 data_time: 0.0034 memory: 1008 2022/11/02 19:00:52 - mmengine - INFO - Epoch(val) [620][70/500] eta: 0:00:20 time: 0.0482 data_time: 0.0035 memory: 1008 2022/11/02 19:00:52 - mmengine - INFO - Epoch(val) [620][75/500] eta: 0:00:20 time: 0.0402 data_time: 0.0028 memory: 1008 2022/11/02 19:00:53 - mmengine - INFO - Epoch(val) [620][80/500] eta: 0:00:15 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 19:00:53 - mmengine - INFO - Epoch(val) [620][85/500] eta: 0:00:15 time: 0.0352 data_time: 0.0026 memory: 1008 2022/11/02 19:00:53 - mmengine - INFO - Epoch(val) [620][90/500] eta: 0:00:16 time: 0.0402 data_time: 0.0029 memory: 1008 2022/11/02 19:00:53 - mmengine - INFO - Epoch(val) [620][95/500] eta: 0:00:16 time: 0.0451 data_time: 0.0031 memory: 1008 2022/11/02 19:00:53 - mmengine - INFO - Epoch(val) [620][100/500] eta: 0:00:16 time: 0.0420 data_time: 0.0032 memory: 1008 2022/11/02 19:00:54 - mmengine - INFO - Epoch(val) [620][105/500] eta: 0:00:16 time: 0.0400 data_time: 0.0033 memory: 1008 2022/11/02 19:00:54 - mmengine - INFO - Epoch(val) [620][110/500] eta: 0:00:15 time: 0.0394 data_time: 0.0030 memory: 1008 2022/11/02 19:00:54 - mmengine - INFO - Epoch(val) [620][115/500] eta: 0:00:15 time: 0.0386 data_time: 0.0027 memory: 1008 2022/11/02 19:00:54 - mmengine - INFO - Epoch(val) [620][120/500] eta: 0:00:15 time: 0.0407 data_time: 0.0030 memory: 1008 2022/11/02 19:00:54 - mmengine - INFO - Epoch(val) [620][125/500] eta: 0:00:15 time: 0.0398 data_time: 0.0030 memory: 1008 2022/11/02 19:00:55 - mmengine - INFO - Epoch(val) [620][130/500] eta: 0:00:14 time: 0.0384 data_time: 0.0028 memory: 1008 2022/11/02 19:00:55 - mmengine - INFO - Epoch(val) [620][135/500] eta: 0:00:14 time: 0.0397 data_time: 0.0028 memory: 1008 2022/11/02 19:00:55 - mmengine - INFO - Epoch(val) [620][140/500] eta: 0:00:14 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 19:00:55 - mmengine - INFO - Epoch(val) [620][145/500] eta: 0:00:14 time: 0.0466 data_time: 0.0031 memory: 1008 2022/11/02 19:00:55 - mmengine - INFO - Epoch(val) [620][150/500] eta: 0:00:15 time: 0.0451 data_time: 0.0027 memory: 1008 2022/11/02 19:00:56 - mmengine - INFO - Epoch(val) [620][155/500] eta: 0:00:15 time: 0.0472 data_time: 0.0025 memory: 1008 2022/11/02 19:00:56 - mmengine - INFO - Epoch(val) [620][160/500] eta: 0:00:16 time: 0.0472 data_time: 0.0025 memory: 1008 2022/11/02 19:00:56 - mmengine - INFO - Epoch(val) [620][165/500] eta: 0:00:16 time: 0.0393 data_time: 0.0023 memory: 1008 2022/11/02 19:00:56 - mmengine - INFO - Epoch(val) [620][170/500] eta: 0:00:13 time: 0.0418 data_time: 0.0026 memory: 1008 2022/11/02 19:00:57 - mmengine - INFO - Epoch(val) [620][175/500] eta: 0:00:13 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/02 19:00:57 - mmengine - INFO - Epoch(val) [620][180/500] eta: 0:00:12 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 19:00:57 - mmengine - INFO - Epoch(val) [620][185/500] eta: 0:00:12 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 19:00:57 - mmengine - INFO - Epoch(val) [620][190/500] eta: 0:00:12 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 19:00:57 - mmengine - INFO - Epoch(val) 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eta: 0:00:10 time: 0.0379 data_time: 0.0027 memory: 1008 2022/11/02 19:00:59 - mmengine - INFO - Epoch(val) [620][240/500] eta: 0:00:11 time: 0.0428 data_time: 0.0035 memory: 1008 2022/11/02 19:00:59 - mmengine - INFO - Epoch(val) [620][245/500] eta: 0:00:11 time: 0.0419 data_time: 0.0035 memory: 1008 2022/11/02 19:01:00 - mmengine - INFO - Epoch(val) [620][250/500] eta: 0:00:11 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/02 19:01:00 - mmengine - INFO - Epoch(val) [620][255/500] eta: 0:00:11 time: 0.0526 data_time: 0.0044 memory: 1008 2022/11/02 19:01:00 - mmengine - INFO - Epoch(val) [620][260/500] eta: 0:00:12 time: 0.0500 data_time: 0.0046 memory: 1008 2022/11/02 19:01:00 - mmengine - INFO - Epoch(val) [620][265/500] eta: 0:00:12 time: 0.0421 data_time: 0.0035 memory: 1008 2022/11/02 19:01:01 - mmengine - INFO - Epoch(val) [620][270/500] eta: 0:00:09 time: 0.0427 data_time: 0.0031 memory: 1008 2022/11/02 19:01:01 - mmengine - INFO - Epoch(val) [620][275/500] eta: 0:00:09 time: 0.0462 data_time: 0.0036 memory: 1008 2022/11/02 19:01:01 - mmengine - INFO - Epoch(val) [620][280/500] eta: 0:00:11 time: 0.0533 data_time: 0.0041 memory: 1008 2022/11/02 19:01:01 - mmengine - INFO - Epoch(val) [620][285/500] eta: 0:00:11 time: 0.0507 data_time: 0.0038 memory: 1008 2022/11/02 19:01:02 - mmengine - INFO - Epoch(val) [620][290/500] eta: 0:00:09 time: 0.0456 data_time: 0.0034 memory: 1008 2022/11/02 19:01:02 - mmengine - INFO - Epoch(val) [620][295/500] eta: 0:00:09 time: 0.0518 data_time: 0.0040 memory: 1008 2022/11/02 19:01:02 - mmengine - INFO - Epoch(val) [620][300/500] eta: 0:00:10 time: 0.0545 data_time: 0.0047 memory: 1008 2022/11/02 19:01:02 - mmengine - INFO - Epoch(val) [620][305/500] eta: 0:00:10 time: 0.0519 data_time: 0.0040 memory: 1008 2022/11/02 19:01:03 - mmengine - INFO - Epoch(val) [620][310/500] eta: 0:00:09 time: 0.0490 data_time: 0.0033 memory: 1008 2022/11/02 19:01:03 - mmengine - INFO - Epoch(val) [620][315/500] eta: 0:00:09 time: 0.0468 data_time: 0.0034 memory: 1008 2022/11/02 19:01:03 - mmengine - INFO - Epoch(val) [620][320/500] eta: 0:00:07 time: 0.0441 data_time: 0.0035 memory: 1008 2022/11/02 19:01:03 - mmengine - INFO - Epoch(val) [620][325/500] eta: 0:00:07 time: 0.0565 data_time: 0.0030 memory: 1008 2022/11/02 19:01:04 - mmengine - INFO - Epoch(val) [620][330/500] eta: 0:00:09 time: 0.0580 data_time: 0.0030 memory: 1008 2022/11/02 19:01:04 - mmengine - INFO - Epoch(val) [620][335/500] eta: 0:00:09 time: 0.0433 data_time: 0.0032 memory: 1008 2022/11/02 19:01:04 - mmengine - INFO - Epoch(val) [620][340/500] eta: 0:00:07 time: 0.0490 data_time: 0.0027 memory: 1008 2022/11/02 19:01:04 - mmengine - INFO - Epoch(val) [620][345/500] eta: 0:00:07 time: 0.0521 data_time: 0.0027 memory: 1008 2022/11/02 19:01:05 - mmengine - INFO - Epoch(val) [620][350/500] eta: 0:00:07 time: 0.0523 data_time: 0.0031 memory: 1008 2022/11/02 19:01:05 - mmengine - INFO - Epoch(val) [620][355/500] eta: 0:00:07 time: 0.0475 data_time: 0.0031 memory: 1008 2022/11/02 19:01:05 - mmengine - INFO - Epoch(val) [620][360/500] eta: 0:00:05 time: 0.0403 data_time: 0.0029 memory: 1008 2022/11/02 19:01:05 - mmengine - INFO - Epoch(val) [620][365/500] eta: 0:00:05 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 19:01:06 - mmengine - INFO - Epoch(val) [620][370/500] eta: 0:00:04 time: 0.0358 data_time: 0.0023 memory: 1008 2022/11/02 19:01:06 - mmengine - INFO - Epoch(val) [620][375/500] eta: 0:00:04 time: 0.0360 data_time: 0.0023 memory: 1008 2022/11/02 19:01:06 - mmengine - INFO - Epoch(val) [620][380/500] eta: 0:00:05 time: 0.0419 data_time: 0.0027 memory: 1008 2022/11/02 19:01:06 - mmengine - INFO - Epoch(val) [620][385/500] eta: 0:00:05 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 19:01:06 - mmengine - INFO - Epoch(val) [620][390/500] eta: 0:00:04 time: 0.0423 data_time: 0.0026 memory: 1008 2022/11/02 19:01:07 - mmengine - INFO - Epoch(val) [620][395/500] eta: 0:00:04 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 19:01:07 - mmengine - INFO - Epoch(val) [620][400/500] eta: 0:00:04 time: 0.0422 data_time: 0.0032 memory: 1008 2022/11/02 19:01:07 - mmengine - INFO - Epoch(val) [620][405/500] eta: 0:00:04 time: 0.0440 data_time: 0.0033 memory: 1008 2022/11/02 19:01:07 - mmengine - INFO - Epoch(val) [620][410/500] eta: 0:00:03 time: 0.0422 data_time: 0.0027 memory: 1008 2022/11/02 19:01:07 - mmengine - INFO - Epoch(val) [620][415/500] eta: 0:00:03 time: 0.0407 data_time: 0.0024 memory: 1008 2022/11/02 19:01:08 - mmengine - INFO - Epoch(val) [620][420/500] eta: 0:00:03 time: 0.0384 data_time: 0.0026 memory: 1008 2022/11/02 19:01:08 - mmengine - INFO - Epoch(val) [620][425/500] eta: 0:00:03 time: 0.0375 data_time: 0.0026 memory: 1008 2022/11/02 19:01:08 - mmengine - INFO - Epoch(val) [620][430/500] eta: 0:00:02 time: 0.0405 data_time: 0.0028 memory: 1008 2022/11/02 19:01:08 - mmengine - INFO - Epoch(val) [620][435/500] eta: 0:00:02 time: 0.0413 data_time: 0.0030 memory: 1008 2022/11/02 19:01:08 - mmengine - INFO - Epoch(val) [620][440/500] eta: 0:00:02 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/02 19:01:09 - mmengine - INFO - Epoch(val) [620][445/500] eta: 0:00:02 time: 0.0400 data_time: 0.0023 memory: 1008 2022/11/02 19:01:09 - mmengine - INFO - Epoch(val) [620][450/500] eta: 0:00:02 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 19:01:09 - mmengine - INFO - Epoch(val) [620][455/500] eta: 0:00:02 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 19:01:09 - mmengine - INFO - Epoch(val) [620][460/500] eta: 0:00:01 time: 0.0370 data_time: 0.0028 memory: 1008 2022/11/02 19:01:09 - mmengine - INFO - Epoch(val) [620][465/500] eta: 0:00:01 time: 0.0339 data_time: 0.0023 memory: 1008 2022/11/02 19:01:10 - mmengine - INFO - Epoch(val) [620][470/500] eta: 0:00:01 time: 0.0372 data_time: 0.0021 memory: 1008 2022/11/02 19:01:10 - mmengine - INFO - Epoch(val) [620][475/500] eta: 0:00:01 time: 0.0372 data_time: 0.0025 memory: 1008 2022/11/02 19:01:10 - mmengine - INFO - Epoch(val) [620][480/500] eta: 0:00:00 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/02 19:01:10 - mmengine - INFO - Epoch(val) [620][485/500] eta: 0:00:00 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 19:01:10 - mmengine - INFO - Epoch(val) [620][490/500] eta: 0:00:00 time: 0.0461 data_time: 0.0034 memory: 1008 2022/11/02 19:01:11 - mmengine - INFO - Epoch(val) [620][495/500] eta: 0:00:00 time: 0.0490 data_time: 0.0030 memory: 1008 2022/11/02 19:01:11 - mmengine - INFO - Epoch(val) [620][500/500] eta: 0:00:00 time: 0.0390 data_time: 0.0022 memory: 1008 2022/11/02 19:01:11 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8320, precision: 0.7191, hmean: 0.7714 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8320, precision: 0.7851, hmean: 0.8079 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8310, precision: 0.8184, hmean: 0.8247 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8257, precision: 0.8465, hmean: 0.8360 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7997, precision: 0.8770, hmean: 0.8366 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6177, precision: 0.9311, hmean: 0.7427 2022/11/02 19:01:11 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0515, precision: 0.9727, hmean: 0.0979 2022/11/02 19:01:11 - mmengine - INFO - Epoch(val) [620][500/500] icdar/precision: 0.8770 icdar/recall: 0.7997 icdar/hmean: 0.8366 2022/11/02 19:01:17 - mmengine - INFO - Epoch(train) [621][5/63] lr: 1.1235e-03 eta: 0:00:00 time: 0.8074 data_time: 0.2388 memory: 14901 loss: 1.1711 loss_prob: 0.6256 loss_thr: 0.4377 loss_db: 0.1079 2022/11/02 19:01:20 - mmengine - INFO - Epoch(train) [621][10/63] lr: 1.1235e-03 eta: 6:03:52 time: 0.9087 data_time: 0.2421 memory: 14901 loss: 1.2636 loss_prob: 0.6965 loss_thr: 0.4477 loss_db: 0.1193 2022/11/02 19:01:23 - mmengine - INFO - Epoch(train) [621][15/63] lr: 1.1235e-03 eta: 6:03:52 time: 0.6748 data_time: 0.0161 memory: 14901 loss: 1.2396 loss_prob: 0.6745 loss_thr: 0.4508 loss_db: 0.1143 2022/11/02 19:01:26 - mmengine - INFO - Epoch(train) [621][20/63] lr: 1.1235e-03 eta: 6:03:46 time: 0.6223 data_time: 0.0156 memory: 14901 loss: 1.1692 loss_prob: 0.6080 loss_thr: 0.4558 loss_db: 0.1054 2022/11/02 19:01:29 - mmengine - INFO - Epoch(train) [621][25/63] lr: 1.1235e-03 eta: 6:03:46 time: 0.5620 data_time: 0.0358 memory: 14901 loss: 1.1907 loss_prob: 0.6230 loss_thr: 0.4577 loss_db: 0.1099 2022/11/02 19:01:31 - mmengine - INFO - Epoch(train) [621][30/63] lr: 1.1235e-03 eta: 6:03:39 time: 0.5322 data_time: 0.0323 memory: 14901 loss: 1.2137 loss_prob: 0.6417 loss_thr: 0.4600 loss_db: 0.1120 2022/11/02 19:01:34 - mmengine - INFO - Epoch(train) [621][35/63] lr: 1.1235e-03 eta: 6:03:39 time: 0.5148 data_time: 0.0156 memory: 14901 loss: 1.2133 loss_prob: 0.6454 loss_thr: 0.4598 loss_db: 0.1082 2022/11/02 19:01:37 - mmengine - INFO - Epoch(train) [621][40/63] lr: 1.1235e-03 eta: 6:03:33 time: 0.5115 data_time: 0.0180 memory: 14901 loss: 1.2608 loss_prob: 0.6809 loss_thr: 0.4637 loss_db: 0.1162 2022/11/02 19:01:41 - mmengine - INFO - Epoch(train) [621][45/63] lr: 1.1235e-03 eta: 6:03:33 time: 0.6518 data_time: 0.0120 memory: 14901 loss: 1.3121 loss_prob: 0.7053 loss_thr: 0.4841 loss_db: 0.1227 2022/11/02 19:01:44 - mmengine - INFO - Epoch(train) [621][50/63] lr: 1.1235e-03 eta: 6:03:28 time: 0.7274 data_time: 0.0228 memory: 14901 loss: 1.2500 loss_prob: 0.6657 loss_thr: 0.4686 loss_db: 0.1157 2022/11/02 19:01:47 - mmengine - INFO - Epoch(train) [621][55/63] lr: 1.1235e-03 eta: 6:03:28 time: 0.6145 data_time: 0.0220 memory: 14901 loss: 1.2534 loss_prob: 0.6671 loss_thr: 0.4729 loss_db: 0.1134 2022/11/02 19:01:49 - mmengine - INFO - Epoch(train) [621][60/63] lr: 1.1235e-03 eta: 6:03:21 time: 0.5502 data_time: 0.0129 memory: 14901 loss: 1.2197 loss_prob: 0.6575 loss_thr: 0.4501 loss_db: 0.1121 2022/11/02 19:01:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:01:58 - mmengine - INFO - Epoch(train) [622][5/63] lr: 1.1217e-03 eta: 6:03:21 time: 0.9210 data_time: 0.2095 memory: 14901 loss: 1.1633 loss_prob: 0.6209 loss_thr: 0.4382 loss_db: 0.1042 2022/11/02 19:02:00 - mmengine - INFO - Epoch(train) [622][10/63] lr: 1.1217e-03 eta: 6:03:15 time: 0.9510 data_time: 0.2087 memory: 14901 loss: 1.1989 loss_prob: 0.6443 loss_thr: 0.4445 loss_db: 0.1100 2022/11/02 19:02:04 - mmengine - INFO - Epoch(train) [622][15/63] lr: 1.1217e-03 eta: 6:03:15 time: 0.6099 data_time: 0.0126 memory: 14901 loss: 1.2450 loss_prob: 0.6748 loss_thr: 0.4536 loss_db: 0.1166 2022/11/02 19:02:07 - mmengine - INFO - Epoch(train) [622][20/63] lr: 1.1217e-03 eta: 6:03:10 time: 0.6321 data_time: 0.0113 memory: 14901 loss: 1.1460 loss_prob: 0.6041 loss_thr: 0.4391 loss_db: 0.1028 2022/11/02 19:02:10 - mmengine - INFO - Epoch(train) [622][25/63] lr: 1.1217e-03 eta: 6:03:10 time: 0.5874 data_time: 0.0249 memory: 14901 loss: 1.1471 loss_prob: 0.6039 loss_thr: 0.4384 loss_db: 0.1048 2022/11/02 19:02:13 - mmengine - INFO - Epoch(train) [622][30/63] lr: 1.1217e-03 eta: 6:03:04 time: 0.6049 data_time: 0.0455 memory: 14901 loss: 1.2110 loss_prob: 0.6470 loss_thr: 0.4509 loss_db: 0.1131 2022/11/02 19:02:15 - mmengine - INFO - Epoch(train) [622][35/63] lr: 1.1217e-03 eta: 6:03:04 time: 0.5861 data_time: 0.0316 memory: 14901 loss: 1.2171 loss_prob: 0.6440 loss_thr: 0.4612 loss_db: 0.1119 2022/11/02 19:02:19 - mmengine - INFO - Epoch(train) [622][40/63] lr: 1.1217e-03 eta: 6:02:58 time: 0.5990 data_time: 0.0105 memory: 14901 loss: 1.2631 loss_prob: 0.6760 loss_thr: 0.4680 loss_db: 0.1192 2022/11/02 19:02:22 - mmengine - INFO - Epoch(train) [622][45/63] lr: 1.1217e-03 eta: 6:02:58 time: 0.6150 data_time: 0.0082 memory: 14901 loss: 1.3069 loss_prob: 0.7240 loss_thr: 0.4622 loss_db: 0.1207 2022/11/02 19:02:25 - mmengine - INFO - Epoch(train) [622][50/63] lr: 1.1217e-03 eta: 6:02:52 time: 0.6233 data_time: 0.0184 memory: 14901 loss: 1.1821 loss_prob: 0.6397 loss_thr: 0.4379 loss_db: 0.1046 2022/11/02 19:02:27 - mmengine - INFO - Epoch(train) [622][55/63] lr: 1.1217e-03 eta: 6:02:52 time: 0.5842 data_time: 0.0311 memory: 14901 loss: 1.1042 loss_prob: 0.5731 loss_thr: 0.4303 loss_db: 0.1008 2022/11/02 19:02:30 - mmengine - INFO - Epoch(train) [622][60/63] lr: 1.1217e-03 eta: 6:02:46 time: 0.5463 data_time: 0.0205 memory: 14901 loss: 1.1440 loss_prob: 0.5949 loss_thr: 0.4455 loss_db: 0.1036 2022/11/02 19:02:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:02:38 - mmengine - INFO - Epoch(train) [623][5/63] lr: 1.1200e-03 eta: 6:02:46 time: 0.9328 data_time: 0.2451 memory: 14901 loss: 1.2178 loss_prob: 0.6398 loss_thr: 0.4693 loss_db: 0.1088 2022/11/02 19:02:42 - mmengine - INFO - Epoch(train) [623][10/63] lr: 1.1200e-03 eta: 6:02:40 time: 1.0381 data_time: 0.2485 memory: 14901 loss: 1.2626 loss_prob: 0.6895 loss_thr: 0.4581 loss_db: 0.1149 2022/11/02 19:02:46 - mmengine - INFO - Epoch(train) [623][15/63] lr: 1.1200e-03 eta: 6:02:40 time: 0.7255 data_time: 0.0132 memory: 14901 loss: 1.2023 loss_prob: 0.6632 loss_thr: 0.4293 loss_db: 0.1098 2022/11/02 19:02:49 - mmengine - INFO - Epoch(train) [623][20/63] lr: 1.1200e-03 eta: 6:02:35 time: 0.6788 data_time: 0.0116 memory: 14901 loss: 1.1331 loss_prob: 0.6103 loss_thr: 0.4194 loss_db: 0.1033 2022/11/02 19:02:52 - mmengine - INFO - Epoch(train) [623][25/63] lr: 1.1200e-03 eta: 6:02:35 time: 0.6203 data_time: 0.0373 memory: 14901 loss: 1.1889 loss_prob: 0.6374 loss_thr: 0.4412 loss_db: 0.1103 2022/11/02 19:02:54 - mmengine - INFO - Epoch(train) [623][30/63] lr: 1.1200e-03 eta: 6:02:29 time: 0.5735 data_time: 0.0462 memory: 14901 loss: 1.2191 loss_prob: 0.6676 loss_thr: 0.4357 loss_db: 0.1158 2022/11/02 19:02:57 - mmengine - INFO - Epoch(train) [623][35/63] lr: 1.1200e-03 eta: 6:02:29 time: 0.5298 data_time: 0.0191 memory: 14901 loss: 1.2385 loss_prob: 0.6696 loss_thr: 0.4552 loss_db: 0.1138 2022/11/02 19:03:01 - mmengine - INFO - Epoch(train) [623][40/63] lr: 1.1200e-03 eta: 6:02:23 time: 0.6216 data_time: 0.0101 memory: 14901 loss: 1.2285 loss_prob: 0.6721 loss_thr: 0.4479 loss_db: 0.1084 2022/11/02 19:03:04 - mmengine - INFO - Epoch(train) [623][45/63] lr: 1.1200e-03 eta: 6:02:23 time: 0.6685 data_time: 0.0102 memory: 14901 loss: 1.2534 loss_prob: 0.7032 loss_thr: 0.4342 loss_db: 0.1160 2022/11/02 19:03:07 - mmengine - INFO - Epoch(train) [623][50/63] lr: 1.1200e-03 eta: 6:02:17 time: 0.6124 data_time: 0.0299 memory: 14901 loss: 1.4448 loss_prob: 0.8118 loss_thr: 0.4928 loss_db: 0.1403 2022/11/02 19:03:12 - mmengine - INFO - Epoch(train) [623][55/63] lr: 1.1200e-03 eta: 6:02:17 time: 0.7837 data_time: 0.0345 memory: 14901 loss: 1.4108 loss_prob: 0.7777 loss_thr: 0.5032 loss_db: 0.1299 2022/11/02 19:03:16 - mmengine - INFO - Epoch(train) [623][60/63] lr: 1.1200e-03 eta: 6:02:14 time: 0.8774 data_time: 0.0151 memory: 14901 loss: 1.3781 loss_prob: 0.7453 loss_thr: 0.5079 loss_db: 0.1249 2022/11/02 19:03:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:03:25 - mmengine - INFO - Epoch(train) [624][5/63] lr: 1.1182e-03 eta: 6:02:14 time: 1.0396 data_time: 0.2644 memory: 14901 loss: 1.3163 loss_prob: 0.7429 loss_thr: 0.4495 loss_db: 0.1239 2022/11/02 19:03:28 - mmengine - INFO - Epoch(train) [624][10/63] lr: 1.1182e-03 eta: 6:02:09 time: 1.0987 data_time: 0.2672 memory: 14901 loss: 1.3087 loss_prob: 0.7308 loss_thr: 0.4590 loss_db: 0.1190 2022/11/02 19:03:31 - mmengine - INFO - Epoch(train) [624][15/63] lr: 1.1182e-03 eta: 6:02:09 time: 0.6002 data_time: 0.0132 memory: 14901 loss: 1.2408 loss_prob: 0.6691 loss_thr: 0.4574 loss_db: 0.1142 2022/11/02 19:03:33 - mmengine - INFO - Epoch(train) [624][20/63] lr: 1.1182e-03 eta: 6:02:02 time: 0.5173 data_time: 0.0106 memory: 14901 loss: 1.2212 loss_prob: 0.6609 loss_thr: 0.4464 loss_db: 0.1138 2022/11/02 19:03:36 - mmengine - INFO - Epoch(train) [624][25/63] lr: 1.1182e-03 eta: 6:02:02 time: 0.4924 data_time: 0.0234 memory: 14901 loss: 1.1669 loss_prob: 0.6279 loss_thr: 0.4311 loss_db: 0.1079 2022/11/02 19:03:38 - mmengine - INFO - Epoch(train) [624][30/63] lr: 1.1182e-03 eta: 6:01:56 time: 0.5225 data_time: 0.0420 memory: 14901 loss: 1.1708 loss_prob: 0.6266 loss_thr: 0.4357 loss_db: 0.1085 2022/11/02 19:03:41 - mmengine - INFO - Epoch(train) [624][35/63] lr: 1.1182e-03 eta: 6:01:56 time: 0.5766 data_time: 0.0294 memory: 14901 loss: 1.2621 loss_prob: 0.6828 loss_thr: 0.4627 loss_db: 0.1166 2022/11/02 19:03:45 - mmengine - INFO - Epoch(train) [624][40/63] lr: 1.1182e-03 eta: 6:01:50 time: 0.6379 data_time: 0.0107 memory: 14901 loss: 1.2663 loss_prob: 0.6858 loss_thr: 0.4635 loss_db: 0.1170 2022/11/02 19:03:48 - mmengine - INFO - Epoch(train) [624][45/63] lr: 1.1182e-03 eta: 6:01:50 time: 0.6078 data_time: 0.0125 memory: 14901 loss: 1.2006 loss_prob: 0.6445 loss_thr: 0.4458 loss_db: 0.1102 2022/11/02 19:03:52 - mmengine - INFO - Epoch(train) [624][50/63] lr: 1.1182e-03 eta: 6:01:45 time: 0.7006 data_time: 0.0166 memory: 14901 loss: 1.2859 loss_prob: 0.6960 loss_thr: 0.4688 loss_db: 0.1211 2022/11/02 19:03:55 - mmengine - INFO - Epoch(train) [624][55/63] lr: 1.1182e-03 eta: 6:01:45 time: 0.7382 data_time: 0.0301 memory: 14901 loss: 1.3466 loss_prob: 0.7403 loss_thr: 0.4805 loss_db: 0.1258 2022/11/02 19:03:58 - mmengine - INFO - Epoch(train) [624][60/63] lr: 1.1182e-03 eta: 6:01:39 time: 0.6122 data_time: 0.0256 memory: 14901 loss: 1.2687 loss_prob: 0.6915 loss_thr: 0.4622 loss_db: 0.1149 2022/11/02 19:03:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:04:05 - mmengine - INFO - Epoch(train) [625][5/63] lr: 1.1165e-03 eta: 6:01:39 time: 0.8939 data_time: 0.2735 memory: 14901 loss: 1.2186 loss_prob: 0.6592 loss_thr: 0.4456 loss_db: 0.1138 2022/11/02 19:04:08 - mmengine - INFO - Epoch(train) [625][10/63] lr: 1.1165e-03 eta: 6:01:32 time: 0.8889 data_time: 0.2756 memory: 14901 loss: 1.2598 loss_prob: 0.6834 loss_thr: 0.4614 loss_db: 0.1149 2022/11/02 19:04:11 - mmengine - INFO - Epoch(train) [625][15/63] lr: 1.1165e-03 eta: 6:01:32 time: 0.5808 data_time: 0.0091 memory: 14901 loss: 1.2243 loss_prob: 0.6620 loss_thr: 0.4497 loss_db: 0.1126 2022/11/02 19:04:15 - mmengine - INFO - Epoch(train) [625][20/63] lr: 1.1165e-03 eta: 6:01:27 time: 0.6656 data_time: 0.0080 memory: 14901 loss: 1.2614 loss_prob: 0.6847 loss_thr: 0.4608 loss_db: 0.1159 2022/11/02 19:04:18 - mmengine - INFO - Epoch(train) [625][25/63] lr: 1.1165e-03 eta: 6:01:27 time: 0.6491 data_time: 0.0292 memory: 14901 loss: 1.2552 loss_prob: 0.6714 loss_thr: 0.4707 loss_db: 0.1131 2022/11/02 19:04:21 - mmengine - INFO - Epoch(train) [625][30/63] lr: 1.1165e-03 eta: 6:01:21 time: 0.6261 data_time: 0.0565 memory: 14901 loss: 1.1665 loss_prob: 0.6122 loss_thr: 0.4480 loss_db: 0.1063 2022/11/02 19:04:24 - mmengine - INFO - Epoch(train) [625][35/63] lr: 1.1165e-03 eta: 6:01:21 time: 0.6076 data_time: 0.0350 memory: 14901 loss: 1.2379 loss_prob: 0.6599 loss_thr: 0.4645 loss_db: 0.1135 2022/11/02 19:04:26 - mmengine - INFO - Epoch(train) [625][40/63] lr: 1.1165e-03 eta: 6:01:15 time: 0.5384 data_time: 0.0090 memory: 14901 loss: 1.2244 loss_prob: 0.6489 loss_thr: 0.4643 loss_db: 0.1112 2022/11/02 19:04:31 - mmengine - INFO - Epoch(train) [625][45/63] lr: 1.1165e-03 eta: 6:01:15 time: 0.6937 data_time: 0.0116 memory: 14901 loss: 1.1926 loss_prob: 0.6336 loss_thr: 0.4498 loss_db: 0.1092 2022/11/02 19:04:34 - mmengine - INFO - Epoch(train) [625][50/63] lr: 1.1165e-03 eta: 6:01:11 time: 0.8011 data_time: 0.0287 memory: 14901 loss: 1.1439 loss_prob: 0.6071 loss_thr: 0.4329 loss_db: 0.1040 2022/11/02 19:04:38 - mmengine - INFO - Epoch(train) [625][55/63] lr: 1.1165e-03 eta: 6:01:11 time: 0.7715 data_time: 0.0299 memory: 14901 loss: 1.0980 loss_prob: 0.5803 loss_thr: 0.4181 loss_db: 0.0996 2022/11/02 19:04:41 - mmengine - INFO - Epoch(train) [625][60/63] lr: 1.1165e-03 eta: 6:01:06 time: 0.6850 data_time: 0.0128 memory: 14901 loss: 1.1245 loss_prob: 0.6023 loss_thr: 0.4180 loss_db: 0.1043 2022/11/02 19:04:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:04:48 - mmengine - INFO - Epoch(train) [626][5/63] lr: 1.1147e-03 eta: 6:01:06 time: 0.8259 data_time: 0.2471 memory: 14901 loss: 1.0980 loss_prob: 0.5743 loss_thr: 0.4236 loss_db: 0.1000 2022/11/02 19:04:52 - mmengine - INFO - Epoch(train) [626][10/63] lr: 1.1147e-03 eta: 6:00:59 time: 0.9130 data_time: 0.2556 memory: 14901 loss: 1.1908 loss_prob: 0.6297 loss_thr: 0.4508 loss_db: 0.1102 2022/11/02 19:04:55 - mmengine - INFO - Epoch(train) [626][15/63] lr: 1.1147e-03 eta: 6:00:59 time: 0.6638 data_time: 0.0151 memory: 14901 loss: 1.2286 loss_prob: 0.6492 loss_thr: 0.4666 loss_db: 0.1129 2022/11/02 19:04:59 - mmengine - INFO - Epoch(train) [626][20/63] lr: 1.1147e-03 eta: 6:00:54 time: 0.6964 data_time: 0.0101 memory: 14901 loss: 1.1522 loss_prob: 0.6030 loss_thr: 0.4453 loss_db: 0.1039 2022/11/02 19:05:03 - mmengine - INFO - Epoch(train) [626][25/63] lr: 1.1147e-03 eta: 6:00:54 time: 0.8197 data_time: 0.0378 memory: 14901 loss: 1.1091 loss_prob: 0.5770 loss_thr: 0.4307 loss_db: 0.1014 2022/11/02 19:05:07 - mmengine - INFO - Epoch(train) [626][30/63] lr: 1.1147e-03 eta: 6:00:50 time: 0.8209 data_time: 0.0364 memory: 14901 loss: 1.1468 loss_prob: 0.6082 loss_thr: 0.4307 loss_db: 0.1078 2022/11/02 19:05:10 - mmengine - INFO - Epoch(train) [626][35/63] lr: 1.1147e-03 eta: 6:00:50 time: 0.6407 data_time: 0.0149 memory: 14901 loss: 1.1329 loss_prob: 0.6031 loss_thr: 0.4269 loss_db: 0.1029 2022/11/02 19:05:12 - mmengine - INFO - Epoch(train) [626][40/63] lr: 1.1147e-03 eta: 6:00:43 time: 0.5110 data_time: 0.0141 memory: 14901 loss: 1.1284 loss_prob: 0.5911 loss_thr: 0.4365 loss_db: 0.1007 2022/11/02 19:05:15 - mmengine - INFO - Epoch(train) [626][45/63] lr: 1.1147e-03 eta: 6:00:43 time: 0.4965 data_time: 0.0122 memory: 14901 loss: 1.1825 loss_prob: 0.6295 loss_thr: 0.4423 loss_db: 0.1106 2022/11/02 19:05:17 - mmengine - INFO - Epoch(train) [626][50/63] lr: 1.1147e-03 eta: 6:00:37 time: 0.5232 data_time: 0.0291 memory: 14901 loss: 1.1573 loss_prob: 0.6214 loss_thr: 0.4298 loss_db: 0.1061 2022/11/02 19:05:20 - mmengine - INFO - Epoch(train) [626][55/63] lr: 1.1147e-03 eta: 6:00:37 time: 0.5708 data_time: 0.0269 memory: 14901 loss: 1.1632 loss_prob: 0.6250 loss_thr: 0.4353 loss_db: 0.1030 2022/11/02 19:05:23 - mmengine - INFO - Epoch(train) [626][60/63] lr: 1.1147e-03 eta: 6:00:30 time: 0.5617 data_time: 0.0181 memory: 14901 loss: 1.2021 loss_prob: 0.6402 loss_thr: 0.4534 loss_db: 0.1085 2022/11/02 19:05:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:05:30 - mmengine - INFO - Epoch(train) [627][5/63] lr: 1.1130e-03 eta: 6:00:30 time: 0.7959 data_time: 0.2797 memory: 14901 loss: 1.1804 loss_prob: 0.6184 loss_thr: 0.4557 loss_db: 0.1063 2022/11/02 19:05:33 - mmengine - INFO - Epoch(train) [627][10/63] lr: 1.1130e-03 eta: 6:00:23 time: 0.8629 data_time: 0.2822 memory: 14901 loss: 1.3429 loss_prob: 0.7606 loss_thr: 0.4628 loss_db: 0.1195 2022/11/02 19:05:36 - mmengine - INFO - Epoch(train) [627][15/63] lr: 1.1130e-03 eta: 6:00:23 time: 0.5903 data_time: 0.0204 memory: 14901 loss: 1.3784 loss_prob: 0.7990 loss_thr: 0.4562 loss_db: 0.1232 2022/11/02 19:05:39 - mmengine - INFO - Epoch(train) [627][20/63] lr: 1.1130e-03 eta: 6:00:17 time: 0.5714 data_time: 0.0166 memory: 14901 loss: 1.2904 loss_prob: 0.7088 loss_thr: 0.4676 loss_db: 0.1140 2022/11/02 19:05:42 - mmengine - INFO - Epoch(train) [627][25/63] lr: 1.1130e-03 eta: 6:00:17 time: 0.5991 data_time: 0.0195 memory: 14901 loss: 1.3178 loss_prob: 0.7186 loss_thr: 0.4775 loss_db: 0.1217 2022/11/02 19:05:45 - mmengine - INFO - Epoch(train) [627][30/63] lr: 1.1130e-03 eta: 6:00:11 time: 0.6505 data_time: 0.0449 memory: 14901 loss: 1.2532 loss_prob: 0.6685 loss_thr: 0.4676 loss_db: 0.1171 2022/11/02 19:05:48 - mmengine - INFO - Epoch(train) [627][35/63] lr: 1.1130e-03 eta: 6:00:11 time: 0.6462 data_time: 0.0366 memory: 14901 loss: 1.1989 loss_prob: 0.6463 loss_thr: 0.4423 loss_db: 0.1103 2022/11/02 19:05:51 - mmengine - INFO - Epoch(train) [627][40/63] lr: 1.1130e-03 eta: 6:00:06 time: 0.6163 data_time: 0.0145 memory: 14901 loss: 1.1484 loss_prob: 0.6252 loss_thr: 0.4155 loss_db: 0.1077 2022/11/02 19:05:54 - mmengine - INFO - Epoch(train) [627][45/63] lr: 1.1130e-03 eta: 6:00:06 time: 0.5893 data_time: 0.0110 memory: 14901 loss: 1.1776 loss_prob: 0.6331 loss_thr: 0.4357 loss_db: 0.1087 2022/11/02 19:05:57 - mmengine - INFO - Epoch(train) [627][50/63] lr: 1.1130e-03 eta: 6:00:00 time: 0.5931 data_time: 0.0200 memory: 14901 loss: 1.2108 loss_prob: 0.6524 loss_thr: 0.4485 loss_db: 0.1098 2022/11/02 19:06:00 - mmengine - INFO - Epoch(train) [627][55/63] lr: 1.1130e-03 eta: 6:00:00 time: 0.5802 data_time: 0.0255 memory: 14901 loss: 1.2007 loss_prob: 0.6441 loss_thr: 0.4479 loss_db: 0.1087 2022/11/02 19:06:03 - mmengine - INFO - Epoch(train) [627][60/63] lr: 1.1130e-03 eta: 5:59:53 time: 0.5334 data_time: 0.0144 memory: 14901 loss: 1.1610 loss_prob: 0.6086 loss_thr: 0.4471 loss_db: 0.1053 2022/11/02 19:06:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:06:09 - mmengine - INFO - Epoch(train) [628][5/63] lr: 1.1112e-03 eta: 5:59:53 time: 0.7582 data_time: 0.2532 memory: 14901 loss: 1.1670 loss_prob: 0.6113 loss_thr: 0.4522 loss_db: 0.1036 2022/11/02 19:06:12 - mmengine - INFO - Epoch(train) [628][10/63] lr: 1.1112e-03 eta: 5:59:46 time: 0.8275 data_time: 0.2586 memory: 14901 loss: 1.1299 loss_prob: 0.5950 loss_thr: 0.4316 loss_db: 0.1033 2022/11/02 19:06:16 - mmengine - INFO - Epoch(train) [628][15/63] lr: 1.1112e-03 eta: 5:59:46 time: 0.6629 data_time: 0.0186 memory: 14901 loss: 1.2086 loss_prob: 0.6416 loss_thr: 0.4530 loss_db: 0.1140 2022/11/02 19:06:19 - mmengine - INFO - Epoch(train) [628][20/63] lr: 1.1112e-03 eta: 5:59:41 time: 0.7148 data_time: 0.0104 memory: 14901 loss: 1.1594 loss_prob: 0.6175 loss_thr: 0.4345 loss_db: 0.1073 2022/11/02 19:06:22 - mmengine - INFO - Epoch(train) [628][25/63] lr: 1.1112e-03 eta: 5:59:41 time: 0.6525 data_time: 0.0415 memory: 14901 loss: 1.1268 loss_prob: 0.5942 loss_thr: 0.4316 loss_db: 0.1010 2022/11/02 19:06:27 - mmengine - INFO - Epoch(train) [628][30/63] lr: 1.1112e-03 eta: 5:59:37 time: 0.7829 data_time: 0.0521 memory: 14901 loss: 1.1025 loss_prob: 0.5779 loss_thr: 0.4251 loss_db: 0.0995 2022/11/02 19:06:30 - mmengine - INFO - Epoch(train) [628][35/63] lr: 1.1112e-03 eta: 5:59:37 time: 0.7468 data_time: 0.0320 memory: 14901 loss: 1.0707 loss_prob: 0.5568 loss_thr: 0.4166 loss_db: 0.0973 2022/11/02 19:06:33 - mmengine - INFO - Epoch(train) [628][40/63] lr: 1.1112e-03 eta: 5:59:30 time: 0.5634 data_time: 0.0201 memory: 14901 loss: 1.1730 loss_prob: 0.6156 loss_thr: 0.4494 loss_db: 0.1081 2022/11/02 19:06:36 - mmengine - INFO - Epoch(train) [628][45/63] lr: 1.1112e-03 eta: 5:59:30 time: 0.5896 data_time: 0.0101 memory: 14901 loss: 1.1416 loss_prob: 0.6033 loss_thr: 0.4345 loss_db: 0.1039 2022/11/02 19:06:39 - mmengine - INFO - Epoch(train) [628][50/63] lr: 1.1112e-03 eta: 5:59:25 time: 0.6325 data_time: 0.0203 memory: 14901 loss: 1.1221 loss_prob: 0.5906 loss_thr: 0.4329 loss_db: 0.0986 2022/11/02 19:06:42 - mmengine - INFO - Epoch(train) [628][55/63] lr: 1.1112e-03 eta: 5:59:25 time: 0.6512 data_time: 0.0287 memory: 14901 loss: 1.1681 loss_prob: 0.6146 loss_thr: 0.4484 loss_db: 0.1051 2022/11/02 19:06:45 - mmengine - INFO - Epoch(train) [628][60/63] lr: 1.1112e-03 eta: 5:59:19 time: 0.6257 data_time: 0.0201 memory: 14901 loss: 1.1280 loss_prob: 0.5947 loss_thr: 0.4295 loss_db: 0.1037 2022/11/02 19:06:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:06:54 - mmengine - INFO - Epoch(train) [629][5/63] lr: 1.1095e-03 eta: 5:59:19 time: 0.9442 data_time: 0.2653 memory: 14901 loss: 1.1077 loss_prob: 0.5840 loss_thr: 0.4253 loss_db: 0.0984 2022/11/02 19:06:56 - mmengine - INFO - Epoch(train) [629][10/63] lr: 1.1095e-03 eta: 5:59:12 time: 0.9261 data_time: 0.2677 memory: 14901 loss: 1.1098 loss_prob: 0.5845 loss_thr: 0.4252 loss_db: 0.1000 2022/11/02 19:06:59 - mmengine - INFO - Epoch(train) [629][15/63] lr: 1.1095e-03 eta: 5:59:12 time: 0.5528 data_time: 0.0134 memory: 14901 loss: 1.1016 loss_prob: 0.5739 loss_thr: 0.4277 loss_db: 0.1000 2022/11/02 19:07:02 - mmengine - INFO - Epoch(train) [629][20/63] lr: 1.1095e-03 eta: 5:59:06 time: 0.5244 data_time: 0.0080 memory: 14901 loss: 1.0992 loss_prob: 0.5830 loss_thr: 0.4162 loss_db: 0.1000 2022/11/02 19:07:06 - mmengine - INFO - Epoch(train) [629][25/63] lr: 1.1095e-03 eta: 5:59:06 time: 0.6588 data_time: 0.0548 memory: 14901 loss: 1.1829 loss_prob: 0.6318 loss_thr: 0.4443 loss_db: 0.1068 2022/11/02 19:07:09 - mmengine - INFO - Epoch(train) [629][30/63] lr: 1.1095e-03 eta: 5:59:01 time: 0.7197 data_time: 0.0580 memory: 14901 loss: 1.2172 loss_prob: 0.6462 loss_thr: 0.4604 loss_db: 0.1106 2022/11/02 19:07:12 - mmengine - INFO - Epoch(train) [629][35/63] lr: 1.1095e-03 eta: 5:59:01 time: 0.6003 data_time: 0.0086 memory: 14901 loss: 1.1656 loss_prob: 0.6118 loss_thr: 0.4476 loss_db: 0.1061 2022/11/02 19:07:14 - mmengine - INFO - Epoch(train) [629][40/63] lr: 1.1095e-03 eta: 5:58:54 time: 0.5247 data_time: 0.0089 memory: 14901 loss: 1.2284 loss_prob: 0.6494 loss_thr: 0.4688 loss_db: 0.1101 2022/11/02 19:07:17 - mmengine - INFO - Epoch(train) [629][45/63] lr: 1.1095e-03 eta: 5:58:54 time: 0.5307 data_time: 0.0135 memory: 14901 loss: 1.2229 loss_prob: 0.6571 loss_thr: 0.4551 loss_db: 0.1108 2022/11/02 19:07:20 - mmengine - INFO - Epoch(train) [629][50/63] lr: 1.1095e-03 eta: 5:58:48 time: 0.5866 data_time: 0.0299 memory: 14901 loss: 1.1852 loss_prob: 0.6384 loss_thr: 0.4381 loss_db: 0.1087 2022/11/02 19:07:23 - mmengine - INFO - Epoch(train) [629][55/63] lr: 1.1095e-03 eta: 5:58:48 time: 0.6218 data_time: 0.0252 memory: 14901 loss: 1.1736 loss_prob: 0.6351 loss_thr: 0.4321 loss_db: 0.1064 2022/11/02 19:07:26 - mmengine - INFO - Epoch(train) [629][60/63] lr: 1.1095e-03 eta: 5:58:42 time: 0.5917 data_time: 0.0091 memory: 14901 loss: 1.1177 loss_prob: 0.5910 loss_thr: 0.4266 loss_db: 0.1002 2022/11/02 19:07:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:07:35 - mmengine - INFO - Epoch(train) [630][5/63] lr: 1.1077e-03 eta: 5:58:42 time: 0.9705 data_time: 0.2235 memory: 14901 loss: 1.1896 loss_prob: 0.6381 loss_thr: 0.4426 loss_db: 0.1089 2022/11/02 19:07:39 - mmengine - INFO - Epoch(train) [630][10/63] lr: 1.1077e-03 eta: 5:58:38 time: 1.1488 data_time: 0.2322 memory: 14901 loss: 1.1414 loss_prob: 0.6015 loss_thr: 0.4367 loss_db: 0.1031 2022/11/02 19:07:42 - mmengine - INFO - Epoch(train) [630][15/63] lr: 1.1077e-03 eta: 5:58:38 time: 0.7420 data_time: 0.0206 memory: 14901 loss: 1.1182 loss_prob: 0.5805 loss_thr: 0.4385 loss_db: 0.0992 2022/11/02 19:07:45 - mmengine - INFO - Epoch(train) [630][20/63] lr: 1.1077e-03 eta: 5:58:32 time: 0.6518 data_time: 0.0120 memory: 14901 loss: 1.0849 loss_prob: 0.5633 loss_thr: 0.4267 loss_db: 0.0948 2022/11/02 19:07:48 - mmengine - INFO - Epoch(train) [630][25/63] lr: 1.1077e-03 eta: 5:58:32 time: 0.6425 data_time: 0.0286 memory: 14901 loss: 1.1222 loss_prob: 0.5889 loss_thr: 0.4350 loss_db: 0.0983 2022/11/02 19:07:51 - mmengine - INFO - Epoch(train) [630][30/63] lr: 1.1077e-03 eta: 5:58:26 time: 0.5869 data_time: 0.0441 memory: 14901 loss: 1.1350 loss_prob: 0.5894 loss_thr: 0.4462 loss_db: 0.0994 2022/11/02 19:07:54 - mmengine - INFO - Epoch(train) [630][35/63] lr: 1.1077e-03 eta: 5:58:26 time: 0.5240 data_time: 0.0295 memory: 14901 loss: 1.0864 loss_prob: 0.5706 loss_thr: 0.4182 loss_db: 0.0975 2022/11/02 19:07:56 - mmengine - INFO - Epoch(train) [630][40/63] lr: 1.1077e-03 eta: 5:58:19 time: 0.5058 data_time: 0.0118 memory: 14901 loss: 1.1448 loss_prob: 0.6094 loss_thr: 0.4304 loss_db: 0.1050 2022/11/02 19:07:59 - mmengine - INFO - Epoch(train) [630][45/63] lr: 1.1077e-03 eta: 5:58:19 time: 0.5349 data_time: 0.0117 memory: 14901 loss: 1.1516 loss_prob: 0.6166 loss_thr: 0.4325 loss_db: 0.1025 2022/11/02 19:08:02 - mmengine - INFO - Epoch(train) [630][50/63] lr: 1.1077e-03 eta: 5:58:13 time: 0.5445 data_time: 0.0199 memory: 14901 loss: 1.0992 loss_prob: 0.5918 loss_thr: 0.4080 loss_db: 0.0995 2022/11/02 19:08:04 - mmengine - INFO - Epoch(train) [630][55/63] lr: 1.1077e-03 eta: 5:58:13 time: 0.5285 data_time: 0.0280 memory: 14901 loss: 1.0943 loss_prob: 0.5746 loss_thr: 0.4197 loss_db: 0.1000 2022/11/02 19:08:07 - mmengine - INFO - Epoch(train) [630][60/63] lr: 1.1077e-03 eta: 5:58:06 time: 0.5086 data_time: 0.0221 memory: 14901 loss: 1.1174 loss_prob: 0.5753 loss_thr: 0.4443 loss_db: 0.0979 2022/11/02 19:08:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:08:14 - mmengine - INFO - Epoch(train) [631][5/63] lr: 1.1060e-03 eta: 5:58:06 time: 0.7742 data_time: 0.2242 memory: 14901 loss: 1.1590 loss_prob: 0.6055 loss_thr: 0.4494 loss_db: 0.1041 2022/11/02 19:08:17 - mmengine - INFO - Epoch(train) [631][10/63] lr: 1.1060e-03 eta: 5:57:59 time: 0.9037 data_time: 0.2253 memory: 14901 loss: 1.0822 loss_prob: 0.5603 loss_thr: 0.4268 loss_db: 0.0951 2022/11/02 19:08:20 - mmengine - INFO - Epoch(train) [631][15/63] lr: 1.1060e-03 eta: 5:57:59 time: 0.6504 data_time: 0.0332 memory: 14901 loss: 1.0485 loss_prob: 0.5501 loss_thr: 0.4009 loss_db: 0.0975 2022/11/02 19:08:23 - mmengine - INFO - Epoch(train) [631][20/63] lr: 1.1060e-03 eta: 5:57:53 time: 0.5816 data_time: 0.0319 memory: 14901 loss: 1.4463 loss_prob: 0.8690 loss_thr: 0.4459 loss_db: 0.1314 2022/11/02 19:08:25 - mmengine - INFO - Epoch(train) [631][25/63] lr: 1.1060e-03 eta: 5:57:53 time: 0.5305 data_time: 0.0147 memory: 14901 loss: 1.5184 loss_prob: 0.9119 loss_thr: 0.4712 loss_db: 0.1353 2022/11/02 19:08:30 - mmengine - INFO - Epoch(train) [631][30/63] lr: 1.1060e-03 eta: 5:57:48 time: 0.6903 data_time: 0.0522 memory: 14901 loss: 1.2621 loss_prob: 0.6971 loss_thr: 0.4487 loss_db: 0.1163 2022/11/02 19:08:32 - mmengine - INFO - Epoch(train) [631][35/63] lr: 1.1060e-03 eta: 5:57:48 time: 0.6907 data_time: 0.0479 memory: 14901 loss: 1.2799 loss_prob: 0.7135 loss_thr: 0.4466 loss_db: 0.1198 2022/11/02 19:08:35 - mmengine - INFO - Epoch(train) [631][40/63] lr: 1.1060e-03 eta: 5:57:42 time: 0.5544 data_time: 0.0117 memory: 14901 loss: 1.2582 loss_prob: 0.6693 loss_thr: 0.4746 loss_db: 0.1143 2022/11/02 19:08:38 - mmengine - INFO - Epoch(train) [631][45/63] lr: 1.1060e-03 eta: 5:57:42 time: 0.6111 data_time: 0.0126 memory: 14901 loss: 1.2363 loss_prob: 0.6493 loss_thr: 0.4771 loss_db: 0.1100 2022/11/02 19:08:42 - mmengine - INFO - Epoch(train) [631][50/63] lr: 1.1060e-03 eta: 5:57:37 time: 0.6918 data_time: 0.0286 memory: 14901 loss: 1.1304 loss_prob: 0.5906 loss_thr: 0.4394 loss_db: 0.1005 2022/11/02 19:08:45 - mmengine - INFO - Epoch(train) [631][55/63] lr: 1.1060e-03 eta: 5:57:37 time: 0.6462 data_time: 0.0272 memory: 14901 loss: 1.2045 loss_prob: 0.6380 loss_thr: 0.4592 loss_db: 0.1073 2022/11/02 19:08:48 - mmengine - INFO - Epoch(train) [631][60/63] lr: 1.1060e-03 eta: 5:57:31 time: 0.6030 data_time: 0.0122 memory: 14901 loss: 1.2738 loss_prob: 0.6820 loss_thr: 0.4751 loss_db: 0.1167 2022/11/02 19:08:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:08:57 - mmengine - INFO - Epoch(train) [632][5/63] lr: 1.1042e-03 eta: 5:57:31 time: 1.0655 data_time: 0.2562 memory: 14901 loss: 1.3144 loss_prob: 0.7063 loss_thr: 0.4887 loss_db: 0.1194 2022/11/02 19:09:01 - mmengine - INFO - Epoch(train) [632][10/63] lr: 1.1042e-03 eta: 5:57:25 time: 0.9680 data_time: 0.2654 memory: 14901 loss: 1.2540 loss_prob: 0.6752 loss_thr: 0.4667 loss_db: 0.1121 2022/11/02 19:09:03 - mmengine - INFO - Epoch(train) [632][15/63] lr: 1.1042e-03 eta: 5:57:25 time: 0.5885 data_time: 0.0222 memory: 14901 loss: 1.2251 loss_prob: 0.6578 loss_thr: 0.4564 loss_db: 0.1109 2022/11/02 19:09:06 - mmengine - INFO - Epoch(train) [632][20/63] lr: 1.1042e-03 eta: 5:57:18 time: 0.5512 data_time: 0.0111 memory: 14901 loss: 1.2285 loss_prob: 0.6557 loss_thr: 0.4603 loss_db: 0.1125 2022/11/02 19:09:09 - mmengine - INFO - Epoch(train) [632][25/63] lr: 1.1042e-03 eta: 5:57:18 time: 0.5577 data_time: 0.0192 memory: 14901 loss: 1.1825 loss_prob: 0.6243 loss_thr: 0.4503 loss_db: 0.1079 2022/11/02 19:09:12 - mmengine - INFO - Epoch(train) [632][30/63] lr: 1.1042e-03 eta: 5:57:12 time: 0.5741 data_time: 0.0442 memory: 14901 loss: 1.1719 loss_prob: 0.6153 loss_thr: 0.4512 loss_db: 0.1053 2022/11/02 19:09:15 - mmengine - INFO - Epoch(train) [632][35/63] lr: 1.1042e-03 eta: 5:57:12 time: 0.5711 data_time: 0.0420 memory: 14901 loss: 1.1290 loss_prob: 0.5897 loss_thr: 0.4367 loss_db: 0.1026 2022/11/02 19:09:17 - mmengine - INFO - Epoch(train) [632][40/63] lr: 1.1042e-03 eta: 5:57:05 time: 0.5261 data_time: 0.0164 memory: 14901 loss: 1.0873 loss_prob: 0.5680 loss_thr: 0.4209 loss_db: 0.0984 2022/11/02 19:09:20 - mmengine - INFO - Epoch(train) [632][45/63] lr: 1.1042e-03 eta: 5:57:05 time: 0.5484 data_time: 0.0093 memory: 14901 loss: 1.1888 loss_prob: 0.6359 loss_thr: 0.4436 loss_db: 0.1093 2022/11/02 19:09:23 - mmengine - INFO - Epoch(train) [632][50/63] lr: 1.1042e-03 eta: 5:56:59 time: 0.5935 data_time: 0.0135 memory: 14901 loss: 1.2359 loss_prob: 0.6711 loss_thr: 0.4490 loss_db: 0.1158 2022/11/02 19:09:26 - mmengine - INFO - Epoch(train) [632][55/63] lr: 1.1042e-03 eta: 5:56:59 time: 0.5679 data_time: 0.0267 memory: 14901 loss: 1.1304 loss_prob: 0.5961 loss_thr: 0.4307 loss_db: 0.1036 2022/11/02 19:09:29 - mmengine - INFO - Epoch(train) [632][60/63] lr: 1.1042e-03 eta: 5:56:53 time: 0.5675 data_time: 0.0312 memory: 14901 loss: 1.1012 loss_prob: 0.5778 loss_thr: 0.4224 loss_db: 0.1011 2022/11/02 19:09:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:09:36 - mmengine - INFO - Epoch(train) [633][5/63] lr: 1.1025e-03 eta: 5:56:53 time: 0.8112 data_time: 0.2636 memory: 14901 loss: 1.1132 loss_prob: 0.5815 loss_thr: 0.4323 loss_db: 0.0994 2022/11/02 19:09:39 - mmengine - INFO - Epoch(train) [633][10/63] lr: 1.1025e-03 eta: 5:56:46 time: 0.8781 data_time: 0.2636 memory: 14901 loss: 1.2112 loss_prob: 0.6541 loss_thr: 0.4468 loss_db: 0.1103 2022/11/02 19:09:42 - mmengine - INFO - Epoch(train) [633][15/63] lr: 1.1025e-03 eta: 5:56:46 time: 0.6737 data_time: 0.0112 memory: 14901 loss: 1.2282 loss_prob: 0.6649 loss_thr: 0.4496 loss_db: 0.1137 2022/11/02 19:09:46 - mmengine - INFO - Epoch(train) [633][20/63] lr: 1.1025e-03 eta: 5:56:41 time: 0.7060 data_time: 0.0088 memory: 14901 loss: 1.0775 loss_prob: 0.5637 loss_thr: 0.4166 loss_db: 0.0972 2022/11/02 19:09:50 - mmengine - INFO - Epoch(train) [633][25/63] lr: 1.1025e-03 eta: 5:56:41 time: 0.7679 data_time: 0.0174 memory: 14901 loss: 1.0579 loss_prob: 0.5529 loss_thr: 0.4109 loss_db: 0.0941 2022/11/02 19:09:53 - mmengine - INFO - Epoch(train) [633][30/63] lr: 1.1025e-03 eta: 5:56:36 time: 0.7098 data_time: 0.0390 memory: 14901 loss: 1.1760 loss_prob: 0.6257 loss_thr: 0.4462 loss_db: 0.1041 2022/11/02 19:09:56 - mmengine - INFO - Epoch(train) [633][35/63] lr: 1.1025e-03 eta: 5:56:36 time: 0.5966 data_time: 0.0312 memory: 14901 loss: 1.1910 loss_prob: 0.6392 loss_thr: 0.4420 loss_db: 0.1098 2022/11/02 19:09:59 - mmengine - INFO - Epoch(train) [633][40/63] lr: 1.1025e-03 eta: 5:56:30 time: 0.6052 data_time: 0.0170 memory: 14901 loss: 1.1313 loss_prob: 0.5985 loss_thr: 0.4273 loss_db: 0.1055 2022/11/02 19:10:03 - mmengine - INFO - Epoch(train) [633][45/63] lr: 1.1025e-03 eta: 5:56:30 time: 0.7360 data_time: 0.0170 memory: 14901 loss: 1.1708 loss_prob: 0.6142 loss_thr: 0.4506 loss_db: 0.1061 2022/11/02 19:10:07 - mmengine - INFO - Epoch(train) [633][50/63] lr: 1.1025e-03 eta: 5:56:26 time: 0.7853 data_time: 0.0314 memory: 14901 loss: 1.1854 loss_prob: 0.6210 loss_thr: 0.4575 loss_db: 0.1068 2022/11/02 19:10:10 - mmengine - INFO - Epoch(train) [633][55/63] lr: 1.1025e-03 eta: 5:56:26 time: 0.6143 data_time: 0.0314 memory: 14901 loss: 1.2369 loss_prob: 0.6616 loss_thr: 0.4608 loss_db: 0.1145 2022/11/02 19:10:12 - mmengine - INFO - Epoch(train) [633][60/63] lr: 1.1025e-03 eta: 5:56:19 time: 0.5513 data_time: 0.0148 memory: 14901 loss: 1.2025 loss_prob: 0.6467 loss_thr: 0.4451 loss_db: 0.1107 2022/11/02 19:10:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:10:19 - mmengine - INFO - Epoch(train) [634][5/63] lr: 1.1007e-03 eta: 5:56:19 time: 0.8276 data_time: 0.2748 memory: 14901 loss: 1.3236 loss_prob: 0.7284 loss_thr: 0.4769 loss_db: 0.1183 2022/11/02 19:10:22 - mmengine - INFO - Epoch(train) [634][10/63] lr: 1.1007e-03 eta: 5:56:12 time: 0.8059 data_time: 0.2715 memory: 14901 loss: 1.2574 loss_prob: 0.6897 loss_thr: 0.4526 loss_db: 0.1152 2022/11/02 19:10:25 - mmengine - INFO - Epoch(train) [634][15/63] lr: 1.1007e-03 eta: 5:56:12 time: 0.5387 data_time: 0.0127 memory: 14901 loss: 1.0667 loss_prob: 0.5632 loss_thr: 0.4060 loss_db: 0.0975 2022/11/02 19:10:27 - mmengine - INFO - Epoch(train) [634][20/63] lr: 1.1007e-03 eta: 5:56:05 time: 0.5196 data_time: 0.0125 memory: 14901 loss: 1.1188 loss_prob: 0.5926 loss_thr: 0.4255 loss_db: 0.1006 2022/11/02 19:10:31 - mmengine - INFO - Epoch(train) [634][25/63] lr: 1.1007e-03 eta: 5:56:05 time: 0.6358 data_time: 0.0237 memory: 14901 loss: 1.0587 loss_prob: 0.5489 loss_thr: 0.4116 loss_db: 0.0982 2022/11/02 19:10:35 - mmengine - INFO - Epoch(train) [634][30/63] lr: 1.1007e-03 eta: 5:56:00 time: 0.7185 data_time: 0.0455 memory: 14901 loss: 1.0711 loss_prob: 0.5577 loss_thr: 0.4142 loss_db: 0.0992 2022/11/02 19:10:37 - mmengine - INFO - Epoch(train) [634][35/63] lr: 1.1007e-03 eta: 5:56:00 time: 0.6009 data_time: 0.0334 memory: 14901 loss: 1.1597 loss_prob: 0.6191 loss_thr: 0.4368 loss_db: 0.1038 2022/11/02 19:10:40 - mmengine - INFO - Epoch(train) [634][40/63] lr: 1.1007e-03 eta: 5:55:54 time: 0.5603 data_time: 0.0108 memory: 14901 loss: 1.1901 loss_prob: 0.6342 loss_thr: 0.4488 loss_db: 0.1071 2022/11/02 19:10:43 - mmengine - INFO - Epoch(train) [634][45/63] lr: 1.1007e-03 eta: 5:55:54 time: 0.5507 data_time: 0.0074 memory: 14901 loss: 1.1328 loss_prob: 0.5902 loss_thr: 0.4392 loss_db: 0.1034 2022/11/02 19:10:45 - mmengine - INFO - Epoch(train) [634][50/63] lr: 1.1007e-03 eta: 5:55:47 time: 0.5177 data_time: 0.0212 memory: 14901 loss: 1.1401 loss_prob: 0.6099 loss_thr: 0.4259 loss_db: 0.1044 2022/11/02 19:10:48 - mmengine - INFO - Epoch(train) [634][55/63] lr: 1.1007e-03 eta: 5:55:47 time: 0.5401 data_time: 0.0320 memory: 14901 loss: 1.2303 loss_prob: 0.6742 loss_thr: 0.4451 loss_db: 0.1111 2022/11/02 19:10:51 - mmengine - INFO - Epoch(train) [634][60/63] lr: 1.1007e-03 eta: 5:55:41 time: 0.5467 data_time: 0.0184 memory: 14901 loss: 1.1534 loss_prob: 0.6095 loss_thr: 0.4405 loss_db: 0.1033 2022/11/02 19:10:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:10:58 - mmengine - INFO - Epoch(train) [635][5/63] lr: 1.0990e-03 eta: 5:55:41 time: 0.7711 data_time: 0.2343 memory: 14901 loss: 1.1049 loss_prob: 0.5828 loss_thr: 0.4215 loss_db: 0.1006 2022/11/02 19:11:00 - mmengine - INFO - Epoch(train) [635][10/63] lr: 1.0990e-03 eta: 5:55:33 time: 0.8028 data_time: 0.2312 memory: 14901 loss: 1.4717 loss_prob: 0.8349 loss_thr: 0.4933 loss_db: 0.1436 2022/11/02 19:11:03 - mmengine - INFO - Epoch(train) [635][15/63] lr: 1.0990e-03 eta: 5:55:33 time: 0.5429 data_time: 0.0101 memory: 14901 loss: 1.4857 loss_prob: 0.8324 loss_thr: 0.5075 loss_db: 0.1457 2022/11/02 19:11:06 - mmengine - INFO - Epoch(train) [635][20/63] lr: 1.0990e-03 eta: 5:55:27 time: 0.5616 data_time: 0.0144 memory: 14901 loss: 1.1729 loss_prob: 0.6172 loss_thr: 0.4511 loss_db: 0.1047 2022/11/02 19:11:10 - mmengine - INFO - Epoch(train) [635][25/63] lr: 1.0990e-03 eta: 5:55:27 time: 0.6857 data_time: 0.0382 memory: 14901 loss: 1.1923 loss_prob: 0.6450 loss_thr: 0.4381 loss_db: 0.1092 2022/11/02 19:11:13 - mmengine - INFO - Epoch(train) [635][30/63] lr: 1.0990e-03 eta: 5:55:22 time: 0.6945 data_time: 0.0436 memory: 14901 loss: 1.2395 loss_prob: 0.6701 loss_thr: 0.4532 loss_db: 0.1163 2022/11/02 19:11:17 - mmengine - INFO - Epoch(train) [635][35/63] lr: 1.0990e-03 eta: 5:55:22 time: 0.6978 data_time: 0.0218 memory: 14901 loss: 1.2593 loss_prob: 0.6797 loss_thr: 0.4622 loss_db: 0.1174 2022/11/02 19:11:20 - mmengine - INFO - Epoch(train) [635][40/63] lr: 1.0990e-03 eta: 5:55:17 time: 0.6979 data_time: 0.0140 memory: 14901 loss: 1.1805 loss_prob: 0.6330 loss_thr: 0.4382 loss_db: 0.1094 2022/11/02 19:11:23 - mmengine - INFO - Epoch(train) [635][45/63] lr: 1.0990e-03 eta: 5:55:17 time: 0.6358 data_time: 0.0128 memory: 14901 loss: 1.1054 loss_prob: 0.5795 loss_thr: 0.4247 loss_db: 0.1012 2022/11/02 19:11:27 - mmengine - INFO - Epoch(train) [635][50/63] lr: 1.0990e-03 eta: 5:55:12 time: 0.6871 data_time: 0.0231 memory: 14901 loss: 1.1035 loss_prob: 0.5789 loss_thr: 0.4242 loss_db: 0.1004 2022/11/02 19:11:30 - mmengine - INFO - Epoch(train) [635][55/63] lr: 1.0990e-03 eta: 5:55:12 time: 0.6955 data_time: 0.0289 memory: 14901 loss: 1.1041 loss_prob: 0.5830 loss_thr: 0.4197 loss_db: 0.1014 2022/11/02 19:11:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:11:33 - mmengine - INFO - Epoch(train) [635][60/63] lr: 1.0990e-03 eta: 5:55:06 time: 0.6521 data_time: 0.0195 memory: 14901 loss: 1.1998 loss_prob: 0.6569 loss_thr: 0.4356 loss_db: 0.1072 2022/11/02 19:11:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:11:41 - mmengine - INFO - Epoch(train) [636][5/63] lr: 1.0972e-03 eta: 5:55:06 time: 0.8919 data_time: 0.2294 memory: 14901 loss: 1.3126 loss_prob: 0.7303 loss_thr: 0.4628 loss_db: 0.1196 2022/11/02 19:11:43 - mmengine - INFO - Epoch(train) [636][10/63] lr: 1.0972e-03 eta: 5:54:59 time: 0.8234 data_time: 0.2283 memory: 14901 loss: 1.1398 loss_prob: 0.6067 loss_thr: 0.4257 loss_db: 0.1074 2022/11/02 19:11:46 - mmengine - INFO - Epoch(train) [636][15/63] lr: 1.0972e-03 eta: 5:54:59 time: 0.5120 data_time: 0.0093 memory: 14901 loss: 1.1501 loss_prob: 0.6064 loss_thr: 0.4384 loss_db: 0.1054 2022/11/02 19:11:49 - mmengine - INFO - Epoch(train) [636][20/63] lr: 1.0972e-03 eta: 5:54:53 time: 0.5852 data_time: 0.0089 memory: 14901 loss: 1.1662 loss_prob: 0.6255 loss_thr: 0.4349 loss_db: 0.1058 2022/11/02 19:11:52 - mmengine - INFO - Epoch(train) [636][25/63] lr: 1.0972e-03 eta: 5:54:53 time: 0.6168 data_time: 0.0130 memory: 14901 loss: 1.1572 loss_prob: 0.6173 loss_thr: 0.4328 loss_db: 0.1071 2022/11/02 19:11:55 - mmengine - INFO - Epoch(train) [636][30/63] lr: 1.0972e-03 eta: 5:54:46 time: 0.5783 data_time: 0.0466 memory: 14901 loss: 1.2030 loss_prob: 0.6293 loss_thr: 0.4639 loss_db: 0.1098 2022/11/02 19:11:57 - mmengine - INFO - Epoch(train) [636][35/63] lr: 1.0972e-03 eta: 5:54:46 time: 0.5253 data_time: 0.0427 memory: 14901 loss: 1.1622 loss_prob: 0.6060 loss_thr: 0.4522 loss_db: 0.1040 2022/11/02 19:12:00 - mmengine - INFO - Epoch(train) [636][40/63] lr: 1.0972e-03 eta: 5:54:40 time: 0.5100 data_time: 0.0081 memory: 14901 loss: 1.1331 loss_prob: 0.5921 loss_thr: 0.4399 loss_db: 0.1011 2022/11/02 19:12:03 - mmengine - INFO - Epoch(train) [636][45/63] lr: 1.0972e-03 eta: 5:54:40 time: 0.5429 data_time: 0.0107 memory: 14901 loss: 1.1707 loss_prob: 0.6147 loss_thr: 0.4502 loss_db: 0.1058 2022/11/02 19:12:06 - mmengine - INFO - Epoch(train) [636][50/63] lr: 1.0972e-03 eta: 5:54:33 time: 0.5690 data_time: 0.0203 memory: 14901 loss: 1.1742 loss_prob: 0.6227 loss_thr: 0.4439 loss_db: 0.1075 2022/11/02 19:12:09 - mmengine - INFO - Epoch(train) [636][55/63] lr: 1.0972e-03 eta: 5:54:33 time: 0.6030 data_time: 0.0315 memory: 14901 loss: 1.1398 loss_prob: 0.5943 loss_thr: 0.4442 loss_db: 0.1013 2022/11/02 19:12:11 - mmengine - INFO - Epoch(train) [636][60/63] lr: 1.0972e-03 eta: 5:54:27 time: 0.5578 data_time: 0.0229 memory: 14901 loss: 1.1571 loss_prob: 0.6201 loss_thr: 0.4356 loss_db: 0.1013 2022/11/02 19:12:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:12:19 - mmengine - INFO - Epoch(train) [637][5/63] lr: 1.0955e-03 eta: 5:54:27 time: 0.8670 data_time: 0.2648 memory: 14901 loss: 1.1656 loss_prob: 0.6410 loss_thr: 0.4168 loss_db: 0.1077 2022/11/02 19:12:22 - mmengine - INFO - Epoch(train) [637][10/63] lr: 1.0955e-03 eta: 5:54:21 time: 0.9471 data_time: 0.2672 memory: 14901 loss: 1.1468 loss_prob: 0.6111 loss_thr: 0.4292 loss_db: 0.1065 2022/11/02 19:12:25 - mmengine - INFO - Epoch(train) [637][15/63] lr: 1.0955e-03 eta: 5:54:21 time: 0.6580 data_time: 0.0101 memory: 14901 loss: 1.1511 loss_prob: 0.6104 loss_thr: 0.4363 loss_db: 0.1044 2022/11/02 19:12:28 - mmengine - INFO - Epoch(train) [637][20/63] lr: 1.0955e-03 eta: 5:54:15 time: 0.5862 data_time: 0.0098 memory: 14901 loss: 1.1998 loss_prob: 0.6400 loss_thr: 0.4484 loss_db: 0.1115 2022/11/02 19:12:32 - mmengine - INFO - Epoch(train) [637][25/63] lr: 1.0955e-03 eta: 5:54:15 time: 0.6900 data_time: 0.0358 memory: 14901 loss: 1.1674 loss_prob: 0.6224 loss_thr: 0.4382 loss_db: 0.1068 2022/11/02 19:12:36 - mmengine - INFO - Epoch(train) [637][30/63] lr: 1.0955e-03 eta: 5:54:11 time: 0.8204 data_time: 0.0540 memory: 14901 loss: 1.1833 loss_prob: 0.6372 loss_thr: 0.4402 loss_db: 0.1058 2022/11/02 19:12:40 - mmengine - INFO - Epoch(train) [637][35/63] lr: 1.0955e-03 eta: 5:54:11 time: 0.7316 data_time: 0.0319 memory: 14901 loss: 1.2808 loss_prob: 0.7003 loss_thr: 0.4624 loss_db: 0.1181 2022/11/02 19:12:42 - mmengine - INFO - Epoch(train) [637][40/63] lr: 1.0955e-03 eta: 5:54:05 time: 0.6118 data_time: 0.0135 memory: 14901 loss: 1.1525 loss_prob: 0.6169 loss_thr: 0.4296 loss_db: 0.1060 2022/11/02 19:12:45 - mmengine - INFO - Epoch(train) [637][45/63] lr: 1.0955e-03 eta: 5:54:05 time: 0.5350 data_time: 0.0103 memory: 14901 loss: 1.0817 loss_prob: 0.5646 loss_thr: 0.4192 loss_db: 0.0980 2022/11/02 19:12:49 - mmengine - INFO - Epoch(train) [637][50/63] lr: 1.0955e-03 eta: 5:54:00 time: 0.6942 data_time: 0.0258 memory: 14901 loss: 1.1852 loss_prob: 0.6198 loss_thr: 0.4585 loss_db: 0.1069 2022/11/02 19:12:52 - mmengine - INFO - Epoch(train) [637][55/63] lr: 1.0955e-03 eta: 5:54:00 time: 0.7240 data_time: 0.0256 memory: 14901 loss: 1.1930 loss_prob: 0.6256 loss_thr: 0.4618 loss_db: 0.1057 2022/11/02 19:12:55 - mmengine - INFO - Epoch(train) [637][60/63] lr: 1.0955e-03 eta: 5:53:53 time: 0.5695 data_time: 0.0113 memory: 14901 loss: 1.3940 loss_prob: 0.7808 loss_thr: 0.4891 loss_db: 0.1240 2022/11/02 19:12:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:13:04 - mmengine - INFO - Epoch(train) [638][5/63] lr: 1.0937e-03 eta: 5:53:53 time: 0.9868 data_time: 0.2413 memory: 14901 loss: 1.3270 loss_prob: 0.7479 loss_thr: 0.4588 loss_db: 0.1202 2022/11/02 19:13:07 - mmengine - INFO - Epoch(train) [638][10/63] lr: 1.0937e-03 eta: 5:53:48 time: 1.0249 data_time: 0.2414 memory: 14901 loss: 1.1089 loss_prob: 0.5909 loss_thr: 0.4177 loss_db: 0.1003 2022/11/02 19:13:10 - mmengine - INFO - Epoch(train) [638][15/63] lr: 1.0937e-03 eta: 5:53:48 time: 0.6132 data_time: 0.0104 memory: 14901 loss: 1.1198 loss_prob: 0.5904 loss_thr: 0.4287 loss_db: 0.1007 2022/11/02 19:13:12 - mmengine - INFO - Epoch(train) [638][20/63] lr: 1.0937e-03 eta: 5:53:41 time: 0.5460 data_time: 0.0107 memory: 14901 loss: 1.1391 loss_prob: 0.5968 loss_thr: 0.4409 loss_db: 0.1014 2022/11/02 19:13:15 - mmengine - INFO - Epoch(train) [638][25/63] lr: 1.0937e-03 eta: 5:53:41 time: 0.5193 data_time: 0.0165 memory: 14901 loss: 1.1548 loss_prob: 0.6065 loss_thr: 0.4439 loss_db: 0.1044 2022/11/02 19:13:19 - mmengine - INFO - Epoch(train) [638][30/63] lr: 1.0937e-03 eta: 5:53:36 time: 0.6809 data_time: 0.0528 memory: 14901 loss: 1.1702 loss_prob: 0.6207 loss_thr: 0.4431 loss_db: 0.1063 2022/11/02 19:13:22 - mmengine - INFO - Epoch(train) [638][35/63] lr: 1.0937e-03 eta: 5:53:36 time: 0.7202 data_time: 0.0477 memory: 14901 loss: 1.1767 loss_prob: 0.6230 loss_thr: 0.4481 loss_db: 0.1056 2022/11/02 19:13:25 - mmengine - INFO - Epoch(train) [638][40/63] lr: 1.0937e-03 eta: 5:53:30 time: 0.6067 data_time: 0.0151 memory: 14901 loss: 1.1811 loss_prob: 0.6235 loss_thr: 0.4505 loss_db: 0.1072 2022/11/02 19:13:28 - mmengine - INFO - Epoch(train) [638][45/63] lr: 1.0937e-03 eta: 5:53:30 time: 0.5857 data_time: 0.0138 memory: 14901 loss: 1.1568 loss_prob: 0.6141 loss_thr: 0.4384 loss_db: 0.1043 2022/11/02 19:13:31 - mmengine - INFO - Epoch(train) [638][50/63] lr: 1.0937e-03 eta: 5:53:24 time: 0.5667 data_time: 0.0280 memory: 14901 loss: 1.1829 loss_prob: 0.6401 loss_thr: 0.4359 loss_db: 0.1068 2022/11/02 19:13:34 - mmengine - INFO - Epoch(train) [638][55/63] lr: 1.0937e-03 eta: 5:53:24 time: 0.5811 data_time: 0.0291 memory: 14901 loss: 1.1247 loss_prob: 0.5994 loss_thr: 0.4232 loss_db: 0.1021 2022/11/02 19:13:39 - mmengine - INFO - Epoch(train) [638][60/63] lr: 1.0937e-03 eta: 5:53:20 time: 0.8066 data_time: 0.0114 memory: 14901 loss: 1.1516 loss_prob: 0.6125 loss_thr: 0.4334 loss_db: 0.1057 2022/11/02 19:13:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:13:47 - mmengine - INFO - Epoch(train) [639][5/63] lr: 1.0920e-03 eta: 5:53:20 time: 1.0016 data_time: 0.2478 memory: 14901 loss: 1.0476 loss_prob: 0.5495 loss_thr: 0.4018 loss_db: 0.0963 2022/11/02 19:13:50 - mmengine - INFO - Epoch(train) [639][10/63] lr: 1.0920e-03 eta: 5:53:14 time: 0.9553 data_time: 0.2527 memory: 14901 loss: 1.1342 loss_prob: 0.6086 loss_thr: 0.4228 loss_db: 0.1028 2022/11/02 19:13:54 - mmengine - INFO - Epoch(train) [639][15/63] lr: 1.0920e-03 eta: 5:53:14 time: 0.7227 data_time: 0.0217 memory: 14901 loss: 1.2641 loss_prob: 0.6929 loss_thr: 0.4585 loss_db: 0.1127 2022/11/02 19:13:57 - mmengine - INFO - Epoch(train) [639][20/63] lr: 1.0920e-03 eta: 5:53:08 time: 0.6696 data_time: 0.0194 memory: 14901 loss: 1.1872 loss_prob: 0.6296 loss_thr: 0.4521 loss_db: 0.1055 2022/11/02 19:14:01 - mmengine - INFO - Epoch(train) [639][25/63] lr: 1.0920e-03 eta: 5:53:08 time: 0.6743 data_time: 0.0163 memory: 14901 loss: 1.1251 loss_prob: 0.5836 loss_thr: 0.4395 loss_db: 0.1020 2022/11/02 19:14:04 - mmengine - INFO - Epoch(train) [639][30/63] lr: 1.0920e-03 eta: 5:53:03 time: 0.6778 data_time: 0.0351 memory: 14901 loss: 1.1514 loss_prob: 0.6103 loss_thr: 0.4337 loss_db: 0.1075 2022/11/02 19:14:07 - mmengine - INFO - Epoch(train) [639][35/63] lr: 1.0920e-03 eta: 5:53:03 time: 0.5756 data_time: 0.0377 memory: 14901 loss: 1.1602 loss_prob: 0.6197 loss_thr: 0.4343 loss_db: 0.1062 2022/11/02 19:14:10 - mmengine - INFO - Epoch(train) [639][40/63] lr: 1.0920e-03 eta: 5:52:57 time: 0.5842 data_time: 0.0264 memory: 14901 loss: 1.1129 loss_prob: 0.5908 loss_thr: 0.4207 loss_db: 0.1013 2022/11/02 19:14:14 - mmengine - INFO - Epoch(train) [639][45/63] lr: 1.0920e-03 eta: 5:52:57 time: 0.6900 data_time: 0.0213 memory: 14901 loss: 1.1089 loss_prob: 0.5841 loss_thr: 0.4214 loss_db: 0.1034 2022/11/02 19:14:17 - mmengine - INFO - Epoch(train) [639][50/63] lr: 1.0920e-03 eta: 5:52:52 time: 0.7434 data_time: 0.0168 memory: 14901 loss: 1.1403 loss_prob: 0.6013 loss_thr: 0.4348 loss_db: 0.1042 2022/11/02 19:14:21 - mmengine - INFO - Epoch(train) [639][55/63] lr: 1.0920e-03 eta: 5:52:52 time: 0.7805 data_time: 0.0240 memory: 14901 loss: 1.1113 loss_prob: 0.5863 loss_thr: 0.4243 loss_db: 0.1006 2022/11/02 19:14:25 - mmengine - INFO - Epoch(train) [639][60/63] lr: 1.0920e-03 eta: 5:52:47 time: 0.7301 data_time: 0.0201 memory: 14901 loss: 1.1238 loss_prob: 0.6040 loss_thr: 0.4149 loss_db: 0.1050 2022/11/02 19:14:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:14:33 - mmengine - INFO - Epoch(train) [640][5/63] lr: 1.0902e-03 eta: 5:52:47 time: 0.9755 data_time: 0.2766 memory: 14901 loss: 1.1626 loss_prob: 0.6371 loss_thr: 0.4199 loss_db: 0.1056 2022/11/02 19:14:36 - mmengine - INFO - Epoch(train) [640][10/63] lr: 1.0902e-03 eta: 5:52:41 time: 0.9818 data_time: 0.2762 memory: 14901 loss: 1.1645 loss_prob: 0.6330 loss_thr: 0.4282 loss_db: 0.1032 2022/11/02 19:14:38 - mmengine - INFO - Epoch(train) [640][15/63] lr: 1.0902e-03 eta: 5:52:41 time: 0.5013 data_time: 0.0112 memory: 14901 loss: 1.0976 loss_prob: 0.5736 loss_thr: 0.4254 loss_db: 0.0986 2022/11/02 19:14:41 - mmengine - INFO - Epoch(train) [640][20/63] lr: 1.0902e-03 eta: 5:52:34 time: 0.5020 data_time: 0.0111 memory: 14901 loss: 1.1905 loss_prob: 0.6245 loss_thr: 0.4601 loss_db: 0.1059 2022/11/02 19:14:44 - mmengine - INFO - Epoch(train) [640][25/63] lr: 1.0902e-03 eta: 5:52:34 time: 0.5895 data_time: 0.0483 memory: 14901 loss: 1.1970 loss_prob: 0.6353 loss_thr: 0.4535 loss_db: 0.1081 2022/11/02 19:14:47 - mmengine - INFO - Epoch(train) [640][30/63] lr: 1.0902e-03 eta: 5:52:28 time: 0.6091 data_time: 0.0488 memory: 14901 loss: 1.1671 loss_prob: 0.6171 loss_thr: 0.4421 loss_db: 0.1079 2022/11/02 19:14:49 - mmengine - INFO - Epoch(train) [640][35/63] lr: 1.0902e-03 eta: 5:52:28 time: 0.5361 data_time: 0.0268 memory: 14901 loss: 1.2306 loss_prob: 0.6656 loss_thr: 0.4514 loss_db: 0.1136 2022/11/02 19:14:52 - mmengine - INFO - Epoch(train) [640][40/63] lr: 1.0902e-03 eta: 5:52:22 time: 0.5250 data_time: 0.0279 memory: 14901 loss: 1.2050 loss_prob: 0.6574 loss_thr: 0.4360 loss_db: 0.1116 2022/11/02 19:14:55 - mmengine - INFO - Epoch(train) [640][45/63] lr: 1.0902e-03 eta: 5:52:22 time: 0.5588 data_time: 0.0087 memory: 14901 loss: 1.1862 loss_prob: 0.6407 loss_thr: 0.4361 loss_db: 0.1094 2022/11/02 19:14:58 - mmengine - INFO - Epoch(train) [640][50/63] lr: 1.0902e-03 eta: 5:52:16 time: 0.6067 data_time: 0.0169 memory: 14901 loss: 1.2170 loss_prob: 0.6586 loss_thr: 0.4474 loss_db: 0.1109 2022/11/02 19:15:01 - mmengine - INFO - Epoch(train) [640][55/63] lr: 1.0902e-03 eta: 5:52:16 time: 0.5501 data_time: 0.0223 memory: 14901 loss: 1.1368 loss_prob: 0.5942 loss_thr: 0.4408 loss_db: 0.1018 2022/11/02 19:15:03 - mmengine - INFO - Epoch(train) [640][60/63] lr: 1.0902e-03 eta: 5:52:09 time: 0.5322 data_time: 0.0157 memory: 14901 loss: 1.1098 loss_prob: 0.5749 loss_thr: 0.4347 loss_db: 0.1002 2022/11/02 19:15:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:15:05 - mmengine - INFO - Saving checkpoint at 640 epochs 2022/11/02 19:15:09 - mmengine - INFO - Epoch(val) [640][5/500] eta: 5:52:09 time: 0.0422 data_time: 0.0043 memory: 14901 2022/11/02 19:15:09 - mmengine - INFO - Epoch(val) [640][10/500] eta: 0:00:23 time: 0.0475 data_time: 0.0046 memory: 1008 2022/11/02 19:15:09 - mmengine - INFO - Epoch(val) [640][15/500] eta: 0:00:23 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/02 19:15:09 - mmengine - INFO - Epoch(val) [640][20/500] eta: 0:00:18 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 19:15:10 - mmengine - INFO - Epoch(val) [640][25/500] eta: 0:00:18 time: 0.0437 data_time: 0.0038 memory: 1008 2022/11/02 19:15:10 - mmengine - INFO - Epoch(val) [640][30/500] eta: 0:00:21 time: 0.0450 data_time: 0.0036 memory: 1008 2022/11/02 19:15:10 - mmengine - INFO - Epoch(val) [640][35/500] eta: 0:00:21 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 19:15:10 - mmengine - INFO - Epoch(val) [640][40/500] eta: 0:00:20 time: 0.0437 data_time: 0.0029 memory: 1008 2022/11/02 19:15:11 - mmengine - INFO - Epoch(val) [640][45/500] eta: 0:00:20 time: 0.0445 data_time: 0.0028 memory: 1008 2022/11/02 19:15:11 - mmengine - INFO - Epoch(val) [640][50/500] eta: 0:00:20 time: 0.0447 data_time: 0.0027 memory: 1008 2022/11/02 19:15:11 - mmengine - INFO - Epoch(val) [640][55/500] eta: 0:00:20 time: 0.0476 data_time: 0.0027 memory: 1008 2022/11/02 19:15:11 - mmengine - INFO - Epoch(val) [640][60/500] eta: 0:00:18 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/02 19:15:11 - mmengine - INFO - Epoch(val) [640][65/500] eta: 0:00:18 time: 0.0422 data_time: 0.0033 memory: 1008 2022/11/02 19:15:12 - mmengine - INFO - Epoch(val) [640][70/500] eta: 0:00:19 time: 0.0450 data_time: 0.0033 memory: 1008 2022/11/02 19:15:12 - mmengine - INFO - Epoch(val) [640][75/500] eta: 0:00:19 time: 0.0426 data_time: 0.0031 memory: 1008 2022/11/02 19:15:12 - mmengine - INFO - Epoch(val) [640][80/500] eta: 0:00:16 time: 0.0387 data_time: 0.0030 memory: 1008 2022/11/02 19:15:12 - mmengine - INFO - Epoch(val) [640][85/500] eta: 0:00:16 time: 0.0349 data_time: 0.0026 memory: 1008 2022/11/02 19:15:12 - mmengine - INFO - Epoch(val) [640][90/500] eta: 0:00:16 time: 0.0394 data_time: 0.0026 memory: 1008 2022/11/02 19:15:13 - mmengine - INFO - Epoch(val) [640][95/500] eta: 0:00:16 time: 0.0430 data_time: 0.0025 memory: 1008 2022/11/02 19:15:13 - mmengine - INFO - Epoch(val) [640][100/500] eta: 0:00:17 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/02 19:15:13 - mmengine - INFO - Epoch(val) [640][105/500] eta: 0:00:17 time: 0.0438 data_time: 0.0041 memory: 1008 2022/11/02 19:15:13 - mmengine - INFO - Epoch(val) [640][110/500] eta: 0:00:14 time: 0.0381 data_time: 0.0034 memory: 1008 2022/11/02 19:15:14 - mmengine - INFO - Epoch(val) [640][115/500] eta: 0:00:14 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/02 19:15:14 - mmengine - INFO - Epoch(val) [640][120/500] eta: 0:00:15 time: 0.0408 data_time: 0.0025 memory: 1008 2022/11/02 19:15:14 - mmengine - INFO - Epoch(val) [640][125/500] eta: 0:00:15 time: 0.0367 data_time: 0.0022 memory: 1008 2022/11/02 19:15:14 - mmengine - INFO - Epoch(val) [640][130/500] eta: 0:00:13 time: 0.0370 data_time: 0.0026 memory: 1008 2022/11/02 19:15:14 - mmengine - INFO - Epoch(val) [640][135/500] eta: 0:00:13 time: 0.0390 data_time: 0.0028 memory: 1008 2022/11/02 19:15:14 - mmengine - INFO - Epoch(val) [640][140/500] eta: 0:00:14 time: 0.0391 data_time: 0.0028 memory: 1008 2022/11/02 19:15:15 - mmengine - INFO - Epoch(val) [640][145/500] eta: 0:00:14 time: 0.0478 data_time: 0.0032 memory: 1008 2022/11/02 19:15:15 - mmengine - INFO - Epoch(val) [640][150/500] eta: 0:00:17 time: 0.0493 data_time: 0.0034 memory: 1008 2022/11/02 19:15:15 - mmengine - INFO - Epoch(val) [640][155/500] eta: 0:00:17 time: 0.0537 data_time: 0.0048 memory: 1008 2022/11/02 19:15:15 - mmengine - INFO - Epoch(val) [640][160/500] eta: 0:00:17 time: 0.0526 data_time: 0.0045 memory: 1008 2022/11/02 19:15:16 - mmengine - INFO - Epoch(val) [640][165/500] eta: 0:00:17 time: 0.0409 data_time: 0.0025 memory: 1008 2022/11/02 19:15:16 - mmengine - INFO - Epoch(val) [640][170/500] eta: 0:00:13 time: 0.0414 data_time: 0.0025 memory: 1008 2022/11/02 19:15:16 - mmengine - INFO - Epoch(val) [640][175/500] eta: 0:00:13 time: 0.0385 data_time: 0.0026 memory: 1008 2022/11/02 19:15:16 - mmengine - INFO - Epoch(val) [640][180/500] eta: 0:00:12 time: 0.0389 data_time: 0.0026 memory: 1008 2022/11/02 19:15:17 - mmengine - INFO - Epoch(val) [640][185/500] eta: 0:00:12 time: 0.0435 data_time: 0.0027 memory: 1008 2022/11/02 19:15:17 - mmengine - INFO - Epoch(val) [640][190/500] eta: 0:00:13 time: 0.0440 data_time: 0.0028 memory: 1008 2022/11/02 19:15:17 - mmengine - INFO - Epoch(val) [640][195/500] eta: 0:00:13 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 19:15:17 - mmengine - INFO - Epoch(val) [640][200/500] eta: 0:00:13 time: 0.0461 data_time: 0.0029 memory: 1008 2022/11/02 19:15:17 - mmengine - INFO - Epoch(val) [640][205/500] eta: 0:00:13 time: 0.0468 data_time: 0.0028 memory: 1008 2022/11/02 19:15:18 - mmengine - INFO - Epoch(val) [640][210/500] eta: 0:00:14 time: 0.0502 data_time: 0.0036 memory: 1008 2022/11/02 19:15:18 - mmengine - INFO - Epoch(val) [640][215/500] eta: 0:00:14 time: 0.0538 data_time: 0.0047 memory: 1008 2022/11/02 19:15:18 - mmengine - INFO - Epoch(val) [640][220/500] eta: 0:00:13 time: 0.0476 data_time: 0.0040 memory: 1008 2022/11/02 19:15:18 - mmengine - INFO - Epoch(val) [640][225/500] eta: 0:00:13 time: 0.0502 data_time: 0.0036 memory: 1008 2022/11/02 19:15:19 - mmengine - INFO - Epoch(val) [640][230/500] eta: 0:00:13 time: 0.0498 data_time: 0.0038 memory: 1008 2022/11/02 19:15:19 - mmengine - INFO - Epoch(val) [640][235/500] eta: 0:00:13 time: 0.0502 data_time: 0.0039 memory: 1008 2022/11/02 19:15:19 - mmengine - INFO - Epoch(val) [640][240/500] eta: 0:00:14 time: 0.0561 data_time: 0.0042 memory: 1008 2022/11/02 19:15:20 - mmengine - INFO - Epoch(val) [640][245/500] eta: 0:00:14 time: 0.0606 data_time: 0.0051 memory: 1008 2022/11/02 19:15:20 - mmengine - INFO - Epoch(val) [640][250/500] eta: 0:00:13 time: 0.0549 data_time: 0.0046 memory: 1008 2022/11/02 19:15:20 - mmengine - INFO - Epoch(val) [640][255/500] eta: 0:00:13 time: 0.0466 data_time: 0.0036 memory: 1008 2022/11/02 19:15:20 - mmengine - INFO - Epoch(val) [640][260/500] eta: 0:00:11 time: 0.0462 data_time: 0.0036 memory: 1008 2022/11/02 19:15:21 - mmengine - INFO - Epoch(val) [640][265/500] eta: 0:00:11 time: 0.0515 data_time: 0.0038 memory: 1008 2022/11/02 19:15:21 - mmengine - INFO - Epoch(val) [640][270/500] eta: 0:00:13 time: 0.0568 data_time: 0.0046 memory: 1008 2022/11/02 19:15:21 - mmengine - INFO - Epoch(val) [640][275/500] eta: 0:00:13 time: 0.0544 data_time: 0.0067 memory: 1008 2022/11/02 19:15:21 - mmengine - INFO - Epoch(val) [640][280/500] eta: 0:00:10 time: 0.0497 data_time: 0.0057 memory: 1008 2022/11/02 19:15:22 - mmengine - INFO - Epoch(val) [640][285/500] eta: 0:00:10 time: 0.0446 data_time: 0.0029 memory: 1008 2022/11/02 19:15:22 - mmengine - INFO - Epoch(val) [640][290/500] eta: 0:00:08 time: 0.0415 data_time: 0.0031 memory: 1008 2022/11/02 19:15:22 - mmengine - INFO - Epoch(val) [640][295/500] eta: 0:00:08 time: 0.0421 data_time: 0.0031 memory: 1008 2022/11/02 19:15:22 - mmengine - INFO - Epoch(val) [640][300/500] eta: 0:00:08 time: 0.0412 data_time: 0.0027 memory: 1008 2022/11/02 19:15:22 - mmengine - INFO - Epoch(val) [640][305/500] eta: 0:00:08 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 19:15:23 - mmengine - INFO - Epoch(val) [640][310/500] eta: 0:00:07 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 19:15:23 - mmengine - INFO - Epoch(val) [640][315/500] eta: 0:00:07 time: 0.0441 data_time: 0.0028 memory: 1008 2022/11/02 19:15:23 - mmengine - INFO - Epoch(val) [640][320/500] eta: 0:00:07 time: 0.0440 data_time: 0.0032 memory: 1008 2022/11/02 19:15:23 - mmengine - INFO - Epoch(val) [640][325/500] eta: 0:00:07 time: 0.0560 data_time: 0.0026 memory: 1008 2022/11/02 19:15:24 - mmengine - INFO - Epoch(val) [640][330/500] eta: 0:00:09 time: 0.0534 data_time: 0.0021 memory: 1008 2022/11/02 19:15:24 - mmengine - INFO - Epoch(val) [640][335/500] eta: 0:00:09 time: 0.0375 data_time: 0.0028 memory: 1008 2022/11/02 19:15:24 - mmengine - INFO - Epoch(val) [640][340/500] eta: 0:00:08 time: 0.0519 data_time: 0.0032 memory: 1008 2022/11/02 19:15:24 - mmengine - INFO - Epoch(val) [640][345/500] eta: 0:00:08 time: 0.0537 data_time: 0.0031 memory: 1008 2022/11/02 19:15:24 - mmengine - INFO - Epoch(val) [640][350/500] eta: 0:00:06 time: 0.0440 data_time: 0.0026 memory: 1008 2022/11/02 19:15:25 - mmengine - INFO - Epoch(val) [640][355/500] eta: 0:00:06 time: 0.0430 data_time: 0.0026 memory: 1008 2022/11/02 19:15:25 - mmengine - INFO - Epoch(val) [640][360/500] eta: 0:00:06 time: 0.0434 data_time: 0.0031 memory: 1008 2022/11/02 19:15:25 - mmengine - INFO - Epoch(val) [640][365/500] eta: 0:00:06 time: 0.0453 data_time: 0.0034 memory: 1008 2022/11/02 19:15:25 - mmengine - INFO - Epoch(val) [640][370/500] eta: 0:00:05 time: 0.0412 data_time: 0.0032 memory: 1008 2022/11/02 19:15:26 - mmengine - INFO - Epoch(val) [640][375/500] eta: 0:00:05 time: 0.0382 data_time: 0.0028 memory: 1008 2022/11/02 19:15:26 - mmengine - INFO - Epoch(val) [640][380/500] eta: 0:00:04 time: 0.0409 data_time: 0.0027 memory: 1008 2022/11/02 19:15:26 - mmengine - INFO - Epoch(val) [640][385/500] eta: 0:00:04 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 19:15:26 - mmengine - INFO - Epoch(val) [640][390/500] eta: 0:00:04 time: 0.0429 data_time: 0.0027 memory: 1008 2022/11/02 19:15:26 - mmengine - INFO - Epoch(val) [640][395/500] eta: 0:00:04 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 19:15:27 - mmengine - INFO - Epoch(val) [640][400/500] eta: 0:00:03 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 19:15:27 - mmengine - INFO - Epoch(val) [640][405/500] eta: 0:00:03 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 19:15:27 - mmengine - INFO - Epoch(val) [640][410/500] eta: 0:00:03 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 19:15:27 - mmengine - INFO - Epoch(val) [640][415/500] eta: 0:00:03 time: 0.0418 data_time: 0.0028 memory: 1008 2022/11/02 19:15:27 - mmengine - INFO - Epoch(val) [640][420/500] eta: 0:00:02 time: 0.0369 data_time: 0.0028 memory: 1008 2022/11/02 19:15:28 - mmengine - INFO - Epoch(val) [640][425/500] eta: 0:00:02 time: 0.0390 data_time: 0.0029 memory: 1008 2022/11/02 19:15:28 - mmengine - INFO - Epoch(val) [640][430/500] eta: 0:00:02 time: 0.0396 data_time: 0.0028 memory: 1008 2022/11/02 19:15:28 - mmengine - INFO - Epoch(val) [640][435/500] eta: 0:00:02 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 19:15:28 - mmengine - INFO - Epoch(val) [640][440/500] eta: 0:00:02 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/02 19:15:28 - mmengine - INFO - Epoch(val) [640][445/500] eta: 0:00:02 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 19:15:29 - mmengine - INFO - Epoch(val) [640][450/500] eta: 0:00:02 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/02 19:15:29 - mmengine - INFO - Epoch(val) [640][455/500] eta: 0:00:02 time: 0.0404 data_time: 0.0029 memory: 1008 2022/11/02 19:15:29 - mmengine - INFO - Epoch(val) [640][460/500] eta: 0:00:01 time: 0.0385 data_time: 0.0028 memory: 1008 2022/11/02 19:15:29 - mmengine - INFO - Epoch(val) [640][465/500] eta: 0:00:01 time: 0.0371 data_time: 0.0027 memory: 1008 2022/11/02 19:15:29 - mmengine - INFO - Epoch(val) [640][470/500] eta: 0:00:01 time: 0.0355 data_time: 0.0026 memory: 1008 2022/11/02 19:15:30 - mmengine - INFO - Epoch(val) [640][475/500] eta: 0:00:01 time: 0.0394 data_time: 0.0030 memory: 1008 2022/11/02 19:15:30 - mmengine - INFO - Epoch(val) [640][480/500] eta: 0:00:00 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 19:15:30 - mmengine - INFO - Epoch(val) [640][485/500] eta: 0:00:00 time: 0.0377 data_time: 0.0028 memory: 1008 2022/11/02 19:15:30 - mmengine - INFO - Epoch(val) [640][490/500] eta: 0:00:00 time: 0.0458 data_time: 0.0029 memory: 1008 2022/11/02 19:15:30 - mmengine - INFO - Epoch(val) [640][495/500] eta: 0:00:00 time: 0.0511 data_time: 0.0032 memory: 1008 2022/11/02 19:15:31 - mmengine - INFO - Epoch(val) [640][500/500] eta: 0:00:00 time: 0.0447 data_time: 0.0035 memory: 1008 2022/11/02 19:15:31 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8296, precision: 0.7456, hmean: 0.7853 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8296, precision: 0.7922, hmean: 0.8104 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8291, precision: 0.8251, hmean: 0.8271 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8190, precision: 0.8514, hmean: 0.8348 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7997, precision: 0.8859, hmean: 0.8406 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6413, precision: 0.9315, hmean: 0.7596 2022/11/02 19:15:31 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0592, precision: 0.9609, hmean: 0.1116 2022/11/02 19:15:31 - mmengine - INFO - Epoch(val) [640][500/500] icdar/precision: 0.8859 icdar/recall: 0.7997 icdar/hmean: 0.8406 2022/11/02 19:15:36 - mmengine - INFO - Epoch(train) [641][5/63] lr: 1.0885e-03 eta: 0:00:00 time: 0.8120 data_time: 0.2703 memory: 14901 loss: 1.1582 loss_prob: 0.6165 loss_thr: 0.4373 loss_db: 0.1044 2022/11/02 19:15:40 - mmengine - INFO - Epoch(train) [641][10/63] lr: 1.0885e-03 eta: 5:52:03 time: 0.9156 data_time: 0.2646 memory: 14901 loss: 1.1862 loss_prob: 0.6305 loss_thr: 0.4491 loss_db: 0.1066 2022/11/02 19:15:43 - mmengine - INFO - Epoch(train) [641][15/63] lr: 1.0885e-03 eta: 5:52:03 time: 0.6628 data_time: 0.0124 memory: 14901 loss: 1.1831 loss_prob: 0.6246 loss_thr: 0.4507 loss_db: 0.1078 2022/11/02 19:15:47 - mmengine - INFO - Epoch(train) [641][20/63] lr: 1.0885e-03 eta: 5:51:57 time: 0.6656 data_time: 0.0110 memory: 14901 loss: 1.2665 loss_prob: 0.6857 loss_thr: 0.4623 loss_db: 0.1185 2022/11/02 19:15:50 - mmengine - INFO - Epoch(train) [641][25/63] lr: 1.0885e-03 eta: 5:51:57 time: 0.6949 data_time: 0.0320 memory: 14901 loss: 1.2675 loss_prob: 0.6969 loss_thr: 0.4530 loss_db: 0.1176 2022/11/02 19:15:53 - mmengine - INFO - Epoch(train) [641][30/63] lr: 1.0885e-03 eta: 5:51:52 time: 0.6822 data_time: 0.0421 memory: 14901 loss: 1.2048 loss_prob: 0.6519 loss_thr: 0.4449 loss_db: 0.1080 2022/11/02 19:15:57 - mmengine - INFO - Epoch(train) [641][35/63] lr: 1.0885e-03 eta: 5:51:52 time: 0.6929 data_time: 0.0214 memory: 14901 loss: 1.1581 loss_prob: 0.6151 loss_thr: 0.4394 loss_db: 0.1037 2022/11/02 19:15:59 - mmengine - INFO - Epoch(train) [641][40/63] lr: 1.0885e-03 eta: 5:51:46 time: 0.5951 data_time: 0.0127 memory: 14901 loss: 1.2060 loss_prob: 0.6446 loss_thr: 0.4506 loss_db: 0.1109 2022/11/02 19:16:03 - mmengine - INFO - Epoch(train) [641][45/63] lr: 1.0885e-03 eta: 5:51:46 time: 0.6686 data_time: 0.0108 memory: 14901 loss: 1.2377 loss_prob: 0.6655 loss_thr: 0.4580 loss_db: 0.1141 2022/11/02 19:16:09 - mmengine - INFO - Epoch(train) [641][50/63] lr: 1.0885e-03 eta: 5:51:43 time: 0.9144 data_time: 0.0257 memory: 14901 loss: 1.1814 loss_prob: 0.6328 loss_thr: 0.4404 loss_db: 0.1081 2022/11/02 19:16:11 - mmengine - INFO - Epoch(train) [641][55/63] lr: 1.0885e-03 eta: 5:51:43 time: 0.7589 data_time: 0.0283 memory: 14901 loss: 1.2177 loss_prob: 0.6478 loss_thr: 0.4590 loss_db: 0.1108 2022/11/02 19:16:14 - mmengine - INFO - Epoch(train) [641][60/63] lr: 1.0885e-03 eta: 5:51:37 time: 0.5639 data_time: 0.0147 memory: 14901 loss: 1.2066 loss_prob: 0.6385 loss_thr: 0.4592 loss_db: 0.1089 2022/11/02 19:16:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:16:23 - mmengine - INFO - Epoch(train) [642][5/63] lr: 1.0867e-03 eta: 5:51:37 time: 0.9863 data_time: 0.2363 memory: 14901 loss: 1.2236 loss_prob: 0.6551 loss_thr: 0.4568 loss_db: 0.1118 2022/11/02 19:16:26 - mmengine - INFO - Epoch(train) [642][10/63] lr: 1.0867e-03 eta: 5:51:31 time: 1.0142 data_time: 0.2406 memory: 14901 loss: 1.1820 loss_prob: 0.6239 loss_thr: 0.4503 loss_db: 0.1077 2022/11/02 19:16:29 - mmengine - INFO - Epoch(train) [642][15/63] lr: 1.0867e-03 eta: 5:51:31 time: 0.6039 data_time: 0.0142 memory: 14901 loss: 1.0864 loss_prob: 0.5666 loss_thr: 0.4217 loss_db: 0.0980 2022/11/02 19:16:32 - mmengine - INFO - Epoch(train) [642][20/63] lr: 1.0867e-03 eta: 5:51:25 time: 0.6010 data_time: 0.0105 memory: 14901 loss: 1.1940 loss_prob: 0.6336 loss_thr: 0.4509 loss_db: 0.1094 2022/11/02 19:16:35 - mmengine - INFO - Epoch(train) [642][25/63] lr: 1.0867e-03 eta: 5:51:25 time: 0.6518 data_time: 0.0432 memory: 14901 loss: 1.1938 loss_prob: 0.6340 loss_thr: 0.4497 loss_db: 0.1101 2022/11/02 19:16:38 - mmengine - INFO - Epoch(train) [642][30/63] lr: 1.0867e-03 eta: 5:51:19 time: 0.6110 data_time: 0.0418 memory: 14901 loss: 1.1473 loss_prob: 0.6080 loss_thr: 0.4334 loss_db: 0.1060 2022/11/02 19:16:41 - mmengine - INFO - Epoch(train) [642][35/63] lr: 1.0867e-03 eta: 5:51:19 time: 0.5776 data_time: 0.0109 memory: 14901 loss: 1.1862 loss_prob: 0.6226 loss_thr: 0.4577 loss_db: 0.1059 2022/11/02 19:16:44 - mmengine - INFO - Epoch(train) [642][40/63] lr: 1.0867e-03 eta: 5:51:13 time: 0.6075 data_time: 0.0137 memory: 14901 loss: 1.1897 loss_prob: 0.6270 loss_thr: 0.4578 loss_db: 0.1049 2022/11/02 19:16:49 - mmengine - INFO - Epoch(train) [642][45/63] lr: 1.0867e-03 eta: 5:51:13 time: 0.7379 data_time: 0.0096 memory: 14901 loss: 1.1171 loss_prob: 0.5875 loss_thr: 0.4279 loss_db: 0.1017 2022/11/02 19:16:52 - mmengine - INFO - Epoch(train) [642][50/63] lr: 1.0867e-03 eta: 5:51:09 time: 0.8149 data_time: 0.0239 memory: 14901 loss: 1.0538 loss_prob: 0.5438 loss_thr: 0.4139 loss_db: 0.0961 2022/11/02 19:16:55 - mmengine - INFO - Epoch(train) [642][55/63] lr: 1.0867e-03 eta: 5:51:09 time: 0.6961 data_time: 0.0258 memory: 14901 loss: 1.0461 loss_prob: 0.5419 loss_thr: 0.4109 loss_db: 0.0933 2022/11/02 19:16:58 - mmengine - INFO - Epoch(train) [642][60/63] lr: 1.0867e-03 eta: 5:51:03 time: 0.6308 data_time: 0.0120 memory: 14901 loss: 1.1250 loss_prob: 0.5923 loss_thr: 0.4321 loss_db: 0.1006 2022/11/02 19:17:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:17:07 - mmengine - INFO - Epoch(train) [643][5/63] lr: 1.0850e-03 eta: 5:51:03 time: 0.9662 data_time: 0.2168 memory: 14901 loss: 1.1219 loss_prob: 0.5810 loss_thr: 0.4406 loss_db: 0.1004 2022/11/02 19:17:10 - mmengine - INFO - Epoch(train) [643][10/63] lr: 1.0850e-03 eta: 5:50:57 time: 1.0151 data_time: 0.2272 memory: 14901 loss: 1.0973 loss_prob: 0.5696 loss_thr: 0.4304 loss_db: 0.0973 2022/11/02 19:17:14 - mmengine - INFO - Epoch(train) [643][15/63] lr: 1.0850e-03 eta: 5:50:57 time: 0.6527 data_time: 0.0239 memory: 14901 loss: 1.1306 loss_prob: 0.5959 loss_thr: 0.4330 loss_db: 0.1017 2022/11/02 19:17:16 - mmengine - INFO - Epoch(train) [643][20/63] lr: 1.0850e-03 eta: 5:50:52 time: 0.6511 data_time: 0.0166 memory: 14901 loss: 1.1681 loss_prob: 0.6294 loss_thr: 0.4289 loss_db: 0.1099 2022/11/02 19:17:20 - mmengine - INFO - Epoch(train) [643][25/63] lr: 1.0850e-03 eta: 5:50:52 time: 0.6120 data_time: 0.0199 memory: 14901 loss: 1.1083 loss_prob: 0.5923 loss_thr: 0.4115 loss_db: 0.1045 2022/11/02 19:17:23 - mmengine - INFO - Epoch(train) [643][30/63] lr: 1.0850e-03 eta: 5:50:46 time: 0.6515 data_time: 0.0343 memory: 14901 loss: 1.0166 loss_prob: 0.5249 loss_thr: 0.4016 loss_db: 0.0901 2022/11/02 19:17:26 - mmengine - INFO - Epoch(train) [643][35/63] lr: 1.0850e-03 eta: 5:50:46 time: 0.6536 data_time: 0.0325 memory: 14901 loss: 1.0446 loss_prob: 0.5502 loss_thr: 0.4005 loss_db: 0.0939 2022/11/02 19:17:29 - mmengine - INFO - Epoch(train) [643][40/63] lr: 1.0850e-03 eta: 5:50:41 time: 0.6227 data_time: 0.0227 memory: 14901 loss: 1.2430 loss_prob: 0.6851 loss_thr: 0.4460 loss_db: 0.1120 2022/11/02 19:17:32 - mmengine - INFO - Epoch(train) [643][45/63] lr: 1.0850e-03 eta: 5:50:41 time: 0.5970 data_time: 0.0180 memory: 14901 loss: 1.2680 loss_prob: 0.6897 loss_thr: 0.4642 loss_db: 0.1141 2022/11/02 19:17:35 - mmengine - INFO - Epoch(train) [643][50/63] lr: 1.0850e-03 eta: 5:50:34 time: 0.5547 data_time: 0.0256 memory: 14901 loss: 1.1244 loss_prob: 0.5850 loss_thr: 0.4367 loss_db: 0.1027 2022/11/02 19:17:38 - mmengine - INFO - Epoch(train) [643][55/63] lr: 1.0850e-03 eta: 5:50:34 time: 0.5445 data_time: 0.0400 memory: 14901 loss: 1.0946 loss_prob: 0.5704 loss_thr: 0.4236 loss_db: 0.1005 2022/11/02 19:17:41 - mmengine - INFO - Epoch(train) [643][60/63] lr: 1.0850e-03 eta: 5:50:28 time: 0.6004 data_time: 0.0272 memory: 14901 loss: 1.0581 loss_prob: 0.5607 loss_thr: 0.4000 loss_db: 0.0974 2022/11/02 19:17:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:17:49 - mmengine - INFO - Epoch(train) [644][5/63] lr: 1.0832e-03 eta: 5:50:28 time: 0.9616 data_time: 0.2418 memory: 14901 loss: 1.1739 loss_prob: 0.6190 loss_thr: 0.4514 loss_db: 0.1035 2022/11/02 19:17:53 - mmengine - INFO - Epoch(train) [644][10/63] lr: 1.0832e-03 eta: 5:50:22 time: 1.0146 data_time: 0.2409 memory: 14901 loss: 1.0764 loss_prob: 0.5553 loss_thr: 0.4236 loss_db: 0.0976 2022/11/02 19:17:55 - mmengine - INFO - Epoch(train) [644][15/63] lr: 1.0832e-03 eta: 5:50:22 time: 0.5936 data_time: 0.0082 memory: 14901 loss: 1.1320 loss_prob: 0.6037 loss_thr: 0.4253 loss_db: 0.1031 2022/11/02 19:17:58 - mmengine - INFO - Epoch(train) [644][20/63] lr: 1.0832e-03 eta: 5:50:16 time: 0.5217 data_time: 0.0081 memory: 14901 loss: 1.1632 loss_prob: 0.6244 loss_thr: 0.4345 loss_db: 0.1043 2022/11/02 19:18:01 - mmengine - INFO - Epoch(train) [644][25/63] lr: 1.0832e-03 eta: 5:50:16 time: 0.5711 data_time: 0.0295 memory: 14901 loss: 1.2087 loss_prob: 0.6411 loss_thr: 0.4575 loss_db: 0.1101 2022/11/02 19:18:04 - mmengine - INFO - Epoch(train) [644][30/63] lr: 1.0832e-03 eta: 5:50:10 time: 0.5968 data_time: 0.0384 memory: 14901 loss: 1.2847 loss_prob: 0.6780 loss_thr: 0.4927 loss_db: 0.1140 2022/11/02 19:18:06 - mmengine - INFO - Epoch(train) [644][35/63] lr: 1.0832e-03 eta: 5:50:10 time: 0.5289 data_time: 0.0168 memory: 14901 loss: 1.2711 loss_prob: 0.6835 loss_thr: 0.4774 loss_db: 0.1102 2022/11/02 19:18:09 - mmengine - INFO - Epoch(train) [644][40/63] lr: 1.0832e-03 eta: 5:50:03 time: 0.5140 data_time: 0.0086 memory: 14901 loss: 1.2688 loss_prob: 0.6855 loss_thr: 0.4681 loss_db: 0.1152 2022/11/02 19:18:12 - mmengine - INFO - Epoch(train) [644][45/63] lr: 1.0832e-03 eta: 5:50:03 time: 0.5804 data_time: 0.0120 memory: 14901 loss: 1.1770 loss_prob: 0.6224 loss_thr: 0.4456 loss_db: 0.1090 2022/11/02 19:18:15 - mmengine - INFO - Epoch(train) [644][50/63] lr: 1.0832e-03 eta: 5:49:57 time: 0.6045 data_time: 0.0178 memory: 14901 loss: 1.1167 loss_prob: 0.5874 loss_thr: 0.4296 loss_db: 0.0998 2022/11/02 19:18:18 - mmengine - INFO - Epoch(train) [644][55/63] lr: 1.0832e-03 eta: 5:49:57 time: 0.5819 data_time: 0.0261 memory: 14901 loss: 1.1298 loss_prob: 0.5968 loss_thr: 0.4322 loss_db: 0.1008 2022/11/02 19:18:21 - mmengine - INFO - Epoch(train) [644][60/63] lr: 1.0832e-03 eta: 5:49:51 time: 0.6273 data_time: 0.0194 memory: 14901 loss: 1.1235 loss_prob: 0.5926 loss_thr: 0.4302 loss_db: 0.1008 2022/11/02 19:18:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:18:30 - mmengine - INFO - Epoch(train) [645][5/63] lr: 1.0815e-03 eta: 5:49:51 time: 1.0399 data_time: 0.2577 memory: 14901 loss: 1.1619 loss_prob: 0.6168 loss_thr: 0.4370 loss_db: 0.1081 2022/11/02 19:18:33 - mmengine - INFO - Epoch(train) [645][10/63] lr: 1.0815e-03 eta: 5:49:46 time: 1.0512 data_time: 0.2649 memory: 14901 loss: 1.2136 loss_prob: 0.6502 loss_thr: 0.4529 loss_db: 0.1105 2022/11/02 19:18:36 - mmengine - INFO - Epoch(train) [645][15/63] lr: 1.0815e-03 eta: 5:49:46 time: 0.6236 data_time: 0.0154 memory: 14901 loss: 1.1632 loss_prob: 0.6186 loss_thr: 0.4393 loss_db: 0.1052 2022/11/02 19:18:39 - mmengine - INFO - Epoch(train) [645][20/63] lr: 1.0815e-03 eta: 5:49:39 time: 0.5373 data_time: 0.0107 memory: 14901 loss: 1.1138 loss_prob: 0.5921 loss_thr: 0.4194 loss_db: 0.1023 2022/11/02 19:18:42 - mmengine - INFO - Epoch(train) [645][25/63] lr: 1.0815e-03 eta: 5:49:39 time: 0.5879 data_time: 0.0327 memory: 14901 loss: 1.1380 loss_prob: 0.6115 loss_thr: 0.4215 loss_db: 0.1049 2022/11/02 19:18:45 - mmengine - INFO - Epoch(train) [645][30/63] lr: 1.0815e-03 eta: 5:49:33 time: 0.6082 data_time: 0.0399 memory: 14901 loss: 1.1429 loss_prob: 0.6059 loss_thr: 0.4331 loss_db: 0.1040 2022/11/02 19:18:47 - mmengine - INFO - Epoch(train) [645][35/63] lr: 1.0815e-03 eta: 5:49:33 time: 0.5356 data_time: 0.0207 memory: 14901 loss: 1.1371 loss_prob: 0.5971 loss_thr: 0.4360 loss_db: 0.1040 2022/11/02 19:18:50 - mmengine - INFO - Epoch(train) [645][40/63] lr: 1.0815e-03 eta: 5:49:27 time: 0.5405 data_time: 0.0132 memory: 14901 loss: 1.1599 loss_prob: 0.6208 loss_thr: 0.4332 loss_db: 0.1059 2022/11/02 19:18:55 - mmengine - INFO - Epoch(train) [645][45/63] lr: 1.0815e-03 eta: 5:49:27 time: 0.7756 data_time: 0.0107 memory: 14901 loss: 1.0916 loss_prob: 0.5764 loss_thr: 0.4172 loss_db: 0.0979 2022/11/02 19:18:58 - mmengine - INFO - Epoch(train) [645][50/63] lr: 1.0815e-03 eta: 5:49:23 time: 0.7755 data_time: 0.0232 memory: 14901 loss: 1.1670 loss_prob: 0.6332 loss_thr: 0.4238 loss_db: 0.1100 2022/11/02 19:19:02 - mmengine - INFO - Epoch(train) [645][55/63] lr: 1.0815e-03 eta: 5:49:23 time: 0.6588 data_time: 0.0262 memory: 14901 loss: 1.2044 loss_prob: 0.6547 loss_thr: 0.4350 loss_db: 0.1146 2022/11/02 19:19:04 - mmengine - INFO - Epoch(train) [645][60/63] lr: 1.0815e-03 eta: 5:49:17 time: 0.6484 data_time: 0.0175 memory: 14901 loss: 1.1703 loss_prob: 0.6158 loss_thr: 0.4478 loss_db: 0.1067 2022/11/02 19:19:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:19:11 - mmengine - INFO - Epoch(train) [646][5/63] lr: 1.0797e-03 eta: 5:49:17 time: 0.7937 data_time: 0.2596 memory: 14901 loss: 1.1839 loss_prob: 0.6351 loss_thr: 0.4413 loss_db: 0.1074 2022/11/02 19:19:14 - mmengine - INFO - Epoch(train) [646][10/63] lr: 1.0797e-03 eta: 5:49:10 time: 0.8594 data_time: 0.2586 memory: 14901 loss: 1.0903 loss_prob: 0.5706 loss_thr: 0.4244 loss_db: 0.0953 2022/11/02 19:19:17 - mmengine - INFO - Epoch(train) [646][15/63] lr: 1.0797e-03 eta: 5:49:10 time: 0.6095 data_time: 0.0104 memory: 14901 loss: 1.0395 loss_prob: 0.5329 loss_thr: 0.4169 loss_db: 0.0897 2022/11/02 19:19:20 - mmengine - INFO - Epoch(train) [646][20/63] lr: 1.0797e-03 eta: 5:49:03 time: 0.5441 data_time: 0.0126 memory: 14901 loss: 1.1099 loss_prob: 0.5817 loss_thr: 0.4272 loss_db: 0.1009 2022/11/02 19:19:23 - mmengine - INFO - Epoch(train) [646][25/63] lr: 1.0797e-03 eta: 5:49:03 time: 0.5333 data_time: 0.0356 memory: 14901 loss: 1.0988 loss_prob: 0.5742 loss_thr: 0.4252 loss_db: 0.0994 2022/11/02 19:19:26 - mmengine - INFO - Epoch(train) [646][30/63] lr: 1.0797e-03 eta: 5:48:57 time: 0.6035 data_time: 0.0457 memory: 14901 loss: 1.1529 loss_prob: 0.5966 loss_thr: 0.4535 loss_db: 0.1027 2022/11/02 19:19:29 - mmengine - INFO - Epoch(train) [646][35/63] lr: 1.0797e-03 eta: 5:48:57 time: 0.6216 data_time: 0.0224 memory: 14901 loss: 1.2435 loss_prob: 0.6591 loss_thr: 0.4700 loss_db: 0.1144 2022/11/02 19:19:32 - mmengine - INFO - Epoch(train) [646][40/63] lr: 1.0797e-03 eta: 5:48:51 time: 0.5812 data_time: 0.0089 memory: 14901 loss: 1.1909 loss_prob: 0.6365 loss_thr: 0.4448 loss_db: 0.1096 2022/11/02 19:19:34 - mmengine - INFO - Epoch(train) [646][45/63] lr: 1.0797e-03 eta: 5:48:51 time: 0.5125 data_time: 0.0106 memory: 14901 loss: 1.0519 loss_prob: 0.5360 loss_thr: 0.4248 loss_db: 0.0910 2022/11/02 19:19:37 - mmengine - INFO - Epoch(train) [646][50/63] lr: 1.0797e-03 eta: 5:48:45 time: 0.5319 data_time: 0.0230 memory: 14901 loss: 1.0170 loss_prob: 0.5117 loss_thr: 0.4192 loss_db: 0.0862 2022/11/02 19:19:40 - mmengine - INFO - Epoch(train) [646][55/63] lr: 1.0797e-03 eta: 5:48:45 time: 0.5651 data_time: 0.0292 memory: 14901 loss: 1.1211 loss_prob: 0.5850 loss_thr: 0.4367 loss_db: 0.0994 2022/11/02 19:19:42 - mmengine - INFO - Epoch(train) [646][60/63] lr: 1.0797e-03 eta: 5:48:38 time: 0.5279 data_time: 0.0181 memory: 14901 loss: 1.1628 loss_prob: 0.6098 loss_thr: 0.4476 loss_db: 0.1054 2022/11/02 19:19:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:19:50 - mmengine - INFO - Epoch(train) [647][5/63] lr: 1.0780e-03 eta: 5:48:38 time: 0.8252 data_time: 0.2527 memory: 14901 loss: 1.0547 loss_prob: 0.5578 loss_thr: 0.4016 loss_db: 0.0953 2022/11/02 19:19:52 - mmengine - INFO - Epoch(train) [647][10/63] lr: 1.0780e-03 eta: 5:48:31 time: 0.8696 data_time: 0.2595 memory: 14901 loss: 1.0394 loss_prob: 0.5447 loss_thr: 0.4009 loss_db: 0.0938 2022/11/02 19:19:55 - mmengine - INFO - Epoch(train) [647][15/63] lr: 1.0780e-03 eta: 5:48:31 time: 0.5535 data_time: 0.0163 memory: 14901 loss: 1.0896 loss_prob: 0.5769 loss_thr: 0.4121 loss_db: 0.1006 2022/11/02 19:19:58 - mmengine - INFO - Epoch(train) [647][20/63] lr: 1.0780e-03 eta: 5:48:24 time: 0.5171 data_time: 0.0086 memory: 14901 loss: 1.2064 loss_prob: 0.6484 loss_thr: 0.4472 loss_db: 0.1108 2022/11/02 19:20:02 - mmengine - INFO - Epoch(train) [647][25/63] lr: 1.0780e-03 eta: 5:48:24 time: 0.6898 data_time: 0.0256 memory: 14901 loss: 1.1719 loss_prob: 0.6148 loss_thr: 0.4514 loss_db: 0.1056 2022/11/02 19:20:05 - mmengine - INFO - Epoch(train) [647][30/63] lr: 1.0780e-03 eta: 5:48:20 time: 0.7402 data_time: 0.0419 memory: 14901 loss: 1.1224 loss_prob: 0.5890 loss_thr: 0.4298 loss_db: 0.1037 2022/11/02 19:20:09 - mmengine - INFO - Epoch(train) [647][35/63] lr: 1.0780e-03 eta: 5:48:20 time: 0.6804 data_time: 0.0252 memory: 14901 loss: 1.1693 loss_prob: 0.6243 loss_thr: 0.4367 loss_db: 0.1083 2022/11/02 19:20:11 - mmengine - INFO - Epoch(train) [647][40/63] lr: 1.0780e-03 eta: 5:48:14 time: 0.6462 data_time: 0.0147 memory: 14901 loss: 1.2049 loss_prob: 0.6545 loss_thr: 0.4432 loss_db: 0.1071 2022/11/02 19:20:14 - mmengine - INFO - Epoch(train) [647][45/63] lr: 1.0780e-03 eta: 5:48:14 time: 0.5300 data_time: 0.0164 memory: 14901 loss: 1.1526 loss_prob: 0.6203 loss_thr: 0.4311 loss_db: 0.1012 2022/11/02 19:20:17 - mmengine - INFO - Epoch(train) [647][50/63] lr: 1.0780e-03 eta: 5:48:08 time: 0.5716 data_time: 0.0257 memory: 14901 loss: 1.1152 loss_prob: 0.5798 loss_thr: 0.4348 loss_db: 0.1006 2022/11/02 19:20:20 - mmengine - INFO - Epoch(train) [647][55/63] lr: 1.0780e-03 eta: 5:48:08 time: 0.5746 data_time: 0.0266 memory: 14901 loss: 1.1625 loss_prob: 0.6127 loss_thr: 0.4411 loss_db: 0.1087 2022/11/02 19:20:22 - mmengine - INFO - Epoch(train) [647][60/63] lr: 1.0780e-03 eta: 5:48:01 time: 0.5202 data_time: 0.0121 memory: 14901 loss: 1.2198 loss_prob: 0.6502 loss_thr: 0.4575 loss_db: 0.1120 2022/11/02 19:20:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:20:30 - mmengine - INFO - Epoch(train) [648][5/63] lr: 1.0762e-03 eta: 5:48:01 time: 0.8191 data_time: 0.2184 memory: 14901 loss: 1.1578 loss_prob: 0.6105 loss_thr: 0.4426 loss_db: 0.1048 2022/11/02 19:20:33 - mmengine - INFO - Epoch(train) [648][10/63] lr: 1.0762e-03 eta: 5:47:55 time: 0.9463 data_time: 0.2211 memory: 14901 loss: 1.1681 loss_prob: 0.6156 loss_thr: 0.4461 loss_db: 0.1063 2022/11/02 19:20:36 - mmengine - INFO - Epoch(train) [648][15/63] lr: 1.0762e-03 eta: 5:47:55 time: 0.6767 data_time: 0.0158 memory: 14901 loss: 1.0664 loss_prob: 0.5582 loss_thr: 0.4148 loss_db: 0.0934 2022/11/02 19:20:40 - mmengine - INFO - Epoch(train) [648][20/63] lr: 1.0762e-03 eta: 5:47:49 time: 0.6569 data_time: 0.0103 memory: 14901 loss: 1.0611 loss_prob: 0.5626 loss_thr: 0.4045 loss_db: 0.0940 2022/11/02 19:20:43 - mmengine - INFO - Epoch(train) [648][25/63] lr: 1.0762e-03 eta: 5:47:49 time: 0.6387 data_time: 0.0115 memory: 14901 loss: 1.0757 loss_prob: 0.5577 loss_thr: 0.4179 loss_db: 0.1002 2022/11/02 19:20:47 - mmengine - INFO - Epoch(train) [648][30/63] lr: 1.0762e-03 eta: 5:47:44 time: 0.6922 data_time: 0.0346 memory: 14901 loss: 1.0971 loss_prob: 0.5687 loss_thr: 0.4299 loss_db: 0.0985 2022/11/02 19:20:50 - mmengine - INFO - Epoch(train) [648][35/63] lr: 1.0762e-03 eta: 5:47:44 time: 0.7265 data_time: 0.0378 memory: 14901 loss: 1.1628 loss_prob: 0.6188 loss_thr: 0.4400 loss_db: 0.1041 2022/11/02 19:20:53 - mmengine - INFO - Epoch(train) [648][40/63] lr: 1.0762e-03 eta: 5:47:38 time: 0.6196 data_time: 0.0162 memory: 14901 loss: 1.1078 loss_prob: 0.5860 loss_thr: 0.4198 loss_db: 0.1019 2022/11/02 19:20:56 - mmengine - INFO - Epoch(train) [648][45/63] lr: 1.0762e-03 eta: 5:47:38 time: 0.6151 data_time: 0.0129 memory: 14901 loss: 1.0878 loss_prob: 0.5728 loss_thr: 0.4162 loss_db: 0.0988 2022/11/02 19:20:59 - mmengine - INFO - Epoch(train) [648][50/63] lr: 1.0762e-03 eta: 5:47:33 time: 0.6623 data_time: 0.0223 memory: 14901 loss: 1.1028 loss_prob: 0.5783 loss_thr: 0.4242 loss_db: 0.1003 2022/11/02 19:21:02 - mmengine - INFO - Epoch(train) [648][55/63] lr: 1.0762e-03 eta: 5:47:33 time: 0.5883 data_time: 0.0256 memory: 14901 loss: 1.0948 loss_prob: 0.5698 loss_thr: 0.4254 loss_db: 0.0996 2022/11/02 19:21:05 - mmengine - INFO - Epoch(train) [648][60/63] lr: 1.0762e-03 eta: 5:47:26 time: 0.5422 data_time: 0.0227 memory: 14901 loss: 1.1005 loss_prob: 0.5799 loss_thr: 0.4217 loss_db: 0.0989 2022/11/02 19:21:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:21:12 - mmengine - INFO - Epoch(train) [649][5/63] lr: 1.0745e-03 eta: 5:47:26 time: 0.8239 data_time: 0.2486 memory: 14901 loss: 1.1188 loss_prob: 0.5898 loss_thr: 0.4262 loss_db: 0.1029 2022/11/02 19:21:15 - mmengine - INFO - Epoch(train) [649][10/63] lr: 1.0745e-03 eta: 5:47:19 time: 0.8709 data_time: 0.2572 memory: 14901 loss: 1.0837 loss_prob: 0.5590 loss_thr: 0.4277 loss_db: 0.0970 2022/11/02 19:21:18 - mmengine - INFO - Epoch(train) [649][15/63] lr: 1.0745e-03 eta: 5:47:19 time: 0.6185 data_time: 0.0154 memory: 14901 loss: 1.1322 loss_prob: 0.5858 loss_thr: 0.4465 loss_db: 0.0999 2022/11/02 19:21:21 - mmengine - INFO - Epoch(train) [649][20/63] lr: 1.0745e-03 eta: 5:47:13 time: 0.6155 data_time: 0.0092 memory: 14901 loss: 1.1528 loss_prob: 0.5996 loss_thr: 0.4510 loss_db: 0.1023 2022/11/02 19:21:24 - mmengine - INFO - Epoch(train) [649][25/63] lr: 1.0745e-03 eta: 5:47:13 time: 0.6142 data_time: 0.0306 memory: 14901 loss: 1.1661 loss_prob: 0.6091 loss_thr: 0.4543 loss_db: 0.1027 2022/11/02 19:21:28 - mmengine - INFO - Epoch(train) [649][30/63] lr: 1.0745e-03 eta: 5:47:08 time: 0.6523 data_time: 0.0340 memory: 14901 loss: 1.1698 loss_prob: 0.6133 loss_thr: 0.4508 loss_db: 0.1056 2022/11/02 19:21:30 - mmengine - INFO - Epoch(train) [649][35/63] lr: 1.0745e-03 eta: 5:47:08 time: 0.5819 data_time: 0.0246 memory: 14901 loss: 1.1829 loss_prob: 0.6326 loss_thr: 0.4451 loss_db: 0.1053 2022/11/02 19:21:33 - mmengine - INFO - Epoch(train) [649][40/63] lr: 1.0745e-03 eta: 5:47:01 time: 0.5279 data_time: 0.0204 memory: 14901 loss: 1.1384 loss_prob: 0.6158 loss_thr: 0.4217 loss_db: 0.1009 2022/11/02 19:21:36 - mmengine - INFO - Epoch(train) [649][45/63] lr: 1.0745e-03 eta: 5:47:01 time: 0.5595 data_time: 0.0142 memory: 14901 loss: 1.0687 loss_prob: 0.5615 loss_thr: 0.4094 loss_db: 0.0979 2022/11/02 19:21:38 - mmengine - INFO - Epoch(train) [649][50/63] lr: 1.0745e-03 eta: 5:46:55 time: 0.5649 data_time: 0.0340 memory: 14901 loss: 1.1799 loss_prob: 0.6311 loss_thr: 0.4395 loss_db: 0.1093 2022/11/02 19:21:41 - mmengine - INFO - Epoch(train) [649][55/63] lr: 1.0745e-03 eta: 5:46:55 time: 0.5204 data_time: 0.0345 memory: 14901 loss: 1.1843 loss_prob: 0.6365 loss_thr: 0.4384 loss_db: 0.1093 2022/11/02 19:21:44 - mmengine - INFO - Epoch(train) [649][60/63] lr: 1.0745e-03 eta: 5:46:49 time: 0.5567 data_time: 0.0254 memory: 14901 loss: 1.0595 loss_prob: 0.5558 loss_thr: 0.4100 loss_db: 0.0937 2022/11/02 19:21:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:21:51 - mmengine - INFO - Epoch(train) [650][5/63] lr: 1.0727e-03 eta: 5:46:49 time: 0.8824 data_time: 0.2324 memory: 14901 loss: 1.1888 loss_prob: 0.6349 loss_thr: 0.4465 loss_db: 0.1074 2022/11/02 19:21:55 - mmengine - INFO - Epoch(train) [650][10/63] lr: 1.0727e-03 eta: 5:46:42 time: 0.8983 data_time: 0.2329 memory: 14901 loss: 1.1402 loss_prob: 0.6057 loss_thr: 0.4291 loss_db: 0.1053 2022/11/02 19:21:58 - mmengine - INFO - Epoch(train) [650][15/63] lr: 1.0727e-03 eta: 5:46:42 time: 0.6795 data_time: 0.0120 memory: 14901 loss: 1.0478 loss_prob: 0.5439 loss_thr: 0.4095 loss_db: 0.0943 2022/11/02 19:22:01 - mmengine - INFO - Epoch(train) [650][20/63] lr: 1.0727e-03 eta: 5:46:37 time: 0.6898 data_time: 0.0093 memory: 14901 loss: 1.1703 loss_prob: 0.6215 loss_thr: 0.4416 loss_db: 0.1072 2022/11/02 19:22:05 - mmengine - INFO - Epoch(train) [650][25/63] lr: 1.0727e-03 eta: 5:46:37 time: 0.7123 data_time: 0.0128 memory: 14901 loss: 1.2099 loss_prob: 0.6585 loss_thr: 0.4400 loss_db: 0.1114 2022/11/02 19:22:10 - mmengine - INFO - Epoch(train) [650][30/63] lr: 1.0727e-03 eta: 5:46:33 time: 0.8301 data_time: 0.0414 memory: 14901 loss: 1.1769 loss_prob: 0.6308 loss_thr: 0.4391 loss_db: 0.1070 2022/11/02 19:22:12 - mmengine - INFO - Epoch(train) [650][35/63] lr: 1.0727e-03 eta: 5:46:33 time: 0.6911 data_time: 0.0378 memory: 14901 loss: 1.1063 loss_prob: 0.5802 loss_thr: 0.4261 loss_db: 0.1000 2022/11/02 19:22:16 - mmengine - INFO - Epoch(train) [650][40/63] lr: 1.0727e-03 eta: 5:46:27 time: 0.6096 data_time: 0.0106 memory: 14901 loss: 1.0875 loss_prob: 0.5685 loss_thr: 0.4227 loss_db: 0.0962 2022/11/02 19:22:18 - mmengine - INFO - Epoch(train) [650][45/63] lr: 1.0727e-03 eta: 5:46:27 time: 0.6075 data_time: 0.0113 memory: 14901 loss: 1.1058 loss_prob: 0.5805 loss_thr: 0.4249 loss_db: 0.1004 2022/11/02 19:22:21 - mmengine - INFO - Epoch(train) [650][50/63] lr: 1.0727e-03 eta: 5:46:20 time: 0.5511 data_time: 0.0232 memory: 14901 loss: 1.2044 loss_prob: 0.6420 loss_thr: 0.4517 loss_db: 0.1107 2022/11/02 19:22:24 - mmengine - INFO - Epoch(train) [650][55/63] lr: 1.0727e-03 eta: 5:46:20 time: 0.5519 data_time: 0.0272 memory: 14901 loss: 1.2402 loss_prob: 0.6656 loss_thr: 0.4644 loss_db: 0.1102 2022/11/02 19:22:27 - mmengine - INFO - Epoch(train) [650][60/63] lr: 1.0727e-03 eta: 5:46:14 time: 0.5146 data_time: 0.0146 memory: 14901 loss: 1.1848 loss_prob: 0.6376 loss_thr: 0.4388 loss_db: 0.1085 2022/11/02 19:22:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:22:34 - mmengine - INFO - Epoch(train) [651][5/63] lr: 1.0709e-03 eta: 5:46:14 time: 0.8118 data_time: 0.2741 memory: 14901 loss: 1.2615 loss_prob: 0.6712 loss_thr: 0.4729 loss_db: 0.1174 2022/11/02 19:22:36 - mmengine - INFO - Epoch(train) [651][10/63] lr: 1.0709e-03 eta: 5:46:06 time: 0.8343 data_time: 0.2738 memory: 14901 loss: 1.2288 loss_prob: 0.6630 loss_thr: 0.4524 loss_db: 0.1134 2022/11/02 19:22:40 - mmengine - INFO - Epoch(train) [651][15/63] lr: 1.0709e-03 eta: 5:46:06 time: 0.6689 data_time: 0.0106 memory: 14901 loss: 1.1946 loss_prob: 0.6339 loss_thr: 0.4507 loss_db: 0.1099 2022/11/02 19:22:43 - mmengine - INFO - Epoch(train) [651][20/63] lr: 1.0709e-03 eta: 5:46:01 time: 0.7079 data_time: 0.0129 memory: 14901 loss: 1.1486 loss_prob: 0.6043 loss_thr: 0.4407 loss_db: 0.1036 2022/11/02 19:22:46 - mmengine - INFO - Epoch(train) [651][25/63] lr: 1.0709e-03 eta: 5:46:01 time: 0.6160 data_time: 0.0221 memory: 14901 loss: 1.1905 loss_prob: 0.6291 loss_thr: 0.4556 loss_db: 0.1059 2022/11/02 19:22:49 - mmengine - INFO - Epoch(train) [651][30/63] lr: 1.0709e-03 eta: 5:45:55 time: 0.5988 data_time: 0.0330 memory: 14901 loss: 1.1636 loss_prob: 0.6094 loss_thr: 0.4496 loss_db: 0.1046 2022/11/02 19:22:52 - mmengine - INFO - Epoch(train) [651][35/63] lr: 1.0709e-03 eta: 5:45:55 time: 0.5626 data_time: 0.0263 memory: 14901 loss: 1.1162 loss_prob: 0.5905 loss_thr: 0.4227 loss_db: 0.1031 2022/11/02 19:22:55 - mmengine - INFO - Epoch(train) [651][40/63] lr: 1.0709e-03 eta: 5:45:49 time: 0.5333 data_time: 0.0210 memory: 14901 loss: 1.0459 loss_prob: 0.5489 loss_thr: 0.4028 loss_db: 0.0943 2022/11/02 19:22:58 - mmengine - INFO - Epoch(train) [651][45/63] lr: 1.0709e-03 eta: 5:45:49 time: 0.5760 data_time: 0.0183 memory: 14901 loss: 1.0871 loss_prob: 0.5770 loss_thr: 0.4108 loss_db: 0.0993 2022/11/02 19:23:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:23:01 - mmengine - INFO - Epoch(train) [651][50/63] lr: 1.0709e-03 eta: 5:45:43 time: 0.6265 data_time: 0.0249 memory: 14901 loss: 1.1838 loss_prob: 0.6358 loss_thr: 0.4394 loss_db: 0.1086 2022/11/02 19:23:04 - mmengine - INFO - Epoch(train) [651][55/63] lr: 1.0709e-03 eta: 5:45:43 time: 0.6231 data_time: 0.0237 memory: 14901 loss: 1.2367 loss_prob: 0.6461 loss_thr: 0.4812 loss_db: 0.1094 2022/11/02 19:23:07 - mmengine - INFO - Epoch(train) [651][60/63] lr: 1.0709e-03 eta: 5:45:37 time: 0.6030 data_time: 0.0157 memory: 14901 loss: 1.2164 loss_prob: 0.6290 loss_thr: 0.4795 loss_db: 0.1079 2022/11/02 19:23:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:23:15 - mmengine - INFO - Epoch(train) [652][5/63] lr: 1.0692e-03 eta: 5:45:37 time: 0.9067 data_time: 0.2943 memory: 14901 loss: 1.1027 loss_prob: 0.5710 loss_thr: 0.4307 loss_db: 0.1010 2022/11/02 19:23:17 - mmengine - INFO - Epoch(train) [652][10/63] lr: 1.0692e-03 eta: 5:45:30 time: 0.9212 data_time: 0.2913 memory: 14901 loss: 1.1096 loss_prob: 0.5806 loss_thr: 0.4276 loss_db: 0.1015 2022/11/02 19:23:20 - mmengine - INFO - Epoch(train) [652][15/63] lr: 1.0692e-03 eta: 5:45:30 time: 0.4969 data_time: 0.0142 memory: 14901 loss: 1.0331 loss_prob: 0.5376 loss_thr: 0.4032 loss_db: 0.0923 2022/11/02 19:23:23 - mmengine - INFO - Epoch(train) [652][20/63] lr: 1.0692e-03 eta: 5:45:24 time: 0.5391 data_time: 0.0117 memory: 14901 loss: 1.0915 loss_prob: 0.5705 loss_thr: 0.4219 loss_db: 0.0991 2022/11/02 19:23:27 - mmengine - INFO - Epoch(train) [652][25/63] lr: 1.0692e-03 eta: 5:45:24 time: 0.6936 data_time: 0.0582 memory: 14901 loss: 1.0623 loss_prob: 0.5508 loss_thr: 0.4162 loss_db: 0.0954 2022/11/02 19:23:30 - mmengine - INFO - Epoch(train) [652][30/63] lr: 1.0692e-03 eta: 5:45:19 time: 0.7090 data_time: 0.0562 memory: 14901 loss: 1.1290 loss_prob: 0.6059 loss_thr: 0.4211 loss_db: 0.1020 2022/11/02 19:23:33 - mmengine - INFO - Epoch(train) [652][35/63] lr: 1.0692e-03 eta: 5:45:19 time: 0.5626 data_time: 0.0096 memory: 14901 loss: 1.2888 loss_prob: 0.7145 loss_thr: 0.4560 loss_db: 0.1183 2022/11/02 19:23:36 - mmengine - INFO - Epoch(train) [652][40/63] lr: 1.0692e-03 eta: 5:45:13 time: 0.6168 data_time: 0.0142 memory: 14901 loss: 1.3750 loss_prob: 0.7492 loss_thr: 0.4993 loss_db: 0.1265 2022/11/02 19:23:39 - mmengine - INFO - Epoch(train) [652][45/63] lr: 1.0692e-03 eta: 5:45:13 time: 0.6947 data_time: 0.0122 memory: 14901 loss: 1.2888 loss_prob: 0.6900 loss_thr: 0.4803 loss_db: 0.1184 2022/11/02 19:23:43 - mmengine - INFO - Epoch(train) [652][50/63] lr: 1.0692e-03 eta: 5:45:07 time: 0.6562 data_time: 0.0341 memory: 14901 loss: 1.1879 loss_prob: 0.6400 loss_thr: 0.4393 loss_db: 0.1085 2022/11/02 19:23:45 - mmengine - INFO - Epoch(train) [652][55/63] lr: 1.0692e-03 eta: 5:45:07 time: 0.6035 data_time: 0.0340 memory: 14901 loss: 1.2063 loss_prob: 0.6555 loss_thr: 0.4380 loss_db: 0.1128 2022/11/02 19:23:48 - mmengine - INFO - Epoch(train) [652][60/63] lr: 1.0692e-03 eta: 5:45:01 time: 0.5540 data_time: 0.0118 memory: 14901 loss: 1.1494 loss_prob: 0.6236 loss_thr: 0.4187 loss_db: 0.1072 2022/11/02 19:23:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:23:56 - mmengine - INFO - Epoch(train) [653][5/63] lr: 1.0674e-03 eta: 5:45:01 time: 0.8466 data_time: 0.2252 memory: 14901 loss: 1.1498 loss_prob: 0.6139 loss_thr: 0.4305 loss_db: 0.1055 2022/11/02 19:23:59 - mmengine - INFO - Epoch(train) [653][10/63] lr: 1.0674e-03 eta: 5:44:54 time: 0.9371 data_time: 0.2330 memory: 14901 loss: 1.0913 loss_prob: 0.5782 loss_thr: 0.4130 loss_db: 0.1001 2022/11/02 19:24:03 - mmengine - INFO - Epoch(train) [653][15/63] lr: 1.0674e-03 eta: 5:44:54 time: 0.7313 data_time: 0.0182 memory: 14901 loss: 1.0401 loss_prob: 0.5452 loss_thr: 0.4006 loss_db: 0.0942 2022/11/02 19:24:06 - mmengine - INFO - Epoch(train) [653][20/63] lr: 1.0674e-03 eta: 5:44:49 time: 0.6618 data_time: 0.0081 memory: 14901 loss: 1.0796 loss_prob: 0.5667 loss_thr: 0.4143 loss_db: 0.0986 2022/11/02 19:24:10 - mmengine - INFO - Epoch(train) [653][25/63] lr: 1.0674e-03 eta: 5:44:49 time: 0.6674 data_time: 0.0117 memory: 14901 loss: 1.1330 loss_prob: 0.6025 loss_thr: 0.4253 loss_db: 0.1053 2022/11/02 19:24:14 - mmengine - INFO - Epoch(train) [653][30/63] lr: 1.0674e-03 eta: 5:44:45 time: 0.8103 data_time: 0.0469 memory: 14901 loss: 1.1597 loss_prob: 0.6080 loss_thr: 0.4467 loss_db: 0.1050 2022/11/02 19:24:18 - mmengine - INFO - Epoch(train) [653][35/63] lr: 1.0674e-03 eta: 5:44:45 time: 0.8286 data_time: 0.0412 memory: 14901 loss: 1.1027 loss_prob: 0.5739 loss_thr: 0.4305 loss_db: 0.0983 2022/11/02 19:24:21 - mmengine - INFO - Epoch(train) [653][40/63] lr: 1.0674e-03 eta: 5:44:40 time: 0.7311 data_time: 0.0093 memory: 14901 loss: 1.0157 loss_prob: 0.5331 loss_thr: 0.3925 loss_db: 0.0900 2022/11/02 19:24:24 - mmengine - INFO - Epoch(train) [653][45/63] lr: 1.0674e-03 eta: 5:44:40 time: 0.5936 data_time: 0.0098 memory: 14901 loss: 1.0421 loss_prob: 0.5454 loss_thr: 0.4016 loss_db: 0.0951 2022/11/02 19:24:27 - mmengine - INFO - Epoch(train) [653][50/63] lr: 1.0674e-03 eta: 5:44:34 time: 0.5810 data_time: 0.0253 memory: 14901 loss: 1.1474 loss_prob: 0.6123 loss_thr: 0.4290 loss_db: 0.1061 2022/11/02 19:24:30 - mmengine - INFO - Epoch(train) [653][55/63] lr: 1.0674e-03 eta: 5:44:34 time: 0.5757 data_time: 0.0306 memory: 14901 loss: 1.2334 loss_prob: 0.6605 loss_thr: 0.4599 loss_db: 0.1130 2022/11/02 19:24:32 - mmengine - INFO - Epoch(train) [653][60/63] lr: 1.0674e-03 eta: 5:44:27 time: 0.5234 data_time: 0.0141 memory: 14901 loss: 1.1924 loss_prob: 0.6363 loss_thr: 0.4469 loss_db: 0.1092 2022/11/02 19:24:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:24:40 - mmengine - INFO - Epoch(train) [654][5/63] lr: 1.0657e-03 eta: 5:44:27 time: 0.9159 data_time: 0.2275 memory: 14901 loss: 1.0792 loss_prob: 0.5645 loss_thr: 0.4173 loss_db: 0.0975 2022/11/02 19:24:43 - mmengine - INFO - Epoch(train) [654][10/63] lr: 1.0657e-03 eta: 5:44:21 time: 0.9912 data_time: 0.2388 memory: 14901 loss: 1.0751 loss_prob: 0.5581 loss_thr: 0.4211 loss_db: 0.0959 2022/11/02 19:24:46 - mmengine - INFO - Epoch(train) [654][15/63] lr: 1.0657e-03 eta: 5:44:21 time: 0.5375 data_time: 0.0186 memory: 14901 loss: 1.0696 loss_prob: 0.5581 loss_thr: 0.4139 loss_db: 0.0976 2022/11/02 19:24:48 - mmengine - INFO - Epoch(train) [654][20/63] lr: 1.0657e-03 eta: 5:44:14 time: 0.5143 data_time: 0.0092 memory: 14901 loss: 1.0586 loss_prob: 0.5583 loss_thr: 0.4035 loss_db: 0.0968 2022/11/02 19:24:51 - mmengine - INFO - Epoch(train) [654][25/63] lr: 1.0657e-03 eta: 5:44:14 time: 0.5855 data_time: 0.0386 memory: 14901 loss: 1.0673 loss_prob: 0.5595 loss_thr: 0.4110 loss_db: 0.0968 2022/11/02 19:24:55 - mmengine - INFO - Epoch(train) [654][30/63] lr: 1.0657e-03 eta: 5:44:09 time: 0.6679 data_time: 0.0445 memory: 14901 loss: 1.0942 loss_prob: 0.5792 loss_thr: 0.4152 loss_db: 0.0998 2022/11/02 19:24:59 - mmengine - INFO - Epoch(train) [654][35/63] lr: 1.0657e-03 eta: 5:44:09 time: 0.7040 data_time: 0.0257 memory: 14901 loss: 1.0702 loss_prob: 0.5609 loss_thr: 0.4126 loss_db: 0.0967 2022/11/02 19:25:02 - mmengine - INFO - Epoch(train) [654][40/63] lr: 1.0657e-03 eta: 5:44:04 time: 0.6845 data_time: 0.0198 memory: 14901 loss: 1.0352 loss_prob: 0.5361 loss_thr: 0.4054 loss_db: 0.0938 2022/11/02 19:25:05 - mmengine - INFO - Epoch(train) [654][45/63] lr: 1.0657e-03 eta: 5:44:04 time: 0.6158 data_time: 0.0104 memory: 14901 loss: 1.2428 loss_prob: 0.7109 loss_thr: 0.4173 loss_db: 0.1146 2022/11/02 19:25:08 - mmengine - INFO - Epoch(train) [654][50/63] lr: 1.0657e-03 eta: 5:43:58 time: 0.6202 data_time: 0.0232 memory: 14901 loss: 1.3678 loss_prob: 0.7862 loss_thr: 0.4561 loss_db: 0.1255 2022/11/02 19:25:11 - mmengine - INFO - Epoch(train) [654][55/63] lr: 1.0657e-03 eta: 5:43:58 time: 0.6734 data_time: 0.0325 memory: 14901 loss: 1.2286 loss_prob: 0.6598 loss_thr: 0.4564 loss_db: 0.1123 2022/11/02 19:25:14 - mmengine - INFO - Epoch(train) [654][60/63] lr: 1.0657e-03 eta: 5:43:52 time: 0.6161 data_time: 0.0228 memory: 14901 loss: 1.1497 loss_prob: 0.6151 loss_thr: 0.4269 loss_db: 0.1077 2022/11/02 19:25:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:25:22 - mmengine - INFO - Epoch(train) [655][5/63] lr: 1.0639e-03 eta: 5:43:52 time: 0.8417 data_time: 0.2170 memory: 14901 loss: 1.0945 loss_prob: 0.5716 loss_thr: 0.4262 loss_db: 0.0967 2022/11/02 19:25:25 - mmengine - INFO - Epoch(train) [655][10/63] lr: 1.0639e-03 eta: 5:43:45 time: 0.8999 data_time: 0.2298 memory: 14901 loss: 1.1810 loss_prob: 0.6382 loss_thr: 0.4364 loss_db: 0.1064 2022/11/02 19:25:28 - mmengine - INFO - Epoch(train) [655][15/63] lr: 1.0639e-03 eta: 5:43:45 time: 0.6098 data_time: 0.0277 memory: 14901 loss: 1.1831 loss_prob: 0.6369 loss_thr: 0.4384 loss_db: 0.1077 2022/11/02 19:25:31 - mmengine - INFO - Epoch(train) [655][20/63] lr: 1.0639e-03 eta: 5:43:39 time: 0.6289 data_time: 0.0157 memory: 14901 loss: 1.1927 loss_prob: 0.6364 loss_thr: 0.4513 loss_db: 0.1050 2022/11/02 19:25:34 - mmengine - INFO - Epoch(train) [655][25/63] lr: 1.0639e-03 eta: 5:43:39 time: 0.6504 data_time: 0.0336 memory: 14901 loss: 1.2085 loss_prob: 0.6546 loss_thr: 0.4491 loss_db: 0.1048 2022/11/02 19:25:37 - mmengine - INFO - Epoch(train) [655][30/63] lr: 1.0639e-03 eta: 5:43:33 time: 0.6104 data_time: 0.0500 memory: 14901 loss: 1.1332 loss_prob: 0.6005 loss_thr: 0.4292 loss_db: 0.1035 2022/11/02 19:25:40 - mmengine - INFO - Epoch(train) [655][35/63] lr: 1.0639e-03 eta: 5:43:33 time: 0.5329 data_time: 0.0349 memory: 14901 loss: 1.1760 loss_prob: 0.6250 loss_thr: 0.4408 loss_db: 0.1102 2022/11/02 19:25:42 - mmengine - INFO - Epoch(train) [655][40/63] lr: 1.0639e-03 eta: 5:43:27 time: 0.5516 data_time: 0.0222 memory: 14901 loss: 1.0932 loss_prob: 0.5853 loss_thr: 0.4096 loss_db: 0.0983 2022/11/02 19:25:45 - mmengine - INFO - Epoch(train) [655][45/63] lr: 1.0639e-03 eta: 5:43:27 time: 0.5590 data_time: 0.0142 memory: 14901 loss: 1.0742 loss_prob: 0.5681 loss_thr: 0.4105 loss_db: 0.0956 2022/11/02 19:25:49 - mmengine - INFO - Epoch(train) [655][50/63] lr: 1.0639e-03 eta: 5:43:21 time: 0.6087 data_time: 0.0224 memory: 14901 loss: 1.1482 loss_prob: 0.6056 loss_thr: 0.4372 loss_db: 0.1055 2022/11/02 19:25:52 - mmengine - INFO - Epoch(train) [655][55/63] lr: 1.0639e-03 eta: 5:43:21 time: 0.6896 data_time: 0.0265 memory: 14901 loss: 1.1546 loss_prob: 0.6134 loss_thr: 0.4351 loss_db: 0.1060 2022/11/02 19:25:55 - mmengine - INFO - Epoch(train) [655][60/63] lr: 1.0639e-03 eta: 5:43:16 time: 0.6659 data_time: 0.0169 memory: 14901 loss: 1.0764 loss_prob: 0.5617 loss_thr: 0.4186 loss_db: 0.0961 2022/11/02 19:25:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:26:03 - mmengine - INFO - Epoch(train) [656][5/63] lr: 1.0622e-03 eta: 5:43:16 time: 0.8645 data_time: 0.2402 memory: 14901 loss: 1.0012 loss_prob: 0.5181 loss_thr: 0.3939 loss_db: 0.0892 2022/11/02 19:26:06 - mmengine - INFO - Epoch(train) [656][10/63] lr: 1.0622e-03 eta: 5:43:09 time: 0.9241 data_time: 0.2390 memory: 14901 loss: 1.0426 loss_prob: 0.5513 loss_thr: 0.3961 loss_db: 0.0952 2022/11/02 19:26:08 - mmengine - INFO - Epoch(train) [656][15/63] lr: 1.0622e-03 eta: 5:43:09 time: 0.5446 data_time: 0.0111 memory: 14901 loss: 1.1293 loss_prob: 0.5963 loss_thr: 0.4306 loss_db: 0.1024 2022/11/02 19:26:13 - mmengine - INFO - Epoch(train) [656][20/63] lr: 1.0622e-03 eta: 5:43:04 time: 0.7145 data_time: 0.0129 memory: 14901 loss: 1.1197 loss_prob: 0.5830 loss_thr: 0.4373 loss_db: 0.0993 2022/11/02 19:26:16 - mmengine - INFO - Epoch(train) [656][25/63] lr: 1.0622e-03 eta: 5:43:04 time: 0.8079 data_time: 0.0192 memory: 14901 loss: 1.0503 loss_prob: 0.5504 loss_thr: 0.4053 loss_db: 0.0947 2022/11/02 19:26:21 - mmengine - INFO - Epoch(train) [656][30/63] lr: 1.0622e-03 eta: 5:43:00 time: 0.7841 data_time: 0.0385 memory: 14901 loss: 1.1154 loss_prob: 0.5935 loss_thr: 0.4201 loss_db: 0.1018 2022/11/02 19:26:24 - mmengine - INFO - Epoch(train) [656][35/63] lr: 1.0622e-03 eta: 5:43:00 time: 0.7916 data_time: 0.0320 memory: 14901 loss: 1.1591 loss_prob: 0.6134 loss_thr: 0.4398 loss_db: 0.1059 2022/11/02 19:26:27 - mmengine - INFO - Epoch(train) [656][40/63] lr: 1.0622e-03 eta: 5:42:54 time: 0.5968 data_time: 0.0134 memory: 14901 loss: 1.1178 loss_prob: 0.5935 loss_thr: 0.4214 loss_db: 0.1029 2022/11/02 19:26:30 - mmengine - INFO - Epoch(train) [656][45/63] lr: 1.0622e-03 eta: 5:42:54 time: 0.5576 data_time: 0.0153 memory: 14901 loss: 1.0532 loss_prob: 0.5564 loss_thr: 0.4024 loss_db: 0.0945 2022/11/02 19:26:32 - mmengine - INFO - Epoch(train) [656][50/63] lr: 1.0622e-03 eta: 5:42:47 time: 0.5603 data_time: 0.0200 memory: 14901 loss: 1.0799 loss_prob: 0.5677 loss_thr: 0.4149 loss_db: 0.0973 2022/11/02 19:26:35 - mmengine - INFO - Epoch(train) [656][55/63] lr: 1.0622e-03 eta: 5:42:47 time: 0.5208 data_time: 0.0278 memory: 14901 loss: 1.2045 loss_prob: 0.6462 loss_thr: 0.4481 loss_db: 0.1102 2022/11/02 19:26:38 - mmengine - INFO - Epoch(train) [656][60/63] lr: 1.0622e-03 eta: 5:42:41 time: 0.5586 data_time: 0.0186 memory: 14901 loss: 1.1785 loss_prob: 0.6314 loss_thr: 0.4389 loss_db: 0.1081 2022/11/02 19:26:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:26:44 - mmengine - INFO - Epoch(train) [657][5/63] lr: 1.0604e-03 eta: 5:42:41 time: 0.7554 data_time: 0.2240 memory: 14901 loss: 1.1160 loss_prob: 0.5830 loss_thr: 0.4321 loss_db: 0.1009 2022/11/02 19:26:47 - mmengine - INFO - Epoch(train) [657][10/63] lr: 1.0604e-03 eta: 5:42:33 time: 0.7549 data_time: 0.2258 memory: 14901 loss: 1.1334 loss_prob: 0.5934 loss_thr: 0.4371 loss_db: 0.1029 2022/11/02 19:26:50 - mmengine - INFO - Epoch(train) [657][15/63] lr: 1.0604e-03 eta: 5:42:33 time: 0.5771 data_time: 0.0136 memory: 14901 loss: 1.1234 loss_prob: 0.5858 loss_thr: 0.4336 loss_db: 0.1040 2022/11/02 19:26:54 - mmengine - INFO - Epoch(train) [657][20/63] lr: 1.0604e-03 eta: 5:42:28 time: 0.6813 data_time: 0.0098 memory: 14901 loss: 1.0881 loss_prob: 0.5750 loss_thr: 0.4145 loss_db: 0.0985 2022/11/02 19:26:58 - mmengine - INFO - Epoch(train) [657][25/63] lr: 1.0604e-03 eta: 5:42:28 time: 0.7745 data_time: 0.0211 memory: 14901 loss: 1.1140 loss_prob: 0.5899 loss_thr: 0.4237 loss_db: 0.1004 2022/11/02 19:27:01 - mmengine - INFO - Epoch(train) [657][30/63] lr: 1.0604e-03 eta: 5:42:23 time: 0.7223 data_time: 0.0411 memory: 14901 loss: 1.3833 loss_prob: 0.7761 loss_thr: 0.4798 loss_db: 0.1274 2022/11/02 19:27:03 - mmengine - INFO - Epoch(train) [657][35/63] lr: 1.0604e-03 eta: 5:42:23 time: 0.5538 data_time: 0.0326 memory: 14901 loss: 1.4432 loss_prob: 0.8158 loss_thr: 0.4945 loss_db: 0.1330 2022/11/02 19:27:06 - mmengine - INFO - Epoch(train) [657][40/63] lr: 1.0604e-03 eta: 5:42:16 time: 0.5100 data_time: 0.0140 memory: 14901 loss: 1.2291 loss_prob: 0.6681 loss_thr: 0.4476 loss_db: 0.1134 2022/11/02 19:27:09 - mmengine - INFO - Epoch(train) [657][45/63] lr: 1.0604e-03 eta: 5:42:16 time: 0.5622 data_time: 0.0107 memory: 14901 loss: 1.1378 loss_prob: 0.6122 loss_thr: 0.4212 loss_db: 0.1043 2022/11/02 19:27:12 - mmengine - INFO - Epoch(train) [657][50/63] lr: 1.0604e-03 eta: 5:42:10 time: 0.5744 data_time: 0.0203 memory: 14901 loss: 1.1132 loss_prob: 0.5823 loss_thr: 0.4291 loss_db: 0.1018 2022/11/02 19:27:14 - mmengine - INFO - Epoch(train) [657][55/63] lr: 1.0604e-03 eta: 5:42:10 time: 0.5323 data_time: 0.0302 memory: 14901 loss: 1.2298 loss_prob: 0.6577 loss_thr: 0.4581 loss_db: 0.1140 2022/11/02 19:27:17 - mmengine - INFO - Epoch(train) [657][60/63] lr: 1.0604e-03 eta: 5:42:03 time: 0.5405 data_time: 0.0207 memory: 14901 loss: 1.2803 loss_prob: 0.6968 loss_thr: 0.4681 loss_db: 0.1154 2022/11/02 19:27:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:27:24 - mmengine - INFO - Epoch(train) [658][5/63] lr: 1.0586e-03 eta: 5:42:03 time: 0.7651 data_time: 0.2155 memory: 14901 loss: 1.0855 loss_prob: 0.5754 loss_thr: 0.4118 loss_db: 0.0983 2022/11/02 19:27:27 - mmengine - INFO - Epoch(train) [658][10/63] lr: 1.0586e-03 eta: 5:41:56 time: 0.8061 data_time: 0.2220 memory: 14901 loss: 1.1833 loss_prob: 0.6220 loss_thr: 0.4544 loss_db: 0.1069 2022/11/02 19:27:30 - mmengine - INFO - Epoch(train) [658][15/63] lr: 1.0586e-03 eta: 5:41:56 time: 0.5962 data_time: 0.0174 memory: 14901 loss: 1.2292 loss_prob: 0.6518 loss_thr: 0.4663 loss_db: 0.1111 2022/11/02 19:27:32 - mmengine - INFO - Epoch(train) [658][20/63] lr: 1.0586e-03 eta: 5:41:49 time: 0.5674 data_time: 0.0109 memory: 14901 loss: 1.1550 loss_prob: 0.6203 loss_thr: 0.4302 loss_db: 0.1046 2022/11/02 19:27:36 - mmengine - INFO - Epoch(train) [658][25/63] lr: 1.0586e-03 eta: 5:41:49 time: 0.6321 data_time: 0.0188 memory: 14901 loss: 1.1528 loss_prob: 0.6183 loss_thr: 0.4290 loss_db: 0.1055 2022/11/02 19:27:39 - mmengine - INFO - Epoch(train) [658][30/63] lr: 1.0586e-03 eta: 5:41:44 time: 0.6574 data_time: 0.0480 memory: 14901 loss: 1.0920 loss_prob: 0.5659 loss_thr: 0.4277 loss_db: 0.0985 2022/11/02 19:27:42 - mmengine - INFO - Epoch(train) [658][35/63] lr: 1.0586e-03 eta: 5:41:44 time: 0.6038 data_time: 0.0465 memory: 14901 loss: 1.0953 loss_prob: 0.5611 loss_thr: 0.4382 loss_db: 0.0959 2022/11/02 19:27:45 - mmengine - INFO - Epoch(train) [658][40/63] lr: 1.0586e-03 eta: 5:41:38 time: 0.5797 data_time: 0.0177 memory: 14901 loss: 1.2929 loss_prob: 0.6974 loss_thr: 0.4771 loss_db: 0.1184 2022/11/02 19:27:48 - mmengine - INFO - Epoch(train) [658][45/63] lr: 1.0586e-03 eta: 5:41:38 time: 0.5632 data_time: 0.0098 memory: 14901 loss: 1.3694 loss_prob: 0.7783 loss_thr: 0.4572 loss_db: 0.1339 2022/11/02 19:27:50 - mmengine - INFO - Epoch(train) [658][50/63] lr: 1.0586e-03 eta: 5:41:31 time: 0.5727 data_time: 0.0286 memory: 14901 loss: 1.2148 loss_prob: 0.6808 loss_thr: 0.4181 loss_db: 0.1159 2022/11/02 19:27:53 - mmengine - INFO - Epoch(train) [658][55/63] lr: 1.0586e-03 eta: 5:41:31 time: 0.5210 data_time: 0.0314 memory: 14901 loss: 1.1049 loss_prob: 0.5920 loss_thr: 0.4135 loss_db: 0.0995 2022/11/02 19:27:56 - mmengine - INFO - Epoch(train) [658][60/63] lr: 1.0586e-03 eta: 5:41:25 time: 0.5299 data_time: 0.0128 memory: 14901 loss: 1.1492 loss_prob: 0.6225 loss_thr: 0.4211 loss_db: 0.1056 2022/11/02 19:27:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:28:03 - mmengine - INFO - Epoch(train) [659][5/63] lr: 1.0569e-03 eta: 5:41:25 time: 0.8216 data_time: 0.2593 memory: 14901 loss: 1.1060 loss_prob: 0.5812 loss_thr: 0.4242 loss_db: 0.1006 2022/11/02 19:28:05 - mmengine - INFO - Epoch(train) [659][10/63] lr: 1.0569e-03 eta: 5:41:17 time: 0.8276 data_time: 0.2588 memory: 14901 loss: 1.1167 loss_prob: 0.5847 loss_thr: 0.4309 loss_db: 0.1011 2022/11/02 19:28:08 - mmengine - INFO - Epoch(train) [659][15/63] lr: 1.0569e-03 eta: 5:41:17 time: 0.5337 data_time: 0.0121 memory: 14901 loss: 1.0945 loss_prob: 0.5767 loss_thr: 0.4175 loss_db: 0.1003 2022/11/02 19:28:11 - mmengine - INFO - Epoch(train) [659][20/63] lr: 1.0569e-03 eta: 5:41:11 time: 0.5461 data_time: 0.0109 memory: 14901 loss: 1.0525 loss_prob: 0.5470 loss_thr: 0.4113 loss_db: 0.0941 2022/11/02 19:28:13 - mmengine - INFO - Epoch(train) [659][25/63] lr: 1.0569e-03 eta: 5:41:11 time: 0.5448 data_time: 0.0206 memory: 14901 loss: 1.1313 loss_prob: 0.5973 loss_thr: 0.4326 loss_db: 0.1015 2022/11/02 19:28:18 - mmengine - INFO - Epoch(train) [659][30/63] lr: 1.0569e-03 eta: 5:41:06 time: 0.7262 data_time: 0.0539 memory: 14901 loss: 1.1292 loss_prob: 0.6098 loss_thr: 0.4189 loss_db: 0.1006 2022/11/02 19:28:21 - mmengine - INFO - Epoch(train) [659][35/63] lr: 1.0569e-03 eta: 5:41:06 time: 0.7383 data_time: 0.0471 memory: 14901 loss: 1.1028 loss_prob: 0.5881 loss_thr: 0.4160 loss_db: 0.0987 2022/11/02 19:28:24 - mmengine - INFO - Epoch(train) [659][40/63] lr: 1.0569e-03 eta: 5:41:00 time: 0.5688 data_time: 0.0152 memory: 14901 loss: 1.1505 loss_prob: 0.6066 loss_thr: 0.4390 loss_db: 0.1049 2022/11/02 19:28:27 - mmengine - INFO - Epoch(train) [659][45/63] lr: 1.0569e-03 eta: 5:41:00 time: 0.5792 data_time: 0.0108 memory: 14901 loss: 1.2064 loss_prob: 0.6447 loss_thr: 0.4526 loss_db: 0.1092 2022/11/02 19:28:30 - mmengine - INFO - Epoch(train) [659][50/63] lr: 1.0569e-03 eta: 5:40:54 time: 0.6257 data_time: 0.0275 memory: 14901 loss: 1.2672 loss_prob: 0.6841 loss_thr: 0.4662 loss_db: 0.1168 2022/11/02 19:28:32 - mmengine - INFO - Epoch(train) [659][55/63] lr: 1.0569e-03 eta: 5:40:54 time: 0.5814 data_time: 0.0309 memory: 14901 loss: 1.2539 loss_prob: 0.6772 loss_thr: 0.4617 loss_db: 0.1150 2022/11/02 19:28:36 - mmengine - INFO - Epoch(train) [659][60/63] lr: 1.0569e-03 eta: 5:40:48 time: 0.5623 data_time: 0.0149 memory: 14901 loss: 1.1572 loss_prob: 0.6219 loss_thr: 0.4297 loss_db: 0.1055 2022/11/02 19:28:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:28:42 - mmengine - INFO - Epoch(train) [660][5/63] lr: 1.0551e-03 eta: 5:40:48 time: 0.8219 data_time: 0.2489 memory: 14901 loss: 1.2447 loss_prob: 0.6715 loss_thr: 0.4598 loss_db: 0.1134 2022/11/02 19:28:45 - mmengine - INFO - Epoch(train) [660][10/63] lr: 1.0551e-03 eta: 5:40:40 time: 0.8199 data_time: 0.2472 memory: 14901 loss: 1.1741 loss_prob: 0.6222 loss_thr: 0.4464 loss_db: 0.1055 2022/11/02 19:28:49 - mmengine - INFO - Epoch(train) [660][15/63] lr: 1.0551e-03 eta: 5:40:40 time: 0.6551 data_time: 0.0136 memory: 14901 loss: 1.1576 loss_prob: 0.6168 loss_thr: 0.4354 loss_db: 0.1054 2022/11/02 19:28:52 - mmengine - INFO - Epoch(train) [660][20/63] lr: 1.0551e-03 eta: 5:40:35 time: 0.6433 data_time: 0.0133 memory: 14901 loss: 1.1463 loss_prob: 0.6116 loss_thr: 0.4309 loss_db: 0.1038 2022/11/02 19:28:55 - mmengine - INFO - Epoch(train) [660][25/63] lr: 1.0551e-03 eta: 5:40:35 time: 0.6021 data_time: 0.0136 memory: 14901 loss: 1.1348 loss_prob: 0.5906 loss_thr: 0.4413 loss_db: 0.1029 2022/11/02 19:28:58 - mmengine - INFO - Epoch(train) [660][30/63] lr: 1.0551e-03 eta: 5:40:29 time: 0.6347 data_time: 0.0480 memory: 14901 loss: 1.1372 loss_prob: 0.5892 loss_thr: 0.4446 loss_db: 0.1035 2022/11/02 19:29:01 - mmengine - INFO - Epoch(train) [660][35/63] lr: 1.0551e-03 eta: 5:40:29 time: 0.5781 data_time: 0.0460 memory: 14901 loss: 1.1374 loss_prob: 0.5988 loss_thr: 0.4341 loss_db: 0.1045 2022/11/02 19:29:04 - mmengine - INFO - Epoch(train) [660][40/63] lr: 1.0551e-03 eta: 5:40:22 time: 0.5413 data_time: 0.0129 memory: 14901 loss: 1.2016 loss_prob: 0.6454 loss_thr: 0.4462 loss_db: 0.1100 2022/11/02 19:29:06 - mmengine - INFO - Epoch(train) [660][45/63] lr: 1.0551e-03 eta: 5:40:22 time: 0.5385 data_time: 0.0115 memory: 14901 loss: 1.1778 loss_prob: 0.6289 loss_thr: 0.4406 loss_db: 0.1084 2022/11/02 19:29:09 - mmengine - INFO - Epoch(train) [660][50/63] lr: 1.0551e-03 eta: 5:40:16 time: 0.5091 data_time: 0.0157 memory: 14901 loss: 1.1843 loss_prob: 0.6274 loss_thr: 0.4472 loss_db: 0.1096 2022/11/02 19:29:11 - mmengine - INFO - Epoch(train) [660][55/63] lr: 1.0551e-03 eta: 5:40:16 time: 0.5352 data_time: 0.0310 memory: 14901 loss: 1.2859 loss_prob: 0.6958 loss_thr: 0.4720 loss_db: 0.1180 2022/11/02 19:29:14 - mmengine - INFO - Epoch(train) [660][60/63] lr: 1.0551e-03 eta: 5:40:09 time: 0.5117 data_time: 0.0249 memory: 14901 loss: 1.2834 loss_prob: 0.6959 loss_thr: 0.4687 loss_db: 0.1187 2022/11/02 19:29:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:29:15 - mmengine - INFO - Saving checkpoint at 660 epochs 2022/11/02 19:29:19 - mmengine - INFO - Epoch(val) [660][5/500] eta: 5:40:09 time: 0.0467 data_time: 0.0063 memory: 14901 2022/11/02 19:29:19 - mmengine - INFO - Epoch(val) [660][10/500] eta: 0:00:21 time: 0.0449 data_time: 0.0060 memory: 1008 2022/11/02 19:29:19 - mmengine - INFO - Epoch(val) [660][15/500] eta: 0:00:21 time: 0.0375 data_time: 0.0026 memory: 1008 2022/11/02 19:29:20 - mmengine - INFO - Epoch(val) [660][20/500] eta: 0:00:17 time: 0.0371 data_time: 0.0024 memory: 1008 2022/11/02 19:29:20 - mmengine - INFO - Epoch(val) [660][25/500] eta: 0:00:17 time: 0.0432 data_time: 0.0032 memory: 1008 2022/11/02 19:29:20 - mmengine - INFO - Epoch(val) [660][30/500] eta: 0:00:22 time: 0.0489 data_time: 0.0034 memory: 1008 2022/11/02 19:29:20 - mmengine - INFO - Epoch(val) [660][35/500] eta: 0:00:22 time: 0.0435 data_time: 0.0029 memory: 1008 2022/11/02 19:29:21 - mmengine - INFO - Epoch(val) [660][40/500] eta: 0:00:19 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 19:29:21 - mmengine - INFO - Epoch(val) [660][45/500] eta: 0:00:19 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/02 19:29:21 - mmengine - INFO - Epoch(val) [660][50/500] eta: 0:00:18 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 19:29:21 - mmengine - INFO - Epoch(val) [660][55/500] eta: 0:00:18 time: 0.0491 data_time: 0.0030 memory: 1008 2022/11/02 19:29:21 - mmengine - INFO - Epoch(val) [660][60/500] eta: 0:00:19 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 19:29:22 - mmengine - INFO - Epoch(val) [660][65/500] eta: 0:00:19 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/02 19:29:22 - mmengine - INFO - Epoch(val) [660][70/500] eta: 0:00:20 time: 0.0467 data_time: 0.0030 memory: 1008 2022/11/02 19:29:22 - mmengine - INFO - Epoch(val) [660][75/500] eta: 0:00:20 time: 0.0463 data_time: 0.0032 memory: 1008 2022/11/02 19:29:22 - mmengine - INFO - Epoch(val) [660][80/500] eta: 0:00:19 time: 0.0475 data_time: 0.0043 memory: 1008 2022/11/02 19:29:23 - mmengine - INFO - Epoch(val) [660][85/500] eta: 0:00:19 time: 0.0434 data_time: 0.0040 memory: 1008 2022/11/02 19:29:23 - mmengine - INFO - Epoch(val) [660][90/500] eta: 0:00:20 time: 0.0488 data_time: 0.0031 memory: 1008 2022/11/02 19:29:23 - mmengine - INFO - Epoch(val) [660][95/500] eta: 0:00:20 time: 0.0503 data_time: 0.0030 memory: 1008 2022/11/02 19:29:23 - mmengine - INFO - Epoch(val) [660][100/500] eta: 0:00:16 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 19:29:23 - mmengine - INFO - Epoch(val) [660][105/500] eta: 0:00:16 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 19:29:24 - mmengine - INFO - Epoch(val) [660][110/500] eta: 0:00:14 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 19:29:24 - mmengine - INFO - Epoch(val) [660][115/500] eta: 0:00:14 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 19:29:24 - mmengine - INFO - Epoch(val) [660][120/500] eta: 0:00:15 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 19:29:24 - mmengine - INFO - Epoch(val) [660][125/500] eta: 0:00:15 time: 0.0399 data_time: 0.0028 memory: 1008 2022/11/02 19:29:24 - mmengine - INFO - Epoch(val) [660][130/500] eta: 0:00:14 time: 0.0388 data_time: 0.0025 memory: 1008 2022/11/02 19:29:25 - mmengine - INFO - Epoch(val) [660][135/500] eta: 0:00:14 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/02 19:29:25 - mmengine - INFO - Epoch(val) [660][140/500] eta: 0:00:14 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 19:29:25 - mmengine - INFO - Epoch(val) [660][145/500] eta: 0:00:14 time: 0.0426 data_time: 0.0032 memory: 1008 2022/11/02 19:29:25 - mmengine - INFO - Epoch(val) [660][150/500] eta: 0:00:15 time: 0.0442 data_time: 0.0034 memory: 1008 2022/11/02 19:29:26 - mmengine - INFO - Epoch(val) [660][155/500] eta: 0:00:15 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/02 19:29:26 - mmengine - INFO - Epoch(val) [660][160/500] eta: 0:00:14 time: 0.0425 data_time: 0.0030 memory: 1008 2022/11/02 19:29:26 - mmengine - INFO - Epoch(val) [660][165/500] eta: 0:00:14 time: 0.0406 data_time: 0.0029 memory: 1008 2022/11/02 19:29:26 - mmengine - INFO - Epoch(val) [660][170/500] eta: 0:00:14 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 19:29:26 - mmengine - INFO - Epoch(val) [660][175/500] eta: 0:00:14 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 19:29:27 - mmengine - INFO - Epoch(val) [660][180/500] eta: 0:00:13 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 19:29:27 - mmengine - INFO - Epoch(val) [660][185/500] eta: 0:00:13 time: 0.0479 data_time: 0.0030 memory: 1008 2022/11/02 19:29:27 - mmengine - INFO - Epoch(val) [660][190/500] eta: 0:00:14 time: 0.0469 data_time: 0.0031 memory: 1008 2022/11/02 19:29:27 - mmengine - INFO - Epoch(val) [660][195/500] eta: 0:00:14 time: 0.0404 data_time: 0.0029 memory: 1008 2022/11/02 19:29:27 - mmengine - INFO - Epoch(val) [660][200/500] eta: 0:00:13 time: 0.0457 data_time: 0.0029 memory: 1008 2022/11/02 19:29:28 - mmengine - INFO - Epoch(val) [660][205/500] eta: 0:00:13 time: 0.0457 data_time: 0.0029 memory: 1008 2022/11/02 19:29:28 - mmengine - INFO - Epoch(val) [660][210/500] eta: 0:00:10 time: 0.0373 data_time: 0.0028 memory: 1008 2022/11/02 19:29:28 - mmengine - INFO - Epoch(val) [660][215/500] eta: 0:00:10 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 19:29:28 - mmengine - INFO - Epoch(val) [660][220/500] eta: 0:00:10 time: 0.0389 data_time: 0.0026 memory: 1008 2022/11/02 19:29:28 - mmengine - INFO - Epoch(val) [660][225/500] eta: 0:00:10 time: 0.0424 data_time: 0.0027 memory: 1008 2022/11/02 19:29:29 - mmengine - INFO - Epoch(val) [660][230/500] eta: 0:00:11 time: 0.0414 data_time: 0.0029 memory: 1008 2022/11/02 19:29:29 - mmengine - INFO - Epoch(val) [660][235/500] eta: 0:00:11 time: 0.0397 data_time: 0.0028 memory: 1008 2022/11/02 19:29:29 - mmengine - INFO - Epoch(val) [660][240/500] eta: 0:00:11 time: 0.0435 data_time: 0.0031 memory: 1008 2022/11/02 19:29:29 - mmengine - INFO - Epoch(val) [660][245/500] eta: 0:00:11 time: 0.0404 data_time: 0.0030 memory: 1008 2022/11/02 19:29:30 - mmengine - INFO - Epoch(val) [660][250/500] eta: 0:00:09 time: 0.0389 data_time: 0.0030 memory: 1008 2022/11/02 19:29:30 - mmengine - INFO - Epoch(val) [660][255/500] eta: 0:00:09 time: 0.0452 data_time: 0.0031 memory: 1008 2022/11/02 19:29:30 - mmengine - INFO - Epoch(val) [660][260/500] eta: 0:00:11 time: 0.0470 data_time: 0.0030 memory: 1008 2022/11/02 19:29:30 - mmengine - INFO - Epoch(val) [660][265/500] eta: 0:00:11 time: 0.0492 data_time: 0.0036 memory: 1008 2022/11/02 19:29:31 - mmengine - INFO - Epoch(val) [660][270/500] eta: 0:00:12 time: 0.0542 data_time: 0.0042 memory: 1008 2022/11/02 19:29:31 - mmengine - INFO - Epoch(val) [660][275/500] eta: 0:00:12 time: 0.0502 data_time: 0.0041 memory: 1008 2022/11/02 19:29:31 - mmengine - INFO - Epoch(val) [660][280/500] eta: 0:00:11 time: 0.0520 data_time: 0.0041 memory: 1008 2022/11/02 19:29:31 - mmengine - INFO - Epoch(val) [660][285/500] eta: 0:00:11 time: 0.0552 data_time: 0.0040 memory: 1008 2022/11/02 19:29:32 - mmengine - INFO - Epoch(val) [660][290/500] eta: 0:00:11 time: 0.0553 data_time: 0.0042 memory: 1008 2022/11/02 19:29:32 - mmengine - INFO - Epoch(val) [660][295/500] eta: 0:00:11 time: 0.0557 data_time: 0.0046 memory: 1008 2022/11/02 19:29:32 - mmengine - INFO - Epoch(val) [660][300/500] eta: 0:00:11 time: 0.0572 data_time: 0.0052 memory: 1008 2022/11/02 19:29:32 - mmengine - INFO - Epoch(val) [660][305/500] eta: 0:00:11 time: 0.0587 data_time: 0.0052 memory: 1008 2022/11/02 19:29:33 - mmengine - INFO - Epoch(val) [660][310/500] eta: 0:00:09 time: 0.0526 data_time: 0.0041 memory: 1008 2022/11/02 19:29:33 - mmengine - INFO - Epoch(val) [660][315/500] eta: 0:00:09 time: 0.0518 data_time: 0.0035 memory: 1008 2022/11/02 19:29:33 - mmengine - INFO - Epoch(val) [660][320/500] eta: 0:00:08 time: 0.0479 data_time: 0.0030 memory: 1008 2022/11/02 19:29:33 - mmengine - INFO - Epoch(val) [660][325/500] eta: 0:00:08 time: 0.0525 data_time: 0.0027 memory: 1008 2022/11/02 19:29:34 - mmengine - INFO - Epoch(val) [660][330/500] eta: 0:00:08 time: 0.0506 data_time: 0.0026 memory: 1008 2022/11/02 19:29:34 - mmengine - INFO - Epoch(val) [660][335/500] eta: 0:00:08 time: 0.0365 data_time: 0.0024 memory: 1008 2022/11/02 19:29:34 - mmengine - INFO - Epoch(val) [660][340/500] eta: 0:00:07 time: 0.0489 data_time: 0.0026 memory: 1008 2022/11/02 19:29:34 - mmengine - INFO - Epoch(val) [660][345/500] eta: 0:00:07 time: 0.0539 data_time: 0.0028 memory: 1008 2022/11/02 19:29:35 - mmengine - INFO - Epoch(val) [660][350/500] eta: 0:00:07 time: 0.0475 data_time: 0.0028 memory: 1008 2022/11/02 19:29:35 - mmengine - INFO - Epoch(val) [660][355/500] eta: 0:00:07 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/02 19:29:35 - mmengine - INFO - Epoch(val) [660][360/500] eta: 0:00:05 time: 0.0387 data_time: 0.0025 memory: 1008 2022/11/02 19:29:35 - mmengine - INFO - Epoch(val) [660][365/500] eta: 0:00:05 time: 0.0420 data_time: 0.0023 memory: 1008 2022/11/02 19:29:35 - mmengine - INFO - Epoch(val) [660][370/500] eta: 0:00:05 time: 0.0416 data_time: 0.0029 memory: 1008 2022/11/02 19:29:36 - mmengine - INFO - Epoch(val) [660][375/500] eta: 0:00:05 time: 0.0411 data_time: 0.0032 memory: 1008 2022/11/02 19:29:36 - mmengine - INFO - Epoch(val) [660][380/500] eta: 0:00:05 time: 0.0474 data_time: 0.0031 memory: 1008 2022/11/02 19:29:36 - mmengine - INFO - Epoch(val) [660][385/500] eta: 0:00:05 time: 0.0457 data_time: 0.0029 memory: 1008 2022/11/02 19:29:36 - mmengine - INFO - Epoch(val) [660][390/500] eta: 0:00:04 time: 0.0429 data_time: 0.0031 memory: 1008 2022/11/02 19:29:37 - mmengine - INFO - Epoch(val) [660][395/500] eta: 0:00:04 time: 0.0438 data_time: 0.0032 memory: 1008 2022/11/02 19:29:37 - mmengine - INFO - Epoch(val) [660][400/500] eta: 0:00:04 time: 0.0414 data_time: 0.0030 memory: 1008 2022/11/02 19:29:37 - mmengine - INFO - Epoch(val) [660][405/500] eta: 0:00:04 time: 0.0406 data_time: 0.0029 memory: 1008 2022/11/02 19:29:37 - mmengine - INFO - Epoch(val) [660][410/500] eta: 0:00:03 time: 0.0436 data_time: 0.0029 memory: 1008 2022/11/02 19:29:37 - mmengine - INFO - Epoch(val) [660][415/500] eta: 0:00:03 time: 0.0451 data_time: 0.0031 memory: 1008 2022/11/02 19:29:38 - mmengine - INFO - Epoch(val) [660][420/500] eta: 0:00:03 time: 0.0402 data_time: 0.0030 memory: 1008 2022/11/02 19:29:38 - mmengine - INFO - Epoch(val) [660][425/500] eta: 0:00:03 time: 0.0377 data_time: 0.0026 memory: 1008 2022/11/02 19:29:38 - mmengine - INFO - Epoch(val) [660][430/500] eta: 0:00:02 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 19:29:38 - mmengine - INFO - Epoch(val) [660][435/500] eta: 0:00:02 time: 0.0380 data_time: 0.0025 memory: 1008 2022/11/02 19:29:38 - mmengine - INFO - Epoch(val) [660][440/500] eta: 0:00:02 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 19:29:39 - mmengine - INFO - Epoch(val) [660][445/500] eta: 0:00:02 time: 0.0428 data_time: 0.0028 memory: 1008 2022/11/02 19:29:39 - mmengine - INFO - Epoch(val) [660][450/500] eta: 0:00:02 time: 0.0487 data_time: 0.0033 memory: 1008 2022/11/02 19:29:39 - mmengine - INFO - Epoch(val) [660][455/500] eta: 0:00:02 time: 0.0503 data_time: 0.0036 memory: 1008 2022/11/02 19:29:39 - mmengine - INFO - Epoch(val) [660][460/500] eta: 0:00:01 time: 0.0431 data_time: 0.0033 memory: 1008 2022/11/02 19:29:40 - mmengine - INFO - Epoch(val) [660][465/500] eta: 0:00:01 time: 0.0394 data_time: 0.0030 memory: 1008 2022/11/02 19:29:40 - mmengine - INFO - Epoch(val) [660][470/500] eta: 0:00:01 time: 0.0403 data_time: 0.0030 memory: 1008 2022/11/02 19:29:40 - mmengine - INFO - Epoch(val) [660][475/500] eta: 0:00:01 time: 0.0377 data_time: 0.0026 memory: 1008 2022/11/02 19:29:40 - mmengine - INFO - Epoch(val) [660][480/500] eta: 0:00:00 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 19:29:40 - mmengine - INFO - Epoch(val) [660][485/500] eta: 0:00:00 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/02 19:29:41 - mmengine - INFO - Epoch(val) [660][490/500] eta: 0:00:00 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 19:29:41 - mmengine - INFO - Epoch(val) [660][495/500] eta: 0:00:00 time: 0.0439 data_time: 0.0031 memory: 1008 2022/11/02 19:29:41 - mmengine - INFO - Epoch(val) [660][500/500] eta: 0:00:00 time: 0.0444 data_time: 0.0035 memory: 1008 2022/11/02 19:29:41 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8093, precision: 0.7386, hmean: 0.7723 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8093, precision: 0.7948, hmean: 0.8020 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8093, precision: 0.8248, hmean: 0.8170 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8036, precision: 0.8555, hmean: 0.8287 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7727, precision: 0.8843, hmean: 0.8248 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5932, precision: 0.9284, hmean: 0.7239 2022/11/02 19:29:41 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0688, precision: 0.9533, hmean: 0.1284 2022/11/02 19:29:41 - mmengine - INFO - Epoch(val) [660][500/500] icdar/precision: 0.8555 icdar/recall: 0.8036 icdar/hmean: 0.8287 2022/11/02 19:29:46 - mmengine - INFO - Epoch(train) [661][5/63] lr: 1.0534e-03 eta: 0:00:00 time: 0.7471 data_time: 0.2528 memory: 14901 loss: 1.2462 loss_prob: 0.6755 loss_thr: 0.4548 loss_db: 0.1159 2022/11/02 19:29:49 - mmengine - INFO - Epoch(train) [661][10/63] lr: 1.0534e-03 eta: 5:40:01 time: 0.8289 data_time: 0.2509 memory: 14901 loss: 1.3236 loss_prob: 0.7215 loss_thr: 0.4766 loss_db: 0.1256 2022/11/02 19:29:52 - mmengine - INFO - Epoch(train) [661][15/63] lr: 1.0534e-03 eta: 5:40:01 time: 0.6205 data_time: 0.0088 memory: 14901 loss: 1.1813 loss_prob: 0.6334 loss_thr: 0.4385 loss_db: 0.1095 2022/11/02 19:29:55 - mmengine - INFO - Epoch(train) [661][20/63] lr: 1.0534e-03 eta: 5:39:56 time: 0.6079 data_time: 0.0114 memory: 14901 loss: 1.1268 loss_prob: 0.6023 loss_thr: 0.4194 loss_db: 0.1051 2022/11/02 19:29:58 - mmengine - INFO - Epoch(train) [661][25/63] lr: 1.0534e-03 eta: 5:39:56 time: 0.5526 data_time: 0.0241 memory: 14901 loss: 1.2053 loss_prob: 0.6509 loss_thr: 0.4403 loss_db: 0.1142 2022/11/02 19:30:01 - mmengine - INFO - Epoch(train) [661][30/63] lr: 1.0534e-03 eta: 5:39:49 time: 0.5613 data_time: 0.0432 memory: 14901 loss: 1.2781 loss_prob: 0.7008 loss_thr: 0.4613 loss_db: 0.1161 2022/11/02 19:30:04 - mmengine - INFO - Epoch(train) [661][35/63] lr: 1.0534e-03 eta: 5:39:49 time: 0.5826 data_time: 0.0305 memory: 14901 loss: 1.2046 loss_prob: 0.6420 loss_thr: 0.4546 loss_db: 0.1079 2022/11/02 19:30:06 - mmengine - INFO - Epoch(train) [661][40/63] lr: 1.0534e-03 eta: 5:39:43 time: 0.5325 data_time: 0.0107 memory: 14901 loss: 1.2105 loss_prob: 0.6367 loss_thr: 0.4634 loss_db: 0.1105 2022/11/02 19:30:09 - mmengine - INFO - Epoch(train) [661][45/63] lr: 1.0534e-03 eta: 5:39:43 time: 0.5173 data_time: 0.0105 memory: 14901 loss: 1.2524 loss_prob: 0.6725 loss_thr: 0.4661 loss_db: 0.1138 2022/11/02 19:30:12 - mmengine - INFO - Epoch(train) [661][50/63] lr: 1.0534e-03 eta: 5:39:36 time: 0.5722 data_time: 0.0186 memory: 14901 loss: 1.1829 loss_prob: 0.6301 loss_thr: 0.4463 loss_db: 0.1065 2022/11/02 19:30:16 - mmengine - INFO - Epoch(train) [661][55/63] lr: 1.0534e-03 eta: 5:39:36 time: 0.6913 data_time: 0.0321 memory: 14901 loss: 1.1614 loss_prob: 0.6188 loss_thr: 0.4367 loss_db: 0.1058 2022/11/02 19:30:19 - mmengine - INFO - Epoch(train) [661][60/63] lr: 1.0534e-03 eta: 5:39:31 time: 0.6587 data_time: 0.0254 memory: 14901 loss: 1.1024 loss_prob: 0.5819 loss_thr: 0.4205 loss_db: 0.1000 2022/11/02 19:30:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:30:26 - mmengine - INFO - Epoch(train) [662][5/63] lr: 1.0516e-03 eta: 5:39:31 time: 0.8290 data_time: 0.2263 memory: 14901 loss: 1.1543 loss_prob: 0.6504 loss_thr: 0.4029 loss_db: 0.1011 2022/11/02 19:30:28 - mmengine - INFO - Epoch(train) [662][10/63] lr: 1.0516e-03 eta: 5:39:24 time: 0.8357 data_time: 0.2285 memory: 14901 loss: 1.2193 loss_prob: 0.6913 loss_thr: 0.4211 loss_db: 0.1070 2022/11/02 19:30:32 - mmengine - INFO - Epoch(train) [662][15/63] lr: 1.0516e-03 eta: 5:39:24 time: 0.5684 data_time: 0.0127 memory: 14901 loss: 1.0529 loss_prob: 0.5562 loss_thr: 0.4031 loss_db: 0.0937 2022/11/02 19:30:34 - mmengine - INFO - Epoch(train) [662][20/63] lr: 1.0516e-03 eta: 5:39:17 time: 0.5647 data_time: 0.0106 memory: 14901 loss: 1.0520 loss_prob: 0.5581 loss_thr: 0.3993 loss_db: 0.0945 2022/11/02 19:30:37 - mmengine - INFO - Epoch(train) [662][25/63] lr: 1.0516e-03 eta: 5:39:17 time: 0.4956 data_time: 0.0213 memory: 14901 loss: 1.1396 loss_prob: 0.6097 loss_thr: 0.4267 loss_db: 0.1032 2022/11/02 19:30:40 - mmengine - INFO - Epoch(train) [662][30/63] lr: 1.0516e-03 eta: 5:39:11 time: 0.5388 data_time: 0.0405 memory: 14901 loss: 1.2067 loss_prob: 0.6520 loss_thr: 0.4436 loss_db: 0.1111 2022/11/02 19:30:42 - mmengine - INFO - Epoch(train) [662][35/63] lr: 1.0516e-03 eta: 5:39:11 time: 0.5413 data_time: 0.0301 memory: 14901 loss: 1.2118 loss_prob: 0.6518 loss_thr: 0.4471 loss_db: 0.1129 2022/11/02 19:30:45 - mmengine - INFO - Epoch(train) [662][40/63] lr: 1.0516e-03 eta: 5:39:04 time: 0.5345 data_time: 0.0079 memory: 14901 loss: 1.1821 loss_prob: 0.6298 loss_thr: 0.4443 loss_db: 0.1079 2022/11/02 19:30:48 - mmengine - INFO - Epoch(train) [662][45/63] lr: 1.0516e-03 eta: 5:39:04 time: 0.5569 data_time: 0.0095 memory: 14901 loss: 1.1054 loss_prob: 0.5841 loss_thr: 0.4216 loss_db: 0.0998 2022/11/02 19:30:51 - mmengine - INFO - Epoch(train) [662][50/63] lr: 1.0516e-03 eta: 5:38:58 time: 0.6152 data_time: 0.0225 memory: 14901 loss: 1.0509 loss_prob: 0.5478 loss_thr: 0.4076 loss_db: 0.0954 2022/11/02 19:30:54 - mmengine - INFO - Epoch(train) [662][55/63] lr: 1.0516e-03 eta: 5:38:58 time: 0.6792 data_time: 0.0472 memory: 14901 loss: 1.0815 loss_prob: 0.5683 loss_thr: 0.4134 loss_db: 0.0998 2022/11/02 19:30:57 - mmengine - INFO - Epoch(train) [662][60/63] lr: 1.0516e-03 eta: 5:38:52 time: 0.5849 data_time: 0.0373 memory: 14901 loss: 1.1296 loss_prob: 0.5991 loss_thr: 0.4280 loss_db: 0.1025 2022/11/02 19:30:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:31:06 - mmengine - INFO - Epoch(train) [663][5/63] lr: 1.0499e-03 eta: 5:38:52 time: 0.9632 data_time: 0.2361 memory: 14901 loss: 1.2596 loss_prob: 0.6985 loss_thr: 0.4449 loss_db: 0.1162 2022/11/02 19:31:08 - mmengine - INFO - Epoch(train) [663][10/63] lr: 1.0499e-03 eta: 5:38:46 time: 0.9852 data_time: 0.2421 memory: 14901 loss: 1.1773 loss_prob: 0.6320 loss_thr: 0.4404 loss_db: 0.1049 2022/11/02 19:31:12 - mmengine - INFO - Epoch(train) [663][15/63] lr: 1.0499e-03 eta: 5:38:46 time: 0.6162 data_time: 0.0163 memory: 14901 loss: 1.2125 loss_prob: 0.6466 loss_thr: 0.4536 loss_db: 0.1123 2022/11/02 19:31:14 - mmengine - INFO - Epoch(train) [663][20/63] lr: 1.0499e-03 eta: 5:38:40 time: 0.6159 data_time: 0.0105 memory: 14901 loss: 1.2007 loss_prob: 0.6358 loss_thr: 0.4539 loss_db: 0.1110 2022/11/02 19:31:17 - mmengine - INFO - Epoch(train) [663][25/63] lr: 1.0499e-03 eta: 5:38:40 time: 0.5435 data_time: 0.0239 memory: 14901 loss: 1.1433 loss_prob: 0.6042 loss_thr: 0.4351 loss_db: 0.1040 2022/11/02 19:31:21 - mmengine - INFO - Epoch(train) [663][30/63] lr: 1.0499e-03 eta: 5:38:34 time: 0.6152 data_time: 0.0348 memory: 14901 loss: 1.0579 loss_prob: 0.5573 loss_thr: 0.4038 loss_db: 0.0969 2022/11/02 19:31:24 - mmengine - INFO - Epoch(train) [663][35/63] lr: 1.0499e-03 eta: 5:38:34 time: 0.6989 data_time: 0.0255 memory: 14901 loss: 1.1052 loss_prob: 0.5773 loss_thr: 0.4261 loss_db: 0.1019 2022/11/02 19:31:27 - mmengine - INFO - Epoch(train) [663][40/63] lr: 1.0499e-03 eta: 5:38:29 time: 0.6323 data_time: 0.0151 memory: 14901 loss: 1.1352 loss_prob: 0.6033 loss_thr: 0.4268 loss_db: 0.1050 2022/11/02 19:31:29 - mmengine - INFO - Epoch(train) [663][45/63] lr: 1.0499e-03 eta: 5:38:29 time: 0.5261 data_time: 0.0113 memory: 14901 loss: 1.0793 loss_prob: 0.5673 loss_thr: 0.4155 loss_db: 0.0966 2022/11/02 19:31:33 - mmengine - INFO - Epoch(train) [663][50/63] lr: 1.0499e-03 eta: 5:38:23 time: 0.5967 data_time: 0.0289 memory: 14901 loss: 1.0787 loss_prob: 0.5717 loss_thr: 0.4109 loss_db: 0.0961 2022/11/02 19:31:36 - mmengine - INFO - Epoch(train) [663][55/63] lr: 1.0499e-03 eta: 5:38:23 time: 0.6342 data_time: 0.0284 memory: 14901 loss: 1.1251 loss_prob: 0.6040 loss_thr: 0.4181 loss_db: 0.1030 2022/11/02 19:31:38 - mmengine - INFO - Epoch(train) [663][60/63] lr: 1.0499e-03 eta: 5:38:16 time: 0.5495 data_time: 0.0136 memory: 14901 loss: 1.1985 loss_prob: 0.6447 loss_thr: 0.4437 loss_db: 0.1100 2022/11/02 19:31:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:31:46 - mmengine - INFO - Epoch(train) [664][5/63] lr: 1.0481e-03 eta: 5:38:16 time: 0.8406 data_time: 0.2340 memory: 14901 loss: 1.2242 loss_prob: 0.6481 loss_thr: 0.4656 loss_db: 0.1105 2022/11/02 19:31:50 - mmengine - INFO - Epoch(train) [664][10/63] lr: 1.0481e-03 eta: 5:38:10 time: 0.9957 data_time: 0.2336 memory: 14901 loss: 1.0939 loss_prob: 0.5764 loss_thr: 0.4183 loss_db: 0.0992 2022/11/02 19:31:53 - mmengine - INFO - Epoch(train) [664][15/63] lr: 1.0481e-03 eta: 5:38:10 time: 0.6822 data_time: 0.0110 memory: 14901 loss: 1.0673 loss_prob: 0.5610 loss_thr: 0.4067 loss_db: 0.0996 2022/11/02 19:31:56 - mmengine - INFO - Epoch(train) [664][20/63] lr: 1.0481e-03 eta: 5:38:04 time: 0.6271 data_time: 0.0093 memory: 14901 loss: 1.1409 loss_prob: 0.6037 loss_thr: 0.4331 loss_db: 0.1042 2022/11/02 19:31:59 - mmengine - INFO - Epoch(train) [664][25/63] lr: 1.0481e-03 eta: 5:38:04 time: 0.6106 data_time: 0.0245 memory: 14901 loss: 1.1667 loss_prob: 0.6266 loss_thr: 0.4333 loss_db: 0.1068 2022/11/02 19:32:02 - mmengine - INFO - Epoch(train) [664][30/63] lr: 1.0481e-03 eta: 5:37:59 time: 0.6145 data_time: 0.0494 memory: 14901 loss: 1.1654 loss_prob: 0.6242 loss_thr: 0.4335 loss_db: 0.1077 2022/11/02 19:32:05 - mmengine - INFO - Epoch(train) [664][35/63] lr: 1.0481e-03 eta: 5:37:59 time: 0.6247 data_time: 0.0360 memory: 14901 loss: 1.1282 loss_prob: 0.5953 loss_thr: 0.4317 loss_db: 0.1012 2022/11/02 19:32:08 - mmengine - INFO - Epoch(train) [664][40/63] lr: 1.0481e-03 eta: 5:37:53 time: 0.6101 data_time: 0.0128 memory: 14901 loss: 1.0496 loss_prob: 0.5357 loss_thr: 0.4205 loss_db: 0.0935 2022/11/02 19:32:11 - mmengine - INFO - Epoch(train) [664][45/63] lr: 1.0481e-03 eta: 5:37:53 time: 0.5764 data_time: 0.0103 memory: 14901 loss: 1.0389 loss_prob: 0.5296 loss_thr: 0.4140 loss_db: 0.0954 2022/11/02 19:32:14 - mmengine - INFO - Epoch(train) [664][50/63] lr: 1.0481e-03 eta: 5:37:46 time: 0.5538 data_time: 0.0250 memory: 14901 loss: 1.1334 loss_prob: 0.5916 loss_thr: 0.4378 loss_db: 0.1040 2022/11/02 19:32:17 - mmengine - INFO - Epoch(train) [664][55/63] lr: 1.0481e-03 eta: 5:37:46 time: 0.6333 data_time: 0.0360 memory: 14901 loss: 1.1189 loss_prob: 0.5792 loss_thr: 0.4411 loss_db: 0.0986 2022/11/02 19:32:20 - mmengine - INFO - Epoch(train) [664][60/63] lr: 1.0481e-03 eta: 5:37:41 time: 0.6670 data_time: 0.0206 memory: 14901 loss: 1.1233 loss_prob: 0.5872 loss_thr: 0.4375 loss_db: 0.0986 2022/11/02 19:32:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:32:28 - mmengine - INFO - Epoch(train) [665][5/63] lr: 1.0463e-03 eta: 5:37:41 time: 0.9162 data_time: 0.2998 memory: 14901 loss: 1.0604 loss_prob: 0.5607 loss_thr: 0.4022 loss_db: 0.0975 2022/11/02 19:32:31 - mmengine - INFO - Epoch(train) [665][10/63] lr: 1.0463e-03 eta: 5:37:34 time: 0.8882 data_time: 0.3002 memory: 14901 loss: 1.1410 loss_prob: 0.6094 loss_thr: 0.4277 loss_db: 0.1039 2022/11/02 19:32:33 - mmengine - INFO - Epoch(train) [665][15/63] lr: 1.0463e-03 eta: 5:37:34 time: 0.5022 data_time: 0.0101 memory: 14901 loss: 1.2680 loss_prob: 0.6929 loss_thr: 0.4581 loss_db: 0.1170 2022/11/02 19:32:36 - mmengine - INFO - Epoch(train) [665][20/63] lr: 1.0463e-03 eta: 5:37:27 time: 0.5399 data_time: 0.0078 memory: 14901 loss: 1.3713 loss_prob: 0.7678 loss_thr: 0.4781 loss_db: 0.1255 2022/11/02 19:32:39 - mmengine - INFO - Epoch(train) [665][25/63] lr: 1.0463e-03 eta: 5:37:27 time: 0.6322 data_time: 0.0371 memory: 14901 loss: 1.3452 loss_prob: 0.7436 loss_thr: 0.4814 loss_db: 0.1203 2022/11/02 19:32:42 - mmengine - INFO - Epoch(train) [665][30/63] lr: 1.0463e-03 eta: 5:37:21 time: 0.5704 data_time: 0.0416 memory: 14901 loss: 1.2715 loss_prob: 0.6822 loss_thr: 0.4742 loss_db: 0.1151 2022/11/02 19:32:45 - mmengine - INFO - Epoch(train) [665][35/63] lr: 1.0463e-03 eta: 5:37:21 time: 0.5688 data_time: 0.0167 memory: 14901 loss: 1.2330 loss_prob: 0.6655 loss_thr: 0.4535 loss_db: 0.1139 2022/11/02 19:32:49 - mmengine - INFO - Epoch(train) [665][40/63] lr: 1.0463e-03 eta: 5:37:16 time: 0.6870 data_time: 0.0150 memory: 14901 loss: 1.2209 loss_prob: 0.6490 loss_thr: 0.4625 loss_db: 0.1095 2022/11/02 19:32:52 - mmengine - INFO - Epoch(train) [665][45/63] lr: 1.0463e-03 eta: 5:37:16 time: 0.6647 data_time: 0.0112 memory: 14901 loss: 1.2171 loss_prob: 0.6388 loss_thr: 0.4708 loss_db: 0.1075 2022/11/02 19:32:55 - mmengine - INFO - Epoch(train) [665][50/63] lr: 1.0463e-03 eta: 5:37:10 time: 0.6538 data_time: 0.0263 memory: 14901 loss: 1.2125 loss_prob: 0.6542 loss_thr: 0.4464 loss_db: 0.1120 2022/11/02 19:32:58 - mmengine - INFO - Epoch(train) [665][55/63] lr: 1.0463e-03 eta: 5:37:10 time: 0.6021 data_time: 0.0286 memory: 14901 loss: 1.2286 loss_prob: 0.6693 loss_thr: 0.4458 loss_db: 0.1135 2022/11/02 19:33:02 - mmengine - INFO - Epoch(train) [665][60/63] lr: 1.0463e-03 eta: 5:37:04 time: 0.6309 data_time: 0.0153 memory: 14901 loss: 1.1946 loss_prob: 0.6438 loss_thr: 0.4427 loss_db: 0.1080 2022/11/02 19:33:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:33:08 - mmengine - INFO - Epoch(train) [666][5/63] lr: 1.0446e-03 eta: 5:37:04 time: 0.8655 data_time: 0.2182 memory: 14901 loss: 1.2615 loss_prob: 0.6851 loss_thr: 0.4609 loss_db: 0.1155 2022/11/02 19:33:11 - mmengine - INFO - Epoch(train) [666][10/63] lr: 1.0446e-03 eta: 5:36:57 time: 0.8128 data_time: 0.2248 memory: 14901 loss: 1.2448 loss_prob: 0.6694 loss_thr: 0.4617 loss_db: 0.1137 2022/11/02 19:33:15 - mmengine - INFO - Epoch(train) [666][15/63] lr: 1.0446e-03 eta: 5:36:57 time: 0.6152 data_time: 0.0147 memory: 14901 loss: 1.1186 loss_prob: 0.5832 loss_thr: 0.4312 loss_db: 0.1042 2022/11/02 19:33:17 - mmengine - INFO - Epoch(train) [666][20/63] lr: 1.0446e-03 eta: 5:36:51 time: 0.5846 data_time: 0.0115 memory: 14901 loss: 1.0858 loss_prob: 0.5694 loss_thr: 0.4189 loss_db: 0.0975 2022/11/02 19:33:20 - mmengine - INFO - Epoch(train) [666][25/63] lr: 1.0446e-03 eta: 5:36:51 time: 0.5241 data_time: 0.0154 memory: 14901 loss: 1.1613 loss_prob: 0.6204 loss_thr: 0.4374 loss_db: 0.1036 2022/11/02 19:33:23 - mmengine - INFO - Epoch(train) [666][30/63] lr: 1.0446e-03 eta: 5:36:45 time: 0.5912 data_time: 0.0402 memory: 14901 loss: 1.1576 loss_prob: 0.6135 loss_thr: 0.4371 loss_db: 0.1069 2022/11/02 19:33:26 - mmengine - INFO - Epoch(train) [666][35/63] lr: 1.0446e-03 eta: 5:36:45 time: 0.6366 data_time: 0.0423 memory: 14901 loss: 1.0892 loss_prob: 0.5692 loss_thr: 0.4207 loss_db: 0.0993 2022/11/02 19:33:29 - mmengine - INFO - Epoch(train) [666][40/63] lr: 1.0446e-03 eta: 5:36:39 time: 0.5738 data_time: 0.0167 memory: 14901 loss: 1.1809 loss_prob: 0.6412 loss_thr: 0.4337 loss_db: 0.1060 2022/11/02 19:33:32 - mmengine - INFO - Epoch(train) [666][45/63] lr: 1.0446e-03 eta: 5:36:39 time: 0.5340 data_time: 0.0113 memory: 14901 loss: 1.1749 loss_prob: 0.6388 loss_thr: 0.4291 loss_db: 0.1070 2022/11/02 19:33:34 - mmengine - INFO - Epoch(train) [666][50/63] lr: 1.0446e-03 eta: 5:36:32 time: 0.5234 data_time: 0.0192 memory: 14901 loss: 1.1008 loss_prob: 0.5782 loss_thr: 0.4212 loss_db: 0.1014 2022/11/02 19:33:37 - mmengine - INFO - Epoch(train) [666][55/63] lr: 1.0446e-03 eta: 5:36:32 time: 0.5078 data_time: 0.0251 memory: 14901 loss: 1.1016 loss_prob: 0.5795 loss_thr: 0.4206 loss_db: 0.1015 2022/11/02 19:33:39 - mmengine - INFO - Epoch(train) [666][60/63] lr: 1.0446e-03 eta: 5:36:25 time: 0.5295 data_time: 0.0205 memory: 14901 loss: 1.1643 loss_prob: 0.6224 loss_thr: 0.4342 loss_db: 0.1077 2022/11/02 19:33:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:33:46 - mmengine - INFO - Epoch(train) [667][5/63] lr: 1.0428e-03 eta: 5:36:25 time: 0.7347 data_time: 0.2304 memory: 14901 loss: 1.1919 loss_prob: 0.6374 loss_thr: 0.4447 loss_db: 0.1098 2022/11/02 19:33:48 - mmengine - INFO - Epoch(train) [667][10/63] lr: 1.0428e-03 eta: 5:36:18 time: 0.7828 data_time: 0.2363 memory: 14901 loss: 1.1110 loss_prob: 0.5892 loss_thr: 0.4217 loss_db: 0.1001 2022/11/02 19:33:51 - mmengine - INFO - Epoch(train) [667][15/63] lr: 1.0428e-03 eta: 5:36:18 time: 0.5308 data_time: 0.0163 memory: 14901 loss: 1.1550 loss_prob: 0.6148 loss_thr: 0.4358 loss_db: 0.1044 2022/11/02 19:33:54 - mmengine - INFO - Epoch(train) [667][20/63] lr: 1.0428e-03 eta: 5:36:11 time: 0.5159 data_time: 0.0111 memory: 14901 loss: 1.1747 loss_prob: 0.6241 loss_thr: 0.4438 loss_db: 0.1067 2022/11/02 19:33:57 - mmengine - INFO - Epoch(train) [667][25/63] lr: 1.0428e-03 eta: 5:36:11 time: 0.5704 data_time: 0.0366 memory: 14901 loss: 1.1312 loss_prob: 0.5943 loss_thr: 0.4343 loss_db: 0.1025 2022/11/02 19:33:59 - mmengine - INFO - Epoch(train) [667][30/63] lr: 1.0428e-03 eta: 5:36:05 time: 0.5606 data_time: 0.0366 memory: 14901 loss: 1.0628 loss_prob: 0.5529 loss_thr: 0.4143 loss_db: 0.0956 2022/11/02 19:34:03 - mmengine - INFO - Epoch(train) [667][35/63] lr: 1.0428e-03 eta: 5:36:05 time: 0.6704 data_time: 0.0351 memory: 14901 loss: 1.0931 loss_prob: 0.5767 loss_thr: 0.4192 loss_db: 0.0972 2022/11/02 19:34:06 - mmengine - INFO - Epoch(train) [667][40/63] lr: 1.0428e-03 eta: 5:35:59 time: 0.7106 data_time: 0.0340 memory: 14901 loss: 1.1653 loss_prob: 0.6228 loss_thr: 0.4361 loss_db: 0.1064 2022/11/02 19:34:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:34:09 - mmengine - INFO - Epoch(train) [667][45/63] lr: 1.0428e-03 eta: 5:35:59 time: 0.5849 data_time: 0.0122 memory: 14901 loss: 1.0828 loss_prob: 0.5697 loss_thr: 0.4140 loss_db: 0.0991 2022/11/02 19:34:12 - mmengine - INFO - Epoch(train) [667][50/63] lr: 1.0428e-03 eta: 5:35:53 time: 0.5392 data_time: 0.0160 memory: 14901 loss: 1.1444 loss_prob: 0.6067 loss_thr: 0.4346 loss_db: 0.1030 2022/11/02 19:34:14 - mmengine - INFO - Epoch(train) [667][55/63] lr: 1.0428e-03 eta: 5:35:53 time: 0.5130 data_time: 0.0144 memory: 14901 loss: 1.1653 loss_prob: 0.6157 loss_thr: 0.4421 loss_db: 0.1075 2022/11/02 19:34:17 - mmengine - INFO - Epoch(train) [667][60/63] lr: 1.0428e-03 eta: 5:35:47 time: 0.5737 data_time: 0.0139 memory: 14901 loss: 1.1002 loss_prob: 0.5743 loss_thr: 0.4262 loss_db: 0.0997 2022/11/02 19:34:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:34:25 - mmengine - INFO - Epoch(train) [668][5/63] lr: 1.0411e-03 eta: 5:35:47 time: 0.8354 data_time: 0.2564 memory: 14901 loss: 1.0982 loss_prob: 0.5791 loss_thr: 0.4186 loss_db: 0.1005 2022/11/02 19:34:27 - mmengine - INFO - Epoch(train) [668][10/63] lr: 1.0411e-03 eta: 5:35:39 time: 0.8360 data_time: 0.2538 memory: 14901 loss: 1.1246 loss_prob: 0.5956 loss_thr: 0.4245 loss_db: 0.1045 2022/11/02 19:34:30 - mmengine - INFO - Epoch(train) [668][15/63] lr: 1.0411e-03 eta: 5:35:39 time: 0.5515 data_time: 0.0104 memory: 14901 loss: 1.1456 loss_prob: 0.6097 loss_thr: 0.4328 loss_db: 0.1030 2022/11/02 19:34:33 - mmengine - INFO - Epoch(train) [668][20/63] lr: 1.0411e-03 eta: 5:35:34 time: 0.6095 data_time: 0.0117 memory: 14901 loss: 1.1235 loss_prob: 0.5879 loss_thr: 0.4348 loss_db: 0.1007 2022/11/02 19:34:36 - mmengine - INFO - Epoch(train) [668][25/63] lr: 1.0411e-03 eta: 5:35:34 time: 0.6306 data_time: 0.0268 memory: 14901 loss: 1.0946 loss_prob: 0.5743 loss_thr: 0.4199 loss_db: 0.1004 2022/11/02 19:34:40 - mmengine - INFO - Epoch(train) [668][30/63] lr: 1.0411e-03 eta: 5:35:28 time: 0.6154 data_time: 0.0428 memory: 14901 loss: 1.0767 loss_prob: 0.5717 loss_thr: 0.4051 loss_db: 0.0998 2022/11/02 19:34:43 - mmengine - INFO - Epoch(train) [668][35/63] lr: 1.0411e-03 eta: 5:35:28 time: 0.6865 data_time: 0.0281 memory: 14901 loss: 1.1049 loss_prob: 0.5888 loss_thr: 0.4149 loss_db: 0.1012 2022/11/02 19:34:46 - mmengine - INFO - Epoch(train) [668][40/63] lr: 1.0411e-03 eta: 5:35:22 time: 0.6405 data_time: 0.0108 memory: 14901 loss: 1.1010 loss_prob: 0.5818 loss_thr: 0.4191 loss_db: 0.1000 2022/11/02 19:34:49 - mmengine - INFO - Epoch(train) [668][45/63] lr: 1.0411e-03 eta: 5:35:22 time: 0.5757 data_time: 0.0081 memory: 14901 loss: 1.0968 loss_prob: 0.5710 loss_thr: 0.4266 loss_db: 0.0993 2022/11/02 19:34:52 - mmengine - INFO - Epoch(train) [668][50/63] lr: 1.0411e-03 eta: 5:35:16 time: 0.6399 data_time: 0.0200 memory: 14901 loss: 1.0864 loss_prob: 0.5693 loss_thr: 0.4203 loss_db: 0.0968 2022/11/02 19:34:56 - mmengine - INFO - Epoch(train) [668][55/63] lr: 1.0411e-03 eta: 5:35:16 time: 0.6567 data_time: 0.0317 memory: 14901 loss: 1.0589 loss_prob: 0.5561 loss_thr: 0.4078 loss_db: 0.0950 2022/11/02 19:34:59 - mmengine - INFO - Epoch(train) [668][60/63] lr: 1.0411e-03 eta: 5:35:11 time: 0.6583 data_time: 0.0214 memory: 14901 loss: 1.1015 loss_prob: 0.5744 loss_thr: 0.4272 loss_db: 0.0999 2022/11/02 19:35:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:35:06 - mmengine - INFO - Epoch(train) [669][5/63] lr: 1.0393e-03 eta: 5:35:11 time: 0.7736 data_time: 0.2749 memory: 14901 loss: 1.2041 loss_prob: 0.6362 loss_thr: 0.4594 loss_db: 0.1086 2022/11/02 19:35:09 - mmengine - INFO - Epoch(train) [669][10/63] lr: 1.0393e-03 eta: 5:35:04 time: 0.9113 data_time: 0.2755 memory: 14901 loss: 1.1587 loss_prob: 0.6236 loss_thr: 0.4320 loss_db: 0.1031 2022/11/02 19:35:12 - mmengine - INFO - Epoch(train) [669][15/63] lr: 1.0393e-03 eta: 5:35:04 time: 0.6825 data_time: 0.0127 memory: 14901 loss: 1.1764 loss_prob: 0.6370 loss_thr: 0.4306 loss_db: 0.1088 2022/11/02 19:35:16 - mmengine - INFO - Epoch(train) [669][20/63] lr: 1.0393e-03 eta: 5:34:59 time: 0.6652 data_time: 0.0117 memory: 14901 loss: 1.1188 loss_prob: 0.5964 loss_thr: 0.4176 loss_db: 0.1048 2022/11/02 19:35:19 - mmengine - INFO - Epoch(train) [669][25/63] lr: 1.0393e-03 eta: 5:34:59 time: 0.6339 data_time: 0.0327 memory: 14901 loss: 1.0619 loss_prob: 0.5646 loss_thr: 0.4006 loss_db: 0.0967 2022/11/02 19:35:22 - mmengine - INFO - Epoch(train) [669][30/63] lr: 1.0393e-03 eta: 5:34:52 time: 0.5536 data_time: 0.0461 memory: 14901 loss: 1.0390 loss_prob: 0.5451 loss_thr: 0.4020 loss_db: 0.0919 2022/11/02 19:35:25 - mmengine - INFO - Epoch(train) [669][35/63] lr: 1.0393e-03 eta: 5:34:52 time: 0.5899 data_time: 0.0271 memory: 14901 loss: 1.1259 loss_prob: 0.5967 loss_thr: 0.4292 loss_db: 0.1001 2022/11/02 19:35:27 - mmengine - INFO - Epoch(train) [669][40/63] lr: 1.0393e-03 eta: 5:34:46 time: 0.5679 data_time: 0.0129 memory: 14901 loss: 1.1944 loss_prob: 0.6285 loss_thr: 0.4587 loss_db: 0.1072 2022/11/02 19:35:30 - mmengine - INFO - Epoch(train) [669][45/63] lr: 1.0393e-03 eta: 5:34:46 time: 0.5204 data_time: 0.0113 memory: 14901 loss: 1.1809 loss_prob: 0.6384 loss_thr: 0.4370 loss_db: 0.1056 2022/11/02 19:35:33 - mmengine - INFO - Epoch(train) [669][50/63] lr: 1.0393e-03 eta: 5:34:40 time: 0.5812 data_time: 0.0244 memory: 14901 loss: 1.1396 loss_prob: 0.6193 loss_thr: 0.4172 loss_db: 0.1030 2022/11/02 19:35:37 - mmengine - INFO - Epoch(train) [669][55/63] lr: 1.0393e-03 eta: 5:34:40 time: 0.6834 data_time: 0.0305 memory: 14901 loss: 1.3556 loss_prob: 0.7837 loss_thr: 0.4509 loss_db: 0.1210 2022/11/02 19:35:39 - mmengine - INFO - Epoch(train) [669][60/63] lr: 1.0393e-03 eta: 5:34:34 time: 0.6407 data_time: 0.0178 memory: 14901 loss: 1.3692 loss_prob: 0.8106 loss_thr: 0.4374 loss_db: 0.1212 2022/11/02 19:35:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:35:47 - mmengine - INFO - Epoch(train) [670][5/63] lr: 1.0375e-03 eta: 5:34:34 time: 0.9020 data_time: 0.2487 memory: 14901 loss: 1.2404 loss_prob: 0.7015 loss_thr: 0.4249 loss_db: 0.1140 2022/11/02 19:35:51 - mmengine - INFO - Epoch(train) [670][10/63] lr: 1.0375e-03 eta: 5:34:28 time: 0.9879 data_time: 0.2565 memory: 14901 loss: 1.1450 loss_prob: 0.6168 loss_thr: 0.4234 loss_db: 0.1049 2022/11/02 19:35:53 - mmengine - INFO - Epoch(train) [670][15/63] lr: 1.0375e-03 eta: 5:34:28 time: 0.5981 data_time: 0.0199 memory: 14901 loss: 1.1634 loss_prob: 0.6147 loss_thr: 0.4406 loss_db: 0.1080 2022/11/02 19:35:56 - mmengine - INFO - Epoch(train) [670][20/63] lr: 1.0375e-03 eta: 5:34:21 time: 0.5375 data_time: 0.0126 memory: 14901 loss: 1.1569 loss_prob: 0.6079 loss_thr: 0.4452 loss_db: 0.1038 2022/11/02 19:35:59 - mmengine - INFO - Epoch(train) [670][25/63] lr: 1.0375e-03 eta: 5:34:21 time: 0.5283 data_time: 0.0232 memory: 14901 loss: 1.1477 loss_prob: 0.5977 loss_thr: 0.4488 loss_db: 0.1012 2022/11/02 19:36:01 - mmengine - INFO - Epoch(train) [670][30/63] lr: 1.0375e-03 eta: 5:34:15 time: 0.5548 data_time: 0.0311 memory: 14901 loss: 1.1558 loss_prob: 0.6041 loss_thr: 0.4488 loss_db: 0.1030 2022/11/02 19:36:05 - mmengine - INFO - Epoch(train) [670][35/63] lr: 1.0375e-03 eta: 5:34:15 time: 0.6040 data_time: 0.0315 memory: 14901 loss: 1.1612 loss_prob: 0.6150 loss_thr: 0.4389 loss_db: 0.1072 2022/11/02 19:36:08 - mmengine - INFO - Epoch(train) [670][40/63] lr: 1.0375e-03 eta: 5:34:09 time: 0.6031 data_time: 0.0208 memory: 14901 loss: 1.0751 loss_prob: 0.5625 loss_thr: 0.4139 loss_db: 0.0987 2022/11/02 19:36:10 - mmengine - INFO - Epoch(train) [670][45/63] lr: 1.0375e-03 eta: 5:34:09 time: 0.5561 data_time: 0.0104 memory: 14901 loss: 1.0421 loss_prob: 0.5476 loss_thr: 0.4017 loss_db: 0.0928 2022/11/02 19:36:14 - mmengine - INFO - Epoch(train) [670][50/63] lr: 1.0375e-03 eta: 5:34:03 time: 0.6073 data_time: 0.0227 memory: 14901 loss: 1.1259 loss_prob: 0.6005 loss_thr: 0.4243 loss_db: 0.1012 2022/11/02 19:36:16 - mmengine - INFO - Epoch(train) [670][55/63] lr: 1.0375e-03 eta: 5:34:03 time: 0.5948 data_time: 0.0306 memory: 14901 loss: 1.1261 loss_prob: 0.6048 loss_thr: 0.4175 loss_db: 0.1038 2022/11/02 19:36:19 - mmengine - INFO - Epoch(train) [670][60/63] lr: 1.0375e-03 eta: 5:33:57 time: 0.5560 data_time: 0.0219 memory: 14901 loss: 1.1486 loss_prob: 0.6262 loss_thr: 0.4167 loss_db: 0.1057 2022/11/02 19:36:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:36:27 - mmengine - INFO - Epoch(train) [671][5/63] lr: 1.0358e-03 eta: 5:33:57 time: 0.8507 data_time: 0.2397 memory: 14901 loss: 1.2003 loss_prob: 0.6493 loss_thr: 0.4433 loss_db: 0.1078 2022/11/02 19:36:30 - mmengine - INFO - Epoch(train) [671][10/63] lr: 1.0358e-03 eta: 5:33:50 time: 0.9406 data_time: 0.2516 memory: 14901 loss: 1.1464 loss_prob: 0.6049 loss_thr: 0.4377 loss_db: 0.1038 2022/11/02 19:36:33 - mmengine - INFO - Epoch(train) [671][15/63] lr: 1.0358e-03 eta: 5:33:50 time: 0.5925 data_time: 0.0190 memory: 14901 loss: 1.1593 loss_prob: 0.6071 loss_thr: 0.4451 loss_db: 0.1070 2022/11/02 19:36:35 - mmengine - INFO - Epoch(train) [671][20/63] lr: 1.0358e-03 eta: 5:33:44 time: 0.5453 data_time: 0.0112 memory: 14901 loss: 1.1317 loss_prob: 0.5886 loss_thr: 0.4398 loss_db: 0.1032 2022/11/02 19:36:39 - mmengine - INFO - Epoch(train) [671][25/63] lr: 1.0358e-03 eta: 5:33:44 time: 0.6656 data_time: 0.0357 memory: 14901 loss: 1.0196 loss_prob: 0.5226 loss_thr: 0.4080 loss_db: 0.0889 2022/11/02 19:36:42 - mmengine - INFO - Epoch(train) [671][30/63] lr: 1.0358e-03 eta: 5:33:38 time: 0.6709 data_time: 0.0387 memory: 14901 loss: 1.0871 loss_prob: 0.5698 loss_thr: 0.4176 loss_db: 0.0997 2022/11/02 19:36:46 - mmengine - INFO - Epoch(train) [671][35/63] lr: 1.0358e-03 eta: 5:33:38 time: 0.6426 data_time: 0.0220 memory: 14901 loss: 1.1261 loss_prob: 0.5907 loss_thr: 0.4308 loss_db: 0.1046 2022/11/02 19:36:49 - mmengine - INFO - Epoch(train) [671][40/63] lr: 1.0358e-03 eta: 5:33:33 time: 0.6538 data_time: 0.0168 memory: 14901 loss: 1.1653 loss_prob: 0.6146 loss_thr: 0.4457 loss_db: 0.1049 2022/11/02 19:36:51 - mmengine - INFO - Epoch(train) [671][45/63] lr: 1.0358e-03 eta: 5:33:33 time: 0.5530 data_time: 0.0119 memory: 14901 loss: 1.1589 loss_prob: 0.6205 loss_thr: 0.4326 loss_db: 0.1058 2022/11/02 19:36:54 - mmengine - INFO - Epoch(train) [671][50/63] lr: 1.0358e-03 eta: 5:33:26 time: 0.5149 data_time: 0.0282 memory: 14901 loss: 1.1403 loss_prob: 0.6139 loss_thr: 0.4222 loss_db: 0.1042 2022/11/02 19:36:57 - mmengine - INFO - Epoch(train) [671][55/63] lr: 1.0358e-03 eta: 5:33:26 time: 0.5468 data_time: 0.0311 memory: 14901 loss: 1.1521 loss_prob: 0.6184 loss_thr: 0.4282 loss_db: 0.1055 2022/11/02 19:37:00 - mmengine - INFO - Epoch(train) [671][60/63] lr: 1.0358e-03 eta: 5:33:20 time: 0.6079 data_time: 0.0144 memory: 14901 loss: 1.1431 loss_prob: 0.6060 loss_thr: 0.4328 loss_db: 0.1043 2022/11/02 19:37:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:37:09 - mmengine - INFO - Epoch(train) [672][5/63] lr: 1.0340e-03 eta: 5:33:20 time: 1.0639 data_time: 0.2636 memory: 14901 loss: 1.2053 loss_prob: 0.6682 loss_thr: 0.4257 loss_db: 0.1113 2022/11/02 19:37:14 - mmengine - INFO - Epoch(train) [672][10/63] lr: 1.0340e-03 eta: 5:33:16 time: 1.2279 data_time: 0.2738 memory: 14901 loss: 1.2806 loss_prob: 0.7160 loss_thr: 0.4443 loss_db: 0.1203 2022/11/02 19:37:17 - mmengine - INFO - Epoch(train) [672][15/63] lr: 1.0340e-03 eta: 5:33:16 time: 0.7965 data_time: 0.0213 memory: 14901 loss: 1.1539 loss_prob: 0.6123 loss_thr: 0.4344 loss_db: 0.1072 2022/11/02 19:37:20 - mmengine - INFO - Epoch(train) [672][20/63] lr: 1.0340e-03 eta: 5:33:10 time: 0.5887 data_time: 0.0115 memory: 14901 loss: 1.1261 loss_prob: 0.5950 loss_thr: 0.4284 loss_db: 0.1027 2022/11/02 19:37:23 - mmengine - INFO - Epoch(train) [672][25/63] lr: 1.0340e-03 eta: 5:33:10 time: 0.5455 data_time: 0.0365 memory: 14901 loss: 1.1387 loss_prob: 0.6075 loss_thr: 0.4284 loss_db: 0.1027 2022/11/02 19:37:27 - mmengine - INFO - Epoch(train) [672][30/63] lr: 1.0340e-03 eta: 5:33:04 time: 0.6791 data_time: 0.0452 memory: 14901 loss: 1.1208 loss_prob: 0.5951 loss_thr: 0.4236 loss_db: 0.1020 2022/11/02 19:37:30 - mmengine - INFO - Epoch(train) [672][35/63] lr: 1.0340e-03 eta: 5:33:04 time: 0.7219 data_time: 0.0182 memory: 14901 loss: 1.2121 loss_prob: 0.6513 loss_thr: 0.4482 loss_db: 0.1125 2022/11/02 19:37:33 - mmengine - INFO - Epoch(train) [672][40/63] lr: 1.0340e-03 eta: 5:32:59 time: 0.6181 data_time: 0.0108 memory: 14901 loss: 1.2117 loss_prob: 0.6462 loss_thr: 0.4546 loss_db: 0.1110 2022/11/02 19:37:36 - mmengine - INFO - Epoch(train) [672][45/63] lr: 1.0340e-03 eta: 5:32:59 time: 0.5710 data_time: 0.0121 memory: 14901 loss: 1.1012 loss_prob: 0.5834 loss_thr: 0.4157 loss_db: 0.1021 2022/11/02 19:37:39 - mmengine - INFO - Epoch(train) [672][50/63] lr: 1.0340e-03 eta: 5:32:53 time: 0.6053 data_time: 0.0256 memory: 14901 loss: 1.1032 loss_prob: 0.5878 loss_thr: 0.4121 loss_db: 0.1033 2022/11/02 19:37:43 - mmengine - INFO - Epoch(train) [672][55/63] lr: 1.0340e-03 eta: 5:32:53 time: 0.6815 data_time: 0.0312 memory: 14901 loss: 1.1581 loss_prob: 0.6165 loss_thr: 0.4349 loss_db: 0.1067 2022/11/02 19:37:46 - mmengine - INFO - Epoch(train) [672][60/63] lr: 1.0340e-03 eta: 5:32:47 time: 0.6589 data_time: 0.0166 memory: 14901 loss: 1.1211 loss_prob: 0.5974 loss_thr: 0.4211 loss_db: 0.1026 2022/11/02 19:37:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:37:53 - mmengine - INFO - Epoch(train) [673][5/63] lr: 1.0322e-03 eta: 5:32:47 time: 0.8535 data_time: 0.2637 memory: 14901 loss: 1.0948 loss_prob: 0.5781 loss_thr: 0.4178 loss_db: 0.0988 2022/11/02 19:37:56 - mmengine - INFO - Epoch(train) [673][10/63] lr: 1.0322e-03 eta: 5:32:40 time: 0.8718 data_time: 0.2623 memory: 14901 loss: 1.0598 loss_prob: 0.5550 loss_thr: 0.4065 loss_db: 0.0983 2022/11/02 19:37:58 - mmengine - INFO - Epoch(train) [673][15/63] lr: 1.0322e-03 eta: 5:32:40 time: 0.5453 data_time: 0.0116 memory: 14901 loss: 1.0616 loss_prob: 0.5604 loss_thr: 0.4031 loss_db: 0.0982 2022/11/02 19:38:01 - mmengine - INFO - Epoch(train) [673][20/63] lr: 1.0322e-03 eta: 5:32:34 time: 0.5556 data_time: 0.0116 memory: 14901 loss: 1.0707 loss_prob: 0.5684 loss_thr: 0.4035 loss_db: 0.0988 2022/11/02 19:38:05 - mmengine - INFO - Epoch(train) [673][25/63] lr: 1.0322e-03 eta: 5:32:34 time: 0.6405 data_time: 0.0585 memory: 14901 loss: 1.1081 loss_prob: 0.5911 loss_thr: 0.4148 loss_db: 0.1022 2022/11/02 19:38:07 - mmengine - INFO - Epoch(train) [673][30/63] lr: 1.0322e-03 eta: 5:32:28 time: 0.6298 data_time: 0.0555 memory: 14901 loss: 1.2038 loss_prob: 0.6573 loss_thr: 0.4365 loss_db: 0.1100 2022/11/02 19:38:10 - mmengine - INFO - Epoch(train) [673][35/63] lr: 1.0322e-03 eta: 5:32:28 time: 0.5592 data_time: 0.0085 memory: 14901 loss: 1.2261 loss_prob: 0.6638 loss_thr: 0.4506 loss_db: 0.1117 2022/11/02 19:38:15 - mmengine - INFO - Epoch(train) [673][40/63] lr: 1.0322e-03 eta: 5:32:23 time: 0.7596 data_time: 0.0113 memory: 14901 loss: 1.1907 loss_prob: 0.6284 loss_thr: 0.4548 loss_db: 0.1074 2022/11/02 19:38:18 - mmengine - INFO - Epoch(train) [673][45/63] lr: 1.0322e-03 eta: 5:32:23 time: 0.7180 data_time: 0.0093 memory: 14901 loss: 1.2249 loss_prob: 0.6477 loss_thr: 0.4655 loss_db: 0.1117 2022/11/02 19:38:20 - mmengine - INFO - Epoch(train) [673][50/63] lr: 1.0322e-03 eta: 5:32:17 time: 0.5412 data_time: 0.0295 memory: 14901 loss: 1.1572 loss_prob: 0.6075 loss_thr: 0.4414 loss_db: 0.1083 2022/11/02 19:38:23 - mmengine - INFO - Epoch(train) [673][55/63] lr: 1.0322e-03 eta: 5:32:17 time: 0.5721 data_time: 0.0351 memory: 14901 loss: 1.0711 loss_prob: 0.5573 loss_thr: 0.4153 loss_db: 0.0984 2022/11/02 19:38:26 - mmengine - INFO - Epoch(train) [673][60/63] lr: 1.0322e-03 eta: 5:32:10 time: 0.5352 data_time: 0.0133 memory: 14901 loss: 1.1915 loss_prob: 0.6337 loss_thr: 0.4510 loss_db: 0.1068 2022/11/02 19:38:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:38:33 - mmengine - INFO - Epoch(train) [674][5/63] lr: 1.0305e-03 eta: 5:32:10 time: 0.8185 data_time: 0.2609 memory: 14901 loss: 1.2082 loss_prob: 0.6353 loss_thr: 0.4632 loss_db: 0.1097 2022/11/02 19:38:36 - mmengine - INFO - Epoch(train) [674][10/63] lr: 1.0305e-03 eta: 5:32:03 time: 0.8743 data_time: 0.2617 memory: 14901 loss: 1.1368 loss_prob: 0.5923 loss_thr: 0.4410 loss_db: 0.1034 2022/11/02 19:38:39 - mmengine - INFO - Epoch(train) [674][15/63] lr: 1.0305e-03 eta: 5:32:03 time: 0.6285 data_time: 0.0155 memory: 14901 loss: 1.0402 loss_prob: 0.5386 loss_thr: 0.4091 loss_db: 0.0926 2022/11/02 19:38:42 - mmengine - INFO - Epoch(train) [674][20/63] lr: 1.0305e-03 eta: 5:31:57 time: 0.6256 data_time: 0.0182 memory: 14901 loss: 1.0321 loss_prob: 0.5218 loss_thr: 0.4193 loss_db: 0.0910 2022/11/02 19:38:46 - mmengine - INFO - Epoch(train) [674][25/63] lr: 1.0305e-03 eta: 5:31:57 time: 0.6930 data_time: 0.0342 memory: 14901 loss: 1.0491 loss_prob: 0.5342 loss_thr: 0.4224 loss_db: 0.0925 2022/11/02 19:38:49 - mmengine - INFO - Epoch(train) [674][30/63] lr: 1.0305e-03 eta: 5:31:52 time: 0.6751 data_time: 0.0357 memory: 14901 loss: 1.1361 loss_prob: 0.5985 loss_thr: 0.4348 loss_db: 0.1028 2022/11/02 19:38:53 - mmengine - INFO - Epoch(train) [674][35/63] lr: 1.0305e-03 eta: 5:31:52 time: 0.6996 data_time: 0.0205 memory: 14901 loss: 1.1446 loss_prob: 0.6058 loss_thr: 0.4318 loss_db: 0.1070 2022/11/02 19:38:56 - mmengine - INFO - Epoch(train) [674][40/63] lr: 1.0305e-03 eta: 5:31:46 time: 0.6720 data_time: 0.0156 memory: 14901 loss: 1.1669 loss_prob: 0.6223 loss_thr: 0.4363 loss_db: 0.1083 2022/11/02 19:38:58 - mmengine - INFO - Epoch(train) [674][45/63] lr: 1.0305e-03 eta: 5:31:46 time: 0.5213 data_time: 0.0156 memory: 14901 loss: 1.1865 loss_prob: 0.6273 loss_thr: 0.4507 loss_db: 0.1085 2022/11/02 19:39:01 - mmengine - INFO - Epoch(train) [674][50/63] lr: 1.0305e-03 eta: 5:31:40 time: 0.5308 data_time: 0.0278 memory: 14901 loss: 1.0932 loss_prob: 0.5733 loss_thr: 0.4226 loss_db: 0.0974 2022/11/02 19:39:04 - mmengine - INFO - Epoch(train) [674][55/63] lr: 1.0305e-03 eta: 5:31:40 time: 0.5314 data_time: 0.0321 memory: 14901 loss: 1.1693 loss_prob: 0.6185 loss_thr: 0.4467 loss_db: 0.1041 2022/11/02 19:39:07 - mmengine - INFO - Epoch(train) [674][60/63] lr: 1.0305e-03 eta: 5:31:33 time: 0.5525 data_time: 0.0216 memory: 14901 loss: 1.2555 loss_prob: 0.6780 loss_thr: 0.4623 loss_db: 0.1152 2022/11/02 19:39:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:39:15 - mmengine - INFO - Epoch(train) [675][5/63] lr: 1.0287e-03 eta: 5:31:33 time: 0.9472 data_time: 0.2760 memory: 14901 loss: 1.1769 loss_prob: 0.6439 loss_thr: 0.4247 loss_db: 0.1083 2022/11/02 19:39:18 - mmengine - INFO - Epoch(train) [675][10/63] lr: 1.0287e-03 eta: 5:31:27 time: 0.8979 data_time: 0.2771 memory: 14901 loss: 1.1837 loss_prob: 0.6409 loss_thr: 0.4308 loss_db: 0.1120 2022/11/02 19:39:21 - mmengine - INFO - Epoch(train) [675][15/63] lr: 1.0287e-03 eta: 5:31:27 time: 0.6640 data_time: 0.0110 memory: 14901 loss: 1.2004 loss_prob: 0.6488 loss_thr: 0.4383 loss_db: 0.1134 2022/11/02 19:39:24 - mmengine - INFO - Epoch(train) [675][20/63] lr: 1.0287e-03 eta: 5:31:21 time: 0.6439 data_time: 0.0120 memory: 14901 loss: 1.2486 loss_prob: 0.6620 loss_thr: 0.4712 loss_db: 0.1154 2022/11/02 19:39:28 - mmengine - INFO - Epoch(train) [675][25/63] lr: 1.0287e-03 eta: 5:31:21 time: 0.6872 data_time: 0.0497 memory: 14901 loss: 1.2686 loss_prob: 0.6722 loss_thr: 0.4818 loss_db: 0.1147 2022/11/02 19:39:31 - mmengine - INFO - Epoch(train) [675][30/63] lr: 1.0287e-03 eta: 5:31:16 time: 0.6825 data_time: 0.0491 memory: 14901 loss: 1.1501 loss_prob: 0.6063 loss_thr: 0.4414 loss_db: 0.1024 2022/11/02 19:39:36 - mmengine - INFO - Epoch(train) [675][35/63] lr: 1.0287e-03 eta: 5:31:16 time: 0.7601 data_time: 0.0105 memory: 14901 loss: 1.0713 loss_prob: 0.5565 loss_thr: 0.4179 loss_db: 0.0969 2022/11/02 19:39:39 - mmengine - INFO - Epoch(train) [675][40/63] lr: 1.0287e-03 eta: 5:31:11 time: 0.8159 data_time: 0.0098 memory: 14901 loss: 1.1177 loss_prob: 0.5864 loss_thr: 0.4281 loss_db: 0.1032 2022/11/02 19:39:42 - mmengine - INFO - Epoch(train) [675][45/63] lr: 1.0287e-03 eta: 5:31:11 time: 0.6187 data_time: 0.0088 memory: 14901 loss: 1.0964 loss_prob: 0.5732 loss_thr: 0.4229 loss_db: 0.1003 2022/11/02 19:39:45 - mmengine - INFO - Epoch(train) [675][50/63] lr: 1.0287e-03 eta: 5:31:05 time: 0.5380 data_time: 0.0301 memory: 14901 loss: 1.1336 loss_prob: 0.5923 loss_thr: 0.4400 loss_db: 0.1012 2022/11/02 19:39:48 - mmengine - INFO - Epoch(train) [675][55/63] lr: 1.0287e-03 eta: 5:31:05 time: 0.5730 data_time: 0.0306 memory: 14901 loss: 1.1881 loss_prob: 0.6292 loss_thr: 0.4512 loss_db: 0.1077 2022/11/02 19:39:51 - mmengine - INFO - Epoch(train) [675][60/63] lr: 1.0287e-03 eta: 5:30:59 time: 0.6830 data_time: 0.0119 memory: 14901 loss: 1.0803 loss_prob: 0.5722 loss_thr: 0.4100 loss_db: 0.0981 2022/11/02 19:39:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:40:00 - mmengine - INFO - Epoch(train) [676][5/63] lr: 1.0270e-03 eta: 5:30:59 time: 1.0758 data_time: 0.2801 memory: 14901 loss: 1.1829 loss_prob: 0.6263 loss_thr: 0.4472 loss_db: 0.1094 2022/11/02 19:40:04 - mmengine - INFO - Epoch(train) [676][10/63] lr: 1.0270e-03 eta: 5:30:54 time: 1.1279 data_time: 0.2844 memory: 14901 loss: 1.0652 loss_prob: 0.5681 loss_thr: 0.3975 loss_db: 0.0995 2022/11/02 19:40:07 - mmengine - INFO - Epoch(train) [676][15/63] lr: 1.0270e-03 eta: 5:30:54 time: 0.6774 data_time: 0.0134 memory: 14901 loss: 1.1277 loss_prob: 0.6127 loss_thr: 0.4105 loss_db: 0.1045 2022/11/02 19:40:10 - mmengine - INFO - Epoch(train) [676][20/63] lr: 1.0270e-03 eta: 5:30:48 time: 0.5429 data_time: 0.0078 memory: 14901 loss: 1.1554 loss_prob: 0.6118 loss_thr: 0.4400 loss_db: 0.1036 2022/11/02 19:40:13 - mmengine - INFO - Epoch(train) [676][25/63] lr: 1.0270e-03 eta: 5:30:48 time: 0.6160 data_time: 0.0381 memory: 14901 loss: 1.0340 loss_prob: 0.5267 loss_thr: 0.4154 loss_db: 0.0918 2022/11/02 19:40:16 - mmengine - INFO - Epoch(train) [676][30/63] lr: 1.0270e-03 eta: 5:30:42 time: 0.6180 data_time: 0.0364 memory: 14901 loss: 1.0552 loss_prob: 0.5402 loss_thr: 0.4206 loss_db: 0.0943 2022/11/02 19:40:19 - mmengine - INFO - Epoch(train) [676][35/63] lr: 1.0270e-03 eta: 5:30:42 time: 0.5799 data_time: 0.0188 memory: 14901 loss: 1.1301 loss_prob: 0.5906 loss_thr: 0.4371 loss_db: 0.1024 2022/11/02 19:40:23 - mmengine - INFO - Epoch(train) [676][40/63] lr: 1.0270e-03 eta: 5:30:36 time: 0.6465 data_time: 0.0206 memory: 14901 loss: 1.1670 loss_prob: 0.6249 loss_thr: 0.4339 loss_db: 0.1082 2022/11/02 19:40:26 - mmengine - INFO - Epoch(train) [676][45/63] lr: 1.0270e-03 eta: 5:30:36 time: 0.6907 data_time: 0.0101 memory: 14901 loss: 1.1799 loss_prob: 0.6476 loss_thr: 0.4231 loss_db: 0.1092 2022/11/02 19:40:30 - mmengine - INFO - Epoch(train) [676][50/63] lr: 1.0270e-03 eta: 5:30:31 time: 0.7171 data_time: 0.0260 memory: 14901 loss: 1.1349 loss_prob: 0.6131 loss_thr: 0.4189 loss_db: 0.1029 2022/11/02 19:40:33 - mmengine - INFO - Epoch(train) [676][55/63] lr: 1.0270e-03 eta: 5:30:31 time: 0.7084 data_time: 0.0272 memory: 14901 loss: 1.0584 loss_prob: 0.5598 loss_thr: 0.4025 loss_db: 0.0961 2022/11/02 19:40:36 - mmengine - INFO - Epoch(train) [676][60/63] lr: 1.0270e-03 eta: 5:30:25 time: 0.6200 data_time: 0.0160 memory: 14901 loss: 1.1508 loss_prob: 0.6195 loss_thr: 0.4246 loss_db: 0.1067 2022/11/02 19:40:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:40:42 - mmengine - INFO - Epoch(train) [677][5/63] lr: 1.0252e-03 eta: 5:30:25 time: 0.7495 data_time: 0.2302 memory: 14901 loss: 1.1396 loss_prob: 0.6099 loss_thr: 0.4262 loss_db: 0.1035 2022/11/02 19:40:45 - mmengine - INFO - Epoch(train) [677][10/63] lr: 1.0252e-03 eta: 5:30:18 time: 0.8050 data_time: 0.2308 memory: 14901 loss: 1.1025 loss_prob: 0.5789 loss_thr: 0.4231 loss_db: 0.1004 2022/11/02 19:40:48 - mmengine - INFO - Epoch(train) [677][15/63] lr: 1.0252e-03 eta: 5:30:18 time: 0.5677 data_time: 0.0171 memory: 14901 loss: 1.1515 loss_prob: 0.6083 loss_thr: 0.4376 loss_db: 0.1057 2022/11/02 19:40:51 - mmengine - INFO - Epoch(train) [677][20/63] lr: 1.0252e-03 eta: 5:30:11 time: 0.5340 data_time: 0.0162 memory: 14901 loss: 1.1270 loss_prob: 0.5944 loss_thr: 0.4285 loss_db: 0.1042 2022/11/02 19:40:53 - mmengine - INFO - Epoch(train) [677][25/63] lr: 1.0252e-03 eta: 5:30:11 time: 0.5273 data_time: 0.0412 memory: 14901 loss: 1.1230 loss_prob: 0.5918 loss_thr: 0.4276 loss_db: 0.1036 2022/11/02 19:40:56 - mmengine - INFO - Epoch(train) [677][30/63] lr: 1.0252e-03 eta: 5:30:05 time: 0.5466 data_time: 0.0458 memory: 14901 loss: 1.1337 loss_prob: 0.6009 loss_thr: 0.4302 loss_db: 0.1027 2022/11/02 19:40:59 - mmengine - INFO - Epoch(train) [677][35/63] lr: 1.0252e-03 eta: 5:30:05 time: 0.6105 data_time: 0.0179 memory: 14901 loss: 1.1230 loss_prob: 0.5829 loss_thr: 0.4407 loss_db: 0.0994 2022/11/02 19:41:02 - mmengine - INFO - Epoch(train) [677][40/63] lr: 1.0252e-03 eta: 5:29:59 time: 0.6361 data_time: 0.0143 memory: 14901 loss: 1.0639 loss_prob: 0.5475 loss_thr: 0.4213 loss_db: 0.0950 2022/11/02 19:41:06 - mmengine - INFO - Epoch(train) [677][45/63] lr: 1.0252e-03 eta: 5:29:59 time: 0.6793 data_time: 0.0132 memory: 14901 loss: 1.0478 loss_prob: 0.5512 loss_thr: 0.4035 loss_db: 0.0931 2022/11/02 19:41:10 - mmengine - INFO - Epoch(train) [677][50/63] lr: 1.0252e-03 eta: 5:29:54 time: 0.7703 data_time: 0.0255 memory: 14901 loss: 1.1445 loss_prob: 0.6206 loss_thr: 0.4219 loss_db: 0.1020 2022/11/02 19:41:13 - mmengine - INFO - Epoch(train) [677][55/63] lr: 1.0252e-03 eta: 5:29:54 time: 0.6685 data_time: 0.0287 memory: 14901 loss: 1.1136 loss_prob: 0.6062 loss_thr: 0.4078 loss_db: 0.0996 2022/11/02 19:41:16 - mmengine - INFO - Epoch(train) [677][60/63] lr: 1.0252e-03 eta: 5:29:48 time: 0.5465 data_time: 0.0173 memory: 14901 loss: 1.0779 loss_prob: 0.5735 loss_thr: 0.4093 loss_db: 0.0951 2022/11/02 19:41:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:41:24 - mmengine - INFO - Epoch(train) [678][5/63] lr: 1.0234e-03 eta: 5:29:48 time: 0.9501 data_time: 0.2840 memory: 14901 loss: 1.2074 loss_prob: 0.6533 loss_thr: 0.4449 loss_db: 0.1092 2022/11/02 19:41:27 - mmengine - INFO - Epoch(train) [678][10/63] lr: 1.0234e-03 eta: 5:29:41 time: 0.8552 data_time: 0.2817 memory: 14901 loss: 1.1300 loss_prob: 0.5995 loss_thr: 0.4273 loss_db: 0.1032 2022/11/02 19:41:30 - mmengine - INFO - Epoch(train) [678][15/63] lr: 1.0234e-03 eta: 5:29:41 time: 0.5575 data_time: 0.0146 memory: 14901 loss: 1.0886 loss_prob: 0.5625 loss_thr: 0.4280 loss_db: 0.0981 2022/11/02 19:41:32 - mmengine - INFO - Epoch(train) [678][20/63] lr: 1.0234e-03 eta: 5:29:35 time: 0.5694 data_time: 0.0174 memory: 14901 loss: 1.0775 loss_prob: 0.5540 loss_thr: 0.4286 loss_db: 0.0950 2022/11/02 19:41:36 - mmengine - INFO - Epoch(train) [678][25/63] lr: 1.0234e-03 eta: 5:29:35 time: 0.6382 data_time: 0.0446 memory: 14901 loss: 1.1275 loss_prob: 0.5893 loss_thr: 0.4365 loss_db: 0.1017 2022/11/02 19:41:40 - mmengine - INFO - Epoch(train) [678][30/63] lr: 1.0234e-03 eta: 5:29:30 time: 0.8126 data_time: 0.0456 memory: 14901 loss: 1.1372 loss_prob: 0.5968 loss_thr: 0.4372 loss_db: 0.1031 2022/11/02 19:41:43 - mmengine - INFO - Epoch(train) [678][35/63] lr: 1.0234e-03 eta: 5:29:30 time: 0.6838 data_time: 0.0165 memory: 14901 loss: 1.0989 loss_prob: 0.5804 loss_thr: 0.4162 loss_db: 0.1024 2022/11/02 19:41:46 - mmengine - INFO - Epoch(train) [678][40/63] lr: 1.0234e-03 eta: 5:29:24 time: 0.5677 data_time: 0.0146 memory: 14901 loss: 1.1180 loss_prob: 0.5980 loss_thr: 0.4149 loss_db: 0.1052 2022/11/02 19:41:49 - mmengine - INFO - Epoch(train) [678][45/63] lr: 1.0234e-03 eta: 5:29:24 time: 0.6078 data_time: 0.0144 memory: 14901 loss: 1.1121 loss_prob: 0.5953 loss_thr: 0.4150 loss_db: 0.1019 2022/11/02 19:41:52 - mmengine - INFO - Epoch(train) [678][50/63] lr: 1.0234e-03 eta: 5:29:18 time: 0.5697 data_time: 0.0293 memory: 14901 loss: 1.0715 loss_prob: 0.5679 loss_thr: 0.4061 loss_db: 0.0974 2022/11/02 19:41:54 - mmengine - INFO - Epoch(train) [678][55/63] lr: 1.0234e-03 eta: 5:29:18 time: 0.5578 data_time: 0.0260 memory: 14901 loss: 1.1967 loss_prob: 0.6494 loss_thr: 0.4379 loss_db: 0.1094 2022/11/02 19:41:58 - mmengine - INFO - Epoch(train) [678][60/63] lr: 1.0234e-03 eta: 5:29:11 time: 0.5765 data_time: 0.0095 memory: 14901 loss: 1.1730 loss_prob: 0.6294 loss_thr: 0.4370 loss_db: 0.1066 2022/11/02 19:41:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:42:05 - mmengine - INFO - Epoch(train) [679][5/63] lr: 1.0217e-03 eta: 5:29:11 time: 0.8314 data_time: 0.2272 memory: 14901 loss: 1.2134 loss_prob: 0.6640 loss_thr: 0.4387 loss_db: 0.1107 2022/11/02 19:42:07 - mmengine - INFO - Epoch(train) [679][10/63] lr: 1.0217e-03 eta: 5:29:04 time: 0.8176 data_time: 0.2258 memory: 14901 loss: 1.2424 loss_prob: 0.6767 loss_thr: 0.4526 loss_db: 0.1131 2022/11/02 19:42:10 - mmengine - INFO - Epoch(train) [679][15/63] lr: 1.0217e-03 eta: 5:29:04 time: 0.5411 data_time: 0.0110 memory: 14901 loss: 1.1810 loss_prob: 0.6276 loss_thr: 0.4434 loss_db: 0.1100 2022/11/02 19:42:13 - mmengine - INFO - Epoch(train) [679][20/63] lr: 1.0217e-03 eta: 5:28:58 time: 0.5607 data_time: 0.0119 memory: 14901 loss: 1.2151 loss_prob: 0.6562 loss_thr: 0.4468 loss_db: 0.1121 2022/11/02 19:42:16 - mmengine - INFO - Epoch(train) [679][25/63] lr: 1.0217e-03 eta: 5:28:58 time: 0.5573 data_time: 0.0300 memory: 14901 loss: 1.1815 loss_prob: 0.6381 loss_thr: 0.4361 loss_db: 0.1073 2022/11/02 19:42:19 - mmengine - INFO - Epoch(train) [679][30/63] lr: 1.0217e-03 eta: 5:28:52 time: 0.6228 data_time: 0.0425 memory: 14901 loss: 1.1118 loss_prob: 0.5920 loss_thr: 0.4176 loss_db: 0.1022 2022/11/02 19:42:22 - mmengine - INFO - Epoch(train) [679][35/63] lr: 1.0217e-03 eta: 5:28:52 time: 0.6612 data_time: 0.0254 memory: 14901 loss: 1.2096 loss_prob: 0.6551 loss_thr: 0.4434 loss_db: 0.1112 2022/11/02 19:42:25 - mmengine - INFO - Epoch(train) [679][40/63] lr: 1.0217e-03 eta: 5:28:46 time: 0.6002 data_time: 0.0118 memory: 14901 loss: 1.1824 loss_prob: 0.6239 loss_thr: 0.4538 loss_db: 0.1047 2022/11/02 19:42:28 - mmengine - INFO - Epoch(train) [679][45/63] lr: 1.0217e-03 eta: 5:28:46 time: 0.5354 data_time: 0.0092 memory: 14901 loss: 1.0513 loss_prob: 0.5438 loss_thr: 0.4138 loss_db: 0.0937 2022/11/02 19:42:31 - mmengine - INFO - Epoch(train) [679][50/63] lr: 1.0217e-03 eta: 5:28:40 time: 0.5699 data_time: 0.0182 memory: 14901 loss: 1.0976 loss_prob: 0.5764 loss_thr: 0.4209 loss_db: 0.1003 2022/11/02 19:42:34 - mmengine - INFO - Epoch(train) [679][55/63] lr: 1.0217e-03 eta: 5:28:40 time: 0.6122 data_time: 0.0295 memory: 14901 loss: 1.1159 loss_prob: 0.5769 loss_thr: 0.4386 loss_db: 0.1004 2022/11/02 19:42:36 - mmengine - INFO - Epoch(train) [679][60/63] lr: 1.0217e-03 eta: 5:28:33 time: 0.5691 data_time: 0.0238 memory: 14901 loss: 1.2088 loss_prob: 0.6760 loss_thr: 0.4191 loss_db: 0.1137 2022/11/02 19:42:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:42:44 - mmengine - INFO - Epoch(train) [680][5/63] lr: 1.0199e-03 eta: 5:28:33 time: 0.8490 data_time: 0.2390 memory: 14901 loss: 1.4995 loss_prob: 0.9308 loss_thr: 0.4297 loss_db: 0.1389 2022/11/02 19:42:47 - mmengine - INFO - Epoch(train) [680][10/63] lr: 1.0199e-03 eta: 5:28:26 time: 0.8795 data_time: 0.2521 memory: 14901 loss: 1.4545 loss_prob: 0.8665 loss_thr: 0.4540 loss_db: 0.1341 2022/11/02 19:42:50 - mmengine - INFO - Epoch(train) [680][15/63] lr: 1.0199e-03 eta: 5:28:26 time: 0.5678 data_time: 0.0226 memory: 14901 loss: 1.2629 loss_prob: 0.6853 loss_thr: 0.4586 loss_db: 0.1190 2022/11/02 19:42:52 - mmengine - INFO - Epoch(train) [680][20/63] lr: 1.0199e-03 eta: 5:28:20 time: 0.5759 data_time: 0.0109 memory: 14901 loss: 1.1972 loss_prob: 0.6367 loss_thr: 0.4527 loss_db: 0.1078 2022/11/02 19:42:55 - mmengine - INFO - Epoch(train) [680][25/63] lr: 1.0199e-03 eta: 5:28:20 time: 0.5848 data_time: 0.0319 memory: 14901 loss: 1.1639 loss_prob: 0.6211 loss_thr: 0.4355 loss_db: 0.1074 2022/11/02 19:43:00 - mmengine - INFO - Epoch(train) [680][30/63] lr: 1.0199e-03 eta: 5:28:15 time: 0.7666 data_time: 0.0503 memory: 14901 loss: 1.1237 loss_prob: 0.6062 loss_thr: 0.4106 loss_db: 0.1068 2022/11/02 19:43:03 - mmengine - INFO - Epoch(train) [680][35/63] lr: 1.0199e-03 eta: 5:28:15 time: 0.7468 data_time: 0.0280 memory: 14901 loss: 1.1843 loss_prob: 0.6349 loss_thr: 0.4412 loss_db: 0.1082 2022/11/02 19:43:06 - mmengine - INFO - Epoch(train) [680][40/63] lr: 1.0199e-03 eta: 5:28:09 time: 0.5925 data_time: 0.0115 memory: 14901 loss: 1.2791 loss_prob: 0.6885 loss_thr: 0.4748 loss_db: 0.1158 2022/11/02 19:43:10 - mmengine - INFO - Epoch(train) [680][45/63] lr: 1.0199e-03 eta: 5:28:09 time: 0.6771 data_time: 0.0135 memory: 14901 loss: 1.2590 loss_prob: 0.6865 loss_thr: 0.4591 loss_db: 0.1134 2022/11/02 19:43:13 - mmengine - INFO - Epoch(train) [680][50/63] lr: 1.0199e-03 eta: 5:28:04 time: 0.6534 data_time: 0.0235 memory: 14901 loss: 1.1544 loss_prob: 0.6235 loss_thr: 0.4275 loss_db: 0.1034 2022/11/02 19:43:16 - mmengine - INFO - Epoch(train) [680][55/63] lr: 1.0199e-03 eta: 5:28:04 time: 0.5853 data_time: 0.0309 memory: 14901 loss: 1.0927 loss_prob: 0.5890 loss_thr: 0.4072 loss_db: 0.0964 2022/11/02 19:43:18 - mmengine - INFO - Epoch(train) [680][60/63] lr: 1.0199e-03 eta: 5:27:57 time: 0.5651 data_time: 0.0188 memory: 14901 loss: 1.1273 loss_prob: 0.6073 loss_thr: 0.4204 loss_db: 0.0997 2022/11/02 19:43:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:43:19 - mmengine - INFO - Saving checkpoint at 680 epochs 2022/11/02 19:43:26 - mmengine - INFO - Epoch(val) [680][5/500] eta: 5:27:57 time: 0.0451 data_time: 0.0050 memory: 14901 2022/11/02 19:43:26 - mmengine - INFO - Epoch(val) [680][10/500] eta: 0:00:23 time: 0.0473 data_time: 0.0053 memory: 1008 2022/11/02 19:43:26 - mmengine - INFO - Epoch(val) [680][15/500] eta: 0:00:23 time: 0.0446 data_time: 0.0037 memory: 1008 2022/11/02 19:43:26 - mmengine - INFO - Epoch(val) [680][20/500] eta: 0:00:20 time: 0.0430 data_time: 0.0033 memory: 1008 2022/11/02 19:43:27 - mmengine - INFO - Epoch(val) [680][25/500] eta: 0:00:20 time: 0.0444 data_time: 0.0034 memory: 1008 2022/11/02 19:43:27 - mmengine - INFO - Epoch(val) [680][30/500] eta: 0:00:22 time: 0.0485 data_time: 0.0035 memory: 1008 2022/11/02 19:43:27 - mmengine - INFO - Epoch(val) [680][35/500] eta: 0:00:22 time: 0.0466 data_time: 0.0031 memory: 1008 2022/11/02 19:43:27 - mmengine - INFO - Epoch(val) [680][40/500] eta: 0:00:21 time: 0.0477 data_time: 0.0032 memory: 1008 2022/11/02 19:43:28 - mmengine - INFO - Epoch(val) [680][45/500] eta: 0:00:21 time: 0.0474 data_time: 0.0031 memory: 1008 2022/11/02 19:43:28 - mmengine - INFO - Epoch(val) [680][50/500] eta: 0:00:19 time: 0.0444 data_time: 0.0029 memory: 1008 2022/11/02 19:43:28 - mmengine - INFO - Epoch(val) [680][55/500] eta: 0:00:19 time: 0.0502 data_time: 0.0032 memory: 1008 2022/11/02 19:43:28 - mmengine - INFO - Epoch(val) [680][60/500] eta: 0:00:21 time: 0.0481 data_time: 0.0033 memory: 1008 2022/11/02 19:43:29 - mmengine - INFO - Epoch(val) [680][65/500] eta: 0:00:21 time: 0.0483 data_time: 0.0030 memory: 1008 2022/11/02 19:43:29 - mmengine - INFO - Epoch(val) [680][70/500] eta: 0:00:20 time: 0.0480 data_time: 0.0027 memory: 1008 2022/11/02 19:43:29 - mmengine - INFO - Epoch(val) [680][75/500] eta: 0:00:20 time: 0.0441 data_time: 0.0028 memory: 1008 2022/11/02 19:43:29 - mmengine - INFO - Epoch(val) [680][80/500] eta: 0:00:18 time: 0.0450 data_time: 0.0032 memory: 1008 2022/11/02 19:43:29 - mmengine - INFO - Epoch(val) [680][85/500] eta: 0:00:18 time: 0.0409 data_time: 0.0031 memory: 1008 2022/11/02 19:43:30 - mmengine - INFO - Epoch(val) [680][90/500] eta: 0:00:17 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 19:43:30 - mmengine - INFO - Epoch(val) [680][95/500] eta: 0:00:17 time: 0.0434 data_time: 0.0026 memory: 1008 2022/11/02 19:43:30 - mmengine - INFO - Epoch(val) [680][100/500] eta: 0:00:16 time: 0.0418 data_time: 0.0033 memory: 1008 2022/11/02 19:43:30 - mmengine - INFO - Epoch(val) [680][105/500] eta: 0:00:16 time: 0.0424 data_time: 0.0039 memory: 1008 2022/11/02 19:43:30 - mmengine - INFO - Epoch(val) [680][110/500] eta: 0:00:16 time: 0.0425 data_time: 0.0034 memory: 1008 2022/11/02 19:43:31 - mmengine - INFO - Epoch(val) [680][115/500] eta: 0:00:16 time: 0.0424 data_time: 0.0030 memory: 1008 2022/11/02 19:43:31 - mmengine - INFO - Epoch(val) [680][120/500] eta: 0:00:15 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/02 19:43:31 - mmengine - INFO - Epoch(val) [680][125/500] eta: 0:00:15 time: 0.0428 data_time: 0.0030 memory: 1008 2022/11/02 19:43:31 - mmengine - INFO - Epoch(val) [680][130/500] eta: 0:00:15 time: 0.0432 data_time: 0.0031 memory: 1008 2022/11/02 19:43:32 - mmengine - INFO - Epoch(val) [680][135/500] eta: 0:00:15 time: 0.0459 data_time: 0.0033 memory: 1008 2022/11/02 19:43:32 - mmengine - INFO - Epoch(val) [680][140/500] eta: 0:00:16 time: 0.0451 data_time: 0.0032 memory: 1008 2022/11/02 19:43:32 - mmengine - INFO - Epoch(val) [680][145/500] eta: 0:00:16 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 19:43:32 - mmengine - INFO - Epoch(val) [680][150/500] eta: 0:00:16 time: 0.0473 data_time: 0.0030 memory: 1008 2022/11/02 19:43:33 - mmengine - INFO - Epoch(val) [680][155/500] eta: 0:00:16 time: 0.0537 data_time: 0.0032 memory: 1008 2022/11/02 19:43:33 - mmengine - INFO - Epoch(val) [680][160/500] eta: 0:00:17 time: 0.0519 data_time: 0.0029 memory: 1008 2022/11/02 19:43:33 - mmengine - INFO - Epoch(val) [680][165/500] eta: 0:00:17 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 19:43:33 - mmengine - INFO - Epoch(val) [680][170/500] eta: 0:00:14 time: 0.0435 data_time: 0.0026 memory: 1008 2022/11/02 19:43:33 - mmengine - INFO - Epoch(val) [680][175/500] eta: 0:00:14 time: 0.0437 data_time: 0.0026 memory: 1008 2022/11/02 19:43:34 - mmengine - INFO - Epoch(val) [680][180/500] eta: 0:00:12 time: 0.0401 data_time: 0.0027 memory: 1008 2022/11/02 19:43:34 - mmengine - INFO - Epoch(val) [680][185/500] eta: 0:00:12 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 19:43:34 - mmengine - INFO - Epoch(val) [680][190/500] eta: 0:00:14 time: 0.0458 data_time: 0.0029 memory: 1008 2022/11/02 19:43:34 - mmengine - INFO - Epoch(val) [680][195/500] eta: 0:00:14 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/02 19:43:35 - mmengine - INFO - Epoch(val) [680][200/500] eta: 0:00:15 time: 0.0517 data_time: 0.0029 memory: 1008 2022/11/02 19:43:35 - mmengine - INFO - Epoch(val) [680][205/500] eta: 0:00:15 time: 0.0515 data_time: 0.0026 memory: 1008 2022/11/02 19:43:35 - mmengine - INFO - Epoch(val) [680][210/500] eta: 0:00:12 time: 0.0427 data_time: 0.0029 memory: 1008 2022/11/02 19:43:35 - mmengine - INFO - Epoch(val) [680][215/500] eta: 0:00:12 time: 0.0460 data_time: 0.0034 memory: 1008 2022/11/02 19:43:36 - mmengine - INFO - Epoch(val) [680][220/500] eta: 0:00:13 time: 0.0480 data_time: 0.0035 memory: 1008 2022/11/02 19:43:36 - mmengine - INFO - Epoch(val) [680][225/500] eta: 0:00:13 time: 0.0464 data_time: 0.0033 memory: 1008 2022/11/02 19:43:36 - mmengine - INFO - Epoch(val) [680][230/500] eta: 0:00:11 time: 0.0429 data_time: 0.0031 memory: 1008 2022/11/02 19:43:36 - mmengine - INFO - Epoch(val) [680][235/500] eta: 0:00:11 time: 0.0435 data_time: 0.0034 memory: 1008 2022/11/02 19:43:36 - mmengine - INFO - Epoch(val) [680][240/500] eta: 0:00:12 time: 0.0489 data_time: 0.0040 memory: 1008 2022/11/02 19:43:37 - mmengine - INFO - Epoch(val) [680][245/500] eta: 0:00:12 time: 0.0505 data_time: 0.0038 memory: 1008 2022/11/02 19:43:37 - mmengine - INFO - Epoch(val) [680][250/500] eta: 0:00:11 time: 0.0476 data_time: 0.0033 memory: 1008 2022/11/02 19:43:37 - mmengine - INFO - Epoch(val) [680][255/500] eta: 0:00:11 time: 0.0486 data_time: 0.0036 memory: 1008 2022/11/02 19:43:37 - mmengine - INFO - Epoch(val) [680][260/500] eta: 0:00:11 time: 0.0475 data_time: 0.0037 memory: 1008 2022/11/02 19:43:38 - mmengine - INFO - Epoch(val) [680][265/500] eta: 0:00:11 time: 0.0451 data_time: 0.0039 memory: 1008 2022/11/02 19:43:38 - mmengine - INFO - Epoch(val) [680][270/500] eta: 0:00:10 time: 0.0462 data_time: 0.0035 memory: 1008 2022/11/02 19:43:38 - mmengine - INFO - Epoch(val) [680][275/500] eta: 0:00:10 time: 0.0435 data_time: 0.0030 memory: 1008 2022/11/02 19:43:38 - mmengine - INFO - Epoch(val) [680][280/500] eta: 0:00:10 time: 0.0456 data_time: 0.0032 memory: 1008 2022/11/02 19:43:39 - mmengine - INFO - Epoch(val) [680][285/500] eta: 0:00:10 time: 0.0462 data_time: 0.0033 memory: 1008 2022/11/02 19:43:39 - mmengine - INFO - Epoch(val) [680][290/500] eta: 0:00:09 time: 0.0433 data_time: 0.0031 memory: 1008 2022/11/02 19:43:39 - mmengine - INFO - Epoch(val) [680][295/500] eta: 0:00:09 time: 0.0418 data_time: 0.0028 memory: 1008 2022/11/02 19:43:39 - mmengine - INFO - Epoch(val) [680][300/500] eta: 0:00:08 time: 0.0405 data_time: 0.0029 memory: 1008 2022/11/02 19:43:39 - mmengine - INFO - Epoch(val) [680][305/500] eta: 0:00:08 time: 0.0386 data_time: 0.0025 memory: 1008 2022/11/02 19:43:40 - mmengine - INFO - Epoch(val) [680][310/500] eta: 0:00:07 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/02 19:43:40 - mmengine - INFO - Epoch(val) [680][315/500] eta: 0:00:07 time: 0.0419 data_time: 0.0025 memory: 1008 2022/11/02 19:43:40 - mmengine - INFO - Epoch(val) [680][320/500] eta: 0:00:07 time: 0.0423 data_time: 0.0028 memory: 1008 2022/11/02 19:43:40 - mmengine - INFO - Epoch(val) [680][325/500] eta: 0:00:07 time: 0.0561 data_time: 0.0030 memory: 1008 2022/11/02 19:43:41 - mmengine - INFO - Epoch(val) [680][330/500] eta: 0:00:09 time: 0.0541 data_time: 0.0027 memory: 1008 2022/11/02 19:43:41 - mmengine - INFO - Epoch(val) [680][335/500] eta: 0:00:09 time: 0.0381 data_time: 0.0026 memory: 1008 2022/11/02 19:43:41 - mmengine - INFO - Epoch(val) [680][340/500] eta: 0:00:07 time: 0.0491 data_time: 0.0029 memory: 1008 2022/11/02 19:43:41 - mmengine - INFO - Epoch(val) [680][345/500] eta: 0:00:07 time: 0.0513 data_time: 0.0030 memory: 1008 2022/11/02 19:43:41 - mmengine - INFO - Epoch(val) [680][350/500] eta: 0:00:07 time: 0.0470 data_time: 0.0029 memory: 1008 2022/11/02 19:43:42 - mmengine - INFO - Epoch(val) [680][355/500] eta: 0:00:07 time: 0.0449 data_time: 0.0029 memory: 1008 2022/11/02 19:43:42 - mmengine - INFO - Epoch(val) [680][360/500] eta: 0:00:05 time: 0.0387 data_time: 0.0028 memory: 1008 2022/11/02 19:43:42 - mmengine - INFO - Epoch(val) [680][365/500] eta: 0:00:05 time: 0.0417 data_time: 0.0031 memory: 1008 2022/11/02 19:43:42 - mmengine - INFO - Epoch(val) [680][370/500] eta: 0:00:05 time: 0.0401 data_time: 0.0032 memory: 1008 2022/11/02 19:43:42 - mmengine - INFO - Epoch(val) [680][375/500] eta: 0:00:05 time: 0.0362 data_time: 0.0028 memory: 1008 2022/11/02 19:43:43 - mmengine - INFO - Epoch(val) [680][380/500] eta: 0:00:04 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 19:43:43 - mmengine - INFO - Epoch(val) [680][385/500] eta: 0:00:04 time: 0.0418 data_time: 0.0026 memory: 1008 2022/11/02 19:43:43 - mmengine - INFO - Epoch(val) [680][390/500] eta: 0:00:04 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/02 19:43:43 - mmengine - INFO - Epoch(val) [680][395/500] eta: 0:00:04 time: 0.0402 data_time: 0.0027 memory: 1008 2022/11/02 19:43:43 - mmengine - INFO - Epoch(val) [680][400/500] eta: 0:00:03 time: 0.0389 data_time: 0.0029 memory: 1008 2022/11/02 19:43:44 - mmengine - INFO - Epoch(val) [680][405/500] eta: 0:00:03 time: 0.0418 data_time: 0.0033 memory: 1008 2022/11/02 19:43:44 - mmengine - INFO - Epoch(val) [680][410/500] eta: 0:00:03 time: 0.0437 data_time: 0.0033 memory: 1008 2022/11/02 19:43:44 - mmengine - INFO - Epoch(val) [680][415/500] eta: 0:00:03 time: 0.0417 data_time: 0.0032 memory: 1008 2022/11/02 19:43:44 - mmengine - INFO - Epoch(val) [680][420/500] eta: 0:00:03 time: 0.0385 data_time: 0.0031 memory: 1008 2022/11/02 19:43:44 - mmengine - INFO - Epoch(val) [680][425/500] eta: 0:00:03 time: 0.0369 data_time: 0.0027 memory: 1008 2022/11/02 19:43:45 - mmengine - INFO - Epoch(val) [680][430/500] eta: 0:00:02 time: 0.0380 data_time: 0.0026 memory: 1008 2022/11/02 19:43:45 - mmengine - INFO - Epoch(val) [680][435/500] eta: 0:00:02 time: 0.0414 data_time: 0.0030 memory: 1008 2022/11/02 19:43:45 - mmengine - INFO - Epoch(val) [680][440/500] eta: 0:00:02 time: 0.0419 data_time: 0.0030 memory: 1008 2022/11/02 19:43:45 - mmengine - INFO - Epoch(val) [680][445/500] eta: 0:00:02 time: 0.0458 data_time: 0.0036 memory: 1008 2022/11/02 19:43:46 - mmengine - INFO - Epoch(val) [680][450/500] eta: 0:00:02 time: 0.0467 data_time: 0.0035 memory: 1008 2022/11/02 19:43:46 - mmengine - INFO - Epoch(val) [680][455/500] eta: 0:00:02 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 19:43:46 - mmengine - INFO - Epoch(val) [680][460/500] eta: 0:00:01 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 19:43:46 - mmengine - INFO - Epoch(val) [680][465/500] eta: 0:00:01 time: 0.0377 data_time: 0.0028 memory: 1008 2022/11/02 19:43:46 - mmengine - INFO - Epoch(val) [680][470/500] eta: 0:00:01 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/02 19:43:47 - mmengine - INFO - Epoch(val) [680][475/500] eta: 0:00:01 time: 0.0446 data_time: 0.0030 memory: 1008 2022/11/02 19:43:47 - mmengine - INFO - Epoch(val) [680][480/500] eta: 0:00:00 time: 0.0408 data_time: 0.0030 memory: 1008 2022/11/02 19:43:47 - mmengine - INFO - Epoch(val) [680][485/500] eta: 0:00:00 time: 0.0427 data_time: 0.0030 memory: 1008 2022/11/02 19:43:47 - mmengine - INFO - Epoch(val) [680][490/500] eta: 0:00:00 time: 0.0470 data_time: 0.0028 memory: 1008 2022/11/02 19:43:47 - mmengine - INFO - Epoch(val) [680][495/500] eta: 0:00:00 time: 0.0471 data_time: 0.0024 memory: 1008 2022/11/02 19:43:48 - mmengine - INFO - Epoch(val) [680][500/500] eta: 0:00:00 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 19:43:48 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8180, precision: 0.7233, hmean: 0.7677 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8180, precision: 0.7992, hmean: 0.8085 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8161, precision: 0.8309, hmean: 0.8234 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8084, precision: 0.8579, hmean: 0.8324 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7829, precision: 0.8900, hmean: 0.8330 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5864, precision: 0.9348, hmean: 0.7207 2022/11/02 19:43:48 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0510, precision: 0.9815, hmean: 0.0970 2022/11/02 19:43:48 - mmengine - INFO - Epoch(val) [680][500/500] icdar/precision: 0.8900 icdar/recall: 0.7829 icdar/hmean: 0.8330 2022/11/02 19:43:54 - mmengine - INFO - Epoch(train) [681][5/63] lr: 1.0181e-03 eta: 0:00:00 time: 0.8119 data_time: 0.2582 memory: 14901 loss: 1.1230 loss_prob: 0.5971 loss_thr: 0.4221 loss_db: 0.1037 2022/11/02 19:43:56 - mmengine - INFO - Epoch(train) [681][10/63] lr: 1.0181e-03 eta: 5:27:50 time: 0.8583 data_time: 0.2581 memory: 14901 loss: 1.1654 loss_prob: 0.6195 loss_thr: 0.4387 loss_db: 0.1072 2022/11/02 19:43:59 - mmengine - INFO - Epoch(train) [681][15/63] lr: 1.0181e-03 eta: 5:27:50 time: 0.5214 data_time: 0.0117 memory: 14901 loss: 1.2842 loss_prob: 0.6945 loss_thr: 0.4732 loss_db: 0.1165 2022/11/02 19:44:01 - mmengine - INFO - Epoch(train) [681][20/63] lr: 1.0181e-03 eta: 5:27:43 time: 0.5027 data_time: 0.0113 memory: 14901 loss: 1.2372 loss_prob: 0.6740 loss_thr: 0.4500 loss_db: 0.1132 2022/11/02 19:44:05 - mmengine - INFO - Epoch(train) [681][25/63] lr: 1.0181e-03 eta: 5:27:43 time: 0.5794 data_time: 0.0457 memory: 14901 loss: 1.0452 loss_prob: 0.5439 loss_thr: 0.4078 loss_db: 0.0934 2022/11/02 19:44:07 - mmengine - INFO - Epoch(train) [681][30/63] lr: 1.0181e-03 eta: 5:27:37 time: 0.5911 data_time: 0.0457 memory: 14901 loss: 1.0564 loss_prob: 0.5354 loss_thr: 0.4281 loss_db: 0.0929 2022/11/02 19:44:10 - mmengine - INFO - Epoch(train) [681][35/63] lr: 1.0181e-03 eta: 5:27:37 time: 0.5554 data_time: 0.0102 memory: 14901 loss: 1.1839 loss_prob: 0.6333 loss_thr: 0.4436 loss_db: 0.1071 2022/11/02 19:44:13 - mmengine - INFO - Epoch(train) [681][40/63] lr: 1.0181e-03 eta: 5:27:31 time: 0.5726 data_time: 0.0084 memory: 14901 loss: 1.1750 loss_prob: 0.6373 loss_thr: 0.4322 loss_db: 0.1056 2022/11/02 19:44:16 - mmengine - INFO - Epoch(train) [681][45/63] lr: 1.0181e-03 eta: 5:27:31 time: 0.5934 data_time: 0.0102 memory: 14901 loss: 1.0673 loss_prob: 0.5575 loss_thr: 0.4131 loss_db: 0.0968 2022/11/02 19:44:20 - mmengine - INFO - Epoch(train) [681][50/63] lr: 1.0181e-03 eta: 5:27:26 time: 0.6751 data_time: 0.0323 memory: 14901 loss: 1.0699 loss_prob: 0.5540 loss_thr: 0.4181 loss_db: 0.0978 2022/11/02 19:44:22 - mmengine - INFO - Epoch(train) [681][55/63] lr: 1.0181e-03 eta: 5:27:26 time: 0.6126 data_time: 0.0289 memory: 14901 loss: 1.1000 loss_prob: 0.5733 loss_thr: 0.4285 loss_db: 0.0981 2022/11/02 19:44:25 - mmengine - INFO - Epoch(train) [681][60/63] lr: 1.0181e-03 eta: 5:27:19 time: 0.5436 data_time: 0.0088 memory: 14901 loss: 1.1070 loss_prob: 0.5823 loss_thr: 0.4252 loss_db: 0.0995 2022/11/02 19:44:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:44:33 - mmengine - INFO - Epoch(train) [682][5/63] lr: 1.0164e-03 eta: 5:27:19 time: 0.8875 data_time: 0.2371 memory: 14901 loss: 1.0613 loss_prob: 0.5621 loss_thr: 0.4016 loss_db: 0.0976 2022/11/02 19:44:35 - mmengine - INFO - Epoch(train) [682][10/63] lr: 1.0164e-03 eta: 5:27:12 time: 0.8996 data_time: 0.2361 memory: 14901 loss: 1.0571 loss_prob: 0.5506 loss_thr: 0.4094 loss_db: 0.0971 2022/11/02 19:44:39 - mmengine - INFO - Epoch(train) [682][15/63] lr: 1.0164e-03 eta: 5:27:12 time: 0.6109 data_time: 0.0132 memory: 14901 loss: 1.1069 loss_prob: 0.5823 loss_thr: 0.4264 loss_db: 0.0981 2022/11/02 19:44:42 - mmengine - INFO - Epoch(train) [682][20/63] lr: 1.0164e-03 eta: 5:27:06 time: 0.6112 data_time: 0.0123 memory: 14901 loss: 1.1395 loss_prob: 0.6038 loss_thr: 0.4336 loss_db: 0.1020 2022/11/02 19:44:44 - mmengine - INFO - Epoch(train) [682][25/63] lr: 1.0164e-03 eta: 5:27:06 time: 0.5456 data_time: 0.0193 memory: 14901 loss: 1.2316 loss_prob: 0.6463 loss_thr: 0.4710 loss_db: 0.1143 2022/11/02 19:44:47 - mmengine - INFO - Epoch(train) [682][30/63] lr: 1.0164e-03 eta: 5:27:00 time: 0.5404 data_time: 0.0421 memory: 14901 loss: 1.1879 loss_prob: 0.6249 loss_thr: 0.4520 loss_db: 0.1110 2022/11/02 19:44:50 - mmengine - INFO - Epoch(train) [682][35/63] lr: 1.0164e-03 eta: 5:27:00 time: 0.5191 data_time: 0.0340 memory: 14901 loss: 1.0965 loss_prob: 0.5868 loss_thr: 0.4095 loss_db: 0.1002 2022/11/02 19:44:52 - mmengine - INFO - Epoch(train) [682][40/63] lr: 1.0164e-03 eta: 5:26:53 time: 0.5100 data_time: 0.0126 memory: 14901 loss: 1.1785 loss_prob: 0.6382 loss_thr: 0.4316 loss_db: 0.1088 2022/11/02 19:44:56 - mmengine - INFO - Epoch(train) [682][45/63] lr: 1.0164e-03 eta: 5:26:53 time: 0.5988 data_time: 0.0084 memory: 14901 loss: 1.1625 loss_prob: 0.6214 loss_thr: 0.4330 loss_db: 0.1082 2022/11/02 19:44:59 - mmengine - INFO - Epoch(train) [682][50/63] lr: 1.0164e-03 eta: 5:26:48 time: 0.6795 data_time: 0.0121 memory: 14901 loss: 1.0863 loss_prob: 0.5730 loss_thr: 0.4144 loss_db: 0.0989 2022/11/02 19:45:03 - mmengine - INFO - Epoch(train) [682][55/63] lr: 1.0164e-03 eta: 5:26:48 time: 0.7612 data_time: 0.0281 memory: 14901 loss: 1.1542 loss_prob: 0.6188 loss_thr: 0.4296 loss_db: 0.1058 2022/11/02 19:45:06 - mmengine - INFO - Epoch(train) [682][60/63] lr: 1.0164e-03 eta: 5:26:43 time: 0.7628 data_time: 0.0270 memory: 14901 loss: 1.1820 loss_prob: 0.6306 loss_thr: 0.4427 loss_db: 0.1087 2022/11/02 19:45:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:45:13 - mmengine - INFO - Epoch(train) [683][5/63] lr: 1.0146e-03 eta: 5:26:43 time: 0.8201 data_time: 0.2143 memory: 14901 loss: 1.2766 loss_prob: 0.7027 loss_thr: 0.4591 loss_db: 0.1147 2022/11/02 19:45:17 - mmengine - INFO - Epoch(train) [683][10/63] lr: 1.0146e-03 eta: 5:26:36 time: 0.9080 data_time: 0.2281 memory: 14901 loss: 1.1036 loss_prob: 0.5823 loss_thr: 0.4210 loss_db: 0.1003 2022/11/02 19:45:20 - mmengine - INFO - Epoch(train) [683][15/63] lr: 1.0146e-03 eta: 5:26:36 time: 0.6379 data_time: 0.0249 memory: 14901 loss: 1.0419 loss_prob: 0.5499 loss_thr: 0.3965 loss_db: 0.0955 2022/11/02 19:45:22 - mmengine - INFO - Epoch(train) [683][20/63] lr: 1.0146e-03 eta: 5:26:30 time: 0.5359 data_time: 0.0117 memory: 14901 loss: 1.0943 loss_prob: 0.5738 loss_thr: 0.4202 loss_db: 0.1003 2022/11/02 19:45:26 - mmengine - INFO - Epoch(train) [683][25/63] lr: 1.0146e-03 eta: 5:26:30 time: 0.5763 data_time: 0.0170 memory: 14901 loss: 1.1502 loss_prob: 0.6023 loss_thr: 0.4426 loss_db: 0.1053 2022/11/02 19:45:29 - mmengine - INFO - Epoch(train) [683][30/63] lr: 1.0146e-03 eta: 5:26:24 time: 0.6152 data_time: 0.0449 memory: 14901 loss: 1.1357 loss_prob: 0.6065 loss_thr: 0.4231 loss_db: 0.1061 2022/11/02 19:45:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:45:31 - mmengine - INFO - Epoch(train) [683][35/63] lr: 1.0146e-03 eta: 5:26:24 time: 0.5819 data_time: 0.0432 memory: 14901 loss: 1.1868 loss_prob: 0.6430 loss_thr: 0.4316 loss_db: 0.1121 2022/11/02 19:45:34 - mmengine - INFO - Epoch(train) [683][40/63] lr: 1.0146e-03 eta: 5:26:17 time: 0.5252 data_time: 0.0135 memory: 14901 loss: 1.2574 loss_prob: 0.6921 loss_thr: 0.4456 loss_db: 0.1196 2022/11/02 19:45:38 - mmengine - INFO - Epoch(train) [683][45/63] lr: 1.0146e-03 eta: 5:26:17 time: 0.6773 data_time: 0.0095 memory: 14901 loss: 1.2230 loss_prob: 0.6732 loss_thr: 0.4361 loss_db: 0.1137 2022/11/02 19:45:42 - mmengine - INFO - Epoch(train) [683][50/63] lr: 1.0146e-03 eta: 5:26:13 time: 0.8070 data_time: 0.0232 memory: 14901 loss: 1.3549 loss_prob: 0.7680 loss_thr: 0.4638 loss_db: 0.1231 2022/11/02 19:45:44 - mmengine - INFO - Epoch(train) [683][55/63] lr: 1.0146e-03 eta: 5:26:13 time: 0.6303 data_time: 0.0265 memory: 14901 loss: 1.3699 loss_prob: 0.7752 loss_thr: 0.4641 loss_db: 0.1306 2022/11/02 19:45:48 - mmengine - INFO - Epoch(train) [683][60/63] lr: 1.0146e-03 eta: 5:26:07 time: 0.5964 data_time: 0.0117 memory: 14901 loss: 1.1718 loss_prob: 0.6245 loss_thr: 0.4373 loss_db: 0.1100 2022/11/02 19:45:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:45:56 - mmengine - INFO - Epoch(train) [684][5/63] lr: 1.0128e-03 eta: 5:26:07 time: 0.9620 data_time: 0.2423 memory: 14901 loss: 1.2295 loss_prob: 0.6609 loss_thr: 0.4580 loss_db: 0.1105 2022/11/02 19:45:59 - mmengine - INFO - Epoch(train) [684][10/63] lr: 1.0128e-03 eta: 5:26:00 time: 0.9157 data_time: 0.2425 memory: 14901 loss: 1.1900 loss_prob: 0.6349 loss_thr: 0.4434 loss_db: 0.1117 2022/11/02 19:46:02 - mmengine - INFO - Epoch(train) [684][15/63] lr: 1.0128e-03 eta: 5:26:00 time: 0.6209 data_time: 0.0194 memory: 14901 loss: 1.2340 loss_prob: 0.6637 loss_thr: 0.4543 loss_db: 0.1160 2022/11/02 19:46:05 - mmengine - INFO - Epoch(train) [684][20/63] lr: 1.0128e-03 eta: 5:25:54 time: 0.6426 data_time: 0.0171 memory: 14901 loss: 1.1725 loss_prob: 0.6226 loss_thr: 0.4454 loss_db: 0.1045 2022/11/02 19:46:08 - mmengine - INFO - Epoch(train) [684][25/63] lr: 1.0128e-03 eta: 5:25:54 time: 0.6280 data_time: 0.0225 memory: 14901 loss: 1.0846 loss_prob: 0.5701 loss_thr: 0.4158 loss_db: 0.0988 2022/11/02 19:46:12 - mmengine - INFO - Epoch(train) [684][30/63] lr: 1.0128e-03 eta: 5:25:49 time: 0.7035 data_time: 0.0443 memory: 14901 loss: 1.0999 loss_prob: 0.5842 loss_thr: 0.4124 loss_db: 0.1032 2022/11/02 19:46:15 - mmengine - INFO - Epoch(train) [684][35/63] lr: 1.0128e-03 eta: 5:25:49 time: 0.6742 data_time: 0.0352 memory: 14901 loss: 1.1507 loss_prob: 0.6082 loss_thr: 0.4392 loss_db: 0.1033 2022/11/02 19:46:18 - mmengine - INFO - Epoch(train) [684][40/63] lr: 1.0128e-03 eta: 5:25:43 time: 0.6171 data_time: 0.0382 memory: 14901 loss: 1.1336 loss_prob: 0.5989 loss_thr: 0.4327 loss_db: 0.1020 2022/11/02 19:46:22 - mmengine - INFO - Epoch(train) [684][45/63] lr: 1.0128e-03 eta: 5:25:43 time: 0.7117 data_time: 0.0332 memory: 14901 loss: 1.2475 loss_prob: 0.6867 loss_thr: 0.4462 loss_db: 0.1146 2022/11/02 19:46:25 - mmengine - INFO - Epoch(train) [684][50/63] lr: 1.0128e-03 eta: 5:25:38 time: 0.6934 data_time: 0.0202 memory: 14901 loss: 1.3019 loss_prob: 0.7166 loss_thr: 0.4657 loss_db: 0.1196 2022/11/02 19:46:28 - mmengine - INFO - Epoch(train) [684][55/63] lr: 1.0128e-03 eta: 5:25:38 time: 0.5478 data_time: 0.0232 memory: 14901 loss: 1.1883 loss_prob: 0.6314 loss_thr: 0.4468 loss_db: 0.1102 2022/11/02 19:46:31 - mmengine - INFO - Epoch(train) [684][60/63] lr: 1.0128e-03 eta: 5:25:32 time: 0.5854 data_time: 0.0165 memory: 14901 loss: 1.1199 loss_prob: 0.5893 loss_thr: 0.4292 loss_db: 0.1013 2022/11/02 19:46:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:46:39 - mmengine - INFO - Epoch(train) [685][5/63] lr: 1.0111e-03 eta: 5:25:32 time: 0.9677 data_time: 0.2403 memory: 14901 loss: 1.1120 loss_prob: 0.5866 loss_thr: 0.4233 loss_db: 0.1021 2022/11/02 19:46:44 - mmengine - INFO - Epoch(train) [685][10/63] lr: 1.0111e-03 eta: 5:25:26 time: 1.0664 data_time: 0.2375 memory: 14901 loss: 1.2024 loss_prob: 0.6491 loss_thr: 0.4428 loss_db: 0.1106 2022/11/02 19:46:47 - mmengine - INFO - Epoch(train) [685][15/63] lr: 1.0111e-03 eta: 5:25:26 time: 0.7251 data_time: 0.0164 memory: 14901 loss: 1.2427 loss_prob: 0.6749 loss_thr: 0.4538 loss_db: 0.1140 2022/11/02 19:46:50 - mmengine - INFO - Epoch(train) [685][20/63] lr: 1.0111e-03 eta: 5:25:20 time: 0.6409 data_time: 0.0142 memory: 14901 loss: 1.1928 loss_prob: 0.6377 loss_thr: 0.4461 loss_db: 0.1090 2022/11/02 19:46:53 - mmengine - INFO - Epoch(train) [685][25/63] lr: 1.0111e-03 eta: 5:25:20 time: 0.6471 data_time: 0.0266 memory: 14901 loss: 1.0920 loss_prob: 0.5686 loss_thr: 0.4241 loss_db: 0.0992 2022/11/02 19:46:56 - mmengine - INFO - Epoch(train) [685][30/63] lr: 1.0111e-03 eta: 5:25:15 time: 0.6338 data_time: 0.0394 memory: 14901 loss: 1.1179 loss_prob: 0.5837 loss_thr: 0.4310 loss_db: 0.1032 2022/11/02 19:46:59 - mmengine - INFO - Epoch(train) [685][35/63] lr: 1.0111e-03 eta: 5:25:15 time: 0.5672 data_time: 0.0247 memory: 14901 loss: 1.1242 loss_prob: 0.6051 loss_thr: 0.4161 loss_db: 0.1030 2022/11/02 19:47:02 - mmengine - INFO - Epoch(train) [685][40/63] lr: 1.0111e-03 eta: 5:25:08 time: 0.5841 data_time: 0.0215 memory: 14901 loss: 1.1109 loss_prob: 0.6015 loss_thr: 0.4082 loss_db: 0.1012 2022/11/02 19:47:07 - mmengine - INFO - Epoch(train) [685][45/63] lr: 1.0111e-03 eta: 5:25:08 time: 0.7714 data_time: 0.0173 memory: 14901 loss: 1.1334 loss_prob: 0.6064 loss_thr: 0.4245 loss_db: 0.1025 2022/11/02 19:47:10 - mmengine - INFO - Epoch(train) [685][50/63] lr: 1.0111e-03 eta: 5:25:04 time: 0.8189 data_time: 0.0260 memory: 14901 loss: 1.0557 loss_prob: 0.5544 loss_thr: 0.4066 loss_db: 0.0947 2022/11/02 19:47:14 - mmengine - INFO - Epoch(train) [685][55/63] lr: 1.0111e-03 eta: 5:25:04 time: 0.7110 data_time: 0.0254 memory: 14901 loss: 1.0881 loss_prob: 0.5717 loss_thr: 0.4182 loss_db: 0.0982 2022/11/02 19:47:17 - mmengine - INFO - Epoch(train) [685][60/63] lr: 1.0111e-03 eta: 5:24:58 time: 0.6276 data_time: 0.0115 memory: 14901 loss: 1.1791 loss_prob: 0.6258 loss_thr: 0.4466 loss_db: 0.1067 2022/11/02 19:47:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:47:25 - mmengine - INFO - Epoch(train) [686][5/63] lr: 1.0093e-03 eta: 5:24:58 time: 0.9161 data_time: 0.2665 memory: 14901 loss: 1.1246 loss_prob: 0.6039 loss_thr: 0.4159 loss_db: 0.1048 2022/11/02 19:47:27 - mmengine - INFO - Epoch(train) [686][10/63] lr: 1.0093e-03 eta: 5:24:52 time: 0.9452 data_time: 0.2639 memory: 14901 loss: 1.2068 loss_prob: 0.6490 loss_thr: 0.4470 loss_db: 0.1108 2022/11/02 19:47:31 - mmengine - INFO - Epoch(train) [686][15/63] lr: 1.0093e-03 eta: 5:24:52 time: 0.5991 data_time: 0.0121 memory: 14901 loss: 1.2226 loss_prob: 0.6580 loss_thr: 0.4530 loss_db: 0.1115 2022/11/02 19:47:33 - mmengine - INFO - Epoch(train) [686][20/63] lr: 1.0093e-03 eta: 5:24:46 time: 0.5853 data_time: 0.0140 memory: 14901 loss: 1.0861 loss_prob: 0.5727 loss_thr: 0.4151 loss_db: 0.0984 2022/11/02 19:47:36 - mmengine - INFO - Epoch(train) [686][25/63] lr: 1.0093e-03 eta: 5:24:46 time: 0.5641 data_time: 0.0394 memory: 14901 loss: 1.0666 loss_prob: 0.5600 loss_thr: 0.4117 loss_db: 0.0948 2022/11/02 19:47:39 - mmengine - INFO - Epoch(train) [686][30/63] lr: 1.0093e-03 eta: 5:24:40 time: 0.6055 data_time: 0.0543 memory: 14901 loss: 1.0937 loss_prob: 0.5835 loss_thr: 0.4100 loss_db: 0.1002 2022/11/02 19:47:43 - mmengine - INFO - Epoch(train) [686][35/63] lr: 1.0093e-03 eta: 5:24:40 time: 0.6412 data_time: 0.0260 memory: 14901 loss: 1.0939 loss_prob: 0.5797 loss_thr: 0.4124 loss_db: 0.1018 2022/11/02 19:47:45 - mmengine - INFO - Epoch(train) [686][40/63] lr: 1.0093e-03 eta: 5:24:33 time: 0.5860 data_time: 0.0110 memory: 14901 loss: 1.1395 loss_prob: 0.6036 loss_thr: 0.4325 loss_db: 0.1034 2022/11/02 19:47:48 - mmengine - INFO - Epoch(train) [686][45/63] lr: 1.0093e-03 eta: 5:24:33 time: 0.5345 data_time: 0.0122 memory: 14901 loss: 1.0887 loss_prob: 0.5756 loss_thr: 0.4154 loss_db: 0.0977 2022/11/02 19:47:51 - mmengine - INFO - Epoch(train) [686][50/63] lr: 1.0093e-03 eta: 5:24:27 time: 0.5770 data_time: 0.0339 memory: 14901 loss: 1.0050 loss_prob: 0.5222 loss_thr: 0.3921 loss_db: 0.0906 2022/11/02 19:47:53 - mmengine - INFO - Epoch(train) [686][55/63] lr: 1.0093e-03 eta: 5:24:27 time: 0.5464 data_time: 0.0344 memory: 14901 loss: 1.1533 loss_prob: 0.6204 loss_thr: 0.4267 loss_db: 0.1062 2022/11/02 19:47:56 - mmengine - INFO - Epoch(train) [686][60/63] lr: 1.0093e-03 eta: 5:24:21 time: 0.5154 data_time: 0.0123 memory: 14901 loss: 1.1935 loss_prob: 0.6490 loss_thr: 0.4340 loss_db: 0.1105 2022/11/02 19:47:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:48:03 - mmengine - INFO - Epoch(train) [687][5/63] lr: 1.0075e-03 eta: 5:24:21 time: 0.7680 data_time: 0.2280 memory: 14901 loss: 1.1352 loss_prob: 0.6132 loss_thr: 0.4186 loss_db: 0.1035 2022/11/02 19:48:06 - mmengine - INFO - Epoch(train) [687][10/63] lr: 1.0075e-03 eta: 5:24:13 time: 0.8169 data_time: 0.2222 memory: 14901 loss: 1.1133 loss_prob: 0.5977 loss_thr: 0.4157 loss_db: 0.0999 2022/11/02 19:48:09 - mmengine - INFO - Epoch(train) [687][15/63] lr: 1.0075e-03 eta: 5:24:13 time: 0.5856 data_time: 0.0105 memory: 14901 loss: 1.1275 loss_prob: 0.5968 loss_thr: 0.4282 loss_db: 0.1026 2022/11/02 19:48:12 - mmengine - INFO - Epoch(train) [687][20/63] lr: 1.0075e-03 eta: 5:24:07 time: 0.6475 data_time: 0.0142 memory: 14901 loss: 1.1694 loss_prob: 0.6245 loss_thr: 0.4367 loss_db: 0.1083 2022/11/02 19:48:16 - mmengine - INFO - Epoch(train) [687][25/63] lr: 1.0075e-03 eta: 5:24:07 time: 0.7618 data_time: 0.0398 memory: 14901 loss: 1.1232 loss_prob: 0.5946 loss_thr: 0.4262 loss_db: 0.1025 2022/11/02 19:48:19 - mmengine - INFO - Epoch(train) [687][30/63] lr: 1.0075e-03 eta: 5:24:02 time: 0.6519 data_time: 0.0407 memory: 14901 loss: 1.1049 loss_prob: 0.5667 loss_thr: 0.4385 loss_db: 0.0998 2022/11/02 19:48:21 - mmengine - INFO - Epoch(train) [687][35/63] lr: 1.0075e-03 eta: 5:24:02 time: 0.5162 data_time: 0.0113 memory: 14901 loss: 1.0909 loss_prob: 0.5576 loss_thr: 0.4342 loss_db: 0.0990 2022/11/02 19:48:24 - mmengine - INFO - Epoch(train) [687][40/63] lr: 1.0075e-03 eta: 5:23:56 time: 0.5754 data_time: 0.0091 memory: 14901 loss: 1.0835 loss_prob: 0.5636 loss_thr: 0.4232 loss_db: 0.0966 2022/11/02 19:48:27 - mmengine - INFO - Epoch(train) [687][45/63] lr: 1.0075e-03 eta: 5:23:56 time: 0.5529 data_time: 0.0115 memory: 14901 loss: 1.1961 loss_prob: 0.6497 loss_thr: 0.4337 loss_db: 0.1127 2022/11/02 19:48:31 - mmengine - INFO - Epoch(train) [687][50/63] lr: 1.0075e-03 eta: 5:23:50 time: 0.6364 data_time: 0.0327 memory: 14901 loss: 1.2337 loss_prob: 0.6693 loss_thr: 0.4452 loss_db: 0.1192 2022/11/02 19:48:34 - mmengine - INFO - Epoch(train) [687][55/63] lr: 1.0075e-03 eta: 5:23:50 time: 0.7463 data_time: 0.0344 memory: 14901 loss: 1.1326 loss_prob: 0.6001 loss_thr: 0.4295 loss_db: 0.1030 2022/11/02 19:48:37 - mmengine - INFO - Epoch(train) [687][60/63] lr: 1.0075e-03 eta: 5:23:44 time: 0.6488 data_time: 0.0136 memory: 14901 loss: 1.1512 loss_prob: 0.6283 loss_thr: 0.4224 loss_db: 0.1005 2022/11/02 19:48:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:48:45 - mmengine - INFO - Epoch(train) [688][5/63] lr: 1.0058e-03 eta: 5:23:44 time: 0.8280 data_time: 0.2265 memory: 14901 loss: 0.9901 loss_prob: 0.5121 loss_thr: 0.3876 loss_db: 0.0904 2022/11/02 19:48:47 - mmengine - INFO - Epoch(train) [688][10/63] lr: 1.0058e-03 eta: 5:23:37 time: 0.8694 data_time: 0.2267 memory: 14901 loss: 0.9771 loss_prob: 0.5060 loss_thr: 0.3817 loss_db: 0.0894 2022/11/02 19:48:50 - mmengine - INFO - Epoch(train) [688][15/63] lr: 1.0058e-03 eta: 5:23:37 time: 0.5725 data_time: 0.0108 memory: 14901 loss: 1.0435 loss_prob: 0.5502 loss_thr: 0.3996 loss_db: 0.0938 2022/11/02 19:48:54 - mmengine - INFO - Epoch(train) [688][20/63] lr: 1.0058e-03 eta: 5:23:31 time: 0.6614 data_time: 0.0118 memory: 14901 loss: 1.0804 loss_prob: 0.5704 loss_thr: 0.4130 loss_db: 0.0969 2022/11/02 19:48:57 - mmengine - INFO - Epoch(train) [688][25/63] lr: 1.0058e-03 eta: 5:23:31 time: 0.6924 data_time: 0.0243 memory: 14901 loss: 1.0758 loss_prob: 0.5566 loss_thr: 0.4227 loss_db: 0.0964 2022/11/02 19:49:00 - mmengine - INFO - Epoch(train) [688][30/63] lr: 1.0058e-03 eta: 5:23:25 time: 0.5954 data_time: 0.0368 memory: 14901 loss: 1.1681 loss_prob: 0.6147 loss_thr: 0.4487 loss_db: 0.1046 2022/11/02 19:49:03 - mmengine - INFO - Epoch(train) [688][35/63] lr: 1.0058e-03 eta: 5:23:25 time: 0.5390 data_time: 0.0242 memory: 14901 loss: 1.2398 loss_prob: 0.6545 loss_thr: 0.4751 loss_db: 0.1101 2022/11/02 19:49:05 - mmengine - INFO - Epoch(train) [688][40/63] lr: 1.0058e-03 eta: 5:23:19 time: 0.5298 data_time: 0.0120 memory: 14901 loss: 1.2121 loss_prob: 0.6326 loss_thr: 0.4724 loss_db: 0.1071 2022/11/02 19:49:08 - mmengine - INFO - Epoch(train) [688][45/63] lr: 1.0058e-03 eta: 5:23:19 time: 0.5032 data_time: 0.0096 memory: 14901 loss: 1.1339 loss_prob: 0.5950 loss_thr: 0.4374 loss_db: 0.1016 2022/11/02 19:49:11 - mmengine - INFO - Epoch(train) [688][50/63] lr: 1.0058e-03 eta: 5:23:12 time: 0.5456 data_time: 0.0160 memory: 14901 loss: 1.0707 loss_prob: 0.5595 loss_thr: 0.4146 loss_db: 0.0966 2022/11/02 19:49:13 - mmengine - INFO - Epoch(train) [688][55/63] lr: 1.0058e-03 eta: 5:23:12 time: 0.5666 data_time: 0.0271 memory: 14901 loss: 1.0606 loss_prob: 0.5552 loss_thr: 0.4087 loss_db: 0.0967 2022/11/02 19:49:16 - mmengine - INFO - Epoch(train) [688][60/63] lr: 1.0058e-03 eta: 5:23:06 time: 0.5407 data_time: 0.0209 memory: 14901 loss: 1.0666 loss_prob: 0.5569 loss_thr: 0.4125 loss_db: 0.0973 2022/11/02 19:49:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:49:24 - mmengine - INFO - Epoch(train) [689][5/63] lr: 1.0040e-03 eta: 5:23:06 time: 0.8897 data_time: 0.2371 memory: 14901 loss: 1.2536 loss_prob: 0.6782 loss_thr: 0.4582 loss_db: 0.1172 2022/11/02 19:49:28 - mmengine - INFO - Epoch(train) [689][10/63] lr: 1.0040e-03 eta: 5:23:00 time: 1.0402 data_time: 0.2359 memory: 14901 loss: 1.2239 loss_prob: 0.6581 loss_thr: 0.4529 loss_db: 0.1129 2022/11/02 19:49:32 - mmengine - INFO - Epoch(train) [689][15/63] lr: 1.0040e-03 eta: 5:23:00 time: 0.7966 data_time: 0.0106 memory: 14901 loss: 1.0560 loss_prob: 0.5565 loss_thr: 0.4027 loss_db: 0.0968 2022/11/02 19:49:35 - mmengine - INFO - Epoch(train) [689][20/63] lr: 1.0040e-03 eta: 5:22:55 time: 0.6633 data_time: 0.0139 memory: 14901 loss: 1.0857 loss_prob: 0.5721 loss_thr: 0.4149 loss_db: 0.0987 2022/11/02 19:49:40 - mmengine - INFO - Epoch(train) [689][25/63] lr: 1.0040e-03 eta: 5:22:55 time: 0.7719 data_time: 0.0380 memory: 14901 loss: 1.0946 loss_prob: 0.5740 loss_thr: 0.4204 loss_db: 0.1002 2022/11/02 19:49:42 - mmengine - INFO - Epoch(train) [689][30/63] lr: 1.0040e-03 eta: 5:22:50 time: 0.7562 data_time: 0.0357 memory: 14901 loss: 1.0598 loss_prob: 0.5539 loss_thr: 0.4083 loss_db: 0.0977 2022/11/02 19:49:45 - mmengine - INFO - Epoch(train) [689][35/63] lr: 1.0040e-03 eta: 5:22:50 time: 0.5070 data_time: 0.0106 memory: 14901 loss: 1.0007 loss_prob: 0.5188 loss_thr: 0.3908 loss_db: 0.0911 2022/11/02 19:49:47 - mmengine - INFO - Epoch(train) [689][40/63] lr: 1.0040e-03 eta: 5:22:43 time: 0.5022 data_time: 0.0126 memory: 14901 loss: 1.0417 loss_prob: 0.5414 loss_thr: 0.4067 loss_db: 0.0935 2022/11/02 19:49:50 - mmengine - INFO - Epoch(train) [689][45/63] lr: 1.0040e-03 eta: 5:22:43 time: 0.5093 data_time: 0.0209 memory: 14901 loss: 1.1489 loss_prob: 0.6125 loss_thr: 0.4321 loss_db: 0.1043 2022/11/02 19:49:53 - mmengine - INFO - Epoch(train) [689][50/63] lr: 1.0040e-03 eta: 5:22:37 time: 0.5563 data_time: 0.0303 memory: 14901 loss: 1.1147 loss_prob: 0.5901 loss_thr: 0.4233 loss_db: 0.1013 2022/11/02 19:49:56 - mmengine - INFO - Epoch(train) [689][55/63] lr: 1.0040e-03 eta: 5:22:37 time: 0.5817 data_time: 0.0207 memory: 14901 loss: 1.1051 loss_prob: 0.5792 loss_thr: 0.4268 loss_db: 0.0992 2022/11/02 19:49:58 - mmengine - INFO - Epoch(train) [689][60/63] lr: 1.0040e-03 eta: 5:22:30 time: 0.5330 data_time: 0.0084 memory: 14901 loss: 1.0998 loss_prob: 0.5848 loss_thr: 0.4151 loss_db: 0.1000 2022/11/02 19:49:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:50:06 - mmengine - INFO - Epoch(train) [690][5/63] lr: 1.0022e-03 eta: 5:22:30 time: 0.8558 data_time: 0.3054 memory: 14901 loss: 1.1480 loss_prob: 0.6111 loss_thr: 0.4290 loss_db: 0.1079 2022/11/02 19:50:09 - mmengine - INFO - Epoch(train) [690][10/63] lr: 1.0022e-03 eta: 5:22:23 time: 0.9120 data_time: 0.3068 memory: 14901 loss: 1.0663 loss_prob: 0.5609 loss_thr: 0.4084 loss_db: 0.0970 2022/11/02 19:50:12 - mmengine - INFO - Epoch(train) [690][15/63] lr: 1.0022e-03 eta: 5:22:23 time: 0.6237 data_time: 0.0078 memory: 14901 loss: 1.0734 loss_prob: 0.5638 loss_thr: 0.4131 loss_db: 0.0965 2022/11/02 19:50:15 - mmengine - INFO - Epoch(train) [690][20/63] lr: 1.0022e-03 eta: 5:22:18 time: 0.6391 data_time: 0.0100 memory: 14901 loss: 1.1217 loss_prob: 0.5931 loss_thr: 0.4268 loss_db: 0.1018 2022/11/02 19:50:19 - mmengine - INFO - Epoch(train) [690][25/63] lr: 1.0022e-03 eta: 5:22:18 time: 0.7379 data_time: 0.0325 memory: 14901 loss: 1.0965 loss_prob: 0.5779 loss_thr: 0.4183 loss_db: 0.1003 2022/11/02 19:50:22 - mmengine - INFO - Epoch(train) [690][30/63] lr: 1.0022e-03 eta: 5:22:12 time: 0.7093 data_time: 0.0519 memory: 14901 loss: 1.0788 loss_prob: 0.5689 loss_thr: 0.4112 loss_db: 0.0987 2022/11/02 19:50:25 - mmengine - INFO - Epoch(train) [690][35/63] lr: 1.0022e-03 eta: 5:22:12 time: 0.5260 data_time: 0.0304 memory: 14901 loss: 1.2210 loss_prob: 0.6689 loss_thr: 0.4433 loss_db: 0.1088 2022/11/02 19:50:27 - mmengine - INFO - Epoch(train) [690][40/63] lr: 1.0022e-03 eta: 5:22:06 time: 0.5109 data_time: 0.0106 memory: 14901 loss: 1.2022 loss_prob: 0.6420 loss_thr: 0.4557 loss_db: 0.1045 2022/11/02 19:50:30 - mmengine - INFO - Epoch(train) [690][45/63] lr: 1.0022e-03 eta: 5:22:06 time: 0.5297 data_time: 0.0106 memory: 14901 loss: 1.1430 loss_prob: 0.5913 loss_thr: 0.4508 loss_db: 0.1010 2022/11/02 19:50:33 - mmengine - INFO - Epoch(train) [690][50/63] lr: 1.0022e-03 eta: 5:22:00 time: 0.6162 data_time: 0.0355 memory: 14901 loss: 1.1209 loss_prob: 0.5881 loss_thr: 0.4330 loss_db: 0.0998 2022/11/02 19:50:36 - mmengine - INFO - Epoch(train) [690][55/63] lr: 1.0022e-03 eta: 5:22:00 time: 0.6043 data_time: 0.0385 memory: 14901 loss: 1.0314 loss_prob: 0.5466 loss_thr: 0.3918 loss_db: 0.0930 2022/11/02 19:50:39 - mmengine - INFO - Epoch(train) [690][60/63] lr: 1.0022e-03 eta: 5:21:53 time: 0.5442 data_time: 0.0147 memory: 14901 loss: 1.1157 loss_prob: 0.6072 loss_thr: 0.4089 loss_db: 0.0996 2022/11/02 19:50:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:50:48 - mmengine - INFO - Epoch(train) [691][5/63] lr: 1.0005e-03 eta: 5:21:53 time: 1.0054 data_time: 0.2568 memory: 14901 loss: 1.2238 loss_prob: 0.6664 loss_thr: 0.4497 loss_db: 0.1077 2022/11/02 19:50:51 - mmengine - INFO - Epoch(train) [691][10/63] lr: 1.0005e-03 eta: 5:21:47 time: 1.0473 data_time: 0.2547 memory: 14901 loss: 1.3154 loss_prob: 0.7362 loss_thr: 0.4583 loss_db: 0.1210 2022/11/02 19:50:54 - mmengine - INFO - Epoch(train) [691][15/63] lr: 1.0005e-03 eta: 5:21:47 time: 0.6163 data_time: 0.0197 memory: 14901 loss: 1.3542 loss_prob: 0.7740 loss_thr: 0.4534 loss_db: 0.1268 2022/11/02 19:50:57 - mmengine - INFO - Epoch(train) [691][20/63] lr: 1.0005e-03 eta: 5:21:41 time: 0.5756 data_time: 0.0202 memory: 14901 loss: 1.2067 loss_prob: 0.6562 loss_thr: 0.4368 loss_db: 0.1137 2022/11/02 19:51:00 - mmengine - INFO - Epoch(train) [691][25/63] lr: 1.0005e-03 eta: 5:21:41 time: 0.5708 data_time: 0.0307 memory: 14901 loss: 1.2353 loss_prob: 0.6767 loss_thr: 0.4429 loss_db: 0.1157 2022/11/02 19:51:02 - mmengine - INFO - Epoch(train) [691][30/63] lr: 1.0005e-03 eta: 5:21:35 time: 0.5706 data_time: 0.0455 memory: 14901 loss: 1.2512 loss_prob: 0.6864 loss_thr: 0.4508 loss_db: 0.1141 2022/11/02 19:51:05 - mmengine - INFO - Epoch(train) [691][35/63] lr: 1.0005e-03 eta: 5:21:35 time: 0.5304 data_time: 0.0307 memory: 14901 loss: 1.1474 loss_prob: 0.6092 loss_thr: 0.4330 loss_db: 0.1052 2022/11/02 19:51:08 - mmengine - INFO - Epoch(train) [691][40/63] lr: 1.0005e-03 eta: 5:21:29 time: 0.5358 data_time: 0.0209 memory: 14901 loss: 1.1796 loss_prob: 0.6317 loss_thr: 0.4363 loss_db: 0.1116 2022/11/02 19:51:11 - mmengine - INFO - Epoch(train) [691][45/63] lr: 1.0005e-03 eta: 5:21:29 time: 0.5687 data_time: 0.0151 memory: 14901 loss: 1.1737 loss_prob: 0.6268 loss_thr: 0.4378 loss_db: 0.1091 2022/11/02 19:51:14 - mmengine - INFO - Epoch(train) [691][50/63] lr: 1.0005e-03 eta: 5:21:23 time: 0.6132 data_time: 0.0206 memory: 14901 loss: 1.0658 loss_prob: 0.5555 loss_thr: 0.4137 loss_db: 0.0966 2022/11/02 19:51:17 - mmengine - INFO - Epoch(train) [691][55/63] lr: 1.0005e-03 eta: 5:21:23 time: 0.6867 data_time: 0.0250 memory: 14901 loss: 1.1123 loss_prob: 0.5916 loss_thr: 0.4178 loss_db: 0.1028 2022/11/02 19:51:21 - mmengine - INFO - Epoch(train) [691][60/63] lr: 1.0005e-03 eta: 5:21:17 time: 0.6993 data_time: 0.0235 memory: 14901 loss: 1.1717 loss_prob: 0.6299 loss_thr: 0.4344 loss_db: 0.1075 2022/11/02 19:51:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:51:29 - mmengine - INFO - Epoch(train) [692][5/63] lr: 9.9869e-04 eta: 5:21:17 time: 0.9331 data_time: 0.2248 memory: 14901 loss: 1.0874 loss_prob: 0.5751 loss_thr: 0.4103 loss_db: 0.1020 2022/11/02 19:51:32 - mmengine - INFO - Epoch(train) [692][10/63] lr: 9.9869e-04 eta: 5:21:11 time: 0.9982 data_time: 0.2211 memory: 14901 loss: 1.0524 loss_prob: 0.5480 loss_thr: 0.4062 loss_db: 0.0981 2022/11/02 19:51:35 - mmengine - INFO - Epoch(train) [692][15/63] lr: 9.9869e-04 eta: 5:21:11 time: 0.6290 data_time: 0.0202 memory: 14901 loss: 1.1626 loss_prob: 0.6221 loss_thr: 0.4325 loss_db: 0.1080 2022/11/02 19:51:38 - mmengine - INFO - Epoch(train) [692][20/63] lr: 9.9869e-04 eta: 5:21:05 time: 0.6214 data_time: 0.0181 memory: 14901 loss: 1.3256 loss_prob: 0.7342 loss_thr: 0.4641 loss_db: 0.1273 2022/11/02 19:51:41 - mmengine - INFO - Epoch(train) [692][25/63] lr: 9.9869e-04 eta: 5:21:05 time: 0.5751 data_time: 0.0200 memory: 14901 loss: 1.4127 loss_prob: 0.7878 loss_thr: 0.4873 loss_db: 0.1377 2022/11/02 19:51:44 - mmengine - INFO - Epoch(train) [692][30/63] lr: 9.9869e-04 eta: 5:20:59 time: 0.5406 data_time: 0.0367 memory: 14901 loss: 1.2782 loss_prob: 0.6971 loss_thr: 0.4605 loss_db: 0.1206 2022/11/02 19:51:47 - mmengine - INFO - Epoch(train) [692][35/63] lr: 9.9869e-04 eta: 5:20:59 time: 0.6074 data_time: 0.0374 memory: 14901 loss: 1.1606 loss_prob: 0.6159 loss_thr: 0.4404 loss_db: 0.1044 2022/11/02 19:51:49 - mmengine - INFO - Epoch(train) [692][40/63] lr: 9.9869e-04 eta: 5:20:52 time: 0.5598 data_time: 0.0191 memory: 14901 loss: 1.2371 loss_prob: 0.6620 loss_thr: 0.4623 loss_db: 0.1128 2022/11/02 19:51:52 - mmengine - INFO - Epoch(train) [692][45/63] lr: 9.9869e-04 eta: 5:20:52 time: 0.5372 data_time: 0.0088 memory: 14901 loss: 1.2469 loss_prob: 0.6795 loss_thr: 0.4524 loss_db: 0.1149 2022/11/02 19:51:56 - mmengine - INFO - Epoch(train) [692][50/63] lr: 9.9869e-04 eta: 5:20:47 time: 0.6182 data_time: 0.0157 memory: 14901 loss: 1.1682 loss_prob: 0.6317 loss_thr: 0.4303 loss_db: 0.1062 2022/11/02 19:51:59 - mmengine - INFO - Epoch(train) [692][55/63] lr: 9.9869e-04 eta: 5:20:47 time: 0.6873 data_time: 0.0286 memory: 14901 loss: 1.1507 loss_prob: 0.6126 loss_thr: 0.4311 loss_db: 0.1070 2022/11/02 19:52:03 - mmengine - INFO - Epoch(train) [692][60/63] lr: 9.9869e-04 eta: 5:20:41 time: 0.7112 data_time: 0.0282 memory: 14901 loss: 1.1484 loss_prob: 0.6002 loss_thr: 0.4432 loss_db: 0.1050 2022/11/02 19:52:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:52:11 - mmengine - INFO - Epoch(train) [693][5/63] lr: 9.9692e-04 eta: 5:20:41 time: 0.9938 data_time: 0.2875 memory: 14901 loss: 1.0952 loss_prob: 0.5603 loss_thr: 0.4367 loss_db: 0.0981 2022/11/02 19:52:14 - mmengine - INFO - Epoch(train) [693][10/63] lr: 9.9692e-04 eta: 5:20:35 time: 1.0048 data_time: 0.2825 memory: 14901 loss: 1.1579 loss_prob: 0.6094 loss_thr: 0.4418 loss_db: 0.1067 2022/11/02 19:52:17 - mmengine - INFO - Epoch(train) [693][15/63] lr: 9.9692e-04 eta: 5:20:35 time: 0.6054 data_time: 0.0127 memory: 14901 loss: 1.1912 loss_prob: 0.6332 loss_thr: 0.4482 loss_db: 0.1098 2022/11/02 19:52:20 - mmengine - INFO - Epoch(train) [693][20/63] lr: 9.9692e-04 eta: 5:20:29 time: 0.5796 data_time: 0.0135 memory: 14901 loss: 1.1403 loss_prob: 0.6005 loss_thr: 0.4371 loss_db: 0.1027 2022/11/02 19:52:25 - mmengine - INFO - Epoch(train) [693][25/63] lr: 9.9692e-04 eta: 5:20:29 time: 0.7307 data_time: 0.0362 memory: 14901 loss: 1.1046 loss_prob: 0.5908 loss_thr: 0.4118 loss_db: 0.1021 2022/11/02 19:52:27 - mmengine - INFO - Epoch(train) [693][30/63] lr: 9.9692e-04 eta: 5:20:24 time: 0.7034 data_time: 0.0363 memory: 14901 loss: 1.0885 loss_prob: 0.5783 loss_thr: 0.4092 loss_db: 0.1010 2022/11/02 19:52:30 - mmengine - INFO - Epoch(train) [693][35/63] lr: 9.9692e-04 eta: 5:20:24 time: 0.5148 data_time: 0.0180 memory: 14901 loss: 1.1697 loss_prob: 0.6152 loss_thr: 0.4492 loss_db: 0.1053 2022/11/02 19:52:32 - mmengine - INFO - Epoch(train) [693][40/63] lr: 9.9692e-04 eta: 5:20:17 time: 0.5023 data_time: 0.0174 memory: 14901 loss: 1.0984 loss_prob: 0.5671 loss_thr: 0.4329 loss_db: 0.0984 2022/11/02 19:52:35 - mmengine - INFO - Epoch(train) [693][45/63] lr: 9.9692e-04 eta: 5:20:17 time: 0.5097 data_time: 0.0096 memory: 14901 loss: 1.0706 loss_prob: 0.5545 loss_thr: 0.4201 loss_db: 0.0961 2022/11/02 19:52:38 - mmengine - INFO - Epoch(train) [693][50/63] lr: 9.9692e-04 eta: 5:20:11 time: 0.5628 data_time: 0.0277 memory: 14901 loss: 1.2487 loss_prob: 0.6839 loss_thr: 0.4508 loss_db: 0.1140 2022/11/02 19:52:42 - mmengine - INFO - Epoch(train) [693][55/63] lr: 9.9692e-04 eta: 5:20:11 time: 0.6906 data_time: 0.0288 memory: 14901 loss: 1.1563 loss_prob: 0.6278 loss_thr: 0.4232 loss_db: 0.1053 2022/11/02 19:52:45 - mmengine - INFO - Epoch(train) [693][60/63] lr: 9.9692e-04 eta: 5:20:05 time: 0.6994 data_time: 0.0139 memory: 14901 loss: 1.0236 loss_prob: 0.5337 loss_thr: 0.3975 loss_db: 0.0925 2022/11/02 19:52:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:52:53 - mmengine - INFO - Epoch(train) [694][5/63] lr: 9.9515e-04 eta: 5:20:05 time: 0.9088 data_time: 0.2922 memory: 14901 loss: 1.1187 loss_prob: 0.5847 loss_thr: 0.4342 loss_db: 0.0998 2022/11/02 19:52:56 - mmengine - INFO - Epoch(train) [694][10/63] lr: 9.9515e-04 eta: 5:19:59 time: 0.9597 data_time: 0.2918 memory: 14901 loss: 1.1494 loss_prob: 0.6047 loss_thr: 0.4402 loss_db: 0.1044 2022/11/02 19:52:58 - mmengine - INFO - Epoch(train) [694][15/63] lr: 9.9515e-04 eta: 5:19:59 time: 0.5690 data_time: 0.0126 memory: 14901 loss: 1.1809 loss_prob: 0.6223 loss_thr: 0.4494 loss_db: 0.1093 2022/11/02 19:53:02 - mmengine - INFO - Epoch(train) [694][20/63] lr: 9.9515e-04 eta: 5:19:53 time: 0.6073 data_time: 0.0114 memory: 14901 loss: 1.2037 loss_prob: 0.6371 loss_thr: 0.4567 loss_db: 0.1099 2022/11/02 19:53:06 - mmengine - INFO - Epoch(train) [694][25/63] lr: 9.9515e-04 eta: 5:19:53 time: 0.7725 data_time: 0.0257 memory: 14901 loss: 1.1512 loss_prob: 0.6024 loss_thr: 0.4462 loss_db: 0.1026 2022/11/02 19:53:09 - mmengine - INFO - Epoch(train) [694][30/63] lr: 9.9515e-04 eta: 5:19:48 time: 0.6923 data_time: 0.0407 memory: 14901 loss: 1.1090 loss_prob: 0.5801 loss_thr: 0.4289 loss_db: 0.1000 2022/11/02 19:53:11 - mmengine - INFO - Epoch(train) [694][35/63] lr: 9.9515e-04 eta: 5:19:48 time: 0.5287 data_time: 0.0315 memory: 14901 loss: 1.1114 loss_prob: 0.5875 loss_thr: 0.4217 loss_db: 0.1023 2022/11/02 19:53:14 - mmengine - INFO - Epoch(train) [694][40/63] lr: 9.9515e-04 eta: 5:19:41 time: 0.5066 data_time: 0.0175 memory: 14901 loss: 1.0740 loss_prob: 0.5626 loss_thr: 0.4132 loss_db: 0.0982 2022/11/02 19:53:17 - mmengine - INFO - Epoch(train) [694][45/63] lr: 9.9515e-04 eta: 5:19:41 time: 0.5085 data_time: 0.0115 memory: 14901 loss: 0.9925 loss_prob: 0.5172 loss_thr: 0.3866 loss_db: 0.0886 2022/11/02 19:53:19 - mmengine - INFO - Epoch(train) [694][50/63] lr: 9.9515e-04 eta: 5:19:34 time: 0.5190 data_time: 0.0223 memory: 14901 loss: 1.0240 loss_prob: 0.5349 loss_thr: 0.3959 loss_db: 0.0932 2022/11/02 19:53:22 - mmengine - INFO - Epoch(train) [694][55/63] lr: 9.9515e-04 eta: 5:19:34 time: 0.5190 data_time: 0.0252 memory: 14901 loss: 1.0813 loss_prob: 0.5687 loss_thr: 0.4119 loss_db: 0.1007 2022/11/02 19:53:24 - mmengine - INFO - Epoch(train) [694][60/63] lr: 9.9515e-04 eta: 5:19:28 time: 0.5189 data_time: 0.0187 memory: 14901 loss: 1.0388 loss_prob: 0.5489 loss_thr: 0.3971 loss_db: 0.0928 2022/11/02 19:53:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:53:32 - mmengine - INFO - Epoch(train) [695][5/63] lr: 9.9338e-04 eta: 5:19:28 time: 0.8792 data_time: 0.2675 memory: 14901 loss: 1.1581 loss_prob: 0.6105 loss_thr: 0.4407 loss_db: 0.1070 2022/11/02 19:53:36 - mmengine - INFO - Epoch(train) [695][10/63] lr: 9.9338e-04 eta: 5:19:21 time: 1.0005 data_time: 0.2685 memory: 14901 loss: 1.1342 loss_prob: 0.5962 loss_thr: 0.4338 loss_db: 0.1043 2022/11/02 19:53:39 - mmengine - INFO - Epoch(train) [695][15/63] lr: 9.9338e-04 eta: 5:19:21 time: 0.6489 data_time: 0.0136 memory: 14901 loss: 1.1640 loss_prob: 0.6099 loss_thr: 0.4477 loss_db: 0.1064 2022/11/02 19:53:42 - mmengine - INFO - Epoch(train) [695][20/63] lr: 9.9338e-04 eta: 5:19:16 time: 0.6601 data_time: 0.0103 memory: 14901 loss: 1.1813 loss_prob: 0.6197 loss_thr: 0.4531 loss_db: 0.1086 2022/11/02 19:53:46 - mmengine - INFO - Epoch(train) [695][25/63] lr: 9.9338e-04 eta: 5:19:16 time: 0.7340 data_time: 0.0356 memory: 14901 loss: 1.0990 loss_prob: 0.5780 loss_thr: 0.4224 loss_db: 0.0986 2022/11/02 19:53:50 - mmengine - INFO - Epoch(train) [695][30/63] lr: 9.9338e-04 eta: 5:19:11 time: 0.7530 data_time: 0.0470 memory: 14901 loss: 1.0541 loss_prob: 0.5534 loss_thr: 0.4050 loss_db: 0.0957 2022/11/02 19:53:52 - mmengine - INFO - Epoch(train) [695][35/63] lr: 9.9338e-04 eta: 5:19:11 time: 0.6537 data_time: 0.0184 memory: 14901 loss: 1.0521 loss_prob: 0.5519 loss_thr: 0.4039 loss_db: 0.0963 2022/11/02 19:53:55 - mmengine - INFO - Epoch(train) [695][40/63] lr: 9.9338e-04 eta: 5:19:04 time: 0.5255 data_time: 0.0068 memory: 14901 loss: 1.0169 loss_prob: 0.5301 loss_thr: 0.3963 loss_db: 0.0906 2022/11/02 19:53:58 - mmengine - INFO - Epoch(train) [695][45/63] lr: 9.9338e-04 eta: 5:19:04 time: 0.5282 data_time: 0.0093 memory: 14901 loss: 1.0432 loss_prob: 0.5459 loss_thr: 0.4021 loss_db: 0.0953 2022/11/02 19:54:01 - mmengine - INFO - Epoch(train) [695][50/63] lr: 9.9338e-04 eta: 5:18:58 time: 0.5933 data_time: 0.0523 memory: 14901 loss: 1.0383 loss_prob: 0.5376 loss_thr: 0.4078 loss_db: 0.0928 2022/11/02 19:54:04 - mmengine - INFO - Epoch(train) [695][55/63] lr: 9.9338e-04 eta: 5:18:58 time: 0.5776 data_time: 0.0539 memory: 14901 loss: 1.0115 loss_prob: 0.5167 loss_thr: 0.4058 loss_db: 0.0891 2022/11/02 19:54:07 - mmengine - INFO - Epoch(train) [695][60/63] lr: 9.9338e-04 eta: 5:18:52 time: 0.5797 data_time: 0.0136 memory: 14901 loss: 1.0918 loss_prob: 0.5721 loss_thr: 0.4197 loss_db: 0.1001 2022/11/02 19:54:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:54:16 - mmengine - INFO - Epoch(train) [696][5/63] lr: 9.9161e-04 eta: 5:18:52 time: 1.0540 data_time: 0.2604 memory: 14901 loss: 1.2195 loss_prob: 0.6634 loss_thr: 0.4458 loss_db: 0.1103 2022/11/02 19:54:19 - mmengine - INFO - Epoch(train) [696][10/63] lr: 9.9161e-04 eta: 5:18:46 time: 1.0155 data_time: 0.2596 memory: 14901 loss: 1.1811 loss_prob: 0.6378 loss_thr: 0.4378 loss_db: 0.1055 2022/11/02 19:54:22 - mmengine - INFO - Epoch(train) [696][15/63] lr: 9.9161e-04 eta: 5:18:46 time: 0.6518 data_time: 0.0118 memory: 14901 loss: 1.0621 loss_prob: 0.5527 loss_thr: 0.4146 loss_db: 0.0948 2022/11/02 19:54:25 - mmengine - INFO - Epoch(train) [696][20/63] lr: 9.9161e-04 eta: 5:18:40 time: 0.6021 data_time: 0.0094 memory: 14901 loss: 0.9995 loss_prob: 0.5155 loss_thr: 0.3939 loss_db: 0.0901 2022/11/02 19:54:29 - mmengine - INFO - Epoch(train) [696][25/63] lr: 9.9161e-04 eta: 5:18:40 time: 0.6698 data_time: 0.0371 memory: 14901 loss: 0.9865 loss_prob: 0.5108 loss_thr: 0.3869 loss_db: 0.0888 2022/11/02 19:54:32 - mmengine - INFO - Epoch(train) [696][30/63] lr: 9.9161e-04 eta: 5:18:35 time: 0.7012 data_time: 0.0377 memory: 14901 loss: 0.9897 loss_prob: 0.5128 loss_thr: 0.3875 loss_db: 0.0893 2022/11/02 19:54:36 - mmengine - INFO - Epoch(train) [696][35/63] lr: 9.9161e-04 eta: 5:18:35 time: 0.7126 data_time: 0.0136 memory: 14901 loss: 1.0151 loss_prob: 0.5302 loss_thr: 0.3928 loss_db: 0.0921 2022/11/02 19:54:39 - mmengine - INFO - Epoch(train) [696][40/63] lr: 9.9161e-04 eta: 5:18:29 time: 0.6784 data_time: 0.0137 memory: 14901 loss: 1.0553 loss_prob: 0.5548 loss_thr: 0.4057 loss_db: 0.0948 2022/11/02 19:54:42 - mmengine - INFO - Epoch(train) [696][45/63] lr: 9.9161e-04 eta: 5:18:29 time: 0.5914 data_time: 0.0102 memory: 14901 loss: 1.0838 loss_prob: 0.5722 loss_thr: 0.4135 loss_db: 0.0982 2022/11/02 19:54:45 - mmengine - INFO - Epoch(train) [696][50/63] lr: 9.9161e-04 eta: 5:18:23 time: 0.5540 data_time: 0.0260 memory: 14901 loss: 1.1586 loss_prob: 0.6182 loss_thr: 0.4339 loss_db: 0.1065 2022/11/02 19:54:47 - mmengine - INFO - Epoch(train) [696][55/63] lr: 9.9161e-04 eta: 5:18:23 time: 0.5353 data_time: 0.0260 memory: 14901 loss: 1.1715 loss_prob: 0.6281 loss_thr: 0.4353 loss_db: 0.1081 2022/11/02 19:54:50 - mmengine - INFO - Epoch(train) [696][60/63] lr: 9.9161e-04 eta: 5:18:17 time: 0.5714 data_time: 0.0154 memory: 14901 loss: 1.0636 loss_prob: 0.5618 loss_thr: 0.4038 loss_db: 0.0979 2022/11/02 19:54:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:54:58 - mmengine - INFO - Epoch(train) [697][5/63] lr: 9.8984e-04 eta: 5:18:17 time: 0.9162 data_time: 0.1992 memory: 14901 loss: 1.0747 loss_prob: 0.5714 loss_thr: 0.4046 loss_db: 0.0987 2022/11/02 19:55:01 - mmengine - INFO - Epoch(train) [697][10/63] lr: 9.8984e-04 eta: 5:18:10 time: 0.9355 data_time: 0.2019 memory: 14901 loss: 1.0407 loss_prob: 0.5617 loss_thr: 0.3828 loss_db: 0.0961 2022/11/02 19:55:04 - mmengine - INFO - Epoch(train) [697][15/63] lr: 9.8984e-04 eta: 5:18:10 time: 0.6130 data_time: 0.0089 memory: 14901 loss: 1.2216 loss_prob: 0.6822 loss_thr: 0.4287 loss_db: 0.1107 2022/11/02 19:55:07 - mmengine - INFO - Epoch(train) [697][20/63] lr: 9.8984e-04 eta: 5:18:04 time: 0.6029 data_time: 0.0094 memory: 14901 loss: 1.1560 loss_prob: 0.6306 loss_thr: 0.4221 loss_db: 0.1033 2022/11/02 19:55:10 - mmengine - INFO - Epoch(train) [697][25/63] lr: 9.8984e-04 eta: 5:18:04 time: 0.5871 data_time: 0.0275 memory: 14901 loss: 0.9946 loss_prob: 0.5110 loss_thr: 0.3947 loss_db: 0.0889 2022/11/02 19:55:14 - mmengine - INFO - Epoch(train) [697][30/63] lr: 9.8984e-04 eta: 5:17:58 time: 0.6603 data_time: 0.0483 memory: 14901 loss: 1.0103 loss_prob: 0.5210 loss_thr: 0.3998 loss_db: 0.0895 2022/11/02 19:55:17 - mmengine - INFO - Epoch(train) [697][35/63] lr: 9.8984e-04 eta: 5:17:58 time: 0.6339 data_time: 0.0326 memory: 14901 loss: 1.1390 loss_prob: 0.6024 loss_thr: 0.4322 loss_db: 0.1043 2022/11/02 19:55:19 - mmengine - INFO - Epoch(train) [697][40/63] lr: 9.8984e-04 eta: 5:17:52 time: 0.5744 data_time: 0.0112 memory: 14901 loss: 1.2612 loss_prob: 0.6895 loss_thr: 0.4560 loss_db: 0.1157 2022/11/02 19:55:22 - mmengine - INFO - Epoch(train) [697][45/63] lr: 9.8984e-04 eta: 5:17:52 time: 0.5521 data_time: 0.0140 memory: 14901 loss: 1.1865 loss_prob: 0.6402 loss_thr: 0.4393 loss_db: 0.1070 2022/11/02 19:55:25 - mmengine - INFO - Epoch(train) [697][50/63] lr: 9.8984e-04 eta: 5:17:46 time: 0.5551 data_time: 0.0232 memory: 14901 loss: 1.1116 loss_prob: 0.5868 loss_thr: 0.4245 loss_db: 0.1003 2022/11/02 19:55:28 - mmengine - INFO - Epoch(train) [697][55/63] lr: 9.8984e-04 eta: 5:17:46 time: 0.5687 data_time: 0.0359 memory: 14901 loss: 1.1593 loss_prob: 0.6202 loss_thr: 0.4320 loss_db: 0.1071 2022/11/02 19:55:31 - mmengine - INFO - Epoch(train) [697][60/63] lr: 9.8984e-04 eta: 5:17:40 time: 0.5935 data_time: 0.0270 memory: 14901 loss: 1.1988 loss_prob: 0.6348 loss_thr: 0.4529 loss_db: 0.1112 2022/11/02 19:55:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:55:39 - mmengine - INFO - Epoch(train) [698][5/63] lr: 9.8807e-04 eta: 5:17:40 time: 0.9142 data_time: 0.2232 memory: 14901 loss: 1.1109 loss_prob: 0.5801 loss_thr: 0.4299 loss_db: 0.1008 2022/11/02 19:55:42 - mmengine - INFO - Epoch(train) [698][10/63] lr: 9.8807e-04 eta: 5:17:33 time: 0.9632 data_time: 0.2358 memory: 14901 loss: 1.1008 loss_prob: 0.5777 loss_thr: 0.4216 loss_db: 0.1014 2022/11/02 19:55:45 - mmengine - INFO - Epoch(train) [698][15/63] lr: 9.8807e-04 eta: 5:17:33 time: 0.6656 data_time: 0.0227 memory: 14901 loss: 1.1354 loss_prob: 0.6024 loss_thr: 0.4301 loss_db: 0.1029 2022/11/02 19:55:49 - mmengine - INFO - Epoch(train) [698][20/63] lr: 9.8807e-04 eta: 5:17:28 time: 0.6588 data_time: 0.0134 memory: 14901 loss: 1.1185 loss_prob: 0.5848 loss_thr: 0.4358 loss_db: 0.0979 2022/11/02 19:55:52 - mmengine - INFO - Epoch(train) [698][25/63] lr: 9.8807e-04 eta: 5:17:28 time: 0.6106 data_time: 0.0183 memory: 14901 loss: 1.0729 loss_prob: 0.5516 loss_thr: 0.4267 loss_db: 0.0946 2022/11/02 19:55:55 - mmengine - INFO - Epoch(train) [698][30/63] lr: 9.8807e-04 eta: 5:17:22 time: 0.6660 data_time: 0.0384 memory: 14901 loss: 1.1470 loss_prob: 0.6090 loss_thr: 0.4336 loss_db: 0.1045 2022/11/02 19:55:59 - mmengine - INFO - Epoch(train) [698][35/63] lr: 9.8807e-04 eta: 5:17:22 time: 0.6979 data_time: 0.0364 memory: 14901 loss: 1.1300 loss_prob: 0.6141 loss_thr: 0.4108 loss_db: 0.1051 2022/11/02 19:56:02 - mmengine - INFO - Epoch(train) [698][40/63] lr: 9.8807e-04 eta: 5:17:16 time: 0.6242 data_time: 0.0142 memory: 14901 loss: 1.0843 loss_prob: 0.5780 loss_thr: 0.4061 loss_db: 0.1001 2022/11/02 19:56:04 - mmengine - INFO - Epoch(train) [698][45/63] lr: 9.8807e-04 eta: 5:17:16 time: 0.5802 data_time: 0.0121 memory: 14901 loss: 1.2117 loss_prob: 0.6459 loss_thr: 0.4551 loss_db: 0.1107 2022/11/02 19:56:07 - mmengine - INFO - Epoch(train) [698][50/63] lr: 9.8807e-04 eta: 5:17:10 time: 0.5344 data_time: 0.0250 memory: 14901 loss: 1.1710 loss_prob: 0.6224 loss_thr: 0.4411 loss_db: 0.1075 2022/11/02 19:56:10 - mmengine - INFO - Epoch(train) [698][55/63] lr: 9.8807e-04 eta: 5:17:10 time: 0.5474 data_time: 0.0312 memory: 14901 loss: 1.1094 loss_prob: 0.5787 loss_thr: 0.4299 loss_db: 0.1007 2022/11/02 19:56:13 - mmengine - INFO - Epoch(train) [698][60/63] lr: 9.8807e-04 eta: 5:17:04 time: 0.5793 data_time: 0.0233 memory: 14901 loss: 1.0877 loss_prob: 0.5641 loss_thr: 0.4264 loss_db: 0.0972 2022/11/02 19:56:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:56:20 - mmengine - INFO - Epoch(train) [699][5/63] lr: 9.8630e-04 eta: 5:17:04 time: 0.8679 data_time: 0.2766 memory: 14901 loss: 1.0512 loss_prob: 0.5492 loss_thr: 0.4052 loss_db: 0.0968 2022/11/02 19:56:23 - mmengine - INFO - Epoch(train) [699][10/63] lr: 9.8630e-04 eta: 5:16:56 time: 0.8436 data_time: 0.2757 memory: 14901 loss: 1.0854 loss_prob: 0.5761 loss_thr: 0.4082 loss_db: 0.1011 2022/11/02 19:56:26 - mmengine - INFO - Epoch(train) [699][15/63] lr: 9.8630e-04 eta: 5:16:56 time: 0.5396 data_time: 0.0103 memory: 14901 loss: 1.1527 loss_prob: 0.6240 loss_thr: 0.4234 loss_db: 0.1053 2022/11/02 19:56:29 - mmengine - INFO - Epoch(train) [699][20/63] lr: 9.8630e-04 eta: 5:16:50 time: 0.6050 data_time: 0.0109 memory: 14901 loss: 1.1496 loss_prob: 0.6155 loss_thr: 0.4295 loss_db: 0.1047 2022/11/02 19:56:33 - mmengine - INFO - Epoch(train) [699][25/63] lr: 9.8630e-04 eta: 5:16:50 time: 0.7125 data_time: 0.0216 memory: 14901 loss: 1.1188 loss_prob: 0.5849 loss_thr: 0.4303 loss_db: 0.1036 2022/11/02 19:56:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:56:36 - mmengine - INFO - Epoch(train) [699][30/63] lr: 9.8630e-04 eta: 5:16:45 time: 0.7048 data_time: 0.0418 memory: 14901 loss: 1.1273 loss_prob: 0.5891 loss_thr: 0.4350 loss_db: 0.1033 2022/11/02 19:56:39 - mmengine - INFO - Epoch(train) [699][35/63] lr: 9.8630e-04 eta: 5:16:45 time: 0.5795 data_time: 0.0317 memory: 14901 loss: 1.1907 loss_prob: 0.6329 loss_thr: 0.4475 loss_db: 0.1103 2022/11/02 19:56:42 - mmengine - INFO - Epoch(train) [699][40/63] lr: 9.8630e-04 eta: 5:16:39 time: 0.6150 data_time: 0.0115 memory: 14901 loss: 1.1682 loss_prob: 0.6231 loss_thr: 0.4367 loss_db: 0.1084 2022/11/02 19:56:45 - mmengine - INFO - Epoch(train) [699][45/63] lr: 9.8630e-04 eta: 5:16:39 time: 0.6225 data_time: 0.0104 memory: 14901 loss: 1.1077 loss_prob: 0.5876 loss_thr: 0.4178 loss_db: 0.1022 2022/11/02 19:56:48 - mmengine - INFO - Epoch(train) [699][50/63] lr: 9.8630e-04 eta: 5:16:33 time: 0.5527 data_time: 0.0260 memory: 14901 loss: 1.0801 loss_prob: 0.5721 loss_thr: 0.4089 loss_db: 0.0991 2022/11/02 19:56:50 - mmengine - INFO - Epoch(train) [699][55/63] lr: 9.8630e-04 eta: 5:16:33 time: 0.5402 data_time: 0.0257 memory: 14901 loss: 1.0642 loss_prob: 0.5605 loss_thr: 0.4087 loss_db: 0.0950 2022/11/02 19:56:53 - mmengine - INFO - Epoch(train) [699][60/63] lr: 9.8630e-04 eta: 5:16:26 time: 0.5218 data_time: 0.0094 memory: 14901 loss: 1.0812 loss_prob: 0.5707 loss_thr: 0.4106 loss_db: 0.0999 2022/11/02 19:56:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:57:01 - mmengine - INFO - Epoch(train) [700][5/63] lr: 9.8453e-04 eta: 5:16:26 time: 0.9139 data_time: 0.2269 memory: 14901 loss: 1.1658 loss_prob: 0.6186 loss_thr: 0.4388 loss_db: 0.1084 2022/11/02 19:57:04 - mmengine - INFO - Epoch(train) [700][10/63] lr: 9.8453e-04 eta: 5:16:20 time: 0.9724 data_time: 0.2246 memory: 14901 loss: 1.1085 loss_prob: 0.5790 loss_thr: 0.4273 loss_db: 0.1022 2022/11/02 19:57:07 - mmengine - INFO - Epoch(train) [700][15/63] lr: 9.8453e-04 eta: 5:16:20 time: 0.5632 data_time: 0.0116 memory: 14901 loss: 1.0571 loss_prob: 0.5527 loss_thr: 0.4088 loss_db: 0.0955 2022/11/02 19:57:09 - mmengine - INFO - Epoch(train) [700][20/63] lr: 9.8453e-04 eta: 5:16:13 time: 0.5655 data_time: 0.0124 memory: 14901 loss: 1.0810 loss_prob: 0.5742 loss_thr: 0.4103 loss_db: 0.0964 2022/11/02 19:57:14 - mmengine - INFO - Epoch(train) [700][25/63] lr: 9.8453e-04 eta: 5:16:13 time: 0.7464 data_time: 0.0172 memory: 14901 loss: 1.1193 loss_prob: 0.6007 loss_thr: 0.4180 loss_db: 0.1007 2022/11/02 19:57:18 - mmengine - INFO - Epoch(train) [700][30/63] lr: 9.8453e-04 eta: 5:16:09 time: 0.8189 data_time: 0.0438 memory: 14901 loss: 1.0803 loss_prob: 0.5706 loss_thr: 0.4125 loss_db: 0.0972 2022/11/02 19:57:21 - mmengine - INFO - Epoch(train) [700][35/63] lr: 9.8453e-04 eta: 5:16:09 time: 0.7020 data_time: 0.0385 memory: 14901 loss: 1.0837 loss_prob: 0.5641 loss_thr: 0.4224 loss_db: 0.0972 2022/11/02 19:57:24 - mmengine - INFO - Epoch(train) [700][40/63] lr: 9.8453e-04 eta: 5:16:03 time: 0.5896 data_time: 0.0114 memory: 14901 loss: 1.0984 loss_prob: 0.5814 loss_thr: 0.4180 loss_db: 0.0989 2022/11/02 19:57:26 - mmengine - INFO - Epoch(train) [700][45/63] lr: 9.8453e-04 eta: 5:16:03 time: 0.5059 data_time: 0.0113 memory: 14901 loss: 1.1146 loss_prob: 0.5980 loss_thr: 0.4151 loss_db: 0.1015 2022/11/02 19:57:29 - mmengine - INFO - Epoch(train) [700][50/63] lr: 9.8453e-04 eta: 5:15:56 time: 0.4966 data_time: 0.0147 memory: 14901 loss: 1.1058 loss_prob: 0.5869 loss_thr: 0.4174 loss_db: 0.1015 2022/11/02 19:57:32 - mmengine - INFO - Epoch(train) [700][55/63] lr: 9.8453e-04 eta: 5:15:56 time: 0.6216 data_time: 0.0416 memory: 14901 loss: 1.0808 loss_prob: 0.5652 loss_thr: 0.4166 loss_db: 0.0991 2022/11/02 19:57:35 - mmengine - INFO - Epoch(train) [700][60/63] lr: 9.8453e-04 eta: 5:15:50 time: 0.6560 data_time: 0.0361 memory: 14901 loss: 1.0861 loss_prob: 0.5715 loss_thr: 0.4152 loss_db: 0.0995 2022/11/02 19:57:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:57:37 - mmengine - INFO - Saving checkpoint at 700 epochs 2022/11/02 19:57:41 - mmengine - INFO - Epoch(val) [700][5/500] eta: 5:15:50 time: 0.0449 data_time: 0.0062 memory: 14901 2022/11/02 19:57:41 - mmengine - INFO - Epoch(val) [700][10/500] eta: 0:00:23 time: 0.0478 data_time: 0.0059 memory: 1008 2022/11/02 19:57:41 - mmengine - INFO - Epoch(val) [700][15/500] eta: 0:00:23 time: 0.0421 data_time: 0.0026 memory: 1008 2022/11/02 19:57:42 - mmengine - INFO - Epoch(val) [700][20/500] eta: 0:00:19 time: 0.0410 data_time: 0.0031 memory: 1008 2022/11/02 19:57:42 - mmengine - INFO - Epoch(val) [700][25/500] eta: 0:00:19 time: 0.0377 data_time: 0.0028 memory: 1008 2022/11/02 19:57:42 - mmengine - INFO - Epoch(val) [700][30/500] eta: 0:00:19 time: 0.0409 data_time: 0.0026 memory: 1008 2022/11/02 19:57:42 - mmengine - INFO - Epoch(val) [700][35/500] eta: 0:00:19 time: 0.0449 data_time: 0.0026 memory: 1008 2022/11/02 19:57:42 - mmengine - INFO - Epoch(val) [700][40/500] eta: 0:00:20 time: 0.0451 data_time: 0.0027 memory: 1008 2022/11/02 19:57:43 - mmengine - INFO - Epoch(val) [700][45/500] eta: 0:00:20 time: 0.0447 data_time: 0.0026 memory: 1008 2022/11/02 19:57:43 - mmengine - INFO - Epoch(val) [700][50/500] eta: 0:00:18 time: 0.0407 data_time: 0.0024 memory: 1008 2022/11/02 19:57:43 - mmengine - INFO - Epoch(val) [700][55/500] eta: 0:00:18 time: 0.0420 data_time: 0.0024 memory: 1008 2022/11/02 19:57:43 - mmengine - INFO - Epoch(val) [700][60/500] eta: 0:00:17 time: 0.0404 data_time: 0.0023 memory: 1008 2022/11/02 19:57:44 - mmengine - INFO - Epoch(val) [700][65/500] eta: 0:00:17 time: 0.0421 data_time: 0.0023 memory: 1008 2022/11/02 19:57:44 - mmengine - INFO - Epoch(val) [700][70/500] eta: 0:00:20 time: 0.0469 data_time: 0.0027 memory: 1008 2022/11/02 19:57:44 - mmengine - INFO - Epoch(val) [700][75/500] eta: 0:00:20 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 19:57:44 - mmengine - INFO - Epoch(val) [700][80/500] eta: 0:00:14 time: 0.0352 data_time: 0.0023 memory: 1008 2022/11/02 19:57:44 - mmengine - INFO - Epoch(val) [700][85/500] eta: 0:00:14 time: 0.0350 data_time: 0.0024 memory: 1008 2022/11/02 19:57:44 - mmengine - INFO - Epoch(val) [700][90/500] eta: 0:00:16 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 19:57:45 - mmengine - INFO - Epoch(val) [700][95/500] eta: 0:00:16 time: 0.0448 data_time: 0.0026 memory: 1008 2022/11/02 19:57:45 - mmengine - INFO - Epoch(val) [700][100/500] eta: 0:00:16 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/02 19:57:45 - mmengine - INFO - Epoch(val) [700][105/500] eta: 0:00:16 time: 0.0380 data_time: 0.0029 memory: 1008 2022/11/02 19:57:45 - mmengine - INFO - Epoch(val) [700][110/500] eta: 0:00:16 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/02 19:57:46 - mmengine - INFO - Epoch(val) [700][115/500] eta: 0:00:16 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 19:57:46 - mmengine - INFO - Epoch(val) [700][120/500] eta: 0:00:15 time: 0.0414 data_time: 0.0029 memory: 1008 2022/11/02 19:57:46 - mmengine - INFO - Epoch(val) [700][125/500] eta: 0:00:15 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 19:57:46 - mmengine - INFO - Epoch(val) [700][130/500] eta: 0:00:13 time: 0.0370 data_time: 0.0022 memory: 1008 2022/11/02 19:57:46 - mmengine - INFO - Epoch(val) [700][135/500] eta: 0:00:13 time: 0.0369 data_time: 0.0025 memory: 1008 2022/11/02 19:57:46 - mmengine - INFO - Epoch(val) [700][140/500] eta: 0:00:13 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 19:57:47 - mmengine - INFO - Epoch(val) [700][145/500] eta: 0:00:13 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/02 19:57:47 - mmengine - INFO - Epoch(val) [700][150/500] eta: 0:00:15 time: 0.0433 data_time: 0.0026 memory: 1008 2022/11/02 19:57:47 - mmengine - INFO - Epoch(val) [700][155/500] eta: 0:00:15 time: 0.0460 data_time: 0.0026 memory: 1008 2022/11/02 19:57:47 - mmengine - INFO - Epoch(val) [700][160/500] eta: 0:00:15 time: 0.0446 data_time: 0.0025 memory: 1008 2022/11/02 19:57:48 - mmengine - INFO - Epoch(val) [700][165/500] eta: 0:00:15 time: 0.0411 data_time: 0.0027 memory: 1008 2022/11/02 19:57:48 - mmengine - INFO - Epoch(val) [700][170/500] eta: 0:00:15 time: 0.0473 data_time: 0.0031 memory: 1008 2022/11/02 19:57:48 - mmengine - INFO - Epoch(val) [700][175/500] eta: 0:00:15 time: 0.0480 data_time: 0.0033 memory: 1008 2022/11/02 19:57:48 - mmengine - INFO - Epoch(val) [700][180/500] eta: 0:00:14 time: 0.0450 data_time: 0.0032 memory: 1008 2022/11/02 19:57:49 - mmengine - INFO - Epoch(val) [700][185/500] eta: 0:00:14 time: 0.0475 data_time: 0.0040 memory: 1008 2022/11/02 19:57:49 - mmengine - INFO - Epoch(val) [700][190/500] eta: 0:00:15 time: 0.0491 data_time: 0.0039 memory: 1008 2022/11/02 19:57:49 - mmengine - INFO - Epoch(val) [700][195/500] eta: 0:00:15 time: 0.0444 data_time: 0.0031 memory: 1008 2022/11/02 19:57:49 - mmengine - INFO - Epoch(val) [700][200/500] eta: 0:00:14 time: 0.0480 data_time: 0.0031 memory: 1008 2022/11/02 19:57:50 - mmengine - INFO - Epoch(val) [700][205/500] eta: 0:00:14 time: 0.0571 data_time: 0.0042 memory: 1008 2022/11/02 19:57:50 - mmengine - INFO - Epoch(val) [700][210/500] eta: 0:00:14 time: 0.0507 data_time: 0.0045 memory: 1008 2022/11/02 19:57:50 - mmengine - INFO - Epoch(val) [700][215/500] eta: 0:00:14 time: 0.0454 data_time: 0.0033 memory: 1008 2022/11/02 19:57:50 - mmengine - INFO - Epoch(val) [700][220/500] eta: 0:00:14 time: 0.0526 data_time: 0.0040 memory: 1008 2022/11/02 19:57:51 - mmengine - INFO - Epoch(val) [700][225/500] eta: 0:00:14 time: 0.0559 data_time: 0.0049 memory: 1008 2022/11/02 19:57:51 - mmengine - INFO - Epoch(val) [700][230/500] eta: 0:00:13 time: 0.0504 data_time: 0.0049 memory: 1008 2022/11/02 19:57:51 - mmengine - INFO - Epoch(val) [700][235/500] eta: 0:00:13 time: 0.0436 data_time: 0.0038 memory: 1008 2022/11/02 19:57:51 - mmengine - INFO - Epoch(val) [700][240/500] eta: 0:00:11 time: 0.0433 data_time: 0.0025 memory: 1008 2022/11/02 19:57:51 - mmengine - INFO - Epoch(val) [700][245/500] eta: 0:00:11 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/02 19:57:52 - mmengine - INFO - Epoch(val) [700][250/500] eta: 0:00:10 time: 0.0434 data_time: 0.0034 memory: 1008 2022/11/02 19:57:52 - mmengine - INFO - Epoch(val) [700][255/500] eta: 0:00:10 time: 0.0416 data_time: 0.0031 memory: 1008 2022/11/02 19:57:52 - mmengine - INFO - Epoch(val) [700][260/500] eta: 0:00:10 time: 0.0424 data_time: 0.0031 memory: 1008 2022/11/02 19:57:52 - mmengine - INFO - Epoch(val) [700][265/500] eta: 0:00:10 time: 0.0444 data_time: 0.0033 memory: 1008 2022/11/02 19:57:53 - mmengine - INFO - Epoch(val) [700][270/500] eta: 0:00:11 time: 0.0480 data_time: 0.0035 memory: 1008 2022/11/02 19:57:53 - mmengine - INFO - Epoch(val) [700][275/500] eta: 0:00:11 time: 0.0473 data_time: 0.0032 memory: 1008 2022/11/02 19:57:53 - mmengine - INFO - Epoch(val) [700][280/500] eta: 0:00:11 time: 0.0518 data_time: 0.0032 memory: 1008 2022/11/02 19:57:53 - mmengine - INFO - Epoch(val) [700][285/500] eta: 0:00:11 time: 0.0516 data_time: 0.0035 memory: 1008 2022/11/02 19:57:54 - mmengine - INFO - Epoch(val) [700][290/500] eta: 0:00:09 time: 0.0461 data_time: 0.0032 memory: 1008 2022/11/02 19:57:54 - mmengine - INFO - Epoch(val) [700][295/500] eta: 0:00:09 time: 0.0471 data_time: 0.0031 memory: 1008 2022/11/02 19:57:54 - mmengine - INFO - Epoch(val) [700][300/500] eta: 0:00:09 time: 0.0478 data_time: 0.0032 memory: 1008 2022/11/02 19:57:54 - mmengine - INFO - Epoch(val) [700][305/500] eta: 0:00:09 time: 0.0456 data_time: 0.0030 memory: 1008 2022/11/02 19:57:54 - mmengine - INFO - Epoch(val) [700][310/500] eta: 0:00:07 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 19:57:55 - mmengine - INFO - Epoch(val) [700][315/500] eta: 0:00:07 time: 0.0443 data_time: 0.0027 memory: 1008 2022/11/02 19:57:55 - mmengine - INFO - Epoch(val) [700][320/500] eta: 0:00:08 time: 0.0446 data_time: 0.0024 memory: 1008 2022/11/02 19:57:55 - mmengine - INFO - Epoch(val) [700][325/500] eta: 0:00:08 time: 0.0555 data_time: 0.0026 memory: 1008 2022/11/02 19:57:55 - mmengine - INFO - Epoch(val) [700][330/500] eta: 0:00:09 time: 0.0546 data_time: 0.0029 memory: 1008 2022/11/02 19:57:56 - mmengine - INFO - Epoch(val) [700][335/500] eta: 0:00:09 time: 0.0371 data_time: 0.0031 memory: 1008 2022/11/02 19:57:56 - mmengine - INFO - Epoch(val) [700][340/500] eta: 0:00:07 time: 0.0487 data_time: 0.0031 memory: 1008 2022/11/02 19:57:56 - mmengine - INFO - Epoch(val) [700][345/500] eta: 0:00:07 time: 0.0491 data_time: 0.0025 memory: 1008 2022/11/02 19:57:56 - mmengine - INFO - Epoch(val) [700][350/500] eta: 0:00:07 time: 0.0488 data_time: 0.0025 memory: 1008 2022/11/02 19:57:57 - mmengine - INFO - Epoch(val) [700][355/500] eta: 0:00:07 time: 0.0487 data_time: 0.0027 memory: 1008 2022/11/02 19:57:57 - mmengine - INFO - Epoch(val) [700][360/500] eta: 0:00:05 time: 0.0409 data_time: 0.0029 memory: 1008 2022/11/02 19:57:57 - mmengine - INFO - Epoch(val) [700][365/500] eta: 0:00:05 time: 0.0452 data_time: 0.0029 memory: 1008 2022/11/02 19:57:57 - mmengine - INFO - Epoch(val) [700][370/500] eta: 0:00:05 time: 0.0415 data_time: 0.0031 memory: 1008 2022/11/02 19:57:57 - mmengine - INFO - Epoch(val) [700][375/500] eta: 0:00:05 time: 0.0406 data_time: 0.0030 memory: 1008 2022/11/02 19:57:58 - mmengine - INFO - Epoch(val) [700][380/500] eta: 0:00:05 time: 0.0440 data_time: 0.0029 memory: 1008 2022/11/02 19:57:58 - mmengine - INFO - Epoch(val) [700][385/500] eta: 0:00:05 time: 0.0445 data_time: 0.0031 memory: 1008 2022/11/02 19:57:58 - mmengine - INFO - Epoch(val) [700][390/500] eta: 0:00:04 time: 0.0436 data_time: 0.0029 memory: 1008 2022/11/02 19:57:58 - mmengine - INFO - Epoch(val) [700][395/500] eta: 0:00:04 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 19:57:59 - mmengine - INFO - Epoch(val) [700][400/500] eta: 0:00:04 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/02 19:57:59 - mmengine - INFO - Epoch(val) [700][405/500] eta: 0:00:04 time: 0.0412 data_time: 0.0024 memory: 1008 2022/11/02 19:57:59 - mmengine - INFO - Epoch(val) [700][410/500] eta: 0:00:03 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 19:57:59 - mmengine - INFO - Epoch(val) [700][415/500] eta: 0:00:03 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 19:57:59 - mmengine - INFO - Epoch(val) [700][420/500] eta: 0:00:03 time: 0.0382 data_time: 0.0027 memory: 1008 2022/11/02 19:58:00 - mmengine - INFO - Epoch(val) [700][425/500] eta: 0:00:03 time: 0.0379 data_time: 0.0025 memory: 1008 2022/11/02 19:58:00 - mmengine - INFO - Epoch(val) [700][430/500] eta: 0:00:02 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/02 19:58:00 - mmengine - INFO - Epoch(val) [700][435/500] eta: 0:00:02 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/02 19:58:00 - mmengine - INFO - Epoch(val) [700][440/500] eta: 0:00:02 time: 0.0387 data_time: 0.0023 memory: 1008 2022/11/02 19:58:00 - mmengine - INFO - Epoch(val) [700][445/500] eta: 0:00:02 time: 0.0419 data_time: 0.0024 memory: 1008 2022/11/02 19:58:01 - mmengine - INFO - Epoch(val) [700][450/500] eta: 0:00:02 time: 0.0406 data_time: 0.0023 memory: 1008 2022/11/02 19:58:01 - mmengine - INFO - Epoch(val) [700][455/500] eta: 0:00:02 time: 0.0392 data_time: 0.0023 memory: 1008 2022/11/02 19:58:01 - mmengine - INFO - Epoch(val) [700][460/500] eta: 0:00:01 time: 0.0399 data_time: 0.0023 memory: 1008 2022/11/02 19:58:01 - mmengine - INFO - Epoch(val) [700][465/500] eta: 0:00:01 time: 0.0391 data_time: 0.0023 memory: 1008 2022/11/02 19:58:01 - mmengine - INFO - Epoch(val) [700][470/500] eta: 0:00:01 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/02 19:58:02 - mmengine - INFO - Epoch(val) [700][475/500] eta: 0:00:01 time: 0.0419 data_time: 0.0035 memory: 1008 2022/11/02 19:58:02 - mmengine - INFO - Epoch(val) [700][480/500] eta: 0:00:00 time: 0.0475 data_time: 0.0039 memory: 1008 2022/11/02 19:58:02 - mmengine - INFO - Epoch(val) [700][485/500] eta: 0:00:00 time: 0.0483 data_time: 0.0033 memory: 1008 2022/11/02 19:58:02 - mmengine - INFO - Epoch(val) [700][490/500] eta: 0:00:00 time: 0.0447 data_time: 0.0031 memory: 1008 2022/11/02 19:58:02 - mmengine - INFO - Epoch(val) [700][495/500] eta: 0:00:00 time: 0.0434 data_time: 0.0027 memory: 1008 2022/11/02 19:58:03 - mmengine - INFO - Epoch(val) [700][500/500] eta: 0:00:00 time: 0.0425 data_time: 0.0031 memory: 1008 2022/11/02 19:58:03 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8416, precision: 0.7179, hmean: 0.7748 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8416, precision: 0.7684, hmean: 0.8033 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8416, precision: 0.7989, hmean: 0.8197 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8397, precision: 0.8230, hmean: 0.8313 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8228, precision: 0.8579, hmean: 0.8400 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6793, precision: 0.9180, hmean: 0.7809 2022/11/02 19:58:03 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0963, precision: 0.9804, hmean: 0.1754 2022/11/02 19:58:03 - mmengine - INFO - Epoch(val) [700][500/500] icdar/precision: 0.8579 icdar/recall: 0.8228 icdar/hmean: 0.8400 2022/11/02 19:58:10 - mmengine - INFO - Epoch(train) [701][5/63] lr: 9.8275e-04 eta: 0:00:00 time: 0.9695 data_time: 0.2102 memory: 14901 loss: 1.1488 loss_prob: 0.6111 loss_thr: 0.4325 loss_db: 0.1052 2022/11/02 19:58:14 - mmengine - INFO - Epoch(train) [701][10/63] lr: 9.8275e-04 eta: 5:15:45 time: 1.0735 data_time: 0.2189 memory: 14901 loss: 1.0978 loss_prob: 0.5836 loss_thr: 0.4144 loss_db: 0.0998 2022/11/02 19:58:17 - mmengine - INFO - Epoch(train) [701][15/63] lr: 9.8275e-04 eta: 5:15:45 time: 0.7325 data_time: 0.0225 memory: 14901 loss: 1.1268 loss_prob: 0.5970 loss_thr: 0.4289 loss_db: 0.1009 2022/11/02 19:58:20 - mmengine - INFO - Epoch(train) [701][20/63] lr: 9.8275e-04 eta: 5:15:39 time: 0.6037 data_time: 0.0114 memory: 14901 loss: 1.1513 loss_prob: 0.6230 loss_thr: 0.4230 loss_db: 0.1053 2022/11/02 19:58:22 - mmengine - INFO - Epoch(train) [701][25/63] lr: 9.8275e-04 eta: 5:15:39 time: 0.5307 data_time: 0.0249 memory: 14901 loss: 1.1603 loss_prob: 0.6272 loss_thr: 0.4284 loss_db: 0.1047 2022/11/02 19:58:26 - mmengine - INFO - Epoch(train) [701][30/63] lr: 9.8275e-04 eta: 5:15:33 time: 0.5978 data_time: 0.0567 memory: 14901 loss: 1.1649 loss_prob: 0.6215 loss_thr: 0.4404 loss_db: 0.1029 2022/11/02 19:58:30 - mmengine - INFO - Epoch(train) [701][35/63] lr: 9.8275e-04 eta: 5:15:33 time: 0.7250 data_time: 0.0421 memory: 14901 loss: 1.1078 loss_prob: 0.5887 loss_thr: 0.4207 loss_db: 0.0983 2022/11/02 19:58:33 - mmengine - INFO - Epoch(train) [701][40/63] lr: 9.8275e-04 eta: 5:15:28 time: 0.7745 data_time: 0.0133 memory: 14901 loss: 1.0858 loss_prob: 0.5687 loss_thr: 0.4184 loss_db: 0.0987 2022/11/02 19:58:38 - mmengine - INFO - Epoch(train) [701][45/63] lr: 9.8275e-04 eta: 5:15:28 time: 0.7959 data_time: 0.0134 memory: 14901 loss: 1.0738 loss_prob: 0.5612 loss_thr: 0.4147 loss_db: 0.0978 2022/11/02 19:58:41 - mmengine - INFO - Epoch(train) [701][50/63] lr: 9.8275e-04 eta: 5:15:23 time: 0.7238 data_time: 0.0235 memory: 14901 loss: 1.1093 loss_prob: 0.5838 loss_thr: 0.4258 loss_db: 0.0996 2022/11/02 19:58:44 - mmengine - INFO - Epoch(train) [701][55/63] lr: 9.8275e-04 eta: 5:15:23 time: 0.6565 data_time: 0.0312 memory: 14901 loss: 1.1817 loss_prob: 0.6333 loss_thr: 0.4412 loss_db: 0.1072 2022/11/02 19:58:47 - mmengine - INFO - Epoch(train) [701][60/63] lr: 9.8275e-04 eta: 5:15:17 time: 0.6646 data_time: 0.0191 memory: 14901 loss: 1.1305 loss_prob: 0.6044 loss_thr: 0.4214 loss_db: 0.1047 2022/11/02 19:58:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:58:55 - mmengine - INFO - Epoch(train) [702][5/63] lr: 9.8098e-04 eta: 5:15:17 time: 0.8766 data_time: 0.2353 memory: 14901 loss: 1.0664 loss_prob: 0.5558 loss_thr: 0.4175 loss_db: 0.0931 2022/11/02 19:58:58 - mmengine - INFO - Epoch(train) [702][10/63] lr: 9.8098e-04 eta: 5:15:11 time: 0.9691 data_time: 0.2402 memory: 14901 loss: 1.0256 loss_prob: 0.5285 loss_thr: 0.4071 loss_db: 0.0900 2022/11/02 19:59:01 - mmengine - INFO - Epoch(train) [702][15/63] lr: 9.8098e-04 eta: 5:15:11 time: 0.6354 data_time: 0.0142 memory: 14901 loss: 1.0548 loss_prob: 0.5400 loss_thr: 0.4182 loss_db: 0.0967 2022/11/02 19:59:04 - mmengine - INFO - Epoch(train) [702][20/63] lr: 9.8098e-04 eta: 5:15:05 time: 0.6030 data_time: 0.0093 memory: 14901 loss: 1.0589 loss_prob: 0.5419 loss_thr: 0.4214 loss_db: 0.0957 2022/11/02 19:59:07 - mmengine - INFO - Epoch(train) [702][25/63] lr: 9.8098e-04 eta: 5:15:05 time: 0.6002 data_time: 0.0160 memory: 14901 loss: 1.0904 loss_prob: 0.5776 loss_thr: 0.4141 loss_db: 0.0987 2022/11/02 19:59:11 - mmengine - INFO - Epoch(train) [702][30/63] lr: 9.8098e-04 eta: 5:14:59 time: 0.6275 data_time: 0.0453 memory: 14901 loss: 1.0904 loss_prob: 0.5843 loss_thr: 0.4063 loss_db: 0.0997 2022/11/02 19:59:14 - mmengine - INFO - Epoch(train) [702][35/63] lr: 9.8098e-04 eta: 5:14:59 time: 0.6578 data_time: 0.0421 memory: 14901 loss: 1.0594 loss_prob: 0.5567 loss_thr: 0.4050 loss_db: 0.0977 2022/11/02 19:59:18 - mmengine - INFO - Epoch(train) [702][40/63] lr: 9.8098e-04 eta: 5:14:53 time: 0.6932 data_time: 0.0132 memory: 14901 loss: 1.0377 loss_prob: 0.5399 loss_thr: 0.4021 loss_db: 0.0957 2022/11/02 19:59:21 - mmengine - INFO - Epoch(train) [702][45/63] lr: 9.8098e-04 eta: 5:14:53 time: 0.7208 data_time: 0.0108 memory: 14901 loss: 1.0939 loss_prob: 0.5696 loss_thr: 0.4265 loss_db: 0.0978 2022/11/02 19:59:24 - mmengine - INFO - Epoch(train) [702][50/63] lr: 9.8098e-04 eta: 5:14:47 time: 0.6091 data_time: 0.0236 memory: 14901 loss: 1.1499 loss_prob: 0.6004 loss_thr: 0.4455 loss_db: 0.1041 2022/11/02 19:59:26 - mmengine - INFO - Epoch(train) [702][55/63] lr: 9.8098e-04 eta: 5:14:47 time: 0.5291 data_time: 0.0302 memory: 14901 loss: 1.1025 loss_prob: 0.5697 loss_thr: 0.4326 loss_db: 0.1002 2022/11/02 19:59:29 - mmengine - INFO - Epoch(train) [702][60/63] lr: 9.8098e-04 eta: 5:14:41 time: 0.5635 data_time: 0.0171 memory: 14901 loss: 1.1221 loss_prob: 0.5868 loss_thr: 0.4361 loss_db: 0.0992 2022/11/02 19:59:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 19:59:36 - mmengine - INFO - Epoch(train) [703][5/63] lr: 9.7921e-04 eta: 5:14:41 time: 0.8101 data_time: 0.2352 memory: 14901 loss: 1.1503 loss_prob: 0.5989 loss_thr: 0.4485 loss_db: 0.1029 2022/11/02 19:59:40 - mmengine - INFO - Epoch(train) [703][10/63] lr: 9.7921e-04 eta: 5:14:34 time: 0.8606 data_time: 0.2408 memory: 14901 loss: 1.1175 loss_prob: 0.5819 loss_thr: 0.4358 loss_db: 0.0998 2022/11/02 19:59:43 - mmengine - INFO - Epoch(train) [703][15/63] lr: 9.7921e-04 eta: 5:14:34 time: 0.6340 data_time: 0.0197 memory: 14901 loss: 1.0097 loss_prob: 0.5247 loss_thr: 0.3970 loss_db: 0.0879 2022/11/02 19:59:45 - mmengine - INFO - Epoch(train) [703][20/63] lr: 9.7921e-04 eta: 5:14:28 time: 0.5869 data_time: 0.0125 memory: 14901 loss: 1.0457 loss_prob: 0.5467 loss_thr: 0.4045 loss_db: 0.0945 2022/11/02 19:59:49 - mmengine - INFO - Epoch(train) [703][25/63] lr: 9.7921e-04 eta: 5:14:28 time: 0.6007 data_time: 0.0170 memory: 14901 loss: 1.1186 loss_prob: 0.5871 loss_thr: 0.4277 loss_db: 0.1038 2022/11/02 19:59:51 - mmengine - INFO - Epoch(train) [703][30/63] lr: 9.7921e-04 eta: 5:14:22 time: 0.5953 data_time: 0.0360 memory: 14901 loss: 1.0890 loss_prob: 0.5656 loss_thr: 0.4249 loss_db: 0.0985 2022/11/02 19:59:54 - mmengine - INFO - Epoch(train) [703][35/63] lr: 9.7921e-04 eta: 5:14:22 time: 0.5534 data_time: 0.0360 memory: 14901 loss: 1.0242 loss_prob: 0.5323 loss_thr: 0.4008 loss_db: 0.0911 2022/11/02 19:59:58 - mmengine - INFO - Epoch(train) [703][40/63] lr: 9.7921e-04 eta: 5:14:16 time: 0.7115 data_time: 0.0192 memory: 14901 loss: 1.0440 loss_prob: 0.5507 loss_thr: 0.3970 loss_db: 0.0963 2022/11/02 20:00:02 - mmengine - INFO - Epoch(train) [703][45/63] lr: 9.7921e-04 eta: 5:14:16 time: 0.7546 data_time: 0.0130 memory: 14901 loss: 1.0558 loss_prob: 0.5538 loss_thr: 0.4047 loss_db: 0.0973 2022/11/02 20:00:05 - mmengine - INFO - Epoch(train) [703][50/63] lr: 9.7921e-04 eta: 5:14:11 time: 0.6606 data_time: 0.0230 memory: 14901 loss: 0.9627 loss_prob: 0.4968 loss_thr: 0.3787 loss_db: 0.0872 2022/11/02 20:00:08 - mmengine - INFO - Epoch(train) [703][55/63] lr: 9.7921e-04 eta: 5:14:11 time: 0.6815 data_time: 0.0211 memory: 14901 loss: 1.0383 loss_prob: 0.5487 loss_thr: 0.3967 loss_db: 0.0928 2022/11/02 20:00:12 - mmengine - INFO - Epoch(train) [703][60/63] lr: 9.7921e-04 eta: 5:14:05 time: 0.6609 data_time: 0.0126 memory: 14901 loss: 1.1045 loss_prob: 0.5917 loss_thr: 0.4138 loss_db: 0.0990 2022/11/02 20:00:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:00:20 - mmengine - INFO - Epoch(train) [704][5/63] lr: 9.7744e-04 eta: 5:14:05 time: 0.9738 data_time: 0.2252 memory: 14901 loss: 1.1607 loss_prob: 0.6156 loss_thr: 0.4389 loss_db: 0.1063 2022/11/02 20:00:23 - mmengine - INFO - Epoch(train) [704][10/63] lr: 9.7744e-04 eta: 5:13:59 time: 0.9826 data_time: 0.2317 memory: 14901 loss: 1.0755 loss_prob: 0.5672 loss_thr: 0.4089 loss_db: 0.0995 2022/11/02 20:00:26 - mmengine - INFO - Epoch(train) [704][15/63] lr: 9.7744e-04 eta: 5:13:59 time: 0.5351 data_time: 0.0226 memory: 14901 loss: 1.1062 loss_prob: 0.5898 loss_thr: 0.4178 loss_db: 0.0986 2022/11/02 20:00:28 - mmengine - INFO - Epoch(train) [704][20/63] lr: 9.7744e-04 eta: 5:13:52 time: 0.5498 data_time: 0.0154 memory: 14901 loss: 1.1072 loss_prob: 0.5929 loss_thr: 0.4154 loss_db: 0.0990 2022/11/02 20:00:31 - mmengine - INFO - Epoch(train) [704][25/63] lr: 9.7744e-04 eta: 5:13:52 time: 0.5284 data_time: 0.0264 memory: 14901 loss: 1.0091 loss_prob: 0.5341 loss_thr: 0.3809 loss_db: 0.0942 2022/11/02 20:00:34 - mmengine - INFO - Epoch(train) [704][30/63] lr: 9.7744e-04 eta: 5:13:46 time: 0.5779 data_time: 0.0287 memory: 14901 loss: 1.0917 loss_prob: 0.5834 loss_thr: 0.4093 loss_db: 0.0990 2022/11/02 20:00:37 - mmengine - INFO - Epoch(train) [704][35/63] lr: 9.7744e-04 eta: 5:13:46 time: 0.6105 data_time: 0.0336 memory: 14901 loss: 1.1605 loss_prob: 0.6166 loss_thr: 0.4399 loss_db: 0.1041 2022/11/02 20:00:41 - mmengine - INFO - Epoch(train) [704][40/63] lr: 9.7744e-04 eta: 5:13:41 time: 0.6540 data_time: 0.0283 memory: 14901 loss: 1.0778 loss_prob: 0.5657 loss_thr: 0.4134 loss_db: 0.0986 2022/11/02 20:00:43 - mmengine - INFO - Epoch(train) [704][45/63] lr: 9.7744e-04 eta: 5:13:41 time: 0.6293 data_time: 0.0096 memory: 14901 loss: 1.1557 loss_prob: 0.6313 loss_thr: 0.4173 loss_db: 0.1071 2022/11/02 20:00:46 - mmengine - INFO - Epoch(train) [704][50/63] lr: 9.7744e-04 eta: 5:13:34 time: 0.5197 data_time: 0.0213 memory: 14901 loss: 1.2074 loss_prob: 0.6604 loss_thr: 0.4360 loss_db: 0.1109 2022/11/02 20:00:49 - mmengine - INFO - Epoch(train) [704][55/63] lr: 9.7744e-04 eta: 5:13:34 time: 0.5978 data_time: 0.0257 memory: 14901 loss: 1.1181 loss_prob: 0.5991 loss_thr: 0.4153 loss_db: 0.1037 2022/11/02 20:00:53 - mmengine - INFO - Epoch(train) [704][60/63] lr: 9.7744e-04 eta: 5:13:29 time: 0.7173 data_time: 0.0220 memory: 14901 loss: 1.2571 loss_prob: 0.7022 loss_thr: 0.4364 loss_db: 0.1185 2022/11/02 20:00:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:01:00 - mmengine - INFO - Epoch(train) [705][5/63] lr: 9.7566e-04 eta: 5:13:29 time: 0.8765 data_time: 0.2238 memory: 14901 loss: 1.0515 loss_prob: 0.5480 loss_thr: 0.4074 loss_db: 0.0961 2022/11/02 20:01:03 - mmengine - INFO - Epoch(train) [705][10/63] lr: 9.7566e-04 eta: 5:13:21 time: 0.8267 data_time: 0.2283 memory: 14901 loss: 1.1281 loss_prob: 0.5971 loss_thr: 0.4282 loss_db: 0.1028 2022/11/02 20:01:07 - mmengine - INFO - Epoch(train) [705][15/63] lr: 9.7566e-04 eta: 5:13:21 time: 0.6300 data_time: 0.0153 memory: 14901 loss: 1.2330 loss_prob: 0.6610 loss_thr: 0.4606 loss_db: 0.1114 2022/11/02 20:01:10 - mmengine - INFO - Epoch(train) [705][20/63] lr: 9.7566e-04 eta: 5:13:16 time: 0.7147 data_time: 0.0091 memory: 14901 loss: 1.1365 loss_prob: 0.6046 loss_thr: 0.4286 loss_db: 0.1033 2022/11/02 20:01:13 - mmengine - INFO - Epoch(train) [705][25/63] lr: 9.7566e-04 eta: 5:13:16 time: 0.6264 data_time: 0.0184 memory: 14901 loss: 1.1419 loss_prob: 0.6061 loss_thr: 0.4314 loss_db: 0.1044 2022/11/02 20:01:16 - mmengine - INFO - Epoch(train) [705][30/63] lr: 9.7566e-04 eta: 5:13:10 time: 0.6112 data_time: 0.0404 memory: 14901 loss: 1.1849 loss_prob: 0.6290 loss_thr: 0.4460 loss_db: 0.1100 2022/11/02 20:01:19 - mmengine - INFO - Epoch(train) [705][35/63] lr: 9.7566e-04 eta: 5:13:10 time: 0.5894 data_time: 0.0364 memory: 14901 loss: 1.2009 loss_prob: 0.6430 loss_thr: 0.4480 loss_db: 0.1100 2022/11/02 20:01:23 - mmengine - INFO - Epoch(train) [705][40/63] lr: 9.7566e-04 eta: 5:13:05 time: 0.6656 data_time: 0.0156 memory: 14901 loss: 1.1385 loss_prob: 0.6076 loss_thr: 0.4284 loss_db: 0.1025 2022/11/02 20:01:26 - mmengine - INFO - Epoch(train) [705][45/63] lr: 9.7566e-04 eta: 5:13:05 time: 0.7052 data_time: 0.0122 memory: 14901 loss: 1.0691 loss_prob: 0.5617 loss_thr: 0.4112 loss_db: 0.0961 2022/11/02 20:01:30 - mmengine - INFO - Epoch(train) [705][50/63] lr: 9.7566e-04 eta: 5:12:59 time: 0.6747 data_time: 0.0167 memory: 14901 loss: 1.1021 loss_prob: 0.5787 loss_thr: 0.4246 loss_db: 0.0988 2022/11/02 20:01:32 - mmengine - INFO - Epoch(train) [705][55/63] lr: 9.7566e-04 eta: 5:12:59 time: 0.6639 data_time: 0.0292 memory: 14901 loss: 1.0853 loss_prob: 0.5679 loss_thr: 0.4191 loss_db: 0.0983 2022/11/02 20:01:36 - mmengine - INFO - Epoch(train) [705][60/63] lr: 9.7566e-04 eta: 5:12:53 time: 0.6015 data_time: 0.0274 memory: 14901 loss: 1.0838 loss_prob: 0.5681 loss_thr: 0.4173 loss_db: 0.0984 2022/11/02 20:01:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:01:44 - mmengine - INFO - Epoch(train) [706][5/63] lr: 9.7389e-04 eta: 5:12:53 time: 0.9313 data_time: 0.2746 memory: 14901 loss: 1.1375 loss_prob: 0.6081 loss_thr: 0.4282 loss_db: 0.1012 2022/11/02 20:01:47 - mmengine - INFO - Epoch(train) [706][10/63] lr: 9.7389e-04 eta: 5:12:47 time: 1.0248 data_time: 0.2722 memory: 14901 loss: 1.2089 loss_prob: 0.6501 loss_thr: 0.4517 loss_db: 0.1072 2022/11/02 20:01:51 - mmengine - INFO - Epoch(train) [706][15/63] lr: 9.7389e-04 eta: 5:12:47 time: 0.7617 data_time: 0.0072 memory: 14901 loss: 1.1257 loss_prob: 0.5949 loss_thr: 0.4307 loss_db: 0.1002 2022/11/02 20:01:54 - mmengine - INFO - Epoch(train) [706][20/63] lr: 9.7389e-04 eta: 5:12:41 time: 0.6622 data_time: 0.0088 memory: 14901 loss: 1.0238 loss_prob: 0.5451 loss_thr: 0.3850 loss_db: 0.0937 2022/11/02 20:01:57 - mmengine - INFO - Epoch(train) [706][25/63] lr: 9.7389e-04 eta: 5:12:41 time: 0.5782 data_time: 0.0535 memory: 14901 loss: 1.1819 loss_prob: 0.6524 loss_thr: 0.4200 loss_db: 0.1095 2022/11/02 20:02:00 - mmengine - INFO - Epoch(train) [706][30/63] lr: 9.7389e-04 eta: 5:12:35 time: 0.5589 data_time: 0.0543 memory: 14901 loss: 1.2222 loss_prob: 0.6671 loss_thr: 0.4433 loss_db: 0.1118 2022/11/02 20:02:02 - mmengine - INFO - Epoch(train) [706][35/63] lr: 9.7389e-04 eta: 5:12:35 time: 0.5260 data_time: 0.0137 memory: 14901 loss: 1.0953 loss_prob: 0.5738 loss_thr: 0.4214 loss_db: 0.1001 2022/11/02 20:02:05 - mmengine - INFO - Epoch(train) [706][40/63] lr: 9.7389e-04 eta: 5:12:28 time: 0.5338 data_time: 0.0109 memory: 14901 loss: 1.1245 loss_prob: 0.5980 loss_thr: 0.4233 loss_db: 0.1032 2022/11/02 20:02:08 - mmengine - INFO - Epoch(train) [706][45/63] lr: 9.7389e-04 eta: 5:12:28 time: 0.5456 data_time: 0.0083 memory: 14901 loss: 1.1919 loss_prob: 0.6425 loss_thr: 0.4411 loss_db: 0.1083 2022/11/02 20:02:11 - mmengine - INFO - Epoch(train) [706][50/63] lr: 9.7389e-04 eta: 5:12:22 time: 0.5809 data_time: 0.0325 memory: 14901 loss: 1.1683 loss_prob: 0.6322 loss_thr: 0.4293 loss_db: 0.1067 2022/11/02 20:02:13 - mmengine - INFO - Epoch(train) [706][55/63] lr: 9.7389e-04 eta: 5:12:22 time: 0.5656 data_time: 0.0337 memory: 14901 loss: 1.0628 loss_prob: 0.5667 loss_thr: 0.3999 loss_db: 0.0962 2022/11/02 20:02:16 - mmengine - INFO - Epoch(train) [706][60/63] lr: 9.7389e-04 eta: 5:12:16 time: 0.5382 data_time: 0.0121 memory: 14901 loss: 1.0197 loss_prob: 0.5275 loss_thr: 0.4008 loss_db: 0.0914 2022/11/02 20:02:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:02:23 - mmengine - INFO - Epoch(train) [707][5/63] lr: 9.7211e-04 eta: 5:12:16 time: 0.8221 data_time: 0.2611 memory: 14901 loss: 1.1597 loss_prob: 0.6103 loss_thr: 0.4438 loss_db: 0.1056 2022/11/02 20:02:26 - mmengine - INFO - Epoch(train) [707][10/63] lr: 9.7211e-04 eta: 5:12:09 time: 0.8631 data_time: 0.2632 memory: 14901 loss: 1.1127 loss_prob: 0.5801 loss_thr: 0.4346 loss_db: 0.0981 2022/11/02 20:02:29 - mmengine - INFO - Epoch(train) [707][15/63] lr: 9.7211e-04 eta: 5:12:09 time: 0.5640 data_time: 0.0159 memory: 14901 loss: 1.2023 loss_prob: 0.6460 loss_thr: 0.4503 loss_db: 0.1061 2022/11/02 20:02:32 - mmengine - INFO - Epoch(train) [707][20/63] lr: 9.7211e-04 eta: 5:12:03 time: 0.6534 data_time: 0.0165 memory: 14901 loss: 1.1626 loss_prob: 0.6370 loss_thr: 0.4180 loss_db: 0.1076 2022/11/02 20:02:35 - mmengine - INFO - Epoch(train) [707][25/63] lr: 9.7211e-04 eta: 5:12:03 time: 0.6596 data_time: 0.0349 memory: 14901 loss: 1.0937 loss_prob: 0.5859 loss_thr: 0.4053 loss_db: 0.1024 2022/11/02 20:02:39 - mmengine - INFO - Epoch(train) [707][30/63] lr: 9.7211e-04 eta: 5:11:57 time: 0.6332 data_time: 0.0376 memory: 14901 loss: 1.1053 loss_prob: 0.5883 loss_thr: 0.4187 loss_db: 0.0983 2022/11/02 20:02:42 - mmengine - INFO - Epoch(train) [707][35/63] lr: 9.7211e-04 eta: 5:11:57 time: 0.6333 data_time: 0.0167 memory: 14901 loss: 1.0571 loss_prob: 0.5540 loss_thr: 0.4100 loss_db: 0.0931 2022/11/02 20:02:44 - mmengine - INFO - Epoch(train) [707][40/63] lr: 9.7211e-04 eta: 5:11:51 time: 0.5702 data_time: 0.0153 memory: 14901 loss: 1.0697 loss_prob: 0.5618 loss_thr: 0.4107 loss_db: 0.0972 2022/11/02 20:02:47 - mmengine - INFO - Epoch(train) [707][45/63] lr: 9.7211e-04 eta: 5:11:51 time: 0.5232 data_time: 0.0130 memory: 14901 loss: 1.1078 loss_prob: 0.5911 loss_thr: 0.4154 loss_db: 0.1013 2022/11/02 20:02:50 - mmengine - INFO - Epoch(train) [707][50/63] lr: 9.7211e-04 eta: 5:11:45 time: 0.5673 data_time: 0.0429 memory: 14901 loss: 1.0415 loss_prob: 0.5444 loss_thr: 0.4027 loss_db: 0.0944 2022/11/02 20:02:53 - mmengine - INFO - Epoch(train) [707][55/63] lr: 9.7211e-04 eta: 5:11:45 time: 0.5533 data_time: 0.0410 memory: 14901 loss: 1.0784 loss_prob: 0.5684 loss_thr: 0.4134 loss_db: 0.0965 2022/11/02 20:02:56 - mmengine - INFO - Epoch(train) [707][60/63] lr: 9.7211e-04 eta: 5:11:38 time: 0.5756 data_time: 0.0096 memory: 14901 loss: 1.1318 loss_prob: 0.6010 loss_thr: 0.4286 loss_db: 0.1021 2022/11/02 20:02:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:03:04 - mmengine - INFO - Epoch(train) [708][5/63] lr: 9.7034e-04 eta: 5:11:38 time: 0.9019 data_time: 0.2554 memory: 14901 loss: 1.0089 loss_prob: 0.5201 loss_thr: 0.3991 loss_db: 0.0897 2022/11/02 20:03:06 - mmengine - INFO - Epoch(train) [708][10/63] lr: 9.7034e-04 eta: 5:11:31 time: 0.8790 data_time: 0.2494 memory: 14901 loss: 1.0431 loss_prob: 0.5428 loss_thr: 0.4064 loss_db: 0.0939 2022/11/02 20:03:09 - mmengine - INFO - Epoch(train) [708][15/63] lr: 9.7034e-04 eta: 5:11:31 time: 0.5550 data_time: 0.0117 memory: 14901 loss: 1.0886 loss_prob: 0.5706 loss_thr: 0.4202 loss_db: 0.0977 2022/11/02 20:03:13 - mmengine - INFO - Epoch(train) [708][20/63] lr: 9.7034e-04 eta: 5:11:26 time: 0.7202 data_time: 0.0150 memory: 14901 loss: 1.0883 loss_prob: 0.5715 loss_thr: 0.4187 loss_db: 0.0981 2022/11/02 20:03:17 - mmengine - INFO - Epoch(train) [708][25/63] lr: 9.7034e-04 eta: 5:11:26 time: 0.7501 data_time: 0.0253 memory: 14901 loss: 1.1332 loss_prob: 0.6025 loss_thr: 0.4259 loss_db: 0.1048 2022/11/02 20:03:19 - mmengine - INFO - Epoch(train) [708][30/63] lr: 9.7034e-04 eta: 5:11:20 time: 0.6099 data_time: 0.0398 memory: 14901 loss: 1.1759 loss_prob: 0.6318 loss_thr: 0.4377 loss_db: 0.1064 2022/11/02 20:03:22 - mmengine - INFO - Epoch(train) [708][35/63] lr: 9.7034e-04 eta: 5:11:20 time: 0.5384 data_time: 0.0277 memory: 14901 loss: 1.0761 loss_prob: 0.5594 loss_thr: 0.4218 loss_db: 0.0949 2022/11/02 20:03:25 - mmengine - INFO - Epoch(train) [708][40/63] lr: 9.7034e-04 eta: 5:11:14 time: 0.5969 data_time: 0.0107 memory: 14901 loss: 1.0496 loss_prob: 0.5395 loss_thr: 0.4145 loss_db: 0.0957 2022/11/02 20:03:29 - mmengine - INFO - Epoch(train) [708][45/63] lr: 9.7034e-04 eta: 5:11:14 time: 0.6542 data_time: 0.0151 memory: 14901 loss: 1.1264 loss_prob: 0.5931 loss_thr: 0.4305 loss_db: 0.1029 2022/11/02 20:03:31 - mmengine - INFO - Epoch(train) [708][50/63] lr: 9.7034e-04 eta: 5:11:08 time: 0.6040 data_time: 0.0277 memory: 14901 loss: 1.1591 loss_prob: 0.6088 loss_thr: 0.4468 loss_db: 0.1035 2022/11/02 20:03:34 - mmengine - INFO - Epoch(train) [708][55/63] lr: 9.7034e-04 eta: 5:11:08 time: 0.5439 data_time: 0.0282 memory: 14901 loss: 1.1730 loss_prob: 0.6250 loss_thr: 0.4427 loss_db: 0.1053 2022/11/02 20:03:37 - mmengine - INFO - Epoch(train) [708][60/63] lr: 9.7034e-04 eta: 5:11:01 time: 0.5158 data_time: 0.0187 memory: 14901 loss: 1.1192 loss_prob: 0.5979 loss_thr: 0.4187 loss_db: 0.1027 2022/11/02 20:03:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:03:45 - mmengine - INFO - Epoch(train) [709][5/63] lr: 9.6856e-04 eta: 5:11:01 time: 0.8888 data_time: 0.2737 memory: 14901 loss: 1.0568 loss_prob: 0.5587 loss_thr: 0.4023 loss_db: 0.0957 2022/11/02 20:03:47 - mmengine - INFO - Epoch(train) [709][10/63] lr: 9.6856e-04 eta: 5:10:55 time: 0.9333 data_time: 0.2733 memory: 14901 loss: 1.1332 loss_prob: 0.6252 loss_thr: 0.4086 loss_db: 0.0994 2022/11/02 20:03:50 - mmengine - INFO - Epoch(train) [709][15/63] lr: 9.6856e-04 eta: 5:10:55 time: 0.5931 data_time: 0.0138 memory: 14901 loss: 1.1461 loss_prob: 0.6288 loss_thr: 0.4160 loss_db: 0.1012 2022/11/02 20:03:54 - mmengine - INFO - Epoch(train) [709][20/63] lr: 9.6856e-04 eta: 5:10:49 time: 0.6381 data_time: 0.0166 memory: 14901 loss: 1.0654 loss_prob: 0.5618 loss_thr: 0.4057 loss_db: 0.0979 2022/11/02 20:03:56 - mmengine - INFO - Epoch(train) [709][25/63] lr: 9.6856e-04 eta: 5:10:49 time: 0.5907 data_time: 0.0194 memory: 14901 loss: 1.0668 loss_prob: 0.5594 loss_thr: 0.4105 loss_db: 0.0969 2022/11/02 20:03:59 - mmengine - INFO - Epoch(train) [709][30/63] lr: 9.6856e-04 eta: 5:10:43 time: 0.5711 data_time: 0.0354 memory: 14901 loss: 1.0923 loss_prob: 0.5749 loss_thr: 0.4203 loss_db: 0.0971 2022/11/02 20:04:02 - mmengine - INFO - Epoch(train) [709][35/63] lr: 9.6856e-04 eta: 5:10:43 time: 0.5505 data_time: 0.0378 memory: 14901 loss: 1.0354 loss_prob: 0.5475 loss_thr: 0.3937 loss_db: 0.0942 2022/11/02 20:04:05 - mmengine - INFO - Epoch(train) [709][40/63] lr: 9.6856e-04 eta: 5:10:36 time: 0.5249 data_time: 0.0169 memory: 14901 loss: 1.0168 loss_prob: 0.5323 loss_thr: 0.3921 loss_db: 0.0924 2022/11/02 20:04:07 - mmengine - INFO - Epoch(train) [709][45/63] lr: 9.6856e-04 eta: 5:10:36 time: 0.5437 data_time: 0.0104 memory: 14901 loss: 1.0237 loss_prob: 0.5241 loss_thr: 0.4102 loss_db: 0.0895 2022/11/02 20:04:10 - mmengine - INFO - Epoch(train) [709][50/63] lr: 9.6856e-04 eta: 5:10:30 time: 0.5780 data_time: 0.0249 memory: 14901 loss: 1.0352 loss_prob: 0.5386 loss_thr: 0.4039 loss_db: 0.0927 2022/11/02 20:04:13 - mmengine - INFO - Epoch(train) [709][55/63] lr: 9.6856e-04 eta: 5:10:30 time: 0.5808 data_time: 0.0277 memory: 14901 loss: 1.0870 loss_prob: 0.5826 loss_thr: 0.4057 loss_db: 0.0987 2022/11/02 20:04:16 - mmengine - INFO - Epoch(train) [709][60/63] lr: 9.6856e-04 eta: 5:10:23 time: 0.5321 data_time: 0.0172 memory: 14901 loss: 1.0876 loss_prob: 0.5689 loss_thr: 0.4226 loss_db: 0.0961 2022/11/02 20:04:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:04:23 - mmengine - INFO - Epoch(train) [710][5/63] lr: 9.6679e-04 eta: 5:10:23 time: 0.8220 data_time: 0.1965 memory: 14901 loss: 1.0921 loss_prob: 0.5725 loss_thr: 0.4208 loss_db: 0.0987 2022/11/02 20:04:26 - mmengine - INFO - Epoch(train) [710][10/63] lr: 9.6679e-04 eta: 5:10:17 time: 0.9336 data_time: 0.1974 memory: 14901 loss: 1.0585 loss_prob: 0.5488 loss_thr: 0.4136 loss_db: 0.0962 2022/11/02 20:04:30 - mmengine - INFO - Epoch(train) [710][15/63] lr: 9.6679e-04 eta: 5:10:17 time: 0.6688 data_time: 0.0132 memory: 14901 loss: 1.1465 loss_prob: 0.5916 loss_thr: 0.4524 loss_db: 0.1025 2022/11/02 20:04:33 - mmengine - INFO - Epoch(train) [710][20/63] lr: 9.6679e-04 eta: 5:10:11 time: 0.6939 data_time: 0.0163 memory: 14901 loss: 1.0719 loss_prob: 0.5577 loss_thr: 0.4186 loss_db: 0.0956 2022/11/02 20:04:37 - mmengine - INFO - Epoch(train) [710][25/63] lr: 9.6679e-04 eta: 5:10:11 time: 0.7225 data_time: 0.0226 memory: 14901 loss: 1.0887 loss_prob: 0.5860 loss_thr: 0.4044 loss_db: 0.0983 2022/11/02 20:04:40 - mmengine - INFO - Epoch(train) [710][30/63] lr: 9.6679e-04 eta: 5:10:06 time: 0.6765 data_time: 0.0377 memory: 14901 loss: 1.1183 loss_prob: 0.6040 loss_thr: 0.4111 loss_db: 0.1032 2022/11/02 20:04:43 - mmengine - INFO - Epoch(train) [710][35/63] lr: 9.6679e-04 eta: 5:10:06 time: 0.5817 data_time: 0.0268 memory: 14901 loss: 1.1403 loss_prob: 0.6063 loss_thr: 0.4288 loss_db: 0.1052 2022/11/02 20:04:46 - mmengine - INFO - Epoch(train) [710][40/63] lr: 9.6679e-04 eta: 5:10:00 time: 0.6057 data_time: 0.0094 memory: 14901 loss: 1.1814 loss_prob: 0.6285 loss_thr: 0.4452 loss_db: 0.1077 2022/11/02 20:04:49 - mmengine - INFO - Epoch(train) [710][45/63] lr: 9.6679e-04 eta: 5:10:00 time: 0.6081 data_time: 0.0147 memory: 14901 loss: 1.1437 loss_prob: 0.6113 loss_thr: 0.4292 loss_db: 0.1032 2022/11/02 20:04:52 - mmengine - INFO - Epoch(train) [710][50/63] lr: 9.6679e-04 eta: 5:09:53 time: 0.5530 data_time: 0.0185 memory: 14901 loss: 1.1456 loss_prob: 0.6079 loss_thr: 0.4342 loss_db: 0.1035 2022/11/02 20:04:54 - mmengine - INFO - Epoch(train) [710][55/63] lr: 9.6679e-04 eta: 5:09:53 time: 0.5328 data_time: 0.0264 memory: 14901 loss: 1.1641 loss_prob: 0.6139 loss_thr: 0.4439 loss_db: 0.1062 2022/11/02 20:04:57 - mmengine - INFO - Epoch(train) [710][60/63] lr: 9.6679e-04 eta: 5:09:47 time: 0.4908 data_time: 0.0219 memory: 14901 loss: 1.1504 loss_prob: 0.6093 loss_thr: 0.4376 loss_db: 0.1035 2022/11/02 20:04:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:05:03 - mmengine - INFO - Epoch(train) [711][5/63] lr: 9.6501e-04 eta: 5:09:47 time: 0.7862 data_time: 0.2137 memory: 14901 loss: 1.0798 loss_prob: 0.5592 loss_thr: 0.4238 loss_db: 0.0967 2022/11/02 20:05:07 - mmengine - INFO - Epoch(train) [711][10/63] lr: 9.6501e-04 eta: 5:09:39 time: 0.8799 data_time: 0.2157 memory: 14901 loss: 1.0885 loss_prob: 0.5695 loss_thr: 0.4196 loss_db: 0.0994 2022/11/02 20:05:09 - mmengine - INFO - Epoch(train) [711][15/63] lr: 9.6501e-04 eta: 5:09:39 time: 0.5966 data_time: 0.0143 memory: 14901 loss: 1.0821 loss_prob: 0.5728 loss_thr: 0.4104 loss_db: 0.0989 2022/11/02 20:05:14 - mmengine - INFO - Epoch(train) [711][20/63] lr: 9.6501e-04 eta: 5:09:34 time: 0.7102 data_time: 0.0137 memory: 14901 loss: 1.0722 loss_prob: 0.5646 loss_thr: 0.4098 loss_db: 0.0978 2022/11/02 20:05:18 - mmengine - INFO - Epoch(train) [711][25/63] lr: 9.6501e-04 eta: 5:09:34 time: 0.8128 data_time: 0.0250 memory: 14901 loss: 1.0514 loss_prob: 0.5437 loss_thr: 0.4133 loss_db: 0.0944 2022/11/02 20:05:20 - mmengine - INFO - Epoch(train) [711][30/63] lr: 9.6501e-04 eta: 5:09:29 time: 0.6802 data_time: 0.0331 memory: 14901 loss: 1.0364 loss_prob: 0.5400 loss_thr: 0.4033 loss_db: 0.0931 2022/11/02 20:05:23 - mmengine - INFO - Epoch(train) [711][35/63] lr: 9.6501e-04 eta: 5:09:29 time: 0.5452 data_time: 0.0239 memory: 14901 loss: 1.0567 loss_prob: 0.5571 loss_thr: 0.4035 loss_db: 0.0960 2022/11/02 20:05:26 - mmengine - INFO - Epoch(train) [711][40/63] lr: 9.6501e-04 eta: 5:09:22 time: 0.5394 data_time: 0.0195 memory: 14901 loss: 1.0685 loss_prob: 0.5554 loss_thr: 0.4141 loss_db: 0.0990 2022/11/02 20:05:29 - mmengine - INFO - Epoch(train) [711][45/63] lr: 9.6501e-04 eta: 5:09:22 time: 0.6239 data_time: 0.0151 memory: 14901 loss: 1.0607 loss_prob: 0.5534 loss_thr: 0.4099 loss_db: 0.0974 2022/11/02 20:05:32 - mmengine - INFO - Epoch(train) [711][50/63] lr: 9.6501e-04 eta: 5:09:17 time: 0.6489 data_time: 0.0190 memory: 14901 loss: 1.1192 loss_prob: 0.5963 loss_thr: 0.4246 loss_db: 0.0982 2022/11/02 20:05:35 - mmengine - INFO - Epoch(train) [711][55/63] lr: 9.6501e-04 eta: 5:09:17 time: 0.6084 data_time: 0.0291 memory: 14901 loss: 1.1700 loss_prob: 0.6291 loss_thr: 0.4371 loss_db: 0.1039 2022/11/02 20:05:38 - mmengine - INFO - Epoch(train) [711][60/63] lr: 9.6501e-04 eta: 5:09:11 time: 0.6070 data_time: 0.0257 memory: 14901 loss: 1.1418 loss_prob: 0.6061 loss_thr: 0.4314 loss_db: 0.1044 2022/11/02 20:05:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:05:46 - mmengine - INFO - Epoch(train) [712][5/63] lr: 9.6324e-04 eta: 5:09:11 time: 0.8883 data_time: 0.2227 memory: 14901 loss: 1.0619 loss_prob: 0.5603 loss_thr: 0.4065 loss_db: 0.0951 2022/11/02 20:05:49 - mmengine - INFO - Epoch(train) [712][10/63] lr: 9.6324e-04 eta: 5:09:03 time: 0.8702 data_time: 0.2188 memory: 14901 loss: 1.0672 loss_prob: 0.5613 loss_thr: 0.4102 loss_db: 0.0958 2022/11/02 20:05:53 - mmengine - INFO - Epoch(train) [712][15/63] lr: 9.6324e-04 eta: 5:09:03 time: 0.6835 data_time: 0.0131 memory: 14901 loss: 1.1104 loss_prob: 0.5832 loss_thr: 0.4257 loss_db: 0.1015 2022/11/02 20:05:56 - mmengine - INFO - Epoch(train) [712][20/63] lr: 9.6324e-04 eta: 5:08:58 time: 0.7612 data_time: 0.0156 memory: 14901 loss: 1.0295 loss_prob: 0.5349 loss_thr: 0.4011 loss_db: 0.0935 2022/11/02 20:05:59 - mmengine - INFO - Epoch(train) [712][25/63] lr: 9.6324e-04 eta: 5:08:58 time: 0.6499 data_time: 0.0239 memory: 14901 loss: 1.0263 loss_prob: 0.5282 loss_thr: 0.4065 loss_db: 0.0917 2022/11/02 20:06:03 - mmengine - INFO - Epoch(train) [712][30/63] lr: 9.6324e-04 eta: 5:08:53 time: 0.6667 data_time: 0.0440 memory: 14901 loss: 1.0981 loss_prob: 0.5726 loss_thr: 0.4262 loss_db: 0.0993 2022/11/02 20:06:06 - mmengine - INFO - Epoch(train) [712][35/63] lr: 9.6324e-04 eta: 5:08:53 time: 0.6914 data_time: 0.0331 memory: 14901 loss: 1.1124 loss_prob: 0.5905 loss_thr: 0.4190 loss_db: 0.1030 2022/11/02 20:06:10 - mmengine - INFO - Epoch(train) [712][40/63] lr: 9.6324e-04 eta: 5:08:47 time: 0.6571 data_time: 0.0131 memory: 14901 loss: 1.1301 loss_prob: 0.5992 loss_thr: 0.4268 loss_db: 0.1040 2022/11/02 20:06:13 - mmengine - INFO - Epoch(train) [712][45/63] lr: 9.6324e-04 eta: 5:08:47 time: 0.7086 data_time: 0.0131 memory: 14901 loss: 1.0837 loss_prob: 0.5693 loss_thr: 0.4154 loss_db: 0.0990 2022/11/02 20:06:16 - mmengine - INFO - Epoch(train) [712][50/63] lr: 9.6324e-04 eta: 5:08:42 time: 0.6593 data_time: 0.0203 memory: 14901 loss: 1.0595 loss_prob: 0.5524 loss_thr: 0.4108 loss_db: 0.0963 2022/11/02 20:06:19 - mmengine - INFO - Epoch(train) [712][55/63] lr: 9.6324e-04 eta: 5:08:42 time: 0.5512 data_time: 0.0315 memory: 14901 loss: 1.1134 loss_prob: 0.5905 loss_thr: 0.4206 loss_db: 0.1023 2022/11/02 20:06:22 - mmengine - INFO - Epoch(train) [712][60/63] lr: 9.6324e-04 eta: 5:08:35 time: 0.5983 data_time: 0.0270 memory: 14901 loss: 1.0396 loss_prob: 0.5525 loss_thr: 0.3924 loss_db: 0.0947 2022/11/02 20:06:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:06:30 - mmengine - INFO - Epoch(train) [713][5/63] lr: 9.6146e-04 eta: 5:08:35 time: 0.9075 data_time: 0.2479 memory: 14901 loss: 1.0970 loss_prob: 0.5786 loss_thr: 0.4208 loss_db: 0.0976 2022/11/02 20:06:34 - mmengine - INFO - Epoch(train) [713][10/63] lr: 9.6146e-04 eta: 5:08:29 time: 1.0347 data_time: 0.2464 memory: 14901 loss: 1.0916 loss_prob: 0.5767 loss_thr: 0.4144 loss_db: 0.1005 2022/11/02 20:06:38 - mmengine - INFO - Epoch(train) [713][15/63] lr: 9.6146e-04 eta: 5:08:29 time: 0.7751 data_time: 0.0144 memory: 14901 loss: 0.9933 loss_prob: 0.5163 loss_thr: 0.3844 loss_db: 0.0925 2022/11/02 20:06:41 - mmengine - INFO - Epoch(train) [713][20/63] lr: 9.6146e-04 eta: 5:08:24 time: 0.6622 data_time: 0.0135 memory: 14901 loss: 1.0033 loss_prob: 0.5241 loss_thr: 0.3884 loss_db: 0.0908 2022/11/02 20:06:44 - mmengine - INFO - Epoch(train) [713][25/63] lr: 9.6146e-04 eta: 5:08:24 time: 0.6019 data_time: 0.0438 memory: 14901 loss: 1.0661 loss_prob: 0.5680 loss_thr: 0.4025 loss_db: 0.0956 2022/11/02 20:06:47 - mmengine - INFO - Epoch(train) [713][30/63] lr: 9.6146e-04 eta: 5:08:18 time: 0.6312 data_time: 0.0454 memory: 14901 loss: 1.0991 loss_prob: 0.5904 loss_thr: 0.4089 loss_db: 0.0998 2022/11/02 20:06:49 - mmengine - INFO - Epoch(train) [713][35/63] lr: 9.6146e-04 eta: 5:08:18 time: 0.5330 data_time: 0.0118 memory: 14901 loss: 1.1603 loss_prob: 0.6214 loss_thr: 0.4337 loss_db: 0.1053 2022/11/02 20:06:52 - mmengine - INFO - Epoch(train) [713][40/63] lr: 9.6146e-04 eta: 5:08:11 time: 0.5208 data_time: 0.0088 memory: 14901 loss: 1.1845 loss_prob: 0.6385 loss_thr: 0.4388 loss_db: 0.1071 2022/11/02 20:06:55 - mmengine - INFO - Epoch(train) [713][45/63] lr: 9.6146e-04 eta: 5:08:11 time: 0.5513 data_time: 0.0098 memory: 14901 loss: 1.1154 loss_prob: 0.5996 loss_thr: 0.4152 loss_db: 0.1006 2022/11/02 20:06:58 - mmengine - INFO - Epoch(train) [713][50/63] lr: 9.6146e-04 eta: 5:08:05 time: 0.5686 data_time: 0.0305 memory: 14901 loss: 1.0650 loss_prob: 0.5587 loss_thr: 0.4096 loss_db: 0.0967 2022/11/02 20:07:00 - mmengine - INFO - Epoch(train) [713][55/63] lr: 9.6146e-04 eta: 5:08:05 time: 0.5677 data_time: 0.0266 memory: 14901 loss: 1.0283 loss_prob: 0.5405 loss_thr: 0.3938 loss_db: 0.0941 2022/11/02 20:07:03 - mmengine - INFO - Epoch(train) [713][60/63] lr: 9.6146e-04 eta: 5:07:59 time: 0.5280 data_time: 0.0079 memory: 14901 loss: 0.9905 loss_prob: 0.5235 loss_thr: 0.3786 loss_db: 0.0884 2022/11/02 20:07:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:07:11 - mmengine - INFO - Epoch(train) [714][5/63] lr: 9.5968e-04 eta: 5:07:59 time: 0.9051 data_time: 0.2419 memory: 14901 loss: 1.1413 loss_prob: 0.6168 loss_thr: 0.4189 loss_db: 0.1056 2022/11/02 20:07:14 - mmengine - INFO - Epoch(train) [714][10/63] lr: 9.5968e-04 eta: 5:07:51 time: 0.8913 data_time: 0.2423 memory: 14901 loss: 1.1295 loss_prob: 0.6071 loss_thr: 0.4186 loss_db: 0.1037 2022/11/02 20:07:16 - mmengine - INFO - Epoch(train) [714][15/63] lr: 9.5968e-04 eta: 5:07:51 time: 0.5116 data_time: 0.0120 memory: 14901 loss: 1.0899 loss_prob: 0.5761 loss_thr: 0.4145 loss_db: 0.0993 2022/11/02 20:07:20 - mmengine - INFO - Epoch(train) [714][20/63] lr: 9.5968e-04 eta: 5:07:46 time: 0.6192 data_time: 0.0089 memory: 14901 loss: 1.0418 loss_prob: 0.5363 loss_thr: 0.4116 loss_db: 0.0939 2022/11/02 20:07:23 - mmengine - INFO - Epoch(train) [714][25/63] lr: 9.5968e-04 eta: 5:07:46 time: 0.6607 data_time: 0.0112 memory: 14901 loss: 1.0548 loss_prob: 0.5463 loss_thr: 0.4143 loss_db: 0.0942 2022/11/02 20:07:26 - mmengine - INFO - Epoch(train) [714][30/63] lr: 9.5968e-04 eta: 5:07:39 time: 0.5908 data_time: 0.0427 memory: 14901 loss: 1.0484 loss_prob: 0.5485 loss_thr: 0.4055 loss_db: 0.0944 2022/11/02 20:07:29 - mmengine - INFO - Epoch(train) [714][35/63] lr: 9.5968e-04 eta: 5:07:39 time: 0.5925 data_time: 0.0428 memory: 14901 loss: 1.0275 loss_prob: 0.5301 loss_thr: 0.4028 loss_db: 0.0946 2022/11/02 20:07:32 - mmengine - INFO - Epoch(train) [714][40/63] lr: 9.5968e-04 eta: 5:07:33 time: 0.5814 data_time: 0.0132 memory: 14901 loss: 1.1672 loss_prob: 0.6197 loss_thr: 0.4390 loss_db: 0.1086 2022/11/02 20:07:34 - mmengine - INFO - Epoch(train) [714][45/63] lr: 9.5968e-04 eta: 5:07:33 time: 0.5280 data_time: 0.0106 memory: 14901 loss: 1.2764 loss_prob: 0.7008 loss_thr: 0.4539 loss_db: 0.1216 2022/11/02 20:07:37 - mmengine - INFO - Epoch(train) [714][50/63] lr: 9.5968e-04 eta: 5:07:27 time: 0.5119 data_time: 0.0118 memory: 14901 loss: 1.1677 loss_prob: 0.6309 loss_thr: 0.4253 loss_db: 0.1115 2022/11/02 20:07:40 - mmengine - INFO - Epoch(train) [714][55/63] lr: 9.5968e-04 eta: 5:07:27 time: 0.6062 data_time: 0.0259 memory: 14901 loss: 1.0605 loss_prob: 0.5650 loss_thr: 0.3981 loss_db: 0.0974 2022/11/02 20:07:43 - mmengine - INFO - Epoch(train) [714][60/63] lr: 9.5968e-04 eta: 5:07:21 time: 0.6020 data_time: 0.0266 memory: 14901 loss: 1.1297 loss_prob: 0.6039 loss_thr: 0.4238 loss_db: 0.1020 2022/11/02 20:07:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:07:50 - mmengine - INFO - Epoch(train) [715][5/63] lr: 9.5791e-04 eta: 5:07:21 time: 0.8631 data_time: 0.2230 memory: 14901 loss: 1.1714 loss_prob: 0.6220 loss_thr: 0.4413 loss_db: 0.1081 2022/11/02 20:07:53 - mmengine - INFO - Epoch(train) [715][10/63] lr: 9.5791e-04 eta: 5:07:14 time: 0.8877 data_time: 0.2226 memory: 14901 loss: 1.1267 loss_prob: 0.5949 loss_thr: 0.4276 loss_db: 0.1042 2022/11/02 20:07:56 - mmengine - INFO - Epoch(train) [715][15/63] lr: 9.5791e-04 eta: 5:07:14 time: 0.5366 data_time: 0.0110 memory: 14901 loss: 1.1098 loss_prob: 0.5834 loss_thr: 0.4233 loss_db: 0.1030 2022/11/02 20:07:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:07:59 - mmengine - INFO - Epoch(train) [715][20/63] lr: 9.5791e-04 eta: 5:07:08 time: 0.6508 data_time: 0.0106 memory: 14901 loss: 1.0709 loss_prob: 0.5650 loss_thr: 0.4087 loss_db: 0.0972 2022/11/02 20:08:03 - mmengine - INFO - Epoch(train) [715][25/63] lr: 9.5791e-04 eta: 5:07:08 time: 0.7120 data_time: 0.0215 memory: 14901 loss: 1.0644 loss_prob: 0.5642 loss_thr: 0.4060 loss_db: 0.0941 2022/11/02 20:08:06 - mmengine - INFO - Epoch(train) [715][30/63] lr: 9.5791e-04 eta: 5:07:02 time: 0.6477 data_time: 0.0506 memory: 14901 loss: 1.1878 loss_prob: 0.6401 loss_thr: 0.4388 loss_db: 0.1088 2022/11/02 20:08:08 - mmengine - INFO - Epoch(train) [715][35/63] lr: 9.5791e-04 eta: 5:07:02 time: 0.5658 data_time: 0.0380 memory: 14901 loss: 1.1266 loss_prob: 0.6058 loss_thr: 0.4157 loss_db: 0.1051 2022/11/02 20:08:11 - mmengine - INFO - Epoch(train) [715][40/63] lr: 9.5791e-04 eta: 5:06:55 time: 0.5049 data_time: 0.0093 memory: 14901 loss: 0.9790 loss_prob: 0.5062 loss_thr: 0.3851 loss_db: 0.0877 2022/11/02 20:08:14 - mmengine - INFO - Epoch(train) [715][45/63] lr: 9.5791e-04 eta: 5:06:55 time: 0.5526 data_time: 0.0108 memory: 14901 loss: 0.9840 loss_prob: 0.5051 loss_thr: 0.3931 loss_db: 0.0858 2022/11/02 20:08:16 - mmengine - INFO - Epoch(train) [715][50/63] lr: 9.5791e-04 eta: 5:06:49 time: 0.5470 data_time: 0.0219 memory: 14901 loss: 1.0324 loss_prob: 0.5387 loss_thr: 0.4014 loss_db: 0.0923 2022/11/02 20:08:19 - mmengine - INFO - Epoch(train) [715][55/63] lr: 9.5791e-04 eta: 5:06:49 time: 0.5179 data_time: 0.0291 memory: 14901 loss: 1.0575 loss_prob: 0.5534 loss_thr: 0.4077 loss_db: 0.0965 2022/11/02 20:08:22 - mmengine - INFO - Epoch(train) [715][60/63] lr: 9.5791e-04 eta: 5:06:42 time: 0.5181 data_time: 0.0183 memory: 14901 loss: 1.0597 loss_prob: 0.5542 loss_thr: 0.4074 loss_db: 0.0981 2022/11/02 20:08:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:08:29 - mmengine - INFO - Epoch(train) [716][5/63] lr: 9.5613e-04 eta: 5:06:42 time: 0.8927 data_time: 0.2349 memory: 14901 loss: 1.0733 loss_prob: 0.5681 loss_thr: 0.4053 loss_db: 0.1000 2022/11/02 20:08:32 - mmengine - INFO - Epoch(train) [716][10/63] lr: 9.5613e-04 eta: 5:06:36 time: 0.9325 data_time: 0.2344 memory: 14901 loss: 1.1608 loss_prob: 0.6141 loss_thr: 0.4407 loss_db: 0.1060 2022/11/02 20:08:36 - mmengine - INFO - Epoch(train) [716][15/63] lr: 9.5613e-04 eta: 5:06:36 time: 0.6131 data_time: 0.0121 memory: 14901 loss: 1.2603 loss_prob: 0.6712 loss_thr: 0.4758 loss_db: 0.1133 2022/11/02 20:08:39 - mmengine - INFO - Epoch(train) [716][20/63] lr: 9.5613e-04 eta: 5:06:30 time: 0.6478 data_time: 0.0104 memory: 14901 loss: 1.1389 loss_prob: 0.6007 loss_thr: 0.4365 loss_db: 0.1017 2022/11/02 20:08:42 - mmengine - INFO - Epoch(train) [716][25/63] lr: 9.5613e-04 eta: 5:06:30 time: 0.6226 data_time: 0.0186 memory: 14901 loss: 0.9808 loss_prob: 0.5116 loss_thr: 0.3799 loss_db: 0.0893 2022/11/02 20:08:44 - mmengine - INFO - Epoch(train) [716][30/63] lr: 9.5613e-04 eta: 5:06:24 time: 0.5689 data_time: 0.0427 memory: 14901 loss: 1.0418 loss_prob: 0.5489 loss_thr: 0.3990 loss_db: 0.0939 2022/11/02 20:08:47 - mmengine - INFO - Epoch(train) [716][35/63] lr: 9.5613e-04 eta: 5:06:24 time: 0.5459 data_time: 0.0334 memory: 14901 loss: 1.0225 loss_prob: 0.5322 loss_thr: 0.3990 loss_db: 0.0914 2022/11/02 20:08:50 - mmengine - INFO - Epoch(train) [716][40/63] lr: 9.5613e-04 eta: 5:06:18 time: 0.5862 data_time: 0.0125 memory: 14901 loss: 0.9789 loss_prob: 0.5017 loss_thr: 0.3893 loss_db: 0.0879 2022/11/02 20:08:53 - mmengine - INFO - Epoch(train) [716][45/63] lr: 9.5613e-04 eta: 5:06:18 time: 0.5736 data_time: 0.0115 memory: 14901 loss: 1.1076 loss_prob: 0.5712 loss_thr: 0.4369 loss_db: 0.0995 2022/11/02 20:08:56 - mmengine - INFO - Epoch(train) [716][50/63] lr: 9.5613e-04 eta: 5:06:11 time: 0.5387 data_time: 0.0135 memory: 14901 loss: 1.1211 loss_prob: 0.5824 loss_thr: 0.4378 loss_db: 0.1009 2022/11/02 20:08:59 - mmengine - INFO - Epoch(train) [716][55/63] lr: 9.5613e-04 eta: 5:06:11 time: 0.5624 data_time: 0.0297 memory: 14901 loss: 1.0789 loss_prob: 0.5720 loss_thr: 0.4071 loss_db: 0.0998 2022/11/02 20:09:01 - mmengine - INFO - Epoch(train) [716][60/63] lr: 9.5613e-04 eta: 5:06:05 time: 0.5652 data_time: 0.0269 memory: 14901 loss: 1.0908 loss_prob: 0.5802 loss_thr: 0.4104 loss_db: 0.1002 2022/11/02 20:09:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:09:10 - mmengine - INFO - Epoch(train) [717][5/63] lr: 9.5435e-04 eta: 5:06:05 time: 0.9287 data_time: 0.2398 memory: 14901 loss: 1.0848 loss_prob: 0.5720 loss_thr: 0.4143 loss_db: 0.0985 2022/11/02 20:09:13 - mmengine - INFO - Epoch(train) [717][10/63] lr: 9.5435e-04 eta: 5:05:58 time: 0.9896 data_time: 0.2394 memory: 14901 loss: 1.0506 loss_prob: 0.5565 loss_thr: 0.3994 loss_db: 0.0947 2022/11/02 20:09:16 - mmengine - INFO - Epoch(train) [717][15/63] lr: 9.5435e-04 eta: 5:05:58 time: 0.6008 data_time: 0.0078 memory: 14901 loss: 1.0314 loss_prob: 0.5418 loss_thr: 0.3957 loss_db: 0.0939 2022/11/02 20:09:19 - mmengine - INFO - Epoch(train) [717][20/63] lr: 9.5435e-04 eta: 5:05:53 time: 0.6607 data_time: 0.0089 memory: 14901 loss: 1.0398 loss_prob: 0.5445 loss_thr: 0.4014 loss_db: 0.0939 2022/11/02 20:09:22 - mmengine - INFO - Epoch(train) [717][25/63] lr: 9.5435e-04 eta: 5:05:53 time: 0.6833 data_time: 0.0386 memory: 14901 loss: 1.1080 loss_prob: 0.5872 loss_thr: 0.4207 loss_db: 0.1001 2022/11/02 20:09:26 - mmengine - INFO - Epoch(train) [717][30/63] lr: 9.5435e-04 eta: 5:05:47 time: 0.6734 data_time: 0.0483 memory: 14901 loss: 1.0868 loss_prob: 0.5731 loss_thr: 0.4155 loss_db: 0.0983 2022/11/02 20:09:29 - mmengine - INFO - Epoch(train) [717][35/63] lr: 9.5435e-04 eta: 5:05:47 time: 0.6373 data_time: 0.0191 memory: 14901 loss: 1.0194 loss_prob: 0.5326 loss_thr: 0.3958 loss_db: 0.0910 2022/11/02 20:09:32 - mmengine - INFO - Epoch(train) [717][40/63] lr: 9.5435e-04 eta: 5:05:41 time: 0.5554 data_time: 0.0094 memory: 14901 loss: 1.0622 loss_prob: 0.5567 loss_thr: 0.4087 loss_db: 0.0968 2022/11/02 20:09:35 - mmengine - INFO - Epoch(train) [717][45/63] lr: 9.5435e-04 eta: 5:05:41 time: 0.5972 data_time: 0.0121 memory: 14901 loss: 1.1015 loss_prob: 0.5787 loss_thr: 0.4224 loss_db: 0.1005 2022/11/02 20:09:38 - mmengine - INFO - Epoch(train) [717][50/63] lr: 9.5435e-04 eta: 5:05:35 time: 0.6219 data_time: 0.0297 memory: 14901 loss: 1.1409 loss_prob: 0.6015 loss_thr: 0.4367 loss_db: 0.1028 2022/11/02 20:09:40 - mmengine - INFO - Epoch(train) [717][55/63] lr: 9.5435e-04 eta: 5:05:35 time: 0.5651 data_time: 0.0307 memory: 14901 loss: 1.1388 loss_prob: 0.5958 loss_thr: 0.4399 loss_db: 0.1030 2022/11/02 20:09:43 - mmengine - INFO - Epoch(train) [717][60/63] lr: 9.5435e-04 eta: 5:05:28 time: 0.5335 data_time: 0.0128 memory: 14901 loss: 1.1451 loss_prob: 0.6020 loss_thr: 0.4367 loss_db: 0.1064 2022/11/02 20:09:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:09:51 - mmengine - INFO - Epoch(train) [718][5/63] lr: 9.5257e-04 eta: 5:05:28 time: 0.8822 data_time: 0.2547 memory: 14901 loss: 1.1777 loss_prob: 0.6501 loss_thr: 0.4217 loss_db: 0.1059 2022/11/02 20:09:54 - mmengine - INFO - Epoch(train) [718][10/63] lr: 9.5257e-04 eta: 5:05:21 time: 0.8947 data_time: 0.2568 memory: 14901 loss: 1.1176 loss_prob: 0.6140 loss_thr: 0.4033 loss_db: 0.1003 2022/11/02 20:09:57 - mmengine - INFO - Epoch(train) [718][15/63] lr: 9.5257e-04 eta: 5:05:21 time: 0.6257 data_time: 0.0177 memory: 14901 loss: 1.0689 loss_prob: 0.5677 loss_thr: 0.4012 loss_db: 0.1000 2022/11/02 20:10:00 - mmengine - INFO - Epoch(train) [718][20/63] lr: 9.5257e-04 eta: 5:05:16 time: 0.6839 data_time: 0.0150 memory: 14901 loss: 1.1091 loss_prob: 0.5872 loss_thr: 0.4191 loss_db: 0.1029 2022/11/02 20:10:03 - mmengine - INFO - Epoch(train) [718][25/63] lr: 9.5257e-04 eta: 5:05:16 time: 0.6534 data_time: 0.0337 memory: 14901 loss: 1.1131 loss_prob: 0.5887 loss_thr: 0.4236 loss_db: 0.1008 2022/11/02 20:10:06 - mmengine - INFO - Epoch(train) [718][30/63] lr: 9.5257e-04 eta: 5:05:10 time: 0.5694 data_time: 0.0378 memory: 14901 loss: 1.1538 loss_prob: 0.6172 loss_thr: 0.4313 loss_db: 0.1053 2022/11/02 20:10:09 - mmengine - INFO - Epoch(train) [718][35/63] lr: 9.5257e-04 eta: 5:05:10 time: 0.5483 data_time: 0.0169 memory: 14901 loss: 1.0269 loss_prob: 0.5330 loss_thr: 0.4012 loss_db: 0.0927 2022/11/02 20:10:12 - mmengine - INFO - Epoch(train) [718][40/63] lr: 9.5257e-04 eta: 5:05:03 time: 0.5747 data_time: 0.0168 memory: 14901 loss: 0.9600 loss_prob: 0.4921 loss_thr: 0.3830 loss_db: 0.0849 2022/11/02 20:10:15 - mmengine - INFO - Epoch(train) [718][45/63] lr: 9.5257e-04 eta: 5:05:03 time: 0.5958 data_time: 0.0162 memory: 14901 loss: 1.0730 loss_prob: 0.5611 loss_thr: 0.4153 loss_db: 0.0965 2022/11/02 20:10:18 - mmengine - INFO - Epoch(train) [718][50/63] lr: 9.5257e-04 eta: 5:04:57 time: 0.5755 data_time: 0.0325 memory: 14901 loss: 1.0563 loss_prob: 0.5538 loss_thr: 0.4066 loss_db: 0.0959 2022/11/02 20:10:20 - mmengine - INFO - Epoch(train) [718][55/63] lr: 9.5257e-04 eta: 5:04:57 time: 0.5215 data_time: 0.0357 memory: 14901 loss: 1.0063 loss_prob: 0.5202 loss_thr: 0.3973 loss_db: 0.0887 2022/11/02 20:10:23 - mmengine - INFO - Epoch(train) [718][60/63] lr: 9.5257e-04 eta: 5:04:51 time: 0.5303 data_time: 0.0160 memory: 14901 loss: 1.2096 loss_prob: 0.6706 loss_thr: 0.4333 loss_db: 0.1057 2022/11/02 20:10:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:10:31 - mmengine - INFO - Epoch(train) [719][5/63] lr: 9.5079e-04 eta: 5:04:51 time: 0.9480 data_time: 0.2419 memory: 14901 loss: 1.0403 loss_prob: 0.5334 loss_thr: 0.4119 loss_db: 0.0950 2022/11/02 20:10:35 - mmengine - INFO - Epoch(train) [719][10/63] lr: 9.5079e-04 eta: 5:04:45 time: 1.0207 data_time: 0.2408 memory: 14901 loss: 1.0488 loss_prob: 0.5459 loss_thr: 0.4085 loss_db: 0.0944 2022/11/02 20:10:37 - mmengine - INFO - Epoch(train) [719][15/63] lr: 9.5079e-04 eta: 5:04:45 time: 0.6245 data_time: 0.0108 memory: 14901 loss: 1.0815 loss_prob: 0.5681 loss_thr: 0.4179 loss_db: 0.0955 2022/11/02 20:10:40 - mmengine - INFO - Epoch(train) [719][20/63] lr: 9.5079e-04 eta: 5:04:38 time: 0.5425 data_time: 0.0123 memory: 14901 loss: 1.1258 loss_prob: 0.5936 loss_thr: 0.4308 loss_db: 0.1013 2022/11/02 20:10:44 - mmengine - INFO - Epoch(train) [719][25/63] lr: 9.5079e-04 eta: 5:04:38 time: 0.6453 data_time: 0.0290 memory: 14901 loss: 1.0573 loss_prob: 0.5554 loss_thr: 0.4041 loss_db: 0.0978 2022/11/02 20:10:47 - mmengine - INFO - Epoch(train) [719][30/63] lr: 9.5079e-04 eta: 5:04:33 time: 0.6952 data_time: 0.0619 memory: 14901 loss: 1.0384 loss_prob: 0.5439 loss_thr: 0.4007 loss_db: 0.0938 2022/11/02 20:10:50 - mmengine - INFO - Epoch(train) [719][35/63] lr: 9.5079e-04 eta: 5:04:33 time: 0.6062 data_time: 0.0441 memory: 14901 loss: 1.0641 loss_prob: 0.5584 loss_thr: 0.4107 loss_db: 0.0951 2022/11/02 20:10:52 - mmengine - INFO - Epoch(train) [719][40/63] lr: 9.5079e-04 eta: 5:04:26 time: 0.5354 data_time: 0.0091 memory: 14901 loss: 1.0835 loss_prob: 0.5708 loss_thr: 0.4135 loss_db: 0.0992 2022/11/02 20:10:55 - mmengine - INFO - Epoch(train) [719][45/63] lr: 9.5079e-04 eta: 5:04:26 time: 0.5521 data_time: 0.0088 memory: 14901 loss: 1.0524 loss_prob: 0.5466 loss_thr: 0.4094 loss_db: 0.0964 2022/11/02 20:10:58 - mmengine - INFO - Epoch(train) [719][50/63] lr: 9.5079e-04 eta: 5:04:20 time: 0.5839 data_time: 0.0276 memory: 14901 loss: 1.1200 loss_prob: 0.5854 loss_thr: 0.4322 loss_db: 0.1023 2022/11/02 20:11:01 - mmengine - INFO - Epoch(train) [719][55/63] lr: 9.5079e-04 eta: 5:04:20 time: 0.5851 data_time: 0.0338 memory: 14901 loss: 1.1525 loss_prob: 0.6218 loss_thr: 0.4250 loss_db: 0.1057 2022/11/02 20:11:04 - mmengine - INFO - Epoch(train) [719][60/63] lr: 9.5079e-04 eta: 5:04:14 time: 0.6139 data_time: 0.0183 memory: 14901 loss: 1.0228 loss_prob: 0.5359 loss_thr: 0.3963 loss_db: 0.0905 2022/11/02 20:11:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:11:11 - mmengine - INFO - Epoch(train) [720][5/63] lr: 9.4902e-04 eta: 5:04:14 time: 0.8283 data_time: 0.2284 memory: 14901 loss: 0.9774 loss_prob: 0.4944 loss_thr: 0.3952 loss_db: 0.0878 2022/11/02 20:11:14 - mmengine - INFO - Epoch(train) [720][10/63] lr: 9.4902e-04 eta: 5:04:07 time: 0.8588 data_time: 0.2385 memory: 14901 loss: 1.0185 loss_prob: 0.5178 loss_thr: 0.4099 loss_db: 0.0908 2022/11/02 20:11:17 - mmengine - INFO - Epoch(train) [720][15/63] lr: 9.4902e-04 eta: 5:04:07 time: 0.5630 data_time: 0.0212 memory: 14901 loss: 1.1040 loss_prob: 0.5566 loss_thr: 0.4507 loss_db: 0.0967 2022/11/02 20:11:20 - mmengine - INFO - Epoch(train) [720][20/63] lr: 9.4902e-04 eta: 5:04:01 time: 0.5850 data_time: 0.0099 memory: 14901 loss: 1.0903 loss_prob: 0.5524 loss_thr: 0.4419 loss_db: 0.0960 2022/11/02 20:11:24 - mmengine - INFO - Epoch(train) [720][25/63] lr: 9.4902e-04 eta: 5:04:01 time: 0.6996 data_time: 0.0097 memory: 14901 loss: 1.0966 loss_prob: 0.5823 loss_thr: 0.4127 loss_db: 0.1017 2022/11/02 20:11:28 - mmengine - INFO - Epoch(train) [720][30/63] lr: 9.4902e-04 eta: 5:03:56 time: 0.7418 data_time: 0.0409 memory: 14901 loss: 1.1494 loss_prob: 0.6179 loss_thr: 0.4280 loss_db: 0.1036 2022/11/02 20:11:30 - mmengine - INFO - Epoch(train) [720][35/63] lr: 9.4902e-04 eta: 5:03:56 time: 0.6141 data_time: 0.0455 memory: 14901 loss: 1.1959 loss_prob: 0.6434 loss_thr: 0.4463 loss_db: 0.1062 2022/11/02 20:11:33 - mmengine - INFO - Epoch(train) [720][40/63] lr: 9.4902e-04 eta: 5:03:49 time: 0.5665 data_time: 0.0156 memory: 14901 loss: 1.2055 loss_prob: 0.6481 loss_thr: 0.4459 loss_db: 0.1116 2022/11/02 20:11:36 - mmengine - INFO - Epoch(train) [720][45/63] lr: 9.4902e-04 eta: 5:03:49 time: 0.5897 data_time: 0.0112 memory: 14901 loss: 1.1300 loss_prob: 0.6102 loss_thr: 0.4167 loss_db: 0.1031 2022/11/02 20:11:39 - mmengine - INFO - Epoch(train) [720][50/63] lr: 9.4902e-04 eta: 5:03:43 time: 0.5875 data_time: 0.0179 memory: 14901 loss: 1.1045 loss_prob: 0.5925 loss_thr: 0.4139 loss_db: 0.0981 2022/11/02 20:11:43 - mmengine - INFO - Epoch(train) [720][55/63] lr: 9.4902e-04 eta: 5:03:43 time: 0.6417 data_time: 0.0262 memory: 14901 loss: 1.0674 loss_prob: 0.5612 loss_thr: 0.4101 loss_db: 0.0961 2022/11/02 20:11:46 - mmengine - INFO - Epoch(train) [720][60/63] lr: 9.4902e-04 eta: 5:03:38 time: 0.6547 data_time: 0.0200 memory: 14901 loss: 1.0832 loss_prob: 0.5781 loss_thr: 0.4041 loss_db: 0.1010 2022/11/02 20:11:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:11:47 - mmengine - INFO - Saving checkpoint at 720 epochs 2022/11/02 20:11:52 - mmengine - INFO - Epoch(val) [720][5/500] eta: 5:03:38 time: 0.0497 data_time: 0.0059 memory: 14901 2022/11/02 20:11:52 - mmengine - INFO - Epoch(val) [720][10/500] eta: 0:00:23 time: 0.0470 data_time: 0.0051 memory: 1008 2022/11/02 20:11:52 - mmengine - INFO - Epoch(val) [720][15/500] eta: 0:00:23 time: 0.0372 data_time: 0.0021 memory: 1008 2022/11/02 20:11:52 - mmengine - INFO - Epoch(val) [720][20/500] eta: 0:00:18 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/02 20:11:52 - mmengine - INFO - Epoch(val) [720][25/500] eta: 0:00:18 time: 0.0368 data_time: 0.0026 memory: 1008 2022/11/02 20:11:53 - mmengine - INFO - Epoch(val) [720][30/500] eta: 0:00:19 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/02 20:11:53 - mmengine - INFO - Epoch(val) [720][35/500] eta: 0:00:19 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 20:11:53 - mmengine - INFO - Epoch(val) [720][40/500] eta: 0:00:19 time: 0.0424 data_time: 0.0031 memory: 1008 2022/11/02 20:11:53 - mmengine - INFO - Epoch(val) [720][45/500] eta: 0:00:19 time: 0.0470 data_time: 0.0032 memory: 1008 2022/11/02 20:11:53 - mmengine - INFO - Epoch(val) [720][50/500] eta: 0:00:18 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 20:11:54 - mmengine - INFO - Epoch(val) [720][55/500] eta: 0:00:18 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/02 20:11:54 - mmengine - INFO - Epoch(val) [720][60/500] eta: 0:00:18 time: 0.0421 data_time: 0.0026 memory: 1008 2022/11/02 20:11:54 - mmengine - INFO - Epoch(val) [720][65/500] eta: 0:00:18 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 20:11:54 - mmengine - INFO - Epoch(val) [720][70/500] eta: 0:00:19 time: 0.0448 data_time: 0.0028 memory: 1008 2022/11/02 20:11:54 - mmengine - INFO - Epoch(val) [720][75/500] eta: 0:00:19 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 20:11:55 - mmengine - INFO - Epoch(val) [720][80/500] eta: 0:00:16 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 20:11:55 - mmengine - INFO - Epoch(val) [720][85/500] eta: 0:00:16 time: 0.0436 data_time: 0.0028 memory: 1008 2022/11/02 20:11:55 - mmengine - INFO - Epoch(val) [720][90/500] eta: 0:00:18 time: 0.0463 data_time: 0.0027 memory: 1008 2022/11/02 20:11:55 - mmengine - INFO - Epoch(val) [720][95/500] eta: 0:00:18 time: 0.0433 data_time: 0.0026 memory: 1008 2022/11/02 20:11:56 - mmengine - INFO - Epoch(val) [720][100/500] eta: 0:00:16 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 20:11:56 - mmengine - INFO - Epoch(val) [720][105/500] eta: 0:00:16 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 20:11:56 - mmengine - INFO - Epoch(val) [720][110/500] eta: 0:00:14 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 20:11:56 - mmengine - INFO - Epoch(val) [720][115/500] eta: 0:00:14 time: 0.0392 data_time: 0.0026 memory: 1008 2022/11/02 20:11:56 - mmengine - INFO - Epoch(val) [720][120/500] eta: 0:00:14 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 20:11:57 - mmengine - INFO - Epoch(val) [720][125/500] eta: 0:00:14 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/02 20:11:57 - mmengine - INFO - Epoch(val) [720][130/500] eta: 0:00:14 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/02 20:11:57 - mmengine - INFO - Epoch(val) [720][135/500] eta: 0:00:14 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/02 20:11:57 - mmengine - INFO - Epoch(val) [720][140/500] eta: 0:00:14 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 20:11:57 - mmengine - INFO - Epoch(val) [720][145/500] eta: 0:00:14 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/02 20:11:58 - mmengine - INFO - Epoch(val) [720][150/500] eta: 0:00:15 time: 0.0434 data_time: 0.0027 memory: 1008 2022/11/02 20:11:58 - mmengine - INFO - Epoch(val) [720][155/500] eta: 0:00:15 time: 0.0450 data_time: 0.0029 memory: 1008 2022/11/02 20:11:58 - mmengine - INFO - Epoch(val) [720][160/500] eta: 0:00:16 time: 0.0481 data_time: 0.0029 memory: 1008 2022/11/02 20:11:58 - mmengine - INFO - Epoch(val) [720][165/500] eta: 0:00:16 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 20:11:58 - mmengine - INFO - Epoch(val) [720][170/500] eta: 0:00:14 time: 0.0439 data_time: 0.0027 memory: 1008 2022/11/02 20:11:59 - mmengine - INFO - Epoch(val) [720][175/500] eta: 0:00:14 time: 0.0443 data_time: 0.0033 memory: 1008 2022/11/02 20:11:59 - mmengine - INFO - Epoch(val) [720][180/500] eta: 0:00:12 time: 0.0399 data_time: 0.0031 memory: 1008 2022/11/02 20:11:59 - mmengine - INFO - Epoch(val) [720][185/500] eta: 0:00:12 time: 0.0418 data_time: 0.0026 memory: 1008 2022/11/02 20:11:59 - mmengine - INFO - Epoch(val) [720][190/500] eta: 0:00:13 time: 0.0447 data_time: 0.0027 memory: 1008 2022/11/02 20:12:00 - mmengine - INFO - Epoch(val) [720][195/500] eta: 0:00:13 time: 0.0440 data_time: 0.0026 memory: 1008 2022/11/02 20:12:00 - mmengine - INFO - Epoch(val) [720][200/500] eta: 0:00:14 time: 0.0470 data_time: 0.0026 memory: 1008 2022/11/02 20:12:00 - mmengine - INFO - Epoch(val) [720][205/500] eta: 0:00:14 time: 0.0429 data_time: 0.0025 memory: 1008 2022/11/02 20:12:00 - mmengine - INFO - Epoch(val) [720][210/500] eta: 0:00:10 time: 0.0376 data_time: 0.0026 memory: 1008 2022/11/02 20:12:00 - mmengine - INFO - Epoch(val) [720][215/500] eta: 0:00:10 time: 0.0426 data_time: 0.0029 memory: 1008 2022/11/02 20:12:01 - mmengine - INFO - Epoch(val) [720][220/500] eta: 0:00:15 time: 0.0553 data_time: 0.0049 memory: 1008 2022/11/02 20:12:01 - mmengine - INFO - Epoch(val) [720][225/500] eta: 0:00:15 time: 0.0585 data_time: 0.0051 memory: 1008 2022/11/02 20:12:01 - mmengine - INFO - Epoch(val) [720][230/500] eta: 0:00:13 time: 0.0482 data_time: 0.0037 memory: 1008 2022/11/02 20:12:01 - mmengine - INFO - Epoch(val) [720][235/500] eta: 0:00:13 time: 0.0452 data_time: 0.0035 memory: 1008 2022/11/02 20:12:02 - mmengine - INFO - Epoch(val) [720][240/500] eta: 0:00:11 time: 0.0448 data_time: 0.0030 memory: 1008 2022/11/02 20:12:02 - mmengine - INFO - Epoch(val) [720][245/500] eta: 0:00:11 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/02 20:12:02 - mmengine - INFO - Epoch(val) [720][250/500] eta: 0:00:10 time: 0.0435 data_time: 0.0034 memory: 1008 2022/11/02 20:12:02 - mmengine - INFO - Epoch(val) [720][255/500] eta: 0:00:10 time: 0.0445 data_time: 0.0034 memory: 1008 2022/11/02 20:12:03 - mmengine - INFO - Epoch(val) [720][260/500] eta: 0:00:10 time: 0.0453 data_time: 0.0032 memory: 1008 2022/11/02 20:12:03 - mmengine - INFO - Epoch(val) [720][265/500] eta: 0:00:10 time: 0.0521 data_time: 0.0039 memory: 1008 2022/11/02 20:12:03 - mmengine - INFO - Epoch(val) [720][270/500] eta: 0:00:14 time: 0.0622 data_time: 0.0049 memory: 1008 2022/11/02 20:12:03 - mmengine - INFO - Epoch(val) [720][275/500] eta: 0:00:14 time: 0.0602 data_time: 0.0050 memory: 1008 2022/11/02 20:12:04 - mmengine - INFO - Epoch(val) [720][280/500] eta: 0:00:11 time: 0.0529 data_time: 0.0040 memory: 1008 2022/11/02 20:12:04 - mmengine - INFO - Epoch(val) [720][285/500] eta: 0:00:11 time: 0.0455 data_time: 0.0031 memory: 1008 2022/11/02 20:12:04 - mmengine - INFO - Epoch(val) [720][290/500] eta: 0:00:08 time: 0.0425 data_time: 0.0029 memory: 1008 2022/11/02 20:12:04 - mmengine - INFO - Epoch(val) [720][295/500] eta: 0:00:08 time: 0.0439 data_time: 0.0029 memory: 1008 2022/11/02 20:12:05 - mmengine - INFO - Epoch(val) [720][300/500] eta: 0:00:08 time: 0.0424 data_time: 0.0028 memory: 1008 2022/11/02 20:12:05 - mmengine - INFO - Epoch(val) [720][305/500] eta: 0:00:08 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/02 20:12:05 - mmengine - INFO - Epoch(val) [720][310/500] eta: 0:00:07 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 20:12:05 - mmengine - INFO - Epoch(val) [720][315/500] eta: 0:00:07 time: 0.0445 data_time: 0.0036 memory: 1008 2022/11/02 20:12:05 - mmengine - INFO - Epoch(val) [720][320/500] eta: 0:00:08 time: 0.0450 data_time: 0.0039 memory: 1008 2022/11/02 20:12:06 - mmengine - INFO - Epoch(val) [720][325/500] eta: 0:00:08 time: 0.0568 data_time: 0.0029 memory: 1008 2022/11/02 20:12:06 - mmengine - INFO - Epoch(val) [720][330/500] eta: 0:00:09 time: 0.0579 data_time: 0.0035 memory: 1008 2022/11/02 20:12:06 - mmengine - INFO - Epoch(val) [720][335/500] eta: 0:00:09 time: 0.0400 data_time: 0.0034 memory: 1008 2022/11/02 20:12:06 - mmengine - INFO - Epoch(val) [720][340/500] eta: 0:00:08 time: 0.0501 data_time: 0.0034 memory: 1008 2022/11/02 20:12:07 - mmengine - INFO - Epoch(val) [720][345/500] eta: 0:00:08 time: 0.0539 data_time: 0.0039 memory: 1008 2022/11/02 20:12:07 - mmengine - INFO - Epoch(val) [720][350/500] eta: 0:00:07 time: 0.0524 data_time: 0.0035 memory: 1008 2022/11/02 20:12:07 - mmengine - INFO - Epoch(val) [720][355/500] eta: 0:00:07 time: 0.0501 data_time: 0.0033 memory: 1008 2022/11/02 20:12:07 - mmengine - INFO - Epoch(val) [720][360/500] eta: 0:00:06 time: 0.0450 data_time: 0.0031 memory: 1008 2022/11/02 20:12:08 - mmengine - INFO - Epoch(val) [720][365/500] eta: 0:00:06 time: 0.0492 data_time: 0.0034 memory: 1008 2022/11/02 20:12:08 - mmengine - INFO - Epoch(val) [720][370/500] eta: 0:00:05 time: 0.0428 data_time: 0.0035 memory: 1008 2022/11/02 20:12:08 - mmengine - INFO - Epoch(val) [720][375/500] eta: 0:00:05 time: 0.0395 data_time: 0.0036 memory: 1008 2022/11/02 20:12:08 - mmengine - INFO - Epoch(val) [720][380/500] eta: 0:00:05 time: 0.0489 data_time: 0.0039 memory: 1008 2022/11/02 20:12:09 - mmengine - INFO - Epoch(val) [720][385/500] eta: 0:00:05 time: 0.0519 data_time: 0.0038 memory: 1008 2022/11/02 20:12:09 - mmengine - INFO - Epoch(val) [720][390/500] eta: 0:00:05 time: 0.0496 data_time: 0.0037 memory: 1008 2022/11/02 20:12:09 - mmengine - INFO - Epoch(val) [720][395/500] eta: 0:00:05 time: 0.0456 data_time: 0.0034 memory: 1008 2022/11/02 20:12:09 - mmengine - INFO - Epoch(val) [720][400/500] eta: 0:00:04 time: 0.0402 data_time: 0.0029 memory: 1008 2022/11/02 20:12:09 - mmengine - INFO - Epoch(val) [720][405/500] eta: 0:00:04 time: 0.0410 data_time: 0.0032 memory: 1008 2022/11/02 20:12:10 - mmengine - INFO - Epoch(val) [720][410/500] eta: 0:00:04 time: 0.0460 data_time: 0.0035 memory: 1008 2022/11/02 20:12:10 - mmengine - INFO - Epoch(val) [720][415/500] eta: 0:00:04 time: 0.0489 data_time: 0.0035 memory: 1008 2022/11/02 20:12:10 - mmengine - INFO - Epoch(val) [720][420/500] eta: 0:00:03 time: 0.0450 data_time: 0.0039 memory: 1008 2022/11/02 20:12:10 - mmengine - INFO - Epoch(val) [720][425/500] eta: 0:00:03 time: 0.0412 data_time: 0.0036 memory: 1008 2022/11/02 20:12:11 - mmengine - INFO - Epoch(val) [720][430/500] eta: 0:00:02 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/02 20:12:11 - mmengine - INFO - Epoch(val) [720][435/500] eta: 0:00:02 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 20:12:11 - mmengine - INFO - Epoch(val) [720][440/500] eta: 0:00:02 time: 0.0389 data_time: 0.0026 memory: 1008 2022/11/02 20:12:11 - mmengine - INFO - Epoch(val) [720][445/500] eta: 0:00:02 time: 0.0439 data_time: 0.0028 memory: 1008 2022/11/02 20:12:11 - mmengine - INFO - Epoch(val) [720][450/500] eta: 0:00:02 time: 0.0454 data_time: 0.0030 memory: 1008 2022/11/02 20:12:12 - mmengine - INFO - Epoch(val) [720][455/500] eta: 0:00:02 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/02 20:12:12 - mmengine - INFO - Epoch(val) [720][460/500] eta: 0:00:01 time: 0.0414 data_time: 0.0030 memory: 1008 2022/11/02 20:12:12 - mmengine - INFO - Epoch(val) [720][465/500] eta: 0:00:01 time: 0.0370 data_time: 0.0026 memory: 1008 2022/11/02 20:12:12 - mmengine - INFO - Epoch(val) [720][470/500] eta: 0:00:01 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 20:12:12 - mmengine - INFO - Epoch(val) [720][475/500] eta: 0:00:01 time: 0.0422 data_time: 0.0032 memory: 1008 2022/11/02 20:12:13 - mmengine - INFO - Epoch(val) [720][480/500] eta: 0:00:00 time: 0.0453 data_time: 0.0033 memory: 1008 2022/11/02 20:12:13 - mmengine - INFO - Epoch(val) [720][485/500] eta: 0:00:00 time: 0.0451 data_time: 0.0032 memory: 1008 2022/11/02 20:12:13 - mmengine - INFO - Epoch(val) [720][490/500] eta: 0:00:00 time: 0.0460 data_time: 0.0032 memory: 1008 2022/11/02 20:12:13 - mmengine - INFO - Epoch(val) [720][495/500] eta: 0:00:00 time: 0.0448 data_time: 0.0032 memory: 1008 2022/11/02 20:12:14 - mmengine - INFO - Epoch(val) [720][500/500] eta: 0:00:00 time: 0.0391 data_time: 0.0030 memory: 1008 2022/11/02 20:12:14 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8175, precision: 0.7421, hmean: 0.7780 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8175, precision: 0.7909, hmean: 0.8040 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8170, precision: 0.8186, hmean: 0.8178 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8122, precision: 0.8452, hmean: 0.8284 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7896, precision: 0.8742, hmean: 0.8297 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6543, precision: 0.9176, hmean: 0.7639 2022/11/02 20:12:14 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0549, precision: 0.8837, hmean: 0.1034 2022/11/02 20:12:14 - mmengine - INFO - Epoch(val) [720][500/500] icdar/precision: 0.8742 icdar/recall: 0.7896 icdar/hmean: 0.8297 2022/11/02 20:12:20 - mmengine - INFO - Epoch(train) [721][5/63] lr: 9.4724e-04 eta: 0:00:00 time: 0.9706 data_time: 0.2576 memory: 14901 loss: 1.0414 loss_prob: 0.5478 loss_thr: 0.4025 loss_db: 0.0911 2022/11/02 20:12:23 - mmengine - INFO - Epoch(train) [721][10/63] lr: 9.4724e-04 eta: 5:03:31 time: 0.9451 data_time: 0.2577 memory: 14901 loss: 0.9982 loss_prob: 0.5129 loss_thr: 0.3986 loss_db: 0.0868 2022/11/02 20:12:26 - mmengine - INFO - Epoch(train) [721][15/63] lr: 9.4724e-04 eta: 5:03:31 time: 0.5570 data_time: 0.0093 memory: 14901 loss: 1.0225 loss_prob: 0.5228 loss_thr: 0.4070 loss_db: 0.0927 2022/11/02 20:12:28 - mmengine - INFO - Epoch(train) [721][20/63] lr: 9.4724e-04 eta: 5:03:24 time: 0.5334 data_time: 0.0131 memory: 14901 loss: 1.0783 loss_prob: 0.5576 loss_thr: 0.4239 loss_db: 0.0968 2022/11/02 20:12:31 - mmengine - INFO - Epoch(train) [721][25/63] lr: 9.4724e-04 eta: 5:03:24 time: 0.5383 data_time: 0.0249 memory: 14901 loss: 1.0808 loss_prob: 0.5633 loss_thr: 0.4218 loss_db: 0.0956 2022/11/02 20:12:35 - mmengine - INFO - Epoch(train) [721][30/63] lr: 9.4724e-04 eta: 5:03:18 time: 0.6062 data_time: 0.0477 memory: 14901 loss: 1.1280 loss_prob: 0.6018 loss_thr: 0.4248 loss_db: 0.1014 2022/11/02 20:12:37 - mmengine - INFO - Epoch(train) [721][35/63] lr: 9.4724e-04 eta: 5:03:18 time: 0.5649 data_time: 0.0358 memory: 14901 loss: 1.1463 loss_prob: 0.6207 loss_thr: 0.4228 loss_db: 0.1029 2022/11/02 20:12:40 - mmengine - INFO - Epoch(train) [721][40/63] lr: 9.4724e-04 eta: 5:03:12 time: 0.5186 data_time: 0.0129 memory: 14901 loss: 1.0572 loss_prob: 0.5682 loss_thr: 0.3927 loss_db: 0.0964 2022/11/02 20:12:43 - mmengine - INFO - Epoch(train) [721][45/63] lr: 9.4724e-04 eta: 5:03:12 time: 0.5660 data_time: 0.0102 memory: 14901 loss: 1.0739 loss_prob: 0.5694 loss_thr: 0.4048 loss_db: 0.0998 2022/11/02 20:12:46 - mmengine - INFO - Epoch(train) [721][50/63] lr: 9.4724e-04 eta: 5:03:06 time: 0.6289 data_time: 0.0231 memory: 14901 loss: 1.1033 loss_prob: 0.5837 loss_thr: 0.4184 loss_db: 0.1013 2022/11/02 20:12:49 - mmengine - INFO - Epoch(train) [721][55/63] lr: 9.4724e-04 eta: 5:03:06 time: 0.6112 data_time: 0.0358 memory: 14901 loss: 1.0771 loss_prob: 0.5757 loss_thr: 0.4025 loss_db: 0.0988 2022/11/02 20:12:52 - mmengine - INFO - Epoch(train) [721][60/63] lr: 9.4724e-04 eta: 5:03:00 time: 0.6012 data_time: 0.0229 memory: 14901 loss: 1.1043 loss_prob: 0.5906 loss_thr: 0.4111 loss_db: 0.1026 2022/11/02 20:12:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:12:59 - mmengine - INFO - Epoch(train) [722][5/63] lr: 9.4546e-04 eta: 5:03:00 time: 0.7782 data_time: 0.2117 memory: 14901 loss: 1.1185 loss_prob: 0.5920 loss_thr: 0.4251 loss_db: 0.1014 2022/11/02 20:13:02 - mmengine - INFO - Epoch(train) [722][10/63] lr: 9.4546e-04 eta: 5:02:52 time: 0.8384 data_time: 0.2164 memory: 14901 loss: 1.1216 loss_prob: 0.5900 loss_thr: 0.4312 loss_db: 0.1004 2022/11/02 20:13:05 - mmengine - INFO - Epoch(train) [722][15/63] lr: 9.4546e-04 eta: 5:02:52 time: 0.6487 data_time: 0.0156 memory: 14901 loss: 1.0998 loss_prob: 0.5913 loss_thr: 0.4062 loss_db: 0.1023 2022/11/02 20:13:08 - mmengine - INFO - Epoch(train) [722][20/63] lr: 9.4546e-04 eta: 5:02:47 time: 0.6570 data_time: 0.0155 memory: 14901 loss: 1.0491 loss_prob: 0.5586 loss_thr: 0.3939 loss_db: 0.0965 2022/11/02 20:13:11 - mmengine - INFO - Epoch(train) [722][25/63] lr: 9.4546e-04 eta: 5:02:47 time: 0.6426 data_time: 0.0191 memory: 14901 loss: 1.0342 loss_prob: 0.5408 loss_thr: 0.3992 loss_db: 0.0943 2022/11/02 20:13:14 - mmengine - INFO - Epoch(train) [722][30/63] lr: 9.4546e-04 eta: 5:02:41 time: 0.5921 data_time: 0.0294 memory: 14901 loss: 0.9988 loss_prob: 0.5279 loss_thr: 0.3782 loss_db: 0.0927 2022/11/02 20:13:17 - mmengine - INFO - Epoch(train) [722][35/63] lr: 9.4546e-04 eta: 5:02:41 time: 0.5619 data_time: 0.0329 memory: 14901 loss: 1.0246 loss_prob: 0.5302 loss_thr: 0.4031 loss_db: 0.0913 2022/11/02 20:13:20 - mmengine - INFO - Epoch(train) [722][40/63] lr: 9.4546e-04 eta: 5:02:35 time: 0.5982 data_time: 0.0180 memory: 14901 loss: 1.0454 loss_prob: 0.5431 loss_thr: 0.4105 loss_db: 0.0917 2022/11/02 20:13:23 - mmengine - INFO - Epoch(train) [722][45/63] lr: 9.4546e-04 eta: 5:02:35 time: 0.6077 data_time: 0.0214 memory: 14901 loss: 1.0522 loss_prob: 0.5581 loss_thr: 0.3999 loss_db: 0.0942 2022/11/02 20:13:27 - mmengine - INFO - Epoch(train) [722][50/63] lr: 9.4546e-04 eta: 5:02:29 time: 0.6398 data_time: 0.0243 memory: 14901 loss: 1.1036 loss_prob: 0.5867 loss_thr: 0.4182 loss_db: 0.0987 2022/11/02 20:13:29 - mmengine - INFO - Epoch(train) [722][55/63] lr: 9.4546e-04 eta: 5:02:29 time: 0.6225 data_time: 0.0339 memory: 14901 loss: 1.1049 loss_prob: 0.5856 loss_thr: 0.4179 loss_db: 0.1013 2022/11/02 20:13:33 - mmengine - INFO - Epoch(train) [722][60/63] lr: 9.4546e-04 eta: 5:02:23 time: 0.5867 data_time: 0.0315 memory: 14901 loss: 1.0578 loss_prob: 0.5546 loss_thr: 0.4068 loss_db: 0.0963 2022/11/02 20:13:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:13:41 - mmengine - INFO - Epoch(train) [723][5/63] lr: 9.4368e-04 eta: 5:02:23 time: 0.9354 data_time: 0.2252 memory: 14901 loss: 1.0234 loss_prob: 0.5337 loss_thr: 0.3984 loss_db: 0.0914 2022/11/02 20:13:43 - mmengine - INFO - Epoch(train) [723][10/63] lr: 9.4368e-04 eta: 5:02:16 time: 0.9167 data_time: 0.2292 memory: 14901 loss: 1.0903 loss_prob: 0.5749 loss_thr: 0.4157 loss_db: 0.0997 2022/11/02 20:13:46 - mmengine - INFO - Epoch(train) [723][15/63] lr: 9.4368e-04 eta: 5:02:16 time: 0.5737 data_time: 0.0146 memory: 14901 loss: 1.0421 loss_prob: 0.5477 loss_thr: 0.4019 loss_db: 0.0924 2022/11/02 20:13:50 - mmengine - INFO - Epoch(train) [723][20/63] lr: 9.4368e-04 eta: 5:02:10 time: 0.6389 data_time: 0.0185 memory: 14901 loss: 1.0262 loss_prob: 0.5365 loss_thr: 0.3989 loss_db: 0.0909 2022/11/02 20:13:53 - mmengine - INFO - Epoch(train) [723][25/63] lr: 9.4368e-04 eta: 5:02:10 time: 0.6553 data_time: 0.0373 memory: 14901 loss: 1.1303 loss_prob: 0.5922 loss_thr: 0.4348 loss_db: 0.1033 2022/11/02 20:13:56 - mmengine - INFO - Epoch(train) [723][30/63] lr: 9.4368e-04 eta: 5:02:04 time: 0.5748 data_time: 0.0398 memory: 14901 loss: 1.1444 loss_prob: 0.5997 loss_thr: 0.4396 loss_db: 0.1051 2022/11/02 20:13:58 - mmengine - INFO - Epoch(train) [723][35/63] lr: 9.4368e-04 eta: 5:02:04 time: 0.5550 data_time: 0.0198 memory: 14901 loss: 1.1814 loss_prob: 0.6369 loss_thr: 0.4376 loss_db: 0.1068 2022/11/02 20:14:01 - mmengine - INFO - Epoch(train) [723][40/63] lr: 9.4368e-04 eta: 5:01:57 time: 0.5601 data_time: 0.0116 memory: 14901 loss: 1.2025 loss_prob: 0.6610 loss_thr: 0.4328 loss_db: 0.1087 2022/11/02 20:14:04 - mmengine - INFO - Epoch(train) [723][45/63] lr: 9.4368e-04 eta: 5:01:57 time: 0.6080 data_time: 0.0152 memory: 14901 loss: 1.3154 loss_prob: 0.7668 loss_thr: 0.4275 loss_db: 0.1212 2022/11/02 20:14:07 - mmengine - INFO - Epoch(train) [723][50/63] lr: 9.4368e-04 eta: 5:01:51 time: 0.6081 data_time: 0.0297 memory: 14901 loss: 1.2752 loss_prob: 0.7425 loss_thr: 0.4149 loss_db: 0.1178 2022/11/02 20:14:11 - mmengine - INFO - Epoch(train) [723][55/63] lr: 9.4368e-04 eta: 5:01:51 time: 0.6377 data_time: 0.0345 memory: 14901 loss: 1.0936 loss_prob: 0.5752 loss_thr: 0.4240 loss_db: 0.0943 2022/11/02 20:14:14 - mmengine - INFO - Epoch(train) [723][60/63] lr: 9.4368e-04 eta: 5:01:46 time: 0.6834 data_time: 0.0165 memory: 14901 loss: 1.2188 loss_prob: 0.6430 loss_thr: 0.4671 loss_db: 0.1088 2022/11/02 20:14:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:14:22 - mmengine - INFO - Epoch(train) [724][5/63] lr: 9.4190e-04 eta: 5:01:46 time: 0.9382 data_time: 0.2822 memory: 14901 loss: 1.1770 loss_prob: 0.6236 loss_thr: 0.4432 loss_db: 0.1102 2022/11/02 20:14:25 - mmengine - INFO - Epoch(train) [724][10/63] lr: 9.4190e-04 eta: 5:01:39 time: 0.9677 data_time: 0.2802 memory: 14901 loss: 1.1743 loss_prob: 0.6229 loss_thr: 0.4442 loss_db: 0.1073 2022/11/02 20:14:29 - mmengine - INFO - Epoch(train) [724][15/63] lr: 9.4190e-04 eta: 5:01:39 time: 0.6577 data_time: 0.0105 memory: 14901 loss: 1.1112 loss_prob: 0.5854 loss_thr: 0.4274 loss_db: 0.0984 2022/11/02 20:14:32 - mmengine - INFO - Epoch(train) [724][20/63] lr: 9.4190e-04 eta: 5:01:34 time: 0.6697 data_time: 0.0102 memory: 14901 loss: 1.1590 loss_prob: 0.6127 loss_thr: 0.4392 loss_db: 0.1072 2022/11/02 20:14:35 - mmengine - INFO - Epoch(train) [724][25/63] lr: 9.4190e-04 eta: 5:01:34 time: 0.5907 data_time: 0.0347 memory: 14901 loss: 1.2101 loss_prob: 0.6481 loss_thr: 0.4490 loss_db: 0.1130 2022/11/02 20:14:37 - mmengine - INFO - Epoch(train) [724][30/63] lr: 9.4190e-04 eta: 5:01:27 time: 0.5475 data_time: 0.0416 memory: 14901 loss: 1.1828 loss_prob: 0.6323 loss_thr: 0.4435 loss_db: 0.1070 2022/11/02 20:14:40 - mmengine - INFO - Epoch(train) [724][35/63] lr: 9.4190e-04 eta: 5:01:27 time: 0.5418 data_time: 0.0175 memory: 14901 loss: 1.1126 loss_prob: 0.5899 loss_thr: 0.4214 loss_db: 0.1013 2022/11/02 20:14:43 - mmengine - INFO - Epoch(train) [724][40/63] lr: 9.4190e-04 eta: 5:01:21 time: 0.5250 data_time: 0.0120 memory: 14901 loss: 1.0830 loss_prob: 0.5722 loss_thr: 0.4123 loss_db: 0.0985 2022/11/02 20:14:46 - mmengine - INFO - Epoch(train) [724][45/63] lr: 9.4190e-04 eta: 5:01:21 time: 0.5975 data_time: 0.0111 memory: 14901 loss: 1.1158 loss_prob: 0.5870 loss_thr: 0.4286 loss_db: 0.1003 2022/11/02 20:14:49 - mmengine - INFO - Epoch(train) [724][50/63] lr: 9.4190e-04 eta: 5:01:15 time: 0.6330 data_time: 0.0350 memory: 14901 loss: 1.0816 loss_prob: 0.5700 loss_thr: 0.4156 loss_db: 0.0960 2022/11/02 20:14:53 - mmengine - INFO - Epoch(train) [724][55/63] lr: 9.4190e-04 eta: 5:01:15 time: 0.6736 data_time: 0.0357 memory: 14901 loss: 1.0235 loss_prob: 0.5441 loss_thr: 0.3849 loss_db: 0.0944 2022/11/02 20:14:56 - mmengine - INFO - Epoch(train) [724][60/63] lr: 9.4190e-04 eta: 5:01:10 time: 0.6903 data_time: 0.0125 memory: 14901 loss: 0.9874 loss_prob: 0.5197 loss_thr: 0.3751 loss_db: 0.0925 2022/11/02 20:14:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:15:04 - mmengine - INFO - Epoch(train) [725][5/63] lr: 9.4011e-04 eta: 5:01:10 time: 0.9575 data_time: 0.2790 memory: 14901 loss: 1.1191 loss_prob: 0.5941 loss_thr: 0.4206 loss_db: 0.1045 2022/11/02 20:15:07 - mmengine - INFO - Epoch(train) [725][10/63] lr: 9.4011e-04 eta: 5:01:03 time: 0.9976 data_time: 0.2790 memory: 14901 loss: 1.0144 loss_prob: 0.5301 loss_thr: 0.3944 loss_db: 0.0900 2022/11/02 20:15:10 - mmengine - INFO - Epoch(train) [725][15/63] lr: 9.4011e-04 eta: 5:01:03 time: 0.5454 data_time: 0.0112 memory: 14901 loss: 1.0710 loss_prob: 0.5773 loss_thr: 0.3983 loss_db: 0.0954 2022/11/02 20:15:12 - mmengine - INFO - Epoch(train) [725][20/63] lr: 9.4011e-04 eta: 5:00:57 time: 0.5140 data_time: 0.0101 memory: 14901 loss: 1.1055 loss_prob: 0.5897 loss_thr: 0.4159 loss_db: 0.0999 2022/11/02 20:15:16 - mmengine - INFO - Epoch(train) [725][25/63] lr: 9.4011e-04 eta: 5:00:57 time: 0.5969 data_time: 0.0410 memory: 14901 loss: 0.9819 loss_prob: 0.5033 loss_thr: 0.3894 loss_db: 0.0893 2022/11/02 20:15:19 - mmengine - INFO - Epoch(train) [725][30/63] lr: 9.4011e-04 eta: 5:00:51 time: 0.6813 data_time: 0.0463 memory: 14901 loss: 1.0507 loss_prob: 0.5599 loss_thr: 0.3988 loss_db: 0.0920 2022/11/02 20:15:23 - mmengine - INFO - Epoch(train) [725][35/63] lr: 9.4011e-04 eta: 5:00:51 time: 0.6763 data_time: 0.0151 memory: 14901 loss: 1.1116 loss_prob: 0.5974 loss_thr: 0.4171 loss_db: 0.0972 2022/11/02 20:15:25 - mmengine - INFO - Epoch(train) [725][40/63] lr: 9.4011e-04 eta: 5:00:45 time: 0.6006 data_time: 0.0113 memory: 14901 loss: 1.1809 loss_prob: 0.6462 loss_thr: 0.4259 loss_db: 0.1087 2022/11/02 20:15:28 - mmengine - INFO - Epoch(train) [725][45/63] lr: 9.4011e-04 eta: 5:00:45 time: 0.5320 data_time: 0.0123 memory: 14901 loss: 1.2044 loss_prob: 0.6544 loss_thr: 0.4386 loss_db: 0.1114 2022/11/02 20:15:31 - mmengine - INFO - Epoch(train) [725][50/63] lr: 9.4011e-04 eta: 5:00:39 time: 0.5632 data_time: 0.0334 memory: 14901 loss: 1.1964 loss_prob: 0.6353 loss_thr: 0.4520 loss_db: 0.1091 2022/11/02 20:15:36 - mmengine - INFO - Epoch(train) [725][55/63] lr: 9.4011e-04 eta: 5:00:39 time: 0.7664 data_time: 0.0329 memory: 14901 loss: 1.2592 loss_prob: 0.6817 loss_thr: 0.4616 loss_db: 0.1159 2022/11/02 20:15:39 - mmengine - INFO - Epoch(train) [725][60/63] lr: 9.4011e-04 eta: 5:00:34 time: 0.7592 data_time: 0.0109 memory: 14901 loss: 1.3162 loss_prob: 0.7364 loss_thr: 0.4599 loss_db: 0.1199 2022/11/02 20:15:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:15:47 - mmengine - INFO - Epoch(train) [726][5/63] lr: 9.3833e-04 eta: 5:00:34 time: 0.9084 data_time: 0.2922 memory: 14901 loss: 1.2265 loss_prob: 0.6597 loss_thr: 0.4575 loss_db: 0.1093 2022/11/02 20:15:50 - mmengine - INFO - Epoch(train) [726][10/63] lr: 9.3833e-04 eta: 5:00:27 time: 0.9890 data_time: 0.2929 memory: 14901 loss: 1.1373 loss_prob: 0.5971 loss_thr: 0.4375 loss_db: 0.1028 2022/11/02 20:15:53 - mmengine - INFO - Epoch(train) [726][15/63] lr: 9.3833e-04 eta: 5:00:27 time: 0.5938 data_time: 0.0119 memory: 14901 loss: 1.1330 loss_prob: 0.6058 loss_thr: 0.4236 loss_db: 0.1037 2022/11/02 20:15:55 - mmengine - INFO - Epoch(train) [726][20/63] lr: 9.3833e-04 eta: 5:00:21 time: 0.5047 data_time: 0.0097 memory: 14901 loss: 1.2378 loss_prob: 0.6791 loss_thr: 0.4463 loss_db: 0.1124 2022/11/02 20:15:58 - mmengine - INFO - Epoch(train) [726][25/63] lr: 9.3833e-04 eta: 5:00:21 time: 0.5390 data_time: 0.0241 memory: 14901 loss: 1.2615 loss_prob: 0.6933 loss_thr: 0.4541 loss_db: 0.1141 2022/11/02 20:16:01 - mmengine - INFO - Epoch(train) [726][30/63] lr: 9.3833e-04 eta: 5:00:15 time: 0.6507 data_time: 0.0388 memory: 14901 loss: 1.2375 loss_prob: 0.6644 loss_thr: 0.4548 loss_db: 0.1183 2022/11/02 20:16:05 - mmengine - INFO - Epoch(train) [726][35/63] lr: 9.3833e-04 eta: 5:00:15 time: 0.6991 data_time: 0.0298 memory: 14901 loss: 1.2394 loss_prob: 0.6635 loss_thr: 0.4566 loss_db: 0.1193 2022/11/02 20:16:09 - mmengine - INFO - Epoch(train) [726][40/63] lr: 9.3833e-04 eta: 5:00:10 time: 0.7125 data_time: 0.0157 memory: 14901 loss: 1.1467 loss_prob: 0.6017 loss_thr: 0.4396 loss_db: 0.1054 2022/11/02 20:16:11 - mmengine - INFO - Epoch(train) [726][45/63] lr: 9.3833e-04 eta: 5:00:10 time: 0.6420 data_time: 0.0098 memory: 14901 loss: 1.0853 loss_prob: 0.5588 loss_thr: 0.4290 loss_db: 0.0975 2022/11/02 20:16:14 - mmengine - INFO - Epoch(train) [726][50/63] lr: 9.3833e-04 eta: 5:00:03 time: 0.5588 data_time: 0.0158 memory: 14901 loss: 1.0503 loss_prob: 0.5451 loss_thr: 0.4102 loss_db: 0.0950 2022/11/02 20:16:17 - mmengine - INFO - Epoch(train) [726][55/63] lr: 9.3833e-04 eta: 5:00:03 time: 0.5486 data_time: 0.0232 memory: 14901 loss: 1.0838 loss_prob: 0.5692 loss_thr: 0.4160 loss_db: 0.0987 2022/11/02 20:16:20 - mmengine - INFO - Epoch(train) [726][60/63] lr: 9.3833e-04 eta: 4:59:57 time: 0.5390 data_time: 0.0226 memory: 14901 loss: 1.0977 loss_prob: 0.5735 loss_thr: 0.4252 loss_db: 0.0990 2022/11/02 20:16:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:16:26 - mmengine - INFO - Epoch(train) [727][5/63] lr: 9.3655e-04 eta: 4:59:57 time: 0.7680 data_time: 0.2228 memory: 14901 loss: 1.1614 loss_prob: 0.6133 loss_thr: 0.4417 loss_db: 0.1065 2022/11/02 20:16:29 - mmengine - INFO - Epoch(train) [727][10/63] lr: 9.3655e-04 eta: 4:59:49 time: 0.8192 data_time: 0.2207 memory: 14901 loss: 1.1272 loss_prob: 0.5938 loss_thr: 0.4296 loss_db: 0.1038 2022/11/02 20:16:32 - mmengine - INFO - Epoch(train) [727][15/63] lr: 9.3655e-04 eta: 4:59:49 time: 0.5889 data_time: 0.0132 memory: 14901 loss: 1.0379 loss_prob: 0.5389 loss_thr: 0.4051 loss_db: 0.0939 2022/11/02 20:16:34 - mmengine - INFO - Epoch(train) [727][20/63] lr: 9.3655e-04 eta: 4:59:43 time: 0.5363 data_time: 0.0125 memory: 14901 loss: 0.9776 loss_prob: 0.5019 loss_thr: 0.3891 loss_db: 0.0866 2022/11/02 20:16:37 - mmengine - INFO - Epoch(train) [727][25/63] lr: 9.3655e-04 eta: 4:59:43 time: 0.5184 data_time: 0.0168 memory: 14901 loss: 1.0512 loss_prob: 0.5497 loss_thr: 0.4062 loss_db: 0.0953 2022/11/02 20:16:40 - mmengine - INFO - Epoch(train) [727][30/63] lr: 9.3655e-04 eta: 4:59:36 time: 0.5530 data_time: 0.0359 memory: 14901 loss: 1.1017 loss_prob: 0.5763 loss_thr: 0.4260 loss_db: 0.0994 2022/11/02 20:16:44 - mmengine - INFO - Epoch(train) [727][35/63] lr: 9.3655e-04 eta: 4:59:36 time: 0.6425 data_time: 0.0343 memory: 14901 loss: 1.0673 loss_prob: 0.5539 loss_thr: 0.4177 loss_db: 0.0957 2022/11/02 20:16:47 - mmengine - INFO - Epoch(train) [727][40/63] lr: 9.3655e-04 eta: 4:59:31 time: 0.6674 data_time: 0.0119 memory: 14901 loss: 1.0302 loss_prob: 0.5374 loss_thr: 0.3984 loss_db: 0.0945 2022/11/02 20:16:50 - mmengine - INFO - Epoch(train) [727][45/63] lr: 9.3655e-04 eta: 4:59:31 time: 0.6169 data_time: 0.0090 memory: 14901 loss: 0.9928 loss_prob: 0.5142 loss_thr: 0.3883 loss_db: 0.0903 2022/11/02 20:16:53 - mmengine - INFO - Epoch(train) [727][50/63] lr: 9.3655e-04 eta: 4:59:25 time: 0.6170 data_time: 0.0167 memory: 14901 loss: 1.0629 loss_prob: 0.5550 loss_thr: 0.4129 loss_db: 0.0950 2022/11/02 20:16:56 - mmengine - INFO - Epoch(train) [727][55/63] lr: 9.3655e-04 eta: 4:59:25 time: 0.6508 data_time: 0.0332 memory: 14901 loss: 1.0714 loss_prob: 0.5607 loss_thr: 0.4133 loss_db: 0.0974 2022/11/02 20:16:59 - mmengine - INFO - Epoch(train) [727][60/63] lr: 9.3655e-04 eta: 4:59:19 time: 0.6263 data_time: 0.0316 memory: 14901 loss: 0.9956 loss_prob: 0.5148 loss_thr: 0.3898 loss_db: 0.0910 2022/11/02 20:17:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:17:06 - mmengine - INFO - Epoch(train) [728][5/63] lr: 9.3477e-04 eta: 4:59:19 time: 0.8151 data_time: 0.2806 memory: 14901 loss: 1.0989 loss_prob: 0.5766 loss_thr: 0.4234 loss_db: 0.0989 2022/11/02 20:17:09 - mmengine - INFO - Epoch(train) [728][10/63] lr: 9.3477e-04 eta: 4:59:11 time: 0.8279 data_time: 0.2874 memory: 14901 loss: 1.1323 loss_prob: 0.5958 loss_thr: 0.4318 loss_db: 0.1047 2022/11/02 20:17:12 - mmengine - INFO - Epoch(train) [728][15/63] lr: 9.3477e-04 eta: 4:59:11 time: 0.6386 data_time: 0.0167 memory: 14901 loss: 1.1461 loss_prob: 0.6062 loss_thr: 0.4336 loss_db: 0.1063 2022/11/02 20:17:15 - mmengine - INFO - Epoch(train) [728][20/63] lr: 9.3477e-04 eta: 4:59:06 time: 0.6571 data_time: 0.0104 memory: 14901 loss: 1.0790 loss_prob: 0.5672 loss_thr: 0.4128 loss_db: 0.0990 2022/11/02 20:17:19 - mmengine - INFO - Epoch(train) [728][25/63] lr: 9.3477e-04 eta: 4:59:06 time: 0.6215 data_time: 0.0298 memory: 14901 loss: 1.0366 loss_prob: 0.5374 loss_thr: 0.4065 loss_db: 0.0927 2022/11/02 20:17:21 - mmengine - INFO - Epoch(train) [728][30/63] lr: 9.3477e-04 eta: 4:59:00 time: 0.6089 data_time: 0.0326 memory: 14901 loss: 1.0725 loss_prob: 0.5615 loss_thr: 0.4152 loss_db: 0.0958 2022/11/02 20:17:26 - mmengine - INFO - Epoch(train) [728][35/63] lr: 9.3477e-04 eta: 4:59:00 time: 0.7022 data_time: 0.0230 memory: 14901 loss: 1.0145 loss_prob: 0.5261 loss_thr: 0.3978 loss_db: 0.0907 2022/11/02 20:17:29 - mmengine - INFO - Epoch(train) [728][40/63] lr: 9.3477e-04 eta: 4:58:55 time: 0.7414 data_time: 0.0227 memory: 14901 loss: 0.9981 loss_prob: 0.5206 loss_thr: 0.3879 loss_db: 0.0897 2022/11/02 20:17:32 - mmengine - INFO - Epoch(train) [728][45/63] lr: 9.3477e-04 eta: 4:58:55 time: 0.6153 data_time: 0.0145 memory: 14901 loss: 1.1013 loss_prob: 0.5975 loss_thr: 0.4020 loss_db: 0.1018 2022/11/02 20:17:35 - mmengine - INFO - Epoch(train) [728][50/63] lr: 9.3477e-04 eta: 4:58:49 time: 0.6215 data_time: 0.0239 memory: 14901 loss: 1.1054 loss_prob: 0.6050 loss_thr: 0.3989 loss_db: 0.1015 2022/11/02 20:17:38 - mmengine - INFO - Epoch(train) [728][55/63] lr: 9.3477e-04 eta: 4:58:49 time: 0.5971 data_time: 0.0266 memory: 14901 loss: 1.0520 loss_prob: 0.5596 loss_thr: 0.3981 loss_db: 0.0943 2022/11/02 20:17:41 - mmengine - INFO - Epoch(train) [728][60/63] lr: 9.3477e-04 eta: 4:58:43 time: 0.6139 data_time: 0.0176 memory: 14901 loss: 1.0935 loss_prob: 0.5771 loss_thr: 0.4179 loss_db: 0.0985 2022/11/02 20:17:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:17:49 - mmengine - INFO - Epoch(train) [729][5/63] lr: 9.3299e-04 eta: 4:58:43 time: 0.8993 data_time: 0.2512 memory: 14901 loss: 1.0907 loss_prob: 0.5845 loss_thr: 0.4053 loss_db: 0.1009 2022/11/02 20:17:52 - mmengine - INFO - Epoch(train) [729][10/63] lr: 9.3299e-04 eta: 4:58:36 time: 0.9015 data_time: 0.2501 memory: 14901 loss: 1.0637 loss_prob: 0.5692 loss_thr: 0.3987 loss_db: 0.0958 2022/11/02 20:17:54 - mmengine - INFO - Epoch(train) [729][15/63] lr: 9.3299e-04 eta: 4:58:36 time: 0.5602 data_time: 0.0127 memory: 14901 loss: 1.1182 loss_prob: 0.5944 loss_thr: 0.4248 loss_db: 0.0991 2022/11/02 20:17:58 - mmengine - INFO - Epoch(train) [729][20/63] lr: 9.3299e-04 eta: 4:58:30 time: 0.6663 data_time: 0.0119 memory: 14901 loss: 1.0933 loss_prob: 0.5714 loss_thr: 0.4233 loss_db: 0.0986 2022/11/02 20:18:02 - mmengine - INFO - Epoch(train) [729][25/63] lr: 9.3299e-04 eta: 4:58:30 time: 0.7335 data_time: 0.0202 memory: 14901 loss: 1.0179 loss_prob: 0.5322 loss_thr: 0.3908 loss_db: 0.0950 2022/11/02 20:18:06 - mmengine - INFO - Epoch(train) [729][30/63] lr: 9.3299e-04 eta: 4:58:25 time: 0.7217 data_time: 0.0446 memory: 14901 loss: 1.0267 loss_prob: 0.5358 loss_thr: 0.3957 loss_db: 0.0951 2022/11/02 20:18:09 - mmengine - INFO - Epoch(train) [729][35/63] lr: 9.3299e-04 eta: 4:58:25 time: 0.7711 data_time: 0.0362 memory: 14901 loss: 1.0778 loss_prob: 0.5656 loss_thr: 0.4137 loss_db: 0.0986 2022/11/02 20:18:13 - mmengine - INFO - Epoch(train) [729][40/63] lr: 9.3299e-04 eta: 4:58:20 time: 0.7518 data_time: 0.0115 memory: 14901 loss: 1.0715 loss_prob: 0.5673 loss_thr: 0.4064 loss_db: 0.0979 2022/11/02 20:18:16 - mmengine - INFO - Epoch(train) [729][45/63] lr: 9.3299e-04 eta: 4:58:20 time: 0.6904 data_time: 0.0115 memory: 14901 loss: 1.0688 loss_prob: 0.5705 loss_thr: 0.3991 loss_db: 0.0993 2022/11/02 20:18:19 - mmengine - INFO - Epoch(train) [729][50/63] lr: 9.3299e-04 eta: 4:58:14 time: 0.6246 data_time: 0.0189 memory: 14901 loss: 1.1262 loss_prob: 0.6033 loss_thr: 0.4203 loss_db: 0.1027 2022/11/02 20:18:22 - mmengine - INFO - Epoch(train) [729][55/63] lr: 9.3299e-04 eta: 4:58:14 time: 0.6063 data_time: 0.0309 memory: 14901 loss: 1.1103 loss_prob: 0.5886 loss_thr: 0.4214 loss_db: 0.1004 2022/11/02 20:18:25 - mmengine - INFO - Epoch(train) [729][60/63] lr: 9.3299e-04 eta: 4:58:08 time: 0.5852 data_time: 0.0241 memory: 14901 loss: 1.0485 loss_prob: 0.5502 loss_thr: 0.4027 loss_db: 0.0955 2022/11/02 20:18:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:18:32 - mmengine - INFO - Epoch(train) [730][5/63] lr: 9.3120e-04 eta: 4:58:08 time: 0.8077 data_time: 0.1949 memory: 14901 loss: 1.1592 loss_prob: 0.6150 loss_thr: 0.4382 loss_db: 0.1060 2022/11/02 20:18:35 - mmengine - INFO - Epoch(train) [730][10/63] lr: 9.3120e-04 eta: 4:58:00 time: 0.8663 data_time: 0.2143 memory: 14901 loss: 1.1214 loss_prob: 0.5985 loss_thr: 0.4191 loss_db: 0.1039 2022/11/02 20:18:38 - mmengine - INFO - Epoch(train) [730][15/63] lr: 9.3120e-04 eta: 4:58:00 time: 0.5793 data_time: 0.0343 memory: 14901 loss: 1.1142 loss_prob: 0.5896 loss_thr: 0.4205 loss_db: 0.1040 2022/11/02 20:18:41 - mmengine - INFO - Epoch(train) [730][20/63] lr: 9.3120e-04 eta: 4:57:54 time: 0.5283 data_time: 0.0154 memory: 14901 loss: 1.0357 loss_prob: 0.5402 loss_thr: 0.3996 loss_db: 0.0959 2022/11/02 20:18:43 - mmengine - INFO - Epoch(train) [730][25/63] lr: 9.3120e-04 eta: 4:57:54 time: 0.5142 data_time: 0.0174 memory: 14901 loss: 1.0731 loss_prob: 0.5536 loss_thr: 0.4228 loss_db: 0.0967 2022/11/02 20:18:47 - mmengine - INFO - Epoch(train) [730][30/63] lr: 9.3120e-04 eta: 4:57:48 time: 0.6826 data_time: 0.0519 memory: 14901 loss: 1.0687 loss_prob: 0.5496 loss_thr: 0.4241 loss_db: 0.0950 2022/11/02 20:18:50 - mmengine - INFO - Epoch(train) [730][35/63] lr: 9.3120e-04 eta: 4:57:48 time: 0.6543 data_time: 0.0463 memory: 14901 loss: 0.9937 loss_prob: 0.5182 loss_thr: 0.3855 loss_db: 0.0901 2022/11/02 20:18:53 - mmengine - INFO - Epoch(train) [730][40/63] lr: 9.3120e-04 eta: 4:57:42 time: 0.5386 data_time: 0.0143 memory: 14901 loss: 1.0348 loss_prob: 0.5409 loss_thr: 0.3995 loss_db: 0.0944 2022/11/02 20:18:56 - mmengine - INFO - Epoch(train) [730][45/63] lr: 9.3120e-04 eta: 4:57:42 time: 0.6147 data_time: 0.0181 memory: 14901 loss: 1.1088 loss_prob: 0.5764 loss_thr: 0.4330 loss_db: 0.0993 2022/11/02 20:18:59 - mmengine - INFO - Epoch(train) [730][50/63] lr: 9.3120e-04 eta: 4:57:36 time: 0.6738 data_time: 0.0194 memory: 14901 loss: 1.0875 loss_prob: 0.5669 loss_thr: 0.4222 loss_db: 0.0984 2022/11/02 20:19:02 - mmengine - INFO - Epoch(train) [730][55/63] lr: 9.3120e-04 eta: 4:57:36 time: 0.6419 data_time: 0.0278 memory: 14901 loss: 1.0351 loss_prob: 0.5388 loss_thr: 0.4027 loss_db: 0.0936 2022/11/02 20:19:05 - mmengine - INFO - Epoch(train) [730][60/63] lr: 9.3120e-04 eta: 4:57:30 time: 0.5583 data_time: 0.0225 memory: 14901 loss: 1.0586 loss_prob: 0.5601 loss_thr: 0.4016 loss_db: 0.0970 2022/11/02 20:19:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:19:12 - mmengine - INFO - Epoch(train) [731][5/63] lr: 9.2942e-04 eta: 4:57:30 time: 0.8228 data_time: 0.2561 memory: 14901 loss: 1.0921 loss_prob: 0.5730 loss_thr: 0.4197 loss_db: 0.0994 2022/11/02 20:19:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:19:15 - mmengine - INFO - Epoch(train) [731][10/63] lr: 9.2942e-04 eta: 4:57:23 time: 0.9062 data_time: 0.2588 memory: 14901 loss: 1.0274 loss_prob: 0.5340 loss_thr: 0.4009 loss_db: 0.0925 2022/11/02 20:19:20 - mmengine - INFO - Epoch(train) [731][15/63] lr: 9.2942e-04 eta: 4:57:23 time: 0.7388 data_time: 0.0128 memory: 14901 loss: 1.1136 loss_prob: 0.5955 loss_thr: 0.4158 loss_db: 0.1022 2022/11/02 20:19:23 - mmengine - INFO - Epoch(train) [731][20/63] lr: 9.2942e-04 eta: 4:57:18 time: 0.7327 data_time: 0.0111 memory: 14901 loss: 1.1358 loss_prob: 0.6057 loss_thr: 0.4262 loss_db: 0.1039 2022/11/02 20:19:26 - mmengine - INFO - Epoch(train) [731][25/63] lr: 9.2942e-04 eta: 4:57:18 time: 0.6455 data_time: 0.0285 memory: 14901 loss: 1.0956 loss_prob: 0.5887 loss_thr: 0.4052 loss_db: 0.1018 2022/11/02 20:19:30 - mmengine - INFO - Epoch(train) [731][30/63] lr: 9.2942e-04 eta: 4:57:13 time: 0.7750 data_time: 0.0484 memory: 14901 loss: 1.0602 loss_prob: 0.5657 loss_thr: 0.3950 loss_db: 0.0995 2022/11/02 20:19:33 - mmengine - INFO - Epoch(train) [731][35/63] lr: 9.2942e-04 eta: 4:57:13 time: 0.7382 data_time: 0.0330 memory: 14901 loss: 1.0131 loss_prob: 0.5231 loss_thr: 0.3984 loss_db: 0.0916 2022/11/02 20:19:36 - mmengine - INFO - Epoch(train) [731][40/63] lr: 9.2942e-04 eta: 4:57:07 time: 0.5560 data_time: 0.0165 memory: 14901 loss: 1.0335 loss_prob: 0.5416 loss_thr: 0.3983 loss_db: 0.0936 2022/11/02 20:19:39 - mmengine - INFO - Epoch(train) [731][45/63] lr: 9.2942e-04 eta: 4:57:07 time: 0.5315 data_time: 0.0129 memory: 14901 loss: 1.0398 loss_prob: 0.5463 loss_thr: 0.3985 loss_db: 0.0950 2022/11/02 20:19:42 - mmengine - INFO - Epoch(train) [731][50/63] lr: 9.2942e-04 eta: 4:57:00 time: 0.5542 data_time: 0.0211 memory: 14901 loss: 1.0492 loss_prob: 0.5479 loss_thr: 0.4068 loss_db: 0.0944 2022/11/02 20:19:44 - mmengine - INFO - Epoch(train) [731][55/63] lr: 9.2942e-04 eta: 4:57:00 time: 0.5493 data_time: 0.0301 memory: 14901 loss: 1.0935 loss_prob: 0.5765 loss_thr: 0.4189 loss_db: 0.0980 2022/11/02 20:19:47 - mmengine - INFO - Epoch(train) [731][60/63] lr: 9.2942e-04 eta: 4:56:54 time: 0.5812 data_time: 0.0197 memory: 14901 loss: 1.0993 loss_prob: 0.5821 loss_thr: 0.4175 loss_db: 0.0997 2022/11/02 20:19:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:19:55 - mmengine - INFO - Epoch(train) [732][5/63] lr: 9.2764e-04 eta: 4:56:54 time: 0.8466 data_time: 0.2051 memory: 14901 loss: 1.1783 loss_prob: 0.6454 loss_thr: 0.4251 loss_db: 0.1078 2022/11/02 20:19:58 - mmengine - INFO - Epoch(train) [732][10/63] lr: 9.2764e-04 eta: 4:56:47 time: 0.9470 data_time: 0.2081 memory: 14901 loss: 1.2900 loss_prob: 0.7045 loss_thr: 0.4699 loss_db: 0.1156 2022/11/02 20:20:01 - mmengine - INFO - Epoch(train) [732][15/63] lr: 9.2764e-04 eta: 4:56:47 time: 0.6681 data_time: 0.0121 memory: 14901 loss: 1.1917 loss_prob: 0.6257 loss_thr: 0.4601 loss_db: 0.1059 2022/11/02 20:20:04 - mmengine - INFO - Epoch(train) [732][20/63] lr: 9.2764e-04 eta: 4:56:41 time: 0.5631 data_time: 0.0162 memory: 14901 loss: 1.1341 loss_prob: 0.5944 loss_thr: 0.4370 loss_db: 0.1027 2022/11/02 20:20:07 - mmengine - INFO - Epoch(train) [732][25/63] lr: 9.2764e-04 eta: 4:56:41 time: 0.5372 data_time: 0.0241 memory: 14901 loss: 1.1011 loss_prob: 0.5713 loss_thr: 0.4301 loss_db: 0.0996 2022/11/02 20:20:11 - mmengine - INFO - Epoch(train) [732][30/63] lr: 9.2764e-04 eta: 4:56:36 time: 0.6979 data_time: 0.0389 memory: 14901 loss: 1.0750 loss_prob: 0.5593 loss_thr: 0.4194 loss_db: 0.0963 2022/11/02 20:20:14 - mmengine - INFO - Epoch(train) [732][35/63] lr: 9.2764e-04 eta: 4:56:36 time: 0.6838 data_time: 0.0282 memory: 14901 loss: 1.0785 loss_prob: 0.5646 loss_thr: 0.4186 loss_db: 0.0953 2022/11/02 20:20:16 - mmengine - INFO - Epoch(train) [732][40/63] lr: 9.2764e-04 eta: 4:56:29 time: 0.5540 data_time: 0.0130 memory: 14901 loss: 1.0458 loss_prob: 0.5442 loss_thr: 0.4081 loss_db: 0.0936 2022/11/02 20:20:20 - mmengine - INFO - Epoch(train) [732][45/63] lr: 9.2764e-04 eta: 4:56:29 time: 0.6252 data_time: 0.0165 memory: 14901 loss: 1.0382 loss_prob: 0.5407 loss_thr: 0.4032 loss_db: 0.0943 2022/11/02 20:20:22 - mmengine - INFO - Epoch(train) [732][50/63] lr: 9.2764e-04 eta: 4:56:23 time: 0.6123 data_time: 0.0204 memory: 14901 loss: 1.0242 loss_prob: 0.5421 loss_thr: 0.3903 loss_db: 0.0917 2022/11/02 20:20:25 - mmengine - INFO - Epoch(train) [732][55/63] lr: 9.2764e-04 eta: 4:56:23 time: 0.5393 data_time: 0.0327 memory: 14901 loss: 1.0154 loss_prob: 0.5367 loss_thr: 0.3875 loss_db: 0.0912 2022/11/02 20:20:28 - mmengine - INFO - Epoch(train) [732][60/63] lr: 9.2764e-04 eta: 4:56:17 time: 0.5510 data_time: 0.0247 memory: 14901 loss: 1.0354 loss_prob: 0.5290 loss_thr: 0.4131 loss_db: 0.0933 2022/11/02 20:20:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:20:35 - mmengine - INFO - Epoch(train) [733][5/63] lr: 9.2585e-04 eta: 4:56:17 time: 0.7963 data_time: 0.2734 memory: 14901 loss: 1.0239 loss_prob: 0.5317 loss_thr: 0.3982 loss_db: 0.0939 2022/11/02 20:20:37 - mmengine - INFO - Epoch(train) [733][10/63] lr: 9.2585e-04 eta: 4:56:09 time: 0.7994 data_time: 0.2707 memory: 14901 loss: 1.0213 loss_prob: 0.5267 loss_thr: 0.4018 loss_db: 0.0928 2022/11/02 20:20:40 - mmengine - INFO - Epoch(train) [733][15/63] lr: 9.2585e-04 eta: 4:56:09 time: 0.5490 data_time: 0.0075 memory: 14901 loss: 1.0262 loss_prob: 0.5347 loss_thr: 0.3984 loss_db: 0.0931 2022/11/02 20:20:43 - mmengine - INFO - Epoch(train) [733][20/63] lr: 9.2585e-04 eta: 4:56:03 time: 0.5155 data_time: 0.0124 memory: 14901 loss: 1.1052 loss_prob: 0.5853 loss_thr: 0.4177 loss_db: 0.1021 2022/11/02 20:20:46 - mmengine - INFO - Epoch(train) [733][25/63] lr: 9.2585e-04 eta: 4:56:03 time: 0.5442 data_time: 0.0275 memory: 14901 loss: 1.1626 loss_prob: 0.6169 loss_thr: 0.4393 loss_db: 0.1063 2022/11/02 20:20:49 - mmengine - INFO - Epoch(train) [733][30/63] lr: 9.2585e-04 eta: 4:55:57 time: 0.6458 data_time: 0.0674 memory: 14901 loss: 1.0976 loss_prob: 0.5779 loss_thr: 0.4207 loss_db: 0.0990 2022/11/02 20:20:52 - mmengine - INFO - Epoch(train) [733][35/63] lr: 9.2585e-04 eta: 4:55:57 time: 0.6042 data_time: 0.0528 memory: 14901 loss: 1.0208 loss_prob: 0.5261 loss_thr: 0.4041 loss_db: 0.0906 2022/11/02 20:20:56 - mmengine - INFO - Epoch(train) [733][40/63] lr: 9.2585e-04 eta: 4:55:51 time: 0.6523 data_time: 0.0106 memory: 14901 loss: 0.9975 loss_prob: 0.5106 loss_thr: 0.3967 loss_db: 0.0901 2022/11/02 20:20:59 - mmengine - INFO - Epoch(train) [733][45/63] lr: 9.2585e-04 eta: 4:55:51 time: 0.7242 data_time: 0.0138 memory: 14901 loss: 0.9831 loss_prob: 0.5051 loss_thr: 0.3879 loss_db: 0.0901 2022/11/02 20:21:02 - mmengine - INFO - Epoch(train) [733][50/63] lr: 9.2585e-04 eta: 4:55:46 time: 0.6929 data_time: 0.0299 memory: 14901 loss: 0.9578 loss_prob: 0.4921 loss_thr: 0.3787 loss_db: 0.0870 2022/11/02 20:21:06 - mmengine - INFO - Epoch(train) [733][55/63] lr: 9.2585e-04 eta: 4:55:46 time: 0.6696 data_time: 0.0278 memory: 14901 loss: 1.0343 loss_prob: 0.5464 loss_thr: 0.3967 loss_db: 0.0912 2022/11/02 20:21:09 - mmengine - INFO - Epoch(train) [733][60/63] lr: 9.2585e-04 eta: 4:55:40 time: 0.6564 data_time: 0.0115 memory: 14901 loss: 1.1162 loss_prob: 0.6003 loss_thr: 0.4159 loss_db: 0.1000 2022/11/02 20:21:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:21:17 - mmengine - INFO - Epoch(train) [734][5/63] lr: 9.2407e-04 eta: 4:55:40 time: 0.9036 data_time: 0.2679 memory: 14901 loss: 1.1673 loss_prob: 0.6432 loss_thr: 0.4183 loss_db: 0.1058 2022/11/02 20:21:20 - mmengine - INFO - Epoch(train) [734][10/63] lr: 9.2407e-04 eta: 4:55:33 time: 0.9481 data_time: 0.2682 memory: 14901 loss: 1.1499 loss_prob: 0.6267 loss_thr: 0.4167 loss_db: 0.1066 2022/11/02 20:21:24 - mmengine - INFO - Epoch(train) [734][15/63] lr: 9.2407e-04 eta: 4:55:33 time: 0.7127 data_time: 0.0119 memory: 14901 loss: 1.0908 loss_prob: 0.5758 loss_thr: 0.4130 loss_db: 0.1020 2022/11/02 20:21:27 - mmengine - INFO - Epoch(train) [734][20/63] lr: 9.2407e-04 eta: 4:55:27 time: 0.6536 data_time: 0.0131 memory: 14901 loss: 1.0592 loss_prob: 0.5597 loss_thr: 0.4034 loss_db: 0.0961 2022/11/02 20:21:30 - mmengine - INFO - Epoch(train) [734][25/63] lr: 9.2407e-04 eta: 4:55:27 time: 0.6170 data_time: 0.0395 memory: 14901 loss: 1.0779 loss_prob: 0.5698 loss_thr: 0.4106 loss_db: 0.0976 2022/11/02 20:21:34 - mmengine - INFO - Epoch(train) [734][30/63] lr: 9.2407e-04 eta: 4:55:22 time: 0.7220 data_time: 0.0376 memory: 14901 loss: 1.1036 loss_prob: 0.5837 loss_thr: 0.4191 loss_db: 0.1008 2022/11/02 20:21:37 - mmengine - INFO - Epoch(train) [734][35/63] lr: 9.2407e-04 eta: 4:55:22 time: 0.7408 data_time: 0.0142 memory: 14901 loss: 1.1851 loss_prob: 0.6611 loss_thr: 0.4180 loss_db: 0.1060 2022/11/02 20:21:43 - mmengine - INFO - Epoch(train) [734][40/63] lr: 9.2407e-04 eta: 4:55:18 time: 0.8535 data_time: 0.0168 memory: 14901 loss: 1.2386 loss_prob: 0.6923 loss_thr: 0.4347 loss_db: 0.1116 2022/11/02 20:21:46 - mmengine - INFO - Epoch(train) [734][45/63] lr: 9.2407e-04 eta: 4:55:18 time: 0.8600 data_time: 0.0135 memory: 14901 loss: 1.1879 loss_prob: 0.6387 loss_thr: 0.4385 loss_db: 0.1107 2022/11/02 20:21:49 - mmengine - INFO - Epoch(train) [734][50/63] lr: 9.2407e-04 eta: 4:55:12 time: 0.6680 data_time: 0.0275 memory: 14901 loss: 1.1320 loss_prob: 0.5993 loss_thr: 0.4289 loss_db: 0.1039 2022/11/02 20:21:53 - mmengine - INFO - Epoch(train) [734][55/63] lr: 9.2407e-04 eta: 4:55:12 time: 0.6507 data_time: 0.0280 memory: 14901 loss: 1.0633 loss_prob: 0.5527 loss_thr: 0.4158 loss_db: 0.0949 2022/11/02 20:21:55 - mmengine - INFO - Epoch(train) [734][60/63] lr: 9.2407e-04 eta: 4:55:06 time: 0.5965 data_time: 0.0154 memory: 14901 loss: 1.1403 loss_prob: 0.6253 loss_thr: 0.4074 loss_db: 0.1076 2022/11/02 20:21:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:22:02 - mmengine - INFO - Epoch(train) [735][5/63] lr: 9.2228e-04 eta: 4:55:06 time: 0.8265 data_time: 0.2648 memory: 14901 loss: 1.1292 loss_prob: 0.6193 loss_thr: 0.4034 loss_db: 0.1066 2022/11/02 20:22:05 - mmengine - INFO - Epoch(train) [735][10/63] lr: 9.2228e-04 eta: 4:54:59 time: 0.8756 data_time: 0.2637 memory: 14901 loss: 1.0693 loss_prob: 0.5702 loss_thr: 0.4005 loss_db: 0.0987 2022/11/02 20:22:08 - mmengine - INFO - Epoch(train) [735][15/63] lr: 9.2228e-04 eta: 4:54:59 time: 0.5819 data_time: 0.0167 memory: 14901 loss: 1.0999 loss_prob: 0.5881 loss_thr: 0.4103 loss_db: 0.1015 2022/11/02 20:22:11 - mmengine - INFO - Epoch(train) [735][20/63] lr: 9.2228e-04 eta: 4:54:53 time: 0.6070 data_time: 0.0155 memory: 14901 loss: 1.1491 loss_prob: 0.6111 loss_thr: 0.4310 loss_db: 0.1070 2022/11/02 20:22:16 - mmengine - INFO - Epoch(train) [735][25/63] lr: 9.2228e-04 eta: 4:54:53 time: 0.7744 data_time: 0.0330 memory: 14901 loss: 1.0110 loss_prob: 0.5238 loss_thr: 0.3942 loss_db: 0.0930 2022/11/02 20:22:19 - mmengine - INFO - Epoch(train) [735][30/63] lr: 9.2228e-04 eta: 4:54:48 time: 0.7661 data_time: 0.0419 memory: 14901 loss: 0.9890 loss_prob: 0.5085 loss_thr: 0.3911 loss_db: 0.0894 2022/11/02 20:22:22 - mmengine - INFO - Epoch(train) [735][35/63] lr: 9.2228e-04 eta: 4:54:48 time: 0.6201 data_time: 0.0204 memory: 14901 loss: 1.1103 loss_prob: 0.5783 loss_thr: 0.4337 loss_db: 0.0982 2022/11/02 20:22:25 - mmengine - INFO - Epoch(train) [735][40/63] lr: 9.2228e-04 eta: 4:54:42 time: 0.5683 data_time: 0.0133 memory: 14901 loss: 1.0791 loss_prob: 0.5647 loss_thr: 0.4173 loss_db: 0.0972 2022/11/02 20:22:28 - mmengine - INFO - Epoch(train) [735][45/63] lr: 9.2228e-04 eta: 4:54:42 time: 0.5668 data_time: 0.0131 memory: 14901 loss: 1.0212 loss_prob: 0.5277 loss_thr: 0.4009 loss_db: 0.0926 2022/11/02 20:22:31 - mmengine - INFO - Epoch(train) [735][50/63] lr: 9.2228e-04 eta: 4:54:36 time: 0.6500 data_time: 0.0245 memory: 14901 loss: 1.0040 loss_prob: 0.5252 loss_thr: 0.3878 loss_db: 0.0910 2022/11/02 20:22:34 - mmengine - INFO - Epoch(train) [735][55/63] lr: 9.2228e-04 eta: 4:54:36 time: 0.6253 data_time: 0.0325 memory: 14901 loss: 1.0363 loss_prob: 0.5507 loss_thr: 0.3898 loss_db: 0.0958 2022/11/02 20:22:37 - mmengine - INFO - Epoch(train) [735][60/63] lr: 9.2228e-04 eta: 4:54:30 time: 0.6271 data_time: 0.0190 memory: 14901 loss: 0.9893 loss_prob: 0.5140 loss_thr: 0.3863 loss_db: 0.0891 2022/11/02 20:22:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:22:45 - mmengine - INFO - Epoch(train) [736][5/63] lr: 9.2050e-04 eta: 4:54:30 time: 0.9021 data_time: 0.2109 memory: 14901 loss: 0.9752 loss_prob: 0.5138 loss_thr: 0.3728 loss_db: 0.0887 2022/11/02 20:22:48 - mmengine - INFO - Epoch(train) [736][10/63] lr: 9.2050e-04 eta: 4:54:23 time: 0.8960 data_time: 0.2241 memory: 14901 loss: 1.0764 loss_prob: 0.5666 loss_thr: 0.4130 loss_db: 0.0968 2022/11/02 20:22:51 - mmengine - INFO - Epoch(train) [736][15/63] lr: 9.2050e-04 eta: 4:54:23 time: 0.6353 data_time: 0.0249 memory: 14901 loss: 1.0818 loss_prob: 0.5715 loss_thr: 0.4120 loss_db: 0.0983 2022/11/02 20:22:54 - mmengine - INFO - Epoch(train) [736][20/63] lr: 9.2050e-04 eta: 4:54:17 time: 0.6173 data_time: 0.0148 memory: 14901 loss: 1.1229 loss_prob: 0.6037 loss_thr: 0.4172 loss_db: 0.1020 2022/11/02 20:22:59 - mmengine - INFO - Epoch(train) [736][25/63] lr: 9.2050e-04 eta: 4:54:17 time: 0.7171 data_time: 0.0169 memory: 14901 loss: 1.0478 loss_prob: 0.5433 loss_thr: 0.4122 loss_db: 0.0923 2022/11/02 20:23:01 - mmengine - INFO - Epoch(train) [736][30/63] lr: 9.2050e-04 eta: 4:54:11 time: 0.6881 data_time: 0.0416 memory: 14901 loss: 0.9813 loss_prob: 0.4971 loss_thr: 0.3980 loss_db: 0.0862 2022/11/02 20:23:04 - mmengine - INFO - Epoch(train) [736][35/63] lr: 9.2050e-04 eta: 4:54:11 time: 0.5825 data_time: 0.0397 memory: 14901 loss: 1.0510 loss_prob: 0.5499 loss_thr: 0.4062 loss_db: 0.0950 2022/11/02 20:23:07 - mmengine - INFO - Epoch(train) [736][40/63] lr: 9.2050e-04 eta: 4:54:05 time: 0.5747 data_time: 0.0089 memory: 14901 loss: 1.1136 loss_prob: 0.5863 loss_thr: 0.4261 loss_db: 0.1012 2022/11/02 20:23:10 - mmengine - INFO - Epoch(train) [736][45/63] lr: 9.2050e-04 eta: 4:54:05 time: 0.5716 data_time: 0.0128 memory: 14901 loss: 1.0635 loss_prob: 0.5529 loss_thr: 0.4145 loss_db: 0.0961 2022/11/02 20:23:13 - mmengine - INFO - Epoch(train) [736][50/63] lr: 9.2050e-04 eta: 4:53:59 time: 0.5780 data_time: 0.0311 memory: 14901 loss: 0.9794 loss_prob: 0.5015 loss_thr: 0.3896 loss_db: 0.0883 2022/11/02 20:23:17 - mmengine - INFO - Epoch(train) [736][55/63] lr: 9.2050e-04 eta: 4:53:59 time: 0.6529 data_time: 0.0335 memory: 14901 loss: 0.9943 loss_prob: 0.5083 loss_thr: 0.3968 loss_db: 0.0892 2022/11/02 20:23:21 - mmengine - INFO - Epoch(train) [736][60/63] lr: 9.2050e-04 eta: 4:53:54 time: 0.7761 data_time: 0.0165 memory: 14901 loss: 1.0452 loss_prob: 0.5368 loss_thr: 0.4157 loss_db: 0.0927 2022/11/02 20:23:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:23:27 - mmengine - INFO - Epoch(train) [737][5/63] lr: 9.1871e-04 eta: 4:53:54 time: 0.8242 data_time: 0.2718 memory: 14901 loss: 1.0506 loss_prob: 0.5360 loss_thr: 0.4207 loss_db: 0.0938 2022/11/02 20:23:30 - mmengine - INFO - Epoch(train) [737][10/63] lr: 9.1871e-04 eta: 4:53:46 time: 0.8080 data_time: 0.2721 memory: 14901 loss: 1.0705 loss_prob: 0.5492 loss_thr: 0.4265 loss_db: 0.0949 2022/11/02 20:23:33 - mmengine - INFO - Epoch(train) [737][15/63] lr: 9.1871e-04 eta: 4:53:46 time: 0.5538 data_time: 0.0120 memory: 14901 loss: 1.2120 loss_prob: 0.6751 loss_thr: 0.4341 loss_db: 0.1028 2022/11/02 20:23:36 - mmengine - INFO - Epoch(train) [737][20/63] lr: 9.1871e-04 eta: 4:53:40 time: 0.6172 data_time: 0.0115 memory: 14901 loss: 1.1699 loss_prob: 0.6584 loss_thr: 0.4115 loss_db: 0.1000 2022/11/02 20:23:40 - mmengine - INFO - Epoch(train) [737][25/63] lr: 9.1871e-04 eta: 4:53:40 time: 0.6496 data_time: 0.0383 memory: 14901 loss: 1.0516 loss_prob: 0.5520 loss_thr: 0.4038 loss_db: 0.0958 2022/11/02 20:23:42 - mmengine - INFO - Epoch(train) [737][30/63] lr: 9.1871e-04 eta: 4:53:34 time: 0.6159 data_time: 0.0421 memory: 14901 loss: 1.0252 loss_prob: 0.5370 loss_thr: 0.3941 loss_db: 0.0941 2022/11/02 20:23:45 - mmengine - INFO - Epoch(train) [737][35/63] lr: 9.1871e-04 eta: 4:53:34 time: 0.5768 data_time: 0.0158 memory: 14901 loss: 0.9915 loss_prob: 0.5176 loss_thr: 0.3840 loss_db: 0.0900 2022/11/02 20:23:49 - mmengine - INFO - Epoch(train) [737][40/63] lr: 9.1871e-04 eta: 4:53:28 time: 0.6170 data_time: 0.0130 memory: 14901 loss: 1.0098 loss_prob: 0.5257 loss_thr: 0.3927 loss_db: 0.0914 2022/11/02 20:23:52 - mmengine - INFO - Epoch(train) [737][45/63] lr: 9.1871e-04 eta: 4:53:28 time: 0.6730 data_time: 0.0105 memory: 14901 loss: 1.0979 loss_prob: 0.5914 loss_thr: 0.4065 loss_db: 0.0999 2022/11/02 20:23:55 - mmengine - INFO - Epoch(train) [737][50/63] lr: 9.1871e-04 eta: 4:53:23 time: 0.6822 data_time: 0.0236 memory: 14901 loss: 1.1247 loss_prob: 0.6063 loss_thr: 0.4158 loss_db: 0.1026 2022/11/02 20:23:58 - mmengine - INFO - Epoch(train) [737][55/63] lr: 9.1871e-04 eta: 4:53:23 time: 0.6463 data_time: 0.0256 memory: 14901 loss: 1.0437 loss_prob: 0.5383 loss_thr: 0.4102 loss_db: 0.0951 2022/11/02 20:24:02 - mmengine - INFO - Epoch(train) [737][60/63] lr: 9.1871e-04 eta: 4:53:17 time: 0.6223 data_time: 0.0106 memory: 14901 loss: 1.0081 loss_prob: 0.5186 loss_thr: 0.3987 loss_db: 0.0907 2022/11/02 20:24:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:24:10 - mmengine - INFO - Epoch(train) [738][5/63] lr: 9.1693e-04 eta: 4:53:17 time: 0.9642 data_time: 0.2427 memory: 14901 loss: 1.1020 loss_prob: 0.5824 loss_thr: 0.4208 loss_db: 0.0988 2022/11/02 20:24:14 - mmengine - INFO - Epoch(train) [738][10/63] lr: 9.1693e-04 eta: 4:53:11 time: 1.0394 data_time: 0.2438 memory: 14901 loss: 1.0727 loss_prob: 0.5575 loss_thr: 0.4178 loss_db: 0.0973 2022/11/02 20:24:16 - mmengine - INFO - Epoch(train) [738][15/63] lr: 9.1693e-04 eta: 4:53:11 time: 0.6007 data_time: 0.0125 memory: 14901 loss: 1.0066 loss_prob: 0.5256 loss_thr: 0.3905 loss_db: 0.0905 2022/11/02 20:24:19 - mmengine - INFO - Epoch(train) [738][20/63] lr: 9.1693e-04 eta: 4:53:04 time: 0.5231 data_time: 0.0118 memory: 14901 loss: 1.0203 loss_prob: 0.5312 loss_thr: 0.3977 loss_db: 0.0913 2022/11/02 20:24:23 - mmengine - INFO - Epoch(train) [738][25/63] lr: 9.1693e-04 eta: 4:53:04 time: 0.6502 data_time: 0.0195 memory: 14901 loss: 1.0988 loss_prob: 0.5701 loss_thr: 0.4285 loss_db: 0.1002 2022/11/02 20:24:26 - mmengine - INFO - Epoch(train) [738][30/63] lr: 9.1693e-04 eta: 4:52:59 time: 0.6790 data_time: 0.0506 memory: 14901 loss: 1.0796 loss_prob: 0.5628 loss_thr: 0.4181 loss_db: 0.0987 2022/11/02 20:24:28 - mmengine - INFO - Epoch(train) [738][35/63] lr: 9.1693e-04 eta: 4:52:59 time: 0.5805 data_time: 0.0442 memory: 14901 loss: 1.0686 loss_prob: 0.5608 loss_thr: 0.4114 loss_db: 0.0964 2022/11/02 20:24:32 - mmengine - INFO - Epoch(train) [738][40/63] lr: 9.1693e-04 eta: 4:52:53 time: 0.6791 data_time: 0.0124 memory: 14901 loss: 1.0374 loss_prob: 0.5335 loss_thr: 0.4117 loss_db: 0.0922 2022/11/02 20:24:36 - mmengine - INFO - Epoch(train) [738][45/63] lr: 9.1693e-04 eta: 4:52:53 time: 0.7561 data_time: 0.0090 memory: 14901 loss: 0.9642 loss_prob: 0.4836 loss_thr: 0.3963 loss_db: 0.0842 2022/11/02 20:24:39 - mmengine - INFO - Epoch(train) [738][50/63] lr: 9.1693e-04 eta: 4:52:47 time: 0.6500 data_time: 0.0242 memory: 14901 loss: 0.9900 loss_prob: 0.5122 loss_thr: 0.3902 loss_db: 0.0876 2022/11/02 20:24:43 - mmengine - INFO - Epoch(train) [738][55/63] lr: 9.1693e-04 eta: 4:52:47 time: 0.6764 data_time: 0.0277 memory: 14901 loss: 0.9962 loss_prob: 0.5248 loss_thr: 0.3806 loss_db: 0.0908 2022/11/02 20:24:45 - mmengine - INFO - Epoch(train) [738][60/63] lr: 9.1693e-04 eta: 4:52:42 time: 0.6552 data_time: 0.0138 memory: 14901 loss: 1.0272 loss_prob: 0.5416 loss_thr: 0.3913 loss_db: 0.0943 2022/11/02 20:24:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:24:53 - mmengine - INFO - Epoch(train) [739][5/63] lr: 9.1514e-04 eta: 4:52:42 time: 0.8822 data_time: 0.2756 memory: 14901 loss: 0.9294 loss_prob: 0.4818 loss_thr: 0.3633 loss_db: 0.0843 2022/11/02 20:24:57 - mmengine - INFO - Epoch(train) [739][10/63] lr: 9.1514e-04 eta: 4:52:35 time: 0.9789 data_time: 0.2770 memory: 14901 loss: 0.9188 loss_prob: 0.4766 loss_thr: 0.3596 loss_db: 0.0825 2022/11/02 20:24:59 - mmengine - INFO - Epoch(train) [739][15/63] lr: 9.1514e-04 eta: 4:52:35 time: 0.6199 data_time: 0.0162 memory: 14901 loss: 1.1250 loss_prob: 0.6170 loss_thr: 0.4082 loss_db: 0.0997 2022/11/02 20:25:03 - mmengine - INFO - Epoch(train) [739][20/63] lr: 9.1514e-04 eta: 4:52:30 time: 0.6902 data_time: 0.0140 memory: 14901 loss: 1.1814 loss_prob: 0.6520 loss_thr: 0.4221 loss_db: 0.1073 2022/11/02 20:25:07 - mmengine - INFO - Epoch(train) [739][25/63] lr: 9.1514e-04 eta: 4:52:30 time: 0.7391 data_time: 0.0292 memory: 14901 loss: 1.0456 loss_prob: 0.5569 loss_thr: 0.3910 loss_db: 0.0976 2022/11/02 20:25:10 - mmengine - INFO - Epoch(train) [739][30/63] lr: 9.1514e-04 eta: 4:52:24 time: 0.6691 data_time: 0.0440 memory: 14901 loss: 1.0473 loss_prob: 0.5514 loss_thr: 0.4022 loss_db: 0.0936 2022/11/02 20:25:13 - mmengine - INFO - Epoch(train) [739][35/63] lr: 9.1514e-04 eta: 4:52:24 time: 0.6046 data_time: 0.0219 memory: 14901 loss: 1.0413 loss_prob: 0.5428 loss_thr: 0.4058 loss_db: 0.0927 2022/11/02 20:25:16 - mmengine - INFO - Epoch(train) [739][40/63] lr: 9.1514e-04 eta: 4:52:18 time: 0.5962 data_time: 0.0114 memory: 14901 loss: 1.0269 loss_prob: 0.5356 loss_thr: 0.3974 loss_db: 0.0939 2022/11/02 20:25:19 - mmengine - INFO - Epoch(train) [739][45/63] lr: 9.1514e-04 eta: 4:52:18 time: 0.5774 data_time: 0.0141 memory: 14901 loss: 1.1054 loss_prob: 0.5808 loss_thr: 0.4269 loss_db: 0.0977 2022/11/02 20:25:21 - mmengine - INFO - Epoch(train) [739][50/63] lr: 9.1514e-04 eta: 4:52:11 time: 0.5311 data_time: 0.0262 memory: 14901 loss: 1.1152 loss_prob: 0.5833 loss_thr: 0.4343 loss_db: 0.0975 2022/11/02 20:25:24 - mmengine - INFO - Epoch(train) [739][55/63] lr: 9.1514e-04 eta: 4:52:11 time: 0.5338 data_time: 0.0275 memory: 14901 loss: 1.0734 loss_prob: 0.5551 loss_thr: 0.4227 loss_db: 0.0956 2022/11/02 20:25:27 - mmengine - INFO - Epoch(train) [739][60/63] lr: 9.1514e-04 eta: 4:52:05 time: 0.6085 data_time: 0.0145 memory: 14901 loss: 1.0815 loss_prob: 0.5645 loss_thr: 0.4207 loss_db: 0.0963 2022/11/02 20:25:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:25:35 - mmengine - INFO - Epoch(train) [740][5/63] lr: 9.1336e-04 eta: 4:52:05 time: 0.8699 data_time: 0.2759 memory: 14901 loss: 1.1681 loss_prob: 0.6249 loss_thr: 0.4362 loss_db: 0.1069 2022/11/02 20:25:37 - mmengine - INFO - Epoch(train) [740][10/63] lr: 9.1336e-04 eta: 4:51:58 time: 0.8073 data_time: 0.2722 memory: 14901 loss: 1.1586 loss_prob: 0.6174 loss_thr: 0.4340 loss_db: 0.1072 2022/11/02 20:25:41 - mmengine - INFO - Epoch(train) [740][15/63] lr: 9.1336e-04 eta: 4:51:58 time: 0.6045 data_time: 0.0081 memory: 14901 loss: 1.0822 loss_prob: 0.5709 loss_thr: 0.4110 loss_db: 0.1003 2022/11/02 20:25:45 - mmengine - INFO - Epoch(train) [740][20/63] lr: 9.1336e-04 eta: 4:51:53 time: 0.7497 data_time: 0.0147 memory: 14901 loss: 1.0026 loss_prob: 0.5251 loss_thr: 0.3855 loss_db: 0.0921 2022/11/02 20:25:48 - mmengine - INFO - Epoch(train) [740][25/63] lr: 9.1336e-04 eta: 4:51:53 time: 0.7132 data_time: 0.0585 memory: 14901 loss: 0.9491 loss_prob: 0.4927 loss_thr: 0.3713 loss_db: 0.0851 2022/11/02 20:25:51 - mmengine - INFO - Epoch(train) [740][30/63] lr: 9.1336e-04 eta: 4:51:46 time: 0.5922 data_time: 0.0539 memory: 14901 loss: 0.9870 loss_prob: 0.5100 loss_thr: 0.3902 loss_db: 0.0868 2022/11/02 20:25:54 - mmengine - INFO - Epoch(train) [740][35/63] lr: 9.1336e-04 eta: 4:51:46 time: 0.5810 data_time: 0.0101 memory: 14901 loss: 1.0226 loss_prob: 0.5269 loss_thr: 0.4037 loss_db: 0.0920 2022/11/02 20:25:56 - mmengine - INFO - Epoch(train) [740][40/63] lr: 9.1336e-04 eta: 4:51:40 time: 0.5818 data_time: 0.0095 memory: 14901 loss: 1.0974 loss_prob: 0.5728 loss_thr: 0.4242 loss_db: 0.1004 2022/11/02 20:26:01 - mmengine - INFO - Epoch(train) [740][45/63] lr: 9.1336e-04 eta: 4:51:40 time: 0.7111 data_time: 0.0117 memory: 14901 loss: 1.1263 loss_prob: 0.5950 loss_thr: 0.4293 loss_db: 0.1021 2022/11/02 20:26:04 - mmengine - INFO - Epoch(train) [740][50/63] lr: 9.1336e-04 eta: 4:51:35 time: 0.7403 data_time: 0.0333 memory: 14901 loss: 1.0726 loss_prob: 0.5673 loss_thr: 0.4091 loss_db: 0.0961 2022/11/02 20:26:07 - mmengine - INFO - Epoch(train) [740][55/63] lr: 9.1336e-04 eta: 4:51:35 time: 0.6582 data_time: 0.0322 memory: 14901 loss: 1.0189 loss_prob: 0.5381 loss_thr: 0.3888 loss_db: 0.0920 2022/11/02 20:26:10 - mmengine - INFO - Epoch(train) [740][60/63] lr: 9.1336e-04 eta: 4:51:29 time: 0.5953 data_time: 0.0106 memory: 14901 loss: 1.0394 loss_prob: 0.5495 loss_thr: 0.3958 loss_db: 0.0940 2022/11/02 20:26:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:26:11 - mmengine - INFO - Saving checkpoint at 740 epochs 2022/11/02 20:26:15 - mmengine - INFO - Epoch(val) [740][5/500] eta: 4:51:29 time: 0.0452 data_time: 0.0059 memory: 14901 2022/11/02 20:26:15 - mmengine - INFO - Epoch(val) [740][10/500] eta: 0:00:23 time: 0.0479 data_time: 0.0056 memory: 1008 2022/11/02 20:26:16 - mmengine - INFO - Epoch(val) [740][15/500] eta: 0:00:23 time: 0.0401 data_time: 0.0023 memory: 1008 2022/11/02 20:26:16 - mmengine - INFO - Epoch(val) [740][20/500] eta: 0:00:18 time: 0.0381 data_time: 0.0026 memory: 1008 2022/11/02 20:26:16 - mmengine - INFO - Epoch(val) [740][25/500] eta: 0:00:18 time: 0.0397 data_time: 0.0029 memory: 1008 2022/11/02 20:26:16 - mmengine - INFO - Epoch(val) [740][30/500] eta: 0:00:19 time: 0.0424 data_time: 0.0030 memory: 1008 2022/11/02 20:26:16 - mmengine - INFO - Epoch(val) [740][35/500] eta: 0:00:19 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/02 20:26:17 - mmengine - INFO - Epoch(val) [740][40/500] eta: 0:00:20 time: 0.0444 data_time: 0.0028 memory: 1008 2022/11/02 20:26:17 - mmengine - INFO - Epoch(val) [740][45/500] eta: 0:00:20 time: 0.0464 data_time: 0.0029 memory: 1008 2022/11/02 20:26:17 - mmengine - INFO - Epoch(val) [740][50/500] eta: 0:00:20 time: 0.0466 data_time: 0.0032 memory: 1008 2022/11/02 20:26:17 - mmengine - INFO - Epoch(val) [740][55/500] eta: 0:00:20 time: 0.0473 data_time: 0.0032 memory: 1008 2022/11/02 20:26:17 - mmengine - INFO - Epoch(val) [740][60/500] eta: 0:00:18 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 20:26:18 - mmengine - INFO - Epoch(val) [740][65/500] eta: 0:00:18 time: 0.0424 data_time: 0.0027 memory: 1008 2022/11/02 20:26:18 - mmengine - INFO - Epoch(val) [740][70/500] eta: 0:00:19 time: 0.0457 data_time: 0.0031 memory: 1008 2022/11/02 20:26:18 - mmengine - INFO - Epoch(val) [740][75/500] eta: 0:00:19 time: 0.0417 data_time: 0.0031 memory: 1008 2022/11/02 20:26:18 - mmengine - INFO - Epoch(val) [740][80/500] eta: 0:00:15 time: 0.0360 data_time: 0.0026 memory: 1008 2022/11/02 20:26:18 - mmengine - INFO - Epoch(val) [740][85/500] eta: 0:00:15 time: 0.0338 data_time: 0.0024 memory: 1008 2022/11/02 20:26:19 - mmengine - INFO - Epoch(val) [740][90/500] eta: 0:00:17 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 20:26:19 - mmengine - INFO - Epoch(val) [740][95/500] eta: 0:00:17 time: 0.0482 data_time: 0.0025 memory: 1008 2022/11/02 20:26:19 - mmengine - INFO - Epoch(val) [740][100/500] eta: 0:00:17 time: 0.0429 data_time: 0.0024 memory: 1008 2022/11/02 20:26:19 - mmengine - INFO - Epoch(val) [740][105/500] eta: 0:00:17 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/02 20:26:20 - mmengine - INFO - Epoch(val) [740][110/500] eta: 0:00:15 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/02 20:26:20 - mmengine - INFO - Epoch(val) [740][115/500] eta: 0:00:15 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 20:26:20 - mmengine - INFO - Epoch(val) [740][120/500] eta: 0:00:17 time: 0.0451 data_time: 0.0028 memory: 1008 2022/11/02 20:26:20 - mmengine - INFO - Epoch(val) [740][125/500] eta: 0:00:17 time: 0.0422 data_time: 0.0029 memory: 1008 2022/11/02 20:26:20 - mmengine - INFO - Epoch(val) [740][130/500] eta: 0:00:15 time: 0.0412 data_time: 0.0035 memory: 1008 2022/11/02 20:26:21 - mmengine - INFO - Epoch(val) [740][135/500] eta: 0:00:15 time: 0.0428 data_time: 0.0037 memory: 1008 2022/11/02 20:26:21 - mmengine - INFO - Epoch(val) [740][140/500] eta: 0:00:15 time: 0.0439 data_time: 0.0036 memory: 1008 2022/11/02 20:26:21 - mmengine - INFO - Epoch(val) [740][145/500] eta: 0:00:15 time: 0.0498 data_time: 0.0037 memory: 1008 2022/11/02 20:26:21 - mmengine - INFO - Epoch(val) [740][150/500] eta: 0:00:17 time: 0.0494 data_time: 0.0034 memory: 1008 2022/11/02 20:26:22 - mmengine - INFO - Epoch(val) [740][155/500] eta: 0:00:17 time: 0.0527 data_time: 0.0032 memory: 1008 2022/11/02 20:26:22 - mmengine - INFO - Epoch(val) [740][160/500] eta: 0:00:18 time: 0.0531 data_time: 0.0032 memory: 1008 2022/11/02 20:26:22 - mmengine - INFO - Epoch(val) [740][165/500] eta: 0:00:18 time: 0.0440 data_time: 0.0032 memory: 1008 2022/11/02 20:26:22 - mmengine - INFO - Epoch(val) [740][170/500] eta: 0:00:16 time: 0.0494 data_time: 0.0038 memory: 1008 2022/11/02 20:26:23 - mmengine - INFO - Epoch(val) [740][175/500] eta: 0:00:16 time: 0.0521 data_time: 0.0041 memory: 1008 2022/11/02 20:26:23 - mmengine - INFO - Epoch(val) [740][180/500] eta: 0:00:16 time: 0.0514 data_time: 0.0041 memory: 1008 2022/11/02 20:26:23 - mmengine - INFO - Epoch(val) [740][185/500] eta: 0:00:16 time: 0.0586 data_time: 0.0045 memory: 1008 2022/11/02 20:26:23 - mmengine - INFO - Epoch(val) [740][190/500] eta: 0:00:16 time: 0.0543 data_time: 0.0040 memory: 1008 2022/11/02 20:26:24 - mmengine - INFO - Epoch(val) [740][195/500] eta: 0:00:16 time: 0.0455 data_time: 0.0031 memory: 1008 2022/11/02 20:26:24 - mmengine - INFO - Epoch(val) [740][200/500] eta: 0:00:14 time: 0.0494 data_time: 0.0029 memory: 1008 2022/11/02 20:26:24 - mmengine - INFO - Epoch(val) [740][205/500] eta: 0:00:14 time: 0.0483 data_time: 0.0030 memory: 1008 2022/11/02 20:26:24 - mmengine - INFO - Epoch(val) [740][210/500] eta: 0:00:12 time: 0.0443 data_time: 0.0035 memory: 1008 2022/11/02 20:26:25 - mmengine - INFO - Epoch(val) [740][215/500] eta: 0:00:12 time: 0.0460 data_time: 0.0035 memory: 1008 2022/11/02 20:26:25 - mmengine - INFO - Epoch(val) [740][220/500] eta: 0:00:13 time: 0.0466 data_time: 0.0032 memory: 1008 2022/11/02 20:26:25 - mmengine - INFO - Epoch(val) [740][225/500] eta: 0:00:13 time: 0.0472 data_time: 0.0030 memory: 1008 2022/11/02 20:26:25 - mmengine - INFO - Epoch(val) [740][230/500] eta: 0:00:11 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/02 20:26:26 - mmengine - INFO - Epoch(val) [740][235/500] eta: 0:00:11 time: 0.0463 data_time: 0.0039 memory: 1008 2022/11/02 20:26:26 - mmengine - INFO - Epoch(val) [740][240/500] eta: 0:00:12 time: 0.0492 data_time: 0.0044 memory: 1008 2022/11/02 20:26:26 - mmengine - INFO - Epoch(val) [740][245/500] eta: 0:00:12 time: 0.0416 data_time: 0.0033 memory: 1008 2022/11/02 20:26:26 - mmengine - INFO - Epoch(val) [740][250/500] eta: 0:00:10 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 20:26:26 - mmengine - INFO - Epoch(val) [740][255/500] eta: 0:00:10 time: 0.0437 data_time: 0.0030 memory: 1008 2022/11/02 20:26:27 - mmengine - INFO - Epoch(val) [740][260/500] eta: 0:00:10 time: 0.0418 data_time: 0.0031 memory: 1008 2022/11/02 20:26:27 - mmengine - INFO - Epoch(val) [740][265/500] eta: 0:00:10 time: 0.0443 data_time: 0.0033 memory: 1008 2022/11/02 20:26:27 - mmengine - INFO - Epoch(val) [740][270/500] eta: 0:00:10 time: 0.0435 data_time: 0.0033 memory: 1008 2022/11/02 20:26:27 - mmengine - INFO - Epoch(val) [740][275/500] eta: 0:00:10 time: 0.0406 data_time: 0.0029 memory: 1008 2022/11/02 20:26:28 - mmengine - INFO - Epoch(val) [740][280/500] eta: 0:00:10 time: 0.0463 data_time: 0.0035 memory: 1008 2022/11/02 20:26:28 - mmengine - INFO - Epoch(val) [740][285/500] eta: 0:00:10 time: 0.0475 data_time: 0.0036 memory: 1008 2022/11/02 20:26:28 - mmengine - INFO - Epoch(val) [740][290/500] eta: 0:00:10 time: 0.0483 data_time: 0.0034 memory: 1008 2022/11/02 20:26:28 - mmengine - INFO - Epoch(val) [740][295/500] eta: 0:00:10 time: 0.0497 data_time: 0.0034 memory: 1008 2022/11/02 20:26:28 - mmengine - INFO - Epoch(val) [740][300/500] eta: 0:00:08 time: 0.0441 data_time: 0.0029 memory: 1008 2022/11/02 20:26:29 - mmengine - INFO - Epoch(val) [740][305/500] eta: 0:00:08 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 20:26:29 - mmengine - INFO - Epoch(val) [740][310/500] eta: 0:00:07 time: 0.0401 data_time: 0.0034 memory: 1008 2022/11/02 20:26:29 - mmengine - INFO - Epoch(val) [740][315/500] eta: 0:00:07 time: 0.0429 data_time: 0.0034 memory: 1008 2022/11/02 20:26:29 - mmengine - INFO - Epoch(val) [740][320/500] eta: 0:00:07 time: 0.0432 data_time: 0.0030 memory: 1008 2022/11/02 20:26:30 - mmengine - INFO - Epoch(val) [740][325/500] eta: 0:00:07 time: 0.0584 data_time: 0.0029 memory: 1008 2022/11/02 20:26:30 - mmengine - INFO - Epoch(val) [740][330/500] eta: 0:00:09 time: 0.0584 data_time: 0.0031 memory: 1008 2022/11/02 20:26:30 - mmengine - INFO - Epoch(val) [740][335/500] eta: 0:00:09 time: 0.0381 data_time: 0.0031 memory: 1008 2022/11/02 20:26:30 - mmengine - INFO - Epoch(val) [740][340/500] eta: 0:00:09 time: 0.0571 data_time: 0.0034 memory: 1008 2022/11/02 20:26:31 - mmengine - INFO - Epoch(val) [740][345/500] eta: 0:00:09 time: 0.0591 data_time: 0.0034 memory: 1008 2022/11/02 20:26:31 - mmengine - INFO - Epoch(val) [740][350/500] eta: 0:00:06 time: 0.0455 data_time: 0.0030 memory: 1008 2022/11/02 20:26:31 - mmengine - INFO - Epoch(val) [740][355/500] eta: 0:00:06 time: 0.0441 data_time: 0.0030 memory: 1008 2022/11/02 20:26:31 - mmengine - INFO - Epoch(val) [740][360/500] eta: 0:00:05 time: 0.0400 data_time: 0.0031 memory: 1008 2022/11/02 20:26:31 - mmengine - INFO - Epoch(val) [740][365/500] eta: 0:00:05 time: 0.0429 data_time: 0.0034 memory: 1008 2022/11/02 20:26:32 - mmengine - INFO - Epoch(val) [740][370/500] eta: 0:00:05 time: 0.0394 data_time: 0.0030 memory: 1008 2022/11/02 20:26:32 - mmengine - INFO - Epoch(val) [740][375/500] eta: 0:00:05 time: 0.0366 data_time: 0.0027 memory: 1008 2022/11/02 20:26:32 - mmengine - INFO - Epoch(val) [740][380/500] eta: 0:00:05 time: 0.0420 data_time: 0.0036 memory: 1008 2022/11/02 20:26:32 - mmengine - INFO - Epoch(val) [740][385/500] eta: 0:00:05 time: 0.0445 data_time: 0.0038 memory: 1008 2022/11/02 20:26:33 - mmengine - INFO - Epoch(val) [740][390/500] eta: 0:00:04 time: 0.0428 data_time: 0.0029 memory: 1008 2022/11/02 20:26:33 - mmengine - INFO - Epoch(val) [740][395/500] eta: 0:00:04 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/02 20:26:33 - mmengine - INFO - Epoch(val) [740][400/500] eta: 0:00:03 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/02 20:26:33 - mmengine - INFO - Epoch(val) [740][405/500] eta: 0:00:03 time: 0.0405 data_time: 0.0029 memory: 1008 2022/11/02 20:26:33 - mmengine - INFO - Epoch(val) [740][410/500] eta: 0:00:03 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/02 20:26:34 - mmengine - INFO - Epoch(val) [740][415/500] eta: 0:00:03 time: 0.0444 data_time: 0.0028 memory: 1008 2022/11/02 20:26:34 - mmengine - INFO - Epoch(val) [740][420/500] eta: 0:00:03 time: 0.0385 data_time: 0.0027 memory: 1008 2022/11/02 20:26:34 - mmengine - INFO - Epoch(val) [740][425/500] eta: 0:00:03 time: 0.0385 data_time: 0.0026 memory: 1008 2022/11/02 20:26:34 - mmengine - INFO - Epoch(val) [740][430/500] eta: 0:00:03 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/02 20:26:34 - mmengine - INFO - Epoch(val) [740][435/500] eta: 0:00:03 time: 0.0412 data_time: 0.0027 memory: 1008 2022/11/02 20:26:35 - mmengine - INFO - Epoch(val) [740][440/500] eta: 0:00:02 time: 0.0404 data_time: 0.0025 memory: 1008 2022/11/02 20:26:35 - mmengine - INFO - Epoch(val) [740][445/500] eta: 0:00:02 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 20:26:35 - mmengine - INFO - Epoch(val) [740][450/500] eta: 0:00:02 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 20:26:35 - mmengine - INFO - Epoch(val) [740][455/500] eta: 0:00:02 time: 0.0414 data_time: 0.0026 memory: 1008 2022/11/02 20:26:35 - mmengine - INFO - Epoch(val) [740][460/500] eta: 0:00:01 time: 0.0377 data_time: 0.0026 memory: 1008 2022/11/02 20:26:36 - mmengine - INFO - Epoch(val) [740][465/500] eta: 0:00:01 time: 0.0352 data_time: 0.0027 memory: 1008 2022/11/02 20:26:36 - mmengine - INFO - Epoch(val) [740][470/500] eta: 0:00:01 time: 0.0374 data_time: 0.0028 memory: 1008 2022/11/02 20:26:36 - mmengine - INFO - Epoch(val) [740][475/500] eta: 0:00:01 time: 0.0378 data_time: 0.0029 memory: 1008 2022/11/02 20:26:36 - mmengine - INFO - Epoch(val) [740][480/500] eta: 0:00:00 time: 0.0410 data_time: 0.0029 memory: 1008 2022/11/02 20:26:36 - mmengine - INFO - Epoch(val) [740][485/500] eta: 0:00:00 time: 0.0409 data_time: 0.0029 memory: 1008 2022/11/02 20:26:37 - mmengine - INFO - Epoch(val) [740][490/500] eta: 0:00:00 time: 0.0430 data_time: 0.0033 memory: 1008 2022/11/02 20:26:37 - mmengine - INFO - Epoch(val) [740][495/500] eta: 0:00:00 time: 0.0470 data_time: 0.0033 memory: 1008 2022/11/02 20:26:37 - mmengine - INFO - Epoch(val) [740][500/500] eta: 0:00:00 time: 0.0417 data_time: 0.0030 memory: 1008 2022/11/02 20:26:37 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8310, precision: 0.7389, hmean: 0.7822 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8310, precision: 0.7936, hmean: 0.8119 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8310, precision: 0.8250, hmean: 0.8280 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8276, precision: 0.8514, hmean: 0.8394 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8069, precision: 0.8775, hmean: 0.8407 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6591, precision: 0.9263, hmean: 0.7702 2022/11/02 20:26:37 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0852, precision: 0.9568, hmean: 0.1565 2022/11/02 20:26:37 - mmengine - INFO - Epoch(val) [740][500/500] icdar/precision: 0.8775 icdar/recall: 0.8069 icdar/hmean: 0.8407 2022/11/02 20:26:44 - mmengine - INFO - Epoch(train) [741][5/63] lr: 9.1157e-04 eta: 0:00:00 time: 0.9525 data_time: 0.2659 memory: 14901 loss: 1.1919 loss_prob: 0.6449 loss_thr: 0.4386 loss_db: 0.1083 2022/11/02 20:26:47 - mmengine - INFO - Epoch(train) [741][10/63] lr: 9.1157e-04 eta: 4:51:22 time: 0.9797 data_time: 0.2733 memory: 14901 loss: 1.1231 loss_prob: 0.5988 loss_thr: 0.4213 loss_db: 0.1031 2022/11/02 20:26:50 - mmengine - INFO - Epoch(train) [741][15/63] lr: 9.1157e-04 eta: 4:51:22 time: 0.6169 data_time: 0.0175 memory: 14901 loss: 1.0984 loss_prob: 0.5907 loss_thr: 0.4060 loss_db: 0.1016 2022/11/02 20:26:54 - mmengine - INFO - Epoch(train) [741][20/63] lr: 9.1157e-04 eta: 4:51:17 time: 0.6772 data_time: 0.0115 memory: 14901 loss: 1.1057 loss_prob: 0.5925 loss_thr: 0.4128 loss_db: 0.1003 2022/11/02 20:26:57 - mmengine - INFO - Epoch(train) [741][25/63] lr: 9.1157e-04 eta: 4:51:17 time: 0.6821 data_time: 0.0380 memory: 14901 loss: 1.1132 loss_prob: 0.5869 loss_thr: 0.4252 loss_db: 0.1012 2022/11/02 20:27:00 - mmengine - INFO - Epoch(train) [741][30/63] lr: 9.1157e-04 eta: 4:51:11 time: 0.6089 data_time: 0.0440 memory: 14901 loss: 1.0840 loss_prob: 0.5728 loss_thr: 0.4126 loss_db: 0.0986 2022/11/02 20:27:04 - mmengine - INFO - Epoch(train) [741][35/63] lr: 9.1157e-04 eta: 4:51:11 time: 0.6923 data_time: 0.0164 memory: 14901 loss: 1.1161 loss_prob: 0.5975 loss_thr: 0.4179 loss_db: 0.1007 2022/11/02 20:27:08 - mmengine - INFO - Epoch(train) [741][40/63] lr: 9.1157e-04 eta: 4:51:06 time: 0.7775 data_time: 0.0131 memory: 14901 loss: 1.2510 loss_prob: 0.6825 loss_thr: 0.4544 loss_db: 0.1141 2022/11/02 20:27:10 - mmengine - INFO - Epoch(train) [741][45/63] lr: 9.1157e-04 eta: 4:51:06 time: 0.6009 data_time: 0.0162 memory: 14901 loss: 1.1539 loss_prob: 0.6176 loss_thr: 0.4307 loss_db: 0.1056 2022/11/02 20:27:13 - mmengine - INFO - Epoch(train) [741][50/63] lr: 9.1157e-04 eta: 4:50:59 time: 0.5412 data_time: 0.0254 memory: 14901 loss: 1.0694 loss_prob: 0.5592 loss_thr: 0.4129 loss_db: 0.0973 2022/11/02 20:27:16 - mmengine - INFO - Epoch(train) [741][55/63] lr: 9.1157e-04 eta: 4:50:59 time: 0.5574 data_time: 0.0279 memory: 14901 loss: 1.0875 loss_prob: 0.5651 loss_thr: 0.4235 loss_db: 0.0989 2022/11/02 20:27:19 - mmengine - INFO - Epoch(train) [741][60/63] lr: 9.1157e-04 eta: 4:50:53 time: 0.6053 data_time: 0.0143 memory: 14901 loss: 1.0691 loss_prob: 0.5532 loss_thr: 0.4202 loss_db: 0.0957 2022/11/02 20:27:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:27:28 - mmengine - INFO - Epoch(train) [742][5/63] lr: 9.0978e-04 eta: 4:50:53 time: 0.9963 data_time: 0.2463 memory: 14901 loss: 1.1520 loss_prob: 0.6134 loss_thr: 0.4314 loss_db: 0.1072 2022/11/02 20:27:31 - mmengine - INFO - Epoch(train) [742][10/63] lr: 9.0978e-04 eta: 4:50:47 time: 0.9827 data_time: 0.2531 memory: 14901 loss: 1.1312 loss_prob: 0.6112 loss_thr: 0.4138 loss_db: 0.1062 2022/11/02 20:27:35 - mmengine - INFO - Epoch(train) [742][15/63] lr: 9.0978e-04 eta: 4:50:47 time: 0.7068 data_time: 0.0128 memory: 14901 loss: 1.0718 loss_prob: 0.5676 loss_thr: 0.4063 loss_db: 0.0979 2022/11/02 20:27:38 - mmengine - INFO - Epoch(train) [742][20/63] lr: 9.0978e-04 eta: 4:50:41 time: 0.7115 data_time: 0.0088 memory: 14901 loss: 1.0486 loss_prob: 0.5445 loss_thr: 0.4087 loss_db: 0.0955 2022/11/02 20:27:41 - mmengine - INFO - Epoch(train) [742][25/63] lr: 9.0978e-04 eta: 4:50:41 time: 0.6049 data_time: 0.0340 memory: 14901 loss: 1.0578 loss_prob: 0.5522 loss_thr: 0.4071 loss_db: 0.0985 2022/11/02 20:27:44 - mmengine - INFO - Epoch(train) [742][30/63] lr: 9.0978e-04 eta: 4:50:35 time: 0.6144 data_time: 0.0382 memory: 14901 loss: 1.0980 loss_prob: 0.5756 loss_thr: 0.4221 loss_db: 0.1003 2022/11/02 20:27:47 - mmengine - INFO - Epoch(train) [742][35/63] lr: 9.0978e-04 eta: 4:50:35 time: 0.6097 data_time: 0.0216 memory: 14901 loss: 1.1225 loss_prob: 0.5915 loss_thr: 0.4301 loss_db: 0.1008 2022/11/02 20:27:50 - mmengine - INFO - Epoch(train) [742][40/63] lr: 9.0978e-04 eta: 4:50:29 time: 0.5770 data_time: 0.0148 memory: 14901 loss: 1.1233 loss_prob: 0.5922 loss_thr: 0.4282 loss_db: 0.1028 2022/11/02 20:27:52 - mmengine - INFO - Epoch(train) [742][45/63] lr: 9.0978e-04 eta: 4:50:29 time: 0.5580 data_time: 0.0070 memory: 14901 loss: 1.1029 loss_prob: 0.5827 loss_thr: 0.4200 loss_db: 0.1002 2022/11/02 20:27:56 - mmengine - INFO - Epoch(train) [742][50/63] lr: 9.0978e-04 eta: 4:50:23 time: 0.6138 data_time: 0.0262 memory: 14901 loss: 1.0980 loss_prob: 0.5773 loss_thr: 0.4231 loss_db: 0.0976 2022/11/02 20:27:59 - mmengine - INFO - Epoch(train) [742][55/63] lr: 9.0978e-04 eta: 4:50:23 time: 0.6237 data_time: 0.0313 memory: 14901 loss: 1.0287 loss_prob: 0.5287 loss_thr: 0.4088 loss_db: 0.0913 2022/11/02 20:28:01 - mmengine - INFO - Epoch(train) [742][60/63] lr: 9.0978e-04 eta: 4:50:17 time: 0.5308 data_time: 0.0176 memory: 14901 loss: 1.0069 loss_prob: 0.5185 loss_thr: 0.3980 loss_db: 0.0904 2022/11/02 20:28:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:28:09 - mmengine - INFO - Epoch(train) [743][5/63] lr: 9.0799e-04 eta: 4:50:17 time: 0.9090 data_time: 0.2272 memory: 14901 loss: 1.0174 loss_prob: 0.5312 loss_thr: 0.3952 loss_db: 0.0910 2022/11/02 20:28:13 - mmengine - INFO - Epoch(train) [743][10/63] lr: 9.0799e-04 eta: 4:50:11 time: 1.0358 data_time: 0.2376 memory: 14901 loss: 1.0286 loss_prob: 0.5373 loss_thr: 0.3988 loss_db: 0.0925 2022/11/02 20:28:16 - mmengine - INFO - Epoch(train) [743][15/63] lr: 9.0799e-04 eta: 4:50:11 time: 0.6992 data_time: 0.0192 memory: 14901 loss: 0.9980 loss_prob: 0.5275 loss_thr: 0.3792 loss_db: 0.0914 2022/11/02 20:28:19 - mmengine - INFO - Epoch(train) [743][20/63] lr: 9.0799e-04 eta: 4:50:05 time: 0.6205 data_time: 0.0101 memory: 14901 loss: 1.0876 loss_prob: 0.5975 loss_thr: 0.3902 loss_db: 0.1000 2022/11/02 20:28:23 - mmengine - INFO - Epoch(train) [743][25/63] lr: 9.0799e-04 eta: 4:50:05 time: 0.6520 data_time: 0.0385 memory: 14901 loss: 1.0941 loss_prob: 0.5950 loss_thr: 0.4013 loss_db: 0.0977 2022/11/02 20:28:26 - mmengine - INFO - Epoch(train) [743][30/63] lr: 9.0799e-04 eta: 4:49:59 time: 0.6400 data_time: 0.0508 memory: 14901 loss: 1.0436 loss_prob: 0.5483 loss_thr: 0.4023 loss_db: 0.0930 2022/11/02 20:28:30 - mmengine - INFO - Epoch(train) [743][35/63] lr: 9.0799e-04 eta: 4:49:59 time: 0.7222 data_time: 0.0394 memory: 14901 loss: 1.0729 loss_prob: 0.5623 loss_thr: 0.4127 loss_db: 0.0979 2022/11/02 20:28:33 - mmengine - INFO - Epoch(train) [743][40/63] lr: 9.0799e-04 eta: 4:49:53 time: 0.7261 data_time: 0.0276 memory: 14901 loss: 1.0073 loss_prob: 0.5186 loss_thr: 0.3979 loss_db: 0.0908 2022/11/02 20:28:36 - mmengine - INFO - Epoch(train) [743][45/63] lr: 9.0799e-04 eta: 4:49:53 time: 0.6396 data_time: 0.0111 memory: 14901 loss: 1.0067 loss_prob: 0.5156 loss_thr: 0.4009 loss_db: 0.0902 2022/11/02 20:28:40 - mmengine - INFO - Epoch(train) [743][50/63] lr: 9.0799e-04 eta: 4:49:48 time: 0.6549 data_time: 0.0250 memory: 14901 loss: 1.1022 loss_prob: 0.5791 loss_thr: 0.4243 loss_db: 0.0988 2022/11/02 20:28:42 - mmengine - INFO - Epoch(train) [743][55/63] lr: 9.0799e-04 eta: 4:49:48 time: 0.5856 data_time: 0.0235 memory: 14901 loss: 1.0769 loss_prob: 0.5673 loss_thr: 0.4143 loss_db: 0.0953 2022/11/02 20:28:45 - mmengine - INFO - Epoch(train) [743][60/63] lr: 9.0799e-04 eta: 4:49:41 time: 0.5495 data_time: 0.0135 memory: 14901 loss: 1.0830 loss_prob: 0.5569 loss_thr: 0.4307 loss_db: 0.0954 2022/11/02 20:28:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:28:52 - mmengine - INFO - Epoch(train) [744][5/63] lr: 9.0621e-04 eta: 4:49:41 time: 0.8346 data_time: 0.2910 memory: 14901 loss: 1.1140 loss_prob: 0.5828 loss_thr: 0.4279 loss_db: 0.1032 2022/11/02 20:28:56 - mmengine - INFO - Epoch(train) [744][10/63] lr: 9.0621e-04 eta: 4:49:35 time: 0.9525 data_time: 0.2914 memory: 14901 loss: 1.0493 loss_prob: 0.5481 loss_thr: 0.4058 loss_db: 0.0955 2022/11/02 20:28:59 - mmengine - INFO - Epoch(train) [744][15/63] lr: 9.0621e-04 eta: 4:49:35 time: 0.6362 data_time: 0.0133 memory: 14901 loss: 0.9682 loss_prob: 0.4967 loss_thr: 0.3858 loss_db: 0.0857 2022/11/02 20:29:02 - mmengine - INFO - Epoch(train) [744][20/63] lr: 9.0621e-04 eta: 4:49:29 time: 0.6021 data_time: 0.0136 memory: 14901 loss: 1.1120 loss_prob: 0.6014 loss_thr: 0.4080 loss_db: 0.1026 2022/11/02 20:29:06 - mmengine - INFO - Epoch(train) [744][25/63] lr: 9.0621e-04 eta: 4:49:29 time: 0.7226 data_time: 0.0679 memory: 14901 loss: 1.1462 loss_prob: 0.6258 loss_thr: 0.4143 loss_db: 0.1061 2022/11/02 20:29:08 - mmengine - INFO - Epoch(train) [744][30/63] lr: 9.0621e-04 eta: 4:49:23 time: 0.6589 data_time: 0.0673 memory: 14901 loss: 1.0403 loss_prob: 0.5463 loss_thr: 0.3990 loss_db: 0.0950 2022/11/02 20:29:13 - mmengine - INFO - Epoch(train) [744][35/63] lr: 9.0621e-04 eta: 4:49:23 time: 0.6780 data_time: 0.0115 memory: 14901 loss: 1.0505 loss_prob: 0.5425 loss_thr: 0.4141 loss_db: 0.0939 2022/11/02 20:29:16 - mmengine - INFO - Epoch(train) [744][40/63] lr: 9.0621e-04 eta: 4:49:17 time: 0.7099 data_time: 0.0097 memory: 14901 loss: 1.0247 loss_prob: 0.5267 loss_thr: 0.4079 loss_db: 0.0900 2022/11/02 20:29:18 - mmengine - INFO - Epoch(train) [744][45/63] lr: 9.0621e-04 eta: 4:49:17 time: 0.5332 data_time: 0.0130 memory: 14901 loss: 1.0887 loss_prob: 0.5734 loss_thr: 0.4175 loss_db: 0.0978 2022/11/02 20:29:21 - mmengine - INFO - Epoch(train) [744][50/63] lr: 9.0621e-04 eta: 4:49:11 time: 0.5829 data_time: 0.0333 memory: 14901 loss: 1.0801 loss_prob: 0.5748 loss_thr: 0.4065 loss_db: 0.0987 2022/11/02 20:29:24 - mmengine - INFO - Epoch(train) [744][55/63] lr: 9.0621e-04 eta: 4:49:11 time: 0.6069 data_time: 0.0298 memory: 14901 loss: 1.0286 loss_prob: 0.5403 loss_thr: 0.3949 loss_db: 0.0934 2022/11/02 20:29:28 - mmengine - INFO - Epoch(train) [744][60/63] lr: 9.0621e-04 eta: 4:49:05 time: 0.6305 data_time: 0.0101 memory: 14901 loss: 1.0461 loss_prob: 0.5452 loss_thr: 0.4070 loss_db: 0.0939 2022/11/02 20:29:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:29:37 - mmengine - INFO - Epoch(train) [745][5/63] lr: 9.0442e-04 eta: 4:49:05 time: 1.0382 data_time: 0.2669 memory: 14901 loss: 1.0997 loss_prob: 0.5740 loss_thr: 0.4249 loss_db: 0.1008 2022/11/02 20:29:40 - mmengine - INFO - Epoch(train) [745][10/63] lr: 9.0442e-04 eta: 4:48:59 time: 1.0228 data_time: 0.2699 memory: 14901 loss: 1.0663 loss_prob: 0.5679 loss_thr: 0.4002 loss_db: 0.0982 2022/11/02 20:29:42 - mmengine - INFO - Epoch(train) [745][15/63] lr: 9.0442e-04 eta: 4:48:59 time: 0.5691 data_time: 0.0225 memory: 14901 loss: 1.0816 loss_prob: 0.5803 loss_thr: 0.4029 loss_db: 0.0985 2022/11/02 20:29:45 - mmengine - INFO - Epoch(train) [745][20/63] lr: 9.0442e-04 eta: 4:48:52 time: 0.5173 data_time: 0.0191 memory: 14901 loss: 1.0846 loss_prob: 0.5630 loss_thr: 0.4249 loss_db: 0.0966 2022/11/02 20:29:48 - mmengine - INFO - Epoch(train) [745][25/63] lr: 9.0442e-04 eta: 4:48:52 time: 0.5730 data_time: 0.0182 memory: 14901 loss: 1.0699 loss_prob: 0.5487 loss_thr: 0.4243 loss_db: 0.0969 2022/11/02 20:29:51 - mmengine - INFO - Epoch(train) [745][30/63] lr: 9.0442e-04 eta: 4:48:47 time: 0.6292 data_time: 0.0282 memory: 14901 loss: 1.1629 loss_prob: 0.6173 loss_thr: 0.4381 loss_db: 0.1074 2022/11/02 20:29:55 - mmengine - INFO - Epoch(train) [745][35/63] lr: 9.0442e-04 eta: 4:48:47 time: 0.6945 data_time: 0.0247 memory: 14901 loss: 1.1208 loss_prob: 0.5860 loss_thr: 0.4332 loss_db: 0.1015 2022/11/02 20:29:58 - mmengine - INFO - Epoch(train) [745][40/63] lr: 9.0442e-04 eta: 4:48:41 time: 0.6527 data_time: 0.0223 memory: 14901 loss: 1.0078 loss_prob: 0.5186 loss_thr: 0.3980 loss_db: 0.0912 2022/11/02 20:30:00 - mmengine - INFO - Epoch(train) [745][45/63] lr: 9.0442e-04 eta: 4:48:41 time: 0.5433 data_time: 0.0188 memory: 14901 loss: 1.0605 loss_prob: 0.5692 loss_thr: 0.3934 loss_db: 0.0978 2022/11/02 20:30:03 - mmengine - INFO - Epoch(train) [745][50/63] lr: 9.0442e-04 eta: 4:48:34 time: 0.5386 data_time: 0.0260 memory: 14901 loss: 1.0650 loss_prob: 0.5716 loss_thr: 0.3959 loss_db: 0.0975 2022/11/02 20:30:06 - mmengine - INFO - Epoch(train) [745][55/63] lr: 9.0442e-04 eta: 4:48:34 time: 0.5326 data_time: 0.0273 memory: 14901 loss: 1.1547 loss_prob: 0.6234 loss_thr: 0.4255 loss_db: 0.1058 2022/11/02 20:30:08 - mmengine - INFO - Epoch(train) [745][60/63] lr: 9.0442e-04 eta: 4:48:28 time: 0.5239 data_time: 0.0141 memory: 14901 loss: 1.0734 loss_prob: 0.5703 loss_thr: 0.4050 loss_db: 0.0981 2022/11/02 20:30:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:30:16 - mmengine - INFO - Epoch(train) [746][5/63] lr: 9.0263e-04 eta: 4:48:28 time: 0.9128 data_time: 0.2640 memory: 14901 loss: 1.0340 loss_prob: 0.5459 loss_thr: 0.3945 loss_db: 0.0936 2022/11/02 20:30:19 - mmengine - INFO - Epoch(train) [746][10/63] lr: 9.0263e-04 eta: 4:48:21 time: 0.8966 data_time: 0.2545 memory: 14901 loss: 1.0915 loss_prob: 0.5762 loss_thr: 0.4179 loss_db: 0.0974 2022/11/02 20:30:22 - mmengine - INFO - Epoch(train) [746][15/63] lr: 9.0263e-04 eta: 4:48:21 time: 0.5966 data_time: 0.0162 memory: 14901 loss: 1.1151 loss_prob: 0.5830 loss_thr: 0.4305 loss_db: 0.1017 2022/11/02 20:30:26 - mmengine - INFO - Epoch(train) [746][20/63] lr: 9.0263e-04 eta: 4:48:15 time: 0.6779 data_time: 0.0150 memory: 14901 loss: 1.1539 loss_prob: 0.6041 loss_thr: 0.4437 loss_db: 0.1061 2022/11/02 20:30:29 - mmengine - INFO - Epoch(train) [746][25/63] lr: 9.0263e-04 eta: 4:48:15 time: 0.6321 data_time: 0.0202 memory: 14901 loss: 1.2073 loss_prob: 0.6534 loss_thr: 0.4455 loss_db: 0.1084 2022/11/02 20:30:31 - mmengine - INFO - Epoch(train) [746][30/63] lr: 9.0263e-04 eta: 4:48:09 time: 0.5727 data_time: 0.0442 memory: 14901 loss: 1.0902 loss_prob: 0.5866 loss_thr: 0.4068 loss_db: 0.0968 2022/11/02 20:30:34 - mmengine - INFO - Epoch(train) [746][35/63] lr: 9.0263e-04 eta: 4:48:09 time: 0.5203 data_time: 0.0343 memory: 14901 loss: 0.9828 loss_prob: 0.5104 loss_thr: 0.3822 loss_db: 0.0903 2022/11/02 20:30:36 - mmengine - INFO - Epoch(train) [746][40/63] lr: 9.0263e-04 eta: 4:48:02 time: 0.5016 data_time: 0.0125 memory: 14901 loss: 1.0178 loss_prob: 0.5293 loss_thr: 0.3942 loss_db: 0.0943 2022/11/02 20:30:39 - mmengine - INFO - Epoch(train) [746][45/63] lr: 9.0263e-04 eta: 4:48:02 time: 0.5237 data_time: 0.0108 memory: 14901 loss: 0.9876 loss_prob: 0.5139 loss_thr: 0.3848 loss_db: 0.0890 2022/11/02 20:30:42 - mmengine - INFO - Epoch(train) [746][50/63] lr: 9.0263e-04 eta: 4:47:56 time: 0.5830 data_time: 0.0262 memory: 14901 loss: 0.9615 loss_prob: 0.4928 loss_thr: 0.3838 loss_db: 0.0849 2022/11/02 20:30:45 - mmengine - INFO - Epoch(train) [746][55/63] lr: 9.0263e-04 eta: 4:47:56 time: 0.5646 data_time: 0.0263 memory: 14901 loss: 1.1810 loss_prob: 0.6235 loss_thr: 0.4523 loss_db: 0.1052 2022/11/02 20:30:47 - mmengine - INFO - Epoch(train) [746][60/63] lr: 9.0263e-04 eta: 4:47:50 time: 0.5210 data_time: 0.0143 memory: 14901 loss: 1.2101 loss_prob: 0.6405 loss_thr: 0.4598 loss_db: 0.1098 2022/11/02 20:30:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:30:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:30:54 - mmengine - INFO - Epoch(train) [747][5/63] lr: 9.0084e-04 eta: 4:47:50 time: 0.7812 data_time: 0.2178 memory: 14901 loss: 2.5828 loss_prob: 1.8212 loss_thr: 0.5231 loss_db: 0.2386 2022/11/02 20:30:57 - mmengine - INFO - Epoch(train) [747][10/63] lr: 9.0084e-04 eta: 4:47:42 time: 0.8175 data_time: 0.2136 memory: 14901 loss: 3.4105 loss_prob: 2.4290 loss_thr: 0.6784 loss_db: 0.3031 2022/11/02 20:31:01 - mmengine - INFO - Epoch(train) [747][15/63] lr: 9.0084e-04 eta: 4:47:42 time: 0.7073 data_time: 0.0182 memory: 14901 loss: 3.0002 loss_prob: 2.0307 loss_thr: 0.6867 loss_db: 0.2828 2022/11/02 20:31:04 - mmengine - INFO - Epoch(train) [747][20/63] lr: 9.0084e-04 eta: 4:47:37 time: 0.7428 data_time: 0.0227 memory: 14901 loss: 2.5439 loss_prob: 1.6406 loss_thr: 0.6495 loss_db: 0.2538 2022/11/02 20:31:07 - mmengine - INFO - Epoch(train) [747][25/63] lr: 9.0084e-04 eta: 4:47:37 time: 0.5686 data_time: 0.0246 memory: 14901 loss: 2.2879 loss_prob: 1.4209 loss_thr: 0.6315 loss_db: 0.2355 2022/11/02 20:31:11 - mmengine - INFO - Epoch(train) [747][30/63] lr: 9.0084e-04 eta: 4:47:31 time: 0.6863 data_time: 0.0436 memory: 14901 loss: 2.1247 loss_prob: 1.2974 loss_thr: 0.6096 loss_db: 0.2177 2022/11/02 20:31:14 - mmengine - INFO - Epoch(train) [747][35/63] lr: 9.0084e-04 eta: 4:47:31 time: 0.7371 data_time: 0.0353 memory: 14901 loss: 2.0962 loss_prob: 1.3001 loss_thr: 0.5823 loss_db: 0.2138 2022/11/02 20:31:18 - mmengine - INFO - Epoch(train) [747][40/63] lr: 9.0084e-04 eta: 4:47:25 time: 0.6376 data_time: 0.0181 memory: 14901 loss: 1.9858 loss_prob: 1.2024 loss_thr: 0.5861 loss_db: 0.1973 2022/11/02 20:31:22 - mmengine - INFO - Epoch(train) [747][45/63] lr: 9.0084e-04 eta: 4:47:25 time: 0.7305 data_time: 0.0154 memory: 14901 loss: 1.9031 loss_prob: 1.1285 loss_thr: 0.5914 loss_db: 0.1832 2022/11/02 20:31:25 - mmengine - INFO - Epoch(train) [747][50/63] lr: 9.0084e-04 eta: 4:47:20 time: 0.6985 data_time: 0.0173 memory: 14901 loss: 1.8594 loss_prob: 1.1028 loss_thr: 0.5724 loss_db: 0.1842 2022/11/02 20:31:27 - mmengine - INFO - Epoch(train) [747][55/63] lr: 9.0084e-04 eta: 4:47:20 time: 0.5591 data_time: 0.0292 memory: 14901 loss: 1.7849 loss_prob: 1.0504 loss_thr: 0.5607 loss_db: 0.1738 2022/11/02 20:31:30 - mmengine - INFO - Epoch(train) [747][60/63] lr: 9.0084e-04 eta: 4:47:13 time: 0.5351 data_time: 0.0243 memory: 14901 loss: 1.8389 loss_prob: 1.1007 loss_thr: 0.5589 loss_db: 0.1793 2022/11/02 20:31:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:31:38 - mmengine - INFO - Epoch(train) [748][5/63] lr: 8.9905e-04 eta: 4:47:13 time: 0.9206 data_time: 0.2180 memory: 14901 loss: 1.7641 loss_prob: 1.0371 loss_thr: 0.5577 loss_db: 0.1693 2022/11/02 20:31:41 - mmengine - INFO - Epoch(train) [748][10/63] lr: 8.9905e-04 eta: 4:47:07 time: 0.9946 data_time: 0.2146 memory: 14901 loss: 1.5661 loss_prob: 0.8820 loss_thr: 0.5377 loss_db: 0.1464 2022/11/02 20:31:46 - mmengine - INFO - Epoch(train) [748][15/63] lr: 8.9905e-04 eta: 4:47:07 time: 0.7450 data_time: 0.0107 memory: 14901 loss: 1.6138 loss_prob: 0.9135 loss_thr: 0.5509 loss_db: 0.1494 2022/11/02 20:31:49 - mmengine - INFO - Epoch(train) [748][20/63] lr: 8.9905e-04 eta: 4:47:02 time: 0.7494 data_time: 0.0091 memory: 14901 loss: 1.6616 loss_prob: 0.9538 loss_thr: 0.5519 loss_db: 0.1558 2022/11/02 20:31:52 - mmengine - INFO - Epoch(train) [748][25/63] lr: 8.9905e-04 eta: 4:47:02 time: 0.6324 data_time: 0.0214 memory: 14901 loss: 1.5170 loss_prob: 0.8572 loss_thr: 0.5170 loss_db: 0.1428 2022/11/02 20:31:56 - mmengine - INFO - Epoch(train) [748][30/63] lr: 8.9905e-04 eta: 4:46:56 time: 0.7280 data_time: 0.0416 memory: 14901 loss: 1.4748 loss_prob: 0.8317 loss_thr: 0.5075 loss_db: 0.1356 2022/11/02 20:31:59 - mmengine - INFO - Epoch(train) [748][35/63] lr: 8.9905e-04 eta: 4:46:56 time: 0.7011 data_time: 0.0277 memory: 14901 loss: 1.4525 loss_prob: 0.8125 loss_thr: 0.5042 loss_db: 0.1358 2022/11/02 20:32:02 - mmengine - INFO - Epoch(train) [748][40/63] lr: 8.9905e-04 eta: 4:46:50 time: 0.6137 data_time: 0.0093 memory: 14901 loss: 1.2929 loss_prob: 0.6952 loss_thr: 0.4785 loss_db: 0.1192 2022/11/02 20:32:04 - mmengine - INFO - Epoch(train) [748][45/63] lr: 8.9905e-04 eta: 4:46:50 time: 0.5557 data_time: 0.0083 memory: 14901 loss: 1.3559 loss_prob: 0.7404 loss_thr: 0.4920 loss_db: 0.1236 2022/11/02 20:32:07 - mmengine - INFO - Epoch(train) [748][50/63] lr: 8.9905e-04 eta: 4:46:44 time: 0.5079 data_time: 0.0169 memory: 14901 loss: 1.4227 loss_prob: 0.7846 loss_thr: 0.5066 loss_db: 0.1315 2022/11/02 20:32:10 - mmengine - INFO - Epoch(train) [748][55/63] lr: 8.9905e-04 eta: 4:46:44 time: 0.5337 data_time: 0.0412 memory: 14901 loss: 1.5235 loss_prob: 0.8464 loss_thr: 0.5314 loss_db: 0.1458 2022/11/02 20:32:12 - mmengine - INFO - Epoch(train) [748][60/63] lr: 8.9905e-04 eta: 4:46:37 time: 0.5276 data_time: 0.0307 memory: 14901 loss: 1.6107 loss_prob: 0.9157 loss_thr: 0.5418 loss_db: 0.1532 2022/11/02 20:32:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:32:20 - mmengine - INFO - Epoch(train) [749][5/63] lr: 8.9726e-04 eta: 4:46:37 time: 0.8525 data_time: 0.2388 memory: 14901 loss: 1.5565 loss_prob: 0.8958 loss_thr: 0.5089 loss_db: 0.1518 2022/11/02 20:32:23 - mmengine - INFO - Epoch(train) [749][10/63] lr: 8.9726e-04 eta: 4:46:30 time: 0.8831 data_time: 0.2415 memory: 14901 loss: 1.4668 loss_prob: 0.8329 loss_thr: 0.4920 loss_db: 0.1419 2022/11/02 20:32:27 - mmengine - INFO - Epoch(train) [749][15/63] lr: 8.9726e-04 eta: 4:46:30 time: 0.7657 data_time: 0.0117 memory: 14901 loss: 1.4718 loss_prob: 0.8216 loss_thr: 0.5139 loss_db: 0.1363 2022/11/02 20:32:31 - mmengine - INFO - Epoch(train) [749][20/63] lr: 8.9726e-04 eta: 4:46:25 time: 0.8153 data_time: 0.0138 memory: 14901 loss: 1.3251 loss_prob: 0.7136 loss_thr: 0.4902 loss_db: 0.1213 2022/11/02 20:32:34 - mmengine - INFO - Epoch(train) [749][25/63] lr: 8.9726e-04 eta: 4:46:25 time: 0.6183 data_time: 0.0165 memory: 14901 loss: 1.2427 loss_prob: 0.6476 loss_thr: 0.4843 loss_db: 0.1108 2022/11/02 20:32:37 - mmengine - INFO - Epoch(train) [749][30/63] lr: 8.9726e-04 eta: 4:46:19 time: 0.5753 data_time: 0.0441 memory: 14901 loss: 1.4007 loss_prob: 0.7805 loss_thr: 0.4918 loss_db: 0.1284 2022/11/02 20:32:40 - mmengine - INFO - Epoch(train) [749][35/63] lr: 8.9726e-04 eta: 4:46:19 time: 0.5852 data_time: 0.0426 memory: 14901 loss: 1.4660 loss_prob: 0.8388 loss_thr: 0.4883 loss_db: 0.1389 2022/11/02 20:32:42 - mmengine - INFO - Epoch(train) [749][40/63] lr: 8.9726e-04 eta: 4:46:12 time: 0.5058 data_time: 0.0124 memory: 14901 loss: 1.3885 loss_prob: 0.7732 loss_thr: 0.4863 loss_db: 0.1290 2022/11/02 20:32:44 - mmengine - INFO - Epoch(train) [749][45/63] lr: 8.9726e-04 eta: 4:46:12 time: 0.4919 data_time: 0.0108 memory: 14901 loss: 1.3263 loss_prob: 0.7275 loss_thr: 0.4773 loss_db: 0.1216 2022/11/02 20:32:48 - mmengine - INFO - Epoch(train) [749][50/63] lr: 8.9726e-04 eta: 4:46:06 time: 0.6172 data_time: 0.0255 memory: 14901 loss: 1.3361 loss_prob: 0.7269 loss_thr: 0.4817 loss_db: 0.1275 2022/11/02 20:32:52 - mmengine - INFO - Epoch(train) [749][55/63] lr: 8.9726e-04 eta: 4:46:06 time: 0.7895 data_time: 0.0299 memory: 14901 loss: 1.4086 loss_prob: 0.7830 loss_thr: 0.4916 loss_db: 0.1340 2022/11/02 20:32:55 - mmengine - INFO - Epoch(train) [749][60/63] lr: 8.9726e-04 eta: 4:46:01 time: 0.6936 data_time: 0.0142 memory: 14901 loss: 1.3345 loss_prob: 0.7478 loss_thr: 0.4595 loss_db: 0.1272 2022/11/02 20:32:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:33:03 - mmengine - INFO - Epoch(train) [750][5/63] lr: 8.9547e-04 eta: 4:46:01 time: 0.9056 data_time: 0.2391 memory: 14901 loss: 1.2788 loss_prob: 0.6955 loss_thr: 0.4674 loss_db: 0.1159 2022/11/02 20:33:06 - mmengine - INFO - Epoch(train) [750][10/63] lr: 8.9547e-04 eta: 4:45:54 time: 0.9288 data_time: 0.2394 memory: 14901 loss: 1.2905 loss_prob: 0.7083 loss_thr: 0.4631 loss_db: 0.1191 2022/11/02 20:33:10 - mmengine - INFO - Epoch(train) [750][15/63] lr: 8.9547e-04 eta: 4:45:54 time: 0.6701 data_time: 0.0094 memory: 14901 loss: 1.3000 loss_prob: 0.7273 loss_thr: 0.4466 loss_db: 0.1260 2022/11/02 20:33:12 - mmengine - INFO - Epoch(train) [750][20/63] lr: 8.9547e-04 eta: 4:45:48 time: 0.6397 data_time: 0.0106 memory: 14901 loss: 1.3734 loss_prob: 0.7770 loss_thr: 0.4606 loss_db: 0.1357 2022/11/02 20:33:16 - mmengine - INFO - Epoch(train) [750][25/63] lr: 8.9547e-04 eta: 4:45:48 time: 0.5809 data_time: 0.0244 memory: 14901 loss: 1.4015 loss_prob: 0.7856 loss_thr: 0.4814 loss_db: 0.1345 2022/11/02 20:33:18 - mmengine - INFO - Epoch(train) [750][30/63] lr: 8.9547e-04 eta: 4:45:42 time: 0.5881 data_time: 0.0420 memory: 14901 loss: 1.4138 loss_prob: 0.7886 loss_thr: 0.4960 loss_db: 0.1292 2022/11/02 20:33:21 - mmengine - INFO - Epoch(train) [750][35/63] lr: 8.9547e-04 eta: 4:45:42 time: 0.5234 data_time: 0.0294 memory: 14901 loss: 1.6117 loss_prob: 0.9514 loss_thr: 0.5114 loss_db: 0.1489 2022/11/02 20:33:24 - mmengine - INFO - Epoch(train) [750][40/63] lr: 8.9547e-04 eta: 4:45:36 time: 0.5359 data_time: 0.0098 memory: 14901 loss: 1.5764 loss_prob: 0.9139 loss_thr: 0.5146 loss_db: 0.1480 2022/11/02 20:33:27 - mmengine - INFO - Epoch(train) [750][45/63] lr: 8.9547e-04 eta: 4:45:36 time: 0.6249 data_time: 0.0158 memory: 14901 loss: 1.3532 loss_prob: 0.7375 loss_thr: 0.4893 loss_db: 0.1264 2022/11/02 20:33:30 - mmengine - INFO - Epoch(train) [750][50/63] lr: 8.9547e-04 eta: 4:45:30 time: 0.6555 data_time: 0.0231 memory: 14901 loss: 1.2367 loss_prob: 0.6621 loss_thr: 0.4625 loss_db: 0.1121 2022/11/02 20:33:33 - mmengine - INFO - Epoch(train) [750][55/63] lr: 8.9547e-04 eta: 4:45:30 time: 0.6074 data_time: 0.0289 memory: 14901 loss: 1.2694 loss_prob: 0.6848 loss_thr: 0.4664 loss_db: 0.1182 2022/11/02 20:33:36 - mmengine - INFO - Epoch(train) [750][60/63] lr: 8.9547e-04 eta: 4:45:24 time: 0.5606 data_time: 0.0222 memory: 14901 loss: 1.4864 loss_prob: 0.8256 loss_thr: 0.5236 loss_db: 0.1373 2022/11/02 20:33:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:33:44 - mmengine - INFO - Epoch(train) [751][5/63] lr: 8.9368e-04 eta: 4:45:24 time: 0.9784 data_time: 0.2065 memory: 14901 loss: 1.3098 loss_prob: 0.7034 loss_thr: 0.4919 loss_db: 0.1146 2022/11/02 20:33:48 - mmengine - INFO - Epoch(train) [751][10/63] lr: 8.9368e-04 eta: 4:45:17 time: 1.0261 data_time: 0.2133 memory: 14901 loss: 1.1041 loss_prob: 0.5814 loss_thr: 0.4202 loss_db: 0.1025 2022/11/02 20:33:52 - mmengine - INFO - Epoch(train) [751][15/63] lr: 8.9368e-04 eta: 4:45:17 time: 0.7658 data_time: 0.0194 memory: 14901 loss: 1.1975 loss_prob: 0.6544 loss_thr: 0.4345 loss_db: 0.1086 2022/11/02 20:33:55 - mmengine - INFO - Epoch(train) [751][20/63] lr: 8.9368e-04 eta: 4:45:11 time: 0.6614 data_time: 0.0117 memory: 14901 loss: 1.2571 loss_prob: 0.6915 loss_thr: 0.4539 loss_db: 0.1117 2022/11/02 20:33:57 - mmengine - INFO - Epoch(train) [751][25/63] lr: 8.9368e-04 eta: 4:45:11 time: 0.5405 data_time: 0.0148 memory: 14901 loss: 1.2537 loss_prob: 0.6801 loss_thr: 0.4588 loss_db: 0.1148 2022/11/02 20:34:00 - mmengine - INFO - Epoch(train) [751][30/63] lr: 8.9368e-04 eta: 4:45:05 time: 0.5758 data_time: 0.0443 memory: 14901 loss: 1.2017 loss_prob: 0.6447 loss_thr: 0.4450 loss_db: 0.1120 2022/11/02 20:34:03 - mmengine - INFO - Epoch(train) [751][35/63] lr: 8.9368e-04 eta: 4:45:05 time: 0.5799 data_time: 0.0415 memory: 14901 loss: 1.2310 loss_prob: 0.6574 loss_thr: 0.4619 loss_db: 0.1117 2022/11/02 20:34:06 - mmengine - INFO - Epoch(train) [751][40/63] lr: 8.9368e-04 eta: 4:44:59 time: 0.5470 data_time: 0.0125 memory: 14901 loss: 1.2644 loss_prob: 0.6679 loss_thr: 0.4831 loss_db: 0.1134 2022/11/02 20:34:09 - mmengine - INFO - Epoch(train) [751][45/63] lr: 8.9368e-04 eta: 4:44:59 time: 0.5583 data_time: 0.0105 memory: 14901 loss: 1.1952 loss_prob: 0.6244 loss_thr: 0.4609 loss_db: 0.1098 2022/11/02 20:34:11 - mmengine - INFO - Epoch(train) [751][50/63] lr: 8.9368e-04 eta: 4:44:52 time: 0.5403 data_time: 0.0132 memory: 14901 loss: 1.2092 loss_prob: 0.6482 loss_thr: 0.4491 loss_db: 0.1119 2022/11/02 20:34:14 - mmengine - INFO - Epoch(train) [751][55/63] lr: 8.9368e-04 eta: 4:44:52 time: 0.5173 data_time: 0.0280 memory: 14901 loss: 1.2690 loss_prob: 0.6995 loss_thr: 0.4520 loss_db: 0.1175 2022/11/02 20:34:17 - mmengine - INFO - Epoch(train) [751][60/63] lr: 8.9368e-04 eta: 4:44:46 time: 0.5812 data_time: 0.0265 memory: 14901 loss: 1.3116 loss_prob: 0.7207 loss_thr: 0.4690 loss_db: 0.1219 2022/11/02 20:34:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:34:24 - mmengine - INFO - Epoch(train) [752][5/63] lr: 8.9189e-04 eta: 4:44:46 time: 0.8489 data_time: 0.2739 memory: 14901 loss: 1.4454 loss_prob: 0.8007 loss_thr: 0.5049 loss_db: 0.1398 2022/11/02 20:34:28 - mmengine - INFO - Epoch(train) [752][10/63] lr: 8.9189e-04 eta: 4:44:40 time: 1.0019 data_time: 0.2712 memory: 14901 loss: 1.4429 loss_prob: 0.8004 loss_thr: 0.5046 loss_db: 0.1379 2022/11/02 20:34:32 - mmengine - INFO - Epoch(train) [752][15/63] lr: 8.9189e-04 eta: 4:44:40 time: 0.7484 data_time: 0.0095 memory: 14901 loss: 1.3636 loss_prob: 0.7374 loss_thr: 0.5001 loss_db: 0.1262 2022/11/02 20:34:35 - mmengine - INFO - Epoch(train) [752][20/63] lr: 8.9189e-04 eta: 4:44:34 time: 0.6119 data_time: 0.0115 memory: 14901 loss: 1.2823 loss_prob: 0.6844 loss_thr: 0.4818 loss_db: 0.1161 2022/11/02 20:34:38 - mmengine - INFO - Epoch(train) [752][25/63] lr: 8.9189e-04 eta: 4:44:34 time: 0.5795 data_time: 0.0322 memory: 14901 loss: 1.3277 loss_prob: 0.7242 loss_thr: 0.4807 loss_db: 0.1228 2022/11/02 20:34:41 - mmengine - INFO - Epoch(train) [752][30/63] lr: 8.9189e-04 eta: 4:44:28 time: 0.6313 data_time: 0.0468 memory: 14901 loss: 1.2734 loss_prob: 0.6949 loss_thr: 0.4606 loss_db: 0.1178 2022/11/02 20:34:44 - mmengine - INFO - Epoch(train) [752][35/63] lr: 8.9189e-04 eta: 4:44:28 time: 0.5814 data_time: 0.0259 memory: 14901 loss: 1.2580 loss_prob: 0.6779 loss_thr: 0.4633 loss_db: 0.1168 2022/11/02 20:34:47 - mmengine - INFO - Epoch(train) [752][40/63] lr: 8.9189e-04 eta: 4:44:22 time: 0.5909 data_time: 0.0108 memory: 14901 loss: 1.2729 loss_prob: 0.6963 loss_thr: 0.4545 loss_db: 0.1222 2022/11/02 20:34:50 - mmengine - INFO - Epoch(train) [752][45/63] lr: 8.9189e-04 eta: 4:44:22 time: 0.6052 data_time: 0.0102 memory: 14901 loss: 1.2367 loss_prob: 0.6769 loss_thr: 0.4451 loss_db: 0.1148 2022/11/02 20:34:52 - mmengine - INFO - Epoch(train) [752][50/63] lr: 8.9189e-04 eta: 4:44:15 time: 0.5613 data_time: 0.0304 memory: 14901 loss: 1.2425 loss_prob: 0.6655 loss_thr: 0.4655 loss_db: 0.1115 2022/11/02 20:34:55 - mmengine - INFO - Epoch(train) [752][55/63] lr: 8.9189e-04 eta: 4:44:15 time: 0.5364 data_time: 0.0299 memory: 14901 loss: 1.2344 loss_prob: 0.6616 loss_thr: 0.4589 loss_db: 0.1139 2022/11/02 20:34:58 - mmengine - INFO - Epoch(train) [752][60/63] lr: 8.9189e-04 eta: 4:44:09 time: 0.5978 data_time: 0.0106 memory: 14901 loss: 1.1464 loss_prob: 0.6148 loss_thr: 0.4245 loss_db: 0.1071 2022/11/02 20:35:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:35:07 - mmengine - INFO - Epoch(train) [753][5/63] lr: 8.9009e-04 eta: 4:44:09 time: 0.9754 data_time: 0.1966 memory: 14901 loss: 1.2509 loss_prob: 0.6945 loss_thr: 0.4425 loss_db: 0.1139 2022/11/02 20:35:11 - mmengine - INFO - Epoch(train) [753][10/63] lr: 8.9009e-04 eta: 4:44:03 time: 1.1263 data_time: 0.2042 memory: 14901 loss: 1.1470 loss_prob: 0.6147 loss_thr: 0.4270 loss_db: 0.1052 2022/11/02 20:35:15 - mmengine - INFO - Epoch(train) [753][15/63] lr: 8.9009e-04 eta: 4:44:03 time: 0.8180 data_time: 0.0276 memory: 14901 loss: 1.0943 loss_prob: 0.5727 loss_thr: 0.4222 loss_db: 0.0994 2022/11/02 20:35:18 - mmengine - INFO - Epoch(train) [753][20/63] lr: 8.9009e-04 eta: 4:43:57 time: 0.6137 data_time: 0.0168 memory: 14901 loss: 1.2501 loss_prob: 0.6702 loss_thr: 0.4669 loss_db: 0.1130 2022/11/02 20:35:21 - mmengine - INFO - Epoch(train) [753][25/63] lr: 8.9009e-04 eta: 4:43:57 time: 0.6269 data_time: 0.0202 memory: 14901 loss: 1.3493 loss_prob: 0.7347 loss_thr: 0.4907 loss_db: 0.1239 2022/11/02 20:35:24 - mmengine - INFO - Epoch(train) [753][30/63] lr: 8.9009e-04 eta: 4:43:52 time: 0.6148 data_time: 0.0299 memory: 14901 loss: 1.2080 loss_prob: 0.6474 loss_thr: 0.4499 loss_db: 0.1107 2022/11/02 20:35:27 - mmengine - INFO - Epoch(train) [753][35/63] lr: 8.9009e-04 eta: 4:43:52 time: 0.6258 data_time: 0.0252 memory: 14901 loss: 1.1183 loss_prob: 0.5908 loss_thr: 0.4246 loss_db: 0.1028 2022/11/02 20:35:31 - mmengine - INFO - Epoch(train) [753][40/63] lr: 8.9009e-04 eta: 4:43:46 time: 0.7027 data_time: 0.0229 memory: 14901 loss: 1.1726 loss_prob: 0.6347 loss_thr: 0.4290 loss_db: 0.1088 2022/11/02 20:35:35 - mmengine - INFO - Epoch(train) [753][45/63] lr: 8.9009e-04 eta: 4:43:46 time: 0.7147 data_time: 0.0171 memory: 14901 loss: 1.3026 loss_prob: 0.7176 loss_thr: 0.4630 loss_db: 0.1220 2022/11/02 20:35:38 - mmengine - INFO - Epoch(train) [753][50/63] lr: 8.9009e-04 eta: 4:43:41 time: 0.7049 data_time: 0.0202 memory: 14901 loss: 1.2779 loss_prob: 0.6950 loss_thr: 0.4631 loss_db: 0.1198 2022/11/02 20:35:41 - mmengine - INFO - Epoch(train) [753][55/63] lr: 8.9009e-04 eta: 4:43:41 time: 0.6250 data_time: 0.0251 memory: 14901 loss: 1.1617 loss_prob: 0.6131 loss_thr: 0.4426 loss_db: 0.1060 2022/11/02 20:35:44 - mmengine - INFO - Epoch(train) [753][60/63] lr: 8.9009e-04 eta: 4:43:34 time: 0.5887 data_time: 0.0284 memory: 14901 loss: 1.2076 loss_prob: 0.6512 loss_thr: 0.4440 loss_db: 0.1125 2022/11/02 20:35:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:35:51 - mmengine - INFO - Epoch(train) [754][5/63] lr: 8.8830e-04 eta: 4:43:34 time: 0.8556 data_time: 0.2454 memory: 14901 loss: 1.2564 loss_prob: 0.6819 loss_thr: 0.4572 loss_db: 0.1173 2022/11/02 20:35:55 - mmengine - INFO - Epoch(train) [754][10/63] lr: 8.8830e-04 eta: 4:43:28 time: 1.0222 data_time: 0.2500 memory: 14901 loss: 1.2178 loss_prob: 0.6490 loss_thr: 0.4561 loss_db: 0.1126 2022/11/02 20:35:59 - mmengine - INFO - Epoch(train) [754][15/63] lr: 8.8830e-04 eta: 4:43:28 time: 0.8274 data_time: 0.0171 memory: 14901 loss: 1.1771 loss_prob: 0.6237 loss_thr: 0.4450 loss_db: 0.1084 2022/11/02 20:36:03 - mmengine - INFO - Epoch(train) [754][20/63] lr: 8.8830e-04 eta: 4:43:23 time: 0.7452 data_time: 0.0104 memory: 14901 loss: 1.1277 loss_prob: 0.5995 loss_thr: 0.4264 loss_db: 0.1019 2022/11/02 20:36:06 - mmengine - INFO - Epoch(train) [754][25/63] lr: 8.8830e-04 eta: 4:43:23 time: 0.6183 data_time: 0.0325 memory: 14901 loss: 1.1584 loss_prob: 0.6221 loss_thr: 0.4340 loss_db: 0.1022 2022/11/02 20:36:09 - mmengine - INFO - Epoch(train) [754][30/63] lr: 8.8830e-04 eta: 4:43:17 time: 0.5794 data_time: 0.0438 memory: 14901 loss: 1.2417 loss_prob: 0.6762 loss_thr: 0.4548 loss_db: 0.1108 2022/11/02 20:36:11 - mmengine - INFO - Epoch(train) [754][35/63] lr: 8.8830e-04 eta: 4:43:17 time: 0.5393 data_time: 0.0250 memory: 14901 loss: 1.3008 loss_prob: 0.7032 loss_thr: 0.4793 loss_db: 0.1183 2022/11/02 20:36:14 - mmengine - INFO - Epoch(train) [754][40/63] lr: 8.8830e-04 eta: 4:43:10 time: 0.5502 data_time: 0.0140 memory: 14901 loss: 1.2437 loss_prob: 0.6640 loss_thr: 0.4649 loss_db: 0.1148 2022/11/02 20:36:17 - mmengine - INFO - Epoch(train) [754][45/63] lr: 8.8830e-04 eta: 4:43:10 time: 0.5891 data_time: 0.0108 memory: 14901 loss: 1.1210 loss_prob: 0.5923 loss_thr: 0.4281 loss_db: 0.1007 2022/11/02 20:36:20 - mmengine - INFO - Epoch(train) [754][50/63] lr: 8.8830e-04 eta: 4:43:04 time: 0.5487 data_time: 0.0232 memory: 14901 loss: 1.1011 loss_prob: 0.5808 loss_thr: 0.4230 loss_db: 0.0974 2022/11/02 20:36:22 - mmengine - INFO - Epoch(train) [754][55/63] lr: 8.8830e-04 eta: 4:43:04 time: 0.5424 data_time: 0.0283 memory: 14901 loss: 1.1102 loss_prob: 0.5862 loss_thr: 0.4240 loss_db: 0.1000 2022/11/02 20:36:25 - mmengine - INFO - Epoch(train) [754][60/63] lr: 8.8830e-04 eta: 4:42:57 time: 0.5370 data_time: 0.0185 memory: 14901 loss: 1.0949 loss_prob: 0.5800 loss_thr: 0.4150 loss_db: 0.0999 2022/11/02 20:36:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:36:33 - mmengine - INFO - Epoch(train) [755][5/63] lr: 8.8651e-04 eta: 4:42:57 time: 0.9187 data_time: 0.2542 memory: 14901 loss: 1.1587 loss_prob: 0.6152 loss_thr: 0.4372 loss_db: 0.1062 2022/11/02 20:36:37 - mmengine - INFO - Epoch(train) [755][10/63] lr: 8.8651e-04 eta: 4:42:52 time: 1.1059 data_time: 0.2535 memory: 14901 loss: 1.2951 loss_prob: 0.7342 loss_thr: 0.4461 loss_db: 0.1148 2022/11/02 20:36:40 - mmengine - INFO - Epoch(train) [755][15/63] lr: 8.8651e-04 eta: 4:42:52 time: 0.7114 data_time: 0.0125 memory: 14901 loss: 1.4016 loss_prob: 0.8031 loss_thr: 0.4732 loss_db: 0.1254 2022/11/02 20:36:44 - mmengine - INFO - Epoch(train) [755][20/63] lr: 8.8651e-04 eta: 4:42:46 time: 0.6259 data_time: 0.0135 memory: 14901 loss: 1.2548 loss_prob: 0.6795 loss_thr: 0.4633 loss_db: 0.1120 2022/11/02 20:36:46 - mmengine - INFO - Epoch(train) [755][25/63] lr: 8.8651e-04 eta: 4:42:46 time: 0.6056 data_time: 0.0173 memory: 14901 loss: 1.2509 loss_prob: 0.6798 loss_thr: 0.4548 loss_db: 0.1162 2022/11/02 20:36:49 - mmengine - INFO - Epoch(train) [755][30/63] lr: 8.8651e-04 eta: 4:42:39 time: 0.5421 data_time: 0.0364 memory: 14901 loss: 1.2213 loss_prob: 0.6579 loss_thr: 0.4483 loss_db: 0.1151 2022/11/02 20:36:52 - mmengine - INFO - Epoch(train) [755][35/63] lr: 8.8651e-04 eta: 4:42:39 time: 0.6230 data_time: 0.0304 memory: 14901 loss: 1.2474 loss_prob: 0.6669 loss_thr: 0.4682 loss_db: 0.1122 2022/11/02 20:36:55 - mmengine - INFO - Epoch(train) [755][40/63] lr: 8.8651e-04 eta: 4:42:33 time: 0.6144 data_time: 0.0135 memory: 14901 loss: 1.2331 loss_prob: 0.6589 loss_thr: 0.4616 loss_db: 0.1125 2022/11/02 20:36:58 - mmengine - INFO - Epoch(train) [755][45/63] lr: 8.8651e-04 eta: 4:42:33 time: 0.5989 data_time: 0.0105 memory: 14901 loss: 1.0950 loss_prob: 0.5762 loss_thr: 0.4174 loss_db: 0.1014 2022/11/02 20:37:02 - mmengine - INFO - Epoch(train) [755][50/63] lr: 8.8651e-04 eta: 4:42:27 time: 0.6458 data_time: 0.0271 memory: 14901 loss: 1.0320 loss_prob: 0.5330 loss_thr: 0.4042 loss_db: 0.0948 2022/11/02 20:37:05 - mmengine - INFO - Epoch(train) [755][55/63] lr: 8.8651e-04 eta: 4:42:27 time: 0.6753 data_time: 0.0296 memory: 14901 loss: 1.2535 loss_prob: 0.6844 loss_thr: 0.4547 loss_db: 0.1145 2022/11/02 20:37:09 - mmengine - INFO - Epoch(train) [755][60/63] lr: 8.8651e-04 eta: 4:42:22 time: 0.6824 data_time: 0.0100 memory: 14901 loss: 1.4979 loss_prob: 0.8903 loss_thr: 0.4655 loss_db: 0.1421 2022/11/02 20:37:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:37:17 - mmengine - INFO - Epoch(train) [756][5/63] lr: 8.8472e-04 eta: 4:42:22 time: 0.9401 data_time: 0.2553 memory: 14901 loss: 1.5446 loss_prob: 0.8957 loss_thr: 0.5120 loss_db: 0.1370 2022/11/02 20:37:21 - mmengine - INFO - Epoch(train) [756][10/63] lr: 8.8472e-04 eta: 4:42:15 time: 0.9943 data_time: 0.2566 memory: 14901 loss: 1.5876 loss_prob: 0.9243 loss_thr: 0.5178 loss_db: 0.1456 2022/11/02 20:37:24 - mmengine - INFO - Epoch(train) [756][15/63] lr: 8.8472e-04 eta: 4:42:15 time: 0.6883 data_time: 0.0142 memory: 14901 loss: 1.4402 loss_prob: 0.8027 loss_thr: 0.4993 loss_db: 0.1382 2022/11/02 20:37:26 - mmengine - INFO - Epoch(train) [756][20/63] lr: 8.8472e-04 eta: 4:42:09 time: 0.5441 data_time: 0.0124 memory: 14901 loss: 1.4005 loss_prob: 0.7686 loss_thr: 0.5009 loss_db: 0.1310 2022/11/02 20:37:29 - mmengine - INFO - Epoch(train) [756][25/63] lr: 8.8472e-04 eta: 4:42:09 time: 0.5757 data_time: 0.0269 memory: 14901 loss: 1.2514 loss_prob: 0.6793 loss_thr: 0.4554 loss_db: 0.1166 2022/11/02 20:37:33 - mmengine - INFO - Epoch(train) [756][30/63] lr: 8.8472e-04 eta: 4:42:03 time: 0.6148 data_time: 0.0460 memory: 14901 loss: 1.1917 loss_prob: 0.6431 loss_thr: 0.4407 loss_db: 0.1079 2022/11/02 20:37:35 - mmengine - INFO - Epoch(train) [756][35/63] lr: 8.8472e-04 eta: 4:42:03 time: 0.5961 data_time: 0.0316 memory: 14901 loss: 1.2175 loss_prob: 0.6598 loss_thr: 0.4481 loss_db: 0.1096 2022/11/02 20:37:39 - mmengine - INFO - Epoch(train) [756][40/63] lr: 8.8472e-04 eta: 4:41:57 time: 0.6235 data_time: 0.0118 memory: 14901 loss: 1.1960 loss_prob: 0.6472 loss_thr: 0.4382 loss_db: 0.1106 2022/11/02 20:37:42 - mmengine - INFO - Epoch(train) [756][45/63] lr: 8.8472e-04 eta: 4:41:57 time: 0.6677 data_time: 0.0102 memory: 14901 loss: 1.1988 loss_prob: 0.6390 loss_thr: 0.4489 loss_db: 0.1109 2022/11/02 20:37:46 - mmengine - INFO - Epoch(train) [756][50/63] lr: 8.8472e-04 eta: 4:41:51 time: 0.6963 data_time: 0.0261 memory: 14901 loss: 1.2068 loss_prob: 0.6466 loss_thr: 0.4473 loss_db: 0.1129 2022/11/02 20:37:49 - mmengine - INFO - Epoch(train) [756][55/63] lr: 8.8472e-04 eta: 4:41:51 time: 0.7392 data_time: 0.0324 memory: 14901 loss: 1.1758 loss_prob: 0.6305 loss_thr: 0.4384 loss_db: 0.1069 2022/11/02 20:37:52 - mmengine - INFO - Epoch(train) [756][60/63] lr: 8.8472e-04 eta: 4:41:46 time: 0.6521 data_time: 0.0167 memory: 14901 loss: 1.2413 loss_prob: 0.6734 loss_thr: 0.4542 loss_db: 0.1137 2022/11/02 20:37:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:38:02 - mmengine - INFO - Epoch(train) [757][5/63] lr: 8.8292e-04 eta: 4:41:46 time: 1.1083 data_time: 0.3044 memory: 14901 loss: 1.2446 loss_prob: 0.6721 loss_thr: 0.4543 loss_db: 0.1183 2022/11/02 20:38:05 - mmengine - INFO - Epoch(train) [757][10/63] lr: 8.8292e-04 eta: 4:41:40 time: 1.0906 data_time: 0.3055 memory: 14901 loss: 1.1895 loss_prob: 0.6364 loss_thr: 0.4441 loss_db: 0.1090 2022/11/02 20:38:08 - mmengine - INFO - Epoch(train) [757][15/63] lr: 8.8292e-04 eta: 4:41:40 time: 0.6057 data_time: 0.0154 memory: 14901 loss: 1.1335 loss_prob: 0.6005 loss_thr: 0.4307 loss_db: 0.1023 2022/11/02 20:38:12 - mmengine - INFO - Epoch(train) [757][20/63] lr: 8.8292e-04 eta: 4:41:34 time: 0.6736 data_time: 0.0168 memory: 14901 loss: 1.2518 loss_prob: 0.6934 loss_thr: 0.4378 loss_db: 0.1207 2022/11/02 20:38:16 - mmengine - INFO - Epoch(train) [757][25/63] lr: 8.8292e-04 eta: 4:41:34 time: 0.7704 data_time: 0.0224 memory: 14901 loss: 1.2784 loss_prob: 0.7131 loss_thr: 0.4425 loss_db: 0.1227 2022/11/02 20:38:19 - mmengine - INFO - Epoch(train) [757][30/63] lr: 8.8292e-04 eta: 4:41:28 time: 0.6724 data_time: 0.0394 memory: 14901 loss: 1.2006 loss_prob: 0.6533 loss_thr: 0.4376 loss_db: 0.1097 2022/11/02 20:38:22 - mmengine - INFO - Epoch(train) [757][35/63] lr: 8.8292e-04 eta: 4:41:28 time: 0.5924 data_time: 0.0316 memory: 14901 loss: 1.1690 loss_prob: 0.6348 loss_thr: 0.4283 loss_db: 0.1058 2022/11/02 20:38:25 - mmengine - INFO - Epoch(train) [757][40/63] lr: 8.8292e-04 eta: 4:41:23 time: 0.6700 data_time: 0.0108 memory: 14901 loss: 1.2157 loss_prob: 0.6643 loss_thr: 0.4390 loss_db: 0.1124 2022/11/02 20:38:29 - mmengine - INFO - Epoch(train) [757][45/63] lr: 8.8292e-04 eta: 4:41:23 time: 0.6824 data_time: 0.0142 memory: 14901 loss: 1.3011 loss_prob: 0.7127 loss_thr: 0.4662 loss_db: 0.1221 2022/11/02 20:38:31 - mmengine - INFO - Epoch(train) [757][50/63] lr: 8.8292e-04 eta: 4:41:16 time: 0.5916 data_time: 0.0323 memory: 14901 loss: 1.1916 loss_prob: 0.6424 loss_thr: 0.4409 loss_db: 0.1083 2022/11/02 20:38:35 - mmengine - INFO - Epoch(train) [757][55/63] lr: 8.8292e-04 eta: 4:41:16 time: 0.5920 data_time: 0.0277 memory: 14901 loss: 1.1193 loss_prob: 0.5956 loss_thr: 0.4227 loss_db: 0.1010 2022/11/02 20:38:38 - mmengine - INFO - Epoch(train) [757][60/63] lr: 8.8292e-04 eta: 4:41:11 time: 0.6264 data_time: 0.0097 memory: 14901 loss: 1.2364 loss_prob: 0.6603 loss_thr: 0.4627 loss_db: 0.1134 2022/11/02 20:38:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:38:48 - mmengine - INFO - Epoch(train) [758][5/63] lr: 8.8113e-04 eta: 4:41:11 time: 1.1455 data_time: 0.2689 memory: 14901 loss: 1.1649 loss_prob: 0.6266 loss_thr: 0.4314 loss_db: 0.1069 2022/11/02 20:38:52 - mmengine - INFO - Epoch(train) [758][10/63] lr: 8.8113e-04 eta: 4:41:05 time: 1.2205 data_time: 0.2679 memory: 14901 loss: 1.1832 loss_prob: 0.6401 loss_thr: 0.4352 loss_db: 0.1079 2022/11/02 20:38:55 - mmengine - INFO - Epoch(train) [758][15/63] lr: 8.8113e-04 eta: 4:41:05 time: 0.6805 data_time: 0.0498 memory: 14901 loss: 1.1464 loss_prob: 0.6065 loss_thr: 0.4344 loss_db: 0.1055 2022/11/02 20:38:57 - mmengine - INFO - Epoch(train) [758][20/63] lr: 8.8113e-04 eta: 4:40:59 time: 0.5583 data_time: 0.0494 memory: 14901 loss: 1.1281 loss_prob: 0.5896 loss_thr: 0.4349 loss_db: 0.1037 2022/11/02 20:39:00 - mmengine - INFO - Epoch(train) [758][25/63] lr: 8.8113e-04 eta: 4:40:59 time: 0.5328 data_time: 0.0105 memory: 14901 loss: 1.0958 loss_prob: 0.5708 loss_thr: 0.4253 loss_db: 0.0997 2022/11/02 20:39:04 - mmengine - INFO - Epoch(train) [758][30/63] lr: 8.8113e-04 eta: 4:40:53 time: 0.6524 data_time: 0.0120 memory: 14901 loss: 1.0708 loss_prob: 0.5605 loss_thr: 0.4119 loss_db: 0.0983 2022/11/02 20:39:07 - mmengine - INFO - Epoch(train) [758][35/63] lr: 8.8113e-04 eta: 4:40:53 time: 0.7083 data_time: 0.0092 memory: 14901 loss: 1.0963 loss_prob: 0.5740 loss_thr: 0.4230 loss_db: 0.0993 2022/11/02 20:39:10 - mmengine - INFO - Epoch(train) [758][40/63] lr: 8.8113e-04 eta: 4:40:47 time: 0.6314 data_time: 0.0303 memory: 14901 loss: 1.1147 loss_prob: 0.5862 loss_thr: 0.4286 loss_db: 0.0999 2022/11/02 20:39:13 - mmengine - INFO - Epoch(train) [758][45/63] lr: 8.8113e-04 eta: 4:40:47 time: 0.6132 data_time: 0.0329 memory: 14901 loss: 1.1710 loss_prob: 0.6264 loss_thr: 0.4366 loss_db: 0.1080 2022/11/02 20:39:17 - mmengine - INFO - Epoch(train) [758][50/63] lr: 8.8113e-04 eta: 4:40:42 time: 0.6707 data_time: 0.0110 memory: 14901 loss: 1.2334 loss_prob: 0.6718 loss_thr: 0.4482 loss_db: 0.1133 2022/11/02 20:39:19 - mmengine - INFO - Epoch(train) [758][55/63] lr: 8.8113e-04 eta: 4:40:42 time: 0.6073 data_time: 0.0126 memory: 14901 loss: 1.3434 loss_prob: 0.7666 loss_thr: 0.4445 loss_db: 0.1323 2022/11/02 20:39:22 - mmengine - INFO - Epoch(train) [758][60/63] lr: 8.8113e-04 eta: 4:40:35 time: 0.5422 data_time: 0.0148 memory: 14901 loss: 1.3968 loss_prob: 0.7910 loss_thr: 0.4637 loss_db: 0.1421 2022/11/02 20:39:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:39:31 - mmengine - INFO - Epoch(train) [759][5/63] lr: 8.7934e-04 eta: 4:40:35 time: 0.9466 data_time: 0.2674 memory: 14901 loss: 1.2906 loss_prob: 0.7051 loss_thr: 0.4623 loss_db: 0.1231 2022/11/02 20:39:35 - mmengine - INFO - Epoch(train) [759][10/63] lr: 8.7934e-04 eta: 4:40:29 time: 1.0948 data_time: 0.2715 memory: 14901 loss: 1.2641 loss_prob: 0.6818 loss_thr: 0.4716 loss_db: 0.1108 2022/11/02 20:39:38 - mmengine - INFO - Epoch(train) [759][15/63] lr: 8.7934e-04 eta: 4:40:29 time: 0.7267 data_time: 0.0234 memory: 14901 loss: 1.2829 loss_prob: 0.6935 loss_thr: 0.4749 loss_db: 0.1146 2022/11/02 20:39:42 - mmengine - INFO - Epoch(train) [759][20/63] lr: 8.7934e-04 eta: 4:40:24 time: 0.7317 data_time: 0.0098 memory: 14901 loss: 1.2558 loss_prob: 0.6739 loss_thr: 0.4647 loss_db: 0.1173 2022/11/02 20:39:45 - mmengine - INFO - Epoch(train) [759][25/63] lr: 8.7934e-04 eta: 4:40:24 time: 0.7137 data_time: 0.0139 memory: 14901 loss: 1.1107 loss_prob: 0.5870 loss_thr: 0.4203 loss_db: 0.1034 2022/11/02 20:39:48 - mmengine - INFO - Epoch(train) [759][30/63] lr: 8.7934e-04 eta: 4:40:18 time: 0.5870 data_time: 0.0326 memory: 14901 loss: 1.1186 loss_prob: 0.5959 loss_thr: 0.4202 loss_db: 0.1025 2022/11/02 20:39:51 - mmengine - INFO - Epoch(train) [759][35/63] lr: 8.7934e-04 eta: 4:40:18 time: 0.5676 data_time: 0.0383 memory: 14901 loss: 1.1433 loss_prob: 0.6110 loss_thr: 0.4267 loss_db: 0.1055 2022/11/02 20:39:54 - mmengine - INFO - Epoch(train) [759][40/63] lr: 8.7934e-04 eta: 4:40:12 time: 0.5926 data_time: 0.0193 memory: 14901 loss: 1.0846 loss_prob: 0.5709 loss_thr: 0.4128 loss_db: 0.1009 2022/11/02 20:39:56 - mmengine - INFO - Epoch(train) [759][45/63] lr: 8.7934e-04 eta: 4:40:12 time: 0.5681 data_time: 0.0065 memory: 14901 loss: 1.0842 loss_prob: 0.5721 loss_thr: 0.4152 loss_db: 0.0969 2022/11/02 20:39:59 - mmengine - INFO - Epoch(train) [759][50/63] lr: 8.7934e-04 eta: 4:40:05 time: 0.5145 data_time: 0.0199 memory: 14901 loss: 1.1594 loss_prob: 0.6183 loss_thr: 0.4347 loss_db: 0.1064 2022/11/02 20:40:02 - mmengine - INFO - Epoch(train) [759][55/63] lr: 8.7934e-04 eta: 4:40:05 time: 0.5218 data_time: 0.0207 memory: 14901 loss: 1.1687 loss_prob: 0.6203 loss_thr: 0.4387 loss_db: 0.1097 2022/11/02 20:40:05 - mmengine - INFO - Epoch(train) [759][60/63] lr: 8.7934e-04 eta: 4:39:59 time: 0.5932 data_time: 0.0163 memory: 14901 loss: 1.2241 loss_prob: 0.6621 loss_thr: 0.4505 loss_db: 0.1115 2022/11/02 20:40:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:40:14 - mmengine - INFO - Epoch(train) [760][5/63] lr: 8.7754e-04 eta: 4:39:59 time: 1.0808 data_time: 0.2808 memory: 14901 loss: 1.1726 loss_prob: 0.6325 loss_thr: 0.4362 loss_db: 0.1040 2022/11/02 20:40:17 - mmengine - INFO - Epoch(train) [760][10/63] lr: 8.7754e-04 eta: 4:39:53 time: 1.0523 data_time: 0.2795 memory: 14901 loss: 1.1816 loss_prob: 0.6409 loss_thr: 0.4353 loss_db: 0.1053 2022/11/02 20:40:20 - mmengine - INFO - Epoch(train) [760][15/63] lr: 8.7754e-04 eta: 4:39:53 time: 0.5578 data_time: 0.0101 memory: 14901 loss: 1.1324 loss_prob: 0.5951 loss_thr: 0.4357 loss_db: 0.1017 2022/11/02 20:40:23 - mmengine - INFO - Epoch(train) [760][20/63] lr: 8.7754e-04 eta: 4:39:47 time: 0.6253 data_time: 0.0103 memory: 14901 loss: 1.1053 loss_prob: 0.5783 loss_thr: 0.4280 loss_db: 0.0990 2022/11/02 20:40:26 - mmengine - INFO - Epoch(train) [760][25/63] lr: 8.7754e-04 eta: 4:39:47 time: 0.6164 data_time: 0.0303 memory: 14901 loss: 1.2930 loss_prob: 0.7158 loss_thr: 0.4633 loss_db: 0.1139 2022/11/02 20:40:29 - mmengine - INFO - Epoch(train) [760][30/63] lr: 8.7754e-04 eta: 4:39:41 time: 0.5930 data_time: 0.0403 memory: 14901 loss: 1.2894 loss_prob: 0.7137 loss_thr: 0.4601 loss_db: 0.1156 2022/11/02 20:40:32 - mmengine - INFO - Epoch(train) [760][35/63] lr: 8.7754e-04 eta: 4:39:41 time: 0.5786 data_time: 0.0201 memory: 14901 loss: 1.0917 loss_prob: 0.5757 loss_thr: 0.4135 loss_db: 0.1024 2022/11/02 20:40:36 - mmengine - INFO - Epoch(train) [760][40/63] lr: 8.7754e-04 eta: 4:39:35 time: 0.6698 data_time: 0.0107 memory: 14901 loss: 1.1368 loss_prob: 0.6085 loss_thr: 0.4230 loss_db: 0.1054 2022/11/02 20:40:39 - mmengine - INFO - Epoch(train) [760][45/63] lr: 8.7754e-04 eta: 4:39:35 time: 0.6726 data_time: 0.0120 memory: 14901 loss: 1.1758 loss_prob: 0.6270 loss_thr: 0.4435 loss_db: 0.1053 2022/11/02 20:40:42 - mmengine - INFO - Epoch(train) [760][50/63] lr: 8.7754e-04 eta: 4:39:29 time: 0.5761 data_time: 0.0248 memory: 14901 loss: 1.1347 loss_prob: 0.5968 loss_thr: 0.4377 loss_db: 0.1002 2022/11/02 20:40:44 - mmengine - INFO - Epoch(train) [760][55/63] lr: 8.7754e-04 eta: 4:39:29 time: 0.5688 data_time: 0.0297 memory: 14901 loss: 1.1216 loss_prob: 0.5941 loss_thr: 0.4247 loss_db: 0.1028 2022/11/02 20:40:47 - mmengine - INFO - Epoch(train) [760][60/63] lr: 8.7754e-04 eta: 4:39:22 time: 0.5512 data_time: 0.0151 memory: 14901 loss: 1.1238 loss_prob: 0.6079 loss_thr: 0.4095 loss_db: 0.1064 2022/11/02 20:40:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:40:49 - mmengine - INFO - Saving checkpoint at 760 epochs 2022/11/02 20:40:53 - mmengine - INFO - Epoch(val) [760][5/500] eta: 4:39:22 time: 0.0453 data_time: 0.0056 memory: 14901 2022/11/02 20:40:53 - mmengine - INFO - Epoch(val) [760][10/500] eta: 0:00:22 time: 0.0450 data_time: 0.0053 memory: 1008 2022/11/02 20:40:54 - mmengine - INFO - Epoch(val) [760][15/500] eta: 0:00:22 time: 0.0418 data_time: 0.0026 memory: 1008 2022/11/02 20:40:54 - mmengine - INFO - Epoch(val) [760][20/500] eta: 0:00:20 time: 0.0437 data_time: 0.0030 memory: 1008 2022/11/02 20:40:54 - mmengine - INFO - Epoch(val) [760][25/500] eta: 0:00:20 time: 0.0428 data_time: 0.0033 memory: 1008 2022/11/02 20:40:54 - mmengine - INFO - Epoch(val) [760][30/500] eta: 0:00:22 time: 0.0470 data_time: 0.0031 memory: 1008 2022/11/02 20:40:54 - mmengine - INFO - Epoch(val) [760][35/500] eta: 0:00:22 time: 0.0447 data_time: 0.0027 memory: 1008 2022/11/02 20:40:55 - mmengine - INFO - Epoch(val) [760][40/500] eta: 0:00:20 time: 0.0455 data_time: 0.0026 memory: 1008 2022/11/02 20:40:55 - mmengine - INFO - Epoch(val) [760][45/500] eta: 0:00:20 time: 0.0476 data_time: 0.0026 memory: 1008 2022/11/02 20:40:55 - mmengine - INFO - Epoch(val) [760][50/500] eta: 0:00:18 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/02 20:40:55 - mmengine - INFO - Epoch(val) [760][55/500] eta: 0:00:18 time: 0.0463 data_time: 0.0028 memory: 1008 2022/11/02 20:40:56 - mmengine - INFO - Epoch(val) [760][60/500] eta: 0:00:20 time: 0.0466 data_time: 0.0029 memory: 1008 2022/11/02 20:40:56 - mmengine - INFO - Epoch(val) [760][65/500] eta: 0:00:20 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 20:40:56 - mmengine - INFO - Epoch(val) [760][70/500] eta: 0:00:18 time: 0.0439 data_time: 0.0026 memory: 1008 2022/11/02 20:40:56 - mmengine - INFO - Epoch(val) [760][75/500] eta: 0:00:18 time: 0.0407 data_time: 0.0028 memory: 1008 2022/11/02 20:40:56 - mmengine - INFO - Epoch(val) [760][80/500] eta: 0:00:16 time: 0.0397 data_time: 0.0031 memory: 1008 2022/11/02 20:40:57 - mmengine - INFO - Epoch(val) [760][85/500] eta: 0:00:16 time: 0.0388 data_time: 0.0029 memory: 1008 2022/11/02 20:40:57 - mmengine - INFO - Epoch(val) [760][90/500] eta: 0:00:16 time: 0.0412 data_time: 0.0029 memory: 1008 2022/11/02 20:40:57 - mmengine - INFO - Epoch(val) [760][95/500] eta: 0:00:16 time: 0.0432 data_time: 0.0030 memory: 1008 2022/11/02 20:40:57 - mmengine - INFO - Epoch(val) [760][100/500] eta: 0:00:16 time: 0.0423 data_time: 0.0033 memory: 1008 2022/11/02 20:40:58 - mmengine - INFO - Epoch(val) [760][105/500] eta: 0:00:16 time: 0.0443 data_time: 0.0033 memory: 1008 2022/11/02 20:40:58 - mmengine - INFO - Epoch(val) [760][110/500] eta: 0:00:17 time: 0.0453 data_time: 0.0032 memory: 1008 2022/11/02 20:40:58 - mmengine - INFO - Epoch(val) [760][115/500] eta: 0:00:17 time: 0.0484 data_time: 0.0035 memory: 1008 2022/11/02 20:40:58 - mmengine - INFO - Epoch(val) [760][120/500] eta: 0:00:18 time: 0.0480 data_time: 0.0036 memory: 1008 2022/11/02 20:40:58 - mmengine - INFO - Epoch(val) [760][125/500] eta: 0:00:18 time: 0.0434 data_time: 0.0032 memory: 1008 2022/11/02 20:40:59 - mmengine - INFO - Epoch(val) [760][130/500] eta: 0:00:15 time: 0.0406 data_time: 0.0028 memory: 1008 2022/11/02 20:40:59 - mmengine - INFO - Epoch(val) [760][135/500] eta: 0:00:15 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 20:40:59 - mmengine - INFO - Epoch(val) [760][140/500] eta: 0:00:15 time: 0.0435 data_time: 0.0029 memory: 1008 2022/11/02 20:40:59 - mmengine - INFO - Epoch(val) [760][145/500] eta: 0:00:15 time: 0.0464 data_time: 0.0030 memory: 1008 2022/11/02 20:41:00 - mmengine - INFO - Epoch(val) [760][150/500] eta: 0:00:14 time: 0.0422 data_time: 0.0027 memory: 1008 2022/11/02 20:41:00 - mmengine - INFO - Epoch(val) [760][155/500] eta: 0:00:14 time: 0.0454 data_time: 0.0031 memory: 1008 2022/11/02 20:41:00 - mmengine - INFO - Epoch(val) [760][160/500] eta: 0:00:15 time: 0.0464 data_time: 0.0030 memory: 1008 2022/11/02 20:41:00 - mmengine - INFO - Epoch(val) [760][165/500] eta: 0:00:15 time: 0.0476 data_time: 0.0029 memory: 1008 2022/11/02 20:41:00 - mmengine - INFO - Epoch(val) [760][170/500] eta: 0:00:16 time: 0.0493 data_time: 0.0031 memory: 1008 2022/11/02 20:41:01 - mmengine - INFO - Epoch(val) [760][175/500] eta: 0:00:16 time: 0.0422 data_time: 0.0029 memory: 1008 2022/11/02 20:41:01 - mmengine - INFO - Epoch(val) [760][180/500] eta: 0:00:13 time: 0.0410 data_time: 0.0030 memory: 1008 2022/11/02 20:41:01 - mmengine - INFO - Epoch(val) [760][185/500] eta: 0:00:13 time: 0.0452 data_time: 0.0032 memory: 1008 2022/11/02 20:41:01 - mmengine - INFO - Epoch(val) [760][190/500] eta: 0:00:14 time: 0.0483 data_time: 0.0041 memory: 1008 2022/11/02 20:41:02 - mmengine - INFO - Epoch(val) [760][195/500] eta: 0:00:14 time: 0.0461 data_time: 0.0040 memory: 1008 2022/11/02 20:41:02 - mmengine - INFO - Epoch(val) [760][200/500] eta: 0:00:14 time: 0.0495 data_time: 0.0027 memory: 1008 2022/11/02 20:41:02 - mmengine - INFO - Epoch(val) [760][205/500] eta: 0:00:14 time: 0.0482 data_time: 0.0025 memory: 1008 2022/11/02 20:41:02 - mmengine - INFO - Epoch(val) [760][210/500] eta: 0:00:11 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 20:41:02 - mmengine - INFO - Epoch(val) [760][215/500] eta: 0:00:11 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 20:41:03 - mmengine - INFO - Epoch(val) [760][220/500] eta: 0:00:11 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/02 20:41:03 - mmengine - INFO - Epoch(val) [760][225/500] eta: 0:00:11 time: 0.0421 data_time: 0.0027 memory: 1008 2022/11/02 20:41:03 - mmengine - INFO - Epoch(val) [760][230/500] eta: 0:00:11 time: 0.0437 data_time: 0.0030 memory: 1008 2022/11/02 20:41:03 - mmengine - INFO - Epoch(val) [760][235/500] eta: 0:00:11 time: 0.0429 data_time: 0.0031 memory: 1008 2022/11/02 20:41:04 - mmengine - INFO - Epoch(val) [760][240/500] eta: 0:00:11 time: 0.0439 data_time: 0.0030 memory: 1008 2022/11/02 20:41:04 - mmengine - INFO - Epoch(val) [760][245/500] eta: 0:00:11 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 20:41:04 - mmengine - INFO - Epoch(val) [760][250/500] eta: 0:00:10 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 20:41:04 - mmengine - INFO - Epoch(val) [760][255/500] eta: 0:00:10 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/02 20:41:04 - mmengine - INFO - Epoch(val) [760][260/500] eta: 0:00:10 time: 0.0431 data_time: 0.0031 memory: 1008 2022/11/02 20:41:05 - mmengine - INFO - Epoch(val) [760][265/500] eta: 0:00:10 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/02 20:41:05 - mmengine - INFO - Epoch(val) [760][270/500] eta: 0:00:09 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/02 20:41:05 - mmengine - INFO - Epoch(val) [760][275/500] eta: 0:00:09 time: 0.0446 data_time: 0.0032 memory: 1008 2022/11/02 20:41:05 - mmengine - INFO - Epoch(val) [760][280/500] eta: 0:00:10 time: 0.0463 data_time: 0.0031 memory: 1008 2022/11/02 20:41:05 - mmengine - INFO - Epoch(val) [760][285/500] eta: 0:00:10 time: 0.0422 data_time: 0.0026 memory: 1008 2022/11/02 20:41:06 - mmengine - INFO - Epoch(val) [760][290/500] eta: 0:00:09 time: 0.0443 data_time: 0.0027 memory: 1008 2022/11/02 20:41:06 - mmengine - INFO - Epoch(val) [760][295/500] eta: 0:00:09 time: 0.0467 data_time: 0.0028 memory: 1008 2022/11/02 20:41:06 - mmengine - INFO - Epoch(val) [760][300/500] eta: 0:00:08 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/02 20:41:06 - mmengine - INFO - Epoch(val) [760][305/500] eta: 0:00:08 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 20:41:07 - mmengine - INFO - Epoch(val) [760][310/500] eta: 0:00:07 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 20:41:07 - mmengine - INFO - Epoch(val) [760][315/500] eta: 0:00:07 time: 0.0480 data_time: 0.0027 memory: 1008 2022/11/02 20:41:07 - mmengine - INFO - Epoch(val) [760][320/500] eta: 0:00:08 time: 0.0487 data_time: 0.0029 memory: 1008 2022/11/02 20:41:07 - mmengine - INFO - Epoch(val) [760][325/500] eta: 0:00:08 time: 0.0622 data_time: 0.0030 memory: 1008 2022/11/02 20:41:08 - mmengine - INFO - Epoch(val) [760][330/500] eta: 0:00:10 time: 0.0608 data_time: 0.0029 memory: 1008 2022/11/02 20:41:08 - mmengine - INFO - Epoch(val) [760][335/500] eta: 0:00:10 time: 0.0376 data_time: 0.0026 memory: 1008 2022/11/02 20:41:08 - mmengine - INFO - Epoch(val) [760][340/500] eta: 0:00:08 time: 0.0539 data_time: 0.0026 memory: 1008 2022/11/02 20:41:08 - mmengine - INFO - Epoch(val) [760][345/500] eta: 0:00:08 time: 0.0578 data_time: 0.0027 memory: 1008 2022/11/02 20:41:09 - mmengine - INFO - Epoch(val) [760][350/500] eta: 0:00:07 time: 0.0468 data_time: 0.0028 memory: 1008 2022/11/02 20:41:09 - mmengine - INFO - Epoch(val) [760][355/500] eta: 0:00:07 time: 0.0433 data_time: 0.0027 memory: 1008 2022/11/02 20:41:09 - mmengine - INFO - Epoch(val) [760][360/500] eta: 0:00:05 time: 0.0394 data_time: 0.0025 memory: 1008 2022/11/02 20:41:09 - mmengine - INFO - Epoch(val) [760][365/500] eta: 0:00:05 time: 0.0412 data_time: 0.0027 memory: 1008 2022/11/02 20:41:09 - mmengine - INFO - Epoch(val) [760][370/500] eta: 0:00:05 time: 0.0406 data_time: 0.0032 memory: 1008 2022/11/02 20:41:10 - mmengine - INFO - Epoch(val) [760][375/500] eta: 0:00:05 time: 0.0381 data_time: 0.0032 memory: 1008 2022/11/02 20:41:10 - mmengine - INFO - Epoch(val) [760][380/500] eta: 0:00:05 time: 0.0441 data_time: 0.0028 memory: 1008 2022/11/02 20:41:10 - mmengine - INFO - Epoch(val) [760][385/500] eta: 0:00:05 time: 0.0496 data_time: 0.0032 memory: 1008 2022/11/02 20:41:10 - mmengine - INFO - Epoch(val) [760][390/500] eta: 0:00:05 time: 0.0463 data_time: 0.0037 memory: 1008 2022/11/02 20:41:11 - mmengine - INFO - Epoch(val) [760][395/500] eta: 0:00:05 time: 0.0425 data_time: 0.0033 memory: 1008 2022/11/02 20:41:11 - mmengine - INFO - Epoch(val) [760][400/500] eta: 0:00:04 time: 0.0411 data_time: 0.0029 memory: 1008 2022/11/02 20:41:11 - mmengine - INFO - Epoch(val) [760][405/500] eta: 0:00:04 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 20:41:11 - mmengine - INFO - Epoch(val) [760][410/500] eta: 0:00:03 time: 0.0428 data_time: 0.0026 memory: 1008 2022/11/02 20:41:11 - mmengine - INFO - Epoch(val) [760][415/500] eta: 0:00:03 time: 0.0412 data_time: 0.0026 memory: 1008 2022/11/02 20:41:12 - mmengine - INFO - Epoch(val) [760][420/500] eta: 0:00:03 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 20:41:12 - mmengine - INFO - Epoch(val) [760][425/500] eta: 0:00:03 time: 0.0408 data_time: 0.0029 memory: 1008 2022/11/02 20:41:12 - mmengine - INFO - Epoch(val) [760][430/500] eta: 0:00:02 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/02 20:41:12 - mmengine - INFO - Epoch(val) [760][435/500] eta: 0:00:02 time: 0.0429 data_time: 0.0032 memory: 1008 2022/11/02 20:41:12 - mmengine - INFO - Epoch(val) [760][440/500] eta: 0:00:02 time: 0.0470 data_time: 0.0034 memory: 1008 2022/11/02 20:41:13 - mmengine - INFO - Epoch(val) [760][445/500] eta: 0:00:02 time: 0.0463 data_time: 0.0032 memory: 1008 2022/11/02 20:41:13 - mmengine - INFO - Epoch(val) [760][450/500] eta: 0:00:02 time: 0.0428 data_time: 0.0029 memory: 1008 2022/11/02 20:41:13 - mmengine - INFO - Epoch(val) [760][455/500] eta: 0:00:02 time: 0.0464 data_time: 0.0032 memory: 1008 2022/11/02 20:41:13 - mmengine - INFO - Epoch(val) [760][460/500] eta: 0:00:01 time: 0.0450 data_time: 0.0031 memory: 1008 2022/11/02 20:41:14 - mmengine - INFO - Epoch(val) [760][465/500] eta: 0:00:01 time: 0.0385 data_time: 0.0027 memory: 1008 2022/11/02 20:41:14 - mmengine - INFO - Epoch(val) [760][470/500] eta: 0:00:01 time: 0.0401 data_time: 0.0028 memory: 1008 2022/11/02 20:41:14 - mmengine - INFO - Epoch(val) [760][475/500] eta: 0:00:01 time: 0.0423 data_time: 0.0031 memory: 1008 2022/11/02 20:41:14 - mmengine - INFO - Epoch(val) [760][480/500] eta: 0:00:00 time: 0.0427 data_time: 0.0031 memory: 1008 2022/11/02 20:41:14 - mmengine - INFO - Epoch(val) [760][485/500] eta: 0:00:00 time: 0.0457 data_time: 0.0037 memory: 1008 2022/11/02 20:41:15 - mmengine - INFO - Epoch(val) [760][490/500] eta: 0:00:00 time: 0.0441 data_time: 0.0035 memory: 1008 2022/11/02 20:41:15 - mmengine - INFO - Epoch(val) [760][495/500] eta: 0:00:00 time: 0.0432 data_time: 0.0026 memory: 1008 2022/11/02 20:41:15 - mmengine - INFO - Epoch(val) [760][500/500] eta: 0:00:00 time: 0.0422 data_time: 0.0028 memory: 1008 2022/11/02 20:41:15 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8320, precision: 0.6931, hmean: 0.7562 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8320, precision: 0.7569, hmean: 0.7927 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8315, precision: 0.7944, hmean: 0.8125 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8252, precision: 0.8276, hmean: 0.8264 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8055, precision: 0.8637, hmean: 0.8336 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6553, precision: 0.9190, hmean: 0.7650 2022/11/02 20:41:15 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0929, precision: 0.9324, hmean: 0.1690 2022/11/02 20:41:15 - mmengine - INFO - Epoch(val) [760][500/500] icdar/precision: 0.8637 icdar/recall: 0.8055 icdar/hmean: 0.8336 2022/11/02 20:41:21 - mmengine - INFO - Epoch(train) [761][5/63] lr: 8.7575e-04 eta: 0:00:00 time: 0.8562 data_time: 0.2370 memory: 14901 loss: 1.1608 loss_prob: 0.6370 loss_thr: 0.4159 loss_db: 0.1079 2022/11/02 20:41:24 - mmengine - INFO - Epoch(train) [761][10/63] lr: 8.7575e-04 eta: 4:39:15 time: 0.8715 data_time: 0.2421 memory: 14901 loss: 1.0723 loss_prob: 0.5625 loss_thr: 0.4140 loss_db: 0.0957 2022/11/02 20:41:28 - mmengine - INFO - Epoch(train) [761][15/63] lr: 8.7575e-04 eta: 4:39:15 time: 0.6531 data_time: 0.0165 memory: 14901 loss: 1.0715 loss_prob: 0.5591 loss_thr: 0.4155 loss_db: 0.0969 2022/11/02 20:41:31 - mmengine - INFO - Epoch(train) [761][20/63] lr: 8.7575e-04 eta: 4:39:10 time: 0.7347 data_time: 0.0114 memory: 14901 loss: 1.0908 loss_prob: 0.5708 loss_thr: 0.4200 loss_db: 0.1001 2022/11/02 20:41:35 - mmengine - INFO - Epoch(train) [761][25/63] lr: 8.7575e-04 eta: 4:39:10 time: 0.7407 data_time: 0.0353 memory: 14901 loss: 1.1415 loss_prob: 0.6056 loss_thr: 0.4299 loss_db: 0.1060 2022/11/02 20:41:39 - mmengine - INFO - Epoch(train) [761][30/63] lr: 8.7575e-04 eta: 4:39:04 time: 0.7322 data_time: 0.0346 memory: 14901 loss: 1.1415 loss_prob: 0.6078 loss_thr: 0.4275 loss_db: 0.1061 2022/11/02 20:41:42 - mmengine - INFO - Epoch(train) [761][35/63] lr: 8.7575e-04 eta: 4:39:04 time: 0.6554 data_time: 0.0174 memory: 14901 loss: 1.0844 loss_prob: 0.5692 loss_thr: 0.4175 loss_db: 0.0977 2022/11/02 20:41:44 - mmengine - INFO - Epoch(train) [761][40/63] lr: 8.7575e-04 eta: 4:38:58 time: 0.5781 data_time: 0.0173 memory: 14901 loss: 1.1275 loss_prob: 0.5966 loss_thr: 0.4285 loss_db: 0.1025 2022/11/02 20:41:47 - mmengine - INFO - Epoch(train) [761][45/63] lr: 8.7575e-04 eta: 4:38:58 time: 0.5796 data_time: 0.0130 memory: 14901 loss: 1.1624 loss_prob: 0.6267 loss_thr: 0.4296 loss_db: 0.1061 2022/11/02 20:41:51 - mmengine - INFO - Epoch(train) [761][50/63] lr: 8.7575e-04 eta: 4:38:52 time: 0.6239 data_time: 0.0268 memory: 14901 loss: 1.1531 loss_prob: 0.6160 loss_thr: 0.4317 loss_db: 0.1054 2022/11/02 20:41:53 - mmengine - INFO - Epoch(train) [761][55/63] lr: 8.7575e-04 eta: 4:38:52 time: 0.5653 data_time: 0.0267 memory: 14901 loss: 1.1437 loss_prob: 0.6052 loss_thr: 0.4327 loss_db: 0.1057 2022/11/02 20:41:56 - mmengine - INFO - Epoch(train) [761][60/63] lr: 8.7575e-04 eta: 4:38:46 time: 0.5130 data_time: 0.0202 memory: 14901 loss: 1.0812 loss_prob: 0.5756 loss_thr: 0.4074 loss_db: 0.0983 2022/11/02 20:41:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:42:03 - mmengine - INFO - Epoch(train) [762][5/63] lr: 8.7395e-04 eta: 4:38:46 time: 0.8126 data_time: 0.2360 memory: 14901 loss: 1.0727 loss_prob: 0.5690 loss_thr: 0.4055 loss_db: 0.0982 2022/11/02 20:42:06 - mmengine - INFO - Epoch(train) [762][10/63] lr: 8.7395e-04 eta: 4:38:38 time: 0.8547 data_time: 0.2381 memory: 14901 loss: 1.0394 loss_prob: 0.5447 loss_thr: 0.4005 loss_db: 0.0941 2022/11/02 20:42:09 - mmengine - INFO - Epoch(train) [762][15/63] lr: 8.7395e-04 eta: 4:38:38 time: 0.5654 data_time: 0.0137 memory: 14901 loss: 1.1016 loss_prob: 0.5842 loss_thr: 0.4156 loss_db: 0.1018 2022/11/02 20:42:11 - mmengine - INFO - Epoch(train) [762][20/63] lr: 8.7395e-04 eta: 4:38:32 time: 0.5516 data_time: 0.0112 memory: 14901 loss: 1.1691 loss_prob: 0.6162 loss_thr: 0.4463 loss_db: 0.1066 2022/11/02 20:42:15 - mmengine - INFO - Epoch(train) [762][25/63] lr: 8.7395e-04 eta: 4:38:32 time: 0.6570 data_time: 0.0364 memory: 14901 loss: 1.1463 loss_prob: 0.5984 loss_thr: 0.4449 loss_db: 0.1030 2022/11/02 20:42:18 - mmengine - INFO - Epoch(train) [762][30/63] lr: 8.7395e-04 eta: 4:38:26 time: 0.6873 data_time: 0.0375 memory: 14901 loss: 1.1035 loss_prob: 0.5778 loss_thr: 0.4246 loss_db: 0.1010 2022/11/02 20:42:21 - mmengine - INFO - Epoch(train) [762][35/63] lr: 8.7395e-04 eta: 4:38:26 time: 0.5582 data_time: 0.0166 memory: 14901 loss: 1.1711 loss_prob: 0.6295 loss_thr: 0.4357 loss_db: 0.1059 2022/11/02 20:42:23 - mmengine - INFO - Epoch(train) [762][40/63] lr: 8.7395e-04 eta: 4:38:20 time: 0.5142 data_time: 0.0155 memory: 14901 loss: 1.1117 loss_prob: 0.5881 loss_thr: 0.4257 loss_db: 0.0979 2022/11/02 20:42:26 - mmengine - INFO - Epoch(train) [762][45/63] lr: 8.7395e-04 eta: 4:38:20 time: 0.5022 data_time: 0.0094 memory: 14901 loss: 1.0461 loss_prob: 0.5418 loss_thr: 0.4097 loss_db: 0.0946 2022/11/02 20:42:28 - mmengine - INFO - Epoch(train) [762][50/63] lr: 8.7395e-04 eta: 4:38:13 time: 0.5328 data_time: 0.0219 memory: 14901 loss: 1.1078 loss_prob: 0.5778 loss_thr: 0.4291 loss_db: 0.1008 2022/11/02 20:42:31 - mmengine - INFO - Epoch(train) [762][55/63] lr: 8.7395e-04 eta: 4:38:13 time: 0.5434 data_time: 0.0200 memory: 14901 loss: 1.1216 loss_prob: 0.5888 loss_thr: 0.4302 loss_db: 0.1026 2022/11/02 20:42:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:42:34 - mmengine - INFO - Epoch(train) [762][60/63] lr: 8.7395e-04 eta: 4:38:07 time: 0.5779 data_time: 0.0115 memory: 14901 loss: 1.0867 loss_prob: 0.5761 loss_thr: 0.4110 loss_db: 0.0997 2022/11/02 20:42:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:42:42 - mmengine - INFO - Epoch(train) [763][5/63] lr: 8.7215e-04 eta: 4:38:07 time: 0.9372 data_time: 0.2661 memory: 14901 loss: 1.1650 loss_prob: 0.6198 loss_thr: 0.4391 loss_db: 0.1061 2022/11/02 20:42:45 - mmengine - INFO - Epoch(train) [763][10/63] lr: 8.7215e-04 eta: 4:38:00 time: 0.9091 data_time: 0.2677 memory: 14901 loss: 1.0946 loss_prob: 0.5774 loss_thr: 0.4182 loss_db: 0.0990 2022/11/02 20:42:48 - mmengine - INFO - Epoch(train) [763][15/63] lr: 8.7215e-04 eta: 4:38:00 time: 0.5356 data_time: 0.0099 memory: 14901 loss: 1.0849 loss_prob: 0.5747 loss_thr: 0.4132 loss_db: 0.0970 2022/11/02 20:42:51 - mmengine - INFO - Epoch(train) [763][20/63] lr: 8.7215e-04 eta: 4:37:54 time: 0.5650 data_time: 0.0091 memory: 14901 loss: 1.1415 loss_prob: 0.6057 loss_thr: 0.4324 loss_db: 0.1034 2022/11/02 20:42:54 - mmengine - INFO - Epoch(train) [763][25/63] lr: 8.7215e-04 eta: 4:37:54 time: 0.6104 data_time: 0.0489 memory: 14901 loss: 1.0581 loss_prob: 0.5535 loss_thr: 0.4072 loss_db: 0.0973 2022/11/02 20:42:56 - mmengine - INFO - Epoch(train) [763][30/63] lr: 8.7215e-04 eta: 4:37:47 time: 0.5755 data_time: 0.0490 memory: 14901 loss: 1.0686 loss_prob: 0.5616 loss_thr: 0.4109 loss_db: 0.0960 2022/11/02 20:42:59 - mmengine - INFO - Epoch(train) [763][35/63] lr: 8.7215e-04 eta: 4:37:47 time: 0.5152 data_time: 0.0091 memory: 14901 loss: 1.1739 loss_prob: 0.6201 loss_thr: 0.4493 loss_db: 0.1045 2022/11/02 20:43:02 - mmengine - INFO - Epoch(train) [763][40/63] lr: 8.7215e-04 eta: 4:37:41 time: 0.5636 data_time: 0.0091 memory: 14901 loss: 1.1806 loss_prob: 0.6221 loss_thr: 0.4529 loss_db: 0.1056 2022/11/02 20:43:05 - mmengine - INFO - Epoch(train) [763][45/63] lr: 8.7215e-04 eta: 4:37:41 time: 0.6495 data_time: 0.0113 memory: 14901 loss: 1.1122 loss_prob: 0.5839 loss_thr: 0.4268 loss_db: 0.1016 2022/11/02 20:43:09 - mmengine - INFO - Epoch(train) [763][50/63] lr: 8.7215e-04 eta: 4:37:35 time: 0.6570 data_time: 0.0275 memory: 14901 loss: 0.9995 loss_prob: 0.5219 loss_thr: 0.3859 loss_db: 0.0916 2022/11/02 20:43:11 - mmengine - INFO - Epoch(train) [763][55/63] lr: 8.7215e-04 eta: 4:37:35 time: 0.5939 data_time: 0.0268 memory: 14901 loss: 1.0974 loss_prob: 0.5823 loss_thr: 0.4148 loss_db: 0.1003 2022/11/02 20:43:14 - mmengine - INFO - Epoch(train) [763][60/63] lr: 8.7215e-04 eta: 4:37:29 time: 0.5245 data_time: 0.0110 memory: 14901 loss: 1.1422 loss_prob: 0.6071 loss_thr: 0.4291 loss_db: 0.1060 2022/11/02 20:43:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:43:21 - mmengine - INFO - Epoch(train) [764][5/63] lr: 8.7036e-04 eta: 4:37:29 time: 0.8222 data_time: 0.2188 memory: 14901 loss: 1.0422 loss_prob: 0.5399 loss_thr: 0.4095 loss_db: 0.0928 2022/11/02 20:43:24 - mmengine - INFO - Epoch(train) [764][10/63] lr: 8.7036e-04 eta: 4:37:21 time: 0.8208 data_time: 0.2321 memory: 14901 loss: 1.1883 loss_prob: 0.6648 loss_thr: 0.4229 loss_db: 0.1006 2022/11/02 20:43:26 - mmengine - INFO - Epoch(train) [764][15/63] lr: 8.7036e-04 eta: 4:37:21 time: 0.5093 data_time: 0.0210 memory: 14901 loss: 1.2408 loss_prob: 0.6922 loss_thr: 0.4402 loss_db: 0.1084 2022/11/02 20:43:29 - mmengine - INFO - Epoch(train) [764][20/63] lr: 8.7036e-04 eta: 4:37:15 time: 0.5016 data_time: 0.0082 memory: 14901 loss: 1.0812 loss_prob: 0.5604 loss_thr: 0.4229 loss_db: 0.0979 2022/11/02 20:43:32 - mmengine - INFO - Epoch(train) [764][25/63] lr: 8.7036e-04 eta: 4:37:15 time: 0.6027 data_time: 0.0235 memory: 14901 loss: 1.0892 loss_prob: 0.5704 loss_thr: 0.4214 loss_db: 0.0974 2022/11/02 20:43:36 - mmengine - INFO - Epoch(train) [764][30/63] lr: 8.7036e-04 eta: 4:37:09 time: 0.7382 data_time: 0.0394 memory: 14901 loss: 1.1947 loss_prob: 0.6379 loss_thr: 0.4485 loss_db: 0.1083 2022/11/02 20:43:39 - mmengine - INFO - Epoch(train) [764][35/63] lr: 8.7036e-04 eta: 4:37:09 time: 0.6916 data_time: 0.0332 memory: 14901 loss: 1.2362 loss_prob: 0.6532 loss_thr: 0.4687 loss_db: 0.1143 2022/11/02 20:43:42 - mmengine - INFO - Epoch(train) [764][40/63] lr: 8.7036e-04 eta: 4:37:03 time: 0.6282 data_time: 0.0199 memory: 14901 loss: 1.1356 loss_prob: 0.5914 loss_thr: 0.4394 loss_db: 0.1047 2022/11/02 20:43:45 - mmengine - INFO - Epoch(train) [764][45/63] lr: 8.7036e-04 eta: 4:37:03 time: 0.6255 data_time: 0.0085 memory: 14901 loss: 1.1331 loss_prob: 0.6094 loss_thr: 0.4195 loss_db: 0.1041 2022/11/02 20:43:48 - mmengine - INFO - Epoch(train) [764][50/63] lr: 8.7036e-04 eta: 4:36:57 time: 0.5657 data_time: 0.0213 memory: 14901 loss: 1.0923 loss_prob: 0.5926 loss_thr: 0.3997 loss_db: 0.1000 2022/11/02 20:43:51 - mmengine - INFO - Epoch(train) [764][55/63] lr: 8.7036e-04 eta: 4:36:57 time: 0.5246 data_time: 0.0246 memory: 14901 loss: 1.0389 loss_prob: 0.5561 loss_thr: 0.3879 loss_db: 0.0949 2022/11/02 20:43:53 - mmengine - INFO - Epoch(train) [764][60/63] lr: 8.7036e-04 eta: 4:36:50 time: 0.5080 data_time: 0.0141 memory: 14901 loss: 1.0965 loss_prob: 0.5818 loss_thr: 0.4146 loss_db: 0.1002 2022/11/02 20:43:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:44:01 - mmengine - INFO - Epoch(train) [765][5/63] lr: 8.6856e-04 eta: 4:36:50 time: 0.8561 data_time: 0.2528 memory: 14901 loss: 1.0820 loss_prob: 0.5513 loss_thr: 0.4353 loss_db: 0.0954 2022/11/02 20:44:03 - mmengine - INFO - Epoch(train) [765][10/63] lr: 8.6856e-04 eta: 4:36:43 time: 0.8746 data_time: 0.2491 memory: 14901 loss: 1.0108 loss_prob: 0.5147 loss_thr: 0.4060 loss_db: 0.0901 2022/11/02 20:44:06 - mmengine - INFO - Epoch(train) [765][15/63] lr: 8.6856e-04 eta: 4:36:43 time: 0.5161 data_time: 0.0102 memory: 14901 loss: 1.0518 loss_prob: 0.5504 loss_thr: 0.4024 loss_db: 0.0990 2022/11/02 20:44:10 - mmengine - INFO - Epoch(train) [765][20/63] lr: 8.6856e-04 eta: 4:36:37 time: 0.6487 data_time: 0.0117 memory: 14901 loss: 1.1225 loss_prob: 0.6009 loss_thr: 0.4177 loss_db: 0.1039 2022/11/02 20:44:13 - mmengine - INFO - Epoch(train) [765][25/63] lr: 8.6856e-04 eta: 4:36:37 time: 0.7482 data_time: 0.0132 memory: 14901 loss: 1.1607 loss_prob: 0.6160 loss_thr: 0.4419 loss_db: 0.1028 2022/11/02 20:44:17 - mmengine - INFO - Epoch(train) [765][30/63] lr: 8.6856e-04 eta: 4:36:32 time: 0.6958 data_time: 0.0346 memory: 14901 loss: 1.1403 loss_prob: 0.5968 loss_thr: 0.4420 loss_db: 0.1015 2022/11/02 20:44:20 - mmengine - INFO - Epoch(train) [765][35/63] lr: 8.6856e-04 eta: 4:36:32 time: 0.6831 data_time: 0.0367 memory: 14901 loss: 1.1050 loss_prob: 0.5799 loss_thr: 0.4227 loss_db: 0.1023 2022/11/02 20:44:23 - mmengine - INFO - Epoch(train) [765][40/63] lr: 8.6856e-04 eta: 4:36:26 time: 0.6205 data_time: 0.0143 memory: 14901 loss: 1.0848 loss_prob: 0.5748 loss_thr: 0.4086 loss_db: 0.1014 2022/11/02 20:44:26 - mmengine - INFO - Epoch(train) [765][45/63] lr: 8.6856e-04 eta: 4:36:26 time: 0.5554 data_time: 0.0080 memory: 14901 loss: 1.0358 loss_prob: 0.5431 loss_thr: 0.3971 loss_db: 0.0956 2022/11/02 20:44:28 - mmengine - INFO - Epoch(train) [765][50/63] lr: 8.6856e-04 eta: 4:36:20 time: 0.5646 data_time: 0.0251 memory: 14901 loss: 1.1003 loss_prob: 0.5807 loss_thr: 0.4195 loss_db: 0.1000 2022/11/02 20:44:32 - mmengine - INFO - Epoch(train) [765][55/63] lr: 8.6856e-04 eta: 4:36:20 time: 0.6314 data_time: 0.0295 memory: 14901 loss: 1.2125 loss_prob: 0.6532 loss_thr: 0.4477 loss_db: 0.1116 2022/11/02 20:44:35 - mmengine - INFO - Epoch(train) [765][60/63] lr: 8.6856e-04 eta: 4:36:14 time: 0.6817 data_time: 0.0152 memory: 14901 loss: 1.1740 loss_prob: 0.6253 loss_thr: 0.4402 loss_db: 0.1084 2022/11/02 20:44:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:44:45 - mmengine - INFO - Epoch(train) [766][5/63] lr: 8.6676e-04 eta: 4:36:14 time: 1.1063 data_time: 0.2497 memory: 14901 loss: 1.1904 loss_prob: 0.6351 loss_thr: 0.4474 loss_db: 0.1078 2022/11/02 20:44:48 - mmengine - INFO - Epoch(train) [766][10/63] lr: 8.6676e-04 eta: 4:36:07 time: 0.9669 data_time: 0.2481 memory: 14901 loss: 1.0464 loss_prob: 0.5519 loss_thr: 0.4007 loss_db: 0.0937 2022/11/02 20:44:51 - mmengine - INFO - Epoch(train) [766][15/63] lr: 8.6676e-04 eta: 4:36:07 time: 0.6100 data_time: 0.0101 memory: 14901 loss: 1.0300 loss_prob: 0.5324 loss_thr: 0.4068 loss_db: 0.0908 2022/11/02 20:44:53 - mmengine - INFO - Epoch(train) [766][20/63] lr: 8.6676e-04 eta: 4:36:01 time: 0.5651 data_time: 0.0097 memory: 14901 loss: 1.0979 loss_prob: 0.5702 loss_thr: 0.4291 loss_db: 0.0986 2022/11/02 20:44:57 - mmengine - INFO - Epoch(train) [766][25/63] lr: 8.6676e-04 eta: 4:36:01 time: 0.5821 data_time: 0.0286 memory: 14901 loss: 1.0926 loss_prob: 0.5822 loss_thr: 0.4110 loss_db: 0.0994 2022/11/02 20:45:00 - mmengine - INFO - Epoch(train) [766][30/63] lr: 8.6676e-04 eta: 4:35:55 time: 0.6130 data_time: 0.0399 memory: 14901 loss: 1.0780 loss_prob: 0.5770 loss_thr: 0.4042 loss_db: 0.0968 2022/11/02 20:45:02 - mmengine - INFO - Epoch(train) [766][35/63] lr: 8.6676e-04 eta: 4:35:55 time: 0.5395 data_time: 0.0206 memory: 14901 loss: 1.1796 loss_prob: 0.6518 loss_thr: 0.4245 loss_db: 0.1033 2022/11/02 20:45:05 - mmengine - INFO - Epoch(train) [766][40/63] lr: 8.6676e-04 eta: 4:35:48 time: 0.5220 data_time: 0.0097 memory: 14901 loss: 1.2357 loss_prob: 0.6883 loss_thr: 0.4364 loss_db: 0.1110 2022/11/02 20:45:07 - mmengine - INFO - Epoch(train) [766][45/63] lr: 8.6676e-04 eta: 4:35:48 time: 0.5115 data_time: 0.0121 memory: 14901 loss: 1.1305 loss_prob: 0.5998 loss_thr: 0.4239 loss_db: 0.1068 2022/11/02 20:45:10 - mmengine - INFO - Epoch(train) [766][50/63] lr: 8.6676e-04 eta: 4:35:42 time: 0.5043 data_time: 0.0202 memory: 14901 loss: 1.0771 loss_prob: 0.5687 loss_thr: 0.4074 loss_db: 0.1010 2022/11/02 20:45:13 - mmengine - INFO - Epoch(train) [766][55/63] lr: 8.6676e-04 eta: 4:35:42 time: 0.5233 data_time: 0.0287 memory: 14901 loss: 1.1435 loss_prob: 0.6114 loss_thr: 0.4275 loss_db: 0.1047 2022/11/02 20:45:15 - mmengine - INFO - Epoch(train) [766][60/63] lr: 8.6676e-04 eta: 4:35:35 time: 0.5330 data_time: 0.0209 memory: 14901 loss: 1.1732 loss_prob: 0.6249 loss_thr: 0.4423 loss_db: 0.1060 2022/11/02 20:45:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:45:23 - mmengine - INFO - Epoch(train) [767][5/63] lr: 8.6497e-04 eta: 4:35:35 time: 0.9108 data_time: 0.2478 memory: 14901 loss: 1.0704 loss_prob: 0.5657 loss_thr: 0.4085 loss_db: 0.0962 2022/11/02 20:45:26 - mmengine - INFO - Epoch(train) [767][10/63] lr: 8.6497e-04 eta: 4:35:28 time: 0.9279 data_time: 0.2475 memory: 14901 loss: 0.9685 loss_prob: 0.4987 loss_thr: 0.3824 loss_db: 0.0874 2022/11/02 20:45:28 - mmengine - INFO - Epoch(train) [767][15/63] lr: 8.6497e-04 eta: 4:35:28 time: 0.5200 data_time: 0.0150 memory: 14901 loss: 1.0937 loss_prob: 0.5854 loss_thr: 0.4093 loss_db: 0.0990 2022/11/02 20:45:31 - mmengine - INFO - Epoch(train) [767][20/63] lr: 8.6497e-04 eta: 4:35:22 time: 0.5238 data_time: 0.0136 memory: 14901 loss: 1.2099 loss_prob: 0.6582 loss_thr: 0.4406 loss_db: 0.1110 2022/11/02 20:45:34 - mmengine - INFO - Epoch(train) [767][25/63] lr: 8.6497e-04 eta: 4:35:22 time: 0.5600 data_time: 0.0128 memory: 14901 loss: 1.1565 loss_prob: 0.6155 loss_thr: 0.4362 loss_db: 0.1049 2022/11/02 20:45:38 - mmengine - INFO - Epoch(train) [767][30/63] lr: 8.6497e-04 eta: 4:35:16 time: 0.7267 data_time: 0.0383 memory: 14901 loss: 1.0457 loss_prob: 0.5469 loss_thr: 0.4059 loss_db: 0.0928 2022/11/02 20:45:42 - mmengine - INFO - Epoch(train) [767][35/63] lr: 8.6497e-04 eta: 4:35:16 time: 0.7597 data_time: 0.0358 memory: 14901 loss: 1.0221 loss_prob: 0.5333 loss_thr: 0.3961 loss_db: 0.0927 2022/11/02 20:45:45 - mmengine - INFO - Epoch(train) [767][40/63] lr: 8.6497e-04 eta: 4:35:10 time: 0.6185 data_time: 0.0154 memory: 14901 loss: 1.0934 loss_prob: 0.5753 loss_thr: 0.4184 loss_db: 0.0997 2022/11/02 20:45:48 - mmengine - INFO - Epoch(train) [767][45/63] lr: 8.6497e-04 eta: 4:35:10 time: 0.5949 data_time: 0.0141 memory: 14901 loss: 1.1424 loss_prob: 0.6116 loss_thr: 0.4253 loss_db: 0.1054 2022/11/02 20:45:51 - mmengine - INFO - Epoch(train) [767][50/63] lr: 8.6497e-04 eta: 4:35:04 time: 0.6020 data_time: 0.0160 memory: 14901 loss: 1.1293 loss_prob: 0.6024 loss_thr: 0.4206 loss_db: 0.1063 2022/11/02 20:45:53 - mmengine - INFO - Epoch(train) [767][55/63] lr: 8.6497e-04 eta: 4:35:04 time: 0.5582 data_time: 0.0266 memory: 14901 loss: 1.0850 loss_prob: 0.5681 loss_thr: 0.4165 loss_db: 0.1004 2022/11/02 20:45:56 - mmengine - INFO - Epoch(train) [767][60/63] lr: 8.6497e-04 eta: 4:34:58 time: 0.5338 data_time: 0.0209 memory: 14901 loss: 1.0427 loss_prob: 0.5436 loss_thr: 0.4042 loss_db: 0.0949 2022/11/02 20:45:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:46:05 - mmengine - INFO - Epoch(train) [768][5/63] lr: 8.6317e-04 eta: 4:34:58 time: 1.0307 data_time: 0.3122 memory: 14901 loss: 1.0272 loss_prob: 0.5367 loss_thr: 0.3977 loss_db: 0.0928 2022/11/02 20:46:08 - mmengine - INFO - Epoch(train) [768][10/63] lr: 8.6317e-04 eta: 4:34:52 time: 1.1189 data_time: 0.3198 memory: 14901 loss: 1.1151 loss_prob: 0.6037 loss_thr: 0.4130 loss_db: 0.0984 2022/11/02 20:46:11 - mmengine - INFO - Epoch(train) [768][15/63] lr: 8.6317e-04 eta: 4:34:52 time: 0.5977 data_time: 0.0220 memory: 14901 loss: 1.1895 loss_prob: 0.6453 loss_thr: 0.4377 loss_db: 0.1065 2022/11/02 20:46:14 - mmengine - INFO - Epoch(train) [768][20/63] lr: 8.6317e-04 eta: 4:34:45 time: 0.5411 data_time: 0.0135 memory: 14901 loss: 1.1294 loss_prob: 0.5970 loss_thr: 0.4296 loss_db: 0.1028 2022/11/02 20:46:17 - mmengine - INFO - Epoch(train) [768][25/63] lr: 8.6317e-04 eta: 4:34:45 time: 0.5631 data_time: 0.0227 memory: 14901 loss: 1.0415 loss_prob: 0.5480 loss_thr: 0.3984 loss_db: 0.0951 2022/11/02 20:46:20 - mmengine - INFO - Epoch(train) [768][30/63] lr: 8.6317e-04 eta: 4:34:40 time: 0.6228 data_time: 0.0403 memory: 14901 loss: 1.0381 loss_prob: 0.5436 loss_thr: 0.4008 loss_db: 0.0937 2022/11/02 20:46:23 - mmengine - INFO - Epoch(train) [768][35/63] lr: 8.6317e-04 eta: 4:34:40 time: 0.5911 data_time: 0.0355 memory: 14901 loss: 0.9979 loss_prob: 0.5126 loss_thr: 0.3985 loss_db: 0.0869 2022/11/02 20:46:25 - mmengine - INFO - Epoch(train) [768][40/63] lr: 8.6317e-04 eta: 4:34:33 time: 0.5244 data_time: 0.0188 memory: 14901 loss: 0.9760 loss_prob: 0.5011 loss_thr: 0.3883 loss_db: 0.0865 2022/11/02 20:46:28 - mmengine - INFO - Epoch(train) [768][45/63] lr: 8.6317e-04 eta: 4:34:33 time: 0.5366 data_time: 0.0111 memory: 14901 loss: 1.0204 loss_prob: 0.5271 loss_thr: 0.4013 loss_db: 0.0920 2022/11/02 20:46:32 - mmengine - INFO - Epoch(train) [768][50/63] lr: 8.6317e-04 eta: 4:34:27 time: 0.6235 data_time: 0.0250 memory: 14901 loss: 1.1141 loss_prob: 0.5812 loss_thr: 0.4345 loss_db: 0.0984 2022/11/02 20:46:34 - mmengine - INFO - Epoch(train) [768][55/63] lr: 8.6317e-04 eta: 4:34:27 time: 0.6133 data_time: 0.0295 memory: 14901 loss: 1.0810 loss_prob: 0.5668 loss_thr: 0.4177 loss_db: 0.0965 2022/11/02 20:46:37 - mmengine - INFO - Epoch(train) [768][60/63] lr: 8.6317e-04 eta: 4:34:21 time: 0.5494 data_time: 0.0150 memory: 14901 loss: 1.0745 loss_prob: 0.5672 loss_thr: 0.4089 loss_db: 0.0984 2022/11/02 20:46:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:46:45 - mmengine - INFO - Epoch(train) [769][5/63] lr: 8.6137e-04 eta: 4:34:21 time: 0.8883 data_time: 0.3175 memory: 14901 loss: 1.0309 loss_prob: 0.5530 loss_thr: 0.3802 loss_db: 0.0977 2022/11/02 20:46:48 - mmengine - INFO - Epoch(train) [769][10/63] lr: 8.6137e-04 eta: 4:34:14 time: 0.9328 data_time: 0.3242 memory: 14901 loss: 1.0220 loss_prob: 0.5386 loss_thr: 0.3874 loss_db: 0.0960 2022/11/02 20:46:50 - mmengine - INFO - Epoch(train) [769][15/63] lr: 8.6137e-04 eta: 4:34:14 time: 0.5183 data_time: 0.0168 memory: 14901 loss: 1.0179 loss_prob: 0.5369 loss_thr: 0.3876 loss_db: 0.0934 2022/11/02 20:46:53 - mmengine - INFO - Epoch(train) [769][20/63] lr: 8.6137e-04 eta: 4:34:07 time: 0.5154 data_time: 0.0089 memory: 14901 loss: 0.9778 loss_prob: 0.5144 loss_thr: 0.3747 loss_db: 0.0887 2022/11/02 20:46:56 - mmengine - INFO - Epoch(train) [769][25/63] lr: 8.6137e-04 eta: 4:34:07 time: 0.5548 data_time: 0.0269 memory: 14901 loss: 1.0260 loss_prob: 0.5321 loss_thr: 0.4010 loss_db: 0.0929 2022/11/02 20:46:59 - mmengine - INFO - Epoch(train) [769][30/63] lr: 8.6137e-04 eta: 4:34:01 time: 0.5874 data_time: 0.0316 memory: 14901 loss: 1.1008 loss_prob: 0.5840 loss_thr: 0.4148 loss_db: 0.1020 2022/11/02 20:47:01 - mmengine - INFO - Epoch(train) [769][35/63] lr: 8.6137e-04 eta: 4:34:01 time: 0.5735 data_time: 0.0236 memory: 14901 loss: 1.2187 loss_prob: 0.6713 loss_thr: 0.4347 loss_db: 0.1127 2022/11/02 20:47:04 - mmengine - INFO - Epoch(train) [769][40/63] lr: 8.6137e-04 eta: 4:33:55 time: 0.5632 data_time: 0.0201 memory: 14901 loss: 1.1745 loss_prob: 0.6339 loss_thr: 0.4336 loss_db: 0.1069 2022/11/02 20:47:07 - mmengine - INFO - Epoch(train) [769][45/63] lr: 8.6137e-04 eta: 4:33:55 time: 0.5394 data_time: 0.0114 memory: 14901 loss: 1.0386 loss_prob: 0.5387 loss_thr: 0.4060 loss_db: 0.0938 2022/11/02 20:47:09 - mmengine - INFO - Epoch(train) [769][50/63] lr: 8.6137e-04 eta: 4:33:48 time: 0.5158 data_time: 0.0277 memory: 14901 loss: 1.0639 loss_prob: 0.5693 loss_thr: 0.3982 loss_db: 0.0964 2022/11/02 20:47:12 - mmengine - INFO - Epoch(train) [769][55/63] lr: 8.6137e-04 eta: 4:33:48 time: 0.5256 data_time: 0.0268 memory: 14901 loss: 1.3099 loss_prob: 0.7632 loss_thr: 0.4286 loss_db: 0.1182 2022/11/02 20:47:15 - mmengine - INFO - Epoch(train) [769][60/63] lr: 8.6137e-04 eta: 4:33:42 time: 0.5506 data_time: 0.0143 memory: 14901 loss: 1.4468 loss_prob: 0.8519 loss_thr: 0.4578 loss_db: 0.1370 2022/11/02 20:47:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:47:23 - mmengine - INFO - Epoch(train) [770][5/63] lr: 8.5957e-04 eta: 4:33:42 time: 0.9387 data_time: 0.2635 memory: 14901 loss: 1.5116 loss_prob: 0.8663 loss_thr: 0.5044 loss_db: 0.1409 2022/11/02 20:47:27 - mmengine - INFO - Epoch(train) [770][10/63] lr: 8.5957e-04 eta: 4:33:36 time: 1.0749 data_time: 0.2691 memory: 14901 loss: 1.2892 loss_prob: 0.7279 loss_thr: 0.4449 loss_db: 0.1164 2022/11/02 20:47:31 - mmengine - INFO - Epoch(train) [770][15/63] lr: 8.5957e-04 eta: 4:33:36 time: 0.7644 data_time: 0.0177 memory: 14901 loss: 1.1369 loss_prob: 0.6106 loss_thr: 0.4240 loss_db: 0.1023 2022/11/02 20:47:34 - mmengine - INFO - Epoch(train) [770][20/63] lr: 8.5957e-04 eta: 4:33:30 time: 0.7451 data_time: 0.0127 memory: 14901 loss: 1.0890 loss_prob: 0.5632 loss_thr: 0.4274 loss_db: 0.0983 2022/11/02 20:47:38 - mmengine - INFO - Epoch(train) [770][25/63] lr: 8.5957e-04 eta: 4:33:30 time: 0.6971 data_time: 0.0365 memory: 14901 loss: 1.1592 loss_prob: 0.6079 loss_thr: 0.4477 loss_db: 0.1036 2022/11/02 20:47:41 - mmengine - INFO - Epoch(train) [770][30/63] lr: 8.5957e-04 eta: 4:33:25 time: 0.6712 data_time: 0.0418 memory: 14901 loss: 1.1522 loss_prob: 0.6086 loss_thr: 0.4387 loss_db: 0.1049 2022/11/02 20:47:45 - mmengine - INFO - Epoch(train) [770][35/63] lr: 8.5957e-04 eta: 4:33:25 time: 0.6934 data_time: 0.0183 memory: 14901 loss: 1.0229 loss_prob: 0.5367 loss_thr: 0.3917 loss_db: 0.0945 2022/11/02 20:47:47 - mmengine - INFO - Epoch(train) [770][40/63] lr: 8.5957e-04 eta: 4:33:18 time: 0.5912 data_time: 0.0106 memory: 14901 loss: 0.9830 loss_prob: 0.5098 loss_thr: 0.3833 loss_db: 0.0899 2022/11/02 20:47:50 - mmengine - INFO - Epoch(train) [770][45/63] lr: 8.5957e-04 eta: 4:33:18 time: 0.4995 data_time: 0.0097 memory: 14901 loss: 1.0527 loss_prob: 0.5564 loss_thr: 0.4010 loss_db: 0.0953 2022/11/02 20:47:52 - mmengine - INFO - Epoch(train) [770][50/63] lr: 8.5957e-04 eta: 4:33:12 time: 0.5354 data_time: 0.0284 memory: 14901 loss: 1.0770 loss_prob: 0.5713 loss_thr: 0.4077 loss_db: 0.0981 2022/11/02 20:47:55 - mmengine - INFO - Epoch(train) [770][55/63] lr: 8.5957e-04 eta: 4:33:12 time: 0.5525 data_time: 0.0291 memory: 14901 loss: 1.0903 loss_prob: 0.5686 loss_thr: 0.4220 loss_db: 0.0998 2022/11/02 20:47:58 - mmengine - INFO - Epoch(train) [770][60/63] lr: 8.5957e-04 eta: 4:33:06 time: 0.5211 data_time: 0.0125 memory: 14901 loss: 1.0973 loss_prob: 0.5754 loss_thr: 0.4217 loss_db: 0.1002 2022/11/02 20:47:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:48:07 - mmengine - INFO - Epoch(train) [771][5/63] lr: 8.5777e-04 eta: 4:33:06 time: 0.9879 data_time: 0.2786 memory: 14901 loss: 1.0921 loss_prob: 0.5701 loss_thr: 0.4238 loss_db: 0.0982 2022/11/02 20:48:10 - mmengine - INFO - Epoch(train) [771][10/63] lr: 8.5777e-04 eta: 4:32:59 time: 1.0516 data_time: 0.2775 memory: 14901 loss: 1.0694 loss_prob: 0.5667 loss_thr: 0.4057 loss_db: 0.0970 2022/11/02 20:48:13 - mmengine - INFO - Epoch(train) [771][15/63] lr: 8.5777e-04 eta: 4:32:59 time: 0.6859 data_time: 0.0092 memory: 14901 loss: 1.0656 loss_prob: 0.5515 loss_thr: 0.4177 loss_db: 0.0965 2022/11/02 20:48:16 - mmengine - INFO - Epoch(train) [771][20/63] lr: 8.5777e-04 eta: 4:32:53 time: 0.6654 data_time: 0.0102 memory: 14901 loss: 0.9927 loss_prob: 0.4979 loss_thr: 0.4077 loss_db: 0.0872 2022/11/02 20:48:19 - mmengine - INFO - Epoch(train) [771][25/63] lr: 8.5777e-04 eta: 4:32:53 time: 0.5461 data_time: 0.0211 memory: 14901 loss: 1.0714 loss_prob: 0.5484 loss_thr: 0.4268 loss_db: 0.0961 2022/11/02 20:48:22 - mmengine - INFO - Epoch(train) [771][30/63] lr: 8.5777e-04 eta: 4:32:47 time: 0.5122 data_time: 0.0393 memory: 14901 loss: 1.1473 loss_prob: 0.6100 loss_thr: 0.4330 loss_db: 0.1043 2022/11/02 20:48:24 - mmengine - INFO - Epoch(train) [771][35/63] lr: 8.5777e-04 eta: 4:32:47 time: 0.5324 data_time: 0.0269 memory: 14901 loss: 1.0946 loss_prob: 0.5803 loss_thr: 0.4140 loss_db: 0.1003 2022/11/02 20:48:27 - mmengine - INFO - Epoch(train) [771][40/63] lr: 8.5777e-04 eta: 4:32:41 time: 0.5776 data_time: 0.0083 memory: 14901 loss: 1.0464 loss_prob: 0.5372 loss_thr: 0.4143 loss_db: 0.0949 2022/11/02 20:48:30 - mmengine - INFO - Epoch(train) [771][45/63] lr: 8.5777e-04 eta: 4:32:41 time: 0.5936 data_time: 0.0106 memory: 14901 loss: 1.0461 loss_prob: 0.5438 loss_thr: 0.4087 loss_db: 0.0936 2022/11/02 20:48:33 - mmengine - INFO - Epoch(train) [771][50/63] lr: 8.5777e-04 eta: 4:32:35 time: 0.5883 data_time: 0.0185 memory: 14901 loss: 1.1475 loss_prob: 0.6120 loss_thr: 0.4299 loss_db: 0.1056 2022/11/02 20:48:36 - mmengine - INFO - Epoch(train) [771][55/63] lr: 8.5777e-04 eta: 4:32:35 time: 0.6136 data_time: 0.0335 memory: 14901 loss: 1.2462 loss_prob: 0.6730 loss_thr: 0.4573 loss_db: 0.1160 2022/11/02 20:48:40 - mmengine - INFO - Epoch(train) [771][60/63] lr: 8.5777e-04 eta: 4:32:29 time: 0.6685 data_time: 0.0258 memory: 14901 loss: 1.2186 loss_prob: 0.6563 loss_thr: 0.4504 loss_db: 0.1118 2022/11/02 20:48:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:48:50 - mmengine - INFO - Epoch(train) [772][5/63] lr: 8.5597e-04 eta: 4:32:29 time: 1.1199 data_time: 0.2574 memory: 14901 loss: 1.2558 loss_prob: 0.6819 loss_thr: 0.4601 loss_db: 0.1139 2022/11/02 20:48:53 - mmengine - INFO - Epoch(train) [772][10/63] lr: 8.5597e-04 eta: 4:32:23 time: 1.0835 data_time: 0.2572 memory: 14901 loss: 1.1815 loss_prob: 0.6308 loss_thr: 0.4423 loss_db: 0.1084 2022/11/02 20:48:55 - mmengine - INFO - Epoch(train) [772][15/63] lr: 8.5597e-04 eta: 4:32:23 time: 0.5555 data_time: 0.0112 memory: 14901 loss: 1.0733 loss_prob: 0.5606 loss_thr: 0.4166 loss_db: 0.0960 2022/11/02 20:48:58 - mmengine - INFO - Epoch(train) [772][20/63] lr: 8.5597e-04 eta: 4:32:16 time: 0.5285 data_time: 0.0101 memory: 14901 loss: 1.0893 loss_prob: 0.5747 loss_thr: 0.4157 loss_db: 0.0988 2022/11/02 20:49:01 - mmengine - INFO - Epoch(train) [772][25/63] lr: 8.5597e-04 eta: 4:32:16 time: 0.5588 data_time: 0.0260 memory: 14901 loss: 1.0944 loss_prob: 0.5784 loss_thr: 0.4156 loss_db: 0.1004 2022/11/02 20:49:04 - mmengine - INFO - Epoch(train) [772][30/63] lr: 8.5597e-04 eta: 4:32:10 time: 0.5808 data_time: 0.0499 memory: 14901 loss: 1.0353 loss_prob: 0.5492 loss_thr: 0.3919 loss_db: 0.0942 2022/11/02 20:49:06 - mmengine - INFO - Epoch(train) [772][35/63] lr: 8.5597e-04 eta: 4:32:10 time: 0.5538 data_time: 0.0323 memory: 14901 loss: 0.9944 loss_prob: 0.5350 loss_thr: 0.3694 loss_db: 0.0900 2022/11/02 20:49:09 - mmengine - INFO - Epoch(train) [772][40/63] lr: 8.5597e-04 eta: 4:32:04 time: 0.5748 data_time: 0.0121 memory: 14901 loss: 1.0823 loss_prob: 0.5811 loss_thr: 0.4026 loss_db: 0.0986 2022/11/02 20:49:13 - mmengine - INFO - Epoch(train) [772][45/63] lr: 8.5597e-04 eta: 4:32:04 time: 0.6791 data_time: 0.0125 memory: 14901 loss: 1.1338 loss_prob: 0.5964 loss_thr: 0.4343 loss_db: 0.1031 2022/11/02 20:49:16 - mmengine - INFO - Epoch(train) [772][50/63] lr: 8.5597e-04 eta: 4:31:58 time: 0.6952 data_time: 0.0214 memory: 14901 loss: 1.0782 loss_prob: 0.5585 loss_thr: 0.4239 loss_db: 0.0958 2022/11/02 20:49:20 - mmengine - INFO - Epoch(train) [772][55/63] lr: 8.5597e-04 eta: 4:31:58 time: 0.6452 data_time: 0.0306 memory: 14901 loss: 1.0575 loss_prob: 0.5463 loss_thr: 0.4162 loss_db: 0.0950 2022/11/02 20:49:22 - mmengine - INFO - Epoch(train) [772][60/63] lr: 8.5597e-04 eta: 4:31:52 time: 0.5851 data_time: 0.0226 memory: 14901 loss: 1.0517 loss_prob: 0.5464 loss_thr: 0.4094 loss_db: 0.0959 2022/11/02 20:49:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:49:32 - mmengine - INFO - Epoch(train) [773][5/63] lr: 8.5417e-04 eta: 4:31:52 time: 1.0800 data_time: 0.3315 memory: 14901 loss: 1.0877 loss_prob: 0.5819 loss_thr: 0.4070 loss_db: 0.0988 2022/11/02 20:49:36 - mmengine - INFO - Epoch(train) [773][10/63] lr: 8.5417e-04 eta: 4:31:47 time: 1.2978 data_time: 0.3296 memory: 14901 loss: 1.0935 loss_prob: 0.5806 loss_thr: 0.4157 loss_db: 0.0972 2022/11/02 20:49:40 - mmengine - INFO - Epoch(train) [773][15/63] lr: 8.5417e-04 eta: 4:31:47 time: 0.7612 data_time: 0.0109 memory: 14901 loss: 1.0820 loss_prob: 0.5766 loss_thr: 0.4050 loss_db: 0.1005 2022/11/02 20:49:43 - mmengine - INFO - Epoch(train) [773][20/63] lr: 8.5417e-04 eta: 4:31:41 time: 0.6254 data_time: 0.0098 memory: 14901 loss: 1.1031 loss_prob: 0.5899 loss_thr: 0.4111 loss_db: 0.1021 2022/11/02 20:49:46 - mmengine - INFO - Epoch(train) [773][25/63] lr: 8.5417e-04 eta: 4:31:41 time: 0.6650 data_time: 0.0401 memory: 14901 loss: 1.1496 loss_prob: 0.6085 loss_thr: 0.4386 loss_db: 0.1025 2022/11/02 20:49:49 - mmengine - INFO - Epoch(train) [773][30/63] lr: 8.5417e-04 eta: 4:31:35 time: 0.6231 data_time: 0.0474 memory: 14901 loss: 1.1316 loss_prob: 0.5954 loss_thr: 0.4354 loss_db: 0.1008 2022/11/02 20:49:52 - mmengine - INFO - Epoch(train) [773][35/63] lr: 8.5417e-04 eta: 4:31:35 time: 0.5222 data_time: 0.0186 memory: 14901 loss: 1.1188 loss_prob: 0.5913 loss_thr: 0.4271 loss_db: 0.1004 2022/11/02 20:49:54 - mmengine - INFO - Epoch(train) [773][40/63] lr: 8.5417e-04 eta: 4:31:29 time: 0.5138 data_time: 0.0101 memory: 14901 loss: 1.1384 loss_prob: 0.6037 loss_thr: 0.4309 loss_db: 0.1037 2022/11/02 20:49:57 - mmengine - INFO - Epoch(train) [773][45/63] lr: 8.5417e-04 eta: 4:31:29 time: 0.5098 data_time: 0.0097 memory: 14901 loss: 1.0862 loss_prob: 0.5737 loss_thr: 0.4116 loss_db: 0.1010 2022/11/02 20:50:00 - mmengine - INFO - Epoch(train) [773][50/63] lr: 8.5417e-04 eta: 4:31:22 time: 0.5669 data_time: 0.0282 memory: 14901 loss: 1.0993 loss_prob: 0.5789 loss_thr: 0.4203 loss_db: 0.1001 2022/11/02 20:50:02 - mmengine - INFO - Epoch(train) [773][55/63] lr: 8.5417e-04 eta: 4:31:22 time: 0.5825 data_time: 0.0261 memory: 14901 loss: 1.1076 loss_prob: 0.5858 loss_thr: 0.4202 loss_db: 0.1016 2022/11/02 20:50:05 - mmengine - INFO - Epoch(train) [773][60/63] lr: 8.5417e-04 eta: 4:31:16 time: 0.5722 data_time: 0.0068 memory: 14901 loss: 1.0345 loss_prob: 0.5452 loss_thr: 0.3936 loss_db: 0.0956 2022/11/02 20:50:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:50:13 - mmengine - INFO - Epoch(train) [774][5/63] lr: 8.5237e-04 eta: 4:31:16 time: 0.9294 data_time: 0.2874 memory: 14901 loss: 0.9931 loss_prob: 0.5144 loss_thr: 0.3891 loss_db: 0.0896 2022/11/02 20:50:16 - mmengine - INFO - Epoch(train) [774][10/63] lr: 8.5237e-04 eta: 4:31:09 time: 0.8976 data_time: 0.2898 memory: 14901 loss: 0.9728 loss_prob: 0.5008 loss_thr: 0.3830 loss_db: 0.0890 2022/11/02 20:50:19 - mmengine - INFO - Epoch(train) [774][15/63] lr: 8.5237e-04 eta: 4:31:09 time: 0.5633 data_time: 0.0152 memory: 14901 loss: 1.0112 loss_prob: 0.5280 loss_thr: 0.3912 loss_db: 0.0920 2022/11/02 20:50:22 - mmengine - INFO - Epoch(train) [774][20/63] lr: 8.5237e-04 eta: 4:31:03 time: 0.5837 data_time: 0.0116 memory: 14901 loss: 0.9825 loss_prob: 0.5090 loss_thr: 0.3873 loss_db: 0.0863 2022/11/02 20:50:25 - mmengine - INFO - Epoch(train) [774][25/63] lr: 8.5237e-04 eta: 4:31:03 time: 0.5919 data_time: 0.0197 memory: 14901 loss: 1.0057 loss_prob: 0.5214 loss_thr: 0.3963 loss_db: 0.0879 2022/11/02 20:50:28 - mmengine - INFO - Epoch(train) [774][30/63] lr: 8.5237e-04 eta: 4:30:56 time: 0.5664 data_time: 0.0425 memory: 14901 loss: 1.3381 loss_prob: 0.7943 loss_thr: 0.4304 loss_db: 0.1134 2022/11/02 20:50:30 - mmengine - INFO - Epoch(train) [774][35/63] lr: 8.5237e-04 eta: 4:30:56 time: 0.5482 data_time: 0.0341 memory: 14901 loss: 1.3766 loss_prob: 0.8104 loss_thr: 0.4487 loss_db: 0.1175 2022/11/02 20:50:33 - mmengine - INFO - Epoch(train) [774][40/63] lr: 8.5237e-04 eta: 4:30:50 time: 0.5659 data_time: 0.0100 memory: 14901 loss: 1.0823 loss_prob: 0.5567 loss_thr: 0.4303 loss_db: 0.0953 2022/11/02 20:50:37 - mmengine - INFO - Epoch(train) [774][45/63] lr: 8.5237e-04 eta: 4:30:50 time: 0.6386 data_time: 0.0093 memory: 14901 loss: 1.0570 loss_prob: 0.5453 loss_thr: 0.4197 loss_db: 0.0920 2022/11/02 20:50:40 - mmengine - INFO - Epoch(train) [774][50/63] lr: 8.5237e-04 eta: 4:30:44 time: 0.6680 data_time: 0.0143 memory: 14901 loss: 1.0585 loss_prob: 0.5594 loss_thr: 0.4020 loss_db: 0.0970 2022/11/02 20:50:44 - mmengine - INFO - Epoch(train) [774][55/63] lr: 8.5237e-04 eta: 4:30:44 time: 0.6928 data_time: 0.0287 memory: 14901 loss: 1.1022 loss_prob: 0.5858 loss_thr: 0.4140 loss_db: 0.1024 2022/11/02 20:50:46 - mmengine - INFO - Epoch(train) [774][60/63] lr: 8.5237e-04 eta: 4:30:39 time: 0.6318 data_time: 0.0265 memory: 14901 loss: 1.1585 loss_prob: 0.6100 loss_thr: 0.4429 loss_db: 0.1056 2022/11/02 20:50:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:50:55 - mmengine - INFO - Epoch(train) [775][5/63] lr: 8.5057e-04 eta: 4:30:39 time: 0.9769 data_time: 0.2545 memory: 14901 loss: 1.0277 loss_prob: 0.5299 loss_thr: 0.4058 loss_db: 0.0921 2022/11/02 20:50:58 - mmengine - INFO - Epoch(train) [775][10/63] lr: 8.5057e-04 eta: 4:30:32 time: 0.9705 data_time: 0.2669 memory: 14901 loss: 1.1304 loss_prob: 0.5855 loss_thr: 0.4422 loss_db: 0.1027 2022/11/02 20:51:00 - mmengine - INFO - Epoch(train) [775][15/63] lr: 8.5057e-04 eta: 4:30:32 time: 0.5367 data_time: 0.0214 memory: 14901 loss: 1.1653 loss_prob: 0.6095 loss_thr: 0.4482 loss_db: 0.1076 2022/11/02 20:51:03 - mmengine - INFO - Epoch(train) [775][20/63] lr: 8.5057e-04 eta: 4:30:25 time: 0.5346 data_time: 0.0107 memory: 14901 loss: 1.0682 loss_prob: 0.5600 loss_thr: 0.4116 loss_db: 0.0967 2022/11/02 20:51:06 - mmengine - INFO - Epoch(train) [775][25/63] lr: 8.5057e-04 eta: 4:30:25 time: 0.5998 data_time: 0.0244 memory: 14901 loss: 1.0371 loss_prob: 0.5409 loss_thr: 0.4024 loss_db: 0.0939 2022/11/02 20:51:10 - mmengine - INFO - Epoch(train) [775][30/63] lr: 8.5057e-04 eta: 4:30:20 time: 0.6765 data_time: 0.0385 memory: 14901 loss: 1.0576 loss_prob: 0.5547 loss_thr: 0.4058 loss_db: 0.0971 2022/11/02 20:51:13 - mmengine - INFO - Epoch(train) [775][35/63] lr: 8.5057e-04 eta: 4:30:20 time: 0.6336 data_time: 0.0268 memory: 14901 loss: 1.0718 loss_prob: 0.5621 loss_thr: 0.4118 loss_db: 0.0979 2022/11/02 20:51:15 - mmengine - INFO - Epoch(train) [775][40/63] lr: 8.5057e-04 eta: 4:30:13 time: 0.5457 data_time: 0.0123 memory: 14901 loss: 1.0665 loss_prob: 0.5533 loss_thr: 0.4169 loss_db: 0.0964 2022/11/02 20:51:18 - mmengine - INFO - Epoch(train) [775][45/63] lr: 8.5057e-04 eta: 4:30:13 time: 0.5544 data_time: 0.0122 memory: 14901 loss: 1.0607 loss_prob: 0.5538 loss_thr: 0.4111 loss_db: 0.0957 2022/11/02 20:51:21 - mmengine - INFO - Epoch(train) [775][50/63] lr: 8.5057e-04 eta: 4:30:07 time: 0.5519 data_time: 0.0218 memory: 14901 loss: 1.1529 loss_prob: 0.6197 loss_thr: 0.4276 loss_db: 0.1056 2022/11/02 20:51:24 - mmengine - INFO - Epoch(train) [775][55/63] lr: 8.5057e-04 eta: 4:30:07 time: 0.5437 data_time: 0.0303 memory: 14901 loss: 1.1372 loss_prob: 0.6034 loss_thr: 0.4295 loss_db: 0.1043 2022/11/02 20:51:27 - mmengine - INFO - Epoch(train) [775][60/63] lr: 8.5057e-04 eta: 4:30:01 time: 0.6631 data_time: 0.0217 memory: 14901 loss: 1.0758 loss_prob: 0.5610 loss_thr: 0.4174 loss_db: 0.0973 2022/11/02 20:51:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:51:36 - mmengine - INFO - Epoch(train) [776][5/63] lr: 8.4877e-04 eta: 4:30:01 time: 1.0356 data_time: 0.2279 memory: 14901 loss: 1.1623 loss_prob: 0.6176 loss_thr: 0.4410 loss_db: 0.1037 2022/11/02 20:51:39 - mmengine - INFO - Epoch(train) [776][10/63] lr: 8.4877e-04 eta: 4:29:55 time: 1.0306 data_time: 0.2332 memory: 14901 loss: 1.1889 loss_prob: 0.6386 loss_thr: 0.4396 loss_db: 0.1107 2022/11/02 20:51:43 - mmengine - INFO - Epoch(train) [776][15/63] lr: 8.4877e-04 eta: 4:29:55 time: 0.7415 data_time: 0.0165 memory: 14901 loss: 1.1852 loss_prob: 0.6505 loss_thr: 0.4225 loss_db: 0.1123 2022/11/02 20:51:46 - mmengine - INFO - Epoch(train) [776][20/63] lr: 8.4877e-04 eta: 4:29:49 time: 0.6866 data_time: 0.0119 memory: 14901 loss: 1.0946 loss_prob: 0.5790 loss_thr: 0.4160 loss_db: 0.0996 2022/11/02 20:51:49 - mmengine - INFO - Epoch(train) [776][25/63] lr: 8.4877e-04 eta: 4:29:49 time: 0.5599 data_time: 0.0113 memory: 14901 loss: 1.1015 loss_prob: 0.5754 loss_thr: 0.4256 loss_db: 0.1004 2022/11/02 20:51:52 - mmengine - INFO - Epoch(train) [776][30/63] lr: 8.4877e-04 eta: 4:29:43 time: 0.6468 data_time: 0.0340 memory: 14901 loss: 1.0361 loss_prob: 0.5426 loss_thr: 0.3997 loss_db: 0.0938 2022/11/02 20:51:55 - mmengine - INFO - Epoch(train) [776][35/63] lr: 8.4877e-04 eta: 4:29:43 time: 0.6540 data_time: 0.0363 memory: 14901 loss: 1.0052 loss_prob: 0.5211 loss_thr: 0.3935 loss_db: 0.0906 2022/11/02 20:51:58 - mmengine - INFO - Epoch(train) [776][40/63] lr: 8.4877e-04 eta: 4:29:37 time: 0.6010 data_time: 0.0153 memory: 14901 loss: 1.0758 loss_prob: 0.5668 loss_thr: 0.4116 loss_db: 0.0974 2022/11/02 20:52:01 - mmengine - INFO - Epoch(train) [776][45/63] lr: 8.4877e-04 eta: 4:29:37 time: 0.5585 data_time: 0.0105 memory: 14901 loss: 1.0716 loss_prob: 0.5724 loss_thr: 0.4010 loss_db: 0.0982 2022/11/02 20:52:04 - mmengine - INFO - Epoch(train) [776][50/63] lr: 8.4877e-04 eta: 4:29:31 time: 0.5453 data_time: 0.0169 memory: 14901 loss: 1.0459 loss_prob: 0.5505 loss_thr: 0.4011 loss_db: 0.0944 2022/11/02 20:52:07 - mmengine - INFO - Epoch(train) [776][55/63] lr: 8.4877e-04 eta: 4:29:31 time: 0.5652 data_time: 0.0296 memory: 14901 loss: 1.0467 loss_prob: 0.5503 loss_thr: 0.4011 loss_db: 0.0953 2022/11/02 20:52:09 - mmengine - INFO - Epoch(train) [776][60/63] lr: 8.4877e-04 eta: 4:29:24 time: 0.5307 data_time: 0.0266 memory: 14901 loss: 1.0760 loss_prob: 0.5729 loss_thr: 0.4042 loss_db: 0.0989 2022/11/02 20:52:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:52:20 - mmengine - INFO - Epoch(train) [777][5/63] lr: 8.4697e-04 eta: 4:29:24 time: 1.1408 data_time: 0.3473 memory: 14901 loss: 1.0780 loss_prob: 0.5660 loss_thr: 0.4129 loss_db: 0.0992 2022/11/02 20:52:23 - mmengine - INFO - Epoch(train) [777][10/63] lr: 8.4697e-04 eta: 4:29:19 time: 1.2261 data_time: 0.3465 memory: 14901 loss: 1.0102 loss_prob: 0.5191 loss_thr: 0.4002 loss_db: 0.0909 2022/11/02 20:52:27 - mmengine - INFO - Epoch(train) [777][15/63] lr: 8.4697e-04 eta: 4:29:19 time: 0.7306 data_time: 0.0111 memory: 14901 loss: 0.9904 loss_prob: 0.5063 loss_thr: 0.3959 loss_db: 0.0882 2022/11/02 20:52:30 - mmengine - INFO - Epoch(train) [777][20/63] lr: 8.4697e-04 eta: 4:29:13 time: 0.6749 data_time: 0.0135 memory: 14901 loss: 0.9939 loss_prob: 0.5084 loss_thr: 0.3959 loss_db: 0.0896 2022/11/02 20:52:33 - mmengine - INFO - Epoch(train) [777][25/63] lr: 8.4697e-04 eta: 4:29:13 time: 0.5980 data_time: 0.0450 memory: 14901 loss: 1.0053 loss_prob: 0.5149 loss_thr: 0.4002 loss_db: 0.0902 2022/11/02 20:52:37 - mmengine - INFO - Epoch(train) [777][30/63] lr: 8.4697e-04 eta: 4:29:08 time: 0.7129 data_time: 0.0412 memory: 14901 loss: 1.0582 loss_prob: 0.5524 loss_thr: 0.4104 loss_db: 0.0954 2022/11/02 20:52:40 - mmengine - INFO - Epoch(train) [777][35/63] lr: 8.4697e-04 eta: 4:29:08 time: 0.6787 data_time: 0.0091 memory: 14901 loss: 1.0648 loss_prob: 0.5580 loss_thr: 0.4095 loss_db: 0.0973 2022/11/02 20:52:43 - mmengine - INFO - Epoch(train) [777][40/63] lr: 8.4697e-04 eta: 4:29:01 time: 0.5709 data_time: 0.0102 memory: 14901 loss: 1.0526 loss_prob: 0.5461 loss_thr: 0.4119 loss_db: 0.0947 2022/11/02 20:52:46 - mmengine - INFO - Epoch(train) [777][45/63] lr: 8.4697e-04 eta: 4:29:01 time: 0.6033 data_time: 0.0102 memory: 14901 loss: 1.0984 loss_prob: 0.5761 loss_thr: 0.4235 loss_db: 0.0988 2022/11/02 20:52:49 - mmengine - INFO - Epoch(train) [777][50/63] lr: 8.4697e-04 eta: 4:28:56 time: 0.6606 data_time: 0.0331 memory: 14901 loss: 1.1329 loss_prob: 0.5968 loss_thr: 0.4336 loss_db: 0.1024 2022/11/02 20:52:52 - mmengine - INFO - Epoch(train) [777][55/63] lr: 8.4697e-04 eta: 4:28:56 time: 0.6773 data_time: 0.0345 memory: 14901 loss: 1.1497 loss_prob: 0.6175 loss_thr: 0.4305 loss_db: 0.1017 2022/11/02 20:52:56 - mmengine - INFO - Epoch(train) [777][60/63] lr: 8.4697e-04 eta: 4:28:50 time: 0.7132 data_time: 0.0107 memory: 14901 loss: 1.0829 loss_prob: 0.5807 loss_thr: 0.4042 loss_db: 0.0980 2022/11/02 20:52:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:53:05 - mmengine - INFO - Epoch(train) [778][5/63] lr: 8.4517e-04 eta: 4:28:50 time: 0.9839 data_time: 0.2743 memory: 14901 loss: 0.9906 loss_prob: 0.5199 loss_thr: 0.3812 loss_db: 0.0895 2022/11/02 20:53:09 - mmengine - INFO - Epoch(train) [778][10/63] lr: 8.4517e-04 eta: 4:28:44 time: 1.0675 data_time: 0.2806 memory: 14901 loss: 0.9651 loss_prob: 0.5119 loss_thr: 0.3672 loss_db: 0.0860 2022/11/02 20:53:12 - mmengine - INFO - Epoch(train) [778][15/63] lr: 8.4517e-04 eta: 4:28:44 time: 0.7318 data_time: 0.0174 memory: 14901 loss: 1.1398 loss_prob: 0.6352 loss_thr: 0.4020 loss_db: 0.1026 2022/11/02 20:53:16 - mmengine - INFO - Epoch(train) [778][20/63] lr: 8.4517e-04 eta: 4:28:39 time: 0.7649 data_time: 0.0108 memory: 14901 loss: 1.2490 loss_prob: 0.7029 loss_thr: 0.4328 loss_db: 0.1133 2022/11/02 20:53:21 - mmengine - INFO - Epoch(train) [778][25/63] lr: 8.4517e-04 eta: 4:28:39 time: 0.8685 data_time: 0.0219 memory: 14901 loss: 1.1303 loss_prob: 0.6088 loss_thr: 0.4192 loss_db: 0.1023 2022/11/02 20:53:25 - mmengine - INFO - Epoch(train) [778][30/63] lr: 8.4517e-04 eta: 4:28:34 time: 0.8404 data_time: 0.0417 memory: 14901 loss: 1.1318 loss_prob: 0.6089 loss_thr: 0.4196 loss_db: 0.1033 2022/11/02 20:53:27 - mmengine - INFO - Epoch(train) [778][35/63] lr: 8.4517e-04 eta: 4:28:34 time: 0.6695 data_time: 0.0287 memory: 14901 loss: 1.2526 loss_prob: 0.6896 loss_thr: 0.4486 loss_db: 0.1145 2022/11/02 20:53:30 - mmengine - INFO - Epoch(train) [778][40/63] lr: 8.4517e-04 eta: 4:28:27 time: 0.5159 data_time: 0.0087 memory: 14901 loss: 1.2198 loss_prob: 0.6687 loss_thr: 0.4393 loss_db: 0.1119 2022/11/02 20:53:33 - mmengine - INFO - Epoch(train) [778][45/63] lr: 8.4517e-04 eta: 4:28:27 time: 0.5368 data_time: 0.0104 memory: 14901 loss: 1.1554 loss_prob: 0.6147 loss_thr: 0.4355 loss_db: 0.1051 2022/11/02 20:53:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:53:36 - mmengine - INFO - Epoch(train) [778][50/63] lr: 8.4517e-04 eta: 4:28:21 time: 0.5727 data_time: 0.0390 memory: 14901 loss: 1.1309 loss_prob: 0.5933 loss_thr: 0.4349 loss_db: 0.1028 2022/11/02 20:53:39 - mmengine - INFO - Epoch(train) [778][55/63] lr: 8.4517e-04 eta: 4:28:21 time: 0.6539 data_time: 0.0442 memory: 14901 loss: 1.1090 loss_prob: 0.5841 loss_thr: 0.4227 loss_db: 0.1022 2022/11/02 20:53:42 - mmengine - INFO - Epoch(train) [778][60/63] lr: 8.4517e-04 eta: 4:28:15 time: 0.6588 data_time: 0.0165 memory: 14901 loss: 1.0632 loss_prob: 0.5591 loss_thr: 0.4066 loss_db: 0.0975 2022/11/02 20:53:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:53:50 - mmengine - INFO - Epoch(train) [779][5/63] lr: 8.4337e-04 eta: 4:28:15 time: 0.9149 data_time: 0.2448 memory: 14901 loss: 1.0649 loss_prob: 0.5557 loss_thr: 0.4153 loss_db: 0.0939 2022/11/02 20:53:53 - mmengine - INFO - Epoch(train) [779][10/63] lr: 8.4337e-04 eta: 4:28:08 time: 0.9394 data_time: 0.2448 memory: 14901 loss: 1.0855 loss_prob: 0.5677 loss_thr: 0.4200 loss_db: 0.0977 2022/11/02 20:53:56 - mmengine - INFO - Epoch(train) [779][15/63] lr: 8.4337e-04 eta: 4:28:08 time: 0.5372 data_time: 0.0114 memory: 14901 loss: 1.0382 loss_prob: 0.5383 loss_thr: 0.4043 loss_db: 0.0956 2022/11/02 20:53:59 - mmengine - INFO - Epoch(train) [779][20/63] lr: 8.4337e-04 eta: 4:28:02 time: 0.5276 data_time: 0.0117 memory: 14901 loss: 1.0527 loss_prob: 0.5543 loss_thr: 0.4033 loss_db: 0.0950 2022/11/02 20:54:01 - mmengine - INFO - Epoch(train) [779][25/63] lr: 8.4337e-04 eta: 4:28:02 time: 0.5426 data_time: 0.0114 memory: 14901 loss: 1.0215 loss_prob: 0.5334 loss_thr: 0.3974 loss_db: 0.0907 2022/11/02 20:54:04 - mmengine - INFO - Epoch(train) [779][30/63] lr: 8.4337e-04 eta: 4:27:55 time: 0.5452 data_time: 0.0370 memory: 14901 loss: 1.0125 loss_prob: 0.5269 loss_thr: 0.3952 loss_db: 0.0904 2022/11/02 20:54:07 - mmengine - INFO - Epoch(train) [779][35/63] lr: 8.4337e-04 eta: 4:27:55 time: 0.6220 data_time: 0.0356 memory: 14901 loss: 1.0385 loss_prob: 0.5393 loss_thr: 0.4057 loss_db: 0.0936 2022/11/02 20:54:10 - mmengine - INFO - Epoch(train) [779][40/63] lr: 8.4337e-04 eta: 4:27:49 time: 0.6145 data_time: 0.0130 memory: 14901 loss: 1.0525 loss_prob: 0.5425 loss_thr: 0.4133 loss_db: 0.0967 2022/11/02 20:54:13 - mmengine - INFO - Epoch(train) [779][45/63] lr: 8.4337e-04 eta: 4:27:49 time: 0.5529 data_time: 0.0150 memory: 14901 loss: 1.1072 loss_prob: 0.5840 loss_thr: 0.4219 loss_db: 0.1013 2022/11/02 20:54:16 - mmengine - INFO - Epoch(train) [779][50/63] lr: 8.4337e-04 eta: 4:27:43 time: 0.5760 data_time: 0.0204 memory: 14901 loss: 1.1393 loss_prob: 0.6117 loss_thr: 0.4252 loss_db: 0.1023 2022/11/02 20:54:19 - mmengine - INFO - Epoch(train) [779][55/63] lr: 8.4337e-04 eta: 4:27:43 time: 0.6062 data_time: 0.0285 memory: 14901 loss: 1.0642 loss_prob: 0.5594 loss_thr: 0.4089 loss_db: 0.0959 2022/11/02 20:54:22 - mmengine - INFO - Epoch(train) [779][60/63] lr: 8.4337e-04 eta: 4:27:37 time: 0.6138 data_time: 0.0219 memory: 14901 loss: 1.0388 loss_prob: 0.5445 loss_thr: 0.3994 loss_db: 0.0949 2022/11/02 20:54:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:54:30 - mmengine - INFO - Epoch(train) [780][5/63] lr: 8.4156e-04 eta: 4:27:37 time: 0.9422 data_time: 0.2934 memory: 14901 loss: 1.0549 loss_prob: 0.5480 loss_thr: 0.4118 loss_db: 0.0951 2022/11/02 20:54:34 - mmengine - INFO - Epoch(train) [780][10/63] lr: 8.4156e-04 eta: 4:27:31 time: 1.0309 data_time: 0.2916 memory: 14901 loss: 0.9867 loss_prob: 0.5172 loss_thr: 0.3821 loss_db: 0.0874 2022/11/02 20:54:38 - mmengine - INFO - Epoch(train) [780][15/63] lr: 8.4156e-04 eta: 4:27:31 time: 0.7494 data_time: 0.0137 memory: 14901 loss: 1.0780 loss_prob: 0.5777 loss_thr: 0.4023 loss_db: 0.0981 2022/11/02 20:54:42 - mmengine - INFO - Epoch(train) [780][20/63] lr: 8.4156e-04 eta: 4:27:26 time: 0.7809 data_time: 0.0118 memory: 14901 loss: 1.0395 loss_prob: 0.5575 loss_thr: 0.3881 loss_db: 0.0939 2022/11/02 20:54:44 - mmengine - INFO - Epoch(train) [780][25/63] lr: 8.4156e-04 eta: 4:27:26 time: 0.6345 data_time: 0.0131 memory: 14901 loss: 1.0132 loss_prob: 0.5401 loss_thr: 0.3812 loss_db: 0.0919 2022/11/02 20:54:47 - mmengine - INFO - Epoch(train) [780][30/63] lr: 8.4156e-04 eta: 4:27:19 time: 0.5773 data_time: 0.0417 memory: 14901 loss: 1.0326 loss_prob: 0.5417 loss_thr: 0.3950 loss_db: 0.0959 2022/11/02 20:54:50 - mmengine - INFO - Epoch(train) [780][35/63] lr: 8.4156e-04 eta: 4:27:19 time: 0.5697 data_time: 0.0349 memory: 14901 loss: 1.0376 loss_prob: 0.5408 loss_thr: 0.4018 loss_db: 0.0950 2022/11/02 20:54:52 - mmengine - INFO - Epoch(train) [780][40/63] lr: 8.4156e-04 eta: 4:27:13 time: 0.5010 data_time: 0.0089 memory: 14901 loss: 1.1499 loss_prob: 0.6339 loss_thr: 0.4137 loss_db: 0.1024 2022/11/02 20:54:55 - mmengine - INFO - Epoch(train) [780][45/63] lr: 8.4156e-04 eta: 4:27:13 time: 0.5175 data_time: 0.0128 memory: 14901 loss: 1.0757 loss_prob: 0.5886 loss_thr: 0.3926 loss_db: 0.0945 2022/11/02 20:54:58 - mmengine - INFO - Epoch(train) [780][50/63] lr: 8.4156e-04 eta: 4:27:06 time: 0.5277 data_time: 0.0167 memory: 14901 loss: 0.9888 loss_prob: 0.5141 loss_thr: 0.3865 loss_db: 0.0882 2022/11/02 20:55:00 - mmengine - INFO - Epoch(train) [780][55/63] lr: 8.4156e-04 eta: 4:27:06 time: 0.5209 data_time: 0.0303 memory: 14901 loss: 1.1904 loss_prob: 0.6439 loss_thr: 0.4396 loss_db: 0.1070 2022/11/02 20:55:03 - mmengine - INFO - Epoch(train) [780][60/63] lr: 8.4156e-04 eta: 4:27:00 time: 0.5001 data_time: 0.0263 memory: 14901 loss: 1.1729 loss_prob: 0.6350 loss_thr: 0.4325 loss_db: 0.1053 2022/11/02 20:55:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:55:04 - mmengine - INFO - Saving checkpoint at 780 epochs 2022/11/02 20:55:08 - mmengine - INFO - Epoch(val) [780][5/500] eta: 4:27:00 time: 0.0487 data_time: 0.0060 memory: 14901 2022/11/02 20:55:09 - mmengine - INFO - Epoch(val) [780][10/500] eta: 0:00:24 time: 0.0503 data_time: 0.0065 memory: 1008 2022/11/02 20:55:09 - mmengine - INFO - Epoch(val) [780][15/500] eta: 0:00:24 time: 0.0437 data_time: 0.0038 memory: 1008 2022/11/02 20:55:09 - mmengine - INFO - Epoch(val) [780][20/500] eta: 0:00:20 time: 0.0425 data_time: 0.0032 memory: 1008 2022/11/02 20:55:09 - mmengine - INFO - Epoch(val) [780][25/500] eta: 0:00:20 time: 0.0452 data_time: 0.0042 memory: 1008 2022/11/02 20:55:10 - mmengine - INFO - Epoch(val) [780][30/500] eta: 0:00:25 time: 0.0534 data_time: 0.0044 memory: 1008 2022/11/02 20:55:10 - mmengine - INFO - Epoch(val) [780][35/500] eta: 0:00:25 time: 0.0483 data_time: 0.0030 memory: 1008 2022/11/02 20:55:10 - mmengine - INFO - Epoch(val) [780][40/500] eta: 0:00:22 time: 0.0481 data_time: 0.0031 memory: 1008 2022/11/02 20:55:10 - mmengine - INFO - Epoch(val) [780][45/500] eta: 0:00:22 time: 0.0522 data_time: 0.0033 memory: 1008 2022/11/02 20:55:11 - mmengine - INFO - Epoch(val) [780][50/500] eta: 0:00:21 time: 0.0484 data_time: 0.0034 memory: 1008 2022/11/02 20:55:11 - mmengine - INFO - Epoch(val) [780][55/500] eta: 0:00:21 time: 0.0473 data_time: 0.0032 memory: 1008 2022/11/02 20:55:11 - mmengine - INFO - Epoch(val) [780][60/500] eta: 0:00:18 time: 0.0417 data_time: 0.0029 memory: 1008 2022/11/02 20:55:11 - mmengine - INFO - Epoch(val) [780][65/500] eta: 0:00:18 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 20:55:12 - mmengine - INFO - Epoch(val) [780][70/500] eta: 0:00:20 time: 0.0481 data_time: 0.0032 memory: 1008 2022/11/02 20:55:12 - mmengine - INFO - Epoch(val) [780][75/500] eta: 0:00:20 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/02 20:55:12 - mmengine - INFO - Epoch(val) [780][80/500] eta: 0:00:15 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/02 20:55:12 - mmengine - INFO - Epoch(val) [780][85/500] eta: 0:00:15 time: 0.0374 data_time: 0.0028 memory: 1008 2022/11/02 20:55:12 - mmengine - INFO - Epoch(val) [780][90/500] eta: 0:00:17 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/02 20:55:13 - mmengine - INFO - Epoch(val) [780][95/500] eta: 0:00:17 time: 0.0467 data_time: 0.0030 memory: 1008 2022/11/02 20:55:13 - mmengine - INFO - Epoch(val) [780][100/500] eta: 0:00:17 time: 0.0433 data_time: 0.0034 memory: 1008 2022/11/02 20:55:13 - mmengine - INFO - Epoch(val) [780][105/500] eta: 0:00:17 time: 0.0488 data_time: 0.0045 memory: 1008 2022/11/02 20:55:13 - mmengine - INFO - Epoch(val) [780][110/500] eta: 0:00:18 time: 0.0471 data_time: 0.0040 memory: 1008 2022/11/02 20:55:13 - mmengine - INFO - Epoch(val) [780][115/500] eta: 0:00:18 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 20:55:14 - mmengine - INFO - Epoch(val) [780][120/500] eta: 0:00:18 time: 0.0483 data_time: 0.0033 memory: 1008 2022/11/02 20:55:14 - mmengine - INFO - Epoch(val) [780][125/500] eta: 0:00:18 time: 0.0458 data_time: 0.0032 memory: 1008 2022/11/02 20:55:14 - mmengine - INFO - Epoch(val) [780][130/500] eta: 0:00:16 time: 0.0457 data_time: 0.0034 memory: 1008 2022/11/02 20:55:14 - mmengine - INFO - Epoch(val) [780][135/500] eta: 0:00:16 time: 0.0471 data_time: 0.0044 memory: 1008 2022/11/02 20:55:15 - mmengine - INFO - Epoch(val) [780][140/500] eta: 0:00:15 time: 0.0423 data_time: 0.0040 memory: 1008 2022/11/02 20:55:15 - mmengine - INFO - Epoch(val) [780][145/500] eta: 0:00:15 time: 0.0491 data_time: 0.0031 memory: 1008 2022/11/02 20:55:15 - mmengine - INFO - Epoch(val) [780][150/500] eta: 0:00:17 time: 0.0507 data_time: 0.0033 memory: 1008 2022/11/02 20:55:15 - mmengine - INFO - Epoch(val) [780][155/500] eta: 0:00:17 time: 0.0480 data_time: 0.0032 memory: 1008 2022/11/02 20:55:16 - mmengine - INFO - Epoch(val) [780][160/500] eta: 0:00:15 time: 0.0464 data_time: 0.0029 memory: 1008 2022/11/02 20:55:16 - mmengine - INFO - Epoch(val) [780][165/500] eta: 0:00:15 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 20:55:16 - mmengine - INFO - Epoch(val) [780][170/500] eta: 0:00:14 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/02 20:55:16 - mmengine - INFO - Epoch(val) [780][175/500] eta: 0:00:14 time: 0.0417 data_time: 0.0029 memory: 1008 2022/11/02 20:55:16 - mmengine - INFO - Epoch(val) [780][180/500] eta: 0:00:12 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 20:55:17 - mmengine - INFO - Epoch(val) [780][185/500] eta: 0:00:12 time: 0.0443 data_time: 0.0026 memory: 1008 2022/11/02 20:55:17 - mmengine - INFO - Epoch(val) [780][190/500] eta: 0:00:13 time: 0.0435 data_time: 0.0025 memory: 1008 2022/11/02 20:55:17 - mmengine - INFO - Epoch(val) [780][195/500] eta: 0:00:13 time: 0.0408 data_time: 0.0030 memory: 1008 2022/11/02 20:55:17 - mmengine - INFO - Epoch(val) [780][200/500] eta: 0:00:14 time: 0.0478 data_time: 0.0031 memory: 1008 2022/11/02 20:55:18 - mmengine - INFO - Epoch(val) [780][205/500] eta: 0:00:14 time: 0.0490 data_time: 0.0029 memory: 1008 2022/11/02 20:55:18 - mmengine - INFO - Epoch(val) [780][210/500] eta: 0:00:12 time: 0.0415 data_time: 0.0031 memory: 1008 2022/11/02 20:55:18 - mmengine - INFO - Epoch(val) [780][215/500] eta: 0:00:12 time: 0.0414 data_time: 0.0029 memory: 1008 2022/11/02 20:55:18 - mmengine - INFO - Epoch(val) [780][220/500] eta: 0:00:12 time: 0.0460 data_time: 0.0028 memory: 1008 2022/11/02 20:55:18 - mmengine - INFO - Epoch(val) [780][225/500] eta: 0:00:12 time: 0.0492 data_time: 0.0033 memory: 1008 2022/11/02 20:55:19 - mmengine - INFO - Epoch(val) [780][230/500] eta: 0:00:12 time: 0.0460 data_time: 0.0033 memory: 1008 2022/11/02 20:55:19 - mmengine - INFO - Epoch(val) [780][235/500] eta: 0:00:12 time: 0.0449 data_time: 0.0029 memory: 1008 2022/11/02 20:55:19 - mmengine - INFO - Epoch(val) [780][240/500] eta: 0:00:11 time: 0.0452 data_time: 0.0029 memory: 1008 2022/11/02 20:55:19 - mmengine - INFO - Epoch(val) [780][245/500] eta: 0:00:11 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 20:55:20 - mmengine - INFO - Epoch(val) [780][250/500] eta: 0:00:10 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 20:55:20 - mmengine - INFO - Epoch(val) [780][255/500] eta: 0:00:10 time: 0.0430 data_time: 0.0029 memory: 1008 2022/11/02 20:55:20 - mmengine - INFO - Epoch(val) [780][260/500] eta: 0:00:09 time: 0.0396 data_time: 0.0029 memory: 1008 2022/11/02 20:55:20 - mmengine - INFO - Epoch(val) [780][265/500] eta: 0:00:09 time: 0.0389 data_time: 0.0026 memory: 1008 2022/11/02 20:55:20 - mmengine - INFO - Epoch(val) [780][270/500] eta: 0:00:09 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/02 20:55:21 - mmengine - INFO - Epoch(val) [780][275/500] eta: 0:00:09 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 20:55:21 - mmengine - INFO - Epoch(val) [780][280/500] eta: 0:00:09 time: 0.0421 data_time: 0.0026 memory: 1008 2022/11/02 20:55:21 - mmengine - INFO - Epoch(val) [780][285/500] eta: 0:00:09 time: 0.0457 data_time: 0.0034 memory: 1008 2022/11/02 20:55:21 - mmengine - INFO - Epoch(val) [780][290/500] eta: 0:00:09 time: 0.0438 data_time: 0.0032 memory: 1008 2022/11/02 20:55:21 - mmengine - INFO - Epoch(val) [780][295/500] eta: 0:00:09 time: 0.0449 data_time: 0.0026 memory: 1008 2022/11/02 20:55:22 - mmengine - INFO - Epoch(val) [780][300/500] eta: 0:00:08 time: 0.0428 data_time: 0.0026 memory: 1008 2022/11/02 20:55:22 - mmengine - INFO - Epoch(val) [780][305/500] eta: 0:00:08 time: 0.0390 data_time: 0.0025 memory: 1008 2022/11/02 20:55:22 - mmengine - INFO - Epoch(val) [780][310/500] eta: 0:00:07 time: 0.0414 data_time: 0.0026 memory: 1008 2022/11/02 20:55:22 - mmengine - INFO - Epoch(val) [780][315/500] eta: 0:00:07 time: 0.0471 data_time: 0.0029 memory: 1008 2022/11/02 20:55:23 - mmengine - INFO - Epoch(val) [780][320/500] eta: 0:00:07 time: 0.0427 data_time: 0.0029 memory: 1008 2022/11/02 20:55:23 - mmengine - INFO - Epoch(val) [780][325/500] eta: 0:00:07 time: 0.0607 data_time: 0.0030 memory: 1008 2022/11/02 20:55:23 - mmengine - INFO - Epoch(val) [780][330/500] eta: 0:00:10 time: 0.0598 data_time: 0.0029 memory: 1008 2022/11/02 20:55:23 - mmengine - INFO - Epoch(val) [780][335/500] eta: 0:00:10 time: 0.0357 data_time: 0.0026 memory: 1008 2022/11/02 20:55:24 - mmengine - INFO - Epoch(val) [780][340/500] eta: 0:00:09 time: 0.0572 data_time: 0.0027 memory: 1008 2022/11/02 20:55:24 - mmengine - INFO - Epoch(val) [780][345/500] eta: 0:00:09 time: 0.0582 data_time: 0.0028 memory: 1008 2022/11/02 20:55:24 - mmengine - INFO - Epoch(val) [780][350/500] eta: 0:00:06 time: 0.0431 data_time: 0.0028 memory: 1008 2022/11/02 20:55:24 - mmengine - INFO - Epoch(val) [780][355/500] eta: 0:00:06 time: 0.0446 data_time: 0.0027 memory: 1008 2022/11/02 20:55:25 - mmengine - INFO - Epoch(val) [780][360/500] eta: 0:00:05 time: 0.0419 data_time: 0.0025 memory: 1008 2022/11/02 20:55:25 - mmengine - INFO - Epoch(val) [780][365/500] eta: 0:00:05 time: 0.0440 data_time: 0.0026 memory: 1008 2022/11/02 20:55:25 - mmengine - INFO - Epoch(val) [780][370/500] eta: 0:00:05 time: 0.0405 data_time: 0.0028 memory: 1008 2022/11/02 20:55:25 - mmengine - INFO - Epoch(val) [780][375/500] eta: 0:00:05 time: 0.0364 data_time: 0.0028 memory: 1008 2022/11/02 20:55:25 - mmengine - INFO - Epoch(val) [780][380/500] eta: 0:00:05 time: 0.0425 data_time: 0.0027 memory: 1008 2022/11/02 20:55:26 - mmengine - INFO - Epoch(val) [780][385/500] eta: 0:00:05 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/02 20:55:26 - mmengine - INFO - Epoch(val) [780][390/500] eta: 0:00:04 time: 0.0413 data_time: 0.0028 memory: 1008 2022/11/02 20:55:26 - mmengine - INFO - Epoch(val) [780][395/500] eta: 0:00:04 time: 0.0462 data_time: 0.0035 memory: 1008 2022/11/02 20:55:26 - mmengine - INFO - Epoch(val) [780][400/500] eta: 0:00:04 time: 0.0439 data_time: 0.0035 memory: 1008 2022/11/02 20:55:26 - mmengine - INFO - Epoch(val) [780][405/500] eta: 0:00:04 time: 0.0425 data_time: 0.0032 memory: 1008 2022/11/02 20:55:27 - mmengine - INFO - Epoch(val) [780][410/500] eta: 0:00:04 time: 0.0445 data_time: 0.0030 memory: 1008 2022/11/02 20:55:27 - mmengine - INFO - Epoch(val) [780][415/500] eta: 0:00:04 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 20:55:27 - mmengine - INFO - Epoch(val) [780][420/500] eta: 0:00:02 time: 0.0368 data_time: 0.0026 memory: 1008 2022/11/02 20:55:27 - mmengine - INFO - Epoch(val) [780][425/500] eta: 0:00:02 time: 0.0374 data_time: 0.0028 memory: 1008 2022/11/02 20:55:27 - mmengine - INFO - Epoch(val) [780][430/500] eta: 0:00:02 time: 0.0416 data_time: 0.0030 memory: 1008 2022/11/02 20:55:28 - mmengine - INFO - Epoch(val) [780][435/500] eta: 0:00:02 time: 0.0430 data_time: 0.0031 memory: 1008 2022/11/02 20:55:28 - mmengine - INFO - Epoch(val) [780][440/500] eta: 0:00:02 time: 0.0436 data_time: 0.0028 memory: 1008 2022/11/02 20:55:28 - mmengine - INFO - Epoch(val) [780][445/500] eta: 0:00:02 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/02 20:55:28 - mmengine - INFO - Epoch(val) [780][450/500] eta: 0:00:02 time: 0.0469 data_time: 0.0027 memory: 1008 2022/11/02 20:55:29 - mmengine - INFO - Epoch(val) [780][455/500] eta: 0:00:02 time: 0.0468 data_time: 0.0027 memory: 1008 2022/11/02 20:55:29 - mmengine - INFO - Epoch(val) [780][460/500] eta: 0:00:01 time: 0.0381 data_time: 0.0026 memory: 1008 2022/11/02 20:55:29 - mmengine - INFO - Epoch(val) [780][465/500] eta: 0:00:01 time: 0.0374 data_time: 0.0028 memory: 1008 2022/11/02 20:55:29 - mmengine - INFO - Epoch(val) [780][470/500] eta: 0:00:01 time: 0.0412 data_time: 0.0029 memory: 1008 2022/11/02 20:55:29 - mmengine - INFO - Epoch(val) [780][475/500] eta: 0:00:01 time: 0.0398 data_time: 0.0029 memory: 1008 2022/11/02 20:55:30 - mmengine - INFO - Epoch(val) [780][480/500] eta: 0:00:00 time: 0.0377 data_time: 0.0027 memory: 1008 2022/11/02 20:55:30 - mmengine - INFO - Epoch(val) [780][485/500] eta: 0:00:00 time: 0.0411 data_time: 0.0034 memory: 1008 2022/11/02 20:55:30 - mmengine - INFO - Epoch(val) [780][490/500] eta: 0:00:00 time: 0.0451 data_time: 0.0039 memory: 1008 2022/11/02 20:55:30 - mmengine - INFO - Epoch(val) [780][495/500] eta: 0:00:00 time: 0.0472 data_time: 0.0032 memory: 1008 2022/11/02 20:55:30 - mmengine - INFO - Epoch(val) [780][500/500] eta: 0:00:00 time: 0.0405 data_time: 0.0028 memory: 1008 2022/11/02 20:55:30 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8276, precision: 0.7265, hmean: 0.7738 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8276, precision: 0.7973, hmean: 0.8122 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8272, precision: 0.8320, hmean: 0.8296 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8214, precision: 0.8551, hmean: 0.8379 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7968, precision: 0.8884, hmean: 0.8401 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6331, precision: 0.9379, hmean: 0.7560 2022/11/02 20:55:30 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0775, precision: 0.9583, hmean: 0.1434 2022/11/02 20:55:30 - mmengine - INFO - Epoch(val) [780][500/500] icdar/precision: 0.8884 icdar/recall: 0.7968 icdar/hmean: 0.8401 2022/11/02 20:55:36 - mmengine - INFO - Epoch(train) [781][5/63] lr: 8.3976e-04 eta: 0:00:00 time: 0.7464 data_time: 0.2448 memory: 14901 loss: 1.0909 loss_prob: 0.5774 loss_thr: 0.4126 loss_db: 0.1008 2022/11/02 20:55:38 - mmengine - INFO - Epoch(train) [781][10/63] lr: 8.3976e-04 eta: 4:26:52 time: 0.7643 data_time: 0.2424 memory: 14901 loss: 1.1858 loss_prob: 0.6439 loss_thr: 0.4355 loss_db: 0.1064 2022/11/02 20:55:41 - mmengine - INFO - Epoch(train) [781][15/63] lr: 8.3976e-04 eta: 4:26:52 time: 0.5124 data_time: 0.0118 memory: 14901 loss: 1.1952 loss_prob: 0.6511 loss_thr: 0.4364 loss_db: 0.1077 2022/11/02 20:55:45 - mmengine - INFO - Epoch(train) [781][20/63] lr: 8.3976e-04 eta: 4:26:46 time: 0.6904 data_time: 0.0168 memory: 14901 loss: 1.0970 loss_prob: 0.5806 loss_thr: 0.4164 loss_db: 0.0999 2022/11/02 20:55:49 - mmengine - INFO - Epoch(train) [781][25/63] lr: 8.3976e-04 eta: 4:26:46 time: 0.8444 data_time: 0.0295 memory: 14901 loss: 1.1214 loss_prob: 0.5988 loss_thr: 0.4222 loss_db: 0.1004 2022/11/02 20:55:53 - mmengine - INFO - Epoch(train) [781][30/63] lr: 8.3976e-04 eta: 4:26:41 time: 0.8200 data_time: 0.0394 memory: 14901 loss: 1.1414 loss_prob: 0.6100 loss_thr: 0.4270 loss_db: 0.1045 2022/11/02 20:55:57 - mmengine - INFO - Epoch(train) [781][35/63] lr: 8.3976e-04 eta: 4:26:41 time: 0.7429 data_time: 0.0291 memory: 14901 loss: 1.1415 loss_prob: 0.6060 loss_thr: 0.4292 loss_db: 0.1064 2022/11/02 20:55:59 - mmengine - INFO - Epoch(train) [781][40/63] lr: 8.3976e-04 eta: 4:26:35 time: 0.6193 data_time: 0.0133 memory: 14901 loss: 1.1544 loss_prob: 0.6154 loss_thr: 0.4345 loss_db: 0.1045 2022/11/02 20:56:03 - mmengine - INFO - Epoch(train) [781][45/63] lr: 8.3976e-04 eta: 4:26:35 time: 0.6141 data_time: 0.0152 memory: 14901 loss: 1.2718 loss_prob: 0.6962 loss_thr: 0.4622 loss_db: 0.1133 2022/11/02 20:56:06 - mmengine - INFO - Epoch(train) [781][50/63] lr: 8.3976e-04 eta: 4:26:30 time: 0.6685 data_time: 0.0311 memory: 14901 loss: 1.2361 loss_prob: 0.6664 loss_thr: 0.4578 loss_db: 0.1119 2022/11/02 20:56:09 - mmengine - INFO - Epoch(train) [781][55/63] lr: 8.3976e-04 eta: 4:26:30 time: 0.6006 data_time: 0.0363 memory: 14901 loss: 1.0924 loss_prob: 0.5725 loss_thr: 0.4186 loss_db: 0.1013 2022/11/02 20:56:12 - mmengine - INFO - Epoch(train) [781][60/63] lr: 8.3976e-04 eta: 4:26:23 time: 0.5453 data_time: 0.0233 memory: 14901 loss: 1.0998 loss_prob: 0.5836 loss_thr: 0.4147 loss_db: 0.1015 2022/11/02 20:56:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:56:19 - mmengine - INFO - Epoch(train) [782][5/63] lr: 8.3796e-04 eta: 4:26:23 time: 0.8371 data_time: 0.2677 memory: 14901 loss: 1.1466 loss_prob: 0.6120 loss_thr: 0.4303 loss_db: 0.1043 2022/11/02 20:56:22 - mmengine - INFO - Epoch(train) [782][10/63] lr: 8.3796e-04 eta: 4:26:16 time: 0.8401 data_time: 0.2686 memory: 14901 loss: 1.0727 loss_prob: 0.5689 loss_thr: 0.4050 loss_db: 0.0988 2022/11/02 20:56:24 - mmengine - INFO - Epoch(train) [782][15/63] lr: 8.3796e-04 eta: 4:26:16 time: 0.5473 data_time: 0.0120 memory: 14901 loss: 1.0883 loss_prob: 0.5793 loss_thr: 0.4077 loss_db: 0.1014 2022/11/02 20:56:29 - mmengine - INFO - Epoch(train) [782][20/63] lr: 8.3796e-04 eta: 4:26:10 time: 0.6962 data_time: 0.0098 memory: 14901 loss: 1.1409 loss_prob: 0.6010 loss_thr: 0.4355 loss_db: 0.1044 2022/11/02 20:56:31 - mmengine - INFO - Epoch(train) [782][25/63] lr: 8.3796e-04 eta: 4:26:10 time: 0.6941 data_time: 0.0301 memory: 14901 loss: 1.1572 loss_prob: 0.6040 loss_thr: 0.4496 loss_db: 0.1036 2022/11/02 20:56:34 - mmengine - INFO - Epoch(train) [782][30/63] lr: 8.3796e-04 eta: 4:26:04 time: 0.5821 data_time: 0.0520 memory: 14901 loss: 1.1950 loss_prob: 0.6498 loss_thr: 0.4387 loss_db: 0.1065 2022/11/02 20:56:37 - mmengine - INFO - Epoch(train) [782][35/63] lr: 8.3796e-04 eta: 4:26:04 time: 0.6127 data_time: 0.0303 memory: 14901 loss: 1.1559 loss_prob: 0.6289 loss_thr: 0.4229 loss_db: 0.1041 2022/11/02 20:56:41 - mmengine - INFO - Epoch(train) [782][40/63] lr: 8.3796e-04 eta: 4:25:58 time: 0.6408 data_time: 0.0107 memory: 14901 loss: 1.0530 loss_prob: 0.5447 loss_thr: 0.4140 loss_db: 0.0943 2022/11/02 20:56:44 - mmengine - INFO - Epoch(train) [782][45/63] lr: 8.3796e-04 eta: 4:25:58 time: 0.6730 data_time: 0.0112 memory: 14901 loss: 1.0503 loss_prob: 0.5550 loss_thr: 0.3993 loss_db: 0.0960 2022/11/02 20:56:47 - mmengine - INFO - Epoch(train) [782][50/63] lr: 8.3796e-04 eta: 4:25:52 time: 0.6387 data_time: 0.0262 memory: 14901 loss: 1.0480 loss_prob: 0.5552 loss_thr: 0.3984 loss_db: 0.0944 2022/11/02 20:56:50 - mmengine - INFO - Epoch(train) [782][55/63] lr: 8.3796e-04 eta: 4:25:52 time: 0.6166 data_time: 0.0299 memory: 14901 loss: 0.9953 loss_prob: 0.5152 loss_thr: 0.3923 loss_db: 0.0879 2022/11/02 20:56:53 - mmengine - INFO - Epoch(train) [782][60/63] lr: 8.3796e-04 eta: 4:25:46 time: 0.5899 data_time: 0.0134 memory: 14901 loss: 1.0493 loss_prob: 0.5587 loss_thr: 0.3941 loss_db: 0.0965 2022/11/02 20:56:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:57:00 - mmengine - INFO - Epoch(train) [783][5/63] lr: 8.3615e-04 eta: 4:25:46 time: 0.8339 data_time: 0.2389 memory: 14901 loss: 1.0991 loss_prob: 0.5865 loss_thr: 0.4137 loss_db: 0.0989 2022/11/02 20:57:03 - mmengine - INFO - Epoch(train) [783][10/63] lr: 8.3615e-04 eta: 4:25:39 time: 0.9106 data_time: 0.2388 memory: 14901 loss: 1.2263 loss_prob: 0.6505 loss_thr: 0.4637 loss_db: 0.1120 2022/11/02 20:57:06 - mmengine - INFO - Epoch(train) [783][15/63] lr: 8.3615e-04 eta: 4:25:39 time: 0.5767 data_time: 0.0123 memory: 14901 loss: 1.1819 loss_prob: 0.6244 loss_thr: 0.4484 loss_db: 0.1091 2022/11/02 20:57:09 - mmengine - INFO - Epoch(train) [783][20/63] lr: 8.3615e-04 eta: 4:25:33 time: 0.5950 data_time: 0.0123 memory: 14901 loss: 1.0357 loss_prob: 0.5493 loss_thr: 0.3930 loss_db: 0.0934 2022/11/02 20:57:13 - mmengine - INFO - Epoch(train) [783][25/63] lr: 8.3615e-04 eta: 4:25:33 time: 0.6466 data_time: 0.0155 memory: 14901 loss: 1.0295 loss_prob: 0.5488 loss_thr: 0.3873 loss_db: 0.0934 2022/11/02 20:57:16 - mmengine - INFO - Epoch(train) [783][30/63] lr: 8.3615e-04 eta: 4:25:27 time: 0.7027 data_time: 0.0438 memory: 14901 loss: 1.2098 loss_prob: 0.6614 loss_thr: 0.4356 loss_db: 0.1128 2022/11/02 20:57:19 - mmengine - INFO - Epoch(train) [783][35/63] lr: 8.3615e-04 eta: 4:25:27 time: 0.6615 data_time: 0.0434 memory: 14901 loss: 1.1681 loss_prob: 0.6315 loss_thr: 0.4277 loss_db: 0.1089 2022/11/02 20:57:22 - mmengine - INFO - Epoch(train) [783][40/63] lr: 8.3615e-04 eta: 4:25:21 time: 0.5829 data_time: 0.0128 memory: 14901 loss: 1.0638 loss_prob: 0.5539 loss_thr: 0.4142 loss_db: 0.0957 2022/11/02 20:57:25 - mmengine - INFO - Epoch(train) [783][45/63] lr: 8.3615e-04 eta: 4:25:21 time: 0.5795 data_time: 0.0108 memory: 14901 loss: 1.0983 loss_prob: 0.5755 loss_thr: 0.4245 loss_db: 0.0982 2022/11/02 20:57:28 - mmengine - INFO - Epoch(train) [783][50/63] lr: 8.3615e-04 eta: 4:25:15 time: 0.5831 data_time: 0.0262 memory: 14901 loss: 1.0579 loss_prob: 0.5548 loss_thr: 0.4078 loss_db: 0.0953 2022/11/02 20:57:31 - mmengine - INFO - Epoch(train) [783][55/63] lr: 8.3615e-04 eta: 4:25:15 time: 0.5755 data_time: 0.0244 memory: 14901 loss: 1.0522 loss_prob: 0.5527 loss_thr: 0.4031 loss_db: 0.0964 2022/11/02 20:57:34 - mmengine - INFO - Epoch(train) [783][60/63] lr: 8.3615e-04 eta: 4:25:09 time: 0.6268 data_time: 0.0122 memory: 14901 loss: 1.0264 loss_prob: 0.5440 loss_thr: 0.3871 loss_db: 0.0952 2022/11/02 20:57:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:57:41 - mmengine - INFO - Epoch(train) [784][5/63] lr: 8.3435e-04 eta: 4:25:09 time: 0.8237 data_time: 0.2387 memory: 14901 loss: 1.0443 loss_prob: 0.5503 loss_thr: 0.4002 loss_db: 0.0938 2022/11/02 20:57:44 - mmengine - INFO - Epoch(train) [784][10/63] lr: 8.3435e-04 eta: 4:25:01 time: 0.8453 data_time: 0.2404 memory: 14901 loss: 1.0560 loss_prob: 0.5577 loss_thr: 0.4044 loss_db: 0.0940 2022/11/02 20:57:47 - mmengine - INFO - Epoch(train) [784][15/63] lr: 8.3435e-04 eta: 4:25:01 time: 0.5493 data_time: 0.0120 memory: 14901 loss: 1.0601 loss_prob: 0.5508 loss_thr: 0.4141 loss_db: 0.0952 2022/11/02 20:57:51 - mmengine - INFO - Epoch(train) [784][20/63] lr: 8.3435e-04 eta: 4:24:55 time: 0.6486 data_time: 0.0133 memory: 14901 loss: 0.9903 loss_prob: 0.5113 loss_thr: 0.3892 loss_db: 0.0898 2022/11/02 20:57:54 - mmengine - INFO - Epoch(train) [784][25/63] lr: 8.3435e-04 eta: 4:24:55 time: 0.6875 data_time: 0.0448 memory: 14901 loss: 1.0239 loss_prob: 0.5400 loss_thr: 0.3904 loss_db: 0.0935 2022/11/02 20:57:57 - mmengine - INFO - Epoch(train) [784][30/63] lr: 8.3435e-04 eta: 4:24:49 time: 0.6229 data_time: 0.0523 memory: 14901 loss: 1.0660 loss_prob: 0.5591 loss_thr: 0.4112 loss_db: 0.0956 2022/11/02 20:58:00 - mmengine - INFO - Epoch(train) [784][35/63] lr: 8.3435e-04 eta: 4:24:49 time: 0.5725 data_time: 0.0209 memory: 14901 loss: 1.0357 loss_prob: 0.5384 loss_thr: 0.4048 loss_db: 0.0925 2022/11/02 20:58:02 - mmengine - INFO - Epoch(train) [784][40/63] lr: 8.3435e-04 eta: 4:24:43 time: 0.5307 data_time: 0.0120 memory: 14901 loss: 1.0610 loss_prob: 0.5603 loss_thr: 0.4027 loss_db: 0.0980 2022/11/02 20:58:05 - mmengine - INFO - Epoch(train) [784][45/63] lr: 8.3435e-04 eta: 4:24:43 time: 0.5885 data_time: 0.0108 memory: 14901 loss: 1.0252 loss_prob: 0.5379 loss_thr: 0.3934 loss_db: 0.0938 2022/11/02 20:58:08 - mmengine - INFO - Epoch(train) [784][50/63] lr: 8.3435e-04 eta: 4:24:37 time: 0.6097 data_time: 0.0410 memory: 14901 loss: 1.0773 loss_prob: 0.5729 loss_thr: 0.4079 loss_db: 0.0965 2022/11/02 20:58:11 - mmengine - INFO - Epoch(train) [784][55/63] lr: 8.3435e-04 eta: 4:24:37 time: 0.5937 data_time: 0.0478 memory: 14901 loss: 1.1095 loss_prob: 0.5919 loss_thr: 0.4164 loss_db: 0.1011 2022/11/02 20:58:14 - mmengine - INFO - Epoch(train) [784][60/63] lr: 8.3435e-04 eta: 4:24:31 time: 0.5968 data_time: 0.0182 memory: 14901 loss: 1.0095 loss_prob: 0.5301 loss_thr: 0.3866 loss_db: 0.0928 2022/11/02 20:58:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:58:22 - mmengine - INFO - Epoch(train) [785][5/63] lr: 8.3254e-04 eta: 4:24:31 time: 0.9151 data_time: 0.2418 memory: 14901 loss: 1.0423 loss_prob: 0.5419 loss_thr: 0.4049 loss_db: 0.0955 2022/11/02 20:58:25 - mmengine - INFO - Epoch(train) [785][10/63] lr: 8.3254e-04 eta: 4:24:24 time: 0.9118 data_time: 0.2426 memory: 14901 loss: 1.0582 loss_prob: 0.5531 loss_thr: 0.4067 loss_db: 0.0985 2022/11/02 20:58:28 - mmengine - INFO - Epoch(train) [785][15/63] lr: 8.3254e-04 eta: 4:24:24 time: 0.6261 data_time: 0.0126 memory: 14901 loss: 1.0335 loss_prob: 0.5329 loss_thr: 0.4085 loss_db: 0.0921 2022/11/02 20:58:33 - mmengine - INFO - Epoch(train) [785][20/63] lr: 8.3254e-04 eta: 4:24:18 time: 0.7521 data_time: 0.0128 memory: 14901 loss: 1.0976 loss_prob: 0.5690 loss_thr: 0.4319 loss_db: 0.0968 2022/11/02 20:58:36 - mmengine - INFO - Epoch(train) [785][25/63] lr: 8.3254e-04 eta: 4:24:18 time: 0.8048 data_time: 0.0260 memory: 14901 loss: 1.1270 loss_prob: 0.5925 loss_thr: 0.4313 loss_db: 0.1033 2022/11/02 20:58:41 - mmengine - INFO - Epoch(train) [785][30/63] lr: 8.3254e-04 eta: 4:24:13 time: 0.7795 data_time: 0.0398 memory: 14901 loss: 1.0528 loss_prob: 0.5507 loss_thr: 0.4050 loss_db: 0.0971 2022/11/02 20:58:43 - mmengine - INFO - Epoch(train) [785][35/63] lr: 8.3254e-04 eta: 4:24:13 time: 0.6720 data_time: 0.0242 memory: 14901 loss: 0.9766 loss_prob: 0.5092 loss_thr: 0.3796 loss_db: 0.0879 2022/11/02 20:58:46 - mmengine - INFO - Epoch(train) [785][40/63] lr: 8.3254e-04 eta: 4:24:07 time: 0.5043 data_time: 0.0098 memory: 14901 loss: 0.9605 loss_prob: 0.5018 loss_thr: 0.3732 loss_db: 0.0855 2022/11/02 20:58:48 - mmengine - INFO - Epoch(train) [785][45/63] lr: 8.3254e-04 eta: 4:24:07 time: 0.5110 data_time: 0.0099 memory: 14901 loss: 0.9968 loss_prob: 0.5111 loss_thr: 0.3952 loss_db: 0.0905 2022/11/02 20:58:51 - mmengine - INFO - Epoch(train) [785][50/63] lr: 8.3254e-04 eta: 4:24:00 time: 0.5669 data_time: 0.0339 memory: 14901 loss: 1.0748 loss_prob: 0.5649 loss_thr: 0.4106 loss_db: 0.0994 2022/11/02 20:58:55 - mmengine - INFO - Epoch(train) [785][55/63] lr: 8.3254e-04 eta: 4:24:00 time: 0.6537 data_time: 0.0348 memory: 14901 loss: 1.0798 loss_prob: 0.5845 loss_thr: 0.3980 loss_db: 0.0973 2022/11/02 20:58:58 - mmengine - INFO - Epoch(train) [785][60/63] lr: 8.3254e-04 eta: 4:23:55 time: 0.6824 data_time: 0.0112 memory: 14901 loss: 1.0188 loss_prob: 0.5429 loss_thr: 0.3836 loss_db: 0.0923 2022/11/02 20:58:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:59:06 - mmengine - INFO - Epoch(train) [786][5/63] lr: 8.3074e-04 eta: 4:23:55 time: 0.8399 data_time: 0.2312 memory: 14901 loss: 1.0453 loss_prob: 0.5474 loss_thr: 0.4050 loss_db: 0.0928 2022/11/02 20:59:08 - mmengine - INFO - Epoch(train) [786][10/63] lr: 8.3074e-04 eta: 4:23:47 time: 0.8815 data_time: 0.2375 memory: 14901 loss: 1.1040 loss_prob: 0.5862 loss_thr: 0.4204 loss_db: 0.0974 2022/11/02 20:59:11 - mmengine - INFO - Epoch(train) [786][15/63] lr: 8.3074e-04 eta: 4:23:47 time: 0.5455 data_time: 0.0192 memory: 14901 loss: 1.1193 loss_prob: 0.5984 loss_thr: 0.4189 loss_db: 0.1021 2022/11/02 20:59:14 - mmengine - INFO - Epoch(train) [786][20/63] lr: 8.3074e-04 eta: 4:23:41 time: 0.5395 data_time: 0.0172 memory: 14901 loss: 1.0348 loss_prob: 0.5481 loss_thr: 0.3943 loss_db: 0.0925 2022/11/02 20:59:16 - mmengine - INFO - Epoch(train) [786][25/63] lr: 8.3074e-04 eta: 4:23:41 time: 0.5408 data_time: 0.0376 memory: 14901 loss: 0.9801 loss_prob: 0.5116 loss_thr: 0.3805 loss_db: 0.0880 2022/11/02 20:59:19 - mmengine - INFO - Epoch(train) [786][30/63] lr: 8.3074e-04 eta: 4:23:35 time: 0.5494 data_time: 0.0399 memory: 14901 loss: 1.0416 loss_prob: 0.5372 loss_thr: 0.4106 loss_db: 0.0938 2022/11/02 20:59:22 - mmengine - INFO - Epoch(train) [786][35/63] lr: 8.3074e-04 eta: 4:23:35 time: 0.5631 data_time: 0.0201 memory: 14901 loss: 1.0701 loss_prob: 0.5515 loss_thr: 0.4229 loss_db: 0.0956 2022/11/02 20:59:25 - mmengine - INFO - Epoch(train) [786][40/63] lr: 8.3074e-04 eta: 4:23:28 time: 0.5559 data_time: 0.0143 memory: 14901 loss: 1.1812 loss_prob: 0.6383 loss_thr: 0.4360 loss_db: 0.1068 2022/11/02 20:59:27 - mmengine - INFO - Epoch(train) [786][45/63] lr: 8.3074e-04 eta: 4:23:28 time: 0.5288 data_time: 0.0128 memory: 14901 loss: 1.1778 loss_prob: 0.6322 loss_thr: 0.4409 loss_db: 0.1048 2022/11/02 20:59:30 - mmengine - INFO - Epoch(train) [786][50/63] lr: 8.3074e-04 eta: 4:23:22 time: 0.5479 data_time: 0.0251 memory: 14901 loss: 1.0499 loss_prob: 0.5413 loss_thr: 0.4160 loss_db: 0.0926 2022/11/02 20:59:33 - mmengine - INFO - Epoch(train) [786][55/63] lr: 8.3074e-04 eta: 4:23:22 time: 0.5656 data_time: 0.0275 memory: 14901 loss: 1.0977 loss_prob: 0.5766 loss_thr: 0.4209 loss_db: 0.1002 2022/11/02 20:59:36 - mmengine - INFO - Epoch(train) [786][60/63] lr: 8.3074e-04 eta: 4:23:16 time: 0.5576 data_time: 0.0187 memory: 14901 loss: 1.0545 loss_prob: 0.5521 loss_thr: 0.4046 loss_db: 0.0978 2022/11/02 20:59:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 20:59:44 - mmengine - INFO - Epoch(train) [787][5/63] lr: 8.2893e-04 eta: 4:23:16 time: 0.9655 data_time: 0.2826 memory: 14901 loss: 1.0305 loss_prob: 0.5408 loss_thr: 0.3982 loss_db: 0.0915 2022/11/02 20:59:47 - mmengine - INFO - Epoch(train) [787][10/63] lr: 8.2893e-04 eta: 4:23:09 time: 0.9834 data_time: 0.2803 memory: 14901 loss: 1.0151 loss_prob: 0.5266 loss_thr: 0.3980 loss_db: 0.0904 2022/11/02 20:59:50 - mmengine - INFO - Epoch(train) [787][15/63] lr: 8.2893e-04 eta: 4:23:09 time: 0.5765 data_time: 0.0083 memory: 14901 loss: 0.9579 loss_prob: 0.4938 loss_thr: 0.3778 loss_db: 0.0863 2022/11/02 20:59:53 - mmengine - INFO - Epoch(train) [787][20/63] lr: 8.2893e-04 eta: 4:23:03 time: 0.5816 data_time: 0.0091 memory: 14901 loss: 1.0323 loss_prob: 0.5327 loss_thr: 0.4069 loss_db: 0.0928 2022/11/02 20:59:57 - mmengine - INFO - Epoch(train) [787][25/63] lr: 8.2893e-04 eta: 4:23:03 time: 0.6642 data_time: 0.0438 memory: 14901 loss: 1.2238 loss_prob: 0.6688 loss_thr: 0.4460 loss_db: 0.1090 2022/11/02 21:00:00 - mmengine - INFO - Epoch(train) [787][30/63] lr: 8.2893e-04 eta: 4:22:57 time: 0.6725 data_time: 0.0466 memory: 14901 loss: 1.2152 loss_prob: 0.6680 loss_thr: 0.4386 loss_db: 0.1086 2022/11/02 21:00:03 - mmengine - INFO - Epoch(train) [787][35/63] lr: 8.2893e-04 eta: 4:22:57 time: 0.6216 data_time: 0.0142 memory: 14901 loss: 1.1043 loss_prob: 0.5725 loss_thr: 0.4329 loss_db: 0.0988 2022/11/02 21:00:06 - mmengine - INFO - Epoch(train) [787][40/63] lr: 8.2893e-04 eta: 4:22:51 time: 0.6198 data_time: 0.0107 memory: 14901 loss: 1.1534 loss_prob: 0.6174 loss_thr: 0.4338 loss_db: 0.1021 2022/11/02 21:00:09 - mmengine - INFO - Epoch(train) [787][45/63] lr: 8.2893e-04 eta: 4:22:51 time: 0.5511 data_time: 0.0090 memory: 14901 loss: 1.1580 loss_prob: 0.6280 loss_thr: 0.4247 loss_db: 0.1053 2022/11/02 21:00:12 - mmengine - INFO - Epoch(train) [787][50/63] lr: 8.2893e-04 eta: 4:22:45 time: 0.5723 data_time: 0.0229 memory: 14901 loss: 1.0716 loss_prob: 0.5624 loss_thr: 0.4114 loss_db: 0.0978 2022/11/02 21:00:14 - mmengine - INFO - Epoch(train) [787][55/63] lr: 8.2893e-04 eta: 4:22:45 time: 0.5529 data_time: 0.0267 memory: 14901 loss: 1.1183 loss_prob: 0.5916 loss_thr: 0.4255 loss_db: 0.1012 2022/11/02 21:00:17 - mmengine - INFO - Epoch(train) [787][60/63] lr: 8.2893e-04 eta: 4:22:38 time: 0.5295 data_time: 0.0105 memory: 14901 loss: 1.1039 loss_prob: 0.5797 loss_thr: 0.4252 loss_db: 0.0990 2022/11/02 21:00:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:00:24 - mmengine - INFO - Epoch(train) [788][5/63] lr: 8.2712e-04 eta: 4:22:38 time: 0.8156 data_time: 0.2914 memory: 14901 loss: 1.1015 loss_prob: 0.5766 loss_thr: 0.4251 loss_db: 0.0998 2022/11/02 21:00:29 - mmengine - INFO - Epoch(train) [788][10/63] lr: 8.2712e-04 eta: 4:22:31 time: 1.0129 data_time: 0.2947 memory: 14901 loss: 1.1618 loss_prob: 0.6216 loss_thr: 0.4330 loss_db: 0.1071 2022/11/02 21:00:32 - mmengine - INFO - Epoch(train) [788][15/63] lr: 8.2712e-04 eta: 4:22:31 time: 0.8213 data_time: 0.0158 memory: 14901 loss: 1.0564 loss_prob: 0.5498 loss_thr: 0.4098 loss_db: 0.0968 2022/11/02 21:00:35 - mmengine - INFO - Epoch(train) [788][20/63] lr: 8.2712e-04 eta: 4:22:26 time: 0.6781 data_time: 0.0131 memory: 14901 loss: 1.0313 loss_prob: 0.5412 loss_thr: 0.3931 loss_db: 0.0970 2022/11/02 21:00:38 - mmengine - INFO - Epoch(train) [788][25/63] lr: 8.2712e-04 eta: 4:22:26 time: 0.6024 data_time: 0.0302 memory: 14901 loss: 1.0527 loss_prob: 0.5582 loss_thr: 0.3987 loss_db: 0.0957 2022/11/02 21:00:41 - mmengine - INFO - Epoch(train) [788][30/63] lr: 8.2712e-04 eta: 4:22:20 time: 0.5641 data_time: 0.0475 memory: 14901 loss: 0.9972 loss_prob: 0.5225 loss_thr: 0.3865 loss_db: 0.0882 2022/11/02 21:00:45 - mmengine - INFO - Epoch(train) [788][35/63] lr: 8.2712e-04 eta: 4:22:20 time: 0.6289 data_time: 0.0267 memory: 14901 loss: 0.9431 loss_prob: 0.4966 loss_thr: 0.3586 loss_db: 0.0879 2022/11/02 21:00:48 - mmengine - INFO - Epoch(train) [788][40/63] lr: 8.2712e-04 eta: 4:22:14 time: 0.6817 data_time: 0.0121 memory: 14901 loss: 0.9501 loss_prob: 0.5005 loss_thr: 0.3601 loss_db: 0.0896 2022/11/02 21:00:50 - mmengine - INFO - Epoch(train) [788][45/63] lr: 8.2712e-04 eta: 4:22:14 time: 0.5737 data_time: 0.0133 memory: 14901 loss: 1.0211 loss_prob: 0.5146 loss_thr: 0.4162 loss_db: 0.0902 2022/11/02 21:00:53 - mmengine - INFO - Epoch(train) [788][50/63] lr: 8.2712e-04 eta: 4:22:08 time: 0.5513 data_time: 0.0290 memory: 14901 loss: 1.0784 loss_prob: 0.5474 loss_thr: 0.4375 loss_db: 0.0935 2022/11/02 21:00:56 - mmengine - INFO - Epoch(train) [788][55/63] lr: 8.2712e-04 eta: 4:22:08 time: 0.5504 data_time: 0.0267 memory: 14901 loss: 1.0638 loss_prob: 0.5566 loss_thr: 0.4115 loss_db: 0.0957 2022/11/02 21:00:58 - mmengine - INFO - Epoch(train) [788][60/63] lr: 8.2712e-04 eta: 4:22:01 time: 0.5147 data_time: 0.0136 memory: 14901 loss: 1.0938 loss_prob: 0.5770 loss_thr: 0.4187 loss_db: 0.0980 2022/11/02 21:01:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:01:09 - mmengine - INFO - Epoch(train) [789][5/63] lr: 8.2532e-04 eta: 4:22:01 time: 1.1174 data_time: 0.3372 memory: 14901 loss: 1.2280 loss_prob: 0.6476 loss_thr: 0.4698 loss_db: 0.1105 2022/11/02 21:01:11 - mmengine - INFO - Epoch(train) [789][10/63] lr: 8.2532e-04 eta: 4:21:55 time: 1.1256 data_time: 0.3329 memory: 14901 loss: 1.1716 loss_prob: 0.6190 loss_thr: 0.4468 loss_db: 0.1057 2022/11/02 21:01:14 - mmengine - INFO - Epoch(train) [789][15/63] lr: 8.2532e-04 eta: 4:21:55 time: 0.5729 data_time: 0.0105 memory: 14901 loss: 1.0206 loss_prob: 0.5255 loss_thr: 0.4039 loss_db: 0.0912 2022/11/02 21:01:17 - mmengine - INFO - Epoch(train) [789][20/63] lr: 8.2532e-04 eta: 4:21:49 time: 0.5890 data_time: 0.0132 memory: 14901 loss: 1.0498 loss_prob: 0.5473 loss_thr: 0.4078 loss_db: 0.0947 2022/11/02 21:01:21 - mmengine - INFO - Epoch(train) [789][25/63] lr: 8.2532e-04 eta: 4:21:49 time: 0.6311 data_time: 0.0390 memory: 14901 loss: 1.0880 loss_prob: 0.5757 loss_thr: 0.4135 loss_db: 0.0988 2022/11/02 21:01:23 - mmengine - INFO - Epoch(train) [789][30/63] lr: 8.2532e-04 eta: 4:21:43 time: 0.6104 data_time: 0.0356 memory: 14901 loss: 1.1399 loss_prob: 0.6047 loss_thr: 0.4290 loss_db: 0.1062 2022/11/02 21:01:26 - mmengine - INFO - Epoch(train) [789][35/63] lr: 8.2532e-04 eta: 4:21:43 time: 0.5197 data_time: 0.0097 memory: 14901 loss: 1.1176 loss_prob: 0.5954 loss_thr: 0.4186 loss_db: 0.1037 2022/11/02 21:01:29 - mmengine - INFO - Epoch(train) [789][40/63] lr: 8.2532e-04 eta: 4:21:36 time: 0.5436 data_time: 0.0129 memory: 14901 loss: 1.0031 loss_prob: 0.5206 loss_thr: 0.3914 loss_db: 0.0911 2022/11/02 21:01:32 - mmengine - INFO - Epoch(train) [789][45/63] lr: 8.2532e-04 eta: 4:21:36 time: 0.5780 data_time: 0.0116 memory: 14901 loss: 1.0267 loss_prob: 0.5385 loss_thr: 0.3945 loss_db: 0.0936 2022/11/02 21:01:35 - mmengine - INFO - Epoch(train) [789][50/63] lr: 8.2532e-04 eta: 4:21:30 time: 0.6163 data_time: 0.0279 memory: 14901 loss: 1.0396 loss_prob: 0.5487 loss_thr: 0.3988 loss_db: 0.0922 2022/11/02 21:01:37 - mmengine - INFO - Epoch(train) [789][55/63] lr: 8.2532e-04 eta: 4:21:30 time: 0.5588 data_time: 0.0253 memory: 14901 loss: 0.9977 loss_prob: 0.5124 loss_thr: 0.3971 loss_db: 0.0882 2022/11/02 21:01:40 - mmengine - INFO - Epoch(train) [789][60/63] lr: 8.2532e-04 eta: 4:21:24 time: 0.5271 data_time: 0.0096 memory: 14901 loss: 1.0374 loss_prob: 0.5407 loss_thr: 0.4011 loss_db: 0.0956 2022/11/02 21:01:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:01:50 - mmengine - INFO - Epoch(train) [790][5/63] lr: 8.2351e-04 eta: 4:21:24 time: 1.1413 data_time: 0.2984 memory: 14901 loss: 1.0599 loss_prob: 0.5603 loss_thr: 0.4024 loss_db: 0.0971 2022/11/02 21:01:53 - mmengine - INFO - Epoch(train) [790][10/63] lr: 8.2351e-04 eta: 4:21:18 time: 1.1567 data_time: 0.2989 memory: 14901 loss: 1.0647 loss_prob: 0.5637 loss_thr: 0.4044 loss_db: 0.0967 2022/11/02 21:01:56 - mmengine - INFO - Epoch(train) [790][15/63] lr: 8.2351e-04 eta: 4:21:18 time: 0.5457 data_time: 0.0105 memory: 14901 loss: 1.1069 loss_prob: 0.5870 loss_thr: 0.4181 loss_db: 0.1017 2022/11/02 21:01:59 - mmengine - INFO - Epoch(train) [790][20/63] lr: 8.2351e-04 eta: 4:21:12 time: 0.6107 data_time: 0.0125 memory: 14901 loss: 1.0541 loss_prob: 0.5604 loss_thr: 0.3977 loss_db: 0.0961 2022/11/02 21:02:03 - mmengine - INFO - Epoch(train) [790][25/63] lr: 8.2351e-04 eta: 4:21:12 time: 0.7590 data_time: 0.0325 memory: 14901 loss: 0.9894 loss_prob: 0.5167 loss_thr: 0.3826 loss_db: 0.0901 2022/11/02 21:02:06 - mmengine - INFO - Epoch(train) [790][30/63] lr: 8.2351e-04 eta: 4:21:06 time: 0.7008 data_time: 0.0460 memory: 14901 loss: 1.0336 loss_prob: 0.5328 loss_thr: 0.4078 loss_db: 0.0930 2022/11/02 21:02:09 - mmengine - INFO - Epoch(train) [790][35/63] lr: 8.2351e-04 eta: 4:21:06 time: 0.5537 data_time: 0.0227 memory: 14901 loss: 1.1139 loss_prob: 0.5836 loss_thr: 0.4294 loss_db: 0.1008 2022/11/02 21:02:12 - mmengine - INFO - Epoch(train) [790][40/63] lr: 8.2351e-04 eta: 4:21:00 time: 0.6016 data_time: 0.0082 memory: 14901 loss: 1.0672 loss_prob: 0.5513 loss_thr: 0.4211 loss_db: 0.0948 2022/11/02 21:02:15 - mmengine - INFO - Epoch(train) [790][45/63] lr: 8.2351e-04 eta: 4:21:00 time: 0.6623 data_time: 0.0112 memory: 14901 loss: 0.9973 loss_prob: 0.5102 loss_thr: 0.3980 loss_db: 0.0891 2022/11/02 21:02:19 - mmengine - INFO - Epoch(train) [790][50/63] lr: 8.2351e-04 eta: 4:20:55 time: 0.7352 data_time: 0.0497 memory: 14901 loss: 1.0667 loss_prob: 0.5607 loss_thr: 0.4077 loss_db: 0.0984 2022/11/02 21:02:22 - mmengine - INFO - Epoch(train) [790][55/63] lr: 8.2351e-04 eta: 4:20:55 time: 0.6628 data_time: 0.0514 memory: 14901 loss: 1.0893 loss_prob: 0.5750 loss_thr: 0.4143 loss_db: 0.1001 2022/11/02 21:02:25 - mmengine - INFO - Epoch(train) [790][60/63] lr: 8.2351e-04 eta: 4:20:48 time: 0.5320 data_time: 0.0134 memory: 14901 loss: 1.0526 loss_prob: 0.5497 loss_thr: 0.4063 loss_db: 0.0966 2022/11/02 21:02:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:02:33 - mmengine - INFO - Epoch(train) [791][5/63] lr: 8.2170e-04 eta: 4:20:48 time: 0.9105 data_time: 0.2755 memory: 14901 loss: 1.0034 loss_prob: 0.5267 loss_thr: 0.3862 loss_db: 0.0906 2022/11/02 21:02:36 - mmengine - INFO - Epoch(train) [791][10/63] lr: 8.2170e-04 eta: 4:20:41 time: 0.9482 data_time: 0.2828 memory: 14901 loss: 0.9889 loss_prob: 0.5192 loss_thr: 0.3792 loss_db: 0.0905 2022/11/02 21:02:39 - mmengine - INFO - Epoch(train) [791][15/63] lr: 8.2170e-04 eta: 4:20:41 time: 0.5909 data_time: 0.0210 memory: 14901 loss: 1.0475 loss_prob: 0.5451 loss_thr: 0.4070 loss_db: 0.0954 2022/11/02 21:02:41 - mmengine - INFO - Epoch(train) [791][20/63] lr: 8.2170e-04 eta: 4:20:35 time: 0.5408 data_time: 0.0126 memory: 14901 loss: 1.0814 loss_prob: 0.5640 loss_thr: 0.4183 loss_db: 0.0992 2022/11/02 21:02:44 - mmengine - INFO - Epoch(train) [791][25/63] lr: 8.2170e-04 eta: 4:20:35 time: 0.5621 data_time: 0.0268 memory: 14901 loss: 1.0376 loss_prob: 0.5464 loss_thr: 0.3975 loss_db: 0.0938 2022/11/02 21:02:47 - mmengine - INFO - Epoch(train) [791][30/63] lr: 8.2170e-04 eta: 4:20:29 time: 0.5888 data_time: 0.0331 memory: 14901 loss: 1.0089 loss_prob: 0.5293 loss_thr: 0.3889 loss_db: 0.0906 2022/11/02 21:02:50 - mmengine - INFO - Epoch(train) [791][35/63] lr: 8.2170e-04 eta: 4:20:29 time: 0.5461 data_time: 0.0243 memory: 14901 loss: 1.0619 loss_prob: 0.5622 loss_thr: 0.4038 loss_db: 0.0959 2022/11/02 21:02:52 - mmengine - INFO - Epoch(train) [791][40/63] lr: 8.2170e-04 eta: 4:20:22 time: 0.5270 data_time: 0.0198 memory: 14901 loss: 1.0742 loss_prob: 0.5652 loss_thr: 0.4123 loss_db: 0.0967 2022/11/02 21:02:55 - mmengine - INFO - Epoch(train) [791][45/63] lr: 8.2170e-04 eta: 4:20:22 time: 0.5174 data_time: 0.0106 memory: 14901 loss: 1.0414 loss_prob: 0.5398 loss_thr: 0.4056 loss_db: 0.0961 2022/11/02 21:02:58 - mmengine - INFO - Epoch(train) [791][50/63] lr: 8.2170e-04 eta: 4:20:16 time: 0.5477 data_time: 0.0233 memory: 14901 loss: 1.1541 loss_prob: 0.6149 loss_thr: 0.4324 loss_db: 0.1068 2022/11/02 21:03:01 - mmengine - INFO - Epoch(train) [791][55/63] lr: 8.2170e-04 eta: 4:20:16 time: 0.5751 data_time: 0.0265 memory: 14901 loss: 1.1423 loss_prob: 0.6094 loss_thr: 0.4285 loss_db: 0.1045 2022/11/02 21:03:03 - mmengine - INFO - Epoch(train) [791][60/63] lr: 8.2170e-04 eta: 4:20:10 time: 0.5356 data_time: 0.0154 memory: 14901 loss: 1.0683 loss_prob: 0.5640 loss_thr: 0.4071 loss_db: 0.0972 2022/11/02 21:03:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:03:12 - mmengine - INFO - Epoch(train) [792][5/63] lr: 8.1989e-04 eta: 4:20:10 time: 0.9953 data_time: 0.2509 memory: 14901 loss: 0.9641 loss_prob: 0.5030 loss_thr: 0.3730 loss_db: 0.0881 2022/11/02 21:03:17 - mmengine - INFO - Epoch(train) [792][10/63] lr: 8.1989e-04 eta: 4:20:04 time: 1.2061 data_time: 0.2517 memory: 14901 loss: 0.9517 loss_prob: 0.5014 loss_thr: 0.3635 loss_db: 0.0868 2022/11/02 21:03:20 - mmengine - INFO - Epoch(train) [792][15/63] lr: 8.1989e-04 eta: 4:20:04 time: 0.7630 data_time: 0.0166 memory: 14901 loss: 1.0019 loss_prob: 0.5350 loss_thr: 0.3760 loss_db: 0.0909 2022/11/02 21:03:23 - mmengine - INFO - Epoch(train) [792][20/63] lr: 8.1989e-04 eta: 4:19:58 time: 0.6085 data_time: 0.0135 memory: 14901 loss: 1.0166 loss_prob: 0.5419 loss_thr: 0.3787 loss_db: 0.0960 2022/11/02 21:03:26 - mmengine - INFO - Epoch(train) [792][25/63] lr: 8.1989e-04 eta: 4:19:58 time: 0.6108 data_time: 0.0188 memory: 14901 loss: 0.9932 loss_prob: 0.5208 loss_thr: 0.3795 loss_db: 0.0930 2022/11/02 21:03:30 - mmengine - INFO - Epoch(train) [792][30/63] lr: 8.1989e-04 eta: 4:19:52 time: 0.6914 data_time: 0.0380 memory: 14901 loss: 1.1033 loss_prob: 0.5816 loss_thr: 0.4212 loss_db: 0.1005 2022/11/02 21:03:33 - mmengine - INFO - Epoch(train) [792][35/63] lr: 8.1989e-04 eta: 4:19:52 time: 0.7030 data_time: 0.0299 memory: 14901 loss: 1.1266 loss_prob: 0.5958 loss_thr: 0.4265 loss_db: 0.1042 2022/11/02 21:03:37 - mmengine - INFO - Epoch(train) [792][40/63] lr: 8.1989e-04 eta: 4:19:47 time: 0.7365 data_time: 0.0130 memory: 14901 loss: 1.0495 loss_prob: 0.5481 loss_thr: 0.4040 loss_db: 0.0973 2022/11/02 21:03:40 - mmengine - INFO - Epoch(train) [792][45/63] lr: 8.1989e-04 eta: 4:19:47 time: 0.6864 data_time: 0.0117 memory: 14901 loss: 1.0668 loss_prob: 0.5635 loss_thr: 0.4059 loss_db: 0.0974 2022/11/02 21:03:43 - mmengine - INFO - Epoch(train) [792][50/63] lr: 8.1989e-04 eta: 4:19:41 time: 0.6083 data_time: 0.0441 memory: 14901 loss: 1.0703 loss_prob: 0.5624 loss_thr: 0.4109 loss_db: 0.0970 2022/11/02 21:03:47 - mmengine - INFO - Epoch(train) [792][55/63] lr: 8.1989e-04 eta: 4:19:41 time: 0.6684 data_time: 0.0470 memory: 14901 loss: 1.0482 loss_prob: 0.5463 loss_thr: 0.4069 loss_db: 0.0950 2022/11/02 21:03:50 - mmengine - INFO - Epoch(train) [792][60/63] lr: 8.1989e-04 eta: 4:19:35 time: 0.6532 data_time: 0.0102 memory: 14901 loss: 1.0701 loss_prob: 0.5664 loss_thr: 0.4048 loss_db: 0.0989 2022/11/02 21:03:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:03:59 - mmengine - INFO - Epoch(train) [793][5/63] lr: 8.1808e-04 eta: 4:19:35 time: 1.0871 data_time: 0.2598 memory: 14901 loss: 1.0959 loss_prob: 0.5712 loss_thr: 0.4247 loss_db: 0.1000 2022/11/02 21:04:02 - mmengine - INFO - Epoch(train) [793][10/63] lr: 8.1808e-04 eta: 4:19:29 time: 1.0687 data_time: 0.2678 memory: 14901 loss: 1.0361 loss_prob: 0.5372 loss_thr: 0.4067 loss_db: 0.0921 2022/11/02 21:04:05 - mmengine - INFO - Epoch(train) [793][15/63] lr: 8.1808e-04 eta: 4:19:29 time: 0.5872 data_time: 0.0191 memory: 14901 loss: 0.9789 loss_prob: 0.5154 loss_thr: 0.3761 loss_db: 0.0874 2022/11/02 21:04:08 - mmengine - INFO - Epoch(train) [793][20/63] lr: 8.1808e-04 eta: 4:19:23 time: 0.6331 data_time: 0.0094 memory: 14901 loss: 1.0277 loss_prob: 0.5446 loss_thr: 0.3898 loss_db: 0.0933 2022/11/02 21:04:11 - mmengine - INFO - Epoch(train) [793][25/63] lr: 8.1808e-04 eta: 4:19:23 time: 0.6338 data_time: 0.0447 memory: 14901 loss: 1.0603 loss_prob: 0.5599 loss_thr: 0.4025 loss_db: 0.0980 2022/11/02 21:04:14 - mmengine - INFO - Epoch(train) [793][30/63] lr: 8.1808e-04 eta: 4:19:17 time: 0.5949 data_time: 0.0470 memory: 14901 loss: 1.0992 loss_prob: 0.5801 loss_thr: 0.4178 loss_db: 0.1013 2022/11/02 21:04:18 - mmengine - INFO - Epoch(train) [793][35/63] lr: 8.1808e-04 eta: 4:19:17 time: 0.6592 data_time: 0.0191 memory: 14901 loss: 1.0858 loss_prob: 0.5763 loss_thr: 0.4108 loss_db: 0.0986 2022/11/02 21:04:21 - mmengine - INFO - Epoch(train) [793][40/63] lr: 8.1808e-04 eta: 4:19:11 time: 0.6520 data_time: 0.0133 memory: 14901 loss: 1.1296 loss_prob: 0.6042 loss_thr: 0.4239 loss_db: 0.1015 2022/11/02 21:04:24 - mmengine - INFO - Epoch(train) [793][45/63] lr: 8.1808e-04 eta: 4:19:11 time: 0.6171 data_time: 0.0078 memory: 14901 loss: 1.1162 loss_prob: 0.5960 loss_thr: 0.4196 loss_db: 0.1007 2022/11/02 21:04:27 - mmengine - INFO - Epoch(train) [793][50/63] lr: 8.1808e-04 eta: 4:19:05 time: 0.6041 data_time: 0.0263 memory: 14901 loss: 1.0752 loss_prob: 0.5677 loss_thr: 0.4079 loss_db: 0.0996 2022/11/02 21:04:30 - mmengine - INFO - Epoch(train) [793][55/63] lr: 8.1808e-04 eta: 4:19:05 time: 0.5744 data_time: 0.0272 memory: 14901 loss: 1.0902 loss_prob: 0.5796 loss_thr: 0.4097 loss_db: 0.1009 2022/11/02 21:04:33 - mmengine - INFO - Epoch(train) [793][60/63] lr: 8.1808e-04 eta: 4:18:58 time: 0.5564 data_time: 0.0143 memory: 14901 loss: 1.0041 loss_prob: 0.5274 loss_thr: 0.3857 loss_db: 0.0910 2022/11/02 21:04:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:04:41 - mmengine - INFO - Epoch(train) [794][5/63] lr: 8.1628e-04 eta: 4:18:58 time: 0.9720 data_time: 0.1994 memory: 14901 loss: 1.0079 loss_prob: 0.5257 loss_thr: 0.3910 loss_db: 0.0913 2022/11/02 21:04:45 - mmengine - INFO - Epoch(train) [794][10/63] lr: 8.1628e-04 eta: 4:18:52 time: 1.1439 data_time: 0.2008 memory: 14901 loss: 0.9406 loss_prob: 0.4845 loss_thr: 0.3708 loss_db: 0.0854 2022/11/02 21:04:49 - mmengine - INFO - Epoch(train) [794][15/63] lr: 8.1628e-04 eta: 4:18:52 time: 0.8178 data_time: 0.0160 memory: 14901 loss: 0.9871 loss_prob: 0.5195 loss_thr: 0.3781 loss_db: 0.0895 2022/11/02 21:04:53 - mmengine - INFO - Epoch(train) [794][20/63] lr: 8.1628e-04 eta: 4:18:47 time: 0.7619 data_time: 0.0144 memory: 14901 loss: 1.0388 loss_prob: 0.5431 loss_thr: 0.4047 loss_db: 0.0910 2022/11/02 21:04:56 - mmengine - INFO - Epoch(train) [794][25/63] lr: 8.1628e-04 eta: 4:18:47 time: 0.6184 data_time: 0.0130 memory: 14901 loss: 1.0581 loss_prob: 0.5553 loss_thr: 0.4108 loss_db: 0.0920 2022/11/02 21:04:58 - mmengine - INFO - Epoch(train) [794][30/63] lr: 8.1628e-04 eta: 4:18:41 time: 0.5402 data_time: 0.0300 memory: 14901 loss: 1.0608 loss_prob: 0.5587 loss_thr: 0.4074 loss_db: 0.0947 2022/11/02 21:05:01 - mmengine - INFO - Epoch(train) [794][35/63] lr: 8.1628e-04 eta: 4:18:41 time: 0.5494 data_time: 0.0365 memory: 14901 loss: 1.0164 loss_prob: 0.5242 loss_thr: 0.3998 loss_db: 0.0925 2022/11/02 21:05:04 - mmengine - INFO - Epoch(train) [794][40/63] lr: 8.1628e-04 eta: 4:18:34 time: 0.5489 data_time: 0.0201 memory: 14901 loss: 1.0586 loss_prob: 0.5541 loss_thr: 0.4091 loss_db: 0.0954 2022/11/02 21:05:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:05:08 - mmengine - INFO - Epoch(train) [794][45/63] lr: 8.1628e-04 eta: 4:18:34 time: 0.7078 data_time: 0.0117 memory: 14901 loss: 1.0768 loss_prob: 0.5666 loss_thr: 0.4124 loss_db: 0.0977 2022/11/02 21:05:11 - mmengine - INFO - Epoch(train) [794][50/63] lr: 8.1628e-04 eta: 4:18:29 time: 0.7221 data_time: 0.0244 memory: 14901 loss: 0.9930 loss_prob: 0.5175 loss_thr: 0.3842 loss_db: 0.0912 2022/11/02 21:05:14 - mmengine - INFO - Epoch(train) [794][55/63] lr: 8.1628e-04 eta: 4:18:29 time: 0.5696 data_time: 0.0241 memory: 14901 loss: 1.0011 loss_prob: 0.5302 loss_thr: 0.3793 loss_db: 0.0917 2022/11/02 21:05:16 - mmengine - INFO - Epoch(train) [794][60/63] lr: 8.1628e-04 eta: 4:18:22 time: 0.5214 data_time: 0.0160 memory: 14901 loss: 1.0972 loss_prob: 0.5844 loss_thr: 0.4099 loss_db: 0.1028 2022/11/02 21:05:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:05:25 - mmengine - INFO - Epoch(train) [795][5/63] lr: 8.1447e-04 eta: 4:18:22 time: 0.9719 data_time: 0.2900 memory: 14901 loss: 1.1150 loss_prob: 0.5970 loss_thr: 0.4170 loss_db: 0.1011 2022/11/02 21:05:28 - mmengine - INFO - Epoch(train) [795][10/63] lr: 8.1447e-04 eta: 4:18:15 time: 0.9860 data_time: 0.2870 memory: 14901 loss: 1.1243 loss_prob: 0.6028 loss_thr: 0.4198 loss_db: 0.1017 2022/11/02 21:05:30 - mmengine - INFO - Epoch(train) [795][15/63] lr: 8.1447e-04 eta: 4:18:15 time: 0.5251 data_time: 0.0097 memory: 14901 loss: 1.0900 loss_prob: 0.5762 loss_thr: 0.4162 loss_db: 0.0976 2022/11/02 21:05:33 - mmengine - INFO - Epoch(train) [795][20/63] lr: 8.1447e-04 eta: 4:18:09 time: 0.5043 data_time: 0.0072 memory: 14901 loss: 1.0146 loss_prob: 0.5231 loss_thr: 0.3991 loss_db: 0.0924 2022/11/02 21:05:36 - mmengine - INFO - Epoch(train) [795][25/63] lr: 8.1447e-04 eta: 4:18:09 time: 0.5435 data_time: 0.0197 memory: 14901 loss: 1.0939 loss_prob: 0.5756 loss_thr: 0.4187 loss_db: 0.0995 2022/11/02 21:05:39 - mmengine - INFO - Epoch(train) [795][30/63] lr: 8.1447e-04 eta: 4:18:03 time: 0.5917 data_time: 0.0444 memory: 14901 loss: 1.1371 loss_prob: 0.6111 loss_thr: 0.4230 loss_db: 0.1029 2022/11/02 21:05:41 - mmengine - INFO - Epoch(train) [795][35/63] lr: 8.1447e-04 eta: 4:18:03 time: 0.5460 data_time: 0.0300 memory: 14901 loss: 1.0748 loss_prob: 0.5688 loss_thr: 0.4083 loss_db: 0.0977 2022/11/02 21:05:44 - mmengine - INFO - Epoch(train) [795][40/63] lr: 8.1447e-04 eta: 4:17:56 time: 0.5229 data_time: 0.0087 memory: 14901 loss: 1.0364 loss_prob: 0.5417 loss_thr: 0.4010 loss_db: 0.0937 2022/11/02 21:05:47 - mmengine - INFO - Epoch(train) [795][45/63] lr: 8.1447e-04 eta: 4:17:56 time: 0.6125 data_time: 0.0117 memory: 14901 loss: 1.0571 loss_prob: 0.5613 loss_thr: 0.3992 loss_db: 0.0965 2022/11/02 21:05:50 - mmengine - INFO - Epoch(train) [795][50/63] lr: 8.1447e-04 eta: 4:17:50 time: 0.6028 data_time: 0.0207 memory: 14901 loss: 1.1056 loss_prob: 0.5859 loss_thr: 0.4177 loss_db: 0.1019 2022/11/02 21:05:53 - mmengine - INFO - Epoch(train) [795][55/63] lr: 8.1447e-04 eta: 4:17:50 time: 0.5384 data_time: 0.0261 memory: 14901 loss: 1.1080 loss_prob: 0.5831 loss_thr: 0.4230 loss_db: 0.1020 2022/11/02 21:05:56 - mmengine - INFO - Epoch(train) [795][60/63] lr: 8.1447e-04 eta: 4:17:44 time: 0.5468 data_time: 0.0199 memory: 14901 loss: 1.0536 loss_prob: 0.5571 loss_thr: 0.3982 loss_db: 0.0982 2022/11/02 21:05:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:06:04 - mmengine - INFO - Epoch(train) [796][5/63] lr: 8.1266e-04 eta: 4:17:44 time: 0.9057 data_time: 0.2498 memory: 14901 loss: 1.0979 loss_prob: 0.5852 loss_thr: 0.4116 loss_db: 0.1011 2022/11/02 21:06:07 - mmengine - INFO - Epoch(train) [796][10/63] lr: 8.1266e-04 eta: 4:17:37 time: 0.9774 data_time: 0.2471 memory: 14901 loss: 1.0632 loss_prob: 0.5629 loss_thr: 0.4018 loss_db: 0.0985 2022/11/02 21:06:10 - mmengine - INFO - Epoch(train) [796][15/63] lr: 8.1266e-04 eta: 4:17:37 time: 0.5955 data_time: 0.0138 memory: 14901 loss: 1.0213 loss_prob: 0.5272 loss_thr: 0.4013 loss_db: 0.0928 2022/11/02 21:06:12 - mmengine - INFO - Epoch(train) [796][20/63] lr: 8.1266e-04 eta: 4:17:31 time: 0.5654 data_time: 0.0137 memory: 14901 loss: 1.0807 loss_prob: 0.5691 loss_thr: 0.4141 loss_db: 0.0975 2022/11/02 21:06:16 - mmengine - INFO - Epoch(train) [796][25/63] lr: 8.1266e-04 eta: 4:17:31 time: 0.5995 data_time: 0.0164 memory: 14901 loss: 1.0584 loss_prob: 0.5639 loss_thr: 0.4000 loss_db: 0.0944 2022/11/02 21:06:19 - mmengine - INFO - Epoch(train) [796][30/63] lr: 8.1266e-04 eta: 4:17:25 time: 0.6428 data_time: 0.0418 memory: 14901 loss: 1.0839 loss_prob: 0.5679 loss_thr: 0.4185 loss_db: 0.0975 2022/11/02 21:06:22 - mmengine - INFO - Epoch(train) [796][35/63] lr: 8.1266e-04 eta: 4:17:25 time: 0.6302 data_time: 0.0347 memory: 14901 loss: 1.0851 loss_prob: 0.5652 loss_thr: 0.4194 loss_db: 0.1005 2022/11/02 21:06:25 - mmengine - INFO - Epoch(train) [796][40/63] lr: 8.1266e-04 eta: 4:17:19 time: 0.5722 data_time: 0.0106 memory: 14901 loss: 0.9559 loss_prob: 0.4905 loss_thr: 0.3802 loss_db: 0.0852 2022/11/02 21:06:27 - mmengine - INFO - Epoch(train) [796][45/63] lr: 8.1266e-04 eta: 4:17:19 time: 0.5640 data_time: 0.0150 memory: 14901 loss: 0.9594 loss_prob: 0.4849 loss_thr: 0.3920 loss_db: 0.0825 2022/11/02 21:06:31 - mmengine - INFO - Epoch(train) [796][50/63] lr: 8.1266e-04 eta: 4:17:13 time: 0.6840 data_time: 0.0278 memory: 14901 loss: 1.0264 loss_prob: 0.5298 loss_thr: 0.4044 loss_db: 0.0923 2022/11/02 21:06:34 - mmengine - INFO - Epoch(train) [796][55/63] lr: 8.1266e-04 eta: 4:17:13 time: 0.6423 data_time: 0.0265 memory: 14901 loss: 1.0055 loss_prob: 0.5185 loss_thr: 0.3959 loss_db: 0.0911 2022/11/02 21:06:37 - mmengine - INFO - Epoch(train) [796][60/63] lr: 8.1266e-04 eta: 4:17:06 time: 0.5270 data_time: 0.0118 memory: 14901 loss: 1.0568 loss_prob: 0.5444 loss_thr: 0.4181 loss_db: 0.0943 2022/11/02 21:06:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:06:46 - mmengine - INFO - Epoch(train) [797][5/63] lr: 8.1085e-04 eta: 4:17:06 time: 1.0743 data_time: 0.3027 memory: 14901 loss: 1.0883 loss_prob: 0.5558 loss_thr: 0.4360 loss_db: 0.0966 2022/11/02 21:06:49 - mmengine - INFO - Epoch(train) [797][10/63] lr: 8.1085e-04 eta: 4:17:00 time: 1.0674 data_time: 0.3042 memory: 14901 loss: 1.0176 loss_prob: 0.5215 loss_thr: 0.4030 loss_db: 0.0931 2022/11/02 21:06:52 - mmengine - INFO - Epoch(train) [797][15/63] lr: 8.1085e-04 eta: 4:17:00 time: 0.5827 data_time: 0.0108 memory: 14901 loss: 0.9559 loss_prob: 0.4914 loss_thr: 0.3767 loss_db: 0.0877 2022/11/02 21:06:55 - mmengine - INFO - Epoch(train) [797][20/63] lr: 8.1085e-04 eta: 4:16:54 time: 0.6058 data_time: 0.0112 memory: 14901 loss: 0.9506 loss_prob: 0.4847 loss_thr: 0.3816 loss_db: 0.0844 2022/11/02 21:06:58 - mmengine - INFO - Epoch(train) [797][25/63] lr: 8.1085e-04 eta: 4:16:54 time: 0.6242 data_time: 0.0340 memory: 14901 loss: 1.0151 loss_prob: 0.5253 loss_thr: 0.3999 loss_db: 0.0899 2022/11/02 21:07:01 - mmengine - INFO - Epoch(train) [797][30/63] lr: 8.1085e-04 eta: 4:16:48 time: 0.6551 data_time: 0.0394 memory: 14901 loss: 1.3398 loss_prob: 0.7794 loss_thr: 0.4397 loss_db: 0.1208 2022/11/02 21:07:05 - mmengine - INFO - Epoch(train) [797][35/63] lr: 8.1085e-04 eta: 4:16:48 time: 0.6598 data_time: 0.0219 memory: 14901 loss: 1.4226 loss_prob: 0.8281 loss_thr: 0.4627 loss_db: 0.1318 2022/11/02 21:07:07 - mmengine - INFO - Epoch(train) [797][40/63] lr: 8.1085e-04 eta: 4:16:42 time: 0.5892 data_time: 0.0152 memory: 14901 loss: 1.1895 loss_prob: 0.6417 loss_thr: 0.4365 loss_db: 0.1113 2022/11/02 21:07:11 - mmengine - INFO - Epoch(train) [797][45/63] lr: 8.1085e-04 eta: 4:16:42 time: 0.6439 data_time: 0.0102 memory: 14901 loss: 1.2315 loss_prob: 0.6703 loss_thr: 0.4495 loss_db: 0.1118 2022/11/02 21:07:14 - mmengine - INFO - Epoch(train) [797][50/63] lr: 8.1085e-04 eta: 4:16:36 time: 0.7066 data_time: 0.0251 memory: 14901 loss: 1.1420 loss_prob: 0.6100 loss_thr: 0.4280 loss_db: 0.1041 2022/11/02 21:07:17 - mmengine - INFO - Epoch(train) [797][55/63] lr: 8.1085e-04 eta: 4:16:36 time: 0.5802 data_time: 0.0272 memory: 14901 loss: 1.1172 loss_prob: 0.5924 loss_thr: 0.4210 loss_db: 0.1039 2022/11/02 21:07:20 - mmengine - INFO - Epoch(train) [797][60/63] lr: 8.1085e-04 eta: 4:16:30 time: 0.5497 data_time: 0.0128 memory: 14901 loss: 1.1885 loss_prob: 0.6373 loss_thr: 0.4443 loss_db: 0.1069 2022/11/02 21:07:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:07:29 - mmengine - INFO - Epoch(train) [798][5/63] lr: 8.0904e-04 eta: 4:16:30 time: 1.0426 data_time: 0.2393 memory: 14901 loss: 1.0550 loss_prob: 0.5604 loss_thr: 0.3979 loss_db: 0.0967 2022/11/02 21:07:32 - mmengine - INFO - Epoch(train) [798][10/63] lr: 8.0904e-04 eta: 4:16:23 time: 1.0131 data_time: 0.2467 memory: 14901 loss: 1.0855 loss_prob: 0.5785 loss_thr: 0.4062 loss_db: 0.1008 2022/11/02 21:07:36 - mmengine - INFO - Epoch(train) [798][15/63] lr: 8.0904e-04 eta: 4:16:23 time: 0.6871 data_time: 0.0187 memory: 14901 loss: 1.0728 loss_prob: 0.5634 loss_thr: 0.4126 loss_db: 0.0967 2022/11/02 21:07:39 - mmengine - INFO - Epoch(train) [798][20/63] lr: 8.0904e-04 eta: 4:16:18 time: 0.7105 data_time: 0.0102 memory: 14901 loss: 1.1344 loss_prob: 0.6058 loss_thr: 0.4270 loss_db: 0.1016 2022/11/02 21:07:43 - mmengine - INFO - Epoch(train) [798][25/63] lr: 8.0904e-04 eta: 4:16:18 time: 0.6794 data_time: 0.0122 memory: 14901 loss: 1.1679 loss_prob: 0.6278 loss_thr: 0.4318 loss_db: 0.1083 2022/11/02 21:07:45 - mmengine - INFO - Epoch(train) [798][30/63] lr: 8.0904e-04 eta: 4:16:12 time: 0.6203 data_time: 0.0385 memory: 14901 loss: 1.1818 loss_prob: 0.6317 loss_thr: 0.4401 loss_db: 0.1100 2022/11/02 21:07:49 - mmengine - INFO - Epoch(train) [798][35/63] lr: 8.0904e-04 eta: 4:16:12 time: 0.6258 data_time: 0.0383 memory: 14901 loss: 1.0978 loss_prob: 0.5837 loss_thr: 0.4149 loss_db: 0.0992 2022/11/02 21:07:52 - mmengine - INFO - Epoch(train) [798][40/63] lr: 8.0904e-04 eta: 4:16:06 time: 0.6626 data_time: 0.0117 memory: 14901 loss: 1.0454 loss_prob: 0.5429 loss_thr: 0.4107 loss_db: 0.0919 2022/11/02 21:07:55 - mmengine - INFO - Epoch(train) [798][45/63] lr: 8.0904e-04 eta: 4:16:06 time: 0.6228 data_time: 0.0093 memory: 14901 loss: 1.1194 loss_prob: 0.5901 loss_thr: 0.4279 loss_db: 0.1014 2022/11/02 21:07:59 - mmengine - INFO - Epoch(train) [798][50/63] lr: 8.0904e-04 eta: 4:16:00 time: 0.6666 data_time: 0.0246 memory: 14901 loss: 1.1167 loss_prob: 0.6031 loss_thr: 0.4090 loss_db: 0.1046 2022/11/02 21:08:02 - mmengine - INFO - Epoch(train) [798][55/63] lr: 8.0904e-04 eta: 4:16:00 time: 0.6676 data_time: 0.0270 memory: 14901 loss: 1.1126 loss_prob: 0.5994 loss_thr: 0.4119 loss_db: 0.1013 2022/11/02 21:08:05 - mmengine - INFO - Epoch(train) [798][60/63] lr: 8.0904e-04 eta: 4:15:54 time: 0.6490 data_time: 0.0140 memory: 14901 loss: 1.0743 loss_prob: 0.5671 loss_thr: 0.4109 loss_db: 0.0963 2022/11/02 21:08:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:08:14 - mmengine - INFO - Epoch(train) [799][5/63] lr: 8.0722e-04 eta: 4:15:54 time: 0.9961 data_time: 0.3637 memory: 14901 loss: 1.0849 loss_prob: 0.5870 loss_thr: 0.3952 loss_db: 0.1026 2022/11/02 21:08:18 - mmengine - INFO - Epoch(train) [799][10/63] lr: 8.0722e-04 eta: 4:15:48 time: 1.0919 data_time: 0.3630 memory: 14901 loss: 1.2060 loss_prob: 0.6660 loss_thr: 0.4238 loss_db: 0.1162 2022/11/02 21:08:21 - mmengine - INFO - Epoch(train) [799][15/63] lr: 8.0722e-04 eta: 4:15:48 time: 0.7043 data_time: 0.0123 memory: 14901 loss: 1.1063 loss_prob: 0.5890 loss_thr: 0.4166 loss_db: 0.1007 2022/11/02 21:08:24 - mmengine - INFO - Epoch(train) [799][20/63] lr: 8.0722e-04 eta: 4:15:42 time: 0.6202 data_time: 0.0104 memory: 14901 loss: 1.0644 loss_prob: 0.5518 loss_thr: 0.4183 loss_db: 0.0944 2022/11/02 21:08:27 - mmengine - INFO - Epoch(train) [799][25/63] lr: 8.0722e-04 eta: 4:15:42 time: 0.6543 data_time: 0.0427 memory: 14901 loss: 1.0363 loss_prob: 0.5362 loss_thr: 0.4069 loss_db: 0.0932 2022/11/02 21:08:30 - mmengine - INFO - Epoch(train) [799][30/63] lr: 8.0722e-04 eta: 4:15:36 time: 0.6171 data_time: 0.0459 memory: 14901 loss: 0.9819 loss_prob: 0.5079 loss_thr: 0.3847 loss_db: 0.0893 2022/11/02 21:08:33 - mmengine - INFO - Epoch(train) [799][35/63] lr: 8.0722e-04 eta: 4:15:36 time: 0.5181 data_time: 0.0142 memory: 14901 loss: 0.9666 loss_prob: 0.4992 loss_thr: 0.3805 loss_db: 0.0869 2022/11/02 21:08:36 - mmengine - INFO - Epoch(train) [799][40/63] lr: 8.0722e-04 eta: 4:15:30 time: 0.5523 data_time: 0.0133 memory: 14901 loss: 1.0118 loss_prob: 0.5330 loss_thr: 0.3855 loss_db: 0.0933 2022/11/02 21:08:39 - mmengine - INFO - Epoch(train) [799][45/63] lr: 8.0722e-04 eta: 4:15:30 time: 0.6104 data_time: 0.0112 memory: 14901 loss: 0.9760 loss_prob: 0.5003 loss_thr: 0.3878 loss_db: 0.0880 2022/11/02 21:08:42 - mmengine - INFO - Epoch(train) [799][50/63] lr: 8.0722e-04 eta: 4:15:24 time: 0.6286 data_time: 0.0286 memory: 14901 loss: 0.9559 loss_prob: 0.4842 loss_thr: 0.3887 loss_db: 0.0830 2022/11/02 21:08:45 - mmengine - INFO - Epoch(train) [799][55/63] lr: 8.0722e-04 eta: 4:15:24 time: 0.5856 data_time: 0.0296 memory: 14901 loss: 1.0052 loss_prob: 0.5175 loss_thr: 0.3983 loss_db: 0.0893 2022/11/02 21:08:47 - mmengine - INFO - Epoch(train) [799][60/63] lr: 8.0722e-04 eta: 4:15:17 time: 0.5465 data_time: 0.0129 memory: 14901 loss: 1.1001 loss_prob: 0.5889 loss_thr: 0.4094 loss_db: 0.1018 2022/11/02 21:08:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:08:55 - mmengine - INFO - Epoch(train) [800][5/63] lr: 8.0541e-04 eta: 4:15:17 time: 0.9326 data_time: 0.2350 memory: 14901 loss: 1.0598 loss_prob: 0.5627 loss_thr: 0.4009 loss_db: 0.0962 2022/11/02 21:08:58 - mmengine - INFO - Epoch(train) [800][10/63] lr: 8.0541e-04 eta: 4:15:10 time: 0.9305 data_time: 0.2412 memory: 14901 loss: 1.0095 loss_prob: 0.5299 loss_thr: 0.3872 loss_db: 0.0925 2022/11/02 21:09:02 - mmengine - INFO - Epoch(train) [800][15/63] lr: 8.0541e-04 eta: 4:15:10 time: 0.6050 data_time: 0.0320 memory: 14901 loss: 0.9945 loss_prob: 0.5201 loss_thr: 0.3833 loss_db: 0.0911 2022/11/02 21:09:04 - mmengine - INFO - Epoch(train) [800][20/63] lr: 8.0541e-04 eta: 4:15:04 time: 0.6075 data_time: 0.0268 memory: 14901 loss: 1.0419 loss_prob: 0.5551 loss_thr: 0.3910 loss_db: 0.0957 2022/11/02 21:09:07 - mmengine - INFO - Epoch(train) [800][25/63] lr: 8.0541e-04 eta: 4:15:04 time: 0.5649 data_time: 0.0141 memory: 14901 loss: 1.0750 loss_prob: 0.5637 loss_thr: 0.4135 loss_db: 0.0978 2022/11/02 21:09:10 - mmengine - INFO - Epoch(train) [800][30/63] lr: 8.0541e-04 eta: 4:14:58 time: 0.6162 data_time: 0.0339 memory: 14901 loss: 1.0251 loss_prob: 0.5312 loss_thr: 0.4022 loss_db: 0.0918 2022/11/02 21:09:13 - mmengine - INFO - Epoch(train) [800][35/63] lr: 8.0541e-04 eta: 4:14:58 time: 0.5675 data_time: 0.0349 memory: 14901 loss: 1.0796 loss_prob: 0.5685 loss_thr: 0.4136 loss_db: 0.0975 2022/11/02 21:09:16 - mmengine - INFO - Epoch(train) [800][40/63] lr: 8.0541e-04 eta: 4:14:52 time: 0.5852 data_time: 0.0164 memory: 14901 loss: 1.1539 loss_prob: 0.6150 loss_thr: 0.4333 loss_db: 0.1057 2022/11/02 21:09:19 - mmengine - INFO - Epoch(train) [800][45/63] lr: 8.0541e-04 eta: 4:14:52 time: 0.5733 data_time: 0.0133 memory: 14901 loss: 1.0672 loss_prob: 0.5584 loss_thr: 0.4119 loss_db: 0.0969 2022/11/02 21:09:22 - mmengine - INFO - Epoch(train) [800][50/63] lr: 8.0541e-04 eta: 4:14:46 time: 0.5443 data_time: 0.0153 memory: 14901 loss: 1.0740 loss_prob: 0.5639 loss_thr: 0.4135 loss_db: 0.0966 2022/11/02 21:09:25 - mmengine - INFO - Epoch(train) [800][55/63] lr: 8.0541e-04 eta: 4:14:46 time: 0.6771 data_time: 0.0238 memory: 14901 loss: 1.1201 loss_prob: 0.5979 loss_thr: 0.4209 loss_db: 0.1013 2022/11/02 21:09:28 - mmengine - INFO - Epoch(train) [800][60/63] lr: 8.0541e-04 eta: 4:14:40 time: 0.6429 data_time: 0.0250 memory: 14901 loss: 1.0816 loss_prob: 0.5761 loss_thr: 0.4052 loss_db: 0.1002 2022/11/02 21:09:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:09:29 - mmengine - INFO - Saving checkpoint at 800 epochs 2022/11/02 21:09:33 - mmengine - INFO - Epoch(val) [800][5/500] eta: 4:14:40 time: 0.0438 data_time: 0.0054 memory: 14901 2022/11/02 21:09:33 - mmengine - INFO - Epoch(val) [800][10/500] eta: 0:00:24 time: 0.0507 data_time: 0.0053 memory: 1008 2022/11/02 21:09:34 - mmengine - INFO - Epoch(val) [800][15/500] eta: 0:00:24 time: 0.0445 data_time: 0.0027 memory: 1008 2022/11/02 21:09:34 - mmengine - INFO - Epoch(val) [800][20/500] eta: 0:00:20 time: 0.0427 data_time: 0.0031 memory: 1008 2022/11/02 21:09:34 - mmengine - INFO - Epoch(val) [800][25/500] eta: 0:00:20 time: 0.0414 data_time: 0.0030 memory: 1008 2022/11/02 21:09:34 - mmengine - INFO - Epoch(val) [800][30/500] eta: 0:00:19 time: 0.0425 data_time: 0.0027 memory: 1008 2022/11/02 21:09:34 - mmengine - INFO - Epoch(val) [800][35/500] eta: 0:00:19 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 21:09:35 - mmengine - INFO - Epoch(val) [800][40/500] eta: 0:00:20 time: 0.0448 data_time: 0.0026 memory: 1008 2022/11/02 21:09:35 - mmengine - INFO - Epoch(val) [800][45/500] eta: 0:00:20 time: 0.0475 data_time: 0.0027 memory: 1008 2022/11/02 21:09:35 - mmengine - INFO - Epoch(val) [800][50/500] eta: 0:00:21 time: 0.0488 data_time: 0.0031 memory: 1008 2022/11/02 21:09:35 - mmengine - INFO - Epoch(val) [800][55/500] eta: 0:00:21 time: 0.0503 data_time: 0.0032 memory: 1008 2022/11/02 21:09:36 - mmengine - INFO - Epoch(val) [800][60/500] eta: 0:00:19 time: 0.0453 data_time: 0.0032 memory: 1008 2022/11/02 21:09:36 - mmengine - INFO - Epoch(val) [800][65/500] eta: 0:00:19 time: 0.0464 data_time: 0.0034 memory: 1008 2022/11/02 21:09:36 - mmengine - INFO - Epoch(val) [800][70/500] eta: 0:00:22 time: 0.0515 data_time: 0.0035 memory: 1008 2022/11/02 21:09:36 - mmengine - INFO - Epoch(val) [800][75/500] eta: 0:00:22 time: 0.0433 data_time: 0.0031 memory: 1008 2022/11/02 21:09:37 - mmengine - INFO - Epoch(val) [800][80/500] eta: 0:00:16 time: 0.0386 data_time: 0.0028 memory: 1008 2022/11/02 21:09:37 - mmengine - INFO - Epoch(val) [800][85/500] eta: 0:00:16 time: 0.0403 data_time: 0.0029 memory: 1008 2022/11/02 21:09:37 - mmengine - INFO - Epoch(val) [800][90/500] eta: 0:00:19 time: 0.0479 data_time: 0.0032 memory: 1008 2022/11/02 21:09:37 - mmengine - INFO - Epoch(val) [800][95/500] eta: 0:00:19 time: 0.0514 data_time: 0.0033 memory: 1008 2022/11/02 21:09:37 - mmengine - INFO - Epoch(val) [800][100/500] eta: 0:00:16 time: 0.0418 data_time: 0.0028 memory: 1008 2022/11/02 21:09:38 - mmengine - INFO - Epoch(val) [800][105/500] eta: 0:00:16 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 21:09:38 - mmengine - INFO - Epoch(val) [800][110/500] eta: 0:00:17 time: 0.0440 data_time: 0.0030 memory: 1008 2022/11/02 21:09:38 - mmengine - INFO - Epoch(val) [800][115/500] eta: 0:00:17 time: 0.0439 data_time: 0.0032 memory: 1008 2022/11/02 21:09:38 - mmengine - INFO - Epoch(val) [800][120/500] eta: 0:00:15 time: 0.0421 data_time: 0.0031 memory: 1008 2022/11/02 21:09:38 - mmengine - INFO - Epoch(val) [800][125/500] eta: 0:00:15 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 21:09:39 - mmengine - INFO - Epoch(val) [800][130/500] eta: 0:00:15 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 21:09:39 - mmengine - INFO - Epoch(val) [800][135/500] eta: 0:00:15 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 21:09:39 - mmengine - INFO - Epoch(val) [800][140/500] eta: 0:00:14 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 21:09:39 - mmengine - INFO - Epoch(val) [800][145/500] eta: 0:00:14 time: 0.0462 data_time: 0.0029 memory: 1008 2022/11/02 21:09:40 - mmengine - INFO - Epoch(val) [800][150/500] eta: 0:00:15 time: 0.0445 data_time: 0.0029 memory: 1008 2022/11/02 21:09:40 - mmengine - INFO - Epoch(val) [800][155/500] eta: 0:00:15 time: 0.0469 data_time: 0.0028 memory: 1008 2022/11/02 21:09:40 - mmengine - INFO - Epoch(val) [800][160/500] eta: 0:00:16 time: 0.0493 data_time: 0.0028 memory: 1008 2022/11/02 21:09:40 - mmengine - INFO - Epoch(val) [800][165/500] eta: 0:00:16 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/02 21:09:40 - mmengine - INFO - Epoch(val) [800][170/500] eta: 0:00:13 time: 0.0408 data_time: 0.0025 memory: 1008 2022/11/02 21:09:41 - mmengine - INFO - Epoch(val) [800][175/500] eta: 0:00:13 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/02 21:09:41 - mmengine - INFO - Epoch(val) [800][180/500] eta: 0:00:12 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/02 21:09:41 - mmengine - INFO - Epoch(val) [800][185/500] eta: 0:00:12 time: 0.0422 data_time: 0.0026 memory: 1008 2022/11/02 21:09:41 - mmengine - INFO - Epoch(val) [800][190/500] eta: 0:00:13 time: 0.0426 data_time: 0.0026 memory: 1008 2022/11/02 21:09:41 - mmengine - INFO - Epoch(val) [800][195/500] eta: 0:00:13 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/02 21:09:42 - mmengine - INFO - Epoch(val) [800][200/500] eta: 0:00:14 time: 0.0471 data_time: 0.0027 memory: 1008 2022/11/02 21:09:42 - mmengine - INFO - Epoch(val) [800][205/500] eta: 0:00:14 time: 0.0491 data_time: 0.0031 memory: 1008 2022/11/02 21:09:42 - mmengine - INFO - Epoch(val) [800][210/500] eta: 0:00:12 time: 0.0418 data_time: 0.0030 memory: 1008 2022/11/02 21:09:42 - mmengine - INFO - Epoch(val) [800][215/500] eta: 0:00:12 time: 0.0407 data_time: 0.0027 memory: 1008 2022/11/02 21:09:43 - mmengine - INFO - Epoch(val) [800][220/500] eta: 0:00:11 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 21:09:43 - mmengine - INFO - Epoch(val) [800][225/500] eta: 0:00:11 time: 0.0454 data_time: 0.0030 memory: 1008 2022/11/02 21:09:43 - mmengine - INFO - Epoch(val) [800][230/500] eta: 0:00:11 time: 0.0431 data_time: 0.0029 memory: 1008 2022/11/02 21:09:43 - mmengine - INFO - Epoch(val) [800][235/500] eta: 0:00:11 time: 0.0383 data_time: 0.0027 memory: 1008 2022/11/02 21:09:43 - mmengine - INFO - Epoch(val) [800][240/500] eta: 0:00:11 time: 0.0427 data_time: 0.0028 memory: 1008 2022/11/02 21:09:44 - mmengine - INFO - Epoch(val) [800][245/500] eta: 0:00:11 time: 0.0443 data_time: 0.0030 memory: 1008 2022/11/02 21:09:44 - mmengine - INFO - Epoch(val) [800][250/500] eta: 0:00:11 time: 0.0449 data_time: 0.0030 memory: 1008 2022/11/02 21:09:44 - mmengine - INFO - Epoch(val) [800][255/500] eta: 0:00:11 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/02 21:09:44 - mmengine - INFO - Epoch(val) [800][260/500] eta: 0:00:09 time: 0.0386 data_time: 0.0026 memory: 1008 2022/11/02 21:09:44 - mmengine - INFO - Epoch(val) [800][265/500] eta: 0:00:09 time: 0.0384 data_time: 0.0025 memory: 1008 2022/11/02 21:09:45 - mmengine - INFO - Epoch(val) [800][270/500] eta: 0:00:08 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 21:09:45 - mmengine - INFO - Epoch(val) [800][275/500] eta: 0:00:08 time: 0.0385 data_time: 0.0027 memory: 1008 2022/11/02 21:09:45 - mmengine - INFO - Epoch(val) [800][280/500] eta: 0:00:09 time: 0.0433 data_time: 0.0027 memory: 1008 2022/11/02 21:09:45 - mmengine - INFO - Epoch(val) [800][285/500] eta: 0:00:09 time: 0.0451 data_time: 0.0025 memory: 1008 2022/11/02 21:09:46 - mmengine - INFO - Epoch(val) [800][290/500] eta: 0:00:09 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/02 21:09:46 - mmengine - INFO - Epoch(val) [800][295/500] eta: 0:00:09 time: 0.0435 data_time: 0.0029 memory: 1008 2022/11/02 21:09:46 - mmengine - INFO - Epoch(val) [800][300/500] eta: 0:00:08 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 21:09:46 - mmengine - INFO - Epoch(val) [800][305/500] eta: 0:00:08 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/02 21:09:46 - mmengine - INFO - Epoch(val) [800][310/500] eta: 0:00:07 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 21:09:47 - mmengine - INFO - Epoch(val) [800][315/500] eta: 0:00:07 time: 0.0430 data_time: 0.0025 memory: 1008 2022/11/02 21:09:47 - mmengine - INFO - Epoch(val) [800][320/500] eta: 0:00:07 time: 0.0406 data_time: 0.0025 memory: 1008 2022/11/02 21:09:47 - mmengine - INFO - Epoch(val) [800][325/500] eta: 0:00:07 time: 0.0541 data_time: 0.0025 memory: 1008 2022/11/02 21:09:47 - mmengine - INFO - Epoch(val) [800][330/500] eta: 0:00:09 time: 0.0577 data_time: 0.0027 memory: 1008 2022/11/02 21:09:48 - mmengine - INFO - Epoch(val) [800][335/500] eta: 0:00:09 time: 0.0485 data_time: 0.0039 memory: 1008 2022/11/02 21:09:48 - mmengine - INFO - Epoch(val) [800][340/500] eta: 0:00:09 time: 0.0604 data_time: 0.0039 memory: 1008 2022/11/02 21:09:48 - mmengine - INFO - Epoch(val) [800][345/500] eta: 0:00:09 time: 0.0545 data_time: 0.0030 memory: 1008 2022/11/02 21:09:49 - mmengine - INFO - Epoch(val) [800][350/500] eta: 0:00:08 time: 0.0599 data_time: 0.0043 memory: 1008 2022/11/02 21:09:49 - mmengine - INFO - Epoch(val) [800][355/500] eta: 0:00:08 time: 0.0579 data_time: 0.0039 memory: 1008 2022/11/02 21:09:49 - mmengine - INFO - Epoch(val) [800][360/500] eta: 0:00:05 time: 0.0401 data_time: 0.0027 memory: 1008 2022/11/02 21:09:49 - mmengine - INFO - Epoch(val) [800][365/500] eta: 0:00:05 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 21:09:49 - mmengine - INFO - Epoch(val) [800][370/500] eta: 0:00:05 time: 0.0394 data_time: 0.0026 memory: 1008 2022/11/02 21:09:50 - mmengine - INFO - Epoch(val) [800][375/500] eta: 0:00:05 time: 0.0396 data_time: 0.0032 memory: 1008 2022/11/02 21:09:50 - mmengine - INFO - Epoch(val) [800][380/500] eta: 0:00:05 time: 0.0453 data_time: 0.0035 memory: 1008 2022/11/02 21:09:50 - mmengine - INFO - Epoch(val) [800][385/500] eta: 0:00:05 time: 0.0474 data_time: 0.0032 memory: 1008 2022/11/02 21:09:50 - mmengine - INFO - Epoch(val) [800][390/500] eta: 0:00:04 time: 0.0414 data_time: 0.0029 memory: 1008 2022/11/02 21:09:50 - mmengine - INFO - Epoch(val) [800][395/500] eta: 0:00:04 time: 0.0416 data_time: 0.0029 memory: 1008 2022/11/02 21:09:51 - mmengine - INFO - Epoch(val) [800][400/500] eta: 0:00:04 time: 0.0413 data_time: 0.0029 memory: 1008 2022/11/02 21:09:51 - mmengine - INFO - Epoch(val) [800][405/500] eta: 0:00:04 time: 0.0382 data_time: 0.0026 memory: 1008 2022/11/02 21:09:51 - mmengine - INFO - Epoch(val) [800][410/500] eta: 0:00:03 time: 0.0423 data_time: 0.0026 memory: 1008 2022/11/02 21:09:51 - mmengine - INFO - Epoch(val) [800][415/500] eta: 0:00:03 time: 0.0410 data_time: 0.0025 memory: 1008 2022/11/02 21:09:51 - mmengine - INFO - Epoch(val) [800][420/500] eta: 0:00:02 time: 0.0357 data_time: 0.0025 memory: 1008 2022/11/02 21:09:52 - mmengine - INFO - Epoch(val) [800][425/500] eta: 0:00:02 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/02 21:09:52 - mmengine - INFO - Epoch(val) [800][430/500] eta: 0:00:02 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 21:09:52 - mmengine - INFO - Epoch(val) [800][435/500] eta: 0:00:02 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 21:09:52 - mmengine - INFO - Epoch(val) [800][440/500] eta: 0:00:02 time: 0.0394 data_time: 0.0026 memory: 1008 2022/11/02 21:09:52 - mmengine - INFO - Epoch(val) [800][445/500] eta: 0:00:02 time: 0.0455 data_time: 0.0030 memory: 1008 2022/11/02 21:09:53 - mmengine - INFO - Epoch(val) [800][450/500] eta: 0:00:02 time: 0.0485 data_time: 0.0030 memory: 1008 2022/11/02 21:09:53 - mmengine - INFO - Epoch(val) [800][455/500] eta: 0:00:02 time: 0.0423 data_time: 0.0027 memory: 1008 2022/11/02 21:09:53 - mmengine - INFO - Epoch(val) [800][460/500] eta: 0:00:01 time: 0.0396 data_time: 0.0030 memory: 1008 2022/11/02 21:09:53 - mmengine - INFO - Epoch(val) [800][465/500] eta: 0:00:01 time: 0.0384 data_time: 0.0031 memory: 1008 2022/11/02 21:09:53 - mmengine - INFO - Epoch(val) [800][470/500] eta: 0:00:01 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 21:09:54 - mmengine - INFO - Epoch(val) [800][475/500] eta: 0:00:01 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/02 21:09:54 - mmengine - INFO - Epoch(val) [800][480/500] eta: 0:00:00 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/02 21:09:54 - mmengine - INFO - Epoch(val) [800][485/500] eta: 0:00:00 time: 0.0460 data_time: 0.0034 memory: 1008 2022/11/02 21:09:54 - mmengine - INFO - Epoch(val) [800][490/500] eta: 0:00:00 time: 0.0483 data_time: 0.0037 memory: 1008 2022/11/02 21:09:55 - mmengine - INFO - Epoch(val) [800][495/500] eta: 0:00:00 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/02 21:09:55 - mmengine - INFO - Epoch(val) [800][500/500] eta: 0:00:00 time: 0.0405 data_time: 0.0030 memory: 1008 2022/11/02 21:09:55 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8416, precision: 0.7083, hmean: 0.7692 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8416, precision: 0.7584, hmean: 0.7978 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8416, precision: 0.7913, hmean: 0.8157 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8387, precision: 0.8190, hmean: 0.8287 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8209, precision: 0.8546, hmean: 0.8374 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7116, precision: 0.9062, hmean: 0.7972 2022/11/02 21:09:55 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1184, precision: 0.9535, hmean: 0.2107 2022/11/02 21:09:55 - mmengine - INFO - Epoch(val) [800][500/500] icdar/precision: 0.8546 icdar/recall: 0.8209 icdar/hmean: 0.8374 2022/11/02 21:10:00 - mmengine - INFO - Epoch(train) [801][5/63] lr: 8.0360e-04 eta: 0:00:00 time: 0.8140 data_time: 0.2066 memory: 14901 loss: 0.9188 loss_prob: 0.4710 loss_thr: 0.3665 loss_db: 0.0813 2022/11/02 21:10:03 - mmengine - INFO - Epoch(train) [801][10/63] lr: 8.0360e-04 eta: 4:14:32 time: 0.8088 data_time: 0.2057 memory: 14901 loss: 0.9257 loss_prob: 0.4802 loss_thr: 0.3623 loss_db: 0.0832 2022/11/02 21:10:06 - mmengine - INFO - Epoch(train) [801][15/63] lr: 8.0360e-04 eta: 4:14:32 time: 0.5535 data_time: 0.0200 memory: 14901 loss: 1.0524 loss_prob: 0.5491 loss_thr: 0.4081 loss_db: 0.0953 2022/11/02 21:10:09 - mmengine - INFO - Epoch(train) [801][20/63] lr: 8.0360e-04 eta: 4:14:26 time: 0.5947 data_time: 0.0147 memory: 14901 loss: 1.1153 loss_prob: 0.5850 loss_thr: 0.4287 loss_db: 0.1016 2022/11/02 21:10:13 - mmengine - INFO - Epoch(train) [801][25/63] lr: 8.0360e-04 eta: 4:14:26 time: 0.7129 data_time: 0.0111 memory: 14901 loss: 1.1138 loss_prob: 0.5881 loss_thr: 0.4245 loss_db: 0.1012 2022/11/02 21:10:17 - mmengine - INFO - Epoch(train) [801][30/63] lr: 8.0360e-04 eta: 4:14:21 time: 0.7803 data_time: 0.0438 memory: 14901 loss: 1.1041 loss_prob: 0.5822 loss_thr: 0.4234 loss_db: 0.0986 2022/11/02 21:10:20 - mmengine - INFO - Epoch(train) [801][35/63] lr: 8.0360e-04 eta: 4:14:21 time: 0.7012 data_time: 0.0454 memory: 14901 loss: 1.0845 loss_prob: 0.5698 loss_thr: 0.4159 loss_db: 0.0988 2022/11/02 21:10:24 - mmengine - INFO - Epoch(train) [801][40/63] lr: 8.0360e-04 eta: 4:14:15 time: 0.7173 data_time: 0.0189 memory: 14901 loss: 1.0847 loss_prob: 0.5641 loss_thr: 0.4226 loss_db: 0.0981 2022/11/02 21:10:27 - mmengine - INFO - Epoch(train) [801][45/63] lr: 8.0360e-04 eta: 4:14:15 time: 0.6675 data_time: 0.0141 memory: 14901 loss: 1.0562 loss_prob: 0.5487 loss_thr: 0.4110 loss_db: 0.0966 2022/11/02 21:10:30 - mmengine - INFO - Epoch(train) [801][50/63] lr: 8.0360e-04 eta: 4:14:09 time: 0.5999 data_time: 0.0168 memory: 14901 loss: 1.0257 loss_prob: 0.5368 loss_thr: 0.3951 loss_db: 0.0937 2022/11/02 21:10:34 - mmengine - INFO - Epoch(train) [801][55/63] lr: 8.0360e-04 eta: 4:14:09 time: 0.6880 data_time: 0.0275 memory: 14901 loss: 0.9989 loss_prob: 0.5148 loss_thr: 0.3963 loss_db: 0.0878 2022/11/02 21:10:37 - mmengine - INFO - Epoch(train) [801][60/63] lr: 8.0360e-04 eta: 4:14:03 time: 0.6795 data_time: 0.0227 memory: 14901 loss: 1.0096 loss_prob: 0.5181 loss_thr: 0.4027 loss_db: 0.0888 2022/11/02 21:10:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:10:44 - mmengine - INFO - Epoch(train) [802][5/63] lr: 8.0179e-04 eta: 4:14:03 time: 0.8261 data_time: 0.2571 memory: 14901 loss: 1.0803 loss_prob: 0.5631 loss_thr: 0.4217 loss_db: 0.0955 2022/11/02 21:10:47 - mmengine - INFO - Epoch(train) [802][10/63] lr: 8.0179e-04 eta: 4:13:56 time: 0.9012 data_time: 0.2550 memory: 14901 loss: 1.0196 loss_prob: 0.5337 loss_thr: 0.3959 loss_db: 0.0900 2022/11/02 21:10:50 - mmengine - INFO - Epoch(train) [802][15/63] lr: 8.0179e-04 eta: 4:13:56 time: 0.6477 data_time: 0.0124 memory: 14901 loss: 0.9928 loss_prob: 0.5127 loss_thr: 0.3912 loss_db: 0.0888 2022/11/02 21:10:55 - mmengine - INFO - Epoch(train) [802][20/63] lr: 8.0179e-04 eta: 4:13:51 time: 0.7610 data_time: 0.0151 memory: 14901 loss: 0.9773 loss_prob: 0.5028 loss_thr: 0.3861 loss_db: 0.0884 2022/11/02 21:10:57 - mmengine - INFO - Epoch(train) [802][25/63] lr: 8.0179e-04 eta: 4:13:51 time: 0.7006 data_time: 0.0350 memory: 14901 loss: 0.9987 loss_prob: 0.5206 loss_thr: 0.3876 loss_db: 0.0905 2022/11/02 21:11:00 - mmengine - INFO - Epoch(train) [802][30/63] lr: 8.0179e-04 eta: 4:13:44 time: 0.5566 data_time: 0.0437 memory: 14901 loss: 1.0372 loss_prob: 0.5403 loss_thr: 0.4032 loss_db: 0.0936 2022/11/02 21:11:03 - mmengine - INFO - Epoch(train) [802][35/63] lr: 8.0179e-04 eta: 4:13:44 time: 0.5852 data_time: 0.0234 memory: 14901 loss: 1.0249 loss_prob: 0.5217 loss_thr: 0.4140 loss_db: 0.0892 2022/11/02 21:11:06 - mmengine - INFO - Epoch(train) [802][40/63] lr: 8.0179e-04 eta: 4:13:38 time: 0.5822 data_time: 0.0088 memory: 14901 loss: 1.0823 loss_prob: 0.5567 loss_thr: 0.4323 loss_db: 0.0932 2022/11/02 21:11:09 - mmengine - INFO - Epoch(train) [802][45/63] lr: 8.0179e-04 eta: 4:13:38 time: 0.5823 data_time: 0.0057 memory: 14901 loss: 1.0816 loss_prob: 0.5616 loss_thr: 0.4228 loss_db: 0.0972 2022/11/02 21:11:12 - mmengine - INFO - Epoch(train) [802][50/63] lr: 8.0179e-04 eta: 4:13:32 time: 0.5665 data_time: 0.0297 memory: 14901 loss: 1.0665 loss_prob: 0.5637 loss_thr: 0.4051 loss_db: 0.0977 2022/11/02 21:11:14 - mmengine - INFO - Epoch(train) [802][55/63] lr: 8.0179e-04 eta: 4:13:32 time: 0.5211 data_time: 0.0320 memory: 14901 loss: 1.0625 loss_prob: 0.5697 loss_thr: 0.3956 loss_db: 0.0972 2022/11/02 21:11:17 - mmengine - INFO - Epoch(train) [802][60/63] lr: 8.0179e-04 eta: 4:13:25 time: 0.5008 data_time: 0.0079 memory: 14901 loss: 0.9463 loss_prob: 0.4961 loss_thr: 0.3643 loss_db: 0.0860 2022/11/02 21:11:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:11:23 - mmengine - INFO - Epoch(train) [803][5/63] lr: 7.9997e-04 eta: 4:13:25 time: 0.7312 data_time: 0.1995 memory: 14901 loss: 1.1090 loss_prob: 0.5989 loss_thr: 0.4072 loss_db: 0.1030 2022/11/02 21:11:26 - mmengine - INFO - Epoch(train) [803][10/63] lr: 7.9997e-04 eta: 4:13:17 time: 0.7836 data_time: 0.2101 memory: 14901 loss: 1.0200 loss_prob: 0.5414 loss_thr: 0.3848 loss_db: 0.0937 2022/11/02 21:11:29 - mmengine - INFO - Epoch(train) [803][15/63] lr: 7.9997e-04 eta: 4:13:17 time: 0.5430 data_time: 0.0176 memory: 14901 loss: 1.0344 loss_prob: 0.5444 loss_thr: 0.3968 loss_db: 0.0931 2022/11/02 21:11:31 - mmengine - INFO - Epoch(train) [803][20/63] lr: 7.9997e-04 eta: 4:13:11 time: 0.5486 data_time: 0.0102 memory: 14901 loss: 1.0678 loss_prob: 0.5603 loss_thr: 0.4083 loss_db: 0.0992 2022/11/02 21:11:34 - mmengine - INFO - Epoch(train) [803][25/63] lr: 7.9997e-04 eta: 4:13:11 time: 0.5482 data_time: 0.0147 memory: 14901 loss: 0.9974 loss_prob: 0.5212 loss_thr: 0.3843 loss_db: 0.0919 2022/11/02 21:11:38 - mmengine - INFO - Epoch(train) [803][30/63] lr: 7.9997e-04 eta: 4:13:05 time: 0.6253 data_time: 0.0366 memory: 14901 loss: 0.9513 loss_prob: 0.4931 loss_thr: 0.3741 loss_db: 0.0841 2022/11/02 21:11:41 - mmengine - INFO - Epoch(train) [803][35/63] lr: 7.9997e-04 eta: 4:13:05 time: 0.6606 data_time: 0.0381 memory: 14901 loss: 1.0462 loss_prob: 0.5500 loss_thr: 0.4026 loss_db: 0.0937 2022/11/02 21:11:44 - mmengine - INFO - Epoch(train) [803][40/63] lr: 7.9997e-04 eta: 4:12:59 time: 0.6486 data_time: 0.0165 memory: 14901 loss: 1.0822 loss_prob: 0.5779 loss_thr: 0.4046 loss_db: 0.0997 2022/11/02 21:11:47 - mmengine - INFO - Epoch(train) [803][45/63] lr: 7.9997e-04 eta: 4:12:59 time: 0.6753 data_time: 0.0118 memory: 14901 loss: 1.0087 loss_prob: 0.5256 loss_thr: 0.3923 loss_db: 0.0908 2022/11/02 21:11:50 - mmengine - INFO - Epoch(train) [803][50/63] lr: 7.9997e-04 eta: 4:12:53 time: 0.6122 data_time: 0.0161 memory: 14901 loss: 0.9816 loss_prob: 0.5056 loss_thr: 0.3895 loss_db: 0.0865 2022/11/02 21:11:53 - mmengine - INFO - Epoch(train) [803][55/63] lr: 7.9997e-04 eta: 4:12:53 time: 0.5226 data_time: 0.0283 memory: 14901 loss: 1.1199 loss_prob: 0.5917 loss_thr: 0.4264 loss_db: 0.1019 2022/11/02 21:11:56 - mmengine - INFO - Epoch(train) [803][60/63] lr: 7.9997e-04 eta: 4:12:47 time: 0.5654 data_time: 0.0278 memory: 14901 loss: 1.1618 loss_prob: 0.6153 loss_thr: 0.4402 loss_db: 0.1064 2022/11/02 21:11:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:12:04 - mmengine - INFO - Epoch(train) [804][5/63] lr: 7.9816e-04 eta: 4:12:47 time: 0.9100 data_time: 0.2790 memory: 14901 loss: 1.0640 loss_prob: 0.5661 loss_thr: 0.4012 loss_db: 0.0967 2022/11/02 21:12:06 - mmengine - INFO - Epoch(train) [804][10/63] lr: 7.9816e-04 eta: 4:12:40 time: 0.9028 data_time: 0.2768 memory: 14901 loss: 1.1623 loss_prob: 0.6367 loss_thr: 0.4194 loss_db: 0.1062 2022/11/02 21:12:09 - mmengine - INFO - Epoch(train) [804][15/63] lr: 7.9816e-04 eta: 4:12:40 time: 0.5217 data_time: 0.0089 memory: 14901 loss: 1.1255 loss_prob: 0.6120 loss_thr: 0.4126 loss_db: 0.1010 2022/11/02 21:12:13 - mmengine - INFO - Epoch(train) [804][20/63] lr: 7.9816e-04 eta: 4:12:34 time: 0.6292 data_time: 0.0145 memory: 14901 loss: 1.0352 loss_prob: 0.5418 loss_thr: 0.4027 loss_db: 0.0907 2022/11/02 21:12:16 - mmengine - INFO - Epoch(train) [804][25/63] lr: 7.9816e-04 eta: 4:12:34 time: 0.6921 data_time: 0.0397 memory: 14901 loss: 1.1137 loss_prob: 0.5970 loss_thr: 0.4147 loss_db: 0.1019 2022/11/02 21:12:19 - mmengine - INFO - Epoch(train) [804][30/63] lr: 7.9816e-04 eta: 4:12:28 time: 0.6445 data_time: 0.0432 memory: 14901 loss: 1.1178 loss_prob: 0.6018 loss_thr: 0.4087 loss_db: 0.1072 2022/11/02 21:12:22 - mmengine - INFO - Epoch(train) [804][35/63] lr: 7.9816e-04 eta: 4:12:28 time: 0.6333 data_time: 0.0189 memory: 14901 loss: 1.0318 loss_prob: 0.5400 loss_thr: 0.3973 loss_db: 0.0946 2022/11/02 21:12:26 - mmengine - INFO - Epoch(train) [804][40/63] lr: 7.9816e-04 eta: 4:12:22 time: 0.6490 data_time: 0.0092 memory: 14901 loss: 0.9920 loss_prob: 0.5144 loss_thr: 0.3928 loss_db: 0.0849 2022/11/02 21:12:29 - mmengine - INFO - Epoch(train) [804][45/63] lr: 7.9816e-04 eta: 4:12:22 time: 0.6377 data_time: 0.0074 memory: 14901 loss: 1.0258 loss_prob: 0.5381 loss_thr: 0.3970 loss_db: 0.0907 2022/11/02 21:12:31 - mmengine - INFO - Epoch(train) [804][50/63] lr: 7.9816e-04 eta: 4:12:16 time: 0.5862 data_time: 0.0294 memory: 14901 loss: 1.0195 loss_prob: 0.5261 loss_thr: 0.3996 loss_db: 0.0938 2022/11/02 21:12:34 - mmengine - INFO - Epoch(train) [804][55/63] lr: 7.9816e-04 eta: 4:12:16 time: 0.5501 data_time: 0.0299 memory: 14901 loss: 1.0818 loss_prob: 0.5677 loss_thr: 0.4149 loss_db: 0.0992 2022/11/02 21:12:37 - mmengine - INFO - Epoch(train) [804][60/63] lr: 7.9816e-04 eta: 4:12:09 time: 0.5504 data_time: 0.0122 memory: 14901 loss: 1.1014 loss_prob: 0.5811 loss_thr: 0.4233 loss_db: 0.0971 2022/11/02 21:12:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:12:45 - mmengine - INFO - Epoch(train) [805][5/63] lr: 7.9635e-04 eta: 4:12:09 time: 0.9424 data_time: 0.2709 memory: 14901 loss: 1.1888 loss_prob: 0.6391 loss_thr: 0.4371 loss_db: 0.1125 2022/11/02 21:12:48 - mmengine - INFO - Epoch(train) [805][10/63] lr: 7.9635e-04 eta: 4:12:02 time: 0.9457 data_time: 0.2719 memory: 14901 loss: 1.1919 loss_prob: 0.6460 loss_thr: 0.4323 loss_db: 0.1136 2022/11/02 21:12:52 - mmengine - INFO - Epoch(train) [805][15/63] lr: 7.9635e-04 eta: 4:12:02 time: 0.6288 data_time: 0.0128 memory: 14901 loss: 1.0426 loss_prob: 0.5489 loss_thr: 0.3997 loss_db: 0.0941 2022/11/02 21:12:54 - mmengine - INFO - Epoch(train) [805][20/63] lr: 7.9635e-04 eta: 4:11:56 time: 0.6338 data_time: 0.0139 memory: 14901 loss: 1.0338 loss_prob: 0.5445 loss_thr: 0.3948 loss_db: 0.0945 2022/11/02 21:12:58 - mmengine - INFO - Epoch(train) [805][25/63] lr: 7.9635e-04 eta: 4:11:56 time: 0.6297 data_time: 0.0135 memory: 14901 loss: 1.0289 loss_prob: 0.5416 loss_thr: 0.3933 loss_db: 0.0940 2022/11/02 21:13:01 - mmengine - INFO - Epoch(train) [805][30/63] lr: 7.9635e-04 eta: 4:11:51 time: 0.7068 data_time: 0.0410 memory: 14901 loss: 1.0752 loss_prob: 0.5607 loss_thr: 0.4180 loss_db: 0.0965 2022/11/02 21:13:04 - mmengine - INFO - Epoch(train) [805][35/63] lr: 7.9635e-04 eta: 4:11:51 time: 0.6366 data_time: 0.0410 memory: 14901 loss: 1.0902 loss_prob: 0.5643 loss_thr: 0.4293 loss_db: 0.0966 2022/11/02 21:13:07 - mmengine - INFO - Epoch(train) [805][40/63] lr: 7.9635e-04 eta: 4:11:45 time: 0.5796 data_time: 0.0104 memory: 14901 loss: 1.0488 loss_prob: 0.5499 loss_thr: 0.4036 loss_db: 0.0952 2022/11/02 21:13:10 - mmengine - INFO - Epoch(train) [805][45/63] lr: 7.9635e-04 eta: 4:11:45 time: 0.6165 data_time: 0.0312 memory: 14901 loss: 1.0507 loss_prob: 0.5552 loss_thr: 0.4000 loss_db: 0.0955 2022/11/02 21:13:13 - mmengine - INFO - Epoch(train) [805][50/63] lr: 7.9635e-04 eta: 4:11:38 time: 0.5908 data_time: 0.0481 memory: 14901 loss: 1.0240 loss_prob: 0.5349 loss_thr: 0.3957 loss_db: 0.0934 2022/11/02 21:13:16 - mmengine - INFO - Epoch(train) [805][55/63] lr: 7.9635e-04 eta: 4:11:38 time: 0.5526 data_time: 0.0297 memory: 14901 loss: 1.0645 loss_prob: 0.5595 loss_thr: 0.4065 loss_db: 0.0984 2022/11/02 21:13:18 - mmengine - INFO - Epoch(train) [805][60/63] lr: 7.9635e-04 eta: 4:11:32 time: 0.5215 data_time: 0.0144 memory: 14901 loss: 1.0898 loss_prob: 0.5774 loss_thr: 0.4135 loss_db: 0.0988 2022/11/02 21:13:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:13:26 - mmengine - INFO - Epoch(train) [806][5/63] lr: 7.9453e-04 eta: 4:11:32 time: 0.8441 data_time: 0.2355 memory: 14901 loss: 1.1535 loss_prob: 0.6164 loss_thr: 0.4301 loss_db: 0.1071 2022/11/02 21:13:29 - mmengine - INFO - Epoch(train) [806][10/63] lr: 7.9453e-04 eta: 4:11:25 time: 0.8988 data_time: 0.2399 memory: 14901 loss: 1.0583 loss_prob: 0.5576 loss_thr: 0.4050 loss_db: 0.0958 2022/11/02 21:13:31 - mmengine - INFO - Epoch(train) [806][15/63] lr: 7.9453e-04 eta: 4:11:25 time: 0.5702 data_time: 0.0166 memory: 14901 loss: 0.9991 loss_prob: 0.5207 loss_thr: 0.3870 loss_db: 0.0913 2022/11/02 21:13:35 - mmengine - INFO - Epoch(train) [806][20/63] lr: 7.9453e-04 eta: 4:11:19 time: 0.5982 data_time: 0.0122 memory: 14901 loss: 1.0231 loss_prob: 0.5301 loss_thr: 0.4018 loss_db: 0.0912 2022/11/02 21:13:38 - mmengine - INFO - Epoch(train) [806][25/63] lr: 7.9453e-04 eta: 4:11:19 time: 0.6042 data_time: 0.0569 memory: 14901 loss: 1.0887 loss_prob: 0.5714 loss_thr: 0.4214 loss_db: 0.0959 2022/11/02 21:13:40 - mmengine - INFO - Epoch(train) [806][30/63] lr: 7.9453e-04 eta: 4:11:12 time: 0.5561 data_time: 0.0746 memory: 14901 loss: 1.0536 loss_prob: 0.5560 loss_thr: 0.4037 loss_db: 0.0939 2022/11/02 21:13:43 - mmengine - INFO - Epoch(train) [806][35/63] lr: 7.9453e-04 eta: 4:11:12 time: 0.5549 data_time: 0.0263 memory: 14901 loss: 1.0616 loss_prob: 0.5645 loss_thr: 0.4026 loss_db: 0.0944 2022/11/02 21:13:46 - mmengine - INFO - Epoch(train) [806][40/63] lr: 7.9453e-04 eta: 4:11:06 time: 0.5412 data_time: 0.0083 memory: 14901 loss: 1.0781 loss_prob: 0.5745 loss_thr: 0.4055 loss_db: 0.0981 2022/11/02 21:13:49 - mmengine - INFO - Epoch(train) [806][45/63] lr: 7.9453e-04 eta: 4:11:06 time: 0.5497 data_time: 0.0117 memory: 14901 loss: 1.0061 loss_prob: 0.5222 loss_thr: 0.3926 loss_db: 0.0913 2022/11/02 21:13:51 - mmengine - INFO - Epoch(train) [806][50/63] lr: 7.9453e-04 eta: 4:11:00 time: 0.5651 data_time: 0.0270 memory: 14901 loss: 1.0309 loss_prob: 0.5260 loss_thr: 0.4130 loss_db: 0.0919 2022/11/02 21:13:54 - mmengine - INFO - Epoch(train) [806][55/63] lr: 7.9453e-04 eta: 4:11:00 time: 0.5518 data_time: 0.0320 memory: 14901 loss: 1.0652 loss_prob: 0.5528 loss_thr: 0.4158 loss_db: 0.0966 2022/11/02 21:13:57 - mmengine - INFO - Epoch(train) [806][60/63] lr: 7.9453e-04 eta: 4:10:53 time: 0.5435 data_time: 0.0175 memory: 14901 loss: 1.0527 loss_prob: 0.5450 loss_thr: 0.4132 loss_db: 0.0944 2022/11/02 21:13:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:14:04 - mmengine - INFO - Epoch(train) [807][5/63] lr: 7.9272e-04 eta: 4:10:53 time: 0.7949 data_time: 0.2652 memory: 14901 loss: 1.1126 loss_prob: 0.6042 loss_thr: 0.4087 loss_db: 0.0997 2022/11/02 21:14:08 - mmengine - INFO - Epoch(train) [807][10/63] lr: 7.9272e-04 eta: 4:10:46 time: 1.0204 data_time: 0.2652 memory: 14901 loss: 1.0688 loss_prob: 0.5740 loss_thr: 0.4004 loss_db: 0.0944 2022/11/02 21:14:12 - mmengine - INFO - Epoch(train) [807][15/63] lr: 7.9272e-04 eta: 4:10:46 time: 0.8040 data_time: 0.0113 memory: 14901 loss: 1.0878 loss_prob: 0.5559 loss_thr: 0.4372 loss_db: 0.0947 2022/11/02 21:14:14 - mmengine - INFO - Epoch(train) [807][20/63] lr: 7.9272e-04 eta: 4:10:40 time: 0.6014 data_time: 0.0112 memory: 14901 loss: 1.0706 loss_prob: 0.5532 loss_thr: 0.4223 loss_db: 0.0951 2022/11/02 21:14:18 - mmengine - INFO - Epoch(train) [807][25/63] lr: 7.9272e-04 eta: 4:10:40 time: 0.5905 data_time: 0.0468 memory: 14901 loss: 1.0809 loss_prob: 0.5710 loss_thr: 0.4093 loss_db: 0.1006 2022/11/02 21:14:20 - mmengine - INFO - Epoch(train) [807][30/63] lr: 7.9272e-04 eta: 4:10:34 time: 0.5759 data_time: 0.0479 memory: 14901 loss: 1.1356 loss_prob: 0.6054 loss_thr: 0.4253 loss_db: 0.1050 2022/11/02 21:14:23 - mmengine - INFO - Epoch(train) [807][35/63] lr: 7.9272e-04 eta: 4:10:34 time: 0.5022 data_time: 0.0100 memory: 14901 loss: 1.0827 loss_prob: 0.5729 loss_thr: 0.4132 loss_db: 0.0966 2022/11/02 21:14:25 - mmengine - INFO - Epoch(train) [807][40/63] lr: 7.9272e-04 eta: 4:10:28 time: 0.5070 data_time: 0.0094 memory: 14901 loss: 0.9981 loss_prob: 0.5165 loss_thr: 0.3921 loss_db: 0.0895 2022/11/02 21:14:28 - mmengine - INFO - Epoch(train) [807][45/63] lr: 7.9272e-04 eta: 4:10:28 time: 0.5452 data_time: 0.0154 memory: 14901 loss: 1.0191 loss_prob: 0.5290 loss_thr: 0.3983 loss_db: 0.0918 2022/11/02 21:14:31 - mmengine - INFO - Epoch(train) [807][50/63] lr: 7.9272e-04 eta: 4:10:21 time: 0.5367 data_time: 0.0285 memory: 14901 loss: 1.0667 loss_prob: 0.5595 loss_thr: 0.4107 loss_db: 0.0965 2022/11/02 21:14:33 - mmengine - INFO - Epoch(train) [807][55/63] lr: 7.9272e-04 eta: 4:10:21 time: 0.5188 data_time: 0.0254 memory: 14901 loss: 1.0239 loss_prob: 0.5288 loss_thr: 0.4046 loss_db: 0.0905 2022/11/02 21:14:36 - mmengine - INFO - Epoch(train) [807][60/63] lr: 7.9272e-04 eta: 4:10:15 time: 0.5513 data_time: 0.0131 memory: 14901 loss: 0.9179 loss_prob: 0.4655 loss_thr: 0.3722 loss_db: 0.0802 2022/11/02 21:14:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:14:43 - mmengine - INFO - Epoch(train) [808][5/63] lr: 7.9090e-04 eta: 4:10:15 time: 0.8426 data_time: 0.2492 memory: 14901 loss: 1.0062 loss_prob: 0.5111 loss_thr: 0.4057 loss_db: 0.0894 2022/11/02 21:14:47 - mmengine - INFO - Epoch(train) [808][10/63] lr: 7.9090e-04 eta: 4:10:08 time: 0.9712 data_time: 0.2483 memory: 14901 loss: 1.0526 loss_prob: 0.5412 loss_thr: 0.4183 loss_db: 0.0931 2022/11/02 21:14:51 - mmengine - INFO - Epoch(train) [808][15/63] lr: 7.9090e-04 eta: 4:10:08 time: 0.7622 data_time: 0.0081 memory: 14901 loss: 1.0017 loss_prob: 0.5229 loss_thr: 0.3882 loss_db: 0.0907 2022/11/02 21:14:54 - mmengine - INFO - Epoch(train) [808][20/63] lr: 7.9090e-04 eta: 4:10:02 time: 0.6853 data_time: 0.0084 memory: 14901 loss: 1.0878 loss_prob: 0.5873 loss_thr: 0.3997 loss_db: 0.1009 2022/11/02 21:14:58 - mmengine - INFO - Epoch(train) [808][25/63] lr: 7.9090e-04 eta: 4:10:02 time: 0.6677 data_time: 0.0202 memory: 14901 loss: 1.1800 loss_prob: 0.6505 loss_thr: 0.4242 loss_db: 0.1054 2022/11/02 21:15:01 - mmengine - INFO - Epoch(train) [808][30/63] lr: 7.9090e-04 eta: 4:09:56 time: 0.6434 data_time: 0.0365 memory: 14901 loss: 1.0842 loss_prob: 0.5840 loss_thr: 0.4051 loss_db: 0.0950 2022/11/02 21:15:03 - mmengine - INFO - Epoch(train) [808][35/63] lr: 7.9090e-04 eta: 4:09:56 time: 0.5584 data_time: 0.0289 memory: 14901 loss: 1.0538 loss_prob: 0.5542 loss_thr: 0.4028 loss_db: 0.0968 2022/11/02 21:15:06 - mmengine - INFO - Epoch(train) [808][40/63] lr: 7.9090e-04 eta: 4:09:50 time: 0.5775 data_time: 0.0142 memory: 14901 loss: 1.1714 loss_prob: 0.6194 loss_thr: 0.4437 loss_db: 0.1083 2022/11/02 21:15:09 - mmengine - INFO - Epoch(train) [808][45/63] lr: 7.9090e-04 eta: 4:09:50 time: 0.5966 data_time: 0.0098 memory: 14901 loss: 1.1939 loss_prob: 0.6349 loss_thr: 0.4490 loss_db: 0.1099 2022/11/02 21:15:12 - mmengine - INFO - Epoch(train) [808][50/63] lr: 7.9090e-04 eta: 4:09:44 time: 0.5901 data_time: 0.0229 memory: 14901 loss: 1.1498 loss_prob: 0.6107 loss_thr: 0.4342 loss_db: 0.1048 2022/11/02 21:15:16 - mmengine - INFO - Epoch(train) [808][55/63] lr: 7.9090e-04 eta: 4:09:44 time: 0.6384 data_time: 0.0319 memory: 14901 loss: 1.0826 loss_prob: 0.5740 loss_thr: 0.4117 loss_db: 0.0969 2022/11/02 21:15:18 - mmengine - INFO - Epoch(train) [808][60/63] lr: 7.9090e-04 eta: 4:09:38 time: 0.6028 data_time: 0.0209 memory: 14901 loss: 0.9911 loss_prob: 0.5169 loss_thr: 0.3847 loss_db: 0.0895 2022/11/02 21:15:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:15:25 - mmengine - INFO - Epoch(train) [809][5/63] lr: 7.8909e-04 eta: 4:09:38 time: 0.8063 data_time: 0.2817 memory: 14901 loss: 1.0174 loss_prob: 0.5248 loss_thr: 0.4011 loss_db: 0.0916 2022/11/02 21:15:28 - mmengine - INFO - Epoch(train) [809][10/63] lr: 7.8909e-04 eta: 4:09:30 time: 0.8244 data_time: 0.2808 memory: 14901 loss: 0.9626 loss_prob: 0.4977 loss_thr: 0.3792 loss_db: 0.0856 2022/11/02 21:15:33 - mmengine - INFO - Epoch(train) [809][15/63] lr: 7.8909e-04 eta: 4:09:30 time: 0.7266 data_time: 0.0099 memory: 14901 loss: 0.9223 loss_prob: 0.4772 loss_thr: 0.3618 loss_db: 0.0833 2022/11/02 21:15:36 - mmengine - INFO - Epoch(train) [809][20/63] lr: 7.8909e-04 eta: 4:09:25 time: 0.7553 data_time: 0.0091 memory: 14901 loss: 1.0611 loss_prob: 0.5523 loss_thr: 0.4124 loss_db: 0.0965 2022/11/02 21:15:39 - mmengine - INFO - Epoch(train) [809][25/63] lr: 7.8909e-04 eta: 4:09:25 time: 0.6217 data_time: 0.0497 memory: 14901 loss: 1.1004 loss_prob: 0.5699 loss_thr: 0.4306 loss_db: 0.0999 2022/11/02 21:15:41 - mmengine - INFO - Epoch(train) [809][30/63] lr: 7.8909e-04 eta: 4:09:19 time: 0.5747 data_time: 0.0492 memory: 14901 loss: 1.0004 loss_prob: 0.5158 loss_thr: 0.3945 loss_db: 0.0902 2022/11/02 21:15:44 - mmengine - INFO - Epoch(train) [809][35/63] lr: 7.8909e-04 eta: 4:09:19 time: 0.5318 data_time: 0.0105 memory: 14901 loss: 1.0102 loss_prob: 0.5270 loss_thr: 0.3931 loss_db: 0.0900 2022/11/02 21:15:47 - mmengine - INFO - Epoch(train) [809][40/63] lr: 7.8909e-04 eta: 4:09:12 time: 0.5487 data_time: 0.0118 memory: 14901 loss: 0.9967 loss_prob: 0.5082 loss_thr: 0.4011 loss_db: 0.0875 2022/11/02 21:15:50 - mmengine - INFO - Epoch(train) [809][45/63] lr: 7.8909e-04 eta: 4:09:12 time: 0.5591 data_time: 0.0106 memory: 14901 loss: 0.9845 loss_prob: 0.4902 loss_thr: 0.4079 loss_db: 0.0864 2022/11/02 21:15:52 - mmengine - INFO - Epoch(train) [809][50/63] lr: 7.8909e-04 eta: 4:09:06 time: 0.5445 data_time: 0.0269 memory: 14901 loss: 0.9960 loss_prob: 0.5064 loss_thr: 0.4013 loss_db: 0.0883 2022/11/02 21:15:55 - mmengine - INFO - Epoch(train) [809][55/63] lr: 7.8909e-04 eta: 4:09:06 time: 0.5257 data_time: 0.0290 memory: 14901 loss: 1.0129 loss_prob: 0.5336 loss_thr: 0.3871 loss_db: 0.0922 2022/11/02 21:15:58 - mmengine - INFO - Epoch(train) [809][60/63] lr: 7.8909e-04 eta: 4:09:00 time: 0.5359 data_time: 0.0094 memory: 14901 loss: 1.0033 loss_prob: 0.5308 loss_thr: 0.3808 loss_db: 0.0916 2022/11/02 21:15:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:16:05 - mmengine - INFO - Epoch(train) [810][5/63] lr: 7.8727e-04 eta: 4:09:00 time: 0.8076 data_time: 0.2037 memory: 14901 loss: 0.9818 loss_prob: 0.5168 loss_thr: 0.3775 loss_db: 0.0875 2022/11/02 21:16:07 - mmengine - INFO - Epoch(train) [810][10/63] lr: 7.8727e-04 eta: 4:08:52 time: 0.8201 data_time: 0.2006 memory: 14901 loss: 1.0670 loss_prob: 0.5684 loss_thr: 0.4016 loss_db: 0.0969 2022/11/02 21:16:10 - mmengine - INFO - Epoch(train) [810][15/63] lr: 7.8727e-04 eta: 4:08:52 time: 0.5520 data_time: 0.0204 memory: 14901 loss: 1.0188 loss_prob: 0.5364 loss_thr: 0.3891 loss_db: 0.0933 2022/11/02 21:16:13 - mmengine - INFO - Epoch(train) [810][20/63] lr: 7.8727e-04 eta: 4:08:46 time: 0.5768 data_time: 0.0206 memory: 14901 loss: 0.9995 loss_prob: 0.5252 loss_thr: 0.3843 loss_db: 0.0899 2022/11/02 21:16:16 - mmengine - INFO - Epoch(train) [810][25/63] lr: 7.8727e-04 eta: 4:08:46 time: 0.5741 data_time: 0.0169 memory: 14901 loss: 0.9931 loss_prob: 0.5142 loss_thr: 0.3913 loss_db: 0.0876 2022/11/02 21:16:19 - mmengine - INFO - Epoch(train) [810][30/63] lr: 7.8727e-04 eta: 4:08:39 time: 0.5633 data_time: 0.0379 memory: 14901 loss: 0.9966 loss_prob: 0.5141 loss_thr: 0.3929 loss_db: 0.0895 2022/11/02 21:16:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:16:22 - mmengine - INFO - Epoch(train) [810][35/63] lr: 7.8727e-04 eta: 4:08:39 time: 0.5796 data_time: 0.0370 memory: 14901 loss: 0.9868 loss_prob: 0.5156 loss_thr: 0.3809 loss_db: 0.0902 2022/11/02 21:16:25 - mmengine - INFO - Epoch(train) [810][40/63] lr: 7.8727e-04 eta: 4:08:33 time: 0.6001 data_time: 0.0196 memory: 14901 loss: 1.1555 loss_prob: 0.6691 loss_thr: 0.3876 loss_db: 0.0988 2022/11/02 21:16:27 - mmengine - INFO - Epoch(train) [810][45/63] lr: 7.8727e-04 eta: 4:08:33 time: 0.5604 data_time: 0.0144 memory: 14901 loss: 1.1702 loss_prob: 0.6795 loss_thr: 0.3900 loss_db: 0.1006 2022/11/02 21:16:30 - mmengine - INFO - Epoch(train) [810][50/63] lr: 7.8727e-04 eta: 4:08:27 time: 0.5130 data_time: 0.0174 memory: 14901 loss: 1.0323 loss_prob: 0.5424 loss_thr: 0.3946 loss_db: 0.0953 2022/11/02 21:16:32 - mmengine - INFO - Epoch(train) [810][55/63] lr: 7.8727e-04 eta: 4:08:27 time: 0.5133 data_time: 0.0288 memory: 14901 loss: 1.0474 loss_prob: 0.5509 loss_thr: 0.4012 loss_db: 0.0952 2022/11/02 21:16:35 - mmengine - INFO - Epoch(train) [810][60/63] lr: 7.8727e-04 eta: 4:08:20 time: 0.5507 data_time: 0.0485 memory: 14901 loss: 1.0677 loss_prob: 0.5661 loss_thr: 0.4037 loss_db: 0.0979 2022/11/02 21:16:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:16:42 - mmengine - INFO - Epoch(train) [811][5/63] lr: 7.8545e-04 eta: 4:08:20 time: 0.8426 data_time: 0.2509 memory: 14901 loss: 1.0563 loss_prob: 0.5568 loss_thr: 0.4021 loss_db: 0.0973 2022/11/02 21:16:45 - mmengine - INFO - Epoch(train) [811][10/63] lr: 7.8545e-04 eta: 4:08:13 time: 0.8325 data_time: 0.2409 memory: 14901 loss: 1.0766 loss_prob: 0.5741 loss_thr: 0.4030 loss_db: 0.0995 2022/11/02 21:16:48 - mmengine - INFO - Epoch(train) [811][15/63] lr: 7.8545e-04 eta: 4:08:13 time: 0.5362 data_time: 0.0212 memory: 14901 loss: 1.0257 loss_prob: 0.5475 loss_thr: 0.3828 loss_db: 0.0954 2022/11/02 21:16:51 - mmengine - INFO - Epoch(train) [811][20/63] lr: 7.8545e-04 eta: 4:08:07 time: 0.6048 data_time: 0.0162 memory: 14901 loss: 1.0273 loss_prob: 0.5462 loss_thr: 0.3870 loss_db: 0.0942 2022/11/02 21:16:54 - mmengine - INFO - Epoch(train) [811][25/63] lr: 7.8545e-04 eta: 4:08:07 time: 0.6380 data_time: 0.0336 memory: 14901 loss: 1.0443 loss_prob: 0.5442 loss_thr: 0.4078 loss_db: 0.0922 2022/11/02 21:16:57 - mmengine - INFO - Epoch(train) [811][30/63] lr: 7.8545e-04 eta: 4:08:01 time: 0.6053 data_time: 0.0317 memory: 14901 loss: 1.0194 loss_prob: 0.5234 loss_thr: 0.4049 loss_db: 0.0911 2022/11/02 21:17:00 - mmengine - INFO - Epoch(train) [811][35/63] lr: 7.8545e-04 eta: 4:08:01 time: 0.5805 data_time: 0.0247 memory: 14901 loss: 1.0304 loss_prob: 0.5320 loss_thr: 0.4038 loss_db: 0.0946 2022/11/02 21:17:02 - mmengine - INFO - Epoch(train) [811][40/63] lr: 7.8545e-04 eta: 4:07:54 time: 0.5203 data_time: 0.0233 memory: 14901 loss: 1.0189 loss_prob: 0.5322 loss_thr: 0.3940 loss_db: 0.0926 2022/11/02 21:17:05 - mmengine - INFO - Epoch(train) [811][45/63] lr: 7.8545e-04 eta: 4:07:54 time: 0.4915 data_time: 0.0166 memory: 14901 loss: 1.0786 loss_prob: 0.5724 loss_thr: 0.4079 loss_db: 0.0982 2022/11/02 21:17:08 - mmengine - INFO - Epoch(train) [811][50/63] lr: 7.8545e-04 eta: 4:07:48 time: 0.5939 data_time: 0.0273 memory: 14901 loss: 1.1500 loss_prob: 0.6203 loss_thr: 0.4216 loss_db: 0.1082 2022/11/02 21:17:11 - mmengine - INFO - Epoch(train) [811][55/63] lr: 7.8545e-04 eta: 4:07:48 time: 0.6129 data_time: 0.0311 memory: 14901 loss: 1.0952 loss_prob: 0.5896 loss_thr: 0.4041 loss_db: 0.1015 2022/11/02 21:17:14 - mmengine - INFO - Epoch(train) [811][60/63] lr: 7.8545e-04 eta: 4:07:42 time: 0.5470 data_time: 0.0207 memory: 14901 loss: 1.0200 loss_prob: 0.5264 loss_thr: 0.4054 loss_db: 0.0881 2022/11/02 21:17:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:17:20 - mmengine - INFO - Epoch(train) [812][5/63] lr: 7.8364e-04 eta: 4:07:42 time: 0.7609 data_time: 0.2651 memory: 14901 loss: 1.1885 loss_prob: 0.6164 loss_thr: 0.4664 loss_db: 0.1057 2022/11/02 21:17:23 - mmengine - INFO - Epoch(train) [812][10/63] lr: 7.8364e-04 eta: 4:07:34 time: 0.8222 data_time: 0.2652 memory: 14901 loss: 1.1191 loss_prob: 0.5839 loss_thr: 0.4350 loss_db: 0.1001 2022/11/02 21:17:26 - mmengine - INFO - Epoch(train) [812][15/63] lr: 7.8364e-04 eta: 4:07:34 time: 0.5405 data_time: 0.0122 memory: 14901 loss: 1.0580 loss_prob: 0.5506 loss_thr: 0.4128 loss_db: 0.0946 2022/11/02 21:17:28 - mmengine - INFO - Epoch(train) [812][20/63] lr: 7.8364e-04 eta: 4:07:27 time: 0.5202 data_time: 0.0097 memory: 14901 loss: 1.0031 loss_prob: 0.5143 loss_thr: 0.3969 loss_db: 0.0918 2022/11/02 21:17:31 - mmengine - INFO - Epoch(train) [812][25/63] lr: 7.8364e-04 eta: 4:07:27 time: 0.5648 data_time: 0.0325 memory: 14901 loss: 1.0093 loss_prob: 0.5197 loss_thr: 0.3959 loss_db: 0.0937 2022/11/02 21:17:34 - mmengine - INFO - Epoch(train) [812][30/63] lr: 7.8364e-04 eta: 4:07:21 time: 0.5940 data_time: 0.0529 memory: 14901 loss: 1.0007 loss_prob: 0.5102 loss_thr: 0.4030 loss_db: 0.0875 2022/11/02 21:17:37 - mmengine - INFO - Epoch(train) [812][35/63] lr: 7.8364e-04 eta: 4:07:21 time: 0.5684 data_time: 0.0297 memory: 14901 loss: 0.9735 loss_prob: 0.4958 loss_thr: 0.3943 loss_db: 0.0835 2022/11/02 21:17:40 - mmengine - INFO - Epoch(train) [812][40/63] lr: 7.8364e-04 eta: 4:07:15 time: 0.5404 data_time: 0.0103 memory: 14901 loss: 1.0449 loss_prob: 0.5449 loss_thr: 0.4056 loss_db: 0.0943 2022/11/02 21:17:42 - mmengine - INFO - Epoch(train) [812][45/63] lr: 7.8364e-04 eta: 4:07:15 time: 0.5297 data_time: 0.0102 memory: 14901 loss: 0.9973 loss_prob: 0.5140 loss_thr: 0.3945 loss_db: 0.0888 2022/11/02 21:17:46 - mmengine - INFO - Epoch(train) [812][50/63] lr: 7.8364e-04 eta: 4:07:09 time: 0.5938 data_time: 0.0318 memory: 14901 loss: 0.9480 loss_prob: 0.4884 loss_thr: 0.3749 loss_db: 0.0848 2022/11/02 21:17:48 - mmengine - INFO - Epoch(train) [812][55/63] lr: 7.8364e-04 eta: 4:07:09 time: 0.5920 data_time: 0.0309 memory: 14901 loss: 0.9099 loss_prob: 0.4754 loss_thr: 0.3506 loss_db: 0.0839 2022/11/02 21:17:51 - mmengine - INFO - Epoch(train) [812][60/63] lr: 7.8364e-04 eta: 4:07:02 time: 0.5442 data_time: 0.0105 memory: 14901 loss: 0.9442 loss_prob: 0.4786 loss_thr: 0.3818 loss_db: 0.0837 2022/11/02 21:17:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:17:58 - mmengine - INFO - Epoch(train) [813][5/63] lr: 7.8182e-04 eta: 4:07:02 time: 0.7912 data_time: 0.2394 memory: 14901 loss: 0.9876 loss_prob: 0.5126 loss_thr: 0.3855 loss_db: 0.0895 2022/11/02 21:18:01 - mmengine - INFO - Epoch(train) [813][10/63] lr: 7.8182e-04 eta: 4:06:55 time: 0.8290 data_time: 0.2382 memory: 14901 loss: 0.9976 loss_prob: 0.5246 loss_thr: 0.3829 loss_db: 0.0901 2022/11/02 21:18:03 - mmengine - INFO - Epoch(train) [813][15/63] lr: 7.8182e-04 eta: 4:06:55 time: 0.5471 data_time: 0.0150 memory: 14901 loss: 1.0489 loss_prob: 0.5568 loss_thr: 0.3970 loss_db: 0.0951 2022/11/02 21:18:06 - mmengine - INFO - Epoch(train) [813][20/63] lr: 7.8182e-04 eta: 4:06:49 time: 0.5727 data_time: 0.0169 memory: 14901 loss: 1.1317 loss_prob: 0.6076 loss_thr: 0.4187 loss_db: 0.1054 2022/11/02 21:18:09 - mmengine - INFO - Epoch(train) [813][25/63] lr: 7.8182e-04 eta: 4:06:49 time: 0.5923 data_time: 0.0271 memory: 14901 loss: 1.1055 loss_prob: 0.5946 loss_thr: 0.4061 loss_db: 0.1049 2022/11/02 21:18:13 - mmengine - INFO - Epoch(train) [813][30/63] lr: 7.8182e-04 eta: 4:06:42 time: 0.6105 data_time: 0.0440 memory: 14901 loss: 0.9935 loss_prob: 0.5239 loss_thr: 0.3789 loss_db: 0.0906 2022/11/02 21:18:15 - mmengine - INFO - Epoch(train) [813][35/63] lr: 7.8182e-04 eta: 4:06:42 time: 0.5666 data_time: 0.0279 memory: 14901 loss: 1.0357 loss_prob: 0.5471 loss_thr: 0.3941 loss_db: 0.0945 2022/11/02 21:18:18 - mmengine - INFO - Epoch(train) [813][40/63] lr: 7.8182e-04 eta: 4:06:36 time: 0.5327 data_time: 0.0128 memory: 14901 loss: 1.0543 loss_prob: 0.5570 loss_thr: 0.4003 loss_db: 0.0970 2022/11/02 21:18:21 - mmengine - INFO - Epoch(train) [813][45/63] lr: 7.8182e-04 eta: 4:06:36 time: 0.5470 data_time: 0.0141 memory: 14901 loss: 1.0510 loss_prob: 0.5519 loss_thr: 0.4042 loss_db: 0.0948 2022/11/02 21:18:23 - mmengine - INFO - Epoch(train) [813][50/63] lr: 7.8182e-04 eta: 4:06:30 time: 0.5222 data_time: 0.0249 memory: 14901 loss: 1.0129 loss_prob: 0.5146 loss_thr: 0.4096 loss_db: 0.0887 2022/11/02 21:18:26 - mmengine - INFO - Epoch(train) [813][55/63] lr: 7.8182e-04 eta: 4:06:30 time: 0.5679 data_time: 0.0332 memory: 14901 loss: 0.9616 loss_prob: 0.4805 loss_thr: 0.3984 loss_db: 0.0827 2022/11/02 21:18:29 - mmengine - INFO - Epoch(train) [813][60/63] lr: 7.8182e-04 eta: 4:06:23 time: 0.5844 data_time: 0.0198 memory: 14901 loss: 1.0573 loss_prob: 0.5503 loss_thr: 0.4112 loss_db: 0.0958 2022/11/02 21:18:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:18:35 - mmengine - INFO - Epoch(train) [814][5/63] lr: 7.8000e-04 eta: 4:06:23 time: 0.7212 data_time: 0.2405 memory: 14901 loss: 1.0023 loss_prob: 0.5253 loss_thr: 0.3856 loss_db: 0.0914 2022/11/02 21:18:38 - mmengine - INFO - Epoch(train) [814][10/63] lr: 7.8000e-04 eta: 4:06:15 time: 0.7430 data_time: 0.2474 memory: 14901 loss: 1.0145 loss_prob: 0.5290 loss_thr: 0.3937 loss_db: 0.0917 2022/11/02 21:18:40 - mmengine - INFO - Epoch(train) [814][15/63] lr: 7.8000e-04 eta: 4:06:15 time: 0.5156 data_time: 0.0184 memory: 14901 loss: 1.0031 loss_prob: 0.5226 loss_thr: 0.3896 loss_db: 0.0908 2022/11/02 21:18:43 - mmengine - INFO - Epoch(train) [814][20/63] lr: 7.8000e-04 eta: 4:06:09 time: 0.5182 data_time: 0.0102 memory: 14901 loss: 1.0021 loss_prob: 0.5271 loss_thr: 0.3831 loss_db: 0.0919 2022/11/02 21:18:46 - mmengine - INFO - Epoch(train) [814][25/63] lr: 7.8000e-04 eta: 4:06:09 time: 0.5346 data_time: 0.0247 memory: 14901 loss: 0.9934 loss_prob: 0.5217 loss_thr: 0.3799 loss_db: 0.0918 2022/11/02 21:18:48 - mmengine - INFO - Epoch(train) [814][30/63] lr: 7.8000e-04 eta: 4:06:02 time: 0.5436 data_time: 0.0367 memory: 14901 loss: 1.0431 loss_prob: 0.5517 loss_thr: 0.3976 loss_db: 0.0937 2022/11/02 21:18:51 - mmengine - INFO - Epoch(train) [814][35/63] lr: 7.8000e-04 eta: 4:06:02 time: 0.5284 data_time: 0.0302 memory: 14901 loss: 1.0169 loss_prob: 0.5268 loss_thr: 0.3993 loss_db: 0.0909 2022/11/02 21:18:54 - mmengine - INFO - Epoch(train) [814][40/63] lr: 7.8000e-04 eta: 4:05:56 time: 0.5340 data_time: 0.0192 memory: 14901 loss: 0.9947 loss_prob: 0.5139 loss_thr: 0.3893 loss_db: 0.0915 2022/11/02 21:18:56 - mmengine - INFO - Epoch(train) [814][45/63] lr: 7.8000e-04 eta: 4:05:56 time: 0.5081 data_time: 0.0118 memory: 14901 loss: 0.9904 loss_prob: 0.5215 loss_thr: 0.3770 loss_db: 0.0918 2022/11/02 21:18:58 - mmengine - INFO - Epoch(train) [814][50/63] lr: 7.8000e-04 eta: 4:05:49 time: 0.4770 data_time: 0.0227 memory: 14901 loss: 1.0112 loss_prob: 0.5384 loss_thr: 0.3801 loss_db: 0.0926 2022/11/02 21:19:01 - mmengine - INFO - Epoch(train) [814][55/63] lr: 7.8000e-04 eta: 4:05:49 time: 0.4867 data_time: 0.0237 memory: 14901 loss: 1.1000 loss_prob: 0.5888 loss_thr: 0.4133 loss_db: 0.0979 2022/11/02 21:19:04 - mmengine - INFO - Epoch(train) [814][60/63] lr: 7.8000e-04 eta: 4:05:43 time: 0.5134 data_time: 0.0151 memory: 14901 loss: 1.0709 loss_prob: 0.5671 loss_thr: 0.4067 loss_db: 0.0972 2022/11/02 21:19:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:19:09 - mmengine - INFO - Epoch(train) [815][5/63] lr: 7.7818e-04 eta: 4:05:43 time: 0.6719 data_time: 0.1920 memory: 14901 loss: 1.1293 loss_prob: 0.6090 loss_thr: 0.4165 loss_db: 0.1037 2022/11/02 21:19:12 - mmengine - INFO - Epoch(train) [815][10/63] lr: 7.7818e-04 eta: 4:05:35 time: 0.6901 data_time: 0.1966 memory: 14901 loss: 1.1317 loss_prob: 0.6112 loss_thr: 0.4170 loss_db: 0.1035 2022/11/02 21:19:14 - mmengine - INFO - Epoch(train) [815][15/63] lr: 7.7818e-04 eta: 4:05:35 time: 0.5111 data_time: 0.0117 memory: 14901 loss: 1.0018 loss_prob: 0.5203 loss_thr: 0.3921 loss_db: 0.0895 2022/11/02 21:19:17 - mmengine - INFO - Epoch(train) [815][20/63] lr: 7.7818e-04 eta: 4:05:28 time: 0.4972 data_time: 0.0101 memory: 14901 loss: 1.0013 loss_prob: 0.5182 loss_thr: 0.3931 loss_db: 0.0901 2022/11/02 21:19:19 - mmengine - INFO - Epoch(train) [815][25/63] lr: 7.7818e-04 eta: 4:05:28 time: 0.4893 data_time: 0.0169 memory: 14901 loss: 1.0334 loss_prob: 0.5405 loss_thr: 0.3968 loss_db: 0.0961 2022/11/02 21:19:22 - mmengine - INFO - Epoch(train) [815][30/63] lr: 7.7818e-04 eta: 4:05:22 time: 0.5356 data_time: 0.0330 memory: 14901 loss: 1.0315 loss_prob: 0.5385 loss_thr: 0.3978 loss_db: 0.0951 2022/11/02 21:19:25 - mmengine - INFO - Epoch(train) [815][35/63] lr: 7.7818e-04 eta: 4:05:22 time: 0.5394 data_time: 0.0306 memory: 14901 loss: 1.0858 loss_prob: 0.5652 loss_thr: 0.4261 loss_db: 0.0945 2022/11/02 21:19:27 - mmengine - INFO - Epoch(train) [815][40/63] lr: 7.7818e-04 eta: 4:05:15 time: 0.5071 data_time: 0.0130 memory: 14901 loss: 1.0832 loss_prob: 0.5689 loss_thr: 0.4195 loss_db: 0.0949 2022/11/02 21:19:29 - mmengine - INFO - Epoch(train) [815][45/63] lr: 7.7818e-04 eta: 4:05:15 time: 0.4898 data_time: 0.0122 memory: 14901 loss: 1.0753 loss_prob: 0.5669 loss_thr: 0.4112 loss_db: 0.0973 2022/11/02 21:19:33 - mmengine - INFO - Epoch(train) [815][50/63] lr: 7.7818e-04 eta: 4:05:09 time: 0.6030 data_time: 0.0207 memory: 14901 loss: 1.0859 loss_prob: 0.5659 loss_thr: 0.4244 loss_db: 0.0956 2022/11/02 21:19:36 - mmengine - INFO - Epoch(train) [815][55/63] lr: 7.7818e-04 eta: 4:05:09 time: 0.6328 data_time: 0.0323 memory: 14901 loss: 1.0492 loss_prob: 0.5417 loss_thr: 0.4148 loss_db: 0.0927 2022/11/02 21:19:39 - mmengine - INFO - Epoch(train) [815][60/63] lr: 7.7818e-04 eta: 4:05:03 time: 0.5465 data_time: 0.0250 memory: 14901 loss: 1.0619 loss_prob: 0.5501 loss_thr: 0.4162 loss_db: 0.0957 2022/11/02 21:19:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:19:45 - mmengine - INFO - Epoch(train) [816][5/63] lr: 7.7636e-04 eta: 4:05:03 time: 0.6933 data_time: 0.2251 memory: 14901 loss: 1.0455 loss_prob: 0.5420 loss_thr: 0.4085 loss_db: 0.0949 2022/11/02 21:19:47 - mmengine - INFO - Epoch(train) [816][10/63] lr: 7.7636e-04 eta: 4:04:54 time: 0.7151 data_time: 0.2261 memory: 14901 loss: 0.9605 loss_prob: 0.4945 loss_thr: 0.3791 loss_db: 0.0869 2022/11/02 21:19:50 - mmengine - INFO - Epoch(train) [816][15/63] lr: 7.7636e-04 eta: 4:04:54 time: 0.5177 data_time: 0.0124 memory: 14901 loss: 0.9937 loss_prob: 0.5125 loss_thr: 0.3921 loss_db: 0.0891 2022/11/02 21:19:53 - mmengine - INFO - Epoch(train) [816][20/63] lr: 7.7636e-04 eta: 4:04:48 time: 0.5460 data_time: 0.0138 memory: 14901 loss: 1.0207 loss_prob: 0.5334 loss_thr: 0.3934 loss_db: 0.0939 2022/11/02 21:19:55 - mmengine - INFO - Epoch(train) [816][25/63] lr: 7.7636e-04 eta: 4:04:48 time: 0.5425 data_time: 0.0288 memory: 14901 loss: 0.9411 loss_prob: 0.4824 loss_thr: 0.3719 loss_db: 0.0868 2022/11/02 21:19:58 - mmengine - INFO - Epoch(train) [816][30/63] lr: 7.7636e-04 eta: 4:04:42 time: 0.5020 data_time: 0.0387 memory: 14901 loss: 0.9493 loss_prob: 0.4982 loss_thr: 0.3656 loss_db: 0.0854 2022/11/02 21:20:00 - mmengine - INFO - Epoch(train) [816][35/63] lr: 7.7636e-04 eta: 4:04:42 time: 0.4951 data_time: 0.0212 memory: 14901 loss: 1.0569 loss_prob: 0.5623 loss_thr: 0.4014 loss_db: 0.0933 2022/11/02 21:20:03 - mmengine - INFO - Epoch(train) [816][40/63] lr: 7.7636e-04 eta: 4:04:35 time: 0.5053 data_time: 0.0120 memory: 14901 loss: 1.0582 loss_prob: 0.5594 loss_thr: 0.4044 loss_db: 0.0944 2022/11/02 21:20:05 - mmengine - INFO - Epoch(train) [816][45/63] lr: 7.7636e-04 eta: 4:04:35 time: 0.4951 data_time: 0.0095 memory: 14901 loss: 1.0478 loss_prob: 0.5600 loss_thr: 0.3941 loss_db: 0.0937 2022/11/02 21:20:08 - mmengine - INFO - Epoch(train) [816][50/63] lr: 7.7636e-04 eta: 4:04:28 time: 0.5023 data_time: 0.0212 memory: 14901 loss: 1.1121 loss_prob: 0.5932 loss_thr: 0.4196 loss_db: 0.0993 2022/11/02 21:20:10 - mmengine - INFO - Epoch(train) [816][55/63] lr: 7.7636e-04 eta: 4:04:28 time: 0.4895 data_time: 0.0285 memory: 14901 loss: 1.0626 loss_prob: 0.5668 loss_thr: 0.4009 loss_db: 0.0949 2022/11/02 21:20:13 - mmengine - INFO - Epoch(train) [816][60/63] lr: 7.7636e-04 eta: 4:04:22 time: 0.5060 data_time: 0.0161 memory: 14901 loss: 1.0424 loss_prob: 0.5509 loss_thr: 0.3991 loss_db: 0.0923 2022/11/02 21:20:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:20:20 - mmengine - INFO - Epoch(train) [817][5/63] lr: 7.7454e-04 eta: 4:04:22 time: 0.8545 data_time: 0.2435 memory: 14901 loss: 1.0401 loss_prob: 0.5463 loss_thr: 0.3992 loss_db: 0.0946 2022/11/02 21:20:23 - mmengine - INFO - Epoch(train) [817][10/63] lr: 7.7454e-04 eta: 4:04:15 time: 0.9218 data_time: 0.2431 memory: 14901 loss: 1.0579 loss_prob: 0.5614 loss_thr: 0.4010 loss_db: 0.0955 2022/11/02 21:20:26 - mmengine - INFO - Epoch(train) [817][15/63] lr: 7.7454e-04 eta: 4:04:15 time: 0.6124 data_time: 0.0120 memory: 14901 loss: 1.0773 loss_prob: 0.5605 loss_thr: 0.4194 loss_db: 0.0974 2022/11/02 21:20:29 - mmengine - INFO - Epoch(train) [817][20/63] lr: 7.7454e-04 eta: 4:04:08 time: 0.5802 data_time: 0.0120 memory: 14901 loss: 1.0643 loss_prob: 0.5534 loss_thr: 0.4133 loss_db: 0.0975 2022/11/02 21:20:32 - mmengine - INFO - Epoch(train) [817][25/63] lr: 7.7454e-04 eta: 4:04:08 time: 0.5388 data_time: 0.0178 memory: 14901 loss: 1.1718 loss_prob: 0.6345 loss_thr: 0.4306 loss_db: 0.1067 2022/11/02 21:20:35 - mmengine - INFO - Epoch(train) [817][30/63] lr: 7.7454e-04 eta: 4:04:02 time: 0.5412 data_time: 0.0413 memory: 14901 loss: 1.1486 loss_prob: 0.6183 loss_thr: 0.4258 loss_db: 0.1044 2022/11/02 21:20:37 - mmengine - INFO - Epoch(train) [817][35/63] lr: 7.7454e-04 eta: 4:04:02 time: 0.5167 data_time: 0.0347 memory: 14901 loss: 0.9737 loss_prob: 0.5069 loss_thr: 0.3774 loss_db: 0.0893 2022/11/02 21:20:40 - mmengine - INFO - Epoch(train) [817][40/63] lr: 7.7454e-04 eta: 4:03:56 time: 0.5836 data_time: 0.0119 memory: 14901 loss: 1.0686 loss_prob: 0.5718 loss_thr: 0.3996 loss_db: 0.0971 2022/11/02 21:20:43 - mmengine - INFO - Epoch(train) [817][45/63] lr: 7.7454e-04 eta: 4:03:56 time: 0.6203 data_time: 0.0120 memory: 14901 loss: 1.0954 loss_prob: 0.5846 loss_thr: 0.4110 loss_db: 0.0997 2022/11/02 21:20:46 - mmengine - INFO - Epoch(train) [817][50/63] lr: 7.7454e-04 eta: 4:03:50 time: 0.5921 data_time: 0.0178 memory: 14901 loss: 0.9731 loss_prob: 0.5088 loss_thr: 0.3749 loss_db: 0.0894 2022/11/02 21:20:49 - mmengine - INFO - Epoch(train) [817][55/63] lr: 7.7454e-04 eta: 4:03:50 time: 0.5677 data_time: 0.0274 memory: 14901 loss: 0.9677 loss_prob: 0.5033 loss_thr: 0.3772 loss_db: 0.0872 2022/11/02 21:20:51 - mmengine - INFO - Epoch(train) [817][60/63] lr: 7.7454e-04 eta: 4:03:43 time: 0.5168 data_time: 0.0214 memory: 14901 loss: 0.9639 loss_prob: 0.5015 loss_thr: 0.3747 loss_db: 0.0876 2022/11/02 21:20:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:20:59 - mmengine - INFO - Epoch(train) [818][5/63] lr: 7.7272e-04 eta: 4:03:43 time: 0.8885 data_time: 0.2895 memory: 14901 loss: 0.9893 loss_prob: 0.5229 loss_thr: 0.3777 loss_db: 0.0888 2022/11/02 21:21:02 - mmengine - INFO - Epoch(train) [818][10/63] lr: 7.7272e-04 eta: 4:03:36 time: 0.9355 data_time: 0.2917 memory: 14901 loss: 1.0794 loss_prob: 0.5762 loss_thr: 0.4043 loss_db: 0.0989 2022/11/02 21:21:05 - mmengine - INFO - Epoch(train) [818][15/63] lr: 7.7272e-04 eta: 4:03:36 time: 0.5257 data_time: 0.0134 memory: 14901 loss: 1.1256 loss_prob: 0.5975 loss_thr: 0.4254 loss_db: 0.1027 2022/11/02 21:21:07 - mmengine - INFO - Epoch(train) [818][20/63] lr: 7.7272e-04 eta: 4:03:30 time: 0.5085 data_time: 0.0104 memory: 14901 loss: 1.0354 loss_prob: 0.5345 loss_thr: 0.4086 loss_db: 0.0923 2022/11/02 21:21:10 - mmengine - INFO - Epoch(train) [818][25/63] lr: 7.7272e-04 eta: 4:03:30 time: 0.5324 data_time: 0.0183 memory: 14901 loss: 1.0339 loss_prob: 0.5334 loss_thr: 0.4075 loss_db: 0.0930 2022/11/02 21:21:12 - mmengine - INFO - Epoch(train) [818][30/63] lr: 7.7272e-04 eta: 4:03:23 time: 0.5338 data_time: 0.0375 memory: 14901 loss: 1.0682 loss_prob: 0.5619 loss_thr: 0.4095 loss_db: 0.0968 2022/11/02 21:21:15 - mmengine - INFO - Epoch(train) [818][35/63] lr: 7.7272e-04 eta: 4:03:23 time: 0.5269 data_time: 0.0377 memory: 14901 loss: 1.0155 loss_prob: 0.5313 loss_thr: 0.3928 loss_db: 0.0913 2022/11/02 21:21:18 - mmengine - INFO - Epoch(train) [818][40/63] lr: 7.7272e-04 eta: 4:03:17 time: 0.5232 data_time: 0.0180 memory: 14901 loss: 0.9941 loss_prob: 0.5152 loss_thr: 0.3875 loss_db: 0.0914 2022/11/02 21:21:20 - mmengine - INFO - Epoch(train) [818][45/63] lr: 7.7272e-04 eta: 4:03:17 time: 0.4978 data_time: 0.0103 memory: 14901 loss: 1.0630 loss_prob: 0.5547 loss_thr: 0.4100 loss_db: 0.0983 2022/11/02 21:21:23 - mmengine - INFO - Epoch(train) [818][50/63] lr: 7.7272e-04 eta: 4:03:10 time: 0.5256 data_time: 0.0201 memory: 14901 loss: 1.0207 loss_prob: 0.5324 loss_thr: 0.3958 loss_db: 0.0926 2022/11/02 21:21:25 - mmengine - INFO - Epoch(train) [818][55/63] lr: 7.7272e-04 eta: 4:03:10 time: 0.5358 data_time: 0.0268 memory: 14901 loss: 0.9441 loss_prob: 0.4914 loss_thr: 0.3673 loss_db: 0.0854 2022/11/02 21:21:28 - mmengine - INFO - Epoch(train) [818][60/63] lr: 7.7272e-04 eta: 4:03:04 time: 0.4814 data_time: 0.0192 memory: 14901 loss: 0.9847 loss_prob: 0.5198 loss_thr: 0.3747 loss_db: 0.0901 2022/11/02 21:21:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:21:34 - mmengine - INFO - Epoch(train) [819][5/63] lr: 7.7090e-04 eta: 4:03:04 time: 0.7473 data_time: 0.2105 memory: 14901 loss: 1.0086 loss_prob: 0.5230 loss_thr: 0.3938 loss_db: 0.0917 2022/11/02 21:21:37 - mmengine - INFO - Epoch(train) [819][10/63] lr: 7.7090e-04 eta: 4:02:56 time: 0.8434 data_time: 0.2267 memory: 14901 loss: 1.0381 loss_prob: 0.5464 loss_thr: 0.3988 loss_db: 0.0928 2022/11/02 21:21:40 - mmengine - INFO - Epoch(train) [819][15/63] lr: 7.7090e-04 eta: 4:02:56 time: 0.6110 data_time: 0.0234 memory: 14901 loss: 1.0869 loss_prob: 0.5826 loss_thr: 0.4057 loss_db: 0.0986 2022/11/02 21:21:43 - mmengine - INFO - Epoch(train) [819][20/63] lr: 7.7090e-04 eta: 4:02:50 time: 0.5385 data_time: 0.0113 memory: 14901 loss: 1.1928 loss_prob: 0.6498 loss_thr: 0.4320 loss_db: 0.1110 2022/11/02 21:21:46 - mmengine - INFO - Epoch(train) [819][25/63] lr: 7.7090e-04 eta: 4:02:50 time: 0.5463 data_time: 0.0204 memory: 14901 loss: 1.1374 loss_prob: 0.6039 loss_thr: 0.4312 loss_db: 0.1023 2022/11/02 21:21:49 - mmengine - INFO - Epoch(train) [819][30/63] lr: 7.7090e-04 eta: 4:02:44 time: 0.5805 data_time: 0.0305 memory: 14901 loss: 1.0354 loss_prob: 0.5438 loss_thr: 0.3995 loss_db: 0.0921 2022/11/02 21:21:51 - mmengine - INFO - Epoch(train) [819][35/63] lr: 7.7090e-04 eta: 4:02:44 time: 0.5610 data_time: 0.0316 memory: 14901 loss: 1.0209 loss_prob: 0.5359 loss_thr: 0.3943 loss_db: 0.0907 2022/11/02 21:21:54 - mmengine - INFO - Epoch(train) [819][40/63] lr: 7.7090e-04 eta: 4:02:37 time: 0.5437 data_time: 0.0216 memory: 14901 loss: 1.0308 loss_prob: 0.5301 loss_thr: 0.4093 loss_db: 0.0914 2022/11/02 21:21:57 - mmengine - INFO - Epoch(train) [819][45/63] lr: 7.7090e-04 eta: 4:02:37 time: 0.5292 data_time: 0.0127 memory: 14901 loss: 1.1056 loss_prob: 0.5794 loss_thr: 0.4268 loss_db: 0.0994 2022/11/02 21:21:59 - mmengine - INFO - Epoch(train) [819][50/63] lr: 7.7090e-04 eta: 4:02:31 time: 0.5186 data_time: 0.0255 memory: 14901 loss: 1.2105 loss_prob: 0.6818 loss_thr: 0.4245 loss_db: 0.1042 2022/11/02 21:22:02 - mmengine - INFO - Epoch(train) [819][55/63] lr: 7.7090e-04 eta: 4:02:31 time: 0.4925 data_time: 0.0251 memory: 14901 loss: 1.1470 loss_prob: 0.6380 loss_thr: 0.4101 loss_db: 0.0989 2022/11/02 21:22:04 - mmengine - INFO - Epoch(train) [819][60/63] lr: 7.7090e-04 eta: 4:02:24 time: 0.4705 data_time: 0.0155 memory: 14901 loss: 1.0053 loss_prob: 0.5199 loss_thr: 0.3970 loss_db: 0.0885 2022/11/02 21:22:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:22:11 - mmengine - INFO - Epoch(train) [820][5/63] lr: 7.6908e-04 eta: 4:02:24 time: 0.7629 data_time: 0.2525 memory: 14901 loss: 1.0732 loss_prob: 0.5615 loss_thr: 0.4161 loss_db: 0.0956 2022/11/02 21:22:14 - mmengine - INFO - Epoch(train) [820][10/63] lr: 7.6908e-04 eta: 4:02:16 time: 0.8384 data_time: 0.2529 memory: 14901 loss: 1.0734 loss_prob: 0.5637 loss_thr: 0.4128 loss_db: 0.0969 2022/11/02 21:22:16 - mmengine - INFO - Epoch(train) [820][15/63] lr: 7.6908e-04 eta: 4:02:16 time: 0.5469 data_time: 0.0131 memory: 14901 loss: 1.0519 loss_prob: 0.5584 loss_thr: 0.3982 loss_db: 0.0952 2022/11/02 21:22:19 - mmengine - INFO - Epoch(train) [820][20/63] lr: 7.6908e-04 eta: 4:02:10 time: 0.5580 data_time: 0.0108 memory: 14901 loss: 1.0877 loss_prob: 0.5892 loss_thr: 0.3940 loss_db: 0.1046 2022/11/02 21:22:22 - mmengine - INFO - Epoch(train) [820][25/63] lr: 7.6908e-04 eta: 4:02:10 time: 0.5528 data_time: 0.0133 memory: 14901 loss: 1.1544 loss_prob: 0.6240 loss_thr: 0.4204 loss_db: 0.1099 2022/11/02 21:22:24 - mmengine - INFO - Epoch(train) [820][30/63] lr: 7.6908e-04 eta: 4:02:04 time: 0.5269 data_time: 0.0424 memory: 14901 loss: 1.0805 loss_prob: 0.5653 loss_thr: 0.4201 loss_db: 0.0951 2022/11/02 21:22:27 - mmengine - INFO - Epoch(train) [820][35/63] lr: 7.6908e-04 eta: 4:02:04 time: 0.5462 data_time: 0.0380 memory: 14901 loss: 0.9988 loss_prob: 0.5122 loss_thr: 0.3996 loss_db: 0.0870 2022/11/02 21:22:30 - mmengine - INFO - Epoch(train) [820][40/63] lr: 7.6908e-04 eta: 4:01:57 time: 0.5129 data_time: 0.0114 memory: 14901 loss: 0.9911 loss_prob: 0.5150 loss_thr: 0.3865 loss_db: 0.0896 2022/11/02 21:22:32 - mmengine - INFO - Epoch(train) [820][45/63] lr: 7.6908e-04 eta: 4:01:57 time: 0.5084 data_time: 0.0104 memory: 14901 loss: 0.9624 loss_prob: 0.4971 loss_thr: 0.3767 loss_db: 0.0886 2022/11/02 21:22:35 - mmengine - INFO - Epoch(train) [820][50/63] lr: 7.6908e-04 eta: 4:01:51 time: 0.5193 data_time: 0.0283 memory: 14901 loss: 1.0125 loss_prob: 0.5271 loss_thr: 0.3926 loss_db: 0.0927 2022/11/02 21:22:37 - mmengine - INFO - Epoch(train) [820][55/63] lr: 7.6908e-04 eta: 4:01:51 time: 0.4924 data_time: 0.0295 memory: 14901 loss: 0.9787 loss_prob: 0.5163 loss_thr: 0.3754 loss_db: 0.0870 2022/11/02 21:22:40 - mmengine - INFO - Epoch(train) [820][60/63] lr: 7.6908e-04 eta: 4:01:44 time: 0.5280 data_time: 0.0085 memory: 14901 loss: 0.9808 loss_prob: 0.5128 loss_thr: 0.3810 loss_db: 0.0870 2022/11/02 21:22:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:22:41 - mmengine - INFO - Saving checkpoint at 820 epochs 2022/11/02 21:22:45 - mmengine - INFO - Epoch(val) [820][5/500] eta: 4:01:44 time: 0.0457 data_time: 0.0062 memory: 14901 2022/11/02 21:22:45 - mmengine - INFO - Epoch(val) [820][10/500] eta: 0:00:21 time: 0.0439 data_time: 0.0054 memory: 1008 2022/11/02 21:22:46 - mmengine - INFO - Epoch(val) [820][15/500] eta: 0:00:21 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 21:22:46 - mmengine - INFO - Epoch(val) [820][20/500] eta: 0:00:17 time: 0.0369 data_time: 0.0026 memory: 1008 2022/11/02 21:22:46 - mmengine - INFO - Epoch(val) [820][25/500] eta: 0:00:17 time: 0.0351 data_time: 0.0025 memory: 1008 2022/11/02 21:22:46 - mmengine - INFO - Epoch(val) [820][30/500] eta: 0:00:18 time: 0.0393 data_time: 0.0026 memory: 1008 2022/11/02 21:22:46 - mmengine - INFO - Epoch(val) [820][35/500] eta: 0:00:18 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/02 21:22:47 - mmengine - INFO - Epoch(val) [820][40/500] eta: 0:00:18 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/02 21:22:47 - mmengine - INFO - Epoch(val) [820][45/500] eta: 0:00:18 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/02 21:22:47 - mmengine - INFO - Epoch(val) [820][50/500] eta: 0:00:18 time: 0.0417 data_time: 0.0026 memory: 1008 2022/11/02 21:22:47 - mmengine - INFO - Epoch(val) [820][55/500] eta: 0:00:18 time: 0.0409 data_time: 0.0024 memory: 1008 2022/11/02 21:22:47 - mmengine - INFO - Epoch(val) [820][60/500] eta: 0:00:18 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 21:22:48 - mmengine - INFO - Epoch(val) [820][65/500] eta: 0:00:18 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 21:22:48 - mmengine - INFO - Epoch(val) [820][70/500] eta: 0:00:18 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 21:22:48 - mmengine - INFO - Epoch(val) [820][75/500] eta: 0:00:18 time: 0.0373 data_time: 0.0024 memory: 1008 2022/11/02 21:22:48 - mmengine - INFO - Epoch(val) [820][80/500] eta: 0:00:13 time: 0.0331 data_time: 0.0022 memory: 1008 2022/11/02 21:22:48 - mmengine - INFO - Epoch(val) [820][85/500] eta: 0:00:13 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/02 21:22:49 - mmengine - INFO - Epoch(val) [820][90/500] eta: 0:00:16 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 21:22:49 - mmengine - INFO - Epoch(val) [820][95/500] eta: 0:00:16 time: 0.0398 data_time: 0.0021 memory: 1008 2022/11/02 21:22:49 - mmengine - INFO - Epoch(val) [820][100/500] eta: 0:00:15 time: 0.0400 data_time: 0.0023 memory: 1008 2022/11/02 21:22:49 - mmengine - INFO - Epoch(val) [820][105/500] eta: 0:00:15 time: 0.0386 data_time: 0.0026 memory: 1008 2022/11/02 21:22:49 - mmengine - INFO - Epoch(val) [820][110/500] eta: 0:00:13 time: 0.0356 data_time: 0.0023 memory: 1008 2022/11/02 21:22:50 - mmengine - INFO - Epoch(val) [820][115/500] eta: 0:00:13 time: 0.0377 data_time: 0.0023 memory: 1008 2022/11/02 21:22:50 - mmengine - INFO - Epoch(val) [820][120/500] eta: 0:00:14 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 21:22:50 - mmengine - INFO - Epoch(val) [820][125/500] eta: 0:00:14 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/02 21:22:50 - mmengine - INFO - Epoch(val) [820][130/500] eta: 0:00:13 time: 0.0371 data_time: 0.0025 memory: 1008 2022/11/02 21:22:50 - mmengine - INFO - Epoch(val) [820][135/500] eta: 0:00:13 time: 0.0370 data_time: 0.0025 memory: 1008 2022/11/02 21:22:51 - mmengine - INFO - Epoch(val) [820][140/500] eta: 0:00:13 time: 0.0370 data_time: 0.0025 memory: 1008 2022/11/02 21:22:51 - mmengine - INFO - Epoch(val) [820][145/500] eta: 0:00:13 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 21:22:51 - mmengine - INFO - Epoch(val) [820][150/500] eta: 0:00:15 time: 0.0433 data_time: 0.0026 memory: 1008 2022/11/02 21:22:51 - mmengine - INFO - Epoch(val) [820][155/500] eta: 0:00:15 time: 0.0448 data_time: 0.0027 memory: 1008 2022/11/02 21:22:51 - mmengine - INFO - Epoch(val) [820][160/500] eta: 0:00:14 time: 0.0426 data_time: 0.0025 memory: 1008 2022/11/02 21:22:52 - mmengine - INFO - Epoch(val) [820][165/500] eta: 0:00:14 time: 0.0383 data_time: 0.0023 memory: 1008 2022/11/02 21:22:52 - mmengine - INFO - Epoch(val) [820][170/500] eta: 0:00:12 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/02 21:22:52 - mmengine - INFO - Epoch(val) [820][175/500] eta: 0:00:12 time: 0.0369 data_time: 0.0023 memory: 1008 2022/11/02 21:22:52 - mmengine - INFO - Epoch(val) [820][180/500] eta: 0:00:11 time: 0.0363 data_time: 0.0020 memory: 1008 2022/11/02 21:22:52 - mmengine - INFO - Epoch(val) [820][185/500] eta: 0:00:11 time: 0.0403 data_time: 0.0024 memory: 1008 2022/11/02 21:22:53 - mmengine - INFO - Epoch(val) [820][190/500] eta: 0:00:12 time: 0.0415 data_time: 0.0026 memory: 1008 2022/11/02 21:22:53 - mmengine - INFO - Epoch(val) [820][195/500] eta: 0:00:12 time: 0.0402 data_time: 0.0027 memory: 1008 2022/11/02 21:22:53 - mmengine - INFO - Epoch(val) [820][200/500] eta: 0:00:13 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 21:22:53 - mmengine - INFO - Epoch(val) [820][205/500] eta: 0:00:13 time: 0.0434 data_time: 0.0025 memory: 1008 2022/11/02 21:22:53 - mmengine - INFO - Epoch(val) [820][210/500] eta: 0:00:10 time: 0.0367 data_time: 0.0025 memory: 1008 2022/11/02 21:22:54 - mmengine - INFO - Epoch(val) [820][215/500] eta: 0:00:10 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 21:22:54 - mmengine - INFO - Epoch(val) [820][220/500] eta: 0:00:11 time: 0.0406 data_time: 0.0024 memory: 1008 2022/11/02 21:22:54 - mmengine - INFO - Epoch(val) [820][225/500] eta: 0:00:11 time: 0.0409 data_time: 0.0027 memory: 1008 2022/11/02 21:22:54 - mmengine - INFO - Epoch(val) [820][230/500] eta: 0:00:10 time: 0.0385 data_time: 0.0028 memory: 1008 2022/11/02 21:22:54 - mmengine - INFO - Epoch(val) [820][235/500] eta: 0:00:10 time: 0.0427 data_time: 0.0033 memory: 1008 2022/11/02 21:22:55 - mmengine - INFO - Epoch(val) [820][240/500] eta: 0:00:11 time: 0.0439 data_time: 0.0035 memory: 1008 2022/11/02 21:22:55 - mmengine - INFO - Epoch(val) [820][245/500] eta: 0:00:11 time: 0.0375 data_time: 0.0029 memory: 1008 2022/11/02 21:22:55 - mmengine - INFO - Epoch(val) [820][250/500] eta: 0:00:09 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/02 21:22:55 - mmengine - INFO - Epoch(val) [820][255/500] eta: 0:00:09 time: 0.0368 data_time: 0.0022 memory: 1008 2022/11/02 21:22:55 - mmengine - INFO - Epoch(val) [820][260/500] eta: 0:00:09 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 21:22:56 - mmengine - INFO - Epoch(val) [820][265/500] eta: 0:00:09 time: 0.0453 data_time: 0.0039 memory: 1008 2022/11/02 21:22:56 - mmengine - INFO - Epoch(val) [820][270/500] eta: 0:00:10 time: 0.0453 data_time: 0.0043 memory: 1008 2022/11/02 21:22:56 - mmengine - INFO - Epoch(val) [820][275/500] eta: 0:00:10 time: 0.0461 data_time: 0.0036 memory: 1008 2022/11/02 21:22:56 - mmengine - INFO - Epoch(val) [820][280/500] eta: 0:00:10 time: 0.0468 data_time: 0.0030 memory: 1008 2022/11/02 21:22:56 - mmengine - INFO - Epoch(val) [820][285/500] eta: 0:00:10 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 21:22:57 - mmengine - INFO - Epoch(val) [820][290/500] eta: 0:00:07 time: 0.0375 data_time: 0.0024 memory: 1008 2022/11/02 21:22:57 - mmengine - INFO - Epoch(val) [820][295/500] eta: 0:00:07 time: 0.0437 data_time: 0.0029 memory: 1008 2022/11/02 21:22:57 - mmengine - INFO - Epoch(val) [820][300/500] eta: 0:00:08 time: 0.0448 data_time: 0.0033 memory: 1008 2022/11/02 21:22:57 - mmengine - INFO - Epoch(val) [820][305/500] eta: 0:00:08 time: 0.0410 data_time: 0.0031 memory: 1008 2022/11/02 21:22:58 - mmengine - INFO - Epoch(val) [820][310/500] eta: 0:00:07 time: 0.0400 data_time: 0.0030 memory: 1008 2022/11/02 21:22:58 - mmengine - INFO - Epoch(val) [820][315/500] eta: 0:00:07 time: 0.0411 data_time: 0.0028 memory: 1008 2022/11/02 21:22:58 - mmengine - INFO - Epoch(val) [820][320/500] eta: 0:00:07 time: 0.0392 data_time: 0.0027 memory: 1008 2022/11/02 21:22:58 - mmengine - INFO - Epoch(val) [820][325/500] eta: 0:00:07 time: 0.0530 data_time: 0.0027 memory: 1008 2022/11/02 21:22:58 - mmengine - INFO - Epoch(val) [820][330/500] eta: 0:00:09 time: 0.0538 data_time: 0.0043 memory: 1008 2022/11/02 21:22:59 - mmengine - INFO - Epoch(val) [820][335/500] eta: 0:00:09 time: 0.0372 data_time: 0.0043 memory: 1008 2022/11/02 21:22:59 - mmengine - INFO - Epoch(val) [820][340/500] eta: 0:00:08 time: 0.0508 data_time: 0.0028 memory: 1008 2022/11/02 21:22:59 - mmengine - INFO - Epoch(val) [820][345/500] eta: 0:00:08 time: 0.0526 data_time: 0.0027 memory: 1008 2022/11/02 21:22:59 - mmengine - INFO - Epoch(val) [820][350/500] eta: 0:00:06 time: 0.0411 data_time: 0.0024 memory: 1008 2022/11/02 21:23:00 - mmengine - INFO - Epoch(val) [820][355/500] eta: 0:00:06 time: 0.0386 data_time: 0.0022 memory: 1008 2022/11/02 21:23:00 - mmengine - INFO - Epoch(val) [820][360/500] eta: 0:00:05 time: 0.0378 data_time: 0.0024 memory: 1008 2022/11/02 21:23:00 - mmengine - INFO - Epoch(val) [820][365/500] eta: 0:00:05 time: 0.0397 data_time: 0.0024 memory: 1008 2022/11/02 21:23:00 - mmengine - INFO - Epoch(val) [820][370/500] eta: 0:00:04 time: 0.0370 data_time: 0.0024 memory: 1008 2022/11/02 21:23:00 - mmengine - INFO - Epoch(val) [820][375/500] eta: 0:00:04 time: 0.0351 data_time: 0.0027 memory: 1008 2022/11/02 21:23:01 - mmengine - INFO - Epoch(val) [820][380/500] eta: 0:00:04 time: 0.0375 data_time: 0.0026 memory: 1008 2022/11/02 21:23:01 - mmengine - INFO - Epoch(val) [820][385/500] eta: 0:00:04 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 21:23:01 - mmengine - INFO - Epoch(val) [820][390/500] eta: 0:00:04 time: 0.0376 data_time: 0.0025 memory: 1008 2022/11/02 21:23:01 - mmengine - INFO - Epoch(val) [820][395/500] eta: 0:00:04 time: 0.0354 data_time: 0.0022 memory: 1008 2022/11/02 21:23:01 - mmengine - INFO - Epoch(val) [820][400/500] eta: 0:00:03 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/02 21:23:01 - mmengine - INFO - Epoch(val) [820][405/500] eta: 0:00:03 time: 0.0394 data_time: 0.0026 memory: 1008 2022/11/02 21:23:02 - mmengine - INFO - Epoch(val) [820][410/500] eta: 0:00:03 time: 0.0410 data_time: 0.0024 memory: 1008 2022/11/02 21:23:02 - mmengine - INFO - Epoch(val) [820][415/500] eta: 0:00:03 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/02 21:23:02 - mmengine - INFO - Epoch(val) [820][420/500] eta: 0:00:02 time: 0.0338 data_time: 0.0022 memory: 1008 2022/11/02 21:23:02 - mmengine - INFO - Epoch(val) [820][425/500] eta: 0:00:02 time: 0.0344 data_time: 0.0021 memory: 1008 2022/11/02 21:23:02 - mmengine - INFO - Epoch(val) [820][430/500] eta: 0:00:02 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 21:23:03 - mmengine - INFO - Epoch(val) [820][435/500] eta: 0:00:02 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 21:23:03 - mmengine - INFO - Epoch(val) [820][440/500] eta: 0:00:02 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 21:23:03 - mmengine - INFO - Epoch(val) [820][445/500] eta: 0:00:02 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 21:23:03 - mmengine - INFO - Epoch(val) [820][450/500] eta: 0:00:02 time: 0.0424 data_time: 0.0031 memory: 1008 2022/11/02 21:23:03 - mmengine - INFO - Epoch(val) [820][455/500] eta: 0:00:02 time: 0.0378 data_time: 0.0025 memory: 1008 2022/11/02 21:23:04 - mmengine - INFO - Epoch(val) [820][460/500] eta: 0:00:01 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/02 21:23:04 - mmengine - INFO - Epoch(val) [820][465/500] eta: 0:00:01 time: 0.0333 data_time: 0.0024 memory: 1008 2022/11/02 21:23:04 - mmengine - INFO - Epoch(val) [820][470/500] eta: 0:00:01 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/02 21:23:04 - mmengine - INFO - Epoch(val) [820][475/500] eta: 0:00:01 time: 0.0378 data_time: 0.0024 memory: 1008 2022/11/02 21:23:04 - mmengine - INFO - Epoch(val) [820][480/500] eta: 0:00:00 time: 0.0362 data_time: 0.0025 memory: 1008 2022/11/02 21:23:05 - mmengine - INFO - Epoch(val) [820][485/500] eta: 0:00:00 time: 0.0417 data_time: 0.0029 memory: 1008 2022/11/02 21:23:05 - mmengine - INFO - Epoch(val) [820][490/500] eta: 0:00:00 time: 0.0424 data_time: 0.0031 memory: 1008 2022/11/02 21:23:05 - mmengine - INFO - Epoch(val) [820][495/500] eta: 0:00:00 time: 0.0402 data_time: 0.0026 memory: 1008 2022/11/02 21:23:05 - mmengine - INFO - Epoch(val) [820][500/500] eta: 0:00:00 time: 0.0364 data_time: 0.0023 memory: 1008 2022/11/02 21:23:05 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8296, precision: 0.7475, hmean: 0.7864 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8296, precision: 0.8007, hmean: 0.8148 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8296, precision: 0.8280, hmean: 0.8288 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8243, precision: 0.8526, hmean: 0.8382 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8137, precision: 0.8811, hmean: 0.8461 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6928, precision: 0.9266, hmean: 0.7928 2022/11/02 21:23:05 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1271, precision: 0.9600, hmean: 0.2245 2022/11/02 21:23:05 - mmengine - INFO - Epoch(val) [820][500/500] icdar/precision: 0.8811 icdar/recall: 0.8137 icdar/hmean: 0.8461 2022/11/02 21:23:10 - mmengine - INFO - Epoch(train) [821][5/63] lr: 7.6726e-04 eta: 0:00:00 time: 0.7279 data_time: 0.2340 memory: 14901 loss: 0.9723 loss_prob: 0.5002 loss_thr: 0.3831 loss_db: 0.0890 2022/11/02 21:23:12 - mmengine - INFO - Epoch(train) [821][10/63] lr: 7.6726e-04 eta: 4:01:36 time: 0.7067 data_time: 0.2309 memory: 14901 loss: 1.0998 loss_prob: 0.5826 loss_thr: 0.4172 loss_db: 0.0999 2022/11/02 21:23:15 - mmengine - INFO - Epoch(train) [821][15/63] lr: 7.6726e-04 eta: 4:01:36 time: 0.5096 data_time: 0.0093 memory: 14901 loss: 1.1107 loss_prob: 0.5881 loss_thr: 0.4242 loss_db: 0.0984 2022/11/02 21:23:17 - mmengine - INFO - Epoch(train) [821][20/63] lr: 7.6726e-04 eta: 4:01:30 time: 0.5221 data_time: 0.0114 memory: 14901 loss: 1.0244 loss_prob: 0.5360 loss_thr: 0.3980 loss_db: 0.0904 2022/11/02 21:23:20 - mmengine - INFO - Epoch(train) [821][25/63] lr: 7.6726e-04 eta: 4:01:30 time: 0.5482 data_time: 0.0448 memory: 14901 loss: 1.0676 loss_prob: 0.5646 loss_thr: 0.4058 loss_db: 0.0972 2022/11/02 21:23:23 - mmengine - INFO - Epoch(train) [821][30/63] lr: 7.6726e-04 eta: 4:01:23 time: 0.5228 data_time: 0.0438 memory: 14901 loss: 1.0668 loss_prob: 0.5620 loss_thr: 0.4076 loss_db: 0.0973 2022/11/02 21:23:26 - mmengine - INFO - Epoch(train) [821][35/63] lr: 7.6726e-04 eta: 4:01:23 time: 0.5376 data_time: 0.0092 memory: 14901 loss: 0.9913 loss_prob: 0.5144 loss_thr: 0.3891 loss_db: 0.0879 2022/11/02 21:23:29 - mmengine - INFO - Epoch(train) [821][40/63] lr: 7.6726e-04 eta: 4:01:17 time: 0.5836 data_time: 0.0100 memory: 14901 loss: 0.9234 loss_prob: 0.4775 loss_thr: 0.3639 loss_db: 0.0820 2022/11/02 21:23:31 - mmengine - INFO - Epoch(train) [821][45/63] lr: 7.6726e-04 eta: 4:01:17 time: 0.5513 data_time: 0.0110 memory: 14901 loss: 0.9658 loss_prob: 0.5050 loss_thr: 0.3733 loss_db: 0.0875 2022/11/02 21:23:34 - mmengine - INFO - Epoch(train) [821][50/63] lr: 7.6726e-04 eta: 4:01:11 time: 0.5348 data_time: 0.0304 memory: 14901 loss: 0.9632 loss_prob: 0.5022 loss_thr: 0.3729 loss_db: 0.0881 2022/11/02 21:23:37 - mmengine - INFO - Epoch(train) [821][55/63] lr: 7.6726e-04 eta: 4:01:11 time: 0.5688 data_time: 0.0298 memory: 14901 loss: 1.0064 loss_prob: 0.5170 loss_thr: 0.4000 loss_db: 0.0894 2022/11/02 21:23:40 - mmengine - INFO - Epoch(train) [821][60/63] lr: 7.6726e-04 eta: 4:01:05 time: 0.6351 data_time: 0.0079 memory: 14901 loss: 1.0503 loss_prob: 0.5350 loss_thr: 0.4219 loss_db: 0.0935 2022/11/02 21:23:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:23:48 - mmengine - INFO - Epoch(train) [822][5/63] lr: 7.6544e-04 eta: 4:01:05 time: 0.8767 data_time: 0.2292 memory: 14901 loss: 0.9595 loss_prob: 0.5014 loss_thr: 0.3707 loss_db: 0.0875 2022/11/02 21:23:51 - mmengine - INFO - Epoch(train) [822][10/63] lr: 7.6544e-04 eta: 4:00:58 time: 0.9499 data_time: 0.2306 memory: 14901 loss: 0.9553 loss_prob: 0.5122 loss_thr: 0.3576 loss_db: 0.0854 2022/11/02 21:23:54 - mmengine - INFO - Epoch(train) [822][15/63] lr: 7.6544e-04 eta: 4:00:58 time: 0.5689 data_time: 0.0129 memory: 14901 loss: 1.0862 loss_prob: 0.5911 loss_thr: 0.4004 loss_db: 0.0946 2022/11/02 21:23:56 - mmengine - INFO - Epoch(train) [822][20/63] lr: 7.6544e-04 eta: 4:00:51 time: 0.5280 data_time: 0.0091 memory: 14901 loss: 1.0745 loss_prob: 0.5699 loss_thr: 0.4093 loss_db: 0.0953 2022/11/02 21:23:59 - mmengine - INFO - Epoch(train) [822][25/63] lr: 7.6544e-04 eta: 4:00:51 time: 0.5141 data_time: 0.0150 memory: 14901 loss: 1.0323 loss_prob: 0.5377 loss_thr: 0.4002 loss_db: 0.0944 2022/11/02 21:24:02 - mmengine - INFO - Epoch(train) [822][30/63] lr: 7.6544e-04 eta: 4:00:45 time: 0.5518 data_time: 0.0563 memory: 14901 loss: 1.0922 loss_prob: 0.5936 loss_thr: 0.3979 loss_db: 0.1007 2022/11/02 21:24:05 - mmengine - INFO - Epoch(train) [822][35/63] lr: 7.6544e-04 eta: 4:00:45 time: 0.5945 data_time: 0.0519 memory: 14901 loss: 1.0670 loss_prob: 0.5807 loss_thr: 0.3895 loss_db: 0.0969 2022/11/02 21:24:08 - mmengine - INFO - Epoch(train) [822][40/63] lr: 7.6544e-04 eta: 4:00:39 time: 0.6119 data_time: 0.0096 memory: 14901 loss: 1.0347 loss_prob: 0.5470 loss_thr: 0.3932 loss_db: 0.0945 2022/11/02 21:24:11 - mmengine - INFO - Epoch(train) [822][45/63] lr: 7.6544e-04 eta: 4:00:39 time: 0.5909 data_time: 0.0081 memory: 14901 loss: 1.0435 loss_prob: 0.5500 loss_thr: 0.3972 loss_db: 0.0963 2022/11/02 21:24:13 - mmengine - INFO - Epoch(train) [822][50/63] lr: 7.6544e-04 eta: 4:00:33 time: 0.5441 data_time: 0.0238 memory: 14901 loss: 1.0121 loss_prob: 0.5237 loss_thr: 0.3979 loss_db: 0.0904 2022/11/02 21:24:16 - mmengine - INFO - Epoch(train) [822][55/63] lr: 7.6544e-04 eta: 4:00:33 time: 0.5554 data_time: 0.0276 memory: 14901 loss: 1.0187 loss_prob: 0.5260 loss_thr: 0.4002 loss_db: 0.0925 2022/11/02 21:24:19 - mmengine - INFO - Epoch(train) [822][60/63] lr: 7.6544e-04 eta: 4:00:26 time: 0.5712 data_time: 0.0149 memory: 14901 loss: 0.9799 loss_prob: 0.5056 loss_thr: 0.3839 loss_db: 0.0903 2022/11/02 21:24:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:24:25 - mmengine - INFO - Epoch(train) [823][5/63] lr: 7.6361e-04 eta: 4:00:26 time: 0.7081 data_time: 0.2243 memory: 14901 loss: 0.9034 loss_prob: 0.4699 loss_thr: 0.3529 loss_db: 0.0807 2022/11/02 21:24:28 - mmengine - INFO - Epoch(train) [823][10/63] lr: 7.6361e-04 eta: 4:00:18 time: 0.7148 data_time: 0.2240 memory: 14901 loss: 0.9547 loss_prob: 0.4955 loss_thr: 0.3729 loss_db: 0.0863 2022/11/02 21:24:30 - mmengine - INFO - Epoch(train) [823][15/63] lr: 7.6361e-04 eta: 4:00:18 time: 0.5484 data_time: 0.0162 memory: 14901 loss: 0.9944 loss_prob: 0.5113 loss_thr: 0.3924 loss_db: 0.0908 2022/11/02 21:24:33 - mmengine - INFO - Epoch(train) [823][20/63] lr: 7.6361e-04 eta: 4:00:12 time: 0.5275 data_time: 0.0158 memory: 14901 loss: 1.0380 loss_prob: 0.5402 loss_thr: 0.4029 loss_db: 0.0948 2022/11/02 21:24:35 - mmengine - INFO - Epoch(train) [823][25/63] lr: 7.6361e-04 eta: 4:00:12 time: 0.4999 data_time: 0.0198 memory: 14901 loss: 1.0523 loss_prob: 0.5571 loss_thr: 0.3982 loss_db: 0.0970 2022/11/02 21:24:38 - mmengine - INFO - Epoch(train) [823][30/63] lr: 7.6361e-04 eta: 4:00:05 time: 0.5256 data_time: 0.0428 memory: 14901 loss: 0.9670 loss_prob: 0.5043 loss_thr: 0.3726 loss_db: 0.0901 2022/11/02 21:24:41 - mmengine - INFO - Epoch(train) [823][35/63] lr: 7.6361e-04 eta: 4:00:05 time: 0.5258 data_time: 0.0352 memory: 14901 loss: 0.9465 loss_prob: 0.4913 loss_thr: 0.3688 loss_db: 0.0864 2022/11/02 21:24:43 - mmengine - INFO - Epoch(train) [823][40/63] lr: 7.6361e-04 eta: 3:59:59 time: 0.5265 data_time: 0.0132 memory: 14901 loss: 0.9938 loss_prob: 0.5236 loss_thr: 0.3802 loss_db: 0.0900 2022/11/02 21:24:46 - mmengine - INFO - Epoch(train) [823][45/63] lr: 7.6361e-04 eta: 3:59:59 time: 0.5490 data_time: 0.0130 memory: 14901 loss: 0.9727 loss_prob: 0.5075 loss_thr: 0.3760 loss_db: 0.0891 2022/11/02 21:24:49 - mmengine - INFO - Epoch(train) [823][50/63] lr: 7.6361e-04 eta: 3:59:53 time: 0.5856 data_time: 0.0226 memory: 14901 loss: 0.9899 loss_prob: 0.5159 loss_thr: 0.3828 loss_db: 0.0912 2022/11/02 21:24:52 - mmengine - INFO - Epoch(train) [823][55/63] lr: 7.6361e-04 eta: 3:59:53 time: 0.5489 data_time: 0.0257 memory: 14901 loss: 1.0596 loss_prob: 0.5596 loss_thr: 0.4037 loss_db: 0.0963 2022/11/02 21:24:54 - mmengine - INFO - Epoch(train) [823][60/63] lr: 7.6361e-04 eta: 3:59:46 time: 0.4897 data_time: 0.0152 memory: 14901 loss: 1.1259 loss_prob: 0.5991 loss_thr: 0.4244 loss_db: 0.1024 2022/11/02 21:24:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:25:02 - mmengine - INFO - Epoch(train) [824][5/63] lr: 7.6179e-04 eta: 3:59:46 time: 0.9413 data_time: 0.2854 memory: 14901 loss: 1.0689 loss_prob: 0.5660 loss_thr: 0.4064 loss_db: 0.0965 2022/11/02 21:25:07 - mmengine - INFO - Epoch(train) [824][10/63] lr: 7.6179e-04 eta: 3:59:40 time: 1.1277 data_time: 0.2817 memory: 14901 loss: 1.0538 loss_prob: 0.5541 loss_thr: 0.4030 loss_db: 0.0967 2022/11/02 21:25:09 - mmengine - INFO - Epoch(train) [824][15/63] lr: 7.6179e-04 eta: 3:59:40 time: 0.6781 data_time: 0.0099 memory: 14901 loss: 0.9787 loss_prob: 0.5094 loss_thr: 0.3782 loss_db: 0.0910 2022/11/02 21:25:12 - mmengine - INFO - Epoch(train) [824][20/63] lr: 7.6179e-04 eta: 3:59:33 time: 0.5331 data_time: 0.0117 memory: 14901 loss: 1.0146 loss_prob: 0.5348 loss_thr: 0.3869 loss_db: 0.0930 2022/11/02 21:25:15 - mmengine - INFO - Epoch(train) [824][25/63] lr: 7.6179e-04 eta: 3:59:33 time: 0.5535 data_time: 0.0219 memory: 14901 loss: 1.0366 loss_prob: 0.5434 loss_thr: 0.3989 loss_db: 0.0943 2022/11/02 21:25:17 - mmengine - INFO - Epoch(train) [824][30/63] lr: 7.6179e-04 eta: 3:59:27 time: 0.5473 data_time: 0.0339 memory: 14901 loss: 1.0128 loss_prob: 0.5283 loss_thr: 0.3930 loss_db: 0.0915 2022/11/02 21:25:20 - mmengine - INFO - Epoch(train) [824][35/63] lr: 7.6179e-04 eta: 3:59:27 time: 0.5452 data_time: 0.0276 memory: 14901 loss: 1.0213 loss_prob: 0.5382 loss_thr: 0.3892 loss_db: 0.0939 2022/11/02 21:25:23 - mmengine - INFO - Epoch(train) [824][40/63] lr: 7.6179e-04 eta: 3:59:21 time: 0.5254 data_time: 0.0164 memory: 14901 loss: 1.0757 loss_prob: 0.5689 loss_thr: 0.4085 loss_db: 0.0983 2022/11/02 21:25:25 - mmengine - INFO - Epoch(train) [824][45/63] lr: 7.6179e-04 eta: 3:59:21 time: 0.4872 data_time: 0.0130 memory: 14901 loss: 0.9850 loss_prob: 0.5007 loss_thr: 0.3991 loss_db: 0.0852 2022/11/02 21:25:28 - mmengine - INFO - Epoch(train) [824][50/63] lr: 7.6179e-04 eta: 3:59:14 time: 0.5122 data_time: 0.0237 memory: 14901 loss: 1.0794 loss_prob: 0.5803 loss_thr: 0.4054 loss_db: 0.0937 2022/11/02 21:25:30 - mmengine - INFO - Epoch(train) [824][55/63] lr: 7.6179e-04 eta: 3:59:14 time: 0.5188 data_time: 0.0270 memory: 14901 loss: 1.1931 loss_prob: 0.6529 loss_thr: 0.4340 loss_db: 0.1063 2022/11/02 21:25:33 - mmengine - INFO - Epoch(train) [824][60/63] lr: 7.6179e-04 eta: 3:59:08 time: 0.5048 data_time: 0.0167 memory: 14901 loss: 1.0296 loss_prob: 0.5385 loss_thr: 0.3962 loss_db: 0.0949 2022/11/02 21:25:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:25:39 - mmengine - INFO - Epoch(train) [825][5/63] lr: 7.5997e-04 eta: 3:59:08 time: 0.7130 data_time: 0.2077 memory: 14901 loss: 1.1249 loss_prob: 0.6032 loss_thr: 0.4195 loss_db: 0.1022 2022/11/02 21:25:42 - mmengine - INFO - Epoch(train) [825][10/63] lr: 7.5997e-04 eta: 3:59:00 time: 0.7643 data_time: 0.2177 memory: 14901 loss: 1.1787 loss_prob: 0.6532 loss_thr: 0.4196 loss_db: 0.1059 2022/11/02 21:25:45 - mmengine - INFO - Epoch(train) [825][15/63] lr: 7.5997e-04 eta: 3:59:00 time: 0.6282 data_time: 0.0221 memory: 14901 loss: 1.1657 loss_prob: 0.6483 loss_thr: 0.4139 loss_db: 0.1035 2022/11/02 21:25:48 - mmengine - INFO - Epoch(train) [825][20/63] lr: 7.5997e-04 eta: 3:58:54 time: 0.6100 data_time: 0.0125 memory: 14901 loss: 1.0952 loss_prob: 0.5916 loss_thr: 0.4038 loss_db: 0.0997 2022/11/02 21:25:51 - mmengine - INFO - Epoch(train) [825][25/63] lr: 7.5997e-04 eta: 3:58:54 time: 0.5233 data_time: 0.0252 memory: 14901 loss: 1.1018 loss_prob: 0.5946 loss_thr: 0.4104 loss_db: 0.0968 2022/11/02 21:25:53 - mmengine - INFO - Epoch(train) [825][30/63] lr: 7.5997e-04 eta: 3:58:47 time: 0.5271 data_time: 0.0338 memory: 14901 loss: 1.1308 loss_prob: 0.6195 loss_thr: 0.4086 loss_db: 0.1027 2022/11/02 21:25:56 - mmengine - INFO - Epoch(train) [825][35/63] lr: 7.5997e-04 eta: 3:58:47 time: 0.5221 data_time: 0.0313 memory: 14901 loss: 1.0351 loss_prob: 0.5518 loss_thr: 0.3881 loss_db: 0.0952 2022/11/02 21:25:58 - mmengine - INFO - Epoch(train) [825][40/63] lr: 7.5997e-04 eta: 3:58:41 time: 0.5064 data_time: 0.0219 memory: 14901 loss: 1.0405 loss_prob: 0.5419 loss_thr: 0.4076 loss_db: 0.0910 2022/11/02 21:26:01 - mmengine - INFO - Epoch(train) [825][45/63] lr: 7.5997e-04 eta: 3:58:41 time: 0.5362 data_time: 0.0118 memory: 14901 loss: 1.1348 loss_prob: 0.6089 loss_thr: 0.4248 loss_db: 0.1011 2022/11/02 21:26:04 - mmengine - INFO - Epoch(train) [825][50/63] lr: 7.5997e-04 eta: 3:58:34 time: 0.5417 data_time: 0.0168 memory: 14901 loss: 1.2070 loss_prob: 0.6655 loss_thr: 0.4334 loss_db: 0.1081 2022/11/02 21:26:07 - mmengine - INFO - Epoch(train) [825][55/63] lr: 7.5997e-04 eta: 3:58:34 time: 0.5612 data_time: 0.0235 memory: 14901 loss: 1.1511 loss_prob: 0.6331 loss_thr: 0.4143 loss_db: 0.1037 2022/11/02 21:26:09 - mmengine - INFO - Epoch(train) [825][60/63] lr: 7.5997e-04 eta: 3:58:28 time: 0.5630 data_time: 0.0246 memory: 14901 loss: 1.0581 loss_prob: 0.5651 loss_thr: 0.3967 loss_db: 0.0964 2022/11/02 21:26:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:26:16 - mmengine - INFO - Epoch(train) [826][5/63] lr: 7.5814e-04 eta: 3:58:28 time: 0.7927 data_time: 0.2631 memory: 14901 loss: 1.0643 loss_prob: 0.5631 loss_thr: 0.4039 loss_db: 0.0973 2022/11/02 21:26:19 - mmengine - INFO - Epoch(train) [826][10/63] lr: 7.5814e-04 eta: 3:58:20 time: 0.8121 data_time: 0.2640 memory: 14901 loss: 1.1052 loss_prob: 0.5965 loss_thr: 0.4053 loss_db: 0.1035 2022/11/02 21:26:22 - mmengine - INFO - Epoch(train) [826][15/63] lr: 7.5814e-04 eta: 3:58:20 time: 0.5595 data_time: 0.0104 memory: 14901 loss: 1.1588 loss_prob: 0.6283 loss_thr: 0.4192 loss_db: 0.1113 2022/11/02 21:26:25 - mmengine - INFO - Epoch(train) [826][20/63] lr: 7.5814e-04 eta: 3:58:14 time: 0.5967 data_time: 0.0101 memory: 14901 loss: 1.0760 loss_prob: 0.5692 loss_thr: 0.4066 loss_db: 0.1002 2022/11/02 21:26:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:26:28 - mmengine - INFO - Epoch(train) [826][25/63] lr: 7.5814e-04 eta: 3:58:14 time: 0.6221 data_time: 0.0423 memory: 14901 loss: 0.9492 loss_prob: 0.4910 loss_thr: 0.3727 loss_db: 0.0855 2022/11/02 21:26:30 - mmengine - INFO - Epoch(train) [826][30/63] lr: 7.5814e-04 eta: 3:58:08 time: 0.5366 data_time: 0.0410 memory: 14901 loss: 0.9944 loss_prob: 0.5281 loss_thr: 0.3766 loss_db: 0.0896 2022/11/02 21:26:33 - mmengine - INFO - Epoch(train) [826][35/63] lr: 7.5814e-04 eta: 3:58:08 time: 0.5015 data_time: 0.0082 memory: 14901 loss: 1.0881 loss_prob: 0.5701 loss_thr: 0.4216 loss_db: 0.0964 2022/11/02 21:26:35 - mmengine - INFO - Epoch(train) [826][40/63] lr: 7.5814e-04 eta: 3:58:01 time: 0.4980 data_time: 0.0068 memory: 14901 loss: 1.0847 loss_prob: 0.5620 loss_thr: 0.4249 loss_db: 0.0978 2022/11/02 21:26:38 - mmengine - INFO - Epoch(train) [826][45/63] lr: 7.5814e-04 eta: 3:58:01 time: 0.4815 data_time: 0.0113 memory: 14901 loss: 1.0654 loss_prob: 0.5604 loss_thr: 0.4064 loss_db: 0.0986 2022/11/02 21:26:41 - mmengine - INFO - Epoch(train) [826][50/63] lr: 7.5814e-04 eta: 3:57:55 time: 0.5236 data_time: 0.0343 memory: 14901 loss: 0.9841 loss_prob: 0.5084 loss_thr: 0.3886 loss_db: 0.0871 2022/11/02 21:26:43 - mmengine - INFO - Epoch(train) [826][55/63] lr: 7.5814e-04 eta: 3:57:55 time: 0.5309 data_time: 0.0295 memory: 14901 loss: 1.0258 loss_prob: 0.5327 loss_thr: 0.4012 loss_db: 0.0918 2022/11/02 21:26:46 - mmengine - INFO - Epoch(train) [826][60/63] lr: 7.5814e-04 eta: 3:57:48 time: 0.4999 data_time: 0.0123 memory: 14901 loss: 1.0312 loss_prob: 0.5317 loss_thr: 0.4054 loss_db: 0.0941 2022/11/02 21:26:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:26:52 - mmengine - INFO - Epoch(train) [827][5/63] lr: 7.5632e-04 eta: 3:57:48 time: 0.7440 data_time: 0.2117 memory: 14901 loss: 0.9633 loss_prob: 0.4995 loss_thr: 0.3764 loss_db: 0.0874 2022/11/02 21:26:55 - mmengine - INFO - Epoch(train) [827][10/63] lr: 7.5632e-04 eta: 3:57:40 time: 0.7416 data_time: 0.2093 memory: 14901 loss: 1.0279 loss_prob: 0.5358 loss_thr: 0.3989 loss_db: 0.0932 2022/11/02 21:26:57 - mmengine - INFO - Epoch(train) [827][15/63] lr: 7.5632e-04 eta: 3:57:40 time: 0.4972 data_time: 0.0111 memory: 14901 loss: 1.0652 loss_prob: 0.5580 loss_thr: 0.4096 loss_db: 0.0975 2022/11/02 21:27:00 - mmengine - INFO - Epoch(train) [827][20/63] lr: 7.5632e-04 eta: 3:57:34 time: 0.5100 data_time: 0.0127 memory: 14901 loss: 1.0843 loss_prob: 0.5758 loss_thr: 0.4089 loss_db: 0.0995 2022/11/02 21:27:03 - mmengine - INFO - Epoch(train) [827][25/63] lr: 7.5632e-04 eta: 3:57:34 time: 0.6075 data_time: 0.0464 memory: 14901 loss: 1.0364 loss_prob: 0.5489 loss_thr: 0.3934 loss_db: 0.0941 2022/11/02 21:27:06 - mmengine - INFO - Epoch(train) [827][30/63] lr: 7.5632e-04 eta: 3:57:28 time: 0.6445 data_time: 0.0463 memory: 14901 loss: 1.0275 loss_prob: 0.5532 loss_thr: 0.3844 loss_db: 0.0899 2022/11/02 21:27:09 - mmengine - INFO - Epoch(train) [827][35/63] lr: 7.5632e-04 eta: 3:57:28 time: 0.5578 data_time: 0.0093 memory: 14901 loss: 1.1680 loss_prob: 0.6449 loss_thr: 0.4184 loss_db: 0.1046 2022/11/02 21:27:11 - mmengine - INFO - Epoch(train) [827][40/63] lr: 7.5632e-04 eta: 3:57:22 time: 0.5334 data_time: 0.0087 memory: 14901 loss: 1.2154 loss_prob: 0.6503 loss_thr: 0.4550 loss_db: 0.1102 2022/11/02 21:27:14 - mmengine - INFO - Epoch(train) [827][45/63] lr: 7.5632e-04 eta: 3:57:22 time: 0.5248 data_time: 0.0101 memory: 14901 loss: 1.0730 loss_prob: 0.5624 loss_thr: 0.4161 loss_db: 0.0945 2022/11/02 21:27:17 - mmengine - INFO - Epoch(train) [827][50/63] lr: 7.5632e-04 eta: 3:57:15 time: 0.5212 data_time: 0.0246 memory: 14901 loss: 0.9716 loss_prob: 0.5124 loss_thr: 0.3732 loss_db: 0.0860 2022/11/02 21:27:19 - mmengine - INFO - Epoch(train) [827][55/63] lr: 7.5632e-04 eta: 3:57:15 time: 0.5347 data_time: 0.0237 memory: 14901 loss: 1.0168 loss_prob: 0.5298 loss_thr: 0.3941 loss_db: 0.0928 2022/11/02 21:27:22 - mmengine - INFO - Epoch(train) [827][60/63] lr: 7.5632e-04 eta: 3:57:09 time: 0.5339 data_time: 0.0119 memory: 14901 loss: 1.0059 loss_prob: 0.5148 loss_thr: 0.3975 loss_db: 0.0936 2022/11/02 21:27:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:27:29 - mmengine - INFO - Epoch(train) [828][5/63] lr: 7.5450e-04 eta: 3:57:09 time: 0.8293 data_time: 0.2388 memory: 14901 loss: 0.9376 loss_prob: 0.4854 loss_thr: 0.3690 loss_db: 0.0832 2022/11/02 21:27:32 - mmengine - INFO - Epoch(train) [828][10/63] lr: 7.5450e-04 eta: 3:57:01 time: 0.8795 data_time: 0.2392 memory: 14901 loss: 1.0108 loss_prob: 0.5373 loss_thr: 0.3837 loss_db: 0.0898 2022/11/02 21:27:35 - mmengine - INFO - Epoch(train) [828][15/63] lr: 7.5450e-04 eta: 3:57:01 time: 0.5710 data_time: 0.0104 memory: 14901 loss: 1.0248 loss_prob: 0.5455 loss_thr: 0.3864 loss_db: 0.0929 2022/11/02 21:27:37 - mmengine - INFO - Epoch(train) [828][20/63] lr: 7.5450e-04 eta: 3:56:55 time: 0.5402 data_time: 0.0090 memory: 14901 loss: 1.0023 loss_prob: 0.5223 loss_thr: 0.3883 loss_db: 0.0917 2022/11/02 21:27:40 - mmengine - INFO - Epoch(train) [828][25/63] lr: 7.5450e-04 eta: 3:56:55 time: 0.5559 data_time: 0.0219 memory: 14901 loss: 0.9849 loss_prob: 0.5137 loss_thr: 0.3822 loss_db: 0.0889 2022/11/02 21:27:43 - mmengine - INFO - Epoch(train) [828][30/63] lr: 7.5450e-04 eta: 3:56:49 time: 0.5583 data_time: 0.0379 memory: 14901 loss: 1.0207 loss_prob: 0.5321 loss_thr: 0.3986 loss_db: 0.0899 2022/11/02 21:27:46 - mmengine - INFO - Epoch(train) [828][35/63] lr: 7.5450e-04 eta: 3:56:49 time: 0.6062 data_time: 0.0256 memory: 14901 loss: 1.0497 loss_prob: 0.5521 loss_thr: 0.4012 loss_db: 0.0963 2022/11/02 21:27:49 - mmengine - INFO - Epoch(train) [828][40/63] lr: 7.5450e-04 eta: 3:56:42 time: 0.5639 data_time: 0.0091 memory: 14901 loss: 0.9822 loss_prob: 0.5125 loss_thr: 0.3797 loss_db: 0.0901 2022/11/02 21:27:51 - mmengine - INFO - Epoch(train) [828][45/63] lr: 7.5450e-04 eta: 3:56:42 time: 0.4747 data_time: 0.0091 memory: 14901 loss: 1.0231 loss_prob: 0.5399 loss_thr: 0.3912 loss_db: 0.0919 2022/11/02 21:27:54 - mmengine - INFO - Epoch(train) [828][50/63] lr: 7.5450e-04 eta: 3:56:36 time: 0.5230 data_time: 0.0215 memory: 14901 loss: 1.0615 loss_prob: 0.5683 loss_thr: 0.3943 loss_db: 0.0990 2022/11/02 21:27:56 - mmengine - INFO - Epoch(train) [828][55/63] lr: 7.5450e-04 eta: 3:56:36 time: 0.5299 data_time: 0.0293 memory: 14901 loss: 0.9678 loss_prob: 0.5027 loss_thr: 0.3775 loss_db: 0.0876 2022/11/02 21:27:59 - mmengine - INFO - Epoch(train) [828][60/63] lr: 7.5450e-04 eta: 3:56:29 time: 0.4967 data_time: 0.0170 memory: 14901 loss: 0.9839 loss_prob: 0.5064 loss_thr: 0.3900 loss_db: 0.0875 2022/11/02 21:28:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:28:05 - mmengine - INFO - Epoch(train) [829][5/63] lr: 7.5267e-04 eta: 3:56:29 time: 0.7502 data_time: 0.2679 memory: 14901 loss: 1.0835 loss_prob: 0.5688 loss_thr: 0.4154 loss_db: 0.0993 2022/11/02 21:28:08 - mmengine - INFO - Epoch(train) [829][10/63] lr: 7.5267e-04 eta: 3:56:21 time: 0.7612 data_time: 0.2676 memory: 14901 loss: 1.0709 loss_prob: 0.5692 loss_thr: 0.4050 loss_db: 0.0967 2022/11/02 21:28:10 - mmengine - INFO - Epoch(train) [829][15/63] lr: 7.5267e-04 eta: 3:56:21 time: 0.4807 data_time: 0.0093 memory: 14901 loss: 1.0314 loss_prob: 0.5368 loss_thr: 0.4021 loss_db: 0.0926 2022/11/02 21:28:13 - mmengine - INFO - Epoch(train) [829][20/63] lr: 7.5267e-04 eta: 3:56:15 time: 0.4867 data_time: 0.0095 memory: 14901 loss: 1.0185 loss_prob: 0.5213 loss_thr: 0.4050 loss_db: 0.0922 2022/11/02 21:28:17 - mmengine - INFO - Epoch(train) [829][25/63] lr: 7.5267e-04 eta: 3:56:15 time: 0.6295 data_time: 0.0461 memory: 14901 loss: 1.0057 loss_prob: 0.5138 loss_thr: 0.4012 loss_db: 0.0907 2022/11/02 21:28:20 - mmengine - INFO - Epoch(train) [829][30/63] lr: 7.5267e-04 eta: 3:56:09 time: 0.7246 data_time: 0.0458 memory: 14901 loss: 1.0183 loss_prob: 0.5321 loss_thr: 0.3961 loss_db: 0.0902 2022/11/02 21:28:22 - mmengine - INFO - Epoch(train) [829][35/63] lr: 7.5267e-04 eta: 3:56:09 time: 0.5864 data_time: 0.0117 memory: 14901 loss: 1.0299 loss_prob: 0.5452 loss_thr: 0.3929 loss_db: 0.0919 2022/11/02 21:28:25 - mmengine - INFO - Epoch(train) [829][40/63] lr: 7.5267e-04 eta: 3:56:03 time: 0.5421 data_time: 0.0122 memory: 14901 loss: 0.9952 loss_prob: 0.5169 loss_thr: 0.3881 loss_db: 0.0902 2022/11/02 21:28:28 - mmengine - INFO - Epoch(train) [829][45/63] lr: 7.5267e-04 eta: 3:56:03 time: 0.5449 data_time: 0.0123 memory: 14901 loss: 1.0348 loss_prob: 0.5409 loss_thr: 0.4010 loss_db: 0.0929 2022/11/02 21:28:31 - mmengine - INFO - Epoch(train) [829][50/63] lr: 7.5267e-04 eta: 3:55:57 time: 0.5334 data_time: 0.0351 memory: 14901 loss: 1.0397 loss_prob: 0.5470 loss_thr: 0.3985 loss_db: 0.0943 2022/11/02 21:28:33 - mmengine - INFO - Epoch(train) [829][55/63] lr: 7.5267e-04 eta: 3:55:57 time: 0.5408 data_time: 0.0364 memory: 14901 loss: 0.9726 loss_prob: 0.5032 loss_thr: 0.3805 loss_db: 0.0889 2022/11/02 21:28:36 - mmengine - INFO - Epoch(train) [829][60/63] lr: 7.5267e-04 eta: 3:55:50 time: 0.5060 data_time: 0.0146 memory: 14901 loss: 1.0346 loss_prob: 0.5343 loss_thr: 0.4062 loss_db: 0.0941 2022/11/02 21:28:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:28:42 - mmengine - INFO - Epoch(train) [830][5/63] lr: 7.5084e-04 eta: 3:55:50 time: 0.6845 data_time: 0.2177 memory: 14901 loss: 1.1047 loss_prob: 0.5943 loss_thr: 0.4077 loss_db: 0.1027 2022/11/02 21:28:44 - mmengine - INFO - Epoch(train) [830][10/63] lr: 7.5084e-04 eta: 3:55:42 time: 0.7214 data_time: 0.2174 memory: 14901 loss: 0.9862 loss_prob: 0.5226 loss_thr: 0.3722 loss_db: 0.0914 2022/11/02 21:28:47 - mmengine - INFO - Epoch(train) [830][15/63] lr: 7.5084e-04 eta: 3:55:42 time: 0.5327 data_time: 0.0155 memory: 14901 loss: 0.9869 loss_prob: 0.5235 loss_thr: 0.3731 loss_db: 0.0903 2022/11/02 21:28:50 - mmengine - INFO - Epoch(train) [830][20/63] lr: 7.5084e-04 eta: 3:55:36 time: 0.5432 data_time: 0.0194 memory: 14901 loss: 1.0374 loss_prob: 0.5546 loss_thr: 0.3897 loss_db: 0.0931 2022/11/02 21:28:52 - mmengine - INFO - Epoch(train) [830][25/63] lr: 7.5084e-04 eta: 3:55:36 time: 0.5291 data_time: 0.0377 memory: 14901 loss: 1.0756 loss_prob: 0.5670 loss_thr: 0.4122 loss_db: 0.0964 2022/11/02 21:28:55 - mmengine - INFO - Epoch(train) [830][30/63] lr: 7.5084e-04 eta: 3:55:29 time: 0.4970 data_time: 0.0338 memory: 14901 loss: 1.1859 loss_prob: 0.6302 loss_thr: 0.4470 loss_db: 0.1087 2022/11/02 21:28:58 - mmengine - INFO - Epoch(train) [830][35/63] lr: 7.5084e-04 eta: 3:55:29 time: 0.6184 data_time: 0.0191 memory: 14901 loss: 1.1105 loss_prob: 0.5807 loss_thr: 0.4309 loss_db: 0.0990 2022/11/02 21:29:01 - mmengine - INFO - Epoch(train) [830][40/63] lr: 7.5084e-04 eta: 3:55:23 time: 0.6381 data_time: 0.0198 memory: 14901 loss: 0.9366 loss_prob: 0.4766 loss_thr: 0.3781 loss_db: 0.0819 2022/11/02 21:29:03 - mmengine - INFO - Epoch(train) [830][45/63] lr: 7.5084e-04 eta: 3:55:23 time: 0.4959 data_time: 0.0140 memory: 14901 loss: 0.9658 loss_prob: 0.4929 loss_thr: 0.3852 loss_db: 0.0876 2022/11/02 21:29:06 - mmengine - INFO - Epoch(train) [830][50/63] lr: 7.5084e-04 eta: 3:55:17 time: 0.5141 data_time: 0.0307 memory: 14901 loss: 1.0563 loss_prob: 0.5513 loss_thr: 0.4090 loss_db: 0.0960 2022/11/02 21:29:09 - mmengine - INFO - Epoch(train) [830][55/63] lr: 7.5084e-04 eta: 3:55:17 time: 0.5366 data_time: 0.0265 memory: 14901 loss: 1.0062 loss_prob: 0.5328 loss_thr: 0.3832 loss_db: 0.0901 2022/11/02 21:29:11 - mmengine - INFO - Epoch(train) [830][60/63] lr: 7.5084e-04 eta: 3:55:10 time: 0.5149 data_time: 0.0125 memory: 14901 loss: 0.9699 loss_prob: 0.5082 loss_thr: 0.3742 loss_db: 0.0875 2022/11/02 21:29:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:29:18 - mmengine - INFO - Epoch(train) [831][5/63] lr: 7.4902e-04 eta: 3:55:10 time: 0.7750 data_time: 0.1905 memory: 14901 loss: 1.0133 loss_prob: 0.5280 loss_thr: 0.3965 loss_db: 0.0887 2022/11/02 21:29:21 - mmengine - INFO - Epoch(train) [831][10/63] lr: 7.4902e-04 eta: 3:55:03 time: 0.8092 data_time: 0.1898 memory: 14901 loss: 1.0724 loss_prob: 0.5719 loss_thr: 0.4049 loss_db: 0.0955 2022/11/02 21:29:23 - mmengine - INFO - Epoch(train) [831][15/63] lr: 7.4902e-04 eta: 3:55:03 time: 0.5196 data_time: 0.0098 memory: 14901 loss: 1.0729 loss_prob: 0.5695 loss_thr: 0.4043 loss_db: 0.0992 2022/11/02 21:29:26 - mmengine - INFO - Epoch(train) [831][20/63] lr: 7.4902e-04 eta: 3:54:56 time: 0.5087 data_time: 0.0116 memory: 14901 loss: 0.9447 loss_prob: 0.4859 loss_thr: 0.3731 loss_db: 0.0856 2022/11/02 21:29:28 - mmengine - INFO - Epoch(train) [831][25/63] lr: 7.4902e-04 eta: 3:54:56 time: 0.5002 data_time: 0.0101 memory: 14901 loss: 0.9552 loss_prob: 0.4910 loss_thr: 0.3789 loss_db: 0.0852 2022/11/02 21:29:31 - mmengine - INFO - Epoch(train) [831][30/63] lr: 7.4902e-04 eta: 3:54:50 time: 0.5145 data_time: 0.0414 memory: 14901 loss: 1.0859 loss_prob: 0.5681 loss_thr: 0.4184 loss_db: 0.0994 2022/11/02 21:29:33 - mmengine - INFO - Epoch(train) [831][35/63] lr: 7.4902e-04 eta: 3:54:50 time: 0.5205 data_time: 0.0433 memory: 14901 loss: 1.0459 loss_prob: 0.5462 loss_thr: 0.4045 loss_db: 0.0952 2022/11/02 21:29:36 - mmengine - INFO - Epoch(train) [831][40/63] lr: 7.4902e-04 eta: 3:54:43 time: 0.4942 data_time: 0.0127 memory: 14901 loss: 0.9200 loss_prob: 0.4828 loss_thr: 0.3540 loss_db: 0.0833 2022/11/02 21:29:40 - mmengine - INFO - Epoch(train) [831][45/63] lr: 7.4902e-04 eta: 3:54:43 time: 0.6359 data_time: 0.0108 memory: 14901 loss: 0.8912 loss_prob: 0.4544 loss_thr: 0.3567 loss_db: 0.0802 2022/11/02 21:29:42 - mmengine - INFO - Epoch(train) [831][50/63] lr: 7.4902e-04 eta: 3:54:37 time: 0.6626 data_time: 0.0164 memory: 14901 loss: 0.9245 loss_prob: 0.4669 loss_thr: 0.3750 loss_db: 0.0826 2022/11/02 21:29:45 - mmengine - INFO - Epoch(train) [831][55/63] lr: 7.4902e-04 eta: 3:54:37 time: 0.5490 data_time: 0.0347 memory: 14901 loss: 0.9582 loss_prob: 0.4955 loss_thr: 0.3768 loss_db: 0.0859 2022/11/02 21:29:48 - mmengine - INFO - Epoch(train) [831][60/63] lr: 7.4902e-04 eta: 3:54:31 time: 0.5402 data_time: 0.0282 memory: 14901 loss: 1.0400 loss_prob: 0.5436 loss_thr: 0.4035 loss_db: 0.0929 2022/11/02 21:29:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:29:54 - mmengine - INFO - Epoch(train) [832][5/63] lr: 7.4719e-04 eta: 3:54:31 time: 0.7500 data_time: 0.1914 memory: 14901 loss: 1.1051 loss_prob: 0.5928 loss_thr: 0.4085 loss_db: 0.1038 2022/11/02 21:29:57 - mmengine - INFO - Epoch(train) [832][10/63] lr: 7.4719e-04 eta: 3:54:23 time: 0.7741 data_time: 0.1928 memory: 14901 loss: 1.0115 loss_prob: 0.5314 loss_thr: 0.3901 loss_db: 0.0900 2022/11/02 21:30:00 - mmengine - INFO - Epoch(train) [832][15/63] lr: 7.4719e-04 eta: 3:54:23 time: 0.5380 data_time: 0.0112 memory: 14901 loss: 0.9430 loss_prob: 0.4782 loss_thr: 0.3823 loss_db: 0.0824 2022/11/02 21:30:03 - mmengine - INFO - Epoch(train) [832][20/63] lr: 7.4719e-04 eta: 3:54:17 time: 0.6046 data_time: 0.0110 memory: 14901 loss: 0.9479 loss_prob: 0.4801 loss_thr: 0.3826 loss_db: 0.0852 2022/11/02 21:30:05 - mmengine - INFO - Epoch(train) [832][25/63] lr: 7.4719e-04 eta: 3:54:17 time: 0.5547 data_time: 0.0187 memory: 14901 loss: 0.9167 loss_prob: 0.4666 loss_thr: 0.3670 loss_db: 0.0831 2022/11/02 21:30:08 - mmengine - INFO - Epoch(train) [832][30/63] lr: 7.4719e-04 eta: 3:54:11 time: 0.5591 data_time: 0.0416 memory: 14901 loss: 0.9604 loss_prob: 0.4923 loss_thr: 0.3823 loss_db: 0.0858 2022/11/02 21:30:11 - mmengine - INFO - Epoch(train) [832][35/63] lr: 7.4719e-04 eta: 3:54:11 time: 0.5599 data_time: 0.0360 memory: 14901 loss: 1.0453 loss_prob: 0.5588 loss_thr: 0.3915 loss_db: 0.0949 2022/11/02 21:30:13 - mmengine - INFO - Epoch(train) [832][40/63] lr: 7.4719e-04 eta: 3:54:04 time: 0.4895 data_time: 0.0143 memory: 14901 loss: 1.0588 loss_prob: 0.5733 loss_thr: 0.3880 loss_db: 0.0975 2022/11/02 21:30:16 - mmengine - INFO - Epoch(train) [832][45/63] lr: 7.4719e-04 eta: 3:54:04 time: 0.4813 data_time: 0.0127 memory: 14901 loss: 0.9977 loss_prob: 0.5217 loss_thr: 0.3868 loss_db: 0.0892 2022/11/02 21:30:18 - mmengine - INFO - Epoch(train) [832][50/63] lr: 7.4719e-04 eta: 3:53:58 time: 0.4964 data_time: 0.0170 memory: 14901 loss: 0.9724 loss_prob: 0.4989 loss_thr: 0.3865 loss_db: 0.0869 2022/11/02 21:30:22 - mmengine - INFO - Epoch(train) [832][55/63] lr: 7.4719e-04 eta: 3:53:58 time: 0.6015 data_time: 0.0202 memory: 14901 loss: 0.9990 loss_prob: 0.5181 loss_thr: 0.3894 loss_db: 0.0915 2022/11/02 21:30:24 - mmengine - INFO - Epoch(train) [832][60/63] lr: 7.4719e-04 eta: 3:53:52 time: 0.6033 data_time: 0.0140 memory: 14901 loss: 1.0550 loss_prob: 0.5496 loss_thr: 0.4104 loss_db: 0.0951 2022/11/02 21:30:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:30:32 - mmengine - INFO - Epoch(train) [833][5/63] lr: 7.4536e-04 eta: 3:53:52 time: 0.8286 data_time: 0.2171 memory: 14901 loss: 1.2465 loss_prob: 0.6746 loss_thr: 0.4564 loss_db: 0.1155 2022/11/02 21:30:34 - mmengine - INFO - Epoch(train) [833][10/63] lr: 7.4536e-04 eta: 3:53:44 time: 0.8023 data_time: 0.2165 memory: 14901 loss: 1.1201 loss_prob: 0.5941 loss_thr: 0.4232 loss_db: 0.1028 2022/11/02 21:30:37 - mmengine - INFO - Epoch(train) [833][15/63] lr: 7.4536e-04 eta: 3:53:44 time: 0.4817 data_time: 0.0125 memory: 14901 loss: 1.0244 loss_prob: 0.5381 loss_thr: 0.3911 loss_db: 0.0952 2022/11/02 21:30:39 - mmengine - INFO - Epoch(train) [833][20/63] lr: 7.4536e-04 eta: 3:53:37 time: 0.4812 data_time: 0.0118 memory: 14901 loss: 1.0049 loss_prob: 0.5325 loss_thr: 0.3804 loss_db: 0.0919 2022/11/02 21:30:42 - mmengine - INFO - Epoch(train) [833][25/63] lr: 7.4536e-04 eta: 3:53:37 time: 0.5543 data_time: 0.0274 memory: 14901 loss: 0.9941 loss_prob: 0.5263 loss_thr: 0.3772 loss_db: 0.0906 2022/11/02 21:30:45 - mmengine - INFO - Epoch(train) [833][30/63] lr: 7.4536e-04 eta: 3:53:31 time: 0.5941 data_time: 0.0508 memory: 14901 loss: 1.0393 loss_prob: 0.5477 loss_thr: 0.3956 loss_db: 0.0960 2022/11/02 21:30:48 - mmengine - INFO - Epoch(train) [833][35/63] lr: 7.4536e-04 eta: 3:53:31 time: 0.5499 data_time: 0.0340 memory: 14901 loss: 1.0574 loss_prob: 0.5487 loss_thr: 0.4124 loss_db: 0.0963 2022/11/02 21:30:50 - mmengine - INFO - Epoch(train) [833][40/63] lr: 7.4536e-04 eta: 3:53:25 time: 0.5240 data_time: 0.0155 memory: 14901 loss: 1.0098 loss_prob: 0.5213 loss_thr: 0.3989 loss_db: 0.0896 2022/11/02 21:30:53 - mmengine - INFO - Epoch(train) [833][45/63] lr: 7.4536e-04 eta: 3:53:25 time: 0.5148 data_time: 0.0156 memory: 14901 loss: 1.0126 loss_prob: 0.5277 loss_thr: 0.3934 loss_db: 0.0915 2022/11/02 21:30:55 - mmengine - INFO - Epoch(train) [833][50/63] lr: 7.4536e-04 eta: 3:53:18 time: 0.5051 data_time: 0.0245 memory: 14901 loss: 0.9974 loss_prob: 0.5178 loss_thr: 0.3907 loss_db: 0.0889 2022/11/02 21:30:58 - mmengine - INFO - Epoch(train) [833][55/63] lr: 7.4536e-04 eta: 3:53:18 time: 0.5108 data_time: 0.0268 memory: 14901 loss: 1.0067 loss_prob: 0.5216 loss_thr: 0.3963 loss_db: 0.0887 2022/11/02 21:31:01 - mmengine - INFO - Epoch(train) [833][60/63] lr: 7.4536e-04 eta: 3:53:12 time: 0.5462 data_time: 0.0165 memory: 14901 loss: 1.0481 loss_prob: 0.5425 loss_thr: 0.4105 loss_db: 0.0951 2022/11/02 21:31:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:31:08 - mmengine - INFO - Epoch(train) [834][5/63] lr: 7.4354e-04 eta: 3:53:12 time: 0.8287 data_time: 0.2376 memory: 14901 loss: 0.9269 loss_prob: 0.4742 loss_thr: 0.3698 loss_db: 0.0829 2022/11/02 21:31:11 - mmengine - INFO - Epoch(train) [834][10/63] lr: 7.4354e-04 eta: 3:53:04 time: 0.8801 data_time: 0.2361 memory: 14901 loss: 0.9276 loss_prob: 0.4803 loss_thr: 0.3643 loss_db: 0.0831 2022/11/02 21:31:14 - mmengine - INFO - Epoch(train) [834][15/63] lr: 7.4354e-04 eta: 3:53:04 time: 0.5998 data_time: 0.0189 memory: 14901 loss: 0.9335 loss_prob: 0.4799 loss_thr: 0.3692 loss_db: 0.0844 2022/11/02 21:31:16 - mmengine - INFO - Epoch(train) [834][20/63] lr: 7.4354e-04 eta: 3:52:58 time: 0.5324 data_time: 0.0153 memory: 14901 loss: 1.0118 loss_prob: 0.5216 loss_thr: 0.3991 loss_db: 0.0911 2022/11/02 21:31:19 - mmengine - INFO - Epoch(train) [834][25/63] lr: 7.4354e-04 eta: 3:52:58 time: 0.5435 data_time: 0.0316 memory: 14901 loss: 1.0054 loss_prob: 0.5172 loss_thr: 0.3984 loss_db: 0.0898 2022/11/02 21:31:22 - mmengine - INFO - Epoch(train) [834][30/63] lr: 7.4354e-04 eta: 3:52:52 time: 0.5264 data_time: 0.0397 memory: 14901 loss: 1.0217 loss_prob: 0.5220 loss_thr: 0.4067 loss_db: 0.0930 2022/11/02 21:31:24 - mmengine - INFO - Epoch(train) [834][35/63] lr: 7.4354e-04 eta: 3:52:52 time: 0.4766 data_time: 0.0185 memory: 14901 loss: 1.0642 loss_prob: 0.5475 loss_thr: 0.4216 loss_db: 0.0952 2022/11/02 21:31:27 - mmengine - INFO - Epoch(train) [834][40/63] lr: 7.4354e-04 eta: 3:52:45 time: 0.5036 data_time: 0.0149 memory: 14901 loss: 1.0470 loss_prob: 0.5455 loss_thr: 0.4083 loss_db: 0.0933 2022/11/02 21:31:29 - mmengine - INFO - Epoch(train) [834][45/63] lr: 7.4354e-04 eta: 3:52:45 time: 0.5080 data_time: 0.0155 memory: 14901 loss: 1.0814 loss_prob: 0.5632 loss_thr: 0.4213 loss_db: 0.0969 2022/11/02 21:31:32 - mmengine - INFO - Epoch(train) [834][50/63] lr: 7.4354e-04 eta: 3:52:39 time: 0.5247 data_time: 0.0250 memory: 14901 loss: 1.0916 loss_prob: 0.5687 loss_thr: 0.4264 loss_db: 0.0965 2022/11/02 21:31:34 - mmengine - INFO - Epoch(train) [834][55/63] lr: 7.4354e-04 eta: 3:52:39 time: 0.5212 data_time: 0.0238 memory: 14901 loss: 1.0317 loss_prob: 0.5403 loss_thr: 0.3979 loss_db: 0.0935 2022/11/02 21:31:37 - mmengine - INFO - Epoch(train) [834][60/63] lr: 7.4354e-04 eta: 3:52:32 time: 0.4876 data_time: 0.0099 memory: 14901 loss: 0.9747 loss_prob: 0.5075 loss_thr: 0.3785 loss_db: 0.0886 2022/11/02 21:31:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:31:44 - mmengine - INFO - Epoch(train) [835][5/63] lr: 7.4171e-04 eta: 3:52:32 time: 0.7573 data_time: 0.2289 memory: 14901 loss: 1.0092 loss_prob: 0.5326 loss_thr: 0.3847 loss_db: 0.0919 2022/11/02 21:31:46 - mmengine - INFO - Epoch(train) [835][10/63] lr: 7.4171e-04 eta: 3:52:24 time: 0.8027 data_time: 0.2262 memory: 14901 loss: 0.9779 loss_prob: 0.5118 loss_thr: 0.3756 loss_db: 0.0906 2022/11/02 21:31:49 - mmengine - INFO - Epoch(train) [835][15/63] lr: 7.4171e-04 eta: 3:52:24 time: 0.5096 data_time: 0.0109 memory: 14901 loss: 0.9740 loss_prob: 0.5067 loss_thr: 0.3787 loss_db: 0.0886 2022/11/02 21:31:51 - mmengine - INFO - Epoch(train) [835][20/63] lr: 7.4171e-04 eta: 3:52:18 time: 0.5151 data_time: 0.0109 memory: 14901 loss: 1.0920 loss_prob: 0.5734 loss_thr: 0.4204 loss_db: 0.0982 2022/11/02 21:31:54 - mmengine - INFO - Epoch(train) [835][25/63] lr: 7.4171e-04 eta: 3:52:18 time: 0.5230 data_time: 0.0250 memory: 14901 loss: 1.1268 loss_prob: 0.5905 loss_thr: 0.4346 loss_db: 0.1016 2022/11/02 21:31:57 - mmengine - INFO - Epoch(train) [835][30/63] lr: 7.4171e-04 eta: 3:52:11 time: 0.5240 data_time: 0.0388 memory: 14901 loss: 1.0364 loss_prob: 0.5370 loss_thr: 0.4071 loss_db: 0.0924 2022/11/02 21:32:00 - mmengine - INFO - Epoch(train) [835][35/63] lr: 7.4171e-04 eta: 3:52:11 time: 0.5717 data_time: 0.0333 memory: 14901 loss: 1.0122 loss_prob: 0.5284 loss_thr: 0.3932 loss_db: 0.0906 2022/11/02 21:32:02 - mmengine - INFO - Epoch(train) [835][40/63] lr: 7.4171e-04 eta: 3:52:05 time: 0.5476 data_time: 0.0184 memory: 14901 loss: 0.9640 loss_prob: 0.5015 loss_thr: 0.3750 loss_db: 0.0875 2022/11/02 21:32:05 - mmengine - INFO - Epoch(train) [835][45/63] lr: 7.4171e-04 eta: 3:52:05 time: 0.5081 data_time: 0.0093 memory: 14901 loss: 0.9408 loss_prob: 0.4883 loss_thr: 0.3688 loss_db: 0.0837 2022/11/02 21:32:07 - mmengine - INFO - Epoch(train) [835][50/63] lr: 7.4171e-04 eta: 3:51:59 time: 0.5240 data_time: 0.0200 memory: 14901 loss: 0.9416 loss_prob: 0.4854 loss_thr: 0.3728 loss_db: 0.0833 2022/11/02 21:32:10 - mmengine - INFO - Epoch(train) [835][55/63] lr: 7.4171e-04 eta: 3:51:59 time: 0.5036 data_time: 0.0215 memory: 14901 loss: 0.9367 loss_prob: 0.4703 loss_thr: 0.3838 loss_db: 0.0827 2022/11/02 21:32:12 - mmengine - INFO - Epoch(train) [835][60/63] lr: 7.4171e-04 eta: 3:51:52 time: 0.4865 data_time: 0.0162 memory: 14901 loss: 1.0536 loss_prob: 0.5509 loss_thr: 0.4077 loss_db: 0.0950 2022/11/02 21:32:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:32:19 - mmengine - INFO - Epoch(train) [836][5/63] lr: 7.3988e-04 eta: 3:51:52 time: 0.7410 data_time: 0.2186 memory: 14901 loss: 1.0266 loss_prob: 0.5403 loss_thr: 0.3950 loss_db: 0.0913 2022/11/02 21:32:21 - mmengine - INFO - Epoch(train) [836][10/63] lr: 7.3988e-04 eta: 3:51:44 time: 0.7896 data_time: 0.2193 memory: 14901 loss: 1.0162 loss_prob: 0.5355 loss_thr: 0.3864 loss_db: 0.0943 2022/11/02 21:32:24 - mmengine - INFO - Epoch(train) [836][15/63] lr: 7.3988e-04 eta: 3:51:44 time: 0.5203 data_time: 0.0137 memory: 14901 loss: 1.0236 loss_prob: 0.5421 loss_thr: 0.3868 loss_db: 0.0947 2022/11/02 21:32:28 - mmengine - INFO - Epoch(train) [836][20/63] lr: 7.3988e-04 eta: 3:51:38 time: 0.6175 data_time: 0.0171 memory: 14901 loss: 0.9535 loss_prob: 0.4910 loss_thr: 0.3767 loss_db: 0.0858 2022/11/02 21:32:30 - mmengine - INFO - Epoch(train) [836][25/63] lr: 7.3988e-04 eta: 3:51:38 time: 0.6691 data_time: 0.0200 memory: 14901 loss: 0.9734 loss_prob: 0.5130 loss_thr: 0.3723 loss_db: 0.0881 2022/11/02 21:32:33 - mmengine - INFO - Epoch(train) [836][30/63] lr: 7.3988e-04 eta: 3:51:32 time: 0.5628 data_time: 0.0460 memory: 14901 loss: 1.0226 loss_prob: 0.5414 loss_thr: 0.3876 loss_db: 0.0936 2022/11/02 21:32:36 - mmengine - INFO - Epoch(train) [836][35/63] lr: 7.3988e-04 eta: 3:51:32 time: 0.5473 data_time: 0.0428 memory: 14901 loss: 0.9669 loss_prob: 0.4981 loss_thr: 0.3826 loss_db: 0.0861 2022/11/02 21:32:39 - mmengine - INFO - Epoch(train) [836][40/63] lr: 7.3988e-04 eta: 3:51:26 time: 0.5581 data_time: 0.0142 memory: 14901 loss: 0.9606 loss_prob: 0.4953 loss_thr: 0.3795 loss_db: 0.0858 2022/11/02 21:32:41 - mmengine - INFO - Epoch(train) [836][45/63] lr: 7.3988e-04 eta: 3:51:26 time: 0.5348 data_time: 0.0133 memory: 14901 loss: 0.9865 loss_prob: 0.5043 loss_thr: 0.3960 loss_db: 0.0862 2022/11/02 21:32:44 - mmengine - INFO - Epoch(train) [836][50/63] lr: 7.3988e-04 eta: 3:51:19 time: 0.4947 data_time: 0.0192 memory: 14901 loss: 0.9103 loss_prob: 0.4599 loss_thr: 0.3722 loss_db: 0.0782 2022/11/02 21:32:46 - mmengine - INFO - Epoch(train) [836][55/63] lr: 7.3988e-04 eta: 3:51:19 time: 0.5087 data_time: 0.0278 memory: 14901 loss: 0.9016 loss_prob: 0.4635 loss_thr: 0.3576 loss_db: 0.0805 2022/11/02 21:32:49 - mmengine - INFO - Epoch(train) [836][60/63] lr: 7.3988e-04 eta: 3:51:13 time: 0.5178 data_time: 0.0201 memory: 14901 loss: 1.0086 loss_prob: 0.5272 loss_thr: 0.3885 loss_db: 0.0929 2022/11/02 21:32:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:32:55 - mmengine - INFO - Epoch(train) [837][5/63] lr: 7.3805e-04 eta: 3:51:13 time: 0.7709 data_time: 0.2284 memory: 14901 loss: 0.9521 loss_prob: 0.4889 loss_thr: 0.3771 loss_db: 0.0862 2022/11/02 21:32:58 - mmengine - INFO - Epoch(train) [837][10/63] lr: 7.3805e-04 eta: 3:51:05 time: 0.7846 data_time: 0.2319 memory: 14901 loss: 1.1159 loss_prob: 0.6255 loss_thr: 0.3942 loss_db: 0.0962 2022/11/02 21:33:00 - mmengine - INFO - Epoch(train) [837][15/63] lr: 7.3805e-04 eta: 3:51:05 time: 0.4927 data_time: 0.0119 memory: 14901 loss: 1.1483 loss_prob: 0.6535 loss_thr: 0.3960 loss_db: 0.0988 2022/11/02 21:33:03 - mmengine - INFO - Epoch(train) [837][20/63] lr: 7.3805e-04 eta: 3:50:58 time: 0.4642 data_time: 0.0088 memory: 14901 loss: 0.9754 loss_prob: 0.5194 loss_thr: 0.3668 loss_db: 0.0892 2022/11/02 21:33:06 - mmengine - INFO - Epoch(train) [837][25/63] lr: 7.3805e-04 eta: 3:50:58 time: 0.5091 data_time: 0.0286 memory: 14901 loss: 0.9043 loss_prob: 0.4703 loss_thr: 0.3531 loss_db: 0.0809 2022/11/02 21:33:08 - mmengine - INFO - Epoch(train) [837][30/63] lr: 7.3805e-04 eta: 3:50:52 time: 0.5448 data_time: 0.0426 memory: 14901 loss: 0.9947 loss_prob: 0.5214 loss_thr: 0.3841 loss_db: 0.0891 2022/11/02 21:33:11 - mmengine - INFO - Epoch(train) [837][35/63] lr: 7.3805e-04 eta: 3:50:52 time: 0.5197 data_time: 0.0304 memory: 14901 loss: 1.0366 loss_prob: 0.5422 loss_thr: 0.4008 loss_db: 0.0937 2022/11/02 21:33:13 - mmengine - INFO - Epoch(train) [837][40/63] lr: 7.3805e-04 eta: 3:50:46 time: 0.4945 data_time: 0.0143 memory: 14901 loss: 0.9665 loss_prob: 0.4992 loss_thr: 0.3805 loss_db: 0.0867 2022/11/02 21:33:16 - mmengine - INFO - Epoch(train) [837][45/63] lr: 7.3805e-04 eta: 3:50:46 time: 0.4881 data_time: 0.0097 memory: 14901 loss: 1.0025 loss_prob: 0.5244 loss_thr: 0.3866 loss_db: 0.0915 2022/11/02 21:33:18 - mmengine - INFO - Epoch(train) [837][50/63] lr: 7.3805e-04 eta: 3:50:39 time: 0.4971 data_time: 0.0200 memory: 14901 loss: 1.0188 loss_prob: 0.5361 loss_thr: 0.3887 loss_db: 0.0940 2022/11/02 21:33:21 - mmengine - INFO - Epoch(train) [837][55/63] lr: 7.3805e-04 eta: 3:50:39 time: 0.5448 data_time: 0.0274 memory: 14901 loss: 1.0357 loss_prob: 0.5527 loss_thr: 0.3857 loss_db: 0.0973 2022/11/02 21:33:23 - mmengine - INFO - Epoch(train) [837][60/63] lr: 7.3805e-04 eta: 3:50:33 time: 0.5315 data_time: 0.0180 memory: 14901 loss: 1.0542 loss_prob: 0.5645 loss_thr: 0.3922 loss_db: 0.0974 2022/11/02 21:33:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:33:30 - mmengine - INFO - Epoch(train) [838][5/63] lr: 7.3622e-04 eta: 3:50:33 time: 0.7946 data_time: 0.2277 memory: 14901 loss: 1.1022 loss_prob: 0.5794 loss_thr: 0.4245 loss_db: 0.0983 2022/11/02 21:33:33 - mmengine - INFO - Epoch(train) [838][10/63] lr: 7.3622e-04 eta: 3:50:25 time: 0.8137 data_time: 0.2242 memory: 14901 loss: 1.0640 loss_prob: 0.5530 loss_thr: 0.4135 loss_db: 0.0975 2022/11/02 21:33:36 - mmengine - INFO - Epoch(train) [838][15/63] lr: 7.3622e-04 eta: 3:50:25 time: 0.5133 data_time: 0.0115 memory: 14901 loss: 1.0241 loss_prob: 0.5377 loss_thr: 0.3917 loss_db: 0.0948 2022/11/02 21:33:38 - mmengine - INFO - Epoch(train) [838][20/63] lr: 7.3622e-04 eta: 3:50:18 time: 0.5058 data_time: 0.0143 memory: 14901 loss: 0.9752 loss_prob: 0.5088 loss_thr: 0.3804 loss_db: 0.0860 2022/11/02 21:33:41 - mmengine - INFO - Epoch(train) [838][25/63] lr: 7.3622e-04 eta: 3:50:18 time: 0.5299 data_time: 0.0368 memory: 14901 loss: 1.0147 loss_prob: 0.5296 loss_thr: 0.3944 loss_db: 0.0907 2022/11/02 21:33:43 - mmengine - INFO - Epoch(train) [838][30/63] lr: 7.3622e-04 eta: 3:50:12 time: 0.5238 data_time: 0.0390 memory: 14901 loss: 1.1820 loss_prob: 0.6568 loss_thr: 0.4217 loss_db: 0.1035 2022/11/02 21:33:46 - mmengine - INFO - Epoch(train) [838][35/63] lr: 7.3622e-04 eta: 3:50:12 time: 0.5424 data_time: 0.0127 memory: 14901 loss: 1.1692 loss_prob: 0.6556 loss_thr: 0.4108 loss_db: 0.1028 2022/11/02 21:33:49 - mmengine - INFO - Epoch(train) [838][40/63] lr: 7.3622e-04 eta: 3:50:06 time: 0.5552 data_time: 0.0114 memory: 14901 loss: 1.0313 loss_prob: 0.5500 loss_thr: 0.3866 loss_db: 0.0947 2022/11/02 21:33:52 - mmengine - INFO - Epoch(train) [838][45/63] lr: 7.3622e-04 eta: 3:50:06 time: 0.5422 data_time: 0.0135 memory: 14901 loss: 1.0039 loss_prob: 0.5333 loss_thr: 0.3787 loss_db: 0.0919 2022/11/02 21:33:55 - mmengine - INFO - Epoch(train) [838][50/63] lr: 7.3622e-04 eta: 3:50:00 time: 0.5832 data_time: 0.0265 memory: 14901 loss: 0.9522 loss_prob: 0.4915 loss_thr: 0.3749 loss_db: 0.0858 2022/11/02 21:33:57 - mmengine - INFO - Epoch(train) [838][55/63] lr: 7.3622e-04 eta: 3:50:00 time: 0.5584 data_time: 0.0288 memory: 14901 loss: 0.9808 loss_prob: 0.5106 loss_thr: 0.3810 loss_db: 0.0892 2022/11/02 21:34:00 - mmengine - INFO - Epoch(train) [838][60/63] lr: 7.3622e-04 eta: 3:49:53 time: 0.5134 data_time: 0.0136 memory: 14901 loss: 1.0067 loss_prob: 0.5321 loss_thr: 0.3815 loss_db: 0.0931 2022/11/02 21:34:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:34:06 - mmengine - INFO - Epoch(train) [839][5/63] lr: 7.3439e-04 eta: 3:49:53 time: 0.7051 data_time: 0.2144 memory: 14901 loss: 1.0916 loss_prob: 0.5884 loss_thr: 0.4013 loss_db: 0.1018 2022/11/02 21:34:09 - mmengine - INFO - Epoch(train) [839][10/63] lr: 7.3439e-04 eta: 3:49:45 time: 0.7580 data_time: 0.2141 memory: 14901 loss: 1.0699 loss_prob: 0.5701 loss_thr: 0.4008 loss_db: 0.0990 2022/11/02 21:34:11 - mmengine - INFO - Epoch(train) [839][15/63] lr: 7.3439e-04 eta: 3:49:45 time: 0.5531 data_time: 0.0120 memory: 14901 loss: 1.0020 loss_prob: 0.5229 loss_thr: 0.3870 loss_db: 0.0921 2022/11/02 21:34:14 - mmengine - INFO - Epoch(train) [839][20/63] lr: 7.3439e-04 eta: 3:49:39 time: 0.5334 data_time: 0.0156 memory: 14901 loss: 0.9949 loss_prob: 0.5152 loss_thr: 0.3910 loss_db: 0.0887 2022/11/02 21:34:17 - mmengine - INFO - Epoch(train) [839][25/63] lr: 7.3439e-04 eta: 3:49:39 time: 0.5582 data_time: 0.0515 memory: 14901 loss: 1.0537 loss_prob: 0.5560 loss_thr: 0.4008 loss_db: 0.0969 2022/11/02 21:34:20 - mmengine - INFO - Epoch(train) [839][30/63] lr: 7.3439e-04 eta: 3:49:33 time: 0.5749 data_time: 0.0499 memory: 14901 loss: 1.0444 loss_prob: 0.5561 loss_thr: 0.3911 loss_db: 0.0972 2022/11/02 21:34:22 - mmengine - INFO - Epoch(train) [839][35/63] lr: 7.3439e-04 eta: 3:49:33 time: 0.5063 data_time: 0.0146 memory: 14901 loss: 0.9947 loss_prob: 0.5247 loss_thr: 0.3799 loss_db: 0.0902 2022/11/02 21:34:25 - mmengine - INFO - Epoch(train) [839][40/63] lr: 7.3439e-04 eta: 3:49:26 time: 0.4885 data_time: 0.0145 memory: 14901 loss: 0.9834 loss_prob: 0.5143 loss_thr: 0.3803 loss_db: 0.0889 2022/11/02 21:34:27 - mmengine - INFO - Epoch(train) [839][45/63] lr: 7.3439e-04 eta: 3:49:26 time: 0.5253 data_time: 0.0132 memory: 14901 loss: 0.9312 loss_prob: 0.4803 loss_thr: 0.3675 loss_db: 0.0834 2022/11/02 21:34:30 - mmengine - INFO - Epoch(train) [839][50/63] lr: 7.3439e-04 eta: 3:49:20 time: 0.5362 data_time: 0.0299 memory: 14901 loss: 0.8972 loss_prob: 0.4608 loss_thr: 0.3554 loss_db: 0.0809 2022/11/02 21:34:33 - mmengine - INFO - Epoch(train) [839][55/63] lr: 7.3439e-04 eta: 3:49:20 time: 0.5328 data_time: 0.0306 memory: 14901 loss: 1.0380 loss_prob: 0.5498 loss_thr: 0.3918 loss_db: 0.0964 2022/11/02 21:34:35 - mmengine - INFO - Epoch(train) [839][60/63] lr: 7.3439e-04 eta: 3:49:13 time: 0.5252 data_time: 0.0137 memory: 14901 loss: 1.1137 loss_prob: 0.5987 loss_thr: 0.4113 loss_db: 0.1037 2022/11/02 21:34:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:34:42 - mmengine - INFO - Epoch(train) [840][5/63] lr: 7.3256e-04 eta: 3:49:13 time: 0.7613 data_time: 0.2417 memory: 14901 loss: 1.0666 loss_prob: 0.5612 loss_thr: 0.4094 loss_db: 0.0960 2022/11/02 21:34:44 - mmengine - INFO - Epoch(train) [840][10/63] lr: 7.3256e-04 eta: 3:49:06 time: 0.8032 data_time: 0.2485 memory: 14901 loss: 0.9922 loss_prob: 0.5126 loss_thr: 0.3906 loss_db: 0.0889 2022/11/02 21:34:47 - mmengine - INFO - Epoch(train) [840][15/63] lr: 7.3256e-04 eta: 3:49:06 time: 0.5303 data_time: 0.0163 memory: 14901 loss: 1.0061 loss_prob: 0.5190 loss_thr: 0.3962 loss_db: 0.0909 2022/11/02 21:34:50 - mmengine - INFO - Epoch(train) [840][20/63] lr: 7.3256e-04 eta: 3:48:59 time: 0.5453 data_time: 0.0124 memory: 14901 loss: 1.0165 loss_prob: 0.5275 loss_thr: 0.3974 loss_db: 0.0916 2022/11/02 21:34:52 - mmengine - INFO - Epoch(train) [840][25/63] lr: 7.3256e-04 eta: 3:48:59 time: 0.5258 data_time: 0.0176 memory: 14901 loss: 0.9783 loss_prob: 0.5048 loss_thr: 0.3865 loss_db: 0.0870 2022/11/02 21:34:55 - mmengine - INFO - Epoch(train) [840][30/63] lr: 7.3256e-04 eta: 3:48:53 time: 0.5093 data_time: 0.0367 memory: 14901 loss: 0.9971 loss_prob: 0.5142 loss_thr: 0.3932 loss_db: 0.0897 2022/11/02 21:34:57 - mmengine - INFO - Epoch(train) [840][35/63] lr: 7.3256e-04 eta: 3:48:53 time: 0.4915 data_time: 0.0334 memory: 14901 loss: 1.0465 loss_prob: 0.5464 loss_thr: 0.4036 loss_db: 0.0965 2022/11/02 21:35:00 - mmengine - INFO - Epoch(train) [840][40/63] lr: 7.3256e-04 eta: 3:48:46 time: 0.5128 data_time: 0.0134 memory: 14901 loss: 1.0131 loss_prob: 0.5273 loss_thr: 0.3930 loss_db: 0.0928 2022/11/02 21:35:03 - mmengine - INFO - Epoch(train) [840][45/63] lr: 7.3256e-04 eta: 3:48:46 time: 0.5450 data_time: 0.0114 memory: 14901 loss: 0.9527 loss_prob: 0.4913 loss_thr: 0.3758 loss_db: 0.0856 2022/11/02 21:35:06 - mmengine - INFO - Epoch(train) [840][50/63] lr: 7.3256e-04 eta: 3:48:40 time: 0.5424 data_time: 0.0213 memory: 14901 loss: 0.9563 loss_prob: 0.4912 loss_thr: 0.3816 loss_db: 0.0835 2022/11/02 21:35:08 - mmengine - INFO - Epoch(train) [840][55/63] lr: 7.3256e-04 eta: 3:48:40 time: 0.5383 data_time: 0.0300 memory: 14901 loss: 0.9903 loss_prob: 0.4994 loss_thr: 0.4056 loss_db: 0.0853 2022/11/02 21:35:11 - mmengine - INFO - Epoch(train) [840][60/63] lr: 7.3256e-04 eta: 3:48:34 time: 0.5323 data_time: 0.0240 memory: 14901 loss: 1.0376 loss_prob: 0.5313 loss_thr: 0.4138 loss_db: 0.0925 2022/11/02 21:35:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:35:12 - mmengine - INFO - Saving checkpoint at 840 epochs 2022/11/02 21:35:16 - mmengine - INFO - Epoch(val) [840][5/500] eta: 3:48:34 time: 0.0433 data_time: 0.0047 memory: 14901 2022/11/02 21:35:17 - mmengine - INFO - Epoch(val) [840][10/500] eta: 0:00:22 time: 0.0465 data_time: 0.0051 memory: 1008 2022/11/02 21:35:17 - mmengine - INFO - Epoch(val) [840][15/500] eta: 0:00:22 time: 0.0419 data_time: 0.0031 memory: 1008 2022/11/02 21:35:17 - mmengine - INFO - Epoch(val) [840][20/500] eta: 0:00:19 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/02 21:35:17 - mmengine - INFO - Epoch(val) [840][25/500] eta: 0:00:19 time: 0.0372 data_time: 0.0026 memory: 1008 2022/11/02 21:35:17 - mmengine - INFO - Epoch(val) [840][30/500] eta: 0:00:18 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/02 21:35:18 - mmengine - INFO - Epoch(val) [840][35/500] eta: 0:00:18 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/02 21:35:18 - mmengine - INFO - Epoch(val) [840][40/500] eta: 0:00:18 time: 0.0408 data_time: 0.0025 memory: 1008 2022/11/02 21:35:18 - mmengine - INFO - Epoch(val) [840][45/500] eta: 0:00:18 time: 0.0425 data_time: 0.0024 memory: 1008 2022/11/02 21:35:18 - mmengine - INFO - Epoch(val) [840][50/500] eta: 0:00:16 time: 0.0375 data_time: 0.0022 memory: 1008 2022/11/02 21:35:18 - mmengine - INFO - Epoch(val) [840][55/500] eta: 0:00:16 time: 0.0386 data_time: 0.0022 memory: 1008 2022/11/02 21:35:19 - mmengine - INFO - Epoch(val) [840][60/500] eta: 0:00:16 time: 0.0383 data_time: 0.0022 memory: 1008 2022/11/02 21:35:19 - mmengine - INFO - Epoch(val) [840][65/500] eta: 0:00:16 time: 0.0452 data_time: 0.0026 memory: 1008 2022/11/02 21:35:19 - mmengine - INFO - Epoch(val) [840][70/500] eta: 0:00:19 time: 0.0451 data_time: 0.0026 memory: 1008 2022/11/02 21:35:19 - mmengine - INFO - Epoch(val) [840][75/500] eta: 0:00:19 time: 0.0374 data_time: 0.0022 memory: 1008 2022/11/02 21:35:19 - mmengine - INFO - Epoch(val) [840][80/500] eta: 0:00:15 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 21:35:20 - mmengine - INFO - Epoch(val) [840][85/500] eta: 0:00:15 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/02 21:35:20 - mmengine - INFO - Epoch(val) [840][90/500] eta: 0:00:16 time: 0.0411 data_time: 0.0024 memory: 1008 2022/11/02 21:35:20 - mmengine - INFO - Epoch(val) [840][95/500] eta: 0:00:16 time: 0.0407 data_time: 0.0025 memory: 1008 2022/11/02 21:35:20 - mmengine - INFO - Epoch(val) [840][100/500] eta: 0:00:14 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/02 21:35:20 - mmengine - INFO - Epoch(val) [840][105/500] eta: 0:00:14 time: 0.0383 data_time: 0.0024 memory: 1008 2022/11/02 21:35:21 - mmengine - INFO - Epoch(val) [840][110/500] eta: 0:00:14 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/02 21:35:21 - mmengine - INFO - Epoch(val) [840][115/500] eta: 0:00:14 time: 0.0352 data_time: 0.0021 memory: 1008 2022/11/02 21:35:21 - mmengine - INFO - Epoch(val) [840][120/500] eta: 0:00:16 time: 0.0435 data_time: 0.0028 memory: 1008 2022/11/02 21:35:21 - mmengine - INFO - Epoch(val) [840][125/500] eta: 0:00:16 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 21:35:21 - mmengine - INFO - Epoch(val) [840][130/500] eta: 0:00:13 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/02 21:35:22 - mmengine - INFO - Epoch(val) [840][135/500] eta: 0:00:13 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/02 21:35:22 - mmengine - INFO - Epoch(val) [840][140/500] eta: 0:00:13 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 21:35:22 - mmengine - INFO - Epoch(val) [840][145/500] eta: 0:00:13 time: 0.0422 data_time: 0.0023 memory: 1008 2022/11/02 21:35:22 - mmengine - INFO - Epoch(val) [840][150/500] eta: 0:00:14 time: 0.0423 data_time: 0.0025 memory: 1008 2022/11/02 21:35:22 - mmengine - INFO - Epoch(val) [840][155/500] eta: 0:00:14 time: 0.0442 data_time: 0.0027 memory: 1008 2022/11/02 21:35:23 - mmengine - INFO - Epoch(val) [840][160/500] eta: 0:00:14 time: 0.0438 data_time: 0.0025 memory: 1008 2022/11/02 21:35:23 - mmengine - INFO - Epoch(val) [840][165/500] eta: 0:00:14 time: 0.0375 data_time: 0.0022 memory: 1008 2022/11/02 21:35:23 - mmengine - INFO - Epoch(val) [840][170/500] eta: 0:00:12 time: 0.0366 data_time: 0.0021 memory: 1008 2022/11/02 21:35:23 - mmengine - INFO - Epoch(val) [840][175/500] eta: 0:00:12 time: 0.0372 data_time: 0.0023 memory: 1008 2022/11/02 21:35:23 - mmengine - INFO - Epoch(val) [840][180/500] eta: 0:00:12 time: 0.0381 data_time: 0.0026 memory: 1008 2022/11/02 21:35:24 - mmengine - INFO - Epoch(val) [840][185/500] eta: 0:00:12 time: 0.0419 data_time: 0.0032 memory: 1008 2022/11/02 21:35:24 - mmengine - INFO - Epoch(val) [840][190/500] eta: 0:00:13 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/02 21:35:24 - mmengine - INFO - Epoch(val) [840][195/500] eta: 0:00:13 time: 0.0367 data_time: 0.0023 memory: 1008 2022/11/02 21:35:24 - mmengine - INFO - Epoch(val) [840][200/500] eta: 0:00:14 time: 0.0477 data_time: 0.0025 memory: 1008 2022/11/02 21:35:24 - mmengine - INFO - Epoch(val) [840][205/500] eta: 0:00:14 time: 0.0491 data_time: 0.0029 memory: 1008 2022/11/02 21:35:25 - mmengine - INFO - Epoch(val) [840][210/500] eta: 0:00:10 time: 0.0376 data_time: 0.0028 memory: 1008 2022/11/02 21:35:25 - mmengine - INFO - Epoch(val) [840][215/500] eta: 0:00:10 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 21:35:25 - mmengine - INFO - Epoch(val) [840][220/500] eta: 0:00:11 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/02 21:35:25 - mmengine - INFO - Epoch(val) [840][225/500] eta: 0:00:11 time: 0.0417 data_time: 0.0023 memory: 1008 2022/11/02 21:35:25 - mmengine - INFO - Epoch(val) [840][230/500] eta: 0:00:10 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 21:35:26 - mmengine - INFO - Epoch(val) [840][235/500] eta: 0:00:10 time: 0.0348 data_time: 0.0020 memory: 1008 2022/11/02 21:35:26 - mmengine - INFO - Epoch(val) [840][240/500] eta: 0:00:09 time: 0.0381 data_time: 0.0021 memory: 1008 2022/11/02 21:35:26 - mmengine - INFO - Epoch(val) [840][245/500] eta: 0:00:09 time: 0.0364 data_time: 0.0023 memory: 1008 2022/11/02 21:35:26 - mmengine - INFO - Epoch(val) [840][250/500] eta: 0:00:09 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 21:35:26 - mmengine - INFO - Epoch(val) [840][255/500] eta: 0:00:09 time: 0.0400 data_time: 0.0029 memory: 1008 2022/11/02 21:35:27 - mmengine - INFO - Epoch(val) [840][260/500] eta: 0:00:08 time: 0.0348 data_time: 0.0023 memory: 1008 2022/11/02 21:35:27 - mmengine - INFO - Epoch(val) [840][265/500] eta: 0:00:08 time: 0.0371 data_time: 0.0031 memory: 1008 2022/11/02 21:35:27 - mmengine - INFO - Epoch(val) [840][270/500] eta: 0:00:08 time: 0.0386 data_time: 0.0033 memory: 1008 2022/11/02 21:35:27 - mmengine - INFO - Epoch(val) [840][275/500] eta: 0:00:08 time: 0.0363 data_time: 0.0025 memory: 1008 2022/11/02 21:35:27 - mmengine - INFO - Epoch(val) [840][280/500] eta: 0:00:09 time: 0.0419 data_time: 0.0025 memory: 1008 2022/11/02 21:35:27 - mmengine - INFO - Epoch(val) [840][285/500] eta: 0:00:09 time: 0.0421 data_time: 0.0026 memory: 1008 2022/11/02 21:35:28 - mmengine - INFO - Epoch(val) [840][290/500] eta: 0:00:08 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 21:35:28 - mmengine - INFO - Epoch(val) [840][295/500] eta: 0:00:08 time: 0.0439 data_time: 0.0029 memory: 1008 2022/11/02 21:35:28 - mmengine - INFO - Epoch(val) [840][300/500] eta: 0:00:08 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 21:35:28 - mmengine - INFO - Epoch(val) [840][305/500] eta: 0:00:08 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/02 21:35:29 - mmengine - INFO - Epoch(val) [840][310/500] eta: 0:00:07 time: 0.0380 data_time: 0.0026 memory: 1008 2022/11/02 21:35:29 - mmengine - INFO - Epoch(val) [840][315/500] eta: 0:00:07 time: 0.0396 data_time: 0.0024 memory: 1008 2022/11/02 21:35:29 - mmengine - INFO - Epoch(val) [840][320/500] eta: 0:00:07 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/02 21:35:29 - mmengine - INFO - Epoch(val) [840][325/500] eta: 0:00:07 time: 0.0508 data_time: 0.0030 memory: 1008 2022/11/02 21:35:29 - mmengine - INFO - Epoch(val) [840][330/500] eta: 0:00:08 time: 0.0496 data_time: 0.0030 memory: 1008 2022/11/02 21:35:30 - mmengine - INFO - Epoch(val) [840][335/500] eta: 0:00:08 time: 0.0366 data_time: 0.0026 memory: 1008 2022/11/02 21:35:30 - mmengine - INFO - Epoch(val) [840][340/500] eta: 0:00:07 time: 0.0467 data_time: 0.0025 memory: 1008 2022/11/02 21:35:30 - mmengine - INFO - Epoch(val) [840][345/500] eta: 0:00:07 time: 0.0515 data_time: 0.0029 memory: 1008 2022/11/02 21:35:30 - mmengine - INFO - Epoch(val) [840][350/500] eta: 0:00:07 time: 0.0497 data_time: 0.0031 memory: 1008 2022/11/02 21:35:31 - mmengine - INFO - Epoch(val) [840][355/500] eta: 0:00:07 time: 0.0457 data_time: 0.0028 memory: 1008 2022/11/02 21:35:31 - mmengine - INFO - Epoch(val) [840][360/500] eta: 0:00:05 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 21:35:31 - mmengine - INFO - Epoch(val) [840][365/500] eta: 0:00:05 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/02 21:35:31 - mmengine - INFO - Epoch(val) [840][370/500] eta: 0:00:04 time: 0.0380 data_time: 0.0026 memory: 1008 2022/11/02 21:35:31 - mmengine - INFO - Epoch(val) [840][375/500] eta: 0:00:04 time: 0.0374 data_time: 0.0028 memory: 1008 2022/11/02 21:35:32 - mmengine - INFO - Epoch(val) [840][380/500] eta: 0:00:04 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/02 21:35:32 - mmengine - INFO - Epoch(val) [840][385/500] eta: 0:00:04 time: 0.0417 data_time: 0.0031 memory: 1008 2022/11/02 21:35:32 - mmengine - INFO - Epoch(val) [840][390/500] eta: 0:00:04 time: 0.0380 data_time: 0.0029 memory: 1008 2022/11/02 21:35:32 - mmengine - INFO - Epoch(val) [840][395/500] eta: 0:00:04 time: 0.0366 data_time: 0.0026 memory: 1008 2022/11/02 21:35:32 - mmengine - INFO - Epoch(val) [840][400/500] eta: 0:00:03 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 21:35:32 - mmengine - INFO - Epoch(val) [840][405/500] eta: 0:00:03 time: 0.0396 data_time: 0.0025 memory: 1008 2022/11/02 21:35:33 - mmengine - INFO - Epoch(val) [840][410/500] eta: 0:00:03 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 21:35:33 - mmengine - INFO - Epoch(val) [840][415/500] eta: 0:00:03 time: 0.0386 data_time: 0.0025 memory: 1008 2022/11/02 21:35:33 - mmengine - INFO - Epoch(val) [840][420/500] eta: 0:00:02 time: 0.0340 data_time: 0.0023 memory: 1008 2022/11/02 21:35:33 - mmengine - INFO - Epoch(val) [840][425/500] eta: 0:00:02 time: 0.0333 data_time: 0.0021 memory: 1008 2022/11/02 21:35:33 - mmengine - INFO - Epoch(val) [840][430/500] eta: 0:00:02 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/02 21:35:34 - mmengine - INFO - Epoch(val) [840][435/500] eta: 0:00:02 time: 0.0350 data_time: 0.0022 memory: 1008 2022/11/02 21:35:34 - mmengine - INFO - Epoch(val) [840][440/500] eta: 0:00:02 time: 0.0346 data_time: 0.0021 memory: 1008 2022/11/02 21:35:34 - mmengine - INFO - Epoch(val) [840][445/500] eta: 0:00:02 time: 0.0389 data_time: 0.0028 memory: 1008 2022/11/02 21:35:34 - mmengine - INFO - Epoch(val) [840][450/500] eta: 0:00:02 time: 0.0404 data_time: 0.0030 memory: 1008 2022/11/02 21:35:34 - mmengine - INFO - Epoch(val) [840][455/500] eta: 0:00:02 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 21:35:35 - mmengine - INFO - Epoch(val) [840][460/500] eta: 0:00:01 time: 0.0362 data_time: 0.0025 memory: 1008 2022/11/02 21:35:35 - mmengine - INFO - Epoch(val) [840][465/500] eta: 0:00:01 time: 0.0325 data_time: 0.0022 memory: 1008 2022/11/02 21:35:35 - mmengine - INFO - Epoch(val) [840][470/500] eta: 0:00:01 time: 0.0345 data_time: 0.0023 memory: 1008 2022/11/02 21:35:35 - mmengine - INFO - Epoch(val) [840][475/500] eta: 0:00:01 time: 0.0346 data_time: 0.0025 memory: 1008 2022/11/02 21:35:35 - mmengine - INFO - Epoch(val) [840][480/500] eta: 0:00:00 time: 0.0338 data_time: 0.0023 memory: 1008 2022/11/02 21:35:35 - mmengine - INFO - Epoch(val) [840][485/500] eta: 0:00:00 time: 0.0355 data_time: 0.0021 memory: 1008 2022/11/02 21:35:36 - mmengine - INFO - Epoch(val) [840][490/500] eta: 0:00:00 time: 0.0376 data_time: 0.0022 memory: 1008 2022/11/02 21:35:36 - mmengine - INFO - Epoch(val) [840][495/500] eta: 0:00:00 time: 0.0378 data_time: 0.0021 memory: 1008 2022/11/02 21:35:36 - mmengine - INFO - Epoch(val) [840][500/500] eta: 0:00:00 time: 0.0355 data_time: 0.0020 memory: 1008 2022/11/02 21:35:36 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8406, precision: 0.7532, hmean: 0.7945 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8406, precision: 0.7951, hmean: 0.8172 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8392, precision: 0.8229, hmean: 0.8310 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8349, precision: 0.8521, hmean: 0.8434 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8214, precision: 0.8758, hmean: 0.8477 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7053, precision: 0.9237, hmean: 0.7999 2022/11/02 21:35:36 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1180, precision: 0.9800, hmean: 0.2106 2022/11/02 21:35:36 - mmengine - INFO - Epoch(val) [840][500/500] icdar/precision: 0.8758 icdar/recall: 0.8214 icdar/hmean: 0.8477 2022/11/02 21:35:42 - mmengine - INFO - Epoch(train) [841][5/63] lr: 7.3073e-04 eta: 0:00:00 time: 0.8702 data_time: 0.2359 memory: 14901 loss: 1.1036 loss_prob: 0.5804 loss_thr: 0.4217 loss_db: 0.1015 2022/11/02 21:35:45 - mmengine - INFO - Epoch(train) [841][10/63] lr: 7.3073e-04 eta: 3:48:26 time: 0.8797 data_time: 0.2349 memory: 14901 loss: 1.0640 loss_prob: 0.5629 loss_thr: 0.4044 loss_db: 0.0967 2022/11/02 21:35:48 - mmengine - INFO - Epoch(train) [841][15/63] lr: 7.3073e-04 eta: 3:48:26 time: 0.5234 data_time: 0.0106 memory: 14901 loss: 1.0345 loss_prob: 0.5435 loss_thr: 0.3980 loss_db: 0.0931 2022/11/02 21:35:50 - mmengine - INFO - Epoch(train) [841][20/63] lr: 7.3073e-04 eta: 3:48:20 time: 0.5627 data_time: 0.0113 memory: 14901 loss: 1.0038 loss_prob: 0.5211 loss_thr: 0.3917 loss_db: 0.0909 2022/11/02 21:35:53 - mmengine - INFO - Epoch(train) [841][25/63] lr: 7.3073e-04 eta: 3:48:20 time: 0.5938 data_time: 0.0360 memory: 14901 loss: 0.9710 loss_prob: 0.5030 loss_thr: 0.3806 loss_db: 0.0874 2022/11/02 21:35:56 - mmengine - INFO - Epoch(train) [841][30/63] lr: 7.3073e-04 eta: 3:48:14 time: 0.5744 data_time: 0.0364 memory: 14901 loss: 0.9798 loss_prob: 0.5069 loss_thr: 0.3855 loss_db: 0.0873 2022/11/02 21:35:59 - mmengine - INFO - Epoch(train) [841][35/63] lr: 7.3073e-04 eta: 3:48:14 time: 0.5265 data_time: 0.0165 memory: 14901 loss: 1.0536 loss_prob: 0.5523 loss_thr: 0.4065 loss_db: 0.0948 2022/11/02 21:36:01 - mmengine - INFO - Epoch(train) [841][40/63] lr: 7.3073e-04 eta: 3:48:07 time: 0.4950 data_time: 0.0152 memory: 14901 loss: 1.0333 loss_prob: 0.5459 loss_thr: 0.3938 loss_db: 0.0935 2022/11/02 21:36:04 - mmengine - INFO - Epoch(train) [841][45/63] lr: 7.3073e-04 eta: 3:48:07 time: 0.5386 data_time: 0.0130 memory: 14901 loss: 1.0257 loss_prob: 0.5520 loss_thr: 0.3811 loss_db: 0.0926 2022/11/02 21:36:07 - mmengine - INFO - Epoch(train) [841][50/63] lr: 7.3073e-04 eta: 3:48:01 time: 0.5842 data_time: 0.0268 memory: 14901 loss: 0.9900 loss_prob: 0.5277 loss_thr: 0.3731 loss_db: 0.0891 2022/11/02 21:36:10 - mmengine - INFO - Epoch(train) [841][55/63] lr: 7.3073e-04 eta: 3:48:01 time: 0.5462 data_time: 0.0268 memory: 14901 loss: 1.0615 loss_prob: 0.5667 loss_thr: 0.3956 loss_db: 0.0992 2022/11/02 21:36:12 - mmengine - INFO - Epoch(train) [841][60/63] lr: 7.3073e-04 eta: 3:47:55 time: 0.4988 data_time: 0.0135 memory: 14901 loss: 1.1292 loss_prob: 0.6039 loss_thr: 0.4214 loss_db: 0.1038 2022/11/02 21:36:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:36:18 - mmengine - INFO - Epoch(train) [842][5/63] lr: 7.2889e-04 eta: 3:47:55 time: 0.7438 data_time: 0.1933 memory: 14901 loss: 0.9801 loss_prob: 0.5132 loss_thr: 0.3795 loss_db: 0.0874 2022/11/02 21:36:21 - mmengine - INFO - Epoch(train) [842][10/63] lr: 7.2889e-04 eta: 3:47:47 time: 0.7895 data_time: 0.1996 memory: 14901 loss: 1.0165 loss_prob: 0.5317 loss_thr: 0.3931 loss_db: 0.0917 2022/11/02 21:36:25 - mmengine - INFO - Epoch(train) [842][15/63] lr: 7.2889e-04 eta: 3:47:47 time: 0.6212 data_time: 0.0150 memory: 14901 loss: 1.0055 loss_prob: 0.5202 loss_thr: 0.3941 loss_db: 0.0912 2022/11/02 21:36:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:36:28 - mmengine - INFO - Epoch(train) [842][20/63] lr: 7.2889e-04 eta: 3:47:41 time: 0.6276 data_time: 0.0081 memory: 14901 loss: 1.0008 loss_prob: 0.5167 loss_thr: 0.3921 loss_db: 0.0919 2022/11/02 21:36:30 - mmengine - INFO - Epoch(train) [842][25/63] lr: 7.2889e-04 eta: 3:47:41 time: 0.5499 data_time: 0.0117 memory: 14901 loss: 0.9665 loss_prob: 0.5035 loss_thr: 0.3743 loss_db: 0.0886 2022/11/02 21:36:33 - mmengine - INFO - Epoch(train) [842][30/63] lr: 7.2889e-04 eta: 3:47:35 time: 0.5190 data_time: 0.0398 memory: 14901 loss: 1.0204 loss_prob: 0.5403 loss_thr: 0.3852 loss_db: 0.0949 2022/11/02 21:36:35 - mmengine - INFO - Epoch(train) [842][35/63] lr: 7.2889e-04 eta: 3:47:35 time: 0.5266 data_time: 0.0404 memory: 14901 loss: 1.0041 loss_prob: 0.5227 loss_thr: 0.3893 loss_db: 0.0921 2022/11/02 21:36:38 - mmengine - INFO - Epoch(train) [842][40/63] lr: 7.2889e-04 eta: 3:47:28 time: 0.5294 data_time: 0.0123 memory: 14901 loss: 0.9612 loss_prob: 0.5027 loss_thr: 0.3738 loss_db: 0.0847 2022/11/02 21:36:40 - mmengine - INFO - Epoch(train) [842][45/63] lr: 7.2889e-04 eta: 3:47:28 time: 0.5045 data_time: 0.0079 memory: 14901 loss: 0.9995 loss_prob: 0.5331 loss_thr: 0.3758 loss_db: 0.0906 2022/11/02 21:36:43 - mmengine - INFO - Epoch(train) [842][50/63] lr: 7.2889e-04 eta: 3:47:22 time: 0.5060 data_time: 0.0121 memory: 14901 loss: 0.9110 loss_prob: 0.4694 loss_thr: 0.3589 loss_db: 0.0827 2022/11/02 21:36:46 - mmengine - INFO - Epoch(train) [842][55/63] lr: 7.2889e-04 eta: 3:47:22 time: 0.5095 data_time: 0.0280 memory: 14901 loss: 0.9992 loss_prob: 0.5177 loss_thr: 0.3910 loss_db: 0.0904 2022/11/02 21:36:49 - mmengine - INFO - Epoch(train) [842][60/63] lr: 7.2889e-04 eta: 3:47:15 time: 0.5624 data_time: 0.0256 memory: 14901 loss: 1.0602 loss_prob: 0.5558 loss_thr: 0.4070 loss_db: 0.0974 2022/11/02 21:36:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:36:55 - mmengine - INFO - Epoch(train) [843][5/63] lr: 7.2706e-04 eta: 3:47:15 time: 0.7679 data_time: 0.2324 memory: 14901 loss: 1.0724 loss_prob: 0.5674 loss_thr: 0.4081 loss_db: 0.0970 2022/11/02 21:36:58 - mmengine - INFO - Epoch(train) [843][10/63] lr: 7.2706e-04 eta: 3:47:08 time: 0.7926 data_time: 0.2323 memory: 14901 loss: 0.9031 loss_prob: 0.4659 loss_thr: 0.3557 loss_db: 0.0816 2022/11/02 21:37:01 - mmengine - INFO - Epoch(train) [843][15/63] lr: 7.2706e-04 eta: 3:47:08 time: 0.6467 data_time: 0.0129 memory: 14901 loss: 0.9673 loss_prob: 0.5108 loss_thr: 0.3681 loss_db: 0.0884 2022/11/02 21:37:04 - mmengine - INFO - Epoch(train) [843][20/63] lr: 7.2706e-04 eta: 3:47:02 time: 0.6113 data_time: 0.0163 memory: 14901 loss: 1.0023 loss_prob: 0.5192 loss_thr: 0.3922 loss_db: 0.0909 2022/11/02 21:37:07 - mmengine - INFO - Epoch(train) [843][25/63] lr: 7.2706e-04 eta: 3:47:02 time: 0.5636 data_time: 0.0217 memory: 14901 loss: 0.9334 loss_prob: 0.4729 loss_thr: 0.3760 loss_db: 0.0845 2022/11/02 21:37:10 - mmengine - INFO - Epoch(train) [843][30/63] lr: 7.2706e-04 eta: 3:46:55 time: 0.5501 data_time: 0.0317 memory: 14901 loss: 0.9627 loss_prob: 0.4977 loss_thr: 0.3766 loss_db: 0.0884 2022/11/02 21:37:12 - mmengine - INFO - Epoch(train) [843][35/63] lr: 7.2706e-04 eta: 3:46:55 time: 0.5041 data_time: 0.0267 memory: 14901 loss: 1.0110 loss_prob: 0.5267 loss_thr: 0.3910 loss_db: 0.0933 2022/11/02 21:37:15 - mmengine - INFO - Epoch(train) [843][40/63] lr: 7.2706e-04 eta: 3:46:49 time: 0.5609 data_time: 0.0158 memory: 14901 loss: 0.9702 loss_prob: 0.5106 loss_thr: 0.3717 loss_db: 0.0879 2022/11/02 21:37:18 - mmengine - INFO - Epoch(train) [843][45/63] lr: 7.2706e-04 eta: 3:46:49 time: 0.5910 data_time: 0.0168 memory: 14901 loss: 0.9818 loss_prob: 0.5229 loss_thr: 0.3690 loss_db: 0.0899 2022/11/02 21:37:21 - mmengine - INFO - Epoch(train) [843][50/63] lr: 7.2706e-04 eta: 3:46:43 time: 0.5845 data_time: 0.0253 memory: 14901 loss: 1.0388 loss_prob: 0.5449 loss_thr: 0.3988 loss_db: 0.0950 2022/11/02 21:37:24 - mmengine - INFO - Epoch(train) [843][55/63] lr: 7.2706e-04 eta: 3:46:43 time: 0.5926 data_time: 0.0294 memory: 14901 loss: 0.9977 loss_prob: 0.5158 loss_thr: 0.3925 loss_db: 0.0893 2022/11/02 21:37:27 - mmengine - INFO - Epoch(train) [843][60/63] lr: 7.2706e-04 eta: 3:46:37 time: 0.5503 data_time: 0.0208 memory: 14901 loss: 1.0210 loss_prob: 0.5390 loss_thr: 0.3891 loss_db: 0.0929 2022/11/02 21:37:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:37:33 - mmengine - INFO - Epoch(train) [844][5/63] lr: 7.2523e-04 eta: 3:46:37 time: 0.7045 data_time: 0.2362 memory: 14901 loss: 1.0603 loss_prob: 0.5628 loss_thr: 0.4001 loss_db: 0.0973 2022/11/02 21:37:35 - mmengine - INFO - Epoch(train) [844][10/63] lr: 7.2523e-04 eta: 3:46:29 time: 0.7356 data_time: 0.2354 memory: 14901 loss: 1.0713 loss_prob: 0.5743 loss_thr: 0.3992 loss_db: 0.0977 2022/11/02 21:37:38 - mmengine - INFO - Epoch(train) [844][15/63] lr: 7.2523e-04 eta: 3:46:29 time: 0.5399 data_time: 0.0133 memory: 14901 loss: 1.1270 loss_prob: 0.6149 loss_thr: 0.4115 loss_db: 0.1006 2022/11/02 21:37:41 - mmengine - INFO - Epoch(train) [844][20/63] lr: 7.2523e-04 eta: 3:46:23 time: 0.5879 data_time: 0.0161 memory: 14901 loss: 1.1105 loss_prob: 0.5865 loss_thr: 0.4247 loss_db: 0.0993 2022/11/02 21:37:44 - mmengine - INFO - Epoch(train) [844][25/63] lr: 7.2523e-04 eta: 3:46:23 time: 0.5984 data_time: 0.0474 memory: 14901 loss: 1.0222 loss_prob: 0.5326 loss_thr: 0.3994 loss_db: 0.0902 2022/11/02 21:37:47 - mmengine - INFO - Epoch(train) [844][30/63] lr: 7.2523e-04 eta: 3:46:16 time: 0.5680 data_time: 0.0438 memory: 14901 loss: 0.9940 loss_prob: 0.5227 loss_thr: 0.3825 loss_db: 0.0888 2022/11/02 21:37:50 - mmengine - INFO - Epoch(train) [844][35/63] lr: 7.2523e-04 eta: 3:46:16 time: 0.6173 data_time: 0.0106 memory: 14901 loss: 1.0211 loss_prob: 0.5358 loss_thr: 0.3901 loss_db: 0.0952 2022/11/02 21:37:53 - mmengine - INFO - Epoch(train) [844][40/63] lr: 7.2523e-04 eta: 3:46:10 time: 0.6021 data_time: 0.0081 memory: 14901 loss: 1.0012 loss_prob: 0.5275 loss_thr: 0.3813 loss_db: 0.0924 2022/11/02 21:37:55 - mmengine - INFO - Epoch(train) [844][45/63] lr: 7.2523e-04 eta: 3:46:10 time: 0.5020 data_time: 0.0118 memory: 14901 loss: 0.9857 loss_prob: 0.5190 loss_thr: 0.3770 loss_db: 0.0897 2022/11/02 21:37:58 - mmengine - INFO - Epoch(train) [844][50/63] lr: 7.2523e-04 eta: 3:46:04 time: 0.5120 data_time: 0.0307 memory: 14901 loss: 0.9788 loss_prob: 0.5090 loss_thr: 0.3806 loss_db: 0.0893 2022/11/02 21:38:00 - mmengine - INFO - Epoch(train) [844][55/63] lr: 7.2523e-04 eta: 3:46:04 time: 0.5193 data_time: 0.0271 memory: 14901 loss: 0.9896 loss_prob: 0.5116 loss_thr: 0.3896 loss_db: 0.0884 2022/11/02 21:38:03 - mmengine - INFO - Epoch(train) [844][60/63] lr: 7.2523e-04 eta: 3:45:58 time: 0.5375 data_time: 0.0102 memory: 14901 loss: 1.0117 loss_prob: 0.5289 loss_thr: 0.3926 loss_db: 0.0902 2022/11/02 21:38:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:38:10 - mmengine - INFO - Epoch(train) [845][5/63] lr: 7.2340e-04 eta: 3:45:58 time: 0.7742 data_time: 0.2291 memory: 14901 loss: 1.0229 loss_prob: 0.5365 loss_thr: 0.3918 loss_db: 0.0945 2022/11/02 21:38:13 - mmengine - INFO - Epoch(train) [845][10/63] lr: 7.2340e-04 eta: 3:45:50 time: 0.8038 data_time: 0.2366 memory: 14901 loss: 1.1396 loss_prob: 0.6033 loss_thr: 0.4323 loss_db: 0.1039 2022/11/02 21:38:15 - mmengine - INFO - Epoch(train) [845][15/63] lr: 7.2340e-04 eta: 3:45:50 time: 0.4945 data_time: 0.0191 memory: 14901 loss: 1.0679 loss_prob: 0.5608 loss_thr: 0.4108 loss_db: 0.0963 2022/11/02 21:38:18 - mmengine - INFO - Epoch(train) [845][20/63] lr: 7.2340e-04 eta: 3:45:43 time: 0.5188 data_time: 0.0119 memory: 14901 loss: 0.9881 loss_prob: 0.5107 loss_thr: 0.3876 loss_db: 0.0898 2022/11/02 21:38:20 - mmengine - INFO - Epoch(train) [845][25/63] lr: 7.2340e-04 eta: 3:45:43 time: 0.5306 data_time: 0.0262 memory: 14901 loss: 1.0574 loss_prob: 0.5575 loss_thr: 0.4003 loss_db: 0.0996 2022/11/02 21:38:23 - mmengine - INFO - Epoch(train) [845][30/63] lr: 7.2340e-04 eta: 3:45:37 time: 0.5219 data_time: 0.0439 memory: 14901 loss: 1.0065 loss_prob: 0.5327 loss_thr: 0.3804 loss_db: 0.0934 2022/11/02 21:38:26 - mmengine - INFO - Epoch(train) [845][35/63] lr: 7.2340e-04 eta: 3:45:37 time: 0.5257 data_time: 0.0288 memory: 14901 loss: 1.0092 loss_prob: 0.5280 loss_thr: 0.3909 loss_db: 0.0903 2022/11/02 21:38:29 - mmengine - INFO - Epoch(train) [845][40/63] lr: 7.2340e-04 eta: 3:45:31 time: 0.6346 data_time: 0.0092 memory: 14901 loss: 1.0248 loss_prob: 0.5355 loss_thr: 0.3980 loss_db: 0.0913 2022/11/02 21:38:32 - mmengine - INFO - Epoch(train) [845][45/63] lr: 7.2340e-04 eta: 3:45:31 time: 0.6416 data_time: 0.0097 memory: 14901 loss: 0.9922 loss_prob: 0.5133 loss_thr: 0.3894 loss_db: 0.0895 2022/11/02 21:38:35 - mmengine - INFO - Epoch(train) [845][50/63] lr: 7.2340e-04 eta: 3:45:25 time: 0.5179 data_time: 0.0242 memory: 14901 loss: 0.9907 loss_prob: 0.5096 loss_thr: 0.3894 loss_db: 0.0916 2022/11/02 21:38:38 - mmengine - INFO - Epoch(train) [845][55/63] lr: 7.2340e-04 eta: 3:45:25 time: 0.5575 data_time: 0.0298 memory: 14901 loss: 1.0302 loss_prob: 0.5390 loss_thr: 0.3977 loss_db: 0.0935 2022/11/02 21:38:40 - mmengine - INFO - Epoch(train) [845][60/63] lr: 7.2340e-04 eta: 3:45:18 time: 0.5576 data_time: 0.0174 memory: 14901 loss: 1.0681 loss_prob: 0.5681 loss_thr: 0.4053 loss_db: 0.0947 2022/11/02 21:38:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:38:47 - mmengine - INFO - Epoch(train) [846][5/63] lr: 7.2156e-04 eta: 3:45:18 time: 0.7970 data_time: 0.2245 memory: 14901 loss: 1.1172 loss_prob: 0.6083 loss_thr: 0.4104 loss_db: 0.0985 2022/11/02 21:38:50 - mmengine - INFO - Epoch(train) [846][10/63] lr: 7.2156e-04 eta: 3:45:11 time: 0.7966 data_time: 0.2246 memory: 14901 loss: 1.0909 loss_prob: 0.5843 loss_thr: 0.4096 loss_db: 0.0970 2022/11/02 21:38:52 - mmengine - INFO - Epoch(train) [846][15/63] lr: 7.2156e-04 eta: 3:45:11 time: 0.4783 data_time: 0.0130 memory: 14901 loss: 1.0308 loss_prob: 0.5291 loss_thr: 0.4108 loss_db: 0.0909 2022/11/02 21:38:55 - mmengine - INFO - Epoch(train) [846][20/63] lr: 7.2156e-04 eta: 3:45:04 time: 0.5200 data_time: 0.0164 memory: 14901 loss: 1.0082 loss_prob: 0.5206 loss_thr: 0.3987 loss_db: 0.0889 2022/11/02 21:38:57 - mmengine - INFO - Epoch(train) [846][25/63] lr: 7.2156e-04 eta: 3:45:04 time: 0.5248 data_time: 0.0220 memory: 14901 loss: 0.9426 loss_prob: 0.4819 loss_thr: 0.3767 loss_db: 0.0840 2022/11/02 21:39:00 - mmengine - INFO - Epoch(train) [846][30/63] lr: 7.2156e-04 eta: 3:44:58 time: 0.5216 data_time: 0.0426 memory: 14901 loss: 0.8785 loss_prob: 0.4469 loss_thr: 0.3516 loss_db: 0.0801 2022/11/02 21:39:03 - mmengine - INFO - Epoch(train) [846][35/63] lr: 7.2156e-04 eta: 3:44:58 time: 0.5360 data_time: 0.0338 memory: 14901 loss: 0.9951 loss_prob: 0.5296 loss_thr: 0.3731 loss_db: 0.0924 2022/11/02 21:39:05 - mmengine - INFO - Epoch(train) [846][40/63] lr: 7.2156e-04 eta: 3:44:51 time: 0.5324 data_time: 0.0100 memory: 14901 loss: 1.0212 loss_prob: 0.5402 loss_thr: 0.3879 loss_db: 0.0931 2022/11/02 21:39:08 - mmengine - INFO - Epoch(train) [846][45/63] lr: 7.2156e-04 eta: 3:44:51 time: 0.5197 data_time: 0.0132 memory: 14901 loss: 0.9501 loss_prob: 0.4904 loss_thr: 0.3740 loss_db: 0.0857 2022/11/02 21:39:12 - mmengine - INFO - Epoch(train) [846][50/63] lr: 7.2156e-04 eta: 3:44:45 time: 0.6261 data_time: 0.0295 memory: 14901 loss: 1.0395 loss_prob: 0.5556 loss_thr: 0.3876 loss_db: 0.0964 2022/11/02 21:39:14 - mmengine - INFO - Epoch(train) [846][55/63] lr: 7.2156e-04 eta: 3:44:45 time: 0.6270 data_time: 0.0319 memory: 14901 loss: 1.0981 loss_prob: 0.5847 loss_thr: 0.4109 loss_db: 0.1025 2022/11/02 21:39:17 - mmengine - INFO - Epoch(train) [846][60/63] lr: 7.2156e-04 eta: 3:44:39 time: 0.5187 data_time: 0.0146 memory: 14901 loss: 1.0854 loss_prob: 0.5697 loss_thr: 0.4175 loss_db: 0.0982 2022/11/02 21:39:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:39:24 - mmengine - INFO - Epoch(train) [847][5/63] lr: 7.1973e-04 eta: 3:44:39 time: 0.8365 data_time: 0.2270 memory: 14901 loss: 1.0375 loss_prob: 0.5439 loss_thr: 0.3989 loss_db: 0.0947 2022/11/02 21:39:27 - mmengine - INFO - Epoch(train) [847][10/63] lr: 7.1973e-04 eta: 3:44:31 time: 0.8425 data_time: 0.2263 memory: 14901 loss: 1.0813 loss_prob: 0.5747 loss_thr: 0.4064 loss_db: 0.1003 2022/11/02 21:39:29 - mmengine - INFO - Epoch(train) [847][15/63] lr: 7.1973e-04 eta: 3:44:31 time: 0.5046 data_time: 0.0121 memory: 14901 loss: 0.9962 loss_prob: 0.5227 loss_thr: 0.3834 loss_db: 0.0901 2022/11/02 21:39:32 - mmengine - INFO - Epoch(train) [847][20/63] lr: 7.1973e-04 eta: 3:44:25 time: 0.5076 data_time: 0.0124 memory: 14901 loss: 0.9517 loss_prob: 0.4986 loss_thr: 0.3671 loss_db: 0.0860 2022/11/02 21:39:35 - mmengine - INFO - Epoch(train) [847][25/63] lr: 7.1973e-04 eta: 3:44:25 time: 0.5565 data_time: 0.0307 memory: 14901 loss: 1.0529 loss_prob: 0.5588 loss_thr: 0.3970 loss_db: 0.0971 2022/11/02 21:39:37 - mmengine - INFO - Epoch(train) [847][30/63] lr: 7.1973e-04 eta: 3:44:19 time: 0.5695 data_time: 0.0422 memory: 14901 loss: 0.9979 loss_prob: 0.5180 loss_thr: 0.3885 loss_db: 0.0913 2022/11/02 21:39:40 - mmengine - INFO - Epoch(train) [847][35/63] lr: 7.1973e-04 eta: 3:44:19 time: 0.5348 data_time: 0.0216 memory: 14901 loss: 1.0028 loss_prob: 0.5338 loss_thr: 0.3790 loss_db: 0.0901 2022/11/02 21:39:43 - mmengine - INFO - Epoch(train) [847][40/63] lr: 7.1973e-04 eta: 3:44:13 time: 0.5483 data_time: 0.0107 memory: 14901 loss: 0.9635 loss_prob: 0.5118 loss_thr: 0.3654 loss_db: 0.0864 2022/11/02 21:39:45 - mmengine - INFO - Epoch(train) [847][45/63] lr: 7.1973e-04 eta: 3:44:13 time: 0.5417 data_time: 0.0124 memory: 14901 loss: 0.9154 loss_prob: 0.4690 loss_thr: 0.3642 loss_db: 0.0822 2022/11/02 21:39:48 - mmengine - INFO - Epoch(train) [847][50/63] lr: 7.1973e-04 eta: 3:44:06 time: 0.5115 data_time: 0.0247 memory: 14901 loss: 0.9319 loss_prob: 0.4763 loss_thr: 0.3735 loss_db: 0.0820 2022/11/02 21:39:51 - mmengine - INFO - Epoch(train) [847][55/63] lr: 7.1973e-04 eta: 3:44:06 time: 0.6100 data_time: 0.0306 memory: 14901 loss: 0.9659 loss_prob: 0.4933 loss_thr: 0.3860 loss_db: 0.0867 2022/11/02 21:39:54 - mmengine - INFO - Epoch(train) [847][60/63] lr: 7.1973e-04 eta: 3:44:00 time: 0.6443 data_time: 0.0167 memory: 14901 loss: 1.1034 loss_prob: 0.5781 loss_thr: 0.4255 loss_db: 0.0999 2022/11/02 21:39:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:40:01 - mmengine - INFO - Epoch(train) [848][5/63] lr: 7.1789e-04 eta: 3:44:00 time: 0.7888 data_time: 0.2360 memory: 14901 loss: 1.0587 loss_prob: 0.5620 loss_thr: 0.3999 loss_db: 0.0968 2022/11/02 21:40:04 - mmengine - INFO - Epoch(train) [848][10/63] lr: 7.1789e-04 eta: 3:43:52 time: 0.7732 data_time: 0.2366 memory: 14901 loss: 0.9679 loss_prob: 0.5109 loss_thr: 0.3682 loss_db: 0.0888 2022/11/02 21:40:06 - mmengine - INFO - Epoch(train) [848][15/63] lr: 7.1789e-04 eta: 3:43:52 time: 0.5350 data_time: 0.0133 memory: 14901 loss: 1.0317 loss_prob: 0.5491 loss_thr: 0.3879 loss_db: 0.0947 2022/11/02 21:40:09 - mmengine - INFO - Epoch(train) [848][20/63] lr: 7.1789e-04 eta: 3:43:46 time: 0.5525 data_time: 0.0132 memory: 14901 loss: 1.0312 loss_prob: 0.5432 loss_thr: 0.3932 loss_db: 0.0948 2022/11/02 21:40:12 - mmengine - INFO - Epoch(train) [848][25/63] lr: 7.1789e-04 eta: 3:43:46 time: 0.5503 data_time: 0.0375 memory: 14901 loss: 1.0307 loss_prob: 0.5392 loss_thr: 0.3976 loss_db: 0.0939 2022/11/02 21:40:15 - mmengine - INFO - Epoch(train) [848][30/63] lr: 7.1789e-04 eta: 3:43:40 time: 0.5348 data_time: 0.0341 memory: 14901 loss: 1.0882 loss_prob: 0.5768 loss_thr: 0.4108 loss_db: 0.1006 2022/11/02 21:40:17 - mmengine - INFO - Epoch(train) [848][35/63] lr: 7.1789e-04 eta: 3:43:40 time: 0.5304 data_time: 0.0148 memory: 14901 loss: 1.1112 loss_prob: 0.5916 loss_thr: 0.4164 loss_db: 0.1032 2022/11/02 21:40:20 - mmengine - INFO - Epoch(train) [848][40/63] lr: 7.1789e-04 eta: 3:43:33 time: 0.5049 data_time: 0.0183 memory: 14901 loss: 1.0474 loss_prob: 0.5486 loss_thr: 0.4039 loss_db: 0.0948 2022/11/02 21:40:22 - mmengine - INFO - Epoch(train) [848][45/63] lr: 7.1789e-04 eta: 3:43:33 time: 0.4913 data_time: 0.0093 memory: 14901 loss: 0.9964 loss_prob: 0.5187 loss_thr: 0.3874 loss_db: 0.0903 2022/11/02 21:40:25 - mmengine - INFO - Epoch(train) [848][50/63] lr: 7.1789e-04 eta: 3:43:27 time: 0.5561 data_time: 0.0259 memory: 14901 loss: 0.9374 loss_prob: 0.4902 loss_thr: 0.3608 loss_db: 0.0863 2022/11/02 21:40:27 - mmengine - INFO - Epoch(train) [848][55/63] lr: 7.1789e-04 eta: 3:43:27 time: 0.5398 data_time: 0.0282 memory: 14901 loss: 1.0166 loss_prob: 0.5506 loss_thr: 0.3727 loss_db: 0.0932 2022/11/02 21:40:30 - mmengine - INFO - Epoch(train) [848][60/63] lr: 7.1789e-04 eta: 3:43:21 time: 0.5066 data_time: 0.0114 memory: 14901 loss: 0.9755 loss_prob: 0.5227 loss_thr: 0.3661 loss_db: 0.0867 2022/11/02 21:40:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:40:37 - mmengine - INFO - Epoch(train) [849][5/63] lr: 7.1606e-04 eta: 3:43:21 time: 0.8298 data_time: 0.2412 memory: 14901 loss: 0.9134 loss_prob: 0.4729 loss_thr: 0.3599 loss_db: 0.0806 2022/11/02 21:40:40 - mmengine - INFO - Epoch(train) [849][10/63] lr: 7.1606e-04 eta: 3:43:13 time: 0.8025 data_time: 0.2407 memory: 14901 loss: 1.0007 loss_prob: 0.5285 loss_thr: 0.3826 loss_db: 0.0895 2022/11/02 21:40:42 - mmengine - INFO - Epoch(train) [849][15/63] lr: 7.1606e-04 eta: 3:43:13 time: 0.4806 data_time: 0.0079 memory: 14901 loss: 1.0565 loss_prob: 0.5606 loss_thr: 0.3962 loss_db: 0.0997 2022/11/02 21:40:45 - mmengine - INFO - Epoch(train) [849][20/63] lr: 7.1606e-04 eta: 3:43:06 time: 0.5196 data_time: 0.0096 memory: 14901 loss: 1.0701 loss_prob: 0.5573 loss_thr: 0.4144 loss_db: 0.0985 2022/11/02 21:40:48 - mmengine - INFO - Epoch(train) [849][25/63] lr: 7.1606e-04 eta: 3:43:06 time: 0.5549 data_time: 0.0276 memory: 14901 loss: 1.0258 loss_prob: 0.5322 loss_thr: 0.4021 loss_db: 0.0915 2022/11/02 21:40:51 - mmengine - INFO - Epoch(train) [849][30/63] lr: 7.1606e-04 eta: 3:43:00 time: 0.5498 data_time: 0.0400 memory: 14901 loss: 0.9864 loss_prob: 0.5148 loss_thr: 0.3816 loss_db: 0.0899 2022/11/02 21:40:53 - mmengine - INFO - Epoch(train) [849][35/63] lr: 7.1606e-04 eta: 3:43:00 time: 0.5346 data_time: 0.0253 memory: 14901 loss: 0.9879 loss_prob: 0.5237 loss_thr: 0.3725 loss_db: 0.0917 2022/11/02 21:40:56 - mmengine - INFO - Epoch(train) [849][40/63] lr: 7.1606e-04 eta: 3:42:54 time: 0.5215 data_time: 0.0100 memory: 14901 loss: 1.0284 loss_prob: 0.5555 loss_thr: 0.3778 loss_db: 0.0951 2022/11/02 21:40:58 - mmengine - INFO - Epoch(train) [849][45/63] lr: 7.1606e-04 eta: 3:42:54 time: 0.5027 data_time: 0.0113 memory: 14901 loss: 1.0134 loss_prob: 0.5357 loss_thr: 0.3869 loss_db: 0.0907 2022/11/02 21:41:01 - mmengine - INFO - Epoch(train) [849][50/63] lr: 7.1606e-04 eta: 3:42:47 time: 0.5138 data_time: 0.0241 memory: 14901 loss: 0.9498 loss_prob: 0.4931 loss_thr: 0.3701 loss_db: 0.0867 2022/11/02 21:41:03 - mmengine - INFO - Epoch(train) [849][55/63] lr: 7.1606e-04 eta: 3:42:47 time: 0.5238 data_time: 0.0263 memory: 14901 loss: 1.0014 loss_prob: 0.5265 loss_thr: 0.3810 loss_db: 0.0940 2022/11/02 21:41:06 - mmengine - INFO - Epoch(train) [849][60/63] lr: 7.1606e-04 eta: 3:42:41 time: 0.5237 data_time: 0.0141 memory: 14901 loss: 1.0881 loss_prob: 0.5765 loss_thr: 0.4123 loss_db: 0.0993 2022/11/02 21:41:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:41:14 - mmengine - INFO - Epoch(train) [850][5/63] lr: 7.1422e-04 eta: 3:42:41 time: 0.8460 data_time: 0.2166 memory: 14901 loss: 1.0542 loss_prob: 0.5502 loss_thr: 0.4080 loss_db: 0.0959 2022/11/02 21:41:16 - mmengine - INFO - Epoch(train) [850][10/63] lr: 7.1422e-04 eta: 3:42:33 time: 0.8452 data_time: 0.2279 memory: 14901 loss: 1.0320 loss_prob: 0.5384 loss_thr: 0.3985 loss_db: 0.0951 2022/11/02 21:41:19 - mmengine - INFO - Epoch(train) [850][15/63] lr: 7.1422e-04 eta: 3:42:33 time: 0.5020 data_time: 0.0235 memory: 14901 loss: 1.0078 loss_prob: 0.5222 loss_thr: 0.3942 loss_db: 0.0914 2022/11/02 21:41:21 - mmengine - INFO - Epoch(train) [850][20/63] lr: 7.1422e-04 eta: 3:42:27 time: 0.5164 data_time: 0.0113 memory: 14901 loss: 0.9682 loss_prob: 0.5054 loss_thr: 0.3760 loss_db: 0.0869 2022/11/02 21:41:25 - mmengine - INFO - Epoch(train) [850][25/63] lr: 7.1422e-04 eta: 3:42:27 time: 0.5958 data_time: 0.0223 memory: 14901 loss: 0.9892 loss_prob: 0.5158 loss_thr: 0.3838 loss_db: 0.0896 2022/11/02 21:41:27 - mmengine - INFO - Epoch(train) [850][30/63] lr: 7.1422e-04 eta: 3:42:21 time: 0.5998 data_time: 0.0326 memory: 14901 loss: 1.0041 loss_prob: 0.5192 loss_thr: 0.3934 loss_db: 0.0915 2022/11/02 21:41:30 - mmengine - INFO - Epoch(train) [850][35/63] lr: 7.1422e-04 eta: 3:42:21 time: 0.5615 data_time: 0.0320 memory: 14901 loss: 0.9323 loss_prob: 0.4858 loss_thr: 0.3611 loss_db: 0.0854 2022/11/02 21:41:33 - mmengine - INFO - Epoch(train) [850][40/63] lr: 7.1422e-04 eta: 3:42:15 time: 0.5483 data_time: 0.0188 memory: 14901 loss: 0.9879 loss_prob: 0.5198 loss_thr: 0.3778 loss_db: 0.0903 2022/11/02 21:41:35 - mmengine - INFO - Epoch(train) [850][45/63] lr: 7.1422e-04 eta: 3:42:15 time: 0.5302 data_time: 0.0095 memory: 14901 loss: 0.9790 loss_prob: 0.5114 loss_thr: 0.3790 loss_db: 0.0887 2022/11/02 21:41:38 - mmengine - INFO - Epoch(train) [850][50/63] lr: 7.1422e-04 eta: 3:42:08 time: 0.5238 data_time: 0.0180 memory: 14901 loss: 0.9275 loss_prob: 0.4876 loss_thr: 0.3539 loss_db: 0.0860 2022/11/02 21:41:40 - mmengine - INFO - Epoch(train) [850][55/63] lr: 7.1422e-04 eta: 3:42:08 time: 0.5048 data_time: 0.0231 memory: 14901 loss: 1.0470 loss_prob: 0.5600 loss_thr: 0.3889 loss_db: 0.0981 2022/11/02 21:41:43 - mmengine - INFO - Epoch(train) [850][60/63] lr: 7.1422e-04 eta: 3:42:02 time: 0.4907 data_time: 0.0222 memory: 14901 loss: 1.1180 loss_prob: 0.6036 loss_thr: 0.4135 loss_db: 0.1009 2022/11/02 21:41:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:41:50 - mmengine - INFO - Epoch(train) [851][5/63] lr: 7.1238e-04 eta: 3:42:02 time: 0.8126 data_time: 0.2285 memory: 14901 loss: 0.9440 loss_prob: 0.4940 loss_thr: 0.3676 loss_db: 0.0824 2022/11/02 21:41:52 - mmengine - INFO - Epoch(train) [851][10/63] lr: 7.1238e-04 eta: 3:41:54 time: 0.8209 data_time: 0.2283 memory: 14901 loss: 0.9759 loss_prob: 0.5158 loss_thr: 0.3710 loss_db: 0.0891 2022/11/02 21:41:55 - mmengine - INFO - Epoch(train) [851][15/63] lr: 7.1238e-04 eta: 3:41:54 time: 0.4670 data_time: 0.0109 memory: 14901 loss: 1.0135 loss_prob: 0.5361 loss_thr: 0.3818 loss_db: 0.0956 2022/11/02 21:41:57 - mmengine - INFO - Epoch(train) [851][20/63] lr: 7.1238e-04 eta: 3:41:47 time: 0.4787 data_time: 0.0106 memory: 14901 loss: 1.0429 loss_prob: 0.5515 loss_thr: 0.3949 loss_db: 0.0965 2022/11/02 21:42:00 - mmengine - INFO - Epoch(train) [851][25/63] lr: 7.1238e-04 eta: 3:41:47 time: 0.5087 data_time: 0.0334 memory: 14901 loss: 1.0941 loss_prob: 0.5782 loss_thr: 0.4176 loss_db: 0.0983 2022/11/02 21:42:02 - mmengine - INFO - Epoch(train) [851][30/63] lr: 7.1238e-04 eta: 3:41:41 time: 0.5215 data_time: 0.0445 memory: 14901 loss: 1.0974 loss_prob: 0.5824 loss_thr: 0.4140 loss_db: 0.1009 2022/11/02 21:42:05 - mmengine - INFO - Epoch(train) [851][35/63] lr: 7.1238e-04 eta: 3:41:41 time: 0.5027 data_time: 0.0218 memory: 14901 loss: 1.0744 loss_prob: 0.5665 loss_thr: 0.4085 loss_db: 0.0994 2022/11/02 21:42:07 - mmengine - INFO - Epoch(train) [851][40/63] lr: 7.1238e-04 eta: 3:41:35 time: 0.5039 data_time: 0.0117 memory: 14901 loss: 0.9871 loss_prob: 0.5104 loss_thr: 0.3877 loss_db: 0.0891 2022/11/02 21:42:10 - mmengine - INFO - Epoch(train) [851][45/63] lr: 7.1238e-04 eta: 3:41:35 time: 0.4986 data_time: 0.0105 memory: 14901 loss: 0.9304 loss_prob: 0.4798 loss_thr: 0.3659 loss_db: 0.0846 2022/11/02 21:42:12 - mmengine - INFO - Epoch(train) [851][50/63] lr: 7.1238e-04 eta: 3:41:28 time: 0.5040 data_time: 0.0280 memory: 14901 loss: 0.9439 loss_prob: 0.4905 loss_thr: 0.3679 loss_db: 0.0856 2022/11/02 21:42:15 - mmengine - INFO - Epoch(train) [851][55/63] lr: 7.1238e-04 eta: 3:41:28 time: 0.5107 data_time: 0.0316 memory: 14901 loss: 0.9605 loss_prob: 0.5080 loss_thr: 0.3648 loss_db: 0.0877 2022/11/02 21:42:18 - mmengine - INFO - Epoch(train) [851][60/63] lr: 7.1238e-04 eta: 3:41:22 time: 0.5026 data_time: 0.0139 memory: 14901 loss: 0.9716 loss_prob: 0.5153 loss_thr: 0.3682 loss_db: 0.0880 2022/11/02 21:42:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:42:24 - mmengine - INFO - Epoch(train) [852][5/63] lr: 7.1055e-04 eta: 3:41:22 time: 0.7608 data_time: 0.2900 memory: 14901 loss: 1.0283 loss_prob: 0.5375 loss_thr: 0.3985 loss_db: 0.0923 2022/11/02 21:42:27 - mmengine - INFO - Epoch(train) [852][10/63] lr: 7.1055e-04 eta: 3:41:14 time: 0.7787 data_time: 0.2911 memory: 14901 loss: 1.0082 loss_prob: 0.5288 loss_thr: 0.3899 loss_db: 0.0895 2022/11/02 21:42:29 - mmengine - INFO - Epoch(train) [852][15/63] lr: 7.1055e-04 eta: 3:41:14 time: 0.5269 data_time: 0.0113 memory: 14901 loss: 0.9521 loss_prob: 0.4995 loss_thr: 0.3657 loss_db: 0.0868 2022/11/02 21:42:32 - mmengine - INFO - Epoch(train) [852][20/63] lr: 7.1055e-04 eta: 3:41:08 time: 0.5256 data_time: 0.0079 memory: 14901 loss: 1.0334 loss_prob: 0.5488 loss_thr: 0.3889 loss_db: 0.0957 2022/11/02 21:42:35 - mmengine - INFO - Epoch(train) [852][25/63] lr: 7.1055e-04 eta: 3:41:08 time: 0.5460 data_time: 0.0331 memory: 14901 loss: 1.0547 loss_prob: 0.5640 loss_thr: 0.3929 loss_db: 0.0978 2022/11/02 21:42:38 - mmengine - INFO - Epoch(train) [852][30/63] lr: 7.1055e-04 eta: 3:41:01 time: 0.5558 data_time: 0.0374 memory: 14901 loss: 0.9856 loss_prob: 0.5138 loss_thr: 0.3808 loss_db: 0.0909 2022/11/02 21:42:40 - mmengine - INFO - Epoch(train) [852][35/63] lr: 7.1055e-04 eta: 3:41:01 time: 0.5433 data_time: 0.0186 memory: 14901 loss: 0.9880 loss_prob: 0.5091 loss_thr: 0.3886 loss_db: 0.0903 2022/11/02 21:42:43 - mmengine - INFO - Epoch(train) [852][40/63] lr: 7.1055e-04 eta: 3:40:55 time: 0.5237 data_time: 0.0133 memory: 14901 loss: 1.0207 loss_prob: 0.5403 loss_thr: 0.3877 loss_db: 0.0927 2022/11/02 21:42:45 - mmengine - INFO - Epoch(train) [852][45/63] lr: 7.1055e-04 eta: 3:40:55 time: 0.5129 data_time: 0.0083 memory: 14901 loss: 0.9581 loss_prob: 0.4982 loss_thr: 0.3740 loss_db: 0.0859 2022/11/02 21:42:48 - mmengine - INFO - Epoch(train) [852][50/63] lr: 7.1055e-04 eta: 3:40:49 time: 0.5227 data_time: 0.0246 memory: 14901 loss: 0.9288 loss_prob: 0.4746 loss_thr: 0.3705 loss_db: 0.0838 2022/11/02 21:42:50 - mmengine - INFO - Epoch(train) [852][55/63] lr: 7.1055e-04 eta: 3:40:49 time: 0.5118 data_time: 0.0304 memory: 14901 loss: 0.9496 loss_prob: 0.4884 loss_thr: 0.3752 loss_db: 0.0860 2022/11/02 21:42:53 - mmengine - INFO - Epoch(train) [852][60/63] lr: 7.1055e-04 eta: 3:40:42 time: 0.5025 data_time: 0.0141 memory: 14901 loss: 0.9835 loss_prob: 0.5028 loss_thr: 0.3926 loss_db: 0.0882 2022/11/02 21:42:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:43:00 - mmengine - INFO - Epoch(train) [853][5/63] lr: 7.0871e-04 eta: 3:40:42 time: 0.7500 data_time: 0.1935 memory: 14901 loss: 1.0104 loss_prob: 0.5222 loss_thr: 0.3980 loss_db: 0.0903 2022/11/02 21:43:03 - mmengine - INFO - Epoch(train) [853][10/63] lr: 7.0871e-04 eta: 3:40:34 time: 0.8348 data_time: 0.2083 memory: 14901 loss: 0.9782 loss_prob: 0.5089 loss_thr: 0.3810 loss_db: 0.0883 2022/11/02 21:43:06 - mmengine - INFO - Epoch(train) [853][15/63] lr: 7.0871e-04 eta: 3:40:34 time: 0.6069 data_time: 0.0261 memory: 14901 loss: 1.0025 loss_prob: 0.5236 loss_thr: 0.3866 loss_db: 0.0923 2022/11/02 21:43:09 - mmengine - INFO - Epoch(train) [853][20/63] lr: 7.0871e-04 eta: 3:40:28 time: 0.5920 data_time: 0.0120 memory: 14901 loss: 0.9792 loss_prob: 0.4988 loss_thr: 0.3937 loss_db: 0.0868 2022/11/02 21:43:11 - mmengine - INFO - Epoch(train) [853][25/63] lr: 7.0871e-04 eta: 3:40:28 time: 0.5629 data_time: 0.0130 memory: 14901 loss: 1.0097 loss_prob: 0.5199 loss_thr: 0.4019 loss_db: 0.0878 2022/11/02 21:43:14 - mmengine - INFO - Epoch(train) [853][30/63] lr: 7.0871e-04 eta: 3:40:22 time: 0.5605 data_time: 0.0440 memory: 14901 loss: 1.0419 loss_prob: 0.5427 loss_thr: 0.4057 loss_db: 0.0936 2022/11/02 21:43:17 - mmengine - INFO - Epoch(train) [853][35/63] lr: 7.0871e-04 eta: 3:40:22 time: 0.5545 data_time: 0.0432 memory: 14901 loss: 1.0229 loss_prob: 0.5302 loss_thr: 0.3993 loss_db: 0.0934 2022/11/02 21:43:19 - mmengine - INFO - Epoch(train) [853][40/63] lr: 7.0871e-04 eta: 3:40:16 time: 0.5190 data_time: 0.0113 memory: 14901 loss: 1.0325 loss_prob: 0.5425 loss_thr: 0.3984 loss_db: 0.0916 2022/11/02 21:43:22 - mmengine - INFO - Epoch(train) [853][45/63] lr: 7.0871e-04 eta: 3:40:16 time: 0.5190 data_time: 0.0129 memory: 14901 loss: 1.0004 loss_prob: 0.5229 loss_thr: 0.3867 loss_db: 0.0908 2022/11/02 21:43:25 - mmengine - INFO - Epoch(train) [853][50/63] lr: 7.0871e-04 eta: 3:40:09 time: 0.5048 data_time: 0.0246 memory: 14901 loss: 1.0372 loss_prob: 0.5457 loss_thr: 0.3945 loss_db: 0.0971 2022/11/02 21:43:27 - mmengine - INFO - Epoch(train) [853][55/63] lr: 7.0871e-04 eta: 3:40:09 time: 0.4989 data_time: 0.0343 memory: 14901 loss: 1.0503 loss_prob: 0.5495 loss_thr: 0.4050 loss_db: 0.0958 2022/11/02 21:43:30 - mmengine - INFO - Epoch(train) [853][60/63] lr: 7.0871e-04 eta: 3:40:03 time: 0.5214 data_time: 0.0211 memory: 14901 loss: 0.9617 loss_prob: 0.4922 loss_thr: 0.3839 loss_db: 0.0857 2022/11/02 21:43:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:43:36 - mmengine - INFO - Epoch(train) [854][5/63] lr: 7.0687e-04 eta: 3:40:03 time: 0.7507 data_time: 0.2075 memory: 14901 loss: 0.8915 loss_prob: 0.4595 loss_thr: 0.3525 loss_db: 0.0796 2022/11/02 21:43:39 - mmengine - INFO - Epoch(train) [854][10/63] lr: 7.0687e-04 eta: 3:39:55 time: 0.7622 data_time: 0.2112 memory: 14901 loss: 0.9440 loss_prob: 0.4907 loss_thr: 0.3686 loss_db: 0.0847 2022/11/02 21:43:41 - mmengine - INFO - Epoch(train) [854][15/63] lr: 7.0687e-04 eta: 3:39:55 time: 0.5114 data_time: 0.0180 memory: 14901 loss: 0.9408 loss_prob: 0.4844 loss_thr: 0.3732 loss_db: 0.0832 2022/11/02 21:43:45 - mmengine - INFO - Epoch(train) [854][20/63] lr: 7.0687e-04 eta: 3:39:49 time: 0.5764 data_time: 0.0161 memory: 14901 loss: 0.9196 loss_prob: 0.4677 loss_thr: 0.3706 loss_db: 0.0813 2022/11/02 21:43:47 - mmengine - INFO - Epoch(train) [854][25/63] lr: 7.0687e-04 eta: 3:39:49 time: 0.5969 data_time: 0.0323 memory: 14901 loss: 0.8856 loss_prob: 0.4494 loss_thr: 0.3562 loss_db: 0.0800 2022/11/02 21:43:50 - mmengine - INFO - Epoch(train) [854][30/63] lr: 7.0687e-04 eta: 3:39:42 time: 0.5295 data_time: 0.0375 memory: 14901 loss: 0.9445 loss_prob: 0.4878 loss_thr: 0.3719 loss_db: 0.0848 2022/11/02 21:43:53 - mmengine - INFO - Epoch(train) [854][35/63] lr: 7.0687e-04 eta: 3:39:42 time: 0.5443 data_time: 0.0177 memory: 14901 loss: 1.0025 loss_prob: 0.5320 loss_thr: 0.3818 loss_db: 0.0887 2022/11/02 21:43:55 - mmengine - INFO - Epoch(train) [854][40/63] lr: 7.0687e-04 eta: 3:39:36 time: 0.5227 data_time: 0.0154 memory: 14901 loss: 1.0701 loss_prob: 0.5744 loss_thr: 0.3988 loss_db: 0.0968 2022/11/02 21:43:58 - mmengine - INFO - Epoch(train) [854][45/63] lr: 7.0687e-04 eta: 3:39:36 time: 0.4933 data_time: 0.0127 memory: 14901 loss: 1.0981 loss_prob: 0.5784 loss_thr: 0.4194 loss_db: 0.1004 2022/11/02 21:44:00 - mmengine - INFO - Epoch(train) [854][50/63] lr: 7.0687e-04 eta: 3:39:30 time: 0.5157 data_time: 0.0206 memory: 14901 loss: 1.0061 loss_prob: 0.5203 loss_thr: 0.3957 loss_db: 0.0902 2022/11/02 21:44:03 - mmengine - INFO - Epoch(train) [854][55/63] lr: 7.0687e-04 eta: 3:39:30 time: 0.5428 data_time: 0.0267 memory: 14901 loss: 1.0490 loss_prob: 0.5484 loss_thr: 0.4053 loss_db: 0.0953 2022/11/02 21:44:05 - mmengine - INFO - Epoch(train) [854][60/63] lr: 7.0687e-04 eta: 3:39:23 time: 0.5222 data_time: 0.0193 memory: 14901 loss: 1.0466 loss_prob: 0.5477 loss_thr: 0.4021 loss_db: 0.0969 2022/11/02 21:44:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:44:13 - mmengine - INFO - Epoch(train) [855][5/63] lr: 7.0503e-04 eta: 3:39:23 time: 0.8282 data_time: 0.1905 memory: 14901 loss: 1.0815 loss_prob: 0.5825 loss_thr: 0.4032 loss_db: 0.0959 2022/11/02 21:44:15 - mmengine - INFO - Epoch(train) [855][10/63] lr: 7.0503e-04 eta: 3:39:16 time: 0.8549 data_time: 0.2005 memory: 14901 loss: 1.0453 loss_prob: 0.5686 loss_thr: 0.3815 loss_db: 0.0952 2022/11/02 21:44:18 - mmengine - INFO - Epoch(train) [855][15/63] lr: 7.0503e-04 eta: 3:39:16 time: 0.5256 data_time: 0.0261 memory: 14901 loss: 1.0041 loss_prob: 0.5341 loss_thr: 0.3788 loss_db: 0.0912 2022/11/02 21:44:21 - mmengine - INFO - Epoch(train) [855][20/63] lr: 7.0503e-04 eta: 3:39:10 time: 0.5869 data_time: 0.0152 memory: 14901 loss: 0.9735 loss_prob: 0.5063 loss_thr: 0.3804 loss_db: 0.0868 2022/11/02 21:44:24 - mmengine - INFO - Epoch(train) [855][25/63] lr: 7.0503e-04 eta: 3:39:10 time: 0.5785 data_time: 0.0123 memory: 14901 loss: 1.0668 loss_prob: 0.5658 loss_thr: 0.4034 loss_db: 0.0975 2022/11/02 21:44:27 - mmengine - INFO - Epoch(train) [855][30/63] lr: 7.0503e-04 eta: 3:39:04 time: 0.6161 data_time: 0.0285 memory: 14901 loss: 1.0085 loss_prob: 0.5307 loss_thr: 0.3850 loss_db: 0.0928 2022/11/02 21:44:30 - mmengine - INFO - Epoch(train) [855][35/63] lr: 7.0503e-04 eta: 3:39:04 time: 0.6141 data_time: 0.0363 memory: 14901 loss: 0.9716 loss_prob: 0.5092 loss_thr: 0.3737 loss_db: 0.0887 2022/11/02 21:44:32 - mmengine - INFO - Epoch(train) [855][40/63] lr: 7.0503e-04 eta: 3:38:57 time: 0.5198 data_time: 0.0205 memory: 14901 loss: 1.0183 loss_prob: 0.5328 loss_thr: 0.3923 loss_db: 0.0932 2022/11/02 21:44:35 - mmengine - INFO - Epoch(train) [855][45/63] lr: 7.0503e-04 eta: 3:38:57 time: 0.4889 data_time: 0.0112 memory: 14901 loss: 0.9778 loss_prob: 0.5073 loss_thr: 0.3841 loss_db: 0.0865 2022/11/02 21:44:38 - mmengine - INFO - Epoch(train) [855][50/63] lr: 7.0503e-04 eta: 3:38:51 time: 0.5454 data_time: 0.0167 memory: 14901 loss: 0.9415 loss_prob: 0.4904 loss_thr: 0.3682 loss_db: 0.0828 2022/11/02 21:44:41 - mmengine - INFO - Epoch(train) [855][55/63] lr: 7.0503e-04 eta: 3:38:51 time: 0.6158 data_time: 0.0271 memory: 14901 loss: 0.9448 loss_prob: 0.4876 loss_thr: 0.3719 loss_db: 0.0852 2022/11/02 21:44:43 - mmengine - INFO - Epoch(train) [855][60/63] lr: 7.0503e-04 eta: 3:38:45 time: 0.5471 data_time: 0.0207 memory: 14901 loss: 0.9349 loss_prob: 0.4783 loss_thr: 0.3717 loss_db: 0.0850 2022/11/02 21:44:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:44:49 - mmengine - INFO - Epoch(train) [856][5/63] lr: 7.0319e-04 eta: 3:38:45 time: 0.6938 data_time: 0.2447 memory: 14901 loss: 0.9039 loss_prob: 0.4705 loss_thr: 0.3541 loss_db: 0.0793 2022/11/02 21:44:52 - mmengine - INFO - Epoch(train) [856][10/63] lr: 7.0319e-04 eta: 3:38:37 time: 0.7591 data_time: 0.2405 memory: 14901 loss: 0.9425 loss_prob: 0.4830 loss_thr: 0.3760 loss_db: 0.0835 2022/11/02 21:44:55 - mmengine - INFO - Epoch(train) [856][15/63] lr: 7.0319e-04 eta: 3:38:37 time: 0.5410 data_time: 0.0105 memory: 14901 loss: 1.0544 loss_prob: 0.5510 loss_thr: 0.4086 loss_db: 0.0948 2022/11/02 21:44:58 - mmengine - INFO - Epoch(train) [856][20/63] lr: 7.0319e-04 eta: 3:38:31 time: 0.5352 data_time: 0.0120 memory: 14901 loss: 1.0565 loss_prob: 0.5541 loss_thr: 0.4066 loss_db: 0.0958 2022/11/02 21:45:00 - mmengine - INFO - Epoch(train) [856][25/63] lr: 7.0319e-04 eta: 3:38:31 time: 0.5183 data_time: 0.0154 memory: 14901 loss: 0.9976 loss_prob: 0.5151 loss_thr: 0.3918 loss_db: 0.0906 2022/11/02 21:45:03 - mmengine - INFO - Epoch(train) [856][30/63] lr: 7.0319e-04 eta: 3:38:24 time: 0.5208 data_time: 0.0385 memory: 14901 loss: 0.9397 loss_prob: 0.4849 loss_thr: 0.3713 loss_db: 0.0835 2022/11/02 21:45:05 - mmengine - INFO - Epoch(train) [856][35/63] lr: 7.0319e-04 eta: 3:38:24 time: 0.5329 data_time: 0.0346 memory: 14901 loss: 0.9473 loss_prob: 0.4963 loss_thr: 0.3655 loss_db: 0.0855 2022/11/02 21:45:09 - mmengine - INFO - Epoch(train) [856][40/63] lr: 7.0319e-04 eta: 3:38:18 time: 0.5946 data_time: 0.0128 memory: 14901 loss: 1.0114 loss_prob: 0.5378 loss_thr: 0.3796 loss_db: 0.0940 2022/11/02 21:45:11 - mmengine - INFO - Epoch(train) [856][45/63] lr: 7.0319e-04 eta: 3:38:18 time: 0.5910 data_time: 0.0101 memory: 14901 loss: 1.0140 loss_prob: 0.5283 loss_thr: 0.3927 loss_db: 0.0930 2022/11/02 21:45:14 - mmengine - INFO - Epoch(train) [856][50/63] lr: 7.0319e-04 eta: 3:38:12 time: 0.5042 data_time: 0.0235 memory: 14901 loss: 0.9903 loss_prob: 0.5093 loss_thr: 0.3907 loss_db: 0.0902 2022/11/02 21:45:16 - mmengine - INFO - Epoch(train) [856][55/63] lr: 7.0319e-04 eta: 3:38:12 time: 0.5295 data_time: 0.0266 memory: 14901 loss: 1.0294 loss_prob: 0.5410 loss_thr: 0.3937 loss_db: 0.0947 2022/11/02 21:45:19 - mmengine - INFO - Epoch(train) [856][60/63] lr: 7.0319e-04 eta: 3:38:05 time: 0.5702 data_time: 0.0110 memory: 14901 loss: 1.0029 loss_prob: 0.5246 loss_thr: 0.3868 loss_db: 0.0914 2022/11/02 21:45:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:45:26 - mmengine - INFO - Epoch(train) [857][5/63] lr: 7.0135e-04 eta: 3:38:05 time: 0.7621 data_time: 0.2386 memory: 14901 loss: 1.0773 loss_prob: 0.5712 loss_thr: 0.4077 loss_db: 0.0984 2022/11/02 21:45:28 - mmengine - INFO - Epoch(train) [857][10/63] lr: 7.0135e-04 eta: 3:37:58 time: 0.7638 data_time: 0.2393 memory: 14901 loss: 1.0322 loss_prob: 0.5447 loss_thr: 0.3936 loss_db: 0.0939 2022/11/02 21:45:31 - mmengine - INFO - Epoch(train) [857][15/63] lr: 7.0135e-04 eta: 3:37:58 time: 0.5483 data_time: 0.0098 memory: 14901 loss: 0.9337 loss_prob: 0.4794 loss_thr: 0.3706 loss_db: 0.0837 2022/11/02 21:45:34 - mmengine - INFO - Epoch(train) [857][20/63] lr: 7.0135e-04 eta: 3:37:51 time: 0.5456 data_time: 0.0116 memory: 14901 loss: 0.9892 loss_prob: 0.5118 loss_thr: 0.3875 loss_db: 0.0898 2022/11/02 21:45:37 - mmengine - INFO - Epoch(train) [857][25/63] lr: 7.0135e-04 eta: 3:37:51 time: 0.5575 data_time: 0.0293 memory: 14901 loss: 1.0092 loss_prob: 0.5319 loss_thr: 0.3867 loss_db: 0.0905 2022/11/02 21:45:40 - mmengine - INFO - Epoch(train) [857][30/63] lr: 7.0135e-04 eta: 3:37:45 time: 0.6089 data_time: 0.0549 memory: 14901 loss: 1.0078 loss_prob: 0.5282 loss_thr: 0.3905 loss_db: 0.0892 2022/11/02 21:45:42 - mmengine - INFO - Epoch(train) [857][35/63] lr: 7.0135e-04 eta: 3:37:45 time: 0.5285 data_time: 0.0331 memory: 14901 loss: 1.0215 loss_prob: 0.5285 loss_thr: 0.4012 loss_db: 0.0919 2022/11/02 21:45:45 - mmengine - INFO - Epoch(train) [857][40/63] lr: 7.0135e-04 eta: 3:37:39 time: 0.4942 data_time: 0.0079 memory: 14901 loss: 1.0461 loss_prob: 0.5484 loss_thr: 0.4006 loss_db: 0.0971 2022/11/02 21:45:47 - mmengine - INFO - Epoch(train) [857][45/63] lr: 7.0135e-04 eta: 3:37:39 time: 0.4928 data_time: 0.0110 memory: 14901 loss: 1.0416 loss_prob: 0.5440 loss_thr: 0.4016 loss_db: 0.0959 2022/11/02 21:45:51 - mmengine - INFO - Epoch(train) [857][50/63] lr: 7.0135e-04 eta: 3:37:33 time: 0.5958 data_time: 0.0214 memory: 14901 loss: 1.0301 loss_prob: 0.5313 loss_thr: 0.4086 loss_db: 0.0903 2022/11/02 21:45:54 - mmengine - INFO - Epoch(train) [857][55/63] lr: 7.0135e-04 eta: 3:37:33 time: 0.6661 data_time: 0.0290 memory: 14901 loss: 0.9745 loss_prob: 0.5032 loss_thr: 0.3843 loss_db: 0.0870 2022/11/02 21:45:57 - mmengine - INFO - Epoch(train) [857][60/63] lr: 7.0135e-04 eta: 3:37:27 time: 0.5869 data_time: 0.0225 memory: 14901 loss: 0.9397 loss_prob: 0.4859 loss_thr: 0.3681 loss_db: 0.0858 2022/11/02 21:45:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:46:04 - mmengine - INFO - Epoch(train) [858][5/63] lr: 6.9951e-04 eta: 3:37:27 time: 0.7971 data_time: 0.1804 memory: 14901 loss: 1.0298 loss_prob: 0.5440 loss_thr: 0.3930 loss_db: 0.0928 2022/11/02 21:46:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:46:06 - mmengine - INFO - Epoch(train) [858][10/63] lr: 6.9951e-04 eta: 3:37:19 time: 0.8089 data_time: 0.1879 memory: 14901 loss: 1.0174 loss_prob: 0.5395 loss_thr: 0.3852 loss_db: 0.0926 2022/11/02 21:46:09 - mmengine - INFO - Epoch(train) [858][15/63] lr: 6.9951e-04 eta: 3:37:19 time: 0.5378 data_time: 0.0177 memory: 14901 loss: 1.0321 loss_prob: 0.5382 loss_thr: 0.3989 loss_db: 0.0950 2022/11/02 21:46:12 - mmengine - INFO - Epoch(train) [858][20/63] lr: 6.9951e-04 eta: 3:37:13 time: 0.5520 data_time: 0.0112 memory: 14901 loss: 0.9350 loss_prob: 0.4766 loss_thr: 0.3741 loss_db: 0.0843 2022/11/02 21:46:14 - mmengine - INFO - Epoch(train) [858][25/63] lr: 6.9951e-04 eta: 3:37:13 time: 0.5059 data_time: 0.0183 memory: 14901 loss: 0.9177 loss_prob: 0.4684 loss_thr: 0.3690 loss_db: 0.0803 2022/11/02 21:46:17 - mmengine - INFO - Epoch(train) [858][30/63] lr: 6.9951e-04 eta: 3:37:06 time: 0.5477 data_time: 0.0367 memory: 14901 loss: 0.9696 loss_prob: 0.4969 loss_thr: 0.3864 loss_db: 0.0864 2022/11/02 21:46:20 - mmengine - INFO - Epoch(train) [858][35/63] lr: 6.9951e-04 eta: 3:37:06 time: 0.5715 data_time: 0.0388 memory: 14901 loss: 1.0146 loss_prob: 0.5300 loss_thr: 0.3924 loss_db: 0.0922 2022/11/02 21:46:22 - mmengine - INFO - Epoch(train) [858][40/63] lr: 6.9951e-04 eta: 3:37:00 time: 0.5101 data_time: 0.0222 memory: 14901 loss: 0.9942 loss_prob: 0.5135 loss_thr: 0.3928 loss_db: 0.0878 2022/11/02 21:46:25 - mmengine - INFO - Epoch(train) [858][45/63] lr: 6.9951e-04 eta: 3:37:00 time: 0.4863 data_time: 0.0118 memory: 14901 loss: 0.9892 loss_prob: 0.5129 loss_thr: 0.3890 loss_db: 0.0872 2022/11/02 21:46:27 - mmengine - INFO - Epoch(train) [858][50/63] lr: 6.9951e-04 eta: 3:36:54 time: 0.5116 data_time: 0.0193 memory: 14901 loss: 1.0589 loss_prob: 0.5728 loss_thr: 0.3897 loss_db: 0.0964 2022/11/02 21:46:30 - mmengine - INFO - Epoch(train) [858][55/63] lr: 6.9951e-04 eta: 3:36:54 time: 0.5264 data_time: 0.0318 memory: 14901 loss: 1.0313 loss_prob: 0.5524 loss_thr: 0.3830 loss_db: 0.0959 2022/11/02 21:46:34 - mmengine - INFO - Epoch(train) [858][60/63] lr: 6.9951e-04 eta: 3:36:48 time: 0.6454 data_time: 0.0221 memory: 14901 loss: 1.0039 loss_prob: 0.5250 loss_thr: 0.3869 loss_db: 0.0920 2022/11/02 21:46:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:46:42 - mmengine - INFO - Epoch(train) [859][5/63] lr: 6.9767e-04 eta: 3:36:48 time: 0.9314 data_time: 0.2295 memory: 14901 loss: 0.9986 loss_prob: 0.5117 loss_thr: 0.3992 loss_db: 0.0877 2022/11/02 21:46:44 - mmengine - INFO - Epoch(train) [859][10/63] lr: 6.9767e-04 eta: 3:36:40 time: 0.9099 data_time: 0.2307 memory: 14901 loss: 0.9858 loss_prob: 0.5071 loss_thr: 0.3909 loss_db: 0.0877 2022/11/02 21:46:47 - mmengine - INFO - Epoch(train) [859][15/63] lr: 6.9767e-04 eta: 3:36:40 time: 0.4993 data_time: 0.0116 memory: 14901 loss: 0.9826 loss_prob: 0.5119 loss_thr: 0.3826 loss_db: 0.0882 2022/11/02 21:46:50 - mmengine - INFO - Epoch(train) [859][20/63] lr: 6.9767e-04 eta: 3:36:34 time: 0.5296 data_time: 0.0121 memory: 14901 loss: 0.9232 loss_prob: 0.4798 loss_thr: 0.3599 loss_db: 0.0835 2022/11/02 21:46:53 - mmengine - INFO - Epoch(train) [859][25/63] lr: 6.9767e-04 eta: 3:36:34 time: 0.5926 data_time: 0.0291 memory: 14901 loss: 0.9356 loss_prob: 0.4865 loss_thr: 0.3633 loss_db: 0.0858 2022/11/02 21:46:55 - mmengine - INFO - Epoch(train) [859][30/63] lr: 6.9767e-04 eta: 3:36:28 time: 0.5655 data_time: 0.0398 memory: 14901 loss: 1.0481 loss_prob: 0.5537 loss_thr: 0.3989 loss_db: 0.0955 2022/11/02 21:46:58 - mmengine - INFO - Epoch(train) [859][35/63] lr: 6.9767e-04 eta: 3:36:28 time: 0.4984 data_time: 0.0221 memory: 14901 loss: 1.0566 loss_prob: 0.5595 loss_thr: 0.4019 loss_db: 0.0952 2022/11/02 21:47:01 - mmengine - INFO - Epoch(train) [859][40/63] lr: 6.9767e-04 eta: 3:36:21 time: 0.5136 data_time: 0.0124 memory: 14901 loss: 0.9532 loss_prob: 0.4980 loss_thr: 0.3685 loss_db: 0.0867 2022/11/02 21:47:03 - mmengine - INFO - Epoch(train) [859][45/63] lr: 6.9767e-04 eta: 3:36:21 time: 0.5390 data_time: 0.0134 memory: 14901 loss: 0.9159 loss_prob: 0.4752 loss_thr: 0.3583 loss_db: 0.0824 2022/11/02 21:47:06 - mmengine - INFO - Epoch(train) [859][50/63] lr: 6.9767e-04 eta: 3:36:15 time: 0.5609 data_time: 0.0215 memory: 14901 loss: 0.9898 loss_prob: 0.5207 loss_thr: 0.3797 loss_db: 0.0893 2022/11/02 21:47:09 - mmengine - INFO - Epoch(train) [859][55/63] lr: 6.9767e-04 eta: 3:36:15 time: 0.5438 data_time: 0.0287 memory: 14901 loss: 1.0311 loss_prob: 0.5445 loss_thr: 0.3927 loss_db: 0.0939 2022/11/02 21:47:11 - mmengine - INFO - Epoch(train) [859][60/63] lr: 6.9767e-04 eta: 3:36:09 time: 0.5080 data_time: 0.0176 memory: 14901 loss: 1.0646 loss_prob: 0.5593 loss_thr: 0.4069 loss_db: 0.0984 2022/11/02 21:47:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:47:20 - mmengine - INFO - Epoch(train) [860][5/63] lr: 6.9583e-04 eta: 3:36:09 time: 0.9687 data_time: 0.2770 memory: 14901 loss: 0.9851 loss_prob: 0.5099 loss_thr: 0.3875 loss_db: 0.0877 2022/11/02 21:47:23 - mmengine - INFO - Epoch(train) [860][10/63] lr: 6.9583e-04 eta: 3:36:02 time: 0.9831 data_time: 0.2769 memory: 14901 loss: 0.9628 loss_prob: 0.4963 loss_thr: 0.3811 loss_db: 0.0854 2022/11/02 21:47:25 - mmengine - INFO - Epoch(train) [860][15/63] lr: 6.9583e-04 eta: 3:36:02 time: 0.5106 data_time: 0.0106 memory: 14901 loss: 0.9638 loss_prob: 0.4968 loss_thr: 0.3811 loss_db: 0.0859 2022/11/02 21:47:28 - mmengine - INFO - Epoch(train) [860][20/63] lr: 6.9583e-04 eta: 3:35:55 time: 0.5039 data_time: 0.0104 memory: 14901 loss: 1.0543 loss_prob: 0.5508 loss_thr: 0.4101 loss_db: 0.0934 2022/11/02 21:47:30 - mmengine - INFO - Epoch(train) [860][25/63] lr: 6.9583e-04 eta: 3:35:55 time: 0.5374 data_time: 0.0291 memory: 14901 loss: 1.0990 loss_prob: 0.5828 loss_thr: 0.4173 loss_db: 0.0989 2022/11/02 21:47:33 - mmengine - INFO - Epoch(train) [860][30/63] lr: 6.9583e-04 eta: 3:35:49 time: 0.5686 data_time: 0.0398 memory: 14901 loss: 1.0567 loss_prob: 0.5530 loss_thr: 0.4110 loss_db: 0.0926 2022/11/02 21:47:36 - mmengine - INFO - Epoch(train) [860][35/63] lr: 6.9583e-04 eta: 3:35:49 time: 0.5334 data_time: 0.0229 memory: 14901 loss: 0.9820 loss_prob: 0.5059 loss_thr: 0.3900 loss_db: 0.0860 2022/11/02 21:47:38 - mmengine - INFO - Epoch(train) [860][40/63] lr: 6.9583e-04 eta: 3:35:43 time: 0.5192 data_time: 0.0129 memory: 14901 loss: 0.9923 loss_prob: 0.5212 loss_thr: 0.3805 loss_db: 0.0906 2022/11/02 21:47:41 - mmengine - INFO - Epoch(train) [860][45/63] lr: 6.9583e-04 eta: 3:35:43 time: 0.5181 data_time: 0.0079 memory: 14901 loss: 1.0277 loss_prob: 0.5484 loss_thr: 0.3871 loss_db: 0.0923 2022/11/02 21:47:44 - mmengine - INFO - Epoch(train) [860][50/63] lr: 6.9583e-04 eta: 3:35:36 time: 0.5225 data_time: 0.0267 memory: 14901 loss: 1.0219 loss_prob: 0.5396 loss_thr: 0.3909 loss_db: 0.0914 2022/11/02 21:47:46 - mmengine - INFO - Epoch(train) [860][55/63] lr: 6.9583e-04 eta: 3:35:36 time: 0.5151 data_time: 0.0284 memory: 14901 loss: 0.9706 loss_prob: 0.5055 loss_thr: 0.3746 loss_db: 0.0905 2022/11/02 21:47:49 - mmengine - INFO - Epoch(train) [860][60/63] lr: 6.9583e-04 eta: 3:35:30 time: 0.4999 data_time: 0.0103 memory: 14901 loss: 0.9936 loss_prob: 0.5162 loss_thr: 0.3845 loss_db: 0.0930 2022/11/02 21:47:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:47:50 - mmengine - INFO - Saving checkpoint at 860 epochs 2022/11/02 21:47:54 - mmengine - INFO - Epoch(val) [860][5/500] eta: 3:35:30 time: 0.0426 data_time: 0.0051 memory: 14901 2022/11/02 21:47:55 - mmengine - INFO - Epoch(val) [860][10/500] eta: 0:00:21 time: 0.0449 data_time: 0.0053 memory: 1008 2022/11/02 21:47:55 - mmengine - INFO - Epoch(val) [860][15/500] eta: 0:00:21 time: 0.0378 data_time: 0.0025 memory: 1008 2022/11/02 21:47:55 - mmengine - INFO - Epoch(val) [860][20/500] eta: 0:00:17 time: 0.0364 data_time: 0.0023 memory: 1008 2022/11/02 21:47:55 - mmengine - INFO - Epoch(val) [860][25/500] eta: 0:00:17 time: 0.0351 data_time: 0.0025 memory: 1008 2022/11/02 21:47:55 - mmengine - INFO - Epoch(val) [860][30/500] eta: 0:00:19 time: 0.0417 data_time: 0.0027 memory: 1008 2022/11/02 21:47:55 - mmengine - INFO - Epoch(val) [860][35/500] eta: 0:00:19 time: 0.0430 data_time: 0.0026 memory: 1008 2022/11/02 21:47:56 - mmengine - INFO - Epoch(val) [860][40/500] eta: 0:00:18 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 21:47:56 - mmengine - INFO - Epoch(val) [860][45/500] eta: 0:00:18 time: 0.0446 data_time: 0.0028 memory: 1008 2022/11/02 21:47:56 - mmengine - INFO - Epoch(val) [860][50/500] eta: 0:00:21 time: 0.0486 data_time: 0.0030 memory: 1008 2022/11/02 21:47:56 - mmengine - INFO - Epoch(val) [860][55/500] eta: 0:00:21 time: 0.0535 data_time: 0.0039 memory: 1008 2022/11/02 21:47:57 - mmengine - INFO - Epoch(val) [860][60/500] eta: 0:00:20 time: 0.0468 data_time: 0.0041 memory: 1008 2022/11/02 21:47:57 - mmengine - INFO - Epoch(val) [860][65/500] eta: 0:00:20 time: 0.0427 data_time: 0.0031 memory: 1008 2022/11/02 21:47:57 - mmengine - INFO - Epoch(val) [860][70/500] eta: 0:00:20 time: 0.0478 data_time: 0.0033 memory: 1008 2022/11/02 21:47:57 - mmengine - INFO - Epoch(val) [860][75/500] eta: 0:00:20 time: 0.0419 data_time: 0.0033 memory: 1008 2022/11/02 21:47:57 - mmengine - INFO - Epoch(val) [860][80/500] eta: 0:00:15 time: 0.0358 data_time: 0.0028 memory: 1008 2022/11/02 21:47:58 - mmengine - INFO - Epoch(val) [860][85/500] eta: 0:00:15 time: 0.0389 data_time: 0.0029 memory: 1008 2022/11/02 21:47:58 - mmengine - INFO - Epoch(val) [860][90/500] eta: 0:00:17 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 21:47:58 - mmengine - INFO - Epoch(val) [860][95/500] eta: 0:00:17 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 21:47:58 - mmengine - INFO - Epoch(val) [860][100/500] eta: 0:00:17 time: 0.0426 data_time: 0.0027 memory: 1008 2022/11/02 21:47:59 - mmengine - INFO - Epoch(val) [860][105/500] eta: 0:00:17 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 21:47:59 - mmengine - INFO - Epoch(val) [860][110/500] eta: 0:00:14 time: 0.0370 data_time: 0.0027 memory: 1008 2022/11/02 21:47:59 - mmengine - INFO - Epoch(val) [860][115/500] eta: 0:00:14 time: 0.0391 data_time: 0.0026 memory: 1008 2022/11/02 21:47:59 - mmengine - INFO - Epoch(val) [860][120/500] eta: 0:00:15 time: 0.0412 data_time: 0.0034 memory: 1008 2022/11/02 21:47:59 - mmengine - INFO - Epoch(val) [860][125/500] eta: 0:00:15 time: 0.0387 data_time: 0.0031 memory: 1008 2022/11/02 21:48:00 - mmengine - INFO - Epoch(val) [860][130/500] eta: 0:00:13 time: 0.0376 data_time: 0.0023 memory: 1008 2022/11/02 21:48:00 - mmengine - INFO - Epoch(val) [860][135/500] eta: 0:00:13 time: 0.0368 data_time: 0.0026 memory: 1008 2022/11/02 21:48:00 - mmengine - INFO - Epoch(val) [860][140/500] eta: 0:00:13 time: 0.0363 data_time: 0.0027 memory: 1008 2022/11/02 21:48:00 - mmengine - INFO - Epoch(val) [860][145/500] eta: 0:00:13 time: 0.0429 data_time: 0.0036 memory: 1008 2022/11/02 21:48:00 - mmengine - INFO - Epoch(val) [860][150/500] eta: 0:00:16 time: 0.0460 data_time: 0.0038 memory: 1008 2022/11/02 21:48:01 - mmengine - INFO - Epoch(val) [860][155/500] eta: 0:00:16 time: 0.0454 data_time: 0.0028 memory: 1008 2022/11/02 21:48:01 - mmengine - INFO - Epoch(val) [860][160/500] eta: 0:00:14 time: 0.0439 data_time: 0.0026 memory: 1008 2022/11/02 21:48:01 - mmengine - INFO - Epoch(val) [860][165/500] eta: 0:00:14 time: 0.0388 data_time: 0.0025 memory: 1008 2022/11/02 21:48:01 - mmengine - INFO - Epoch(val) [860][170/500] eta: 0:00:13 time: 0.0399 data_time: 0.0024 memory: 1008 2022/11/02 21:48:01 - mmengine - INFO - Epoch(val) [860][175/500] eta: 0:00:13 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/02 21:48:02 - mmengine - INFO - Epoch(val) [860][180/500] eta: 0:00:12 time: 0.0402 data_time: 0.0030 memory: 1008 2022/11/02 21:48:02 - mmengine - INFO - Epoch(val) [860][185/500] eta: 0:00:12 time: 0.0454 data_time: 0.0029 memory: 1008 2022/11/02 21:48:02 - mmengine - INFO - Epoch(val) [860][190/500] eta: 0:00:13 time: 0.0451 data_time: 0.0028 memory: 1008 2022/11/02 21:48:02 - mmengine - INFO - Epoch(val) [860][195/500] eta: 0:00:13 time: 0.0382 data_time: 0.0024 memory: 1008 2022/11/02 21:48:02 - mmengine - INFO - Epoch(val) [860][200/500] eta: 0:00:12 time: 0.0432 data_time: 0.0024 memory: 1008 2022/11/02 21:48:03 - mmengine - INFO - Epoch(val) [860][205/500] eta: 0:00:12 time: 0.0414 data_time: 0.0022 memory: 1008 2022/11/02 21:48:03 - mmengine - INFO - Epoch(val) [860][210/500] eta: 0:00:10 time: 0.0359 data_time: 0.0024 memory: 1008 2022/11/02 21:48:03 - mmengine - INFO - Epoch(val) [860][215/500] eta: 0:00:10 time: 0.0398 data_time: 0.0030 memory: 1008 2022/11/02 21:48:03 - mmengine - INFO - Epoch(val) [860][220/500] eta: 0:00:11 time: 0.0401 data_time: 0.0029 memory: 1008 2022/11/02 21:48:03 - mmengine - INFO - Epoch(val) [860][225/500] eta: 0:00:11 time: 0.0393 data_time: 0.0027 memory: 1008 2022/11/02 21:48:04 - mmengine - INFO - Epoch(val) [860][230/500] eta: 0:00:10 time: 0.0378 data_time: 0.0027 memory: 1008 2022/11/02 21:48:04 - mmengine - INFO - Epoch(val) [860][235/500] eta: 0:00:10 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/02 21:48:04 - mmengine - INFO - Epoch(val) [860][240/500] eta: 0:00:11 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 21:48:04 - mmengine - INFO - Epoch(val) [860][245/500] eta: 0:00:11 time: 0.0420 data_time: 0.0030 memory: 1008 2022/11/02 21:48:04 - mmengine - INFO - Epoch(val) [860][250/500] eta: 0:00:09 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/02 21:48:05 - mmengine - INFO - Epoch(val) [860][255/500] eta: 0:00:09 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/02 21:48:05 - mmengine - INFO - Epoch(val) [860][260/500] eta: 0:00:09 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/02 21:48:05 - mmengine - INFO - Epoch(val) [860][265/500] eta: 0:00:09 time: 0.0380 data_time: 0.0026 memory: 1008 2022/11/02 21:48:05 - mmengine - INFO - Epoch(val) [860][270/500] eta: 0:00:09 time: 0.0397 data_time: 0.0025 memory: 1008 2022/11/02 21:48:05 - mmengine - INFO - Epoch(val) [860][275/500] eta: 0:00:09 time: 0.0393 data_time: 0.0027 memory: 1008 2022/11/02 21:48:06 - mmengine - INFO - Epoch(val) [860][280/500] eta: 0:00:08 time: 0.0402 data_time: 0.0027 memory: 1008 2022/11/02 21:48:06 - mmengine - INFO - Epoch(val) [860][285/500] eta: 0:00:08 time: 0.0417 data_time: 0.0027 memory: 1008 2022/11/02 21:48:06 - mmengine - INFO - Epoch(val) [860][290/500] eta: 0:00:08 time: 0.0428 data_time: 0.0032 memory: 1008 2022/11/02 21:48:06 - mmengine - INFO - Epoch(val) [860][295/500] eta: 0:00:08 time: 0.0433 data_time: 0.0031 memory: 1008 2022/11/02 21:48:06 - mmengine - INFO - Epoch(val) [860][300/500] eta: 0:00:08 time: 0.0409 data_time: 0.0025 memory: 1008 2022/11/02 21:48:07 - mmengine - INFO - Epoch(val) [860][305/500] eta: 0:00:08 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 21:48:07 - mmengine - INFO - Epoch(val) [860][310/500] eta: 0:00:07 time: 0.0385 data_time: 0.0026 memory: 1008 2022/11/02 21:48:07 - mmengine - INFO - Epoch(val) [860][315/500] eta: 0:00:07 time: 0.0422 data_time: 0.0027 memory: 1008 2022/11/02 21:48:07 - mmengine - INFO - Epoch(val) [860][320/500] eta: 0:00:07 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 21:48:08 - mmengine - INFO - Epoch(val) [860][325/500] eta: 0:00:07 time: 0.0479 data_time: 0.0025 memory: 1008 2022/11/02 21:48:08 - mmengine - INFO - Epoch(val) [860][330/500] eta: 0:00:08 time: 0.0497 data_time: 0.0029 memory: 1008 2022/11/02 21:48:08 - mmengine - INFO - Epoch(val) [860][335/500] eta: 0:00:08 time: 0.0360 data_time: 0.0030 memory: 1008 2022/11/02 21:48:08 - mmengine - INFO - Epoch(val) [860][340/500] eta: 0:00:08 time: 0.0514 data_time: 0.0027 memory: 1008 2022/11/02 21:48:08 - mmengine - INFO - Epoch(val) [860][345/500] eta: 0:00:08 time: 0.0536 data_time: 0.0026 memory: 1008 2022/11/02 21:48:09 - mmengine - INFO - Epoch(val) [860][350/500] eta: 0:00:06 time: 0.0438 data_time: 0.0026 memory: 1008 2022/11/02 21:48:09 - mmengine - INFO - Epoch(val) [860][355/500] eta: 0:00:06 time: 0.0442 data_time: 0.0029 memory: 1008 2022/11/02 21:48:09 - mmengine - INFO - Epoch(val) [860][360/500] eta: 0:00:05 time: 0.0394 data_time: 0.0029 memory: 1008 2022/11/02 21:48:09 - mmengine - INFO - Epoch(val) [860][365/500] eta: 0:00:05 time: 0.0391 data_time: 0.0029 memory: 1008 2022/11/02 21:48:09 - mmengine - INFO - Epoch(val) [860][370/500] eta: 0:00:05 time: 0.0391 data_time: 0.0032 memory: 1008 2022/11/02 21:48:10 - mmengine - INFO - Epoch(val) [860][375/500] eta: 0:00:05 time: 0.0389 data_time: 0.0042 memory: 1008 2022/11/02 21:48:10 - mmengine - INFO - Epoch(val) [860][380/500] eta: 0:00:04 time: 0.0393 data_time: 0.0036 memory: 1008 2022/11/02 21:48:10 - mmengine - INFO - Epoch(val) [860][385/500] eta: 0:00:04 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 21:48:10 - mmengine - INFO - Epoch(val) [860][390/500] eta: 0:00:04 time: 0.0390 data_time: 0.0028 memory: 1008 2022/11/02 21:48:10 - mmengine - INFO - Epoch(val) [860][395/500] eta: 0:00:04 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/02 21:48:11 - mmengine - INFO - Epoch(val) [860][400/500] eta: 0:00:03 time: 0.0379 data_time: 0.0027 memory: 1008 2022/11/02 21:48:11 - mmengine - INFO - Epoch(val) [860][405/500] eta: 0:00:03 time: 0.0401 data_time: 0.0030 memory: 1008 2022/11/02 21:48:11 - mmengine - INFO - Epoch(val) [860][410/500] eta: 0:00:03 time: 0.0412 data_time: 0.0029 memory: 1008 2022/11/02 21:48:11 - mmengine - INFO - Epoch(val) [860][415/500] eta: 0:00:03 time: 0.0411 data_time: 0.0028 memory: 1008 2022/11/02 21:48:11 - mmengine - INFO - Epoch(val) [860][420/500] eta: 0:00:03 time: 0.0384 data_time: 0.0031 memory: 1008 2022/11/02 21:48:12 - mmengine - INFO - Epoch(val) [860][425/500] eta: 0:00:03 time: 0.0360 data_time: 0.0029 memory: 1008 2022/11/02 21:48:12 - mmengine - INFO - Epoch(val) [860][430/500] eta: 0:00:02 time: 0.0413 data_time: 0.0032 memory: 1008 2022/11/02 21:48:12 - mmengine - INFO - Epoch(val) [860][435/500] eta: 0:00:02 time: 0.0423 data_time: 0.0033 memory: 1008 2022/11/02 21:48:12 - mmengine - INFO - Epoch(val) [860][440/500] eta: 0:00:02 time: 0.0376 data_time: 0.0026 memory: 1008 2022/11/02 21:48:12 - mmengine - INFO - Epoch(val) [860][445/500] eta: 0:00:02 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 21:48:13 - mmengine - INFO - Epoch(val) [860][450/500] eta: 0:00:01 time: 0.0399 data_time: 0.0025 memory: 1008 2022/11/02 21:48:13 - mmengine - INFO - Epoch(val) [860][455/500] eta: 0:00:01 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/02 21:48:13 - mmengine - INFO - Epoch(val) [860][460/500] eta: 0:00:01 time: 0.0392 data_time: 0.0028 memory: 1008 2022/11/02 21:48:13 - mmengine - INFO - Epoch(val) [860][465/500] eta: 0:00:01 time: 0.0366 data_time: 0.0027 memory: 1008 2022/11/02 21:48:13 - mmengine - INFO - Epoch(val) [860][470/500] eta: 0:00:01 time: 0.0368 data_time: 0.0028 memory: 1008 2022/11/02 21:48:14 - mmengine - INFO - Epoch(val) [860][475/500] eta: 0:00:01 time: 0.0346 data_time: 0.0023 memory: 1008 2022/11/02 21:48:14 - mmengine - INFO - Epoch(val) [860][480/500] eta: 0:00:00 time: 0.0426 data_time: 0.0054 memory: 1008 2022/11/02 21:48:14 - mmengine - INFO - Epoch(val) [860][485/500] eta: 0:00:00 time: 0.0439 data_time: 0.0058 memory: 1008 2022/11/02 21:48:14 - mmengine - INFO - Epoch(val) [860][490/500] eta: 0:00:00 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/02 21:48:14 - mmengine - INFO - Epoch(val) [860][495/500] eta: 0:00:00 time: 0.0439 data_time: 0.0040 memory: 1008 2022/11/02 21:48:15 - mmengine - INFO - Epoch(val) [860][500/500] eta: 0:00:00 time: 0.0400 data_time: 0.0039 memory: 1008 2022/11/02 21:48:15 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8377, precision: 0.7452, hmean: 0.7888 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8377, precision: 0.8052, hmean: 0.8211 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8377, precision: 0.8337, hmean: 0.8357 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8339, precision: 0.8549, hmean: 0.8443 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8185, precision: 0.8831, hmean: 0.8496 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6943, precision: 0.9303, hmean: 0.7951 2022/11/02 21:48:15 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1343, precision: 0.9755, hmean: 0.2361 2022/11/02 21:48:15 - mmengine - INFO - Epoch(val) [860][500/500] icdar/precision: 0.8831 icdar/recall: 0.8185 icdar/hmean: 0.8496 2022/11/02 21:48:21 - mmengine - INFO - Epoch(train) [861][5/63] lr: 6.9399e-04 eta: 0:00:00 time: 0.8440 data_time: 0.2504 memory: 14901 loss: 0.9436 loss_prob: 0.4874 loss_thr: 0.3711 loss_db: 0.0850 2022/11/02 21:48:23 - mmengine - INFO - Epoch(train) [861][10/63] lr: 6.9399e-04 eta: 3:35:22 time: 0.8784 data_time: 0.2506 memory: 14901 loss: 0.9744 loss_prob: 0.5061 loss_thr: 0.3802 loss_db: 0.0881 2022/11/02 21:48:26 - mmengine - INFO - Epoch(train) [861][15/63] lr: 6.9399e-04 eta: 3:35:22 time: 0.5383 data_time: 0.0128 memory: 14901 loss: 0.9968 loss_prob: 0.5168 loss_thr: 0.3893 loss_db: 0.0907 2022/11/02 21:48:29 - mmengine - INFO - Epoch(train) [861][20/63] lr: 6.9399e-04 eta: 3:35:16 time: 0.5187 data_time: 0.0128 memory: 14901 loss: 1.0101 loss_prob: 0.5289 loss_thr: 0.3891 loss_db: 0.0922 2022/11/02 21:48:32 - mmengine - INFO - Epoch(train) [861][25/63] lr: 6.9399e-04 eta: 3:35:16 time: 0.5387 data_time: 0.0230 memory: 14901 loss: 0.9871 loss_prob: 0.5140 loss_thr: 0.3850 loss_db: 0.0881 2022/11/02 21:48:34 - mmengine - INFO - Epoch(train) [861][30/63] lr: 6.9399e-04 eta: 3:35:10 time: 0.5500 data_time: 0.0425 memory: 14901 loss: 1.0003 loss_prob: 0.5210 loss_thr: 0.3911 loss_db: 0.0882 2022/11/02 21:48:37 - mmengine - INFO - Epoch(train) [861][35/63] lr: 6.9399e-04 eta: 3:35:10 time: 0.5115 data_time: 0.0311 memory: 14901 loss: 1.0082 loss_prob: 0.5358 loss_thr: 0.3791 loss_db: 0.0934 2022/11/02 21:48:40 - mmengine - INFO - Epoch(train) [861][40/63] lr: 6.9399e-04 eta: 3:35:04 time: 0.6172 data_time: 0.0113 memory: 14901 loss: 0.9591 loss_prob: 0.4985 loss_thr: 0.3716 loss_db: 0.0890 2022/11/02 21:48:43 - mmengine - INFO - Epoch(train) [861][45/63] lr: 6.9399e-04 eta: 3:35:04 time: 0.6405 data_time: 0.0121 memory: 14901 loss: 0.9761 loss_prob: 0.4980 loss_thr: 0.3907 loss_db: 0.0874 2022/11/02 21:48:46 - mmengine - INFO - Epoch(train) [861][50/63] lr: 6.9399e-04 eta: 3:34:58 time: 0.5640 data_time: 0.0213 memory: 14901 loss: 0.9917 loss_prob: 0.5053 loss_thr: 0.3982 loss_db: 0.0881 2022/11/02 21:48:49 - mmengine - INFO - Epoch(train) [861][55/63] lr: 6.9399e-04 eta: 3:34:58 time: 0.5421 data_time: 0.0257 memory: 14901 loss: 1.0151 loss_prob: 0.5356 loss_thr: 0.3873 loss_db: 0.0922 2022/11/02 21:48:51 - mmengine - INFO - Epoch(train) [861][60/63] lr: 6.9399e-04 eta: 3:34:51 time: 0.4915 data_time: 0.0188 memory: 14901 loss: 1.0140 loss_prob: 0.5426 loss_thr: 0.3790 loss_db: 0.0924 2022/11/02 21:48:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:48:58 - mmengine - INFO - Epoch(train) [862][5/63] lr: 6.9215e-04 eta: 3:34:51 time: 0.7702 data_time: 0.2538 memory: 14901 loss: 1.0649 loss_prob: 0.5610 loss_thr: 0.4084 loss_db: 0.0955 2022/11/02 21:49:00 - mmengine - INFO - Epoch(train) [862][10/63] lr: 6.9215e-04 eta: 3:34:43 time: 0.8036 data_time: 0.2509 memory: 14901 loss: 1.0407 loss_prob: 0.5542 loss_thr: 0.3910 loss_db: 0.0955 2022/11/02 21:49:03 - mmengine - INFO - Epoch(train) [862][15/63] lr: 6.9215e-04 eta: 3:34:43 time: 0.5292 data_time: 0.0085 memory: 14901 loss: 0.9884 loss_prob: 0.5221 loss_thr: 0.3748 loss_db: 0.0915 2022/11/02 21:49:06 - mmengine - INFO - Epoch(train) [862][20/63] lr: 6.9215e-04 eta: 3:34:37 time: 0.5471 data_time: 0.0151 memory: 14901 loss: 1.0127 loss_prob: 0.5350 loss_thr: 0.3872 loss_db: 0.0905 2022/11/02 21:49:09 - mmengine - INFO - Epoch(train) [862][25/63] lr: 6.9215e-04 eta: 3:34:37 time: 0.5792 data_time: 0.0502 memory: 14901 loss: 1.0605 loss_prob: 0.5604 loss_thr: 0.4037 loss_db: 0.0964 2022/11/02 21:49:11 - mmengine - INFO - Epoch(train) [862][30/63] lr: 6.9215e-04 eta: 3:34:31 time: 0.5706 data_time: 0.0426 memory: 14901 loss: 1.0362 loss_prob: 0.5506 loss_thr: 0.3882 loss_db: 0.0975 2022/11/02 21:49:14 - mmengine - INFO - Epoch(train) [862][35/63] lr: 6.9215e-04 eta: 3:34:31 time: 0.4874 data_time: 0.0063 memory: 14901 loss: 0.9999 loss_prob: 0.5252 loss_thr: 0.3840 loss_db: 0.0907 2022/11/02 21:49:16 - mmengine - INFO - Epoch(train) [862][40/63] lr: 6.9215e-04 eta: 3:34:25 time: 0.5126 data_time: 0.0121 memory: 14901 loss: 1.0233 loss_prob: 0.5317 loss_thr: 0.4002 loss_db: 0.0914 2022/11/02 21:49:20 - mmengine - INFO - Epoch(train) [862][45/63] lr: 6.9215e-04 eta: 3:34:25 time: 0.6092 data_time: 0.0151 memory: 14901 loss: 1.0166 loss_prob: 0.5304 loss_thr: 0.3945 loss_db: 0.0916 2022/11/02 21:49:22 - mmengine - INFO - Epoch(train) [862][50/63] lr: 6.9215e-04 eta: 3:34:18 time: 0.5772 data_time: 0.0303 memory: 14901 loss: 1.0308 loss_prob: 0.5435 loss_thr: 0.3924 loss_db: 0.0949 2022/11/02 21:49:25 - mmengine - INFO - Epoch(train) [862][55/63] lr: 6.9215e-04 eta: 3:34:18 time: 0.5377 data_time: 0.0293 memory: 14901 loss: 1.0483 loss_prob: 0.5506 loss_thr: 0.4012 loss_db: 0.0965 2022/11/02 21:49:28 - mmengine - INFO - Epoch(train) [862][60/63] lr: 6.9215e-04 eta: 3:34:12 time: 0.5875 data_time: 0.0109 memory: 14901 loss: 0.9827 loss_prob: 0.5068 loss_thr: 0.3878 loss_db: 0.0882 2022/11/02 21:49:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:49:35 - mmengine - INFO - Epoch(train) [863][5/63] lr: 6.9030e-04 eta: 3:34:12 time: 0.8582 data_time: 0.2685 memory: 14901 loss: 0.9813 loss_prob: 0.5082 loss_thr: 0.3841 loss_db: 0.0890 2022/11/02 21:49:38 - mmengine - INFO - Epoch(train) [863][10/63] lr: 6.9030e-04 eta: 3:34:05 time: 0.8672 data_time: 0.2720 memory: 14901 loss: 0.9708 loss_prob: 0.5063 loss_thr: 0.3776 loss_db: 0.0869 2022/11/02 21:49:41 - mmengine - INFO - Epoch(train) [863][15/63] lr: 6.9030e-04 eta: 3:34:05 time: 0.5503 data_time: 0.0160 memory: 14901 loss: 0.9164 loss_prob: 0.4746 loss_thr: 0.3607 loss_db: 0.0811 2022/11/02 21:49:44 - mmengine - INFO - Epoch(train) [863][20/63] lr: 6.9030e-04 eta: 3:33:59 time: 0.5531 data_time: 0.0121 memory: 14901 loss: 0.9385 loss_prob: 0.4874 loss_thr: 0.3661 loss_db: 0.0850 2022/11/02 21:49:46 - mmengine - INFO - Epoch(train) [863][25/63] lr: 6.9030e-04 eta: 3:33:59 time: 0.5690 data_time: 0.0317 memory: 14901 loss: 1.2045 loss_prob: 0.6898 loss_thr: 0.4084 loss_db: 0.1064 2022/11/02 21:49:49 - mmengine - INFO - Epoch(train) [863][30/63] lr: 6.9030e-04 eta: 3:33:52 time: 0.5478 data_time: 0.0402 memory: 14901 loss: 1.2195 loss_prob: 0.7081 loss_thr: 0.4011 loss_db: 0.1103 2022/11/02 21:49:52 - mmengine - INFO - Epoch(train) [863][35/63] lr: 6.9030e-04 eta: 3:33:52 time: 0.5256 data_time: 0.0219 memory: 14901 loss: 1.0539 loss_prob: 0.5618 loss_thr: 0.3932 loss_db: 0.0989 2022/11/02 21:49:54 - mmengine - INFO - Epoch(train) [863][40/63] lr: 6.9030e-04 eta: 3:33:46 time: 0.5096 data_time: 0.0134 memory: 14901 loss: 1.0116 loss_prob: 0.5290 loss_thr: 0.3894 loss_db: 0.0932 2022/11/02 21:49:57 - mmengine - INFO - Epoch(train) [863][45/63] lr: 6.9030e-04 eta: 3:33:46 time: 0.4858 data_time: 0.0108 memory: 14901 loss: 0.9360 loss_prob: 0.4781 loss_thr: 0.3725 loss_db: 0.0854 2022/11/02 21:49:59 - mmengine - INFO - Epoch(train) [863][50/63] lr: 6.9030e-04 eta: 3:33:39 time: 0.4884 data_time: 0.0177 memory: 14901 loss: 1.0012 loss_prob: 0.5170 loss_thr: 0.3938 loss_db: 0.0904 2022/11/02 21:50:02 - mmengine - INFO - Epoch(train) [863][55/63] lr: 6.9030e-04 eta: 3:33:39 time: 0.5646 data_time: 0.0252 memory: 14901 loss: 1.0173 loss_prob: 0.5224 loss_thr: 0.4048 loss_db: 0.0901 2022/11/02 21:50:05 - mmengine - INFO - Epoch(train) [863][60/63] lr: 6.9030e-04 eta: 3:33:33 time: 0.5792 data_time: 0.0194 memory: 14901 loss: 0.9640 loss_prob: 0.4913 loss_thr: 0.3868 loss_db: 0.0860 2022/11/02 21:50:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:50:12 - mmengine - INFO - Epoch(train) [864][5/63] lr: 6.8846e-04 eta: 3:33:33 time: 0.8300 data_time: 0.2304 memory: 14901 loss: 0.9321 loss_prob: 0.4853 loss_thr: 0.3637 loss_db: 0.0831 2022/11/02 21:50:15 - mmengine - INFO - Epoch(train) [864][10/63] lr: 6.8846e-04 eta: 3:33:26 time: 0.8760 data_time: 0.2314 memory: 14901 loss: 0.9480 loss_prob: 0.4947 loss_thr: 0.3662 loss_db: 0.0871 2022/11/02 21:50:18 - mmengine - INFO - Epoch(train) [864][15/63] lr: 6.8846e-04 eta: 3:33:26 time: 0.5520 data_time: 0.0163 memory: 14901 loss: 0.9881 loss_prob: 0.5156 loss_thr: 0.3836 loss_db: 0.0889 2022/11/02 21:50:20 - mmengine - INFO - Epoch(train) [864][20/63] lr: 6.8846e-04 eta: 3:33:20 time: 0.5510 data_time: 0.0173 memory: 14901 loss: 1.0185 loss_prob: 0.5251 loss_thr: 0.4041 loss_db: 0.0892 2022/11/02 21:50:23 - mmengine - INFO - Epoch(train) [864][25/63] lr: 6.8846e-04 eta: 3:33:20 time: 0.5483 data_time: 0.0162 memory: 14901 loss: 0.9531 loss_prob: 0.4866 loss_thr: 0.3812 loss_db: 0.0853 2022/11/02 21:50:26 - mmengine - INFO - Epoch(train) [864][30/63] lr: 6.8846e-04 eta: 3:33:13 time: 0.5526 data_time: 0.0410 memory: 14901 loss: 0.9662 loss_prob: 0.4972 loss_thr: 0.3823 loss_db: 0.0867 2022/11/02 21:50:29 - mmengine - INFO - Epoch(train) [864][35/63] lr: 6.8846e-04 eta: 3:33:13 time: 0.5586 data_time: 0.0371 memory: 14901 loss: 1.0656 loss_prob: 0.5593 loss_thr: 0.4098 loss_db: 0.0965 2022/11/02 21:50:31 - mmengine - INFO - Epoch(train) [864][40/63] lr: 6.8846e-04 eta: 3:33:07 time: 0.5309 data_time: 0.0185 memory: 14901 loss: 1.0621 loss_prob: 0.5611 loss_thr: 0.4043 loss_db: 0.0967 2022/11/02 21:50:34 - mmengine - INFO - Epoch(train) [864][45/63] lr: 6.8846e-04 eta: 3:33:07 time: 0.5035 data_time: 0.0171 memory: 14901 loss: 1.0425 loss_prob: 0.5447 loss_thr: 0.4031 loss_db: 0.0947 2022/11/02 21:50:36 - mmengine - INFO - Epoch(train) [864][50/63] lr: 6.8846e-04 eta: 3:33:01 time: 0.5185 data_time: 0.0242 memory: 14901 loss: 1.0194 loss_prob: 0.5325 loss_thr: 0.3940 loss_db: 0.0929 2022/11/02 21:50:39 - mmengine - INFO - Epoch(train) [864][55/63] lr: 6.8846e-04 eta: 3:33:01 time: 0.5065 data_time: 0.0281 memory: 14901 loss: 1.0030 loss_prob: 0.5264 loss_thr: 0.3860 loss_db: 0.0906 2022/11/02 21:50:41 - mmengine - INFO - Epoch(train) [864][60/63] lr: 6.8846e-04 eta: 3:32:54 time: 0.4744 data_time: 0.0126 memory: 14901 loss: 0.9652 loss_prob: 0.5010 loss_thr: 0.3772 loss_db: 0.0869 2022/11/02 21:50:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:50:49 - mmengine - INFO - Epoch(train) [865][5/63] lr: 6.8662e-04 eta: 3:32:54 time: 0.9166 data_time: 0.2368 memory: 14901 loss: 0.9050 loss_prob: 0.4646 loss_thr: 0.3583 loss_db: 0.0821 2022/11/02 21:50:52 - mmengine - INFO - Epoch(train) [865][10/63] lr: 6.8662e-04 eta: 3:32:47 time: 0.8782 data_time: 0.2378 memory: 14901 loss: 0.9656 loss_prob: 0.4977 loss_thr: 0.3805 loss_db: 0.0874 2022/11/02 21:50:55 - mmengine - INFO - Epoch(train) [865][15/63] lr: 6.8662e-04 eta: 3:32:47 time: 0.5360 data_time: 0.0193 memory: 14901 loss: 0.9647 loss_prob: 0.4979 loss_thr: 0.3800 loss_db: 0.0867 2022/11/02 21:50:57 - mmengine - INFO - Epoch(train) [865][20/63] lr: 6.8662e-04 eta: 3:32:40 time: 0.5394 data_time: 0.0164 memory: 14901 loss: 0.9636 loss_prob: 0.4923 loss_thr: 0.3849 loss_db: 0.0864 2022/11/02 21:51:00 - mmengine - INFO - Epoch(train) [865][25/63] lr: 6.8662e-04 eta: 3:32:40 time: 0.5344 data_time: 0.0325 memory: 14901 loss: 0.9383 loss_prob: 0.4794 loss_thr: 0.3760 loss_db: 0.0829 2022/11/02 21:51:03 - mmengine - INFO - Epoch(train) [865][30/63] lr: 6.8662e-04 eta: 3:32:34 time: 0.5316 data_time: 0.0331 memory: 14901 loss: 0.9616 loss_prob: 0.4935 loss_thr: 0.3821 loss_db: 0.0860 2022/11/02 21:51:05 - mmengine - INFO - Epoch(train) [865][35/63] lr: 6.8662e-04 eta: 3:32:34 time: 0.5323 data_time: 0.0126 memory: 14901 loss: 1.0193 loss_prob: 0.5294 loss_thr: 0.3978 loss_db: 0.0921 2022/11/02 21:51:08 - mmengine - INFO - Epoch(train) [865][40/63] lr: 6.8662e-04 eta: 3:32:28 time: 0.5261 data_time: 0.0129 memory: 14901 loss: 1.0103 loss_prob: 0.5359 loss_thr: 0.3822 loss_db: 0.0923 2022/11/02 21:51:11 - mmengine - INFO - Epoch(train) [865][45/63] lr: 6.8662e-04 eta: 3:32:28 time: 0.5060 data_time: 0.0085 memory: 14901 loss: 1.0845 loss_prob: 0.5764 loss_thr: 0.4127 loss_db: 0.0954 2022/11/02 21:51:13 - mmengine - INFO - Epoch(train) [865][50/63] lr: 6.8662e-04 eta: 3:32:21 time: 0.5060 data_time: 0.0244 memory: 14901 loss: 1.0578 loss_prob: 0.5517 loss_thr: 0.4120 loss_db: 0.0941 2022/11/02 21:51:16 - mmengine - INFO - Epoch(train) [865][55/63] lr: 6.8662e-04 eta: 3:32:21 time: 0.5234 data_time: 0.0268 memory: 14901 loss: 0.9164 loss_prob: 0.4706 loss_thr: 0.3604 loss_db: 0.0853 2022/11/02 21:51:18 - mmengine - INFO - Epoch(train) [865][60/63] lr: 6.8662e-04 eta: 3:32:15 time: 0.5386 data_time: 0.0132 memory: 14901 loss: 0.8900 loss_prob: 0.4577 loss_thr: 0.3514 loss_db: 0.0809 2022/11/02 21:51:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:51:26 - mmengine - INFO - Epoch(train) [866][5/63] lr: 6.8477e-04 eta: 3:32:15 time: 0.9015 data_time: 0.2750 memory: 14901 loss: 0.9848 loss_prob: 0.5327 loss_thr: 0.3621 loss_db: 0.0899 2022/11/02 21:51:29 - mmengine - INFO - Epoch(train) [866][10/63] lr: 6.8477e-04 eta: 3:32:08 time: 0.9067 data_time: 0.2713 memory: 14901 loss: 0.9480 loss_prob: 0.4960 loss_thr: 0.3658 loss_db: 0.0862 2022/11/02 21:51:31 - mmengine - INFO - Epoch(train) [866][15/63] lr: 6.8477e-04 eta: 3:32:08 time: 0.5007 data_time: 0.0089 memory: 14901 loss: 1.0439 loss_prob: 0.5479 loss_thr: 0.3989 loss_db: 0.0971 2022/11/02 21:51:34 - mmengine - INFO - Epoch(train) [866][20/63] lr: 6.8477e-04 eta: 3:32:01 time: 0.4972 data_time: 0.0125 memory: 14901 loss: 1.0433 loss_prob: 0.5578 loss_thr: 0.3874 loss_db: 0.0981 2022/11/02 21:51:37 - mmengine - INFO - Epoch(train) [866][25/63] lr: 6.8477e-04 eta: 3:32:01 time: 0.5723 data_time: 0.0448 memory: 14901 loss: 1.0117 loss_prob: 0.5494 loss_thr: 0.3695 loss_db: 0.0928 2022/11/02 21:51:40 - mmengine - INFO - Epoch(train) [866][30/63] lr: 6.8477e-04 eta: 3:31:55 time: 0.5689 data_time: 0.0412 memory: 14901 loss: 0.9734 loss_prob: 0.5157 loss_thr: 0.3694 loss_db: 0.0883 2022/11/02 21:51:42 - mmengine - INFO - Epoch(train) [866][35/63] lr: 6.8477e-04 eta: 3:31:55 time: 0.4828 data_time: 0.0072 memory: 14901 loss: 0.9524 loss_prob: 0.4944 loss_thr: 0.3720 loss_db: 0.0860 2022/11/02 21:51:45 - mmengine - INFO - Epoch(train) [866][40/63] lr: 6.8477e-04 eta: 3:31:49 time: 0.5127 data_time: 0.0053 memory: 14901 loss: 1.0096 loss_prob: 0.5263 loss_thr: 0.3916 loss_db: 0.0917 2022/11/02 21:51:48 - mmengine - INFO - Epoch(train) [866][45/63] lr: 6.8477e-04 eta: 3:31:49 time: 0.5839 data_time: 0.0100 memory: 14901 loss: 0.9809 loss_prob: 0.5118 loss_thr: 0.3796 loss_db: 0.0896 2022/11/02 21:51:51 - mmengine - INFO - Epoch(train) [866][50/63] lr: 6.8477e-04 eta: 3:31:43 time: 0.5913 data_time: 0.0291 memory: 14901 loss: 0.9534 loss_prob: 0.4961 loss_thr: 0.3711 loss_db: 0.0862 2022/11/02 21:51:53 - mmengine - INFO - Epoch(train) [866][55/63] lr: 6.8477e-04 eta: 3:31:43 time: 0.5195 data_time: 0.0278 memory: 14901 loss: 0.9750 loss_prob: 0.5043 loss_thr: 0.3824 loss_db: 0.0884 2022/11/02 21:51:56 - mmengine - INFO - Epoch(train) [866][60/63] lr: 6.8477e-04 eta: 3:31:36 time: 0.5026 data_time: 0.0117 memory: 14901 loss: 0.9694 loss_prob: 0.4928 loss_thr: 0.3910 loss_db: 0.0856 2022/11/02 21:51:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:52:02 - mmengine - INFO - Epoch(train) [867][5/63] lr: 6.8293e-04 eta: 3:31:36 time: 0.7822 data_time: 0.2204 memory: 14901 loss: 0.9614 loss_prob: 0.4908 loss_thr: 0.3837 loss_db: 0.0869 2022/11/02 21:52:06 - mmengine - INFO - Epoch(train) [867][10/63] lr: 6.8293e-04 eta: 3:31:29 time: 0.9483 data_time: 0.2301 memory: 14901 loss: 1.0792 loss_prob: 0.5666 loss_thr: 0.4145 loss_db: 0.0981 2022/11/02 21:52:09 - mmengine - INFO - Epoch(train) [867][15/63] lr: 6.8293e-04 eta: 3:31:29 time: 0.6542 data_time: 0.0196 memory: 14901 loss: 1.0659 loss_prob: 0.5589 loss_thr: 0.4129 loss_db: 0.0942 2022/11/02 21:52:12 - mmengine - INFO - Epoch(train) [867][20/63] lr: 6.8293e-04 eta: 3:31:23 time: 0.5602 data_time: 0.0121 memory: 14901 loss: 0.9704 loss_prob: 0.4987 loss_thr: 0.3869 loss_db: 0.0847 2022/11/02 21:52:14 - mmengine - INFO - Epoch(train) [867][25/63] lr: 6.8293e-04 eta: 3:31:23 time: 0.5410 data_time: 0.0159 memory: 14901 loss: 0.9625 loss_prob: 0.4943 loss_thr: 0.3815 loss_db: 0.0868 2022/11/02 21:52:17 - mmengine - INFO - Epoch(train) [867][30/63] lr: 6.8293e-04 eta: 3:31:16 time: 0.5267 data_time: 0.0469 memory: 14901 loss: 0.9290 loss_prob: 0.4787 loss_thr: 0.3654 loss_db: 0.0849 2022/11/02 21:52:20 - mmengine - INFO - Epoch(train) [867][35/63] lr: 6.8293e-04 eta: 3:31:16 time: 0.5535 data_time: 0.0434 memory: 14901 loss: 0.9145 loss_prob: 0.4730 loss_thr: 0.3586 loss_db: 0.0829 2022/11/02 21:52:23 - mmengine - INFO - Epoch(train) [867][40/63] lr: 6.8293e-04 eta: 3:31:10 time: 0.5347 data_time: 0.0116 memory: 14901 loss: 0.9640 loss_prob: 0.5071 loss_thr: 0.3694 loss_db: 0.0875 2022/11/02 21:52:25 - mmengine - INFO - Epoch(train) [867][45/63] lr: 6.8293e-04 eta: 3:31:10 time: 0.5149 data_time: 0.0118 memory: 14901 loss: 0.9411 loss_prob: 0.4914 loss_thr: 0.3640 loss_db: 0.0857 2022/11/02 21:52:28 - mmengine - INFO - Epoch(train) [867][50/63] lr: 6.8293e-04 eta: 3:31:04 time: 0.5209 data_time: 0.0271 memory: 14901 loss: 0.9033 loss_prob: 0.4618 loss_thr: 0.3603 loss_db: 0.0812 2022/11/02 21:52:31 - mmengine - INFO - Epoch(train) [867][55/63] lr: 6.8293e-04 eta: 3:31:04 time: 0.5553 data_time: 0.0515 memory: 14901 loss: 0.9186 loss_prob: 0.4750 loss_thr: 0.3605 loss_db: 0.0831 2022/11/02 21:52:33 - mmengine - INFO - Epoch(train) [867][60/63] lr: 6.8293e-04 eta: 3:30:58 time: 0.5415 data_time: 0.0393 memory: 14901 loss: 1.0256 loss_prob: 0.5327 loss_thr: 0.4001 loss_db: 0.0929 2022/11/02 21:52:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:52:41 - mmengine - INFO - Epoch(train) [868][5/63] lr: 6.8108e-04 eta: 3:30:58 time: 0.8335 data_time: 0.2274 memory: 14901 loss: 1.0387 loss_prob: 0.5475 loss_thr: 0.3954 loss_db: 0.0958 2022/11/02 21:52:43 - mmengine - INFO - Epoch(train) [868][10/63] lr: 6.8108e-04 eta: 3:30:50 time: 0.8505 data_time: 0.2283 memory: 14901 loss: 0.9559 loss_prob: 0.5013 loss_thr: 0.3650 loss_db: 0.0896 2022/11/02 21:52:46 - mmengine - INFO - Epoch(train) [868][15/63] lr: 6.8108e-04 eta: 3:30:50 time: 0.5314 data_time: 0.0121 memory: 14901 loss: 0.9599 loss_prob: 0.4986 loss_thr: 0.3749 loss_db: 0.0864 2022/11/02 21:52:48 - mmengine - INFO - Epoch(train) [868][20/63] lr: 6.8108e-04 eta: 3:30:44 time: 0.5509 data_time: 0.0166 memory: 14901 loss: 0.9610 loss_prob: 0.5019 loss_thr: 0.3738 loss_db: 0.0853 2022/11/02 21:52:51 - mmengine - INFO - Epoch(train) [868][25/63] lr: 6.8108e-04 eta: 3:30:44 time: 0.5419 data_time: 0.0195 memory: 14901 loss: 0.9379 loss_prob: 0.4932 loss_thr: 0.3564 loss_db: 0.0882 2022/11/02 21:52:54 - mmengine - INFO - Epoch(train) [868][30/63] lr: 6.8108e-04 eta: 3:30:38 time: 0.5959 data_time: 0.0434 memory: 14901 loss: 1.0006 loss_prob: 0.5226 loss_thr: 0.3846 loss_db: 0.0934 2022/11/02 21:52:57 - mmengine - INFO - Epoch(train) [868][35/63] lr: 6.8108e-04 eta: 3:30:38 time: 0.6080 data_time: 0.0398 memory: 14901 loss: 1.0302 loss_prob: 0.5313 loss_thr: 0.4070 loss_db: 0.0919 2022/11/02 21:53:00 - mmengine - INFO - Epoch(train) [868][40/63] lr: 6.8108e-04 eta: 3:30:31 time: 0.5159 data_time: 0.0093 memory: 14901 loss: 0.9470 loss_prob: 0.4848 loss_thr: 0.3781 loss_db: 0.0842 2022/11/02 21:53:02 - mmengine - INFO - Epoch(train) [868][45/63] lr: 6.8108e-04 eta: 3:30:31 time: 0.4785 data_time: 0.0092 memory: 14901 loss: 0.8892 loss_prob: 0.4592 loss_thr: 0.3493 loss_db: 0.0807 2022/11/02 21:53:05 - mmengine - INFO - Epoch(train) [868][50/63] lr: 6.8108e-04 eta: 3:30:25 time: 0.5448 data_time: 0.0153 memory: 14901 loss: 0.9461 loss_prob: 0.4982 loss_thr: 0.3613 loss_db: 0.0866 2022/11/02 21:53:08 - mmengine - INFO - Epoch(train) [868][55/63] lr: 6.8108e-04 eta: 3:30:25 time: 0.5750 data_time: 0.0288 memory: 14901 loss: 0.9802 loss_prob: 0.5075 loss_thr: 0.3842 loss_db: 0.0884 2022/11/02 21:53:11 - mmengine - INFO - Epoch(train) [868][60/63] lr: 6.8108e-04 eta: 3:30:19 time: 0.5471 data_time: 0.0243 memory: 14901 loss: 1.0038 loss_prob: 0.5123 loss_thr: 0.4015 loss_db: 0.0900 2022/11/02 21:53:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:53:17 - mmengine - INFO - Epoch(train) [869][5/63] lr: 6.7923e-04 eta: 3:30:19 time: 0.7575 data_time: 0.1888 memory: 14901 loss: 1.0347 loss_prob: 0.5514 loss_thr: 0.3884 loss_db: 0.0950 2022/11/02 21:53:20 - mmengine - INFO - Epoch(train) [869][10/63] lr: 6.7923e-04 eta: 3:30:11 time: 0.7856 data_time: 0.1921 memory: 14901 loss: 0.9976 loss_prob: 0.5197 loss_thr: 0.3869 loss_db: 0.0910 2022/11/02 21:53:22 - mmengine - INFO - Epoch(train) [869][15/63] lr: 6.7923e-04 eta: 3:30:11 time: 0.5140 data_time: 0.0174 memory: 14901 loss: 1.0200 loss_prob: 0.5419 loss_thr: 0.3865 loss_db: 0.0917 2022/11/02 21:53:25 - mmengine - INFO - Epoch(train) [869][20/63] lr: 6.7923e-04 eta: 3:30:04 time: 0.4928 data_time: 0.0121 memory: 14901 loss: 1.0647 loss_prob: 0.5724 loss_thr: 0.3981 loss_db: 0.0941 2022/11/02 21:53:27 - mmengine - INFO - Epoch(train) [869][25/63] lr: 6.7923e-04 eta: 3:30:04 time: 0.5073 data_time: 0.0278 memory: 14901 loss: 0.9562 loss_prob: 0.4995 loss_thr: 0.3707 loss_db: 0.0860 2022/11/02 21:53:31 - mmengine - INFO - Epoch(train) [869][30/63] lr: 6.7923e-04 eta: 3:29:58 time: 0.6085 data_time: 0.0388 memory: 14901 loss: 0.9430 loss_prob: 0.4952 loss_thr: 0.3607 loss_db: 0.0871 2022/11/02 21:53:33 - mmengine - INFO - Epoch(train) [869][35/63] lr: 6.7923e-04 eta: 3:29:58 time: 0.6070 data_time: 0.0292 memory: 14901 loss: 0.9711 loss_prob: 0.5145 loss_thr: 0.3678 loss_db: 0.0888 2022/11/02 21:53:36 - mmengine - INFO - Epoch(train) [869][40/63] lr: 6.7923e-04 eta: 3:29:52 time: 0.5197 data_time: 0.0208 memory: 14901 loss: 0.9728 loss_prob: 0.5080 loss_thr: 0.3774 loss_db: 0.0873 2022/11/02 21:53:38 - mmengine - INFO - Epoch(train) [869][45/63] lr: 6.7923e-04 eta: 3:29:52 time: 0.5045 data_time: 0.0146 memory: 14901 loss: 0.9865 loss_prob: 0.5144 loss_thr: 0.3809 loss_db: 0.0913 2022/11/02 21:53:41 - mmengine - INFO - Epoch(train) [869][50/63] lr: 6.7923e-04 eta: 3:29:46 time: 0.4834 data_time: 0.0221 memory: 14901 loss: 0.9892 loss_prob: 0.5234 loss_thr: 0.3722 loss_db: 0.0936 2022/11/02 21:53:43 - mmengine - INFO - Epoch(train) [869][55/63] lr: 6.7923e-04 eta: 3:29:46 time: 0.5017 data_time: 0.0306 memory: 14901 loss: 0.9803 loss_prob: 0.5180 loss_thr: 0.3711 loss_db: 0.0911 2022/11/02 21:53:46 - mmengine - INFO - Epoch(train) [869][60/63] lr: 6.7923e-04 eta: 3:29:39 time: 0.4981 data_time: 0.0216 memory: 14901 loss: 1.0409 loss_prob: 0.5492 loss_thr: 0.3969 loss_db: 0.0948 2022/11/02 21:53:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:53:53 - mmengine - INFO - Epoch(train) [870][5/63] lr: 6.7739e-04 eta: 3:29:39 time: 0.7764 data_time: 0.2591 memory: 14901 loss: 0.9944 loss_prob: 0.5127 loss_thr: 0.3903 loss_db: 0.0913 2022/11/02 21:53:55 - mmengine - INFO - Epoch(train) [870][10/63] lr: 6.7739e-04 eta: 3:29:31 time: 0.7946 data_time: 0.2628 memory: 14901 loss: 1.0119 loss_prob: 0.5226 loss_thr: 0.3984 loss_db: 0.0910 2022/11/02 21:53:59 - mmengine - INFO - Epoch(train) [870][15/63] lr: 6.7739e-04 eta: 3:29:31 time: 0.6162 data_time: 0.0163 memory: 14901 loss: 1.0309 loss_prob: 0.5453 loss_thr: 0.3960 loss_db: 0.0897 2022/11/02 21:54:02 - mmengine - INFO - Epoch(train) [870][20/63] lr: 6.7739e-04 eta: 3:29:26 time: 0.6707 data_time: 0.0127 memory: 14901 loss: 1.0138 loss_prob: 0.5337 loss_thr: 0.3900 loss_db: 0.0901 2022/11/02 21:54:05 - mmengine - INFO - Epoch(train) [870][25/63] lr: 6.7739e-04 eta: 3:29:26 time: 0.5910 data_time: 0.0241 memory: 14901 loss: 1.0665 loss_prob: 0.5504 loss_thr: 0.4205 loss_db: 0.0956 2022/11/02 21:54:08 - mmengine - INFO - Epoch(train) [870][30/63] lr: 6.7739e-04 eta: 3:29:20 time: 0.6058 data_time: 0.0379 memory: 14901 loss: 0.9757 loss_prob: 0.4955 loss_thr: 0.3953 loss_db: 0.0850 2022/11/02 21:54:11 - mmengine - INFO - Epoch(train) [870][35/63] lr: 6.7739e-04 eta: 3:29:20 time: 0.6068 data_time: 0.0310 memory: 14901 loss: 0.8741 loss_prob: 0.4375 loss_thr: 0.3592 loss_db: 0.0774 2022/11/02 21:54:14 - mmengine - INFO - Epoch(train) [870][40/63] lr: 6.7739e-04 eta: 3:29:14 time: 0.5937 data_time: 0.0148 memory: 14901 loss: 0.9201 loss_prob: 0.4716 loss_thr: 0.3650 loss_db: 0.0835 2022/11/02 21:54:17 - mmengine - INFO - Epoch(train) [870][45/63] lr: 6.7739e-04 eta: 3:29:14 time: 0.6175 data_time: 0.0128 memory: 14901 loss: 0.9474 loss_prob: 0.4924 loss_thr: 0.3702 loss_db: 0.0848 2022/11/02 21:54:20 - mmengine - INFO - Epoch(train) [870][50/63] lr: 6.7739e-04 eta: 3:29:07 time: 0.5763 data_time: 0.0293 memory: 14901 loss: 1.0006 loss_prob: 0.5314 loss_thr: 0.3790 loss_db: 0.0902 2022/11/02 21:54:22 - mmengine - INFO - Epoch(train) [870][55/63] lr: 6.7739e-04 eta: 3:29:07 time: 0.5361 data_time: 0.0275 memory: 14901 loss: 0.9808 loss_prob: 0.5162 loss_thr: 0.3741 loss_db: 0.0905 2022/11/02 21:54:25 - mmengine - INFO - Epoch(train) [870][60/63] lr: 6.7739e-04 eta: 3:29:01 time: 0.5476 data_time: 0.0117 memory: 14901 loss: 1.0529 loss_prob: 0.5490 loss_thr: 0.4073 loss_db: 0.0966 2022/11/02 21:54:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:54:31 - mmengine - INFO - Epoch(train) [871][5/63] lr: 6.7554e-04 eta: 3:29:01 time: 0.7427 data_time: 0.2266 memory: 14901 loss: 1.0500 loss_prob: 0.5459 loss_thr: 0.4109 loss_db: 0.0932 2022/11/02 21:54:34 - mmengine - INFO - Epoch(train) [871][10/63] lr: 6.7554e-04 eta: 3:28:53 time: 0.8126 data_time: 0.2255 memory: 14901 loss: 0.9311 loss_prob: 0.4738 loss_thr: 0.3746 loss_db: 0.0828 2022/11/02 21:54:37 - mmengine - INFO - Epoch(train) [871][15/63] lr: 6.7554e-04 eta: 3:28:53 time: 0.5826 data_time: 0.0107 memory: 14901 loss: 0.9318 loss_prob: 0.4725 loss_thr: 0.3752 loss_db: 0.0841 2022/11/02 21:54:40 - mmengine - INFO - Epoch(train) [871][20/63] lr: 6.7554e-04 eta: 3:28:47 time: 0.5245 data_time: 0.0111 memory: 14901 loss: 0.9752 loss_prob: 0.5062 loss_thr: 0.3813 loss_db: 0.0876 2022/11/02 21:54:43 - mmengine - INFO - Epoch(train) [871][25/63] lr: 6.7554e-04 eta: 3:28:47 time: 0.5884 data_time: 0.0308 memory: 14901 loss: 1.0099 loss_prob: 0.5286 loss_thr: 0.3911 loss_db: 0.0902 2022/11/02 21:54:46 - mmengine - INFO - Epoch(train) [871][30/63] lr: 6.7554e-04 eta: 3:28:41 time: 0.6034 data_time: 0.0455 memory: 14901 loss: 1.0454 loss_prob: 0.5443 loss_thr: 0.4067 loss_db: 0.0945 2022/11/02 21:54:48 - mmengine - INFO - Epoch(train) [871][35/63] lr: 6.7554e-04 eta: 3:28:41 time: 0.5065 data_time: 0.0275 memory: 14901 loss: 1.0019 loss_prob: 0.5234 loss_thr: 0.3864 loss_db: 0.0920 2022/11/02 21:54:51 - mmengine - INFO - Epoch(train) [871][40/63] lr: 6.7554e-04 eta: 3:28:35 time: 0.5272 data_time: 0.0128 memory: 14901 loss: 0.9350 loss_prob: 0.4866 loss_thr: 0.3632 loss_db: 0.0851 2022/11/02 21:54:53 - mmengine - INFO - Epoch(train) [871][45/63] lr: 6.7554e-04 eta: 3:28:35 time: 0.5261 data_time: 0.0108 memory: 14901 loss: 0.9510 loss_prob: 0.5008 loss_thr: 0.3648 loss_db: 0.0854 2022/11/02 21:54:57 - mmengine - INFO - Epoch(train) [871][50/63] lr: 6.7554e-04 eta: 3:28:29 time: 0.5868 data_time: 0.0322 memory: 14901 loss: 1.0105 loss_prob: 0.5343 loss_thr: 0.3853 loss_db: 0.0910 2022/11/02 21:54:59 - mmengine - INFO - Epoch(train) [871][55/63] lr: 6.7554e-04 eta: 3:28:29 time: 0.6042 data_time: 0.0392 memory: 14901 loss: 1.0366 loss_prob: 0.5357 loss_thr: 0.4077 loss_db: 0.0931 2022/11/02 21:55:02 - mmengine - INFO - Epoch(train) [871][60/63] lr: 6.7554e-04 eta: 3:28:22 time: 0.5429 data_time: 0.0202 memory: 14901 loss: 1.0398 loss_prob: 0.5337 loss_thr: 0.4115 loss_db: 0.0946 2022/11/02 21:55:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:55:08 - mmengine - INFO - Epoch(train) [872][5/63] lr: 6.7369e-04 eta: 3:28:22 time: 0.7263 data_time: 0.2222 memory: 14901 loss: 0.9600 loss_prob: 0.5074 loss_thr: 0.3660 loss_db: 0.0866 2022/11/02 21:55:11 - mmengine - INFO - Epoch(train) [872][10/63] lr: 6.7369e-04 eta: 3:28:14 time: 0.7634 data_time: 0.2207 memory: 14901 loss: 1.0490 loss_prob: 0.5563 loss_thr: 0.3961 loss_db: 0.0966 2022/11/02 21:55:14 - mmengine - INFO - Epoch(train) [872][15/63] lr: 6.7369e-04 eta: 3:28:14 time: 0.5255 data_time: 0.0102 memory: 14901 loss: 1.0013 loss_prob: 0.5194 loss_thr: 0.3921 loss_db: 0.0898 2022/11/02 21:55:16 - mmengine - INFO - Epoch(train) [872][20/63] lr: 6.7369e-04 eta: 3:28:08 time: 0.5013 data_time: 0.0164 memory: 14901 loss: 0.9262 loss_prob: 0.4743 loss_thr: 0.3697 loss_db: 0.0821 2022/11/02 21:55:19 - mmengine - INFO - Epoch(train) [872][25/63] lr: 6.7369e-04 eta: 3:28:08 time: 0.5882 data_time: 0.0280 memory: 14901 loss: 1.0377 loss_prob: 0.5409 loss_thr: 0.4017 loss_db: 0.0951 2022/11/02 21:55:22 - mmengine - INFO - Epoch(train) [872][30/63] lr: 6.7369e-04 eta: 3:28:02 time: 0.5928 data_time: 0.0353 memory: 14901 loss: 1.0328 loss_prob: 0.5292 loss_thr: 0.4129 loss_db: 0.0906 2022/11/02 21:55:25 - mmengine - INFO - Epoch(train) [872][35/63] lr: 6.7369e-04 eta: 3:28:02 time: 0.5128 data_time: 0.0225 memory: 14901 loss: 0.9907 loss_prob: 0.5100 loss_thr: 0.3942 loss_db: 0.0864 2022/11/02 21:55:27 - mmengine - INFO - Epoch(train) [872][40/63] lr: 6.7369e-04 eta: 3:27:56 time: 0.4961 data_time: 0.0123 memory: 14901 loss: 1.0054 loss_prob: 0.5308 loss_thr: 0.3815 loss_db: 0.0930 2022/11/02 21:55:29 - mmengine - INFO - Epoch(train) [872][45/63] lr: 6.7369e-04 eta: 3:27:56 time: 0.4919 data_time: 0.0098 memory: 14901 loss: 0.9669 loss_prob: 0.5030 loss_thr: 0.3752 loss_db: 0.0887 2022/11/02 21:55:32 - mmengine - INFO - Epoch(train) [872][50/63] lr: 6.7369e-04 eta: 3:27:49 time: 0.5100 data_time: 0.0190 memory: 14901 loss: 1.0373 loss_prob: 0.5604 loss_thr: 0.3839 loss_db: 0.0931 2022/11/02 21:55:35 - mmengine - INFO - Epoch(train) [872][55/63] lr: 6.7369e-04 eta: 3:27:49 time: 0.5799 data_time: 0.0238 memory: 14901 loss: 1.1038 loss_prob: 0.6091 loss_thr: 0.3950 loss_db: 0.0998 2022/11/02 21:55:38 - mmengine - INFO - Epoch(train) [872][60/63] lr: 6.7369e-04 eta: 3:27:43 time: 0.5904 data_time: 0.0156 memory: 14901 loss: 1.0000 loss_prob: 0.5246 loss_thr: 0.3840 loss_db: 0.0915 2022/11/02 21:55:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:55:45 - mmengine - INFO - Epoch(train) [873][5/63] lr: 6.7184e-04 eta: 3:27:43 time: 0.7696 data_time: 0.2122 memory: 14901 loss: 0.8996 loss_prob: 0.4601 loss_thr: 0.3582 loss_db: 0.0812 2022/11/02 21:55:47 - mmengine - INFO - Epoch(train) [873][10/63] lr: 6.7184e-04 eta: 3:27:35 time: 0.7948 data_time: 0.2199 memory: 14901 loss: 1.0717 loss_prob: 0.5736 loss_thr: 0.4009 loss_db: 0.0973 2022/11/02 21:55:50 - mmengine - INFO - Epoch(train) [873][15/63] lr: 6.7184e-04 eta: 3:27:35 time: 0.5024 data_time: 0.0201 memory: 14901 loss: 1.0791 loss_prob: 0.5685 loss_thr: 0.4137 loss_db: 0.0968 2022/11/02 21:55:52 - mmengine - INFO - Epoch(train) [873][20/63] lr: 6.7184e-04 eta: 3:27:29 time: 0.5044 data_time: 0.0084 memory: 14901 loss: 0.9662 loss_prob: 0.4933 loss_thr: 0.3850 loss_db: 0.0879 2022/11/02 21:55:55 - mmengine - INFO - Epoch(train) [873][25/63] lr: 6.7184e-04 eta: 3:27:29 time: 0.5721 data_time: 0.0357 memory: 14901 loss: 0.9336 loss_prob: 0.4810 loss_thr: 0.3682 loss_db: 0.0844 2022/11/02 21:55:58 - mmengine - INFO - Epoch(train) [873][30/63] lr: 6.7184e-04 eta: 3:27:23 time: 0.6004 data_time: 0.0508 memory: 14901 loss: 0.9488 loss_prob: 0.4918 loss_thr: 0.3727 loss_db: 0.0843 2022/11/02 21:56:01 - mmengine - INFO - Epoch(train) [873][35/63] lr: 6.7184e-04 eta: 3:27:23 time: 0.5276 data_time: 0.0236 memory: 14901 loss: 1.0851 loss_prob: 0.6040 loss_thr: 0.3855 loss_db: 0.0956 2022/11/02 21:56:03 - mmengine - INFO - Epoch(train) [873][40/63] lr: 6.7184e-04 eta: 3:27:16 time: 0.4909 data_time: 0.0121 memory: 14901 loss: 1.1385 loss_prob: 0.6437 loss_thr: 0.3934 loss_db: 0.1013 2022/11/02 21:56:06 - mmengine - INFO - Epoch(train) [873][45/63] lr: 6.7184e-04 eta: 3:27:16 time: 0.4936 data_time: 0.0123 memory: 14901 loss: 1.0217 loss_prob: 0.5480 loss_thr: 0.3803 loss_db: 0.0933 2022/11/02 21:56:08 - mmengine - INFO - Epoch(train) [873][50/63] lr: 6.7184e-04 eta: 3:27:10 time: 0.5146 data_time: 0.0186 memory: 14901 loss: 0.9937 loss_prob: 0.5268 loss_thr: 0.3760 loss_db: 0.0909 2022/11/02 21:56:11 - mmengine - INFO - Epoch(train) [873][55/63] lr: 6.7184e-04 eta: 3:27:10 time: 0.5588 data_time: 0.0234 memory: 14901 loss: 1.0320 loss_prob: 0.5463 loss_thr: 0.3919 loss_db: 0.0938 2022/11/02 21:56:14 - mmengine - INFO - Epoch(train) [873][60/63] lr: 6.7184e-04 eta: 3:27:04 time: 0.5706 data_time: 0.0210 memory: 14901 loss: 1.1064 loss_prob: 0.5898 loss_thr: 0.4152 loss_db: 0.1014 2022/11/02 21:56:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:56:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:56:20 - mmengine - INFO - Epoch(train) [874][5/63] lr: 6.6999e-04 eta: 3:27:04 time: 0.6973 data_time: 0.2309 memory: 14901 loss: 1.0021 loss_prob: 0.5246 loss_thr: 0.3856 loss_db: 0.0919 2022/11/02 21:56:22 - mmengine - INFO - Epoch(train) [874][10/63] lr: 6.6999e-04 eta: 3:26:56 time: 0.7278 data_time: 0.2341 memory: 14901 loss: 0.9350 loss_prob: 0.4876 loss_thr: 0.3616 loss_db: 0.0858 2022/11/02 21:56:25 - mmengine - INFO - Epoch(train) [874][15/63] lr: 6.6999e-04 eta: 3:26:56 time: 0.5025 data_time: 0.0190 memory: 14901 loss: 0.9731 loss_prob: 0.5122 loss_thr: 0.3726 loss_db: 0.0883 2022/11/02 21:56:28 - mmengine - INFO - Epoch(train) [874][20/63] lr: 6.6999e-04 eta: 3:26:49 time: 0.5142 data_time: 0.0188 memory: 14901 loss: 1.0994 loss_prob: 0.5873 loss_thr: 0.4122 loss_db: 0.1000 2022/11/02 21:56:30 - mmengine - INFO - Epoch(train) [874][25/63] lr: 6.6999e-04 eta: 3:26:49 time: 0.5130 data_time: 0.0347 memory: 14901 loss: 1.0827 loss_prob: 0.5779 loss_thr: 0.4050 loss_db: 0.0998 2022/11/02 21:56:33 - mmengine - INFO - Epoch(train) [874][30/63] lr: 6.6999e-04 eta: 3:26:43 time: 0.4995 data_time: 0.0313 memory: 14901 loss: 0.9625 loss_prob: 0.5032 loss_thr: 0.3714 loss_db: 0.0880 2022/11/02 21:56:35 - mmengine - INFO - Epoch(train) [874][35/63] lr: 6.6999e-04 eta: 3:26:43 time: 0.4951 data_time: 0.0130 memory: 14901 loss: 1.0189 loss_prob: 0.5421 loss_thr: 0.3824 loss_db: 0.0944 2022/11/02 21:56:38 - mmengine - INFO - Epoch(train) [874][40/63] lr: 6.6999e-04 eta: 3:26:37 time: 0.5033 data_time: 0.0159 memory: 14901 loss: 0.9890 loss_prob: 0.5223 loss_thr: 0.3765 loss_db: 0.0901 2022/11/02 21:56:40 - mmengine - INFO - Epoch(train) [874][45/63] lr: 6.6999e-04 eta: 3:26:37 time: 0.5069 data_time: 0.0152 memory: 14901 loss: 0.9220 loss_prob: 0.4759 loss_thr: 0.3640 loss_db: 0.0821 2022/11/02 21:56:43 - mmengine - INFO - Epoch(train) [874][50/63] lr: 6.6999e-04 eta: 3:26:30 time: 0.5581 data_time: 0.0313 memory: 14901 loss: 0.9935 loss_prob: 0.5206 loss_thr: 0.3815 loss_db: 0.0914 2022/11/02 21:56:46 - mmengine - INFO - Epoch(train) [874][55/63] lr: 6.6999e-04 eta: 3:26:30 time: 0.5749 data_time: 0.0306 memory: 14901 loss: 0.9633 loss_prob: 0.5037 loss_thr: 0.3709 loss_db: 0.0888 2022/11/02 21:56:49 - mmengine - INFO - Epoch(train) [874][60/63] lr: 6.6999e-04 eta: 3:26:24 time: 0.5386 data_time: 0.0101 memory: 14901 loss: 0.9864 loss_prob: 0.5307 loss_thr: 0.3665 loss_db: 0.0891 2022/11/02 21:56:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:56:55 - mmengine - INFO - Epoch(train) [875][5/63] lr: 6.6814e-04 eta: 3:26:24 time: 0.7871 data_time: 0.2423 memory: 14901 loss: 1.1215 loss_prob: 0.6195 loss_thr: 0.3990 loss_db: 0.1030 2022/11/02 21:56:58 - mmengine - INFO - Epoch(train) [875][10/63] lr: 6.6814e-04 eta: 3:26:16 time: 0.7717 data_time: 0.2417 memory: 14901 loss: 1.0500 loss_prob: 0.5539 loss_thr: 0.3987 loss_db: 0.0974 2022/11/02 21:57:00 - mmengine - INFO - Epoch(train) [875][15/63] lr: 6.6814e-04 eta: 3:26:16 time: 0.5088 data_time: 0.0133 memory: 14901 loss: 0.9644 loss_prob: 0.4947 loss_thr: 0.3824 loss_db: 0.0874 2022/11/02 21:57:03 - mmengine - INFO - Epoch(train) [875][20/63] lr: 6.6814e-04 eta: 3:26:10 time: 0.5110 data_time: 0.0153 memory: 14901 loss: 0.9600 loss_prob: 0.4955 loss_thr: 0.3774 loss_db: 0.0871 2022/11/02 21:57:06 - mmengine - INFO - Epoch(train) [875][25/63] lr: 6.6814e-04 eta: 3:26:10 time: 0.5216 data_time: 0.0257 memory: 14901 loss: 0.9978 loss_prob: 0.5197 loss_thr: 0.3883 loss_db: 0.0897 2022/11/02 21:57:08 - mmengine - INFO - Epoch(train) [875][30/63] lr: 6.6814e-04 eta: 3:26:04 time: 0.5456 data_time: 0.0345 memory: 14901 loss: 1.0153 loss_prob: 0.5275 loss_thr: 0.3976 loss_db: 0.0902 2022/11/02 21:57:11 - mmengine - INFO - Epoch(train) [875][35/63] lr: 6.6814e-04 eta: 3:26:04 time: 0.5148 data_time: 0.0270 memory: 14901 loss: 1.0481 loss_prob: 0.5528 loss_thr: 0.3991 loss_db: 0.0962 2022/11/02 21:57:13 - mmengine - INFO - Epoch(train) [875][40/63] lr: 6.6814e-04 eta: 3:25:57 time: 0.4795 data_time: 0.0181 memory: 14901 loss: 1.1052 loss_prob: 0.5892 loss_thr: 0.4132 loss_db: 0.1028 2022/11/02 21:57:16 - mmengine - INFO - Epoch(train) [875][45/63] lr: 6.6814e-04 eta: 3:25:57 time: 0.4701 data_time: 0.0155 memory: 14901 loss: 1.0359 loss_prob: 0.5426 loss_thr: 0.3987 loss_db: 0.0946 2022/11/02 21:57:18 - mmengine - INFO - Epoch(train) [875][50/63] lr: 6.6814e-04 eta: 3:25:51 time: 0.5019 data_time: 0.0248 memory: 14901 loss: 1.0390 loss_prob: 0.5464 loss_thr: 0.3972 loss_db: 0.0954 2022/11/02 21:57:22 - mmengine - INFO - Epoch(train) [875][55/63] lr: 6.6814e-04 eta: 3:25:51 time: 0.6299 data_time: 0.0244 memory: 14901 loss: 1.0025 loss_prob: 0.5277 loss_thr: 0.3829 loss_db: 0.0919 2022/11/02 21:57:25 - mmengine - INFO - Epoch(train) [875][60/63] lr: 6.6814e-04 eta: 3:25:45 time: 0.6431 data_time: 0.0171 memory: 14901 loss: 0.9674 loss_prob: 0.4982 loss_thr: 0.3833 loss_db: 0.0859 2022/11/02 21:57:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:57:31 - mmengine - INFO - Epoch(train) [876][5/63] lr: 6.6629e-04 eta: 3:25:45 time: 0.7248 data_time: 0.1801 memory: 14901 loss: 0.9360 loss_prob: 0.4755 loss_thr: 0.3772 loss_db: 0.0834 2022/11/02 21:57:33 - mmengine - INFO - Epoch(train) [876][10/63] lr: 6.6629e-04 eta: 3:25:37 time: 0.7490 data_time: 0.1934 memory: 14901 loss: 0.9552 loss_prob: 0.4841 loss_thr: 0.3867 loss_db: 0.0843 2022/11/02 21:57:36 - mmengine - INFO - Epoch(train) [876][15/63] lr: 6.6629e-04 eta: 3:25:37 time: 0.4845 data_time: 0.0265 memory: 14901 loss: 1.0310 loss_prob: 0.5373 loss_thr: 0.3993 loss_db: 0.0945 2022/11/02 21:57:39 - mmengine - INFO - Epoch(train) [876][20/63] lr: 6.6629e-04 eta: 3:25:31 time: 0.5420 data_time: 0.0136 memory: 14901 loss: 1.0323 loss_prob: 0.5596 loss_thr: 0.3776 loss_db: 0.0951 2022/11/02 21:57:42 - mmengine - INFO - Epoch(train) [876][25/63] lr: 6.6629e-04 eta: 3:25:31 time: 0.6087 data_time: 0.0138 memory: 14901 loss: 0.9489 loss_prob: 0.5059 loss_thr: 0.3572 loss_db: 0.0858 2022/11/02 21:57:45 - mmengine - INFO - Epoch(train) [876][30/63] lr: 6.6629e-04 eta: 3:25:25 time: 0.5738 data_time: 0.0384 memory: 14901 loss: 0.9163 loss_prob: 0.4673 loss_thr: 0.3665 loss_db: 0.0825 2022/11/02 21:57:47 - mmengine - INFO - Epoch(train) [876][35/63] lr: 6.6629e-04 eta: 3:25:25 time: 0.5217 data_time: 0.0402 memory: 14901 loss: 0.9006 loss_prob: 0.4631 loss_thr: 0.3553 loss_db: 0.0823 2022/11/02 21:57:49 - mmengine - INFO - Epoch(train) [876][40/63] lr: 6.6629e-04 eta: 3:25:18 time: 0.4959 data_time: 0.0173 memory: 14901 loss: 0.8935 loss_prob: 0.4665 loss_thr: 0.3445 loss_db: 0.0825 2022/11/02 21:57:52 - mmengine - INFO - Epoch(train) [876][45/63] lr: 6.6629e-04 eta: 3:25:18 time: 0.4779 data_time: 0.0136 memory: 14901 loss: 0.8977 loss_prob: 0.4642 loss_thr: 0.3517 loss_db: 0.0817 2022/11/02 21:57:54 - mmengine - INFO - Epoch(train) [876][50/63] lr: 6.6629e-04 eta: 3:25:12 time: 0.4847 data_time: 0.0151 memory: 14901 loss: 1.0483 loss_prob: 0.5535 loss_thr: 0.3995 loss_db: 0.0953 2022/11/02 21:57:57 - mmengine - INFO - Epoch(train) [876][55/63] lr: 6.6629e-04 eta: 3:25:12 time: 0.5080 data_time: 0.0273 memory: 14901 loss: 1.2443 loss_prob: 0.6961 loss_thr: 0.4365 loss_db: 0.1118 2022/11/02 21:58:00 - mmengine - INFO - Epoch(train) [876][60/63] lr: 6.6629e-04 eta: 3:25:05 time: 0.5181 data_time: 0.0282 memory: 14901 loss: 1.1485 loss_prob: 0.6310 loss_thr: 0.4150 loss_db: 0.1025 2022/11/02 21:58:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:58:07 - mmengine - INFO - Epoch(train) [877][5/63] lr: 6.6444e-04 eta: 3:25:05 time: 0.8127 data_time: 0.2261 memory: 14901 loss: 1.0866 loss_prob: 0.5784 loss_thr: 0.4099 loss_db: 0.0983 2022/11/02 21:58:09 - mmengine - INFO - Epoch(train) [877][10/63] lr: 6.6444e-04 eta: 3:24:57 time: 0.7789 data_time: 0.2277 memory: 14901 loss: 1.1498 loss_prob: 0.6070 loss_thr: 0.4405 loss_db: 0.1023 2022/11/02 21:58:12 - mmengine - INFO - Epoch(train) [877][15/63] lr: 6.6444e-04 eta: 3:24:57 time: 0.5070 data_time: 0.0150 memory: 14901 loss: 1.0579 loss_prob: 0.5440 loss_thr: 0.4212 loss_db: 0.0928 2022/11/02 21:58:14 - mmengine - INFO - Epoch(train) [877][20/63] lr: 6.6444e-04 eta: 3:24:51 time: 0.4944 data_time: 0.0149 memory: 14901 loss: 1.0787 loss_prob: 0.5652 loss_thr: 0.4161 loss_db: 0.0974 2022/11/02 21:58:17 - mmengine - INFO - Epoch(train) [877][25/63] lr: 6.6444e-04 eta: 3:24:51 time: 0.5158 data_time: 0.0341 memory: 14901 loss: 0.9867 loss_prob: 0.5184 loss_thr: 0.3782 loss_db: 0.0902 2022/11/02 21:58:19 - mmengine - INFO - Epoch(train) [877][30/63] lr: 6.6444e-04 eta: 3:24:45 time: 0.5116 data_time: 0.0380 memory: 14901 loss: 0.9723 loss_prob: 0.5070 loss_thr: 0.3764 loss_db: 0.0889 2022/11/02 21:58:22 - mmengine - INFO - Epoch(train) [877][35/63] lr: 6.6444e-04 eta: 3:24:45 time: 0.5583 data_time: 0.0160 memory: 14901 loss: 1.0191 loss_prob: 0.5373 loss_thr: 0.3891 loss_db: 0.0927 2022/11/02 21:58:25 - mmengine - INFO - Epoch(train) [877][40/63] lr: 6.6444e-04 eta: 3:24:39 time: 0.5767 data_time: 0.0122 memory: 14901 loss: 0.9701 loss_prob: 0.5044 loss_thr: 0.3782 loss_db: 0.0876 2022/11/02 21:58:27 - mmengine - INFO - Epoch(train) [877][45/63] lr: 6.6444e-04 eta: 3:24:39 time: 0.4896 data_time: 0.0146 memory: 14901 loss: 0.9692 loss_prob: 0.5034 loss_thr: 0.3774 loss_db: 0.0884 2022/11/02 21:58:30 - mmengine - INFO - Epoch(train) [877][50/63] lr: 6.6444e-04 eta: 3:24:32 time: 0.4805 data_time: 0.0223 memory: 14901 loss: 0.9865 loss_prob: 0.5199 loss_thr: 0.3763 loss_db: 0.0903 2022/11/02 21:58:33 - mmengine - INFO - Epoch(train) [877][55/63] lr: 6.6444e-04 eta: 3:24:32 time: 0.5372 data_time: 0.0246 memory: 14901 loss: 1.0174 loss_prob: 0.5383 loss_thr: 0.3884 loss_db: 0.0908 2022/11/02 21:58:35 - mmengine - INFO - Epoch(train) [877][60/63] lr: 6.6444e-04 eta: 3:24:26 time: 0.5318 data_time: 0.0141 memory: 14901 loss: 1.0822 loss_prob: 0.5726 loss_thr: 0.4117 loss_db: 0.0980 2022/11/02 21:58:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:58:43 - mmengine - INFO - Epoch(train) [878][5/63] lr: 6.6259e-04 eta: 3:24:26 time: 0.9095 data_time: 0.2531 memory: 14901 loss: 1.0326 loss_prob: 0.5339 loss_thr: 0.4059 loss_db: 0.0927 2022/11/02 21:58:46 - mmengine - INFO - Epoch(train) [878][10/63] lr: 6.6259e-04 eta: 3:24:19 time: 0.9545 data_time: 0.2509 memory: 14901 loss: 0.9737 loss_prob: 0.5082 loss_thr: 0.3772 loss_db: 0.0883 2022/11/02 21:58:49 - mmengine - INFO - Epoch(train) [878][15/63] lr: 6.6259e-04 eta: 3:24:19 time: 0.5468 data_time: 0.0081 memory: 14901 loss: 1.0482 loss_prob: 0.5583 loss_thr: 0.3938 loss_db: 0.0961 2022/11/02 21:58:51 - mmengine - INFO - Epoch(train) [878][20/63] lr: 6.6259e-04 eta: 3:24:12 time: 0.5282 data_time: 0.0105 memory: 14901 loss: 1.1410 loss_prob: 0.6174 loss_thr: 0.4188 loss_db: 0.1049 2022/11/02 21:58:54 - mmengine - INFO - Epoch(train) [878][25/63] lr: 6.6259e-04 eta: 3:24:12 time: 0.5668 data_time: 0.0195 memory: 14901 loss: 1.0127 loss_prob: 0.5409 loss_thr: 0.3785 loss_db: 0.0933 2022/11/02 21:58:58 - mmengine - INFO - Epoch(train) [878][30/63] lr: 6.6259e-04 eta: 3:24:06 time: 0.6351 data_time: 0.0422 memory: 14901 loss: 0.9386 loss_prob: 0.4906 loss_thr: 0.3637 loss_db: 0.0843 2022/11/02 21:59:00 - mmengine - INFO - Epoch(train) [878][35/63] lr: 6.6259e-04 eta: 3:24:06 time: 0.5562 data_time: 0.0337 memory: 14901 loss: 0.9665 loss_prob: 0.5038 loss_thr: 0.3783 loss_db: 0.0844 2022/11/02 21:59:03 - mmengine - INFO - Epoch(train) [878][40/63] lr: 6.6259e-04 eta: 3:24:00 time: 0.5102 data_time: 0.0087 memory: 14901 loss: 0.9395 loss_prob: 0.4845 loss_thr: 0.3718 loss_db: 0.0832 2022/11/02 21:59:06 - mmengine - INFO - Epoch(train) [878][45/63] lr: 6.6259e-04 eta: 3:24:00 time: 0.5561 data_time: 0.0126 memory: 14901 loss: 0.9887 loss_prob: 0.5067 loss_thr: 0.3928 loss_db: 0.0892 2022/11/02 21:59:08 - mmengine - INFO - Epoch(train) [878][50/63] lr: 6.6259e-04 eta: 3:23:54 time: 0.5406 data_time: 0.0216 memory: 14901 loss: 0.9348 loss_prob: 0.4709 loss_thr: 0.3814 loss_db: 0.0825 2022/11/02 21:59:11 - mmengine - INFO - Epoch(train) [878][55/63] lr: 6.6259e-04 eta: 3:23:54 time: 0.5061 data_time: 0.0340 memory: 14901 loss: 0.8785 loss_prob: 0.4429 loss_thr: 0.3578 loss_db: 0.0778 2022/11/02 21:59:13 - mmengine - INFO - Epoch(train) [878][60/63] lr: 6.6259e-04 eta: 3:23:47 time: 0.5040 data_time: 0.0253 memory: 14901 loss: 0.9520 loss_prob: 0.4984 loss_thr: 0.3676 loss_db: 0.0860 2022/11/02 21:59:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:59:20 - mmengine - INFO - Epoch(train) [879][5/63] lr: 6.6074e-04 eta: 3:23:47 time: 0.8235 data_time: 0.2307 memory: 14901 loss: 1.0250 loss_prob: 0.5474 loss_thr: 0.3830 loss_db: 0.0946 2022/11/02 21:59:23 - mmengine - INFO - Epoch(train) [879][10/63] lr: 6.6074e-04 eta: 3:23:40 time: 0.8350 data_time: 0.2296 memory: 14901 loss: 1.0532 loss_prob: 0.5753 loss_thr: 0.3870 loss_db: 0.0909 2022/11/02 21:59:26 - mmengine - INFO - Epoch(train) [879][15/63] lr: 6.6074e-04 eta: 3:23:40 time: 0.5895 data_time: 0.0089 memory: 14901 loss: 0.9976 loss_prob: 0.5375 loss_thr: 0.3752 loss_db: 0.0849 2022/11/02 21:59:29 - mmengine - INFO - Epoch(train) [879][20/63] lr: 6.6074e-04 eta: 3:23:34 time: 0.6014 data_time: 0.0098 memory: 14901 loss: 0.9382 loss_prob: 0.4865 loss_thr: 0.3674 loss_db: 0.0843 2022/11/02 21:59:32 - mmengine - INFO - Epoch(train) [879][25/63] lr: 6.6074e-04 eta: 3:23:34 time: 0.5262 data_time: 0.0194 memory: 14901 loss: 1.0311 loss_prob: 0.5347 loss_thr: 0.4038 loss_db: 0.0926 2022/11/02 21:59:35 - mmengine - INFO - Epoch(train) [879][30/63] lr: 6.6074e-04 eta: 3:23:27 time: 0.5504 data_time: 0.0415 memory: 14901 loss: 1.0634 loss_prob: 0.5544 loss_thr: 0.4128 loss_db: 0.0963 2022/11/02 21:59:37 - mmengine - INFO - Epoch(train) [879][35/63] lr: 6.6074e-04 eta: 3:23:27 time: 0.5379 data_time: 0.0344 memory: 14901 loss: 0.9757 loss_prob: 0.5056 loss_thr: 0.3821 loss_db: 0.0880 2022/11/02 21:59:39 - mmengine - INFO - Epoch(train) [879][40/63] lr: 6.6074e-04 eta: 3:23:21 time: 0.4868 data_time: 0.0117 memory: 14901 loss: 0.9761 loss_prob: 0.5102 loss_thr: 0.3787 loss_db: 0.0872 2022/11/02 21:59:42 - mmengine - INFO - Epoch(train) [879][45/63] lr: 6.6074e-04 eta: 3:23:21 time: 0.4976 data_time: 0.0112 memory: 14901 loss: 0.9905 loss_prob: 0.5174 loss_thr: 0.3830 loss_db: 0.0901 2022/11/02 21:59:44 - mmengine - INFO - Epoch(train) [879][50/63] lr: 6.6074e-04 eta: 3:23:15 time: 0.4957 data_time: 0.0179 memory: 14901 loss: 1.0416 loss_prob: 0.5489 loss_thr: 0.3993 loss_db: 0.0933 2022/11/02 21:59:47 - mmengine - INFO - Epoch(train) [879][55/63] lr: 6.6074e-04 eta: 3:23:15 time: 0.5111 data_time: 0.0307 memory: 14901 loss: 1.0380 loss_prob: 0.5488 loss_thr: 0.3986 loss_db: 0.0907 2022/11/02 21:59:50 - mmengine - INFO - Epoch(train) [879][60/63] lr: 6.6074e-04 eta: 3:23:08 time: 0.5185 data_time: 0.0245 memory: 14901 loss: 0.9516 loss_prob: 0.4863 loss_thr: 0.3821 loss_db: 0.0832 2022/11/02 21:59:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 21:59:56 - mmengine - INFO - Epoch(train) [880][5/63] lr: 6.5889e-04 eta: 3:23:08 time: 0.7205 data_time: 0.2286 memory: 14901 loss: 1.0870 loss_prob: 0.5870 loss_thr: 0.3974 loss_db: 0.1027 2022/11/02 21:59:59 - mmengine - INFO - Epoch(train) [880][10/63] lr: 6.5889e-04 eta: 3:23:00 time: 0.7927 data_time: 0.2289 memory: 14901 loss: 1.1285 loss_prob: 0.6103 loss_thr: 0.4170 loss_db: 0.1012 2022/11/02 22:00:01 - mmengine - INFO - Epoch(train) [880][15/63] lr: 6.5889e-04 eta: 3:23:00 time: 0.5714 data_time: 0.0120 memory: 14901 loss: 1.1482 loss_prob: 0.6299 loss_thr: 0.4127 loss_db: 0.1056 2022/11/02 22:00:04 - mmengine - INFO - Epoch(train) [880][20/63] lr: 6.5889e-04 eta: 3:22:54 time: 0.5578 data_time: 0.0114 memory: 14901 loss: 0.9854 loss_prob: 0.5297 loss_thr: 0.3642 loss_db: 0.0914 2022/11/02 22:00:07 - mmengine - INFO - Epoch(train) [880][25/63] lr: 6.5889e-04 eta: 3:22:54 time: 0.5601 data_time: 0.0222 memory: 14901 loss: 0.9896 loss_prob: 0.5190 loss_thr: 0.3809 loss_db: 0.0897 2022/11/02 22:00:10 - mmengine - INFO - Epoch(train) [880][30/63] lr: 6.5889e-04 eta: 3:22:48 time: 0.5528 data_time: 0.0472 memory: 14901 loss: 1.1013 loss_prob: 0.6033 loss_thr: 0.4033 loss_db: 0.0947 2022/11/02 22:00:12 - mmengine - INFO - Epoch(train) [880][35/63] lr: 6.5889e-04 eta: 3:22:48 time: 0.5120 data_time: 0.0359 memory: 14901 loss: 1.0575 loss_prob: 0.5793 loss_thr: 0.3864 loss_db: 0.0918 2022/11/02 22:00:15 - mmengine - INFO - Epoch(train) [880][40/63] lr: 6.5889e-04 eta: 3:22:42 time: 0.5060 data_time: 0.0095 memory: 14901 loss: 1.0951 loss_prob: 0.5973 loss_thr: 0.3959 loss_db: 0.1020 2022/11/02 22:00:18 - mmengine - INFO - Epoch(train) [880][45/63] lr: 6.5889e-04 eta: 3:22:42 time: 0.5387 data_time: 0.0085 memory: 14901 loss: 1.1330 loss_prob: 0.6153 loss_thr: 0.4132 loss_db: 0.1045 2022/11/02 22:00:20 - mmengine - INFO - Epoch(train) [880][50/63] lr: 6.5889e-04 eta: 3:22:35 time: 0.5594 data_time: 0.0281 memory: 14901 loss: 1.1132 loss_prob: 0.5896 loss_thr: 0.4226 loss_db: 0.1010 2022/11/02 22:00:23 - mmengine - INFO - Epoch(train) [880][55/63] lr: 6.5889e-04 eta: 3:22:35 time: 0.5500 data_time: 0.0315 memory: 14901 loss: 1.1315 loss_prob: 0.5969 loss_thr: 0.4319 loss_db: 0.1027 2022/11/02 22:00:26 - mmengine - INFO - Epoch(train) [880][60/63] lr: 6.5889e-04 eta: 3:22:29 time: 0.5490 data_time: 0.0138 memory: 14901 loss: 1.0738 loss_prob: 0.5624 loss_thr: 0.4148 loss_db: 0.0967 2022/11/02 22:00:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:00:27 - mmengine - INFO - Saving checkpoint at 880 epochs 2022/11/02 22:00:31 - mmengine - INFO - Epoch(val) [880][5/500] eta: 3:22:29 time: 0.0433 data_time: 0.0058 memory: 14901 2022/11/02 22:00:31 - mmengine - INFO - Epoch(val) [880][10/500] eta: 0:00:22 time: 0.0457 data_time: 0.0057 memory: 1008 2022/11/02 22:00:31 - mmengine - INFO - Epoch(val) [880][15/500] eta: 0:00:22 time: 0.0385 data_time: 0.0026 memory: 1008 2022/11/02 22:00:32 - mmengine - INFO - Epoch(val) [880][20/500] eta: 0:00:17 time: 0.0373 data_time: 0.0027 memory: 1008 2022/11/02 22:00:32 - mmengine - INFO - Epoch(val) [880][25/500] eta: 0:00:17 time: 0.0366 data_time: 0.0027 memory: 1008 2022/11/02 22:00:32 - mmengine - INFO - Epoch(val) [880][30/500] eta: 0:00:18 time: 0.0401 data_time: 0.0027 memory: 1008 2022/11/02 22:00:32 - mmengine - INFO - Epoch(val) [880][35/500] eta: 0:00:18 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 22:00:32 - mmengine - INFO - Epoch(val) [880][40/500] eta: 0:00:19 time: 0.0422 data_time: 0.0027 memory: 1008 2022/11/02 22:00:33 - mmengine - INFO - Epoch(val) [880][45/500] eta: 0:00:19 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/02 22:00:33 - mmengine - INFO - Epoch(val) [880][50/500] eta: 0:00:17 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 22:00:33 - mmengine - INFO - Epoch(val) [880][55/500] eta: 0:00:17 time: 0.0439 data_time: 0.0026 memory: 1008 2022/11/02 22:00:33 - mmengine - INFO - Epoch(val) [880][60/500] eta: 0:00:18 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 22:00:33 - mmengine - INFO - Epoch(val) [880][65/500] eta: 0:00:18 time: 0.0418 data_time: 0.0033 memory: 1008 2022/11/02 22:00:34 - mmengine - INFO - Epoch(val) [880][70/500] eta: 0:00:19 time: 0.0451 data_time: 0.0032 memory: 1008 2022/11/02 22:00:34 - mmengine - INFO - Epoch(val) [880][75/500] eta: 0:00:19 time: 0.0414 data_time: 0.0031 memory: 1008 2022/11/02 22:00:34 - mmengine - INFO - Epoch(val) [880][80/500] eta: 0:00:16 time: 0.0382 data_time: 0.0033 memory: 1008 2022/11/02 22:00:34 - mmengine - INFO - Epoch(val) [880][85/500] eta: 0:00:16 time: 0.0377 data_time: 0.0032 memory: 1008 2022/11/02 22:00:34 - mmengine - INFO - Epoch(val) [880][90/500] eta: 0:00:17 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/02 22:00:35 - mmengine - INFO - Epoch(val) [880][95/500] eta: 0:00:17 time: 0.0440 data_time: 0.0031 memory: 1008 2022/11/02 22:00:35 - mmengine - INFO - Epoch(val) [880][100/500] eta: 0:00:15 time: 0.0387 data_time: 0.0030 memory: 1008 2022/11/02 22:00:35 - mmengine - INFO - Epoch(val) [880][105/500] eta: 0:00:15 time: 0.0373 data_time: 0.0026 memory: 1008 2022/11/02 22:00:35 - mmengine - INFO - Epoch(val) [880][110/500] eta: 0:00:15 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/02 22:00:35 - mmengine - INFO - Epoch(val) [880][115/500] eta: 0:00:15 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 22:00:36 - mmengine - INFO - Epoch(val) [880][120/500] eta: 0:00:14 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 22:00:36 - mmengine - INFO - Epoch(val) [880][125/500] eta: 0:00:14 time: 0.0388 data_time: 0.0029 memory: 1008 2022/11/02 22:00:36 - mmengine - INFO - Epoch(val) [880][130/500] eta: 0:00:13 time: 0.0370 data_time: 0.0028 memory: 1008 2022/11/02 22:00:36 - mmengine - INFO - Epoch(val) [880][135/500] eta: 0:00:13 time: 0.0363 data_time: 0.0026 memory: 1008 2022/11/02 22:00:36 - mmengine - INFO - Epoch(val) [880][140/500] eta: 0:00:13 time: 0.0376 data_time: 0.0028 memory: 1008 2022/11/02 22:00:37 - mmengine - INFO - Epoch(val) [880][145/500] eta: 0:00:13 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/02 22:00:37 - mmengine - INFO - Epoch(val) [880][150/500] eta: 0:00:15 time: 0.0434 data_time: 0.0029 memory: 1008 2022/11/02 22:00:37 - mmengine - INFO - Epoch(val) [880][155/500] eta: 0:00:15 time: 0.0447 data_time: 0.0029 memory: 1008 2022/11/02 22:00:37 - mmengine - INFO - Epoch(val) [880][160/500] eta: 0:00:14 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/02 22:00:37 - mmengine - INFO - Epoch(val) [880][165/500] eta: 0:00:14 time: 0.0407 data_time: 0.0029 memory: 1008 2022/11/02 22:00:38 - mmengine - INFO - Epoch(val) [880][170/500] eta: 0:00:13 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/02 22:00:38 - mmengine - INFO - Epoch(val) [880][175/500] eta: 0:00:13 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/02 22:00:38 - mmengine - INFO - Epoch(val) [880][180/500] eta: 0:00:12 time: 0.0390 data_time: 0.0026 memory: 1008 2022/11/02 22:00:38 - mmengine - INFO - Epoch(val) [880][185/500] eta: 0:00:12 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/02 22:00:38 - mmengine - INFO - Epoch(val) [880][190/500] eta: 0:00:13 time: 0.0438 data_time: 0.0027 memory: 1008 2022/11/02 22:00:39 - mmengine - INFO - Epoch(val) [880][195/500] eta: 0:00:13 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 22:00:39 - mmengine - INFO - Epoch(val) [880][200/500] eta: 0:00:15 time: 0.0512 data_time: 0.0029 memory: 1008 2022/11/02 22:00:39 - mmengine - INFO - Epoch(val) [880][205/500] eta: 0:00:15 time: 0.0492 data_time: 0.0028 memory: 1008 2022/11/02 22:00:39 - mmengine - INFO - Epoch(val) [880][210/500] eta: 0:00:10 time: 0.0363 data_time: 0.0025 memory: 1008 2022/11/02 22:00:40 - mmengine - INFO - Epoch(val) [880][215/500] eta: 0:00:10 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/02 22:00:40 - mmengine - INFO - Epoch(val) [880][220/500] eta: 0:00:11 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/02 22:00:40 - mmengine - INFO - Epoch(val) [880][225/500] eta: 0:00:11 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/02 22:00:40 - mmengine - INFO - Epoch(val) [880][230/500] eta: 0:00:10 time: 0.0375 data_time: 0.0028 memory: 1008 2022/11/02 22:00:40 - mmengine - INFO - Epoch(val) [880][235/500] eta: 0:00:10 time: 0.0382 data_time: 0.0030 memory: 1008 2022/11/02 22:00:41 - mmengine - INFO - Epoch(val) [880][240/500] eta: 0:00:11 time: 0.0450 data_time: 0.0033 memory: 1008 2022/11/02 22:00:41 - mmengine - INFO - Epoch(val) [880][245/500] eta: 0:00:11 time: 0.0456 data_time: 0.0033 memory: 1008 2022/11/02 22:00:41 - mmengine - INFO - Epoch(val) [880][250/500] eta: 0:00:11 time: 0.0477 data_time: 0.0035 memory: 1008 2022/11/02 22:00:41 - mmengine - INFO - Epoch(val) 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eta: 0:00:09 time: 0.0516 data_time: 0.0038 memory: 1008 2022/11/02 22:00:43 - mmengine - INFO - Epoch(val) [880][300/500] eta: 0:00:09 time: 0.0472 data_time: 0.0036 memory: 1008 2022/11/02 22:00:44 - mmengine - INFO - Epoch(val) [880][305/500] eta: 0:00:09 time: 0.0439 data_time: 0.0034 memory: 1008 2022/11/02 22:00:44 - mmengine - INFO - Epoch(val) [880][310/500] eta: 0:00:07 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/02 22:00:44 - mmengine - INFO - Epoch(val) [880][315/500] eta: 0:00:07 time: 0.0457 data_time: 0.0030 memory: 1008 2022/11/02 22:00:44 - mmengine - INFO - Epoch(val) [880][320/500] eta: 0:00:08 time: 0.0447 data_time: 0.0036 memory: 1008 2022/11/02 22:00:45 - mmengine - INFO - Epoch(val) [880][325/500] eta: 0:00:08 time: 0.0528 data_time: 0.0033 memory: 1008 2022/11/02 22:00:45 - mmengine - INFO - Epoch(val) [880][330/500] eta: 0:00:09 time: 0.0536 data_time: 0.0030 memory: 1008 2022/11/02 22:00:45 - mmengine - INFO - Epoch(val) [880][335/500] eta: 0:00:09 time: 0.0380 data_time: 0.0031 memory: 1008 2022/11/02 22:00:45 - mmengine - INFO - Epoch(val) [880][340/500] eta: 0:00:07 time: 0.0487 data_time: 0.0031 memory: 1008 2022/11/02 22:00:45 - mmengine - INFO - Epoch(val) [880][345/500] eta: 0:00:07 time: 0.0501 data_time: 0.0029 memory: 1008 2022/11/02 22:00:46 - mmengine - INFO - Epoch(val) [880][350/500] eta: 0:00:06 time: 0.0426 data_time: 0.0027 memory: 1008 2022/11/02 22:00:46 - mmengine - INFO - Epoch(val) [880][355/500] eta: 0:00:06 time: 0.0426 data_time: 0.0028 memory: 1008 2022/11/02 22:00:46 - mmengine - INFO - Epoch(val) [880][360/500] eta: 0:00:05 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 22:00:46 - mmengine - INFO - Epoch(val) [880][365/500] eta: 0:00:05 time: 0.0407 data_time: 0.0027 memory: 1008 2022/11/02 22:00:46 - mmengine - INFO - Epoch(val) [880][370/500] eta: 0:00:05 time: 0.0391 data_time: 0.0029 memory: 1008 2022/11/02 22:00:47 - mmengine - INFO - Epoch(val) [880][375/500] eta: 0:00:05 time: 0.0367 data_time: 0.0029 memory: 1008 2022/11/02 22:00:47 - mmengine - INFO - Epoch(val) [880][380/500] eta: 0:00:05 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 22:00:47 - mmengine - INFO - Epoch(val) [880][385/500] eta: 0:00:05 time: 0.0427 data_time: 0.0028 memory: 1008 2022/11/02 22:00:47 - mmengine - INFO - Epoch(val) [880][390/500] eta: 0:00:04 time: 0.0371 data_time: 0.0028 memory: 1008 2022/11/02 22:00:47 - mmengine - INFO - Epoch(val) [880][395/500] eta: 0:00:04 time: 0.0399 data_time: 0.0028 memory: 1008 2022/11/02 22:00:48 - mmengine - INFO - Epoch(val) [880][400/500] eta: 0:00:03 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/02 22:00:48 - mmengine - INFO - Epoch(val) [880][405/500] eta: 0:00:03 time: 0.0370 data_time: 0.0027 memory: 1008 2022/11/02 22:00:48 - mmengine - INFO - Epoch(val) [880][410/500] eta: 0:00:03 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/02 22:00:48 - mmengine - INFO - Epoch(val) [880][415/500] eta: 0:00:03 time: 0.0384 data_time: 0.0028 memory: 1008 2022/11/02 22:00:48 - mmengine - INFO - Epoch(val) [880][420/500] eta: 0:00:02 time: 0.0361 data_time: 0.0028 memory: 1008 2022/11/02 22:00:49 - mmengine - INFO - Epoch(val) [880][425/500] eta: 0:00:02 time: 0.0391 data_time: 0.0031 memory: 1008 2022/11/02 22:00:49 - mmengine - INFO - Epoch(val) [880][430/500] eta: 0:00:02 time: 0.0407 data_time: 0.0032 memory: 1008 2022/11/02 22:00:49 - mmengine - INFO - Epoch(val) [880][435/500] eta: 0:00:02 time: 0.0372 data_time: 0.0027 memory: 1008 2022/11/02 22:00:49 - mmengine - INFO - Epoch(val) [880][440/500] eta: 0:00:02 time: 0.0393 data_time: 0.0027 memory: 1008 2022/11/02 22:00:49 - mmengine - INFO - Epoch(val) [880][445/500] eta: 0:00:02 time: 0.0412 data_time: 0.0027 memory: 1008 2022/11/02 22:00:50 - mmengine - INFO - Epoch(val) [880][450/500] eta: 0:00:02 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/02 22:00:50 - mmengine - INFO - Epoch(val) [880][455/500] eta: 0:00:02 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/02 22:00:50 - mmengine - INFO - Epoch(val) [880][460/500] eta: 0:00:01 time: 0.0371 data_time: 0.0030 memory: 1008 2022/11/02 22:00:50 - mmengine - INFO - Epoch(val) [880][465/500] eta: 0:00:01 time: 0.0390 data_time: 0.0028 memory: 1008 2022/11/02 22:00:50 - mmengine - INFO - Epoch(val) [880][470/500] eta: 0:00:01 time: 0.0406 data_time: 0.0029 memory: 1008 2022/11/02 22:00:51 - mmengine - INFO - Epoch(val) [880][475/500] eta: 0:00:01 time: 0.0412 data_time: 0.0031 memory: 1008 2022/11/02 22:00:51 - mmengine - INFO - Epoch(val) [880][480/500] eta: 0:00:00 time: 0.0423 data_time: 0.0030 memory: 1008 2022/11/02 22:00:51 - mmengine - INFO - Epoch(val) [880][485/500] eta: 0:00:00 time: 0.0385 data_time: 0.0026 memory: 1008 2022/11/02 22:00:51 - mmengine - INFO - Epoch(val) [880][490/500] eta: 0:00:00 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/02 22:00:51 - mmengine - INFO - Epoch(val) [880][495/500] eta: 0:00:00 time: 0.0422 data_time: 0.0027 memory: 1008 2022/11/02 22:00:52 - mmengine - INFO - Epoch(val) [880][500/500] eta: 0:00:00 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 22:00:52 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8300, precision: 0.7565, hmean: 0.7916 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8300, precision: 0.8026, hmean: 0.8161 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8286, precision: 0.8274, hmean: 0.8280 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8238, precision: 0.8483, hmean: 0.8359 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8108, precision: 0.8762, hmean: 0.8422 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6639, precision: 0.9206, hmean: 0.7715 2022/11/02 22:00:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1040, precision: 0.9558, hmean: 0.1876 2022/11/02 22:00:52 - mmengine - INFO - Epoch(val) [880][500/500] icdar/precision: 0.8762 icdar/recall: 0.8108 icdar/hmean: 0.8422 2022/11/02 22:00:57 - mmengine - INFO - Epoch(train) [881][5/63] lr: 6.5703e-04 eta: 0:00:00 time: 0.7720 data_time: 0.2336 memory: 14901 loss: 1.0090 loss_prob: 0.5329 loss_thr: 0.3845 loss_db: 0.0916 2022/11/02 22:01:00 - mmengine - INFO - Epoch(train) [881][10/63] lr: 6.5703e-04 eta: 3:22:21 time: 0.7821 data_time: 0.2343 memory: 14901 loss: 0.9352 loss_prob: 0.4846 loss_thr: 0.3656 loss_db: 0.0849 2022/11/02 22:01:02 - mmengine - INFO - Epoch(train) [881][15/63] lr: 6.5703e-04 eta: 3:22:21 time: 0.5065 data_time: 0.0077 memory: 14901 loss: 0.9466 loss_prob: 0.4885 loss_thr: 0.3727 loss_db: 0.0853 2022/11/02 22:01:05 - mmengine - INFO - Epoch(train) [881][20/63] lr: 6.5703e-04 eta: 3:22:15 time: 0.5011 data_time: 0.0101 memory: 14901 loss: 1.0836 loss_prob: 0.5699 loss_thr: 0.4162 loss_db: 0.0976 2022/11/02 22:01:07 - mmengine - INFO - Epoch(train) [881][25/63] lr: 6.5703e-04 eta: 3:22:15 time: 0.5140 data_time: 0.0214 memory: 14901 loss: 1.1469 loss_prob: 0.6127 loss_thr: 0.4302 loss_db: 0.1040 2022/11/02 22:01:10 - mmengine - INFO - Epoch(train) [881][30/63] lr: 6.5703e-04 eta: 3:22:09 time: 0.5354 data_time: 0.0434 memory: 14901 loss: 1.0202 loss_prob: 0.5335 loss_thr: 0.3945 loss_db: 0.0923 2022/11/02 22:01:12 - mmengine - INFO - Epoch(train) [881][35/63] lr: 6.5703e-04 eta: 3:22:09 time: 0.4995 data_time: 0.0336 memory: 14901 loss: 1.0603 loss_prob: 0.5553 loss_thr: 0.4078 loss_db: 0.0972 2022/11/02 22:01:15 - mmengine - INFO - Epoch(train) [881][40/63] lr: 6.5703e-04 eta: 3:22:02 time: 0.4902 data_time: 0.0119 memory: 14901 loss: 1.0605 loss_prob: 0.5547 loss_thr: 0.4090 loss_db: 0.0968 2022/11/02 22:01:17 - mmengine - INFO - Epoch(train) [881][45/63] lr: 6.5703e-04 eta: 3:22:02 time: 0.5237 data_time: 0.0099 memory: 14901 loss: 1.0629 loss_prob: 0.5548 loss_thr: 0.4121 loss_db: 0.0960 2022/11/02 22:01:20 - mmengine - INFO - Epoch(train) [881][50/63] lr: 6.5703e-04 eta: 3:21:56 time: 0.5403 data_time: 0.0197 memory: 14901 loss: 1.0831 loss_prob: 0.5720 loss_thr: 0.4126 loss_db: 0.0984 2022/11/02 22:01:23 - mmengine - INFO - Epoch(train) [881][55/63] lr: 6.5703e-04 eta: 3:21:56 time: 0.5536 data_time: 0.0354 memory: 14901 loss: 0.9504 loss_prob: 0.4934 loss_thr: 0.3711 loss_db: 0.0859 2022/11/02 22:01:26 - mmengine - INFO - Epoch(train) [881][60/63] lr: 6.5703e-04 eta: 3:21:50 time: 0.5497 data_time: 0.0249 memory: 14901 loss: 0.9545 loss_prob: 0.4924 loss_thr: 0.3769 loss_db: 0.0853 2022/11/02 22:01:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:01:33 - mmengine - INFO - Epoch(train) [882][5/63] lr: 6.5518e-04 eta: 3:21:50 time: 0.8043 data_time: 0.2585 memory: 14901 loss: 1.1401 loss_prob: 0.6111 loss_thr: 0.4281 loss_db: 0.1008 2022/11/02 22:01:35 - mmengine - INFO - Epoch(train) [882][10/63] lr: 6.5518e-04 eta: 3:21:42 time: 0.8162 data_time: 0.2598 memory: 14901 loss: 1.0022 loss_prob: 0.5206 loss_thr: 0.3904 loss_db: 0.0912 2022/11/02 22:01:38 - mmengine - INFO - Epoch(train) [882][15/63] lr: 6.5518e-04 eta: 3:21:42 time: 0.5198 data_time: 0.0154 memory: 14901 loss: 0.9817 loss_prob: 0.5196 loss_thr: 0.3727 loss_db: 0.0894 2022/11/02 22:01:41 - mmengine - INFO - Epoch(train) [882][20/63] lr: 6.5518e-04 eta: 3:21:36 time: 0.5340 data_time: 0.0145 memory: 14901 loss: 0.9730 loss_prob: 0.5141 loss_thr: 0.3713 loss_db: 0.0875 2022/11/02 22:01:48 - mmengine - INFO - Epoch(train) [882][25/63] lr: 6.5518e-04 eta: 3:21:36 time: 1.0277 data_time: 0.0572 memory: 14901 loss: 0.9046 loss_prob: 0.4639 loss_thr: 0.3602 loss_db: 0.0805 2022/11/02 22:01:57 - mmengine - INFO - Epoch(train) [882][30/63] lr: 6.5518e-04 eta: 3:21:34 time: 1.6217 data_time: 0.0585 memory: 14901 loss: 0.9001 loss_prob: 0.4618 loss_thr: 0.3565 loss_db: 0.0819 2022/11/02 22:02:02 - mmengine - INFO - Epoch(train) [882][35/63] lr: 6.5518e-04 eta: 3:21:34 time: 1.4331 data_time: 0.0142 memory: 14901 loss: 0.9710 loss_prob: 0.5153 loss_thr: 0.3660 loss_db: 0.0897 2022/11/02 22:02:09 - mmengine - INFO - Epoch(train) [882][40/63] lr: 6.5518e-04 eta: 3:21:30 time: 1.1960 data_time: 0.0174 memory: 14901 loss: 1.0376 loss_prob: 0.5479 loss_thr: 0.3957 loss_db: 0.0939 2022/11/02 22:02:14 - mmengine - INFO - Epoch(train) [882][45/63] lr: 6.5518e-04 eta: 3:21:30 time: 1.2074 data_time: 0.0187 memory: 14901 loss: 1.0357 loss_prob: 0.5418 loss_thr: 0.4003 loss_db: 0.0936 2022/11/02 22:02:24 - mmengine - INFO - Epoch(train) [882][50/63] lr: 6.5518e-04 eta: 3:21:27 time: 1.4884 data_time: 0.0389 memory: 14901 loss: 0.9832 loss_prob: 0.5099 loss_thr: 0.3838 loss_db: 0.0895 2022/11/02 22:02:31 - mmengine - INFO - Epoch(train) [882][55/63] lr: 6.5518e-04 eta: 3:21:27 time: 1.6097 data_time: 0.0380 memory: 14901 loss: 0.9658 loss_prob: 0.5013 loss_thr: 0.3777 loss_db: 0.0868 2022/11/02 22:02:38 - mmengine - INFO - Epoch(train) [882][60/63] lr: 6.5518e-04 eta: 3:21:24 time: 1.4127 data_time: 0.0140 memory: 14901 loss: 0.9910 loss_prob: 0.5239 loss_thr: 0.3773 loss_db: 0.0899 2022/11/02 22:02:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:02:53 - mmengine - INFO - Epoch(train) [883][5/63] lr: 6.5333e-04 eta: 3:21:24 time: 1.8476 data_time: 0.2539 memory: 14901 loss: 0.9423 loss_prob: 0.4855 loss_thr: 0.3707 loss_db: 0.0861 2022/11/02 22:03:01 - mmengine - INFO - Epoch(train) [883][10/63] lr: 6.5333e-04 eta: 3:21:20 time: 2.0420 data_time: 0.2520 memory: 14901 loss: 0.9035 loss_prob: 0.4568 loss_thr: 0.3660 loss_db: 0.0807 2022/11/02 22:03:08 - mmengine - INFO - Epoch(train) [883][15/63] lr: 6.5333e-04 eta: 3:21:20 time: 1.5391 data_time: 0.0128 memory: 14901 loss: 0.9502 loss_prob: 0.4907 loss_thr: 0.3747 loss_db: 0.0848 2022/11/02 22:03:16 - mmengine - INFO - Epoch(train) [883][20/63] lr: 6.5333e-04 eta: 3:21:18 time: 1.5248 data_time: 0.0129 memory: 14901 loss: 0.9725 loss_prob: 0.5047 loss_thr: 0.3812 loss_db: 0.0867 2022/11/02 22:03:22 - mmengine - INFO - Epoch(train) [883][25/63] lr: 6.5333e-04 eta: 3:21:18 time: 1.4092 data_time: 0.0121 memory: 14901 loss: 1.0639 loss_prob: 0.5629 loss_thr: 0.4066 loss_db: 0.0945 2022/11/02 22:03:30 - mmengine - INFO - Epoch(train) [883][30/63] lr: 6.5333e-04 eta: 3:21:15 time: 1.4066 data_time: 0.0601 memory: 14901 loss: 1.0479 loss_prob: 0.5561 loss_thr: 0.3967 loss_db: 0.0951 2022/11/02 22:03:38 - mmengine - INFO - Epoch(train) [883][35/63] lr: 6.5333e-04 eta: 3:21:15 time: 1.5794 data_time: 0.0596 memory: 14901 loss: 0.9187 loss_prob: 0.4713 loss_thr: 0.3653 loss_db: 0.0821 2022/11/02 22:03:44 - mmengine - INFO - Epoch(train) [883][40/63] lr: 6.5333e-04 eta: 3:21:11 time: 1.3793 data_time: 0.0114 memory: 14901 loss: 0.9083 loss_prob: 0.4653 loss_thr: 0.3618 loss_db: 0.0812 2022/11/02 22:03:49 - mmengine - INFO - Epoch(train) [883][45/63] lr: 6.5333e-04 eta: 3:21:11 time: 1.0782 data_time: 0.0117 memory: 14901 loss: 0.9303 loss_prob: 0.4765 loss_thr: 0.3702 loss_db: 0.0835 2022/11/02 22:03:58 - mmengine - INFO - Epoch(train) [883][50/63] lr: 6.5333e-04 eta: 3:21:08 time: 1.3742 data_time: 0.0292 memory: 14901 loss: 0.9887 loss_prob: 0.5061 loss_thr: 0.3948 loss_db: 0.0878 2022/11/02 22:04:03 - mmengine - INFO - Epoch(train) [883][55/63] lr: 6.5333e-04 eta: 3:21:08 time: 1.4382 data_time: 0.0398 memory: 14901 loss: 1.0489 loss_prob: 0.5381 loss_thr: 0.4163 loss_db: 0.0945 2022/11/02 22:04:11 - mmengine - INFO - Epoch(train) [883][60/63] lr: 6.5333e-04 eta: 3:21:04 time: 1.2841 data_time: 0.0221 memory: 14901 loss: 1.0553 loss_prob: 0.5509 loss_thr: 0.4059 loss_db: 0.0986 2022/11/02 22:04:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:04:25 - mmengine - INFO - Epoch(train) [884][5/63] lr: 6.5147e-04 eta: 3:21:04 time: 1.6268 data_time: 0.2082 memory: 14901 loss: 0.9725 loss_prob: 0.5090 loss_thr: 0.3757 loss_db: 0.0879 2022/11/02 22:04:33 - mmengine - INFO - Epoch(train) [884][10/63] lr: 6.5147e-04 eta: 3:21:00 time: 1.8368 data_time: 0.2148 memory: 14901 loss: 1.0507 loss_prob: 0.5537 loss_thr: 0.4041 loss_db: 0.0929 2022/11/02 22:04:42 - mmengine - INFO - Epoch(train) [884][15/63] lr: 6.5147e-04 eta: 3:21:00 time: 1.6681 data_time: 0.0203 memory: 14901 loss: 1.0607 loss_prob: 0.5560 loss_thr: 0.4094 loss_db: 0.0952 2022/11/02 22:04:49 - mmengine - INFO - Epoch(train) [884][20/63] lr: 6.5147e-04 eta: 3:20:58 time: 1.6465 data_time: 0.0141 memory: 14901 loss: 0.8909 loss_prob: 0.4573 loss_thr: 0.3528 loss_db: 0.0808 2022/11/02 22:04:57 - mmengine - INFO - Epoch(train) [884][25/63] lr: 6.5147e-04 eta: 3:20:58 time: 1.5169 data_time: 0.0182 memory: 14901 loss: 0.8976 loss_prob: 0.4664 loss_thr: 0.3493 loss_db: 0.0819 2022/11/02 22:05:03 - mmengine - INFO - Epoch(train) [884][30/63] lr: 6.5147e-04 eta: 3:20:55 time: 1.3782 data_time: 0.0474 memory: 14901 loss: 0.9663 loss_prob: 0.5051 loss_thr: 0.3735 loss_db: 0.0878 2022/11/02 22:05:11 - mmengine - INFO - Epoch(train) [884][35/63] lr: 6.5147e-04 eta: 3:20:55 time: 1.4448 data_time: 0.0525 memory: 14901 loss: 0.9807 loss_prob: 0.5038 loss_thr: 0.3898 loss_db: 0.0872 2022/11/02 22:05:18 - mmengine - INFO - Epoch(train) [884][40/63] lr: 6.5147e-04 eta: 3:20:52 time: 1.4725 data_time: 0.0207 memory: 14901 loss: 1.0263 loss_prob: 0.5466 loss_thr: 0.3850 loss_db: 0.0946 2022/11/02 22:05:25 - mmengine - INFO - Epoch(train) [884][45/63] lr: 6.5147e-04 eta: 3:20:52 time: 1.3631 data_time: 0.0101 memory: 14901 loss: 0.9880 loss_prob: 0.5233 loss_thr: 0.3714 loss_db: 0.0934 2022/11/02 22:05:32 - mmengine - INFO - Epoch(train) [884][50/63] lr: 6.5147e-04 eta: 3:20:49 time: 1.4498 data_time: 0.0225 memory: 14901 loss: 0.9350 loss_prob: 0.4743 loss_thr: 0.3773 loss_db: 0.0834 2022/11/02 22:05:41 - mmengine - INFO - Epoch(train) [884][55/63] lr: 6.5147e-04 eta: 3:20:49 time: 1.5833 data_time: 0.0381 memory: 14901 loss: 0.9867 loss_prob: 0.5103 loss_thr: 0.3896 loss_db: 0.0868 2022/11/02 22:05:48 - mmengine - INFO - Epoch(train) [884][60/63] lr: 6.5147e-04 eta: 3:20:46 time: 1.5912 data_time: 0.0280 memory: 14901 loss: 1.0121 loss_prob: 0.5305 loss_thr: 0.3914 loss_db: 0.0902 2022/11/02 22:05:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:06:03 - mmengine - INFO - Epoch(train) [885][5/63] lr: 6.4962e-04 eta: 3:20:46 time: 1.6620 data_time: 0.3303 memory: 14901 loss: 0.9909 loss_prob: 0.5221 loss_thr: 0.3765 loss_db: 0.0924 2022/11/02 22:06:10 - mmengine - INFO - Epoch(train) [885][10/63] lr: 6.4962e-04 eta: 3:20:42 time: 1.9076 data_time: 0.3336 memory: 14901 loss: 1.0274 loss_prob: 0.5386 loss_thr: 0.3960 loss_db: 0.0928 2022/11/02 22:06:17 - mmengine - INFO - Epoch(train) [885][15/63] lr: 6.4962e-04 eta: 3:20:42 time: 1.4008 data_time: 0.0140 memory: 14901 loss: 0.9870 loss_prob: 0.5140 loss_thr: 0.3840 loss_db: 0.0889 2022/11/02 22:06:22 - mmengine - INFO - Epoch(train) [885][20/63] lr: 6.4962e-04 eta: 3:20:39 time: 1.2293 data_time: 0.0096 memory: 14901 loss: 1.0008 loss_prob: 0.5522 loss_thr: 0.3626 loss_db: 0.0859 2022/11/02 22:06:29 - mmengine - INFO - Epoch(train) [885][25/63] lr: 6.4962e-04 eta: 3:20:39 time: 1.2113 data_time: 0.0249 memory: 14901 loss: 1.0558 loss_prob: 0.5812 loss_thr: 0.3843 loss_db: 0.0903 2022/11/02 22:06:36 - mmengine - INFO - Epoch(train) [885][30/63] lr: 6.4962e-04 eta: 3:20:35 time: 1.3703 data_time: 0.0551 memory: 14901 loss: 1.1836 loss_prob: 0.6801 loss_thr: 0.4038 loss_db: 0.0997 2022/11/02 22:06:43 - mmengine - INFO - Epoch(train) [885][35/63] lr: 6.4962e-04 eta: 3:20:35 time: 1.3397 data_time: 0.0420 memory: 14901 loss: 1.1085 loss_prob: 0.6324 loss_thr: 0.3822 loss_db: 0.0940 2022/11/02 22:06:48 - mmengine - INFO - Epoch(train) [885][40/63] lr: 6.4962e-04 eta: 3:20:32 time: 1.2447 data_time: 0.0104 memory: 14901 loss: 0.8723 loss_prob: 0.4374 loss_thr: 0.3561 loss_db: 0.0787 2022/11/02 22:06:55 - mmengine - INFO - Epoch(train) [885][45/63] lr: 6.4962e-04 eta: 3:20:32 time: 1.2669 data_time: 0.0095 memory: 14901 loss: 0.9354 loss_prob: 0.4818 loss_thr: 0.3688 loss_db: 0.0849 2022/11/02 22:07:02 - mmengine - INFO - Epoch(train) [885][50/63] lr: 6.4962e-04 eta: 3:20:28 time: 1.4176 data_time: 0.0229 memory: 14901 loss: 0.9274 loss_prob: 0.4783 loss_thr: 0.3644 loss_db: 0.0848 2022/11/02 22:07:10 - mmengine - INFO - Epoch(train) [885][55/63] lr: 6.4962e-04 eta: 3:20:28 time: 1.4436 data_time: 0.0375 memory: 14901 loss: 0.9081 loss_prob: 0.4652 loss_thr: 0.3605 loss_db: 0.0825 2022/11/02 22:07:16 - mmengine - INFO - Epoch(train) [885][60/63] lr: 6.4962e-04 eta: 3:20:25 time: 1.3434 data_time: 0.0257 memory: 14901 loss: 1.0389 loss_prob: 0.5470 loss_thr: 0.3964 loss_db: 0.0955 2022/11/02 22:07:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:07:29 - mmengine - INFO - Epoch(train) [886][5/63] lr: 6.4776e-04 eta: 3:20:25 time: 1.5405 data_time: 0.3008 memory: 14901 loss: 0.9634 loss_prob: 0.4998 loss_thr: 0.3778 loss_db: 0.0859 2022/11/02 22:07:37 - mmengine - INFO - Epoch(train) [886][10/63] lr: 6.4776e-04 eta: 3:20:21 time: 1.7987 data_time: 0.2994 memory: 14901 loss: 0.9116 loss_prob: 0.4687 loss_thr: 0.3621 loss_db: 0.0808 2022/11/02 22:07:44 - mmengine - INFO - Epoch(train) [886][15/63] lr: 6.4776e-04 eta: 3:20:21 time: 1.4906 data_time: 0.0099 memory: 14901 loss: 0.8919 loss_prob: 0.4553 loss_thr: 0.3560 loss_db: 0.0806 2022/11/02 22:07:50 - mmengine - INFO - Epoch(train) [886][20/63] lr: 6.4776e-04 eta: 3:20:17 time: 1.3668 data_time: 0.0137 memory: 14901 loss: 0.9055 loss_prob: 0.4705 loss_thr: 0.3520 loss_db: 0.0830 2022/11/02 22:08:01 - mmengine - INFO - Epoch(train) [886][25/63] lr: 6.4776e-04 eta: 3:20:17 time: 1.6376 data_time: 0.0458 memory: 14901 loss: 0.9657 loss_prob: 0.5082 loss_thr: 0.3694 loss_db: 0.0881 2022/11/02 22:08:06 - mmengine - INFO - Epoch(train) [886][30/63] lr: 6.4776e-04 eta: 3:20:15 time: 1.5874 data_time: 0.0444 memory: 14901 loss: 0.9713 loss_prob: 0.5018 loss_thr: 0.3816 loss_db: 0.0879 2022/11/02 22:08:15 - mmengine - INFO - Epoch(train) [886][35/63] lr: 6.4776e-04 eta: 3:20:15 time: 1.4119 data_time: 0.0103 memory: 14901 loss: 0.9707 loss_prob: 0.5021 loss_thr: 0.3816 loss_db: 0.0871 2022/11/02 22:08:22 - mmengine - INFO - Epoch(train) [886][40/63] lr: 6.4776e-04 eta: 3:20:12 time: 1.6125 data_time: 0.0098 memory: 14901 loss: 1.0708 loss_prob: 0.5633 loss_thr: 0.4148 loss_db: 0.0927 2022/11/02 22:08:29 - mmengine - INFO - Epoch(train) [886][45/63] lr: 6.4776e-04 eta: 3:20:12 time: 1.4179 data_time: 0.0104 memory: 14901 loss: 1.0646 loss_prob: 0.5614 loss_thr: 0.4091 loss_db: 0.0941 2022/11/02 22:08:37 - mmengine - INFO - Epoch(train) [886][50/63] lr: 6.4776e-04 eta: 3:20:09 time: 1.4447 data_time: 0.0373 memory: 14901 loss: 0.9970 loss_prob: 0.5269 loss_thr: 0.3766 loss_db: 0.0936 2022/11/02 22:08:45 - mmengine - INFO - Epoch(train) [886][55/63] lr: 6.4776e-04 eta: 3:20:09 time: 1.5645 data_time: 0.0384 memory: 14901 loss: 1.0356 loss_prob: 0.5510 loss_thr: 0.3882 loss_db: 0.0964 2022/11/02 22:08:51 - mmengine - INFO - Epoch(train) [886][60/63] lr: 6.4776e-04 eta: 3:20:06 time: 1.3774 data_time: 0.0130 memory: 14901 loss: 1.0191 loss_prob: 0.5347 loss_thr: 0.3914 loss_db: 0.0929 2022/11/02 22:08:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:09:04 - mmengine - INFO - Epoch(train) [887][5/63] lr: 6.4590e-04 eta: 3:20:06 time: 1.5796 data_time: 0.2964 memory: 14901 loss: 0.9559 loss_prob: 0.4903 loss_thr: 0.3810 loss_db: 0.0847 2022/11/02 22:09:12 - mmengine - INFO - Epoch(train) [887][10/63] lr: 6.4590e-04 eta: 3:20:01 time: 1.6599 data_time: 0.3166 memory: 14901 loss: 1.0195 loss_prob: 0.5301 loss_thr: 0.3991 loss_db: 0.0903 2022/11/02 22:09:18 - mmengine - INFO - Epoch(train) [887][15/63] lr: 6.4590e-04 eta: 3:20:01 time: 1.4216 data_time: 0.0356 memory: 14901 loss: 0.9408 loss_prob: 0.4805 loss_thr: 0.3773 loss_db: 0.0831 2022/11/02 22:09:27 - mmengine - INFO - Epoch(train) [887][20/63] lr: 6.4590e-04 eta: 3:19:58 time: 1.5511 data_time: 0.0154 memory: 14901 loss: 0.8802 loss_prob: 0.4448 loss_thr: 0.3565 loss_db: 0.0790 2022/11/02 22:09:31 - mmengine - INFO - Epoch(train) [887][25/63] lr: 6.4590e-04 eta: 3:19:58 time: 1.2293 data_time: 0.0401 memory: 14901 loss: 0.9345 loss_prob: 0.4817 loss_thr: 0.3669 loss_db: 0.0859 2022/11/02 22:09:38 - mmengine - INFO - Epoch(train) [887][30/63] lr: 6.4590e-04 eta: 3:19:54 time: 1.0982 data_time: 0.0482 memory: 14901 loss: 0.9454 loss_prob: 0.4945 loss_thr: 0.3654 loss_db: 0.0856 2022/11/02 22:09:46 - mmengine - INFO - Epoch(train) [887][35/63] lr: 6.4590e-04 eta: 3:19:54 time: 1.5135 data_time: 0.0310 memory: 14901 loss: 0.9448 loss_prob: 0.5027 loss_thr: 0.3580 loss_db: 0.0841 2022/11/02 22:09:53 - mmengine - INFO - Epoch(train) [887][40/63] lr: 6.4590e-04 eta: 3:19:51 time: 1.4555 data_time: 0.0237 memory: 14901 loss: 0.9852 loss_prob: 0.5273 loss_thr: 0.3673 loss_db: 0.0906 2022/11/02 22:10:00 - mmengine - INFO - Epoch(train) [887][45/63] lr: 6.4590e-04 eta: 3:19:51 time: 1.4136 data_time: 0.0120 memory: 14901 loss: 1.0107 loss_prob: 0.5337 loss_thr: 0.3832 loss_db: 0.0938 2022/11/02 22:10:08 - mmengine - INFO - Epoch(train) [887][50/63] lr: 6.4590e-04 eta: 3:19:48 time: 1.5308 data_time: 0.0291 memory: 14901 loss: 1.0469 loss_prob: 0.5547 loss_thr: 0.3968 loss_db: 0.0954 2022/11/02 22:10:13 - mmengine - INFO - Epoch(train) [887][55/63] lr: 6.4590e-04 eta: 3:19:48 time: 1.3431 data_time: 0.0333 memory: 14901 loss: 1.0160 loss_prob: 0.5352 loss_thr: 0.3886 loss_db: 0.0922 2022/11/02 22:10:23 - mmengine - INFO - Epoch(train) [887][60/63] lr: 6.4590e-04 eta: 3:19:45 time: 1.4564 data_time: 0.0200 memory: 14901 loss: 0.9446 loss_prob: 0.4890 loss_thr: 0.3698 loss_db: 0.0858 2022/11/02 22:10:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:10:39 - mmengine - INFO - Epoch(train) [888][5/63] lr: 6.4405e-04 eta: 3:19:45 time: 2.0008 data_time: 0.2562 memory: 14901 loss: 0.9899 loss_prob: 0.5185 loss_thr: 0.3824 loss_db: 0.0890 2022/11/02 22:10:49 - mmengine - INFO - Epoch(train) [888][10/63] lr: 6.4405e-04 eta: 3:19:41 time: 2.0440 data_time: 0.2597 memory: 14901 loss: 0.9044 loss_prob: 0.4574 loss_thr: 0.3675 loss_db: 0.0794 2022/11/02 22:10:54 - mmengine - INFO - Epoch(train) [888][15/63] lr: 6.4405e-04 eta: 3:19:41 time: 1.5620 data_time: 0.0174 memory: 14901 loss: 0.9069 loss_prob: 0.4622 loss_thr: 0.3629 loss_db: 0.0818 2022/11/02 22:11:01 - mmengine - INFO - Epoch(train) [888][20/63] lr: 6.4405e-04 eta: 3:19:38 time: 1.2769 data_time: 0.0146 memory: 14901 loss: 0.9284 loss_prob: 0.4832 loss_thr: 0.3616 loss_db: 0.0836 2022/11/02 22:11:09 - mmengine - INFO - Epoch(train) [888][25/63] lr: 6.4405e-04 eta: 3:19:38 time: 1.4510 data_time: 0.0517 memory: 14901 loss: 0.9650 loss_prob: 0.5013 loss_thr: 0.3773 loss_db: 0.0864 2022/11/02 22:11:15 - mmengine - INFO - Epoch(train) [888][30/63] lr: 6.4405e-04 eta: 3:19:34 time: 1.3917 data_time: 0.0620 memory: 14901 loss: 0.9416 loss_prob: 0.4831 loss_thr: 0.3728 loss_db: 0.0857 2022/11/02 22:11:22 - mmengine - INFO - Epoch(train) [888][35/63] lr: 6.4405e-04 eta: 3:19:34 time: 1.3214 data_time: 0.0289 memory: 14901 loss: 0.9105 loss_prob: 0.4616 loss_thr: 0.3671 loss_db: 0.0819 2022/11/02 22:11:30 - mmengine - INFO - Epoch(train) [888][40/63] lr: 6.4405e-04 eta: 3:19:31 time: 1.4633 data_time: 0.0185 memory: 14901 loss: 0.9789 loss_prob: 0.5068 loss_thr: 0.3839 loss_db: 0.0882 2022/11/02 22:11:38 - mmengine - INFO - Epoch(train) [888][45/63] lr: 6.4405e-04 eta: 3:19:31 time: 1.5830 data_time: 0.0119 memory: 14901 loss: 0.9928 loss_prob: 0.5241 loss_thr: 0.3772 loss_db: 0.0914 2022/11/02 22:11:45 - mmengine - INFO - Epoch(train) [888][50/63] lr: 6.4405e-04 eta: 3:19:28 time: 1.5030 data_time: 0.0250 memory: 14901 loss: 1.0056 loss_prob: 0.5349 loss_thr: 0.3793 loss_db: 0.0913 2022/11/02 22:11:53 - mmengine - INFO - Epoch(train) [888][55/63] lr: 6.4405e-04 eta: 3:19:28 time: 1.5531 data_time: 0.0265 memory: 14901 loss: 1.0171 loss_prob: 0.5369 loss_thr: 0.3876 loss_db: 0.0927 2022/11/02 22:12:00 - mmengine - INFO - Epoch(train) [888][60/63] lr: 6.4405e-04 eta: 3:19:25 time: 1.4727 data_time: 0.0159 memory: 14901 loss: 1.0797 loss_prob: 0.5724 loss_thr: 0.4070 loss_db: 0.1002 2022/11/02 22:12:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:12:13 - mmengine - INFO - Epoch(train) [889][5/63] lr: 6.4219e-04 eta: 3:19:25 time: 1.3826 data_time: 0.2744 memory: 14901 loss: 1.0229 loss_prob: 0.5431 loss_thr: 0.3870 loss_db: 0.0929 2022/11/02 22:12:19 - mmengine - INFO - Epoch(train) [889][10/63] lr: 6.4219e-04 eta: 3:19:21 time: 1.7244 data_time: 0.2757 memory: 14901 loss: 0.9685 loss_prob: 0.5160 loss_thr: 0.3650 loss_db: 0.0874 2022/11/02 22:12:24 - mmengine - INFO - Epoch(train) [889][15/63] lr: 6.4219e-04 eta: 3:19:21 time: 1.1191 data_time: 0.0154 memory: 14901 loss: 0.9193 loss_prob: 0.4843 loss_thr: 0.3506 loss_db: 0.0845 2022/11/02 22:12:32 - mmengine - INFO - Epoch(train) [889][20/63] lr: 6.4219e-04 eta: 3:19:17 time: 1.3539 data_time: 0.0172 memory: 14901 loss: 0.9071 loss_prob: 0.4674 loss_thr: 0.3579 loss_db: 0.0818 2022/11/02 22:12:41 - mmengine - INFO - Epoch(train) [889][25/63] lr: 6.4219e-04 eta: 3:19:17 time: 1.6852 data_time: 0.0489 memory: 14901 loss: 0.9313 loss_prob: 0.4787 loss_thr: 0.3688 loss_db: 0.0838 2022/11/02 22:12:48 - mmengine - INFO - Epoch(train) [889][30/63] lr: 6.4219e-04 eta: 3:19:15 time: 1.5687 data_time: 0.0398 memory: 14901 loss: 0.9345 loss_prob: 0.4898 loss_thr: 0.3600 loss_db: 0.0846 2022/11/02 22:12:56 - mmengine - INFO - Epoch(train) [889][35/63] lr: 6.4219e-04 eta: 3:19:15 time: 1.5406 data_time: 0.0175 memory: 14901 loss: 0.8986 loss_prob: 0.4636 loss_thr: 0.3551 loss_db: 0.0799 2022/11/02 22:13:01 - mmengine - INFO - Epoch(train) [889][40/63] lr: 6.4219e-04 eta: 3:19:11 time: 1.2409 data_time: 0.0206 memory: 14901 loss: 1.0087 loss_prob: 0.5232 loss_thr: 0.3946 loss_db: 0.0909 2022/11/02 22:13:09 - mmengine - INFO - Epoch(train) [889][45/63] lr: 6.4219e-04 eta: 3:19:11 time: 1.2794 data_time: 0.0187 memory: 14901 loss: 1.0476 loss_prob: 0.5409 loss_thr: 0.4129 loss_db: 0.0938 2022/11/02 22:13:17 - mmengine - INFO - Epoch(train) [889][50/63] lr: 6.4219e-04 eta: 3:19:08 time: 1.6204 data_time: 0.0312 memory: 14901 loss: 1.0140 loss_prob: 0.5267 loss_thr: 0.3967 loss_db: 0.0906 2022/11/02 22:13:23 - mmengine - INFO - Epoch(train) [889][55/63] lr: 6.4219e-04 eta: 3:19:08 time: 1.4399 data_time: 0.0323 memory: 14901 loss: 0.9929 loss_prob: 0.5227 loss_thr: 0.3799 loss_db: 0.0904 2022/11/02 22:13:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:13:30 - mmengine - INFO - Epoch(train) [889][60/63] lr: 6.4219e-04 eta: 3:19:04 time: 1.2788 data_time: 0.0202 memory: 14901 loss: 0.9426 loss_prob: 0.4885 loss_thr: 0.3680 loss_db: 0.0862 2022/11/02 22:13:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:13:43 - mmengine - INFO - Epoch(train) [890][5/63] lr: 6.4033e-04 eta: 3:19:04 time: 1.5378 data_time: 0.2962 memory: 14901 loss: 1.0370 loss_prob: 0.5485 loss_thr: 0.3961 loss_db: 0.0924 2022/11/02 22:13:50 - mmengine - INFO - Epoch(train) [890][10/63] lr: 6.4033e-04 eta: 3:19:00 time: 1.7314 data_time: 0.2981 memory: 14901 loss: 1.0692 loss_prob: 0.5518 loss_thr: 0.4183 loss_db: 0.0991 2022/11/02 22:13:58 - mmengine - INFO - Epoch(train) [890][15/63] lr: 6.4033e-04 eta: 3:19:00 time: 1.5181 data_time: 0.0170 memory: 14901 loss: 1.0173 loss_prob: 0.5300 loss_thr: 0.3933 loss_db: 0.0939 2022/11/02 22:14:06 - mmengine - INFO - Epoch(train) [890][20/63] lr: 6.4033e-04 eta: 3:18:57 time: 1.5611 data_time: 0.0194 memory: 14901 loss: 0.9838 loss_prob: 0.5216 loss_thr: 0.3744 loss_db: 0.0878 2022/11/02 22:14:13 - mmengine - INFO - Epoch(train) [890][25/63] lr: 6.4033e-04 eta: 3:18:57 time: 1.4498 data_time: 0.0435 memory: 14901 loss: 0.9461 loss_prob: 0.4934 loss_thr: 0.3691 loss_db: 0.0837 2022/11/02 22:14:19 - mmengine - INFO - Epoch(train) [890][30/63] lr: 6.4033e-04 eta: 3:18:53 time: 1.3376 data_time: 0.0641 memory: 14901 loss: 1.0979 loss_prob: 0.5822 loss_thr: 0.4163 loss_db: 0.0993 2022/11/02 22:14:25 - mmengine - INFO - Epoch(train) [890][35/63] lr: 6.4033e-04 eta: 3:18:53 time: 1.2094 data_time: 0.0334 memory: 14901 loss: 1.1093 loss_prob: 0.5889 loss_thr: 0.4184 loss_db: 0.1020 2022/11/02 22:14:31 - mmengine - INFO - Epoch(train) [890][40/63] lr: 6.4033e-04 eta: 3:18:49 time: 1.2187 data_time: 0.0135 memory: 14901 loss: 0.9502 loss_prob: 0.4910 loss_thr: 0.3715 loss_db: 0.0877 2022/11/02 22:14:38 - mmengine - INFO - Epoch(train) [890][45/63] lr: 6.4033e-04 eta: 3:18:49 time: 1.3605 data_time: 0.0157 memory: 14901 loss: 0.9921 loss_prob: 0.5106 loss_thr: 0.3924 loss_db: 0.0890 2022/11/02 22:14:44 - mmengine - INFO - Epoch(train) [890][50/63] lr: 6.4033e-04 eta: 3:18:46 time: 1.2764 data_time: 0.0400 memory: 14901 loss: 0.9568 loss_prob: 0.5006 loss_thr: 0.3703 loss_db: 0.0859 2022/11/02 22:14:50 - mmengine - INFO - Epoch(train) [890][55/63] lr: 6.4033e-04 eta: 3:18:46 time: 1.1657 data_time: 0.0440 memory: 14901 loss: 0.9288 loss_prob: 0.4868 loss_thr: 0.3575 loss_db: 0.0845 2022/11/02 22:14:57 - mmengine - INFO - Epoch(train) [890][60/63] lr: 6.4033e-04 eta: 3:18:42 time: 1.3272 data_time: 0.0168 memory: 14901 loss: 1.0208 loss_prob: 0.5376 loss_thr: 0.3905 loss_db: 0.0927 2022/11/02 22:15:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:15:10 - mmengine - INFO - Epoch(train) [891][5/63] lr: 6.3847e-04 eta: 3:18:42 time: 1.5679 data_time: 0.3256 memory: 14901 loss: 0.9279 loss_prob: 0.4782 loss_thr: 0.3650 loss_db: 0.0847 2022/11/02 22:15:19 - mmengine - INFO - Epoch(train) [891][10/63] lr: 6.3847e-04 eta: 3:18:38 time: 1.8423 data_time: 0.3240 memory: 14901 loss: 0.9522 loss_prob: 0.4898 loss_thr: 0.3729 loss_db: 0.0895 2022/11/02 22:15:24 - mmengine - INFO - Epoch(train) [891][15/63] lr: 6.3847e-04 eta: 3:18:38 time: 1.4396 data_time: 0.0129 memory: 14901 loss: 1.0395 loss_prob: 0.5623 loss_thr: 0.3807 loss_db: 0.0965 2022/11/02 22:15:33 - mmengine - INFO - Epoch(train) [891][20/63] lr: 6.3847e-04 eta: 3:18:34 time: 1.3748 data_time: 0.0106 memory: 14901 loss: 1.0320 loss_prob: 0.5696 loss_thr: 0.3687 loss_db: 0.0937 2022/11/02 22:15:41 - mmengine - INFO - Epoch(train) [891][25/63] lr: 6.3847e-04 eta: 3:18:34 time: 1.6423 data_time: 0.0568 memory: 14901 loss: 0.9445 loss_prob: 0.4974 loss_thr: 0.3620 loss_db: 0.0851 2022/11/02 22:15:47 - mmengine - INFO - Epoch(train) [891][30/63] lr: 6.3847e-04 eta: 3:18:31 time: 1.4503 data_time: 0.0595 memory: 14901 loss: 0.9701 loss_prob: 0.5036 loss_thr: 0.3807 loss_db: 0.0858 2022/11/02 22:15:54 - mmengine - INFO - Epoch(train) [891][35/63] lr: 6.3847e-04 eta: 3:18:31 time: 1.3629 data_time: 0.0138 memory: 14901 loss: 1.0122 loss_prob: 0.5313 loss_thr: 0.3889 loss_db: 0.0921 2022/11/02 22:16:03 - mmengine - INFO - Epoch(train) [891][40/63] lr: 6.3847e-04 eta: 3:18:28 time: 1.5220 data_time: 0.0136 memory: 14901 loss: 0.9490 loss_prob: 0.4923 loss_thr: 0.3685 loss_db: 0.0881 2022/11/02 22:16:08 - mmengine - INFO - Epoch(train) [891][45/63] lr: 6.3847e-04 eta: 3:18:28 time: 1.3807 data_time: 0.0138 memory: 14901 loss: 0.9725 loss_prob: 0.4966 loss_thr: 0.3895 loss_db: 0.0864 2022/11/02 22:16:15 - mmengine - INFO - Epoch(train) [891][50/63] lr: 6.3847e-04 eta: 3:18:24 time: 1.2838 data_time: 0.0385 memory: 14901 loss: 1.0515 loss_prob: 0.5412 loss_thr: 0.4161 loss_db: 0.0943 2022/11/02 22:16:22 - mmengine - INFO - Epoch(train) [891][55/63] lr: 6.3847e-04 eta: 3:18:24 time: 1.3566 data_time: 0.0396 memory: 14901 loss: 1.0240 loss_prob: 0.5325 loss_thr: 0.3963 loss_db: 0.0952 2022/11/02 22:16:27 - mmengine - INFO - Epoch(train) [891][60/63] lr: 6.3847e-04 eta: 3:18:20 time: 1.2066 data_time: 0.0110 memory: 14901 loss: 0.9733 loss_prob: 0.5071 loss_thr: 0.3775 loss_db: 0.0887 2022/11/02 22:16:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:16:39 - mmengine - INFO - Epoch(train) [892][5/63] lr: 6.3661e-04 eta: 3:18:20 time: 1.3970 data_time: 0.2388 memory: 14901 loss: 0.9940 loss_prob: 0.5234 loss_thr: 0.3808 loss_db: 0.0898 2022/11/02 22:16:46 - mmengine - INFO - Epoch(train) [892][10/63] lr: 6.3661e-04 eta: 3:18:15 time: 1.5306 data_time: 0.2376 memory: 14901 loss: 1.0402 loss_prob: 0.5490 loss_thr: 0.3961 loss_db: 0.0951 2022/11/02 22:16:52 - mmengine - INFO - Epoch(train) [892][15/63] lr: 6.3661e-04 eta: 3:18:15 time: 1.3174 data_time: 0.0159 memory: 14901 loss: 1.0354 loss_prob: 0.5453 loss_thr: 0.3970 loss_db: 0.0931 2022/11/02 22:17:00 - mmengine - INFO - Epoch(train) [892][20/63] lr: 6.3661e-04 eta: 3:18:12 time: 1.4108 data_time: 0.0139 memory: 14901 loss: 0.9880 loss_prob: 0.5131 loss_thr: 0.3845 loss_db: 0.0904 2022/11/02 22:17:08 - mmengine - INFO - Epoch(train) [892][25/63] lr: 6.3661e-04 eta: 3:18:12 time: 1.5568 data_time: 0.0351 memory: 14901 loss: 0.9207 loss_prob: 0.4686 loss_thr: 0.3676 loss_db: 0.0845 2022/11/02 22:17:16 - mmengine - INFO - Epoch(train) [892][30/63] lr: 6.3661e-04 eta: 3:18:09 time: 1.5653 data_time: 0.0492 memory: 14901 loss: 0.8907 loss_prob: 0.4601 loss_thr: 0.3511 loss_db: 0.0795 2022/11/02 22:17:24 - mmengine - INFO - Epoch(train) [892][35/63] lr: 6.3661e-04 eta: 3:18:09 time: 1.5534 data_time: 0.0233 memory: 14901 loss: 0.9216 loss_prob: 0.4819 loss_thr: 0.3558 loss_db: 0.0840 2022/11/02 22:17:29 - mmengine - INFO - Epoch(train) [892][40/63] lr: 6.3661e-04 eta: 3:18:05 time: 1.3828 data_time: 0.0194 memory: 14901 loss: 0.9602 loss_prob: 0.4986 loss_thr: 0.3732 loss_db: 0.0884 2022/11/02 22:17:34 - mmengine - INFO - Epoch(train) [892][45/63] lr: 6.3661e-04 eta: 3:18:05 time: 1.0576 data_time: 0.0217 memory: 14901 loss: 0.9890 loss_prob: 0.5165 loss_thr: 0.3823 loss_db: 0.0902 2022/11/02 22:17:41 - mmengine - INFO - Epoch(train) [892][50/63] lr: 6.3661e-04 eta: 3:18:01 time: 1.1968 data_time: 0.0340 memory: 14901 loss: 0.9722 loss_prob: 0.5034 loss_thr: 0.3821 loss_db: 0.0866 2022/11/02 22:17:49 - mmengine - INFO - Epoch(train) [892][55/63] lr: 6.3661e-04 eta: 3:18:01 time: 1.4602 data_time: 0.0392 memory: 14901 loss: 1.0144 loss_prob: 0.5328 loss_thr: 0.3898 loss_db: 0.0918 2022/11/02 22:17:53 - mmengine - INFO - Epoch(train) [892][60/63] lr: 6.3661e-04 eta: 3:17:57 time: 1.1748 data_time: 0.0184 memory: 14901 loss: 1.0067 loss_prob: 0.5359 loss_thr: 0.3781 loss_db: 0.0927 2022/11/02 22:17:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:18:08 - mmengine - INFO - Epoch(train) [893][5/63] lr: 6.3475e-04 eta: 3:17:57 time: 1.6972 data_time: 0.3082 memory: 14901 loss: 0.9719 loss_prob: 0.5101 loss_thr: 0.3765 loss_db: 0.0854 2022/11/02 22:18:15 - mmengine - INFO - Epoch(train) [893][10/63] lr: 6.3475e-04 eta: 3:17:53 time: 1.7813 data_time: 0.3121 memory: 14901 loss: 0.9392 loss_prob: 0.4857 loss_thr: 0.3679 loss_db: 0.0857 2022/11/02 22:18:21 - mmengine - INFO - Epoch(train) [893][15/63] lr: 6.3475e-04 eta: 3:17:53 time: 1.3305 data_time: 0.0195 memory: 14901 loss: 0.9842 loss_prob: 0.5068 loss_thr: 0.3873 loss_db: 0.0901 2022/11/02 22:18:29 - mmengine - INFO - Epoch(train) [893][20/63] lr: 6.3475e-04 eta: 3:17:49 time: 1.4524 data_time: 0.0112 memory: 14901 loss: 0.9569 loss_prob: 0.4934 loss_thr: 0.3770 loss_db: 0.0865 2022/11/02 22:18:35 - mmengine - INFO - Epoch(train) [893][25/63] lr: 6.3475e-04 eta: 3:17:49 time: 1.3894 data_time: 0.0609 memory: 14901 loss: 0.9507 loss_prob: 0.4984 loss_thr: 0.3646 loss_db: 0.0877 2022/11/02 22:18:43 - mmengine - INFO - Epoch(train) [893][30/63] lr: 6.3475e-04 eta: 3:17:46 time: 1.3366 data_time: 0.0691 memory: 14901 loss: 1.0006 loss_prob: 0.5311 loss_thr: 0.3786 loss_db: 0.0909 2022/11/02 22:18:49 - mmengine - INFO - Epoch(train) [893][35/63] lr: 6.3475e-04 eta: 3:17:46 time: 1.4183 data_time: 0.0179 memory: 14901 loss: 0.9640 loss_prob: 0.5055 loss_thr: 0.3715 loss_db: 0.0870 2022/11/02 22:18:54 - mmengine - INFO - Epoch(train) [893][40/63] lr: 6.3475e-04 eta: 3:17:41 time: 1.1600 data_time: 0.0112 memory: 14901 loss: 0.9840 loss_prob: 0.5158 loss_thr: 0.3784 loss_db: 0.0898 2022/11/02 22:19:02 - mmengine - INFO - Epoch(train) [893][45/63] lr: 6.3475e-04 eta: 3:17:41 time: 1.2461 data_time: 0.0116 memory: 14901 loss: 0.9892 loss_prob: 0.5225 loss_thr: 0.3772 loss_db: 0.0895 2022/11/02 22:19:08 - mmengine - INFO - Epoch(train) [893][50/63] lr: 6.3475e-04 eta: 3:17:38 time: 1.3233 data_time: 0.0408 memory: 14901 loss: 0.9627 loss_prob: 0.5030 loss_thr: 0.3753 loss_db: 0.0845 2022/11/02 22:19:14 - mmengine - INFO - Epoch(train) [893][55/63] lr: 6.3475e-04 eta: 3:17:38 time: 1.2228 data_time: 0.0453 memory: 14901 loss: 0.9339 loss_prob: 0.4821 loss_thr: 0.3697 loss_db: 0.0822 2022/11/02 22:19:22 - mmengine - INFO - Epoch(train) [893][60/63] lr: 6.3475e-04 eta: 3:17:34 time: 1.3861 data_time: 0.0156 memory: 14901 loss: 0.9450 loss_prob: 0.4925 loss_thr: 0.3651 loss_db: 0.0874 2022/11/02 22:19:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:19:35 - mmengine - INFO - Epoch(train) [894][5/63] lr: 6.3289e-04 eta: 3:17:34 time: 1.7079 data_time: 0.2369 memory: 14901 loss: 0.9823 loss_prob: 0.5080 loss_thr: 0.3869 loss_db: 0.0874 2022/11/02 22:19:42 - mmengine - INFO - Epoch(train) [894][10/63] lr: 6.3289e-04 eta: 3:17:29 time: 1.7237 data_time: 0.2388 memory: 14901 loss: 0.9732 loss_prob: 0.5030 loss_thr: 0.3835 loss_db: 0.0867 2022/11/02 22:19:47 - mmengine - INFO - Epoch(train) [894][15/63] lr: 6.3289e-04 eta: 3:17:29 time: 1.2084 data_time: 0.0158 memory: 14901 loss: 0.9629 loss_prob: 0.5000 loss_thr: 0.3739 loss_db: 0.0891 2022/11/02 22:19:55 - mmengine - INFO - Epoch(train) [894][20/63] lr: 6.3289e-04 eta: 3:17:26 time: 1.3532 data_time: 0.0131 memory: 14901 loss: 0.9876 loss_prob: 0.5162 loss_thr: 0.3816 loss_db: 0.0898 2022/11/02 22:20:05 - mmengine - INFO - Epoch(train) [894][25/63] lr: 6.3289e-04 eta: 3:17:26 time: 1.7393 data_time: 0.0257 memory: 14901 loss: 1.0341 loss_prob: 0.5452 loss_thr: 0.3952 loss_db: 0.0936 2022/11/02 22:20:12 - mmengine - INFO - Epoch(train) [894][30/63] lr: 6.3289e-04 eta: 3:17:23 time: 1.6368 data_time: 0.0621 memory: 14901 loss: 1.1126 loss_prob: 0.5885 loss_thr: 0.4227 loss_db: 0.1014 2022/11/02 22:20:21 - mmengine - INFO - Epoch(train) [894][35/63] lr: 6.3289e-04 eta: 3:17:23 time: 1.5747 data_time: 0.0463 memory: 14901 loss: 1.0331 loss_prob: 0.5495 loss_thr: 0.3895 loss_db: 0.0941 2022/11/02 22:20:28 - mmengine - INFO - Epoch(train) [894][40/63] lr: 6.3289e-04 eta: 3:17:21 time: 1.6235 data_time: 0.0109 memory: 14901 loss: 0.9539 loss_prob: 0.5005 loss_thr: 0.3651 loss_db: 0.0883 2022/11/02 22:20:34 - mmengine - INFO - Epoch(train) [894][45/63] lr: 6.3289e-04 eta: 3:17:21 time: 1.3605 data_time: 0.0118 memory: 14901 loss: 1.0026 loss_prob: 0.5267 loss_thr: 0.3831 loss_db: 0.0928 2022/11/02 22:20:40 - mmengine - INFO - Epoch(train) [894][50/63] lr: 6.3289e-04 eta: 3:17:17 time: 1.2123 data_time: 0.0139 memory: 14901 loss: 0.9483 loss_prob: 0.5025 loss_thr: 0.3596 loss_db: 0.0862 2022/11/02 22:20:45 - mmengine - INFO - Epoch(train) [894][55/63] lr: 6.3289e-04 eta: 3:17:17 time: 1.0606 data_time: 0.0335 memory: 14901 loss: 0.9577 loss_prob: 0.5042 loss_thr: 0.3680 loss_db: 0.0855 2022/11/02 22:20:51 - mmengine - INFO - Epoch(train) [894][60/63] lr: 6.3289e-04 eta: 3:17:12 time: 1.1300 data_time: 0.0297 memory: 14901 loss: 1.0428 loss_prob: 0.5514 loss_thr: 0.3971 loss_db: 0.0943 2022/11/02 22:20:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:21:06 - mmengine - INFO - Epoch(train) [895][5/63] lr: 6.3103e-04 eta: 3:17:12 time: 1.7375 data_time: 0.3100 memory: 14901 loss: 1.0210 loss_prob: 0.5471 loss_thr: 0.3783 loss_db: 0.0957 2022/11/02 22:21:11 - mmengine - INFO - Epoch(train) [895][10/63] lr: 6.3103e-04 eta: 3:17:07 time: 1.4778 data_time: 0.3167 memory: 14901 loss: 1.0347 loss_prob: 0.5599 loss_thr: 0.3812 loss_db: 0.0936 2022/11/02 22:21:18 - mmengine - INFO - Epoch(train) [895][15/63] lr: 6.3103e-04 eta: 3:17:07 time: 1.2517 data_time: 0.0261 memory: 14901 loss: 1.0368 loss_prob: 0.5578 loss_thr: 0.3862 loss_db: 0.0928 2022/11/02 22:21:27 - mmengine - INFO - Epoch(train) [895][20/63] lr: 6.3103e-04 eta: 3:17:04 time: 1.6025 data_time: 0.0164 memory: 14901 loss: 0.9261 loss_prob: 0.4857 loss_thr: 0.3557 loss_db: 0.0847 2022/11/02 22:21:32 - mmengine - INFO - Epoch(train) [895][25/63] lr: 6.3103e-04 eta: 3:17:04 time: 1.3332 data_time: 0.0501 memory: 14901 loss: 0.9214 loss_prob: 0.4779 loss_thr: 0.3590 loss_db: 0.0845 2022/11/02 22:21:37 - mmengine - INFO - Epoch(train) [895][30/63] lr: 6.3103e-04 eta: 3:16:59 time: 0.9878 data_time: 0.0536 memory: 14901 loss: 0.9552 loss_prob: 0.5021 loss_thr: 0.3653 loss_db: 0.0878 2022/11/02 22:21:41 - mmengine - INFO - Epoch(train) [895][35/63] lr: 6.3103e-04 eta: 3:16:59 time: 0.9045 data_time: 0.0226 memory: 14901 loss: 0.9661 loss_prob: 0.5126 loss_thr: 0.3630 loss_db: 0.0905 2022/11/02 22:21:45 - mmengine - INFO - Epoch(train) [895][40/63] lr: 6.3103e-04 eta: 3:16:53 time: 0.8194 data_time: 0.0185 memory: 14901 loss: 0.9100 loss_prob: 0.4719 loss_thr: 0.3541 loss_db: 0.0841 2022/11/02 22:21:48 - mmengine - INFO - Epoch(train) [895][45/63] lr: 6.3103e-04 eta: 3:16:53 time: 0.7583 data_time: 0.0100 memory: 14901 loss: 0.9162 loss_prob: 0.4710 loss_thr: 0.3628 loss_db: 0.0825 2022/11/02 22:21:52 - mmengine - INFO - Epoch(train) [895][50/63] lr: 6.3103e-04 eta: 3:16:48 time: 0.7682 data_time: 0.0284 memory: 14901 loss: 0.9785 loss_prob: 0.5117 loss_thr: 0.3785 loss_db: 0.0883 2022/11/02 22:22:00 - mmengine - INFO - Epoch(train) [895][55/63] lr: 6.3103e-04 eta: 3:16:48 time: 1.1370 data_time: 0.0263 memory: 14901 loss: 0.9449 loss_prob: 0.4859 loss_thr: 0.3754 loss_db: 0.0836 2022/11/02 22:22:06 - mmengine - INFO - Epoch(train) [895][60/63] lr: 6.3103e-04 eta: 3:16:44 time: 1.3414 data_time: 0.0204 memory: 14901 loss: 0.8836 loss_prob: 0.4420 loss_thr: 0.3644 loss_db: 0.0772 2022/11/02 22:22:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:22:19 - mmengine - INFO - Epoch(train) [896][5/63] lr: 6.2917e-04 eta: 3:16:44 time: 1.5676 data_time: 0.2579 memory: 14901 loss: 0.9581 loss_prob: 0.4944 loss_thr: 0.3772 loss_db: 0.0865 2022/11/02 22:22:26 - mmengine - INFO - Epoch(train) [896][10/63] lr: 6.2917e-04 eta: 3:16:39 time: 1.7559 data_time: 0.2578 memory: 14901 loss: 1.0217 loss_prob: 0.5336 loss_thr: 0.3950 loss_db: 0.0931 2022/11/02 22:22:32 - mmengine - INFO - Epoch(train) [896][15/63] lr: 6.2917e-04 eta: 3:16:39 time: 1.2920 data_time: 0.0122 memory: 14901 loss: 0.9554 loss_prob: 0.4820 loss_thr: 0.3891 loss_db: 0.0843 2022/11/02 22:22:40 - mmengine - INFO - Epoch(train) [896][20/63] lr: 6.2917e-04 eta: 3:16:36 time: 1.4255 data_time: 0.0118 memory: 14901 loss: 0.8883 loss_prob: 0.4492 loss_thr: 0.3606 loss_db: 0.0785 2022/11/02 22:22:47 - mmengine - INFO - Epoch(train) [896][25/63] lr: 6.2917e-04 eta: 3:16:36 time: 1.5186 data_time: 0.0168 memory: 14901 loss: 0.9418 loss_prob: 0.4886 loss_thr: 0.3674 loss_db: 0.0859 2022/11/02 22:22:54 - mmengine - INFO - Epoch(train) [896][30/63] lr: 6.2917e-04 eta: 3:16:32 time: 1.3758 data_time: 0.0850 memory: 14901 loss: 1.0064 loss_prob: 0.5216 loss_thr: 0.3928 loss_db: 0.0920 2022/11/02 22:23:00 - mmengine - INFO - Epoch(train) [896][35/63] lr: 6.2917e-04 eta: 3:16:32 time: 1.2719 data_time: 0.0790 memory: 14901 loss: 1.0822 loss_prob: 0.5799 loss_thr: 0.4039 loss_db: 0.0984 2022/11/02 22:23:07 - mmengine - INFO - Epoch(train) [896][40/63] lr: 6.2917e-04 eta: 3:16:29 time: 1.3755 data_time: 0.0083 memory: 14901 loss: 1.0832 loss_prob: 0.5919 loss_thr: 0.3945 loss_db: 0.0967 2022/11/02 22:23:14 - mmengine - INFO - Epoch(train) [896][45/63] lr: 6.2917e-04 eta: 3:16:29 time: 1.4039 data_time: 0.0085 memory: 14901 loss: 1.0512 loss_prob: 0.5642 loss_thr: 0.3942 loss_db: 0.0927 2022/11/02 22:23:22 - mmengine - INFO - Epoch(train) [896][50/63] lr: 6.2917e-04 eta: 3:16:26 time: 1.4423 data_time: 0.0100 memory: 14901 loss: 1.0107 loss_prob: 0.5318 loss_thr: 0.3886 loss_db: 0.0904 2022/11/02 22:23:29 - mmengine - INFO - Epoch(train) [896][55/63] lr: 6.2917e-04 eta: 3:16:26 time: 1.4734 data_time: 0.0177 memory: 14901 loss: 0.9238 loss_prob: 0.4794 loss_thr: 0.3594 loss_db: 0.0850 2022/11/02 22:23:39 - mmengine - INFO - Epoch(train) [896][60/63] lr: 6.2917e-04 eta: 3:16:23 time: 1.6983 data_time: 0.0190 memory: 14901 loss: 0.9268 loss_prob: 0.4788 loss_thr: 0.3630 loss_db: 0.0850 2022/11/02 22:23:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:23:52 - mmengine - INFO - Epoch(train) [897][5/63] lr: 6.2730e-04 eta: 3:16:23 time: 1.7430 data_time: 0.3111 memory: 14901 loss: 1.0127 loss_prob: 0.5299 loss_thr: 0.3904 loss_db: 0.0924 2022/11/02 22:23:59 - mmengine - INFO - Epoch(train) [897][10/63] lr: 6.2730e-04 eta: 3:16:19 time: 1.9108 data_time: 0.3129 memory: 14901 loss: 1.0197 loss_prob: 0.5228 loss_thr: 0.4039 loss_db: 0.0930 2022/11/02 22:24:05 - mmengine - INFO - Epoch(train) [897][15/63] lr: 6.2730e-04 eta: 3:16:19 time: 1.2267 data_time: 0.0099 memory: 14901 loss: 0.9529 loss_prob: 0.4885 loss_thr: 0.3792 loss_db: 0.0852 2022/11/02 22:24:13 - mmengine - INFO - Epoch(train) [897][20/63] lr: 6.2730e-04 eta: 3:16:15 time: 1.3139 data_time: 0.0112 memory: 14901 loss: 0.9620 loss_prob: 0.4965 loss_thr: 0.3800 loss_db: 0.0855 2022/11/02 22:24:20 - mmengine - INFO - Epoch(train) [897][25/63] lr: 6.2730e-04 eta: 3:16:15 time: 1.5608 data_time: 0.0687 memory: 14901 loss: 0.9520 loss_prob: 0.4820 loss_thr: 0.3852 loss_db: 0.0848 2022/11/02 22:24:26 - mmengine - INFO - Epoch(train) [897][30/63] lr: 6.2730e-04 eta: 3:16:11 time: 1.3427 data_time: 0.0735 memory: 14901 loss: 0.9736 loss_prob: 0.4979 loss_thr: 0.3881 loss_db: 0.0877 2022/11/02 22:24:34 - mmengine - INFO - Epoch(train) [897][35/63] lr: 6.2730e-04 eta: 3:16:11 time: 1.3522 data_time: 0.0169 memory: 14901 loss: 1.0134 loss_prob: 0.5309 loss_thr: 0.3904 loss_db: 0.0921 2022/11/02 22:24:40 - mmengine - INFO - Epoch(train) [897][40/63] lr: 6.2730e-04 eta: 3:16:08 time: 1.4279 data_time: 0.0105 memory: 14901 loss: 0.9833 loss_prob: 0.5204 loss_thr: 0.3745 loss_db: 0.0884 2022/11/02 22:24:46 - mmengine - INFO - Epoch(train) [897][45/63] lr: 6.2730e-04 eta: 3:16:08 time: 1.2357 data_time: 0.0094 memory: 14901 loss: 1.0125 loss_prob: 0.5415 loss_thr: 0.3807 loss_db: 0.0904 2022/11/02 22:24:55 - mmengine - INFO - Epoch(train) [897][50/63] lr: 6.2730e-04 eta: 3:16:05 time: 1.4334 data_time: 0.0283 memory: 14901 loss: 1.0479 loss_prob: 0.5584 loss_thr: 0.3939 loss_db: 0.0956 2022/11/02 22:25:02 - mmengine - INFO - Epoch(train) [897][55/63] lr: 6.2730e-04 eta: 3:16:05 time: 1.6047 data_time: 0.0344 memory: 14901 loss: 1.0031 loss_prob: 0.5245 loss_thr: 0.3867 loss_db: 0.0920 2022/11/02 22:25:10 - mmengine - INFO - Epoch(train) [897][60/63] lr: 6.2730e-04 eta: 3:16:02 time: 1.5463 data_time: 0.0154 memory: 14901 loss: 0.9858 loss_prob: 0.5154 loss_thr: 0.3818 loss_db: 0.0887 2022/11/02 22:25:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:25:25 - mmengine - INFO - Epoch(train) [898][5/63] lr: 6.2544e-04 eta: 3:16:02 time: 1.8820 data_time: 0.2821 memory: 14901 loss: 0.8762 loss_prob: 0.4421 loss_thr: 0.3556 loss_db: 0.0785 2022/11/02 22:25:31 - mmengine - INFO - Epoch(train) [898][10/63] lr: 6.2544e-04 eta: 3:15:57 time: 1.6895 data_time: 0.2832 memory: 14901 loss: 0.8752 loss_prob: 0.4442 loss_thr: 0.3529 loss_db: 0.0780 2022/11/02 22:25:39 - mmengine - INFO - Epoch(train) [898][15/63] lr: 6.2544e-04 eta: 3:15:57 time: 1.4034 data_time: 0.0124 memory: 14901 loss: 0.9203 loss_prob: 0.4670 loss_thr: 0.3720 loss_db: 0.0813 2022/11/02 22:25:47 - mmengine - INFO - Epoch(train) [898][20/63] lr: 6.2544e-04 eta: 3:15:54 time: 1.5996 data_time: 0.0108 memory: 14901 loss: 0.9452 loss_prob: 0.4882 loss_thr: 0.3722 loss_db: 0.0848 2022/11/02 22:25:52 - mmengine - INFO - Epoch(train) [898][25/63] lr: 6.2544e-04 eta: 3:15:54 time: 1.2773 data_time: 0.0435 memory: 14901 loss: 1.0391 loss_prob: 0.5410 loss_thr: 0.4035 loss_db: 0.0946 2022/11/02 22:25:59 - mmengine - INFO - Epoch(train) [898][30/63] lr: 6.2544e-04 eta: 3:15:50 time: 1.2638 data_time: 0.0634 memory: 14901 loss: 1.0196 loss_prob: 0.5229 loss_thr: 0.4033 loss_db: 0.0934 2022/11/02 22:26:05 - mmengine - INFO - Epoch(train) [898][35/63] lr: 6.2544e-04 eta: 3:15:50 time: 1.3013 data_time: 0.0307 memory: 14901 loss: 0.9399 loss_prob: 0.4801 loss_thr: 0.3749 loss_db: 0.0849 2022/11/02 22:26:10 - mmengine - INFO - Epoch(train) [898][40/63] lr: 6.2544e-04 eta: 3:15:45 time: 1.0887 data_time: 0.0186 memory: 14901 loss: 0.9326 loss_prob: 0.4758 loss_thr: 0.3746 loss_db: 0.0822 2022/11/02 22:26:19 - mmengine - INFO - Epoch(train) [898][45/63] lr: 6.2544e-04 eta: 3:15:45 time: 1.3831 data_time: 0.0180 memory: 14901 loss: 0.9720 loss_prob: 0.4995 loss_thr: 0.3864 loss_db: 0.0861 2022/11/02 22:26:25 - mmengine - INFO - Epoch(train) [898][50/63] lr: 6.2544e-04 eta: 3:15:42 time: 1.4262 data_time: 0.0223 memory: 14901 loss: 1.0283 loss_prob: 0.5355 loss_thr: 0.4004 loss_db: 0.0924 2022/11/02 22:26:31 - mmengine - INFO - Epoch(train) [898][55/63] lr: 6.2544e-04 eta: 3:15:42 time: 1.1987 data_time: 0.0309 memory: 14901 loss: 1.0482 loss_prob: 0.5526 loss_thr: 0.3990 loss_db: 0.0966 2022/11/02 22:26:37 - mmengine - INFO - Epoch(train) [898][60/63] lr: 6.2544e-04 eta: 3:15:38 time: 1.2244 data_time: 0.0202 memory: 14901 loss: 1.0069 loss_prob: 0.5250 loss_thr: 0.3907 loss_db: 0.0912 2022/11/02 22:26:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:26:49 - mmengine - INFO - Epoch(train) [899][5/63] lr: 6.2358e-04 eta: 3:15:38 time: 1.6623 data_time: 0.2730 memory: 14901 loss: 1.0253 loss_prob: 0.5336 loss_thr: 0.4005 loss_db: 0.0912 2022/11/02 22:26:56 - mmengine - INFO - Epoch(train) [899][10/63] lr: 6.2358e-04 eta: 3:15:32 time: 1.6590 data_time: 0.2721 memory: 14901 loss: 0.9635 loss_prob: 0.4959 loss_thr: 0.3811 loss_db: 0.0865 2022/11/02 22:27:03 - mmengine - INFO - Epoch(train) [899][15/63] lr: 6.2358e-04 eta: 3:15:32 time: 1.3820 data_time: 0.0110 memory: 14901 loss: 0.9581 loss_prob: 0.5003 loss_thr: 0.3697 loss_db: 0.0880 2022/11/02 22:27:08 - mmengine - INFO - Epoch(train) [899][20/63] lr: 6.2358e-04 eta: 3:15:28 time: 1.2264 data_time: 0.0134 memory: 14901 loss: 0.9799 loss_prob: 0.5142 loss_thr: 0.3774 loss_db: 0.0883 2022/11/02 22:27:15 - mmengine - INFO - Epoch(train) [899][25/63] lr: 6.2358e-04 eta: 3:15:28 time: 1.1837 data_time: 0.0194 memory: 14901 loss: 1.0146 loss_prob: 0.5296 loss_thr: 0.3940 loss_db: 0.0910 2022/11/02 22:27:24 - mmengine - INFO - Epoch(train) [899][30/63] lr: 6.2358e-04 eta: 3:15:25 time: 1.5454 data_time: 0.0527 memory: 14901 loss: 1.0355 loss_prob: 0.5483 loss_thr: 0.3913 loss_db: 0.0959 2022/11/02 22:27:29 - mmengine - INFO - Epoch(train) [899][35/63] lr: 6.2358e-04 eta: 3:15:25 time: 1.4040 data_time: 0.0452 memory: 14901 loss: 0.9629 loss_prob: 0.5016 loss_thr: 0.3738 loss_db: 0.0876 2022/11/02 22:27:34 - mmengine - INFO - Epoch(train) [899][40/63] lr: 6.2358e-04 eta: 3:15:21 time: 1.0840 data_time: 0.0118 memory: 14901 loss: 0.9510 loss_prob: 0.4922 loss_thr: 0.3740 loss_db: 0.0848 2022/11/02 22:27:40 - mmengine - INFO - Epoch(train) [899][45/63] lr: 6.2358e-04 eta: 3:15:21 time: 1.1320 data_time: 0.0091 memory: 14901 loss: 1.0316 loss_prob: 0.5544 loss_thr: 0.3840 loss_db: 0.0931 2022/11/02 22:27:46 - mmengine - INFO - Epoch(train) [899][50/63] lr: 6.2358e-04 eta: 3:15:16 time: 1.1602 data_time: 0.0249 memory: 14901 loss: 0.9943 loss_prob: 0.5304 loss_thr: 0.3729 loss_db: 0.0910 2022/11/02 22:27:50 - mmengine - INFO - Epoch(train) [899][55/63] lr: 6.2358e-04 eta: 3:15:16 time: 0.9704 data_time: 0.0352 memory: 14901 loss: 0.9567 loss_prob: 0.4921 loss_thr: 0.3763 loss_db: 0.0882 2022/11/02 22:27:56 - mmengine - INFO - Epoch(train) [899][60/63] lr: 6.2358e-04 eta: 3:15:11 time: 0.9881 data_time: 0.0200 memory: 14901 loss: 0.9603 loss_prob: 0.4923 loss_thr: 0.3816 loss_db: 0.0864 2022/11/02 22:28:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:28:10 - mmengine - INFO - Epoch(train) [900][5/63] lr: 6.2171e-04 eta: 3:15:11 time: 1.5833 data_time: 0.2912 memory: 14901 loss: 0.9885 loss_prob: 0.5122 loss_thr: 0.3847 loss_db: 0.0915 2022/11/02 22:28:17 - mmengine - INFO - Epoch(train) [900][10/63] lr: 6.2171e-04 eta: 3:15:06 time: 1.6527 data_time: 0.2880 memory: 14901 loss: 0.9488 loss_prob: 0.4820 loss_thr: 0.3822 loss_db: 0.0846 2022/11/02 22:28:24 - mmengine - INFO - Epoch(train) [900][15/63] lr: 6.2171e-04 eta: 3:15:06 time: 1.4894 data_time: 0.0116 memory: 14901 loss: 0.9589 loss_prob: 0.4992 loss_thr: 0.3724 loss_db: 0.0873 2022/11/02 22:28:32 - mmengine - INFO - Epoch(train) [900][20/63] lr: 6.2171e-04 eta: 3:15:03 time: 1.5302 data_time: 0.0159 memory: 14901 loss: 1.0138 loss_prob: 0.5318 loss_thr: 0.3887 loss_db: 0.0933 2022/11/02 22:28:39 - mmengine - INFO - Epoch(train) [900][25/63] lr: 6.2171e-04 eta: 3:15:03 time: 1.4237 data_time: 0.0522 memory: 14901 loss: 0.9536 loss_prob: 0.4905 loss_thr: 0.3775 loss_db: 0.0857 2022/11/02 22:28:45 - mmengine - INFO - Epoch(train) [900][30/63] lr: 6.2171e-04 eta: 3:14:59 time: 1.3378 data_time: 0.0683 memory: 14901 loss: 0.9471 loss_prob: 0.4877 loss_thr: 0.3746 loss_db: 0.0848 2022/11/02 22:28:51 - mmengine - INFO - Epoch(train) [900][35/63] lr: 6.2171e-04 eta: 3:14:59 time: 1.1872 data_time: 0.0306 memory: 14901 loss: 1.0168 loss_prob: 0.5289 loss_thr: 0.3967 loss_db: 0.0913 2022/11/02 22:28:58 - mmengine - INFO - Epoch(train) [900][40/63] lr: 6.2171e-04 eta: 3:14:55 time: 1.2911 data_time: 0.0145 memory: 14901 loss: 0.9933 loss_prob: 0.5205 loss_thr: 0.3827 loss_db: 0.0901 2022/11/02 22:29:05 - mmengine - INFO - Epoch(train) [900][45/63] lr: 6.2171e-04 eta: 3:14:55 time: 1.4531 data_time: 0.0199 memory: 14901 loss: 0.9234 loss_prob: 0.4780 loss_thr: 0.3615 loss_db: 0.0839 2022/11/02 22:29:12 - mmengine - INFO - Epoch(train) [900][50/63] lr: 6.2171e-04 eta: 3:14:52 time: 1.3581 data_time: 0.0331 memory: 14901 loss: 0.9672 loss_prob: 0.4975 loss_thr: 0.3831 loss_db: 0.0867 2022/11/02 22:29:19 - mmengine - INFO - Epoch(train) [900][55/63] lr: 6.2171e-04 eta: 3:14:52 time: 1.3690 data_time: 0.0330 memory: 14901 loss: 1.0126 loss_prob: 0.5277 loss_thr: 0.3924 loss_db: 0.0925 2022/11/02 22:29:25 - mmengine - INFO - Epoch(train) [900][60/63] lr: 6.2171e-04 eta: 3:14:48 time: 1.3117 data_time: 0.0158 memory: 14901 loss: 0.9461 loss_prob: 0.4889 loss_thr: 0.3726 loss_db: 0.0847 2022/11/02 22:29:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:29:29 - mmengine - INFO - Saving checkpoint at 900 epochs 2022/11/02 22:29:34 - mmengine - INFO - Epoch(val) [900][5/500] eta: 3:14:48 time: 0.0597 data_time: 0.0096 memory: 14901 2022/11/02 22:29:34 - mmengine - INFO - Epoch(val) [900][10/500] eta: 0:00:37 time: 0.0758 data_time: 0.0121 memory: 1008 2022/11/02 22:29:34 - mmengine - INFO - Epoch(val) [900][15/500] eta: 0:00:37 time: 0.0614 data_time: 0.0067 memory: 1008 2022/11/02 22:29:35 - mmengine - INFO - Epoch(val) [900][20/500] eta: 0:00:25 time: 0.0533 data_time: 0.0053 memory: 1008 2022/11/02 22:29:35 - mmengine - INFO - Epoch(val) [900][25/500] eta: 0:00:25 time: 0.0511 data_time: 0.0047 memory: 1008 2022/11/02 22:29:35 - mmengine - INFO - Epoch(val) [900][30/500] eta: 0:00:26 time: 0.0570 data_time: 0.0042 memory: 1008 2022/11/02 22:29:35 - mmengine - INFO - Epoch(val) [900][35/500] eta: 0:00:26 time: 0.0614 data_time: 0.0056 memory: 1008 2022/11/02 22:29:36 - mmengine - INFO - Epoch(val) [900][40/500] eta: 0:00:30 time: 0.0666 data_time: 0.0077 memory: 1008 2022/11/02 22:29:36 - mmengine - INFO - Epoch(val) [900][45/500] eta: 0:00:30 time: 0.0684 data_time: 0.0087 memory: 1008 2022/11/02 22:29:37 - mmengine - INFO - Epoch(val) [900][50/500] eta: 0:00:30 time: 0.0675 data_time: 0.0097 memory: 1008 2022/11/02 22:29:37 - mmengine - INFO - Epoch(val) [900][55/500] eta: 0:00:30 time: 0.0639 data_time: 0.0070 memory: 1008 2022/11/02 22:29:37 - mmengine - INFO - Epoch(val) [900][60/500] eta: 0:00:25 time: 0.0570 data_time: 0.0081 memory: 1008 2022/11/02 22:29:37 - mmengine - INFO - Epoch(val) [900][65/500] eta: 0:00:25 time: 0.0621 data_time: 0.0107 memory: 1008 2022/11/02 22:29:38 - mmengine - INFO - Epoch(val) [900][70/500] eta: 0:00:23 time: 0.0539 data_time: 0.0057 memory: 1008 2022/11/02 22:29:38 - mmengine - INFO - Epoch(val) [900][75/500] eta: 0:00:23 time: 0.0400 data_time: 0.0025 memory: 1008 2022/11/02 22:29:38 - mmengine - INFO - Epoch(val) [900][80/500] eta: 0:00:16 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/02 22:29:38 - mmengine - INFO - Epoch(val) [900][85/500] eta: 0:00:16 time: 0.0383 data_time: 0.0030 memory: 1008 2022/11/02 22:29:38 - mmengine - INFO - Epoch(val) [900][90/500] eta: 0:00:19 time: 0.0465 data_time: 0.0039 memory: 1008 2022/11/02 22:29:39 - mmengine - INFO - Epoch(val) [900][95/500] eta: 0:00:19 time: 0.0610 data_time: 0.0088 memory: 1008 2022/11/02 22:29:39 - mmengine - INFO - Epoch(val) [900][100/500] eta: 0:00:24 time: 0.0600 data_time: 0.0108 memory: 1008 2022/11/02 22:29:39 - mmengine - INFO - Epoch(val) [900][105/500] eta: 0:00:24 time: 0.0582 data_time: 0.0076 memory: 1008 2022/11/02 22:29:40 - mmengine - INFO - Epoch(val) [900][110/500] eta: 0:00:22 time: 0.0582 data_time: 0.0071 memory: 1008 2022/11/02 22:29:40 - mmengine - INFO - Epoch(val) [900][115/500] eta: 0:00:22 time: 0.0537 data_time: 0.0052 memory: 1008 2022/11/02 22:29:40 - mmengine - INFO - Epoch(val) [900][120/500] eta: 0:00:21 time: 0.0559 data_time: 0.0050 memory: 1008 2022/11/02 22:29:40 - mmengine - INFO - Epoch(val) [900][125/500] eta: 0:00:21 time: 0.0514 data_time: 0.0049 memory: 1008 2022/11/02 22:29:41 - mmengine - INFO - Epoch(val) [900][130/500] eta: 0:00:17 time: 0.0460 data_time: 0.0028 memory: 1008 2022/11/02 22:29:41 - mmengine - INFO - Epoch(val) [900][135/500] eta: 0:00:17 time: 0.0545 data_time: 0.0068 memory: 1008 2022/11/02 22:29:41 - mmengine - INFO - Epoch(val) [900][140/500] eta: 0:00:21 time: 0.0607 data_time: 0.0095 memory: 1008 2022/11/02 22:29:42 - mmengine - INFO - Epoch(val) [900][145/500] eta: 0:00:21 time: 0.0621 data_time: 0.0076 memory: 1008 2022/11/02 22:29:42 - mmengine - INFO - Epoch(val) [900][150/500] eta: 0:00:22 time: 0.0635 data_time: 0.0085 memory: 1008 2022/11/02 22:29:42 - mmengine - INFO - Epoch(val) [900][155/500] eta: 0:00:22 time: 0.0616 data_time: 0.0069 memory: 1008 2022/11/02 22:29:42 - mmengine - INFO - Epoch(val) [900][160/500] eta: 0:00:19 time: 0.0563 data_time: 0.0037 memory: 1008 2022/11/02 22:29:43 - mmengine - INFO - Epoch(val) [900][165/500] eta: 0:00:19 time: 0.0533 data_time: 0.0044 memory: 1008 2022/11/02 22:29:43 - mmengine - INFO - Epoch(val) [900][170/500] eta: 0:00:19 time: 0.0584 data_time: 0.0059 memory: 1008 2022/11/02 22:29:43 - mmengine - INFO - Epoch(val) [900][175/500] eta: 0:00:19 time: 0.0577 data_time: 0.0062 memory: 1008 2022/11/02 22:29:44 - mmengine - INFO - Epoch(val) [900][180/500] eta: 0:00:16 time: 0.0509 data_time: 0.0048 memory: 1008 2022/11/02 22:29:44 - mmengine - INFO - Epoch(val) [900][185/500] eta: 0:00:16 time: 0.0492 data_time: 0.0034 memory: 1008 2022/11/02 22:29:44 - mmengine - INFO - Epoch(val) [900][190/500] eta: 0:00:14 time: 0.0473 data_time: 0.0029 memory: 1008 2022/11/02 22:29:44 - mmengine - INFO - Epoch(val) [900][195/500] eta: 0:00:14 time: 0.0420 data_time: 0.0027 memory: 1008 2022/11/02 22:29:45 - mmengine - INFO - Epoch(val) [900][200/500] eta: 0:00:13 time: 0.0442 data_time: 0.0027 memory: 1008 2022/11/02 22:29:45 - mmengine - INFO - Epoch(val) [900][205/500] eta: 0:00:13 time: 0.0460 data_time: 0.0029 memory: 1008 2022/11/02 22:29:45 - mmengine - INFO - Epoch(val) [900][210/500] eta: 0:00:13 time: 0.0467 data_time: 0.0041 memory: 1008 2022/11/02 22:29:45 - mmengine - INFO - Epoch(val) [900][215/500] eta: 0:00:13 time: 0.0470 data_time: 0.0041 memory: 1008 2022/11/02 22:29:45 - mmengine - INFO - Epoch(val) [900][220/500] eta: 0:00:14 time: 0.0502 data_time: 0.0051 memory: 1008 2022/11/02 22:29:46 - mmengine - INFO - Epoch(val) [900][225/500] eta: 0:00:14 time: 0.0554 data_time: 0.0058 memory: 1008 2022/11/02 22:29:46 - mmengine - INFO - Epoch(val) [900][230/500] eta: 0:00:15 time: 0.0566 data_time: 0.0079 memory: 1008 2022/11/02 22:29:46 - mmengine - INFO - Epoch(val) [900][235/500] eta: 0:00:15 time: 0.0583 data_time: 0.0081 memory: 1008 2022/11/02 22:29:47 - mmengine - INFO - Epoch(val) [900][240/500] eta: 0:00:14 time: 0.0549 data_time: 0.0041 memory: 1008 2022/11/02 22:29:47 - mmengine - INFO - Epoch(val) [900][245/500] eta: 0:00:14 time: 0.0513 data_time: 0.0040 memory: 1008 2022/11/02 22:29:47 - mmengine - INFO - Epoch(val) [900][250/500] eta: 0:00:13 time: 0.0541 data_time: 0.0042 memory: 1008 2022/11/02 22:29:47 - mmengine - INFO - Epoch(val) [900][255/500] eta: 0:00:13 time: 0.0552 data_time: 0.0050 memory: 1008 2022/11/02 22:29:48 - mmengine - INFO - Epoch(val) [900][260/500] eta: 0:00:13 time: 0.0560 data_time: 0.0071 memory: 1008 2022/11/02 22:29:48 - mmengine - INFO - Epoch(val) [900][265/500] eta: 0:00:13 time: 0.0584 data_time: 0.0090 memory: 1008 2022/11/02 22:29:48 - mmengine - INFO - Epoch(val) [900][270/500] eta: 0:00:12 time: 0.0522 data_time: 0.0066 memory: 1008 2022/11/02 22:29:48 - mmengine - INFO - Epoch(val) [900][275/500] eta: 0:00:12 time: 0.0473 data_time: 0.0043 memory: 1008 2022/11/02 22:29:49 - mmengine - INFO - Epoch(val) [900][280/500] eta: 0:00:11 time: 0.0511 data_time: 0.0048 memory: 1008 2022/11/02 22:29:49 - mmengine - INFO - Epoch(val) [900][285/500] eta: 0:00:11 time: 0.0451 data_time: 0.0032 memory: 1008 2022/11/02 22:29:49 - mmengine - INFO - Epoch(val) [900][290/500] eta: 0:00:08 time: 0.0402 data_time: 0.0025 memory: 1008 2022/11/02 22:29:49 - mmengine - INFO - Epoch(val) [900][295/500] eta: 0:00:08 time: 0.0422 data_time: 0.0025 memory: 1008 2022/11/02 22:29:50 - mmengine - INFO - Epoch(val) [900][300/500] eta: 0:00:08 time: 0.0414 data_time: 0.0026 memory: 1008 2022/11/02 22:29:50 - mmengine - INFO - Epoch(val) [900][305/500] eta: 0:00:08 time: 0.0472 data_time: 0.0043 memory: 1008 2022/11/02 22:29:50 - mmengine - INFO - Epoch(val) [900][310/500] eta: 0:00:10 time: 0.0547 data_time: 0.0056 memory: 1008 2022/11/02 22:29:50 - mmengine - INFO - Epoch(val) [900][315/500] eta: 0:00:10 time: 0.0526 data_time: 0.0039 memory: 1008 2022/11/02 22:29:51 - mmengine - INFO - Epoch(val) [900][320/500] eta: 0:00:08 time: 0.0453 data_time: 0.0029 memory: 1008 2022/11/02 22:29:51 - mmengine - INFO - Epoch(val) [900][325/500] eta: 0:00:08 time: 0.0577 data_time: 0.0039 memory: 1008 2022/11/02 22:29:51 - mmengine - INFO - Epoch(val) [900][330/500] eta: 0:00:10 time: 0.0609 data_time: 0.0038 memory: 1008 2022/11/02 22:29:51 - mmengine - INFO - Epoch(val) [900][335/500] eta: 0:00:10 time: 0.0554 data_time: 0.0075 memory: 1008 2022/11/02 22:29:52 - mmengine - INFO - Epoch(val) [900][340/500] eta: 0:00:11 time: 0.0723 data_time: 0.0108 memory: 1008 2022/11/02 22:29:52 - mmengine - INFO - Epoch(val) [900][345/500] eta: 0:00:11 time: 0.0710 data_time: 0.0092 memory: 1008 2022/11/02 22:29:52 - mmengine - INFO - Epoch(val) [900][350/500] eta: 0:00:08 time: 0.0558 data_time: 0.0062 memory: 1008 2022/11/02 22:29:53 - mmengine - INFO - Epoch(val) [900][355/500] eta: 0:00:08 time: 0.0511 data_time: 0.0035 memory: 1008 2022/11/02 22:29:53 - mmengine - INFO - Epoch(val) [900][360/500] eta: 0:00:07 time: 0.0534 data_time: 0.0057 memory: 1008 2022/11/02 22:29:53 - mmengine - INFO - Epoch(val) [900][365/500] eta: 0:00:07 time: 0.0635 data_time: 0.0108 memory: 1008 2022/11/02 22:29:54 - mmengine - INFO - Epoch(val) [900][370/500] eta: 0:00:08 time: 0.0644 data_time: 0.0156 memory: 1008 2022/11/02 22:29:54 - mmengine - INFO - Epoch(val) [900][375/500] eta: 0:00:08 time: 0.0542 data_time: 0.0124 memory: 1008 2022/11/02 22:29:54 - mmengine - INFO - Epoch(val) [900][380/500] eta: 0:00:06 time: 0.0542 data_time: 0.0056 memory: 1008 2022/11/02 22:29:54 - mmengine - INFO - Epoch(val) [900][385/500] eta: 0:00:06 time: 0.0478 data_time: 0.0032 memory: 1008 2022/11/02 22:29:55 - mmengine - INFO - Epoch(val) [900][390/500] eta: 0:00:04 time: 0.0383 data_time: 0.0026 memory: 1008 2022/11/02 22:29:55 - mmengine - INFO - Epoch(val) [900][395/500] eta: 0:00:04 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/02 22:29:55 - mmengine - INFO - Epoch(val) [900][400/500] eta: 0:00:03 time: 0.0375 data_time: 0.0026 memory: 1008 2022/11/02 22:29:55 - mmengine - INFO - Epoch(val) [900][405/500] eta: 0:00:03 time: 0.0418 data_time: 0.0036 memory: 1008 2022/11/02 22:29:55 - mmengine - INFO - Epoch(val) [900][410/500] eta: 0:00:04 time: 0.0497 data_time: 0.0041 memory: 1008 2022/11/02 22:29:56 - mmengine - INFO - Epoch(val) [900][415/500] eta: 0:00:04 time: 0.0504 data_time: 0.0057 memory: 1008 2022/11/02 22:29:56 - mmengine - INFO - Epoch(val) [900][420/500] eta: 0:00:03 time: 0.0470 data_time: 0.0056 memory: 1008 2022/11/02 22:29:56 - mmengine - INFO - Epoch(val) [900][425/500] eta: 0:00:03 time: 0.0471 data_time: 0.0032 memory: 1008 2022/11/02 22:29:56 - mmengine - INFO - Epoch(val) [900][430/500] eta: 0:00:03 time: 0.0499 data_time: 0.0031 memory: 1008 2022/11/02 22:29:57 - mmengine - INFO - Epoch(val) [900][435/500] eta: 0:00:03 time: 0.0573 data_time: 0.0094 memory: 1008 2022/11/02 22:29:57 - mmengine - INFO - Epoch(val) [900][440/500] eta: 0:00:03 time: 0.0570 data_time: 0.0095 memory: 1008 2022/11/02 22:29:57 - mmengine - INFO - Epoch(val) [900][445/500] eta: 0:00:03 time: 0.0568 data_time: 0.0043 memory: 1008 2022/11/02 22:29:58 - mmengine - INFO - Epoch(val) [900][450/500] eta: 0:00:03 time: 0.0603 data_time: 0.0054 memory: 1008 2022/11/02 22:29:58 - mmengine - INFO - Epoch(val) [900][455/500] eta: 0:00:03 time: 0.0528 data_time: 0.0043 memory: 1008 2022/11/02 22:29:58 - mmengine - INFO - Epoch(val) [900][460/500] eta: 0:00:01 time: 0.0481 data_time: 0.0033 memory: 1008 2022/11/02 22:29:58 - mmengine - INFO - Epoch(val) [900][465/500] eta: 0:00:01 time: 0.0443 data_time: 0.0032 memory: 1008 2022/11/02 22:29:58 - mmengine - INFO - Epoch(val) [900][470/500] eta: 0:00:01 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/02 22:29:59 - mmengine - INFO - Epoch(val) [900][475/500] eta: 0:00:01 time: 0.0403 data_time: 0.0035 memory: 1008 2022/11/02 22:29:59 - mmengine - INFO - Epoch(val) [900][480/500] eta: 0:00:00 time: 0.0405 data_time: 0.0034 memory: 1008 2022/11/02 22:29:59 - mmengine - INFO - Epoch(val) [900][485/500] eta: 0:00:00 time: 0.0408 data_time: 0.0025 memory: 1008 2022/11/02 22:29:59 - mmengine - INFO - Epoch(val) [900][490/500] eta: 0:00:00 time: 0.0416 data_time: 0.0027 memory: 1008 2022/11/02 22:30:00 - mmengine - INFO - Epoch(val) [900][495/500] eta: 0:00:00 time: 0.0442 data_time: 0.0028 memory: 1008 2022/11/02 22:30:00 - mmengine - INFO - Epoch(val) [900][500/500] eta: 0:00:00 time: 0.0459 data_time: 0.0042 memory: 1008 2022/11/02 22:30:00 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8233, precision: 0.7724, hmean: 0.7970 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8233, precision: 0.8155, hmean: 0.8194 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8228, precision: 0.8369, hmean: 0.8298 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8199, precision: 0.8571, hmean: 0.8381 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8093, precision: 0.8880, hmean: 0.8469 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7058, precision: 0.9238, hmean: 0.8002 2022/11/02 22:30:00 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1632, precision: 0.9631, hmean: 0.2791 2022/11/02 22:30:00 - mmengine - INFO - Epoch(val) [900][500/500] icdar/precision: 0.8880 icdar/recall: 0.8093 icdar/hmean: 0.8469 2022/11/02 22:30:10 - mmengine - INFO - Epoch(train) [901][5/63] lr: 6.1985e-04 eta: 0:00:00 time: 1.7067 data_time: 0.2725 memory: 14901 loss: 0.9088 loss_prob: 0.4842 loss_thr: 0.3422 loss_db: 0.0824 2022/11/02 22:30:16 - mmengine - INFO - Epoch(train) [901][10/63] lr: 6.1985e-04 eta: 3:14:42 time: 1.5907 data_time: 0.2698 memory: 14901 loss: 0.9150 loss_prob: 0.4877 loss_thr: 0.3419 loss_db: 0.0854 2022/11/02 22:30:23 - mmengine - INFO - Epoch(train) [901][15/63] lr: 6.1985e-04 eta: 3:14:42 time: 1.3669 data_time: 0.0066 memory: 14901 loss: 0.9069 loss_prob: 0.4628 loss_thr: 0.3621 loss_db: 0.0820 2022/11/02 22:30:32 - mmengine - INFO - Epoch(train) [901][20/63] lr: 6.1985e-04 eta: 3:14:40 time: 1.6681 data_time: 0.0183 memory: 14901 loss: 0.9656 loss_prob: 0.4941 loss_thr: 0.3845 loss_db: 0.0869 2022/11/02 22:30:40 - mmengine - INFO - Epoch(train) [901][25/63] lr: 6.1985e-04 eta: 3:14:40 time: 1.6719 data_time: 0.0332 memory: 14901 loss: 0.9944 loss_prob: 0.5248 loss_thr: 0.3771 loss_db: 0.0925 2022/11/02 22:30:44 - mmengine - INFO - Epoch(train) [901][30/63] lr: 6.1985e-04 eta: 3:14:35 time: 1.1678 data_time: 0.0425 memory: 14901 loss: 1.0032 loss_prob: 0.5301 loss_thr: 0.3808 loss_db: 0.0924 2022/11/02 22:30:53 - mmengine - INFO - Epoch(train) [901][35/63] lr: 6.1985e-04 eta: 3:14:35 time: 1.2796 data_time: 0.0300 memory: 14901 loss: 1.0310 loss_prob: 0.5337 loss_thr: 0.4042 loss_db: 0.0931 2022/11/02 22:31:00 - mmengine - INFO - Epoch(train) [901][40/63] lr: 6.1985e-04 eta: 3:14:32 time: 1.5896 data_time: 0.0124 memory: 14901 loss: 0.9970 loss_prob: 0.5131 loss_thr: 0.3946 loss_db: 0.0893 2022/11/02 22:31:03 - mmengine - INFO - Epoch(train) [901][45/63] lr: 6.1985e-04 eta: 3:14:32 time: 1.0633 data_time: 0.0238 memory: 14901 loss: 1.0179 loss_prob: 0.5346 loss_thr: 0.3930 loss_db: 0.0903 2022/11/02 22:31:13 - mmengine - INFO - Epoch(train) [901][50/63] lr: 6.1985e-04 eta: 3:14:28 time: 1.2474 data_time: 0.0497 memory: 14901 loss: 1.0306 loss_prob: 0.5444 loss_thr: 0.3934 loss_db: 0.0928 2022/11/02 22:31:21 - mmengine - INFO - Epoch(train) [901][55/63] lr: 6.1985e-04 eta: 3:14:28 time: 1.7184 data_time: 0.0401 memory: 14901 loss: 0.9875 loss_prob: 0.5158 loss_thr: 0.3824 loss_db: 0.0893 2022/11/02 22:31:25 - mmengine - INFO - Epoch(train) [901][60/63] lr: 6.1985e-04 eta: 3:14:24 time: 1.2349 data_time: 0.0113 memory: 14901 loss: 0.9219 loss_prob: 0.4800 loss_thr: 0.3584 loss_db: 0.0834 2022/11/02 22:31:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:31:39 - mmengine - INFO - Epoch(train) [902][5/63] lr: 6.1798e-04 eta: 3:14:24 time: 1.5453 data_time: 0.2889 memory: 14901 loss: 0.8829 loss_prob: 0.4616 loss_thr: 0.3409 loss_db: 0.0804 2022/11/02 22:31:45 - mmengine - INFO - Epoch(train) [902][10/63] lr: 6.1798e-04 eta: 3:14:19 time: 1.6355 data_time: 0.2874 memory: 14901 loss: 1.0809 loss_prob: 0.5680 loss_thr: 0.4152 loss_db: 0.0977 2022/11/02 22:31:52 - mmengine - INFO - Epoch(train) [902][15/63] lr: 6.1798e-04 eta: 3:14:19 time: 1.3843 data_time: 0.0113 memory: 14901 loss: 1.1262 loss_prob: 0.5921 loss_thr: 0.4337 loss_db: 0.1004 2022/11/02 22:31:58 - mmengine - INFO - Epoch(train) [902][20/63] lr: 6.1798e-04 eta: 3:14:15 time: 1.2734 data_time: 0.0117 memory: 14901 loss: 0.9594 loss_prob: 0.4981 loss_thr: 0.3755 loss_db: 0.0857 2022/11/02 22:32:04 - mmengine - INFO - Epoch(train) [902][25/63] lr: 6.1798e-04 eta: 3:14:15 time: 1.1392 data_time: 0.0363 memory: 14901 loss: 0.9142 loss_prob: 0.4703 loss_thr: 0.3612 loss_db: 0.0827 2022/11/02 22:32:09 - mmengine - INFO - Epoch(train) [902][30/63] lr: 6.1798e-04 eta: 3:14:10 time: 1.1481 data_time: 0.0565 memory: 14901 loss: 0.9819 loss_prob: 0.5143 loss_thr: 0.3796 loss_db: 0.0880 2022/11/02 22:32:16 - mmengine - INFO - Epoch(train) [902][35/63] lr: 6.1798e-04 eta: 3:14:10 time: 1.1910 data_time: 0.0307 memory: 14901 loss: 0.9637 loss_prob: 0.5068 loss_thr: 0.3712 loss_db: 0.0857 2022/11/02 22:32:21 - mmengine - INFO - Epoch(train) [902][40/63] lr: 6.1798e-04 eta: 3:14:06 time: 1.1488 data_time: 0.0114 memory: 14901 loss: 0.9489 loss_prob: 0.4992 loss_thr: 0.3626 loss_db: 0.0871 2022/11/02 22:32:28 - mmengine - INFO - Epoch(train) [902][45/63] lr: 6.1798e-04 eta: 3:14:06 time: 1.2177 data_time: 0.0143 memory: 14901 loss: 0.9521 loss_prob: 0.4961 loss_thr: 0.3701 loss_db: 0.0859 2022/11/02 22:32:33 - mmengine - INFO - Epoch(train) [902][50/63] lr: 6.1798e-04 eta: 3:14:02 time: 1.2463 data_time: 0.0299 memory: 14901 loss: 0.9363 loss_prob: 0.4844 loss_thr: 0.3692 loss_db: 0.0827 2022/11/02 22:32:41 - mmengine - INFO - Epoch(train) [902][55/63] lr: 6.1798e-04 eta: 3:14:02 time: 1.3489 data_time: 0.0289 memory: 14901 loss: 0.9720 loss_prob: 0.5125 loss_thr: 0.3697 loss_db: 0.0898 2022/11/02 22:32:46 - mmengine - INFO - Epoch(train) [902][60/63] lr: 6.1798e-04 eta: 3:13:58 time: 1.3207 data_time: 0.0117 memory: 14901 loss: 1.0216 loss_prob: 0.5439 loss_thr: 0.3823 loss_db: 0.0955 2022/11/02 22:32:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:33:01 - mmengine - INFO - Epoch(train) [903][5/63] lr: 6.1611e-04 eta: 3:13:58 time: 1.7908 data_time: 0.2879 memory: 14901 loss: 1.0257 loss_prob: 0.5439 loss_thr: 0.3853 loss_db: 0.0965 2022/11/02 22:33:07 - mmengine - INFO - Epoch(train) [903][10/63] lr: 6.1611e-04 eta: 3:13:53 time: 1.7197 data_time: 0.2859 memory: 14901 loss: 1.0441 loss_prob: 0.5531 loss_thr: 0.3955 loss_db: 0.0954 2022/11/02 22:33:17 - mmengine - INFO - Epoch(train) [903][15/63] lr: 6.1611e-04 eta: 3:13:53 time: 1.6460 data_time: 0.0105 memory: 14901 loss: 0.9858 loss_prob: 0.5168 loss_thr: 0.3784 loss_db: 0.0905 2022/11/02 22:33:23 - mmengine - INFO - Epoch(train) [903][20/63] lr: 6.1611e-04 eta: 3:13:50 time: 1.5920 data_time: 0.0129 memory: 14901 loss: 0.9906 loss_prob: 0.5266 loss_thr: 0.3739 loss_db: 0.0902 2022/11/02 22:33:31 - mmengine - INFO - Epoch(train) [903][25/63] lr: 6.1611e-04 eta: 3:13:50 time: 1.3259 data_time: 0.0484 memory: 14901 loss: 1.0726 loss_prob: 0.5839 loss_thr: 0.3889 loss_db: 0.0999 2022/11/02 22:33:37 - mmengine - INFO - Epoch(train) [903][30/63] lr: 6.1611e-04 eta: 3:13:46 time: 1.3656 data_time: 0.0630 memory: 14901 loss: 1.1631 loss_prob: 0.6544 loss_thr: 0.3957 loss_db: 0.1130 2022/11/02 22:33:44 - mmengine - INFO - Epoch(train) [903][35/63] lr: 6.1611e-04 eta: 3:13:46 time: 1.3677 data_time: 0.0277 memory: 14901 loss: 1.0736 loss_prob: 0.5918 loss_thr: 0.3821 loss_db: 0.0998 2022/11/02 22:33:49 - mmengine - INFO - Epoch(train) [903][40/63] lr: 6.1611e-04 eta: 3:13:42 time: 1.1636 data_time: 0.0115 memory: 14901 loss: 0.9897 loss_prob: 0.5166 loss_thr: 0.3852 loss_db: 0.0879 2022/11/02 22:33:56 - mmengine - INFO - Epoch(train) [903][45/63] lr: 6.1611e-04 eta: 3:13:42 time: 1.1538 data_time: 0.0096 memory: 14901 loss: 0.9907 loss_prob: 0.5124 loss_thr: 0.3902 loss_db: 0.0881 2022/11/02 22:34:02 - mmengine - INFO - Epoch(train) [903][50/63] lr: 6.1611e-04 eta: 3:13:38 time: 1.3482 data_time: 0.0297 memory: 14901 loss: 0.9800 loss_prob: 0.4973 loss_thr: 0.3969 loss_db: 0.0859 2022/11/02 22:34:08 - mmengine - INFO - Epoch(train) [903][55/63] lr: 6.1611e-04 eta: 3:13:38 time: 1.2568 data_time: 0.0295 memory: 14901 loss: 1.0316 loss_prob: 0.5279 loss_thr: 0.4114 loss_db: 0.0922 2022/11/02 22:34:14 - mmengine - INFO - Epoch(train) [903][60/63] lr: 6.1611e-04 eta: 3:13:34 time: 1.1877 data_time: 0.0143 memory: 14901 loss: 1.0502 loss_prob: 0.5407 loss_thr: 0.4170 loss_db: 0.0926 2022/11/02 22:34:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:34:27 - mmengine - INFO - Epoch(train) [904][5/63] lr: 6.1425e-04 eta: 3:13:34 time: 1.5152 data_time: 0.2666 memory: 14901 loss: 0.9950 loss_prob: 0.5110 loss_thr: 0.3935 loss_db: 0.0905 2022/11/02 22:34:34 - mmengine - INFO - Epoch(train) [904][10/63] lr: 6.1425e-04 eta: 3:13:28 time: 1.5237 data_time: 0.2717 memory: 14901 loss: 0.8878 loss_prob: 0.4525 loss_thr: 0.3553 loss_db: 0.0800 2022/11/02 22:34:41 - mmengine - INFO - Epoch(train) [904][15/63] lr: 6.1425e-04 eta: 3:13:28 time: 1.3633 data_time: 0.0238 memory: 14901 loss: 0.8921 loss_prob: 0.4574 loss_thr: 0.3554 loss_db: 0.0794 2022/11/02 22:34:46 - mmengine - INFO - Epoch(train) [904][20/63] lr: 6.1425e-04 eta: 3:13:24 time: 1.2075 data_time: 0.0217 memory: 14901 loss: 0.8959 loss_prob: 0.4608 loss_thr: 0.3548 loss_db: 0.0803 2022/11/02 22:34:53 - mmengine - INFO - Epoch(train) [904][25/63] lr: 6.1425e-04 eta: 3:13:24 time: 1.2247 data_time: 0.0319 memory: 14901 loss: 1.0011 loss_prob: 0.5308 loss_thr: 0.3791 loss_db: 0.0912 2022/11/02 22:35:01 - mmengine - INFO - Epoch(train) [904][30/63] lr: 6.1425e-04 eta: 3:13:20 time: 1.4797 data_time: 0.0335 memory: 14901 loss: 0.9853 loss_prob: 0.5135 loss_thr: 0.3839 loss_db: 0.0878 2022/11/02 22:35:06 - mmengine - INFO - Epoch(train) [904][35/63] lr: 6.1425e-04 eta: 3:13:20 time: 1.2681 data_time: 0.0216 memory: 14901 loss: 0.8574 loss_prob: 0.4353 loss_thr: 0.3449 loss_db: 0.0773 2022/11/02 22:35:12 - mmengine - INFO - Epoch(train) [904][40/63] lr: 6.1425e-04 eta: 3:13:15 time: 1.0565 data_time: 0.0189 memory: 14901 loss: 0.8802 loss_prob: 0.4555 loss_thr: 0.3432 loss_db: 0.0816 2022/11/02 22:35:18 - mmengine - INFO - Epoch(train) [904][45/63] lr: 6.1425e-04 eta: 3:13:15 time: 1.2108 data_time: 0.0166 memory: 14901 loss: 0.9091 loss_prob: 0.4690 loss_thr: 0.3582 loss_db: 0.0819 2022/11/02 22:35:22 - mmengine - INFO - Epoch(train) [904][50/63] lr: 6.1425e-04 eta: 3:13:11 time: 1.0382 data_time: 0.0250 memory: 14901 loss: 0.9059 loss_prob: 0.4640 loss_thr: 0.3632 loss_db: 0.0787 2022/11/02 22:35:30 - mmengine - INFO - Epoch(train) [904][55/63] lr: 6.1425e-04 eta: 3:13:11 time: 1.2366 data_time: 0.0248 memory: 14901 loss: 1.0290 loss_prob: 0.5341 loss_thr: 0.4033 loss_db: 0.0917 2022/11/02 22:35:36 - mmengine - INFO - Epoch(train) [904][60/63] lr: 6.1425e-04 eta: 3:13:07 time: 1.4507 data_time: 0.0197 memory: 14901 loss: 1.1565 loss_prob: 0.6180 loss_thr: 0.4337 loss_db: 0.1048 2022/11/02 22:35:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:35:48 - mmengine - INFO - Epoch(train) [905][5/63] lr: 6.1238e-04 eta: 3:13:07 time: 1.5197 data_time: 0.2136 memory: 14901 loss: 1.1553 loss_prob: 0.6181 loss_thr: 0.4300 loss_db: 0.1072 2022/11/02 22:35:56 - mmengine - INFO - Epoch(train) [905][10/63] lr: 6.1238e-04 eta: 3:13:01 time: 1.5328 data_time: 0.2298 memory: 14901 loss: 1.0554 loss_prob: 0.5595 loss_thr: 0.3991 loss_db: 0.0967 2022/11/02 22:36:02 - mmengine - INFO - Epoch(train) [905][15/63] lr: 6.1238e-04 eta: 3:13:01 time: 1.3826 data_time: 0.0326 memory: 14901 loss: 1.0092 loss_prob: 0.5251 loss_thr: 0.3932 loss_db: 0.0909 2022/11/02 22:36:07 - mmengine - INFO - Epoch(train) [905][20/63] lr: 6.1238e-04 eta: 3:12:57 time: 1.1092 data_time: 0.0117 memory: 14901 loss: 1.0536 loss_prob: 0.5505 loss_thr: 0.4096 loss_db: 0.0935 2022/11/02 22:36:14 - mmengine - INFO - Epoch(train) [905][25/63] lr: 6.1238e-04 eta: 3:12:57 time: 1.2088 data_time: 0.0170 memory: 14901 loss: 0.9584 loss_prob: 0.5021 loss_thr: 0.3695 loss_db: 0.0868 2022/11/02 22:36:21 - mmengine - INFO - Epoch(train) [905][30/63] lr: 6.1238e-04 eta: 3:12:53 time: 1.4311 data_time: 0.0454 memory: 14901 loss: 0.9136 loss_prob: 0.4752 loss_thr: 0.3541 loss_db: 0.0843 2022/11/02 22:36:28 - mmengine - INFO - Epoch(train) [905][35/63] lr: 6.1238e-04 eta: 3:12:53 time: 1.3693 data_time: 0.0407 memory: 14901 loss: 0.9544 loss_prob: 0.4927 loss_thr: 0.3749 loss_db: 0.0869 2022/11/02 22:36:35 - mmengine - INFO - Epoch(train) [905][40/63] lr: 6.1238e-04 eta: 3:12:50 time: 1.3976 data_time: 0.0177 memory: 14901 loss: 0.9378 loss_prob: 0.4795 loss_thr: 0.3748 loss_db: 0.0835 2022/11/02 22:36:41 - mmengine - INFO - Epoch(train) [905][45/63] lr: 6.1238e-04 eta: 3:12:50 time: 1.3096 data_time: 0.0140 memory: 14901 loss: 0.9891 loss_prob: 0.5200 loss_thr: 0.3810 loss_db: 0.0880 2022/11/02 22:36:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:36:48 - mmengine - INFO - Epoch(train) [905][50/63] lr: 6.1238e-04 eta: 3:12:46 time: 1.3350 data_time: 0.0227 memory: 14901 loss: 0.9931 loss_prob: 0.5203 loss_thr: 0.3826 loss_db: 0.0901 2022/11/02 22:36:55 - mmengine - INFO - Epoch(train) [905][55/63] lr: 6.1238e-04 eta: 3:12:46 time: 1.4504 data_time: 0.0447 memory: 14901 loss: 0.9421 loss_prob: 0.4854 loss_thr: 0.3700 loss_db: 0.0867 2022/11/02 22:37:04 - mmengine - INFO - Epoch(train) [905][60/63] lr: 6.1238e-04 eta: 3:12:42 time: 1.5066 data_time: 0.0315 memory: 14901 loss: 0.9519 loss_prob: 0.4959 loss_thr: 0.3696 loss_db: 0.0864 2022/11/02 22:37:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:37:17 - mmengine - INFO - Epoch(train) [906][5/63] lr: 6.1051e-04 eta: 3:12:42 time: 1.6138 data_time: 0.2891 memory: 14901 loss: 1.0624 loss_prob: 0.5536 loss_thr: 0.4133 loss_db: 0.0955 2022/11/02 22:37:22 - mmengine - INFO - Epoch(train) [906][10/63] lr: 6.1051e-04 eta: 3:12:37 time: 1.5376 data_time: 0.2910 memory: 14901 loss: 1.0489 loss_prob: 0.5445 loss_thr: 0.4076 loss_db: 0.0968 2022/11/02 22:37:30 - mmengine - INFO - Epoch(train) [906][15/63] lr: 6.1051e-04 eta: 3:12:37 time: 1.2686 data_time: 0.0167 memory: 14901 loss: 0.9876 loss_prob: 0.5094 loss_thr: 0.3874 loss_db: 0.0909 2022/11/02 22:37:35 - mmengine - INFO - Epoch(train) [906][20/63] lr: 6.1051e-04 eta: 3:12:33 time: 1.3547 data_time: 0.0142 memory: 14901 loss: 0.9718 loss_prob: 0.5078 loss_thr: 0.3753 loss_db: 0.0887 2022/11/02 22:37:41 - mmengine - INFO - Epoch(train) [906][25/63] lr: 6.1051e-04 eta: 3:12:33 time: 1.0553 data_time: 0.0469 memory: 14901 loss: 1.0005 loss_prob: 0.5227 loss_thr: 0.3877 loss_db: 0.0901 2022/11/02 22:37:46 - mmengine - INFO - Epoch(train) [906][30/63] lr: 6.1051e-04 eta: 3:12:28 time: 1.1167 data_time: 0.0573 memory: 14901 loss: 0.9984 loss_prob: 0.5115 loss_thr: 0.3989 loss_db: 0.0880 2022/11/02 22:37:53 - mmengine - INFO - Epoch(train) [906][35/63] lr: 6.1051e-04 eta: 3:12:28 time: 1.2479 data_time: 0.0248 memory: 14901 loss: 0.9803 loss_prob: 0.5014 loss_thr: 0.3924 loss_db: 0.0866 2022/11/02 22:38:02 - mmengine - INFO - Epoch(train) [906][40/63] lr: 6.1051e-04 eta: 3:12:25 time: 1.5883 data_time: 0.0136 memory: 14901 loss: 0.9653 loss_prob: 0.4943 loss_thr: 0.3844 loss_db: 0.0866 2022/11/02 22:38:07 - mmengine - INFO - Epoch(train) [906][45/63] lr: 6.1051e-04 eta: 3:12:25 time: 1.3803 data_time: 0.0132 memory: 14901 loss: 0.9228 loss_prob: 0.4776 loss_thr: 0.3610 loss_db: 0.0842 2022/11/02 22:38:12 - mmengine - INFO - Epoch(train) [906][50/63] lr: 6.1051e-04 eta: 3:12:20 time: 0.9966 data_time: 0.0353 memory: 14901 loss: 0.9943 loss_prob: 0.5255 loss_thr: 0.3791 loss_db: 0.0897 2022/11/02 22:38:17 - mmengine - INFO - Epoch(train) [906][55/63] lr: 6.1051e-04 eta: 3:12:20 time: 1.0586 data_time: 0.0323 memory: 14901 loss: 1.0122 loss_prob: 0.5355 loss_thr: 0.3843 loss_db: 0.0924 2022/11/02 22:38:25 - mmengine - INFO - Epoch(train) [906][60/63] lr: 6.1051e-04 eta: 3:12:16 time: 1.2787 data_time: 0.0152 memory: 14901 loss: 0.9005 loss_prob: 0.4692 loss_thr: 0.3489 loss_db: 0.0824 2022/11/02 22:38:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:38:37 - mmengine - INFO - Epoch(train) [907][5/63] lr: 6.0864e-04 eta: 3:12:16 time: 1.5309 data_time: 0.2774 memory: 14901 loss: 0.9709 loss_prob: 0.4701 loss_thr: 0.4187 loss_db: 0.0820 2022/11/02 22:38:42 - mmengine - INFO - Epoch(train) [907][10/63] lr: 6.0864e-04 eta: 3:12:10 time: 1.4721 data_time: 0.2789 memory: 14901 loss: 0.9472 loss_prob: 0.4862 loss_thr: 0.3738 loss_db: 0.0873 2022/11/02 22:38:48 - mmengine - INFO - Epoch(train) [907][15/63] lr: 6.0864e-04 eta: 3:12:10 time: 1.1218 data_time: 0.0181 memory: 14901 loss: 0.9925 loss_prob: 0.5131 loss_thr: 0.3901 loss_db: 0.0892 2022/11/02 22:38:54 - mmengine - INFO - Epoch(train) [907][20/63] lr: 6.0864e-04 eta: 3:12:06 time: 1.2515 data_time: 0.0127 memory: 14901 loss: 1.0514 loss_prob: 0.5472 loss_thr: 0.4123 loss_db: 0.0919 2022/11/02 22:39:01 - mmengine - INFO - Epoch(train) [907][25/63] lr: 6.0864e-04 eta: 3:12:06 time: 1.3504 data_time: 0.0248 memory: 14901 loss: 0.9376 loss_prob: 0.4720 loss_thr: 0.3840 loss_db: 0.0816 2022/11/02 22:39:07 - mmengine - INFO - Epoch(train) [907][30/63] lr: 6.0864e-04 eta: 3:12:02 time: 1.3365 data_time: 0.0638 memory: 14901 loss: 0.8778 loss_prob: 0.4407 loss_thr: 0.3594 loss_db: 0.0777 2022/11/02 22:39:13 - mmengine - INFO - Epoch(train) [907][35/63] lr: 6.0864e-04 eta: 3:12:02 time: 1.2134 data_time: 0.0550 memory: 14901 loss: 1.1699 loss_prob: 0.6596 loss_thr: 0.4111 loss_db: 0.0992 2022/11/02 22:39:20 - mmengine - INFO - Epoch(train) [907][40/63] lr: 6.0864e-04 eta: 3:11:58 time: 1.2224 data_time: 0.0144 memory: 14901 loss: 1.1848 loss_prob: 0.6698 loss_thr: 0.4127 loss_db: 0.1024 2022/11/02 22:39:25 - mmengine - INFO - Epoch(train) [907][45/63] lr: 6.0864e-04 eta: 3:11:58 time: 1.1571 data_time: 0.0113 memory: 14901 loss: 0.9950 loss_prob: 0.5280 loss_thr: 0.3762 loss_db: 0.0908 2022/11/02 22:39:32 - mmengine - INFO - Epoch(train) [907][50/63] lr: 6.0864e-04 eta: 3:11:53 time: 1.1798 data_time: 0.0276 memory: 14901 loss: 1.0391 loss_prob: 0.5530 loss_thr: 0.3936 loss_db: 0.0925 2022/11/02 22:39:37 - mmengine - INFO - Epoch(train) [907][55/63] lr: 6.0864e-04 eta: 3:11:53 time: 1.1843 data_time: 0.0313 memory: 14901 loss: 1.0443 loss_prob: 0.5541 loss_thr: 0.3954 loss_db: 0.0948 2022/11/02 22:39:43 - mmengine - INFO - Epoch(train) [907][60/63] lr: 6.0864e-04 eta: 3:11:49 time: 1.1175 data_time: 0.0242 memory: 14901 loss: 1.0184 loss_prob: 0.5331 loss_thr: 0.3910 loss_db: 0.0942 2022/11/02 22:39:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:39:57 - mmengine - INFO - Epoch(train) [908][5/63] lr: 6.0677e-04 eta: 3:11:49 time: 1.5131 data_time: 0.3643 memory: 14901 loss: 0.9767 loss_prob: 0.5077 loss_thr: 0.3792 loss_db: 0.0899 2022/11/02 22:40:01 - mmengine - INFO - Epoch(train) [908][10/63] lr: 6.0677e-04 eta: 3:11:43 time: 1.6130 data_time: 0.3600 memory: 14901 loss: 1.0268 loss_prob: 0.5376 loss_thr: 0.3954 loss_db: 0.0938 2022/11/02 22:40:07 - mmengine - INFO - Epoch(train) [908][15/63] lr: 6.0677e-04 eta: 3:11:43 time: 1.0205 data_time: 0.0084 memory: 14901 loss: 0.9731 loss_prob: 0.5095 loss_thr: 0.3753 loss_db: 0.0883 2022/11/02 22:40:13 - mmengine - INFO - Epoch(train) [908][20/63] lr: 6.0677e-04 eta: 3:11:39 time: 1.1916 data_time: 0.0112 memory: 14901 loss: 0.9017 loss_prob: 0.4719 loss_thr: 0.3485 loss_db: 0.0813 2022/11/02 22:40:22 - mmengine - INFO - Epoch(train) [908][25/63] lr: 6.0677e-04 eta: 3:11:39 time: 1.4795 data_time: 0.0580 memory: 14901 loss: 0.9820 loss_prob: 0.5153 loss_thr: 0.3765 loss_db: 0.0902 2022/11/02 22:40:26 - mmengine - INFO - Epoch(train) [908][30/63] lr: 6.0677e-04 eta: 3:11:35 time: 1.3442 data_time: 0.0573 memory: 14901 loss: 1.0077 loss_prob: 0.5312 loss_thr: 0.3834 loss_db: 0.0931 2022/11/02 22:40:32 - mmengine - INFO - Epoch(train) [908][35/63] lr: 6.0677e-04 eta: 3:11:35 time: 1.0638 data_time: 0.0102 memory: 14901 loss: 0.9905 loss_prob: 0.5210 loss_thr: 0.3799 loss_db: 0.0896 2022/11/02 22:40:40 - mmengine - INFO - Epoch(train) [908][40/63] lr: 6.0677e-04 eta: 3:11:31 time: 1.4263 data_time: 0.0113 memory: 14901 loss: 0.9936 loss_prob: 0.5191 loss_thr: 0.3842 loss_db: 0.0903 2022/11/02 22:40:43 - mmengine - INFO - Epoch(train) [908][45/63] lr: 6.0677e-04 eta: 3:11:31 time: 1.0934 data_time: 0.0141 memory: 14901 loss: 0.9563 loss_prob: 0.4996 loss_thr: 0.3679 loss_db: 0.0888 2022/11/02 22:40:51 - mmengine - INFO - Epoch(train) [908][50/63] lr: 6.0677e-04 eta: 3:11:26 time: 1.0597 data_time: 0.0340 memory: 14901 loss: 0.9430 loss_prob: 0.4947 loss_thr: 0.3628 loss_db: 0.0854 2022/11/02 22:40:56 - mmengine - INFO - Epoch(train) [908][55/63] lr: 6.0677e-04 eta: 3:11:26 time: 1.3091 data_time: 0.0305 memory: 14901 loss: 0.9304 loss_prob: 0.4851 loss_thr: 0.3623 loss_db: 0.0830 2022/11/02 22:41:02 - mmengine - INFO - Epoch(train) [908][60/63] lr: 6.0677e-04 eta: 3:11:21 time: 1.1006 data_time: 0.0100 memory: 14901 loss: 0.9395 loss_prob: 0.4781 loss_thr: 0.3757 loss_db: 0.0856 2022/11/02 22:41:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:41:15 - mmengine - INFO - Epoch(train) [909][5/63] lr: 6.0490e-04 eta: 3:11:21 time: 1.4393 data_time: 0.3030 memory: 14901 loss: 0.9485 loss_prob: 0.4908 loss_thr: 0.3713 loss_db: 0.0865 2022/11/02 22:41:22 - mmengine - INFO - Epoch(train) [909][10/63] lr: 6.0490e-04 eta: 3:11:16 time: 1.6135 data_time: 0.3070 memory: 14901 loss: 0.9316 loss_prob: 0.4867 loss_thr: 0.3604 loss_db: 0.0844 2022/11/02 22:41:29 - mmengine - INFO - Epoch(train) [909][15/63] lr: 6.0490e-04 eta: 3:11:16 time: 1.3661 data_time: 0.0116 memory: 14901 loss: 0.9457 loss_prob: 0.4940 loss_thr: 0.3669 loss_db: 0.0847 2022/11/02 22:41:36 - mmengine - INFO - Epoch(train) [909][20/63] lr: 6.0490e-04 eta: 3:11:12 time: 1.4471 data_time: 0.0100 memory: 14901 loss: 0.9642 loss_prob: 0.4971 loss_thr: 0.3811 loss_db: 0.0860 2022/11/02 22:41:41 - mmengine - INFO - Epoch(train) [909][25/63] lr: 6.0490e-04 eta: 3:11:12 time: 1.2511 data_time: 0.0210 memory: 14901 loss: 0.9254 loss_prob: 0.4785 loss_thr: 0.3623 loss_db: 0.0846 2022/11/02 22:41:46 - mmengine - INFO - Epoch(train) [909][30/63] lr: 6.0490e-04 eta: 3:11:07 time: 1.0069 data_time: 0.0530 memory: 14901 loss: 0.8983 loss_prob: 0.4583 loss_thr: 0.3590 loss_db: 0.0810 2022/11/02 22:41:50 - mmengine - INFO - Epoch(train) [909][35/63] lr: 6.0490e-04 eta: 3:11:07 time: 0.8420 data_time: 0.0431 memory: 14901 loss: 0.8715 loss_prob: 0.4441 loss_thr: 0.3497 loss_db: 0.0777 2022/11/02 22:41:55 - mmengine - INFO - Epoch(train) [909][40/63] lr: 6.0490e-04 eta: 3:11:02 time: 0.9043 data_time: 0.0118 memory: 14901 loss: 0.9147 loss_prob: 0.4713 loss_thr: 0.3601 loss_db: 0.0833 2022/11/02 22:42:02 - mmengine - INFO - Epoch(train) [909][45/63] lr: 6.0490e-04 eta: 3:11:02 time: 1.1991 data_time: 0.0125 memory: 14901 loss: 0.9324 loss_prob: 0.4747 loss_thr: 0.3745 loss_db: 0.0833 2022/11/02 22:42:07 - mmengine - INFO - Epoch(train) [909][50/63] lr: 6.0490e-04 eta: 3:10:57 time: 1.1605 data_time: 0.0319 memory: 14901 loss: 0.9116 loss_prob: 0.4619 loss_thr: 0.3692 loss_db: 0.0806 2022/11/02 22:42:15 - mmengine - INFO - Epoch(train) [909][55/63] lr: 6.0490e-04 eta: 3:10:57 time: 1.2792 data_time: 0.0325 memory: 14901 loss: 0.9616 loss_prob: 0.4935 loss_thr: 0.3819 loss_db: 0.0862 2022/11/02 22:42:21 - mmengine - INFO - Epoch(train) [909][60/63] lr: 6.0490e-04 eta: 3:10:54 time: 1.3781 data_time: 0.0126 memory: 14901 loss: 0.8909 loss_prob: 0.4473 loss_thr: 0.3650 loss_db: 0.0786 2022/11/02 22:42:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:42:33 - mmengine - INFO - Epoch(train) [910][5/63] lr: 6.0303e-04 eta: 3:10:54 time: 1.5836 data_time: 0.2559 memory: 14901 loss: 0.9305 loss_prob: 0.4732 loss_thr: 0.3726 loss_db: 0.0848 2022/11/02 22:42:42 - mmengine - INFO - Epoch(train) [910][10/63] lr: 6.0303e-04 eta: 3:10:49 time: 1.7941 data_time: 0.2502 memory: 14901 loss: 1.0089 loss_prob: 0.5206 loss_thr: 0.3982 loss_db: 0.0902 2022/11/02 22:42:51 - mmengine - INFO - Epoch(train) [910][15/63] lr: 6.0303e-04 eta: 3:10:49 time: 1.7271 data_time: 0.0089 memory: 14901 loss: 0.9217 loss_prob: 0.4667 loss_thr: 0.3757 loss_db: 0.0792 2022/11/02 22:42:58 - mmengine - INFO - Epoch(train) [910][20/63] lr: 6.0303e-04 eta: 3:10:46 time: 1.6835 data_time: 0.0106 memory: 14901 loss: 0.8222 loss_prob: 0.4086 loss_thr: 0.3422 loss_db: 0.0714 2022/11/02 22:43:05 - mmengine - INFO - Epoch(train) [910][25/63] lr: 6.0303e-04 eta: 3:10:46 time: 1.4814 data_time: 0.0175 memory: 14901 loss: 0.8493 loss_prob: 0.4255 loss_thr: 0.3488 loss_db: 0.0750 2022/11/02 22:43:11 - mmengine - INFO - Epoch(train) [910][30/63] lr: 6.0303e-04 eta: 3:10:42 time: 1.3072 data_time: 0.0557 memory: 14901 loss: 0.9270 loss_prob: 0.4733 loss_thr: 0.3706 loss_db: 0.0831 2022/11/02 22:43:17 - mmengine - INFO - Epoch(train) [910][35/63] lr: 6.0303e-04 eta: 3:10:42 time: 1.1705 data_time: 0.0492 memory: 14901 loss: 0.9203 loss_prob: 0.4728 loss_thr: 0.3654 loss_db: 0.0821 2022/11/02 22:43:23 - mmengine - INFO - Epoch(train) [910][40/63] lr: 6.0303e-04 eta: 3:10:37 time: 1.1917 data_time: 0.0101 memory: 14901 loss: 0.9070 loss_prob: 0.4713 loss_thr: 0.3555 loss_db: 0.0802 2022/11/02 22:43:30 - mmengine - INFO - Epoch(train) [910][45/63] lr: 6.0303e-04 eta: 3:10:37 time: 1.2642 data_time: 0.0087 memory: 14901 loss: 1.0132 loss_prob: 0.5363 loss_thr: 0.3838 loss_db: 0.0931 2022/11/02 22:43:36 - mmengine - INFO - Epoch(train) [910][50/63] lr: 6.0303e-04 eta: 3:10:33 time: 1.3076 data_time: 0.0179 memory: 14901 loss: 1.0295 loss_prob: 0.5397 loss_thr: 0.3942 loss_db: 0.0956 2022/11/02 22:43:43 - mmengine - INFO - Epoch(train) [910][55/63] lr: 6.0303e-04 eta: 3:10:33 time: 1.3155 data_time: 0.0360 memory: 14901 loss: 0.9669 loss_prob: 0.4978 loss_thr: 0.3821 loss_db: 0.0870 2022/11/02 22:43:49 - mmengine - INFO - Epoch(train) [910][60/63] lr: 6.0303e-04 eta: 3:10:29 time: 1.2753 data_time: 0.0244 memory: 14901 loss: 0.9672 loss_prob: 0.4989 loss_thr: 0.3827 loss_db: 0.0856 2022/11/02 22:43:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:44:01 - mmengine - INFO - Epoch(train) [911][5/63] lr: 6.0116e-04 eta: 3:10:29 time: 1.2953 data_time: 0.3128 memory: 14901 loss: 0.9622 loss_prob: 0.4996 loss_thr: 0.3752 loss_db: 0.0874 2022/11/02 22:44:07 - mmengine - INFO - Epoch(train) [911][10/63] lr: 6.0116e-04 eta: 3:10:23 time: 1.4741 data_time: 0.3099 memory: 14901 loss: 1.0195 loss_prob: 0.5365 loss_thr: 0.3922 loss_db: 0.0909 2022/11/02 22:44:12 - mmengine - INFO - Epoch(train) [911][15/63] lr: 6.0116e-04 eta: 3:10:23 time: 1.0423 data_time: 0.0107 memory: 14901 loss: 0.9927 loss_prob: 0.5262 loss_thr: 0.3773 loss_db: 0.0891 2022/11/02 22:44:18 - mmengine - INFO - Epoch(train) [911][20/63] lr: 6.0116e-04 eta: 3:10:18 time: 1.0878 data_time: 0.0106 memory: 14901 loss: 0.9541 loss_prob: 0.5029 loss_thr: 0.3632 loss_db: 0.0880 2022/11/02 22:44:27 - mmengine - INFO - Epoch(train) [911][25/63] lr: 6.0116e-04 eta: 3:10:18 time: 1.5237 data_time: 0.0181 memory: 14901 loss: 0.9977 loss_prob: 0.5325 loss_thr: 0.3717 loss_db: 0.0935 2022/11/02 22:44:32 - mmengine - INFO - Epoch(train) [911][30/63] lr: 6.0116e-04 eta: 3:10:15 time: 1.4523 data_time: 0.0603 memory: 14901 loss: 1.0521 loss_prob: 0.5602 loss_thr: 0.3944 loss_db: 0.0975 2022/11/02 22:44:38 - mmengine - INFO - Epoch(train) [911][35/63] lr: 6.0116e-04 eta: 3:10:15 time: 1.1152 data_time: 0.0519 memory: 14901 loss: 0.9778 loss_prob: 0.5155 loss_thr: 0.3725 loss_db: 0.0899 2022/11/02 22:44:44 - mmengine - INFO - Epoch(train) [911][40/63] lr: 6.0116e-04 eta: 3:10:10 time: 1.1941 data_time: 0.0118 memory: 14901 loss: 0.9354 loss_prob: 0.4876 loss_thr: 0.3620 loss_db: 0.0857 2022/11/02 22:44:50 - mmengine - INFO - Epoch(train) [911][45/63] lr: 6.0116e-04 eta: 3:10:10 time: 1.2179 data_time: 0.0114 memory: 14901 loss: 1.0081 loss_prob: 0.5298 loss_thr: 0.3859 loss_db: 0.0924 2022/11/02 22:44:57 - mmengine - INFO - Epoch(train) [911][50/63] lr: 6.0116e-04 eta: 3:10:06 time: 1.2795 data_time: 0.0358 memory: 14901 loss: 0.9809 loss_prob: 0.5105 loss_thr: 0.3819 loss_db: 0.0885 2022/11/02 22:45:05 - mmengine - INFO - Epoch(train) [911][55/63] lr: 6.0116e-04 eta: 3:10:06 time: 1.4652 data_time: 0.0356 memory: 14901 loss: 0.9478 loss_prob: 0.4860 loss_thr: 0.3777 loss_db: 0.0841 2022/11/02 22:45:09 - mmengine - INFO - Epoch(train) [911][60/63] lr: 6.0116e-04 eta: 3:10:02 time: 1.2380 data_time: 0.0114 memory: 14901 loss: 0.9396 loss_prob: 0.4857 loss_thr: 0.3695 loss_db: 0.0843 2022/11/02 22:45:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:45:22 - mmengine - INFO - Epoch(train) [912][5/63] lr: 5.9929e-04 eta: 3:10:02 time: 1.5442 data_time: 0.2192 memory: 14901 loss: 1.0163 loss_prob: 0.5454 loss_thr: 0.3790 loss_db: 0.0919 2022/11/02 22:45:27 - mmengine - INFO - Epoch(train) [912][10/63] lr: 5.9929e-04 eta: 3:09:56 time: 1.4966 data_time: 0.2222 memory: 14901 loss: 0.9265 loss_prob: 0.4823 loss_thr: 0.3599 loss_db: 0.0843 2022/11/02 22:45:34 - mmengine - INFO - Epoch(train) [912][15/63] lr: 5.9929e-04 eta: 3:09:56 time: 1.1993 data_time: 0.0157 memory: 14901 loss: 0.9685 loss_prob: 0.5127 loss_thr: 0.3668 loss_db: 0.0890 2022/11/02 22:45:42 - mmengine - INFO - Epoch(train) [912][20/63] lr: 5.9929e-04 eta: 3:09:52 time: 1.4385 data_time: 0.0156 memory: 14901 loss: 0.9592 loss_prob: 0.5046 loss_thr: 0.3676 loss_db: 0.0870 2022/11/02 22:45:45 - mmengine - INFO - Epoch(train) [912][25/63] lr: 5.9929e-04 eta: 3:09:52 time: 1.0255 data_time: 0.0172 memory: 14901 loss: 0.9090 loss_prob: 0.4708 loss_thr: 0.3569 loss_db: 0.0813 2022/11/02 22:45:52 - mmengine - INFO - Epoch(train) [912][30/63] lr: 5.9929e-04 eta: 3:09:47 time: 1.0195 data_time: 0.0588 memory: 14901 loss: 0.9776 loss_prob: 0.5135 loss_thr: 0.3760 loss_db: 0.0882 2022/11/02 22:45:57 - mmengine - INFO - Epoch(train) [912][35/63] lr: 5.9929e-04 eta: 3:09:47 time: 1.2920 data_time: 0.0543 memory: 14901 loss: 1.0070 loss_prob: 0.5206 loss_thr: 0.3971 loss_db: 0.0893 2022/11/02 22:46:04 - mmengine - INFO - Epoch(train) [912][40/63] lr: 5.9929e-04 eta: 3:09:42 time: 1.1848 data_time: 0.0127 memory: 14901 loss: 1.0320 loss_prob: 0.5371 loss_thr: 0.4023 loss_db: 0.0926 2022/11/02 22:46:12 - mmengine - INFO - Epoch(train) [912][45/63] lr: 5.9929e-04 eta: 3:09:42 time: 1.4075 data_time: 0.0136 memory: 14901 loss: 1.0541 loss_prob: 0.5568 loss_thr: 0.4002 loss_db: 0.0971 2022/11/02 22:46:17 - mmengine - INFO - Epoch(train) [912][50/63] lr: 5.9929e-04 eta: 3:09:38 time: 1.3358 data_time: 0.0337 memory: 14901 loss: 1.0107 loss_prob: 0.5365 loss_thr: 0.3814 loss_db: 0.0928 2022/11/02 22:46:23 - mmengine - INFO - Epoch(train) [912][55/63] lr: 5.9929e-04 eta: 3:09:38 time: 1.1472 data_time: 0.0421 memory: 14901 loss: 0.9605 loss_prob: 0.5049 loss_thr: 0.3682 loss_db: 0.0874 2022/11/02 22:46:29 - mmengine - INFO - Epoch(train) [912][60/63] lr: 5.9929e-04 eta: 3:09:34 time: 1.1367 data_time: 0.0226 memory: 14901 loss: 1.0203 loss_prob: 0.5434 loss_thr: 0.3834 loss_db: 0.0935 2022/11/02 22:46:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:46:41 - mmengine - INFO - Epoch(train) [913][5/63] lr: 5.9742e-04 eta: 3:09:34 time: 1.4619 data_time: 0.2441 memory: 14901 loss: 1.0355 loss_prob: 0.5448 loss_thr: 0.3957 loss_db: 0.0950 2022/11/02 22:46:48 - mmengine - INFO - Epoch(train) [913][10/63] lr: 5.9742e-04 eta: 3:09:28 time: 1.6797 data_time: 0.2437 memory: 14901 loss: 0.9994 loss_prob: 0.5226 loss_thr: 0.3850 loss_db: 0.0917 2022/11/02 22:46:54 - mmengine - INFO - Epoch(train) [913][15/63] lr: 5.9742e-04 eta: 3:09:28 time: 1.2841 data_time: 0.0135 memory: 14901 loss: 0.9507 loss_prob: 0.4918 loss_thr: 0.3720 loss_db: 0.0869 2022/11/02 22:47:01 - mmengine - INFO - Epoch(train) [913][20/63] lr: 5.9742e-04 eta: 3:09:24 time: 1.3073 data_time: 0.0152 memory: 14901 loss: 0.8772 loss_prob: 0.4441 loss_thr: 0.3532 loss_db: 0.0800 2022/11/02 22:47:07 - mmengine - INFO - Epoch(train) [913][25/63] lr: 5.9742e-04 eta: 3:09:24 time: 1.3388 data_time: 0.0256 memory: 14901 loss: 0.9269 loss_prob: 0.4785 loss_thr: 0.3655 loss_db: 0.0828 2022/11/02 22:47:13 - mmengine - INFO - Epoch(train) [913][30/63] lr: 5.9742e-04 eta: 3:09:20 time: 1.2275 data_time: 0.0413 memory: 14901 loss: 0.9792 loss_prob: 0.5151 loss_thr: 0.3770 loss_db: 0.0871 2022/11/02 22:47:20 - mmengine - INFO - Epoch(train) [913][35/63] lr: 5.9742e-04 eta: 3:09:20 time: 1.2525 data_time: 0.0336 memory: 14901 loss: 1.0230 loss_prob: 0.5395 loss_thr: 0.3918 loss_db: 0.0918 2022/11/02 22:47:27 - mmengine - INFO - Epoch(train) [913][40/63] lr: 5.9742e-04 eta: 3:09:16 time: 1.4133 data_time: 0.0117 memory: 14901 loss: 1.0057 loss_prob: 0.5278 loss_thr: 0.3891 loss_db: 0.0888 2022/11/02 22:47:32 - mmengine - INFO - Epoch(train) [913][45/63] lr: 5.9742e-04 eta: 3:09:16 time: 1.1957 data_time: 0.0141 memory: 14901 loss: 1.0299 loss_prob: 0.5448 loss_thr: 0.3931 loss_db: 0.0920 2022/11/02 22:47:39 - mmengine - INFO - Epoch(train) [913][50/63] lr: 5.9742e-04 eta: 3:09:12 time: 1.2467 data_time: 0.0283 memory: 14901 loss: 0.9788 loss_prob: 0.5115 loss_thr: 0.3782 loss_db: 0.0890 2022/11/02 22:47:46 - mmengine - INFO - Epoch(train) [913][55/63] lr: 5.9742e-04 eta: 3:09:12 time: 1.4055 data_time: 0.0317 memory: 14901 loss: 0.8976 loss_prob: 0.4622 loss_thr: 0.3553 loss_db: 0.0801 2022/11/02 22:47:52 - mmengine - INFO - Epoch(train) [913][60/63] lr: 5.9742e-04 eta: 3:09:07 time: 1.2704 data_time: 0.0199 memory: 14901 loss: 0.9232 loss_prob: 0.4809 loss_thr: 0.3602 loss_db: 0.0821 2022/11/02 22:47:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:48:07 - mmengine - INFO - Epoch(train) [914][5/63] lr: 5.9554e-04 eta: 3:09:07 time: 1.7017 data_time: 0.2858 memory: 14901 loss: 0.9634 loss_prob: 0.4937 loss_thr: 0.3841 loss_db: 0.0856 2022/11/02 22:48:13 - mmengine - INFO - Epoch(train) [914][10/63] lr: 5.9554e-04 eta: 3:09:02 time: 1.7692 data_time: 0.2860 memory: 14901 loss: 0.9492 loss_prob: 0.4871 loss_thr: 0.3762 loss_db: 0.0859 2022/11/02 22:48:19 - mmengine - INFO - Epoch(train) [914][15/63] lr: 5.9554e-04 eta: 3:09:02 time: 1.1773 data_time: 0.0130 memory: 14901 loss: 0.9457 loss_prob: 0.4917 loss_thr: 0.3675 loss_db: 0.0865 2022/11/02 22:48:25 - mmengine - INFO - Epoch(train) [914][20/63] lr: 5.9554e-04 eta: 3:08:58 time: 1.1969 data_time: 0.0123 memory: 14901 loss: 0.9469 loss_prob: 0.4931 loss_thr: 0.3666 loss_db: 0.0872 2022/11/02 22:48:31 - mmengine - INFO - Epoch(train) [914][25/63] lr: 5.9554e-04 eta: 3:08:58 time: 1.2177 data_time: 0.0271 memory: 14901 loss: 0.8911 loss_prob: 0.4538 loss_thr: 0.3560 loss_db: 0.0813 2022/11/02 22:48:38 - mmengine - INFO - Epoch(train) [914][30/63] lr: 5.9554e-04 eta: 3:08:54 time: 1.3733 data_time: 0.0508 memory: 14901 loss: 0.9209 loss_prob: 0.4743 loss_thr: 0.3639 loss_db: 0.0828 2022/11/02 22:48:44 - mmengine - INFO - Epoch(train) [914][35/63] lr: 5.9554e-04 eta: 3:08:54 time: 1.3152 data_time: 0.0348 memory: 14901 loss: 0.9461 loss_prob: 0.4964 loss_thr: 0.3642 loss_db: 0.0855 2022/11/02 22:48:51 - mmengine - INFO - Epoch(train) [914][40/63] lr: 5.9554e-04 eta: 3:08:50 time: 1.2572 data_time: 0.0120 memory: 14901 loss: 0.9666 loss_prob: 0.5059 loss_thr: 0.3735 loss_db: 0.0871 2022/11/02 22:48:57 - mmengine - INFO - Epoch(train) [914][45/63] lr: 5.9554e-04 eta: 3:08:50 time: 1.3071 data_time: 0.0123 memory: 14901 loss: 1.0006 loss_prob: 0.5280 loss_thr: 0.3837 loss_db: 0.0890 2022/11/02 22:49:03 - mmengine - INFO - Epoch(train) [914][50/63] lr: 5.9554e-04 eta: 3:08:45 time: 1.2075 data_time: 0.0307 memory: 14901 loss: 0.9460 loss_prob: 0.5014 loss_thr: 0.3609 loss_db: 0.0836 2022/11/02 22:49:10 - mmengine - INFO - Epoch(train) [914][55/63] lr: 5.9554e-04 eta: 3:08:45 time: 1.3094 data_time: 0.0279 memory: 14901 loss: 0.9416 loss_prob: 0.4905 loss_thr: 0.3662 loss_db: 0.0850 2022/11/02 22:49:15 - mmengine - INFO - Epoch(train) [914][60/63] lr: 5.9554e-04 eta: 3:08:41 time: 1.1918 data_time: 0.0084 memory: 14901 loss: 0.9224 loss_prob: 0.4745 loss_thr: 0.3638 loss_db: 0.0841 2022/11/02 22:49:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:49:29 - mmengine - INFO - Epoch(train) [915][5/63] lr: 5.9367e-04 eta: 3:08:41 time: 1.6384 data_time: 0.2873 memory: 14901 loss: 0.9415 loss_prob: 0.4838 loss_thr: 0.3739 loss_db: 0.0838 2022/11/02 22:49:33 - mmengine - INFO - Epoch(train) [915][10/63] lr: 5.9367e-04 eta: 3:08:35 time: 1.5224 data_time: 0.2914 memory: 14901 loss: 1.0021 loss_prob: 0.5084 loss_thr: 0.4038 loss_db: 0.0899 2022/11/02 22:49:39 - mmengine - INFO - Epoch(train) [915][15/63] lr: 5.9367e-04 eta: 3:08:35 time: 1.0575 data_time: 0.0161 memory: 14901 loss: 1.0219 loss_prob: 0.5290 loss_thr: 0.4011 loss_db: 0.0918 2022/11/02 22:49:45 - mmengine - INFO - Epoch(train) [915][20/63] lr: 5.9367e-04 eta: 3:08:30 time: 1.1780 data_time: 0.0103 memory: 14901 loss: 0.8938 loss_prob: 0.4622 loss_thr: 0.3531 loss_db: 0.0784 2022/11/02 22:49:50 - mmengine - INFO - Epoch(train) [915][25/63] lr: 5.9367e-04 eta: 3:08:30 time: 1.0313 data_time: 0.0392 memory: 14901 loss: 0.9406 loss_prob: 0.4916 loss_thr: 0.3637 loss_db: 0.0853 2022/11/02 22:49:56 - mmengine - INFO - Epoch(train) [915][30/63] lr: 5.9367e-04 eta: 3:08:25 time: 1.1277 data_time: 0.0530 memory: 14901 loss: 1.1014 loss_prob: 0.5752 loss_thr: 0.4231 loss_db: 0.1032 2022/11/02 22:50:03 - mmengine - INFO - Epoch(train) [915][35/63] lr: 5.9367e-04 eta: 3:08:25 time: 1.3041 data_time: 0.0226 memory: 14901 loss: 1.0751 loss_prob: 0.5579 loss_thr: 0.4182 loss_db: 0.0990 2022/11/02 22:50:08 - mmengine - INFO - Epoch(train) [915][40/63] lr: 5.9367e-04 eta: 3:08:21 time: 1.2281 data_time: 0.0073 memory: 14901 loss: 0.9570 loss_prob: 0.5018 loss_thr: 0.3673 loss_db: 0.0879 2022/11/02 22:50:15 - mmengine - INFO - Epoch(train) [915][45/63] lr: 5.9367e-04 eta: 3:08:21 time: 1.1882 data_time: 0.0068 memory: 14901 loss: 0.9777 loss_prob: 0.5258 loss_thr: 0.3629 loss_db: 0.0891 2022/11/02 22:50:20 - mmengine - INFO - Epoch(train) [915][50/63] lr: 5.9367e-04 eta: 3:08:16 time: 1.2142 data_time: 0.0478 memory: 14901 loss: 0.9553 loss_prob: 0.5109 loss_thr: 0.3590 loss_db: 0.0854 2022/11/02 22:50:28 - mmengine - INFO - Epoch(train) [915][55/63] lr: 5.9367e-04 eta: 3:08:16 time: 1.2938 data_time: 0.0567 memory: 14901 loss: 0.9794 loss_prob: 0.5139 loss_thr: 0.3771 loss_db: 0.0884 2022/11/02 22:50:34 - mmengine - INFO - Epoch(train) [915][60/63] lr: 5.9367e-04 eta: 3:08:12 time: 1.3385 data_time: 0.0191 memory: 14901 loss: 1.0008 loss_prob: 0.5274 loss_thr: 0.3814 loss_db: 0.0920 2022/11/02 22:50:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:50:46 - mmengine - INFO - Epoch(train) [916][5/63] lr: 5.9179e-04 eta: 3:08:12 time: 1.5520 data_time: 0.2411 memory: 14901 loss: 0.9554 loss_prob: 0.5012 loss_thr: 0.3673 loss_db: 0.0868 2022/11/02 22:50:51 - mmengine - INFO - Epoch(train) [916][10/63] lr: 5.9179e-04 eta: 3:08:06 time: 1.3978 data_time: 0.2397 memory: 14901 loss: 0.9817 loss_prob: 0.5101 loss_thr: 0.3838 loss_db: 0.0879 2022/11/02 22:50:56 - mmengine - INFO - Epoch(train) [916][15/63] lr: 5.9179e-04 eta: 3:08:06 time: 1.0489 data_time: 0.0101 memory: 14901 loss: 1.0039 loss_prob: 0.5286 loss_thr: 0.3841 loss_db: 0.0912 2022/11/02 22:51:02 - mmengine - INFO - Epoch(train) [916][20/63] lr: 5.9179e-04 eta: 3:08:01 time: 1.1250 data_time: 0.0103 memory: 14901 loss: 1.0286 loss_prob: 0.5501 loss_thr: 0.3842 loss_db: 0.0943 2022/11/02 22:51:07 - mmengine - INFO - Epoch(train) [916][25/63] lr: 5.9179e-04 eta: 3:08:01 time: 1.1313 data_time: 0.0708 memory: 14901 loss: 1.0357 loss_prob: 0.5474 loss_thr: 0.3940 loss_db: 0.0942 2022/11/02 22:51:13 - mmengine - INFO - Epoch(train) [916][30/63] lr: 5.9179e-04 eta: 3:07:56 time: 1.0364 data_time: 0.0796 memory: 14901 loss: 1.0007 loss_prob: 0.5199 loss_thr: 0.3904 loss_db: 0.0904 2022/11/02 22:51:16 - mmengine - INFO - Epoch(train) [916][35/63] lr: 5.9179e-04 eta: 3:07:56 time: 0.8352 data_time: 0.0201 memory: 14901 loss: 0.9530 loss_prob: 0.4916 loss_thr: 0.3745 loss_db: 0.0869 2022/11/02 22:51:20 - mmengine - INFO - Epoch(train) [916][40/63] lr: 5.9179e-04 eta: 3:07:50 time: 0.7057 data_time: 0.0107 memory: 14901 loss: 0.8997 loss_prob: 0.4631 loss_thr: 0.3538 loss_db: 0.0828 2022/11/02 22:51:23 - mmengine - INFO - Epoch(train) [916][45/63] lr: 5.9179e-04 eta: 3:07:50 time: 0.7264 data_time: 0.0228 memory: 14901 loss: 0.9176 loss_prob: 0.4809 loss_thr: 0.3520 loss_db: 0.0846 2022/11/02 22:51:27 - mmengine - INFO - Epoch(train) [916][50/63] lr: 5.9179e-04 eta: 3:07:44 time: 0.7636 data_time: 0.0287 memory: 14901 loss: 0.9462 loss_prob: 0.4923 loss_thr: 0.3679 loss_db: 0.0859 2022/11/02 22:51:31 - mmengine - INFO - Epoch(train) [916][55/63] lr: 5.9179e-04 eta: 3:07:44 time: 0.7717 data_time: 0.0178 memory: 14901 loss: 0.9422 loss_prob: 0.4828 loss_thr: 0.3749 loss_db: 0.0844 2022/11/02 22:51:35 - mmengine - INFO - Epoch(train) [916][60/63] lr: 5.9179e-04 eta: 3:07:38 time: 0.7124 data_time: 0.0139 memory: 14901 loss: 1.0178 loss_prob: 0.5330 loss_thr: 0.3942 loss_db: 0.0906 2022/11/02 22:51:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:51:43 - mmengine - INFO - Epoch(train) [917][5/63] lr: 5.8992e-04 eta: 3:07:38 time: 0.9542 data_time: 0.2181 memory: 14901 loss: 0.9558 loss_prob: 0.4980 loss_thr: 0.3686 loss_db: 0.0892 2022/11/02 22:51:51 - mmengine - INFO - Epoch(train) [917][10/63] lr: 5.8992e-04 eta: 3:07:32 time: 1.4154 data_time: 0.2218 memory: 14901 loss: 0.9846 loss_prob: 0.5130 loss_thr: 0.3818 loss_db: 0.0897 2022/11/02 22:52:00 - mmengine - INFO - Epoch(train) [917][15/63] lr: 5.8992e-04 eta: 3:07:32 time: 1.6642 data_time: 0.0241 memory: 14901 loss: 0.9955 loss_prob: 0.5205 loss_thr: 0.3879 loss_db: 0.0871 2022/11/02 22:52:04 - mmengine - INFO - Epoch(train) [917][20/63] lr: 5.8992e-04 eta: 3:07:28 time: 1.3096 data_time: 0.0174 memory: 14901 loss: 0.9285 loss_prob: 0.4950 loss_thr: 0.3517 loss_db: 0.0818 2022/11/02 22:52:13 - mmengine - INFO - Epoch(train) [917][25/63] lr: 5.8992e-04 eta: 3:07:28 time: 1.3086 data_time: 0.0286 memory: 14901 loss: 0.9928 loss_prob: 0.5307 loss_thr: 0.3704 loss_db: 0.0917 2022/11/02 22:52:19 - mmengine - INFO - Epoch(train) [917][30/63] lr: 5.8992e-04 eta: 3:07:24 time: 1.4875 data_time: 0.0482 memory: 14901 loss: 1.0777 loss_prob: 0.5780 loss_thr: 0.4005 loss_db: 0.0993 2022/11/02 22:52:24 - mmengine - INFO - Epoch(train) [917][35/63] lr: 5.8992e-04 eta: 3:07:24 time: 1.0932 data_time: 0.0377 memory: 14901 loss: 1.0252 loss_prob: 0.5448 loss_thr: 0.3885 loss_db: 0.0920 2022/11/02 22:52:29 - mmengine - INFO - Epoch(train) [917][40/63] lr: 5.8992e-04 eta: 3:07:19 time: 1.0012 data_time: 0.0237 memory: 14901 loss: 0.9731 loss_prob: 0.5075 loss_thr: 0.3776 loss_db: 0.0881 2022/11/02 22:52:36 - mmengine - INFO - Epoch(train) [917][45/63] lr: 5.8992e-04 eta: 3:07:19 time: 1.2217 data_time: 0.0235 memory: 14901 loss: 0.9633 loss_prob: 0.4998 loss_thr: 0.3754 loss_db: 0.0881 2022/11/02 22:52:39 - mmengine - INFO - Epoch(train) [917][50/63] lr: 5.8992e-04 eta: 3:07:14 time: 1.0837 data_time: 0.0495 memory: 14901 loss: 0.9198 loss_prob: 0.4715 loss_thr: 0.3659 loss_db: 0.0825 2022/11/02 22:52:46 - mmengine - INFO - Epoch(train) [917][55/63] lr: 5.8992e-04 eta: 3:07:14 time: 0.9524 data_time: 0.0431 memory: 14901 loss: 0.9071 loss_prob: 0.4688 loss_thr: 0.3562 loss_db: 0.0821 2022/11/02 22:52:53 - mmengine - INFO - Epoch(train) [917][60/63] lr: 5.8992e-04 eta: 3:07:10 time: 1.3890 data_time: 0.0151 memory: 14901 loss: 0.9129 loss_prob: 0.4783 loss_thr: 0.3498 loss_db: 0.0848 2022/11/02 22:52:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:53:06 - mmengine - INFO - Epoch(train) [918][5/63] lr: 5.8804e-04 eta: 3:07:10 time: 1.5583 data_time: 0.2432 memory: 14901 loss: 0.9849 loss_prob: 0.5178 loss_thr: 0.3763 loss_db: 0.0907 2022/11/02 22:53:13 - mmengine - INFO - Epoch(train) [918][10/63] lr: 5.8804e-04 eta: 3:07:04 time: 1.5549 data_time: 0.2514 memory: 14901 loss: 0.9789 loss_prob: 0.5076 loss_thr: 0.3835 loss_db: 0.0878 2022/11/02 22:53:22 - mmengine - INFO - Epoch(train) [918][15/63] lr: 5.8804e-04 eta: 3:07:04 time: 1.5355 data_time: 0.0237 memory: 14901 loss: 0.8930 loss_prob: 0.4527 loss_thr: 0.3603 loss_db: 0.0801 2022/11/02 22:53:28 - mmengine - INFO - Epoch(train) [918][20/63] lr: 5.8804e-04 eta: 3:07:00 time: 1.4568 data_time: 0.0125 memory: 14901 loss: 0.9384 loss_prob: 0.4899 loss_thr: 0.3628 loss_db: 0.0858 2022/11/02 22:53:33 - mmengine - INFO - Epoch(train) [918][25/63] lr: 5.8804e-04 eta: 3:07:00 time: 1.1206 data_time: 0.0322 memory: 14901 loss: 1.0184 loss_prob: 0.5442 loss_thr: 0.3833 loss_db: 0.0909 2022/11/02 22:53:40 - mmengine - INFO - Epoch(train) [918][30/63] lr: 5.8804e-04 eta: 3:06:56 time: 1.2719 data_time: 0.0593 memory: 14901 loss: 1.0049 loss_prob: 0.5310 loss_thr: 0.3864 loss_db: 0.0876 2022/11/02 22:53:48 - mmengine - INFO - Epoch(train) [918][35/63] lr: 5.8804e-04 eta: 3:06:56 time: 1.5603 data_time: 0.0380 memory: 14901 loss: 0.9795 loss_prob: 0.5082 loss_thr: 0.3842 loss_db: 0.0872 2022/11/02 22:53:54 - mmengine - INFO - Epoch(train) [918][40/63] lr: 5.8804e-04 eta: 3:06:52 time: 1.3066 data_time: 0.0159 memory: 14901 loss: 0.9929 loss_prob: 0.5184 loss_thr: 0.3843 loss_db: 0.0902 2022/11/02 22:53:58 - mmengine - INFO - Epoch(train) [918][45/63] lr: 5.8804e-04 eta: 3:06:52 time: 0.9370 data_time: 0.0205 memory: 14901 loss: 1.0051 loss_prob: 0.5320 loss_thr: 0.3804 loss_db: 0.0927 2022/11/02 22:54:04 - mmengine - INFO - Epoch(train) [918][50/63] lr: 5.8804e-04 eta: 3:06:47 time: 1.0768 data_time: 0.0288 memory: 14901 loss: 0.9193 loss_prob: 0.4773 loss_thr: 0.3567 loss_db: 0.0853 2022/11/02 22:54:12 - mmengine - INFO - Epoch(train) [918][55/63] lr: 5.8804e-04 eta: 3:06:47 time: 1.3762 data_time: 0.0327 memory: 14901 loss: 0.8615 loss_prob: 0.4381 loss_thr: 0.3452 loss_db: 0.0782 2022/11/02 22:54:18 - mmengine - INFO - Epoch(train) [918][60/63] lr: 5.8804e-04 eta: 3:06:43 time: 1.3496 data_time: 0.0219 memory: 14901 loss: 0.9231 loss_prob: 0.4787 loss_thr: 0.3607 loss_db: 0.0838 2022/11/02 22:54:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:54:31 - mmengine - INFO - Epoch(train) [919][5/63] lr: 5.8617e-04 eta: 3:06:43 time: 1.7455 data_time: 0.2149 memory: 14901 loss: 0.9246 loss_prob: 0.4735 loss_thr: 0.3688 loss_db: 0.0823 2022/11/02 22:54:37 - mmengine - INFO - Epoch(train) [919][10/63] lr: 5.8617e-04 eta: 3:06:37 time: 1.4962 data_time: 0.2142 memory: 14901 loss: 0.8700 loss_prob: 0.4356 loss_thr: 0.3578 loss_db: 0.0767 2022/11/02 22:54:44 - mmengine - INFO - Epoch(train) [919][15/63] lr: 5.8617e-04 eta: 3:06:37 time: 1.2454 data_time: 0.0113 memory: 14901 loss: 0.9274 loss_prob: 0.4774 loss_thr: 0.3693 loss_db: 0.0807 2022/11/02 22:54:50 - mmengine - INFO - Epoch(train) [919][20/63] lr: 5.8617e-04 eta: 3:06:32 time: 1.2557 data_time: 0.0112 memory: 14901 loss: 0.9129 loss_prob: 0.4744 loss_thr: 0.3570 loss_db: 0.0816 2022/11/02 22:54:56 - mmengine - INFO - Epoch(train) [919][25/63] lr: 5.8617e-04 eta: 3:06:32 time: 1.1942 data_time: 0.0334 memory: 14901 loss: 0.8971 loss_prob: 0.4622 loss_thr: 0.3524 loss_db: 0.0825 2022/11/02 22:55:03 - mmengine - INFO - Epoch(train) [919][30/63] lr: 5.8617e-04 eta: 3:06:28 time: 1.3246 data_time: 0.0549 memory: 14901 loss: 0.9718 loss_prob: 0.5018 loss_thr: 0.3822 loss_db: 0.0878 2022/11/02 22:55:11 - mmengine - INFO - Epoch(train) [919][35/63] lr: 5.8617e-04 eta: 3:06:28 time: 1.5330 data_time: 0.0301 memory: 14901 loss: 0.9686 loss_prob: 0.5019 loss_thr: 0.3807 loss_db: 0.0860 2022/11/02 22:55:16 - mmengine - INFO - Epoch(train) [919][40/63] lr: 5.8617e-04 eta: 3:06:24 time: 1.3336 data_time: 0.0087 memory: 14901 loss: 0.9764 loss_prob: 0.5086 loss_thr: 0.3793 loss_db: 0.0885 2022/11/02 22:55:24 - mmengine - INFO - Epoch(train) [919][45/63] lr: 5.8617e-04 eta: 3:06:24 time: 1.2434 data_time: 0.0087 memory: 14901 loss: 0.8958 loss_prob: 0.4576 loss_thr: 0.3571 loss_db: 0.0811 2022/11/02 22:55:30 - mmengine - INFO - Epoch(train) [919][50/63] lr: 5.8617e-04 eta: 3:06:20 time: 1.3503 data_time: 0.0230 memory: 14901 loss: 0.8552 loss_prob: 0.4383 loss_thr: 0.3417 loss_db: 0.0753 2022/11/02 22:55:35 - mmengine - INFO - Epoch(train) [919][55/63] lr: 5.8617e-04 eta: 3:06:20 time: 1.1053 data_time: 0.0365 memory: 14901 loss: 0.9291 loss_prob: 0.4829 loss_thr: 0.3625 loss_db: 0.0837 2022/11/02 22:55:41 - mmengine - INFO - Epoch(train) [919][60/63] lr: 5.8617e-04 eta: 3:06:15 time: 1.1177 data_time: 0.0244 memory: 14901 loss: 0.9409 loss_prob: 0.4860 loss_thr: 0.3687 loss_db: 0.0862 2022/11/02 22:55:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:55:53 - mmengine - INFO - Epoch(train) [920][5/63] lr: 5.8429e-04 eta: 3:06:15 time: 1.5319 data_time: 0.2352 memory: 14901 loss: 0.8818 loss_prob: 0.4563 loss_thr: 0.3468 loss_db: 0.0787 2022/11/02 22:56:01 - mmengine - INFO - Epoch(train) [920][10/63] lr: 5.8429e-04 eta: 3:06:10 time: 1.7277 data_time: 0.2444 memory: 14901 loss: 0.9154 loss_prob: 0.4805 loss_thr: 0.3534 loss_db: 0.0815 2022/11/02 22:56:04 - mmengine - INFO - Epoch(train) [920][15/63] lr: 5.8429e-04 eta: 3:06:10 time: 1.0876 data_time: 0.0199 memory: 14901 loss: 0.9764 loss_prob: 0.5150 loss_thr: 0.3726 loss_db: 0.0889 2022/11/02 22:56:11 - mmengine - INFO - Epoch(train) [920][20/63] lr: 5.8429e-04 eta: 3:06:05 time: 1.0758 data_time: 0.0128 memory: 14901 loss: 0.9176 loss_prob: 0.4759 loss_thr: 0.3585 loss_db: 0.0832 2022/11/02 22:56:15 - mmengine - INFO - Epoch(train) [920][25/63] lr: 5.8429e-04 eta: 3:06:05 time: 1.1455 data_time: 0.0205 memory: 14901 loss: 0.9355 loss_prob: 0.4809 loss_thr: 0.3691 loss_db: 0.0855 2022/11/02 22:56:24 - mmengine - INFO - Epoch(train) [920][30/63] lr: 5.8429e-04 eta: 3:06:00 time: 1.2025 data_time: 0.0518 memory: 14901 loss: 0.9866 loss_prob: 0.5097 loss_thr: 0.3866 loss_db: 0.0903 2022/11/02 22:56:28 - mmengine - INFO - Epoch(train) [920][35/63] lr: 5.8429e-04 eta: 3:06:00 time: 1.2644 data_time: 0.0465 memory: 14901 loss: 0.9479 loss_prob: 0.4955 loss_thr: 0.3662 loss_db: 0.0862 2022/11/02 22:56:34 - mmengine - INFO - Epoch(train) [920][40/63] lr: 5.8429e-04 eta: 3:05:55 time: 1.0330 data_time: 0.0121 memory: 14901 loss: 0.8770 loss_prob: 0.4551 loss_thr: 0.3426 loss_db: 0.0793 2022/11/02 22:56:41 - mmengine - INFO - Epoch(train) [920][45/63] lr: 5.8429e-04 eta: 3:05:55 time: 1.2776 data_time: 0.0098 memory: 14901 loss: 0.9491 loss_prob: 0.4892 loss_thr: 0.3746 loss_db: 0.0853 2022/11/02 22:56:45 - mmengine - INFO - Epoch(train) [920][50/63] lr: 5.8429e-04 eta: 3:05:50 time: 1.1059 data_time: 0.0229 memory: 14901 loss: 0.9820 loss_prob: 0.5107 loss_thr: 0.3831 loss_db: 0.0883 2022/11/02 22:56:52 - mmengine - INFO - Epoch(train) [920][55/63] lr: 5.8429e-04 eta: 3:05:50 time: 1.1061 data_time: 0.0428 memory: 14901 loss: 0.9270 loss_prob: 0.4836 loss_thr: 0.3588 loss_db: 0.0846 2022/11/02 22:56:57 - mmengine - INFO - Epoch(train) [920][60/63] lr: 5.8429e-04 eta: 3:05:46 time: 1.2122 data_time: 0.0300 memory: 14901 loss: 0.8881 loss_prob: 0.4652 loss_thr: 0.3410 loss_db: 0.0819 2022/11/02 22:57:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:57:02 - mmengine - INFO - Saving checkpoint at 920 epochs 2022/11/02 22:57:06 - mmengine - INFO - Epoch(val) [920][5/500] eta: 3:05:46 time: 0.0603 data_time: 0.0097 memory: 14901 2022/11/02 22:57:06 - mmengine - INFO - Epoch(val) [920][10/500] eta: 0:00:31 time: 0.0639 data_time: 0.0095 memory: 1008 2022/11/02 22:57:06 - mmengine - INFO - Epoch(val) [920][15/500] eta: 0:00:31 time: 0.0579 data_time: 0.0101 memory: 1008 2022/11/02 22:57:06 - mmengine - INFO - Epoch(val) [920][20/500] eta: 0:00:27 time: 0.0564 data_time: 0.0106 memory: 1008 2022/11/02 22:57:07 - mmengine - INFO - Epoch(val) [920][25/500] eta: 0:00:27 time: 0.0484 data_time: 0.0049 memory: 1008 2022/11/02 22:57:07 - mmengine - INFO - Epoch(val) [920][30/500] eta: 0:00:27 time: 0.0593 data_time: 0.0065 memory: 1008 2022/11/02 22:57:07 - mmengine - INFO - Epoch(val) [920][35/500] eta: 0:00:27 time: 0.0624 data_time: 0.0068 memory: 1008 2022/11/02 22:57:08 - mmengine - INFO - Epoch(val) [920][40/500] eta: 0:00:27 time: 0.0592 data_time: 0.0077 memory: 1008 2022/11/02 22:57:08 - mmengine - INFO - Epoch(val) [920][45/500] eta: 0:00:27 time: 0.0572 data_time: 0.0073 memory: 1008 2022/11/02 22:57:08 - mmengine - INFO - Epoch(val) [920][50/500] eta: 0:00:21 time: 0.0478 data_time: 0.0035 memory: 1008 2022/11/02 22:57:08 - mmengine - INFO - Epoch(val) [920][55/500] eta: 0:00:21 time: 0.0474 data_time: 0.0035 memory: 1008 2022/11/02 22:57:09 - mmengine - INFO - Epoch(val) [920][60/500] eta: 0:00:18 time: 0.0419 data_time: 0.0029 memory: 1008 2022/11/02 22:57:09 - mmengine - INFO - Epoch(val) [920][65/500] eta: 0:00:18 time: 0.0462 data_time: 0.0035 memory: 1008 2022/11/02 22:57:09 - mmengine - INFO - Epoch(val) [920][70/500] eta: 0:00:20 time: 0.0478 data_time: 0.0034 memory: 1008 2022/11/02 22:57:09 - mmengine - INFO - Epoch(val) [920][75/500] eta: 0:00:20 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/02 22:57:09 - mmengine - INFO - Epoch(val) [920][80/500] eta: 0:00:15 time: 0.0377 data_time: 0.0028 memory: 1008 2022/11/02 22:57:10 - mmengine - INFO - Epoch(val) [920][85/500] eta: 0:00:15 time: 0.0474 data_time: 0.0062 memory: 1008 2022/11/02 22:57:10 - mmengine - INFO - Epoch(val) [920][90/500] eta: 0:00:23 time: 0.0569 data_time: 0.0070 memory: 1008 2022/11/02 22:57:10 - mmengine - INFO - Epoch(val) [920][95/500] eta: 0:00:23 time: 0.0540 data_time: 0.0036 memory: 1008 2022/11/02 22:57:10 - mmengine - INFO - Epoch(val) [920][100/500] eta: 0:00:18 time: 0.0463 data_time: 0.0031 memory: 1008 2022/11/02 22:57:11 - mmengine - INFO - Epoch(val) [920][105/500] eta: 0:00:18 time: 0.0515 data_time: 0.0064 memory: 1008 2022/11/02 22:57:11 - mmengine - INFO - Epoch(val) [920][110/500] eta: 0:00:22 time: 0.0584 data_time: 0.0077 memory: 1008 2022/11/02 22:57:11 - mmengine - INFO - Epoch(val) [920][115/500] eta: 0:00:22 time: 0.0530 data_time: 0.0061 memory: 1008 2022/11/02 22:57:12 - mmengine - INFO - Epoch(val) [920][120/500] eta: 0:00:19 time: 0.0516 data_time: 0.0053 memory: 1008 2022/11/02 22:57:12 - mmengine - INFO - Epoch(val) [920][125/500] eta: 0:00:19 time: 0.0571 data_time: 0.0093 memory: 1008 2022/11/02 22:57:12 - mmengine - INFO - Epoch(val) [920][130/500] eta: 0:00:21 time: 0.0570 data_time: 0.0100 memory: 1008 2022/11/02 22:57:12 - mmengine - INFO - Epoch(val) [920][135/500] eta: 0:00:21 time: 0.0532 data_time: 0.0073 memory: 1008 2022/11/02 22:57:13 - mmengine - INFO - Epoch(val) [920][140/500] eta: 0:00:17 time: 0.0489 data_time: 0.0059 memory: 1008 2022/11/02 22:57:13 - mmengine - INFO - Epoch(val) [920][145/500] eta: 0:00:17 time: 0.0474 data_time: 0.0032 memory: 1008 2022/11/02 22:57:13 - mmengine - INFO - Epoch(val) [920][150/500] eta: 0:00:14 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/02 22:57:13 - mmengine - INFO - Epoch(val) [920][155/500] eta: 0:00:14 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/02 22:57:13 - mmengine - INFO - Epoch(val) [920][160/500] eta: 0:00:14 time: 0.0428 data_time: 0.0025 memory: 1008 2022/11/02 22:57:14 - mmengine - INFO - Epoch(val) [920][165/500] eta: 0:00:14 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/02 22:57:14 - mmengine - INFO - Epoch(val) [920][170/500] eta: 0:00:13 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/02 22:57:14 - mmengine - INFO - Epoch(val) [920][175/500] eta: 0:00:13 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/02 22:57:14 - mmengine - INFO - Epoch(val) [920][180/500] eta: 0:00:11 time: 0.0370 data_time: 0.0026 memory: 1008 2022/11/02 22:57:15 - mmengine - INFO - Epoch(val) [920][185/500] eta: 0:00:11 time: 0.0474 data_time: 0.0049 memory: 1008 2022/11/02 22:57:15 - mmengine - INFO - Epoch(val) [920][190/500] eta: 0:00:15 time: 0.0508 data_time: 0.0051 memory: 1008 2022/11/02 22:57:15 - mmengine - INFO - Epoch(val) [920][195/500] eta: 0:00:15 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/02 22:57:15 - mmengine - INFO - Epoch(val) [920][200/500] eta: 0:00:15 time: 0.0504 data_time: 0.0044 memory: 1008 2022/11/02 22:57:16 - mmengine - INFO - Epoch(val) [920][205/500] eta: 0:00:15 time: 0.0603 data_time: 0.0080 memory: 1008 2022/11/02 22:57:16 - mmengine - INFO - Epoch(val) [920][210/500] eta: 0:00:14 time: 0.0498 data_time: 0.0066 memory: 1008 2022/11/02 22:57:16 - mmengine - INFO - Epoch(val) [920][215/500] eta: 0:00:14 time: 0.0420 data_time: 0.0031 memory: 1008 2022/11/02 22:57:16 - mmengine - INFO - Epoch(val) [920][220/500] eta: 0:00:14 time: 0.0513 data_time: 0.0075 memory: 1008 2022/11/02 22:57:17 - mmengine - INFO - Epoch(val) [920][225/500] eta: 0:00:14 time: 0.0550 data_time: 0.0076 memory: 1008 2022/11/02 22:57:17 - mmengine - INFO - Epoch(val) [920][230/500] eta: 0:00:11 time: 0.0431 data_time: 0.0031 memory: 1008 2022/11/02 22:57:17 - mmengine - INFO - Epoch(val) [920][235/500] eta: 0:00:11 time: 0.0451 data_time: 0.0044 memory: 1008 2022/11/02 22:57:17 - mmengine - INFO - Epoch(val) [920][240/500] eta: 0:00:15 time: 0.0592 data_time: 0.0060 memory: 1008 2022/11/02 22:57:18 - mmengine - INFO - Epoch(val) [920][245/500] eta: 0:00:15 time: 0.0567 data_time: 0.0059 memory: 1008 2022/11/02 22:57:18 - mmengine - INFO - Epoch(val) [920][250/500] eta: 0:00:13 time: 0.0546 data_time: 0.0045 memory: 1008 2022/11/02 22:57:18 - mmengine - INFO - Epoch(val) [920][255/500] eta: 0:00:13 time: 0.0532 data_time: 0.0043 memory: 1008 2022/11/02 22:57:18 - mmengine - INFO - Epoch(val) [920][260/500] eta: 0:00:10 time: 0.0451 data_time: 0.0044 memory: 1008 2022/11/02 22:57:19 - mmengine - INFO - Epoch(val) [920][265/500] eta: 0:00:10 time: 0.0457 data_time: 0.0037 memory: 1008 2022/11/02 22:57:19 - mmengine - INFO - Epoch(val) [920][270/500] eta: 0:00:10 time: 0.0469 data_time: 0.0042 memory: 1008 2022/11/02 22:57:19 - mmengine - INFO - Epoch(val) [920][275/500] eta: 0:00:10 time: 0.0432 data_time: 0.0035 memory: 1008 2022/11/02 22:57:19 - mmengine - INFO - Epoch(val) [920][280/500] eta: 0:00:10 time: 0.0458 data_time: 0.0030 memory: 1008 2022/11/02 22:57:19 - mmengine - INFO - Epoch(val) [920][285/500] eta: 0:00:10 time: 0.0462 data_time: 0.0034 memory: 1008 2022/11/02 22:57:20 - mmengine - INFO - Epoch(val) [920][290/500] eta: 0:00:09 time: 0.0435 data_time: 0.0037 memory: 1008 2022/11/02 22:57:20 - mmengine - INFO - Epoch(val) [920][295/500] eta: 0:00:09 time: 0.0442 data_time: 0.0035 memory: 1008 2022/11/02 22:57:20 - mmengine - INFO - Epoch(val) [920][300/500] eta: 0:00:09 time: 0.0454 data_time: 0.0034 memory: 1008 2022/11/02 22:57:20 - mmengine - INFO - Epoch(val) [920][305/500] eta: 0:00:09 time: 0.0523 data_time: 0.0045 memory: 1008 2022/11/02 22:57:21 - mmengine - INFO - Epoch(val) [920][310/500] eta: 0:00:12 time: 0.0635 data_time: 0.0071 memory: 1008 2022/11/02 22:57:21 - mmengine - INFO - Epoch(val) [920][315/500] eta: 0:00:12 time: 0.0725 data_time: 0.0088 memory: 1008 2022/11/02 22:57:22 - mmengine - INFO - Epoch(val) [920][320/500] eta: 0:00:12 time: 0.0711 data_time: 0.0120 memory: 1008 2022/11/02 22:57:22 - mmengine - INFO - Epoch(val) [920][325/500] eta: 0:00:12 time: 0.0762 data_time: 0.0097 memory: 1008 2022/11/02 22:57:22 - mmengine - INFO - Epoch(val) [920][330/500] eta: 0:00:11 time: 0.0674 data_time: 0.0046 memory: 1008 2022/11/02 22:57:22 - mmengine - INFO - Epoch(val) [920][335/500] eta: 0:00:11 time: 0.0549 data_time: 0.0079 memory: 1008 2022/11/02 22:57:23 - mmengine - INFO - Epoch(val) [920][340/500] eta: 0:00:11 time: 0.0747 data_time: 0.0119 memory: 1008 2022/11/02 22:57:23 - mmengine - INFO - Epoch(val) [920][345/500] eta: 0:00:11 time: 0.0677 data_time: 0.0091 memory: 1008 2022/11/02 22:57:23 - mmengine - INFO - Epoch(val) [920][350/500] eta: 0:00:07 time: 0.0479 data_time: 0.0038 memory: 1008 2022/11/02 22:57:24 - mmengine - INFO - Epoch(val) [920][355/500] eta: 0:00:07 time: 0.0496 data_time: 0.0039 memory: 1008 2022/11/02 22:57:24 - mmengine - INFO - Epoch(val) [920][360/500] eta: 0:00:07 time: 0.0560 data_time: 0.0068 memory: 1008 2022/11/02 22:57:24 - mmengine - INFO - Epoch(val) [920][365/500] eta: 0:00:07 time: 0.0647 data_time: 0.0093 memory: 1008 2022/11/02 22:57:25 - mmengine - INFO - Epoch(val) [920][370/500] eta: 0:00:07 time: 0.0598 data_time: 0.0087 memory: 1008 2022/11/02 22:57:25 - mmengine - INFO - Epoch(val) [920][375/500] eta: 0:00:07 time: 0.0520 data_time: 0.0059 memory: 1008 2022/11/02 22:57:25 - mmengine - INFO - Epoch(val) [920][380/500] eta: 0:00:06 time: 0.0543 data_time: 0.0058 memory: 1008 2022/11/02 22:57:25 - mmengine - INFO - Epoch(val) [920][385/500] eta: 0:00:06 time: 0.0606 data_time: 0.0099 memory: 1008 2022/11/02 22:57:26 - mmengine - INFO - Epoch(val) [920][390/500] eta: 0:00:06 time: 0.0561 data_time: 0.0083 memory: 1008 2022/11/02 22:57:26 - mmengine - INFO - Epoch(val) [920][395/500] eta: 0:00:06 time: 0.0482 data_time: 0.0038 memory: 1008 2022/11/02 22:57:26 - mmengine - INFO - Epoch(val) [920][400/500] eta: 0:00:04 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/02 22:57:26 - mmengine - INFO - Epoch(val) [920][405/500] eta: 0:00:04 time: 0.0404 data_time: 0.0030 memory: 1008 2022/11/02 22:57:27 - mmengine - INFO - Epoch(val) [920][410/500] eta: 0:00:03 time: 0.0435 data_time: 0.0032 memory: 1008 2022/11/02 22:57:27 - mmengine - INFO - Epoch(val) [920][415/500] eta: 0:00:03 time: 0.0436 data_time: 0.0032 memory: 1008 2022/11/02 22:57:27 - mmengine - INFO - Epoch(val) [920][420/500] eta: 0:00:02 time: 0.0370 data_time: 0.0028 memory: 1008 2022/11/02 22:57:27 - mmengine - INFO - Epoch(val) [920][425/500] eta: 0:00:02 time: 0.0405 data_time: 0.0029 memory: 1008 2022/11/02 22:57:27 - mmengine - INFO - Epoch(val) [920][430/500] eta: 0:00:02 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 22:57:28 - mmengine - INFO - Epoch(val) [920][435/500] eta: 0:00:02 time: 0.0361 data_time: 0.0025 memory: 1008 2022/11/02 22:57:28 - mmengine - INFO - Epoch(val) [920][440/500] eta: 0:00:02 time: 0.0415 data_time: 0.0033 memory: 1008 2022/11/02 22:57:28 - mmengine - INFO - Epoch(val) [920][445/500] eta: 0:00:02 time: 0.0522 data_time: 0.0046 memory: 1008 2022/11/02 22:57:28 - mmengine - INFO - Epoch(val) [920][450/500] eta: 0:00:02 time: 0.0554 data_time: 0.0050 memory: 1008 2022/11/02 22:57:29 - mmengine - INFO - Epoch(val) [920][455/500] eta: 0:00:02 time: 0.0502 data_time: 0.0039 memory: 1008 2022/11/02 22:57:29 - mmengine - INFO - Epoch(val) [920][460/500] eta: 0:00:01 time: 0.0486 data_time: 0.0062 memory: 1008 2022/11/02 22:57:29 - mmengine - INFO - Epoch(val) [920][465/500] eta: 0:00:01 time: 0.0470 data_time: 0.0067 memory: 1008 2022/11/02 22:57:29 - mmengine - INFO - Epoch(val) [920][470/500] eta: 0:00:01 time: 0.0465 data_time: 0.0044 memory: 1008 2022/11/02 22:57:30 - mmengine - INFO - Epoch(val) [920][475/500] eta: 0:00:01 time: 0.0519 data_time: 0.0049 memory: 1008 2022/11/02 22:57:30 - mmengine - INFO - Epoch(val) [920][480/500] eta: 0:00:01 time: 0.0556 data_time: 0.0053 memory: 1008 2022/11/02 22:57:30 - mmengine - INFO - Epoch(val) [920][485/500] eta: 0:00:01 time: 0.0529 data_time: 0.0052 memory: 1008 2022/11/02 22:57:30 - mmengine - INFO - Epoch(val) [920][490/500] eta: 0:00:00 time: 0.0539 data_time: 0.0055 memory: 1008 2022/11/02 22:57:31 - mmengine - INFO - Epoch(val) [920][495/500] eta: 0:00:00 time: 0.0576 data_time: 0.0052 memory: 1008 2022/11/02 22:57:31 - mmengine - INFO - Epoch(val) [920][500/500] eta: 0:00:00 time: 0.0535 data_time: 0.0038 memory: 1008 2022/11/02 22:57:31 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8267, precision: 0.7498, hmean: 0.7864 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8267, precision: 0.7982, hmean: 0.8122 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8262, precision: 0.8294, hmean: 0.8278 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8247, precision: 0.8522, hmean: 0.8383 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8089, precision: 0.8833, hmean: 0.8444 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6962, precision: 0.9240, hmean: 0.7941 2022/11/02 22:57:31 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1425, precision: 0.9673, hmean: 0.2484 2022/11/02 22:57:31 - mmengine - INFO - Epoch(val) [920][500/500] icdar/precision: 0.8833 icdar/recall: 0.8089 icdar/hmean: 0.8444 2022/11/02 22:57:39 - mmengine - INFO - Epoch(train) [921][5/63] lr: 5.8241e-04 eta: 0:00:00 time: 1.6134 data_time: 0.2523 memory: 14901 loss: 0.9254 loss_prob: 0.4718 loss_thr: 0.3702 loss_db: 0.0834 2022/11/02 22:57:47 - mmengine - INFO - Epoch(train) [921][10/63] lr: 5.8241e-04 eta: 3:05:40 time: 1.5589 data_time: 0.2496 memory: 14901 loss: 1.0024 loss_prob: 0.5048 loss_thr: 0.4085 loss_db: 0.0891 2022/11/02 22:57:51 - mmengine - INFO - Epoch(train) [921][15/63] lr: 5.8241e-04 eta: 3:05:40 time: 1.2499 data_time: 0.0115 memory: 14901 loss: 0.9228 loss_prob: 0.4666 loss_thr: 0.3759 loss_db: 0.0803 2022/11/02 22:57:56 - mmengine - INFO - Epoch(train) [921][20/63] lr: 5.8241e-04 eta: 3:05:34 time: 0.9647 data_time: 0.0145 memory: 14901 loss: 0.9403 loss_prob: 0.4868 loss_thr: 0.3689 loss_db: 0.0846 2022/11/02 22:58:05 - mmengine - INFO - Epoch(train) [921][25/63] lr: 5.8241e-04 eta: 3:05:34 time: 1.3060 data_time: 0.0265 memory: 14901 loss: 0.9798 loss_prob: 0.5066 loss_thr: 0.3838 loss_db: 0.0895 2022/11/02 22:58:10 - mmengine - INFO - Epoch(train) [921][30/63] lr: 5.8241e-04 eta: 3:05:30 time: 1.3442 data_time: 0.0399 memory: 14901 loss: 0.9245 loss_prob: 0.4706 loss_thr: 0.3706 loss_db: 0.0832 2022/11/02 22:58:14 - mmengine - INFO - Epoch(train) [921][35/63] lr: 5.8241e-04 eta: 3:05:30 time: 0.9435 data_time: 0.0258 memory: 14901 loss: 1.0238 loss_prob: 0.5290 loss_thr: 0.4007 loss_db: 0.0941 2022/11/02 22:58:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:58:19 - mmengine - INFO - Epoch(train) [921][40/63] lr: 5.8241e-04 eta: 3:05:25 time: 0.9336 data_time: 0.0397 memory: 14901 loss: 1.0919 loss_prob: 0.5797 loss_thr: 0.4113 loss_db: 0.1009 2022/11/02 22:58:23 - mmengine - INFO - Epoch(train) [921][45/63] lr: 5.8241e-04 eta: 3:05:25 time: 0.9291 data_time: 0.0397 memory: 14901 loss: 0.9953 loss_prob: 0.5184 loss_thr: 0.3879 loss_db: 0.0890 2022/11/02 22:58:30 - mmengine - INFO - Epoch(train) [921][50/63] lr: 5.8241e-04 eta: 3:05:20 time: 1.1408 data_time: 0.0096 memory: 14901 loss: 0.9500 loss_prob: 0.4855 loss_thr: 0.3811 loss_db: 0.0834 2022/11/02 22:58:35 - mmengine - INFO - Epoch(train) [921][55/63] lr: 5.8241e-04 eta: 3:05:20 time: 1.1879 data_time: 0.0119 memory: 14901 loss: 0.9679 loss_prob: 0.5051 loss_thr: 0.3759 loss_db: 0.0869 2022/11/02 22:58:43 - mmengine - INFO - Epoch(train) [921][60/63] lr: 5.8241e-04 eta: 3:05:15 time: 1.2114 data_time: 0.0142 memory: 14901 loss: 0.9687 loss_prob: 0.4977 loss_thr: 0.3836 loss_db: 0.0874 2022/11/02 22:58:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 22:58:53 - mmengine - INFO - Epoch(train) [922][5/63] lr: 5.8053e-04 eta: 3:05:15 time: 1.3565 data_time: 0.2162 memory: 14901 loss: 0.8923 loss_prob: 0.4517 loss_thr: 0.3619 loss_db: 0.0787 2022/11/02 22:58:57 - mmengine - INFO - Epoch(train) [922][10/63] lr: 5.8053e-04 eta: 3:05:09 time: 1.2629 data_time: 0.2258 memory: 14901 loss: 0.8665 loss_prob: 0.4349 loss_thr: 0.3558 loss_db: 0.0758 2022/11/02 22:59:02 - mmengine - INFO - Epoch(train) [922][15/63] lr: 5.8053e-04 eta: 3:05:09 time: 0.9679 data_time: 0.0266 memory: 14901 loss: 0.8412 loss_prob: 0.4211 loss_thr: 0.3458 loss_db: 0.0742 2022/11/02 22:59:08 - mmengine - INFO - Epoch(train) [922][20/63] lr: 5.8053e-04 eta: 3:05:04 time: 1.0859 data_time: 0.0120 memory: 14901 loss: 0.8900 loss_prob: 0.4600 loss_thr: 0.3497 loss_db: 0.0802 2022/11/02 22:59:13 - mmengine - INFO - Epoch(train) [922][25/63] lr: 5.8053e-04 eta: 3:05:04 time: 1.1034 data_time: 0.0198 memory: 14901 loss: 0.9619 loss_prob: 0.5027 loss_thr: 0.3718 loss_db: 0.0875 2022/11/02 22:59:21 - mmengine - INFO - Epoch(train) [922][30/63] lr: 5.8053e-04 eta: 3:04:59 time: 1.2632 data_time: 0.0379 memory: 14901 loss: 0.9024 loss_prob: 0.4600 loss_thr: 0.3616 loss_db: 0.0808 2022/11/02 22:59:25 - mmengine - INFO - Epoch(train) [922][35/63] lr: 5.8053e-04 eta: 3:04:59 time: 1.1288 data_time: 0.0347 memory: 14901 loss: 0.8946 loss_prob: 0.4576 loss_thr: 0.3578 loss_db: 0.0792 2022/11/02 22:59:33 - mmengine - INFO - Epoch(train) [922][40/63] lr: 5.8053e-04 eta: 3:04:55 time: 1.2153 data_time: 0.0183 memory: 14901 loss: 0.9462 loss_prob: 0.4987 loss_thr: 0.3616 loss_db: 0.0858 2022/11/02 22:59:38 - mmengine - INFO - Epoch(train) [922][45/63] lr: 5.8053e-04 eta: 3:04:55 time: 1.3459 data_time: 0.0101 memory: 14901 loss: 0.9360 loss_prob: 0.4877 loss_thr: 0.3645 loss_db: 0.0837 2022/11/02 22:59:45 - mmengine - INFO - Epoch(train) [922][50/63] lr: 5.8053e-04 eta: 3:04:50 time: 1.2614 data_time: 0.0133 memory: 14901 loss: 0.9421 loss_prob: 0.4828 loss_thr: 0.3768 loss_db: 0.0825 2022/11/02 22:59:49 - mmengine - INFO - Epoch(train) [922][55/63] lr: 5.8053e-04 eta: 3:04:50 time: 1.1377 data_time: 0.0233 memory: 14901 loss: 0.9761 loss_prob: 0.5091 loss_thr: 0.3770 loss_db: 0.0900 2022/11/02 22:59:56 - mmengine - INFO - Epoch(train) [922][60/63] lr: 5.8053e-04 eta: 3:04:45 time: 1.1011 data_time: 0.0299 memory: 14901 loss: 0.9973 loss_prob: 0.5214 loss_thr: 0.3845 loss_db: 0.0914 2022/11/02 22:59:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:00:09 - mmengine - INFO - Epoch(train) [923][5/63] lr: 5.7865e-04 eta: 3:04:45 time: 1.4707 data_time: 0.2532 memory: 14901 loss: 1.0475 loss_prob: 0.5534 loss_thr: 0.4008 loss_db: 0.0932 2022/11/02 23:00:14 - mmengine - INFO - Epoch(train) [923][10/63] lr: 5.7865e-04 eta: 3:04:39 time: 1.5771 data_time: 0.2726 memory: 14901 loss: 0.9608 loss_prob: 0.5054 loss_thr: 0.3691 loss_db: 0.0863 2022/11/02 23:00:21 - mmengine - INFO - Epoch(train) [923][15/63] lr: 5.7865e-04 eta: 3:04:39 time: 1.2878 data_time: 0.0366 memory: 14901 loss: 0.8567 loss_prob: 0.4360 loss_thr: 0.3433 loss_db: 0.0774 2022/11/02 23:00:27 - mmengine - INFO - Epoch(train) [923][20/63] lr: 5.7865e-04 eta: 3:04:35 time: 1.3537 data_time: 0.0180 memory: 14901 loss: 0.8494 loss_prob: 0.4250 loss_thr: 0.3507 loss_db: 0.0737 2022/11/02 23:00:34 - mmengine - INFO - Epoch(train) [923][25/63] lr: 5.7865e-04 eta: 3:04:35 time: 1.2708 data_time: 0.0378 memory: 14901 loss: 0.9364 loss_prob: 0.4817 loss_thr: 0.3713 loss_db: 0.0834 2022/11/02 23:00:39 - mmengine - INFO - Epoch(train) [923][30/63] lr: 5.7865e-04 eta: 3:04:31 time: 1.2030 data_time: 0.0409 memory: 14901 loss: 0.9436 loss_prob: 0.4872 loss_thr: 0.3712 loss_db: 0.0853 2022/11/02 23:00:43 - mmengine - INFO - Epoch(train) [923][35/63] lr: 5.7865e-04 eta: 3:04:31 time: 0.9367 data_time: 0.0277 memory: 14901 loss: 0.8882 loss_prob: 0.4529 loss_thr: 0.3556 loss_db: 0.0797 2022/11/02 23:00:48 - mmengine - INFO - Epoch(train) [923][40/63] lr: 5.7865e-04 eta: 3:04:25 time: 0.9174 data_time: 0.0244 memory: 14901 loss: 0.9436 loss_prob: 0.4890 loss_thr: 0.3685 loss_db: 0.0860 2022/11/02 23:00:53 - mmengine - INFO - Epoch(train) [923][45/63] lr: 5.7865e-04 eta: 3:04:25 time: 0.9943 data_time: 0.0105 memory: 14901 loss: 0.9652 loss_prob: 0.5055 loss_thr: 0.3722 loss_db: 0.0876 2022/11/02 23:01:01 - mmengine - INFO - Epoch(train) [923][50/63] lr: 5.7865e-04 eta: 3:04:21 time: 1.2807 data_time: 0.0259 memory: 14901 loss: 0.9374 loss_prob: 0.4874 loss_thr: 0.3653 loss_db: 0.0846 2022/11/02 23:01:06 - mmengine - INFO - Epoch(train) [923][55/63] lr: 5.7865e-04 eta: 3:04:21 time: 1.2317 data_time: 0.0359 memory: 14901 loss: 0.9323 loss_prob: 0.4849 loss_thr: 0.3623 loss_db: 0.0852 2022/11/02 23:01:12 - mmengine - INFO - Epoch(train) [923][60/63] lr: 5.7865e-04 eta: 3:04:16 time: 1.0469 data_time: 0.0244 memory: 14901 loss: 0.8960 loss_prob: 0.4570 loss_thr: 0.3581 loss_db: 0.0809 2022/11/02 23:01:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:01:24 - mmengine - INFO - Epoch(train) [924][5/63] lr: 5.7677e-04 eta: 3:04:16 time: 1.3506 data_time: 0.2853 memory: 14901 loss: 0.9660 loss_prob: 0.5086 loss_thr: 0.3698 loss_db: 0.0876 2022/11/02 23:01:31 - mmengine - INFO - Epoch(train) [924][10/63] lr: 5.7677e-04 eta: 3:04:10 time: 1.5747 data_time: 0.2903 memory: 14901 loss: 0.9075 loss_prob: 0.4743 loss_thr: 0.3523 loss_db: 0.0810 2022/11/02 23:01:35 - mmengine - INFO - Epoch(train) [924][15/63] lr: 5.7677e-04 eta: 3:04:10 time: 1.1017 data_time: 0.0175 memory: 14901 loss: 0.8578 loss_prob: 0.4398 loss_thr: 0.3423 loss_db: 0.0758 2022/11/02 23:01:42 - mmengine - INFO - Epoch(train) [924][20/63] lr: 5.7677e-04 eta: 3:04:05 time: 1.1441 data_time: 0.0291 memory: 14901 loss: 0.9657 loss_prob: 0.5125 loss_thr: 0.3652 loss_db: 0.0880 2022/11/02 23:01:49 - mmengine - INFO - Epoch(train) [924][25/63] lr: 5.7677e-04 eta: 3:04:05 time: 1.4002 data_time: 0.0627 memory: 14901 loss: 1.0590 loss_prob: 0.5586 loss_thr: 0.4038 loss_db: 0.0967 2022/11/02 23:01:53 - mmengine - INFO - Epoch(train) [924][30/63] lr: 5.7677e-04 eta: 3:04:00 time: 1.0884 data_time: 0.0588 memory: 14901 loss: 0.9616 loss_prob: 0.4882 loss_thr: 0.3875 loss_db: 0.0860 2022/11/02 23:01:58 - mmengine - INFO - Epoch(train) [924][35/63] lr: 5.7677e-04 eta: 3:04:00 time: 0.9225 data_time: 0.0233 memory: 14901 loss: 0.9710 loss_prob: 0.5049 loss_thr: 0.3762 loss_db: 0.0899 2022/11/02 23:02:05 - mmengine - INFO - Epoch(train) [924][40/63] lr: 5.7677e-04 eta: 3:03:55 time: 1.1814 data_time: 0.0160 memory: 14901 loss: 1.0044 loss_prob: 0.5301 loss_thr: 0.3809 loss_db: 0.0935 2022/11/02 23:02:10 - mmengine - INFO - Epoch(train) [924][45/63] lr: 5.7677e-04 eta: 3:03:55 time: 1.2029 data_time: 0.0252 memory: 14901 loss: 0.9845 loss_prob: 0.5257 loss_thr: 0.3689 loss_db: 0.0899 2022/11/02 23:02:17 - mmengine - INFO - Epoch(train) [924][50/63] lr: 5.7677e-04 eta: 3:03:50 time: 1.1732 data_time: 0.0308 memory: 14901 loss: 0.9565 loss_prob: 0.5051 loss_thr: 0.3642 loss_db: 0.0871 2022/11/02 23:02:24 - mmengine - INFO - Epoch(train) [924][55/63] lr: 5.7677e-04 eta: 3:03:50 time: 1.3759 data_time: 0.0313 memory: 14901 loss: 0.9299 loss_prob: 0.4897 loss_thr: 0.3563 loss_db: 0.0839 2022/11/02 23:02:31 - mmengine - INFO - Epoch(train) [924][60/63] lr: 5.7677e-04 eta: 3:03:46 time: 1.3724 data_time: 0.0215 memory: 14901 loss: 0.9587 loss_prob: 0.5050 loss_thr: 0.3676 loss_db: 0.0861 2022/11/02 23:02:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:02:41 - mmengine - INFO - Epoch(train) [925][5/63] lr: 5.7489e-04 eta: 3:03:46 time: 1.2637 data_time: 0.2579 memory: 14901 loss: 0.9508 loss_prob: 0.4940 loss_thr: 0.3705 loss_db: 0.0863 2022/11/02 23:02:48 - mmengine - INFO - Epoch(train) [925][10/63] lr: 5.7489e-04 eta: 3:03:40 time: 1.5764 data_time: 0.2708 memory: 14901 loss: 0.9457 loss_prob: 0.4889 loss_thr: 0.3709 loss_db: 0.0858 2022/11/02 23:02:54 - mmengine - INFO - Epoch(train) [925][15/63] lr: 5.7489e-04 eta: 3:03:40 time: 1.3239 data_time: 0.0264 memory: 14901 loss: 0.9651 loss_prob: 0.5085 loss_thr: 0.3692 loss_db: 0.0874 2022/11/02 23:02:59 - mmengine - INFO - Epoch(train) [925][20/63] lr: 5.7489e-04 eta: 3:03:35 time: 1.0903 data_time: 0.0143 memory: 14901 loss: 0.9089 loss_prob: 0.4708 loss_thr: 0.3560 loss_db: 0.0821 2022/11/02 23:03:03 - mmengine - INFO - Epoch(train) [925][25/63] lr: 5.7489e-04 eta: 3:03:35 time: 0.9022 data_time: 0.0135 memory: 14901 loss: 0.8908 loss_prob: 0.4507 loss_thr: 0.3611 loss_db: 0.0790 2022/11/02 23:03:08 - mmengine - INFO - Epoch(train) [925][30/63] lr: 5.7489e-04 eta: 3:03:30 time: 0.8632 data_time: 0.0443 memory: 14901 loss: 0.9245 loss_prob: 0.4807 loss_thr: 0.3595 loss_db: 0.0843 2022/11/02 23:03:13 - mmengine - INFO - Epoch(train) [925][35/63] lr: 5.7489e-04 eta: 3:03:30 time: 1.0297 data_time: 0.0534 memory: 14901 loss: 0.9892 loss_prob: 0.5203 loss_thr: 0.3794 loss_db: 0.0895 2022/11/02 23:03:19 - mmengine - INFO - Epoch(train) [925][40/63] lr: 5.7489e-04 eta: 3:03:25 time: 1.1483 data_time: 0.0213 memory: 14901 loss: 0.9330 loss_prob: 0.4792 loss_thr: 0.3719 loss_db: 0.0819 2022/11/02 23:03:24 - mmengine - INFO - Epoch(train) [925][45/63] lr: 5.7489e-04 eta: 3:03:25 time: 1.0560 data_time: 0.0192 memory: 14901 loss: 0.9292 loss_prob: 0.4780 loss_thr: 0.3671 loss_db: 0.0841 2022/11/02 23:03:30 - mmengine - INFO - Epoch(train) [925][50/63] lr: 5.7489e-04 eta: 3:03:20 time: 1.1069 data_time: 0.0401 memory: 14901 loss: 1.0508 loss_prob: 0.5429 loss_thr: 0.4133 loss_db: 0.0947 2022/11/02 23:03:35 - mmengine - INFO - Epoch(train) [925][55/63] lr: 5.7489e-04 eta: 3:03:20 time: 1.0906 data_time: 0.0311 memory: 14901 loss: 1.0129 loss_prob: 0.5212 loss_thr: 0.4019 loss_db: 0.0898 2022/11/02 23:03:41 - mmengine - INFO - Epoch(train) [925][60/63] lr: 5.7489e-04 eta: 3:03:15 time: 1.0255 data_time: 0.0214 memory: 14901 loss: 0.9279 loss_prob: 0.4759 loss_thr: 0.3686 loss_db: 0.0833 2022/11/02 23:03:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:03:52 - mmengine - INFO - Epoch(train) [926][5/63] lr: 5.7301e-04 eta: 3:03:15 time: 1.5459 data_time: 0.2722 memory: 14901 loss: 0.8731 loss_prob: 0.4484 loss_thr: 0.3450 loss_db: 0.0797 2022/11/02 23:03:58 - mmengine - INFO - Epoch(train) [926][10/63] lr: 5.7301e-04 eta: 3:03:08 time: 1.4161 data_time: 0.2816 memory: 14901 loss: 0.8694 loss_prob: 0.4428 loss_thr: 0.3511 loss_db: 0.0755 2022/11/02 23:04:03 - mmengine - INFO - Epoch(train) [926][15/63] lr: 5.7301e-04 eta: 3:03:08 time: 1.0283 data_time: 0.0219 memory: 14901 loss: 0.9110 loss_prob: 0.4597 loss_thr: 0.3734 loss_db: 0.0778 2022/11/02 23:04:09 - mmengine - INFO - Epoch(train) [926][20/63] lr: 5.7301e-04 eta: 3:03:03 time: 1.1460 data_time: 0.0106 memory: 14901 loss: 0.9298 loss_prob: 0.4779 loss_thr: 0.3680 loss_db: 0.0839 2022/11/02 23:04:14 - mmengine - INFO - Epoch(train) [926][25/63] lr: 5.7301e-04 eta: 3:03:03 time: 1.0875 data_time: 0.0257 memory: 14901 loss: 0.9846 loss_prob: 0.5153 loss_thr: 0.3788 loss_db: 0.0905 2022/11/02 23:04:20 - mmengine - INFO - Epoch(train) [926][30/63] lr: 5.7301e-04 eta: 3:02:58 time: 1.0393 data_time: 0.0422 memory: 14901 loss: 0.9563 loss_prob: 0.4946 loss_thr: 0.3769 loss_db: 0.0848 2022/11/02 23:04:25 - mmengine - INFO - Epoch(train) [926][35/63] lr: 5.7301e-04 eta: 3:02:58 time: 1.0918 data_time: 0.0374 memory: 14901 loss: 0.8893 loss_prob: 0.4485 loss_thr: 0.3627 loss_db: 0.0781 2022/11/02 23:04:31 - mmengine - INFO - Epoch(train) [926][40/63] lr: 5.7301e-04 eta: 3:02:54 time: 1.1842 data_time: 0.0248 memory: 14901 loss: 0.9502 loss_prob: 0.4888 loss_thr: 0.3767 loss_db: 0.0846 2022/11/02 23:04:38 - mmengine - INFO - Epoch(train) [926][45/63] lr: 5.7301e-04 eta: 3:02:54 time: 1.3423 data_time: 0.0139 memory: 14901 loss: 0.9821 loss_prob: 0.5137 loss_thr: 0.3806 loss_db: 0.0879 2022/11/02 23:04:46 - mmengine - INFO - Epoch(train) [926][50/63] lr: 5.7301e-04 eta: 3:02:50 time: 1.4210 data_time: 0.0237 memory: 14901 loss: 0.9869 loss_prob: 0.5077 loss_thr: 0.3884 loss_db: 0.0908 2022/11/02 23:04:53 - mmengine - INFO - Epoch(train) [926][55/63] lr: 5.7301e-04 eta: 3:02:50 time: 1.5286 data_time: 0.0291 memory: 14901 loss: 1.0727 loss_prob: 0.5681 loss_thr: 0.4082 loss_db: 0.0964 2022/11/02 23:04:57 - mmengine - INFO - Epoch(train) [926][60/63] lr: 5.7301e-04 eta: 3:02:45 time: 1.1488 data_time: 0.0229 memory: 14901 loss: 1.0175 loss_prob: 0.5435 loss_thr: 0.3855 loss_db: 0.0885 2022/11/02 23:05:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:05:13 - mmengine - INFO - Epoch(train) [927][5/63] lr: 5.7113e-04 eta: 3:02:45 time: 1.7459 data_time: 0.2564 memory: 14901 loss: 0.9957 loss_prob: 0.5281 loss_thr: 0.3738 loss_db: 0.0938 2022/11/02 23:05:18 - mmengine - INFO - Epoch(train) [927][10/63] lr: 5.7113e-04 eta: 3:02:39 time: 1.6565 data_time: 0.2530 memory: 14901 loss: 0.9417 loss_prob: 0.4918 loss_thr: 0.3669 loss_db: 0.0830 2022/11/02 23:05:26 - mmengine - INFO - Epoch(train) [927][15/63] lr: 5.7113e-04 eta: 3:02:39 time: 1.2955 data_time: 0.0233 memory: 14901 loss: 0.9370 loss_prob: 0.4964 loss_thr: 0.3580 loss_db: 0.0825 2022/11/02 23:05:29 - mmengine - INFO - Epoch(train) [927][20/63] lr: 5.7113e-04 eta: 3:02:34 time: 1.0670 data_time: 0.0208 memory: 14901 loss: 0.9942 loss_prob: 0.5231 loss_thr: 0.3814 loss_db: 0.0897 2022/11/02 23:05:36 - mmengine - INFO - Epoch(train) [927][25/63] lr: 5.7113e-04 eta: 3:02:34 time: 0.9800 data_time: 0.0445 memory: 14901 loss: 0.9743 loss_prob: 0.5008 loss_thr: 0.3858 loss_db: 0.0877 2022/11/02 23:05:41 - mmengine - INFO - Epoch(train) [927][30/63] lr: 5.7113e-04 eta: 3:02:29 time: 1.2255 data_time: 0.0554 memory: 14901 loss: 0.9774 loss_prob: 0.5053 loss_thr: 0.3841 loss_db: 0.0881 2022/11/02 23:05:47 - mmengine - INFO - Epoch(train) [927][35/63] lr: 5.7113e-04 eta: 3:02:29 time: 1.0729 data_time: 0.0196 memory: 14901 loss: 1.0004 loss_prob: 0.5202 loss_thr: 0.3898 loss_db: 0.0904 2022/11/02 23:05:56 - mmengine - INFO - Epoch(train) [927][40/63] lr: 5.7113e-04 eta: 3:02:25 time: 1.4441 data_time: 0.0154 memory: 14901 loss: 0.9951 loss_prob: 0.5188 loss_thr: 0.3861 loss_db: 0.0903 2022/11/02 23:05:59 - mmengine - INFO - Epoch(train) [927][45/63] lr: 5.7113e-04 eta: 3:02:25 time: 1.2366 data_time: 0.0155 memory: 14901 loss: 0.9727 loss_prob: 0.5111 loss_thr: 0.3740 loss_db: 0.0876 2022/11/02 23:06:06 - mmengine - INFO - Epoch(train) [927][50/63] lr: 5.7113e-04 eta: 3:02:20 time: 1.0043 data_time: 0.0305 memory: 14901 loss: 0.9243 loss_prob: 0.4806 loss_thr: 0.3616 loss_db: 0.0822 2022/11/02 23:06:11 - mmengine - INFO - Epoch(train) [927][55/63] lr: 5.7113e-04 eta: 3:02:20 time: 1.1809 data_time: 0.0336 memory: 14901 loss: 0.9357 loss_prob: 0.4869 loss_thr: 0.3628 loss_db: 0.0860 2022/11/02 23:06:16 - mmengine - INFO - Epoch(train) [927][60/63] lr: 5.7113e-04 eta: 3:02:15 time: 1.0080 data_time: 0.0121 memory: 14901 loss: 0.9931 loss_prob: 0.5154 loss_thr: 0.3867 loss_db: 0.0910 2022/11/02 23:06:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:06:26 - mmengine - INFO - Epoch(train) [928][5/63] lr: 5.6924e-04 eta: 3:02:15 time: 1.1591 data_time: 0.2754 memory: 14901 loss: 0.9253 loss_prob: 0.4755 loss_thr: 0.3653 loss_db: 0.0845 2022/11/02 23:06:31 - mmengine - INFO - Epoch(train) [928][10/63] lr: 5.6924e-04 eta: 3:02:08 time: 1.2004 data_time: 0.2767 memory: 14901 loss: 0.9656 loss_prob: 0.5014 loss_thr: 0.3779 loss_db: 0.0862 2022/11/02 23:06:38 - mmengine - INFO - Epoch(train) [928][15/63] lr: 5.6924e-04 eta: 3:02:08 time: 1.1815 data_time: 0.0340 memory: 14901 loss: 1.0467 loss_prob: 0.5509 loss_thr: 0.3990 loss_db: 0.0968 2022/11/02 23:06:45 - mmengine - INFO - Epoch(train) [928][20/63] lr: 5.6924e-04 eta: 3:02:03 time: 1.3396 data_time: 0.0295 memory: 14901 loss: 1.0293 loss_prob: 0.5372 loss_thr: 0.3963 loss_db: 0.0958 2022/11/02 23:06:48 - mmengine - INFO - Epoch(train) [928][25/63] lr: 5.6924e-04 eta: 3:02:03 time: 0.9766 data_time: 0.0374 memory: 14901 loss: 0.9842 loss_prob: 0.5114 loss_thr: 0.3854 loss_db: 0.0874 2022/11/02 23:06:54 - mmengine - INFO - Epoch(train) [928][30/63] lr: 5.6924e-04 eta: 3:01:58 time: 0.9358 data_time: 0.0346 memory: 14901 loss: 0.9246 loss_prob: 0.4779 loss_thr: 0.3646 loss_db: 0.0821 2022/11/02 23:07:00 - mmengine - INFO - Epoch(train) [928][35/63] lr: 5.6924e-04 eta: 3:01:58 time: 1.2702 data_time: 0.0249 memory: 14901 loss: 0.9087 loss_prob: 0.4655 loss_thr: 0.3596 loss_db: 0.0835 2022/11/02 23:07:05 - mmengine - INFO - Epoch(train) [928][40/63] lr: 5.6924e-04 eta: 3:01:53 time: 1.0938 data_time: 0.0241 memory: 14901 loss: 0.9157 loss_prob: 0.4733 loss_thr: 0.3580 loss_db: 0.0844 2022/11/02 23:07:09 - mmengine - INFO - Epoch(train) [928][45/63] lr: 5.6924e-04 eta: 3:01:53 time: 0.8307 data_time: 0.0095 memory: 14901 loss: 0.8764 loss_prob: 0.4563 loss_thr: 0.3403 loss_db: 0.0798 2022/11/02 23:07:14 - mmengine - INFO - Epoch(train) [928][50/63] lr: 5.6924e-04 eta: 3:01:47 time: 0.9294 data_time: 0.0594 memory: 14901 loss: 0.8822 loss_prob: 0.4570 loss_thr: 0.3456 loss_db: 0.0796 2022/11/02 23:07:22 - mmengine - INFO - Epoch(train) [928][55/63] lr: 5.6924e-04 eta: 3:01:47 time: 1.3155 data_time: 0.0593 memory: 14901 loss: 0.9176 loss_prob: 0.4769 loss_thr: 0.3569 loss_db: 0.0838 2022/11/02 23:07:28 - mmengine - INFO - Epoch(train) [928][60/63] lr: 5.6924e-04 eta: 3:01:43 time: 1.3655 data_time: 0.0123 memory: 14901 loss: 0.9145 loss_prob: 0.4774 loss_thr: 0.3535 loss_db: 0.0836 2022/11/02 23:07:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:07:42 - mmengine - INFO - Epoch(train) [929][5/63] lr: 5.6736e-04 eta: 3:01:43 time: 1.8112 data_time: 0.3156 memory: 14901 loss: 0.8572 loss_prob: 0.4339 loss_thr: 0.3479 loss_db: 0.0754 2022/11/02 23:07:50 - mmengine - INFO - Epoch(train) [929][10/63] lr: 5.6736e-04 eta: 3:01:38 time: 1.7953 data_time: 0.3143 memory: 14901 loss: 0.8796 loss_prob: 0.4505 loss_thr: 0.3501 loss_db: 0.0791 2022/11/02 23:07:56 - mmengine - INFO - Epoch(train) [929][15/63] lr: 5.6736e-04 eta: 3:01:38 time: 1.4184 data_time: 0.0124 memory: 14901 loss: 0.9204 loss_prob: 0.4765 loss_thr: 0.3610 loss_db: 0.0829 2022/11/02 23:08:02 - mmengine - INFO - Epoch(train) [929][20/63] lr: 5.6736e-04 eta: 3:01:33 time: 1.2115 data_time: 0.0108 memory: 14901 loss: 0.8574 loss_prob: 0.4399 loss_thr: 0.3407 loss_db: 0.0768 2022/11/02 23:08:07 - mmengine - INFO - Epoch(train) [929][25/63] lr: 5.6736e-04 eta: 3:01:33 time: 1.0328 data_time: 0.0351 memory: 14901 loss: 0.9106 loss_prob: 0.4717 loss_thr: 0.3556 loss_db: 0.0832 2022/11/02 23:08:12 - mmengine - INFO - Epoch(train) [929][30/63] lr: 5.6736e-04 eta: 3:01:28 time: 1.0181 data_time: 0.0518 memory: 14901 loss: 1.0579 loss_prob: 0.5590 loss_thr: 0.4038 loss_db: 0.0950 2022/11/02 23:08:19 - mmengine - INFO - Epoch(train) [929][35/63] lr: 5.6736e-04 eta: 3:01:28 time: 1.1848 data_time: 0.0278 memory: 14901 loss: 0.9801 loss_prob: 0.5063 loss_thr: 0.3867 loss_db: 0.0871 2022/11/02 23:08:22 - mmengine - INFO - Epoch(train) [929][40/63] lr: 5.6736e-04 eta: 3:01:22 time: 1.0402 data_time: 0.0150 memory: 14901 loss: 0.9693 loss_prob: 0.5009 loss_thr: 0.3798 loss_db: 0.0886 2022/11/02 23:08:30 - mmengine - INFO - Epoch(train) [929][45/63] lr: 5.6736e-04 eta: 3:01:22 time: 1.1239 data_time: 0.0120 memory: 14901 loss: 0.9768 loss_prob: 0.5159 loss_thr: 0.3727 loss_db: 0.0882 2022/11/02 23:08:34 - mmengine - INFO - Epoch(train) [929][50/63] lr: 5.6736e-04 eta: 3:01:18 time: 1.1544 data_time: 0.0344 memory: 14901 loss: 0.9335 loss_prob: 0.4897 loss_thr: 0.3578 loss_db: 0.0860 2022/11/02 23:08:40 - mmengine - INFO - Epoch(train) [929][55/63] lr: 5.6736e-04 eta: 3:01:18 time: 1.0695 data_time: 0.0366 memory: 14901 loss: 0.9586 loss_prob: 0.4909 loss_thr: 0.3795 loss_db: 0.0882 2022/11/02 23:08:44 - mmengine - INFO - Epoch(train) [929][60/63] lr: 5.6736e-04 eta: 3:01:12 time: 1.0133 data_time: 0.0120 memory: 14901 loss: 0.9794 loss_prob: 0.5043 loss_thr: 0.3864 loss_db: 0.0887 2022/11/02 23:08:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:08:57 - mmengine - INFO - Epoch(train) [930][5/63] lr: 5.6548e-04 eta: 3:01:12 time: 1.4969 data_time: 0.2513 memory: 14901 loss: 0.9046 loss_prob: 0.4616 loss_thr: 0.3615 loss_db: 0.0815 2022/11/02 23:09:02 - mmengine - INFO - Epoch(train) [930][10/63] lr: 5.6548e-04 eta: 3:01:06 time: 1.3577 data_time: 0.2563 memory: 14901 loss: 0.8722 loss_prob: 0.4421 loss_thr: 0.3524 loss_db: 0.0777 2022/11/02 23:09:09 - mmengine - INFO - Epoch(train) [930][15/63] lr: 5.6548e-04 eta: 3:01:06 time: 1.2171 data_time: 0.0245 memory: 14901 loss: 0.9498 loss_prob: 0.4831 loss_thr: 0.3816 loss_db: 0.0852 2022/11/02 23:09:15 - mmengine - INFO - Epoch(train) [930][20/63] lr: 5.6548e-04 eta: 3:01:01 time: 1.2685 data_time: 0.0218 memory: 14901 loss: 0.9917 loss_prob: 0.5150 loss_thr: 0.3864 loss_db: 0.0903 2022/11/02 23:09:20 - mmengine - INFO - Epoch(train) [930][25/63] lr: 5.6548e-04 eta: 3:01:01 time: 1.0414 data_time: 0.0181 memory: 14901 loss: 0.9824 loss_prob: 0.5219 loss_thr: 0.3712 loss_db: 0.0893 2022/11/02 23:09:23 - mmengine - INFO - Epoch(train) [930][30/63] lr: 5.6548e-04 eta: 3:00:55 time: 0.8538 data_time: 0.0540 memory: 14901 loss: 0.9618 loss_prob: 0.5059 loss_thr: 0.3691 loss_db: 0.0868 2022/11/02 23:09:31 - mmengine - INFO - Epoch(train) [930][35/63] lr: 5.6548e-04 eta: 3:00:55 time: 1.0969 data_time: 0.0511 memory: 14901 loss: 1.0928 loss_prob: 0.5899 loss_thr: 0.4033 loss_db: 0.0997 2022/11/02 23:09:35 - mmengine - INFO - Epoch(train) [930][40/63] lr: 5.6548e-04 eta: 3:00:51 time: 1.2351 data_time: 0.0202 memory: 14901 loss: 1.0313 loss_prob: 0.5520 loss_thr: 0.3837 loss_db: 0.0956 2022/11/02 23:09:43 - mmengine - INFO - Epoch(train) [930][45/63] lr: 5.6548e-04 eta: 3:00:51 time: 1.2013 data_time: 0.0180 memory: 14901 loss: 0.8727 loss_prob: 0.4539 loss_thr: 0.3380 loss_db: 0.0808 2022/11/02 23:09:49 - mmengine - INFO - Epoch(train) [930][50/63] lr: 5.6548e-04 eta: 3:00:46 time: 1.3620 data_time: 0.0240 memory: 14901 loss: 0.9601 loss_prob: 0.5041 loss_thr: 0.3693 loss_db: 0.0867 2022/11/02 23:09:56 - mmengine - INFO - Epoch(train) [930][55/63] lr: 5.6548e-04 eta: 3:00:46 time: 1.3670 data_time: 0.0278 memory: 14901 loss: 0.9380 loss_prob: 0.4890 loss_thr: 0.3637 loss_db: 0.0852 2022/11/02 23:10:01 - mmengine - INFO - Epoch(train) [930][60/63] lr: 5.6548e-04 eta: 3:00:42 time: 1.2276 data_time: 0.0162 memory: 14901 loss: 0.8797 loss_prob: 0.4586 loss_thr: 0.3419 loss_db: 0.0792 2022/11/02 23:10:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:10:15 - mmengine - INFO - Epoch(train) [931][5/63] lr: 5.6359e-04 eta: 3:00:42 time: 1.7196 data_time: 0.2601 memory: 14901 loss: 0.9814 loss_prob: 0.5119 loss_thr: 0.3803 loss_db: 0.0893 2022/11/02 23:10:19 - mmengine - INFO - Epoch(train) [931][10/63] lr: 5.6359e-04 eta: 3:00:36 time: 1.5525 data_time: 0.2606 memory: 14901 loss: 0.9722 loss_prob: 0.5083 loss_thr: 0.3758 loss_db: 0.0881 2022/11/02 23:10:28 - mmengine - INFO - Epoch(train) [931][15/63] lr: 5.6359e-04 eta: 3:00:36 time: 1.2776 data_time: 0.0129 memory: 14901 loss: 0.9979 loss_prob: 0.5246 loss_thr: 0.3830 loss_db: 0.0903 2022/11/02 23:10:34 - mmengine - INFO - Epoch(train) [931][20/63] lr: 5.6359e-04 eta: 3:00:31 time: 1.4139 data_time: 0.0130 memory: 14901 loss: 0.9497 loss_prob: 0.4934 loss_thr: 0.3703 loss_db: 0.0861 2022/11/02 23:10:41 - mmengine - INFO - Epoch(train) [931][25/63] lr: 5.6359e-04 eta: 3:00:31 time: 1.3215 data_time: 0.0335 memory: 14901 loss: 0.9718 loss_prob: 0.5093 loss_thr: 0.3748 loss_db: 0.0877 2022/11/02 23:10:47 - mmengine - INFO - Epoch(train) [931][30/63] lr: 5.6359e-04 eta: 3:00:27 time: 1.3758 data_time: 0.0456 memory: 14901 loss: 0.9826 loss_prob: 0.5178 loss_thr: 0.3775 loss_db: 0.0873 2022/11/02 23:10:53 - mmengine - INFO - Epoch(train) [931][35/63] lr: 5.6359e-04 eta: 3:00:27 time: 1.1238 data_time: 0.0299 memory: 14901 loss: 0.9279 loss_prob: 0.4831 loss_thr: 0.3612 loss_db: 0.0836 2022/11/02 23:11:01 - mmengine - INFO - Epoch(train) [931][40/63] lr: 5.6359e-04 eta: 3:00:23 time: 1.3112 data_time: 0.0176 memory: 14901 loss: 0.8790 loss_prob: 0.4497 loss_thr: 0.3500 loss_db: 0.0793 2022/11/02 23:11:04 - mmengine - INFO - Epoch(train) [931][45/63] lr: 5.6359e-04 eta: 3:00:23 time: 1.1693 data_time: 0.0151 memory: 14901 loss: 0.9515 loss_prob: 0.4892 loss_thr: 0.3782 loss_db: 0.0842 2022/11/02 23:11:12 - mmengine - INFO - Epoch(train) [931][50/63] lr: 5.6359e-04 eta: 3:00:18 time: 1.1918 data_time: 0.0491 memory: 14901 loss: 0.9527 loss_prob: 0.4994 loss_thr: 0.3673 loss_db: 0.0860 2022/11/02 23:11:17 - mmengine - INFO - Epoch(train) [931][55/63] lr: 5.6359e-04 eta: 3:00:18 time: 1.2795 data_time: 0.0489 memory: 14901 loss: 1.0629 loss_prob: 0.5990 loss_thr: 0.3678 loss_db: 0.0961 2022/11/02 23:11:22 - mmengine - INFO - Epoch(train) [931][60/63] lr: 5.6359e-04 eta: 3:00:13 time: 0.9546 data_time: 0.0178 memory: 14901 loss: 1.0988 loss_prob: 0.6109 loss_thr: 0.3898 loss_db: 0.0981 2022/11/02 23:11:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:11:38 - mmengine - INFO - Epoch(train) [932][5/63] lr: 5.6171e-04 eta: 3:00:13 time: 1.9109 data_time: 0.2910 memory: 14901 loss: 0.9791 loss_prob: 0.5133 loss_thr: 0.3749 loss_db: 0.0909 2022/11/02 23:11:43 - mmengine - INFO - Epoch(train) [932][10/63] lr: 5.6171e-04 eta: 3:00:07 time: 1.7057 data_time: 0.2901 memory: 14901 loss: 0.9876 loss_prob: 0.5178 loss_thr: 0.3798 loss_db: 0.0901 2022/11/02 23:11:48 - mmengine - INFO - Epoch(train) [932][15/63] lr: 5.6171e-04 eta: 3:00:07 time: 0.9939 data_time: 0.0264 memory: 14901 loss: 0.9870 loss_prob: 0.5136 loss_thr: 0.3846 loss_db: 0.0887 2022/11/02 23:11:55 - mmengine - INFO - Epoch(train) [932][20/63] lr: 5.6171e-04 eta: 3:00:02 time: 1.1594 data_time: 0.0240 memory: 14901 loss: 0.9053 loss_prob: 0.4705 loss_thr: 0.3534 loss_db: 0.0814 2022/11/02 23:11:59 - mmengine - INFO - Epoch(train) [932][25/63] lr: 5.6171e-04 eta: 3:00:02 time: 1.1147 data_time: 0.0113 memory: 14901 loss: 0.9121 loss_prob: 0.4751 loss_thr: 0.3551 loss_db: 0.0820 2022/11/02 23:12:06 - mmengine - INFO - Epoch(train) [932][30/63] lr: 5.6171e-04 eta: 2:59:57 time: 1.1132 data_time: 0.0191 memory: 14901 loss: 0.9447 loss_prob: 0.4873 loss_thr: 0.3718 loss_db: 0.0856 2022/11/02 23:12:09 - mmengine - INFO - Epoch(train) [932][35/63] lr: 5.6171e-04 eta: 2:59:57 time: 1.0444 data_time: 0.0163 memory: 14901 loss: 0.9275 loss_prob: 0.4723 loss_thr: 0.3717 loss_db: 0.0835 2022/11/02 23:12:16 - mmengine - INFO - Epoch(train) [932][40/63] lr: 5.6171e-04 eta: 2:59:52 time: 1.0164 data_time: 0.0232 memory: 14901 loss: 0.9947 loss_prob: 0.5232 loss_thr: 0.3810 loss_db: 0.0905 2022/11/02 23:12:21 - mmengine - INFO - Epoch(train) [932][45/63] lr: 5.6171e-04 eta: 2:59:52 time: 1.1766 data_time: 0.0278 memory: 14901 loss: 1.0010 loss_prob: 0.5298 loss_thr: 0.3809 loss_db: 0.0903 2022/11/02 23:12:27 - mmengine - INFO - Epoch(train) [932][50/63] lr: 5.6171e-04 eta: 2:59:47 time: 1.1334 data_time: 0.0126 memory: 14901 loss: 0.9965 loss_prob: 0.5237 loss_thr: 0.3835 loss_db: 0.0894 2022/11/02 23:12:32 - mmengine - INFO - Epoch(train) [932][55/63] lr: 5.6171e-04 eta: 2:59:47 time: 1.1199 data_time: 0.0178 memory: 14901 loss: 1.0089 loss_prob: 0.5264 loss_thr: 0.3907 loss_db: 0.0918 2022/11/02 23:12:37 - mmengine - INFO - Epoch(train) [932][60/63] lr: 5.6171e-04 eta: 2:59:41 time: 0.9534 data_time: 0.0211 memory: 14901 loss: 0.9452 loss_prob: 0.4892 loss_thr: 0.3698 loss_db: 0.0862 2022/11/02 23:12:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:12:51 - mmengine - INFO - Epoch(train) [933][5/63] lr: 5.5982e-04 eta: 2:59:41 time: 1.5352 data_time: 0.2907 memory: 14901 loss: 0.9263 loss_prob: 0.4925 loss_thr: 0.3499 loss_db: 0.0839 2022/11/02 23:12:56 - mmengine - INFO - Epoch(train) [933][10/63] lr: 5.5982e-04 eta: 2:59:35 time: 1.6908 data_time: 0.2931 memory: 14901 loss: 0.9287 loss_prob: 0.4872 loss_thr: 0.3552 loss_db: 0.0863 2022/11/02 23:13:04 - mmengine - INFO - Epoch(train) [933][15/63] lr: 5.5982e-04 eta: 2:59:35 time: 1.2717 data_time: 0.0168 memory: 14901 loss: 0.8775 loss_prob: 0.4370 loss_thr: 0.3621 loss_db: 0.0784 2022/11/02 23:13:09 - mmengine - INFO - Epoch(train) [933][20/63] lr: 5.5982e-04 eta: 2:59:31 time: 1.3140 data_time: 0.0190 memory: 14901 loss: 0.9921 loss_prob: 0.5082 loss_thr: 0.3977 loss_db: 0.0862 2022/11/02 23:13:15 - mmengine - INFO - Epoch(train) [933][25/63] lr: 5.5982e-04 eta: 2:59:31 time: 1.0977 data_time: 0.0386 memory: 14901 loss: 0.9489 loss_prob: 0.4894 loss_thr: 0.3759 loss_db: 0.0836 2022/11/02 23:13:19 - mmengine - INFO - Epoch(train) [933][30/63] lr: 5.5982e-04 eta: 2:59:26 time: 1.0010 data_time: 0.0485 memory: 14901 loss: 1.0246 loss_prob: 0.5425 loss_thr: 0.3910 loss_db: 0.0911 2022/11/02 23:13:24 - mmengine - INFO - Epoch(train) [933][35/63] lr: 5.5982e-04 eta: 2:59:26 time: 0.9629 data_time: 0.0276 memory: 14901 loss: 1.1128 loss_prob: 0.5956 loss_thr: 0.4171 loss_db: 0.1000 2022/11/02 23:13:30 - mmengine - INFO - Epoch(train) [933][40/63] lr: 5.5982e-04 eta: 2:59:21 time: 1.1160 data_time: 0.0103 memory: 14901 loss: 0.9744 loss_prob: 0.5057 loss_thr: 0.3803 loss_db: 0.0884 2022/11/02 23:13:36 - mmengine - INFO - Epoch(train) [933][45/63] lr: 5.5982e-04 eta: 2:59:21 time: 1.1533 data_time: 0.0144 memory: 14901 loss: 0.9233 loss_prob: 0.4811 loss_thr: 0.3569 loss_db: 0.0853 2022/11/02 23:13:41 - mmengine - INFO - Epoch(train) [933][50/63] lr: 5.5982e-04 eta: 2:59:15 time: 1.0375 data_time: 0.0284 memory: 14901 loss: 0.9118 loss_prob: 0.4780 loss_thr: 0.3505 loss_db: 0.0832 2022/11/02 23:13:48 - mmengine - INFO - Epoch(train) [933][55/63] lr: 5.5982e-04 eta: 2:59:15 time: 1.2066 data_time: 0.0292 memory: 14901 loss: 0.9542 loss_prob: 0.5052 loss_thr: 0.3630 loss_db: 0.0860 2022/11/02 23:13:55 - mmengine - INFO - Epoch(train) [933][60/63] lr: 5.5982e-04 eta: 2:59:11 time: 1.4066 data_time: 0.0170 memory: 14901 loss: 0.9691 loss_prob: 0.5150 loss_thr: 0.3646 loss_db: 0.0895 2022/11/02 23:13:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:14:08 - mmengine - INFO - Epoch(train) [934][5/63] lr: 5.5793e-04 eta: 2:59:11 time: 1.5585 data_time: 0.3102 memory: 14901 loss: 0.9514 loss_prob: 0.4968 loss_thr: 0.3674 loss_db: 0.0871 2022/11/02 23:14:16 - mmengine - INFO - Epoch(train) [934][10/63] lr: 5.5793e-04 eta: 2:59:06 time: 1.9649 data_time: 0.3103 memory: 14901 loss: 1.0174 loss_prob: 0.5340 loss_thr: 0.3906 loss_db: 0.0928 2022/11/02 23:14:22 - mmengine - INFO - Epoch(train) [934][15/63] lr: 5.5793e-04 eta: 2:59:06 time: 1.3811 data_time: 0.0141 memory: 14901 loss: 1.0277 loss_prob: 0.5358 loss_thr: 0.4009 loss_db: 0.0910 2022/11/02 23:14:30 - mmengine - INFO - Epoch(train) [934][20/63] lr: 5.5793e-04 eta: 2:59:02 time: 1.3833 data_time: 0.0110 memory: 14901 loss: 0.9959 loss_prob: 0.5149 loss_thr: 0.3924 loss_db: 0.0886 2022/11/02 23:14:35 - mmengine - INFO - Epoch(train) [934][25/63] lr: 5.5793e-04 eta: 2:59:02 time: 1.3277 data_time: 0.0189 memory: 14901 loss: 0.9854 loss_prob: 0.5144 loss_thr: 0.3789 loss_db: 0.0920 2022/11/02 23:14:38 - mmengine - INFO - Epoch(train) [934][30/63] lr: 5.5793e-04 eta: 2:58:56 time: 0.8641 data_time: 0.0438 memory: 14901 loss: 0.9357 loss_prob: 0.4830 loss_thr: 0.3671 loss_db: 0.0856 2022/11/02 23:14:46 - mmengine - INFO - Epoch(train) [934][35/63] lr: 5.5793e-04 eta: 2:58:56 time: 1.1076 data_time: 0.0363 memory: 14901 loss: 0.9345 loss_prob: 0.4764 loss_thr: 0.3753 loss_db: 0.0828 2022/11/02 23:14:52 - mmengine - INFO - Epoch(train) [934][40/63] lr: 5.5793e-04 eta: 2:58:52 time: 1.4067 data_time: 0.0122 memory: 14901 loss: 0.9320 loss_prob: 0.4848 loss_thr: 0.3623 loss_db: 0.0850 2022/11/02 23:14:58 - mmengine - INFO - Epoch(train) [934][45/63] lr: 5.5793e-04 eta: 2:58:52 time: 1.1494 data_time: 0.0112 memory: 14901 loss: 0.8296 loss_prob: 0.4290 loss_thr: 0.3260 loss_db: 0.0746 2022/11/02 23:15:03 - mmengine - INFO - Epoch(train) [934][50/63] lr: 5.5793e-04 eta: 2:58:47 time: 1.0526 data_time: 0.0544 memory: 14901 loss: 0.9139 loss_prob: 0.4805 loss_thr: 0.3503 loss_db: 0.0831 2022/11/02 23:15:10 - mmengine - INFO - Epoch(train) [934][55/63] lr: 5.5793e-04 eta: 2:58:47 time: 1.2026 data_time: 0.0537 memory: 14901 loss: 0.9661 loss_prob: 0.5096 loss_thr: 0.3673 loss_db: 0.0892 2022/11/02 23:15:17 - mmengine - INFO - Epoch(train) [934][60/63] lr: 5.5793e-04 eta: 2:58:42 time: 1.3715 data_time: 0.0106 memory: 14901 loss: 0.8894 loss_prob: 0.4622 loss_thr: 0.3459 loss_db: 0.0814 2022/11/02 23:15:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:15:28 - mmengine - INFO - Epoch(train) [935][5/63] lr: 5.5604e-04 eta: 2:58:42 time: 1.5001 data_time: 0.3114 memory: 14901 loss: 0.8903 loss_prob: 0.4566 loss_thr: 0.3559 loss_db: 0.0778 2022/11/02 23:15:34 - mmengine - INFO - Epoch(train) [935][10/63] lr: 5.5604e-04 eta: 2:58:36 time: 1.4303 data_time: 0.3114 memory: 14901 loss: 0.9637 loss_prob: 0.4973 loss_thr: 0.3808 loss_db: 0.0856 2022/11/02 23:15:40 - mmengine - INFO - Epoch(train) [935][15/63] lr: 5.5604e-04 eta: 2:58:36 time: 1.1325 data_time: 0.0117 memory: 14901 loss: 0.9428 loss_prob: 0.4879 loss_thr: 0.3692 loss_db: 0.0856 2022/11/02 23:15:46 - mmengine - INFO - Epoch(train) [935][20/63] lr: 5.5604e-04 eta: 2:58:31 time: 1.1580 data_time: 0.0126 memory: 14901 loss: 0.9151 loss_prob: 0.4718 loss_thr: 0.3602 loss_db: 0.0832 2022/11/02 23:15:52 - mmengine - INFO - Epoch(train) [935][25/63] lr: 5.5604e-04 eta: 2:58:31 time: 1.2666 data_time: 0.0240 memory: 14901 loss: 0.9656 loss_prob: 0.5033 loss_thr: 0.3753 loss_db: 0.0870 2022/11/02 23:15:58 - mmengine - INFO - Epoch(train) [935][30/63] lr: 5.5604e-04 eta: 2:58:26 time: 1.1500 data_time: 0.0489 memory: 14901 loss: 0.9950 loss_prob: 0.5217 loss_thr: 0.3837 loss_db: 0.0895 2022/11/02 23:16:03 - mmengine - INFO - Epoch(train) [935][35/63] lr: 5.5604e-04 eta: 2:58:26 time: 1.0599 data_time: 0.0389 memory: 14901 loss: 0.9666 loss_prob: 0.4979 loss_thr: 0.3815 loss_db: 0.0872 2022/11/02 23:16:07 - mmengine - INFO - Epoch(train) [935][40/63] lr: 5.5604e-04 eta: 2:58:20 time: 0.9546 data_time: 0.0136 memory: 14901 loss: 0.9376 loss_prob: 0.4759 loss_thr: 0.3779 loss_db: 0.0838 2022/11/02 23:16:14 - mmengine - INFO - Epoch(train) [935][45/63] lr: 5.5604e-04 eta: 2:58:20 time: 1.0629 data_time: 0.0143 memory: 14901 loss: 0.9590 loss_prob: 0.4955 loss_thr: 0.3770 loss_db: 0.0865 2022/11/02 23:16:19 - mmengine - INFO - Epoch(train) [935][50/63] lr: 5.5604e-04 eta: 2:58:15 time: 1.1893 data_time: 0.0260 memory: 14901 loss: 0.9165 loss_prob: 0.4725 loss_thr: 0.3616 loss_db: 0.0824 2022/11/02 23:16:25 - mmengine - INFO - Epoch(train) [935][55/63] lr: 5.5604e-04 eta: 2:58:15 time: 1.1709 data_time: 0.0386 memory: 14901 loss: 0.9083 loss_prob: 0.4717 loss_thr: 0.3538 loss_db: 0.0828 2022/11/02 23:16:32 - mmengine - INFO - Epoch(train) [935][60/63] lr: 5.5604e-04 eta: 2:58:11 time: 1.2870 data_time: 0.0264 memory: 14901 loss: 0.9793 loss_prob: 0.5148 loss_thr: 0.3752 loss_db: 0.0893 2022/11/02 23:16:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:16:46 - mmengine - INFO - Epoch(train) [936][5/63] lr: 5.5416e-04 eta: 2:58:11 time: 1.6743 data_time: 0.3323 memory: 14901 loss: 0.9390 loss_prob: 0.4930 loss_thr: 0.3611 loss_db: 0.0850 2022/11/02 23:16:54 - mmengine - INFO - Epoch(train) [936][10/63] lr: 5.5416e-04 eta: 2:58:06 time: 2.0571 data_time: 0.3404 memory: 14901 loss: 0.9122 loss_prob: 0.4793 loss_thr: 0.3501 loss_db: 0.0829 2022/11/02 23:16:57 - mmengine - INFO - Epoch(train) [936][15/63] lr: 5.5416e-04 eta: 2:58:06 time: 1.1052 data_time: 0.0198 memory: 14901 loss: 0.9095 loss_prob: 0.4719 loss_thr: 0.3548 loss_db: 0.0828 2022/11/02 23:17:05 - mmengine - INFO - Epoch(train) [936][20/63] lr: 5.5416e-04 eta: 2:58:01 time: 1.1201 data_time: 0.0129 memory: 14901 loss: 0.8420 loss_prob: 0.4313 loss_thr: 0.3342 loss_db: 0.0764 2022/11/02 23:17:11 - mmengine - INFO - Epoch(train) [936][25/63] lr: 5.5416e-04 eta: 2:58:01 time: 1.3698 data_time: 0.0344 memory: 14901 loss: 0.9381 loss_prob: 0.4871 loss_thr: 0.3655 loss_db: 0.0855 2022/11/02 23:17:16 - mmengine - INFO - Epoch(train) [936][30/63] lr: 5.5416e-04 eta: 2:57:56 time: 1.0518 data_time: 0.0423 memory: 14901 loss: 1.0499 loss_prob: 0.5529 loss_thr: 0.4013 loss_db: 0.0957 2022/11/02 23:17:21 - mmengine - INFO - Epoch(train) [936][35/63] lr: 5.5416e-04 eta: 2:57:56 time: 1.0460 data_time: 0.0204 memory: 14901 loss: 0.9200 loss_prob: 0.4775 loss_thr: 0.3592 loss_db: 0.0833 2022/11/02 23:17:26 - mmengine - INFO - Epoch(train) [936][40/63] lr: 5.5416e-04 eta: 2:57:51 time: 1.0674 data_time: 0.0161 memory: 14901 loss: 0.8768 loss_prob: 0.4496 loss_thr: 0.3485 loss_db: 0.0787 2022/11/02 23:17:33 - mmengine - INFO - Epoch(train) [936][45/63] lr: 5.5416e-04 eta: 2:57:51 time: 1.1538 data_time: 0.0159 memory: 14901 loss: 0.9400 loss_prob: 0.4816 loss_thr: 0.3740 loss_db: 0.0844 2022/11/02 23:17:39 - mmengine - INFO - Epoch(train) [936][50/63] lr: 5.5416e-04 eta: 2:57:46 time: 1.2556 data_time: 0.0255 memory: 14901 loss: 0.9442 loss_prob: 0.4840 loss_thr: 0.3754 loss_db: 0.0847 2022/11/02 23:17:45 - mmengine - INFO - Epoch(train) [936][55/63] lr: 5.5416e-04 eta: 2:57:46 time: 1.2461 data_time: 0.0338 memory: 14901 loss: 0.9408 loss_prob: 0.4858 loss_thr: 0.3698 loss_db: 0.0853 2022/11/02 23:17:51 - mmengine - INFO - Epoch(train) [936][60/63] lr: 5.5416e-04 eta: 2:57:41 time: 1.1593 data_time: 0.0228 memory: 14901 loss: 0.9408 loss_prob: 0.4879 loss_thr: 0.3669 loss_db: 0.0860 2022/11/02 23:17:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:18:00 - mmengine - INFO - Epoch(train) [937][5/63] lr: 5.5227e-04 eta: 2:57:41 time: 1.0126 data_time: 0.2367 memory: 14901 loss: 0.9085 loss_prob: 0.4696 loss_thr: 0.3573 loss_db: 0.0816 2022/11/02 23:18:04 - mmengine - INFO - Epoch(train) [937][10/63] lr: 5.5227e-04 eta: 2:57:33 time: 1.1238 data_time: 0.2500 memory: 14901 loss: 0.9377 loss_prob: 0.4846 loss_thr: 0.3686 loss_db: 0.0846 2022/11/02 23:18:09 - mmengine - INFO - Epoch(train) [937][15/63] lr: 5.5227e-04 eta: 2:57:33 time: 0.9271 data_time: 0.0262 memory: 14901 loss: 1.0359 loss_prob: 0.5463 loss_thr: 0.3949 loss_db: 0.0948 2022/11/02 23:18:13 - mmengine - INFO - Epoch(train) [937][20/63] lr: 5.5227e-04 eta: 2:57:28 time: 0.8206 data_time: 0.0100 memory: 14901 loss: 1.0162 loss_prob: 0.5391 loss_thr: 0.3838 loss_db: 0.0933 2022/11/02 23:18:17 - mmengine - INFO - Epoch(train) [937][25/63] lr: 5.5227e-04 eta: 2:57:28 time: 0.8215 data_time: 0.0182 memory: 14901 loss: 0.9067 loss_prob: 0.4631 loss_thr: 0.3620 loss_db: 0.0816 2022/11/02 23:18:21 - mmengine - INFO - Epoch(train) [937][30/63] lr: 5.5227e-04 eta: 2:57:22 time: 0.8481 data_time: 0.0344 memory: 14901 loss: 0.8691 loss_prob: 0.4408 loss_thr: 0.3511 loss_db: 0.0772 2022/11/02 23:18:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:18:24 - mmengine - INFO - Epoch(train) [937][35/63] lr: 5.5227e-04 eta: 2:57:22 time: 0.6496 data_time: 0.0451 memory: 14901 loss: 0.8946 loss_prob: 0.4541 loss_thr: 0.3626 loss_db: 0.0779 2022/11/02 23:18:28 - mmengine - INFO - Epoch(train) [937][40/63] lr: 5.5227e-04 eta: 2:57:15 time: 0.6757 data_time: 0.0344 memory: 14901 loss: 0.9457 loss_prob: 0.4803 loss_thr: 0.3824 loss_db: 0.0829 2022/11/02 23:18:34 - mmengine - INFO - Epoch(train) [937][45/63] lr: 5.5227e-04 eta: 2:57:15 time: 1.0163 data_time: 0.0146 memory: 14901 loss: 0.9725 loss_prob: 0.4984 loss_thr: 0.3860 loss_db: 0.0881 2022/11/02 23:18:41 - mmengine - INFO - Epoch(train) [937][50/63] lr: 5.5227e-04 eta: 2:57:11 time: 1.3476 data_time: 0.0256 memory: 14901 loss: 0.9125 loss_prob: 0.4610 loss_thr: 0.3684 loss_db: 0.0830 2022/11/02 23:18:47 - mmengine - INFO - Epoch(train) [937][55/63] lr: 5.5227e-04 eta: 2:57:11 time: 1.3081 data_time: 0.0426 memory: 14901 loss: 0.9149 loss_prob: 0.4720 loss_thr: 0.3589 loss_db: 0.0841 2022/11/02 23:18:54 - mmengine - INFO - Epoch(train) [937][60/63] lr: 5.5227e-04 eta: 2:57:06 time: 1.2442 data_time: 0.0293 memory: 14901 loss: 0.9231 loss_prob: 0.4810 loss_thr: 0.3575 loss_db: 0.0846 2022/11/02 23:18:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:19:06 - mmengine - INFO - Epoch(train) [938][5/63] lr: 5.5038e-04 eta: 2:57:06 time: 1.4861 data_time: 0.2674 memory: 14901 loss: 0.9519 loss_prob: 0.4901 loss_thr: 0.3760 loss_db: 0.0859 2022/11/02 23:19:11 - mmengine - INFO - Epoch(train) [938][10/63] lr: 5.5038e-04 eta: 2:56:59 time: 1.3825 data_time: 0.2758 memory: 14901 loss: 0.9020 loss_prob: 0.4552 loss_thr: 0.3667 loss_db: 0.0800 2022/11/02 23:19:19 - mmengine - INFO - Epoch(train) [938][15/63] lr: 5.5038e-04 eta: 2:56:59 time: 1.3003 data_time: 0.0196 memory: 14901 loss: 0.9426 loss_prob: 0.4776 loss_thr: 0.3804 loss_db: 0.0846 2022/11/02 23:19:23 - mmengine - INFO - Epoch(train) [938][20/63] lr: 5.5038e-04 eta: 2:56:55 time: 1.1768 data_time: 0.0169 memory: 14901 loss: 1.0296 loss_prob: 0.5330 loss_thr: 0.4027 loss_db: 0.0939 2022/11/02 23:19:29 - mmengine - INFO - Epoch(train) [938][25/63] lr: 5.5038e-04 eta: 2:56:55 time: 0.9978 data_time: 0.0282 memory: 14901 loss: 0.9936 loss_prob: 0.5149 loss_thr: 0.3888 loss_db: 0.0899 2022/11/02 23:19:32 - mmengine - INFO - Epoch(train) [938][30/63] lr: 5.5038e-04 eta: 2:56:49 time: 0.8858 data_time: 0.0431 memory: 14901 loss: 0.9281 loss_prob: 0.4718 loss_thr: 0.3740 loss_db: 0.0824 2022/11/02 23:19:38 - mmengine - INFO - Epoch(train) [938][35/63] lr: 5.5038e-04 eta: 2:56:49 time: 0.9050 data_time: 0.0377 memory: 14901 loss: 0.9010 loss_prob: 0.4630 loss_thr: 0.3555 loss_db: 0.0825 2022/11/02 23:19:45 - mmengine - INFO - Epoch(train) [938][40/63] lr: 5.5038e-04 eta: 2:56:44 time: 1.3370 data_time: 0.0194 memory: 14901 loss: 0.9159 loss_prob: 0.4836 loss_thr: 0.3484 loss_db: 0.0839 2022/11/02 23:19:50 - mmengine - INFO - Epoch(train) [938][45/63] lr: 5.5038e-04 eta: 2:56:44 time: 1.2230 data_time: 0.0226 memory: 14901 loss: 0.9711 loss_prob: 0.5114 loss_thr: 0.3717 loss_db: 0.0880 2022/11/02 23:19:55 - mmengine - INFO - Epoch(train) [938][50/63] lr: 5.5038e-04 eta: 2:56:39 time: 0.9484 data_time: 0.0434 memory: 14901 loss: 0.9515 loss_prob: 0.4887 loss_thr: 0.3766 loss_db: 0.0861 2022/11/02 23:20:00 - mmengine - INFO - Epoch(train) [938][55/63] lr: 5.5038e-04 eta: 2:56:39 time: 1.0114 data_time: 0.0350 memory: 14901 loss: 0.8555 loss_prob: 0.4366 loss_thr: 0.3421 loss_db: 0.0767 2022/11/02 23:20:05 - mmengine - INFO - Epoch(train) [938][60/63] lr: 5.5038e-04 eta: 2:56:34 time: 1.0622 data_time: 0.0218 memory: 14901 loss: 0.8995 loss_prob: 0.4583 loss_thr: 0.3599 loss_db: 0.0813 2022/11/02 23:20:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:20:18 - mmengine - INFO - Epoch(train) [939][5/63] lr: 5.4849e-04 eta: 2:56:34 time: 1.4067 data_time: 0.2995 memory: 14901 loss: 0.9065 loss_prob: 0.4608 loss_thr: 0.3661 loss_db: 0.0796 2022/11/02 23:20:25 - mmengine - INFO - Epoch(train) [939][10/63] lr: 5.4849e-04 eta: 2:56:27 time: 1.5476 data_time: 0.3043 memory: 14901 loss: 0.9528 loss_prob: 0.4946 loss_thr: 0.3730 loss_db: 0.0852 2022/11/02 23:20:29 - mmengine - INFO - Epoch(train) [939][15/63] lr: 5.4849e-04 eta: 2:56:27 time: 1.1841 data_time: 0.0199 memory: 14901 loss: 0.9431 loss_prob: 0.4974 loss_thr: 0.3602 loss_db: 0.0855 2022/11/02 23:20:37 - mmengine - INFO - Epoch(train) [939][20/63] lr: 5.4849e-04 eta: 2:56:22 time: 1.1903 data_time: 0.0185 memory: 14901 loss: 0.9200 loss_prob: 0.4835 loss_thr: 0.3537 loss_db: 0.0829 2022/11/02 23:20:40 - mmengine - INFO - Epoch(train) [939][25/63] lr: 5.4849e-04 eta: 2:56:22 time: 1.1045 data_time: 0.0631 memory: 14901 loss: 0.9599 loss_prob: 0.5097 loss_thr: 0.3634 loss_db: 0.0868 2022/11/02 23:20:45 - mmengine - INFO - Epoch(train) [939][30/63] lr: 5.4849e-04 eta: 2:56:16 time: 0.8584 data_time: 0.0708 memory: 14901 loss: 0.9549 loss_prob: 0.5074 loss_thr: 0.3605 loss_db: 0.0870 2022/11/02 23:20:54 - mmengine - INFO - Epoch(train) [939][35/63] lr: 5.4849e-04 eta: 2:56:16 time: 1.3213 data_time: 0.0188 memory: 14901 loss: 0.9426 loss_prob: 0.4923 loss_thr: 0.3653 loss_db: 0.0849 2022/11/02 23:20:59 - mmengine - INFO - Epoch(train) [939][40/63] lr: 5.4849e-04 eta: 2:56:12 time: 1.3512 data_time: 0.0107 memory: 14901 loss: 0.9212 loss_prob: 0.4767 loss_thr: 0.3631 loss_db: 0.0814 2022/11/02 23:21:07 - mmengine - INFO - Epoch(train) [939][45/63] lr: 5.4849e-04 eta: 2:56:12 time: 1.3607 data_time: 0.0221 memory: 14901 loss: 0.8738 loss_prob: 0.4453 loss_thr: 0.3514 loss_db: 0.0771 2022/11/02 23:21:13 - mmengine - INFO - Epoch(train) [939][50/63] lr: 5.4849e-04 eta: 2:56:08 time: 1.3618 data_time: 0.0575 memory: 14901 loss: 0.8834 loss_prob: 0.4443 loss_thr: 0.3608 loss_db: 0.0782 2022/11/02 23:21:20 - mmengine - INFO - Epoch(train) [939][55/63] lr: 5.4849e-04 eta: 2:56:08 time: 1.2869 data_time: 0.0532 memory: 14901 loss: 1.0144 loss_prob: 0.5221 loss_thr: 0.4012 loss_db: 0.0910 2022/11/02 23:21:25 - mmengine - INFO - Epoch(train) [939][60/63] lr: 5.4849e-04 eta: 2:56:03 time: 1.2896 data_time: 0.0175 memory: 14901 loss: 1.0552 loss_prob: 0.5588 loss_thr: 0.3993 loss_db: 0.0971 2022/11/02 23:21:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:21:38 - mmengine - INFO - Epoch(train) [940][5/63] lr: 5.4660e-04 eta: 2:56:03 time: 1.5625 data_time: 0.3106 memory: 14901 loss: 0.8931 loss_prob: 0.4583 loss_thr: 0.3549 loss_db: 0.0800 2022/11/02 23:21:41 - mmengine - INFO - Epoch(train) [940][10/63] lr: 5.4660e-04 eta: 2:55:55 time: 1.1158 data_time: 0.3166 memory: 14901 loss: 0.9789 loss_prob: 0.5073 loss_thr: 0.3826 loss_db: 0.0891 2022/11/02 23:21:48 - mmengine - INFO - Epoch(train) [940][15/63] lr: 5.4660e-04 eta: 2:55:55 time: 1.0294 data_time: 0.0189 memory: 14901 loss: 0.9846 loss_prob: 0.5071 loss_thr: 0.3887 loss_db: 0.0888 2022/11/02 23:21:54 - mmengine - INFO - Epoch(train) [940][20/63] lr: 5.4660e-04 eta: 2:55:51 time: 1.3045 data_time: 0.0125 memory: 14901 loss: 0.9311 loss_prob: 0.4752 loss_thr: 0.3723 loss_db: 0.0836 2022/11/02 23:21:58 - mmengine - INFO - Epoch(train) [940][25/63] lr: 5.4660e-04 eta: 2:55:51 time: 0.9932 data_time: 0.0348 memory: 14901 loss: 0.9525 loss_prob: 0.4919 loss_thr: 0.3751 loss_db: 0.0855 2022/11/02 23:22:05 - mmengine - INFO - Epoch(train) [940][30/63] lr: 5.4660e-04 eta: 2:55:46 time: 1.0401 data_time: 0.0390 memory: 14901 loss: 0.9574 loss_prob: 0.4904 loss_thr: 0.3824 loss_db: 0.0846 2022/11/02 23:22:11 - mmengine - INFO - Epoch(train) [940][35/63] lr: 5.4660e-04 eta: 2:55:46 time: 1.3096 data_time: 0.0201 memory: 14901 loss: 0.9677 loss_prob: 0.4972 loss_thr: 0.3837 loss_db: 0.0868 2022/11/02 23:22:17 - mmengine - INFO - Epoch(train) [940][40/63] lr: 5.4660e-04 eta: 2:55:41 time: 1.1889 data_time: 0.0154 memory: 14901 loss: 0.9828 loss_prob: 0.5125 loss_thr: 0.3813 loss_db: 0.0890 2022/11/02 23:22:23 - mmengine - INFO - Epoch(train) [940][45/63] lr: 5.4660e-04 eta: 2:55:41 time: 1.1962 data_time: 0.0105 memory: 14901 loss: 0.9268 loss_prob: 0.4784 loss_thr: 0.3647 loss_db: 0.0837 2022/11/02 23:22:29 - mmengine - INFO - Epoch(train) [940][50/63] lr: 5.4660e-04 eta: 2:55:36 time: 1.1908 data_time: 0.0342 memory: 14901 loss: 0.8450 loss_prob: 0.4326 loss_thr: 0.3355 loss_db: 0.0769 2022/11/02 23:22:37 - mmengine - INFO - Epoch(train) [940][55/63] lr: 5.4660e-04 eta: 2:55:36 time: 1.3438 data_time: 0.0383 memory: 14901 loss: 0.8559 loss_prob: 0.4344 loss_thr: 0.3445 loss_db: 0.0769 2022/11/02 23:22:41 - mmengine - INFO - Epoch(train) [940][60/63] lr: 5.4660e-04 eta: 2:55:31 time: 1.1993 data_time: 0.0165 memory: 14901 loss: 0.9016 loss_prob: 0.4549 loss_thr: 0.3679 loss_db: 0.0788 2022/11/02 23:22:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:22:44 - mmengine - INFO - Saving checkpoint at 940 epochs 2022/11/02 23:22:48 - mmengine - INFO - Epoch(val) [940][5/500] eta: 2:55:31 time: 0.0540 data_time: 0.0054 memory: 14901 2022/11/02 23:22:48 - mmengine - INFO - Epoch(val) [940][10/500] eta: 0:00:23 time: 0.0487 data_time: 0.0049 memory: 1008 2022/11/02 23:22:48 - mmengine - INFO - Epoch(val) [940][15/500] eta: 0:00:23 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/02 23:22:49 - mmengine - INFO - Epoch(val) [940][20/500] eta: 0:00:22 time: 0.0469 data_time: 0.0034 memory: 1008 2022/11/02 23:22:49 - mmengine - INFO - Epoch(val) [940][25/500] eta: 0:00:22 time: 0.0520 data_time: 0.0056 memory: 1008 2022/11/02 23:22:49 - mmengine - INFO - Epoch(val) [940][30/500] eta: 0:00:27 time: 0.0588 data_time: 0.0081 memory: 1008 2022/11/02 23:22:49 - mmengine - INFO - Epoch(val) [940][35/500] eta: 0:00:27 time: 0.0555 data_time: 0.0058 memory: 1008 2022/11/02 23:22:50 - mmengine - INFO - Epoch(val) [940][40/500] eta: 0:00:23 time: 0.0504 data_time: 0.0030 memory: 1008 2022/11/02 23:22:50 - mmengine - INFO - Epoch(val) [940][45/500] eta: 0:00:23 time: 0.0540 data_time: 0.0039 memory: 1008 2022/11/02 23:22:50 - mmengine - INFO - Epoch(val) [940][50/500] eta: 0:00:23 time: 0.0529 data_time: 0.0081 memory: 1008 2022/11/02 23:22:50 - mmengine - INFO - Epoch(val) [940][55/500] eta: 0:00:23 time: 0.0596 data_time: 0.0114 memory: 1008 2022/11/02 23:22:51 - mmengine - INFO - Epoch(val) [940][60/500] eta: 0:00:26 time: 0.0603 data_time: 0.0091 memory: 1008 2022/11/02 23:22:51 - mmengine - INFO - Epoch(val) [940][65/500] eta: 0:00:26 time: 0.0539 data_time: 0.0055 memory: 1008 2022/11/02 23:22:51 - mmengine - INFO - Epoch(val) [940][70/500] eta: 0:00:26 time: 0.0610 data_time: 0.0044 memory: 1008 2022/11/02 23:22:52 - mmengine - INFO - Epoch(val) [940][75/500] eta: 0:00:26 time: 0.0592 data_time: 0.0042 memory: 1008 2022/11/02 23:22:52 - mmengine - INFO - Epoch(val) [940][80/500] eta: 0:00:20 time: 0.0482 data_time: 0.0035 memory: 1008 2022/11/02 23:22:52 - mmengine - INFO - Epoch(val) [940][85/500] eta: 0:00:20 time: 0.0457 data_time: 0.0036 memory: 1008 2022/11/02 23:22:52 - mmengine - INFO - Epoch(val) [940][90/500] eta: 0:00:21 time: 0.0524 data_time: 0.0043 memory: 1008 2022/11/02 23:22:53 - mmengine - INFO - Epoch(val) [940][95/500] eta: 0:00:21 time: 0.0585 data_time: 0.0065 memory: 1008 2022/11/02 23:22:53 - mmengine - INFO - Epoch(val) [940][100/500] eta: 0:00:21 time: 0.0537 data_time: 0.0060 memory: 1008 2022/11/02 23:22:53 - mmengine - INFO - Epoch(val) [940][105/500] eta: 0:00:21 time: 0.0524 data_time: 0.0042 memory: 1008 2022/11/02 23:22:53 - mmengine - INFO - Epoch(val) [940][110/500] eta: 0:00:18 time: 0.0479 data_time: 0.0037 memory: 1008 2022/11/02 23:22:54 - mmengine - INFO - Epoch(val) [940][115/500] eta: 0:00:18 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/02 23:22:54 - mmengine - INFO - Epoch(val) [940][120/500] eta: 0:00:14 time: 0.0395 data_time: 0.0029 memory: 1008 2022/11/02 23:22:54 - mmengine - INFO - Epoch(val) [940][125/500] eta: 0:00:14 time: 0.0380 data_time: 0.0029 memory: 1008 2022/11/02 23:22:54 - mmengine - INFO - Epoch(val) [940][130/500] eta: 0:00:15 time: 0.0416 data_time: 0.0030 memory: 1008 2022/11/02 23:22:54 - mmengine - INFO - Epoch(val) [940][135/500] eta: 0:00:15 time: 0.0438 data_time: 0.0031 memory: 1008 2022/11/02 23:22:55 - mmengine - INFO - Epoch(val) [940][140/500] eta: 0:00:14 time: 0.0395 data_time: 0.0028 memory: 1008 2022/11/02 23:22:55 - mmengine - INFO - Epoch(val) [940][145/500] eta: 0:00:14 time: 0.0433 data_time: 0.0025 memory: 1008 2022/11/02 23:22:55 - mmengine - INFO - Epoch(val) [940][150/500] eta: 0:00:16 time: 0.0468 data_time: 0.0024 memory: 1008 2022/11/02 23:22:55 - mmengine - INFO - Epoch(val) [940][155/500] eta: 0:00:16 time: 0.0497 data_time: 0.0025 memory: 1008 2022/11/02 23:22:56 - mmengine - INFO - Epoch(val) [940][160/500] eta: 0:00:16 time: 0.0492 data_time: 0.0026 memory: 1008 2022/11/02 23:22:56 - mmengine - INFO - Epoch(val) [940][165/500] eta: 0:00:16 time: 0.0446 data_time: 0.0025 memory: 1008 2022/11/02 23:22:56 - mmengine - INFO - Epoch(val) [940][170/500] eta: 0:00:14 time: 0.0433 data_time: 0.0024 memory: 1008 2022/11/02 23:22:56 - mmengine - INFO - Epoch(val) [940][175/500] eta: 0:00:14 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/02 23:22:56 - mmengine - INFO - Epoch(val) [940][180/500] eta: 0:00:12 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/02 23:22:57 - mmengine - INFO - Epoch(val) [940][185/500] eta: 0:00:12 time: 0.0437 data_time: 0.0028 memory: 1008 2022/11/02 23:22:57 - mmengine - INFO - Epoch(val) [940][190/500] eta: 0:00:13 time: 0.0420 data_time: 0.0029 memory: 1008 2022/11/02 23:22:57 - mmengine - INFO - Epoch(val) [940][195/500] eta: 0:00:13 time: 0.0436 data_time: 0.0044 memory: 1008 2022/11/02 23:22:57 - mmengine - INFO - Epoch(val) [940][200/500] eta: 0:00:18 time: 0.0610 data_time: 0.0069 memory: 1008 2022/11/02 23:22:58 - mmengine - INFO - Epoch(val) [940][205/500] eta: 0:00:18 time: 0.0545 data_time: 0.0052 memory: 1008 2022/11/02 23:22:58 - mmengine - INFO - Epoch(val) [940][210/500] eta: 0:00:11 time: 0.0396 data_time: 0.0029 memory: 1008 2022/11/02 23:22:58 - mmengine - INFO - Epoch(val) [940][215/500] eta: 0:00:11 time: 0.0482 data_time: 0.0036 memory: 1008 2022/11/02 23:22:58 - mmengine - INFO - Epoch(val) [940][220/500] eta: 0:00:13 time: 0.0491 data_time: 0.0043 memory: 1008 2022/11/02 23:22:59 - mmengine - INFO - Epoch(val) [940][225/500] eta: 0:00:13 time: 0.0462 data_time: 0.0039 memory: 1008 2022/11/02 23:22:59 - mmengine - INFO - Epoch(val) [940][230/500] eta: 0:00:12 time: 0.0468 data_time: 0.0036 memory: 1008 2022/11/02 23:22:59 - mmengine - INFO - Epoch(val) [940][235/500] eta: 0:00:12 time: 0.0514 data_time: 0.0056 memory: 1008 2022/11/02 23:22:59 - mmengine - INFO - Epoch(val) [940][240/500] eta: 0:00:15 time: 0.0614 data_time: 0.0136 memory: 1008 2022/11/02 23:23:00 - mmengine - INFO - Epoch(val) [940][245/500] eta: 0:00:15 time: 0.0549 data_time: 0.0119 memory: 1008 2022/11/02 23:23:00 - mmengine - INFO - Epoch(val) [940][250/500] eta: 0:00:12 time: 0.0499 data_time: 0.0047 memory: 1008 2022/11/02 23:23:00 - mmengine - INFO - Epoch(val) [940][255/500] eta: 0:00:12 time: 0.0531 data_time: 0.0046 memory: 1008 2022/11/02 23:23:00 - mmengine - INFO - Epoch(val) [940][260/500] eta: 0:00:12 time: 0.0540 data_time: 0.0067 memory: 1008 2022/11/02 23:23:01 - mmengine - INFO - Epoch(val) [940][265/500] eta: 0:00:12 time: 0.0578 data_time: 0.0087 memory: 1008 2022/11/02 23:23:01 - mmengine - INFO - Epoch(val) [940][270/500] eta: 0:00:12 time: 0.0533 data_time: 0.0061 memory: 1008 2022/11/02 23:23:01 - mmengine - INFO - Epoch(val) [940][275/500] eta: 0:00:12 time: 0.0496 data_time: 0.0042 memory: 1008 2022/11/02 23:23:02 - mmengine - INFO - Epoch(val) [940][280/500] eta: 0:00:11 time: 0.0544 data_time: 0.0054 memory: 1008 2022/11/02 23:23:02 - mmengine - INFO - Epoch(val) [940][285/500] eta: 0:00:11 time: 0.0569 data_time: 0.0103 memory: 1008 2022/11/02 23:23:02 - mmengine - INFO - Epoch(val) [940][290/500] eta: 0:00:11 time: 0.0536 data_time: 0.0105 memory: 1008 2022/11/02 23:23:02 - mmengine - INFO - Epoch(val) [940][295/500] eta: 0:00:11 time: 0.0469 data_time: 0.0049 memory: 1008 2022/11/02 23:23:03 - mmengine - INFO - Epoch(val) [940][300/500] eta: 0:00:08 time: 0.0426 data_time: 0.0029 memory: 1008 2022/11/02 23:23:03 - mmengine - INFO - Epoch(val) [940][305/500] eta: 0:00:08 time: 0.0425 data_time: 0.0031 memory: 1008 2022/11/02 23:23:03 - mmengine - INFO - Epoch(val) [940][310/500] eta: 0:00:07 time: 0.0412 data_time: 0.0028 memory: 1008 2022/11/02 23:23:03 - mmengine - INFO - Epoch(val) [940][315/500] eta: 0:00:07 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/02 23:23:03 - mmengine - INFO - Epoch(val) [940][320/500] eta: 0:00:07 time: 0.0403 data_time: 0.0025 memory: 1008 2022/11/02 23:23:04 - mmengine - INFO - Epoch(val) [940][325/500] eta: 0:00:07 time: 0.0565 data_time: 0.0026 memory: 1008 2022/11/02 23:23:04 - mmengine - INFO - Epoch(val) [940][330/500] eta: 0:00:10 time: 0.0632 data_time: 0.0046 memory: 1008 2022/11/02 23:23:04 - mmengine - INFO - Epoch(val) [940][335/500] eta: 0:00:10 time: 0.0469 data_time: 0.0054 memory: 1008 2022/11/02 23:23:05 - mmengine - INFO - Epoch(val) [940][340/500] eta: 0:00:09 time: 0.0596 data_time: 0.0050 memory: 1008 2022/11/02 23:23:05 - mmengine - INFO - Epoch(val) [940][345/500] eta: 0:00:09 time: 0.0637 data_time: 0.0049 memory: 1008 2022/11/02 23:23:05 - mmengine - INFO - Epoch(val) [940][350/500] eta: 0:00:09 time: 0.0603 data_time: 0.0053 memory: 1008 2022/11/02 23:23:05 - mmengine - INFO - Epoch(val) [940][355/500] eta: 0:00:09 time: 0.0563 data_time: 0.0047 memory: 1008 2022/11/02 23:23:06 - mmengine - INFO - Epoch(val) [940][360/500] eta: 0:00:06 time: 0.0450 data_time: 0.0028 memory: 1008 2022/11/02 23:23:06 - mmengine - INFO - Epoch(val) [940][365/500] eta: 0:00:06 time: 0.0510 data_time: 0.0034 memory: 1008 2022/11/02 23:23:06 - mmengine - INFO - Epoch(val) [940][370/500] eta: 0:00:06 time: 0.0477 data_time: 0.0038 memory: 1008 2022/11/02 23:23:06 - mmengine - INFO - Epoch(val) [940][375/500] eta: 0:00:06 time: 0.0458 data_time: 0.0050 memory: 1008 2022/11/02 23:23:07 - mmengine - INFO - Epoch(val) [940][380/500] eta: 0:00:05 time: 0.0484 data_time: 0.0050 memory: 1008 2022/11/02 23:23:07 - mmengine - INFO - Epoch(val) [940][385/500] eta: 0:00:05 time: 0.0429 data_time: 0.0031 memory: 1008 2022/11/02 23:23:07 - mmengine - INFO - Epoch(val) [940][390/500] eta: 0:00:04 time: 0.0402 data_time: 0.0029 memory: 1008 2022/11/02 23:23:07 - mmengine - INFO - Epoch(val) [940][395/500] eta: 0:00:04 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/02 23:23:07 - mmengine - INFO - Epoch(val) [940][400/500] eta: 0:00:04 time: 0.0400 data_time: 0.0027 memory: 1008 2022/11/02 23:23:08 - mmengine - INFO - Epoch(val) [940][405/500] eta: 0:00:04 time: 0.0413 data_time: 0.0030 memory: 1008 2022/11/02 23:23:08 - mmengine - INFO - Epoch(val) [940][410/500] eta: 0:00:03 time: 0.0437 data_time: 0.0030 memory: 1008 2022/11/02 23:23:08 - mmengine - INFO - Epoch(val) [940][415/500] eta: 0:00:03 time: 0.0429 data_time: 0.0028 memory: 1008 2022/11/02 23:23:08 - mmengine - INFO - Epoch(val) [940][420/500] eta: 0:00:03 time: 0.0388 data_time: 0.0027 memory: 1008 2022/11/02 23:23:08 - mmengine - INFO - Epoch(val) [940][425/500] eta: 0:00:03 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/02 23:23:09 - mmengine - INFO - Epoch(val) [940][430/500] eta: 0:00:02 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/02 23:23:09 - mmengine - INFO - Epoch(val) [940][435/500] eta: 0:00:02 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/02 23:23:09 - mmengine - INFO - Epoch(val) [940][440/500] eta: 0:00:02 time: 0.0441 data_time: 0.0029 memory: 1008 2022/11/02 23:23:09 - mmengine - INFO - Epoch(val) [940][445/500] eta: 0:00:02 time: 0.0584 data_time: 0.0055 memory: 1008 2022/11/02 23:23:10 - mmengine - INFO - Epoch(val) [940][450/500] eta: 0:00:02 time: 0.0597 data_time: 0.0065 memory: 1008 2022/11/02 23:23:10 - mmengine - INFO - Epoch(val) [940][455/500] eta: 0:00:02 time: 0.0525 data_time: 0.0063 memory: 1008 2022/11/02 23:23:10 - mmengine - INFO - Epoch(val) [940][460/500] eta: 0:00:02 time: 0.0533 data_time: 0.0088 memory: 1008 2022/11/02 23:23:10 - mmengine - INFO - Epoch(val) [940][465/500] eta: 0:00:02 time: 0.0559 data_time: 0.0120 memory: 1008 2022/11/02 23:23:11 - mmengine - INFO - Epoch(val) [940][470/500] eta: 0:00:01 time: 0.0537 data_time: 0.0098 memory: 1008 2022/11/02 23:23:11 - mmengine - INFO - Epoch(val) [940][475/500] eta: 0:00:01 time: 0.0449 data_time: 0.0045 memory: 1008 2022/11/02 23:23:11 - mmengine - INFO - Epoch(val) [940][480/500] eta: 0:00:00 time: 0.0436 data_time: 0.0032 memory: 1008 2022/11/02 23:23:11 - mmengine - INFO - Epoch(val) [940][485/500] eta: 0:00:00 time: 0.0440 data_time: 0.0030 memory: 1008 2022/11/02 23:23:12 - mmengine - INFO - Epoch(val) [940][490/500] eta: 0:00:00 time: 0.0499 data_time: 0.0040 memory: 1008 2022/11/02 23:23:12 - mmengine - INFO - Epoch(val) [940][495/500] eta: 0:00:00 time: 0.0529 data_time: 0.0043 memory: 1008 2022/11/02 23:23:12 - mmengine - INFO - Epoch(val) [940][500/500] eta: 0:00:00 time: 0.0440 data_time: 0.0048 memory: 1008 2022/11/02 23:23:12 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8426, precision: 0.7353, hmean: 0.7853 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8426, precision: 0.7743, hmean: 0.8070 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8421, precision: 0.8012, hmean: 0.8211 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8397, precision: 0.8333, hmean: 0.8365 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8291, precision: 0.8623, hmean: 0.8454 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7390, precision: 0.9137, hmean: 0.8171 2022/11/02 23:23:12 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1675, precision: 0.9508, hmean: 0.2849 2022/11/02 23:23:12 - mmengine - INFO - Epoch(val) [940][500/500] icdar/precision: 0.8623 icdar/recall: 0.8291 icdar/hmean: 0.8454 2022/11/02 23:23:23 - mmengine - INFO - Epoch(train) [941][5/63] lr: 5.4470e-04 eta: 0:00:00 time: 1.4576 data_time: 0.2936 memory: 14901 loss: 0.9569 loss_prob: 0.4966 loss_thr: 0.3728 loss_db: 0.0875 2022/11/02 23:23:28 - mmengine - INFO - Epoch(train) [941][10/63] lr: 5.4470e-04 eta: 2:55:25 time: 1.6095 data_time: 0.2923 memory: 14901 loss: 0.9787 loss_prob: 0.5013 loss_thr: 0.3890 loss_db: 0.0884 2022/11/02 23:23:34 - mmengine - INFO - Epoch(train) [941][15/63] lr: 5.4470e-04 eta: 2:55:25 time: 1.1394 data_time: 0.0099 memory: 14901 loss: 0.9785 loss_prob: 0.4962 loss_thr: 0.3947 loss_db: 0.0876 2022/11/02 23:23:41 - mmengine - INFO - Epoch(train) [941][20/63] lr: 5.4470e-04 eta: 2:55:20 time: 1.2815 data_time: 0.0130 memory: 14901 loss: 0.9783 loss_prob: 0.5109 loss_thr: 0.3770 loss_db: 0.0904 2022/11/02 23:23:48 - mmengine - INFO - Epoch(train) [941][25/63] lr: 5.4470e-04 eta: 2:55:20 time: 1.4170 data_time: 0.0361 memory: 14901 loss: 0.9348 loss_prob: 0.4881 loss_thr: 0.3606 loss_db: 0.0861 2022/11/02 23:23:55 - mmengine - INFO - Epoch(train) [941][30/63] lr: 5.4470e-04 eta: 2:55:16 time: 1.3843 data_time: 0.0636 memory: 14901 loss: 0.9567 loss_prob: 0.5003 loss_thr: 0.3682 loss_db: 0.0882 2022/11/02 23:23:57 - mmengine - INFO - Epoch(train) [941][35/63] lr: 5.4470e-04 eta: 2:55:16 time: 0.9409 data_time: 0.0421 memory: 14901 loss: 0.9446 loss_prob: 0.4890 loss_thr: 0.3705 loss_db: 0.0851 2022/11/02 23:24:05 - mmengine - INFO - Epoch(train) [941][40/63] lr: 5.4470e-04 eta: 2:55:10 time: 0.9797 data_time: 0.0128 memory: 14901 loss: 0.8792 loss_prob: 0.4457 loss_thr: 0.3563 loss_db: 0.0772 2022/11/02 23:24:09 - mmengine - INFO - Epoch(train) [941][45/63] lr: 5.4470e-04 eta: 2:55:10 time: 1.1584 data_time: 0.0113 memory: 14901 loss: 0.8721 loss_prob: 0.4455 loss_thr: 0.3482 loss_db: 0.0785 2022/11/02 23:24:16 - mmengine - INFO - Epoch(train) [941][50/63] lr: 5.4470e-04 eta: 2:55:05 time: 1.0986 data_time: 0.0345 memory: 14901 loss: 0.8827 loss_prob: 0.4479 loss_thr: 0.3554 loss_db: 0.0794 2022/11/02 23:24:19 - mmengine - INFO - Epoch(train) [941][55/63] lr: 5.4470e-04 eta: 2:55:05 time: 0.9966 data_time: 0.0421 memory: 14901 loss: 0.9203 loss_prob: 0.4744 loss_thr: 0.3626 loss_db: 0.0832 2022/11/02 23:24:24 - mmengine - INFO - Epoch(train) [941][60/63] lr: 5.4470e-04 eta: 2:54:59 time: 0.8683 data_time: 0.0188 memory: 14901 loss: 0.9261 loss_prob: 0.4845 loss_thr: 0.3582 loss_db: 0.0834 2022/11/02 23:24:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:24:37 - mmengine - INFO - Epoch(train) [942][5/63] lr: 5.4281e-04 eta: 2:54:59 time: 1.5313 data_time: 0.2630 memory: 14901 loss: 0.9245 loss_prob: 0.4823 loss_thr: 0.3575 loss_db: 0.0847 2022/11/02 23:24:44 - mmengine - INFO - Epoch(train) [942][10/63] lr: 5.4281e-04 eta: 2:54:53 time: 1.5883 data_time: 0.2650 memory: 14901 loss: 0.8912 loss_prob: 0.4594 loss_thr: 0.3519 loss_db: 0.0799 2022/11/02 23:24:49 - mmengine - INFO - Epoch(train) [942][15/63] lr: 5.4281e-04 eta: 2:54:53 time: 1.2038 data_time: 0.0152 memory: 14901 loss: 0.9346 loss_prob: 0.4800 loss_thr: 0.3714 loss_db: 0.0831 2022/11/02 23:24:54 - mmengine - INFO - Epoch(train) [942][20/63] lr: 5.4281e-04 eta: 2:54:47 time: 0.9720 data_time: 0.0120 memory: 14901 loss: 0.9702 loss_prob: 0.5028 loss_thr: 0.3797 loss_db: 0.0877 2022/11/02 23:24:59 - mmengine - INFO - Epoch(train) [942][25/63] lr: 5.4281e-04 eta: 2:54:47 time: 0.9917 data_time: 0.0361 memory: 14901 loss: 0.8875 loss_prob: 0.4550 loss_thr: 0.3508 loss_db: 0.0817 2022/11/02 23:25:04 - mmengine - INFO - Epoch(train) [942][30/63] lr: 5.4281e-04 eta: 2:54:42 time: 1.0382 data_time: 0.0395 memory: 14901 loss: 0.8564 loss_prob: 0.4369 loss_thr: 0.3421 loss_db: 0.0774 2022/11/02 23:25:07 - mmengine - INFO - Epoch(train) [942][35/63] lr: 5.4281e-04 eta: 2:54:42 time: 0.8030 data_time: 0.0195 memory: 14901 loss: 0.8609 loss_prob: 0.4471 loss_thr: 0.3354 loss_db: 0.0783 2022/11/02 23:25:14 - mmengine - INFO - Epoch(train) [942][40/63] lr: 5.4281e-04 eta: 2:54:36 time: 0.9494 data_time: 0.0160 memory: 14901 loss: 0.8925 loss_prob: 0.4573 loss_thr: 0.3536 loss_db: 0.0815 2022/11/02 23:25:17 - mmengine - INFO - Epoch(train) [942][45/63] lr: 5.4281e-04 eta: 2:54:36 time: 0.9766 data_time: 0.0090 memory: 14901 loss: 0.9665 loss_prob: 0.4931 loss_thr: 0.3859 loss_db: 0.0875 2022/11/02 23:25:26 - mmengine - INFO - Epoch(train) [942][50/63] lr: 5.4281e-04 eta: 2:54:31 time: 1.2013 data_time: 0.0428 memory: 14901 loss: 1.0151 loss_prob: 0.5271 loss_thr: 0.3960 loss_db: 0.0920 2022/11/02 23:25:33 - mmengine - INFO - Epoch(train) [942][55/63] lr: 5.4281e-04 eta: 2:54:31 time: 1.5907 data_time: 0.0519 memory: 14901 loss: 1.0230 loss_prob: 0.5374 loss_thr: 0.3940 loss_db: 0.0916 2022/11/02 23:25:36 - mmengine - INFO - Epoch(train) [942][60/63] lr: 5.4281e-04 eta: 2:54:26 time: 1.0730 data_time: 0.0208 memory: 14901 loss: 0.9721 loss_prob: 0.5133 loss_thr: 0.3708 loss_db: 0.0879 2022/11/02 23:25:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:25:48 - mmengine - INFO - Epoch(train) [943][5/63] lr: 5.4092e-04 eta: 2:54:26 time: 1.2991 data_time: 0.2873 memory: 14901 loss: 0.8779 loss_prob: 0.4447 loss_thr: 0.3539 loss_db: 0.0793 2022/11/02 23:25:54 - mmengine - INFO - Epoch(train) [943][10/63] lr: 5.4092e-04 eta: 2:54:20 time: 1.5669 data_time: 0.2981 memory: 14901 loss: 0.8782 loss_prob: 0.4455 loss_thr: 0.3541 loss_db: 0.0785 2022/11/02 23:26:01 - mmengine - INFO - Epoch(train) [943][15/63] lr: 5.4092e-04 eta: 2:54:20 time: 1.3024 data_time: 0.0604 memory: 14901 loss: 0.8485 loss_prob: 0.4338 loss_thr: 0.3388 loss_db: 0.0758 2022/11/02 23:26:06 - mmengine - INFO - Epoch(train) [943][20/63] lr: 5.4092e-04 eta: 2:54:15 time: 1.1668 data_time: 0.0489 memory: 14901 loss: 0.8459 loss_prob: 0.4321 loss_thr: 0.3380 loss_db: 0.0758 2022/11/02 23:26:11 - mmengine - INFO - Epoch(train) [943][25/63] lr: 5.4092e-04 eta: 2:54:15 time: 0.9180 data_time: 0.0095 memory: 14901 loss: 0.9390 loss_prob: 0.4882 loss_thr: 0.3665 loss_db: 0.0843 2022/11/02 23:26:16 - mmengine - INFO - Epoch(train) [943][30/63] lr: 5.4092e-04 eta: 2:54:09 time: 1.0247 data_time: 0.0113 memory: 14901 loss: 1.0031 loss_prob: 0.5366 loss_thr: 0.3772 loss_db: 0.0893 2022/11/02 23:26:21 - mmengine - INFO - Epoch(train) [943][35/63] lr: 5.4092e-04 eta: 2:54:09 time: 1.0046 data_time: 0.0109 memory: 14901 loss: 0.9324 loss_prob: 0.4930 loss_thr: 0.3557 loss_db: 0.0837 2022/11/02 23:26:28 - mmengine - INFO - Epoch(train) [943][40/63] lr: 5.4092e-04 eta: 2:54:04 time: 1.1646 data_time: 0.0559 memory: 14901 loss: 0.9010 loss_prob: 0.4637 loss_thr: 0.3564 loss_db: 0.0809 2022/11/02 23:26:32 - mmengine - INFO - Epoch(train) [943][45/63] lr: 5.4092e-04 eta: 2:54:04 time: 1.0905 data_time: 0.0575 memory: 14901 loss: 0.9559 loss_prob: 0.4877 loss_thr: 0.3846 loss_db: 0.0835 2022/11/02 23:26:39 - mmengine - INFO - Epoch(train) [943][50/63] lr: 5.4092e-04 eta: 2:53:59 time: 1.1101 data_time: 0.0161 memory: 14901 loss: 0.9578 loss_prob: 0.4812 loss_thr: 0.3926 loss_db: 0.0840 2022/11/02 23:26:43 - mmengine - INFO - Epoch(train) [943][55/63] lr: 5.4092e-04 eta: 2:53:59 time: 1.1467 data_time: 0.0146 memory: 14901 loss: 1.0030 loss_prob: 0.5283 loss_thr: 0.3832 loss_db: 0.0916 2022/11/02 23:26:49 - mmengine - INFO - Epoch(train) [943][60/63] lr: 5.4092e-04 eta: 2:53:54 time: 1.0538 data_time: 0.0173 memory: 14901 loss: 1.0683 loss_prob: 0.5788 loss_thr: 0.3920 loss_db: 0.0974 2022/11/02 23:26:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:27:01 - mmengine - INFO - Epoch(train) [944][5/63] lr: 5.3902e-04 eta: 2:53:54 time: 1.4879 data_time: 0.2225 memory: 14901 loss: 0.9167 loss_prob: 0.4694 loss_thr: 0.3654 loss_db: 0.0819 2022/11/02 23:27:07 - mmengine - INFO - Epoch(train) [944][10/63] lr: 5.3902e-04 eta: 2:53:47 time: 1.4553 data_time: 0.2237 memory: 14901 loss: 0.9866 loss_prob: 0.5208 loss_thr: 0.3753 loss_db: 0.0905 2022/11/02 23:27:10 - mmengine - INFO - Epoch(train) [944][15/63] lr: 5.3902e-04 eta: 2:53:47 time: 0.8616 data_time: 0.0151 memory: 14901 loss: 0.9784 loss_prob: 0.5097 loss_thr: 0.3803 loss_db: 0.0884 2022/11/02 23:27:16 - mmengine - INFO - Epoch(train) [944][20/63] lr: 5.3902e-04 eta: 2:53:41 time: 0.8669 data_time: 0.0113 memory: 14901 loss: 0.9377 loss_prob: 0.4751 loss_thr: 0.3798 loss_db: 0.0828 2022/11/02 23:27:23 - mmengine - INFO - Epoch(train) [944][25/63] lr: 5.3902e-04 eta: 2:53:41 time: 1.2567 data_time: 0.0347 memory: 14901 loss: 0.9293 loss_prob: 0.4719 loss_thr: 0.3733 loss_db: 0.0841 2022/11/02 23:27:29 - mmengine - INFO - Epoch(train) [944][30/63] lr: 5.3902e-04 eta: 2:53:37 time: 1.3519 data_time: 0.0520 memory: 14901 loss: 0.8744 loss_prob: 0.4469 loss_thr: 0.3479 loss_db: 0.0796 2022/11/02 23:27:36 - mmengine - INFO - Epoch(train) [944][35/63] lr: 5.3902e-04 eta: 2:53:37 time: 1.3366 data_time: 0.0343 memory: 14901 loss: 0.9170 loss_prob: 0.4749 loss_thr: 0.3583 loss_db: 0.0837 2022/11/02 23:27:43 - mmengine - INFO - Epoch(train) [944][40/63] lr: 5.3902e-04 eta: 2:53:32 time: 1.3441 data_time: 0.0150 memory: 14901 loss: 1.0314 loss_prob: 0.5424 loss_thr: 0.3942 loss_db: 0.0949 2022/11/02 23:27:50 - mmengine - INFO - Epoch(train) [944][45/63] lr: 5.3902e-04 eta: 2:53:32 time: 1.4304 data_time: 0.0141 memory: 14901 loss: 1.0336 loss_prob: 0.5462 loss_thr: 0.3930 loss_db: 0.0945 2022/11/02 23:27:55 - mmengine - INFO - Epoch(train) [944][50/63] lr: 5.3902e-04 eta: 2:53:27 time: 1.2767 data_time: 0.0271 memory: 14901 loss: 0.9241 loss_prob: 0.4798 loss_thr: 0.3611 loss_db: 0.0831 2022/11/02 23:28:03 - mmengine - INFO - Epoch(train) [944][55/63] lr: 5.3902e-04 eta: 2:53:27 time: 1.2531 data_time: 0.0369 memory: 14901 loss: 0.9142 loss_prob: 0.4758 loss_thr: 0.3552 loss_db: 0.0832 2022/11/02 23:28:06 - mmengine - INFO - Epoch(train) [944][60/63] lr: 5.3902e-04 eta: 2:53:22 time: 1.1072 data_time: 0.0226 memory: 14901 loss: 0.9581 loss_prob: 0.5050 loss_thr: 0.3652 loss_db: 0.0879 2022/11/02 23:28:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:28:19 - mmengine - INFO - Epoch(train) [945][5/63] lr: 5.3713e-04 eta: 2:53:22 time: 1.3083 data_time: 0.3100 memory: 14901 loss: 0.9484 loss_prob: 0.4919 loss_thr: 0.3694 loss_db: 0.0870 2022/11/02 23:28:24 - mmengine - INFO - Epoch(train) [945][10/63] lr: 5.3713e-04 eta: 2:53:16 time: 1.5699 data_time: 0.3081 memory: 14901 loss: 1.0076 loss_prob: 0.5239 loss_thr: 0.3910 loss_db: 0.0927 2022/11/02 23:28:32 - mmengine - INFO - Epoch(train) [945][15/63] lr: 5.3713e-04 eta: 2:53:16 time: 1.3800 data_time: 0.0196 memory: 14901 loss: 1.0309 loss_prob: 0.5419 loss_thr: 0.3955 loss_db: 0.0935 2022/11/02 23:28:37 - mmengine - INFO - Epoch(train) [945][20/63] lr: 5.3713e-04 eta: 2:53:11 time: 1.2373 data_time: 0.0190 memory: 14901 loss: 0.9421 loss_prob: 0.4875 loss_thr: 0.3713 loss_db: 0.0833 2022/11/02 23:28:44 - mmengine - INFO - Epoch(train) [945][25/63] lr: 5.3713e-04 eta: 2:53:11 time: 1.1897 data_time: 0.0250 memory: 14901 loss: 0.9594 loss_prob: 0.4976 loss_thr: 0.3737 loss_db: 0.0881 2022/11/02 23:28:48 - mmengine - INFO - Epoch(train) [945][30/63] lr: 5.3713e-04 eta: 2:53:06 time: 1.1060 data_time: 0.0381 memory: 14901 loss: 1.0005 loss_prob: 0.5285 loss_thr: 0.3792 loss_db: 0.0928 2022/11/02 23:28:55 - mmengine - INFO - Epoch(train) [945][35/63] lr: 5.3713e-04 eta: 2:53:06 time: 1.0422 data_time: 0.0270 memory: 14901 loss: 0.8716 loss_prob: 0.4494 loss_thr: 0.3448 loss_db: 0.0774 2022/11/02 23:28:59 - mmengine - INFO - Epoch(train) [945][40/63] lr: 5.3713e-04 eta: 2:53:01 time: 1.1715 data_time: 0.0169 memory: 14901 loss: 0.8307 loss_prob: 0.4208 loss_thr: 0.3366 loss_db: 0.0733 2022/11/02 23:29:06 - mmengine - INFO - Epoch(train) [945][45/63] lr: 5.3713e-04 eta: 2:53:01 time: 1.1239 data_time: 0.0158 memory: 14901 loss: 0.8507 loss_prob: 0.4352 loss_thr: 0.3398 loss_db: 0.0757 2022/11/02 23:29:12 - mmengine - INFO - Epoch(train) [945][50/63] lr: 5.3713e-04 eta: 2:52:56 time: 1.2901 data_time: 0.0257 memory: 14901 loss: 0.8849 loss_prob: 0.4499 loss_thr: 0.3561 loss_db: 0.0788 2022/11/02 23:29:17 - mmengine - INFO - Epoch(train) [945][55/63] lr: 5.3713e-04 eta: 2:52:56 time: 1.1008 data_time: 0.0320 memory: 14901 loss: 0.9846 loss_prob: 0.5056 loss_thr: 0.3904 loss_db: 0.0886 2022/11/02 23:29:23 - mmengine - INFO - Epoch(train) [945][60/63] lr: 5.3713e-04 eta: 2:52:51 time: 1.0948 data_time: 0.0262 memory: 14901 loss: 1.0371 loss_prob: 0.5443 loss_thr: 0.3977 loss_db: 0.0950 2022/11/02 23:29:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:29:37 - mmengine - INFO - Epoch(train) [946][5/63] lr: 5.3523e-04 eta: 2:52:51 time: 1.5572 data_time: 0.2659 memory: 14901 loss: 0.9938 loss_prob: 0.5220 loss_thr: 0.3819 loss_db: 0.0898 2022/11/02 23:29:46 - mmengine - INFO - Epoch(train) [946][10/63] lr: 5.3523e-04 eta: 2:52:45 time: 1.8745 data_time: 0.2774 memory: 14901 loss: 0.9310 loss_prob: 0.4806 loss_thr: 0.3678 loss_db: 0.0825 2022/11/02 23:29:49 - mmengine - INFO - Epoch(train) [946][15/63] lr: 5.3523e-04 eta: 2:52:45 time: 1.2774 data_time: 0.0258 memory: 14901 loss: 0.9167 loss_prob: 0.4703 loss_thr: 0.3629 loss_db: 0.0835 2022/11/02 23:29:57 - mmengine - INFO - Epoch(train) [946][20/63] lr: 5.3523e-04 eta: 2:52:40 time: 1.1397 data_time: 0.0103 memory: 14901 loss: 0.9747 loss_prob: 0.5036 loss_thr: 0.3830 loss_db: 0.0881 2022/11/02 23:30:02 - mmengine - INFO - Epoch(train) [946][25/63] lr: 5.3523e-04 eta: 2:52:40 time: 1.2661 data_time: 0.0751 memory: 14901 loss: 0.9652 loss_prob: 0.4944 loss_thr: 0.3855 loss_db: 0.0853 2022/11/02 23:30:08 - mmengine - INFO - Epoch(train) [946][30/63] lr: 5.3523e-04 eta: 2:52:35 time: 1.1100 data_time: 0.0758 memory: 14901 loss: 0.9446 loss_prob: 0.4954 loss_thr: 0.3639 loss_db: 0.0853 2022/11/02 23:30:11 - mmengine - INFO - Epoch(train) [946][35/63] lr: 5.3523e-04 eta: 2:52:35 time: 0.9128 data_time: 0.0129 memory: 14901 loss: 1.0312 loss_prob: 0.5525 loss_thr: 0.3851 loss_db: 0.0936 2022/11/02 23:30:18 - mmengine - INFO - Epoch(train) [946][40/63] lr: 5.3523e-04 eta: 2:52:29 time: 1.0085 data_time: 0.0128 memory: 14901 loss: 1.0527 loss_prob: 0.5546 loss_thr: 0.4021 loss_db: 0.0959 2022/11/02 23:30:25 - mmengine - INFO - Epoch(train) [946][45/63] lr: 5.3523e-04 eta: 2:52:29 time: 1.3751 data_time: 0.0121 memory: 14901 loss: 0.9889 loss_prob: 0.5190 loss_thr: 0.3795 loss_db: 0.0903 2022/11/02 23:30:29 - mmengine - INFO - Epoch(train) [946][50/63] lr: 5.3523e-04 eta: 2:52:24 time: 1.0756 data_time: 0.0235 memory: 14901 loss: 0.9715 loss_prob: 0.5156 loss_thr: 0.3692 loss_db: 0.0867 2022/11/02 23:30:34 - mmengine - INFO - Epoch(train) [946][55/63] lr: 5.3523e-04 eta: 2:52:24 time: 0.9404 data_time: 0.0247 memory: 14901 loss: 0.9365 loss_prob: 0.4873 loss_thr: 0.3661 loss_db: 0.0831 2022/11/02 23:30:38 - mmengine - INFO - Epoch(train) [946][60/63] lr: 5.3523e-04 eta: 2:52:18 time: 0.9404 data_time: 0.0126 memory: 14901 loss: 0.9413 loss_prob: 0.4844 loss_thr: 0.3712 loss_db: 0.0857 2022/11/02 23:30:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:30:50 - mmengine - INFO - Epoch(train) [947][5/63] lr: 5.3334e-04 eta: 2:52:18 time: 1.2260 data_time: 0.2313 memory: 14901 loss: 0.9098 loss_prob: 0.4669 loss_thr: 0.3615 loss_db: 0.0814 2022/11/02 23:30:56 - mmengine - INFO - Epoch(train) [947][10/63] lr: 5.3334e-04 eta: 2:52:12 time: 1.5060 data_time: 0.2342 memory: 14901 loss: 0.9298 loss_prob: 0.4769 loss_thr: 0.3693 loss_db: 0.0837 2022/11/02 23:31:05 - mmengine - INFO - Epoch(train) [947][15/63] lr: 5.3334e-04 eta: 2:52:12 time: 1.4728 data_time: 0.0154 memory: 14901 loss: 0.9513 loss_prob: 0.4898 loss_thr: 0.3744 loss_db: 0.0872 2022/11/02 23:31:09 - mmengine - INFO - Epoch(train) [947][20/63] lr: 5.3334e-04 eta: 2:52:07 time: 1.2876 data_time: 0.0088 memory: 14901 loss: 0.9570 loss_prob: 0.4971 loss_thr: 0.3728 loss_db: 0.0872 2022/11/02 23:31:12 - mmengine - INFO - Epoch(train) [947][25/63] lr: 5.3334e-04 eta: 2:52:07 time: 0.7934 data_time: 0.0131 memory: 14901 loss: 0.9201 loss_prob: 0.4781 loss_thr: 0.3585 loss_db: 0.0836 2022/11/02 23:31:19 - mmengine - INFO - Epoch(train) [947][30/63] lr: 5.3334e-04 eta: 2:52:01 time: 0.9390 data_time: 0.0469 memory: 14901 loss: 0.9241 loss_prob: 0.4748 loss_thr: 0.3675 loss_db: 0.0818 2022/11/02 23:31:25 - mmengine - INFO - Epoch(train) [947][35/63] lr: 5.3334e-04 eta: 2:52:01 time: 1.2508 data_time: 0.0486 memory: 14901 loss: 0.9193 loss_prob: 0.4725 loss_thr: 0.3647 loss_db: 0.0821 2022/11/02 23:31:28 - mmengine - INFO - Epoch(train) [947][40/63] lr: 5.3334e-04 eta: 2:51:56 time: 0.8830 data_time: 0.0160 memory: 14901 loss: 0.9158 loss_prob: 0.4808 loss_thr: 0.3505 loss_db: 0.0845 2022/11/02 23:31:33 - mmengine - INFO - Epoch(train) [947][45/63] lr: 5.3334e-04 eta: 2:51:56 time: 0.7967 data_time: 0.0108 memory: 14901 loss: 0.9657 loss_prob: 0.5096 loss_thr: 0.3703 loss_db: 0.0858 2022/11/02 23:31:37 - mmengine - INFO - Epoch(train) [947][50/63] lr: 5.3334e-04 eta: 2:51:50 time: 0.9402 data_time: 0.0245 memory: 14901 loss: 1.0007 loss_prob: 0.5279 loss_thr: 0.3843 loss_db: 0.0886 2022/11/02 23:31:46 - mmengine - INFO - Epoch(train) [947][55/63] lr: 5.3334e-04 eta: 2:51:50 time: 1.2917 data_time: 0.0300 memory: 14901 loss: 0.9478 loss_prob: 0.4972 loss_thr: 0.3647 loss_db: 0.0859 2022/11/02 23:31:51 - mmengine - INFO - Epoch(train) [947][60/63] lr: 5.3334e-04 eta: 2:51:46 time: 1.4301 data_time: 0.0179 memory: 14901 loss: 0.9207 loss_prob: 0.4792 loss_thr: 0.3585 loss_db: 0.0830 2022/11/02 23:31:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:32:04 - mmengine - INFO - Epoch(train) [948][5/63] lr: 5.3144e-04 eta: 2:51:46 time: 1.4683 data_time: 0.2359 memory: 14901 loss: 0.9427 loss_prob: 0.4790 loss_thr: 0.3774 loss_db: 0.0862 2022/11/02 23:32:11 - mmengine - INFO - Epoch(train) [948][10/63] lr: 5.3144e-04 eta: 2:51:40 time: 1.8144 data_time: 0.2377 memory: 14901 loss: 0.9444 loss_prob: 0.4827 loss_thr: 0.3770 loss_db: 0.0847 2022/11/02 23:32:16 - mmengine - INFO - Epoch(train) [948][15/63] lr: 5.3144e-04 eta: 2:51:40 time: 1.2629 data_time: 0.0098 memory: 14901 loss: 0.9137 loss_prob: 0.4715 loss_thr: 0.3609 loss_db: 0.0813 2022/11/02 23:32:24 - mmengine - INFO - Epoch(train) [948][20/63] lr: 5.3144e-04 eta: 2:51:35 time: 1.3327 data_time: 0.0090 memory: 14901 loss: 0.8784 loss_prob: 0.4510 loss_thr: 0.3479 loss_db: 0.0796 2022/11/02 23:32:30 - mmengine - INFO - Epoch(train) [948][25/63] lr: 5.3144e-04 eta: 2:51:35 time: 1.3743 data_time: 0.0199 memory: 14901 loss: 0.9752 loss_prob: 0.5125 loss_thr: 0.3757 loss_db: 0.0871 2022/11/02 23:32:38 - mmengine - INFO - Epoch(train) [948][30/63] lr: 5.3144e-04 eta: 2:51:31 time: 1.3625 data_time: 0.0486 memory: 14901 loss: 1.0277 loss_prob: 0.5432 loss_thr: 0.3914 loss_db: 0.0932 2022/11/02 23:32:41 - mmengine - INFO - Epoch(train) [948][35/63] lr: 5.3144e-04 eta: 2:51:31 time: 1.0741 data_time: 0.0420 memory: 14901 loss: 0.9245 loss_prob: 0.4778 loss_thr: 0.3631 loss_db: 0.0837 2022/11/02 23:32:47 - mmengine - INFO - Epoch(train) [948][40/63] lr: 5.3144e-04 eta: 2:51:25 time: 0.9192 data_time: 0.0167 memory: 14901 loss: 0.9252 loss_prob: 0.4760 loss_thr: 0.3669 loss_db: 0.0823 2022/11/02 23:32:55 - mmengine - INFO - Epoch(train) [948][45/63] lr: 5.3144e-04 eta: 2:51:25 time: 1.3603 data_time: 0.0147 memory: 14901 loss: 0.9689 loss_prob: 0.4982 loss_thr: 0.3832 loss_db: 0.0875 2022/11/02 23:32:58 - mmengine - INFO - Epoch(train) [948][50/63] lr: 5.3144e-04 eta: 2:51:20 time: 1.1271 data_time: 0.0277 memory: 14901 loss: 0.9293 loss_prob: 0.4720 loss_thr: 0.3739 loss_db: 0.0833 2022/11/02 23:33:03 - mmengine - INFO - Epoch(train) [948][55/63] lr: 5.3144e-04 eta: 2:51:20 time: 0.8563 data_time: 0.0327 memory: 14901 loss: 0.8879 loss_prob: 0.4464 loss_thr: 0.3620 loss_db: 0.0795 2022/11/02 23:33:09 - mmengine - INFO - Epoch(train) [948][60/63] lr: 5.3144e-04 eta: 2:51:14 time: 1.0978 data_time: 0.0163 memory: 14901 loss: 0.8781 loss_prob: 0.4497 loss_thr: 0.3486 loss_db: 0.0798 2022/11/02 23:33:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:33:20 - mmengine - INFO - Epoch(train) [949][5/63] lr: 5.2954e-04 eta: 2:51:14 time: 1.2954 data_time: 0.2088 memory: 14901 loss: 0.8586 loss_prob: 0.4366 loss_thr: 0.3444 loss_db: 0.0776 2022/11/02 23:33:24 - mmengine - INFO - Epoch(train) [949][10/63] lr: 5.2954e-04 eta: 2:51:07 time: 1.2902 data_time: 0.2172 memory: 14901 loss: 0.9585 loss_prob: 0.5019 loss_thr: 0.3693 loss_db: 0.0874 2022/11/02 23:33:32 - mmengine - INFO - Epoch(train) [949][15/63] lr: 5.2954e-04 eta: 2:51:07 time: 1.2190 data_time: 0.0251 memory: 14901 loss: 0.9902 loss_prob: 0.5305 loss_thr: 0.3675 loss_db: 0.0922 2022/11/02 23:33:36 - mmengine - INFO - Epoch(train) [949][20/63] lr: 5.2954e-04 eta: 2:51:02 time: 1.1436 data_time: 0.0165 memory: 14901 loss: 0.9008 loss_prob: 0.4717 loss_thr: 0.3457 loss_db: 0.0834 2022/11/02 23:33:44 - mmengine - INFO - Epoch(train) [949][25/63] lr: 5.2954e-04 eta: 2:51:02 time: 1.1385 data_time: 0.0202 memory: 14901 loss: 0.8982 loss_prob: 0.4627 loss_thr: 0.3549 loss_db: 0.0806 2022/11/02 23:33:48 - mmengine - INFO - Epoch(train) [949][30/63] lr: 5.2954e-04 eta: 2:50:57 time: 1.2470 data_time: 0.0353 memory: 14901 loss: 0.9207 loss_prob: 0.4832 loss_thr: 0.3552 loss_db: 0.0823 2022/11/02 23:33:55 - mmengine - INFO - Epoch(train) [949][35/63] lr: 5.2954e-04 eta: 2:50:57 time: 1.1276 data_time: 0.0414 memory: 14901 loss: 0.8931 loss_prob: 0.4688 loss_thr: 0.3437 loss_db: 0.0807 2022/11/02 23:33:59 - mmengine - INFO - Epoch(train) [949][40/63] lr: 5.2954e-04 eta: 2:50:52 time: 1.0326 data_time: 0.0308 memory: 14901 loss: 0.9470 loss_prob: 0.5064 loss_thr: 0.3533 loss_db: 0.0873 2022/11/02 23:34:07 - mmengine - INFO - Epoch(train) [949][45/63] lr: 5.2954e-04 eta: 2:50:52 time: 1.1614 data_time: 0.0176 memory: 14901 loss: 1.0213 loss_prob: 0.5423 loss_thr: 0.3860 loss_db: 0.0931 2022/11/02 23:34:13 - mmengine - INFO - Epoch(train) [949][50/63] lr: 5.2954e-04 eta: 2:50:47 time: 1.3937 data_time: 0.0186 memory: 14901 loss: 1.0351 loss_prob: 0.5383 loss_thr: 0.4035 loss_db: 0.0933 2022/11/02 23:34:18 - mmengine - INFO - Epoch(train) [949][55/63] lr: 5.2954e-04 eta: 2:50:47 time: 1.1121 data_time: 0.0326 memory: 14901 loss: 1.0593 loss_prob: 0.5616 loss_thr: 0.4014 loss_db: 0.0963 2022/11/02 23:34:24 - mmengine - INFO - Epoch(train) [949][60/63] lr: 5.2954e-04 eta: 2:50:42 time: 1.1329 data_time: 0.0255 memory: 14901 loss: 0.9894 loss_prob: 0.5170 loss_thr: 0.3834 loss_db: 0.0889 2022/11/02 23:34:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:34:34 - mmengine - INFO - Epoch(train) [950][5/63] lr: 5.2764e-04 eta: 2:50:42 time: 1.3808 data_time: 0.2600 memory: 14901 loss: 0.8502 loss_prob: 0.4364 loss_thr: 0.3380 loss_db: 0.0758 2022/11/02 23:34:40 - mmengine - INFO - Epoch(train) [950][10/63] lr: 5.2764e-04 eta: 2:50:35 time: 1.2200 data_time: 0.2587 memory: 14901 loss: 0.8823 loss_prob: 0.4575 loss_thr: 0.3464 loss_db: 0.0784 2022/11/02 23:34:48 - mmengine - INFO - Epoch(train) [950][15/63] lr: 5.2764e-04 eta: 2:50:35 time: 1.3651 data_time: 0.0166 memory: 14901 loss: 0.9674 loss_prob: 0.5045 loss_thr: 0.3756 loss_db: 0.0873 2022/11/02 23:34:53 - mmengine - INFO - Epoch(train) [950][20/63] lr: 5.2764e-04 eta: 2:50:30 time: 1.3097 data_time: 0.0163 memory: 14901 loss: 0.9699 loss_prob: 0.4985 loss_thr: 0.3855 loss_db: 0.0859 2022/11/02 23:35:01 - mmengine - INFO - Epoch(train) [950][25/63] lr: 5.2764e-04 eta: 2:50:30 time: 1.2575 data_time: 0.0216 memory: 14901 loss: 0.9779 loss_prob: 0.5037 loss_thr: 0.3865 loss_db: 0.0877 2022/11/02 23:35:08 - mmengine - INFO - Epoch(train) [950][30/63] lr: 5.2764e-04 eta: 2:50:26 time: 1.5265 data_time: 0.0605 memory: 14901 loss: 0.9952 loss_prob: 0.5172 loss_thr: 0.3862 loss_db: 0.0918 2022/11/02 23:35:13 - mmengine - INFO - Epoch(train) [950][35/63] lr: 5.2764e-04 eta: 2:50:26 time: 1.2384 data_time: 0.0521 memory: 14901 loss: 0.9565 loss_prob: 0.4969 loss_thr: 0.3734 loss_db: 0.0863 2022/11/02 23:35:20 - mmengine - INFO - Epoch(train) [950][40/63] lr: 5.2764e-04 eta: 2:50:21 time: 1.2510 data_time: 0.0175 memory: 14901 loss: 0.9065 loss_prob: 0.4676 loss_thr: 0.3599 loss_db: 0.0791 2022/11/02 23:35:25 - mmengine - INFO - Epoch(train) [950][45/63] lr: 5.2764e-04 eta: 2:50:21 time: 1.2018 data_time: 0.0156 memory: 14901 loss: 0.8904 loss_prob: 0.4559 loss_thr: 0.3554 loss_db: 0.0792 2022/11/02 23:35:28 - mmengine - INFO - Epoch(train) [950][50/63] lr: 5.2764e-04 eta: 2:50:15 time: 0.7872 data_time: 0.0242 memory: 14901 loss: 0.8637 loss_prob: 0.4324 loss_thr: 0.3538 loss_db: 0.0775 2022/11/02 23:35:33 - mmengine - INFO - Epoch(train) [950][55/63] lr: 5.2764e-04 eta: 2:50:15 time: 0.7906 data_time: 0.0308 memory: 14901 loss: 0.8535 loss_prob: 0.4248 loss_thr: 0.3528 loss_db: 0.0759 2022/11/02 23:35:40 - mmengine - INFO - Epoch(train) [950][60/63] lr: 5.2764e-04 eta: 2:50:09 time: 1.1295 data_time: 0.0187 memory: 14901 loss: 0.8912 loss_prob: 0.4514 loss_thr: 0.3593 loss_db: 0.0806 2022/11/02 23:35:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:35:52 - mmengine - INFO - Epoch(train) [951][5/63] lr: 5.2574e-04 eta: 2:50:09 time: 1.5353 data_time: 0.2171 memory: 14901 loss: 0.9198 loss_prob: 0.4749 loss_thr: 0.3619 loss_db: 0.0830 2022/11/02 23:35:57 - mmengine - INFO - Epoch(train) [951][10/63] lr: 5.2574e-04 eta: 2:50:02 time: 1.3464 data_time: 0.2246 memory: 14901 loss: 0.8992 loss_prob: 0.4597 loss_thr: 0.3590 loss_db: 0.0805 2022/11/02 23:36:04 - mmengine - INFO - Epoch(train) [951][15/63] lr: 5.2574e-04 eta: 2:50:02 time: 1.1975 data_time: 0.0265 memory: 14901 loss: 0.9489 loss_prob: 0.4911 loss_thr: 0.3724 loss_db: 0.0854 2022/11/02 23:36:10 - mmengine - INFO - Epoch(train) [951][20/63] lr: 5.2574e-04 eta: 2:49:58 time: 1.3044 data_time: 0.0191 memory: 14901 loss: 0.9560 loss_prob: 0.5030 loss_thr: 0.3683 loss_db: 0.0847 2022/11/02 23:36:16 - mmengine - INFO - Epoch(train) [951][25/63] lr: 5.2574e-04 eta: 2:49:58 time: 1.1887 data_time: 0.0221 memory: 14901 loss: 1.0681 loss_prob: 0.5970 loss_thr: 0.3766 loss_db: 0.0945 2022/11/02 23:36:19 - mmengine - INFO - Epoch(train) [951][30/63] lr: 5.2574e-04 eta: 2:49:52 time: 0.9551 data_time: 0.0287 memory: 14901 loss: 1.1340 loss_prob: 0.6462 loss_thr: 0.3861 loss_db: 0.1018 2022/11/02 23:36:26 - mmengine - INFO - Epoch(train) [951][35/63] lr: 5.2574e-04 eta: 2:49:52 time: 0.9513 data_time: 0.0286 memory: 14901 loss: 1.0016 loss_prob: 0.5466 loss_thr: 0.3655 loss_db: 0.0895 2022/11/02 23:36:30 - mmengine - INFO - Epoch(train) [951][40/63] lr: 5.2574e-04 eta: 2:49:47 time: 1.0988 data_time: 0.0274 memory: 14901 loss: 0.9107 loss_prob: 0.4778 loss_thr: 0.3514 loss_db: 0.0814 2022/11/02 23:36:34 - mmengine - INFO - Epoch(train) [951][45/63] lr: 5.2574e-04 eta: 2:49:47 time: 0.8105 data_time: 0.0186 memory: 14901 loss: 0.9703 loss_prob: 0.5103 loss_thr: 0.3703 loss_db: 0.0898 2022/11/02 23:36:39 - mmengine - INFO - Epoch(train) [951][50/63] lr: 5.2574e-04 eta: 2:49:41 time: 0.8576 data_time: 0.0202 memory: 14901 loss: 0.9593 loss_prob: 0.5054 loss_thr: 0.3654 loss_db: 0.0886 2022/11/02 23:36:43 - mmengine - INFO - Epoch(train) [951][55/63] lr: 5.2574e-04 eta: 2:49:41 time: 0.9638 data_time: 0.0280 memory: 14901 loss: 0.9849 loss_prob: 0.5211 loss_thr: 0.3750 loss_db: 0.0888 2022/11/02 23:36:48 - mmengine - INFO - Epoch(train) [951][60/63] lr: 5.2574e-04 eta: 2:49:35 time: 0.9177 data_time: 0.0220 memory: 14901 loss: 1.0121 loss_prob: 0.5301 loss_thr: 0.3920 loss_db: 0.0900 2022/11/02 23:36:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:36:59 - mmengine - INFO - Epoch(train) [952][5/63] lr: 5.2384e-04 eta: 2:49:35 time: 1.3383 data_time: 0.2922 memory: 14901 loss: 0.9555 loss_prob: 0.4956 loss_thr: 0.3722 loss_db: 0.0877 2022/11/02 23:37:07 - mmengine - INFO - Epoch(train) [952][10/63] lr: 5.2384e-04 eta: 2:49:28 time: 1.4681 data_time: 0.2910 memory: 14901 loss: 0.9889 loss_prob: 0.5285 loss_thr: 0.3704 loss_db: 0.0900 2022/11/02 23:37:12 - mmengine - INFO - Epoch(train) [952][15/63] lr: 5.2384e-04 eta: 2:49:28 time: 1.2746 data_time: 0.0129 memory: 14901 loss: 0.8869 loss_prob: 0.4668 loss_thr: 0.3396 loss_db: 0.0805 2022/11/02 23:37:19 - mmengine - INFO - Epoch(train) [952][20/63] lr: 5.2384e-04 eta: 2:49:23 time: 1.2010 data_time: 0.0112 memory: 14901 loss: 0.8986 loss_prob: 0.4606 loss_thr: 0.3573 loss_db: 0.0807 2022/11/02 23:37:24 - mmengine - INFO - Epoch(train) [952][25/63] lr: 5.2384e-04 eta: 2:49:23 time: 1.2332 data_time: 0.0466 memory: 14901 loss: 0.9920 loss_prob: 0.5093 loss_thr: 0.3946 loss_db: 0.0881 2022/11/02 23:37:28 - mmengine - INFO - Epoch(train) [952][30/63] lr: 5.2384e-04 eta: 2:49:17 time: 0.9301 data_time: 0.0460 memory: 14901 loss: 0.9612 loss_prob: 0.5009 loss_thr: 0.3740 loss_db: 0.0863 2022/11/02 23:37:34 - mmengine - INFO - Epoch(train) [952][35/63] lr: 5.2384e-04 eta: 2:49:17 time: 1.0233 data_time: 0.0176 memory: 14901 loss: 0.9109 loss_prob: 0.4743 loss_thr: 0.3544 loss_db: 0.0822 2022/11/02 23:37:38 - mmengine - INFO - Epoch(train) [952][40/63] lr: 5.2384e-04 eta: 2:49:12 time: 0.9634 data_time: 0.0192 memory: 14901 loss: 0.9714 loss_prob: 0.5031 loss_thr: 0.3825 loss_db: 0.0859 2022/11/02 23:37:43 - mmengine - INFO - Epoch(train) [952][45/63] lr: 5.2384e-04 eta: 2:49:12 time: 0.8805 data_time: 0.0089 memory: 14901 loss: 0.9526 loss_prob: 0.4944 loss_thr: 0.3742 loss_db: 0.0840 2022/11/02 23:37:49 - mmengine - INFO - Epoch(train) [952][50/63] lr: 5.2384e-04 eta: 2:49:06 time: 1.1674 data_time: 0.0300 memory: 14901 loss: 0.9541 loss_prob: 0.5038 loss_thr: 0.3635 loss_db: 0.0868 2022/11/02 23:37:54 - mmengine - INFO - Epoch(train) [952][55/63] lr: 5.2384e-04 eta: 2:49:06 time: 1.1012 data_time: 0.0306 memory: 14901 loss: 1.0340 loss_prob: 0.5348 loss_thr: 0.4066 loss_db: 0.0926 2022/11/02 23:38:02 - mmengine - INFO - Epoch(train) [952][60/63] lr: 5.2384e-04 eta: 2:49:02 time: 1.3096 data_time: 0.0106 memory: 14901 loss: 0.9393 loss_prob: 0.4762 loss_thr: 0.3790 loss_db: 0.0841 2022/11/02 23:38:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:38:14 - mmengine - INFO - Epoch(train) [953][5/63] lr: 5.2194e-04 eta: 2:49:02 time: 1.4476 data_time: 0.2462 memory: 14901 loss: 0.9578 loss_prob: 0.4992 loss_thr: 0.3710 loss_db: 0.0876 2022/11/02 23:38:21 - mmengine - INFO - Epoch(train) [953][10/63] lr: 5.2194e-04 eta: 2:48:55 time: 1.5030 data_time: 0.2497 memory: 14901 loss: 0.9427 loss_prob: 0.4922 loss_thr: 0.3645 loss_db: 0.0860 2022/11/02 23:38:26 - mmengine - INFO - Epoch(train) [953][15/63] lr: 5.2194e-04 eta: 2:48:55 time: 1.2613 data_time: 0.0177 memory: 14901 loss: 0.9269 loss_prob: 0.4736 loss_thr: 0.3701 loss_db: 0.0833 2022/11/02 23:38:32 - mmengine - INFO - Epoch(train) [953][20/63] lr: 5.2194e-04 eta: 2:48:49 time: 1.0243 data_time: 0.0186 memory: 14901 loss: 0.9034 loss_prob: 0.4540 loss_thr: 0.3694 loss_db: 0.0800 2022/11/02 23:38:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:38:37 - mmengine - INFO - Epoch(train) [953][25/63] lr: 5.2194e-04 eta: 2:48:49 time: 1.0438 data_time: 0.0337 memory: 14901 loss: 0.8957 loss_prob: 0.4563 loss_thr: 0.3587 loss_db: 0.0808 2022/11/02 23:38:42 - mmengine - INFO - Epoch(train) [953][30/63] lr: 5.2194e-04 eta: 2:48:44 time: 1.0856 data_time: 0.0295 memory: 14901 loss: 1.0206 loss_prob: 0.5425 loss_thr: 0.3855 loss_db: 0.0927 2022/11/02 23:38:48 - mmengine - INFO - Epoch(train) [953][35/63] lr: 5.2194e-04 eta: 2:48:44 time: 1.1573 data_time: 0.0265 memory: 14901 loss: 1.0054 loss_prob: 0.5336 loss_thr: 0.3813 loss_db: 0.0905 2022/11/02 23:38:54 - mmengine - INFO - Epoch(train) [953][40/63] lr: 5.2194e-04 eta: 2:48:39 time: 1.1065 data_time: 0.0245 memory: 14901 loss: 0.9555 loss_prob: 0.5014 loss_thr: 0.3680 loss_db: 0.0861 2022/11/02 23:39:00 - mmengine - INFO - Epoch(train) [953][45/63] lr: 5.2194e-04 eta: 2:48:39 time: 1.1405 data_time: 0.0169 memory: 14901 loss: 0.9601 loss_prob: 0.5058 loss_thr: 0.3682 loss_db: 0.0861 2022/11/02 23:39:03 - mmengine - INFO - Epoch(train) [953][50/63] lr: 5.2194e-04 eta: 2:48:33 time: 0.9724 data_time: 0.0268 memory: 14901 loss: 0.8776 loss_prob: 0.4491 loss_thr: 0.3497 loss_db: 0.0788 2022/11/02 23:39:10 - mmengine - INFO - Epoch(train) [953][55/63] lr: 5.2194e-04 eta: 2:48:33 time: 1.0751 data_time: 0.0265 memory: 14901 loss: 0.9422 loss_prob: 0.4840 loss_thr: 0.3723 loss_db: 0.0859 2022/11/02 23:39:14 - mmengine - INFO - Epoch(train) [953][60/63] lr: 5.2194e-04 eta: 2:48:28 time: 1.0992 data_time: 0.0265 memory: 14901 loss: 0.9637 loss_prob: 0.4987 loss_thr: 0.3767 loss_db: 0.0882 2022/11/02 23:39:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:39:26 - mmengine - INFO - Epoch(train) [954][5/63] lr: 5.2004e-04 eta: 2:48:28 time: 1.3616 data_time: 0.2804 memory: 14901 loss: 0.9364 loss_prob: 0.4800 loss_thr: 0.3727 loss_db: 0.0837 2022/11/02 23:39:29 - mmengine - INFO - Epoch(train) [954][10/63] lr: 5.2004e-04 eta: 2:48:20 time: 1.2460 data_time: 0.2792 memory: 14901 loss: 0.9697 loss_prob: 0.5025 loss_thr: 0.3795 loss_db: 0.0878 2022/11/02 23:39:36 - mmengine - INFO - Epoch(train) [954][15/63] lr: 5.2004e-04 eta: 2:48:20 time: 0.9837 data_time: 0.0107 memory: 14901 loss: 1.0367 loss_prob: 0.5455 loss_thr: 0.3971 loss_db: 0.0941 2022/11/02 23:39:44 - mmengine - INFO - Epoch(train) [954][20/63] lr: 5.2004e-04 eta: 2:48:16 time: 1.4445 data_time: 0.0162 memory: 14901 loss: 1.0226 loss_prob: 0.5358 loss_thr: 0.3939 loss_db: 0.0929 2022/11/02 23:39:48 - mmengine - INFO - Epoch(train) [954][25/63] lr: 5.2004e-04 eta: 2:48:16 time: 1.2419 data_time: 0.0437 memory: 14901 loss: 0.8318 loss_prob: 0.4159 loss_thr: 0.3411 loss_db: 0.0748 2022/11/02 23:39:55 - mmengine - INFO - Epoch(train) [954][30/63] lr: 5.2004e-04 eta: 2:48:11 time: 1.1364 data_time: 0.0524 memory: 14901 loss: 0.8372 loss_prob: 0.4171 loss_thr: 0.3463 loss_db: 0.0737 2022/11/02 23:40:01 - mmengine - INFO - Epoch(train) [954][35/63] lr: 5.2004e-04 eta: 2:48:11 time: 1.2718 data_time: 0.0223 memory: 14901 loss: 0.9369 loss_prob: 0.4843 loss_thr: 0.3690 loss_db: 0.0836 2022/11/02 23:40:07 - mmengine - INFO - Epoch(train) [954][40/63] lr: 5.2004e-04 eta: 2:48:06 time: 1.2002 data_time: 0.0139 memory: 14901 loss: 0.9778 loss_prob: 0.5115 loss_thr: 0.3775 loss_db: 0.0888 2022/11/02 23:40:11 - mmengine - INFO - Epoch(train) [954][45/63] lr: 5.2004e-04 eta: 2:48:06 time: 0.9862 data_time: 0.0165 memory: 14901 loss: 1.0147 loss_prob: 0.5344 loss_thr: 0.3858 loss_db: 0.0945 2022/11/02 23:40:17 - mmengine - INFO - Epoch(train) [954][50/63] lr: 5.2004e-04 eta: 2:48:00 time: 1.0085 data_time: 0.0260 memory: 14901 loss: 1.0132 loss_prob: 0.5341 loss_thr: 0.3841 loss_db: 0.0949 2022/11/02 23:40:22 - mmengine - INFO - Epoch(train) [954][55/63] lr: 5.2004e-04 eta: 2:48:00 time: 1.1346 data_time: 0.0303 memory: 14901 loss: 0.8884 loss_prob: 0.4577 loss_thr: 0.3508 loss_db: 0.0799 2022/11/02 23:40:30 - mmengine - INFO - Epoch(train) [954][60/63] lr: 5.2004e-04 eta: 2:47:55 time: 1.2870 data_time: 0.0171 memory: 14901 loss: 0.8410 loss_prob: 0.4330 loss_thr: 0.3332 loss_db: 0.0748 2022/11/02 23:40:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:40:43 - mmengine - INFO - Epoch(train) [955][5/63] lr: 5.1814e-04 eta: 2:47:55 time: 1.5815 data_time: 0.2952 memory: 14901 loss: 0.9967 loss_prob: 0.5151 loss_thr: 0.3907 loss_db: 0.0909 2022/11/02 23:40:52 - mmengine - INFO - Epoch(train) [955][10/63] lr: 5.1814e-04 eta: 2:47:50 time: 2.0221 data_time: 0.2954 memory: 14901 loss: 0.9233 loss_prob: 0.4668 loss_thr: 0.3736 loss_db: 0.0829 2022/11/02 23:40:56 - mmengine - INFO - Epoch(train) [955][15/63] lr: 5.1814e-04 eta: 2:47:50 time: 1.2880 data_time: 0.0131 memory: 14901 loss: 0.9157 loss_prob: 0.4768 loss_thr: 0.3578 loss_db: 0.0811 2022/11/02 23:41:02 - mmengine - INFO - Epoch(train) [955][20/63] lr: 5.1814e-04 eta: 2:47:44 time: 0.9701 data_time: 0.0131 memory: 14901 loss: 0.9168 loss_prob: 0.4818 loss_thr: 0.3529 loss_db: 0.0822 2022/11/02 23:41:09 - mmengine - INFO - Epoch(train) [955][25/63] lr: 5.1814e-04 eta: 2:47:44 time: 1.3182 data_time: 0.0359 memory: 14901 loss: 0.8907 loss_prob: 0.4673 loss_thr: 0.3421 loss_db: 0.0814 2022/11/02 23:41:15 - mmengine - INFO - Epoch(train) [955][30/63] lr: 5.1814e-04 eta: 2:47:39 time: 1.3385 data_time: 0.0556 memory: 14901 loss: 0.9666 loss_prob: 0.5101 loss_thr: 0.3680 loss_db: 0.0885 2022/11/02 23:41:23 - mmengine - INFO - Epoch(train) [955][35/63] lr: 5.1814e-04 eta: 2:47:39 time: 1.4146 data_time: 0.0319 memory: 14901 loss: 0.9747 loss_prob: 0.5020 loss_thr: 0.3861 loss_db: 0.0866 2022/11/02 23:41:28 - mmengine - INFO - Epoch(train) [955][40/63] lr: 5.1814e-04 eta: 2:47:35 time: 1.3031 data_time: 0.0100 memory: 14901 loss: 0.8844 loss_prob: 0.4476 loss_thr: 0.3581 loss_db: 0.0787 2022/11/02 23:41:32 - mmengine - INFO - Epoch(train) [955][45/63] lr: 5.1814e-04 eta: 2:47:35 time: 0.8159 data_time: 0.0093 memory: 14901 loss: 0.8831 loss_prob: 0.4555 loss_thr: 0.3482 loss_db: 0.0795 2022/11/02 23:41:38 - mmengine - INFO - Epoch(train) [955][50/63] lr: 5.1814e-04 eta: 2:47:29 time: 0.9507 data_time: 0.0214 memory: 14901 loss: 0.9616 loss_prob: 0.5134 loss_thr: 0.3616 loss_db: 0.0867 2022/11/02 23:41:43 - mmengine - INFO - Epoch(train) [955][55/63] lr: 5.1814e-04 eta: 2:47:29 time: 1.1620 data_time: 0.0297 memory: 14901 loss: 0.9847 loss_prob: 0.5213 loss_thr: 0.3735 loss_db: 0.0899 2022/11/02 23:41:48 - mmengine - INFO - Epoch(train) [955][60/63] lr: 5.1814e-04 eta: 2:47:23 time: 1.0617 data_time: 0.0224 memory: 14901 loss: 1.0212 loss_prob: 0.5361 loss_thr: 0.3922 loss_db: 0.0929 2022/11/02 23:41:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:42:00 - mmengine - INFO - Epoch(train) [956][5/63] lr: 5.1623e-04 eta: 2:47:23 time: 1.3689 data_time: 0.3112 memory: 14901 loss: 1.1314 loss_prob: 0.6459 loss_thr: 0.3867 loss_db: 0.0989 2022/11/02 23:42:03 - mmengine - INFO - Epoch(train) [956][10/63] lr: 5.1623e-04 eta: 2:47:16 time: 1.3325 data_time: 0.3115 memory: 14901 loss: 1.0896 loss_prob: 0.6113 loss_thr: 0.3799 loss_db: 0.0984 2022/11/02 23:42:09 - mmengine - INFO - Epoch(train) [956][15/63] lr: 5.1623e-04 eta: 2:47:16 time: 0.9455 data_time: 0.0144 memory: 14901 loss: 1.0783 loss_prob: 0.5736 loss_thr: 0.4063 loss_db: 0.0984 2022/11/02 23:42:16 - mmengine - INFO - Epoch(train) [956][20/63] lr: 5.1623e-04 eta: 2:47:11 time: 1.2850 data_time: 0.0154 memory: 14901 loss: 0.9524 loss_prob: 0.4950 loss_thr: 0.3720 loss_db: 0.0854 2022/11/02 23:42:23 - mmengine - INFO - Epoch(train) [956][25/63] lr: 5.1623e-04 eta: 2:47:11 time: 1.3507 data_time: 0.0356 memory: 14901 loss: 0.8892 loss_prob: 0.4594 loss_thr: 0.3492 loss_db: 0.0806 2022/11/02 23:42:27 - mmengine - INFO - Epoch(train) [956][30/63] lr: 5.1623e-04 eta: 2:47:06 time: 1.1605 data_time: 0.0395 memory: 14901 loss: 1.0409 loss_prob: 0.5624 loss_thr: 0.3842 loss_db: 0.0944 2022/11/02 23:42:36 - mmengine - INFO - Epoch(train) [956][35/63] lr: 5.1623e-04 eta: 2:47:06 time: 1.2945 data_time: 0.0263 memory: 14901 loss: 1.0034 loss_prob: 0.5363 loss_thr: 0.3775 loss_db: 0.0895 2022/11/02 23:42:40 - mmengine - INFO - Epoch(train) [956][40/63] lr: 5.1623e-04 eta: 2:47:01 time: 1.2966 data_time: 0.0214 memory: 14901 loss: 0.9522 loss_prob: 0.4951 loss_thr: 0.3712 loss_db: 0.0859 2022/11/02 23:42:43 - mmengine - INFO - Epoch(train) [956][45/63] lr: 5.1623e-04 eta: 2:47:01 time: 0.7327 data_time: 0.0114 memory: 14901 loss: 1.0453 loss_prob: 0.5494 loss_thr: 0.4016 loss_db: 0.0944 2022/11/02 23:42:50 - mmengine - INFO - Epoch(train) [956][50/63] lr: 5.1623e-04 eta: 2:46:56 time: 0.9907 data_time: 0.0283 memory: 14901 loss: 0.9678 loss_prob: 0.5005 loss_thr: 0.3791 loss_db: 0.0881 2022/11/02 23:42:56 - mmengine - INFO - Epoch(train) [956][55/63] lr: 5.1623e-04 eta: 2:46:56 time: 1.2633 data_time: 0.0340 memory: 14901 loss: 0.9086 loss_prob: 0.4674 loss_thr: 0.3584 loss_db: 0.0828 2022/11/02 23:43:03 - mmengine - INFO - Epoch(train) [956][60/63] lr: 5.1623e-04 eta: 2:46:51 time: 1.2841 data_time: 0.0200 memory: 14901 loss: 0.9416 loss_prob: 0.4885 loss_thr: 0.3679 loss_db: 0.0852 2022/11/02 23:43:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:43:13 - mmengine - INFO - Epoch(train) [957][5/63] lr: 5.1433e-04 eta: 2:46:51 time: 1.3888 data_time: 0.2870 memory: 14901 loss: 0.8960 loss_prob: 0.4636 loss_thr: 0.3494 loss_db: 0.0831 2022/11/02 23:43:18 - mmengine - INFO - Epoch(train) [957][10/63] lr: 5.1433e-04 eta: 2:46:44 time: 1.3531 data_time: 0.2873 memory: 14901 loss: 0.9718 loss_prob: 0.5199 loss_thr: 0.3625 loss_db: 0.0894 2022/11/02 23:43:24 - mmengine - INFO - Epoch(train) [957][15/63] lr: 5.1433e-04 eta: 2:46:44 time: 1.0886 data_time: 0.0147 memory: 14901 loss: 0.9508 loss_prob: 0.5113 loss_thr: 0.3518 loss_db: 0.0877 2022/11/02 23:43:28 - mmengine - INFO - Epoch(train) [957][20/63] lr: 5.1433e-04 eta: 2:46:38 time: 1.0060 data_time: 0.0153 memory: 14901 loss: 0.9240 loss_prob: 0.4806 loss_thr: 0.3596 loss_db: 0.0838 2022/11/02 23:43:31 - mmengine - INFO - Epoch(train) [957][25/63] lr: 5.1433e-04 eta: 2:46:38 time: 0.6618 data_time: 0.0160 memory: 14901 loss: 0.9411 loss_prob: 0.4889 loss_thr: 0.3666 loss_db: 0.0855 2022/11/02 23:43:35 - mmengine - INFO - Epoch(train) [957][30/63] lr: 5.1433e-04 eta: 2:46:31 time: 0.6453 data_time: 0.0437 memory: 14901 loss: 0.9868 loss_prob: 0.5336 loss_thr: 0.3609 loss_db: 0.0923 2022/11/02 23:43:38 - mmengine - INFO - Epoch(train) [957][35/63] lr: 5.1433e-04 eta: 2:46:31 time: 0.7154 data_time: 0.0397 memory: 14901 loss: 1.0522 loss_prob: 0.5741 loss_thr: 0.3804 loss_db: 0.0977 2022/11/02 23:43:41 - mmengine - INFO - Epoch(train) [957][40/63] lr: 5.1433e-04 eta: 2:46:25 time: 0.6862 data_time: 0.0105 memory: 14901 loss: 0.9395 loss_prob: 0.4869 loss_thr: 0.3680 loss_db: 0.0846 2022/11/02 23:43:45 - mmengine - INFO - Epoch(train) [957][45/63] lr: 5.1433e-04 eta: 2:46:25 time: 0.6476 data_time: 0.0109 memory: 14901 loss: 0.8564 loss_prob: 0.4398 loss_thr: 0.3398 loss_db: 0.0768 2022/11/02 23:43:49 - mmengine - INFO - Epoch(train) [957][50/63] lr: 5.1433e-04 eta: 2:46:19 time: 0.7384 data_time: 0.0543 memory: 14901 loss: 0.9959 loss_prob: 0.5250 loss_thr: 0.3802 loss_db: 0.0907 2022/11/02 23:43:51 - mmengine - INFO - Epoch(train) [957][55/63] lr: 5.1433e-04 eta: 2:46:19 time: 0.6838 data_time: 0.0576 memory: 14901 loss: 1.0663 loss_prob: 0.5604 loss_thr: 0.4087 loss_db: 0.0972 2022/11/02 23:43:56 - mmengine - INFO - Epoch(train) [957][60/63] lr: 5.1433e-04 eta: 2:46:12 time: 0.7572 data_time: 0.0160 memory: 14901 loss: 0.9250 loss_prob: 0.4785 loss_thr: 0.3621 loss_db: 0.0844 2022/11/02 23:43:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:44:09 - mmengine - INFO - Epoch(train) [958][5/63] lr: 5.1242e-04 eta: 2:46:12 time: 1.4426 data_time: 0.3152 memory: 14901 loss: 0.7572 loss_prob: 0.3831 loss_thr: 0.3065 loss_db: 0.0676 2022/11/02 23:44:14 - mmengine - INFO - Epoch(train) [958][10/63] lr: 5.1242e-04 eta: 2:46:06 time: 1.6863 data_time: 0.3230 memory: 14901 loss: 0.8355 loss_prob: 0.4224 loss_thr: 0.3392 loss_db: 0.0740 2022/11/02 23:44:22 - mmengine - INFO - Epoch(train) [958][15/63] lr: 5.1242e-04 eta: 2:46:06 time: 1.3002 data_time: 0.0167 memory: 14901 loss: 0.8917 loss_prob: 0.4532 loss_thr: 0.3595 loss_db: 0.0790 2022/11/02 23:44:27 - mmengine - INFO - Epoch(train) [958][20/63] lr: 5.1242e-04 eta: 2:46:01 time: 1.2845 data_time: 0.0109 memory: 14901 loss: 0.9222 loss_prob: 0.4791 loss_thr: 0.3603 loss_db: 0.0828 2022/11/02 23:44:36 - mmengine - INFO - Epoch(train) [958][25/63] lr: 5.1242e-04 eta: 2:46:01 time: 1.3760 data_time: 0.0534 memory: 14901 loss: 0.9849 loss_prob: 0.5186 loss_thr: 0.3782 loss_db: 0.0881 2022/11/02 23:44:39 - mmengine - INFO - Epoch(train) [958][30/63] lr: 5.1242e-04 eta: 2:45:56 time: 1.2041 data_time: 0.0555 memory: 14901 loss: 0.9610 loss_prob: 0.5009 loss_thr: 0.3741 loss_db: 0.0860 2022/11/02 23:44:46 - mmengine - INFO - Epoch(train) [958][35/63] lr: 5.1242e-04 eta: 2:45:56 time: 1.0175 data_time: 0.0198 memory: 14901 loss: 0.9631 loss_prob: 0.5039 loss_thr: 0.3721 loss_db: 0.0871 2022/11/02 23:44:52 - mmengine - INFO - Epoch(train) [958][40/63] lr: 5.1242e-04 eta: 2:45:51 time: 1.2202 data_time: 0.0171 memory: 14901 loss: 0.9810 loss_prob: 0.5173 loss_thr: 0.3761 loss_db: 0.0876 2022/11/02 23:44:58 - mmengine - INFO - Epoch(train) [958][45/63] lr: 5.1242e-04 eta: 2:45:51 time: 1.2033 data_time: 0.0114 memory: 14901 loss: 0.9107 loss_prob: 0.4736 loss_thr: 0.3546 loss_db: 0.0825 2022/11/02 23:45:01 - mmengine - INFO - Epoch(train) [958][50/63] lr: 5.1242e-04 eta: 2:45:45 time: 0.9401 data_time: 0.0246 memory: 14901 loss: 0.9085 loss_prob: 0.4628 loss_thr: 0.3625 loss_db: 0.0831 2022/11/02 23:45:09 - mmengine - INFO - Epoch(train) [958][55/63] lr: 5.1242e-04 eta: 2:45:45 time: 1.1102 data_time: 0.0273 memory: 14901 loss: 0.9686 loss_prob: 0.5069 loss_thr: 0.3757 loss_db: 0.0860 2022/11/02 23:45:15 - mmengine - INFO - Epoch(train) [958][60/63] lr: 5.1242e-04 eta: 2:45:41 time: 1.3899 data_time: 0.0157 memory: 14901 loss: 0.9556 loss_prob: 0.5088 loss_thr: 0.3619 loss_db: 0.0848 2022/11/02 23:45:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:45:27 - mmengine - INFO - Epoch(train) [959][5/63] lr: 5.1052e-04 eta: 2:45:41 time: 1.3906 data_time: 0.2864 memory: 14901 loss: 0.9821 loss_prob: 0.5136 loss_thr: 0.3785 loss_db: 0.0899 2022/11/02 23:45:33 - mmengine - INFO - Epoch(train) [959][10/63] lr: 5.1052e-04 eta: 2:45:34 time: 1.6508 data_time: 0.2903 memory: 14901 loss: 0.9678 loss_prob: 0.5104 loss_thr: 0.3689 loss_db: 0.0885 2022/11/02 23:45:39 - mmengine - INFO - Epoch(train) [959][15/63] lr: 5.1052e-04 eta: 2:45:34 time: 1.1966 data_time: 0.0239 memory: 14901 loss: 0.8893 loss_prob: 0.4615 loss_thr: 0.3478 loss_db: 0.0801 2022/11/02 23:45:46 - mmengine - INFO - Epoch(train) [959][20/63] lr: 5.1052e-04 eta: 2:45:29 time: 1.3731 data_time: 0.0187 memory: 14901 loss: 0.8453 loss_prob: 0.4302 loss_thr: 0.3395 loss_db: 0.0756 2022/11/02 23:45:49 - mmengine - INFO - Epoch(train) [959][25/63] lr: 5.1052e-04 eta: 2:45:29 time: 0.9847 data_time: 0.0259 memory: 14901 loss: 0.9085 loss_prob: 0.4710 loss_thr: 0.3552 loss_db: 0.0823 2022/11/02 23:45:57 - mmengine - INFO - Epoch(train) [959][30/63] lr: 5.1052e-04 eta: 2:45:24 time: 1.0656 data_time: 0.0389 memory: 14901 loss: 0.8815 loss_prob: 0.4556 loss_thr: 0.3473 loss_db: 0.0786 2022/11/02 23:46:04 - mmengine - INFO - Epoch(train) [959][35/63] lr: 5.1052e-04 eta: 2:45:24 time: 1.5036 data_time: 0.0254 memory: 14901 loss: 0.8428 loss_prob: 0.4236 loss_thr: 0.3449 loss_db: 0.0743 2022/11/02 23:46:07 - mmengine - INFO - Epoch(train) [959][40/63] lr: 5.1052e-04 eta: 2:45:18 time: 1.0017 data_time: 0.0190 memory: 14901 loss: 0.8388 loss_prob: 0.4280 loss_thr: 0.3365 loss_db: 0.0743 2022/11/02 23:46:14 - mmengine - INFO - Epoch(train) [959][45/63] lr: 5.1052e-04 eta: 2:45:18 time: 0.9863 data_time: 0.0205 memory: 14901 loss: 0.8625 loss_prob: 0.4451 loss_thr: 0.3401 loss_db: 0.0774 2022/11/02 23:46:17 - mmengine - INFO - Epoch(train) [959][50/63] lr: 5.1052e-04 eta: 2:45:13 time: 0.9780 data_time: 0.0275 memory: 14901 loss: 0.9054 loss_prob: 0.4651 loss_thr: 0.3580 loss_db: 0.0823 2022/11/02 23:46:23 - mmengine - INFO - Epoch(train) [959][55/63] lr: 5.1052e-04 eta: 2:45:13 time: 0.8562 data_time: 0.0368 memory: 14901 loss: 0.9487 loss_prob: 0.4950 loss_thr: 0.3661 loss_db: 0.0875 2022/11/02 23:46:26 - mmengine - INFO - Epoch(train) [959][60/63] lr: 5.1052e-04 eta: 2:45:07 time: 0.9182 data_time: 0.0230 memory: 14901 loss: 0.9390 loss_prob: 0.4907 loss_thr: 0.3623 loss_db: 0.0859 2022/11/02 23:46:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:46:36 - mmengine - INFO - Epoch(train) [960][5/63] lr: 5.0861e-04 eta: 2:45:07 time: 1.0507 data_time: 0.2605 memory: 14901 loss: 0.9314 loss_prob: 0.4815 loss_thr: 0.3662 loss_db: 0.0837 2022/11/02 23:46:41 - mmengine - INFO - Epoch(train) [960][10/63] lr: 5.0861e-04 eta: 2:44:59 time: 1.3096 data_time: 0.2583 memory: 14901 loss: 0.8804 loss_prob: 0.4456 loss_thr: 0.3571 loss_db: 0.0777 2022/11/02 23:46:46 - mmengine - INFO - Epoch(train) [960][15/63] lr: 5.0861e-04 eta: 2:44:59 time: 0.9893 data_time: 0.0066 memory: 14901 loss: 0.8673 loss_prob: 0.4415 loss_thr: 0.3486 loss_db: 0.0772 2022/11/02 23:46:49 - mmengine - INFO - Epoch(train) [960][20/63] lr: 5.0861e-04 eta: 2:44:53 time: 0.7714 data_time: 0.0069 memory: 14901 loss: 0.9271 loss_prob: 0.4783 loss_thr: 0.3658 loss_db: 0.0831 2022/11/02 23:46:53 - mmengine - INFO - Epoch(train) [960][25/63] lr: 5.0861e-04 eta: 2:44:53 time: 0.7923 data_time: 0.0104 memory: 14901 loss: 0.8797 loss_prob: 0.4535 loss_thr: 0.3462 loss_db: 0.0800 2022/11/02 23:46:56 - mmengine - INFO - Epoch(train) [960][30/63] lr: 5.0861e-04 eta: 2:44:47 time: 0.7479 data_time: 0.0400 memory: 14901 loss: 0.8942 loss_prob: 0.4631 loss_thr: 0.3503 loss_db: 0.0807 2022/11/02 23:46:59 - mmengine - INFO - Epoch(train) [960][35/63] lr: 5.0861e-04 eta: 2:44:47 time: 0.5914 data_time: 0.0358 memory: 14901 loss: 0.9223 loss_prob: 0.4717 loss_thr: 0.3691 loss_db: 0.0816 2022/11/02 23:47:03 - mmengine - INFO - Epoch(train) [960][40/63] lr: 5.0861e-04 eta: 2:44:40 time: 0.6735 data_time: 0.0057 memory: 14901 loss: 0.9553 loss_prob: 0.4890 loss_thr: 0.3808 loss_db: 0.0855 2022/11/02 23:47:07 - mmengine - INFO - Epoch(train) [960][45/63] lr: 5.0861e-04 eta: 2:44:40 time: 0.7798 data_time: 0.0058 memory: 14901 loss: 0.9534 loss_prob: 0.4897 loss_thr: 0.3789 loss_db: 0.0848 2022/11/02 23:47:13 - mmengine - INFO - Epoch(train) [960][50/63] lr: 5.0861e-04 eta: 2:44:35 time: 0.9447 data_time: 0.0194 memory: 14901 loss: 0.9640 loss_prob: 0.4996 loss_thr: 0.3785 loss_db: 0.0859 2022/11/02 23:47:16 - mmengine - INFO - Epoch(train) [960][55/63] lr: 5.0861e-04 eta: 2:44:35 time: 0.8344 data_time: 0.0262 memory: 14901 loss: 0.9091 loss_prob: 0.4821 loss_thr: 0.3469 loss_db: 0.0801 2022/11/02 23:47:19 - mmengine - INFO - Epoch(train) [960][60/63] lr: 5.0861e-04 eta: 2:44:28 time: 0.6496 data_time: 0.0127 memory: 14901 loss: 0.8624 loss_prob: 0.4461 loss_thr: 0.3429 loss_db: 0.0734 2022/11/02 23:47:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:47:21 - mmengine - INFO - Saving checkpoint at 960 epochs 2022/11/02 23:47:24 - mmengine - INFO - Epoch(val) [960][5/500] eta: 2:44:28 time: 0.0538 data_time: 0.0084 memory: 14901 2022/11/02 23:47:25 - mmengine - INFO - Epoch(val) [960][10/500] eta: 0:00:27 time: 0.0556 data_time: 0.0064 memory: 1008 2022/11/02 23:47:25 - mmengine - INFO - Epoch(val) [960][15/500] eta: 0:00:27 time: 0.0488 data_time: 0.0032 memory: 1008 2022/11/02 23:47:25 - mmengine - INFO - Epoch(val) [960][20/500] eta: 0:00:25 time: 0.0528 data_time: 0.0041 memory: 1008 2022/11/02 23:47:25 - mmengine - INFO - Epoch(val) [960][25/500] eta: 0:00:25 time: 0.0503 data_time: 0.0046 memory: 1008 2022/11/02 23:47:26 - mmengine - INFO - Epoch(val) [960][30/500] eta: 0:00:22 time: 0.0470 data_time: 0.0040 memory: 1008 2022/11/02 23:47:26 - mmengine - INFO - Epoch(val) [960][35/500] eta: 0:00:22 time: 0.0438 data_time: 0.0029 memory: 1008 2022/11/02 23:47:26 - mmengine - INFO - Epoch(val) [960][40/500] eta: 0:00:23 time: 0.0505 data_time: 0.0032 memory: 1008 2022/11/02 23:47:26 - mmengine - INFO - Epoch(val) [960][45/500] eta: 0:00:23 time: 0.0516 data_time: 0.0032 memory: 1008 2022/11/02 23:47:27 - mmengine - INFO - Epoch(val) [960][50/500] eta: 0:00:18 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/02 23:47:27 - mmengine - INFO - Epoch(val) [960][55/500] eta: 0:00:18 time: 0.0458 data_time: 0.0028 memory: 1008 2022/11/02 23:47:27 - mmengine - INFO - Epoch(val) [960][60/500] eta: 0:00:20 time: 0.0472 data_time: 0.0031 memory: 1008 2022/11/02 23:47:27 - mmengine - INFO - Epoch(val) [960][65/500] eta: 0:00:20 time: 0.0532 data_time: 0.0038 memory: 1008 2022/11/02 23:47:28 - mmengine - INFO - Epoch(val) [960][70/500] eta: 0:00:24 time: 0.0562 data_time: 0.0040 memory: 1008 2022/11/02 23:47:28 - mmengine - INFO - Epoch(val) [960][75/500] eta: 0:00:24 time: 0.0472 data_time: 0.0039 memory: 1008 2022/11/02 23:47:28 - mmengine - INFO - Epoch(val) [960][80/500] eta: 0:00:21 time: 0.0504 data_time: 0.0097 memory: 1008 2022/11/02 23:47:28 - mmengine - INFO - Epoch(val) [960][85/500] eta: 0:00:21 time: 0.0502 data_time: 0.0093 memory: 1008 2022/11/02 23:47:29 - mmengine - INFO - Epoch(val) [960][90/500] eta: 0:00:21 time: 0.0526 data_time: 0.0041 memory: 1008 2022/11/02 23:47:29 - mmengine - INFO - Epoch(val) [960][95/500] eta: 0:00:21 time: 0.0591 data_time: 0.0052 memory: 1008 2022/11/02 23:47:29 - mmengine - INFO - Epoch(val) [960][100/500] eta: 0:00:20 time: 0.0503 data_time: 0.0048 memory: 1008 2022/11/02 23:47:29 - mmengine - INFO - Epoch(val) [960][105/500] eta: 0:00:20 time: 0.0429 data_time: 0.0034 memory: 1008 2022/11/02 23:47:30 - mmengine - INFO - Epoch(val) [960][110/500] eta: 0:00:18 time: 0.0477 data_time: 0.0032 memory: 1008 2022/11/02 23:47:30 - mmengine - INFO - Epoch(val) [960][115/500] eta: 0:00:18 time: 0.0537 data_time: 0.0063 memory: 1008 2022/11/02 23:47:30 - mmengine - INFO - Epoch(val) [960][120/500] eta: 0:00:19 time: 0.0524 data_time: 0.0072 memory: 1008 2022/11/02 23:47:30 - mmengine - INFO - Epoch(val) [960][125/500] eta: 0:00:19 time: 0.0430 data_time: 0.0041 memory: 1008 2022/11/02 23:47:30 - mmengine - INFO - Epoch(val) [960][130/500] eta: 0:00:13 time: 0.0360 data_time: 0.0024 memory: 1008 2022/11/02 23:47:31 - mmengine - INFO - Epoch(val) [960][135/500] eta: 0:00:13 time: 0.0363 data_time: 0.0022 memory: 1008 2022/11/02 23:47:31 - mmengine - INFO - Epoch(val) [960][140/500] eta: 0:00:13 time: 0.0368 data_time: 0.0022 memory: 1008 2022/11/02 23:47:31 - mmengine - INFO - Epoch(val) [960][145/500] eta: 0:00:13 time: 0.0418 data_time: 0.0023 memory: 1008 2022/11/02 23:47:31 - mmengine - INFO - Epoch(val) [960][150/500] eta: 0:00:14 time: 0.0414 data_time: 0.0023 memory: 1008 2022/11/02 23:47:32 - mmengine - INFO - Epoch(val) [960][155/500] eta: 0:00:14 time: 0.0487 data_time: 0.0031 memory: 1008 2022/11/02 23:47:32 - mmengine - INFO - Epoch(val) [960][160/500] eta: 0:00:18 time: 0.0555 data_time: 0.0041 memory: 1008 2022/11/02 23:47:32 - mmengine - INFO - Epoch(val) [960][165/500] eta: 0:00:18 time: 0.0503 data_time: 0.0062 memory: 1008 2022/11/02 23:47:32 - mmengine - INFO - Epoch(val) [960][170/500] eta: 0:00:16 time: 0.0511 data_time: 0.0072 memory: 1008 2022/11/02 23:47:33 - mmengine - INFO - Epoch(val) [960][175/500] eta: 0:00:16 time: 0.0477 data_time: 0.0061 memory: 1008 2022/11/02 23:47:33 - mmengine - INFO - Epoch(val) [960][180/500] eta: 0:00:15 time: 0.0487 data_time: 0.0054 memory: 1008 2022/11/02 23:47:33 - mmengine - INFO - Epoch(val) [960][185/500] eta: 0:00:15 time: 0.0610 data_time: 0.0066 memory: 1008 2022/11/02 23:47:33 - mmengine - INFO - Epoch(val) [960][190/500] eta: 0:00:18 time: 0.0595 data_time: 0.0056 memory: 1008 2022/11/02 23:47:34 - mmengine - INFO - Epoch(val) [960][195/500] eta: 0:00:18 time: 0.0485 data_time: 0.0044 memory: 1008 2022/11/02 23:47:34 - mmengine - INFO - Epoch(val) [960][200/500] eta: 0:00:16 time: 0.0551 data_time: 0.0059 memory: 1008 2022/11/02 23:47:34 - mmengine - INFO - Epoch(val) [960][205/500] eta: 0:00:16 time: 0.0569 data_time: 0.0052 memory: 1008 2022/11/02 23:47:34 - mmengine - INFO - Epoch(val) [960][210/500] eta: 0:00:13 time: 0.0481 data_time: 0.0037 memory: 1008 2022/11/02 23:47:35 - mmengine - INFO - Epoch(val) [960][215/500] eta: 0:00:13 time: 0.0440 data_time: 0.0027 memory: 1008 2022/11/02 23:47:35 - mmengine - INFO - Epoch(val) [960][220/500] eta: 0:00:10 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/02 23:47:35 - mmengine - INFO - Epoch(val) [960][225/500] eta: 0:00:10 time: 0.0413 data_time: 0.0040 memory: 1008 2022/11/02 23:47:35 - mmengine - INFO - Epoch(val) [960][230/500] eta: 0:00:10 time: 0.0399 data_time: 0.0040 memory: 1008 2022/11/02 23:47:35 - mmengine - INFO - Epoch(val) [960][235/500] eta: 0:00:10 time: 0.0352 data_time: 0.0020 memory: 1008 2022/11/02 23:47:36 - mmengine - INFO - Epoch(val) [960][240/500] eta: 0:00:09 time: 0.0376 data_time: 0.0020 memory: 1008 2022/11/02 23:47:36 - mmengine - INFO - Epoch(val) [960][245/500] eta: 0:00:09 time: 0.0362 data_time: 0.0022 memory: 1008 2022/11/02 23:47:36 - mmengine - INFO - Epoch(val) [960][250/500] eta: 0:00:08 time: 0.0359 data_time: 0.0022 memory: 1008 2022/11/02 23:47:36 - mmengine - INFO - Epoch(val) [960][255/500] eta: 0:00:08 time: 0.0430 data_time: 0.0057 memory: 1008 2022/11/02 23:47:36 - mmengine - INFO - Epoch(val) [960][260/500] eta: 0:00:11 time: 0.0461 data_time: 0.0061 memory: 1008 2022/11/02 23:47:37 - mmengine - INFO - Epoch(val) [960][265/500] eta: 0:00:11 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/02 23:47:37 - mmengine - INFO - Epoch(val) [960][270/500] eta: 0:00:10 time: 0.0455 data_time: 0.0027 memory: 1008 2022/11/02 23:47:37 - mmengine - INFO - Epoch(val) [960][275/500] eta: 0:00:10 time: 0.0494 data_time: 0.0039 memory: 1008 2022/11/02 23:47:37 - mmengine - INFO - Epoch(val) [960][280/500] eta: 0:00:10 time: 0.0495 data_time: 0.0037 memory: 1008 2022/11/02 23:47:38 - mmengine - INFO - Epoch(val) [960][285/500] eta: 0:00:10 time: 0.0455 data_time: 0.0026 memory: 1008 2022/11/02 23:47:38 - mmengine - INFO - Epoch(val) [960][290/500] eta: 0:00:09 time: 0.0441 data_time: 0.0029 memory: 1008 2022/11/02 23:47:38 - mmengine - INFO - Epoch(val) [960][295/500] eta: 0:00:09 time: 0.0434 data_time: 0.0029 memory: 1008 2022/11/02 23:47:38 - mmengine - INFO - Epoch(val) [960][300/500] eta: 0:00:08 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/02 23:47:38 - mmengine - INFO - Epoch(val) [960][305/500] eta: 0:00:08 time: 0.0389 data_time: 0.0026 memory: 1008 2022/11/02 23:47:39 - mmengine - INFO - Epoch(val) [960][310/500] eta: 0:00:07 time: 0.0383 data_time: 0.0022 memory: 1008 2022/11/02 23:47:39 - mmengine - INFO - Epoch(val) [960][315/500] eta: 0:00:07 time: 0.0419 data_time: 0.0022 memory: 1008 2022/11/02 23:47:39 - mmengine - INFO - Epoch(val) [960][320/500] eta: 0:00:06 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/02 23:47:39 - mmengine - INFO - Epoch(val) [960][325/500] eta: 0:00:06 time: 0.0507 data_time: 0.0022 memory: 1008 2022/11/02 23:47:40 - mmengine - INFO - Epoch(val) [960][330/500] eta: 0:00:09 time: 0.0561 data_time: 0.0039 memory: 1008 2022/11/02 23:47:40 - mmengine - INFO - Epoch(val) [960][335/500] eta: 0:00:09 time: 0.0472 data_time: 0.0062 memory: 1008 2022/11/02 23:47:40 - mmengine - INFO - Epoch(val) [960][340/500] eta: 0:00:09 time: 0.0599 data_time: 0.0067 memory: 1008 2022/11/02 23:47:40 - mmengine - INFO - Epoch(val) [960][345/500] eta: 0:00:09 time: 0.0611 data_time: 0.0063 memory: 1008 2022/11/02 23:47:41 - mmengine - INFO - Epoch(val) [960][350/500] eta: 0:00:08 time: 0.0591 data_time: 0.0060 memory: 1008 2022/11/02 23:47:41 - mmengine - INFO - Epoch(val) [960][355/500] eta: 0:00:08 time: 0.0647 data_time: 0.0101 memory: 1008 2022/11/02 23:47:41 - mmengine - INFO - Epoch(val) [960][360/500] eta: 0:00:07 time: 0.0549 data_time: 0.0088 memory: 1008 2022/11/02 23:47:42 - mmengine - INFO - Epoch(val) [960][365/500] eta: 0:00:07 time: 0.0500 data_time: 0.0049 memory: 1008 2022/11/02 23:47:42 - mmengine - INFO - Epoch(val) [960][370/500] eta: 0:00:05 time: 0.0452 data_time: 0.0058 memory: 1008 2022/11/02 23:47:42 - mmengine - INFO - Epoch(val) [960][375/500] eta: 0:00:05 time: 0.0359 data_time: 0.0035 memory: 1008 2022/11/02 23:47:42 - mmengine - INFO - Epoch(val) [960][380/500] eta: 0:00:04 time: 0.0381 data_time: 0.0022 memory: 1008 2022/11/02 23:47:42 - mmengine - INFO - Epoch(val) [960][385/500] eta: 0:00:04 time: 0.0398 data_time: 0.0023 memory: 1008 2022/11/02 23:47:43 - mmengine - INFO - Epoch(val) [960][390/500] eta: 0:00:04 time: 0.0366 data_time: 0.0022 memory: 1008 2022/11/02 23:47:43 - mmengine - INFO - Epoch(val) [960][395/500] eta: 0:00:04 time: 0.0355 data_time: 0.0022 memory: 1008 2022/11/02 23:47:43 - mmengine - INFO - Epoch(val) [960][400/500] eta: 0:00:03 time: 0.0373 data_time: 0.0024 memory: 1008 2022/11/02 23:47:43 - mmengine - INFO - Epoch(val) [960][405/500] eta: 0:00:03 time: 0.0392 data_time: 0.0025 memory: 1008 2022/11/02 23:47:43 - mmengine - INFO - Epoch(val) [960][410/500] eta: 0:00:04 time: 0.0456 data_time: 0.0031 memory: 1008 2022/11/02 23:47:44 - mmengine - INFO - Epoch(val) [960][415/500] eta: 0:00:04 time: 0.0472 data_time: 0.0037 memory: 1008 2022/11/02 23:47:44 - mmengine - INFO - Epoch(val) [960][420/500] eta: 0:00:03 time: 0.0421 data_time: 0.0032 memory: 1008 2022/11/02 23:47:44 - mmengine - INFO - Epoch(val) [960][425/500] eta: 0:00:03 time: 0.0444 data_time: 0.0039 memory: 1008 2022/11/02 23:47:44 - mmengine - INFO - Epoch(val) [960][430/500] eta: 0:00:03 time: 0.0492 data_time: 0.0049 memory: 1008 2022/11/02 23:47:45 - mmengine - INFO - Epoch(val) [960][435/500] eta: 0:00:03 time: 0.0509 data_time: 0.0056 memory: 1008 2022/11/02 23:47:45 - mmengine - INFO - Epoch(val) [960][440/500] eta: 0:00:02 time: 0.0475 data_time: 0.0045 memory: 1008 2022/11/02 23:47:45 - mmengine - INFO - Epoch(val) [960][445/500] eta: 0:00:02 time: 0.0520 data_time: 0.0059 memory: 1008 2022/11/02 23:47:45 - mmengine - INFO - Epoch(val) [960][450/500] eta: 0:00:02 time: 0.0560 data_time: 0.0074 memory: 1008 2022/11/02 23:47:46 - mmengine - INFO - Epoch(val) [960][455/500] eta: 0:00:02 time: 0.0495 data_time: 0.0043 memory: 1008 2022/11/02 23:47:46 - mmengine - INFO - Epoch(val) [960][460/500] eta: 0:00:01 time: 0.0452 data_time: 0.0033 memory: 1008 2022/11/02 23:47:46 - mmengine - INFO - Epoch(val) [960][465/500] eta: 0:00:01 time: 0.0479 data_time: 0.0039 memory: 1008 2022/11/02 23:47:46 - mmengine - INFO - Epoch(val) [960][470/500] eta: 0:00:01 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/02 23:47:46 - mmengine - INFO - Epoch(val) [960][475/500] eta: 0:00:01 time: 0.0353 data_time: 0.0021 memory: 1008 2022/11/02 23:47:47 - mmengine - INFO - Epoch(val) [960][480/500] eta: 0:00:00 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/02 23:47:47 - mmengine - INFO - Epoch(val) [960][485/500] eta: 0:00:00 time: 0.0386 data_time: 0.0024 memory: 1008 2022/11/02 23:47:47 - mmengine - INFO - Epoch(val) [960][490/500] eta: 0:00:00 time: 0.0403 data_time: 0.0024 memory: 1008 2022/11/02 23:47:47 - mmengine - INFO - Epoch(val) [960][495/500] eta: 0:00:00 time: 0.0418 data_time: 0.0024 memory: 1008 2022/11/02 23:47:47 - mmengine - INFO - Epoch(val) [960][500/500] eta: 0:00:00 time: 0.0369 data_time: 0.0022 memory: 1008 2022/11/02 23:47:47 - mmengine - INFO - Evaluating hmean-iou... 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8406, precision: 0.7370, hmean: 0.7854 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8406, precision: 0.7837, hmean: 0.8111 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8402, precision: 0.8162, hmean: 0.8280 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8368, precision: 0.8396, hmean: 0.8382 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8247, precision: 0.8718, hmean: 0.8476 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7371, precision: 0.9140, hmean: 0.8161 2022/11/02 23:47:47 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1993, precision: 0.9606, hmean: 0.3301 2022/11/02 23:47:47 - mmengine - INFO - Epoch(val) [960][500/500] icdar/precision: 0.8718 icdar/recall: 0.8247 icdar/hmean: 0.8476 2022/11/02 23:47:55 - mmengine - INFO - Epoch(train) [961][5/63] lr: 5.0670e-04 eta: 0:00:00 time: 0.9587 data_time: 0.1987 memory: 14901 loss: 0.9880 loss_prob: 0.5077 loss_thr: 0.3909 loss_db: 0.0893 2022/11/02 23:47:59 - mmengine - INFO - Epoch(train) [961][10/63] lr: 5.0670e-04 eta: 2:44:20 time: 1.1745 data_time: 0.2080 memory: 14901 loss: 0.9468 loss_prob: 0.4837 loss_thr: 0.3788 loss_db: 0.0844 2022/11/02 23:48:02 - mmengine - INFO - Epoch(train) [961][15/63] lr: 5.0670e-04 eta: 2:44:20 time: 0.7159 data_time: 0.0171 memory: 14901 loss: 0.9425 loss_prob: 0.4810 loss_thr: 0.3774 loss_db: 0.0840 2022/11/02 23:48:04 - mmengine - INFO - Epoch(train) [961][20/63] lr: 5.0670e-04 eta: 2:44:14 time: 0.4942 data_time: 0.0076 memory: 14901 loss: 0.9086 loss_prob: 0.4657 loss_thr: 0.3612 loss_db: 0.0817 2022/11/02 23:48:06 - mmengine - INFO - Epoch(train) [961][25/63] lr: 5.0670e-04 eta: 2:44:14 time: 0.4613 data_time: 0.0090 memory: 14901 loss: 0.8410 loss_prob: 0.4298 loss_thr: 0.3365 loss_db: 0.0748 2022/11/02 23:48:09 - mmengine - INFO - Epoch(train) [961][30/63] lr: 5.0670e-04 eta: 2:44:07 time: 0.4917 data_time: 0.0233 memory: 14901 loss: 0.9378 loss_prob: 0.4860 loss_thr: 0.3671 loss_db: 0.0847 2022/11/02 23:48:12 - mmengine - INFO - Epoch(train) [961][35/63] lr: 5.0670e-04 eta: 2:44:07 time: 0.5196 data_time: 0.0250 memory: 14901 loss: 0.9245 loss_prob: 0.4748 loss_thr: 0.3679 loss_db: 0.0818 2022/11/02 23:48:14 - mmengine - INFO - Epoch(train) [961][40/63] lr: 5.0670e-04 eta: 2:44:00 time: 0.5334 data_time: 0.0137 memory: 14901 loss: 0.9168 loss_prob: 0.4742 loss_thr: 0.3614 loss_db: 0.0812 2022/11/02 23:48:17 - mmengine - INFO - Epoch(train) [961][45/63] lr: 5.0670e-04 eta: 2:44:00 time: 0.5664 data_time: 0.0082 memory: 14901 loss: 1.0687 loss_prob: 0.5712 loss_thr: 0.3976 loss_db: 0.1000 2022/11/02 23:48:20 - mmengine - INFO - Epoch(train) [961][50/63] lr: 5.0670e-04 eta: 2:43:53 time: 0.5765 data_time: 0.0085 memory: 14901 loss: 1.0228 loss_prob: 0.5402 loss_thr: 0.3868 loss_db: 0.0958 2022/11/02 23:48:23 - mmengine - INFO - Epoch(train) [961][55/63] lr: 5.0670e-04 eta: 2:43:53 time: 0.5305 data_time: 0.0198 memory: 14901 loss: 0.9212 loss_prob: 0.4743 loss_thr: 0.3630 loss_db: 0.0839 2022/11/02 23:48:25 - mmengine - INFO - Epoch(train) [961][60/63] lr: 5.0670e-04 eta: 2:43:46 time: 0.4864 data_time: 0.0173 memory: 14901 loss: 0.8926 loss_prob: 0.4607 loss_thr: 0.3521 loss_db: 0.0799 2022/11/02 23:48:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:48:31 - mmengine - INFO - Epoch(train) [962][5/63] lr: 5.0480e-04 eta: 2:43:46 time: 0.6775 data_time: 0.2076 memory: 14901 loss: 0.9648 loss_prob: 0.4977 loss_thr: 0.3811 loss_db: 0.0860 2022/11/02 23:48:33 - mmengine - INFO - Epoch(train) [962][10/63] lr: 5.0480e-04 eta: 2:43:37 time: 0.6954 data_time: 0.2069 memory: 14901 loss: 0.9459 loss_prob: 0.4808 loss_thr: 0.3796 loss_db: 0.0854 2022/11/02 23:48:36 - mmengine - INFO - Epoch(train) [962][15/63] lr: 5.0480e-04 eta: 2:43:37 time: 0.4936 data_time: 0.0053 memory: 14901 loss: 0.9378 loss_prob: 0.4871 loss_thr: 0.3647 loss_db: 0.0859 2022/11/02 23:48:38 - mmengine - INFO - Epoch(train) [962][20/63] lr: 5.0480e-04 eta: 2:43:30 time: 0.4902 data_time: 0.0063 memory: 14901 loss: 0.9135 loss_prob: 0.4761 loss_thr: 0.3549 loss_db: 0.0825 2022/11/02 23:48:41 - mmengine - INFO - Epoch(train) [962][25/63] lr: 5.0480e-04 eta: 2:43:30 time: 0.5127 data_time: 0.0294 memory: 14901 loss: 0.9823 loss_prob: 0.5115 loss_thr: 0.3819 loss_db: 0.0890 2022/11/02 23:48:43 - mmengine - INFO - Epoch(train) [962][30/63] lr: 5.0480e-04 eta: 2:43:23 time: 0.5132 data_time: 0.0311 memory: 14901 loss: 0.9776 loss_prob: 0.5064 loss_thr: 0.3821 loss_db: 0.0891 2022/11/02 23:48:46 - mmengine - INFO - Epoch(train) [962][35/63] lr: 5.0480e-04 eta: 2:43:23 time: 0.4677 data_time: 0.0079 memory: 14901 loss: 0.8987 loss_prob: 0.4625 loss_thr: 0.3547 loss_db: 0.0815 2022/11/02 23:48:48 - mmengine - INFO - Epoch(train) [962][40/63] lr: 5.0480e-04 eta: 2:43:16 time: 0.4789 data_time: 0.0055 memory: 14901 loss: 0.9459 loss_prob: 0.4919 loss_thr: 0.3670 loss_db: 0.0870 2022/11/02 23:48:50 - mmengine - INFO - Epoch(train) [962][45/63] lr: 5.0480e-04 eta: 2:43:16 time: 0.4943 data_time: 0.0069 memory: 14901 loss: 0.9718 loss_prob: 0.5104 loss_thr: 0.3724 loss_db: 0.0890 2022/11/02 23:48:53 - mmengine - INFO - Epoch(train) [962][50/63] lr: 5.0480e-04 eta: 2:43:10 time: 0.5157 data_time: 0.0203 memory: 14901 loss: 0.8246 loss_prob: 0.4250 loss_thr: 0.3263 loss_db: 0.0732 2022/11/02 23:48:56 - mmengine - INFO - Epoch(train) [962][55/63] lr: 5.0480e-04 eta: 2:43:10 time: 0.5306 data_time: 0.0206 memory: 14901 loss: 0.6983 loss_prob: 0.3515 loss_thr: 0.2857 loss_db: 0.0611 2022/11/02 23:48:58 - mmengine - INFO - Epoch(train) [962][60/63] lr: 5.0480e-04 eta: 2:43:03 time: 0.5044 data_time: 0.0066 memory: 14901 loss: 0.9004 loss_prob: 0.4736 loss_thr: 0.3482 loss_db: 0.0786 2022/11/02 23:48:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:49:04 - mmengine - INFO - Epoch(train) [963][5/63] lr: 5.0289e-04 eta: 2:43:03 time: 0.6892 data_time: 0.2349 memory: 14901 loss: 0.8938 loss_prob: 0.4537 loss_thr: 0.3598 loss_db: 0.0803 2022/11/02 23:49:07 - mmengine - INFO - Epoch(train) [963][10/63] lr: 5.0289e-04 eta: 2:42:54 time: 0.7154 data_time: 0.2363 memory: 14901 loss: 0.9186 loss_prob: 0.4662 loss_thr: 0.3707 loss_db: 0.0817 2022/11/02 23:49:09 - mmengine - INFO - Epoch(train) [963][15/63] lr: 5.0289e-04 eta: 2:42:54 time: 0.4673 data_time: 0.0100 memory: 14901 loss: 0.9606 loss_prob: 0.4945 loss_thr: 0.3820 loss_db: 0.0842 2022/11/02 23:49:11 - mmengine - INFO - Epoch(train) [963][20/63] lr: 5.0289e-04 eta: 2:42:47 time: 0.4844 data_time: 0.0090 memory: 14901 loss: 0.9203 loss_prob: 0.4690 loss_thr: 0.3690 loss_db: 0.0823 2022/11/02 23:49:14 - mmengine - INFO - Epoch(train) [963][25/63] lr: 5.0289e-04 eta: 2:42:47 time: 0.4841 data_time: 0.0210 memory: 14901 loss: 0.9499 loss_prob: 0.4964 loss_thr: 0.3666 loss_db: 0.0869 2022/11/02 23:49:16 - mmengine - INFO - Epoch(train) [963][30/63] lr: 5.0289e-04 eta: 2:42:40 time: 0.4833 data_time: 0.0308 memory: 14901 loss: 0.9840 loss_prob: 0.5237 loss_thr: 0.3703 loss_db: 0.0900 2022/11/02 23:49:21 - mmengine - INFO - Epoch(train) [963][35/63] lr: 5.0289e-04 eta: 2:42:40 time: 0.6681 data_time: 0.0147 memory: 14901 loss: 0.8906 loss_prob: 0.4686 loss_thr: 0.3400 loss_db: 0.0819 2022/11/02 23:49:23 - mmengine - INFO - Epoch(train) [963][40/63] lr: 5.0289e-04 eta: 2:42:34 time: 0.6525 data_time: 0.0060 memory: 14901 loss: 0.8833 loss_prob: 0.4730 loss_thr: 0.3302 loss_db: 0.0802 2022/11/02 23:49:25 - mmengine - INFO - Epoch(train) [963][45/63] lr: 5.0289e-04 eta: 2:42:34 time: 0.4888 data_time: 0.0064 memory: 14901 loss: 0.9477 loss_prob: 0.5037 loss_thr: 0.3596 loss_db: 0.0843 2022/11/02 23:49:28 - mmengine - INFO - Epoch(train) [963][50/63] lr: 5.0289e-04 eta: 2:42:27 time: 0.5003 data_time: 0.0140 memory: 14901 loss: 0.9434 loss_prob: 0.4856 loss_thr: 0.3724 loss_db: 0.0854 2022/11/02 23:49:30 - mmengine - INFO - Epoch(train) [963][55/63] lr: 5.0289e-04 eta: 2:42:27 time: 0.4761 data_time: 0.0199 memory: 14901 loss: 0.9794 loss_prob: 0.5074 loss_thr: 0.3833 loss_db: 0.0886 2022/11/02 23:49:32 - mmengine - INFO - Epoch(train) [963][60/63] lr: 5.0289e-04 eta: 2:42:20 time: 0.4617 data_time: 0.0111 memory: 14901 loss: 0.9507 loss_prob: 0.4954 loss_thr: 0.3704 loss_db: 0.0850 2022/11/02 23:49:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:49:38 - mmengine - INFO - Epoch(train) [964][5/63] lr: 5.0098e-04 eta: 2:42:20 time: 0.6677 data_time: 0.2094 memory: 14901 loss: 0.9323 loss_prob: 0.4828 loss_thr: 0.3652 loss_db: 0.0843 2022/11/02 23:49:41 - mmengine - INFO - Epoch(train) [964][10/63] lr: 5.0098e-04 eta: 2:42:11 time: 0.7112 data_time: 0.2086 memory: 14901 loss: 1.0022 loss_prob: 0.5180 loss_thr: 0.3926 loss_db: 0.0917 2022/11/02 23:49:44 - mmengine - INFO - Epoch(train) [964][15/63] lr: 5.0098e-04 eta: 2:42:11 time: 0.5265 data_time: 0.0048 memory: 14901 loss: 0.9595 loss_prob: 0.4992 loss_thr: 0.3730 loss_db: 0.0873 2022/11/02 23:49:46 - mmengine - INFO - Epoch(train) [964][20/63] lr: 5.0098e-04 eta: 2:42:04 time: 0.5091 data_time: 0.0044 memory: 14901 loss: 0.9076 loss_prob: 0.4704 loss_thr: 0.3543 loss_db: 0.0828 2022/11/02 23:49:49 - mmengine - INFO - Epoch(train) [964][25/63] lr: 5.0098e-04 eta: 2:42:04 time: 0.5353 data_time: 0.0185 memory: 14901 loss: 0.9613 loss_prob: 0.5012 loss_thr: 0.3722 loss_db: 0.0879 2022/11/02 23:49:57 - mmengine - INFO - Epoch(train) [964][30/63] lr: 5.0098e-04 eta: 2:41:59 time: 1.1630 data_time: 0.0883 memory: 14901 loss: 1.0239 loss_prob: 0.5409 loss_thr: 0.3897 loss_db: 0.0933 2022/11/02 23:50:06 - mmengine - INFO - Epoch(train) [964][35/63] lr: 5.0098e-04 eta: 2:41:59 time: 1.7155 data_time: 0.0758 memory: 14901 loss: 0.9707 loss_prob: 0.5130 loss_thr: 0.3706 loss_db: 0.0871 2022/11/02 23:50:10 - mmengine - INFO - Epoch(train) [964][40/63] lr: 5.0098e-04 eta: 2:41:54 time: 1.2571 data_time: 0.0067 memory: 14901 loss: 0.9312 loss_prob: 0.4869 loss_thr: 0.3602 loss_db: 0.0840 2022/11/02 23:50:13 - mmengine - INFO - Epoch(train) [964][45/63] lr: 5.0098e-04 eta: 2:41:54 time: 0.6649 data_time: 0.0053 memory: 14901 loss: 0.9293 loss_prob: 0.4838 loss_thr: 0.3596 loss_db: 0.0859 2022/11/02 23:50:16 - mmengine - INFO - Epoch(train) [964][50/63] lr: 5.0098e-04 eta: 2:41:47 time: 0.6400 data_time: 0.0135 memory: 14901 loss: 1.0112 loss_prob: 0.5319 loss_thr: 0.3856 loss_db: 0.0936 2022/11/02 23:50:20 - mmengine - INFO - Epoch(train) [964][55/63] lr: 5.0098e-04 eta: 2:41:47 time: 0.7527 data_time: 0.0299 memory: 14901 loss: 0.9859 loss_prob: 0.5107 loss_thr: 0.3867 loss_db: 0.0885 2022/11/02 23:50:26 - mmengine - INFO - Epoch(train) [964][60/63] lr: 5.0098e-04 eta: 2:41:41 time: 0.9457 data_time: 0.0222 memory: 14901 loss: 0.9056 loss_prob: 0.4506 loss_thr: 0.3752 loss_db: 0.0798 2022/11/02 23:50:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:50:36 - mmengine - INFO - Epoch(train) [965][5/63] lr: 4.9907e-04 eta: 2:41:41 time: 1.2169 data_time: 0.2703 memory: 14901 loss: 0.9510 loss_prob: 0.4918 loss_thr: 0.3727 loss_db: 0.0866 2022/11/02 23:50:39 - mmengine - INFO - Epoch(train) [965][10/63] lr: 4.9907e-04 eta: 2:41:33 time: 1.0680 data_time: 0.2701 memory: 14901 loss: 0.9107 loss_prob: 0.4738 loss_thr: 0.3533 loss_db: 0.0836 2022/11/02 23:50:43 - mmengine - INFO - Epoch(train) [965][15/63] lr: 4.9907e-04 eta: 2:41:33 time: 0.7693 data_time: 0.0061 memory: 14901 loss: 0.9178 loss_prob: 0.4730 loss_thr: 0.3609 loss_db: 0.0839 2022/11/02 23:50:46 - mmengine - INFO - Epoch(train) [965][20/63] lr: 4.9907e-04 eta: 2:41:27 time: 0.6808 data_time: 0.0058 memory: 14901 loss: 0.8976 loss_prob: 0.4630 loss_thr: 0.3535 loss_db: 0.0810 2022/11/02 23:50:50 - mmengine - INFO - Epoch(train) [965][25/63] lr: 4.9907e-04 eta: 2:41:27 time: 0.6230 data_time: 0.0315 memory: 14901 loss: 0.8616 loss_prob: 0.4490 loss_thr: 0.3343 loss_db: 0.0783 2022/11/02 23:50:52 - mmengine - INFO - Epoch(train) [965][30/63] lr: 4.9907e-04 eta: 2:41:20 time: 0.5882 data_time: 0.0394 memory: 14901 loss: 0.8658 loss_prob: 0.4490 loss_thr: 0.3383 loss_db: 0.0784 2022/11/02 23:50:55 - mmengine - INFO - Epoch(train) [965][35/63] lr: 4.9907e-04 eta: 2:41:20 time: 0.5788 data_time: 0.0133 memory: 14901 loss: 0.9073 loss_prob: 0.4698 loss_thr: 0.3559 loss_db: 0.0815 2022/11/02 23:50:59 - mmengine - INFO - Epoch(train) [965][40/63] lr: 4.9907e-04 eta: 2:41:14 time: 0.7009 data_time: 0.0067 memory: 14901 loss: 1.0113 loss_prob: 0.5326 loss_thr: 0.3854 loss_db: 0.0933 2022/11/02 23:51:02 - mmengine - INFO - Epoch(train) [965][45/63] lr: 4.9907e-04 eta: 2:41:14 time: 0.7059 data_time: 0.0074 memory: 14901 loss: 0.9511 loss_prob: 0.4946 loss_thr: 0.3697 loss_db: 0.0868 2022/11/02 23:51:06 - mmengine - INFO - Epoch(train) [965][50/63] lr: 4.9907e-04 eta: 2:41:07 time: 0.6478 data_time: 0.0272 memory: 14901 loss: 0.9054 loss_prob: 0.4665 loss_thr: 0.3584 loss_db: 0.0806 2022/11/02 23:51:10 - mmengine - INFO - Epoch(train) [965][55/63] lr: 4.9907e-04 eta: 2:41:07 time: 0.7126 data_time: 0.0291 memory: 14901 loss: 0.8682 loss_prob: 0.4459 loss_thr: 0.3439 loss_db: 0.0784 2022/11/02 23:51:12 - mmengine - INFO - Epoch(train) [965][60/63] lr: 4.9907e-04 eta: 2:41:01 time: 0.6957 data_time: 0.0083 memory: 14901 loss: 0.7641 loss_prob: 0.3808 loss_thr: 0.3133 loss_db: 0.0700 2022/11/02 23:51:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:51:20 - mmengine - INFO - Epoch(train) [966][5/63] lr: 4.9716e-04 eta: 2:41:01 time: 0.9360 data_time: 0.2912 memory: 14901 loss: 0.8768 loss_prob: 0.4582 loss_thr: 0.3388 loss_db: 0.0798 2022/11/02 23:51:24 - mmengine - INFO - Epoch(train) [966][10/63] lr: 4.9716e-04 eta: 2:40:53 time: 0.9455 data_time: 0.2905 memory: 14901 loss: 0.9126 loss_prob: 0.4695 loss_thr: 0.3617 loss_db: 0.0814 2022/11/02 23:51:26 - mmengine - INFO - Epoch(train) [966][15/63] lr: 4.9716e-04 eta: 2:40:53 time: 0.5891 data_time: 0.0052 memory: 14901 loss: 0.9080 loss_prob: 0.4659 loss_thr: 0.3610 loss_db: 0.0811 2022/11/02 23:51:29 - mmengine - INFO - Epoch(train) [966][20/63] lr: 4.9716e-04 eta: 2:40:46 time: 0.5267 data_time: 0.0052 memory: 14901 loss: 0.9582 loss_prob: 0.4989 loss_thr: 0.3742 loss_db: 0.0850 2022/11/02 23:51:32 - mmengine - INFO - Epoch(train) [966][25/63] lr: 4.9716e-04 eta: 2:40:46 time: 0.5277 data_time: 0.0171 memory: 14901 loss: 0.9863 loss_prob: 0.5157 loss_thr: 0.3810 loss_db: 0.0896 2022/11/02 23:51:34 - mmengine - INFO - Epoch(train) [966][30/63] lr: 4.9716e-04 eta: 2:40:39 time: 0.5440 data_time: 0.0377 memory: 14901 loss: 0.9522 loss_prob: 0.4918 loss_thr: 0.3726 loss_db: 0.0878 2022/11/02 23:51:37 - mmengine - INFO - Epoch(train) [966][35/63] lr: 4.9716e-04 eta: 2:40:39 time: 0.5503 data_time: 0.0287 memory: 14901 loss: 0.9451 loss_prob: 0.4835 loss_thr: 0.3773 loss_db: 0.0843 2022/11/02 23:51:40 - mmengine - INFO - Epoch(train) [966][40/63] lr: 4.9716e-04 eta: 2:40:32 time: 0.5589 data_time: 0.0093 memory: 14901 loss: 0.9093 loss_prob: 0.4682 loss_thr: 0.3589 loss_db: 0.0822 2022/11/02 23:51:43 - mmengine - INFO - Epoch(train) [966][45/63] lr: 4.9716e-04 eta: 2:40:32 time: 0.5326 data_time: 0.0068 memory: 14901 loss: 0.9640 loss_prob: 0.5000 loss_thr: 0.3751 loss_db: 0.0889 2022/11/02 23:51:45 - mmengine - INFO - Epoch(train) [966][50/63] lr: 4.9716e-04 eta: 2:40:25 time: 0.5544 data_time: 0.0242 memory: 14901 loss: 1.0983 loss_prob: 0.5830 loss_thr: 0.4161 loss_db: 0.0992 2022/11/02 23:51:50 - mmengine - INFO - Epoch(train) [966][55/63] lr: 4.9716e-04 eta: 2:40:25 time: 0.7066 data_time: 0.0317 memory: 14901 loss: 1.0080 loss_prob: 0.5282 loss_thr: 0.3902 loss_db: 0.0896 2022/11/02 23:51:53 - mmengine - INFO - Epoch(train) [966][60/63] lr: 4.9716e-04 eta: 2:40:19 time: 0.7044 data_time: 0.0146 memory: 14901 loss: 0.9186 loss_prob: 0.4822 loss_thr: 0.3497 loss_db: 0.0867 2022/11/02 23:51:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:52:03 - mmengine - INFO - Epoch(train) [967][5/63] lr: 4.9524e-04 eta: 2:40:19 time: 1.1678 data_time: 0.2643 memory: 14901 loss: 1.0087 loss_prob: 0.5180 loss_thr: 0.4035 loss_db: 0.0872 2022/11/02 23:52:07 - mmengine - INFO - Epoch(train) [967][10/63] lr: 4.9524e-04 eta: 2:40:12 time: 1.2418 data_time: 0.2739 memory: 14901 loss: 0.9953 loss_prob: 0.5063 loss_thr: 0.4022 loss_db: 0.0868 2022/11/02 23:52:10 - mmengine - INFO - Epoch(train) [967][15/63] lr: 4.9524e-04 eta: 2:40:12 time: 0.7592 data_time: 0.0233 memory: 14901 loss: 0.9320 loss_prob: 0.4764 loss_thr: 0.3682 loss_db: 0.0875 2022/11/02 23:52:14 - mmengine - INFO - Epoch(train) [967][20/63] lr: 4.9524e-04 eta: 2:40:05 time: 0.6953 data_time: 0.0134 memory: 14901 loss: 0.9793 loss_prob: 0.5050 loss_thr: 0.3829 loss_db: 0.0914 2022/11/02 23:52:17 - mmengine - INFO - Epoch(train) [967][25/63] lr: 4.9524e-04 eta: 2:40:05 time: 0.6310 data_time: 0.0175 memory: 14901 loss: 1.0473 loss_prob: 0.5576 loss_thr: 0.3965 loss_db: 0.0932 2022/11/02 23:52:19 - mmengine - INFO - Epoch(train) [967][30/63] lr: 4.9524e-04 eta: 2:39:58 time: 0.5583 data_time: 0.0277 memory: 14901 loss: 1.0978 loss_prob: 0.5892 loss_thr: 0.4122 loss_db: 0.0963 2022/11/02 23:52:22 - mmengine - INFO - Epoch(train) [967][35/63] lr: 4.9524e-04 eta: 2:39:58 time: 0.5603 data_time: 0.0223 memory: 14901 loss: 1.0268 loss_prob: 0.5368 loss_thr: 0.3966 loss_db: 0.0934 2022/11/02 23:52:25 - mmengine - INFO - Epoch(train) [967][40/63] lr: 4.9524e-04 eta: 2:39:52 time: 0.5918 data_time: 0.0177 memory: 14901 loss: 0.9872 loss_prob: 0.5233 loss_thr: 0.3721 loss_db: 0.0918 2022/11/02 23:52:28 - mmengine - INFO - Epoch(train) [967][45/63] lr: 4.9524e-04 eta: 2:39:52 time: 0.5985 data_time: 0.0112 memory: 14901 loss: 0.9667 loss_prob: 0.5134 loss_thr: 0.3654 loss_db: 0.0878 2022/11/02 23:52:31 - mmengine - INFO - Epoch(train) [967][50/63] lr: 4.9524e-04 eta: 2:39:45 time: 0.5848 data_time: 0.0149 memory: 14901 loss: 0.9485 loss_prob: 0.4991 loss_thr: 0.3650 loss_db: 0.0845 2022/11/02 23:52:34 - mmengine - INFO - Epoch(train) [967][55/63] lr: 4.9524e-04 eta: 2:39:45 time: 0.5976 data_time: 0.0304 memory: 14901 loss: 0.9774 loss_prob: 0.5188 loss_thr: 0.3710 loss_db: 0.0876 2022/11/02 23:52:38 - mmengine - INFO - Epoch(train) [967][60/63] lr: 4.9524e-04 eta: 2:39:38 time: 0.6447 data_time: 0.0219 memory: 14901 loss: 0.9561 loss_prob: 0.4977 loss_thr: 0.3732 loss_db: 0.0852 2022/11/02 23:52:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:52:48 - mmengine - INFO - Epoch(train) [968][5/63] lr: 4.9333e-04 eta: 2:39:38 time: 1.1658 data_time: 0.3043 memory: 14901 loss: 0.9106 loss_prob: 0.4577 loss_thr: 0.3735 loss_db: 0.0794 2022/11/02 23:52:52 - mmengine - INFO - Epoch(train) [968][10/63] lr: 4.9333e-04 eta: 2:39:31 time: 1.2026 data_time: 0.3024 memory: 14901 loss: 0.8274 loss_prob: 0.4140 loss_thr: 0.3401 loss_db: 0.0733 2022/11/02 23:52:56 - mmengine - INFO - Epoch(train) [968][15/63] lr: 4.9333e-04 eta: 2:39:31 time: 0.7623 data_time: 0.0082 memory: 14901 loss: 0.8825 loss_prob: 0.4535 loss_thr: 0.3487 loss_db: 0.0803 2022/11/02 23:52:59 - mmengine - INFO - Epoch(train) [968][20/63] lr: 4.9333e-04 eta: 2:39:24 time: 0.7001 data_time: 0.0082 memory: 14901 loss: 0.9953 loss_prob: 0.5250 loss_thr: 0.3798 loss_db: 0.0905 2022/11/02 23:53:01 - mmengine - INFO - Epoch(train) [968][25/63] lr: 4.9333e-04 eta: 2:39:24 time: 0.5697 data_time: 0.0393 memory: 14901 loss: 1.0074 loss_prob: 0.5270 loss_thr: 0.3894 loss_db: 0.0911 2022/11/02 23:53:05 - mmengine - INFO - Epoch(train) [968][30/63] lr: 4.9333e-04 eta: 2:39:18 time: 0.6426 data_time: 0.0417 memory: 14901 loss: 0.9571 loss_prob: 0.4975 loss_thr: 0.3718 loss_db: 0.0878 2022/11/02 23:53:09 - mmengine - INFO - Epoch(train) [968][35/63] lr: 4.9333e-04 eta: 2:39:18 time: 0.7240 data_time: 0.0121 memory: 14901 loss: 0.9389 loss_prob: 0.4863 loss_thr: 0.3686 loss_db: 0.0840 2022/11/02 23:53:11 - mmengine - INFO - Epoch(train) [968][40/63] lr: 4.9333e-04 eta: 2:39:11 time: 0.6432 data_time: 0.0108 memory: 14901 loss: 0.9360 loss_prob: 0.4814 loss_thr: 0.3711 loss_db: 0.0834 2022/11/02 23:53:14 - mmengine - INFO - Epoch(train) [968][45/63] lr: 4.9333e-04 eta: 2:39:11 time: 0.5898 data_time: 0.0071 memory: 14901 loss: 0.8857 loss_prob: 0.4586 loss_thr: 0.3471 loss_db: 0.0801 2022/11/02 23:53:18 - mmengine - INFO - Epoch(train) [968][50/63] lr: 4.9333e-04 eta: 2:39:05 time: 0.6712 data_time: 0.0268 memory: 14901 loss: 0.8703 loss_prob: 0.4540 loss_thr: 0.3364 loss_db: 0.0800 2022/11/02 23:53:22 - mmengine - INFO - Epoch(train) [968][55/63] lr: 4.9333e-04 eta: 2:39:05 time: 0.7495 data_time: 0.0270 memory: 14901 loss: 0.8746 loss_prob: 0.4527 loss_thr: 0.3426 loss_db: 0.0794 2022/11/02 23:53:27 - mmengine - INFO - Epoch(train) [968][60/63] lr: 4.9333e-04 eta: 2:38:59 time: 0.8387 data_time: 0.0102 memory: 14901 loss: 0.9287 loss_prob: 0.4807 loss_thr: 0.3655 loss_db: 0.0824 2022/11/02 23:53:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:53:37 - mmengine - INFO - Epoch(train) [969][5/63] lr: 4.9142e-04 eta: 2:38:59 time: 1.2567 data_time: 0.2858 memory: 14901 loss: 0.9218 loss_prob: 0.4789 loss_thr: 0.3586 loss_db: 0.0844 2022/11/02 23:53:40 - mmengine - INFO - Epoch(train) [969][10/63] lr: 4.9142e-04 eta: 2:38:51 time: 1.1562 data_time: 0.2848 memory: 14901 loss: 0.8652 loss_prob: 0.4431 loss_thr: 0.3434 loss_db: 0.0788 2022/11/02 23:53:44 - mmengine - INFO - Epoch(train) [969][15/63] lr: 4.9142e-04 eta: 2:38:51 time: 0.7515 data_time: 0.0076 memory: 14901 loss: 0.9138 loss_prob: 0.4730 loss_thr: 0.3582 loss_db: 0.0825 2022/11/02 23:53:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:53:47 - mmengine - INFO - Epoch(train) [969][20/63] lr: 4.9142e-04 eta: 2:38:45 time: 0.6893 data_time: 0.0088 memory: 14901 loss: 0.9932 loss_prob: 0.5256 loss_thr: 0.3796 loss_db: 0.0880 2022/11/02 23:53:50 - mmengine - INFO - Epoch(train) [969][25/63] lr: 4.9142e-04 eta: 2:38:45 time: 0.5812 data_time: 0.0137 memory: 14901 loss: 0.9913 loss_prob: 0.5296 loss_thr: 0.3728 loss_db: 0.0888 2022/11/02 23:53:53 - mmengine - INFO - Epoch(train) [969][30/63] lr: 4.9142e-04 eta: 2:38:38 time: 0.5986 data_time: 0.0518 memory: 14901 loss: 0.9529 loss_prob: 0.4995 loss_thr: 0.3668 loss_db: 0.0866 2022/11/02 23:53:56 - mmengine - INFO - Epoch(train) [969][35/63] lr: 4.9142e-04 eta: 2:38:38 time: 0.6169 data_time: 0.0449 memory: 14901 loss: 0.9823 loss_prob: 0.5150 loss_thr: 0.3764 loss_db: 0.0910 2022/11/02 23:53:59 - mmengine - INFO - Epoch(train) [969][40/63] lr: 4.9142e-04 eta: 2:38:31 time: 0.6243 data_time: 0.0070 memory: 14901 loss: 0.9835 loss_prob: 0.5147 loss_thr: 0.3781 loss_db: 0.0908 2022/11/02 23:54:02 - mmengine - INFO - Epoch(train) [969][45/63] lr: 4.9142e-04 eta: 2:38:31 time: 0.6281 data_time: 0.0073 memory: 14901 loss: 0.9433 loss_prob: 0.4872 loss_thr: 0.3707 loss_db: 0.0854 2022/11/02 23:54:06 - mmengine - INFO - Epoch(train) [969][50/63] lr: 4.9142e-04 eta: 2:38:25 time: 0.6347 data_time: 0.0178 memory: 14901 loss: 0.9566 loss_prob: 0.4966 loss_thr: 0.3728 loss_db: 0.0872 2022/11/02 23:54:08 - mmengine - INFO - Epoch(train) [969][55/63] lr: 4.9142e-04 eta: 2:38:25 time: 0.5876 data_time: 0.0262 memory: 14901 loss: 0.9413 loss_prob: 0.4872 loss_thr: 0.3686 loss_db: 0.0855 2022/11/02 23:54:11 - mmengine - INFO - Epoch(train) [969][60/63] lr: 4.9142e-04 eta: 2:38:18 time: 0.5679 data_time: 0.0141 memory: 14901 loss: 0.8614 loss_prob: 0.4441 loss_thr: 0.3415 loss_db: 0.0759 2022/11/02 23:54:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:54:21 - mmengine - INFO - Epoch(train) [970][5/63] lr: 4.8950e-04 eta: 2:38:18 time: 1.0978 data_time: 0.2350 memory: 14901 loss: 0.9244 loss_prob: 0.4830 loss_thr: 0.3576 loss_db: 0.0838 2022/11/02 23:54:26 - mmengine - INFO - Epoch(train) [970][10/63] lr: 4.8950e-04 eta: 2:38:10 time: 1.1781 data_time: 0.2436 memory: 14901 loss: 0.9596 loss_prob: 0.5066 loss_thr: 0.3683 loss_db: 0.0848 2022/11/02 23:54:30 - mmengine - INFO - Epoch(train) [970][15/63] lr: 4.8950e-04 eta: 2:38:10 time: 0.9293 data_time: 0.0176 memory: 14901 loss: 0.9934 loss_prob: 0.5212 loss_thr: 0.3835 loss_db: 0.0887 2022/11/02 23:54:34 - mmengine - INFO - Epoch(train) [970][20/63] lr: 4.8950e-04 eta: 2:38:04 time: 0.8286 data_time: 0.0061 memory: 14901 loss: 0.9474 loss_prob: 0.4911 loss_thr: 0.3703 loss_db: 0.0859 2022/11/02 23:54:37 - mmengine - INFO - Epoch(train) [970][25/63] lr: 4.8950e-04 eta: 2:38:04 time: 0.6737 data_time: 0.0176 memory: 14901 loss: 0.9267 loss_prob: 0.4892 loss_thr: 0.3544 loss_db: 0.0831 2022/11/02 23:54:40 - mmengine - INFO - Epoch(train) [970][30/63] lr: 4.8950e-04 eta: 2:37:58 time: 0.5848 data_time: 0.0395 memory: 14901 loss: 0.9471 loss_prob: 0.5046 loss_thr: 0.3560 loss_db: 0.0865 2022/11/02 23:54:42 - mmengine - INFO - Epoch(train) [970][35/63] lr: 4.8950e-04 eta: 2:37:58 time: 0.5450 data_time: 0.0277 memory: 14901 loss: 0.9098 loss_prob: 0.4647 loss_thr: 0.3639 loss_db: 0.0812 2022/11/02 23:54:45 - mmengine - INFO - Epoch(train) [970][40/63] lr: 4.8950e-04 eta: 2:37:51 time: 0.5193 data_time: 0.0054 memory: 14901 loss: 0.8879 loss_prob: 0.4452 loss_thr: 0.3663 loss_db: 0.0765 2022/11/02 23:54:48 - mmengine - INFO - Epoch(train) [970][45/63] lr: 4.8950e-04 eta: 2:37:51 time: 0.5499 data_time: 0.0056 memory: 14901 loss: 0.8620 loss_prob: 0.4363 loss_thr: 0.3494 loss_db: 0.0763 2022/11/02 23:54:51 - mmengine - INFO - Epoch(train) [970][50/63] lr: 4.8950e-04 eta: 2:37:44 time: 0.6153 data_time: 0.0156 memory: 14901 loss: 0.8561 loss_prob: 0.4326 loss_thr: 0.3466 loss_db: 0.0770 2022/11/02 23:54:55 - mmengine - INFO - Epoch(train) [970][55/63] lr: 4.8950e-04 eta: 2:37:44 time: 0.7119 data_time: 0.0278 memory: 14901 loss: 0.9074 loss_prob: 0.4623 loss_thr: 0.3637 loss_db: 0.0814 2022/11/02 23:54:58 - mmengine - INFO - Epoch(train) [970][60/63] lr: 4.8950e-04 eta: 2:37:38 time: 0.6770 data_time: 0.0178 memory: 14901 loss: 0.9201 loss_prob: 0.4675 loss_thr: 0.3706 loss_db: 0.0821 2022/11/02 23:55:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:55:08 - mmengine - INFO - Epoch(train) [971][5/63] lr: 4.8759e-04 eta: 2:37:38 time: 1.0907 data_time: 0.2958 memory: 14901 loss: 0.9401 loss_prob: 0.4871 loss_thr: 0.3684 loss_db: 0.0846 2022/11/02 23:55:11 - mmengine - INFO - Epoch(train) [971][10/63] lr: 4.8759e-04 eta: 2:37:30 time: 1.1691 data_time: 0.2964 memory: 14901 loss: 0.8551 loss_prob: 0.4326 loss_thr: 0.3449 loss_db: 0.0776 2022/11/02 23:55:14 - mmengine - INFO - Epoch(train) [971][15/63] lr: 4.8759e-04 eta: 2:37:30 time: 0.6583 data_time: 0.0125 memory: 14901 loss: 0.9069 loss_prob: 0.4589 loss_thr: 0.3666 loss_db: 0.0814 2022/11/02 23:55:17 - mmengine - INFO - Epoch(train) [971][20/63] lr: 4.8759e-04 eta: 2:37:23 time: 0.6125 data_time: 0.0115 memory: 14901 loss: 0.9114 loss_prob: 0.4662 loss_thr: 0.3645 loss_db: 0.0808 2022/11/02 23:55:21 - mmengine - INFO - Epoch(train) [971][25/63] lr: 4.8759e-04 eta: 2:37:23 time: 0.6528 data_time: 0.0134 memory: 14901 loss: 0.8980 loss_prob: 0.4612 loss_thr: 0.3565 loss_db: 0.0803 2022/11/02 23:55:25 - mmengine - INFO - Epoch(train) [971][30/63] lr: 4.8759e-04 eta: 2:37:17 time: 0.7536 data_time: 0.0322 memory: 14901 loss: 0.9150 loss_prob: 0.4677 loss_thr: 0.3655 loss_db: 0.0819 2022/11/02 23:55:28 - mmengine - INFO - Epoch(train) [971][35/63] lr: 4.8759e-04 eta: 2:37:17 time: 0.6968 data_time: 0.0295 memory: 14901 loss: 0.8719 loss_prob: 0.4408 loss_thr: 0.3541 loss_db: 0.0770 2022/11/02 23:55:31 - mmengine - INFO - Epoch(train) [971][40/63] lr: 4.8759e-04 eta: 2:37:10 time: 0.6228 data_time: 0.0121 memory: 14901 loss: 0.9318 loss_prob: 0.4841 loss_thr: 0.3640 loss_db: 0.0837 2022/11/02 23:55:34 - mmengine - INFO - Epoch(train) [971][45/63] lr: 4.8759e-04 eta: 2:37:10 time: 0.6588 data_time: 0.0069 memory: 14901 loss: 0.9467 loss_prob: 0.4918 loss_thr: 0.3686 loss_db: 0.0863 2022/11/02 23:55:37 - mmengine - INFO - Epoch(train) [971][50/63] lr: 4.8759e-04 eta: 2:37:04 time: 0.5952 data_time: 0.0168 memory: 14901 loss: 0.9801 loss_prob: 0.5019 loss_thr: 0.3904 loss_db: 0.0879 2022/11/02 23:55:40 - mmengine - INFO - Epoch(train) [971][55/63] lr: 4.8759e-04 eta: 2:37:04 time: 0.5659 data_time: 0.0307 memory: 14901 loss: 1.0043 loss_prob: 0.5163 loss_thr: 0.3991 loss_db: 0.0889 2022/11/02 23:55:43 - mmengine - INFO - Epoch(train) [971][60/63] lr: 4.8759e-04 eta: 2:36:57 time: 0.6343 data_time: 0.0221 memory: 14901 loss: 0.9345 loss_prob: 0.4882 loss_thr: 0.3622 loss_db: 0.0840 2022/11/02 23:55:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:55:55 - mmengine - INFO - Epoch(train) [972][5/63] lr: 4.8567e-04 eta: 2:36:57 time: 1.2725 data_time: 0.2976 memory: 14901 loss: 0.9721 loss_prob: 0.5175 loss_thr: 0.3653 loss_db: 0.0893 2022/11/02 23:55:58 - mmengine - INFO - Epoch(train) [972][10/63] lr: 4.8567e-04 eta: 2:36:50 time: 1.2429 data_time: 0.2921 memory: 14901 loss: 0.9346 loss_prob: 0.4892 loss_thr: 0.3592 loss_db: 0.0863 2022/11/02 23:56:01 - mmengine - INFO - Epoch(train) [972][15/63] lr: 4.8567e-04 eta: 2:36:50 time: 0.6542 data_time: 0.0374 memory: 14901 loss: 0.9688 loss_prob: 0.5050 loss_thr: 0.3751 loss_db: 0.0887 2022/11/02 23:56:05 - mmengine - INFO - Epoch(train) [972][20/63] lr: 4.8567e-04 eta: 2:36:43 time: 0.7216 data_time: 0.0372 memory: 14901 loss: 0.9269 loss_prob: 0.4841 loss_thr: 0.3587 loss_db: 0.0842 2022/11/02 23:56:08 - mmengine - INFO - Epoch(train) [972][25/63] lr: 4.8567e-04 eta: 2:36:43 time: 0.6584 data_time: 0.0050 memory: 14901 loss: 0.8558 loss_prob: 0.4364 loss_thr: 0.3434 loss_db: 0.0760 2022/11/02 23:56:11 - mmengine - INFO - Epoch(train) [972][30/63] lr: 4.8567e-04 eta: 2:36:37 time: 0.6219 data_time: 0.0115 memory: 14901 loss: 0.9413 loss_prob: 0.4824 loss_thr: 0.3750 loss_db: 0.0839 2022/11/02 23:56:14 - mmengine - INFO - Epoch(train) [972][35/63] lr: 4.8567e-04 eta: 2:36:37 time: 0.5995 data_time: 0.0121 memory: 14901 loss: 0.9463 loss_prob: 0.4918 loss_thr: 0.3680 loss_db: 0.0866 2022/11/02 23:56:18 - mmengine - INFO - Epoch(train) [972][40/63] lr: 4.8567e-04 eta: 2:36:30 time: 0.6240 data_time: 0.0230 memory: 14901 loss: 0.9526 loss_prob: 0.4946 loss_thr: 0.3726 loss_db: 0.0854 2022/11/02 23:56:20 - mmengine - INFO - Epoch(train) [972][45/63] lr: 4.8567e-04 eta: 2:36:30 time: 0.6029 data_time: 0.0225 memory: 14901 loss: 0.9434 loss_prob: 0.4949 loss_thr: 0.3642 loss_db: 0.0843 2022/11/02 23:56:23 - mmengine - INFO - Epoch(train) [972][50/63] lr: 4.8567e-04 eta: 2:36:23 time: 0.5224 data_time: 0.0068 memory: 14901 loss: 0.8656 loss_prob: 0.4461 loss_thr: 0.3419 loss_db: 0.0777 2022/11/02 23:56:26 - mmengine - INFO - Epoch(train) [972][55/63] lr: 4.8567e-04 eta: 2:36:23 time: 0.5748 data_time: 0.0110 memory: 14901 loss: 0.9000 loss_prob: 0.4652 loss_thr: 0.3520 loss_db: 0.0828 2022/11/02 23:56:29 - mmengine - INFO - Epoch(train) [972][60/63] lr: 4.8567e-04 eta: 2:36:17 time: 0.6282 data_time: 0.0093 memory: 14901 loss: 0.9423 loss_prob: 0.4910 loss_thr: 0.3643 loss_db: 0.0870 2022/11/02 23:56:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:56:40 - mmengine - INFO - Epoch(train) [973][5/63] lr: 4.8375e-04 eta: 2:36:17 time: 1.2262 data_time: 0.2671 memory: 14901 loss: 0.9076 loss_prob: 0.4639 loss_thr: 0.3624 loss_db: 0.0813 2022/11/02 23:56:43 - mmengine - INFO - Epoch(train) [973][10/63] lr: 4.8375e-04 eta: 2:36:09 time: 1.2081 data_time: 0.2683 memory: 14901 loss: 0.9809 loss_prob: 0.5122 loss_thr: 0.3775 loss_db: 0.0912 2022/11/02 23:56:46 - mmengine - INFO - Epoch(train) [973][15/63] lr: 4.8375e-04 eta: 2:36:09 time: 0.6176 data_time: 0.0109 memory: 14901 loss: 0.9978 loss_prob: 0.5196 loss_thr: 0.3878 loss_db: 0.0905 2022/11/02 23:56:50 - mmengine - INFO - Epoch(train) [973][20/63] lr: 4.8375e-04 eta: 2:36:02 time: 0.6394 data_time: 0.0102 memory: 14901 loss: 0.8922 loss_prob: 0.4567 loss_thr: 0.3560 loss_db: 0.0796 2022/11/02 23:56:53 - mmengine - INFO - Epoch(train) [973][25/63] lr: 4.8375e-04 eta: 2:36:02 time: 0.7128 data_time: 0.0247 memory: 14901 loss: 0.9657 loss_prob: 0.5026 loss_thr: 0.3761 loss_db: 0.0869 2022/11/02 23:56:56 - mmengine - INFO - Epoch(train) [973][30/63] lr: 4.8375e-04 eta: 2:35:56 time: 0.6702 data_time: 0.0329 memory: 14901 loss: 0.9806 loss_prob: 0.5148 loss_thr: 0.3745 loss_db: 0.0913 2022/11/02 23:56:59 - mmengine - INFO - Epoch(train) [973][35/63] lr: 4.8375e-04 eta: 2:35:56 time: 0.6284 data_time: 0.0204 memory: 14901 loss: 0.9599 loss_prob: 0.5013 loss_thr: 0.3692 loss_db: 0.0894 2022/11/02 23:57:03 - mmengine - INFO - Epoch(train) [973][40/63] lr: 4.8375e-04 eta: 2:35:49 time: 0.6520 data_time: 0.0089 memory: 14901 loss: 0.9600 loss_prob: 0.4976 loss_thr: 0.3765 loss_db: 0.0859 2022/11/02 23:57:05 - mmengine - INFO - Epoch(train) [973][45/63] lr: 4.8375e-04 eta: 2:35:49 time: 0.6144 data_time: 0.0100 memory: 14901 loss: 0.8645 loss_prob: 0.4387 loss_thr: 0.3489 loss_db: 0.0770 2022/11/02 23:57:08 - mmengine - INFO - Epoch(train) [973][50/63] lr: 4.8375e-04 eta: 2:35:43 time: 0.5453 data_time: 0.0268 memory: 14901 loss: 0.8404 loss_prob: 0.4277 loss_thr: 0.3371 loss_db: 0.0756 2022/11/02 23:57:11 - mmengine - INFO - Epoch(train) [973][55/63] lr: 4.8375e-04 eta: 2:35:43 time: 0.5835 data_time: 0.0236 memory: 14901 loss: 0.8922 loss_prob: 0.4603 loss_thr: 0.3519 loss_db: 0.0800 2022/11/02 23:57:14 - mmengine - INFO - Epoch(train) [973][60/63] lr: 4.8375e-04 eta: 2:35:36 time: 0.5612 data_time: 0.0114 memory: 14901 loss: 0.8730 loss_prob: 0.4439 loss_thr: 0.3518 loss_db: 0.0772 2022/11/02 23:57:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:57:22 - mmengine - INFO - Epoch(train) [974][5/63] lr: 4.8183e-04 eta: 2:35:36 time: 0.9652 data_time: 0.2696 memory: 14901 loss: 0.8785 loss_prob: 0.4485 loss_thr: 0.3501 loss_db: 0.0799 2022/11/02 23:57:25 - mmengine - INFO - Epoch(train) [974][10/63] lr: 4.8183e-04 eta: 2:35:28 time: 1.0035 data_time: 0.2743 memory: 14901 loss: 0.9174 loss_prob: 0.4754 loss_thr: 0.3582 loss_db: 0.0839 2022/11/02 23:57:29 - mmengine - INFO - Epoch(train) [974][15/63] lr: 4.8183e-04 eta: 2:35:28 time: 0.6144 data_time: 0.0117 memory: 14901 loss: 0.9232 loss_prob: 0.4761 loss_thr: 0.3647 loss_db: 0.0824 2022/11/02 23:57:32 - mmengine - INFO - Epoch(train) [974][20/63] lr: 4.8183e-04 eta: 2:35:21 time: 0.6431 data_time: 0.0080 memory: 14901 loss: 0.9191 loss_prob: 0.4728 loss_thr: 0.3632 loss_db: 0.0831 2022/11/02 23:57:34 - mmengine - INFO - Epoch(train) [974][25/63] lr: 4.8183e-04 eta: 2:35:21 time: 0.5910 data_time: 0.0259 memory: 14901 loss: 0.9266 loss_prob: 0.4737 loss_thr: 0.3687 loss_db: 0.0842 2022/11/02 23:57:37 - mmengine - INFO - Epoch(train) [974][30/63] lr: 4.8183e-04 eta: 2:35:14 time: 0.5430 data_time: 0.0353 memory: 14901 loss: 0.8598 loss_prob: 0.4393 loss_thr: 0.3431 loss_db: 0.0773 2022/11/02 23:57:40 - mmengine - INFO - Epoch(train) [974][35/63] lr: 4.8183e-04 eta: 2:35:14 time: 0.5503 data_time: 0.0184 memory: 14901 loss: 0.8995 loss_prob: 0.4651 loss_thr: 0.3542 loss_db: 0.0802 2022/11/02 23:57:42 - mmengine - INFO - Epoch(train) [974][40/63] lr: 4.8183e-04 eta: 2:35:08 time: 0.5232 data_time: 0.0117 memory: 14901 loss: 0.9753 loss_prob: 0.5039 loss_thr: 0.3836 loss_db: 0.0878 2022/11/02 23:57:45 - mmengine - INFO - Epoch(train) [974][45/63] lr: 4.8183e-04 eta: 2:35:08 time: 0.4998 data_time: 0.0093 memory: 14901 loss: 0.8924 loss_prob: 0.4543 loss_thr: 0.3571 loss_db: 0.0811 2022/11/02 23:57:48 - mmengine - INFO - Epoch(train) [974][50/63] lr: 4.8183e-04 eta: 2:35:01 time: 0.5326 data_time: 0.0192 memory: 14901 loss: 0.8953 loss_prob: 0.4539 loss_thr: 0.3610 loss_db: 0.0804 2022/11/02 23:57:50 - mmengine - INFO - Epoch(train) [974][55/63] lr: 4.8183e-04 eta: 2:35:01 time: 0.5395 data_time: 0.0231 memory: 14901 loss: 0.9140 loss_prob: 0.4603 loss_thr: 0.3724 loss_db: 0.0813 2022/11/02 23:57:53 - mmengine - INFO - Epoch(train) [974][60/63] lr: 4.8183e-04 eta: 2:34:54 time: 0.5327 data_time: 0.0126 memory: 14901 loss: 1.1051 loss_prob: 0.6244 loss_thr: 0.3874 loss_db: 0.0933 2022/11/02 23:57:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:58:03 - mmengine - INFO - Epoch(train) [975][5/63] lr: 4.7992e-04 eta: 2:34:54 time: 1.1523 data_time: 0.2212 memory: 14901 loss: 1.2143 loss_prob: 0.6966 loss_thr: 0.4181 loss_db: 0.0996 2022/11/02 23:58:08 - mmengine - INFO - Epoch(train) [975][10/63] lr: 4.7992e-04 eta: 2:34:47 time: 1.3144 data_time: 0.2305 memory: 14901 loss: 0.9205 loss_prob: 0.4729 loss_thr: 0.3624 loss_db: 0.0852 2022/11/02 23:58:10 - mmengine - INFO - Epoch(train) [975][15/63] lr: 4.7992e-04 eta: 2:34:47 time: 0.7004 data_time: 0.0167 memory: 14901 loss: 0.9474 loss_prob: 0.4882 loss_thr: 0.3723 loss_db: 0.0869 2022/11/02 23:58:13 - mmengine - INFO - Epoch(train) [975][20/63] lr: 4.7992e-04 eta: 2:34:40 time: 0.5649 data_time: 0.0073 memory: 14901 loss: 0.8882 loss_prob: 0.4504 loss_thr: 0.3590 loss_db: 0.0788 2022/11/02 23:58:17 - mmengine - INFO - Epoch(train) [975][25/63] lr: 4.7992e-04 eta: 2:34:40 time: 0.6457 data_time: 0.0333 memory: 14901 loss: 0.8861 loss_prob: 0.4457 loss_thr: 0.3611 loss_db: 0.0792 2022/11/02 23:58:20 - mmengine - INFO - Epoch(train) [975][30/63] lr: 4.7992e-04 eta: 2:34:33 time: 0.6895 data_time: 0.0432 memory: 14901 loss: 0.8752 loss_prob: 0.4467 loss_thr: 0.3499 loss_db: 0.0786 2022/11/02 23:58:23 - mmengine - INFO - Epoch(train) [975][35/63] lr: 4.7992e-04 eta: 2:34:33 time: 0.5801 data_time: 0.0286 memory: 14901 loss: 0.8531 loss_prob: 0.4410 loss_thr: 0.3357 loss_db: 0.0765 2022/11/02 23:58:26 - mmengine - INFO - Epoch(train) [975][40/63] lr: 4.7992e-04 eta: 2:34:27 time: 0.5638 data_time: 0.0178 memory: 14901 loss: 0.8956 loss_prob: 0.4638 loss_thr: 0.3505 loss_db: 0.0813 2022/11/02 23:58:31 - mmengine - INFO - Epoch(train) [975][45/63] lr: 4.7992e-04 eta: 2:34:27 time: 0.7979 data_time: 0.0068 memory: 14901 loss: 0.8780 loss_prob: 0.4567 loss_thr: 0.3393 loss_db: 0.0819 2022/11/02 23:58:35 - mmengine - INFO - Epoch(train) [975][50/63] lr: 4.7992e-04 eta: 2:34:21 time: 0.9213 data_time: 0.0159 memory: 14901 loss: 0.8915 loss_prob: 0.4648 loss_thr: 0.3439 loss_db: 0.0828 2022/11/02 23:58:38 - mmengine - INFO - Epoch(train) [975][55/63] lr: 4.7992e-04 eta: 2:34:21 time: 0.7111 data_time: 0.0240 memory: 14901 loss: 0.9221 loss_prob: 0.4754 loss_thr: 0.3636 loss_db: 0.0831 2022/11/02 23:58:41 - mmengine - INFO - Epoch(train) [975][60/63] lr: 4.7992e-04 eta: 2:34:14 time: 0.6054 data_time: 0.0157 memory: 14901 loss: 0.9428 loss_prob: 0.4927 loss_thr: 0.3644 loss_db: 0.0858 2022/11/02 23:58:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:58:51 - mmengine - INFO - Epoch(train) [976][5/63] lr: 4.7800e-04 eta: 2:34:14 time: 1.1085 data_time: 0.2338 memory: 14901 loss: 0.9465 loss_prob: 0.4920 loss_thr: 0.3688 loss_db: 0.0857 2022/11/02 23:58:54 - mmengine - INFO - Epoch(train) [976][10/63] lr: 4.7800e-04 eta: 2:34:06 time: 1.1245 data_time: 0.2342 memory: 14901 loss: 0.9738 loss_prob: 0.5083 loss_thr: 0.3778 loss_db: 0.0877 2022/11/02 23:58:57 - mmengine - INFO - Epoch(train) [976][15/63] lr: 4.7800e-04 eta: 2:34:06 time: 0.6024 data_time: 0.0173 memory: 14901 loss: 0.9645 loss_prob: 0.4992 loss_thr: 0.3779 loss_db: 0.0873 2022/11/02 23:59:00 - mmengine - INFO - Epoch(train) [976][20/63] lr: 4.7800e-04 eta: 2:34:00 time: 0.6182 data_time: 0.0178 memory: 14901 loss: 0.9024 loss_prob: 0.4637 loss_thr: 0.3564 loss_db: 0.0824 2022/11/02 23:59:03 - mmengine - INFO - Epoch(train) [976][25/63] lr: 4.7800e-04 eta: 2:34:00 time: 0.6223 data_time: 0.0108 memory: 14901 loss: 0.8727 loss_prob: 0.4444 loss_thr: 0.3491 loss_db: 0.0792 2022/11/02 23:59:06 - mmengine - INFO - Epoch(train) [976][30/63] lr: 4.7800e-04 eta: 2:33:53 time: 0.5903 data_time: 0.0359 memory: 14901 loss: 0.9758 loss_prob: 0.5000 loss_thr: 0.3883 loss_db: 0.0875 2022/11/02 23:59:09 - mmengine - INFO - Epoch(train) [976][35/63] lr: 4.7800e-04 eta: 2:33:53 time: 0.5847 data_time: 0.0317 memory: 14901 loss: 0.9586 loss_prob: 0.4923 loss_thr: 0.3800 loss_db: 0.0863 2022/11/02 23:59:12 - mmengine - INFO - Epoch(train) [976][40/63] lr: 4.7800e-04 eta: 2:33:46 time: 0.5619 data_time: 0.0119 memory: 14901 loss: 0.8943 loss_prob: 0.4537 loss_thr: 0.3602 loss_db: 0.0804 2022/11/02 23:59:16 - mmengine - INFO - Epoch(train) [976][45/63] lr: 4.7800e-04 eta: 2:33:46 time: 0.6825 data_time: 0.0118 memory: 14901 loss: 0.9729 loss_prob: 0.5089 loss_thr: 0.3747 loss_db: 0.0893 2022/11/02 23:59:19 - mmengine - INFO - Epoch(train) [976][50/63] lr: 4.7800e-04 eta: 2:33:40 time: 0.6819 data_time: 0.0085 memory: 14901 loss: 0.9470 loss_prob: 0.4959 loss_thr: 0.3652 loss_db: 0.0859 2022/11/02 23:59:22 - mmengine - INFO - Epoch(train) [976][55/63] lr: 4.7800e-04 eta: 2:33:40 time: 0.6462 data_time: 0.0216 memory: 14901 loss: 0.9266 loss_prob: 0.4776 loss_thr: 0.3655 loss_db: 0.0835 2022/11/02 23:59:25 - mmengine - INFO - Epoch(train) [976][60/63] lr: 4.7800e-04 eta: 2:33:33 time: 0.6768 data_time: 0.0218 memory: 14901 loss: 0.9744 loss_prob: 0.5010 loss_thr: 0.3863 loss_db: 0.0871 2022/11/02 23:59:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/02 23:59:35 - mmengine - INFO - Epoch(train) [977][5/63] lr: 4.7608e-04 eta: 2:33:33 time: 1.0632 data_time: 0.2781 memory: 14901 loss: 0.9544 loss_prob: 0.4851 loss_thr: 0.3833 loss_db: 0.0860 2022/11/02 23:59:40 - mmengine - INFO - Epoch(train) [977][10/63] lr: 4.7608e-04 eta: 2:33:26 time: 1.2871 data_time: 0.2711 memory: 14901 loss: 0.9146 loss_prob: 0.4758 loss_thr: 0.3545 loss_db: 0.0842 2022/11/02 23:59:45 - mmengine - INFO - Epoch(train) [977][15/63] lr: 4.7608e-04 eta: 2:33:26 time: 1.0313 data_time: 0.0093 memory: 14901 loss: 0.9437 loss_prob: 0.4945 loss_thr: 0.3631 loss_db: 0.0862 2022/11/02 23:59:48 - mmengine - INFO - Epoch(train) [977][20/63] lr: 4.7608e-04 eta: 2:33:20 time: 0.8602 data_time: 0.0094 memory: 14901 loss: 0.9111 loss_prob: 0.4718 loss_thr: 0.3571 loss_db: 0.0822 2022/11/02 23:59:52 - mmengine - INFO - Epoch(train) [977][25/63] lr: 4.7608e-04 eta: 2:33:20 time: 0.6409 data_time: 0.0369 memory: 14901 loss: 0.8754 loss_prob: 0.4525 loss_thr: 0.3438 loss_db: 0.0791 2022/11/02 23:59:55 - mmengine - INFO - Epoch(train) [977][30/63] lr: 4.7608e-04 eta: 2:33:13 time: 0.6404 data_time: 0.0380 memory: 14901 loss: 0.9573 loss_prob: 0.5045 loss_thr: 0.3654 loss_db: 0.0874 2022/11/02 23:59:57 - mmengine - INFO - Epoch(train) [977][35/63] lr: 4.7608e-04 eta: 2:33:13 time: 0.5650 data_time: 0.0070 memory: 14901 loss: 0.9484 loss_prob: 0.4921 loss_thr: 0.3708 loss_db: 0.0854 2022/11/03 00:00:00 - mmengine - INFO - Epoch(train) [977][40/63] lr: 4.7608e-04 eta: 2:33:06 time: 0.5260 data_time: 0.0107 memory: 14901 loss: 0.8521 loss_prob: 0.4330 loss_thr: 0.3444 loss_db: 0.0747 2022/11/03 00:00:03 - mmengine - INFO - Epoch(train) [977][45/63] lr: 4.7608e-04 eta: 2:33:06 time: 0.5274 data_time: 0.0169 memory: 14901 loss: 0.8538 loss_prob: 0.4443 loss_thr: 0.3310 loss_db: 0.0785 2022/11/03 00:00:05 - mmengine - INFO - Epoch(train) [977][50/63] lr: 4.7608e-04 eta: 2:33:00 time: 0.5445 data_time: 0.0279 memory: 14901 loss: 0.8753 loss_prob: 0.4564 loss_thr: 0.3382 loss_db: 0.0807 2022/11/03 00:00:08 - mmengine - INFO - Epoch(train) [977][55/63] lr: 4.7608e-04 eta: 2:33:00 time: 0.5802 data_time: 0.0235 memory: 14901 loss: 0.8640 loss_prob: 0.4464 loss_thr: 0.3406 loss_db: 0.0770 2022/11/03 00:00:11 - mmengine - INFO - Epoch(train) [977][60/63] lr: 4.7608e-04 eta: 2:32:53 time: 0.5787 data_time: 0.0072 memory: 14901 loss: 0.8844 loss_prob: 0.4571 loss_thr: 0.3467 loss_db: 0.0805 2022/11/03 00:00:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:00:19 - mmengine - INFO - Epoch(train) [978][5/63] lr: 4.7415e-04 eta: 2:32:53 time: 0.9101 data_time: 0.2416 memory: 14901 loss: 0.9156 loss_prob: 0.4808 loss_thr: 0.3510 loss_db: 0.0838 2022/11/03 00:00:22 - mmengine - INFO - Epoch(train) [978][10/63] lr: 4.7415e-04 eta: 2:32:44 time: 0.8506 data_time: 0.2384 memory: 14901 loss: 0.9326 loss_prob: 0.4835 loss_thr: 0.3654 loss_db: 0.0837 2022/11/03 00:00:25 - mmengine - INFO - Epoch(train) [978][15/63] lr: 4.7415e-04 eta: 2:32:44 time: 0.5750 data_time: 0.0148 memory: 14901 loss: 1.0322 loss_prob: 0.5764 loss_thr: 0.3668 loss_db: 0.0890 2022/11/03 00:00:28 - mmengine - INFO - Epoch(train) [978][20/63] lr: 4.7415e-04 eta: 2:32:38 time: 0.5978 data_time: 0.0148 memory: 14901 loss: 1.0365 loss_prob: 0.5780 loss_thr: 0.3685 loss_db: 0.0900 2022/11/03 00:00:31 - mmengine - INFO - Epoch(train) [978][25/63] lr: 4.7415e-04 eta: 2:32:38 time: 0.5893 data_time: 0.0309 memory: 14901 loss: 0.9376 loss_prob: 0.4971 loss_thr: 0.3538 loss_db: 0.0867 2022/11/03 00:00:33 - mmengine - INFO - Epoch(train) [978][30/63] lr: 4.7415e-04 eta: 2:32:31 time: 0.5524 data_time: 0.0335 memory: 14901 loss: 0.8856 loss_prob: 0.4664 loss_thr: 0.3385 loss_db: 0.0806 2022/11/03 00:00:36 - mmengine - INFO - Epoch(train) [978][35/63] lr: 4.7415e-04 eta: 2:32:31 time: 0.5150 data_time: 0.0086 memory: 14901 loss: 0.9002 loss_prob: 0.4674 loss_thr: 0.3508 loss_db: 0.0820 2022/11/03 00:00:39 - mmengine - INFO - Epoch(train) [978][40/63] lr: 4.7415e-04 eta: 2:32:24 time: 0.5512 data_time: 0.0186 memory: 14901 loss: 0.9942 loss_prob: 0.5188 loss_thr: 0.3858 loss_db: 0.0896 2022/11/03 00:00:42 - mmengine - INFO - Epoch(train) [978][45/63] lr: 4.7415e-04 eta: 2:32:24 time: 0.5606 data_time: 0.0186 memory: 14901 loss: 1.0353 loss_prob: 0.5371 loss_thr: 0.4067 loss_db: 0.0915 2022/11/03 00:00:45 - mmengine - INFO - Epoch(train) [978][50/63] lr: 4.7415e-04 eta: 2:32:18 time: 0.5767 data_time: 0.0250 memory: 14901 loss: 1.0006 loss_prob: 0.5226 loss_thr: 0.3847 loss_db: 0.0933 2022/11/03 00:00:48 - mmengine - INFO - Epoch(train) [978][55/63] lr: 4.7415e-04 eta: 2:32:18 time: 0.6465 data_time: 0.0273 memory: 14901 loss: 1.0219 loss_prob: 0.5330 loss_thr: 0.3936 loss_db: 0.0953 2022/11/03 00:00:51 - mmengine - INFO - Epoch(train) [978][60/63] lr: 4.7415e-04 eta: 2:32:11 time: 0.6736 data_time: 0.0086 memory: 14901 loss: 1.0111 loss_prob: 0.5277 loss_thr: 0.3927 loss_db: 0.0907 2022/11/03 00:00:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:01:01 - mmengine - INFO - Epoch(train) [979][5/63] lr: 4.7223e-04 eta: 2:32:11 time: 1.1164 data_time: 0.2394 memory: 14901 loss: 0.9882 loss_prob: 0.5250 loss_thr: 0.3736 loss_db: 0.0897 2022/11/03 00:01:05 - mmengine - INFO - Epoch(train) [979][10/63] lr: 4.7223e-04 eta: 2:32:03 time: 1.0861 data_time: 0.2386 memory: 14901 loss: 0.9895 loss_prob: 0.5244 loss_thr: 0.3744 loss_db: 0.0907 2022/11/03 00:01:08 - mmengine - INFO - Epoch(train) [979][15/63] lr: 4.7223e-04 eta: 2:32:03 time: 0.6518 data_time: 0.0064 memory: 14901 loss: 0.9855 loss_prob: 0.5203 loss_thr: 0.3763 loss_db: 0.0889 2022/11/03 00:01:11 - mmengine - INFO - Epoch(train) [979][20/63] lr: 4.7223e-04 eta: 2:31:57 time: 0.6375 data_time: 0.0054 memory: 14901 loss: 0.8548 loss_prob: 0.4403 loss_thr: 0.3377 loss_db: 0.0769 2022/11/03 00:01:14 - mmengine - INFO - Epoch(train) [979][25/63] lr: 4.7223e-04 eta: 2:31:57 time: 0.6703 data_time: 0.0177 memory: 14901 loss: 0.8701 loss_prob: 0.4503 loss_thr: 0.3398 loss_db: 0.0800 2022/11/03 00:01:18 - mmengine - INFO - Epoch(train) [979][30/63] lr: 4.7223e-04 eta: 2:31:50 time: 0.6578 data_time: 0.0415 memory: 14901 loss: 0.9305 loss_prob: 0.4847 loss_thr: 0.3609 loss_db: 0.0848 2022/11/03 00:01:21 - mmengine - INFO - Epoch(train) [979][35/63] lr: 4.7223e-04 eta: 2:31:50 time: 0.6565 data_time: 0.0290 memory: 14901 loss: 0.9915 loss_prob: 0.5187 loss_thr: 0.3828 loss_db: 0.0900 2022/11/03 00:01:24 - mmengine - INFO - Epoch(train) [979][40/63] lr: 4.7223e-04 eta: 2:31:43 time: 0.6097 data_time: 0.0068 memory: 14901 loss: 0.9926 loss_prob: 0.5215 loss_thr: 0.3822 loss_db: 0.0889 2022/11/03 00:01:28 - mmengine - INFO - Epoch(train) [979][45/63] lr: 4.7223e-04 eta: 2:31:43 time: 0.6631 data_time: 0.0072 memory: 14901 loss: 0.9291 loss_prob: 0.4849 loss_thr: 0.3619 loss_db: 0.0823 2022/11/03 00:01:31 - mmengine - INFO - Epoch(train) [979][50/63] lr: 4.7223e-04 eta: 2:31:37 time: 0.6814 data_time: 0.0185 memory: 14901 loss: 0.9161 loss_prob: 0.4765 loss_thr: 0.3561 loss_db: 0.0836 2022/11/03 00:01:34 - mmengine - INFO - Epoch(train) [979][55/63] lr: 4.7223e-04 eta: 2:31:37 time: 0.5848 data_time: 0.0295 memory: 14901 loss: 0.9629 loss_prob: 0.5053 loss_thr: 0.3677 loss_db: 0.0899 2022/11/03 00:01:37 - mmengine - INFO - Epoch(train) [979][60/63] lr: 4.7223e-04 eta: 2:31:30 time: 0.6415 data_time: 0.0177 memory: 14901 loss: 1.0043 loss_prob: 0.5290 loss_thr: 0.3837 loss_db: 0.0917 2022/11/03 00:01:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:01:47 - mmengine - INFO - Epoch(train) [980][5/63] lr: 4.7031e-04 eta: 2:31:30 time: 1.0742 data_time: 0.2647 memory: 14901 loss: 0.9844 loss_prob: 0.5156 loss_thr: 0.3786 loss_db: 0.0902 2022/11/03 00:01:51 - mmengine - INFO - Epoch(train) [980][10/63] lr: 4.7031e-04 eta: 2:31:23 time: 1.2075 data_time: 0.2684 memory: 14901 loss: 0.9530 loss_prob: 0.4894 loss_thr: 0.3777 loss_db: 0.0859 2022/11/03 00:01:54 - mmengine - INFO - Epoch(train) [980][15/63] lr: 4.7031e-04 eta: 2:31:23 time: 0.6988 data_time: 0.0116 memory: 14901 loss: 0.9779 loss_prob: 0.5086 loss_thr: 0.3808 loss_db: 0.0885 2022/11/03 00:01:57 - mmengine - INFO - Epoch(train) [980][20/63] lr: 4.7031e-04 eta: 2:31:16 time: 0.6779 data_time: 0.0062 memory: 14901 loss: 0.9153 loss_prob: 0.4779 loss_thr: 0.3534 loss_db: 0.0841 2022/11/03 00:02:01 - mmengine - INFO - Epoch(train) [980][25/63] lr: 4.7031e-04 eta: 2:31:16 time: 0.7042 data_time: 0.0335 memory: 14901 loss: 0.8831 loss_prob: 0.4542 loss_thr: 0.3481 loss_db: 0.0808 2022/11/03 00:02:05 - mmengine - INFO - Epoch(train) [980][30/63] lr: 4.7031e-04 eta: 2:31:10 time: 0.7301 data_time: 0.0328 memory: 14901 loss: 0.9305 loss_prob: 0.4832 loss_thr: 0.3624 loss_db: 0.0848 2022/11/03 00:02:08 - mmengine - INFO - Epoch(train) [980][35/63] lr: 4.7031e-04 eta: 2:31:10 time: 0.7062 data_time: 0.0112 memory: 14901 loss: 0.9949 loss_prob: 0.5336 loss_thr: 0.3703 loss_db: 0.0911 2022/11/03 00:02:11 - mmengine - INFO - Epoch(train) [980][40/63] lr: 4.7031e-04 eta: 2:31:03 time: 0.5986 data_time: 0.0113 memory: 14901 loss: 1.0078 loss_prob: 0.5449 loss_thr: 0.3702 loss_db: 0.0927 2022/11/03 00:02:14 - mmengine - INFO - Epoch(train) [980][45/63] lr: 4.7031e-04 eta: 2:31:03 time: 0.6161 data_time: 0.0057 memory: 14901 loss: 0.9146 loss_prob: 0.4800 loss_thr: 0.3521 loss_db: 0.0825 2022/11/03 00:02:18 - mmengine - INFO - Epoch(train) [980][50/63] lr: 4.7031e-04 eta: 2:30:57 time: 0.6761 data_time: 0.0252 memory: 14901 loss: 0.8211 loss_prob: 0.4150 loss_thr: 0.3337 loss_db: 0.0724 2022/11/03 00:02:21 - mmengine - INFO - Epoch(train) [980][55/63] lr: 4.7031e-04 eta: 2:30:57 time: 0.6413 data_time: 0.0249 memory: 14901 loss: 0.8051 loss_prob: 0.4041 loss_thr: 0.3289 loss_db: 0.0721 2022/11/03 00:02:25 - mmengine - INFO - Epoch(train) [980][60/63] lr: 4.7031e-04 eta: 2:30:50 time: 0.7072 data_time: 0.0074 memory: 14901 loss: 0.8397 loss_prob: 0.4320 loss_thr: 0.3324 loss_db: 0.0753 2022/11/03 00:02:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:02:26 - mmengine - INFO - Saving checkpoint at 980 epochs 2022/11/03 00:02:30 - mmengine - INFO - Epoch(val) [980][5/500] eta: 2:30:50 time: 0.0433 data_time: 0.0051 memory: 14901 2022/11/03 00:02:30 - mmengine - INFO - Epoch(val) [980][10/500] eta: 0:00:24 time: 0.0501 data_time: 0.0056 memory: 1008 2022/11/03 00:02:30 - mmengine - INFO - Epoch(val) [980][15/500] eta: 0:00:24 time: 0.0470 data_time: 0.0036 memory: 1008 2022/11/03 00:02:30 - mmengine - INFO - Epoch(val) [980][20/500] eta: 0:00:20 time: 0.0421 data_time: 0.0032 memory: 1008 2022/11/03 00:02:31 - mmengine - INFO - Epoch(val) [980][25/500] eta: 0:00:20 time: 0.0396 data_time: 0.0025 memory: 1008 2022/11/03 00:02:31 - mmengine - INFO - Epoch(val) [980][30/500] eta: 0:00:20 time: 0.0444 data_time: 0.0029 memory: 1008 2022/11/03 00:02:31 - mmengine - INFO - Epoch(val) [980][35/500] eta: 0:00:20 time: 0.0477 data_time: 0.0049 memory: 1008 2022/11/03 00:02:31 - mmengine - INFO - Epoch(val) [980][40/500] eta: 0:00:23 time: 0.0506 data_time: 0.0050 memory: 1008 2022/11/03 00:02:32 - mmengine - INFO - Epoch(val) [980][45/500] eta: 0:00:23 time: 0.0480 data_time: 0.0028 memory: 1008 2022/11/03 00:02:32 - mmengine - INFO - Epoch(val) [980][50/500] eta: 0:00:20 time: 0.0457 data_time: 0.0026 memory: 1008 2022/11/03 00:02:32 - mmengine - INFO - Epoch(val) [980][55/500] eta: 0:00:20 time: 0.0505 data_time: 0.0028 memory: 1008 2022/11/03 00:02:32 - mmengine - INFO - Epoch(val) [980][60/500] eta: 0:00:20 time: 0.0466 data_time: 0.0028 memory: 1008 2022/11/03 00:02:33 - mmengine - INFO - Epoch(val) [980][65/500] eta: 0:00:20 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/03 00:02:33 - mmengine - INFO - Epoch(val) [980][70/500] eta: 0:00:20 time: 0.0466 data_time: 0.0031 memory: 1008 2022/11/03 00:02:33 - mmengine - INFO - Epoch(val) [980][75/500] eta: 0:00:20 time: 0.0445 data_time: 0.0033 memory: 1008 2022/11/03 00:02:33 - mmengine - INFO - Epoch(val) [980][80/500] eta: 0:00:16 time: 0.0389 data_time: 0.0032 memory: 1008 2022/11/03 00:02:33 - mmengine - INFO - Epoch(val) [980][85/500] eta: 0:00:16 time: 0.0398 data_time: 0.0031 memory: 1008 2022/11/03 00:02:34 - mmengine - INFO - Epoch(val) [980][90/500] eta: 0:00:19 time: 0.0474 data_time: 0.0035 memory: 1008 2022/11/03 00:02:34 - mmengine - INFO - Epoch(val) [980][95/500] eta: 0:00:19 time: 0.0465 data_time: 0.0031 memory: 1008 2022/11/03 00:02:34 - mmengine - INFO - Epoch(val) [980][100/500] eta: 0:00:17 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/03 00:02:34 - mmengine - INFO - Epoch(val) [980][105/500] eta: 0:00:17 time: 0.0419 data_time: 0.0027 memory: 1008 2022/11/03 00:02:35 - mmengine - INFO - Epoch(val) [980][110/500] eta: 0:00:15 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/03 00:02:35 - mmengine - INFO - Epoch(val) [980][115/500] eta: 0:00:15 time: 0.0450 data_time: 0.0031 memory: 1008 2022/11/03 00:02:35 - mmengine - INFO - Epoch(val) [980][120/500] eta: 0:00:17 time: 0.0460 data_time: 0.0031 memory: 1008 2022/11/03 00:02:35 - mmengine - INFO - Epoch(val) [980][125/500] eta: 0:00:17 time: 0.0428 data_time: 0.0030 memory: 1008 2022/11/03 00:02:35 - mmengine - INFO - Epoch(val) [980][130/500] eta: 0:00:16 time: 0.0448 data_time: 0.0035 memory: 1008 2022/11/03 00:02:36 - mmengine - INFO - Epoch(val) [980][135/500] eta: 0:00:16 time: 0.0429 data_time: 0.0032 memory: 1008 2022/11/03 00:02:36 - mmengine - INFO - Epoch(val) [980][140/500] eta: 0:00:14 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/03 00:02:36 - mmengine - INFO - Epoch(val) [980][145/500] eta: 0:00:14 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/03 00:02:36 - mmengine - INFO - Epoch(val) [980][150/500] eta: 0:00:14 time: 0.0423 data_time: 0.0029 memory: 1008 2022/11/03 00:02:37 - mmengine - INFO - Epoch(val) [980][155/500] eta: 0:00:14 time: 0.0450 data_time: 0.0027 memory: 1008 2022/11/03 00:02:37 - mmengine - INFO - Epoch(val) [980][160/500] eta: 0:00:15 time: 0.0447 data_time: 0.0026 memory: 1008 2022/11/03 00:02:37 - mmengine - INFO - Epoch(val) [980][165/500] eta: 0:00:15 time: 0.0427 data_time: 0.0029 memory: 1008 2022/11/03 00:02:37 - mmengine - INFO - Epoch(val) [980][170/500] eta: 0:00:14 time: 0.0449 data_time: 0.0029 memory: 1008 2022/11/03 00:02:37 - mmengine - INFO - Epoch(val) [980][175/500] eta: 0:00:14 time: 0.0408 data_time: 0.0025 memory: 1008 2022/11/03 00:02:38 - mmengine - INFO - Epoch(val) [980][180/500] eta: 0:00:12 time: 0.0401 data_time: 0.0026 memory: 1008 2022/11/03 00:02:38 - mmengine - INFO - Epoch(val) [980][185/500] eta: 0:00:12 time: 0.0442 data_time: 0.0027 memory: 1008 2022/11/03 00:02:38 - mmengine - INFO - Epoch(val) [980][190/500] eta: 0:00:13 time: 0.0440 data_time: 0.0026 memory: 1008 2022/11/03 00:02:38 - mmengine - INFO - Epoch(val) [980][195/500] eta: 0:00:13 time: 0.0420 data_time: 0.0031 memory: 1008 2022/11/03 00:02:39 - mmengine - INFO - Epoch(val) [980][200/500] eta: 0:00:15 time: 0.0512 data_time: 0.0033 memory: 1008 2022/11/03 00:02:39 - mmengine - INFO - Epoch(val) [980][205/500] eta: 0:00:15 time: 0.0516 data_time: 0.0028 memory: 1008 2022/11/03 00:02:39 - mmengine - INFO - Epoch(val) [980][210/500] eta: 0:00:12 time: 0.0418 data_time: 0.0027 memory: 1008 2022/11/03 00:02:39 - mmengine - INFO - Epoch(val) [980][215/500] eta: 0:00:12 time: 0.0429 data_time: 0.0027 memory: 1008 2022/11/03 00:02:39 - mmengine - INFO - Epoch(val) [980][220/500] eta: 0:00:11 time: 0.0411 data_time: 0.0025 memory: 1008 2022/11/03 00:02:40 - mmengine - INFO - Epoch(val) [980][225/500] eta: 0:00:11 time: 0.0374 data_time: 0.0021 memory: 1008 2022/11/03 00:02:40 - mmengine - INFO - Epoch(val) [980][230/500] eta: 0:00:11 time: 0.0415 data_time: 0.0029 memory: 1008 2022/11/03 00:02:40 - mmengine - INFO - Epoch(val) [980][235/500] eta: 0:00:11 time: 0.0425 data_time: 0.0033 memory: 1008 2022/11/03 00:02:40 - mmengine - INFO - Epoch(val) [980][240/500] eta: 0:00:10 time: 0.0410 data_time: 0.0028 memory: 1008 2022/11/03 00:02:40 - mmengine - INFO - Epoch(val) [980][245/500] eta: 0:00:10 time: 0.0414 data_time: 0.0033 memory: 1008 2022/11/03 00:02:41 - mmengine - INFO - Epoch(val) [980][250/500] eta: 0:00:10 time: 0.0404 data_time: 0.0032 memory: 1008 2022/11/03 00:02:41 - mmengine - INFO - Epoch(val) [980][255/500] eta: 0:00:10 time: 0.0400 data_time: 0.0035 memory: 1008 2022/11/03 00:02:41 - mmengine - INFO - Epoch(val) [980][260/500] eta: 0:00:10 time: 0.0424 data_time: 0.0037 memory: 1008 2022/11/03 00:02:41 - mmengine - INFO - Epoch(val) [980][265/500] eta: 0:00:10 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/03 00:02:41 - mmengine - INFO - Epoch(val) [980][270/500] eta: 0:00:10 time: 0.0438 data_time: 0.0032 memory: 1008 2022/11/03 00:02:42 - mmengine - INFO - Epoch(val) [980][275/500] eta: 0:00:10 time: 0.0414 data_time: 0.0031 memory: 1008 2022/11/03 00:02:42 - mmengine - INFO - Epoch(val) [980][280/500] eta: 0:00:09 time: 0.0426 data_time: 0.0031 memory: 1008 2022/11/03 00:02:42 - mmengine - INFO - Epoch(val) [980][285/500] eta: 0:00:09 time: 0.0429 data_time: 0.0032 memory: 1008 2022/11/03 00:02:42 - mmengine - INFO - Epoch(val) [980][290/500] eta: 0:00:08 time: 0.0409 data_time: 0.0032 memory: 1008 2022/11/03 00:02:43 - mmengine - INFO - Epoch(val) [980][295/500] eta: 0:00:08 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/03 00:02:43 - mmengine - INFO - Epoch(val) [980][300/500] eta: 0:00:08 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/03 00:02:43 - mmengine - INFO - Epoch(val) [980][305/500] eta: 0:00:08 time: 0.0397 data_time: 0.0031 memory: 1008 2022/11/03 00:02:43 - mmengine - INFO - Epoch(val) [980][310/500] eta: 0:00:08 time: 0.0434 data_time: 0.0031 memory: 1008 2022/11/03 00:02:43 - mmengine - INFO - Epoch(val) [980][315/500] eta: 0:00:08 time: 0.0452 data_time: 0.0030 memory: 1008 2022/11/03 00:02:44 - mmengine - INFO - Epoch(val) [980][320/500] eta: 0:00:07 time: 0.0408 data_time: 0.0029 memory: 1008 2022/11/03 00:02:44 - mmengine - INFO - Epoch(val) [980][325/500] eta: 0:00:07 time: 0.0564 data_time: 0.0031 memory: 1008 2022/11/03 00:02:44 - mmengine - INFO - Epoch(val) [980][330/500] eta: 0:00:09 time: 0.0568 data_time: 0.0030 memory: 1008 2022/11/03 00:02:44 - mmengine - INFO - Epoch(val) [980][335/500] eta: 0:00:09 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/03 00:02:45 - mmengine - INFO - Epoch(val) [980][340/500] eta: 0:00:07 time: 0.0487 data_time: 0.0026 memory: 1008 2022/11/03 00:02:45 - mmengine - INFO - Epoch(val) [980][345/500] eta: 0:00:07 time: 0.0497 data_time: 0.0026 memory: 1008 2022/11/03 00:02:45 - mmengine - INFO - Epoch(val) [980][350/500] eta: 0:00:06 time: 0.0443 data_time: 0.0027 memory: 1008 2022/11/03 00:02:45 - mmengine - INFO - Epoch(val) [980][355/500] eta: 0:00:06 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/03 00:02:45 - mmengine - INFO - Epoch(val) [980][360/500] eta: 0:00:05 time: 0.0399 data_time: 0.0028 memory: 1008 2022/11/03 00:02:46 - mmengine - INFO - Epoch(val) [980][365/500] eta: 0:00:05 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/03 00:02:46 - mmengine - INFO - Epoch(val) [980][370/500] eta: 0:00:05 time: 0.0460 data_time: 0.0045 memory: 1008 2022/11/03 00:02:46 - mmengine - INFO - Epoch(val) [980][375/500] eta: 0:00:05 time: 0.0473 data_time: 0.0049 memory: 1008 2022/11/03 00:02:46 - mmengine - INFO - Epoch(val) [980][380/500] eta: 0:00:05 time: 0.0432 data_time: 0.0031 memory: 1008 2022/11/03 00:02:47 - mmengine - INFO - Epoch(val) [980][385/500] eta: 0:00:05 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/03 00:02:47 - mmengine - INFO - Epoch(val) [980][390/500] eta: 0:00:04 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/03 00:02:47 - mmengine - INFO - Epoch(val) [980][395/500] eta: 0:00:04 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/03 00:02:47 - mmengine - INFO - Epoch(val) [980][400/500] eta: 0:00:04 time: 0.0430 data_time: 0.0030 memory: 1008 2022/11/03 00:02:47 - mmengine - INFO - Epoch(val) [980][405/500] eta: 0:00:04 time: 0.0418 data_time: 0.0028 memory: 1008 2022/11/03 00:02:48 - mmengine - INFO - Epoch(val) [980][410/500] eta: 0:00:03 time: 0.0438 data_time: 0.0026 memory: 1008 2022/11/03 00:02:48 - mmengine - INFO - Epoch(val) [980][415/500] eta: 0:00:03 time: 0.0427 data_time: 0.0026 memory: 1008 2022/11/03 00:02:48 - mmengine - INFO - Epoch(val) [980][420/500] eta: 0:00:03 time: 0.0380 data_time: 0.0027 memory: 1008 2022/11/03 00:02:48 - mmengine - INFO - Epoch(val) [980][425/500] eta: 0:00:03 time: 0.0406 data_time: 0.0028 memory: 1008 2022/11/03 00:02:49 - mmengine - INFO - Epoch(val) [980][430/500] eta: 0:00:03 time: 0.0439 data_time: 0.0033 memory: 1008 2022/11/03 00:02:49 - mmengine - INFO - Epoch(val) [980][435/500] eta: 0:00:03 time: 0.0398 data_time: 0.0032 memory: 1008 2022/11/03 00:02:49 - mmengine - INFO - Epoch(val) [980][440/500] eta: 0:00:02 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/03 00:02:49 - mmengine - INFO - Epoch(val) [980][445/500] eta: 0:00:02 time: 0.0433 data_time: 0.0027 memory: 1008 2022/11/03 00:02:49 - mmengine - INFO - Epoch(val) [980][450/500] eta: 0:00:02 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/03 00:02:50 - mmengine - INFO - Epoch(val) [980][455/500] eta: 0:00:02 time: 0.0461 data_time: 0.0030 memory: 1008 2022/11/03 00:02:50 - mmengine - INFO - Epoch(val) [980][460/500] eta: 0:00:01 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/03 00:02:50 - mmengine - INFO - Epoch(val) [980][465/500] eta: 0:00:01 time: 0.0398 data_time: 0.0028 memory: 1008 2022/11/03 00:02:50 - mmengine - INFO - Epoch(val) [980][470/500] eta: 0:00:01 time: 0.0458 data_time: 0.0031 memory: 1008 2022/11/03 00:02:50 - mmengine - INFO - Epoch(val) [980][475/500] eta: 0:00:01 time: 0.0437 data_time: 0.0030 memory: 1008 2022/11/03 00:02:51 - mmengine - INFO - Epoch(val) [980][480/500] eta: 0:00:00 time: 0.0399 data_time: 0.0028 memory: 1008 2022/11/03 00:02:51 - mmengine - INFO - Epoch(val) [980][485/500] eta: 0:00:00 time: 0.0441 data_time: 0.0030 memory: 1008 2022/11/03 00:02:51 - mmengine - INFO - Epoch(val) [980][490/500] eta: 0:00:00 time: 0.0459 data_time: 0.0038 memory: 1008 2022/11/03 00:02:51 - mmengine - INFO - Epoch(val) [980][495/500] eta: 0:00:00 time: 0.0473 data_time: 0.0037 memory: 1008 2022/11/03 00:02:52 - mmengine - INFO - Epoch(val) [980][500/500] eta: 0:00:00 time: 0.0468 data_time: 0.0043 memory: 1008 2022/11/03 00:02:52 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8247, precision: 0.7556, hmean: 0.7887 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8247, precision: 0.8001, hmean: 0.8122 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8247, precision: 0.8259, hmean: 0.8253 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8195, precision: 0.8455, hmean: 0.8323 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8050, precision: 0.8717, hmean: 0.8370 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7015, precision: 0.9146, hmean: 0.7940 2022/11/03 00:02:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1603, precision: 0.9597, hmean: 0.2748 2022/11/03 00:02:52 - mmengine - INFO - Epoch(val) [980][500/500] icdar/precision: 0.8717 icdar/recall: 0.8050 icdar/hmean: 0.8370 2022/11/03 00:02:59 - mmengine - INFO - Epoch(train) [981][5/63] lr: 4.6838e-04 eta: 0:00:00 time: 1.0850 data_time: 0.2678 memory: 14901 loss: 0.9423 loss_prob: 0.4895 loss_thr: 0.3674 loss_db: 0.0854 2022/11/03 00:03:03 - mmengine - INFO - Epoch(train) [981][10/63] lr: 4.6838e-04 eta: 2:30:43 time: 1.1564 data_time: 0.2671 memory: 14901 loss: 0.9353 loss_prob: 0.4825 loss_thr: 0.3682 loss_db: 0.0846 2022/11/03 00:03:08 - mmengine - INFO - Epoch(train) [981][15/63] lr: 4.6838e-04 eta: 2:30:43 time: 0.8844 data_time: 0.0064 memory: 14901 loss: 0.9580 loss_prob: 0.4958 loss_thr: 0.3747 loss_db: 0.0875 2022/11/03 00:03:11 - mmengine - INFO - Epoch(train) [981][20/63] lr: 4.6838e-04 eta: 2:30:36 time: 0.7695 data_time: 0.0064 memory: 14901 loss: 0.9620 loss_prob: 0.5054 loss_thr: 0.3679 loss_db: 0.0887 2022/11/03 00:03:14 - mmengine - INFO - Epoch(train) [981][25/63] lr: 4.6838e-04 eta: 2:30:36 time: 0.6506 data_time: 0.0400 memory: 14901 loss: 0.9567 loss_prob: 0.5048 loss_thr: 0.3643 loss_db: 0.0875 2022/11/03 00:03:18 - mmengine - INFO - Epoch(train) [981][30/63] lr: 4.6838e-04 eta: 2:30:30 time: 0.7416 data_time: 0.0402 memory: 14901 loss: 0.9554 loss_prob: 0.4984 loss_thr: 0.3714 loss_db: 0.0855 2022/11/03 00:03:21 - mmengine - INFO - Epoch(train) [981][35/63] lr: 4.6838e-04 eta: 2:30:30 time: 0.6834 data_time: 0.0062 memory: 14901 loss: 0.9454 loss_prob: 0.4889 loss_thr: 0.3726 loss_db: 0.0839 2022/11/03 00:03:24 - mmengine - INFO - Epoch(train) [981][40/63] lr: 4.6838e-04 eta: 2:30:23 time: 0.5911 data_time: 0.0071 memory: 14901 loss: 0.9868 loss_prob: 0.5144 loss_thr: 0.3823 loss_db: 0.0901 2022/11/03 00:03:29 - mmengine - INFO - Epoch(train) [981][45/63] lr: 4.6838e-04 eta: 2:30:23 time: 0.7660 data_time: 0.0066 memory: 14901 loss: 1.0178 loss_prob: 0.5282 loss_thr: 0.3960 loss_db: 0.0936 2022/11/03 00:03:33 - mmengine - INFO - Epoch(train) [981][50/63] lr: 4.6838e-04 eta: 2:30:17 time: 0.8312 data_time: 0.0302 memory: 14901 loss: 0.9923 loss_prob: 0.5167 loss_thr: 0.3858 loss_db: 0.0899 2022/11/03 00:03:36 - mmengine - INFO - Epoch(train) [981][55/63] lr: 4.6838e-04 eta: 2:30:17 time: 0.7017 data_time: 0.0309 memory: 14901 loss: 0.9295 loss_prob: 0.4779 loss_thr: 0.3680 loss_db: 0.0836 2022/11/03 00:03:40 - mmengine - INFO - Epoch(train) [981][60/63] lr: 4.6838e-04 eta: 2:30:11 time: 0.7686 data_time: 0.0060 memory: 14901 loss: 0.8774 loss_prob: 0.4498 loss_thr: 0.3474 loss_db: 0.0802 2022/11/03 00:03:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:03:49 - mmengine - INFO - Epoch(train) [982][5/63] lr: 4.6646e-04 eta: 2:30:11 time: 1.0897 data_time: 0.2553 memory: 14901 loss: 0.9141 loss_prob: 0.4733 loss_thr: 0.3617 loss_db: 0.0791 2022/11/03 00:03:54 - mmengine - INFO - Epoch(train) [982][10/63] lr: 4.6646e-04 eta: 2:30:03 time: 1.2274 data_time: 0.2840 memory: 14901 loss: 0.9588 loss_prob: 0.4915 loss_thr: 0.3807 loss_db: 0.0866 2022/11/03 00:03:59 - mmengine - INFO - Epoch(train) [982][15/63] lr: 4.6646e-04 eta: 2:30:03 time: 0.9542 data_time: 0.0364 memory: 14901 loss: 0.9711 loss_prob: 0.5109 loss_thr: 0.3712 loss_db: 0.0890 2022/11/03 00:04:03 - mmengine - INFO - Epoch(train) [982][20/63] lr: 4.6646e-04 eta: 2:29:57 time: 0.9148 data_time: 0.0080 memory: 14901 loss: 0.8918 loss_prob: 0.4763 loss_thr: 0.3358 loss_db: 0.0798 2022/11/03 00:04:07 - mmengine - INFO - Epoch(train) [982][25/63] lr: 4.6646e-04 eta: 2:29:57 time: 0.7949 data_time: 0.0310 memory: 14901 loss: 0.8927 loss_prob: 0.4618 loss_thr: 0.3524 loss_db: 0.0784 2022/11/03 00:04:11 - mmengine - INFO - Epoch(train) [982][30/63] lr: 4.6646e-04 eta: 2:29:51 time: 0.7389 data_time: 0.0366 memory: 14901 loss: 0.9131 loss_prob: 0.4686 loss_thr: 0.3621 loss_db: 0.0824 2022/11/03 00:04:13 - mmengine - INFO - Epoch(train) [982][35/63] lr: 4.6646e-04 eta: 2:29:51 time: 0.6691 data_time: 0.0130 memory: 14901 loss: 0.9273 loss_prob: 0.4764 loss_thr: 0.3660 loss_db: 0.0849 2022/11/03 00:04:16 - mmengine - INFO - Epoch(train) [982][40/63] lr: 4.6646e-04 eta: 2:29:44 time: 0.5550 data_time: 0.0098 memory: 14901 loss: 0.9645 loss_prob: 0.4953 loss_thr: 0.3829 loss_db: 0.0864 2022/11/03 00:04:19 - mmengine - INFO - Epoch(train) [982][45/63] lr: 4.6646e-04 eta: 2:29:44 time: 0.5125 data_time: 0.0081 memory: 14901 loss: 0.9600 loss_prob: 0.4982 loss_thr: 0.3753 loss_db: 0.0865 2022/11/03 00:04:21 - mmengine - INFO - Epoch(train) [982][50/63] lr: 4.6646e-04 eta: 2:29:37 time: 0.5279 data_time: 0.0203 memory: 14901 loss: 0.8861 loss_prob: 0.4544 loss_thr: 0.3514 loss_db: 0.0804 2022/11/03 00:04:24 - mmengine - INFO - Epoch(train) [982][55/63] lr: 4.6646e-04 eta: 2:29:37 time: 0.5885 data_time: 0.0242 memory: 14901 loss: 0.9165 loss_prob: 0.4693 loss_thr: 0.3648 loss_db: 0.0824 2022/11/03 00:04:29 - mmengine - INFO - Epoch(train) [982][60/63] lr: 4.6646e-04 eta: 2:29:31 time: 0.8024 data_time: 0.0108 memory: 14901 loss: 0.9213 loss_prob: 0.4728 loss_thr: 0.3671 loss_db: 0.0814 2022/11/03 00:04:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:04:38 - mmengine - INFO - Epoch(train) [983][5/63] lr: 4.6453e-04 eta: 2:29:31 time: 1.0543 data_time: 0.2650 memory: 14901 loss: 0.7708 loss_prob: 0.3878 loss_thr: 0.3139 loss_db: 0.0691 2022/11/03 00:04:41 - mmengine - INFO - Epoch(train) [983][10/63] lr: 4.6453e-04 eta: 2:29:23 time: 0.9497 data_time: 0.2626 memory: 14901 loss: 0.9030 loss_prob: 0.4813 loss_thr: 0.3376 loss_db: 0.0841 2022/11/03 00:04:45 - mmengine - INFO - Epoch(train) [983][15/63] lr: 4.6453e-04 eta: 2:29:23 time: 0.6215 data_time: 0.0105 memory: 14901 loss: 0.9700 loss_prob: 0.5172 loss_thr: 0.3640 loss_db: 0.0887 2022/11/03 00:04:49 - mmengine - INFO - Epoch(train) [983][20/63] lr: 4.6453e-04 eta: 2:29:17 time: 0.8119 data_time: 0.0111 memory: 14901 loss: 0.9444 loss_prob: 0.4815 loss_thr: 0.3791 loss_db: 0.0838 2022/11/03 00:04:53 - mmengine - INFO - Epoch(train) [983][25/63] lr: 4.6453e-04 eta: 2:29:17 time: 0.8397 data_time: 0.0160 memory: 14901 loss: 0.9624 loss_prob: 0.4986 loss_thr: 0.3758 loss_db: 0.0880 2022/11/03 00:04:57 - mmengine - INFO - Epoch(train) [983][30/63] lr: 4.6453e-04 eta: 2:29:10 time: 0.7237 data_time: 0.0368 memory: 14901 loss: 0.9472 loss_prob: 0.4952 loss_thr: 0.3646 loss_db: 0.0874 2022/11/03 00:04:59 - mmengine - INFO - Epoch(train) [983][35/63] lr: 4.6453e-04 eta: 2:29:10 time: 0.6299 data_time: 0.0271 memory: 14901 loss: 0.9443 loss_prob: 0.4908 loss_thr: 0.3692 loss_db: 0.0843 2022/11/03 00:05:02 - mmengine - INFO - Epoch(train) [983][40/63] lr: 4.6453e-04 eta: 2:29:04 time: 0.5250 data_time: 0.0100 memory: 14901 loss: 0.8719 loss_prob: 0.4508 loss_thr: 0.3444 loss_db: 0.0767 2022/11/03 00:05:05 - mmengine - INFO - Epoch(train) [983][45/63] lr: 4.6453e-04 eta: 2:29:04 time: 0.5988 data_time: 0.0106 memory: 14901 loss: 0.9546 loss_prob: 0.4946 loss_thr: 0.3725 loss_db: 0.0875 2022/11/03 00:05:08 - mmengine - INFO - Epoch(train) [983][50/63] lr: 4.6453e-04 eta: 2:28:57 time: 0.6146 data_time: 0.0188 memory: 14901 loss: 1.0301 loss_prob: 0.5368 loss_thr: 0.3987 loss_db: 0.0945 2022/11/03 00:05:11 - mmengine - INFO - Epoch(train) [983][55/63] lr: 4.6453e-04 eta: 2:28:57 time: 0.5390 data_time: 0.0289 memory: 14901 loss: 0.9577 loss_prob: 0.4905 loss_thr: 0.3827 loss_db: 0.0844 2022/11/03 00:05:14 - mmengine - INFO - Epoch(train) [983][60/63] lr: 4.6453e-04 eta: 2:28:50 time: 0.5800 data_time: 0.0180 memory: 14901 loss: 0.9108 loss_prob: 0.4608 loss_thr: 0.3681 loss_db: 0.0818 2022/11/03 00:05:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:05:22 - mmengine - INFO - Epoch(train) [984][5/63] lr: 4.6261e-04 eta: 2:28:50 time: 0.9950 data_time: 0.2429 memory: 14901 loss: 0.9092 loss_prob: 0.4637 loss_thr: 0.3639 loss_db: 0.0815 2022/11/03 00:05:26 - mmengine - INFO - Epoch(train) [984][10/63] lr: 4.6261e-04 eta: 2:28:42 time: 0.9907 data_time: 0.2527 memory: 14901 loss: 0.8945 loss_prob: 0.4574 loss_thr: 0.3570 loss_db: 0.0800 2022/11/03 00:05:29 - mmengine - INFO - Epoch(train) [984][15/63] lr: 4.6261e-04 eta: 2:28:42 time: 0.6641 data_time: 0.0173 memory: 14901 loss: 0.9370 loss_prob: 0.4844 loss_thr: 0.3686 loss_db: 0.0840 2022/11/03 00:05:32 - mmengine - INFO - Epoch(train) [984][20/63] lr: 4.6261e-04 eta: 2:28:36 time: 0.6147 data_time: 0.0082 memory: 14901 loss: 0.9160 loss_prob: 0.4697 loss_thr: 0.3646 loss_db: 0.0817 2022/11/03 00:05:34 - mmengine - INFO - Epoch(train) [984][25/63] lr: 4.6261e-04 eta: 2:28:36 time: 0.5352 data_time: 0.0092 memory: 14901 loss: 0.9309 loss_prob: 0.4776 loss_thr: 0.3699 loss_db: 0.0834 2022/11/03 00:05:37 - mmengine - INFO - Epoch(train) [984][30/63] lr: 4.6261e-04 eta: 2:28:29 time: 0.4872 data_time: 0.0364 memory: 14901 loss: 0.9589 loss_prob: 0.4930 loss_thr: 0.3799 loss_db: 0.0860 2022/11/03 00:05:39 - mmengine - INFO - Epoch(train) [984][35/63] lr: 4.6261e-04 eta: 2:28:29 time: 0.5070 data_time: 0.0370 memory: 14901 loss: 0.9490 loss_prob: 0.4884 loss_thr: 0.3746 loss_db: 0.0860 2022/11/03 00:05:42 - mmengine - INFO - Epoch(train) [984][40/63] lr: 4.6261e-04 eta: 2:28:22 time: 0.5202 data_time: 0.0065 memory: 14901 loss: 0.9176 loss_prob: 0.4743 loss_thr: 0.3585 loss_db: 0.0848 2022/11/03 00:05:44 - mmengine - INFO - Epoch(train) [984][45/63] lr: 4.6261e-04 eta: 2:28:22 time: 0.5122 data_time: 0.0041 memory: 14901 loss: 0.8389 loss_prob: 0.4322 loss_thr: 0.3300 loss_db: 0.0767 2022/11/03 00:05:47 - mmengine - INFO - Epoch(train) [984][50/63] lr: 4.6261e-04 eta: 2:28:15 time: 0.4715 data_time: 0.0103 memory: 14901 loss: 0.8602 loss_prob: 0.4395 loss_thr: 0.3427 loss_db: 0.0780 2022/11/03 00:05:49 - mmengine - INFO - Epoch(train) [984][55/63] lr: 4.6261e-04 eta: 2:28:15 time: 0.4758 data_time: 0.0204 memory: 14901 loss: 0.8739 loss_prob: 0.4483 loss_thr: 0.3475 loss_db: 0.0781 2022/11/03 00:05:52 - mmengine - INFO - Epoch(train) [984][60/63] lr: 4.6261e-04 eta: 2:28:08 time: 0.4943 data_time: 0.0156 memory: 14901 loss: 0.8678 loss_prob: 0.4504 loss_thr: 0.3401 loss_db: 0.0773 2022/11/03 00:05:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:05:58 - mmengine - INFO - Epoch(train) [985][5/63] lr: 4.6068e-04 eta: 2:28:08 time: 0.7561 data_time: 0.2152 memory: 14901 loss: 0.8968 loss_prob: 0.4603 loss_thr: 0.3572 loss_db: 0.0793 2022/11/03 00:06:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:06:01 - mmengine - INFO - Epoch(train) [985][10/63] lr: 4.6068e-04 eta: 2:27:59 time: 0.8084 data_time: 0.2162 memory: 14901 loss: 0.8677 loss_prob: 0.4462 loss_thr: 0.3421 loss_db: 0.0793 2022/11/03 00:06:04 - mmengine - INFO - Epoch(train) [985][15/63] lr: 4.6068e-04 eta: 2:27:59 time: 0.5968 data_time: 0.0074 memory: 14901 loss: 0.9087 loss_prob: 0.4714 loss_thr: 0.3549 loss_db: 0.0824 2022/11/03 00:06:07 - mmengine - INFO - Epoch(train) [985][20/63] lr: 4.6068e-04 eta: 2:27:53 time: 0.6357 data_time: 0.0086 memory: 14901 loss: 0.8744 loss_prob: 0.4447 loss_thr: 0.3515 loss_db: 0.0782 2022/11/03 00:06:11 - mmengine - INFO - Epoch(train) [985][25/63] lr: 4.6068e-04 eta: 2:27:53 time: 0.6917 data_time: 0.0176 memory: 14901 loss: 0.8907 loss_prob: 0.4558 loss_thr: 0.3546 loss_db: 0.0803 2022/11/03 00:06:15 - mmengine - INFO - Epoch(train) [985][30/63] lr: 4.6068e-04 eta: 2:27:47 time: 0.7694 data_time: 0.0423 memory: 14901 loss: 0.9293 loss_prob: 0.4828 loss_thr: 0.3630 loss_db: 0.0835 2022/11/03 00:06:20 - mmengine - INFO - Epoch(train) [985][35/63] lr: 4.6068e-04 eta: 2:27:47 time: 0.9265 data_time: 0.0324 memory: 14901 loss: 1.0229 loss_prob: 0.5355 loss_thr: 0.3949 loss_db: 0.0925 2022/11/03 00:06:24 - mmengine - INFO - Epoch(train) [985][40/63] lr: 4.6068e-04 eta: 2:27:41 time: 0.9038 data_time: 0.0059 memory: 14901 loss: 0.9476 loss_prob: 0.4881 loss_thr: 0.3741 loss_db: 0.0854 2022/11/03 00:06:27 - mmengine - INFO - Epoch(train) [985][45/63] lr: 4.6068e-04 eta: 2:27:41 time: 0.6973 data_time: 0.0081 memory: 14901 loss: 0.8503 loss_prob: 0.4351 loss_thr: 0.3384 loss_db: 0.0768 2022/11/03 00:06:30 - mmengine - INFO - Epoch(train) [985][50/63] lr: 4.6068e-04 eta: 2:27:34 time: 0.5882 data_time: 0.0131 memory: 14901 loss: 0.8735 loss_prob: 0.4498 loss_thr: 0.3468 loss_db: 0.0769 2022/11/03 00:06:32 - mmengine - INFO - Epoch(train) [985][55/63] lr: 4.6068e-04 eta: 2:27:34 time: 0.4993 data_time: 0.0220 memory: 14901 loss: 0.9034 loss_prob: 0.4684 loss_thr: 0.3525 loss_db: 0.0825 2022/11/03 00:06:35 - mmengine - INFO - Epoch(train) [985][60/63] lr: 4.6068e-04 eta: 2:27:27 time: 0.4656 data_time: 0.0163 memory: 14901 loss: 0.8893 loss_prob: 0.4666 loss_thr: 0.3383 loss_db: 0.0844 2022/11/03 00:06:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:06:41 - mmengine - INFO - Epoch(train) [986][5/63] lr: 4.5875e-04 eta: 2:27:27 time: 0.6986 data_time: 0.2287 memory: 14901 loss: 0.8315 loss_prob: 0.4317 loss_thr: 0.3260 loss_db: 0.0739 2022/11/03 00:06:43 - mmengine - INFO - Epoch(train) [986][10/63] lr: 4.5875e-04 eta: 2:27:18 time: 0.7007 data_time: 0.2304 memory: 14901 loss: 0.9852 loss_prob: 0.5391 loss_thr: 0.3609 loss_db: 0.0852 2022/11/03 00:06:45 - mmengine - INFO - Epoch(train) [986][15/63] lr: 4.5875e-04 eta: 2:27:18 time: 0.4861 data_time: 0.0064 memory: 14901 loss: 0.9724 loss_prob: 0.5232 loss_thr: 0.3649 loss_db: 0.0844 2022/11/03 00:06:48 - mmengine - INFO - Epoch(train) [986][20/63] lr: 4.5875e-04 eta: 2:27:11 time: 0.5159 data_time: 0.0049 memory: 14901 loss: 0.8330 loss_prob: 0.4174 loss_thr: 0.3411 loss_db: 0.0745 2022/11/03 00:06:50 - mmengine - INFO - Epoch(train) [986][25/63] lr: 4.5875e-04 eta: 2:27:11 time: 0.5022 data_time: 0.0112 memory: 14901 loss: 0.8652 loss_prob: 0.4423 loss_thr: 0.3456 loss_db: 0.0773 2022/11/03 00:06:54 - mmengine - INFO - Epoch(train) [986][30/63] lr: 4.5875e-04 eta: 2:27:05 time: 0.5610 data_time: 0.0387 memory: 14901 loss: 0.9076 loss_prob: 0.4738 loss_thr: 0.3524 loss_db: 0.0814 2022/11/03 00:06:56 - mmengine - INFO - Epoch(train) [986][35/63] lr: 4.5875e-04 eta: 2:27:05 time: 0.5467 data_time: 0.0335 memory: 14901 loss: 0.9417 loss_prob: 0.4911 loss_thr: 0.3662 loss_db: 0.0845 2022/11/03 00:06:58 - mmengine - INFO - Epoch(train) [986][40/63] lr: 4.5875e-04 eta: 2:26:58 time: 0.4777 data_time: 0.0056 memory: 14901 loss: 0.9871 loss_prob: 0.5192 loss_thr: 0.3795 loss_db: 0.0884 2022/11/03 00:07:06 - mmengine - INFO - Epoch(train) [986][45/63] lr: 4.5875e-04 eta: 2:26:58 time: 0.9900 data_time: 0.0071 memory: 14901 loss: 1.0629 loss_prob: 0.5602 loss_thr: 0.4079 loss_db: 0.0949 2022/11/03 00:07:13 - mmengine - INFO - Epoch(train) [986][50/63] lr: 4.5875e-04 eta: 2:26:53 time: 1.4908 data_time: 0.0446 memory: 14901 loss: 0.9878 loss_prob: 0.5114 loss_thr: 0.3879 loss_db: 0.0885 2022/11/03 00:07:20 - mmengine - INFO - Epoch(train) [986][55/63] lr: 4.5875e-04 eta: 2:26:53 time: 1.3710 data_time: 0.0482 memory: 14901 loss: 0.9050 loss_prob: 0.4672 loss_thr: 0.3565 loss_db: 0.0812 2022/11/03 00:07:25 - mmengine - INFO - Epoch(train) [986][60/63] lr: 4.5875e-04 eta: 2:26:48 time: 1.2042 data_time: 0.0126 memory: 14901 loss: 0.9301 loss_prob: 0.4774 loss_thr: 0.3690 loss_db: 0.0837 2022/11/03 00:07:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:07:35 - mmengine - INFO - Epoch(train) [987][5/63] lr: 4.5682e-04 eta: 2:26:48 time: 1.1553 data_time: 0.2428 memory: 14901 loss: 0.8930 loss_prob: 0.4665 loss_thr: 0.3451 loss_db: 0.0814 2022/11/03 00:07:39 - mmengine - INFO - Epoch(train) [987][10/63] lr: 4.5682e-04 eta: 2:26:40 time: 1.1126 data_time: 0.2387 memory: 14901 loss: 0.9218 loss_prob: 0.4846 loss_thr: 0.3515 loss_db: 0.0858 2022/11/03 00:07:42 - mmengine - INFO - Epoch(train) [987][15/63] lr: 4.5682e-04 eta: 2:26:40 time: 0.7038 data_time: 0.0094 memory: 14901 loss: 0.9062 loss_prob: 0.4750 loss_thr: 0.3452 loss_db: 0.0861 2022/11/03 00:07:44 - mmengine - INFO - Epoch(train) [987][20/63] lr: 4.5682e-04 eta: 2:26:33 time: 0.5186 data_time: 0.0089 memory: 14901 loss: 0.8873 loss_prob: 0.4676 loss_thr: 0.3370 loss_db: 0.0827 2022/11/03 00:07:48 - mmengine - INFO - Epoch(train) [987][25/63] lr: 4.5682e-04 eta: 2:26:33 time: 0.6437 data_time: 0.0092 memory: 14901 loss: 0.9202 loss_prob: 0.4830 loss_thr: 0.3548 loss_db: 0.0824 2022/11/03 00:07:53 - mmengine - INFO - Epoch(train) [987][30/63] lr: 4.5682e-04 eta: 2:26:27 time: 0.8408 data_time: 0.0618 memory: 14901 loss: 0.8516 loss_prob: 0.4333 loss_thr: 0.3453 loss_db: 0.0730 2022/11/03 00:07:56 - mmengine - INFO - Epoch(train) [987][35/63] lr: 4.5682e-04 eta: 2:26:27 time: 0.7917 data_time: 0.0606 memory: 14901 loss: 1.0579 loss_prob: 0.5848 loss_thr: 0.3796 loss_db: 0.0935 2022/11/03 00:08:00 - mmengine - INFO - Epoch(train) [987][40/63] lr: 4.5682e-04 eta: 2:26:20 time: 0.7415 data_time: 0.0071 memory: 14901 loss: 1.1933 loss_prob: 0.6833 loss_thr: 0.3969 loss_db: 0.1132 2022/11/03 00:08:05 - mmengine - INFO - Epoch(train) [987][45/63] lr: 4.5682e-04 eta: 2:26:20 time: 0.8350 data_time: 0.0057 memory: 14901 loss: 1.0105 loss_prob: 0.5345 loss_thr: 0.3817 loss_db: 0.0943 2022/11/03 00:08:09 - mmengine - INFO - Epoch(train) [987][50/63] lr: 4.5682e-04 eta: 2:26:14 time: 0.8945 data_time: 0.0144 memory: 14901 loss: 0.9810 loss_prob: 0.4998 loss_thr: 0.3964 loss_db: 0.0848 2022/11/03 00:08:12 - mmengine - INFO - Epoch(train) [987][55/63] lr: 4.5682e-04 eta: 2:26:14 time: 0.7101 data_time: 0.0252 memory: 14901 loss: 1.0578 loss_prob: 0.5637 loss_thr: 0.3999 loss_db: 0.0942 2022/11/03 00:08:16 - mmengine - INFO - Epoch(train) [987][60/63] lr: 4.5682e-04 eta: 2:26:08 time: 0.6639 data_time: 0.0179 memory: 14901 loss: 1.0919 loss_prob: 0.5913 loss_thr: 0.4014 loss_db: 0.0992 2022/11/03 00:08:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:08:26 - mmengine - INFO - Epoch(train) [988][5/63] lr: 4.5489e-04 eta: 2:26:08 time: 1.1970 data_time: 0.2484 memory: 14901 loss: 1.0010 loss_prob: 0.5231 loss_thr: 0.3872 loss_db: 0.0907 2022/11/03 00:08:29 - mmengine - INFO - Epoch(train) [988][10/63] lr: 4.5489e-04 eta: 2:26:00 time: 1.1281 data_time: 0.2475 memory: 14901 loss: 0.9259 loss_prob: 0.4769 loss_thr: 0.3646 loss_db: 0.0844 2022/11/03 00:08:33 - mmengine - INFO - Epoch(train) [988][15/63] lr: 4.5489e-04 eta: 2:26:00 time: 0.6683 data_time: 0.0080 memory: 14901 loss: 0.9183 loss_prob: 0.4781 loss_thr: 0.3569 loss_db: 0.0833 2022/11/03 00:08:36 - mmengine - INFO - Epoch(train) [988][20/63] lr: 4.5489e-04 eta: 2:25:54 time: 0.6666 data_time: 0.0072 memory: 14901 loss: 0.9180 loss_prob: 0.4906 loss_thr: 0.3428 loss_db: 0.0847 2022/11/03 00:08:39 - mmengine - INFO - Epoch(train) [988][25/63] lr: 4.5489e-04 eta: 2:25:54 time: 0.6221 data_time: 0.0228 memory: 14901 loss: 0.9472 loss_prob: 0.5044 loss_thr: 0.3549 loss_db: 0.0880 2022/11/03 00:08:44 - mmengine - INFO - Epoch(train) [988][30/63] lr: 4.5489e-04 eta: 2:25:47 time: 0.7747 data_time: 0.0470 memory: 14901 loss: 0.9515 loss_prob: 0.5021 loss_thr: 0.3631 loss_db: 0.0863 2022/11/03 00:08:48 - mmengine - INFO - Epoch(train) [988][35/63] lr: 4.5489e-04 eta: 2:25:47 time: 0.8939 data_time: 0.0323 memory: 14901 loss: 0.9328 loss_prob: 0.4943 loss_thr: 0.3546 loss_db: 0.0839 2022/11/03 00:08:51 - mmengine - INFO - Epoch(train) [988][40/63] lr: 4.5489e-04 eta: 2:25:41 time: 0.7540 data_time: 0.0089 memory: 14901 loss: 0.8614 loss_prob: 0.4476 loss_thr: 0.3364 loss_db: 0.0773 2022/11/03 00:08:55 - mmengine - INFO - Epoch(train) [988][45/63] lr: 4.5489e-04 eta: 2:25:41 time: 0.7705 data_time: 0.0063 memory: 14901 loss: 0.9435 loss_prob: 0.4981 loss_thr: 0.3576 loss_db: 0.0878 2022/11/03 00:08:59 - mmengine - INFO - Epoch(train) [988][50/63] lr: 4.5489e-04 eta: 2:25:35 time: 0.8016 data_time: 0.0179 memory: 14901 loss: 1.0245 loss_prob: 0.5472 loss_thr: 0.3823 loss_db: 0.0951 2022/11/03 00:09:03 - mmengine - INFO - Epoch(train) [988][55/63] lr: 4.5489e-04 eta: 2:25:35 time: 0.7096 data_time: 0.0310 memory: 14901 loss: 0.9972 loss_prob: 0.5215 loss_thr: 0.3862 loss_db: 0.0894 2022/11/03 00:09:06 - mmengine - INFO - Epoch(train) [988][60/63] lr: 4.5489e-04 eta: 2:25:28 time: 0.7088 data_time: 0.0204 memory: 14901 loss: 0.9699 loss_prob: 0.4985 loss_thr: 0.3837 loss_db: 0.0877 2022/11/03 00:09:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:09:15 - mmengine - INFO - Epoch(train) [989][5/63] lr: 4.5296e-04 eta: 2:25:28 time: 0.9640 data_time: 0.2981 memory: 14901 loss: 0.9546 loss_prob: 0.4878 loss_thr: 0.3815 loss_db: 0.0853 2022/11/03 00:09:18 - mmengine - INFO - Epoch(train) [989][10/63] lr: 4.5296e-04 eta: 2:25:20 time: 1.0495 data_time: 0.2971 memory: 14901 loss: 0.9593 loss_prob: 0.4904 loss_thr: 0.3850 loss_db: 0.0839 2022/11/03 00:09:22 - mmengine - INFO - Epoch(train) [989][15/63] lr: 4.5296e-04 eta: 2:25:20 time: 0.7594 data_time: 0.0058 memory: 14901 loss: 0.9687 loss_prob: 0.4934 loss_thr: 0.3887 loss_db: 0.0867 2022/11/03 00:09:26 - mmengine - INFO - Epoch(train) [989][20/63] lr: 4.5296e-04 eta: 2:25:14 time: 0.7498 data_time: 0.0057 memory: 14901 loss: 1.0220 loss_prob: 0.5402 loss_thr: 0.3881 loss_db: 0.0938 2022/11/03 00:09:29 - mmengine - INFO - Epoch(train) [989][25/63] lr: 4.5296e-04 eta: 2:25:14 time: 0.6386 data_time: 0.0253 memory: 14901 loss: 1.0386 loss_prob: 0.5547 loss_thr: 0.3878 loss_db: 0.0962 2022/11/03 00:09:33 - mmengine - INFO - Epoch(train) [989][30/63] lr: 4.5296e-04 eta: 2:25:08 time: 0.7408 data_time: 0.0458 memory: 14901 loss: 0.9275 loss_prob: 0.4815 loss_thr: 0.3612 loss_db: 0.0848 2022/11/03 00:09:36 - mmengine - INFO - Epoch(train) [989][35/63] lr: 4.5296e-04 eta: 2:25:08 time: 0.7072 data_time: 0.0261 memory: 14901 loss: 0.8153 loss_prob: 0.4149 loss_thr: 0.3267 loss_db: 0.0737 2022/11/03 00:09:40 - mmengine - INFO - Epoch(train) [989][40/63] lr: 4.5296e-04 eta: 2:25:01 time: 0.6752 data_time: 0.0055 memory: 14901 loss: 0.9636 loss_prob: 0.4951 loss_thr: 0.3820 loss_db: 0.0865 2022/11/03 00:09:44 - mmengine - INFO - Epoch(train) [989][45/63] lr: 4.5296e-04 eta: 2:25:01 time: 0.8609 data_time: 0.0057 memory: 14901 loss: 1.0504 loss_prob: 0.5497 loss_thr: 0.4080 loss_db: 0.0928 2022/11/03 00:09:48 - mmengine - INFO - Epoch(train) [989][50/63] lr: 4.5296e-04 eta: 2:24:55 time: 0.8426 data_time: 0.0250 memory: 14901 loss: 0.9933 loss_prob: 0.5267 loss_thr: 0.3769 loss_db: 0.0898 2022/11/03 00:09:52 - mmengine - INFO - Epoch(train) [989][55/63] lr: 4.5296e-04 eta: 2:24:55 time: 0.7368 data_time: 0.0315 memory: 14901 loss: 0.9863 loss_prob: 0.5171 loss_thr: 0.3785 loss_db: 0.0907 2022/11/03 00:09:55 - mmengine - INFO - Epoch(train) [989][60/63] lr: 4.5296e-04 eta: 2:24:49 time: 0.7070 data_time: 0.0119 memory: 14901 loss: 1.0241 loss_prob: 0.5305 loss_thr: 0.3989 loss_db: 0.0947 2022/11/03 00:09:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:10:05 - mmengine - INFO - Epoch(train) [990][5/63] lr: 4.5103e-04 eta: 2:24:49 time: 1.0671 data_time: 0.2654 memory: 14901 loss: 0.9169 loss_prob: 0.4639 loss_thr: 0.3727 loss_db: 0.0803 2022/11/03 00:10:09 - mmengine - INFO - Epoch(train) [990][10/63] lr: 4.5103e-04 eta: 2:24:41 time: 1.2069 data_time: 0.2675 memory: 14901 loss: 0.8658 loss_prob: 0.4315 loss_thr: 0.3607 loss_db: 0.0735 2022/11/03 00:10:12 - mmengine - INFO - Epoch(train) [990][15/63] lr: 4.5103e-04 eta: 2:24:41 time: 0.6935 data_time: 0.0124 memory: 14901 loss: 0.9315 loss_prob: 0.4773 loss_thr: 0.3708 loss_db: 0.0834 2022/11/03 00:10:15 - mmengine - INFO - Epoch(train) [990][20/63] lr: 4.5103e-04 eta: 2:24:34 time: 0.5921 data_time: 0.0103 memory: 14901 loss: 0.9359 loss_prob: 0.4869 loss_thr: 0.3644 loss_db: 0.0847 2022/11/03 00:10:19 - mmengine - INFO - Epoch(train) [990][25/63] lr: 4.5103e-04 eta: 2:24:34 time: 0.6913 data_time: 0.0331 memory: 14901 loss: 0.9636 loss_prob: 0.5044 loss_thr: 0.3728 loss_db: 0.0864 2022/11/03 00:10:22 - mmengine - INFO - Epoch(train) [990][30/63] lr: 4.5103e-04 eta: 2:24:28 time: 0.7415 data_time: 0.0334 memory: 14901 loss: 0.9988 loss_prob: 0.5247 loss_thr: 0.3833 loss_db: 0.0909 2022/11/03 00:10:28 - mmengine - INFO - Epoch(train) [990][35/63] lr: 4.5103e-04 eta: 2:24:28 time: 0.9124 data_time: 0.0123 memory: 14901 loss: 0.9366 loss_prob: 0.4878 loss_thr: 0.3643 loss_db: 0.0844 2022/11/03 00:10:32 - mmengine - INFO - Epoch(train) [990][40/63] lr: 4.5103e-04 eta: 2:24:22 time: 0.9891 data_time: 0.0128 memory: 14901 loss: 0.8734 loss_prob: 0.4463 loss_thr: 0.3486 loss_db: 0.0786 2022/11/03 00:10:36 - mmengine - INFO - Epoch(train) [990][45/63] lr: 4.5103e-04 eta: 2:24:22 time: 0.8150 data_time: 0.0065 memory: 14901 loss: 0.8982 loss_prob: 0.4647 loss_thr: 0.3515 loss_db: 0.0820 2022/11/03 00:10:39 - mmengine - INFO - Epoch(train) [990][50/63] lr: 4.5103e-04 eta: 2:24:16 time: 0.6999 data_time: 0.0241 memory: 14901 loss: 0.9270 loss_prob: 0.4897 loss_thr: 0.3524 loss_db: 0.0850 2022/11/03 00:10:42 - mmengine - INFO - Epoch(train) [990][55/63] lr: 4.5103e-04 eta: 2:24:16 time: 0.5726 data_time: 0.0241 memory: 14901 loss: 0.9186 loss_prob: 0.4798 loss_thr: 0.3553 loss_db: 0.0834 2022/11/03 00:10:45 - mmengine - INFO - Epoch(train) [990][60/63] lr: 4.5103e-04 eta: 2:24:09 time: 0.5796 data_time: 0.0090 memory: 14901 loss: 0.9251 loss_prob: 0.4781 loss_thr: 0.3637 loss_db: 0.0833 2022/11/03 00:10:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:10:54 - mmengine - INFO - Epoch(train) [991][5/63] lr: 4.4910e-04 eta: 2:24:09 time: 0.9820 data_time: 0.2350 memory: 14901 loss: 0.8808 loss_prob: 0.4555 loss_thr: 0.3467 loss_db: 0.0786 2022/11/03 00:10:59 - mmengine - INFO - Epoch(train) [991][10/63] lr: 4.4910e-04 eta: 2:24:01 time: 1.2442 data_time: 0.2343 memory: 14901 loss: 0.8366 loss_prob: 0.4238 loss_thr: 0.3381 loss_db: 0.0748 2022/11/03 00:11:03 - mmengine - INFO - Epoch(train) [991][15/63] lr: 4.4910e-04 eta: 2:24:01 time: 0.9085 data_time: 0.0078 memory: 14901 loss: 0.9324 loss_prob: 0.4776 loss_thr: 0.3732 loss_db: 0.0816 2022/11/03 00:11:06 - mmengine - INFO - Epoch(train) [991][20/63] lr: 4.4910e-04 eta: 2:23:55 time: 0.7037 data_time: 0.0096 memory: 14901 loss: 0.9674 loss_prob: 0.5036 loss_thr: 0.3779 loss_db: 0.0859 2022/11/03 00:11:08 - mmengine - INFO - Epoch(train) [991][25/63] lr: 4.4910e-04 eta: 2:23:55 time: 0.5596 data_time: 0.0177 memory: 14901 loss: 0.9606 loss_prob: 0.4979 loss_thr: 0.3750 loss_db: 0.0877 2022/11/03 00:11:12 - mmengine - INFO - Epoch(train) [991][30/63] lr: 4.4910e-04 eta: 2:23:48 time: 0.6073 data_time: 0.0380 memory: 14901 loss: 0.9062 loss_prob: 0.4699 loss_thr: 0.3535 loss_db: 0.0828 2022/11/03 00:11:15 - mmengine - INFO - Epoch(train) [991][35/63] lr: 4.4910e-04 eta: 2:23:48 time: 0.6927 data_time: 0.0311 memory: 14901 loss: 0.8565 loss_prob: 0.4449 loss_thr: 0.3331 loss_db: 0.0784 2022/11/03 00:11:18 - mmengine - INFO - Epoch(train) [991][40/63] lr: 4.4910e-04 eta: 2:23:41 time: 0.5955 data_time: 0.0074 memory: 14901 loss: 0.9559 loss_prob: 0.5017 loss_thr: 0.3661 loss_db: 0.0881 2022/11/03 00:11:20 - mmengine - INFO - Epoch(train) [991][45/63] lr: 4.4910e-04 eta: 2:23:41 time: 0.5203 data_time: 0.0096 memory: 14901 loss: 1.0097 loss_prob: 0.5239 loss_thr: 0.3945 loss_db: 0.0914 2022/11/03 00:11:23 - mmengine - INFO - Epoch(train) [991][50/63] lr: 4.4910e-04 eta: 2:23:35 time: 0.5719 data_time: 0.0199 memory: 14901 loss: 0.9157 loss_prob: 0.4642 loss_thr: 0.3714 loss_db: 0.0801 2022/11/03 00:11:26 - mmengine - INFO - Epoch(train) [991][55/63] lr: 4.4910e-04 eta: 2:23:35 time: 0.6096 data_time: 0.0238 memory: 14901 loss: 0.7990 loss_prob: 0.4062 loss_thr: 0.3230 loss_db: 0.0698 2022/11/03 00:11:30 - mmengine - INFO - Epoch(train) [991][60/63] lr: 4.4910e-04 eta: 2:23:28 time: 0.6469 data_time: 0.0140 memory: 14901 loss: 0.8424 loss_prob: 0.4331 loss_thr: 0.3326 loss_db: 0.0766 2022/11/03 00:11:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:11:40 - mmengine - INFO - Epoch(train) [992][5/63] lr: 4.4716e-04 eta: 2:23:28 time: 1.1682 data_time: 0.2181 memory: 14901 loss: 0.9282 loss_prob: 0.4766 loss_thr: 0.3682 loss_db: 0.0835 2022/11/03 00:11:44 - mmengine - INFO - Epoch(train) [992][10/63] lr: 4.4716e-04 eta: 2:23:20 time: 1.1946 data_time: 0.2280 memory: 14901 loss: 0.9223 loss_prob: 0.4732 loss_thr: 0.3657 loss_db: 0.0834 2022/11/03 00:11:48 - mmengine - INFO - Epoch(train) [992][15/63] lr: 4.4716e-04 eta: 2:23:20 time: 0.7809 data_time: 0.0166 memory: 14901 loss: 1.0673 loss_prob: 0.5947 loss_thr: 0.3766 loss_db: 0.0960 2022/11/03 00:11:50 - mmengine - INFO - Epoch(train) [992][20/63] lr: 4.4716e-04 eta: 2:23:14 time: 0.6598 data_time: 0.0065 memory: 14901 loss: 1.0325 loss_prob: 0.5737 loss_thr: 0.3661 loss_db: 0.0927 2022/11/03 00:11:54 - mmengine - INFO - Epoch(train) [992][25/63] lr: 4.4716e-04 eta: 2:23:14 time: 0.5898 data_time: 0.0117 memory: 14901 loss: 0.9875 loss_prob: 0.5258 loss_thr: 0.3718 loss_db: 0.0899 2022/11/03 00:11:56 - mmengine - INFO - Epoch(train) [992][30/63] lr: 4.4716e-04 eta: 2:23:07 time: 0.5956 data_time: 0.0343 memory: 14901 loss: 0.9944 loss_prob: 0.5340 loss_thr: 0.3700 loss_db: 0.0905 2022/11/03 00:12:00 - mmengine - INFO - Epoch(train) [992][35/63] lr: 4.4716e-04 eta: 2:23:07 time: 0.6283 data_time: 0.0383 memory: 14901 loss: 0.9049 loss_prob: 0.4721 loss_thr: 0.3505 loss_db: 0.0822 2022/11/03 00:12:04 - mmengine - INFO - Epoch(train) [992][40/63] lr: 4.4716e-04 eta: 2:23:01 time: 0.7956 data_time: 0.0163 memory: 14901 loss: 0.9356 loss_prob: 0.4884 loss_thr: 0.3629 loss_db: 0.0843 2022/11/03 00:12:09 - mmengine - INFO - Epoch(train) [992][45/63] lr: 4.4716e-04 eta: 2:23:01 time: 0.9379 data_time: 0.0066 memory: 14901 loss: 0.8778 loss_prob: 0.4595 loss_thr: 0.3383 loss_db: 0.0800 2022/11/03 00:12:12 - mmengine - INFO - Epoch(train) [992][50/63] lr: 4.4716e-04 eta: 2:22:55 time: 0.7677 data_time: 0.0111 memory: 14901 loss: 0.8325 loss_prob: 0.4333 loss_thr: 0.3232 loss_db: 0.0759 2022/11/03 00:12:15 - mmengine - INFO - Epoch(train) [992][55/63] lr: 4.4716e-04 eta: 2:22:55 time: 0.6092 data_time: 0.0237 memory: 14901 loss: 0.8703 loss_prob: 0.4528 loss_thr: 0.3390 loss_db: 0.0785 2022/11/03 00:12:18 - mmengine - INFO - Epoch(train) [992][60/63] lr: 4.4716e-04 eta: 2:22:48 time: 0.6179 data_time: 0.0253 memory: 14901 loss: 0.8757 loss_prob: 0.4493 loss_thr: 0.3474 loss_db: 0.0790 2022/11/03 00:12:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:12:26 - mmengine - INFO - Epoch(train) [993][5/63] lr: 4.4523e-04 eta: 2:22:48 time: 0.8729 data_time: 0.2700 memory: 14901 loss: 0.9240 loss_prob: 0.4901 loss_thr: 0.3487 loss_db: 0.0852 2022/11/03 00:12:29 - mmengine - INFO - Epoch(train) [993][10/63] lr: 4.4523e-04 eta: 2:22:40 time: 0.9533 data_time: 0.2706 memory: 14901 loss: 0.9496 loss_prob: 0.4990 loss_thr: 0.3634 loss_db: 0.0872 2022/11/03 00:12:34 - mmengine - INFO - Epoch(train) [993][15/63] lr: 4.4523e-04 eta: 2:22:40 time: 0.7814 data_time: 0.0069 memory: 14901 loss: 0.9016 loss_prob: 0.4658 loss_thr: 0.3551 loss_db: 0.0807 2022/11/03 00:12:37 - mmengine - INFO - Epoch(train) [993][20/63] lr: 4.4523e-04 eta: 2:22:34 time: 0.7722 data_time: 0.0071 memory: 14901 loss: 0.8870 loss_prob: 0.4571 loss_thr: 0.3513 loss_db: 0.0785 2022/11/03 00:12:40 - mmengine - INFO - Epoch(train) [993][25/63] lr: 4.4523e-04 eta: 2:22:34 time: 0.6571 data_time: 0.0519 memory: 14901 loss: 0.8765 loss_prob: 0.4492 loss_thr: 0.3495 loss_db: 0.0778 2022/11/03 00:12:46 - mmengine - INFO - Epoch(train) [993][30/63] lr: 4.4523e-04 eta: 2:22:27 time: 0.8502 data_time: 0.0535 memory: 14901 loss: 0.9362 loss_prob: 0.4871 loss_thr: 0.3647 loss_db: 0.0844 2022/11/03 00:12:49 - mmengine - INFO - Epoch(train) [993][35/63] lr: 4.4523e-04 eta: 2:22:27 time: 0.8214 data_time: 0.0091 memory: 14901 loss: 0.9793 loss_prob: 0.5118 loss_thr: 0.3794 loss_db: 0.0882 2022/11/03 00:12:53 - mmengine - INFO - Epoch(train) [993][40/63] lr: 4.4523e-04 eta: 2:22:21 time: 0.7755 data_time: 0.0107 memory: 14901 loss: 0.9231 loss_prob: 0.4744 loss_thr: 0.3656 loss_db: 0.0830 2022/11/03 00:12:56 - mmengine - INFO - Epoch(train) [993][45/63] lr: 4.4523e-04 eta: 2:22:21 time: 0.7506 data_time: 0.0098 memory: 14901 loss: 0.8792 loss_prob: 0.4405 loss_thr: 0.3602 loss_db: 0.0784 2022/11/03 00:12:59 - mmengine - INFO - Epoch(train) [993][50/63] lr: 4.4523e-04 eta: 2:22:14 time: 0.5872 data_time: 0.0273 memory: 14901 loss: 0.8764 loss_prob: 0.4435 loss_thr: 0.3551 loss_db: 0.0778 2022/11/03 00:13:03 - mmengine - INFO - Epoch(train) [993][55/63] lr: 4.4523e-04 eta: 2:22:14 time: 0.6529 data_time: 0.0278 memory: 14901 loss: 0.8050 loss_prob: 0.4087 loss_thr: 0.3254 loss_db: 0.0710 2022/11/03 00:13:05 - mmengine - INFO - Epoch(train) [993][60/63] lr: 4.4523e-04 eta: 2:22:08 time: 0.6054 data_time: 0.0075 memory: 14901 loss: 0.8688 loss_prob: 0.4467 loss_thr: 0.3446 loss_db: 0.0775 2022/11/03 00:13:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:13:14 - mmengine - INFO - Epoch(train) [994][5/63] lr: 4.4329e-04 eta: 2:22:08 time: 0.9753 data_time: 0.2388 memory: 14901 loss: 0.8862 loss_prob: 0.4565 loss_thr: 0.3514 loss_db: 0.0783 2022/11/03 00:13:17 - mmengine - INFO - Epoch(train) [994][10/63] lr: 4.4329e-04 eta: 2:22:00 time: 1.0255 data_time: 0.2387 memory: 14901 loss: 0.9007 loss_prob: 0.4650 loss_thr: 0.3550 loss_db: 0.0807 2022/11/03 00:13:22 - mmengine - INFO - Epoch(train) [994][15/63] lr: 4.4329e-04 eta: 2:22:00 time: 0.8155 data_time: 0.0065 memory: 14901 loss: 0.8759 loss_prob: 0.4475 loss_thr: 0.3490 loss_db: 0.0794 2022/11/03 00:13:26 - mmengine - INFO - Epoch(train) [994][20/63] lr: 4.4329e-04 eta: 2:21:54 time: 0.8555 data_time: 0.0055 memory: 14901 loss: 0.8253 loss_prob: 0.4197 loss_thr: 0.3310 loss_db: 0.0745 2022/11/03 00:13:30 - mmengine - INFO - Epoch(train) [994][25/63] lr: 4.4329e-04 eta: 2:21:54 time: 0.7649 data_time: 0.0178 memory: 14901 loss: 0.8556 loss_prob: 0.4418 loss_thr: 0.3364 loss_db: 0.0774 2022/11/03 00:13:33 - mmengine - INFO - Epoch(train) [994][30/63] lr: 4.4329e-04 eta: 2:21:47 time: 0.6892 data_time: 0.0465 memory: 14901 loss: 0.8276 loss_prob: 0.4226 loss_thr: 0.3309 loss_db: 0.0741 2022/11/03 00:13:35 - mmengine - INFO - Epoch(train) [994][35/63] lr: 4.4329e-04 eta: 2:21:47 time: 0.5761 data_time: 0.0342 memory: 14901 loss: 0.8084 loss_prob: 0.4127 loss_thr: 0.3233 loss_db: 0.0724 2022/11/03 00:13:40 - mmengine - INFO - Epoch(train) [994][40/63] lr: 4.4329e-04 eta: 2:21:41 time: 0.7009 data_time: 0.0067 memory: 14901 loss: 0.8673 loss_prob: 0.4481 loss_thr: 0.3420 loss_db: 0.0772 2022/11/03 00:13:44 - mmengine - INFO - Epoch(train) [994][45/63] lr: 4.4329e-04 eta: 2:21:41 time: 0.8866 data_time: 0.0071 memory: 14901 loss: 0.9547 loss_prob: 0.5025 loss_thr: 0.3665 loss_db: 0.0856 2022/11/03 00:13:47 - mmengine - INFO - Epoch(train) [994][50/63] lr: 4.4329e-04 eta: 2:21:34 time: 0.7660 data_time: 0.0117 memory: 14901 loss: 0.9613 loss_prob: 0.5065 loss_thr: 0.3673 loss_db: 0.0875 2022/11/03 00:13:50 - mmengine - INFO - Epoch(train) [994][55/63] lr: 4.4329e-04 eta: 2:21:34 time: 0.5826 data_time: 0.0249 memory: 14901 loss: 0.8711 loss_prob: 0.4473 loss_thr: 0.3447 loss_db: 0.0791 2022/11/03 00:13:53 - mmengine - INFO - Epoch(train) [994][60/63] lr: 4.4329e-04 eta: 2:21:28 time: 0.5895 data_time: 0.0192 memory: 14901 loss: 0.9317 loss_prob: 0.4853 loss_thr: 0.3621 loss_db: 0.0844 2022/11/03 00:13:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:14:02 - mmengine - INFO - Epoch(train) [995][5/63] lr: 4.4135e-04 eta: 2:21:28 time: 0.9470 data_time: 0.2761 memory: 14901 loss: 0.9352 loss_prob: 0.4926 loss_thr: 0.3566 loss_db: 0.0860 2022/11/03 00:14:06 - mmengine - INFO - Epoch(train) [995][10/63] lr: 4.4135e-04 eta: 2:21:20 time: 1.1056 data_time: 0.2767 memory: 14901 loss: 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memory: 14901 loss: 0.9880 loss_prob: 0.5154 loss_thr: 0.3841 loss_db: 0.0885 2022/11/03 00:14:27 - mmengine - INFO - Epoch(train) [995][40/63] lr: 4.4135e-04 eta: 2:21:00 time: 0.8069 data_time: 0.0063 memory: 14901 loss: 0.8992 loss_prob: 0.4674 loss_thr: 0.3519 loss_db: 0.0799 2022/11/03 00:14:31 - mmengine - INFO - Epoch(train) [995][45/63] lr: 4.4135e-04 eta: 2:21:00 time: 0.9075 data_time: 0.0069 memory: 14901 loss: 0.8583 loss_prob: 0.4440 loss_thr: 0.3368 loss_db: 0.0775 2022/11/03 00:14:35 - mmengine - INFO - Epoch(train) [995][50/63] lr: 4.4135e-04 eta: 2:20:54 time: 0.7837 data_time: 0.0175 memory: 14901 loss: 0.8688 loss_prob: 0.4442 loss_thr: 0.3459 loss_db: 0.0787 2022/11/03 00:14:38 - mmengine - INFO - Epoch(train) [995][55/63] lr: 4.4135e-04 eta: 2:20:54 time: 0.7038 data_time: 0.0280 memory: 14901 loss: 0.9013 loss_prob: 0.4650 loss_thr: 0.3543 loss_db: 0.0821 2022/11/03 00:14:41 - mmengine - INFO - Epoch(train) [995][60/63] lr: 4.4135e-04 eta: 2:20:48 time: 0.6154 data_time: 0.0171 memory: 14901 loss: 0.9015 loss_prob: 0.4719 loss_thr: 0.3474 loss_db: 0.0822 2022/11/03 00:14:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:14:48 - mmengine - INFO - Epoch(train) [996][5/63] lr: 4.3942e-04 eta: 2:20:48 time: 0.8235 data_time: 0.2878 memory: 14901 loss: 0.8908 loss_prob: 0.4701 loss_thr: 0.3397 loss_db: 0.0810 2022/11/03 00:14:52 - mmengine - INFO - Epoch(train) [996][10/63] lr: 4.3942e-04 eta: 2:20:39 time: 0.9682 data_time: 0.2878 memory: 14901 loss: 0.9318 loss_prob: 0.4834 loss_thr: 0.3643 loss_db: 0.0842 2022/11/03 00:14:56 - mmengine - INFO - Epoch(train) [996][15/63] lr: 4.3942e-04 eta: 2:20:39 time: 0.7562 data_time: 0.0086 memory: 14901 loss: 0.9478 loss_prob: 0.4821 loss_thr: 0.3812 loss_db: 0.0844 2022/11/03 00:14:58 - mmengine - INFO - Epoch(train) [996][20/63] lr: 4.3942e-04 eta: 2:20:33 time: 0.6727 data_time: 0.0085 memory: 14901 loss: 0.9015 loss_prob: 0.4573 loss_thr: 0.3645 loss_db: 0.0797 2022/11/03 00:15:02 - mmengine - INFO - Epoch(train) [996][25/63] lr: 4.3942e-04 eta: 2:20:33 time: 0.6060 data_time: 0.0222 memory: 14901 loss: 0.8793 loss_prob: 0.4500 loss_thr: 0.3515 loss_db: 0.0778 2022/11/03 00:15:05 - mmengine - INFO - Epoch(train) [996][30/63] lr: 4.3942e-04 eta: 2:20:26 time: 0.6148 data_time: 0.0415 memory: 14901 loss: 0.8789 loss_prob: 0.4547 loss_thr: 0.3446 loss_db: 0.0796 2022/11/03 00:15:07 - mmengine - INFO - Epoch(train) [996][35/63] lr: 4.3942e-04 eta: 2:20:26 time: 0.5360 data_time: 0.0252 memory: 14901 loss: 0.8860 loss_prob: 0.4599 loss_thr: 0.3447 loss_db: 0.0813 2022/11/03 00:15:10 - mmengine - INFO - Epoch(train) [996][40/63] lr: 4.3942e-04 eta: 2:20:19 time: 0.5694 data_time: 0.0065 memory: 14901 loss: 0.9214 loss_prob: 0.4838 loss_thr: 0.3540 loss_db: 0.0836 2022/11/03 00:15:15 - mmengine - INFO - Epoch(train) [996][45/63] lr: 4.3942e-04 eta: 2:20:19 time: 0.7607 data_time: 0.0065 memory: 14901 loss: 0.8624 loss_prob: 0.4498 loss_thr: 0.3341 loss_db: 0.0785 2022/11/03 00:15:18 - mmengine - INFO - Epoch(train) [996][50/63] lr: 4.3942e-04 eta: 2:20:13 time: 0.8240 data_time: 0.0259 memory: 14901 loss: 0.8455 loss_prob: 0.4371 loss_thr: 0.3318 loss_db: 0.0765 2022/11/03 00:15:21 - mmengine - INFO - Epoch(train) [996][55/63] lr: 4.3942e-04 eta: 2:20:13 time: 0.6422 data_time: 0.0272 memory: 14901 loss: 0.8618 loss_prob: 0.4511 loss_thr: 0.3349 loss_db: 0.0759 2022/11/03 00:15:24 - mmengine - INFO - Epoch(train) [996][60/63] lr: 4.3942e-04 eta: 2:20:07 time: 0.5919 data_time: 0.0073 memory: 14901 loss: 0.8545 loss_prob: 0.4420 loss_thr: 0.3359 loss_db: 0.0766 2022/11/03 00:15:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:15:33 - mmengine - INFO - Epoch(train) [997][5/63] lr: 4.3748e-04 eta: 2:20:07 time: 1.0289 data_time: 0.2350 memory: 14901 loss: 0.9008 loss_prob: 0.4679 loss_thr: 0.3503 loss_db: 0.0826 2022/11/03 00:15:37 - mmengine - INFO - Epoch(train) [997][10/63] lr: 4.3748e-04 eta: 2:19:58 time: 1.0637 data_time: 0.2410 memory: 14901 loss: 0.8775 loss_prob: 0.4553 loss_thr: 0.3443 loss_db: 0.0779 2022/11/03 00:15:41 - mmengine - INFO - Epoch(train) [997][15/63] lr: 4.3748e-04 eta: 2:19:58 time: 0.8029 data_time: 0.0126 memory: 14901 loss: 0.8699 loss_prob: 0.4490 loss_thr: 0.3439 loss_db: 0.0770 2022/11/03 00:15:44 - mmengine - INFO - Epoch(train) [997][20/63] lr: 4.3748e-04 eta: 2:19:52 time: 0.6836 data_time: 0.0063 memory: 14901 loss: 0.9663 loss_prob: 0.4942 loss_thr: 0.3844 loss_db: 0.0878 2022/11/03 00:15:46 - mmengine - INFO - Epoch(train) [997][25/63] lr: 4.3748e-04 eta: 2:19:52 time: 0.5154 data_time: 0.0207 memory: 14901 loss: 1.0196 loss_prob: 0.5250 loss_thr: 0.4017 loss_db: 0.0929 2022/11/03 00:15:49 - mmengine - INFO - Epoch(train) [997][30/63] lr: 4.3748e-04 eta: 2:19:45 time: 0.5528 data_time: 0.0396 memory: 14901 loss: 1.0423 loss_prob: 0.5546 loss_thr: 0.3961 loss_db: 0.0916 2022/11/03 00:15:53 - mmengine - INFO - Epoch(train) [997][35/63] lr: 4.3748e-04 eta: 2:19:45 time: 0.6166 data_time: 0.0242 memory: 14901 loss: 1.0116 loss_prob: 0.5392 loss_thr: 0.3837 loss_db: 0.0887 2022/11/03 00:15:55 - mmengine - INFO - Epoch(train) [997][40/63] lr: 4.3748e-04 eta: 2:19:39 time: 0.6076 data_time: 0.0054 memory: 14901 loss: 0.9063 loss_prob: 0.4670 loss_thr: 0.3565 loss_db: 0.0828 2022/11/03 00:15:58 - mmengine - INFO - Epoch(train) [997][45/63] lr: 4.3748e-04 eta: 2:19:39 time: 0.5939 data_time: 0.0071 memory: 14901 loss: 0.9143 loss_prob: 0.4728 loss_thr: 0.3579 loss_db: 0.0836 2022/11/03 00:16:02 - mmengine - INFO - Epoch(train) [997][50/63] lr: 4.3748e-04 eta: 2:19:32 time: 0.7115 data_time: 0.0229 memory: 14901 loss: 0.9193 loss_prob: 0.4792 loss_thr: 0.3563 loss_db: 0.0838 2022/11/03 00:16:07 - mmengine - INFO - Epoch(train) [997][55/63] lr: 4.3748e-04 eta: 2:19:32 time: 0.8407 data_time: 0.0454 memory: 14901 loss: 0.8725 loss_prob: 0.4514 loss_thr: 0.3420 loss_db: 0.0791 2022/11/03 00:16:10 - mmengine - INFO - Epoch(train) [997][60/63] lr: 4.3748e-04 eta: 2:19:26 time: 0.7528 data_time: 0.0296 memory: 14901 loss: 0.8637 loss_prob: 0.4411 loss_thr: 0.3458 loss_db: 0.0768 2022/11/03 00:16:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:16:19 - mmengine - INFO - Epoch(train) [998][5/63] lr: 4.3554e-04 eta: 2:19:26 time: 1.0442 data_time: 0.2856 memory: 14901 loss: 0.8896 loss_prob: 0.4585 loss_thr: 0.3516 loss_db: 0.0795 2022/11/03 00:16:23 - mmengine - INFO - Epoch(train) [998][10/63] lr: 4.3554e-04 eta: 2:19:18 time: 1.1180 data_time: 0.2847 memory: 14901 loss: 0.9049 loss_prob: 0.4637 loss_thr: 0.3605 loss_db: 0.0807 2022/11/03 00:16:28 - mmengine - INFO - Epoch(train) [998][15/63] lr: 4.3554e-04 eta: 2:19:18 time: 0.9456 data_time: 0.0062 memory: 14901 loss: 0.9603 loss_prob: 0.5060 loss_thr: 0.3674 loss_db: 0.0869 2022/11/03 00:16:33 - mmengine - INFO - Epoch(train) [998][20/63] lr: 4.3554e-04 eta: 2:19:12 time: 1.0209 data_time: 0.0064 memory: 14901 loss: 0.9610 loss_prob: 0.5095 loss_thr: 0.3636 loss_db: 0.0879 2022/11/03 00:16:37 - mmengine - INFO - Epoch(train) [998][25/63] lr: 4.3554e-04 eta: 2:19:12 time: 0.8745 data_time: 0.0355 memory: 14901 loss: 0.9088 loss_prob: 0.4731 loss_thr: 0.3532 loss_db: 0.0825 2022/11/03 00:16:40 - mmengine - INFO - Epoch(train) [998][30/63] lr: 4.3554e-04 eta: 2:19:06 time: 0.6439 data_time: 0.0380 memory: 14901 loss: 0.9140 loss_prob: 0.4761 loss_thr: 0.3557 loss_db: 0.0822 2022/11/03 00:16:42 - mmengine - INFO - Epoch(train) [998][35/63] lr: 4.3554e-04 eta: 2:19:06 time: 0.5130 data_time: 0.0081 memory: 14901 loss: 0.9456 loss_prob: 0.4893 loss_thr: 0.3710 loss_db: 0.0853 2022/11/03 00:16:46 - mmengine - INFO - Epoch(train) [998][40/63] lr: 4.3554e-04 eta: 2:18:59 time: 0.6142 data_time: 0.0056 memory: 14901 loss: 0.9787 loss_prob: 0.5091 loss_thr: 0.3801 loss_db: 0.0896 2022/11/03 00:16:49 - mmengine - INFO - Epoch(train) [998][45/63] lr: 4.3554e-04 eta: 2:18:59 time: 0.6857 data_time: 0.0060 memory: 14901 loss: 0.9333 loss_prob: 0.4884 loss_thr: 0.3592 loss_db: 0.0857 2022/11/03 00:16:52 - mmengine - INFO - Epoch(train) [998][50/63] lr: 4.3554e-04 eta: 2:18:52 time: 0.6067 data_time: 0.0251 memory: 14901 loss: 0.9269 loss_prob: 0.4854 loss_thr: 0.3554 loss_db: 0.0861 2022/11/03 00:16:55 - mmengine - INFO - Epoch(train) [998][55/63] lr: 4.3554e-04 eta: 2:18:52 time: 0.5590 data_time: 0.0274 memory: 14901 loss: 0.9759 loss_prob: 0.5136 loss_thr: 0.3724 loss_db: 0.0900 2022/11/03 00:16:58 - mmengine - INFO - Epoch(train) [998][60/63] lr: 4.3554e-04 eta: 2:18:46 time: 0.5613 data_time: 0.0090 memory: 14901 loss: 0.9198 loss_prob: 0.4774 loss_thr: 0.3609 loss_db: 0.0815 2022/11/03 00:16:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:17:05 - mmengine - INFO - Epoch(train) [999][5/63] lr: 4.3360e-04 eta: 2:18:46 time: 0.8880 data_time: 0.2682 memory: 14901 loss: 0.9480 loss_prob: 0.4980 loss_thr: 0.3644 loss_db: 0.0856 2022/11/03 00:17:08 - mmengine - INFO - Epoch(train) [999][10/63] lr: 4.3360e-04 eta: 2:18:37 time: 0.9198 data_time: 0.2718 memory: 14901 loss: 0.9979 loss_prob: 0.5308 loss_thr: 0.3754 loss_db: 0.0917 2022/11/03 00:17:11 - mmengine - INFO - Epoch(train) [999][15/63] lr: 4.3360e-04 eta: 2:18:37 time: 0.5650 data_time: 0.0094 memory: 14901 loss: 0.9487 loss_prob: 0.4966 loss_thr: 0.3661 loss_db: 0.0860 2022/11/03 00:17:14 - mmengine - INFO - Epoch(train) [999][20/63] lr: 4.3360e-04 eta: 2:18:30 time: 0.5755 data_time: 0.0065 memory: 14901 loss: 0.9119 loss_prob: 0.4699 loss_thr: 0.3612 loss_db: 0.0808 2022/11/03 00:17:17 - mmengine - INFO - Epoch(train) [999][25/63] lr: 4.3360e-04 eta: 2:18:30 time: 0.6032 data_time: 0.0239 memory: 14901 loss: 0.9225 loss_prob: 0.4779 loss_thr: 0.3620 loss_db: 0.0826 2022/11/03 00:17:21 - mmengine - INFO - Epoch(train) [999][30/63] lr: 4.3360e-04 eta: 2:18:24 time: 0.7523 data_time: 0.0471 memory: 14901 loss: 0.9375 loss_prob: 0.4913 loss_thr: 0.3605 loss_db: 0.0857 2022/11/03 00:17:26 - mmengine - INFO - Epoch(train) [999][35/63] lr: 4.3360e-04 eta: 2:18:24 time: 0.9193 data_time: 0.0328 memory: 14901 loss: 1.0064 loss_prob: 0.5391 loss_thr: 0.3755 loss_db: 0.0918 2022/11/03 00:17:30 - mmengine - INFO - Epoch(train) [999][40/63] lr: 4.3360e-04 eta: 2:18:18 time: 0.8668 data_time: 0.0093 memory: 14901 loss: 0.9468 loss_prob: 0.5062 loss_thr: 0.3544 loss_db: 0.0862 2022/11/03 00:17:33 - mmengine - INFO - Epoch(train) [999][45/63] lr: 4.3360e-04 eta: 2:18:18 time: 0.6652 data_time: 0.0065 memory: 14901 loss: 0.8169 loss_prob: 0.4162 loss_thr: 0.3277 loss_db: 0.0730 2022/11/03 00:17:36 - mmengine - INFO - Epoch(train) [999][50/63] lr: 4.3360e-04 eta: 2:18:11 time: 0.6155 data_time: 0.0213 memory: 14901 loss: 0.8007 loss_prob: 0.4021 loss_thr: 0.3270 loss_db: 0.0716 2022/11/03 00:17:40 - mmengine - INFO - Epoch(train) [999][55/63] lr: 4.3360e-04 eta: 2:18:11 time: 0.7002 data_time: 0.0268 memory: 14901 loss: 0.8161 loss_prob: 0.4122 loss_thr: 0.3312 loss_db: 0.0727 2022/11/03 00:17:43 - mmengine - INFO - Epoch(train) [999][60/63] lr: 4.3360e-04 eta: 2:18:05 time: 0.6488 data_time: 0.0135 memory: 14901 loss: 0.8571 loss_prob: 0.4358 loss_thr: 0.3449 loss_db: 0.0764 2022/11/03 00:17:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:17:53 - mmengine - INFO - Epoch(train) [1000][5/63] lr: 4.3166e-04 eta: 2:18:05 time: 1.1060 data_time: 0.3176 memory: 14901 loss: 0.8448 loss_prob: 0.4356 loss_thr: 0.3320 loss_db: 0.0771 2022/11/03 00:17:56 - mmengine - INFO - Epoch(train) [1000][10/63] lr: 4.3166e-04 eta: 2:17:57 time: 1.1090 data_time: 0.3180 memory: 14901 loss: 0.9013 loss_prob: 0.4689 loss_thr: 0.3522 loss_db: 0.0803 2022/11/03 00:18:00 - mmengine - INFO - Epoch(train) [1000][15/63] lr: 4.3166e-04 eta: 2:17:57 time: 0.6786 data_time: 0.0069 memory: 14901 loss: 0.8876 loss_prob: 0.4615 loss_thr: 0.3458 loss_db: 0.0803 2022/11/03 00:18:03 - mmengine - INFO - Epoch(train) [1000][20/63] lr: 4.3166e-04 eta: 2:17:51 time: 0.7381 data_time: 0.0074 memory: 14901 loss: 0.8797 loss_prob: 0.4447 loss_thr: 0.3555 loss_db: 0.0794 2022/11/03 00:18:07 - mmengine - INFO - Epoch(train) [1000][25/63] lr: 4.3166e-04 eta: 2:17:51 time: 0.7312 data_time: 0.0440 memory: 14901 loss: 0.9736 loss_prob: 0.4936 loss_thr: 0.3930 loss_db: 0.0870 2022/11/03 00:18:10 - mmengine - INFO - Epoch(train) [1000][30/63] lr: 4.3166e-04 eta: 2:17:44 time: 0.6962 data_time: 0.0433 memory: 14901 loss: 0.9887 loss_prob: 0.5155 loss_thr: 0.3835 loss_db: 0.0898 2022/11/03 00:18:13 - mmengine - INFO - Epoch(train) [1000][35/63] lr: 4.3166e-04 eta: 2:17:44 time: 0.6405 data_time: 0.0069 memory: 14901 loss: 0.9298 loss_prob: 0.4869 loss_thr: 0.3583 loss_db: 0.0847 2022/11/03 00:18:16 - mmengine - INFO - Epoch(train) [1000][40/63] lr: 4.3166e-04 eta: 2:17:37 time: 0.5774 data_time: 0.0057 memory: 14901 loss: 0.8253 loss_prob: 0.4230 loss_thr: 0.3287 loss_db: 0.0736 2022/11/03 00:18:19 - mmengine - INFO - Epoch(train) [1000][45/63] lr: 4.3166e-04 eta: 2:17:37 time: 0.6116 data_time: 0.0053 memory: 14901 loss: 0.8081 loss_prob: 0.4147 loss_thr: 0.3207 loss_db: 0.0727 2022/11/03 00:18:23 - mmengine - INFO - Epoch(train) [1000][50/63] lr: 4.3166e-04 eta: 2:17:31 time: 0.6846 data_time: 0.0267 memory: 14901 loss: 0.8356 loss_prob: 0.4296 loss_thr: 0.3298 loss_db: 0.0762 2022/11/03 00:18:26 - mmengine - INFO - Epoch(train) [1000][55/63] lr: 4.3166e-04 eta: 2:17:31 time: 0.6222 data_time: 0.0268 memory: 14901 loss: 0.8786 loss_prob: 0.4549 loss_thr: 0.3429 loss_db: 0.0808 2022/11/03 00:18:29 - mmengine - INFO - Epoch(train) [1000][60/63] lr: 4.3166e-04 eta: 2:17:24 time: 0.5705 data_time: 0.0055 memory: 14901 loss: 0.9337 loss_prob: 0.4887 loss_thr: 0.3594 loss_db: 0.0856 2022/11/03 00:18:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:18:31 - mmengine - INFO - Saving checkpoint at 1000 epochs 2022/11/03 00:18:34 - mmengine - INFO - Epoch(val) [1000][5/500] eta: 2:17:24 time: 0.0491 data_time: 0.0065 memory: 14901 2022/11/03 00:18:35 - mmengine - INFO - Epoch(val) [1000][10/500] eta: 0:00:23 time: 0.0479 data_time: 0.0054 memory: 1008 2022/11/03 00:18:35 - mmengine - INFO - Epoch(val) [1000][15/500] eta: 0:00:23 time: 0.0432 data_time: 0.0032 memory: 1008 2022/11/03 00:18:35 - mmengine - INFO - Epoch(val) [1000][20/500] eta: 0:00:19 time: 0.0406 data_time: 0.0030 memory: 1008 2022/11/03 00:18:35 - mmengine - INFO - Epoch(val) [1000][25/500] eta: 0:00:19 time: 0.0379 data_time: 0.0027 memory: 1008 2022/11/03 00:18:35 - mmengine - INFO - Epoch(val) [1000][30/500] eta: 0:00:20 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/03 00:18:36 - mmengine - INFO - Epoch(val) [1000][35/500] eta: 0:00:20 time: 0.0440 data_time: 0.0027 memory: 1008 2022/11/03 00:18:36 - mmengine - INFO - Epoch(val) [1000][40/500] eta: 0:00:20 time: 0.0438 data_time: 0.0027 memory: 1008 2022/11/03 00:18:36 - mmengine - INFO - Epoch(val) [1000][45/500] eta: 0:00:20 time: 0.0454 data_time: 0.0027 memory: 1008 2022/11/03 00:18:36 - mmengine - INFO - Epoch(val) [1000][50/500] eta: 0:00:19 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/03 00:18:37 - mmengine - INFO - Epoch(val) [1000][55/500] eta: 0:00:19 time: 0.0455 data_time: 0.0028 memory: 1008 2022/11/03 00:18:37 - mmengine - INFO - Epoch(val) [1000][60/500] eta: 0:00:18 time: 0.0419 data_time: 0.0027 memory: 1008 2022/11/03 00:18:37 - mmengine - INFO - Epoch(val) [1000][65/500] eta: 0:00:18 time: 0.0433 data_time: 0.0030 memory: 1008 2022/11/03 00:18:37 - mmengine - INFO - Epoch(val) [1000][70/500] eta: 0:00:20 time: 0.0474 data_time: 0.0031 memory: 1008 2022/11/03 00:18:37 - mmengine - INFO - Epoch(val) [1000][75/500] eta: 0:00:20 time: 0.0424 data_time: 0.0033 memory: 1008 2022/11/03 00:18:38 - mmengine - INFO - Epoch(val) [1000][80/500] eta: 0:00:16 time: 0.0399 data_time: 0.0035 memory: 1008 2022/11/03 00:18:38 - mmengine - INFO - Epoch(val) [1000][85/500] eta: 0:00:16 time: 0.0379 data_time: 0.0028 memory: 1008 2022/11/03 00:18:38 - mmengine - INFO - Epoch(val) [1000][90/500] eta: 0:00:17 time: 0.0416 data_time: 0.0026 memory: 1008 2022/11/03 00:18:38 - mmengine - INFO - Epoch(val) [1000][95/500] eta: 0:00:17 time: 0.0466 data_time: 0.0029 memory: 1008 2022/11/03 00:18:39 - mmengine - INFO - Epoch(val) [1000][100/500] eta: 0:00:16 time: 0.0421 data_time: 0.0029 memory: 1008 2022/11/03 00:18:39 - mmengine - INFO - Epoch(val) [1000][105/500] eta: 0:00:16 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/03 00:18:39 - mmengine - INFO - Epoch(val) [1000][110/500] eta: 0:00:16 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/03 00:18:39 - mmengine - INFO - Epoch(val) [1000][115/500] eta: 0:00:16 time: 0.0442 data_time: 0.0030 memory: 1008 2022/11/03 00:18:39 - mmengine - INFO - Epoch(val) [1000][120/500] eta: 0:00:18 time: 0.0478 data_time: 0.0035 memory: 1008 2022/11/03 00:18:40 - mmengine - INFO - Epoch(val) [1000][125/500] eta: 0:00:18 time: 0.0457 data_time: 0.0044 memory: 1008 2022/11/03 00:18:40 - mmengine - INFO - Epoch(val) [1000][130/500] eta: 0:00:16 time: 0.0457 data_time: 0.0043 memory: 1008 2022/11/03 00:18:40 - mmengine - INFO - Epoch(val) [1000][135/500] eta: 0:00:16 time: 0.0433 data_time: 0.0035 memory: 1008 2022/11/03 00:18:40 - mmengine - INFO - Epoch(val) [1000][140/500] eta: 0:00:14 time: 0.0410 data_time: 0.0032 memory: 1008 2022/11/03 00:18:41 - mmengine - INFO - Epoch(val) [1000][145/500] eta: 0:00:14 time: 0.0480 data_time: 0.0032 memory: 1008 2022/11/03 00:18:41 - mmengine - INFO - Epoch(val) [1000][150/500] eta: 0:00:16 time: 0.0479 data_time: 0.0033 memory: 1008 2022/11/03 00:18:41 - mmengine - INFO - Epoch(val) [1000][155/500] eta: 0:00:16 time: 0.0457 data_time: 0.0033 memory: 1008 2022/11/03 00:18:41 - mmengine - INFO - Epoch(val) [1000][160/500] eta: 0:00:15 time: 0.0465 data_time: 0.0029 memory: 1008 2022/11/03 00:18:41 - mmengine - INFO - Epoch(val) [1000][165/500] eta: 0:00:15 time: 0.0418 data_time: 0.0025 memory: 1008 2022/11/03 00:18:42 - mmengine - INFO - Epoch(val) [1000][170/500] eta: 0:00:14 time: 0.0429 data_time: 0.0028 memory: 1008 2022/11/03 00:18:42 - mmengine - INFO - Epoch(val) [1000][175/500] eta: 0:00:14 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/03 00:18:42 - mmengine - INFO - Epoch(val) [1000][180/500] eta: 0:00:13 time: 0.0406 data_time: 0.0028 memory: 1008 2022/11/03 00:18:42 - mmengine - INFO - Epoch(val) [1000][185/500] eta: 0:00:13 time: 0.0467 data_time: 0.0029 memory: 1008 2022/11/03 00:18:43 - mmengine - INFO - Epoch(val) [1000][190/500] eta: 0:00:14 time: 0.0467 data_time: 0.0028 memory: 1008 2022/11/03 00:18:43 - mmengine - INFO - Epoch(val) [1000][195/500] eta: 0:00:14 time: 0.0423 data_time: 0.0026 memory: 1008 2022/11/03 00:18:43 - mmengine - INFO - Epoch(val) [1000][200/500] eta: 0:00:14 time: 0.0489 data_time: 0.0028 memory: 1008 2022/11/03 00:18:43 - mmengine - INFO - Epoch(val) [1000][205/500] eta: 0:00:14 time: 0.0477 data_time: 0.0028 memory: 1008 2022/11/03 00:18:43 - mmengine - INFO - Epoch(val) [1000][210/500] eta: 0:00:11 time: 0.0412 data_time: 0.0027 memory: 1008 2022/11/03 00:18:44 - mmengine - INFO - Epoch(val) [1000][215/500] eta: 0:00:11 time: 0.0442 data_time: 0.0030 memory: 1008 2022/11/03 00:18:44 - mmengine - INFO - Epoch(val) [1000][220/500] eta: 0:00:12 time: 0.0434 data_time: 0.0028 memory: 1008 2022/11/03 00:18:44 - mmengine - INFO - Epoch(val) [1000][225/500] eta: 0:00:12 time: 0.0422 data_time: 0.0026 memory: 1008 2022/11/03 00:18:44 - mmengine - INFO - Epoch(val) [1000][230/500] eta: 0:00:11 time: 0.0410 data_time: 0.0029 memory: 1008 2022/11/03 00:18:45 - mmengine - INFO - Epoch(val) [1000][235/500] eta: 0:00:11 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/03 00:18:45 - mmengine - INFO - Epoch(val) [1000][240/500] eta: 0:00:11 time: 0.0439 data_time: 0.0027 memory: 1008 2022/11/03 00:18:45 - mmengine - INFO - Epoch(val) [1000][245/500] eta: 0:00:11 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/03 00:18:45 - mmengine - INFO - Epoch(val) [1000][250/500] eta: 0:00:10 time: 0.0435 data_time: 0.0029 memory: 1008 2022/11/03 00:18:45 - mmengine - INFO - Epoch(val) [1000][255/500] eta: 0:00:10 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/03 00:18:46 - mmengine - INFO - Epoch(val) [1000][260/500] eta: 0:00:09 time: 0.0393 data_time: 0.0028 memory: 1008 2022/11/03 00:18:46 - mmengine - INFO - Epoch(val) [1000][265/500] eta: 0:00:09 time: 0.0398 data_time: 0.0027 memory: 1008 2022/11/03 00:18:46 - mmengine - INFO - Epoch(val) [1000][270/500] eta: 0:00:09 time: 0.0425 data_time: 0.0028 memory: 1008 2022/11/03 00:18:46 - mmengine - INFO - Epoch(val) [1000][275/500] eta: 0:00:09 time: 0.0400 data_time: 0.0030 memory: 1008 2022/11/03 00:18:46 - mmengine - INFO - Epoch(val) [1000][280/500] eta: 0:00:09 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/03 00:18:47 - mmengine - INFO - Epoch(val) [1000][285/500] eta: 0:00:09 time: 0.0426 data_time: 0.0028 memory: 1008 2022/11/03 00:18:47 - mmengine - INFO - Epoch(val) [1000][290/500] eta: 0:00:08 time: 0.0413 data_time: 0.0028 memory: 1008 2022/11/03 00:18:47 - mmengine - INFO - Epoch(val) [1000][295/500] eta: 0:00:08 time: 0.0449 data_time: 0.0028 memory: 1008 2022/11/03 00:18:47 - mmengine - INFO - Epoch(val) [1000][300/500] eta: 0:00:09 time: 0.0472 data_time: 0.0049 memory: 1008 2022/11/03 00:18:47 - mmengine - INFO - Epoch(val) [1000][305/500] eta: 0:00:09 time: 0.0435 data_time: 0.0047 memory: 1008 2022/11/03 00:18:48 - mmengine - INFO - Epoch(val) [1000][310/500] eta: 0:00:07 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/03 00:18:48 - mmengine - INFO - Epoch(val) [1000][315/500] eta: 0:00:07 time: 0.0497 data_time: 0.0034 memory: 1008 2022/11/03 00:18:48 - mmengine - INFO - Epoch(val) [1000][320/500] eta: 0:00:09 time: 0.0529 data_time: 0.0040 memory: 1008 2022/11/03 00:18:49 - mmengine - INFO - Epoch(val) [1000][325/500] eta: 0:00:09 time: 0.0637 data_time: 0.0040 memory: 1008 2022/11/03 00:18:49 - mmengine - INFO - Epoch(val) [1000][330/500] eta: 0:00:10 time: 0.0624 data_time: 0.0039 memory: 1008 2022/11/03 00:18:49 - mmengine - INFO - Epoch(val) [1000][335/500] eta: 0:00:10 time: 0.0459 data_time: 0.0039 memory: 1008 2022/11/03 00:18:49 - mmengine - INFO - Epoch(val) [1000][340/500] eta: 0:00:10 time: 0.0640 data_time: 0.0051 memory: 1008 2022/11/03 00:18:50 - mmengine - INFO - Epoch(val) [1000][345/500] eta: 0:00:10 time: 0.0727 data_time: 0.0055 memory: 1008 2022/11/03 00:18:50 - mmengine - INFO - Epoch(val) [1000][350/500] eta: 0:00:09 time: 0.0660 data_time: 0.0044 memory: 1008 2022/11/03 00:18:50 - mmengine - INFO - Epoch(val) [1000][355/500] eta: 0:00:09 time: 0.0596 data_time: 0.0039 memory: 1008 2022/11/03 00:18:51 - mmengine - INFO - Epoch(val) [1000][360/500] eta: 0:00:07 time: 0.0508 data_time: 0.0038 memory: 1008 2022/11/03 00:18:51 - mmengine - INFO - Epoch(val) [1000][365/500] eta: 0:00:07 time: 0.0535 data_time: 0.0039 memory: 1008 2022/11/03 00:18:51 - mmengine - INFO - Epoch(val) [1000][370/500] eta: 0:00:07 time: 0.0550 data_time: 0.0044 memory: 1008 2022/11/03 00:18:51 - mmengine - INFO - Epoch(val) [1000][375/500] eta: 0:00:07 time: 0.0530 data_time: 0.0050 memory: 1008 2022/11/03 00:18:52 - mmengine - INFO - Epoch(val) [1000][380/500] eta: 0:00:06 time: 0.0501 data_time: 0.0043 memory: 1008 2022/11/03 00:18:52 - mmengine - INFO - Epoch(val) [1000][385/500] eta: 0:00:06 time: 0.0454 data_time: 0.0029 memory: 1008 2022/11/03 00:18:52 - mmengine - INFO - Epoch(val) [1000][390/500] eta: 0:00:04 time: 0.0440 data_time: 0.0028 memory: 1008 2022/11/03 00:18:52 - mmengine - INFO - Epoch(val) [1000][395/500] eta: 0:00:04 time: 0.0439 data_time: 0.0032 memory: 1008 2022/11/03 00:18:53 - mmengine - INFO - Epoch(val) [1000][400/500] eta: 0:00:04 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/03 00:18:53 - mmengine - INFO - Epoch(val) [1000][405/500] eta: 0:00:04 time: 0.0456 data_time: 0.0032 memory: 1008 2022/11/03 00:18:53 - mmengine - INFO - Epoch(val) [1000][410/500] eta: 0:00:04 time: 0.0453 data_time: 0.0031 memory: 1008 2022/11/03 00:18:53 - mmengine - INFO - Epoch(val) [1000][415/500] eta: 0:00:04 time: 0.0463 data_time: 0.0035 memory: 1008 2022/11/03 00:18:53 - mmengine - INFO - Epoch(val) [1000][420/500] eta: 0:00:03 time: 0.0415 data_time: 0.0033 memory: 1008 2022/11/03 00:18:54 - mmengine - INFO - Epoch(val) [1000][425/500] eta: 0:00:03 time: 0.0383 data_time: 0.0026 memory: 1008 2022/11/03 00:18:54 - mmengine - INFO - Epoch(val) [1000][430/500] eta: 0:00:03 time: 0.0468 data_time: 0.0031 memory: 1008 2022/11/03 00:18:54 - mmengine - INFO - Epoch(val) [1000][435/500] eta: 0:00:03 time: 0.0469 data_time: 0.0031 memory: 1008 2022/11/03 00:18:54 - mmengine - INFO - Epoch(val) [1000][440/500] eta: 0:00:02 time: 0.0405 data_time: 0.0026 memory: 1008 2022/11/03 00:18:55 - mmengine - INFO - Epoch(val) [1000][445/500] eta: 0:00:02 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/03 00:18:55 - mmengine - INFO - Epoch(val) [1000][450/500] eta: 0:00:02 time: 0.0457 data_time: 0.0028 memory: 1008 2022/11/03 00:18:55 - mmengine - INFO - Epoch(val) [1000][455/500] eta: 0:00:02 time: 0.0472 data_time: 0.0031 memory: 1008 2022/11/03 00:18:55 - mmengine - INFO - Epoch(val) [1000][460/500] eta: 0:00:01 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/03 00:18:55 - mmengine - INFO - Epoch(val) [1000][465/500] eta: 0:00:01 time: 0.0421 data_time: 0.0029 memory: 1008 2022/11/03 00:18:56 - mmengine - INFO - Epoch(val) [1000][470/500] eta: 0:00:01 time: 0.0446 data_time: 0.0031 memory: 1008 2022/11/03 00:18:56 - mmengine - INFO - Epoch(val) [1000][475/500] eta: 0:00:01 time: 0.0455 data_time: 0.0035 memory: 1008 2022/11/03 00:18:56 - mmengine - INFO - Epoch(val) [1000][480/500] eta: 0:00:00 time: 0.0429 data_time: 0.0033 memory: 1008 2022/11/03 00:18:56 - mmengine - INFO - Epoch(val) [1000][485/500] eta: 0:00:00 time: 0.0422 data_time: 0.0028 memory: 1008 2022/11/03 00:18:57 - mmengine - INFO - Epoch(val) [1000][490/500] eta: 0:00:00 time: 0.0458 data_time: 0.0030 memory: 1008 2022/11/03 00:18:57 - mmengine - INFO - Epoch(val) [1000][495/500] eta: 0:00:00 time: 0.0481 data_time: 0.0031 memory: 1008 2022/11/03 00:18:57 - mmengine - INFO - Epoch(val) [1000][500/500] eta: 0:00:00 time: 0.0445 data_time: 0.0028 memory: 1008 2022/11/03 00:18:57 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8262, precision: 0.7664, hmean: 0.7952 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8262, precision: 0.8087, hmean: 0.8173 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8257, precision: 0.8325, hmean: 0.8291 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8223, precision: 0.8498, hmean: 0.8358 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8122, precision: 0.8832, hmean: 0.8463 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7135, precision: 0.9211, hmean: 0.8041 2022/11/03 00:18:57 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1916, precision: 0.9544, hmean: 0.3192 2022/11/03 00:18:57 - mmengine - INFO - Epoch(val) [1000][500/500] icdar/precision: 0.8832 icdar/recall: 0.8122 icdar/hmean: 0.8463 2022/11/03 00:19:04 - mmengine - INFO - Epoch(train) [1001][5/63] lr: 4.2971e-04 eta: 0:00:00 time: 1.0274 data_time: 0.2802 memory: 14901 loss: 0.9139 loss_prob: 0.4658 loss_thr: 0.3669 loss_db: 0.0812 2022/11/03 00:19:08 - mmengine - INFO - Epoch(train) [1001][10/63] lr: 4.2971e-04 eta: 2:17:16 time: 1.0714 data_time: 0.2810 memory: 14901 loss: 0.8425 loss_prob: 0.4303 loss_thr: 0.3364 loss_db: 0.0758 2022/11/03 00:19:11 - mmengine - INFO - Epoch(train) [1001][15/63] lr: 4.2971e-04 eta: 2:17:16 time: 0.6697 data_time: 0.0070 memory: 14901 loss: 0.8357 loss_prob: 0.4312 loss_thr: 0.3289 loss_db: 0.0756 2022/11/03 00:19:14 - mmengine - INFO - Epoch(train) [1001][20/63] lr: 4.2971e-04 eta: 2:17:09 time: 0.6165 data_time: 0.0065 memory: 14901 loss: 0.9655 loss_prob: 0.5074 loss_thr: 0.3697 loss_db: 0.0884 2022/11/03 00:19:17 - mmengine - INFO - Epoch(train) [1001][25/63] lr: 4.2971e-04 eta: 2:17:09 time: 0.5911 data_time: 0.0107 memory: 14901 loss: 0.9602 loss_prob: 0.4938 loss_thr: 0.3800 loss_db: 0.0865 2022/11/03 00:19:20 - mmengine - INFO - Epoch(train) [1001][30/63] lr: 4.2971e-04 eta: 2:17:03 time: 0.6064 data_time: 0.0420 memory: 14901 loss: 0.8399 loss_prob: 0.4226 loss_thr: 0.3434 loss_db: 0.0740 2022/11/03 00:19:23 - mmengine - INFO - Epoch(train) [1001][35/63] lr: 4.2971e-04 eta: 2:17:03 time: 0.5824 data_time: 0.0377 memory: 14901 loss: 0.8594 loss_prob: 0.4468 loss_thr: 0.3361 loss_db: 0.0764 2022/11/03 00:19:25 - mmengine - INFO - Epoch(train) [1001][40/63] lr: 4.2971e-04 eta: 2:16:56 time: 0.5436 data_time: 0.0064 memory: 14901 loss: 0.9057 loss_prob: 0.4798 loss_thr: 0.3440 loss_db: 0.0819 2022/11/03 00:19:30 - mmengine - INFO - Epoch(train) [1001][45/63] lr: 4.2971e-04 eta: 2:16:56 time: 0.7021 data_time: 0.0069 memory: 14901 loss: 0.9338 loss_prob: 0.4900 loss_thr: 0.3582 loss_db: 0.0856 2022/11/03 00:19:33 - mmengine - INFO - Epoch(train) [1001][50/63] lr: 4.2971e-04 eta: 2:16:50 time: 0.7407 data_time: 0.0126 memory: 14901 loss: 0.9438 loss_prob: 0.4900 loss_thr: 0.3674 loss_db: 0.0865 2022/11/03 00:19:37 - mmengine - INFO - Epoch(train) [1001][55/63] lr: 4.2971e-04 eta: 2:16:50 time: 0.7659 data_time: 0.0250 memory: 14901 loss: 0.8951 loss_prob: 0.4593 loss_thr: 0.3553 loss_db: 0.0804 2022/11/03 00:19:41 - mmengine - INFO - Epoch(train) [1001][60/63] lr: 4.2971e-04 eta: 2:16:44 time: 0.8342 data_time: 0.0188 memory: 14901 loss: 0.8567 loss_prob: 0.4428 loss_thr: 0.3361 loss_db: 0.0778 2022/11/03 00:19:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:19:49 - mmengine - INFO - Epoch(train) [1002][5/63] lr: 4.2777e-04 eta: 2:16:44 time: 0.9781 data_time: 0.2568 memory: 14901 loss: 0.9652 loss_prob: 0.5125 loss_thr: 0.3627 loss_db: 0.0901 2022/11/03 00:19:54 - mmengine - INFO - Epoch(train) [1002][10/63] lr: 4.2777e-04 eta: 2:16:35 time: 1.0669 data_time: 0.2555 memory: 14901 loss: 0.9026 loss_prob: 0.4780 loss_thr: 0.3415 loss_db: 0.0832 2022/11/03 00:19:57 - mmengine - INFO - Epoch(train) [1002][15/63] lr: 4.2777e-04 eta: 2:16:35 time: 0.7156 data_time: 0.0061 memory: 14901 loss: 0.8561 loss_prob: 0.4435 loss_thr: 0.3360 loss_db: 0.0766 2022/11/03 00:20:01 - mmengine - INFO - Epoch(train) [1002][20/63] lr: 4.2777e-04 eta: 2:16:29 time: 0.7617 data_time: 0.0062 memory: 14901 loss: 0.8784 loss_prob: 0.4556 loss_thr: 0.3438 loss_db: 0.0790 2022/11/03 00:20:04 - mmengine - INFO - Epoch(train) [1002][25/63] lr: 4.2777e-04 eta: 2:16:29 time: 0.7410 data_time: 0.0243 memory: 14901 loss: 0.9340 loss_prob: 0.4798 loss_thr: 0.3700 loss_db: 0.0843 2022/11/03 00:20:08 - mmengine - INFO - Epoch(train) [1002][30/63] lr: 4.2777e-04 eta: 2:16:23 time: 0.6439 data_time: 0.0363 memory: 14901 loss: 0.9886 loss_prob: 0.5164 loss_thr: 0.3814 loss_db: 0.0908 2022/11/03 00:20:11 - mmengine - INFO - Epoch(train) [1002][35/63] lr: 4.2777e-04 eta: 2:16:23 time: 0.6529 data_time: 0.0184 memory: 14901 loss: 0.9138 loss_prob: 0.4794 loss_thr: 0.3509 loss_db: 0.0834 2022/11/03 00:20:15 - mmengine - INFO - Epoch(train) [1002][40/63] lr: 4.2777e-04 eta: 2:16:16 time: 0.6902 data_time: 0.0076 memory: 14901 loss: 0.8937 loss_prob: 0.4613 loss_thr: 0.3523 loss_db: 0.0802 2022/11/03 00:20:18 - mmengine - INFO - Epoch(train) [1002][45/63] lr: 4.2777e-04 eta: 2:16:16 time: 0.7545 data_time: 0.0073 memory: 14901 loss: 0.8767 loss_prob: 0.4478 loss_thr: 0.3501 loss_db: 0.0788 2022/11/03 00:20:22 - mmengine - INFO - Epoch(train) [1002][50/63] lr: 4.2777e-04 eta: 2:16:10 time: 0.7711 data_time: 0.0239 memory: 14901 loss: 0.8328 loss_prob: 0.4216 loss_thr: 0.3354 loss_db: 0.0757 2022/11/03 00:20:26 - mmengine - INFO - Epoch(train) [1002][55/63] lr: 4.2777e-04 eta: 2:16:10 time: 0.7615 data_time: 0.0243 memory: 14901 loss: 0.8369 loss_prob: 0.4248 loss_thr: 0.3373 loss_db: 0.0749 2022/11/03 00:20:30 - mmengine - INFO - Epoch(train) [1002][60/63] lr: 4.2777e-04 eta: 2:16:03 time: 0.7824 data_time: 0.0073 memory: 14901 loss: 0.8388 loss_prob: 0.4240 loss_thr: 0.3416 loss_db: 0.0732 2022/11/03 00:20:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:20:38 - mmengine - INFO - Epoch(train) [1003][5/63] lr: 4.2583e-04 eta: 2:16:03 time: 0.8915 data_time: 0.2624 memory: 14901 loss: 0.9142 loss_prob: 0.4531 loss_thr: 0.3817 loss_db: 0.0794 2022/11/03 00:20:40 - mmengine - INFO - Epoch(train) [1003][10/63] lr: 4.2583e-04 eta: 2:15:55 time: 0.8740 data_time: 0.2604 memory: 14901 loss: 0.9015 loss_prob: 0.4531 loss_thr: 0.3700 loss_db: 0.0784 2022/11/03 00:20:45 - mmengine - INFO - Epoch(train) [1003][15/63] lr: 4.2583e-04 eta: 2:15:55 time: 0.7175 data_time: 0.0133 memory: 14901 loss: 0.8430 loss_prob: 0.4222 loss_thr: 0.3485 loss_db: 0.0723 2022/11/03 00:20:48 - mmengine - INFO - Epoch(train) [1003][20/63] lr: 4.2583e-04 eta: 2:15:49 time: 0.7529 data_time: 0.0145 memory: 14901 loss: 0.8771 loss_prob: 0.4500 loss_thr: 0.3496 loss_db: 0.0775 2022/11/03 00:20:51 - mmengine - INFO - Epoch(train) [1003][25/63] lr: 4.2583e-04 eta: 2:15:49 time: 0.6666 data_time: 0.0114 memory: 14901 loss: 0.9100 loss_prob: 0.4738 loss_thr: 0.3543 loss_db: 0.0819 2022/11/03 00:20:56 - mmengine - INFO - Epoch(train) [1003][30/63] lr: 4.2583e-04 eta: 2:15:42 time: 0.8190 data_time: 0.0345 memory: 14901 loss: 0.9481 loss_prob: 0.4817 loss_thr: 0.3821 loss_db: 0.0843 2022/11/03 00:21:00 - mmengine - INFO - Epoch(train) [1003][35/63] lr: 4.2583e-04 eta: 2:15:42 time: 0.8180 data_time: 0.0301 memory: 14901 loss: 0.9731 loss_prob: 0.4947 loss_thr: 0.3910 loss_db: 0.0874 2022/11/03 00:21:04 - mmengine - INFO - Epoch(train) [1003][40/63] lr: 4.2583e-04 eta: 2:15:36 time: 0.7815 data_time: 0.0076 memory: 14901 loss: 0.9560 loss_prob: 0.4957 loss_thr: 0.3734 loss_db: 0.0869 2022/11/03 00:21:07 - mmengine - INFO - Epoch(train) [1003][45/63] lr: 4.2583e-04 eta: 2:15:36 time: 0.7162 data_time: 0.0101 memory: 14901 loss: 0.9223 loss_prob: 0.4814 loss_thr: 0.3573 loss_db: 0.0836 2022/11/03 00:21:11 - mmengine - INFO - Epoch(train) [1003][50/63] lr: 4.2583e-04 eta: 2:15:30 time: 0.7189 data_time: 0.0186 memory: 14901 loss: 0.8702 loss_prob: 0.4513 loss_thr: 0.3406 loss_db: 0.0782 2022/11/03 00:21:15 - mmengine - INFO - Epoch(train) [1003][55/63] lr: 4.2583e-04 eta: 2:15:30 time: 0.8002 data_time: 0.0256 memory: 14901 loss: 0.9004 loss_prob: 0.4656 loss_thr: 0.3552 loss_db: 0.0795 2022/11/03 00:21:18 - mmengine - INFO - Epoch(train) [1003][60/63] lr: 4.2583e-04 eta: 2:15:23 time: 0.7343 data_time: 0.0154 memory: 14901 loss: 0.9475 loss_prob: 0.4868 loss_thr: 0.3756 loss_db: 0.0851 2022/11/03 00:21:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:21:29 - mmengine - INFO - Epoch(train) [1004][5/63] lr: 4.2388e-04 eta: 2:15:23 time: 1.2324 data_time: 0.2723 memory: 14901 loss: 0.9832 loss_prob: 0.5173 loss_thr: 0.3765 loss_db: 0.0893 2022/11/03 00:21:32 - mmengine - INFO - Epoch(train) [1004][10/63] lr: 4.2388e-04 eta: 2:15:15 time: 1.1492 data_time: 0.2758 memory: 14901 loss: 0.9520 loss_prob: 0.4906 loss_thr: 0.3761 loss_db: 0.0853 2022/11/03 00:21:35 - mmengine - INFO - Epoch(train) [1004][15/63] lr: 4.2388e-04 eta: 2:15:15 time: 0.5740 data_time: 0.0140 memory: 14901 loss: 0.9340 loss_prob: 0.4764 loss_thr: 0.3753 loss_db: 0.0822 2022/11/03 00:21:37 - mmengine - INFO - Epoch(train) [1004][20/63] lr: 4.2388e-04 eta: 2:15:09 time: 0.5533 data_time: 0.0072 memory: 14901 loss: 0.8737 loss_prob: 0.4449 loss_thr: 0.3504 loss_db: 0.0784 2022/11/03 00:21:40 - mmengine - INFO - Epoch(train) [1004][25/63] lr: 4.2388e-04 eta: 2:15:09 time: 0.5733 data_time: 0.0209 memory: 14901 loss: 0.8829 loss_prob: 0.4518 loss_thr: 0.3505 loss_db: 0.0806 2022/11/03 00:21:43 - mmengine - INFO - Epoch(train) [1004][30/63] lr: 4.2388e-04 eta: 2:15:02 time: 0.6120 data_time: 0.0379 memory: 14901 loss: 0.9322 loss_prob: 0.4825 loss_thr: 0.3665 loss_db: 0.0833 2022/11/03 00:21:46 - mmengine - INFO - Epoch(train) [1004][35/63] lr: 4.2388e-04 eta: 2:15:02 time: 0.5579 data_time: 0.0269 memory: 14901 loss: 0.8685 loss_prob: 0.4515 loss_thr: 0.3381 loss_db: 0.0789 2022/11/03 00:21:50 - mmengine - INFO - Epoch(train) [1004][40/63] lr: 4.2388e-04 eta: 2:14:56 time: 0.6653 data_time: 0.0120 memory: 14901 loss: 0.8265 loss_prob: 0.4249 loss_thr: 0.3257 loss_db: 0.0759 2022/11/03 00:21:53 - mmengine - INFO - Epoch(train) [1004][45/63] lr: 4.2388e-04 eta: 2:14:56 time: 0.7315 data_time: 0.0067 memory: 14901 loss: 0.8934 loss_prob: 0.4639 loss_thr: 0.3485 loss_db: 0.0810 2022/11/03 00:21:56 - mmengine - INFO - Epoch(train) [1004][50/63] lr: 4.2388e-04 eta: 2:14:49 time: 0.5864 data_time: 0.0154 memory: 14901 loss: 0.9419 loss_prob: 0.4996 loss_thr: 0.3565 loss_db: 0.0859 2022/11/03 00:21:59 - mmengine - INFO - Epoch(train) [1004][55/63] lr: 4.2388e-04 eta: 2:14:49 time: 0.5482 data_time: 0.0216 memory: 14901 loss: 0.9085 loss_prob: 0.4787 loss_thr: 0.3480 loss_db: 0.0818 2022/11/03 00:22:01 - mmengine - INFO - Epoch(train) [1004][60/63] lr: 4.2388e-04 eta: 2:14:42 time: 0.5499 data_time: 0.0165 memory: 14901 loss: 0.8555 loss_prob: 0.4445 loss_thr: 0.3338 loss_db: 0.0772 2022/11/03 00:22:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:22:13 - mmengine - INFO - Epoch(train) [1005][5/63] lr: 4.2193e-04 eta: 2:14:42 time: 1.2994 data_time: 0.2823 memory: 14901 loss: 0.9909 loss_prob: 0.5234 loss_thr: 0.3788 loss_db: 0.0887 2022/11/03 00:22:18 - mmengine - INFO - Epoch(train) [1005][10/63] lr: 4.2193e-04 eta: 2:14:35 time: 1.4074 data_time: 0.2843 memory: 14901 loss: 0.9121 loss_prob: 0.4788 loss_thr: 0.3531 loss_db: 0.0802 2022/11/03 00:22:22 - mmengine - INFO - Epoch(train) [1005][15/63] lr: 4.2193e-04 eta: 2:14:35 time: 0.8244 data_time: 0.0122 memory: 14901 loss: 0.8841 loss_prob: 0.4627 loss_thr: 0.3393 loss_db: 0.0821 2022/11/03 00:22:25 - mmengine - INFO - Epoch(train) [1005][20/63] lr: 4.2193e-04 eta: 2:14:28 time: 0.6864 data_time: 0.0087 memory: 14901 loss: 0.9199 loss_prob: 0.4867 loss_thr: 0.3456 loss_db: 0.0876 2022/11/03 00:22:27 - mmengine - INFO - Epoch(train) [1005][25/63] lr: 4.2193e-04 eta: 2:14:28 time: 0.5923 data_time: 0.0257 memory: 14901 loss: 0.8695 loss_prob: 0.4534 loss_thr: 0.3356 loss_db: 0.0805 2022/11/03 00:22:30 - mmengine - INFO - Epoch(train) [1005][30/63] lr: 4.2193e-04 eta: 2:14:21 time: 0.5535 data_time: 0.0367 memory: 14901 loss: 0.8911 loss_prob: 0.4684 loss_thr: 0.3408 loss_db: 0.0819 2022/11/03 00:22:33 - mmengine - INFO - Epoch(train) [1005][35/63] lr: 4.2193e-04 eta: 2:14:21 time: 0.5954 data_time: 0.0258 memory: 14901 loss: 0.8765 loss_prob: 0.4592 loss_thr: 0.3394 loss_db: 0.0780 2022/11/03 00:22:37 - mmengine - INFO - Epoch(train) [1005][40/63] lr: 4.2193e-04 eta: 2:14:15 time: 0.7361 data_time: 0.0145 memory: 14901 loss: 0.8700 loss_prob: 0.4442 loss_thr: 0.3468 loss_db: 0.0790 2022/11/03 00:22:40 - mmengine - INFO - Epoch(train) [1005][45/63] lr: 4.2193e-04 eta: 2:14:15 time: 0.6940 data_time: 0.0051 memory: 14901 loss: 0.9033 loss_prob: 0.4595 loss_thr: 0.3616 loss_db: 0.0822 2022/11/03 00:22:43 - mmengine - INFO - Epoch(train) [1005][50/63] lr: 4.2193e-04 eta: 2:14:08 time: 0.5495 data_time: 0.0167 memory: 14901 loss: 0.9170 loss_prob: 0.4712 loss_thr: 0.3645 loss_db: 0.0813 2022/11/03 00:22:46 - mmengine - INFO - Epoch(train) [1005][55/63] lr: 4.2193e-04 eta: 2:14:08 time: 0.5558 data_time: 0.0216 memory: 14901 loss: 0.9014 loss_prob: 0.4651 loss_thr: 0.3549 loss_db: 0.0814 2022/11/03 00:22:49 - mmengine - INFO - Epoch(train) [1005][60/63] lr: 4.2193e-04 eta: 2:14:02 time: 0.6313 data_time: 0.0173 memory: 14901 loss: 0.8922 loss_prob: 0.4574 loss_thr: 0.3535 loss_db: 0.0813 2022/11/03 00:22:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:22:58 - mmengine - INFO - Epoch(train) [1006][5/63] lr: 4.1999e-04 eta: 2:14:02 time: 0.9660 data_time: 0.2998 memory: 14901 loss: 0.9120 loss_prob: 0.4731 loss_thr: 0.3568 loss_db: 0.0821 2022/11/03 00:23:01 - mmengine - INFO - Epoch(train) [1006][10/63] lr: 4.1999e-04 eta: 2:13:54 time: 1.0045 data_time: 0.3075 memory: 14901 loss: 0.8942 loss_prob: 0.4608 loss_thr: 0.3539 loss_db: 0.0794 2022/11/03 00:23:04 - mmengine - INFO - Epoch(train) [1006][15/63] lr: 4.1999e-04 eta: 2:13:54 time: 0.6190 data_time: 0.0177 memory: 14901 loss: 0.8785 loss_prob: 0.4492 loss_thr: 0.3511 loss_db: 0.0781 2022/11/03 00:23:06 - mmengine - INFO - Epoch(train) [1006][20/63] lr: 4.1999e-04 eta: 2:13:47 time: 0.5523 data_time: 0.0058 memory: 14901 loss: 0.8936 loss_prob: 0.4606 loss_thr: 0.3518 loss_db: 0.0812 2022/11/03 00:23:09 - mmengine - INFO - Epoch(train) [1006][25/63] lr: 4.1999e-04 eta: 2:13:47 time: 0.5168 data_time: 0.0191 memory: 14901 loss: 0.9964 loss_prob: 0.5474 loss_thr: 0.3622 loss_db: 0.0868 2022/11/03 00:23:11 - mmengine - INFO - Epoch(train) [1006][30/63] lr: 4.1999e-04 eta: 2:13:40 time: 0.4797 data_time: 0.0227 memory: 14901 loss: 0.9771 loss_prob: 0.5422 loss_thr: 0.3500 loss_db: 0.0849 2022/11/03 00:23:14 - mmengine - INFO - Epoch(train) [1006][35/63] lr: 4.1999e-04 eta: 2:13:40 time: 0.4653 data_time: 0.0189 memory: 14901 loss: 0.8692 loss_prob: 0.4520 loss_thr: 0.3384 loss_db: 0.0788 2022/11/03 00:23:16 - mmengine - INFO - Epoch(train) [1006][40/63] lr: 4.1999e-04 eta: 2:13:33 time: 0.4719 data_time: 0.0150 memory: 14901 loss: 0.8547 loss_prob: 0.4369 loss_thr: 0.3431 loss_db: 0.0748 2022/11/03 00:23:18 - mmengine - INFO - Epoch(train) [1006][45/63] lr: 4.1999e-04 eta: 2:13:33 time: 0.4714 data_time: 0.0045 memory: 14901 loss: 0.9422 loss_prob: 0.4892 loss_thr: 0.3706 loss_db: 0.0824 2022/11/03 00:23:21 - mmengine - INFO - Epoch(train) [1006][50/63] lr: 4.1999e-04 eta: 2:13:26 time: 0.4876 data_time: 0.0144 memory: 14901 loss: 1.0340 loss_prob: 0.5434 loss_thr: 0.3971 loss_db: 0.0934 2022/11/03 00:23:23 - mmengine - INFO - Epoch(train) [1006][55/63] lr: 4.1999e-04 eta: 2:13:26 time: 0.4858 data_time: 0.0184 memory: 14901 loss: 0.9663 loss_prob: 0.5121 loss_thr: 0.3666 loss_db: 0.0876 2022/11/03 00:23:26 - mmengine - INFO - Epoch(train) [1006][60/63] lr: 4.1999e-04 eta: 2:13:19 time: 0.4743 data_time: 0.0108 memory: 14901 loss: 0.8957 loss_prob: 0.4725 loss_thr: 0.3435 loss_db: 0.0796 2022/11/03 00:23:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:23:33 - mmengine - INFO - Epoch(train) [1007][5/63] lr: 4.1804e-04 eta: 2:13:19 time: 0.8180 data_time: 0.2281 memory: 14901 loss: 0.9018 loss_prob: 0.4622 loss_thr: 0.3590 loss_db: 0.0806 2022/11/03 00:23:36 - mmengine - INFO - Epoch(train) [1007][10/63] lr: 4.1804e-04 eta: 2:13:11 time: 0.9098 data_time: 0.2423 memory: 14901 loss: 0.9157 loss_prob: 0.4743 loss_thr: 0.3601 loss_db: 0.0812 2022/11/03 00:23:38 - mmengine - INFO - Epoch(train) [1007][15/63] lr: 4.1804e-04 eta: 2:13:11 time: 0.5601 data_time: 0.0211 memory: 14901 loss: 0.9611 loss_prob: 0.5017 loss_thr: 0.3746 loss_db: 0.0849 2022/11/03 00:23:46 - mmengine - INFO - Epoch(train) [1007][20/63] lr: 4.1804e-04 eta: 2:13:05 time: 0.9882 data_time: 0.0085 memory: 14901 loss: 0.9230 loss_prob: 0.4750 loss_thr: 0.3644 loss_db: 0.0836 2022/11/03 00:23:54 - mmengine - INFO - Epoch(train) [1007][25/63] lr: 4.1804e-04 eta: 2:13:05 time: 1.5243 data_time: 0.0339 memory: 14901 loss: 0.8364 loss_prob: 0.4348 loss_thr: 0.3241 loss_db: 0.0775 2022/11/03 00:24:00 - mmengine - INFO - Epoch(train) [1007][30/63] lr: 4.1804e-04 eta: 2:13:00 time: 1.4271 data_time: 0.0592 memory: 14901 loss: 0.8449 loss_prob: 0.4359 loss_thr: 0.3319 loss_db: 0.0771 2022/11/03 00:24:07 - mmengine - INFO - Epoch(train) [1007][35/63] lr: 4.1804e-04 eta: 2:13:00 time: 1.3134 data_time: 0.0343 memory: 14901 loss: 0.9101 loss_prob: 0.4741 loss_thr: 0.3532 loss_db: 0.0828 2022/11/03 00:24:10 - mmengine - INFO - Epoch(train) [1007][40/63] lr: 4.1804e-04 eta: 2:12:54 time: 1.0180 data_time: 0.0108 memory: 14901 loss: 0.9254 loss_prob: 0.4820 loss_thr: 0.3609 loss_db: 0.0826 2022/11/03 00:24:13 - mmengine - INFO - Epoch(train) [1007][45/63] lr: 4.1804e-04 eta: 2:12:54 time: 0.6607 data_time: 0.0088 memory: 14901 loss: 0.9087 loss_prob: 0.4679 loss_thr: 0.3600 loss_db: 0.0808 2022/11/03 00:24:16 - mmengine - INFO - Epoch(train) [1007][50/63] lr: 4.1804e-04 eta: 2:12:47 time: 0.6115 data_time: 0.0242 memory: 14901 loss: 0.8843 loss_prob: 0.4627 loss_thr: 0.3415 loss_db: 0.0801 2022/11/03 00:24:19 - mmengine - INFO - Epoch(train) [1007][55/63] lr: 4.1804e-04 eta: 2:12:47 time: 0.5543 data_time: 0.0289 memory: 14901 loss: 0.9272 loss_prob: 0.4871 loss_thr: 0.3566 loss_db: 0.0836 2022/11/03 00:24:23 - mmengine - INFO - Epoch(train) [1007][60/63] lr: 4.1804e-04 eta: 2:12:41 time: 0.6855 data_time: 0.0105 memory: 14901 loss: 0.9695 loss_prob: 0.5104 loss_thr: 0.3702 loss_db: 0.0890 2022/11/03 00:24:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:24:34 - mmengine - INFO - Epoch(train) [1008][5/63] lr: 4.1609e-04 eta: 2:12:41 time: 1.2705 data_time: 0.2508 memory: 14901 loss: 0.8611 loss_prob: 0.4358 loss_thr: 0.3483 loss_db: 0.0770 2022/11/03 00:24:40 - mmengine - INFO - Epoch(train) [1008][10/63] lr: 4.1609e-04 eta: 2:12:34 time: 1.4427 data_time: 0.2545 memory: 14901 loss: 0.8578 loss_prob: 0.4343 loss_thr: 0.3473 loss_db: 0.0762 2022/11/03 00:24:46 - mmengine - INFO - Epoch(train) [1008][15/63] lr: 4.1609e-04 eta: 2:12:34 time: 1.1618 data_time: 0.0122 memory: 14901 loss: 0.9001 loss_prob: 0.4640 loss_thr: 0.3551 loss_db: 0.0811 2022/11/03 00:24:49 - mmengine - INFO - Epoch(train) [1008][20/63] lr: 4.1609e-04 eta: 2:12:28 time: 0.9328 data_time: 0.0066 memory: 14901 loss: 0.8973 loss_prob: 0.4683 loss_thr: 0.3474 loss_db: 0.0816 2022/11/03 00:24:52 - mmengine - INFO - Epoch(train) [1008][25/63] lr: 4.1609e-04 eta: 2:12:28 time: 0.5770 data_time: 0.0113 memory: 14901 loss: 0.9093 loss_prob: 0.4791 loss_thr: 0.3461 loss_db: 0.0842 2022/11/03 00:24:56 - mmengine - INFO - Epoch(train) [1008][30/63] lr: 4.1609e-04 eta: 2:12:21 time: 0.6957 data_time: 0.0374 memory: 14901 loss: 0.8396 loss_prob: 0.4285 loss_thr: 0.3367 loss_db: 0.0744 2022/11/03 00:24:59 - mmengine - INFO - Epoch(train) [1008][35/63] lr: 4.1609e-04 eta: 2:12:21 time: 0.7353 data_time: 0.0350 memory: 14901 loss: 0.9160 loss_prob: 0.4585 loss_thr: 0.3773 loss_db: 0.0802 2022/11/03 00:25:02 - mmengine - INFO - Epoch(train) [1008][40/63] lr: 4.1609e-04 eta: 2:12:14 time: 0.5940 data_time: 0.0087 memory: 14901 loss: 0.9610 loss_prob: 0.4911 loss_thr: 0.3838 loss_db: 0.0861 2022/11/03 00:25:07 - mmengine - INFO - Epoch(train) [1008][45/63] lr: 4.1609e-04 eta: 2:12:14 time: 0.7772 data_time: 0.0054 memory: 14901 loss: 0.9236 loss_prob: 0.4851 loss_thr: 0.3558 loss_db: 0.0827 2022/11/03 00:25:11 - mmengine - INFO - Epoch(train) [1008][50/63] lr: 4.1609e-04 eta: 2:12:08 time: 0.8686 data_time: 0.0098 memory: 14901 loss: 0.9822 loss_prob: 0.5025 loss_thr: 0.3927 loss_db: 0.0870 2022/11/03 00:25:14 - mmengine - INFO - Epoch(train) [1008][55/63] lr: 4.1609e-04 eta: 2:12:08 time: 0.6767 data_time: 0.0251 memory: 14901 loss: 0.9586 loss_prob: 0.4819 loss_thr: 0.3917 loss_db: 0.0850 2022/11/03 00:25:16 - mmengine - INFO - Epoch(train) [1008][60/63] lr: 4.1609e-04 eta: 2:12:02 time: 0.5341 data_time: 0.0239 memory: 14901 loss: 0.8562 loss_prob: 0.4385 loss_thr: 0.3399 loss_db: 0.0778 2022/11/03 00:25:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:25:26 - mmengine - INFO - Epoch(train) [1009][5/63] lr: 4.1414e-04 eta: 2:12:02 time: 1.1130 data_time: 0.2610 memory: 14901 loss: 0.9319 loss_prob: 0.4830 loss_thr: 0.3666 loss_db: 0.0824 2022/11/03 00:25:30 - mmengine - INFO - Epoch(train) [1009][10/63] lr: 4.1414e-04 eta: 2:11:54 time: 1.1942 data_time: 0.2649 memory: 14901 loss: 0.9781 loss_prob: 0.5097 loss_thr: 0.3793 loss_db: 0.0891 2022/11/03 00:25:33 - mmengine - INFO - Epoch(train) [1009][15/63] lr: 4.1414e-04 eta: 2:11:54 time: 0.6912 data_time: 0.0115 memory: 14901 loss: 0.8495 loss_prob: 0.4349 loss_thr: 0.3358 loss_db: 0.0788 2022/11/03 00:25:37 - mmengine - INFO - Epoch(train) [1009][20/63] lr: 4.1414e-04 eta: 2:11:47 time: 0.7071 data_time: 0.0063 memory: 14901 loss: 0.8783 loss_prob: 0.4538 loss_thr: 0.3433 loss_db: 0.0812 2022/11/03 00:25:41 - mmengine - INFO - Epoch(train) [1009][25/63] lr: 4.1414e-04 eta: 2:11:47 time: 0.7929 data_time: 0.0229 memory: 14901 loss: 0.8702 loss_prob: 0.4535 loss_thr: 0.3371 loss_db: 0.0796 2022/11/03 00:25:44 - mmengine - INFO - Epoch(train) [1009][30/63] lr: 4.1414e-04 eta: 2:11:41 time: 0.7142 data_time: 0.0395 memory: 14901 loss: 0.8067 loss_prob: 0.4079 loss_thr: 0.3284 loss_db: 0.0704 2022/11/03 00:25:47 - mmengine - INFO - Epoch(train) [1009][35/63] lr: 4.1414e-04 eta: 2:11:41 time: 0.6079 data_time: 0.0292 memory: 14901 loss: 0.8710 loss_prob: 0.4417 loss_thr: 0.3524 loss_db: 0.0769 2022/11/03 00:25:50 - mmengine - INFO - Epoch(train) [1009][40/63] lr: 4.1414e-04 eta: 2:11:34 time: 0.5798 data_time: 0.0130 memory: 14901 loss: 0.9213 loss_prob: 0.4779 loss_thr: 0.3594 loss_db: 0.0840 2022/11/03 00:25:53 - mmengine - INFO - Epoch(train) [1009][45/63] lr: 4.1414e-04 eta: 2:11:34 time: 0.5655 data_time: 0.0062 memory: 14901 loss: 0.9077 loss_prob: 0.4712 loss_thr: 0.3541 loss_db: 0.0823 2022/11/03 00:25:56 - mmengine - INFO - Epoch(train) [1009][50/63] lr: 4.1414e-04 eta: 2:11:27 time: 0.6105 data_time: 0.0301 memory: 14901 loss: 0.8519 loss_prob: 0.4352 loss_thr: 0.3397 loss_db: 0.0770 2022/11/03 00:25:59 - mmengine - INFO - Epoch(train) [1009][55/63] lr: 4.1414e-04 eta: 2:11:27 time: 0.6307 data_time: 0.0444 memory: 14901 loss: 0.8952 loss_prob: 0.4550 loss_thr: 0.3593 loss_db: 0.0809 2022/11/03 00:26:03 - mmengine - INFO - Epoch(train) [1009][60/63] lr: 4.1414e-04 eta: 2:11:21 time: 0.6384 data_time: 0.0202 memory: 14901 loss: 0.9114 loss_prob: 0.4612 loss_thr: 0.3708 loss_db: 0.0794 2022/11/03 00:26:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:26:12 - mmengine - INFO - Epoch(train) [1010][5/63] lr: 4.1219e-04 eta: 2:11:21 time: 1.0465 data_time: 0.2659 memory: 14901 loss: 0.8666 loss_prob: 0.4396 loss_thr: 0.3494 loss_db: 0.0777 2022/11/03 00:26:15 - mmengine - INFO - Epoch(train) [1010][10/63] lr: 4.1219e-04 eta: 2:11:13 time: 1.0661 data_time: 0.2671 memory: 14901 loss: 0.8879 loss_prob: 0.4604 loss_thr: 0.3467 loss_db: 0.0808 2022/11/03 00:26:20 - mmengine - INFO - Epoch(train) [1010][15/63] lr: 4.1219e-04 eta: 2:11:13 time: 0.8408 data_time: 0.0070 memory: 14901 loss: 0.9180 loss_prob: 0.4804 loss_thr: 0.3537 loss_db: 0.0840 2022/11/03 00:26:23 - mmengine - INFO - Epoch(train) [1010][20/63] lr: 4.1219e-04 eta: 2:11:06 time: 0.7433 data_time: 0.0059 memory: 14901 loss: 0.9105 loss_prob: 0.4700 loss_thr: 0.3590 loss_db: 0.0815 2022/11/03 00:26:26 - mmengine - INFO - Epoch(train) [1010][25/63] lr: 4.1219e-04 eta: 2:11:06 time: 0.5652 data_time: 0.0128 memory: 14901 loss: 0.8664 loss_prob: 0.4408 loss_thr: 0.3485 loss_db: 0.0771 2022/11/03 00:26:30 - mmengine - INFO - Epoch(train) [1010][30/63] lr: 4.1219e-04 eta: 2:11:00 time: 0.7059 data_time: 0.0431 memory: 14901 loss: 0.9072 loss_prob: 0.4674 loss_thr: 0.3592 loss_db: 0.0806 2022/11/03 00:26:34 - mmengine - INFO - Epoch(train) [1010][35/63] lr: 4.1219e-04 eta: 2:11:00 time: 0.8677 data_time: 0.0358 memory: 14901 loss: 0.8772 loss_prob: 0.4481 loss_thr: 0.3516 loss_db: 0.0776 2022/11/03 00:26:38 - mmengine - INFO - Epoch(train) [1010][40/63] lr: 4.1219e-04 eta: 2:10:54 time: 0.8206 data_time: 0.0083 memory: 14901 loss: 0.9162 loss_prob: 0.4705 loss_thr: 0.3620 loss_db: 0.0837 2022/11/03 00:26:43 - mmengine - INFO - Epoch(train) [1010][45/63] lr: 4.1219e-04 eta: 2:10:54 time: 0.8341 data_time: 0.0085 memory: 14901 loss: 0.9075 loss_prob: 0.4672 loss_thr: 0.3561 loss_db: 0.0842 2022/11/03 00:26:46 - mmengine - INFO - Epoch(train) [1010][50/63] lr: 4.1219e-04 eta: 2:10:47 time: 0.7915 data_time: 0.0176 memory: 14901 loss: 0.8152 loss_prob: 0.4077 loss_thr: 0.3351 loss_db: 0.0724 2022/11/03 00:26:49 - mmengine - INFO - Epoch(train) [1010][55/63] lr: 4.1219e-04 eta: 2:10:47 time: 0.6116 data_time: 0.0252 memory: 14901 loss: 0.9032 loss_prob: 0.4633 loss_thr: 0.3602 loss_db: 0.0798 2022/11/03 00:26:52 - mmengine - INFO - Epoch(train) [1010][60/63] lr: 4.1219e-04 eta: 2:10:41 time: 0.6532 data_time: 0.0142 memory: 14901 loss: 0.9637 loss_prob: 0.5035 loss_thr: 0.3721 loss_db: 0.0881 2022/11/03 00:26:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:27:04 - mmengine - INFO - Epoch(train) [1011][5/63] lr: 4.1023e-04 eta: 2:10:41 time: 1.3468 data_time: 0.3193 memory: 14901 loss: 0.8603 loss_prob: 0.4379 loss_thr: 0.3462 loss_db: 0.0762 2022/11/03 00:27:09 - mmengine - INFO - Epoch(train) [1011][10/63] lr: 4.1023e-04 eta: 2:10:33 time: 1.4467 data_time: 0.3194 memory: 14901 loss: 0.8956 loss_prob: 0.4683 loss_thr: 0.3497 loss_db: 0.0776 2022/11/03 00:27:14 - mmengine - INFO - Epoch(train) [1011][15/63] lr: 4.1023e-04 eta: 2:10:33 time: 0.9708 data_time: 0.0089 memory: 14901 loss: 0.9951 loss_prob: 0.5228 loss_thr: 0.3849 loss_db: 0.0874 2022/11/03 00:27:17 - mmengine - INFO - Epoch(train) [1011][20/63] lr: 4.1023e-04 eta: 2:10:27 time: 0.7680 data_time: 0.0085 memory: 14901 loss: 0.9268 loss_prob: 0.4773 loss_thr: 0.3666 loss_db: 0.0829 2022/11/03 00:27:20 - mmengine - INFO - Epoch(train) [1011][25/63] lr: 4.1023e-04 eta: 2:10:27 time: 0.5691 data_time: 0.0267 memory: 14901 loss: 0.8493 loss_prob: 0.4305 loss_thr: 0.3445 loss_db: 0.0743 2022/11/03 00:27:23 - mmengine - INFO - Epoch(train) [1011][30/63] lr: 4.1023e-04 eta: 2:10:21 time: 0.6498 data_time: 0.0438 memory: 14901 loss: 0.9428 loss_prob: 0.4903 loss_thr: 0.3694 loss_db: 0.0831 2022/11/03 00:27:26 - mmengine - INFO - Epoch(train) [1011][35/63] lr: 4.1023e-04 eta: 2:10:21 time: 0.6678 data_time: 0.0238 memory: 14901 loss: 0.9217 loss_prob: 0.4822 loss_thr: 0.3559 loss_db: 0.0837 2022/11/03 00:27:29 - mmengine - INFO - Epoch(train) [1011][40/63] lr: 4.1023e-04 eta: 2:10:14 time: 0.6093 data_time: 0.0056 memory: 14901 loss: 0.8159 loss_prob: 0.4127 loss_thr: 0.3307 loss_db: 0.0725 2022/11/03 00:27:33 - mmengine - INFO - Epoch(train) [1011][45/63] lr: 4.1023e-04 eta: 2:10:14 time: 0.6371 data_time: 0.0054 memory: 14901 loss: 0.8889 loss_prob: 0.4606 loss_thr: 0.3493 loss_db: 0.0789 2022/11/03 00:27:37 - mmengine - INFO - Epoch(train) [1011][50/63] lr: 4.1023e-04 eta: 2:10:07 time: 0.7212 data_time: 0.0148 memory: 14901 loss: 0.9251 loss_prob: 0.4810 loss_thr: 0.3613 loss_db: 0.0828 2022/11/03 00:27:40 - mmengine - INFO - Epoch(train) [1011][55/63] lr: 4.1023e-04 eta: 2:10:07 time: 0.7191 data_time: 0.0244 memory: 14901 loss: 0.9295 loss_prob: 0.4812 loss_thr: 0.3610 loss_db: 0.0872 2022/11/03 00:27:43 - mmengine - INFO - Epoch(train) [1011][60/63] lr: 4.1023e-04 eta: 2:10:01 time: 0.6186 data_time: 0.0153 memory: 14901 loss: 0.9361 loss_prob: 0.4856 loss_thr: 0.3623 loss_db: 0.0881 2022/11/03 00:27:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:27:52 - mmengine - INFO - Epoch(train) [1012][5/63] lr: 4.0828e-04 eta: 2:10:01 time: 1.0442 data_time: 0.2711 memory: 14901 loss: 0.8453 loss_prob: 0.4312 loss_thr: 0.3387 loss_db: 0.0753 2022/11/03 00:27:56 - mmengine - INFO - Epoch(train) [1012][10/63] lr: 4.0828e-04 eta: 2:09:53 time: 1.1740 data_time: 0.2716 memory: 14901 loss: 0.8532 loss_prob: 0.4444 loss_thr: 0.3310 loss_db: 0.0778 2022/11/03 00:27:59 - mmengine - INFO - Epoch(train) [1012][15/63] lr: 4.0828e-04 eta: 2:09:53 time: 0.7458 data_time: 0.0074 memory: 14901 loss: 0.8124 loss_prob: 0.4233 loss_thr: 0.3156 loss_db: 0.0735 2022/11/03 00:28:02 - mmengine - INFO - Epoch(train) [1012][20/63] lr: 4.0828e-04 eta: 2:09:46 time: 0.6529 data_time: 0.0072 memory: 14901 loss: 0.8509 loss_prob: 0.4435 loss_thr: 0.3304 loss_db: 0.0770 2022/11/03 00:28:06 - mmengine - INFO - Epoch(train) [1012][25/63] lr: 4.0828e-04 eta: 2:09:46 time: 0.6662 data_time: 0.0420 memory: 14901 loss: 0.9410 loss_prob: 0.4951 loss_thr: 0.3614 loss_db: 0.0846 2022/11/03 00:28:09 - mmengine - INFO - Epoch(train) [1012][30/63] lr: 4.0828e-04 eta: 2:09:40 time: 0.6950 data_time: 0.0423 memory: 14901 loss: 0.9458 loss_prob: 0.4942 loss_thr: 0.3670 loss_db: 0.0846 2022/11/03 00:28:12 - mmengine - INFO - Epoch(train) [1012][35/63] lr: 4.0828e-04 eta: 2:09:40 time: 0.6043 data_time: 0.0067 memory: 14901 loss: 0.9066 loss_prob: 0.4682 loss_thr: 0.3558 loss_db: 0.0826 2022/11/03 00:28:15 - mmengine - INFO - Epoch(train) [1012][40/63] lr: 4.0828e-04 eta: 2:09:33 time: 0.5600 data_time: 0.0058 memory: 14901 loss: 0.9715 loss_prob: 0.5031 loss_thr: 0.3807 loss_db: 0.0877 2022/11/03 00:28:19 - mmengine - INFO - Epoch(train) [1012][45/63] lr: 4.0828e-04 eta: 2:09:33 time: 0.6896 data_time: 0.0055 memory: 14901 loss: 1.0152 loss_prob: 0.5301 loss_thr: 0.3925 loss_db: 0.0926 2022/11/03 00:28:23 - mmengine - INFO - Epoch(train) [1012][50/63] lr: 4.0828e-04 eta: 2:09:27 time: 0.7846 data_time: 0.0221 memory: 14901 loss: 0.9726 loss_prob: 0.5075 loss_thr: 0.3767 loss_db: 0.0884 2022/11/03 00:28:26 - mmengine - INFO - Epoch(train) [1012][55/63] lr: 4.0828e-04 eta: 2:09:27 time: 0.6770 data_time: 0.0234 memory: 14901 loss: 0.9600 loss_prob: 0.5006 loss_thr: 0.3749 loss_db: 0.0846 2022/11/03 00:28:29 - mmengine - INFO - Epoch(train) [1012][60/63] lr: 4.0828e-04 eta: 2:09:20 time: 0.5982 data_time: 0.0064 memory: 14901 loss: 0.9219 loss_prob: 0.4705 loss_thr: 0.3694 loss_db: 0.0820 2022/11/03 00:28:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:28:38 - mmengine - INFO - Epoch(train) [1013][5/63] lr: 4.0633e-04 eta: 2:09:20 time: 1.0974 data_time: 0.2937 memory: 14901 loss: 0.9493 loss_prob: 0.4879 loss_thr: 0.3756 loss_db: 0.0858 2022/11/03 00:28:42 - mmengine - INFO - Epoch(train) [1013][10/63] lr: 4.0633e-04 eta: 2:09:12 time: 1.1984 data_time: 0.2946 memory: 14901 loss: 0.8882 loss_prob: 0.4541 loss_thr: 0.3536 loss_db: 0.0805 2022/11/03 00:28:46 - mmengine - INFO - Epoch(train) [1013][15/63] lr: 4.0633e-04 eta: 2:09:12 time: 0.7819 data_time: 0.0077 memory: 14901 loss: 0.9821 loss_prob: 0.5280 loss_thr: 0.3658 loss_db: 0.0884 2022/11/03 00:28:50 - mmengine - INFO - Epoch(train) [1013][20/63] lr: 4.0633e-04 eta: 2:09:06 time: 0.8130 data_time: 0.0076 memory: 14901 loss: 0.8962 loss_prob: 0.4794 loss_thr: 0.3372 loss_db: 0.0796 2022/11/03 00:28:54 - mmengine - INFO - Epoch(train) [1013][25/63] lr: 4.0633e-04 eta: 2:09:06 time: 0.8133 data_time: 0.0162 memory: 14901 loss: 0.8060 loss_prob: 0.4097 loss_thr: 0.3247 loss_db: 0.0717 2022/11/03 00:28:58 - mmengine - INFO - Epoch(train) [1013][30/63] lr: 4.0633e-04 eta: 2:09:00 time: 0.7085 data_time: 0.0496 memory: 14901 loss: 0.9285 loss_prob: 0.4825 loss_thr: 0.3611 loss_db: 0.0850 2022/11/03 00:29:01 - mmengine - INFO - Epoch(train) [1013][35/63] lr: 4.0633e-04 eta: 2:09:00 time: 0.6404 data_time: 0.0393 memory: 14901 loss: 0.9719 loss_prob: 0.5073 loss_thr: 0.3749 loss_db: 0.0897 2022/11/03 00:29:05 - mmengine - INFO - Epoch(train) [1013][40/63] lr: 4.0633e-04 eta: 2:08:53 time: 0.7048 data_time: 0.0083 memory: 14901 loss: 0.8765 loss_prob: 0.4466 loss_thr: 0.3525 loss_db: 0.0774 2022/11/03 00:29:09 - mmengine - INFO - Epoch(train) [1013][45/63] lr: 4.0633e-04 eta: 2:08:53 time: 0.8006 data_time: 0.0082 memory: 14901 loss: 0.8318 loss_prob: 0.4200 loss_thr: 0.3387 loss_db: 0.0732 2022/11/03 00:29:13 - mmengine - INFO - Epoch(train) [1013][50/63] lr: 4.0633e-04 eta: 2:08:47 time: 0.8675 data_time: 0.0318 memory: 14901 loss: 0.8879 loss_prob: 0.4565 loss_thr: 0.3519 loss_db: 0.0795 2022/11/03 00:29:16 - mmengine - INFO - Epoch(train) [1013][55/63] lr: 4.0633e-04 eta: 2:08:47 time: 0.7122 data_time: 0.0324 memory: 14901 loss: 1.0344 loss_prob: 0.5482 loss_thr: 0.3950 loss_db: 0.0911 2022/11/03 00:29:19 - mmengine - INFO - Epoch(train) [1013][60/63] lr: 4.0633e-04 eta: 2:08:40 time: 0.6195 data_time: 0.0083 memory: 14901 loss: 1.0703 loss_prob: 0.5672 loss_thr: 0.4066 loss_db: 0.0965 2022/11/03 00:29:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:29:30 - mmengine - INFO - Epoch(train) [1014][5/63] lr: 4.0437e-04 eta: 2:08:40 time: 1.1572 data_time: 0.2539 memory: 14901 loss: 0.9935 loss_prob: 0.5229 loss_thr: 0.3808 loss_db: 0.0899 2022/11/03 00:29:34 - mmengine - INFO - Epoch(train) [1014][10/63] lr: 4.0437e-04 eta: 2:08:33 time: 1.2313 data_time: 0.2517 memory: 14901 loss: 0.9410 loss_prob: 0.4910 loss_thr: 0.3658 loss_db: 0.0843 2022/11/03 00:29:38 - mmengine - INFO - Epoch(train) [1014][15/63] lr: 4.0437e-04 eta: 2:08:33 time: 0.8314 data_time: 0.0071 memory: 14901 loss: 0.8962 loss_prob: 0.4649 loss_thr: 0.3498 loss_db: 0.0815 2022/11/03 00:29:43 - mmengine - INFO - Epoch(train) [1014][20/63] lr: 4.0437e-04 eta: 2:08:27 time: 0.9112 data_time: 0.0064 memory: 14901 loss: 0.9215 loss_prob: 0.4719 loss_thr: 0.3656 loss_db: 0.0839 2022/11/03 00:29:47 - mmengine - INFO - Epoch(train) [1014][25/63] lr: 4.0437e-04 eta: 2:08:27 time: 0.8611 data_time: 0.0185 memory: 14901 loss: 0.8794 loss_prob: 0.4486 loss_thr: 0.3528 loss_db: 0.0780 2022/11/03 00:29:50 - mmengine - INFO - Epoch(train) [1014][30/63] lr: 4.0437e-04 eta: 2:08:20 time: 0.7518 data_time: 0.0410 memory: 14901 loss: 0.8781 loss_prob: 0.4541 loss_thr: 0.3453 loss_db: 0.0787 2022/11/03 00:29:53 - mmengine - INFO - Epoch(train) [1014][35/63] lr: 4.0437e-04 eta: 2:08:20 time: 0.6449 data_time: 0.0277 memory: 14901 loss: 0.9509 loss_prob: 0.5017 loss_thr: 0.3614 loss_db: 0.0879 2022/11/03 00:29:56 - mmengine - INFO - Epoch(train) [1014][40/63] lr: 4.0437e-04 eta: 2:08:13 time: 0.5758 data_time: 0.0055 memory: 14901 loss: 0.9675 loss_prob: 0.5013 loss_thr: 0.3787 loss_db: 0.0874 2022/11/03 00:30:00 - mmengine - INFO - Epoch(train) [1014][45/63] lr: 4.0437e-04 eta: 2:08:13 time: 0.6932 data_time: 0.0060 memory: 14901 loss: 0.8915 loss_prob: 0.4538 loss_thr: 0.3579 loss_db: 0.0798 2022/11/03 00:30:03 - mmengine - INFO - Epoch(train) [1014][50/63] lr: 4.0437e-04 eta: 2:08:07 time: 0.7285 data_time: 0.0135 memory: 14901 loss: 0.8934 loss_prob: 0.4657 loss_thr: 0.3460 loss_db: 0.0817 2022/11/03 00:30:08 - mmengine - INFO - Epoch(train) [1014][55/63] lr: 4.0437e-04 eta: 2:08:07 time: 0.7637 data_time: 0.0273 memory: 14901 loss: 0.9219 loss_prob: 0.4801 loss_thr: 0.3595 loss_db: 0.0823 2022/11/03 00:30:11 - mmengine - INFO - Epoch(train) [1014][60/63] lr: 4.0437e-04 eta: 2:08:01 time: 0.7975 data_time: 0.0192 memory: 14901 loss: 0.8689 loss_prob: 0.4474 loss_thr: 0.3443 loss_db: 0.0771 2022/11/03 00:30:13 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:30:21 - mmengine - INFO - Epoch(train) [1015][5/63] lr: 4.0241e-04 eta: 2:08:01 time: 1.1521 data_time: 0.2715 memory: 14901 loss: 0.8662 loss_prob: 0.4449 loss_thr: 0.3448 loss_db: 0.0766 2022/11/03 00:30:26 - mmengine - INFO - Epoch(train) [1015][10/63] lr: 4.0241e-04 eta: 2:07:53 time: 1.3000 data_time: 0.2880 memory: 14901 loss: 0.8977 loss_prob: 0.4580 loss_thr: 0.3610 loss_db: 0.0787 2022/11/03 00:30:30 - mmengine - INFO - Epoch(train) [1015][15/63] lr: 4.0241e-04 eta: 2:07:53 time: 0.8986 data_time: 0.0228 memory: 14901 loss: 0.9326 loss_prob: 0.4820 loss_thr: 0.3676 loss_db: 0.0829 2022/11/03 00:30:34 - mmengine - INFO - Epoch(train) [1015][20/63] lr: 4.0241e-04 eta: 2:07:47 time: 0.7807 data_time: 0.0064 memory: 14901 loss: 0.9514 loss_prob: 0.4865 loss_thr: 0.3794 loss_db: 0.0854 2022/11/03 00:30:38 - mmengine - INFO - Epoch(train) [1015][25/63] lr: 4.0241e-04 eta: 2:07:47 time: 0.7217 data_time: 0.0311 memory: 14901 loss: 0.9714 loss_prob: 0.4970 loss_thr: 0.3863 loss_db: 0.0881 2022/11/03 00:30:40 - mmengine - INFO - Epoch(train) [1015][30/63] lr: 4.0241e-04 eta: 2:07:40 time: 0.6492 data_time: 0.0341 memory: 14901 loss: 0.9554 loss_prob: 0.4983 loss_thr: 0.3696 loss_db: 0.0875 2022/11/03 00:30:43 - mmengine - INFO - Epoch(train) [1015][35/63] lr: 4.0241e-04 eta: 2:07:40 time: 0.5606 data_time: 0.0174 memory: 14901 loss: 0.9037 loss_prob: 0.4705 loss_thr: 0.3510 loss_db: 0.0822 2022/11/03 00:30:48 - mmengine - INFO - Epoch(train) [1015][40/63] lr: 4.0241e-04 eta: 2:07:34 time: 0.7979 data_time: 0.0143 memory: 14901 loss: 0.9104 loss_prob: 0.4697 loss_thr: 0.3600 loss_db: 0.0807 2022/11/03 00:30:51 - mmengine - INFO - Epoch(train) [1015][45/63] lr: 4.0241e-04 eta: 2:07:34 time: 0.7683 data_time: 0.0083 memory: 14901 loss: 0.9296 loss_prob: 0.4778 loss_thr: 0.3688 loss_db: 0.0831 2022/11/03 00:30:54 - mmengine - INFO - Epoch(train) [1015][50/63] lr: 4.0241e-04 eta: 2:07:27 time: 0.5648 data_time: 0.0222 memory: 14901 loss: 0.8394 loss_prob: 0.4216 loss_thr: 0.3423 loss_db: 0.0756 2022/11/03 00:30:56 - mmengine - INFO - Epoch(train) [1015][55/63] lr: 4.0241e-04 eta: 2:07:27 time: 0.5527 data_time: 0.0241 memory: 14901 loss: 0.9117 loss_prob: 0.4720 loss_thr: 0.3571 loss_db: 0.0826 2022/11/03 00:31:00 - mmengine - INFO - Epoch(train) [1015][60/63] lr: 4.0241e-04 eta: 2:07:20 time: 0.5779 data_time: 0.0172 memory: 14901 loss: 0.9574 loss_prob: 0.5092 loss_thr: 0.3606 loss_db: 0.0876 2022/11/03 00:31:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:31:08 - mmengine - INFO - Epoch(train) [1016][5/63] lr: 4.0046e-04 eta: 2:07:20 time: 0.9867 data_time: 0.3277 memory: 14901 loss: 0.8981 loss_prob: 0.4696 loss_thr: 0.3483 loss_db: 0.0801 2022/11/03 00:31:12 - mmengine - INFO - Epoch(train) [1016][10/63] lr: 4.0046e-04 eta: 2:07:12 time: 1.0479 data_time: 0.3283 memory: 14901 loss: 0.8826 loss_prob: 0.4586 loss_thr: 0.3458 loss_db: 0.0781 2022/11/03 00:31:16 - mmengine - INFO - Epoch(train) [1016][15/63] lr: 4.0046e-04 eta: 2:07:12 time: 0.7874 data_time: 0.0063 memory: 14901 loss: 0.8257 loss_prob: 0.4190 loss_thr: 0.3338 loss_db: 0.0729 2022/11/03 00:31:19 - mmengine - INFO - Epoch(train) [1016][20/63] lr: 4.0046e-04 eta: 2:07:06 time: 0.7130 data_time: 0.0057 memory: 14901 loss: 0.7860 loss_prob: 0.3928 loss_thr: 0.3231 loss_db: 0.0700 2022/11/03 00:31:22 - mmengine - INFO - Epoch(train) [1016][25/63] lr: 4.0046e-04 eta: 2:07:06 time: 0.6573 data_time: 0.0361 memory: 14901 loss: 0.7739 loss_prob: 0.3852 loss_thr: 0.3205 loss_db: 0.0683 2022/11/03 00:31:26 - mmengine - INFO - Epoch(train) [1016][30/63] lr: 4.0046e-04 eta: 2:06:59 time: 0.6571 data_time: 0.0383 memory: 14901 loss: 0.8456 loss_prob: 0.4221 loss_thr: 0.3500 loss_db: 0.0735 2022/11/03 00:31:29 - mmengine - INFO - Epoch(train) [1016][35/63] lr: 4.0046e-04 eta: 2:06:59 time: 0.6798 data_time: 0.0088 memory: 14901 loss: 0.9484 loss_prob: 0.4858 loss_thr: 0.3777 loss_db: 0.0849 2022/11/03 00:31:32 - mmengine - INFO - Epoch(train) [1016][40/63] lr: 4.0046e-04 eta: 2:06:53 time: 0.6819 data_time: 0.0067 memory: 14901 loss: 0.9751 loss_prob: 0.5096 loss_thr: 0.3760 loss_db: 0.0895 2022/11/03 00:31:37 - mmengine - INFO - Epoch(train) [1016][45/63] lr: 4.0046e-04 eta: 2:06:53 time: 0.7505 data_time: 0.0055 memory: 14901 loss: 0.9685 loss_prob: 0.5037 loss_thr: 0.3765 loss_db: 0.0883 2022/11/03 00:31:41 - mmengine - INFO - Epoch(train) [1016][50/63] lr: 4.0046e-04 eta: 2:06:46 time: 0.8195 data_time: 0.0231 memory: 14901 loss: 0.9545 loss_prob: 0.4936 loss_thr: 0.3733 loss_db: 0.0876 2022/11/03 00:31:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:31:45 - mmengine - INFO - Epoch(train) [1016][55/63] lr: 4.0046e-04 eta: 2:06:46 time: 0.8064 data_time: 0.0257 memory: 14901 loss: 0.8888 loss_prob: 0.4574 loss_thr: 0.3502 loss_db: 0.0812 2022/11/03 00:31:48 - mmengine - INFO - Epoch(train) [1016][60/63] lr: 4.0046e-04 eta: 2:06:40 time: 0.7594 data_time: 0.0102 memory: 14901 loss: 0.8633 loss_prob: 0.4394 loss_thr: 0.3452 loss_db: 0.0787 2022/11/03 00:31:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:31:56 - mmengine - INFO - Epoch(train) [1017][5/63] lr: 3.9850e-04 eta: 2:06:40 time: 0.9110 data_time: 0.2690 memory: 14901 loss: 0.9317 loss_prob: 0.4818 loss_thr: 0.3655 loss_db: 0.0844 2022/11/03 00:32:00 - mmengine - INFO - Epoch(train) [1017][10/63] lr: 3.9850e-04 eta: 2:06:32 time: 0.9605 data_time: 0.2713 memory: 14901 loss: 0.9098 loss_prob: 0.4729 loss_thr: 0.3538 loss_db: 0.0831 2022/11/03 00:32:04 - mmengine - INFO - Epoch(train) [1017][15/63] lr: 3.9850e-04 eta: 2:06:32 time: 0.7724 data_time: 0.0081 memory: 14901 loss: 0.8979 loss_prob: 0.4656 loss_thr: 0.3482 loss_db: 0.0841 2022/11/03 00:32:07 - mmengine - INFO - Epoch(train) [1017][20/63] lr: 3.9850e-04 eta: 2:06:25 time: 0.7120 data_time: 0.0060 memory: 14901 loss: 0.8414 loss_prob: 0.4305 loss_thr: 0.3351 loss_db: 0.0758 2022/11/03 00:32:10 - mmengine - INFO - Epoch(train) [1017][25/63] lr: 3.9850e-04 eta: 2:06:25 time: 0.5824 data_time: 0.0342 memory: 14901 loss: 0.9036 loss_prob: 0.4631 loss_thr: 0.3609 loss_db: 0.0796 2022/11/03 00:32:13 - mmengine - INFO - Epoch(train) [1017][30/63] lr: 3.9850e-04 eta: 2:06:19 time: 0.6799 data_time: 0.0416 memory: 14901 loss: 0.9465 loss_prob: 0.4932 loss_thr: 0.3660 loss_db: 0.0873 2022/11/03 00:32:19 - mmengine - INFO - Epoch(train) [1017][35/63] lr: 3.9850e-04 eta: 2:06:19 time: 0.8632 data_time: 0.0148 memory: 14901 loss: 0.8891 loss_prob: 0.4654 loss_thr: 0.3417 loss_db: 0.0819 2022/11/03 00:32:21 - mmengine - INFO - Epoch(train) [1017][40/63] lr: 3.9850e-04 eta: 2:06:13 time: 0.7867 data_time: 0.0074 memory: 14901 loss: 0.8820 loss_prob: 0.4540 loss_thr: 0.3488 loss_db: 0.0793 2022/11/03 00:32:25 - mmengine - INFO - Epoch(train) [1017][45/63] lr: 3.9850e-04 eta: 2:06:13 time: 0.6345 data_time: 0.0060 memory: 14901 loss: 0.8649 loss_prob: 0.4433 loss_thr: 0.3432 loss_db: 0.0785 2022/11/03 00:32:27 - mmengine - INFO - Epoch(train) [1017][50/63] lr: 3.9850e-04 eta: 2:06:06 time: 0.6089 data_time: 0.0206 memory: 14901 loss: 0.9083 loss_prob: 0.4785 loss_thr: 0.3458 loss_db: 0.0841 2022/11/03 00:32:30 - mmengine - INFO - Epoch(train) [1017][55/63] lr: 3.9850e-04 eta: 2:06:06 time: 0.5351 data_time: 0.0308 memory: 14901 loss: 1.0265 loss_prob: 0.5412 loss_thr: 0.3943 loss_db: 0.0910 2022/11/03 00:32:33 - mmengine - INFO - Epoch(train) [1017][60/63] lr: 3.9850e-04 eta: 2:05:59 time: 0.5434 data_time: 0.0176 memory: 14901 loss: 0.9980 loss_prob: 0.5146 loss_thr: 0.3955 loss_db: 0.0880 2022/11/03 00:32:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:32:42 - mmengine - INFO - Epoch(train) [1018][5/63] lr: 3.9654e-04 eta: 2:05:59 time: 0.9784 data_time: 0.2492 memory: 14901 loss: 0.8735 loss_prob: 0.4594 loss_thr: 0.3352 loss_db: 0.0789 2022/11/03 00:32:46 - mmengine - INFO - Epoch(train) [1018][10/63] lr: 3.9654e-04 eta: 2:05:51 time: 1.1428 data_time: 0.2493 memory: 14901 loss: 0.9198 loss_prob: 0.4924 loss_thr: 0.3463 loss_db: 0.0810 2022/11/03 00:32:50 - mmengine - INFO - Epoch(train) [1018][15/63] lr: 3.9654e-04 eta: 2:05:51 time: 0.8278 data_time: 0.0074 memory: 14901 loss: 0.8552 loss_prob: 0.4449 loss_thr: 0.3348 loss_db: 0.0754 2022/11/03 00:32:54 - mmengine - INFO - Epoch(train) [1018][20/63] lr: 3.9654e-04 eta: 2:05:45 time: 0.8193 data_time: 0.0072 memory: 14901 loss: 0.8657 loss_prob: 0.4509 loss_thr: 0.3367 loss_db: 0.0781 2022/11/03 00:32:57 - mmengine - INFO - Epoch(train) [1018][25/63] lr: 3.9654e-04 eta: 2:05:45 time: 0.6880 data_time: 0.0175 memory: 14901 loss: 0.8603 loss_prob: 0.4486 loss_thr: 0.3339 loss_db: 0.0778 2022/11/03 00:33:01 - mmengine - INFO - Epoch(train) [1018][30/63] lr: 3.9654e-04 eta: 2:05:38 time: 0.6915 data_time: 0.0405 memory: 14901 loss: 0.8367 loss_prob: 0.4294 loss_thr: 0.3302 loss_db: 0.0771 2022/11/03 00:33:05 - mmengine - INFO - Epoch(train) [1018][35/63] lr: 3.9654e-04 eta: 2:05:38 time: 0.8151 data_time: 0.0287 memory: 14901 loss: 0.8684 loss_prob: 0.4462 loss_thr: 0.3421 loss_db: 0.0801 2022/11/03 00:33:08 - mmengine - INFO - Epoch(train) [1018][40/63] lr: 3.9654e-04 eta: 2:05:32 time: 0.7709 data_time: 0.0062 memory: 14901 loss: 0.9199 loss_prob: 0.4658 loss_thr: 0.3731 loss_db: 0.0810 2022/11/03 00:33:12 - mmengine - INFO - Epoch(train) [1018][45/63] lr: 3.9654e-04 eta: 2:05:32 time: 0.7208 data_time: 0.0062 memory: 14901 loss: 0.8936 loss_prob: 0.4482 loss_thr: 0.3674 loss_db: 0.0780 2022/11/03 00:33:16 - mmengine - INFO - Epoch(train) [1018][50/63] lr: 3.9654e-04 eta: 2:05:26 time: 0.7838 data_time: 0.0119 memory: 14901 loss: 0.8488 loss_prob: 0.4331 loss_thr: 0.3412 loss_db: 0.0746 2022/11/03 00:33:20 - mmengine - INFO - Epoch(train) [1018][55/63] lr: 3.9654e-04 eta: 2:05:26 time: 0.8106 data_time: 0.0237 memory: 14901 loss: 0.9523 loss_prob: 0.4961 loss_thr: 0.3721 loss_db: 0.0841 2022/11/03 00:33:23 - mmengine - INFO - Epoch(train) [1018][60/63] lr: 3.9654e-04 eta: 2:05:19 time: 0.6752 data_time: 0.0177 memory: 14901 loss: 1.0176 loss_prob: 0.5380 loss_thr: 0.3861 loss_db: 0.0935 2022/11/03 00:33:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:33:32 - mmengine - INFO - Epoch(train) [1019][5/63] lr: 3.9458e-04 eta: 2:05:19 time: 1.0079 data_time: 0.2131 memory: 14901 loss: 0.9049 loss_prob: 0.4666 loss_thr: 0.3557 loss_db: 0.0826 2022/11/03 00:33:36 - mmengine - INFO - Epoch(train) [1019][10/63] lr: 3.9458e-04 eta: 2:05:11 time: 1.1845 data_time: 0.2268 memory: 14901 loss: 0.8776 loss_prob: 0.4488 loss_thr: 0.3504 loss_db: 0.0783 2022/11/03 00:33:40 - mmengine - INFO - Epoch(train) [1019][15/63] lr: 3.9458e-04 eta: 2:05:11 time: 0.7555 data_time: 0.0221 memory: 14901 loss: 0.8649 loss_prob: 0.4350 loss_thr: 0.3520 loss_db: 0.0779 2022/11/03 00:33:42 - mmengine - INFO - Epoch(train) [1019][20/63] lr: 3.9458e-04 eta: 2:05:05 time: 0.6292 data_time: 0.0143 memory: 14901 loss: 0.8867 loss_prob: 0.4545 loss_thr: 0.3518 loss_db: 0.0803 2022/11/03 00:33:46 - mmengine - INFO - Epoch(train) [1019][25/63] lr: 3.9458e-04 eta: 2:05:05 time: 0.5806 data_time: 0.0385 memory: 14901 loss: 0.9057 loss_prob: 0.4741 loss_thr: 0.3497 loss_db: 0.0819 2022/11/03 00:33:48 - mmengine - INFO - Epoch(train) [1019][30/63] lr: 3.9458e-04 eta: 2:04:58 time: 0.5802 data_time: 0.0376 memory: 14901 loss: 0.9076 loss_prob: 0.4751 loss_thr: 0.3496 loss_db: 0.0830 2022/11/03 00:33:51 - mmengine - INFO - Epoch(train) [1019][35/63] lr: 3.9458e-04 eta: 2:04:58 time: 0.5899 data_time: 0.0237 memory: 14901 loss: 0.9026 loss_prob: 0.4739 loss_thr: 0.3457 loss_db: 0.0830 2022/11/03 00:33:54 - mmengine - INFO - Epoch(train) [1019][40/63] lr: 3.9458e-04 eta: 2:04:51 time: 0.5782 data_time: 0.0208 memory: 14901 loss: 0.9133 loss_prob: 0.4820 loss_thr: 0.3479 loss_db: 0.0833 2022/11/03 00:33:57 - mmengine - INFO - Epoch(train) [1019][45/63] lr: 3.9458e-04 eta: 2:04:51 time: 0.5481 data_time: 0.0118 memory: 14901 loss: 0.9099 loss_prob: 0.4735 loss_thr: 0.3544 loss_db: 0.0820 2022/11/03 00:34:00 - mmengine - INFO - Epoch(train) [1019][50/63] lr: 3.9458e-04 eta: 2:04:45 time: 0.5494 data_time: 0.0156 memory: 14901 loss: 0.9822 loss_prob: 0.5141 loss_thr: 0.3786 loss_db: 0.0896 2022/11/03 00:34:02 - mmengine - INFO - Epoch(train) [1019][55/63] lr: 3.9458e-04 eta: 2:04:45 time: 0.5118 data_time: 0.0143 memory: 14901 loss: 0.9737 loss_prob: 0.5081 loss_thr: 0.3747 loss_db: 0.0910 2022/11/03 00:34:05 - mmengine - INFO - Epoch(train) [1019][60/63] lr: 3.9458e-04 eta: 2:04:38 time: 0.5222 data_time: 0.0155 memory: 14901 loss: 0.8776 loss_prob: 0.4449 loss_thr: 0.3526 loss_db: 0.0801 2022/11/03 00:34:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:34:14 - mmengine - INFO - Epoch(train) [1020][5/63] lr: 3.9261e-04 eta: 2:04:38 time: 1.0216 data_time: 0.2792 memory: 14901 loss: 0.8947 loss_prob: 0.4564 loss_thr: 0.3585 loss_db: 0.0798 2022/11/03 00:34:18 - mmengine - INFO - Epoch(train) [1020][10/63] lr: 3.9261e-04 eta: 2:04:30 time: 1.1761 data_time: 0.2840 memory: 14901 loss: 0.8466 loss_prob: 0.4250 loss_thr: 0.3454 loss_db: 0.0761 2022/11/03 00:34:21 - mmengine - INFO - Epoch(train) [1020][15/63] lr: 3.9261e-04 eta: 2:04:30 time: 0.6850 data_time: 0.0135 memory: 14901 loss: 0.8845 loss_prob: 0.4487 loss_thr: 0.3574 loss_db: 0.0785 2022/11/03 00:34:24 - mmengine - INFO - Epoch(train) [1020][20/63] lr: 3.9261e-04 eta: 2:04:23 time: 0.5665 data_time: 0.0071 memory: 14901 loss: 0.9806 loss_prob: 0.5094 loss_thr: 0.3851 loss_db: 0.0861 2022/11/03 00:34:27 - mmengine - INFO - Epoch(train) [1020][25/63] lr: 3.9261e-04 eta: 2:04:23 time: 0.6521 data_time: 0.0279 memory: 14901 loss: 0.9513 loss_prob: 0.4924 loss_thr: 0.3741 loss_db: 0.0848 2022/11/03 00:34:31 - mmengine - INFO - Epoch(train) [1020][30/63] lr: 3.9261e-04 eta: 2:04:17 time: 0.6987 data_time: 0.0303 memory: 14901 loss: 0.8524 loss_prob: 0.4415 loss_thr: 0.3335 loss_db: 0.0773 2022/11/03 00:34:34 - mmengine - INFO - Epoch(train) [1020][35/63] lr: 3.9261e-04 eta: 2:04:17 time: 0.6182 data_time: 0.0159 memory: 14901 loss: 0.9468 loss_prob: 0.4962 loss_thr: 0.3648 loss_db: 0.0857 2022/11/03 00:34:37 - mmengine - INFO - Epoch(train) [1020][40/63] lr: 3.9261e-04 eta: 2:04:10 time: 0.5997 data_time: 0.0121 memory: 14901 loss: 0.9568 loss_prob: 0.5016 loss_thr: 0.3678 loss_db: 0.0874 2022/11/03 00:34:40 - mmengine - INFO - Epoch(train) [1020][45/63] lr: 3.9261e-04 eta: 2:04:10 time: 0.6051 data_time: 0.0073 memory: 14901 loss: 0.8763 loss_prob: 0.4583 loss_thr: 0.3378 loss_db: 0.0802 2022/11/03 00:34:44 - mmengine - INFO - Epoch(train) [1020][50/63] lr: 3.9261e-04 eta: 2:04:03 time: 0.7067 data_time: 0.0236 memory: 14901 loss: 0.8739 loss_prob: 0.4546 loss_thr: 0.3408 loss_db: 0.0785 2022/11/03 00:34:48 - mmengine - INFO - Epoch(train) [1020][55/63] lr: 3.9261e-04 eta: 2:04:03 time: 0.8389 data_time: 0.0292 memory: 14901 loss: 0.8725 loss_prob: 0.4540 loss_thr: 0.3414 loss_db: 0.0771 2022/11/03 00:34:52 - mmengine - INFO - Epoch(train) [1020][60/63] lr: 3.9261e-04 eta: 2:03:57 time: 0.7809 data_time: 0.0130 memory: 14901 loss: 0.8646 loss_prob: 0.4455 loss_thr: 0.3419 loss_db: 0.0772 2022/11/03 00:34:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:34:53 - mmengine - INFO - Saving checkpoint at 1020 epochs 2022/11/03 00:34:57 - mmengine - INFO - Epoch(val) [1020][5/500] eta: 2:03:57 time: 0.0543 data_time: 0.0073 memory: 14901 2022/11/03 00:34:57 - mmengine - INFO - Epoch(val) [1020][10/500] eta: 0:00:27 time: 0.0559 data_time: 0.0070 memory: 1008 2022/11/03 00:34:57 - mmengine - INFO - Epoch(val) [1020][15/500] eta: 0:00:27 time: 0.0526 data_time: 0.0039 memory: 1008 2022/11/03 00:34:58 - mmengine - INFO - Epoch(val) [1020][20/500] eta: 0:00:26 time: 0.0553 data_time: 0.0049 memory: 1008 2022/11/03 00:34:58 - mmengine - INFO - Epoch(val) [1020][25/500] eta: 0:00:26 time: 0.0519 data_time: 0.0043 memory: 1008 2022/11/03 00:34:58 - mmengine - INFO - Epoch(val) [1020][30/500] eta: 0:00:26 time: 0.0559 data_time: 0.0041 memory: 1008 2022/11/03 00:34:58 - mmengine - INFO - Epoch(val) [1020][35/500] eta: 0:00:26 time: 0.0544 data_time: 0.0041 memory: 1008 2022/11/03 00:34:59 - mmengine - INFO - Epoch(val) [1020][40/500] eta: 0:00:25 time: 0.0553 data_time: 0.0038 memory: 1008 2022/11/03 00:34:59 - mmengine - INFO - Epoch(val) [1020][45/500] eta: 0:00:25 time: 0.0534 data_time: 0.0029 memory: 1008 2022/11/03 00:34:59 - mmengine - INFO - Epoch(val) [1020][50/500] eta: 0:00:21 time: 0.0474 data_time: 0.0030 memory: 1008 2022/11/03 00:34:59 - mmengine - INFO - Epoch(val) [1020][55/500] eta: 0:00:21 time: 0.0478 data_time: 0.0029 memory: 1008 2022/11/03 00:35:00 - mmengine - INFO - Epoch(val) [1020][60/500] eta: 0:00:20 time: 0.0470 data_time: 0.0032 memory: 1008 2022/11/03 00:35:00 - mmengine - INFO - Epoch(val) [1020][65/500] eta: 0:00:20 time: 0.0512 data_time: 0.0034 memory: 1008 2022/11/03 00:35:00 - mmengine - INFO - Epoch(val) [1020][70/500] eta: 0:00:21 time: 0.0503 data_time: 0.0029 memory: 1008 2022/11/03 00:35:00 - mmengine - INFO - Epoch(val) [1020][75/500] eta: 0:00:21 time: 0.0431 data_time: 0.0027 memory: 1008 2022/11/03 00:35:01 - mmengine - INFO - Epoch(val) [1020][80/500] eta: 0:00:17 time: 0.0420 data_time: 0.0028 memory: 1008 2022/11/03 00:35:01 - mmengine - INFO - Epoch(val) [1020][85/500] eta: 0:00:17 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/03 00:35:01 - mmengine - INFO - Epoch(val) [1020][90/500] eta: 0:00:18 time: 0.0444 data_time: 0.0025 memory: 1008 2022/11/03 00:35:01 - mmengine - INFO - Epoch(val) [1020][95/500] eta: 0:00:18 time: 0.0474 data_time: 0.0027 memory: 1008 2022/11/03 00:35:02 - mmengine - INFO - Epoch(val) [1020][100/500] eta: 0:00:17 time: 0.0433 data_time: 0.0031 memory: 1008 2022/11/03 00:35:02 - mmengine - INFO - Epoch(val) [1020][105/500] eta: 0:00:17 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/03 00:35:02 - mmengine - INFO - Epoch(val) [1020][110/500] eta: 0:00:17 time: 0.0440 data_time: 0.0029 memory: 1008 2022/11/03 00:35:02 - mmengine - INFO - Epoch(val) [1020][115/500] eta: 0:00:17 time: 0.0436 data_time: 0.0029 memory: 1008 2022/11/03 00:35:02 - mmengine - INFO - Epoch(val) [1020][120/500] eta: 0:00:15 time: 0.0413 data_time: 0.0028 memory: 1008 2022/11/03 00:35:03 - mmengine - INFO - Epoch(val) [1020][125/500] eta: 0:00:15 time: 0.0410 data_time: 0.0029 memory: 1008 2022/11/03 00:35:03 - mmengine - INFO - Epoch(val) [1020][130/500] eta: 0:00:14 time: 0.0394 data_time: 0.0029 memory: 1008 2022/11/03 00:35:03 - mmengine - INFO - Epoch(val) [1020][135/500] eta: 0:00:14 time: 0.0454 data_time: 0.0052 memory: 1008 2022/11/03 00:35:03 - mmengine - INFO - Epoch(val) [1020][140/500] eta: 0:00:16 time: 0.0455 data_time: 0.0051 memory: 1008 2022/11/03 00:35:03 - mmengine - INFO - Epoch(val) [1020][145/500] eta: 0:00:16 time: 0.0448 data_time: 0.0027 memory: 1008 2022/11/03 00:35:04 - mmengine - INFO - Epoch(val) [1020][150/500] eta: 0:00:16 time: 0.0474 data_time: 0.0028 memory: 1008 2022/11/03 00:35:04 - mmengine - INFO - Epoch(val) [1020][155/500] eta: 0:00:16 time: 0.0487 data_time: 0.0029 memory: 1008 2022/11/03 00:35:04 - mmengine - INFO - Epoch(val) [1020][160/500] eta: 0:00:17 time: 0.0517 data_time: 0.0033 memory: 1008 2022/11/03 00:35:04 - mmengine - INFO - Epoch(val) [1020][165/500] eta: 0:00:17 time: 0.0457 data_time: 0.0031 memory: 1008 2022/11/03 00:35:05 - mmengine - INFO - Epoch(val) [1020][170/500] eta: 0:00:13 time: 0.0423 data_time: 0.0027 memory: 1008 2022/11/03 00:35:05 - mmengine - INFO - Epoch(val) [1020][175/500] eta: 0:00:13 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/03 00:35:05 - mmengine - INFO - Epoch(val) [1020][180/500] eta: 0:00:13 time: 0.0418 data_time: 0.0030 memory: 1008 2022/11/03 00:35:05 - mmengine - INFO - Epoch(val) [1020][185/500] eta: 0:00:13 time: 0.0450 data_time: 0.0029 memory: 1008 2022/11/03 00:35:06 - mmengine - INFO - Epoch(val) [1020][190/500] eta: 0:00:14 time: 0.0466 data_time: 0.0029 memory: 1008 2022/11/03 00:35:06 - mmengine - INFO - Epoch(val) [1020][195/500] eta: 0:00:14 time: 0.0415 data_time: 0.0028 memory: 1008 2022/11/03 00:35:06 - mmengine - INFO - Epoch(val) [1020][200/500] eta: 0:00:14 time: 0.0500 data_time: 0.0028 memory: 1008 2022/11/03 00:35:06 - mmengine - INFO - Epoch(val) [1020][205/500] eta: 0:00:14 time: 0.0503 data_time: 0.0030 memory: 1008 2022/11/03 00:35:06 - mmengine - INFO - Epoch(val) [1020][210/500] eta: 0:00:12 time: 0.0438 data_time: 0.0034 memory: 1008 2022/11/03 00:35:07 - mmengine - INFO - Epoch(val) [1020][215/500] eta: 0:00:12 time: 0.0468 data_time: 0.0034 memory: 1008 2022/11/03 00:35:07 - mmengine - INFO - Epoch(val) [1020][220/500] eta: 0:00:11 time: 0.0424 data_time: 0.0028 memory: 1008 2022/11/03 00:35:07 - mmengine - INFO - Epoch(val) [1020][225/500] eta: 0:00:11 time: 0.0415 data_time: 0.0027 memory: 1008 2022/11/03 00:35:07 - mmengine - INFO - Epoch(val) [1020][230/500] eta: 0:00:11 time: 0.0421 data_time: 0.0027 memory: 1008 2022/11/03 00:35:08 - mmengine - INFO - Epoch(val) [1020][235/500] eta: 0:00:11 time: 0.0421 data_time: 0.0027 memory: 1008 2022/11/03 00:35:08 - mmengine - INFO - Epoch(val) [1020][240/500] eta: 0:00:11 time: 0.0454 data_time: 0.0029 memory: 1008 2022/11/03 00:35:08 - mmengine - INFO - Epoch(val) [1020][245/500] eta: 0:00:11 time: 0.0428 data_time: 0.0028 memory: 1008 2022/11/03 00:35:08 - mmengine - INFO - Epoch(val) [1020][250/500] eta: 0:00:11 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/03 00:35:08 - mmengine - INFO - Epoch(val) [1020][255/500] eta: 0:00:11 time: 0.0477 data_time: 0.0032 memory: 1008 2022/11/03 00:35:09 - mmengine - INFO - Epoch(val) [1020][260/500] eta: 0:00:10 time: 0.0424 data_time: 0.0031 memory: 1008 2022/11/03 00:35:09 - mmengine - INFO - Epoch(val) [1020][265/500] eta: 0:00:10 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/03 00:35:09 - mmengine - INFO - Epoch(val) [1020][270/500] eta: 0:00:10 time: 0.0463 data_time: 0.0030 memory: 1008 2022/11/03 00:35:09 - mmengine - INFO - Epoch(val) [1020][275/500] eta: 0:00:10 time: 0.0473 data_time: 0.0031 memory: 1008 2022/11/03 00:35:10 - mmengine - INFO - Epoch(val) [1020][280/500] eta: 0:00:09 time: 0.0441 data_time: 0.0028 memory: 1008 2022/11/03 00:35:10 - mmengine - INFO - Epoch(val) [1020][285/500] eta: 0:00:09 time: 0.0425 data_time: 0.0026 memory: 1008 2022/11/03 00:35:10 - mmengine - INFO - Epoch(val) [1020][290/500] eta: 0:00:08 time: 0.0413 data_time: 0.0025 memory: 1008 2022/11/03 00:35:10 - mmengine - INFO - Epoch(val) [1020][295/500] eta: 0:00:08 time: 0.0452 data_time: 0.0029 memory: 1008 2022/11/03 00:35:10 - mmengine - INFO - Epoch(val) [1020][300/500] eta: 0:00:08 time: 0.0430 data_time: 0.0034 memory: 1008 2022/11/03 00:35:11 - mmengine - INFO - Epoch(val) [1020][305/500] eta: 0:00:08 time: 0.0425 data_time: 0.0031 memory: 1008 2022/11/03 00:35:11 - mmengine - INFO - Epoch(val) [1020][310/500] eta: 0:00:09 time: 0.0476 data_time: 0.0031 memory: 1008 2022/11/03 00:35:11 - mmengine - INFO - Epoch(val) [1020][315/500] eta: 0:00:09 time: 0.0471 data_time: 0.0030 memory: 1008 2022/11/03 00:35:11 - mmengine - INFO - Epoch(val) [1020][320/500] eta: 0:00:08 time: 0.0454 data_time: 0.0029 memory: 1008 2022/11/03 00:35:12 - mmengine - INFO - Epoch(val) [1020][325/500] eta: 0:00:08 time: 0.0578 data_time: 0.0030 memory: 1008 2022/11/03 00:35:12 - mmengine - INFO - Epoch(val) [1020][330/500] eta: 0:00:09 time: 0.0555 data_time: 0.0029 memory: 1008 2022/11/03 00:35:12 - mmengine - INFO - Epoch(val) [1020][335/500] eta: 0:00:09 time: 0.0418 data_time: 0.0029 memory: 1008 2022/11/03 00:35:12 - mmengine - INFO - Epoch(val) [1020][340/500] eta: 0:00:08 time: 0.0508 data_time: 0.0027 memory: 1008 2022/11/03 00:35:13 - mmengine - INFO - Epoch(val) [1020][345/500] eta: 0:00:08 time: 0.0503 data_time: 0.0027 memory: 1008 2022/11/03 00:35:13 - mmengine - INFO - Epoch(val) [1020][350/500] eta: 0:00:07 time: 0.0479 data_time: 0.0027 memory: 1008 2022/11/03 00:35:13 - mmengine - INFO - Epoch(val) [1020][355/500] eta: 0:00:07 time: 0.0462 data_time: 0.0026 memory: 1008 2022/11/03 00:35:13 - mmengine - INFO - Epoch(val) [1020][360/500] eta: 0:00:05 time: 0.0405 data_time: 0.0028 memory: 1008 2022/11/03 00:35:14 - mmengine - INFO - Epoch(val) [1020][365/500] eta: 0:00:05 time: 0.0423 data_time: 0.0028 memory: 1008 2022/11/03 00:35:14 - mmengine - INFO - Epoch(val) [1020][370/500] eta: 0:00:05 time: 0.0398 data_time: 0.0029 memory: 1008 2022/11/03 00:35:14 - mmengine - INFO - Epoch(val) [1020][375/500] eta: 0:00:05 time: 0.0456 data_time: 0.0037 memory: 1008 2022/11/03 00:35:14 - mmengine - INFO - Epoch(val) [1020][380/500] eta: 0:00:05 time: 0.0499 data_time: 0.0037 memory: 1008 2022/11/03 00:35:14 - mmengine - INFO - Epoch(val) [1020][385/500] eta: 0:00:05 time: 0.0431 data_time: 0.0029 memory: 1008 2022/11/03 00:35:15 - mmengine - INFO - Epoch(val) [1020][390/500] eta: 0:00:04 time: 0.0429 data_time: 0.0027 memory: 1008 2022/11/03 00:35:15 - mmengine - INFO - Epoch(val) [1020][395/500] eta: 0:00:04 time: 0.0426 data_time: 0.0027 memory: 1008 2022/11/03 00:35:15 - mmengine - INFO - Epoch(val) [1020][400/500] eta: 0:00:03 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/03 00:35:15 - mmengine - INFO - Epoch(val) [1020][405/500] eta: 0:00:03 time: 0.0394 data_time: 0.0026 memory: 1008 2022/11/03 00:35:15 - mmengine - INFO - Epoch(val) [1020][410/500] eta: 0:00:03 time: 0.0421 data_time: 0.0027 memory: 1008 2022/11/03 00:35:16 - mmengine - INFO - Epoch(val) [1020][415/500] eta: 0:00:03 time: 0.0439 data_time: 0.0029 memory: 1008 2022/11/03 00:35:16 - mmengine - INFO - Epoch(val) [1020][420/500] eta: 0:00:03 time: 0.0408 data_time: 0.0032 memory: 1008 2022/11/03 00:35:16 - mmengine - INFO - Epoch(val) [1020][425/500] eta: 0:00:03 time: 0.0381 data_time: 0.0030 memory: 1008 2022/11/03 00:35:16 - mmengine - INFO - Epoch(val) [1020][430/500] eta: 0:00:02 time: 0.0409 data_time: 0.0033 memory: 1008 2022/11/03 00:35:16 - mmengine - INFO - Epoch(val) [1020][435/500] eta: 0:00:02 time: 0.0421 data_time: 0.0031 memory: 1008 2022/11/03 00:35:17 - mmengine - INFO - Epoch(val) [1020][440/500] eta: 0:00:02 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/03 00:35:17 - mmengine - INFO - Epoch(val) [1020][445/500] eta: 0:00:02 time: 0.0441 data_time: 0.0032 memory: 1008 2022/11/03 00:35:17 - mmengine - INFO - Epoch(val) [1020][450/500] eta: 0:00:02 time: 0.0456 data_time: 0.0032 memory: 1008 2022/11/03 00:35:17 - mmengine - INFO - Epoch(val) [1020][455/500] eta: 0:00:02 time: 0.0418 data_time: 0.0026 memory: 1008 2022/11/03 00:35:18 - mmengine - INFO - Epoch(val) [1020][460/500] eta: 0:00:01 time: 0.0394 data_time: 0.0027 memory: 1008 2022/11/03 00:35:18 - mmengine - INFO - Epoch(val) [1020][465/500] eta: 0:00:01 time: 0.0390 data_time: 0.0027 memory: 1008 2022/11/03 00:35:18 - mmengine - INFO - Epoch(val) [1020][470/500] eta: 0:00:01 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/03 00:35:18 - mmengine - INFO - Epoch(val) [1020][475/500] eta: 0:00:01 time: 0.0463 data_time: 0.0031 memory: 1008 2022/11/03 00:35:18 - mmengine - INFO - Epoch(val) [1020][480/500] eta: 0:00:00 time: 0.0448 data_time: 0.0033 memory: 1008 2022/11/03 00:35:19 - mmengine - INFO - Epoch(val) [1020][485/500] eta: 0:00:00 time: 0.0431 data_time: 0.0031 memory: 1008 2022/11/03 00:35:19 - mmengine - INFO - Epoch(val) [1020][490/500] eta: 0:00:00 time: 0.0444 data_time: 0.0028 memory: 1008 2022/11/03 00:35:19 - mmengine - INFO - Epoch(val) [1020][495/500] eta: 0:00:00 time: 0.0467 data_time: 0.0028 memory: 1008 2022/11/03 00:35:19 - mmengine - INFO - Epoch(val) [1020][500/500] eta: 0:00:00 time: 0.0428 data_time: 0.0027 memory: 1008 2022/11/03 00:35:19 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8325, precision: 0.7514, hmean: 0.7899 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8325, precision: 0.7990, hmean: 0.8154 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8310, precision: 0.8243, hmean: 0.8276 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8276, precision: 0.8451, hmean: 0.8363 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8190, precision: 0.8755, hmean: 0.8463 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7338, precision: 0.9153, hmean: 0.8145 2022/11/03 00:35:19 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1911, precision: 0.9589, hmean: 0.3187 2022/11/03 00:35:19 - mmengine - INFO - Epoch(val) [1020][500/500] icdar/precision: 0.8755 icdar/recall: 0.8190 icdar/hmean: 0.8463 2022/11/03 00:35:27 - mmengine - INFO - Epoch(train) [1021][5/63] lr: 3.9065e-04 eta: 0:00:00 time: 1.0514 data_time: 0.2795 memory: 14901 loss: 0.9167 loss_prob: 0.4748 loss_thr: 0.3583 loss_db: 0.0836 2022/11/03 00:35:32 - mmengine - INFO - Epoch(train) [1021][10/63] lr: 3.9065e-04 eta: 2:03:49 time: 1.2375 data_time: 0.2895 memory: 14901 loss: 0.8595 loss_prob: 0.4352 loss_thr: 0.3460 loss_db: 0.0783 2022/11/03 00:35:34 - mmengine - INFO - Epoch(train) [1021][15/63] lr: 3.9065e-04 eta: 2:03:49 time: 0.7411 data_time: 0.0186 memory: 14901 loss: 0.8917 loss_prob: 0.4625 loss_thr: 0.3483 loss_db: 0.0810 2022/11/03 00:35:37 - mmengine - INFO - Epoch(train) [1021][20/63] lr: 3.9065e-04 eta: 2:03:42 time: 0.5058 data_time: 0.0093 memory: 14901 loss: 0.8962 loss_prob: 0.4745 loss_thr: 0.3409 loss_db: 0.0808 2022/11/03 00:35:40 - mmengine - INFO - Epoch(train) [1021][25/63] lr: 3.9065e-04 eta: 2:03:42 time: 0.5562 data_time: 0.0209 memory: 14901 loss: 0.9059 loss_prob: 0.4744 loss_thr: 0.3500 loss_db: 0.0815 2022/11/03 00:35:45 - mmengine - INFO - Epoch(train) [1021][30/63] lr: 3.9065e-04 eta: 2:03:36 time: 0.7757 data_time: 0.0351 memory: 14901 loss: 0.9392 loss_prob: 0.4875 loss_thr: 0.3652 loss_db: 0.0865 2022/11/03 00:35:48 - mmengine - INFO - Epoch(train) [1021][35/63] lr: 3.9065e-04 eta: 2:03:36 time: 0.7738 data_time: 0.0283 memory: 14901 loss: 0.9953 loss_prob: 0.5179 loss_thr: 0.3852 loss_db: 0.0922 2022/11/03 00:35:51 - mmengine - INFO - Epoch(train) [1021][40/63] lr: 3.9065e-04 eta: 2:03:30 time: 0.6445 data_time: 0.0187 memory: 14901 loss: 0.9839 loss_prob: 0.5062 loss_thr: 0.3883 loss_db: 0.0894 2022/11/03 00:35:55 - mmengine - INFO - Epoch(train) [1021][45/63] lr: 3.9065e-04 eta: 2:03:30 time: 0.7357 data_time: 0.0130 memory: 14901 loss: 0.9482 loss_prob: 0.4870 loss_thr: 0.3755 loss_db: 0.0857 2022/11/03 00:35:58 - mmengine - INFO - Epoch(train) [1021][50/63] lr: 3.9065e-04 eta: 2:03:23 time: 0.6867 data_time: 0.0162 memory: 14901 loss: 0.8867 loss_prob: 0.4581 loss_thr: 0.3479 loss_db: 0.0807 2022/11/03 00:36:01 - mmengine - INFO - Epoch(train) [1021][55/63] lr: 3.9065e-04 eta: 2:03:23 time: 0.5939 data_time: 0.0207 memory: 14901 loss: 0.8957 loss_prob: 0.4628 loss_thr: 0.3515 loss_db: 0.0813 2022/11/03 00:36:04 - mmengine - INFO - Epoch(train) [1021][60/63] lr: 3.9065e-04 eta: 2:03:16 time: 0.5669 data_time: 0.0180 memory: 14901 loss: 0.9014 loss_prob: 0.4676 loss_thr: 0.3520 loss_db: 0.0817 2022/11/03 00:36:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:36:12 - mmengine - INFO - Epoch(train) [1022][5/63] lr: 3.8869e-04 eta: 2:03:16 time: 0.8957 data_time: 0.2518 memory: 14901 loss: 0.9662 loss_prob: 0.5057 loss_thr: 0.3732 loss_db: 0.0873 2022/11/03 00:36:16 - mmengine - INFO - Epoch(train) [1022][10/63] lr: 3.8869e-04 eta: 2:03:08 time: 1.1052 data_time: 0.2513 memory: 14901 loss: 1.0499 loss_prob: 0.5558 loss_thr: 0.3985 loss_db: 0.0956 2022/11/03 00:36:19 - mmengine - INFO - Epoch(train) [1022][15/63] lr: 3.8869e-04 eta: 2:03:08 time: 0.7460 data_time: 0.0078 memory: 14901 loss: 0.8569 loss_prob: 0.4444 loss_thr: 0.3343 loss_db: 0.0781 2022/11/03 00:36:24 - mmengine - INFO - Epoch(train) [1022][20/63] lr: 3.8869e-04 eta: 2:03:02 time: 0.7896 data_time: 0.0067 memory: 14901 loss: 0.7604 loss_prob: 0.3814 loss_thr: 0.3096 loss_db: 0.0695 2022/11/03 00:36:27 - mmengine - INFO - Epoch(train) [1022][25/63] lr: 3.8869e-04 eta: 2:03:02 time: 0.7896 data_time: 0.0202 memory: 14901 loss: 0.8409 loss_prob: 0.4288 loss_thr: 0.3368 loss_db: 0.0754 2022/11/03 00:36:30 - mmengine - INFO - Epoch(train) [1022][30/63] lr: 3.8869e-04 eta: 2:02:55 time: 0.6387 data_time: 0.0400 memory: 14901 loss: 0.8424 loss_prob: 0.4330 loss_thr: 0.3343 loss_db: 0.0752 2022/11/03 00:36:34 - mmengine - INFO - Epoch(train) [1022][35/63] lr: 3.8869e-04 eta: 2:02:55 time: 0.7253 data_time: 0.0301 memory: 14901 loss: 0.9194 loss_prob: 0.4790 loss_thr: 0.3578 loss_db: 0.0826 2022/11/03 00:36:38 - mmengine - INFO - Epoch(train) [1022][40/63] lr: 3.8869e-04 eta: 2:02:49 time: 0.7954 data_time: 0.0100 memory: 14901 loss: 0.9822 loss_prob: 0.5193 loss_thr: 0.3735 loss_db: 0.0894 2022/11/03 00:36:41 - mmengine - INFO - Epoch(train) [1022][45/63] lr: 3.8869e-04 eta: 2:02:49 time: 0.7179 data_time: 0.0080 memory: 14901 loss: 0.9294 loss_prob: 0.4835 loss_thr: 0.3601 loss_db: 0.0857 2022/11/03 00:36:44 - mmengine - INFO - Epoch(train) [1022][50/63] lr: 3.8869e-04 eta: 2:02:42 time: 0.6088 data_time: 0.0233 memory: 14901 loss: 0.9378 loss_prob: 0.4943 loss_thr: 0.3561 loss_db: 0.0874 2022/11/03 00:36:47 - mmengine - INFO - Epoch(train) [1022][55/63] lr: 3.8869e-04 eta: 2:02:42 time: 0.5500 data_time: 0.0263 memory: 14901 loss: 0.9422 loss_prob: 0.4993 loss_thr: 0.3548 loss_db: 0.0881 2022/11/03 00:36:50 - mmengine - INFO - Epoch(train) [1022][60/63] lr: 3.8869e-04 eta: 2:02:36 time: 0.6189 data_time: 0.0105 memory: 14901 loss: 0.8825 loss_prob: 0.4565 loss_thr: 0.3450 loss_db: 0.0810 2022/11/03 00:36:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:36:59 - mmengine - INFO - Epoch(train) [1023][5/63] lr: 3.8672e-04 eta: 2:02:36 time: 1.0806 data_time: 0.2350 memory: 14901 loss: 0.8969 loss_prob: 0.4537 loss_thr: 0.3628 loss_db: 0.0803 2022/11/03 00:37:04 - mmengine - INFO - Epoch(train) [1023][10/63] lr: 3.8672e-04 eta: 2:02:28 time: 1.1575 data_time: 0.2382 memory: 14901 loss: 0.9070 loss_prob: 0.4590 loss_thr: 0.3660 loss_db: 0.0820 2022/11/03 00:37:07 - mmengine - INFO - Epoch(train) [1023][15/63] lr: 3.8672e-04 eta: 2:02:28 time: 0.7760 data_time: 0.0091 memory: 14901 loss: 1.0144 loss_prob: 0.5430 loss_thr: 0.3808 loss_db: 0.0905 2022/11/03 00:37:10 - mmengine - INFO - Epoch(train) [1023][20/63] lr: 3.8672e-04 eta: 2:02:21 time: 0.6026 data_time: 0.0051 memory: 14901 loss: 0.9973 loss_prob: 0.5390 loss_thr: 0.3680 loss_db: 0.0903 2022/11/03 00:37:12 - mmengine - INFO - Epoch(train) [1023][25/63] lr: 3.8672e-04 eta: 2:02:21 time: 0.5022 data_time: 0.0136 memory: 14901 loss: 0.9477 loss_prob: 0.4869 loss_thr: 0.3737 loss_db: 0.0870 2022/11/03 00:37:15 - mmengine - INFO - Epoch(train) [1023][30/63] lr: 3.8672e-04 eta: 2:02:14 time: 0.5308 data_time: 0.0326 memory: 14901 loss: 1.0153 loss_prob: 0.5352 loss_thr: 0.3867 loss_db: 0.0934 2022/11/03 00:37:18 - mmengine - INFO - Epoch(train) [1023][35/63] lr: 3.8672e-04 eta: 2:02:14 time: 0.5466 data_time: 0.0258 memory: 14901 loss: 0.9580 loss_prob: 0.5045 loss_thr: 0.3669 loss_db: 0.0866 2022/11/03 00:37:21 - mmengine - INFO - Epoch(train) [1023][40/63] lr: 3.8672e-04 eta: 2:02:08 time: 0.6414 data_time: 0.0069 memory: 14901 loss: 0.9059 loss_prob: 0.4718 loss_thr: 0.3526 loss_db: 0.0815 2022/11/03 00:37:24 - mmengine - INFO - Epoch(train) [1023][45/63] lr: 3.8672e-04 eta: 2:02:08 time: 0.6744 data_time: 0.0052 memory: 14901 loss: 0.8489 loss_prob: 0.4396 loss_thr: 0.3301 loss_db: 0.0793 2022/11/03 00:37:27 - mmengine - INFO - Epoch(train) [1023][50/63] lr: 3.8672e-04 eta: 2:02:01 time: 0.5699 data_time: 0.0236 memory: 14901 loss: 0.8376 loss_prob: 0.4292 loss_thr: 0.3301 loss_db: 0.0784 2022/11/03 00:37:30 - mmengine - INFO - Epoch(train) [1023][55/63] lr: 3.8672e-04 eta: 2:02:01 time: 0.5803 data_time: 0.0238 memory: 14901 loss: 0.8616 loss_prob: 0.4457 loss_thr: 0.3373 loss_db: 0.0786 2022/11/03 00:37:33 - mmengine - INFO - Epoch(train) [1023][60/63] lr: 3.8672e-04 eta: 2:01:54 time: 0.6122 data_time: 0.0073 memory: 14901 loss: 0.8748 loss_prob: 0.4511 loss_thr: 0.3469 loss_db: 0.0768 2022/11/03 00:37:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:37:41 - mmengine - INFO - Epoch(train) [1024][5/63] lr: 3.8476e-04 eta: 2:01:54 time: 0.9244 data_time: 0.2559 memory: 14901 loss: 0.9544 loss_prob: 0.5000 loss_thr: 0.3691 loss_db: 0.0853 2022/11/03 00:37:44 - mmengine - INFO - Epoch(train) [1024][10/63] lr: 3.8476e-04 eta: 2:01:46 time: 0.9197 data_time: 0.2555 memory: 14901 loss: 0.9035 loss_prob: 0.4672 loss_thr: 0.3521 loss_db: 0.0842 2022/11/03 00:37:47 - mmengine - INFO - Epoch(train) [1024][15/63] lr: 3.8476e-04 eta: 2:01:46 time: 0.5721 data_time: 0.0065 memory: 14901 loss: 0.8906 loss_prob: 0.4519 loss_thr: 0.3576 loss_db: 0.0811 2022/11/03 00:37:50 - mmengine - INFO - Epoch(train) [1024][20/63] lr: 3.8476e-04 eta: 2:01:39 time: 0.5895 data_time: 0.0070 memory: 14901 loss: 0.8917 loss_prob: 0.4574 loss_thr: 0.3539 loss_db: 0.0805 2022/11/03 00:37:53 - mmengine - INFO - Epoch(train) [1024][25/63] lr: 3.8476e-04 eta: 2:01:39 time: 0.5540 data_time: 0.0082 memory: 14901 loss: 0.9385 loss_prob: 0.4990 loss_thr: 0.3536 loss_db: 0.0860 2022/11/03 00:37:56 - mmengine - INFO - Epoch(train) [1024][30/63] lr: 3.8476e-04 eta: 2:01:33 time: 0.6221 data_time: 0.0345 memory: 14901 loss: 1.0104 loss_prob: 0.5470 loss_thr: 0.3731 loss_db: 0.0903 2022/11/03 00:38:00 - mmengine - INFO - Epoch(train) [1024][35/63] lr: 3.8476e-04 eta: 2:01:33 time: 0.6950 data_time: 0.0333 memory: 14901 loss: 0.9625 loss_prob: 0.5096 loss_thr: 0.3677 loss_db: 0.0852 2022/11/03 00:38:05 - mmengine - INFO - Epoch(train) [1024][40/63] lr: 3.8476e-04 eta: 2:01:26 time: 0.8395 data_time: 0.0075 memory: 14901 loss: 0.9093 loss_prob: 0.4587 loss_thr: 0.3701 loss_db: 0.0805 2022/11/03 00:38:08 - mmengine - INFO - Epoch(train) [1024][45/63] lr: 3.8476e-04 eta: 2:01:26 time: 0.8090 data_time: 0.0085 memory: 14901 loss: 0.8420 loss_prob: 0.4255 loss_thr: 0.3412 loss_db: 0.0753 2022/11/03 00:38:11 - mmengine - INFO - Epoch(train) [1024][50/63] lr: 3.8476e-04 eta: 2:01:20 time: 0.6136 data_time: 0.0226 memory: 14901 loss: 0.8692 loss_prob: 0.4592 loss_thr: 0.3301 loss_db: 0.0799 2022/11/03 00:38:15 - mmengine - INFO - Epoch(train) [1024][55/63] lr: 3.8476e-04 eta: 2:01:20 time: 0.7080 data_time: 0.0298 memory: 14901 loss: 0.9383 loss_prob: 0.4974 loss_thr: 0.3547 loss_db: 0.0863 2022/11/03 00:38:19 - mmengine - INFO - Epoch(train) [1024][60/63] lr: 3.8476e-04 eta: 2:01:14 time: 0.8637 data_time: 0.0143 memory: 14901 loss: 0.8956 loss_prob: 0.4618 loss_thr: 0.3511 loss_db: 0.0826 2022/11/03 00:38:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:38:30 - mmengine - INFO - Epoch(train) [1025][5/63] lr: 3.8279e-04 eta: 2:01:14 time: 1.3022 data_time: 0.2851 memory: 14901 loss: 0.9472 loss_prob: 0.4975 loss_thr: 0.3630 loss_db: 0.0867 2022/11/03 00:38:34 - mmengine - INFO - Epoch(train) [1025][10/63] lr: 3.8279e-04 eta: 2:01:06 time: 1.2982 data_time: 0.2858 memory: 14901 loss: 0.9354 loss_prob: 0.4932 loss_thr: 0.3564 loss_db: 0.0858 2022/11/03 00:38:38 - mmengine - INFO - Epoch(train) [1025][15/63] lr: 3.8279e-04 eta: 2:01:06 time: 0.7842 data_time: 0.0071 memory: 14901 loss: 0.9610 loss_prob: 0.5037 loss_thr: 0.3718 loss_db: 0.0856 2022/11/03 00:38:41 - mmengine - INFO - Epoch(train) [1025][20/63] lr: 3.8279e-04 eta: 2:00:59 time: 0.6580 data_time: 0.0062 memory: 14901 loss: 0.9948 loss_prob: 0.5189 loss_thr: 0.3873 loss_db: 0.0886 2022/11/03 00:38:45 - mmengine - INFO - Epoch(train) [1025][25/63] lr: 3.8279e-04 eta: 2:00:59 time: 0.6878 data_time: 0.0404 memory: 14901 loss: 1.0030 loss_prob: 0.5231 loss_thr: 0.3884 loss_db: 0.0915 2022/11/03 00:38:48 - mmengine - INFO - Epoch(train) [1025][30/63] lr: 3.8279e-04 eta: 2:00:53 time: 0.6701 data_time: 0.0438 memory: 14901 loss: 0.9022 loss_prob: 0.4668 loss_thr: 0.3532 loss_db: 0.0822 2022/11/03 00:38:51 - mmengine - INFO - Epoch(train) [1025][35/63] lr: 3.8279e-04 eta: 2:00:53 time: 0.5892 data_time: 0.0097 memory: 14901 loss: 0.8658 loss_prob: 0.4481 loss_thr: 0.3379 loss_db: 0.0798 2022/11/03 00:38:54 - mmengine - INFO - Epoch(train) [1025][40/63] lr: 3.8279e-04 eta: 2:00:46 time: 0.6638 data_time: 0.0071 memory: 14901 loss: 0.9159 loss_prob: 0.4797 loss_thr: 0.3519 loss_db: 0.0843 2022/11/03 00:38:58 - mmengine - INFO - Epoch(train) [1025][45/63] lr: 3.8279e-04 eta: 2:00:46 time: 0.7520 data_time: 0.0079 memory: 14901 loss: 0.9957 loss_prob: 0.5256 loss_thr: 0.3797 loss_db: 0.0904 2022/11/03 00:39:02 - mmengine - INFO - Epoch(train) [1025][50/63] lr: 3.8279e-04 eta: 2:00:40 time: 0.7937 data_time: 0.0252 memory: 14901 loss: 1.0112 loss_prob: 0.5358 loss_thr: 0.3821 loss_db: 0.0934 2022/11/03 00:39:05 - mmengine - INFO - Epoch(train) [1025][55/63] lr: 3.8279e-04 eta: 2:00:40 time: 0.6913 data_time: 0.0259 memory: 14901 loss: 0.9231 loss_prob: 0.4831 loss_thr: 0.3551 loss_db: 0.0848 2022/11/03 00:39:07 - mmengine - INFO - Epoch(train) [1025][60/63] lr: 3.8279e-04 eta: 2:00:33 time: 0.5225 data_time: 0.0080 memory: 14901 loss: 0.9063 loss_prob: 0.4732 loss_thr: 0.3511 loss_db: 0.0820 2022/11/03 00:39:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:39:17 - mmengine - INFO - Epoch(train) [1026][5/63] lr: 3.8082e-04 eta: 2:00:33 time: 1.0091 data_time: 0.2506 memory: 14901 loss: 0.8359 loss_prob: 0.4234 loss_thr: 0.3368 loss_db: 0.0758 2022/11/03 00:39:19 - mmengine - INFO - Epoch(train) [1026][10/63] lr: 3.8082e-04 eta: 2:00:25 time: 1.0687 data_time: 0.2552 memory: 14901 loss: 0.8818 loss_prob: 0.4540 loss_thr: 0.3477 loss_db: 0.0801 2022/11/03 00:39:22 - mmengine - INFO - Epoch(train) [1026][15/63] lr: 3.8082e-04 eta: 2:00:25 time: 0.5382 data_time: 0.0104 memory: 14901 loss: 0.9247 loss_prob: 0.4848 loss_thr: 0.3573 loss_db: 0.0825 2022/11/03 00:39:25 - mmengine - INFO - Epoch(train) [1026][20/63] lr: 3.8082e-04 eta: 2:00:18 time: 0.5282 data_time: 0.0065 memory: 14901 loss: 0.9692 loss_prob: 0.5015 loss_thr: 0.3817 loss_db: 0.0861 2022/11/03 00:39:28 - mmengine - INFO - Epoch(train) [1026][25/63] lr: 3.8082e-04 eta: 2:00:18 time: 0.5845 data_time: 0.0262 memory: 14901 loss: 0.9283 loss_prob: 0.4715 loss_thr: 0.3726 loss_db: 0.0842 2022/11/03 00:39:32 - mmengine - INFO - Epoch(train) [1026][30/63] lr: 3.8082e-04 eta: 2:00:12 time: 0.7051 data_time: 0.0519 memory: 14901 loss: 0.9070 loss_prob: 0.4636 loss_thr: 0.3616 loss_db: 0.0817 2022/11/03 00:39:36 - mmengine - INFO - Epoch(train) [1026][35/63] lr: 3.8082e-04 eta: 2:00:12 time: 0.8459 data_time: 0.0321 memory: 14901 loss: 1.0192 loss_prob: 0.5603 loss_thr: 0.3657 loss_db: 0.0932 2022/11/03 00:39:41 - mmengine - INFO - Epoch(train) [1026][40/63] lr: 3.8082e-04 eta: 2:00:06 time: 0.8982 data_time: 0.0065 memory: 14901 loss: 1.0256 loss_prob: 0.5656 loss_thr: 0.3666 loss_db: 0.0934 2022/11/03 00:39:44 - mmengine - INFO - Epoch(train) [1026][45/63] lr: 3.8082e-04 eta: 2:00:06 time: 0.8023 data_time: 0.0066 memory: 14901 loss: 0.9608 loss_prob: 0.5026 loss_thr: 0.3731 loss_db: 0.0850 2022/11/03 00:39:47 - mmengine - INFO - Epoch(train) [1026][50/63] lr: 3.8082e-04 eta: 1:59:59 time: 0.6039 data_time: 0.0158 memory: 14901 loss: 0.9288 loss_prob: 0.4807 loss_thr: 0.3654 loss_db: 0.0826 2022/11/03 00:39:49 - mmengine - INFO - Epoch(train) [1026][55/63] lr: 3.8082e-04 eta: 1:59:59 time: 0.5009 data_time: 0.0215 memory: 14901 loss: 0.9122 loss_prob: 0.4750 loss_thr: 0.3556 loss_db: 0.0815 2022/11/03 00:39:52 - mmengine - INFO - Epoch(train) [1026][60/63] lr: 3.8082e-04 eta: 1:59:52 time: 0.4727 data_time: 0.0114 memory: 14901 loss: 0.9810 loss_prob: 0.5193 loss_thr: 0.3745 loss_db: 0.0872 2022/11/03 00:39:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:39:58 - mmengine - INFO - Epoch(train) [1027][5/63] lr: 3.7885e-04 eta: 1:59:52 time: 0.7419 data_time: 0.1959 memory: 14901 loss: 0.9679 loss_prob: 0.4957 loss_thr: 0.3846 loss_db: 0.0876 2022/11/03 00:40:01 - mmengine - INFO - Epoch(train) [1027][10/63] lr: 3.7885e-04 eta: 1:59:43 time: 0.8035 data_time: 0.1970 memory: 14901 loss: 0.8646 loss_prob: 0.4257 loss_thr: 0.3616 loss_db: 0.0773 2022/11/03 00:40:03 - mmengine - INFO - Epoch(train) [1027][15/63] lr: 3.7885e-04 eta: 1:59:43 time: 0.5136 data_time: 0.0058 memory: 14901 loss: 0.9169 loss_prob: 0.4696 loss_thr: 0.3658 loss_db: 0.0815 2022/11/03 00:40:06 - mmengine - INFO - Epoch(train) [1027][20/63] lr: 3.7885e-04 eta: 1:59:37 time: 0.4699 data_time: 0.0046 memory: 14901 loss: 1.0108 loss_prob: 0.5270 loss_thr: 0.3920 loss_db: 0.0918 2022/11/03 00:40:08 - mmengine - INFO - Epoch(train) [1027][25/63] lr: 3.7885e-04 eta: 1:59:37 time: 0.4917 data_time: 0.0231 memory: 14901 loss: 0.9083 loss_prob: 0.4651 loss_thr: 0.3606 loss_db: 0.0826 2022/11/03 00:40:11 - mmengine - INFO - Epoch(train) [1027][30/63] lr: 3.7885e-04 eta: 1:59:30 time: 0.5516 data_time: 0.0297 memory: 14901 loss: 0.8817 loss_prob: 0.4495 loss_thr: 0.3534 loss_db: 0.0789 2022/11/03 00:40:15 - mmengine - INFO - Epoch(train) [1027][35/63] lr: 3.7885e-04 eta: 1:59:30 time: 0.7341 data_time: 0.0122 memory: 14901 loss: 0.9327 loss_prob: 0.4797 loss_thr: 0.3706 loss_db: 0.0824 2022/11/03 00:40:25 - mmengine - INFO - Epoch(train) [1027][40/63] lr: 3.7885e-04 eta: 1:59:24 time: 1.3916 data_time: 0.0092 memory: 14901 loss: 0.8569 loss_prob: 0.4464 loss_thr: 0.3362 loss_db: 0.0744 2022/11/03 00:40:34 - mmengine - INFO - Epoch(train) [1027][45/63] lr: 3.7885e-04 eta: 1:59:24 time: 1.8638 data_time: 0.0105 memory: 14901 loss: 0.8431 loss_prob: 0.4432 loss_thr: 0.3237 loss_db: 0.0762 2022/11/03 00:40:41 - mmengine - INFO - Epoch(train) [1027][50/63] lr: 3.7885e-04 eta: 1:59:19 time: 1.5656 data_time: 0.0338 memory: 14901 loss: 0.9089 loss_prob: 0.4764 loss_thr: 0.3489 loss_db: 0.0835 2022/11/03 00:40:44 - mmengine - INFO - Epoch(train) [1027][55/63] lr: 3.7885e-04 eta: 1:59:19 time: 0.9896 data_time: 0.0405 memory: 14901 loss: 0.9100 loss_prob: 0.4694 loss_thr: 0.3598 loss_db: 0.0808 2022/11/03 00:40:47 - mmengine - INFO - Epoch(train) [1027][60/63] lr: 3.7885e-04 eta: 1:59:13 time: 0.6168 data_time: 0.0163 memory: 14901 loss: 0.8956 loss_prob: 0.4542 loss_thr: 0.3605 loss_db: 0.0810 2022/11/03 00:40:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:40:56 - mmengine - INFO - Epoch(train) [1028][5/63] lr: 3.7688e-04 eta: 1:59:13 time: 0.9943 data_time: 0.2562 memory: 14901 loss: 0.9685 loss_prob: 0.4969 loss_thr: 0.3845 loss_db: 0.0871 2022/11/03 00:40:59 - mmengine - INFO - Epoch(train) [1028][10/63] lr: 3.7688e-04 eta: 1:59:05 time: 1.0946 data_time: 0.2571 memory: 14901 loss: 0.9045 loss_prob: 0.4662 loss_thr: 0.3548 loss_db: 0.0835 2022/11/03 00:41:04 - mmengine - INFO - Epoch(train) [1028][15/63] lr: 3.7688e-04 eta: 1:59:05 time: 0.8471 data_time: 0.0079 memory: 14901 loss: 0.8746 loss_prob: 0.4498 loss_thr: 0.3458 loss_db: 0.0790 2022/11/03 00:41:07 - mmengine - INFO - Epoch(train) [1028][20/63] lr: 3.7688e-04 eta: 1:58:58 time: 0.8134 data_time: 0.0064 memory: 14901 loss: 0.9147 loss_prob: 0.4738 loss_thr: 0.3589 loss_db: 0.0821 2022/11/03 00:41:11 - mmengine - INFO - Epoch(train) [1028][25/63] lr: 3.7688e-04 eta: 1:58:58 time: 0.6985 data_time: 0.0245 memory: 14901 loss: 0.8819 loss_prob: 0.4553 loss_thr: 0.3476 loss_db: 0.0791 2022/11/03 00:41:15 - mmengine - INFO - Epoch(train) [1028][30/63] lr: 3.7688e-04 eta: 1:58:52 time: 0.7853 data_time: 0.0394 memory: 14901 loss: 0.8358 loss_prob: 0.4256 loss_thr: 0.3353 loss_db: 0.0748 2022/11/03 00:41:19 - mmengine - INFO - Epoch(train) [1028][35/63] lr: 3.7688e-04 eta: 1:58:52 time: 0.7688 data_time: 0.0203 memory: 14901 loss: 0.7996 loss_prob: 0.4074 loss_thr: 0.3202 loss_db: 0.0720 2022/11/03 00:41:23 - mmengine - INFO - Epoch(train) [1028][40/63] lr: 3.7688e-04 eta: 1:58:46 time: 0.7853 data_time: 0.0071 memory: 14901 loss: 0.8435 loss_prob: 0.4344 loss_thr: 0.3331 loss_db: 0.0760 2022/11/03 00:41:27 - mmengine - INFO - Epoch(train) [1028][45/63] lr: 3.7688e-04 eta: 1:58:46 time: 0.7695 data_time: 0.0076 memory: 14901 loss: 0.8669 loss_prob: 0.4471 loss_thr: 0.3410 loss_db: 0.0788 2022/11/03 00:41:30 - mmengine - INFO - Epoch(train) [1028][50/63] lr: 3.7688e-04 eta: 1:58:39 time: 0.6516 data_time: 0.0303 memory: 14901 loss: 0.8339 loss_prob: 0.4321 loss_thr: 0.3251 loss_db: 0.0767 2022/11/03 00:41:33 - mmengine - INFO - Epoch(train) [1028][55/63] lr: 3.7688e-04 eta: 1:58:39 time: 0.6561 data_time: 0.0297 memory: 14901 loss: 0.8779 loss_prob: 0.4501 loss_thr: 0.3492 loss_db: 0.0786 2022/11/03 00:41:37 - mmengine - INFO - Epoch(train) [1028][60/63] lr: 3.7688e-04 eta: 1:58:33 time: 0.6949 data_time: 0.0060 memory: 14901 loss: 0.8800 loss_prob: 0.4517 loss_thr: 0.3507 loss_db: 0.0776 2022/11/03 00:41:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:41:44 - mmengine - INFO - Epoch(train) [1029][5/63] lr: 3.7491e-04 eta: 1:58:33 time: 0.8457 data_time: 0.2692 memory: 14901 loss: 0.8842 loss_prob: 0.4575 loss_thr: 0.3467 loss_db: 0.0800 2022/11/03 00:41:47 - mmengine - INFO - Epoch(train) [1029][10/63] lr: 3.7491e-04 eta: 1:58:24 time: 0.9485 data_time: 0.2740 memory: 14901 loss: 0.9228 loss_prob: 0.4767 loss_thr: 0.3618 loss_db: 0.0843 2022/11/03 00:41:51 - mmengine - INFO - Epoch(train) [1029][15/63] lr: 3.7491e-04 eta: 1:58:24 time: 0.6776 data_time: 0.0127 memory: 14901 loss: 0.9601 loss_prob: 0.5033 loss_thr: 0.3697 loss_db: 0.0870 2022/11/03 00:41:55 - mmengine - INFO - Epoch(train) [1029][20/63] lr: 3.7491e-04 eta: 1:58:18 time: 0.7881 data_time: 0.0078 memory: 14901 loss: 1.0048 loss_prob: 0.5294 loss_thr: 0.3845 loss_db: 0.0908 2022/11/03 00:42:00 - mmengine - INFO - Epoch(train) [1029][25/63] lr: 3.7491e-04 eta: 1:58:18 time: 0.8967 data_time: 0.0214 memory: 14901 loss: 0.9356 loss_prob: 0.4816 loss_thr: 0.3698 loss_db: 0.0843 2022/11/03 00:42:04 - mmengine - INFO - Epoch(train) [1029][30/63] lr: 3.7491e-04 eta: 1:58:12 time: 0.8397 data_time: 0.0399 memory: 14901 loss: 0.8050 loss_prob: 0.4035 loss_thr: 0.3305 loss_db: 0.0710 2022/11/03 00:42:07 - mmengine - INFO - Epoch(train) [1029][35/63] lr: 3.7491e-04 eta: 1:58:12 time: 0.6909 data_time: 0.0305 memory: 14901 loss: 0.8358 loss_prob: 0.4251 loss_thr: 0.3350 loss_db: 0.0758 2022/11/03 00:42:10 - mmengine - INFO - Epoch(train) [1029][40/63] lr: 3.7491e-04 eta: 1:58:05 time: 0.6183 data_time: 0.0141 memory: 14901 loss: 0.8652 loss_prob: 0.4444 loss_thr: 0.3407 loss_db: 0.0801 2022/11/03 00:42:15 - mmengine - INFO - Epoch(train) [1029][45/63] lr: 3.7491e-04 eta: 1:58:05 time: 0.8014 data_time: 0.0090 memory: 14901 loss: 0.8619 loss_prob: 0.4412 loss_thr: 0.3427 loss_db: 0.0779 2022/11/03 00:42:19 - mmengine - INFO - Epoch(train) [1029][50/63] lr: 3.7491e-04 eta: 1:57:59 time: 0.8758 data_time: 0.0252 memory: 14901 loss: 0.8489 loss_prob: 0.4284 loss_thr: 0.3442 loss_db: 0.0763 2022/11/03 00:42:22 - mmengine - INFO - Epoch(train) [1029][55/63] lr: 3.7491e-04 eta: 1:57:59 time: 0.7296 data_time: 0.0238 memory: 14901 loss: 0.8477 loss_prob: 0.4317 loss_thr: 0.3403 loss_db: 0.0757 2022/11/03 00:42:26 - mmengine - INFO - Epoch(train) [1029][60/63] lr: 3.7491e-04 eta: 1:57:52 time: 0.7058 data_time: 0.0075 memory: 14901 loss: 0.8874 loss_prob: 0.4574 loss_thr: 0.3523 loss_db: 0.0777 2022/11/03 00:42:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:42:35 - mmengine - INFO - Epoch(train) [1030][5/63] lr: 3.7293e-04 eta: 1:57:52 time: 1.0461 data_time: 0.2118 memory: 14901 loss: 0.8898 loss_prob: 0.4593 loss_thr: 0.3518 loss_db: 0.0787 2022/11/03 00:42:38 - mmengine - INFO - Epoch(train) [1030][10/63] lr: 3.7293e-04 eta: 1:57:44 time: 0.9820 data_time: 0.2095 memory: 14901 loss: 0.8771 loss_prob: 0.4605 loss_thr: 0.3359 loss_db: 0.0807 2022/11/03 00:42:40 - mmengine - INFO - Epoch(train) [1030][15/63] lr: 3.7293e-04 eta: 1:57:44 time: 0.5542 data_time: 0.0076 memory: 14901 loss: 0.8993 loss_prob: 0.4675 loss_thr: 0.3486 loss_db: 0.0832 2022/11/03 00:42:43 - mmengine - INFO - Epoch(train) [1030][20/63] lr: 3.7293e-04 eta: 1:57:37 time: 0.5300 data_time: 0.0077 memory: 14901 loss: 0.8949 loss_prob: 0.4627 loss_thr: 0.3506 loss_db: 0.0817 2022/11/03 00:42:47 - mmengine - INFO - Epoch(train) [1030][25/63] lr: 3.7293e-04 eta: 1:57:37 time: 0.6933 data_time: 0.0176 memory: 14901 loss: 0.8744 loss_prob: 0.4496 loss_thr: 0.3464 loss_db: 0.0783 2022/11/03 00:42:51 - mmengine - INFO - Epoch(train) [1030][30/63] lr: 3.7293e-04 eta: 1:57:31 time: 0.7785 data_time: 0.0445 memory: 14901 loss: 0.9260 loss_prob: 0.4783 loss_thr: 0.3636 loss_db: 0.0842 2022/11/03 00:42:53 - mmengine - INFO - Epoch(train) [1030][35/63] lr: 3.7293e-04 eta: 1:57:31 time: 0.6116 data_time: 0.0326 memory: 14901 loss: 0.9066 loss_prob: 0.4794 loss_thr: 0.3433 loss_db: 0.0838 2022/11/03 00:42:57 - mmengine - INFO - Epoch(train) [1030][40/63] lr: 3.7293e-04 eta: 1:57:24 time: 0.6141 data_time: 0.0067 memory: 14901 loss: 0.8559 loss_prob: 0.4526 loss_thr: 0.3267 loss_db: 0.0766 2022/11/03 00:43:00 - mmengine - INFO - Epoch(train) [1030][45/63] lr: 3.7293e-04 eta: 1:57:24 time: 0.6922 data_time: 0.0131 memory: 14901 loss: 0.8552 loss_prob: 0.4367 loss_thr: 0.3436 loss_db: 0.0749 2022/11/03 00:43:05 - mmengine - INFO - Epoch(train) [1030][50/63] lr: 3.7293e-04 eta: 1:57:18 time: 0.7730 data_time: 0.0189 memory: 14901 loss: 0.8810 loss_prob: 0.4450 loss_thr: 0.3578 loss_db: 0.0782 2022/11/03 00:43:08 - mmengine - INFO - Epoch(train) [1030][55/63] lr: 3.7293e-04 eta: 1:57:18 time: 0.8084 data_time: 0.0256 memory: 14901 loss: 0.9150 loss_prob: 0.4667 loss_thr: 0.3662 loss_db: 0.0821 2022/11/03 00:43:13 - mmengine - INFO - Epoch(train) [1030][60/63] lr: 3.7293e-04 eta: 1:57:12 time: 0.8107 data_time: 0.0194 memory: 14901 loss: 0.9213 loss_prob: 0.4706 loss_thr: 0.3693 loss_db: 0.0815 2022/11/03 00:43:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:43:21 - mmengine - INFO - Epoch(train) [1031][5/63] lr: 3.7096e-04 eta: 1:57:12 time: 0.9704 data_time: 0.3210 memory: 14901 loss: 0.8592 loss_prob: 0.4463 loss_thr: 0.3354 loss_db: 0.0775 2022/11/03 00:43:24 - mmengine - INFO - Epoch(train) [1031][10/63] lr: 3.7096e-04 eta: 1:57:03 time: 0.9383 data_time: 0.3250 memory: 14901 loss: 0.8496 loss_prob: 0.4384 loss_thr: 0.3350 loss_db: 0.0762 2022/11/03 00:43:26 - mmengine - INFO - Epoch(train) [1031][15/63] lr: 3.7096e-04 eta: 1:57:03 time: 0.5601 data_time: 0.0127 memory: 14901 loss: 0.8627 loss_prob: 0.4447 loss_thr: 0.3386 loss_db: 0.0794 2022/11/03 00:43:29 - mmengine - INFO - Epoch(train) [1031][20/63] lr: 3.7096e-04 eta: 1:56:56 time: 0.5553 data_time: 0.0062 memory: 14901 loss: 0.9001 loss_prob: 0.4670 loss_thr: 0.3504 loss_db: 0.0828 2022/11/03 00:43:32 - mmengine - INFO - Epoch(train) [1031][25/63] lr: 3.7096e-04 eta: 1:56:56 time: 0.5900 data_time: 0.0247 memory: 14901 loss: 0.8632 loss_prob: 0.4433 loss_thr: 0.3402 loss_db: 0.0798 2022/11/03 00:43:36 - mmengine - INFO - Epoch(train) [1031][30/63] lr: 3.7096e-04 eta: 1:56:50 time: 0.6662 data_time: 0.0423 memory: 14901 loss: 0.8356 loss_prob: 0.4254 loss_thr: 0.3329 loss_db: 0.0773 2022/11/03 00:43:40 - mmengine - INFO - Epoch(train) [1031][35/63] lr: 3.7096e-04 eta: 1:56:50 time: 0.7738 data_time: 0.0243 memory: 14901 loss: 0.8834 loss_prob: 0.4574 loss_thr: 0.3471 loss_db: 0.0789 2022/11/03 00:43:43 - mmengine - INFO - Epoch(train) [1031][40/63] lr: 3.7096e-04 eta: 1:56:43 time: 0.6711 data_time: 0.0063 memory: 14901 loss: 0.8924 loss_prob: 0.4663 loss_thr: 0.3456 loss_db: 0.0806 2022/11/03 00:43:47 - mmengine - INFO - Epoch(train) [1031][45/63] lr: 3.7096e-04 eta: 1:56:43 time: 0.7345 data_time: 0.0072 memory: 14901 loss: 0.9007 loss_prob: 0.4736 loss_thr: 0.3449 loss_db: 0.0823 2022/11/03 00:43:52 - mmengine - INFO - Epoch(train) [1031][50/63] lr: 3.7096e-04 eta: 1:56:37 time: 0.9221 data_time: 0.0247 memory: 14901 loss: 0.9043 loss_prob: 0.4756 loss_thr: 0.3464 loss_db: 0.0823 2022/11/03 00:43:57 - mmengine - INFO - Epoch(train) [1031][55/63] lr: 3.7096e-04 eta: 1:56:37 time: 0.9033 data_time: 0.0271 memory: 14901 loss: 0.8543 loss_prob: 0.4405 loss_thr: 0.3374 loss_db: 0.0763 2022/11/03 00:44:00 - mmengine - INFO - Epoch(train) [1031][60/63] lr: 3.7096e-04 eta: 1:56:31 time: 0.7954 data_time: 0.0096 memory: 14901 loss: 0.8420 loss_prob: 0.4303 loss_thr: 0.3369 loss_db: 0.0749 2022/11/03 00:44:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:44:08 - mmengine - INFO - Epoch(train) [1032][5/63] lr: 3.6898e-04 eta: 1:56:31 time: 0.9209 data_time: 0.2911 memory: 14901 loss: 0.9640 loss_prob: 0.5124 loss_thr: 0.3626 loss_db: 0.0890 2022/11/03 00:44:11 - mmengine - INFO - Epoch(train) [1032][10/63] lr: 3.6898e-04 eta: 1:56:23 time: 0.9365 data_time: 0.2912 memory: 14901 loss: 0.9705 loss_prob: 0.5156 loss_thr: 0.3634 loss_db: 0.0915 2022/11/03 00:44:14 - mmengine - INFO - Epoch(train) [1032][15/63] lr: 3.6898e-04 eta: 1:56:23 time: 0.6337 data_time: 0.0078 memory: 14901 loss: 0.8770 loss_prob: 0.4484 loss_thr: 0.3481 loss_db: 0.0805 2022/11/03 00:44:18 - mmengine - INFO - Epoch(train) [1032][20/63] lr: 3.6898e-04 eta: 1:56:16 time: 0.6954 data_time: 0.0079 memory: 14901 loss: 0.8895 loss_prob: 0.4657 loss_thr: 0.3417 loss_db: 0.0820 2022/11/03 00:44:22 - mmengine - INFO - Epoch(train) [1032][25/63] lr: 3.6898e-04 eta: 1:56:16 time: 0.7471 data_time: 0.0176 memory: 14901 loss: 0.9223 loss_prob: 0.4954 loss_thr: 0.3409 loss_db: 0.0859 2022/11/03 00:44:25 - mmengine - INFO - Epoch(train) [1032][30/63] lr: 3.6898e-04 eta: 1:56:10 time: 0.6887 data_time: 0.0385 memory: 14901 loss: 0.9569 loss_prob: 0.5021 loss_thr: 0.3689 loss_db: 0.0859 2022/11/03 00:44:29 - mmengine - INFO - Epoch(train) [1032][35/63] lr: 3.6898e-04 eta: 1:56:10 time: 0.6700 data_time: 0.0277 memory: 14901 loss: 0.9301 loss_prob: 0.4817 loss_thr: 0.3650 loss_db: 0.0834 2022/11/03 00:44:33 - mmengine - INFO - Epoch(train) [1032][40/63] lr: 3.6898e-04 eta: 1:56:03 time: 0.7864 data_time: 0.0080 memory: 14901 loss: 0.8529 loss_prob: 0.4330 loss_thr: 0.3435 loss_db: 0.0764 2022/11/03 00:44:36 - mmengine - INFO - Epoch(train) [1032][45/63] lr: 3.6898e-04 eta: 1:56:03 time: 0.6979 data_time: 0.0075 memory: 14901 loss: 0.8238 loss_prob: 0.4077 loss_thr: 0.3438 loss_db: 0.0723 2022/11/03 00:44:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:44:41 - mmengine - INFO - Epoch(train) [1032][50/63] lr: 3.6898e-04 eta: 1:55:57 time: 0.8154 data_time: 0.0176 memory: 14901 loss: 0.8336 loss_prob: 0.4143 loss_thr: 0.3456 loss_db: 0.0737 2022/11/03 00:44:44 - mmengine - INFO - Epoch(train) [1032][55/63] lr: 3.6898e-04 eta: 1:55:57 time: 0.8420 data_time: 0.0293 memory: 14901 loss: 0.8334 loss_prob: 0.4245 loss_thr: 0.3357 loss_db: 0.0733 2022/11/03 00:44:48 - mmengine - INFO - Epoch(train) [1032][60/63] lr: 3.6898e-04 eta: 1:55:50 time: 0.6799 data_time: 0.0196 memory: 14901 loss: 0.8316 loss_prob: 0.4259 loss_thr: 0.3323 loss_db: 0.0735 2022/11/03 00:44:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:44:56 - mmengine - INFO - Epoch(train) [1033][5/63] lr: 3.6701e-04 eta: 1:55:50 time: 1.0037 data_time: 0.2854 memory: 14901 loss: 0.7639 loss_prob: 0.3801 loss_thr: 0.3150 loss_db: 0.0688 2022/11/03 00:45:00 - mmengine - INFO - Epoch(train) [1033][10/63] lr: 3.6701e-04 eta: 1:55:42 time: 1.0431 data_time: 0.2872 memory: 14901 loss: 0.8262 loss_prob: 0.4215 loss_thr: 0.3307 loss_db: 0.0739 2022/11/03 00:45:03 - mmengine - INFO - Epoch(train) [1033][15/63] lr: 3.6701e-04 eta: 1:55:42 time: 0.7326 data_time: 0.0097 memory: 14901 loss: 0.9153 loss_prob: 0.4748 loss_thr: 0.3582 loss_db: 0.0824 2022/11/03 00:45:07 - mmengine - INFO - Epoch(train) [1033][20/63] lr: 3.6701e-04 eta: 1:55:36 time: 0.6847 data_time: 0.0058 memory: 14901 loss: 0.8471 loss_prob: 0.4329 loss_thr: 0.3396 loss_db: 0.0745 2022/11/03 00:45:10 - mmengine - INFO - Epoch(train) [1033][25/63] lr: 3.6701e-04 eta: 1:55:36 time: 0.6348 data_time: 0.0235 memory: 14901 loss: 0.8663 loss_prob: 0.4494 loss_thr: 0.3371 loss_db: 0.0797 2022/11/03 00:45:13 - mmengine - INFO - Epoch(train) [1033][30/63] lr: 3.6701e-04 eta: 1:55:29 time: 0.6163 data_time: 0.0360 memory: 14901 loss: 0.8577 loss_prob: 0.4454 loss_thr: 0.3333 loss_db: 0.0790 2022/11/03 00:45:15 - mmengine - INFO - Epoch(train) [1033][35/63] lr: 3.6701e-04 eta: 1:55:29 time: 0.5318 data_time: 0.0208 memory: 14901 loss: 0.8834 loss_prob: 0.4560 loss_thr: 0.3494 loss_db: 0.0779 2022/11/03 00:45:18 - mmengine - INFO - Epoch(train) [1033][40/63] lr: 3.6701e-04 eta: 1:55:22 time: 0.4975 data_time: 0.0080 memory: 14901 loss: 0.9202 loss_prob: 0.4791 loss_thr: 0.3585 loss_db: 0.0826 2022/11/03 00:45:20 - mmengine - INFO - Epoch(train) [1033][45/63] lr: 3.6701e-04 eta: 1:55:22 time: 0.5364 data_time: 0.0059 memory: 14901 loss: 0.8735 loss_prob: 0.4506 loss_thr: 0.3446 loss_db: 0.0784 2022/11/03 00:45:23 - mmengine - INFO - Epoch(train) [1033][50/63] lr: 3.6701e-04 eta: 1:55:15 time: 0.5446 data_time: 0.0187 memory: 14901 loss: 0.9046 loss_prob: 0.4723 loss_thr: 0.3528 loss_db: 0.0795 2022/11/03 00:45:26 - mmengine - INFO - Epoch(train) [1033][55/63] lr: 3.6701e-04 eta: 1:55:15 time: 0.5398 data_time: 0.0223 memory: 14901 loss: 0.9601 loss_prob: 0.5034 loss_thr: 0.3704 loss_db: 0.0862 2022/11/03 00:45:28 - mmengine - INFO - Epoch(train) [1033][60/63] lr: 3.6701e-04 eta: 1:55:09 time: 0.5160 data_time: 0.0105 memory: 14901 loss: 0.8677 loss_prob: 0.4445 loss_thr: 0.3439 loss_db: 0.0794 2022/11/03 00:45:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:45:36 - mmengine - INFO - Epoch(train) [1034][5/63] lr: 3.6503e-04 eta: 1:55:09 time: 0.8562 data_time: 0.2236 memory: 14901 loss: 0.8263 loss_prob: 0.4173 loss_thr: 0.3359 loss_db: 0.0731 2022/11/03 00:45:39 - mmengine - INFO - Epoch(train) [1034][10/63] lr: 3.6503e-04 eta: 1:55:00 time: 0.9733 data_time: 0.2256 memory: 14901 loss: 0.9162 loss_prob: 0.4701 loss_thr: 0.3648 loss_db: 0.0813 2022/11/03 00:45:43 - mmengine - INFO - Epoch(train) [1034][15/63] lr: 3.6503e-04 eta: 1:55:00 time: 0.6823 data_time: 0.0091 memory: 14901 loss: 0.9161 loss_prob: 0.4751 loss_thr: 0.3593 loss_db: 0.0817 2022/11/03 00:45:46 - mmengine - INFO - Epoch(train) [1034][20/63] lr: 3.6503e-04 eta: 1:54:54 time: 0.6772 data_time: 0.0078 memory: 14901 loss: 0.9369 loss_prob: 0.4905 loss_thr: 0.3621 loss_db: 0.0843 2022/11/03 00:45:49 - mmengine - INFO - Epoch(train) [1034][25/63] lr: 3.6503e-04 eta: 1:54:54 time: 0.6527 data_time: 0.0223 memory: 14901 loss: 0.8885 loss_prob: 0.4571 loss_thr: 0.3524 loss_db: 0.0789 2022/11/03 00:45:53 - mmengine - INFO - Epoch(train) [1034][30/63] lr: 3.6503e-04 eta: 1:54:47 time: 0.6736 data_time: 0.0378 memory: 14901 loss: 0.8913 loss_prob: 0.4519 loss_thr: 0.3607 loss_db: 0.0787 2022/11/03 00:45:57 - mmengine - INFO - Epoch(train) [1034][35/63] lr: 3.6503e-04 eta: 1:54:47 time: 0.7803 data_time: 0.0238 memory: 14901 loss: 0.9368 loss_prob: 0.4860 loss_thr: 0.3659 loss_db: 0.0850 2022/11/03 00:46:00 - mmengine - INFO - Epoch(train) [1034][40/63] lr: 3.6503e-04 eta: 1:54:41 time: 0.7614 data_time: 0.0090 memory: 14901 loss: 0.8928 loss_prob: 0.4657 loss_thr: 0.3475 loss_db: 0.0797 2022/11/03 00:46:03 - mmengine - INFO - Epoch(train) [1034][45/63] lr: 3.6503e-04 eta: 1:54:41 time: 0.6358 data_time: 0.0067 memory: 14901 loss: 0.9226 loss_prob: 0.4799 loss_thr: 0.3613 loss_db: 0.0814 2022/11/03 00:46:07 - mmengine - INFO - Epoch(train) [1034][50/63] lr: 3.6503e-04 eta: 1:54:34 time: 0.6688 data_time: 0.0179 memory: 14901 loss: 0.9521 loss_prob: 0.4992 loss_thr: 0.3669 loss_db: 0.0860 2022/11/03 00:46:11 - mmengine - INFO - Epoch(train) [1034][55/63] lr: 3.6503e-04 eta: 1:54:34 time: 0.7531 data_time: 0.0284 memory: 14901 loss: 0.9124 loss_prob: 0.4745 loss_thr: 0.3550 loss_db: 0.0830 2022/11/03 00:46:14 - mmengine - INFO - Epoch(train) [1034][60/63] lr: 3.6503e-04 eta: 1:54:28 time: 0.6929 data_time: 0.0173 memory: 14901 loss: 0.8928 loss_prob: 0.4669 loss_thr: 0.3440 loss_db: 0.0819 2022/11/03 00:46:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:46:23 - mmengine - INFO - Epoch(train) [1035][5/63] lr: 3.6305e-04 eta: 1:54:28 time: 1.0573 data_time: 0.3131 memory: 14901 loss: 0.9120 loss_prob: 0.4699 loss_thr: 0.3624 loss_db: 0.0797 2022/11/03 00:46:27 - mmengine - INFO - Epoch(train) [1035][10/63] lr: 3.6305e-04 eta: 1:54:20 time: 1.1602 data_time: 0.3121 memory: 14901 loss: 0.9201 loss_prob: 0.4689 loss_thr: 0.3701 loss_db: 0.0811 2022/11/03 00:46:30 - mmengine - INFO - Epoch(train) [1035][15/63] lr: 3.6305e-04 eta: 1:54:20 time: 0.6515 data_time: 0.0084 memory: 14901 loss: 0.8585 loss_prob: 0.4368 loss_thr: 0.3438 loss_db: 0.0779 2022/11/03 00:46:34 - mmengine - INFO - Epoch(train) [1035][20/63] lr: 3.6305e-04 eta: 1:54:13 time: 0.7165 data_time: 0.0079 memory: 14901 loss: 0.9065 loss_prob: 0.4671 loss_thr: 0.3561 loss_db: 0.0832 2022/11/03 00:46:38 - mmengine - INFO - Epoch(train) [1035][25/63] lr: 3.6305e-04 eta: 1:54:13 time: 0.8304 data_time: 0.0383 memory: 14901 loss: 0.8921 loss_prob: 0.4587 loss_thr: 0.3536 loss_db: 0.0798 2022/11/03 00:46:41 - mmengine - INFO - Epoch(train) [1035][30/63] lr: 3.6305e-04 eta: 1:54:07 time: 0.7471 data_time: 0.0381 memory: 14901 loss: 0.8339 loss_prob: 0.4256 loss_thr: 0.3342 loss_db: 0.0741 2022/11/03 00:46:45 - mmengine - INFO - Epoch(train) [1035][35/63] lr: 3.6305e-04 eta: 1:54:07 time: 0.6691 data_time: 0.0049 memory: 14901 loss: 0.8520 loss_prob: 0.4396 loss_thr: 0.3356 loss_db: 0.0767 2022/11/03 00:46:47 - mmengine - INFO - Epoch(train) [1035][40/63] lr: 3.6305e-04 eta: 1:54:00 time: 0.5991 data_time: 0.0107 memory: 14901 loss: 0.8528 loss_prob: 0.4445 loss_thr: 0.3305 loss_db: 0.0778 2022/11/03 00:46:51 - mmengine - INFO - Epoch(train) [1035][45/63] lr: 3.6305e-04 eta: 1:54:00 time: 0.5665 data_time: 0.0111 memory: 14901 loss: 0.8478 loss_prob: 0.4410 loss_thr: 0.3302 loss_db: 0.0766 2022/11/03 00:46:54 - mmengine - INFO - Epoch(train) [1035][50/63] lr: 3.6305e-04 eta: 1:53:54 time: 0.6614 data_time: 0.0289 memory: 14901 loss: 0.9973 loss_prob: 0.5232 loss_thr: 0.3872 loss_db: 0.0869 2022/11/03 00:46:59 - mmengine - INFO - Epoch(train) [1035][55/63] lr: 3.6305e-04 eta: 1:53:54 time: 0.7924 data_time: 0.0293 memory: 14901 loss: 1.0543 loss_prob: 0.5565 loss_thr: 0.4028 loss_db: 0.0950 2022/11/03 00:47:01 - mmengine - INFO - Epoch(train) [1035][60/63] lr: 3.6305e-04 eta: 1:53:47 time: 0.7192 data_time: 0.0097 memory: 14901 loss: 0.9583 loss_prob: 0.5030 loss_thr: 0.3657 loss_db: 0.0896 2022/11/03 00:47:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:47:11 - mmengine - INFO - Epoch(train) [1036][5/63] lr: 3.6107e-04 eta: 1:53:47 time: 1.0876 data_time: 0.3105 memory: 14901 loss: 0.9041 loss_prob: 0.4702 loss_thr: 0.3533 loss_db: 0.0806 2022/11/03 00:47:14 - mmengine - INFO - Epoch(train) [1036][10/63] lr: 3.6107e-04 eta: 1:53:39 time: 1.0904 data_time: 0.3069 memory: 14901 loss: 0.8946 loss_prob: 0.4696 loss_thr: 0.3453 loss_db: 0.0797 2022/11/03 00:47:17 - mmengine - INFO - Epoch(train) [1036][15/63] lr: 3.6107e-04 eta: 1:53:39 time: 0.6265 data_time: 0.0065 memory: 14901 loss: 0.9051 loss_prob: 0.4670 loss_thr: 0.3561 loss_db: 0.0820 2022/11/03 00:47:21 - mmengine - INFO - Epoch(train) [1036][20/63] lr: 3.6107e-04 eta: 1:53:32 time: 0.7037 data_time: 0.0089 memory: 14901 loss: 0.9441 loss_prob: 0.4877 loss_thr: 0.3716 loss_db: 0.0848 2022/11/03 00:47:24 - mmengine - INFO - Epoch(train) [1036][25/63] lr: 3.6107e-04 eta: 1:53:32 time: 0.7004 data_time: 0.0380 memory: 14901 loss: 0.9370 loss_prob: 0.4883 loss_thr: 0.3635 loss_db: 0.0852 2022/11/03 00:47:28 - mmengine - INFO - Epoch(train) [1036][30/63] lr: 3.6107e-04 eta: 1:53:26 time: 0.6676 data_time: 0.0352 memory: 14901 loss: 0.8795 loss_prob: 0.4531 loss_thr: 0.3453 loss_db: 0.0811 2022/11/03 00:47:31 - mmengine - INFO - Epoch(train) [1036][35/63] lr: 3.6107e-04 eta: 1:53:26 time: 0.6085 data_time: 0.0083 memory: 14901 loss: 0.8201 loss_prob: 0.4199 loss_thr: 0.3251 loss_db: 0.0751 2022/11/03 00:47:33 - mmengine - INFO - Epoch(train) [1036][40/63] lr: 3.6107e-04 eta: 1:53:19 time: 0.5574 data_time: 0.0081 memory: 14901 loss: 0.8253 loss_prob: 0.4242 loss_thr: 0.3276 loss_db: 0.0735 2022/11/03 00:47:37 - mmengine - INFO - Epoch(train) [1036][45/63] lr: 3.6107e-04 eta: 1:53:19 time: 0.6360 data_time: 0.0067 memory: 14901 loss: 0.8552 loss_prob: 0.4431 loss_thr: 0.3352 loss_db: 0.0769 2022/11/03 00:47:41 - mmengine - INFO - Epoch(train) [1036][50/63] lr: 3.6107e-04 eta: 1:53:13 time: 0.7353 data_time: 0.0270 memory: 14901 loss: 0.8713 loss_prob: 0.4509 loss_thr: 0.3409 loss_db: 0.0796 2022/11/03 00:47:45 - mmengine - INFO - Epoch(train) [1036][55/63] lr: 3.6107e-04 eta: 1:53:13 time: 0.7741 data_time: 0.0261 memory: 14901 loss: 0.9149 loss_prob: 0.4773 loss_thr: 0.3547 loss_db: 0.0829 2022/11/03 00:47:48 - mmengine - INFO - Epoch(train) [1036][60/63] lr: 3.6107e-04 eta: 1:53:06 time: 0.7703 data_time: 0.0075 memory: 14901 loss: 0.9245 loss_prob: 0.4882 loss_thr: 0.3517 loss_db: 0.0846 2022/11/03 00:47:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:47:58 - mmengine - INFO - Epoch(train) [1037][5/63] lr: 3.5909e-04 eta: 1:53:06 time: 1.0846 data_time: 0.3078 memory: 14901 loss: 0.9748 loss_prob: 0.5173 loss_thr: 0.3691 loss_db: 0.0884 2022/11/03 00:48:02 - mmengine - INFO - Epoch(train) [1037][10/63] lr: 3.5909e-04 eta: 1:52:58 time: 1.2794 data_time: 0.3082 memory: 14901 loss: 0.9452 loss_prob: 0.5032 loss_thr: 0.3568 loss_db: 0.0853 2022/11/03 00:48:06 - mmengine - INFO - Epoch(train) [1037][15/63] lr: 3.5909e-04 eta: 1:52:58 time: 0.8679 data_time: 0.0085 memory: 14901 loss: 0.9680 loss_prob: 0.4965 loss_thr: 0.3862 loss_db: 0.0852 2022/11/03 00:48:09 - mmengine - INFO - Epoch(train) [1037][20/63] lr: 3.5909e-04 eta: 1:52:52 time: 0.6837 data_time: 0.0076 memory: 14901 loss: 1.0273 loss_prob: 0.5382 loss_thr: 0.3963 loss_db: 0.0928 2022/11/03 00:48:14 - mmengine - INFO - Epoch(train) [1037][25/63] lr: 3.5909e-04 eta: 1:52:52 time: 0.7726 data_time: 0.0353 memory: 14901 loss: 0.9168 loss_prob: 0.4840 loss_thr: 0.3479 loss_db: 0.0849 2022/11/03 00:48:17 - mmengine - INFO - Epoch(train) [1037][30/63] lr: 3.5909e-04 eta: 1:52:46 time: 0.7667 data_time: 0.0393 memory: 14901 loss: 0.9018 loss_prob: 0.4666 loss_thr: 0.3524 loss_db: 0.0827 2022/11/03 00:48:20 - mmengine - INFO - Epoch(train) [1037][35/63] lr: 3.5909e-04 eta: 1:52:46 time: 0.6276 data_time: 0.0095 memory: 14901 loss: 0.9118 loss_prob: 0.4702 loss_thr: 0.3581 loss_db: 0.0835 2022/11/03 00:48:23 - mmengine - INFO - Epoch(train) [1037][40/63] lr: 3.5909e-04 eta: 1:52:39 time: 0.6350 data_time: 0.0077 memory: 14901 loss: 0.8677 loss_prob: 0.4426 loss_thr: 0.3463 loss_db: 0.0788 2022/11/03 00:48:27 - mmengine - INFO - Epoch(train) [1037][45/63] lr: 3.5909e-04 eta: 1:52:39 time: 0.7211 data_time: 0.0097 memory: 14901 loss: 0.8470 loss_prob: 0.4274 loss_thr: 0.3443 loss_db: 0.0753 2022/11/03 00:48:31 - mmengine - INFO - Epoch(train) [1037][50/63] lr: 3.5909e-04 eta: 1:52:33 time: 0.7896 data_time: 0.0280 memory: 14901 loss: 0.8591 loss_prob: 0.4409 loss_thr: 0.3423 loss_db: 0.0759 2022/11/03 00:48:35 - mmengine - INFO - Epoch(train) [1037][55/63] lr: 3.5909e-04 eta: 1:52:33 time: 0.7618 data_time: 0.0258 memory: 14901 loss: 0.8863 loss_prob: 0.4655 loss_thr: 0.3401 loss_db: 0.0807 2022/11/03 00:48:40 - mmengine - INFO - Epoch(train) [1037][60/63] lr: 3.5909e-04 eta: 1:52:26 time: 0.8821 data_time: 0.0061 memory: 14901 loss: 0.9252 loss_prob: 0.4848 loss_thr: 0.3578 loss_db: 0.0826 2022/11/03 00:48:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:48:50 - mmengine - INFO - Epoch(train) [1038][5/63] lr: 3.5710e-04 eta: 1:52:26 time: 1.1939 data_time: 0.2603 memory: 14901 loss: 0.9596 loss_prob: 0.5125 loss_thr: 0.3654 loss_db: 0.0817 2022/11/03 00:48:55 - mmengine - INFO - Epoch(train) [1038][10/63] lr: 3.5710e-04 eta: 1:52:19 time: 1.2827 data_time: 0.2631 memory: 14901 loss: 0.9262 loss_prob: 0.4998 loss_thr: 0.3433 loss_db: 0.0831 2022/11/03 00:48:58 - mmengine - INFO - Epoch(train) [1038][15/63] lr: 3.5710e-04 eta: 1:52:19 time: 0.7909 data_time: 0.0099 memory: 14901 loss: 0.8630 loss_prob: 0.4553 loss_thr: 0.3278 loss_db: 0.0800 2022/11/03 00:49:02 - mmengine - INFO - Epoch(train) [1038][20/63] lr: 3.5710e-04 eta: 1:52:12 time: 0.6716 data_time: 0.0068 memory: 14901 loss: 0.8422 loss_prob: 0.4360 loss_thr: 0.3303 loss_db: 0.0759 2022/11/03 00:49:05 - mmengine - INFO - Epoch(train) [1038][25/63] lr: 3.5710e-04 eta: 1:52:12 time: 0.6607 data_time: 0.0134 memory: 14901 loss: 0.8658 loss_prob: 0.4368 loss_thr: 0.3522 loss_db: 0.0768 2022/11/03 00:49:08 - mmengine - INFO - Epoch(train) [1038][30/63] lr: 3.5710e-04 eta: 1:52:05 time: 0.6056 data_time: 0.0336 memory: 14901 loss: 0.9102 loss_prob: 0.4613 loss_thr: 0.3666 loss_db: 0.0822 2022/11/03 00:49:11 - mmengine - INFO - Epoch(train) [1038][35/63] lr: 3.5710e-04 eta: 1:52:05 time: 0.6436 data_time: 0.0296 memory: 14901 loss: 0.8708 loss_prob: 0.4466 loss_thr: 0.3446 loss_db: 0.0796 2022/11/03 00:49:15 - mmengine - INFO - Epoch(train) [1038][40/63] lr: 3.5710e-04 eta: 1:51:59 time: 0.7271 data_time: 0.0101 memory: 14901 loss: 0.9395 loss_prob: 0.4847 loss_thr: 0.3704 loss_db: 0.0844 2022/11/03 00:49:18 - mmengine - INFO - Epoch(train) [1038][45/63] lr: 3.5710e-04 eta: 1:51:59 time: 0.6738 data_time: 0.0065 memory: 14901 loss: 0.9935 loss_prob: 0.5171 loss_thr: 0.3875 loss_db: 0.0889 2022/11/03 00:49:21 - mmengine - INFO - Epoch(train) [1038][50/63] lr: 3.5710e-04 eta: 1:51:52 time: 0.6264 data_time: 0.0233 memory: 14901 loss: 0.8895 loss_prob: 0.4567 loss_thr: 0.3534 loss_db: 0.0795 2022/11/03 00:49:25 - mmengine - INFO - Epoch(train) [1038][55/63] lr: 3.5710e-04 eta: 1:51:52 time: 0.7077 data_time: 0.0239 memory: 14901 loss: 0.8439 loss_prob: 0.4246 loss_thr: 0.3438 loss_db: 0.0755 2022/11/03 00:49:30 - mmengine - INFO - Epoch(train) [1038][60/63] lr: 3.5710e-04 eta: 1:51:46 time: 0.8467 data_time: 0.0095 memory: 14901 loss: 0.8469 loss_prob: 0.4342 loss_thr: 0.3364 loss_db: 0.0763 2022/11/03 00:49:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:49:40 - mmengine - INFO - Epoch(train) [1039][5/63] lr: 3.5512e-04 eta: 1:51:46 time: 1.1632 data_time: 0.2706 memory: 14901 loss: 1.0022 loss_prob: 0.5313 loss_thr: 0.3781 loss_db: 0.0928 2022/11/03 00:49:44 - mmengine - INFO - Epoch(train) [1039][10/63] lr: 3.5512e-04 eta: 1:51:38 time: 1.1611 data_time: 0.2759 memory: 14901 loss: 0.9585 loss_prob: 0.4994 loss_thr: 0.3731 loss_db: 0.0859 2022/11/03 00:49:47 - mmengine - INFO - Epoch(train) [1039][15/63] lr: 3.5512e-04 eta: 1:51:38 time: 0.6933 data_time: 0.0145 memory: 14901 loss: 0.9020 loss_prob: 0.4663 loss_thr: 0.3557 loss_db: 0.0799 2022/11/03 00:49:50 - mmengine - INFO - Epoch(train) [1039][20/63] lr: 3.5512e-04 eta: 1:51:31 time: 0.5835 data_time: 0.0058 memory: 14901 loss: 0.9415 loss_prob: 0.4927 loss_thr: 0.3633 loss_db: 0.0855 2022/11/03 00:49:54 - mmengine - INFO - Epoch(train) [1039][25/63] lr: 3.5512e-04 eta: 1:51:31 time: 0.6914 data_time: 0.0317 memory: 14901 loss: 0.9535 loss_prob: 0.5010 loss_thr: 0.3644 loss_db: 0.0881 2022/11/03 00:49:58 - mmengine - INFO - Epoch(train) [1039][30/63] lr: 3.5512e-04 eta: 1:51:25 time: 0.7655 data_time: 0.0439 memory: 14901 loss: 0.9475 loss_prob: 0.4973 loss_thr: 0.3622 loss_db: 0.0880 2022/11/03 00:50:01 - mmengine - INFO - Epoch(train) [1039][35/63] lr: 3.5512e-04 eta: 1:51:25 time: 0.7102 data_time: 0.0185 memory: 14901 loss: 0.8561 loss_prob: 0.4330 loss_thr: 0.3472 loss_db: 0.0760 2022/11/03 00:50:04 - mmengine - INFO - Epoch(train) [1039][40/63] lr: 3.5512e-04 eta: 1:51:18 time: 0.6443 data_time: 0.0059 memory: 14901 loss: 0.8637 loss_prob: 0.4412 loss_thr: 0.3476 loss_db: 0.0750 2022/11/03 00:50:07 - mmengine - INFO - Epoch(train) [1039][45/63] lr: 3.5512e-04 eta: 1:51:18 time: 0.6092 data_time: 0.0056 memory: 14901 loss: 0.9449 loss_prob: 0.4907 loss_thr: 0.3702 loss_db: 0.0839 2022/11/03 00:50:10 - mmengine - INFO - Epoch(train) [1039][50/63] lr: 3.5512e-04 eta: 1:51:12 time: 0.6228 data_time: 0.0237 memory: 14901 loss: 1.0192 loss_prob: 0.5546 loss_thr: 0.3770 loss_db: 0.0876 2022/11/03 00:50:13 - mmengine - INFO - Epoch(train) [1039][55/63] lr: 3.5512e-04 eta: 1:51:12 time: 0.6019 data_time: 0.0287 memory: 14901 loss: 0.9160 loss_prob: 0.5008 loss_thr: 0.3353 loss_db: 0.0799 2022/11/03 00:50:16 - mmengine - INFO - Epoch(train) [1039][60/63] lr: 3.5512e-04 eta: 1:51:05 time: 0.5439 data_time: 0.0109 memory: 14901 loss: 0.8523 loss_prob: 0.4396 loss_thr: 0.3351 loss_db: 0.0777 2022/11/03 00:50:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:50:23 - mmengine - INFO - Epoch(train) [1040][5/63] lr: 3.5314e-04 eta: 1:51:05 time: 0.8236 data_time: 0.2345 memory: 14901 loss: 0.8880 loss_prob: 0.4670 loss_thr: 0.3418 loss_db: 0.0792 2022/11/03 00:50:26 - mmengine - INFO - Epoch(train) [1040][10/63] lr: 3.5314e-04 eta: 1:50:56 time: 0.8779 data_time: 0.2371 memory: 14901 loss: 0.8314 loss_prob: 0.4317 loss_thr: 0.3257 loss_db: 0.0741 2022/11/03 00:50:28 - mmengine - INFO - Epoch(train) [1040][15/63] lr: 3.5314e-04 eta: 1:50:56 time: 0.5582 data_time: 0.0152 memory: 14901 loss: 0.8882 loss_prob: 0.4619 loss_thr: 0.3460 loss_db: 0.0803 2022/11/03 00:50:31 - mmengine - INFO - Epoch(train) [1040][20/63] lr: 3.5314e-04 eta: 1:50:50 time: 0.5403 data_time: 0.0194 memory: 14901 loss: 0.9393 loss_prob: 0.4879 loss_thr: 0.3646 loss_db: 0.0868 2022/11/03 00:50:34 - mmengine - INFO - Epoch(train) [1040][25/63] lr: 3.5314e-04 eta: 1:50:50 time: 0.5440 data_time: 0.0225 memory: 14901 loss: 0.9203 loss_prob: 0.4786 loss_thr: 0.3570 loss_db: 0.0846 2022/11/03 00:50:37 - mmengine - INFO - Epoch(train) [1040][30/63] lr: 3.5314e-04 eta: 1:50:43 time: 0.5534 data_time: 0.0274 memory: 14901 loss: 0.8503 loss_prob: 0.4360 loss_thr: 0.3380 loss_db: 0.0763 2022/11/03 00:50:39 - mmengine - INFO - Epoch(train) [1040][35/63] lr: 3.5314e-04 eta: 1:50:43 time: 0.5533 data_time: 0.0238 memory: 14901 loss: 0.8976 loss_prob: 0.4641 loss_thr: 0.3509 loss_db: 0.0827 2022/11/03 00:50:42 - mmengine - INFO - Epoch(train) [1040][40/63] lr: 3.5314e-04 eta: 1:50:36 time: 0.5338 data_time: 0.0115 memory: 14901 loss: 0.9269 loss_prob: 0.4813 loss_thr: 0.3607 loss_db: 0.0849 2022/11/03 00:50:46 - mmengine - INFO - Epoch(train) [1040][45/63] lr: 3.5314e-04 eta: 1:50:36 time: 0.6270 data_time: 0.0166 memory: 14901 loss: 0.8394 loss_prob: 0.4258 loss_thr: 0.3397 loss_db: 0.0739 2022/11/03 00:50:49 - mmengine - INFO - Epoch(train) [1040][50/63] lr: 3.5314e-04 eta: 1:50:30 time: 0.6835 data_time: 0.0241 memory: 14901 loss: 0.8350 loss_prob: 0.4292 loss_thr: 0.3304 loss_db: 0.0755 2022/11/03 00:50:52 - mmengine - INFO - Epoch(train) [1040][55/63] lr: 3.5314e-04 eta: 1:50:30 time: 0.6660 data_time: 0.0204 memory: 14901 loss: 0.8463 loss_prob: 0.4320 loss_thr: 0.3380 loss_db: 0.0763 2022/11/03 00:50:56 - mmengine - INFO - Epoch(train) [1040][60/63] lr: 3.5314e-04 eta: 1:50:23 time: 0.6936 data_time: 0.0166 memory: 14901 loss: 0.8706 loss_prob: 0.4387 loss_thr: 0.3550 loss_db: 0.0770 2022/11/03 00:50:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:50:57 - mmengine - INFO - Saving checkpoint at 1040 epochs 2022/11/03 00:51:01 - mmengine - INFO - Epoch(val) [1040][5/500] eta: 1:50:23 time: 0.0455 data_time: 0.0048 memory: 14901 2022/11/03 00:51:01 - mmengine - INFO - Epoch(val) [1040][10/500] eta: 0:00:22 time: 0.0450 data_time: 0.0046 memory: 1008 2022/11/03 00:51:02 - mmengine - INFO - Epoch(val) [1040][15/500] eta: 0:00:22 time: 0.0414 data_time: 0.0026 memory: 1008 2022/11/03 00:51:02 - mmengine - INFO - Epoch(val) [1040][20/500] eta: 0:00:19 time: 0.0414 data_time: 0.0028 memory: 1008 2022/11/03 00:51:02 - mmengine - INFO - Epoch(val) [1040][25/500] eta: 0:00:19 time: 0.0376 data_time: 0.0027 memory: 1008 2022/11/03 00:51:02 - mmengine - INFO - Epoch(val) [1040][30/500] eta: 0:00:20 time: 0.0439 data_time: 0.0026 memory: 1008 2022/11/03 00:51:02 - mmengine - INFO - Epoch(val) [1040][35/500] eta: 0:00:20 time: 0.0471 data_time: 0.0029 memory: 1008 2022/11/03 00:51:03 - mmengine - INFO - Epoch(val) [1040][40/500] eta: 0:00:20 time: 0.0435 data_time: 0.0027 memory: 1008 2022/11/03 00:51:03 - mmengine - INFO - Epoch(val) [1040][45/500] eta: 0:00:20 time: 0.0450 data_time: 0.0028 memory: 1008 2022/11/03 00:51:03 - mmengine - INFO - Epoch(val) [1040][50/500] eta: 0:00:19 time: 0.0435 data_time: 0.0028 memory: 1008 2022/11/03 00:51:03 - mmengine - INFO - Epoch(val) [1040][55/500] eta: 0:00:19 time: 0.0458 data_time: 0.0028 memory: 1008 2022/11/03 00:51:04 - mmengine - INFO - Epoch(val) [1040][60/500] eta: 0:00:20 time: 0.0456 data_time: 0.0028 memory: 1008 2022/11/03 00:51:04 - mmengine - INFO - Epoch(val) [1040][65/500] eta: 0:00:20 time: 0.0417 data_time: 0.0026 memory: 1008 2022/11/03 00:51:04 - mmengine - INFO - Epoch(val) [1040][70/500] eta: 0:00:18 time: 0.0432 data_time: 0.0027 memory: 1008 2022/11/03 00:51:04 - mmengine - INFO - Epoch(val) [1040][75/500] eta: 0:00:18 time: 0.0413 data_time: 0.0031 memory: 1008 2022/11/03 00:51:04 - mmengine - INFO - Epoch(val) [1040][80/500] eta: 0:00:15 time: 0.0365 data_time: 0.0028 memory: 1008 2022/11/03 00:51:05 - mmengine - INFO - Epoch(val) [1040][85/500] eta: 0:00:15 time: 0.0361 data_time: 0.0025 memory: 1008 2022/11/03 00:51:05 - mmengine - INFO - Epoch(val) [1040][90/500] eta: 0:00:17 time: 0.0416 data_time: 0.0028 memory: 1008 2022/11/03 00:51:05 - mmengine - INFO - Epoch(val) [1040][95/500] eta: 0:00:17 time: 0.0473 data_time: 0.0031 memory: 1008 2022/11/03 00:51:05 - mmengine - INFO - Epoch(val) [1040][100/500] eta: 0:00:18 time: 0.0457 data_time: 0.0032 memory: 1008 2022/11/03 00:51:05 - mmengine - INFO - Epoch(val) [1040][105/500] eta: 0:00:18 time: 0.0414 data_time: 0.0030 memory: 1008 2022/11/03 00:51:06 - mmengine - INFO - Epoch(val) [1040][110/500] eta: 0:00:15 time: 0.0406 data_time: 0.0032 memory: 1008 2022/11/03 00:51:06 - mmengine - INFO - Epoch(val) [1040][115/500] eta: 0:00:15 time: 0.0433 data_time: 0.0033 memory: 1008 2022/11/03 00:51:06 - mmengine - INFO - Epoch(val) [1040][120/500] eta: 0:00:16 time: 0.0440 data_time: 0.0033 memory: 1008 2022/11/03 00:51:06 - mmengine - INFO - Epoch(val) [1040][125/500] eta: 0:00:16 time: 0.0408 data_time: 0.0032 memory: 1008 2022/11/03 00:51:07 - mmengine - INFO - Epoch(val) [1040][130/500] eta: 0:00:14 time: 0.0395 data_time: 0.0027 memory: 1008 2022/11/03 00:51:07 - mmengine - INFO - Epoch(val) [1040][135/500] eta: 0:00:14 time: 0.0402 data_time: 0.0029 memory: 1008 2022/11/03 00:51:07 - mmengine - INFO - Epoch(val) [1040][140/500] eta: 0:00:15 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/03 00:51:07 - mmengine - INFO - Epoch(val) [1040][145/500] eta: 0:00:15 time: 0.0479 data_time: 0.0034 memory: 1008 2022/11/03 00:51:07 - mmengine - INFO - Epoch(val) [1040][150/500] eta: 0:00:15 time: 0.0449 data_time: 0.0032 memory: 1008 2022/11/03 00:51:08 - mmengine - INFO - Epoch(val) [1040][155/500] eta: 0:00:15 time: 0.0469 data_time: 0.0027 memory: 1008 2022/11/03 00:51:08 - mmengine - INFO - Epoch(val) [1040][160/500] eta: 0:00:16 time: 0.0491 data_time: 0.0030 memory: 1008 2022/11/03 00:51:08 - mmengine - INFO - Epoch(val) [1040][165/500] eta: 0:00:16 time: 0.0466 data_time: 0.0033 memory: 1008 2022/11/03 00:51:08 - mmengine - INFO - Epoch(val) [1040][170/500] eta: 0:00:14 time: 0.0450 data_time: 0.0031 memory: 1008 2022/11/03 00:51:09 - mmengine - INFO - Epoch(val) [1040][175/500] eta: 0:00:14 time: 0.0426 data_time: 0.0033 memory: 1008 2022/11/03 00:51:09 - mmengine - INFO - Epoch(val) [1040][180/500] eta: 0:00:13 time: 0.0431 data_time: 0.0034 memory: 1008 2022/11/03 00:51:09 - mmengine - INFO - Epoch(val) [1040][185/500] eta: 0:00:13 time: 0.0430 data_time: 0.0029 memory: 1008 2022/11/03 00:51:09 - mmengine - INFO - Epoch(val) [1040][190/500] eta: 0:00:14 time: 0.0466 data_time: 0.0031 memory: 1008 2022/11/03 00:51:09 - mmengine - INFO - Epoch(val) [1040][195/500] eta: 0:00:14 time: 0.0443 data_time: 0.0033 memory: 1008 2022/11/03 00:51:10 - mmengine - INFO - Epoch(val) [1040][200/500] eta: 0:00:14 time: 0.0468 data_time: 0.0032 memory: 1008 2022/11/03 00:51:10 - mmengine - INFO - Epoch(val) [1040][205/500] eta: 0:00:14 time: 0.0467 data_time: 0.0030 memory: 1008 2022/11/03 00:51:10 - mmengine - INFO - Epoch(val) [1040][210/500] eta: 0:00:12 time: 0.0415 data_time: 0.0031 memory: 1008 2022/11/03 00:51:10 - mmengine - INFO - Epoch(val) [1040][215/500] eta: 0:00:12 time: 0.0464 data_time: 0.0035 memory: 1008 2022/11/03 00:51:11 - mmengine - INFO - Epoch(val) [1040][220/500] eta: 0:00:12 time: 0.0436 data_time: 0.0031 memory: 1008 2022/11/03 00:51:11 - mmengine - INFO - Epoch(val) [1040][225/500] eta: 0:00:12 time: 0.0406 data_time: 0.0026 memory: 1008 2022/11/03 00:51:11 - mmengine - INFO - Epoch(val) [1040][230/500] eta: 0:00:11 time: 0.0410 data_time: 0.0029 memory: 1008 2022/11/03 00:51:11 - mmengine - INFO - Epoch(val) [1040][235/500] eta: 0:00:11 time: 0.0416 data_time: 0.0033 memory: 1008 2022/11/03 00:51:11 - mmengine - INFO - Epoch(val) [1040][240/500] eta: 0:00:11 time: 0.0441 data_time: 0.0033 memory: 1008 2022/11/03 00:51:12 - mmengine - INFO - Epoch(val) [1040][245/500] eta: 0:00:11 time: 0.0413 data_time: 0.0031 memory: 1008 2022/11/03 00:51:12 - mmengine - INFO - Epoch(val) [1040][250/500] eta: 0:00:10 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/03 00:51:12 - mmengine - INFO - Epoch(val) [1040][255/500] eta: 0:00:10 time: 0.0442 data_time: 0.0031 memory: 1008 2022/11/03 00:51:12 - mmengine - INFO - Epoch(val) [1040][260/500] eta: 0:00:10 time: 0.0419 data_time: 0.0030 memory: 1008 2022/11/03 00:51:12 - mmengine - INFO - Epoch(val) [1040][265/500] eta: 0:00:10 time: 0.0405 data_time: 0.0028 memory: 1008 2022/11/03 00:51:13 - mmengine - INFO - Epoch(val) [1040][270/500] eta: 0:00:09 time: 0.0421 data_time: 0.0028 memory: 1008 2022/11/03 00:51:13 - mmengine - INFO - Epoch(val) [1040][275/500] eta: 0:00:09 time: 0.0405 data_time: 0.0027 memory: 1008 2022/11/03 00:51:13 - mmengine - INFO - Epoch(val) [1040][280/500] eta: 0:00:09 time: 0.0436 data_time: 0.0031 memory: 1008 2022/11/03 00:51:13 - mmengine - INFO - Epoch(val) [1040][285/500] eta: 0:00:09 time: 0.0438 data_time: 0.0033 memory: 1008 2022/11/03 00:51:14 - mmengine - INFO - Epoch(val) [1040][290/500] eta: 0:00:08 time: 0.0422 data_time: 0.0033 memory: 1008 2022/11/03 00:51:14 - mmengine - INFO - Epoch(val) [1040][295/500] eta: 0:00:08 time: 0.0453 data_time: 0.0032 memory: 1008 2022/11/03 00:51:14 - mmengine - INFO - Epoch(val) [1040][300/500] eta: 0:00:08 time: 0.0413 data_time: 0.0034 memory: 1008 2022/11/03 00:51:14 - mmengine - INFO - Epoch(val) [1040][305/500] eta: 0:00:08 time: 0.0394 data_time: 0.0032 memory: 1008 2022/11/03 00:51:14 - mmengine - INFO - Epoch(val) [1040][310/500] eta: 0:00:07 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/03 00:51:15 - mmengine - INFO - Epoch(val) [1040][315/500] eta: 0:00:07 time: 0.0419 data_time: 0.0026 memory: 1008 2022/11/03 00:51:15 - mmengine - INFO - Epoch(val) [1040][320/500] eta: 0:00:07 time: 0.0418 data_time: 0.0027 memory: 1008 2022/11/03 00:51:15 - mmengine - INFO - Epoch(val) [1040][325/500] eta: 0:00:07 time: 0.0538 data_time: 0.0029 memory: 1008 2022/11/03 00:51:15 - mmengine - INFO - Epoch(val) [1040][330/500] eta: 0:00:08 time: 0.0528 data_time: 0.0027 memory: 1008 2022/11/03 00:51:16 - mmengine - INFO - Epoch(val) [1040][335/500] eta: 0:00:08 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/03 00:51:16 - mmengine - INFO - Epoch(val) [1040][340/500] eta: 0:00:08 time: 0.0530 data_time: 0.0028 memory: 1008 2022/11/03 00:51:16 - mmengine - INFO - Epoch(val) [1040][345/500] eta: 0:00:08 time: 0.0584 data_time: 0.0030 memory: 1008 2022/11/03 00:51:16 - mmengine - INFO - Epoch(val) [1040][350/500] eta: 0:00:07 time: 0.0514 data_time: 0.0029 memory: 1008 2022/11/03 00:51:17 - mmengine - INFO - Epoch(val) [1040][355/500] eta: 0:00:07 time: 0.0458 data_time: 0.0027 memory: 1008 2022/11/03 00:51:17 - mmengine - INFO - Epoch(val) [1040][360/500] eta: 0:00:06 time: 0.0434 data_time: 0.0027 memory: 1008 2022/11/03 00:51:17 - mmengine - INFO - Epoch(val) [1040][365/500] eta: 0:00:06 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/03 00:51:17 - mmengine - INFO - Epoch(val) [1040][370/500] eta: 0:00:05 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/03 00:51:17 - mmengine - INFO - Epoch(val) [1040][375/500] eta: 0:00:05 time: 0.0449 data_time: 0.0029 memory: 1008 2022/11/03 00:51:18 - mmengine - INFO - Epoch(val) [1040][380/500] eta: 0:00:05 time: 0.0492 data_time: 0.0030 memory: 1008 2022/11/03 00:51:18 - mmengine - INFO - Epoch(val) [1040][385/500] eta: 0:00:05 time: 0.0465 data_time: 0.0029 memory: 1008 2022/11/03 00:51:18 - mmengine - INFO - Epoch(val) [1040][390/500] eta: 0:00:04 time: 0.0437 data_time: 0.0027 memory: 1008 2022/11/03 00:51:18 - mmengine - INFO - Epoch(val) [1040][395/500] eta: 0:00:04 time: 0.0417 data_time: 0.0025 memory: 1008 2022/11/03 00:51:19 - mmengine - INFO - Epoch(val) [1040][400/500] eta: 0:00:04 time: 0.0459 data_time: 0.0030 memory: 1008 2022/11/03 00:51:19 - mmengine - INFO - Epoch(val) [1040][405/500] eta: 0:00:04 time: 0.0492 data_time: 0.0035 memory: 1008 2022/11/03 00:51:19 - mmengine - INFO - Epoch(val) [1040][410/500] eta: 0:00:04 time: 0.0458 data_time: 0.0032 memory: 1008 2022/11/03 00:51:19 - mmengine - INFO - Epoch(val) [1040][415/500] eta: 0:00:04 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/03 00:51:19 - mmengine - INFO - Epoch(val) [1040][420/500] eta: 0:00:03 time: 0.0400 data_time: 0.0030 memory: 1008 2022/11/03 00:51:20 - mmengine - INFO - Epoch(val) [1040][425/500] eta: 0:00:03 time: 0.0441 data_time: 0.0031 memory: 1008 2022/11/03 00:51:20 - mmengine - INFO - Epoch(val) [1040][430/500] eta: 0:00:03 time: 0.0447 data_time: 0.0029 memory: 1008 2022/11/03 00:51:20 - mmengine - INFO - Epoch(val) [1040][435/500] eta: 0:00:03 time: 0.0424 data_time: 0.0028 memory: 1008 2022/11/03 00:51:20 - mmengine - INFO - Epoch(val) [1040][440/500] eta: 0:00:02 time: 0.0450 data_time: 0.0031 memory: 1008 2022/11/03 00:51:21 - mmengine - INFO - Epoch(val) [1040][445/500] eta: 0:00:02 time: 0.0455 data_time: 0.0034 memory: 1008 2022/11/03 00:51:21 - mmengine - INFO - Epoch(val) [1040][450/500] eta: 0:00:02 time: 0.0468 data_time: 0.0035 memory: 1008 2022/11/03 00:51:21 - mmengine - INFO - Epoch(val) [1040][455/500] eta: 0:00:02 time: 0.0460 data_time: 0.0033 memory: 1008 2022/11/03 00:51:21 - mmengine - INFO - Epoch(val) [1040][460/500] eta: 0:00:01 time: 0.0393 data_time: 0.0029 memory: 1008 2022/11/03 00:51:21 - mmengine - INFO - Epoch(val) [1040][465/500] eta: 0:00:01 time: 0.0431 data_time: 0.0052 memory: 1008 2022/11/03 00:51:22 - mmengine - INFO - Epoch(val) [1040][470/500] eta: 0:00:01 time: 0.0461 data_time: 0.0054 memory: 1008 2022/11/03 00:51:22 - mmengine - INFO - Epoch(val) [1040][475/500] eta: 0:00:01 time: 0.0408 data_time: 0.0030 memory: 1008 2022/11/03 00:51:22 - mmengine - INFO - Epoch(val) [1040][480/500] eta: 0:00:00 time: 0.0411 data_time: 0.0026 memory: 1008 2022/11/03 00:51:22 - mmengine - INFO - Epoch(val) [1040][485/500] eta: 0:00:00 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/03 00:51:23 - mmengine - INFO - Epoch(val) [1040][490/500] eta: 0:00:00 time: 0.0417 data_time: 0.0029 memory: 1008 2022/11/03 00:51:23 - mmengine - INFO - Epoch(val) [1040][495/500] eta: 0:00:00 time: 0.0474 data_time: 0.0032 memory: 1008 2022/11/03 00:51:23 - mmengine - INFO - Epoch(val) [1040][500/500] eta: 0:00:00 time: 0.0475 data_time: 0.0036 memory: 1008 2022/11/03 00:51:23 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8296, precision: 0.7459, hmean: 0.7855 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8296, precision: 0.7907, hmean: 0.8097 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8296, precision: 0.8181, hmean: 0.8238 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8267, precision: 0.8417, hmean: 0.8341 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8146, precision: 0.8677, hmean: 0.8403 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7347, precision: 0.9083, hmean: 0.8124 2022/11/03 00:51:23 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1839, precision: 0.9409, hmean: 0.3077 2022/11/03 00:51:23 - mmengine - INFO - Epoch(val) [1040][500/500] icdar/precision: 0.8677 icdar/recall: 0.8146 icdar/hmean: 0.8403 2022/11/03 00:51:30 - mmengine - INFO - Epoch(train) [1041][5/63] lr: 3.5115e-04 eta: 0:00:00 time: 1.0318 data_time: 0.2595 memory: 14901 loss: 0.9107 loss_prob: 0.4693 loss_thr: 0.3598 loss_db: 0.0816 2022/11/03 00:51:34 - mmengine - INFO - Epoch(train) [1041][10/63] lr: 3.5115e-04 eta: 1:50:15 time: 1.0407 data_time: 0.2552 memory: 14901 loss: 0.8529 loss_prob: 0.4354 loss_thr: 0.3429 loss_db: 0.0745 2022/11/03 00:51:39 - mmengine - INFO - Epoch(train) [1041][15/63] lr: 3.5115e-04 eta: 1:50:15 time: 0.8322 data_time: 0.0084 memory: 14901 loss: 0.8416 loss_prob: 0.4299 loss_thr: 0.3368 loss_db: 0.0749 2022/11/03 00:51:43 - mmengine - INFO - Epoch(train) [1041][20/63] lr: 3.5115e-04 eta: 1:50:09 time: 0.9085 data_time: 0.0082 memory: 14901 loss: 0.8366 loss_prob: 0.4291 loss_thr: 0.3317 loss_db: 0.0759 2022/11/03 00:51:45 - mmengine - INFO - Epoch(train) [1041][25/63] lr: 3.5115e-04 eta: 1:50:09 time: 0.6782 data_time: 0.0156 memory: 14901 loss: 0.8641 loss_prob: 0.4502 loss_thr: 0.3361 loss_db: 0.0779 2022/11/03 00:51:49 - mmengine - INFO - Epoch(train) [1041][30/63] lr: 3.5115e-04 eta: 1:50:02 time: 0.6181 data_time: 0.0377 memory: 14901 loss: 0.8628 loss_prob: 0.4471 loss_thr: 0.3385 loss_db: 0.0771 2022/11/03 00:51:53 - mmengine - INFO - Epoch(train) [1041][35/63] lr: 3.5115e-04 eta: 1:50:02 time: 0.7596 data_time: 0.0276 memory: 14901 loss: 0.8517 loss_prob: 0.4412 loss_thr: 0.3329 loss_db: 0.0776 2022/11/03 00:51:57 - mmengine - INFO - Epoch(train) [1041][40/63] lr: 3.5115e-04 eta: 1:49:56 time: 0.8582 data_time: 0.0065 memory: 14901 loss: 0.8673 loss_prob: 0.4546 loss_thr: 0.3340 loss_db: 0.0787 2022/11/03 00:52:01 - mmengine - INFO - Epoch(train) [1041][45/63] lr: 3.5115e-04 eta: 1:49:56 time: 0.7732 data_time: 0.0076 memory: 14901 loss: 0.9268 loss_prob: 0.4845 loss_thr: 0.3586 loss_db: 0.0836 2022/11/03 00:52:04 - mmengine - INFO - Epoch(train) [1041][50/63] lr: 3.5115e-04 eta: 1:49:49 time: 0.6971 data_time: 0.0241 memory: 14901 loss: 0.9414 loss_prob: 0.4837 loss_thr: 0.3724 loss_db: 0.0853 2022/11/03 00:52:07 - mmengine - INFO - Epoch(train) [1041][55/63] lr: 3.5115e-04 eta: 1:49:49 time: 0.6124 data_time: 0.0237 memory: 14901 loss: 0.9396 loss_prob: 0.4906 loss_thr: 0.3638 loss_db: 0.0852 2022/11/03 00:52:10 - mmengine - INFO - Epoch(train) [1041][60/63] lr: 3.5115e-04 eta: 1:49:43 time: 0.5964 data_time: 0.0061 memory: 14901 loss: 0.8969 loss_prob: 0.4639 loss_thr: 0.3527 loss_db: 0.0803 2022/11/03 00:52:12 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:52:20 - mmengine - INFO - Epoch(train) [1042][5/63] lr: 3.4916e-04 eta: 1:49:43 time: 1.1119 data_time: 0.2681 memory: 14901 loss: 0.8600 loss_prob: 0.4427 loss_thr: 0.3415 loss_db: 0.0758 2022/11/03 00:52:24 - mmengine - INFO - Epoch(train) [1042][10/63] lr: 3.4916e-04 eta: 1:49:35 time: 1.1540 data_time: 0.2677 memory: 14901 loss: 0.9160 loss_prob: 0.4909 loss_thr: 0.3407 loss_db: 0.0844 2022/11/03 00:52:27 - mmengine - INFO - Epoch(train) [1042][15/63] lr: 3.4916e-04 eta: 1:49:35 time: 0.6550 data_time: 0.0067 memory: 14901 loss: 1.0312 loss_prob: 0.5666 loss_thr: 0.3720 loss_db: 0.0925 2022/11/03 00:52:30 - mmengine - INFO - Epoch(train) [1042][20/63] lr: 3.4916e-04 eta: 1:49:28 time: 0.6163 data_time: 0.0061 memory: 14901 loss: 1.0800 loss_prob: 0.5820 loss_thr: 0.4038 loss_db: 0.0943 2022/11/03 00:52:32 - mmengine - INFO - Epoch(train) [1042][25/63] lr: 3.4916e-04 eta: 1:49:28 time: 0.5613 data_time: 0.0153 memory: 14901 loss: 0.9202 loss_prob: 0.4846 loss_thr: 0.3522 loss_db: 0.0834 2022/11/03 00:52:35 - mmengine - INFO - Epoch(train) [1042][30/63] lr: 3.4916e-04 eta: 1:49:21 time: 0.5285 data_time: 0.0422 memory: 14901 loss: 0.8962 loss_prob: 0.4651 loss_thr: 0.3481 loss_db: 0.0830 2022/11/03 00:52:39 - mmengine - INFO - Epoch(train) [1042][35/63] lr: 3.4916e-04 eta: 1:49:21 time: 0.6729 data_time: 0.0362 memory: 14901 loss: 0.9453 loss_prob: 0.4925 loss_thr: 0.3651 loss_db: 0.0877 2022/11/03 00:52:42 - mmengine - INFO - Epoch(train) [1042][40/63] lr: 3.4916e-04 eta: 1:49:15 time: 0.6635 data_time: 0.0094 memory: 14901 loss: 0.9213 loss_prob: 0.4784 loss_thr: 0.3594 loss_db: 0.0835 2022/11/03 00:52:44 - mmengine - INFO - Epoch(train) [1042][45/63] lr: 3.4916e-04 eta: 1:49:15 time: 0.5375 data_time: 0.0090 memory: 14901 loss: 0.9284 loss_prob: 0.4793 loss_thr: 0.3663 loss_db: 0.0827 2022/11/03 00:52:47 - mmengine - INFO - Epoch(train) [1042][50/63] lr: 3.4916e-04 eta: 1:49:08 time: 0.5572 data_time: 0.0316 memory: 14901 loss: 0.9507 loss_prob: 0.4844 loss_thr: 0.3826 loss_db: 0.0837 2022/11/03 00:52:51 - mmengine - INFO - Epoch(train) [1042][55/63] lr: 3.4916e-04 eta: 1:49:08 time: 0.6648 data_time: 0.0550 memory: 14901 loss: 0.9170 loss_prob: 0.4726 loss_thr: 0.3632 loss_db: 0.0812 2022/11/03 00:52:54 - mmengine - INFO - Epoch(train) [1042][60/63] lr: 3.4916e-04 eta: 1:49:01 time: 0.6639 data_time: 0.0336 memory: 14901 loss: 0.8912 loss_prob: 0.4670 loss_thr: 0.3427 loss_db: 0.0815 2022/11/03 00:52:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:53:04 - mmengine - INFO - Epoch(train) [1043][5/63] lr: 3.4717e-04 eta: 1:49:01 time: 1.1651 data_time: 0.2993 memory: 14901 loss: 0.8576 loss_prob: 0.4364 loss_thr: 0.3444 loss_db: 0.0768 2022/11/03 00:53:09 - mmengine - INFO - Epoch(train) [1043][10/63] lr: 3.4717e-04 eta: 1:48:53 time: 1.3482 data_time: 0.2967 memory: 14901 loss: 0.9244 loss_prob: 0.4813 loss_thr: 0.3600 loss_db: 0.0831 2022/11/03 00:53:12 - mmengine - INFO - Epoch(train) [1043][15/63] lr: 3.4717e-04 eta: 1:48:53 time: 0.7780 data_time: 0.0067 memory: 14901 loss: 0.8849 loss_prob: 0.4684 loss_thr: 0.3355 loss_db: 0.0810 2022/11/03 00:53:15 - mmengine - INFO - Epoch(train) [1043][20/63] lr: 3.4717e-04 eta: 1:48:47 time: 0.5796 data_time: 0.0054 memory: 14901 loss: 0.8838 loss_prob: 0.4602 loss_thr: 0.3429 loss_db: 0.0807 2022/11/03 00:53:18 - mmengine - INFO - Epoch(train) [1043][25/63] lr: 3.4717e-04 eta: 1:48:47 time: 0.6258 data_time: 0.0413 memory: 14901 loss: 0.9296 loss_prob: 0.4841 loss_thr: 0.3616 loss_db: 0.0839 2022/11/03 00:53:22 - mmengine - INFO - Epoch(train) [1043][30/63] lr: 3.4717e-04 eta: 1:48:40 time: 0.6816 data_time: 0.0435 memory: 14901 loss: 0.9040 loss_prob: 0.4749 loss_thr: 0.3470 loss_db: 0.0822 2022/11/03 00:53:26 - mmengine - INFO - Epoch(train) [1043][35/63] lr: 3.4717e-04 eta: 1:48:40 time: 0.7096 data_time: 0.0071 memory: 14901 loss: 0.8781 loss_prob: 0.4566 loss_thr: 0.3412 loss_db: 0.0804 2022/11/03 00:53:29 - mmengine - INFO - Epoch(train) [1043][40/63] lr: 3.4717e-04 eta: 1:48:34 time: 0.6839 data_time: 0.0052 memory: 14901 loss: 0.8095 loss_prob: 0.4159 loss_thr: 0.3209 loss_db: 0.0727 2022/11/03 00:53:31 - mmengine - INFO - Epoch(train) [1043][45/63] lr: 3.4717e-04 eta: 1:48:34 time: 0.5602 data_time: 0.0056 memory: 14901 loss: 0.8361 loss_prob: 0.4262 loss_thr: 0.3358 loss_db: 0.0741 2022/11/03 00:53:35 - mmengine - INFO - Epoch(train) [1043][50/63] lr: 3.4717e-04 eta: 1:48:27 time: 0.6416 data_time: 0.0246 memory: 14901 loss: 0.9855 loss_prob: 0.5014 loss_thr: 0.3969 loss_db: 0.0872 2022/11/03 00:53:38 - mmengine - INFO - Epoch(train) [1043][55/63] lr: 3.4717e-04 eta: 1:48:27 time: 0.7184 data_time: 0.0260 memory: 14901 loss: 0.9802 loss_prob: 0.5049 loss_thr: 0.3878 loss_db: 0.0876 2022/11/03 00:53:41 - mmengine - INFO - Epoch(train) [1043][60/63] lr: 3.4717e-04 eta: 1:48:20 time: 0.6018 data_time: 0.0075 memory: 14901 loss: 0.9449 loss_prob: 0.5037 loss_thr: 0.3492 loss_db: 0.0919 2022/11/03 00:53:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:53:49 - mmengine - INFO - Epoch(train) [1044][5/63] lr: 3.4518e-04 eta: 1:48:20 time: 0.8754 data_time: 0.2532 memory: 14901 loss: 0.9386 loss_prob: 0.4983 loss_thr: 0.3494 loss_db: 0.0909 2022/11/03 00:53:54 - mmengine - INFO - Epoch(train) [1044][10/63] lr: 3.4518e-04 eta: 1:48:12 time: 1.1620 data_time: 0.2723 memory: 14901 loss: 0.8852 loss_prob: 0.4594 loss_thr: 0.3471 loss_db: 0.0787 2022/11/03 00:53:59 - mmengine - INFO - Epoch(train) [1044][15/63] lr: 3.4518e-04 eta: 1:48:12 time: 1.0128 data_time: 0.0257 memory: 14901 loss: 0.9701 loss_prob: 0.5114 loss_thr: 0.3708 loss_db: 0.0879 2022/11/03 00:54:02 - mmengine - INFO - Epoch(train) [1044][20/63] lr: 3.4518e-04 eta: 1:48:06 time: 0.8300 data_time: 0.0064 memory: 14901 loss: 0.9434 loss_prob: 0.4997 loss_thr: 0.3584 loss_db: 0.0854 2022/11/03 00:54:06 - mmengine - INFO - Epoch(train) [1044][25/63] lr: 3.4518e-04 eta: 1:48:06 time: 0.7186 data_time: 0.0330 memory: 14901 loss: 0.8973 loss_prob: 0.4669 loss_thr: 0.3500 loss_db: 0.0804 2022/11/03 00:54:09 - mmengine - INFO - Epoch(train) [1044][30/63] lr: 3.4518e-04 eta: 1:48:00 time: 0.7122 data_time: 0.0329 memory: 14901 loss: 0.9561 loss_prob: 0.5004 loss_thr: 0.3687 loss_db: 0.0870 2022/11/03 00:54:13 - mmengine - INFO - Epoch(train) [1044][35/63] lr: 3.4518e-04 eta: 1:48:00 time: 0.7089 data_time: 0.0154 memory: 14901 loss: 0.9760 loss_prob: 0.5125 loss_thr: 0.3724 loss_db: 0.0911 2022/11/03 00:54:17 - mmengine - INFO - Epoch(train) [1044][40/63] lr: 3.4518e-04 eta: 1:47:53 time: 0.7389 data_time: 0.0159 memory: 14901 loss: 0.9744 loss_prob: 0.5102 loss_thr: 0.3742 loss_db: 0.0900 2022/11/03 00:54:22 - mmengine - INFO - Epoch(train) [1044][45/63] lr: 3.4518e-04 eta: 1:47:53 time: 0.8554 data_time: 0.0069 memory: 14901 loss: 0.9968 loss_prob: 0.5279 loss_thr: 0.3790 loss_db: 0.0898 2022/11/03 00:54:27 - mmengine - INFO - Epoch(train) [1044][50/63] lr: 3.4518e-04 eta: 1:47:47 time: 0.9751 data_time: 0.0246 memory: 14901 loss: 0.9247 loss_prob: 0.4816 loss_thr: 0.3581 loss_db: 0.0850 2022/11/03 00:54:30 - mmengine - INFO - Epoch(train) [1044][55/63] lr: 3.4518e-04 eta: 1:47:47 time: 0.8541 data_time: 0.0242 memory: 14901 loss: 0.8518 loss_prob: 0.4316 loss_thr: 0.3428 loss_db: 0.0774 2022/11/03 00:54:33 - mmengine - INFO - Epoch(train) [1044][60/63] lr: 3.4518e-04 eta: 1:47:40 time: 0.6296 data_time: 0.0091 memory: 14901 loss: 0.9092 loss_prob: 0.4690 loss_thr: 0.3585 loss_db: 0.0817 2022/11/03 00:54:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:54:41 - mmengine - INFO - Epoch(train) [1045][5/63] lr: 3.4319e-04 eta: 1:47:40 time: 0.9443 data_time: 0.2526 memory: 14901 loss: 0.8851 loss_prob: 0.4658 loss_thr: 0.3370 loss_db: 0.0822 2022/11/03 00:54:46 - mmengine - INFO - Epoch(train) [1045][10/63] lr: 3.4319e-04 eta: 1:47:32 time: 1.1662 data_time: 0.2618 memory: 14901 loss: 0.8833 loss_prob: 0.4585 loss_thr: 0.3424 loss_db: 0.0825 2022/11/03 00:54:50 - mmengine - INFO - Epoch(train) [1045][15/63] lr: 3.4319e-04 eta: 1:47:32 time: 0.8490 data_time: 0.0175 memory: 14901 loss: 0.9420 loss_prob: 0.4897 loss_thr: 0.3668 loss_db: 0.0855 2022/11/03 00:54:53 - mmengine - INFO - Epoch(train) [1045][20/63] lr: 3.4319e-04 eta: 1:47:26 time: 0.6848 data_time: 0.0082 memory: 14901 loss: 0.8848 loss_prob: 0.4528 loss_thr: 0.3529 loss_db: 0.0791 2022/11/03 00:54:56 - mmengine - INFO - Epoch(train) [1045][25/63] lr: 3.4319e-04 eta: 1:47:26 time: 0.5883 data_time: 0.0247 memory: 14901 loss: 0.8981 loss_prob: 0.4630 loss_thr: 0.3540 loss_db: 0.0812 2022/11/03 00:54:59 - mmengine - INFO - Epoch(train) [1045][30/63] lr: 3.4319e-04 eta: 1:47:19 time: 0.5723 data_time: 0.0336 memory: 14901 loss: 0.9322 loss_prob: 0.4857 loss_thr: 0.3619 loss_db: 0.0846 2022/11/03 00:55:02 - mmengine - INFO - Epoch(train) [1045][35/63] lr: 3.4319e-04 eta: 1:47:19 time: 0.5968 data_time: 0.0249 memory: 14901 loss: 0.8924 loss_prob: 0.4595 loss_thr: 0.3523 loss_db: 0.0806 2022/11/03 00:55:04 - mmengine - INFO - Epoch(train) [1045][40/63] lr: 3.4319e-04 eta: 1:47:12 time: 0.5633 data_time: 0.0143 memory: 14901 loss: 0.8888 loss_prob: 0.4555 loss_thr: 0.3534 loss_db: 0.0798 2022/11/03 00:55:07 - mmengine - INFO - Epoch(train) [1045][45/63] lr: 3.4319e-04 eta: 1:47:12 time: 0.5584 data_time: 0.0073 memory: 14901 loss: 0.9164 loss_prob: 0.4748 loss_thr: 0.3584 loss_db: 0.0832 2022/11/03 00:55:10 - mmengine - INFO - Epoch(train) [1045][50/63] lr: 3.4319e-04 eta: 1:47:06 time: 0.5514 data_time: 0.0178 memory: 14901 loss: 0.9004 loss_prob: 0.4710 loss_thr: 0.3466 loss_db: 0.0827 2022/11/03 00:55:14 - mmengine - INFO - Epoch(train) [1045][55/63] lr: 3.4319e-04 eta: 1:47:06 time: 0.6603 data_time: 0.0248 memory: 14901 loss: 0.8960 loss_prob: 0.4606 loss_thr: 0.3549 loss_db: 0.0805 2022/11/03 00:55:17 - mmengine - INFO - Epoch(train) [1045][60/63] lr: 3.4319e-04 eta: 1:46:59 time: 0.6746 data_time: 0.0148 memory: 14901 loss: 0.8592 loss_prob: 0.4331 loss_thr: 0.3507 loss_db: 0.0754 2022/11/03 00:55:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:55:27 - mmengine - INFO - Epoch(train) [1046][5/63] lr: 3.4120e-04 eta: 1:46:59 time: 1.1335 data_time: 0.2316 memory: 14901 loss: 0.9310 loss_prob: 0.4806 loss_thr: 0.3690 loss_db: 0.0815 2022/11/03 00:55:32 - mmengine - INFO - Epoch(train) [1046][10/63] lr: 3.4120e-04 eta: 1:46:51 time: 1.3176 data_time: 0.2441 memory: 14901 loss: 0.9948 loss_prob: 0.5239 loss_thr: 0.3812 loss_db: 0.0897 2022/11/03 00:55:35 - mmengine - INFO - Epoch(train) [1046][15/63] lr: 3.4120e-04 eta: 1:46:51 time: 0.7977 data_time: 0.0200 memory: 14901 loss: 0.9206 loss_prob: 0.4770 loss_thr: 0.3606 loss_db: 0.0829 2022/11/03 00:55:38 - mmengine - INFO - Epoch(train) [1046][20/63] lr: 3.4120e-04 eta: 1:46:45 time: 0.6043 data_time: 0.0073 memory: 14901 loss: 0.9025 loss_prob: 0.4677 loss_thr: 0.3558 loss_db: 0.0790 2022/11/03 00:55:41 - mmengine - INFO - Epoch(train) [1046][25/63] lr: 3.4120e-04 eta: 1:46:45 time: 0.6432 data_time: 0.0242 memory: 14901 loss: 0.9271 loss_prob: 0.4826 loss_thr: 0.3626 loss_db: 0.0819 2022/11/03 00:55:46 - mmengine - INFO - Epoch(train) [1046][30/63] lr: 3.4120e-04 eta: 1:46:38 time: 0.7889 data_time: 0.0394 memory: 14901 loss: 0.8421 loss_prob: 0.4303 loss_thr: 0.3363 loss_db: 0.0755 2022/11/03 00:55:49 - mmengine - INFO - Epoch(train) [1046][35/63] lr: 3.4120e-04 eta: 1:46:38 time: 0.7974 data_time: 0.0309 memory: 14901 loss: 0.7921 loss_prob: 0.3970 loss_thr: 0.3250 loss_db: 0.0700 2022/11/03 00:55:52 - mmengine - INFO - Epoch(train) [1046][40/63] lr: 3.4120e-04 eta: 1:46:32 time: 0.6117 data_time: 0.0156 memory: 14901 loss: 0.9266 loss_prob: 0.4661 loss_thr: 0.3775 loss_db: 0.0829 2022/11/03 00:55:55 - mmengine - INFO - Epoch(train) [1046][45/63] lr: 3.4120e-04 eta: 1:46:32 time: 0.6045 data_time: 0.0066 memory: 14901 loss: 0.9943 loss_prob: 0.5167 loss_thr: 0.3867 loss_db: 0.0910 2022/11/03 00:55:59 - mmengine - INFO - Epoch(train) [1046][50/63] lr: 3.4120e-04 eta: 1:46:25 time: 0.6937 data_time: 0.0101 memory: 14901 loss: 0.9277 loss_prob: 0.4856 loss_thr: 0.3576 loss_db: 0.0845 2022/11/03 00:56:01 - mmengine - INFO - Epoch(train) [1046][55/63] lr: 3.4120e-04 eta: 1:46:25 time: 0.6197 data_time: 0.0235 memory: 14901 loss: 0.8458 loss_prob: 0.4300 loss_thr: 0.3397 loss_db: 0.0761 2022/11/03 00:56:04 - mmengine - INFO - Epoch(train) [1046][60/63] lr: 3.4120e-04 eta: 1:46:18 time: 0.5463 data_time: 0.0203 memory: 14901 loss: 0.8117 loss_prob: 0.4088 loss_thr: 0.3290 loss_db: 0.0739 2022/11/03 00:56:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:56:14 - mmengine - INFO - Epoch(train) [1047][5/63] lr: 3.3920e-04 eta: 1:46:18 time: 1.1167 data_time: 0.2686 memory: 14901 loss: 0.9215 loss_prob: 0.4864 loss_thr: 0.3511 loss_db: 0.0840 2022/11/03 00:56:19 - mmengine - INFO - Epoch(train) [1047][10/63] lr: 3.3920e-04 eta: 1:46:10 time: 1.2606 data_time: 0.2688 memory: 14901 loss: 0.8664 loss_prob: 0.4430 loss_thr: 0.3454 loss_db: 0.0780 2022/11/03 00:56:25 - mmengine - INFO - Epoch(train) [1047][15/63] lr: 3.3920e-04 eta: 1:46:10 time: 1.0651 data_time: 0.0084 memory: 14901 loss: 0.8953 loss_prob: 0.4591 loss_thr: 0.3560 loss_db: 0.0802 2022/11/03 00:56:28 - mmengine - INFO - Epoch(train) [1047][20/63] lr: 3.3920e-04 eta: 1:46:04 time: 0.9560 data_time: 0.0084 memory: 14901 loss: 0.8713 loss_prob: 0.4524 loss_thr: 0.3396 loss_db: 0.0792 2022/11/03 00:56:31 - mmengine - INFO - Epoch(train) [1047][25/63] lr: 3.3920e-04 eta: 1:46:04 time: 0.6291 data_time: 0.0203 memory: 14901 loss: 0.8569 loss_prob: 0.4439 loss_thr: 0.3355 loss_db: 0.0775 2022/11/03 00:56:35 - mmengine - INFO - Epoch(train) [1047][30/63] lr: 3.3920e-04 eta: 1:45:58 time: 0.6493 data_time: 0.0571 memory: 14901 loss: 0.9294 loss_prob: 0.4864 loss_thr: 0.3594 loss_db: 0.0836 2022/11/03 00:56:38 - mmengine - INFO - Epoch(train) [1047][35/63] lr: 3.3920e-04 eta: 1:45:58 time: 0.6716 data_time: 0.0434 memory: 14901 loss: 1.0079 loss_prob: 0.5312 loss_thr: 0.3862 loss_db: 0.0905 2022/11/03 00:56:41 - mmengine - INFO - Epoch(train) [1047][40/63] lr: 3.3920e-04 eta: 1:45:51 time: 0.5706 data_time: 0.0068 memory: 14901 loss: 0.9860 loss_prob: 0.5099 loss_thr: 0.3861 loss_db: 0.0899 2022/11/03 00:56:43 - mmengine - INFO - Epoch(train) [1047][45/63] lr: 3.3920e-04 eta: 1:45:51 time: 0.5053 data_time: 0.0061 memory: 14901 loss: 0.9076 loss_prob: 0.4675 loss_thr: 0.3563 loss_db: 0.0837 2022/11/03 00:56:46 - mmengine - INFO - Epoch(train) [1047][50/63] lr: 3.3920e-04 eta: 1:45:44 time: 0.5080 data_time: 0.0206 memory: 14901 loss: 0.8547 loss_prob: 0.4447 loss_thr: 0.3320 loss_db: 0.0780 2022/11/03 00:56:48 - mmengine - INFO - Epoch(train) [1047][55/63] lr: 3.3920e-04 eta: 1:45:44 time: 0.5386 data_time: 0.0212 memory: 14901 loss: 0.8742 loss_prob: 0.4487 loss_thr: 0.3461 loss_db: 0.0793 2022/11/03 00:56:51 - mmengine - INFO - Epoch(train) [1047][60/63] lr: 3.3920e-04 eta: 1:45:37 time: 0.4960 data_time: 0.0050 memory: 14901 loss: 0.8726 loss_prob: 0.4450 loss_thr: 0.3487 loss_db: 0.0788 2022/11/03 00:56:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:56:57 - mmengine - INFO - Epoch(train) [1048][5/63] lr: 3.3721e-04 eta: 1:45:37 time: 0.7313 data_time: 0.2016 memory: 14901 loss: 0.8454 loss_prob: 0.4358 loss_thr: 0.3322 loss_db: 0.0773 2022/11/03 00:56:59 - mmengine - INFO - Epoch(train) [1048][10/63] lr: 3.3721e-04 eta: 1:45:29 time: 0.7508 data_time: 0.2015 memory: 14901 loss: 0.8853 loss_prob: 0.4588 loss_thr: 0.3457 loss_db: 0.0807 2022/11/03 00:57:02 - mmengine - INFO - Epoch(train) [1048][15/63] lr: 3.3721e-04 eta: 1:45:29 time: 0.5116 data_time: 0.0062 memory: 14901 loss: 0.8803 loss_prob: 0.4517 loss_thr: 0.3488 loss_db: 0.0799 2022/11/03 00:57:05 - mmengine - INFO - Epoch(train) [1048][20/63] lr: 3.3721e-04 eta: 1:45:22 time: 0.5286 data_time: 0.0076 memory: 14901 loss: 0.8979 loss_prob: 0.4690 loss_thr: 0.3455 loss_db: 0.0835 2022/11/03 00:57:07 - mmengine - INFO - Epoch(train) [1048][25/63] lr: 3.3721e-04 eta: 1:45:22 time: 0.5310 data_time: 0.0310 memory: 14901 loss: 0.9088 loss_prob: 0.4678 loss_thr: 0.3590 loss_db: 0.0820 2022/11/03 00:57:11 - mmengine - INFO - Epoch(train) [1048][30/63] lr: 3.3721e-04 eta: 1:45:15 time: 0.6395 data_time: 0.0361 memory: 14901 loss: 0.8999 loss_prob: 0.4378 loss_thr: 0.3862 loss_db: 0.0759 2022/11/03 00:57:20 - mmengine - INFO - Epoch(train) [1048][35/63] lr: 3.3721e-04 eta: 1:45:15 time: 1.2506 data_time: 0.0133 memory: 14901 loss: 0.9104 loss_prob: 0.4543 loss_thr: 0.3775 loss_db: 0.0785 2022/11/03 00:57:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:57:28 - mmengine - INFO - Epoch(train) [1048][40/63] lr: 3.3721e-04 eta: 1:45:10 time: 1.6918 data_time: 0.0110 memory: 14901 loss: 0.8600 loss_prob: 0.4504 loss_thr: 0.3310 loss_db: 0.0786 2022/11/03 00:57:34 - mmengine - INFO - Epoch(train) [1048][45/63] lr: 3.3721e-04 eta: 1:45:10 time: 1.4216 data_time: 0.0104 memory: 14901 loss: 0.8076 loss_prob: 0.4158 loss_thr: 0.3188 loss_db: 0.0730 2022/11/03 00:57:41 - mmengine - INFO - Epoch(train) [1048][50/63] lr: 3.3721e-04 eta: 1:45:05 time: 1.2723 data_time: 0.0256 memory: 14901 loss: 0.8687 loss_prob: 0.4492 loss_thr: 0.3411 loss_db: 0.0784 2022/11/03 00:57:44 - mmengine - INFO - Epoch(train) [1048][55/63] lr: 3.3721e-04 eta: 1:45:05 time: 1.0288 data_time: 0.0305 memory: 14901 loss: 0.9358 loss_prob: 0.4887 loss_thr: 0.3616 loss_db: 0.0855 2022/11/03 00:57:49 - mmengine - INFO - Epoch(train) [1048][60/63] lr: 3.3721e-04 eta: 1:44:58 time: 0.8384 data_time: 0.0129 memory: 14901 loss: 0.8987 loss_prob: 0.4624 loss_thr: 0.3572 loss_db: 0.0792 2022/11/03 00:57:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:57:59 - mmengine - INFO - Epoch(train) [1049][5/63] lr: 3.3521e-04 eta: 1:44:58 time: 1.1454 data_time: 0.3115 memory: 14901 loss: 0.8895 loss_prob: 0.4662 loss_thr: 0.3435 loss_db: 0.0798 2022/11/03 00:58:03 - mmengine - INFO - Epoch(train) [1049][10/63] lr: 3.3521e-04 eta: 1:44:50 time: 1.2490 data_time: 0.3128 memory: 14901 loss: 0.8602 loss_prob: 0.4373 loss_thr: 0.3456 loss_db: 0.0773 2022/11/03 00:58:10 - mmengine - INFO - Epoch(train) [1049][15/63] lr: 3.3521e-04 eta: 1:44:50 time: 1.1073 data_time: 0.0115 memory: 14901 loss: 0.9077 loss_prob: 0.4653 loss_thr: 0.3613 loss_db: 0.0810 2022/11/03 00:58:13 - mmengine - INFO - Epoch(train) [1049][20/63] lr: 3.3521e-04 eta: 1:44:44 time: 0.9730 data_time: 0.0094 memory: 14901 loss: 0.9858 loss_prob: 0.5267 loss_thr: 0.3720 loss_db: 0.0871 2022/11/03 00:58:17 - mmengine - INFO - Epoch(train) [1049][25/63] lr: 3.3521e-04 eta: 1:44:44 time: 0.7092 data_time: 0.0458 memory: 14901 loss: 0.9489 loss_prob: 0.5035 loss_thr: 0.3602 loss_db: 0.0853 2022/11/03 00:58:21 - mmengine - INFO - Epoch(train) [1049][30/63] lr: 3.3521e-04 eta: 1:44:38 time: 0.7651 data_time: 0.0457 memory: 14901 loss: 0.8801 loss_prob: 0.4482 loss_thr: 0.3522 loss_db: 0.0797 2022/11/03 00:58:24 - mmengine - INFO - Epoch(train) [1049][35/63] lr: 3.3521e-04 eta: 1:44:38 time: 0.7236 data_time: 0.0059 memory: 14901 loss: 0.8671 loss_prob: 0.4382 loss_thr: 0.3524 loss_db: 0.0765 2022/11/03 00:58:28 - mmengine - INFO - Epoch(train) [1049][40/63] lr: 3.3521e-04 eta: 1:44:31 time: 0.6839 data_time: 0.0061 memory: 14901 loss: 0.8882 loss_prob: 0.4578 loss_thr: 0.3508 loss_db: 0.0796 2022/11/03 00:58:30 - mmengine - INFO - Epoch(train) [1049][45/63] lr: 3.3521e-04 eta: 1:44:31 time: 0.6050 data_time: 0.0071 memory: 14901 loss: 0.9837 loss_prob: 0.5246 loss_thr: 0.3691 loss_db: 0.0899 2022/11/03 00:58:33 - mmengine - INFO - Epoch(train) [1049][50/63] lr: 3.3521e-04 eta: 1:44:25 time: 0.5852 data_time: 0.0283 memory: 14901 loss: 0.9890 loss_prob: 0.5239 loss_thr: 0.3755 loss_db: 0.0897 2022/11/03 00:58:36 - mmengine - INFO - Epoch(train) [1049][55/63] lr: 3.3521e-04 eta: 1:44:25 time: 0.5670 data_time: 0.0270 memory: 14901 loss: 0.8433 loss_prob: 0.4270 loss_thr: 0.3417 loss_db: 0.0746 2022/11/03 00:58:39 - mmengine - INFO - Epoch(train) [1049][60/63] lr: 3.3521e-04 eta: 1:44:18 time: 0.6062 data_time: 0.0061 memory: 14901 loss: 0.8009 loss_prob: 0.4025 loss_thr: 0.3270 loss_db: 0.0714 2022/11/03 00:58:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:58:48 - mmengine - INFO - Epoch(train) [1050][5/63] lr: 3.3321e-04 eta: 1:44:18 time: 0.9895 data_time: 0.2498 memory: 14901 loss: 0.9915 loss_prob: 0.5123 loss_thr: 0.3895 loss_db: 0.0898 2022/11/03 00:58:51 - mmengine - INFO - Epoch(train) [1050][10/63] lr: 3.3321e-04 eta: 1:44:10 time: 1.0159 data_time: 0.2654 memory: 14901 loss: 0.9557 loss_prob: 0.4907 loss_thr: 0.3796 loss_db: 0.0854 2022/11/03 00:58:56 - mmengine - INFO - Epoch(train) [1050][15/63] lr: 3.3321e-04 eta: 1:44:10 time: 0.8094 data_time: 0.0267 memory: 14901 loss: 0.9174 loss_prob: 0.4729 loss_thr: 0.3628 loss_db: 0.0816 2022/11/03 00:59:00 - mmengine - INFO - Epoch(train) [1050][20/63] lr: 3.3321e-04 eta: 1:44:03 time: 0.9458 data_time: 0.0128 memory: 14901 loss: 0.8523 loss_prob: 0.4372 loss_thr: 0.3404 loss_db: 0.0746 2022/11/03 00:59:05 - mmengine - INFO - Epoch(train) [1050][25/63] lr: 3.3321e-04 eta: 1:44:03 time: 0.8857 data_time: 0.0221 memory: 14901 loss: 0.8892 loss_prob: 0.4600 loss_thr: 0.3504 loss_db: 0.0787 2022/11/03 00:59:09 - mmengine - INFO - Epoch(train) [1050][30/63] lr: 3.3321e-04 eta: 1:43:57 time: 0.8454 data_time: 0.0390 memory: 14901 loss: 0.9091 loss_prob: 0.4772 loss_thr: 0.3492 loss_db: 0.0827 2022/11/03 00:59:13 - mmengine - INFO - Epoch(train) [1050][35/63] lr: 3.3321e-04 eta: 1:43:57 time: 0.7808 data_time: 0.0273 memory: 14901 loss: 0.8643 loss_prob: 0.4468 loss_thr: 0.3386 loss_db: 0.0788 2022/11/03 00:59:17 - mmengine - INFO - Epoch(train) [1050][40/63] lr: 3.3321e-04 eta: 1:43:51 time: 0.7657 data_time: 0.0115 memory: 14901 loss: 0.9458 loss_prob: 0.4929 loss_thr: 0.3659 loss_db: 0.0870 2022/11/03 00:59:20 - mmengine - INFO - Epoch(train) [1050][45/63] lr: 3.3321e-04 eta: 1:43:51 time: 0.7736 data_time: 0.0126 memory: 14901 loss: 0.9394 loss_prob: 0.4935 loss_thr: 0.3594 loss_db: 0.0865 2022/11/03 00:59:24 - mmengine - INFO - Epoch(train) [1050][50/63] lr: 3.3321e-04 eta: 1:43:44 time: 0.7829 data_time: 0.0260 memory: 14901 loss: 0.9004 loss_prob: 0.4759 loss_thr: 0.3404 loss_db: 0.0841 2022/11/03 00:59:29 - mmengine - INFO - Epoch(train) [1050][55/63] lr: 3.3321e-04 eta: 1:43:44 time: 0.8742 data_time: 0.0261 memory: 14901 loss: 0.8308 loss_prob: 0.4311 loss_thr: 0.3225 loss_db: 0.0772 2022/11/03 00:59:32 - mmengine - INFO - Epoch(train) [1050][60/63] lr: 3.3321e-04 eta: 1:43:38 time: 0.7888 data_time: 0.0139 memory: 14901 loss: 0.8099 loss_prob: 0.4076 loss_thr: 0.3306 loss_db: 0.0717 2022/11/03 00:59:34 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 00:59:42 - mmengine - INFO - Epoch(train) [1051][5/63] lr: 3.3121e-04 eta: 1:43:38 time: 1.0842 data_time: 0.2932 memory: 14901 loss: 0.8763 loss_prob: 0.4508 loss_thr: 0.3485 loss_db: 0.0770 2022/11/03 00:59:45 - mmengine - INFO - Epoch(train) [1051][10/63] lr: 3.3121e-04 eta: 1:43:30 time: 1.0683 data_time: 0.2938 memory: 14901 loss: 0.9299 loss_prob: 0.4948 loss_thr: 0.3496 loss_db: 0.0855 2022/11/03 00:59:49 - mmengine - INFO - Epoch(train) [1051][15/63] lr: 3.3121e-04 eta: 1:43:30 time: 0.7254 data_time: 0.0103 memory: 14901 loss: 0.8982 loss_prob: 0.4816 loss_thr: 0.3333 loss_db: 0.0833 2022/11/03 00:59:52 - mmengine - INFO - Epoch(train) [1051][20/63] lr: 3.3121e-04 eta: 1:43:23 time: 0.7144 data_time: 0.0090 memory: 14901 loss: 0.8377 loss_prob: 0.4391 loss_thr: 0.3208 loss_db: 0.0779 2022/11/03 00:59:55 - mmengine - INFO - Epoch(train) [1051][25/63] lr: 3.3121e-04 eta: 1:43:23 time: 0.5759 data_time: 0.0379 memory: 14901 loss: 0.8355 loss_prob: 0.4317 loss_thr: 0.3270 loss_db: 0.0768 2022/11/03 00:59:57 - mmengine - INFO - Epoch(train) [1051][30/63] lr: 3.3121e-04 eta: 1:43:16 time: 0.5621 data_time: 0.0407 memory: 14901 loss: 0.9007 loss_prob: 0.4584 loss_thr: 0.3607 loss_db: 0.0815 2022/11/03 01:00:01 - mmengine - INFO - Epoch(train) [1051][35/63] lr: 3.3121e-04 eta: 1:43:16 time: 0.5927 data_time: 0.0114 memory: 14901 loss: 0.9521 loss_prob: 0.4907 loss_thr: 0.3754 loss_db: 0.0861 2022/11/03 01:00:04 - mmengine - INFO - Epoch(train) [1051][40/63] lr: 3.3121e-04 eta: 1:43:10 time: 0.6819 data_time: 0.0099 memory: 14901 loss: 0.9370 loss_prob: 0.4916 loss_thr: 0.3612 loss_db: 0.0842 2022/11/03 01:00:08 - mmengine - INFO - Epoch(train) [1051][45/63] lr: 3.3121e-04 eta: 1:43:10 time: 0.7058 data_time: 0.0084 memory: 14901 loss: 0.8990 loss_prob: 0.4697 loss_thr: 0.3485 loss_db: 0.0808 2022/11/03 01:00:12 - mmengine - INFO - Epoch(train) [1051][50/63] lr: 3.3121e-04 eta: 1:43:03 time: 0.7488 data_time: 0.0249 memory: 14901 loss: 0.8545 loss_prob: 0.4339 loss_thr: 0.3438 loss_db: 0.0768 2022/11/03 01:00:15 - mmengine - INFO - Epoch(train) [1051][55/63] lr: 3.3121e-04 eta: 1:43:03 time: 0.6845 data_time: 0.0258 memory: 14901 loss: 0.8937 loss_prob: 0.4552 loss_thr: 0.3573 loss_db: 0.0812 2022/11/03 01:00:17 - mmengine - INFO - Epoch(train) [1051][60/63] lr: 3.3121e-04 eta: 1:42:57 time: 0.5676 data_time: 0.0098 memory: 14901 loss: 0.8665 loss_prob: 0.4398 loss_thr: 0.3493 loss_db: 0.0774 2022/11/03 01:00:19 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:00:25 - mmengine - INFO - Epoch(train) [1052][5/63] lr: 3.2921e-04 eta: 1:42:57 time: 0.9249 data_time: 0.2914 memory: 14901 loss: 0.9609 loss_prob: 0.4938 loss_thr: 0.3826 loss_db: 0.0845 2022/11/03 01:00:30 - mmengine - INFO - Epoch(train) [1052][10/63] lr: 3.2921e-04 eta: 1:42:48 time: 1.0257 data_time: 0.2908 memory: 14901 loss: 0.9243 loss_prob: 0.4795 loss_thr: 0.3620 loss_db: 0.0828 2022/11/03 01:00:34 - mmengine - INFO - Epoch(train) [1052][15/63] lr: 3.2921e-04 eta: 1:42:48 time: 0.8625 data_time: 0.0087 memory: 14901 loss: 0.8961 loss_prob: 0.4659 loss_thr: 0.3479 loss_db: 0.0823 2022/11/03 01:00:38 - mmengine - INFO - Epoch(train) [1052][20/63] lr: 3.2921e-04 eta: 1:42:42 time: 0.8749 data_time: 0.0068 memory: 14901 loss: 0.9395 loss_prob: 0.4835 loss_thr: 0.3723 loss_db: 0.0838 2022/11/03 01:00:44 - mmengine - INFO - Epoch(train) [1052][25/63] lr: 3.2921e-04 eta: 1:42:42 time: 0.9545 data_time: 0.0363 memory: 14901 loss: 0.8874 loss_prob: 0.4551 loss_thr: 0.3537 loss_db: 0.0786 2022/11/03 01:00:48 - mmengine - INFO - Epoch(train) [1052][30/63] lr: 3.2921e-04 eta: 1:42:36 time: 0.9236 data_time: 0.0485 memory: 14901 loss: 0.8191 loss_prob: 0.4158 loss_thr: 0.3285 loss_db: 0.0747 2022/11/03 01:00:53 - mmengine - INFO - Epoch(train) [1052][35/63] lr: 3.2921e-04 eta: 1:42:36 time: 0.9212 data_time: 0.0205 memory: 14901 loss: 0.8770 loss_prob: 0.4516 loss_thr: 0.3440 loss_db: 0.0814 2022/11/03 01:00:56 - mmengine - INFO - Epoch(train) [1052][40/63] lr: 3.2921e-04 eta: 1:42:30 time: 0.8565 data_time: 0.0085 memory: 14901 loss: 0.9055 loss_prob: 0.4685 loss_thr: 0.3542 loss_db: 0.0829 2022/11/03 01:01:00 - mmengine - INFO - Epoch(train) [1052][45/63] lr: 3.2921e-04 eta: 1:42:30 time: 0.6903 data_time: 0.0061 memory: 14901 loss: 0.8243 loss_prob: 0.4148 loss_thr: 0.3370 loss_db: 0.0725 2022/11/03 01:01:03 - mmengine - INFO - Epoch(train) [1052][50/63] lr: 3.2921e-04 eta: 1:42:23 time: 0.6788 data_time: 0.0253 memory: 14901 loss: 0.7892 loss_prob: 0.3924 loss_thr: 0.3296 loss_db: 0.0672 2022/11/03 01:01:06 - mmengine - INFO - Epoch(train) [1052][55/63] lr: 3.2921e-04 eta: 1:42:23 time: 0.6508 data_time: 0.0273 memory: 14901 loss: 0.8813 loss_prob: 0.4558 loss_thr: 0.3478 loss_db: 0.0777 2022/11/03 01:01:09 - mmengine - INFO - Epoch(train) [1052][60/63] lr: 3.2921e-04 eta: 1:42:16 time: 0.5986 data_time: 0.0076 memory: 14901 loss: 0.9406 loss_prob: 0.4941 loss_thr: 0.3597 loss_db: 0.0868 2022/11/03 01:01:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:01:20 - mmengine - INFO - Epoch(train) [1053][5/63] lr: 3.2721e-04 eta: 1:42:16 time: 1.1857 data_time: 0.2803 memory: 14901 loss: 0.9633 loss_prob: 0.5039 loss_thr: 0.3704 loss_db: 0.0890 2022/11/03 01:01:24 - mmengine - INFO - Epoch(train) [1053][10/63] lr: 3.2721e-04 eta: 1:42:09 time: 1.4114 data_time: 0.2806 memory: 14901 loss: 0.8663 loss_prob: 0.4437 loss_thr: 0.3452 loss_db: 0.0774 2022/11/03 01:01:29 - mmengine - INFO - Epoch(train) [1053][15/63] lr: 3.2721e-04 eta: 1:42:09 time: 0.9292 data_time: 0.0083 memory: 14901 loss: 0.9659 loss_prob: 0.4927 loss_thr: 0.3874 loss_db: 0.0858 2022/11/03 01:01:32 - mmengine - INFO - Epoch(train) [1053][20/63] lr: 3.2721e-04 eta: 1:42:02 time: 0.7561 data_time: 0.0076 memory: 14901 loss: 0.9394 loss_prob: 0.4763 loss_thr: 0.3791 loss_db: 0.0840 2022/11/03 01:01:35 - mmengine - INFO - Epoch(train) [1053][25/63] lr: 3.2721e-04 eta: 1:42:02 time: 0.6258 data_time: 0.0471 memory: 14901 loss: 0.8743 loss_prob: 0.4481 loss_thr: 0.3468 loss_db: 0.0793 2022/11/03 01:01:40 - mmengine - INFO - Epoch(train) [1053][30/63] lr: 3.2721e-04 eta: 1:41:56 time: 0.8465 data_time: 0.0519 memory: 14901 loss: 0.9007 loss_prob: 0.4676 loss_thr: 0.3527 loss_db: 0.0804 2022/11/03 01:01:44 - mmengine - INFO - Epoch(train) [1053][35/63] lr: 3.2721e-04 eta: 1:41:56 time: 0.8163 data_time: 0.0223 memory: 14901 loss: 0.9536 loss_prob: 0.4965 loss_thr: 0.3720 loss_db: 0.0850 2022/11/03 01:01:47 - mmengine - INFO - Epoch(train) [1053][40/63] lr: 3.2721e-04 eta: 1:41:49 time: 0.6327 data_time: 0.0169 memory: 14901 loss: 0.9686 loss_prob: 0.5081 loss_thr: 0.3715 loss_db: 0.0890 2022/11/03 01:01:49 - mmengine - INFO - Epoch(train) [1053][45/63] lr: 3.2721e-04 eta: 1:41:49 time: 0.5784 data_time: 0.0060 memory: 14901 loss: 0.9131 loss_prob: 0.4788 loss_thr: 0.3494 loss_db: 0.0848 2022/11/03 01:01:52 - mmengine - INFO - Epoch(train) [1053][50/63] lr: 3.2721e-04 eta: 1:41:43 time: 0.5476 data_time: 0.0213 memory: 14901 loss: 0.8340 loss_prob: 0.4294 loss_thr: 0.3298 loss_db: 0.0748 2022/11/03 01:01:55 - mmengine - INFO - Epoch(train) [1053][55/63] lr: 3.2721e-04 eta: 1:41:43 time: 0.5623 data_time: 0.0255 memory: 14901 loss: 0.8728 loss_prob: 0.4487 loss_thr: 0.3469 loss_db: 0.0772 2022/11/03 01:01:58 - mmengine - INFO - Epoch(train) [1053][60/63] lr: 3.2721e-04 eta: 1:41:36 time: 0.5488 data_time: 0.0138 memory: 14901 loss: 0.9100 loss_prob: 0.4706 loss_thr: 0.3577 loss_db: 0.0817 2022/11/03 01:01:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:02:08 - mmengine - INFO - Epoch(train) [1054][5/63] lr: 3.2521e-04 eta: 1:41:36 time: 1.1236 data_time: 0.2359 memory: 14901 loss: 0.9756 loss_prob: 0.5098 loss_thr: 0.3761 loss_db: 0.0897 2022/11/03 01:02:12 - mmengine - INFO - Epoch(train) [1054][10/63] lr: 3.2521e-04 eta: 1:41:28 time: 1.2468 data_time: 0.2503 memory: 14901 loss: 0.9957 loss_prob: 0.5228 loss_thr: 0.3826 loss_db: 0.0903 2022/11/03 01:02:15 - mmengine - INFO - Epoch(train) [1054][15/63] lr: 3.2521e-04 eta: 1:41:28 time: 0.7580 data_time: 0.0254 memory: 14901 loss: 0.9375 loss_prob: 0.4870 loss_thr: 0.3662 loss_db: 0.0844 2022/11/03 01:02:20 - mmengine - INFO - Epoch(train) [1054][20/63] lr: 3.2521e-04 eta: 1:41:21 time: 0.8024 data_time: 0.0084 memory: 14901 loss: 0.9429 loss_prob: 0.4858 loss_thr: 0.3713 loss_db: 0.0857 2022/11/03 01:02:25 - mmengine - INFO - Epoch(train) [1054][25/63] lr: 3.2521e-04 eta: 1:41:21 time: 0.9459 data_time: 0.0178 memory: 14901 loss: 0.8849 loss_prob: 0.4517 loss_thr: 0.3530 loss_db: 0.0801 2022/11/03 01:02:28 - mmengine - INFO - Epoch(train) [1054][30/63] lr: 3.2521e-04 eta: 1:41:15 time: 0.8202 data_time: 0.0381 memory: 14901 loss: 0.8723 loss_prob: 0.4466 loss_thr: 0.3475 loss_db: 0.0782 2022/11/03 01:02:32 - mmengine - INFO - Epoch(train) [1054][35/63] lr: 3.2521e-04 eta: 1:41:15 time: 0.7151 data_time: 0.0358 memory: 14901 loss: 0.8753 loss_prob: 0.4512 loss_thr: 0.3463 loss_db: 0.0778 2022/11/03 01:02:35 - mmengine - INFO - Epoch(train) [1054][40/63] lr: 3.2521e-04 eta: 1:41:09 time: 0.7128 data_time: 0.0154 memory: 14901 loss: 0.8248 loss_prob: 0.4225 loss_thr: 0.3288 loss_db: 0.0735 2022/11/03 01:02:39 - mmengine - INFO - Epoch(train) [1054][45/63] lr: 3.2521e-04 eta: 1:41:09 time: 0.6733 data_time: 0.0088 memory: 14901 loss: 0.9208 loss_prob: 0.4815 loss_thr: 0.3560 loss_db: 0.0832 2022/11/03 01:02:42 - mmengine - INFO - Epoch(train) [1054][50/63] lr: 3.2521e-04 eta: 1:41:02 time: 0.7153 data_time: 0.0151 memory: 14901 loss: 0.9454 loss_prob: 0.5001 loss_thr: 0.3605 loss_db: 0.0848 2022/11/03 01:02:45 - mmengine - INFO - Epoch(train) [1054][55/63] lr: 3.2521e-04 eta: 1:41:02 time: 0.6872 data_time: 0.0209 memory: 14901 loss: 0.8272 loss_prob: 0.4273 loss_thr: 0.3261 loss_db: 0.0738 2022/11/03 01:02:48 - mmengine - INFO - Epoch(train) [1054][60/63] lr: 3.2521e-04 eta: 1:40:55 time: 0.6008 data_time: 0.0224 memory: 14901 loss: 0.8755 loss_prob: 0.4471 loss_thr: 0.3509 loss_db: 0.0775 2022/11/03 01:02:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:02:57 - mmengine - INFO - Epoch(train) [1055][5/63] lr: 3.2320e-04 eta: 1:40:55 time: 0.9711 data_time: 0.2245 memory: 14901 loss: 0.8790 loss_prob: 0.4549 loss_thr: 0.3446 loss_db: 0.0794 2022/11/03 01:03:00 - mmengine - INFO - Epoch(train) [1055][10/63] lr: 3.2320e-04 eta: 1:40:47 time: 0.9582 data_time: 0.2317 memory: 14901 loss: 0.9177 loss_prob: 0.4794 loss_thr: 0.3535 loss_db: 0.0848 2022/11/03 01:03:03 - mmengine - INFO - Epoch(train) [1055][15/63] lr: 3.2320e-04 eta: 1:40:47 time: 0.6077 data_time: 0.0141 memory: 14901 loss: 0.8917 loss_prob: 0.4666 loss_thr: 0.3437 loss_db: 0.0814 2022/11/03 01:03:06 - mmengine - INFO - Epoch(train) [1055][20/63] lr: 3.2320e-04 eta: 1:40:40 time: 0.6061 data_time: 0.0068 memory: 14901 loss: 0.8346 loss_prob: 0.4285 loss_thr: 0.3323 loss_db: 0.0739 2022/11/03 01:03:09 - mmengine - INFO - Epoch(train) [1055][25/63] lr: 3.2320e-04 eta: 1:40:40 time: 0.6009 data_time: 0.0115 memory: 14901 loss: 0.8898 loss_prob: 0.4576 loss_thr: 0.3527 loss_db: 0.0795 2022/11/03 01:03:12 - mmengine - INFO - Epoch(train) [1055][30/63] lr: 3.2320e-04 eta: 1:40:34 time: 0.5911 data_time: 0.0373 memory: 14901 loss: 0.8730 loss_prob: 0.4533 loss_thr: 0.3408 loss_db: 0.0789 2022/11/03 01:03:15 - mmengine - INFO - Epoch(train) [1055][35/63] lr: 3.2320e-04 eta: 1:40:34 time: 0.6388 data_time: 0.0377 memory: 14901 loss: 0.8391 loss_prob: 0.4354 loss_thr: 0.3288 loss_db: 0.0750 2022/11/03 01:03:20 - mmengine - INFO - Epoch(train) [1055][40/63] lr: 3.2320e-04 eta: 1:40:27 time: 0.8044 data_time: 0.0113 memory: 14901 loss: 0.8625 loss_prob: 0.4519 loss_thr: 0.3335 loss_db: 0.0772 2022/11/03 01:03:23 - mmengine - INFO - Epoch(train) [1055][45/63] lr: 3.2320e-04 eta: 1:40:27 time: 0.7498 data_time: 0.0058 memory: 14901 loss: 0.9660 loss_prob: 0.5109 loss_thr: 0.3705 loss_db: 0.0846 2022/11/03 01:03:26 - mmengine - INFO - Epoch(train) [1055][50/63] lr: 3.2320e-04 eta: 1:40:21 time: 0.6676 data_time: 0.0100 memory: 14901 loss: 1.0237 loss_prob: 0.5319 loss_thr: 0.4011 loss_db: 0.0907 2022/11/03 01:03:30 - mmengine - INFO - Epoch(train) [1055][55/63] lr: 3.2320e-04 eta: 1:40:21 time: 0.7173 data_time: 0.0237 memory: 14901 loss: 0.9692 loss_prob: 0.4994 loss_thr: 0.3802 loss_db: 0.0895 2022/11/03 01:03:33 - mmengine - INFO - Epoch(train) [1055][60/63] lr: 3.2320e-04 eta: 1:40:14 time: 0.6398 data_time: 0.0222 memory: 14901 loss: 0.8738 loss_prob: 0.4524 loss_thr: 0.3418 loss_db: 0.0796 2022/11/03 01:03:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:03:40 - mmengine - INFO - Epoch(train) [1056][5/63] lr: 3.2120e-04 eta: 1:40:14 time: 0.8603 data_time: 0.2741 memory: 14901 loss: 0.8967 loss_prob: 0.4647 loss_thr: 0.3510 loss_db: 0.0810 2022/11/03 01:03:44 - mmengine - INFO - Epoch(train) [1056][10/63] lr: 3.2120e-04 eta: 1:40:06 time: 0.9619 data_time: 0.2735 memory: 14901 loss: 1.0997 loss_prob: 0.6257 loss_thr: 0.3790 loss_db: 0.0949 2022/11/03 01:03:47 - mmengine - INFO - Epoch(train) [1056][15/63] lr: 3.2120e-04 eta: 1:40:06 time: 0.6598 data_time: 0.0073 memory: 14901 loss: 1.0767 loss_prob: 0.6118 loss_thr: 0.3725 loss_db: 0.0924 2022/11/03 01:03:51 - mmengine - INFO - Epoch(train) [1056][20/63] lr: 3.2120e-04 eta: 1:39:59 time: 0.6642 data_time: 0.0074 memory: 14901 loss: 0.9217 loss_prob: 0.4820 loss_thr: 0.3552 loss_db: 0.0845 2022/11/03 01:03:55 - mmengine - INFO - Epoch(train) [1056][25/63] lr: 3.2120e-04 eta: 1:39:59 time: 0.7809 data_time: 0.0177 memory: 14901 loss: 0.9132 loss_prob: 0.4719 loss_thr: 0.3581 loss_db: 0.0833 2022/11/03 01:03:58 - mmengine - INFO - Epoch(train) [1056][30/63] lr: 3.2120e-04 eta: 1:39:53 time: 0.7140 data_time: 0.0435 memory: 14901 loss: 0.8523 loss_prob: 0.4371 loss_thr: 0.3398 loss_db: 0.0753 2022/11/03 01:04:02 - mmengine - INFO - Epoch(train) [1056][35/63] lr: 3.2120e-04 eta: 1:39:53 time: 0.7116 data_time: 0.0341 memory: 14901 loss: 0.8277 loss_prob: 0.4283 loss_thr: 0.3253 loss_db: 0.0740 2022/11/03 01:04:05 - mmengine - INFO - Epoch(train) [1056][40/63] lr: 3.2120e-04 eta: 1:39:46 time: 0.6541 data_time: 0.0114 memory: 14901 loss: 0.8874 loss_prob: 0.4591 loss_thr: 0.3470 loss_db: 0.0813 2022/11/03 01:04:08 - mmengine - INFO - Epoch(train) [1056][45/63] lr: 3.2120e-04 eta: 1:39:46 time: 0.6183 data_time: 0.0093 memory: 14901 loss: 0.9754 loss_prob: 0.4981 loss_thr: 0.3896 loss_db: 0.0876 2022/11/03 01:04:13 - mmengine - INFO - Epoch(train) [1056][50/63] lr: 3.2120e-04 eta: 1:39:40 time: 0.8064 data_time: 0.0255 memory: 14901 loss: 0.9114 loss_prob: 0.4621 loss_thr: 0.3693 loss_db: 0.0800 2022/11/03 01:04:16 - mmengine - INFO - Epoch(train) [1056][55/63] lr: 3.2120e-04 eta: 1:39:40 time: 0.7603 data_time: 0.0251 memory: 14901 loss: 0.8431 loss_prob: 0.4320 loss_thr: 0.3354 loss_db: 0.0756 2022/11/03 01:04:18 - mmengine - INFO - Epoch(train) [1056][60/63] lr: 3.2120e-04 eta: 1:39:33 time: 0.5896 data_time: 0.0065 memory: 14901 loss: 0.8497 loss_prob: 0.4361 loss_thr: 0.3368 loss_db: 0.0767 2022/11/03 01:04:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:04:27 - mmengine - INFO - Epoch(train) [1057][5/63] lr: 3.1919e-04 eta: 1:39:33 time: 0.9875 data_time: 0.2539 memory: 14901 loss: 0.8842 loss_prob: 0.4691 loss_thr: 0.3335 loss_db: 0.0816 2022/11/03 01:04:30 - mmengine - INFO - Epoch(train) [1057][10/63] lr: 3.1919e-04 eta: 1:39:25 time: 1.0445 data_time: 0.2624 memory: 14901 loss: 0.8530 loss_prob: 0.4473 loss_thr: 0.3280 loss_db: 0.0777 2022/11/03 01:04:33 - mmengine - INFO - Epoch(train) [1057][15/63] lr: 3.1919e-04 eta: 1:39:25 time: 0.5750 data_time: 0.0220 memory: 14901 loss: 0.9255 loss_prob: 0.4856 loss_thr: 0.3557 loss_db: 0.0842 2022/11/03 01:04:36 - mmengine - INFO - Epoch(train) [1057][20/63] lr: 3.1919e-04 eta: 1:39:18 time: 0.5574 data_time: 0.0116 memory: 14901 loss: 0.9875 loss_prob: 0.5172 loss_thr: 0.3807 loss_db: 0.0895 2022/11/03 01:04:41 - mmengine - INFO - Epoch(train) [1057][25/63] lr: 3.1919e-04 eta: 1:39:18 time: 0.8186 data_time: 0.0199 memory: 14901 loss: 0.9341 loss_prob: 0.4868 loss_thr: 0.3645 loss_db: 0.0828 2022/11/03 01:04:45 - mmengine - INFO - Epoch(train) [1057][30/63] lr: 3.1919e-04 eta: 1:39:12 time: 0.8789 data_time: 0.0410 memory: 14901 loss: 0.8790 loss_prob: 0.4545 loss_thr: 0.3451 loss_db: 0.0793 2022/11/03 01:04:48 - mmengine - INFO - Epoch(train) [1057][35/63] lr: 3.1919e-04 eta: 1:39:12 time: 0.6251 data_time: 0.0294 memory: 14901 loss: 0.8649 loss_prob: 0.4376 loss_thr: 0.3482 loss_db: 0.0790 2022/11/03 01:04:50 - mmengine - INFO - Epoch(train) [1057][40/63] lr: 3.1919e-04 eta: 1:39:05 time: 0.5300 data_time: 0.0143 memory: 14901 loss: 0.9187 loss_prob: 0.4757 loss_thr: 0.3598 loss_db: 0.0832 2022/11/03 01:04:53 - mmengine - INFO - Epoch(train) [1057][45/63] lr: 3.1919e-04 eta: 1:39:05 time: 0.5531 data_time: 0.0117 memory: 14901 loss: 0.8892 loss_prob: 0.4579 loss_thr: 0.3515 loss_db: 0.0798 2022/11/03 01:04:56 - mmengine - INFO - Epoch(train) [1057][50/63] lr: 3.1919e-04 eta: 1:38:58 time: 0.5871 data_time: 0.0130 memory: 14901 loss: 0.8956 loss_prob: 0.4559 loss_thr: 0.3605 loss_db: 0.0792 2022/11/03 01:05:00 - mmengine - INFO - Epoch(train) [1057][55/63] lr: 3.1919e-04 eta: 1:38:58 time: 0.6632 data_time: 0.0232 memory: 14901 loss: 0.8706 loss_prob: 0.4414 loss_thr: 0.3519 loss_db: 0.0773 2022/11/03 01:05:02 - mmengine - INFO - Epoch(train) [1057][60/63] lr: 3.1919e-04 eta: 1:38:52 time: 0.6285 data_time: 0.0223 memory: 14901 loss: 0.8613 loss_prob: 0.4383 loss_thr: 0.3443 loss_db: 0.0787 2022/11/03 01:05:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:05:11 - mmengine - INFO - Epoch(train) [1058][5/63] lr: 3.1718e-04 eta: 1:38:52 time: 0.9539 data_time: 0.2419 memory: 14901 loss: 0.9365 loss_prob: 0.4871 loss_thr: 0.3642 loss_db: 0.0853 2022/11/03 01:05:15 - mmengine - INFO - Epoch(train) [1058][10/63] lr: 3.1718e-04 eta: 1:38:43 time: 1.0589 data_time: 0.2366 memory: 14901 loss: 0.8854 loss_prob: 0.4517 loss_thr: 0.3560 loss_db: 0.0778 2022/11/03 01:05:19 - mmengine - INFO - Epoch(train) [1058][15/63] lr: 3.1718e-04 eta: 1:38:43 time: 0.8515 data_time: 0.0095 memory: 14901 loss: 0.8955 loss_prob: 0.4584 loss_thr: 0.3563 loss_db: 0.0808 2022/11/03 01:05:22 - mmengine - INFO - Epoch(train) [1058][20/63] lr: 3.1718e-04 eta: 1:38:37 time: 0.6864 data_time: 0.0103 memory: 14901 loss: 0.9215 loss_prob: 0.4806 loss_thr: 0.3561 loss_db: 0.0848 2022/11/03 01:05:25 - mmengine - INFO - Epoch(train) [1058][25/63] lr: 3.1718e-04 eta: 1:38:37 time: 0.5299 data_time: 0.0247 memory: 14901 loss: 0.9729 loss_prob: 0.5120 loss_thr: 0.3731 loss_db: 0.0878 2022/11/03 01:05:29 - mmengine - INFO - Epoch(train) [1058][30/63] lr: 3.1718e-04 eta: 1:38:30 time: 0.7574 data_time: 0.0452 memory: 14901 loss: 0.9297 loss_prob: 0.4884 loss_thr: 0.3572 loss_db: 0.0841 2022/11/03 01:05:32 - mmengine - INFO - Epoch(train) [1058][35/63] lr: 3.1718e-04 eta: 1:38:30 time: 0.7753 data_time: 0.0272 memory: 14901 loss: 0.8919 loss_prob: 0.4605 loss_thr: 0.3526 loss_db: 0.0788 2022/11/03 01:05:36 - mmengine - INFO - Epoch(train) [1058][40/63] lr: 3.1718e-04 eta: 1:38:24 time: 0.6346 data_time: 0.0059 memory: 14901 loss: 0.8977 loss_prob: 0.4641 loss_thr: 0.3535 loss_db: 0.0802 2022/11/03 01:05:39 - mmengine - INFO - Epoch(train) [1058][45/63] lr: 3.1718e-04 eta: 1:38:24 time: 0.6649 data_time: 0.0057 memory: 14901 loss: 0.8787 loss_prob: 0.4597 loss_thr: 0.3377 loss_db: 0.0813 2022/11/03 01:05:42 - mmengine - INFO - Epoch(train) [1058][50/63] lr: 3.1718e-04 eta: 1:38:17 time: 0.6699 data_time: 0.0316 memory: 14901 loss: 0.9176 loss_prob: 0.4817 loss_thr: 0.3518 loss_db: 0.0841 2022/11/03 01:05:45 - mmengine - INFO - Epoch(train) [1058][55/63] lr: 3.1718e-04 eta: 1:38:17 time: 0.6280 data_time: 0.0382 memory: 14901 loss: 0.8649 loss_prob: 0.4527 loss_thr: 0.3333 loss_db: 0.0789 2022/11/03 01:05:48 - mmengine - INFO - Epoch(train) [1058][60/63] lr: 3.1718e-04 eta: 1:38:10 time: 0.5726 data_time: 0.0122 memory: 14901 loss: 0.8567 loss_prob: 0.4437 loss_thr: 0.3345 loss_db: 0.0784 2022/11/03 01:05:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:05:58 - mmengine - INFO - Epoch(train) [1059][5/63] lr: 3.1517e-04 eta: 1:38:10 time: 1.0925 data_time: 0.2985 memory: 14901 loss: 0.7998 loss_prob: 0.4100 loss_thr: 0.3178 loss_db: 0.0720 2022/11/03 01:06:02 - mmengine - INFO - Epoch(train) [1059][10/63] lr: 3.1517e-04 eta: 1:38:02 time: 1.2404 data_time: 0.2974 memory: 14901 loss: 0.8381 loss_prob: 0.4249 loss_thr: 0.3399 loss_db: 0.0732 2022/11/03 01:06:08 - mmengine - INFO - Epoch(train) [1059][15/63] lr: 3.1517e-04 eta: 1:38:02 time: 0.9816 data_time: 0.0065 memory: 14901 loss: 0.8186 loss_prob: 0.4172 loss_thr: 0.3292 loss_db: 0.0722 2022/11/03 01:06:12 - mmengine - INFO - Epoch(train) [1059][20/63] lr: 3.1517e-04 eta: 1:37:56 time: 0.9987 data_time: 0.0061 memory: 14901 loss: 0.8429 loss_prob: 0.4406 loss_thr: 0.3247 loss_db: 0.0776 2022/11/03 01:06:16 - mmengine - INFO - Epoch(train) [1059][25/63] lr: 3.1517e-04 eta: 1:37:56 time: 0.8303 data_time: 0.0666 memory: 14901 loss: 0.9160 loss_prob: 0.4733 loss_thr: 0.3597 loss_db: 0.0829 2022/11/03 01:06:21 - mmengine - INFO - Epoch(train) [1059][30/63] lr: 3.1517e-04 eta: 1:37:50 time: 0.9219 data_time: 0.0727 memory: 14901 loss: 0.8957 loss_prob: 0.4598 loss_thr: 0.3573 loss_db: 0.0787 2022/11/03 01:06:25 - mmengine - INFO - Epoch(train) [1059][35/63] lr: 3.1517e-04 eta: 1:37:50 time: 0.9090 data_time: 0.0115 memory: 14901 loss: 0.8946 loss_prob: 0.4689 loss_thr: 0.3466 loss_db: 0.0791 2022/11/03 01:06:30 - mmengine - INFO - Epoch(train) [1059][40/63] lr: 3.1517e-04 eta: 1:37:44 time: 0.9260 data_time: 0.0058 memory: 14901 loss: 0.9410 loss_prob: 0.5039 loss_thr: 0.3540 loss_db: 0.0831 2022/11/03 01:06:33 - mmengine - INFO - Epoch(train) [1059][45/63] lr: 3.1517e-04 eta: 1:37:44 time: 0.7887 data_time: 0.0062 memory: 14901 loss: 0.9310 loss_prob: 0.4945 loss_thr: 0.3535 loss_db: 0.0830 2022/11/03 01:06:36 - mmengine - INFO - Epoch(train) [1059][50/63] lr: 3.1517e-04 eta: 1:37:37 time: 0.6189 data_time: 0.0315 memory: 14901 loss: 0.9343 loss_prob: 0.4895 loss_thr: 0.3596 loss_db: 0.0852 2022/11/03 01:06:40 - mmengine - INFO - Epoch(train) [1059][55/63] lr: 3.1517e-04 eta: 1:37:37 time: 0.7229 data_time: 0.0339 memory: 14901 loss: 0.9377 loss_prob: 0.4927 loss_thr: 0.3600 loss_db: 0.0850 2022/11/03 01:06:44 - mmengine - INFO - Epoch(train) [1059][60/63] lr: 3.1517e-04 eta: 1:37:31 time: 0.7420 data_time: 0.0086 memory: 14901 loss: 0.9105 loss_prob: 0.4776 loss_thr: 0.3507 loss_db: 0.0822 2022/11/03 01:06:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:06:51 - mmengine - INFO - Epoch(train) [1060][5/63] lr: 3.1316e-04 eta: 1:37:31 time: 0.8547 data_time: 0.2434 memory: 14901 loss: 0.9235 loss_prob: 0.4702 loss_thr: 0.3708 loss_db: 0.0825 2022/11/03 01:06:54 - mmengine - INFO - Epoch(train) [1060][10/63] lr: 3.1316e-04 eta: 1:37:22 time: 0.8798 data_time: 0.2457 memory: 14901 loss: 0.9136 loss_prob: 0.4689 loss_thr: 0.3606 loss_db: 0.0841 2022/11/03 01:06:58 - mmengine - INFO - Epoch(train) [1060][15/63] lr: 3.1316e-04 eta: 1:37:22 time: 0.7322 data_time: 0.0123 memory: 14901 loss: 0.8757 loss_prob: 0.4544 loss_thr: 0.3406 loss_db: 0.0808 2022/11/03 01:07:02 - mmengine - INFO - Epoch(train) [1060][20/63] lr: 3.1316e-04 eta: 1:37:16 time: 0.8470 data_time: 0.0095 memory: 14901 loss: 0.8699 loss_prob: 0.4458 loss_thr: 0.3466 loss_db: 0.0774 2022/11/03 01:07:06 - mmengine - INFO - Epoch(train) [1060][25/63] lr: 3.1316e-04 eta: 1:37:16 time: 0.7325 data_time: 0.0324 memory: 14901 loss: 0.8329 loss_prob: 0.4193 loss_thr: 0.3405 loss_db: 0.0732 2022/11/03 01:07:08 - mmengine - INFO - Epoch(train) [1060][30/63] lr: 3.1316e-04 eta: 1:37:09 time: 0.5854 data_time: 0.0355 memory: 14901 loss: 0.8252 loss_prob: 0.4114 loss_thr: 0.3396 loss_db: 0.0742 2022/11/03 01:07:11 - mmengine - INFO - Epoch(train) [1060][35/63] lr: 3.1316e-04 eta: 1:37:09 time: 0.5424 data_time: 0.0108 memory: 14901 loss: 0.8685 loss_prob: 0.4439 loss_thr: 0.3445 loss_db: 0.0801 2022/11/03 01:07:14 - mmengine - INFO - Epoch(train) [1060][40/63] lr: 3.1316e-04 eta: 1:37:02 time: 0.5706 data_time: 0.0100 memory: 14901 loss: 0.8396 loss_prob: 0.4343 loss_thr: 0.3284 loss_db: 0.0769 2022/11/03 01:07:17 - mmengine - INFO - Epoch(train) [1060][45/63] lr: 3.1316e-04 eta: 1:37:02 time: 0.5448 data_time: 0.0089 memory: 14901 loss: 0.7963 loss_prob: 0.4080 loss_thr: 0.3164 loss_db: 0.0719 2022/11/03 01:07:19 - mmengine - INFO - Epoch(train) [1060][50/63] lr: 3.1316e-04 eta: 1:36:56 time: 0.5504 data_time: 0.0202 memory: 14901 loss: 0.8344 loss_prob: 0.4349 loss_thr: 0.3230 loss_db: 0.0765 2022/11/03 01:07:22 - mmengine - INFO - Epoch(train) [1060][55/63] lr: 3.1316e-04 eta: 1:36:56 time: 0.5722 data_time: 0.0240 memory: 14901 loss: 0.8805 loss_prob: 0.4553 loss_thr: 0.3446 loss_db: 0.0806 2022/11/03 01:07:25 - mmengine - INFO - Epoch(train) [1060][60/63] lr: 3.1316e-04 eta: 1:36:49 time: 0.5493 data_time: 0.0115 memory: 14901 loss: 0.8584 loss_prob: 0.4382 loss_thr: 0.3428 loss_db: 0.0773 2022/11/03 01:07:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:07:26 - mmengine - INFO - Saving checkpoint at 1060 epochs 2022/11/03 01:07:31 - mmengine - INFO - Epoch(val) [1060][5/500] eta: 1:36:49 time: 0.0494 data_time: 0.0053 memory: 14901 2022/11/03 01:07:31 - mmengine - INFO - Epoch(val) [1060][10/500] eta: 0:00:22 time: 0.0464 data_time: 0.0048 memory: 1008 2022/11/03 01:07:31 - mmengine - INFO - Epoch(val) [1060][15/500] eta: 0:00:22 time: 0.0382 data_time: 0.0025 memory: 1008 2022/11/03 01:07:32 - mmengine - INFO - Epoch(val) [1060][20/500] eta: 0:00:19 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/03 01:07:32 - mmengine - INFO - Epoch(val) [1060][25/500] eta: 0:00:19 time: 0.0403 data_time: 0.0027 memory: 1008 2022/11/03 01:07:32 - mmengine - INFO - Epoch(val) [1060][30/500] eta: 0:00:19 time: 0.0417 data_time: 0.0027 memory: 1008 2022/11/03 01:07:32 - mmengine - INFO - Epoch(val) [1060][35/500] eta: 0:00:19 time: 0.0454 data_time: 0.0030 memory: 1008 2022/11/03 01:07:33 - mmengine - INFO - Epoch(val) [1060][40/500] eta: 0:00:22 time: 0.0484 data_time: 0.0032 memory: 1008 2022/11/03 01:07:33 - mmengine - INFO - Epoch(val) [1060][45/500] eta: 0:00:22 time: 0.0496 data_time: 0.0032 memory: 1008 2022/11/03 01:07:33 - mmengine - INFO - Epoch(val) [1060][50/500] eta: 0:00:21 time: 0.0471 data_time: 0.0033 memory: 1008 2022/11/03 01:07:33 - mmengine - INFO - Epoch(val) [1060][55/500] eta: 0:00:21 time: 0.0502 data_time: 0.0033 memory: 1008 2022/11/03 01:07:34 - mmengine - INFO - Epoch(val) [1060][60/500] eta: 0:00:21 time: 0.0491 data_time: 0.0033 memory: 1008 2022/11/03 01:07:34 - mmengine - INFO - Epoch(val) [1060][65/500] eta: 0:00:21 time: 0.0468 data_time: 0.0031 memory: 1008 2022/11/03 01:07:34 - mmengine - INFO - Epoch(val) [1060][70/500] eta: 0:00:21 time: 0.0501 data_time: 0.0033 memory: 1008 2022/11/03 01:07:34 - mmengine - INFO - Epoch(val) [1060][75/500] eta: 0:00:21 time: 0.0484 data_time: 0.0037 memory: 1008 2022/11/03 01:07:35 - mmengine - INFO - Epoch(val) [1060][80/500] eta: 0:00:20 time: 0.0481 data_time: 0.0040 memory: 1008 2022/11/03 01:07:35 - mmengine - INFO - Epoch(val) [1060][85/500] eta: 0:00:20 time: 0.0481 data_time: 0.0039 memory: 1008 2022/11/03 01:07:35 - mmengine - INFO - Epoch(val) [1060][90/500] eta: 0:00:23 time: 0.0585 data_time: 0.0042 memory: 1008 2022/11/03 01:07:35 - mmengine - INFO - Epoch(val) [1060][95/500] eta: 0:00:23 time: 0.0632 data_time: 0.0045 memory: 1008 2022/11/03 01:07:36 - mmengine - INFO - Epoch(val) [1060][100/500] eta: 0:00:18 time: 0.0454 data_time: 0.0034 memory: 1008 2022/11/03 01:07:36 - mmengine - INFO - Epoch(val) [1060][105/500] eta: 0:00:18 time: 0.0394 data_time: 0.0032 memory: 1008 2022/11/03 01:07:36 - mmengine - INFO - Epoch(val) [1060][110/500] eta: 0:00:17 time: 0.0446 data_time: 0.0034 memory: 1008 2022/11/03 01:07:36 - mmengine - INFO - Epoch(val) [1060][115/500] eta: 0:00:17 time: 0.0435 data_time: 0.0029 memory: 1008 2022/11/03 01:07:37 - mmengine - INFO - Epoch(val) [1060][120/500] eta: 0:00:16 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/03 01:07:37 - mmengine - INFO - Epoch(val) [1060][125/500] eta: 0:00:16 time: 0.0455 data_time: 0.0038 memory: 1008 2022/11/03 01:07:37 - mmengine - INFO - Epoch(val) [1060][130/500] eta: 0:00:15 time: 0.0426 data_time: 0.0037 memory: 1008 2022/11/03 01:07:37 - mmengine - INFO - Epoch(val) [1060][135/500] eta: 0:00:15 time: 0.0445 data_time: 0.0032 memory: 1008 2022/11/03 01:07:37 - mmengine - INFO - Epoch(val) [1060][140/500] eta: 0:00:15 time: 0.0431 data_time: 0.0032 memory: 1008 2022/11/03 01:07:38 - mmengine - INFO - Epoch(val) [1060][145/500] eta: 0:00:15 time: 0.0479 data_time: 0.0030 memory: 1008 2022/11/03 01:07:38 - mmengine - INFO - Epoch(val) [1060][150/500] eta: 0:00:17 time: 0.0514 data_time: 0.0034 memory: 1008 2022/11/03 01:07:38 - mmengine - INFO - Epoch(val) [1060][155/500] eta: 0:00:17 time: 0.0564 data_time: 0.0048 memory: 1008 2022/11/03 01:07:38 - mmengine - INFO - Epoch(val) [1060][160/500] eta: 0:00:18 time: 0.0556 data_time: 0.0045 memory: 1008 2022/11/03 01:07:39 - mmengine - INFO - Epoch(val) [1060][165/500] eta: 0:00:18 time: 0.0441 data_time: 0.0030 memory: 1008 2022/11/03 01:07:39 - mmengine - INFO - Epoch(val) [1060][170/500] eta: 0:00:15 time: 0.0480 data_time: 0.0034 memory: 1008 2022/11/03 01:07:39 - mmengine - INFO - Epoch(val) [1060][175/500] eta: 0:00:15 time: 0.0448 data_time: 0.0032 memory: 1008 2022/11/03 01:07:39 - mmengine - INFO - Epoch(val) [1060][180/500] eta: 0:00:13 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/03 01:07:40 - mmengine - INFO - Epoch(val) [1060][185/500] eta: 0:00:13 time: 0.0550 data_time: 0.0041 memory: 1008 2022/11/03 01:07:40 - mmengine - INFO - Epoch(val) [1060][190/500] eta: 0:00:18 time: 0.0597 data_time: 0.0047 memory: 1008 2022/11/03 01:07:40 - mmengine - INFO - Epoch(val) [1060][195/500] eta: 0:00:18 time: 0.0523 data_time: 0.0041 memory: 1008 2022/11/03 01:07:41 - mmengine - INFO - Epoch(val) [1060][200/500] eta: 0:00:17 time: 0.0579 data_time: 0.0035 memory: 1008 2022/11/03 01:07:41 - mmengine - INFO - Epoch(val) [1060][205/500] eta: 0:00:17 time: 0.0537 data_time: 0.0031 memory: 1008 2022/11/03 01:07:41 - mmengine - INFO - Epoch(val) [1060][210/500] eta: 0:00:11 time: 0.0409 data_time: 0.0030 memory: 1008 2022/11/03 01:07:41 - mmengine - INFO - Epoch(val) [1060][215/500] eta: 0:00:11 time: 0.0431 data_time: 0.0028 memory: 1008 2022/11/03 01:07:41 - mmengine - INFO - Epoch(val) [1060][220/500] eta: 0:00:12 time: 0.0447 data_time: 0.0030 memory: 1008 2022/11/03 01:07:42 - mmengine - INFO - Epoch(val) [1060][225/500] eta: 0:00:12 time: 0.0447 data_time: 0.0029 memory: 1008 2022/11/03 01:07:42 - mmengine - INFO - Epoch(val) [1060][230/500] eta: 0:00:11 time: 0.0434 data_time: 0.0030 memory: 1008 2022/11/03 01:07:42 - mmengine - INFO - Epoch(val) [1060][235/500] eta: 0:00:11 time: 0.0432 data_time: 0.0031 memory: 1008 2022/11/03 01:07:42 - mmengine - INFO - Epoch(val) [1060][240/500] eta: 0:00:12 time: 0.0476 data_time: 0.0030 memory: 1008 2022/11/03 01:07:43 - mmengine - INFO - Epoch(val) [1060][245/500] eta: 0:00:12 time: 0.0461 data_time: 0.0034 memory: 1008 2022/11/03 01:07:43 - mmengine - INFO - Epoch(val) [1060][250/500] eta: 0:00:12 time: 0.0515 data_time: 0.0039 memory: 1008 2022/11/03 01:07:43 - mmengine - INFO - Epoch(val) [1060][255/500] eta: 0:00:12 time: 0.0500 data_time: 0.0033 memory: 1008 2022/11/03 01:07:43 - mmengine - INFO - Epoch(val) [1060][260/500] eta: 0:00:10 time: 0.0428 data_time: 0.0030 memory: 1008 2022/11/03 01:07:43 - mmengine - INFO - Epoch(val) [1060][265/500] eta: 0:00:10 time: 0.0429 data_time: 0.0031 memory: 1008 2022/11/03 01:07:44 - mmengine - INFO - Epoch(val) [1060][270/500] eta: 0:00:09 time: 0.0412 data_time: 0.0029 memory: 1008 2022/11/03 01:07:44 - mmengine - INFO - Epoch(val) [1060][275/500] eta: 0:00:09 time: 0.0400 data_time: 0.0031 memory: 1008 2022/11/03 01:07:44 - mmengine - INFO - Epoch(val) [1060][280/500] eta: 0:00:09 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/03 01:07:44 - mmengine - INFO - Epoch(val) [1060][285/500] eta: 0:00:09 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/03 01:07:45 - mmengine - INFO - Epoch(val) [1060][290/500] eta: 0:00:10 time: 0.0477 data_time: 0.0032 memory: 1008 2022/11/03 01:07:45 - mmengine - INFO - Epoch(val) [1060][295/500] eta: 0:00:10 time: 0.0471 data_time: 0.0031 memory: 1008 2022/11/03 01:07:45 - mmengine - INFO - Epoch(val) [1060][300/500] eta: 0:00:07 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/03 01:07:45 - mmengine - INFO - Epoch(val) [1060][305/500] eta: 0:00:07 time: 0.0417 data_time: 0.0028 memory: 1008 2022/11/03 01:07:45 - mmengine - INFO - Epoch(val) [1060][310/500] eta: 0:00:08 time: 0.0435 data_time: 0.0030 memory: 1008 2022/11/03 01:07:46 - mmengine - INFO - Epoch(val) [1060][315/500] eta: 0:00:08 time: 0.0446 data_time: 0.0028 memory: 1008 2022/11/03 01:07:46 - mmengine - INFO - Epoch(val) [1060][320/500] eta: 0:00:08 time: 0.0447 data_time: 0.0039 memory: 1008 2022/11/03 01:07:46 - mmengine - INFO - Epoch(val) [1060][325/500] eta: 0:00:08 time: 0.0525 data_time: 0.0039 memory: 1008 2022/11/03 01:07:46 - mmengine - INFO - Epoch(val) [1060][330/500] eta: 0:00:09 time: 0.0554 data_time: 0.0052 memory: 1008 2022/11/03 01:07:47 - mmengine - INFO - Epoch(val) [1060][335/500] eta: 0:00:09 time: 0.0431 data_time: 0.0054 memory: 1008 2022/11/03 01:07:47 - mmengine - INFO - Epoch(val) [1060][340/500] eta: 0:00:08 time: 0.0552 data_time: 0.0034 memory: 1008 2022/11/03 01:07:47 - mmengine - INFO - Epoch(val) [1060][345/500] eta: 0:00:08 time: 0.0567 data_time: 0.0031 memory: 1008 2022/11/03 01:07:47 - mmengine - INFO - Epoch(val) [1060][350/500] eta: 0:00:06 time: 0.0444 data_time: 0.0028 memory: 1008 2022/11/03 01:07:48 - mmengine - INFO - Epoch(val) [1060][355/500] eta: 0:00:06 time: 0.0441 data_time: 0.0030 memory: 1008 2022/11/03 01:07:48 - mmengine - INFO - Epoch(val) [1060][360/500] eta: 0:00:05 time: 0.0400 data_time: 0.0028 memory: 1008 2022/11/03 01:07:48 - mmengine - INFO - Epoch(val) [1060][365/500] eta: 0:00:05 time: 0.0404 data_time: 0.0028 memory: 1008 2022/11/03 01:07:48 - mmengine - INFO - Epoch(val) [1060][370/500] eta: 0:00:04 time: 0.0368 data_time: 0.0027 memory: 1008 2022/11/03 01:07:48 - mmengine - INFO - Epoch(val) [1060][375/500] eta: 0:00:04 time: 0.0388 data_time: 0.0028 memory: 1008 2022/11/03 01:07:49 - mmengine - INFO - Epoch(val) [1060][380/500] eta: 0:00:05 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/03 01:07:49 - mmengine - INFO - Epoch(val) [1060][385/500] eta: 0:00:05 time: 0.0420 data_time: 0.0026 memory: 1008 2022/11/03 01:07:49 - mmengine - INFO - Epoch(val) [1060][390/500] eta: 0:00:04 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/03 01:07:49 - mmengine - INFO - Epoch(val) [1060][395/500] eta: 0:00:04 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/03 01:07:49 - mmengine - INFO - Epoch(val) [1060][400/500] eta: 0:00:04 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/03 01:07:50 - mmengine - INFO - Epoch(val) [1060][405/500] eta: 0:00:04 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/03 01:07:50 - mmengine - INFO - Epoch(val) [1060][410/500] eta: 0:00:03 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/03 01:07:50 - mmengine - INFO - Epoch(val) [1060][415/500] eta: 0:00:03 time: 0.0426 data_time: 0.0028 memory: 1008 2022/11/03 01:07:50 - mmengine - INFO - Epoch(val) [1060][420/500] eta: 0:00:03 time: 0.0393 data_time: 0.0030 memory: 1008 2022/11/03 01:07:50 - mmengine - INFO - Epoch(val) [1060][425/500] eta: 0:00:03 time: 0.0389 data_time: 0.0029 memory: 1008 2022/11/03 01:07:51 - mmengine - INFO - Epoch(val) [1060][430/500] eta: 0:00:02 time: 0.0406 data_time: 0.0028 memory: 1008 2022/11/03 01:07:51 - mmengine - INFO - Epoch(val) [1060][435/500] eta: 0:00:02 time: 0.0396 data_time: 0.0028 memory: 1008 2022/11/03 01:07:51 - mmengine - INFO - Epoch(val) [1060][440/500] eta: 0:00:02 time: 0.0385 data_time: 0.0028 memory: 1008 2022/11/03 01:07:51 - mmengine - INFO - Epoch(val) [1060][445/500] eta: 0:00:02 time: 0.0422 data_time: 0.0029 memory: 1008 2022/11/03 01:07:51 - mmengine - INFO - Epoch(val) [1060][450/500] eta: 0:00:02 time: 0.0470 data_time: 0.0029 memory: 1008 2022/11/03 01:07:52 - mmengine - INFO - Epoch(val) [1060][455/500] eta: 0:00:02 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/03 01:07:52 - mmengine - INFO - Epoch(val) [1060][460/500] eta: 0:00:01 time: 0.0397 data_time: 0.0027 memory: 1008 2022/11/03 01:07:52 - mmengine - INFO - Epoch(val) [1060][465/500] eta: 0:00:01 time: 0.0403 data_time: 0.0028 memory: 1008 2022/11/03 01:07:52 - mmengine - INFO - Epoch(val) [1060][470/500] eta: 0:00:01 time: 0.0436 data_time: 0.0030 memory: 1008 2022/11/03 01:07:53 - mmengine - INFO - Epoch(val) [1060][475/500] eta: 0:00:01 time: 0.0415 data_time: 0.0033 memory: 1008 2022/11/03 01:07:53 - mmengine - INFO - Epoch(val) [1060][480/500] eta: 0:00:00 time: 0.0414 data_time: 0.0030 memory: 1008 2022/11/03 01:07:53 - mmengine - INFO - Epoch(val) [1060][485/500] eta: 0:00:00 time: 0.0460 data_time: 0.0034 memory: 1008 2022/11/03 01:07:53 - mmengine - INFO - Epoch(val) [1060][490/500] eta: 0:00:00 time: 0.0466 data_time: 0.0034 memory: 1008 2022/11/03 01:07:53 - mmengine - INFO - Epoch(val) [1060][495/500] eta: 0:00:00 time: 0.0472 data_time: 0.0029 memory: 1008 2022/11/03 01:07:54 - mmengine - INFO - Epoch(val) [1060][500/500] eta: 0:00:00 time: 0.0425 data_time: 0.0030 memory: 1008 2022/11/03 01:07:54 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8363, precision: 0.7555, hmean: 0.7939 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8363, precision: 0.7979, hmean: 0.8166 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8358, precision: 0.8220, hmean: 0.8288 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8344, precision: 0.8483, hmean: 0.8413 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8276, precision: 0.8744, hmean: 0.8504 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7468, precision: 0.9081, hmean: 0.8196 2022/11/03 01:07:54 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2229, precision: 0.9666, hmean: 0.3623 2022/11/03 01:07:54 - mmengine - INFO - Epoch(val) [1060][500/500] icdar/precision: 0.8744 icdar/recall: 0.8276 icdar/hmean: 0.8504 2022/11/03 01:08:00 - mmengine - INFO - Epoch(train) [1061][5/63] lr: 3.1115e-04 eta: 0:00:00 time: 0.8577 data_time: 0.2333 memory: 14901 loss: 0.8770 loss_prob: 0.4543 loss_thr: 0.3448 loss_db: 0.0779 2022/11/03 01:08:04 - mmengine - INFO - Epoch(train) [1061][10/63] lr: 3.1115e-04 eta: 1:36:41 time: 1.0342 data_time: 0.2328 memory: 14901 loss: 0.8055 loss_prob: 0.4205 loss_thr: 0.3119 loss_db: 0.0731 2022/11/03 01:08:07 - mmengine - INFO - Epoch(train) [1061][15/63] lr: 3.1115e-04 eta: 1:36:41 time: 0.7259 data_time: 0.0063 memory: 14901 loss: 0.7854 loss_prob: 0.4045 loss_thr: 0.3093 loss_db: 0.0717 2022/11/03 01:08:10 - mmengine - INFO - Epoch(train) [1061][20/63] lr: 3.1115e-04 eta: 1:36:34 time: 0.6022 data_time: 0.0074 memory: 14901 loss: 0.8523 loss_prob: 0.4407 loss_thr: 0.3350 loss_db: 0.0765 2022/11/03 01:08:14 - mmengine - INFO - Epoch(train) [1061][25/63] lr: 3.1115e-04 eta: 1:36:34 time: 0.6592 data_time: 0.0255 memory: 14901 loss: 0.8482 loss_prob: 0.4383 loss_thr: 0.3349 loss_db: 0.0750 2022/11/03 01:08:17 - mmengine - INFO - Epoch(train) [1061][30/63] lr: 3.1115e-04 eta: 1:36:28 time: 0.7312 data_time: 0.0471 memory: 14901 loss: 0.9494 loss_prob: 0.5034 loss_thr: 0.3615 loss_db: 0.0845 2022/11/03 01:08:23 - mmengine - INFO - Epoch(train) [1061][35/63] lr: 3.1115e-04 eta: 1:36:28 time: 0.8821 data_time: 0.0291 memory: 14901 loss: 0.9735 loss_prob: 0.5179 loss_thr: 0.3673 loss_db: 0.0883 2022/11/03 01:08:26 - mmengine - INFO - Epoch(train) [1061][40/63] lr: 3.1115e-04 eta: 1:36:21 time: 0.8646 data_time: 0.0065 memory: 14901 loss: 0.8918 loss_prob: 0.4534 loss_thr: 0.3588 loss_db: 0.0795 2022/11/03 01:08:29 - mmengine - INFO - Epoch(train) [1061][45/63] lr: 3.1115e-04 eta: 1:36:21 time: 0.6266 data_time: 0.0072 memory: 14901 loss: 0.9126 loss_prob: 0.4589 loss_thr: 0.3732 loss_db: 0.0805 2022/11/03 01:08:33 - mmengine - INFO - Epoch(train) [1061][50/63] lr: 3.1115e-04 eta: 1:36:15 time: 0.6554 data_time: 0.0284 memory: 14901 loss: 0.9921 loss_prob: 0.5083 loss_thr: 0.3961 loss_db: 0.0877 2022/11/03 01:08:36 - mmengine - INFO - Epoch(train) [1061][55/63] lr: 3.1115e-04 eta: 1:36:15 time: 0.7396 data_time: 0.0297 memory: 14901 loss: 0.9415 loss_prob: 0.4846 loss_thr: 0.3737 loss_db: 0.0832 2022/11/03 01:08:39 - mmengine - INFO - Epoch(train) [1061][60/63] lr: 3.1115e-04 eta: 1:36:08 time: 0.6828 data_time: 0.0087 memory: 14901 loss: 0.7894 loss_prob: 0.4002 loss_thr: 0.3186 loss_db: 0.0706 2022/11/03 01:08:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:08:46 - mmengine - INFO - Epoch(train) [1062][5/63] lr: 3.0913e-04 eta: 1:36:08 time: 0.8295 data_time: 0.2118 memory: 14901 loss: 0.7924 loss_prob: 0.3933 loss_thr: 0.3301 loss_db: 0.0690 2022/11/03 01:08:49 - mmengine - INFO - Epoch(train) [1062][10/63] lr: 3.0913e-04 eta: 1:35:59 time: 0.8312 data_time: 0.2107 memory: 14901 loss: 0.8251 loss_prob: 0.4160 loss_thr: 0.3369 loss_db: 0.0722 2022/11/03 01:08:52 - mmengine - INFO - Epoch(train) [1062][15/63] lr: 3.0913e-04 eta: 1:35:59 time: 0.5509 data_time: 0.0062 memory: 14901 loss: 0.9349 loss_prob: 0.4809 loss_thr: 0.3686 loss_db: 0.0854 2022/11/03 01:08:55 - mmengine - INFO - Epoch(train) [1062][20/63] lr: 3.0913e-04 eta: 1:35:53 time: 0.6281 data_time: 0.0084 memory: 14901 loss: 0.9937 loss_prob: 0.5168 loss_thr: 0.3851 loss_db: 0.0917 2022/11/03 01:08:59 - mmengine - INFO - Epoch(train) [1062][25/63] lr: 3.0913e-04 eta: 1:35:53 time: 0.7183 data_time: 0.0264 memory: 14901 loss: 0.9522 loss_prob: 0.4953 loss_thr: 0.3702 loss_db: 0.0868 2022/11/03 01:09:03 - mmengine - INFO - Epoch(train) [1062][30/63] lr: 3.0913e-04 eta: 1:35:46 time: 0.7837 data_time: 0.0432 memory: 14901 loss: 0.8986 loss_prob: 0.4569 loss_thr: 0.3619 loss_db: 0.0798 2022/11/03 01:09:08 - mmengine - INFO - Epoch(train) [1062][35/63] lr: 3.0913e-04 eta: 1:35:46 time: 0.9277 data_time: 0.0267 memory: 14901 loss: 0.8712 loss_prob: 0.4483 loss_thr: 0.3443 loss_db: 0.0786 2022/11/03 01:09:13 - mmengine - INFO - Epoch(train) [1062][40/63] lr: 3.0913e-04 eta: 1:35:40 time: 0.9432 data_time: 0.0080 memory: 14901 loss: 0.8509 loss_prob: 0.4393 loss_thr: 0.3340 loss_db: 0.0775 2022/11/03 01:09:15 - mmengine - INFO - Epoch(train) [1062][45/63] lr: 3.0913e-04 eta: 1:35:40 time: 0.6844 data_time: 0.0056 memory: 14901 loss: 0.8261 loss_prob: 0.4192 loss_thr: 0.3343 loss_db: 0.0725 2022/11/03 01:09:19 - mmengine - INFO - Epoch(train) [1062][50/63] lr: 3.0913e-04 eta: 1:35:34 time: 0.6375 data_time: 0.0159 memory: 14901 loss: 0.8835 loss_prob: 0.4739 loss_thr: 0.3327 loss_db: 0.0770 2022/11/03 01:09:22 - mmengine - INFO - Epoch(train) [1062][55/63] lr: 3.0913e-04 eta: 1:35:34 time: 0.7049 data_time: 0.0269 memory: 14901 loss: 0.9230 loss_prob: 0.4930 loss_thr: 0.3479 loss_db: 0.0821 2022/11/03 01:09:25 - mmengine - INFO - Epoch(train) [1062][60/63] lr: 3.0913e-04 eta: 1:35:27 time: 0.5935 data_time: 0.0180 memory: 14901 loss: 0.9234 loss_prob: 0.4808 loss_thr: 0.3584 loss_db: 0.0842 2022/11/03 01:09:26 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:09:32 - mmengine - INFO - Epoch(train) [1063][5/63] lr: 3.0711e-04 eta: 1:35:27 time: 0.8389 data_time: 0.2712 memory: 14901 loss: 0.9253 loss_prob: 0.4802 loss_thr: 0.3604 loss_db: 0.0847 2022/11/03 01:09:36 - mmengine - INFO - Epoch(train) [1063][10/63] lr: 3.0711e-04 eta: 1:35:18 time: 0.9280 data_time: 0.2702 memory: 14901 loss: 0.9015 loss_prob: 0.4628 loss_thr: 0.3577 loss_db: 0.0809 2022/11/03 01:09:38 - mmengine - INFO - Epoch(train) [1063][15/63] lr: 3.0711e-04 eta: 1:35:18 time: 0.5724 data_time: 0.0120 memory: 14901 loss: 0.9174 loss_prob: 0.4750 loss_thr: 0.3606 loss_db: 0.0818 2022/11/03 01:09:42 - mmengine - INFO - Epoch(train) [1063][20/63] lr: 3.0711e-04 eta: 1:35:12 time: 0.6169 data_time: 0.0122 memory: 14901 loss: 0.9519 loss_prob: 0.4993 loss_thr: 0.3660 loss_db: 0.0866 2022/11/03 01:09:46 - mmengine - INFO - Epoch(train) [1063][25/63] lr: 3.0711e-04 eta: 1:35:12 time: 0.7544 data_time: 0.0422 memory: 14901 loss: 0.8877 loss_prob: 0.4619 loss_thr: 0.3448 loss_db: 0.0810 2022/11/03 01:09:49 - mmengine - INFO - Epoch(train) [1063][30/63] lr: 3.0711e-04 eta: 1:35:05 time: 0.7230 data_time: 0.0417 memory: 14901 loss: 0.9650 loss_prob: 0.5327 loss_thr: 0.3481 loss_db: 0.0842 2022/11/03 01:09:53 - mmengine - INFO - Epoch(train) [1063][35/63] lr: 3.0711e-04 eta: 1:35:05 time: 0.7220 data_time: 0.0086 memory: 14901 loss: 0.9960 loss_prob: 0.5513 loss_thr: 0.3567 loss_db: 0.0880 2022/11/03 01:09:58 - mmengine - INFO - Epoch(train) [1063][40/63] lr: 3.0711e-04 eta: 1:34:59 time: 0.8997 data_time: 0.0124 memory: 14901 loss: 0.8400 loss_prob: 0.4314 loss_thr: 0.3333 loss_db: 0.0753 2022/11/03 01:10:03 - mmengine - INFO - Epoch(train) [1063][45/63] lr: 3.0711e-04 eta: 1:34:59 time: 1.0326 data_time: 0.0101 memory: 14901 loss: 0.8339 loss_prob: 0.4308 loss_thr: 0.3283 loss_db: 0.0748 2022/11/03 01:10:07 - mmengine - INFO - Epoch(train) [1063][50/63] lr: 3.0711e-04 eta: 1:34:53 time: 0.9491 data_time: 0.0224 memory: 14901 loss: 0.9294 loss_prob: 0.4924 loss_thr: 0.3499 loss_db: 0.0871 2022/11/03 01:10:10 - mmengine - INFO - Epoch(train) [1063][55/63] lr: 3.0711e-04 eta: 1:34:53 time: 0.6905 data_time: 0.0220 memory: 14901 loss: 0.9431 loss_prob: 0.5033 loss_thr: 0.3515 loss_db: 0.0883 2022/11/03 01:10:14 - mmengine - INFO - Epoch(train) [1063][60/63] lr: 3.0711e-04 eta: 1:34:46 time: 0.6524 data_time: 0.0059 memory: 14901 loss: 0.9058 loss_prob: 0.4724 loss_thr: 0.3504 loss_db: 0.0830 2022/11/03 01:10:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:10:24 - mmengine - INFO - Epoch(train) [1064][5/63] lr: 3.0510e-04 eta: 1:34:46 time: 1.1459 data_time: 0.3337 memory: 14901 loss: 0.9206 loss_prob: 0.4785 loss_thr: 0.3575 loss_db: 0.0846 2022/11/03 01:10:28 - mmengine - INFO - Epoch(train) [1064][10/63] lr: 3.0510e-04 eta: 1:34:38 time: 1.1771 data_time: 0.3331 memory: 14901 loss: 0.8656 loss_prob: 0.4481 loss_thr: 0.3399 loss_db: 0.0777 2022/11/03 01:10:30 - mmengine - INFO - Epoch(train) [1064][15/63] lr: 3.0510e-04 eta: 1:34:38 time: 0.6287 data_time: 0.0057 memory: 14901 loss: 0.8353 loss_prob: 0.4327 loss_thr: 0.3276 loss_db: 0.0749 2022/11/03 01:10:34 - mmengine - INFO - Epoch(train) [1064][20/63] lr: 3.0510e-04 eta: 1:34:31 time: 0.6222 data_time: 0.0068 memory: 14901 loss: 0.8240 loss_prob: 0.4156 loss_thr: 0.3352 loss_db: 0.0732 2022/11/03 01:10:38 - mmengine - INFO - Epoch(train) [1064][25/63] lr: 3.0510e-04 eta: 1:34:31 time: 0.7278 data_time: 0.0472 memory: 14901 loss: 0.8625 loss_prob: 0.4354 loss_thr: 0.3504 loss_db: 0.0766 2022/11/03 01:10:41 - mmengine - INFO - Epoch(train) [1064][30/63] lr: 3.0510e-04 eta: 1:34:25 time: 0.6878 data_time: 0.0461 memory: 14901 loss: 0.8854 loss_prob: 0.4550 loss_thr: 0.3513 loss_db: 0.0792 2022/11/03 01:10:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:10:45 - mmengine - INFO - Epoch(train) [1064][35/63] lr: 3.0510e-04 eta: 1:34:25 time: 0.7619 data_time: 0.0060 memory: 14901 loss: 0.8792 loss_prob: 0.4499 loss_thr: 0.3511 loss_db: 0.0782 2022/11/03 01:10:49 - mmengine - INFO - Epoch(train) [1064][40/63] lr: 3.0510e-04 eta: 1:34:19 time: 0.8309 data_time: 0.0082 memory: 14901 loss: 0.8217 loss_prob: 0.4152 loss_thr: 0.3337 loss_db: 0.0729 2022/11/03 01:10:52 - mmengine - INFO - Epoch(train) [1064][45/63] lr: 3.0510e-04 eta: 1:34:19 time: 0.6484 data_time: 0.0080 memory: 14901 loss: 0.8246 loss_prob: 0.4197 loss_thr: 0.3303 loss_db: 0.0746 2022/11/03 01:10:55 - mmengine - INFO - Epoch(train) [1064][50/63] lr: 3.0510e-04 eta: 1:34:12 time: 0.5981 data_time: 0.0296 memory: 14901 loss: 0.8597 loss_prob: 0.4398 loss_thr: 0.3424 loss_db: 0.0776 2022/11/03 01:10:59 - mmengine - INFO - Epoch(train) [1064][55/63] lr: 3.0510e-04 eta: 1:34:12 time: 0.7485 data_time: 0.0297 memory: 14901 loss: 0.8801 loss_prob: 0.4576 loss_thr: 0.3427 loss_db: 0.0798 2022/11/03 01:11:03 - mmengine - INFO - Epoch(train) [1064][60/63] lr: 3.0510e-04 eta: 1:34:05 time: 0.8035 data_time: 0.0068 memory: 14901 loss: 0.9283 loss_prob: 0.4889 loss_thr: 0.3551 loss_db: 0.0844 2022/11/03 01:11:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:11:11 - mmengine - INFO - Epoch(train) [1065][5/63] lr: 3.0308e-04 eta: 1:34:05 time: 0.9462 data_time: 0.2892 memory: 14901 loss: 0.8201 loss_prob: 0.4068 loss_thr: 0.3425 loss_db: 0.0708 2022/11/03 01:11:15 - mmengine - INFO - Epoch(train) [1065][10/63] lr: 3.0308e-04 eta: 1:33:57 time: 1.0406 data_time: 0.2871 memory: 14901 loss: 0.8369 loss_prob: 0.4228 loss_thr: 0.3404 loss_db: 0.0737 2022/11/03 01:11:18 - mmengine - INFO - Epoch(train) [1065][15/63] lr: 3.0308e-04 eta: 1:33:57 time: 0.6600 data_time: 0.0126 memory: 14901 loss: 0.8531 loss_prob: 0.4445 loss_thr: 0.3302 loss_db: 0.0785 2022/11/03 01:11:21 - mmengine - INFO - Epoch(train) [1065][20/63] lr: 3.0308e-04 eta: 1:33:51 time: 0.6324 data_time: 0.0113 memory: 14901 loss: 0.8727 loss_prob: 0.4496 loss_thr: 0.3430 loss_db: 0.0801 2022/11/03 01:11:25 - mmengine - INFO - Epoch(train) [1065][25/63] lr: 3.0308e-04 eta: 1:33:51 time: 0.6793 data_time: 0.0370 memory: 14901 loss: 0.9138 loss_prob: 0.4682 loss_thr: 0.3633 loss_db: 0.0822 2022/11/03 01:11:28 - mmengine - INFO - Epoch(train) [1065][30/63] lr: 3.0308e-04 eta: 1:33:44 time: 0.6495 data_time: 0.0413 memory: 14901 loss: 0.9391 loss_prob: 0.4839 loss_thr: 0.3705 loss_db: 0.0847 2022/11/03 01:11:32 - mmengine - INFO - Epoch(train) [1065][35/63] lr: 3.0308e-04 eta: 1:33:44 time: 0.6848 data_time: 0.0121 memory: 14901 loss: 0.8996 loss_prob: 0.4615 loss_thr: 0.3567 loss_db: 0.0813 2022/11/03 01:11:35 - mmengine - INFO - Epoch(train) [1065][40/63] lr: 3.0308e-04 eta: 1:33:37 time: 0.7194 data_time: 0.0107 memory: 14901 loss: 0.8326 loss_prob: 0.4264 loss_thr: 0.3312 loss_db: 0.0750 2022/11/03 01:11:39 - mmengine - INFO - Epoch(train) [1065][45/63] lr: 3.0308e-04 eta: 1:33:37 time: 0.7006 data_time: 0.0092 memory: 14901 loss: 0.9208 loss_prob: 0.4738 loss_thr: 0.3640 loss_db: 0.0830 2022/11/03 01:11:43 - mmengine - INFO - Epoch(train) [1065][50/63] lr: 3.0308e-04 eta: 1:33:31 time: 0.7685 data_time: 0.0458 memory: 14901 loss: 1.0108 loss_prob: 0.5202 loss_thr: 0.3989 loss_db: 0.0917 2022/11/03 01:11:46 - mmengine - INFO - Epoch(train) [1065][55/63] lr: 3.0308e-04 eta: 1:33:31 time: 0.7794 data_time: 0.0452 memory: 14901 loss: 0.9398 loss_prob: 0.4836 loss_thr: 0.3707 loss_db: 0.0855 2022/11/03 01:11:50 - mmengine - INFO - Epoch(train) [1065][60/63] lr: 3.0308e-04 eta: 1:33:24 time: 0.7108 data_time: 0.0056 memory: 14901 loss: 1.1318 loss_prob: 0.6654 loss_thr: 0.3697 loss_db: 0.0966 2022/11/03 01:11:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:11:59 - mmengine - INFO - Epoch(train) [1066][5/63] lr: 3.0106e-04 eta: 1:33:24 time: 1.0711 data_time: 0.2533 memory: 14901 loss: 0.9469 loss_prob: 0.4873 loss_thr: 0.3736 loss_db: 0.0861 2022/11/03 01:12:04 - mmengine - INFO - Epoch(train) [1066][10/63] lr: 3.0106e-04 eta: 1:33:16 time: 1.2172 data_time: 0.2551 memory: 14901 loss: 1.0413 loss_prob: 0.5511 loss_thr: 0.3931 loss_db: 0.0971 2022/11/03 01:12:09 - mmengine - INFO - Epoch(train) [1066][15/63] lr: 3.0106e-04 eta: 1:33:16 time: 0.9939 data_time: 0.0118 memory: 14901 loss: 0.9761 loss_prob: 0.5205 loss_thr: 0.3639 loss_db: 0.0917 2022/11/03 01:12:12 - mmengine - INFO - Epoch(train) [1066][20/63] lr: 3.0106e-04 eta: 1:33:10 time: 0.8233 data_time: 0.0090 memory: 14901 loss: 0.9511 loss_prob: 0.4913 loss_thr: 0.3744 loss_db: 0.0854 2022/11/03 01:12:15 - mmengine - INFO - Epoch(train) [1066][25/63] lr: 3.0106e-04 eta: 1:33:10 time: 0.6469 data_time: 0.0305 memory: 14901 loss: 0.9412 loss_prob: 0.4818 loss_thr: 0.3769 loss_db: 0.0825 2022/11/03 01:12:19 - mmengine - INFO - Epoch(train) [1066][30/63] lr: 3.0106e-04 eta: 1:33:03 time: 0.6947 data_time: 0.0398 memory: 14901 loss: 0.8914 loss_prob: 0.4606 loss_thr: 0.3505 loss_db: 0.0803 2022/11/03 01:12:23 - mmengine - INFO - Epoch(train) [1066][35/63] lr: 3.0106e-04 eta: 1:33:03 time: 0.7476 data_time: 0.0200 memory: 14901 loss: 0.9796 loss_prob: 0.5155 loss_thr: 0.3748 loss_db: 0.0893 2022/11/03 01:12:27 - mmengine - INFO - Epoch(train) [1066][40/63] lr: 3.0106e-04 eta: 1:32:57 time: 0.7588 data_time: 0.0140 memory: 14901 loss: 1.0099 loss_prob: 0.5346 loss_thr: 0.3826 loss_db: 0.0927 2022/11/03 01:12:30 - mmengine - INFO - Epoch(train) [1066][45/63] lr: 3.0106e-04 eta: 1:32:57 time: 0.6859 data_time: 0.0096 memory: 14901 loss: 0.9285 loss_prob: 0.4892 loss_thr: 0.3550 loss_db: 0.0843 2022/11/03 01:12:33 - mmengine - INFO - Epoch(train) [1066][50/63] lr: 3.0106e-04 eta: 1:32:50 time: 0.6004 data_time: 0.0201 memory: 14901 loss: 0.8687 loss_prob: 0.4448 loss_thr: 0.3477 loss_db: 0.0762 2022/11/03 01:12:36 - mmengine - INFO - Epoch(train) [1066][55/63] lr: 3.0106e-04 eta: 1:32:50 time: 0.6148 data_time: 0.0258 memory: 14901 loss: 0.8783 loss_prob: 0.4507 loss_thr: 0.3486 loss_db: 0.0790 2022/11/03 01:12:39 - mmengine - INFO - Epoch(train) [1066][60/63] lr: 3.0106e-04 eta: 1:32:44 time: 0.6429 data_time: 0.0135 memory: 14901 loss: 0.8410 loss_prob: 0.4389 loss_thr: 0.3247 loss_db: 0.0774 2022/11/03 01:12:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:12:47 - mmengine - INFO - Epoch(train) [1067][5/63] lr: 2.9904e-04 eta: 1:32:44 time: 0.9486 data_time: 0.2366 memory: 14901 loss: 0.8503 loss_prob: 0.4414 loss_thr: 0.3314 loss_db: 0.0776 2022/11/03 01:12:51 - mmengine - INFO - Epoch(train) [1067][10/63] lr: 2.9904e-04 eta: 1:32:35 time: 1.0700 data_time: 0.2358 memory: 14901 loss: 0.9177 loss_prob: 0.4793 loss_thr: 0.3556 loss_db: 0.0828 2022/11/03 01:12:55 - mmengine - INFO - Epoch(train) [1067][15/63] lr: 2.9904e-04 eta: 1:32:35 time: 0.7447 data_time: 0.0066 memory: 14901 loss: 0.9365 loss_prob: 0.4801 loss_thr: 0.3727 loss_db: 0.0837 2022/11/03 01:12:58 - mmengine - INFO - Epoch(train) [1067][20/63] lr: 2.9904e-04 eta: 1:32:29 time: 0.6254 data_time: 0.0058 memory: 14901 loss: 0.8703 loss_prob: 0.4389 loss_thr: 0.3540 loss_db: 0.0775 2022/11/03 01:13:02 - mmengine - INFO - Epoch(train) [1067][25/63] lr: 2.9904e-04 eta: 1:32:29 time: 0.7353 data_time: 0.0150 memory: 14901 loss: 0.8814 loss_prob: 0.4515 loss_thr: 0.3512 loss_db: 0.0787 2022/11/03 01:13:05 - mmengine - INFO - Epoch(train) [1067][30/63] lr: 2.9904e-04 eta: 1:32:22 time: 0.7637 data_time: 0.0393 memory: 14901 loss: 0.9119 loss_prob: 0.4705 loss_thr: 0.3590 loss_db: 0.0824 2022/11/03 01:13:09 - mmengine - INFO - Epoch(train) [1067][35/63] lr: 2.9904e-04 eta: 1:32:22 time: 0.6899 data_time: 0.0302 memory: 14901 loss: 0.9016 loss_prob: 0.4652 loss_thr: 0.3533 loss_db: 0.0831 2022/11/03 01:13:12 - mmengine - INFO - Epoch(train) [1067][40/63] lr: 2.9904e-04 eta: 1:32:16 time: 0.6572 data_time: 0.0062 memory: 14901 loss: 0.8904 loss_prob: 0.4552 loss_thr: 0.3534 loss_db: 0.0818 2022/11/03 01:13:14 - mmengine - INFO - Epoch(train) [1067][45/63] lr: 2.9904e-04 eta: 1:32:16 time: 0.5104 data_time: 0.0051 memory: 14901 loss: 0.8613 loss_prob: 0.4409 loss_thr: 0.3426 loss_db: 0.0777 2022/11/03 01:13:17 - mmengine - INFO - Epoch(train) [1067][50/63] lr: 2.9904e-04 eta: 1:32:09 time: 0.4782 data_time: 0.0139 memory: 14901 loss: 0.9002 loss_prob: 0.4730 loss_thr: 0.3452 loss_db: 0.0820 2022/11/03 01:13:19 - mmengine - INFO - Epoch(train) [1067][55/63] lr: 2.9904e-04 eta: 1:32:09 time: 0.4896 data_time: 0.0210 memory: 14901 loss: 0.9105 loss_prob: 0.4862 loss_thr: 0.3404 loss_db: 0.0839 2022/11/03 01:13:21 - mmengine - INFO - Epoch(train) [1067][60/63] lr: 2.9904e-04 eta: 1:32:02 time: 0.4744 data_time: 0.0114 memory: 14901 loss: 0.9557 loss_prob: 0.5103 loss_thr: 0.3612 loss_db: 0.0842 2022/11/03 01:13:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:13:27 - mmengine - INFO - Epoch(train) [1068][5/63] lr: 2.9701e-04 eta: 1:32:02 time: 0.6441 data_time: 0.1811 memory: 14901 loss: 0.8843 loss_prob: 0.4657 loss_thr: 0.3371 loss_db: 0.0815 2022/11/03 01:13:30 - mmengine - INFO - Epoch(train) [1068][10/63] lr: 2.9701e-04 eta: 1:31:53 time: 0.7005 data_time: 0.1957 memory: 14901 loss: 0.8604 loss_prob: 0.4509 loss_thr: 0.3282 loss_db: 0.0813 2022/11/03 01:13:32 - mmengine - INFO - Epoch(train) [1068][15/63] lr: 2.9701e-04 eta: 1:31:53 time: 0.5050 data_time: 0.0190 memory: 14901 loss: 0.8392 loss_prob: 0.4200 loss_thr: 0.3463 loss_db: 0.0729 2022/11/03 01:13:34 - mmengine - INFO - Epoch(train) [1068][20/63] lr: 2.9701e-04 eta: 1:31:47 time: 0.4739 data_time: 0.0043 memory: 14901 loss: 0.8010 loss_prob: 0.3997 loss_thr: 0.3331 loss_db: 0.0682 2022/11/03 01:13:37 - mmengine - INFO - Epoch(train) [1068][25/63] lr: 2.9701e-04 eta: 1:31:47 time: 0.4803 data_time: 0.0089 memory: 14901 loss: 0.8354 loss_prob: 0.4252 loss_thr: 0.3371 loss_db: 0.0732 2022/11/03 01:13:40 - mmengine - INFO - Epoch(train) [1068][30/63] lr: 2.9701e-04 eta: 1:31:40 time: 0.5625 data_time: 0.0244 memory: 14901 loss: 0.9021 loss_prob: 0.4606 loss_thr: 0.3608 loss_db: 0.0808 2022/11/03 01:13:43 - mmengine - INFO - Epoch(train) [1068][35/63] lr: 2.9701e-04 eta: 1:31:40 time: 0.5723 data_time: 0.0317 memory: 14901 loss: 0.8471 loss_prob: 0.4249 loss_thr: 0.3459 loss_db: 0.0763 2022/11/03 01:13:52 - mmengine - INFO - Epoch(train) [1068][40/63] lr: 2.9701e-04 eta: 1:31:34 time: 1.2371 data_time: 0.0188 memory: 14901 loss: 0.8082 loss_prob: 0.4045 loss_thr: 0.3313 loss_db: 0.0724 2022/11/03 01:14:01 - mmengine - INFO - Epoch(train) [1068][45/63] lr: 2.9701e-04 eta: 1:31:34 time: 1.8508 data_time: 0.0103 memory: 14901 loss: 0.8696 loss_prob: 0.4517 loss_thr: 0.3404 loss_db: 0.0774 2022/11/03 01:14:08 - mmengine - INFO - Epoch(train) [1068][50/63] lr: 2.9701e-04 eta: 1:31:29 time: 1.6086 data_time: 0.0253 memory: 14901 loss: 0.9296 loss_prob: 0.4765 loss_thr: 0.3706 loss_db: 0.0825 2022/11/03 01:14:15 - mmengine - INFO - Epoch(train) [1068][55/63] lr: 2.9701e-04 eta: 1:31:29 time: 1.4205 data_time: 0.0315 memory: 14901 loss: 0.8970 loss_prob: 0.4529 loss_thr: 0.3633 loss_db: 0.0808 2022/11/03 01:14:19 - mmengine - INFO - Epoch(train) [1068][60/63] lr: 2.9701e-04 eta: 1:31:22 time: 1.0313 data_time: 0.0246 memory: 14901 loss: 0.8643 loss_prob: 0.4459 loss_thr: 0.3405 loss_db: 0.0779 2022/11/03 01:14:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:14:29 - mmengine - INFO - Epoch(train) [1069][5/63] lr: 2.9499e-04 eta: 1:31:22 time: 1.1462 data_time: 0.3044 memory: 14901 loss: 0.8936 loss_prob: 0.4592 loss_thr: 0.3528 loss_db: 0.0815 2022/11/03 01:14:33 - mmengine - INFO - Epoch(train) [1069][10/63] lr: 2.9499e-04 eta: 1:31:14 time: 1.2540 data_time: 0.3046 memory: 14901 loss: 0.9239 loss_prob: 0.4789 loss_thr: 0.3600 loss_db: 0.0850 2022/11/03 01:14:37 - mmengine - INFO - Epoch(train) [1069][15/63] lr: 2.9499e-04 eta: 1:31:14 time: 0.8066 data_time: 0.0060 memory: 14901 loss: 0.8735 loss_prob: 0.4460 loss_thr: 0.3492 loss_db: 0.0784 2022/11/03 01:14:42 - mmengine - INFO - Epoch(train) [1069][20/63] lr: 2.9499e-04 eta: 1:31:08 time: 0.8644 data_time: 0.0058 memory: 14901 loss: 0.8975 loss_prob: 0.4590 loss_thr: 0.3586 loss_db: 0.0798 2022/11/03 01:14:45 - mmengine - INFO - Epoch(train) [1069][25/63] lr: 2.9499e-04 eta: 1:31:08 time: 0.7481 data_time: 0.0375 memory: 14901 loss: 0.9077 loss_prob: 0.4712 loss_thr: 0.3543 loss_db: 0.0822 2022/11/03 01:14:47 - mmengine - INFO - Epoch(train) [1069][30/63] lr: 2.9499e-04 eta: 1:31:01 time: 0.5933 data_time: 0.0468 memory: 14901 loss: 0.8385 loss_prob: 0.4256 loss_thr: 0.3379 loss_db: 0.0750 2022/11/03 01:14:50 - mmengine - INFO - Epoch(train) [1069][35/63] lr: 2.9499e-04 eta: 1:31:01 time: 0.5674 data_time: 0.0153 memory: 14901 loss: 0.8313 loss_prob: 0.4222 loss_thr: 0.3346 loss_db: 0.0744 2022/11/03 01:14:54 - mmengine - INFO - Epoch(train) [1069][40/63] lr: 2.9499e-04 eta: 1:30:55 time: 0.6707 data_time: 0.0119 memory: 14901 loss: 0.8436 loss_prob: 0.4430 loss_thr: 0.3231 loss_db: 0.0776 2022/11/03 01:14:57 - mmengine - INFO - Epoch(train) [1069][45/63] lr: 2.9499e-04 eta: 1:30:55 time: 0.6337 data_time: 0.0122 memory: 14901 loss: 0.8124 loss_prob: 0.4285 loss_thr: 0.3085 loss_db: 0.0754 2022/11/03 01:15:00 - mmengine - INFO - Epoch(train) [1069][50/63] lr: 2.9499e-04 eta: 1:30:48 time: 0.5792 data_time: 0.0261 memory: 14901 loss: 0.8484 loss_prob: 0.4422 loss_thr: 0.3289 loss_db: 0.0773 2022/11/03 01:15:05 - mmengine - INFO - Epoch(train) [1069][55/63] lr: 2.9499e-04 eta: 1:30:48 time: 0.7956 data_time: 0.0338 memory: 14901 loss: 0.9061 loss_prob: 0.4673 loss_thr: 0.3578 loss_db: 0.0811 2022/11/03 01:15:08 - mmengine - INFO - Epoch(train) [1069][60/63] lr: 2.9499e-04 eta: 1:30:42 time: 0.8378 data_time: 0.0142 memory: 14901 loss: 0.9185 loss_prob: 0.4734 loss_thr: 0.3612 loss_db: 0.0839 2022/11/03 01:15:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:15:16 - mmengine - INFO - Epoch(train) [1070][5/63] lr: 2.9296e-04 eta: 1:30:42 time: 0.9259 data_time: 0.2509 memory: 14901 loss: 0.9235 loss_prob: 0.4747 loss_thr: 0.3652 loss_db: 0.0836 2022/11/03 01:15:20 - mmengine - INFO - Epoch(train) [1070][10/63] lr: 2.9296e-04 eta: 1:30:33 time: 1.0414 data_time: 0.2512 memory: 14901 loss: 0.9001 loss_prob: 0.4718 loss_thr: 0.3494 loss_db: 0.0789 2022/11/03 01:15:24 - mmengine - INFO - Epoch(train) [1070][15/63] lr: 2.9296e-04 eta: 1:30:33 time: 0.7208 data_time: 0.0077 memory: 14901 loss: 0.8908 loss_prob: 0.4661 loss_thr: 0.3461 loss_db: 0.0785 2022/11/03 01:15:26 - mmengine - INFO - Epoch(train) [1070][20/63] lr: 2.9296e-04 eta: 1:30:27 time: 0.6152 data_time: 0.0075 memory: 14901 loss: 0.8705 loss_prob: 0.4394 loss_thr: 0.3540 loss_db: 0.0771 2022/11/03 01:15:30 - mmengine - INFO - Epoch(train) [1070][25/63] lr: 2.9296e-04 eta: 1:30:27 time: 0.6337 data_time: 0.0148 memory: 14901 loss: 0.9268 loss_prob: 0.4716 loss_thr: 0.3735 loss_db: 0.0817 2022/11/03 01:15:34 - mmengine - INFO - Epoch(train) [1070][30/63] lr: 2.9296e-04 eta: 1:30:20 time: 0.7250 data_time: 0.0384 memory: 14901 loss: 0.9071 loss_prob: 0.4637 loss_thr: 0.3617 loss_db: 0.0816 2022/11/03 01:15:37 - mmengine - INFO - Epoch(train) [1070][35/63] lr: 2.9296e-04 eta: 1:30:20 time: 0.7364 data_time: 0.0315 memory: 14901 loss: 0.8790 loss_prob: 0.4446 loss_thr: 0.3565 loss_db: 0.0779 2022/11/03 01:15:42 - mmengine - INFO - Epoch(train) [1070][40/63] lr: 2.9296e-04 eta: 1:30:14 time: 0.8730 data_time: 0.0089 memory: 14901 loss: 0.8906 loss_prob: 0.4545 loss_thr: 0.3562 loss_db: 0.0799 2022/11/03 01:15:48 - mmengine - INFO - Epoch(train) [1070][45/63] lr: 2.9296e-04 eta: 1:30:14 time: 1.0226 data_time: 0.0077 memory: 14901 loss: 0.8901 loss_prob: 0.4648 loss_thr: 0.3433 loss_db: 0.0820 2022/11/03 01:15:53 - mmengine - INFO - Epoch(train) [1070][50/63] lr: 2.9296e-04 eta: 1:30:08 time: 1.0326 data_time: 0.0275 memory: 14901 loss: 0.8581 loss_prob: 0.4445 loss_thr: 0.3348 loss_db: 0.0788 2022/11/03 01:15:56 - mmengine - INFO - Epoch(train) [1070][55/63] lr: 2.9296e-04 eta: 1:30:08 time: 0.8755 data_time: 0.0270 memory: 14901 loss: 0.8261 loss_prob: 0.4269 loss_thr: 0.3236 loss_db: 0.0756 2022/11/03 01:16:00 - mmengine - INFO - Epoch(train) [1070][60/63] lr: 2.9296e-04 eta: 1:30:01 time: 0.7082 data_time: 0.0076 memory: 14901 loss: 0.8575 loss_prob: 0.4395 loss_thr: 0.3413 loss_db: 0.0767 2022/11/03 01:16:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:16:09 - mmengine - INFO - Epoch(train) [1071][5/63] lr: 2.9093e-04 eta: 1:30:01 time: 1.0287 data_time: 0.2561 memory: 14901 loss: 0.9324 loss_prob: 0.4808 loss_thr: 0.3673 loss_db: 0.0844 2022/11/03 01:16:14 - mmengine - INFO - Epoch(train) [1071][10/63] lr: 2.9093e-04 eta: 1:29:53 time: 1.2448 data_time: 0.2553 memory: 14901 loss: 0.8826 loss_prob: 0.4551 loss_thr: 0.3476 loss_db: 0.0799 2022/11/03 01:16:19 - mmengine - INFO - Epoch(train) [1071][15/63] lr: 2.9093e-04 eta: 1:29:53 time: 1.0187 data_time: 0.0090 memory: 14901 loss: 0.8683 loss_prob: 0.4518 loss_thr: 0.3383 loss_db: 0.0782 2022/11/03 01:16:22 - mmengine - INFO - Epoch(train) [1071][20/63] lr: 2.9093e-04 eta: 1:29:47 time: 0.8189 data_time: 0.0087 memory: 14901 loss: 0.9348 loss_prob: 0.4960 loss_thr: 0.3530 loss_db: 0.0858 2022/11/03 01:16:25 - mmengine - INFO - Epoch(train) [1071][25/63] lr: 2.9093e-04 eta: 1:29:47 time: 0.6526 data_time: 0.0255 memory: 14901 loss: 0.8775 loss_prob: 0.4561 loss_thr: 0.3410 loss_db: 0.0804 2022/11/03 01:16:30 - mmengine - INFO - Epoch(train) [1071][30/63] lr: 2.9093e-04 eta: 1:29:40 time: 0.8203 data_time: 0.0370 memory: 14901 loss: 0.8417 loss_prob: 0.4304 loss_thr: 0.3357 loss_db: 0.0756 2022/11/03 01:16:34 - mmengine - INFO - Epoch(train) [1071][35/63] lr: 2.9093e-04 eta: 1:29:40 time: 0.8993 data_time: 0.0183 memory: 14901 loss: 1.1039 loss_prob: 0.6281 loss_thr: 0.3711 loss_db: 0.1046 2022/11/03 01:16:38 - mmengine - INFO - Epoch(train) [1071][40/63] lr: 2.9093e-04 eta: 1:29:34 time: 0.7914 data_time: 0.0083 memory: 14901 loss: 1.0514 loss_prob: 0.5894 loss_thr: 0.3626 loss_db: 0.0994 2022/11/03 01:16:42 - mmengine - INFO - Epoch(train) [1071][45/63] lr: 2.9093e-04 eta: 1:29:34 time: 0.7395 data_time: 0.0080 memory: 14901 loss: 0.8456 loss_prob: 0.4346 loss_thr: 0.3357 loss_db: 0.0753 2022/11/03 01:16:45 - mmengine - INFO - Epoch(train) [1071][50/63] lr: 2.9093e-04 eta: 1:29:27 time: 0.7200 data_time: 0.0266 memory: 14901 loss: 0.9288 loss_prob: 0.4947 loss_thr: 0.3517 loss_db: 0.0824 2022/11/03 01:16:48 - mmengine - INFO - Epoch(train) [1071][55/63] lr: 2.9093e-04 eta: 1:29:27 time: 0.6023 data_time: 0.0274 memory: 14901 loss: 0.9217 loss_prob: 0.4795 loss_thr: 0.3611 loss_db: 0.0812 2022/11/03 01:16:51 - mmengine - INFO - Epoch(train) [1071][60/63] lr: 2.9093e-04 eta: 1:29:21 time: 0.6311 data_time: 0.0085 memory: 14901 loss: 0.8635 loss_prob: 0.4382 loss_thr: 0.3493 loss_db: 0.0760 2022/11/03 01:16:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:16:58 - mmengine - INFO - Epoch(train) [1072][5/63] lr: 2.8890e-04 eta: 1:29:21 time: 0.8281 data_time: 0.2831 memory: 14901 loss: 0.8760 loss_prob: 0.4547 loss_thr: 0.3440 loss_db: 0.0772 2022/11/03 01:17:02 - mmengine - INFO - Epoch(train) [1072][10/63] lr: 2.8890e-04 eta: 1:29:12 time: 0.8960 data_time: 0.2800 memory: 14901 loss: 0.9374 loss_prob: 0.4954 loss_thr: 0.3580 loss_db: 0.0841 2022/11/03 01:17:06 - mmengine - INFO - Epoch(train) [1072][15/63] lr: 2.8890e-04 eta: 1:29:12 time: 0.7779 data_time: 0.0071 memory: 14901 loss: 0.9388 loss_prob: 0.4912 loss_thr: 0.3608 loss_db: 0.0869 2022/11/03 01:17:10 - mmengine - INFO - Epoch(train) [1072][20/63] lr: 2.8890e-04 eta: 1:29:06 time: 0.7798 data_time: 0.0076 memory: 14901 loss: 0.9076 loss_prob: 0.4747 loss_thr: 0.3489 loss_db: 0.0840 2022/11/03 01:17:13 - mmengine - INFO - Epoch(train) [1072][25/63] lr: 2.8890e-04 eta: 1:29:06 time: 0.6973 data_time: 0.0123 memory: 14901 loss: 0.8726 loss_prob: 0.4565 loss_thr: 0.3383 loss_db: 0.0778 2022/11/03 01:17:17 - mmengine - INFO - Epoch(train) [1072][30/63] lr: 2.8890e-04 eta: 1:28:59 time: 0.6984 data_time: 0.0375 memory: 14901 loss: 0.8344 loss_prob: 0.4273 loss_thr: 0.3333 loss_db: 0.0739 2022/11/03 01:17:21 - mmengine - INFO - Epoch(train) [1072][35/63] lr: 2.8890e-04 eta: 1:28:59 time: 0.8012 data_time: 0.0328 memory: 14901 loss: 0.8385 loss_prob: 0.4245 loss_thr: 0.3383 loss_db: 0.0757 2022/11/03 01:17:24 - mmengine - INFO - Epoch(train) [1072][40/63] lr: 2.8890e-04 eta: 1:28:53 time: 0.7250 data_time: 0.0094 memory: 14901 loss: 0.8702 loss_prob: 0.4426 loss_thr: 0.3505 loss_db: 0.0770 2022/11/03 01:17:28 - mmengine - INFO - Epoch(train) [1072][45/63] lr: 2.8890e-04 eta: 1:28:53 time: 0.7184 data_time: 0.0105 memory: 14901 loss: 0.9104 loss_prob: 0.4674 loss_thr: 0.3624 loss_db: 0.0807 2022/11/03 01:17:32 - mmengine - INFO - Epoch(train) [1072][50/63] lr: 2.8890e-04 eta: 1:28:46 time: 0.8204 data_time: 0.0156 memory: 14901 loss: 0.9155 loss_prob: 0.4741 loss_thr: 0.3573 loss_db: 0.0841 2022/11/03 01:17:36 - mmengine - INFO - Epoch(train) [1072][55/63] lr: 2.8890e-04 eta: 1:28:46 time: 0.8034 data_time: 0.0248 memory: 14901 loss: 0.9278 loss_prob: 0.4869 loss_thr: 0.3565 loss_db: 0.0844 2022/11/03 01:17:40 - mmengine - INFO - Epoch(train) [1072][60/63] lr: 2.8890e-04 eta: 1:28:40 time: 0.8073 data_time: 0.0178 memory: 14901 loss: 0.9256 loss_prob: 0.4875 loss_thr: 0.3540 loss_db: 0.0840 2022/11/03 01:17:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:17:49 - mmengine - INFO - Epoch(train) [1073][5/63] lr: 2.8687e-04 eta: 1:28:40 time: 1.0319 data_time: 0.2473 memory: 14901 loss: 0.8782 loss_prob: 0.4465 loss_thr: 0.3512 loss_db: 0.0805 2022/11/03 01:17:52 - mmengine - INFO - Epoch(train) [1073][10/63] lr: 2.8687e-04 eta: 1:28:31 time: 0.9758 data_time: 0.2499 memory: 14901 loss: 0.8562 loss_prob: 0.4372 loss_thr: 0.3418 loss_db: 0.0773 2022/11/03 01:17:54 - mmengine - INFO - Epoch(train) [1073][15/63] lr: 2.8687e-04 eta: 1:28:31 time: 0.5456 data_time: 0.0104 memory: 14901 loss: 0.8506 loss_prob: 0.4446 loss_thr: 0.3311 loss_db: 0.0749 2022/11/03 01:17:57 - mmengine - INFO - Epoch(train) [1073][20/63] lr: 2.8687e-04 eta: 1:28:25 time: 0.5763 data_time: 0.0054 memory: 14901 loss: 0.9476 loss_prob: 0.5029 loss_thr: 0.3582 loss_db: 0.0865 2022/11/03 01:18:01 - mmengine - INFO - Epoch(train) [1073][25/63] lr: 2.8687e-04 eta: 1:28:25 time: 0.6452 data_time: 0.0121 memory: 14901 loss: 0.8823 loss_prob: 0.4616 loss_thr: 0.3379 loss_db: 0.0828 2022/11/03 01:18:06 - mmengine - INFO - Epoch(train) [1073][30/63] lr: 2.8687e-04 eta: 1:28:18 time: 0.8115 data_time: 0.0458 memory: 14901 loss: 0.7996 loss_prob: 0.4122 loss_thr: 0.3137 loss_db: 0.0738 2022/11/03 01:18:09 - mmengine - INFO - Epoch(train) [1073][35/63] lr: 2.8687e-04 eta: 1:28:18 time: 0.7861 data_time: 0.0393 memory: 14901 loss: 0.8848 loss_prob: 0.4767 loss_thr: 0.3222 loss_db: 0.0859 2022/11/03 01:18:11 - mmengine - INFO - Epoch(train) [1073][40/63] lr: 2.8687e-04 eta: 1:28:12 time: 0.5613 data_time: 0.0052 memory: 14901 loss: 0.8849 loss_prob: 0.4807 loss_thr: 0.3189 loss_db: 0.0852 2022/11/03 01:18:14 - mmengine - INFO - Epoch(train) [1073][45/63] lr: 2.8687e-04 eta: 1:28:12 time: 0.5290 data_time: 0.0063 memory: 14901 loss: 0.8903 loss_prob: 0.4653 loss_thr: 0.3456 loss_db: 0.0794 2022/11/03 01:18:18 - mmengine - INFO - Epoch(train) [1073][50/63] lr: 2.8687e-04 eta: 1:28:05 time: 0.7090 data_time: 0.0218 memory: 14901 loss: 0.9725 loss_prob: 0.5066 loss_thr: 0.3787 loss_db: 0.0872 2022/11/03 01:18:23 - mmengine - INFO - Epoch(train) [1073][55/63] lr: 2.8687e-04 eta: 1:28:05 time: 0.8618 data_time: 0.0275 memory: 14901 loss: 0.9387 loss_prob: 0.4834 loss_thr: 0.3700 loss_db: 0.0854 2022/11/03 01:18:26 - mmengine - INFO - Epoch(train) [1073][60/63] lr: 2.8687e-04 eta: 1:27:59 time: 0.8130 data_time: 0.0127 memory: 14901 loss: 0.9481 loss_prob: 0.4914 loss_thr: 0.3696 loss_db: 0.0871 2022/11/03 01:18:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:18:35 - mmengine - INFO - Epoch(train) [1074][5/63] lr: 2.8484e-04 eta: 1:27:59 time: 0.9156 data_time: 0.2510 memory: 14901 loss: 0.9869 loss_prob: 0.5216 loss_thr: 0.3756 loss_db: 0.0897 2022/11/03 01:18:37 - mmengine - INFO - Epoch(train) [1074][10/63] lr: 2.8484e-04 eta: 1:27:50 time: 0.9649 data_time: 0.2512 memory: 14901 loss: 0.9387 loss_prob: 0.4900 loss_thr: 0.3646 loss_db: 0.0841 2022/11/03 01:18:41 - mmengine - INFO - Epoch(train) [1074][15/63] lr: 2.8484e-04 eta: 1:27:50 time: 0.6820 data_time: 0.0100 memory: 14901 loss: 0.8579 loss_prob: 0.4445 loss_thr: 0.3346 loss_db: 0.0788 2022/11/03 01:18:45 - mmengine - INFO - Epoch(train) [1074][20/63] lr: 2.8484e-04 eta: 1:27:44 time: 0.7913 data_time: 0.0103 memory: 14901 loss: 0.8983 loss_prob: 0.4609 loss_thr: 0.3557 loss_db: 0.0817 2022/11/03 01:18:50 - mmengine - INFO - Epoch(train) [1074][25/63] lr: 2.8484e-04 eta: 1:27:44 time: 0.8734 data_time: 0.0213 memory: 14901 loss: 0.9970 loss_prob: 0.5312 loss_thr: 0.3751 loss_db: 0.0906 2022/11/03 01:18:53 - mmengine - INFO - Epoch(train) [1074][30/63] lr: 2.8484e-04 eta: 1:27:37 time: 0.7784 data_time: 0.0452 memory: 14901 loss: 0.9704 loss_prob: 0.5112 loss_thr: 0.3708 loss_db: 0.0884 2022/11/03 01:18:57 - mmengine - INFO - Epoch(train) [1074][35/63] lr: 2.8484e-04 eta: 1:27:37 time: 0.7012 data_time: 0.0296 memory: 14901 loss: 0.9019 loss_prob: 0.4626 loss_thr: 0.3580 loss_db: 0.0813 2022/11/03 01:19:02 - mmengine - INFO - Epoch(train) [1074][40/63] lr: 2.8484e-04 eta: 1:27:31 time: 0.8919 data_time: 0.0080 memory: 14901 loss: 0.9134 loss_prob: 0.4777 loss_thr: 0.3550 loss_db: 0.0807 2022/11/03 01:19:06 - mmengine - INFO - Epoch(train) [1074][45/63] lr: 2.8484e-04 eta: 1:27:31 time: 0.9283 data_time: 0.0098 memory: 14901 loss: 0.9009 loss_prob: 0.4695 loss_thr: 0.3516 loss_db: 0.0799 2022/11/03 01:19:10 - mmengine - INFO - Epoch(train) [1074][50/63] lr: 2.8484e-04 eta: 1:27:25 time: 0.8126 data_time: 0.0254 memory: 14901 loss: 0.9377 loss_prob: 0.4862 loss_thr: 0.3676 loss_db: 0.0840 2022/11/03 01:19:13 - mmengine - INFO - Epoch(train) [1074][55/63] lr: 2.8484e-04 eta: 1:27:25 time: 0.6555 data_time: 0.0289 memory: 14901 loss: 0.9190 loss_prob: 0.4759 loss_thr: 0.3610 loss_db: 0.0822 2022/11/03 01:19:16 - mmengine - INFO - Epoch(train) [1074][60/63] lr: 2.8484e-04 eta: 1:27:18 time: 0.5513 data_time: 0.0119 memory: 14901 loss: 0.9115 loss_prob: 0.4783 loss_thr: 0.3502 loss_db: 0.0830 2022/11/03 01:19:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:19:25 - mmengine - INFO - Epoch(train) [1075][5/63] lr: 2.8280e-04 eta: 1:27:18 time: 1.0316 data_time: 0.2691 memory: 14901 loss: 0.9018 loss_prob: 0.4666 loss_thr: 0.3552 loss_db: 0.0800 2022/11/03 01:19:29 - mmengine - INFO - Epoch(train) [1075][10/63] lr: 2.8280e-04 eta: 1:27:09 time: 1.0887 data_time: 0.2697 memory: 14901 loss: 0.9119 loss_prob: 0.4755 loss_thr: 0.3543 loss_db: 0.0821 2022/11/03 01:19:34 - mmengine - INFO - Epoch(train) [1075][15/63] lr: 2.8280e-04 eta: 1:27:09 time: 0.8879 data_time: 0.0101 memory: 14901 loss: 0.8774 loss_prob: 0.4539 loss_thr: 0.3434 loss_db: 0.0801 2022/11/03 01:19:37 - mmengine - INFO - Epoch(train) [1075][20/63] lr: 2.8280e-04 eta: 1:27:03 time: 0.8115 data_time: 0.0090 memory: 14901 loss: 0.7835 loss_prob: 0.3930 loss_thr: 0.3196 loss_db: 0.0710 2022/11/03 01:19:40 - mmengine - INFO - Epoch(train) [1075][25/63] lr: 2.8280e-04 eta: 1:27:03 time: 0.6793 data_time: 0.0199 memory: 14901 loss: 0.9135 loss_prob: 0.4737 loss_thr: 0.3579 loss_db: 0.0819 2022/11/03 01:19:46 - mmengine - INFO - Epoch(train) [1075][30/63] lr: 2.8280e-04 eta: 1:26:57 time: 0.8700 data_time: 0.0537 memory: 14901 loss: 0.9770 loss_prob: 0.5094 loss_thr: 0.3808 loss_db: 0.0868 2022/11/03 01:19:48 - mmengine - INFO - Epoch(train) [1075][35/63] lr: 2.8280e-04 eta: 1:26:57 time: 0.7801 data_time: 0.0425 memory: 14901 loss: 0.8686 loss_prob: 0.4388 loss_thr: 0.3552 loss_db: 0.0747 2022/11/03 01:19:51 - mmengine - INFO - Epoch(train) [1075][40/63] lr: 2.8280e-04 eta: 1:26:50 time: 0.5394 data_time: 0.0085 memory: 14901 loss: 0.8630 loss_prob: 0.4398 loss_thr: 0.3477 loss_db: 0.0754 2022/11/03 01:19:54 - mmengine - INFO - Epoch(train) [1075][45/63] lr: 2.8280e-04 eta: 1:26:50 time: 0.5683 data_time: 0.0105 memory: 14901 loss: 0.8304 loss_prob: 0.4276 loss_thr: 0.3272 loss_db: 0.0757 2022/11/03 01:19:58 - mmengine - INFO - Epoch(train) [1075][50/63] lr: 2.8280e-04 eta: 1:26:43 time: 0.7153 data_time: 0.0195 memory: 14901 loss: 0.8704 loss_prob: 0.4552 loss_thr: 0.3348 loss_db: 0.0804 2022/11/03 01:20:03 - mmengine - INFO - Epoch(train) [1075][55/63] lr: 2.8280e-04 eta: 1:26:43 time: 0.8969 data_time: 0.0270 memory: 14901 loss: 0.9260 loss_prob: 0.4916 loss_thr: 0.3483 loss_db: 0.0861 2022/11/03 01:20:05 - mmengine - INFO - Epoch(train) [1075][60/63] lr: 2.8280e-04 eta: 1:26:37 time: 0.7261 data_time: 0.0182 memory: 14901 loss: 0.8948 loss_prob: 0.4675 loss_thr: 0.3457 loss_db: 0.0816 2022/11/03 01:20:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:20:15 - mmengine - INFO - Epoch(train) [1076][5/63] lr: 2.8077e-04 eta: 1:26:37 time: 1.0730 data_time: 0.2458 memory: 14901 loss: 0.8697 loss_prob: 0.4517 loss_thr: 0.3397 loss_db: 0.0783 2022/11/03 01:20:19 - mmengine - INFO - Epoch(train) [1076][10/63] lr: 2.8077e-04 eta: 1:26:29 time: 1.2041 data_time: 0.2565 memory: 14901 loss: 0.8734 loss_prob: 0.4633 loss_thr: 0.3237 loss_db: 0.0864 2022/11/03 01:20:23 - mmengine - INFO - Epoch(train) [1076][15/63] lr: 2.8077e-04 eta: 1:26:29 time: 0.7477 data_time: 0.0236 memory: 14901 loss: 0.8727 loss_prob: 0.4531 loss_thr: 0.3333 loss_db: 0.0863 2022/11/03 01:20:27 - mmengine - INFO - Epoch(train) [1076][20/63] lr: 2.8077e-04 eta: 1:26:22 time: 0.7382 data_time: 0.0107 memory: 14901 loss: 0.8247 loss_prob: 0.4198 loss_thr: 0.3293 loss_db: 0.0757 2022/11/03 01:20:30 - mmengine - INFO - Epoch(train) [1076][25/63] lr: 2.8077e-04 eta: 1:26:22 time: 0.6921 data_time: 0.0259 memory: 14901 loss: 0.9199 loss_prob: 0.4823 loss_thr: 0.3541 loss_db: 0.0835 2022/11/03 01:20:32 - mmengine - INFO - Epoch(train) [1076][30/63] lr: 2.8077e-04 eta: 1:26:16 time: 0.5777 data_time: 0.0264 memory: 14901 loss: 0.9861 loss_prob: 0.5217 loss_thr: 0.3731 loss_db: 0.0913 2022/11/03 01:20:36 - mmengine - INFO - Epoch(train) [1076][35/63] lr: 2.8077e-04 eta: 1:26:16 time: 0.6928 data_time: 0.0126 memory: 14901 loss: 0.8628 loss_prob: 0.4410 loss_thr: 0.3413 loss_db: 0.0804 2022/11/03 01:20:39 - mmengine - INFO - Epoch(train) [1076][40/63] lr: 2.8077e-04 eta: 1:26:09 time: 0.6640 data_time: 0.0166 memory: 14901 loss: 0.8898 loss_prob: 0.4562 loss_thr: 0.3537 loss_db: 0.0799 2022/11/03 01:20:42 - mmengine - INFO - Epoch(train) [1076][45/63] lr: 2.8077e-04 eta: 1:26:09 time: 0.5262 data_time: 0.0125 memory: 14901 loss: 0.9823 loss_prob: 0.5087 loss_thr: 0.3859 loss_db: 0.0877 2022/11/03 01:20:46 - mmengine - INFO - Epoch(train) [1076][50/63] lr: 2.8077e-04 eta: 1:26:02 time: 0.6460 data_time: 0.0229 memory: 14901 loss: 0.9034 loss_prob: 0.4594 loss_thr: 0.3624 loss_db: 0.0816 2022/11/03 01:20:50 - mmengine - INFO - Epoch(train) [1076][55/63] lr: 2.8077e-04 eta: 1:26:02 time: 0.8685 data_time: 0.0210 memory: 14901 loss: 0.8429 loss_prob: 0.4315 loss_thr: 0.3350 loss_db: 0.0765 2022/11/03 01:20:55 - mmengine - INFO - Epoch(train) [1076][60/63] lr: 2.8077e-04 eta: 1:25:56 time: 0.9112 data_time: 0.0124 memory: 14901 loss: 0.9586 loss_prob: 0.4965 loss_thr: 0.3753 loss_db: 0.0868 2022/11/03 01:20:57 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:21:05 - mmengine - INFO - Epoch(train) [1077][5/63] lr: 2.7873e-04 eta: 1:25:56 time: 1.1965 data_time: 0.3152 memory: 14901 loss: 0.9107 loss_prob: 0.4713 loss_thr: 0.3600 loss_db: 0.0795 2022/11/03 01:21:10 - mmengine - INFO - Epoch(train) [1077][10/63] lr: 2.7873e-04 eta: 1:25:48 time: 1.2819 data_time: 0.3167 memory: 14901 loss: 0.9253 loss_prob: 0.4816 loss_thr: 0.3629 loss_db: 0.0808 2022/11/03 01:21:13 - mmengine - INFO - Epoch(train) [1077][15/63] lr: 2.7873e-04 eta: 1:25:48 time: 0.8155 data_time: 0.0123 memory: 14901 loss: 0.9376 loss_prob: 0.4813 loss_thr: 0.3713 loss_db: 0.0851 2022/11/03 01:21:18 - mmengine - INFO - Epoch(train) [1077][20/63] lr: 2.7873e-04 eta: 1:25:41 time: 0.7784 data_time: 0.0118 memory: 14901 loss: 0.9705 loss_prob: 0.5199 loss_thr: 0.3608 loss_db: 0.0897 2022/11/03 01:21:22 - mmengine - INFO - Epoch(train) [1077][25/63] lr: 2.7873e-04 eta: 1:25:41 time: 0.8655 data_time: 0.0445 memory: 14901 loss: 0.8962 loss_prob: 0.4747 loss_thr: 0.3393 loss_db: 0.0822 2022/11/03 01:21:24 - mmengine - INFO - Epoch(train) [1077][30/63] lr: 2.7873e-04 eta: 1:25:35 time: 0.6955 data_time: 0.0438 memory: 14901 loss: 0.7973 loss_prob: 0.3989 loss_thr: 0.3268 loss_db: 0.0716 2022/11/03 01:21:28 - mmengine - INFO - Epoch(train) [1077][35/63] lr: 2.7873e-04 eta: 1:25:35 time: 0.5947 data_time: 0.0098 memory: 14901 loss: 0.8716 loss_prob: 0.4462 loss_thr: 0.3479 loss_db: 0.0776 2022/11/03 01:21:30 - mmengine - INFO - Epoch(train) [1077][40/63] lr: 2.7873e-04 eta: 1:25:28 time: 0.5771 data_time: 0.0137 memory: 14901 loss: 0.9163 loss_prob: 0.4706 loss_thr: 0.3639 loss_db: 0.0818 2022/11/03 01:21:34 - mmengine - INFO - Epoch(train) [1077][45/63] lr: 2.7873e-04 eta: 1:25:28 time: 0.6539 data_time: 0.0112 memory: 14901 loss: 0.8697 loss_prob: 0.4454 loss_thr: 0.3460 loss_db: 0.0782 2022/11/03 01:21:37 - mmengine - INFO - Epoch(train) [1077][50/63] lr: 2.7873e-04 eta: 1:25:22 time: 0.7019 data_time: 0.0213 memory: 14901 loss: 0.9424 loss_prob: 0.5006 loss_thr: 0.3589 loss_db: 0.0830 2022/11/03 01:21:41 - mmengine - INFO - Epoch(train) [1077][55/63] lr: 2.7873e-04 eta: 1:25:22 time: 0.7050 data_time: 0.0234 memory: 14901 loss: 0.9430 loss_prob: 0.4995 loss_thr: 0.3614 loss_db: 0.0821 2022/11/03 01:21:45 - mmengine - INFO - Epoch(train) [1077][60/63] lr: 2.7873e-04 eta: 1:25:15 time: 0.7728 data_time: 0.0100 memory: 14901 loss: 0.8227 loss_prob: 0.4160 loss_thr: 0.3339 loss_db: 0.0727 2022/11/03 01:21:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:21:55 - mmengine - INFO - Epoch(train) [1078][5/63] lr: 2.7669e-04 eta: 1:25:15 time: 1.0850 data_time: 0.2790 memory: 14901 loss: 0.9202 loss_prob: 0.4685 loss_thr: 0.3704 loss_db: 0.0813 2022/11/03 01:21:58 - mmengine - INFO - Epoch(train) [1078][10/63] lr: 2.7669e-04 eta: 1:25:07 time: 1.1752 data_time: 0.2814 memory: 14901 loss: 0.8836 loss_prob: 0.4511 loss_thr: 0.3537 loss_db: 0.0788 2022/11/03 01:22:02 - mmengine - INFO - Epoch(train) [1078][15/63] lr: 2.7669e-04 eta: 1:25:07 time: 0.7008 data_time: 0.0114 memory: 14901 loss: 0.8881 loss_prob: 0.4532 loss_thr: 0.3529 loss_db: 0.0820 2022/11/03 01:22:06 - mmengine - INFO - Epoch(train) [1078][20/63] lr: 2.7669e-04 eta: 1:25:01 time: 0.7893 data_time: 0.0057 memory: 14901 loss: 0.8761 loss_prob: 0.4533 loss_thr: 0.3417 loss_db: 0.0811 2022/11/03 01:22:11 - mmengine - INFO - Epoch(train) [1078][25/63] lr: 2.7669e-04 eta: 1:25:01 time: 0.9085 data_time: 0.0130 memory: 14901 loss: 0.8835 loss_prob: 0.4558 loss_thr: 0.3482 loss_db: 0.0796 2022/11/03 01:22:14 - mmengine - INFO - Epoch(train) [1078][30/63] lr: 2.7669e-04 eta: 1:24:54 time: 0.8210 data_time: 0.0454 memory: 14901 loss: 0.8703 loss_prob: 0.4474 loss_thr: 0.3452 loss_db: 0.0777 2022/11/03 01:22:18 - mmengine - INFO - Epoch(train) [1078][35/63] lr: 2.7669e-04 eta: 1:24:54 time: 0.6836 data_time: 0.0379 memory: 14901 loss: 0.9269 loss_prob: 0.4801 loss_thr: 0.3625 loss_db: 0.0844 2022/11/03 01:22:22 - mmengine - INFO - Epoch(train) [1078][40/63] lr: 2.7669e-04 eta: 1:24:48 time: 0.7353 data_time: 0.0070 memory: 14901 loss: 0.9640 loss_prob: 0.5022 loss_thr: 0.3725 loss_db: 0.0892 2022/11/03 01:22:24 - mmengine - INFO - Epoch(train) [1078][45/63] lr: 2.7669e-04 eta: 1:24:48 time: 0.6643 data_time: 0.0071 memory: 14901 loss: 0.8647 loss_prob: 0.4517 loss_thr: 0.3328 loss_db: 0.0802 2022/11/03 01:22:27 - mmengine - INFO - Epoch(train) [1078][50/63] lr: 2.7669e-04 eta: 1:24:41 time: 0.5486 data_time: 0.0199 memory: 14901 loss: 0.8660 loss_prob: 0.4534 loss_thr: 0.3344 loss_db: 0.0782 2022/11/03 01:22:30 - mmengine - INFO - Epoch(train) [1078][55/63] lr: 2.7669e-04 eta: 1:24:41 time: 0.6226 data_time: 0.0288 memory: 14901 loss: 0.9209 loss_prob: 0.4822 loss_thr: 0.3558 loss_db: 0.0829 2022/11/03 01:22:35 - mmengine - INFO - Epoch(train) [1078][60/63] lr: 2.7669e-04 eta: 1:24:34 time: 0.7800 data_time: 0.0166 memory: 14901 loss: 0.8610 loss_prob: 0.4466 loss_thr: 0.3347 loss_db: 0.0796 2022/11/03 01:22:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:22:45 - mmengine - INFO - Epoch(train) [1079][5/63] lr: 2.7465e-04 eta: 1:24:34 time: 1.1222 data_time: 0.3009 memory: 14901 loss: 0.8454 loss_prob: 0.4299 loss_thr: 0.3400 loss_db: 0.0755 2022/11/03 01:22:49 - mmengine - INFO - Epoch(train) [1079][10/63] lr: 2.7465e-04 eta: 1:24:26 time: 1.2912 data_time: 0.3007 memory: 14901 loss: 0.8585 loss_prob: 0.4513 loss_thr: 0.3309 loss_db: 0.0763 2022/11/03 01:22:52 - mmengine - INFO - Epoch(train) [1079][15/63] lr: 2.7465e-04 eta: 1:24:26 time: 0.7187 data_time: 0.0102 memory: 14901 loss: 0.9267 loss_prob: 0.4913 loss_thr: 0.3507 loss_db: 0.0846 2022/11/03 01:22:55 - mmengine - INFO - Epoch(train) [1079][20/63] lr: 2.7465e-04 eta: 1:24:20 time: 0.6271 data_time: 0.0104 memory: 14901 loss: 0.9722 loss_prob: 0.5071 loss_thr: 0.3766 loss_db: 0.0885 2022/11/03 01:22:59 - mmengine - INFO - Epoch(train) [1079][25/63] lr: 2.7465e-04 eta: 1:24:20 time: 0.6829 data_time: 0.0420 memory: 14901 loss: 0.8938 loss_prob: 0.4669 loss_thr: 0.3456 loss_db: 0.0813 2022/11/03 01:23:01 - mmengine - INFO - Epoch(train) [1079][30/63] lr: 2.7465e-04 eta: 1:24:13 time: 0.6098 data_time: 0.0414 memory: 14901 loss: 0.8935 loss_prob: 0.4610 loss_thr: 0.3515 loss_db: 0.0810 2022/11/03 01:23:04 - mmengine - INFO - Epoch(train) [1079][35/63] lr: 2.7465e-04 eta: 1:24:13 time: 0.5289 data_time: 0.0087 memory: 14901 loss: 0.9324 loss_prob: 0.4768 loss_thr: 0.3722 loss_db: 0.0835 2022/11/03 01:23:07 - mmengine - INFO - Epoch(train) [1079][40/63] lr: 2.7465e-04 eta: 1:24:06 time: 0.5861 data_time: 0.0090 memory: 14901 loss: 0.9129 loss_prob: 0.4760 loss_thr: 0.3516 loss_db: 0.0854 2022/11/03 01:23:10 - mmengine - INFO - Epoch(train) [1079][45/63] lr: 2.7465e-04 eta: 1:24:06 time: 0.6106 data_time: 0.0088 memory: 14901 loss: 0.8920 loss_prob: 0.4677 loss_thr: 0.3398 loss_db: 0.0845 2022/11/03 01:23:13 - mmengine - INFO - Epoch(train) [1079][50/63] lr: 2.7465e-04 eta: 1:24:00 time: 0.6098 data_time: 0.0326 memory: 14901 loss: 0.8419 loss_prob: 0.4361 loss_thr: 0.3288 loss_db: 0.0771 2022/11/03 01:23:16 - mmengine - INFO - Epoch(train) [1079][55/63] lr: 2.7465e-04 eta: 1:24:00 time: 0.5494 data_time: 0.0300 memory: 14901 loss: 0.8342 loss_prob: 0.4333 loss_thr: 0.3262 loss_db: 0.0748 2022/11/03 01:23:20 - mmengine - INFO - Epoch(train) [1079][60/63] lr: 2.7465e-04 eta: 1:23:53 time: 0.6563 data_time: 0.0077 memory: 14901 loss: 0.8499 loss_prob: 0.4408 loss_thr: 0.3335 loss_db: 0.0755 2022/11/03 01:23:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:23:30 - mmengine - INFO - Epoch(train) [1080][5/63] lr: 2.7260e-04 eta: 1:23:53 time: 1.1870 data_time: 0.2291 memory: 14901 loss: 0.9238 loss_prob: 0.4868 loss_thr: 0.3507 loss_db: 0.0863 2022/11/03 01:23:34 - mmengine - INFO - Epoch(train) [1080][10/63] lr: 2.7260e-04 eta: 1:23:45 time: 1.2597 data_time: 0.2261 memory: 14901 loss: 0.8985 loss_prob: 0.4775 loss_thr: 0.3389 loss_db: 0.0821 2022/11/03 01:23:38 - mmengine - INFO - Epoch(train) [1080][15/63] lr: 2.7260e-04 eta: 1:23:45 time: 0.8403 data_time: 0.0063 memory: 14901 loss: 0.8632 loss_prob: 0.4446 loss_thr: 0.3431 loss_db: 0.0755 2022/11/03 01:23:41 - mmengine - INFO - Epoch(train) [1080][20/63] lr: 2.7260e-04 eta: 1:23:38 time: 0.6220 data_time: 0.0078 memory: 14901 loss: 0.8440 loss_prob: 0.4249 loss_thr: 0.3445 loss_db: 0.0746 2022/11/03 01:23:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:23:44 - mmengine - INFO - Epoch(train) [1080][25/63] lr: 2.7260e-04 eta: 1:23:38 time: 0.5505 data_time: 0.0179 memory: 14901 loss: 0.8661 loss_prob: 0.4398 loss_thr: 0.3485 loss_db: 0.0778 2022/11/03 01:23:47 - mmengine - INFO - Epoch(train) [1080][30/63] lr: 2.7260e-04 eta: 1:23:32 time: 0.6427 data_time: 0.0388 memory: 14901 loss: 0.8614 loss_prob: 0.4392 loss_thr: 0.3453 loss_db: 0.0769 2022/11/03 01:23:50 - mmengine - INFO - Epoch(train) [1080][35/63] lr: 2.7260e-04 eta: 1:23:32 time: 0.6478 data_time: 0.0285 memory: 14901 loss: 0.8490 loss_prob: 0.4386 loss_thr: 0.3354 loss_db: 0.0751 2022/11/03 01:23:54 - mmengine - INFO - Epoch(train) [1080][40/63] lr: 2.7260e-04 eta: 1:23:25 time: 0.6602 data_time: 0.0061 memory: 14901 loss: 0.8771 loss_prob: 0.4634 loss_thr: 0.3349 loss_db: 0.0788 2022/11/03 01:23:56 - mmengine - INFO - Epoch(train) [1080][45/63] lr: 2.7260e-04 eta: 1:23:25 time: 0.6244 data_time: 0.0076 memory: 14901 loss: 0.9209 loss_prob: 0.4910 loss_thr: 0.3456 loss_db: 0.0842 2022/11/03 01:24:00 - mmengine - INFO - Epoch(train) [1080][50/63] lr: 2.7260e-04 eta: 1:23:18 time: 0.6066 data_time: 0.0189 memory: 14901 loss: 0.8804 loss_prob: 0.4558 loss_thr: 0.3454 loss_db: 0.0792 2022/11/03 01:24:04 - mmengine - INFO - Epoch(train) [1080][55/63] lr: 2.7260e-04 eta: 1:23:18 time: 0.7494 data_time: 0.0251 memory: 14901 loss: 0.9009 loss_prob: 0.4587 loss_thr: 0.3610 loss_db: 0.0812 2022/11/03 01:24:07 - mmengine - INFO - Epoch(train) [1080][60/63] lr: 2.7260e-04 eta: 1:23:12 time: 0.7540 data_time: 0.0137 memory: 14901 loss: 0.9031 loss_prob: 0.4623 loss_thr: 0.3611 loss_db: 0.0797 2022/11/03 01:24:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:24:09 - mmengine - INFO - Saving checkpoint at 1080 epochs 2022/11/03 01:24:13 - mmengine - INFO - Epoch(val) [1080][5/500] eta: 1:23:12 time: 0.0470 data_time: 0.0058 memory: 14901 2022/11/03 01:24:13 - mmengine - INFO - Epoch(val) [1080][10/500] eta: 0:00:23 time: 0.0482 data_time: 0.0059 memory: 1008 2022/11/03 01:24:13 - mmengine - INFO - Epoch(val) [1080][15/500] eta: 0:00:23 time: 0.0409 data_time: 0.0028 memory: 1008 2022/11/03 01:24:13 - mmengine - INFO - Epoch(val) [1080][20/500] eta: 0:00:19 time: 0.0414 data_time: 0.0025 memory: 1008 2022/11/03 01:24:13 - mmengine - INFO - Epoch(val) [1080][25/500] eta: 0:00:19 time: 0.0400 data_time: 0.0032 memory: 1008 2022/11/03 01:24:14 - mmengine - INFO - Epoch(val) [1080][30/500] eta: 0:00:20 time: 0.0440 data_time: 0.0032 memory: 1008 2022/11/03 01:24:14 - mmengine - INFO - Epoch(val) [1080][35/500] eta: 0:00:20 time: 0.0458 data_time: 0.0029 memory: 1008 2022/11/03 01:24:14 - mmengine - INFO - Epoch(val) [1080][40/500] eta: 0:00:22 time: 0.0482 data_time: 0.0035 memory: 1008 2022/11/03 01:24:14 - mmengine - INFO - Epoch(val) [1080][45/500] eta: 0:00:22 time: 0.0492 data_time: 0.0038 memory: 1008 2022/11/03 01:24:15 - mmengine - INFO - Epoch(val) [1080][50/500] eta: 0:00:21 time: 0.0470 data_time: 0.0037 memory: 1008 2022/11/03 01:24:15 - mmengine - INFO - Epoch(val) [1080][55/500] eta: 0:00:21 time: 0.0475 data_time: 0.0032 memory: 1008 2022/11/03 01:24:15 - mmengine - INFO - Epoch(val) [1080][60/500] eta: 0:00:18 time: 0.0415 data_time: 0.0027 memory: 1008 2022/11/03 01:24:15 - mmengine - INFO - Epoch(val) [1080][65/500] eta: 0:00:18 time: 0.0426 data_time: 0.0027 memory: 1008 2022/11/03 01:24:16 - mmengine - INFO - Epoch(val) [1080][70/500] eta: 0:00:19 time: 0.0451 data_time: 0.0027 memory: 1008 2022/11/03 01:24:16 - mmengine - INFO - Epoch(val) [1080][75/500] eta: 0:00:19 time: 0.0408 data_time: 0.0027 memory: 1008 2022/11/03 01:24:16 - mmengine - INFO - Epoch(val) [1080][80/500] eta: 0:00:16 time: 0.0384 data_time: 0.0027 memory: 1008 2022/11/03 01:24:16 - mmengine - INFO - Epoch(val) [1080][85/500] eta: 0:00:16 time: 0.0371 data_time: 0.0027 memory: 1008 2022/11/03 01:24:16 - mmengine - INFO - Epoch(val) [1080][90/500] eta: 0:00:16 time: 0.0409 data_time: 0.0029 memory: 1008 2022/11/03 01:24:17 - mmengine - INFO - Epoch(val) [1080][95/500] eta: 0:00:16 time: 0.0456 data_time: 0.0037 memory: 1008 2022/11/03 01:24:17 - mmengine - INFO - Epoch(val) [1080][100/500] eta: 0:00:16 time: 0.0415 data_time: 0.0036 memory: 1008 2022/11/03 01:24:17 - mmengine - INFO - Epoch(val) [1080][105/500] eta: 0:00:16 time: 0.0379 data_time: 0.0029 memory: 1008 2022/11/03 01:24:17 - mmengine - INFO - Epoch(val) [1080][110/500] eta: 0:00:14 time: 0.0368 data_time: 0.0024 memory: 1008 2022/11/03 01:24:17 - mmengine - INFO - Epoch(val) [1080][115/500] eta: 0:00:14 time: 0.0369 data_time: 0.0021 memory: 1008 2022/11/03 01:24:18 - mmengine - INFO - Epoch(val) [1080][120/500] eta: 0:00:14 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/03 01:24:18 - mmengine - INFO - Epoch(val) [1080][125/500] eta: 0:00:14 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/03 01:24:18 - mmengine - INFO - Epoch(val) [1080][130/500] eta: 0:00:13 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/03 01:24:18 - mmengine - INFO - Epoch(val) [1080][135/500] eta: 0:00:13 time: 0.0367 data_time: 0.0023 memory: 1008 2022/11/03 01:24:18 - mmengine - INFO - Epoch(val) [1080][140/500] eta: 0:00:13 time: 0.0382 data_time: 0.0025 memory: 1008 2022/11/03 01:24:19 - mmengine - INFO - Epoch(val) [1080][145/500] eta: 0:00:13 time: 0.0429 data_time: 0.0026 memory: 1008 2022/11/03 01:24:19 - mmengine - INFO - Epoch(val) [1080][150/500] eta: 0:00:14 time: 0.0417 data_time: 0.0026 memory: 1008 2022/11/03 01:24:19 - mmengine - INFO - Epoch(val) [1080][155/500] eta: 0:00:14 time: 0.0431 data_time: 0.0030 memory: 1008 2022/11/03 01:24:19 - mmengine - INFO - Epoch(val) [1080][160/500] eta: 0:00:14 time: 0.0432 data_time: 0.0028 memory: 1008 2022/11/03 01:24:19 - mmengine - INFO - Epoch(val) [1080][165/500] eta: 0:00:14 time: 0.0384 data_time: 0.0023 memory: 1008 2022/11/03 01:24:20 - mmengine - INFO - Epoch(val) [1080][170/500] eta: 0:00:12 time: 0.0383 data_time: 0.0024 memory: 1008 2022/11/03 01:24:20 - mmengine - INFO - Epoch(val) [1080][175/500] eta: 0:00:12 time: 0.0367 data_time: 0.0024 memory: 1008 2022/11/03 01:24:20 - mmengine - INFO - Epoch(val) [1080][180/500] eta: 0:00:11 time: 0.0366 data_time: 0.0024 memory: 1008 2022/11/03 01:24:20 - mmengine - INFO - Epoch(val) [1080][185/500] eta: 0:00:11 time: 0.0390 data_time: 0.0028 memory: 1008 2022/11/03 01:24:20 - mmengine - INFO - Epoch(val) [1080][190/500] eta: 0:00:12 time: 0.0399 data_time: 0.0027 memory: 1008 2022/11/03 01:24:20 - mmengine - INFO - Epoch(val) [1080][195/500] eta: 0:00:12 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/03 01:24:21 - mmengine - INFO - Epoch(val) [1080][200/500] eta: 0:00:13 time: 0.0441 data_time: 0.0027 memory: 1008 2022/11/03 01:24:21 - mmengine - INFO - Epoch(val) [1080][205/500] eta: 0:00:13 time: 0.0411 data_time: 0.0022 memory: 1008 2022/11/03 01:24:21 - mmengine - INFO - Epoch(val) [1080][210/500] eta: 0:00:09 time: 0.0338 data_time: 0.0018 memory: 1008 2022/11/03 01:24:21 - mmengine - INFO - Epoch(val) [1080][215/500] eta: 0:00:09 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/03 01:24:21 - mmengine - INFO - Epoch(val) [1080][220/500] eta: 0:00:10 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/03 01:24:22 - mmengine - INFO - Epoch(val) [1080][225/500] eta: 0:00:10 time: 0.0372 data_time: 0.0023 memory: 1008 2022/11/03 01:24:22 - mmengine - INFO - Epoch(val) [1080][230/500] eta: 0:00:09 time: 0.0359 data_time: 0.0024 memory: 1008 2022/11/03 01:24:22 - mmengine - INFO - Epoch(val) [1080][235/500] eta: 0:00:09 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/03 01:24:22 - mmengine - INFO - Epoch(val) [1080][240/500] eta: 0:00:10 time: 0.0410 data_time: 0.0024 memory: 1008 2022/11/03 01:24:22 - mmengine - INFO - Epoch(val) [1080][245/500] eta: 0:00:10 time: 0.0357 data_time: 0.0022 memory: 1008 2022/11/03 01:24:23 - mmengine - INFO - Epoch(val) [1080][250/500] eta: 0:00:09 time: 0.0371 data_time: 0.0024 memory: 1008 2022/11/03 01:24:23 - mmengine - INFO - Epoch(val) [1080][255/500] eta: 0:00:09 time: 0.0385 data_time: 0.0023 memory: 1008 2022/11/03 01:24:23 - mmengine - INFO - Epoch(val) [1080][260/500] eta: 0:00:08 time: 0.0370 data_time: 0.0023 memory: 1008 2022/11/03 01:24:23 - mmengine - INFO - Epoch(val) [1080][265/500] eta: 0:00:08 time: 0.0355 data_time: 0.0022 memory: 1008 2022/11/03 01:24:23 - mmengine - INFO - Epoch(val) [1080][270/500] eta: 0:00:08 time: 0.0360 data_time: 0.0024 memory: 1008 2022/11/03 01:24:24 - mmengine - INFO - Epoch(val) [1080][275/500] eta: 0:00:08 time: 0.0358 data_time: 0.0024 memory: 1008 2022/11/03 01:24:24 - mmengine - INFO - Epoch(val) [1080][280/500] eta: 0:00:08 time: 0.0383 data_time: 0.0024 memory: 1008 2022/11/03 01:24:24 - mmengine - INFO - Epoch(val) [1080][285/500] eta: 0:00:08 time: 0.0380 data_time: 0.0024 memory: 1008 2022/11/03 01:24:24 - mmengine - INFO - Epoch(val) [1080][290/500] eta: 0:00:07 time: 0.0378 data_time: 0.0022 memory: 1008 2022/11/03 01:24:24 - mmengine - INFO - Epoch(val) [1080][295/500] eta: 0:00:07 time: 0.0426 data_time: 0.0024 memory: 1008 2022/11/03 01:24:25 - mmengine - INFO - Epoch(val) [1080][300/500] eta: 0:00:07 time: 0.0398 data_time: 0.0024 memory: 1008 2022/11/03 01:24:25 - mmengine - INFO - Epoch(val) [1080][305/500] eta: 0:00:07 time: 0.0362 data_time: 0.0021 memory: 1008 2022/11/03 01:24:25 - mmengine - INFO - Epoch(val) [1080][310/500] eta: 0:00:06 time: 0.0359 data_time: 0.0022 memory: 1008 2022/11/03 01:24:25 - mmengine - INFO - Epoch(val) [1080][315/500] eta: 0:00:06 time: 0.0391 data_time: 0.0023 memory: 1008 2022/11/03 01:24:25 - mmengine - INFO - Epoch(val) [1080][320/500] eta: 0:00:07 time: 0.0411 data_time: 0.0025 memory: 1008 2022/11/03 01:24:26 - mmengine - INFO - Epoch(val) [1080][325/500] eta: 0:00:07 time: 0.0497 data_time: 0.0026 memory: 1008 2022/11/03 01:24:26 - mmengine - INFO - Epoch(val) [1080][330/500] eta: 0:00:08 time: 0.0478 data_time: 0.0024 memory: 1008 2022/11/03 01:24:26 - mmengine - INFO - Epoch(val) [1080][335/500] eta: 0:00:08 time: 0.0349 data_time: 0.0022 memory: 1008 2022/11/03 01:24:26 - mmengine - INFO - Epoch(val) [1080][340/500] eta: 0:00:07 time: 0.0446 data_time: 0.0022 memory: 1008 2022/11/03 01:24:26 - mmengine - INFO - Epoch(val) [1080][345/500] eta: 0:00:07 time: 0.0462 data_time: 0.0022 memory: 1008 2022/11/03 01:24:27 - mmengine - INFO - Epoch(val) [1080][350/500] eta: 0:00:06 time: 0.0446 data_time: 0.0023 memory: 1008 2022/11/03 01:24:27 - mmengine - INFO - Epoch(val) [1080][355/500] eta: 0:00:06 time: 0.0438 data_time: 0.0024 memory: 1008 2022/11/03 01:24:27 - mmengine - INFO - Epoch(val) [1080][360/500] eta: 0:00:05 time: 0.0366 data_time: 0.0024 memory: 1008 2022/11/03 01:24:27 - mmengine - INFO - Epoch(val) [1080][365/500] eta: 0:00:05 time: 0.0375 data_time: 0.0023 memory: 1008 2022/11/03 01:24:27 - mmengine - INFO - Epoch(val) [1080][370/500] eta: 0:00:05 time: 0.0389 data_time: 0.0024 memory: 1008 2022/11/03 01:24:28 - mmengine - INFO - Epoch(val) [1080][375/500] eta: 0:00:05 time: 0.0378 data_time: 0.0024 memory: 1008 2022/11/03 01:24:28 - mmengine - INFO - Epoch(val) [1080][380/500] eta: 0:00:04 time: 0.0376 data_time: 0.0021 memory: 1008 2022/11/03 01:24:28 - mmengine - INFO - Epoch(val) [1080][385/500] eta: 0:00:04 time: 0.0386 data_time: 0.0022 memory: 1008 2022/11/03 01:24:28 - mmengine - INFO - Epoch(val) [1080][390/500] eta: 0:00:04 time: 0.0368 data_time: 0.0022 memory: 1008 2022/11/03 01:24:28 - mmengine - INFO - Epoch(val) [1080][395/500] eta: 0:00:04 time: 0.0361 data_time: 0.0022 memory: 1008 2022/11/03 01:24:29 - mmengine - INFO - Epoch(val) [1080][400/500] eta: 0:00:03 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/03 01:24:29 - mmengine - INFO - Epoch(val) [1080][405/500] eta: 0:00:03 time: 0.0366 data_time: 0.0023 memory: 1008 2022/11/03 01:24:29 - mmengine - INFO - Epoch(val) [1080][410/500] eta: 0:00:03 time: 0.0374 data_time: 0.0021 memory: 1008 2022/11/03 01:24:29 - mmengine - INFO - Epoch(val) [1080][415/500] eta: 0:00:03 time: 0.0396 data_time: 0.0024 memory: 1008 2022/11/03 01:24:29 - mmengine - INFO - Epoch(val) [1080][420/500] eta: 0:00:02 time: 0.0368 data_time: 0.0024 memory: 1008 2022/11/03 01:24:29 - mmengine - INFO - Epoch(val) [1080][425/500] eta: 0:00:02 time: 0.0351 data_time: 0.0021 memory: 1008 2022/11/03 01:24:30 - mmengine - INFO - Epoch(val) [1080][430/500] eta: 0:00:02 time: 0.0373 data_time: 0.0021 memory: 1008 2022/11/03 01:24:30 - mmengine - INFO - Epoch(val) [1080][435/500] eta: 0:00:02 time: 0.0363 data_time: 0.0023 memory: 1008 2022/11/03 01:24:30 - mmengine - INFO - Epoch(val) [1080][440/500] eta: 0:00:02 time: 0.0365 data_time: 0.0022 memory: 1008 2022/11/03 01:24:30 - mmengine - INFO - Epoch(val) [1080][445/500] eta: 0:00:02 time: 0.0375 data_time: 0.0020 memory: 1008 2022/11/03 01:24:30 - mmengine - INFO - Epoch(val) [1080][450/500] eta: 0:00:01 time: 0.0376 data_time: 0.0021 memory: 1008 2022/11/03 01:24:31 - mmengine - INFO - Epoch(val) [1080][455/500] eta: 0:00:01 time: 0.0385 data_time: 0.0022 memory: 1008 2022/11/03 01:24:31 - mmengine - INFO - Epoch(val) [1080][460/500] eta: 0:00:01 time: 0.0388 data_time: 0.0023 memory: 1008 2022/11/03 01:24:31 - mmengine - INFO - Epoch(val) [1080][465/500] eta: 0:00:01 time: 0.0368 data_time: 0.0022 memory: 1008 2022/11/03 01:24:31 - mmengine - INFO - Epoch(val) [1080][470/500] eta: 0:00:01 time: 0.0356 data_time: 0.0024 memory: 1008 2022/11/03 01:24:31 - mmengine - INFO - Epoch(val) [1080][475/500] eta: 0:00:01 time: 0.0357 data_time: 0.0024 memory: 1008 2022/11/03 01:24:32 - mmengine - INFO - Epoch(val) [1080][480/500] eta: 0:00:00 time: 0.0371 data_time: 0.0021 memory: 1008 2022/11/03 01:24:32 - mmengine - INFO - Epoch(val) [1080][485/500] eta: 0:00:00 time: 0.0364 data_time: 0.0021 memory: 1008 2022/11/03 01:24:32 - mmengine - INFO - Epoch(val) [1080][490/500] eta: 0:00:00 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/03 01:24:32 - mmengine - INFO - Epoch(val) [1080][495/500] eta: 0:00:00 time: 0.0409 data_time: 0.0027 memory: 1008 2022/11/03 01:24:32 - mmengine - INFO - Epoch(val) [1080][500/500] eta: 0:00:00 time: 0.0377 data_time: 0.0027 memory: 1008 2022/11/03 01:24:32 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8373, precision: 0.7512, hmean: 0.7919 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8373, precision: 0.7981, hmean: 0.8172 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8368, precision: 0.8257, hmean: 0.8312 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8334, precision: 0.8444, hmean: 0.8389 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8209, precision: 0.8712, hmean: 0.8453 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7386, precision: 0.9115, hmean: 0.8160 2022/11/03 01:24:32 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2152, precision: 0.9613, hmean: 0.3517 2022/11/03 01:24:32 - mmengine - INFO - Epoch(val) [1080][500/500] icdar/precision: 0.8712 icdar/recall: 0.8209 icdar/hmean: 0.8453 2022/11/03 01:24:38 - mmengine - INFO - Epoch(train) [1081][5/63] lr: 2.7056e-04 eta: 0:00:00 time: 0.8985 data_time: 0.2703 memory: 14901 loss: 0.9520 loss_prob: 0.4979 loss_thr: 0.3696 loss_db: 0.0844 2022/11/03 01:24:41 - mmengine - INFO - Epoch(train) [1081][10/63] lr: 2.7056e-04 eta: 1:23:03 time: 0.8635 data_time: 0.2705 memory: 14901 loss: 0.9594 loss_prob: 0.5029 loss_thr: 0.3716 loss_db: 0.0849 2022/11/03 01:24:44 - mmengine - INFO - Epoch(train) [1081][15/63] lr: 2.7056e-04 eta: 1:23:03 time: 0.5474 data_time: 0.0054 memory: 14901 loss: 0.8949 loss_prob: 0.4629 loss_thr: 0.3510 loss_db: 0.0809 2022/11/03 01:24:46 - mmengine - INFO - Epoch(train) [1081][20/63] lr: 2.7056e-04 eta: 1:22:57 time: 0.5404 data_time: 0.0125 memory: 14901 loss: 0.8203 loss_prob: 0.4207 loss_thr: 0.3252 loss_db: 0.0744 2022/11/03 01:24:49 - mmengine - INFO - Epoch(train) [1081][25/63] lr: 2.7056e-04 eta: 1:22:57 time: 0.5477 data_time: 0.0526 memory: 14901 loss: 0.8161 loss_prob: 0.4158 loss_thr: 0.3268 loss_db: 0.0736 2022/11/03 01:24:52 - mmengine - INFO - Epoch(train) [1081][30/63] lr: 2.7056e-04 eta: 1:22:50 time: 0.5738 data_time: 0.0453 memory: 14901 loss: 0.8408 loss_prob: 0.4296 loss_thr: 0.3355 loss_db: 0.0757 2022/11/03 01:24:56 - mmengine - INFO - Epoch(train) [1081][35/63] lr: 2.7056e-04 eta: 1:22:50 time: 0.6525 data_time: 0.0082 memory: 14901 loss: 0.8899 loss_prob: 0.4652 loss_thr: 0.3444 loss_db: 0.0803 2022/11/03 01:24:59 - mmengine - INFO - Epoch(train) [1081][40/63] lr: 2.7056e-04 eta: 1:22:43 time: 0.7346 data_time: 0.0079 memory: 14901 loss: 0.9457 loss_prob: 0.4942 loss_thr: 0.3657 loss_db: 0.0859 2022/11/03 01:25:03 - mmengine - INFO - Epoch(train) [1081][45/63] lr: 2.7056e-04 eta: 1:22:43 time: 0.6694 data_time: 0.0064 memory: 14901 loss: 0.8997 loss_prob: 0.4586 loss_thr: 0.3591 loss_db: 0.0820 2022/11/03 01:25:06 - mmengine - INFO - Epoch(train) [1081][50/63] lr: 2.7056e-04 eta: 1:22:37 time: 0.6965 data_time: 0.0289 memory: 14901 loss: 0.8848 loss_prob: 0.4543 loss_thr: 0.3508 loss_db: 0.0797 2022/11/03 01:25:10 - mmengine - INFO - Epoch(train) [1081][55/63] lr: 2.7056e-04 eta: 1:22:37 time: 0.7740 data_time: 0.0282 memory: 14901 loss: 0.9229 loss_prob: 0.4815 loss_thr: 0.3583 loss_db: 0.0830 2022/11/03 01:25:14 - mmengine - INFO - Epoch(train) [1081][60/63] lr: 2.7056e-04 eta: 1:22:30 time: 0.7894 data_time: 0.0074 memory: 14901 loss: 0.9121 loss_prob: 0.4726 loss_thr: 0.3570 loss_db: 0.0826 2022/11/03 01:25:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:25:24 - mmengine - INFO - Epoch(train) [1082][5/63] lr: 2.6851e-04 eta: 1:22:30 time: 1.0818 data_time: 0.2549 memory: 14901 loss: 0.8321 loss_prob: 0.4306 loss_thr: 0.3269 loss_db: 0.0746 2022/11/03 01:25:28 - mmengine - INFO - Epoch(train) [1082][10/63] lr: 2.6851e-04 eta: 1:22:22 time: 1.1837 data_time: 0.2710 memory: 14901 loss: 0.8333 loss_prob: 0.4221 loss_thr: 0.3370 loss_db: 0.0743 2022/11/03 01:25:31 - mmengine - INFO - Epoch(train) [1082][15/63] lr: 2.6851e-04 eta: 1:22:22 time: 0.6743 data_time: 0.0250 memory: 14901 loss: 0.8516 loss_prob: 0.4288 loss_thr: 0.3466 loss_db: 0.0761 2022/11/03 01:25:33 - mmengine - INFO - Epoch(train) [1082][20/63] lr: 2.6851e-04 eta: 1:22:15 time: 0.5449 data_time: 0.0097 memory: 14901 loss: 0.8105 loss_prob: 0.4173 loss_thr: 0.3197 loss_db: 0.0735 2022/11/03 01:25:37 - mmengine - INFO - Epoch(train) [1082][25/63] lr: 2.6851e-04 eta: 1:22:15 time: 0.6661 data_time: 0.0447 memory: 14901 loss: 0.8289 loss_prob: 0.4302 loss_thr: 0.3235 loss_db: 0.0752 2022/11/03 01:25:40 - mmengine - INFO - Epoch(train) [1082][30/63] lr: 2.6851e-04 eta: 1:22:09 time: 0.6874 data_time: 0.0561 memory: 14901 loss: 0.8692 loss_prob: 0.4481 loss_thr: 0.3420 loss_db: 0.0791 2022/11/03 01:25:43 - mmengine - INFO - Epoch(train) [1082][35/63] lr: 2.6851e-04 eta: 1:22:09 time: 0.5648 data_time: 0.0202 memory: 14901 loss: 0.8747 loss_prob: 0.4488 loss_thr: 0.3460 loss_db: 0.0799 2022/11/03 01:25:46 - mmengine - INFO - Epoch(train) [1082][40/63] lr: 2.6851e-04 eta: 1:22:02 time: 0.5265 data_time: 0.0079 memory: 14901 loss: 0.8945 loss_prob: 0.4629 loss_thr: 0.3509 loss_db: 0.0807 2022/11/03 01:25:49 - mmengine - INFO - Epoch(train) [1082][45/63] lr: 2.6851e-04 eta: 1:22:02 time: 0.6294 data_time: 0.0055 memory: 14901 loss: 0.8809 loss_prob: 0.4601 loss_thr: 0.3415 loss_db: 0.0793 2022/11/03 01:25:53 - mmengine - INFO - Epoch(train) [1082][50/63] lr: 2.6851e-04 eta: 1:21:56 time: 0.7627 data_time: 0.0191 memory: 14901 loss: 0.8852 loss_prob: 0.4585 loss_thr: 0.3478 loss_db: 0.0789 2022/11/03 01:25:56 - mmengine - INFO - Epoch(train) [1082][55/63] lr: 2.6851e-04 eta: 1:21:56 time: 0.7081 data_time: 0.0243 memory: 14901 loss: 0.8639 loss_prob: 0.4464 loss_thr: 0.3406 loss_db: 0.0769 2022/11/03 01:25:59 - mmengine - INFO - Epoch(train) [1082][60/63] lr: 2.6851e-04 eta: 1:21:49 time: 0.5890 data_time: 0.0128 memory: 14901 loss: 0.8159 loss_prob: 0.4228 loss_thr: 0.3186 loss_db: 0.0746 2022/11/03 01:26:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:26:08 - mmengine - INFO - Epoch(train) [1083][5/63] lr: 2.6647e-04 eta: 1:21:49 time: 1.0324 data_time: 0.3094 memory: 14901 loss: 0.8884 loss_prob: 0.4633 loss_thr: 0.3465 loss_db: 0.0786 2022/11/03 01:26:12 - mmengine - INFO - Epoch(train) [1083][10/63] lr: 2.6647e-04 eta: 1:21:41 time: 1.1075 data_time: 0.3097 memory: 14901 loss: 0.9196 loss_prob: 0.4761 loss_thr: 0.3624 loss_db: 0.0811 2022/11/03 01:26:16 - mmengine - INFO - Epoch(train) [1083][15/63] lr: 2.6647e-04 eta: 1:21:41 time: 0.7380 data_time: 0.0105 memory: 14901 loss: 0.8691 loss_prob: 0.4458 loss_thr: 0.3454 loss_db: 0.0778 2022/11/03 01:26:19 - mmengine - INFO - Epoch(train) [1083][20/63] lr: 2.6647e-04 eta: 1:21:34 time: 0.7098 data_time: 0.0089 memory: 14901 loss: 0.8590 loss_prob: 0.4426 loss_thr: 0.3374 loss_db: 0.0791 2022/11/03 01:26:22 - mmengine - INFO - Epoch(train) [1083][25/63] lr: 2.6647e-04 eta: 1:21:34 time: 0.5699 data_time: 0.0214 memory: 14901 loss: 0.8065 loss_prob: 0.4071 loss_thr: 0.3253 loss_db: 0.0741 2022/11/03 01:26:24 - mmengine - INFO - Epoch(train) [1083][30/63] lr: 2.6647e-04 eta: 1:21:27 time: 0.5420 data_time: 0.0403 memory: 14901 loss: 0.7952 loss_prob: 0.3962 loss_thr: 0.3284 loss_db: 0.0706 2022/11/03 01:26:28 - mmengine - INFO - Epoch(train) [1083][35/63] lr: 2.6647e-04 eta: 1:21:27 time: 0.6008 data_time: 0.0253 memory: 14901 loss: 0.8555 loss_prob: 0.4487 loss_thr: 0.3302 loss_db: 0.0767 2022/11/03 01:26:31 - mmengine - INFO - Epoch(train) [1083][40/63] lr: 2.6647e-04 eta: 1:21:21 time: 0.6492 data_time: 0.0055 memory: 14901 loss: 0.9490 loss_prob: 0.5029 loss_thr: 0.3601 loss_db: 0.0860 2022/11/03 01:26:34 - mmengine - INFO - Epoch(train) [1083][45/63] lr: 2.6647e-04 eta: 1:21:21 time: 0.6137 data_time: 0.0058 memory: 14901 loss: 0.9784 loss_prob: 0.5053 loss_thr: 0.3838 loss_db: 0.0893 2022/11/03 01:26:37 - mmengine - INFO - Epoch(train) [1083][50/63] lr: 2.6647e-04 eta: 1:21:14 time: 0.6114 data_time: 0.0216 memory: 14901 loss: 0.8827 loss_prob: 0.4506 loss_thr: 0.3525 loss_db: 0.0795 2022/11/03 01:26:39 - mmengine - INFO - Epoch(train) [1083][55/63] lr: 2.6647e-04 eta: 1:21:14 time: 0.5796 data_time: 0.0273 memory: 14901 loss: 0.8753 loss_prob: 0.4539 loss_thr: 0.3439 loss_db: 0.0775 2022/11/03 01:26:43 - mmengine - INFO - Epoch(train) [1083][60/63] lr: 2.6647e-04 eta: 1:21:07 time: 0.6467 data_time: 0.0115 memory: 14901 loss: 0.8963 loss_prob: 0.4647 loss_thr: 0.3513 loss_db: 0.0803 2022/11/03 01:26:45 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:26:51 - mmengine - INFO - Epoch(train) [1084][5/63] lr: 2.6442e-04 eta: 1:21:07 time: 0.9348 data_time: 0.3010 memory: 14901 loss: 0.9068 loss_prob: 0.4625 loss_thr: 0.3629 loss_db: 0.0814 2022/11/03 01:26:56 - mmengine - INFO - Epoch(train) [1084][10/63] lr: 2.6442e-04 eta: 1:20:59 time: 1.0986 data_time: 0.3023 memory: 14901 loss: 0.8737 loss_prob: 0.4478 loss_thr: 0.3477 loss_db: 0.0782 2022/11/03 01:27:00 - mmengine - INFO - Epoch(train) [1084][15/63] lr: 2.6442e-04 eta: 1:20:59 time: 0.8219 data_time: 0.0089 memory: 14901 loss: 0.8844 loss_prob: 0.4574 loss_thr: 0.3479 loss_db: 0.0791 2022/11/03 01:27:05 - mmengine - INFO - Epoch(train) [1084][20/63] lr: 2.6442e-04 eta: 1:20:53 time: 0.9033 data_time: 0.0085 memory: 14901 loss: 0.8583 loss_prob: 0.4386 loss_thr: 0.3428 loss_db: 0.0770 2022/11/03 01:27:09 - mmengine - INFO - Epoch(train) [1084][25/63] lr: 2.6442e-04 eta: 1:20:53 time: 0.8995 data_time: 0.0173 memory: 14901 loss: 0.8559 loss_prob: 0.4379 loss_thr: 0.3403 loss_db: 0.0777 2022/11/03 01:27:12 - mmengine - INFO - Epoch(train) [1084][30/63] lr: 2.6442e-04 eta: 1:20:46 time: 0.7618 data_time: 0.0338 memory: 14901 loss: 0.8799 loss_prob: 0.4535 loss_thr: 0.3467 loss_db: 0.0797 2022/11/03 01:27:16 - mmengine - INFO - Epoch(train) [1084][35/63] lr: 2.6442e-04 eta: 1:20:46 time: 0.7091 data_time: 0.0263 memory: 14901 loss: 0.7915 loss_prob: 0.3954 loss_thr: 0.3265 loss_db: 0.0696 2022/11/03 01:27:18 - mmengine - INFO - Epoch(train) [1084][40/63] lr: 2.6442e-04 eta: 1:20:40 time: 0.6094 data_time: 0.0164 memory: 14901 loss: 0.8157 loss_prob: 0.4096 loss_thr: 0.3342 loss_db: 0.0718 2022/11/03 01:27:21 - mmengine - INFO - Epoch(train) [1084][45/63] lr: 2.6442e-04 eta: 1:20:40 time: 0.5211 data_time: 0.0132 memory: 14901 loss: 0.8966 loss_prob: 0.4601 loss_thr: 0.3557 loss_db: 0.0807 2022/11/03 01:27:24 - mmengine - INFO - Epoch(train) [1084][50/63] lr: 2.6442e-04 eta: 1:20:33 time: 0.5540 data_time: 0.0214 memory: 14901 loss: 0.8830 loss_prob: 0.4524 loss_thr: 0.3510 loss_db: 0.0796 2022/11/03 01:27:27 - mmengine - INFO - Epoch(train) [1084][55/63] lr: 2.6442e-04 eta: 1:20:33 time: 0.5903 data_time: 0.0234 memory: 14901 loss: 0.8567 loss_prob: 0.4359 loss_thr: 0.3449 loss_db: 0.0760 2022/11/03 01:27:30 - mmengine - INFO - Epoch(train) [1084][60/63] lr: 2.6442e-04 eta: 1:20:26 time: 0.5872 data_time: 0.0097 memory: 14901 loss: 0.8820 loss_prob: 0.4543 loss_thr: 0.3486 loss_db: 0.0791 2022/11/03 01:27:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:27:38 - mmengine - INFO - Epoch(train) [1085][5/63] lr: 2.6236e-04 eta: 1:20:26 time: 0.9581 data_time: 0.2498 memory: 14901 loss: 0.8913 loss_prob: 0.4623 loss_thr: 0.3479 loss_db: 0.0811 2022/11/03 01:27:43 - mmengine - INFO - Epoch(train) [1085][10/63] lr: 2.6236e-04 eta: 1:20:18 time: 1.1862 data_time: 0.2583 memory: 14901 loss: 0.8093 loss_prob: 0.4135 loss_thr: 0.3236 loss_db: 0.0722 2022/11/03 01:27:48 - mmengine - INFO - Epoch(train) [1085][15/63] lr: 2.6236e-04 eta: 1:20:18 time: 1.0195 data_time: 0.0158 memory: 14901 loss: 0.8337 loss_prob: 0.4340 loss_thr: 0.3242 loss_db: 0.0755 2022/11/03 01:27:51 - mmengine - INFO - Epoch(train) [1085][20/63] lr: 2.6236e-04 eta: 1:20:12 time: 0.8423 data_time: 0.0059 memory: 14901 loss: 0.8413 loss_prob: 0.4353 loss_thr: 0.3294 loss_db: 0.0765 2022/11/03 01:27:54 - mmengine - INFO - Epoch(train) [1085][25/63] lr: 2.6236e-04 eta: 1:20:12 time: 0.5911 data_time: 0.0209 memory: 14901 loss: 0.8656 loss_prob: 0.4475 loss_thr: 0.3396 loss_db: 0.0786 2022/11/03 01:27:58 - mmengine - INFO - Epoch(train) [1085][30/63] lr: 2.6236e-04 eta: 1:20:05 time: 0.7028 data_time: 0.0396 memory: 14901 loss: 0.9473 loss_prob: 0.4944 loss_thr: 0.3655 loss_db: 0.0874 2022/11/03 01:28:01 - mmengine - INFO - Epoch(train) [1085][35/63] lr: 2.6236e-04 eta: 1:20:05 time: 0.6988 data_time: 0.0294 memory: 14901 loss: 0.9034 loss_prob: 0.4659 loss_thr: 0.3558 loss_db: 0.0818 2022/11/03 01:28:05 - mmengine - INFO - Epoch(train) [1085][40/63] lr: 2.6236e-04 eta: 1:19:58 time: 0.6247 data_time: 0.0110 memory: 14901 loss: 0.8873 loss_prob: 0.4657 loss_thr: 0.3437 loss_db: 0.0779 2022/11/03 01:28:07 - mmengine - INFO - Epoch(train) [1085][45/63] lr: 2.6236e-04 eta: 1:19:58 time: 0.6082 data_time: 0.0064 memory: 14901 loss: 0.9018 loss_prob: 0.4738 loss_thr: 0.3485 loss_db: 0.0795 2022/11/03 01:28:11 - mmengine - INFO - Epoch(train) [1085][50/63] lr: 2.6236e-04 eta: 1:19:52 time: 0.6870 data_time: 0.0210 memory: 14901 loss: 0.9371 loss_prob: 0.4934 loss_thr: 0.3594 loss_db: 0.0842 2022/11/03 01:28:15 - mmengine - INFO - Epoch(train) [1085][55/63] lr: 2.6236e-04 eta: 1:19:52 time: 0.8146 data_time: 0.0255 memory: 14901 loss: 0.8798 loss_prob: 0.4574 loss_thr: 0.3433 loss_db: 0.0792 2022/11/03 01:28:19 - mmengine - INFO - Epoch(train) [1085][60/63] lr: 2.6236e-04 eta: 1:19:45 time: 0.7756 data_time: 0.0136 memory: 14901 loss: 0.9090 loss_prob: 0.4728 loss_thr: 0.3542 loss_db: 0.0820 2022/11/03 01:28:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:28:29 - mmengine - INFO - Epoch(train) [1086][5/63] lr: 2.6031e-04 eta: 1:19:45 time: 1.1205 data_time: 0.2527 memory: 14901 loss: 0.9722 loss_prob: 0.5259 loss_thr: 0.3572 loss_db: 0.0891 2022/11/03 01:28:33 - mmengine - INFO - Epoch(train) [1086][10/63] lr: 2.6031e-04 eta: 1:19:37 time: 1.2085 data_time: 0.2526 memory: 14901 loss: 0.9036 loss_prob: 0.4811 loss_thr: 0.3409 loss_db: 0.0816 2022/11/03 01:28:38 - mmengine - INFO - Epoch(train) [1086][15/63] lr: 2.6031e-04 eta: 1:19:37 time: 0.8731 data_time: 0.0088 memory: 14901 loss: 0.9092 loss_prob: 0.4763 loss_thr: 0.3513 loss_db: 0.0816 2022/11/03 01:28:40 - mmengine - INFO - Epoch(train) [1086][20/63] lr: 2.6031e-04 eta: 1:19:31 time: 0.7047 data_time: 0.0081 memory: 14901 loss: 0.9198 loss_prob: 0.4779 loss_thr: 0.3585 loss_db: 0.0833 2022/11/03 01:28:43 - mmengine - INFO - Epoch(train) [1086][25/63] lr: 2.6031e-04 eta: 1:19:31 time: 0.5529 data_time: 0.0215 memory: 14901 loss: 0.8800 loss_prob: 0.4539 loss_thr: 0.3459 loss_db: 0.0802 2022/11/03 01:28:46 - mmengine - INFO - Epoch(train) [1086][30/63] lr: 2.6031e-04 eta: 1:19:24 time: 0.5465 data_time: 0.0427 memory: 14901 loss: 0.8944 loss_prob: 0.4614 loss_thr: 0.3515 loss_db: 0.0814 2022/11/03 01:28:48 - mmengine - INFO - Epoch(train) [1086][35/63] lr: 2.6031e-04 eta: 1:19:24 time: 0.5230 data_time: 0.0307 memory: 14901 loss: 0.8881 loss_prob: 0.4577 loss_thr: 0.3483 loss_db: 0.0820 2022/11/03 01:28:51 - mmengine - INFO - Epoch(train) [1086][40/63] lr: 2.6031e-04 eta: 1:19:17 time: 0.5439 data_time: 0.0082 memory: 14901 loss: 0.8125 loss_prob: 0.4134 loss_thr: 0.3253 loss_db: 0.0737 2022/11/03 01:28:54 - mmengine - INFO - Epoch(train) [1086][45/63] lr: 2.6031e-04 eta: 1:19:17 time: 0.5437 data_time: 0.0056 memory: 14901 loss: 0.8359 loss_prob: 0.4245 loss_thr: 0.3374 loss_db: 0.0740 2022/11/03 01:28:57 - mmengine - INFO - Epoch(train) [1086][50/63] lr: 2.6031e-04 eta: 1:19:10 time: 0.5217 data_time: 0.0196 memory: 14901 loss: 0.8742 loss_prob: 0.4517 loss_thr: 0.3447 loss_db: 0.0779 2022/11/03 01:29:00 - mmengine - INFO - Epoch(train) [1086][55/63] lr: 2.6031e-04 eta: 1:19:10 time: 0.6250 data_time: 0.0268 memory: 14901 loss: 0.8857 loss_prob: 0.4613 loss_thr: 0.3445 loss_db: 0.0799 2022/11/03 01:29:03 - mmengine - INFO - Epoch(train) [1086][60/63] lr: 2.6031e-04 eta: 1:19:04 time: 0.6543 data_time: 0.0130 memory: 14901 loss: 0.8442 loss_prob: 0.4309 loss_thr: 0.3378 loss_db: 0.0754 2022/11/03 01:29:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:29:12 - mmengine - INFO - Epoch(train) [1087][5/63] lr: 2.5826e-04 eta: 1:19:04 time: 0.9825 data_time: 0.2714 memory: 14901 loss: 0.8263 loss_prob: 0.4249 loss_thr: 0.3253 loss_db: 0.0761 2022/11/03 01:29:15 - mmengine - INFO - Epoch(train) [1087][10/63] lr: 2.5826e-04 eta: 1:18:55 time: 0.9763 data_time: 0.2728 memory: 14901 loss: 0.9040 loss_prob: 0.4714 loss_thr: 0.3496 loss_db: 0.0829 2022/11/03 01:29:18 - mmengine - INFO - Epoch(train) [1087][15/63] lr: 2.5826e-04 eta: 1:18:55 time: 0.6057 data_time: 0.0087 memory: 14901 loss: 0.8999 loss_prob: 0.4655 loss_thr: 0.3549 loss_db: 0.0795 2022/11/03 01:29:22 - mmengine - INFO - Epoch(train) [1087][20/63] lr: 2.5826e-04 eta: 1:18:49 time: 0.7180 data_time: 0.0086 memory: 14901 loss: 0.8698 loss_prob: 0.4509 loss_thr: 0.3420 loss_db: 0.0769 2022/11/03 01:29:26 - mmengine - INFO - Epoch(train) [1087][25/63] lr: 2.5826e-04 eta: 1:18:49 time: 0.8267 data_time: 0.0088 memory: 14901 loss: 0.8325 loss_prob: 0.4262 loss_thr: 0.3309 loss_db: 0.0755 2022/11/03 01:29:31 - mmengine - INFO - Epoch(train) [1087][30/63] lr: 2.5826e-04 eta: 1:18:42 time: 0.9209 data_time: 0.0352 memory: 14901 loss: 0.8067 loss_prob: 0.4099 loss_thr: 0.3225 loss_db: 0.0743 2022/11/03 01:29:34 - mmengine - INFO - Epoch(train) [1087][35/63] lr: 2.5826e-04 eta: 1:18:42 time: 0.8636 data_time: 0.0389 memory: 14901 loss: 0.8772 loss_prob: 0.4478 loss_thr: 0.3504 loss_db: 0.0790 2022/11/03 01:29:38 - mmengine - INFO - Epoch(train) [1087][40/63] lr: 2.5826e-04 eta: 1:18:36 time: 0.6609 data_time: 0.0131 memory: 14901 loss: 0.9200 loss_prob: 0.4727 loss_thr: 0.3644 loss_db: 0.0829 2022/11/03 01:29:40 - mmengine - INFO - Epoch(train) [1087][45/63] lr: 2.5826e-04 eta: 1:18:36 time: 0.5601 data_time: 0.0082 memory: 14901 loss: 0.8731 loss_prob: 0.4467 loss_thr: 0.3473 loss_db: 0.0791 2022/11/03 01:29:44 - mmengine - INFO - Epoch(train) [1087][50/63] lr: 2.5826e-04 eta: 1:18:29 time: 0.6368 data_time: 0.0234 memory: 14901 loss: 0.8427 loss_prob: 0.4283 loss_thr: 0.3388 loss_db: 0.0756 2022/11/03 01:29:48 - mmengine - INFO - Epoch(train) [1087][55/63] lr: 2.5826e-04 eta: 1:18:29 time: 0.7629 data_time: 0.0281 memory: 14901 loss: 0.8610 loss_prob: 0.4427 loss_thr: 0.3408 loss_db: 0.0775 2022/11/03 01:29:52 - mmengine - INFO - Epoch(train) [1087][60/63] lr: 2.5826e-04 eta: 1:18:23 time: 0.8093 data_time: 0.0133 memory: 14901 loss: 0.8317 loss_prob: 0.4297 loss_thr: 0.3273 loss_db: 0.0748 2022/11/03 01:29:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:30:01 - mmengine - INFO - Epoch(train) [1088][5/63] lr: 2.5620e-04 eta: 1:18:23 time: 1.0184 data_time: 0.3092 memory: 14901 loss: 0.9170 loss_prob: 0.4787 loss_thr: 0.3542 loss_db: 0.0840 2022/11/03 01:30:06 - mmengine - INFO - Epoch(train) [1088][10/63] lr: 2.5620e-04 eta: 1:18:15 time: 1.2641 data_time: 0.3137 memory: 14901 loss: 0.8750 loss_prob: 0.4546 loss_thr: 0.3423 loss_db: 0.0781 2022/11/03 01:30:09 - mmengine - INFO - Epoch(train) [1088][15/63] lr: 2.5620e-04 eta: 1:18:15 time: 0.7705 data_time: 0.0120 memory: 14901 loss: 0.8074 loss_prob: 0.4099 loss_thr: 0.3258 loss_db: 0.0717 2022/11/03 01:30:11 - mmengine - INFO - Epoch(train) [1088][20/63] lr: 2.5620e-04 eta: 1:18:08 time: 0.5188 data_time: 0.0060 memory: 14901 loss: 0.8708 loss_prob: 0.4537 loss_thr: 0.3406 loss_db: 0.0765 2022/11/03 01:30:14 - mmengine - INFO - Epoch(train) [1088][25/63] lr: 2.5620e-04 eta: 1:18:08 time: 0.5083 data_time: 0.0247 memory: 14901 loss: 0.9281 loss_prob: 0.4919 loss_thr: 0.3533 loss_db: 0.0828 2022/11/03 01:30:16 - mmengine - INFO - Epoch(train) [1088][30/63] lr: 2.5620e-04 eta: 1:18:01 time: 0.4739 data_time: 0.0296 memory: 14901 loss: 0.9488 loss_prob: 0.4949 loss_thr: 0.3677 loss_db: 0.0862 2022/11/03 01:30:19 - mmengine - INFO - Epoch(train) [1088][35/63] lr: 2.5620e-04 eta: 1:18:01 time: 0.4972 data_time: 0.0191 memory: 14901 loss: 0.8798 loss_prob: 0.4541 loss_thr: 0.3453 loss_db: 0.0803 2022/11/03 01:30:21 - mmengine - INFO - Epoch(train) [1088][40/63] lr: 2.5620e-04 eta: 1:17:54 time: 0.5222 data_time: 0.0130 memory: 14901 loss: 0.8019 loss_prob: 0.4116 loss_thr: 0.3181 loss_db: 0.0722 2022/11/03 01:30:24 - mmengine - INFO - Epoch(train) [1088][45/63] lr: 2.5620e-04 eta: 1:17:54 time: 0.4906 data_time: 0.0044 memory: 14901 loss: 0.8126 loss_prob: 0.4176 loss_thr: 0.3220 loss_db: 0.0730 2022/11/03 01:30:26 - mmengine - INFO - Epoch(train) [1088][50/63] lr: 2.5620e-04 eta: 1:17:48 time: 0.5042 data_time: 0.0129 memory: 14901 loss: 0.8211 loss_prob: 0.4136 loss_thr: 0.3338 loss_db: 0.0737 2022/11/03 01:30:29 - mmengine - INFO - Epoch(train) [1088][55/63] lr: 2.5620e-04 eta: 1:17:48 time: 0.5549 data_time: 0.0165 memory: 14901 loss: 0.8281 loss_prob: 0.4139 loss_thr: 0.3401 loss_db: 0.0742 2022/11/03 01:30:32 - mmengine - INFO - Epoch(train) [1088][60/63] lr: 2.5620e-04 eta: 1:17:41 time: 0.5245 data_time: 0.0111 memory: 14901 loss: 0.8762 loss_prob: 0.4486 loss_thr: 0.3491 loss_db: 0.0785 2022/11/03 01:30:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:30:40 - mmengine - INFO - Epoch(train) [1089][5/63] lr: 2.5414e-04 eta: 1:17:41 time: 0.9203 data_time: 0.2061 memory: 14901 loss: 0.7538 loss_prob: 0.3815 loss_thr: 0.3058 loss_db: 0.0664 2022/11/03 01:30:50 - mmengine - INFO - Epoch(train) [1089][10/63] lr: 2.5414e-04 eta: 1:17:33 time: 1.6695 data_time: 0.2114 memory: 14901 loss: 0.7770 loss_prob: 0.3911 loss_thr: 0.3173 loss_db: 0.0687 2022/11/03 01:30:58 - mmengine - INFO - Epoch(train) [1089][15/63] lr: 2.5414e-04 eta: 1:17:33 time: 1.8302 data_time: 0.0127 memory: 14901 loss: 0.8404 loss_prob: 0.4279 loss_thr: 0.3393 loss_db: 0.0732 2022/11/03 01:31:05 - mmengine - INFO - Epoch(train) [1089][20/63] lr: 2.5414e-04 eta: 1:17:27 time: 1.5856 data_time: 0.0114 memory: 14901 loss: 0.8819 loss_prob: 0.4535 loss_thr: 0.3505 loss_db: 0.0779 2022/11/03 01:31:10 - mmengine - INFO - Epoch(train) [1089][25/63] lr: 2.5414e-04 eta: 1:17:27 time: 1.1993 data_time: 0.0267 memory: 14901 loss: 0.8579 loss_prob: 0.4465 loss_thr: 0.3324 loss_db: 0.0791 2022/11/03 01:31:15 - mmengine - INFO - Epoch(train) [1089][30/63] lr: 2.5414e-04 eta: 1:17:21 time: 0.9701 data_time: 0.0408 memory: 14901 loss: 0.8503 loss_prob: 0.4389 loss_thr: 0.3332 loss_db: 0.0783 2022/11/03 01:31:19 - mmengine - INFO - Epoch(train) [1089][35/63] lr: 2.5414e-04 eta: 1:17:21 time: 0.8937 data_time: 0.0291 memory: 14901 loss: 0.9211 loss_prob: 0.4922 loss_thr: 0.3464 loss_db: 0.0825 2022/11/03 01:31:22 - mmengine - INFO - Epoch(train) [1089][40/63] lr: 2.5414e-04 eta: 1:17:15 time: 0.7230 data_time: 0.0108 memory: 14901 loss: 0.9754 loss_prob: 0.5224 loss_thr: 0.3670 loss_db: 0.0860 2022/11/03 01:31:26 - mmengine - INFO - Epoch(train) [1089][45/63] lr: 2.5414e-04 eta: 1:17:15 time: 0.6825 data_time: 0.0055 memory: 14901 loss: 0.9082 loss_prob: 0.4714 loss_thr: 0.3561 loss_db: 0.0807 2022/11/03 01:31:30 - mmengine - INFO - Epoch(train) [1089][50/63] lr: 2.5414e-04 eta: 1:17:08 time: 0.7345 data_time: 0.0105 memory: 14901 loss: 0.8496 loss_prob: 0.4445 loss_thr: 0.3297 loss_db: 0.0755 2022/11/03 01:31:32 - mmengine - INFO - Epoch(train) [1089][55/63] lr: 2.5414e-04 eta: 1:17:08 time: 0.6586 data_time: 0.0231 memory: 14901 loss: 0.9021 loss_prob: 0.4722 loss_thr: 0.3501 loss_db: 0.0798 2022/11/03 01:31:36 - mmengine - INFO - Epoch(train) [1089][60/63] lr: 2.5414e-04 eta: 1:17:01 time: 0.6012 data_time: 0.0178 memory: 14901 loss: 0.9468 loss_prob: 0.4920 loss_thr: 0.3697 loss_db: 0.0850 2022/11/03 01:31:37 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:31:44 - mmengine - INFO - Epoch(train) [1090][5/63] lr: 2.5208e-04 eta: 1:17:01 time: 0.9106 data_time: 0.2306 memory: 14901 loss: 0.8950 loss_prob: 0.4602 loss_thr: 0.3538 loss_db: 0.0811 2022/11/03 01:31:47 - mmengine - INFO - Epoch(train) [1090][10/63] lr: 2.5208e-04 eta: 1:16:53 time: 0.9726 data_time: 0.2307 memory: 14901 loss: 0.9160 loss_prob: 0.4676 loss_thr: 0.3650 loss_db: 0.0834 2022/11/03 01:31:50 - mmengine - INFO - Epoch(train) [1090][15/63] lr: 2.5208e-04 eta: 1:16:53 time: 0.6712 data_time: 0.0072 memory: 14901 loss: 0.8539 loss_prob: 0.4368 loss_thr: 0.3401 loss_db: 0.0771 2022/11/03 01:31:54 - mmengine - INFO - Epoch(train) [1090][20/63] lr: 2.5208e-04 eta: 1:16:46 time: 0.6551 data_time: 0.0075 memory: 14901 loss: 0.8547 loss_prob: 0.4378 loss_thr: 0.3420 loss_db: 0.0749 2022/11/03 01:31:58 - mmengine - INFO - Epoch(train) [1090][25/63] lr: 2.5208e-04 eta: 1:16:46 time: 0.7535 data_time: 0.0228 memory: 14901 loss: 0.8774 loss_prob: 0.4552 loss_thr: 0.3451 loss_db: 0.0771 2022/11/03 01:32:02 - mmengine - INFO - Epoch(train) [1090][30/63] lr: 2.5208e-04 eta: 1:16:40 time: 0.8070 data_time: 0.0431 memory: 14901 loss: 0.8555 loss_prob: 0.4459 loss_thr: 0.3334 loss_db: 0.0762 2022/11/03 01:32:06 - mmengine - INFO - Epoch(train) [1090][35/63] lr: 2.5208e-04 eta: 1:16:40 time: 0.7917 data_time: 0.0266 memory: 14901 loss: 0.8872 loss_prob: 0.4641 loss_thr: 0.3440 loss_db: 0.0792 2022/11/03 01:32:11 - mmengine - INFO - Epoch(train) [1090][40/63] lr: 2.5208e-04 eta: 1:16:34 time: 0.9481 data_time: 0.0093 memory: 14901 loss: 0.8963 loss_prob: 0.4671 loss_thr: 0.3487 loss_db: 0.0805 2022/11/03 01:32:14 - mmengine - INFO - Epoch(train) [1090][45/63] lr: 2.5208e-04 eta: 1:16:34 time: 0.8178 data_time: 0.0096 memory: 14901 loss: 0.9186 loss_prob: 0.4806 loss_thr: 0.3542 loss_db: 0.0838 2022/11/03 01:32:18 - mmengine - INFO - Epoch(train) [1090][50/63] lr: 2.5208e-04 eta: 1:16:27 time: 0.6921 data_time: 0.0254 memory: 14901 loss: 0.9170 loss_prob: 0.4692 loss_thr: 0.3654 loss_db: 0.0824 2022/11/03 01:32:22 - mmengine - INFO - Epoch(train) [1090][55/63] lr: 2.5208e-04 eta: 1:16:27 time: 0.8026 data_time: 0.0261 memory: 14901 loss: 0.8419 loss_prob: 0.4346 loss_thr: 0.3329 loss_db: 0.0744 2022/11/03 01:32:27 - mmengine - INFO - Epoch(train) [1090][60/63] lr: 2.5208e-04 eta: 1:16:21 time: 0.8489 data_time: 0.0090 memory: 14901 loss: 0.8247 loss_prob: 0.4427 loss_thr: 0.3067 loss_db: 0.0753 2022/11/03 01:32:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:32:36 - mmengine - INFO - Epoch(train) [1091][5/63] lr: 2.5002e-04 eta: 1:16:21 time: 1.1103 data_time: 0.3188 memory: 14901 loss: 0.8070 loss_prob: 0.4058 loss_thr: 0.3295 loss_db: 0.0716 2022/11/03 01:32:39 - mmengine - INFO - Epoch(train) [1091][10/63] lr: 2.5002e-04 eta: 1:16:12 time: 1.1374 data_time: 0.3163 memory: 14901 loss: 0.8228 loss_prob: 0.4294 loss_thr: 0.3189 loss_db: 0.0745 2022/11/03 01:32:43 - mmengine - INFO - Epoch(train) [1091][15/63] lr: 2.5002e-04 eta: 1:16:12 time: 0.6766 data_time: 0.0057 memory: 14901 loss: 0.8439 loss_prob: 0.4398 loss_thr: 0.3286 loss_db: 0.0756 2022/11/03 01:32:46 - mmengine - INFO - Epoch(train) [1091][20/63] lr: 2.5002e-04 eta: 1:16:06 time: 0.6623 data_time: 0.0079 memory: 14901 loss: 0.8682 loss_prob: 0.4529 loss_thr: 0.3374 loss_db: 0.0778 2022/11/03 01:32:49 - mmengine - INFO - Epoch(train) [1091][25/63] lr: 2.5002e-04 eta: 1:16:06 time: 0.6064 data_time: 0.0504 memory: 14901 loss: 0.8775 loss_prob: 0.4598 loss_thr: 0.3381 loss_db: 0.0795 2022/11/03 01:32:54 - mmengine - INFO - Epoch(train) [1091][30/63] lr: 2.5002e-04 eta: 1:15:59 time: 0.8153 data_time: 0.0483 memory: 14901 loss: 0.8536 loss_prob: 0.4370 loss_thr: 0.3400 loss_db: 0.0766 2022/11/03 01:32:58 - mmengine - INFO - Epoch(train) [1091][35/63] lr: 2.5002e-04 eta: 1:15:59 time: 0.9219 data_time: 0.0090 memory: 14901 loss: 1.0852 loss_prob: 0.5918 loss_thr: 0.3956 loss_db: 0.0977 2022/11/03 01:33:03 - mmengine - INFO - Epoch(train) [1091][40/63] lr: 2.5002e-04 eta: 1:15:53 time: 0.8995 data_time: 0.0094 memory: 14901 loss: 1.0768 loss_prob: 0.5846 loss_thr: 0.3960 loss_db: 0.0962 2022/11/03 01:33:07 - mmengine - INFO - Epoch(train) [1091][45/63] lr: 2.5002e-04 eta: 1:15:53 time: 0.8215 data_time: 0.0064 memory: 14901 loss: 0.8979 loss_prob: 0.4534 loss_thr: 0.3653 loss_db: 0.0792 2022/11/03 01:33:11 - mmengine - INFO - Epoch(train) [1091][50/63] lr: 2.5002e-04 eta: 1:15:46 time: 0.7357 data_time: 0.0251 memory: 14901 loss: 0.9213 loss_prob: 0.4731 loss_thr: 0.3647 loss_db: 0.0834 2022/11/03 01:33:14 - mmengine - INFO - Epoch(train) [1091][55/63] lr: 2.5002e-04 eta: 1:15:46 time: 0.6980 data_time: 0.0278 memory: 14901 loss: 0.8429 loss_prob: 0.4374 loss_thr: 0.3288 loss_db: 0.0767 2022/11/03 01:33:17 - mmengine - INFO - Epoch(train) [1091][60/63] lr: 2.5002e-04 eta: 1:15:40 time: 0.6538 data_time: 0.0105 memory: 14901 loss: 0.8391 loss_prob: 0.4325 loss_thr: 0.3314 loss_db: 0.0752 2022/11/03 01:33:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:33:26 - mmengine - INFO - Epoch(train) [1092][5/63] lr: 2.4795e-04 eta: 1:15:40 time: 1.0380 data_time: 0.2650 memory: 14901 loss: 0.8663 loss_prob: 0.4529 loss_thr: 0.3339 loss_db: 0.0796 2022/11/03 01:33:29 - mmengine - INFO - Epoch(train) [1092][10/63] lr: 2.4795e-04 eta: 1:15:31 time: 1.0615 data_time: 0.2663 memory: 14901 loss: 0.8347 loss_prob: 0.4292 loss_thr: 0.3297 loss_db: 0.0758 2022/11/03 01:33:32 - mmengine - INFO - Epoch(train) [1092][15/63] lr: 2.4795e-04 eta: 1:15:31 time: 0.5564 data_time: 0.0106 memory: 14901 loss: 0.8273 loss_prob: 0.4251 loss_thr: 0.3281 loss_db: 0.0740 2022/11/03 01:33:35 - mmengine - INFO - Epoch(train) [1092][20/63] lr: 2.4795e-04 eta: 1:15:25 time: 0.6438 data_time: 0.0117 memory: 14901 loss: 0.8770 loss_prob: 0.4534 loss_thr: 0.3448 loss_db: 0.0787 2022/11/03 01:33:39 - mmengine - INFO - Epoch(train) [1092][25/63] lr: 2.4795e-04 eta: 1:15:25 time: 0.7404 data_time: 0.0360 memory: 14901 loss: 0.9739 loss_prob: 0.5171 loss_thr: 0.3680 loss_db: 0.0888 2022/11/03 01:33:44 - mmengine - INFO - Epoch(train) [1092][30/63] lr: 2.4795e-04 eta: 1:15:18 time: 0.8289 data_time: 0.0382 memory: 14901 loss: 0.9244 loss_prob: 0.4944 loss_thr: 0.3444 loss_db: 0.0857 2022/11/03 01:33:47 - mmengine - INFO - Epoch(train) [1092][35/63] lr: 2.4795e-04 eta: 1:15:18 time: 0.7885 data_time: 0.0122 memory: 14901 loss: 0.7838 loss_prob: 0.3988 loss_thr: 0.3132 loss_db: 0.0718 2022/11/03 01:33:50 - mmengine - INFO - Epoch(train) [1092][40/63] lr: 2.4795e-04 eta: 1:15:12 time: 0.6505 data_time: 0.0073 memory: 14901 loss: 0.8501 loss_prob: 0.4266 loss_thr: 0.3484 loss_db: 0.0751 2022/11/03 01:33:53 - mmengine - INFO - Epoch(train) [1092][45/63] lr: 2.4795e-04 eta: 1:15:12 time: 0.6000 data_time: 0.0058 memory: 14901 loss: 0.9378 loss_prob: 0.4808 loss_thr: 0.3730 loss_db: 0.0840 2022/11/03 01:33:56 - mmengine - INFO - Epoch(train) [1092][50/63] lr: 2.4795e-04 eta: 1:15:05 time: 0.6155 data_time: 0.0241 memory: 14901 loss: 0.8952 loss_prob: 0.4613 loss_thr: 0.3535 loss_db: 0.0804 2022/11/03 01:34:00 - mmengine - INFO - Epoch(train) [1092][55/63] lr: 2.4795e-04 eta: 1:15:05 time: 0.6596 data_time: 0.0266 memory: 14901 loss: 0.8556 loss_prob: 0.4323 loss_thr: 0.3489 loss_db: 0.0744 2022/11/03 01:34:03 - mmengine - INFO - Epoch(train) [1092][60/63] lr: 2.4795e-04 eta: 1:14:58 time: 0.6849 data_time: 0.0101 memory: 14901 loss: 0.8843 loss_prob: 0.4511 loss_thr: 0.3540 loss_db: 0.0792 2022/11/03 01:34:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:34:13 - mmengine - INFO - Epoch(train) [1093][5/63] lr: 2.4589e-04 eta: 1:14:58 time: 1.1137 data_time: 0.2322 memory: 14901 loss: 0.9423 loss_prob: 0.4930 loss_thr: 0.3640 loss_db: 0.0853 2022/11/03 01:34:17 - mmengine - INFO - Epoch(train) [1093][10/63] lr: 2.4589e-04 eta: 1:14:50 time: 1.1323 data_time: 0.2330 memory: 14901 loss: 0.8945 loss_prob: 0.4617 loss_thr: 0.3523 loss_db: 0.0804 2022/11/03 01:34:21 - mmengine - INFO - Epoch(train) [1093][15/63] lr: 2.4589e-04 eta: 1:14:50 time: 0.7906 data_time: 0.0069 memory: 14901 loss: 0.9192 loss_prob: 0.4845 loss_thr: 0.3495 loss_db: 0.0851 2022/11/03 01:34:24 - mmengine - INFO - Epoch(train) [1093][20/63] lr: 2.4589e-04 eta: 1:14:43 time: 0.7142 data_time: 0.0063 memory: 14901 loss: 0.8668 loss_prob: 0.4521 loss_thr: 0.3341 loss_db: 0.0805 2022/11/03 01:34:28 - mmengine - INFO - Epoch(train) [1093][25/63] lr: 2.4589e-04 eta: 1:14:43 time: 0.7638 data_time: 0.0285 memory: 14901 loss: 0.8139 loss_prob: 0.4169 loss_thr: 0.3225 loss_db: 0.0745 2022/11/03 01:34:32 - mmengine - INFO - Epoch(train) [1093][30/63] lr: 2.4589e-04 eta: 1:14:37 time: 0.8297 data_time: 0.0581 memory: 14901 loss: 0.8275 loss_prob: 0.4242 loss_thr: 0.3286 loss_db: 0.0747 2022/11/03 01:34:37 - mmengine - INFO - Epoch(train) [1093][35/63] lr: 2.4589e-04 eta: 1:14:37 time: 0.8598 data_time: 0.0366 memory: 14901 loss: 0.8384 loss_prob: 0.4332 loss_thr: 0.3300 loss_db: 0.0752 2022/11/03 01:34:40 - mmengine - INFO - Epoch(train) [1093][40/63] lr: 2.4589e-04 eta: 1:14:31 time: 0.8164 data_time: 0.0068 memory: 14901 loss: 0.8203 loss_prob: 0.4182 loss_thr: 0.3286 loss_db: 0.0736 2022/11/03 01:34:43 - mmengine - INFO - Epoch(train) [1093][45/63] lr: 2.4589e-04 eta: 1:14:31 time: 0.6560 data_time: 0.0070 memory: 14901 loss: 0.8101 loss_prob: 0.4074 loss_thr: 0.3310 loss_db: 0.0716 2022/11/03 01:34:46 - mmengine - INFO - Epoch(train) [1093][50/63] lr: 2.4589e-04 eta: 1:14:24 time: 0.5841 data_time: 0.0143 memory: 14901 loss: 0.8243 loss_prob: 0.4184 loss_thr: 0.3315 loss_db: 0.0744 2022/11/03 01:34:49 - mmengine - INFO - Epoch(train) [1093][55/63] lr: 2.4589e-04 eta: 1:14:24 time: 0.5474 data_time: 0.0270 memory: 14901 loss: 0.7475 loss_prob: 0.3772 loss_thr: 0.3032 loss_db: 0.0672 2022/11/03 01:34:52 - mmengine - INFO - Epoch(train) [1093][60/63] lr: 2.4589e-04 eta: 1:14:17 time: 0.5712 data_time: 0.0259 memory: 14901 loss: 0.7679 loss_prob: 0.3935 loss_thr: 0.3067 loss_db: 0.0678 2022/11/03 01:34:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:35:00 - mmengine - INFO - Epoch(train) [1094][5/63] lr: 2.4382e-04 eta: 1:14:17 time: 0.9121 data_time: 0.2716 memory: 14901 loss: 0.8349 loss_prob: 0.4343 loss_thr: 0.3256 loss_db: 0.0750 2022/11/03 01:35:03 - mmengine - INFO - Epoch(train) [1094][10/63] lr: 2.4382e-04 eta: 1:14:09 time: 0.9507 data_time: 0.2717 memory: 14901 loss: 0.8126 loss_prob: 0.4107 loss_thr: 0.3288 loss_db: 0.0731 2022/11/03 01:35:07 - mmengine - INFO - Epoch(train) [1094][15/63] lr: 2.4382e-04 eta: 1:14:09 time: 0.6814 data_time: 0.0068 memory: 14901 loss: 0.8744 loss_prob: 0.4484 loss_thr: 0.3487 loss_db: 0.0772 2022/11/03 01:35:09 - mmengine - INFO - Epoch(train) [1094][20/63] lr: 2.4382e-04 eta: 1:14:02 time: 0.6632 data_time: 0.0060 memory: 14901 loss: 0.9108 loss_prob: 0.4744 loss_thr: 0.3566 loss_db: 0.0799 2022/11/03 01:35:13 - mmengine - INFO - Epoch(train) [1094][25/63] lr: 2.4382e-04 eta: 1:14:02 time: 0.6498 data_time: 0.0329 memory: 14901 loss: 0.8459 loss_prob: 0.4325 loss_thr: 0.3405 loss_db: 0.0729 2022/11/03 01:35:16 - mmengine - INFO - Epoch(train) [1094][30/63] lr: 2.4382e-04 eta: 1:13:55 time: 0.6179 data_time: 0.0355 memory: 14901 loss: 0.8168 loss_prob: 0.4085 loss_thr: 0.3381 loss_db: 0.0702 2022/11/03 01:35:20 - mmengine - INFO - Epoch(train) [1094][35/63] lr: 2.4382e-04 eta: 1:13:55 time: 0.6464 data_time: 0.0081 memory: 14901 loss: 0.8218 loss_prob: 0.4182 loss_thr: 0.3299 loss_db: 0.0736 2022/11/03 01:35:23 - mmengine - INFO - Epoch(train) [1094][40/63] lr: 2.4382e-04 eta: 1:13:49 time: 0.7673 data_time: 0.0065 memory: 14901 loss: 0.8652 loss_prob: 0.4475 loss_thr: 0.3384 loss_db: 0.0792 2022/11/03 01:35:27 - mmengine - INFO - Epoch(train) [1094][45/63] lr: 2.4382e-04 eta: 1:13:49 time: 0.7159 data_time: 0.0068 memory: 14901 loss: 1.0211 loss_prob: 0.5519 loss_thr: 0.3747 loss_db: 0.0945 2022/11/03 01:35:31 - mmengine - INFO - Epoch(train) [1094][50/63] lr: 2.4382e-04 eta: 1:13:42 time: 0.7196 data_time: 0.0242 memory: 14901 loss: 1.0304 loss_prob: 0.5559 loss_thr: 0.3794 loss_db: 0.0951 2022/11/03 01:35:34 - mmengine - INFO - Epoch(train) [1094][55/63] lr: 2.4382e-04 eta: 1:13:42 time: 0.7711 data_time: 0.0239 memory: 14901 loss: 0.9053 loss_prob: 0.4664 loss_thr: 0.3583 loss_db: 0.0806 2022/11/03 01:35:37 - mmengine - INFO - Epoch(train) [1094][60/63] lr: 2.4382e-04 eta: 1:13:36 time: 0.6631 data_time: 0.0056 memory: 14901 loss: 0.8720 loss_prob: 0.4492 loss_thr: 0.3445 loss_db: 0.0783 2022/11/03 01:35:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:35:45 - mmengine - INFO - Epoch(train) [1095][5/63] lr: 2.4175e-04 eta: 1:13:36 time: 0.8516 data_time: 0.2159 memory: 14901 loss: 0.8823 loss_prob: 0.4575 loss_thr: 0.3440 loss_db: 0.0807 2022/11/03 01:35:48 - mmengine - INFO - Epoch(train) [1095][10/63] lr: 2.4175e-04 eta: 1:13:27 time: 0.9496 data_time: 0.2162 memory: 14901 loss: 0.8736 loss_prob: 0.4602 loss_thr: 0.3350 loss_db: 0.0784 2022/11/03 01:35:52 - mmengine - INFO - Epoch(train) [1095][15/63] lr: 2.4175e-04 eta: 1:13:27 time: 0.7479 data_time: 0.0108 memory: 14901 loss: 0.9071 loss_prob: 0.4759 loss_thr: 0.3500 loss_db: 0.0811 2022/11/03 01:35:56 - mmengine - INFO - Epoch(train) [1095][20/63] lr: 2.4175e-04 eta: 1:13:21 time: 0.7900 data_time: 0.0109 memory: 14901 loss: 0.8025 loss_prob: 0.4060 loss_thr: 0.3237 loss_db: 0.0727 2022/11/03 01:36:00 - mmengine - INFO - Epoch(train) [1095][25/63] lr: 2.4175e-04 eta: 1:13:21 time: 0.8356 data_time: 0.0372 memory: 14901 loss: 0.7987 loss_prob: 0.4072 loss_thr: 0.3179 loss_db: 0.0736 2022/11/03 01:36:04 - mmengine - INFO - Epoch(train) [1095][30/63] lr: 2.4175e-04 eta: 1:13:14 time: 0.8151 data_time: 0.0451 memory: 14901 loss: 0.8853 loss_prob: 0.4644 loss_thr: 0.3380 loss_db: 0.0830 2022/11/03 01:36:07 - mmengine - INFO - Epoch(train) [1095][35/63] lr: 2.4175e-04 eta: 1:13:14 time: 0.6491 data_time: 0.0137 memory: 14901 loss: 0.8956 loss_prob: 0.4635 loss_thr: 0.3505 loss_db: 0.0815 2022/11/03 01:36:11 - mmengine - INFO - Epoch(train) [1095][40/63] lr: 2.4175e-04 eta: 1:13:08 time: 0.6529 data_time: 0.0091 memory: 14901 loss: 0.8567 loss_prob: 0.4389 loss_thr: 0.3424 loss_db: 0.0755 2022/11/03 01:36:14 - mmengine - INFO - Epoch(train) [1095][45/63] lr: 2.4175e-04 eta: 1:13:08 time: 0.7178 data_time: 0.0090 memory: 14901 loss: 0.9414 loss_prob: 0.4920 loss_thr: 0.3647 loss_db: 0.0846 2022/11/03 01:36:20 - mmengine - INFO - Epoch(train) [1095][50/63] lr: 2.4175e-04 eta: 1:13:01 time: 0.8803 data_time: 0.0199 memory: 14901 loss: 0.9821 loss_prob: 0.5136 loss_thr: 0.3785 loss_db: 0.0900 2022/11/03 01:36:24 - mmengine - INFO - Epoch(train) [1095][55/63] lr: 2.4175e-04 eta: 1:13:01 time: 0.9642 data_time: 0.0231 memory: 14901 loss: 0.8839 loss_prob: 0.4562 loss_thr: 0.3468 loss_db: 0.0809 2022/11/03 01:36:26 - mmengine - INFO - Epoch(train) [1095][60/63] lr: 2.4175e-04 eta: 1:12:55 time: 0.6659 data_time: 0.0089 memory: 14901 loss: 0.9591 loss_prob: 0.4887 loss_thr: 0.3860 loss_db: 0.0844 2022/11/03 01:36:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:36:35 - mmengine - INFO - Epoch(train) [1096][5/63] lr: 2.3967e-04 eta: 1:12:55 time: 0.9952 data_time: 0.1998 memory: 14901 loss: 1.0588 loss_prob: 0.5566 loss_thr: 0.4065 loss_db: 0.0957 2022/11/03 01:36:40 - mmengine - INFO - Epoch(train) [1096][10/63] lr: 2.3967e-04 eta: 1:12:46 time: 1.2091 data_time: 0.1992 memory: 14901 loss: 0.8995 loss_prob: 0.4691 loss_thr: 0.3473 loss_db: 0.0831 2022/11/03 01:36:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:36:42 - mmengine - INFO - Epoch(train) [1096][15/63] lr: 2.3967e-04 eta: 1:12:46 time: 0.7114 data_time: 0.0128 memory: 14901 loss: 0.8471 loss_prob: 0.4416 loss_thr: 0.3279 loss_db: 0.0776 2022/11/03 01:36:46 - mmengine - INFO - Epoch(train) [1096][20/63] lr: 2.3967e-04 eta: 1:12:40 time: 0.6226 data_time: 0.0101 memory: 14901 loss: 0.9422 loss_prob: 0.4915 loss_thr: 0.3663 loss_db: 0.0843 2022/11/03 01:36:49 - mmengine - INFO - Epoch(train) [1096][25/63] lr: 2.3967e-04 eta: 1:12:40 time: 0.6231 data_time: 0.0149 memory: 14901 loss: 1.0679 loss_prob: 0.5825 loss_thr: 0.3826 loss_db: 0.1029 2022/11/03 01:36:52 - mmengine - INFO - Epoch(train) [1096][30/63] lr: 2.3967e-04 eta: 1:12:33 time: 0.5814 data_time: 0.0351 memory: 14901 loss: 1.1475 loss_prob: 0.6339 loss_thr: 0.4056 loss_db: 0.1080 2022/11/03 01:36:55 - mmengine - INFO - Epoch(train) [1096][35/63] lr: 2.3967e-04 eta: 1:12:33 time: 0.6131 data_time: 0.0256 memory: 14901 loss: 1.1127 loss_prob: 0.6051 loss_thr: 0.4118 loss_db: 0.0958 2022/11/03 01:36:57 - mmengine - INFO - Epoch(train) [1096][40/63] lr: 2.3967e-04 eta: 1:12:26 time: 0.5789 data_time: 0.0101 memory: 14901 loss: 1.2051 loss_prob: 0.6760 loss_thr: 0.4226 loss_db: 0.1065 2022/11/03 01:37:02 - mmengine - INFO - Epoch(train) [1096][45/63] lr: 2.3967e-04 eta: 1:12:26 time: 0.7069 data_time: 0.0155 memory: 14901 loss: 1.1788 loss_prob: 0.6471 loss_thr: 0.4251 loss_db: 0.1066 2022/11/03 01:37:06 - mmengine - INFO - Epoch(train) [1096][50/63] lr: 2.3967e-04 eta: 1:12:20 time: 0.8979 data_time: 0.0185 memory: 14901 loss: 1.1304 loss_prob: 0.5995 loss_thr: 0.4306 loss_db: 0.1003 2022/11/03 01:37:10 - mmengine - INFO - Epoch(train) [1096][55/63] lr: 2.3967e-04 eta: 1:12:20 time: 0.8449 data_time: 0.0259 memory: 14901 loss: 1.1464 loss_prob: 0.6147 loss_thr: 0.4312 loss_db: 0.1005 2022/11/03 01:37:14 - mmengine - INFO - Epoch(train) [1096][60/63] lr: 2.3967e-04 eta: 1:12:13 time: 0.7301 data_time: 0.0179 memory: 14901 loss: 1.0146 loss_prob: 0.5402 loss_thr: 0.3833 loss_db: 0.0911 2022/11/03 01:37:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:37:23 - mmengine - INFO - Epoch(train) [1097][5/63] lr: 2.3760e-04 eta: 1:12:13 time: 1.0719 data_time: 0.2760 memory: 14901 loss: 0.9429 loss_prob: 0.4952 loss_thr: 0.3602 loss_db: 0.0876 2022/11/03 01:37:27 - mmengine - INFO - Epoch(train) [1097][10/63] lr: 2.3760e-04 eta: 1:12:05 time: 1.1148 data_time: 0.2754 memory: 14901 loss: 0.9400 loss_prob: 0.4920 loss_thr: 0.3600 loss_db: 0.0880 2022/11/03 01:37:30 - mmengine - INFO - Epoch(train) [1097][15/63] lr: 2.3760e-04 eta: 1:12:05 time: 0.7274 data_time: 0.0067 memory: 14901 loss: 0.9460 loss_prob: 0.4933 loss_thr: 0.3653 loss_db: 0.0874 2022/11/03 01:37:33 - mmengine - INFO - Epoch(train) [1097][20/63] lr: 2.3760e-04 eta: 1:11:58 time: 0.6112 data_time: 0.0070 memory: 14901 loss: 0.9822 loss_prob: 0.5100 loss_thr: 0.3832 loss_db: 0.0890 2022/11/03 01:37:38 - mmengine - INFO - Epoch(train) [1097][25/63] lr: 2.3760e-04 eta: 1:11:58 time: 0.7345 data_time: 0.0359 memory: 14901 loss: 0.9620 loss_prob: 0.4909 loss_thr: 0.3861 loss_db: 0.0849 2022/11/03 01:37:41 - mmengine - INFO - Epoch(train) [1097][30/63] lr: 2.3760e-04 eta: 1:11:52 time: 0.8231 data_time: 0.0436 memory: 14901 loss: 0.9330 loss_prob: 0.4749 loss_thr: 0.3753 loss_db: 0.0829 2022/11/03 01:37:45 - mmengine - INFO - Epoch(train) [1097][35/63] lr: 2.3760e-04 eta: 1:11:52 time: 0.6988 data_time: 0.0139 memory: 14901 loss: 0.9678 loss_prob: 0.5001 loss_thr: 0.3789 loss_db: 0.0888 2022/11/03 01:37:47 - mmengine - INFO - Epoch(train) [1097][40/63] lr: 2.3760e-04 eta: 1:11:45 time: 0.6155 data_time: 0.0078 memory: 14901 loss: 0.9701 loss_prob: 0.5121 loss_thr: 0.3676 loss_db: 0.0904 2022/11/03 01:37:50 - mmengine - INFO - Epoch(train) [1097][45/63] lr: 2.3760e-04 eta: 1:11:45 time: 0.5847 data_time: 0.0106 memory: 14901 loss: 0.9300 loss_prob: 0.4900 loss_thr: 0.3555 loss_db: 0.0845 2022/11/03 01:37:56 - mmengine - INFO - Epoch(train) [1097][50/63] lr: 2.3760e-04 eta: 1:11:39 time: 0.8163 data_time: 0.0253 memory: 14901 loss: 0.9207 loss_prob: 0.4855 loss_thr: 0.3539 loss_db: 0.0813 2022/11/03 01:38:00 - mmengine - INFO - Epoch(train) [1097][55/63] lr: 2.3760e-04 eta: 1:11:39 time: 1.0095 data_time: 0.0287 memory: 14901 loss: 1.0047 loss_prob: 0.5302 loss_thr: 0.3838 loss_db: 0.0906 2022/11/03 01:38:05 - mmengine - INFO - Epoch(train) [1097][60/63] lr: 2.3760e-04 eta: 1:11:32 time: 0.9002 data_time: 0.0158 memory: 14901 loss: 1.0131 loss_prob: 0.5332 loss_thr: 0.3851 loss_db: 0.0948 2022/11/03 01:38:07 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:38:14 - mmengine - INFO - Epoch(train) [1098][5/63] lr: 2.3552e-04 eta: 1:11:32 time: 1.1100 data_time: 0.2580 memory: 14901 loss: 0.8915 loss_prob: 0.4615 loss_thr: 0.3489 loss_db: 0.0810 2022/11/03 01:38:17 - mmengine - INFO - Epoch(train) [1098][10/63] lr: 2.3552e-04 eta: 1:11:24 time: 1.0115 data_time: 0.2658 memory: 14901 loss: 0.8063 loss_prob: 0.4041 loss_thr: 0.3319 loss_db: 0.0704 2022/11/03 01:38:21 - mmengine - INFO - Epoch(train) [1098][15/63] lr: 2.3552e-04 eta: 1:11:24 time: 0.7005 data_time: 0.0156 memory: 14901 loss: 0.8433 loss_prob: 0.4284 loss_thr: 0.3390 loss_db: 0.0759 2022/11/03 01:38:25 - mmengine - INFO - Epoch(train) [1098][20/63] lr: 2.3552e-04 eta: 1:11:17 time: 0.7438 data_time: 0.0066 memory: 14901 loss: 0.9055 loss_prob: 0.4733 loss_thr: 0.3495 loss_db: 0.0827 2022/11/03 01:38:30 - mmengine - INFO - Epoch(train) [1098][25/63] lr: 2.3552e-04 eta: 1:11:17 time: 0.8737 data_time: 0.0393 memory: 14901 loss: 0.9387 loss_prob: 0.4985 loss_thr: 0.3569 loss_db: 0.0833 2022/11/03 01:38:33 - mmengine - INFO - Epoch(train) [1098][30/63] lr: 2.3552e-04 eta: 1:11:11 time: 0.8032 data_time: 0.0686 memory: 14901 loss: 0.9027 loss_prob: 0.4741 loss_thr: 0.3479 loss_db: 0.0806 2022/11/03 01:38:36 - mmengine - INFO - Epoch(train) [1098][35/63] lr: 2.3552e-04 eta: 1:11:11 time: 0.5993 data_time: 0.0347 memory: 14901 loss: 0.9573 loss_prob: 0.5082 loss_thr: 0.3626 loss_db: 0.0865 2022/11/03 01:38:39 - mmengine - INFO - Epoch(train) [1098][40/63] lr: 2.3552e-04 eta: 1:11:04 time: 0.6151 data_time: 0.0052 memory: 14901 loss: 1.0194 loss_prob: 0.5439 loss_thr: 0.3830 loss_db: 0.0925 2022/11/03 01:38:44 - mmengine - INFO - Epoch(train) [1098][45/63] lr: 2.3552e-04 eta: 1:11:04 time: 0.8136 data_time: 0.0080 memory: 14901 loss: 0.9274 loss_prob: 0.4748 loss_thr: 0.3694 loss_db: 0.0832 2022/11/03 01:38:48 - mmengine - INFO - Epoch(train) [1098][50/63] lr: 2.3552e-04 eta: 1:10:58 time: 0.8829 data_time: 0.0353 memory: 14901 loss: 0.9390 loss_prob: 0.4821 loss_thr: 0.3744 loss_db: 0.0825 2022/11/03 01:38:52 - mmengine - INFO - Epoch(train) [1098][55/63] lr: 2.3552e-04 eta: 1:10:58 time: 0.7999 data_time: 0.0368 memory: 14901 loss: 0.9583 loss_prob: 0.4924 loss_thr: 0.3811 loss_db: 0.0848 2022/11/03 01:38:56 - mmengine - INFO - Epoch(train) [1098][60/63] lr: 2.3552e-04 eta: 1:10:51 time: 0.7789 data_time: 0.0094 memory: 14901 loss: 0.9861 loss_prob: 0.5096 loss_thr: 0.3867 loss_db: 0.0898 2022/11/03 01:38:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:39:06 - mmengine - INFO - Epoch(train) [1099][5/63] lr: 2.3345e-04 eta: 1:10:51 time: 1.1810 data_time: 0.2524 memory: 14901 loss: 0.9187 loss_prob: 0.4871 loss_thr: 0.3480 loss_db: 0.0837 2022/11/03 01:39:10 - mmengine - INFO - Epoch(train) [1099][10/63] lr: 2.3345e-04 eta: 1:10:43 time: 1.1554 data_time: 0.2554 memory: 14901 loss: 0.8708 loss_prob: 0.4460 loss_thr: 0.3478 loss_db: 0.0770 2022/11/03 01:39:14 - mmengine - INFO - Epoch(train) [1099][15/63] lr: 2.3345e-04 eta: 1:10:43 time: 0.7973 data_time: 0.0095 memory: 14901 loss: 0.8611 loss_prob: 0.4310 loss_thr: 0.3541 loss_db: 0.0760 2022/11/03 01:39:17 - mmengine - INFO - Epoch(train) [1099][20/63] lr: 2.3345e-04 eta: 1:10:37 time: 0.6895 data_time: 0.0063 memory: 14901 loss: 0.9230 loss_prob: 0.4730 loss_thr: 0.3670 loss_db: 0.0831 2022/11/03 01:39:20 - mmengine - INFO - Epoch(train) [1099][25/63] lr: 2.3345e-04 eta: 1:10:37 time: 0.6021 data_time: 0.0267 memory: 14901 loss: 0.9671 loss_prob: 0.5073 loss_thr: 0.3742 loss_db: 0.0856 2022/11/03 01:39:24 - mmengine - INFO - Epoch(train) [1099][30/63] lr: 2.3345e-04 eta: 1:10:30 time: 0.6949 data_time: 0.0420 memory: 14901 loss: 0.8726 loss_prob: 0.4538 loss_thr: 0.3421 loss_db: 0.0766 2022/11/03 01:39:27 - mmengine - INFO - Epoch(train) [1099][35/63] lr: 2.3345e-04 eta: 1:10:30 time: 0.6878 data_time: 0.0355 memory: 14901 loss: 0.7962 loss_prob: 0.4073 loss_thr: 0.3159 loss_db: 0.0730 2022/11/03 01:39:31 - mmengine - INFO - Epoch(train) [1099][40/63] lr: 2.3345e-04 eta: 1:10:23 time: 0.7281 data_time: 0.0202 memory: 14901 loss: 0.8549 loss_prob: 0.4428 loss_thr: 0.3325 loss_db: 0.0796 2022/11/03 01:39:35 - mmengine - INFO - Epoch(train) [1099][45/63] lr: 2.3345e-04 eta: 1:10:23 time: 0.8600 data_time: 0.0062 memory: 14901 loss: 0.8686 loss_prob: 0.4481 loss_thr: 0.3421 loss_db: 0.0784 2022/11/03 01:39:38 - mmengine - INFO - Epoch(train) [1099][50/63] lr: 2.3345e-04 eta: 1:10:17 time: 0.7192 data_time: 0.0066 memory: 14901 loss: 0.8779 loss_prob: 0.4590 loss_thr: 0.3408 loss_db: 0.0781 2022/11/03 01:39:43 - mmengine - INFO - Epoch(train) [1099][55/63] lr: 2.3345e-04 eta: 1:10:17 time: 0.7765 data_time: 0.0102 memory: 14901 loss: 0.8962 loss_prob: 0.4692 loss_thr: 0.3452 loss_db: 0.0818 2022/11/03 01:39:47 - mmengine - INFO - Epoch(train) [1099][60/63] lr: 2.3345e-04 eta: 1:10:10 time: 0.8780 data_time: 0.0121 memory: 14901 loss: 0.9168 loss_prob: 0.4714 loss_thr: 0.3610 loss_db: 0.0843 2022/11/03 01:39:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:39:57 - mmengine - INFO - Epoch(train) [1100][5/63] lr: 2.3137e-04 eta: 1:10:10 time: 1.1962 data_time: 0.2484 memory: 14901 loss: 0.9170 loss_prob: 0.4753 loss_thr: 0.3596 loss_db: 0.0820 2022/11/03 01:40:01 - mmengine - INFO - Epoch(train) [1100][10/63] lr: 2.3137e-04 eta: 1:10:02 time: 1.1771 data_time: 0.2537 memory: 14901 loss: 0.8762 loss_prob: 0.4507 loss_thr: 0.3484 loss_db: 0.0771 2022/11/03 01:40:05 - mmengine - INFO - Epoch(train) [1100][15/63] lr: 2.3137e-04 eta: 1:10:02 time: 0.7909 data_time: 0.0144 memory: 14901 loss: 0.9132 loss_prob: 0.4680 loss_thr: 0.3634 loss_db: 0.0819 2022/11/03 01:40:08 - mmengine - INFO - Epoch(train) [1100][20/63] lr: 2.3137e-04 eta: 1:09:56 time: 0.7402 data_time: 0.0088 memory: 14901 loss: 0.9234 loss_prob: 0.4751 loss_thr: 0.3635 loss_db: 0.0847 2022/11/03 01:40:13 - mmengine - INFO - Epoch(train) [1100][25/63] lr: 2.3137e-04 eta: 1:09:56 time: 0.8065 data_time: 0.0185 memory: 14901 loss: 0.8818 loss_prob: 0.4558 loss_thr: 0.3452 loss_db: 0.0809 2022/11/03 01:40:16 - mmengine - INFO - Epoch(train) [1100][30/63] lr: 2.3137e-04 eta: 1:09:49 time: 0.7795 data_time: 0.0296 memory: 14901 loss: 0.9105 loss_prob: 0.4775 loss_thr: 0.3496 loss_db: 0.0833 2022/11/03 01:40:18 - mmengine - INFO - Epoch(train) [1100][35/63] lr: 2.3137e-04 eta: 1:09:49 time: 0.5366 data_time: 0.0198 memory: 14901 loss: 0.8778 loss_prob: 0.4625 loss_thr: 0.3358 loss_db: 0.0795 2022/11/03 01:40:22 - mmengine - INFO - Epoch(train) [1100][40/63] lr: 2.3137e-04 eta: 1:09:42 time: 0.5804 data_time: 0.0113 memory: 14901 loss: 0.9315 loss_prob: 0.4841 loss_thr: 0.3633 loss_db: 0.0841 2022/11/03 01:40:26 - mmengine - INFO - Epoch(train) [1100][45/63] lr: 2.3137e-04 eta: 1:09:42 time: 0.8057 data_time: 0.0084 memory: 14901 loss: 0.9390 loss_prob: 0.4868 loss_thr: 0.3669 loss_db: 0.0854 2022/11/03 01:40:30 - mmengine - INFO - Epoch(train) [1100][50/63] lr: 2.3137e-04 eta: 1:09:36 time: 0.8764 data_time: 0.0146 memory: 14901 loss: 0.9353 loss_prob: 0.4909 loss_thr: 0.3598 loss_db: 0.0846 2022/11/03 01:40:34 - mmengine - INFO - Epoch(train) [1100][55/63] lr: 2.3137e-04 eta: 1:09:36 time: 0.7151 data_time: 0.0265 memory: 14901 loss: 0.9140 loss_prob: 0.4822 loss_thr: 0.3479 loss_db: 0.0838 2022/11/03 01:40:38 - mmengine - INFO - Epoch(train) [1100][60/63] lr: 2.3137e-04 eta: 1:09:29 time: 0.7861 data_time: 0.0180 memory: 14901 loss: 0.9240 loss_prob: 0.4800 loss_thr: 0.3596 loss_db: 0.0844 2022/11/03 01:40:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:40:40 - mmengine - INFO - Saving checkpoint at 1100 epochs 2022/11/03 01:40:44 - mmengine - INFO - Epoch(val) [1100][5/500] eta: 1:09:29 time: 0.0459 data_time: 0.0052 memory: 14901 2022/11/03 01:40:44 - mmengine - INFO - Epoch(val) [1100][10/500] eta: 0:00:24 time: 0.0509 data_time: 0.0054 memory: 1008 2022/11/03 01:40:45 - mmengine - INFO - Epoch(val) [1100][15/500] eta: 0:00:24 time: 0.0437 data_time: 0.0031 memory: 1008 2022/11/03 01:40:45 - mmengine - INFO - Epoch(val) [1100][20/500] eta: 0:00:20 time: 0.0427 data_time: 0.0032 memory: 1008 2022/11/03 01:40:45 - mmengine - INFO - Epoch(val) [1100][25/500] eta: 0:00:20 time: 0.0448 data_time: 0.0036 memory: 1008 2022/11/03 01:40:45 - mmengine - INFO - Epoch(val) [1100][30/500] eta: 0:00:23 time: 0.0505 data_time: 0.0035 memory: 1008 2022/11/03 01:40:46 - mmengine - INFO - Epoch(val) [1100][35/500] eta: 0:00:23 time: 0.0496 data_time: 0.0032 memory: 1008 2022/11/03 01:40:46 - mmengine - INFO - Epoch(val) [1100][40/500] eta: 0:00:22 time: 0.0491 data_time: 0.0031 memory: 1008 2022/11/03 01:40:46 - mmengine - INFO - Epoch(val) [1100][45/500] eta: 0:00:22 time: 0.0496 data_time: 0.0029 memory: 1008 2022/11/03 01:40:46 - mmengine - INFO - Epoch(val) [1100][50/500] eta: 0:00:21 time: 0.0482 data_time: 0.0030 memory: 1008 2022/11/03 01:40:47 - mmengine - INFO - Epoch(val) [1100][55/500] eta: 0:00:21 time: 0.0513 data_time: 0.0031 memory: 1008 2022/11/03 01:40:47 - mmengine - INFO - Epoch(val) [1100][60/500] eta: 0:00:20 time: 0.0469 data_time: 0.0030 memory: 1008 2022/11/03 01:40:47 - mmengine - INFO - Epoch(val) [1100][65/500] eta: 0:00:20 time: 0.0480 data_time: 0.0029 memory: 1008 2022/11/03 01:40:47 - mmengine - INFO - Epoch(val) [1100][70/500] eta: 0:00:21 time: 0.0505 data_time: 0.0031 memory: 1008 2022/11/03 01:40:47 - mmengine - INFO - Epoch(val) [1100][75/500] eta: 0:00:21 time: 0.0430 data_time: 0.0030 memory: 1008 2022/11/03 01:40:48 - mmengine - INFO - Epoch(val) [1100][80/500] eta: 0:00:18 time: 0.0432 data_time: 0.0030 memory: 1008 2022/11/03 01:40:48 - mmengine - INFO - Epoch(val) [1100][85/500] eta: 0:00:18 time: 0.0455 data_time: 0.0028 memory: 1008 2022/11/03 01:40:48 - mmengine - INFO - Epoch(val) [1100][90/500] eta: 0:00:19 time: 0.0467 data_time: 0.0027 memory: 1008 2022/11/03 01:40:48 - mmengine - INFO - Epoch(val) [1100][95/500] eta: 0:00:19 time: 0.0516 data_time: 0.0041 memory: 1008 2022/11/03 01:40:49 - mmengine - INFO - Epoch(val) [1100][100/500] eta: 0:00:19 time: 0.0479 data_time: 0.0049 memory: 1008 2022/11/03 01:40:49 - mmengine - INFO - Epoch(val) [1100][105/500] eta: 0:00:19 time: 0.0437 data_time: 0.0045 memory: 1008 2022/11/03 01:40:49 - mmengine - INFO - Epoch(val) [1100][110/500] eta: 0:00:17 time: 0.0441 data_time: 0.0036 memory: 1008 2022/11/03 01:40:49 - mmengine - INFO - Epoch(val) [1100][115/500] eta: 0:00:17 time: 0.0436 data_time: 0.0028 memory: 1008 2022/11/03 01:40:50 - mmengine - INFO - Epoch(val) [1100][120/500] eta: 0:00:16 time: 0.0446 data_time: 0.0026 memory: 1008 2022/11/03 01:40:50 - mmengine - INFO - Epoch(val) [1100][125/500] eta: 0:00:16 time: 0.0461 data_time: 0.0030 memory: 1008 2022/11/03 01:40:50 - mmengine - INFO - Epoch(val) [1100][130/500] eta: 0:00:16 time: 0.0440 data_time: 0.0032 memory: 1008 2022/11/03 01:40:50 - mmengine - INFO - Epoch(val) [1100][135/500] eta: 0:00:16 time: 0.0408 data_time: 0.0028 memory: 1008 2022/11/03 01:40:50 - mmengine - INFO - Epoch(val) [1100][140/500] eta: 0:00:15 time: 0.0425 data_time: 0.0031 memory: 1008 2022/11/03 01:40:51 - mmengine - INFO - Epoch(val) [1100][145/500] eta: 0:00:15 time: 0.0459 data_time: 0.0029 memory: 1008 2022/11/03 01:40:51 - mmengine - INFO - Epoch(val) [1100][150/500] eta: 0:00:16 time: 0.0459 data_time: 0.0027 memory: 1008 2022/11/03 01:40:51 - mmengine - INFO - Epoch(val) [1100][155/500] eta: 0:00:16 time: 0.0482 data_time: 0.0028 memory: 1008 2022/11/03 01:40:51 - mmengine - INFO - Epoch(val) [1100][160/500] eta: 0:00:16 time: 0.0495 data_time: 0.0029 memory: 1008 2022/11/03 01:40:52 - mmengine - INFO - Epoch(val) [1100][165/500] eta: 0:00:16 time: 0.0476 data_time: 0.0032 memory: 1008 2022/11/03 01:40:52 - mmengine - INFO - Epoch(val) [1100][170/500] eta: 0:00:15 time: 0.0466 data_time: 0.0031 memory: 1008 2022/11/03 01:40:52 - mmengine - INFO - Epoch(val) [1100][175/500] eta: 0:00:15 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/03 01:40:52 - mmengine - INFO - Epoch(val) [1100][180/500] eta: 0:00:13 time: 0.0427 data_time: 0.0027 memory: 1008 2022/11/03 01:40:52 - mmengine - INFO - Epoch(val) [1100][185/500] eta: 0:00:13 time: 0.0445 data_time: 0.0027 memory: 1008 2022/11/03 01:40:53 - mmengine - INFO - Epoch(val) [1100][190/500] eta: 0:00:14 time: 0.0458 data_time: 0.0026 memory: 1008 2022/11/03 01:40:53 - mmengine - INFO - Epoch(val) [1100][195/500] eta: 0:00:14 time: 0.0442 data_time: 0.0026 memory: 1008 2022/11/03 01:40:53 - mmengine - INFO - Epoch(val) [1100][200/500] eta: 0:00:13 time: 0.0458 data_time: 0.0026 memory: 1008 2022/11/03 01:40:53 - mmengine - INFO - Epoch(val) [1100][205/500] eta: 0:00:13 time: 0.0454 data_time: 0.0027 memory: 1008 2022/11/03 01:40:54 - mmengine - INFO - Epoch(val) [1100][210/500] eta: 0:00:13 time: 0.0461 data_time: 0.0032 memory: 1008 2022/11/03 01:40:54 - mmengine - INFO - Epoch(val) [1100][215/500] eta: 0:00:13 time: 0.0473 data_time: 0.0032 memory: 1008 2022/11/03 01:40:54 - mmengine - INFO - Epoch(val) [1100][220/500] eta: 0:00:12 time: 0.0459 data_time: 0.0030 memory: 1008 2022/11/03 01:40:54 - mmengine - INFO - Epoch(val) [1100][225/500] eta: 0:00:12 time: 0.0477 data_time: 0.0031 memory: 1008 2022/11/03 01:40:55 - mmengine - INFO - Epoch(val) [1100][230/500] eta: 0:00:11 time: 0.0423 data_time: 0.0030 memory: 1008 2022/11/03 01:40:55 - mmengine - INFO - Epoch(val) [1100][235/500] eta: 0:00:11 time: 0.0462 data_time: 0.0032 memory: 1008 2022/11/03 01:40:55 - mmengine - INFO - Epoch(val) [1100][240/500] eta: 0:00:13 time: 0.0517 data_time: 0.0034 memory: 1008 2022/11/03 01:40:55 - mmengine - INFO - Epoch(val) [1100][245/500] eta: 0:00:13 time: 0.0443 data_time: 0.0030 memory: 1008 2022/11/03 01:40:55 - mmengine - INFO - Epoch(val) [1100][250/500] eta: 0:00:10 time: 0.0432 data_time: 0.0027 memory: 1008 2022/11/03 01:40:56 - mmengine - INFO - Epoch(val) [1100][255/500] eta: 0:00:10 time: 0.0449 data_time: 0.0028 memory: 1008 2022/11/03 01:40:56 - mmengine - INFO - Epoch(val) [1100][260/500] eta: 0:00:10 time: 0.0436 data_time: 0.0028 memory: 1008 2022/11/03 01:40:56 - mmengine - INFO - Epoch(val) [1100][265/500] eta: 0:00:10 time: 0.0447 data_time: 0.0029 memory: 1008 2022/11/03 01:40:56 - mmengine - INFO - Epoch(val) [1100][270/500] eta: 0:00:10 time: 0.0450 data_time: 0.0029 memory: 1008 2022/11/03 01:40:57 - mmengine - INFO - Epoch(val) [1100][275/500] eta: 0:00:10 time: 0.0448 data_time: 0.0028 memory: 1008 2022/11/03 01:40:57 - mmengine - INFO - Epoch(val) [1100][280/500] eta: 0:00:10 time: 0.0469 data_time: 0.0027 memory: 1008 2022/11/03 01:40:57 - mmengine - INFO - Epoch(val) [1100][285/500] eta: 0:00:10 time: 0.0464 data_time: 0.0026 memory: 1008 2022/11/03 01:40:57 - mmengine - INFO - Epoch(val) [1100][290/500] eta: 0:00:10 time: 0.0498 data_time: 0.0029 memory: 1008 2022/11/03 01:40:58 - mmengine - INFO - Epoch(val) [1100][295/500] eta: 0:00:10 time: 0.0503 data_time: 0.0032 memory: 1008 2022/11/03 01:40:58 - mmengine - INFO - Epoch(val) [1100][300/500] eta: 0:00:08 time: 0.0436 data_time: 0.0028 memory: 1008 2022/11/03 01:40:58 - mmengine - INFO - Epoch(val) [1100][305/500] eta: 0:00:08 time: 0.0420 data_time: 0.0025 memory: 1008 2022/11/03 01:40:58 - mmengine - INFO - Epoch(val) [1100][310/500] eta: 0:00:08 time: 0.0440 data_time: 0.0026 memory: 1008 2022/11/03 01:40:58 - mmengine - INFO - Epoch(val) [1100][315/500] eta: 0:00:08 time: 0.0468 data_time: 0.0027 memory: 1008 2022/11/03 01:40:59 - mmengine - INFO - Epoch(val) [1100][320/500] eta: 0:00:07 time: 0.0440 data_time: 0.0027 memory: 1008 2022/11/03 01:40:59 - mmengine - INFO - Epoch(val) [1100][325/500] eta: 0:00:07 time: 0.0515 data_time: 0.0026 memory: 1008 2022/11/03 01:40:59 - mmengine - INFO - Epoch(val) [1100][330/500] eta: 0:00:08 time: 0.0525 data_time: 0.0025 memory: 1008 2022/11/03 01:40:59 - mmengine - INFO - Epoch(val) [1100][335/500] eta: 0:00:08 time: 0.0416 data_time: 0.0024 memory: 1008 2022/11/03 01:41:00 - mmengine - INFO - Epoch(val) [1100][340/500] eta: 0:00:08 time: 0.0553 data_time: 0.0027 memory: 1008 2022/11/03 01:41:00 - mmengine - INFO - Epoch(val) [1100][345/500] eta: 0:00:08 time: 0.0593 data_time: 0.0032 memory: 1008 2022/11/03 01:41:00 - mmengine - INFO - Epoch(val) [1100][350/500] eta: 0:00:07 time: 0.0522 data_time: 0.0032 memory: 1008 2022/11/03 01:41:01 - mmengine - INFO - Epoch(val) [1100][355/500] eta: 0:00:07 time: 0.0522 data_time: 0.0036 memory: 1008 2022/11/03 01:41:01 - mmengine - INFO - Epoch(val) [1100][360/500] eta: 0:00:06 time: 0.0469 data_time: 0.0035 memory: 1008 2022/11/03 01:41:01 - mmengine - INFO - Epoch(val) [1100][365/500] eta: 0:00:06 time: 0.0448 data_time: 0.0027 memory: 1008 2022/11/03 01:41:01 - mmengine - INFO - Epoch(val) [1100][370/500] eta: 0:00:05 time: 0.0440 data_time: 0.0028 memory: 1008 2022/11/03 01:41:01 - mmengine - INFO - Epoch(val) [1100][375/500] eta: 0:00:05 time: 0.0445 data_time: 0.0029 memory: 1008 2022/11/03 01:41:02 - mmengine - INFO - Epoch(val) [1100][380/500] eta: 0:00:05 time: 0.0472 data_time: 0.0027 memory: 1008 2022/11/03 01:41:02 - mmengine - INFO - Epoch(val) [1100][385/500] eta: 0:00:05 time: 0.0479 data_time: 0.0029 memory: 1008 2022/11/03 01:41:02 - mmengine - INFO - Epoch(val) [1100][390/500] eta: 0:00:04 time: 0.0443 data_time: 0.0029 memory: 1008 2022/11/03 01:41:02 - mmengine - INFO - Epoch(val) [1100][395/500] eta: 0:00:04 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/03 01:41:03 - mmengine - INFO - Epoch(val) [1100][400/500] eta: 0:00:04 time: 0.0421 data_time: 0.0034 memory: 1008 2022/11/03 01:41:03 - mmengine - INFO - Epoch(val) [1100][405/500] eta: 0:00:04 time: 0.0459 data_time: 0.0035 memory: 1008 2022/11/03 01:41:03 - mmengine - INFO - Epoch(val) [1100][410/500] eta: 0:00:04 time: 0.0457 data_time: 0.0028 memory: 1008 2022/11/03 01:41:03 - mmengine - INFO - Epoch(val) [1100][415/500] eta: 0:00:04 time: 0.0472 data_time: 0.0040 memory: 1008 2022/11/03 01:41:03 - mmengine - INFO - Epoch(val) [1100][420/500] eta: 0:00:03 time: 0.0435 data_time: 0.0040 memory: 1008 2022/11/03 01:41:04 - mmengine - INFO - Epoch(val) [1100][425/500] eta: 0:00:03 time: 0.0396 data_time: 0.0027 memory: 1008 2022/11/03 01:41:04 - mmengine - INFO - Epoch(val) [1100][430/500] eta: 0:00:03 time: 0.0433 data_time: 0.0028 memory: 1008 2022/11/03 01:41:04 - mmengine - INFO - Epoch(val) [1100][435/500] eta: 0:00:03 time: 0.0430 data_time: 0.0028 memory: 1008 2022/11/03 01:41:04 - mmengine - INFO - Epoch(val) [1100][440/500] eta: 0:00:02 time: 0.0451 data_time: 0.0030 memory: 1008 2022/11/03 01:41:05 - mmengine - INFO - Epoch(val) [1100][445/500] eta: 0:00:02 time: 0.0503 data_time: 0.0032 memory: 1008 2022/11/03 01:41:05 - mmengine - INFO - Epoch(val) [1100][450/500] eta: 0:00:02 time: 0.0484 data_time: 0.0029 memory: 1008 2022/11/03 01:41:05 - mmengine - INFO - Epoch(val) [1100][455/500] eta: 0:00:02 time: 0.0444 data_time: 0.0027 memory: 1008 2022/11/03 01:41:05 - mmengine - INFO - Epoch(val) [1100][460/500] eta: 0:00:01 time: 0.0443 data_time: 0.0030 memory: 1008 2022/11/03 01:41:05 - mmengine - INFO - Epoch(val) [1100][465/500] eta: 0:00:01 time: 0.0432 data_time: 0.0033 memory: 1008 2022/11/03 01:41:06 - mmengine - INFO - Epoch(val) [1100][470/500] eta: 0:00:01 time: 0.0429 data_time: 0.0032 memory: 1008 2022/11/03 01:41:06 - mmengine - INFO - Epoch(val) [1100][475/500] eta: 0:00:01 time: 0.0445 data_time: 0.0033 memory: 1008 2022/11/03 01:41:06 - mmengine - INFO - Epoch(val) [1100][480/500] eta: 0:00:00 time: 0.0425 data_time: 0.0030 memory: 1008 2022/11/03 01:41:06 - mmengine - INFO - Epoch(val) [1100][485/500] eta: 0:00:00 time: 0.0401 data_time: 0.0029 memory: 1008 2022/11/03 01:41:07 - mmengine - INFO - Epoch(val) [1100][490/500] eta: 0:00:00 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/03 01:41:07 - mmengine - INFO - Epoch(val) [1100][495/500] eta: 0:00:00 time: 0.0423 data_time: 0.0026 memory: 1008 2022/11/03 01:41:07 - mmengine - INFO - Epoch(val) [1100][500/500] eta: 0:00:00 time: 0.0407 data_time: 0.0027 memory: 1008 2022/11/03 01:41:07 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8233, precision: 0.7634, hmean: 0.7922 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8233, precision: 0.8047, hmean: 0.8139 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8233, precision: 0.8329, hmean: 0.8281 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8209, precision: 0.8559, hmean: 0.8380 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8084, precision: 0.8754, hmean: 0.8406 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7130, precision: 0.9153, hmean: 0.8016 2022/11/03 01:41:07 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1825, precision: 0.9619, hmean: 0.3068 2022/11/03 01:41:07 - mmengine - INFO - Epoch(val) [1100][500/500] icdar/precision: 0.8754 icdar/recall: 0.8084 icdar/hmean: 0.8406 2022/11/03 01:41:16 - mmengine - INFO - Epoch(train) [1101][5/63] lr: 2.2928e-04 eta: 0:00:00 time: 1.1999 data_time: 0.2670 memory: 14901 loss: 0.8862 loss_prob: 0.4538 loss_thr: 0.3524 loss_db: 0.0799 2022/11/03 01:41:21 - mmengine - INFO - Epoch(train) [1101][10/63] lr: 2.2928e-04 eta: 1:09:21 time: 1.4381 data_time: 0.2693 memory: 14901 loss: 0.7920 loss_prob: 0.4036 loss_thr: 0.3165 loss_db: 0.0719 2022/11/03 01:41:24 - mmengine - INFO - Epoch(train) [1101][15/63] lr: 2.2928e-04 eta: 1:09:21 time: 0.8124 data_time: 0.0096 memory: 14901 loss: 0.7721 loss_prob: 0.3994 loss_thr: 0.3024 loss_db: 0.0703 2022/11/03 01:41:26 - mmengine - INFO - Epoch(train) [1101][20/63] lr: 2.2928e-04 eta: 1:09:15 time: 0.5058 data_time: 0.0058 memory: 14901 loss: 0.8848 loss_prob: 0.4595 loss_thr: 0.3466 loss_db: 0.0788 2022/11/03 01:41:30 - mmengine - INFO - Epoch(train) [1101][25/63] lr: 2.2928e-04 eta: 1:09:15 time: 0.5785 data_time: 0.0387 memory: 14901 loss: 0.9384 loss_prob: 0.4928 loss_thr: 0.3627 loss_db: 0.0828 2022/11/03 01:41:32 - mmengine - INFO - Epoch(train) [1101][30/63] lr: 2.2928e-04 eta: 1:09:08 time: 0.6065 data_time: 0.0395 memory: 14901 loss: 0.8957 loss_prob: 0.4651 loss_thr: 0.3510 loss_db: 0.0796 2022/11/03 01:41:35 - mmengine - INFO - Epoch(train) [1101][35/63] lr: 2.2928e-04 eta: 1:09:08 time: 0.5661 data_time: 0.0061 memory: 14901 loss: 0.8748 loss_prob: 0.4537 loss_thr: 0.3416 loss_db: 0.0795 2022/11/03 01:41:38 - mmengine - INFO - Epoch(train) [1101][40/63] lr: 2.2928e-04 eta: 1:09:01 time: 0.5729 data_time: 0.0059 memory: 14901 loss: 0.8573 loss_prob: 0.4480 loss_thr: 0.3305 loss_db: 0.0788 2022/11/03 01:41:41 - mmengine - INFO - Epoch(train) [1101][45/63] lr: 2.2928e-04 eta: 1:09:01 time: 0.5513 data_time: 0.0101 memory: 14901 loss: 0.9097 loss_prob: 0.4761 loss_thr: 0.3517 loss_db: 0.0819 2022/11/03 01:41:44 - mmengine - INFO - Epoch(train) [1101][50/63] lr: 2.2928e-04 eta: 1:08:55 time: 0.5807 data_time: 0.0279 memory: 14901 loss: 0.9319 loss_prob: 0.4839 loss_thr: 0.3657 loss_db: 0.0823 2022/11/03 01:41:47 - mmengine - INFO - Epoch(train) [1101][55/63] lr: 2.2928e-04 eta: 1:08:55 time: 0.6390 data_time: 0.0242 memory: 14901 loss: 0.8642 loss_prob: 0.4433 loss_thr: 0.3433 loss_db: 0.0775 2022/11/03 01:41:50 - mmengine - INFO - Epoch(train) [1101][60/63] lr: 2.2928e-04 eta: 1:08:48 time: 0.6463 data_time: 0.0061 memory: 14901 loss: 0.9055 loss_prob: 0.4708 loss_thr: 0.3528 loss_db: 0.0819 2022/11/03 01:41:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:42:02 - mmengine - INFO - Epoch(train) [1102][5/63] lr: 2.2720e-04 eta: 1:08:48 time: 1.2544 data_time: 0.3131 memory: 14901 loss: 0.8277 loss_prob: 0.4255 loss_thr: 0.3271 loss_db: 0.0751 2022/11/03 01:42:06 - mmengine - INFO - Epoch(train) [1102][10/63] lr: 2.2720e-04 eta: 1:08:40 time: 1.3499 data_time: 0.3085 memory: 14901 loss: 0.8548 loss_prob: 0.4424 loss_thr: 0.3359 loss_db: 0.0765 2022/11/03 01:42:10 - mmengine - INFO - Epoch(train) [1102][15/63] lr: 2.2720e-04 eta: 1:08:40 time: 0.7813 data_time: 0.0057 memory: 14901 loss: 0.9269 loss_prob: 0.4813 loss_thr: 0.3617 loss_db: 0.0840 2022/11/03 01:42:14 - mmengine - INFO - Epoch(train) [1102][20/63] lr: 2.2720e-04 eta: 1:08:33 time: 0.8362 data_time: 0.0066 memory: 14901 loss: 0.9448 loss_prob: 0.4945 loss_thr: 0.3649 loss_db: 0.0854 2022/11/03 01:42:18 - mmengine - INFO - Epoch(train) [1102][25/63] lr: 2.2720e-04 eta: 1:08:33 time: 0.8305 data_time: 0.0332 memory: 14901 loss: 0.9099 loss_prob: 0.4732 loss_thr: 0.3575 loss_db: 0.0792 2022/11/03 01:42:21 - mmengine - INFO - Epoch(train) [1102][30/63] lr: 2.2720e-04 eta: 1:08:27 time: 0.6680 data_time: 0.0442 memory: 14901 loss: 0.8723 loss_prob: 0.4392 loss_thr: 0.3561 loss_db: 0.0769 2022/11/03 01:42:24 - mmengine - INFO - Epoch(train) [1102][35/63] lr: 2.2720e-04 eta: 1:08:27 time: 0.5897 data_time: 0.0171 memory: 14901 loss: 0.8816 loss_prob: 0.4457 loss_thr: 0.3570 loss_db: 0.0789 2022/11/03 01:42:28 - mmengine - INFO - Epoch(train) [1102][40/63] lr: 2.2720e-04 eta: 1:08:20 time: 0.7422 data_time: 0.0063 memory: 14901 loss: 0.8912 loss_prob: 0.4543 loss_thr: 0.3577 loss_db: 0.0793 2022/11/03 01:42:32 - mmengine - INFO - Epoch(train) [1102][45/63] lr: 2.2720e-04 eta: 1:08:20 time: 0.8597 data_time: 0.0094 memory: 14901 loss: 0.9202 loss_prob: 0.4718 loss_thr: 0.3654 loss_db: 0.0830 2022/11/03 01:42:37 - mmengine - INFO - Epoch(train) [1102][50/63] lr: 2.2720e-04 eta: 1:08:14 time: 0.8828 data_time: 0.0248 memory: 14901 loss: 0.9079 loss_prob: 0.4714 loss_thr: 0.3550 loss_db: 0.0816 2022/11/03 01:42:40 - mmengine - INFO - Epoch(train) [1102][55/63] lr: 2.2720e-04 eta: 1:08:14 time: 0.7719 data_time: 0.0275 memory: 14901 loss: 0.9292 loss_prob: 0.4838 loss_thr: 0.3626 loss_db: 0.0828 2022/11/03 01:42:44 - mmengine - INFO - Epoch(train) [1102][60/63] lr: 2.2720e-04 eta: 1:08:07 time: 0.6605 data_time: 0.0110 memory: 14901 loss: 0.9025 loss_prob: 0.4635 loss_thr: 0.3580 loss_db: 0.0810 2022/11/03 01:42:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:42:54 - mmengine - INFO - Epoch(train) [1103][5/63] lr: 2.2511e-04 eta: 1:08:07 time: 1.2391 data_time: 0.2013 memory: 14901 loss: 0.8508 loss_prob: 0.4385 loss_thr: 0.3364 loss_db: 0.0758 2022/11/03 01:42:59 - mmengine - INFO - Epoch(train) [1103][10/63] lr: 2.2511e-04 eta: 1:07:59 time: 1.3350 data_time: 0.2177 memory: 14901 loss: 0.9314 loss_prob: 0.4943 loss_thr: 0.3524 loss_db: 0.0848 2022/11/03 01:43:04 - mmengine - INFO - Epoch(train) [1103][15/63] lr: 2.2511e-04 eta: 1:07:59 time: 0.9917 data_time: 0.0247 memory: 14901 loss: 0.9647 loss_prob: 0.5074 loss_thr: 0.3714 loss_db: 0.0859 2022/11/03 01:43:08 - mmengine - INFO - Epoch(train) [1103][20/63] lr: 2.2511e-04 eta: 1:07:52 time: 0.8929 data_time: 0.0113 memory: 14901 loss: 0.9007 loss_prob: 0.4675 loss_thr: 0.3539 loss_db: 0.0794 2022/11/03 01:43:12 - mmengine - INFO - Epoch(train) [1103][25/63] lr: 2.2511e-04 eta: 1:07:52 time: 0.7984 data_time: 0.0100 memory: 14901 loss: 0.8884 loss_prob: 0.4645 loss_thr: 0.3435 loss_db: 0.0804 2022/11/03 01:43:15 - mmengine - INFO - Epoch(train) [1103][30/63] lr: 2.2511e-04 eta: 1:07:46 time: 0.7338 data_time: 0.0214 memory: 14901 loss: 0.8553 loss_prob: 0.4405 loss_thr: 0.3366 loss_db: 0.0782 2022/11/03 01:43:19 - mmengine - INFO - Epoch(train) [1103][35/63] lr: 2.2511e-04 eta: 1:07:46 time: 0.6779 data_time: 0.0356 memory: 14901 loss: 0.8019 loss_prob: 0.4073 loss_thr: 0.3217 loss_db: 0.0729 2022/11/03 01:43:23 - mmengine - INFO - Epoch(train) [1103][40/63] lr: 2.2511e-04 eta: 1:07:39 time: 0.7666 data_time: 0.0243 memory: 14901 loss: 0.9014 loss_prob: 0.4713 loss_thr: 0.3475 loss_db: 0.0826 2022/11/03 01:43:28 - mmengine - INFO - Epoch(train) [1103][45/63] lr: 2.2511e-04 eta: 1:07:39 time: 0.9094 data_time: 0.0085 memory: 14901 loss: 0.9113 loss_prob: 0.4738 loss_thr: 0.3551 loss_db: 0.0824 2022/11/03 01:43:32 - mmengine - INFO - Epoch(train) [1103][50/63] lr: 2.2511e-04 eta: 1:07:33 time: 0.8863 data_time: 0.0121 memory: 14901 loss: 0.8201 loss_prob: 0.4137 loss_thr: 0.3347 loss_db: 0.0718 2022/11/03 01:43:35 - mmengine - INFO - Epoch(train) [1103][55/63] lr: 2.2511e-04 eta: 1:07:33 time: 0.7213 data_time: 0.0263 memory: 14901 loss: 0.8340 loss_prob: 0.4229 loss_thr: 0.3372 loss_db: 0.0738 2022/11/03 01:43:39 - mmengine - INFO - Epoch(train) [1103][60/63] lr: 2.2511e-04 eta: 1:07:26 time: 0.6957 data_time: 0.0194 memory: 14901 loss: 0.8536 loss_prob: 0.4310 loss_thr: 0.3462 loss_db: 0.0765 2022/11/03 01:43:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:43:49 - mmengine - INFO - Epoch(train) [1104][5/63] lr: 2.2302e-04 eta: 1:07:26 time: 1.1922 data_time: 0.2850 memory: 14901 loss: 0.9766 loss_prob: 0.5083 loss_thr: 0.3804 loss_db: 0.0880 2022/11/03 01:43:53 - mmengine - INFO - Epoch(train) [1104][10/63] lr: 2.2302e-04 eta: 1:07:18 time: 1.2509 data_time: 0.2848 memory: 14901 loss: 0.8931 loss_prob: 0.4614 loss_thr: 0.3499 loss_db: 0.0817 2022/11/03 01:43:59 - mmengine - INFO - Epoch(train) [1104][15/63] lr: 2.2302e-04 eta: 1:07:18 time: 0.9747 data_time: 0.0082 memory: 14901 loss: 0.8623 loss_prob: 0.4400 loss_thr: 0.3450 loss_db: 0.0774 2022/11/03 01:44:03 - mmengine - INFO - Epoch(train) [1104][20/63] lr: 2.2302e-04 eta: 1:07:12 time: 0.9631 data_time: 0.0066 memory: 14901 loss: 0.8719 loss_prob: 0.4490 loss_thr: 0.3452 loss_db: 0.0777 2022/11/03 01:44:06 - mmengine - INFO - Epoch(train) [1104][25/63] lr: 2.2302e-04 eta: 1:07:12 time: 0.7132 data_time: 0.0202 memory: 14901 loss: 0.9069 loss_prob: 0.4778 loss_thr: 0.3479 loss_db: 0.0813 2022/11/03 01:44:09 - mmengine - INFO - Epoch(train) [1104][30/63] lr: 2.2302e-04 eta: 1:07:05 time: 0.6145 data_time: 0.0349 memory: 14901 loss: 1.0168 loss_prob: 0.5475 loss_thr: 0.3752 loss_db: 0.0940 2022/11/03 01:44:12 - mmengine - INFO - Epoch(train) [1104][35/63] lr: 2.2302e-04 eta: 1:07:05 time: 0.6718 data_time: 0.0250 memory: 14901 loss: 0.9417 loss_prob: 0.4977 loss_thr: 0.3562 loss_db: 0.0878 2022/11/03 01:44:15 - mmengine - INFO - Epoch(train) [1104][40/63] lr: 2.2302e-04 eta: 1:06:58 time: 0.6072 data_time: 0.0106 memory: 14901 loss: 0.8317 loss_prob: 0.4218 loss_thr: 0.3349 loss_db: 0.0750 2022/11/03 01:44:19 - mmengine - INFO - Epoch(train) [1104][45/63] lr: 2.2302e-04 eta: 1:06:58 time: 0.6692 data_time: 0.0055 memory: 14901 loss: 0.9250 loss_prob: 0.4738 loss_thr: 0.3693 loss_db: 0.0820 2022/11/03 01:44:22 - mmengine - INFO - Epoch(train) [1104][50/63] lr: 2.2302e-04 eta: 1:06:52 time: 0.7336 data_time: 0.0225 memory: 14901 loss: 0.9494 loss_prob: 0.4891 loss_thr: 0.3765 loss_db: 0.0839 2022/11/03 01:44:25 - mmengine - INFO - Epoch(train) [1104][55/63] lr: 2.2302e-04 eta: 1:06:52 time: 0.5883 data_time: 0.0226 memory: 14901 loss: 0.8781 loss_prob: 0.4495 loss_thr: 0.3508 loss_db: 0.0778 2022/11/03 01:44:29 - mmengine - INFO - Epoch(train) [1104][60/63] lr: 2.2302e-04 eta: 1:06:45 time: 0.6384 data_time: 0.0069 memory: 14901 loss: 0.8410 loss_prob: 0.4353 loss_thr: 0.3283 loss_db: 0.0774 2022/11/03 01:44:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:44:36 - mmengine - INFO - Epoch(train) [1105][5/63] lr: 2.2093e-04 eta: 1:06:45 time: 0.8968 data_time: 0.2568 memory: 14901 loss: 0.9788 loss_prob: 0.5121 loss_thr: 0.3775 loss_db: 0.0892 2022/11/03 01:44:41 - mmengine - INFO - Epoch(train) [1105][10/63] lr: 2.2093e-04 eta: 1:06:37 time: 1.1072 data_time: 0.2579 memory: 14901 loss: 0.9494 loss_prob: 0.4926 loss_thr: 0.3707 loss_db: 0.0861 2022/11/03 01:44:46 - mmengine - INFO - Epoch(train) [1105][15/63] lr: 2.2093e-04 eta: 1:06:37 time: 0.9750 data_time: 0.0070 memory: 14901 loss: 0.9178 loss_prob: 0.4780 loss_thr: 0.3569 loss_db: 0.0829 2022/11/03 01:44:50 - mmengine - INFO - Epoch(train) [1105][20/63] lr: 2.2093e-04 eta: 1:06:30 time: 0.8849 data_time: 0.0069 memory: 14901 loss: 0.8838 loss_prob: 0.4541 loss_thr: 0.3494 loss_db: 0.0804 2022/11/03 01:44:53 - mmengine - INFO - Epoch(train) [1105][25/63] lr: 2.2093e-04 eta: 1:06:30 time: 0.6507 data_time: 0.0266 memory: 14901 loss: 0.8731 loss_prob: 0.4513 loss_thr: 0.3419 loss_db: 0.0799 2022/11/03 01:44:58 - mmengine - INFO - Epoch(train) [1105][30/63] lr: 2.2093e-04 eta: 1:06:24 time: 0.7862 data_time: 0.0383 memory: 14901 loss: 0.8834 loss_prob: 0.4588 loss_thr: 0.3465 loss_db: 0.0781 2022/11/03 01:45:02 - mmengine - INFO - Epoch(train) [1105][35/63] lr: 2.2093e-04 eta: 1:06:24 time: 0.8872 data_time: 0.0182 memory: 14901 loss: 0.9030 loss_prob: 0.4681 loss_thr: 0.3551 loss_db: 0.0799 2022/11/03 01:45:04 - mmengine - INFO - Epoch(train) [1105][40/63] lr: 2.2093e-04 eta: 1:06:17 time: 0.6401 data_time: 0.0055 memory: 14901 loss: 0.8829 loss_prob: 0.4550 loss_thr: 0.3469 loss_db: 0.0810 2022/11/03 01:45:07 - mmengine - INFO - Epoch(train) [1105][45/63] lr: 2.2093e-04 eta: 1:06:17 time: 0.5715 data_time: 0.0053 memory: 14901 loss: 0.8161 loss_prob: 0.4134 loss_thr: 0.3277 loss_db: 0.0750 2022/11/03 01:45:12 - mmengine - INFO - Epoch(train) [1105][50/63] lr: 2.2093e-04 eta: 1:06:11 time: 0.7746 data_time: 0.0152 memory: 14901 loss: 0.8185 loss_prob: 0.4171 loss_thr: 0.3278 loss_db: 0.0736 2022/11/03 01:45:17 - mmengine - INFO - Epoch(train) [1105][55/63] lr: 2.2093e-04 eta: 1:06:11 time: 0.9630 data_time: 0.0255 memory: 14901 loss: 0.8446 loss_prob: 0.4350 loss_thr: 0.3346 loss_db: 0.0750 2022/11/03 01:45:21 - mmengine - INFO - Epoch(train) [1105][60/63] lr: 2.2093e-04 eta: 1:06:04 time: 0.8989 data_time: 0.0160 memory: 14901 loss: 0.8728 loss_prob: 0.4514 loss_thr: 0.3439 loss_db: 0.0775 2022/11/03 01:45:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:45:29 - mmengine - INFO - Epoch(train) [1106][5/63] lr: 2.1884e-04 eta: 1:06:04 time: 0.9731 data_time: 0.2225 memory: 14901 loss: 0.8587 loss_prob: 0.4480 loss_thr: 0.3322 loss_db: 0.0785 2022/11/03 01:45:32 - mmengine - INFO - Epoch(train) [1106][10/63] lr: 2.1884e-04 eta: 1:05:56 time: 1.0164 data_time: 0.2231 memory: 14901 loss: 0.8104 loss_prob: 0.4145 loss_thr: 0.3209 loss_db: 0.0750 2022/11/03 01:45:37 - mmengine - INFO - Epoch(train) [1106][15/63] lr: 2.1884e-04 eta: 1:05:56 time: 0.7888 data_time: 0.0073 memory: 14901 loss: 0.8639 loss_prob: 0.4401 loss_thr: 0.3450 loss_db: 0.0788 2022/11/03 01:45:40 - mmengine - INFO - Epoch(train) [1106][20/63] lr: 2.1884e-04 eta: 1:05:49 time: 0.7356 data_time: 0.0065 memory: 14901 loss: 0.9148 loss_prob: 0.4703 loss_thr: 0.3596 loss_db: 0.0849 2022/11/03 01:45:43 - mmengine - INFO - Epoch(train) [1106][25/63] lr: 2.1884e-04 eta: 1:05:49 time: 0.6216 data_time: 0.0284 memory: 14901 loss: 0.9008 loss_prob: 0.4673 loss_thr: 0.3504 loss_db: 0.0831 2022/11/03 01:45:47 - mmengine - INFO - Epoch(train) [1106][30/63] lr: 2.1884e-04 eta: 1:05:43 time: 0.7468 data_time: 0.0412 memory: 14901 loss: 0.9292 loss_prob: 0.4812 loss_thr: 0.3643 loss_db: 0.0837 2022/11/03 01:45:51 - mmengine - INFO - Epoch(train) [1106][35/63] lr: 2.1884e-04 eta: 1:05:43 time: 0.7989 data_time: 0.0184 memory: 14901 loss: 0.9537 loss_prob: 0.4895 loss_thr: 0.3792 loss_db: 0.0850 2022/11/03 01:45:54 - mmengine - INFO - Epoch(train) [1106][40/63] lr: 2.1884e-04 eta: 1:05:36 time: 0.7163 data_time: 0.0071 memory: 14901 loss: 0.9243 loss_prob: 0.4772 loss_thr: 0.3648 loss_db: 0.0823 2022/11/03 01:45:58 - mmengine - INFO - Epoch(train) [1106][45/63] lr: 2.1884e-04 eta: 1:05:36 time: 0.6305 data_time: 0.0071 memory: 14901 loss: 0.8814 loss_prob: 0.4557 loss_thr: 0.3477 loss_db: 0.0780 2022/11/03 01:46:01 - mmengine - INFO - Epoch(train) [1106][50/63] lr: 2.1884e-04 eta: 1:05:30 time: 0.6833 data_time: 0.0159 memory: 14901 loss: 0.7973 loss_prob: 0.4075 loss_thr: 0.3181 loss_db: 0.0717 2022/11/03 01:46:05 - mmengine - INFO - Epoch(train) [1106][55/63] lr: 2.1884e-04 eta: 1:05:30 time: 0.7624 data_time: 0.0231 memory: 14901 loss: 0.7932 loss_prob: 0.4053 loss_thr: 0.3145 loss_db: 0.0734 2022/11/03 01:46:08 - mmengine - INFO - Epoch(train) [1106][60/63] lr: 2.1884e-04 eta: 1:05:23 time: 0.6612 data_time: 0.0132 memory: 14901 loss: 0.8273 loss_prob: 0.4256 loss_thr: 0.3264 loss_db: 0.0754 2022/11/03 01:46:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:46:17 - mmengine - INFO - Epoch(train) [1107][5/63] lr: 2.1674e-04 eta: 1:05:23 time: 1.0674 data_time: 0.2623 memory: 14901 loss: 0.8859 loss_prob: 0.4495 loss_thr: 0.3573 loss_db: 0.0791 2022/11/03 01:46:21 - mmengine - INFO - Epoch(train) [1107][10/63] lr: 2.1674e-04 eta: 1:05:15 time: 1.0324 data_time: 0.2619 memory: 14901 loss: 0.8289 loss_prob: 0.4202 loss_thr: 0.3343 loss_db: 0.0744 2022/11/03 01:46:24 - mmengine - INFO - Epoch(train) [1107][15/63] lr: 2.1674e-04 eta: 1:05:15 time: 0.6708 data_time: 0.0058 memory: 14901 loss: 0.8494 loss_prob: 0.4386 loss_thr: 0.3341 loss_db: 0.0766 2022/11/03 01:46:28 - mmengine - INFO - Epoch(train) [1107][20/63] lr: 2.1674e-04 eta: 1:05:08 time: 0.7917 data_time: 0.0068 memory: 14901 loss: 0.9028 loss_prob: 0.4740 loss_thr: 0.3477 loss_db: 0.0810 2022/11/03 01:46:33 - mmengine - INFO - Epoch(train) [1107][25/63] lr: 2.1674e-04 eta: 1:05:08 time: 0.8712 data_time: 0.0274 memory: 14901 loss: 0.9836 loss_prob: 0.5172 loss_thr: 0.3764 loss_db: 0.0899 2022/11/03 01:46:37 - mmengine - INFO - Epoch(train) [1107][30/63] lr: 2.1674e-04 eta: 1:05:02 time: 0.8307 data_time: 0.0417 memory: 14901 loss: 0.9547 loss_prob: 0.4917 loss_thr: 0.3759 loss_db: 0.0871 2022/11/03 01:46:39 - mmengine - INFO - Epoch(train) [1107][35/63] lr: 2.1674e-04 eta: 1:05:02 time: 0.6546 data_time: 0.0206 memory: 14901 loss: 0.8686 loss_prob: 0.4463 loss_thr: 0.3433 loss_db: 0.0790 2022/11/03 01:46:42 - mmengine - INFO - Epoch(train) [1107][40/63] lr: 2.1674e-04 eta: 1:04:55 time: 0.4808 data_time: 0.0052 memory: 14901 loss: 0.8446 loss_prob: 0.4318 loss_thr: 0.3377 loss_db: 0.0751 2022/11/03 01:46:44 - mmengine - INFO - Epoch(train) [1107][45/63] lr: 2.1674e-04 eta: 1:04:55 time: 0.4482 data_time: 0.0053 memory: 14901 loss: 0.9047 loss_prob: 0.4693 loss_thr: 0.3533 loss_db: 0.0820 2022/11/03 01:46:46 - mmengine - INFO - Epoch(train) [1107][50/63] lr: 2.1674e-04 eta: 1:04:48 time: 0.4865 data_time: 0.0205 memory: 14901 loss: 1.0667 loss_prob: 0.5991 loss_thr: 0.3700 loss_db: 0.0977 2022/11/03 01:46:49 - mmengine - INFO - Epoch(train) [1107][55/63] lr: 2.1674e-04 eta: 1:04:48 time: 0.5072 data_time: 0.0199 memory: 14901 loss: 0.9973 loss_prob: 0.5550 loss_thr: 0.3523 loss_db: 0.0900 2022/11/03 01:46:51 - mmengine - INFO - Epoch(train) [1107][60/63] lr: 2.1674e-04 eta: 1:04:41 time: 0.4712 data_time: 0.0043 memory: 14901 loss: 0.8478 loss_prob: 0.4385 loss_thr: 0.3308 loss_db: 0.0785 2022/11/03 01:46:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:46:57 - mmengine - INFO - Epoch(train) [1108][5/63] lr: 2.1465e-04 eta: 1:04:41 time: 0.6986 data_time: 0.1962 memory: 14901 loss: 0.8588 loss_prob: 0.4497 loss_thr: 0.3307 loss_db: 0.0785 2022/11/03 01:47:00 - mmengine - INFO - Epoch(train) [1108][10/63] lr: 2.1465e-04 eta: 1:04:32 time: 0.7526 data_time: 0.1965 memory: 14901 loss: 0.8377 loss_prob: 0.4281 loss_thr: 0.3342 loss_db: 0.0754 2022/11/03 01:47:02 - mmengine - INFO - Epoch(train) [1108][15/63] lr: 2.1465e-04 eta: 1:04:32 time: 0.5106 data_time: 0.0052 memory: 14901 loss: 0.8503 loss_prob: 0.4393 loss_thr: 0.3337 loss_db: 0.0773 2022/11/03 01:47:05 - mmengine - INFO - Epoch(train) [1108][20/63] lr: 2.1465e-04 eta: 1:04:26 time: 0.5041 data_time: 0.0080 memory: 14901 loss: 0.8614 loss_prob: 0.4469 loss_thr: 0.3352 loss_db: 0.0793 2022/11/03 01:47:07 - mmengine - INFO - Epoch(train) [1108][25/63] lr: 2.1465e-04 eta: 1:04:26 time: 0.5162 data_time: 0.0107 memory: 14901 loss: 0.9173 loss_prob: 0.4804 loss_thr: 0.3523 loss_db: 0.0845 2022/11/03 01:47:15 - mmengine - INFO - Epoch(train) [1108][30/63] lr: 2.1465e-04 eta: 1:04:19 time: 0.9904 data_time: 0.0574 memory: 14901 loss: 0.9159 loss_prob: 0.4785 loss_thr: 0.3551 loss_db: 0.0822 2022/11/03 01:47:23 - mmengine - INFO - Epoch(train) [1108][35/63] lr: 2.1465e-04 eta: 1:04:19 time: 1.5975 data_time: 0.0570 memory: 14901 loss: 0.8419 loss_prob: 0.4286 loss_thr: 0.3388 loss_db: 0.0745 2022/11/03 01:47:32 - mmengine - INFO - Epoch(train) [1108][40/63] lr: 2.1465e-04 eta: 1:04:14 time: 1.7578 data_time: 0.0084 memory: 14901 loss: 0.8801 loss_prob: 0.4513 loss_thr: 0.3496 loss_db: 0.0791 2022/11/03 01:47:38 - mmengine - INFO - Epoch(train) [1108][45/63] lr: 2.1465e-04 eta: 1:04:14 time: 1.5053 data_time: 0.0066 memory: 14901 loss: 0.8679 loss_prob: 0.4444 loss_thr: 0.3451 loss_db: 0.0784 2022/11/03 01:47:43 - mmengine - INFO - Epoch(train) [1108][50/63] lr: 2.1465e-04 eta: 1:04:07 time: 1.0239 data_time: 0.0124 memory: 14901 loss: 0.8830 loss_prob: 0.4608 loss_thr: 0.3411 loss_db: 0.0811 2022/11/03 01:47:46 - mmengine - INFO - Epoch(train) [1108][55/63] lr: 2.1465e-04 eta: 1:04:07 time: 0.7804 data_time: 0.0262 memory: 14901 loss: 0.9286 loss_prob: 0.4899 loss_thr: 0.3530 loss_db: 0.0857 2022/11/03 01:47:51 - mmengine - INFO - Epoch(train) [1108][60/63] lr: 2.1465e-04 eta: 1:04:01 time: 0.8180 data_time: 0.0197 memory: 14901 loss: 0.8793 loss_prob: 0.4524 loss_thr: 0.3466 loss_db: 0.0803 2022/11/03 01:47:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:47:59 - mmengine - INFO - Epoch(train) [1109][5/63] lr: 2.1255e-04 eta: 1:04:01 time: 0.9622 data_time: 0.2670 memory: 14901 loss: 0.8309 loss_prob: 0.4189 loss_thr: 0.3367 loss_db: 0.0753 2022/11/03 01:48:03 - mmengine - INFO - Epoch(train) [1109][10/63] lr: 2.1255e-04 eta: 1:03:52 time: 1.0965 data_time: 0.2740 memory: 14901 loss: 0.8783 loss_prob: 0.4498 loss_thr: 0.3499 loss_db: 0.0787 2022/11/03 01:48:06 - mmengine - INFO - Epoch(train) [1109][15/63] lr: 2.1255e-04 eta: 1:03:52 time: 0.7243 data_time: 0.0133 memory: 14901 loss: 0.9242 loss_prob: 0.4771 loss_thr: 0.3644 loss_db: 0.0827 2022/11/03 01:48:09 - mmengine - INFO - Epoch(train) [1109][20/63] lr: 2.1255e-04 eta: 1:03:46 time: 0.5894 data_time: 0.0061 memory: 14901 loss: 1.0098 loss_prob: 0.5300 loss_thr: 0.3880 loss_db: 0.0918 2022/11/03 01:48:13 - mmengine - INFO - Epoch(train) [1109][25/63] lr: 2.1255e-04 eta: 1:03:46 time: 0.6305 data_time: 0.0385 memory: 14901 loss: 1.0263 loss_prob: 0.5435 loss_thr: 0.3863 loss_db: 0.0965 2022/11/03 01:48:18 - mmengine - INFO - Epoch(train) [1109][30/63] lr: 2.1255e-04 eta: 1:03:39 time: 0.8641 data_time: 0.0654 memory: 14901 loss: 0.9929 loss_prob: 0.5242 loss_thr: 0.3748 loss_db: 0.0938 2022/11/03 01:48:21 - mmengine - INFO - Epoch(train) [1109][35/63] lr: 2.1255e-04 eta: 1:03:39 time: 0.8175 data_time: 0.0360 memory: 14901 loss: 0.9791 loss_prob: 0.5244 loss_thr: 0.3661 loss_db: 0.0887 2022/11/03 01:48:24 - mmengine - INFO - Epoch(train) [1109][40/63] lr: 2.1255e-04 eta: 1:03:33 time: 0.6587 data_time: 0.0095 memory: 14901 loss: 0.8862 loss_prob: 0.4647 loss_thr: 0.3418 loss_db: 0.0798 2022/11/03 01:48:27 - mmengine - INFO - Epoch(train) [1109][45/63] lr: 2.1255e-04 eta: 1:03:33 time: 0.5886 data_time: 0.0063 memory: 14901 loss: 0.8627 loss_prob: 0.4440 loss_thr: 0.3393 loss_db: 0.0795 2022/11/03 01:48:31 - mmengine - INFO - Epoch(train) [1109][50/63] lr: 2.1255e-04 eta: 1:03:26 time: 0.6522 data_time: 0.0211 memory: 14901 loss: 0.9121 loss_prob: 0.4725 loss_thr: 0.3569 loss_db: 0.0827 2022/11/03 01:48:34 - mmengine - INFO - Epoch(train) [1109][55/63] lr: 2.1255e-04 eta: 1:03:26 time: 0.6977 data_time: 0.0214 memory: 14901 loss: 0.8668 loss_prob: 0.4470 loss_thr: 0.3419 loss_db: 0.0778 2022/11/03 01:48:38 - mmengine - INFO - Epoch(train) [1109][60/63] lr: 2.1255e-04 eta: 1:03:19 time: 0.7004 data_time: 0.0091 memory: 14901 loss: 0.8804 loss_prob: 0.4516 loss_thr: 0.3504 loss_db: 0.0784 2022/11/03 01:48:39 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:48:47 - mmengine - INFO - Epoch(train) [1110][5/63] lr: 2.1044e-04 eta: 1:03:19 time: 1.0562 data_time: 0.2329 memory: 14901 loss: 0.9290 loss_prob: 0.4852 loss_thr: 0.3588 loss_db: 0.0850 2022/11/03 01:48:50 - mmengine - INFO - Epoch(train) [1110][10/63] lr: 2.1044e-04 eta: 1:03:11 time: 1.0329 data_time: 0.2330 memory: 14901 loss: 0.9118 loss_prob: 0.4766 loss_thr: 0.3514 loss_db: 0.0839 2022/11/03 01:48:53 - mmengine - INFO - Epoch(train) [1110][15/63] lr: 2.1044e-04 eta: 1:03:11 time: 0.6275 data_time: 0.0095 memory: 14901 loss: 0.8155 loss_prob: 0.4144 loss_thr: 0.3287 loss_db: 0.0723 2022/11/03 01:48:57 - mmengine - INFO - Epoch(train) [1110][20/63] lr: 2.1044e-04 eta: 1:03:04 time: 0.6867 data_time: 0.0128 memory: 14901 loss: 0.8498 loss_prob: 0.4363 loss_thr: 0.3366 loss_db: 0.0769 2022/11/03 01:49:00 - mmengine - INFO - Epoch(train) [1110][25/63] lr: 2.1044e-04 eta: 1:03:04 time: 0.6825 data_time: 0.0221 memory: 14901 loss: 0.8526 loss_prob: 0.4384 loss_thr: 0.3363 loss_db: 0.0779 2022/11/03 01:49:04 - mmengine - INFO - Epoch(train) [1110][30/63] lr: 2.1044e-04 eta: 1:02:58 time: 0.7159 data_time: 0.0368 memory: 14901 loss: 0.8349 loss_prob: 0.4258 loss_thr: 0.3331 loss_db: 0.0760 2022/11/03 01:49:07 - mmengine - INFO - Epoch(train) [1110][35/63] lr: 2.1044e-04 eta: 1:02:58 time: 0.6935 data_time: 0.0236 memory: 14901 loss: 0.8831 loss_prob: 0.4560 loss_thr: 0.3460 loss_db: 0.0811 2022/11/03 01:49:13 - mmengine - INFO - Epoch(train) [1110][40/63] lr: 2.1044e-04 eta: 1:02:51 time: 0.8825 data_time: 0.0113 memory: 14901 loss: 0.8923 loss_prob: 0.4577 loss_thr: 0.3537 loss_db: 0.0810 2022/11/03 01:49:18 - mmengine - INFO - Epoch(train) [1110][45/63] lr: 2.1044e-04 eta: 1:02:51 time: 1.1010 data_time: 0.0113 memory: 14901 loss: 0.8347 loss_prob: 0.4241 loss_thr: 0.3370 loss_db: 0.0735 2022/11/03 01:49:23 - mmengine - INFO - Epoch(train) [1110][50/63] lr: 2.1044e-04 eta: 1:02:45 time: 0.9965 data_time: 0.0134 memory: 14901 loss: 0.8485 loss_prob: 0.4363 loss_thr: 0.3379 loss_db: 0.0743 2022/11/03 01:49:26 - mmengine - INFO - Epoch(train) [1110][55/63] lr: 2.1044e-04 eta: 1:02:45 time: 0.8770 data_time: 0.0220 memory: 14901 loss: 0.8815 loss_prob: 0.4559 loss_thr: 0.3456 loss_db: 0.0800 2022/11/03 01:49:31 - mmengine - INFO - Epoch(train) [1110][60/63] lr: 2.1044e-04 eta: 1:02:38 time: 0.8078 data_time: 0.0155 memory: 14901 loss: 0.8581 loss_prob: 0.4412 loss_thr: 0.3374 loss_db: 0.0795 2022/11/03 01:49:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:49:40 - mmengine - INFO - Epoch(train) [1111][5/63] lr: 2.0834e-04 eta: 1:02:38 time: 1.1280 data_time: 0.2317 memory: 14901 loss: 0.9012 loss_prob: 0.4631 loss_thr: 0.3584 loss_db: 0.0797 2022/11/03 01:49:42 - mmengine - INFO - Epoch(train) [1111][10/63] lr: 2.0834e-04 eta: 1:02:30 time: 0.9550 data_time: 0.2392 memory: 14901 loss: 0.9050 loss_prob: 0.4612 loss_thr: 0.3631 loss_db: 0.0807 2022/11/03 01:49:47 - mmengine - INFO - Epoch(train) [1111][15/63] lr: 2.0834e-04 eta: 1:02:30 time: 0.7199 data_time: 0.0178 memory: 14901 loss: 0.8700 loss_prob: 0.4434 loss_thr: 0.3489 loss_db: 0.0777 2022/11/03 01:49:50 - mmengine - INFO - Epoch(train) [1111][20/63] lr: 2.0834e-04 eta: 1:02:23 time: 0.7351 data_time: 0.0117 memory: 14901 loss: 0.7920 loss_prob: 0.4012 loss_thr: 0.3197 loss_db: 0.0712 2022/11/03 01:49:53 - mmengine - INFO - Epoch(train) [1111][25/63] lr: 2.0834e-04 eta: 1:02:23 time: 0.6099 data_time: 0.0321 memory: 14901 loss: 0.8415 loss_prob: 0.4314 loss_thr: 0.3337 loss_db: 0.0764 2022/11/03 01:49:56 - mmengine - INFO - Epoch(train) [1111][30/63] lr: 2.0834e-04 eta: 1:02:17 time: 0.6521 data_time: 0.0362 memory: 14901 loss: 0.8948 loss_prob: 0.4643 loss_thr: 0.3492 loss_db: 0.0812 2022/11/03 01:50:00 - mmengine - INFO - Epoch(train) [1111][35/63] lr: 2.0834e-04 eta: 1:02:17 time: 0.7086 data_time: 0.0220 memory: 14901 loss: 0.9155 loss_prob: 0.4813 loss_thr: 0.3505 loss_db: 0.0836 2022/11/03 01:50:04 - mmengine - INFO - Epoch(train) [1111][40/63] lr: 2.0834e-04 eta: 1:02:10 time: 0.7592 data_time: 0.0131 memory: 14901 loss: 0.8761 loss_prob: 0.4555 loss_thr: 0.3422 loss_db: 0.0784 2022/11/03 01:50:08 - mmengine - INFO - Epoch(train) [1111][45/63] lr: 2.0834e-04 eta: 1:02:10 time: 0.7613 data_time: 0.0172 memory: 14901 loss: 0.7917 loss_prob: 0.3968 loss_thr: 0.3260 loss_db: 0.0689 2022/11/03 01:50:13 - mmengine - INFO - Epoch(train) [1111][50/63] lr: 2.0834e-04 eta: 1:02:04 time: 0.8869 data_time: 0.0308 memory: 14901 loss: 0.8756 loss_prob: 0.4471 loss_thr: 0.3508 loss_db: 0.0778 2022/11/03 01:50:17 - mmengine - INFO - Epoch(train) [1111][55/63] lr: 2.0834e-04 eta: 1:02:04 time: 0.9614 data_time: 0.0235 memory: 14901 loss: 0.9240 loss_prob: 0.4780 loss_thr: 0.3615 loss_db: 0.0845 2022/11/03 01:50:20 - mmengine - INFO - Epoch(train) [1111][60/63] lr: 2.0834e-04 eta: 1:01:57 time: 0.7571 data_time: 0.0117 memory: 14901 loss: 0.8339 loss_prob: 0.4232 loss_thr: 0.3336 loss_db: 0.0770 2022/11/03 01:50:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:50:32 - mmengine - INFO - Epoch(train) [1112][5/63] lr: 2.0623e-04 eta: 1:01:57 time: 1.3022 data_time: 0.2810 memory: 14901 loss: 0.9147 loss_prob: 0.4740 loss_thr: 0.3594 loss_db: 0.0813 2022/11/03 01:50:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:50:38 - mmengine - INFO - Epoch(train) [1112][10/63] lr: 2.0623e-04 eta: 1:01:49 time: 1.4779 data_time: 0.2812 memory: 14901 loss: 0.9768 loss_prob: 0.5152 loss_thr: 0.3737 loss_db: 0.0878 2022/11/03 01:50:43 - mmengine - INFO - Epoch(train) [1112][15/63] lr: 2.0623e-04 eta: 1:01:49 time: 1.0838 data_time: 0.0060 memory: 14901 loss: 0.8668 loss_prob: 0.4521 loss_thr: 0.3352 loss_db: 0.0796 2022/11/03 01:50:47 - mmengine - INFO - Epoch(train) [1112][20/63] lr: 2.0623e-04 eta: 1:01:43 time: 0.9136 data_time: 0.0085 memory: 14901 loss: 0.7978 loss_prob: 0.4089 loss_thr: 0.3165 loss_db: 0.0724 2022/11/03 01:50:51 - mmengine - INFO - Epoch(train) [1112][25/63] lr: 2.0623e-04 eta: 1:01:43 time: 0.7762 data_time: 0.0386 memory: 14901 loss: 0.8412 loss_prob: 0.4400 loss_thr: 0.3257 loss_db: 0.0755 2022/11/03 01:50:55 - mmengine - INFO - Epoch(train) [1112][30/63] lr: 2.0623e-04 eta: 1:01:36 time: 0.7177 data_time: 0.0360 memory: 14901 loss: 0.8907 loss_prob: 0.4714 loss_thr: 0.3384 loss_db: 0.0809 2022/11/03 01:50:58 - mmengine - INFO - Epoch(train) [1112][35/63] lr: 2.0623e-04 eta: 1:01:36 time: 0.7336 data_time: 0.0077 memory: 14901 loss: 0.8556 loss_prob: 0.4436 loss_thr: 0.3348 loss_db: 0.0772 2022/11/03 01:51:03 - mmengine - INFO - Epoch(train) [1112][40/63] lr: 2.0623e-04 eta: 1:01:30 time: 0.8536 data_time: 0.0120 memory: 14901 loss: 0.8560 loss_prob: 0.4379 loss_thr: 0.3427 loss_db: 0.0755 2022/11/03 01:51:07 - mmengine - INFO - Epoch(train) [1112][45/63] lr: 2.0623e-04 eta: 1:01:30 time: 0.8935 data_time: 0.0105 memory: 14901 loss: 0.8904 loss_prob: 0.4503 loss_thr: 0.3619 loss_db: 0.0783 2022/11/03 01:51:12 - mmengine - INFO - Epoch(train) [1112][50/63] lr: 2.0623e-04 eta: 1:01:23 time: 0.8375 data_time: 0.0288 memory: 14901 loss: 0.8574 loss_prob: 0.4320 loss_thr: 0.3489 loss_db: 0.0764 2022/11/03 01:51:16 - mmengine - INFO - Epoch(train) [1112][55/63] lr: 2.0623e-04 eta: 1:01:23 time: 0.8235 data_time: 0.0283 memory: 14901 loss: 0.8527 loss_prob: 0.4384 loss_thr: 0.3379 loss_db: 0.0764 2022/11/03 01:51:19 - mmengine - INFO - Epoch(train) [1112][60/63] lr: 2.0623e-04 eta: 1:01:17 time: 0.7755 data_time: 0.0073 memory: 14901 loss: 0.8827 loss_prob: 0.4572 loss_thr: 0.3466 loss_db: 0.0788 2022/11/03 01:51:21 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:51:27 - mmengine - INFO - Epoch(train) [1113][5/63] lr: 2.0412e-04 eta: 1:01:17 time: 0.9559 data_time: 0.2514 memory: 14901 loss: 0.9351 loss_prob: 0.4938 loss_thr: 0.3559 loss_db: 0.0854 2022/11/03 01:51:32 - mmengine - INFO - Epoch(train) [1113][10/63] lr: 2.0412e-04 eta: 1:01:08 time: 1.1164 data_time: 0.2580 memory: 14901 loss: 0.9142 loss_prob: 0.4787 loss_thr: 0.3541 loss_db: 0.0814 2022/11/03 01:51:37 - mmengine - INFO - Epoch(train) [1113][15/63] lr: 2.0412e-04 eta: 1:01:08 time: 0.9640 data_time: 0.0158 memory: 14901 loss: 0.8881 loss_prob: 0.4637 loss_thr: 0.3447 loss_db: 0.0797 2022/11/03 01:51:43 - mmengine - INFO - Epoch(train) [1113][20/63] lr: 2.0412e-04 eta: 1:01:02 time: 1.0477 data_time: 0.0068 memory: 14901 loss: 0.8471 loss_prob: 0.4332 loss_thr: 0.3364 loss_db: 0.0775 2022/11/03 01:51:47 - mmengine - INFO - Epoch(train) [1113][25/63] lr: 2.0412e-04 eta: 1:01:02 time: 0.9718 data_time: 0.0228 memory: 14901 loss: 0.8477 loss_prob: 0.4345 loss_thr: 0.3349 loss_db: 0.0783 2022/11/03 01:51:50 - mmengine - INFO - Epoch(train) [1113][30/63] lr: 2.0412e-04 eta: 1:00:55 time: 0.7343 data_time: 0.0349 memory: 14901 loss: 0.8669 loss_prob: 0.4429 loss_thr: 0.3463 loss_db: 0.0778 2022/11/03 01:51:54 - mmengine - INFO - Epoch(train) [1113][35/63] lr: 2.0412e-04 eta: 1:00:55 time: 0.7583 data_time: 0.0260 memory: 14901 loss: 0.9176 loss_prob: 0.4745 loss_thr: 0.3615 loss_db: 0.0817 2022/11/03 01:51:58 - mmengine - INFO - Epoch(train) [1113][40/63] lr: 2.0412e-04 eta: 1:00:49 time: 0.8392 data_time: 0.0154 memory: 14901 loss: 0.8881 loss_prob: 0.4593 loss_thr: 0.3481 loss_db: 0.0807 2022/11/03 01:52:02 - mmengine - INFO - Epoch(train) [1113][45/63] lr: 2.0412e-04 eta: 1:00:49 time: 0.7682 data_time: 0.0088 memory: 14901 loss: 0.8296 loss_prob: 0.4199 loss_thr: 0.3343 loss_db: 0.0754 2022/11/03 01:52:06 - mmengine - INFO - Epoch(train) [1113][50/63] lr: 2.0412e-04 eta: 1:00:42 time: 0.7871 data_time: 0.0164 memory: 14901 loss: 0.8350 loss_prob: 0.4287 loss_thr: 0.3298 loss_db: 0.0765 2022/11/03 01:52:10 - mmengine - INFO - Epoch(train) [1113][55/63] lr: 2.0412e-04 eta: 1:00:42 time: 0.7701 data_time: 0.0285 memory: 14901 loss: 0.9085 loss_prob: 0.4733 loss_thr: 0.3531 loss_db: 0.0821 2022/11/03 01:52:14 - mmengine - INFO - Epoch(train) [1113][60/63] lr: 2.0412e-04 eta: 1:00:36 time: 0.7685 data_time: 0.0194 memory: 14901 loss: 0.9037 loss_prob: 0.4630 loss_thr: 0.3604 loss_db: 0.0803 2022/11/03 01:52:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:52:23 - mmengine - INFO - Epoch(train) [1114][5/63] lr: 2.0201e-04 eta: 1:00:36 time: 1.1600 data_time: 0.2630 memory: 14901 loss: 0.9269 loss_prob: 0.4821 loss_thr: 0.3612 loss_db: 0.0837 2022/11/03 01:52:27 - mmengine - INFO - Epoch(train) [1114][10/63] lr: 2.0201e-04 eta: 1:00:27 time: 1.1522 data_time: 0.2686 memory: 14901 loss: 0.8779 loss_prob: 0.4592 loss_thr: 0.3406 loss_db: 0.0780 2022/11/03 01:52:30 - mmengine - INFO - Epoch(train) [1114][15/63] lr: 2.0201e-04 eta: 1:00:27 time: 0.6997 data_time: 0.0128 memory: 14901 loss: 0.9129 loss_prob: 0.4739 loss_thr: 0.3571 loss_db: 0.0819 2022/11/03 01:52:33 - mmengine - INFO - Epoch(train) [1114][20/63] lr: 2.0201e-04 eta: 1:00:21 time: 0.5347 data_time: 0.0067 memory: 14901 loss: 0.8563 loss_prob: 0.4324 loss_thr: 0.3468 loss_db: 0.0770 2022/11/03 01:52:36 - mmengine - INFO - Epoch(train) [1114][25/63] lr: 2.0201e-04 eta: 1:00:21 time: 0.5952 data_time: 0.0334 memory: 14901 loss: 0.8402 loss_prob: 0.4270 loss_thr: 0.3371 loss_db: 0.0761 2022/11/03 01:52:39 - mmengine - INFO - Epoch(train) [1114][30/63] lr: 2.0201e-04 eta: 1:00:14 time: 0.6668 data_time: 0.0432 memory: 14901 loss: 0.8602 loss_prob: 0.4373 loss_thr: 0.3452 loss_db: 0.0777 2022/11/03 01:52:42 - mmengine - INFO - Epoch(train) [1114][35/63] lr: 2.0201e-04 eta: 1:00:14 time: 0.6018 data_time: 0.0225 memory: 14901 loss: 0.8780 loss_prob: 0.4490 loss_thr: 0.3500 loss_db: 0.0790 2022/11/03 01:52:45 - mmengine - INFO - Epoch(train) [1114][40/63] lr: 2.0201e-04 eta: 1:00:07 time: 0.5582 data_time: 0.0134 memory: 14901 loss: 0.9297 loss_prob: 0.4882 loss_thr: 0.3562 loss_db: 0.0853 2022/11/03 01:52:49 - mmengine - INFO - Epoch(train) [1114][45/63] lr: 2.0201e-04 eta: 1:00:07 time: 0.7568 data_time: 0.0069 memory: 14901 loss: 0.9370 loss_prob: 0.4839 loss_thr: 0.3679 loss_db: 0.0852 2022/11/03 01:52:54 - mmengine - INFO - Epoch(train) [1114][50/63] lr: 2.0201e-04 eta: 1:00:01 time: 0.9383 data_time: 0.0169 memory: 14901 loss: 0.8628 loss_prob: 0.4418 loss_thr: 0.3426 loss_db: 0.0784 2022/11/03 01:52:58 - mmengine - INFO - Epoch(train) [1114][55/63] lr: 2.0201e-04 eta: 1:00:01 time: 0.8412 data_time: 0.0244 memory: 14901 loss: 0.8416 loss_prob: 0.4281 loss_thr: 0.3384 loss_db: 0.0751 2022/11/03 01:53:02 - mmengine - INFO - Epoch(train) [1114][60/63] lr: 2.0201e-04 eta: 0:59:54 time: 0.7344 data_time: 0.0161 memory: 14901 loss: 0.8993 loss_prob: 0.4585 loss_thr: 0.3620 loss_db: 0.0788 2022/11/03 01:53:03 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:53:11 - mmengine - INFO - Epoch(train) [1115][5/63] lr: 1.9990e-04 eta: 0:59:54 time: 1.1494 data_time: 0.2551 memory: 14901 loss: 0.9676 loss_prob: 0.5050 loss_thr: 0.3766 loss_db: 0.0860 2022/11/03 01:53:14 - mmengine - INFO - Epoch(train) [1115][10/63] lr: 1.9990e-04 eta: 0:59:46 time: 1.0982 data_time: 0.2568 memory: 14901 loss: 0.9242 loss_prob: 0.4795 loss_thr: 0.3610 loss_db: 0.0836 2022/11/03 01:53:18 - mmengine - INFO - Epoch(train) [1115][15/63] lr: 1.9990e-04 eta: 0:59:46 time: 0.6613 data_time: 0.0067 memory: 14901 loss: 0.8778 loss_prob: 0.4514 loss_thr: 0.3474 loss_db: 0.0791 2022/11/03 01:53:21 - mmengine - INFO - Epoch(train) [1115][20/63] lr: 1.9990e-04 eta: 0:59:39 time: 0.6629 data_time: 0.0055 memory: 14901 loss: 0.9115 loss_prob: 0.4767 loss_thr: 0.3525 loss_db: 0.0823 2022/11/03 01:53:25 - mmengine - INFO - Epoch(train) [1115][25/63] lr: 1.9990e-04 eta: 0:59:39 time: 0.7009 data_time: 0.0285 memory: 14901 loss: 0.8719 loss_prob: 0.4422 loss_thr: 0.3532 loss_db: 0.0765 2022/11/03 01:53:28 - mmengine - INFO - Epoch(train) [1115][30/63] lr: 1.9990e-04 eta: 0:59:33 time: 0.7267 data_time: 0.0593 memory: 14901 loss: 0.8542 loss_prob: 0.4312 loss_thr: 0.3467 loss_db: 0.0764 2022/11/03 01:53:31 - mmengine - INFO - Epoch(train) [1115][35/63] lr: 1.9990e-04 eta: 0:59:33 time: 0.6072 data_time: 0.0362 memory: 14901 loss: 0.8590 loss_prob: 0.4436 loss_thr: 0.3373 loss_db: 0.0781 2022/11/03 01:53:35 - mmengine - INFO - Epoch(train) [1115][40/63] lr: 1.9990e-04 eta: 0:59:26 time: 0.6555 data_time: 0.0049 memory: 14901 loss: 0.8207 loss_prob: 0.4185 loss_thr: 0.3285 loss_db: 0.0737 2022/11/03 01:53:39 - mmengine - INFO - Epoch(train) [1115][45/63] lr: 1.9990e-04 eta: 0:59:26 time: 0.7728 data_time: 0.0055 memory: 14901 loss: 0.8247 loss_prob: 0.4252 loss_thr: 0.3238 loss_db: 0.0757 2022/11/03 01:53:43 - mmengine - INFO - Epoch(train) [1115][50/63] lr: 1.9990e-04 eta: 0:59:19 time: 0.8606 data_time: 0.0290 memory: 14901 loss: 0.9692 loss_prob: 0.5163 loss_thr: 0.3673 loss_db: 0.0856 2022/11/03 01:53:48 - mmengine - INFO - Epoch(train) [1115][55/63] lr: 1.9990e-04 eta: 0:59:19 time: 0.8840 data_time: 0.0306 memory: 14901 loss: 0.9797 loss_prob: 0.5176 loss_thr: 0.3773 loss_db: 0.0848 2022/11/03 01:53:51 - mmengine - INFO - Epoch(train) [1115][60/63] lr: 1.9990e-04 eta: 0:59:13 time: 0.7576 data_time: 0.0083 memory: 14901 loss: 0.8496 loss_prob: 0.4308 loss_thr: 0.3424 loss_db: 0.0765 2022/11/03 01:53:53 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:54:00 - mmengine - INFO - Epoch(train) [1116][5/63] lr: 1.9778e-04 eta: 0:59:13 time: 1.0685 data_time: 0.2330 memory: 14901 loss: 0.9233 loss_prob: 0.4981 loss_thr: 0.3423 loss_db: 0.0830 2022/11/03 01:54:04 - mmengine - INFO - Epoch(train) [1116][10/63] lr: 1.9778e-04 eta: 0:59:04 time: 1.1236 data_time: 0.2369 memory: 14901 loss: 0.9219 loss_prob: 0.4809 loss_thr: 0.3561 loss_db: 0.0849 2022/11/03 01:54:10 - mmengine - INFO - Epoch(train) [1116][15/63] lr: 1.9778e-04 eta: 0:59:04 time: 0.9340 data_time: 0.0136 memory: 14901 loss: 0.9338 loss_prob: 0.4869 loss_thr: 0.3621 loss_db: 0.0849 2022/11/03 01:54:14 - mmengine - INFO - Epoch(train) [1116][20/63] lr: 1.9778e-04 eta: 0:58:58 time: 0.9889 data_time: 0.0055 memory: 14901 loss: 0.8389 loss_prob: 0.4316 loss_thr: 0.3331 loss_db: 0.0741 2022/11/03 01:54:17 - mmengine - INFO - Epoch(train) [1116][25/63] lr: 1.9778e-04 eta: 0:58:58 time: 0.6962 data_time: 0.0142 memory: 14901 loss: 0.8273 loss_prob: 0.4279 loss_thr: 0.3240 loss_db: 0.0754 2022/11/03 01:54:20 - mmengine - INFO - Epoch(train) [1116][30/63] lr: 1.9778e-04 eta: 0:58:51 time: 0.6191 data_time: 0.0357 memory: 14901 loss: 0.8527 loss_prob: 0.4473 loss_thr: 0.3258 loss_db: 0.0796 2022/11/03 01:54:23 - mmengine - INFO - Epoch(train) [1116][35/63] lr: 1.9778e-04 eta: 0:58:51 time: 0.6125 data_time: 0.0333 memory: 14901 loss: 0.8572 loss_prob: 0.4492 loss_thr: 0.3286 loss_db: 0.0795 2022/11/03 01:54:27 - mmengine - INFO - Epoch(train) [1116][40/63] lr: 1.9778e-04 eta: 0:58:45 time: 0.7025 data_time: 0.0119 memory: 14901 loss: 0.8051 loss_prob: 0.4143 loss_thr: 0.3175 loss_db: 0.0733 2022/11/03 01:54:31 - mmengine - INFO - Epoch(train) [1116][45/63] lr: 1.9778e-04 eta: 0:58:45 time: 0.8087 data_time: 0.0058 memory: 14901 loss: 0.8334 loss_prob: 0.4248 loss_thr: 0.3349 loss_db: 0.0738 2022/11/03 01:54:35 - mmengine - INFO - Epoch(train) [1116][50/63] lr: 1.9778e-04 eta: 0:58:38 time: 0.8308 data_time: 0.0338 memory: 14901 loss: 0.8450 loss_prob: 0.4267 loss_thr: 0.3445 loss_db: 0.0738 2022/11/03 01:54:39 - mmengine - INFO - Epoch(train) [1116][55/63] lr: 1.9778e-04 eta: 0:58:38 time: 0.7821 data_time: 0.0371 memory: 14901 loss: 0.8100 loss_prob: 0.4109 loss_thr: 0.3288 loss_db: 0.0703 2022/11/03 01:54:41 - mmengine - INFO - Epoch(train) [1116][60/63] lr: 1.9778e-04 eta: 0:58:32 time: 0.5821 data_time: 0.0109 memory: 14901 loss: 0.8497 loss_prob: 0.4342 loss_thr: 0.3423 loss_db: 0.0732 2022/11/03 01:54:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:54:51 - mmengine - INFO - Epoch(train) [1117][5/63] lr: 1.9566e-04 eta: 0:58:32 time: 1.0444 data_time: 0.2302 memory: 14901 loss: 0.9588 loss_prob: 0.4948 loss_thr: 0.3787 loss_db: 0.0853 2022/11/03 01:54:56 - mmengine - INFO - Epoch(train) [1117][10/63] lr: 1.9566e-04 eta: 0:58:23 time: 1.2655 data_time: 0.2381 memory: 14901 loss: 0.8859 loss_prob: 0.4591 loss_thr: 0.3459 loss_db: 0.0810 2022/11/03 01:54:59 - mmengine - INFO - Epoch(train) [1117][15/63] lr: 1.9566e-04 eta: 0:58:23 time: 0.8534 data_time: 0.0168 memory: 14901 loss: 0.8912 loss_prob: 0.4525 loss_thr: 0.3598 loss_db: 0.0789 2022/11/03 01:55:04 - mmengine - INFO - Epoch(train) [1117][20/63] lr: 1.9566e-04 eta: 0:58:17 time: 0.8647 data_time: 0.0062 memory: 14901 loss: 0.8519 loss_prob: 0.4222 loss_thr: 0.3564 loss_db: 0.0733 2022/11/03 01:55:08 - mmengine - INFO - Epoch(train) [1117][25/63] lr: 1.9566e-04 eta: 0:58:17 time: 0.8472 data_time: 0.0154 memory: 14901 loss: 0.8437 loss_prob: 0.4320 loss_thr: 0.3382 loss_db: 0.0735 2022/11/03 01:55:11 - mmengine - INFO - Epoch(train) [1117][30/63] lr: 1.9566e-04 eta: 0:58:10 time: 0.6749 data_time: 0.0420 memory: 14901 loss: 0.8361 loss_prob: 0.4247 loss_thr: 0.3384 loss_db: 0.0730 2022/11/03 01:55:15 - mmengine - INFO - Epoch(train) [1117][35/63] lr: 1.9566e-04 eta: 0:58:10 time: 0.7219 data_time: 0.0324 memory: 14901 loss: 0.8251 loss_prob: 0.4208 loss_thr: 0.3294 loss_db: 0.0748 2022/11/03 01:55:19 - mmengine - INFO - Epoch(train) [1117][40/63] lr: 1.9566e-04 eta: 0:58:04 time: 0.8095 data_time: 0.0065 memory: 14901 loss: 0.8550 loss_prob: 0.4382 loss_thr: 0.3387 loss_db: 0.0781 2022/11/03 01:55:24 - mmengine - INFO - Epoch(train) [1117][45/63] lr: 1.9566e-04 eta: 0:58:04 time: 0.8505 data_time: 0.0075 memory: 14901 loss: 0.8850 loss_prob: 0.4492 loss_thr: 0.3573 loss_db: 0.0785 2022/11/03 01:55:27 - mmengine - INFO - Epoch(train) [1117][50/63] lr: 1.9566e-04 eta: 0:57:57 time: 0.8339 data_time: 0.0227 memory: 14901 loss: 0.8351 loss_prob: 0.4281 loss_thr: 0.3316 loss_db: 0.0753 2022/11/03 01:55:32 - mmengine - INFO - Epoch(train) [1117][55/63] lr: 1.9566e-04 eta: 0:57:57 time: 0.8434 data_time: 0.0277 memory: 14901 loss: 0.7495 loss_prob: 0.3794 loss_thr: 0.3027 loss_db: 0.0674 2022/11/03 01:55:36 - mmengine - INFO - Epoch(train) [1117][60/63] lr: 1.9566e-04 eta: 0:57:51 time: 0.8414 data_time: 0.0122 memory: 14901 loss: 0.8207 loss_prob: 0.4229 loss_thr: 0.3234 loss_db: 0.0744 2022/11/03 01:55:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:55:45 - mmengine - INFO - Epoch(train) [1118][5/63] lr: 1.9354e-04 eta: 0:57:51 time: 1.1053 data_time: 0.2319 memory: 14901 loss: 1.0200 loss_prob: 0.5479 loss_thr: 0.3782 loss_db: 0.0940 2022/11/03 01:55:47 - mmengine - INFO - Epoch(train) [1118][10/63] lr: 1.9354e-04 eta: 0:57:42 time: 0.9678 data_time: 0.2337 memory: 14901 loss: 0.9688 loss_prob: 0.5127 loss_thr: 0.3681 loss_db: 0.0880 2022/11/03 01:55:50 - mmengine - INFO - Epoch(train) [1118][15/63] lr: 1.9354e-04 eta: 0:57:42 time: 0.5164 data_time: 0.0080 memory: 14901 loss: 0.8660 loss_prob: 0.4515 loss_thr: 0.3367 loss_db: 0.0778 2022/11/03 01:55:53 - mmengine - INFO - Epoch(train) [1118][20/63] lr: 1.9354e-04 eta: 0:57:35 time: 0.5078 data_time: 0.0054 memory: 14901 loss: 0.8471 loss_prob: 0.4373 loss_thr: 0.3348 loss_db: 0.0751 2022/11/03 01:55:55 - mmengine - INFO - Epoch(train) [1118][25/63] lr: 1.9354e-04 eta: 0:57:35 time: 0.5085 data_time: 0.0161 memory: 14901 loss: 0.8987 loss_prob: 0.4673 loss_thr: 0.3518 loss_db: 0.0796 2022/11/03 01:56:00 - mmengine - INFO - Epoch(train) [1118][30/63] lr: 1.9354e-04 eta: 0:57:29 time: 0.7321 data_time: 0.0376 memory: 14901 loss: 0.9235 loss_prob: 0.4731 loss_thr: 0.3697 loss_db: 0.0808 2022/11/03 01:56:03 - mmengine - INFO - Epoch(train) [1118][35/63] lr: 1.9354e-04 eta: 0:57:29 time: 0.8291 data_time: 0.0304 memory: 14901 loss: 0.8099 loss_prob: 0.4056 loss_thr: 0.3322 loss_db: 0.0720 2022/11/03 01:56:06 - mmengine - INFO - Epoch(train) [1118][40/63] lr: 1.9354e-04 eta: 0:57:22 time: 0.6336 data_time: 0.0089 memory: 14901 loss: 0.7952 loss_prob: 0.3937 loss_thr: 0.3306 loss_db: 0.0709 2022/11/03 01:56:10 - mmengine - INFO - Epoch(train) [1118][45/63] lr: 1.9354e-04 eta: 0:57:22 time: 0.6080 data_time: 0.0052 memory: 14901 loss: 0.8339 loss_prob: 0.4168 loss_thr: 0.3435 loss_db: 0.0736 2022/11/03 01:56:14 - mmengine - INFO - Epoch(train) [1118][50/63] lr: 1.9354e-04 eta: 0:57:16 time: 0.7627 data_time: 0.0180 memory: 14901 loss: 0.8595 loss_prob: 0.4445 loss_thr: 0.3376 loss_db: 0.0775 2022/11/03 01:56:18 - mmengine - INFO - Epoch(train) [1118][55/63] lr: 1.9354e-04 eta: 0:57:16 time: 0.8523 data_time: 0.0323 memory: 14901 loss: 0.8794 loss_prob: 0.4584 loss_thr: 0.3417 loss_db: 0.0793 2022/11/03 01:56:22 - mmengine - INFO - Epoch(train) [1118][60/63] lr: 1.9354e-04 eta: 0:57:09 time: 0.8401 data_time: 0.0211 memory: 14901 loss: 0.8056 loss_prob: 0.4157 loss_thr: 0.3188 loss_db: 0.0711 2022/11/03 01:56:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:56:31 - mmengine - INFO - Epoch(train) [1119][5/63] lr: 1.9141e-04 eta: 0:57:09 time: 1.0226 data_time: 0.2368 memory: 14901 loss: 0.8308 loss_prob: 0.4263 loss_thr: 0.3292 loss_db: 0.0753 2022/11/03 01:56:36 - mmengine - INFO - Epoch(train) [1119][10/63] lr: 1.9141e-04 eta: 0:57:01 time: 1.1684 data_time: 0.2366 memory: 14901 loss: 0.8154 loss_prob: 0.4175 loss_thr: 0.3246 loss_db: 0.0733 2022/11/03 01:56:40 - mmengine - INFO - Epoch(train) [1119][15/63] lr: 1.9141e-04 eta: 0:57:01 time: 0.8748 data_time: 0.0054 memory: 14901 loss: 0.8744 loss_prob: 0.4538 loss_thr: 0.3434 loss_db: 0.0772 2022/11/03 01:56:43 - mmengine - INFO - Epoch(train) [1119][20/63] lr: 1.9141e-04 eta: 0:56:54 time: 0.7591 data_time: 0.0053 memory: 14901 loss: 0.9214 loss_prob: 0.4798 loss_thr: 0.3593 loss_db: 0.0823 2022/11/03 01:56:47 - mmengine - INFO - Epoch(train) [1119][25/63] lr: 1.9141e-04 eta: 0:56:54 time: 0.7217 data_time: 0.0116 memory: 14901 loss: 0.9124 loss_prob: 0.4724 loss_thr: 0.3578 loss_db: 0.0822 2022/11/03 01:56:52 - mmengine - INFO - Epoch(train) [1119][30/63] lr: 1.9141e-04 eta: 0:56:48 time: 0.8455 data_time: 0.0382 memory: 14901 loss: 0.9182 loss_prob: 0.4747 loss_thr: 0.3616 loss_db: 0.0819 2022/11/03 01:56:55 - mmengine - INFO - Epoch(train) [1119][35/63] lr: 1.9141e-04 eta: 0:56:48 time: 0.7635 data_time: 0.0321 memory: 14901 loss: 0.8529 loss_prob: 0.4382 loss_thr: 0.3388 loss_db: 0.0759 2022/11/03 01:56:59 - mmengine - INFO - Epoch(train) [1119][40/63] lr: 1.9141e-04 eta: 0:56:41 time: 0.6903 data_time: 0.0059 memory: 14901 loss: 0.8606 loss_prob: 0.4424 loss_thr: 0.3419 loss_db: 0.0763 2022/11/03 01:57:03 - mmengine - INFO - Epoch(train) [1119][45/63] lr: 1.9141e-04 eta: 0:56:41 time: 0.7987 data_time: 0.0056 memory: 14901 loss: 0.8872 loss_prob: 0.4612 loss_thr: 0.3467 loss_db: 0.0793 2022/11/03 01:57:06 - mmengine - INFO - Epoch(train) [1119][50/63] lr: 1.9141e-04 eta: 0:56:34 time: 0.7391 data_time: 0.0129 memory: 14901 loss: 0.8201 loss_prob: 0.4189 loss_thr: 0.3266 loss_db: 0.0746 2022/11/03 01:57:09 - mmengine - INFO - Epoch(train) [1119][55/63] lr: 1.9141e-04 eta: 0:56:34 time: 0.6003 data_time: 0.0256 memory: 14901 loss: 0.7805 loss_prob: 0.3894 loss_thr: 0.3221 loss_db: 0.0689 2022/11/03 01:57:12 - mmengine - INFO - Epoch(train) [1119][60/63] lr: 1.9141e-04 eta: 0:56:28 time: 0.5862 data_time: 0.0179 memory: 14901 loss: 0.7905 loss_prob: 0.4013 loss_thr: 0.3192 loss_db: 0.0699 2022/11/03 01:57:14 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:57:23 - mmengine - INFO - Epoch(train) [1120][5/63] lr: 1.8929e-04 eta: 0:56:28 time: 1.2323 data_time: 0.2711 memory: 14901 loss: 0.7871 loss_prob: 0.4003 loss_thr: 0.3155 loss_db: 0.0713 2022/11/03 01:57:27 - mmengine - INFO - Epoch(train) [1120][10/63] lr: 1.8929e-04 eta: 0:56:19 time: 1.2475 data_time: 0.2758 memory: 14901 loss: 0.8774 loss_prob: 0.4497 loss_thr: 0.3481 loss_db: 0.0796 2022/11/03 01:57:30 - mmengine - INFO - Epoch(train) [1120][15/63] lr: 1.8929e-04 eta: 0:56:19 time: 0.6422 data_time: 0.0113 memory: 14901 loss: 0.9004 loss_prob: 0.4634 loss_thr: 0.3566 loss_db: 0.0805 2022/11/03 01:57:33 - mmengine - INFO - Epoch(train) [1120][20/63] lr: 1.8929e-04 eta: 0:56:13 time: 0.6044 data_time: 0.0087 memory: 14901 loss: 0.8767 loss_prob: 0.4450 loss_thr: 0.3538 loss_db: 0.0779 2022/11/03 01:57:36 - mmengine - INFO - Epoch(train) [1120][25/63] lr: 1.8929e-04 eta: 0:56:13 time: 0.6491 data_time: 0.0368 memory: 14901 loss: 0.9169 loss_prob: 0.4685 loss_thr: 0.3669 loss_db: 0.0815 2022/11/03 01:57:39 - mmengine - INFO - Epoch(train) [1120][30/63] lr: 1.8929e-04 eta: 0:56:06 time: 0.6139 data_time: 0.0340 memory: 14901 loss: 0.9705 loss_prob: 0.5101 loss_thr: 0.3736 loss_db: 0.0868 2022/11/03 01:57:44 - mmengine - INFO - Epoch(train) [1120][35/63] lr: 1.8929e-04 eta: 0:56:06 time: 0.7484 data_time: 0.0082 memory: 14901 loss: 0.9306 loss_prob: 0.4882 loss_thr: 0.3592 loss_db: 0.0833 2022/11/03 01:57:48 - mmengine - INFO - Epoch(train) [1120][40/63] lr: 1.8929e-04 eta: 0:55:59 time: 0.8497 data_time: 0.0081 memory: 14901 loss: 0.8768 loss_prob: 0.4539 loss_thr: 0.3426 loss_db: 0.0803 2022/11/03 01:57:50 - mmengine - INFO - Epoch(train) [1120][45/63] lr: 1.8929e-04 eta: 0:55:59 time: 0.6388 data_time: 0.0078 memory: 14901 loss: 0.8564 loss_prob: 0.4450 loss_thr: 0.3323 loss_db: 0.0791 2022/11/03 01:57:54 - mmengine - INFO - Epoch(train) [1120][50/63] lr: 1.8929e-04 eta: 0:55:53 time: 0.6364 data_time: 0.0242 memory: 14901 loss: 0.8586 loss_prob: 0.4467 loss_thr: 0.3341 loss_db: 0.0779 2022/11/03 01:57:57 - mmengine - INFO - Epoch(train) [1120][55/63] lr: 1.8929e-04 eta: 0:55:53 time: 0.6748 data_time: 0.0233 memory: 14901 loss: 0.8230 loss_prob: 0.4161 loss_thr: 0.3341 loss_db: 0.0728 2022/11/03 01:58:00 - mmengine - INFO - Epoch(train) [1120][60/63] lr: 1.8929e-04 eta: 0:55:46 time: 0.6153 data_time: 0.0097 memory: 14901 loss: 0.8949 loss_prob: 0.4594 loss_thr: 0.3555 loss_db: 0.0801 2022/11/03 01:58:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:58:02 - mmengine - INFO - Saving checkpoint at 1120 epochs 2022/11/03 01:58:06 - mmengine - INFO - Epoch(val) [1120][5/500] eta: 0:55:46 time: 0.0462 data_time: 0.0054 memory: 14901 2022/11/03 01:58:06 - mmengine - INFO - Epoch(val) [1120][10/500] eta: 0:00:24 time: 0.0490 data_time: 0.0055 memory: 1008 2022/11/03 01:58:06 - mmengine - INFO - Epoch(val) [1120][15/500] eta: 0:00:24 time: 0.0449 data_time: 0.0030 memory: 1008 2022/11/03 01:58:07 - mmengine - INFO - Epoch(val) [1120][20/500] eta: 0:00:21 time: 0.0455 data_time: 0.0036 memory: 1008 2022/11/03 01:58:07 - mmengine - INFO - Epoch(val) [1120][25/500] eta: 0:00:21 time: 0.0484 data_time: 0.0040 memory: 1008 2022/11/03 01:58:07 - mmengine - INFO - Epoch(val) [1120][30/500] eta: 0:00:23 time: 0.0493 data_time: 0.0031 memory: 1008 2022/11/03 01:58:07 - mmengine - INFO - Epoch(val) [1120][35/500] eta: 0:00:23 time: 0.0430 data_time: 0.0027 memory: 1008 2022/11/03 01:58:08 - mmengine - INFO - Epoch(val) [1120][40/500] eta: 0:00:20 time: 0.0451 data_time: 0.0028 memory: 1008 2022/11/03 01:58:08 - mmengine - INFO - Epoch(val) [1120][45/500] eta: 0:00:20 time: 0.0479 data_time: 0.0028 memory: 1008 2022/11/03 01:58:08 - mmengine - INFO - Epoch(val) [1120][50/500] eta: 0:00:20 time: 0.0454 data_time: 0.0026 memory: 1008 2022/11/03 01:58:08 - mmengine - INFO - Epoch(val) [1120][55/500] eta: 0:00:20 time: 0.0490 data_time: 0.0028 memory: 1008 2022/11/03 01:58:08 - mmengine - INFO - Epoch(val) [1120][60/500] eta: 0:00:20 time: 0.0464 data_time: 0.0028 memory: 1008 2022/11/03 01:58:09 - mmengine - INFO - Epoch(val) [1120][65/500] eta: 0:00:20 time: 0.0475 data_time: 0.0028 memory: 1008 2022/11/03 01:58:09 - mmengine - INFO - Epoch(val) [1120][70/500] eta: 0:00:21 time: 0.0505 data_time: 0.0031 memory: 1008 2022/11/03 01:58:09 - mmengine - INFO - Epoch(val) [1120][75/500] eta: 0:00:21 time: 0.0444 data_time: 0.0030 memory: 1008 2022/11/03 01:58:09 - mmengine - INFO - Epoch(val) [1120][80/500] eta: 0:00:16 time: 0.0404 data_time: 0.0027 memory: 1008 2022/11/03 01:58:10 - mmengine - INFO - Epoch(val) [1120][85/500] eta: 0:00:16 time: 0.0410 data_time: 0.0027 memory: 1008 2022/11/03 01:58:10 - mmengine - INFO - Epoch(val) [1120][90/500] eta: 0:00:18 time: 0.0452 data_time: 0.0028 memory: 1008 2022/11/03 01:58:10 - mmengine - INFO - Epoch(val) [1120][95/500] eta: 0:00:18 time: 0.0464 data_time: 0.0028 memory: 1008 2022/11/03 01:58:10 - mmengine - INFO - Epoch(val) [1120][100/500] eta: 0:00:19 time: 0.0476 data_time: 0.0028 memory: 1008 2022/11/03 01:58:11 - mmengine - INFO - Epoch(val) [1120][105/500] eta: 0:00:19 time: 0.0484 data_time: 0.0034 memory: 1008 2022/11/03 01:58:11 - mmengine - INFO - Epoch(val) [1120][110/500] eta: 0:00:17 time: 0.0455 data_time: 0.0033 memory: 1008 2022/11/03 01:58:11 - mmengine - INFO - Epoch(val) [1120][115/500] eta: 0:00:17 time: 0.0464 data_time: 0.0031 memory: 1008 2022/11/03 01:58:11 - mmengine - INFO - Epoch(val) [1120][120/500] eta: 0:00:16 time: 0.0440 data_time: 0.0029 memory: 1008 2022/11/03 01:58:11 - mmengine - INFO - Epoch(val) [1120][125/500] eta: 0:00:16 time: 0.0428 data_time: 0.0026 memory: 1008 2022/11/03 01:58:12 - mmengine - INFO - Epoch(val) [1120][130/500] eta: 0:00:16 time: 0.0450 data_time: 0.0028 memory: 1008 2022/11/03 01:58:12 - mmengine - INFO - Epoch(val) [1120][135/500] eta: 0:00:16 time: 0.0428 data_time: 0.0028 memory: 1008 2022/11/03 01:58:12 - mmengine - INFO - Epoch(val) [1120][140/500] eta: 0:00:14 time: 0.0403 data_time: 0.0026 memory: 1008 2022/11/03 01:58:12 - mmengine - INFO - Epoch(val) [1120][145/500] eta: 0:00:14 time: 0.0462 data_time: 0.0027 memory: 1008 2022/11/03 01:58:13 - mmengine - INFO - Epoch(val) [1120][150/500] eta: 0:00:17 time: 0.0494 data_time: 0.0030 memory: 1008 2022/11/03 01:58:13 - mmengine - INFO - Epoch(val) [1120][155/500] eta: 0:00:17 time: 0.0531 data_time: 0.0034 memory: 1008 2022/11/03 01:58:13 - mmengine - INFO - Epoch(val) [1120][160/500] eta: 0:00:18 time: 0.0543 data_time: 0.0038 memory: 1008 2022/11/03 01:58:13 - mmengine - INFO - Epoch(val) [1120][165/500] eta: 0:00:18 time: 0.0477 data_time: 0.0037 memory: 1008 2022/11/03 01:58:14 - mmengine - INFO - Epoch(val) [1120][170/500] eta: 0:00:15 time: 0.0455 data_time: 0.0033 memory: 1008 2022/11/03 01:58:14 - mmengine - INFO - Epoch(val) [1120][175/500] eta: 0:00:15 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/03 01:58:14 - mmengine - INFO - Epoch(val) [1120][180/500] eta: 0:00:12 time: 0.0404 data_time: 0.0027 memory: 1008 2022/11/03 01:58:14 - mmengine - INFO - Epoch(val) [1120][185/500] eta: 0:00:12 time: 0.0457 data_time: 0.0029 memory: 1008 2022/11/03 01:58:14 - mmengine - INFO - Epoch(val) [1120][190/500] eta: 0:00:15 time: 0.0486 data_time: 0.0028 memory: 1008 2022/11/03 01:58:15 - mmengine - INFO - Epoch(val) [1120][195/500] eta: 0:00:15 time: 0.0451 data_time: 0.0029 memory: 1008 2022/11/03 01:58:15 - mmengine - INFO - Epoch(val) [1120][200/500] eta: 0:00:15 time: 0.0514 data_time: 0.0031 memory: 1008 2022/11/03 01:58:15 - mmengine - INFO - Epoch(val) [1120][205/500] eta: 0:00:15 time: 0.0517 data_time: 0.0029 memory: 1008 2022/11/03 01:58:15 - mmengine - INFO - Epoch(val) [1120][210/500] eta: 0:00:12 time: 0.0414 data_time: 0.0027 memory: 1008 2022/11/03 01:58:16 - mmengine - INFO - Epoch(val) [1120][215/500] eta: 0:00:12 time: 0.0424 data_time: 0.0026 memory: 1008 2022/11/03 01:58:16 - mmengine - INFO - Epoch(val) [1120][220/500] eta: 0:00:12 time: 0.0440 data_time: 0.0027 memory: 1008 2022/11/03 01:58:16 - mmengine - INFO - Epoch(val) [1120][225/500] eta: 0:00:12 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/03 01:58:16 - mmengine - INFO - Epoch(val) [1120][230/500] eta: 0:00:11 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/03 01:58:16 - mmengine - INFO - Epoch(val) [1120][235/500] eta: 0:00:11 time: 0.0413 data_time: 0.0026 memory: 1008 2022/11/03 01:58:17 - mmengine - INFO - Epoch(val) [1120][240/500] eta: 0:00:12 time: 0.0490 data_time: 0.0039 memory: 1008 2022/11/03 01:58:17 - mmengine - INFO - Epoch(val) [1120][245/500] eta: 0:00:12 time: 0.0552 data_time: 0.0048 memory: 1008 2022/11/03 01:58:17 - mmengine - INFO - Epoch(val) [1120][250/500] eta: 0:00:12 time: 0.0507 data_time: 0.0037 memory: 1008 2022/11/03 01:58:17 - mmengine - INFO - Epoch(val) [1120][255/500] eta: 0:00:12 time: 0.0458 data_time: 0.0032 memory: 1008 2022/11/03 01:58:18 - mmengine - INFO - Epoch(val) [1120][260/500] eta: 0:00:10 time: 0.0456 data_time: 0.0034 memory: 1008 2022/11/03 01:58:18 - mmengine - INFO - Epoch(val) [1120][265/500] eta: 0:00:10 time: 0.0454 data_time: 0.0032 memory: 1008 2022/11/03 01:58:18 - mmengine - INFO - Epoch(val) [1120][270/500] eta: 0:00:10 time: 0.0436 data_time: 0.0027 memory: 1008 2022/11/03 01:58:18 - mmengine - INFO - Epoch(val) [1120][275/500] eta: 0:00:10 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/03 01:58:19 - mmengine - INFO - Epoch(val) [1120][280/500] eta: 0:00:10 time: 0.0467 data_time: 0.0026 memory: 1008 2022/11/03 01:58:19 - mmengine - INFO - Epoch(val) [1120][285/500] eta: 0:00:10 time: 0.0478 data_time: 0.0031 memory: 1008 2022/11/03 01:58:19 - mmengine - INFO - Epoch(val) [1120][290/500] eta: 0:00:08 time: 0.0421 data_time: 0.0032 memory: 1008 2022/11/03 01:58:19 - mmengine - INFO - Epoch(val) [1120][295/500] eta: 0:00:08 time: 0.0426 data_time: 0.0027 memory: 1008 2022/11/03 01:58:19 - mmengine - INFO - Epoch(val) [1120][300/500] eta: 0:00:08 time: 0.0407 data_time: 0.0026 memory: 1008 2022/11/03 01:58:20 - mmengine - INFO - Epoch(val) [1120][305/500] eta: 0:00:08 time: 0.0416 data_time: 0.0025 memory: 1008 2022/11/03 01:58:20 - mmengine - INFO - Epoch(val) [1120][310/500] eta: 0:00:08 time: 0.0450 data_time: 0.0029 memory: 1008 2022/11/03 01:58:20 - mmengine - INFO - Epoch(val) [1120][315/500] eta: 0:00:08 time: 0.0477 data_time: 0.0039 memory: 1008 2022/11/03 01:58:20 - mmengine - INFO - Epoch(val) [1120][320/500] eta: 0:00:08 time: 0.0445 data_time: 0.0036 memory: 1008 2022/11/03 01:58:21 - mmengine - INFO - Epoch(val) [1120][325/500] eta: 0:00:08 time: 0.0519 data_time: 0.0030 memory: 1008 2022/11/03 01:58:21 - mmengine - INFO - Epoch(val) [1120][330/500] eta: 0:00:09 time: 0.0532 data_time: 0.0025 memory: 1008 2022/11/03 01:58:21 - mmengine - INFO - Epoch(val) [1120][335/500] eta: 0:00:09 time: 0.0429 data_time: 0.0027 memory: 1008 2022/11/03 01:58:21 - mmengine - INFO - Epoch(val) [1120][340/500] eta: 0:00:09 time: 0.0610 data_time: 0.0031 memory: 1008 2022/11/03 01:58:22 - mmengine - INFO - Epoch(val) [1120][345/500] eta: 0:00:09 time: 0.0623 data_time: 0.0028 memory: 1008 2022/11/03 01:58:22 - mmengine - INFO - Epoch(val) [1120][350/500] eta: 0:00:07 time: 0.0474 data_time: 0.0027 memory: 1008 2022/11/03 01:58:22 - mmengine - INFO - Epoch(val) [1120][355/500] eta: 0:00:07 time: 0.0458 data_time: 0.0037 memory: 1008 2022/11/03 01:58:22 - mmengine - INFO - Epoch(val) [1120][360/500] eta: 0:00:06 time: 0.0429 data_time: 0.0037 memory: 1008 2022/11/03 01:58:23 - mmengine - INFO - Epoch(val) [1120][365/500] eta: 0:00:06 time: 0.0436 data_time: 0.0025 memory: 1008 2022/11/03 01:58:23 - mmengine - INFO - Epoch(val) [1120][370/500] eta: 0:00:05 time: 0.0438 data_time: 0.0031 memory: 1008 2022/11/03 01:58:23 - mmengine - INFO - Epoch(val) [1120][375/500] eta: 0:00:05 time: 0.0456 data_time: 0.0039 memory: 1008 2022/11/03 01:58:23 - mmengine - INFO - Epoch(val) [1120][380/500] eta: 0:00:05 time: 0.0498 data_time: 0.0036 memory: 1008 2022/11/03 01:58:24 - mmengine - INFO - Epoch(val) [1120][385/500] eta: 0:00:05 time: 0.0486 data_time: 0.0031 memory: 1008 2022/11/03 01:58:24 - mmengine - INFO - Epoch(val) [1120][390/500] eta: 0:00:04 time: 0.0446 data_time: 0.0033 memory: 1008 2022/11/03 01:58:24 - mmengine - INFO - Epoch(val) [1120][395/500] eta: 0:00:04 time: 0.0437 data_time: 0.0032 memory: 1008 2022/11/03 01:58:24 - mmengine - INFO - Epoch(val) [1120][400/500] eta: 0:00:04 time: 0.0440 data_time: 0.0029 memory: 1008 2022/11/03 01:58:24 - mmengine - INFO - Epoch(val) [1120][405/500] eta: 0:00:04 time: 0.0452 data_time: 0.0029 memory: 1008 2022/11/03 01:58:25 - mmengine - INFO - Epoch(val) [1120][410/500] eta: 0:00:04 time: 0.0497 data_time: 0.0032 memory: 1008 2022/11/03 01:58:25 - mmengine - INFO - Epoch(val) [1120][415/500] eta: 0:00:04 time: 0.0517 data_time: 0.0035 memory: 1008 2022/11/03 01:58:25 - mmengine - INFO - Epoch(val) [1120][420/500] eta: 0:00:03 time: 0.0439 data_time: 0.0031 memory: 1008 2022/11/03 01:58:25 - mmengine - INFO - Epoch(val) [1120][425/500] eta: 0:00:03 time: 0.0414 data_time: 0.0026 memory: 1008 2022/11/03 01:58:26 - mmengine - INFO - Epoch(val) [1120][430/500] eta: 0:00:03 time: 0.0446 data_time: 0.0028 memory: 1008 2022/11/03 01:58:26 - mmengine - INFO - Epoch(val) [1120][435/500] eta: 0:00:03 time: 0.0438 data_time: 0.0030 memory: 1008 2022/11/03 01:58:26 - mmengine - INFO - Epoch(val) [1120][440/500] eta: 0:00:02 time: 0.0408 data_time: 0.0030 memory: 1008 2022/11/03 01:58:26 - mmengine - INFO - Epoch(val) [1120][445/500] eta: 0:00:02 time: 0.0438 data_time: 0.0029 memory: 1008 2022/11/03 01:58:26 - mmengine - INFO - Epoch(val) [1120][450/500] eta: 0:00:02 time: 0.0473 data_time: 0.0028 memory: 1008 2022/11/03 01:58:27 - mmengine - INFO - Epoch(val) [1120][455/500] eta: 0:00:02 time: 0.0439 data_time: 0.0028 memory: 1008 2022/11/03 01:58:27 - mmengine - INFO - Epoch(val) [1120][460/500] eta: 0:00:01 time: 0.0407 data_time: 0.0028 memory: 1008 2022/11/03 01:58:27 - mmengine - INFO - Epoch(val) [1120][465/500] eta: 0:00:01 time: 0.0381 data_time: 0.0027 memory: 1008 2022/11/03 01:58:27 - mmengine - INFO - Epoch(val) [1120][470/500] eta: 0:00:01 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/03 01:58:27 - mmengine - INFO - Epoch(val) [1120][475/500] eta: 0:00:01 time: 0.0395 data_time: 0.0026 memory: 1008 2022/11/03 01:58:28 - mmengine - INFO - Epoch(val) [1120][480/500] eta: 0:00:00 time: 0.0397 data_time: 0.0026 memory: 1008 2022/11/03 01:58:28 - mmengine - INFO - Epoch(val) [1120][485/500] eta: 0:00:00 time: 0.0387 data_time: 0.0025 memory: 1008 2022/11/03 01:58:28 - mmengine - INFO - Epoch(val) [1120][490/500] eta: 0:00:00 time: 0.0436 data_time: 0.0025 memory: 1008 2022/11/03 01:58:28 - mmengine - INFO - Epoch(val) [1120][495/500] eta: 0:00:00 time: 0.0512 data_time: 0.0030 memory: 1008 2022/11/03 01:58:29 - mmengine - INFO - Epoch(val) [1120][500/500] eta: 0:00:00 time: 0.0466 data_time: 0.0029 memory: 1008 2022/11/03 01:58:29 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8262, precision: 0.7644, hmean: 0.7941 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8262, precision: 0.8137, hmean: 0.8199 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8262, precision: 0.8379, hmean: 0.8320 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8219, precision: 0.8599, hmean: 0.8405 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8098, precision: 0.8774, hmean: 0.8423 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7338, precision: 0.9186, hmean: 0.8158 2022/11/03 01:58:29 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2085, precision: 0.9558, hmean: 0.3423 2022/11/03 01:58:29 - mmengine - INFO - Epoch(val) [1120][500/500] icdar/precision: 0.8774 icdar/recall: 0.8098 icdar/hmean: 0.8423 2022/11/03 01:58:36 - mmengine - INFO - Epoch(train) [1121][5/63] lr: 1.8716e-04 eta: 0:00:00 time: 1.0257 data_time: 0.2819 memory: 14901 loss: 0.9748 loss_prob: 0.5153 loss_thr: 0.3687 loss_db: 0.0909 2022/11/03 01:58:39 - mmengine - INFO - Epoch(train) [1121][10/63] lr: 1.8716e-04 eta: 0:55:38 time: 1.0504 data_time: 0.2814 memory: 14901 loss: 0.8723 loss_prob: 0.4502 loss_thr: 0.3429 loss_db: 0.0792 2022/11/03 01:58:42 - mmengine - INFO - Epoch(train) [1121][15/63] lr: 1.8716e-04 eta: 0:55:38 time: 0.5653 data_time: 0.0079 memory: 14901 loss: 0.8875 loss_prob: 0.4505 loss_thr: 0.3577 loss_db: 0.0793 2022/11/03 01:58:46 - mmengine - INFO - Epoch(train) [1121][20/63] lr: 1.8716e-04 eta: 0:55:31 time: 0.6832 data_time: 0.0092 memory: 14901 loss: 0.8823 loss_prob: 0.4502 loss_thr: 0.3528 loss_db: 0.0794 2022/11/03 01:58:52 - mmengine - INFO - Epoch(train) [1121][25/63] lr: 1.8716e-04 eta: 0:55:31 time: 0.9679 data_time: 0.0403 memory: 14901 loss: 0.8524 loss_prob: 0.4397 loss_thr: 0.3358 loss_db: 0.0770 2022/11/03 01:58:55 - mmengine - INFO - Epoch(train) [1121][30/63] lr: 1.8716e-04 eta: 0:55:25 time: 0.9275 data_time: 0.0392 memory: 14901 loss: 0.8436 loss_prob: 0.4341 loss_thr: 0.3340 loss_db: 0.0755 2022/11/03 01:58:58 - mmengine - INFO - Epoch(train) [1121][35/63] lr: 1.8716e-04 eta: 0:55:25 time: 0.6397 data_time: 0.0054 memory: 14901 loss: 0.7747 loss_prob: 0.3893 loss_thr: 0.3188 loss_db: 0.0665 2022/11/03 01:59:03 - mmengine - INFO - Epoch(train) [1121][40/63] lr: 1.8716e-04 eta: 0:55:18 time: 0.7668 data_time: 0.0068 memory: 14901 loss: 0.7898 loss_prob: 0.4074 loss_thr: 0.3117 loss_db: 0.0706 2022/11/03 01:59:06 - mmengine - INFO - Epoch(train) [1121][45/63] lr: 1.8716e-04 eta: 0:55:18 time: 0.8432 data_time: 0.0074 memory: 14901 loss: 0.8178 loss_prob: 0.4216 loss_thr: 0.3219 loss_db: 0.0743 2022/11/03 01:59:10 - mmengine - INFO - Epoch(train) [1121][50/63] lr: 1.8716e-04 eta: 0:55:11 time: 0.6675 data_time: 0.0232 memory: 14901 loss: 0.8426 loss_prob: 0.4282 loss_thr: 0.3410 loss_db: 0.0735 2022/11/03 01:59:13 - mmengine - INFO - Epoch(train) [1121][55/63] lr: 1.8716e-04 eta: 0:55:11 time: 0.6337 data_time: 0.0228 memory: 14901 loss: 0.8900 loss_prob: 0.4629 loss_thr: 0.3475 loss_db: 0.0796 2022/11/03 01:59:17 - mmengine - INFO - Epoch(train) [1121][60/63] lr: 1.8716e-04 eta: 0:55:05 time: 0.7604 data_time: 0.0070 memory: 14901 loss: 0.8893 loss_prob: 0.4667 loss_thr: 0.3412 loss_db: 0.0814 2022/11/03 01:59:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 01:59:25 - mmengine - INFO - Epoch(train) [1122][5/63] lr: 1.8502e-04 eta: 0:55:05 time: 1.0067 data_time: 0.2556 memory: 14901 loss: 0.8781 loss_prob: 0.4564 loss_thr: 0.3414 loss_db: 0.0804 2022/11/03 01:59:29 - mmengine - INFO - Epoch(train) [1122][10/63] lr: 1.8502e-04 eta: 0:54:56 time: 1.0966 data_time: 0.2595 memory: 14901 loss: 0.9215 loss_prob: 0.4861 loss_thr: 0.3495 loss_db: 0.0859 2022/11/03 01:59:33 - mmengine - INFO - Epoch(train) [1122][15/63] lr: 1.8502e-04 eta: 0:54:56 time: 0.8060 data_time: 0.0143 memory: 14901 loss: 0.9040 loss_prob: 0.4750 loss_thr: 0.3447 loss_db: 0.0843 2022/11/03 01:59:36 - mmengine - INFO - Epoch(train) [1122][20/63] lr: 1.8502e-04 eta: 0:54:50 time: 0.6988 data_time: 0.0102 memory: 14901 loss: 0.9034 loss_prob: 0.4630 loss_thr: 0.3596 loss_db: 0.0809 2022/11/03 01:59:40 - mmengine - INFO - Epoch(train) [1122][25/63] lr: 1.8502e-04 eta: 0:54:50 time: 0.6428 data_time: 0.0230 memory: 14901 loss: 0.8442 loss_prob: 0.4356 loss_thr: 0.3328 loss_db: 0.0758 2022/11/03 01:59:42 - mmengine - INFO - Epoch(train) [1122][30/63] lr: 1.8502e-04 eta: 0:54:43 time: 0.5881 data_time: 0.0467 memory: 14901 loss: 0.8363 loss_prob: 0.4377 loss_thr: 0.3238 loss_db: 0.0749 2022/11/03 01:59:45 - mmengine - INFO - Epoch(train) [1122][35/63] lr: 1.8502e-04 eta: 0:54:43 time: 0.5496 data_time: 0.0335 memory: 14901 loss: 0.8037 loss_prob: 0.4107 loss_thr: 0.3215 loss_db: 0.0715 2022/11/03 01:59:48 - mmengine - INFO - Epoch(train) [1122][40/63] lr: 1.8502e-04 eta: 0:54:36 time: 0.5556 data_time: 0.0123 memory: 14901 loss: 0.7810 loss_prob: 0.3952 loss_thr: 0.3144 loss_db: 0.0713 2022/11/03 01:59:51 - mmengine - INFO - Epoch(train) [1122][45/63] lr: 1.8502e-04 eta: 0:54:36 time: 0.5583 data_time: 0.0087 memory: 14901 loss: 0.8371 loss_prob: 0.4276 loss_thr: 0.3344 loss_db: 0.0750 2022/11/03 01:59:54 - mmengine - INFO - Epoch(train) [1122][50/63] lr: 1.8502e-04 eta: 0:54:30 time: 0.5856 data_time: 0.0196 memory: 14901 loss: 0.8926 loss_prob: 0.4608 loss_thr: 0.3515 loss_db: 0.0803 2022/11/03 01:59:57 - mmengine - INFO - Epoch(train) [1122][55/63] lr: 1.8502e-04 eta: 0:54:30 time: 0.6024 data_time: 0.0231 memory: 14901 loss: 0.8721 loss_prob: 0.4464 loss_thr: 0.3471 loss_db: 0.0787 2022/11/03 01:59:59 - mmengine - INFO - Epoch(train) [1122][60/63] lr: 1.8502e-04 eta: 0:54:23 time: 0.5722 data_time: 0.0101 memory: 14901 loss: 0.8705 loss_prob: 0.4364 loss_thr: 0.3562 loss_db: 0.0779 2022/11/03 02:00:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:00:07 - mmengine - INFO - Epoch(train) [1123][5/63] lr: 1.8289e-04 eta: 0:54:23 time: 0.8391 data_time: 0.3025 memory: 14901 loss: 0.8640 loss_prob: 0.4368 loss_thr: 0.3494 loss_db: 0.0778 2022/11/03 02:00:11 - mmengine - INFO - Epoch(train) [1123][10/63] lr: 1.8289e-04 eta: 0:54:14 time: 1.0147 data_time: 0.3032 memory: 14901 loss: 0.8995 loss_prob: 0.4692 loss_thr: 0.3492 loss_db: 0.0811 2022/11/03 02:00:17 - mmengine - INFO - Epoch(train) [1123][15/63] lr: 1.8289e-04 eta: 0:54:14 time: 1.0149 data_time: 0.0112 memory: 14901 loss: 0.9685 loss_prob: 0.5175 loss_thr: 0.3654 loss_db: 0.0856 2022/11/03 02:00:24 - mmengine - INFO - Epoch(train) [1123][20/63] lr: 1.8289e-04 eta: 0:54:08 time: 1.2662 data_time: 0.0114 memory: 14901 loss: 0.9713 loss_prob: 0.5169 loss_thr: 0.3671 loss_db: 0.0873 2022/11/03 02:00:29 - mmengine - INFO - Epoch(train) [1123][25/63] lr: 1.8289e-04 eta: 0:54:08 time: 1.1734 data_time: 0.0492 memory: 14901 loss: 0.8895 loss_prob: 0.4657 loss_thr: 0.3415 loss_db: 0.0823 2022/11/03 02:00:34 - mmengine - INFO - Epoch(train) [1123][30/63] lr: 1.8289e-04 eta: 0:54:02 time: 1.0063 data_time: 0.0484 memory: 14901 loss: 0.8475 loss_prob: 0.4318 loss_thr: 0.3403 loss_db: 0.0753 2022/11/03 02:00:38 - mmengine - INFO - Epoch(train) [1123][35/63] lr: 1.8289e-04 eta: 0:54:02 time: 0.9151 data_time: 0.0070 memory: 14901 loss: 0.8628 loss_prob: 0.4344 loss_thr: 0.3538 loss_db: 0.0747 2022/11/03 02:00:41 - mmengine - INFO - Epoch(train) [1123][40/63] lr: 1.8289e-04 eta: 0:53:55 time: 0.6968 data_time: 0.0136 memory: 14901 loss: 0.8753 loss_prob: 0.4530 loss_thr: 0.3428 loss_db: 0.0795 2022/11/03 02:00:44 - mmengine - INFO - Epoch(train) [1123][45/63] lr: 1.8289e-04 eta: 0:53:55 time: 0.6409 data_time: 0.0167 memory: 14901 loss: 0.8709 loss_prob: 0.4527 loss_thr: 0.3385 loss_db: 0.0796 2022/11/03 02:00:47 - mmengine - INFO - Epoch(train) [1123][50/63] lr: 1.8289e-04 eta: 0:53:49 time: 0.6323 data_time: 0.0263 memory: 14901 loss: 0.8909 loss_prob: 0.4580 loss_thr: 0.3522 loss_db: 0.0807 2022/11/03 02:00:50 - mmengine - INFO - Epoch(train) [1123][55/63] lr: 1.8289e-04 eta: 0:53:49 time: 0.5441 data_time: 0.0244 memory: 14901 loss: 0.8859 loss_prob: 0.4543 loss_thr: 0.3510 loss_db: 0.0806 2022/11/03 02:00:53 - mmengine - INFO - Epoch(train) [1123][60/63] lr: 1.8289e-04 eta: 0:53:42 time: 0.5783 data_time: 0.0103 memory: 14901 loss: 0.8025 loss_prob: 0.4036 loss_thr: 0.3272 loss_db: 0.0717 2022/11/03 02:00:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:01:00 - mmengine - INFO - Epoch(train) [1124][5/63] lr: 1.8075e-04 eta: 0:53:42 time: 0.8547 data_time: 0.2206 memory: 14901 loss: 0.8122 loss_prob: 0.4179 loss_thr: 0.3223 loss_db: 0.0720 2022/11/03 02:01:04 - mmengine - INFO - Epoch(train) [1124][10/63] lr: 1.8075e-04 eta: 0:53:33 time: 0.9531 data_time: 0.2235 memory: 14901 loss: 0.8363 loss_prob: 0.4310 loss_thr: 0.3312 loss_db: 0.0742 2022/11/03 02:01:10 - mmengine - INFO - Epoch(train) [1124][15/63] lr: 1.8075e-04 eta: 0:53:33 time: 0.9398 data_time: 0.0145 memory: 14901 loss: 0.7919 loss_prob: 0.4039 loss_thr: 0.3181 loss_db: 0.0699 2022/11/03 02:01:15 - mmengine - INFO - Epoch(train) [1124][20/63] lr: 1.8075e-04 eta: 0:53:27 time: 1.1191 data_time: 0.0083 memory: 14901 loss: 0.8248 loss_prob: 0.4261 loss_thr: 0.3250 loss_db: 0.0737 2022/11/03 02:01:19 - mmengine - INFO - Epoch(train) [1124][25/63] lr: 1.8075e-04 eta: 0:53:27 time: 0.9337 data_time: 0.0179 memory: 14901 loss: 0.8292 loss_prob: 0.4305 loss_thr: 0.3234 loss_db: 0.0752 2022/11/03 02:01:23 - mmengine - INFO - Epoch(train) [1124][30/63] lr: 1.8075e-04 eta: 0:53:20 time: 0.7793 data_time: 0.0436 memory: 14901 loss: 0.8803 loss_prob: 0.4590 loss_thr: 0.3397 loss_db: 0.0817 2022/11/03 02:01:25 - mmengine - INFO - Epoch(train) [1124][35/63] lr: 1.8075e-04 eta: 0:53:20 time: 0.6340 data_time: 0.0324 memory: 14901 loss: 0.9418 loss_prob: 0.4881 loss_thr: 0.3684 loss_db: 0.0854 2022/11/03 02:01:30 - mmengine - INFO - Epoch(train) [1124][40/63] lr: 1.8075e-04 eta: 0:53:14 time: 0.7278 data_time: 0.0066 memory: 14901 loss: 0.9736 loss_prob: 0.5088 loss_thr: 0.3777 loss_db: 0.0871 2022/11/03 02:01:34 - mmengine - INFO - Epoch(train) [1124][45/63] lr: 1.8075e-04 eta: 0:53:14 time: 0.8547 data_time: 0.0077 memory: 14901 loss: 0.9671 loss_prob: 0.5101 loss_thr: 0.3698 loss_db: 0.0872 2022/11/03 02:01:40 - mmengine - INFO - Epoch(train) [1124][50/63] lr: 1.8075e-04 eta: 0:53:07 time: 0.9859 data_time: 0.0177 memory: 14901 loss: 0.8828 loss_prob: 0.4542 loss_thr: 0.3491 loss_db: 0.0794 2022/11/03 02:01:44 - mmengine - INFO - Epoch(train) [1124][55/63] lr: 1.8075e-04 eta: 0:53:07 time: 1.0123 data_time: 0.0247 memory: 14901 loss: 0.8106 loss_prob: 0.4008 loss_thr: 0.3376 loss_db: 0.0723 2022/11/03 02:01:49 - mmengine - INFO - Epoch(train) [1124][60/63] lr: 1.8075e-04 eta: 0:53:01 time: 0.9217 data_time: 0.0164 memory: 14901 loss: 0.7840 loss_prob: 0.3828 loss_thr: 0.3325 loss_db: 0.0687 2022/11/03 02:01:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:01:58 - mmengine - INFO - Epoch(train) [1125][5/63] lr: 1.7861e-04 eta: 0:53:01 time: 1.0417 data_time: 0.2763 memory: 14901 loss: 0.8776 loss_prob: 0.4547 loss_thr: 0.3439 loss_db: 0.0790 2022/11/03 02:02:03 - mmengine - INFO - Epoch(train) [1125][10/63] lr: 1.7861e-04 eta: 0:52:53 time: 1.2871 data_time: 0.2771 memory: 14901 loss: 0.8287 loss_prob: 0.4273 loss_thr: 0.3268 loss_db: 0.0747 2022/11/03 02:02:08 - mmengine - INFO - Epoch(train) [1125][15/63] lr: 1.7861e-04 eta: 0:52:53 time: 1.0256 data_time: 0.0077 memory: 14901 loss: 0.8909 loss_prob: 0.4618 loss_thr: 0.3494 loss_db: 0.0797 2022/11/03 02:02:11 - mmengine - INFO - Epoch(train) [1125][20/63] lr: 1.7861e-04 eta: 0:52:46 time: 0.7749 data_time: 0.0063 memory: 14901 loss: 0.9430 loss_prob: 0.4851 loss_thr: 0.3747 loss_db: 0.0832 2022/11/03 02:02:15 - mmengine - INFO - Epoch(train) [1125][25/63] lr: 1.7861e-04 eta: 0:52:46 time: 0.7136 data_time: 0.0080 memory: 14901 loss: 0.8390 loss_prob: 0.4286 loss_thr: 0.3356 loss_db: 0.0747 2022/11/03 02:02:20 - mmengine - INFO - Epoch(train) [1125][30/63] lr: 1.7861e-04 eta: 0:52:39 time: 0.8880 data_time: 0.0386 memory: 14901 loss: 0.8550 loss_prob: 0.4448 loss_thr: 0.3328 loss_db: 0.0775 2022/11/03 02:02:23 - mmengine - INFO - Epoch(train) [1125][35/63] lr: 1.7861e-04 eta: 0:52:39 time: 0.7245 data_time: 0.0367 memory: 14901 loss: 0.9560 loss_prob: 0.5063 loss_thr: 0.3631 loss_db: 0.0867 2022/11/03 02:02:26 - mmengine - INFO - Epoch(train) [1125][40/63] lr: 1.7861e-04 eta: 0:52:33 time: 0.5680 data_time: 0.0055 memory: 14901 loss: 0.8877 loss_prob: 0.4651 loss_thr: 0.3431 loss_db: 0.0795 2022/11/03 02:02:28 - mmengine - INFO - Epoch(train) [1125][45/63] lr: 1.7861e-04 eta: 0:52:33 time: 0.5691 data_time: 0.0055 memory: 14901 loss: 0.8375 loss_prob: 0.4287 loss_thr: 0.3349 loss_db: 0.0739 2022/11/03 02:02:32 - mmengine - INFO - Epoch(train) [1125][50/63] lr: 1.7861e-04 eta: 0:52:26 time: 0.5796 data_time: 0.0265 memory: 14901 loss: 0.8019 loss_prob: 0.4118 loss_thr: 0.3185 loss_db: 0.0716 2022/11/03 02:02:35 - mmengine - INFO - Epoch(train) [1125][55/63] lr: 1.7861e-04 eta: 0:52:26 time: 0.6361 data_time: 0.0261 memory: 14901 loss: 0.8124 loss_prob: 0.4161 loss_thr: 0.3236 loss_db: 0.0726 2022/11/03 02:02:38 - mmengine - INFO - Epoch(train) [1125][60/63] lr: 1.7861e-04 eta: 0:52:19 time: 0.6146 data_time: 0.0049 memory: 14901 loss: 0.8493 loss_prob: 0.4358 loss_thr: 0.3364 loss_db: 0.0770 2022/11/03 02:02:40 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:02:48 - mmengine - INFO - Epoch(train) [1126][5/63] lr: 1.7647e-04 eta: 0:52:19 time: 1.1160 data_time: 0.2009 memory: 14901 loss: 0.7991 loss_prob: 0.4059 loss_thr: 0.3208 loss_db: 0.0724 2022/11/03 02:02:52 - mmengine - INFO - Epoch(train) [1126][10/63] lr: 1.7647e-04 eta: 0:52:11 time: 1.1835 data_time: 0.2081 memory: 14901 loss: 0.8359 loss_prob: 0.4226 loss_thr: 0.3385 loss_db: 0.0748 2022/11/03 02:02:55 - mmengine - INFO - Epoch(train) [1126][15/63] lr: 1.7647e-04 eta: 0:52:11 time: 0.7488 data_time: 0.0129 memory: 14901 loss: 0.9522 loss_prob: 0.5007 loss_thr: 0.3638 loss_db: 0.0877 2022/11/03 02:03:01 - mmengine - INFO - Epoch(train) [1126][20/63] lr: 1.7647e-04 eta: 0:52:05 time: 0.9290 data_time: 0.0064 memory: 14901 loss: 0.9140 loss_prob: 0.4791 loss_thr: 0.3528 loss_db: 0.0820 2022/11/03 02:03:04 - mmengine - INFO - Epoch(train) [1126][25/63] lr: 1.7647e-04 eta: 0:52:05 time: 0.8463 data_time: 0.0136 memory: 14901 loss: 0.9635 loss_prob: 0.5100 loss_thr: 0.3678 loss_db: 0.0858 2022/11/03 02:03:07 - mmengine - INFO - Epoch(train) [1126][30/63] lr: 1.7647e-04 eta: 0:51:58 time: 0.6219 data_time: 0.0362 memory: 14901 loss: 0.9742 loss_prob: 0.5191 loss_thr: 0.3650 loss_db: 0.0901 2022/11/03 02:03:10 - mmengine - INFO - Epoch(train) [1126][35/63] lr: 1.7647e-04 eta: 0:51:58 time: 0.6070 data_time: 0.0346 memory: 14901 loss: 0.8807 loss_prob: 0.4489 loss_thr: 0.3508 loss_db: 0.0810 2022/11/03 02:03:12 - mmengine - INFO - Epoch(train) [1126][40/63] lr: 1.7647e-04 eta: 0:51:51 time: 0.5003 data_time: 0.0110 memory: 14901 loss: 0.8782 loss_prob: 0.4447 loss_thr: 0.3541 loss_db: 0.0795 2022/11/03 02:03:14 - mmengine - INFO - Epoch(train) [1126][45/63] lr: 1.7647e-04 eta: 0:51:51 time: 0.4444 data_time: 0.0046 memory: 14901 loss: 0.9097 loss_prob: 0.4649 loss_thr: 0.3630 loss_db: 0.0818 2022/11/03 02:03:17 - mmengine - INFO - Epoch(train) [1126][50/63] lr: 1.7647e-04 eta: 0:51:44 time: 0.4828 data_time: 0.0097 memory: 14901 loss: 0.9112 loss_prob: 0.4683 loss_thr: 0.3630 loss_db: 0.0799 2022/11/03 02:03:19 - mmengine - INFO - Epoch(train) [1126][55/63] lr: 1.7647e-04 eta: 0:51:44 time: 0.5176 data_time: 0.0185 memory: 14901 loss: 0.8834 loss_prob: 0.4556 loss_thr: 0.3504 loss_db: 0.0774 2022/11/03 02:03:22 - mmengine - INFO - Epoch(train) [1126][60/63] lr: 1.7647e-04 eta: 0:51:38 time: 0.4969 data_time: 0.0144 memory: 14901 loss: 0.8743 loss_prob: 0.4592 loss_thr: 0.3348 loss_db: 0.0802 2022/11/03 02:03:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:03:28 - mmengine - INFO - Epoch(train) [1127][5/63] lr: 1.7432e-04 eta: 0:51:38 time: 0.6924 data_time: 0.2311 memory: 14901 loss: 0.7622 loss_prob: 0.3885 loss_thr: 0.3048 loss_db: 0.0690 2022/11/03 02:03:30 - mmengine - INFO - Epoch(train) [1127][10/63] lr: 1.7432e-04 eta: 0:51:29 time: 0.6993 data_time: 0.2313 memory: 14901 loss: 0.8343 loss_prob: 0.4263 loss_thr: 0.3341 loss_db: 0.0739 2022/11/03 02:03:32 - mmengine - INFO - Epoch(train) [1127][15/63] lr: 1.7432e-04 eta: 0:51:29 time: 0.4678 data_time: 0.0057 memory: 14901 loss: 0.9268 loss_prob: 0.4772 loss_thr: 0.3670 loss_db: 0.0826 2022/11/03 02:03:35 - mmengine - INFO - Epoch(train) [1127][20/63] lr: 1.7432e-04 eta: 0:51:22 time: 0.4949 data_time: 0.0101 memory: 14901 loss: 0.9073 loss_prob: 0.4613 loss_thr: 0.3667 loss_db: 0.0793 2022/11/03 02:03:38 - mmengine - INFO - Epoch(train) [1127][25/63] lr: 1.7432e-04 eta: 0:51:22 time: 0.5137 data_time: 0.0210 memory: 14901 loss: 0.8351 loss_prob: 0.4248 loss_thr: 0.3377 loss_db: 0.0726 2022/11/03 02:03:40 - mmengine - INFO - Epoch(train) [1127][30/63] lr: 1.7432e-04 eta: 0:51:15 time: 0.5117 data_time: 0.0275 memory: 14901 loss: 0.8923 loss_prob: 0.4699 loss_thr: 0.3415 loss_db: 0.0809 2022/11/03 02:03:43 - mmengine - INFO - Epoch(train) [1127][35/63] lr: 1.7432e-04 eta: 0:51:15 time: 0.4915 data_time: 0.0166 memory: 14901 loss: 0.9499 loss_prob: 0.5089 loss_thr: 0.3524 loss_db: 0.0886 2022/11/03 02:03:45 - mmengine - INFO - Epoch(train) [1127][40/63] lr: 1.7432e-04 eta: 0:51:09 time: 0.4701 data_time: 0.0072 memory: 14901 loss: 0.8914 loss_prob: 0.4653 loss_thr: 0.3437 loss_db: 0.0825 2022/11/03 02:03:47 - mmengine - INFO - Epoch(train) [1127][45/63] lr: 1.7432e-04 eta: 0:51:09 time: 0.4721 data_time: 0.0084 memory: 14901 loss: 0.8966 loss_prob: 0.4632 loss_thr: 0.3524 loss_db: 0.0811 2022/11/03 02:03:50 - mmengine - INFO - Epoch(train) [1127][50/63] lr: 1.7432e-04 eta: 0:51:02 time: 0.4883 data_time: 0.0115 memory: 14901 loss: 0.8642 loss_prob: 0.4486 loss_thr: 0.3364 loss_db: 0.0792 2022/11/03 02:03:52 - mmengine - INFO - Epoch(train) [1127][55/63] lr: 1.7432e-04 eta: 0:51:02 time: 0.4783 data_time: 0.0187 memory: 14901 loss: 0.8854 loss_prob: 0.4592 loss_thr: 0.3476 loss_db: 0.0786 2022/11/03 02:03:54 - mmengine - INFO - Epoch(train) [1127][60/63] lr: 1.7432e-04 eta: 0:50:55 time: 0.4732 data_time: 0.0149 memory: 14901 loss: 0.9363 loss_prob: 0.4920 loss_thr: 0.3608 loss_db: 0.0835 2022/11/03 02:03:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:03:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:04:02 - mmengine - INFO - Epoch(train) [1128][5/63] lr: 1.7217e-04 eta: 0:50:55 time: 0.8217 data_time: 0.2002 memory: 14901 loss: 0.8345 loss_prob: 0.4325 loss_thr: 0.3290 loss_db: 0.0730 2022/11/03 02:04:08 - mmengine - INFO - Epoch(train) [1128][10/63] lr: 1.7217e-04 eta: 0:50:47 time: 1.2419 data_time: 0.2043 memory: 14901 loss: 0.8361 loss_prob: 0.4350 loss_thr: 0.3265 loss_db: 0.0746 2022/11/03 02:04:17 - mmengine - INFO - Epoch(train) [1128][15/63] lr: 1.7217e-04 eta: 0:50:47 time: 1.4986 data_time: 0.0122 memory: 14901 loss: 0.8949 loss_prob: 0.4528 loss_thr: 0.3645 loss_db: 0.0776 2022/11/03 02:04:23 - mmengine - INFO - Epoch(train) [1128][20/63] lr: 1.7217e-04 eta: 0:50:41 time: 1.4469 data_time: 0.0080 memory: 14901 loss: 0.9470 loss_prob: 0.4795 loss_thr: 0.3846 loss_db: 0.0828 2022/11/03 02:04:30 - mmengine - INFO - Epoch(train) [1128][25/63] lr: 1.7217e-04 eta: 0:50:41 time: 1.3492 data_time: 0.0276 memory: 14901 loss: 0.8316 loss_prob: 0.4199 loss_thr: 0.3381 loss_db: 0.0736 2022/11/03 02:04:34 - mmengine - INFO - Epoch(train) [1128][30/63] lr: 1.7217e-04 eta: 0:50:34 time: 1.1422 data_time: 0.0473 memory: 14901 loss: 0.7325 loss_prob: 0.3648 loss_thr: 0.3033 loss_db: 0.0644 2022/11/03 02:04:38 - mmengine - INFO - Epoch(train) [1128][35/63] lr: 1.7217e-04 eta: 0:50:34 time: 0.7738 data_time: 0.0262 memory: 14901 loss: 0.8206 loss_prob: 0.4208 loss_thr: 0.3260 loss_db: 0.0737 2022/11/03 02:04:41 - mmengine - INFO - Epoch(train) [1128][40/63] lr: 1.7217e-04 eta: 0:50:28 time: 0.6698 data_time: 0.0060 memory: 14901 loss: 0.9185 loss_prob: 0.4792 loss_thr: 0.3551 loss_db: 0.0842 2022/11/03 02:04:44 - mmengine - INFO - Epoch(train) [1128][45/63] lr: 1.7217e-04 eta: 0:50:28 time: 0.5720 data_time: 0.0059 memory: 14901 loss: 0.9066 loss_prob: 0.4675 loss_thr: 0.3564 loss_db: 0.0826 2022/11/03 02:04:46 - mmengine - INFO - Epoch(train) [1128][50/63] lr: 1.7217e-04 eta: 0:50:21 time: 0.5600 data_time: 0.0152 memory: 14901 loss: 0.8851 loss_prob: 0.4622 loss_thr: 0.3429 loss_db: 0.0800 2022/11/03 02:04:50 - mmengine - INFO - Epoch(train) [1128][55/63] lr: 1.7217e-04 eta: 0:50:21 time: 0.5869 data_time: 0.0262 memory: 14901 loss: 0.8597 loss_prob: 0.4473 loss_thr: 0.3351 loss_db: 0.0773 2022/11/03 02:04:52 - mmengine - INFO - Epoch(train) [1128][60/63] lr: 1.7217e-04 eta: 0:50:14 time: 0.5975 data_time: 0.0167 memory: 14901 loss: 0.8185 loss_prob: 0.4101 loss_thr: 0.3363 loss_db: 0.0722 2022/11/03 02:04:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:05:00 - mmengine - INFO - Epoch(train) [1129][5/63] lr: 1.7002e-04 eta: 0:50:14 time: 0.8745 data_time: 0.2184 memory: 14901 loss: 0.8723 loss_prob: 0.4485 loss_thr: 0.3456 loss_db: 0.0782 2022/11/03 02:05:04 - mmengine - INFO - Epoch(train) [1129][10/63] lr: 1.7002e-04 eta: 0:50:06 time: 0.9493 data_time: 0.2204 memory: 14901 loss: 0.8694 loss_prob: 0.4450 loss_thr: 0.3461 loss_db: 0.0783 2022/11/03 02:05:06 - mmengine - INFO - Epoch(train) [1129][15/63] lr: 1.7002e-04 eta: 0:50:06 time: 0.6512 data_time: 0.0101 memory: 14901 loss: 0.8710 loss_prob: 0.4467 loss_thr: 0.3456 loss_db: 0.0787 2022/11/03 02:05:09 - mmengine - INFO - Epoch(train) [1129][20/63] lr: 1.7002e-04 eta: 0:49:59 time: 0.5791 data_time: 0.0077 memory: 14901 loss: 0.8148 loss_prob: 0.4127 loss_thr: 0.3294 loss_db: 0.0727 2022/11/03 02:05:12 - mmengine - INFO - Epoch(train) [1129][25/63] lr: 1.7002e-04 eta: 0:49:59 time: 0.5568 data_time: 0.0259 memory: 14901 loss: 0.7516 loss_prob: 0.3746 loss_thr: 0.3105 loss_db: 0.0665 2022/11/03 02:05:16 - mmengine - INFO - Epoch(train) [1129][30/63] lr: 1.7002e-04 eta: 0:49:52 time: 0.6942 data_time: 0.0342 memory: 14901 loss: 0.7717 loss_prob: 0.3888 loss_thr: 0.3143 loss_db: 0.0686 2022/11/03 02:05:20 - mmengine - INFO - Epoch(train) [1129][35/63] lr: 1.7002e-04 eta: 0:49:52 time: 0.7714 data_time: 0.0170 memory: 14901 loss: 0.8103 loss_prob: 0.4060 loss_thr: 0.3325 loss_db: 0.0717 2022/11/03 02:05:23 - mmengine - INFO - Epoch(train) [1129][40/63] lr: 1.7002e-04 eta: 0:49:46 time: 0.6799 data_time: 0.0092 memory: 14901 loss: 0.9260 loss_prob: 0.4754 loss_thr: 0.3674 loss_db: 0.0832 2022/11/03 02:05:26 - mmengine - INFO - Epoch(train) [1129][45/63] lr: 1.7002e-04 eta: 0:49:46 time: 0.6001 data_time: 0.0054 memory: 14901 loss: 0.9658 loss_prob: 0.5065 loss_thr: 0.3712 loss_db: 0.0880 2022/11/03 02:05:28 - mmengine - INFO - Epoch(train) [1129][50/63] lr: 1.7002e-04 eta: 0:49:39 time: 0.4996 data_time: 0.0153 memory: 14901 loss: 0.8894 loss_prob: 0.4672 loss_thr: 0.3405 loss_db: 0.0817 2022/11/03 02:05:31 - mmengine - INFO - Epoch(train) [1129][55/63] lr: 1.7002e-04 eta: 0:49:39 time: 0.5210 data_time: 0.0229 memory: 14901 loss: 0.8783 loss_prob: 0.4573 loss_thr: 0.3407 loss_db: 0.0802 2022/11/03 02:05:33 - mmengine - INFO - Epoch(train) [1129][60/63] lr: 1.7002e-04 eta: 0:49:32 time: 0.5427 data_time: 0.0164 memory: 14901 loss: 0.8766 loss_prob: 0.4460 loss_thr: 0.3514 loss_db: 0.0791 2022/11/03 02:05:35 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:05:41 - mmengine - INFO - Epoch(train) [1130][5/63] lr: 1.6786e-04 eta: 0:49:32 time: 0.8470 data_time: 0.2197 memory: 14901 loss: 0.7761 loss_prob: 0.3993 loss_thr: 0.3064 loss_db: 0.0705 2022/11/03 02:05:44 - mmengine - INFO - Epoch(train) [1130][10/63] lr: 1.6786e-04 eta: 0:49:24 time: 0.9483 data_time: 0.2200 memory: 14901 loss: 0.8903 loss_prob: 0.4652 loss_thr: 0.3437 loss_db: 0.0814 2022/11/03 02:05:47 - mmengine - INFO - Epoch(train) [1130][15/63] lr: 1.6786e-04 eta: 0:49:24 time: 0.6009 data_time: 0.0113 memory: 14901 loss: 1.0062 loss_prob: 0.5301 loss_thr: 0.3838 loss_db: 0.0923 2022/11/03 02:05:50 - mmengine - INFO - Epoch(train) [1130][20/63] lr: 1.6786e-04 eta: 0:49:17 time: 0.5721 data_time: 0.0098 memory: 14901 loss: 0.9153 loss_prob: 0.4764 loss_thr: 0.3551 loss_db: 0.0837 2022/11/03 02:05:53 - mmengine - INFO - Epoch(train) [1130][25/63] lr: 1.6786e-04 eta: 0:49:17 time: 0.5916 data_time: 0.0117 memory: 14901 loss: 0.8720 loss_prob: 0.4474 loss_thr: 0.3453 loss_db: 0.0793 2022/11/03 02:05:56 - mmengine - INFO - Epoch(train) [1130][30/63] lr: 1.6786e-04 eta: 0:49:10 time: 0.6059 data_time: 0.0347 memory: 14901 loss: 0.8937 loss_prob: 0.4595 loss_thr: 0.3542 loss_db: 0.0800 2022/11/03 02:06:00 - mmengine - INFO - Epoch(train) [1130][35/63] lr: 1.6786e-04 eta: 0:49:10 time: 0.6706 data_time: 0.0311 memory: 14901 loss: 0.8459 loss_prob: 0.4353 loss_thr: 0.3352 loss_db: 0.0754 2022/11/03 02:06:03 - mmengine - INFO - Epoch(train) [1130][40/63] lr: 1.6786e-04 eta: 0:49:04 time: 0.7029 data_time: 0.0126 memory: 14901 loss: 0.7981 loss_prob: 0.3998 loss_thr: 0.3282 loss_db: 0.0701 2022/11/03 02:06:06 - mmengine - INFO - Epoch(train) [1130][45/63] lr: 1.6786e-04 eta: 0:49:04 time: 0.6184 data_time: 0.0110 memory: 14901 loss: 0.8647 loss_prob: 0.4388 loss_thr: 0.3515 loss_db: 0.0745 2022/11/03 02:06:08 - mmengine - INFO - Epoch(train) [1130][50/63] lr: 1.6786e-04 eta: 0:48:57 time: 0.5191 data_time: 0.0167 memory: 14901 loss: 0.9426 loss_prob: 0.4945 loss_thr: 0.3634 loss_db: 0.0846 2022/11/03 02:06:12 - mmengine - INFO - Epoch(train) [1130][55/63] lr: 1.6786e-04 eta: 0:48:57 time: 0.5876 data_time: 0.0250 memory: 14901 loss: 0.9034 loss_prob: 0.4682 loss_thr: 0.3523 loss_db: 0.0829 2022/11/03 02:06:15 - mmengine - INFO - Epoch(train) [1130][60/63] lr: 1.6786e-04 eta: 0:48:50 time: 0.6883 data_time: 0.0180 memory: 14901 loss: 0.8471 loss_prob: 0.4290 loss_thr: 0.3430 loss_db: 0.0751 2022/11/03 02:06:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:06:24 - mmengine - INFO - Epoch(train) [1131][5/63] lr: 1.6571e-04 eta: 0:48:50 time: 1.0037 data_time: 0.2802 memory: 14901 loss: 0.8127 loss_prob: 0.4068 loss_thr: 0.3344 loss_db: 0.0715 2022/11/03 02:06:27 - mmengine - INFO - Epoch(train) [1131][10/63] lr: 1.6571e-04 eta: 0:48:42 time: 1.0560 data_time: 0.2798 memory: 14901 loss: 0.8256 loss_prob: 0.4202 loss_thr: 0.3306 loss_db: 0.0748 2022/11/03 02:06:30 - mmengine - INFO - Epoch(train) [1131][15/63] lr: 1.6571e-04 eta: 0:48:42 time: 0.6471 data_time: 0.0074 memory: 14901 loss: 0.8361 loss_prob: 0.4340 loss_thr: 0.3258 loss_db: 0.0763 2022/11/03 02:06:33 - mmengine - INFO - Epoch(train) [1131][20/63] lr: 1.6571e-04 eta: 0:48:35 time: 0.5934 data_time: 0.0061 memory: 14901 loss: 0.8555 loss_prob: 0.4425 loss_thr: 0.3356 loss_db: 0.0775 2022/11/03 02:06:36 - mmengine - INFO - Epoch(train) [1131][25/63] lr: 1.6571e-04 eta: 0:48:35 time: 0.6332 data_time: 0.0282 memory: 14901 loss: 0.8068 loss_prob: 0.4072 loss_thr: 0.3292 loss_db: 0.0705 2022/11/03 02:06:39 - mmengine - INFO - Epoch(train) [1131][30/63] lr: 1.6571e-04 eta: 0:48:28 time: 0.6066 data_time: 0.0410 memory: 14901 loss: 0.7977 loss_prob: 0.4050 loss_thr: 0.3225 loss_db: 0.0701 2022/11/03 02:06:43 - mmengine - INFO - Epoch(train) [1131][35/63] lr: 1.6571e-04 eta: 0:48:28 time: 0.6140 data_time: 0.0183 memory: 14901 loss: 0.8834 loss_prob: 0.4637 loss_thr: 0.3391 loss_db: 0.0805 2022/11/03 02:06:46 - mmengine - INFO - Epoch(train) [1131][40/63] lr: 1.6571e-04 eta: 0:48:22 time: 0.6504 data_time: 0.0059 memory: 14901 loss: 0.8999 loss_prob: 0.4720 loss_thr: 0.3461 loss_db: 0.0818 2022/11/03 02:06:48 - mmengine - INFO - Epoch(train) [1131][45/63] lr: 1.6571e-04 eta: 0:48:22 time: 0.5842 data_time: 0.0060 memory: 14901 loss: 0.8632 loss_prob: 0.4392 loss_thr: 0.3459 loss_db: 0.0781 2022/11/03 02:06:52 - mmengine - INFO - Epoch(train) [1131][50/63] lr: 1.6571e-04 eta: 0:48:15 time: 0.6480 data_time: 0.0244 memory: 14901 loss: 0.8119 loss_prob: 0.4064 loss_thr: 0.3318 loss_db: 0.0737 2022/11/03 02:06:55 - mmengine - INFO - Epoch(train) [1131][55/63] lr: 1.6571e-04 eta: 0:48:15 time: 0.6836 data_time: 0.0278 memory: 14901 loss: 0.8279 loss_prob: 0.4221 loss_thr: 0.3297 loss_db: 0.0761 2022/11/03 02:06:58 - mmengine - INFO - Epoch(train) [1131][60/63] lr: 1.6571e-04 eta: 0:48:08 time: 0.5960 data_time: 0.0086 memory: 14901 loss: 0.8398 loss_prob: 0.4307 loss_thr: 0.3329 loss_db: 0.0763 2022/11/03 02:06:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:07:05 - mmengine - INFO - Epoch(train) [1132][5/63] lr: 1.6354e-04 eta: 0:48:08 time: 0.7642 data_time: 0.1741 memory: 14901 loss: 0.8258 loss_prob: 0.4191 loss_thr: 0.3339 loss_db: 0.0728 2022/11/03 02:07:09 - mmengine - INFO - Epoch(train) [1132][10/63] lr: 1.6354e-04 eta: 0:48:00 time: 0.9432 data_time: 0.1920 memory: 14901 loss: 0.7149 loss_prob: 0.3563 loss_thr: 0.2960 loss_db: 0.0626 2022/11/03 02:07:12 - mmengine - INFO - Epoch(train) [1132][15/63] lr: 1.6354e-04 eta: 0:48:00 time: 0.7323 data_time: 0.0295 memory: 14901 loss: 0.7748 loss_prob: 0.3961 loss_thr: 0.3085 loss_db: 0.0702 2022/11/03 02:07:15 - mmengine - INFO - Epoch(train) [1132][20/63] lr: 1.6354e-04 eta: 0:47:53 time: 0.5834 data_time: 0.0131 memory: 14901 loss: 0.8686 loss_prob: 0.4514 loss_thr: 0.3379 loss_db: 0.0792 2022/11/03 02:07:17 - mmengine - INFO - Epoch(train) [1132][25/63] lr: 1.6354e-04 eta: 0:47:53 time: 0.5095 data_time: 0.0168 memory: 14901 loss: 0.8771 loss_prob: 0.4597 loss_thr: 0.3369 loss_db: 0.0805 2022/11/03 02:07:20 - mmengine - INFO - Epoch(train) [1132][30/63] lr: 1.6354e-04 eta: 0:47:46 time: 0.5472 data_time: 0.0165 memory: 14901 loss: 0.8916 loss_prob: 0.4737 loss_thr: 0.3365 loss_db: 0.0814 2022/11/03 02:07:23 - mmengine - INFO - Epoch(train) [1132][35/63] lr: 1.6354e-04 eta: 0:47:46 time: 0.5559 data_time: 0.0284 memory: 14901 loss: 0.8247 loss_prob: 0.4317 loss_thr: 0.3182 loss_db: 0.0748 2022/11/03 02:07:26 - mmengine - INFO - Epoch(train) [1132][40/63] lr: 1.6354e-04 eta: 0:47:40 time: 0.5794 data_time: 0.0270 memory: 14901 loss: 0.8694 loss_prob: 0.4483 loss_thr: 0.3425 loss_db: 0.0786 2022/11/03 02:07:31 - mmengine - INFO - Epoch(train) [1132][45/63] lr: 1.6354e-04 eta: 0:47:40 time: 0.8110 data_time: 0.0106 memory: 14901 loss: 0.8901 loss_prob: 0.4586 loss_thr: 0.3512 loss_db: 0.0804 2022/11/03 02:07:34 - mmengine - INFO - Epoch(train) [1132][50/63] lr: 1.6354e-04 eta: 0:47:33 time: 0.7858 data_time: 0.0197 memory: 14901 loss: 0.8251 loss_prob: 0.4195 loss_thr: 0.3299 loss_db: 0.0757 2022/11/03 02:07:37 - mmengine - INFO - Epoch(train) [1132][55/63] lr: 1.6354e-04 eta: 0:47:33 time: 0.5985 data_time: 0.0205 memory: 14901 loss: 0.8771 loss_prob: 0.4457 loss_thr: 0.3519 loss_db: 0.0796 2022/11/03 02:07:40 - mmengine - INFO - Epoch(train) [1132][60/63] lr: 1.6354e-04 eta: 0:47:26 time: 0.6124 data_time: 0.0195 memory: 14901 loss: 0.8740 loss_prob: 0.4485 loss_thr: 0.3466 loss_db: 0.0789 2022/11/03 02:07:41 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:07:46 - mmengine - INFO - Epoch(train) [1133][5/63] lr: 1.6138e-04 eta: 0:47:26 time: 0.7624 data_time: 0.1723 memory: 14901 loss: 0.8313 loss_prob: 0.4209 loss_thr: 0.3363 loss_db: 0.0741 2022/11/03 02:07:50 - mmengine - INFO - Epoch(train) [1133][10/63] lr: 1.6138e-04 eta: 0:47:18 time: 0.8434 data_time: 0.1833 memory: 14901 loss: 0.8706 loss_prob: 0.4452 loss_thr: 0.3471 loss_db: 0.0784 2022/11/03 02:07:53 - mmengine - INFO - Epoch(train) [1133][15/63] lr: 1.6138e-04 eta: 0:47:18 time: 0.6374 data_time: 0.0219 memory: 14901 loss: 0.8064 loss_prob: 0.4071 loss_thr: 0.3279 loss_db: 0.0714 2022/11/03 02:07:55 - mmengine - INFO - Epoch(train) [1133][20/63] lr: 1.6138e-04 eta: 0:47:11 time: 0.5321 data_time: 0.0121 memory: 14901 loss: 0.8643 loss_prob: 0.4427 loss_thr: 0.3457 loss_db: 0.0759 2022/11/03 02:07:58 - mmengine - INFO - Epoch(train) [1133][25/63] lr: 1.6138e-04 eta: 0:47:11 time: 0.5069 data_time: 0.0167 memory: 14901 loss: 0.8626 loss_prob: 0.4436 loss_thr: 0.3420 loss_db: 0.0770 2022/11/03 02:08:01 - mmengine - INFO - Epoch(train) [1133][30/63] lr: 1.6138e-04 eta: 0:47:04 time: 0.5847 data_time: 0.0436 memory: 14901 loss: 0.7982 loss_prob: 0.4067 loss_thr: 0.3200 loss_db: 0.0715 2022/11/03 02:08:04 - mmengine - INFO - Epoch(train) [1133][35/63] lr: 1.6138e-04 eta: 0:47:04 time: 0.5939 data_time: 0.0400 memory: 14901 loss: 0.7922 loss_prob: 0.4022 loss_thr: 0.3200 loss_db: 0.0700 2022/11/03 02:08:06 - mmengine - INFO - Epoch(train) [1133][40/63] lr: 1.6138e-04 eta: 0:46:58 time: 0.5414 data_time: 0.0106 memory: 14901 loss: 0.8644 loss_prob: 0.4464 loss_thr: 0.3406 loss_db: 0.0775 2022/11/03 02:08:09 - mmengine - INFO - Epoch(train) [1133][45/63] lr: 1.6138e-04 eta: 0:46:58 time: 0.5648 data_time: 0.0081 memory: 14901 loss: 0.9149 loss_prob: 0.5000 loss_thr: 0.3324 loss_db: 0.0825 2022/11/03 02:08:13 - mmengine - INFO - Epoch(train) [1133][50/63] lr: 1.6138e-04 eta: 0:46:51 time: 0.6521 data_time: 0.0131 memory: 14901 loss: 0.8978 loss_prob: 0.4842 loss_thr: 0.3341 loss_db: 0.0796 2022/11/03 02:08:16 - mmengine - INFO - Epoch(train) [1133][55/63] lr: 1.6138e-04 eta: 0:46:51 time: 0.7116 data_time: 0.0234 memory: 14901 loss: 0.8837 loss_prob: 0.4585 loss_thr: 0.3450 loss_db: 0.0803 2022/11/03 02:08:20 - mmengine - INFO - Epoch(train) [1133][60/63] lr: 1.6138e-04 eta: 0:46:44 time: 0.7482 data_time: 0.0206 memory: 14901 loss: 0.7972 loss_prob: 0.4082 loss_thr: 0.3161 loss_db: 0.0728 2022/11/03 02:08:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:08:29 - mmengine - INFO - Epoch(train) [1134][5/63] lr: 1.5921e-04 eta: 0:46:44 time: 1.0313 data_time: 0.2493 memory: 14901 loss: 0.8579 loss_prob: 0.4444 loss_thr: 0.3345 loss_db: 0.0790 2022/11/03 02:08:32 - mmengine - INFO - Epoch(train) [1134][10/63] lr: 1.5921e-04 eta: 0:46:36 time: 0.9939 data_time: 0.2595 memory: 14901 loss: 0.8647 loss_prob: 0.4459 loss_thr: 0.3407 loss_db: 0.0781 2022/11/03 02:08:35 - mmengine - INFO - Epoch(train) [1134][15/63] lr: 1.5921e-04 eta: 0:46:36 time: 0.5864 data_time: 0.0170 memory: 14901 loss: 0.8301 loss_prob: 0.4207 loss_thr: 0.3350 loss_db: 0.0745 2022/11/03 02:08:38 - mmengine - INFO - Epoch(train) [1134][20/63] lr: 1.5921e-04 eta: 0:46:29 time: 0.5864 data_time: 0.0057 memory: 14901 loss: 0.8814 loss_prob: 0.4520 loss_thr: 0.3489 loss_db: 0.0806 2022/11/03 02:08:41 - mmengine - INFO - Epoch(train) [1134][25/63] lr: 1.5921e-04 eta: 0:46:29 time: 0.6168 data_time: 0.0295 memory: 14901 loss: 0.8591 loss_prob: 0.4397 loss_thr: 0.3410 loss_db: 0.0784 2022/11/03 02:08:44 - mmengine - INFO - Epoch(train) [1134][30/63] lr: 1.5921e-04 eta: 0:46:23 time: 0.6169 data_time: 0.0295 memory: 14901 loss: 0.8246 loss_prob: 0.4171 loss_thr: 0.3350 loss_db: 0.0724 2022/11/03 02:08:47 - mmengine - INFO - Epoch(train) [1134][35/63] lr: 1.5921e-04 eta: 0:46:23 time: 0.5759 data_time: 0.0138 memory: 14901 loss: 0.8032 loss_prob: 0.4081 loss_thr: 0.3247 loss_db: 0.0704 2022/11/03 02:08:49 - mmengine - INFO - Epoch(train) [1134][40/63] lr: 1.5921e-04 eta: 0:46:16 time: 0.5247 data_time: 0.0142 memory: 14901 loss: 0.8021 loss_prob: 0.4134 loss_thr: 0.3173 loss_db: 0.0715 2022/11/03 02:08:53 - mmengine - INFO - Epoch(train) [1134][45/63] lr: 1.5921e-04 eta: 0:46:16 time: 0.5837 data_time: 0.0058 memory: 14901 loss: 0.8436 loss_prob: 0.4335 loss_thr: 0.3350 loss_db: 0.0751 2022/11/03 02:08:57 - mmengine - INFO - Epoch(train) [1134][50/63] lr: 1.5921e-04 eta: 0:46:09 time: 0.7520 data_time: 0.0261 memory: 14901 loss: 0.8432 loss_prob: 0.4286 loss_thr: 0.3377 loss_db: 0.0770 2022/11/03 02:09:01 - mmengine - INFO - Epoch(train) [1134][55/63] lr: 1.5921e-04 eta: 0:46:09 time: 0.7744 data_time: 0.0265 memory: 14901 loss: 0.7652 loss_prob: 0.3878 loss_thr: 0.3077 loss_db: 0.0697 2022/11/03 02:09:03 - mmengine - INFO - Epoch(train) [1134][60/63] lr: 1.5921e-04 eta: 0:46:03 time: 0.6419 data_time: 0.0153 memory: 14901 loss: 0.8145 loss_prob: 0.4185 loss_thr: 0.3236 loss_db: 0.0724 2022/11/03 02:09:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:09:10 - mmengine - INFO - Epoch(train) [1135][5/63] lr: 1.5704e-04 eta: 0:46:03 time: 0.7862 data_time: 0.2579 memory: 14901 loss: 0.8646 loss_prob: 0.4400 loss_thr: 0.3500 loss_db: 0.0746 2022/11/03 02:09:13 - mmengine - INFO - Epoch(train) [1135][10/63] lr: 1.5704e-04 eta: 0:45:54 time: 0.8702 data_time: 0.2602 memory: 14901 loss: 0.7958 loss_prob: 0.4046 loss_thr: 0.3189 loss_db: 0.0723 2022/11/03 02:09:17 - mmengine - INFO - Epoch(train) [1135][15/63] lr: 1.5704e-04 eta: 0:45:54 time: 0.7174 data_time: 0.0087 memory: 14901 loss: 0.7814 loss_prob: 0.3981 loss_thr: 0.3111 loss_db: 0.0721 2022/11/03 02:09:20 - mmengine - INFO - Epoch(train) [1135][20/63] lr: 1.5704e-04 eta: 0:45:47 time: 0.6665 data_time: 0.0073 memory: 14901 loss: 0.7885 loss_prob: 0.4033 loss_thr: 0.3122 loss_db: 0.0730 2022/11/03 02:09:23 - mmengine - INFO - Epoch(train) [1135][25/63] lr: 1.5704e-04 eta: 0:45:47 time: 0.5426 data_time: 0.0300 memory: 14901 loss: 0.8142 loss_prob: 0.4167 loss_thr: 0.3242 loss_db: 0.0733 2022/11/03 02:09:26 - mmengine - INFO - Epoch(train) [1135][30/63] lr: 1.5704e-04 eta: 0:45:41 time: 0.5655 data_time: 0.0356 memory: 14901 loss: 0.8823 loss_prob: 0.4581 loss_thr: 0.3452 loss_db: 0.0790 2022/11/03 02:09:28 - mmengine - INFO - Epoch(train) [1135][35/63] lr: 1.5704e-04 eta: 0:45:41 time: 0.5483 data_time: 0.0136 memory: 14901 loss: 0.9508 loss_prob: 0.5026 loss_thr: 0.3606 loss_db: 0.0876 2022/11/03 02:09:31 - mmengine - INFO - Epoch(train) [1135][40/63] lr: 1.5704e-04 eta: 0:45:34 time: 0.5235 data_time: 0.0073 memory: 14901 loss: 0.9098 loss_prob: 0.4736 loss_thr: 0.3539 loss_db: 0.0823 2022/11/03 02:09:34 - mmengine - INFO - Epoch(train) [1135][45/63] lr: 1.5704e-04 eta: 0:45:34 time: 0.5634 data_time: 0.0088 memory: 14901 loss: 0.8561 loss_prob: 0.4282 loss_thr: 0.3519 loss_db: 0.0761 2022/11/03 02:09:37 - mmengine - INFO - Epoch(train) [1135][50/63] lr: 1.5704e-04 eta: 0:45:27 time: 0.5985 data_time: 0.0289 memory: 14901 loss: 0.9075 loss_prob: 0.4590 loss_thr: 0.3659 loss_db: 0.0826 2022/11/03 02:09:41 - mmengine - INFO - Epoch(train) [1135][55/63] lr: 1.5704e-04 eta: 0:45:27 time: 0.6816 data_time: 0.0265 memory: 14901 loss: 0.8651 loss_prob: 0.4401 loss_thr: 0.3467 loss_db: 0.0783 2022/11/03 02:09:44 - mmengine - INFO - Epoch(train) [1135][60/63] lr: 1.5704e-04 eta: 0:45:21 time: 0.6909 data_time: 0.0074 memory: 14901 loss: 0.8495 loss_prob: 0.4331 loss_thr: 0.3420 loss_db: 0.0744 2022/11/03 02:09:46 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:09:52 - mmengine - INFO - Epoch(train) [1136][5/63] lr: 1.5486e-04 eta: 0:45:21 time: 0.9822 data_time: 0.2264 memory: 14901 loss: 0.8681 loss_prob: 0.4520 loss_thr: 0.3372 loss_db: 0.0789 2022/11/03 02:09:56 - mmengine - INFO - Epoch(train) [1136][10/63] lr: 1.5486e-04 eta: 0:45:12 time: 1.0079 data_time: 0.2385 memory: 14901 loss: 0.8559 loss_prob: 0.4470 loss_thr: 0.3303 loss_db: 0.0786 2022/11/03 02:09:59 - mmengine - INFO - Epoch(train) [1136][15/63] lr: 1.5486e-04 eta: 0:45:12 time: 0.6333 data_time: 0.0190 memory: 14901 loss: 0.8890 loss_prob: 0.4652 loss_thr: 0.3435 loss_db: 0.0803 2022/11/03 02:10:01 - mmengine - INFO - Epoch(train) [1136][20/63] lr: 1.5486e-04 eta: 0:45:05 time: 0.5447 data_time: 0.0056 memory: 14901 loss: 0.8428 loss_prob: 0.4368 loss_thr: 0.3325 loss_db: 0.0735 2022/11/03 02:10:04 - mmengine - INFO - Epoch(train) [1136][25/63] lr: 1.5486e-04 eta: 0:45:05 time: 0.5073 data_time: 0.0115 memory: 14901 loss: 0.8470 loss_prob: 0.4236 loss_thr: 0.3499 loss_db: 0.0735 2022/11/03 02:10:07 - mmengine - INFO - Epoch(train) [1136][30/63] lr: 1.5486e-04 eta: 0:44:59 time: 0.5673 data_time: 0.0253 memory: 14901 loss: 0.8772 loss_prob: 0.4363 loss_thr: 0.3635 loss_db: 0.0774 2022/11/03 02:10:10 - mmengine - INFO - Epoch(train) [1136][35/63] lr: 1.5486e-04 eta: 0:44:59 time: 0.6106 data_time: 0.0465 memory: 14901 loss: 0.8831 loss_prob: 0.4604 loss_thr: 0.3418 loss_db: 0.0809 2022/11/03 02:10:13 - mmengine - INFO - Epoch(train) [1136][40/63] lr: 1.5486e-04 eta: 0:44:52 time: 0.6552 data_time: 0.0340 memory: 14901 loss: 0.9328 loss_prob: 0.4947 loss_thr: 0.3519 loss_db: 0.0862 2022/11/03 02:10:17 - mmengine - INFO - Epoch(train) [1136][45/63] lr: 1.5486e-04 eta: 0:44:52 time: 0.6610 data_time: 0.0099 memory: 14901 loss: 0.8577 loss_prob: 0.4440 loss_thr: 0.3368 loss_db: 0.0769 2022/11/03 02:10:20 - mmengine - INFO - Epoch(train) [1136][50/63] lr: 1.5486e-04 eta: 0:44:45 time: 0.6819 data_time: 0.0198 memory: 14901 loss: 0.7889 loss_prob: 0.4002 loss_thr: 0.3207 loss_db: 0.0680 2022/11/03 02:10:23 - mmengine - INFO - Epoch(train) [1136][55/63] lr: 1.5486e-04 eta: 0:44:45 time: 0.6509 data_time: 0.0241 memory: 14901 loss: 0.8582 loss_prob: 0.4422 loss_thr: 0.3402 loss_db: 0.0758 2022/11/03 02:10:27 - mmengine - INFO - Epoch(train) [1136][60/63] lr: 1.5486e-04 eta: 0:44:39 time: 0.7016 data_time: 0.0161 memory: 14901 loss: 0.8597 loss_prob: 0.4414 loss_thr: 0.3406 loss_db: 0.0777 2022/11/03 02:10:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:10:36 - mmengine - INFO - Epoch(train) [1137][5/63] lr: 1.5269e-04 eta: 0:44:39 time: 0.9850 data_time: 0.1969 memory: 14901 loss: 0.8576 loss_prob: 0.4408 loss_thr: 0.3391 loss_db: 0.0777 2022/11/03 02:10:39 - mmengine - INFO - Epoch(train) [1137][10/63] lr: 1.5269e-04 eta: 0:44:30 time: 0.9979 data_time: 0.2000 memory: 14901 loss: 0.8081 loss_prob: 0.4115 loss_thr: 0.3240 loss_db: 0.0727 2022/11/03 02:10:42 - mmengine - INFO - Epoch(train) [1137][15/63] lr: 1.5269e-04 eta: 0:44:30 time: 0.5725 data_time: 0.0164 memory: 14901 loss: 0.8405 loss_prob: 0.4372 loss_thr: 0.3259 loss_db: 0.0774 2022/11/03 02:10:45 - mmengine - INFO - Epoch(train) [1137][20/63] lr: 1.5269e-04 eta: 0:44:24 time: 0.5668 data_time: 0.0101 memory: 14901 loss: 0.8561 loss_prob: 0.4471 loss_thr: 0.3301 loss_db: 0.0788 2022/11/03 02:10:48 - mmengine - INFO - Epoch(train) [1137][25/63] lr: 1.5269e-04 eta: 0:44:24 time: 0.5969 data_time: 0.0074 memory: 14901 loss: 0.8291 loss_prob: 0.4251 loss_thr: 0.3294 loss_db: 0.0746 2022/11/03 02:10:51 - mmengine - INFO - Epoch(train) [1137][30/63] lr: 1.5269e-04 eta: 0:44:17 time: 0.5877 data_time: 0.0287 memory: 14901 loss: 0.8285 loss_prob: 0.4164 loss_thr: 0.3379 loss_db: 0.0742 2022/11/03 02:10:53 - mmengine - INFO - Epoch(train) [1137][35/63] lr: 1.5269e-04 eta: 0:44:17 time: 0.5674 data_time: 0.0320 memory: 14901 loss: 0.8385 loss_prob: 0.4255 loss_thr: 0.3365 loss_db: 0.0764 2022/11/03 02:10:56 - mmengine - INFO - Epoch(train) [1137][40/63] lr: 1.5269e-04 eta: 0:44:10 time: 0.5458 data_time: 0.0153 memory: 14901 loss: 0.8874 loss_prob: 0.4650 loss_thr: 0.3408 loss_db: 0.0816 2022/11/03 02:10:59 - mmengine - INFO - Epoch(train) [1137][45/63] lr: 1.5269e-04 eta: 0:44:10 time: 0.5903 data_time: 0.0095 memory: 14901 loss: 0.8402 loss_prob: 0.4342 loss_thr: 0.3312 loss_db: 0.0748 2022/11/03 02:11:02 - mmengine - INFO - Epoch(train) [1137][50/63] lr: 1.5269e-04 eta: 0:44:03 time: 0.6093 data_time: 0.0150 memory: 14901 loss: 0.7942 loss_prob: 0.4010 loss_thr: 0.3238 loss_db: 0.0695 2022/11/03 02:11:05 - mmengine - INFO - Epoch(train) [1137][55/63] lr: 1.5269e-04 eta: 0:44:03 time: 0.5545 data_time: 0.0221 memory: 14901 loss: 0.8563 loss_prob: 0.4466 loss_thr: 0.3330 loss_db: 0.0768 2022/11/03 02:11:08 - mmengine - INFO - Epoch(train) [1137][60/63] lr: 1.5269e-04 eta: 0:43:57 time: 0.6198 data_time: 0.0171 memory: 14901 loss: 0.8388 loss_prob: 0.4368 loss_thr: 0.3263 loss_db: 0.0758 2022/11/03 02:11:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:11:16 - mmengine - INFO - Epoch(train) [1138][5/63] lr: 1.5051e-04 eta: 0:43:57 time: 0.8718 data_time: 0.3251 memory: 14901 loss: 0.8867 loss_prob: 0.4607 loss_thr: 0.3444 loss_db: 0.0817 2022/11/03 02:11:19 - mmengine - INFO - Epoch(train) [1138][10/63] lr: 1.5051e-04 eta: 0:43:48 time: 0.8819 data_time: 0.3217 memory: 14901 loss: 0.9599 loss_prob: 0.5064 loss_thr: 0.3632 loss_db: 0.0902 2022/11/03 02:11:22 - mmengine - INFO - Epoch(train) [1138][15/63] lr: 1.5051e-04 eta: 0:43:48 time: 0.6140 data_time: 0.0057 memory: 14901 loss: 0.9428 loss_prob: 0.4959 loss_thr: 0.3589 loss_db: 0.0880 2022/11/03 02:11:25 - mmengine - INFO - Epoch(train) [1138][20/63] lr: 1.5051e-04 eta: 0:43:42 time: 0.6452 data_time: 0.0109 memory: 14901 loss: 0.9183 loss_prob: 0.4799 loss_thr: 0.3555 loss_db: 0.0828 2022/11/03 02:11:28 - mmengine - INFO - Epoch(train) [1138][25/63] lr: 1.5051e-04 eta: 0:43:42 time: 0.6166 data_time: 0.0246 memory: 14901 loss: 0.9320 loss_prob: 0.4899 loss_thr: 0.3582 loss_db: 0.0839 2022/11/03 02:11:31 - mmengine - INFO - Epoch(train) [1138][30/63] lr: 1.5051e-04 eta: 0:43:35 time: 0.6075 data_time: 0.0351 memory: 14901 loss: 0.8659 loss_prob: 0.4509 loss_thr: 0.3378 loss_db: 0.0772 2022/11/03 02:11:34 - mmengine - INFO - Epoch(train) [1138][35/63] lr: 1.5051e-04 eta: 0:43:35 time: 0.5665 data_time: 0.0212 memory: 14901 loss: 0.8526 loss_prob: 0.4398 loss_thr: 0.3361 loss_db: 0.0767 2022/11/03 02:11:36 - mmengine - INFO - Epoch(train) [1138][40/63] lr: 1.5051e-04 eta: 0:43:28 time: 0.5202 data_time: 0.0051 memory: 14901 loss: 0.8634 loss_prob: 0.4476 loss_thr: 0.3373 loss_db: 0.0786 2022/11/03 02:11:40 - mmengine - INFO - Epoch(train) [1138][45/63] lr: 1.5051e-04 eta: 0:43:28 time: 0.6121 data_time: 0.0063 memory: 14901 loss: 0.8553 loss_prob: 0.4485 loss_thr: 0.3286 loss_db: 0.0782 2022/11/03 02:11:43 - mmengine - INFO - Epoch(train) [1138][50/63] lr: 1.5051e-04 eta: 0:43:21 time: 0.6613 data_time: 0.0131 memory: 14901 loss: 0.8835 loss_prob: 0.4579 loss_thr: 0.3441 loss_db: 0.0815 2022/11/03 02:11:45 - mmengine - INFO - Epoch(train) [1138][55/63] lr: 1.5051e-04 eta: 0:43:21 time: 0.5624 data_time: 0.0191 memory: 14901 loss: 0.8092 loss_prob: 0.4108 loss_thr: 0.3241 loss_db: 0.0743 2022/11/03 02:11:48 - mmengine - INFO - Epoch(train) [1138][60/63] lr: 1.5051e-04 eta: 0:43:15 time: 0.4765 data_time: 0.0121 memory: 14901 loss: 0.7629 loss_prob: 0.3900 loss_thr: 0.3023 loss_db: 0.0706 2022/11/03 02:11:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:11:54 - mmengine - INFO - Epoch(train) [1139][5/63] lr: 1.4832e-04 eta: 0:43:15 time: 0.7477 data_time: 0.2124 memory: 14901 loss: 0.8530 loss_prob: 0.4433 loss_thr: 0.3331 loss_db: 0.0767 2022/11/03 02:11:57 - mmengine - INFO - Epoch(train) [1139][10/63] lr: 1.4832e-04 eta: 0:43:06 time: 0.7816 data_time: 0.2121 memory: 14901 loss: 0.8966 loss_prob: 0.4693 loss_thr: 0.3473 loss_db: 0.0801 2022/11/03 02:11:59 - mmengine - INFO - Epoch(train) [1139][15/63] lr: 1.4832e-04 eta: 0:43:06 time: 0.4750 data_time: 0.0091 memory: 14901 loss: 0.8836 loss_prob: 0.4607 loss_thr: 0.3424 loss_db: 0.0806 2022/11/03 02:12:02 - mmengine - INFO - Epoch(train) [1139][20/63] lr: 1.4832e-04 eta: 0:42:59 time: 0.4927 data_time: 0.0097 memory: 14901 loss: 0.8935 loss_prob: 0.4634 loss_thr: 0.3486 loss_db: 0.0814 2022/11/03 02:12:04 - mmengine - INFO - Epoch(train) [1139][25/63] lr: 1.4832e-04 eta: 0:42:59 time: 0.4789 data_time: 0.0078 memory: 14901 loss: 0.8270 loss_prob: 0.4263 loss_thr: 0.3254 loss_db: 0.0752 2022/11/03 02:12:06 - mmengine - INFO - Epoch(train) [1139][30/63] lr: 1.4832e-04 eta: 0:42:53 time: 0.4797 data_time: 0.0394 memory: 14901 loss: 0.8258 loss_prob: 0.4251 loss_thr: 0.3259 loss_db: 0.0748 2022/11/03 02:12:09 - mmengine - INFO - Epoch(train) [1139][35/63] lr: 1.4832e-04 eta: 0:42:53 time: 0.4871 data_time: 0.0385 memory: 14901 loss: 0.8794 loss_prob: 0.4523 loss_thr: 0.3482 loss_db: 0.0789 2022/11/03 02:12:11 - mmengine - INFO - Epoch(train) [1139][40/63] lr: 1.4832e-04 eta: 0:42:46 time: 0.4838 data_time: 0.0056 memory: 14901 loss: 0.8338 loss_prob: 0.4222 loss_thr: 0.3370 loss_db: 0.0745 2022/11/03 02:12:14 - mmengine - INFO - Epoch(train) [1139][45/63] lr: 1.4832e-04 eta: 0:42:46 time: 0.4904 data_time: 0.0062 memory: 14901 loss: 0.8087 loss_prob: 0.4034 loss_thr: 0.3334 loss_db: 0.0719 2022/11/03 02:12:16 - mmengine - INFO - Epoch(train) [1139][50/63] lr: 1.4832e-04 eta: 0:42:39 time: 0.4846 data_time: 0.0205 memory: 14901 loss: 0.8110 loss_prob: 0.4121 loss_thr: 0.3254 loss_db: 0.0736 2022/11/03 02:12:19 - mmengine - INFO - Epoch(train) [1139][55/63] lr: 1.4832e-04 eta: 0:42:39 time: 0.4863 data_time: 0.0213 memory: 14901 loss: 0.8620 loss_prob: 0.4442 loss_thr: 0.3389 loss_db: 0.0788 2022/11/03 02:12:21 - mmengine - INFO - Epoch(train) [1139][60/63] lr: 1.4832e-04 eta: 0:42:32 time: 0.4706 data_time: 0.0083 memory: 14901 loss: 0.8982 loss_prob: 0.4617 loss_thr: 0.3558 loss_db: 0.0807 2022/11/03 02:12:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:12:26 - mmengine - INFO - Epoch(train) [1140][5/63] lr: 1.4613e-04 eta: 0:42:32 time: 0.6504 data_time: 0.2121 memory: 14901 loss: 0.9139 loss_prob: 0.4714 loss_thr: 0.3607 loss_db: 0.0818 2022/11/03 02:12:29 - mmengine - INFO - Epoch(train) [1140][10/63] lr: 1.4613e-04 eta: 0:42:24 time: 0.7022 data_time: 0.2234 memory: 14901 loss: 0.9391 loss_prob: 0.4892 loss_thr: 0.3645 loss_db: 0.0855 2022/11/03 02:12:31 - mmengine - INFO - Epoch(train) [1140][15/63] lr: 1.4613e-04 eta: 0:42:24 time: 0.4915 data_time: 0.0213 memory: 14901 loss: 0.9037 loss_prob: 0.4658 loss_thr: 0.3559 loss_db: 0.0821 2022/11/03 02:12:34 - mmengine - INFO - Epoch(train) [1140][20/63] lr: 1.4613e-04 eta: 0:42:17 time: 0.4941 data_time: 0.0093 memory: 14901 loss: 0.8403 loss_prob: 0.4261 loss_thr: 0.3401 loss_db: 0.0741 2022/11/03 02:12:37 - mmengine - INFO - Epoch(train) [1140][25/63] lr: 1.4613e-04 eta: 0:42:17 time: 0.5226 data_time: 0.0225 memory: 14901 loss: 0.8271 loss_prob: 0.4186 loss_thr: 0.3346 loss_db: 0.0739 2022/11/03 02:12:39 - mmengine - INFO - Epoch(train) [1140][30/63] lr: 1.4613e-04 eta: 0:42:10 time: 0.5251 data_time: 0.0396 memory: 14901 loss: 0.8138 loss_prob: 0.4176 loss_thr: 0.3224 loss_db: 0.0738 2022/11/03 02:12:42 - mmengine - INFO - Epoch(train) [1140][35/63] lr: 1.4613e-04 eta: 0:42:10 time: 0.5111 data_time: 0.0226 memory: 14901 loss: 0.8162 loss_prob: 0.4198 loss_thr: 0.3220 loss_db: 0.0744 2022/11/03 02:12:44 - mmengine - INFO - Epoch(train) [1140][40/63] lr: 1.4613e-04 eta: 0:42:03 time: 0.4852 data_time: 0.0075 memory: 14901 loss: 0.8582 loss_prob: 0.4463 loss_thr: 0.3329 loss_db: 0.0790 2022/11/03 02:12:46 - mmengine - INFO - Epoch(train) [1140][45/63] lr: 1.4613e-04 eta: 0:42:03 time: 0.4756 data_time: 0.0070 memory: 14901 loss: 0.7868 loss_prob: 0.4066 loss_thr: 0.3089 loss_db: 0.0713 2022/11/03 02:12:49 - mmengine - INFO - Epoch(train) [1140][50/63] lr: 1.4613e-04 eta: 0:41:57 time: 0.4711 data_time: 0.0178 memory: 14901 loss: 0.8394 loss_prob: 0.4400 loss_thr: 0.3231 loss_db: 0.0763 2022/11/03 02:12:51 - mmengine - INFO - Epoch(train) [1140][55/63] lr: 1.4613e-04 eta: 0:41:57 time: 0.4482 data_time: 0.0206 memory: 14901 loss: 0.8590 loss_prob: 0.4529 loss_thr: 0.3277 loss_db: 0.0784 2022/11/03 02:12:54 - mmengine - INFO - Epoch(train) [1140][60/63] lr: 1.4613e-04 eta: 0:41:50 time: 0.4776 data_time: 0.0095 memory: 14901 loss: 0.8942 loss_prob: 0.4699 loss_thr: 0.3421 loss_db: 0.0822 2022/11/03 02:12:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:12:55 - mmengine - INFO - Saving checkpoint at 1140 epochs 2022/11/03 02:12:58 - mmengine - INFO - Epoch(val) [1140][5/500] eta: 0:41:50 time: 0.0468 data_time: 0.0051 memory: 14901 2022/11/03 02:12:59 - mmengine - INFO - Epoch(val) [1140][10/500] eta: 0:00:21 time: 0.0448 data_time: 0.0048 memory: 1008 2022/11/03 02:12:59 - mmengine - INFO - Epoch(val) [1140][15/500] eta: 0:00:21 time: 0.0378 data_time: 0.0021 memory: 1008 2022/11/03 02:12:59 - mmengine - INFO - Epoch(val) [1140][20/500] eta: 0:00:17 time: 0.0374 data_time: 0.0023 memory: 1008 2022/11/03 02:12:59 - mmengine - INFO - Epoch(val) [1140][25/500] eta: 0:00:17 time: 0.0351 data_time: 0.0023 memory: 1008 2022/11/03 02:12:59 - mmengine - INFO - Epoch(val) [1140][30/500] eta: 0:00:17 time: 0.0383 data_time: 0.0022 memory: 1008 2022/11/03 02:13:00 - mmengine - INFO - Epoch(val) [1140][35/500] eta: 0:00:17 time: 0.0387 data_time: 0.0021 memory: 1008 2022/11/03 02:13:00 - mmengine - INFO - Epoch(val) [1140][40/500] eta: 0:00:18 time: 0.0411 data_time: 0.0023 memory: 1008 2022/11/03 02:13:00 - mmengine - INFO - Epoch(val) [1140][45/500] eta: 0:00:18 time: 0.0417 data_time: 0.0024 memory: 1008 2022/11/03 02:13:00 - mmengine - INFO - Epoch(val) [1140][50/500] eta: 0:00:16 time: 0.0375 data_time: 0.0022 memory: 1008 2022/11/03 02:13:00 - mmengine - INFO - Epoch(val) [1140][55/500] eta: 0:00:16 time: 0.0403 data_time: 0.0022 memory: 1008 2022/11/03 02:13:01 - mmengine - INFO - Epoch(val) [1140][60/500] eta: 0:00:17 time: 0.0397 data_time: 0.0024 memory: 1008 2022/11/03 02:13:01 - mmengine - INFO - Epoch(val) [1140][65/500] eta: 0:00:17 time: 0.0398 data_time: 0.0025 memory: 1008 2022/11/03 02:13:01 - mmengine - INFO - Epoch(val) [1140][70/500] eta: 0:00:17 time: 0.0416 data_time: 0.0024 memory: 1008 2022/11/03 02:13:01 - mmengine - INFO - Epoch(val) [1140][75/500] eta: 0:00:17 time: 0.0399 data_time: 0.0026 memory: 1008 2022/11/03 02:13:01 - mmengine - INFO - Epoch(val) [1140][80/500] eta: 0:00:16 time: 0.0397 data_time: 0.0033 memory: 1008 2022/11/03 02:13:02 - mmengine - INFO - Epoch(val) [1140][85/500] eta: 0:00:16 time: 0.0414 data_time: 0.0036 memory: 1008 2022/11/03 02:13:02 - mmengine - INFO - Epoch(val) [1140][90/500] eta: 0:00:17 time: 0.0432 data_time: 0.0032 memory: 1008 2022/11/03 02:13:02 - mmengine - INFO - Epoch(val) [1140][95/500] eta: 0:00:17 time: 0.0483 data_time: 0.0033 memory: 1008 2022/11/03 02:13:02 - mmengine - INFO - Epoch(val) [1140][100/500] eta: 0:00:18 time: 0.0464 data_time: 0.0035 memory: 1008 2022/11/03 02:13:03 - mmengine - INFO - Epoch(val) [1140][105/500] eta: 0:00:18 time: 0.0441 data_time: 0.0036 memory: 1008 2022/11/03 02:13:03 - mmengine - INFO - Epoch(val) [1140][110/500] eta: 0:00:16 time: 0.0431 data_time: 0.0037 memory: 1008 2022/11/03 02:13:03 - mmengine - INFO - Epoch(val) [1140][115/500] eta: 0:00:16 time: 0.0389 data_time: 0.0031 memory: 1008 2022/11/03 02:13:03 - mmengine - INFO - Epoch(val) [1140][120/500] eta: 0:00:16 time: 0.0426 data_time: 0.0032 memory: 1008 2022/11/03 02:13:03 - mmengine - INFO - Epoch(val) [1140][125/500] eta: 0:00:16 time: 0.0400 data_time: 0.0028 memory: 1008 2022/11/03 02:13:03 - mmengine - INFO - Epoch(val) [1140][130/500] eta: 0:00:12 time: 0.0346 data_time: 0.0023 memory: 1008 2022/11/03 02:13:04 - mmengine - INFO - Epoch(val) [1140][135/500] eta: 0:00:12 time: 0.0360 data_time: 0.0025 memory: 1008 2022/11/03 02:13:04 - mmengine - INFO - Epoch(val) [1140][140/500] eta: 0:00:13 time: 0.0367 data_time: 0.0023 memory: 1008 2022/11/03 02:13:04 - mmengine - INFO - Epoch(val) [1140][145/500] eta: 0:00:13 time: 0.0412 data_time: 0.0021 memory: 1008 2022/11/03 02:13:04 - mmengine - INFO - Epoch(val) [1140][150/500] eta: 0:00:14 time: 0.0419 data_time: 0.0023 memory: 1008 2022/11/03 02:13:05 - mmengine - INFO - Epoch(val) [1140][155/500] eta: 0:00:14 time: 0.0413 data_time: 0.0023 memory: 1008 2022/11/03 02:13:05 - mmengine - INFO - Epoch(val) [1140][160/500] eta: 0:00:14 time: 0.0417 data_time: 0.0024 memory: 1008 2022/11/03 02:13:05 - mmengine - INFO - Epoch(val) [1140][165/500] eta: 0:00:14 time: 0.0377 data_time: 0.0024 memory: 1008 2022/11/03 02:13:05 - mmengine - INFO - Epoch(val) [1140][170/500] eta: 0:00:12 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/03 02:13:05 - mmengine - INFO - Epoch(val) [1140][175/500] eta: 0:00:12 time: 0.0385 data_time: 0.0025 memory: 1008 2022/11/03 02:13:05 - mmengine - INFO - Epoch(val) [1140][180/500] eta: 0:00:12 time: 0.0380 data_time: 0.0028 memory: 1008 2022/11/03 02:13:06 - mmengine - INFO - Epoch(val) [1140][185/500] eta: 0:00:12 time: 0.0396 data_time: 0.0026 memory: 1008 2022/11/03 02:13:06 - mmengine - INFO - Epoch(val) [1140][190/500] eta: 0:00:12 time: 0.0394 data_time: 0.0021 memory: 1008 2022/11/03 02:13:06 - mmengine - INFO - Epoch(val) [1140][195/500] eta: 0:00:12 time: 0.0368 data_time: 0.0020 memory: 1008 2022/11/03 02:13:06 - mmengine - INFO - Epoch(val) [1140][200/500] eta: 0:00:12 time: 0.0422 data_time: 0.0021 memory: 1008 2022/11/03 02:13:06 - mmengine - INFO - Epoch(val) [1140][205/500] eta: 0:00:12 time: 0.0430 data_time: 0.0023 memory: 1008 2022/11/03 02:13:07 - mmengine - INFO - Epoch(val) [1140][210/500] eta: 0:00:10 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/03 02:13:07 - mmengine - INFO - Epoch(val) [1140][215/500] eta: 0:00:10 time: 0.0369 data_time: 0.0025 memory: 1008 2022/11/03 02:13:07 - mmengine - INFO - Epoch(val) [1140][220/500] eta: 0:00:10 time: 0.0383 data_time: 0.0025 memory: 1008 2022/11/03 02:13:07 - mmengine - INFO - Epoch(val) [1140][225/500] eta: 0:00:10 time: 0.0394 data_time: 0.0024 memory: 1008 2022/11/03 02:13:07 - mmengine - INFO - Epoch(val) [1140][230/500] eta: 0:00:09 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/03 02:13:08 - mmengine - INFO - Epoch(val) [1140][235/500] eta: 0:00:09 time: 0.0373 data_time: 0.0022 memory: 1008 2022/11/03 02:13:08 - mmengine - INFO - Epoch(val) [1140][240/500] eta: 0:00:10 time: 0.0389 data_time: 0.0022 memory: 1008 2022/11/03 02:13:08 - mmengine - INFO - Epoch(val) [1140][245/500] eta: 0:00:10 time: 0.0349 data_time: 0.0020 memory: 1008 2022/11/03 02:13:08 - mmengine - INFO - Epoch(val) [1140][250/500] eta: 0:00:10 time: 0.0400 data_time: 0.0022 memory: 1008 2022/11/03 02:13:08 - mmengine - INFO - Epoch(val) [1140][255/500] eta: 0:00:10 time: 0.0402 data_time: 0.0023 memory: 1008 2022/11/03 02:13:09 - mmengine - INFO - Epoch(val) [1140][260/500] eta: 0:00:08 time: 0.0354 data_time: 0.0022 memory: 1008 2022/11/03 02:13:09 - mmengine - INFO - Epoch(val) [1140][265/500] eta: 0:00:08 time: 0.0386 data_time: 0.0025 memory: 1008 2022/11/03 02:13:09 - mmengine - INFO - Epoch(val) [1140][270/500] eta: 0:00:08 time: 0.0388 data_time: 0.0026 memory: 1008 2022/11/03 02:13:09 - mmengine - INFO - Epoch(val) [1140][275/500] eta: 0:00:08 time: 0.0359 data_time: 0.0024 memory: 1008 2022/11/03 02:13:09 - mmengine - INFO - Epoch(val) [1140][280/500] eta: 0:00:08 time: 0.0399 data_time: 0.0023 memory: 1008 2022/11/03 02:13:10 - mmengine - INFO - Epoch(val) [1140][285/500] eta: 0:00:08 time: 0.0394 data_time: 0.0023 memory: 1008 2022/11/03 02:13:10 - mmengine - INFO - Epoch(val) [1140][290/500] eta: 0:00:08 time: 0.0393 data_time: 0.0024 memory: 1008 2022/11/03 02:13:10 - mmengine - INFO - Epoch(val) [1140][295/500] eta: 0:00:08 time: 0.0419 data_time: 0.0028 memory: 1008 2022/11/03 02:13:10 - mmengine - INFO - Epoch(val) [1140][300/500] eta: 0:00:07 time: 0.0376 data_time: 0.0026 memory: 1008 2022/11/03 02:13:10 - mmengine - INFO - Epoch(val) [1140][305/500] eta: 0:00:07 time: 0.0352 data_time: 0.0022 memory: 1008 2022/11/03 02:13:10 - mmengine - INFO - Epoch(val) [1140][310/500] eta: 0:00:06 time: 0.0349 data_time: 0.0021 memory: 1008 2022/11/03 02:13:11 - mmengine - INFO - Epoch(val) [1140][315/500] eta: 0:00:06 time: 0.0414 data_time: 0.0021 memory: 1008 2022/11/03 02:13:11 - mmengine - INFO - Epoch(val) [1140][320/500] eta: 0:00:07 time: 0.0412 data_time: 0.0022 memory: 1008 2022/11/03 02:13:11 - mmengine - INFO - Epoch(val) [1140][325/500] eta: 0:00:07 time: 0.0469 data_time: 0.0021 memory: 1008 2022/11/03 02:13:11 - mmengine - INFO - Epoch(val) [1140][330/500] eta: 0:00:08 time: 0.0472 data_time: 0.0022 memory: 1008 2022/11/03 02:13:12 - mmengine - INFO - Epoch(val) [1140][335/500] eta: 0:00:08 time: 0.0345 data_time: 0.0022 memory: 1008 2022/11/03 02:13:12 - mmengine - INFO - Epoch(val) [1140][340/500] eta: 0:00:07 time: 0.0460 data_time: 0.0023 memory: 1008 2022/11/03 02:13:12 - mmengine - INFO - Epoch(val) [1140][345/500] eta: 0:00:07 time: 0.0476 data_time: 0.0024 memory: 1008 2022/11/03 02:13:12 - mmengine - INFO - Epoch(val) [1140][350/500] eta: 0:00:06 time: 0.0415 data_time: 0.0024 memory: 1008 2022/11/03 02:13:12 - mmengine - INFO - Epoch(val) [1140][355/500] eta: 0:00:06 time: 0.0398 data_time: 0.0024 memory: 1008 2022/11/03 02:13:13 - mmengine - INFO - Epoch(val) [1140][360/500] eta: 0:00:04 time: 0.0352 data_time: 0.0023 memory: 1008 2022/11/03 02:13:13 - mmengine - INFO - Epoch(val) [1140][365/500] eta: 0:00:04 time: 0.0368 data_time: 0.0023 memory: 1008 2022/11/03 02:13:13 - mmengine - INFO - Epoch(val) [1140][370/500] eta: 0:00:04 time: 0.0345 data_time: 0.0023 memory: 1008 2022/11/03 02:13:13 - mmengine - INFO - Epoch(val) [1140][375/500] eta: 0:00:04 time: 0.0342 data_time: 0.0023 memory: 1008 2022/11/03 02:13:13 - mmengine - INFO - Epoch(val) [1140][380/500] eta: 0:00:04 time: 0.0395 data_time: 0.0024 memory: 1008 2022/11/03 02:13:13 - mmengine - INFO - Epoch(val) [1140][385/500] eta: 0:00:04 time: 0.0389 data_time: 0.0023 memory: 1008 2022/11/03 02:13:14 - mmengine - INFO - Epoch(val) [1140][390/500] eta: 0:00:04 time: 0.0370 data_time: 0.0022 memory: 1008 2022/11/03 02:13:14 - mmengine - INFO - Epoch(val) [1140][395/500] eta: 0:00:04 time: 0.0373 data_time: 0.0025 memory: 1008 2022/11/03 02:13:14 - mmengine - INFO - Epoch(val) [1140][400/500] eta: 0:00:03 time: 0.0360 data_time: 0.0024 memory: 1008 2022/11/03 02:13:14 - mmengine - INFO - Epoch(val) [1140][405/500] eta: 0:00:03 time: 0.0371 data_time: 0.0024 memory: 1008 2022/11/03 02:13:14 - mmengine - INFO - Epoch(val) [1140][410/500] eta: 0:00:03 time: 0.0392 data_time: 0.0024 memory: 1008 2022/11/03 02:13:15 - mmengine - INFO - Epoch(val) [1140][415/500] eta: 0:00:03 time: 0.0378 data_time: 0.0022 memory: 1008 2022/11/03 02:13:15 - mmengine - INFO - Epoch(val) [1140][420/500] eta: 0:00:02 time: 0.0341 data_time: 0.0022 memory: 1008 2022/11/03 02:13:15 - mmengine - INFO - Epoch(val) [1140][425/500] eta: 0:00:02 time: 0.0356 data_time: 0.0025 memory: 1008 2022/11/03 02:13:15 - mmengine - INFO - Epoch(val) [1140][430/500] eta: 0:00:02 time: 0.0391 data_time: 0.0025 memory: 1008 2022/11/03 02:13:15 - mmengine - INFO - Epoch(val) [1140][435/500] eta: 0:00:02 time: 0.0379 data_time: 0.0023 memory: 1008 2022/11/03 02:13:16 - mmengine - INFO - Epoch(val) [1140][440/500] eta: 0:00:02 time: 0.0357 data_time: 0.0022 memory: 1008 2022/11/03 02:13:16 - mmengine - INFO - Epoch(val) [1140][445/500] eta: 0:00:02 time: 0.0366 data_time: 0.0021 memory: 1008 2022/11/03 02:13:16 - mmengine - INFO - Epoch(val) [1140][450/500] eta: 0:00:01 time: 0.0382 data_time: 0.0022 memory: 1008 2022/11/03 02:13:16 - mmengine - INFO - Epoch(val) [1140][455/500] eta: 0:00:01 time: 0.0384 data_time: 0.0023 memory: 1008 2022/11/03 02:13:16 - mmengine - INFO - Epoch(val) [1140][460/500] eta: 0:00:01 time: 0.0350 data_time: 0.0022 memory: 1008 2022/11/03 02:13:16 - mmengine - INFO - Epoch(val) [1140][465/500] eta: 0:00:01 time: 0.0343 data_time: 0.0023 memory: 1008 2022/11/03 02:13:17 - mmengine - INFO - Epoch(val) [1140][470/500] eta: 0:00:01 time: 0.0356 data_time: 0.0022 memory: 1008 2022/11/03 02:13:17 - mmengine - INFO - Epoch(val) [1140][475/500] eta: 0:00:01 time: 0.0338 data_time: 0.0021 memory: 1008 2022/11/03 02:13:17 - mmengine - INFO - Epoch(val) [1140][480/500] eta: 0:00:00 time: 0.0362 data_time: 0.0024 memory: 1008 2022/11/03 02:13:17 - mmengine - INFO - Epoch(val) [1140][485/500] eta: 0:00:00 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/03 02:13:17 - mmengine - INFO - Epoch(val) [1140][490/500] eta: 0:00:00 time: 0.0362 data_time: 0.0022 memory: 1008 2022/11/03 02:13:18 - mmengine - INFO - Epoch(val) [1140][495/500] eta: 0:00:00 time: 0.0406 data_time: 0.0023 memory: 1008 2022/11/03 02:13:18 - mmengine - INFO - Epoch(val) [1140][500/500] eta: 0:00:00 time: 0.0387 data_time: 0.0021 memory: 1008 2022/11/03 02:13:18 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8363, precision: 0.7710, hmean: 0.8023 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8363, precision: 0.8057, hmean: 0.8207 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8363, precision: 0.8291, hmean: 0.8327 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8325, precision: 0.8521, hmean: 0.8422 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8233, precision: 0.8738, hmean: 0.8478 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7439, precision: 0.9175, hmean: 0.8216 2022/11/03 02:13:18 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2162, precision: 0.9635, hmean: 0.3531 2022/11/03 02:13:18 - mmengine - INFO - Epoch(val) [1140][500/500] icdar/precision: 0.8738 icdar/recall: 0.8233 icdar/hmean: 0.8478 2022/11/03 02:13:22 - mmengine - INFO - Epoch(train) [1141][5/63] lr: 1.4394e-04 eta: 0:00:00 time: 0.6851 data_time: 0.2001 memory: 14901 loss: 0.9187 loss_prob: 0.4855 loss_thr: 0.3496 loss_db: 0.0837 2022/11/03 02:13:25 - mmengine - INFO - Epoch(train) [1141][10/63] lr: 1.4394e-04 eta: 0:41:41 time: 0.6887 data_time: 0.1991 memory: 14901 loss: 0.8239 loss_prob: 0.4218 loss_thr: 0.3278 loss_db: 0.0743 2022/11/03 02:13:27 - mmengine - INFO - Epoch(train) [1141][15/63] lr: 1.4394e-04 eta: 0:41:41 time: 0.4800 data_time: 0.0069 memory: 14901 loss: 0.8568 loss_prob: 0.4423 loss_thr: 0.3375 loss_db: 0.0769 2022/11/03 02:13:29 - mmengine - INFO - Epoch(train) [1141][20/63] lr: 1.4394e-04 eta: 0:41:35 time: 0.4803 data_time: 0.0056 memory: 14901 loss: 0.7780 loss_prob: 0.4008 loss_thr: 0.3069 loss_db: 0.0703 2022/11/03 02:13:32 - mmengine - INFO - Epoch(train) [1141][25/63] lr: 1.4394e-04 eta: 0:41:35 time: 0.4645 data_time: 0.0170 memory: 14901 loss: 0.7761 loss_prob: 0.3949 loss_thr: 0.3114 loss_db: 0.0699 2022/11/03 02:13:34 - mmengine - INFO - Epoch(train) [1141][30/63] lr: 1.4394e-04 eta: 0:41:28 time: 0.4717 data_time: 0.0341 memory: 14901 loss: 0.8590 loss_prob: 0.4321 loss_thr: 0.3526 loss_db: 0.0742 2022/11/03 02:13:37 - mmengine - INFO - Epoch(train) [1141][35/63] lr: 1.4394e-04 eta: 0:41:28 time: 0.5225 data_time: 0.0250 memory: 14901 loss: 0.9575 loss_prob: 0.4938 loss_thr: 0.3777 loss_db: 0.0859 2022/11/03 02:13:39 - mmengine - INFO - Epoch(train) [1141][40/63] lr: 1.4394e-04 eta: 0:41:21 time: 0.5210 data_time: 0.0078 memory: 14901 loss: 0.9356 loss_prob: 0.4871 loss_thr: 0.3621 loss_db: 0.0864 2022/11/03 02:13:42 - mmengine - INFO - Epoch(train) [1141][45/63] lr: 1.4394e-04 eta: 0:41:21 time: 0.4795 data_time: 0.0051 memory: 14901 loss: 0.8535 loss_prob: 0.4359 loss_thr: 0.3395 loss_db: 0.0781 2022/11/03 02:13:44 - mmengine - INFO - Epoch(train) [1141][50/63] lr: 1.4394e-04 eta: 0:41:14 time: 0.4790 data_time: 0.0126 memory: 14901 loss: 0.8476 loss_prob: 0.4313 loss_thr: 0.3381 loss_db: 0.0781 2022/11/03 02:13:47 - mmengine - INFO - Epoch(train) [1141][55/63] lr: 1.4394e-04 eta: 0:41:14 time: 0.4798 data_time: 0.0252 memory: 14901 loss: 0.7907 loss_prob: 0.4040 loss_thr: 0.3145 loss_db: 0.0722 2022/11/03 02:13:49 - mmengine - INFO - Epoch(train) [1141][60/63] lr: 1.4394e-04 eta: 0:41:08 time: 0.4766 data_time: 0.0187 memory: 14901 loss: 0.7949 loss_prob: 0.4098 loss_thr: 0.3135 loss_db: 0.0716 2022/11/03 02:13:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:13:55 - mmengine - INFO - Epoch(train) [1142][5/63] lr: 1.4174e-04 eta: 0:41:08 time: 0.6496 data_time: 0.2011 memory: 14901 loss: 0.8508 loss_prob: 0.4358 loss_thr: 0.3400 loss_db: 0.0750 2022/11/03 02:13:57 - mmengine - INFO - Epoch(train) [1142][10/63] lr: 1.4174e-04 eta: 0:40:59 time: 0.6752 data_time: 0.2009 memory: 14901 loss: 0.8712 loss_prob: 0.4494 loss_thr: 0.3445 loss_db: 0.0773 2022/11/03 02:13:59 - mmengine - INFO - Epoch(train) [1142][15/63] lr: 1.4174e-04 eta: 0:40:59 time: 0.4699 data_time: 0.0059 memory: 14901 loss: 0.8580 loss_prob: 0.4462 loss_thr: 0.3339 loss_db: 0.0779 2022/11/03 02:14:01 - mmengine - INFO - Epoch(train) [1142][20/63] lr: 1.4174e-04 eta: 0:40:52 time: 0.4521 data_time: 0.0066 memory: 14901 loss: 0.8461 loss_prob: 0.4388 loss_thr: 0.3317 loss_db: 0.0757 2022/11/03 02:14:04 - mmengine - INFO - Epoch(train) [1142][25/63] lr: 1.4174e-04 eta: 0:40:52 time: 0.4664 data_time: 0.0161 memory: 14901 loss: 0.8526 loss_prob: 0.4392 loss_thr: 0.3363 loss_db: 0.0772 2022/11/03 02:14:07 - mmengine - INFO - Epoch(train) [1142][30/63] lr: 1.4174e-04 eta: 0:40:45 time: 0.5131 data_time: 0.0336 memory: 14901 loss: 0.8167 loss_prob: 0.4174 loss_thr: 0.3248 loss_db: 0.0745 2022/11/03 02:14:09 - mmengine - INFO - Epoch(train) [1142][35/63] lr: 1.4174e-04 eta: 0:40:45 time: 0.5010 data_time: 0.0238 memory: 14901 loss: 0.8563 loss_prob: 0.4406 loss_thr: 0.3387 loss_db: 0.0769 2022/11/03 02:14:11 - mmengine - INFO - Epoch(train) [1142][40/63] lr: 1.4174e-04 eta: 0:40:39 time: 0.4908 data_time: 0.0051 memory: 14901 loss: 0.9540 loss_prob: 0.5056 loss_thr: 0.3631 loss_db: 0.0853 2022/11/03 02:14:14 - mmengine - INFO - Epoch(train) [1142][45/63] lr: 1.4174e-04 eta: 0:40:39 time: 0.5119 data_time: 0.0071 memory: 14901 loss: 0.9256 loss_prob: 0.4906 loss_thr: 0.3515 loss_db: 0.0835 2022/11/03 02:14:17 - mmengine - INFO - Epoch(train) [1142][50/63] lr: 1.4174e-04 eta: 0:40:32 time: 0.5046 data_time: 0.0221 memory: 14901 loss: 0.8251 loss_prob: 0.4301 loss_thr: 0.3200 loss_db: 0.0750 2022/11/03 02:14:19 - mmengine - INFO - Epoch(train) [1142][55/63] lr: 1.4174e-04 eta: 0:40:32 time: 0.4748 data_time: 0.0220 memory: 14901 loss: 0.7694 loss_prob: 0.3915 loss_thr: 0.3102 loss_db: 0.0678 2022/11/03 02:14:21 - mmengine - INFO - Epoch(train) [1142][60/63] lr: 1.4174e-04 eta: 0:40:25 time: 0.4730 data_time: 0.0069 memory: 14901 loss: 0.7559 loss_prob: 0.3726 loss_thr: 0.3177 loss_db: 0.0656 2022/11/03 02:14:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:14:27 - mmengine - INFO - Epoch(train) [1143][5/63] lr: 1.3954e-04 eta: 0:40:25 time: 0.6534 data_time: 0.1821 memory: 14901 loss: 0.8137 loss_prob: 0.4127 loss_thr: 0.3276 loss_db: 0.0733 2022/11/03 02:14:29 - mmengine - INFO - Epoch(train) [1143][10/63] lr: 1.3954e-04 eta: 0:40:17 time: 0.6935 data_time: 0.1824 memory: 14901 loss: 0.8327 loss_prob: 0.4264 loss_thr: 0.3312 loss_db: 0.0752 2022/11/03 02:14:32 - mmengine - INFO - Epoch(train) [1143][15/63] lr: 1.3954e-04 eta: 0:40:17 time: 0.5148 data_time: 0.0091 memory: 14901 loss: 0.8626 loss_prob: 0.4432 loss_thr: 0.3399 loss_db: 0.0795 2022/11/03 02:14:34 - mmengine - INFO - Epoch(train) [1143][20/63] lr: 1.3954e-04 eta: 0:40:10 time: 0.4917 data_time: 0.0085 memory: 14901 loss: 0.8587 loss_prob: 0.4377 loss_thr: 0.3433 loss_db: 0.0776 2022/11/03 02:14:37 - mmengine - INFO - Epoch(train) [1143][25/63] lr: 1.3954e-04 eta: 0:40:10 time: 0.5153 data_time: 0.0071 memory: 14901 loss: 0.8139 loss_prob: 0.4097 loss_thr: 0.3340 loss_db: 0.0702 2022/11/03 02:14:40 - mmengine - INFO - Epoch(train) [1143][30/63] lr: 1.3954e-04 eta: 0:40:03 time: 0.5414 data_time: 0.0329 memory: 14901 loss: 0.8221 loss_prob: 0.4194 loss_thr: 0.3310 loss_db: 0.0717 2022/11/03 02:14:42 - mmengine - INFO - Epoch(train) [1143][35/63] lr: 1.3954e-04 eta: 0:40:03 time: 0.5164 data_time: 0.0348 memory: 14901 loss: 0.8357 loss_prob: 0.4297 loss_thr: 0.3301 loss_db: 0.0759 2022/11/03 02:14:45 - mmengine - INFO - Epoch(train) [1143][40/63] lr: 1.3954e-04 eta: 0:39:56 time: 0.4764 data_time: 0.0089 memory: 14901 loss: 0.8710 loss_prob: 0.4495 loss_thr: 0.3425 loss_db: 0.0789 2022/11/03 02:14:47 - mmengine - INFO - Epoch(train) [1143][45/63] lr: 1.3954e-04 eta: 0:39:56 time: 0.4490 data_time: 0.0050 memory: 14901 loss: 0.9637 loss_prob: 0.5232 loss_thr: 0.3535 loss_db: 0.0870 2022/11/03 02:14:49 - mmengine - INFO - Epoch(train) [1143][50/63] lr: 1.3954e-04 eta: 0:39:50 time: 0.4704 data_time: 0.0158 memory: 14901 loss: 0.9232 loss_prob: 0.5051 loss_thr: 0.3332 loss_db: 0.0849 2022/11/03 02:14:51 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:14:52 - mmengine - INFO - Epoch(train) [1143][55/63] lr: 1.3954e-04 eta: 0:39:50 time: 0.4802 data_time: 0.0265 memory: 14901 loss: 0.8086 loss_prob: 0.4134 loss_thr: 0.3209 loss_db: 0.0742 2022/11/03 02:14:54 - mmengine - INFO - Epoch(train) [1143][60/63] lr: 1.3954e-04 eta: 0:39:43 time: 0.4669 data_time: 0.0173 memory: 14901 loss: 0.8037 loss_prob: 0.4053 loss_thr: 0.3253 loss_db: 0.0732 2022/11/03 02:14:55 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:14:59 - mmengine - INFO - Epoch(train) [1144][5/63] lr: 1.3734e-04 eta: 0:39:43 time: 0.6521 data_time: 0.2173 memory: 14901 loss: 0.8684 loss_prob: 0.4567 loss_thr: 0.3338 loss_db: 0.0780 2022/11/03 02:15:02 - mmengine - INFO - Epoch(train) [1144][10/63] lr: 1.3734e-04 eta: 0:39:34 time: 0.6808 data_time: 0.2157 memory: 14901 loss: 0.8818 loss_prob: 0.4551 loss_thr: 0.3488 loss_db: 0.0779 2022/11/03 02:15:04 - mmengine - INFO - Epoch(train) [1144][15/63] lr: 1.3734e-04 eta: 0:39:34 time: 0.4591 data_time: 0.0065 memory: 14901 loss: 0.8879 loss_prob: 0.4603 loss_thr: 0.3466 loss_db: 0.0810 2022/11/03 02:15:06 - mmengine - INFO - Epoch(train) [1144][20/63] lr: 1.3734e-04 eta: 0:39:28 time: 0.4592 data_time: 0.0078 memory: 14901 loss: 0.8509 loss_prob: 0.4432 loss_thr: 0.3292 loss_db: 0.0784 2022/11/03 02:15:09 - mmengine - INFO - Epoch(train) [1144][25/63] lr: 1.3734e-04 eta: 0:39:28 time: 0.4908 data_time: 0.0252 memory: 14901 loss: 0.8465 loss_prob: 0.4350 loss_thr: 0.3347 loss_db: 0.0768 2022/11/03 02:15:11 - mmengine - INFO - Epoch(train) [1144][30/63] lr: 1.3734e-04 eta: 0:39:21 time: 0.4946 data_time: 0.0363 memory: 14901 loss: 0.9246 loss_prob: 0.4878 loss_thr: 0.3529 loss_db: 0.0838 2022/11/03 02:15:14 - mmengine - INFO - Epoch(train) [1144][35/63] lr: 1.3734e-04 eta: 0:39:21 time: 0.5066 data_time: 0.0175 memory: 14901 loss: 0.9086 loss_prob: 0.4893 loss_thr: 0.3391 loss_db: 0.0801 2022/11/03 02:15:16 - mmengine - INFO - Epoch(train) [1144][40/63] lr: 1.3734e-04 eta: 0:39:14 time: 0.4963 data_time: 0.0056 memory: 14901 loss: 0.9283 loss_prob: 0.5024 loss_thr: 0.3428 loss_db: 0.0831 2022/11/03 02:15:19 - mmengine - INFO - Epoch(train) [1144][45/63] lr: 1.3734e-04 eta: 0:39:14 time: 0.4713 data_time: 0.0074 memory: 14901 loss: 0.8967 loss_prob: 0.4729 loss_thr: 0.3441 loss_db: 0.0797 2022/11/03 02:15:21 - mmengine - INFO - Epoch(train) [1144][50/63] lr: 1.3734e-04 eta: 0:39:07 time: 0.4874 data_time: 0.0236 memory: 14901 loss: 0.8165 loss_prob: 0.4145 loss_thr: 0.3305 loss_db: 0.0716 2022/11/03 02:15:24 - mmengine - INFO - Epoch(train) [1144][55/63] lr: 1.3734e-04 eta: 0:39:07 time: 0.4875 data_time: 0.0359 memory: 14901 loss: 0.8349 loss_prob: 0.4298 loss_thr: 0.3295 loss_db: 0.0757 2022/11/03 02:15:26 - mmengine - INFO - Epoch(train) [1144][60/63] lr: 1.3734e-04 eta: 0:39:01 time: 0.4882 data_time: 0.0191 memory: 14901 loss: 0.8425 loss_prob: 0.4353 loss_thr: 0.3294 loss_db: 0.0778 2022/11/03 02:15:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:15:32 - mmengine - INFO - Epoch(train) [1145][5/63] lr: 1.3513e-04 eta: 0:39:01 time: 0.7160 data_time: 0.2174 memory: 14901 loss: 0.8261 loss_prob: 0.4230 loss_thr: 0.3282 loss_db: 0.0748 2022/11/03 02:15:35 - mmengine - INFO - Epoch(train) [1145][10/63] lr: 1.3513e-04 eta: 0:38:52 time: 0.7235 data_time: 0.2199 memory: 14901 loss: 0.7908 loss_prob: 0.4095 loss_thr: 0.3087 loss_db: 0.0727 2022/11/03 02:15:37 - mmengine - INFO - Epoch(train) [1145][15/63] lr: 1.3513e-04 eta: 0:38:52 time: 0.4718 data_time: 0.0076 memory: 14901 loss: 0.8282 loss_prob: 0.4259 loss_thr: 0.3275 loss_db: 0.0748 2022/11/03 02:15:39 - mmengine - INFO - Epoch(train) [1145][20/63] lr: 1.3513e-04 eta: 0:38:45 time: 0.4945 data_time: 0.0052 memory: 14901 loss: 0.8548 loss_prob: 0.4358 loss_thr: 0.3431 loss_db: 0.0759 2022/11/03 02:15:42 - mmengine - INFO - Epoch(train) [1145][25/63] lr: 1.3513e-04 eta: 0:38:45 time: 0.5105 data_time: 0.0356 memory: 14901 loss: 0.8152 loss_prob: 0.4196 loss_thr: 0.3224 loss_db: 0.0732 2022/11/03 02:15:44 - mmengine - INFO - Epoch(train) [1145][30/63] lr: 1.3513e-04 eta: 0:38:39 time: 0.4916 data_time: 0.0358 memory: 14901 loss: 0.8076 loss_prob: 0.4099 loss_thr: 0.3256 loss_db: 0.0721 2022/11/03 02:15:47 - mmengine - INFO - Epoch(train) [1145][35/63] lr: 1.3513e-04 eta: 0:38:39 time: 0.4652 data_time: 0.0050 memory: 14901 loss: 0.8576 loss_prob: 0.4375 loss_thr: 0.3425 loss_db: 0.0776 2022/11/03 02:15:49 - mmengine - INFO - Epoch(train) [1145][40/63] lr: 1.3513e-04 eta: 0:38:32 time: 0.4904 data_time: 0.0054 memory: 14901 loss: 0.8660 loss_prob: 0.4483 loss_thr: 0.3386 loss_db: 0.0791 2022/11/03 02:15:52 - mmengine - INFO - Epoch(train) [1145][45/63] lr: 1.3513e-04 eta: 0:38:32 time: 0.4840 data_time: 0.0067 memory: 14901 loss: 0.8890 loss_prob: 0.4682 loss_thr: 0.3409 loss_db: 0.0799 2022/11/03 02:15:54 - mmengine - INFO - Epoch(train) [1145][50/63] lr: 1.3513e-04 eta: 0:38:25 time: 0.4843 data_time: 0.0231 memory: 14901 loss: 0.8857 loss_prob: 0.4657 loss_thr: 0.3402 loss_db: 0.0799 2022/11/03 02:15:56 - mmengine - INFO - Epoch(train) [1145][55/63] lr: 1.3513e-04 eta: 0:38:25 time: 0.4768 data_time: 0.0251 memory: 14901 loss: 0.8376 loss_prob: 0.4279 loss_thr: 0.3346 loss_db: 0.0751 2022/11/03 02:15:59 - mmengine - INFO - Epoch(train) [1145][60/63] lr: 1.3513e-04 eta: 0:38:18 time: 0.4757 data_time: 0.0081 memory: 14901 loss: 0.8242 loss_prob: 0.4192 loss_thr: 0.3315 loss_db: 0.0735 2022/11/03 02:16:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:16:04 - mmengine - INFO - Epoch(train) [1146][5/63] lr: 1.3292e-04 eta: 0:38:18 time: 0.6040 data_time: 0.1774 memory: 14901 loss: 0.8267 loss_prob: 0.4256 loss_thr: 0.3265 loss_db: 0.0746 2022/11/03 02:16:06 - mmengine - INFO - Epoch(train) [1146][10/63] lr: 1.3292e-04 eta: 0:38:10 time: 0.6321 data_time: 0.1826 memory: 14901 loss: 0.8148 loss_prob: 0.4139 loss_thr: 0.3287 loss_db: 0.0723 2022/11/03 02:16:09 - mmengine - INFO - Epoch(train) [1146][15/63] lr: 1.3292e-04 eta: 0:38:10 time: 0.4746 data_time: 0.0145 memory: 14901 loss: 0.8710 loss_prob: 0.4430 loss_thr: 0.3510 loss_db: 0.0769 2022/11/03 02:16:11 - mmengine - INFO - Epoch(train) [1146][20/63] lr: 1.3292e-04 eta: 0:38:03 time: 0.4653 data_time: 0.0094 memory: 14901 loss: 0.8799 loss_prob: 0.4539 loss_thr: 0.3462 loss_db: 0.0798 2022/11/03 02:16:14 - mmengine - INFO - Epoch(train) [1146][25/63] lr: 1.3292e-04 eta: 0:38:03 time: 0.4774 data_time: 0.0179 memory: 14901 loss: 0.9030 loss_prob: 0.4762 loss_thr: 0.3435 loss_db: 0.0832 2022/11/03 02:16:16 - mmengine - INFO - Epoch(train) [1146][30/63] lr: 1.3292e-04 eta: 0:37:56 time: 0.5139 data_time: 0.0217 memory: 14901 loss: 0.8842 loss_prob: 0.4660 loss_thr: 0.3370 loss_db: 0.0812 2022/11/03 02:16:19 - mmengine - INFO - Epoch(train) [1146][35/63] lr: 1.3292e-04 eta: 0:37:56 time: 0.5087 data_time: 0.0231 memory: 14901 loss: 0.8093 loss_prob: 0.4165 loss_thr: 0.3191 loss_db: 0.0736 2022/11/03 02:16:21 - mmengine - INFO - Epoch(train) [1146][40/63] lr: 1.3292e-04 eta: 0:37:50 time: 0.4813 data_time: 0.0198 memory: 14901 loss: 0.8235 loss_prob: 0.4229 loss_thr: 0.3253 loss_db: 0.0753 2022/11/03 02:16:24 - mmengine - INFO - Epoch(train) [1146][45/63] lr: 1.3292e-04 eta: 0:37:50 time: 0.5126 data_time: 0.0101 memory: 14901 loss: 0.8235 loss_prob: 0.4236 loss_thr: 0.3248 loss_db: 0.0751 2022/11/03 02:16:26 - mmengine - INFO - Epoch(train) [1146][50/63] lr: 1.3292e-04 eta: 0:37:43 time: 0.5362 data_time: 0.0192 memory: 14901 loss: 0.9031 loss_prob: 0.4779 loss_thr: 0.3453 loss_db: 0.0799 2022/11/03 02:16:29 - mmengine - INFO - Epoch(train) [1146][55/63] lr: 1.3292e-04 eta: 0:37:43 time: 0.5129 data_time: 0.0239 memory: 14901 loss: 0.9288 loss_prob: 0.4920 loss_thr: 0.3558 loss_db: 0.0811 2022/11/03 02:16:31 - mmengine - INFO - Epoch(train) [1146][60/63] lr: 1.3292e-04 eta: 0:37:36 time: 0.4937 data_time: 0.0139 memory: 14901 loss: 0.8874 loss_prob: 0.4572 loss_thr: 0.3510 loss_db: 0.0792 2022/11/03 02:16:32 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:16:37 - mmengine - INFO - Epoch(train) [1147][5/63] lr: 1.3070e-04 eta: 0:37:36 time: 0.6834 data_time: 0.2218 memory: 14901 loss: 0.8738 loss_prob: 0.4506 loss_thr: 0.3424 loss_db: 0.0807 2022/11/03 02:16:40 - mmengine - INFO - Epoch(train) [1147][10/63] lr: 1.3070e-04 eta: 0:37:27 time: 0.7106 data_time: 0.2217 memory: 14901 loss: 0.8383 loss_prob: 0.4325 loss_thr: 0.3279 loss_db: 0.0779 2022/11/03 02:16:42 - mmengine - INFO - Epoch(train) [1147][15/63] lr: 1.3070e-04 eta: 0:37:27 time: 0.4813 data_time: 0.0054 memory: 14901 loss: 0.7772 loss_prob: 0.3911 loss_thr: 0.3171 loss_db: 0.0689 2022/11/03 02:16:44 - mmengine - INFO - Epoch(train) [1147][20/63] lr: 1.3070e-04 eta: 0:37:21 time: 0.4860 data_time: 0.0054 memory: 14901 loss: 0.8290 loss_prob: 0.4246 loss_thr: 0.3319 loss_db: 0.0726 2022/11/03 02:16:47 - mmengine - INFO - Epoch(train) [1147][25/63] lr: 1.3070e-04 eta: 0:37:21 time: 0.4903 data_time: 0.0298 memory: 14901 loss: 0.8682 loss_prob: 0.4479 loss_thr: 0.3427 loss_db: 0.0776 2022/11/03 02:16:49 - mmengine - INFO - Epoch(train) [1147][30/63] lr: 1.3070e-04 eta: 0:37:14 time: 0.4878 data_time: 0.0353 memory: 14901 loss: 0.9434 loss_prob: 0.4929 loss_thr: 0.3633 loss_db: 0.0872 2022/11/03 02:16:52 - mmengine - INFO - Epoch(train) [1147][35/63] lr: 1.3070e-04 eta: 0:37:14 time: 0.4694 data_time: 0.0120 memory: 14901 loss: 0.9044 loss_prob: 0.4759 loss_thr: 0.3447 loss_db: 0.0838 2022/11/03 02:16:54 - mmengine - INFO - Epoch(train) [1147][40/63] lr: 1.3070e-04 eta: 0:37:07 time: 0.4655 data_time: 0.0069 memory: 14901 loss: 0.7802 loss_prob: 0.3984 loss_thr: 0.3122 loss_db: 0.0696 2022/11/03 02:16:56 - mmengine - INFO - Epoch(train) [1147][45/63] lr: 1.3070e-04 eta: 0:37:07 time: 0.4619 data_time: 0.0057 memory: 14901 loss: 0.8631 loss_prob: 0.4435 loss_thr: 0.3416 loss_db: 0.0780 2022/11/03 02:16:59 - mmengine - INFO - Epoch(train) [1147][50/63] lr: 1.3070e-04 eta: 0:37:01 time: 0.4768 data_time: 0.0258 memory: 14901 loss: 0.8944 loss_prob: 0.4695 loss_thr: 0.3427 loss_db: 0.0823 2022/11/03 02:17:01 - mmengine - INFO - Epoch(train) [1147][55/63] lr: 1.3070e-04 eta: 0:37:01 time: 0.4882 data_time: 0.0259 memory: 14901 loss: 0.8591 loss_prob: 0.4455 loss_thr: 0.3373 loss_db: 0.0763 2022/11/03 02:17:04 - mmengine - INFO - Epoch(train) [1147][60/63] lr: 1.3070e-04 eta: 0:36:54 time: 0.4790 data_time: 0.0062 memory: 14901 loss: 0.8944 loss_prob: 0.4630 loss_thr: 0.3526 loss_db: 0.0788 2022/11/03 02:17:05 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:17:09 - mmengine - INFO - Epoch(train) [1148][5/63] lr: 1.2848e-04 eta: 0:36:54 time: 0.6365 data_time: 0.1891 memory: 14901 loss: 0.8446 loss_prob: 0.4279 loss_thr: 0.3439 loss_db: 0.0728 2022/11/03 02:17:11 - mmengine - INFO - Epoch(train) [1148][10/63] lr: 1.2848e-04 eta: 0:36:45 time: 0.6694 data_time: 0.1878 memory: 14901 loss: 0.7816 loss_prob: 0.3935 loss_thr: 0.3187 loss_db: 0.0693 2022/11/03 02:17:14 - mmengine - INFO - Epoch(train) [1148][15/63] lr: 1.2848e-04 eta: 0:36:45 time: 0.4908 data_time: 0.0074 memory: 14901 loss: 0.9062 loss_prob: 0.4675 loss_thr: 0.3541 loss_db: 0.0846 2022/11/03 02:17:16 - mmengine - INFO - Epoch(train) [1148][20/63] lr: 1.2848e-04 eta: 0:36:39 time: 0.4871 data_time: 0.0105 memory: 14901 loss: 0.9940 loss_prob: 0.5214 loss_thr: 0.3784 loss_db: 0.0941 2022/11/03 02:17:19 - mmengine - INFO - Epoch(train) [1148][25/63] lr: 1.2848e-04 eta: 0:36:39 time: 0.4910 data_time: 0.0251 memory: 14901 loss: 0.9353 loss_prob: 0.4931 loss_thr: 0.3575 loss_db: 0.0847 2022/11/03 02:17:21 - mmengine - INFO - Epoch(train) [1148][30/63] lr: 1.2848e-04 eta: 0:36:32 time: 0.4910 data_time: 0.0271 memory: 14901 loss: 0.9754 loss_prob: 0.5114 loss_thr: 0.3758 loss_db: 0.0883 2022/11/03 02:17:24 - mmengine - INFO - Epoch(train) [1148][35/63] lr: 1.2848e-04 eta: 0:36:32 time: 0.4913 data_time: 0.0139 memory: 14901 loss: 0.9537 loss_prob: 0.4944 loss_thr: 0.3711 loss_db: 0.0882 2022/11/03 02:17:26 - mmengine - INFO - Epoch(train) [1148][40/63] lr: 1.2848e-04 eta: 0:36:25 time: 0.5256 data_time: 0.0102 memory: 14901 loss: 0.8731 loss_prob: 0.4446 loss_thr: 0.3514 loss_db: 0.0771 2022/11/03 02:17:29 - mmengine - INFO - Epoch(train) [1148][45/63] lr: 1.2848e-04 eta: 0:36:25 time: 0.5377 data_time: 0.0076 memory: 14901 loss: 0.8705 loss_prob: 0.4439 loss_thr: 0.3484 loss_db: 0.0781 2022/11/03 02:17:32 - mmengine - INFO - Epoch(train) [1148][50/63] lr: 1.2848e-04 eta: 0:36:18 time: 0.5265 data_time: 0.0254 memory: 14901 loss: 0.8564 loss_prob: 0.4399 loss_thr: 0.3375 loss_db: 0.0790 2022/11/03 02:17:34 - mmengine - INFO - Epoch(train) [1148][55/63] lr: 1.2848e-04 eta: 0:36:18 time: 0.5280 data_time: 0.0277 memory: 14901 loss: 0.8490 loss_prob: 0.4404 loss_thr: 0.3312 loss_db: 0.0774 2022/11/03 02:17:37 - mmengine - INFO - Epoch(train) [1148][60/63] lr: 1.2848e-04 eta: 0:36:12 time: 0.5040 data_time: 0.0103 memory: 14901 loss: 0.8392 loss_prob: 0.4415 loss_thr: 0.3192 loss_db: 0.0784 2022/11/03 02:17:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:17:43 - mmengine - INFO - Epoch(train) [1149][5/63] lr: 1.2626e-04 eta: 0:36:12 time: 0.6732 data_time: 0.2077 memory: 14901 loss: 0.7560 loss_prob: 0.3853 loss_thr: 0.3037 loss_db: 0.0671 2022/11/03 02:17:45 - mmengine - INFO - Epoch(train) [1149][10/63] lr: 1.2626e-04 eta: 0:36:03 time: 0.7185 data_time: 0.2101 memory: 14901 loss: 0.7616 loss_prob: 0.3839 loss_thr: 0.3119 loss_db: 0.0657 2022/11/03 02:17:47 - mmengine - INFO - Epoch(train) [1149][15/63] lr: 1.2626e-04 eta: 0:36:03 time: 0.4653 data_time: 0.0097 memory: 14901 loss: 0.8197 loss_prob: 0.4175 loss_thr: 0.3293 loss_db: 0.0728 2022/11/03 02:17:50 - mmengine - INFO - Epoch(train) [1149][20/63] lr: 1.2626e-04 eta: 0:35:56 time: 0.4518 data_time: 0.0065 memory: 14901 loss: 0.8496 loss_prob: 0.4381 loss_thr: 0.3340 loss_db: 0.0775 2022/11/03 02:17:52 - mmengine - INFO - Epoch(train) [1149][25/63] lr: 1.2626e-04 eta: 0:35:56 time: 0.4959 data_time: 0.0311 memory: 14901 loss: 0.8782 loss_prob: 0.4544 loss_thr: 0.3444 loss_db: 0.0793 2022/11/03 02:17:54 - mmengine - INFO - Epoch(train) [1149][30/63] lr: 1.2626e-04 eta: 0:35:50 time: 0.4829 data_time: 0.0338 memory: 14901 loss: 0.8858 loss_prob: 0.4573 loss_thr: 0.3481 loss_db: 0.0805 2022/11/03 02:17:57 - mmengine - INFO - Epoch(train) [1149][35/63] lr: 1.2626e-04 eta: 0:35:50 time: 0.4756 data_time: 0.0088 memory: 14901 loss: 0.8340 loss_prob: 0.4260 loss_thr: 0.3329 loss_db: 0.0751 2022/11/03 02:17:59 - mmengine - INFO - Epoch(train) [1149][40/63] lr: 1.2626e-04 eta: 0:35:43 time: 0.4823 data_time: 0.0055 memory: 14901 loss: 0.8497 loss_prob: 0.4346 loss_thr: 0.3396 loss_db: 0.0755 2022/11/03 02:18:02 - mmengine - INFO - Epoch(train) [1149][45/63] lr: 1.2626e-04 eta: 0:35:43 time: 0.4627 data_time: 0.0053 memory: 14901 loss: 0.8957 loss_prob: 0.4690 loss_thr: 0.3453 loss_db: 0.0814 2022/11/03 02:18:04 - mmengine - INFO - Epoch(train) [1149][50/63] lr: 1.2626e-04 eta: 0:35:36 time: 0.4936 data_time: 0.0208 memory: 14901 loss: 0.8875 loss_prob: 0.4593 loss_thr: 0.3472 loss_db: 0.0811 2022/11/03 02:18:07 - mmengine - INFO - Epoch(train) [1149][55/63] lr: 1.2626e-04 eta: 0:35:36 time: 0.5043 data_time: 0.0226 memory: 14901 loss: 0.8667 loss_prob: 0.4435 loss_thr: 0.3453 loss_db: 0.0780 2022/11/03 02:18:09 - mmengine - INFO - Epoch(train) [1149][60/63] lr: 1.2626e-04 eta: 0:35:30 time: 0.5084 data_time: 0.0072 memory: 14901 loss: 0.8853 loss_prob: 0.4632 loss_thr: 0.3417 loss_db: 0.0804 2022/11/03 02:18:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:18:15 - mmengine - INFO - Epoch(train) [1150][5/63] lr: 1.2403e-04 eta: 0:35:30 time: 0.6661 data_time: 0.2038 memory: 14901 loss: 0.8584 loss_prob: 0.4359 loss_thr: 0.3473 loss_db: 0.0752 2022/11/03 02:18:17 - mmengine - INFO - Epoch(train) [1150][10/63] lr: 1.2403e-04 eta: 0:35:21 time: 0.6855 data_time: 0.2040 memory: 14901 loss: 0.8748 loss_prob: 0.4440 loss_thr: 0.3548 loss_db: 0.0760 2022/11/03 02:18:19 - mmengine - INFO - Epoch(train) [1150][15/63] lr: 1.2403e-04 eta: 0:35:21 time: 0.4427 data_time: 0.0051 memory: 14901 loss: 0.8831 loss_prob: 0.4526 loss_thr: 0.3514 loss_db: 0.0791 2022/11/03 02:18:22 - mmengine - INFO - Epoch(train) [1150][20/63] lr: 1.2403e-04 eta: 0:35:14 time: 0.4354 data_time: 0.0049 memory: 14901 loss: 0.8396 loss_prob: 0.4327 loss_thr: 0.3295 loss_db: 0.0774 2022/11/03 02:18:24 - mmengine - INFO - Epoch(train) [1150][25/63] lr: 1.2403e-04 eta: 0:35:14 time: 0.4842 data_time: 0.0293 memory: 14901 loss: 0.9046 loss_prob: 0.4770 loss_thr: 0.3454 loss_db: 0.0822 2022/11/03 02:18:27 - mmengine - INFO - Epoch(train) [1150][30/63] lr: 1.2403e-04 eta: 0:35:07 time: 0.5248 data_time: 0.0467 memory: 14901 loss: 0.8628 loss_prob: 0.4475 loss_thr: 0.3386 loss_db: 0.0767 2022/11/03 02:18:29 - mmengine - INFO - Epoch(train) [1150][35/63] lr: 1.2403e-04 eta: 0:35:07 time: 0.4777 data_time: 0.0222 memory: 14901 loss: 0.8497 loss_prob: 0.4293 loss_thr: 0.3441 loss_db: 0.0763 2022/11/03 02:18:32 - mmengine - INFO - Epoch(train) [1150][40/63] lr: 1.2403e-04 eta: 0:35:01 time: 0.4620 data_time: 0.0050 memory: 14901 loss: 0.8799 loss_prob: 0.4520 loss_thr: 0.3483 loss_db: 0.0796 2022/11/03 02:18:34 - mmengine - INFO - Epoch(train) [1150][45/63] lr: 1.2403e-04 eta: 0:35:01 time: 0.4863 data_time: 0.0070 memory: 14901 loss: 0.8063 loss_prob: 0.4108 loss_thr: 0.3235 loss_db: 0.0720 2022/11/03 02:18:36 - mmengine - INFO - Epoch(train) [1150][50/63] lr: 1.2403e-04 eta: 0:34:54 time: 0.4934 data_time: 0.0189 memory: 14901 loss: 0.8071 loss_prob: 0.4134 loss_thr: 0.3213 loss_db: 0.0724 2022/11/03 02:18:39 - mmengine - INFO - Epoch(train) [1150][55/63] lr: 1.2403e-04 eta: 0:34:54 time: 0.5002 data_time: 0.0268 memory: 14901 loss: 0.8029 loss_prob: 0.4120 loss_thr: 0.3192 loss_db: 0.0717 2022/11/03 02:18:41 - mmengine - INFO - Epoch(train) [1150][60/63] lr: 1.2403e-04 eta: 0:34:47 time: 0.4888 data_time: 0.0172 memory: 14901 loss: 0.7741 loss_prob: 0.3793 loss_thr: 0.3282 loss_db: 0.0666 2022/11/03 02:18:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:18:47 - mmengine - INFO - Epoch(train) [1151][5/63] lr: 1.2180e-04 eta: 0:34:47 time: 0.6742 data_time: 0.2011 memory: 14901 loss: 0.8199 loss_prob: 0.4109 loss_thr: 0.3367 loss_db: 0.0723 2022/11/03 02:18:50 - mmengine - INFO - Epoch(train) [1151][10/63] lr: 1.2180e-04 eta: 0:34:39 time: 0.7107 data_time: 0.2013 memory: 14901 loss: 0.8822 loss_prob: 0.4561 loss_thr: 0.3453 loss_db: 0.0809 2022/11/03 02:18:52 - mmengine - INFO - Epoch(train) [1151][15/63] lr: 1.2180e-04 eta: 0:34:39 time: 0.4831 data_time: 0.0084 memory: 14901 loss: 0.8650 loss_prob: 0.4488 loss_thr: 0.3363 loss_db: 0.0799 2022/11/03 02:18:54 - mmengine - INFO - Epoch(train) [1151][20/63] lr: 1.2180e-04 eta: 0:34:32 time: 0.4621 data_time: 0.0091 memory: 14901 loss: 0.8030 loss_prob: 0.4173 loss_thr: 0.3133 loss_db: 0.0723 2022/11/03 02:18:57 - mmengine - INFO - Epoch(train) [1151][25/63] lr: 1.2180e-04 eta: 0:34:32 time: 0.4730 data_time: 0.0220 memory: 14901 loss: 0.7557 loss_prob: 0.3888 loss_thr: 0.2996 loss_db: 0.0673 2022/11/03 02:18:59 - mmengine - INFO - Epoch(train) [1151][30/63] lr: 1.2180e-04 eta: 0:34:25 time: 0.4903 data_time: 0.0304 memory: 14901 loss: 0.7495 loss_prob: 0.3832 loss_thr: 0.3005 loss_db: 0.0657 2022/11/03 02:19:01 - mmengine - INFO - Epoch(train) [1151][35/63] lr: 1.2180e-04 eta: 0:34:25 time: 0.4720 data_time: 0.0167 memory: 14901 loss: 0.8702 loss_prob: 0.4565 loss_thr: 0.3355 loss_db: 0.0781 2022/11/03 02:19:04 - mmengine - INFO - Epoch(train) [1151][40/63] lr: 1.2180e-04 eta: 0:34:19 time: 0.4451 data_time: 0.0073 memory: 14901 loss: 0.9849 loss_prob: 0.5182 loss_thr: 0.3774 loss_db: 0.0894 2022/11/03 02:19:06 - mmengine - INFO - Epoch(train) [1151][45/63] lr: 1.2180e-04 eta: 0:34:19 time: 0.4818 data_time: 0.0065 memory: 14901 loss: 0.8543 loss_prob: 0.4435 loss_thr: 0.3342 loss_db: 0.0766 2022/11/03 02:19:09 - mmengine - INFO - Epoch(train) [1151][50/63] lr: 1.2180e-04 eta: 0:34:12 time: 0.5178 data_time: 0.0130 memory: 14901 loss: 0.7829 loss_prob: 0.4014 loss_thr: 0.3106 loss_db: 0.0709 2022/11/03 02:19:11 - mmengine - INFO - Epoch(train) [1151][55/63] lr: 1.2180e-04 eta: 0:34:12 time: 0.5016 data_time: 0.0202 memory: 14901 loss: 0.8058 loss_prob: 0.4098 loss_thr: 0.3238 loss_db: 0.0721 2022/11/03 02:19:14 - mmengine - INFO - Epoch(train) [1151][60/63] lr: 1.2180e-04 eta: 0:34:05 time: 0.4873 data_time: 0.0156 memory: 14901 loss: 0.7885 loss_prob: 0.4040 loss_thr: 0.3145 loss_db: 0.0700 2022/11/03 02:19:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:19:20 - mmengine - INFO - Epoch(train) [1152][5/63] lr: 1.1956e-04 eta: 0:34:05 time: 0.7455 data_time: 0.2554 memory: 14901 loss: 0.9062 loss_prob: 0.4820 loss_thr: 0.3415 loss_db: 0.0827 2022/11/03 02:19:23 - mmengine - INFO - Epoch(train) [1152][10/63] lr: 1.1956e-04 eta: 0:33:57 time: 0.7571 data_time: 0.2540 memory: 14901 loss: 0.9259 loss_prob: 0.4956 loss_thr: 0.3412 loss_db: 0.0891 2022/11/03 02:19:25 - mmengine - INFO - Epoch(train) [1152][15/63] lr: 1.1956e-04 eta: 0:33:57 time: 0.4935 data_time: 0.0070 memory: 14901 loss: 0.9241 loss_prob: 0.4892 loss_thr: 0.3468 loss_db: 0.0881 2022/11/03 02:19:27 - mmengine - INFO - Epoch(train) [1152][20/63] lr: 1.1956e-04 eta: 0:33:50 time: 0.4776 data_time: 0.0066 memory: 14901 loss: 0.8709 loss_prob: 0.4548 loss_thr: 0.3383 loss_db: 0.0778 2022/11/03 02:19:30 - mmengine - INFO - Epoch(train) [1152][25/63] lr: 1.1956e-04 eta: 0:33:50 time: 0.4801 data_time: 0.0273 memory: 14901 loss: 0.8343 loss_prob: 0.4311 loss_thr: 0.3301 loss_db: 0.0731 2022/11/03 02:19:32 - mmengine - INFO - Epoch(train) [1152][30/63] lr: 1.1956e-04 eta: 0:33:43 time: 0.5013 data_time: 0.0349 memory: 14901 loss: 0.8509 loss_prob: 0.4428 loss_thr: 0.3323 loss_db: 0.0757 2022/11/03 02:19:35 - mmengine - INFO - Epoch(train) [1152][35/63] lr: 1.1956e-04 eta: 0:33:43 time: 0.4914 data_time: 0.0142 memory: 14901 loss: 0.8526 loss_prob: 0.4434 loss_thr: 0.3328 loss_db: 0.0764 2022/11/03 02:19:37 - mmengine - INFO - Epoch(train) [1152][40/63] lr: 1.1956e-04 eta: 0:33:36 time: 0.4748 data_time: 0.0052 memory: 14901 loss: 0.8253 loss_prob: 0.4230 loss_thr: 0.3277 loss_db: 0.0745 2022/11/03 02:19:39 - mmengine - INFO - Epoch(train) [1152][45/63] lr: 1.1956e-04 eta: 0:33:36 time: 0.4596 data_time: 0.0079 memory: 14901 loss: 0.8770 loss_prob: 0.4429 loss_thr: 0.3557 loss_db: 0.0784 2022/11/03 02:19:42 - mmengine - INFO - Epoch(train) [1152][50/63] lr: 1.1956e-04 eta: 0:33:30 time: 0.4852 data_time: 0.0251 memory: 14901 loss: 0.8951 loss_prob: 0.4517 loss_thr: 0.3638 loss_db: 0.0796 2022/11/03 02:19:44 - mmengine - INFO - Epoch(train) [1152][55/63] lr: 1.1956e-04 eta: 0:33:30 time: 0.4958 data_time: 0.0269 memory: 14901 loss: 0.8765 loss_prob: 0.4449 loss_thr: 0.3535 loss_db: 0.0781 2022/11/03 02:19:47 - mmengine - INFO - Epoch(train) [1152][60/63] lr: 1.1956e-04 eta: 0:33:23 time: 0.4827 data_time: 0.0100 memory: 14901 loss: 0.8924 loss_prob: 0.4595 loss_thr: 0.3531 loss_db: 0.0799 2022/11/03 02:19:48 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:19:53 - mmengine - INFO - Epoch(train) [1153][5/63] lr: 1.1732e-04 eta: 0:33:23 time: 0.7674 data_time: 0.2305 memory: 14901 loss: 0.8605 loss_prob: 0.4430 loss_thr: 0.3390 loss_db: 0.0786 2022/11/03 02:19:56 - mmengine - INFO - Epoch(train) [1153][10/63] lr: 1.1732e-04 eta: 0:33:14 time: 0.7786 data_time: 0.2285 memory: 14901 loss: 0.7957 loss_prob: 0.4043 loss_thr: 0.3189 loss_db: 0.0725 2022/11/03 02:19:58 - mmengine - INFO - Epoch(train) [1153][15/63] lr: 1.1732e-04 eta: 0:33:14 time: 0.4887 data_time: 0.0058 memory: 14901 loss: 0.8208 loss_prob: 0.4188 loss_thr: 0.3279 loss_db: 0.0741 2022/11/03 02:20:01 - mmengine - INFO - Epoch(train) [1153][20/63] lr: 1.1732e-04 eta: 0:33:08 time: 0.4660 data_time: 0.0055 memory: 14901 loss: 0.8324 loss_prob: 0.4269 loss_thr: 0.3303 loss_db: 0.0752 2022/11/03 02:20:03 - mmengine - INFO - Epoch(train) [1153][25/63] lr: 1.1732e-04 eta: 0:33:08 time: 0.4798 data_time: 0.0162 memory: 14901 loss: 0.8454 loss_prob: 0.4407 loss_thr: 0.3260 loss_db: 0.0787 2022/11/03 02:20:06 - mmengine - INFO - Epoch(train) [1153][30/63] lr: 1.1732e-04 eta: 0:33:01 time: 0.5199 data_time: 0.0409 memory: 14901 loss: 0.8598 loss_prob: 0.4503 loss_thr: 0.3296 loss_db: 0.0798 2022/11/03 02:20:08 - mmengine - INFO - Epoch(train) [1153][35/63] lr: 1.1732e-04 eta: 0:33:01 time: 0.5115 data_time: 0.0297 memory: 14901 loss: 0.8081 loss_prob: 0.4169 loss_thr: 0.3176 loss_db: 0.0736 2022/11/03 02:20:11 - mmengine - INFO - Epoch(train) [1153][40/63] lr: 1.1732e-04 eta: 0:32:54 time: 0.4740 data_time: 0.0049 memory: 14901 loss: 0.7752 loss_prob: 0.3896 loss_thr: 0.3178 loss_db: 0.0678 2022/11/03 02:20:13 - mmengine - INFO - Epoch(train) [1153][45/63] lr: 1.1732e-04 eta: 0:32:54 time: 0.4740 data_time: 0.0049 memory: 14901 loss: 0.7756 loss_prob: 0.3858 loss_thr: 0.3231 loss_db: 0.0667 2022/11/03 02:20:15 - mmengine - INFO - Epoch(train) [1153][50/63] lr: 1.1732e-04 eta: 0:32:48 time: 0.4801 data_time: 0.0078 memory: 14901 loss: 0.8818 loss_prob: 0.4569 loss_thr: 0.3464 loss_db: 0.0785 2022/11/03 02:20:18 - mmengine - INFO - Epoch(train) [1153][55/63] lr: 1.1732e-04 eta: 0:32:48 time: 0.5144 data_time: 0.0177 memory: 14901 loss: 0.9717 loss_prob: 0.5114 loss_thr: 0.3725 loss_db: 0.0878 2022/11/03 02:20:22 - mmengine - INFO - Epoch(train) [1153][60/63] lr: 1.1732e-04 eta: 0:32:41 time: 0.6335 data_time: 0.0152 memory: 14901 loss: 0.9085 loss_prob: 0.4716 loss_thr: 0.3555 loss_db: 0.0815 2022/11/03 02:20:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:20:32 - mmengine - INFO - Epoch(train) [1154][5/63] lr: 1.1507e-04 eta: 0:32:41 time: 1.1453 data_time: 0.2381 memory: 14901 loss: 0.7855 loss_prob: 0.3923 loss_thr: 0.3239 loss_db: 0.0694 2022/11/03 02:20:38 - mmengine - INFO - Epoch(train) [1154][10/63] lr: 1.1507e-04 eta: 0:32:33 time: 1.3306 data_time: 0.2454 memory: 14901 loss: 0.8140 loss_prob: 0.4096 loss_thr: 0.3311 loss_db: 0.0733 2022/11/03 02:20:45 - mmengine - INFO - Epoch(train) [1154][15/63] lr: 1.1507e-04 eta: 0:32:33 time: 1.3589 data_time: 0.0162 memory: 14901 loss: 0.8049 loss_prob: 0.4076 loss_thr: 0.3255 loss_db: 0.0717 2022/11/03 02:20:47 - mmengine - INFO - Epoch(train) [1154][20/63] lr: 1.1507e-04 eta: 0:32:26 time: 0.9476 data_time: 0.0109 memory: 14901 loss: 0.8127 loss_prob: 0.4136 loss_thr: 0.3287 loss_db: 0.0704 2022/11/03 02:20:50 - mmengine - INFO - Epoch(train) [1154][25/63] lr: 1.1507e-04 eta: 0:32:26 time: 0.4966 data_time: 0.0287 memory: 14901 loss: 0.8581 loss_prob: 0.4430 loss_thr: 0.3394 loss_db: 0.0757 2022/11/03 02:20:52 - mmengine - INFO - Epoch(train) [1154][30/63] lr: 1.1507e-04 eta: 0:32:19 time: 0.4894 data_time: 0.0279 memory: 14901 loss: 0.8400 loss_prob: 0.4276 loss_thr: 0.3354 loss_db: 0.0770 2022/11/03 02:20:55 - mmengine - INFO - Epoch(train) [1154][35/63] lr: 1.1507e-04 eta: 0:32:19 time: 0.4740 data_time: 0.0093 memory: 14901 loss: 0.8409 loss_prob: 0.4290 loss_thr: 0.3341 loss_db: 0.0778 2022/11/03 02:20:57 - mmengine - INFO - Epoch(train) [1154][40/63] lr: 1.1507e-04 eta: 0:32:13 time: 0.4754 data_time: 0.0088 memory: 14901 loss: 0.8553 loss_prob: 0.4419 loss_thr: 0.3364 loss_db: 0.0770 2022/11/03 02:20:59 - mmengine - INFO - Epoch(train) [1154][45/63] lr: 1.1507e-04 eta: 0:32:13 time: 0.4608 data_time: 0.0083 memory: 14901 loss: 0.8838 loss_prob: 0.4605 loss_thr: 0.3447 loss_db: 0.0787 2022/11/03 02:21:02 - mmengine - INFO - Epoch(train) [1154][50/63] lr: 1.1507e-04 eta: 0:32:06 time: 0.4790 data_time: 0.0201 memory: 14901 loss: 0.8571 loss_prob: 0.4418 loss_thr: 0.3386 loss_db: 0.0767 2022/11/03 02:21:04 - mmengine - INFO - Epoch(train) [1154][55/63] lr: 1.1507e-04 eta: 0:32:06 time: 0.4910 data_time: 0.0197 memory: 14901 loss: 0.8042 loss_prob: 0.4068 loss_thr: 0.3267 loss_db: 0.0708 2022/11/03 02:21:07 - mmengine - INFO - Epoch(train) [1154][60/63] lr: 1.1507e-04 eta: 0:31:59 time: 0.4705 data_time: 0.0073 memory: 14901 loss: 0.8125 loss_prob: 0.4117 loss_thr: 0.3295 loss_db: 0.0713 2022/11/03 02:21:08 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:21:13 - mmengine - INFO - Epoch(train) [1155][5/63] lr: 1.1282e-04 eta: 0:31:59 time: 0.7021 data_time: 0.2036 memory: 14901 loss: 0.8310 loss_prob: 0.4237 loss_thr: 0.3290 loss_db: 0.0784 2022/11/03 02:21:15 - mmengine - INFO - Epoch(train) [1155][10/63] lr: 1.1282e-04 eta: 0:31:51 time: 0.7516 data_time: 0.2086 memory: 14901 loss: 0.8671 loss_prob: 0.4470 loss_thr: 0.3392 loss_db: 0.0810 2022/11/03 02:21:18 - mmengine - INFO - Epoch(train) [1155][15/63] lr: 1.1282e-04 eta: 0:31:51 time: 0.5283 data_time: 0.0112 memory: 14901 loss: 0.8537 loss_prob: 0.4347 loss_thr: 0.3425 loss_db: 0.0765 2022/11/03 02:21:21 - mmengine - INFO - Epoch(train) [1155][20/63] lr: 1.1282e-04 eta: 0:31:44 time: 0.5688 data_time: 0.0112 memory: 14901 loss: 0.8715 loss_prob: 0.4453 loss_thr: 0.3491 loss_db: 0.0771 2022/11/03 02:21:23 - mmengine - INFO - Epoch(train) [1155][25/63] lr: 1.1282e-04 eta: 0:31:44 time: 0.5445 data_time: 0.0157 memory: 14901 loss: 0.9508 loss_prob: 0.4964 loss_thr: 0.3702 loss_db: 0.0842 2022/11/03 02:21:26 - mmengine - INFO - Epoch(train) [1155][30/63] lr: 1.1282e-04 eta: 0:31:37 time: 0.5071 data_time: 0.0331 memory: 14901 loss: 0.9005 loss_prob: 0.4689 loss_thr: 0.3515 loss_db: 0.0801 2022/11/03 02:21:28 - mmengine - INFO - Epoch(train) [1155][35/63] lr: 1.1282e-04 eta: 0:31:37 time: 0.5000 data_time: 0.0299 memory: 14901 loss: 0.8290 loss_prob: 0.4272 loss_thr: 0.3279 loss_db: 0.0739 2022/11/03 02:21:31 - mmengine - INFO - Epoch(train) [1155][40/63] lr: 1.1282e-04 eta: 0:31:31 time: 0.4838 data_time: 0.0108 memory: 14901 loss: 0.8512 loss_prob: 0.4425 loss_thr: 0.3328 loss_db: 0.0759 2022/11/03 02:21:34 - mmengine - INFO - Epoch(train) [1155][45/63] lr: 1.1282e-04 eta: 0:31:31 time: 0.5157 data_time: 0.0094 memory: 14901 loss: 0.8905 loss_prob: 0.4727 loss_thr: 0.3361 loss_db: 0.0817 2022/11/03 02:21:36 - mmengine - INFO - Epoch(train) [1155][50/63] lr: 1.1282e-04 eta: 0:31:24 time: 0.5378 data_time: 0.0157 memory: 14901 loss: 0.8852 loss_prob: 0.4609 loss_thr: 0.3434 loss_db: 0.0809 2022/11/03 02:21:39 - mmengine - INFO - Epoch(train) [1155][55/63] lr: 1.1282e-04 eta: 0:31:24 time: 0.5183 data_time: 0.0212 memory: 14901 loss: 0.8654 loss_prob: 0.4370 loss_thr: 0.3529 loss_db: 0.0756 2022/11/03 02:21:41 - mmengine - INFO - Epoch(train) [1155][60/63] lr: 1.1282e-04 eta: 0:31:17 time: 0.4995 data_time: 0.0126 memory: 14901 loss: 0.8522 loss_prob: 0.4462 loss_thr: 0.3316 loss_db: 0.0744 2022/11/03 02:21:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:21:48 - mmengine - INFO - Epoch(train) [1156][5/63] lr: 1.1056e-04 eta: 0:31:17 time: 0.7385 data_time: 0.1814 memory: 14901 loss: 0.9382 loss_prob: 0.4955 loss_thr: 0.3602 loss_db: 0.0825 2022/11/03 02:21:50 - mmengine - INFO - Epoch(train) [1156][10/63] lr: 1.1056e-04 eta: 0:31:09 time: 0.7590 data_time: 0.1846 memory: 14901 loss: 0.8656 loss_prob: 0.4530 loss_thr: 0.3357 loss_db: 0.0770 2022/11/03 02:21:53 - mmengine - INFO - Epoch(train) [1156][15/63] lr: 1.1056e-04 eta: 0:31:09 time: 0.5201 data_time: 0.0083 memory: 14901 loss: 0.7900 loss_prob: 0.4036 loss_thr: 0.3143 loss_db: 0.0720 2022/11/03 02:21:56 - mmengine - INFO - Epoch(train) [1156][20/63] lr: 1.1056e-04 eta: 0:31:02 time: 0.5511 data_time: 0.0124 memory: 14901 loss: 0.8362 loss_prob: 0.4251 loss_thr: 0.3357 loss_db: 0.0754 2022/11/03 02:21:58 - mmengine - INFO - Epoch(train) [1156][25/63] lr: 1.1056e-04 eta: 0:31:02 time: 0.5217 data_time: 0.0155 memory: 14901 loss: 0.8375 loss_prob: 0.4254 loss_thr: 0.3382 loss_db: 0.0738 2022/11/03 02:22:01 - mmengine - INFO - Epoch(train) [1156][30/63] lr: 1.1056e-04 eta: 0:30:55 time: 0.4833 data_time: 0.0235 memory: 14901 loss: 0.8427 loss_prob: 0.4356 loss_thr: 0.3310 loss_db: 0.0762 2022/11/03 02:22:03 - mmengine - INFO - Epoch(train) [1156][35/63] lr: 1.1056e-04 eta: 0:30:55 time: 0.4699 data_time: 0.0234 memory: 14901 loss: 0.8898 loss_prob: 0.4592 loss_thr: 0.3494 loss_db: 0.0812 2022/11/03 02:22:05 - mmengine - INFO - Epoch(train) [1156][40/63] lr: 1.1056e-04 eta: 0:30:49 time: 0.4885 data_time: 0.0144 memory: 14901 loss: 0.9011 loss_prob: 0.4627 loss_thr: 0.3565 loss_db: 0.0819 2022/11/03 02:22:09 - mmengine - INFO - Epoch(train) [1156][45/63] lr: 1.1056e-04 eta: 0:30:49 time: 0.5773 data_time: 0.0129 memory: 14901 loss: 0.9055 loss_prob: 0.4720 loss_thr: 0.3525 loss_db: 0.0809 2022/11/03 02:22:11 - mmengine - INFO - Epoch(train) [1156][50/63] lr: 1.1056e-04 eta: 0:30:42 time: 0.5820 data_time: 0.0089 memory: 14901 loss: 0.8784 loss_prob: 0.4649 loss_thr: 0.3354 loss_db: 0.0781 2022/11/03 02:22:14 - mmengine - INFO - Epoch(train) [1156][55/63] lr: 1.1056e-04 eta: 0:30:42 time: 0.5680 data_time: 0.0185 memory: 14901 loss: 0.8442 loss_prob: 0.4432 loss_thr: 0.3242 loss_db: 0.0769 2022/11/03 02:22:17 - mmengine - INFO - Epoch(train) [1156][60/63] lr: 1.1056e-04 eta: 0:30:35 time: 0.5339 data_time: 0.0187 memory: 14901 loss: 0.7881 loss_prob: 0.4011 loss_thr: 0.3172 loss_db: 0.0698 2022/11/03 02:22:18 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:22:22 - mmengine - INFO - Epoch(train) [1157][5/63] lr: 1.0830e-04 eta: 0:30:35 time: 0.6812 data_time: 0.1853 memory: 14901 loss: 0.8109 loss_prob: 0.4115 loss_thr: 0.3282 loss_db: 0.0712 2022/11/03 02:22:25 - mmengine - INFO - Epoch(train) [1157][10/63] lr: 1.0830e-04 eta: 0:30:27 time: 0.7376 data_time: 0.1869 memory: 14901 loss: 0.8339 loss_prob: 0.4272 loss_thr: 0.3303 loss_db: 0.0764 2022/11/03 02:22:27 - mmengine - INFO - Epoch(train) [1157][15/63] lr: 1.0830e-04 eta: 0:30:27 time: 0.4981 data_time: 0.0063 memory: 14901 loss: 0.8315 loss_prob: 0.4196 loss_thr: 0.3368 loss_db: 0.0751 2022/11/03 02:22:30 - mmengine - INFO - Epoch(train) [1157][20/63] lr: 1.0830e-04 eta: 0:30:20 time: 0.4725 data_time: 0.0081 memory: 14901 loss: 0.8359 loss_prob: 0.4309 loss_thr: 0.3283 loss_db: 0.0766 2022/11/03 02:22:33 - mmengine - INFO - Epoch(train) [1157][25/63] lr: 1.0830e-04 eta: 0:30:20 time: 0.5335 data_time: 0.0323 memory: 14901 loss: 0.8865 loss_prob: 0.4708 loss_thr: 0.3325 loss_db: 0.0832 2022/11/03 02:22:36 - mmengine - INFO - Epoch(train) [1157][30/63] lr: 1.0830e-04 eta: 0:30:13 time: 0.5749 data_time: 0.0337 memory: 14901 loss: 0.8667 loss_prob: 0.4481 loss_thr: 0.3403 loss_db: 0.0783 2022/11/03 02:22:38 - mmengine - INFO - Epoch(train) [1157][35/63] lr: 1.0830e-04 eta: 0:30:13 time: 0.5410 data_time: 0.0102 memory: 14901 loss: 0.8909 loss_prob: 0.4552 loss_thr: 0.3567 loss_db: 0.0790 2022/11/03 02:22:41 - mmengine - INFO - Epoch(train) [1157][40/63] lr: 1.0830e-04 eta: 0:30:07 time: 0.5059 data_time: 0.0068 memory: 14901 loss: 0.9107 loss_prob: 0.4719 loss_thr: 0.3563 loss_db: 0.0826 2022/11/03 02:22:43 - mmengine - INFO - Epoch(train) [1157][45/63] lr: 1.0830e-04 eta: 0:30:07 time: 0.4917 data_time: 0.0084 memory: 14901 loss: 0.8222 loss_prob: 0.4248 loss_thr: 0.3222 loss_db: 0.0751 2022/11/03 02:22:46 - mmengine - INFO - Epoch(train) [1157][50/63] lr: 1.0830e-04 eta: 0:30:00 time: 0.4984 data_time: 0.0214 memory: 14901 loss: 0.8253 loss_prob: 0.4227 loss_thr: 0.3283 loss_db: 0.0744 2022/11/03 02:22:48 - mmengine - INFO - Epoch(train) [1157][55/63] lr: 1.0830e-04 eta: 0:30:00 time: 0.5018 data_time: 0.0234 memory: 14901 loss: 0.8863 loss_prob: 0.4480 loss_thr: 0.3594 loss_db: 0.0789 2022/11/03 02:22:50 - mmengine - INFO - Epoch(train) [1157][60/63] lr: 1.0830e-04 eta: 0:29:53 time: 0.4741 data_time: 0.0107 memory: 14901 loss: 0.9317 loss_prob: 0.4805 loss_thr: 0.3661 loss_db: 0.0851 2022/11/03 02:22:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:22:56 - mmengine - INFO - Epoch(train) [1158][5/63] lr: 1.0603e-04 eta: 0:29:53 time: 0.6825 data_time: 0.2238 memory: 14901 loss: 0.8482 loss_prob: 0.4392 loss_thr: 0.3325 loss_db: 0.0765 2022/11/03 02:22:59 - mmengine - INFO - Epoch(train) [1158][10/63] lr: 1.0603e-04 eta: 0:29:45 time: 0.7030 data_time: 0.2224 memory: 14901 loss: 0.8456 loss_prob: 0.4255 loss_thr: 0.3460 loss_db: 0.0741 2022/11/03 02:23:01 - mmengine - INFO - Epoch(train) [1158][15/63] lr: 1.0603e-04 eta: 0:29:45 time: 0.4554 data_time: 0.0065 memory: 14901 loss: 0.8855 loss_prob: 0.4468 loss_thr: 0.3598 loss_db: 0.0790 2022/11/03 02:23:03 - mmengine - INFO - Epoch(train) [1158][20/63] lr: 1.0603e-04 eta: 0:29:38 time: 0.4736 data_time: 0.0062 memory: 14901 loss: 0.9469 loss_prob: 0.5001 loss_thr: 0.3599 loss_db: 0.0869 2022/11/03 02:23:07 - mmengine - INFO - Epoch(train) [1158][25/63] lr: 1.0603e-04 eta: 0:29:38 time: 0.5568 data_time: 0.0379 memory: 14901 loss: 0.9299 loss_prob: 0.4900 loss_thr: 0.3550 loss_db: 0.0849 2022/11/03 02:23:10 - mmengine - INFO - Epoch(train) [1158][30/63] lr: 1.0603e-04 eta: 0:29:31 time: 0.6062 data_time: 0.0387 memory: 14901 loss: 0.8760 loss_prob: 0.4513 loss_thr: 0.3460 loss_db: 0.0786 2022/11/03 02:23:12 - mmengine - INFO - Epoch(train) [1158][35/63] lr: 1.0603e-04 eta: 0:29:31 time: 0.5454 data_time: 0.0087 memory: 14901 loss: 0.8491 loss_prob: 0.4404 loss_thr: 0.3324 loss_db: 0.0763 2022/11/03 02:23:14 - mmengine - INFO - Epoch(train) [1158][40/63] lr: 1.0603e-04 eta: 0:29:25 time: 0.4922 data_time: 0.0087 memory: 14901 loss: 0.8445 loss_prob: 0.4353 loss_thr: 0.3326 loss_db: 0.0766 2022/11/03 02:23:17 - mmengine - INFO - Epoch(train) [1158][45/63] lr: 1.0603e-04 eta: 0:29:25 time: 0.4816 data_time: 0.0059 memory: 14901 loss: 0.8650 loss_prob: 0.4443 loss_thr: 0.3424 loss_db: 0.0784 2022/11/03 02:23:19 - mmengine - INFO - Epoch(train) [1158][50/63] lr: 1.0603e-04 eta: 0:29:18 time: 0.4884 data_time: 0.0228 memory: 14901 loss: 0.8013 loss_prob: 0.4052 loss_thr: 0.3243 loss_db: 0.0718 2022/11/03 02:23:22 - mmengine - INFO - Epoch(train) [1158][55/63] lr: 1.0603e-04 eta: 0:29:18 time: 0.4950 data_time: 0.0226 memory: 14901 loss: 0.7612 loss_prob: 0.3819 loss_thr: 0.3105 loss_db: 0.0688 2022/11/03 02:23:24 - mmengine - INFO - Epoch(train) [1158][60/63] lr: 1.0603e-04 eta: 0:29:11 time: 0.4708 data_time: 0.0064 memory: 14901 loss: 0.8200 loss_prob: 0.4115 loss_thr: 0.3349 loss_db: 0.0735 2022/11/03 02:23:25 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:23:30 - mmengine - INFO - Epoch(train) [1159][5/63] lr: 1.0376e-04 eta: 0:29:11 time: 0.6847 data_time: 0.1936 memory: 14901 loss: 0.8428 loss_prob: 0.4284 loss_thr: 0.3388 loss_db: 0.0756 2022/11/03 02:23:32 - mmengine - INFO - Epoch(train) [1159][10/63] lr: 1.0376e-04 eta: 0:29:03 time: 0.7054 data_time: 0.1938 memory: 14901 loss: 0.8190 loss_prob: 0.4156 loss_thr: 0.3298 loss_db: 0.0735 2022/11/03 02:23:35 - mmengine - INFO - Epoch(train) [1159][15/63] lr: 1.0376e-04 eta: 0:29:03 time: 0.4683 data_time: 0.0096 memory: 14901 loss: 0.8705 loss_prob: 0.4447 loss_thr: 0.3478 loss_db: 0.0780 2022/11/03 02:23:37 - mmengine - INFO - Epoch(train) [1159][20/63] lr: 1.0376e-04 eta: 0:28:56 time: 0.4637 data_time: 0.0081 memory: 14901 loss: 0.8628 loss_prob: 0.4352 loss_thr: 0.3498 loss_db: 0.0778 2022/11/03 02:23:40 - mmengine - INFO - Epoch(train) [1159][25/63] lr: 1.0376e-04 eta: 0:28:56 time: 0.4898 data_time: 0.0192 memory: 14901 loss: 0.8218 loss_prob: 0.4118 loss_thr: 0.3349 loss_db: 0.0751 2022/11/03 02:23:42 - mmengine - INFO - Epoch(train) [1159][30/63] lr: 1.0376e-04 eta: 0:28:49 time: 0.5028 data_time: 0.0309 memory: 14901 loss: 0.7658 loss_prob: 0.3902 loss_thr: 0.3047 loss_db: 0.0709 2022/11/03 02:23:44 - mmengine - INFO - Epoch(train) [1159][35/63] lr: 1.0376e-04 eta: 0:28:49 time: 0.4908 data_time: 0.0195 memory: 14901 loss: 0.7572 loss_prob: 0.3802 loss_thr: 0.3102 loss_db: 0.0668 2022/11/03 02:23:47 - mmengine - INFO - Epoch(train) [1159][40/63] lr: 1.0376e-04 eta: 0:28:43 time: 0.4910 data_time: 0.0083 memory: 14901 loss: 0.8276 loss_prob: 0.4166 loss_thr: 0.3374 loss_db: 0.0736 2022/11/03 02:23:49 - mmengine - INFO - Epoch(train) [1159][45/63] lr: 1.0376e-04 eta: 0:28:43 time: 0.4979 data_time: 0.0077 memory: 14901 loss: 0.8450 loss_prob: 0.4295 loss_thr: 0.3391 loss_db: 0.0763 2022/11/03 02:23:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:23:52 - mmengine - INFO - Epoch(train) [1159][50/63] lr: 1.0376e-04 eta: 0:28:36 time: 0.4878 data_time: 0.0148 memory: 14901 loss: 0.8282 loss_prob: 0.4256 loss_thr: 0.3287 loss_db: 0.0740 2022/11/03 02:23:54 - mmengine - INFO - Epoch(train) [1159][55/63] lr: 1.0376e-04 eta: 0:28:36 time: 0.4703 data_time: 0.0240 memory: 14901 loss: 0.8974 loss_prob: 0.4708 loss_thr: 0.3455 loss_db: 0.0811 2022/11/03 02:23:57 - mmengine - INFO - Epoch(train) [1159][60/63] lr: 1.0376e-04 eta: 0:28:29 time: 0.4825 data_time: 0.0174 memory: 14901 loss: 0.9261 loss_prob: 0.4839 loss_thr: 0.3577 loss_db: 0.0845 2022/11/03 02:23:58 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:24:02 - mmengine - INFO - Epoch(train) [1160][5/63] lr: 1.0148e-04 eta: 0:28:29 time: 0.6734 data_time: 0.2089 memory: 14901 loss: 0.7659 loss_prob: 0.3843 loss_thr: 0.3127 loss_db: 0.0689 2022/11/03 02:24:05 - mmengine - INFO - Epoch(train) [1160][10/63] lr: 1.0148e-04 eta: 0:28:21 time: 0.6762 data_time: 0.2140 memory: 14901 loss: 0.8774 loss_prob: 0.4499 loss_thr: 0.3503 loss_db: 0.0773 2022/11/03 02:24:07 - mmengine - INFO - Epoch(train) [1160][15/63] lr: 1.0148e-04 eta: 0:28:21 time: 0.4706 data_time: 0.0135 memory: 14901 loss: 0.8834 loss_prob: 0.4578 loss_thr: 0.3474 loss_db: 0.0782 2022/11/03 02:24:10 - mmengine - INFO - Epoch(train) [1160][20/63] lr: 1.0148e-04 eta: 0:28:14 time: 0.5043 data_time: 0.0084 memory: 14901 loss: 0.8299 loss_prob: 0.4223 loss_thr: 0.3333 loss_db: 0.0743 2022/11/03 02:24:12 - mmengine - INFO - Epoch(train) [1160][25/63] lr: 1.0148e-04 eta: 0:28:14 time: 0.5139 data_time: 0.0228 memory: 14901 loss: 0.8224 loss_prob: 0.4193 loss_thr: 0.3309 loss_db: 0.0722 2022/11/03 02:24:15 - mmengine - INFO - Epoch(train) [1160][30/63] lr: 1.0148e-04 eta: 0:28:07 time: 0.5058 data_time: 0.0296 memory: 14901 loss: 0.8456 loss_prob: 0.4362 loss_thr: 0.3348 loss_db: 0.0746 2022/11/03 02:24:17 - mmengine - INFO - Epoch(train) [1160][35/63] lr: 1.0148e-04 eta: 0:28:07 time: 0.4768 data_time: 0.0159 memory: 14901 loss: 0.9172 loss_prob: 0.4754 loss_thr: 0.3604 loss_db: 0.0813 2022/11/03 02:24:19 - mmengine - INFO - Epoch(train) [1160][40/63] lr: 1.0148e-04 eta: 0:28:01 time: 0.4561 data_time: 0.0084 memory: 14901 loss: 0.9011 loss_prob: 0.4590 loss_thr: 0.3620 loss_db: 0.0801 2022/11/03 02:24:22 - mmengine - INFO - Epoch(train) [1160][45/63] lr: 1.0148e-04 eta: 0:28:01 time: 0.4809 data_time: 0.0068 memory: 14901 loss: 0.8183 loss_prob: 0.4146 loss_thr: 0.3295 loss_db: 0.0742 2022/11/03 02:24:24 - mmengine - INFO - Epoch(train) [1160][50/63] lr: 1.0148e-04 eta: 0:27:54 time: 0.5068 data_time: 0.0186 memory: 14901 loss: 0.7605 loss_prob: 0.3849 loss_thr: 0.3068 loss_db: 0.0688 2022/11/03 02:24:27 - mmengine - INFO - Epoch(train) [1160][55/63] lr: 1.0148e-04 eta: 0:27:54 time: 0.4981 data_time: 0.0229 memory: 14901 loss: 0.8095 loss_prob: 0.4066 loss_thr: 0.3330 loss_db: 0.0699 2022/11/03 02:24:29 - mmengine - INFO - Epoch(train) [1160][60/63] lr: 1.0148e-04 eta: 0:27:47 time: 0.4725 data_time: 0.0168 memory: 14901 loss: 0.8701 loss_prob: 0.4479 loss_thr: 0.3479 loss_db: 0.0743 2022/11/03 02:24:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:24:30 - mmengine - INFO - Saving checkpoint at 1160 epochs 2022/11/03 02:24:36 - mmengine - INFO - Epoch(val) [1160][5/500] eta: 0:27:47 time: 0.0411 data_time: 0.0043 memory: 14901 2022/11/03 02:24:36 - mmengine - INFO - Epoch(val) [1160][10/500] eta: 0:00:20 time: 0.0413 data_time: 0.0042 memory: 1008 2022/11/03 02:24:36 - mmengine - INFO - Epoch(val) [1160][15/500] eta: 0:00:20 time: 0.0369 data_time: 0.0021 memory: 1008 2022/11/03 02:24:36 - mmengine - INFO - Epoch(val) [1160][20/500] eta: 0:00:17 time: 0.0372 data_time: 0.0026 memory: 1008 2022/11/03 02:24:36 - mmengine - INFO - Epoch(val) [1160][25/500] eta: 0:00:17 time: 0.0347 data_time: 0.0022 memory: 1008 2022/11/03 02:24:37 - mmengine - INFO - Epoch(val) [1160][30/500] eta: 0:00:18 time: 0.0402 data_time: 0.0022 memory: 1008 2022/11/03 02:24:37 - mmengine - INFO - Epoch(val) [1160][35/500] eta: 0:00:18 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/03 02:24:37 - mmengine - INFO - Epoch(val) [1160][40/500] eta: 0:00:19 time: 0.0415 data_time: 0.0025 memory: 1008 2022/11/03 02:24:37 - mmengine - INFO - Epoch(val) [1160][45/500] eta: 0:00:19 time: 0.0429 data_time: 0.0023 memory: 1008 2022/11/03 02:24:37 - mmengine - INFO - Epoch(val) [1160][50/500] eta: 0:00:17 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/03 02:24:38 - mmengine - INFO - Epoch(val) [1160][55/500] eta: 0:00:17 time: 0.0407 data_time: 0.0022 memory: 1008 2022/11/03 02:24:38 - mmengine - INFO - Epoch(val) [1160][60/500] eta: 0:00:16 time: 0.0378 data_time: 0.0022 memory: 1008 2022/11/03 02:24:38 - mmengine - INFO - Epoch(val) [1160][65/500] eta: 0:00:16 time: 0.0373 data_time: 0.0022 memory: 1008 2022/11/03 02:24:38 - mmengine - INFO - Epoch(val) [1160][70/500] eta: 0:00:17 time: 0.0397 data_time: 0.0022 memory: 1008 2022/11/03 02:24:38 - mmengine - INFO - Epoch(val) [1160][75/500] eta: 0:00:17 time: 0.0370 data_time: 0.0021 memory: 1008 2022/11/03 02:24:38 - mmengine - INFO - Epoch(val) [1160][80/500] eta: 0:00:14 time: 0.0334 data_time: 0.0021 memory: 1008 2022/11/03 02:24:39 - mmengine - INFO - Epoch(val) [1160][85/500] eta: 0:00:14 time: 0.0364 data_time: 0.0029 memory: 1008 2022/11/03 02:24:39 - mmengine - INFO - Epoch(val) [1160][90/500] eta: 0:00:17 time: 0.0421 data_time: 0.0030 memory: 1008 2022/11/03 02:24:39 - mmengine - INFO - Epoch(val) [1160][95/500] eta: 0:00:17 time: 0.0413 data_time: 0.0022 memory: 1008 2022/11/03 02:24:39 - mmengine - INFO - Epoch(val) [1160][100/500] eta: 0:00:14 time: 0.0373 data_time: 0.0022 memory: 1008 2022/11/03 02:24:39 - mmengine - INFO - Epoch(val) [1160][105/500] eta: 0:00:14 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/03 02:24:40 - mmengine - INFO - Epoch(val) [1160][110/500] eta: 0:00:14 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/03 02:24:40 - mmengine - INFO - Epoch(val) [1160][115/500] eta: 0:00:14 time: 0.0375 data_time: 0.0024 memory: 1008 2022/11/03 02:24:40 - mmengine - INFO - Epoch(val) [1160][120/500] eta: 0:00:14 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/03 02:24:40 - mmengine - INFO - Epoch(val) [1160][125/500] eta: 0:00:14 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/03 02:24:40 - mmengine - INFO - Epoch(val) [1160][130/500] eta: 0:00:13 time: 0.0365 data_time: 0.0024 memory: 1008 2022/11/03 02:24:41 - mmengine - INFO - Epoch(val) [1160][135/500] eta: 0:00:13 time: 0.0360 data_time: 0.0024 memory: 1008 2022/11/03 02:24:41 - mmengine - INFO - Epoch(val) [1160][140/500] eta: 0:00:12 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/03 02:24:41 - mmengine - INFO - Epoch(val) [1160][145/500] eta: 0:00:12 time: 0.0421 data_time: 0.0023 memory: 1008 2022/11/03 02:24:41 - mmengine - INFO - Epoch(val) [1160][150/500] eta: 0:00:14 time: 0.0426 data_time: 0.0023 memory: 1008 2022/11/03 02:24:41 - mmengine - INFO - Epoch(val) [1160][155/500] eta: 0:00:14 time: 0.0425 data_time: 0.0025 memory: 1008 2022/11/03 02:24:42 - mmengine - INFO - Epoch(val) [1160][160/500] eta: 0:00:14 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/03 02:24:42 - mmengine - INFO - Epoch(val) [1160][165/500] eta: 0:00:14 time: 0.0404 data_time: 0.0028 memory: 1008 2022/11/03 02:24:42 - mmengine - INFO - Epoch(val) [1160][170/500] eta: 0:00:12 time: 0.0391 data_time: 0.0027 memory: 1008 2022/11/03 02:24:42 - mmengine - INFO - Epoch(val) [1160][175/500] eta: 0:00:12 time: 0.0352 data_time: 0.0024 memory: 1008 2022/11/03 02:24:42 - mmengine - INFO - Epoch(val) [1160][180/500] eta: 0:00:11 time: 0.0354 data_time: 0.0023 memory: 1008 2022/11/03 02:24:43 - mmengine - INFO - Epoch(val) [1160][185/500] eta: 0:00:11 time: 0.0389 data_time: 0.0023 memory: 1008 2022/11/03 02:24:43 - mmengine - INFO - Epoch(val) [1160][190/500] eta: 0:00:12 time: 0.0395 data_time: 0.0023 memory: 1008 2022/11/03 02:24:43 - mmengine - INFO - Epoch(val) [1160][195/500] eta: 0:00:12 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/03 02:24:43 - mmengine - INFO - Epoch(val) [1160][200/500] eta: 0:00:12 time: 0.0429 data_time: 0.0029 memory: 1008 2022/11/03 02:24:43 - mmengine - INFO - Epoch(val) [1160][205/500] eta: 0:00:12 time: 0.0441 data_time: 0.0028 memory: 1008 2022/11/03 02:24:44 - mmengine - INFO - Epoch(val) [1160][210/500] eta: 0:00:10 time: 0.0368 data_time: 0.0025 memory: 1008 2022/11/03 02:24:44 - mmengine - INFO - Epoch(val) [1160][215/500] eta: 0:00:10 time: 0.0353 data_time: 0.0023 memory: 1008 2022/11/03 02:24:44 - mmengine - INFO - Epoch(val) [1160][220/500] eta: 0:00:10 time: 0.0378 data_time: 0.0022 memory: 1008 2022/11/03 02:24:44 - mmengine - INFO - Epoch(val) [1160][225/500] eta: 0:00:10 time: 0.0397 data_time: 0.0021 memory: 1008 2022/11/03 02:24:44 - mmengine - INFO - Epoch(val) [1160][230/500] eta: 0:00:10 time: 0.0379 data_time: 0.0022 memory: 1008 2022/11/03 02:24:45 - mmengine - INFO - Epoch(val) [1160][235/500] eta: 0:00:10 time: 0.0372 data_time: 0.0025 memory: 1008 2022/11/03 02:24:45 - mmengine - INFO - Epoch(val) [1160][240/500] eta: 0:00:09 time: 0.0373 data_time: 0.0022 memory: 1008 2022/11/03 02:24:45 - mmengine - INFO - Epoch(val) [1160][245/500] eta: 0:00:09 time: 0.0372 data_time: 0.0022 memory: 1008 2022/11/03 02:24:45 - mmengine - INFO - Epoch(val) [1160][250/500] eta: 0:00:09 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/03 02:24:45 - mmengine - INFO - Epoch(val) [1160][255/500] eta: 0:00:09 time: 0.0365 data_time: 0.0024 memory: 1008 2022/11/03 02:24:45 - mmengine - INFO - Epoch(val) [1160][260/500] eta: 0:00:08 time: 0.0373 data_time: 0.0024 memory: 1008 2022/11/03 02:24:46 - mmengine - INFO - Epoch(val) [1160][265/500] eta: 0:00:08 time: 0.0402 data_time: 0.0024 memory: 1008 2022/11/03 02:24:46 - mmengine - INFO - Epoch(val) [1160][270/500] eta: 0:00:09 time: 0.0415 data_time: 0.0024 memory: 1008 2022/11/03 02:24:46 - mmengine - INFO - Epoch(val) [1160][275/500] eta: 0:00:09 time: 0.0389 data_time: 0.0025 memory: 1008 2022/11/03 02:24:46 - mmengine - INFO - Epoch(val) [1160][280/500] eta: 0:00:08 time: 0.0385 data_time: 0.0024 memory: 1008 2022/11/03 02:24:46 - mmengine - INFO - Epoch(val) [1160][285/500] eta: 0:00:08 time: 0.0400 data_time: 0.0026 memory: 1008 2022/11/03 02:24:47 - mmengine - INFO - Epoch(val) [1160][290/500] eta: 0:00:08 time: 0.0387 data_time: 0.0027 memory: 1008 2022/11/03 02:24:47 - mmengine - INFO - Epoch(val) [1160][295/500] eta: 0:00:08 time: 0.0372 data_time: 0.0023 memory: 1008 2022/11/03 02:24:47 - mmengine - INFO - Epoch(val) [1160][300/500] eta: 0:00:07 time: 0.0371 data_time: 0.0025 memory: 1008 2022/11/03 02:24:47 - mmengine - INFO - Epoch(val) [1160][305/500] eta: 0:00:07 time: 0.0370 data_time: 0.0025 memory: 1008 2022/11/03 02:24:47 - mmengine - INFO - Epoch(val) [1160][310/500] eta: 0:00:07 time: 0.0374 data_time: 0.0022 memory: 1008 2022/11/03 02:24:48 - mmengine - INFO - Epoch(val) [1160][315/500] eta: 0:00:07 time: 0.0419 data_time: 0.0027 memory: 1008 2022/11/03 02:24:48 - mmengine - INFO - Epoch(val) [1160][320/500] eta: 0:00:06 time: 0.0386 data_time: 0.0026 memory: 1008 2022/11/03 02:24:48 - mmengine - INFO - Epoch(val) [1160][325/500] eta: 0:00:06 time: 0.0475 data_time: 0.0022 memory: 1008 2022/11/03 02:24:48 - mmengine - INFO - Epoch(val) [1160][330/500] eta: 0:00:08 time: 0.0478 data_time: 0.0022 memory: 1008 2022/11/03 02:24:48 - mmengine - INFO - Epoch(val) [1160][335/500] eta: 0:00:08 time: 0.0339 data_time: 0.0022 memory: 1008 2022/11/03 02:24:49 - mmengine - INFO - Epoch(val) [1160][340/500] eta: 0:00:07 time: 0.0455 data_time: 0.0023 memory: 1008 2022/11/03 02:24:49 - mmengine - INFO - Epoch(val) [1160][345/500] eta: 0:00:07 time: 0.0475 data_time: 0.0023 memory: 1008 2022/11/03 02:24:49 - mmengine - INFO - Epoch(val) [1160][350/500] eta: 0:00:06 time: 0.0414 data_time: 0.0022 memory: 1008 2022/11/03 02:24:49 - mmengine - INFO - Epoch(val) [1160][355/500] eta: 0:00:06 time: 0.0388 data_time: 0.0021 memory: 1008 2022/11/03 02:24:50 - mmengine - INFO - Epoch(val) [1160][360/500] eta: 0:00:04 time: 0.0352 data_time: 0.0020 memory: 1008 2022/11/03 02:24:50 - mmengine - INFO - Epoch(val) [1160][365/500] eta: 0:00:04 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/03 02:24:50 - mmengine - INFO - Epoch(val) [1160][370/500] eta: 0:00:04 time: 0.0363 data_time: 0.0025 memory: 1008 2022/11/03 02:24:50 - mmengine - INFO - Epoch(val) [1160][375/500] eta: 0:00:04 time: 0.0369 data_time: 0.0027 memory: 1008 2022/11/03 02:24:50 - mmengine - INFO - Epoch(val) [1160][380/500] eta: 0:00:04 time: 0.0410 data_time: 0.0026 memory: 1008 2022/11/03 02:24:50 - mmengine - INFO - Epoch(val) [1160][385/500] eta: 0:00:04 time: 0.0425 data_time: 0.0026 memory: 1008 2022/11/03 02:24:51 - mmengine - INFO - Epoch(val) [1160][390/500] eta: 0:00:04 time: 0.0397 data_time: 0.0024 memory: 1008 2022/11/03 02:24:51 - mmengine - INFO - Epoch(val) [1160][395/500] eta: 0:00:04 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/03 02:24:51 - mmengine - INFO - Epoch(val) [1160][400/500] eta: 0:00:03 time: 0.0386 data_time: 0.0028 memory: 1008 2022/11/03 02:24:51 - mmengine - INFO - Epoch(val) [1160][405/500] eta: 0:00:03 time: 0.0429 data_time: 0.0037 memory: 1008 2022/11/03 02:24:52 - mmengine - INFO - Epoch(val) [1160][410/500] eta: 0:00:03 time: 0.0443 data_time: 0.0038 memory: 1008 2022/11/03 02:24:52 - mmengine - INFO - Epoch(val) [1160][415/500] eta: 0:00:03 time: 0.0393 data_time: 0.0029 memory: 1008 2022/11/03 02:24:52 - mmengine - INFO - Epoch(val) [1160][420/500] eta: 0:00:02 time: 0.0362 data_time: 0.0031 memory: 1008 2022/11/03 02:24:52 - mmengine - INFO - Epoch(val) [1160][425/500] eta: 0:00:02 time: 0.0391 data_time: 0.0033 memory: 1008 2022/11/03 02:24:52 - mmengine - INFO - Epoch(val) [1160][430/500] eta: 0:00:02 time: 0.0399 data_time: 0.0029 memory: 1008 2022/11/03 02:24:52 - mmengine - INFO - Epoch(val) [1160][435/500] eta: 0:00:02 time: 0.0365 data_time: 0.0026 memory: 1008 2022/11/03 02:24:53 - mmengine - INFO - Epoch(val) [1160][440/500] eta: 0:00:02 time: 0.0366 data_time: 0.0026 memory: 1008 2022/11/03 02:24:53 - mmengine - INFO - Epoch(val) [1160][445/500] eta: 0:00:02 time: 0.0376 data_time: 0.0024 memory: 1008 2022/11/03 02:24:53 - mmengine - INFO - Epoch(val) [1160][450/500] eta: 0:00:01 time: 0.0384 data_time: 0.0021 memory: 1008 2022/11/03 02:24:53 - mmengine - INFO - Epoch(val) [1160][455/500] eta: 0:00:01 time: 0.0376 data_time: 0.0022 memory: 1008 2022/11/03 02:24:53 - mmengine - INFO - Epoch(val) [1160][460/500] eta: 0:00:01 time: 0.0340 data_time: 0.0022 memory: 1008 2022/11/03 02:24:54 - mmengine - INFO - Epoch(val) [1160][465/500] eta: 0:00:01 time: 0.0336 data_time: 0.0021 memory: 1008 2022/11/03 02:24:54 - mmengine - INFO - Epoch(val) [1160][470/500] eta: 0:00:01 time: 0.0353 data_time: 0.0022 memory: 1008 2022/11/03 02:24:54 - mmengine - INFO - Epoch(val) [1160][475/500] eta: 0:00:01 time: 0.0335 data_time: 0.0020 memory: 1008 2022/11/03 02:24:54 - mmengine - INFO - Epoch(val) [1160][480/500] eta: 0:00:00 time: 0.0383 data_time: 0.0035 memory: 1008 2022/11/03 02:24:54 - mmengine - INFO - Epoch(val) [1160][485/500] eta: 0:00:00 time: 0.0394 data_time: 0.0036 memory: 1008 2022/11/03 02:24:54 - mmengine - INFO - Epoch(val) [1160][490/500] eta: 0:00:00 time: 0.0363 data_time: 0.0020 memory: 1008 2022/11/03 02:24:55 - mmengine - INFO - Epoch(val) [1160][495/500] eta: 0:00:00 time: 0.0384 data_time: 0.0020 memory: 1008 2022/11/03 02:24:55 - mmengine - INFO - Epoch(val) [1160][500/500] eta: 0:00:00 time: 0.0372 data_time: 0.0022 memory: 1008 2022/11/03 02:24:55 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8267, precision: 0.7679, hmean: 0.7962 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8267, precision: 0.8114, hmean: 0.8190 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8267, precision: 0.8319, hmean: 0.8293 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8233, precision: 0.8554, hmean: 0.8391 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8127, precision: 0.8796, hmean: 0.8448 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7395, precision: 0.9198, hmean: 0.8199 2022/11/03 02:24:55 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2335, precision: 0.9642, hmean: 0.3760 2022/11/03 02:24:55 - mmengine - INFO - Epoch(val) [1160][500/500] icdar/precision: 0.8796 icdar/recall: 0.8127 icdar/hmean: 0.8448 2022/11/03 02:25:00 - mmengine - INFO - Epoch(train) [1161][5/63] lr: 9.9199e-05 eta: 0:00:00 time: 0.6864 data_time: 0.2138 memory: 14901 loss: 0.9252 loss_prob: 0.4828 loss_thr: 0.3573 loss_db: 0.0851 2022/11/03 02:25:02 - mmengine - INFO - Epoch(train) [1161][10/63] lr: 9.9199e-05 eta: 0:27:39 time: 0.7248 data_time: 0.2129 memory: 14901 loss: 0.8741 loss_prob: 0.4524 loss_thr: 0.3395 loss_db: 0.0821 2022/11/03 02:25:05 - mmengine - INFO - Epoch(train) [1161][15/63] lr: 9.9199e-05 eta: 0:27:39 time: 0.4858 data_time: 0.0077 memory: 14901 loss: 0.8511 loss_prob: 0.4403 loss_thr: 0.3328 loss_db: 0.0779 2022/11/03 02:25:07 - mmengine - INFO - Epoch(train) [1161][20/63] lr: 9.9199e-05 eta: 0:27:32 time: 0.4720 data_time: 0.0080 memory: 14901 loss: 0.8543 loss_prob: 0.4374 loss_thr: 0.3401 loss_db: 0.0768 2022/11/03 02:25:09 - mmengine - INFO - Epoch(train) [1161][25/63] lr: 9.9199e-05 eta: 0:27:32 time: 0.4845 data_time: 0.0251 memory: 14901 loss: 0.8162 loss_prob: 0.4141 loss_thr: 0.3299 loss_db: 0.0721 2022/11/03 02:25:12 - mmengine - INFO - Epoch(train) [1161][30/63] lr: 9.9199e-05 eta: 0:27:25 time: 0.4873 data_time: 0.0292 memory: 14901 loss: 0.7782 loss_prob: 0.3927 loss_thr: 0.3170 loss_db: 0.0685 2022/11/03 02:25:14 - mmengine - INFO - Epoch(train) [1161][35/63] lr: 9.9199e-05 eta: 0:27:25 time: 0.4825 data_time: 0.0160 memory: 14901 loss: 0.8510 loss_prob: 0.4354 loss_thr: 0.3393 loss_db: 0.0763 2022/11/03 02:25:17 - mmengine - INFO - Epoch(train) [1161][40/63] lr: 9.9199e-05 eta: 0:27:19 time: 0.5059 data_time: 0.0125 memory: 14901 loss: 0.8575 loss_prob: 0.4363 loss_thr: 0.3448 loss_db: 0.0764 2022/11/03 02:25:19 - mmengine - INFO - Epoch(train) [1161][45/63] lr: 9.9199e-05 eta: 0:27:19 time: 0.4913 data_time: 0.0075 memory: 14901 loss: 0.7974 loss_prob: 0.4053 loss_thr: 0.3206 loss_db: 0.0716 2022/11/03 02:25:22 - mmengine - INFO - Epoch(train) [1161][50/63] lr: 9.9199e-05 eta: 0:27:12 time: 0.4691 data_time: 0.0140 memory: 14901 loss: 0.7991 loss_prob: 0.4092 loss_thr: 0.3169 loss_db: 0.0730 2022/11/03 02:25:24 - mmengine - INFO - Epoch(train) [1161][55/63] lr: 9.9199e-05 eta: 0:27:12 time: 0.4758 data_time: 0.0185 memory: 14901 loss: 0.8090 loss_prob: 0.4154 loss_thr: 0.3200 loss_db: 0.0736 2022/11/03 02:25:26 - mmengine - INFO - Epoch(train) [1161][60/63] lr: 9.9199e-05 eta: 0:27:05 time: 0.4652 data_time: 0.0123 memory: 14901 loss: 0.8689 loss_prob: 0.4494 loss_thr: 0.3407 loss_db: 0.0787 2022/11/03 02:25:28 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:25:32 - mmengine - INFO - Epoch(train) [1162][5/63] lr: 9.6909e-05 eta: 0:27:05 time: 0.6831 data_time: 0.1838 memory: 14901 loss: 0.8878 loss_prob: 0.4571 loss_thr: 0.3528 loss_db: 0.0779 2022/11/03 02:25:34 - mmengine - INFO - Epoch(train) [1162][10/63] lr: 9.6909e-05 eta: 0:26:57 time: 0.6491 data_time: 0.1824 memory: 14901 loss: 0.8686 loss_prob: 0.4484 loss_thr: 0.3421 loss_db: 0.0781 2022/11/03 02:25:37 - mmengine - INFO - Epoch(train) [1162][15/63] lr: 9.6909e-05 eta: 0:26:57 time: 0.4630 data_time: 0.0060 memory: 14901 loss: 0.8128 loss_prob: 0.4107 loss_thr: 0.3299 loss_db: 0.0722 2022/11/03 02:25:39 - mmengine - INFO - Epoch(train) [1162][20/63] lr: 9.6909e-05 eta: 0:26:50 time: 0.4606 data_time: 0.0055 memory: 14901 loss: 0.9287 loss_prob: 0.4772 loss_thr: 0.3706 loss_db: 0.0809 2022/11/03 02:25:41 - mmengine - INFO - Epoch(train) [1162][25/63] lr: 9.6909e-05 eta: 0:26:50 time: 0.4730 data_time: 0.0125 memory: 14901 loss: 0.9499 loss_prob: 0.4939 loss_thr: 0.3724 loss_db: 0.0836 2022/11/03 02:25:44 - mmengine - INFO - Epoch(train) [1162][30/63] lr: 9.6909e-05 eta: 0:26:43 time: 0.4929 data_time: 0.0403 memory: 14901 loss: 0.8252 loss_prob: 0.4155 loss_thr: 0.3372 loss_db: 0.0724 2022/11/03 02:25:46 - mmengine - INFO - Epoch(train) [1162][35/63] lr: 9.6909e-05 eta: 0:26:43 time: 0.4801 data_time: 0.0338 memory: 14901 loss: 0.9037 loss_prob: 0.4800 loss_thr: 0.3399 loss_db: 0.0839 2022/11/03 02:25:49 - mmengine - INFO - Epoch(train) [1162][40/63] lr: 9.6909e-05 eta: 0:26:37 time: 0.4622 data_time: 0.0058 memory: 14901 loss: 0.9235 loss_prob: 0.4950 loss_thr: 0.3417 loss_db: 0.0868 2022/11/03 02:25:51 - mmengine - INFO - Epoch(train) [1162][45/63] lr: 9.6909e-05 eta: 0:26:37 time: 0.4753 data_time: 0.0073 memory: 14901 loss: 0.8580 loss_prob: 0.4412 loss_thr: 0.3388 loss_db: 0.0779 2022/11/03 02:25:53 - mmengine - INFO - Epoch(train) [1162][50/63] lr: 9.6909e-05 eta: 0:26:30 time: 0.4887 data_time: 0.0148 memory: 14901 loss: 0.8672 loss_prob: 0.4472 loss_thr: 0.3415 loss_db: 0.0785 2022/11/03 02:25:56 - mmengine - INFO - Epoch(train) [1162][55/63] lr: 9.6909e-05 eta: 0:26:30 time: 0.5103 data_time: 0.0249 memory: 14901 loss: 0.8307 loss_prob: 0.4270 loss_thr: 0.3295 loss_db: 0.0741 2022/11/03 02:25:59 - mmengine - INFO - Epoch(train) [1162][60/63] lr: 9.6909e-05 eta: 0:26:23 time: 0.5120 data_time: 0.0172 memory: 14901 loss: 0.8002 loss_prob: 0.4085 loss_thr: 0.3209 loss_db: 0.0709 2022/11/03 02:26:00 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:26:06 - mmengine - INFO - Epoch(train) [1163][5/63] lr: 9.4613e-05 eta: 0:26:23 time: 0.8064 data_time: 0.2531 memory: 14901 loss: 0.8400 loss_prob: 0.4334 loss_thr: 0.3315 loss_db: 0.0751 2022/11/03 02:26:08 - mmengine - INFO - Epoch(train) [1163][10/63] lr: 9.4613e-05 eta: 0:26:15 time: 0.8396 data_time: 0.2526 memory: 14901 loss: 0.8492 loss_prob: 0.4355 loss_thr: 0.3383 loss_db: 0.0754 2022/11/03 02:26:11 - mmengine - INFO - Epoch(train) [1163][15/63] lr: 9.4613e-05 eta: 0:26:15 time: 0.5065 data_time: 0.0054 memory: 14901 loss: 0.8336 loss_prob: 0.4254 loss_thr: 0.3327 loss_db: 0.0755 2022/11/03 02:26:13 - mmengine - INFO - Epoch(train) [1163][20/63] lr: 9.4613e-05 eta: 0:26:08 time: 0.4788 data_time: 0.0056 memory: 14901 loss: 0.7805 loss_prob: 0.3950 loss_thr: 0.3133 loss_db: 0.0722 2022/11/03 02:26:16 - mmengine - INFO - Epoch(train) [1163][25/63] lr: 9.4613e-05 eta: 0:26:08 time: 0.4871 data_time: 0.0150 memory: 14901 loss: 0.7845 loss_prob: 0.3980 loss_thr: 0.3168 loss_db: 0.0697 2022/11/03 02:26:18 - mmengine - INFO - Epoch(train) [1163][30/63] lr: 9.4613e-05 eta: 0:26:01 time: 0.4893 data_time: 0.0318 memory: 14901 loss: 0.8750 loss_prob: 0.4498 loss_thr: 0.3493 loss_db: 0.0759 2022/11/03 02:26:20 - mmengine - INFO - Epoch(train) [1163][35/63] lr: 9.4613e-05 eta: 0:26:01 time: 0.4726 data_time: 0.0224 memory: 14901 loss: 0.8856 loss_prob: 0.4627 loss_thr: 0.3427 loss_db: 0.0803 2022/11/03 02:26:23 - mmengine - INFO - Epoch(train) [1163][40/63] lr: 9.4613e-05 eta: 0:25:55 time: 0.4716 data_time: 0.0061 memory: 14901 loss: 0.8037 loss_prob: 0.4165 loss_thr: 0.3132 loss_db: 0.0741 2022/11/03 02:26:25 - mmengine - INFO - Epoch(train) [1163][45/63] lr: 9.4613e-05 eta: 0:25:55 time: 0.4579 data_time: 0.0054 memory: 14901 loss: 0.8565 loss_prob: 0.4366 loss_thr: 0.3420 loss_db: 0.0780 2022/11/03 02:26:27 - mmengine - INFO - Epoch(train) [1163][50/63] lr: 9.4613e-05 eta: 0:25:48 time: 0.4566 data_time: 0.0183 memory: 14901 loss: 0.9091 loss_prob: 0.4709 loss_thr: 0.3546 loss_db: 0.0836 2022/11/03 02:26:30 - mmengine - INFO - Epoch(train) [1163][55/63] lr: 9.4613e-05 eta: 0:25:48 time: 0.4764 data_time: 0.0247 memory: 14901 loss: 0.8780 loss_prob: 0.4563 loss_thr: 0.3421 loss_db: 0.0796 2022/11/03 02:26:32 - mmengine - INFO - Epoch(train) [1163][60/63] lr: 9.4613e-05 eta: 0:25:41 time: 0.4722 data_time: 0.0113 memory: 14901 loss: 0.8565 loss_prob: 0.4406 loss_thr: 0.3388 loss_db: 0.0771 2022/11/03 02:26:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:26:39 - mmengine - INFO - Epoch(train) [1164][5/63] lr: 9.2311e-05 eta: 0:25:41 time: 0.7512 data_time: 0.2323 memory: 14901 loss: 0.8885 loss_prob: 0.4664 loss_thr: 0.3419 loss_db: 0.0802 2022/11/03 02:26:41 - mmengine - INFO - Epoch(train) [1164][10/63] lr: 9.2311e-05 eta: 0:25:33 time: 0.7584 data_time: 0.2331 memory: 14901 loss: 0.9211 loss_prob: 0.4881 loss_thr: 0.3484 loss_db: 0.0845 2022/11/03 02:26:43 - mmengine - INFO - Epoch(train) [1164][15/63] lr: 9.2311e-05 eta: 0:25:33 time: 0.4389 data_time: 0.0058 memory: 14901 loss: 0.8808 loss_prob: 0.4572 loss_thr: 0.3422 loss_db: 0.0814 2022/11/03 02:26:45 - mmengine - INFO - Epoch(train) [1164][20/63] lr: 9.2311e-05 eta: 0:25:26 time: 0.4470 data_time: 0.0052 memory: 14901 loss: 0.8134 loss_prob: 0.4072 loss_thr: 0.3342 loss_db: 0.0720 2022/11/03 02:26:48 - mmengine - INFO - Epoch(train) [1164][25/63] lr: 9.2311e-05 eta: 0:25:26 time: 0.4846 data_time: 0.0349 memory: 14901 loss: 0.8040 loss_prob: 0.4059 loss_thr: 0.3273 loss_db: 0.0708 2022/11/03 02:26:50 - mmengine - INFO - Epoch(train) [1164][30/63] lr: 9.2311e-05 eta: 0:25:19 time: 0.4898 data_time: 0.0349 memory: 14901 loss: 0.7865 loss_prob: 0.4045 loss_thr: 0.3104 loss_db: 0.0716 2022/11/03 02:26:52 - mmengine - INFO - Epoch(train) [1164][35/63] lr: 9.2311e-05 eta: 0:25:19 time: 0.4565 data_time: 0.0052 memory: 14901 loss: 0.8503 loss_prob: 0.4449 loss_thr: 0.3275 loss_db: 0.0779 2022/11/03 02:26:55 - mmengine - INFO - Epoch(train) [1164][40/63] lr: 9.2311e-05 eta: 0:25:13 time: 0.4888 data_time: 0.0052 memory: 14901 loss: 0.9023 loss_prob: 0.4726 loss_thr: 0.3473 loss_db: 0.0824 2022/11/03 02:26:57 - mmengine - INFO - Epoch(train) [1164][45/63] lr: 9.2311e-05 eta: 0:25:13 time: 0.5051 data_time: 0.0052 memory: 14901 loss: 0.8497 loss_prob: 0.4363 loss_thr: 0.3373 loss_db: 0.0761 2022/11/03 02:27:00 - mmengine - INFO - Epoch(train) [1164][50/63] lr: 9.2311e-05 eta: 0:25:06 time: 0.4945 data_time: 0.0218 memory: 14901 loss: 0.8748 loss_prob: 0.4518 loss_thr: 0.3443 loss_db: 0.0787 2022/11/03 02:27:02 - mmengine - INFO - Epoch(train) [1164][55/63] lr: 9.2311e-05 eta: 0:25:06 time: 0.4765 data_time: 0.0219 memory: 14901 loss: 0.8876 loss_prob: 0.4614 loss_thr: 0.3453 loss_db: 0.0809 2022/11/03 02:27:05 - mmengine - INFO - Epoch(train) [1164][60/63] lr: 9.2311e-05 eta: 0:24:59 time: 0.4692 data_time: 0.0054 memory: 14901 loss: 0.8656 loss_prob: 0.4464 loss_thr: 0.3409 loss_db: 0.0783 2022/11/03 02:27:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:27:10 - mmengine - INFO - Epoch(train) [1165][5/63] lr: 9.0002e-05 eta: 0:24:59 time: 0.6499 data_time: 0.2018 memory: 14901 loss: 0.8475 loss_prob: 0.4423 loss_thr: 0.3289 loss_db: 0.0763 2022/11/03 02:27:12 - mmengine - INFO - Epoch(train) [1165][10/63] lr: 9.0002e-05 eta: 0:24:51 time: 0.6662 data_time: 0.2025 memory: 14901 loss: 0.8284 loss_prob: 0.4276 loss_thr: 0.3263 loss_db: 0.0745 2022/11/03 02:27:15 - mmengine - INFO - Epoch(train) [1165][15/63] lr: 9.0002e-05 eta: 0:24:51 time: 0.4792 data_time: 0.0071 memory: 14901 loss: 0.8762 loss_prob: 0.4534 loss_thr: 0.3438 loss_db: 0.0790 2022/11/03 02:27:17 - mmengine - INFO - Epoch(train) [1165][20/63] lr: 9.0002e-05 eta: 0:24:44 time: 0.5019 data_time: 0.0063 memory: 14901 loss: 0.8296 loss_prob: 0.4273 loss_thr: 0.3274 loss_db: 0.0749 2022/11/03 02:27:20 - mmengine - INFO - Epoch(train) [1165][25/63] lr: 9.0002e-05 eta: 0:24:44 time: 0.5064 data_time: 0.0319 memory: 14901 loss: 0.7844 loss_prob: 0.4029 loss_thr: 0.3101 loss_db: 0.0714 2022/11/03 02:27:22 - mmengine - INFO - Epoch(train) [1165][30/63] lr: 9.0002e-05 eta: 0:24:37 time: 0.4865 data_time: 0.0359 memory: 14901 loss: 0.8563 loss_prob: 0.4373 loss_thr: 0.3433 loss_db: 0.0757 2022/11/03 02:27:25 - mmengine - INFO - Epoch(train) [1165][35/63] lr: 9.0002e-05 eta: 0:24:37 time: 0.4694 data_time: 0.0097 memory: 14901 loss: 0.8010 loss_prob: 0.4092 loss_thr: 0.3197 loss_db: 0.0721 2022/11/03 02:27:27 - mmengine - INFO - Epoch(train) [1165][40/63] lr: 9.0002e-05 eta: 0:24:31 time: 0.4848 data_time: 0.0071 memory: 14901 loss: 0.8091 loss_prob: 0.4171 loss_thr: 0.3189 loss_db: 0.0731 2022/11/03 02:27:30 - mmengine - INFO - Epoch(train) [1165][45/63] lr: 9.0002e-05 eta: 0:24:31 time: 0.4812 data_time: 0.0061 memory: 14901 loss: 0.8686 loss_prob: 0.4448 loss_thr: 0.3471 loss_db: 0.0767 2022/11/03 02:27:32 - mmengine - INFO - Epoch(train) [1165][50/63] lr: 9.0002e-05 eta: 0:24:24 time: 0.4882 data_time: 0.0189 memory: 14901 loss: 0.8732 loss_prob: 0.4463 loss_thr: 0.3487 loss_db: 0.0783 2022/11/03 02:27:34 - mmengine - INFO - Epoch(train) [1165][55/63] lr: 9.0002e-05 eta: 0:24:24 time: 0.4791 data_time: 0.0201 memory: 14901 loss: 0.8453 loss_prob: 0.4291 loss_thr: 0.3404 loss_db: 0.0758 2022/11/03 02:27:37 - mmengine - INFO - Epoch(train) [1165][60/63] lr: 9.0002e-05 eta: 0:24:18 time: 0.4778 data_time: 0.0078 memory: 14901 loss: 0.8246 loss_prob: 0.4178 loss_thr: 0.3334 loss_db: 0.0734 2022/11/03 02:27:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:27:42 - mmengine - INFO - Epoch(train) [1166][5/63] lr: 8.7687e-05 eta: 0:24:18 time: 0.6547 data_time: 0.1813 memory: 14901 loss: 0.8290 loss_prob: 0.4236 loss_thr: 0.3324 loss_db: 0.0731 2022/11/03 02:27:45 - mmengine - INFO - Epoch(train) [1166][10/63] lr: 8.7687e-05 eta: 0:24:09 time: 0.6576 data_time: 0.1826 memory: 14901 loss: 0.7925 loss_prob: 0.4090 loss_thr: 0.3116 loss_db: 0.0718 2022/11/03 02:27:47 - mmengine - INFO - Epoch(train) [1166][15/63] lr: 8.7687e-05 eta: 0:24:09 time: 0.4744 data_time: 0.0148 memory: 14901 loss: 0.7854 loss_prob: 0.4045 loss_thr: 0.3096 loss_db: 0.0713 2022/11/03 02:27:50 - mmengine - INFO - Epoch(train) [1166][20/63] lr: 8.7687e-05 eta: 0:24:02 time: 0.4924 data_time: 0.0114 memory: 14901 loss: 0.8493 loss_prob: 0.4457 loss_thr: 0.3254 loss_db: 0.0782 2022/11/03 02:27:52 - mmengine - INFO - Epoch(train) [1166][25/63] lr: 8.7687e-05 eta: 0:24:02 time: 0.4897 data_time: 0.0098 memory: 14901 loss: 0.8485 loss_prob: 0.4462 loss_thr: 0.3246 loss_db: 0.0778 2022/11/03 02:27:54 - mmengine - INFO - Epoch(train) [1166][30/63] lr: 8.7687e-05 eta: 0:23:56 time: 0.4796 data_time: 0.0225 memory: 14901 loss: 0.8327 loss_prob: 0.4370 loss_thr: 0.3199 loss_db: 0.0758 2022/11/03 02:27:57 - mmengine - INFO - Epoch(train) [1166][35/63] lr: 8.7687e-05 eta: 0:23:56 time: 0.4962 data_time: 0.0215 memory: 14901 loss: 0.8868 loss_prob: 0.4632 loss_thr: 0.3431 loss_db: 0.0805 2022/11/03 02:27:59 - mmengine - INFO - Epoch(train) [1166][40/63] lr: 8.7687e-05 eta: 0:23:49 time: 0.5053 data_time: 0.0165 memory: 14901 loss: 0.9410 loss_prob: 0.4808 loss_thr: 0.3764 loss_db: 0.0838 2022/11/03 02:28:02 - mmengine - INFO - Epoch(train) [1166][45/63] lr: 8.7687e-05 eta: 0:23:49 time: 0.4843 data_time: 0.0126 memory: 14901 loss: 0.8923 loss_prob: 0.4586 loss_thr: 0.3536 loss_db: 0.0801 2022/11/03 02:28:04 - mmengine - INFO - Epoch(train) [1166][50/63] lr: 8.7687e-05 eta: 0:23:42 time: 0.5007 data_time: 0.0163 memory: 14901 loss: 0.8433 loss_prob: 0.4390 loss_thr: 0.3276 loss_db: 0.0767 2022/11/03 02:28:07 - mmengine - INFO - Epoch(train) [1166][55/63] lr: 8.7687e-05 eta: 0:23:42 time: 0.5076 data_time: 0.0182 memory: 14901 loss: 0.8725 loss_prob: 0.4484 loss_thr: 0.3447 loss_db: 0.0794 2022/11/03 02:28:09 - mmengine - INFO - Epoch(train) [1166][60/63] lr: 8.7687e-05 eta: 0:23:36 time: 0.4833 data_time: 0.0089 memory: 14901 loss: 0.8440 loss_prob: 0.4290 loss_thr: 0.3399 loss_db: 0.0751 2022/11/03 02:28:10 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:28:15 - mmengine - INFO - Epoch(train) [1167][5/63] lr: 8.5365e-05 eta: 0:23:36 time: 0.6991 data_time: 0.2407 memory: 14901 loss: 0.9096 loss_prob: 0.4725 loss_thr: 0.3549 loss_db: 0.0822 2022/11/03 02:28:18 - mmengine - INFO - Epoch(train) [1167][10/63] lr: 8.5365e-05 eta: 0:23:27 time: 0.7214 data_time: 0.2386 memory: 14901 loss: 0.7720 loss_prob: 0.4012 loss_thr: 0.3004 loss_db: 0.0704 2022/11/03 02:28:20 - mmengine - INFO - Epoch(train) [1167][15/63] lr: 8.5365e-05 eta: 0:23:27 time: 0.4924 data_time: 0.0084 memory: 14901 loss: 0.7930 loss_prob: 0.4100 loss_thr: 0.3109 loss_db: 0.0721 2022/11/03 02:28:22 - mmengine - INFO - Epoch(train) [1167][20/63] lr: 8.5365e-05 eta: 0:23:20 time: 0.4742 data_time: 0.0078 memory: 14901 loss: 0.9486 loss_prob: 0.5025 loss_thr: 0.3584 loss_db: 0.0877 2022/11/03 02:28:25 - mmengine - INFO - Epoch(train) [1167][25/63] lr: 8.5365e-05 eta: 0:23:20 time: 0.4644 data_time: 0.0114 memory: 14901 loss: 0.9027 loss_prob: 0.4764 loss_thr: 0.3431 loss_db: 0.0831 2022/11/03 02:28:27 - mmengine - INFO - Epoch(train) [1167][30/63] lr: 8.5365e-05 eta: 0:23:14 time: 0.4885 data_time: 0.0309 memory: 14901 loss: 0.8364 loss_prob: 0.4309 loss_thr: 0.3302 loss_db: 0.0753 2022/11/03 02:28:29 - mmengine - INFO - Epoch(train) [1167][35/63] lr: 8.5365e-05 eta: 0:23:14 time: 0.4657 data_time: 0.0240 memory: 14901 loss: 0.8904 loss_prob: 0.4603 loss_thr: 0.3508 loss_db: 0.0792 2022/11/03 02:28:32 - mmengine - INFO - Epoch(train) [1167][40/63] lr: 8.5365e-05 eta: 0:23:07 time: 0.4621 data_time: 0.0047 memory: 14901 loss: 0.8203 loss_prob: 0.4202 loss_thr: 0.3266 loss_db: 0.0735 2022/11/03 02:28:34 - mmengine - INFO - Epoch(train) [1167][45/63] lr: 8.5365e-05 eta: 0:23:07 time: 0.4648 data_time: 0.0052 memory: 14901 loss: 0.8319 loss_prob: 0.4293 loss_thr: 0.3277 loss_db: 0.0749 2022/11/03 02:28:37 - mmengine - INFO - Epoch(train) [1167][50/63] lr: 8.5365e-05 eta: 0:23:00 time: 0.4621 data_time: 0.0205 memory: 14901 loss: 0.8210 loss_prob: 0.4238 loss_thr: 0.3232 loss_db: 0.0739 2022/11/03 02:28:39 - mmengine - INFO - Epoch(train) [1167][55/63] lr: 8.5365e-05 eta: 0:23:00 time: 0.4917 data_time: 0.0217 memory: 14901 loss: 0.7994 loss_prob: 0.4060 loss_thr: 0.3206 loss_db: 0.0729 2022/11/03 02:28:41 - mmengine - INFO - Epoch(train) [1167][60/63] lr: 8.5365e-05 eta: 0:22:54 time: 0.4800 data_time: 0.0063 memory: 14901 loss: 0.8223 loss_prob: 0.4229 loss_thr: 0.3263 loss_db: 0.0730 2022/11/03 02:28:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:28:48 - mmengine - INFO - Epoch(train) [1168][5/63] lr: 8.3036e-05 eta: 0:22:54 time: 0.8063 data_time: 0.2343 memory: 14901 loss: 0.8212 loss_prob: 0.4209 loss_thr: 0.3279 loss_db: 0.0725 2022/11/03 02:28:51 - mmengine - INFO - Epoch(train) [1168][10/63] lr: 8.3036e-05 eta: 0:22:45 time: 0.8384 data_time: 0.2362 memory: 14901 loss: 0.7595 loss_prob: 0.3806 loss_thr: 0.3105 loss_db: 0.0684 2022/11/03 02:28:53 - mmengine - INFO - Epoch(train) [1168][15/63] lr: 8.3036e-05 eta: 0:22:45 time: 0.4930 data_time: 0.0077 memory: 14901 loss: 0.8550 loss_prob: 0.4356 loss_thr: 0.3423 loss_db: 0.0771 2022/11/03 02:28:56 - mmengine - INFO - Epoch(train) [1168][20/63] lr: 8.3036e-05 eta: 0:22:38 time: 0.4791 data_time: 0.0066 memory: 14901 loss: 0.8810 loss_prob: 0.4536 loss_thr: 0.3490 loss_db: 0.0784 2022/11/03 02:28:58 - mmengine - INFO - Epoch(train) [1168][25/63] lr: 8.3036e-05 eta: 0:22:38 time: 0.4791 data_time: 0.0199 memory: 14901 loss: 0.8582 loss_prob: 0.4443 loss_thr: 0.3366 loss_db: 0.0773 2022/11/03 02:29:01 - mmengine - INFO - Epoch(train) [1168][30/63] lr: 8.3036e-05 eta: 0:22:32 time: 0.4898 data_time: 0.0324 memory: 14901 loss: 0.8783 loss_prob: 0.4560 loss_thr: 0.3422 loss_db: 0.0800 2022/11/03 02:29:03 - mmengine - INFO - Epoch(train) [1168][35/63] lr: 8.3036e-05 eta: 0:22:32 time: 0.4552 data_time: 0.0193 memory: 14901 loss: 0.8612 loss_prob: 0.4483 loss_thr: 0.3337 loss_db: 0.0792 2022/11/03 02:29:05 - mmengine - INFO - Epoch(train) [1168][40/63] lr: 8.3036e-05 eta: 0:22:25 time: 0.4552 data_time: 0.0060 memory: 14901 loss: 0.9015 loss_prob: 0.4738 loss_thr: 0.3427 loss_db: 0.0850 2022/11/03 02:29:08 - mmengine - INFO - Epoch(train) [1168][45/63] lr: 8.3036e-05 eta: 0:22:25 time: 0.4855 data_time: 0.0046 memory: 14901 loss: 0.8470 loss_prob: 0.4414 loss_thr: 0.3260 loss_db: 0.0796 2022/11/03 02:29:10 - mmengine - INFO - Epoch(train) [1168][50/63] lr: 8.3036e-05 eta: 0:22:19 time: 0.4999 data_time: 0.0134 memory: 14901 loss: 0.7837 loss_prob: 0.4041 loss_thr: 0.3096 loss_db: 0.0699 2022/11/03 02:29:13 - mmengine - INFO - Epoch(train) [1168][55/63] lr: 8.3036e-05 eta: 0:22:19 time: 0.5095 data_time: 0.0211 memory: 14901 loss: 0.8367 loss_prob: 0.4374 loss_thr: 0.3235 loss_db: 0.0759 2022/11/03 02:29:15 - mmengine - INFO - Epoch(train) [1168][60/63] lr: 8.3036e-05 eta: 0:22:12 time: 0.4874 data_time: 0.0136 memory: 14901 loss: 0.8748 loss_prob: 0.4560 loss_thr: 0.3386 loss_db: 0.0802 2022/11/03 02:29:16 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:29:21 - mmengine - INFO - Epoch(train) [1169][5/63] lr: 8.0700e-05 eta: 0:22:12 time: 0.7044 data_time: 0.2012 memory: 14901 loss: 0.8634 loss_prob: 0.4414 loss_thr: 0.3449 loss_db: 0.0772 2022/11/03 02:29:24 - mmengine - INFO - Epoch(train) [1169][10/63] lr: 8.0700e-05 eta: 0:22:03 time: 0.7691 data_time: 0.2055 memory: 14901 loss: 0.8870 loss_prob: 0.4576 loss_thr: 0.3504 loss_db: 0.0790 2022/11/03 02:29:26 - mmengine - INFO - Epoch(train) [1169][15/63] lr: 8.0700e-05 eta: 0:22:03 time: 0.5120 data_time: 0.0131 memory: 14901 loss: 0.8994 loss_prob: 0.4639 loss_thr: 0.3553 loss_db: 0.0802 2022/11/03 02:29:29 - mmengine - INFO - Epoch(train) [1169][20/63] lr: 8.0700e-05 eta: 0:21:57 time: 0.4668 data_time: 0.0084 memory: 14901 loss: 0.8772 loss_prob: 0.4512 loss_thr: 0.3454 loss_db: 0.0806 2022/11/03 02:29:31 - mmengine - INFO - Epoch(train) [1169][25/63] lr: 8.0700e-05 eta: 0:21:57 time: 0.4648 data_time: 0.0154 memory: 14901 loss: 0.9105 loss_prob: 0.4743 loss_thr: 0.3514 loss_db: 0.0848 2022/11/03 02:29:34 - mmengine - INFO - Epoch(train) [1169][30/63] lr: 8.0700e-05 eta: 0:21:50 time: 0.5109 data_time: 0.0271 memory: 14901 loss: 0.9223 loss_prob: 0.4687 loss_thr: 0.3721 loss_db: 0.0815 2022/11/03 02:29:36 - mmengine - INFO - Epoch(train) [1169][35/63] lr: 8.0700e-05 eta: 0:21:50 time: 0.5161 data_time: 0.0205 memory: 14901 loss: 0.8303 loss_prob: 0.4133 loss_thr: 0.3451 loss_db: 0.0719 2022/11/03 02:29:39 - mmengine - INFO - Epoch(train) [1169][40/63] lr: 8.0700e-05 eta: 0:21:43 time: 0.4971 data_time: 0.0100 memory: 14901 loss: 0.8208 loss_prob: 0.4183 loss_thr: 0.3295 loss_db: 0.0730 2022/11/03 02:29:41 - mmengine - INFO - Epoch(train) [1169][45/63] lr: 8.0700e-05 eta: 0:21:43 time: 0.4816 data_time: 0.0093 memory: 14901 loss: 0.8695 loss_prob: 0.4463 loss_thr: 0.3464 loss_db: 0.0768 2022/11/03 02:29:43 - mmengine - INFO - Epoch(train) [1169][50/63] lr: 8.0700e-05 eta: 0:21:37 time: 0.4620 data_time: 0.0201 memory: 14901 loss: 0.8397 loss_prob: 0.4324 loss_thr: 0.3319 loss_db: 0.0754 2022/11/03 02:29:46 - mmengine - INFO - Epoch(train) [1169][55/63] lr: 8.0700e-05 eta: 0:21:37 time: 0.4652 data_time: 0.0184 memory: 14901 loss: 0.7972 loss_prob: 0.4154 loss_thr: 0.3093 loss_db: 0.0724 2022/11/03 02:29:48 - mmengine - INFO - Epoch(train) [1169][60/63] lr: 8.0700e-05 eta: 0:21:30 time: 0.4783 data_time: 0.0094 memory: 14901 loss: 0.7729 loss_prob: 0.3978 loss_thr: 0.3054 loss_db: 0.0697 2022/11/03 02:29:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:29:54 - mmengine - INFO - Epoch(train) [1170][5/63] lr: 7.8356e-05 eta: 0:21:30 time: 0.6586 data_time: 0.1957 memory: 14901 loss: 1.0009 loss_prob: 0.5282 loss_thr: 0.3817 loss_db: 0.0910 2022/11/03 02:29:56 - mmengine - INFO - Epoch(train) [1170][10/63] lr: 7.8356e-05 eta: 0:21:21 time: 0.6682 data_time: 0.1956 memory: 14901 loss: 0.9419 loss_prob: 0.4941 loss_thr: 0.3647 loss_db: 0.0831 2022/11/03 02:29:58 - mmengine - INFO - Epoch(train) [1170][15/63] lr: 7.8356e-05 eta: 0:21:21 time: 0.4760 data_time: 0.0067 memory: 14901 loss: 0.8395 loss_prob: 0.4256 loss_thr: 0.3403 loss_db: 0.0736 2022/11/03 02:30:01 - mmengine - INFO - Epoch(train) [1170][20/63] lr: 7.8356e-05 eta: 0:21:15 time: 0.4788 data_time: 0.0061 memory: 14901 loss: 0.8834 loss_prob: 0.4492 loss_thr: 0.3568 loss_db: 0.0775 2022/11/03 02:30:03 - mmengine - INFO - Epoch(train) [1170][25/63] lr: 7.8356e-05 eta: 0:21:15 time: 0.4979 data_time: 0.0232 memory: 14901 loss: 0.8302 loss_prob: 0.4240 loss_thr: 0.3321 loss_db: 0.0741 2022/11/03 02:30:06 - mmengine - INFO - Epoch(train) [1170][30/63] lr: 7.8356e-05 eta: 0:21:08 time: 0.5182 data_time: 0.0315 memory: 14901 loss: 0.7967 loss_prob: 0.4067 loss_thr: 0.3177 loss_db: 0.0723 2022/11/03 02:30:09 - mmengine - INFO - Epoch(train) [1170][35/63] lr: 7.8356e-05 eta: 0:21:08 time: 0.5154 data_time: 0.0130 memory: 14901 loss: 0.7946 loss_prob: 0.4049 loss_thr: 0.3171 loss_db: 0.0727 2022/11/03 02:30:11 - mmengine - INFO - Epoch(train) [1170][40/63] lr: 7.8356e-05 eta: 0:21:01 time: 0.4921 data_time: 0.0047 memory: 14901 loss: 0.8180 loss_prob: 0.4203 loss_thr: 0.3229 loss_db: 0.0748 2022/11/03 02:30:13 - mmengine - INFO - Epoch(train) [1170][45/63] lr: 7.8356e-05 eta: 0:21:01 time: 0.4684 data_time: 0.0048 memory: 14901 loss: 0.8481 loss_prob: 0.4369 loss_thr: 0.3348 loss_db: 0.0765 2022/11/03 02:30:16 - mmengine - INFO - Epoch(train) [1170][50/63] lr: 7.8356e-05 eta: 0:20:55 time: 0.4749 data_time: 0.0155 memory: 14901 loss: 0.8468 loss_prob: 0.4333 loss_thr: 0.3387 loss_db: 0.0748 2022/11/03 02:30:18 - mmengine - INFO - Epoch(train) [1170][55/63] lr: 7.8356e-05 eta: 0:20:55 time: 0.4776 data_time: 0.0264 memory: 14901 loss: 0.8456 loss_prob: 0.4400 loss_thr: 0.3295 loss_db: 0.0761 2022/11/03 02:30:21 - mmengine - INFO - Epoch(train) [1170][60/63] lr: 7.8356e-05 eta: 0:20:48 time: 0.4888 data_time: 0.0159 memory: 14901 loss: 0.8458 loss_prob: 0.4415 loss_thr: 0.3260 loss_db: 0.0783 2022/11/03 02:30:22 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:30:26 - mmengine - INFO - Epoch(train) [1171][5/63] lr: 7.6005e-05 eta: 0:20:48 time: 0.6866 data_time: 0.1802 memory: 14901 loss: 0.8904 loss_prob: 0.4690 loss_thr: 0.3396 loss_db: 0.0817 2022/11/03 02:30:29 - mmengine - INFO - Epoch(train) [1171][10/63] lr: 7.6005e-05 eta: 0:20:40 time: 0.7403 data_time: 0.1818 memory: 14901 loss: 0.8513 loss_prob: 0.4419 loss_thr: 0.3337 loss_db: 0.0757 2022/11/03 02:30:32 - mmengine - INFO - Epoch(train) [1171][15/63] lr: 7.6005e-05 eta: 0:20:40 time: 0.5189 data_time: 0.0083 memory: 14901 loss: 0.8005 loss_prob: 0.4109 loss_thr: 0.3175 loss_db: 0.0721 2022/11/03 02:30:34 - mmengine - INFO - Epoch(train) [1171][20/63] lr: 7.6005e-05 eta: 0:20:33 time: 0.5100 data_time: 0.0076 memory: 14901 loss: 0.8267 loss_prob: 0.4234 loss_thr: 0.3285 loss_db: 0.0749 2022/11/03 02:30:37 - mmengine - INFO - Epoch(train) [1171][25/63] lr: 7.6005e-05 eta: 0:20:33 time: 0.5053 data_time: 0.0233 memory: 14901 loss: 0.8844 loss_prob: 0.4559 loss_thr: 0.3491 loss_db: 0.0794 2022/11/03 02:30:39 - mmengine - INFO - Epoch(train) [1171][30/63] lr: 7.6005e-05 eta: 0:20:26 time: 0.5036 data_time: 0.0337 memory: 14901 loss: 0.8922 loss_prob: 0.4608 loss_thr: 0.3516 loss_db: 0.0798 2022/11/03 02:30:42 - mmengine - INFO - Epoch(train) [1171][35/63] lr: 7.6005e-05 eta: 0:20:26 time: 0.4937 data_time: 0.0177 memory: 14901 loss: 0.8831 loss_prob: 0.4556 loss_thr: 0.3479 loss_db: 0.0796 2022/11/03 02:30:44 - mmengine - INFO - Epoch(train) [1171][40/63] lr: 7.6005e-05 eta: 0:20:20 time: 0.4599 data_time: 0.0061 memory: 14901 loss: 0.9226 loss_prob: 0.4869 loss_thr: 0.3529 loss_db: 0.0828 2022/11/03 02:30:46 - mmengine - INFO - Epoch(train) [1171][45/63] lr: 7.6005e-05 eta: 0:20:20 time: 0.4573 data_time: 0.0052 memory: 14901 loss: 0.8772 loss_prob: 0.4533 loss_thr: 0.3463 loss_db: 0.0775 2022/11/03 02:30:49 - mmengine - INFO - Epoch(train) [1171][50/63] lr: 7.6005e-05 eta: 0:20:13 time: 0.4787 data_time: 0.0168 memory: 14901 loss: 0.8708 loss_prob: 0.4432 loss_thr: 0.3492 loss_db: 0.0784 2022/11/03 02:30:51 - mmengine - INFO - Epoch(train) [1171][55/63] lr: 7.6005e-05 eta: 0:20:13 time: 0.4685 data_time: 0.0213 memory: 14901 loss: 0.9626 loss_prob: 0.4938 loss_thr: 0.3825 loss_db: 0.0862 2022/11/03 02:30:53 - mmengine - INFO - Epoch(train) [1171][60/63] lr: 7.6005e-05 eta: 0:20:06 time: 0.4533 data_time: 0.0120 memory: 14901 loss: 0.9734 loss_prob: 0.5017 loss_thr: 0.3847 loss_db: 0.0871 2022/11/03 02:30:54 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:30:59 - mmengine - INFO - Epoch(train) [1172][5/63] lr: 7.3645e-05 eta: 0:20:06 time: 0.6482 data_time: 0.1816 memory: 14901 loss: 0.7921 loss_prob: 0.4153 loss_thr: 0.3032 loss_db: 0.0736 2022/11/03 02:31:01 - mmengine - INFO - Epoch(train) [1172][10/63] lr: 7.3645e-05 eta: 0:19:58 time: 0.6624 data_time: 0.1877 memory: 14901 loss: 0.8116 loss_prob: 0.4267 loss_thr: 0.3101 loss_db: 0.0748 2022/11/03 02:31:03 - mmengine - INFO - Epoch(train) [1172][15/63] lr: 7.3645e-05 eta: 0:19:58 time: 0.4589 data_time: 0.0126 memory: 14901 loss: 0.8114 loss_prob: 0.4231 loss_thr: 0.3147 loss_db: 0.0736 2022/11/03 02:31:06 - mmengine - INFO - Epoch(train) [1172][20/63] lr: 7.3645e-05 eta: 0:19:51 time: 0.4743 data_time: 0.0051 memory: 14901 loss: 0.7823 loss_prob: 0.3969 loss_thr: 0.3152 loss_db: 0.0701 2022/11/03 02:31:08 - mmengine - INFO - Epoch(train) [1172][25/63] lr: 7.3645e-05 eta: 0:19:51 time: 0.5103 data_time: 0.0185 memory: 14901 loss: 0.8563 loss_prob: 0.4397 loss_thr: 0.3406 loss_db: 0.0760 2022/11/03 02:31:11 - mmengine - INFO - Epoch(train) [1172][30/63] lr: 7.3645e-05 eta: 0:19:45 time: 0.5423 data_time: 0.0294 memory: 14901 loss: 0.8669 loss_prob: 0.4501 loss_thr: 0.3394 loss_db: 0.0773 2022/11/03 02:31:14 - mmengine - INFO - Epoch(train) [1172][35/63] lr: 7.3645e-05 eta: 0:19:45 time: 0.5232 data_time: 0.0230 memory: 14901 loss: 0.8624 loss_prob: 0.4492 loss_thr: 0.3336 loss_db: 0.0796 2022/11/03 02:31:16 - mmengine - INFO - Epoch(train) [1172][40/63] lr: 7.3645e-05 eta: 0:19:38 time: 0.4681 data_time: 0.0118 memory: 14901 loss: 0.8552 loss_prob: 0.4412 loss_thr: 0.3353 loss_db: 0.0787 2022/11/03 02:31:18 - mmengine - INFO - Epoch(train) [1172][45/63] lr: 7.3645e-05 eta: 0:19:38 time: 0.4542 data_time: 0.0046 memory: 14901 loss: 0.8181 loss_prob: 0.4152 loss_thr: 0.3282 loss_db: 0.0746 2022/11/03 02:31:21 - mmengine - INFO - Epoch(train) [1172][50/63] lr: 7.3645e-05 eta: 0:19:31 time: 0.4821 data_time: 0.0123 memory: 14901 loss: 0.8224 loss_prob: 0.4235 loss_thr: 0.3222 loss_db: 0.0766 2022/11/03 02:31:23 - mmengine - INFO - Epoch(train) [1172][55/63] lr: 7.3645e-05 eta: 0:19:31 time: 0.4817 data_time: 0.0187 memory: 14901 loss: 0.7942 loss_prob: 0.4075 loss_thr: 0.3120 loss_db: 0.0747 2022/11/03 02:31:25 - mmengine - INFO - Epoch(train) [1172][60/63] lr: 7.3645e-05 eta: 0:19:25 time: 0.4650 data_time: 0.0156 memory: 14901 loss: 0.8526 loss_prob: 0.4345 loss_thr: 0.3394 loss_db: 0.0787 2022/11/03 02:31:27 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:31:31 - mmengine - INFO - Epoch(train) [1173][5/63] lr: 7.1277e-05 eta: 0:19:25 time: 0.6234 data_time: 0.1696 memory: 14901 loss: 0.9036 loss_prob: 0.4610 loss_thr: 0.3618 loss_db: 0.0807 2022/11/03 02:31:33 - mmengine - INFO - Epoch(train) [1173][10/63] lr: 7.1277e-05 eta: 0:19:16 time: 0.6397 data_time: 0.1852 memory: 14901 loss: 0.8280 loss_prob: 0.4182 loss_thr: 0.3362 loss_db: 0.0735 2022/11/03 02:31:36 - mmengine - INFO - Epoch(train) [1173][15/63] lr: 7.1277e-05 eta: 0:19:16 time: 0.4916 data_time: 0.0236 memory: 14901 loss: 0.8382 loss_prob: 0.4291 loss_thr: 0.3340 loss_db: 0.0751 2022/11/03 02:31:38 - mmengine - INFO - Epoch(train) [1173][20/63] lr: 7.1277e-05 eta: 0:19:09 time: 0.4682 data_time: 0.0090 memory: 14901 loss: 0.8598 loss_prob: 0.4488 loss_thr: 0.3316 loss_db: 0.0794 2022/11/03 02:31:40 - mmengine - INFO - Epoch(train) [1173][25/63] lr: 7.1277e-05 eta: 0:19:09 time: 0.4857 data_time: 0.0206 memory: 14901 loss: 0.8672 loss_prob: 0.4520 loss_thr: 0.3351 loss_db: 0.0802 2022/11/03 02:31:43 - mmengine - INFO - Epoch(train) [1173][30/63] lr: 7.1277e-05 eta: 0:19:03 time: 0.5124 data_time: 0.0202 memory: 14901 loss: 0.8786 loss_prob: 0.4590 loss_thr: 0.3400 loss_db: 0.0796 2022/11/03 02:31:45 - mmengine - INFO - Epoch(train) [1173][35/63] lr: 7.1277e-05 eta: 0:19:03 time: 0.5040 data_time: 0.0202 memory: 14901 loss: 0.9048 loss_prob: 0.4775 loss_thr: 0.3455 loss_db: 0.0818 2022/11/03 02:31:48 - mmengine - INFO - Epoch(train) [1173][40/63] lr: 7.1277e-05 eta: 0:18:56 time: 0.5043 data_time: 0.0234 memory: 14901 loss: 0.8896 loss_prob: 0.4603 loss_thr: 0.3484 loss_db: 0.0808 2022/11/03 02:31:50 - mmengine - INFO - Epoch(train) [1173][45/63] lr: 7.1277e-05 eta: 0:18:56 time: 0.4818 data_time: 0.0090 memory: 14901 loss: 0.9927 loss_prob: 0.5312 loss_thr: 0.3716 loss_db: 0.0900 2022/11/03 02:31:53 - mmengine - INFO - Epoch(train) [1173][50/63] lr: 7.1277e-05 eta: 0:18:49 time: 0.4709 data_time: 0.0132 memory: 14901 loss: 0.9598 loss_prob: 0.5188 loss_thr: 0.3546 loss_db: 0.0864 2022/11/03 02:31:55 - mmengine - INFO - Epoch(train) [1173][55/63] lr: 7.1277e-05 eta: 0:18:49 time: 0.4807 data_time: 0.0204 memory: 14901 loss: 0.8385 loss_prob: 0.4347 loss_thr: 0.3291 loss_db: 0.0748 2022/11/03 02:31:57 - mmengine - INFO - Epoch(train) [1173][60/63] lr: 7.1277e-05 eta: 0:18:43 time: 0.4815 data_time: 0.0133 memory: 14901 loss: 0.8354 loss_prob: 0.4307 loss_thr: 0.3305 loss_db: 0.0742 2022/11/03 02:31:59 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:32:03 - mmengine - INFO - Epoch(train) [1174][5/63] lr: 6.8900e-05 eta: 0:18:43 time: 0.6453 data_time: 0.1988 memory: 14901 loss: 0.8064 loss_prob: 0.4076 loss_thr: 0.3275 loss_db: 0.0713 2022/11/03 02:32:06 - mmengine - INFO - Epoch(train) [1174][10/63] lr: 6.8900e-05 eta: 0:18:34 time: 0.7104 data_time: 0.2053 memory: 14901 loss: 0.8357 loss_prob: 0.4291 loss_thr: 0.3325 loss_db: 0.0741 2022/11/03 02:32:08 - mmengine - INFO - Epoch(train) [1174][15/63] lr: 6.8900e-05 eta: 0:18:34 time: 0.5013 data_time: 0.0134 memory: 14901 loss: 0.8140 loss_prob: 0.4161 loss_thr: 0.3252 loss_db: 0.0727 2022/11/03 02:32:10 - mmengine - INFO - Epoch(train) [1174][20/63] lr: 6.8900e-05 eta: 0:18:28 time: 0.4659 data_time: 0.0061 memory: 14901 loss: 0.8144 loss_prob: 0.4095 loss_thr: 0.3320 loss_db: 0.0728 2022/11/03 02:32:13 - mmengine - INFO - Epoch(train) [1174][25/63] lr: 6.8900e-05 eta: 0:18:28 time: 0.4815 data_time: 0.0203 memory: 14901 loss: 0.8920 loss_prob: 0.4626 loss_thr: 0.3478 loss_db: 0.0816 2022/11/03 02:32:15 - mmengine - INFO - Epoch(train) [1174][30/63] lr: 6.8900e-05 eta: 0:18:21 time: 0.4891 data_time: 0.0267 memory: 14901 loss: 0.8588 loss_prob: 0.4551 loss_thr: 0.3233 loss_db: 0.0804 2022/11/03 02:32:18 - mmengine - INFO - Epoch(train) [1174][35/63] lr: 6.8900e-05 eta: 0:18:21 time: 0.5190 data_time: 0.0238 memory: 14901 loss: 0.8277 loss_prob: 0.4281 loss_thr: 0.3246 loss_db: 0.0749 2022/11/03 02:32:20 - mmengine - INFO - Epoch(train) [1174][40/63] lr: 6.8900e-05 eta: 0:18:14 time: 0.5173 data_time: 0.0170 memory: 14901 loss: 0.8668 loss_prob: 0.4468 loss_thr: 0.3437 loss_db: 0.0763 2022/11/03 02:32:23 - mmengine - INFO - Epoch(train) [1174][45/63] lr: 6.8900e-05 eta: 0:18:14 time: 0.4583 data_time: 0.0057 memory: 14901 loss: 0.8540 loss_prob: 0.4484 loss_thr: 0.3295 loss_db: 0.0761 2022/11/03 02:32:25 - mmengine - INFO - Epoch(train) [1174][50/63] lr: 6.8900e-05 eta: 0:18:08 time: 0.4949 data_time: 0.0369 memory: 14901 loss: 0.8350 loss_prob: 0.4258 loss_thr: 0.3358 loss_db: 0.0735 2022/11/03 02:32:28 - mmengine - INFO - Epoch(train) [1174][55/63] lr: 6.8900e-05 eta: 0:18:08 time: 0.5060 data_time: 0.0367 memory: 14901 loss: 0.8416 loss_prob: 0.4209 loss_thr: 0.3475 loss_db: 0.0732 2022/11/03 02:32:30 - mmengine - INFO - Epoch(train) [1174][60/63] lr: 6.8900e-05 eta: 0:18:01 time: 0.4791 data_time: 0.0093 memory: 14901 loss: 0.8457 loss_prob: 0.4276 loss_thr: 0.3425 loss_db: 0.0756 2022/11/03 02:32:31 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:32:36 - mmengine - INFO - Epoch(train) [1175][5/63] lr: 6.6513e-05 eta: 0:18:01 time: 0.6656 data_time: 0.2064 memory: 14901 loss: 0.8437 loss_prob: 0.4394 loss_thr: 0.3275 loss_db: 0.0768 2022/11/03 02:32:38 - mmengine - INFO - Epoch(train) [1175][10/63] lr: 6.6513e-05 eta: 0:17:52 time: 0.6811 data_time: 0.2066 memory: 14901 loss: 0.8278 loss_prob: 0.4284 loss_thr: 0.3241 loss_db: 0.0753 2022/11/03 02:32:41 - mmengine - INFO - Epoch(train) [1175][15/63] lr: 6.6513e-05 eta: 0:17:52 time: 0.4821 data_time: 0.0078 memory: 14901 loss: 0.8391 loss_prob: 0.4390 loss_thr: 0.3231 loss_db: 0.0770 2022/11/03 02:32:43 - mmengine - INFO - Epoch(train) [1175][20/63] lr: 6.6513e-05 eta: 0:17:46 time: 0.4902 data_time: 0.0107 memory: 14901 loss: 0.7780 loss_prob: 0.3990 loss_thr: 0.3088 loss_db: 0.0702 2022/11/03 02:32:46 - mmengine - INFO - Epoch(train) [1175][25/63] lr: 6.6513e-05 eta: 0:17:46 time: 0.4973 data_time: 0.0262 memory: 14901 loss: 0.7753 loss_prob: 0.3908 loss_thr: 0.3152 loss_db: 0.0693 2022/11/03 02:32:48 - mmengine - INFO - Epoch(train) [1175][30/63] lr: 6.6513e-05 eta: 0:17:39 time: 0.5054 data_time: 0.0329 memory: 14901 loss: 0.7786 loss_prob: 0.3938 loss_thr: 0.3147 loss_db: 0.0700 2022/11/03 02:32:51 - mmengine - INFO - Epoch(train) [1175][35/63] lr: 6.6513e-05 eta: 0:17:39 time: 0.5162 data_time: 0.0163 memory: 14901 loss: 0.8232 loss_prob: 0.4192 loss_thr: 0.3280 loss_db: 0.0760 2022/11/03 02:32:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:32:53 - mmengine - INFO - Epoch(train) [1175][40/63] lr: 6.6513e-05 eta: 0:17:33 time: 0.5260 data_time: 0.0108 memory: 14901 loss: 0.9133 loss_prob: 0.4715 loss_thr: 0.3576 loss_db: 0.0842 2022/11/03 02:32:56 - mmengine - INFO - Epoch(train) [1175][45/63] lr: 6.6513e-05 eta: 0:17:33 time: 0.4924 data_time: 0.0124 memory: 14901 loss: 0.9265 loss_prob: 0.4788 loss_thr: 0.3637 loss_db: 0.0839 2022/11/03 02:32:58 - mmengine - INFO - Epoch(train) [1175][50/63] lr: 6.6513e-05 eta: 0:17:26 time: 0.4757 data_time: 0.0182 memory: 14901 loss: 0.8934 loss_prob: 0.4491 loss_thr: 0.3648 loss_db: 0.0795 2022/11/03 02:33:00 - mmengine - INFO - Epoch(train) [1175][55/63] lr: 6.6513e-05 eta: 0:17:26 time: 0.4796 data_time: 0.0189 memory: 14901 loss: 0.9069 loss_prob: 0.4593 loss_thr: 0.3669 loss_db: 0.0806 2022/11/03 02:33:03 - mmengine - INFO - Epoch(train) [1175][60/63] lr: 6.6513e-05 eta: 0:17:19 time: 0.4693 data_time: 0.0100 memory: 14901 loss: 0.9224 loss_prob: 0.4800 loss_thr: 0.3594 loss_db: 0.0831 2022/11/03 02:33:04 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:33:08 - mmengine - INFO - Epoch(train) [1176][5/63] lr: 6.4118e-05 eta: 0:17:19 time: 0.6436 data_time: 0.2012 memory: 14901 loss: 0.8957 loss_prob: 0.4619 loss_thr: 0.3523 loss_db: 0.0815 2022/11/03 02:33:11 - mmengine - INFO - Epoch(train) [1176][10/63] lr: 6.4118e-05 eta: 0:17:11 time: 0.6759 data_time: 0.2007 memory: 14901 loss: 0.9454 loss_prob: 0.4932 loss_thr: 0.3642 loss_db: 0.0879 2022/11/03 02:33:13 - mmengine - INFO - Epoch(train) [1176][15/63] lr: 6.4118e-05 eta: 0:17:11 time: 0.4795 data_time: 0.0083 memory: 14901 loss: 0.8443 loss_prob: 0.4357 loss_thr: 0.3326 loss_db: 0.0760 2022/11/03 02:33:15 - mmengine - INFO - Epoch(train) [1176][20/63] lr: 6.4118e-05 eta: 0:17:04 time: 0.4638 data_time: 0.0081 memory: 14901 loss: 0.7880 loss_prob: 0.4019 loss_thr: 0.3153 loss_db: 0.0707 2022/11/03 02:33:18 - mmengine - INFO - Epoch(train) [1176][25/63] lr: 6.4118e-05 eta: 0:17:04 time: 0.4629 data_time: 0.0139 memory: 14901 loss: 0.8532 loss_prob: 0.4500 loss_thr: 0.3252 loss_db: 0.0780 2022/11/03 02:33:20 - mmengine - INFO - Epoch(train) [1176][30/63] lr: 6.4118e-05 eta: 0:16:57 time: 0.4977 data_time: 0.0300 memory: 14901 loss: 0.8634 loss_prob: 0.4538 loss_thr: 0.3329 loss_db: 0.0766 2022/11/03 02:33:23 - mmengine - INFO - Epoch(train) [1176][35/63] lr: 6.4118e-05 eta: 0:16:57 time: 0.5044 data_time: 0.0243 memory: 14901 loss: 0.8760 loss_prob: 0.4497 loss_thr: 0.3495 loss_db: 0.0768 2022/11/03 02:33:25 - mmengine - INFO - Epoch(train) [1176][40/63] lr: 6.4118e-05 eta: 0:16:51 time: 0.4895 data_time: 0.0096 memory: 14901 loss: 0.8709 loss_prob: 0.4431 loss_thr: 0.3502 loss_db: 0.0776 2022/11/03 02:33:28 - mmengine - INFO - Epoch(train) [1176][45/63] lr: 6.4118e-05 eta: 0:16:51 time: 0.4951 data_time: 0.0092 memory: 14901 loss: 0.8089 loss_prob: 0.4128 loss_thr: 0.3232 loss_db: 0.0729 2022/11/03 02:33:30 - mmengine - INFO - Epoch(train) [1176][50/63] lr: 6.4118e-05 eta: 0:16:44 time: 0.4975 data_time: 0.0158 memory: 14901 loss: 0.9220 loss_prob: 0.4860 loss_thr: 0.3530 loss_db: 0.0831 2022/11/03 02:33:33 - mmengine - INFO - Epoch(train) [1176][55/63] lr: 6.4118e-05 eta: 0:16:44 time: 0.4852 data_time: 0.0219 memory: 14901 loss: 0.9127 loss_prob: 0.4789 loss_thr: 0.3513 loss_db: 0.0825 2022/11/03 02:33:35 - mmengine - INFO - Epoch(train) [1176][60/63] lr: 6.4118e-05 eta: 0:16:38 time: 0.4730 data_time: 0.0137 memory: 14901 loss: 0.7961 loss_prob: 0.4101 loss_thr: 0.3133 loss_db: 0.0728 2022/11/03 02:33:36 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:33:41 - mmengine - INFO - Epoch(train) [1177][5/63] lr: 6.1712e-05 eta: 0:16:38 time: 0.6729 data_time: 0.2009 memory: 14901 loss: 0.8423 loss_prob: 0.4274 loss_thr: 0.3415 loss_db: 0.0734 2022/11/03 02:33:43 - mmengine - INFO - Epoch(train) [1177][10/63] lr: 6.1712e-05 eta: 0:16:29 time: 0.6972 data_time: 0.2008 memory: 14901 loss: 0.8837 loss_prob: 0.4394 loss_thr: 0.3684 loss_db: 0.0758 2022/11/03 02:33:46 - mmengine - INFO - Epoch(train) [1177][15/63] lr: 6.1712e-05 eta: 0:16:29 time: 0.5123 data_time: 0.0058 memory: 14901 loss: 0.8255 loss_prob: 0.4154 loss_thr: 0.3368 loss_db: 0.0733 2022/11/03 02:33:48 - mmengine - INFO - Epoch(train) [1177][20/63] lr: 6.1712e-05 eta: 0:16:22 time: 0.4927 data_time: 0.0067 memory: 14901 loss: 0.8220 loss_prob: 0.4257 loss_thr: 0.3230 loss_db: 0.0734 2022/11/03 02:33:51 - mmengine - INFO - Epoch(train) [1177][25/63] lr: 6.1712e-05 eta: 0:16:22 time: 0.5010 data_time: 0.0330 memory: 14901 loss: 0.8119 loss_prob: 0.4211 loss_thr: 0.3187 loss_db: 0.0721 2022/11/03 02:33:53 - mmengine - INFO - Epoch(train) [1177][30/63] lr: 6.1712e-05 eta: 0:16:16 time: 0.5351 data_time: 0.0338 memory: 14901 loss: 0.8540 loss_prob: 0.4438 loss_thr: 0.3337 loss_db: 0.0765 2022/11/03 02:33:56 - mmengine - INFO - Epoch(train) [1177][35/63] lr: 6.1712e-05 eta: 0:16:16 time: 0.4878 data_time: 0.0067 memory: 14901 loss: 0.7985 loss_prob: 0.4132 loss_thr: 0.3123 loss_db: 0.0730 2022/11/03 02:33:58 - mmengine - INFO - Epoch(train) [1177][40/63] lr: 6.1712e-05 eta: 0:16:09 time: 0.4519 data_time: 0.0052 memory: 14901 loss: 0.7627 loss_prob: 0.3925 loss_thr: 0.2994 loss_db: 0.0708 2022/11/03 02:34:01 - mmengine - INFO - Epoch(train) [1177][45/63] lr: 6.1712e-05 eta: 0:16:09 time: 0.4954 data_time: 0.0071 memory: 14901 loss: 0.8091 loss_prob: 0.4093 loss_thr: 0.3267 loss_db: 0.0732 2022/11/03 02:34:03 - mmengine - INFO - Epoch(train) [1177][50/63] lr: 6.1712e-05 eta: 0:16:03 time: 0.5539 data_time: 0.0228 memory: 14901 loss: 0.8379 loss_prob: 0.4223 loss_thr: 0.3404 loss_db: 0.0752 2022/11/03 02:34:06 - mmengine - INFO - Epoch(train) [1177][55/63] lr: 6.1712e-05 eta: 0:16:03 time: 0.5105 data_time: 0.0228 memory: 14901 loss: 0.8358 loss_prob: 0.4247 loss_thr: 0.3366 loss_db: 0.0745 2022/11/03 02:34:08 - mmengine - INFO - Epoch(train) [1177][60/63] lr: 6.1712e-05 eta: 0:15:56 time: 0.4694 data_time: 0.0068 memory: 14901 loss: 0.8918 loss_prob: 0.4634 loss_thr: 0.3492 loss_db: 0.0793 2022/11/03 02:34:09 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:34:14 - mmengine - INFO - Epoch(train) [1178][5/63] lr: 5.9296e-05 eta: 0:15:56 time: 0.6821 data_time: 0.1946 memory: 14901 loss: 0.9551 loss_prob: 0.5090 loss_thr: 0.3602 loss_db: 0.0858 2022/11/03 02:34:16 - mmengine - INFO - Epoch(train) [1178][10/63] lr: 5.9296e-05 eta: 0:15:47 time: 0.7058 data_time: 0.1962 memory: 14901 loss: 0.8754 loss_prob: 0.4573 loss_thr: 0.3390 loss_db: 0.0791 2022/11/03 02:34:19 - mmengine - INFO - Epoch(train) [1178][15/63] lr: 5.9296e-05 eta: 0:15:47 time: 0.4867 data_time: 0.0069 memory: 14901 loss: 0.7598 loss_prob: 0.3871 loss_thr: 0.3045 loss_db: 0.0682 2022/11/03 02:34:21 - mmengine - INFO - Epoch(train) [1178][20/63] lr: 5.9296e-05 eta: 0:15:41 time: 0.4650 data_time: 0.0055 memory: 14901 loss: 0.8295 loss_prob: 0.4281 loss_thr: 0.3274 loss_db: 0.0740 2022/11/03 02:34:24 - mmengine - INFO - Epoch(train) [1178][25/63] lr: 5.9296e-05 eta: 0:15:41 time: 0.4741 data_time: 0.0202 memory: 14901 loss: 0.8625 loss_prob: 0.4472 loss_thr: 0.3374 loss_db: 0.0779 2022/11/03 02:34:26 - mmengine - INFO - Epoch(train) [1178][30/63] lr: 5.9296e-05 eta: 0:15:34 time: 0.4957 data_time: 0.0346 memory: 14901 loss: 0.8474 loss_prob: 0.4408 loss_thr: 0.3302 loss_db: 0.0763 2022/11/03 02:34:29 - mmengine - INFO - Epoch(train) [1178][35/63] lr: 5.9296e-05 eta: 0:15:34 time: 0.4931 data_time: 0.0199 memory: 14901 loss: 0.8494 loss_prob: 0.4461 loss_thr: 0.3277 loss_db: 0.0756 2022/11/03 02:34:31 - mmengine - INFO - Epoch(train) [1178][40/63] lr: 5.9296e-05 eta: 0:15:27 time: 0.4692 data_time: 0.0052 memory: 14901 loss: 0.8242 loss_prob: 0.4301 loss_thr: 0.3196 loss_db: 0.0745 2022/11/03 02:34:33 - mmengine - INFO - Epoch(train) [1178][45/63] lr: 5.9296e-05 eta: 0:15:27 time: 0.4700 data_time: 0.0052 memory: 14901 loss: 0.8338 loss_prob: 0.4327 loss_thr: 0.3249 loss_db: 0.0762 2022/11/03 02:34:36 - mmengine - INFO - Epoch(train) [1178][50/63] lr: 5.9296e-05 eta: 0:15:21 time: 0.5430 data_time: 0.0172 memory: 14901 loss: 0.8287 loss_prob: 0.4293 loss_thr: 0.3244 loss_db: 0.0749 2022/11/03 02:34:39 - mmengine - INFO - Epoch(train) [1178][55/63] lr: 5.9296e-05 eta: 0:15:21 time: 0.5400 data_time: 0.0241 memory: 14901 loss: 0.8641 loss_prob: 0.4456 loss_thr: 0.3405 loss_db: 0.0781 2022/11/03 02:34:41 - mmengine - INFO - Epoch(train) [1178][60/63] lr: 5.9296e-05 eta: 0:15:14 time: 0.4700 data_time: 0.0117 memory: 14901 loss: 0.9156 loss_prob: 0.4769 loss_thr: 0.3557 loss_db: 0.0830 2022/11/03 02:34:42 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:34:47 - mmengine - INFO - Epoch(train) [1179][5/63] lr: 5.6869e-05 eta: 0:15:14 time: 0.6797 data_time: 0.1999 memory: 14901 loss: 0.9442 loss_prob: 0.4947 loss_thr: 0.3640 loss_db: 0.0855 2022/11/03 02:34:49 - mmengine - INFO - Epoch(train) [1179][10/63] lr: 5.6869e-05 eta: 0:15:06 time: 0.7003 data_time: 0.2026 memory: 14901 loss: 0.9343 loss_prob: 0.4896 loss_thr: 0.3594 loss_db: 0.0853 2022/11/03 02:34:52 - mmengine - INFO - Epoch(train) [1179][15/63] lr: 5.6869e-05 eta: 0:15:06 time: 0.4876 data_time: 0.0127 memory: 14901 loss: 0.8919 loss_prob: 0.4708 loss_thr: 0.3395 loss_db: 0.0816 2022/11/03 02:34:54 - mmengine - INFO - Epoch(train) [1179][20/63] lr: 5.6869e-05 eta: 0:14:59 time: 0.4949 data_time: 0.0105 memory: 14901 loss: 0.8461 loss_prob: 0.4376 loss_thr: 0.3329 loss_db: 0.0756 2022/11/03 02:34:57 - mmengine - INFO - Epoch(train) [1179][25/63] lr: 5.6869e-05 eta: 0:14:59 time: 0.5081 data_time: 0.0165 memory: 14901 loss: 0.8591 loss_prob: 0.4407 loss_thr: 0.3413 loss_db: 0.0770 2022/11/03 02:34:59 - mmengine - INFO - Epoch(train) [1179][30/63] lr: 5.6869e-05 eta: 0:14:52 time: 0.5022 data_time: 0.0290 memory: 14901 loss: 0.8434 loss_prob: 0.4319 loss_thr: 0.3355 loss_db: 0.0760 2022/11/03 02:35:02 - mmengine - INFO - Epoch(train) [1179][35/63] lr: 5.6869e-05 eta: 0:14:52 time: 0.5082 data_time: 0.0180 memory: 14901 loss: 0.7426 loss_prob: 0.3691 loss_thr: 0.3072 loss_db: 0.0662 2022/11/03 02:35:04 - mmengine - INFO - Epoch(train) [1179][40/63] lr: 5.6869e-05 eta: 0:14:46 time: 0.5270 data_time: 0.0092 memory: 14901 loss: 0.7983 loss_prob: 0.4023 loss_thr: 0.3260 loss_db: 0.0700 2022/11/03 02:35:07 - mmengine - INFO - Epoch(train) [1179][45/63] lr: 5.6869e-05 eta: 0:14:46 time: 0.4944 data_time: 0.0091 memory: 14901 loss: 0.8606 loss_prob: 0.4419 loss_thr: 0.3424 loss_db: 0.0762 2022/11/03 02:35:09 - mmengine - INFO - Epoch(train) [1179][50/63] lr: 5.6869e-05 eta: 0:14:39 time: 0.4864 data_time: 0.0159 memory: 14901 loss: 0.8731 loss_prob: 0.4518 loss_thr: 0.3420 loss_db: 0.0793 2022/11/03 02:35:12 - mmengine - INFO - Epoch(train) [1179][55/63] lr: 5.6869e-05 eta: 0:14:39 time: 0.4985 data_time: 0.0212 memory: 14901 loss: 0.8081 loss_prob: 0.4136 loss_thr: 0.3213 loss_db: 0.0732 2022/11/03 02:35:14 - mmengine - INFO - Epoch(train) [1179][60/63] lr: 5.6869e-05 eta: 0:14:33 time: 0.4930 data_time: 0.0134 memory: 14901 loss: 0.7852 loss_prob: 0.4003 loss_thr: 0.3143 loss_db: 0.0706 2022/11/03 02:35:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:35:20 - mmengine - INFO - Epoch(train) [1180][5/63] lr: 5.4430e-05 eta: 0:14:33 time: 0.6529 data_time: 0.2050 memory: 14901 loss: 0.8376 loss_prob: 0.4276 loss_thr: 0.3362 loss_db: 0.0738 2022/11/03 02:35:22 - mmengine - INFO - Epoch(train) [1180][10/63] lr: 5.4430e-05 eta: 0:14:24 time: 0.6739 data_time: 0.2013 memory: 14901 loss: 0.8623 loss_prob: 0.4445 loss_thr: 0.3393 loss_db: 0.0784 2022/11/03 02:35:25 - mmengine - INFO - Epoch(train) [1180][15/63] lr: 5.4430e-05 eta: 0:14:24 time: 0.4750 data_time: 0.0049 memory: 14901 loss: 0.8019 loss_prob: 0.4118 loss_thr: 0.3166 loss_db: 0.0735 2022/11/03 02:35:27 - mmengine - INFO - Epoch(train) [1180][20/63] lr: 5.4430e-05 eta: 0:14:17 time: 0.4624 data_time: 0.0057 memory: 14901 loss: 0.7713 loss_prob: 0.3920 loss_thr: 0.3098 loss_db: 0.0696 2022/11/03 02:35:29 - mmengine - INFO - Epoch(train) [1180][25/63] lr: 5.4430e-05 eta: 0:14:17 time: 0.4626 data_time: 0.0284 memory: 14901 loss: 0.8758 loss_prob: 0.4408 loss_thr: 0.3576 loss_db: 0.0774 2022/11/03 02:35:32 - mmengine - INFO - Epoch(train) [1180][30/63] lr: 5.4430e-05 eta: 0:14:11 time: 0.4785 data_time: 0.0325 memory: 14901 loss: 0.9865 loss_prob: 0.5135 loss_thr: 0.3849 loss_db: 0.0880 2022/11/03 02:35:34 - mmengine - INFO - Epoch(train) [1180][35/63] lr: 5.4430e-05 eta: 0:14:11 time: 0.4567 data_time: 0.0095 memory: 14901 loss: 0.9052 loss_prob: 0.4815 loss_thr: 0.3414 loss_db: 0.0822 2022/11/03 02:35:36 - mmengine - INFO - Epoch(train) [1180][40/63] lr: 5.4430e-05 eta: 0:14:04 time: 0.4656 data_time: 0.0048 memory: 14901 loss: 0.8152 loss_prob: 0.4244 loss_thr: 0.3174 loss_db: 0.0735 2022/11/03 02:35:39 - mmengine - INFO - Epoch(train) [1180][45/63] lr: 5.4430e-05 eta: 0:14:04 time: 0.4926 data_time: 0.0049 memory: 14901 loss: 0.9080 loss_prob: 0.4824 loss_thr: 0.3439 loss_db: 0.0816 2022/11/03 02:35:41 - mmengine - INFO - Epoch(train) [1180][50/63] lr: 5.4430e-05 eta: 0:13:58 time: 0.4867 data_time: 0.0197 memory: 14901 loss: 0.8375 loss_prob: 0.4388 loss_thr: 0.3242 loss_db: 0.0744 2022/11/03 02:35:44 - mmengine - INFO - Epoch(train) [1180][55/63] lr: 5.4430e-05 eta: 0:13:58 time: 0.4878 data_time: 0.0248 memory: 14901 loss: 0.7823 loss_prob: 0.3921 loss_thr: 0.3217 loss_db: 0.0685 2022/11/03 02:35:46 - mmengine - INFO - Epoch(train) [1180][60/63] lr: 5.4430e-05 eta: 0:13:51 time: 0.5108 data_time: 0.0103 memory: 14901 loss: 0.8975 loss_prob: 0.4611 loss_thr: 0.3544 loss_db: 0.0820 2022/11/03 02:35:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:35:47 - mmengine - INFO - Saving checkpoint at 1180 epochs 2022/11/03 02:35:51 - mmengine - INFO - Epoch(val) [1180][5/500] eta: 0:13:51 time: 0.0438 data_time: 0.0049 memory: 14901 2022/11/03 02:35:51 - mmengine - INFO - Epoch(val) [1180][10/500] eta: 0:00:21 time: 0.0439 data_time: 0.0050 memory: 1008 2022/11/03 02:35:51 - mmengine - INFO - Epoch(val) [1180][15/500] eta: 0:00:21 time: 0.0355 data_time: 0.0024 memory: 1008 2022/11/03 02:35:52 - mmengine - INFO - Epoch(val) [1180][20/500] eta: 0:00:17 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/03 02:35:52 - mmengine - INFO - Epoch(val) [1180][25/500] eta: 0:00:17 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/03 02:35:52 - mmengine - INFO - Epoch(val) [1180][30/500] eta: 0:00:18 time: 0.0387 data_time: 0.0024 memory: 1008 2022/11/03 02:35:52 - mmengine - INFO - Epoch(val) [1180][35/500] eta: 0:00:18 time: 0.0387 data_time: 0.0022 memory: 1008 2022/11/03 02:35:52 - mmengine - INFO - Epoch(val) [1180][40/500] eta: 0:00:17 time: 0.0389 data_time: 0.0020 memory: 1008 2022/11/03 02:35:53 - mmengine - INFO - Epoch(val) [1180][45/500] eta: 0:00:17 time: 0.0412 data_time: 0.0021 memory: 1008 2022/11/03 02:35:53 - mmengine - INFO - Epoch(val) [1180][50/500] eta: 0:00:17 time: 0.0383 data_time: 0.0020 memory: 1008 2022/11/03 02:35:53 - mmengine - INFO - Epoch(val) [1180][55/500] eta: 0:00:17 time: 0.0415 data_time: 0.0020 memory: 1008 2022/11/03 02:35:53 - mmengine - INFO - Epoch(val) [1180][60/500] eta: 0:00:18 time: 0.0414 data_time: 0.0020 memory: 1008 2022/11/03 02:35:53 - mmengine - INFO - Epoch(val) [1180][65/500] eta: 0:00:18 time: 0.0385 data_time: 0.0020 memory: 1008 2022/11/03 02:35:54 - mmengine - INFO - Epoch(val) [1180][70/500] eta: 0:00:17 time: 0.0405 data_time: 0.0024 memory: 1008 2022/11/03 02:35:54 - mmengine - INFO - Epoch(val) [1180][75/500] eta: 0:00:17 time: 0.0379 data_time: 0.0024 memory: 1008 2022/11/03 02:35:54 - mmengine - INFO - Epoch(val) [1180][80/500] eta: 0:00:14 time: 0.0335 data_time: 0.0023 memory: 1008 2022/11/03 02:35:54 - mmengine - INFO - Epoch(val) [1180][85/500] eta: 0:00:14 time: 0.0348 data_time: 0.0025 memory: 1008 2022/11/03 02:35:54 - mmengine - INFO - Epoch(val) [1180][90/500] eta: 0:00:16 time: 0.0393 data_time: 0.0025 memory: 1008 2022/11/03 02:35:55 - mmengine - INFO - Epoch(val) [1180][95/500] eta: 0:00:16 time: 0.0412 data_time: 0.0025 memory: 1008 2022/11/03 02:35:55 - mmengine - INFO - Epoch(val) [1180][100/500] eta: 0:00:15 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/03 02:35:55 - mmengine - INFO - Epoch(val) [1180][105/500] eta: 0:00:15 time: 0.0360 data_time: 0.0025 memory: 1008 2022/11/03 02:35:55 - mmengine - INFO - Epoch(val) [1180][110/500] eta: 0:00:14 time: 0.0365 data_time: 0.0025 memory: 1008 2022/11/03 02:35:55 - mmengine - INFO - Epoch(val) [1180][115/500] eta: 0:00:14 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/03 02:35:56 - mmengine - INFO - Epoch(val) [1180][120/500] eta: 0:00:15 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/03 02:35:56 - mmengine - INFO - Epoch(val) [1180][125/500] eta: 0:00:15 time: 0.0382 data_time: 0.0022 memory: 1008 2022/11/03 02:35:56 - mmengine - INFO - Epoch(val) [1180][130/500] eta: 0:00:12 time: 0.0342 data_time: 0.0021 memory: 1008 2022/11/03 02:35:56 - mmengine - INFO - Epoch(val) [1180][135/500] eta: 0:00:12 time: 0.0342 data_time: 0.0021 memory: 1008 2022/11/03 02:35:56 - mmengine - INFO - Epoch(val) [1180][140/500] eta: 0:00:12 time: 0.0361 data_time: 0.0022 memory: 1008 2022/11/03 02:35:56 - mmengine - INFO - Epoch(val) [1180][145/500] eta: 0:00:12 time: 0.0418 data_time: 0.0023 memory: 1008 2022/11/03 02:35:57 - mmengine - INFO - Epoch(val) [1180][150/500] eta: 0:00:14 time: 0.0421 data_time: 0.0025 memory: 1008 2022/11/03 02:35:57 - mmengine - INFO - Epoch(val) [1180][155/500] eta: 0:00:14 time: 0.0428 data_time: 0.0027 memory: 1008 2022/11/03 02:35:57 - mmengine - INFO - Epoch(val) [1180][160/500] eta: 0:00:14 time: 0.0419 data_time: 0.0024 memory: 1008 2022/11/03 02:35:57 - mmengine - INFO - Epoch(val) [1180][165/500] eta: 0:00:14 time: 0.0372 data_time: 0.0021 memory: 1008 2022/11/03 02:35:57 - mmengine - INFO - Epoch(val) [1180][170/500] eta: 0:00:13 time: 0.0410 data_time: 0.0025 memory: 1008 2022/11/03 02:35:58 - mmengine - INFO - Epoch(val) [1180][175/500] eta: 0:00:13 time: 0.0384 data_time: 0.0024 memory: 1008 2022/11/03 02:35:58 - mmengine - INFO - Epoch(val) [1180][180/500] eta: 0:00:11 time: 0.0346 data_time: 0.0020 memory: 1008 2022/11/03 02:35:58 - mmengine - INFO - Epoch(val) [1180][185/500] eta: 0:00:11 time: 0.0389 data_time: 0.0022 memory: 1008 2022/11/03 02:35:58 - mmengine - INFO - Epoch(val) [1180][190/500] eta: 0:00:12 time: 0.0396 data_time: 0.0021 memory: 1008 2022/11/03 02:35:58 - mmengine - INFO - Epoch(val) [1180][195/500] eta: 0:00:12 time: 0.0362 data_time: 0.0021 memory: 1008 2022/11/03 02:35:59 - mmengine - INFO - Epoch(val) [1180][200/500] eta: 0:00:12 time: 0.0406 data_time: 0.0022 memory: 1008 2022/11/03 02:35:59 - mmengine - INFO - Epoch(val) [1180][205/500] eta: 0:00:12 time: 0.0397 data_time: 0.0021 memory: 1008 2022/11/03 02:35:59 - mmengine - INFO - Epoch(val) [1180][210/500] eta: 0:00:09 time: 0.0343 data_time: 0.0020 memory: 1008 2022/11/03 02:35:59 - mmengine - INFO - Epoch(val) [1180][215/500] eta: 0:00:09 time: 0.0378 data_time: 0.0020 memory: 1008 2022/11/03 02:35:59 - mmengine - INFO - Epoch(val) [1180][220/500] eta: 0:00:10 time: 0.0379 data_time: 0.0020 memory: 1008 2022/11/03 02:36:00 - mmengine - INFO - Epoch(val) [1180][225/500] eta: 0:00:10 time: 0.0376 data_time: 0.0020 memory: 1008 2022/11/03 02:36:00 - mmengine - INFO - Epoch(val) [1180][230/500] eta: 0:00:09 time: 0.0360 data_time: 0.0020 memory: 1008 2022/11/03 02:36:00 - mmengine - INFO - Epoch(val) [1180][235/500] eta: 0:00:09 time: 0.0360 data_time: 0.0020 memory: 1008 2022/11/03 02:36:00 - mmengine - INFO - Epoch(val) [1180][240/500] eta: 0:00:10 time: 0.0389 data_time: 0.0021 memory: 1008 2022/11/03 02:36:00 - mmengine - INFO - Epoch(val) [1180][245/500] eta: 0:00:10 time: 0.0362 data_time: 0.0020 memory: 1008 2022/11/03 02:36:01 - mmengine - INFO - Epoch(val) [1180][250/500] eta: 0:00:09 time: 0.0372 data_time: 0.0020 memory: 1008 2022/11/03 02:36:01 - mmengine - INFO - Epoch(val) [1180][255/500] eta: 0:00:09 time: 0.0366 data_time: 0.0021 memory: 1008 2022/11/03 02:36:01 - mmengine - INFO - Epoch(val) [1180][260/500] eta: 0:00:08 time: 0.0352 data_time: 0.0021 memory: 1008 2022/11/03 02:36:01 - mmengine - INFO - Epoch(val) [1180][265/500] eta: 0:00:08 time: 0.0373 data_time: 0.0023 memory: 1008 2022/11/03 02:36:01 - mmengine - INFO - Epoch(val) [1180][270/500] eta: 0:00:08 time: 0.0366 data_time: 0.0023 memory: 1008 2022/11/03 02:36:01 - mmengine - INFO - Epoch(val) [1180][275/500] eta: 0:00:08 time: 0.0345 data_time: 0.0020 memory: 1008 2022/11/03 02:36:02 - mmengine - INFO - Epoch(val) [1180][280/500] eta: 0:00:08 time: 0.0381 data_time: 0.0020 memory: 1008 2022/11/03 02:36:02 - mmengine - INFO - Epoch(val) [1180][285/500] eta: 0:00:08 time: 0.0398 data_time: 0.0022 memory: 1008 2022/11/03 02:36:02 - mmengine - INFO - Epoch(val) [1180][290/500] eta: 0:00:08 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/03 02:36:02 - mmengine - INFO - Epoch(val) [1180][295/500] eta: 0:00:08 time: 0.0409 data_time: 0.0027 memory: 1008 2022/11/03 02:36:02 - mmengine - INFO - Epoch(val) [1180][300/500] eta: 0:00:07 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/03 02:36:03 - mmengine - INFO - Epoch(val) [1180][305/500] eta: 0:00:07 time: 0.0361 data_time: 0.0021 memory: 1008 2022/11/03 02:36:03 - mmengine - INFO - Epoch(val) [1180][310/500] eta: 0:00:06 time: 0.0351 data_time: 0.0021 memory: 1008 2022/11/03 02:36:03 - mmengine - INFO - Epoch(val) [1180][315/500] eta: 0:00:06 time: 0.0382 data_time: 0.0021 memory: 1008 2022/11/03 02:36:03 - mmengine - INFO - Epoch(val) [1180][320/500] eta: 0:00:06 time: 0.0374 data_time: 0.0020 memory: 1008 2022/11/03 02:36:03 - mmengine - INFO - Epoch(val) [1180][325/500] eta: 0:00:06 time: 0.0466 data_time: 0.0020 memory: 1008 2022/11/03 02:36:04 - mmengine - INFO - Epoch(val) [1180][330/500] eta: 0:00:07 time: 0.0461 data_time: 0.0020 memory: 1008 2022/11/03 02:36:04 - mmengine - INFO - Epoch(val) [1180][335/500] eta: 0:00:07 time: 0.0345 data_time: 0.0022 memory: 1008 2022/11/03 02:36:04 - mmengine - INFO - Epoch(val) [1180][340/500] eta: 0:00:08 time: 0.0513 data_time: 0.0020 memory: 1008 2022/11/03 02:36:04 - mmengine - INFO - Epoch(val) [1180][345/500] eta: 0:00:08 time: 0.0525 data_time: 0.0018 memory: 1008 2022/11/03 02:36:05 - mmengine - INFO - Epoch(val) [1180][350/500] eta: 0:00:06 time: 0.0413 data_time: 0.0021 memory: 1008 2022/11/03 02:36:05 - mmengine - INFO - Epoch(val) [1180][355/500] eta: 0:00:06 time: 0.0390 data_time: 0.0020 memory: 1008 2022/11/03 02:36:05 - mmengine - INFO - Epoch(val) [1180][360/500] eta: 0:00:05 time: 0.0367 data_time: 0.0023 memory: 1008 2022/11/03 02:36:05 - mmengine - INFO - Epoch(val) [1180][365/500] eta: 0:00:05 time: 0.0382 data_time: 0.0023 memory: 1008 2022/11/03 02:36:05 - mmengine - INFO - Epoch(val) [1180][370/500] eta: 0:00:04 time: 0.0342 data_time: 0.0020 memory: 1008 2022/11/03 02:36:05 - mmengine - INFO - Epoch(val) [1180][375/500] eta: 0:00:04 time: 0.0345 data_time: 0.0024 memory: 1008 2022/11/03 02:36:06 - mmengine - INFO - Epoch(val) [1180][380/500] eta: 0:00:04 time: 0.0387 data_time: 0.0025 memory: 1008 2022/11/03 02:36:06 - mmengine - INFO - Epoch(val) [1180][385/500] eta: 0:00:04 time: 0.0382 data_time: 0.0021 memory: 1008 2022/11/03 02:36:06 - mmengine - INFO - Epoch(val) [1180][390/500] eta: 0:00:03 time: 0.0358 data_time: 0.0020 memory: 1008 2022/11/03 02:36:06 - mmengine - INFO - Epoch(val) [1180][395/500] eta: 0:00:03 time: 0.0348 data_time: 0.0020 memory: 1008 2022/11/03 02:36:06 - mmengine - INFO - Epoch(val) [1180][400/500] eta: 0:00:03 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/03 02:36:07 - mmengine - INFO - Epoch(val) [1180][405/500] eta: 0:00:03 time: 0.0374 data_time: 0.0025 memory: 1008 2022/11/03 02:36:07 - mmengine - INFO - Epoch(val) [1180][410/500] eta: 0:00:03 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/03 02:36:07 - mmengine - INFO - Epoch(val) [1180][415/500] eta: 0:00:03 time: 0.0386 data_time: 0.0027 memory: 1008 2022/11/03 02:36:07 - mmengine - INFO - Epoch(val) [1180][420/500] eta: 0:00:02 time: 0.0349 data_time: 0.0025 memory: 1008 2022/11/03 02:36:07 - mmengine - INFO - Epoch(val) [1180][425/500] eta: 0:00:02 time: 0.0348 data_time: 0.0024 memory: 1008 2022/11/03 02:36:07 - mmengine - INFO - Epoch(val) [1180][430/500] eta: 0:00:02 time: 0.0379 data_time: 0.0026 memory: 1008 2022/11/03 02:36:08 - mmengine - INFO - Epoch(val) [1180][435/500] eta: 0:00:02 time: 0.0367 data_time: 0.0025 memory: 1008 2022/11/03 02:36:08 - mmengine - INFO - Epoch(val) [1180][440/500] eta: 0:00:02 time: 0.0362 data_time: 0.0023 memory: 1008 2022/11/03 02:36:08 - mmengine - INFO - Epoch(val) [1180][445/500] eta: 0:00:02 time: 0.0376 data_time: 0.0022 memory: 1008 2022/11/03 02:36:08 - mmengine - INFO - Epoch(val) [1180][450/500] eta: 0:00:01 time: 0.0383 data_time: 0.0021 memory: 1008 2022/11/03 02:36:08 - mmengine - INFO - Epoch(val) [1180][455/500] eta: 0:00:01 time: 0.0397 data_time: 0.0022 memory: 1008 2022/11/03 02:36:09 - mmengine - INFO - Epoch(val) [1180][460/500] eta: 0:00:01 time: 0.0378 data_time: 0.0026 memory: 1008 2022/11/03 02:36:09 - mmengine - INFO - Epoch(val) [1180][465/500] eta: 0:00:01 time: 0.0347 data_time: 0.0025 memory: 1008 2022/11/03 02:36:09 - mmengine - INFO - Epoch(val) [1180][470/500] eta: 0:00:01 time: 0.0350 data_time: 0.0023 memory: 1008 2022/11/03 02:36:09 - mmengine - INFO - Epoch(val) [1180][475/500] eta: 0:00:01 time: 0.0352 data_time: 0.0023 memory: 1008 2022/11/03 02:36:09 - mmengine - INFO - Epoch(val) [1180][480/500] eta: 0:00:00 time: 0.0349 data_time: 0.0025 memory: 1008 2022/11/03 02:36:09 - mmengine - INFO - Epoch(val) [1180][485/500] eta: 0:00:00 time: 0.0348 data_time: 0.0019 memory: 1008 2022/11/03 02:36:10 - mmengine - INFO - Epoch(val) [1180][490/500] eta: 0:00:00 time: 0.0371 data_time: 0.0016 memory: 1008 2022/11/03 02:36:10 - mmengine - INFO - Epoch(val) [1180][495/500] eta: 0:00:00 time: 0.0385 data_time: 0.0020 memory: 1008 2022/11/03 02:36:10 - mmengine - INFO - Epoch(val) [1180][500/500] eta: 0:00:00 time: 0.0356 data_time: 0.0020 memory: 1008 2022/11/03 02:36:10 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8320, precision: 0.7687, hmean: 0.7991 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8320, precision: 0.8071, hmean: 0.8193 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8315, precision: 0.8279, hmean: 0.8297 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8286, precision: 0.8486, hmean: 0.8385 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8166, precision: 0.8711, hmean: 0.8429 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7415, precision: 0.9102, hmean: 0.8172 2022/11/03 02:36:10 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2239, precision: 0.9588, hmean: 0.3630 2022/11/03 02:36:10 - mmengine - INFO - Epoch(val) [1180][500/500] icdar/precision: 0.8711 icdar/recall: 0.8166 icdar/hmean: 0.8429 2022/11/03 02:36:15 - mmengine - INFO - Epoch(train) [1181][5/63] lr: 5.1979e-05 eta: 0:00:00 time: 0.6572 data_time: 0.2030 memory: 14901 loss: 0.9067 loss_prob: 0.4699 loss_thr: 0.3541 loss_db: 0.0827 2022/11/03 02:36:17 - mmengine - INFO - Epoch(train) [1181][10/63] lr: 5.1979e-05 eta: 0:13:42 time: 0.6753 data_time: 0.2031 memory: 14901 loss: 0.8557 loss_prob: 0.4432 loss_thr: 0.3358 loss_db: 0.0768 2022/11/03 02:36:19 - mmengine - INFO - Epoch(train) [1181][15/63] lr: 5.1979e-05 eta: 0:13:42 time: 0.4904 data_time: 0.0066 memory: 14901 loss: 0.8531 loss_prob: 0.4436 loss_thr: 0.3325 loss_db: 0.0770 2022/11/03 02:36:22 - mmengine - INFO - Epoch(train) [1181][20/63] lr: 5.1979e-05 eta: 0:13:36 time: 0.5292 data_time: 0.0066 memory: 14901 loss: 0.8138 loss_prob: 0.4228 loss_thr: 0.3161 loss_db: 0.0749 2022/11/03 02:36:25 - mmengine - INFO - Epoch(train) [1181][25/63] lr: 5.1979e-05 eta: 0:13:36 time: 0.5418 data_time: 0.0186 memory: 14901 loss: 0.9332 loss_prob: 0.5143 loss_thr: 0.3381 loss_db: 0.0808 2022/11/03 02:36:28 - mmengine - INFO - Epoch(train) [1181][30/63] lr: 5.1979e-05 eta: 0:13:29 time: 0.5421 data_time: 0.0327 memory: 14901 loss: 1.0289 loss_prob: 0.5700 loss_thr: 0.3687 loss_db: 0.0903 2022/11/03 02:36:30 - mmengine - INFO - Epoch(train) [1181][35/63] lr: 5.1979e-05 eta: 0:13:29 time: 0.5055 data_time: 0.0195 memory: 14901 loss: 0.8780 loss_prob: 0.4568 loss_thr: 0.3397 loss_db: 0.0816 2022/11/03 02:36:32 - mmengine - INFO - Epoch(train) [1181][40/63] lr: 5.1979e-05 eta: 0:13:22 time: 0.4493 data_time: 0.0049 memory: 14901 loss: 0.8491 loss_prob: 0.4325 loss_thr: 0.3399 loss_db: 0.0767 2022/11/03 02:36:34 - mmengine - INFO - Epoch(train) [1181][45/63] lr: 5.1979e-05 eta: 0:13:22 time: 0.4480 data_time: 0.0047 memory: 14901 loss: 0.8690 loss_prob: 0.4370 loss_thr: 0.3564 loss_db: 0.0756 2022/11/03 02:36:37 - mmengine - INFO - Epoch(train) [1181][50/63] lr: 5.1979e-05 eta: 0:13:16 time: 0.4774 data_time: 0.0246 memory: 14901 loss: 0.8797 loss_prob: 0.4571 loss_thr: 0.3426 loss_db: 0.0800 2022/11/03 02:36:39 - mmengine - INFO - Epoch(train) [1181][55/63] lr: 5.1979e-05 eta: 0:13:16 time: 0.4773 data_time: 0.0323 memory: 14901 loss: 0.8622 loss_prob: 0.4580 loss_thr: 0.3243 loss_db: 0.0799 2022/11/03 02:36:42 - mmengine - INFO - Epoch(train) [1181][60/63] lr: 5.1979e-05 eta: 0:13:09 time: 0.4847 data_time: 0.0127 memory: 14901 loss: 0.8338 loss_prob: 0.4344 loss_thr: 0.3231 loss_db: 0.0763 2022/11/03 02:36:43 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:36:47 - mmengine - INFO - Epoch(train) [1182][5/63] lr: 4.9515e-05 eta: 0:13:09 time: 0.6609 data_time: 0.1640 memory: 14901 loss: 0.8388 loss_prob: 0.4352 loss_thr: 0.3271 loss_db: 0.0765 2022/11/03 02:36:50 - mmengine - INFO - Epoch(train) [1182][10/63] lr: 4.9515e-05 eta: 0:13:01 time: 0.6991 data_time: 0.1710 memory: 14901 loss: 0.7553 loss_prob: 0.3850 loss_thr: 0.3020 loss_db: 0.0684 2022/11/03 02:36:52 - mmengine - INFO - Epoch(train) [1182][15/63] lr: 4.9515e-05 eta: 0:13:01 time: 0.4881 data_time: 0.0130 memory: 14901 loss: 0.7908 loss_prob: 0.4034 loss_thr: 0.3158 loss_db: 0.0716 2022/11/03 02:36:55 - mmengine - INFO - Epoch(train) [1182][20/63] lr: 4.9515e-05 eta: 0:12:54 time: 0.4701 data_time: 0.0067 memory: 14901 loss: 0.8706 loss_prob: 0.4416 loss_thr: 0.3512 loss_db: 0.0778 2022/11/03 02:36:57 - mmengine - INFO - Epoch(train) [1182][25/63] lr: 4.9515e-05 eta: 0:12:54 time: 0.5084 data_time: 0.0223 memory: 14901 loss: 0.9182 loss_prob: 0.4786 loss_thr: 0.3575 loss_db: 0.0821 2022/11/03 02:37:00 - mmengine - INFO - Epoch(train) [1182][30/63] lr: 4.9515e-05 eta: 0:12:47 time: 0.4986 data_time: 0.0267 memory: 14901 loss: 0.8349 loss_prob: 0.4363 loss_thr: 0.3241 loss_db: 0.0745 2022/11/03 02:37:02 - mmengine - INFO - Epoch(train) [1182][35/63] lr: 4.9515e-05 eta: 0:12:47 time: 0.4687 data_time: 0.0183 memory: 14901 loss: 0.7548 loss_prob: 0.3830 loss_thr: 0.3041 loss_db: 0.0678 2022/11/03 02:37:04 - mmengine - INFO - Epoch(train) [1182][40/63] lr: 4.9515e-05 eta: 0:12:41 time: 0.4570 data_time: 0.0136 memory: 14901 loss: 0.8580 loss_prob: 0.4492 loss_thr: 0.3299 loss_db: 0.0789 2022/11/03 02:37:07 - mmengine - INFO - Epoch(train) [1182][45/63] lr: 4.9515e-05 eta: 0:12:41 time: 0.4841 data_time: 0.0052 memory: 14901 loss: 0.8690 loss_prob: 0.4569 loss_thr: 0.3320 loss_db: 0.0801 2022/11/03 02:37:09 - mmengine - INFO - Epoch(train) [1182][50/63] lr: 4.9515e-05 eta: 0:12:34 time: 0.4843 data_time: 0.0184 memory: 14901 loss: 0.8583 loss_prob: 0.4458 loss_thr: 0.3341 loss_db: 0.0785 2022/11/03 02:37:11 - mmengine - INFO - Epoch(train) [1182][55/63] lr: 4.9515e-05 eta: 0:12:34 time: 0.4689 data_time: 0.0224 memory: 14901 loss: 0.8264 loss_prob: 0.4210 loss_thr: 0.3315 loss_db: 0.0738 2022/11/03 02:37:14 - mmengine - INFO - Epoch(train) [1182][60/63] lr: 4.9515e-05 eta: 0:12:28 time: 0.4648 data_time: 0.0147 memory: 14901 loss: 0.7817 loss_prob: 0.3971 loss_thr: 0.3151 loss_db: 0.0695 2022/11/03 02:37:15 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:37:19 - mmengine - INFO - Epoch(train) [1183][5/63] lr: 4.7037e-05 eta: 0:12:28 time: 0.6218 data_time: 0.1936 memory: 14901 loss: 0.7811 loss_prob: 0.4054 loss_thr: 0.3042 loss_db: 0.0715 2022/11/03 02:37:22 - mmengine - INFO - Epoch(train) [1183][10/63] lr: 4.7037e-05 eta: 0:12:19 time: 0.6685 data_time: 0.1944 memory: 14901 loss: 0.8419 loss_prob: 0.4331 loss_thr: 0.3335 loss_db: 0.0754 2022/11/03 02:37:24 - mmengine - INFO - Epoch(train) [1183][15/63] lr: 4.7037e-05 eta: 0:12:19 time: 0.4906 data_time: 0.0103 memory: 14901 loss: 0.8847 loss_prob: 0.4558 loss_thr: 0.3494 loss_db: 0.0796 2022/11/03 02:37:26 - mmengine - INFO - Epoch(train) [1183][20/63] lr: 4.7037e-05 eta: 0:12:12 time: 0.4570 data_time: 0.0083 memory: 14901 loss: 0.8291 loss_prob: 0.4247 loss_thr: 0.3299 loss_db: 0.0745 2022/11/03 02:37:29 - mmengine - INFO - Epoch(train) [1183][25/63] lr: 4.7037e-05 eta: 0:12:12 time: 0.5386 data_time: 0.0333 memory: 14901 loss: 0.7688 loss_prob: 0.3878 loss_thr: 0.3134 loss_db: 0.0676 2022/11/03 02:37:32 - mmengine - INFO - Epoch(train) [1183][30/63] lr: 4.7037e-05 eta: 0:12:06 time: 0.5675 data_time: 0.0332 memory: 14901 loss: 0.8808 loss_prob: 0.4532 loss_thr: 0.3491 loss_db: 0.0785 2022/11/03 02:37:34 - mmengine - INFO - Epoch(train) [1183][35/63] lr: 4.7037e-05 eta: 0:12:06 time: 0.4845 data_time: 0.0148 memory: 14901 loss: 0.8932 loss_prob: 0.4623 loss_thr: 0.3495 loss_db: 0.0814 2022/11/03 02:37:37 - mmengine - INFO - Epoch(train) [1183][40/63] lr: 4.7037e-05 eta: 0:11:59 time: 0.4704 data_time: 0.0171 memory: 14901 loss: 0.8657 loss_prob: 0.4494 loss_thr: 0.3373 loss_db: 0.0790 2022/11/03 02:37:39 - mmengine - INFO - Epoch(train) [1183][45/63] lr: 4.7037e-05 eta: 0:11:59 time: 0.4716 data_time: 0.0076 memory: 14901 loss: 0.8543 loss_prob: 0.4444 loss_thr: 0.3329 loss_db: 0.0770 2022/11/03 02:37:41 - mmengine - INFO - Epoch(train) [1183][50/63] lr: 4.7037e-05 eta: 0:11:53 time: 0.4693 data_time: 0.0183 memory: 14901 loss: 0.8676 loss_prob: 0.4469 loss_thr: 0.3417 loss_db: 0.0790 2022/11/03 02:37:44 - mmengine - INFO - Epoch(train) [1183][55/63] lr: 4.7037e-05 eta: 0:11:53 time: 0.4707 data_time: 0.0193 memory: 14901 loss: 0.9001 loss_prob: 0.4651 loss_thr: 0.3537 loss_db: 0.0813 2022/11/03 02:37:46 - mmengine - INFO - Epoch(train) [1183][60/63] lr: 4.7037e-05 eta: 0:11:46 time: 0.4845 data_time: 0.0107 memory: 14901 loss: 0.8276 loss_prob: 0.4268 loss_thr: 0.3281 loss_db: 0.0726 2022/11/03 02:37:47 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:37:52 - mmengine - INFO - Epoch(train) [1184][5/63] lr: 4.4545e-05 eta: 0:11:46 time: 0.6590 data_time: 0.1833 memory: 14901 loss: 0.8305 loss_prob: 0.4413 loss_thr: 0.3130 loss_db: 0.0762 2022/11/03 02:37:54 - mmengine - INFO - Epoch(train) [1184][10/63] lr: 4.4545e-05 eta: 0:11:37 time: 0.6620 data_time: 0.1833 memory: 14901 loss: 0.8521 loss_prob: 0.4446 loss_thr: 0.3298 loss_db: 0.0777 2022/11/03 02:37:56 - mmengine - INFO - Epoch(train) [1184][15/63] lr: 4.4545e-05 eta: 0:11:37 time: 0.4884 data_time: 0.0121 memory: 14901 loss: 0.8141 loss_prob: 0.4088 loss_thr: 0.3334 loss_db: 0.0720 2022/11/03 02:37:59 - mmengine - INFO - Epoch(train) [1184][20/63] lr: 4.4545e-05 eta: 0:11:31 time: 0.4986 data_time: 0.0110 memory: 14901 loss: 0.8641 loss_prob: 0.4373 loss_thr: 0.3493 loss_db: 0.0775 2022/11/03 02:38:02 - mmengine - INFO - Epoch(train) [1184][25/63] lr: 4.4545e-05 eta: 0:11:31 time: 0.5077 data_time: 0.0304 memory: 14901 loss: 0.9284 loss_prob: 0.4777 loss_thr: 0.3667 loss_db: 0.0840 2022/11/03 02:38:04 - mmengine - INFO - Epoch(train) [1184][30/63] lr: 4.4545e-05 eta: 0:11:24 time: 0.5058 data_time: 0.0306 memory: 14901 loss: 0.8329 loss_prob: 0.4261 loss_thr: 0.3325 loss_db: 0.0743 2022/11/03 02:38:06 - mmengine - INFO - Epoch(train) [1184][35/63] lr: 4.4545e-05 eta: 0:11:24 time: 0.4771 data_time: 0.0070 memory: 14901 loss: 0.8430 loss_prob: 0.4364 loss_thr: 0.3295 loss_db: 0.0771 2022/11/03 02:38:09 - mmengine - INFO - Epoch(train) [1184][40/63] lr: 4.4545e-05 eta: 0:11:18 time: 0.4811 data_time: 0.0118 memory: 14901 loss: 0.9283 loss_prob: 0.4861 loss_thr: 0.3571 loss_db: 0.0851 2022/11/03 02:38:11 - mmengine - INFO - Epoch(train) [1184][45/63] lr: 4.4545e-05 eta: 0:11:18 time: 0.4743 data_time: 0.0102 memory: 14901 loss: 0.9208 loss_prob: 0.4789 loss_thr: 0.3592 loss_db: 0.0827 2022/11/03 02:38:13 - mmengine - INFO - Epoch(train) [1184][50/63] lr: 4.4545e-05 eta: 0:11:11 time: 0.4701 data_time: 0.0195 memory: 14901 loss: 0.8473 loss_prob: 0.4351 loss_thr: 0.3359 loss_db: 0.0762 2022/11/03 02:38:16 - mmengine - INFO - Epoch(train) [1184][55/63] lr: 4.4545e-05 eta: 0:11:11 time: 0.4876 data_time: 0.0196 memory: 14901 loss: 0.8434 loss_prob: 0.4210 loss_thr: 0.3478 loss_db: 0.0746 2022/11/03 02:38:19 - mmengine - INFO - Epoch(train) [1184][60/63] lr: 4.4545e-05 eta: 0:11:04 time: 0.5191 data_time: 0.0066 memory: 14901 loss: 0.8758 loss_prob: 0.4333 loss_thr: 0.3656 loss_db: 0.0769 2022/11/03 02:38:20 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:38:25 - mmengine - INFO - Epoch(train) [1185][5/63] lr: 4.2037e-05 eta: 0:11:04 time: 0.6863 data_time: 0.1927 memory: 14901 loss: 0.8583 loss_prob: 0.4355 loss_thr: 0.3450 loss_db: 0.0778 2022/11/03 02:38:27 - mmengine - INFO - Epoch(train) [1185][10/63] lr: 4.2037e-05 eta: 0:10:56 time: 0.7062 data_time: 0.1900 memory: 14901 loss: 0.8648 loss_prob: 0.4410 loss_thr: 0.3460 loss_db: 0.0778 2022/11/03 02:38:29 - mmengine - INFO - Epoch(train) [1185][15/63] lr: 4.2037e-05 eta: 0:10:56 time: 0.4720 data_time: 0.0059 memory: 14901 loss: 0.7850 loss_prob: 0.4013 loss_thr: 0.3138 loss_db: 0.0699 2022/11/03 02:38:32 - mmengine - INFO - Epoch(train) [1185][20/63] lr: 4.2037e-05 eta: 0:10:49 time: 0.4743 data_time: 0.0059 memory: 14901 loss: 0.8515 loss_prob: 0.4415 loss_thr: 0.3334 loss_db: 0.0766 2022/11/03 02:38:34 - mmengine - INFO - Epoch(train) [1185][25/63] lr: 4.2037e-05 eta: 0:10:49 time: 0.4817 data_time: 0.0234 memory: 14901 loss: 0.9548 loss_prob: 0.4964 loss_thr: 0.3716 loss_db: 0.0869 2022/11/03 02:38:37 - mmengine - INFO - Epoch(train) [1185][30/63] lr: 4.2037e-05 eta: 0:10:43 time: 0.4948 data_time: 0.0408 memory: 14901 loss: 0.9173 loss_prob: 0.4770 loss_thr: 0.3563 loss_db: 0.0839 2022/11/03 02:38:39 - mmengine - INFO - Epoch(train) [1185][35/63] lr: 4.2037e-05 eta: 0:10:43 time: 0.5089 data_time: 0.0232 memory: 14901 loss: 0.8375 loss_prob: 0.4367 loss_thr: 0.3246 loss_db: 0.0762 2022/11/03 02:38:42 - mmengine - INFO - Epoch(train) [1185][40/63] lr: 4.2037e-05 eta: 0:10:36 time: 0.4998 data_time: 0.0057 memory: 14901 loss: 0.9033 loss_prob: 0.4752 loss_thr: 0.3460 loss_db: 0.0821 2022/11/03 02:38:44 - mmengine - INFO - Epoch(train) [1185][45/63] lr: 4.2037e-05 eta: 0:10:36 time: 0.4691 data_time: 0.0056 memory: 14901 loss: 0.9079 loss_prob: 0.4725 loss_thr: 0.3527 loss_db: 0.0827 2022/11/03 02:38:46 - mmengine - INFO - Epoch(train) [1185][50/63] lr: 4.2037e-05 eta: 0:10:29 time: 0.4643 data_time: 0.0172 memory: 14901 loss: 0.8445 loss_prob: 0.4321 loss_thr: 0.3367 loss_db: 0.0757 2022/11/03 02:38:49 - mmengine - INFO - Epoch(train) [1185][55/63] lr: 4.2037e-05 eta: 0:10:29 time: 0.4842 data_time: 0.0239 memory: 14901 loss: 0.7904 loss_prob: 0.4038 loss_thr: 0.3160 loss_db: 0.0706 2022/11/03 02:38:51 - mmengine - INFO - Epoch(train) [1185][60/63] lr: 4.2037e-05 eta: 0:10:23 time: 0.4690 data_time: 0.0124 memory: 14901 loss: 0.7777 loss_prob: 0.3980 loss_thr: 0.3097 loss_db: 0.0699 2022/11/03 02:38:52 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:38:56 - mmengine - INFO - Epoch(train) [1186][5/63] lr: 3.9512e-05 eta: 0:10:23 time: 0.6347 data_time: 0.2047 memory: 14901 loss: 0.8342 loss_prob: 0.4334 loss_thr: 0.3258 loss_db: 0.0751 2022/11/03 02:38:59 - mmengine - INFO - Epoch(train) [1186][10/63] lr: 3.9512e-05 eta: 0:10:14 time: 0.6700 data_time: 0.2106 memory: 14901 loss: 0.8360 loss_prob: 0.4362 loss_thr: 0.3247 loss_db: 0.0750 2022/11/03 02:39:01 - mmengine - INFO - Epoch(train) [1186][15/63] lr: 3.9512e-05 eta: 0:10:14 time: 0.4583 data_time: 0.0155 memory: 14901 loss: 0.8326 loss_prob: 0.4350 loss_thr: 0.3222 loss_db: 0.0753 2022/11/03 02:39:03 - mmengine - INFO - Epoch(train) [1186][20/63] lr: 3.9512e-05 eta: 0:10:08 time: 0.4475 data_time: 0.0075 memory: 14901 loss: 0.8309 loss_prob: 0.4294 loss_thr: 0.3266 loss_db: 0.0749 2022/11/03 02:39:06 - mmengine - INFO - Epoch(train) [1186][25/63] lr: 3.9512e-05 eta: 0:10:08 time: 0.4551 data_time: 0.0146 memory: 14901 loss: 0.8641 loss_prob: 0.4432 loss_thr: 0.3436 loss_db: 0.0773 2022/11/03 02:39:08 - mmengine - INFO - Epoch(train) [1186][30/63] lr: 3.9512e-05 eta: 0:10:01 time: 0.5075 data_time: 0.0532 memory: 14901 loss: 0.8910 loss_prob: 0.4570 loss_thr: 0.3532 loss_db: 0.0808 2022/11/03 02:39:11 - mmengine - INFO - Epoch(train) [1186][35/63] lr: 3.9512e-05 eta: 0:10:01 time: 0.5284 data_time: 0.0485 memory: 14901 loss: 0.8607 loss_prob: 0.4388 loss_thr: 0.3437 loss_db: 0.0782 2022/11/03 02:39:13 - mmengine - INFO - Epoch(train) [1186][40/63] lr: 3.9512e-05 eta: 0:09:55 time: 0.4719 data_time: 0.0071 memory: 14901 loss: 0.7873 loss_prob: 0.4023 loss_thr: 0.3135 loss_db: 0.0714 2022/11/03 02:39:15 - mmengine - INFO - Epoch(train) [1186][45/63] lr: 3.9512e-05 eta: 0:09:55 time: 0.4553 data_time: 0.0053 memory: 14901 loss: 0.7321 loss_prob: 0.3739 loss_thr: 0.2930 loss_db: 0.0651 2022/11/03 02:39:18 - mmengine - INFO - Epoch(train) [1186][50/63] lr: 3.9512e-05 eta: 0:09:48 time: 0.4693 data_time: 0.0143 memory: 14901 loss: 0.7204 loss_prob: 0.3626 loss_thr: 0.2949 loss_db: 0.0629 2022/11/03 02:39:20 - mmengine - INFO - Epoch(train) [1186][55/63] lr: 3.9512e-05 eta: 0:09:48 time: 0.4902 data_time: 0.0213 memory: 14901 loss: 0.7832 loss_prob: 0.3934 loss_thr: 0.3214 loss_db: 0.0683 2022/11/03 02:39:23 - mmengine - INFO - Epoch(train) [1186][60/63] lr: 3.9512e-05 eta: 0:09:41 time: 0.4848 data_time: 0.0134 memory: 14901 loss: 0.8707 loss_prob: 0.4425 loss_thr: 0.3521 loss_db: 0.0762 2022/11/03 02:39:24 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:39:28 - mmengine - INFO - Epoch(train) [1187][5/63] lr: 3.6969e-05 eta: 0:09:41 time: 0.6115 data_time: 0.1763 memory: 14901 loss: 0.9068 loss_prob: 0.4687 loss_thr: 0.3557 loss_db: 0.0824 2022/11/03 02:39:30 - mmengine - INFO - Epoch(train) [1187][10/63] lr: 3.6969e-05 eta: 0:09:33 time: 0.6679 data_time: 0.1891 memory: 14901 loss: 0.8981 loss_prob: 0.4675 loss_thr: 0.3489 loss_db: 0.0816 2022/11/03 02:39:33 - mmengine - INFO - Epoch(train) [1187][15/63] lr: 3.6969e-05 eta: 0:09:33 time: 0.4822 data_time: 0.0175 memory: 14901 loss: 0.8882 loss_prob: 0.4605 loss_thr: 0.3460 loss_db: 0.0818 2022/11/03 02:39:35 - mmengine - INFO - Epoch(train) [1187][20/63] lr: 3.6969e-05 eta: 0:09:26 time: 0.4812 data_time: 0.0048 memory: 14901 loss: 0.8770 loss_prob: 0.4503 loss_thr: 0.3470 loss_db: 0.0796 2022/11/03 02:39:38 - mmengine - INFO - Epoch(train) [1187][25/63] lr: 3.6969e-05 eta: 0:09:26 time: 0.5133 data_time: 0.0132 memory: 14901 loss: 0.8749 loss_prob: 0.4518 loss_thr: 0.3448 loss_db: 0.0782 2022/11/03 02:39:40 - mmengine - INFO - Epoch(train) [1187][30/63] lr: 3.6969e-05 eta: 0:09:20 time: 0.5009 data_time: 0.0245 memory: 14901 loss: 0.9498 loss_prob: 0.5025 loss_thr: 0.3607 loss_db: 0.0866 2022/11/03 02:39:43 - mmengine - INFO - Epoch(train) [1187][35/63] lr: 3.6969e-05 eta: 0:09:20 time: 0.4974 data_time: 0.0296 memory: 14901 loss: 1.0157 loss_prob: 0.5371 loss_thr: 0.3868 loss_db: 0.0918 2022/11/03 02:39:45 - mmengine - INFO - Epoch(train) [1187][40/63] lr: 3.6969e-05 eta: 0:09:13 time: 0.5126 data_time: 0.0187 memory: 14901 loss: 0.9067 loss_prob: 0.4639 loss_thr: 0.3613 loss_db: 0.0814 2022/11/03 02:39:48 - mmengine - INFO - Epoch(train) [1187][45/63] lr: 3.6969e-05 eta: 0:09:13 time: 0.4820 data_time: 0.0056 memory: 14901 loss: 0.8839 loss_prob: 0.4573 loss_thr: 0.3469 loss_db: 0.0797 2022/11/03 02:39:50 - mmengine - INFO - Epoch(train) [1187][50/63] lr: 3.6969e-05 eta: 0:09:06 time: 0.4760 data_time: 0.0115 memory: 14901 loss: 0.9590 loss_prob: 0.5104 loss_thr: 0.3626 loss_db: 0.0860 2022/11/03 02:39:53 - mmengine - INFO - Epoch(train) [1187][55/63] lr: 3.6969e-05 eta: 0:09:06 time: 0.4877 data_time: 0.0154 memory: 14901 loss: 0.8703 loss_prob: 0.4517 loss_thr: 0.3405 loss_db: 0.0782 2022/11/03 02:39:55 - mmengine - INFO - Epoch(train) [1187][60/63] lr: 3.6969e-05 eta: 0:09:00 time: 0.4769 data_time: 0.0168 memory: 14901 loss: 0.7719 loss_prob: 0.3959 loss_thr: 0.3069 loss_db: 0.0691 2022/11/03 02:39:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:40:00 - mmengine - INFO - Epoch(train) [1188][5/63] lr: 3.4406e-05 eta: 0:09:00 time: 0.6525 data_time: 0.1707 memory: 14901 loss: 0.7796 loss_prob: 0.3923 loss_thr: 0.3190 loss_db: 0.0683 2022/11/03 02:40:03 - mmengine - INFO - Epoch(train) [1188][10/63] lr: 3.4406e-05 eta: 0:08:51 time: 0.6734 data_time: 0.1743 memory: 14901 loss: 0.8090 loss_prob: 0.4138 loss_thr: 0.3232 loss_db: 0.0721 2022/11/03 02:40:05 - mmengine - INFO - Epoch(train) [1188][15/63] lr: 3.4406e-05 eta: 0:08:51 time: 0.4884 data_time: 0.0142 memory: 14901 loss: 0.8273 loss_prob: 0.4300 loss_thr: 0.3222 loss_db: 0.0750 2022/11/03 02:40:08 - mmengine - INFO - Epoch(train) [1188][20/63] lr: 3.4406e-05 eta: 0:08:45 time: 0.4833 data_time: 0.0101 memory: 14901 loss: 0.8350 loss_prob: 0.4344 loss_thr: 0.3244 loss_db: 0.0761 2022/11/03 02:40:10 - mmengine - INFO - Epoch(train) [1188][25/63] lr: 3.4406e-05 eta: 0:08:45 time: 0.4706 data_time: 0.0130 memory: 14901 loss: 0.7809 loss_prob: 0.3988 loss_thr: 0.3118 loss_db: 0.0703 2022/11/03 02:40:13 - mmengine - INFO - Epoch(train) [1188][30/63] lr: 3.4406e-05 eta: 0:08:38 time: 0.5070 data_time: 0.0266 memory: 14901 loss: 0.7574 loss_prob: 0.3823 loss_thr: 0.3081 loss_db: 0.0670 2022/11/03 02:40:15 - mmengine - INFO - Epoch(train) [1188][35/63] lr: 3.4406e-05 eta: 0:08:38 time: 0.5182 data_time: 0.0286 memory: 14901 loss: 0.8308 loss_prob: 0.4273 loss_thr: 0.3302 loss_db: 0.0733 2022/11/03 02:40:18 - mmengine - INFO - Epoch(train) [1188][40/63] lr: 3.4406e-05 eta: 0:08:31 time: 0.5052 data_time: 0.0295 memory: 14901 loss: 0.8819 loss_prob: 0.4520 loss_thr: 0.3523 loss_db: 0.0776 2022/11/03 02:40:20 - mmengine - INFO - Epoch(train) [1188][45/63] lr: 3.4406e-05 eta: 0:08:31 time: 0.5022 data_time: 0.0210 memory: 14901 loss: 0.8724 loss_prob: 0.4485 loss_thr: 0.3459 loss_db: 0.0781 2022/11/03 02:40:23 - mmengine - INFO - Epoch(train) [1188][50/63] lr: 3.4406e-05 eta: 0:08:25 time: 0.4756 data_time: 0.0062 memory: 14901 loss: 0.8584 loss_prob: 0.4462 loss_thr: 0.3328 loss_db: 0.0793 2022/11/03 02:40:25 - mmengine - INFO - Epoch(train) [1188][55/63] lr: 3.4406e-05 eta: 0:08:25 time: 0.4736 data_time: 0.0042 memory: 14901 loss: 0.8102 loss_prob: 0.4115 loss_thr: 0.3267 loss_db: 0.0720 2022/11/03 02:40:28 - mmengine - INFO - Epoch(train) [1188][60/63] lr: 3.4406e-05 eta: 0:08:18 time: 0.4852 data_time: 0.0062 memory: 14901 loss: 0.7386 loss_prob: 0.3666 loss_thr: 0.3092 loss_db: 0.0628 2022/11/03 02:40:29 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:40:33 - mmengine - INFO - Epoch(train) [1189][5/63] lr: 3.1822e-05 eta: 0:08:18 time: 0.6637 data_time: 0.2240 memory: 14901 loss: 0.9028 loss_prob: 0.4650 loss_thr: 0.3560 loss_db: 0.0818 2022/11/03 02:40:36 - mmengine - INFO - Epoch(train) [1189][10/63] lr: 3.1822e-05 eta: 0:08:10 time: 0.7009 data_time: 0.2245 memory: 14901 loss: 0.8416 loss_prob: 0.4279 loss_thr: 0.3359 loss_db: 0.0778 2022/11/03 02:40:38 - mmengine - INFO - Epoch(train) [1189][15/63] lr: 3.1822e-05 eta: 0:08:10 time: 0.5120 data_time: 0.0093 memory: 14901 loss: 0.8373 loss_prob: 0.4305 loss_thr: 0.3315 loss_db: 0.0753 2022/11/03 02:40:41 - mmengine - INFO - Epoch(train) [1189][20/63] lr: 3.1822e-05 eta: 0:08:03 time: 0.5053 data_time: 0.0089 memory: 14901 loss: 0.8912 loss_prob: 0.4592 loss_thr: 0.3525 loss_db: 0.0795 2022/11/03 02:40:43 - mmengine - INFO - Epoch(train) [1189][25/63] lr: 3.1822e-05 eta: 0:08:03 time: 0.4742 data_time: 0.0219 memory: 14901 loss: 0.8738 loss_prob: 0.4487 loss_thr: 0.3476 loss_db: 0.0776 2022/11/03 02:40:46 - mmengine - INFO - Epoch(train) [1189][30/63] lr: 3.1822e-05 eta: 0:07:57 time: 0.5110 data_time: 0.0202 memory: 14901 loss: 0.8849 loss_prob: 0.4609 loss_thr: 0.3445 loss_db: 0.0796 2022/11/03 02:40:49 - mmengine - INFO - Epoch(train) [1189][35/63] lr: 3.1822e-05 eta: 0:07:57 time: 0.5509 data_time: 0.0210 memory: 14901 loss: 0.8511 loss_prob: 0.4419 loss_thr: 0.3313 loss_db: 0.0778 2022/11/03 02:40:51 - mmengine - INFO - Epoch(train) [1189][40/63] lr: 3.1822e-05 eta: 0:07:50 time: 0.5273 data_time: 0.0214 memory: 14901 loss: 0.8131 loss_prob: 0.4237 loss_thr: 0.3149 loss_db: 0.0745 2022/11/03 02:40:53 - mmengine - INFO - Epoch(train) [1189][45/63] lr: 3.1822e-05 eta: 0:07:50 time: 0.4864 data_time: 0.0087 memory: 14901 loss: 0.8858 loss_prob: 0.4654 loss_thr: 0.3390 loss_db: 0.0815 2022/11/03 02:40:56 - mmengine - INFO - Epoch(train) [1189][50/63] lr: 3.1822e-05 eta: 0:07:43 time: 0.4763 data_time: 0.0173 memory: 14901 loss: 0.8654 loss_prob: 0.4478 loss_thr: 0.3402 loss_db: 0.0775 2022/11/03 02:40:58 - mmengine - INFO - Epoch(train) [1189][55/63] lr: 3.1822e-05 eta: 0:07:43 time: 0.4566 data_time: 0.0143 memory: 14901 loss: 0.8073 loss_prob: 0.4078 loss_thr: 0.3292 loss_db: 0.0703 2022/11/03 02:41:00 - mmengine - INFO - Epoch(train) [1189][60/63] lr: 3.1822e-05 eta: 0:07:37 time: 0.4521 data_time: 0.0119 memory: 14901 loss: 0.8558 loss_prob: 0.4342 loss_thr: 0.3454 loss_db: 0.0762 2022/11/03 02:41:01 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:41:06 - mmengine - INFO - Epoch(train) [1190][5/63] lr: 2.9215e-05 eta: 0:07:37 time: 0.6462 data_time: 0.2019 memory: 14901 loss: 0.9008 loss_prob: 0.4665 loss_thr: 0.3524 loss_db: 0.0819 2022/11/03 02:41:08 - mmengine - INFO - Epoch(train) [1190][10/63] lr: 2.9215e-05 eta: 0:07:28 time: 0.6906 data_time: 0.2070 memory: 14901 loss: 0.8900 loss_prob: 0.4551 loss_thr: 0.3569 loss_db: 0.0780 2022/11/03 02:41:11 - mmengine - INFO - Epoch(train) [1190][15/63] lr: 2.9215e-05 eta: 0:07:28 time: 0.4738 data_time: 0.0101 memory: 14901 loss: 0.8094 loss_prob: 0.4114 loss_thr: 0.3267 loss_db: 0.0713 2022/11/03 02:41:13 - mmengine - INFO - Epoch(train) [1190][20/63] lr: 2.9215e-05 eta: 0:07:22 time: 0.4602 data_time: 0.0052 memory: 14901 loss: 0.8044 loss_prob: 0.4221 loss_thr: 0.3076 loss_db: 0.0747 2022/11/03 02:41:15 - mmengine - INFO - Epoch(train) [1190][25/63] lr: 2.9215e-05 eta: 0:07:22 time: 0.4760 data_time: 0.0257 memory: 14901 loss: 0.8463 loss_prob: 0.4382 loss_thr: 0.3311 loss_db: 0.0770 2022/11/03 02:41:18 - mmengine - INFO - Epoch(train) [1190][30/63] lr: 2.9215e-05 eta: 0:07:15 time: 0.4777 data_time: 0.0294 memory: 14901 loss: 0.8272 loss_prob: 0.4237 loss_thr: 0.3299 loss_db: 0.0736 2022/11/03 02:41:20 - mmengine - INFO - Epoch(train) [1190][35/63] lr: 2.9215e-05 eta: 0:07:15 time: 0.4776 data_time: 0.0136 memory: 14901 loss: 0.9147 loss_prob: 0.4770 loss_thr: 0.3549 loss_db: 0.0829 2022/11/03 02:41:23 - mmengine - INFO - Epoch(train) [1190][40/63] lr: 2.9215e-05 eta: 0:07:08 time: 0.4943 data_time: 0.0101 memory: 14901 loss: 0.9698 loss_prob: 0.5097 loss_thr: 0.3697 loss_db: 0.0904 2022/11/03 02:41:25 - mmengine - INFO - Epoch(train) [1190][45/63] lr: 2.9215e-05 eta: 0:07:08 time: 0.4806 data_time: 0.0055 memory: 14901 loss: 0.8877 loss_prob: 0.4603 loss_thr: 0.3449 loss_db: 0.0825 2022/11/03 02:41:28 - mmengine - INFO - Epoch(train) [1190][50/63] lr: 2.9215e-05 eta: 0:07:02 time: 0.4940 data_time: 0.0264 memory: 14901 loss: 0.8183 loss_prob: 0.4176 loss_thr: 0.3251 loss_db: 0.0756 2022/11/03 02:41:30 - mmengine - INFO - Epoch(train) [1190][55/63] lr: 2.9215e-05 eta: 0:07:02 time: 0.4842 data_time: 0.0281 memory: 14901 loss: 0.8048 loss_prob: 0.4106 loss_thr: 0.3195 loss_db: 0.0747 2022/11/03 02:41:32 - mmengine - INFO - Epoch(train) [1190][60/63] lr: 2.9215e-05 eta: 0:06:55 time: 0.4618 data_time: 0.0068 memory: 14901 loss: 0.8544 loss_prob: 0.4351 loss_thr: 0.3427 loss_db: 0.0766 2022/11/03 02:41:33 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:41:38 - mmengine - INFO - Epoch(train) [1191][5/63] lr: 2.6581e-05 eta: 0:06:55 time: 0.6315 data_time: 0.1804 memory: 14901 loss: 0.8093 loss_prob: 0.4117 loss_thr: 0.3261 loss_db: 0.0715 2022/11/03 02:41:40 - mmengine - INFO - Epoch(train) [1191][10/63] lr: 2.6581e-05 eta: 0:06:47 time: 0.6607 data_time: 0.1841 memory: 14901 loss: 0.8355 loss_prob: 0.4311 loss_thr: 0.3299 loss_db: 0.0745 2022/11/03 02:41:42 - mmengine - INFO - Epoch(train) [1191][15/63] lr: 2.6581e-05 eta: 0:06:47 time: 0.4641 data_time: 0.0093 memory: 14901 loss: 0.8065 loss_prob: 0.4137 loss_thr: 0.3208 loss_db: 0.0720 2022/11/03 02:41:44 - mmengine - INFO - Epoch(train) [1191][20/63] lr: 2.6581e-05 eta: 0:06:40 time: 0.4481 data_time: 0.0062 memory: 14901 loss: 0.8213 loss_prob: 0.4191 loss_thr: 0.3283 loss_db: 0.0739 2022/11/03 02:41:47 - mmengine - INFO - Epoch(train) [1191][25/63] lr: 2.6581e-05 eta: 0:06:40 time: 0.4853 data_time: 0.0103 memory: 14901 loss: 0.8343 loss_prob: 0.4229 loss_thr: 0.3373 loss_db: 0.0741 2022/11/03 02:41:50 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:41:50 - mmengine - INFO - Epoch(train) [1191][30/63] lr: 2.6581e-05 eta: 0:06:34 time: 0.5271 data_time: 0.0278 memory: 14901 loss: 0.8310 loss_prob: 0.4246 loss_thr: 0.3322 loss_db: 0.0743 2022/11/03 02:41:52 - mmengine - INFO - Epoch(train) [1191][35/63] lr: 2.6581e-05 eta: 0:06:34 time: 0.5208 data_time: 0.0254 memory: 14901 loss: 0.8608 loss_prob: 0.4496 loss_thr: 0.3320 loss_db: 0.0792 2022/11/03 02:41:55 - mmengine - INFO - Epoch(train) [1191][40/63] lr: 2.6581e-05 eta: 0:06:27 time: 0.4859 data_time: 0.0083 memory: 14901 loss: 0.8153 loss_prob: 0.4163 loss_thr: 0.3248 loss_db: 0.0742 2022/11/03 02:41:57 - mmengine - INFO - Epoch(train) [1191][45/63] lr: 2.6581e-05 eta: 0:06:27 time: 0.5143 data_time: 0.0070 memory: 14901 loss: 0.8541 loss_prob: 0.4369 loss_thr: 0.3397 loss_db: 0.0775 2022/11/03 02:42:00 - mmengine - INFO - Epoch(train) [1191][50/63] lr: 2.6581e-05 eta: 0:06:20 time: 0.5272 data_time: 0.0094 memory: 14901 loss: 0.8428 loss_prob: 0.4314 loss_thr: 0.3351 loss_db: 0.0763 2022/11/03 02:42:02 - mmengine - INFO - Epoch(train) [1191][55/63] lr: 2.6581e-05 eta: 0:06:20 time: 0.5011 data_time: 0.0192 memory: 14901 loss: 0.7769 loss_prob: 0.3948 loss_thr: 0.3122 loss_db: 0.0699 2022/11/03 02:42:05 - mmengine - INFO - Epoch(train) [1191][60/63] lr: 2.6581e-05 eta: 0:06:14 time: 0.4870 data_time: 0.0176 memory: 14901 loss: 0.8285 loss_prob: 0.4229 loss_thr: 0.3319 loss_db: 0.0738 2022/11/03 02:42:06 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:42:10 - mmengine - INFO - Epoch(train) [1192][5/63] lr: 2.3917e-05 eta: 0:06:14 time: 0.6536 data_time: 0.1985 memory: 14901 loss: 0.9267 loss_prob: 0.4964 loss_thr: 0.3462 loss_db: 0.0841 2022/11/03 02:42:13 - mmengine - INFO - Epoch(train) [1192][10/63] lr: 2.3917e-05 eta: 0:06:05 time: 0.6957 data_time: 0.1982 memory: 14901 loss: 0.8685 loss_prob: 0.4608 loss_thr: 0.3293 loss_db: 0.0784 2022/11/03 02:42:15 - mmengine - INFO - Epoch(train) [1192][15/63] lr: 2.3917e-05 eta: 0:06:05 time: 0.4784 data_time: 0.0065 memory: 14901 loss: 0.8129 loss_prob: 0.4195 loss_thr: 0.3197 loss_db: 0.0738 2022/11/03 02:42:18 - mmengine - INFO - Epoch(train) [1192][20/63] lr: 2.3917e-05 eta: 0:05:59 time: 0.4752 data_time: 0.0060 memory: 14901 loss: 0.8950 loss_prob: 0.4689 loss_thr: 0.3451 loss_db: 0.0810 2022/11/03 02:42:20 - mmengine - INFO - Epoch(train) [1192][25/63] lr: 2.3917e-05 eta: 0:05:59 time: 0.5098 data_time: 0.0429 memory: 14901 loss: 0.8299 loss_prob: 0.4228 loss_thr: 0.3342 loss_db: 0.0729 2022/11/03 02:42:23 - mmengine - INFO - Epoch(train) [1192][30/63] lr: 2.3917e-05 eta: 0:05:52 time: 0.4956 data_time: 0.0545 memory: 14901 loss: 0.7814 loss_prob: 0.3962 loss_thr: 0.3158 loss_db: 0.0694 2022/11/03 02:42:25 - mmengine - INFO - Epoch(train) [1192][35/63] lr: 2.3917e-05 eta: 0:05:52 time: 0.4596 data_time: 0.0169 memory: 14901 loss: 0.8187 loss_prob: 0.4186 loss_thr: 0.3254 loss_db: 0.0747 2022/11/03 02:42:27 - mmengine - INFO - Epoch(train) [1192][40/63] lr: 2.3917e-05 eta: 0:05:46 time: 0.4770 data_time: 0.0051 memory: 14901 loss: 0.7890 loss_prob: 0.3981 loss_thr: 0.3202 loss_db: 0.0706 2022/11/03 02:42:30 - mmengine - INFO - Epoch(train) [1192][45/63] lr: 2.3917e-05 eta: 0:05:46 time: 0.4838 data_time: 0.0063 memory: 14901 loss: 0.8050 loss_prob: 0.4150 loss_thr: 0.3179 loss_db: 0.0722 2022/11/03 02:42:32 - mmengine - INFO - Epoch(train) [1192][50/63] lr: 2.3917e-05 eta: 0:05:39 time: 0.4922 data_time: 0.0213 memory: 14901 loss: 0.8451 loss_prob: 0.4402 loss_thr: 0.3279 loss_db: 0.0770 2022/11/03 02:42:35 - mmengine - INFO - Epoch(train) [1192][55/63] lr: 2.3917e-05 eta: 0:05:39 time: 0.4956 data_time: 0.0240 memory: 14901 loss: 0.8467 loss_prob: 0.4321 loss_thr: 0.3386 loss_db: 0.0760 2022/11/03 02:42:37 - mmengine - INFO - Epoch(train) [1192][60/63] lr: 2.3917e-05 eta: 0:05:32 time: 0.4735 data_time: 0.0091 memory: 14901 loss: 0.8351 loss_prob: 0.4247 loss_thr: 0.3364 loss_db: 0.0740 2022/11/03 02:42:38 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:42:43 - mmengine - INFO - Epoch(train) [1193][5/63] lr: 2.1220e-05 eta: 0:05:32 time: 0.6702 data_time: 0.1922 memory: 14901 loss: 0.8599 loss_prob: 0.4440 loss_thr: 0.3393 loss_db: 0.0766 2022/11/03 02:42:45 - mmengine - INFO - Epoch(train) [1193][10/63] lr: 2.1220e-05 eta: 0:05:24 time: 0.7072 data_time: 0.1928 memory: 14901 loss: 0.7700 loss_prob: 0.3884 loss_thr: 0.3149 loss_db: 0.0667 2022/11/03 02:42:48 - mmengine - INFO - Epoch(train) [1193][15/63] lr: 2.1220e-05 eta: 0:05:24 time: 0.5026 data_time: 0.0077 memory: 14901 loss: 0.7803 loss_prob: 0.3938 loss_thr: 0.3179 loss_db: 0.0686 2022/11/03 02:42:50 - mmengine - INFO - Epoch(train) [1193][20/63] lr: 2.1220e-05 eta: 0:05:17 time: 0.4894 data_time: 0.0065 memory: 14901 loss: 0.8551 loss_prob: 0.4398 loss_thr: 0.3390 loss_db: 0.0763 2022/11/03 02:42:53 - mmengine - INFO - Epoch(train) [1193][25/63] lr: 2.1220e-05 eta: 0:05:17 time: 0.4934 data_time: 0.0221 memory: 14901 loss: 0.9269 loss_prob: 0.4924 loss_thr: 0.3541 loss_db: 0.0804 2022/11/03 02:42:55 - mmengine - INFO - Epoch(train) [1193][30/63] lr: 2.1220e-05 eta: 0:05:11 time: 0.5289 data_time: 0.0313 memory: 14901 loss: 0.8776 loss_prob: 0.4624 loss_thr: 0.3391 loss_db: 0.0761 2022/11/03 02:42:58 - mmengine - INFO - Epoch(train) [1193][35/63] lr: 2.1220e-05 eta: 0:05:11 time: 0.5011 data_time: 0.0174 memory: 14901 loss: 0.8994 loss_prob: 0.4629 loss_thr: 0.3552 loss_db: 0.0813 2022/11/03 02:43:00 - mmengine - INFO - Epoch(train) [1193][40/63] lr: 2.1220e-05 eta: 0:05:04 time: 0.4636 data_time: 0.0082 memory: 14901 loss: 0.9562 loss_prob: 0.5034 loss_thr: 0.3636 loss_db: 0.0892 2022/11/03 02:43:02 - mmengine - INFO - Epoch(train) [1193][45/63] lr: 2.1220e-05 eta: 0:05:04 time: 0.4546 data_time: 0.0056 memory: 14901 loss: 0.8501 loss_prob: 0.4378 loss_thr: 0.3343 loss_db: 0.0780 2022/11/03 02:43:05 - mmengine - INFO - Epoch(train) [1193][50/63] lr: 2.1220e-05 eta: 0:04:58 time: 0.4820 data_time: 0.0132 memory: 14901 loss: 0.8966 loss_prob: 0.4648 loss_thr: 0.3516 loss_db: 0.0802 2022/11/03 02:43:08 - mmengine - INFO - Epoch(train) [1193][55/63] lr: 2.1220e-05 eta: 0:04:58 time: 0.5325 data_time: 0.0233 memory: 14901 loss: 0.9224 loss_prob: 0.4902 loss_thr: 0.3492 loss_db: 0.0830 2022/11/03 02:43:10 - mmengine - INFO - Epoch(train) [1193][60/63] lr: 2.1220e-05 eta: 0:04:51 time: 0.5001 data_time: 0.0166 memory: 14901 loss: 0.8397 loss_prob: 0.4318 loss_thr: 0.3337 loss_db: 0.0741 2022/11/03 02:43:11 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:43:15 - mmengine - INFO - Epoch(train) [1194][5/63] lr: 1.8484e-05 eta: 0:04:51 time: 0.6377 data_time: 0.1855 memory: 14901 loss: 0.8436 loss_prob: 0.4277 loss_thr: 0.3393 loss_db: 0.0766 2022/11/03 02:43:18 - mmengine - INFO - Epoch(train) [1194][10/63] lr: 1.8484e-05 eta: 0:04:42 time: 0.6467 data_time: 0.1894 memory: 14901 loss: 0.8753 loss_prob: 0.4530 loss_thr: 0.3432 loss_db: 0.0791 2022/11/03 02:43:20 - mmengine - INFO - Epoch(train) [1194][15/63] lr: 1.8484e-05 eta: 0:04:42 time: 0.4556 data_time: 0.0112 memory: 14901 loss: 0.9033 loss_prob: 0.4739 loss_thr: 0.3481 loss_db: 0.0813 2022/11/03 02:43:22 - mmengine - INFO - Epoch(train) [1194][20/63] lr: 1.8484e-05 eta: 0:04:36 time: 0.4705 data_time: 0.0091 memory: 14901 loss: 0.8487 loss_prob: 0.4393 loss_thr: 0.3327 loss_db: 0.0767 2022/11/03 02:43:25 - mmengine - INFO - Epoch(train) [1194][25/63] lr: 1.8484e-05 eta: 0:04:36 time: 0.4992 data_time: 0.0160 memory: 14901 loss: 0.8375 loss_prob: 0.4263 loss_thr: 0.3352 loss_db: 0.0760 2022/11/03 02:43:27 - mmengine - INFO - Epoch(train) [1194][30/63] lr: 1.8484e-05 eta: 0:04:29 time: 0.5019 data_time: 0.0286 memory: 14901 loss: 0.8575 loss_prob: 0.4398 loss_thr: 0.3398 loss_db: 0.0780 2022/11/03 02:43:30 - mmengine - INFO - Epoch(train) [1194][35/63] lr: 1.8484e-05 eta: 0:04:29 time: 0.4835 data_time: 0.0206 memory: 14901 loss: 0.8265 loss_prob: 0.4209 loss_thr: 0.3319 loss_db: 0.0737 2022/11/03 02:43:32 - mmengine - INFO - Epoch(train) [1194][40/63] lr: 1.8484e-05 eta: 0:04:23 time: 0.4747 data_time: 0.0065 memory: 14901 loss: 0.8125 loss_prob: 0.4115 loss_thr: 0.3286 loss_db: 0.0724 2022/11/03 02:43:34 - mmengine - INFO - Epoch(train) [1194][45/63] lr: 1.8484e-05 eta: 0:04:23 time: 0.4708 data_time: 0.0081 memory: 14901 loss: 0.8278 loss_prob: 0.4272 loss_thr: 0.3252 loss_db: 0.0755 2022/11/03 02:43:37 - mmengine - INFO - Epoch(train) [1194][50/63] lr: 1.8484e-05 eta: 0:04:16 time: 0.4610 data_time: 0.0100 memory: 14901 loss: 0.8352 loss_prob: 0.4337 loss_thr: 0.3249 loss_db: 0.0766 2022/11/03 02:43:40 - mmengine - INFO - Epoch(train) [1194][55/63] lr: 1.8484e-05 eta: 0:04:16 time: 0.5070 data_time: 0.0207 memory: 14901 loss: 0.9085 loss_prob: 0.4756 loss_thr: 0.3492 loss_db: 0.0837 2022/11/03 02:43:42 - mmengine - INFO - Epoch(train) [1194][60/63] lr: 1.8484e-05 eta: 0:04:10 time: 0.5499 data_time: 0.0192 memory: 14901 loss: 0.9406 loss_prob: 0.4933 loss_thr: 0.3611 loss_db: 0.0862 2022/11/03 02:43:44 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:43:48 - mmengine - INFO - Epoch(train) [1195][5/63] lr: 1.5702e-05 eta: 0:04:10 time: 0.7094 data_time: 0.2362 memory: 14901 loss: 0.8357 loss_prob: 0.4313 loss_thr: 0.3290 loss_db: 0.0754 2022/11/03 02:43:51 - mmengine - INFO - Epoch(train) [1195][10/63] lr: 1.5702e-05 eta: 0:04:01 time: 0.7098 data_time: 0.2345 memory: 14901 loss: 0.8647 loss_prob: 0.4458 loss_thr: 0.3414 loss_db: 0.0775 2022/11/03 02:43:53 - mmengine - INFO - Epoch(train) [1195][15/63] lr: 1.5702e-05 eta: 0:04:01 time: 0.4588 data_time: 0.0052 memory: 14901 loss: 0.8846 loss_prob: 0.4575 loss_thr: 0.3474 loss_db: 0.0797 2022/11/03 02:43:55 - mmengine - INFO - Epoch(train) [1195][20/63] lr: 1.5702e-05 eta: 0:03:54 time: 0.4575 data_time: 0.0051 memory: 14901 loss: 0.8564 loss_prob: 0.4453 loss_thr: 0.3346 loss_db: 0.0765 2022/11/03 02:43:58 - mmengine - INFO - Epoch(train) [1195][25/63] lr: 1.5702e-05 eta: 0:03:54 time: 0.5022 data_time: 0.0300 memory: 14901 loss: 0.7896 loss_prob: 0.4089 loss_thr: 0.3105 loss_db: 0.0702 2022/11/03 02:44:00 - mmengine - INFO - Epoch(train) [1195][30/63] lr: 1.5702e-05 eta: 0:03:48 time: 0.5204 data_time: 0.0332 memory: 14901 loss: 0.8350 loss_prob: 0.4338 loss_thr: 0.3250 loss_db: 0.0762 2022/11/03 02:44:03 - mmengine - INFO - Epoch(train) [1195][35/63] lr: 1.5702e-05 eta: 0:03:48 time: 0.5057 data_time: 0.0081 memory: 14901 loss: 0.8189 loss_prob: 0.4153 loss_thr: 0.3299 loss_db: 0.0737 2022/11/03 02:44:05 - mmengine - INFO - Epoch(train) [1195][40/63] lr: 1.5702e-05 eta: 0:03:41 time: 0.4835 data_time: 0.0050 memory: 14901 loss: 0.8048 loss_prob: 0.3996 loss_thr: 0.3330 loss_db: 0.0722 2022/11/03 02:44:08 - mmengine - INFO - Epoch(train) [1195][45/63] lr: 1.5702e-05 eta: 0:03:41 time: 0.4726 data_time: 0.0048 memory: 14901 loss: 0.8650 loss_prob: 0.4420 loss_thr: 0.3441 loss_db: 0.0789 2022/11/03 02:44:10 - mmengine - INFO - Epoch(train) [1195][50/63] lr: 1.5702e-05 eta: 0:03:35 time: 0.4976 data_time: 0.0190 memory: 14901 loss: 0.8699 loss_prob: 0.4537 loss_thr: 0.3372 loss_db: 0.0790 2022/11/03 02:44:13 - mmengine - INFO - Epoch(train) [1195][55/63] lr: 1.5702e-05 eta: 0:03:35 time: 0.4916 data_time: 0.0205 memory: 14901 loss: 0.8414 loss_prob: 0.4405 loss_thr: 0.3263 loss_db: 0.0746 2022/11/03 02:44:16 - mmengine - INFO - Epoch(train) [1195][60/63] lr: 1.5702e-05 eta: 0:03:28 time: 0.5374 data_time: 0.0073 memory: 14901 loss: 0.8219 loss_prob: 0.4282 loss_thr: 0.3205 loss_db: 0.0732 2022/11/03 02:44:17 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:44:22 - mmengine - INFO - Epoch(train) [1196][5/63] lr: 1.2863e-05 eta: 0:03:28 time: 0.7204 data_time: 0.1877 memory: 14901 loss: 0.9196 loss_prob: 0.5011 loss_thr: 0.3333 loss_db: 0.0853 2022/11/03 02:44:24 - mmengine - INFO - Epoch(train) [1196][10/63] lr: 1.2863e-05 eta: 0:03:20 time: 0.7262 data_time: 0.1870 memory: 14901 loss: 0.8188 loss_prob: 0.4332 loss_thr: 0.3110 loss_db: 0.0746 2022/11/03 02:44:26 - mmengine - INFO - Epoch(train) [1196][15/63] lr: 1.2863e-05 eta: 0:03:20 time: 0.4793 data_time: 0.0051 memory: 14901 loss: 0.7530 loss_prob: 0.3710 loss_thr: 0.3146 loss_db: 0.0674 2022/11/03 02:44:29 - mmengine - INFO - Epoch(train) [1196][20/63] lr: 1.2863e-05 eta: 0:03:13 time: 0.4820 data_time: 0.0049 memory: 14901 loss: 0.7783 loss_prob: 0.3834 loss_thr: 0.3240 loss_db: 0.0709 2022/11/03 02:44:31 - mmengine - INFO - Epoch(train) [1196][25/63] lr: 1.2863e-05 eta: 0:03:13 time: 0.4954 data_time: 0.0195 memory: 14901 loss: 0.8471 loss_prob: 0.4328 loss_thr: 0.3367 loss_db: 0.0777 2022/11/03 02:44:34 - mmengine - INFO - Epoch(train) [1196][30/63] lr: 1.2863e-05 eta: 0:03:07 time: 0.4925 data_time: 0.0366 memory: 14901 loss: 0.8760 loss_prob: 0.4481 loss_thr: 0.3490 loss_db: 0.0789 2022/11/03 02:44:36 - mmengine - INFO - Epoch(train) [1196][35/63] lr: 1.2863e-05 eta: 0:03:07 time: 0.4837 data_time: 0.0223 memory: 14901 loss: 0.8711 loss_prob: 0.4405 loss_thr: 0.3536 loss_db: 0.0770 2022/11/03 02:44:38 - mmengine - INFO - Epoch(train) [1196][40/63] lr: 1.2863e-05 eta: 0:03:00 time: 0.4775 data_time: 0.0051 memory: 14901 loss: 0.8252 loss_prob: 0.4174 loss_thr: 0.3337 loss_db: 0.0741 2022/11/03 02:44:41 - mmengine - INFO - Epoch(train) [1196][45/63] lr: 1.2863e-05 eta: 0:03:00 time: 0.4675 data_time: 0.0052 memory: 14901 loss: 0.7850 loss_prob: 0.3989 loss_thr: 0.3169 loss_db: 0.0691 2022/11/03 02:44:43 - mmengine - INFO - Epoch(train) [1196][50/63] lr: 1.2863e-05 eta: 0:02:53 time: 0.4817 data_time: 0.0200 memory: 14901 loss: 0.8308 loss_prob: 0.4293 loss_thr: 0.3276 loss_db: 0.0739 2022/11/03 02:44:46 - mmengine - INFO - Epoch(train) [1196][55/63] lr: 1.2863e-05 eta: 0:02:53 time: 0.4885 data_time: 0.0260 memory: 14901 loss: 0.7961 loss_prob: 0.4082 loss_thr: 0.3157 loss_db: 0.0722 2022/11/03 02:44:48 - mmengine - INFO - Epoch(train) [1196][60/63] lr: 1.2863e-05 eta: 0:02:47 time: 0.4844 data_time: 0.0117 memory: 14901 loss: 0.7797 loss_prob: 0.3958 loss_thr: 0.3139 loss_db: 0.0701 2022/11/03 02:44:49 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:44:54 - mmengine - INFO - Epoch(train) [1197][5/63] lr: 9.9519e-06 eta: 0:02:47 time: 0.7247 data_time: 0.2130 memory: 14901 loss: 1.0108 loss_prob: 0.5609 loss_thr: 0.3590 loss_db: 0.0909 2022/11/03 02:44:57 - mmengine - INFO - Epoch(train) [1197][10/63] lr: 9.9519e-06 eta: 0:02:38 time: 0.7507 data_time: 0.2190 memory: 14901 loss: 0.8362 loss_prob: 0.4331 loss_thr: 0.3273 loss_db: 0.0758 2022/11/03 02:44:59 - mmengine - INFO - Epoch(train) [1197][15/63] lr: 9.9519e-06 eta: 0:02:38 time: 0.4864 data_time: 0.0123 memory: 14901 loss: 0.9107 loss_prob: 0.4663 loss_thr: 0.3626 loss_db: 0.0818 2022/11/03 02:45:02 - mmengine - INFO - Epoch(train) [1197][20/63] lr: 9.9519e-06 eta: 0:02:32 time: 0.5003 data_time: 0.0053 memory: 14901 loss: 0.9328 loss_prob: 0.4838 loss_thr: 0.3654 loss_db: 0.0836 2022/11/03 02:45:05 - mmengine - INFO - Epoch(train) [1197][25/63] lr: 9.9519e-06 eta: 0:02:32 time: 0.5403 data_time: 0.0253 memory: 14901 loss: 0.8716 loss_prob: 0.4393 loss_thr: 0.3566 loss_db: 0.0757 2022/11/03 02:45:07 - mmengine - INFO - Epoch(train) [1197][30/63] lr: 9.9519e-06 eta: 0:02:25 time: 0.5351 data_time: 0.0275 memory: 14901 loss: 0.8310 loss_prob: 0.4141 loss_thr: 0.3434 loss_db: 0.0735 2022/11/03 02:45:10 - mmengine - INFO - Epoch(train) [1197][35/63] lr: 9.9519e-06 eta: 0:02:25 time: 0.5065 data_time: 0.0134 memory: 14901 loss: 0.7854 loss_prob: 0.4044 loss_thr: 0.3081 loss_db: 0.0728 2022/11/03 02:45:12 - mmengine - INFO - Epoch(train) [1197][40/63] lr: 9.9519e-06 eta: 0:02:19 time: 0.4715 data_time: 0.0108 memory: 14901 loss: 0.9242 loss_prob: 0.5269 loss_thr: 0.3180 loss_db: 0.0793 2022/11/03 02:45:14 - mmengine - INFO - Epoch(train) [1197][45/63] lr: 9.9519e-06 eta: 0:02:19 time: 0.4523 data_time: 0.0065 memory: 14901 loss: 0.9983 loss_prob: 0.5651 loss_thr: 0.3496 loss_db: 0.0836 2022/11/03 02:45:17 - mmengine - INFO - Epoch(train) [1197][50/63] lr: 9.9519e-06 eta: 0:02:12 time: 0.4910 data_time: 0.0198 memory: 14901 loss: 0.8615 loss_prob: 0.4473 loss_thr: 0.3363 loss_db: 0.0780 2022/11/03 02:45:19 - mmengine - INFO - Epoch(train) [1197][55/63] lr: 9.9519e-06 eta: 0:02:12 time: 0.4816 data_time: 0.0193 memory: 14901 loss: 0.8302 loss_prob: 0.4332 loss_thr: 0.3202 loss_db: 0.0768 2022/11/03 02:45:22 - mmengine - INFO - Epoch(train) [1197][60/63] lr: 9.9519e-06 eta: 0:02:05 time: 0.4563 data_time: 0.0071 memory: 14901 loss: 0.9172 loss_prob: 0.4847 loss_thr: 0.3473 loss_db: 0.0853 2022/11/03 02:45:23 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:45:29 - mmengine - INFO - Epoch(train) [1198][5/63] lr: 6.9397e-06 eta: 0:02:05 time: 0.7938 data_time: 0.2275 memory: 14901 loss: 0.9197 loss_prob: 0.4758 loss_thr: 0.3600 loss_db: 0.0839 2022/11/03 02:45:31 - mmengine - INFO - Epoch(train) [1198][10/63] lr: 6.9397e-06 eta: 0:01:57 time: 0.8143 data_time: 0.2283 memory: 14901 loss: 0.8551 loss_prob: 0.4387 loss_thr: 0.3391 loss_db: 0.0773 2022/11/03 02:45:33 - mmengine - INFO - Epoch(train) [1198][15/63] lr: 6.9397e-06 eta: 0:01:57 time: 0.4758 data_time: 0.0097 memory: 14901 loss: 0.8821 loss_prob: 0.4543 loss_thr: 0.3473 loss_db: 0.0805 2022/11/03 02:45:36 - mmengine - INFO - Epoch(train) [1198][20/63] lr: 6.9397e-06 eta: 0:01:50 time: 0.4713 data_time: 0.0091 memory: 14901 loss: 0.8979 loss_prob: 0.4616 loss_thr: 0.3558 loss_db: 0.0804 2022/11/03 02:45:38 - mmengine - INFO - Epoch(train) [1198][25/63] lr: 6.9397e-06 eta: 0:01:50 time: 0.4771 data_time: 0.0179 memory: 14901 loss: 0.8638 loss_prob: 0.4416 loss_thr: 0.3450 loss_db: 0.0771 2022/11/03 02:45:41 - mmengine - INFO - Epoch(train) [1198][30/63] lr: 6.9397e-06 eta: 0:01:44 time: 0.5049 data_time: 0.0459 memory: 14901 loss: 0.8220 loss_prob: 0.4236 loss_thr: 0.3225 loss_db: 0.0759 2022/11/03 02:45:43 - mmengine - INFO - Epoch(train) [1198][35/63] lr: 6.9397e-06 eta: 0:01:44 time: 0.4680 data_time: 0.0368 memory: 14901 loss: 0.7546 loss_prob: 0.3853 loss_thr: 0.3008 loss_db: 0.0685 2022/11/03 02:45:45 - mmengine - INFO - Epoch(train) [1198][40/63] lr: 6.9397e-06 eta: 0:01:37 time: 0.4665 data_time: 0.0118 memory: 14901 loss: 0.7597 loss_prob: 0.3861 loss_thr: 0.3053 loss_db: 0.0683 2022/11/03 02:45:48 - mmengine - INFO - Epoch(train) [1198][45/63] lr: 6.9397e-06 eta: 0:01:37 time: 0.4871 data_time: 0.0079 memory: 14901 loss: 0.8413 loss_prob: 0.4240 loss_thr: 0.3434 loss_db: 0.0739 2022/11/03 02:45:50 - mmengine - INFO - Epoch(train) [1198][50/63] lr: 6.9397e-06 eta: 0:01:31 time: 0.4914 data_time: 0.0104 memory: 14901 loss: 0.8949 loss_prob: 0.4552 loss_thr: 0.3607 loss_db: 0.0790 2022/11/03 02:45:53 - mmengine - INFO - Epoch(train) [1198][55/63] lr: 6.9397e-06 eta: 0:01:31 time: 0.5149 data_time: 0.0217 memory: 14901 loss: 0.8756 loss_prob: 0.4556 loss_thr: 0.3411 loss_db: 0.0789 2022/11/03 02:45:55 - mmengine - INFO - Epoch(train) [1198][60/63] lr: 6.9397e-06 eta: 0:01:24 time: 0.4799 data_time: 0.0158 memory: 14901 loss: 0.8648 loss_prob: 0.4461 loss_thr: 0.3419 loss_db: 0.0768 2022/11/03 02:45:56 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:46:01 - mmengine - INFO - Epoch(train) [1199][5/63] lr: 3.7653e-06 eta: 0:01:24 time: 0.7423 data_time: 0.2506 memory: 14901 loss: 0.8967 loss_prob: 0.4624 loss_thr: 0.3520 loss_db: 0.0823 2022/11/03 02:46:04 - mmengine - INFO - Epoch(train) [1199][10/63] lr: 3.7653e-06 eta: 0:01:16 time: 0.7486 data_time: 0.2504 memory: 14901 loss: 0.8418 loss_prob: 0.4340 loss_thr: 0.3315 loss_db: 0.0762 2022/11/03 02:46:06 - mmengine - INFO - Epoch(train) [1199][15/63] lr: 3.7653e-06 eta: 0:01:16 time: 0.4617 data_time: 0.0056 memory: 14901 loss: 0.8692 loss_prob: 0.4543 loss_thr: 0.3359 loss_db: 0.0790 2022/11/03 02:46:09 - mmengine - INFO - Epoch(train) [1199][20/63] lr: 3.7653e-06 eta: 0:01:09 time: 0.4898 data_time: 0.0054 memory: 14901 loss: 0.9095 loss_prob: 0.4750 loss_thr: 0.3525 loss_db: 0.0819 2022/11/03 02:46:11 - mmengine - INFO - Epoch(train) [1199][25/63] lr: 3.7653e-06 eta: 0:01:09 time: 0.5229 data_time: 0.0264 memory: 14901 loss: 0.8748 loss_prob: 0.4578 loss_thr: 0.3380 loss_db: 0.0790 2022/11/03 02:46:14 - mmengine - INFO - Epoch(train) [1199][30/63] lr: 3.7653e-06 eta: 0:01:02 time: 0.5142 data_time: 0.0373 memory: 14901 loss: 0.9190 loss_prob: 0.4892 loss_thr: 0.3465 loss_db: 0.0833 2022/11/03 02:46:16 - mmengine - INFO - Epoch(train) [1199][35/63] lr: 3.7653e-06 eta: 0:01:02 time: 0.4776 data_time: 0.0164 memory: 14901 loss: 1.1637 loss_prob: 0.6750 loss_thr: 0.3831 loss_db: 0.1056 2022/11/03 02:46:19 - mmengine - INFO - Epoch(train) [1199][40/63] lr: 3.7653e-06 eta: 0:00:56 time: 0.4742 data_time: 0.0051 memory: 14901 loss: 1.0833 loss_prob: 0.6193 loss_thr: 0.3666 loss_db: 0.0975 2022/11/03 02:46:21 - mmengine - INFO - Epoch(train) [1199][45/63] lr: 3.7653e-06 eta: 0:00:56 time: 0.4808 data_time: 0.0049 memory: 14901 loss: 0.7970 loss_prob: 0.4037 loss_thr: 0.3224 loss_db: 0.0709 2022/11/03 02:46:24 - mmengine - INFO - Epoch(train) [1199][50/63] lr: 3.7653e-06 eta: 0:00:49 time: 0.4995 data_time: 0.0221 memory: 14901 loss: 0.7927 loss_prob: 0.4024 loss_thr: 0.3184 loss_db: 0.0718 2022/11/03 02:46:26 - mmengine - INFO - Epoch(train) [1199][55/63] lr: 3.7653e-06 eta: 0:00:49 time: 0.4993 data_time: 0.0219 memory: 14901 loss: 0.7818 loss_prob: 0.3975 loss_thr: 0.3117 loss_db: 0.0726 2022/11/03 02:46:28 - mmengine - INFO - Epoch(train) [1199][60/63] lr: 3.7653e-06 eta: 0:00:43 time: 0.4880 data_time: 0.0050 memory: 14901 loss: 0.7261 loss_prob: 0.3670 loss_thr: 0.2919 loss_db: 0.0672 2022/11/03 02:46:30 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:46:34 - mmengine - INFO - Epoch(train) [1200][5/63] lr: 1.0000e-07 eta: 0:00:43 time: 0.6429 data_time: 0.1812 memory: 14901 loss: 0.7428 loss_prob: 0.3819 loss_thr: 0.2930 loss_db: 0.0679 2022/11/03 02:46:36 - mmengine - INFO - Epoch(train) [1200][10/63] lr: 1.0000e-07 eta: 0:00:34 time: 0.6621 data_time: 0.1843 memory: 14901 loss: 0.7668 loss_prob: 0.3948 loss_thr: 0.3027 loss_db: 0.0693 2022/11/03 02:46:39 - mmengine - INFO - Epoch(train) [1200][15/63] lr: 1.0000e-07 eta: 0:00:34 time: 0.4965 data_time: 0.0369 memory: 14901 loss: 0.8450 loss_prob: 0.4339 loss_thr: 0.3366 loss_db: 0.0745 2022/11/03 02:46:41 - mmengine - INFO - Epoch(train) [1200][20/63] lr: 1.0000e-07 eta: 0:00:28 time: 0.5009 data_time: 0.0335 memory: 14901 loss: 0.9071 loss_prob: 0.4739 loss_thr: 0.3523 loss_db: 0.0810 2022/11/03 02:46:44 - mmengine - INFO - Epoch(train) [1200][25/63] lr: 1.0000e-07 eta: 0:00:28 time: 0.4833 data_time: 0.0059 memory: 14901 loss: 0.7993 loss_prob: 0.4128 loss_thr: 0.3144 loss_db: 0.0721 2022/11/03 02:46:46 - mmengine - INFO - Epoch(train) [1200][30/63] lr: 1.0000e-07 eta: 0:00:21 time: 0.5003 data_time: 0.0105 memory: 14901 loss: 0.7861 loss_prob: 0.4024 loss_thr: 0.3133 loss_db: 0.0704 2022/11/03 02:46:49 - mmengine - INFO - Epoch(train) [1200][35/63] lr: 1.0000e-07 eta: 0:00:21 time: 0.5040 data_time: 0.0193 memory: 14901 loss: 0.8176 loss_prob: 0.4180 loss_thr: 0.3258 loss_db: 0.0737 2022/11/03 02:46:51 - mmengine - INFO - Epoch(train) [1200][40/63] lr: 1.0000e-07 eta: 0:00:15 time: 0.4894 data_time: 0.0247 memory: 14901 loss: 0.8418 loss_prob: 0.4322 loss_thr: 0.3342 loss_db: 0.0755 2022/11/03 02:46:53 - mmengine - INFO - Epoch(train) [1200][45/63] lr: 1.0000e-07 eta: 0:00:15 time: 0.4616 data_time: 0.0156 memory: 14901 loss: 0.8477 loss_prob: 0.4407 loss_thr: 0.3309 loss_db: 0.0760 2022/11/03 02:46:56 - mmengine - INFO - Epoch(train) [1200][50/63] lr: 1.0000e-07 eta: 0:00:08 time: 0.4707 data_time: 0.0053 memory: 14901 loss: 0.8522 loss_prob: 0.4465 loss_thr: 0.3269 loss_db: 0.0788 2022/11/03 02:46:58 - mmengine - INFO - Epoch(train) [1200][55/63] lr: 1.0000e-07 eta: 0:00:08 time: 0.4916 data_time: 0.0107 memory: 14901 loss: 0.8840 loss_prob: 0.4584 loss_thr: 0.3452 loss_db: 0.0804 2022/11/03 02:47:01 - mmengine - INFO - Epoch(train) [1200][60/63] lr: 1.0000e-07 eta: 0:00:01 time: 0.4801 data_time: 0.0160 memory: 14901 loss: 0.9434 loss_prob: 0.4872 loss_thr: 0.3730 loss_db: 0.0832 2022/11/03 02:47:02 - mmengine - INFO - Exp name: dbnet_resnet50_1200e_icdar2015_20221102_115917 2022/11/03 02:47:02 - mmengine - INFO - Saving checkpoint at 1200 epochs 2022/11/03 02:47:06 - mmengine - INFO - Epoch(val) [1200][5/500] eta: 0:00:01 time: 0.0406 data_time: 0.0043 memory: 14901 2022/11/03 02:47:06 - mmengine - INFO - Epoch(val) [1200][10/500] eta: 0:00:20 time: 0.0415 data_time: 0.0042 memory: 1008 2022/11/03 02:47:06 - mmengine - INFO - Epoch(val) [1200][15/500] eta: 0:00:20 time: 0.0360 data_time: 0.0019 memory: 1008 2022/11/03 02:47:06 - mmengine - INFO - Epoch(val) [1200][20/500] eta: 0:00:17 time: 0.0355 data_time: 0.0021 memory: 1008 2022/11/03 02:47:06 - mmengine - INFO - Epoch(val) [1200][25/500] eta: 0:00:17 time: 0.0360 data_time: 0.0023 memory: 1008 2022/11/03 02:47:06 - mmengine - INFO - Epoch(val) [1200][30/500] eta: 0:00:18 time: 0.0397 data_time: 0.0024 memory: 1008 2022/11/03 02:47:07 - mmengine - INFO - Epoch(val) [1200][35/500] eta: 0:00:18 time: 0.0383 data_time: 0.0023 memory: 1008 2022/11/03 02:47:07 - mmengine - INFO - Epoch(val) [1200][40/500] eta: 0:00:18 time: 0.0402 data_time: 0.0022 memory: 1008 2022/11/03 02:47:07 - mmengine - INFO - Epoch(val) [1200][45/500] eta: 0:00:18 time: 0.0415 data_time: 0.0021 memory: 1008 2022/11/03 02:47:07 - mmengine - INFO - Epoch(val) [1200][50/500] eta: 0:00:19 time: 0.0425 data_time: 0.0020 memory: 1008 2022/11/03 02:47:08 - mmengine - INFO - Epoch(val) [1200][55/500] eta: 0:00:19 time: 0.0439 data_time: 0.0020 memory: 1008 2022/11/03 02:47:08 - mmengine - INFO - Epoch(val) [1200][60/500] eta: 0:00:16 time: 0.0365 data_time: 0.0021 memory: 1008 2022/11/03 02:47:08 - mmengine - INFO - Epoch(val) [1200][65/500] eta: 0:00:16 time: 0.0381 data_time: 0.0021 memory: 1008 2022/11/03 02:47:08 - mmengine - INFO - Epoch(val) [1200][70/500] eta: 0:00:17 time: 0.0403 data_time: 0.0022 memory: 1008 2022/11/03 02:47:08 - mmengine - INFO - Epoch(val) [1200][75/500] eta: 0:00:17 time: 0.0362 data_time: 0.0022 memory: 1008 2022/11/03 02:47:08 - mmengine - INFO - Epoch(val) [1200][80/500] eta: 0:00:14 time: 0.0345 data_time: 0.0024 memory: 1008 2022/11/03 02:47:09 - mmengine - INFO - Epoch(val) [1200][85/500] eta: 0:00:14 time: 0.0360 data_time: 0.0026 memory: 1008 2022/11/03 02:47:09 - mmengine - INFO - Epoch(val) [1200][90/500] eta: 0:00:17 time: 0.0438 data_time: 0.0028 memory: 1008 2022/11/03 02:47:09 - mmengine - INFO - Epoch(val) [1200][95/500] eta: 0:00:17 time: 0.0460 data_time: 0.0031 memory: 1008 2022/11/03 02:47:09 - mmengine - INFO - Epoch(val) [1200][100/500] eta: 0:00:15 time: 0.0385 data_time: 0.0029 memory: 1008 2022/11/03 02:47:09 - mmengine - INFO - Epoch(val) [1200][105/500] eta: 0:00:15 time: 0.0366 data_time: 0.0025 memory: 1008 2022/11/03 02:47:10 - mmengine - INFO - Epoch(val) [1200][110/500] eta: 0:00:14 time: 0.0375 data_time: 0.0025 memory: 1008 2022/11/03 02:47:10 - mmengine - INFO - Epoch(val) [1200][115/500] eta: 0:00:14 time: 0.0381 data_time: 0.0025 memory: 1008 2022/11/03 02:47:10 - mmengine - INFO - Epoch(val) [1200][120/500] eta: 0:00:15 time: 0.0404 data_time: 0.0026 memory: 1008 2022/11/03 02:47:10 - mmengine - INFO - Epoch(val) [1200][125/500] eta: 0:00:15 time: 0.0394 data_time: 0.0028 memory: 1008 2022/11/03 02:47:10 - mmengine - INFO - Epoch(val) [1200][130/500] eta: 0:00:14 time: 0.0380 data_time: 0.0030 memory: 1008 2022/11/03 02:47:11 - mmengine - INFO - Epoch(val) [1200][135/500] eta: 0:00:14 time: 0.0385 data_time: 0.0029 memory: 1008 2022/11/03 02:47:11 - mmengine - INFO - Epoch(val) [1200][140/500] eta: 0:00:13 time: 0.0383 data_time: 0.0028 memory: 1008 2022/11/03 02:47:11 - mmengine - INFO - Epoch(val) [1200][145/500] eta: 0:00:13 time: 0.0451 data_time: 0.0032 memory: 1008 2022/11/03 02:47:11 - mmengine - INFO - Epoch(val) [1200][150/500] eta: 0:00:15 time: 0.0444 data_time: 0.0028 memory: 1008 2022/11/03 02:47:12 - mmengine - INFO - Epoch(val) [1200][155/500] eta: 0:00:15 time: 0.0431 data_time: 0.0023 memory: 1008 2022/11/03 02:47:12 - mmengine - INFO - Epoch(val) [1200][160/500] eta: 0:00:14 time: 0.0426 data_time: 0.0022 memory: 1008 2022/11/03 02:47:12 - mmengine - INFO - Epoch(val) [1200][165/500] eta: 0:00:14 time: 0.0365 data_time: 0.0023 memory: 1008 2022/11/03 02:47:12 - mmengine - INFO - Epoch(val) [1200][170/500] eta: 0:00:12 time: 0.0381 data_time: 0.0023 memory: 1008 2022/11/03 02:47:12 - mmengine - INFO - Epoch(val) [1200][175/500] eta: 0:00:12 time: 0.0388 data_time: 0.0024 memory: 1008 2022/11/03 02:47:12 - mmengine - INFO - Epoch(val) [1200][180/500] eta: 0:00:12 time: 0.0405 data_time: 0.0025 memory: 1008 2022/11/03 02:47:13 - mmengine - INFO - Epoch(val) [1200][185/500] eta: 0:00:12 time: 0.0420 data_time: 0.0024 memory: 1008 2022/11/03 02:47:13 - mmengine - INFO - Epoch(val) [1200][190/500] eta: 0:00:12 time: 0.0396 data_time: 0.0023 memory: 1008 2022/11/03 02:47:13 - mmengine - INFO - Epoch(val) [1200][195/500] eta: 0:00:12 time: 0.0367 data_time: 0.0024 memory: 1008 2022/11/03 02:47:13 - mmengine - INFO - Epoch(val) [1200][200/500] eta: 0:00:12 time: 0.0413 data_time: 0.0027 memory: 1008 2022/11/03 02:47:13 - mmengine - INFO - Epoch(val) [1200][205/500] eta: 0:00:12 time: 0.0408 data_time: 0.0024 memory: 1008 2022/11/03 02:47:14 - mmengine - INFO - Epoch(val) [1200][210/500] eta: 0:00:10 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/03 02:47:14 - mmengine - INFO - Epoch(val) [1200][215/500] eta: 0:00:10 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/03 02:47:14 - mmengine - INFO - Epoch(val) [1200][220/500] eta: 0:00:10 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/03 02:47:14 - mmengine - INFO - Epoch(val) [1200][225/500] eta: 0:00:10 time: 0.0376 data_time: 0.0022 memory: 1008 2022/11/03 02:47:14 - mmengine - INFO - Epoch(val) [1200][230/500] eta: 0:00:10 time: 0.0371 data_time: 0.0023 memory: 1008 2022/11/03 02:47:15 - mmengine - INFO - Epoch(val) [1200][235/500] eta: 0:00:10 time: 0.0373 data_time: 0.0024 memory: 1008 2022/11/03 02:47:15 - mmengine - INFO - Epoch(val) [1200][240/500] eta: 0:00:10 time: 0.0390 data_time: 0.0024 memory: 1008 2022/11/03 02:47:15 - mmengine - INFO - Epoch(val) [1200][245/500] eta: 0:00:10 time: 0.0453 data_time: 0.0115 memory: 1008 2022/11/03 02:47:15 - mmengine - INFO - Epoch(val) [1200][250/500] eta: 0:00:11 time: 0.0473 data_time: 0.0114 memory: 1008 2022/11/03 02:47:15 - mmengine - INFO - Epoch(val) [1200][255/500] eta: 0:00:11 time: 0.0378 data_time: 0.0023 memory: 1008 2022/11/03 02:47:16 - mmengine - INFO - Epoch(val) [1200][260/500] eta: 0:00:08 time: 0.0354 data_time: 0.0023 memory: 1008 2022/11/03 02:47:16 - mmengine - INFO - Epoch(val) [1200][265/500] eta: 0:00:08 time: 0.0370 data_time: 0.0023 memory: 1008 2022/11/03 02:47:16 - mmengine - INFO - Epoch(val) [1200][270/500] eta: 0:00:08 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/03 02:47:16 - mmengine - INFO - Epoch(val) [1200][275/500] eta: 0:00:08 time: 0.0361 data_time: 0.0023 memory: 1008 2022/11/03 02:47:16 - mmengine - INFO - Epoch(val) [1200][280/500] eta: 0:00:08 time: 0.0390 data_time: 0.0023 memory: 1008 2022/11/03 02:47:17 - mmengine - INFO - Epoch(val) [1200][285/500] eta: 0:00:08 time: 0.0409 data_time: 0.0022 memory: 1008 2022/11/03 02:47:17 - mmengine - INFO - Epoch(val) [1200][290/500] eta: 0:00:08 time: 0.0400 data_time: 0.0022 memory: 1008 2022/11/03 02:47:17 - mmengine - INFO - Epoch(val) [1200][295/500] eta: 0:00:08 time: 0.0375 data_time: 0.0022 memory: 1008 2022/11/03 02:47:17 - mmengine - INFO - Epoch(val) [1200][300/500] eta: 0:00:07 time: 0.0359 data_time: 0.0022 memory: 1008 2022/11/03 02:47:17 - mmengine - INFO - Epoch(val) [1200][305/500] eta: 0:00:07 time: 0.0366 data_time: 0.0024 memory: 1008 2022/11/03 02:47:18 - mmengine - INFO - Epoch(val) [1200][310/500] eta: 0:00:07 time: 0.0387 data_time: 0.0026 memory: 1008 2022/11/03 02:47:18 - mmengine - INFO - Epoch(val) [1200][315/500] eta: 0:00:07 time: 0.0423 data_time: 0.0027 memory: 1008 2022/11/03 02:47:18 - mmengine - INFO - Epoch(val) [1200][320/500] eta: 0:00:07 time: 0.0395 data_time: 0.0025 memory: 1008 2022/11/03 02:47:18 - mmengine - INFO - Epoch(val) [1200][325/500] eta: 0:00:07 time: 0.0470 data_time: 0.0022 memory: 1008 2022/11/03 02:47:18 - mmengine - INFO - Epoch(val) [1200][330/500] eta: 0:00:08 time: 0.0478 data_time: 0.0021 memory: 1008 2022/11/03 02:47:19 - mmengine - INFO - Epoch(val) [1200][335/500] eta: 0:00:08 time: 0.0356 data_time: 0.0021 memory: 1008 2022/11/03 02:47:19 - mmengine - INFO - Epoch(val) [1200][340/500] eta: 0:00:07 time: 0.0472 data_time: 0.0023 memory: 1008 2022/11/03 02:47:19 - mmengine - INFO - Epoch(val) [1200][345/500] eta: 0:00:07 time: 0.0481 data_time: 0.0023 memory: 1008 2022/11/03 02:47:19 - mmengine - INFO - Epoch(val) [1200][350/500] eta: 0:00:06 time: 0.0422 data_time: 0.0030 memory: 1008 2022/11/03 02:47:19 - mmengine - INFO - Epoch(val) [1200][355/500] eta: 0:00:06 time: 0.0412 data_time: 0.0030 memory: 1008 2022/11/03 02:47:20 - mmengine - INFO - Epoch(val) [1200][360/500] eta: 0:00:05 time: 0.0368 data_time: 0.0026 memory: 1008 2022/11/03 02:47:20 - mmengine - INFO - Epoch(val) [1200][365/500] eta: 0:00:05 time: 0.0377 data_time: 0.0025 memory: 1008 2022/11/03 02:47:20 - mmengine - INFO - Epoch(val) [1200][370/500] eta: 0:00:04 time: 0.0336 data_time: 0.0019 memory: 1008 2022/11/03 02:47:20 - mmengine - INFO - Epoch(val) [1200][375/500] eta: 0:00:04 time: 0.0338 data_time: 0.0020 memory: 1008 2022/11/03 02:47:20 - mmengine - INFO - Epoch(val) [1200][380/500] eta: 0:00:04 time: 0.0377 data_time: 0.0022 memory: 1008 2022/11/03 02:47:21 - mmengine - INFO - Epoch(val) [1200][385/500] eta: 0:00:04 time: 0.0388 data_time: 0.0022 memory: 1008 2022/11/03 02:47:21 - mmengine - INFO - Epoch(val) [1200][390/500] eta: 0:00:04 time: 0.0386 data_time: 0.0023 memory: 1008 2022/11/03 02:47:21 - mmengine - INFO - Epoch(val) [1200][395/500] eta: 0:00:04 time: 0.0381 data_time: 0.0022 memory: 1008 2022/11/03 02:47:21 - mmengine - INFO - Epoch(val) [1200][400/500] eta: 0:00:03 time: 0.0371 data_time: 0.0021 memory: 1008 2022/11/03 02:47:21 - mmengine - INFO - Epoch(val) [1200][405/500] eta: 0:00:03 time: 0.0366 data_time: 0.0021 memory: 1008 2022/11/03 02:47:22 - mmengine - INFO - Epoch(val) [1200][410/500] eta: 0:00:03 time: 0.0372 data_time: 0.0021 memory: 1008 2022/11/03 02:47:22 - mmengine - INFO - Epoch(val) [1200][415/500] eta: 0:00:03 time: 0.0373 data_time: 0.0020 memory: 1008 2022/11/03 02:47:22 - mmengine - INFO - Epoch(val) [1200][420/500] eta: 0:00:02 time: 0.0339 data_time: 0.0020 memory: 1008 2022/11/03 02:47:22 - mmengine - INFO - Epoch(val) [1200][425/500] eta: 0:00:02 time: 0.0341 data_time: 0.0020 memory: 1008 2022/11/03 02:47:22 - mmengine - INFO - Epoch(val) [1200][430/500] eta: 0:00:02 time: 0.0383 data_time: 0.0022 memory: 1008 2022/11/03 02:47:22 - mmengine - INFO - Epoch(val) [1200][435/500] eta: 0:00:02 time: 0.0364 data_time: 0.0022 memory: 1008 2022/11/03 02:47:23 - mmengine - INFO - Epoch(val) [1200][440/500] eta: 0:00:02 time: 0.0354 data_time: 0.0022 memory: 1008 2022/11/03 02:47:23 - mmengine - INFO - Epoch(val) [1200][445/500] eta: 0:00:02 time: 0.0380 data_time: 0.0023 memory: 1008 2022/11/03 02:47:23 - mmengine - INFO - Epoch(val) [1200][450/500] eta: 0:00:01 time: 0.0389 data_time: 0.0022 memory: 1008 2022/11/03 02:47:23 - mmengine - INFO - Epoch(val) [1200][455/500] eta: 0:00:01 time: 0.0379 data_time: 0.0021 memory: 1008 2022/11/03 02:47:23 - mmengine - INFO - Epoch(val) [1200][460/500] eta: 0:00:01 time: 0.0361 data_time: 0.0024 memory: 1008 2022/11/03 02:47:24 - mmengine - INFO - Epoch(val) [1200][465/500] eta: 0:00:01 time: 0.0340 data_time: 0.0023 memory: 1008 2022/11/03 02:47:24 - mmengine - INFO - Epoch(val) [1200][470/500] eta: 0:00:01 time: 0.0337 data_time: 0.0019 memory: 1008 2022/11/03 02:47:24 - mmengine - INFO - Epoch(val) [1200][475/500] eta: 0:00:01 time: 0.0341 data_time: 0.0019 memory: 1008 2022/11/03 02:47:24 - mmengine - INFO - Epoch(val) [1200][480/500] eta: 0:00:00 time: 0.0340 data_time: 0.0019 memory: 1008 2022/11/03 02:47:24 - mmengine - INFO - Epoch(val) [1200][485/500] eta: 0:00:00 time: 0.0341 data_time: 0.0020 memory: 1008 2022/11/03 02:47:24 - mmengine - INFO - Epoch(val) [1200][490/500] eta: 0:00:00 time: 0.0362 data_time: 0.0020 memory: 1008 2022/11/03 02:47:25 - mmengine - INFO - Epoch(val) [1200][495/500] eta: 0:00:00 time: 0.0378 data_time: 0.0020 memory: 1008 2022/11/03 02:47:25 - mmengine - INFO - Epoch(val) [1200][500/500] eta: 0:00:00 time: 0.0350 data_time: 0.0018 memory: 1008 2022/11/03 02:47:25 - mmengine - INFO - Evaluating hmean-iou... 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8339, precision: 0.7729, hmean: 0.8022 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8339, precision: 0.8131, hmean: 0.8234 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8339, precision: 0.8375, hmean: 0.8357 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8325, precision: 0.8559, hmean: 0.8440 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8180, precision: 0.8780, hmean: 0.8470 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7342, precision: 0.9148, hmean: 0.8146 2022/11/03 02:47:25 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2234, precision: 0.9687, hmean: 0.3631 2022/11/03 02:47:25 - mmengine - INFO - Epoch(val) [1200][500/500] icdar/precision: 0.8780 icdar/recall: 0.8180 icdar/hmean: 0.8470