2022/10/25 18:55:50 - 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: 569598859 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 ------------------------------------------------------------ 2022/10/25 18:55:50 - mmengine - INFO - Config: 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, asf_cfg=dict(attention_type='ScaleChannelSpatial')), det_head=dict( type='DBHead', in_channels=256, module_loss=dict(type='DBModuleLoss'), postprocessor=dict( type='DBPostprocessor', text_repr_type='quad', epsilon_ratio=0.002)), 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', 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', 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', 'instances')) ] 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')]) 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=None) 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=None) optim_wrapper = dict( type='OptimWrapper', optimizer=dict(type='SGD', lr=0.003, 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=200, start_factor=0.001), dict(type='PolyLR', power=0.9, eta_min=1e-07, begin=200, end=1200) ] train_list = [ 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=None) ] test_list = [ dict( type='OCRDataset', data_root='data/det/icdar2015', ann_file='instances_test.json', data_prefix=dict(img_path='imgs/'), test_mode=True, pipeline=None) ] train_dataloader = dict( batch_size=16, num_workers=24, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='ConcatDataset', datasets=[ 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=None) ], pipeline=[ dict( type='LoadImageFromFile', color_type='color_ignore_orientation', file_client_args=dict(backend='petrel')), 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=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ 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=None) ], pipeline=[ dict( type='LoadImageFromFile', color_type='color_ignore_orientation', file_client_args=dict(backend='petrel')), 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', 'instances')) ])) test_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type='ConcatDataset', datasets=[ 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=None) ], pipeline=[ dict( type='LoadImageFromFile', color_type='color_ignore_orientation', file_client_args=dict(backend='petrel')), 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', 'instances')) ])) auto_scale_lr = dict(base_batch_size=16) launcher = 'slurm' work_dir = './work_dirs/dbnetpp_resnet50_fpnc_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 neck.asf_conv.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.asf_conv.conv.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of DBNet neck.asf_attn.channel_wise.0.conv.weight - torch.Size([64, 256, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.channel_wise.1.conv.weight - torch.Size([256, 64, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.spatial_wise.0.conv.weight - torch.Size([1, 1, 3, 3]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.spatial_wise.1.conv.weight - torch.Size([1, 1, 1, 1]): Initialized by user-defined `init_weights` in ConvModule neck.asf_attn.attention_wise.conv.weight - torch.Size([4, 256, 1, 1]): 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 2022/10/25 18:56:42 - mmengine - INFO - Checkpoints will be saved to sproject:s3://oclip/dbnetpp_resnet50_fpnc_1200e_icdar2015. 2022/10/25 19:02:51 - mmengine - INFO - Epoch(train) [1][5/63] lr: 3.0000e-06 memory: 48125 data_time: 70.5837 loss: 26.8851 loss_prob: 23.1102 loss_thr: 2.7845 loss_db: 0.9904 time: 73.8319 2022/10/25 19:02:54 - mmengine - INFO - Epoch(train) [1][10/63] lr: 3.0000e-06 eta: 32 days, 13:16:04 time: 37.2082 data_time: 35.2950 memory: 16131 loss: 26.5800 loss_prob: 22.7963 loss_thr: 2.7940 loss_db: 0.9897 2022/10/25 19:02:57 - mmengine - INFO - Epoch(train) [1][15/63] lr: 3.0000e-06 eta: 32 days, 13:16:04 time: 0.5776 data_time: 0.0068 memory: 16131 loss: 25.1510 loss_prob: 21.3961 loss_thr: 2.7666 loss_db: 0.9884 2022/10/25 19:03:00 - mmengine - INFO - Epoch(train) [1][20/63] lr: 3.0000e-06 eta: 16 days, 12:22:58 time: 0.5526 data_time: 0.0125 memory: 16131 loss: 23.7134 loss_prob: 20.0323 loss_thr: 2.6920 loss_db: 0.9890 2022/10/25 19:03:03 - mmengine - INFO - Epoch(train) [1][25/63] lr: 3.0000e-06 eta: 16 days, 12:22:58 time: 0.5443 data_time: 0.0203 memory: 16131 loss: 22.8747 loss_prob: 19.2053 loss_thr: 2.6789 loss_db: 0.9905 2022/10/25 19:03:07 - mmengine - INFO - Epoch(train) [1][30/63] lr: 3.0000e-06 eta: 11 days, 5:00:25 time: 0.6841 data_time: 0.0346 memory: 16131 loss: 21.4808 loss_prob: 17.8362 loss_thr: 2.6555 loss_db: 0.9890 2022/10/25 19:03:11 - mmengine - INFO - Epoch(train) [1][35/63] lr: 3.0000e-06 eta: 11 days, 5:00:25 time: 0.8224 data_time: 0.0253 memory: 16131 loss: 19.9941 loss_prob: 16.4164 loss_thr: 2.5907 loss_db: 0.9869 2022/10/25 19:03:13 - mmengine - INFO - Epoch(train) [1][40/63] lr: 3.0000e-06 eta: 8 days, 13:17:16 time: 0.6783 data_time: 0.0046 memory: 16131 loss: 19.5058 loss_prob: 15.9433 loss_thr: 2.5742 loss_db: 0.9883 2022/10/25 19:03:17 - mmengine - INFO - Epoch(train) [1][45/63] lr: 3.0000e-06 eta: 8 days, 13:17:16 time: 0.6692 data_time: 0.0062 memory: 16131 loss: 19.2855 loss_prob: 15.7520 loss_thr: 2.5440 loss_db: 0.9895 2022/10/25 19:03:20 - mmengine - INFO - Epoch(train) [1][50/63] lr: 3.0000e-06 eta: 6 days, 23:10:45 time: 0.7078 data_time: 0.0189 memory: 16131 loss: 18.6262 loss_prob: 15.1693 loss_thr: 2.4686 loss_db: 0.9882 2022/10/25 19:03:26 - mmengine - INFO - Epoch(train) [1][55/63] lr: 3.0000e-06 eta: 6 days, 23:10:45 time: 0.8782 data_time: 0.0215 memory: 16131 loss: 18.1273 loss_prob: 14.7044 loss_thr: 2.4356 loss_db: 0.9872 2022/10/25 19:03:29 - mmengine - INFO - Epoch(train) [1][60/63] lr: 3.0000e-06 eta: 5 days, 22:21:25 time: 0.8748 data_time: 0.0084 memory: 16131 loss: 18.3208 loss_prob: 14.8506 loss_thr: 2.4814 loss_db: 0.9888 2022/10/25 19:03:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:03:47 - mmengine - INFO - Epoch(train) [2][5/63] lr: 1.8060e-05 eta: 5 days, 22:21:25 time: 1.8458 data_time: 0.2317 memory: 40880 loss: 17.5036 loss_prob: 14.1545 loss_thr: 2.3609 loss_db: 0.9881 2022/10/25 19:03:51 - mmengine - INFO - Epoch(train) [2][10/63] lr: 1.8060e-05 eta: 4 days, 23:37:54 time: 0.9208 data_time: 0.2365 memory: 16126 loss: 17.0013 loss_prob: 13.6806 loss_thr: 2.3327 loss_db: 0.9880 2022/10/25 19:03:54 - mmengine - INFO - Epoch(train) [2][15/63] lr: 1.8060e-05 eta: 4 days, 23:37:54 time: 0.7194 data_time: 0.0099 memory: 16126 loss: 16.6991 loss_prob: 13.4511 loss_thr: 2.2583 loss_db: 0.9897 2022/10/25 19:03:56 - mmengine - INFO - Epoch(train) [2][20/63] lr: 1.8060e-05 eta: 4 days, 10:41:47 time: 0.5904 data_time: 0.0069 memory: 16126 loss: 15.1295 loss_prob: 12.0512 loss_thr: 2.0885 loss_db: 0.9897 2022/10/25 19:03:59 - mmengine - INFO - Epoch(train) [2][25/63] lr: 1.8060e-05 eta: 4 days, 10:41:47 time: 0.5442 data_time: 0.0217 memory: 16126 loss: 13.0408 loss_prob: 10.1878 loss_thr: 1.8644 loss_db: 0.9886 2022/10/25 19:04:04 - mmengine - INFO - Epoch(train) [2][30/63] lr: 1.8060e-05 eta: 4 days, 0:58:11 time: 0.7797 data_time: 0.0364 memory: 16126 loss: 11.7409 loss_prob: 9.0636 loss_thr: 1.6905 loss_db: 0.9868 2022/10/25 19:04:08 - mmengine - INFO - Epoch(train) [2][35/63] lr: 1.8060e-05 eta: 4 days, 0:58:11 time: 0.8303 data_time: 0.0231 memory: 16126 loss: 10.9039 loss_prob: 8.3646 loss_thr: 1.5525 loss_db: 0.9868 2022/10/25 19:04:10 - mmengine - INFO - Epoch(train) [2][40/63] lr: 1.8060e-05 eta: 3 days, 16:46:33 time: 0.6053 data_time: 0.0067 memory: 16126 loss: 10.2683 loss_prob: 7.8954 loss_thr: 1.3840 loss_db: 0.9890 2022/10/25 19:04:13 - mmengine - INFO - Epoch(train) [2][45/63] lr: 1.8060e-05 eta: 3 days, 16:46:33 time: 0.5417 data_time: 0.0047 memory: 16126 loss: 9.7216 loss_prob: 7.4289 loss_thr: 1.3046 loss_db: 0.9881 2022/10/25 19:04:16 - mmengine - INFO - Epoch(train) [2][50/63] lr: 1.8060e-05 eta: 3 days, 9:55:28 time: 0.5472 data_time: 0.0172 memory: 16126 loss: 9.3158 loss_prob: 7.0362 loss_thr: 1.2942 loss_db: 0.9855 2022/10/25 19:04:23 - mmengine - INFO - Epoch(train) [2][55/63] lr: 1.8060e-05 eta: 3 days, 9:55:28 time: 1.0053 data_time: 0.0188 memory: 16126 loss: 8.9738 loss_prob: 6.7257 loss_thr: 1.2622 loss_db: 0.9859 2022/10/25 19:04:26 - mmengine - INFO - Epoch(train) [2][60/63] lr: 1.8060e-05 eta: 3 days, 4:57:52 time: 1.0035 data_time: 0.0090 memory: 16126 loss: 8.7331 loss_prob: 6.5006 loss_thr: 1.2467 loss_db: 0.9858 2022/10/25 19:04:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:04:36 - mmengine - INFO - Epoch(train) [3][5/63] lr: 3.3121e-05 eta: 3 days, 4:57:52 time: 1.0817 data_time: 0.2043 memory: 16126 loss: 8.4369 loss_prob: 6.2378 loss_thr: 1.2126 loss_db: 0.9865 2022/10/25 19:04:39 - mmengine - INFO - Epoch(train) [3][10/63] lr: 3.3121e-05 eta: 2 days, 23:11:04 time: 1.0309 data_time: 0.2044 memory: 16126 loss: 8.1850 loss_prob: 6.0032 loss_thr: 1.1967 loss_db: 0.9850 2022/10/25 19:04:43 - mmengine - INFO - Epoch(train) [3][15/63] lr: 3.3121e-05 eta: 2 days, 23:11:04 time: 0.7078 data_time: 0.0079 memory: 16126 loss: 8.0353 loss_prob: 5.8495 loss_thr: 1.1992 loss_db: 0.9867 2022/10/25 19:04:47 - mmengine - INFO - Epoch(train) [3][20/63] lr: 3.3121e-05 eta: 2 days, 19:27:54 time: 0.8116 data_time: 0.0056 memory: 16126 loss: 7.9014 loss_prob: 5.7271 loss_thr: 1.1867 loss_db: 0.9876 2022/10/25 19:04:51 - mmengine - INFO - Epoch(train) [3][25/63] lr: 3.3121e-05 eta: 2 days, 19:27:54 time: 0.8191 data_time: 0.0309 memory: 16126 loss: 7.7312 loss_prob: 5.5670 loss_thr: 1.1786 loss_db: 0.9855 2022/10/25 19:04:54 - mmengine - INFO - Epoch(train) [3][30/63] lr: 3.3121e-05 eta: 2 days, 16:09:26 time: 0.7631 data_time: 0.0380 memory: 16126 loss: 7.6153 loss_prob: 5.4488 loss_thr: 1.1799 loss_db: 0.9867 2022/10/25 19:04:57 - mmengine - INFO - Epoch(train) [3][35/63] lr: 3.3121e-05 eta: 2 days, 16:09:26 time: 0.6141 data_time: 0.0143 memory: 16126 loss: 7.5161 loss_prob: 5.3556 loss_thr: 1.1731 loss_db: 0.9875 2022/10/25 19:04:59 - mmengine - INFO - Epoch(train) [3][40/63] lr: 3.3121e-05 eta: 2 days, 12:55:52 time: 0.5125 data_time: 0.0076 memory: 16126 loss: 7.4104 loss_prob: 5.2484 loss_thr: 1.1758 loss_db: 0.9863 2022/10/25 19:05:03 - mmengine - INFO - Epoch(train) [3][45/63] lr: 3.3121e-05 eta: 2 days, 12:55:52 time: 0.6222 data_time: 0.0049 memory: 16126 loss: 7.2849 loss_prob: 5.1218 loss_thr: 1.1766 loss_db: 0.9866 2022/10/25 19:05:09 - mmengine - INFO - Epoch(train) [3][50/63] lr: 3.3121e-05 eta: 2 days, 10:33:05 time: 0.9156 data_time: 0.0266 memory: 16126 loss: 7.1471 loss_prob: 4.9897 loss_thr: 1.1705 loss_db: 0.9869 2022/10/25 19:05:11 - mmengine - INFO - Epoch(train) [3][55/63] lr: 3.3121e-05 eta: 2 days, 10:33:05 time: 0.8021 data_time: 0.0283 memory: 16126 loss: 7.0253 loss_prob: 4.8723 loss_thr: 1.1673 loss_db: 0.9857 2022/10/25 19:05:14 - mmengine - INFO - Epoch(train) [3][60/63] lr: 3.3121e-05 eta: 2 days, 8:01:16 time: 0.5547 data_time: 0.0070 memory: 16126 loss: 6.9234 loss_prob: 4.7721 loss_thr: 1.1643 loss_db: 0.9869 2022/10/25 19:05:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:05:23 - mmengine - INFO - Epoch(train) [4][5/63] lr: 4.8181e-05 eta: 2 days, 8:01:16 time: 0.9629 data_time: 0.2448 memory: 16126 loss: 6.7914 loss_prob: 4.6421 loss_thr: 1.1613 loss_db: 0.9879 2022/10/25 19:05:26 - mmengine - INFO - Epoch(train) [4][10/63] lr: 4.8181e-05 eta: 2 days, 5:24:30 time: 1.0034 data_time: 0.2454 memory: 16126 loss: 6.7020 loss_prob: 4.5476 loss_thr: 1.1659 loss_db: 0.9884 2022/10/25 19:05:29 - mmengine - INFO - Epoch(train) [4][15/63] lr: 4.8181e-05 eta: 2 days, 5:24:30 time: 0.6280 data_time: 0.0069 memory: 16126 loss: 6.6146 loss_prob: 4.4641 loss_thr: 1.1635 loss_db: 0.9869 2022/10/25 19:05:33 - mmengine - INFO - Epoch(train) [4][20/63] lr: 4.8181e-05 eta: 2 days, 3:35:36 time: 0.7457 data_time: 0.0067 memory: 16126 loss: 6.5383 loss_prob: 4.3896 loss_thr: 1.1634 loss_db: 0.9853 2022/10/25 19:05:37 - mmengine - INFO - Epoch(train) [4][25/63] lr: 4.8181e-05 eta: 2 days, 3:35:36 time: 0.7605 data_time: 0.0328 memory: 16126 loss: 6.4663 loss_prob: 4.3160 loss_thr: 1.1656 loss_db: 0.9847 2022/10/25 19:05:40 - mmengine - INFO - Epoch(train) [4][30/63] lr: 4.8181e-05 eta: 2 days, 1:54:20 time: 0.7054 data_time: 0.0322 memory: 16126 loss: 6.4190 loss_prob: 4.2605 loss_thr: 1.1714 loss_db: 0.9871 2022/10/25 19:05:43 - mmengine - INFO - Epoch(train) [4][35/63] lr: 4.8181e-05 eta: 2 days, 1:54:20 time: 0.6056 data_time: 0.0044 memory: 16126 loss: 6.3749 loss_prob: 4.2155 loss_thr: 1.1703 loss_db: 0.9891 2022/10/25 19:05:47 - mmengine - INFO - Epoch(train) [4][40/63] lr: 4.8181e-05 eta: 2 days, 0:20:11 time: 0.6743 data_time: 0.0051 memory: 16126 loss: 6.2848 loss_prob: 4.1314 loss_thr: 1.1648 loss_db: 0.9886 2022/10/25 19:05:49 - mmengine - INFO - Epoch(train) [4][45/63] lr: 4.8181e-05 eta: 2 days, 0:20:11 time: 0.6687 data_time: 0.0093 memory: 16126 loss: 6.2033 loss_prob: 4.0545 loss_thr: 1.1611 loss_db: 0.9877 2022/10/25 19:05:53 - mmengine - INFO - Epoch(train) [4][50/63] lr: 4.8181e-05 eta: 1 day, 22:50:59 time: 0.6188 data_time: 0.0244 memory: 16126 loss: 6.1504 loss_prob: 4.0019 loss_thr: 1.1628 loss_db: 0.9858 2022/10/25 19:05:56 - mmengine - INFO - Epoch(train) [4][55/63] lr: 4.8181e-05 eta: 1 day, 22:50:59 time: 0.6250 data_time: 0.0215 memory: 16126 loss: 6.0891 loss_prob: 3.9373 loss_thr: 1.1655 loss_db: 0.9863 2022/10/25 19:05:58 - mmengine - INFO - Epoch(train) [4][60/63] lr: 4.8181e-05 eta: 1 day, 21:23:49 time: 0.5172 data_time: 0.0060 memory: 16126 loss: 6.0298 loss_prob: 3.8789 loss_thr: 1.1627 loss_db: 0.9882 2022/10/25 19:06:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:06:08 - mmengine - INFO - Epoch(train) [5][5/63] lr: 6.3241e-05 eta: 1 day, 21:23:49 time: 1.1281 data_time: 0.2207 memory: 16126 loss: 5.9805 loss_prob: 3.8337 loss_thr: 1.1590 loss_db: 0.9879 2022/10/25 19:06:12 - mmengine - INFO - Epoch(train) [5][10/63] lr: 6.3241e-05 eta: 1 day, 20:04:48 time: 1.1805 data_time: 0.2199 memory: 16126 loss: 5.9994 loss_prob: 3.8496 loss_thr: 1.1607 loss_db: 0.9891 2022/10/25 19:06:15 - mmengine - INFO - Epoch(train) [5][15/63] lr: 6.3241e-05 eta: 1 day, 20:04:48 time: 0.6510 data_time: 0.0052 memory: 16126 loss: 5.9736 loss_prob: 3.8251 loss_thr: 1.1596 loss_db: 0.9888 2022/10/25 19:06:19 - mmengine - INFO - Epoch(train) [5][20/63] lr: 6.3241e-05 eta: 1 day, 19:00:01 time: 0.7106 data_time: 0.0199 memory: 16126 loss: 5.9177 loss_prob: 3.7694 loss_thr: 1.1627 loss_db: 0.9856 2022/10/25 19:06:23 - mmengine - INFO - Epoch(train) [5][25/63] lr: 6.3241e-05 eta: 1 day, 19:00:01 time: 0.8469 data_time: 0.0253 memory: 16126 loss: 5.8984 loss_prob: 3.7469 loss_thr: 1.1676 loss_db: 0.9839 2022/10/25 19:06:30 - mmengine - INFO - Epoch(train) [5][30/63] lr: 6.3241e-05 eta: 1 day, 18:14:37 time: 1.0429 data_time: 0.0306 memory: 16126 loss: 5.8717 loss_prob: 3.7253 loss_thr: 1.1614 loss_db: 0.9850 2022/10/25 19:06:33 - mmengine - INFO - Epoch(train) [5][35/63] lr: 6.3241e-05 eta: 1 day, 18:14:37 time: 0.9473 data_time: 0.0252 memory: 16126 loss: 5.8480 loss_prob: 3.7030 loss_thr: 1.1575 loss_db: 0.9875 2022/10/25 19:06:38 - mmengine - INFO - Epoch(train) [5][40/63] lr: 6.3241e-05 eta: 1 day, 17:22:21 time: 0.8108 data_time: 0.0058 memory: 16126 loss: 5.8159 loss_prob: 3.6691 loss_thr: 1.1582 loss_db: 0.9886 2022/10/25 19:06:43 - mmengine - INFO - Epoch(train) [5][45/63] lr: 6.3241e-05 eta: 1 day, 17:22:21 time: 0.9709 data_time: 0.0066 memory: 16126 loss: 5.7648 loss_prob: 3.6183 loss_thr: 1.1611 loss_db: 0.9853 2022/10/25 19:06:47 - mmengine - INFO - Epoch(train) [5][50/63] lr: 6.3241e-05 eta: 1 day, 16:36:49 time: 0.8898 data_time: 0.0190 memory: 16126 loss: 5.7402 loss_prob: 3.5898 loss_thr: 1.1654 loss_db: 0.9849 2022/10/25 19:06:50 - mmengine - INFO - Epoch(train) [5][55/63] lr: 6.3241e-05 eta: 1 day, 16:36:49 time: 0.7671 data_time: 0.0211 memory: 16126 loss: 5.7216 loss_prob: 3.5702 loss_thr: 1.1634 loss_db: 0.9879 2022/10/25 19:06:53 - mmengine - INFO - Epoch(train) [5][60/63] lr: 6.3241e-05 eta: 1 day, 15:43:49 time: 0.6320 data_time: 0.0072 memory: 16126 loss: 5.6873 loss_prob: 3.5415 loss_thr: 1.1581 loss_db: 0.9877 2022/10/25 19:06:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:07:02 - mmengine - INFO - Epoch(train) [6][5/63] lr: 7.8302e-05 eta: 1 day, 15:43:49 time: 0.9480 data_time: 0.2117 memory: 16126 loss: 5.6435 loss_prob: 3.4954 loss_thr: 1.1598 loss_db: 0.9882 2022/10/25 19:07:04 - mmengine - INFO - Epoch(train) [6][10/63] lr: 7.8302e-05 eta: 1 day, 14:42:33 time: 0.8936 data_time: 0.2120 memory: 16126 loss: 5.6139 loss_prob: 3.4631 loss_thr: 1.1617 loss_db: 0.9890 2022/10/25 19:07:07 - mmengine - INFO - Epoch(train) [6][15/63] lr: 7.8302e-05 eta: 1 day, 14:42:33 time: 0.4929 data_time: 0.0045 memory: 16126 loss: 5.5953 loss_prob: 3.4423 loss_thr: 1.1624 loss_db: 0.9906 2022/10/25 19:07:09 - mmengine - INFO - Epoch(train) [6][20/63] lr: 7.8302e-05 eta: 1 day, 13:51:49 time: 0.5046 data_time: 0.0044 memory: 16126 loss: 5.5930 loss_prob: 3.4436 loss_thr: 1.1581 loss_db: 0.9914 2022/10/25 19:07:12 - mmengine - INFO - Epoch(train) [6][25/63] lr: 7.8302e-05 eta: 1 day, 13:51:49 time: 0.5184 data_time: 0.0170 memory: 16126 loss: 5.5716 loss_prob: 3.4191 loss_thr: 1.1613 loss_db: 0.9912 2022/10/25 19:07:14 - mmengine - INFO - Epoch(train) [6][30/63] lr: 7.8302e-05 eta: 1 day, 13:05:16 time: 0.5390 data_time: 0.0427 memory: 16126 loss: 5.5122 loss_prob: 3.3604 loss_thr: 1.1615 loss_db: 0.9903 2022/10/25 19:07:17 - mmengine - INFO - Epoch(train) [6][35/63] lr: 7.8302e-05 eta: 1 day, 13:05:16 time: 0.5206 data_time: 0.0302 memory: 16126 loss: 5.4709 loss_prob: 3.3190 loss_thr: 1.1613 loss_db: 0.9906 2022/10/25 19:07:20 - mmengine - INFO - Epoch(train) [6][40/63] lr: 7.8302e-05 eta: 1 day, 12:20:16 time: 0.5087 data_time: 0.0045 memory: 16126 loss: 5.4503 loss_prob: 3.2964 loss_thr: 1.1631 loss_db: 0.9908 2022/10/25 19:07:24 - mmengine - INFO - Epoch(train) [6][45/63] lr: 7.8302e-05 eta: 1 day, 12:20:16 time: 0.7202 data_time: 0.0046 memory: 16126 loss: 5.4346 loss_prob: 3.2830 loss_thr: 1.1598 loss_db: 0.9918 2022/10/25 19:07:27 - mmengine - INFO - Epoch(train) [6][50/63] lr: 7.8302e-05 eta: 1 day, 11:47:22 time: 0.7891 data_time: 0.0088 memory: 16126 loss: 5.4382 loss_prob: 3.2869 loss_thr: 1.1582 loss_db: 0.9932 2022/10/25 19:07:31 - mmengine - INFO - Epoch(train) [6][55/63] lr: 7.8302e-05 eta: 1 day, 11:47:22 time: 0.6494 data_time: 0.0201 memory: 16126 loss: 5.4227 loss_prob: 3.2726 loss_thr: 1.1555 loss_db: 0.9946 2022/10/25 19:07:33 - mmengine - INFO - Epoch(train) [6][60/63] lr: 7.8302e-05 eta: 1 day, 11:09:47 time: 0.5971 data_time: 0.0164 memory: 16126 loss: 5.3962 loss_prob: 3.2414 loss_thr: 1.1581 loss_db: 0.9967 2022/10/25 19:07:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:07:40 - mmengine - INFO - Epoch(train) [7][5/63] lr: 9.3362e-05 eta: 1 day, 11:09:47 time: 0.7488 data_time: 0.1689 memory: 16126 loss: 5.3701 loss_prob: 3.2144 loss_thr: 1.1581 loss_db: 0.9976 2022/10/25 19:07:43 - mmengine - INFO - Epoch(train) [7][10/63] lr: 9.3362e-05 eta: 1 day, 10:26:30 time: 0.8592 data_time: 0.1691 memory: 16126 loss: 5.3987 loss_prob: 3.2398 loss_thr: 1.1621 loss_db: 0.9968 2022/10/25 19:07:46 - mmengine - INFO - Epoch(train) [7][15/63] lr: 9.3362e-05 eta: 1 day, 10:26:30 time: 0.5769 data_time: 0.0047 memory: 16126 loss: 5.4096 loss_prob: 3.2549 loss_thr: 1.1598 loss_db: 0.9949 2022/10/25 19:07:50 - mmengine - INFO - Epoch(train) [7][20/63] lr: 9.3362e-05 eta: 1 day, 9:55:25 time: 0.6702 data_time: 0.0061 memory: 16126 loss: 5.3970 loss_prob: 3.2451 loss_thr: 1.1574 loss_db: 0.9945 2022/10/25 19:07:55 - mmengine - INFO - Epoch(train) [7][25/63] lr: 9.3362e-05 eta: 1 day, 9:55:25 time: 0.9619 data_time: 0.0158 memory: 16126 loss: 5.4185 loss_prob: 3.2639 loss_thr: 1.1598 loss_db: 0.9949 2022/10/25 19:07:58 - mmengine - INFO - Epoch(train) [7][30/63] lr: 9.3362e-05 eta: 1 day, 9:30:25 time: 0.8185 data_time: 0.0327 memory: 16126 loss: 5.4273 loss_prob: 3.2681 loss_thr: 1.1650 loss_db: 0.9942 2022/10/25 19:08:05 - mmengine - INFO - Epoch(train) [7][35/63] lr: 9.3362e-05 eta: 1 day, 9:30:25 time: 0.9644 data_time: 0.0233 memory: 16126 loss: 5.4029 loss_prob: 3.2399 loss_thr: 1.1681 loss_db: 0.9949 2022/10/25 19:08:08 - mmengine - INFO - Epoch(train) [7][40/63] lr: 9.3362e-05 eta: 1 day, 9:12:48 time: 1.0256 data_time: 0.0061 memory: 16126 loss: 5.3886 loss_prob: 3.2295 loss_thr: 1.1635 loss_db: 0.9955 2022/10/25 19:08:11 - mmengine - INFO - Epoch(train) [7][45/63] lr: 9.3362e-05 eta: 1 day, 9:12:48 time: 0.6428 data_time: 0.0061 memory: 16126 loss: 5.3641 loss_prob: 3.2137 loss_thr: 1.1549 loss_db: 0.9955 2022/10/25 19:08:15 - mmengine - INFO - Epoch(train) [7][50/63] lr: 9.3362e-05 eta: 1 day, 8:46:06 time: 0.6874 data_time: 0.0183 memory: 16126 loss: 5.3401 loss_prob: 3.1853 loss_thr: 1.1583 loss_db: 0.9965 2022/10/25 19:08:20 - mmengine - INFO - Epoch(train) [7][55/63] lr: 9.3362e-05 eta: 1 day, 8:46:06 time: 0.8327 data_time: 0.0229 memory: 16126 loss: 5.3223 loss_prob: 3.1638 loss_thr: 1.1616 loss_db: 0.9969 2022/10/25 19:08:23 - mmengine - INFO - Epoch(train) [7][60/63] lr: 9.3362e-05 eta: 1 day, 8:22:26 time: 0.7508 data_time: 0.0094 memory: 16126 loss: 5.3088 loss_prob: 3.1545 loss_thr: 1.1571 loss_db: 0.9971 2022/10/25 19:08:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:08:32 - mmengine - INFO - Epoch(train) [8][5/63] lr: 1.0842e-04 eta: 1 day, 8:22:26 time: 1.0397 data_time: 0.2086 memory: 16126 loss: 5.2778 loss_prob: 3.1190 loss_thr: 1.1618 loss_db: 0.9971 2022/10/25 19:08:35 - mmengine - INFO - Epoch(train) [8][10/63] lr: 1.0842e-04 eta: 1 day, 7:51:18 time: 0.9068 data_time: 0.2073 memory: 16126 loss: 5.2528 loss_prob: 3.0934 loss_thr: 1.1618 loss_db: 0.9976 2022/10/25 19:08:39 - mmengine - INFO - Epoch(train) [8][15/63] lr: 1.0842e-04 eta: 1 day, 7:51:18 time: 0.7057 data_time: 0.0076 memory: 16126 loss: 5.2107 loss_prob: 3.0578 loss_thr: 1.1541 loss_db: 0.9988 2022/10/25 19:08:44 - mmengine - INFO - Epoch(train) [8][20/63] lr: 1.0842e-04 eta: 1 day, 7:34:27 time: 0.9152 data_time: 0.0042 memory: 16126 loss: 5.1983 loss_prob: 3.0463 loss_thr: 1.1527 loss_db: 0.9993 2022/10/25 19:08:47 - mmengine - INFO - Epoch(train) [8][25/63] lr: 1.0842e-04 eta: 1 day, 7:34:27 time: 0.7463 data_time: 0.0096 memory: 16126 loss: 5.1810 loss_prob: 3.0239 loss_thr: 1.1576 loss_db: 0.9995 2022/10/25 19:08:51 - mmengine - INFO - Epoch(train) [8][30/63] lr: 1.0842e-04 eta: 1 day, 7:13:23 time: 0.7298 data_time: 0.0336 memory: 16126 loss: 5.1589 loss_prob: 3.0012 loss_thr: 1.1580 loss_db: 0.9996 2022/10/25 19:08:54 - mmengine - INFO - Epoch(train) [8][35/63] lr: 1.0842e-04 eta: 1 day, 7:13:23 time: 0.7386 data_time: 0.0299 memory: 16126 loss: 5.1468 loss_prob: 2.9926 loss_thr: 1.1546 loss_db: 0.9997 2022/10/25 19:08:57 - mmengine - INFO - Epoch(train) [8][40/63] lr: 1.0842e-04 eta: 1 day, 6:48:49 time: 0.5622 data_time: 0.0061 memory: 16126 loss: 5.1700 loss_prob: 3.0163 loss_thr: 1.1541 loss_db: 0.9997 2022/10/25 19:09:00 - mmengine - INFO - Epoch(train) [8][45/63] lr: 1.0842e-04 eta: 1 day, 6:48:49 time: 0.5634 data_time: 0.0050 memory: 16126 loss: 5.1860 loss_prob: 3.0306 loss_thr: 1.1557 loss_db: 0.9997 2022/10/25 19:09:04 - mmengine - INFO - Epoch(train) [8][50/63] lr: 1.0842e-04 eta: 1 day, 6:29:21 time: 0.7228 data_time: 0.0188 memory: 16126 loss: 5.1622 loss_prob: 3.0114 loss_thr: 1.1511 loss_db: 0.9997 2022/10/25 19:09:07 - mmengine - INFO - Epoch(train) [8][55/63] lr: 1.0842e-04 eta: 1 day, 6:29:21 time: 0.7587 data_time: 0.0226 memory: 16126 loss: 5.1728 loss_prob: 3.0232 loss_thr: 1.1499 loss_db: 0.9998 2022/10/25 19:09:10 - mmengine - INFO - Epoch(train) [8][60/63] lr: 1.0842e-04 eta: 1 day, 6:07:46 time: 0.6069 data_time: 0.0098 memory: 16126 loss: 5.1853 loss_prob: 3.0291 loss_thr: 1.1564 loss_db: 0.9998 2022/10/25 19:09:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:09:17 - mmengine - INFO - Epoch(train) [9][5/63] lr: 1.2348e-04 eta: 1 day, 6:07:46 time: 0.8134 data_time: 0.1735 memory: 16126 loss: 5.1493 loss_prob: 2.9951 loss_thr: 1.1544 loss_db: 0.9998 2022/10/25 19:09:22 - mmengine - INFO - Epoch(train) [9][10/63] lr: 1.2348e-04 eta: 1 day, 5:46:47 time: 1.0286 data_time: 0.1734 memory: 16126 loss: 5.1502 loss_prob: 2.9940 loss_thr: 1.1563 loss_db: 0.9999 2022/10/25 19:09:27 - mmengine - INFO - Epoch(train) [9][15/63] lr: 1.2348e-04 eta: 1 day, 5:46:47 time: 0.9658 data_time: 0.0077 memory: 16126 loss: 5.1440 loss_prob: 2.9824 loss_thr: 1.1617 loss_db: 0.9999 2022/10/25 19:09:30 - mmengine - INFO - Epoch(train) [9][20/63] lr: 1.2348e-04 eta: 1 day, 5:32:49 time: 0.8527 data_time: 0.0125 memory: 16126 loss: 5.1141 loss_prob: 2.9572 loss_thr: 1.1570 loss_db: 0.9999 2022/10/25 19:09:33 - mmengine - INFO - Epoch(train) [9][25/63] lr: 1.2348e-04 eta: 1 day, 5:32:49 time: 0.5910 data_time: 0.0146 memory: 16126 loss: 5.1004 loss_prob: 2.9464 loss_thr: 1.1541 loss_db: 0.9999 2022/10/25 19:09:37 - mmengine - INFO - Epoch(train) [9][30/63] lr: 1.2348e-04 eta: 1 day, 5:13:59 time: 0.6236 data_time: 0.0335 memory: 16126 loss: 5.0999 loss_prob: 2.9401 loss_thr: 1.1599 loss_db: 0.9999 2022/10/25 19:09:40 - mmengine - INFO - Epoch(train) [9][35/63] lr: 1.2348e-04 eta: 1 day, 5:13:59 time: 0.7479 data_time: 0.0300 memory: 16126 loss: 5.0966 loss_prob: 2.9353 loss_thr: 1.1613 loss_db: 0.9999 2022/10/25 19:09:43 - mmengine - INFO - Epoch(train) [9][40/63] lr: 1.2348e-04 eta: 1 day, 4:56:37 time: 0.6565 data_time: 0.0092 memory: 16126 loss: 5.1032 loss_prob: 2.9436 loss_thr: 1.1596 loss_db: 0.9999 2022/10/25 19:09:47 - mmengine - INFO - Epoch(train) [9][45/63] lr: 1.2348e-04 eta: 1 day, 4:56:37 time: 0.7109 data_time: 0.0110 memory: 16126 loss: 5.1073 loss_prob: 2.9476 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:09:51 - mmengine - INFO - Epoch(train) [9][50/63] lr: 1.2348e-04 eta: 1 day, 4:42:44 time: 0.7836 data_time: 0.0158 memory: 16126 loss: 5.1029 loss_prob: 2.9454 loss_thr: 1.1575 loss_db: 0.9999 2022/10/25 19:09:55 - mmengine - INFO - Epoch(train) [9][55/63] lr: 1.2348e-04 eta: 1 day, 4:42:44 time: 0.7179 data_time: 0.0197 memory: 16126 loss: 5.0905 loss_prob: 2.9356 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 19:09:58 - mmengine - INFO - Epoch(train) [9][60/63] lr: 1.2348e-04 eta: 1 day, 4:27:49 time: 0.7153 data_time: 0.0145 memory: 16126 loss: 5.0919 loss_prob: 2.9375 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:10:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:10:08 - mmengine - INFO - Epoch(train) [10][5/63] lr: 1.3854e-04 eta: 1 day, 4:27:49 time: 1.1477 data_time: 0.2376 memory: 16126 loss: 5.1079 loss_prob: 2.9505 loss_thr: 1.1575 loss_db: 0.9999 2022/10/25 19:10:11 - mmengine - INFO - Epoch(train) [10][10/63] lr: 1.3854e-04 eta: 1 day, 4:11:12 time: 1.0220 data_time: 0.2355 memory: 16126 loss: 5.1142 loss_prob: 2.9577 loss_thr: 1.1566 loss_db: 0.9999 2022/10/25 19:10:14 - mmengine - INFO - Epoch(train) [10][15/63] lr: 1.3854e-04 eta: 1 day, 4:11:12 time: 0.5181 data_time: 0.0091 memory: 16126 loss: 5.1316 loss_prob: 2.9762 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:10:18 - mmengine - INFO - Epoch(train) [10][20/63] lr: 1.3854e-04 eta: 1 day, 3:56:42 time: 0.6819 data_time: 0.0096 memory: 16126 loss: 5.1519 loss_prob: 2.9944 loss_thr: 1.1576 loss_db: 0.9999 2022/10/25 19:10:23 - mmengine - INFO - Epoch(train) [10][25/63] lr: 1.3854e-04 eta: 1 day, 3:56:42 time: 0.9638 data_time: 0.0358 memory: 16126 loss: 5.1566 loss_prob: 2.9969 loss_thr: 1.1599 loss_db: 0.9998 2022/10/25 19:10:26 - mmengine - INFO - Epoch(train) [10][30/63] lr: 1.3854e-04 eta: 1 day, 3:45:29 time: 0.8161 data_time: 0.0351 memory: 16126 loss: 5.1649 loss_prob: 3.0036 loss_thr: 1.1615 loss_db: 0.9997 2022/10/25 19:10:29 - mmengine - INFO - Epoch(train) [10][35/63] lr: 1.3854e-04 eta: 1 day, 3:45:29 time: 0.6181 data_time: 0.0059 memory: 16126 loss: 5.1407 loss_prob: 2.9831 loss_thr: 1.1578 loss_db: 0.9998 2022/10/25 19:10:32 - mmengine - INFO - Epoch(train) [10][40/63] lr: 1.3854e-04 eta: 1 day, 3:31:01 time: 0.6411 data_time: 0.0058 memory: 16126 loss: 5.1024 loss_prob: 2.9500 loss_thr: 1.1525 loss_db: 0.9999 2022/10/25 19:10:35 - mmengine - INFO - Epoch(train) [10][45/63] lr: 1.3854e-04 eta: 1 day, 3:31:01 time: 0.6062 data_time: 0.0055 memory: 16126 loss: 5.1078 loss_prob: 2.9537 loss_thr: 1.1542 loss_db: 0.9999 2022/10/25 19:10:38 - mmengine - INFO - Epoch(train) [10][50/63] lr: 1.3854e-04 eta: 1 day, 3:16:18 time: 0.6050 data_time: 0.0441 memory: 16126 loss: 5.1173 loss_prob: 2.9630 loss_thr: 1.1545 loss_db: 0.9999 2022/10/25 19:10:42 - mmengine - INFO - Epoch(train) [10][55/63] lr: 1.3854e-04 eta: 1 day, 3:16:18 time: 0.6433 data_time: 0.0450 memory: 16126 loss: 5.1009 loss_prob: 2.9462 loss_thr: 1.1548 loss_db: 0.9998 2022/10/25 19:10:46 - mmengine - INFO - Epoch(train) [10][60/63] lr: 1.3854e-04 eta: 1 day, 3:05:15 time: 0.7659 data_time: 0.0061 memory: 16126 loss: 5.0880 loss_prob: 2.9285 loss_thr: 1.1596 loss_db: 0.9998 2022/10/25 19:10:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:10:56 - mmengine - INFO - Epoch(train) [11][5/63] lr: 1.5360e-04 eta: 1 day, 3:05:15 time: 1.1765 data_time: 0.1884 memory: 16126 loss: 5.0863 loss_prob: 2.9306 loss_thr: 1.1558 loss_db: 0.9999 2022/10/25 19:11:00 - mmengine - INFO - Epoch(train) [11][10/63] lr: 1.5360e-04 eta: 1 day, 2:56:40 time: 1.2657 data_time: 0.1943 memory: 16126 loss: 5.0649 loss_prob: 2.9113 loss_thr: 1.1537 loss_db: 0.9999 2022/10/25 19:11:03 - mmengine - INFO - Epoch(train) [11][15/63] lr: 1.5360e-04 eta: 1 day, 2:56:40 time: 0.7085 data_time: 0.0149 memory: 16126 loss: 5.0631 loss_prob: 2.9125 loss_thr: 1.1508 loss_db: 0.9999 2022/10/25 19:11:07 - mmengine - INFO - Epoch(train) [11][20/63] lr: 1.5360e-04 eta: 1 day, 2:44:08 time: 0.6529 data_time: 0.0063 memory: 16126 loss: 5.0672 loss_prob: 2.9154 loss_thr: 1.1518 loss_db: 0.9999 2022/10/25 19:11:09 - mmengine - INFO - Epoch(train) [11][25/63] lr: 1.5360e-04 eta: 1 day, 2:44:08 time: 0.6124 data_time: 0.0209 memory: 16126 loss: 5.0554 loss_prob: 2.8996 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:11:13 - mmengine - INFO - Epoch(train) [11][30/63] lr: 1.5360e-04 eta: 1 day, 2:31:28 time: 0.6263 data_time: 0.0322 memory: 16126 loss: 5.0544 loss_prob: 2.8967 loss_thr: 1.1578 loss_db: 0.9999 2022/10/25 19:11:17 - mmengine - INFO - Epoch(train) [11][35/63] lr: 1.5360e-04 eta: 1 day, 2:31:28 time: 0.7653 data_time: 0.0160 memory: 16126 loss: 5.0541 loss_prob: 2.8963 loss_thr: 1.1579 loss_db: 0.9999 2022/10/25 19:11:21 - mmengine - INFO - Epoch(train) [11][40/63] lr: 1.5360e-04 eta: 1 day, 2:23:01 time: 0.8324 data_time: 0.0096 memory: 16126 loss: 5.0397 loss_prob: 2.8846 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 19:11:24 - mmengine - INFO - Epoch(train) [11][45/63] lr: 1.5360e-04 eta: 1 day, 2:23:01 time: 0.7173 data_time: 0.0110 memory: 16126 loss: 5.0470 loss_prob: 2.8880 loss_thr: 1.1595 loss_db: 0.9995 2022/10/25 19:11:27 - mmengine - INFO - Epoch(train) [11][50/63] lr: 1.5360e-04 eta: 1 day, 2:10:43 time: 0.6088 data_time: 0.0339 memory: 16126 loss: 5.0345 loss_prob: 2.8780 loss_thr: 1.1571 loss_db: 0.9994 2022/10/25 19:11:34 - mmengine - INFO - Epoch(train) [11][55/63] lr: 1.5360e-04 eta: 1 day, 2:10:43 time: 1.0217 data_time: 0.0390 memory: 16126 loss: 5.0172 loss_prob: 2.8626 loss_thr: 1.1547 loss_db: 0.9999 2022/10/25 19:11:39 - mmengine - INFO - Epoch(train) [11][60/63] lr: 1.5360e-04 eta: 1 day, 2:08:54 time: 1.1696 data_time: 0.0122 memory: 16126 loss: 5.0225 loss_prob: 2.8660 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 19:11:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:11:50 - mmengine - INFO - Epoch(train) [12][5/63] lr: 1.6866e-04 eta: 1 day, 2:08:54 time: 1.2545 data_time: 0.2059 memory: 16126 loss: 5.0495 loss_prob: 2.9040 loss_thr: 1.1461 loss_db: 0.9995 2022/10/25 19:11:54 - mmengine - INFO - Epoch(train) [12][10/63] lr: 1.6866e-04 eta: 1 day, 2:00:41 time: 1.1864 data_time: 0.2046 memory: 16126 loss: 5.0423 loss_prob: 2.8942 loss_thr: 1.1489 loss_db: 0.9993 2022/10/25 19:11:56 - mmengine - INFO - Epoch(train) [12][15/63] lr: 1.6866e-04 eta: 1 day, 2:00:41 time: 0.6565 data_time: 0.0087 memory: 16126 loss: 5.0315 loss_prob: 2.8819 loss_thr: 1.1498 loss_db: 0.9998 2022/10/25 19:11:59 - mmengine - INFO - Epoch(train) [12][20/63] lr: 1.6866e-04 eta: 1 day, 1:47:31 time: 0.5093 data_time: 0.0091 memory: 16126 loss: 5.0446 loss_prob: 2.8902 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:12:02 - mmengine - INFO - Epoch(train) [12][25/63] lr: 1.6866e-04 eta: 1 day, 1:47:31 time: 0.5387 data_time: 0.0393 memory: 16126 loss: 5.0369 loss_prob: 2.8856 loss_thr: 1.1513 loss_db: 0.9999 2022/10/25 19:12:05 - mmengine - INFO - Epoch(train) [12][30/63] lr: 1.6866e-04 eta: 1 day, 1:37:13 time: 0.6552 data_time: 0.0524 memory: 16126 loss: 5.0289 loss_prob: 2.8790 loss_thr: 1.1500 loss_db: 0.9999 2022/10/25 19:12:08 - mmengine - INFO - Epoch(train) [12][35/63] lr: 1.6866e-04 eta: 1 day, 1:37:13 time: 0.6154 data_time: 0.0177 memory: 16126 loss: 5.0194 loss_prob: 2.8679 loss_thr: 1.1515 loss_db: 0.9999 2022/10/25 19:12:11 - mmengine - INFO - Epoch(train) [12][40/63] lr: 1.6866e-04 eta: 1 day, 1:25:35 time: 0.5608 data_time: 0.0104 memory: 16126 loss: 5.0066 loss_prob: 2.8600 loss_thr: 1.1469 loss_db: 0.9997 2022/10/25 19:12:14 - mmengine - INFO - Epoch(train) [12][45/63] lr: 1.6866e-04 eta: 1 day, 1:25:35 time: 0.5957 data_time: 0.0110 memory: 16126 loss: 5.0148 loss_prob: 2.8632 loss_thr: 1.1519 loss_db: 0.9997 2022/10/25 19:12:17 - mmengine - INFO - Epoch(train) [12][50/63] lr: 1.6866e-04 eta: 1 day, 1:14:30 time: 0.5748 data_time: 0.0196 memory: 16126 loss: 5.0238 loss_prob: 2.8707 loss_thr: 1.1532 loss_db: 0.9999 2022/10/25 19:12:21 - mmengine - INFO - Epoch(train) [12][55/63] lr: 1.6866e-04 eta: 1 day, 1:14:30 time: 0.7226 data_time: 0.0250 memory: 16126 loss: 5.0372 loss_prob: 2.8846 loss_thr: 1.1527 loss_db: 0.9999 2022/10/25 19:12:25 - mmengine - INFO - Epoch(train) [12][60/63] lr: 1.6866e-04 eta: 1 day, 1:07:40 time: 0.8131 data_time: 0.0168 memory: 16126 loss: 5.0280 loss_prob: 2.8759 loss_thr: 1.1523 loss_db: 0.9998 2022/10/25 19:12:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:12:31 - mmengine - INFO - Epoch(train) [13][5/63] lr: 1.8372e-04 eta: 1 day, 1:07:40 time: 0.8018 data_time: 0.1575 memory: 16126 loss: 5.0138 loss_prob: 2.8647 loss_thr: 1.1494 loss_db: 0.9998 2022/10/25 19:12:34 - mmengine - INFO - Epoch(train) [13][10/63] lr: 1.8372e-04 eta: 1 day, 0:54:01 time: 0.7498 data_time: 0.1620 memory: 16126 loss: 5.0022 loss_prob: 2.8591 loss_thr: 1.1442 loss_db: 0.9988 2022/10/25 19:12:40 - mmengine - INFO - Epoch(train) [13][15/63] lr: 1.8372e-04 eta: 1 day, 0:54:01 time: 0.9333 data_time: 0.0147 memory: 16126 loss: 5.0055 loss_prob: 2.8618 loss_thr: 1.1459 loss_db: 0.9978 2022/10/25 19:12:43 - mmengine - INFO - Epoch(train) [13][20/63] lr: 1.8372e-04 eta: 1 day, 0:48:49 time: 0.8859 data_time: 0.0053 memory: 16126 loss: 5.0086 loss_prob: 2.8567 loss_thr: 1.1532 loss_db: 0.9987 2022/10/25 19:12:48 - mmengine - INFO - Epoch(train) [13][25/63] lr: 1.8372e-04 eta: 1 day, 0:48:49 time: 0.8244 data_time: 0.0092 memory: 16126 loss: 4.9809 loss_prob: 2.8366 loss_thr: 1.1448 loss_db: 0.9995 2022/10/25 19:12:52 - mmengine - INFO - Epoch(train) [13][30/63] lr: 1.8372e-04 eta: 1 day, 0:44:04 time: 0.9069 data_time: 0.0312 memory: 16126 loss: 4.9738 loss_prob: 2.8350 loss_thr: 1.1401 loss_db: 0.9988 2022/10/25 19:12:54 - mmengine - INFO - Epoch(train) [13][35/63] lr: 1.8372e-04 eta: 1 day, 0:44:04 time: 0.5963 data_time: 0.0300 memory: 16126 loss: 5.0071 loss_prob: 2.8599 loss_thr: 1.1493 loss_db: 0.9978 2022/10/25 19:12:57 - mmengine - INFO - Epoch(train) [13][40/63] lr: 1.8372e-04 eta: 1 day, 0:34:10 time: 0.5714 data_time: 0.0076 memory: 16126 loss: 5.0384 loss_prob: 2.8813 loss_thr: 1.1589 loss_db: 0.9982 2022/10/25 19:13:02 - mmengine - INFO - Epoch(train) [13][45/63] lr: 1.8372e-04 eta: 1 day, 0:34:10 time: 0.7887 data_time: 0.0041 memory: 16126 loss: 5.0315 loss_prob: 2.8748 loss_thr: 1.1571 loss_db: 0.9995 2022/10/25 19:13:06 - mmengine - INFO - Epoch(train) [13][50/63] lr: 1.8372e-04 eta: 1 day, 0:29:19 time: 0.8815 data_time: 0.0089 memory: 16126 loss: 4.9991 loss_prob: 2.8554 loss_thr: 1.1472 loss_db: 0.9966 2022/10/25 19:13:10 - mmengine - INFO - Epoch(train) [13][55/63] lr: 1.8372e-04 eta: 1 day, 0:29:19 time: 0.7701 data_time: 0.0334 memory: 16126 loss: 4.9960 loss_prob: 2.8574 loss_thr: 1.1445 loss_db: 0.9942 2022/10/25 19:13:14 - mmengine - INFO - Epoch(train) [13][60/63] lr: 1.8372e-04 eta: 1 day, 0:23:25 time: 0.8047 data_time: 0.0346 memory: 16126 loss: 4.9883 loss_prob: 2.8500 loss_thr: 1.1416 loss_db: 0.9966 2022/10/25 19:13:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:13:23 - mmengine - INFO - Epoch(train) [14][5/63] lr: 1.9878e-04 eta: 1 day, 0:23:25 time: 1.1331 data_time: 0.1706 memory: 16126 loss: 4.9314 loss_prob: 2.8277 loss_thr: 1.1267 loss_db: 0.9769 2022/10/25 19:13:25 - mmengine - INFO - Epoch(train) [14][10/63] lr: 1.9878e-04 eta: 1 day, 0:13:29 time: 0.8832 data_time: 0.1709 memory: 16126 loss: 5.0979 loss_prob: 2.9260 loss_thr: 1.2123 loss_db: 0.9595 2022/10/25 19:13:28 - mmengine - INFO - Epoch(train) [14][15/63] lr: 1.9878e-04 eta: 1 day, 0:13:29 time: 0.5696 data_time: 0.0048 memory: 16126 loss: 6.0947 loss_prob: 3.3563 loss_thr: 1.7706 loss_db: 0.9678 2022/10/25 19:13:31 - mmengine - INFO - Epoch(train) [14][20/63] lr: 1.9878e-04 eta: 1 day, 0:04:24 time: 0.5670 data_time: 0.0043 memory: 16126 loss: 6.4151 loss_prob: 3.4559 loss_thr: 1.9805 loss_db: 0.9787 2022/10/25 19:13:35 - mmengine - INFO - Epoch(train) [14][25/63] lr: 1.9878e-04 eta: 1 day, 0:04:24 time: 0.6520 data_time: 0.0134 memory: 16126 loss: 6.1205 loss_prob: 3.5844 loss_thr: 1.5528 loss_db: 0.9833 2022/10/25 19:13:38 - mmengine - INFO - Epoch(train) [14][30/63] lr: 1.9878e-04 eta: 23:56:40 time: 0.6464 data_time: 0.0348 memory: 16126 loss: 6.5583 loss_prob: 4.1086 loss_thr: 1.4623 loss_db: 0.9874 2022/10/25 19:13:40 - mmengine - INFO - Epoch(train) [14][35/63] lr: 1.9878e-04 eta: 23:56:40 time: 0.5218 data_time: 0.0265 memory: 16126 loss: 6.7226 loss_prob: 4.2121 loss_thr: 1.5183 loss_db: 0.9921 2022/10/25 19:13:44 - mmengine - INFO - Epoch(train) [14][40/63] lr: 1.9878e-04 eta: 23:49:19 time: 0.6596 data_time: 0.0092 memory: 16126 loss: 6.4816 loss_prob: 4.0632 loss_thr: 1.4231 loss_db: 0.9952 2022/10/25 19:13:48 - mmengine - INFO - Epoch(train) [14][45/63] lr: 1.9878e-04 eta: 23:49:19 time: 0.8118 data_time: 0.0089 memory: 16126 loss: 6.2408 loss_prob: 3.9150 loss_thr: 1.3290 loss_db: 0.9968 2022/10/25 19:13:51 - mmengine - INFO - Epoch(train) [14][50/63] lr: 1.9878e-04 eta: 23:42:25 time: 0.6795 data_time: 0.0121 memory: 16126 loss: 6.0808 loss_prob: 3.8068 loss_thr: 1.2767 loss_db: 0.9972 2022/10/25 19:13:56 - mmengine - INFO - Epoch(train) [14][55/63] lr: 1.9878e-04 eta: 23:42:25 time: 0.7615 data_time: 0.0270 memory: 16126 loss: 5.8461 loss_prob: 3.6322 loss_thr: 1.2156 loss_db: 0.9983 2022/10/25 19:13:59 - mmengine - INFO - Epoch(train) [14][60/63] lr: 1.9878e-04 eta: 23:36:50 time: 0.7605 data_time: 0.0200 memory: 16126 loss: 5.6691 loss_prob: 3.4648 loss_thr: 1.2056 loss_db: 0.9987 2022/10/25 19:14:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:14:09 - mmengine - INFO - Epoch(train) [15][5/63] lr: 2.1384e-04 eta: 23:36:50 time: 1.1576 data_time: 0.2282 memory: 16126 loss: 5.6300 loss_prob: 3.3587 loss_thr: 1.2755 loss_db: 0.9957 2022/10/25 19:14:12 - mmengine - INFO - Epoch(train) [15][10/63] lr: 2.1384e-04 eta: 23:32:36 time: 1.1943 data_time: 0.2361 memory: 16126 loss: 5.5707 loss_prob: 3.3181 loss_thr: 1.2559 loss_db: 0.9967 2022/10/25 19:14:15 - mmengine - INFO - Epoch(train) [15][15/63] lr: 2.1384e-04 eta: 23:32:36 time: 0.5893 data_time: 0.0147 memory: 16126 loss: 5.4796 loss_prob: 3.2828 loss_thr: 1.1975 loss_db: 0.9992 2022/10/25 19:14:18 - mmengine - INFO - Epoch(train) [15][20/63] lr: 2.1384e-04 eta: 23:24:11 time: 0.5383 data_time: 0.0067 memory: 16126 loss: 5.4193 loss_prob: 3.2366 loss_thr: 1.1833 loss_db: 0.9995 2022/10/25 19:14:20 - mmengine - INFO - Epoch(train) [15][25/63] lr: 2.1384e-04 eta: 23:24:11 time: 0.5170 data_time: 0.0245 memory: 16126 loss: 5.3498 loss_prob: 3.1773 loss_thr: 1.1726 loss_db: 0.9999 2022/10/25 19:14:23 - mmengine - INFO - Epoch(train) [15][30/63] lr: 2.1384e-04 eta: 23:16:12 time: 0.5558 data_time: 0.0244 memory: 16126 loss: 5.2929 loss_prob: 3.1106 loss_thr: 1.1825 loss_db: 0.9998 2022/10/25 19:14:28 - mmengine - INFO - Epoch(train) [15][35/63] lr: 2.1384e-04 eta: 23:16:12 time: 0.7813 data_time: 0.0205 memory: 16126 loss: 5.2532 loss_prob: 3.0667 loss_thr: 1.1867 loss_db: 0.9998 2022/10/25 19:14:32 - mmengine - INFO - Epoch(train) [15][40/63] lr: 2.1384e-04 eta: 23:12:24 time: 0.8550 data_time: 0.0221 memory: 16126 loss: 5.2633 loss_prob: 3.0927 loss_thr: 1.1707 loss_db: 0.9999 2022/10/25 19:14:35 - mmengine - INFO - Epoch(train) [15][45/63] lr: 2.1384e-04 eta: 23:12:24 time: 0.6548 data_time: 0.0062 memory: 16126 loss: 5.2473 loss_prob: 3.0825 loss_thr: 1.1650 loss_db: 0.9998 2022/10/25 19:14:37 - mmengine - INFO - Epoch(train) [15][50/63] lr: 2.1384e-04 eta: 23:04:56 time: 0.5731 data_time: 0.0138 memory: 16126 loss: 5.2060 loss_prob: 3.0369 loss_thr: 1.1692 loss_db: 0.9999 2022/10/25 19:14:41 - mmengine - INFO - Epoch(train) [15][55/63] lr: 2.1384e-04 eta: 23:04:56 time: 0.5940 data_time: 0.0318 memory: 16126 loss: 5.1846 loss_prob: 3.0135 loss_thr: 1.1713 loss_db: 0.9999 2022/10/25 19:14:45 - mmengine - INFO - Epoch(train) [15][60/63] lr: 2.1384e-04 eta: 23:00:45 time: 0.8097 data_time: 0.0304 memory: 16126 loss: 5.2074 loss_prob: 3.0400 loss_thr: 1.1675 loss_db: 0.9999 2022/10/25 19:14:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:14:56 - mmengine - INFO - Epoch(train) [16][5/63] lr: 2.2890e-04 eta: 23:00:45 time: 1.3159 data_time: 0.1624 memory: 16126 loss: 5.2528 loss_prob: 3.0901 loss_thr: 1.1628 loss_db: 0.9999 2022/10/25 19:15:01 - mmengine - INFO - Epoch(train) [16][10/63] lr: 2.2890e-04 eta: 22:59:05 time: 1.3337 data_time: 0.1640 memory: 16126 loss: 5.3311 loss_prob: 3.1683 loss_thr: 1.1630 loss_db: 0.9999 2022/10/25 19:15:04 - mmengine - INFO - Epoch(train) [16][15/63] lr: 2.2890e-04 eta: 22:59:05 time: 0.7572 data_time: 0.0185 memory: 16126 loss: 5.3779 loss_prob: 3.2132 loss_thr: 1.1648 loss_db: 1.0000 2022/10/25 19:15:07 - mmengine - INFO - Epoch(train) [16][20/63] lr: 2.2890e-04 eta: 22:51:55 time: 0.5672 data_time: 0.0155 memory: 16126 loss: 5.3518 loss_prob: 3.1826 loss_thr: 1.1693 loss_db: 0.9999 2022/10/25 19:15:10 - mmengine - INFO - Epoch(train) [16][25/63] lr: 2.2890e-04 eta: 22:51:55 time: 0.5678 data_time: 0.0150 memory: 16126 loss: 5.2768 loss_prob: 3.1064 loss_thr: 1.1706 loss_db: 0.9997 2022/10/25 19:15:12 - mmengine - INFO - Epoch(train) [16][30/63] lr: 2.2890e-04 eta: 22:44:36 time: 0.5438 data_time: 0.0345 memory: 16126 loss: 5.2221 loss_prob: 3.0430 loss_thr: 1.1798 loss_db: 0.9992 2022/10/25 19:15:16 - mmengine - INFO - Epoch(train) [16][35/63] lr: 2.2890e-04 eta: 22:44:36 time: 0.6494 data_time: 0.0243 memory: 16126 loss: 5.2191 loss_prob: 3.0439 loss_thr: 1.1758 loss_db: 0.9993 2022/10/25 19:15:20 - mmengine - INFO - Epoch(train) [16][40/63] lr: 2.2890e-04 eta: 22:40:07 time: 0.7556 data_time: 0.0080 memory: 16126 loss: 5.2421 loss_prob: 3.0780 loss_thr: 1.1641 loss_db: 1.0000 2022/10/25 19:15:23 - mmengine - INFO - Epoch(train) [16][45/63] lr: 2.2890e-04 eta: 22:40:07 time: 0.7140 data_time: 0.0077 memory: 16126 loss: 5.2859 loss_prob: 3.1179 loss_thr: 1.1681 loss_db: 0.9999 2022/10/25 19:15:26 - mmengine - INFO - Epoch(train) [16][50/63] lr: 2.2890e-04 eta: 22:34:08 time: 0.6301 data_time: 0.0125 memory: 16126 loss: 5.2885 loss_prob: 3.1216 loss_thr: 1.1672 loss_db: 0.9997 2022/10/25 19:15:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:15:31 - mmengine - INFO - Epoch(train) [16][55/63] lr: 2.2890e-04 eta: 22:34:08 time: 0.7233 data_time: 0.0260 memory: 16126 loss: 5.2523 loss_prob: 3.0878 loss_thr: 1.1648 loss_db: 0.9998 2022/10/25 19:15:33 - mmengine - INFO - Epoch(train) [16][60/63] lr: 2.2890e-04 eta: 22:28:56 time: 0.6837 data_time: 0.0196 memory: 16126 loss: 5.2270 loss_prob: 3.0656 loss_thr: 1.1613 loss_db: 1.0000 2022/10/25 19:15:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:15:40 - mmengine - INFO - Epoch(train) [17][5/63] lr: 2.4396e-04 eta: 22:28:56 time: 0.8224 data_time: 0.2349 memory: 16126 loss: 5.1436 loss_prob: 2.9895 loss_thr: 1.1541 loss_db: 1.0000 2022/10/25 19:15:45 - mmengine - INFO - Epoch(train) [17][10/63] lr: 2.4396e-04 eta: 22:24:30 time: 1.0656 data_time: 0.2325 memory: 16126 loss: 5.1496 loss_prob: 2.9909 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:15:48 - mmengine - INFO - Epoch(train) [17][15/63] lr: 2.4396e-04 eta: 22:24:30 time: 0.7777 data_time: 0.0057 memory: 16126 loss: 5.1854 loss_prob: 3.0255 loss_thr: 1.1599 loss_db: 1.0000 2022/10/25 19:15:51 - mmengine - INFO - Epoch(train) [17][20/63] lr: 2.4396e-04 eta: 22:18:04 time: 0.5657 data_time: 0.0059 memory: 16126 loss: 5.2058 loss_prob: 3.0508 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 19:15:55 - mmengine - INFO - Epoch(train) [17][25/63] lr: 2.4396e-04 eta: 22:18:04 time: 0.6738 data_time: 0.0224 memory: 16126 loss: 5.2182 loss_prob: 3.0599 loss_thr: 1.1586 loss_db: 0.9998 2022/10/25 19:15:58 - mmengine - INFO - Epoch(train) [17][30/63] lr: 2.4396e-04 eta: 22:13:02 time: 0.6699 data_time: 0.0373 memory: 16126 loss: 5.2024 loss_prob: 3.0397 loss_thr: 1.1629 loss_db: 0.9998 2022/10/25 19:16:00 - mmengine - INFO - Epoch(train) [17][35/63] lr: 2.4396e-04 eta: 22:13:02 time: 0.5659 data_time: 0.0212 memory: 16126 loss: 5.1882 loss_prob: 3.0244 loss_thr: 1.1639 loss_db: 0.9999 2022/10/25 19:16:04 - mmengine - INFO - Epoch(train) [17][40/63] lr: 2.4396e-04 eta: 22:08:19 time: 0.6903 data_time: 0.0051 memory: 16126 loss: 5.2015 loss_prob: 3.0378 loss_thr: 1.1638 loss_db: 0.9999 2022/10/25 19:16:08 - mmengine - INFO - Epoch(train) [17][45/63] lr: 2.4396e-04 eta: 22:08:19 time: 0.8047 data_time: 0.0047 memory: 16126 loss: 5.1904 loss_prob: 3.0252 loss_thr: 1.1654 loss_db: 0.9998 2022/10/25 19:16:12 - mmengine - INFO - Epoch(train) [17][50/63] lr: 2.4396e-04 eta: 22:04:08 time: 0.7288 data_time: 0.0149 memory: 16126 loss: 5.1562 loss_prob: 2.9887 loss_thr: 1.1677 loss_db: 0.9998 2022/10/25 19:16:16 - mmengine - INFO - Epoch(train) [17][55/63] lr: 2.4396e-04 eta: 22:04:08 time: 0.7699 data_time: 0.0199 memory: 16126 loss: 5.1349 loss_prob: 2.9704 loss_thr: 1.1645 loss_db: 1.0000 2022/10/25 19:16:22 - mmengine - INFO - Epoch(train) [17][60/63] lr: 2.4396e-04 eta: 22:03:35 time: 1.0328 data_time: 0.0102 memory: 16126 loss: 5.1257 loss_prob: 2.9682 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 19:16:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:16:31 - mmengine - INFO - Epoch(train) [18][5/63] lr: 2.5903e-04 eta: 22:03:35 time: 1.1441 data_time: 0.2379 memory: 16126 loss: 5.1100 loss_prob: 2.9560 loss_thr: 1.1539 loss_db: 1.0000 2022/10/25 19:16:34 - mmengine - INFO - Epoch(train) [18][10/63] lr: 2.5903e-04 eta: 21:58:48 time: 0.9896 data_time: 0.2416 memory: 16126 loss: 5.1135 loss_prob: 2.9519 loss_thr: 1.1617 loss_db: 1.0000 2022/10/25 19:16:37 - mmengine - INFO - Epoch(train) [18][15/63] lr: 2.5903e-04 eta: 21:58:48 time: 0.5823 data_time: 0.0082 memory: 16126 loss: 5.1073 loss_prob: 2.9426 loss_thr: 1.1647 loss_db: 1.0000 2022/10/25 19:16:40 - mmengine - INFO - Epoch(train) [18][20/63] lr: 2.5903e-04 eta: 21:53:11 time: 0.5834 data_time: 0.0043 memory: 16126 loss: 5.1059 loss_prob: 2.9449 loss_thr: 1.1611 loss_db: 1.0000 2022/10/25 19:16:43 - mmengine - INFO - Epoch(train) [18][25/63] lr: 2.5903e-04 eta: 21:53:11 time: 0.5792 data_time: 0.0240 memory: 16126 loss: 5.1092 loss_prob: 2.9438 loss_thr: 1.1655 loss_db: 1.0000 2022/10/25 19:16:48 - mmengine - INFO - Epoch(train) [18][30/63] lr: 2.5903e-04 eta: 21:51:03 time: 0.8839 data_time: 0.0292 memory: 16126 loss: 5.0959 loss_prob: 2.9304 loss_thr: 1.1655 loss_db: 1.0000 2022/10/25 19:16:51 - mmengine - INFO - Epoch(train) [18][35/63] lr: 2.5903e-04 eta: 21:51:03 time: 0.8197 data_time: 0.0121 memory: 16126 loss: 5.1134 loss_prob: 2.9516 loss_thr: 1.1618 loss_db: 1.0000 2022/10/25 19:16:54 - mmengine - INFO - Epoch(train) [18][40/63] lr: 2.5903e-04 eta: 21:44:55 time: 0.5237 data_time: 0.0068 memory: 16126 loss: 5.1210 loss_prob: 2.9621 loss_thr: 1.1590 loss_db: 1.0000 2022/10/25 19:16:56 - mmengine - INFO - Epoch(train) [18][45/63] lr: 2.5903e-04 eta: 21:44:55 time: 0.5098 data_time: 0.0072 memory: 16126 loss: 5.1158 loss_prob: 2.9552 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:17:01 - mmengine - INFO - Epoch(train) [18][50/63] lr: 2.5903e-04 eta: 21:41:29 time: 0.7560 data_time: 0.0209 memory: 16126 loss: 5.1125 loss_prob: 2.9538 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:17:05 - mmengine - INFO - Epoch(train) [18][55/63] lr: 2.5903e-04 eta: 21:41:29 time: 0.9012 data_time: 0.0186 memory: 16126 loss: 5.1111 loss_prob: 2.9535 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 19:17:09 - mmengine - INFO - Epoch(train) [18][60/63] lr: 2.5903e-04 eta: 21:38:20 time: 0.7778 data_time: 0.0135 memory: 16126 loss: 5.1076 loss_prob: 2.9475 loss_thr: 1.1602 loss_db: 1.0000 2022/10/25 19:17:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:17:17 - mmengine - INFO - Epoch(train) [19][5/63] lr: 2.7409e-04 eta: 21:38:20 time: 0.9819 data_time: 0.2205 memory: 16126 loss: 5.1035 loss_prob: 2.9482 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 19:17:21 - mmengine - INFO - Epoch(train) [19][10/63] lr: 2.7409e-04 eta: 21:35:09 time: 1.0866 data_time: 0.2206 memory: 16126 loss: 5.1390 loss_prob: 2.9815 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:17:26 - mmengine - INFO - Epoch(train) [19][15/63] lr: 2.7409e-04 eta: 21:35:09 time: 0.8158 data_time: 0.0050 memory: 16126 loss: 5.1596 loss_prob: 2.9961 loss_thr: 1.1641 loss_db: 0.9995 2022/10/25 19:17:32 - mmengine - INFO - Epoch(train) [19][20/63] lr: 2.7409e-04 eta: 21:34:53 time: 1.0364 data_time: 0.0058 memory: 16126 loss: 5.1560 loss_prob: 2.9897 loss_thr: 1.1668 loss_db: 0.9994 2022/10/25 19:17:36 - mmengine - INFO - Epoch(train) [19][25/63] lr: 2.7409e-04 eta: 21:34:53 time: 0.9947 data_time: 0.0261 memory: 16126 loss: 5.1457 loss_prob: 2.9822 loss_thr: 1.1635 loss_db: 1.0000 2022/10/25 19:17:38 - mmengine - INFO - Epoch(train) [19][30/63] lr: 2.7409e-04 eta: 21:30:34 time: 0.6539 data_time: 0.0326 memory: 16126 loss: 5.1264 loss_prob: 2.9622 loss_thr: 1.1641 loss_db: 1.0000 2022/10/25 19:17:41 - mmengine - INFO - Epoch(train) [19][35/63] lr: 2.7409e-04 eta: 21:30:34 time: 0.5179 data_time: 0.0133 memory: 16126 loss: 5.1115 loss_prob: 2.9451 loss_thr: 1.1664 loss_db: 1.0000 2022/10/25 19:17:44 - mmengine - INFO - Epoch(train) [19][40/63] lr: 2.7409e-04 eta: 21:26:04 time: 0.6314 data_time: 0.0088 memory: 16126 loss: 5.1031 loss_prob: 2.9416 loss_thr: 1.1615 loss_db: 1.0000 2022/10/25 19:17:49 - mmengine - INFO - Epoch(train) [19][45/63] lr: 2.7409e-04 eta: 21:26:04 time: 0.8418 data_time: 0.0094 memory: 16126 loss: 5.0981 loss_prob: 2.9404 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:17:52 - mmengine - INFO - Epoch(train) [19][50/63] lr: 2.7409e-04 eta: 21:22:56 time: 0.7546 data_time: 0.0171 memory: 16126 loss: 5.0796 loss_prob: 2.9227 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:17:56 - mmengine - INFO - Epoch(train) [19][55/63] lr: 2.7409e-04 eta: 21:22:56 time: 0.7102 data_time: 0.0222 memory: 16126 loss: 5.0595 loss_prob: 2.9040 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:17:59 - mmengine - INFO - Epoch(train) [19][60/63] lr: 2.7409e-04 eta: 21:19:05 time: 0.6801 data_time: 0.0116 memory: 16126 loss: 5.0609 loss_prob: 2.9010 loss_thr: 1.1600 loss_db: 0.9999 2022/10/25 19:18:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:18:08 - mmengine - INFO - Epoch(train) [20][5/63] lr: 2.8915e-04 eta: 21:19:05 time: 0.9895 data_time: 0.2257 memory: 16126 loss: 5.0611 loss_prob: 2.9033 loss_thr: 1.1578 loss_db: 1.0000 2022/10/25 19:18:12 - mmengine - INFO - Epoch(train) [20][10/63] lr: 2.8915e-04 eta: 21:16:45 time: 1.1353 data_time: 0.2259 memory: 16126 loss: 5.0738 loss_prob: 2.9174 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 19:18:15 - mmengine - INFO - Epoch(train) [20][15/63] lr: 2.8915e-04 eta: 21:16:45 time: 0.7070 data_time: 0.0046 memory: 16126 loss: 5.0816 loss_prob: 2.9265 loss_thr: 1.1552 loss_db: 1.0000 2022/10/25 19:18:17 - mmengine - INFO - Epoch(train) [20][20/63] lr: 2.8915e-04 eta: 21:11:17 time: 0.5091 data_time: 0.0067 memory: 16126 loss: 5.0957 loss_prob: 2.9345 loss_thr: 1.1612 loss_db: 1.0000 2022/10/25 19:18:20 - mmengine - INFO - Epoch(train) [20][25/63] lr: 2.8915e-04 eta: 21:11:17 time: 0.5643 data_time: 0.0429 memory: 16126 loss: 5.1205 loss_prob: 2.9601 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 19:18:25 - mmengine - INFO - Epoch(train) [20][30/63] lr: 2.8915e-04 eta: 21:08:16 time: 0.7443 data_time: 0.0404 memory: 16126 loss: 5.1218 loss_prob: 2.9664 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 19:18:27 - mmengine - INFO - Epoch(train) [20][35/63] lr: 2.8915e-04 eta: 21:08:16 time: 0.6966 data_time: 0.0042 memory: 16126 loss: 5.1125 loss_prob: 2.9545 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:18:30 - mmengine - INFO - Epoch(train) [20][40/63] lr: 2.8915e-04 eta: 21:02:52 time: 0.5010 data_time: 0.0043 memory: 16126 loss: 5.0977 loss_prob: 2.9410 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:18:32 - mmengine - INFO - Epoch(train) [20][45/63] lr: 2.8915e-04 eta: 21:02:52 time: 0.5090 data_time: 0.0044 memory: 16126 loss: 5.0934 loss_prob: 2.9387 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 19:18:36 - mmengine - INFO - Epoch(train) [20][50/63] lr: 2.8915e-04 eta: 20:58:18 time: 0.5776 data_time: 0.0206 memory: 16126 loss: 5.1237 loss_prob: 2.9686 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 19:18:38 - mmengine - INFO - Epoch(train) [20][55/63] lr: 2.8915e-04 eta: 20:58:18 time: 0.5715 data_time: 0.0205 memory: 16126 loss: 5.1259 loss_prob: 2.9709 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 19:18:43 - mmengine - INFO - Epoch(train) [20][60/63] lr: 2.8915e-04 eta: 20:55:41 time: 0.7666 data_time: 0.0056 memory: 16126 loss: 5.1319 loss_prob: 2.9794 loss_thr: 1.1525 loss_db: 1.0000 2022/10/25 19:18:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:18:45 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/10/25 19:20:47 - mmengine - INFO - Epoch(val) [20][5/32] eta: 20:55:41 time: 23.8591 data_time: 21.8039 memory: 40863 2022/10/25 19:20:50 - mmengine - INFO - Epoch(val) [20][10/32] eta: 0:04:27 time: 12.1534 data_time: 10.9390 memory: 15724 2022/10/25 19:20:52 - mmengine - INFO - Epoch(val) [20][15/32] eta: 0:04:27 time: 0.4179 data_time: 0.0446 memory: 15724 2022/10/25 19:20:54 - mmengine - INFO - Epoch(val) [20][20/32] eta: 0:00:05 time: 0.4255 data_time: 0.0428 memory: 15724 2022/10/25 19:20:56 - mmengine - INFO - Epoch(val) [20][25/32] eta: 0:00:05 time: 0.4417 data_time: 0.0553 memory: 15724 2022/10/25 19:20:58 - mmengine - INFO - Epoch(val) [20][30/32] eta: 0:00:00 time: 0.4118 data_time: 0.0341 memory: 15724 2022/10/25 19:21:06 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:21:06 - mmengine - INFO - Epoch(val) [20][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/10/25 19:21:11 - mmengine - INFO - Epoch(train) [21][5/63] lr: 3.0421e-04 eta: 0:00:00 time: 0.7927 data_time: 0.1727 memory: 35420 loss: 5.1909 loss_prob: 3.0300 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:21:14 - mmengine - INFO - Epoch(train) [21][10/63] lr: 3.0421e-04 eta: 20:49:58 time: 0.7545 data_time: 0.1761 memory: 16131 loss: 5.2049 loss_prob: 3.0434 loss_thr: 1.1615 loss_db: 1.0000 2022/10/25 19:21:16 - mmengine - INFO - Epoch(train) [21][15/63] lr: 3.0421e-04 eta: 20:49:58 time: 0.4914 data_time: 0.0105 memory: 16131 loss: 5.2423 loss_prob: 3.0879 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:21:19 - mmengine - INFO - Epoch(train) [21][20/63] lr: 3.0421e-04 eta: 20:45:01 time: 0.5148 data_time: 0.0082 memory: 16131 loss: 5.2578 loss_prob: 3.0992 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 19:21:22 - mmengine - INFO - Epoch(train) [21][25/63] lr: 3.0421e-04 eta: 20:45:01 time: 0.5471 data_time: 0.0155 memory: 16131 loss: 5.2158 loss_prob: 3.0543 loss_thr: 1.1615 loss_db: 1.0000 2022/10/25 19:21:25 - mmengine - INFO - Epoch(train) [21][30/63] lr: 3.0421e-04 eta: 20:40:46 time: 0.5787 data_time: 0.0283 memory: 16131 loss: 5.1840 loss_prob: 3.0222 loss_thr: 1.1618 loss_db: 1.0000 2022/10/25 19:21:27 - mmengine - INFO - Epoch(train) [21][35/63] lr: 3.0421e-04 eta: 20:40:46 time: 0.5468 data_time: 0.0184 memory: 16131 loss: 5.1769 loss_prob: 3.0172 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:21:31 - mmengine - INFO - Epoch(train) [21][40/63] lr: 3.0421e-04 eta: 20:36:55 time: 0.6158 data_time: 0.0090 memory: 16131 loss: 5.1654 loss_prob: 3.0091 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 19:21:34 - mmengine - INFO - Epoch(train) [21][45/63] lr: 3.0421e-04 eta: 20:36:55 time: 0.6610 data_time: 0.0102 memory: 16131 loss: 5.1638 loss_prob: 3.0019 loss_thr: 1.1618 loss_db: 1.0000 2022/10/25 19:21:37 - mmengine - INFO - Epoch(train) [21][50/63] lr: 3.0421e-04 eta: 20:32:44 time: 0.5744 data_time: 0.0226 memory: 16131 loss: 5.1589 loss_prob: 2.9970 loss_thr: 1.1619 loss_db: 1.0000 2022/10/25 19:21:39 - mmengine - INFO - Epoch(train) [21][55/63] lr: 3.0421e-04 eta: 20:32:44 time: 0.5124 data_time: 0.0237 memory: 16131 loss: 5.1499 loss_prob: 2.9911 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:21:41 - mmengine - INFO - Epoch(train) [21][60/63] lr: 3.0421e-04 eta: 20:27:53 time: 0.4949 data_time: 0.0101 memory: 16131 loss: 5.1630 loss_prob: 3.0024 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:21:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:21:48 - mmengine - INFO - Epoch(train) [22][5/63] lr: 3.1927e-04 eta: 20:27:53 time: 0.7032 data_time: 0.1865 memory: 16131 loss: 5.1407 loss_prob: 2.9797 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:21:52 - mmengine - INFO - Epoch(train) [22][10/63] lr: 3.1927e-04 eta: 20:23:40 time: 0.8589 data_time: 0.1862 memory: 16131 loss: 5.1271 loss_prob: 2.9649 loss_thr: 1.1623 loss_db: 1.0000 2022/10/25 19:21:55 - mmengine - INFO - Epoch(train) [22][15/63] lr: 3.1927e-04 eta: 20:23:40 time: 0.7356 data_time: 0.0059 memory: 16131 loss: 5.1486 loss_prob: 2.9897 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:22:00 - mmengine - INFO - Epoch(train) [22][20/63] lr: 3.1927e-04 eta: 20:21:50 time: 0.8075 data_time: 0.0054 memory: 16131 loss: 5.1699 loss_prob: 3.0162 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 19:22:04 - mmengine - INFO - Epoch(train) [22][25/63] lr: 3.1927e-04 eta: 20:21:50 time: 0.9370 data_time: 0.0207 memory: 16131 loss: 5.1666 loss_prob: 3.0129 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 19:22:07 - mmengine - INFO - Epoch(train) [22][30/63] lr: 3.1927e-04 eta: 20:19:17 time: 0.7257 data_time: 0.0328 memory: 16131 loss: 5.1488 loss_prob: 2.9903 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:22:10 - mmengine - INFO - Epoch(train) [22][35/63] lr: 3.1927e-04 eta: 20:19:17 time: 0.6132 data_time: 0.0167 memory: 16131 loss: 5.1501 loss_prob: 2.9840 loss_thr: 1.1660 loss_db: 1.0000 2022/10/25 19:22:13 - mmengine - INFO - Epoch(train) [22][40/63] lr: 3.1927e-04 eta: 20:15:31 time: 0.5899 data_time: 0.0044 memory: 16131 loss: 5.1527 loss_prob: 2.9887 loss_thr: 1.1640 loss_db: 1.0000 2022/10/25 19:22:16 - mmengine - INFO - Epoch(train) [22][45/63] lr: 3.1927e-04 eta: 20:15:31 time: 0.5426 data_time: 0.0041 memory: 16131 loss: 5.1511 loss_prob: 2.9924 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:22:18 - mmengine - INFO - Epoch(train) [22][50/63] lr: 3.1927e-04 eta: 20:11:13 time: 0.5233 data_time: 0.0157 memory: 16131 loss: 5.1868 loss_prob: 3.0298 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:22:21 - mmengine - INFO - Epoch(train) [22][55/63] lr: 3.1927e-04 eta: 20:11:13 time: 0.4911 data_time: 0.0240 memory: 16131 loss: 5.1973 loss_prob: 3.0323 loss_thr: 1.1650 loss_db: 1.0000 2022/10/25 19:22:23 - mmengine - INFO - Epoch(train) [22][60/63] lr: 3.1927e-04 eta: 20:06:45 time: 0.4975 data_time: 0.0126 memory: 16131 loss: 5.1867 loss_prob: 3.0230 loss_thr: 1.1638 loss_db: 1.0000 2022/10/25 19:22:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:22:29 - mmengine - INFO - Epoch(train) [23][5/63] lr: 3.3433e-04 eta: 20:06:45 time: 0.7110 data_time: 0.2129 memory: 16131 loss: 5.1868 loss_prob: 3.0271 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:22:34 - mmengine - INFO - Epoch(train) [23][10/63] lr: 3.3433e-04 eta: 20:04:12 time: 1.0035 data_time: 0.2136 memory: 16131 loss: 5.1558 loss_prob: 2.9978 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:22:37 - mmengine - INFO - Epoch(train) [23][15/63] lr: 3.3433e-04 eta: 20:04:12 time: 0.8093 data_time: 0.0053 memory: 16131 loss: 5.1627 loss_prob: 3.0055 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:22:43 - mmengine - INFO - Epoch(train) [23][20/63] lr: 3.3433e-04 eta: 20:02:43 time: 0.8247 data_time: 0.0127 memory: 16131 loss: 5.1975 loss_prob: 3.0343 loss_thr: 1.1633 loss_db: 0.9999 2022/10/25 19:22:46 - mmengine - INFO - Epoch(train) [23][25/63] lr: 3.3433e-04 eta: 20:02:43 time: 0.8300 data_time: 0.0346 memory: 16131 loss: 5.2194 loss_prob: 3.0590 loss_thr: 1.1605 loss_db: 0.9999 2022/10/25 19:22:52 - mmengine - INFO - Epoch(train) [23][30/63] lr: 3.3433e-04 eta: 20:02:14 time: 0.9356 data_time: 0.0373 memory: 16131 loss: 5.2074 loss_prob: 3.0508 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:22:56 - mmengine - INFO - Epoch(train) [23][35/63] lr: 3.3433e-04 eta: 20:02:14 time: 1.0060 data_time: 0.0174 memory: 16131 loss: 5.1766 loss_prob: 3.0200 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:22:59 - mmengine - INFO - Epoch(train) [23][40/63] lr: 3.3433e-04 eta: 19:59:54 time: 0.7216 data_time: 0.0090 memory: 16131 loss: 5.1417 loss_prob: 2.9837 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:23:03 - mmengine - INFO - Epoch(train) [23][45/63] lr: 3.3433e-04 eta: 19:59:54 time: 0.7573 data_time: 0.0068 memory: 16131 loss: 5.0971 loss_prob: 2.9360 loss_thr: 1.1611 loss_db: 1.0000 2022/10/25 19:23:06 - mmengine - INFO - Epoch(train) [23][50/63] lr: 3.3433e-04 eta: 19:57:27 time: 0.7039 data_time: 0.0144 memory: 16131 loss: 5.0804 loss_prob: 2.9220 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 19:23:09 - mmengine - INFO - Epoch(train) [23][55/63] lr: 3.3433e-04 eta: 19:57:27 time: 0.5422 data_time: 0.0182 memory: 16131 loss: 5.0961 loss_prob: 2.9356 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:23:12 - mmengine - INFO - Epoch(train) [23][60/63] lr: 3.3433e-04 eta: 19:53:30 time: 0.5271 data_time: 0.0102 memory: 16131 loss: 5.0945 loss_prob: 2.9321 loss_thr: 1.1624 loss_db: 1.0000 2022/10/25 19:23:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:23:20 - mmengine - INFO - Epoch(train) [24][5/63] lr: 3.4939e-04 eta: 19:53:30 time: 0.9658 data_time: 0.2306 memory: 16131 loss: 5.1113 loss_prob: 2.9539 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 19:23:25 - mmengine - INFO - Epoch(train) [24][10/63] lr: 3.4939e-04 eta: 19:53:15 time: 1.2507 data_time: 0.2308 memory: 16131 loss: 5.1249 loss_prob: 2.9653 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:23:31 - mmengine - INFO - Epoch(train) [24][15/63] lr: 3.4939e-04 eta: 19:53:15 time: 1.0994 data_time: 0.0056 memory: 16131 loss: 5.1099 loss_prob: 2.9550 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 19:23:34 - mmengine - INFO - Epoch(train) [24][20/63] lr: 3.4939e-04 eta: 19:52:15 time: 0.8651 data_time: 0.0080 memory: 16131 loss: 5.1019 loss_prob: 2.9483 loss_thr: 1.1536 loss_db: 1.0000 2022/10/25 19:23:38 - mmengine - INFO - Epoch(train) [24][25/63] lr: 3.4939e-04 eta: 19:52:15 time: 0.6603 data_time: 0.0355 memory: 16131 loss: 5.1067 loss_prob: 2.9500 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:23:41 - mmengine - INFO - Epoch(train) [24][30/63] lr: 3.4939e-04 eta: 19:49:42 time: 0.6788 data_time: 0.0410 memory: 16131 loss: 5.0992 loss_prob: 2.9473 loss_thr: 1.1520 loss_db: 1.0000 2022/10/25 19:23:44 - mmengine - INFO - Epoch(train) [24][35/63] lr: 3.4939e-04 eta: 19:49:42 time: 0.6048 data_time: 0.0126 memory: 16131 loss: 5.0905 loss_prob: 2.9376 loss_thr: 1.1528 loss_db: 1.0000 2022/10/25 19:23:49 - mmengine - INFO - Epoch(train) [24][40/63] lr: 3.4939e-04 eta: 19:48:29 time: 0.8367 data_time: 0.0047 memory: 16131 loss: 5.1051 loss_prob: 2.9492 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 19:23:54 - mmengine - INFO - Epoch(train) [24][45/63] lr: 3.4939e-04 eta: 19:48:29 time: 1.0828 data_time: 0.0045 memory: 16131 loss: 5.1385 loss_prob: 2.9782 loss_thr: 1.1603 loss_db: 1.0000 2022/10/25 19:23:57 - mmengine - INFO - Epoch(train) [24][50/63] lr: 3.4939e-04 eta: 19:47:09 time: 0.8181 data_time: 0.0181 memory: 16131 loss: 5.1645 loss_prob: 3.0037 loss_thr: 1.1608 loss_db: 1.0000 2022/10/25 19:24:00 - mmengine - INFO - Epoch(train) [24][55/63] lr: 3.4939e-04 eta: 19:47:09 time: 0.5375 data_time: 0.0207 memory: 16131 loss: 5.1591 loss_prob: 2.9976 loss_thr: 1.1615 loss_db: 1.0000 2022/10/25 19:24:03 - mmengine - INFO - Epoch(train) [24][60/63] lr: 3.4939e-04 eta: 19:43:24 time: 0.5238 data_time: 0.0065 memory: 16131 loss: 5.1323 loss_prob: 2.9706 loss_thr: 1.1617 loss_db: 1.0000 2022/10/25 19:24:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:24:09 - mmengine - INFO - Epoch(train) [25][5/63] lr: 3.6445e-04 eta: 19:43:24 time: 0.7096 data_time: 0.1991 memory: 16131 loss: 5.0939 loss_prob: 2.9309 loss_thr: 1.1630 loss_db: 1.0000 2022/10/25 19:24:12 - mmengine - INFO - Epoch(train) [25][10/63] lr: 3.6445e-04 eta: 19:39:44 time: 0.8199 data_time: 0.2028 memory: 16131 loss: 5.0699 loss_prob: 2.9095 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 19:24:16 - mmengine - INFO - Epoch(train) [25][15/63] lr: 3.6445e-04 eta: 19:39:44 time: 0.7280 data_time: 0.0088 memory: 16131 loss: 5.0886 loss_prob: 2.9201 loss_thr: 1.1685 loss_db: 1.0000 2022/10/25 19:24:22 - mmengine - INFO - Epoch(train) [25][20/63] lr: 3.6445e-04 eta: 19:40:17 time: 1.0420 data_time: 0.0087 memory: 16131 loss: 5.1268 loss_prob: 2.9602 loss_thr: 1.1666 loss_db: 1.0000 2022/10/25 19:24:26 - mmengine - INFO - Epoch(train) [25][25/63] lr: 3.6445e-04 eta: 19:40:17 time: 0.9629 data_time: 0.0121 memory: 16131 loss: 5.1523 loss_prob: 2.9951 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:24:28 - mmengine - INFO - Epoch(train) [25][30/63] lr: 3.6445e-04 eta: 19:37:03 time: 0.5730 data_time: 0.0319 memory: 16131 loss: 5.1435 loss_prob: 2.9891 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:24:32 - mmengine - INFO - Epoch(train) [25][35/63] lr: 3.6445e-04 eta: 19:37:03 time: 0.6130 data_time: 0.0298 memory: 16131 loss: 5.1272 loss_prob: 2.9721 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 19:24:35 - mmengine - INFO - Epoch(train) [25][40/63] lr: 3.6445e-04 eta: 19:34:46 time: 0.6867 data_time: 0.0068 memory: 16131 loss: 5.1161 loss_prob: 2.9626 loss_thr: 1.1536 loss_db: 1.0000 2022/10/25 19:24:38 - mmengine - INFO - Epoch(train) [25][45/63] lr: 3.6445e-04 eta: 19:34:46 time: 0.5987 data_time: 0.0048 memory: 16131 loss: 5.1162 loss_prob: 2.9569 loss_thr: 1.1593 loss_db: 1.0000 2022/10/25 19:24:42 - mmengine - INFO - Epoch(train) [25][50/63] lr: 3.6445e-04 eta: 19:32:10 time: 0.6432 data_time: 0.0138 memory: 16131 loss: 5.1006 loss_prob: 2.9412 loss_thr: 1.1594 loss_db: 1.0000 2022/10/25 19:24:44 - mmengine - INFO - Epoch(train) [25][55/63] lr: 3.6445e-04 eta: 19:32:10 time: 0.6693 data_time: 0.0198 memory: 16131 loss: 5.0774 loss_prob: 2.9248 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 19:24:47 - mmengine - INFO - Epoch(train) [25][60/63] lr: 3.6445e-04 eta: 19:29:02 time: 0.5711 data_time: 0.0117 memory: 16131 loss: 5.0829 loss_prob: 2.9252 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:24:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:24:54 - mmengine - INFO - Epoch(train) [26][5/63] lr: 3.7951e-04 eta: 19:29:02 time: 0.8092 data_time: 0.2022 memory: 16131 loss: 5.0949 loss_prob: 2.9343 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:24:57 - mmengine - INFO - Epoch(train) [26][10/63] lr: 3.7951e-04 eta: 19:26:13 time: 0.8961 data_time: 0.2079 memory: 16131 loss: 5.1107 loss_prob: 2.9494 loss_thr: 1.1613 loss_db: 1.0000 2022/10/25 19:25:02 - mmengine - INFO - Epoch(train) [26][15/63] lr: 3.7951e-04 eta: 19:26:13 time: 0.7932 data_time: 0.0112 memory: 16131 loss: 5.1077 loss_prob: 2.9532 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:25:07 - mmengine - INFO - Epoch(train) [26][20/63] lr: 3.7951e-04 eta: 19:26:17 time: 0.9729 data_time: 0.0072 memory: 16131 loss: 5.0896 loss_prob: 2.9394 loss_thr: 1.1503 loss_db: 1.0000 2022/10/25 19:25:12 - mmengine - INFO - Epoch(train) [26][25/63] lr: 3.7951e-04 eta: 19:26:17 time: 0.9313 data_time: 0.0303 memory: 16131 loss: 5.0754 loss_prob: 2.9182 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:25:17 - mmengine - INFO - Epoch(train) [26][30/63] lr: 3.7951e-04 eta: 19:26:07 time: 0.9460 data_time: 0.0277 memory: 16131 loss: 5.0717 loss_prob: 2.9137 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 19:25:24 - mmengine - INFO - Epoch(train) [26][35/63] lr: 3.7951e-04 eta: 19:26:07 time: 1.2660 data_time: 0.0098 memory: 16131 loss: 5.0681 loss_prob: 2.9132 loss_thr: 1.1550 loss_db: 0.9999 2022/10/25 19:25:28 - mmengine - INFO - Epoch(train) [26][40/63] lr: 3.7951e-04 eta: 19:27:10 time: 1.1027 data_time: 0.0099 memory: 16131 loss: 5.0637 loss_prob: 2.9061 loss_thr: 1.1577 loss_db: 0.9999 2022/10/25 19:25:31 - mmengine - INFO - Epoch(train) [26][45/63] lr: 3.7951e-04 eta: 19:27:10 time: 0.7114 data_time: 0.0065 memory: 16131 loss: 5.0916 loss_prob: 2.9332 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 19:25:37 - mmengine - INFO - Epoch(train) [26][50/63] lr: 3.7951e-04 eta: 19:26:41 time: 0.9029 data_time: 0.0213 memory: 16131 loss: 5.1422 loss_prob: 2.9782 loss_thr: 1.1645 loss_db: 0.9996 2022/10/25 19:25:40 - mmengine - INFO - Epoch(train) [26][55/63] lr: 3.7951e-04 eta: 19:26:41 time: 0.8552 data_time: 0.0203 memory: 16131 loss: 5.1357 loss_prob: 2.9719 loss_thr: 1.1641 loss_db: 0.9996 2022/10/25 19:25:43 - mmengine - INFO - Epoch(train) [26][60/63] lr: 3.7951e-04 eta: 19:23:53 time: 0.5977 data_time: 0.0096 memory: 16131 loss: 5.0946 loss_prob: 2.9378 loss_thr: 1.1569 loss_db: 1.0000 2022/10/25 19:25:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:25:50 - mmengine - INFO - Epoch(train) [27][5/63] lr: 3.9457e-04 eta: 19:23:53 time: 0.8453 data_time: 0.2058 memory: 16131 loss: 5.0677 loss_prob: 2.9056 loss_thr: 1.1621 loss_db: 1.0000 2022/10/25 19:25:54 - mmengine - INFO - Epoch(train) [27][10/63] lr: 3.9457e-04 eta: 19:22:04 time: 1.0104 data_time: 0.2076 memory: 16131 loss: 5.0549 loss_prob: 2.8953 loss_thr: 1.1596 loss_db: 0.9999 2022/10/25 19:25:57 - mmengine - INFO - Epoch(train) [27][15/63] lr: 3.9457e-04 eta: 19:22:04 time: 0.7070 data_time: 0.0103 memory: 16131 loss: 5.0774 loss_prob: 2.9153 loss_thr: 1.1622 loss_db: 0.9999 2022/10/25 19:26:02 - mmengine - INFO - Epoch(train) [27][20/63] lr: 3.9457e-04 eta: 19:20:27 time: 0.7464 data_time: 0.0100 memory: 16131 loss: 5.1132 loss_prob: 2.9546 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 19:26:04 - mmengine - INFO - Epoch(train) [27][25/63] lr: 3.9457e-04 eta: 19:20:27 time: 0.7362 data_time: 0.0088 memory: 16131 loss: 5.1232 loss_prob: 2.9698 loss_thr: 1.1536 loss_db: 0.9998 2022/10/25 19:26:08 - mmengine - INFO - Epoch(train) [27][30/63] lr: 3.9457e-04 eta: 19:17:46 time: 0.5996 data_time: 0.0332 memory: 16131 loss: 5.1046 loss_prob: 2.9483 loss_thr: 1.1565 loss_db: 0.9999 2022/10/25 19:26:12 - mmengine - INFO - Epoch(train) [27][35/63] lr: 3.9457e-04 eta: 19:17:46 time: 0.7336 data_time: 0.0342 memory: 16131 loss: 5.0917 loss_prob: 2.9335 loss_thr: 1.1582 loss_db: 1.0000 2022/10/25 19:26:15 - mmengine - INFO - Epoch(train) [27][40/63] lr: 3.9457e-04 eta: 19:16:16 time: 0.7569 data_time: 0.0076 memory: 16131 loss: 5.0935 loss_prob: 2.9336 loss_thr: 1.1599 loss_db: 1.0000 2022/10/25 19:26:18 - mmengine - INFO - Epoch(train) [27][45/63] lr: 3.9457e-04 eta: 19:16:16 time: 0.6041 data_time: 0.0048 memory: 16131 loss: 5.0834 loss_prob: 2.9197 loss_thr: 1.1637 loss_db: 1.0000 2022/10/25 19:26:21 - mmengine - INFO - Epoch(train) [27][50/63] lr: 3.9457e-04 eta: 19:13:46 time: 0.6182 data_time: 0.0182 memory: 16131 loss: 5.0581 loss_prob: 2.9009 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:26:25 - mmengine - INFO - Epoch(train) [27][55/63] lr: 3.9457e-04 eta: 19:13:46 time: 0.7543 data_time: 0.0196 memory: 16131 loss: 5.0496 loss_prob: 2.8990 loss_thr: 1.1507 loss_db: 1.0000 2022/10/25 19:26:30 - mmengine - INFO - Epoch(train) [27][60/63] lr: 3.9457e-04 eta: 19:13:04 time: 0.8601 data_time: 0.0089 memory: 16131 loss: 5.0770 loss_prob: 2.9201 loss_thr: 1.1571 loss_db: 0.9998 2022/10/25 19:26:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:26:38 - mmengine - INFO - Epoch(train) [28][5/63] lr: 4.0963e-04 eta: 19:13:04 time: 1.0236 data_time: 0.1849 memory: 16131 loss: 5.0912 loss_prob: 2.9310 loss_thr: 1.1602 loss_db: 1.0000 2022/10/25 19:26:41 - mmengine - INFO - Epoch(train) [28][10/63] lr: 4.0963e-04 eta: 19:10:30 time: 0.8904 data_time: 0.1927 memory: 16131 loss: 5.0863 loss_prob: 2.9267 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:26:46 - mmengine - INFO - Epoch(train) [28][15/63] lr: 4.0963e-04 eta: 19:10:30 time: 0.7736 data_time: 0.0127 memory: 16131 loss: 5.0784 loss_prob: 2.9187 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:26:52 - mmengine - INFO - Epoch(train) [28][20/63] lr: 4.0963e-04 eta: 19:11:18 time: 1.0674 data_time: 0.0067 memory: 16131 loss: 5.0697 loss_prob: 2.9104 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 19:26:55 - mmengine - INFO - Epoch(train) [28][25/63] lr: 4.0963e-04 eta: 19:11:18 time: 0.9579 data_time: 0.0354 memory: 16131 loss: 5.0711 loss_prob: 2.9110 loss_thr: 1.1602 loss_db: 0.9999 2022/10/25 19:26:58 - mmengine - INFO - Epoch(train) [28][30/63] lr: 4.0963e-04 eta: 19:09:09 time: 0.6534 data_time: 0.0504 memory: 16131 loss: 5.0713 loss_prob: 2.9121 loss_thr: 1.1593 loss_db: 0.9999 2022/10/25 19:27:03 - mmengine - INFO - Epoch(train) [28][35/63] lr: 4.0963e-04 eta: 19:09:09 time: 0.7399 data_time: 0.0281 memory: 16131 loss: 5.0543 loss_prob: 2.8990 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:27:07 - mmengine - INFO - Epoch(train) [28][40/63] lr: 4.0963e-04 eta: 19:08:35 time: 0.8767 data_time: 0.0114 memory: 16131 loss: 5.0588 loss_prob: 2.9021 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:27:09 - mmengine - INFO - Epoch(train) [28][45/63] lr: 4.0963e-04 eta: 19:08:35 time: 0.6440 data_time: 0.0063 memory: 16131 loss: 5.0794 loss_prob: 2.9246 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 19:27:12 - mmengine - INFO - Epoch(train) [28][50/63] lr: 4.0963e-04 eta: 19:05:44 time: 0.5499 data_time: 0.0173 memory: 16131 loss: 5.1052 loss_prob: 2.9520 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 19:27:15 - mmengine - INFO - Epoch(train) [28][55/63] lr: 4.0963e-04 eta: 19:05:44 time: 0.6059 data_time: 0.0218 memory: 16131 loss: 5.1212 loss_prob: 2.9639 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:27:19 - mmengine - INFO - Epoch(train) [28][60/63] lr: 4.0963e-04 eta: 19:03:42 time: 0.6624 data_time: 0.0143 memory: 16131 loss: 5.1020 loss_prob: 2.9431 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:27:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:27:26 - mmengine - INFO - Epoch(train) [29][5/63] lr: 4.2469e-04 eta: 19:03:42 time: 0.9057 data_time: 0.1993 memory: 16131 loss: 5.1356 loss_prob: 2.9696 loss_thr: 1.1662 loss_db: 0.9999 2022/10/25 19:27:30 - mmengine - INFO - Epoch(train) [29][10/63] lr: 4.2469e-04 eta: 19:01:24 time: 0.9054 data_time: 0.2037 memory: 16131 loss: 5.1964 loss_prob: 3.0253 loss_thr: 1.1713 loss_db: 0.9998 2022/10/25 19:27:36 - mmengine - INFO - Epoch(train) [29][15/63] lr: 4.2469e-04 eta: 19:01:24 time: 0.9753 data_time: 0.0089 memory: 16131 loss: 5.1922 loss_prob: 3.0254 loss_thr: 1.1669 loss_db: 0.9999 2022/10/25 19:27:43 - mmengine - INFO - Epoch(train) [29][20/63] lr: 4.2469e-04 eta: 19:03:27 time: 1.2456 data_time: 0.0068 memory: 16131 loss: 5.2108 loss_prob: 3.0413 loss_thr: 1.1696 loss_db: 0.9999 2022/10/25 19:27:46 - mmengine - INFO - Epoch(train) [29][25/63] lr: 4.2469e-04 eta: 19:03:27 time: 1.0571 data_time: 0.0268 memory: 16131 loss: 5.2053 loss_prob: 3.0314 loss_thr: 1.1742 loss_db: 0.9996 2022/10/25 19:27:52 - mmengine - INFO - Epoch(train) [29][30/63] lr: 4.2469e-04 eta: 19:03:24 time: 0.9466 data_time: 0.0331 memory: 16131 loss: 5.1936 loss_prob: 3.0181 loss_thr: 1.1761 loss_db: 0.9994 2022/10/25 19:27:55 - mmengine - INFO - Epoch(train) [29][35/63] lr: 4.2469e-04 eta: 19:03:24 time: 0.8587 data_time: 0.0185 memory: 16131 loss: 5.2277 loss_prob: 3.0371 loss_thr: 1.1915 loss_db: 0.9991 2022/10/25 19:27:58 - mmengine - INFO - Epoch(train) [29][40/63] lr: 4.2469e-04 eta: 19:00:36 time: 0.5402 data_time: 0.0100 memory: 16131 loss: 5.2694 loss_prob: 3.0695 loss_thr: 1.2013 loss_db: 0.9986 2022/10/25 19:28:01 - mmengine - INFO - Epoch(train) [29][45/63] lr: 4.2469e-04 eta: 19:00:36 time: 0.6086 data_time: 0.0048 memory: 16131 loss: 5.2669 loss_prob: 3.0853 loss_thr: 1.1824 loss_db: 0.9992 2022/10/25 19:28:04 - mmengine - INFO - Epoch(train) [29][50/63] lr: 4.2469e-04 eta: 18:58:34 time: 0.6496 data_time: 0.0182 memory: 16131 loss: 5.2681 loss_prob: 3.1019 loss_thr: 1.1663 loss_db: 0.9999 2022/10/25 19:28:08 - mmengine - INFO - Epoch(train) [29][55/63] lr: 4.2469e-04 eta: 18:58:34 time: 0.6677 data_time: 0.0183 memory: 16131 loss: 5.2587 loss_prob: 3.0960 loss_thr: 1.1628 loss_db: 0.9999 2022/10/25 19:28:12 - mmengine - INFO - Epoch(train) [29][60/63] lr: 4.2469e-04 eta: 18:57:13 time: 0.7486 data_time: 0.0066 memory: 16131 loss: 5.2418 loss_prob: 3.0734 loss_thr: 1.1686 loss_db: 0.9998 2022/10/25 19:28:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:28:18 - mmengine - INFO - Epoch(train) [30][5/63] lr: 4.3975e-04 eta: 18:57:13 time: 0.7955 data_time: 0.1750 memory: 16131 loss: 5.3017 loss_prob: 3.1270 loss_thr: 1.1754 loss_db: 0.9993 2022/10/25 19:28:21 - mmengine - INFO - Epoch(train) [30][10/63] lr: 4.3975e-04 eta: 18:54:06 time: 0.7678 data_time: 0.1755 memory: 16131 loss: 5.3064 loss_prob: 3.1270 loss_thr: 1.1802 loss_db: 0.9991 2022/10/25 19:28:24 - mmengine - INFO - Epoch(train) [30][15/63] lr: 4.3975e-04 eta: 18:54:06 time: 0.5811 data_time: 0.0193 memory: 16131 loss: 5.2712 loss_prob: 3.0931 loss_thr: 1.1786 loss_db: 0.9995 2022/10/25 19:28:27 - mmengine - INFO - Epoch(train) [30][20/63] lr: 4.3975e-04 eta: 18:51:47 time: 0.5963 data_time: 0.0196 memory: 16131 loss: 5.2559 loss_prob: 3.0813 loss_thr: 1.1748 loss_db: 0.9998 2022/10/25 19:28:30 - mmengine - INFO - Epoch(train) [30][25/63] lr: 4.3975e-04 eta: 18:51:47 time: 0.5868 data_time: 0.0299 memory: 16131 loss: 5.2231 loss_prob: 3.0544 loss_thr: 1.1688 loss_db: 0.9999 2022/10/25 19:28:34 - mmengine - INFO - Epoch(train) [30][30/63] lr: 4.3975e-04 eta: 18:50:08 time: 0.6959 data_time: 0.0295 memory: 16131 loss: 5.1872 loss_prob: 3.0277 loss_thr: 1.1596 loss_db: 0.9998 2022/10/25 19:28:37 - mmengine - INFO - Epoch(train) [30][35/63] lr: 4.3975e-04 eta: 18:50:08 time: 0.6815 data_time: 0.0067 memory: 16131 loss: 5.1760 loss_prob: 3.0160 loss_thr: 1.1601 loss_db: 0.9998 2022/10/25 19:28:40 - mmengine - INFO - Epoch(train) [30][40/63] lr: 4.3975e-04 eta: 18:48:13 time: 0.6504 data_time: 0.0138 memory: 16131 loss: 5.1667 loss_prob: 3.0068 loss_thr: 1.1599 loss_db: 1.0000 2022/10/25 19:28:43 - mmengine - INFO - Epoch(train) [30][45/63] lr: 4.3975e-04 eta: 18:48:13 time: 0.6090 data_time: 0.0119 memory: 16131 loss: 5.1990 loss_prob: 3.0369 loss_thr: 1.1623 loss_db: 0.9998 2022/10/25 19:28:47 - mmengine - INFO - Epoch(train) [30][50/63] lr: 4.3975e-04 eta: 18:46:16 time: 0.6437 data_time: 0.0221 memory: 16131 loss: 5.2175 loss_prob: 3.0476 loss_thr: 1.1704 loss_db: 0.9995 2022/10/25 19:28:50 - mmengine - INFO - Epoch(train) [30][55/63] lr: 4.3975e-04 eta: 18:46:16 time: 0.7421 data_time: 0.0222 memory: 16131 loss: 5.1884 loss_prob: 3.0231 loss_thr: 1.1656 loss_db: 0.9997 2022/10/25 19:28:54 - mmengine - INFO - Epoch(train) [30][60/63] lr: 4.3975e-04 eta: 18:45:13 time: 0.7801 data_time: 0.0048 memory: 16131 loss: 5.1936 loss_prob: 3.0325 loss_thr: 1.1614 loss_db: 0.9997 2022/10/25 19:28:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:29:03 - mmengine - INFO - Epoch(train) [31][5/63] lr: 4.5481e-04 eta: 18:45:13 time: 1.1292 data_time: 0.2305 memory: 16131 loss: 5.1525 loss_prob: 2.9805 loss_thr: 1.1725 loss_db: 0.9995 2022/10/25 19:29:06 - mmengine - INFO - Epoch(train) [31][10/63] lr: 4.5481e-04 eta: 18:43:31 time: 0.9583 data_time: 0.2315 memory: 16131 loss: 5.1577 loss_prob: 2.9847 loss_thr: 1.1736 loss_db: 0.9995 2022/10/25 19:29:08 - mmengine - INFO - Epoch(train) [31][15/63] lr: 4.5481e-04 eta: 18:43:31 time: 0.5429 data_time: 0.0068 memory: 16131 loss: 5.1649 loss_prob: 3.0071 loss_thr: 1.1578 loss_db: 1.0000 2022/10/25 19:29:12 - mmengine - INFO - Epoch(train) [31][20/63] lr: 4.5481e-04 eta: 18:41:38 time: 0.6446 data_time: 0.0048 memory: 16131 loss: 5.1772 loss_prob: 3.0234 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 19:29:15 - mmengine - INFO - Epoch(train) [31][25/63] lr: 4.5481e-04 eta: 18:41:38 time: 0.6596 data_time: 0.0188 memory: 16131 loss: 5.1735 loss_prob: 3.0162 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:29:18 - mmengine - INFO - Epoch(train) [31][30/63] lr: 4.5481e-04 eta: 18:39:25 time: 0.5913 data_time: 0.0314 memory: 16131 loss: 5.1833 loss_prob: 3.0198 loss_thr: 1.1637 loss_db: 0.9999 2022/10/25 19:29:23 - mmengine - INFO - Epoch(train) [31][35/63] lr: 4.5481e-04 eta: 18:39:25 time: 0.7623 data_time: 0.0198 memory: 16131 loss: 5.2139 loss_prob: 3.0503 loss_thr: 1.1637 loss_db: 0.9999 2022/10/25 19:29:26 - mmengine - INFO - Epoch(train) [31][40/63] lr: 4.5481e-04 eta: 18:38:10 time: 0.7375 data_time: 0.0076 memory: 16131 loss: 5.2710 loss_prob: 3.1049 loss_thr: 1.1665 loss_db: 0.9996 2022/10/25 19:29:31 - mmengine - INFO - Epoch(train) [31][45/63] lr: 4.5481e-04 eta: 18:38:10 time: 0.8397 data_time: 0.0052 memory: 16131 loss: 5.2575 loss_prob: 3.0925 loss_thr: 1.1654 loss_db: 0.9996 2022/10/25 19:29:35 - mmengine - INFO - Epoch(train) [31][50/63] lr: 4.5481e-04 eta: 18:38:15 time: 0.9493 data_time: 0.0137 memory: 16131 loss: 5.2044 loss_prob: 3.0433 loss_thr: 1.1611 loss_db: 0.9999 2022/10/25 19:29:38 - mmengine - INFO - Epoch(train) [31][55/63] lr: 4.5481e-04 eta: 18:38:15 time: 0.6589 data_time: 0.0182 memory: 16131 loss: 5.2019 loss_prob: 3.0330 loss_thr: 1.1695 loss_db: 0.9994 2022/10/25 19:29:40 - mmengine - INFO - Epoch(train) [31][60/63] lr: 4.5481e-04 eta: 18:35:33 time: 0.5063 data_time: 0.0120 memory: 16131 loss: 5.1953 loss_prob: 3.0279 loss_thr: 1.1679 loss_db: 0.9995 2022/10/25 19:29:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:29:49 - mmengine - INFO - Epoch(train) [32][5/63] lr: 4.6987e-04 eta: 18:35:33 time: 0.9743 data_time: 0.1976 memory: 16131 loss: 5.1974 loss_prob: 3.0362 loss_thr: 1.1615 loss_db: 0.9997 2022/10/25 19:29:52 - mmengine - INFO - Epoch(train) [32][10/63] lr: 4.6987e-04 eta: 18:32:43 time: 0.7595 data_time: 0.1979 memory: 16131 loss: 5.1735 loss_prob: 3.0083 loss_thr: 1.1654 loss_db: 0.9997 2022/10/25 19:29:55 - mmengine - INFO - Epoch(train) [32][15/63] lr: 4.6987e-04 eta: 18:32:43 time: 0.5792 data_time: 0.0060 memory: 16131 loss: 5.1432 loss_prob: 2.9809 loss_thr: 1.1624 loss_db: 1.0000 2022/10/25 19:29:58 - mmengine - INFO - Epoch(train) [32][20/63] lr: 4.6987e-04 eta: 18:30:37 time: 0.5926 data_time: 0.0089 memory: 16131 loss: 5.1324 loss_prob: 2.9755 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:30:01 - mmengine - INFO - Epoch(train) [32][25/63] lr: 4.6987e-04 eta: 18:30:37 time: 0.6005 data_time: 0.0342 memory: 16131 loss: 5.1654 loss_prob: 3.0053 loss_thr: 1.1601 loss_db: 1.0000 2022/10/25 19:30:04 - mmengine - INFO - Epoch(train) [32][30/63] lr: 4.6987e-04 eta: 18:28:39 time: 0.6127 data_time: 0.0344 memory: 16131 loss: 5.2211 loss_prob: 3.0597 loss_thr: 1.1615 loss_db: 1.0000 2022/10/25 19:30:07 - mmengine - INFO - Epoch(train) [32][35/63] lr: 4.6987e-04 eta: 18:28:39 time: 0.6052 data_time: 0.0089 memory: 16131 loss: 5.2333 loss_prob: 3.0773 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 19:30:12 - mmengine - INFO - Epoch(train) [32][40/63] lr: 4.6987e-04 eta: 18:27:51 time: 0.7980 data_time: 0.0063 memory: 16131 loss: 5.1901 loss_prob: 3.0341 loss_thr: 1.1561 loss_db: 0.9999 2022/10/25 19:30:16 - mmengine - INFO - Epoch(train) [32][45/63] lr: 4.6987e-04 eta: 18:27:51 time: 0.8990 data_time: 0.0090 memory: 16131 loss: 5.1226 loss_prob: 2.9704 loss_thr: 1.1523 loss_db: 0.9999 2022/10/25 19:30:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:30:18 - mmengine - INFO - Epoch(train) [32][50/63] lr: 4.6987e-04 eta: 18:26:18 time: 0.6741 data_time: 0.0306 memory: 16131 loss: 5.1277 loss_prob: 2.9757 loss_thr: 1.1521 loss_db: 1.0000 2022/10/25 19:30:21 - mmengine - INFO - Epoch(train) [32][55/63] lr: 4.6987e-04 eta: 18:26:18 time: 0.5465 data_time: 0.0288 memory: 16131 loss: 5.1644 loss_prob: 3.0074 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 19:30:26 - mmengine - INFO - Epoch(train) [32][60/63] lr: 4.6987e-04 eta: 18:25:00 time: 0.7130 data_time: 0.0063 memory: 16131 loss: 5.1625 loss_prob: 3.0027 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:30:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:30:33 - mmengine - INFO - Epoch(train) [33][5/63] lr: 4.8493e-04 eta: 18:25:00 time: 1.0003 data_time: 0.2019 memory: 16131 loss: 5.1497 loss_prob: 2.9904 loss_thr: 1.1593 loss_db: 1.0000 2022/10/25 19:30:35 - mmengine - INFO - Epoch(train) [33][10/63] lr: 4.8493e-04 eta: 18:22:38 time: 0.8128 data_time: 0.2091 memory: 16131 loss: 5.1186 loss_prob: 2.9609 loss_thr: 1.1578 loss_db: 0.9999 2022/10/25 19:30:39 - mmengine - INFO - Epoch(train) [33][15/63] lr: 4.8493e-04 eta: 18:22:38 time: 0.5996 data_time: 0.0123 memory: 16131 loss: 5.1411 loss_prob: 2.9806 loss_thr: 1.1606 loss_db: 0.9999 2022/10/25 19:30:43 - mmengine - INFO - Epoch(train) [33][20/63] lr: 4.8493e-04 eta: 18:21:28 time: 0.7294 data_time: 0.0054 memory: 16131 loss: 5.1747 loss_prob: 3.0152 loss_thr: 1.1595 loss_db: 1.0000 2022/10/25 19:30:47 - mmengine - INFO - Epoch(train) [33][25/63] lr: 4.8493e-04 eta: 18:21:28 time: 0.7948 data_time: 0.0222 memory: 16131 loss: 5.1968 loss_prob: 3.0429 loss_thr: 1.1539 loss_db: 1.0000 2022/10/25 19:30:51 - mmengine - INFO - Epoch(train) [33][30/63] lr: 4.8493e-04 eta: 18:20:50 time: 0.8183 data_time: 0.0330 memory: 16131 loss: 5.1757 loss_prob: 3.0223 loss_thr: 1.1534 loss_db: 1.0000 2022/10/25 19:30:55 - mmengine - INFO - Epoch(train) [33][35/63] lr: 4.8493e-04 eta: 18:20:50 time: 0.7859 data_time: 0.0208 memory: 16131 loss: 5.1452 loss_prob: 2.9848 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 19:30:57 - mmengine - INFO - Epoch(train) [33][40/63] lr: 4.8493e-04 eta: 18:19:09 time: 0.6406 data_time: 0.0103 memory: 16131 loss: 5.1424 loss_prob: 2.9767 loss_thr: 1.1658 loss_db: 0.9999 2022/10/25 19:31:00 - mmengine - INFO - Epoch(train) [33][45/63] lr: 4.8493e-04 eta: 18:19:09 time: 0.5718 data_time: 0.0085 memory: 16131 loss: 5.1423 loss_prob: 2.9794 loss_thr: 1.1629 loss_db: 0.9999 2022/10/25 19:31:04 - mmengine - INFO - Epoch(train) [33][50/63] lr: 4.8493e-04 eta: 18:17:33 time: 0.6515 data_time: 0.0186 memory: 16131 loss: 5.1218 loss_prob: 2.9652 loss_thr: 1.1567 loss_db: 0.9999 2022/10/25 19:31:06 - mmengine - INFO - Epoch(train) [33][55/63] lr: 4.8493e-04 eta: 18:17:33 time: 0.6146 data_time: 0.0251 memory: 16131 loss: 5.0913 loss_prob: 2.9324 loss_thr: 1.1591 loss_db: 0.9999 2022/10/25 19:31:09 - mmengine - INFO - Epoch(train) [33][60/63] lr: 4.8493e-04 eta: 18:15:22 time: 0.5510 data_time: 0.0171 memory: 16131 loss: 5.0807 loss_prob: 2.9198 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:31:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:31:16 - mmengine - INFO - Epoch(train) [34][5/63] lr: 4.9999e-04 eta: 18:15:22 time: 0.7362 data_time: 0.2360 memory: 16131 loss: 5.0801 loss_prob: 2.9253 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 19:31:18 - mmengine - INFO - Epoch(train) [34][10/63] lr: 4.9999e-04 eta: 18:13:03 time: 0.8016 data_time: 0.2389 memory: 16131 loss: 5.0979 loss_prob: 2.9413 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:31:22 - mmengine - INFO - Epoch(train) [34][15/63] lr: 4.9999e-04 eta: 18:13:03 time: 0.6971 data_time: 0.0079 memory: 16131 loss: 5.1037 loss_prob: 2.9492 loss_thr: 1.1546 loss_db: 1.0000 2022/10/25 19:31:25 - mmengine - INFO - Epoch(train) [34][20/63] lr: 4.9999e-04 eta: 18:11:35 time: 0.6659 data_time: 0.0049 memory: 16131 loss: 5.1566 loss_prob: 2.9852 loss_thr: 1.1716 loss_db: 0.9998 2022/10/25 19:31:29 - mmengine - INFO - Epoch(train) [34][25/63] lr: 4.9999e-04 eta: 18:11:35 time: 0.6245 data_time: 0.0346 memory: 16131 loss: 5.1805 loss_prob: 3.0064 loss_thr: 1.1743 loss_db: 0.9998 2022/10/25 19:31:33 - mmengine - INFO - Epoch(train) [34][30/63] lr: 4.9999e-04 eta: 18:10:35 time: 0.7440 data_time: 0.0394 memory: 16131 loss: 5.1395 loss_prob: 2.9776 loss_thr: 1.1619 loss_db: 1.0000 2022/10/25 19:31:36 - mmengine - INFO - Epoch(train) [34][35/63] lr: 4.9999e-04 eta: 18:10:35 time: 0.6904 data_time: 0.0094 memory: 16131 loss: 5.1373 loss_prob: 2.9752 loss_thr: 1.1622 loss_db: 0.9999 2022/10/25 19:31:42 - mmengine - INFO - Epoch(train) [34][40/63] lr: 4.9999e-04 eta: 18:10:44 time: 0.9419 data_time: 0.0065 memory: 16131 loss: 5.1338 loss_prob: 2.9767 loss_thr: 1.1572 loss_db: 0.9999 2022/10/25 19:31:45 - mmengine - INFO - Epoch(train) [34][45/63] lr: 4.9999e-04 eta: 18:10:44 time: 0.9332 data_time: 0.0071 memory: 16131 loss: 5.1146 loss_prob: 2.9591 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 19:31:48 - mmengine - INFO - Epoch(train) [34][50/63] lr: 4.9999e-04 eta: 18:08:41 time: 0.5597 data_time: 0.0189 memory: 16131 loss: 5.1002 loss_prob: 2.9388 loss_thr: 1.1614 loss_db: 1.0000 2022/10/25 19:31:50 - mmengine - INFO - Epoch(train) [34][55/63] lr: 4.9999e-04 eta: 18:08:41 time: 0.5396 data_time: 0.0245 memory: 16131 loss: 5.0881 loss_prob: 2.9331 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 19:31:56 - mmengine - INFO - Epoch(train) [34][60/63] lr: 4.9999e-04 eta: 18:08:20 time: 0.8555 data_time: 0.0108 memory: 16131 loss: 5.0887 loss_prob: 2.9350 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 19:31:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:32:05 - mmengine - INFO - Epoch(train) [35][5/63] lr: 5.1505e-04 eta: 18:08:20 time: 1.1702 data_time: 0.1896 memory: 16131 loss: 5.0819 loss_prob: 2.9260 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:32:08 - mmengine - INFO - Epoch(train) [35][10/63] lr: 5.1505e-04 eta: 18:06:41 time: 0.8969 data_time: 0.1900 memory: 16131 loss: 5.0945 loss_prob: 2.9360 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:32:10 - mmengine - INFO - Epoch(train) [35][15/63] lr: 5.1505e-04 eta: 18:06:41 time: 0.5139 data_time: 0.0048 memory: 16131 loss: 5.0958 loss_prob: 2.9401 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 19:32:15 - mmengine - INFO - Epoch(train) [35][20/63] lr: 5.1505e-04 eta: 18:05:28 time: 0.6989 data_time: 0.0045 memory: 16131 loss: 5.0814 loss_prob: 2.9281 loss_thr: 1.1533 loss_db: 1.0000 2022/10/25 19:32:18 - mmengine - INFO - Epoch(train) [35][25/63] lr: 5.1505e-04 eta: 18:05:28 time: 0.7168 data_time: 0.0197 memory: 16131 loss: 5.0861 loss_prob: 2.9271 loss_thr: 1.1590 loss_db: 1.0000 2022/10/25 19:32:23 - mmengine - INFO - Epoch(train) [35][30/63] lr: 5.1505e-04 eta: 18:05:00 time: 0.8322 data_time: 0.0503 memory: 16131 loss: 5.1007 loss_prob: 2.9399 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:32:25 - mmengine - INFO - Epoch(train) [35][35/63] lr: 5.1505e-04 eta: 18:05:00 time: 0.7940 data_time: 0.0357 memory: 16131 loss: 5.1009 loss_prob: 2.9443 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:32:29 - mmengine - INFO - Epoch(train) [35][40/63] lr: 5.1505e-04 eta: 18:03:08 time: 0.5786 data_time: 0.0054 memory: 16131 loss: 5.0927 loss_prob: 2.9365 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 19:32:31 - mmengine - INFO - Epoch(train) [35][45/63] lr: 5.1505e-04 eta: 18:03:08 time: 0.5815 data_time: 0.0070 memory: 16131 loss: 5.0947 loss_prob: 2.9379 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:32:34 - mmengine - INFO - Epoch(train) [35][50/63] lr: 5.1505e-04 eta: 18:01:08 time: 0.5541 data_time: 0.0303 memory: 16131 loss: 5.0925 loss_prob: 2.9357 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:32:40 - mmengine - INFO - Epoch(train) [35][55/63] lr: 5.1505e-04 eta: 18:01:08 time: 0.8657 data_time: 0.0284 memory: 16131 loss: 5.0825 loss_prob: 2.9250 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:32:43 - mmengine - INFO - Epoch(train) [35][60/63] lr: 5.1505e-04 eta: 18:01:02 time: 0.8926 data_time: 0.0046 memory: 16131 loss: 5.0802 loss_prob: 2.9211 loss_thr: 1.1591 loss_db: 1.0000 2022/10/25 19:32:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:32:51 - mmengine - INFO - Epoch(train) [36][5/63] lr: 5.3011e-04 eta: 18:01:02 time: 0.9025 data_time: 0.2229 memory: 16131 loss: 5.0736 loss_prob: 2.9166 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:32:54 - mmengine - INFO - Epoch(train) [36][10/63] lr: 5.3011e-04 eta: 17:59:24 time: 0.8881 data_time: 0.2230 memory: 16131 loss: 5.0796 loss_prob: 2.9217 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:32:57 - mmengine - INFO - Epoch(train) [36][15/63] lr: 5.3011e-04 eta: 17:59:24 time: 0.5904 data_time: 0.0047 memory: 16131 loss: 5.1023 loss_prob: 2.9378 loss_thr: 1.1645 loss_db: 1.0000 2022/10/25 19:33:00 - mmengine - INFO - Epoch(train) [36][20/63] lr: 5.3011e-04 eta: 17:57:22 time: 0.5397 data_time: 0.0047 memory: 16131 loss: 5.1176 loss_prob: 2.9521 loss_thr: 1.1656 loss_db: 1.0000 2022/10/25 19:33:03 - mmengine - INFO - Epoch(train) [36][25/63] lr: 5.3011e-04 eta: 17:57:22 time: 0.5499 data_time: 0.0213 memory: 16131 loss: 5.1116 loss_prob: 2.9526 loss_thr: 1.1590 loss_db: 1.0000 2022/10/25 19:33:07 - mmengine - INFO - Epoch(train) [36][30/63] lr: 5.3011e-04 eta: 17:56:37 time: 0.7691 data_time: 0.0362 memory: 16131 loss: 5.1003 loss_prob: 2.9415 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:33:10 - mmengine - INFO - Epoch(train) [36][35/63] lr: 5.3011e-04 eta: 17:56:37 time: 0.7288 data_time: 0.0195 memory: 16131 loss: 5.0893 loss_prob: 2.9303 loss_thr: 1.1591 loss_db: 1.0000 2022/10/25 19:33:13 - mmengine - INFO - Epoch(train) [36][40/63] lr: 5.3011e-04 eta: 17:54:33 time: 0.5273 data_time: 0.0045 memory: 16131 loss: 5.0941 loss_prob: 2.9398 loss_thr: 1.1543 loss_db: 1.0000 2022/10/25 19:33:15 - mmengine - INFO - Epoch(train) [36][45/63] lr: 5.3011e-04 eta: 17:54:33 time: 0.5465 data_time: 0.0044 memory: 16131 loss: 5.1174 loss_prob: 2.9632 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 19:33:18 - mmengine - INFO - Epoch(train) [36][50/63] lr: 5.3011e-04 eta: 17:52:40 time: 0.5597 data_time: 0.0246 memory: 16131 loss: 5.1264 loss_prob: 2.9678 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:33:23 - mmengine - INFO - Epoch(train) [36][55/63] lr: 5.3011e-04 eta: 17:52:40 time: 0.7173 data_time: 0.0249 memory: 16131 loss: 5.1074 loss_prob: 2.9520 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 19:33:25 - mmengine - INFO - Epoch(train) [36][60/63] lr: 5.3011e-04 eta: 17:51:29 time: 0.6865 data_time: 0.0053 memory: 16131 loss: 5.0980 loss_prob: 2.9471 loss_thr: 1.1509 loss_db: 1.0000 2022/10/25 19:33:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:33:32 - mmengine - INFO - Epoch(train) [37][5/63] lr: 5.4517e-04 eta: 17:51:29 time: 0.8483 data_time: 0.1686 memory: 16131 loss: 5.0861 loss_prob: 2.9273 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:33:37 - mmengine - INFO - Epoch(train) [37][10/63] lr: 5.4517e-04 eta: 17:50:37 time: 1.0112 data_time: 0.1697 memory: 16131 loss: 5.0795 loss_prob: 2.9188 loss_thr: 1.1607 loss_db: 1.0000 2022/10/25 19:33:41 - mmengine - INFO - Epoch(train) [37][15/63] lr: 5.4517e-04 eta: 17:50:37 time: 0.8793 data_time: 0.0099 memory: 16131 loss: 5.0944 loss_prob: 2.9374 loss_thr: 1.1571 loss_db: 0.9999 2022/10/25 19:33:44 - mmengine - INFO - Epoch(train) [37][20/63] lr: 5.4517e-04 eta: 17:49:36 time: 0.7132 data_time: 0.0112 memory: 16131 loss: 5.1200 loss_prob: 2.9573 loss_thr: 1.1628 loss_db: 1.0000 2022/10/25 19:33:47 - mmengine - INFO - Epoch(train) [37][25/63] lr: 5.4517e-04 eta: 17:49:36 time: 0.5348 data_time: 0.0166 memory: 16131 loss: 5.1277 loss_prob: 2.9636 loss_thr: 1.1642 loss_db: 1.0000 2022/10/25 19:33:51 - mmengine - INFO - Epoch(train) [37][30/63] lr: 5.4517e-04 eta: 17:48:34 time: 0.7089 data_time: 0.0281 memory: 16131 loss: 5.1308 loss_prob: 2.9815 loss_thr: 1.1493 loss_db: 1.0000 2022/10/25 19:33:55 - mmengine - INFO - Epoch(train) [37][35/63] lr: 5.4517e-04 eta: 17:48:34 time: 0.8542 data_time: 0.0205 memory: 16131 loss: 5.1360 loss_prob: 2.9837 loss_thr: 1.1522 loss_db: 1.0000 2022/10/25 19:33:58 - mmengine - INFO - Epoch(train) [37][40/63] lr: 5.4517e-04 eta: 17:47:37 time: 0.7242 data_time: 0.0086 memory: 16131 loss: 5.1314 loss_prob: 2.9717 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:34:03 - mmengine - INFO - Epoch(train) [37][45/63] lr: 5.4517e-04 eta: 17:47:37 time: 0.8066 data_time: 0.0097 memory: 16131 loss: 5.1274 loss_prob: 2.9715 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:34:06 - mmengine - INFO - Epoch(train) [37][50/63] lr: 5.4517e-04 eta: 17:46:52 time: 0.7584 data_time: 0.0129 memory: 16131 loss: 5.1205 loss_prob: 2.9630 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 19:34:10 - mmengine - INFO - Epoch(train) [37][55/63] lr: 5.4517e-04 eta: 17:46:52 time: 0.6922 data_time: 0.0163 memory: 16131 loss: 5.0930 loss_prob: 2.9333 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:34:13 - mmengine - INFO - Epoch(train) [37][60/63] lr: 5.4517e-04 eta: 17:46:04 time: 0.7476 data_time: 0.0202 memory: 16131 loss: 5.0829 loss_prob: 2.9244 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:34:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:34:21 - mmengine - INFO - Epoch(train) [38][5/63] lr: 5.6023e-04 eta: 17:46:04 time: 0.9157 data_time: 0.2025 memory: 16131 loss: 5.1201 loss_prob: 2.9620 loss_thr: 1.1582 loss_db: 1.0000 2022/10/25 19:34:24 - mmengine - INFO - Epoch(train) [38][10/63] lr: 5.6023e-04 eta: 17:44:23 time: 0.8488 data_time: 0.1937 memory: 16131 loss: 5.1225 loss_prob: 2.9666 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 19:34:27 - mmengine - INFO - Epoch(train) [38][15/63] lr: 5.6023e-04 eta: 17:44:23 time: 0.5642 data_time: 0.0085 memory: 16131 loss: 5.1122 loss_prob: 2.9550 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:34:30 - mmengine - INFO - Epoch(train) [38][20/63] lr: 5.6023e-04 eta: 17:42:49 time: 0.5976 data_time: 0.0081 memory: 16131 loss: 5.0983 loss_prob: 2.9378 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 19:34:32 - mmengine - INFO - Epoch(train) [38][25/63] lr: 5.6023e-04 eta: 17:42:49 time: 0.5881 data_time: 0.0296 memory: 16131 loss: 5.0781 loss_prob: 2.9197 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 19:34:36 - mmengine - INFO - Epoch(train) [38][30/63] lr: 5.6023e-04 eta: 17:41:20 time: 0.6141 data_time: 0.0408 memory: 16131 loss: 5.0641 loss_prob: 2.9058 loss_thr: 1.1583 loss_db: 1.0000 2022/10/25 19:34:38 - mmengine - INFO - Epoch(train) [38][35/63] lr: 5.6023e-04 eta: 17:41:20 time: 0.6073 data_time: 0.0228 memory: 16131 loss: 5.0515 loss_prob: 2.8939 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 19:34:41 - mmengine - INFO - Epoch(train) [38][40/63] lr: 5.6023e-04 eta: 17:39:26 time: 0.5269 data_time: 0.0086 memory: 16131 loss: 5.0586 loss_prob: 2.9036 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 19:34:45 - mmengine - INFO - Epoch(train) [38][45/63] lr: 5.6023e-04 eta: 17:39:26 time: 0.6146 data_time: 0.0063 memory: 16131 loss: 5.0649 loss_prob: 2.9104 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:34:47 - mmengine - INFO - Epoch(train) [38][50/63] lr: 5.6023e-04 eta: 17:38:05 time: 0.6349 data_time: 0.0186 memory: 16131 loss: 5.0731 loss_prob: 2.9177 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 19:34:50 - mmengine - INFO - Epoch(train) [38][55/63] lr: 5.6023e-04 eta: 17:38:05 time: 0.5518 data_time: 0.0213 memory: 16131 loss: 5.1004 loss_prob: 2.9405 loss_thr: 1.1600 loss_db: 1.0000 2022/10/25 19:34:56 - mmengine - INFO - Epoch(train) [38][60/63] lr: 5.6023e-04 eta: 17:37:45 time: 0.8291 data_time: 0.0127 memory: 16131 loss: 5.1212 loss_prob: 2.9596 loss_thr: 1.1616 loss_db: 1.0000 2022/10/25 19:34:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:35:04 - mmengine - INFO - Epoch(train) [39][5/63] lr: 5.7529e-04 eta: 17:37:45 time: 1.0161 data_time: 0.1916 memory: 16131 loss: 5.0999 loss_prob: 2.9427 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:35:07 - mmengine - INFO - Epoch(train) [39][10/63] lr: 5.7529e-04 eta: 17:36:11 time: 0.8536 data_time: 0.1922 memory: 16131 loss: 5.0738 loss_prob: 2.9158 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:35:10 - mmengine - INFO - Epoch(train) [39][15/63] lr: 5.7529e-04 eta: 17:36:11 time: 0.5730 data_time: 0.0068 memory: 16131 loss: 5.0612 loss_prob: 2.9038 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:35:12 - mmengine - INFO - Epoch(train) [39][20/63] lr: 5.7529e-04 eta: 17:34:21 time: 0.5317 data_time: 0.0064 memory: 16131 loss: 5.0857 loss_prob: 2.9294 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:35:18 - mmengine - INFO - Epoch(train) [39][25/63] lr: 5.7529e-04 eta: 17:34:21 time: 0.7940 data_time: 0.0473 memory: 16131 loss: 5.1244 loss_prob: 2.9689 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:35:20 - mmengine - INFO - Epoch(train) [39][30/63] lr: 5.7529e-04 eta: 17:33:59 time: 0.8221 data_time: 0.0609 memory: 16131 loss: 5.1378 loss_prob: 2.9803 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 19:35:23 - mmengine - INFO - Epoch(train) [39][35/63] lr: 5.7529e-04 eta: 17:33:59 time: 0.5665 data_time: 0.0214 memory: 16131 loss: 5.1058 loss_prob: 2.9508 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 19:35:26 - mmengine - INFO - Epoch(train) [39][40/63] lr: 5.7529e-04 eta: 17:32:09 time: 0.5266 data_time: 0.0075 memory: 16131 loss: 5.0692 loss_prob: 2.9147 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:35:29 - mmengine - INFO - Epoch(train) [39][45/63] lr: 5.7529e-04 eta: 17:32:09 time: 0.6183 data_time: 0.0048 memory: 16131 loss: 5.0689 loss_prob: 2.9120 loss_thr: 1.1569 loss_db: 1.0000 2022/10/25 19:35:32 - mmengine - INFO - Epoch(train) [39][50/63] lr: 5.7529e-04 eta: 17:30:57 time: 0.6516 data_time: 0.0192 memory: 16131 loss: 5.0933 loss_prob: 2.9382 loss_thr: 1.1552 loss_db: 1.0000 2022/10/25 19:35:35 - mmengine - INFO - Epoch(train) [39][55/63] lr: 5.7529e-04 eta: 17:30:57 time: 0.5366 data_time: 0.0221 memory: 16131 loss: 5.1250 loss_prob: 2.9708 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 19:35:38 - mmengine - INFO - Epoch(train) [39][60/63] lr: 5.7529e-04 eta: 17:29:10 time: 0.5298 data_time: 0.0073 memory: 16131 loss: 5.1165 loss_prob: 2.9629 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 19:35:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:35:46 - mmengine - INFO - Epoch(train) [40][5/63] lr: 5.9035e-04 eta: 17:29:10 time: 0.9277 data_time: 0.1672 memory: 16131 loss: 5.0770 loss_prob: 2.9222 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 19:35:50 - mmengine - INFO - Epoch(train) [40][10/63] lr: 5.9035e-04 eta: 17:28:19 time: 0.9867 data_time: 0.1706 memory: 16131 loss: 5.0825 loss_prob: 2.9310 loss_thr: 1.1515 loss_db: 1.0000 2022/10/25 19:35:53 - mmengine - INFO - Epoch(train) [40][15/63] lr: 5.9035e-04 eta: 17:28:19 time: 0.7190 data_time: 0.0084 memory: 16131 loss: 5.0846 loss_prob: 2.9312 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 19:35:56 - mmengine - INFO - Epoch(train) [40][20/63] lr: 5.9035e-04 eta: 17:26:50 time: 0.5849 data_time: 0.0060 memory: 16131 loss: 5.0786 loss_prob: 2.9249 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 19:35:59 - mmengine - INFO - Epoch(train) [40][25/63] lr: 5.9035e-04 eta: 17:26:50 time: 0.6633 data_time: 0.0091 memory: 16131 loss: 5.0851 loss_prob: 2.9286 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 19:36:04 - mmengine - INFO - Epoch(train) [40][30/63] lr: 5.9035e-04 eta: 17:26:29 time: 0.8172 data_time: 0.0381 memory: 16131 loss: 5.0902 loss_prob: 2.9334 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:36:09 - mmengine - INFO - Epoch(train) [40][35/63] lr: 5.9035e-04 eta: 17:26:29 time: 0.9661 data_time: 0.0365 memory: 16131 loss: 5.1051 loss_prob: 2.9468 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 19:36:12 - mmengine - INFO - Epoch(train) [40][40/63] lr: 5.9035e-04 eta: 17:26:22 time: 0.8664 data_time: 0.0061 memory: 16131 loss: 5.1093 loss_prob: 2.9485 loss_thr: 1.1608 loss_db: 1.0000 2022/10/25 19:36:15 - mmengine - INFO - Epoch(train) [40][45/63] lr: 5.9035e-04 eta: 17:26:22 time: 0.5909 data_time: 0.0062 memory: 16131 loss: 5.0731 loss_prob: 2.9137 loss_thr: 1.1594 loss_db: 1.0000 2022/10/25 19:36:18 - mmengine - INFO - Epoch(train) [40][50/63] lr: 5.9035e-04 eta: 17:24:31 time: 0.5051 data_time: 0.0096 memory: 16131 loss: 5.0486 loss_prob: 2.8897 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:36:20 - mmengine - INFO - Epoch(train) [40][55/63] lr: 5.9035e-04 eta: 17:24:31 time: 0.5196 data_time: 0.0220 memory: 16131 loss: 5.0664 loss_prob: 2.9052 loss_thr: 1.1612 loss_db: 1.0000 2022/10/25 19:36:25 - mmengine - INFO - Epoch(train) [40][60/63] lr: 5.9035e-04 eta: 17:23:54 time: 0.7619 data_time: 0.0203 memory: 16131 loss: 5.1103 loss_prob: 2.9517 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:36:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:36:26 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/10/25 19:36:33 - mmengine - INFO - Epoch(val) [40][5/32] eta: 17:23:54 time: 1.1875 data_time: 0.0854 memory: 16131 2022/10/25 19:36:35 - mmengine - INFO - Epoch(val) [40][10/32] eta: 0:00:11 time: 0.5068 data_time: 0.1271 memory: 15724 2022/10/25 19:36:37 - mmengine - INFO - Epoch(val) [40][15/32] eta: 0:00:11 time: 0.4351 data_time: 0.0558 memory: 15724 2022/10/25 19:36:39 - mmengine - INFO - Epoch(val) [40][20/32] eta: 0:00:05 time: 0.4308 data_time: 0.0550 memory: 15724 2022/10/25 19:36:41 - mmengine - INFO - Epoch(val) [40][25/32] eta: 0:00:05 time: 0.4375 data_time: 0.0587 memory: 15724 2022/10/25 19:36:43 - mmengine - INFO - Epoch(val) [40][30/32] eta: 0:00:00 time: 0.4044 data_time: 0.0224 memory: 15724 2022/10/25 19:36:44 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:36:44 - mmengine - INFO - Epoch(val) [40][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/10/25 19:36:50 - mmengine - INFO - Epoch(train) [41][5/63] lr: 6.0541e-04 eta: 0:00:00 time: 1.0465 data_time: 0.1862 memory: 16131 loss: 5.0954 loss_prob: 2.9487 loss_thr: 1.1467 loss_db: 1.0000 2022/10/25 19:36:53 - mmengine - INFO - Epoch(train) [41][10/63] lr: 6.0541e-04 eta: 17:22:35 time: 0.8768 data_time: 0.1881 memory: 16131 loss: 5.0731 loss_prob: 2.9170 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 19:36:57 - mmengine - INFO - Epoch(train) [41][15/63] lr: 6.0541e-04 eta: 17:22:35 time: 0.6839 data_time: 0.0086 memory: 16131 loss: 5.0711 loss_prob: 2.9125 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:36:59 - mmengine - INFO - Epoch(train) [41][20/63] lr: 6.0541e-04 eta: 17:21:38 time: 0.6891 data_time: 0.0044 memory: 16131 loss: 5.0570 loss_prob: 2.9027 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:37:04 - mmengine - INFO - Epoch(train) [41][25/63] lr: 6.0541e-04 eta: 17:21:38 time: 0.7361 data_time: 0.0200 memory: 16131 loss: 5.0403 loss_prob: 2.8806 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:37:07 - mmengine - INFO - Epoch(train) [41][30/63] lr: 6.0541e-04 eta: 17:21:11 time: 0.7918 data_time: 0.0425 memory: 16131 loss: 5.0291 loss_prob: 2.8723 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:37:10 - mmengine - INFO - Epoch(train) [41][35/63] lr: 6.0541e-04 eta: 17:21:11 time: 0.6412 data_time: 0.0279 memory: 16131 loss: 5.0520 loss_prob: 2.8959 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 19:37:14 - mmengine - INFO - Epoch(train) [41][40/63] lr: 6.0541e-04 eta: 17:20:00 time: 0.6344 data_time: 0.0058 memory: 16131 loss: 5.0753 loss_prob: 2.9210 loss_thr: 1.1543 loss_db: 1.0000 2022/10/25 19:37:16 - mmengine - INFO - Epoch(train) [41][45/63] lr: 6.0541e-04 eta: 17:20:00 time: 0.5930 data_time: 0.0049 memory: 16131 loss: 5.0730 loss_prob: 2.9197 loss_thr: 1.1533 loss_db: 1.0000 2022/10/25 19:37:19 - mmengine - INFO - Epoch(train) [41][50/63] lr: 6.0541e-04 eta: 17:18:25 time: 0.5514 data_time: 0.0135 memory: 16131 loss: 5.0685 loss_prob: 2.9113 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:37:22 - mmengine - INFO - Epoch(train) [41][55/63] lr: 6.0541e-04 eta: 17:18:25 time: 0.5987 data_time: 0.0257 memory: 16131 loss: 5.0565 loss_prob: 2.8970 loss_thr: 1.1595 loss_db: 1.0000 2022/10/25 19:37:26 - mmengine - INFO - Epoch(train) [41][60/63] lr: 6.0541e-04 eta: 17:17:34 time: 0.7045 data_time: 0.0181 memory: 16131 loss: 5.0480 loss_prob: 2.8860 loss_thr: 1.1620 loss_db: 1.0000 2022/10/25 19:37:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:37:33 - mmengine - INFO - Epoch(train) [42][5/63] lr: 6.2047e-04 eta: 17:17:34 time: 0.8461 data_time: 0.2265 memory: 16131 loss: 5.0387 loss_prob: 2.8829 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:37:36 - mmengine - INFO - Epoch(train) [42][10/63] lr: 6.2047e-04 eta: 17:16:05 time: 0.8304 data_time: 0.2283 memory: 16131 loss: 5.0454 loss_prob: 2.8876 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 19:37:39 - mmengine - INFO - Epoch(train) [42][15/63] lr: 6.2047e-04 eta: 17:16:05 time: 0.5964 data_time: 0.0076 memory: 16131 loss: 5.0602 loss_prob: 2.9046 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 19:37:42 - mmengine - INFO - Epoch(train) [42][20/63] lr: 6.2047e-04 eta: 17:14:48 time: 0.6066 data_time: 0.0079 memory: 16131 loss: 5.0671 loss_prob: 2.9122 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 19:37:45 - mmengine - INFO - Epoch(train) [42][25/63] lr: 6.2047e-04 eta: 17:14:48 time: 0.6404 data_time: 0.0327 memory: 16131 loss: 5.0731 loss_prob: 2.9210 loss_thr: 1.1521 loss_db: 1.0000 2022/10/25 19:37:48 - mmengine - INFO - Epoch(train) [42][30/63] lr: 6.2047e-04 eta: 17:13:12 time: 0.5391 data_time: 0.0294 memory: 16131 loss: 5.0650 loss_prob: 2.9157 loss_thr: 1.1494 loss_db: 1.0000 2022/10/25 19:37:51 - mmengine - INFO - Epoch(train) [42][35/63] lr: 6.2047e-04 eta: 17:13:12 time: 0.5463 data_time: 0.0088 memory: 16131 loss: 5.0729 loss_prob: 2.9183 loss_thr: 1.1547 loss_db: 0.9999 2022/10/25 19:37:53 - mmengine - INFO - Epoch(train) [42][40/63] lr: 6.2047e-04 eta: 17:11:38 time: 0.5410 data_time: 0.0087 memory: 16131 loss: 5.0872 loss_prob: 2.9293 loss_thr: 1.1580 loss_db: 0.9999 2022/10/25 19:37:55 - mmengine - INFO - Epoch(train) [42][45/63] lr: 6.2047e-04 eta: 17:11:38 time: 0.4924 data_time: 0.0057 memory: 16131 loss: 5.0791 loss_prob: 2.9170 loss_thr: 1.1622 loss_db: 0.9999 2022/10/25 19:37:59 - mmengine - INFO - Epoch(train) [42][50/63] lr: 6.2047e-04 eta: 17:10:16 time: 0.5805 data_time: 0.0184 memory: 16131 loss: 5.0833 loss_prob: 2.9214 loss_thr: 1.1620 loss_db: 0.9999 2022/10/25 19:38:01 - mmengine - INFO - Epoch(train) [42][55/63] lr: 6.2047e-04 eta: 17:10:16 time: 0.5842 data_time: 0.0201 memory: 16131 loss: 5.0844 loss_prob: 2.9249 loss_thr: 1.1595 loss_db: 1.0000 2022/10/25 19:38:04 - mmengine - INFO - Epoch(train) [42][60/63] lr: 6.2047e-04 eta: 17:08:31 time: 0.4994 data_time: 0.0083 memory: 16131 loss: 5.0822 loss_prob: 2.9258 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 19:38:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:38:10 - mmengine - INFO - Epoch(train) [43][5/63] lr: 6.3553e-04 eta: 17:08:31 time: 0.6728 data_time: 0.2085 memory: 16131 loss: 5.0929 loss_prob: 2.9422 loss_thr: 1.1508 loss_db: 1.0000 2022/10/25 19:38:12 - mmengine - INFO - Epoch(train) [43][10/63] lr: 6.3553e-04 eta: 17:06:34 time: 0.7133 data_time: 0.2082 memory: 16131 loss: 5.1066 loss_prob: 2.9565 loss_thr: 1.1501 loss_db: 1.0000 2022/10/25 19:38:15 - mmengine - INFO - Epoch(train) [43][15/63] lr: 6.3553e-04 eta: 17:06:34 time: 0.5156 data_time: 0.0060 memory: 16131 loss: 5.1088 loss_prob: 2.9570 loss_thr: 1.1519 loss_db: 1.0000 2022/10/25 19:38:17 - mmengine - INFO - Epoch(train) [43][20/63] lr: 6.3553e-04 eta: 17:04:55 time: 0.5125 data_time: 0.0074 memory: 16131 loss: 5.0871 loss_prob: 2.9348 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 19:38:20 - mmengine - INFO - Epoch(train) [43][25/63] lr: 6.3553e-04 eta: 17:04:55 time: 0.5564 data_time: 0.0314 memory: 16131 loss: 5.0647 loss_prob: 2.9117 loss_thr: 1.1530 loss_db: 1.0000 2022/10/25 19:38:23 - mmengine - INFO - Epoch(train) [43][30/63] lr: 6.3553e-04 eta: 17:03:27 time: 0.5537 data_time: 0.0309 memory: 16131 loss: 5.0600 loss_prob: 2.9058 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 19:38:27 - mmengine - INFO - Epoch(train) [43][35/63] lr: 6.3553e-04 eta: 17:03:27 time: 0.6374 data_time: 0.0057 memory: 16131 loss: 5.0641 loss_prob: 2.9070 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:38:30 - mmengine - INFO - Epoch(train) [43][40/63] lr: 6.3553e-04 eta: 17:02:48 time: 0.7295 data_time: 0.0125 memory: 16131 loss: 5.0834 loss_prob: 2.9259 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:38:33 - mmengine - INFO - Epoch(train) [43][45/63] lr: 6.3553e-04 eta: 17:02:48 time: 0.6715 data_time: 0.0141 memory: 16131 loss: 5.0798 loss_prob: 2.9275 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 19:38:39 - mmengine - INFO - Epoch(train) [43][50/63] lr: 6.3553e-04 eta: 17:02:47 time: 0.8673 data_time: 0.0224 memory: 16131 loss: 5.0630 loss_prob: 2.9077 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:38:43 - mmengine - INFO - Epoch(train) [43][55/63] lr: 6.3553e-04 eta: 17:02:47 time: 0.9729 data_time: 0.0225 memory: 16131 loss: 5.0692 loss_prob: 2.9090 loss_thr: 1.1603 loss_db: 1.0000 2022/10/25 19:38:46 - mmengine - INFO - Epoch(train) [43][60/63] lr: 6.3553e-04 eta: 17:01:55 time: 0.6821 data_time: 0.0063 memory: 16131 loss: 5.0532 loss_prob: 2.8955 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:38:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:38:55 - mmengine - INFO - Epoch(train) [44][5/63] lr: 6.5059e-04 eta: 17:01:55 time: 1.0781 data_time: 0.1739 memory: 16131 loss: 5.0450 loss_prob: 2.8882 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:38:59 - mmengine - INFO - Epoch(train) [44][10/63] lr: 6.5059e-04 eta: 17:01:37 time: 1.0637 data_time: 0.1815 memory: 16131 loss: 5.0466 loss_prob: 2.8880 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 19:39:01 - mmengine - INFO - Epoch(train) [44][15/63] lr: 6.5059e-04 eta: 17:01:37 time: 0.5831 data_time: 0.0129 memory: 16131 loss: 5.0406 loss_prob: 2.8826 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:39:04 - mmengine - INFO - Epoch(train) [44][20/63] lr: 6.5059e-04 eta: 17:00:04 time: 0.5259 data_time: 0.0049 memory: 16131 loss: 5.0334 loss_prob: 2.8776 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:39:08 - mmengine - INFO - Epoch(train) [44][25/63] lr: 6.5059e-04 eta: 17:00:04 time: 0.6319 data_time: 0.0188 memory: 16131 loss: 5.0409 loss_prob: 2.8883 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 19:39:12 - mmengine - INFO - Epoch(train) [44][30/63] lr: 6.5059e-04 eta: 16:59:44 time: 0.7974 data_time: 0.0304 memory: 16131 loss: 5.0545 loss_prob: 2.9032 loss_thr: 1.1514 loss_db: 1.0000 2022/10/25 19:39:17 - mmengine - INFO - Epoch(train) [44][35/63] lr: 6.5059e-04 eta: 16:59:44 time: 0.9368 data_time: 0.0246 memory: 16131 loss: 5.0501 loss_prob: 2.8963 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 19:39:20 - mmengine - INFO - Epoch(train) [44][40/63] lr: 6.5059e-04 eta: 16:59:34 time: 0.8316 data_time: 0.0131 memory: 16131 loss: 5.0354 loss_prob: 2.8791 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:39:24 - mmengine - INFO - Epoch(train) [44][45/63] lr: 6.5059e-04 eta: 16:59:34 time: 0.7514 data_time: 0.0051 memory: 16131 loss: 5.0552 loss_prob: 2.8965 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:39:29 - mmengine - INFO - Epoch(train) [44][50/63] lr: 6.5059e-04 eta: 16:59:24 time: 0.8330 data_time: 0.0185 memory: 16131 loss: 5.0939 loss_prob: 2.9384 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:39:32 - mmengine - INFO - Epoch(train) [44][55/63] lr: 6.5059e-04 eta: 16:59:24 time: 0.7423 data_time: 0.0198 memory: 16131 loss: 5.1027 loss_prob: 2.9463 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 19:39:36 - mmengine - INFO - Epoch(train) [44][60/63] lr: 6.5059e-04 eta: 16:58:52 time: 0.7499 data_time: 0.0110 memory: 16131 loss: 5.0857 loss_prob: 2.9252 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 19:39:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:39:44 - mmengine - INFO - Epoch(train) [45][5/63] lr: 6.6565e-04 eta: 16:58:52 time: 0.8828 data_time: 0.2244 memory: 16131 loss: 5.0771 loss_prob: 2.9208 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:39:48 - mmengine - INFO - Epoch(train) [45][10/63] lr: 6.6565e-04 eta: 16:58:15 time: 0.9930 data_time: 0.2267 memory: 16131 loss: 5.0878 loss_prob: 2.9282 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:39:51 - mmengine - INFO - Epoch(train) [45][15/63] lr: 6.6565e-04 eta: 16:58:15 time: 0.7303 data_time: 0.0069 memory: 16131 loss: 5.0669 loss_prob: 2.9103 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:39:54 - mmengine - INFO - Epoch(train) [45][20/63] lr: 6.6565e-04 eta: 16:57:06 time: 0.6076 data_time: 0.0075 memory: 16131 loss: 5.0416 loss_prob: 2.8841 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:39:57 - mmengine - INFO - Epoch(train) [45][25/63] lr: 6.6565e-04 eta: 16:57:06 time: 0.6301 data_time: 0.0104 memory: 16131 loss: 5.0370 loss_prob: 2.8753 loss_thr: 1.1617 loss_db: 1.0000 2022/10/25 19:40:02 - mmengine - INFO - Epoch(train) [45][30/63] lr: 6.6565e-04 eta: 16:56:53 time: 0.8212 data_time: 0.0336 memory: 16131 loss: 5.0324 loss_prob: 2.8736 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:40:04 - mmengine - INFO - Epoch(train) [45][35/63] lr: 6.6565e-04 eta: 16:56:53 time: 0.7037 data_time: 0.0324 memory: 16131 loss: 5.0472 loss_prob: 2.8906 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:40:08 - mmengine - INFO - Epoch(train) [45][40/63] lr: 6.6565e-04 eta: 16:55:38 time: 0.5804 data_time: 0.0152 memory: 16131 loss: 5.0854 loss_prob: 2.9243 loss_thr: 1.1611 loss_db: 1.0000 2022/10/25 19:40:10 - mmengine - INFO - Epoch(train) [45][45/63] lr: 6.6565e-04 eta: 16:55:38 time: 0.6006 data_time: 0.0150 memory: 16131 loss: 5.0951 loss_prob: 2.9364 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:40:13 - mmengine - INFO - Epoch(train) [45][50/63] lr: 6.6565e-04 eta: 16:54:19 time: 0.5631 data_time: 0.0292 memory: 16131 loss: 5.1025 loss_prob: 2.9492 loss_thr: 1.1533 loss_db: 1.0000 2022/10/25 19:40:17 - mmengine - INFO - Epoch(train) [45][55/63] lr: 6.6565e-04 eta: 16:54:19 time: 0.6455 data_time: 0.0284 memory: 16131 loss: 5.1387 loss_prob: 2.9849 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 19:40:19 - mmengine - INFO - Epoch(train) [45][60/63] lr: 6.6565e-04 eta: 16:53:14 time: 0.6141 data_time: 0.0053 memory: 16131 loss: 5.1381 loss_prob: 2.9849 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 19:40:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:40:28 - mmengine - INFO - Epoch(train) [46][5/63] lr: 6.8071e-04 eta: 16:53:14 time: 0.9868 data_time: 0.1965 memory: 16131 loss: 5.1080 loss_prob: 2.9507 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:40:35 - mmengine - INFO - Epoch(train) [46][10/63] lr: 6.8071e-04 eta: 16:54:24 time: 1.4030 data_time: 0.2014 memory: 16131 loss: 5.1224 loss_prob: 2.9633 loss_thr: 1.1590 loss_db: 1.0000 2022/10/25 19:40:41 - mmengine - INFO - Epoch(train) [46][15/63] lr: 6.8071e-04 eta: 16:54:24 time: 1.2906 data_time: 0.0124 memory: 16131 loss: 5.1190 loss_prob: 2.9646 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:40:45 - mmengine - INFO - Epoch(train) [46][20/63] lr: 6.8071e-04 eta: 16:55:07 time: 1.0400 data_time: 0.0052 memory: 16131 loss: 5.0940 loss_prob: 2.9395 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:40:48 - mmengine - INFO - Epoch(train) [46][25/63] lr: 6.8071e-04 eta: 16:55:07 time: 0.7107 data_time: 0.0282 memory: 16131 loss: 5.0827 loss_prob: 2.9273 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:40:51 - mmengine - INFO - Epoch(train) [46][30/63] lr: 6.8071e-04 eta: 16:53:54 time: 0.5821 data_time: 0.0349 memory: 16131 loss: 5.0937 loss_prob: 2.9365 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:40:54 - mmengine - INFO - Epoch(train) [46][35/63] lr: 6.8071e-04 eta: 16:53:54 time: 0.5618 data_time: 0.0211 memory: 16131 loss: 5.0903 loss_prob: 2.9336 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:41:01 - mmengine - INFO - Epoch(train) [46][40/63] lr: 6.8071e-04 eta: 16:54:24 time: 0.9869 data_time: 0.0140 memory: 16131 loss: 5.0804 loss_prob: 2.9218 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 19:41:07 - mmengine - INFO - Epoch(train) [46][45/63] lr: 6.8071e-04 eta: 16:54:24 time: 1.3118 data_time: 0.0085 memory: 16131 loss: 5.0820 loss_prob: 2.9217 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 19:41:11 - mmengine - INFO - Epoch(train) [46][50/63] lr: 6.8071e-04 eta: 16:54:47 time: 0.9606 data_time: 0.0185 memory: 16131 loss: 5.0793 loss_prob: 2.9235 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 19:41:13 - mmengine - INFO - Epoch(train) [46][55/63] lr: 6.8071e-04 eta: 16:54:47 time: 0.6364 data_time: 0.0187 memory: 16131 loss: 5.0764 loss_prob: 2.9205 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:41:17 - mmengine - INFO - Epoch(train) [46][60/63] lr: 6.8071e-04 eta: 16:53:46 time: 0.6301 data_time: 0.0124 memory: 16131 loss: 5.0640 loss_prob: 2.9100 loss_thr: 1.1540 loss_db: 1.0000 2022/10/25 19:41:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:41:26 - mmengine - INFO - Epoch(train) [47][5/63] lr: 6.9577e-04 eta: 16:53:46 time: 1.1240 data_time: 0.1966 memory: 16131 loss: 5.0440 loss_prob: 2.8905 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 19:41:31 - mmengine - INFO - Epoch(train) [47][10/63] lr: 6.9577e-04 eta: 16:54:17 time: 1.2533 data_time: 0.2022 memory: 16131 loss: 5.0334 loss_prob: 2.8815 loss_thr: 1.1519 loss_db: 1.0000 2022/10/25 19:41:34 - mmengine - INFO - Epoch(train) [47][15/63] lr: 6.9577e-04 eta: 16:54:17 time: 0.7688 data_time: 0.0171 memory: 16131 loss: 5.0317 loss_prob: 2.8815 loss_thr: 1.1503 loss_db: 1.0000 2022/10/25 19:41:38 - mmengine - INFO - Epoch(train) [47][20/63] lr: 6.9577e-04 eta: 16:53:25 time: 0.6638 data_time: 0.0148 memory: 16131 loss: 5.0427 loss_prob: 2.8835 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 19:41:43 - mmengine - INFO - Epoch(train) [47][25/63] lr: 6.9577e-04 eta: 16:53:25 time: 0.9345 data_time: 0.0165 memory: 16131 loss: 5.0577 loss_prob: 2.9025 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:41:47 - mmengine - INFO - Epoch(train) [47][30/63] lr: 6.9577e-04 eta: 16:53:45 time: 0.9509 data_time: 0.0224 memory: 16131 loss: 5.0587 loss_prob: 2.9046 loss_thr: 1.1541 loss_db: 0.9999 2022/10/25 19:41:53 - mmengine - INFO - Epoch(train) [47][35/63] lr: 6.9577e-04 eta: 16:53:45 time: 0.9619 data_time: 0.0269 memory: 16131 loss: 5.0455 loss_prob: 2.8892 loss_thr: 1.1563 loss_db: 0.9999 2022/10/25 19:41:56 - mmengine - INFO - Epoch(train) [47][40/63] lr: 6.9577e-04 eta: 16:53:38 time: 0.8412 data_time: 0.0174 memory: 16131 loss: 5.0380 loss_prob: 2.8872 loss_thr: 1.1510 loss_db: 0.9999 2022/10/25 19:42:00 - mmengine - INFO - Epoch(train) [47][45/63] lr: 6.9577e-04 eta: 16:53:38 time: 0.7021 data_time: 0.0049 memory: 16131 loss: 5.0488 loss_prob: 2.8930 loss_thr: 1.1560 loss_db: 0.9999 2022/10/25 19:42:02 - mmengine - INFO - Epoch(train) [47][50/63] lr: 6.9577e-04 eta: 16:52:46 time: 0.6617 data_time: 0.0199 memory: 16131 loss: 5.0386 loss_prob: 2.8803 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 19:42:05 - mmengine - INFO - Epoch(train) [47][55/63] lr: 6.9577e-04 eta: 16:52:46 time: 0.5139 data_time: 0.0231 memory: 16131 loss: 5.0240 loss_prob: 2.8669 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:42:09 - mmengine - INFO - Epoch(train) [47][60/63] lr: 6.9577e-04 eta: 16:51:42 time: 0.6077 data_time: 0.0113 memory: 16131 loss: 5.0356 loss_prob: 2.8779 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:42:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:42:17 - mmengine - INFO - Epoch(train) [48][5/63] lr: 7.1083e-04 eta: 16:51:42 time: 0.9350 data_time: 0.1645 memory: 16131 loss: 5.0396 loss_prob: 2.8874 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 19:42:21 - mmengine - INFO - Epoch(train) [48][10/63] lr: 7.1083e-04 eta: 16:51:30 time: 1.0826 data_time: 0.1747 memory: 16131 loss: 5.0310 loss_prob: 2.8792 loss_thr: 1.1519 loss_db: 1.0000 2022/10/25 19:42:24 - mmengine - INFO - Epoch(train) [48][15/63] lr: 7.1083e-04 eta: 16:51:30 time: 0.7096 data_time: 0.0195 memory: 16131 loss: 5.0329 loss_prob: 2.8799 loss_thr: 1.1530 loss_db: 1.0000 2022/10/25 19:42:28 - mmengine - INFO - Epoch(train) [48][20/63] lr: 7.1083e-04 eta: 16:50:49 time: 0.6990 data_time: 0.0072 memory: 16131 loss: 5.0372 loss_prob: 2.8819 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:42:31 - mmengine - INFO - Epoch(train) [48][25/63] lr: 7.1083e-04 eta: 16:50:49 time: 0.6998 data_time: 0.0103 memory: 16131 loss: 5.0326 loss_prob: 2.8743 loss_thr: 1.1583 loss_db: 1.0000 2022/10/25 19:42:34 - mmengine - INFO - Epoch(train) [48][30/63] lr: 7.1083e-04 eta: 16:50:03 time: 0.6842 data_time: 0.0237 memory: 16131 loss: 5.0189 loss_prob: 2.8633 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 19:42:38 - mmengine - INFO - Epoch(train) [48][35/63] lr: 7.1083e-04 eta: 16:50:03 time: 0.6537 data_time: 0.0275 memory: 16131 loss: 5.0185 loss_prob: 2.8598 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:42:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:42:41 - mmengine - INFO - Epoch(train) [48][40/63] lr: 7.1083e-04 eta: 16:49:03 time: 0.6207 data_time: 0.0187 memory: 16131 loss: 5.0232 loss_prob: 2.8670 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:42:46 - mmengine - INFO - Epoch(train) [48][45/63] lr: 7.1083e-04 eta: 16:49:03 time: 0.8263 data_time: 0.0141 memory: 16131 loss: 5.0366 loss_prob: 2.8852 loss_thr: 1.1514 loss_db: 1.0000 2022/10/25 19:42:50 - mmengine - INFO - Epoch(train) [48][50/63] lr: 7.1083e-04 eta: 16:49:26 time: 0.9619 data_time: 0.0136 memory: 16131 loss: 5.0504 loss_prob: 2.8916 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:42:54 - mmengine - INFO - Epoch(train) [48][55/63] lr: 7.1083e-04 eta: 16:49:26 time: 0.7821 data_time: 0.0161 memory: 16131 loss: 5.0476 loss_prob: 2.8873 loss_thr: 1.1603 loss_db: 1.0000 2022/10/25 19:42:57 - mmengine - INFO - Epoch(train) [48][60/63] lr: 7.1083e-04 eta: 16:48:49 time: 0.7169 data_time: 0.0195 memory: 16131 loss: 5.0910 loss_prob: 2.9198 loss_thr: 1.1720 loss_db: 0.9991 2022/10/25 19:43:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:43:06 - mmengine - INFO - Epoch(train) [49][5/63] lr: 7.2589e-04 eta: 16:48:49 time: 1.0623 data_time: 0.2215 memory: 16131 loss: 5.0725 loss_prob: 2.9127 loss_thr: 1.1599 loss_db: 1.0000 2022/10/25 19:43:10 - mmengine - INFO - Epoch(train) [49][10/63] lr: 7.2589e-04 eta: 16:48:03 time: 0.9355 data_time: 0.2198 memory: 16131 loss: 5.1038 loss_prob: 2.9460 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 19:43:14 - mmengine - INFO - Epoch(train) [49][15/63] lr: 7.2589e-04 eta: 16:48:03 time: 0.7808 data_time: 0.0052 memory: 16131 loss: 5.1150 loss_prob: 2.9605 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:43:18 - mmengine - INFO - Epoch(train) [49][20/63] lr: 7.2589e-04 eta: 16:47:58 time: 0.8468 data_time: 0.0073 memory: 16131 loss: 5.1072 loss_prob: 2.9546 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 19:43:21 - mmengine - INFO - Epoch(train) [49][25/63] lr: 7.2589e-04 eta: 16:47:58 time: 0.7223 data_time: 0.0169 memory: 16131 loss: 5.0825 loss_prob: 2.9254 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 19:43:24 - mmengine - INFO - Epoch(train) [49][30/63] lr: 7.2589e-04 eta: 16:46:52 time: 0.5912 data_time: 0.0333 memory: 16131 loss: 5.0632 loss_prob: 2.9037 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:43:27 - mmengine - INFO - Epoch(train) [49][35/63] lr: 7.2589e-04 eta: 16:46:52 time: 0.6307 data_time: 0.0235 memory: 16131 loss: 5.0802 loss_prob: 2.9227 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:43:30 - mmengine - INFO - Epoch(train) [49][40/63] lr: 7.2589e-04 eta: 16:45:48 time: 0.5998 data_time: 0.0092 memory: 16131 loss: 5.1064 loss_prob: 2.9501 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:43:35 - mmengine - INFO - Epoch(train) [49][45/63] lr: 7.2589e-04 eta: 16:45:48 time: 0.7877 data_time: 0.0091 memory: 16131 loss: 5.1049 loss_prob: 2.9494 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:43:43 - mmengine - INFO - Epoch(train) [49][50/63] lr: 7.2589e-04 eta: 16:47:25 time: 1.2785 data_time: 0.0121 memory: 16131 loss: 5.1169 loss_prob: 2.9537 loss_thr: 1.1632 loss_db: 1.0000 2022/10/25 19:43:48 - mmengine - INFO - Epoch(train) [49][55/63] lr: 7.2589e-04 eta: 16:47:25 time: 1.2984 data_time: 0.0207 memory: 16131 loss: 5.1266 loss_prob: 2.9630 loss_thr: 1.1636 loss_db: 1.0000 2022/10/25 19:43:51 - mmengine - INFO - Epoch(train) [49][60/63] lr: 7.2589e-04 eta: 16:47:08 time: 0.7933 data_time: 0.0134 memory: 16131 loss: 5.0980 loss_prob: 2.9440 loss_thr: 1.1540 loss_db: 1.0000 2022/10/25 19:43:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:43:58 - mmengine - INFO - Epoch(train) [50][5/63] lr: 7.4095e-04 eta: 16:47:08 time: 0.7918 data_time: 0.2096 memory: 16131 loss: 5.0733 loss_prob: 2.9163 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:44:03 - mmengine - INFO - Epoch(train) [50][10/63] lr: 7.4095e-04 eta: 16:46:29 time: 0.9630 data_time: 0.2082 memory: 16131 loss: 5.0657 loss_prob: 2.9081 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:44:07 - mmengine - INFO - Epoch(train) [50][15/63] lr: 7.4095e-04 eta: 16:46:29 time: 0.9599 data_time: 0.0056 memory: 16131 loss: 5.0797 loss_prob: 2.9205 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 19:44:13 - mmengine - INFO - Epoch(train) [50][20/63] lr: 7.4095e-04 eta: 16:47:03 time: 1.0158 data_time: 0.0064 memory: 16131 loss: 5.0759 loss_prob: 2.9185 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:44:16 - mmengine - INFO - Epoch(train) [50][25/63] lr: 7.4095e-04 eta: 16:47:03 time: 0.9093 data_time: 0.0108 memory: 16131 loss: 5.0522 loss_prob: 2.8954 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:44:21 - mmengine - INFO - Epoch(train) [50][30/63] lr: 7.4095e-04 eta: 16:46:45 time: 0.7922 data_time: 0.0324 memory: 16131 loss: 5.0424 loss_prob: 2.8826 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:44:23 - mmengine - INFO - Epoch(train) [50][35/63] lr: 7.4095e-04 eta: 16:46:45 time: 0.7011 data_time: 0.0269 memory: 16131 loss: 5.0378 loss_prob: 2.8806 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:44:26 - mmengine - INFO - Epoch(train) [50][40/63] lr: 7.4095e-04 eta: 16:45:24 time: 0.5187 data_time: 0.0063 memory: 16131 loss: 5.0282 loss_prob: 2.8730 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:44:29 - mmengine - INFO - Epoch(train) [50][45/63] lr: 7.4095e-04 eta: 16:45:24 time: 0.5427 data_time: 0.0067 memory: 16131 loss: 5.0394 loss_prob: 2.8752 loss_thr: 1.1642 loss_db: 1.0000 2022/10/25 19:44:33 - mmengine - INFO - Epoch(train) [50][50/63] lr: 7.4095e-04 eta: 16:44:47 time: 0.7099 data_time: 0.0186 memory: 16131 loss: 5.0952 loss_prob: 2.9267 loss_thr: 1.1686 loss_db: 1.0000 2022/10/25 19:44:36 - mmengine - INFO - Epoch(train) [50][55/63] lr: 7.4095e-04 eta: 16:44:47 time: 0.7253 data_time: 0.0219 memory: 16131 loss: 5.1551 loss_prob: 2.9927 loss_thr: 1.1624 loss_db: 1.0000 2022/10/25 19:44:41 - mmengine - INFO - Epoch(train) [50][60/63] lr: 7.4095e-04 eta: 16:44:43 time: 0.8478 data_time: 0.0083 memory: 16131 loss: 5.1631 loss_prob: 3.0054 loss_thr: 1.1578 loss_db: 1.0000 2022/10/25 19:44:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:44:48 - mmengine - INFO - Epoch(train) [51][5/63] lr: 7.5602e-04 eta: 16:44:43 time: 0.8508 data_time: 0.2090 memory: 16131 loss: 5.1433 loss_prob: 2.9888 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:44:53 - mmengine - INFO - Epoch(train) [51][10/63] lr: 7.5602e-04 eta: 16:43:54 time: 0.9160 data_time: 0.2091 memory: 16131 loss: 5.1172 loss_prob: 2.9646 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 19:44:56 - mmengine - INFO - Epoch(train) [51][15/63] lr: 7.5602e-04 eta: 16:43:54 time: 0.7193 data_time: 0.0052 memory: 16131 loss: 5.1363 loss_prob: 2.9794 loss_thr: 1.1569 loss_db: 1.0000 2022/10/25 19:44:59 - mmengine - INFO - Epoch(train) [51][20/63] lr: 7.5602e-04 eta: 16:43:08 time: 0.6672 data_time: 0.0074 memory: 16131 loss: 5.1430 loss_prob: 2.9875 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:45:03 - mmengine - INFO - Epoch(train) [51][25/63] lr: 7.5602e-04 eta: 16:43:08 time: 0.7694 data_time: 0.0371 memory: 16131 loss: 5.1253 loss_prob: 2.9739 loss_thr: 1.1514 loss_db: 1.0000 2022/10/25 19:45:06 - mmengine - INFO - Epoch(train) [51][30/63] lr: 7.5602e-04 eta: 16:42:26 time: 0.6830 data_time: 0.0465 memory: 16131 loss: 5.1404 loss_prob: 2.9894 loss_thr: 1.1511 loss_db: 1.0000 2022/10/25 19:45:09 - mmengine - INFO - Epoch(train) [51][35/63] lr: 7.5602e-04 eta: 16:42:26 time: 0.5535 data_time: 0.0164 memory: 16131 loss: 5.1680 loss_prob: 3.0116 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 19:45:12 - mmengine - INFO - Epoch(train) [51][40/63] lr: 7.5602e-04 eta: 16:41:15 time: 0.5546 data_time: 0.0069 memory: 16131 loss: 5.1670 loss_prob: 3.0081 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:45:17 - mmengine - INFO - Epoch(train) [51][45/63] lr: 7.5602e-04 eta: 16:41:15 time: 0.8234 data_time: 0.0112 memory: 16131 loss: 5.1488 loss_prob: 2.9917 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 19:45:20 - mmengine - INFO - Epoch(train) [51][50/63] lr: 7.5602e-04 eta: 16:41:14 time: 0.8626 data_time: 0.0258 memory: 16131 loss: 5.1350 loss_prob: 2.9774 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:45:23 - mmengine - INFO - Epoch(train) [51][55/63] lr: 7.5602e-04 eta: 16:41:14 time: 0.5865 data_time: 0.0213 memory: 16131 loss: 5.1089 loss_prob: 2.9517 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:45:28 - mmengine - INFO - Epoch(train) [51][60/63] lr: 7.5602e-04 eta: 16:40:40 time: 0.7149 data_time: 0.0049 memory: 16131 loss: 5.0776 loss_prob: 2.9206 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:45:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:45:36 - mmengine - INFO - Epoch(train) [52][5/63] lr: 7.7108e-04 eta: 16:40:40 time: 1.1120 data_time: 0.1905 memory: 16131 loss: 5.0955 loss_prob: 2.9413 loss_thr: 1.1543 loss_db: 1.0000 2022/10/25 19:45:43 - mmengine - INFO - Epoch(train) [52][10/63] lr: 7.7108e-04 eta: 16:41:03 time: 1.2296 data_time: 0.1935 memory: 16131 loss: 5.1039 loss_prob: 2.9444 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:45:46 - mmengine - INFO - Epoch(train) [52][15/63] lr: 7.7108e-04 eta: 16:41:03 time: 0.9817 data_time: 0.0107 memory: 16131 loss: 5.0896 loss_prob: 2.9302 loss_thr: 1.1594 loss_db: 1.0000 2022/10/25 19:45:49 - mmengine - INFO - Epoch(train) [52][20/63] lr: 7.7108e-04 eta: 16:40:08 time: 0.6189 data_time: 0.0115 memory: 16131 loss: 5.0728 loss_prob: 2.9205 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 19:45:52 - mmengine - INFO - Epoch(train) [52][25/63] lr: 7.7108e-04 eta: 16:40:08 time: 0.5558 data_time: 0.0352 memory: 16131 loss: 5.0789 loss_prob: 2.9245 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:45:56 - mmengine - INFO - Epoch(train) [52][30/63] lr: 7.7108e-04 eta: 16:39:29 time: 0.6919 data_time: 0.0363 memory: 16131 loss: 5.0978 loss_prob: 2.9347 loss_thr: 1.1631 loss_db: 1.0000 2022/10/25 19:46:02 - mmengine - INFO - Epoch(train) [52][35/63] lr: 7.7108e-04 eta: 16:39:29 time: 1.0654 data_time: 0.0095 memory: 16131 loss: 5.0885 loss_prob: 2.9276 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:46:08 - mmengine - INFO - Epoch(train) [52][40/63] lr: 7.7108e-04 eta: 16:40:53 time: 1.2476 data_time: 0.0057 memory: 16131 loss: 5.0701 loss_prob: 2.9167 loss_thr: 1.1534 loss_db: 1.0000 2022/10/25 19:46:14 - mmengine - INFO - Epoch(train) [52][45/63] lr: 7.7108e-04 eta: 16:40:53 time: 1.2185 data_time: 0.0061 memory: 16131 loss: 5.0796 loss_prob: 2.9247 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 19:46:19 - mmengine - INFO - Epoch(train) [52][50/63] lr: 7.7108e-04 eta: 16:41:50 time: 1.1213 data_time: 0.0230 memory: 16131 loss: 5.0750 loss_prob: 2.9184 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:46:23 - mmengine - INFO - Epoch(train) [52][55/63] lr: 7.7108e-04 eta: 16:41:50 time: 0.8051 data_time: 0.0258 memory: 16131 loss: 5.0629 loss_prob: 2.9067 loss_thr: 1.1562 loss_db: 1.0000 2022/10/25 19:46:28 - mmengine - INFO - Epoch(train) [52][60/63] lr: 7.7108e-04 eta: 16:41:35 time: 0.8018 data_time: 0.0074 memory: 16131 loss: 5.0817 loss_prob: 2.9268 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 19:46:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:46:35 - mmengine - INFO - Epoch(train) [53][5/63] lr: 7.8614e-04 eta: 16:41:35 time: 0.9582 data_time: 0.1956 memory: 16131 loss: 5.0953 loss_prob: 2.9445 loss_thr: 1.1509 loss_db: 1.0000 2022/10/25 19:46:39 - mmengine - INFO - Epoch(train) [53][10/63] lr: 7.8614e-04 eta: 16:41:05 time: 0.9923 data_time: 0.2018 memory: 16131 loss: 5.0735 loss_prob: 2.9205 loss_thr: 1.1530 loss_db: 1.0000 2022/10/25 19:46:42 - mmengine - INFO - Epoch(train) [53][15/63] lr: 7.8614e-04 eta: 16:41:05 time: 0.7936 data_time: 0.0109 memory: 16131 loss: 5.0720 loss_prob: 2.9185 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 19:46:50 - mmengine - INFO - Epoch(train) [53][20/63] lr: 7.8614e-04 eta: 16:41:54 time: 1.0918 data_time: 0.0065 memory: 16131 loss: 5.0791 loss_prob: 2.9249 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 19:46:54 - mmengine - INFO - Epoch(train) [53][25/63] lr: 7.8614e-04 eta: 16:41:54 time: 1.1247 data_time: 0.0270 memory: 16131 loss: 5.0806 loss_prob: 2.9253 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:46:57 - mmengine - INFO - Epoch(train) [53][30/63] lr: 7.8614e-04 eta: 16:41:20 time: 0.7148 data_time: 0.0368 memory: 16131 loss: 5.0679 loss_prob: 2.9167 loss_thr: 1.1512 loss_db: 1.0000 2022/10/25 19:46:59 - mmengine - INFO - Epoch(train) [53][35/63] lr: 7.8614e-04 eta: 16:41:20 time: 0.5643 data_time: 0.0166 memory: 16131 loss: 5.0509 loss_prob: 2.8966 loss_thr: 1.1543 loss_db: 1.0000 2022/10/25 19:47:06 - mmengine - INFO - Epoch(train) [53][40/63] lr: 7.8614e-04 eta: 16:41:41 time: 0.9676 data_time: 0.0053 memory: 16131 loss: 5.0428 loss_prob: 2.8850 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 19:47:13 - mmengine - INFO - Epoch(train) [53][45/63] lr: 7.8614e-04 eta: 16:41:41 time: 1.3876 data_time: 0.0091 memory: 16131 loss: 5.0344 loss_prob: 2.8738 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:47:17 - mmengine - INFO - Epoch(train) [53][50/63] lr: 7.8614e-04 eta: 16:42:13 time: 1.0151 data_time: 0.0218 memory: 16131 loss: 5.0331 loss_prob: 2.8725 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:47:19 - mmengine - INFO - Epoch(train) [53][55/63] lr: 7.8614e-04 eta: 16:42:13 time: 0.6105 data_time: 0.0256 memory: 16131 loss: 5.0509 loss_prob: 2.8966 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:47:23 - mmengine - INFO - Epoch(train) [53][60/63] lr: 7.8614e-04 eta: 16:41:16 time: 0.6090 data_time: 0.0124 memory: 16131 loss: 5.0749 loss_prob: 2.9185 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 19:47:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:47:33 - mmengine - INFO - Epoch(train) [54][5/63] lr: 8.0120e-04 eta: 16:41:16 time: 1.1392 data_time: 0.1848 memory: 16131 loss: 5.0750 loss_prob: 2.9194 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 19:47:36 - mmengine - INFO - Epoch(train) [54][10/63] lr: 8.0120e-04 eta: 16:40:59 time: 1.0509 data_time: 0.1987 memory: 16131 loss: 5.0740 loss_prob: 2.9184 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 19:47:40 - mmengine - INFO - Epoch(train) [54][15/63] lr: 8.0120e-04 eta: 16:40:59 time: 0.6500 data_time: 0.0183 memory: 16131 loss: 5.0587 loss_prob: 2.9039 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 19:47:42 - mmengine - INFO - Epoch(train) [54][20/63] lr: 8.0120e-04 eta: 16:40:04 time: 0.6112 data_time: 0.0063 memory: 16131 loss: 5.0390 loss_prob: 2.8777 loss_thr: 1.1613 loss_db: 1.0000 2022/10/25 19:47:45 - mmengine - INFO - Epoch(train) [54][25/63] lr: 8.0120e-04 eta: 16:40:04 time: 0.5544 data_time: 0.0214 memory: 16131 loss: 5.0274 loss_prob: 2.8676 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:47:48 - mmengine - INFO - Epoch(train) [54][30/63] lr: 8.0120e-04 eta: 16:39:08 time: 0.6096 data_time: 0.0329 memory: 16131 loss: 5.0252 loss_prob: 2.8685 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 19:47:51 - mmengine - INFO - Epoch(train) [54][35/63] lr: 8.0120e-04 eta: 16:39:08 time: 0.6080 data_time: 0.0243 memory: 16131 loss: 5.0471 loss_prob: 2.8893 loss_thr: 1.1578 loss_db: 1.0000 2022/10/25 19:47:55 - mmengine - INFO - Epoch(train) [54][40/63] lr: 8.0120e-04 eta: 16:38:28 time: 0.6827 data_time: 0.0118 memory: 16131 loss: 5.0724 loss_prob: 2.9141 loss_thr: 1.1583 loss_db: 1.0000 2022/10/25 19:47:58 - mmengine - INFO - Epoch(train) [54][45/63] lr: 8.0120e-04 eta: 16:38:28 time: 0.6865 data_time: 0.0074 memory: 16131 loss: 5.0725 loss_prob: 2.9125 loss_thr: 1.1600 loss_db: 1.0000 2022/10/25 19:48:02 - mmengine - INFO - Epoch(train) [54][50/63] lr: 8.0120e-04 eta: 16:37:42 time: 0.6500 data_time: 0.0169 memory: 16131 loss: 5.0581 loss_prob: 2.9032 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 19:48:07 - mmengine - INFO - Epoch(train) [54][55/63] lr: 8.0120e-04 eta: 16:37:42 time: 0.9173 data_time: 0.0246 memory: 16131 loss: 5.0590 loss_prob: 2.9064 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 19:48:11 - mmengine - INFO - Epoch(train) [54][60/63] lr: 8.0120e-04 eta: 16:37:56 time: 0.9366 data_time: 0.0142 memory: 16131 loss: 5.0549 loss_prob: 2.8991 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 19:48:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:48:19 - mmengine - INFO - Epoch(train) [55][5/63] lr: 8.1626e-04 eta: 16:37:56 time: 0.8503 data_time: 0.2314 memory: 16131 loss: 5.0357 loss_prob: 2.8785 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:48:22 - mmengine - INFO - Epoch(train) [55][10/63] lr: 8.1626e-04 eta: 16:37:14 time: 0.9297 data_time: 0.2302 memory: 16131 loss: 5.0274 loss_prob: 2.8700 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 19:48:26 - mmengine - INFO - Epoch(train) [55][15/63] lr: 8.1626e-04 eta: 16:37:14 time: 0.7882 data_time: 0.0051 memory: 16131 loss: 5.0201 loss_prob: 2.8654 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 19:48:31 - mmengine - INFO - Epoch(train) [55][20/63] lr: 8.1626e-04 eta: 16:37:16 time: 0.8793 data_time: 0.0084 memory: 16131 loss: 5.0193 loss_prob: 2.8653 loss_thr: 1.1540 loss_db: 1.0000 2022/10/25 19:48:34 - mmengine - INFO - Epoch(train) [55][25/63] lr: 8.1626e-04 eta: 16:37:16 time: 0.7460 data_time: 0.0473 memory: 16131 loss: 5.0174 loss_prob: 2.8602 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:48:38 - mmengine - INFO - Epoch(train) [55][30/63] lr: 8.1626e-04 eta: 16:36:55 time: 0.7656 data_time: 0.0453 memory: 16131 loss: 5.0081 loss_prob: 2.8543 loss_thr: 1.1539 loss_db: 1.0000 2022/10/25 19:48:42 - mmengine - INFO - Epoch(train) [55][35/63] lr: 8.1626e-04 eta: 16:36:55 time: 0.7870 data_time: 0.0077 memory: 16131 loss: 5.0176 loss_prob: 2.8646 loss_thr: 1.1530 loss_db: 1.0000 2022/10/25 19:48:46 - mmengine - INFO - Epoch(train) [55][40/63] lr: 8.1626e-04 eta: 16:36:33 time: 0.7629 data_time: 0.0068 memory: 16131 loss: 5.0392 loss_prob: 2.8806 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 19:48:49 - mmengine - INFO - Epoch(train) [55][45/63] lr: 8.1626e-04 eta: 16:36:33 time: 0.7611 data_time: 0.0051 memory: 16131 loss: 5.0380 loss_prob: 2.8792 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 19:48:53 - mmengine - INFO - Epoch(train) [55][50/63] lr: 8.1626e-04 eta: 16:36:01 time: 0.7157 data_time: 0.0251 memory: 16131 loss: 5.0300 loss_prob: 2.8781 loss_thr: 1.1519 loss_db: 1.0000 2022/10/25 19:48:59 - mmengine - INFO - Epoch(train) [55][55/63] lr: 8.1626e-04 eta: 16:36:01 time: 0.9468 data_time: 0.0282 memory: 16131 loss: 5.0362 loss_prob: 2.8815 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 19:49:02 - mmengine - INFO - Epoch(train) [55][60/63] lr: 8.1626e-04 eta: 16:36:01 time: 0.8681 data_time: 0.0129 memory: 16131 loss: 5.0288 loss_prob: 2.8702 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 19:49:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:49:10 - mmengine - INFO - Epoch(train) [56][5/63] lr: 8.3132e-04 eta: 16:36:01 time: 0.8980 data_time: 0.1782 memory: 16131 loss: 5.0226 loss_prob: 2.8643 loss_thr: 1.1583 loss_db: 1.0000 2022/10/25 19:49:15 - mmengine - INFO - Epoch(train) [56][10/63] lr: 8.3132e-04 eta: 16:36:09 time: 1.1711 data_time: 0.1747 memory: 16131 loss: 5.0118 loss_prob: 2.8546 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 19:49:21 - mmengine - INFO - Epoch(train) [56][15/63] lr: 8.3132e-04 eta: 16:36:09 time: 1.1700 data_time: 0.0126 memory: 16131 loss: 5.0038 loss_prob: 2.8472 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:49:26 - mmengine - INFO - Epoch(train) [56][20/63] lr: 8.3132e-04 eta: 16:37:01 time: 1.1163 data_time: 0.0123 memory: 16131 loss: 5.0015 loss_prob: 2.8461 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 19:49:30 - mmengine - INFO - Epoch(train) [56][25/63] lr: 8.3132e-04 eta: 16:37:01 time: 0.8648 data_time: 0.0120 memory: 16131 loss: 5.0007 loss_prob: 2.8453 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:49:33 - mmengine - INFO - Epoch(train) [56][30/63] lr: 8.3132e-04 eta: 16:36:24 time: 0.6914 data_time: 0.0283 memory: 16131 loss: 5.0020 loss_prob: 2.8460 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 19:49:37 - mmengine - INFO - Epoch(train) [56][35/63] lr: 8.3132e-04 eta: 16:36:24 time: 0.7033 data_time: 0.0220 memory: 16131 loss: 5.0110 loss_prob: 2.8582 loss_thr: 1.1528 loss_db: 1.0000 2022/10/25 19:49:42 - mmengine - INFO - Epoch(train) [56][40/63] lr: 8.3132e-04 eta: 16:36:24 time: 0.8695 data_time: 0.0111 memory: 16131 loss: 5.0182 loss_prob: 2.8635 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 19:49:44 - mmengine - INFO - Epoch(train) [56][45/63] lr: 8.3132e-04 eta: 16:36:24 time: 0.7350 data_time: 0.0124 memory: 16131 loss: 5.0159 loss_prob: 2.8554 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 19:49:47 - mmengine - INFO - Epoch(train) [56][50/63] lr: 8.3132e-04 eta: 16:35:20 time: 0.5565 data_time: 0.0155 memory: 16131 loss: 5.0103 loss_prob: 2.8484 loss_thr: 1.1619 loss_db: 1.0000 2022/10/25 19:49:50 - mmengine - INFO - Epoch(train) [56][55/63] lr: 8.3132e-04 eta: 16:35:20 time: 0.5628 data_time: 0.0220 memory: 16131 loss: 4.9989 loss_prob: 2.8444 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:49:54 - mmengine - INFO - Epoch(train) [56][60/63] lr: 8.3132e-04 eta: 16:34:35 time: 0.6483 data_time: 0.0162 memory: 16131 loss: 4.9946 loss_prob: 2.8432 loss_thr: 1.1514 loss_db: 0.9999 2022/10/25 19:49:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:50:00 - mmengine - INFO - Epoch(train) [57][5/63] lr: 8.4638e-04 eta: 16:34:35 time: 0.8021 data_time: 0.2359 memory: 16131 loss: 4.9988 loss_prob: 2.8432 loss_thr: 1.1557 loss_db: 0.9999 2022/10/25 19:50:03 - mmengine - INFO - Epoch(train) [57][10/63] lr: 8.4638e-04 eta: 16:33:24 time: 0.7811 data_time: 0.2244 memory: 16131 loss: 5.0051 loss_prob: 2.8517 loss_thr: 1.1534 loss_db: 1.0000 2022/10/25 19:50:06 - mmengine - INFO - Epoch(train) [57][15/63] lr: 8.4638e-04 eta: 16:33:24 time: 0.5625 data_time: 0.0099 memory: 16131 loss: 5.0084 loss_prob: 2.8551 loss_thr: 1.1533 loss_db: 1.0000 2022/10/25 19:50:08 - mmengine - INFO - Epoch(train) [57][20/63] lr: 8.4638e-04 eta: 16:32:16 time: 0.5334 data_time: 0.0052 memory: 16131 loss: 5.0178 loss_prob: 2.8615 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:50:11 - mmengine - INFO - Epoch(train) [57][25/63] lr: 8.4638e-04 eta: 16:32:16 time: 0.5417 data_time: 0.0252 memory: 16131 loss: 5.0176 loss_prob: 2.8641 loss_thr: 1.1536 loss_db: 1.0000 2022/10/25 19:50:14 - mmengine - INFO - Epoch(train) [57][30/63] lr: 8.4638e-04 eta: 16:31:13 time: 0.5550 data_time: 0.0340 memory: 16131 loss: 5.0159 loss_prob: 2.8592 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:50:17 - mmengine - INFO - Epoch(train) [57][35/63] lr: 8.4638e-04 eta: 16:31:13 time: 0.6273 data_time: 0.0205 memory: 16131 loss: 5.0266 loss_prob: 2.8585 loss_thr: 1.1681 loss_db: 0.9999 2022/10/25 19:50:20 - mmengine - INFO - Epoch(train) [57][40/63] lr: 8.4638e-04 eta: 16:30:16 time: 0.5873 data_time: 0.0119 memory: 16131 loss: 5.0191 loss_prob: 2.8536 loss_thr: 1.1656 loss_db: 0.9999 2022/10/25 19:50:23 - mmengine - INFO - Epoch(train) [57][45/63] lr: 8.4638e-04 eta: 16:30:16 time: 0.6033 data_time: 0.0083 memory: 16131 loss: 5.0101 loss_prob: 2.8550 loss_thr: 1.1552 loss_db: 1.0000 2022/10/25 19:50:26 - mmengine - INFO - Epoch(train) [57][50/63] lr: 8.4638e-04 eta: 16:29:31 time: 0.6429 data_time: 0.0195 memory: 16131 loss: 5.0136 loss_prob: 2.8601 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 19:50:29 - mmengine - INFO - Epoch(train) [57][55/63] lr: 8.4638e-04 eta: 16:29:31 time: 0.5386 data_time: 0.0209 memory: 16131 loss: 5.0212 loss_prob: 2.8653 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 19:50:33 - mmengine - INFO - Epoch(train) [57][60/63] lr: 8.4638e-04 eta: 16:28:57 time: 0.6929 data_time: 0.0107 memory: 16131 loss: 5.0263 loss_prob: 2.8712 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 19:50:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:50:41 - mmengine - INFO - Epoch(train) [58][5/63] lr: 8.6144e-04 eta: 16:28:57 time: 0.8928 data_time: 0.1822 memory: 16131 loss: 5.0825 loss_prob: 2.9143 loss_thr: 1.1683 loss_db: 0.9999 2022/10/25 19:50:44 - mmengine - INFO - Epoch(train) [58][10/63] lr: 8.6144e-04 eta: 16:28:16 time: 0.9227 data_time: 0.1892 memory: 16131 loss: 5.1249 loss_prob: 2.9529 loss_thr: 1.1724 loss_db: 0.9996 2022/10/25 19:50:48 - mmengine - INFO - Epoch(train) [58][15/63] lr: 8.6144e-04 eta: 16:28:16 time: 0.7516 data_time: 0.0145 memory: 16131 loss: 5.0782 loss_prob: 2.9122 loss_thr: 1.1664 loss_db: 0.9996 2022/10/25 19:50:51 - mmengine - INFO - Epoch(train) [58][20/63] lr: 8.6144e-04 eta: 16:27:46 time: 0.7134 data_time: 0.0058 memory: 16131 loss: 5.0342 loss_prob: 2.8743 loss_thr: 1.1601 loss_db: 0.9999 2022/10/25 19:50:55 - mmengine - INFO - Epoch(train) [58][25/63] lr: 8.6144e-04 eta: 16:27:46 time: 0.7260 data_time: 0.0229 memory: 16131 loss: 5.0232 loss_prob: 2.8680 loss_thr: 1.1552 loss_db: 0.9999 2022/10/25 19:51:01 - mmengine - INFO - Epoch(train) [58][30/63] lr: 8.6144e-04 eta: 16:28:09 time: 0.9796 data_time: 0.0232 memory: 16131 loss: 5.0148 loss_prob: 2.8574 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 19:51:05 - mmengine - INFO - Epoch(train) [58][35/63] lr: 8.6144e-04 eta: 16:28:09 time: 0.9964 data_time: 0.0192 memory: 16131 loss: 5.0080 loss_prob: 2.8493 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:51:08 - mmengine - INFO - Epoch(train) [58][40/63] lr: 8.6144e-04 eta: 16:27:46 time: 0.7513 data_time: 0.0226 memory: 16131 loss: 4.9984 loss_prob: 2.8429 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:51:11 - mmengine - INFO - Epoch(train) [58][45/63] lr: 8.6144e-04 eta: 16:27:46 time: 0.5979 data_time: 0.0098 memory: 16131 loss: 4.9921 loss_prob: 2.8374 loss_thr: 1.1548 loss_db: 0.9999 2022/10/25 19:51:15 - mmengine - INFO - Epoch(train) [58][50/63] lr: 8.6144e-04 eta: 16:27:15 time: 0.7064 data_time: 0.0169 memory: 16131 loss: 4.9860 loss_prob: 2.8336 loss_thr: 1.1524 loss_db: 0.9999 2022/10/25 19:51:18 - mmengine - INFO - Epoch(train) [58][55/63] lr: 8.6144e-04 eta: 16:27:15 time: 0.6688 data_time: 0.0195 memory: 16131 loss: 4.9875 loss_prob: 2.8331 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 19:51:23 - mmengine - INFO - Epoch(train) [58][60/63] lr: 8.6144e-04 eta: 16:26:50 time: 0.7361 data_time: 0.0152 memory: 16131 loss: 4.9914 loss_prob: 2.8329 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:51:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:51:33 - mmengine - INFO - Epoch(train) [59][5/63] lr: 8.7650e-04 eta: 16:26:50 time: 1.3141 data_time: 0.2067 memory: 16131 loss: 4.9891 loss_prob: 2.8337 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 19:51:36 - mmengine - INFO - Epoch(train) [59][10/63] lr: 8.7650e-04 eta: 16:26:42 time: 1.0876 data_time: 0.2052 memory: 16131 loss: 4.9928 loss_prob: 2.8365 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:51:39 - mmengine - INFO - Epoch(train) [59][15/63] lr: 8.7650e-04 eta: 16:26:42 time: 0.5979 data_time: 0.0056 memory: 16131 loss: 4.9977 loss_prob: 2.8393 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:51:42 - mmengine - INFO - Epoch(train) [59][20/63] lr: 8.7650e-04 eta: 16:25:47 time: 0.5845 data_time: 0.0052 memory: 16131 loss: 4.9932 loss_prob: 2.8374 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 19:51:45 - mmengine - INFO - Epoch(train) [59][25/63] lr: 8.7650e-04 eta: 16:25:47 time: 0.5583 data_time: 0.0264 memory: 16131 loss: 4.9929 loss_prob: 2.8380 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 19:51:49 - mmengine - INFO - Epoch(train) [59][30/63] lr: 8.7650e-04 eta: 16:25:23 time: 0.7393 data_time: 0.0344 memory: 16131 loss: 4.9980 loss_prob: 2.8401 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 19:51:52 - mmengine - INFO - Epoch(train) [59][35/63] lr: 8.7650e-04 eta: 16:25:23 time: 0.7305 data_time: 0.0150 memory: 16131 loss: 4.9950 loss_prob: 2.8388 loss_thr: 1.1562 loss_db: 1.0000 2022/10/25 19:51:55 - mmengine - INFO - Epoch(train) [59][40/63] lr: 8.7650e-04 eta: 16:24:24 time: 0.5611 data_time: 0.0067 memory: 16131 loss: 4.9931 loss_prob: 2.8390 loss_thr: 1.1541 loss_db: 1.0000 2022/10/25 19:51:58 - mmengine - INFO - Epoch(train) [59][45/63] lr: 8.7650e-04 eta: 16:24:24 time: 0.5574 data_time: 0.0057 memory: 16131 loss: 4.9996 loss_prob: 2.8408 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:52:02 - mmengine - INFO - Epoch(train) [59][50/63] lr: 8.7650e-04 eta: 16:23:53 time: 0.7052 data_time: 0.0198 memory: 16131 loss: 4.9965 loss_prob: 2.8402 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:52:08 - mmengine - INFO - Epoch(train) [59][55/63] lr: 8.7650e-04 eta: 16:23:53 time: 0.9918 data_time: 0.0211 memory: 16131 loss: 4.9903 loss_prob: 2.8373 loss_thr: 1.1531 loss_db: 1.0000 2022/10/25 19:52:13 - mmengine - INFO - Epoch(train) [59][60/63] lr: 8.7650e-04 eta: 16:24:38 time: 1.0945 data_time: 0.0076 memory: 16131 loss: 4.9880 loss_prob: 2.8349 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 19:52:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:52:22 - mmengine - INFO - Epoch(train) [60][5/63] lr: 8.9156e-04 eta: 16:24:38 time: 1.0229 data_time: 0.1934 memory: 16131 loss: 4.9944 loss_prob: 2.8337 loss_thr: 1.1608 loss_db: 1.0000 2022/10/25 19:52:26 - mmengine - INFO - Epoch(train) [60][10/63] lr: 8.9156e-04 eta: 16:24:30 time: 1.0832 data_time: 0.2037 memory: 16131 loss: 4.9925 loss_prob: 2.8318 loss_thr: 1.1607 loss_db: 1.0000 2022/10/25 19:52:28 - mmengine - INFO - Epoch(train) [60][15/63] lr: 8.9156e-04 eta: 16:24:30 time: 0.6361 data_time: 0.0161 memory: 16131 loss: 4.9918 loss_prob: 2.8333 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:52:33 - mmengine - INFO - Epoch(train) [60][20/63] lr: 8.9156e-04 eta: 16:24:08 time: 0.7527 data_time: 0.0047 memory: 16131 loss: 5.0355 loss_prob: 2.8674 loss_thr: 1.1682 loss_db: 0.9999 2022/10/25 19:52:36 - mmengine - INFO - Epoch(train) [60][25/63] lr: 8.9156e-04 eta: 16:24:08 time: 0.7980 data_time: 0.0219 memory: 16131 loss: 5.0526 loss_prob: 2.8788 loss_thr: 1.1739 loss_db: 0.9999 2022/10/25 19:52:40 - mmengine - INFO - Epoch(train) [60][30/63] lr: 8.9156e-04 eta: 16:23:45 time: 0.7430 data_time: 0.0234 memory: 16131 loss: 5.0172 loss_prob: 2.8555 loss_thr: 1.1617 loss_db: 0.9999 2022/10/25 19:52:44 - mmengine - INFO - Epoch(train) [60][35/63] lr: 8.9156e-04 eta: 16:23:45 time: 0.7414 data_time: 0.0153 memory: 16131 loss: 5.1237 loss_prob: 2.9370 loss_thr: 1.1874 loss_db: 0.9993 2022/10/25 19:52:47 - mmengine - INFO - Epoch(train) [60][40/63] lr: 8.9156e-04 eta: 16:23:10 time: 0.6781 data_time: 0.0145 memory: 16131 loss: 5.2318 loss_prob: 3.0188 loss_thr: 1.2137 loss_db: 0.9993 2022/10/25 19:52:51 - mmengine - INFO - Epoch(train) [60][45/63] lr: 8.9156e-04 eta: 16:23:10 time: 0.7236 data_time: 0.0073 memory: 16131 loss: 5.1995 loss_prob: 3.0050 loss_thr: 1.1946 loss_db: 0.9999 2022/10/25 19:52:55 - mmengine - INFO - Epoch(train) [60][50/63] lr: 8.9156e-04 eta: 16:22:56 time: 0.7948 data_time: 0.0190 memory: 16131 loss: 5.1416 loss_prob: 2.9687 loss_thr: 1.1729 loss_db: 1.0000 2022/10/25 19:53:00 - mmengine - INFO - Epoch(train) [60][55/63] lr: 8.9156e-04 eta: 16:22:56 time: 0.8712 data_time: 0.0268 memory: 16131 loss: 5.1416 loss_prob: 2.9595 loss_thr: 1.1825 loss_db: 0.9996 2022/10/25 19:53:02 - mmengine - INFO - Epoch(train) [60][60/63] lr: 8.9156e-04 eta: 16:22:29 time: 0.7198 data_time: 0.0176 memory: 16131 loss: 5.1314 loss_prob: 2.9435 loss_thr: 1.1883 loss_db: 0.9996 2022/10/25 19:53:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:53:04 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/25 19:53:10 - mmengine - INFO - Epoch(val) [60][5/32] eta: 16:22:29 time: 0.4264 data_time: 0.0766 memory: 16131 2022/10/25 19:53:12 - mmengine - INFO - Epoch(val) [60][10/32] eta: 0:00:10 time: 0.4601 data_time: 0.0803 memory: 15724 2022/10/25 19:53:14 - mmengine - INFO - Epoch(val) [60][15/32] eta: 0:00:10 time: 0.4142 data_time: 0.0395 memory: 15724 2022/10/25 19:53:16 - mmengine - INFO - Epoch(val) [60][20/32] eta: 0:00:05 time: 0.4374 data_time: 0.0637 memory: 15724 2022/10/25 19:53:18 - mmengine - INFO - Epoch(val) [60][25/32] eta: 0:00:05 time: 0.4157 data_time: 0.0421 memory: 15724 2022/10/25 19:53:20 - mmengine - INFO - Epoch(val) [60][30/32] eta: 0:00:00 time: 0.3973 data_time: 0.0221 memory: 15724 2022/10/25 19:53:21 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 19:53:21 - mmengine - INFO - Epoch(val) [60][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/10/25 19:53:30 - mmengine - INFO - Epoch(train) [61][5/63] lr: 9.0662e-04 eta: 0:00:00 time: 1.1640 data_time: 0.2080 memory: 16131 loss: 5.0646 loss_prob: 2.8908 loss_thr: 1.1743 loss_db: 0.9995 2022/10/25 19:53:35 - mmengine - INFO - Epoch(train) [61][10/63] lr: 9.0662e-04 eta: 16:23:15 time: 1.3688 data_time: 0.2131 memory: 16131 loss: 5.0307 loss_prob: 2.8655 loss_thr: 1.1652 loss_db: 1.0000 2022/10/25 19:53:39 - mmengine - INFO - Epoch(train) [61][15/63] lr: 9.0662e-04 eta: 16:23:15 time: 0.8764 data_time: 0.0098 memory: 16131 loss: 5.0195 loss_prob: 2.8542 loss_thr: 1.1654 loss_db: 1.0000 2022/10/25 19:53:44 - mmengine - INFO - Epoch(train) [61][20/63] lr: 9.0662e-04 eta: 16:23:26 time: 0.9226 data_time: 0.0049 memory: 16131 loss: 5.0052 loss_prob: 2.8434 loss_thr: 1.1619 loss_db: 1.0000 2022/10/25 19:53:47 - mmengine - INFO - Epoch(train) [61][25/63] lr: 9.0662e-04 eta: 16:23:26 time: 0.8440 data_time: 0.0219 memory: 16131 loss: 4.9952 loss_prob: 2.8367 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 19:53:52 - mmengine - INFO - Epoch(train) [61][30/63] lr: 9.0662e-04 eta: 16:23:21 time: 0.8380 data_time: 0.0312 memory: 16131 loss: 4.9964 loss_prob: 2.8383 loss_thr: 1.1582 loss_db: 1.0000 2022/10/25 19:53:55 - mmengine - INFO - Epoch(train) [61][35/63] lr: 9.0662e-04 eta: 16:23:21 time: 0.7578 data_time: 0.0192 memory: 16131 loss: 5.0081 loss_prob: 2.8460 loss_thr: 1.1621 loss_db: 1.0000 2022/10/25 19:53:59 - mmengine - INFO - Epoch(train) [61][40/63] lr: 9.0662e-04 eta: 16:22:51 time: 0.7075 data_time: 0.0096 memory: 16131 loss: 5.0016 loss_prob: 2.8417 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:54:02 - mmengine - INFO - Epoch(train) [61][45/63] lr: 9.0662e-04 eta: 16:22:51 time: 0.7380 data_time: 0.0046 memory: 16131 loss: 4.9955 loss_prob: 2.8343 loss_thr: 1.1612 loss_db: 1.0000 2022/10/25 19:54:07 - mmengine - INFO - Epoch(train) [61][50/63] lr: 9.0662e-04 eta: 16:22:28 time: 0.7427 data_time: 0.0165 memory: 16131 loss: 4.9993 loss_prob: 2.8326 loss_thr: 1.1667 loss_db: 1.0000 2022/10/25 19:54:11 - mmengine - INFO - Epoch(train) [61][55/63] lr: 9.0662e-04 eta: 16:22:28 time: 0.8922 data_time: 0.0210 memory: 16131 loss: 4.9964 loss_prob: 2.8312 loss_thr: 1.1652 loss_db: 1.0000 2022/10/25 19:54:14 - mmengine - INFO - Epoch(train) [61][60/63] lr: 9.0662e-04 eta: 16:21:55 time: 0.6873 data_time: 0.0118 memory: 16131 loss: 4.9868 loss_prob: 2.8302 loss_thr: 1.1566 loss_db: 1.0000 2022/10/25 19:54:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:54:22 - mmengine - INFO - Epoch(train) [62][5/63] lr: 9.2168e-04 eta: 16:21:55 time: 0.9406 data_time: 0.1649 memory: 16131 loss: 4.9850 loss_prob: 2.8336 loss_thr: 1.1515 loss_db: 1.0000 2022/10/25 19:54:25 - mmengine - INFO - Epoch(train) [62][10/63] lr: 9.2168e-04 eta: 16:21:32 time: 0.9992 data_time: 0.1745 memory: 16131 loss: 4.9947 loss_prob: 2.8383 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:54:28 - mmengine - INFO - Epoch(train) [62][15/63] lr: 9.2168e-04 eta: 16:21:32 time: 0.5952 data_time: 0.0147 memory: 16131 loss: 5.0038 loss_prob: 2.8440 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:54:32 - mmengine - INFO - Epoch(train) [62][20/63] lr: 9.2168e-04 eta: 16:20:50 time: 0.6395 data_time: 0.0066 memory: 16131 loss: 4.9986 loss_prob: 2.8439 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 19:54:36 - mmengine - INFO - Epoch(train) [62][25/63] lr: 9.2168e-04 eta: 16:20:50 time: 0.7691 data_time: 0.0094 memory: 16131 loss: 4.9978 loss_prob: 2.8433 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 19:54:39 - mmengine - INFO - Epoch(train) [62][30/63] lr: 9.2168e-04 eta: 16:20:16 time: 0.6817 data_time: 0.0398 memory: 16131 loss: 4.9972 loss_prob: 2.8402 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:54:41 - mmengine - INFO - Epoch(train) [62][35/63] lr: 9.2168e-04 eta: 16:20:16 time: 0.5700 data_time: 0.0379 memory: 16131 loss: 4.9962 loss_prob: 2.8380 loss_thr: 1.1582 loss_db: 1.0000 2022/10/25 19:54:45 - mmengine - INFO - Epoch(train) [62][40/63] lr: 9.2168e-04 eta: 16:19:27 time: 0.5970 data_time: 0.0062 memory: 16131 loss: 4.9981 loss_prob: 2.8376 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 19:54:48 - mmengine - INFO - Epoch(train) [62][45/63] lr: 9.2168e-04 eta: 16:19:27 time: 0.6957 data_time: 0.0071 memory: 16131 loss: 4.9913 loss_prob: 2.8342 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 19:54:51 - mmengine - INFO - Epoch(train) [62][50/63] lr: 9.2168e-04 eta: 16:18:51 time: 0.6693 data_time: 0.0187 memory: 16131 loss: 4.9888 loss_prob: 2.8340 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 19:54:55 - mmengine - INFO - Epoch(train) [62][55/63] lr: 9.2168e-04 eta: 16:18:51 time: 0.6343 data_time: 0.0343 memory: 16131 loss: 4.9888 loss_prob: 2.8342 loss_thr: 1.1546 loss_db: 1.0000 2022/10/25 19:54:58 - mmengine - INFO - Epoch(train) [62][60/63] lr: 9.2168e-04 eta: 16:18:13 time: 0.6601 data_time: 0.0234 memory: 16131 loss: 4.9864 loss_prob: 2.8338 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 19:54:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:55:03 - mmengine - INFO - Epoch(train) [63][5/63] lr: 9.3674e-04 eta: 16:18:13 time: 0.6721 data_time: 0.1449 memory: 16131 loss: 4.9926 loss_prob: 2.8355 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 19:55:06 - mmengine - INFO - Epoch(train) [63][10/63] lr: 9.3674e-04 eta: 16:16:51 time: 0.6702 data_time: 0.1510 memory: 16131 loss: 4.9923 loss_prob: 2.8349 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:55:09 - mmengine - INFO - Epoch(train) [63][15/63] lr: 9.3674e-04 eta: 16:16:51 time: 0.5350 data_time: 0.0152 memory: 16131 loss: 4.9927 loss_prob: 2.8332 loss_thr: 1.1595 loss_db: 1.0000 2022/10/25 19:55:11 - mmengine - INFO - Epoch(train) [63][20/63] lr: 9.3674e-04 eta: 16:15:51 time: 0.5336 data_time: 0.0112 memory: 16131 loss: 4.9875 loss_prob: 2.8315 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 19:55:14 - mmengine - INFO - Epoch(train) [63][25/63] lr: 9.3674e-04 eta: 16:15:51 time: 0.5036 data_time: 0.0134 memory: 16131 loss: 4.9846 loss_prob: 2.8311 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 19:55:16 - mmengine - INFO - Epoch(train) [63][30/63] lr: 9.3674e-04 eta: 16:14:48 time: 0.5203 data_time: 0.0227 memory: 16131 loss: 4.9885 loss_prob: 2.8331 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:55:19 - mmengine - INFO - Epoch(train) [63][35/63] lr: 9.3674e-04 eta: 16:14:48 time: 0.5437 data_time: 0.0227 memory: 16131 loss: 4.9946 loss_prob: 2.8342 loss_thr: 1.1603 loss_db: 1.0000 2022/10/25 19:55:23 - mmengine - INFO - Epoch(train) [63][40/63] lr: 9.3674e-04 eta: 16:14:15 time: 0.6790 data_time: 0.0212 memory: 16131 loss: 4.9942 loss_prob: 2.8334 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:55:27 - mmengine - INFO - Epoch(train) [63][45/63] lr: 9.3674e-04 eta: 16:14:15 time: 0.8144 data_time: 0.0173 memory: 16131 loss: 4.9913 loss_prob: 2.8316 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:55:30 - mmengine - INFO - Epoch(train) [63][50/63] lr: 9.3674e-04 eta: 16:13:38 time: 0.6547 data_time: 0.0102 memory: 16131 loss: 4.9903 loss_prob: 2.8316 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:55:32 - mmengine - INFO - Epoch(train) [63][55/63] lr: 9.3674e-04 eta: 16:13:38 time: 0.4938 data_time: 0.0150 memory: 16131 loss: 4.9930 loss_prob: 2.8325 loss_thr: 1.1606 loss_db: 1.0000 2022/10/25 19:55:35 - mmengine - INFO - Epoch(train) [63][60/63] lr: 9.3674e-04 eta: 16:12:33 time: 0.4988 data_time: 0.0163 memory: 16131 loss: 4.9957 loss_prob: 2.8350 loss_thr: 1.1607 loss_db: 1.0000 2022/10/25 19:55:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:55:41 - mmengine - INFO - Epoch(train) [64][5/63] lr: 9.5180e-04 eta: 16:12:33 time: 0.6827 data_time: 0.2017 memory: 16131 loss: 4.9895 loss_prob: 2.8332 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 19:55:43 - mmengine - INFO - Epoch(train) [64][10/63] lr: 9.5180e-04 eta: 16:11:21 time: 0.7197 data_time: 0.2029 memory: 16131 loss: 4.9996 loss_prob: 2.8368 loss_thr: 1.1628 loss_db: 1.0000 2022/10/25 19:55:46 - mmengine - INFO - Epoch(train) [64][15/63] lr: 9.5180e-04 eta: 16:11:21 time: 0.5336 data_time: 0.0091 memory: 16131 loss: 5.0020 loss_prob: 2.8373 loss_thr: 1.1647 loss_db: 1.0000 2022/10/25 19:55:48 - mmengine - INFO - Epoch(train) [64][20/63] lr: 9.5180e-04 eta: 16:10:22 time: 0.5304 data_time: 0.0071 memory: 16131 loss: 4.9948 loss_prob: 2.8355 loss_thr: 1.1593 loss_db: 1.0000 2022/10/25 19:55:53 - mmengine - INFO - Epoch(train) [64][25/63] lr: 9.5180e-04 eta: 16:10:22 time: 0.6923 data_time: 0.0350 memory: 16131 loss: 4.9891 loss_prob: 2.8333 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 19:55:57 - mmengine - INFO - Epoch(train) [64][30/63] lr: 9.5180e-04 eta: 16:10:26 time: 0.8837 data_time: 0.0375 memory: 16131 loss: 4.9840 loss_prob: 2.8292 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 19:55:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:56:00 - mmengine - INFO - Epoch(train) [64][35/63] lr: 9.5180e-04 eta: 16:10:26 time: 0.7001 data_time: 0.0068 memory: 16131 loss: 4.9841 loss_prob: 2.8274 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:56:04 - mmengine - INFO - Epoch(train) [64][40/63] lr: 9.5180e-04 eta: 16:09:55 time: 0.6845 data_time: 0.0059 memory: 16131 loss: 4.9826 loss_prob: 2.8269 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 19:56:08 - mmengine - INFO - Epoch(train) [64][45/63] lr: 9.5180e-04 eta: 16:09:55 time: 0.8099 data_time: 0.0058 memory: 16131 loss: 4.9865 loss_prob: 2.8290 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 19:56:11 - mmengine - INFO - Epoch(train) [64][50/63] lr: 9.5180e-04 eta: 16:09:24 time: 0.6819 data_time: 0.0193 memory: 16131 loss: 4.9937 loss_prob: 2.8333 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 19:56:14 - mmengine - INFO - Epoch(train) [64][55/63] lr: 9.5180e-04 eta: 16:09:24 time: 0.6165 data_time: 0.0203 memory: 16131 loss: 4.9934 loss_prob: 2.8342 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 19:56:17 - mmengine - INFO - Epoch(train) [64][60/63] lr: 9.5180e-04 eta: 16:08:37 time: 0.5932 data_time: 0.0055 memory: 16131 loss: 4.9857 loss_prob: 2.8325 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 19:56:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:56:27 - mmengine - INFO - Epoch(train) [65][5/63] lr: 9.6686e-04 eta: 16:08:37 time: 1.0980 data_time: 0.2141 memory: 16131 loss: 4.9891 loss_prob: 2.8326 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 19:56:29 - mmengine - INFO - Epoch(train) [65][10/63] lr: 9.6686e-04 eta: 16:08:40 time: 1.1316 data_time: 0.2146 memory: 16131 loss: 4.9870 loss_prob: 2.8273 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 19:56:33 - mmengine - INFO - Epoch(train) [65][15/63] lr: 9.6686e-04 eta: 16:08:40 time: 0.6327 data_time: 0.0063 memory: 16131 loss: 4.9880 loss_prob: 2.8254 loss_thr: 1.1627 loss_db: 1.0000 2022/10/25 19:56:37 - mmengine - INFO - Epoch(train) [65][20/63] lr: 9.6686e-04 eta: 16:08:28 time: 0.7893 data_time: 0.0043 memory: 16131 loss: 4.9867 loss_prob: 2.8279 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:56:42 - mmengine - INFO - Epoch(train) [65][25/63] lr: 9.6686e-04 eta: 16:08:28 time: 0.9233 data_time: 0.0253 memory: 16131 loss: 4.9864 loss_prob: 2.8285 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 19:56:46 - mmengine - INFO - Epoch(train) [65][30/63] lr: 9.6686e-04 eta: 16:08:30 time: 0.8721 data_time: 0.0331 memory: 16131 loss: 4.9802 loss_prob: 2.8280 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 19:56:51 - mmengine - INFO - Epoch(train) [65][35/63] lr: 9.6686e-04 eta: 16:08:30 time: 0.8355 data_time: 0.0146 memory: 16131 loss: 4.9796 loss_prob: 2.8270 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 19:56:58 - mmengine - INFO - Epoch(train) [65][40/63] lr: 9.6686e-04 eta: 16:09:25 time: 1.1703 data_time: 0.0072 memory: 16131 loss: 4.9809 loss_prob: 2.8266 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 19:57:01 - mmengine - INFO - Epoch(train) [65][45/63] lr: 9.6686e-04 eta: 16:09:25 time: 1.0029 data_time: 0.0048 memory: 16131 loss: 4.9851 loss_prob: 2.8296 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 19:57:04 - mmengine - INFO - Epoch(train) [65][50/63] lr: 9.6686e-04 eta: 16:08:35 time: 0.5734 data_time: 0.0249 memory: 16131 loss: 4.9888 loss_prob: 2.8295 loss_thr: 1.1594 loss_db: 1.0000 2022/10/25 19:57:06 - mmengine - INFO - Epoch(train) [65][55/63] lr: 9.6686e-04 eta: 16:08:35 time: 0.5523 data_time: 0.0256 memory: 16131 loss: 4.9884 loss_prob: 2.8269 loss_thr: 1.1614 loss_db: 1.0000 2022/10/25 19:57:09 - mmengine - INFO - Epoch(train) [65][60/63] lr: 9.6686e-04 eta: 16:07:42 time: 0.5597 data_time: 0.0057 memory: 16131 loss: 4.9901 loss_prob: 2.8274 loss_thr: 1.1627 loss_db: 1.0000 2022/10/25 19:57:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:57:18 - mmengine - INFO - Epoch(train) [66][5/63] lr: 9.8192e-04 eta: 16:07:42 time: 0.9575 data_time: 0.1742 memory: 16131 loss: 4.9917 loss_prob: 2.8263 loss_thr: 1.1654 loss_db: 1.0000 2022/10/25 19:57:20 - mmengine - INFO - Epoch(train) [66][10/63] lr: 9.8192e-04 eta: 16:07:10 time: 0.9312 data_time: 0.1755 memory: 16131 loss: 4.9810 loss_prob: 2.8250 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 19:57:23 - mmengine - INFO - Epoch(train) [66][15/63] lr: 9.8192e-04 eta: 16:07:10 time: 0.5001 data_time: 0.0090 memory: 16131 loss: 4.9782 loss_prob: 2.8264 loss_thr: 1.1518 loss_db: 1.0000 2022/10/25 19:57:25 - mmengine - INFO - Epoch(train) [66][20/63] lr: 9.8192e-04 eta: 16:06:10 time: 0.5129 data_time: 0.0073 memory: 16131 loss: 4.9797 loss_prob: 2.8286 loss_thr: 1.1511 loss_db: 1.0000 2022/10/25 19:57:28 - mmengine - INFO - Epoch(train) [66][25/63] lr: 9.8192e-04 eta: 16:06:10 time: 0.5888 data_time: 0.0248 memory: 16131 loss: 4.9798 loss_prob: 2.8289 loss_thr: 1.1509 loss_db: 1.0000 2022/10/25 19:57:31 - mmengine - INFO - Epoch(train) [66][30/63] lr: 9.8192e-04 eta: 16:05:26 time: 0.6059 data_time: 0.0404 memory: 16131 loss: 4.9782 loss_prob: 2.8273 loss_thr: 1.1510 loss_db: 1.0000 2022/10/25 19:57:35 - mmengine - INFO - Epoch(train) [66][35/63] lr: 9.8192e-04 eta: 16:05:26 time: 0.6718 data_time: 0.0214 memory: 16131 loss: 4.9822 loss_prob: 2.8250 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:57:40 - mmengine - INFO - Epoch(train) [66][40/63] lr: 9.8192e-04 eta: 16:05:37 time: 0.9198 data_time: 0.0117 memory: 16131 loss: 4.9880 loss_prob: 2.8261 loss_thr: 1.1620 loss_db: 1.0000 2022/10/25 19:57:47 - mmengine - INFO - Epoch(train) [66][45/63] lr: 9.8192e-04 eta: 16:05:37 time: 1.1383 data_time: 0.0104 memory: 16131 loss: 4.9873 loss_prob: 2.8265 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 19:57:50 - mmengine - INFO - Epoch(train) [66][50/63] lr: 9.8192e-04 eta: 16:05:50 time: 0.9295 data_time: 0.0167 memory: 16131 loss: 4.9814 loss_prob: 2.8247 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 19:57:54 - mmengine - INFO - Epoch(train) [66][55/63] lr: 9.8192e-04 eta: 16:05:50 time: 0.7333 data_time: 0.0206 memory: 16131 loss: 4.9764 loss_prob: 2.8237 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 19:57:58 - mmengine - INFO - Epoch(train) [66][60/63] lr: 9.8192e-04 eta: 16:05:46 time: 0.8345 data_time: 0.0113 memory: 16131 loss: 4.9717 loss_prob: 2.8224 loss_thr: 1.1493 loss_db: 1.0000 2022/10/25 19:57:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:58:05 - mmengine - INFO - Epoch(train) [67][5/63] lr: 9.9698e-04 eta: 16:05:46 time: 0.8307 data_time: 0.1977 memory: 16131 loss: 4.9791 loss_prob: 2.8239 loss_thr: 1.1552 loss_db: 1.0000 2022/10/25 19:58:08 - mmengine - INFO - Epoch(train) [67][10/63] lr: 9.9698e-04 eta: 16:05:09 time: 0.9044 data_time: 0.1941 memory: 16131 loss: 4.9804 loss_prob: 2.8222 loss_thr: 1.1583 loss_db: 1.0000 2022/10/25 19:58:11 - mmengine - INFO - Epoch(train) [67][15/63] lr: 9.9698e-04 eta: 16:05:09 time: 0.5747 data_time: 0.0105 memory: 16131 loss: 4.9810 loss_prob: 2.8222 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 19:58:14 - mmengine - INFO - Epoch(train) [67][20/63] lr: 9.9698e-04 eta: 16:04:10 time: 0.5131 data_time: 0.0112 memory: 16131 loss: 4.9794 loss_prob: 2.8236 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 19:58:19 - mmengine - INFO - Epoch(train) [67][25/63] lr: 9.9698e-04 eta: 16:04:10 time: 0.7370 data_time: 0.0267 memory: 16131 loss: 4.9789 loss_prob: 2.8237 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 19:58:23 - mmengine - INFO - Epoch(train) [67][30/63] lr: 9.9698e-04 eta: 16:04:16 time: 0.8902 data_time: 0.0314 memory: 16131 loss: 4.9843 loss_prob: 2.8238 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 19:58:26 - mmengine - INFO - Epoch(train) [67][35/63] lr: 9.9698e-04 eta: 16:04:16 time: 0.7648 data_time: 0.0112 memory: 16131 loss: 4.9833 loss_prob: 2.8229 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 19:58:32 - mmengine - INFO - Epoch(train) [67][40/63] lr: 9.9698e-04 eta: 16:04:33 time: 0.9615 data_time: 0.0151 memory: 16131 loss: 4.9760 loss_prob: 2.8214 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 19:58:37 - mmengine - INFO - Epoch(train) [67][45/63] lr: 9.9698e-04 eta: 16:04:33 time: 1.0580 data_time: 0.0164 memory: 16131 loss: 4.9859 loss_prob: 2.8279 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 19:58:41 - mmengine - INFO - Epoch(train) [67][50/63] lr: 9.9698e-04 eta: 16:04:31 time: 0.8439 data_time: 0.0202 memory: 16131 loss: 4.9879 loss_prob: 2.8289 loss_thr: 1.1590 loss_db: 1.0000 2022/10/25 19:58:43 - mmengine - INFO - Epoch(train) [67][55/63] lr: 9.9698e-04 eta: 16:04:31 time: 0.6297 data_time: 0.0241 memory: 16131 loss: 4.9787 loss_prob: 2.8260 loss_thr: 1.1528 loss_db: 1.0000 2022/10/25 19:58:46 - mmengine - INFO - Epoch(train) [67][60/63] lr: 9.9698e-04 eta: 16:03:46 time: 0.5905 data_time: 0.0101 memory: 16131 loss: 4.9783 loss_prob: 2.8274 loss_thr: 1.1509 loss_db: 1.0000 2022/10/25 19:58:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:58:56 - mmengine - INFO - Epoch(train) [68][5/63] lr: 1.0120e-03 eta: 16:03:46 time: 1.1249 data_time: 0.1981 memory: 16131 loss: 4.9798 loss_prob: 2.8224 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 19:59:02 - mmengine - INFO - Epoch(train) [68][10/63] lr: 1.0120e-03 eta: 16:04:36 time: 1.4155 data_time: 0.1982 memory: 16131 loss: 4.9828 loss_prob: 2.8223 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 19:59:08 - mmengine - INFO - Epoch(train) [68][15/63] lr: 1.0120e-03 eta: 16:04:36 time: 1.1470 data_time: 0.0102 memory: 16131 loss: 4.9834 loss_prob: 2.8238 loss_thr: 1.1597 loss_db: 1.0000 2022/10/25 19:59:11 - mmengine - INFO - Epoch(train) [68][20/63] lr: 1.0120e-03 eta: 16:04:49 time: 0.9339 data_time: 0.0073 memory: 16131 loss: 4.9803 loss_prob: 2.8223 loss_thr: 1.1581 loss_db: 1.0000 2022/10/25 19:59:14 - mmengine - INFO - Epoch(train) [68][25/63] lr: 1.0120e-03 eta: 16:04:49 time: 0.6538 data_time: 0.0220 memory: 16131 loss: 4.9842 loss_prob: 2.8229 loss_thr: 1.1613 loss_db: 1.0000 2022/10/25 19:59:19 - mmengine - INFO - Epoch(train) [68][30/63] lr: 1.0120e-03 eta: 16:04:29 time: 0.7429 data_time: 0.0367 memory: 16131 loss: 4.9853 loss_prob: 2.8257 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 19:59:23 - mmengine - INFO - Epoch(train) [68][35/63] lr: 1.0120e-03 eta: 16:04:29 time: 0.8987 data_time: 0.0213 memory: 16131 loss: 4.9818 loss_prob: 2.8261 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 19:59:26 - mmengine - INFO - Epoch(train) [68][40/63] lr: 1.0120e-03 eta: 16:04:14 time: 0.7710 data_time: 0.0100 memory: 16131 loss: 4.9807 loss_prob: 2.8246 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 19:59:31 - mmengine - INFO - Epoch(train) [68][45/63] lr: 1.0120e-03 eta: 16:04:14 time: 0.7306 data_time: 0.0098 memory: 16131 loss: 4.9795 loss_prob: 2.8225 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 19:59:33 - mmengine - INFO - Epoch(train) [68][50/63] lr: 1.0120e-03 eta: 16:03:48 time: 0.7025 data_time: 0.0200 memory: 16131 loss: 4.9796 loss_prob: 2.8225 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 19:59:37 - mmengine - INFO - Epoch(train) [68][55/63] lr: 1.0120e-03 eta: 16:03:48 time: 0.6674 data_time: 0.0233 memory: 16131 loss: 4.9794 loss_prob: 2.8230 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 19:59:42 - mmengine - INFO - Epoch(train) [68][60/63] lr: 1.0120e-03 eta: 16:03:43 time: 0.8260 data_time: 0.0109 memory: 16131 loss: 4.9835 loss_prob: 2.8257 loss_thr: 1.1577 loss_db: 1.0000 2022/10/25 19:59:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 19:59:48 - mmengine - INFO - Epoch(train) [69][5/63] lr: 1.0271e-03 eta: 16:03:43 time: 0.8303 data_time: 0.2041 memory: 16131 loss: 4.9816 loss_prob: 2.8244 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 19:59:51 - mmengine - INFO - Epoch(train) [69][10/63] lr: 1.0271e-03 eta: 16:02:49 time: 0.7953 data_time: 0.2032 memory: 16131 loss: 4.9827 loss_prob: 2.8228 loss_thr: 1.1599 loss_db: 1.0000 2022/10/25 19:59:54 - mmengine - INFO - Epoch(train) [69][15/63] lr: 1.0271e-03 eta: 16:02:49 time: 0.5064 data_time: 0.0049 memory: 16131 loss: 4.9822 loss_prob: 2.8234 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 19:59:56 - mmengine - INFO - Epoch(train) [69][20/63] lr: 1.0271e-03 eta: 16:01:54 time: 0.5277 data_time: 0.0048 memory: 16131 loss: 4.9782 loss_prob: 2.8236 loss_thr: 1.1546 loss_db: 1.0000 2022/10/25 19:59:59 - mmengine - INFO - Epoch(train) [69][25/63] lr: 1.0271e-03 eta: 16:01:54 time: 0.5650 data_time: 0.0337 memory: 16131 loss: 4.9784 loss_prob: 2.8249 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 20:00:02 - mmengine - INFO - Epoch(train) [69][30/63] lr: 1.0271e-03 eta: 16:01:05 time: 0.5594 data_time: 0.0411 memory: 16131 loss: 4.9796 loss_prob: 2.8243 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 20:00:04 - mmengine - INFO - Epoch(train) [69][35/63] lr: 1.0271e-03 eta: 16:01:05 time: 0.5141 data_time: 0.0119 memory: 16131 loss: 4.9792 loss_prob: 2.8238 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 20:00:08 - mmengine - INFO - Epoch(train) [69][40/63] lr: 1.0271e-03 eta: 16:00:19 time: 0.5771 data_time: 0.0057 memory: 16131 loss: 4.9838 loss_prob: 2.8247 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 20:00:10 - mmengine - INFO - Epoch(train) [69][45/63] lr: 1.0271e-03 eta: 16:00:19 time: 0.6168 data_time: 0.0064 memory: 16131 loss: 4.9807 loss_prob: 2.8243 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 20:00:17 - mmengine - INFO - Epoch(train) [69][50/63] lr: 1.0271e-03 eta: 16:00:28 time: 0.9173 data_time: 0.0174 memory: 16131 loss: 4.9782 loss_prob: 2.8251 loss_thr: 1.1531 loss_db: 1.0000 2022/10/25 20:00:19 - mmengine - INFO - Epoch(train) [69][55/63] lr: 1.0271e-03 eta: 16:00:28 time: 0.8731 data_time: 0.0233 memory: 16131 loss: 4.9832 loss_prob: 2.8253 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 20:00:23 - mmengine - INFO - Epoch(train) [69][60/63] lr: 1.0271e-03 eta: 15:59:51 time: 0.6308 data_time: 0.0152 memory: 16131 loss: 4.9813 loss_prob: 2.8240 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 20:00:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:00:30 - mmengine - INFO - Epoch(train) [70][5/63] lr: 1.0422e-03 eta: 15:59:51 time: 0.8958 data_time: 0.2057 memory: 16131 loss: 4.9709 loss_prob: 2.8259 loss_thr: 1.1450 loss_db: 1.0000 2022/10/25 20:00:32 - mmengine - INFO - Epoch(train) [70][10/63] lr: 1.0422e-03 eta: 15:59:03 time: 0.8199 data_time: 0.2056 memory: 16131 loss: 4.9826 loss_prob: 2.8271 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 20:00:36 - mmengine - INFO - Epoch(train) [70][15/63] lr: 1.0422e-03 eta: 15:59:03 time: 0.6074 data_time: 0.0073 memory: 16131 loss: 4.9877 loss_prob: 2.8245 loss_thr: 1.1632 loss_db: 1.0000 2022/10/25 20:00:38 - mmengine - INFO - Epoch(train) [70][20/63] lr: 1.0422e-03 eta: 15:58:20 time: 0.5917 data_time: 0.0098 memory: 16131 loss: 4.9808 loss_prob: 2.8220 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 20:00:41 - mmengine - INFO - Epoch(train) [70][25/63] lr: 1.0422e-03 eta: 15:58:20 time: 0.5441 data_time: 0.0122 memory: 16131 loss: 4.9785 loss_prob: 2.8227 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 20:00:44 - mmengine - INFO - Epoch(train) [70][30/63] lr: 1.0422e-03 eta: 15:57:32 time: 0.5629 data_time: 0.0399 memory: 16131 loss: 4.9787 loss_prob: 2.8271 loss_thr: 1.1516 loss_db: 1.0000 2022/10/25 20:00:48 - mmengine - INFO - Epoch(train) [70][35/63] lr: 1.0422e-03 eta: 15:57:32 time: 0.6769 data_time: 0.0351 memory: 16131 loss: 4.9814 loss_prob: 2.8288 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 20:00:52 - mmengine - INFO - Epoch(train) [70][40/63] lr: 1.0422e-03 eta: 15:57:28 time: 0.8320 data_time: 0.0064 memory: 16131 loss: 4.9815 loss_prob: 2.8250 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 20:00:58 - mmengine - INFO - Epoch(train) [70][45/63] lr: 1.0422e-03 eta: 15:57:28 time: 1.0013 data_time: 0.0062 memory: 16131 loss: 4.9794 loss_prob: 2.8225 loss_thr: 1.1569 loss_db: 1.0000 2022/10/25 20:01:04 - mmengine - INFO - Epoch(train) [70][50/63] lr: 1.0422e-03 eta: 15:58:24 time: 1.2011 data_time: 0.0202 memory: 16131 loss: 4.9797 loss_prob: 2.8208 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 20:01:08 - mmengine - INFO - Epoch(train) [70][55/63] lr: 1.0422e-03 eta: 15:58:24 time: 0.9915 data_time: 0.0210 memory: 16131 loss: 4.9813 loss_prob: 2.8215 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 20:01:11 - mmengine - INFO - Epoch(train) [70][60/63] lr: 1.0422e-03 eta: 15:57:47 time: 0.6282 data_time: 0.0073 memory: 16131 loss: 4.9788 loss_prob: 2.8227 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 20:01:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:01:19 - mmengine - INFO - Epoch(train) [71][5/63] lr: 1.0572e-03 eta: 15:57:47 time: 0.9260 data_time: 0.1641 memory: 16131 loss: 4.9753 loss_prob: 2.8218 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 20:01:22 - mmengine - INFO - Epoch(train) [71][10/63] lr: 1.0572e-03 eta: 15:57:06 time: 0.8643 data_time: 0.1625 memory: 16131 loss: 4.9725 loss_prob: 2.8209 loss_thr: 1.1516 loss_db: 1.0000 2022/10/25 20:01:25 - mmengine - INFO - Epoch(train) [71][15/63] lr: 1.0572e-03 eta: 15:57:06 time: 0.5756 data_time: 0.0058 memory: 16131 loss: 4.9789 loss_prob: 2.8219 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 20:01:27 - mmengine - INFO - Epoch(train) [71][20/63] lr: 1.0572e-03 eta: 15:56:19 time: 0.5602 data_time: 0.0057 memory: 16131 loss: 4.9831 loss_prob: 2.8223 loss_thr: 1.1608 loss_db: 1.0000 2022/10/25 20:01:30 - mmengine - INFO - Epoch(train) [71][25/63] lr: 1.0572e-03 eta: 15:56:19 time: 0.5415 data_time: 0.0080 memory: 16131 loss: 4.9798 loss_prob: 2.8208 loss_thr: 1.1591 loss_db: 1.0000 2022/10/25 20:01:33 - mmengine - INFO - Epoch(train) [71][30/63] lr: 1.0572e-03 eta: 15:55:39 time: 0.6091 data_time: 0.0343 memory: 16131 loss: 4.9804 loss_prob: 2.8193 loss_thr: 1.1611 loss_db: 1.0000 2022/10/25 20:01:37 - mmengine - INFO - Epoch(train) [71][35/63] lr: 1.0572e-03 eta: 15:55:39 time: 0.6479 data_time: 0.0331 memory: 16131 loss: 4.9805 loss_prob: 2.8194 loss_thr: 1.1611 loss_db: 1.0000 2022/10/25 20:01:41 - mmengine - INFO - Epoch(train) [71][40/63] lr: 1.0572e-03 eta: 15:55:24 time: 0.7609 data_time: 0.0070 memory: 16131 loss: 4.9742 loss_prob: 2.8191 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 20:01:44 - mmengine - INFO - Epoch(train) [71][45/63] lr: 1.0572e-03 eta: 15:55:24 time: 0.7326 data_time: 0.0050 memory: 16131 loss: 4.9776 loss_prob: 2.8201 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 20:01:48 - mmengine - INFO - Epoch(train) [71][50/63] lr: 1.0572e-03 eta: 15:54:59 time: 0.7022 data_time: 0.0165 memory: 16131 loss: 4.9763 loss_prob: 2.8200 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 20:01:51 - mmengine - INFO - Epoch(train) [71][55/63] lr: 1.0572e-03 eta: 15:54:59 time: 0.6651 data_time: 0.0225 memory: 16131 loss: 4.9738 loss_prob: 2.8180 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 20:01:56 - mmengine - INFO - Epoch(train) [71][60/63] lr: 1.0572e-03 eta: 15:54:51 time: 0.8030 data_time: 0.0119 memory: 16131 loss: 4.9829 loss_prob: 2.8208 loss_thr: 1.1623 loss_db: 0.9999 2022/10/25 20:01:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:02:04 - mmengine - INFO - Epoch(train) [72][5/63] lr: 1.0723e-03 eta: 15:54:51 time: 1.1176 data_time: 0.2488 memory: 16131 loss: 4.9854 loss_prob: 2.8233 loss_thr: 1.1622 loss_db: 0.9999 2022/10/25 20:02:08 - mmengine - INFO - Epoch(train) [72][10/63] lr: 1.0723e-03 eta: 15:54:33 time: 1.0016 data_time: 0.2428 memory: 16131 loss: 4.9841 loss_prob: 2.8227 loss_thr: 1.1614 loss_db: 1.0000 2022/10/25 20:02:12 - mmengine - INFO - Epoch(train) [72][15/63] lr: 1.0723e-03 eta: 15:54:33 time: 0.7670 data_time: 0.0064 memory: 16131 loss: 4.9821 loss_prob: 2.8246 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 20:02:15 - mmengine - INFO - Epoch(train) [72][20/63] lr: 1.0723e-03 eta: 15:54:07 time: 0.6896 data_time: 0.0048 memory: 16131 loss: 4.9804 loss_prob: 2.8244 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 20:02:18 - mmengine - INFO - Epoch(train) [72][25/63] lr: 1.0723e-03 eta: 15:54:07 time: 0.5849 data_time: 0.0322 memory: 16131 loss: 4.9762 loss_prob: 2.8235 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 20:02:22 - mmengine - INFO - Epoch(train) [72][30/63] lr: 1.0723e-03 eta: 15:53:38 time: 0.6725 data_time: 0.0325 memory: 16131 loss: 4.9776 loss_prob: 2.8220 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:02:24 - mmengine - INFO - Epoch(train) [72][35/63] lr: 1.0723e-03 eta: 15:53:38 time: 0.6719 data_time: 0.0058 memory: 16131 loss: 4.9782 loss_prob: 2.8212 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 20:02:28 - mmengine - INFO - Epoch(train) [72][40/63] lr: 1.0723e-03 eta: 15:53:11 time: 0.6875 data_time: 0.0058 memory: 16131 loss: 4.9804 loss_prob: 2.8216 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 20:02:32 - mmengine - INFO - Epoch(train) [72][45/63] lr: 1.0723e-03 eta: 15:53:11 time: 0.7475 data_time: 0.0057 memory: 16131 loss: 4.9834 loss_prob: 2.8227 loss_thr: 1.1607 loss_db: 1.0000 2022/10/25 20:02:37 - mmengine - INFO - Epoch(train) [72][50/63] lr: 1.0723e-03 eta: 15:53:18 time: 0.9027 data_time: 0.0230 memory: 16131 loss: 4.9786 loss_prob: 2.8235 loss_thr: 1.1552 loss_db: 1.0000 2022/10/25 20:02:40 - mmengine - INFO - Epoch(train) [72][55/63] lr: 1.0723e-03 eta: 15:53:18 time: 0.8396 data_time: 0.0224 memory: 16131 loss: 4.9796 loss_prob: 2.8253 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 20:02:43 - mmengine - INFO - Epoch(train) [72][60/63] lr: 1.0723e-03 eta: 15:52:34 time: 0.5744 data_time: 0.0050 memory: 16131 loss: 4.9835 loss_prob: 2.8249 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 20:02:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:02:50 - mmengine - INFO - Epoch(train) [73][5/63] lr: 1.0873e-03 eta: 15:52:34 time: 0.7766 data_time: 0.2079 memory: 16131 loss: 4.9828 loss_prob: 2.8232 loss_thr: 1.1596 loss_db: 1.0000 2022/10/25 20:02:54 - mmengine - INFO - Epoch(train) [73][10/63] lr: 1.0873e-03 eta: 15:52:12 time: 0.9682 data_time: 0.2089 memory: 16131 loss: 4.9771 loss_prob: 2.8222 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 20:03:00 - mmengine - INFO - Epoch(train) [73][15/63] lr: 1.0873e-03 eta: 15:52:12 time: 0.9778 data_time: 0.0068 memory: 16131 loss: 4.9764 loss_prob: 2.8214 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 20:03:05 - mmengine - INFO - Epoch(train) [73][20/63] lr: 1.0873e-03 eta: 15:52:53 time: 1.1183 data_time: 0.0073 memory: 16131 loss: 4.9732 loss_prob: 2.8215 loss_thr: 1.1518 loss_db: 1.0000 2022/10/25 20:03:10 - mmengine - INFO - Epoch(train) [73][25/63] lr: 1.0873e-03 eta: 15:52:53 time: 1.0223 data_time: 0.0137 memory: 16131 loss: 4.9758 loss_prob: 2.8207 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 20:03:13 - mmengine - INFO - Epoch(train) [73][30/63] lr: 1.0873e-03 eta: 15:52:35 time: 0.7395 data_time: 0.0353 memory: 16131 loss: 4.9768 loss_prob: 2.8207 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 20:03:15 - mmengine - INFO - Epoch(train) [73][35/63] lr: 1.0873e-03 eta: 15:52:35 time: 0.5387 data_time: 0.0296 memory: 16131 loss: 4.9794 loss_prob: 2.8215 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 20:03:18 - mmengine - INFO - Epoch(train) [73][40/63] lr: 1.0873e-03 eta: 15:51:49 time: 0.5627 data_time: 0.0056 memory: 16131 loss: 4.9819 loss_prob: 2.8209 loss_thr: 1.1610 loss_db: 1.0000 2022/10/25 20:03:23 - mmengine - INFO - Epoch(train) [73][45/63] lr: 1.0873e-03 eta: 15:51:49 time: 0.7453 data_time: 0.0075 memory: 16131 loss: 4.9742 loss_prob: 2.8190 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 20:03:25 - mmengine - INFO - Epoch(train) [73][50/63] lr: 1.0873e-03 eta: 15:51:28 time: 0.7212 data_time: 0.0148 memory: 16131 loss: 4.9713 loss_prob: 2.8182 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 20:03:29 - mmengine - INFO - Epoch(train) [73][55/63] lr: 1.0873e-03 eta: 15:51:28 time: 0.6140 data_time: 0.0219 memory: 16131 loss: 4.9733 loss_prob: 2.8186 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 20:03:32 - mmengine - INFO - Epoch(train) [73][60/63] lr: 1.0873e-03 eta: 15:50:50 time: 0.6065 data_time: 0.0194 memory: 16131 loss: 4.9726 loss_prob: 2.8175 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 20:03:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:03:39 - mmengine - INFO - Epoch(train) [74][5/63] lr: 1.1024e-03 eta: 15:50:50 time: 0.8370 data_time: 0.2284 memory: 16131 loss: 4.9750 loss_prob: 2.8172 loss_thr: 1.1578 loss_db: 1.0000 2022/10/25 20:03:44 - mmengine - INFO - Epoch(train) [74][10/63] lr: 1.1024e-03 eta: 15:50:32 time: 1.0009 data_time: 0.2279 memory: 16131 loss: 4.9774 loss_prob: 2.8173 loss_thr: 1.1601 loss_db: 1.0000 2022/10/25 20:03:48 - mmengine - INFO - Epoch(train) [74][15/63] lr: 1.1024e-03 eta: 15:50:32 time: 0.9199 data_time: 0.0093 memory: 16131 loss: 4.9765 loss_prob: 2.8182 loss_thr: 1.1583 loss_db: 1.0000 2022/10/25 20:03:51 - mmengine - INFO - Epoch(train) [74][20/63] lr: 1.1024e-03 eta: 15:50:05 time: 0.6798 data_time: 0.0091 memory: 16131 loss: 4.9780 loss_prob: 2.8208 loss_thr: 1.1572 loss_db: 1.0000 2022/10/25 20:03:56 - mmengine - INFO - Epoch(train) [74][25/63] lr: 1.1024e-03 eta: 15:50:05 time: 0.7750 data_time: 0.0275 memory: 16131 loss: 4.9762 loss_prob: 2.8227 loss_thr: 1.1536 loss_db: 1.0000 2022/10/25 20:03:59 - mmengine - INFO - Epoch(train) [74][30/63] lr: 1.1024e-03 eta: 15:50:05 time: 0.8514 data_time: 0.0378 memory: 16131 loss: 4.9769 loss_prob: 2.8214 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 20:04:02 - mmengine - INFO - Epoch(train) [74][35/63] lr: 1.1024e-03 eta: 15:50:05 time: 0.5931 data_time: 0.0180 memory: 16131 loss: 4.9779 loss_prob: 2.8194 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 20:04:04 - mmengine - INFO - Epoch(train) [74][40/63] lr: 1.1024e-03 eta: 15:49:12 time: 0.5113 data_time: 0.0079 memory: 16131 loss: 4.9785 loss_prob: 2.8190 loss_thr: 1.1595 loss_db: 1.0000 2022/10/25 20:04:09 - mmengine - INFO - Epoch(train) [74][45/63] lr: 1.1024e-03 eta: 15:49:12 time: 0.6784 data_time: 0.0052 memory: 16131 loss: 4.9792 loss_prob: 2.8198 loss_thr: 1.1594 loss_db: 1.0000 2022/10/25 20:04:12 - mmengine - INFO - Epoch(train) [74][50/63] lr: 1.1024e-03 eta: 15:49:02 time: 0.7888 data_time: 0.0184 memory: 16131 loss: 4.9773 loss_prob: 2.8213 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 20:04:15 - mmengine - INFO - Epoch(train) [74][55/63] lr: 1.1024e-03 eta: 15:49:02 time: 0.6153 data_time: 0.0201 memory: 16131 loss: 4.9722 loss_prob: 2.8209 loss_thr: 1.1513 loss_db: 1.0000 2022/10/25 20:04:17 - mmengine - INFO - Epoch(train) [74][60/63] lr: 1.1024e-03 eta: 15:48:10 time: 0.5118 data_time: 0.0079 memory: 16131 loss: 4.9676 loss_prob: 2.8191 loss_thr: 1.1485 loss_db: 1.0000 2022/10/25 20:04:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:04:24 - mmengine - INFO - Epoch(train) [75][5/63] lr: 1.1175e-03 eta: 15:48:10 time: 0.7549 data_time: 0.2548 memory: 16131 loss: 4.9764 loss_prob: 2.8196 loss_thr: 1.1569 loss_db: 1.0000 2022/10/25 20:04:27 - mmengine - INFO - Epoch(train) [75][10/63] lr: 1.1175e-03 eta: 15:47:26 time: 0.8226 data_time: 0.2533 memory: 16131 loss: 4.9738 loss_prob: 2.8195 loss_thr: 1.1543 loss_db: 1.0000 2022/10/25 20:04:31 - mmengine - INFO - Epoch(train) [75][15/63] lr: 1.1175e-03 eta: 15:47:26 time: 0.6880 data_time: 0.0088 memory: 16131 loss: 4.9782 loss_prob: 2.8193 loss_thr: 1.1589 loss_db: 1.0000 2022/10/25 20:04:33 - mmengine - INFO - Epoch(train) [75][20/63] lr: 1.1175e-03 eta: 15:46:53 time: 0.6368 data_time: 0.0088 memory: 16131 loss: 4.9768 loss_prob: 2.8203 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 20:04:36 - mmengine - INFO - Epoch(train) [75][25/63] lr: 1.1175e-03 eta: 15:46:53 time: 0.5302 data_time: 0.0311 memory: 16131 loss: 4.9754 loss_prob: 2.8207 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 20:04:39 - mmengine - INFO - Epoch(train) [75][30/63] lr: 1.1175e-03 eta: 15:46:06 time: 0.5446 data_time: 0.0311 memory: 16131 loss: 4.9794 loss_prob: 2.8215 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 20:04:45 - mmengine - INFO - Epoch(train) [75][35/63] lr: 1.1175e-03 eta: 15:46:06 time: 0.8953 data_time: 0.0044 memory: 16131 loss: 4.9807 loss_prob: 2.8220 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 20:04:49 - mmengine - INFO - Epoch(train) [75][40/63] lr: 1.1175e-03 eta: 15:46:31 time: 1.0183 data_time: 0.0064 memory: 16131 loss: 4.9783 loss_prob: 2.8213 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 20:04:55 - mmengine - INFO - Epoch(train) [75][45/63] lr: 1.1175e-03 eta: 15:46:31 time: 0.9655 data_time: 0.0073 memory: 16131 loss: 4.9790 loss_prob: 2.8223 loss_thr: 1.1568 loss_db: 1.0000 2022/10/25 20:04:57 - mmengine - INFO - Epoch(train) [75][50/63] lr: 1.1175e-03 eta: 15:46:31 time: 0.8534 data_time: 0.0194 memory: 16131 loss: 4.9770 loss_prob: 2.8232 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 20:05:02 - mmengine - INFO - Epoch(train) [75][55/63] lr: 1.1175e-03 eta: 15:46:31 time: 0.7779 data_time: 0.0204 memory: 16131 loss: 4.9711 loss_prob: 2.8225 loss_thr: 1.1486 loss_db: 1.0000 2022/10/25 20:05:05 - mmengine - INFO - Epoch(train) [75][60/63] lr: 1.1175e-03 eta: 15:46:16 time: 0.7584 data_time: 0.0076 memory: 16131 loss: 4.9704 loss_prob: 2.8199 loss_thr: 1.1506 loss_db: 1.0000 2022/10/25 20:05:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:05:14 - mmengine - INFO - Epoch(train) [76][5/63] lr: 1.1325e-03 eta: 15:46:16 time: 0.9560 data_time: 0.1902 memory: 16131 loss: 4.9758 loss_prob: 2.8185 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 20:05:19 - mmengine - INFO - Epoch(train) [76][10/63] lr: 1.1325e-03 eta: 15:46:34 time: 1.2297 data_time: 0.1944 memory: 16131 loss: 4.9745 loss_prob: 2.8187 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 20:05:21 - mmengine - INFO - Epoch(train) [76][15/63] lr: 1.1325e-03 eta: 15:46:34 time: 0.7826 data_time: 0.0118 memory: 16131 loss: 4.9750 loss_prob: 2.8190 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 20:05:25 - mmengine - INFO - Epoch(train) [76][20/63] lr: 1.1325e-03 eta: 15:46:03 time: 0.6443 data_time: 0.0054 memory: 16131 loss: 4.9725 loss_prob: 2.8191 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 20:05:28 - mmengine - INFO - Epoch(train) [76][25/63] lr: 1.1325e-03 eta: 15:46:03 time: 0.6449 data_time: 0.0131 memory: 16131 loss: 4.9713 loss_prob: 2.8193 loss_thr: 1.1521 loss_db: 1.0000 2022/10/25 20:05:31 - mmengine - INFO - Epoch(train) [76][30/63] lr: 1.1325e-03 eta: 15:45:25 time: 0.6050 data_time: 0.0271 memory: 16131 loss: 4.9745 loss_prob: 2.8190 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 20:05:35 - mmengine - INFO - Epoch(train) [76][35/63] lr: 1.1325e-03 eta: 15:45:25 time: 0.7208 data_time: 0.0239 memory: 16131 loss: 4.9754 loss_prob: 2.8184 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 20:05:38 - mmengine - INFO - Epoch(train) [76][40/63] lr: 1.1325e-03 eta: 15:45:02 time: 0.6993 data_time: 0.0099 memory: 16131 loss: 4.9733 loss_prob: 2.8187 loss_thr: 1.1546 loss_db: 1.0000 2022/10/25 20:05:41 - mmengine - INFO - Epoch(train) [76][45/63] lr: 1.1325e-03 eta: 15:45:02 time: 0.6372 data_time: 0.0051 memory: 16131 loss: 4.9734 loss_prob: 2.8179 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:05:44 - mmengine - INFO - Epoch(train) [76][50/63] lr: 1.1325e-03 eta: 15:44:28 time: 0.6202 data_time: 0.0117 memory: 16131 loss: 4.9724 loss_prob: 2.8175 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 20:05:48 - mmengine - INFO - Epoch(train) [76][55/63] lr: 1.1325e-03 eta: 15:44:28 time: 0.6752 data_time: 0.0223 memory: 16131 loss: 4.9716 loss_prob: 2.8180 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 20:05:52 - mmengine - INFO - Epoch(train) [76][60/63] lr: 1.1325e-03 eta: 15:44:13 time: 0.7529 data_time: 0.0158 memory: 16131 loss: 4.9730 loss_prob: 2.8176 loss_thr: 1.1554 loss_db: 1.0000 2022/10/25 20:05:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:05:59 - mmengine - INFO - Epoch(train) [77][5/63] lr: 1.1476e-03 eta: 15:44:13 time: 0.8056 data_time: 0.1900 memory: 16131 loss: 4.9758 loss_prob: 2.8194 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 20:06:03 - mmengine - INFO - Epoch(train) [77][10/63] lr: 1.1476e-03 eta: 15:43:55 time: 0.9892 data_time: 0.1958 memory: 16131 loss: 4.9714 loss_prob: 2.8182 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 20:06:06 - mmengine - INFO - Epoch(train) [77][15/63] lr: 1.1476e-03 eta: 15:43:55 time: 0.6635 data_time: 0.0106 memory: 16131 loss: 4.9769 loss_prob: 2.8187 loss_thr: 1.1582 loss_db: 1.0000 2022/10/25 20:06:08 - mmengine - INFO - Epoch(train) [77][20/63] lr: 1.1476e-03 eta: 15:43:07 time: 0.5289 data_time: 0.0049 memory: 16131 loss: 4.9770 loss_prob: 2.8198 loss_thr: 1.1573 loss_db: 1.0000 2022/10/25 20:06:11 - mmengine - INFO - Epoch(train) [77][25/63] lr: 1.1476e-03 eta: 15:43:07 time: 0.5626 data_time: 0.0127 memory: 16131 loss: 4.9768 loss_prob: 2.8202 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 20:06:15 - mmengine - INFO - Epoch(train) [77][30/63] lr: 1.1476e-03 eta: 15:42:40 time: 0.6744 data_time: 0.0321 memory: 16131 loss: 4.9784 loss_prob: 2.8198 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 20:06:19 - mmengine - INFO - Epoch(train) [77][35/63] lr: 1.1476e-03 eta: 15:42:40 time: 0.7412 data_time: 0.0259 memory: 16131 loss: 4.9755 loss_prob: 2.8184 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 20:06:24 - mmengine - INFO - Epoch(train) [77][40/63] lr: 1.1476e-03 eta: 15:42:39 time: 0.8448 data_time: 0.0079 memory: 16131 loss: 4.9735 loss_prob: 2.8191 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 20:06:27 - mmengine - INFO - Epoch(train) [77][45/63] lr: 1.1476e-03 eta: 15:42:39 time: 0.7947 data_time: 0.0078 memory: 16131 loss: 4.9781 loss_prob: 2.8192 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 20:06:29 - mmengine - INFO - Epoch(train) [77][50/63] lr: 1.1476e-03 eta: 15:41:57 time: 0.5683 data_time: 0.0143 memory: 16131 loss: 4.9836 loss_prob: 2.8194 loss_thr: 1.1643 loss_db: 1.0000 2022/10/25 20:06:33 - mmengine - INFO - Epoch(train) [77][55/63] lr: 1.1476e-03 eta: 15:41:57 time: 0.6539 data_time: 0.0206 memory: 16131 loss: 4.9787 loss_prob: 2.8194 loss_thr: 1.1593 loss_db: 1.0000 2022/10/25 20:06:38 - mmengine - INFO - Epoch(train) [77][60/63] lr: 1.1476e-03 eta: 15:41:54 time: 0.8330 data_time: 0.0156 memory: 16131 loss: 4.9747 loss_prob: 2.8192 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:06:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:06:49 - mmengine - INFO - Epoch(train) [78][5/63] lr: 1.1626e-03 eta: 15:41:54 time: 1.2757 data_time: 0.1988 memory: 16131 loss: 4.9773 loss_prob: 2.8182 loss_thr: 1.1591 loss_db: 1.0000 2022/10/25 20:06:52 - mmengine - INFO - Epoch(train) [78][10/63] lr: 1.1626e-03 eta: 15:42:10 time: 1.2178 data_time: 0.2023 memory: 16131 loss: 4.9774 loss_prob: 2.8186 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 20:06:59 - mmengine - INFO - Epoch(train) [78][15/63] lr: 1.1626e-03 eta: 15:42:10 time: 0.9308 data_time: 0.0154 memory: 16131 loss: 4.9799 loss_prob: 2.8184 loss_thr: 1.1615 loss_db: 1.0000 2022/10/25 20:07:01 - mmengine - INFO - Epoch(train) [78][20/63] lr: 1.1626e-03 eta: 15:42:15 time: 0.8875 data_time: 0.0119 memory: 16131 loss: 4.9751 loss_prob: 2.8184 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 20:07:08 - mmengine - INFO - Epoch(train) [78][25/63] lr: 1.1626e-03 eta: 15:42:15 time: 0.9304 data_time: 0.0218 memory: 16131 loss: 4.9774 loss_prob: 2.8182 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 20:07:12 - mmengine - INFO - Epoch(train) [78][30/63] lr: 1.1626e-03 eta: 15:42:47 time: 1.0743 data_time: 0.0361 memory: 16131 loss: 4.9810 loss_prob: 2.8204 loss_thr: 1.1607 loss_db: 1.0000 2022/10/25 20:07:16 - mmengine - INFO - Epoch(train) [78][35/63] lr: 1.1626e-03 eta: 15:42:47 time: 0.8629 data_time: 0.0219 memory: 16131 loss: 4.9763 loss_prob: 2.8207 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:07:19 - mmengine - INFO - Epoch(train) [78][40/63] lr: 1.1626e-03 eta: 15:42:26 time: 0.7090 data_time: 0.0115 memory: 16131 loss: 4.9739 loss_prob: 2.8201 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 20:07:24 - mmengine - INFO - Epoch(train) [78][45/63] lr: 1.1626e-03 eta: 15:42:26 time: 0.7430 data_time: 0.0089 memory: 16131 loss: 4.9761 loss_prob: 2.8190 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 20:07:30 - mmengine - INFO - Epoch(train) [78][50/63] lr: 1.1626e-03 eta: 15:42:59 time: 1.0896 data_time: 0.0210 memory: 16131 loss: 4.9758 loss_prob: 2.8170 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 20:07:34 - mmengine - INFO - Epoch(train) [78][55/63] lr: 1.1626e-03 eta: 15:42:59 time: 1.0547 data_time: 0.0221 memory: 16131 loss: 4.9739 loss_prob: 2.8181 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 20:07:37 - mmengine - INFO - Epoch(train) [78][60/63] lr: 1.1626e-03 eta: 15:42:40 time: 0.7193 data_time: 0.0073 memory: 16131 loss: 4.9717 loss_prob: 2.8195 loss_thr: 1.1522 loss_db: 1.0000 2022/10/25 20:07:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:07:46 - mmengine - INFO - Epoch(train) [79][5/63] lr: 1.1777e-03 eta: 15:42:40 time: 1.0068 data_time: 0.1563 memory: 16131 loss: 4.9709 loss_prob: 2.8182 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 20:07:49 - mmengine - INFO - Epoch(train) [79][10/63] lr: 1.1777e-03 eta: 15:42:37 time: 1.0952 data_time: 0.1564 memory: 16131 loss: 4.9686 loss_prob: 2.8189 loss_thr: 1.1497 loss_db: 1.0000 2022/10/25 20:07:53 - mmengine - INFO - Epoch(train) [79][15/63] lr: 1.1777e-03 eta: 15:42:37 time: 0.6818 data_time: 0.0106 memory: 16131 loss: 4.9713 loss_prob: 2.8202 loss_thr: 1.1511 loss_db: 1.0000 2022/10/25 20:07:56 - mmengine - INFO - Epoch(train) [79][20/63] lr: 1.1777e-03 eta: 15:42:14 time: 0.6957 data_time: 0.0115 memory: 16131 loss: 4.9775 loss_prob: 2.8198 loss_thr: 1.1578 loss_db: 1.0000 2022/10/25 20:07:59 - mmengine - INFO - Epoch(train) [79][25/63] lr: 1.1777e-03 eta: 15:42:14 time: 0.6046 data_time: 0.0173 memory: 16131 loss: 4.9717 loss_prob: 2.8190 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 20:08:02 - mmengine - INFO - Epoch(train) [79][30/63] lr: 1.1777e-03 eta: 15:41:31 time: 0.5558 data_time: 0.0293 memory: 16131 loss: 4.9708 loss_prob: 2.8189 loss_thr: 1.1519 loss_db: 1.0000 2022/10/25 20:08:06 - mmengine - INFO - Epoch(train) [79][35/63] lr: 1.1777e-03 eta: 15:41:31 time: 0.6459 data_time: 0.0225 memory: 16131 loss: 4.9746 loss_prob: 2.8189 loss_thr: 1.1558 loss_db: 1.0000 2022/10/25 20:08:08 - mmengine - INFO - Epoch(train) [79][40/63] lr: 1.1777e-03 eta: 15:41:01 time: 0.6410 data_time: 0.0090 memory: 16131 loss: 4.9809 loss_prob: 2.8193 loss_thr: 1.1616 loss_db: 1.0000 2022/10/25 20:08:11 - mmengine - INFO - Epoch(train) [79][45/63] lr: 1.1777e-03 eta: 15:41:01 time: 0.5641 data_time: 0.0074 memory: 16131 loss: 4.9824 loss_prob: 2.8203 loss_thr: 1.1622 loss_db: 1.0000 2022/10/25 20:08:14 - mmengine - INFO - Epoch(train) [79][50/63] lr: 1.1777e-03 eta: 15:40:22 time: 0.5801 data_time: 0.0159 memory: 16131 loss: 4.9732 loss_prob: 2.8196 loss_thr: 1.1536 loss_db: 1.0000 2022/10/25 20:08:17 - mmengine - INFO - Epoch(train) [79][55/63] lr: 1.1777e-03 eta: 15:40:22 time: 0.5603 data_time: 0.0233 memory: 16131 loss: 4.9753 loss_prob: 2.8194 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 20:08:20 - mmengine - INFO - Epoch(train) [79][60/63] lr: 1.1777e-03 eta: 15:39:46 time: 0.6006 data_time: 0.0140 memory: 16131 loss: 4.9810 loss_prob: 2.8197 loss_thr: 1.1613 loss_db: 1.0000 2022/10/25 20:08:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:08:28 - mmengine - INFO - Epoch(train) [80][5/63] lr: 1.1928e-03 eta: 15:39:46 time: 0.9734 data_time: 0.1648 memory: 16131 loss: 4.9790 loss_prob: 2.8219 loss_thr: 1.1571 loss_db: 1.0000 2022/10/25 20:08:32 - mmengine - INFO - Epoch(train) [80][10/63] lr: 1.1928e-03 eta: 15:39:39 time: 1.0639 data_time: 0.1748 memory: 16131 loss: 4.9793 loss_prob: 2.8218 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 20:08:36 - mmengine - INFO - Epoch(train) [80][15/63] lr: 1.1928e-03 eta: 15:39:39 time: 0.7980 data_time: 0.0202 memory: 16131 loss: 4.9748 loss_prob: 2.8199 loss_thr: 1.1549 loss_db: 1.0000 2022/10/25 20:08:39 - mmengine - INFO - Epoch(train) [80][20/63] lr: 1.1928e-03 eta: 15:39:18 time: 0.7068 data_time: 0.0233 memory: 16131 loss: 4.9731 loss_prob: 2.8192 loss_thr: 1.1538 loss_db: 1.0000 2022/10/25 20:08:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:08:44 - mmengine - INFO - Epoch(train) [80][25/63] lr: 1.1928e-03 eta: 15:39:18 time: 0.7799 data_time: 0.0211 memory: 16131 loss: 4.9720 loss_prob: 2.8176 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 20:08:49 - mmengine - INFO - Epoch(train) [80][30/63] lr: 1.1928e-03 eta: 15:39:33 time: 0.9650 data_time: 0.0213 memory: 16131 loss: 4.9747 loss_prob: 2.8172 loss_thr: 1.1576 loss_db: 1.0000 2022/10/25 20:08:52 - mmengine - INFO - Epoch(train) [80][35/63] lr: 1.1928e-03 eta: 15:39:33 time: 0.7470 data_time: 0.0275 memory: 16131 loss: 4.9783 loss_prob: 2.8175 loss_thr: 1.1609 loss_db: 1.0000 2022/10/25 20:08:55 - mmengine - INFO - Epoch(train) [80][40/63] lr: 1.1928e-03 eta: 15:38:58 time: 0.6023 data_time: 0.0171 memory: 16131 loss: 4.9770 loss_prob: 2.8165 loss_thr: 1.1605 loss_db: 1.0000 2022/10/25 20:08:59 - mmengine - INFO - Epoch(train) [80][45/63] lr: 1.1928e-03 eta: 15:38:58 time: 0.7449 data_time: 0.0092 memory: 16131 loss: 4.9731 loss_prob: 2.8158 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 20:09:02 - mmengine - INFO - Epoch(train) [80][50/63] lr: 1.1928e-03 eta: 15:38:40 time: 0.7310 data_time: 0.0067 memory: 16131 loss: 4.9705 loss_prob: 2.8160 loss_thr: 1.1545 loss_db: 1.0000 2022/10/25 20:09:05 - mmengine - INFO - Epoch(train) [80][55/63] lr: 1.1928e-03 eta: 15:38:40 time: 0.6512 data_time: 0.0236 memory: 16131 loss: 4.9693 loss_prob: 2.8162 loss_thr: 1.1531 loss_db: 1.0000 2022/10/25 20:09:09 - mmengine - INFO - Epoch(train) [80][60/63] lr: 1.1928e-03 eta: 15:38:17 time: 0.6856 data_time: 0.0251 memory: 16131 loss: 4.9703 loss_prob: 2.8167 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 20:09:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:09:11 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/10/25 20:09:17 - mmengine - INFO - Epoch(val) [80][5/32] eta: 15:38:17 time: 0.4247 data_time: 0.0680 memory: 16131 2022/10/25 20:09:19 - mmengine - INFO - Epoch(val) [80][10/32] eta: 0:00:09 time: 0.4508 data_time: 0.0729 memory: 15724 2022/10/25 20:09:22 - mmengine - INFO - Epoch(val) [80][15/32] eta: 0:00:09 time: 0.4205 data_time: 0.0420 memory: 15724 2022/10/25 20:09:24 - mmengine - INFO - Epoch(val) [80][20/32] eta: 0:00:05 time: 0.4679 data_time: 0.0740 memory: 15724 2022/10/25 20:09:26 - mmengine - INFO - Epoch(val) [80][25/32] eta: 0:00:05 time: 0.4471 data_time: 0.0594 memory: 15724 2022/10/25 20:09:28 - mmengine - INFO - Epoch(val) [80][30/32] eta: 0:00:00 time: 0.3931 data_time: 0.0235 memory: 15724 2022/10/25 20:09:29 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:09:29 - mmengine - INFO - Epoch(val) [80][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/10/25 20:09:33 - mmengine - INFO - Epoch(train) [81][5/63] lr: 1.2078e-03 eta: 0:00:00 time: 0.8794 data_time: 0.1931 memory: 16131 loss: 4.9724 loss_prob: 2.8175 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 20:09:37 - mmengine - INFO - Epoch(train) [81][10/63] lr: 1.2078e-03 eta: 15:37:43 time: 0.8720 data_time: 0.1955 memory: 16131 loss: 4.9759 loss_prob: 2.8174 loss_thr: 1.1585 loss_db: 1.0000 2022/10/25 20:09:42 - mmengine - INFO - Epoch(train) [81][15/63] lr: 1.2078e-03 eta: 15:37:43 time: 0.8306 data_time: 0.0136 memory: 16131 loss: 4.9757 loss_prob: 2.8173 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 20:09:46 - mmengine - INFO - Epoch(train) [81][20/63] lr: 1.2078e-03 eta: 15:37:41 time: 0.8419 data_time: 0.0080 memory: 16131 loss: 4.9722 loss_prob: 2.8191 loss_thr: 1.1531 loss_db: 1.0000 2022/10/25 20:09:51 - mmengine - INFO - Epoch(train) [81][25/63] lr: 1.2078e-03 eta: 15:37:41 time: 0.8735 data_time: 0.0149 memory: 16131 loss: 4.9711 loss_prob: 2.8189 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 20:09:54 - mmengine - INFO - Epoch(train) [81][30/63] lr: 1.2078e-03 eta: 15:37:40 time: 0.8415 data_time: 0.0266 memory: 16131 loss: 4.9743 loss_prob: 2.8175 loss_thr: 1.1569 loss_db: 1.0000 2022/10/25 20:09:57 - mmengine - INFO - Epoch(train) [81][35/63] lr: 1.2078e-03 eta: 15:37:40 time: 0.5997 data_time: 0.0253 memory: 16131 loss: 4.9781 loss_prob: 2.8181 loss_thr: 1.1600 loss_db: 1.0000 2022/10/25 20:09:59 - mmengine - INFO - Epoch(train) [81][40/63] lr: 1.2078e-03 eta: 15:36:51 time: 0.5046 data_time: 0.0133 memory: 16131 loss: 4.9726 loss_prob: 2.8179 loss_thr: 1.1547 loss_db: 1.0000 2022/10/25 20:10:02 - mmengine - INFO - Epoch(train) [81][45/63] lr: 1.2078e-03 eta: 15:36:51 time: 0.5492 data_time: 0.0111 memory: 16131 loss: 4.9708 loss_prob: 2.8177 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 20:10:06 - mmengine - INFO - Epoch(train) [81][50/63] lr: 1.2078e-03 eta: 15:36:33 time: 0.7266 data_time: 0.0151 memory: 16131 loss: 4.9748 loss_prob: 2.8191 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 20:10:11 - mmengine - INFO - Epoch(train) [81][55/63] lr: 1.2078e-03 eta: 15:36:33 time: 0.9452 data_time: 0.0170 memory: 16131 loss: 4.9751 loss_prob: 2.8192 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 20:10:16 - mmengine - INFO - Epoch(train) [81][60/63] lr: 1.2078e-03 eta: 15:36:51 time: 0.9833 data_time: 0.0182 memory: 16131 loss: 4.9726 loss_prob: 2.8184 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 20:10:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:10:24 - mmengine - INFO - Epoch(train) [82][5/63] lr: 1.2229e-03 eta: 15:36:51 time: 0.9450 data_time: 0.1733 memory: 16131 loss: 4.9722 loss_prob: 2.8195 loss_thr: 1.1526 loss_db: 1.0000 2022/10/25 20:10:29 - mmengine - INFO - Epoch(train) [82][10/63] lr: 1.2229e-03 eta: 15:36:50 time: 1.1041 data_time: 0.1727 memory: 16131 loss: 4.9776 loss_prob: 2.8195 loss_thr: 1.1581 loss_db: 1.0000 2022/10/25 20:10:33 - mmengine - INFO - Epoch(train) [82][15/63] lr: 1.2229e-03 eta: 15:36:50 time: 0.9664 data_time: 0.0070 memory: 16131 loss: 4.9735 loss_prob: 2.8179 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:10:37 - mmengine - INFO - Epoch(train) [82][20/63] lr: 1.2229e-03 eta: 15:36:52 time: 0.8691 data_time: 0.0083 memory: 16131 loss: 4.9721 loss_prob: 2.8180 loss_thr: 1.1541 loss_db: 1.0000 2022/10/25 20:10:40 - mmengine - INFO - Epoch(train) [82][25/63] lr: 1.2229e-03 eta: 15:36:52 time: 0.6881 data_time: 0.0195 memory: 16131 loss: 4.9723 loss_prob: 2.8180 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 20:10:43 - mmengine - INFO - Epoch(train) [82][30/63] lr: 1.2229e-03 eta: 15:36:12 time: 0.5646 data_time: 0.0368 memory: 16131 loss: 4.9712 loss_prob: 2.8172 loss_thr: 1.1541 loss_db: 1.0000 2022/10/25 20:10:46 - mmengine - INFO - Epoch(train) [82][35/63] lr: 1.2229e-03 eta: 15:36:12 time: 0.6278 data_time: 0.0237 memory: 16131 loss: 4.9694 loss_prob: 2.8168 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 20:10:50 - mmengine - INFO - Epoch(train) [82][40/63] lr: 1.2229e-03 eta: 15:35:57 time: 0.7504 data_time: 0.0045 memory: 16131 loss: 4.9665 loss_prob: 2.8162 loss_thr: 1.1503 loss_db: 1.0000 2022/10/25 20:10:53 - mmengine - INFO - Epoch(train) [82][45/63] lr: 1.2229e-03 eta: 15:35:57 time: 0.6645 data_time: 0.0056 memory: 16131 loss: 4.9667 loss_prob: 2.8160 loss_thr: 1.1507 loss_db: 1.0000 2022/10/25 20:10:56 - mmengine - INFO - Epoch(train) [82][50/63] lr: 1.2229e-03 eta: 15:35:15 time: 0.5412 data_time: 0.0156 memory: 16131 loss: 4.9725 loss_prob: 2.8170 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 20:11:00 - mmengine - INFO - Epoch(train) [82][55/63] lr: 1.2229e-03 eta: 15:35:15 time: 0.6765 data_time: 0.0297 memory: 16131 loss: 4.9747 loss_prob: 2.8166 loss_thr: 1.1582 loss_db: 1.0000 2022/10/25 20:11:06 - mmengine - INFO - Epoch(train) [82][60/63] lr: 1.2229e-03 eta: 15:35:32 time: 0.9833 data_time: 0.0222 memory: 16131 loss: 4.9733 loss_prob: 2.8168 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 20:11:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:11:17 - mmengine - INFO - Epoch(train) [83][5/63] lr: 1.2379e-03 eta: 15:35:32 time: 1.3296 data_time: 0.1901 memory: 16131 loss: 4.9781 loss_prob: 2.8177 loss_thr: 1.1604 loss_db: 1.0000 2022/10/25 20:11:20 - mmengine - INFO - Epoch(train) [83][10/63] lr: 1.2379e-03 eta: 15:35:26 time: 1.0703 data_time: 0.1862 memory: 16131 loss: 4.9762 loss_prob: 2.8160 loss_thr: 1.1603 loss_db: 1.0000 2022/10/25 20:11:22 - mmengine - INFO - Epoch(train) [83][15/63] lr: 1.2379e-03 eta: 15:35:26 time: 0.5840 data_time: 0.0073 memory: 16131 loss: 4.9724 loss_prob: 2.8160 loss_thr: 1.1564 loss_db: 1.0000 2022/10/25 20:11:25 - mmengine - INFO - Epoch(train) [83][20/63] lr: 1.2379e-03 eta: 15:34:45 time: 0.5504 data_time: 0.0110 memory: 16131 loss: 4.9740 loss_prob: 2.8173 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 20:11:28 - mmengine - INFO - Epoch(train) [83][25/63] lr: 1.2379e-03 eta: 15:34:45 time: 0.5794 data_time: 0.0229 memory: 16131 loss: 4.9756 loss_prob: 2.8170 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 20:11:31 - mmengine - INFO - Epoch(train) [83][30/63] lr: 1.2379e-03 eta: 15:34:05 time: 0.5619 data_time: 0.0298 memory: 16131 loss: 4.9713 loss_prob: 2.8174 loss_thr: 1.1540 loss_db: 1.0000 2022/10/25 20:11:33 - mmengine - INFO - Epoch(train) [83][35/63] lr: 1.2379e-03 eta: 15:34:05 time: 0.5155 data_time: 0.0152 memory: 16131 loss: 4.9688 loss_prob: 2.8180 loss_thr: 1.1508 loss_db: 1.0000 2022/10/25 20:11:36 - mmengine - INFO - Epoch(train) [83][40/63] lr: 1.2379e-03 eta: 15:33:19 time: 0.5142 data_time: 0.0100 memory: 16131 loss: 4.9700 loss_prob: 2.8176 loss_thr: 1.1524 loss_db: 1.0000 2022/10/25 20:11:38 - mmengine - INFO - Epoch(train) [83][45/63] lr: 1.2379e-03 eta: 15:33:19 time: 0.4985 data_time: 0.0097 memory: 16131 loss: 4.9711 loss_prob: 2.8176 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 20:11:41 - mmengine - INFO - Epoch(train) [83][50/63] lr: 1.2379e-03 eta: 15:32:31 time: 0.5016 data_time: 0.0150 memory: 16131 loss: 4.9735 loss_prob: 2.8179 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 20:11:44 - mmengine - INFO - Epoch(train) [83][55/63] lr: 1.2379e-03 eta: 15:32:31 time: 0.6036 data_time: 0.0220 memory: 16131 loss: 4.9709 loss_prob: 2.8180 loss_thr: 1.1529 loss_db: 1.0000 2022/10/25 20:11:49 - mmengine - INFO - Epoch(train) [83][60/63] lr: 1.2379e-03 eta: 15:32:26 time: 0.8168 data_time: 0.0113 memory: 16131 loss: 4.9636 loss_prob: 2.8172 loss_thr: 1.1464 loss_db: 1.0000 2022/10/25 20:11:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:12:00 - mmengine - INFO - Epoch(train) [84][5/63] lr: 1.2530e-03 eta: 15:32:26 time: 1.2748 data_time: 0.2362 memory: 16131 loss: 4.9653 loss_prob: 2.8164 loss_thr: 1.1488 loss_db: 1.0000 2022/10/25 20:12:03 - mmengine - INFO - Epoch(train) [84][10/63] lr: 1.2530e-03 eta: 15:32:43 time: 1.2359 data_time: 0.2317 memory: 16131 loss: 4.9686 loss_prob: 2.8168 loss_thr: 1.1518 loss_db: 1.0000 2022/10/25 20:12:07 - mmengine - INFO - Epoch(train) [84][15/63] lr: 1.2530e-03 eta: 15:32:43 time: 0.7629 data_time: 0.0047 memory: 16131 loss: 4.9720 loss_prob: 2.8179 loss_thr: 1.1542 loss_db: 1.0000 2022/10/25 20:12:10 - mmengine - INFO - Epoch(train) [84][20/63] lr: 1.2530e-03 eta: 15:32:18 time: 0.6653 data_time: 0.0059 memory: 16131 loss: 4.9738 loss_prob: 2.8178 loss_thr: 1.1561 loss_db: 1.0000 2022/10/25 20:12:14 - mmengine - INFO - Epoch(train) [84][25/63] lr: 1.2530e-03 eta: 15:32:18 time: 0.6267 data_time: 0.0337 memory: 16131 loss: 4.9709 loss_prob: 2.8177 loss_thr: 1.1532 loss_db: 1.0000 2022/10/25 20:12:16 - mmengine - INFO - Epoch(train) [84][30/63] lr: 1.2530e-03 eta: 15:31:53 time: 0.6661 data_time: 0.0328 memory: 16131 loss: 4.9753 loss_prob: 2.8179 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 20:12:20 - mmengine - INFO - Epoch(train) [84][35/63] lr: 1.2530e-03 eta: 15:31:53 time: 0.6818 data_time: 0.0072 memory: 16131 loss: 4.9735 loss_prob: 2.8176 loss_thr: 1.1559 loss_db: 1.0000 2022/10/25 20:12:23 - mmengine - INFO - Epoch(train) [84][40/63] lr: 1.2530e-03 eta: 15:31:31 time: 0.6942 data_time: 0.0068 memory: 16131 loss: 4.9709 loss_prob: 2.8174 loss_thr: 1.1535 loss_db: 1.0000 2022/10/25 20:12:28 - mmengine - INFO - Epoch(train) [84][45/63] lr: 1.2530e-03 eta: 15:31:31 time: 0.7217 data_time: 0.0071 memory: 16131 loss: 4.9758 loss_prob: 2.8165 loss_thr: 1.1592 loss_db: 1.0000 2022/10/25 20:12:32 - mmengine - INFO - Epoch(train) [84][50/63] lr: 1.2530e-03 eta: 15:31:30 time: 0.8438 data_time: 0.0240 memory: 16131 loss: 4.9749 loss_prob: 2.8166 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 20:12:36 - mmengine - INFO - Epoch(train) [84][55/63] lr: 1.2530e-03 eta: 15:31:30 time: 0.8069 data_time: 0.0217 memory: 16131 loss: 4.9717 loss_prob: 2.8170 loss_thr: 1.1548 loss_db: 1.0000 2022/10/25 20:12:39 - mmengine - INFO - Epoch(train) [84][60/63] lr: 1.2530e-03 eta: 15:31:13 time: 0.7261 data_time: 0.0048 memory: 16131 loss: 4.9708 loss_prob: 2.8164 loss_thr: 1.1544 loss_db: 1.0000 2022/10/25 20:12:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:12:45 - mmengine - INFO - Epoch(train) [85][5/63] lr: 1.2681e-03 eta: 15:31:13 time: 0.7328 data_time: 0.1702 memory: 16131 loss: 4.9688 loss_prob: 2.8173 loss_thr: 1.1515 loss_db: 1.0000 2022/10/25 20:12:48 - mmengine - INFO - Epoch(train) [85][10/63] lr: 1.2681e-03 eta: 15:30:25 time: 0.7483 data_time: 0.1719 memory: 16131 loss: 4.9645 loss_prob: 2.8165 loss_thr: 1.1481 loss_db: 1.0000 2022/10/25 20:12:50 - mmengine - INFO - Epoch(train) [85][15/63] lr: 1.2681e-03 eta: 15:30:25 time: 0.5240 data_time: 0.0078 memory: 16131 loss: 4.9708 loss_prob: 2.8156 loss_thr: 1.1552 loss_db: 1.0000 2022/10/25 20:12:53 - mmengine - INFO - Epoch(train) [85][20/63] lr: 1.2681e-03 eta: 15:29:39 time: 0.5099 data_time: 0.0055 memory: 16131 loss: 4.9760 loss_prob: 2.8159 loss_thr: 1.1601 loss_db: 1.0000 2022/10/25 20:12:55 - mmengine - INFO - Epoch(train) [85][25/63] lr: 1.2681e-03 eta: 15:29:39 time: 0.5006 data_time: 0.0069 memory: 16131 loss: 4.9743 loss_prob: 2.8164 loss_thr: 1.1579 loss_db: 1.0000 2022/10/25 20:12:59 - mmengine - INFO - Epoch(train) [85][30/63] lr: 1.2681e-03 eta: 15:29:05 time: 0.5918 data_time: 0.0314 memory: 16131 loss: 4.9745 loss_prob: 2.8161 loss_thr: 1.1584 loss_db: 1.0000 2022/10/25 20:13:02 - mmengine - INFO - Epoch(train) [85][35/63] lr: 1.2681e-03 eta: 15:29:05 time: 0.6319 data_time: 0.0309 memory: 16131 loss: 4.9723 loss_prob: 2.8167 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:13:07 - mmengine - INFO - Epoch(train) [85][40/63] lr: 1.2681e-03 eta: 15:28:58 time: 0.8015 data_time: 0.0069 memory: 16131 loss: 4.9673 loss_prob: 2.8168 loss_thr: 1.1505 loss_db: 1.0000 2022/10/25 20:13:13 - mmengine - INFO - Epoch(train) [85][45/63] lr: 1.2681e-03 eta: 15:28:58 time: 1.1677 data_time: 0.0061 memory: 16131 loss: 4.9674 loss_prob: 2.8164 loss_thr: 1.1510 loss_db: 1.0000 2022/10/25 20:13:19 - mmengine - INFO - Epoch(train) [85][50/63] lr: 1.2681e-03 eta: 15:29:39 time: 1.1674 data_time: 0.0079 memory: 16131 loss: 4.9696 loss_prob: 2.8162 loss_thr: 1.1534 loss_db: 1.0000 2022/10/25 20:13:21 - mmengine - INFO - Epoch(train) [85][55/63] lr: 1.2681e-03 eta: 15:29:39 time: 0.7937 data_time: 0.0201 memory: 16131 loss: 4.9716 loss_prob: 2.8166 loss_thr: 1.1551 loss_db: 1.0000 2022/10/25 20:13:26 - mmengine - INFO - Epoch(train) [85][60/63] lr: 1.2681e-03 eta: 15:29:23 time: 0.7321 data_time: 0.0193 memory: 16131 loss: 4.9673 loss_prob: 2.8163 loss_thr: 1.1511 loss_db: 1.0000 2022/10/25 20:13:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:13:33 - mmengine - INFO - Epoch(train) [86][5/63] lr: 1.2831e-03 eta: 15:29:23 time: 0.8820 data_time: 0.2079 memory: 16131 loss: 4.9729 loss_prob: 2.8166 loss_thr: 1.1564 loss_db: 0.9999 2022/10/25 20:13:39 - mmengine - INFO - Epoch(train) [86][10/63] lr: 1.2831e-03 eta: 15:29:25 time: 1.1233 data_time: 0.2125 memory: 16131 loss: 4.9709 loss_prob: 2.8170 loss_thr: 1.1540 loss_db: 1.0000 2022/10/25 20:13:45 - mmengine - INFO - Epoch(train) [86][15/63] lr: 1.2831e-03 eta: 15:29:25 time: 1.1484 data_time: 0.0151 memory: 16131 loss: 4.9694 loss_prob: 2.8171 loss_thr: 1.1524 loss_db: 1.0000 2022/10/25 20:13:47 - mmengine - INFO - Epoch(train) [86][20/63] lr: 1.2831e-03 eta: 15:29:17 time: 0.7983 data_time: 0.0096 memory: 16131 loss: 4.9637 loss_prob: 2.8173 loss_thr: 1.1464 loss_db: 0.9999 2022/10/25 20:13:50 - mmengine - INFO - Epoch(train) [86][25/63] lr: 1.2831e-03 eta: 15:29:17 time: 0.5317 data_time: 0.0269 memory: 16131 loss: 4.9638 loss_prob: 2.8167 loss_thr: 1.1472 loss_db: 0.9999 2022/10/25 20:13:53 - mmengine - INFO - Epoch(train) [86][30/63] lr: 1.2831e-03 eta: 15:28:40 time: 0.5673 data_time: 0.0288 memory: 16131 loss: 4.9753 loss_prob: 2.8167 loss_thr: 1.1586 loss_db: 1.0000 2022/10/25 20:13:55 - mmengine - INFO - Epoch(train) [86][35/63] lr: 1.2831e-03 eta: 15:28:40 time: 0.5359 data_time: 0.0217 memory: 16131 loss: 4.9742 loss_prob: 2.8178 loss_thr: 1.1564 loss_db: 0.9999 2022/10/25 20:13:58 - mmengine - INFO - Epoch(train) [86][40/63] lr: 1.2831e-03 eta: 15:27:59 time: 0.5443 data_time: 0.0249 memory: 16131 loss: 4.9715 loss_prob: 2.8187 loss_thr: 1.1529 loss_db: 0.9999 2022/10/25 20:14:02 - mmengine - INFO - Epoch(train) [86][45/63] lr: 1.2831e-03 eta: 15:27:59 time: 0.6107 data_time: 0.0124 memory: 16131 loss: 4.9740 loss_prob: 2.8188 loss_thr: 1.1553 loss_db: 1.0000 2022/10/25 20:14:05 - mmengine - INFO - Epoch(train) [86][50/63] lr: 1.2831e-03 eta: 15:27:30 time: 0.6262 data_time: 0.0199 memory: 16131 loss: 4.9749 loss_prob: 2.8200 loss_thr: 1.1550 loss_db: 1.0000 2022/10/25 20:14:08 - mmengine - INFO - Epoch(train) [86][55/63] lr: 1.2831e-03 eta: 15:27:30 time: 0.6810 data_time: 0.0205 memory: 16131 loss: 4.9739 loss_prob: 2.8208 loss_thr: 1.1531 loss_db: 1.0000 2022/10/25 20:14:11 - mmengine - INFO - Epoch(train) [86][60/63] lr: 1.2831e-03 eta: 15:27:03 time: 0.6503 data_time: 0.0098 memory: 16131 loss: 4.9714 loss_prob: 2.8201 loss_thr: 1.1513 loss_db: 1.0000 2022/10/25 20:14:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:14:20 - mmengine - INFO - Epoch(train) [87][5/63] lr: 1.2982e-03 eta: 15:27:03 time: 0.9720 data_time: 0.1799 memory: 16131 loss: 4.9698 loss_prob: 2.8202 loss_thr: 1.1496 loss_db: 1.0000 2022/10/25 20:14:23 - mmengine - INFO - Epoch(train) [87][10/63] lr: 1.2982e-03 eta: 15:26:40 time: 0.9267 data_time: 0.1682 memory: 16131 loss: 4.9695 loss_prob: 2.8191 loss_thr: 1.1505 loss_db: 0.9999 2022/10/25 20:14:26 - mmengine - INFO - Epoch(train) [87][15/63] lr: 1.2982e-03 eta: 15:26:40 time: 0.5987 data_time: 0.0058 memory: 16131 loss: 4.9722 loss_prob: 2.8177 loss_thr: 1.1546 loss_db: 1.0000 2022/10/25 20:14:29 - mmengine - INFO - Epoch(train) [87][20/63] lr: 1.2982e-03 eta: 15:26:06 time: 0.5962 data_time: 0.0066 memory: 16131 loss: 4.9706 loss_prob: 2.8176 loss_thr: 1.1530 loss_db: 1.0000 2022/10/25 20:14:31 - mmengine - INFO - Epoch(train) [87][25/63] lr: 1.2982e-03 eta: 15:26:06 time: 0.5506 data_time: 0.0120 memory: 16131 loss: 4.9676 loss_prob: 2.8167 loss_thr: 1.1509 loss_db: 1.0000 2022/10/25 20:14:34 - mmengine - INFO - Epoch(train) [87][30/63] lr: 1.2982e-03 eta: 15:25:27 time: 0.5445 data_time: 0.0316 memory: 16131 loss: 4.9663 loss_prob: 2.8154 loss_thr: 1.1510 loss_db: 0.9999 2022/10/25 20:14:37 - mmengine - INFO - Epoch(train) [87][35/63] lr: 1.2982e-03 eta: 15:25:27 time: 0.5994 data_time: 0.0258 memory: 16131 loss: 4.9625 loss_prob: 2.8150 loss_thr: 1.1476 loss_db: 0.9999 2022/10/25 20:14:43 - mmengine - INFO - Epoch(train) [87][40/63] lr: 1.2982e-03 eta: 15:25:32 time: 0.8942 data_time: 0.0059 memory: 16131 loss: 4.9614 loss_prob: 2.8158 loss_thr: 1.1456 loss_db: 0.9999 2022/10/25 20:14:48 - mmengine - INFO - Epoch(train) [87][45/63] lr: 1.2982e-03 eta: 15:25:32 time: 1.1188 data_time: 0.0056 memory: 16131 loss: 4.9697 loss_prob: 2.8159 loss_thr: 1.1539 loss_db: 0.9999 2022/10/25 20:14:51 - mmengine - INFO - Epoch(train) [87][50/63] lr: 1.2982e-03 eta: 15:25:24 time: 0.7932 data_time: 0.0154 memory: 16131 loss: 4.9773 loss_prob: 2.8154 loss_thr: 1.1619 loss_db: 1.0000 2022/10/25 20:14:55 - mmengine - INFO - Epoch(train) [87][55/63] lr: 1.2982e-03 eta: 15:25:24 time: 0.6962 data_time: 0.0268 memory: 16131 loss: 4.9700 loss_prob: 2.8160 loss_thr: 1.1541 loss_db: 0.9999 2022/10/25 20:14:59 - mmengine - INFO - Epoch(train) [87][60/63] lr: 1.2982e-03 eta: 15:25:21 time: 0.8310 data_time: 0.0176 memory: 16131 loss: 4.9606 loss_prob: 2.8154 loss_thr: 1.1453 loss_db: 0.9999 2022/10/25 20:15:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:15:09 - mmengine - INFO - Epoch(train) [88][5/63] lr: 1.3132e-03 eta: 15:25:21 time: 1.1332 data_time: 0.1986 memory: 16131 loss: 4.9679 loss_prob: 2.8167 loss_thr: 1.1513 loss_db: 0.9999 2022/10/25 20:15:15 - mmengine - INFO - Epoch(train) [88][10/63] lr: 1.3132e-03 eta: 15:25:57 time: 1.3878 data_time: 0.2022 memory: 16131 loss: 4.9658 loss_prob: 2.8167 loss_thr: 1.1491 loss_db: 0.9999 2022/10/25 20:15:20 - mmengine - INFO - Epoch(train) [88][15/63] lr: 1.3132e-03 eta: 15:25:57 time: 1.0951 data_time: 0.0084 memory: 16131 loss: 4.9617 loss_prob: 2.8167 loss_thr: 1.1451 loss_db: 0.9999 2022/10/25 20:15:24 - mmengine - INFO - Epoch(train) [88][20/63] lr: 1.3132e-03 eta: 15:25:54 time: 0.8316 data_time: 0.0051 memory: 16131 loss: 4.9659 loss_prob: 2.8177 loss_thr: 1.1484 loss_db: 0.9999 2022/10/25 20:15:27 - mmengine - INFO - Epoch(train) [88][25/63] lr: 1.3132e-03 eta: 15:25:54 time: 0.6449 data_time: 0.0197 memory: 16131 loss: 4.9740 loss_prob: 2.8174 loss_thr: 1.1567 loss_db: 0.9999 2022/10/25 20:15:30 - mmengine - INFO - Epoch(train) [88][30/63] lr: 1.3132e-03 eta: 15:25:28 time: 0.6533 data_time: 0.0341 memory: 16131 loss: 4.9690 loss_prob: 2.8167 loss_thr: 1.1523 loss_db: 0.9999 2022/10/25 20:15:34 - mmengine - INFO - Epoch(train) [88][35/63] lr: 1.3132e-03 eta: 15:25:28 time: 0.6873 data_time: 0.0196 memory: 16131 loss: 4.9692 loss_prob: 2.8174 loss_thr: 1.1519 loss_db: 0.9999 2022/10/25 20:15:38 - mmengine - INFO - Epoch(train) [88][40/63] lr: 1.3132e-03 eta: 15:25:14 time: 0.7416 data_time: 0.0050 memory: 16131 loss: 4.9697 loss_prob: 2.8183 loss_thr: 1.1515 loss_db: 0.9999 2022/10/25 20:15:40 - mmengine - INFO - Epoch(train) [88][45/63] lr: 1.3132e-03 eta: 15:25:14 time: 0.6807 data_time: 0.0057 memory: 16131 loss: 4.9697 loss_prob: 2.8190 loss_thr: 1.1508 loss_db: 0.9999 2022/10/25 20:15:45 - mmengine - INFO - Epoch(train) [88][50/63] lr: 1.3132e-03 eta: 15:24:55 time: 0.7071 data_time: 0.0133 memory: 16131 loss: 4.9626 loss_prob: 2.8210 loss_thr: 1.1417 loss_db: 0.9999 2022/10/25 20:15:49 - mmengine - INFO - Epoch(train) [88][55/63] lr: 1.3132e-03 eta: 15:24:55 time: 0.8292 data_time: 0.0246 memory: 16131 loss: 4.9640 loss_prob: 2.8198 loss_thr: 1.1443 loss_db: 0.9999 2022/10/25 20:15:52 - mmengine - INFO - Epoch(train) [88][60/63] lr: 1.3132e-03 eta: 15:24:36 time: 0.7057 data_time: 0.0191 memory: 16131 loss: 4.9732 loss_prob: 2.8177 loss_thr: 1.1555 loss_db: 1.0000 2022/10/25 20:15:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:16:00 - mmengine - INFO - Epoch(train) [89][5/63] lr: 1.3283e-03 eta: 15:24:36 time: 0.9290 data_time: 0.2141 memory: 16131 loss: 4.9805 loss_prob: 2.8219 loss_thr: 1.1587 loss_db: 1.0000 2022/10/25 20:16:04 - mmengine - INFO - Epoch(train) [89][10/63] lr: 1.3283e-03 eta: 15:24:35 time: 1.0982 data_time: 0.2135 memory: 16131 loss: 4.9740 loss_prob: 2.8170 loss_thr: 1.1570 loss_db: 1.0000 2022/10/25 20:16:07 - mmengine - INFO - Epoch(train) [89][15/63] lr: 1.3283e-03 eta: 15:24:35 time: 0.7006 data_time: 0.0078 memory: 16131 loss: 4.9755 loss_prob: 2.8194 loss_thr: 1.1562 loss_db: 1.0000 2022/10/25 20:16:09 - mmengine - INFO - Epoch(train) [89][20/63] lr: 1.3283e-03 eta: 15:23:54 time: 0.5309 data_time: 0.0094 memory: 16131 loss: 4.9775 loss_prob: 2.8195 loss_thr: 1.1580 loss_db: 1.0000 2022/10/25 20:16:12 - mmengine - INFO - Epoch(train) [89][25/63] lr: 1.3283e-03 eta: 15:23:54 time: 0.5576 data_time: 0.0300 memory: 16131 loss: 4.9727 loss_prob: 2.8168 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 20:16:15 - mmengine - INFO - Epoch(train) [89][30/63] lr: 1.3283e-03 eta: 15:23:17 time: 0.5591 data_time: 0.0280 memory: 16131 loss: 4.9729 loss_prob: 2.8163 loss_thr: 1.1567 loss_db: 1.0000 2022/10/25 20:16:18 - mmengine - INFO - Epoch(train) [89][35/63] lr: 1.3283e-03 eta: 15:23:17 time: 0.5363 data_time: 0.0067 memory: 16131 loss: 4.9719 loss_prob: 2.8159 loss_thr: 1.1560 loss_db: 1.0000 2022/10/25 20:16:20 - mmengine - INFO - Epoch(train) [89][40/63] lr: 1.3283e-03 eta: 15:22:35 time: 0.5220 data_time: 0.0072 memory: 16131 loss: 4.9681 loss_prob: 2.8159 loss_thr: 1.1522 loss_db: 1.0000 2022/10/25 20:16:23 - mmengine - INFO - Epoch(train) [89][45/63] lr: 1.3283e-03 eta: 15:22:35 time: 0.5667 data_time: 0.0081 memory: 16131 loss: 4.9706 loss_prob: 2.8163 loss_thr: 1.1544 loss_db: 0.9999 2022/10/25 20:16:27 - mmengine - INFO - Epoch(train) [89][50/63] lr: 1.3283e-03 eta: 15:22:19 time: 0.7210 data_time: 0.0286 memory: 16131 loss: 4.9721 loss_prob: 2.8163 loss_thr: 1.1559 loss_db: 0.9999 2022/10/25 20:16:33 - mmengine - INFO - Epoch(train) [89][55/63] lr: 1.3283e-03 eta: 15:22:19 time: 0.9295 data_time: 0.0289 memory: 16131 loss: 4.9599 loss_prob: 2.8165 loss_thr: 1.1435 loss_db: 0.9999 2022/10/25 20:16:36 - mmengine - INFO - Epoch(train) [89][60/63] lr: 1.3283e-03 eta: 15:22:24 time: 0.9013 data_time: 0.0087 memory: 16131 loss: 4.9648 loss_prob: 2.8208 loss_thr: 1.1442 loss_db: 0.9998 2022/10/25 20:16:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:16:44 - mmengine - INFO - Epoch(train) [90][5/63] lr: 1.3434e-03 eta: 15:22:24 time: 0.9154 data_time: 0.2042 memory: 16131 loss: 4.9692 loss_prob: 2.8198 loss_thr: 1.1495 loss_db: 0.9999 2022/10/25 20:16:50 - mmengine - INFO - Epoch(train) [90][10/63] lr: 1.3434e-03 eta: 15:22:28 time: 1.1359 data_time: 0.1995 memory: 16131 loss: 4.9693 loss_prob: 2.8155 loss_thr: 1.1540 loss_db: 0.9999 2022/10/25 20:16:53 - mmengine - INFO - Epoch(train) [90][15/63] lr: 1.3434e-03 eta: 15:22:28 time: 0.8444 data_time: 0.0051 memory: 16131 loss: 4.9553 loss_prob: 2.8159 loss_thr: 1.1395 loss_db: 0.9999 2022/10/25 20:16:56 - mmengine - INFO - Epoch(train) [90][20/63] lr: 1.3434e-03 eta: 15:21:54 time: 0.5873 data_time: 0.0084 memory: 16131 loss: 4.9483 loss_prob: 2.8184 loss_thr: 1.1301 loss_db: 0.9998 2022/10/25 20:16:58 - mmengine - INFO - Epoch(train) [90][25/63] lr: 1.3434e-03 eta: 15:21:54 time: 0.5216 data_time: 0.0219 memory: 16131 loss: 4.9528 loss_prob: 2.8178 loss_thr: 1.1352 loss_db: 0.9998 2022/10/25 20:17:02 - mmengine - INFO - Epoch(train) [90][30/63] lr: 1.3434e-03 eta: 15:21:24 time: 0.6100 data_time: 0.0473 memory: 16131 loss: 4.9600 loss_prob: 2.8160 loss_thr: 1.1440 loss_db: 0.9999 2022/10/25 20:17:05 - mmengine - INFO - Epoch(train) [90][35/63] lr: 1.3434e-03 eta: 15:21:24 time: 0.6706 data_time: 0.0333 memory: 16131 loss: 4.9611 loss_prob: 2.8163 loss_thr: 1.1449 loss_db: 0.9999 2022/10/25 20:17:08 - mmengine - INFO - Epoch(train) [90][40/63] lr: 1.3434e-03 eta: 15:20:54 time: 0.6114 data_time: 0.0049 memory: 16131 loss: 4.9485 loss_prob: 2.8155 loss_thr: 1.1336 loss_db: 0.9994 2022/10/25 20:17:11 - mmengine - INFO - Epoch(train) [90][45/63] lr: 1.3434e-03 eta: 15:20:54 time: 0.5961 data_time: 0.0096 memory: 16131 loss: 4.9517 loss_prob: 2.8155 loss_thr: 1.1368 loss_db: 0.9995 2022/10/25 20:17:14 - mmengine - INFO - Epoch(train) [90][50/63] lr: 1.3434e-03 eta: 15:20:20 time: 0.5807 data_time: 0.0373 memory: 16131 loss: 4.9565 loss_prob: 2.8159 loss_thr: 1.1408 loss_db: 0.9999 2022/10/25 20:17:16 - mmengine - INFO - Epoch(train) [90][55/63] lr: 1.3434e-03 eta: 15:20:20 time: 0.5565 data_time: 0.0335 memory: 16131 loss: 4.9617 loss_prob: 2.8162 loss_thr: 1.1457 loss_db: 0.9998 2022/10/25 20:17:21 - mmengine - INFO - Epoch(train) [90][60/63] lr: 1.3434e-03 eta: 15:20:00 time: 0.6921 data_time: 0.0066 memory: 16131 loss: 4.9612 loss_prob: 2.8159 loss_thr: 1.1457 loss_db: 0.9997 2022/10/25 20:17:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:17:26 - mmengine - INFO - Epoch(train) [91][5/63] lr: 1.3584e-03 eta: 15:20:00 time: 0.8325 data_time: 0.1779 memory: 16131 loss: 4.9735 loss_prob: 2.8163 loss_thr: 1.1576 loss_db: 0.9997 2022/10/25 20:17:29 - mmengine - INFO - Epoch(train) [91][10/63] lr: 1.3584e-03 eta: 15:19:12 time: 0.7137 data_time: 0.1786 memory: 16131 loss: 4.9553 loss_prob: 2.8159 loss_thr: 1.1397 loss_db: 0.9997 2022/10/25 20:17:32 - mmengine - INFO - Epoch(train) [91][15/63] lr: 1.3584e-03 eta: 15:19:12 time: 0.5333 data_time: 0.0086 memory: 16131 loss: 4.9384 loss_prob: 2.8182 loss_thr: 1.1239 loss_db: 0.9963 2022/10/25 20:17:34 - mmengine - INFO - Epoch(train) [91][20/63] lr: 1.3584e-03 eta: 15:18:31 time: 0.5214 data_time: 0.0063 memory: 16131 loss: 4.9407 loss_prob: 2.8199 loss_thr: 1.1262 loss_db: 0.9945 2022/10/25 20:17:37 - mmengine - INFO - Epoch(train) [91][25/63] lr: 1.3584e-03 eta: 15:18:31 time: 0.5515 data_time: 0.0160 memory: 16131 loss: 4.9532 loss_prob: 2.8192 loss_thr: 1.1423 loss_db: 0.9917 2022/10/25 20:17:41 - mmengine - INFO - Epoch(train) [91][30/63] lr: 1.3584e-03 eta: 15:18:04 time: 0.6343 data_time: 0.0363 memory: 16131 loss: 4.9580 loss_prob: 2.8196 loss_thr: 1.1558 loss_db: 0.9826 2022/10/25 20:17:43 - mmengine - INFO - Epoch(train) [91][35/63] lr: 1.3584e-03 eta: 15:18:04 time: 0.5795 data_time: 0.0263 memory: 16131 loss: 4.9369 loss_prob: 2.8191 loss_thr: 1.1589 loss_db: 0.9589 2022/10/25 20:17:46 - mmengine - INFO - Epoch(train) [91][40/63] lr: 1.3584e-03 eta: 15:17:28 time: 0.5566 data_time: 0.0116 memory: 16131 loss: 4.9282 loss_prob: 2.8189 loss_thr: 1.1591 loss_db: 0.9502 2022/10/25 20:17:49 - mmengine - INFO - Epoch(train) [91][45/63] lr: 1.3584e-03 eta: 15:17:28 time: 0.6009 data_time: 0.0112 memory: 16131 loss: 4.9352 loss_prob: 2.8199 loss_thr: 1.1577 loss_db: 0.9576 2022/10/25 20:17:52 - mmengine - INFO - Epoch(train) [91][50/63] lr: 1.3584e-03 eta: 15:16:52 time: 0.5619 data_time: 0.0124 memory: 16131 loss: 4.9407 loss_prob: 2.8207 loss_thr: 1.1684 loss_db: 0.9516 2022/10/25 20:17:55 - mmengine - INFO - Epoch(train) [91][55/63] lr: 1.3584e-03 eta: 15:16:52 time: 0.5833 data_time: 0.0377 memory: 16131 loss: 4.8934 loss_prob: 2.8219 loss_thr: 1.1688 loss_db: 0.9027 2022/10/25 20:18:01 - mmengine - INFO - Epoch(train) [91][60/63] lr: 1.3584e-03 eta: 15:17:01 time: 0.9255 data_time: 0.0307 memory: 16131 loss: 4.8260 loss_prob: 2.8209 loss_thr: 1.1622 loss_db: 0.8429 2022/10/25 20:18:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:18:11 - mmengine - INFO - Epoch(train) [92][5/63] lr: 1.3735e-03 eta: 15:17:01 time: 1.1988 data_time: 0.1745 memory: 16131 loss: 4.9667 loss_prob: 2.8290 loss_thr: 1.1658 loss_db: 0.9719 2022/10/25 20:18:15 - mmengine - INFO - Epoch(train) [92][10/63] lr: 1.3735e-03 eta: 15:17:21 time: 1.2686 data_time: 0.1695 memory: 16131 loss: 4.9873 loss_prob: 2.8269 loss_thr: 1.1605 loss_db: 0.9999 2022/10/25 20:18:19 - mmengine - INFO - Epoch(train) [92][15/63] lr: 1.3735e-03 eta: 15:17:21 time: 0.8405 data_time: 0.0101 memory: 16131 loss: 4.9825 loss_prob: 2.8225 loss_thr: 1.1601 loss_db: 0.9999 2022/10/25 20:18:22 - mmengine - INFO - Epoch(train) [92][20/63] lr: 1.3735e-03 eta: 15:17:02 time: 0.6934 data_time: 0.0132 memory: 16131 loss: 4.9862 loss_prob: 2.8240 loss_thr: 1.1622 loss_db: 0.9999 2022/10/25 20:18:26 - mmengine - INFO - Epoch(train) [92][25/63] lr: 1.3735e-03 eta: 15:17:02 time: 0.6542 data_time: 0.0094 memory: 16131 loss: 4.9812 loss_prob: 2.8224 loss_thr: 1.1589 loss_db: 0.9999 2022/10/25 20:18:29 - mmengine - INFO - Epoch(train) [92][30/63] lr: 1.3735e-03 eta: 15:16:42 time: 0.6914 data_time: 0.0368 memory: 16131 loss: 4.9732 loss_prob: 2.8189 loss_thr: 1.1543 loss_db: 0.9999 2022/10/25 20:18:34 - mmengine - INFO - Epoch(train) [92][35/63] lr: 1.3735e-03 eta: 15:16:42 time: 0.8103 data_time: 0.0439 memory: 16131 loss: 4.9953 loss_prob: 2.8351 loss_thr: 1.1602 loss_db: 0.9999 2022/10/25 20:18:38 - mmengine - INFO - Epoch(train) [92][40/63] lr: 1.3735e-03 eta: 15:16:47 time: 0.8901 data_time: 0.0184 memory: 16131 loss: 4.9997 loss_prob: 2.8366 loss_thr: 1.1632 loss_db: 0.9999 2022/10/25 20:18:43 - mmengine - INFO - Epoch(train) [92][45/63] lr: 1.3735e-03 eta: 15:16:47 time: 0.9153 data_time: 0.0113 memory: 16131 loss: 4.9758 loss_prob: 2.8204 loss_thr: 1.1555 loss_db: 0.9999 2022/10/25 20:18:48 - mmengine - INFO - Epoch(train) [92][50/63] lr: 1.3735e-03 eta: 15:17:00 time: 0.9672 data_time: 0.0185 memory: 16131 loss: 4.9749 loss_prob: 2.8185 loss_thr: 1.1565 loss_db: 0.9999 2022/10/25 20:18:53 - mmengine - INFO - Epoch(train) [92][55/63] lr: 1.3735e-03 eta: 15:17:00 time: 0.9673 data_time: 0.0220 memory: 16131 loss: 4.9763 loss_prob: 2.8183 loss_thr: 1.1581 loss_db: 0.9999 2022/10/25 20:18:58 - mmengine - INFO - Epoch(train) [92][60/63] lr: 1.3735e-03 eta: 15:17:17 time: 0.9916 data_time: 0.0121 memory: 16131 loss: 4.9747 loss_prob: 2.8179 loss_thr: 1.1569 loss_db: 0.9999 2022/10/25 20:19:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:19:07 - mmengine - INFO - Epoch(train) [93][5/63] lr: 1.3885e-03 eta: 15:17:17 time: 1.1797 data_time: 0.2061 memory: 16131 loss: 4.9654 loss_prob: 2.8182 loss_thr: 1.1473 loss_db: 0.9999 2022/10/25 20:19:10 - mmengine - INFO - Epoch(train) [93][10/63] lr: 1.3885e-03 eta: 15:17:06 time: 1.0220 data_time: 0.2079 memory: 16131 loss: 4.9618 loss_prob: 2.8174 loss_thr: 1.1446 loss_db: 0.9998 2022/10/25 20:19:16 - mmengine - INFO - Epoch(train) [93][15/63] lr: 1.3885e-03 eta: 15:17:06 time: 0.9218 data_time: 0.0108 memory: 16131 loss: 4.9499 loss_prob: 2.8176 loss_thr: 1.1330 loss_db: 0.9993 2022/10/25 20:19:19 - mmengine - INFO - Epoch(train) [93][20/63] lr: 1.3885e-03 eta: 15:17:06 time: 0.8479 data_time: 0.0079 memory: 16131 loss: 4.9523 loss_prob: 2.8178 loss_thr: 1.1365 loss_db: 0.9980 2022/10/25 20:19:23 - mmengine - INFO - Epoch(train) [93][25/63] lr: 1.3885e-03 eta: 15:17:06 time: 0.6931 data_time: 0.0185 memory: 16131 loss: 4.9521 loss_prob: 2.8175 loss_thr: 1.1382 loss_db: 0.9964 2022/10/25 20:19:26 - mmengine - INFO - Epoch(train) [93][30/63] lr: 1.3885e-03 eta: 15:16:51 time: 0.7351 data_time: 0.0290 memory: 16131 loss: 4.9541 loss_prob: 2.8284 loss_thr: 1.1508 loss_db: 0.9750 2022/10/25 20:19:29 - mmengine - INFO - Epoch(train) [93][35/63] lr: 1.3885e-03 eta: 15:16:51 time: 0.5922 data_time: 0.0224 memory: 16131 loss: 4.9594 loss_prob: 2.8377 loss_thr: 1.1642 loss_db: 0.9575 2022/10/25 20:19:33 - mmengine - INFO - Epoch(train) [93][40/63] lr: 1.3885e-03 eta: 15:16:24 time: 0.6250 data_time: 0.0093 memory: 16131 loss: 4.9294 loss_prob: 2.8360 loss_thr: 1.1606 loss_db: 0.9328 2022/10/25 20:19:36 - mmengine - INFO - Epoch(train) [93][45/63] lr: 1.3885e-03 eta: 15:16:24 time: 0.6526 data_time: 0.0094 memory: 16131 loss: 4.9337 loss_prob: 2.8351 loss_thr: 1.1661 loss_db: 0.9324 2022/10/25 20:19:38 - mmengine - INFO - Epoch(train) [93][50/63] lr: 1.3885e-03 eta: 15:15:50 time: 0.5708 data_time: 0.0158 memory: 16131 loss: 4.9945 loss_prob: 2.8375 loss_thr: 1.1997 loss_db: 0.9572 2022/10/25 20:19:41 - mmengine - INFO - Epoch(train) [93][55/63] lr: 1.3885e-03 eta: 15:15:50 time: 0.5889 data_time: 0.0208 memory: 16131 loss: 5.0126 loss_prob: 2.8365 loss_thr: 1.1988 loss_db: 0.9773 2022/10/25 20:19:44 - mmengine - INFO - Epoch(train) [93][60/63] lr: 1.3885e-03 eta: 15:15:19 time: 0.5911 data_time: 0.0159 memory: 16131 loss: 4.9916 loss_prob: 2.8284 loss_thr: 1.1633 loss_db: 0.9999 2022/10/25 20:19:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:19:52 - mmengine - INFO - Epoch(train) [94][5/63] lr: 1.4036e-03 eta: 15:15:19 time: 0.8567 data_time: 0.2017 memory: 16131 loss: 4.9959 loss_prob: 2.8329 loss_thr: 1.1632 loss_db: 0.9999 2022/10/25 20:19:56 - mmengine - INFO - Epoch(train) [94][10/63] lr: 1.4036e-03 eta: 15:15:09 time: 1.0296 data_time: 0.1974 memory: 16131 loss: 4.9961 loss_prob: 2.8287 loss_thr: 1.1675 loss_db: 0.9999 2022/10/25 20:19:59 - mmengine - INFO - Epoch(train) [94][15/63] lr: 1.4036e-03 eta: 15:15:09 time: 0.7070 data_time: 0.0091 memory: 16131 loss: 4.9787 loss_prob: 2.8192 loss_thr: 1.1595 loss_db: 1.0000 2022/10/25 20:20:05 - mmengine - INFO - Epoch(train) [94][20/63] lr: 1.4036e-03 eta: 15:15:13 time: 0.8882 data_time: 0.0085 memory: 16131 loss: 4.9743 loss_prob: 2.8186 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 20:20:08 - mmengine - INFO - Epoch(train) [94][25/63] lr: 1.4036e-03 eta: 15:15:13 time: 0.8971 data_time: 0.0153 memory: 16131 loss: 4.9778 loss_prob: 2.8214 loss_thr: 1.1565 loss_db: 0.9999 2022/10/25 20:20:12 - mmengine - INFO - Epoch(train) [94][30/63] lr: 1.4036e-03 eta: 15:14:59 time: 0.7346 data_time: 0.0374 memory: 16131 loss: 4.9754 loss_prob: 2.8233 loss_thr: 1.1522 loss_db: 0.9999 2022/10/25 20:20:16 - mmengine - INFO - Epoch(train) [94][35/63] lr: 1.4036e-03 eta: 15:14:59 time: 0.7943 data_time: 0.0302 memory: 16131 loss: 4.9751 loss_prob: 2.8216 loss_thr: 1.1535 loss_db: 0.9999 2022/10/25 20:20:18 - mmengine - INFO - Epoch(train) [94][40/63] lr: 1.4036e-03 eta: 15:14:31 time: 0.6180 data_time: 0.0081 memory: 16131 loss: 4.9752 loss_prob: 2.8187 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 20:20:21 - mmengine - INFO - Epoch(train) [94][45/63] lr: 1.4036e-03 eta: 15:14:31 time: 0.5389 data_time: 0.0070 memory: 16131 loss: 4.9873 loss_prob: 2.8288 loss_thr: 1.1585 loss_db: 0.9999 2022/10/25 20:20:24 - mmengine - INFO - Epoch(train) [94][50/63] lr: 1.4036e-03 eta: 15:13:55 time: 0.5473 data_time: 0.0188 memory: 16131 loss: 4.9903 loss_prob: 2.8316 loss_thr: 1.1588 loss_db: 0.9999 2022/10/25 20:20:27 - mmengine - INFO - Epoch(train) [94][55/63] lr: 1.4036e-03 eta: 15:13:55 time: 0.6063 data_time: 0.0271 memory: 16131 loss: 4.9793 loss_prob: 2.8219 loss_thr: 1.1575 loss_db: 1.0000 2022/10/25 20:20:31 - mmengine - INFO - Epoch(train) [94][60/63] lr: 1.4036e-03 eta: 15:13:36 time: 0.6877 data_time: 0.0158 memory: 16131 loss: 4.9796 loss_prob: 2.8208 loss_thr: 1.1588 loss_db: 1.0000 2022/10/25 20:20:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:20:41 - mmengine - INFO - Epoch(train) [95][5/63] lr: 1.4187e-03 eta: 15:13:36 time: 1.1100 data_time: 0.2066 memory: 16131 loss: 4.9749 loss_prob: 2.8185 loss_thr: 1.1565 loss_db: 1.0000 2022/10/25 20:20:46 - mmengine - INFO - Epoch(train) [95][10/63] lr: 1.4187e-03 eta: 15:14:05 time: 1.3605 data_time: 0.2092 memory: 16131 loss: 4.9742 loss_prob: 2.8206 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 20:20:49 - mmengine - INFO - Epoch(train) [95][15/63] lr: 1.4187e-03 eta: 15:14:05 time: 0.8522 data_time: 0.0088 memory: 16131 loss: 4.9737 loss_prob: 2.8198 loss_thr: 1.1539 loss_db: 1.0000 2022/10/25 20:20:52 - mmengine - INFO - Epoch(train) [95][20/63] lr: 1.4187e-03 eta: 15:13:41 time: 0.6505 data_time: 0.0089 memory: 16131 loss: 4.9796 loss_prob: 2.8240 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:20:56 - mmengine - INFO - Epoch(train) [95][25/63] lr: 1.4187e-03 eta: 15:13:41 time: 0.6707 data_time: 0.0357 memory: 16131 loss: 4.9798 loss_prob: 2.8243 loss_thr: 1.1556 loss_db: 1.0000 2022/10/25 20:20:59 - mmengine - INFO - Epoch(train) [95][30/63] lr: 1.4187e-03 eta: 15:13:13 time: 0.6141 data_time: 0.0329 memory: 16131 loss: 4.9707 loss_prob: 2.8180 loss_thr: 1.1527 loss_db: 1.0000 2022/10/25 20:21:02 - mmengine - INFO - Epoch(train) [95][35/63] lr: 1.4187e-03 eta: 15:13:13 time: 0.5612 data_time: 0.0084 memory: 16131 loss: 4.9718 loss_prob: 2.8182 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 20:21:06 - mmengine - INFO - Epoch(train) [95][40/63] lr: 1.4187e-03 eta: 15:12:58 time: 0.7255 data_time: 0.0078 memory: 16131 loss: 4.9709 loss_prob: 2.8172 loss_thr: 1.1537 loss_db: 1.0000 2022/10/25 20:21:11 - mmengine - INFO - Epoch(train) [95][45/63] lr: 1.4187e-03 eta: 15:12:58 time: 0.8901 data_time: 0.0049 memory: 16131 loss: 4.9690 loss_prob: 2.8167 loss_thr: 1.1523 loss_db: 1.0000 2022/10/25 20:21:15 - mmengine - INFO - Epoch(train) [95][50/63] lr: 1.4187e-03 eta: 15:13:03 time: 0.8968 data_time: 0.0233 memory: 16131 loss: 4.9739 loss_prob: 2.8183 loss_thr: 1.1557 loss_db: 1.0000 2022/10/25 20:21:18 - mmengine - INFO - Epoch(train) [95][55/63] lr: 1.4187e-03 eta: 15:13:03 time: 0.7075 data_time: 0.0234 memory: 16131 loss: 4.9783 loss_prob: 2.8190 loss_thr: 1.1594 loss_db: 1.0000 2022/10/25 20:21:25 - mmengine - INFO - Epoch(train) [95][60/63] lr: 1.4187e-03 eta: 15:13:17 time: 0.9760 data_time: 0.0077 memory: 16131 loss: 4.9752 loss_prob: 2.8191 loss_thr: 1.1562 loss_db: 1.0000 2022/10/25 20:21:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:21:31 - mmengine - INFO - Epoch(train) [96][5/63] lr: 1.4337e-03 eta: 15:13:17 time: 0.9456 data_time: 0.1742 memory: 16131 loss: 4.9767 loss_prob: 2.8193 loss_thr: 1.1574 loss_db: 1.0000 2022/10/25 20:21:34 - mmengine - INFO - Epoch(train) [96][10/63] lr: 1.4337e-03 eta: 15:12:36 time: 0.7590 data_time: 0.1828 memory: 16131 loss: 4.9764 loss_prob: 2.8166 loss_thr: 1.1598 loss_db: 1.0000 2022/10/25 20:21:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:21:38 - mmengine - INFO - Epoch(train) [96][15/63] lr: 1.4337e-03 eta: 15:12:36 time: 0.7356 data_time: 0.0150 memory: 16131 loss: 4.9757 loss_prob: 2.8158 loss_thr: 1.1600 loss_db: 1.0000 2022/10/25 20:21:43 - mmengine - INFO - Epoch(train) [96][20/63] lr: 1.4337e-03 eta: 15:12:42 time: 0.9000 data_time: 0.0092 memory: 16131 loss: 4.9718 loss_prob: 2.8155 loss_thr: 1.1563 loss_db: 1.0000 2022/10/25 20:21:46 - mmengine - INFO - Epoch(train) [96][25/63] lr: 1.4337e-03 eta: 15:12:42 time: 0.7510 data_time: 0.0163 memory: 16131 loss: 4.9685 loss_prob: 2.8149 loss_thr: 1.1537 loss_db: 0.9999 2022/10/25 20:21:49 - mmengine - INFO - Epoch(train) [96][30/63] lr: 1.4337e-03 eta: 15:12:09 time: 0.5776 data_time: 0.0325 memory: 16131 loss: 4.9693 loss_prob: 2.8172 loss_thr: 1.1522 loss_db: 0.9999 2022/10/25 20:21:54 - mmengine - INFO - Epoch(train) [96][35/63] lr: 1.4337e-03 eta: 15:12:09 time: 0.8676 data_time: 0.0369 memory: 16131 loss: 4.9687 loss_prob: 2.8173 loss_thr: 1.1515 loss_db: 0.9999 2022/10/25 20:21:57 - mmengine - INFO - Epoch(train) [96][40/63] lr: 1.4337e-03 eta: 15:12:05 time: 0.8181 data_time: 0.0174 memory: 16131 loss: 4.9649 loss_prob: 2.8147 loss_thr: 1.1502 loss_db: 0.9999 2022/10/25 20:22:04 - mmengine - INFO - Epoch(train) [96][45/63] lr: 1.4337e-03 eta: 15:12:05 time: 0.9920 data_time: 0.0060 memory: 16131 loss: 4.9628 loss_prob: 2.8147 loss_thr: 1.1482 loss_db: 0.9999 2022/10/25 20:22:08 - mmengine - INFO - Epoch(train) [96][50/63] lr: 1.4337e-03 eta: 15:12:36 time: 1.1251 data_time: 0.0138 memory: 16131 loss: 4.9595 loss_prob: 2.8153 loss_thr: 1.1444 loss_db: 0.9998 2022/10/25 20:22:11 - mmengine - INFO - Epoch(train) [96][55/63] lr: 1.4337e-03 eta: 15:12:36 time: 0.6684 data_time: 0.0255 memory: 16131 loss: 4.9337 loss_prob: 2.8145 loss_thr: 1.1210 loss_db: 0.9982 2022/10/25 20:22:15 - mmengine - INFO - Epoch(train) [96][60/63] lr: 1.4337e-03 eta: 15:12:19 time: 0.7013 data_time: 0.0187 memory: 16131 loss: 4.9331 loss_prob: 2.8183 loss_thr: 1.1235 loss_db: 0.9913 2022/10/25 20:22:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:22:27 - mmengine - INFO - Epoch(train) [97][5/63] lr: 1.4488e-03 eta: 15:12:19 time: 1.4430 data_time: 0.1809 memory: 16131 loss: 4.8987 loss_prob: 2.8211 loss_thr: 1.1638 loss_db: 0.9138 2022/10/25 20:22:31 - mmengine - INFO - Epoch(train) [97][10/63] lr: 1.4488e-03 eta: 15:12:42 time: 1.3193 data_time: 0.1853 memory: 16131 loss: 4.9323 loss_prob: 2.8211 loss_thr: 1.1682 loss_db: 0.9431 2022/10/25 20:22:34 - mmengine - INFO - Epoch(train) [97][15/63] lr: 1.4488e-03 eta: 15:12:42 time: 0.7341 data_time: 0.0142 memory: 16131 loss: 4.9190 loss_prob: 2.8246 loss_thr: 1.1507 loss_db: 0.9436 2022/10/25 20:22:38 - mmengine - INFO - Epoch(train) [97][20/63] lr: 1.4488e-03 eta: 15:12:24 time: 0.6978 data_time: 0.0099 memory: 16131 loss: 4.8829 loss_prob: 2.8291 loss_thr: 1.1645 loss_db: 0.8893 2022/10/25 20:22:42 - mmengine - INFO - Epoch(train) [97][25/63] lr: 1.4488e-03 eta: 15:12:24 time: 0.7102 data_time: 0.0208 memory: 16131 loss: 4.8643 loss_prob: 2.8288 loss_thr: 1.1784 loss_db: 0.8571 2022/10/25 20:22:46 - mmengine - INFO - Epoch(train) [97][30/63] lr: 1.4488e-03 eta: 15:12:20 time: 0.8158 data_time: 0.0720 memory: 16131 loss: 4.8785 loss_prob: 2.8259 loss_thr: 1.1648 loss_db: 0.8878 2022/10/25 20:22:50 - mmengine - INFO - Epoch(train) [97][35/63] lr: 1.4488e-03 eta: 15:12:20 time: 0.8261 data_time: 0.0595 memory: 16131 loss: 4.8955 loss_prob: 2.8244 loss_thr: 1.1887 loss_db: 0.8824 2022/10/25 20:22:55 - mmengine - INFO - Epoch(train) [97][40/63] lr: 1.4488e-03 eta: 15:12:16 time: 0.8236 data_time: 0.0068 memory: 16131 loss: 4.8604 loss_prob: 2.8271 loss_thr: 1.1795 loss_db: 0.8538 2022/10/25 20:23:00 - mmengine - INFO - Epoch(train) [97][45/63] lr: 1.4488e-03 eta: 15:12:16 time: 0.9936 data_time: 0.0057 memory: 16131 loss: 4.8156 loss_prob: 2.8249 loss_thr: 1.1616 loss_db: 0.8291 2022/10/25 20:23:03 - mmengine - INFO - Epoch(train) [97][50/63] lr: 1.4488e-03 eta: 15:12:11 time: 0.8157 data_time: 0.0215 memory: 16131 loss: 4.8409 loss_prob: 2.8226 loss_thr: 1.2081 loss_db: 0.8102 2022/10/25 20:23:05 - mmengine - INFO - Epoch(train) [97][55/63] lr: 1.4488e-03 eta: 15:12:11 time: 0.5646 data_time: 0.0218 memory: 16131 loss: 4.9022 loss_prob: 2.8407 loss_thr: 1.2017 loss_db: 0.8598 2022/10/25 20:23:11 - mmengine - INFO - Epoch(train) [97][60/63] lr: 1.4488e-03 eta: 15:12:04 time: 0.7954 data_time: 0.0086 memory: 16131 loss: 4.8481 loss_prob: 2.8377 loss_thr: 1.1681 loss_db: 0.8423 2022/10/25 20:23:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:23:20 - mmengine - INFO - Epoch(train) [98][5/63] lr: 1.4638e-03 eta: 15:12:04 time: 1.1632 data_time: 0.1940 memory: 16131 loss: 4.8100 loss_prob: 2.8219 loss_thr: 1.1710 loss_db: 0.8172 2022/10/25 20:23:22 - mmengine - INFO - Epoch(train) [98][10/63] lr: 1.4638e-03 eta: 15:11:38 time: 0.8845 data_time: 0.2019 memory: 16131 loss: 4.8069 loss_prob: 2.8269 loss_thr: 1.1838 loss_db: 0.7962 2022/10/25 20:23:25 - mmengine - INFO - Epoch(train) [98][15/63] lr: 1.4638e-03 eta: 15:11:38 time: 0.5610 data_time: 0.0211 memory: 16131 loss: 4.7605 loss_prob: 2.8118 loss_thr: 1.1722 loss_db: 0.7765 2022/10/25 20:23:29 - mmengine - INFO - Epoch(train) [98][20/63] lr: 1.4638e-03 eta: 15:11:13 time: 0.6341 data_time: 0.0122 memory: 16131 loss: 4.7886 loss_prob: 2.8134 loss_thr: 1.1443 loss_db: 0.8309 2022/10/25 20:23:32 - mmengine - INFO - Epoch(train) [98][25/63] lr: 1.4638e-03 eta: 15:11:13 time: 0.7000 data_time: 0.0151 memory: 16131 loss: 4.7842 loss_prob: 2.8302 loss_thr: 1.1496 loss_db: 0.8044 2022/10/25 20:23:35 - mmengine - INFO - Epoch(train) [98][30/63] lr: 1.4638e-03 eta: 15:10:47 time: 0.6231 data_time: 0.0295 memory: 16131 loss: 4.6366 loss_prob: 2.8027 loss_thr: 1.1336 loss_db: 0.7003 2022/10/25 20:23:38 - mmengine - INFO - Epoch(train) [98][35/63] lr: 1.4638e-03 eta: 15:10:47 time: 0.5310 data_time: 0.0254 memory: 16131 loss: 4.5686 loss_prob: 2.7821 loss_thr: 1.1252 loss_db: 0.6613 2022/10/25 20:23:41 - mmengine - INFO - Epoch(train) [98][40/63] lr: 1.4638e-03 eta: 15:10:13 time: 0.5597 data_time: 0.0172 memory: 16131 loss: 4.5624 loss_prob: 2.7838 loss_thr: 1.1257 loss_db: 0.6529 2022/10/25 20:23:43 - mmengine - INFO - Epoch(train) [98][45/63] lr: 1.4638e-03 eta: 15:10:13 time: 0.5486 data_time: 0.0105 memory: 16131 loss: 4.6290 loss_prob: 2.7966 loss_thr: 1.1418 loss_db: 0.6905 2022/10/25 20:23:47 - mmengine - INFO - Epoch(train) [98][50/63] lr: 1.4638e-03 eta: 15:09:48 time: 0.6368 data_time: 0.0145 memory: 16131 loss: 4.7456 loss_prob: 2.8068 loss_thr: 1.1568 loss_db: 0.7820 2022/10/25 20:23:53 - mmengine - INFO - Epoch(train) [98][55/63] lr: 1.4638e-03 eta: 15:09:48 time: 0.9378 data_time: 0.0227 memory: 16131 loss: 4.7086 loss_prob: 2.7950 loss_thr: 1.1481 loss_db: 0.7655 2022/10/25 20:23:57 - mmengine - INFO - Epoch(train) [98][60/63] lr: 1.4638e-03 eta: 15:10:02 time: 0.9751 data_time: 0.0172 memory: 16131 loss: 4.6278 loss_prob: 2.7829 loss_thr: 1.1358 loss_db: 0.7090 2022/10/25 20:23:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:24:04 - mmengine - INFO - Epoch(train) [99][5/63] lr: 1.4789e-03 eta: 15:10:02 time: 0.9236 data_time: 0.2219 memory: 16131 loss: 4.5252 loss_prob: 2.7584 loss_thr: 1.1169 loss_db: 0.6498 2022/10/25 20:24:08 - mmengine - INFO - Epoch(train) [99][10/63] lr: 1.4789e-03 eta: 15:09:48 time: 0.9897 data_time: 0.2194 memory: 16131 loss: 4.7098 loss_prob: 2.7986 loss_thr: 1.1606 loss_db: 0.7506 2022/10/25 20:24:11 - mmengine - INFO - Epoch(train) [99][15/63] lr: 1.4789e-03 eta: 15:09:48 time: 0.7186 data_time: 0.0047 memory: 16131 loss: 4.6628 loss_prob: 2.7748 loss_thr: 1.1484 loss_db: 0.7396 2022/10/25 20:24:14 - mmengine - INFO - Epoch(train) [99][20/63] lr: 1.4789e-03 eta: 15:09:14 time: 0.5504 data_time: 0.0046 memory: 16131 loss: 4.5722 loss_prob: 2.7540 loss_thr: 1.1271 loss_db: 0.6911 2022/10/25 20:24:18 - mmengine - INFO - Epoch(train) [99][25/63] lr: 1.4789e-03 eta: 15:09:14 time: 0.6813 data_time: 0.0369 memory: 16131 loss: 4.6463 loss_prob: 2.7847 loss_thr: 1.1350 loss_db: 0.7266 2022/10/25 20:24:21 - mmengine - INFO - Epoch(train) [99][30/63] lr: 1.4789e-03 eta: 15:09:00 time: 0.7321 data_time: 0.0389 memory: 16131 loss: 4.5898 loss_prob: 2.7687 loss_thr: 1.1207 loss_db: 0.7004 2022/10/25 20:24:24 - mmengine - INFO - Epoch(train) [99][35/63] lr: 1.4789e-03 eta: 15:09:00 time: 0.6259 data_time: 0.0073 memory: 16131 loss: 4.4862 loss_prob: 2.7356 loss_thr: 1.1157 loss_db: 0.6349 2022/10/25 20:24:27 - mmengine - INFO - Epoch(train) [99][40/63] lr: 1.4789e-03 eta: 15:08:36 time: 0.6424 data_time: 0.0056 memory: 16131 loss: 4.5061 loss_prob: 2.7307 loss_thr: 1.1227 loss_db: 0.6527 2022/10/25 20:24:31 - mmengine - INFO - Epoch(train) [99][45/63] lr: 1.4789e-03 eta: 15:08:36 time: 0.6889 data_time: 0.0052 memory: 16131 loss: 4.4334 loss_prob: 2.6948 loss_thr: 1.1139 loss_db: 0.6248 2022/10/25 20:24:34 - mmengine - INFO - Epoch(train) [99][50/63] lr: 1.4789e-03 eta: 15:08:17 time: 0.6873 data_time: 0.0317 memory: 16131 loss: 4.4834 loss_prob: 2.7171 loss_thr: 1.1140 loss_db: 0.6524 2022/10/25 20:24:38 - mmengine - INFO - Epoch(train) [99][55/63] lr: 1.4789e-03 eta: 15:08:17 time: 0.7457 data_time: 0.0337 memory: 16131 loss: 4.5148 loss_prob: 2.7382 loss_thr: 1.1131 loss_db: 0.6635 2022/10/25 20:24:42 - mmengine - INFO - Epoch(train) [99][60/63] lr: 1.4789e-03 eta: 15:08:04 time: 0.7362 data_time: 0.0071 memory: 16131 loss: 4.4597 loss_prob: 2.7176 loss_thr: 1.1099 loss_db: 0.6322 2022/10/25 20:24:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:24:51 - mmengine - INFO - Epoch(train) [100][5/63] lr: 1.4940e-03 eta: 15:08:04 time: 1.0899 data_time: 0.1883 memory: 16131 loss: 4.3724 loss_prob: 2.6731 loss_thr: 1.1111 loss_db: 0.5882 2022/10/25 20:24:55 - mmengine - INFO - Epoch(train) [100][10/63] lr: 1.4940e-03 eta: 15:08:10 time: 1.1693 data_time: 0.1934 memory: 16131 loss: 4.3250 loss_prob: 2.6493 loss_thr: 1.0935 loss_db: 0.5822 2022/10/25 20:24:58 - mmengine - INFO - Epoch(train) [100][15/63] lr: 1.4940e-03 eta: 15:08:10 time: 0.6702 data_time: 0.0147 memory: 16131 loss: 4.3522 loss_prob: 2.6591 loss_thr: 1.1021 loss_db: 0.5910 2022/10/25 20:25:01 - mmengine - INFO - Epoch(train) [100][20/63] lr: 1.4940e-03 eta: 15:07:36 time: 0.5478 data_time: 0.0089 memory: 16131 loss: 4.4345 loss_prob: 2.7064 loss_thr: 1.0940 loss_db: 0.6341 2022/10/25 20:25:04 - mmengine - INFO - Epoch(train) [100][25/63] lr: 1.4940e-03 eta: 15:07:36 time: 0.5891 data_time: 0.0245 memory: 16131 loss: 4.6237 loss_prob: 2.8180 loss_thr: 1.1075 loss_db: 0.6982 2022/10/25 20:25:07 - mmengine - INFO - Epoch(train) [100][30/63] lr: 1.4940e-03 eta: 15:07:12 time: 0.6380 data_time: 0.0387 memory: 16131 loss: 4.6227 loss_prob: 2.7950 loss_thr: 1.1291 loss_db: 0.6986 2022/10/25 20:25:10 - mmengine - INFO - Epoch(train) [100][35/63] lr: 1.4940e-03 eta: 15:07:12 time: 0.6453 data_time: 0.0226 memory: 16131 loss: 4.4626 loss_prob: 2.6956 loss_thr: 1.1184 loss_db: 0.6487 2022/10/25 20:25:13 - mmengine - INFO - Epoch(train) [100][40/63] lr: 1.4940e-03 eta: 15:06:41 time: 0.5765 data_time: 0.0109 memory: 16131 loss: 4.4290 loss_prob: 2.7056 loss_thr: 1.0924 loss_db: 0.6310 2022/10/25 20:25:16 - mmengine - INFO - Epoch(train) [100][45/63] lr: 1.4940e-03 eta: 15:06:41 time: 0.5945 data_time: 0.0069 memory: 16131 loss: 4.4275 loss_prob: 2.7019 loss_thr: 1.0862 loss_db: 0.6394 2022/10/25 20:25:20 - mmengine - INFO - Epoch(train) [100][50/63] lr: 1.4940e-03 eta: 15:06:19 time: 0.6610 data_time: 0.0128 memory: 16131 loss: 4.5129 loss_prob: 2.7420 loss_thr: 1.1055 loss_db: 0.6654 2022/10/25 20:25:24 - mmengine - INFO - Epoch(train) [100][55/63] lr: 1.4940e-03 eta: 15:06:19 time: 0.7767 data_time: 0.0180 memory: 16131 loss: 4.5322 loss_prob: 2.7697 loss_thr: 1.1147 loss_db: 0.6478 2022/10/25 20:25:27 - mmengine - INFO - Epoch(train) [100][60/63] lr: 1.4940e-03 eta: 15:06:12 time: 0.7868 data_time: 0.0135 memory: 16131 loss: 4.4803 loss_prob: 2.7221 loss_thr: 1.1055 loss_db: 0.6527 2022/10/25 20:25:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:25:30 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/25 20:25:37 - mmengine - INFO - Epoch(val) [100][5/32] eta: 15:06:12 time: 0.5545 data_time: 0.0613 memory: 16131 2022/10/25 20:25:41 - mmengine - INFO - Epoch(val) [100][10/32] eta: 0:00:16 time: 0.7485 data_time: 0.0804 memory: 15724 2022/10/25 20:25:45 - mmengine - INFO - Epoch(val) [100][15/32] eta: 0:00:16 time: 0.7205 data_time: 0.0473 memory: 15724 2022/10/25 20:25:48 - mmengine - INFO - Epoch(val) [100][20/32] eta: 0:00:08 time: 0.7178 data_time: 0.0515 memory: 15724 2022/10/25 20:25:51 - mmengine - INFO - Epoch(val) [100][25/32] eta: 0:00:08 time: 0.6940 data_time: 0.0479 memory: 15724 2022/10/25 20:25:55 - mmengine - INFO - Epoch(val) [100][30/32] eta: 0:00:01 time: 0.6524 data_time: 0.0320 memory: 15724 2022/10/25 20:25:56 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.1738, precision: 0.0830, hmean: 0.1124 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0655, precision: 0.5939, hmean: 0.1180 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0029, precision: 0.6667, hmean: 0.0058 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:25:56 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:25:56 - mmengine - INFO - Epoch(val) [100][32/32] icdar/precision: 0.5939 icdar/recall: 0.0655 icdar/hmean: 0.1180 2022/10/25 20:26:02 - mmengine - INFO - Epoch(train) [101][5/63] lr: 1.5090e-03 eta: 0:00:01 time: 1.0436 data_time: 0.2101 memory: 16131 loss: 4.4221 loss_prob: 2.6853 loss_thr: 1.0847 loss_db: 0.6521 2022/10/25 20:26:06 - mmengine - INFO - Epoch(train) [101][10/63] lr: 1.5090e-03 eta: 15:06:06 time: 1.0579 data_time: 0.2072 memory: 16131 loss: 4.3944 loss_prob: 2.6704 loss_thr: 1.0888 loss_db: 0.6352 2022/10/25 20:26:11 - mmengine - INFO - Epoch(train) [101][15/63] lr: 1.5090e-03 eta: 15:06:06 time: 0.8480 data_time: 0.0075 memory: 16131 loss: 4.3675 loss_prob: 2.6723 loss_thr: 1.0836 loss_db: 0.6116 2022/10/25 20:26:13 - mmengine - INFO - Epoch(train) [101][20/63] lr: 1.5090e-03 eta: 15:05:50 time: 0.7127 data_time: 0.0088 memory: 16131 loss: 4.3233 loss_prob: 2.6393 loss_thr: 1.0867 loss_db: 0.5974 2022/10/25 20:26:16 - mmengine - INFO - Epoch(train) [101][25/63] lr: 1.5090e-03 eta: 15:05:50 time: 0.5454 data_time: 0.0171 memory: 16131 loss: 4.2580 loss_prob: 2.6142 loss_thr: 1.0796 loss_db: 0.5642 2022/10/25 20:26:21 - mmengine - INFO - Epoch(train) [101][30/63] lr: 1.5090e-03 eta: 15:05:43 time: 0.7920 data_time: 0.0359 memory: 16131 loss: 4.2581 loss_prob: 2.6323 loss_thr: 1.0589 loss_db: 0.5669 2022/10/25 20:26:24 - mmengine - INFO - Epoch(train) [101][35/63] lr: 1.5090e-03 eta: 15:05:43 time: 0.8098 data_time: 0.0252 memory: 16131 loss: 4.3252 loss_prob: 2.6499 loss_thr: 1.0750 loss_db: 0.6004 2022/10/25 20:26:30 - mmengine - INFO - Epoch(train) [101][40/63] lr: 1.5090e-03 eta: 15:05:42 time: 0.8451 data_time: 0.0063 memory: 16131 loss: 4.4117 loss_prob: 2.6841 loss_thr: 1.0945 loss_db: 0.6332 2022/10/25 20:26:32 - mmengine - INFO - Epoch(train) [101][45/63] lr: 1.5090e-03 eta: 15:05:42 time: 0.7998 data_time: 0.0066 memory: 16131 loss: 4.5211 loss_prob: 2.7378 loss_thr: 1.1064 loss_db: 0.6769 2022/10/25 20:26:35 - mmengine - INFO - Epoch(train) [101][50/63] lr: 1.5090e-03 eta: 15:05:08 time: 0.5503 data_time: 0.0254 memory: 16131 loss: 4.4946 loss_prob: 2.7183 loss_thr: 1.0971 loss_db: 0.6792 2022/10/25 20:26:41 - mmengine - INFO - Epoch(train) [101][55/63] lr: 1.5090e-03 eta: 15:05:08 time: 0.8950 data_time: 0.0250 memory: 16131 loss: 4.2621 loss_prob: 2.5978 loss_thr: 1.0765 loss_db: 0.5878 2022/10/25 20:26:44 - mmengine - INFO - Epoch(train) [101][60/63] lr: 1.5090e-03 eta: 15:05:07 time: 0.8448 data_time: 0.0078 memory: 16131 loss: 4.2425 loss_prob: 2.5972 loss_thr: 1.0726 loss_db: 0.5727 2022/10/25 20:26:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:26:51 - mmengine - INFO - Epoch(train) [102][5/63] lr: 1.5241e-03 eta: 15:05:07 time: 0.8103 data_time: 0.2389 memory: 16131 loss: 4.5094 loss_prob: 2.7347 loss_thr: 1.0955 loss_db: 0.6793 2022/10/25 20:26:55 - mmengine - INFO - Epoch(train) [102][10/63] lr: 1.5241e-03 eta: 15:04:56 time: 1.0138 data_time: 0.2394 memory: 16131 loss: 4.5261 loss_prob: 2.7286 loss_thr: 1.0967 loss_db: 0.7008 2022/10/25 20:27:02 - mmengine - INFO - Epoch(train) [102][15/63] lr: 1.5241e-03 eta: 15:04:56 time: 1.1472 data_time: 0.0057 memory: 16131 loss: 4.4361 loss_prob: 2.7021 loss_thr: 1.0996 loss_db: 0.6344 2022/10/25 20:27:08 - mmengine - INFO - Epoch(train) [102][20/63] lr: 1.5241e-03 eta: 15:05:45 time: 1.3122 data_time: 0.0059 memory: 16131 loss: 4.3660 loss_prob: 2.6835 loss_thr: 1.0786 loss_db: 0.6040 2022/10/25 20:27:13 - mmengine - INFO - Epoch(train) [102][25/63] lr: 1.5241e-03 eta: 15:05:45 time: 1.1068 data_time: 0.0293 memory: 16131 loss: 4.3492 loss_prob: 2.6745 loss_thr: 1.0827 loss_db: 0.5920 2022/10/25 20:27:18 - mmengine - INFO - Epoch(train) [102][30/63] lr: 1.5241e-03 eta: 15:05:58 time: 0.9764 data_time: 0.0306 memory: 16131 loss: 4.3185 loss_prob: 2.6444 loss_thr: 1.0799 loss_db: 0.5942 2022/10/25 20:27:24 - mmengine - INFO - Epoch(train) [102][35/63] lr: 1.5241e-03 eta: 15:05:58 time: 1.0559 data_time: 0.0111 memory: 16131 loss: 4.3753 loss_prob: 2.6742 loss_thr: 1.0760 loss_db: 0.6251 2022/10/25 20:27:27 - mmengine - INFO - Epoch(train) [102][40/63] lr: 1.5241e-03 eta: 15:06:05 time: 0.9231 data_time: 0.0090 memory: 16131 loss: 4.3485 loss_prob: 2.6601 loss_thr: 1.0770 loss_db: 0.6114 2022/10/25 20:27:30 - mmengine - INFO - Epoch(train) [102][45/63] lr: 1.5241e-03 eta: 15:06:05 time: 0.6512 data_time: 0.0055 memory: 16131 loss: 4.2192 loss_prob: 2.6025 loss_thr: 1.0644 loss_db: 0.5524 2022/10/25 20:27:33 - mmengine - INFO - Epoch(train) [102][50/63] lr: 1.5241e-03 eta: 15:05:37 time: 0.5954 data_time: 0.0206 memory: 16131 loss: 4.3410 loss_prob: 2.6646 loss_thr: 1.0879 loss_db: 0.5885 2022/10/25 20:27:36 - mmengine - INFO - Epoch(train) [102][55/63] lr: 1.5241e-03 eta: 15:05:37 time: 0.5473 data_time: 0.0218 memory: 16131 loss: 4.3980 loss_prob: 2.6844 loss_thr: 1.0893 loss_db: 0.6243 2022/10/25 20:27:39 - mmengine - INFO - Epoch(train) [102][60/63] lr: 1.5241e-03 eta: 15:05:01 time: 0.5289 data_time: 0.0083 memory: 16131 loss: 4.3128 loss_prob: 2.6372 loss_thr: 1.0834 loss_db: 0.5922 2022/10/25 20:27:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:27:45 - mmengine - INFO - Epoch(train) [103][5/63] lr: 1.5392e-03 eta: 15:05:01 time: 0.7079 data_time: 0.1899 memory: 16131 loss: 4.2649 loss_prob: 2.6208 loss_thr: 1.0584 loss_db: 0.5856 2022/10/25 20:27:47 - mmengine - INFO - Epoch(train) [103][10/63] lr: 1.5392e-03 eta: 15:04:21 time: 0.7405 data_time: 0.1958 memory: 16131 loss: 4.3621 loss_prob: 2.6528 loss_thr: 1.0847 loss_db: 0.6246 2022/10/25 20:27:50 - mmengine - INFO - Epoch(train) [103][15/63] lr: 1.5392e-03 eta: 15:04:21 time: 0.5311 data_time: 0.0128 memory: 16131 loss: 4.3440 loss_prob: 2.6444 loss_thr: 1.0967 loss_db: 0.6029 2022/10/25 20:27:52 - mmengine - INFO - Epoch(train) [103][20/63] lr: 1.5392e-03 eta: 15:03:45 time: 0.5226 data_time: 0.0072 memory: 16131 loss: 4.1737 loss_prob: 2.5738 loss_thr: 1.0626 loss_db: 0.5373 2022/10/25 20:27:55 - mmengine - INFO - Epoch(train) [103][25/63] lr: 1.5392e-03 eta: 15:03:45 time: 0.5134 data_time: 0.0185 memory: 16131 loss: 4.0678 loss_prob: 2.5156 loss_thr: 1.0326 loss_db: 0.5196 2022/10/25 20:27:58 - mmengine - INFO - Epoch(train) [103][30/63] lr: 1.5392e-03 eta: 15:03:09 time: 0.5225 data_time: 0.0415 memory: 16131 loss: 4.1065 loss_prob: 2.5380 loss_thr: 1.0497 loss_db: 0.5188 2022/10/25 20:28:00 - mmengine - INFO - Epoch(train) [103][35/63] lr: 1.5392e-03 eta: 15:03:09 time: 0.5193 data_time: 0.0286 memory: 16131 loss: 4.1865 loss_prob: 2.5759 loss_thr: 1.0688 loss_db: 0.5418 2022/10/25 20:28:03 - mmengine - INFO - Epoch(train) [103][40/63] lr: 1.5392e-03 eta: 15:02:32 time: 0.5057 data_time: 0.0041 memory: 16131 loss: 4.1675 loss_prob: 2.5547 loss_thr: 1.0627 loss_db: 0.5502 2022/10/25 20:28:05 - mmengine - INFO - Epoch(train) [103][45/63] lr: 1.5392e-03 eta: 15:02:32 time: 0.5178 data_time: 0.0060 memory: 16131 loss: 4.0685 loss_prob: 2.5003 loss_thr: 1.0445 loss_db: 0.5237 2022/10/25 20:28:10 - mmengine - INFO - Epoch(train) [103][50/63] lr: 1.5392e-03 eta: 15:02:17 time: 0.7182 data_time: 0.0234 memory: 16131 loss: 4.1869 loss_prob: 2.5637 loss_thr: 1.0640 loss_db: 0.5593 2022/10/25 20:28:14 - mmengine - INFO - Epoch(train) [103][55/63] lr: 1.5392e-03 eta: 15:02:17 time: 0.8513 data_time: 0.0244 memory: 16131 loss: 4.2900 loss_prob: 2.6223 loss_thr: 1.0759 loss_db: 0.5918 2022/10/25 20:28:18 - mmengine - INFO - Epoch(train) [103][60/63] lr: 1.5392e-03 eta: 15:02:16 time: 0.8424 data_time: 0.0093 memory: 16131 loss: 4.2969 loss_prob: 2.6332 loss_thr: 1.0734 loss_db: 0.5903 2022/10/25 20:28:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:28:28 - mmengine - INFO - Epoch(train) [104][5/63] lr: 1.5542e-03 eta: 15:02:16 time: 1.0491 data_time: 0.2306 memory: 16131 loss: 4.0789 loss_prob: 2.5116 loss_thr: 1.0571 loss_db: 0.5102 2022/10/25 20:28:31 - mmengine - INFO - Epoch(train) [104][10/63] lr: 1.5542e-03 eta: 15:02:10 time: 1.0666 data_time: 0.2408 memory: 16131 loss: 3.9543 loss_prob: 2.4412 loss_thr: 1.0299 loss_db: 0.4832 2022/10/25 20:28:34 - mmengine - INFO - Epoch(train) [104][15/63] lr: 1.5542e-03 eta: 15:02:10 time: 0.6006 data_time: 0.0192 memory: 16131 loss: 4.0489 loss_prob: 2.4911 loss_thr: 1.0347 loss_db: 0.5232 2022/10/25 20:28:39 - mmengine - INFO - Epoch(train) [104][20/63] lr: 1.5542e-03 eta: 15:02:07 time: 0.8249 data_time: 0.0099 memory: 16131 loss: 4.3035 loss_prob: 2.6288 loss_thr: 1.0757 loss_db: 0.5989 2022/10/25 20:28:42 - mmengine - INFO - Epoch(train) [104][25/63] lr: 1.5542e-03 eta: 15:02:07 time: 0.8517 data_time: 0.0112 memory: 16131 loss: 4.3886 loss_prob: 2.6685 loss_thr: 1.0894 loss_db: 0.6307 2022/10/25 20:28:46 - mmengine - INFO - Epoch(train) [104][30/63] lr: 1.5542e-03 eta: 15:01:53 time: 0.7293 data_time: 0.0321 memory: 16131 loss: 4.3191 loss_prob: 2.6465 loss_thr: 1.0796 loss_db: 0.5930 2022/10/25 20:28:49 - mmengine - INFO - Epoch(train) [104][35/63] lr: 1.5542e-03 eta: 15:01:53 time: 0.6854 data_time: 0.0380 memory: 16131 loss: 4.2404 loss_prob: 2.6143 loss_thr: 1.0690 loss_db: 0.5571 2022/10/25 20:28:52 - mmengine - INFO - Epoch(train) [104][40/63] lr: 1.5542e-03 eta: 15:01:25 time: 0.5871 data_time: 0.0157 memory: 16131 loss: 4.1837 loss_prob: 2.5817 loss_thr: 1.0552 loss_db: 0.5468 2022/10/25 20:28:55 - mmengine - INFO - Epoch(train) [104][45/63] lr: 1.5542e-03 eta: 15:01:25 time: 0.6010 data_time: 0.0072 memory: 16131 loss: 4.1098 loss_prob: 2.5292 loss_thr: 1.0524 loss_db: 0.5282 2022/10/25 20:28:59 - mmengine - INFO - Epoch(train) [104][50/63] lr: 1.5542e-03 eta: 15:01:04 time: 0.6616 data_time: 0.0213 memory: 16131 loss: 4.0512 loss_prob: 2.4828 loss_thr: 1.0552 loss_db: 0.5132 2022/10/25 20:29:05 - mmengine - INFO - Epoch(train) [104][55/63] lr: 1.5542e-03 eta: 15:01:04 time: 0.9881 data_time: 0.0247 memory: 16131 loss: 4.1127 loss_prob: 2.5283 loss_thr: 1.0562 loss_db: 0.5282 2022/10/25 20:29:09 - mmengine - INFO - Epoch(train) [104][60/63] lr: 1.5542e-03 eta: 15:01:27 time: 1.0759 data_time: 0.0140 memory: 16131 loss: 4.2032 loss_prob: 2.5842 loss_thr: 1.0673 loss_db: 0.5517 2022/10/25 20:29:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:29:18 - mmengine - INFO - Epoch(train) [105][5/63] lr: 1.5693e-03 eta: 15:01:27 time: 1.1212 data_time: 0.1901 memory: 16131 loss: 4.0505 loss_prob: 2.4820 loss_thr: 1.0523 loss_db: 0.5162 2022/10/25 20:29:21 - mmengine - INFO - Epoch(train) [105][10/63] lr: 1.5693e-03 eta: 15:00:57 time: 0.8307 data_time: 0.1889 memory: 16131 loss: 4.0598 loss_prob: 2.5026 loss_thr: 1.0358 loss_db: 0.5215 2022/10/25 20:29:23 - mmengine - INFO - Epoch(train) [105][15/63] lr: 1.5693e-03 eta: 15:00:57 time: 0.5496 data_time: 0.0062 memory: 16131 loss: 4.0075 loss_prob: 2.4820 loss_thr: 1.0256 loss_db: 0.4999 2022/10/25 20:29:29 - mmengine - INFO - Epoch(train) [105][20/63] lr: 1.5693e-03 eta: 15:00:57 time: 0.8499 data_time: 0.0081 memory: 16131 loss: 4.2040 loss_prob: 2.6082 loss_thr: 1.0421 loss_db: 0.5537 2022/10/25 20:29:32 - mmengine - INFO - Epoch(train) [105][25/63] lr: 1.5693e-03 eta: 15:00:57 time: 0.8531 data_time: 0.0215 memory: 16131 loss: 4.3432 loss_prob: 2.7136 loss_thr: 1.0687 loss_db: 0.5610 2022/10/25 20:29:36 - mmengine - INFO - Epoch(train) [105][30/63] lr: 1.5693e-03 eta: 15:00:34 time: 0.6398 data_time: 0.0359 memory: 16131 loss: 4.3087 loss_prob: 2.6513 loss_thr: 1.0775 loss_db: 0.5799 2022/10/25 20:29:41 - mmengine - INFO - Epoch(train) [105][35/63] lr: 1.5693e-03 eta: 15:00:34 time: 0.9406 data_time: 0.0220 memory: 16131 loss: 4.3123 loss_prob: 2.6361 loss_thr: 1.0765 loss_db: 0.5997 2022/10/25 20:29:45 - mmengine - INFO - Epoch(train) [105][40/63] lr: 1.5693e-03 eta: 15:00:43 time: 0.9473 data_time: 0.0059 memory: 16131 loss: 4.3468 loss_prob: 2.6647 loss_thr: 1.0775 loss_db: 0.6045 2022/10/25 20:29:48 - mmengine - INFO - Epoch(train) [105][45/63] lr: 1.5693e-03 eta: 15:00:43 time: 0.6361 data_time: 0.0052 memory: 16131 loss: 4.4113 loss_prob: 2.6890 loss_thr: 1.0889 loss_db: 0.6334 2022/10/25 20:29:50 - mmengine - INFO - Epoch(train) [105][50/63] lr: 1.5693e-03 eta: 15:00:08 time: 0.5219 data_time: 0.0237 memory: 16131 loss: 4.1987 loss_prob: 2.5883 loss_thr: 1.0609 loss_db: 0.5495 2022/10/25 20:29:55 - mmengine - INFO - Epoch(train) [105][55/63] lr: 1.5693e-03 eta: 15:00:08 time: 0.6729 data_time: 0.0287 memory: 16131 loss: 3.9883 loss_prob: 2.4809 loss_thr: 1.0204 loss_db: 0.4870 2022/10/25 20:30:00 - mmengine - INFO - Epoch(train) [105][60/63] lr: 1.5693e-03 eta: 15:00:17 time: 0.9405 data_time: 0.0102 memory: 16131 loss: 4.0409 loss_prob: 2.4963 loss_thr: 1.0277 loss_db: 0.5168 2022/10/25 20:30:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:30:06 - mmengine - INFO - Epoch(train) [106][5/63] lr: 1.5843e-03 eta: 15:00:17 time: 0.8172 data_time: 0.1741 memory: 16131 loss: 4.0308 loss_prob: 2.4910 loss_thr: 1.0307 loss_db: 0.5091 2022/10/25 20:30:09 - mmengine - INFO - Epoch(train) [106][10/63] lr: 1.5843e-03 eta: 14:59:42 time: 0.7869 data_time: 0.1737 memory: 16131 loss: 4.1175 loss_prob: 2.5578 loss_thr: 1.0363 loss_db: 0.5234 2022/10/25 20:30:12 - mmengine - INFO - Epoch(train) [106][15/63] lr: 1.5843e-03 eta: 14:59:42 time: 0.5519 data_time: 0.0070 memory: 16131 loss: 4.3522 loss_prob: 2.6552 loss_thr: 1.0622 loss_db: 0.6348 2022/10/25 20:30:14 - mmengine - INFO - Epoch(train) [106][20/63] lr: 1.5843e-03 eta: 14:59:05 time: 0.4991 data_time: 0.0072 memory: 16131 loss: 4.3588 loss_prob: 2.6402 loss_thr: 1.0571 loss_db: 0.6615 2022/10/25 20:30:17 - mmengine - INFO - Epoch(train) [106][25/63] lr: 1.5843e-03 eta: 14:59:05 time: 0.5094 data_time: 0.0074 memory: 16131 loss: 4.2758 loss_prob: 2.6223 loss_thr: 1.0582 loss_db: 0.5953 2022/10/25 20:30:20 - mmengine - INFO - Epoch(train) [106][30/63] lr: 1.5843e-03 eta: 14:58:34 time: 0.5537 data_time: 0.0359 memory: 16131 loss: 4.2921 loss_prob: 2.6330 loss_thr: 1.0622 loss_db: 0.5968 2022/10/25 20:30:22 - mmengine - INFO - Epoch(train) [106][35/63] lr: 1.5843e-03 eta: 14:58:34 time: 0.5673 data_time: 0.0370 memory: 16131 loss: 4.1952 loss_prob: 2.6003 loss_thr: 1.0369 loss_db: 0.5579 2022/10/25 20:30:26 - mmengine - INFO - Epoch(train) [106][40/63] lr: 1.5843e-03 eta: 14:58:07 time: 0.6003 data_time: 0.0084 memory: 16131 loss: 4.1236 loss_prob: 2.5605 loss_thr: 1.0384 loss_db: 0.5247 2022/10/25 20:30:29 - mmengine - INFO - Epoch(train) [106][45/63] lr: 1.5843e-03 eta: 14:58:07 time: 0.6612 data_time: 0.0061 memory: 16131 loss: 4.0838 loss_prob: 2.5231 loss_thr: 1.0429 loss_db: 0.5178 2022/10/25 20:30:33 - mmengine - INFO - Epoch(train) [106][50/63] lr: 1.5843e-03 eta: 14:57:52 time: 0.7169 data_time: 0.0152 memory: 16131 loss: 4.0547 loss_prob: 2.5020 loss_thr: 1.0273 loss_db: 0.5254 2022/10/25 20:30:39 - mmengine - INFO - Epoch(train) [106][55/63] lr: 1.5843e-03 eta: 14:57:52 time: 0.9574 data_time: 0.0250 memory: 16131 loss: 4.0463 loss_prob: 2.4998 loss_thr: 1.0360 loss_db: 0.5105 2022/10/25 20:30:44 - mmengine - INFO - Epoch(train) [106][60/63] lr: 1.5843e-03 eta: 14:58:20 time: 1.1208 data_time: 0.0171 memory: 16131 loss: 4.2480 loss_prob: 2.6023 loss_thr: 1.0674 loss_db: 0.5784 2022/10/25 20:30:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:30:54 - mmengine - INFO - Epoch(train) [107][5/63] lr: 1.5994e-03 eta: 14:58:20 time: 1.1893 data_time: 0.2063 memory: 16131 loss: 4.1321 loss_prob: 2.5532 loss_thr: 1.0316 loss_db: 0.5474 2022/10/25 20:30:58 - mmengine - INFO - Epoch(train) [107][10/63] lr: 1.5994e-03 eta: 14:58:14 time: 1.0625 data_time: 0.2074 memory: 16131 loss: 4.1508 loss_prob: 2.5646 loss_thr: 1.0364 loss_db: 0.5499 2022/10/25 20:31:01 - mmengine - INFO - Epoch(train) [107][15/63] lr: 1.5994e-03 eta: 14:58:14 time: 0.6619 data_time: 0.0128 memory: 16131 loss: 4.2461 loss_prob: 2.6083 loss_thr: 1.0552 loss_db: 0.5826 2022/10/25 20:31:03 - mmengine - INFO - Epoch(train) [107][20/63] lr: 1.5994e-03 eta: 14:57:43 time: 0.5520 data_time: 0.0105 memory: 16131 loss: 4.1448 loss_prob: 2.5587 loss_thr: 1.0348 loss_db: 0.5513 2022/10/25 20:31:08 - mmengine - INFO - Epoch(train) [107][25/63] lr: 1.5994e-03 eta: 14:57:43 time: 0.7468 data_time: 0.0259 memory: 16131 loss: 4.1615 loss_prob: 2.5587 loss_thr: 1.0256 loss_db: 0.5771 2022/10/25 20:31:12 - mmengine - INFO - Epoch(train) [107][30/63] lr: 1.5994e-03 eta: 14:57:41 time: 0.8447 data_time: 0.0334 memory: 16131 loss: 4.2450 loss_prob: 2.5956 loss_thr: 1.0698 loss_db: 0.5796 2022/10/25 20:31:14 - mmengine - INFO - Epoch(train) [107][35/63] lr: 1.5994e-03 eta: 14:57:41 time: 0.6079 data_time: 0.0121 memory: 16131 loss: 4.1553 loss_prob: 2.5622 loss_thr: 1.0688 loss_db: 0.5243 2022/10/25 20:31:17 - mmengine - INFO - Epoch(train) [107][40/63] lr: 1.5994e-03 eta: 14:57:06 time: 0.5123 data_time: 0.0083 memory: 16131 loss: 4.1179 loss_prob: 2.5448 loss_thr: 1.0455 loss_db: 0.5276 2022/10/25 20:31:20 - mmengine - INFO - Epoch(train) [107][45/63] lr: 1.5994e-03 eta: 14:57:06 time: 0.5757 data_time: 0.0085 memory: 16131 loss: 4.1337 loss_prob: 2.5454 loss_thr: 1.0560 loss_db: 0.5324 2022/10/25 20:31:24 - mmengine - INFO - Epoch(train) [107][50/63] lr: 1.5994e-03 eta: 14:56:56 time: 0.7636 data_time: 0.0225 memory: 16131 loss: 4.1758 loss_prob: 2.5672 loss_thr: 1.0671 loss_db: 0.5416 2022/10/25 20:31:27 - mmengine - INFO - Epoch(train) [107][55/63] lr: 1.5994e-03 eta: 14:56:56 time: 0.7351 data_time: 0.0265 memory: 16131 loss: 4.1282 loss_prob: 2.5483 loss_thr: 1.0490 loss_db: 0.5309 2022/10/25 20:31:34 - mmengine - INFO - Epoch(train) [107][60/63] lr: 1.5994e-03 eta: 14:57:02 time: 0.9168 data_time: 0.0098 memory: 16131 loss: 4.1689 loss_prob: 2.5884 loss_thr: 1.0452 loss_db: 0.5353 2022/10/25 20:31:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:31:42 - mmengine - INFO - Epoch(train) [108][5/63] lr: 1.6145e-03 eta: 14:57:02 time: 1.1362 data_time: 0.1775 memory: 16131 loss: 4.2249 loss_prob: 2.6175 loss_thr: 1.0416 loss_db: 0.5658 2022/10/25 20:31:45 - mmengine - INFO - Epoch(train) [108][10/63] lr: 1.6145e-03 eta: 14:56:38 time: 0.8802 data_time: 0.1786 memory: 16131 loss: 4.1712 loss_prob: 2.5883 loss_thr: 1.0386 loss_db: 0.5442 2022/10/25 20:31:48 - mmengine - INFO - Epoch(train) [108][15/63] lr: 1.6145e-03 eta: 14:56:38 time: 0.5733 data_time: 0.0141 memory: 16131 loss: 4.1282 loss_prob: 2.5581 loss_thr: 1.0306 loss_db: 0.5395 2022/10/25 20:31:51 - mmengine - INFO - Epoch(train) [108][20/63] lr: 1.6145e-03 eta: 14:56:05 time: 0.5328 data_time: 0.0079 memory: 16131 loss: 4.0262 loss_prob: 2.4966 loss_thr: 1.0249 loss_db: 0.5047 2022/10/25 20:31:55 - mmengine - INFO - Epoch(train) [108][25/63] lr: 1.6145e-03 eta: 14:56:05 time: 0.7167 data_time: 0.0077 memory: 16131 loss: 4.1075 loss_prob: 2.5306 loss_thr: 1.0471 loss_db: 0.5298 2022/10/25 20:31:58 - mmengine - INFO - Epoch(train) [108][30/63] lr: 1.6145e-03 eta: 14:55:52 time: 0.7314 data_time: 0.0295 memory: 16131 loss: 4.2029 loss_prob: 2.5901 loss_thr: 1.0576 loss_db: 0.5553 2022/10/25 20:32:03 - mmengine - INFO - Epoch(train) [108][35/63] lr: 1.6145e-03 eta: 14:55:52 time: 0.7447 data_time: 0.0368 memory: 16131 loss: 4.0555 loss_prob: 2.5015 loss_thr: 1.0463 loss_db: 0.5077 2022/10/25 20:32:05 - mmengine - INFO - Epoch(train) [108][40/63] lr: 1.6145e-03 eta: 14:55:41 time: 0.7429 data_time: 0.0197 memory: 16131 loss: 3.9594 loss_prob: 2.4290 loss_thr: 1.0253 loss_db: 0.5050 2022/10/25 20:32:08 - mmengine - INFO - Epoch(train) [108][45/63] lr: 1.6145e-03 eta: 14:55:41 time: 0.5520 data_time: 0.0123 memory: 16131 loss: 4.0881 loss_prob: 2.5287 loss_thr: 1.0261 loss_db: 0.5333 2022/10/25 20:32:12 - mmengine - INFO - Epoch(train) [108][50/63] lr: 1.6145e-03 eta: 14:55:20 time: 0.6562 data_time: 0.0256 memory: 16131 loss: 4.1710 loss_prob: 2.5761 loss_thr: 1.0434 loss_db: 0.5514 2022/10/25 20:32:18 - mmengine - INFO - Epoch(train) [108][55/63] lr: 1.6145e-03 eta: 14:55:20 time: 0.9616 data_time: 0.0257 memory: 16131 loss: 4.1119 loss_prob: 2.5265 loss_thr: 1.0398 loss_db: 0.5456 2022/10/25 20:32:25 - mmengine - INFO - Epoch(train) [108][60/63] lr: 1.6145e-03 eta: 14:56:08 time: 1.3339 data_time: 0.0090 memory: 16131 loss: 4.0560 loss_prob: 2.5060 loss_thr: 1.0258 loss_db: 0.5243 2022/10/25 20:32:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:32:35 - mmengine - INFO - Epoch(train) [109][5/63] lr: 1.6295e-03 eta: 14:56:08 time: 1.2264 data_time: 0.1969 memory: 16131 loss: 4.0703 loss_prob: 2.5088 loss_thr: 1.0194 loss_db: 0.5421 2022/10/25 20:32:37 - mmengine - INFO - Epoch(train) [109][10/63] lr: 1.6295e-03 eta: 14:55:46 time: 0.9008 data_time: 0.1966 memory: 16131 loss: 4.2086 loss_prob: 2.6097 loss_thr: 1.0191 loss_db: 0.5798 2022/10/25 20:32:41 - mmengine - INFO - Epoch(train) [109][15/63] lr: 1.6295e-03 eta: 14:55:46 time: 0.6490 data_time: 0.0108 memory: 16131 loss: 4.2093 loss_prob: 2.6144 loss_thr: 1.0314 loss_db: 0.5636 2022/10/25 20:32:46 - mmengine - INFO - Epoch(train) [109][20/63] lr: 1.6295e-03 eta: 14:55:42 time: 0.8153 data_time: 0.0119 memory: 16131 loss: 4.1876 loss_prob: 2.5754 loss_thr: 1.0599 loss_db: 0.5522 2022/10/25 20:32:49 - mmengine - INFO - Epoch(train) [109][25/63] lr: 1.6295e-03 eta: 14:55:42 time: 0.8123 data_time: 0.0259 memory: 16131 loss: 4.1935 loss_prob: 2.5769 loss_thr: 1.0541 loss_db: 0.5625 2022/10/25 20:32:53 - mmengine - INFO - Epoch(train) [109][30/63] lr: 1.6295e-03 eta: 14:55:34 time: 0.7826 data_time: 0.0377 memory: 16131 loss: 4.2009 loss_prob: 2.5886 loss_thr: 1.0472 loss_db: 0.5650 2022/10/25 20:32:56 - mmengine - INFO - Epoch(train) [109][35/63] lr: 1.6295e-03 eta: 14:55:34 time: 0.6949 data_time: 0.0235 memory: 16131 loss: 4.1545 loss_prob: 2.5739 loss_thr: 1.0261 loss_db: 0.5545 2022/10/25 20:33:00 - mmengine - INFO - Epoch(train) [109][40/63] lr: 1.6295e-03 eta: 14:55:10 time: 0.6161 data_time: 0.0092 memory: 16131 loss: 4.2046 loss_prob: 2.6103 loss_thr: 1.0208 loss_db: 0.5735 2022/10/25 20:33:03 - mmengine - INFO - Epoch(train) [109][45/63] lr: 1.6295e-03 eta: 14:55:10 time: 0.6309 data_time: 0.0059 memory: 16131 loss: 4.1887 loss_prob: 2.5859 loss_thr: 1.0302 loss_db: 0.5726 2022/10/25 20:33:08 - mmengine - INFO - Epoch(train) [109][50/63] lr: 1.6295e-03 eta: 14:55:04 time: 0.8041 data_time: 0.0256 memory: 16131 loss: 4.0595 loss_prob: 2.5043 loss_thr: 1.0252 loss_db: 0.5300 2022/10/25 20:33:12 - mmengine - INFO - Epoch(train) [109][55/63] lr: 1.6295e-03 eta: 14:55:04 time: 0.9447 data_time: 0.0284 memory: 16131 loss: 3.9854 loss_prob: 2.4721 loss_thr: 1.0125 loss_db: 0.5008 2022/10/25 20:33:18 - mmengine - INFO - Epoch(train) [109][60/63] lr: 1.6295e-03 eta: 14:55:19 time: 1.0053 data_time: 0.0107 memory: 16131 loss: 3.9371 loss_prob: 2.4506 loss_thr: 1.0068 loss_db: 0.4797 2022/10/25 20:33:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:33:25 - mmengine - INFO - Epoch(train) [110][5/63] lr: 1.6446e-03 eta: 14:55:19 time: 1.0229 data_time: 0.2221 memory: 16131 loss: 3.9756 loss_prob: 2.4695 loss_thr: 1.0132 loss_db: 0.4929 2022/10/25 20:33:29 - mmengine - INFO - Epoch(train) [110][10/63] lr: 1.6446e-03 eta: 14:54:58 time: 0.9098 data_time: 0.2211 memory: 16131 loss: 3.9610 loss_prob: 2.4504 loss_thr: 1.0139 loss_db: 0.4967 2022/10/25 20:33:31 - mmengine - INFO - Epoch(train) [110][15/63] lr: 1.6446e-03 eta: 14:54:58 time: 0.6083 data_time: 0.0060 memory: 16131 loss: 3.9713 loss_prob: 2.4559 loss_thr: 1.0117 loss_db: 0.5037 2022/10/25 20:33:34 - mmengine - INFO - Epoch(train) [110][20/63] lr: 1.6446e-03 eta: 14:54:29 time: 0.5669 data_time: 0.0065 memory: 16131 loss: 4.1176 loss_prob: 2.5295 loss_thr: 1.0490 loss_db: 0.5390 2022/10/25 20:33:38 - mmengine - INFO - Epoch(train) [110][25/63] lr: 1.6446e-03 eta: 14:54:29 time: 0.6320 data_time: 0.0328 memory: 16131 loss: 4.1295 loss_prob: 2.5320 loss_thr: 1.0568 loss_db: 0.5406 2022/10/25 20:33:43 - mmengine - INFO - Epoch(train) [110][30/63] lr: 1.6446e-03 eta: 14:54:32 time: 0.8841 data_time: 0.0354 memory: 16131 loss: 3.8710 loss_prob: 2.3952 loss_thr: 0.9934 loss_db: 0.4824 2022/10/25 20:33:47 - mmengine - INFO - Epoch(train) [110][35/63] lr: 1.6446e-03 eta: 14:54:32 time: 0.9176 data_time: 0.0080 memory: 16131 loss: 3.8977 loss_prob: 2.4336 loss_thr: 0.9839 loss_db: 0.4801 2022/10/25 20:33:49 - mmengine - INFO - Epoch(train) [110][40/63] lr: 1.6446e-03 eta: 14:54:09 time: 0.6344 data_time: 0.0058 memory: 16131 loss: 4.1186 loss_prob: 2.5527 loss_thr: 1.0085 loss_db: 0.5574 2022/10/25 20:33:54 - mmengine - INFO - Epoch(train) [110][45/63] lr: 1.6446e-03 eta: 14:54:09 time: 0.6716 data_time: 0.0095 memory: 16131 loss: 4.1718 loss_prob: 2.5830 loss_thr: 1.0234 loss_db: 0.5654 2022/10/25 20:33:58 - mmengine - INFO - Epoch(train) [110][50/63] lr: 1.6446e-03 eta: 14:54:09 time: 0.8609 data_time: 0.0274 memory: 16131 loss: 4.2042 loss_prob: 2.5919 loss_thr: 1.0504 loss_db: 0.5619 2022/10/25 20:34:02 - mmengine - INFO - Epoch(train) [110][55/63] lr: 1.6446e-03 eta: 14:54:09 time: 0.8568 data_time: 0.0256 memory: 16131 loss: 4.0822 loss_prob: 2.5169 loss_thr: 1.0348 loss_db: 0.5305 2022/10/25 20:34:06 - mmengine - INFO - Epoch(train) [110][60/63] lr: 1.6446e-03 eta: 14:54:03 time: 0.7918 data_time: 0.0063 memory: 16131 loss: 3.8644 loss_prob: 2.4110 loss_thr: 0.9855 loss_db: 0.4679 2022/10/25 20:34:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:34:12 - mmengine - INFO - Epoch(train) [111][5/63] lr: 1.6596e-03 eta: 14:54:03 time: 0.7154 data_time: 0.2074 memory: 16131 loss: 3.9962 loss_prob: 2.4611 loss_thr: 1.0180 loss_db: 0.5171 2022/10/25 20:34:17 - mmengine - INFO - Epoch(train) [111][10/63] lr: 1.6596e-03 eta: 14:53:50 time: 0.9916 data_time: 0.2119 memory: 16131 loss: 3.9747 loss_prob: 2.4492 loss_thr: 1.0158 loss_db: 0.5097 2022/10/25 20:34:23 - mmengine - INFO - Epoch(train) [111][15/63] lr: 1.6596e-03 eta: 14:53:50 time: 1.0969 data_time: 0.0132 memory: 16131 loss: 3.8927 loss_prob: 2.4077 loss_thr: 1.0057 loss_db: 0.4793 2022/10/25 20:34:27 - mmengine - INFO - Epoch(train) [111][20/63] lr: 1.6596e-03 eta: 14:54:04 time: 1.0048 data_time: 0.0088 memory: 16131 loss: 3.9473 loss_prob: 2.4401 loss_thr: 1.0132 loss_db: 0.4940 2022/10/25 20:34:31 - mmengine - INFO - Epoch(train) [111][25/63] lr: 1.6596e-03 eta: 14:54:04 time: 0.7923 data_time: 0.0182 memory: 16131 loss: 3.9072 loss_prob: 2.4152 loss_thr: 1.0092 loss_db: 0.4828 2022/10/25 20:34:35 - mmengine - INFO - Epoch(train) [111][30/63] lr: 1.6596e-03 eta: 14:53:52 time: 0.7341 data_time: 0.0281 memory: 16131 loss: 3.9897 loss_prob: 2.4631 loss_thr: 1.0194 loss_db: 0.5071 2022/10/25 20:34:39 - mmengine - INFO - Epoch(train) [111][35/63] lr: 1.6596e-03 eta: 14:53:52 time: 0.8336 data_time: 0.0193 memory: 16131 loss: 4.0616 loss_prob: 2.4979 loss_thr: 1.0307 loss_db: 0.5330 2022/10/25 20:34:45 - mmengine - INFO - Epoch(train) [111][40/63] lr: 1.6596e-03 eta: 14:54:05 time: 0.9989 data_time: 0.0144 memory: 16131 loss: 4.0511 loss_prob: 2.4923 loss_thr: 1.0324 loss_db: 0.5265 2022/10/25 20:34:47 - mmengine - INFO - Epoch(train) [111][45/63] lr: 1.6596e-03 eta: 14:54:05 time: 0.8032 data_time: 0.0114 memory: 16131 loss: 4.1719 loss_prob: 2.5703 loss_thr: 1.0279 loss_db: 0.5736 2022/10/25 20:34:51 - mmengine - INFO - Epoch(train) [111][50/63] lr: 1.6596e-03 eta: 14:53:41 time: 0.6152 data_time: 0.0141 memory: 16131 loss: 4.2070 loss_prob: 2.6118 loss_thr: 1.0306 loss_db: 0.5647 2022/10/25 20:34:54 - mmengine - INFO - Epoch(train) [111][55/63] lr: 1.6596e-03 eta: 14:53:41 time: 0.6317 data_time: 0.0213 memory: 16131 loss: 4.0344 loss_prob: 2.5130 loss_thr: 1.0133 loss_db: 0.5081 2022/10/25 20:34:57 - mmengine - INFO - Epoch(train) [111][60/63] lr: 1.6596e-03 eta: 14:53:14 time: 0.5884 data_time: 0.0234 memory: 16131 loss: 3.9692 loss_prob: 2.4592 loss_thr: 1.0034 loss_db: 0.5065 2022/10/25 20:35:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:35:06 - mmengine - INFO - Epoch(train) [112][5/63] lr: 1.6747e-03 eta: 14:53:14 time: 1.0653 data_time: 0.2505 memory: 16131 loss: 4.0315 loss_prob: 2.4975 loss_thr: 1.0192 loss_db: 0.5149 2022/10/25 20:35:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:35:09 - mmengine - INFO - Epoch(train) [112][10/63] lr: 1.6747e-03 eta: 14:52:54 time: 0.9090 data_time: 0.2451 memory: 16131 loss: 3.9342 loss_prob: 2.4447 loss_thr: 0.9911 loss_db: 0.4984 2022/10/25 20:35:14 - mmengine - INFO - Epoch(train) [112][15/63] lr: 1.6747e-03 eta: 14:52:54 time: 0.7795 data_time: 0.0049 memory: 16131 loss: 3.8552 loss_prob: 2.3827 loss_thr: 0.9808 loss_db: 0.4916 2022/10/25 20:35:17 - mmengine - INFO - Epoch(train) [112][20/63] lr: 1.6747e-03 eta: 14:52:50 time: 0.8167 data_time: 0.0074 memory: 16131 loss: 4.0908 loss_prob: 2.5203 loss_thr: 1.0427 loss_db: 0.5278 2022/10/25 20:35:20 - mmengine - INFO - Epoch(train) [112][25/63] lr: 1.6747e-03 eta: 14:52:50 time: 0.6148 data_time: 0.0388 memory: 16131 loss: 4.1936 loss_prob: 2.5790 loss_thr: 1.0650 loss_db: 0.5497 2022/10/25 20:35:23 - mmengine - INFO - Epoch(train) [112][30/63] lr: 1.6747e-03 eta: 14:52:20 time: 0.5624 data_time: 0.0360 memory: 16131 loss: 4.0915 loss_prob: 2.5197 loss_thr: 1.0301 loss_db: 0.5417 2022/10/25 20:35:25 - mmengine - INFO - Epoch(train) [112][35/63] lr: 1.6747e-03 eta: 14:52:20 time: 0.5104 data_time: 0.0054 memory: 16131 loss: 3.8919 loss_prob: 2.4103 loss_thr: 1.0002 loss_db: 0.4814 2022/10/25 20:35:30 - mmengine - INFO - Epoch(train) [112][40/63] lr: 1.6747e-03 eta: 14:52:11 time: 0.7595 data_time: 0.0064 memory: 16131 loss: 3.9553 loss_prob: 2.4675 loss_thr: 1.0020 loss_db: 0.4857 2022/10/25 20:35:33 - mmengine - INFO - Epoch(train) [112][45/63] lr: 1.6747e-03 eta: 14:52:11 time: 0.7909 data_time: 0.0085 memory: 16131 loss: 4.0947 loss_prob: 2.5451 loss_thr: 1.0148 loss_db: 0.5348 2022/10/25 20:35:37 - mmengine - INFO - Epoch(train) [112][50/63] lr: 1.6747e-03 eta: 14:51:51 time: 0.6588 data_time: 0.0266 memory: 16131 loss: 4.0499 loss_prob: 2.5069 loss_thr: 1.0252 loss_db: 0.5178 2022/10/25 20:35:41 - mmengine - INFO - Epoch(train) [112][55/63] lr: 1.6747e-03 eta: 14:51:51 time: 0.7454 data_time: 0.0240 memory: 16131 loss: 4.0289 loss_prob: 2.4963 loss_thr: 1.0266 loss_db: 0.5060 2022/10/25 20:35:45 - mmengine - INFO - Epoch(train) [112][60/63] lr: 1.6747e-03 eta: 14:51:42 time: 0.7719 data_time: 0.0046 memory: 16131 loss: 3.9503 loss_prob: 2.4413 loss_thr: 1.0119 loss_db: 0.4971 2022/10/25 20:35:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:35:55 - mmengine - INFO - Epoch(train) [113][5/63] lr: 1.6898e-03 eta: 14:51:42 time: 1.1307 data_time: 0.2492 memory: 16131 loss: 3.9030 loss_prob: 2.4037 loss_thr: 1.0171 loss_db: 0.4822 2022/10/25 20:35:59 - mmengine - INFO - Epoch(train) [113][10/63] lr: 1.6898e-03 eta: 14:52:00 time: 1.3032 data_time: 0.2457 memory: 16131 loss: 3.8349 loss_prob: 2.3570 loss_thr: 1.0173 loss_db: 0.4607 2022/10/25 20:36:04 - mmengine - INFO - Epoch(train) [113][15/63] lr: 1.6898e-03 eta: 14:52:00 time: 0.8751 data_time: 0.0047 memory: 16131 loss: 3.8138 loss_prob: 2.3640 loss_thr: 0.9946 loss_db: 0.4553 2022/10/25 20:36:07 - mmengine - INFO - Epoch(train) [113][20/63] lr: 1.6898e-03 eta: 14:51:49 time: 0.7476 data_time: 0.0046 memory: 16131 loss: 3.9125 loss_prob: 2.4294 loss_thr: 0.9964 loss_db: 0.4867 2022/10/25 20:36:10 - mmengine - INFO - Epoch(train) [113][25/63] lr: 1.6898e-03 eta: 14:51:49 time: 0.5863 data_time: 0.0383 memory: 16131 loss: 3.8619 loss_prob: 2.3876 loss_thr: 0.9945 loss_db: 0.4798 2022/10/25 20:36:13 - mmengine - INFO - Epoch(train) [113][30/63] lr: 1.6898e-03 eta: 14:51:22 time: 0.5862 data_time: 0.0387 memory: 16131 loss: 3.8297 loss_prob: 2.3724 loss_thr: 0.9895 loss_db: 0.4678 2022/10/25 20:36:17 - mmengine - INFO - Epoch(train) [113][35/63] lr: 1.6898e-03 eta: 14:51:22 time: 0.7223 data_time: 0.0050 memory: 16131 loss: 3.8738 loss_prob: 2.3838 loss_thr: 1.0044 loss_db: 0.4855 2022/10/25 20:36:20 - mmengine - INFO - Epoch(train) [113][40/63] lr: 1.6898e-03 eta: 14:51:10 time: 0.7288 data_time: 0.0046 memory: 16131 loss: 3.7227 loss_prob: 2.3022 loss_thr: 0.9718 loss_db: 0.4487 2022/10/25 20:36:23 - mmengine - INFO - Epoch(train) [113][45/63] lr: 1.6898e-03 eta: 14:51:10 time: 0.5558 data_time: 0.0071 memory: 16131 loss: 3.8220 loss_prob: 2.3777 loss_thr: 0.9832 loss_db: 0.4611 2022/10/25 20:36:26 - mmengine - INFO - Epoch(train) [113][50/63] lr: 1.6898e-03 eta: 14:50:51 time: 0.6674 data_time: 0.0284 memory: 16131 loss: 3.9377 loss_prob: 2.4410 loss_thr: 1.0053 loss_db: 0.4914 2022/10/25 20:36:30 - mmengine - INFO - Epoch(train) [113][55/63] lr: 1.6898e-03 eta: 14:50:51 time: 0.7047 data_time: 0.0296 memory: 16131 loss: 3.9704 loss_prob: 2.4581 loss_thr: 1.0089 loss_db: 0.5033 2022/10/25 20:36:33 - mmengine - INFO - Epoch(train) [113][60/63] lr: 1.6898e-03 eta: 14:50:29 time: 0.6378 data_time: 0.0088 memory: 16131 loss: 4.0623 loss_prob: 2.5035 loss_thr: 1.0333 loss_db: 0.5255 2022/10/25 20:36:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:36:41 - mmengine - INFO - Epoch(train) [114][5/63] lr: 1.7048e-03 eta: 14:50:29 time: 0.8947 data_time: 0.2199 memory: 16131 loss: 3.9687 loss_prob: 2.4583 loss_thr: 1.0128 loss_db: 0.4975 2022/10/25 20:36:45 - mmengine - INFO - Epoch(train) [114][10/63] lr: 1.7048e-03 eta: 14:50:27 time: 1.0995 data_time: 0.2193 memory: 16131 loss: 3.8972 loss_prob: 2.4226 loss_thr: 0.9941 loss_db: 0.4806 2022/10/25 20:36:48 - mmengine - INFO - Epoch(train) [114][15/63] lr: 1.7048e-03 eta: 14:50:27 time: 0.7705 data_time: 0.0082 memory: 16131 loss: 3.8824 loss_prob: 2.4171 loss_thr: 0.9929 loss_db: 0.4724 2022/10/25 20:36:51 - mmengine - INFO - Epoch(train) [114][20/63] lr: 1.7048e-03 eta: 14:49:59 time: 0.5633 data_time: 0.0067 memory: 16131 loss: 3.9048 loss_prob: 2.4264 loss_thr: 1.0032 loss_db: 0.4752 2022/10/25 20:36:55 - mmengine - INFO - Epoch(train) [114][25/63] lr: 1.7048e-03 eta: 14:49:59 time: 0.6963 data_time: 0.0526 memory: 16131 loss: 3.9215 loss_prob: 2.4295 loss_thr: 1.0063 loss_db: 0.4857 2022/10/25 20:36:58 - mmengine - INFO - Epoch(train) [114][30/63] lr: 1.7048e-03 eta: 14:49:44 time: 0.7067 data_time: 0.0574 memory: 16131 loss: 3.8976 loss_prob: 2.4073 loss_thr: 1.0004 loss_db: 0.4899 2022/10/25 20:37:01 - mmengine - INFO - Epoch(train) [114][35/63] lr: 1.7048e-03 eta: 14:49:44 time: 0.5226 data_time: 0.0116 memory: 16131 loss: 3.8677 loss_prob: 2.3975 loss_thr: 0.9943 loss_db: 0.4758 2022/10/25 20:37:03 - mmengine - INFO - Epoch(train) [114][40/63] lr: 1.7048e-03 eta: 14:49:11 time: 0.5173 data_time: 0.0051 memory: 16131 loss: 3.8171 loss_prob: 2.3720 loss_thr: 0.9776 loss_db: 0.4675 2022/10/25 20:37:06 - mmengine - INFO - Epoch(train) [114][45/63] lr: 1.7048e-03 eta: 14:49:11 time: 0.5133 data_time: 0.0110 memory: 16131 loss: 3.9435 loss_prob: 2.4508 loss_thr: 0.9892 loss_db: 0.5035 2022/10/25 20:37:10 - mmengine - INFO - Epoch(train) [114][50/63] lr: 1.7048e-03 eta: 14:48:57 time: 0.7170 data_time: 0.0499 memory: 16131 loss: 4.0787 loss_prob: 2.5303 loss_thr: 1.0188 loss_db: 0.5296 2022/10/25 20:37:15 - mmengine - INFO - Epoch(train) [114][55/63] lr: 1.7048e-03 eta: 14:48:57 time: 0.9042 data_time: 0.0484 memory: 16131 loss: 4.1113 loss_prob: 2.5867 loss_thr: 0.9960 loss_db: 0.5285 2022/10/25 20:37:18 - mmengine - INFO - Epoch(train) [114][60/63] lr: 1.7048e-03 eta: 14:48:46 time: 0.7443 data_time: 0.0119 memory: 16131 loss: 4.1095 loss_prob: 2.5745 loss_thr: 0.9958 loss_db: 0.5392 2022/10/25 20:37:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:37:25 - mmengine - INFO - Epoch(train) [115][5/63] lr: 1.7199e-03 eta: 14:48:46 time: 0.8897 data_time: 0.2100 memory: 16131 loss: 3.9184 loss_prob: 2.4428 loss_thr: 0.9959 loss_db: 0.4797 2022/10/25 20:37:29 - mmengine - INFO - Epoch(train) [115][10/63] lr: 1.7199e-03 eta: 14:48:33 time: 0.9820 data_time: 0.2104 memory: 16131 loss: 3.7904 loss_prob: 2.3606 loss_thr: 0.9777 loss_db: 0.4521 2022/10/25 20:37:34 - mmengine - INFO - Epoch(train) [115][15/63] lr: 1.7199e-03 eta: 14:48:33 time: 0.8789 data_time: 0.0123 memory: 16131 loss: 3.9485 loss_prob: 2.4319 loss_thr: 1.0146 loss_db: 0.5020 2022/10/25 20:37:37 - mmengine - INFO - Epoch(train) [115][20/63] lr: 1.7199e-03 eta: 14:48:23 time: 0.7583 data_time: 0.0114 memory: 16131 loss: 3.9962 loss_prob: 2.4575 loss_thr: 1.0270 loss_db: 0.5118 2022/10/25 20:37:42 - mmengine - INFO - Epoch(train) [115][25/63] lr: 1.7199e-03 eta: 14:48:23 time: 0.7507 data_time: 0.0317 memory: 16131 loss: 3.8376 loss_prob: 2.3738 loss_thr: 0.9996 loss_db: 0.4643 2022/10/25 20:37:44 - mmengine - INFO - Epoch(train) [115][30/63] lr: 1.7199e-03 eta: 14:48:13 time: 0.7582 data_time: 0.0328 memory: 16131 loss: 3.6839 loss_prob: 2.2794 loss_thr: 0.9722 loss_db: 0.4323 2022/10/25 20:37:47 - mmengine - INFO - Epoch(train) [115][35/63] lr: 1.7199e-03 eta: 14:48:13 time: 0.5621 data_time: 0.0058 memory: 16131 loss: 3.7774 loss_prob: 2.3426 loss_thr: 0.9871 loss_db: 0.4478 2022/10/25 20:37:51 - mmengine - INFO - Epoch(train) [115][40/63] lr: 1.7199e-03 eta: 14:47:50 time: 0.6103 data_time: 0.0075 memory: 16131 loss: 3.8424 loss_prob: 2.3761 loss_thr: 0.9966 loss_db: 0.4697 2022/10/25 20:37:53 - mmengine - INFO - Epoch(train) [115][45/63] lr: 1.7199e-03 eta: 14:47:50 time: 0.5902 data_time: 0.0086 memory: 16131 loss: 3.8156 loss_prob: 2.3693 loss_thr: 0.9764 loss_db: 0.4699 2022/10/25 20:37:58 - mmengine - INFO - Epoch(train) [115][50/63] lr: 1.7199e-03 eta: 14:47:39 time: 0.7496 data_time: 0.0409 memory: 16131 loss: 3.8631 loss_prob: 2.4115 loss_thr: 0.9882 loss_db: 0.4634 2022/10/25 20:38:01 - mmengine - INFO - Epoch(train) [115][55/63] lr: 1.7199e-03 eta: 14:47:39 time: 0.7517 data_time: 0.0401 memory: 16131 loss: 3.9393 loss_prob: 2.4358 loss_thr: 1.0354 loss_db: 0.4681 2022/10/25 20:38:03 - mmengine - INFO - Epoch(train) [115][60/63] lr: 1.7199e-03 eta: 14:47:07 time: 0.5179 data_time: 0.0053 memory: 16131 loss: 3.9320 loss_prob: 2.4324 loss_thr: 1.0207 loss_db: 0.4789 2022/10/25 20:38:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:38:12 - mmengine - INFO - Epoch(train) [116][5/63] lr: 1.7349e-03 eta: 14:47:07 time: 0.9849 data_time: 0.1668 memory: 16131 loss: 3.9808 loss_prob: 2.4656 loss_thr: 1.0101 loss_db: 0.5050 2022/10/25 20:38:16 - mmengine - INFO - Epoch(train) [116][10/63] lr: 1.7349e-03 eta: 14:47:07 time: 1.1224 data_time: 0.1607 memory: 16131 loss: 4.0534 loss_prob: 2.5015 loss_thr: 1.0215 loss_db: 0.5304 2022/10/25 20:38:21 - mmengine - INFO - Epoch(train) [116][15/63] lr: 1.7349e-03 eta: 14:47:07 time: 0.9291 data_time: 0.0066 memory: 16131 loss: 4.0034 loss_prob: 2.4736 loss_thr: 1.0295 loss_db: 0.5003 2022/10/25 20:38:25 - mmengine - INFO - Epoch(train) [116][20/63] lr: 1.7349e-03 eta: 14:47:11 time: 0.9101 data_time: 0.0077 memory: 16131 loss: 3.8876 loss_prob: 2.4029 loss_thr: 1.0169 loss_db: 0.4678 2022/10/25 20:38:28 - mmengine - INFO - Epoch(train) [116][25/63] lr: 1.7349e-03 eta: 14:47:11 time: 0.6716 data_time: 0.0107 memory: 16131 loss: 3.8150 loss_prob: 2.3588 loss_thr: 0.9988 loss_db: 0.4573 2022/10/25 20:38:31 - mmengine - INFO - Epoch(train) [116][30/63] lr: 1.7349e-03 eta: 14:46:47 time: 0.6019 data_time: 0.0347 memory: 16131 loss: 3.9876 loss_prob: 2.4478 loss_thr: 1.0250 loss_db: 0.5147 2022/10/25 20:38:36 - mmengine - INFO - Epoch(train) [116][35/63] lr: 1.7349e-03 eta: 14:46:47 time: 0.7653 data_time: 0.0306 memory: 16131 loss: 4.0027 loss_prob: 2.4635 loss_thr: 1.0218 loss_db: 0.5173 2022/10/25 20:38:41 - mmengine - INFO - Epoch(train) [116][40/63] lr: 1.7349e-03 eta: 14:47:02 time: 1.0245 data_time: 0.0061 memory: 16131 loss: 3.9573 loss_prob: 2.4511 loss_thr: 1.0065 loss_db: 0.4996 2022/10/25 20:38:44 - mmengine - INFO - Epoch(train) [116][45/63] lr: 1.7349e-03 eta: 14:47:02 time: 0.8877 data_time: 0.0073 memory: 16131 loss: 3.9270 loss_prob: 2.4293 loss_thr: 1.0055 loss_db: 0.4922 2022/10/25 20:38:48 - mmengine - INFO - Epoch(train) [116][50/63] lr: 1.7349e-03 eta: 14:46:41 time: 0.6384 data_time: 0.0183 memory: 16131 loss: 3.8143 loss_prob: 2.3620 loss_thr: 0.9939 loss_db: 0.4583 2022/10/25 20:38:52 - mmengine - INFO - Epoch(train) [116][55/63] lr: 1.7349e-03 eta: 14:46:41 time: 0.7035 data_time: 0.0272 memory: 16131 loss: 3.9423 loss_prob: 2.4422 loss_thr: 1.0068 loss_db: 0.4933 2022/10/25 20:38:55 - mmengine - INFO - Epoch(train) [116][60/63] lr: 1.7349e-03 eta: 14:46:35 time: 0.7936 data_time: 0.0160 memory: 16131 loss: 4.0457 loss_prob: 2.5024 loss_thr: 1.0201 loss_db: 0.5232 2022/10/25 20:38:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:39:03 - mmengine - INFO - Epoch(train) [117][5/63] lr: 1.7500e-03 eta: 14:46:35 time: 0.9338 data_time: 0.1924 memory: 16131 loss: 3.8908 loss_prob: 2.4237 loss_thr: 0.9870 loss_db: 0.4800 2022/10/25 20:39:06 - mmengine - INFO - Epoch(train) [117][10/63] lr: 1.7500e-03 eta: 14:46:10 time: 0.8528 data_time: 0.1926 memory: 16131 loss: 3.9323 loss_prob: 2.4437 loss_thr: 1.0092 loss_db: 0.4794 2022/10/25 20:39:10 - mmengine - INFO - Epoch(train) [117][15/63] lr: 1.7500e-03 eta: 14:46:10 time: 0.7330 data_time: 0.0050 memory: 16131 loss: 3.8745 loss_prob: 2.3969 loss_thr: 1.0028 loss_db: 0.4748 2022/10/25 20:39:13 - mmengine - INFO - Epoch(train) [117][20/63] lr: 1.7500e-03 eta: 14:46:00 time: 0.7570 data_time: 0.0088 memory: 16131 loss: 3.8894 loss_prob: 2.3939 loss_thr: 1.0249 loss_db: 0.4706 2022/10/25 20:39:17 - mmengine - INFO - Epoch(train) [117][25/63] lr: 1.7500e-03 eta: 14:46:00 time: 0.6739 data_time: 0.0312 memory: 16131 loss: 3.9177 loss_prob: 2.4130 loss_thr: 1.0240 loss_db: 0.4807 2022/10/25 20:39:22 - mmengine - INFO - Epoch(train) [117][30/63] lr: 1.7500e-03 eta: 14:45:59 time: 0.8473 data_time: 0.0450 memory: 16131 loss: 3.9569 loss_prob: 2.4560 loss_thr: 1.0063 loss_db: 0.4946 2022/10/25 20:39:25 - mmengine - INFO - Epoch(train) [117][35/63] lr: 1.7500e-03 eta: 14:45:59 time: 0.7621 data_time: 0.0305 memory: 16131 loss: 3.9356 loss_prob: 2.4458 loss_thr: 0.9982 loss_db: 0.4916 2022/10/25 20:39:27 - mmengine - INFO - Epoch(train) [117][40/63] lr: 1.7500e-03 eta: 14:45:30 time: 0.5553 data_time: 0.0132 memory: 16131 loss: 3.8721 loss_prob: 2.3924 loss_thr: 1.0009 loss_db: 0.4788 2022/10/25 20:39:31 - mmengine - INFO - Epoch(train) [117][45/63] lr: 1.7500e-03 eta: 14:45:30 time: 0.6487 data_time: 0.0055 memory: 16131 loss: 3.8874 loss_prob: 2.3967 loss_thr: 1.0050 loss_db: 0.4857 2022/10/25 20:39:34 - mmengine - INFO - Epoch(train) [117][50/63] lr: 1.7500e-03 eta: 14:45:16 time: 0.7099 data_time: 0.0237 memory: 16131 loss: 3.8520 loss_prob: 2.3816 loss_thr: 0.9952 loss_db: 0.4752 2022/10/25 20:39:38 - mmengine - INFO - Epoch(train) [117][55/63] lr: 1.7500e-03 eta: 14:45:16 time: 0.7211 data_time: 0.0278 memory: 16131 loss: 3.8223 loss_prob: 2.3838 loss_thr: 0.9826 loss_db: 0.4559 2022/10/25 20:39:43 - mmengine - INFO - Epoch(train) [117][60/63] lr: 1.7500e-03 eta: 14:45:16 time: 0.8654 data_time: 0.0091 memory: 16131 loss: 3.9840 loss_prob: 2.4694 loss_thr: 1.0224 loss_db: 0.4922 2022/10/25 20:39:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:39:51 - mmengine - INFO - Epoch(train) [118][5/63] lr: 1.7651e-03 eta: 14:45:16 time: 1.0056 data_time: 0.1963 memory: 16131 loss: 3.8937 loss_prob: 2.3884 loss_thr: 1.0240 loss_db: 0.4813 2022/10/25 20:39:53 - mmengine - INFO - Epoch(train) [118][10/63] lr: 1.7651e-03 eta: 14:44:42 time: 0.7499 data_time: 0.1969 memory: 16131 loss: 3.7724 loss_prob: 2.3190 loss_thr: 0.9967 loss_db: 0.4567 2022/10/25 20:39:56 - mmengine - INFO - Epoch(train) [118][15/63] lr: 1.7651e-03 eta: 14:44:42 time: 0.5353 data_time: 0.0067 memory: 16131 loss: 3.7720 loss_prob: 2.3263 loss_thr: 0.9901 loss_db: 0.4556 2022/10/25 20:40:01 - mmengine - INFO - Epoch(train) [118][20/63] lr: 1.7651e-03 eta: 14:44:35 time: 0.7924 data_time: 0.0090 memory: 16131 loss: 3.9191 loss_prob: 2.4191 loss_thr: 1.0157 loss_db: 0.4843 2022/10/25 20:40:07 - mmengine - INFO - Epoch(train) [118][25/63] lr: 1.7651e-03 eta: 14:44:35 time: 1.0829 data_time: 0.0260 memory: 16131 loss: 4.0293 loss_prob: 2.4848 loss_thr: 1.0317 loss_db: 0.5128 2022/10/25 20:40:11 - mmengine - INFO - Epoch(train) [118][30/63] lr: 1.7651e-03 eta: 14:44:44 time: 0.9578 data_time: 0.0445 memory: 16131 loss: 4.0079 loss_prob: 2.4770 loss_thr: 1.0245 loss_db: 0.5064 2022/10/25 20:40:15 - mmengine - INFO - Epoch(train) [118][35/63] lr: 1.7651e-03 eta: 14:44:44 time: 0.7885 data_time: 0.0262 memory: 16131 loss: 3.8856 loss_prob: 2.4039 loss_thr: 1.0039 loss_db: 0.4777 2022/10/25 20:40:23 - mmengine - INFO - Epoch(train) [118][40/63] lr: 1.7651e-03 eta: 14:45:15 time: 1.1936 data_time: 0.0054 memory: 16131 loss: 3.8617 loss_prob: 2.3764 loss_thr: 1.0010 loss_db: 0.4843 2022/10/25 20:40:29 - mmengine - INFO - Epoch(train) [118][45/63] lr: 1.7651e-03 eta: 14:45:15 time: 1.4676 data_time: 0.0141 memory: 16131 loss: 3.9423 loss_prob: 2.4324 loss_thr: 1.0033 loss_db: 0.5066 2022/10/25 20:40:32 - mmengine - INFO - Epoch(train) [118][50/63] lr: 1.7651e-03 eta: 14:45:24 time: 0.9609 data_time: 0.0307 memory: 16131 loss: 3.9581 loss_prob: 2.4552 loss_thr: 1.0046 loss_db: 0.4982 2022/10/25 20:40:36 - mmengine - INFO - Epoch(train) [118][55/63] lr: 1.7651e-03 eta: 14:45:24 time: 0.6234 data_time: 0.0246 memory: 16131 loss: 4.1348 loss_prob: 2.5570 loss_thr: 1.0277 loss_db: 0.5500 2022/10/25 20:40:42 - mmengine - INFO - Epoch(train) [118][60/63] lr: 1.7651e-03 eta: 14:45:31 time: 0.9498 data_time: 0.0076 memory: 16131 loss: 3.9387 loss_prob: 2.4259 loss_thr: 0.9987 loss_db: 0.5141 2022/10/25 20:40:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:40:53 - mmengine - INFO - Epoch(train) [119][5/63] lr: 1.7801e-03 eta: 14:45:31 time: 1.6011 data_time: 0.2368 memory: 16131 loss: 3.7512 loss_prob: 2.2986 loss_thr: 1.0039 loss_db: 0.4487 2022/10/25 20:40:59 - mmengine - INFO - Epoch(train) [119][10/63] lr: 1.7801e-03 eta: 14:45:57 time: 1.4050 data_time: 0.2383 memory: 16131 loss: 3.9301 loss_prob: 2.3990 loss_thr: 1.0338 loss_db: 0.4973 2022/10/25 20:41:02 - mmengine - INFO - Epoch(train) [119][15/63] lr: 1.7801e-03 eta: 14:45:57 time: 0.8952 data_time: 0.0135 memory: 16131 loss: 3.9745 loss_prob: 2.4518 loss_thr: 1.0260 loss_db: 0.4966 2022/10/25 20:41:06 - mmengine - INFO - Epoch(train) [119][20/63] lr: 1.7801e-03 eta: 14:45:43 time: 0.7062 data_time: 0.0130 memory: 16131 loss: 3.9147 loss_prob: 2.4107 loss_thr: 1.0324 loss_db: 0.4716 2022/10/25 20:41:09 - mmengine - INFO - Epoch(train) [119][25/63] lr: 1.7801e-03 eta: 14:45:43 time: 0.6580 data_time: 0.0336 memory: 16131 loss: 3.8671 loss_prob: 2.3793 loss_thr: 1.0247 loss_db: 0.4631 2022/10/25 20:41:12 - mmengine - INFO - Epoch(train) [119][30/63] lr: 1.7801e-03 eta: 14:45:20 time: 0.6219 data_time: 0.0439 memory: 16131 loss: 3.9194 loss_prob: 2.4319 loss_thr: 1.0121 loss_db: 0.4754 2022/10/25 20:41:16 - mmengine - INFO - Epoch(train) [119][35/63] lr: 1.7801e-03 eta: 14:45:20 time: 0.6672 data_time: 0.0199 memory: 16131 loss: 3.8655 loss_prob: 2.3951 loss_thr: 1.0045 loss_db: 0.4660 2022/10/25 20:41:18 - mmengine - INFO - Epoch(train) [119][40/63] lr: 1.7801e-03 eta: 14:44:59 time: 0.6297 data_time: 0.0143 memory: 16131 loss: 3.7919 loss_prob: 2.3414 loss_thr: 1.0010 loss_db: 0.4496 2022/10/25 20:41:22 - mmengine - INFO - Epoch(train) [119][45/63] lr: 1.7801e-03 eta: 14:44:59 time: 0.6127 data_time: 0.0128 memory: 16131 loss: 3.7801 loss_prob: 2.3280 loss_thr: 1.0083 loss_db: 0.4437 2022/10/25 20:41:26 - mmengine - INFO - Epoch(train) [119][50/63] lr: 1.7801e-03 eta: 14:44:48 time: 0.7451 data_time: 0.0252 memory: 16131 loss: 3.8707 loss_prob: 2.3689 loss_thr: 1.0199 loss_db: 0.4819 2022/10/25 20:41:31 - mmengine - INFO - Epoch(train) [119][55/63] lr: 1.7801e-03 eta: 14:44:48 time: 0.9277 data_time: 0.0229 memory: 16131 loss: 3.8775 loss_prob: 2.3972 loss_thr: 1.0046 loss_db: 0.4757 2022/10/25 20:41:35 - mmengine - INFO - Epoch(train) [119][60/63] lr: 1.7801e-03 eta: 14:44:54 time: 0.9356 data_time: 0.0052 memory: 16131 loss: 3.8710 loss_prob: 2.4017 loss_thr: 1.0010 loss_db: 0.4683 2022/10/25 20:41:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:41:42 - mmengine - INFO - Epoch(train) [120][5/63] lr: 1.7952e-03 eta: 14:44:54 time: 0.8763 data_time: 0.1963 memory: 16131 loss: 4.0490 loss_prob: 2.4794 loss_thr: 1.0395 loss_db: 0.5302 2022/10/25 20:41:45 - mmengine - INFO - Epoch(train) [120][10/63] lr: 1.7952e-03 eta: 14:44:28 time: 0.8363 data_time: 0.1951 memory: 16131 loss: 3.9802 loss_prob: 2.4554 loss_thr: 1.0106 loss_db: 0.5141 2022/10/25 20:41:49 - mmengine - INFO - Epoch(train) [120][15/63] lr: 1.7952e-03 eta: 14:44:28 time: 0.7290 data_time: 0.0049 memory: 16131 loss: 4.1823 loss_prob: 2.6048 loss_thr: 1.0142 loss_db: 0.5633 2022/10/25 20:41:53 - mmengine - INFO - Epoch(train) [120][20/63] lr: 1.7952e-03 eta: 14:44:22 time: 0.8011 data_time: 0.0051 memory: 16131 loss: 4.5894 loss_prob: 2.8390 loss_thr: 1.0534 loss_db: 0.6970 2022/10/25 20:41:57 - mmengine - INFO - Epoch(train) [120][25/63] lr: 1.7952e-03 eta: 14:44:22 time: 0.7987 data_time: 0.0151 memory: 16131 loss: 4.4423 loss_prob: 2.7262 loss_thr: 1.0761 loss_db: 0.6400 2022/10/25 20:42:02 - mmengine - INFO - Epoch(train) [120][30/63] lr: 1.7952e-03 eta: 14:44:28 time: 0.9299 data_time: 0.0448 memory: 16131 loss: 4.1149 loss_prob: 2.5282 loss_thr: 1.0584 loss_db: 0.5283 2022/10/25 20:42:07 - mmengine - INFO - Epoch(train) [120][35/63] lr: 1.7952e-03 eta: 14:44:28 time: 0.9964 data_time: 0.0346 memory: 16131 loss: 3.9795 loss_prob: 2.4630 loss_thr: 1.0247 loss_db: 0.4919 2022/10/25 20:42:11 - mmengine - INFO - Epoch(train) [120][40/63] lr: 1.7952e-03 eta: 14:44:31 time: 0.8991 data_time: 0.0071 memory: 16131 loss: 3.8094 loss_prob: 2.3707 loss_thr: 0.9877 loss_db: 0.4511 2022/10/25 20:42:17 - mmengine - INFO - Epoch(train) [120][45/63] lr: 1.7952e-03 eta: 14:44:31 time: 0.9553 data_time: 0.0079 memory: 16131 loss: 3.6469 loss_prob: 2.2565 loss_thr: 0.9720 loss_db: 0.4183 2022/10/25 20:42:20 - mmengine - INFO - Epoch(train) [120][50/63] lr: 1.7952e-03 eta: 14:44:32 time: 0.8758 data_time: 0.0138 memory: 16131 loss: 3.8627 loss_prob: 2.3774 loss_thr: 1.0122 loss_db: 0.4732 2022/10/25 20:42:26 - mmengine - INFO - Epoch(train) [120][55/63] lr: 1.7952e-03 eta: 14:44:32 time: 0.8916 data_time: 0.0384 memory: 16131 loss: 4.0786 loss_prob: 2.5011 loss_thr: 1.0455 loss_db: 0.5319 2022/10/25 20:42:30 - mmengine - INFO - Epoch(train) [120][60/63] lr: 1.7952e-03 eta: 14:44:46 time: 1.0216 data_time: 0.0336 memory: 16131 loss: 3.9559 loss_prob: 2.4460 loss_thr: 1.0193 loss_db: 0.4906 2022/10/25 20:42:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:42:32 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/10/25 20:42:39 - mmengine - INFO - Epoch(val) [120][5/32] eta: 14:44:46 time: 0.6262 data_time: 0.0923 memory: 16131 2022/10/25 20:42:42 - mmengine - INFO - Epoch(val) [120][10/32] eta: 0:00:13 time: 0.6208 data_time: 0.1125 memory: 15724 2022/10/25 20:42:45 - mmengine - INFO - Epoch(val) [120][15/32] eta: 0:00:13 time: 0.5712 data_time: 0.0603 memory: 15724 2022/10/25 20:42:48 - mmengine - INFO - Epoch(val) [120][20/32] eta: 0:00:07 time: 0.6029 data_time: 0.0791 memory: 15724 2022/10/25 20:42:51 - mmengine - INFO - Epoch(val) [120][25/32] eta: 0:00:07 time: 0.5733 data_time: 0.0588 memory: 15724 2022/10/25 20:42:53 - mmengine - INFO - Epoch(val) [120][30/32] eta: 0:00:01 time: 0.5309 data_time: 0.0214 memory: 15724 2022/10/25 20:42:54 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.2884, precision: 0.3131, hmean: 0.3003 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.2605, precision: 0.5932, hmean: 0.3620 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.1348, precision: 0.7018, hmean: 0.2262 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0255, precision: 0.7465, hmean: 0.0493 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0010, precision: 1.0000, hmean: 0.0019 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:42:54 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 20:42:54 - mmengine - INFO - Epoch(val) [120][32/32] icdar/precision: 0.5932 icdar/recall: 0.2605 icdar/hmean: 0.3620 2022/10/25 20:43:00 - mmengine - INFO - Epoch(train) [121][5/63] lr: 1.8102e-03 eta: 0:00:01 time: 1.0565 data_time: 0.1816 memory: 16131 loss: 3.9775 loss_prob: 2.4974 loss_thr: 0.9935 loss_db: 0.4866 2022/10/25 20:43:05 - mmengine - INFO - Epoch(train) [121][10/63] lr: 1.8102e-03 eta: 14:44:44 time: 1.1084 data_time: 0.1906 memory: 16131 loss: 3.8923 loss_prob: 2.4390 loss_thr: 0.9797 loss_db: 0.4736 2022/10/25 20:43:08 - mmengine - INFO - Epoch(train) [121][15/63] lr: 1.8102e-03 eta: 14:44:44 time: 0.7823 data_time: 0.0139 memory: 16131 loss: 3.9742 loss_prob: 2.4632 loss_thr: 1.0030 loss_db: 0.5081 2022/10/25 20:43:13 - mmengine - INFO - Epoch(train) [121][20/63] lr: 1.8102e-03 eta: 14:44:42 time: 0.8381 data_time: 0.0060 memory: 16131 loss: 4.0471 loss_prob: 2.5058 loss_thr: 1.0362 loss_db: 0.5051 2022/10/25 20:43:17 - mmengine - INFO - Epoch(train) [121][25/63] lr: 1.8102e-03 eta: 14:44:42 time: 0.8905 data_time: 0.0183 memory: 16131 loss: 3.9179 loss_prob: 2.4269 loss_thr: 1.0346 loss_db: 0.4564 2022/10/25 20:43:23 - mmengine - INFO - Epoch(train) [121][30/63] lr: 1.8102e-03 eta: 14:44:53 time: 0.9888 data_time: 0.0371 memory: 16131 loss: 3.8918 loss_prob: 2.3974 loss_thr: 1.0214 loss_db: 0.4729 2022/10/25 20:43:27 - mmengine - INFO - Epoch(train) [121][35/63] lr: 1.8102e-03 eta: 14:44:53 time: 1.0272 data_time: 0.0257 memory: 16131 loss: 4.0063 loss_prob: 2.4713 loss_thr: 1.0337 loss_db: 0.5014 2022/10/25 20:43:30 - mmengine - INFO - Epoch(train) [121][40/63] lr: 1.8102e-03 eta: 14:44:37 time: 0.6902 data_time: 0.0082 memory: 16131 loss: 4.0231 loss_prob: 2.5010 loss_thr: 1.0181 loss_db: 0.5039 2022/10/25 20:43:33 - mmengine - INFO - Epoch(train) [121][45/63] lr: 1.8102e-03 eta: 14:44:37 time: 0.6030 data_time: 0.0082 memory: 16131 loss: 3.9819 loss_prob: 2.4720 loss_thr: 1.0113 loss_db: 0.4987 2022/10/25 20:43:36 - mmengine - INFO - Epoch(train) [121][50/63] lr: 1.8102e-03 eta: 14:44:10 time: 0.5686 data_time: 0.0162 memory: 16131 loss: 3.9335 loss_prob: 2.4412 loss_thr: 1.0183 loss_db: 0.4739 2022/10/25 20:43:39 - mmengine - INFO - Epoch(train) [121][55/63] lr: 1.8102e-03 eta: 14:44:10 time: 0.5376 data_time: 0.0243 memory: 16131 loss: 3.8975 loss_prob: 2.4257 loss_thr: 1.0078 loss_db: 0.4640 2022/10/25 20:43:44 - mmengine - INFO - Epoch(train) [121][60/63] lr: 1.8102e-03 eta: 14:44:04 time: 0.7972 data_time: 0.0152 memory: 16131 loss: 3.9041 loss_prob: 2.4207 loss_thr: 1.0012 loss_db: 0.4823 2022/10/25 20:43:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:43:55 - mmengine - INFO - Epoch(train) [122][5/63] lr: 1.8253e-03 eta: 14:44:04 time: 1.4079 data_time: 0.2080 memory: 16131 loss: 3.9903 loss_prob: 2.4584 loss_thr: 1.0264 loss_db: 0.5055 2022/10/25 20:44:00 - mmengine - INFO - Epoch(train) [122][10/63] lr: 1.8253e-03 eta: 14:44:25 time: 1.3647 data_time: 0.2188 memory: 16131 loss: 4.0041 loss_prob: 2.4644 loss_thr: 1.0334 loss_db: 0.5064 2022/10/25 20:44:05 - mmengine - INFO - Epoch(train) [122][15/63] lr: 1.8253e-03 eta: 14:44:25 time: 0.9714 data_time: 0.0195 memory: 16131 loss: 3.9524 loss_prob: 2.4359 loss_thr: 1.0177 loss_db: 0.4988 2022/10/25 20:44:13 - mmengine - INFO - Epoch(train) [122][20/63] lr: 1.8253e-03 eta: 14:45:04 time: 1.3141 data_time: 0.0109 memory: 16131 loss: 3.8835 loss_prob: 2.3860 loss_thr: 1.0096 loss_db: 0.4880 2022/10/25 20:44:17 - mmengine - INFO - Epoch(train) [122][25/63] lr: 1.8253e-03 eta: 14:45:04 time: 1.1519 data_time: 0.0269 memory: 16131 loss: 3.8344 loss_prob: 2.3508 loss_thr: 1.0177 loss_db: 0.4659 2022/10/25 20:44:21 - mmengine - INFO - Epoch(train) [122][30/63] lr: 1.8253e-03 eta: 14:45:01 time: 0.8352 data_time: 0.0308 memory: 16131 loss: 3.9913 loss_prob: 2.4575 loss_thr: 1.0377 loss_db: 0.4961 2022/10/25 20:44:26 - mmengine - INFO - Epoch(train) [122][35/63] lr: 1.8253e-03 eta: 14:45:01 time: 0.9497 data_time: 0.0199 memory: 16131 loss: 4.0711 loss_prob: 2.5274 loss_thr: 1.0349 loss_db: 0.5087 2022/10/25 20:44:29 - mmengine - INFO - Epoch(train) [122][40/63] lr: 1.8253e-03 eta: 14:44:55 time: 0.8040 data_time: 0.0159 memory: 16131 loss: 3.9819 loss_prob: 2.4692 loss_thr: 1.0128 loss_db: 0.5000 2022/10/25 20:44:34 - mmengine - INFO - Epoch(train) [122][45/63] lr: 1.8253e-03 eta: 14:44:55 time: 0.8074 data_time: 0.0100 memory: 16131 loss: 3.8776 loss_prob: 2.4065 loss_thr: 0.9960 loss_db: 0.4751 2022/10/25 20:44:41 - mmengine - INFO - Epoch(train) [122][50/63] lr: 1.8253e-03 eta: 14:45:19 time: 1.1387 data_time: 0.0174 memory: 16131 loss: 3.8741 loss_prob: 2.4010 loss_thr: 1.0116 loss_db: 0.4615 2022/10/25 20:44:47 - mmengine - INFO - Epoch(train) [122][55/63] lr: 1.8253e-03 eta: 14:45:19 time: 1.3348 data_time: 0.0212 memory: 16131 loss: 3.8427 loss_prob: 2.3693 loss_thr: 1.0196 loss_db: 0.4539 2022/10/25 20:44:51 - mmengine - INFO - Epoch(train) [122][60/63] lr: 1.8253e-03 eta: 14:45:38 time: 1.0794 data_time: 0.0113 memory: 16131 loss: 3.7507 loss_prob: 2.3143 loss_thr: 1.0074 loss_db: 0.4289 2022/10/25 20:44:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:45:04 - mmengine - INFO - Epoch(train) [123][5/63] lr: 1.8404e-03 eta: 14:45:38 time: 1.3452 data_time: 0.2354 memory: 16131 loss: 4.1102 loss_prob: 2.5363 loss_thr: 1.0462 loss_db: 0.5277 2022/10/25 20:45:10 - mmengine - INFO - Epoch(train) [123][10/63] lr: 1.8404e-03 eta: 14:46:19 time: 1.6031 data_time: 0.2333 memory: 16131 loss: 4.0560 loss_prob: 2.4808 loss_thr: 1.0434 loss_db: 0.5318 2022/10/25 20:45:13 - mmengine - INFO - Epoch(train) [123][15/63] lr: 1.8404e-03 eta: 14:46:19 time: 0.9002 data_time: 0.0111 memory: 16131 loss: 3.9468 loss_prob: 2.4229 loss_thr: 1.0276 loss_db: 0.4964 2022/10/25 20:45:17 - mmengine - INFO - Epoch(train) [123][20/63] lr: 1.8404e-03 eta: 14:45:58 time: 0.6319 data_time: 0.0094 memory: 16131 loss: 3.8930 loss_prob: 2.4069 loss_thr: 1.0148 loss_db: 0.4712 2022/10/25 20:45:20 - mmengine - INFO - Epoch(train) [123][25/63] lr: 1.8404e-03 eta: 14:45:58 time: 0.6609 data_time: 0.0302 memory: 16131 loss: 3.9472 loss_prob: 2.4410 loss_thr: 1.0203 loss_db: 0.4860 2022/10/25 20:45:22 - mmengine - INFO - Epoch(train) [123][30/63] lr: 1.8404e-03 eta: 14:45:33 time: 0.5851 data_time: 0.0324 memory: 16131 loss: 3.9752 loss_prob: 2.4605 loss_thr: 1.0248 loss_db: 0.4899 2022/10/25 20:45:25 - mmengine - INFO - Epoch(train) [123][35/63] lr: 1.8404e-03 eta: 14:45:33 time: 0.5356 data_time: 0.0089 memory: 16131 loss: 3.8600 loss_prob: 2.3856 loss_thr: 1.0064 loss_db: 0.4679 2022/10/25 20:45:28 - mmengine - INFO - Epoch(train) [123][40/63] lr: 1.8404e-03 eta: 14:45:09 time: 0.5949 data_time: 0.0063 memory: 16131 loss: 3.7491 loss_prob: 2.3179 loss_thr: 0.9871 loss_db: 0.4441 2022/10/25 20:45:32 - mmengine - INFO - Epoch(train) [123][45/63] lr: 1.8404e-03 eta: 14:45:09 time: 0.6693 data_time: 0.0056 memory: 16131 loss: 3.7193 loss_prob: 2.3064 loss_thr: 0.9761 loss_db: 0.4368 2022/10/25 20:45:37 - mmengine - INFO - Epoch(train) [123][50/63] lr: 1.8404e-03 eta: 14:45:12 time: 0.9079 data_time: 0.0237 memory: 16131 loss: 3.8782 loss_prob: 2.4028 loss_thr: 1.0013 loss_db: 0.4741 2022/10/25 20:45:41 - mmengine - INFO - Epoch(train) [123][55/63] lr: 1.8404e-03 eta: 14:45:12 time: 0.9795 data_time: 0.0255 memory: 16131 loss: 3.8281 loss_prob: 2.3656 loss_thr: 1.0023 loss_db: 0.4603 2022/10/25 20:45:49 - mmengine - INFO - Epoch(train) [123][60/63] lr: 1.8404e-03 eta: 14:45:33 time: 1.1144 data_time: 0.0099 memory: 16131 loss: 3.8168 loss_prob: 2.3563 loss_thr: 1.0019 loss_db: 0.4587 2022/10/25 20:45:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:46:00 - mmengine - INFO - Epoch(train) [124][5/63] lr: 1.8554e-03 eta: 14:45:33 time: 1.3715 data_time: 0.1709 memory: 16131 loss: 3.8091 loss_prob: 2.3397 loss_thr: 1.0083 loss_db: 0.4611 2022/10/25 20:46:05 - mmengine - INFO - Epoch(train) [124][10/63] lr: 1.8554e-03 eta: 14:45:48 time: 1.3075 data_time: 0.1706 memory: 16131 loss: 3.9619 loss_prob: 2.4499 loss_thr: 1.0156 loss_db: 0.4965 2022/10/25 20:46:08 - mmengine - INFO - Epoch(train) [124][15/63] lr: 1.8554e-03 eta: 14:45:48 time: 0.8427 data_time: 0.0110 memory: 16131 loss: 4.1492 loss_prob: 2.5901 loss_thr: 1.0224 loss_db: 0.5367 2022/10/25 20:46:12 - mmengine - INFO - Epoch(train) [124][20/63] lr: 1.8554e-03 eta: 14:45:40 time: 0.7771 data_time: 0.0144 memory: 16131 loss: 4.1423 loss_prob: 2.5722 loss_thr: 1.0288 loss_db: 0.5412 2022/10/25 20:46:18 - mmengine - INFO - Epoch(train) [124][25/63] lr: 1.8554e-03 eta: 14:45:40 time: 0.9940 data_time: 0.0179 memory: 16131 loss: 4.0618 loss_prob: 2.5022 loss_thr: 1.0484 loss_db: 0.5112 2022/10/25 20:46:24 - mmengine - INFO - Epoch(train) [124][30/63] lr: 1.8554e-03 eta: 14:46:02 time: 1.1319 data_time: 0.0319 memory: 16131 loss: 3.9909 loss_prob: 2.4751 loss_thr: 1.0282 loss_db: 0.4876 2022/10/25 20:46:28 - mmengine - INFO - Epoch(train) [124][35/63] lr: 1.8554e-03 eta: 14:46:02 time: 1.0094 data_time: 0.0248 memory: 16131 loss: 4.0335 loss_prob: 2.5196 loss_thr: 1.0033 loss_db: 0.5107 2022/10/25 20:46:34 - mmengine - INFO - Epoch(train) [124][40/63] lr: 1.8554e-03 eta: 14:46:16 time: 1.0279 data_time: 0.0163 memory: 16131 loss: 4.2264 loss_prob: 2.6174 loss_thr: 1.0228 loss_db: 0.5862 2022/10/25 20:46:41 - mmengine - INFO - Epoch(train) [124][45/63] lr: 1.8554e-03 eta: 14:46:16 time: 1.2767 data_time: 0.0174 memory: 16131 loss: 4.0961 loss_prob: 2.5371 loss_thr: 1.0123 loss_db: 0.5467 2022/10/25 20:46:45 - mmengine - INFO - Epoch(train) [124][50/63] lr: 1.8554e-03 eta: 14:46:39 time: 1.1406 data_time: 0.0218 memory: 16131 loss: 3.9654 loss_prob: 2.4769 loss_thr: 0.9948 loss_db: 0.4937 2022/10/25 20:46:49 - mmengine - INFO - Epoch(train) [124][55/63] lr: 1.8554e-03 eta: 14:46:39 time: 0.8346 data_time: 0.0240 memory: 16131 loss: 3.8901 loss_prob: 2.4185 loss_thr: 0.9908 loss_db: 0.4808 2022/10/25 20:46:52 - mmengine - INFO - Epoch(train) [124][60/63] lr: 1.8554e-03 eta: 14:46:23 time: 0.6944 data_time: 0.0163 memory: 16131 loss: 3.8337 loss_prob: 2.3781 loss_thr: 0.9929 loss_db: 0.4627 2022/10/25 20:46:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:47:01 - mmengine - INFO - Epoch(train) [125][5/63] lr: 1.8705e-03 eta: 14:46:23 time: 0.9996 data_time: 0.2095 memory: 16131 loss: 4.0222 loss_prob: 2.4927 loss_thr: 1.0081 loss_db: 0.5213 2022/10/25 20:47:05 - mmengine - INFO - Epoch(train) [125][10/63] lr: 1.8705e-03 eta: 14:46:22 time: 1.1263 data_time: 0.2192 memory: 16131 loss: 3.9964 loss_prob: 2.4844 loss_thr: 1.0031 loss_db: 0.5088 2022/10/25 20:47:10 - mmengine - INFO - Epoch(train) [125][15/63] lr: 1.8705e-03 eta: 14:46:22 time: 0.8410 data_time: 0.0194 memory: 16131 loss: 4.0410 loss_prob: 2.5116 loss_thr: 1.0022 loss_db: 0.5272 2022/10/25 20:47:14 - mmengine - INFO - Epoch(train) [125][20/63] lr: 1.8705e-03 eta: 14:46:19 time: 0.8379 data_time: 0.0060 memory: 16131 loss: 4.1250 loss_prob: 2.5663 loss_thr: 1.0140 loss_db: 0.5448 2022/10/25 20:47:18 - mmengine - INFO - Epoch(train) [125][25/63] lr: 1.8705e-03 eta: 14:46:19 time: 0.8566 data_time: 0.0362 memory: 16131 loss: 3.9716 loss_prob: 2.4757 loss_thr: 1.0109 loss_db: 0.4850 2022/10/25 20:47:25 - mmengine - INFO - Epoch(train) [125][30/63] lr: 1.8705e-03 eta: 14:46:43 time: 1.1489 data_time: 0.0428 memory: 16131 loss: 4.0102 loss_prob: 2.4757 loss_thr: 1.0201 loss_db: 0.5145 2022/10/25 20:47:32 - mmengine - INFO - Epoch(train) [125][35/63] lr: 1.8705e-03 eta: 14:46:43 time: 1.3977 data_time: 0.0400 memory: 16131 loss: 3.9019 loss_prob: 2.4018 loss_thr: 1.0023 loss_db: 0.4979 2022/10/25 20:47:38 - mmengine - INFO - Epoch(train) [125][40/63] lr: 1.8705e-03 eta: 14:47:15 time: 1.2565 data_time: 0.0328 memory: 16131 loss: 3.8401 loss_prob: 2.3658 loss_thr: 0.9982 loss_db: 0.4761 2022/10/25 20:47:42 - mmengine - INFO - Epoch(train) [125][45/63] lr: 1.8705e-03 eta: 14:47:15 time: 0.9895 data_time: 0.0078 memory: 16131 loss: 3.9241 loss_prob: 2.4051 loss_thr: 1.0195 loss_db: 0.4995 2022/10/25 20:47:47 - mmengine - INFO - Epoch(train) [125][50/63] lr: 1.8705e-03 eta: 14:47:22 time: 0.9482 data_time: 0.0209 memory: 16131 loss: 3.7784 loss_prob: 2.3239 loss_thr: 1.0072 loss_db: 0.4473 2022/10/25 20:47:54 - mmengine - INFO - Epoch(train) [125][55/63] lr: 1.8705e-03 eta: 14:47:22 time: 1.1626 data_time: 0.0236 memory: 16131 loss: 3.6251 loss_prob: 2.2282 loss_thr: 0.9867 loss_db: 0.4102 2022/10/25 20:47:58 - mmengine - INFO - Epoch(train) [125][60/63] lr: 1.8705e-03 eta: 14:47:41 time: 1.1060 data_time: 0.0115 memory: 16131 loss: 3.6477 loss_prob: 2.2460 loss_thr: 0.9819 loss_db: 0.4199 2022/10/25 20:47:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:48:05 - mmengine - INFO - Epoch(train) [126][5/63] lr: 1.8855e-03 eta: 14:47:41 time: 0.9135 data_time: 0.2244 memory: 16131 loss: 3.8942 loss_prob: 2.3942 loss_thr: 1.0478 loss_db: 0.4522 2022/10/25 20:48:11 - mmengine - INFO - Epoch(train) [126][10/63] lr: 1.8855e-03 eta: 14:47:40 time: 1.1231 data_time: 0.2291 memory: 16131 loss: 4.2569 loss_prob: 2.6101 loss_thr: 1.1176 loss_db: 0.5292 2022/10/25 20:48:14 - mmengine - INFO - Epoch(train) [126][15/63] lr: 1.8855e-03 eta: 14:47:40 time: 0.8959 data_time: 0.0126 memory: 16131 loss: 4.2936 loss_prob: 2.6392 loss_thr: 1.0812 loss_db: 0.5731 2022/10/25 20:48:19 - mmengine - INFO - Epoch(train) [126][20/63] lr: 1.8855e-03 eta: 14:47:33 time: 0.8007 data_time: 0.0090 memory: 16131 loss: 4.1921 loss_prob: 2.5978 loss_thr: 1.0417 loss_db: 0.5525 2022/10/25 20:48:22 - mmengine - INFO - Epoch(train) [126][25/63] lr: 1.8855e-03 eta: 14:47:33 time: 0.7567 data_time: 0.0303 memory: 16131 loss: 4.0898 loss_prob: 2.5278 loss_thr: 1.0463 loss_db: 0.5157 2022/10/25 20:48:26 - mmengine - INFO - Epoch(train) [126][30/63] lr: 1.8855e-03 eta: 14:47:20 time: 0.7230 data_time: 0.0306 memory: 16131 loss: 4.0345 loss_prob: 2.4884 loss_thr: 1.0422 loss_db: 0.5039 2022/10/25 20:48:31 - mmengine - INFO - Epoch(train) [126][35/63] lr: 1.8855e-03 eta: 14:47:20 time: 0.8999 data_time: 0.0126 memory: 16131 loss: 4.0021 loss_prob: 2.4671 loss_thr: 1.0324 loss_db: 0.5026 2022/10/25 20:48:35 - mmengine - INFO - Epoch(train) [126][40/63] lr: 1.8855e-03 eta: 14:47:20 time: 0.8781 data_time: 0.0115 memory: 16131 loss: 3.9213 loss_prob: 2.4293 loss_thr: 1.0053 loss_db: 0.4867 2022/10/25 20:48:40 - mmengine - INFO - Epoch(train) [126][45/63] lr: 1.8855e-03 eta: 14:47:20 time: 0.9007 data_time: 0.0056 memory: 16131 loss: 3.6810 loss_prob: 2.2931 loss_thr: 0.9604 loss_db: 0.4275 2022/10/25 20:48:43 - mmengine - INFO - Epoch(train) [126][50/63] lr: 1.8855e-03 eta: 14:47:12 time: 0.7953 data_time: 0.0276 memory: 16131 loss: 3.6635 loss_prob: 2.2835 loss_thr: 0.9538 loss_db: 0.4262 2022/10/25 20:48:47 - mmengine - INFO - Epoch(train) [126][55/63] lr: 1.8855e-03 eta: 14:47:12 time: 0.7763 data_time: 0.0287 memory: 16131 loss: 3.8301 loss_prob: 2.3868 loss_thr: 0.9692 loss_db: 0.4741 2022/10/25 20:48:51 - mmengine - INFO - Epoch(train) [126][60/63] lr: 1.8855e-03 eta: 14:47:10 time: 0.8546 data_time: 0.0100 memory: 16131 loss: 3.7125 loss_prob: 2.3035 loss_thr: 0.9684 loss_db: 0.4406 2022/10/25 20:48:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:49:03 - mmengine - INFO - Epoch(train) [127][5/63] lr: 1.9006e-03 eta: 14:47:10 time: 1.4132 data_time: 0.2086 memory: 16131 loss: 3.8211 loss_prob: 2.3713 loss_thr: 0.9786 loss_db: 0.4712 2022/10/25 20:49:08 - mmengine - INFO - Epoch(train) [127][10/63] lr: 1.9006e-03 eta: 14:47:31 time: 1.3829 data_time: 0.2110 memory: 16131 loss: 3.8202 loss_prob: 2.3684 loss_thr: 0.9819 loss_db: 0.4698 2022/10/25 20:49:11 - mmengine - INFO - Epoch(train) [127][15/63] lr: 1.9006e-03 eta: 14:47:31 time: 0.7833 data_time: 0.0076 memory: 16131 loss: 3.7223 loss_prob: 2.3179 loss_thr: 0.9659 loss_db: 0.4384 2022/10/25 20:49:14 - mmengine - INFO - Epoch(train) [127][20/63] lr: 1.9006e-03 eta: 14:47:03 time: 0.5575 data_time: 0.0059 memory: 16131 loss: 3.9480 loss_prob: 2.4582 loss_thr: 0.9772 loss_db: 0.5126 2022/10/25 20:49:17 - mmengine - INFO - Epoch(train) [127][25/63] lr: 1.9006e-03 eta: 14:47:03 time: 0.5575 data_time: 0.0253 memory: 16131 loss: 3.8197 loss_prob: 2.3664 loss_thr: 0.9694 loss_db: 0.4839 2022/10/25 20:49:20 - mmengine - INFO - Epoch(train) [127][30/63] lr: 1.9006e-03 eta: 14:46:36 time: 0.5562 data_time: 0.0410 memory: 16131 loss: 3.5689 loss_prob: 2.2173 loss_thr: 0.9380 loss_db: 0.4136 2022/10/25 20:49:23 - mmengine - INFO - Epoch(train) [127][35/63] lr: 1.9006e-03 eta: 14:46:36 time: 0.5821 data_time: 0.0212 memory: 16131 loss: 3.6952 loss_prob: 2.2916 loss_thr: 0.9475 loss_db: 0.4561 2022/10/25 20:49:25 - mmengine - INFO - Epoch(train) [127][40/63] lr: 1.9006e-03 eta: 14:46:10 time: 0.5711 data_time: 0.0054 memory: 16131 loss: 3.7267 loss_prob: 2.3180 loss_thr: 0.9565 loss_db: 0.4523 2022/10/25 20:49:28 - mmengine - INFO - Epoch(train) [127][45/63] lr: 1.9006e-03 eta: 14:46:10 time: 0.5455 data_time: 0.0070 memory: 16131 loss: 3.5174 loss_prob: 2.2078 loss_thr: 0.9153 loss_db: 0.3942 2022/10/25 20:49:31 - mmengine - INFO - Epoch(train) [127][50/63] lr: 1.9006e-03 eta: 14:45:44 time: 0.5731 data_time: 0.0275 memory: 16131 loss: 3.4596 loss_prob: 2.1652 loss_thr: 0.9150 loss_db: 0.3794 2022/10/25 20:49:34 - mmengine - INFO - Epoch(train) [127][55/63] lr: 1.9006e-03 eta: 14:45:44 time: 0.5907 data_time: 0.0265 memory: 16131 loss: 3.4220 loss_prob: 2.1342 loss_thr: 0.9135 loss_db: 0.3744 2022/10/25 20:49:37 - mmengine - INFO - Epoch(train) [127][60/63] lr: 1.9006e-03 eta: 14:45:23 time: 0.6308 data_time: 0.0102 memory: 16131 loss: 3.3480 loss_prob: 2.0847 loss_thr: 0.9007 loss_db: 0.3626 2022/10/25 20:49:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:49:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:49:43 - mmengine - INFO - Epoch(train) [128][5/63] lr: 1.9157e-03 eta: 14:45:23 time: 0.7162 data_time: 0.2137 memory: 16131 loss: 3.4191 loss_prob: 2.1233 loss_thr: 0.9129 loss_db: 0.3830 2022/10/25 20:49:47 - mmengine - INFO - Epoch(train) [128][10/63] lr: 1.9157e-03 eta: 14:44:59 time: 0.8623 data_time: 0.2123 memory: 16131 loss: 3.4028 loss_prob: 2.1110 loss_thr: 0.9238 loss_db: 0.3680 2022/10/25 20:49:51 - mmengine - INFO - Epoch(train) [128][15/63] lr: 1.9157e-03 eta: 14:44:59 time: 0.7815 data_time: 0.0060 memory: 16131 loss: 3.4854 loss_prob: 2.1503 loss_thr: 0.9461 loss_db: 0.3890 2022/10/25 20:49:57 - mmengine - INFO - Epoch(train) [128][20/63] lr: 1.9157e-03 eta: 14:45:10 time: 1.0019 data_time: 0.0107 memory: 16131 loss: 3.5332 loss_prob: 2.1925 loss_thr: 0.9293 loss_db: 0.4113 2022/10/25 20:50:01 - mmengine - INFO - Epoch(train) [128][25/63] lr: 1.9157e-03 eta: 14:45:10 time: 1.0227 data_time: 0.0398 memory: 16131 loss: 3.3140 loss_prob: 2.0541 loss_thr: 0.8930 loss_db: 0.3670 2022/10/25 20:50:06 - mmengine - INFO - Epoch(train) [128][30/63] lr: 1.9157e-03 eta: 14:45:06 time: 0.8349 data_time: 0.0349 memory: 16131 loss: 3.3006 loss_prob: 2.0474 loss_thr: 0.8893 loss_db: 0.3639 2022/10/25 20:50:08 - mmengine - INFO - Epoch(train) [128][35/63] lr: 1.9157e-03 eta: 14:45:06 time: 0.6693 data_time: 0.0061 memory: 16131 loss: 3.3940 loss_prob: 2.1099 loss_thr: 0.9064 loss_db: 0.3776 2022/10/25 20:50:11 - mmengine - INFO - Epoch(train) [128][40/63] lr: 1.9157e-03 eta: 14:44:38 time: 0.5450 data_time: 0.0072 memory: 16131 loss: 3.2469 loss_prob: 2.0149 loss_thr: 0.8840 loss_db: 0.3481 2022/10/25 20:50:14 - mmengine - INFO - Epoch(train) [128][45/63] lr: 1.9157e-03 eta: 14:44:38 time: 0.6185 data_time: 0.0124 memory: 16131 loss: 3.2670 loss_prob: 2.0309 loss_thr: 0.8756 loss_db: 0.3605 2022/10/25 20:50:17 - mmengine - INFO - Epoch(train) [128][50/63] lr: 1.9157e-03 eta: 14:44:17 time: 0.6314 data_time: 0.0283 memory: 16131 loss: 3.4563 loss_prob: 2.1640 loss_thr: 0.8979 loss_db: 0.3944 2022/10/25 20:50:22 - mmengine - INFO - Epoch(train) [128][55/63] lr: 1.9157e-03 eta: 14:44:17 time: 0.7432 data_time: 0.0228 memory: 16131 loss: 3.4134 loss_prob: 2.1343 loss_thr: 0.8969 loss_db: 0.3822 2022/10/25 20:50:29 - mmengine - INFO - Epoch(train) [128][60/63] lr: 1.9157e-03 eta: 14:44:42 time: 1.1816 data_time: 0.0075 memory: 16131 loss: 3.3576 loss_prob: 2.0842 loss_thr: 0.9037 loss_db: 0.3698 2022/10/25 20:50:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:50:40 - mmengine - INFO - Epoch(train) [129][5/63] lr: 1.9307e-03 eta: 14:44:42 time: 1.4561 data_time: 0.2393 memory: 16131 loss: 3.3347 loss_prob: 2.0812 loss_thr: 0.8905 loss_db: 0.3630 2022/10/25 20:50:44 - mmengine - INFO - Epoch(train) [129][10/63] lr: 1.9307e-03 eta: 14:44:40 time: 1.1173 data_time: 0.2389 memory: 16131 loss: 3.4579 loss_prob: 2.1611 loss_thr: 0.9103 loss_db: 0.3865 2022/10/25 20:50:47 - mmengine - INFO - Epoch(train) [129][15/63] lr: 1.9307e-03 eta: 14:44:40 time: 0.6355 data_time: 0.0155 memory: 16131 loss: 3.5287 loss_prob: 2.1986 loss_thr: 0.9294 loss_db: 0.4006 2022/10/25 20:50:51 - mmengine - INFO - Epoch(train) [129][20/63] lr: 1.9307e-03 eta: 14:44:24 time: 0.6908 data_time: 0.0147 memory: 16131 loss: 3.4376 loss_prob: 2.1383 loss_thr: 0.9122 loss_db: 0.3870 2022/10/25 20:50:55 - mmengine - INFO - Epoch(train) [129][25/63] lr: 1.9307e-03 eta: 14:44:24 time: 0.8309 data_time: 0.0338 memory: 16131 loss: 3.3706 loss_prob: 2.1029 loss_thr: 0.8899 loss_db: 0.3778 2022/10/25 20:50:58 - mmengine - INFO - Epoch(train) [129][30/63] lr: 1.9307e-03 eta: 14:44:09 time: 0.7000 data_time: 0.0444 memory: 16131 loss: 3.3682 loss_prob: 2.0939 loss_thr: 0.8988 loss_db: 0.3755 2022/10/25 20:51:02 - mmengine - INFO - Epoch(train) [129][35/63] lr: 1.9307e-03 eta: 14:44:09 time: 0.6563 data_time: 0.0174 memory: 16131 loss: 3.3269 loss_prob: 2.0732 loss_thr: 0.8837 loss_db: 0.3700 2022/10/25 20:51:07 - mmengine - INFO - Epoch(train) [129][40/63] lr: 1.9307e-03 eta: 14:44:09 time: 0.8816 data_time: 0.0112 memory: 16131 loss: 3.2578 loss_prob: 2.0295 loss_thr: 0.8670 loss_db: 0.3613 2022/10/25 20:51:09 - mmengine - INFO - Epoch(train) [129][45/63] lr: 1.9307e-03 eta: 14:44:09 time: 0.7857 data_time: 0.0118 memory: 16131 loss: 3.2413 loss_prob: 2.0095 loss_thr: 0.8761 loss_db: 0.3556 2022/10/25 20:51:13 - mmengine - INFO - Epoch(train) [129][50/63] lr: 1.9307e-03 eta: 14:43:51 time: 0.6614 data_time: 0.0175 memory: 16131 loss: 3.2832 loss_prob: 2.0437 loss_thr: 0.8794 loss_db: 0.3601 2022/10/25 20:51:17 - mmengine - INFO - Epoch(train) [129][55/63] lr: 1.9307e-03 eta: 14:43:51 time: 0.7789 data_time: 0.0233 memory: 16131 loss: 3.5183 loss_prob: 2.2002 loss_thr: 0.9069 loss_db: 0.4112 2022/10/25 20:51:25 - mmengine - INFO - Epoch(train) [129][60/63] lr: 1.9307e-03 eta: 14:44:15 time: 1.1705 data_time: 0.0150 memory: 16131 loss: 3.3800 loss_prob: 2.1136 loss_thr: 0.8781 loss_db: 0.3883 2022/10/25 20:51:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:51:35 - mmengine - INFO - Epoch(train) [130][5/63] lr: 1.9458e-03 eta: 14:44:15 time: 1.2766 data_time: 0.2007 memory: 16131 loss: 3.2088 loss_prob: 1.9955 loss_thr: 0.8586 loss_db: 0.3548 2022/10/25 20:51:40 - mmengine - INFO - Epoch(train) [130][10/63] lr: 1.9458e-03 eta: 14:44:25 time: 1.2561 data_time: 0.2023 memory: 16131 loss: 3.2714 loss_prob: 2.0242 loss_thr: 0.8885 loss_db: 0.3587 2022/10/25 20:51:44 - mmengine - INFO - Epoch(train) [130][15/63] lr: 1.9458e-03 eta: 14:44:25 time: 0.8936 data_time: 0.0095 memory: 16131 loss: 3.3125 loss_prob: 2.0541 loss_thr: 0.8883 loss_db: 0.3700 2022/10/25 20:51:51 - mmengine - INFO - Epoch(train) [130][20/63] lr: 1.9458e-03 eta: 14:44:49 time: 1.1732 data_time: 0.0083 memory: 16131 loss: 3.1272 loss_prob: 1.9482 loss_thr: 0.8389 loss_db: 0.3401 2022/10/25 20:51:54 - mmengine - INFO - Epoch(train) [130][25/63] lr: 1.9458e-03 eta: 14:44:49 time: 1.0673 data_time: 0.0160 memory: 16131 loss: 3.2723 loss_prob: 2.0383 loss_thr: 0.8718 loss_db: 0.3622 2022/10/25 20:51:57 - mmengine - INFO - Epoch(train) [130][30/63] lr: 1.9458e-03 eta: 14:44:27 time: 0.6222 data_time: 0.0376 memory: 16131 loss: 3.3062 loss_prob: 2.0612 loss_thr: 0.8760 loss_db: 0.3690 2022/10/25 20:52:03 - mmengine - INFO - Epoch(train) [130][35/63] lr: 1.9458e-03 eta: 14:44:27 time: 0.8565 data_time: 0.0365 memory: 16131 loss: 3.1843 loss_prob: 1.9922 loss_thr: 0.8437 loss_db: 0.3484 2022/10/25 20:52:07 - mmengine - INFO - Epoch(train) [130][40/63] lr: 1.9458e-03 eta: 14:44:35 time: 0.9797 data_time: 0.0140 memory: 16131 loss: 3.1191 loss_prob: 1.9405 loss_thr: 0.8450 loss_db: 0.3336 2022/10/25 20:52:12 - mmengine - INFO - Epoch(train) [130][45/63] lr: 1.9458e-03 eta: 14:44:35 time: 0.8563 data_time: 0.0088 memory: 16131 loss: 3.0885 loss_prob: 1.9238 loss_thr: 0.8382 loss_db: 0.3264 2022/10/25 20:52:15 - mmengine - INFO - Epoch(train) [130][50/63] lr: 1.9458e-03 eta: 14:44:23 time: 0.7332 data_time: 0.0115 memory: 16131 loss: 3.2165 loss_prob: 2.0082 loss_thr: 0.8618 loss_db: 0.3465 2022/10/25 20:52:18 - mmengine - INFO - Epoch(train) [130][55/63] lr: 1.9458e-03 eta: 14:44:23 time: 0.6881 data_time: 0.0309 memory: 16131 loss: 3.2214 loss_prob: 2.0065 loss_thr: 0.8587 loss_db: 0.3562 2022/10/25 20:52:21 - mmengine - INFO - Epoch(train) [130][60/63] lr: 1.9458e-03 eta: 14:44:03 time: 0.6457 data_time: 0.0276 memory: 16131 loss: 3.1143 loss_prob: 1.9338 loss_thr: 0.8443 loss_db: 0.3361 2022/10/25 20:52:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:52:28 - mmengine - INFO - Epoch(train) [131][5/63] lr: 1.9608e-03 eta: 14:44:03 time: 0.8203 data_time: 0.2572 memory: 16131 loss: 2.8456 loss_prob: 1.7646 loss_thr: 0.7891 loss_db: 0.2919 2022/10/25 20:52:34 - mmengine - INFO - Epoch(train) [131][10/63] lr: 1.9608e-03 eta: 14:44:04 time: 1.1568 data_time: 0.2654 memory: 16131 loss: 2.8428 loss_prob: 1.7615 loss_thr: 0.7882 loss_db: 0.2930 2022/10/25 20:52:41 - mmengine - INFO - Epoch(train) [131][15/63] lr: 1.9608e-03 eta: 14:44:04 time: 1.2481 data_time: 0.0156 memory: 16131 loss: 3.0390 loss_prob: 1.8878 loss_thr: 0.8248 loss_db: 0.3264 2022/10/25 20:52:47 - mmengine - INFO - Epoch(train) [131][20/63] lr: 1.9608e-03 eta: 14:44:35 time: 1.2548 data_time: 0.0101 memory: 16131 loss: 3.1916 loss_prob: 2.0086 loss_thr: 0.8339 loss_db: 0.3491 2022/10/25 20:52:52 - mmengine - INFO - Epoch(train) [131][25/63] lr: 1.9608e-03 eta: 14:44:35 time: 1.1059 data_time: 0.0380 memory: 16131 loss: 3.2158 loss_prob: 2.0268 loss_thr: 0.8352 loss_db: 0.3538 2022/10/25 20:52:56 - mmengine - INFO - Epoch(train) [131][30/63] lr: 1.9608e-03 eta: 14:44:38 time: 0.9224 data_time: 0.0381 memory: 16131 loss: 3.3330 loss_prob: 2.0891 loss_thr: 0.8647 loss_db: 0.3791 2022/10/25 20:53:02 - mmengine - INFO - Epoch(train) [131][35/63] lr: 1.9608e-03 eta: 14:44:38 time: 1.0092 data_time: 0.0151 memory: 16131 loss: 3.2347 loss_prob: 2.0283 loss_thr: 0.8474 loss_db: 0.3590 2022/10/25 20:53:09 - mmengine - INFO - Epoch(train) [131][40/63] lr: 1.9608e-03 eta: 14:45:14 time: 1.3301 data_time: 0.0167 memory: 16131 loss: 3.1655 loss_prob: 1.9917 loss_thr: 0.8240 loss_db: 0.3498 2022/10/25 20:53:15 - mmengine - INFO - Epoch(train) [131][45/63] lr: 1.9608e-03 eta: 14:45:14 time: 1.3446 data_time: 0.0112 memory: 16131 loss: 3.1657 loss_prob: 1.9746 loss_thr: 0.8410 loss_db: 0.3501 2022/10/25 20:53:18 - mmengine - INFO - Epoch(train) [131][50/63] lr: 1.9608e-03 eta: 14:45:15 time: 0.8939 data_time: 0.0216 memory: 16131 loss: 3.0095 loss_prob: 1.8566 loss_thr: 0.8297 loss_db: 0.3231 2022/10/25 20:53:22 - mmengine - INFO - Epoch(train) [131][55/63] lr: 1.9608e-03 eta: 14:45:15 time: 0.6271 data_time: 0.0271 memory: 16131 loss: 3.1386 loss_prob: 1.9410 loss_thr: 0.8534 loss_db: 0.3443 2022/10/25 20:53:27 - mmengine - INFO - Epoch(train) [131][60/63] lr: 1.9608e-03 eta: 14:45:14 time: 0.8693 data_time: 0.0129 memory: 16131 loss: 3.3272 loss_prob: 2.0813 loss_thr: 0.8677 loss_db: 0.3782 2022/10/25 20:53:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:53:35 - mmengine - INFO - Epoch(train) [132][5/63] lr: 1.9759e-03 eta: 14:45:14 time: 1.1364 data_time: 0.2285 memory: 16131 loss: 3.3733 loss_prob: 2.1409 loss_thr: 0.8477 loss_db: 0.3847 2022/10/25 20:53:41 - mmengine - INFO - Epoch(train) [132][10/63] lr: 1.9759e-03 eta: 14:45:21 time: 1.2343 data_time: 0.2313 memory: 16131 loss: 3.2367 loss_prob: 2.0266 loss_thr: 0.8473 loss_db: 0.3628 2022/10/25 20:53:45 - mmengine - INFO - Epoch(train) [132][15/63] lr: 1.9759e-03 eta: 14:45:21 time: 1.0219 data_time: 0.0132 memory: 16131 loss: 3.1736 loss_prob: 1.9779 loss_thr: 0.8505 loss_db: 0.3452 2022/10/25 20:53:50 - mmengine - INFO - Epoch(train) [132][20/63] lr: 1.9759e-03 eta: 14:45:21 time: 0.8877 data_time: 0.0123 memory: 16131 loss: 3.1659 loss_prob: 1.9883 loss_thr: 0.8361 loss_db: 0.3415 2022/10/25 20:53:57 - mmengine - INFO - Epoch(train) [132][25/63] lr: 1.9759e-03 eta: 14:45:21 time: 1.1665 data_time: 0.0360 memory: 16131 loss: 3.1236 loss_prob: 1.9574 loss_thr: 0.8258 loss_db: 0.3404 2022/10/25 20:54:01 - mmengine - INFO - Epoch(train) [132][30/63] lr: 1.9759e-03 eta: 14:45:40 time: 1.1246 data_time: 0.0339 memory: 16131 loss: 3.0020 loss_prob: 1.8651 loss_thr: 0.8165 loss_db: 0.3204 2022/10/25 20:54:04 - mmengine - INFO - Epoch(train) [132][35/63] lr: 1.9759e-03 eta: 14:45:40 time: 0.7273 data_time: 0.0073 memory: 16131 loss: 2.8741 loss_prob: 1.7750 loss_thr: 0.8013 loss_db: 0.2978 2022/10/25 20:54:08 - mmengine - INFO - Epoch(train) [132][40/63] lr: 1.9759e-03 eta: 14:45:26 time: 0.7155 data_time: 0.0116 memory: 16131 loss: 3.0945 loss_prob: 1.9271 loss_thr: 0.8226 loss_db: 0.3447 2022/10/25 20:54:14 - mmengine - INFO - Epoch(train) [132][45/63] lr: 1.9759e-03 eta: 14:45:26 time: 0.9363 data_time: 0.0103 memory: 16131 loss: 3.2033 loss_prob: 2.0092 loss_thr: 0.8360 loss_db: 0.3580 2022/10/25 20:54:18 - mmengine - INFO - Epoch(train) [132][50/63] lr: 1.9759e-03 eta: 14:45:28 time: 0.9130 data_time: 0.0233 memory: 16131 loss: 3.0678 loss_prob: 1.9155 loss_thr: 0.8294 loss_db: 0.3229 2022/10/25 20:54:23 - mmengine - INFO - Epoch(train) [132][55/63] lr: 1.9759e-03 eta: 14:45:28 time: 0.9839 data_time: 0.0224 memory: 16131 loss: 3.0571 loss_prob: 1.9108 loss_thr: 0.8217 loss_db: 0.3246 2022/10/25 20:54:29 - mmengine - INFO - Epoch(train) [132][60/63] lr: 1.9759e-03 eta: 14:45:50 time: 1.1573 data_time: 0.0050 memory: 16131 loss: 2.9633 loss_prob: 1.8463 loss_thr: 0.8007 loss_db: 0.3163 2022/10/25 20:54:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:54:37 - mmengine - INFO - Epoch(train) [133][5/63] lr: 1.9910e-03 eta: 14:45:50 time: 0.9379 data_time: 0.2438 memory: 16131 loss: 3.0747 loss_prob: 1.8996 loss_thr: 0.8399 loss_db: 0.3352 2022/10/25 20:54:41 - mmengine - INFO - Epoch(train) [133][10/63] lr: 1.9910e-03 eta: 14:45:43 time: 1.0680 data_time: 0.2406 memory: 16131 loss: 3.1988 loss_prob: 2.0032 loss_thr: 0.8383 loss_db: 0.3573 2022/10/25 20:54:44 - mmengine - INFO - Epoch(train) [133][15/63] lr: 1.9910e-03 eta: 14:45:43 time: 0.7074 data_time: 0.0118 memory: 16131 loss: 3.0641 loss_prob: 1.9121 loss_thr: 0.8177 loss_db: 0.3343 2022/10/25 20:54:48 - mmengine - INFO - Epoch(train) [133][20/63] lr: 1.9910e-03 eta: 14:45:27 time: 0.6888 data_time: 0.0128 memory: 16131 loss: 2.9132 loss_prob: 1.8139 loss_thr: 0.7885 loss_db: 0.3107 2022/10/25 20:54:52 - mmengine - INFO - Epoch(train) [133][25/63] lr: 1.9910e-03 eta: 14:45:27 time: 0.8171 data_time: 0.0353 memory: 16131 loss: 2.8455 loss_prob: 1.7620 loss_thr: 0.7875 loss_db: 0.2959 2022/10/25 20:54:57 - mmengine - INFO - Epoch(train) [133][30/63] lr: 1.9910e-03 eta: 14:45:29 time: 0.9134 data_time: 0.0345 memory: 16131 loss: 2.9165 loss_prob: 1.7997 loss_thr: 0.8126 loss_db: 0.3042 2022/10/25 20:55:02 - mmengine - INFO - Epoch(train) [133][35/63] lr: 1.9910e-03 eta: 14:45:29 time: 1.0142 data_time: 0.0077 memory: 16131 loss: 2.9290 loss_prob: 1.8006 loss_thr: 0.8210 loss_db: 0.3074 2022/10/25 20:55:07 - mmengine - INFO - Epoch(train) [133][40/63] lr: 1.9910e-03 eta: 14:45:33 time: 0.9342 data_time: 0.0095 memory: 16131 loss: 2.9113 loss_prob: 1.7949 loss_thr: 0.8088 loss_db: 0.3076 2022/10/25 20:55:10 - mmengine - INFO - Epoch(train) [133][45/63] lr: 1.9910e-03 eta: 14:45:33 time: 0.7276 data_time: 0.0092 memory: 16131 loss: 3.1429 loss_prob: 1.9697 loss_thr: 0.8232 loss_db: 0.3500 2022/10/25 20:55:13 - mmengine - INFO - Epoch(train) [133][50/63] lr: 1.9910e-03 eta: 14:45:10 time: 0.5978 data_time: 0.0330 memory: 16131 loss: 3.2644 loss_prob: 2.0503 loss_thr: 0.8471 loss_db: 0.3670 2022/10/25 20:55:16 - mmengine - INFO - Epoch(train) [133][55/63] lr: 1.9910e-03 eta: 14:45:10 time: 0.6651 data_time: 0.0328 memory: 16131 loss: 3.1546 loss_prob: 1.9780 loss_thr: 0.8353 loss_db: 0.3413 2022/10/25 20:55:23 - mmengine - INFO - Epoch(train) [133][60/63] lr: 1.9910e-03 eta: 14:45:19 time: 1.0076 data_time: 0.0069 memory: 16131 loss: 3.0669 loss_prob: 1.9087 loss_thr: 0.8352 loss_db: 0.3231 2022/10/25 20:55:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:55:32 - mmengine - INFO - Epoch(train) [134][5/63] lr: 2.0060e-03 eta: 14:45:19 time: 1.1741 data_time: 0.1871 memory: 16131 loss: 2.9071 loss_prob: 1.8010 loss_thr: 0.8020 loss_db: 0.3041 2022/10/25 20:55:36 - mmengine - INFO - Epoch(train) [134][10/63] lr: 2.0060e-03 eta: 14:45:11 time: 1.0541 data_time: 0.1878 memory: 16131 loss: 2.9117 loss_prob: 1.8215 loss_thr: 0.7855 loss_db: 0.3048 2022/10/25 20:55:43 - mmengine - INFO - Epoch(train) [134][15/63] lr: 2.0060e-03 eta: 14:45:11 time: 1.0482 data_time: 0.0091 memory: 16131 loss: 2.8616 loss_prob: 1.7676 loss_thr: 0.8033 loss_db: 0.2906 2022/10/25 20:55:48 - mmengine - INFO - Epoch(train) [134][20/63] lr: 2.0060e-03 eta: 14:45:33 time: 1.1618 data_time: 0.0108 memory: 16131 loss: 2.7730 loss_prob: 1.6911 loss_thr: 0.8080 loss_db: 0.2738 2022/10/25 20:55:52 - mmengine - INFO - Epoch(train) [134][25/63] lr: 2.0060e-03 eta: 14:45:33 time: 0.9600 data_time: 0.0355 memory: 16131 loss: 2.8778 loss_prob: 1.7921 loss_thr: 0.7913 loss_db: 0.2944 2022/10/25 20:55:57 - mmengine - INFO - Epoch(train) [134][30/63] lr: 2.0060e-03 eta: 14:45:36 time: 0.9263 data_time: 0.0308 memory: 16131 loss: 3.0758 loss_prob: 1.9611 loss_thr: 0.7831 loss_db: 0.3316 2022/10/25 20:56:00 - mmengine - INFO - Epoch(train) [134][35/63] lr: 2.0060e-03 eta: 14:45:36 time: 0.7973 data_time: 0.0067 memory: 16131 loss: 3.1198 loss_prob: 1.9754 loss_thr: 0.8006 loss_db: 0.3438 2022/10/25 20:56:06 - mmengine - INFO - Epoch(train) [134][40/63] lr: 2.0060e-03 eta: 14:45:38 time: 0.9163 data_time: 0.0165 memory: 16131 loss: 2.9734 loss_prob: 1.8442 loss_thr: 0.8037 loss_db: 0.3255 2022/10/25 20:56:09 - mmengine - INFO - Epoch(train) [134][45/63] lr: 2.0060e-03 eta: 14:45:38 time: 0.8960 data_time: 0.0157 memory: 16131 loss: 3.1061 loss_prob: 1.9395 loss_thr: 0.8206 loss_db: 0.3460 2022/10/25 20:56:14 - mmengine - INFO - Epoch(train) [134][50/63] lr: 2.0060e-03 eta: 14:45:31 time: 0.8028 data_time: 0.0279 memory: 16131 loss: 3.1469 loss_prob: 1.9670 loss_thr: 0.8361 loss_db: 0.3439 2022/10/25 20:56:20 - mmengine - INFO - Epoch(train) [134][55/63] lr: 2.0060e-03 eta: 14:45:31 time: 1.0381 data_time: 0.0314 memory: 16131 loss: 3.0447 loss_prob: 1.8974 loss_thr: 0.8243 loss_db: 0.3230 2022/10/25 20:56:24 - mmengine - INFO - Epoch(train) [134][60/63] lr: 2.0060e-03 eta: 14:45:37 time: 0.9658 data_time: 0.0083 memory: 16131 loss: 2.9560 loss_prob: 1.8121 loss_thr: 0.8381 loss_db: 0.3058 2022/10/25 20:56:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:56:33 - mmengine - INFO - Epoch(train) [135][5/63] lr: 2.0211e-03 eta: 14:45:37 time: 1.1905 data_time: 0.2400 memory: 16131 loss: 2.9704 loss_prob: 1.8127 loss_thr: 0.8503 loss_db: 0.3074 2022/10/25 20:56:36 - mmengine - INFO - Epoch(train) [135][10/63] lr: 2.0211e-03 eta: 14:45:19 time: 0.9360 data_time: 0.2402 memory: 16131 loss: 2.9203 loss_prob: 1.8034 loss_thr: 0.8052 loss_db: 0.3117 2022/10/25 20:56:39 - mmengine - INFO - Epoch(train) [135][15/63] lr: 2.0211e-03 eta: 14:45:19 time: 0.5597 data_time: 0.0120 memory: 16131 loss: 2.9022 loss_prob: 1.8039 loss_thr: 0.7938 loss_db: 0.3045 2022/10/25 20:56:43 - mmengine - INFO - Epoch(train) [135][20/63] lr: 2.0211e-03 eta: 14:45:01 time: 0.6540 data_time: 0.0158 memory: 16131 loss: 2.8608 loss_prob: 1.7598 loss_thr: 0.8061 loss_db: 0.2948 2022/10/25 20:56:49 - mmengine - INFO - Epoch(train) [135][25/63] lr: 2.0211e-03 eta: 14:45:01 time: 1.0014 data_time: 0.0225 memory: 16131 loss: 2.7529 loss_prob: 1.6784 loss_thr: 0.7936 loss_db: 0.2809 2022/10/25 20:56:54 - mmengine - INFO - Epoch(train) [135][30/63] lr: 2.0211e-03 eta: 14:45:22 time: 1.1578 data_time: 0.0368 memory: 16131 loss: 2.7605 loss_prob: 1.7020 loss_thr: 0.7730 loss_db: 0.2855 2022/10/25 20:56:57 - mmengine - INFO - Epoch(train) [135][35/63] lr: 2.0211e-03 eta: 14:45:22 time: 0.8588 data_time: 0.0235 memory: 16131 loss: 2.9107 loss_prob: 1.8146 loss_thr: 0.7850 loss_db: 0.3111 2022/10/25 20:57:02 - mmengine - INFO - Epoch(train) [135][40/63] lr: 2.0211e-03 eta: 14:45:13 time: 0.7784 data_time: 0.0054 memory: 16131 loss: 3.1136 loss_prob: 1.9666 loss_thr: 0.8080 loss_db: 0.3390 2022/10/25 20:57:04 - mmengine - INFO - Epoch(train) [135][45/63] lr: 2.0211e-03 eta: 14:45:13 time: 0.7122 data_time: 0.0078 memory: 16131 loss: 3.0111 loss_prob: 1.8942 loss_thr: 0.7971 loss_db: 0.3199 2022/10/25 20:57:10 - mmengine - INFO - Epoch(train) [135][50/63] lr: 2.0211e-03 eta: 14:45:08 time: 0.8316 data_time: 0.0228 memory: 16131 loss: 2.7687 loss_prob: 1.7229 loss_thr: 0.7638 loss_db: 0.2819 2022/10/25 20:57:13 - mmengine - INFO - Epoch(train) [135][55/63] lr: 2.0211e-03 eta: 14:45:08 time: 0.8820 data_time: 0.0271 memory: 16131 loss: 2.6919 loss_prob: 1.6662 loss_thr: 0.7519 loss_db: 0.2739 2022/10/25 20:57:16 - mmengine - INFO - Epoch(train) [135][60/63] lr: 2.0211e-03 eta: 14:44:44 time: 0.5810 data_time: 0.0120 memory: 16131 loss: 2.8516 loss_prob: 1.7537 loss_thr: 0.7982 loss_db: 0.2997 2022/10/25 20:57:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:57:25 - mmengine - INFO - Epoch(train) [136][5/63] lr: 2.0361e-03 eta: 14:44:44 time: 1.0298 data_time: 0.2145 memory: 16131 loss: 3.0638 loss_prob: 1.9071 loss_thr: 0.8311 loss_db: 0.3255 2022/10/25 20:57:31 - mmengine - INFO - Epoch(train) [136][10/63] lr: 2.0361e-03 eta: 14:44:38 time: 1.0943 data_time: 0.2140 memory: 16131 loss: 3.1342 loss_prob: 1.9743 loss_thr: 0.8201 loss_db: 0.3398 2022/10/25 20:57:34 - mmengine - INFO - Epoch(train) [136][15/63] lr: 2.0361e-03 eta: 14:44:38 time: 0.9052 data_time: 0.0111 memory: 16131 loss: 3.0249 loss_prob: 1.8885 loss_thr: 0.8077 loss_db: 0.3287 2022/10/25 20:57:38 - mmengine - INFO - Epoch(train) [136][20/63] lr: 2.0361e-03 eta: 14:44:26 time: 0.7291 data_time: 0.0170 memory: 16131 loss: 2.9310 loss_prob: 1.8108 loss_thr: 0.8133 loss_db: 0.3069 2022/10/25 20:57:41 - mmengine - INFO - Epoch(train) [136][25/63] lr: 2.0361e-03 eta: 14:44:26 time: 0.6990 data_time: 0.0344 memory: 16131 loss: 2.9299 loss_prob: 1.8200 loss_thr: 0.8104 loss_db: 0.2995 2022/10/25 20:57:45 - mmengine - INFO - Epoch(train) [136][30/63] lr: 2.0361e-03 eta: 14:44:10 time: 0.6988 data_time: 0.0357 memory: 16131 loss: 2.8138 loss_prob: 1.7446 loss_thr: 0.7843 loss_db: 0.2849 2022/10/25 20:57:48 - mmengine - INFO - Epoch(train) [136][35/63] lr: 2.0361e-03 eta: 14:44:10 time: 0.6703 data_time: 0.0148 memory: 16131 loss: 2.7227 loss_prob: 1.6781 loss_thr: 0.7713 loss_db: 0.2733 2022/10/25 20:57:55 - mmengine - INFO - Epoch(train) [136][40/63] lr: 2.0361e-03 eta: 14:44:14 time: 0.9334 data_time: 0.0116 memory: 16131 loss: 2.8261 loss_prob: 1.7494 loss_thr: 0.7860 loss_db: 0.2907 2022/10/25 20:57:59 - mmengine - INFO - Epoch(train) [136][45/63] lr: 2.0361e-03 eta: 14:44:14 time: 1.1282 data_time: 0.0130 memory: 16131 loss: 2.8713 loss_prob: 1.7763 loss_thr: 0.7901 loss_db: 0.3049 2022/10/25 20:58:06 - mmengine - INFO - Epoch(train) [136][50/63] lr: 2.0361e-03 eta: 14:44:29 time: 1.0879 data_time: 0.0305 memory: 16131 loss: 2.8056 loss_prob: 1.7361 loss_thr: 0.7772 loss_db: 0.2923 2022/10/25 20:58:11 - mmengine - INFO - Epoch(train) [136][55/63] lr: 2.0361e-03 eta: 14:44:29 time: 1.1253 data_time: 0.0454 memory: 16131 loss: 2.7333 loss_prob: 1.6801 loss_thr: 0.7785 loss_db: 0.2747 2022/10/25 20:58:14 - mmengine - INFO - Epoch(train) [136][60/63] lr: 2.0361e-03 eta: 14:44:24 time: 0.8262 data_time: 0.0217 memory: 16131 loss: 2.8115 loss_prob: 1.7291 loss_thr: 0.7922 loss_db: 0.2902 2022/10/25 20:58:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:58:23 - mmengine - INFO - Epoch(train) [137][5/63] lr: 2.0512e-03 eta: 14:44:24 time: 1.0971 data_time: 0.2507 memory: 16131 loss: 2.9960 loss_prob: 1.8725 loss_thr: 0.8042 loss_db: 0.3193 2022/10/25 20:58:30 - mmengine - INFO - Epoch(train) [137][10/63] lr: 2.0512e-03 eta: 14:44:51 time: 1.5132 data_time: 0.2503 memory: 16131 loss: 3.0260 loss_prob: 1.8985 loss_thr: 0.8044 loss_db: 0.3231 2022/10/25 20:58:34 - mmengine - INFO - Epoch(train) [137][15/63] lr: 2.0512e-03 eta: 14:44:51 time: 1.0160 data_time: 0.0062 memory: 16131 loss: 2.9576 loss_prob: 1.8388 loss_thr: 0.8059 loss_db: 0.3129 2022/10/25 20:58:39 - mmengine - INFO - Epoch(train) [137][20/63] lr: 2.0512e-03 eta: 14:44:47 time: 0.8320 data_time: 0.0097 memory: 16131 loss: 2.6650 loss_prob: 1.6295 loss_thr: 0.7655 loss_db: 0.2701 2022/10/25 20:58:43 - mmengine - INFO - Epoch(train) [137][25/63] lr: 2.0512e-03 eta: 14:44:47 time: 0.9228 data_time: 0.0406 memory: 16131 loss: 2.7644 loss_prob: 1.7099 loss_thr: 0.7718 loss_db: 0.2827 2022/10/25 20:58:46 - mmengine - INFO - Epoch(train) [137][30/63] lr: 2.0512e-03 eta: 14:44:33 time: 0.7165 data_time: 0.0369 memory: 16131 loss: 2.8017 loss_prob: 1.7398 loss_thr: 0.7740 loss_db: 0.2879 2022/10/25 20:58:50 - mmengine - INFO - Epoch(train) [137][35/63] lr: 2.0512e-03 eta: 14:44:33 time: 0.7482 data_time: 0.0117 memory: 16131 loss: 2.7384 loss_prob: 1.6850 loss_thr: 0.7709 loss_db: 0.2825 2022/10/25 20:58:56 - mmengine - INFO - Epoch(train) [137][40/63] lr: 2.0512e-03 eta: 14:44:45 time: 1.0452 data_time: 0.0139 memory: 16131 loss: 2.8866 loss_prob: 1.7757 loss_thr: 0.8084 loss_db: 0.3025 2022/10/25 20:59:00 - mmengine - INFO - Epoch(train) [137][45/63] lr: 2.0512e-03 eta: 14:44:45 time: 1.0254 data_time: 0.0134 memory: 16131 loss: 2.9769 loss_prob: 1.8381 loss_thr: 0.8202 loss_db: 0.3186 2022/10/25 20:59:04 - mmengine - INFO - Epoch(train) [137][50/63] lr: 2.0512e-03 eta: 14:44:35 time: 0.7698 data_time: 0.0262 memory: 16131 loss: 3.0421 loss_prob: 1.9075 loss_thr: 0.8024 loss_db: 0.3322 2022/10/25 20:59:08 - mmengine - INFO - Epoch(train) [137][55/63] lr: 2.0512e-03 eta: 14:44:35 time: 0.7892 data_time: 0.0217 memory: 16131 loss: 2.9165 loss_prob: 1.8243 loss_thr: 0.7800 loss_db: 0.3123 2022/10/25 20:59:14 - mmengine - INFO - Epoch(train) [137][60/63] lr: 2.0512e-03 eta: 14:44:45 time: 1.0246 data_time: 0.0078 memory: 16131 loss: 2.7476 loss_prob: 1.7047 loss_thr: 0.7560 loss_db: 0.2869 2022/10/25 20:59:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 20:59:26 - mmengine - INFO - Epoch(train) [138][5/63] lr: 2.0663e-03 eta: 14:44:45 time: 1.3717 data_time: 0.1682 memory: 16131 loss: 2.8734 loss_prob: 1.7768 loss_thr: 0.7975 loss_db: 0.2990 2022/10/25 20:59:29 - mmengine - INFO - Epoch(train) [138][10/63] lr: 2.0663e-03 eta: 14:44:49 time: 1.2165 data_time: 0.1713 memory: 16131 loss: 2.7275 loss_prob: 1.6638 loss_thr: 0.7843 loss_db: 0.2793 2022/10/25 20:59:32 - mmengine - INFO - Epoch(train) [138][15/63] lr: 2.0663e-03 eta: 14:44:49 time: 0.6435 data_time: 0.0137 memory: 16131 loss: 2.6899 loss_prob: 1.6648 loss_thr: 0.7456 loss_db: 0.2795 2022/10/25 20:59:37 - mmengine - INFO - Epoch(train) [138][20/63] lr: 2.0663e-03 eta: 14:44:41 time: 0.7968 data_time: 0.0105 memory: 16131 loss: 3.3967 loss_prob: 2.1878 loss_thr: 0.8142 loss_db: 0.3947 2022/10/25 20:59:40 - mmengine - INFO - Epoch(train) [138][25/63] lr: 2.0663e-03 eta: 14:44:41 time: 0.7468 data_time: 0.0093 memory: 16131 loss: 3.1735 loss_prob: 2.0261 loss_thr: 0.7906 loss_db: 0.3568 2022/10/25 20:59:43 - mmengine - INFO - Epoch(train) [138][30/63] lr: 2.0663e-03 eta: 14:44:16 time: 0.5678 data_time: 0.0384 memory: 16131 loss: 2.5960 loss_prob: 1.5885 loss_thr: 0.7518 loss_db: 0.2558 2022/10/25 20:59:49 - mmengine - INFO - Epoch(train) [138][35/63] lr: 2.0663e-03 eta: 14:44:16 time: 0.9524 data_time: 0.0403 memory: 16131 loss: 2.6710 loss_prob: 1.6484 loss_thr: 0.7529 loss_db: 0.2696 2022/10/25 20:59:54 - mmengine - INFO - Epoch(train) [138][40/63] lr: 2.0663e-03 eta: 14:44:34 time: 1.1290 data_time: 0.0142 memory: 16131 loss: 2.7915 loss_prob: 1.7322 loss_thr: 0.7734 loss_db: 0.2859 2022/10/25 20:59:57 - mmengine - INFO - Epoch(train) [138][45/63] lr: 2.0663e-03 eta: 14:44:34 time: 0.7884 data_time: 0.0101 memory: 16131 loss: 3.0812 loss_prob: 1.9384 loss_thr: 0.8033 loss_db: 0.3395 2022/10/25 21:00:00 - mmengine - INFO - Epoch(train) [138][50/63] lr: 2.0663e-03 eta: 14:44:10 time: 0.5884 data_time: 0.0212 memory: 16131 loss: 2.9314 loss_prob: 1.8360 loss_thr: 0.7757 loss_db: 0.3197 2022/10/25 21:00:04 - mmengine - INFO - Epoch(train) [138][55/63] lr: 2.0663e-03 eta: 14:44:10 time: 0.7203 data_time: 0.0273 memory: 16131 loss: 2.7047 loss_prob: 1.6595 loss_thr: 0.7710 loss_db: 0.2742 2022/10/25 21:00:08 - mmengine - INFO - Epoch(train) [138][60/63] lr: 2.0663e-03 eta: 14:44:07 time: 0.8454 data_time: 0.0162 memory: 16131 loss: 2.7259 loss_prob: 1.6786 loss_thr: 0.7683 loss_db: 0.2789 2022/10/25 21:00:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:00:20 - mmengine - INFO - Epoch(train) [139][5/63] lr: 2.0813e-03 eta: 14:44:07 time: 1.2956 data_time: 0.2365 memory: 16131 loss: 2.7122 loss_prob: 1.6616 loss_thr: 0.7721 loss_db: 0.2785 2022/10/25 21:00:23 - mmengine - INFO - Epoch(train) [139][10/63] lr: 2.0813e-03 eta: 14:44:18 time: 1.3118 data_time: 0.2281 memory: 16131 loss: 2.8661 loss_prob: 1.7811 loss_thr: 0.7757 loss_db: 0.3093 2022/10/25 21:00:28 - mmengine - INFO - Epoch(train) [139][15/63] lr: 2.0813e-03 eta: 14:44:18 time: 0.7820 data_time: 0.0061 memory: 16131 loss: 3.1106 loss_prob: 1.9869 loss_thr: 0.7715 loss_db: 0.3522 2022/10/25 21:00:32 - mmengine - INFO - Epoch(train) [139][20/63] lr: 2.0813e-03 eta: 14:44:16 time: 0.8770 data_time: 0.0080 memory: 16131 loss: 3.1832 loss_prob: 2.0429 loss_thr: 0.7819 loss_db: 0.3585 2022/10/25 21:00:37 - mmengine - INFO - Epoch(train) [139][25/63] lr: 2.0813e-03 eta: 14:44:16 time: 0.9248 data_time: 0.0293 memory: 16131 loss: 2.9309 loss_prob: 1.8451 loss_thr: 0.7698 loss_db: 0.3160 2022/10/25 21:00:41 - mmengine - INFO - Epoch(train) [139][30/63] lr: 2.0813e-03 eta: 14:44:20 time: 0.9382 data_time: 0.0460 memory: 16131 loss: 2.7560 loss_prob: 1.7177 loss_thr: 0.7507 loss_db: 0.2876 2022/10/25 21:00:44 - mmengine - INFO - Epoch(train) [139][35/63] lr: 2.0813e-03 eta: 14:44:20 time: 0.7069 data_time: 0.0248 memory: 16131 loss: 2.9569 loss_prob: 1.8465 loss_thr: 0.7916 loss_db: 0.3188 2022/10/25 21:00:47 - mmengine - INFO - Epoch(train) [139][40/63] lr: 2.0813e-03 eta: 14:43:54 time: 0.5609 data_time: 0.0058 memory: 16131 loss: 2.8533 loss_prob: 1.7693 loss_thr: 0.7809 loss_db: 0.3031 2022/10/25 21:00:50 - mmengine - INFO - Epoch(train) [139][45/63] lr: 2.0813e-03 eta: 14:43:54 time: 0.5704 data_time: 0.0071 memory: 16131 loss: 2.7714 loss_prob: 1.7318 loss_thr: 0.7535 loss_db: 0.2861 2022/10/25 21:00:53 - mmengine - INFO - Epoch(train) [139][50/63] lr: 2.0813e-03 eta: 14:43:30 time: 0.5843 data_time: 0.0197 memory: 16131 loss: 2.7376 loss_prob: 1.7049 loss_thr: 0.7489 loss_db: 0.2839 2022/10/25 21:00:56 - mmengine - INFO - Epoch(train) [139][55/63] lr: 2.0813e-03 eta: 14:43:30 time: 0.5723 data_time: 0.0237 memory: 16131 loss: 2.6551 loss_prob: 1.6214 loss_thr: 0.7646 loss_db: 0.2691 2022/10/25 21:00:59 - mmengine - INFO - Epoch(train) [139][60/63] lr: 2.0813e-03 eta: 14:43:05 time: 0.5757 data_time: 0.0111 memory: 16131 loss: 2.7175 loss_prob: 1.6600 loss_thr: 0.7795 loss_db: 0.2780 2022/10/25 21:01:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:01:07 - mmengine - INFO - Epoch(train) [140][5/63] lr: 2.0964e-03 eta: 14:43:05 time: 0.9112 data_time: 0.2088 memory: 16131 loss: 2.4894 loss_prob: 1.5198 loss_thr: 0.7239 loss_db: 0.2457 2022/10/25 21:01:12 - mmengine - INFO - Epoch(train) [140][10/63] lr: 2.0964e-03 eta: 14:43:05 time: 1.1573 data_time: 0.2179 memory: 16131 loss: 2.5617 loss_prob: 1.5583 loss_thr: 0.7490 loss_db: 0.2544 2022/10/25 21:01:17 - mmengine - INFO - Epoch(train) [140][15/63] lr: 2.0964e-03 eta: 14:43:05 time: 0.9983 data_time: 0.0164 memory: 16131 loss: 2.7188 loss_prob: 1.6488 loss_thr: 0.7975 loss_db: 0.2724 2022/10/25 21:01:20 - mmengine - INFO - Epoch(train) [140][20/63] lr: 2.0964e-03 eta: 14:43:02 time: 0.8554 data_time: 0.0082 memory: 16131 loss: 2.6897 loss_prob: 1.6350 loss_thr: 0.7848 loss_db: 0.2698 2022/10/25 21:01:25 - mmengine - INFO - Epoch(train) [140][25/63] lr: 2.0964e-03 eta: 14:43:02 time: 0.8457 data_time: 0.0140 memory: 16131 loss: 2.6538 loss_prob: 1.6301 loss_thr: 0.7518 loss_db: 0.2719 2022/10/25 21:01:28 - mmengine - INFO - Epoch(train) [140][30/63] lr: 2.0964e-03 eta: 14:42:53 time: 0.7811 data_time: 0.0303 memory: 16131 loss: 2.6475 loss_prob: 1.6223 loss_thr: 0.7505 loss_db: 0.2747 2022/10/25 21:01:32 - mmengine - INFO - Epoch(train) [140][35/63] lr: 2.0964e-03 eta: 14:42:53 time: 0.6916 data_time: 0.0266 memory: 16131 loss: 2.5968 loss_prob: 1.5809 loss_thr: 0.7529 loss_db: 0.2630 2022/10/25 21:01:34 - mmengine - INFO - Epoch(train) [140][40/63] lr: 2.0964e-03 eta: 14:42:34 time: 0.6555 data_time: 0.0113 memory: 16131 loss: 2.4838 loss_prob: 1.5024 loss_thr: 0.7373 loss_db: 0.2441 2022/10/25 21:01:42 - mmengine - INFO - Epoch(train) [140][45/63] lr: 2.0964e-03 eta: 14:42:34 time: 1.0312 data_time: 0.0085 memory: 16131 loss: 2.5894 loss_prob: 1.5824 loss_thr: 0.7465 loss_db: 0.2606 2022/10/25 21:01:46 - mmengine - INFO - Epoch(train) [140][50/63] lr: 2.0964e-03 eta: 14:42:52 time: 1.1253 data_time: 0.0144 memory: 16131 loss: 2.7758 loss_prob: 1.7249 loss_thr: 0.7582 loss_db: 0.2927 2022/10/25 21:01:49 - mmengine - INFO - Epoch(train) [140][55/63] lr: 2.0964e-03 eta: 14:42:52 time: 0.6994 data_time: 0.0232 memory: 16131 loss: 3.0296 loss_prob: 1.9371 loss_thr: 0.7534 loss_db: 0.3391 2022/10/25 21:01:52 - mmengine - INFO - Epoch(train) [140][60/63] lr: 2.0964e-03 eta: 14:42:33 time: 0.6490 data_time: 0.0180 memory: 16131 loss: 3.1606 loss_prob: 2.0285 loss_thr: 0.7768 loss_db: 0.3553 2022/10/25 21:01:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:01:55 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/10/25 21:02:02 - mmengine - INFO - Epoch(val) [140][5/32] eta: 14:42:33 time: 0.5868 data_time: 0.0804 memory: 16131 2022/10/25 21:02:05 - mmengine - INFO - Epoch(val) [140][10/32] eta: 0:00:15 time: 0.6907 data_time: 0.0951 memory: 15724 2022/10/25 21:02:09 - mmengine - INFO - Epoch(val) [140][15/32] eta: 0:00:15 time: 0.6418 data_time: 0.0530 memory: 15724 2022/10/25 21:02:12 - mmengine - INFO - Epoch(val) [140][20/32] eta: 0:00:07 time: 0.6451 data_time: 0.0709 memory: 15724 2022/10/25 21:02:15 - mmengine - INFO - Epoch(val) [140][25/32] eta: 0:00:07 time: 0.6274 data_time: 0.0458 memory: 15724 2022/10/25 21:02:18 - mmengine - INFO - Epoch(val) [140][30/32] eta: 0:00:01 time: 0.5917 data_time: 0.0212 memory: 15724 2022/10/25 21:02:19 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.5676, precision: 0.3320, hmean: 0.4190 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.5676, precision: 0.4758, hmean: 0.5177 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.5551, precision: 0.6024, hmean: 0.5778 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.5128, precision: 0.7030, hmean: 0.5930 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.3799, precision: 0.7954, hmean: 0.5142 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0236, precision: 0.8909, hmean: 0.0460 2022/10/25 21:02:19 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 21:02:19 - mmengine - INFO - Epoch(val) [140][32/32] icdar/precision: 0.7030 icdar/recall: 0.5128 icdar/hmean: 0.5930 2022/10/25 21:02:25 - mmengine - INFO - Epoch(train) [141][5/63] lr: 2.1114e-03 eta: 0:00:01 time: 1.0960 data_time: 0.2536 memory: 16131 loss: 2.9741 loss_prob: 1.8588 loss_thr: 0.7997 loss_db: 0.3157 2022/10/25 21:02:32 - mmengine - INFO - Epoch(train) [141][10/63] lr: 2.1114e-03 eta: 14:42:46 time: 1.3463 data_time: 0.2545 memory: 16131 loss: 2.8205 loss_prob: 1.7426 loss_thr: 0.7787 loss_db: 0.2992 2022/10/25 21:02:35 - mmengine - INFO - Epoch(train) [141][15/63] lr: 2.1114e-03 eta: 14:42:46 time: 0.9484 data_time: 0.0073 memory: 16131 loss: 2.5991 loss_prob: 1.5850 loss_thr: 0.7537 loss_db: 0.2603 2022/10/25 21:02:39 - mmengine - INFO - Epoch(train) [141][20/63] lr: 2.1114e-03 eta: 14:42:32 time: 0.7065 data_time: 0.0082 memory: 16131 loss: 2.6367 loss_prob: 1.6127 loss_thr: 0.7575 loss_db: 0.2665 2022/10/25 21:02:44 - mmengine - INFO - Epoch(train) [141][25/63] lr: 2.1114e-03 eta: 14:42:32 time: 0.8650 data_time: 0.0223 memory: 16131 loss: 2.6309 loss_prob: 1.5968 loss_thr: 0.7689 loss_db: 0.2651 2022/10/25 21:02:49 - mmengine - INFO - Epoch(train) [141][30/63] lr: 2.1114e-03 eta: 14:42:39 time: 0.9886 data_time: 0.0342 memory: 16131 loss: 2.8838 loss_prob: 1.7730 loss_thr: 0.8049 loss_db: 0.3059 2022/10/25 21:02:52 - mmengine - INFO - Epoch(train) [141][35/63] lr: 2.1114e-03 eta: 14:42:39 time: 0.8432 data_time: 0.0210 memory: 16131 loss: 3.1012 loss_prob: 1.9427 loss_thr: 0.8187 loss_db: 0.3397 2022/10/25 21:02:56 - mmengine - INFO - Epoch(train) [141][40/63] lr: 2.1114e-03 eta: 14:42:27 time: 0.7407 data_time: 0.0083 memory: 16131 loss: 2.9524 loss_prob: 1.8508 loss_thr: 0.7822 loss_db: 0.3194 2022/10/25 21:03:01 - mmengine - INFO - Epoch(train) [141][45/63] lr: 2.1114e-03 eta: 14:42:27 time: 0.8648 data_time: 0.0074 memory: 16131 loss: 2.9826 loss_prob: 1.8770 loss_thr: 0.7785 loss_db: 0.3270 2022/10/25 21:03:07 - mmengine - INFO - Epoch(train) [141][50/63] lr: 2.1114e-03 eta: 14:42:39 time: 1.0543 data_time: 0.0253 memory: 16131 loss: 2.8475 loss_prob: 1.7815 loss_thr: 0.7591 loss_db: 0.3069 2022/10/25 21:03:15 - mmengine - INFO - Epoch(train) [141][55/63] lr: 2.1114e-03 eta: 14:42:39 time: 1.4244 data_time: 0.0248 memory: 16131 loss: 2.6656 loss_prob: 1.6550 loss_thr: 0.7350 loss_db: 0.2756 2022/10/25 21:03:20 - mmengine - INFO - Epoch(train) [141][60/63] lr: 2.1114e-03 eta: 14:43:07 time: 1.2728 data_time: 0.0055 memory: 16131 loss: 2.9664 loss_prob: 1.8683 loss_thr: 0.7852 loss_db: 0.3130 2022/10/25 21:03:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:03:29 - mmengine - INFO - Epoch(train) [142][5/63] lr: 2.1265e-03 eta: 14:43:07 time: 1.0592 data_time: 0.2616 memory: 16131 loss: 2.6545 loss_prob: 1.6239 loss_thr: 0.7601 loss_db: 0.2705 2022/10/25 21:03:32 - mmengine - INFO - Epoch(train) [142][10/63] lr: 2.1265e-03 eta: 14:42:59 time: 1.0731 data_time: 0.2616 memory: 16131 loss: 2.7296 loss_prob: 1.6857 loss_thr: 0.7633 loss_db: 0.2806 2022/10/25 21:03:37 - mmengine - INFO - Epoch(train) [142][15/63] lr: 2.1265e-03 eta: 14:42:59 time: 0.7930 data_time: 0.0122 memory: 16131 loss: 2.7612 loss_prob: 1.7233 loss_thr: 0.7508 loss_db: 0.2870 2022/10/25 21:03:42 - mmengine - INFO - Epoch(train) [142][20/63] lr: 2.1265e-03 eta: 14:43:08 time: 1.0191 data_time: 0.0103 memory: 16131 loss: 2.6134 loss_prob: 1.6178 loss_thr: 0.7268 loss_db: 0.2688 2022/10/25 21:03:45 - mmengine - INFO - Epoch(train) [142][25/63] lr: 2.1265e-03 eta: 14:43:08 time: 0.8148 data_time: 0.0108 memory: 16131 loss: 2.7052 loss_prob: 1.6724 loss_thr: 0.7536 loss_db: 0.2792 2022/10/25 21:03:48 - mmengine - INFO - Epoch(train) [142][30/63] lr: 2.1265e-03 eta: 14:42:44 time: 0.5722 data_time: 0.0394 memory: 16131 loss: 3.0397 loss_prob: 1.9152 loss_thr: 0.7999 loss_db: 0.3247 2022/10/25 21:03:54 - mmengine - INFO - Epoch(train) [142][35/63] lr: 2.1265e-03 eta: 14:42:44 time: 0.8890 data_time: 0.0406 memory: 16131 loss: 3.1953 loss_prob: 2.0281 loss_thr: 0.8161 loss_db: 0.3512 2022/10/25 21:03:59 - mmengine - INFO - Epoch(train) [142][40/63] lr: 2.1265e-03 eta: 14:43:04 time: 1.1699 data_time: 0.0148 memory: 16131 loss: 2.8926 loss_prob: 1.8118 loss_thr: 0.7741 loss_db: 0.3066 2022/10/25 21:04:06 - mmengine - INFO - Epoch(train) [142][45/63] lr: 2.1265e-03 eta: 14:43:04 time: 1.2254 data_time: 0.0089 memory: 16131 loss: 2.6822 loss_prob: 1.6653 loss_thr: 0.7416 loss_db: 0.2753 2022/10/25 21:04:10 - mmengine - INFO - Epoch(train) [142][50/63] lr: 2.1265e-03 eta: 14:43:14 time: 1.0346 data_time: 0.0186 memory: 16131 loss: 2.8199 loss_prob: 1.7549 loss_thr: 0.7692 loss_db: 0.2959 2022/10/25 21:04:14 - mmengine - INFO - Epoch(train) [142][55/63] lr: 2.1265e-03 eta: 14:43:14 time: 0.7861 data_time: 0.0223 memory: 16131 loss: 2.8002 loss_prob: 1.7362 loss_thr: 0.7735 loss_db: 0.2904 2022/10/25 21:04:21 - mmengine - INFO - Epoch(train) [142][60/63] lr: 2.1265e-03 eta: 14:43:30 time: 1.1139 data_time: 0.0121 memory: 16131 loss: 3.0014 loss_prob: 1.8894 loss_thr: 0.7873 loss_db: 0.3247 2022/10/25 21:04:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:04:31 - mmengine - INFO - Epoch(train) [143][5/63] lr: 2.1416e-03 eta: 14:43:30 time: 1.2508 data_time: 0.2203 memory: 16131 loss: 2.9551 loss_prob: 1.8614 loss_thr: 0.7763 loss_db: 0.3174 2022/10/25 21:04:36 - mmengine - INFO - Epoch(train) [143][10/63] lr: 2.1416e-03 eta: 14:43:42 time: 1.3337 data_time: 0.2186 memory: 16131 loss: 2.7433 loss_prob: 1.7043 loss_thr: 0.7513 loss_db: 0.2877 2022/10/25 21:04:40 - mmengine - INFO - Epoch(train) [143][15/63] lr: 2.1416e-03 eta: 14:43:42 time: 0.8369 data_time: 0.0062 memory: 16131 loss: 2.7166 loss_prob: 1.6793 loss_thr: 0.7544 loss_db: 0.2830 2022/10/25 21:04:42 - mmengine - INFO - Epoch(train) [143][20/63] lr: 2.1416e-03 eta: 14:43:21 time: 0.6217 data_time: 0.0077 memory: 16131 loss: 2.9709 loss_prob: 1.8665 loss_thr: 0.7774 loss_db: 0.3270 2022/10/25 21:04:46 - mmengine - INFO - Epoch(train) [143][25/63] lr: 2.1416e-03 eta: 14:43:21 time: 0.6332 data_time: 0.0459 memory: 16131 loss: 3.1101 loss_prob: 1.9781 loss_thr: 0.7803 loss_db: 0.3517 2022/10/25 21:04:49 - mmengine - INFO - Epoch(train) [143][30/63] lr: 2.1416e-03 eta: 14:43:01 time: 0.6422 data_time: 0.0584 memory: 16131 loss: 2.8514 loss_prob: 1.7889 loss_thr: 0.7608 loss_db: 0.3016 2022/10/25 21:04:52 - mmengine - INFO - Epoch(train) [143][35/63] lr: 2.1416e-03 eta: 14:43:01 time: 0.5732 data_time: 0.0235 memory: 16131 loss: 2.7172 loss_prob: 1.6790 loss_thr: 0.7561 loss_db: 0.2821 2022/10/25 21:04:55 - mmengine - INFO - Epoch(train) [143][40/63] lr: 2.1416e-03 eta: 14:42:38 time: 0.5889 data_time: 0.0101 memory: 16131 loss: 2.7124 loss_prob: 1.6713 loss_thr: 0.7637 loss_db: 0.2774 2022/10/25 21:04:58 - mmengine - INFO - Epoch(train) [143][45/63] lr: 2.1416e-03 eta: 14:42:38 time: 0.6568 data_time: 0.0097 memory: 16131 loss: 2.8453 loss_prob: 1.7901 loss_thr: 0.7556 loss_db: 0.2996 2022/10/25 21:05:01 - mmengine - INFO - Epoch(train) [143][50/63] lr: 2.1416e-03 eta: 14:42:19 time: 0.6407 data_time: 0.0200 memory: 16131 loss: 2.9191 loss_prob: 1.8432 loss_thr: 0.7602 loss_db: 0.3158 2022/10/25 21:05:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:05:05 - mmengine - INFO - Epoch(train) [143][55/63] lr: 2.1416e-03 eta: 14:42:19 time: 0.7166 data_time: 0.0373 memory: 16131 loss: 3.0264 loss_prob: 1.9077 loss_thr: 0.7900 loss_db: 0.3286 2022/10/25 21:05:09 - mmengine - INFO - Epoch(train) [143][60/63] lr: 2.1416e-03 eta: 14:42:10 time: 0.7773 data_time: 0.0264 memory: 16131 loss: 3.3675 loss_prob: 2.1697 loss_thr: 0.8161 loss_db: 0.3817 2022/10/25 21:05:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:05:21 - mmengine - INFO - Epoch(train) [144][5/63] lr: 2.1566e-03 eta: 14:42:10 time: 1.3102 data_time: 0.2247 memory: 16131 loss: 2.9259 loss_prob: 1.8285 loss_thr: 0.7878 loss_db: 0.3097 2022/10/25 21:05:24 - mmengine - INFO - Epoch(train) [144][10/63] lr: 2.1566e-03 eta: 14:42:15 time: 1.2441 data_time: 0.2243 memory: 16131 loss: 2.7532 loss_prob: 1.7030 loss_thr: 0.7604 loss_db: 0.2898 2022/10/25 21:05:27 - mmengine - INFO - Epoch(train) [144][15/63] lr: 2.1566e-03 eta: 14:42:15 time: 0.6011 data_time: 0.0062 memory: 16131 loss: 2.7999 loss_prob: 1.7366 loss_thr: 0.7689 loss_db: 0.2944 2022/10/25 21:05:30 - mmengine - INFO - Epoch(train) [144][20/63] lr: 2.1566e-03 eta: 14:41:52 time: 0.6000 data_time: 0.0117 memory: 16131 loss: 2.7837 loss_prob: 1.6887 loss_thr: 0.8107 loss_db: 0.2843 2022/10/25 21:05:34 - mmengine - INFO - Epoch(train) [144][25/63] lr: 2.1566e-03 eta: 14:41:52 time: 0.7007 data_time: 0.0406 memory: 16131 loss: 2.7579 loss_prob: 1.6651 loss_thr: 0.8116 loss_db: 0.2812 2022/10/25 21:05:37 - mmengine - INFO - Epoch(train) [144][30/63] lr: 2.1566e-03 eta: 14:41:34 time: 0.6559 data_time: 0.0365 memory: 16131 loss: 2.8285 loss_prob: 1.7573 loss_thr: 0.7723 loss_db: 0.2990 2022/10/25 21:05:39 - mmengine - INFO - Epoch(train) [144][35/63] lr: 2.1566e-03 eta: 14:41:34 time: 0.5183 data_time: 0.0083 memory: 16131 loss: 2.8309 loss_prob: 1.7707 loss_thr: 0.7582 loss_db: 0.3021 2022/10/25 21:05:42 - mmengine - INFO - Epoch(train) [144][40/63] lr: 2.1566e-03 eta: 14:41:08 time: 0.5491 data_time: 0.0085 memory: 16131 loss: 2.7614 loss_prob: 1.7216 loss_thr: 0.7495 loss_db: 0.2903 2022/10/25 21:05:47 - mmengine - INFO - Epoch(train) [144][45/63] lr: 2.1566e-03 eta: 14:41:08 time: 0.7944 data_time: 0.0090 memory: 16131 loss: 2.6276 loss_prob: 1.6194 loss_thr: 0.7395 loss_db: 0.2687 2022/10/25 21:05:53 - mmengine - INFO - Epoch(train) [144][50/63] lr: 2.1566e-03 eta: 14:41:21 time: 1.0768 data_time: 0.0272 memory: 16131 loss: 2.4692 loss_prob: 1.5047 loss_thr: 0.7189 loss_db: 0.2457 2022/10/25 21:05:56 - mmengine - INFO - Epoch(train) [144][55/63] lr: 2.1566e-03 eta: 14:41:21 time: 0.9550 data_time: 0.0255 memory: 16131 loss: 2.5824 loss_prob: 1.5994 loss_thr: 0.7233 loss_db: 0.2597 2022/10/25 21:06:05 - mmengine - INFO - Epoch(train) [144][60/63] lr: 2.1566e-03 eta: 14:41:48 time: 1.2708 data_time: 0.0057 memory: 16131 loss: 2.7150 loss_prob: 1.6783 loss_thr: 0.7621 loss_db: 0.2745 2022/10/25 21:06:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:06:15 - mmengine - INFO - Epoch(train) [145][5/63] lr: 2.1717e-03 eta: 14:41:48 time: 1.3705 data_time: 0.1863 memory: 16131 loss: 2.7717 loss_prob: 1.7004 loss_thr: 0.7833 loss_db: 0.2880 2022/10/25 21:06:19 - mmengine - INFO - Epoch(train) [145][10/63] lr: 2.1717e-03 eta: 14:41:42 time: 1.0911 data_time: 0.1861 memory: 16131 loss: 2.8174 loss_prob: 1.7494 loss_thr: 0.7727 loss_db: 0.2953 2022/10/25 21:06:24 - mmengine - INFO - Epoch(train) [145][15/63] lr: 2.1717e-03 eta: 14:41:42 time: 0.9064 data_time: 0.0080 memory: 16131 loss: 2.7947 loss_prob: 1.7361 loss_thr: 0.7630 loss_db: 0.2956 2022/10/25 21:06:27 - mmengine - INFO - Epoch(train) [145][20/63] lr: 2.1717e-03 eta: 14:41:31 time: 0.7571 data_time: 0.0124 memory: 16131 loss: 2.8396 loss_prob: 1.7684 loss_thr: 0.7754 loss_db: 0.2958 2022/10/25 21:06:31 - mmengine - INFO - Epoch(train) [145][25/63] lr: 2.1717e-03 eta: 14:41:31 time: 0.6982 data_time: 0.0317 memory: 16131 loss: 2.5772 loss_prob: 1.5956 loss_thr: 0.7293 loss_db: 0.2523 2022/10/25 21:06:36 - mmengine - INFO - Epoch(train) [145][30/63] lr: 2.1717e-03 eta: 14:41:33 time: 0.9350 data_time: 0.0420 memory: 16131 loss: 2.6257 loss_prob: 1.6178 loss_thr: 0.7411 loss_db: 0.2668 2022/10/25 21:06:42 - mmengine - INFO - Epoch(train) [145][35/63] lr: 2.1717e-03 eta: 14:41:33 time: 1.0496 data_time: 0.0206 memory: 16131 loss: 2.6575 loss_prob: 1.6259 loss_thr: 0.7600 loss_db: 0.2717 2022/10/25 21:06:46 - mmengine - INFO - Epoch(train) [145][40/63] lr: 2.1717e-03 eta: 14:41:39 time: 0.9821 data_time: 0.0080 memory: 16131 loss: 2.6414 loss_prob: 1.6256 loss_thr: 0.7496 loss_db: 0.2662 2022/10/25 21:06:50 - mmengine - INFO - Epoch(train) [145][45/63] lr: 2.1717e-03 eta: 14:41:39 time: 0.8686 data_time: 0.0076 memory: 16131 loss: 2.6384 loss_prob: 1.6159 loss_thr: 0.7547 loss_db: 0.2678 2022/10/25 21:06:55 - mmengine - INFO - Epoch(train) [145][50/63] lr: 2.1717e-03 eta: 14:41:40 time: 0.9190 data_time: 0.0194 memory: 16131 loss: 2.5664 loss_prob: 1.5565 loss_thr: 0.7525 loss_db: 0.2574 2022/10/25 21:07:01 - mmengine - INFO - Epoch(train) [145][55/63] lr: 2.1717e-03 eta: 14:41:40 time: 1.0989 data_time: 0.0278 memory: 16131 loss: 2.6522 loss_prob: 1.6375 loss_thr: 0.7465 loss_db: 0.2681 2022/10/25 21:07:04 - mmengine - INFO - Epoch(train) [145][60/63] lr: 2.1717e-03 eta: 14:41:42 time: 0.9272 data_time: 0.0171 memory: 16131 loss: 2.6441 loss_prob: 1.6395 loss_thr: 0.7342 loss_db: 0.2704 2022/10/25 21:07:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:07:13 - mmengine - INFO - Epoch(train) [146][5/63] lr: 2.1867e-03 eta: 14:41:42 time: 1.0336 data_time: 0.1572 memory: 16131 loss: 2.5897 loss_prob: 1.5865 loss_thr: 0.7449 loss_db: 0.2582 2022/10/25 21:07:16 - mmengine - INFO - Epoch(train) [146][10/63] lr: 2.1867e-03 eta: 14:41:28 time: 0.9951 data_time: 0.1567 memory: 16131 loss: 2.5661 loss_prob: 1.5734 loss_thr: 0.7362 loss_db: 0.2565 2022/10/25 21:07:22 - mmengine - INFO - Epoch(train) [146][15/63] lr: 2.1867e-03 eta: 14:41:28 time: 0.9363 data_time: 0.0236 memory: 16131 loss: 2.8809 loss_prob: 1.7984 loss_thr: 0.7772 loss_db: 0.3052 2022/10/25 21:07:27 - mmengine - INFO - Epoch(train) [146][20/63] lr: 2.1867e-03 eta: 14:41:46 time: 1.1411 data_time: 0.0211 memory: 16131 loss: 2.9380 loss_prob: 1.8286 loss_thr: 0.7939 loss_db: 0.3155 2022/10/25 21:07:30 - mmengine - INFO - Epoch(train) [146][25/63] lr: 2.1867e-03 eta: 14:41:46 time: 0.7805 data_time: 0.0123 memory: 16131 loss: 2.7296 loss_prob: 1.6793 loss_thr: 0.7652 loss_db: 0.2851 2022/10/25 21:07:35 - mmengine - INFO - Epoch(train) [146][30/63] lr: 2.1867e-03 eta: 14:41:37 time: 0.7904 data_time: 0.0287 memory: 16131 loss: 2.7711 loss_prob: 1.7091 loss_thr: 0.7750 loss_db: 0.2870 2022/10/25 21:07:39 - mmengine - INFO - Epoch(train) [146][35/63] lr: 2.1867e-03 eta: 14:41:37 time: 0.8305 data_time: 0.0350 memory: 16131 loss: 2.8102 loss_prob: 1.7485 loss_thr: 0.7703 loss_db: 0.2914 2022/10/25 21:07:44 - mmengine - INFO - Epoch(train) [146][40/63] lr: 2.1867e-03 eta: 14:41:34 time: 0.8608 data_time: 0.0177 memory: 16131 loss: 2.6388 loss_prob: 1.6218 loss_thr: 0.7490 loss_db: 0.2680 2022/10/25 21:07:47 - mmengine - INFO - Epoch(train) [146][45/63] lr: 2.1867e-03 eta: 14:41:34 time: 0.8743 data_time: 0.0054 memory: 16131 loss: 2.7618 loss_prob: 1.7242 loss_thr: 0.7499 loss_db: 0.2876 2022/10/25 21:07:52 - mmengine - INFO - Epoch(train) [146][50/63] lr: 2.1867e-03 eta: 14:41:25 time: 0.7895 data_time: 0.0151 memory: 16131 loss: 2.9061 loss_prob: 1.8545 loss_thr: 0.7385 loss_db: 0.3132 2022/10/25 21:07:56 - mmengine - INFO - Epoch(train) [146][55/63] lr: 2.1867e-03 eta: 14:41:25 time: 0.8813 data_time: 0.0237 memory: 16131 loss: 2.8244 loss_prob: 1.7761 loss_thr: 0.7506 loss_db: 0.2977 2022/10/25 21:07:59 - mmengine - INFO - Epoch(train) [146][60/63] lr: 2.1867e-03 eta: 14:41:13 time: 0.7406 data_time: 0.0255 memory: 16131 loss: 2.6807 loss_prob: 1.6659 loss_thr: 0.7367 loss_db: 0.2781 2022/10/25 21:08:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:08:06 - mmengine - INFO - Epoch(train) [147][5/63] lr: 2.2018e-03 eta: 14:41:13 time: 0.7781 data_time: 0.2199 memory: 16131 loss: 2.7823 loss_prob: 1.7183 loss_thr: 0.7678 loss_db: 0.2961 2022/10/25 21:08:10 - mmengine - INFO - Epoch(train) [147][10/63] lr: 2.2018e-03 eta: 14:40:59 time: 0.9751 data_time: 0.2138 memory: 16131 loss: 2.8052 loss_prob: 1.7378 loss_thr: 0.7755 loss_db: 0.2919 2022/10/25 21:08:15 - mmengine - INFO - Epoch(train) [147][15/63] lr: 2.2018e-03 eta: 14:40:59 time: 0.9238 data_time: 0.0172 memory: 16131 loss: 2.7993 loss_prob: 1.7376 loss_thr: 0.7700 loss_db: 0.2917 2022/10/25 21:08:21 - mmengine - INFO - Epoch(train) [147][20/63] lr: 2.2018e-03 eta: 14:41:09 time: 1.0450 data_time: 0.0148 memory: 16131 loss: 2.7765 loss_prob: 1.7056 loss_thr: 0.7807 loss_db: 0.2902 2022/10/25 21:08:24 - mmengine - INFO - Epoch(train) [147][25/63] lr: 2.2018e-03 eta: 14:41:09 time: 0.8620 data_time: 0.0250 memory: 16131 loss: 2.7603 loss_prob: 1.7031 loss_thr: 0.7710 loss_db: 0.2862 2022/10/25 21:08:26 - mmengine - INFO - Epoch(train) [147][30/63] lr: 2.2018e-03 eta: 14:40:44 time: 0.5580 data_time: 0.0331 memory: 16131 loss: 2.6020 loss_prob: 1.5956 loss_thr: 0.7471 loss_db: 0.2593 2022/10/25 21:08:29 - mmengine - INFO - Epoch(train) [147][35/63] lr: 2.2018e-03 eta: 14:40:44 time: 0.5497 data_time: 0.0159 memory: 16131 loss: 2.5256 loss_prob: 1.5382 loss_thr: 0.7318 loss_db: 0.2556 2022/10/25 21:08:33 - mmengine - INFO - Epoch(train) [147][40/63] lr: 2.2018e-03 eta: 14:40:26 time: 0.6572 data_time: 0.0137 memory: 16131 loss: 2.7682 loss_prob: 1.7323 loss_thr: 0.7355 loss_db: 0.3004 2022/10/25 21:08:37 - mmengine - INFO - Epoch(train) [147][45/63] lr: 2.2018e-03 eta: 14:40:26 time: 0.7941 data_time: 0.0150 memory: 16131 loss: 2.7361 loss_prob: 1.7100 loss_thr: 0.7392 loss_db: 0.2869 2022/10/25 21:08:40 - mmengine - INFO - Epoch(train) [147][50/63] lr: 2.2018e-03 eta: 14:40:09 time: 0.6713 data_time: 0.0262 memory: 16131 loss: 2.8073 loss_prob: 1.7673 loss_thr: 0.7475 loss_db: 0.2925 2022/10/25 21:08:43 - mmengine - INFO - Epoch(train) [147][55/63] lr: 2.2018e-03 eta: 14:40:09 time: 0.5726 data_time: 0.0277 memory: 16131 loss: 2.9429 loss_prob: 1.8581 loss_thr: 0.7726 loss_db: 0.3122 2022/10/25 21:08:51 - mmengine - INFO - Epoch(train) [147][60/63] lr: 2.2018e-03 eta: 14:40:23 time: 1.0989 data_time: 0.0133 memory: 16131 loss: 2.9979 loss_prob: 1.8817 loss_thr: 0.7975 loss_db: 0.3187 2022/10/25 21:08:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:09:00 - mmengine - INFO - Epoch(train) [148][5/63] lr: 2.2169e-03 eta: 14:40:23 time: 1.1760 data_time: 0.2553 memory: 16131 loss: 2.7595 loss_prob: 1.7098 loss_thr: 0.7665 loss_db: 0.2833 2022/10/25 21:09:03 - mmengine - INFO - Epoch(train) [148][10/63] lr: 2.2169e-03 eta: 14:40:13 time: 1.0484 data_time: 0.2533 memory: 16131 loss: 2.7174 loss_prob: 1.6843 loss_thr: 0.7584 loss_db: 0.2746 2022/10/25 21:09:08 - mmengine - INFO - Epoch(train) [148][15/63] lr: 2.2169e-03 eta: 14:40:13 time: 0.8066 data_time: 0.0115 memory: 16131 loss: 2.8651 loss_prob: 1.7774 loss_thr: 0.7928 loss_db: 0.2949 2022/10/25 21:09:11 - mmengine - INFO - Epoch(train) [148][20/63] lr: 2.2169e-03 eta: 14:40:05 time: 0.7974 data_time: 0.0125 memory: 16131 loss: 2.7834 loss_prob: 1.7230 loss_thr: 0.7782 loss_db: 0.2822 2022/10/25 21:09:15 - mmengine - INFO - Epoch(train) [148][25/63] lr: 2.2169e-03 eta: 14:40:05 time: 0.6659 data_time: 0.0197 memory: 16131 loss: 2.7960 loss_prob: 1.7551 loss_thr: 0.7547 loss_db: 0.2862 2022/10/25 21:09:20 - mmengine - INFO - Epoch(train) [148][30/63] lr: 2.2169e-03 eta: 14:40:04 time: 0.8942 data_time: 0.0308 memory: 16131 loss: 2.7373 loss_prob: 1.7156 loss_thr: 0.7398 loss_db: 0.2819 2022/10/25 21:09:25 - mmengine - INFO - Epoch(train) [148][35/63] lr: 2.2169e-03 eta: 14:40:04 time: 1.0138 data_time: 0.0213 memory: 16131 loss: 2.5054 loss_prob: 1.5356 loss_thr: 0.7182 loss_db: 0.2515 2022/10/25 21:09:29 - mmengine - INFO - Epoch(train) [148][40/63] lr: 2.2169e-03 eta: 14:40:05 time: 0.9231 data_time: 0.0104 memory: 16131 loss: 2.5471 loss_prob: 1.5640 loss_thr: 0.7245 loss_db: 0.2585 2022/10/25 21:09:34 - mmengine - INFO - Epoch(train) [148][45/63] lr: 2.2169e-03 eta: 14:40:05 time: 0.9377 data_time: 0.0077 memory: 16131 loss: 2.5720 loss_prob: 1.5860 loss_thr: 0.7224 loss_db: 0.2635 2022/10/25 21:09:38 - mmengine - INFO - Epoch(train) [148][50/63] lr: 2.2169e-03 eta: 14:40:02 time: 0.8544 data_time: 0.0165 memory: 16131 loss: 2.5030 loss_prob: 1.5229 loss_thr: 0.7291 loss_db: 0.2510 2022/10/25 21:09:40 - mmengine - INFO - Epoch(train) [148][55/63] lr: 2.2169e-03 eta: 14:40:02 time: 0.6272 data_time: 0.0242 memory: 16131 loss: 2.6228 loss_prob: 1.6029 loss_thr: 0.7508 loss_db: 0.2691 2022/10/25 21:09:45 - mmengine - INFO - Epoch(train) [148][60/63] lr: 2.2169e-03 eta: 14:39:53 time: 0.7909 data_time: 0.0159 memory: 16131 loss: 2.6780 loss_prob: 1.6467 loss_thr: 0.7517 loss_db: 0.2796 2022/10/25 21:09:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:09:52 - mmengine - INFO - Epoch(train) [149][5/63] lr: 2.2319e-03 eta: 14:39:53 time: 0.7494 data_time: 0.2040 memory: 16131 loss: 2.6790 loss_prob: 1.6538 loss_thr: 0.7477 loss_db: 0.2775 2022/10/25 21:09:55 - mmengine - INFO - Epoch(train) [149][10/63] lr: 2.2319e-03 eta: 14:39:29 time: 0.8482 data_time: 0.2038 memory: 16131 loss: 2.6017 loss_prob: 1.6089 loss_thr: 0.7258 loss_db: 0.2670 2022/10/25 21:09:58 - mmengine - INFO - Epoch(train) [149][15/63] lr: 2.2319e-03 eta: 14:39:29 time: 0.6272 data_time: 0.0098 memory: 16131 loss: 2.4811 loss_prob: 1.5149 loss_thr: 0.7158 loss_db: 0.2505 2022/10/25 21:10:01 - mmengine - INFO - Epoch(train) [149][20/63] lr: 2.2319e-03 eta: 14:39:05 time: 0.5669 data_time: 0.0095 memory: 16131 loss: 2.3811 loss_prob: 1.4321 loss_thr: 0.7144 loss_db: 0.2346 2022/10/25 21:10:04 - mmengine - INFO - Epoch(train) [149][25/63] lr: 2.2319e-03 eta: 14:39:05 time: 0.6012 data_time: 0.0374 memory: 16131 loss: 2.5152 loss_prob: 1.5257 loss_thr: 0.7418 loss_db: 0.2477 2022/10/25 21:10:07 - mmengine - INFO - Epoch(train) [149][30/63] lr: 2.2319e-03 eta: 14:38:43 time: 0.5982 data_time: 0.0384 memory: 16131 loss: 2.6977 loss_prob: 1.6637 loss_thr: 0.7613 loss_db: 0.2727 2022/10/25 21:10:10 - mmengine - INFO - Epoch(train) [149][35/63] lr: 2.2319e-03 eta: 14:38:43 time: 0.5364 data_time: 0.0060 memory: 16131 loss: 2.6646 loss_prob: 1.6558 loss_thr: 0.7396 loss_db: 0.2693 2022/10/25 21:10:14 - mmengine - INFO - Epoch(train) [149][40/63] lr: 2.2319e-03 eta: 14:38:27 time: 0.6799 data_time: 0.0073 memory: 16131 loss: 2.6182 loss_prob: 1.6356 loss_thr: 0.7182 loss_db: 0.2644 2022/10/25 21:10:16 - mmengine - INFO - Epoch(train) [149][45/63] lr: 2.2319e-03 eta: 14:38:27 time: 0.6880 data_time: 0.0106 memory: 16131 loss: 2.5462 loss_prob: 1.5659 loss_thr: 0.7216 loss_db: 0.2588 2022/10/25 21:10:20 - mmengine - INFO - Epoch(train) [149][50/63] lr: 2.2319e-03 eta: 14:38:06 time: 0.6164 data_time: 0.0591 memory: 16131 loss: 2.7100 loss_prob: 1.6663 loss_thr: 0.7609 loss_db: 0.2828 2022/10/25 21:10:26 - mmengine - INFO - Epoch(train) [149][55/63] lr: 2.2319e-03 eta: 14:38:06 time: 0.9786 data_time: 0.0586 memory: 16131 loss: 2.7217 loss_prob: 1.6631 loss_thr: 0.7725 loss_db: 0.2860 2022/10/25 21:10:31 - mmengine - INFO - Epoch(train) [149][60/63] lr: 2.2319e-03 eta: 14:38:18 time: 1.0705 data_time: 0.0097 memory: 16131 loss: 2.4808 loss_prob: 1.4955 loss_thr: 0.7341 loss_db: 0.2512 2022/10/25 21:10:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:10:42 - mmengine - INFO - Epoch(train) [150][5/63] lr: 2.2470e-03 eta: 14:38:18 time: 1.2694 data_time: 0.2219 memory: 16131 loss: 2.8231 loss_prob: 1.7461 loss_thr: 0.7851 loss_db: 0.2919 2022/10/25 21:10:47 - mmengine - INFO - Epoch(train) [150][10/63] lr: 2.2470e-03 eta: 14:38:41 time: 1.5084 data_time: 0.2210 memory: 16131 loss: 2.7069 loss_prob: 1.6607 loss_thr: 0.7704 loss_db: 0.2759 2022/10/25 21:10:51 - mmengine - INFO - Epoch(train) [150][15/63] lr: 2.2470e-03 eta: 14:38:41 time: 0.9292 data_time: 0.0080 memory: 16131 loss: 2.6461 loss_prob: 1.6266 loss_thr: 0.7424 loss_db: 0.2772 2022/10/25 21:10:54 - mmengine - INFO - Epoch(train) [150][20/63] lr: 2.2470e-03 eta: 14:38:22 time: 0.6338 data_time: 0.0075 memory: 16131 loss: 2.6605 loss_prob: 1.6455 loss_thr: 0.7384 loss_db: 0.2766 2022/10/25 21:10:58 - mmengine - INFO - Epoch(train) [150][25/63] lr: 2.2470e-03 eta: 14:38:22 time: 0.7004 data_time: 0.0293 memory: 16131 loss: 2.6277 loss_prob: 1.6280 loss_thr: 0.7329 loss_db: 0.2669 2022/10/25 21:11:06 - mmengine - INFO - Epoch(train) [150][30/63] lr: 2.2470e-03 eta: 14:38:44 time: 1.2230 data_time: 0.0415 memory: 16131 loss: 2.6594 loss_prob: 1.6439 loss_thr: 0.7432 loss_db: 0.2723 2022/10/25 21:11:13 - mmengine - INFO - Epoch(train) [150][35/63] lr: 2.2470e-03 eta: 14:38:44 time: 1.4720 data_time: 0.0182 memory: 16131 loss: 2.6667 loss_prob: 1.6385 loss_thr: 0.7592 loss_db: 0.2690 2022/10/25 21:11:16 - mmengine - INFO - Epoch(train) [150][40/63] lr: 2.2470e-03 eta: 14:38:52 time: 1.0323 data_time: 0.0069 memory: 16131 loss: 2.6577 loss_prob: 1.6353 loss_thr: 0.7538 loss_db: 0.2686 2022/10/25 21:11:22 - mmengine - INFO - Epoch(train) [150][45/63] lr: 2.2470e-03 eta: 14:38:52 time: 0.9487 data_time: 0.0055 memory: 16131 loss: 2.8091 loss_prob: 1.7466 loss_thr: 0.7620 loss_db: 0.3006 2022/10/25 21:11:30 - mmengine - INFO - Epoch(train) [150][50/63] lr: 2.2470e-03 eta: 14:39:24 time: 1.3583 data_time: 0.0198 memory: 16131 loss: 2.8889 loss_prob: 1.8107 loss_thr: 0.7652 loss_db: 0.3130 2022/10/25 21:11:35 - mmengine - INFO - Epoch(train) [150][55/63] lr: 2.2470e-03 eta: 14:39:24 time: 1.2588 data_time: 0.0237 memory: 16131 loss: 2.6474 loss_prob: 1.6388 loss_thr: 0.7367 loss_db: 0.2719 2022/10/25 21:11:40 - mmengine - INFO - Epoch(train) [150][60/63] lr: 2.2470e-03 eta: 14:39:32 time: 1.0296 data_time: 0.0107 memory: 16131 loss: 2.4764 loss_prob: 1.5040 loss_thr: 0.7268 loss_db: 0.2456 2022/10/25 21:11:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:11:49 - mmengine - INFO - Epoch(train) [151][5/63] lr: 2.2620e-03 eta: 14:39:32 time: 1.0726 data_time: 0.2426 memory: 16131 loss: 2.5205 loss_prob: 1.5328 loss_thr: 0.7353 loss_db: 0.2524 2022/10/25 21:11:52 - mmengine - INFO - Epoch(train) [151][10/63] lr: 2.2620e-03 eta: 14:39:27 time: 1.1136 data_time: 0.2497 memory: 16131 loss: 2.6090 loss_prob: 1.6106 loss_thr: 0.7357 loss_db: 0.2627 2022/10/25 21:11:56 - mmengine - INFO - Epoch(train) [151][15/63] lr: 2.2620e-03 eta: 14:39:27 time: 0.6577 data_time: 0.0170 memory: 16131 loss: 2.6465 loss_prob: 1.6383 loss_thr: 0.7394 loss_db: 0.2687 2022/10/25 21:12:03 - mmengine - INFO - Epoch(train) [151][20/63] lr: 2.2620e-03 eta: 14:39:36 time: 1.0459 data_time: 0.0121 memory: 16131 loss: 2.5967 loss_prob: 1.6070 loss_thr: 0.7228 loss_db: 0.2669 2022/10/25 21:12:10 - mmengine - INFO - Epoch(train) [151][25/63] lr: 2.2620e-03 eta: 14:39:36 time: 1.3978 data_time: 0.0332 memory: 16131 loss: 2.7793 loss_prob: 1.7462 loss_thr: 0.7401 loss_db: 0.2931 2022/10/25 21:12:13 - mmengine - INFO - Epoch(train) [151][30/63] lr: 2.2620e-03 eta: 14:39:42 time: 0.9904 data_time: 0.0314 memory: 16131 loss: 2.8412 loss_prob: 1.7794 loss_thr: 0.7613 loss_db: 0.3004 2022/10/25 21:12:16 - mmengine - INFO - Epoch(train) [151][35/63] lr: 2.2620e-03 eta: 14:39:42 time: 0.6035 data_time: 0.0182 memory: 16131 loss: 2.6380 loss_prob: 1.6265 loss_thr: 0.7405 loss_db: 0.2710 2022/10/25 21:12:20 - mmengine - INFO - Epoch(train) [151][40/63] lr: 2.2620e-03 eta: 14:39:28 time: 0.7201 data_time: 0.0175 memory: 16131 loss: 2.6102 loss_prob: 1.6176 loss_thr: 0.7267 loss_db: 0.2659 2022/10/25 21:12:27 - mmengine - INFO - Epoch(train) [151][45/63] lr: 2.2620e-03 eta: 14:39:28 time: 1.1143 data_time: 0.0128 memory: 16131 loss: 2.5821 loss_prob: 1.5916 loss_thr: 0.7293 loss_db: 0.2612 2022/10/25 21:12:30 - mmengine - INFO - Epoch(train) [151][50/63] lr: 2.2620e-03 eta: 14:39:36 time: 1.0255 data_time: 0.0339 memory: 16131 loss: 2.5694 loss_prob: 1.5900 loss_thr: 0.7152 loss_db: 0.2642 2022/10/25 21:12:35 - mmengine - INFO - Epoch(train) [151][55/63] lr: 2.2620e-03 eta: 14:39:36 time: 0.7539 data_time: 0.0328 memory: 16131 loss: 2.6751 loss_prob: 1.6777 loss_thr: 0.7170 loss_db: 0.2804 2022/10/25 21:12:37 - mmengine - INFO - Epoch(train) [151][60/63] lr: 2.2620e-03 eta: 14:39:23 time: 0.7188 data_time: 0.0120 memory: 16131 loss: 2.6830 loss_prob: 1.6541 loss_thr: 0.7561 loss_db: 0.2728 2022/10/25 21:12:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:12:52 - mmengine - INFO - Epoch(train) [152][5/63] lr: 2.2771e-03 eta: 14:39:23 time: 1.5231 data_time: 0.2002 memory: 16131 loss: 2.6772 loss_prob: 1.6568 loss_thr: 0.7403 loss_db: 0.2801 2022/10/25 21:12:55 - mmengine - INFO - Epoch(train) [152][10/63] lr: 2.2771e-03 eta: 14:39:39 time: 1.4208 data_time: 0.2113 memory: 16131 loss: 2.6679 loss_prob: 1.6467 loss_thr: 0.7397 loss_db: 0.2815 2022/10/25 21:12:59 - mmengine - INFO - Epoch(train) [152][15/63] lr: 2.2771e-03 eta: 14:39:39 time: 0.6814 data_time: 0.0200 memory: 16131 loss: 3.1193 loss_prob: 2.0042 loss_thr: 0.7714 loss_db: 0.3437 2022/10/25 21:13:05 - mmengine - INFO - Epoch(train) [152][20/63] lr: 2.2771e-03 eta: 14:39:45 time: 1.0119 data_time: 0.0113 memory: 16131 loss: 3.1002 loss_prob: 1.9890 loss_thr: 0.7714 loss_db: 0.3398 2022/10/25 21:13:11 - mmengine - INFO - Epoch(train) [152][25/63] lr: 2.2771e-03 eta: 14:39:45 time: 1.2306 data_time: 0.0144 memory: 16131 loss: 2.7085 loss_prob: 1.6773 loss_thr: 0.7477 loss_db: 0.2835 2022/10/25 21:13:15 - mmengine - INFO - Epoch(train) [152][30/63] lr: 2.2771e-03 eta: 14:39:56 time: 1.0600 data_time: 0.0233 memory: 16131 loss: 2.5935 loss_prob: 1.5984 loss_thr: 0.7281 loss_db: 0.2670 2022/10/25 21:13:20 - mmengine - INFO - Epoch(train) [152][35/63] lr: 2.2771e-03 eta: 14:39:56 time: 0.9330 data_time: 0.0228 memory: 16131 loss: 2.5945 loss_prob: 1.5942 loss_thr: 0.7371 loss_db: 0.2632 2022/10/25 21:13:23 - mmengine - INFO - Epoch(train) [152][40/63] lr: 2.2771e-03 eta: 14:39:44 time: 0.7485 data_time: 0.0150 memory: 16131 loss: 2.9417 loss_prob: 1.8379 loss_thr: 0.7855 loss_db: 0.3183 2022/10/25 21:13:26 - mmengine - INFO - Epoch(train) [152][45/63] lr: 2.2771e-03 eta: 14:39:44 time: 0.5541 data_time: 0.0117 memory: 16131 loss: 2.8588 loss_prob: 1.7794 loss_thr: 0.7766 loss_db: 0.3029 2022/10/25 21:13:29 - mmengine - INFO - Epoch(train) [152][50/63] lr: 2.2771e-03 eta: 14:39:22 time: 0.5990 data_time: 0.0317 memory: 16131 loss: 2.6209 loss_prob: 1.6202 loss_thr: 0.7374 loss_db: 0.2633 2022/10/25 21:13:36 - mmengine - INFO - Epoch(train) [152][55/63] lr: 2.2771e-03 eta: 14:39:22 time: 0.9840 data_time: 0.0320 memory: 16131 loss: 2.6441 loss_prob: 1.6493 loss_thr: 0.7218 loss_db: 0.2730 2022/10/25 21:13:38 - mmengine - INFO - Epoch(train) [152][60/63] lr: 2.2771e-03 eta: 14:39:25 time: 0.9560 data_time: 0.0118 memory: 16131 loss: 2.5562 loss_prob: 1.5870 loss_thr: 0.7068 loss_db: 0.2625 2022/10/25 21:13:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:13:52 - mmengine - INFO - Epoch(train) [153][5/63] lr: 2.2922e-03 eta: 14:39:25 time: 1.4627 data_time: 0.2058 memory: 16131 loss: 2.6989 loss_prob: 1.6728 loss_thr: 0.7466 loss_db: 0.2795 2022/10/25 21:13:56 - mmengine - INFO - Epoch(train) [153][10/63] lr: 2.2922e-03 eta: 14:39:47 time: 1.5053 data_time: 0.2107 memory: 16131 loss: 2.7499 loss_prob: 1.7133 loss_thr: 0.7511 loss_db: 0.2855 2022/10/25 21:14:00 - mmengine - INFO - Epoch(train) [153][15/63] lr: 2.2922e-03 eta: 14:39:47 time: 0.7697 data_time: 0.0117 memory: 16131 loss: 2.6595 loss_prob: 1.6513 loss_thr: 0.7333 loss_db: 0.2749 2022/10/25 21:14:02 - mmengine - INFO - Epoch(train) [153][20/63] lr: 2.2922e-03 eta: 14:39:25 time: 0.5957 data_time: 0.0083 memory: 16131 loss: 2.7302 loss_prob: 1.6969 loss_thr: 0.7446 loss_db: 0.2887 2022/10/25 21:14:07 - mmengine - INFO - Epoch(train) [153][25/63] lr: 2.2922e-03 eta: 14:39:25 time: 0.7623 data_time: 0.0211 memory: 16131 loss: 2.7033 loss_prob: 1.6671 loss_thr: 0.7560 loss_db: 0.2802 2022/10/25 21:14:15 - mmengine - INFO - Epoch(train) [153][30/63] lr: 2.2922e-03 eta: 14:39:51 time: 1.2969 data_time: 0.0301 memory: 16131 loss: 2.6158 loss_prob: 1.6086 loss_thr: 0.7385 loss_db: 0.2687 2022/10/25 21:14:20 - mmengine - INFO - Epoch(train) [153][35/63] lr: 2.2922e-03 eta: 14:39:51 time: 1.3088 data_time: 0.0229 memory: 16131 loss: 2.6143 loss_prob: 1.6236 loss_thr: 0.7135 loss_db: 0.2772 2022/10/25 21:14:23 - mmengine - INFO - Epoch(train) [153][40/63] lr: 2.2922e-03 eta: 14:39:42 time: 0.7809 data_time: 0.0138 memory: 16131 loss: 2.6147 loss_prob: 1.6307 loss_thr: 0.7029 loss_db: 0.2810 2022/10/25 21:14:27 - mmengine - INFO - Epoch(train) [153][45/63] lr: 2.2922e-03 eta: 14:39:42 time: 0.6852 data_time: 0.0339 memory: 16131 loss: 2.5778 loss_prob: 1.6101 loss_thr: 0.7015 loss_db: 0.2662 2022/10/25 21:14:33 - mmengine - INFO - Epoch(train) [153][50/63] lr: 2.2922e-03 eta: 14:39:49 time: 1.0215 data_time: 0.0323 memory: 16131 loss: 2.6441 loss_prob: 1.6549 loss_thr: 0.7221 loss_db: 0.2672 2022/10/25 21:14:38 - mmengine - INFO - Epoch(train) [153][55/63] lr: 2.2922e-03 eta: 14:39:49 time: 1.0673 data_time: 0.0112 memory: 16131 loss: 2.6494 loss_prob: 1.6600 loss_thr: 0.7188 loss_db: 0.2707 2022/10/25 21:14:43 - mmengine - INFO - Epoch(train) [153][60/63] lr: 2.2922e-03 eta: 14:39:52 time: 0.9588 data_time: 0.0146 memory: 16131 loss: 2.7275 loss_prob: 1.7111 loss_thr: 0.7342 loss_db: 0.2823 2022/10/25 21:14:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:14:55 - mmengine - INFO - Epoch(train) [154][5/63] lr: 2.3072e-03 eta: 14:39:52 time: 1.4426 data_time: 0.2808 memory: 16131 loss: 2.5888 loss_prob: 1.5972 loss_thr: 0.7289 loss_db: 0.2626 2022/10/25 21:14:59 - mmengine - INFO - Epoch(train) [154][10/63] lr: 2.3072e-03 eta: 14:39:53 time: 1.2049 data_time: 0.2773 memory: 16131 loss: 2.5657 loss_prob: 1.5771 loss_thr: 0.7253 loss_db: 0.2634 2022/10/25 21:15:05 - mmengine - INFO - Epoch(train) [154][15/63] lr: 2.3072e-03 eta: 14:39:53 time: 0.9918 data_time: 0.0094 memory: 16131 loss: 2.7253 loss_prob: 1.6855 loss_thr: 0.7577 loss_db: 0.2821 2022/10/25 21:15:09 - mmengine - INFO - Epoch(train) [154][20/63] lr: 2.3072e-03 eta: 14:40:02 time: 1.0603 data_time: 0.0079 memory: 16131 loss: 2.6360 loss_prob: 1.6273 loss_thr: 0.7419 loss_db: 0.2668 2022/10/25 21:15:12 - mmengine - INFO - Epoch(train) [154][25/63] lr: 2.3072e-03 eta: 14:40:02 time: 0.6940 data_time: 0.0423 memory: 16131 loss: 2.5844 loss_prob: 1.5930 loss_thr: 0.7320 loss_db: 0.2593 2022/10/25 21:15:20 - mmengine - INFO - Epoch(train) [154][30/63] lr: 2.3072e-03 eta: 14:40:11 time: 1.0526 data_time: 0.0456 memory: 16131 loss: 2.5823 loss_prob: 1.5835 loss_thr: 0.7355 loss_db: 0.2633 2022/10/25 21:15:24 - mmengine - INFO - Epoch(train) [154][35/63] lr: 2.3072e-03 eta: 14:40:11 time: 1.1989 data_time: 0.0098 memory: 16131 loss: 2.5456 loss_prob: 1.5562 loss_thr: 0.7283 loss_db: 0.2611 2022/10/25 21:15:28 - mmengine - INFO - Epoch(train) [154][40/63] lr: 2.3072e-03 eta: 14:40:04 time: 0.8089 data_time: 0.0081 memory: 16131 loss: 2.6076 loss_prob: 1.6140 loss_thr: 0.7257 loss_db: 0.2680 2022/10/25 21:15:31 - mmengine - INFO - Epoch(train) [154][45/63] lr: 2.3072e-03 eta: 14:40:04 time: 0.6767 data_time: 0.0068 memory: 16131 loss: 2.8231 loss_prob: 1.7739 loss_thr: 0.7425 loss_db: 0.3067 2022/10/25 21:15:36 - mmengine - INFO - Epoch(train) [154][50/63] lr: 2.3072e-03 eta: 14:40:00 time: 0.8534 data_time: 0.0243 memory: 16131 loss: 2.8206 loss_prob: 1.7629 loss_thr: 0.7536 loss_db: 0.3042 2022/10/25 21:15:40 - mmengine - INFO - Epoch(train) [154][55/63] lr: 2.3072e-03 eta: 14:40:00 time: 0.9468 data_time: 0.0264 memory: 16131 loss: 2.5510 loss_prob: 1.5686 loss_thr: 0.7238 loss_db: 0.2586 2022/10/25 21:15:47 - mmengine - INFO - Epoch(train) [154][60/63] lr: 2.3072e-03 eta: 14:40:09 time: 1.0628 data_time: 0.0079 memory: 16131 loss: 2.4452 loss_prob: 1.4925 loss_thr: 0.7086 loss_db: 0.2441 2022/10/25 21:15:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:15:57 - mmengine - INFO - Epoch(train) [155][5/63] lr: 2.3223e-03 eta: 14:40:09 time: 1.3116 data_time: 0.2150 memory: 16131 loss: 2.5103 loss_prob: 1.5336 loss_thr: 0.7301 loss_db: 0.2466 2022/10/25 21:16:01 - mmengine - INFO - Epoch(train) [155][10/63] lr: 2.3223e-03 eta: 14:40:13 time: 1.2475 data_time: 0.2149 memory: 16131 loss: 2.3226 loss_prob: 1.4036 loss_thr: 0.6920 loss_db: 0.2270 2022/10/25 21:16:06 - mmengine - INFO - Epoch(train) [155][15/63] lr: 2.3223e-03 eta: 14:40:13 time: 0.8629 data_time: 0.0304 memory: 16131 loss: 2.4660 loss_prob: 1.5160 loss_thr: 0.7004 loss_db: 0.2496 2022/10/25 21:16:11 - mmengine - INFO - Epoch(train) [155][20/63] lr: 2.3223e-03 eta: 14:40:21 time: 1.0424 data_time: 0.0367 memory: 16131 loss: 2.8482 loss_prob: 1.7903 loss_thr: 0.7584 loss_db: 0.2995 2022/10/25 21:16:16 - mmengine - INFO - Epoch(train) [155][25/63] lr: 2.3223e-03 eta: 14:40:21 time: 1.0351 data_time: 0.0197 memory: 16131 loss: 2.8431 loss_prob: 1.7743 loss_thr: 0.7773 loss_db: 0.2916 2022/10/25 21:16:22 - mmengine - INFO - Epoch(train) [155][30/63] lr: 2.3223e-03 eta: 14:40:31 time: 1.0651 data_time: 0.0438 memory: 16131 loss: 2.5870 loss_prob: 1.5729 loss_thr: 0.7557 loss_db: 0.2584 2022/10/25 21:16:29 - mmengine - INFO - Epoch(train) [155][35/63] lr: 2.3223e-03 eta: 14:40:31 time: 1.3093 data_time: 0.0407 memory: 16131 loss: 2.5342 loss_prob: 1.5402 loss_thr: 0.7436 loss_db: 0.2504 2022/10/25 21:16:36 - mmengine - INFO - Epoch(train) [155][40/63] lr: 2.3223e-03 eta: 14:41:07 time: 1.4499 data_time: 0.0125 memory: 16131 loss: 2.4654 loss_prob: 1.5053 loss_thr: 0.7170 loss_db: 0.2431 2022/10/25 21:16:39 - mmengine - INFO - Epoch(train) [155][45/63] lr: 2.3223e-03 eta: 14:41:07 time: 0.9772 data_time: 0.0092 memory: 16131 loss: 2.5646 loss_prob: 1.5681 loss_thr: 0.7338 loss_db: 0.2627 2022/10/25 21:16:43 - mmengine - INFO - Epoch(train) [155][50/63] lr: 2.3223e-03 eta: 14:40:47 time: 0.6265 data_time: 0.0304 memory: 16131 loss: 2.6687 loss_prob: 1.6724 loss_thr: 0.7165 loss_db: 0.2798 2022/10/25 21:16:46 - mmengine - INFO - Epoch(train) [155][55/63] lr: 2.3223e-03 eta: 14:40:47 time: 0.6883 data_time: 0.0283 memory: 16131 loss: 2.7465 loss_prob: 1.7578 loss_thr: 0.6934 loss_db: 0.2953 2022/10/25 21:16:50 - mmengine - INFO - Epoch(train) [155][60/63] lr: 2.3223e-03 eta: 14:40:32 time: 0.7087 data_time: 0.0075 memory: 16131 loss: 2.7369 loss_prob: 1.7551 loss_thr: 0.6902 loss_db: 0.2916 2022/10/25 21:16:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:17:00 - mmengine - INFO - Epoch(train) [156][5/63] lr: 2.3373e-03 eta: 14:40:32 time: 1.1963 data_time: 0.2454 memory: 16131 loss: 2.6813 loss_prob: 1.6834 loss_thr: 0.7156 loss_db: 0.2823 2022/10/25 21:17:05 - mmengine - INFO - Epoch(train) [156][10/63] lr: 2.3373e-03 eta: 14:40:33 time: 1.2045 data_time: 0.2509 memory: 16131 loss: 2.7561 loss_prob: 1.7242 loss_thr: 0.7367 loss_db: 0.2951 2022/10/25 21:17:11 - mmengine - INFO - Epoch(train) [156][15/63] lr: 2.3373e-03 eta: 14:40:33 time: 1.0936 data_time: 0.0152 memory: 16131 loss: 2.8758 loss_prob: 1.7930 loss_thr: 0.7777 loss_db: 0.3051 2022/10/25 21:17:14 - mmengine - INFO - Epoch(train) [156][20/63] lr: 2.3373e-03 eta: 14:40:36 time: 0.9728 data_time: 0.0053 memory: 16131 loss: 2.5933 loss_prob: 1.5932 loss_thr: 0.7379 loss_db: 0.2622 2022/10/25 21:17:20 - mmengine - INFO - Epoch(train) [156][25/63] lr: 2.3373e-03 eta: 14:40:36 time: 0.8702 data_time: 0.0172 memory: 16131 loss: 2.7737 loss_prob: 1.7302 loss_thr: 0.7500 loss_db: 0.2934 2022/10/25 21:17:23 - mmengine - INFO - Epoch(train) [156][30/63] lr: 2.3373e-03 eta: 14:40:33 time: 0.8773 data_time: 0.0503 memory: 16131 loss: 2.9285 loss_prob: 1.8526 loss_thr: 0.7568 loss_db: 0.3191 2022/10/25 21:17:29 - mmengine - INFO - Epoch(train) [156][35/63] lr: 2.3373e-03 eta: 14:40:33 time: 0.9051 data_time: 0.0425 memory: 16131 loss: 2.7450 loss_prob: 1.7151 loss_thr: 0.7402 loss_db: 0.2898 2022/10/25 21:17:32 - mmengine - INFO - Epoch(train) [156][40/63] lr: 2.3373e-03 eta: 14:40:33 time: 0.9177 data_time: 0.0107 memory: 16131 loss: 2.7112 loss_prob: 1.6956 loss_thr: 0.7271 loss_db: 0.2885 2022/10/25 21:17:36 - mmengine - INFO - Epoch(train) [156][45/63] lr: 2.3373e-03 eta: 14:40:33 time: 0.6901 data_time: 0.0075 memory: 16131 loss: 2.4796 loss_prob: 1.5500 loss_thr: 0.6735 loss_db: 0.2562 2022/10/25 21:17:40 - mmengine - INFO - Epoch(train) [156][50/63] lr: 2.3373e-03 eta: 14:40:27 time: 0.8291 data_time: 0.0219 memory: 16131 loss: 2.3982 loss_prob: 1.4692 loss_thr: 0.6902 loss_db: 0.2389 2022/10/25 21:17:44 - mmengine - INFO - Epoch(train) [156][55/63] lr: 2.3373e-03 eta: 14:40:27 time: 0.7833 data_time: 0.0268 memory: 16131 loss: 2.4578 loss_prob: 1.4981 loss_thr: 0.7161 loss_db: 0.2436 2022/10/25 21:17:51 - mmengine - INFO - Epoch(train) [156][60/63] lr: 2.3373e-03 eta: 14:40:36 time: 1.0571 data_time: 0.0131 memory: 16131 loss: 2.4797 loss_prob: 1.5253 loss_thr: 0.7045 loss_db: 0.2499 2022/10/25 21:17:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:18:04 - mmengine - INFO - Epoch(train) [157][5/63] lr: 2.3524e-03 eta: 14:40:36 time: 1.5320 data_time: 0.2092 memory: 16131 loss: 2.5288 loss_prob: 1.5489 loss_thr: 0.7232 loss_db: 0.2566 2022/10/25 21:18:08 - mmengine - INFO - Epoch(train) [157][10/63] lr: 2.3524e-03 eta: 14:40:45 time: 1.3407 data_time: 0.2120 memory: 16131 loss: 2.6109 loss_prob: 1.6118 loss_thr: 0.7333 loss_db: 0.2658 2022/10/25 21:18:11 - mmengine - INFO - Epoch(train) [157][15/63] lr: 2.3524e-03 eta: 14:40:45 time: 0.7186 data_time: 0.0179 memory: 16131 loss: 2.6333 loss_prob: 1.6299 loss_thr: 0.7370 loss_db: 0.2664 2022/10/25 21:18:14 - mmengine - INFO - Epoch(train) [157][20/63] lr: 2.3524e-03 eta: 14:40:23 time: 0.5998 data_time: 0.0151 memory: 16131 loss: 2.5161 loss_prob: 1.5251 loss_thr: 0.7438 loss_db: 0.2473 2022/10/25 21:18:19 - mmengine - INFO - Epoch(train) [157][25/63] lr: 2.3524e-03 eta: 14:40:23 time: 0.8231 data_time: 0.0123 memory: 16131 loss: 2.5594 loss_prob: 1.5710 loss_thr: 0.7255 loss_db: 0.2630 2022/10/25 21:18:23 - mmengine - INFO - Epoch(train) [157][30/63] lr: 2.3524e-03 eta: 14:40:23 time: 0.9221 data_time: 0.0281 memory: 16131 loss: 2.4396 loss_prob: 1.5122 loss_thr: 0.6750 loss_db: 0.2523 2022/10/25 21:18:27 - mmengine - INFO - Epoch(train) [157][35/63] lr: 2.3524e-03 eta: 14:40:23 time: 0.7606 data_time: 0.0216 memory: 16131 loss: 2.4792 loss_prob: 1.5008 loss_thr: 0.7313 loss_db: 0.2471 2022/10/25 21:18:32 - mmengine - INFO - Epoch(train) [157][40/63] lr: 2.3524e-03 eta: 14:40:23 time: 0.9146 data_time: 0.0165 memory: 16131 loss: 2.6469 loss_prob: 1.6103 loss_thr: 0.7707 loss_db: 0.2659 2022/10/25 21:18:38 - mmengine - INFO - Epoch(train) [157][45/63] lr: 2.3524e-03 eta: 14:40:23 time: 1.1282 data_time: 0.0156 memory: 16131 loss: 2.7448 loss_prob: 1.6990 loss_thr: 0.7619 loss_db: 0.2839 2022/10/25 21:18:42 - mmengine - INFO - Epoch(train) [157][50/63] lr: 2.3524e-03 eta: 14:40:25 time: 0.9646 data_time: 0.0140 memory: 16131 loss: 2.7658 loss_prob: 1.7134 loss_thr: 0.7615 loss_db: 0.2909 2022/10/25 21:18:47 - mmengine - INFO - Epoch(train) [157][55/63] lr: 2.3524e-03 eta: 14:40:25 time: 0.8627 data_time: 0.0214 memory: 16131 loss: 2.5248 loss_prob: 1.5509 loss_thr: 0.7160 loss_db: 0.2580 2022/10/25 21:18:54 - mmengine - INFO - Epoch(train) [157][60/63] lr: 2.3524e-03 eta: 14:40:40 time: 1.1514 data_time: 0.0158 memory: 16131 loss: 2.3136 loss_prob: 1.3938 loss_thr: 0.6927 loss_db: 0.2271 2022/10/25 21:18:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:19:01 - mmengine - INFO - Epoch(train) [158][5/63] lr: 2.3675e-03 eta: 14:40:40 time: 0.9948 data_time: 0.2259 memory: 16131 loss: 2.5081 loss_prob: 1.5293 loss_thr: 0.7275 loss_db: 0.2513 2022/10/25 21:19:06 - mmengine - INFO - Epoch(train) [158][10/63] lr: 2.3675e-03 eta: 14:40:32 time: 1.0846 data_time: 0.2257 memory: 16131 loss: 2.5610 loss_prob: 1.5758 loss_thr: 0.7262 loss_db: 0.2591 2022/10/25 21:19:12 - mmengine - INFO - Epoch(train) [158][15/63] lr: 2.3675e-03 eta: 14:40:32 time: 1.0489 data_time: 0.0063 memory: 16131 loss: 2.6070 loss_prob: 1.6234 loss_thr: 0.7119 loss_db: 0.2717 2022/10/25 21:19:16 - mmengine - INFO - Epoch(train) [158][20/63] lr: 2.3675e-03 eta: 14:40:38 time: 1.0081 data_time: 0.0061 memory: 16131 loss: 2.5962 loss_prob: 1.6116 loss_thr: 0.7164 loss_db: 0.2682 2022/10/25 21:19:19 - mmengine - INFO - Epoch(train) [158][25/63] lr: 2.3675e-03 eta: 14:40:38 time: 0.7774 data_time: 0.0331 memory: 16131 loss: 2.4513 loss_prob: 1.5123 loss_thr: 0.6961 loss_db: 0.2429 2022/10/25 21:19:23 - mmengine - INFO - Epoch(train) [158][30/63] lr: 2.3675e-03 eta: 14:40:24 time: 0.7087 data_time: 0.0421 memory: 16131 loss: 2.4800 loss_prob: 1.5179 loss_thr: 0.7173 loss_db: 0.2448 2022/10/25 21:19:27 - mmengine - INFO - Epoch(train) [158][35/63] lr: 2.3675e-03 eta: 14:40:24 time: 0.7643 data_time: 0.0161 memory: 16131 loss: 2.5987 loss_prob: 1.5990 loss_thr: 0.7291 loss_db: 0.2705 2022/10/25 21:19:31 - mmengine - INFO - Epoch(train) [158][40/63] lr: 2.3675e-03 eta: 14:40:16 time: 0.8093 data_time: 0.0069 memory: 16131 loss: 2.6734 loss_prob: 1.6627 loss_thr: 0.7285 loss_db: 0.2821 2022/10/25 21:19:35 - mmengine - INFO - Epoch(train) [158][45/63] lr: 2.3675e-03 eta: 14:40:16 time: 0.7959 data_time: 0.0056 memory: 16131 loss: 2.7308 loss_prob: 1.6816 loss_thr: 0.7679 loss_db: 0.2813 2022/10/25 21:19:39 - mmengine - INFO - Epoch(train) [158][50/63] lr: 2.3675e-03 eta: 14:40:05 time: 0.7551 data_time: 0.0182 memory: 16131 loss: 2.7071 loss_prob: 1.6608 loss_thr: 0.7698 loss_db: 0.2765 2022/10/25 21:19:44 - mmengine - INFO - Epoch(train) [158][55/63] lr: 2.3675e-03 eta: 14:40:05 time: 0.9519 data_time: 0.0239 memory: 16131 loss: 2.5765 loss_prob: 1.5754 loss_thr: 0.7382 loss_db: 0.2629 2022/10/25 21:19:50 - mmengine - INFO - Epoch(train) [158][60/63] lr: 2.3675e-03 eta: 14:40:19 time: 1.1442 data_time: 0.0114 memory: 16131 loss: 2.5365 loss_prob: 1.5438 loss_thr: 0.7368 loss_db: 0.2560 2022/10/25 21:19:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:20:00 - mmengine - INFO - Epoch(train) [159][5/63] lr: 2.3825e-03 eta: 14:40:19 time: 1.1797 data_time: 0.1761 memory: 16131 loss: 2.3481 loss_prob: 1.4310 loss_thr: 0.6850 loss_db: 0.2321 2022/10/25 21:20:08 - mmengine - INFO - Epoch(train) [159][10/63] lr: 2.3825e-03 eta: 14:40:37 time: 1.4791 data_time: 0.1919 memory: 16131 loss: 2.4510 loss_prob: 1.5057 loss_thr: 0.6933 loss_db: 0.2520 2022/10/25 21:20:14 - mmengine - INFO - Epoch(train) [159][15/63] lr: 2.3825e-03 eta: 14:40:37 time: 1.3497 data_time: 0.0228 memory: 16131 loss: 2.6010 loss_prob: 1.6098 loss_thr: 0.7207 loss_db: 0.2705 2022/10/25 21:20:17 - mmengine - INFO - Epoch(train) [159][20/63] lr: 2.3825e-03 eta: 14:40:36 time: 0.9069 data_time: 0.0070 memory: 16131 loss: 2.4583 loss_prob: 1.5109 loss_thr: 0.7002 loss_db: 0.2472 2022/10/25 21:20:24 - mmengine - INFO - Epoch(train) [159][25/63] lr: 2.3825e-03 eta: 14:40:36 time: 1.0528 data_time: 0.0168 memory: 16131 loss: 2.6559 loss_prob: 1.6580 loss_thr: 0.7243 loss_db: 0.2736 2022/10/25 21:20:29 - mmengine - INFO - Epoch(train) [159][30/63] lr: 2.3825e-03 eta: 14:40:53 time: 1.1839 data_time: 0.0364 memory: 16131 loss: 2.8384 loss_prob: 1.7931 loss_thr: 0.7420 loss_db: 0.3033 2022/10/25 21:20:33 - mmengine - INFO - Epoch(train) [159][35/63] lr: 2.3825e-03 eta: 14:40:53 time: 0.8318 data_time: 0.0243 memory: 16131 loss: 2.6896 loss_prob: 1.6679 loss_thr: 0.7411 loss_db: 0.2806 2022/10/25 21:20:36 - mmengine - INFO - Epoch(train) [159][40/63] lr: 2.3825e-03 eta: 14:40:43 time: 0.7852 data_time: 0.0064 memory: 16131 loss: 2.7943 loss_prob: 1.7589 loss_thr: 0.7402 loss_db: 0.2953 2022/10/25 21:20:44 - mmengine - INFO - Epoch(train) [159][45/63] lr: 2.3825e-03 eta: 14:40:43 time: 1.1071 data_time: 0.0076 memory: 16131 loss: 2.8984 loss_prob: 1.8492 loss_thr: 0.7325 loss_db: 0.3168 2022/10/25 21:20:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:20:47 - mmengine - INFO - Epoch(train) [159][50/63] lr: 2.3825e-03 eta: 14:40:50 time: 1.0380 data_time: 0.0134 memory: 16131 loss: 2.8261 loss_prob: 1.7813 loss_thr: 0.7372 loss_db: 0.3075 2022/10/25 21:20:50 - mmengine - INFO - Epoch(train) [159][55/63] lr: 2.3825e-03 eta: 14:40:50 time: 0.6765 data_time: 0.0224 memory: 16131 loss: 2.6850 loss_prob: 1.6562 loss_thr: 0.7451 loss_db: 0.2837 2022/10/25 21:20:54 - mmengine - INFO - Epoch(train) [159][60/63] lr: 2.3825e-03 eta: 14:40:40 time: 0.7686 data_time: 0.0146 memory: 16131 loss: 2.7290 loss_prob: 1.6891 loss_thr: 0.7525 loss_db: 0.2874 2022/10/25 21:20:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:21:03 - mmengine - INFO - Epoch(train) [160][5/63] lr: 2.3976e-03 eta: 14:40:40 time: 1.1229 data_time: 0.2694 memory: 16131 loss: 2.7441 loss_prob: 1.7095 loss_thr: 0.7404 loss_db: 0.2941 2022/10/25 21:21:06 - mmengine - INFO - Epoch(train) [160][10/63] lr: 2.3976e-03 eta: 14:40:21 time: 0.9220 data_time: 0.2651 memory: 16131 loss: 2.5378 loss_prob: 1.5760 loss_thr: 0.6985 loss_db: 0.2633 2022/10/25 21:21:11 - mmengine - INFO - Epoch(train) [160][15/63] lr: 2.3976e-03 eta: 14:40:21 time: 0.7751 data_time: 0.0085 memory: 16131 loss: 2.3659 loss_prob: 1.4552 loss_thr: 0.6753 loss_db: 0.2353 2022/10/25 21:21:18 - mmengine - INFO - Epoch(train) [160][20/63] lr: 2.3976e-03 eta: 14:40:37 time: 1.1661 data_time: 0.0090 memory: 16131 loss: 2.3752 loss_prob: 1.4558 loss_thr: 0.6840 loss_db: 0.2355 2022/10/25 21:21:23 - mmengine - INFO - Epoch(train) [160][25/63] lr: 2.3976e-03 eta: 14:40:37 time: 1.1421 data_time: 0.0436 memory: 16131 loss: 2.4819 loss_prob: 1.5229 loss_thr: 0.7071 loss_db: 0.2519 2022/10/25 21:21:29 - mmengine - INFO - Epoch(train) [160][30/63] lr: 2.3976e-03 eta: 14:40:46 time: 1.0723 data_time: 0.0455 memory: 16131 loss: 2.5986 loss_prob: 1.5820 loss_thr: 0.7528 loss_db: 0.2637 2022/10/25 21:21:32 - mmengine - INFO - Epoch(train) [160][35/63] lr: 2.3976e-03 eta: 14:40:46 time: 0.9060 data_time: 0.0077 memory: 16131 loss: 2.5931 loss_prob: 1.5808 loss_thr: 0.7518 loss_db: 0.2605 2022/10/25 21:21:36 - mmengine - INFO - Epoch(train) [160][40/63] lr: 2.3976e-03 eta: 14:40:31 time: 0.7024 data_time: 0.0080 memory: 16131 loss: 2.5712 loss_prob: 1.5830 loss_thr: 0.7299 loss_db: 0.2583 2022/10/25 21:21:40 - mmengine - INFO - Epoch(train) [160][45/63] lr: 2.3976e-03 eta: 14:40:31 time: 0.8710 data_time: 0.0073 memory: 16131 loss: 2.4445 loss_prob: 1.4797 loss_thr: 0.7237 loss_db: 0.2411 2022/10/25 21:21:43 - mmengine - INFO - Epoch(train) [160][50/63] lr: 2.3976e-03 eta: 14:40:20 time: 0.7628 data_time: 0.0264 memory: 16131 loss: 2.5354 loss_prob: 1.5487 loss_thr: 0.7289 loss_db: 0.2578 2022/10/25 21:21:49 - mmengine - INFO - Epoch(train) [160][55/63] lr: 2.3976e-03 eta: 14:40:20 time: 0.8273 data_time: 0.0281 memory: 16131 loss: 2.6935 loss_prob: 1.6800 loss_thr: 0.7328 loss_db: 0.2807 2022/10/25 21:21:51 - mmengine - INFO - Epoch(train) [160][60/63] lr: 2.3976e-03 eta: 14:40:12 time: 0.7999 data_time: 0.0065 memory: 16131 loss: 2.7833 loss_prob: 1.7649 loss_thr: 0.7244 loss_db: 0.2941 2022/10/25 21:21:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:21:53 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/10/25 21:22:00 - mmengine - INFO - Epoch(val) [160][5/32] eta: 14:40:12 time: 0.5818 data_time: 0.0652 memory: 16131 2022/10/25 21:22:03 - mmengine - INFO - Epoch(val) [160][10/32] eta: 0:00:14 time: 0.6643 data_time: 0.0886 memory: 15724 2022/10/25 21:22:06 - mmengine - INFO - Epoch(val) [160][15/32] eta: 0:00:14 time: 0.6079 data_time: 0.0487 memory: 15724 2022/10/25 21:22:10 - mmengine - INFO - Epoch(val) [160][20/32] eta: 0:00:07 time: 0.6368 data_time: 0.0833 memory: 15724 2022/10/25 21:22:13 - mmengine - INFO - Epoch(val) [160][25/32] eta: 0:00:07 time: 0.6493 data_time: 0.0746 memory: 15724 2022/10/25 21:22:15 - mmengine - INFO - Epoch(val) [160][30/32] eta: 0:00:01 time: 0.5651 data_time: 0.0219 memory: 15724 2022/10/25 21:22:16 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7251, precision: 0.5572, hmean: 0.6301 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7246, precision: 0.7232, hmean: 0.7239 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7121, precision: 0.8140, hmean: 0.7596 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.6505, precision: 0.8894, hmean: 0.7514 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.3943, precision: 0.9557, hmean: 0.5583 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0043, precision: 1.0000, hmean: 0.0086 2022/10/25 21:22:16 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 21:22:16 - mmengine - INFO - Epoch(val) [160][32/32] icdar/precision: 0.8140 icdar/recall: 0.7121 icdar/hmean: 0.7596 2022/10/25 21:22:23 - mmengine - INFO - Epoch(train) [161][5/63] lr: 2.4126e-03 eta: 0:00:01 time: 0.9831 data_time: 0.2372 memory: 16131 loss: 2.9073 loss_prob: 1.8416 loss_thr: 0.7629 loss_db: 0.3028 2022/10/25 21:22:32 - mmengine - INFO - Epoch(train) [161][10/63] lr: 2.4126e-03 eta: 14:40:38 time: 1.6076 data_time: 0.2369 memory: 16131 loss: 2.6257 loss_prob: 1.6348 loss_thr: 0.7242 loss_db: 0.2668 2022/10/25 21:22:38 - mmengine - INFO - Epoch(train) [161][15/63] lr: 2.4126e-03 eta: 14:40:38 time: 1.4407 data_time: 0.0065 memory: 16131 loss: 2.5309 loss_prob: 1.5548 loss_thr: 0.7218 loss_db: 0.2543 2022/10/25 21:22:42 - mmengine - INFO - Epoch(train) [161][20/63] lr: 2.4126e-03 eta: 14:40:39 time: 0.9466 data_time: 0.0105 memory: 16131 loss: 2.5281 loss_prob: 1.5479 loss_thr: 0.7282 loss_db: 0.2521 2022/10/25 21:22:47 - mmengine - INFO - Epoch(train) [161][25/63] lr: 2.4126e-03 eta: 14:40:39 time: 0.9342 data_time: 0.0256 memory: 16131 loss: 2.5088 loss_prob: 1.5413 loss_thr: 0.7136 loss_db: 0.2539 2022/10/25 21:22:52 - mmengine - INFO - Epoch(train) [161][30/63] lr: 2.4126e-03 eta: 14:40:45 time: 1.0236 data_time: 0.0464 memory: 16131 loss: 2.7366 loss_prob: 1.7022 loss_thr: 0.7429 loss_db: 0.2916 2022/10/25 21:22:54 - mmengine - INFO - Epoch(train) [161][35/63] lr: 2.4126e-03 eta: 14:40:45 time: 0.7304 data_time: 0.0302 memory: 16131 loss: 2.7441 loss_prob: 1.7138 loss_thr: 0.7356 loss_db: 0.2948 2022/10/25 21:23:00 - mmengine - INFO - Epoch(train) [161][40/63] lr: 2.4126e-03 eta: 14:40:36 time: 0.7906 data_time: 0.0055 memory: 16131 loss: 2.5084 loss_prob: 1.5425 loss_thr: 0.7089 loss_db: 0.2569 2022/10/25 21:23:03 - mmengine - INFO - Epoch(train) [161][45/63] lr: 2.4126e-03 eta: 14:40:36 time: 0.8532 data_time: 0.0081 memory: 16131 loss: 2.5778 loss_prob: 1.5844 loss_thr: 0.7267 loss_db: 0.2667 2022/10/25 21:23:09 - mmengine - INFO - Epoch(train) [161][50/63] lr: 2.4126e-03 eta: 14:40:34 time: 0.9056 data_time: 0.0247 memory: 16131 loss: 2.5048 loss_prob: 1.5379 loss_thr: 0.7130 loss_db: 0.2539 2022/10/25 21:23:11 - mmengine - INFO - Epoch(train) [161][55/63] lr: 2.4126e-03 eta: 14:40:34 time: 0.8505 data_time: 0.0264 memory: 16131 loss: 2.4721 loss_prob: 1.5141 loss_thr: 0.7099 loss_db: 0.2480 2022/10/25 21:23:16 - mmengine - INFO - Epoch(train) [161][60/63] lr: 2.4126e-03 eta: 14:40:20 time: 0.7178 data_time: 0.0114 memory: 16131 loss: 2.6281 loss_prob: 1.6296 loss_thr: 0.7266 loss_db: 0.2718 2022/10/25 21:23:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:23:25 - mmengine - INFO - Epoch(train) [162][5/63] lr: 2.4277e-03 eta: 14:40:20 time: 1.0244 data_time: 0.2102 memory: 16131 loss: 2.5007 loss_prob: 1.5349 loss_thr: 0.7126 loss_db: 0.2531 2022/10/25 21:23:29 - mmengine - INFO - Epoch(train) [162][10/63] lr: 2.4277e-03 eta: 14:40:19 time: 1.1894 data_time: 0.2071 memory: 16131 loss: 2.5955 loss_prob: 1.5909 loss_thr: 0.7423 loss_db: 0.2624 2022/10/25 21:23:32 - mmengine - INFO - Epoch(train) [162][15/63] lr: 2.4277e-03 eta: 14:40:19 time: 0.7149 data_time: 0.0104 memory: 16131 loss: 2.6912 loss_prob: 1.6568 loss_thr: 0.7579 loss_db: 0.2766 2022/10/25 21:23:36 - mmengine - INFO - Epoch(train) [162][20/63] lr: 2.4277e-03 eta: 14:40:02 time: 0.6705 data_time: 0.0076 memory: 16131 loss: 2.8127 loss_prob: 1.7512 loss_thr: 0.7644 loss_db: 0.2971 2022/10/25 21:23:40 - mmengine - INFO - Epoch(train) [162][25/63] lr: 2.4277e-03 eta: 14:40:02 time: 0.7811 data_time: 0.0246 memory: 16131 loss: 2.6216 loss_prob: 1.6134 loss_thr: 0.7370 loss_db: 0.2712 2022/10/25 21:23:45 - mmengine - INFO - Epoch(train) [162][30/63] lr: 2.4277e-03 eta: 14:40:02 time: 0.9410 data_time: 0.0357 memory: 16131 loss: 2.4669 loss_prob: 1.5001 loss_thr: 0.7171 loss_db: 0.2498 2022/10/25 21:23:51 - mmengine - INFO - Epoch(train) [162][35/63] lr: 2.4277e-03 eta: 14:40:02 time: 1.0486 data_time: 0.0194 memory: 16131 loss: 2.5453 loss_prob: 1.5714 loss_thr: 0.7115 loss_db: 0.2624 2022/10/25 21:23:55 - mmengine - INFO - Epoch(train) [162][40/63] lr: 2.4277e-03 eta: 14:40:07 time: 1.0026 data_time: 0.0123 memory: 16131 loss: 2.4547 loss_prob: 1.5064 loss_thr: 0.7021 loss_db: 0.2462 2022/10/25 21:24:03 - mmengine - INFO - Epoch(train) [162][45/63] lr: 2.4277e-03 eta: 14:40:07 time: 1.2185 data_time: 0.0109 memory: 16131 loss: 2.3649 loss_prob: 1.4217 loss_thr: 0.7134 loss_db: 0.2297 2022/10/25 21:24:08 - mmengine - INFO - Epoch(train) [162][50/63] lr: 2.4277e-03 eta: 14:40:30 time: 1.2939 data_time: 0.0169 memory: 16131 loss: 2.3324 loss_prob: 1.3924 loss_thr: 0.7143 loss_db: 0.2258 2022/10/25 21:24:13 - mmengine - INFO - Epoch(train) [162][55/63] lr: 2.4277e-03 eta: 14:40:30 time: 1.0483 data_time: 0.0200 memory: 16131 loss: 2.2775 loss_prob: 1.3679 loss_thr: 0.6873 loss_db: 0.2224 2022/10/25 21:24:17 - mmengine - INFO - Epoch(train) [162][60/63] lr: 2.4277e-03 eta: 14:40:23 time: 0.8270 data_time: 0.0166 memory: 16131 loss: 2.3364 loss_prob: 1.4159 loss_thr: 0.6877 loss_db: 0.2328 2022/10/25 21:24:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:24:27 - mmengine - INFO - Epoch(train) [163][5/63] lr: 2.4428e-03 eta: 14:40:23 time: 1.1245 data_time: 0.3230 memory: 16131 loss: 2.3983 loss_prob: 1.4530 loss_thr: 0.7065 loss_db: 0.2388 2022/10/25 21:24:32 - mmengine - INFO - Epoch(train) [163][10/63] lr: 2.4428e-03 eta: 14:40:36 time: 1.4096 data_time: 0.3304 memory: 16131 loss: 2.4739 loss_prob: 1.5183 loss_thr: 0.7038 loss_db: 0.2518 2022/10/25 21:24:36 - mmengine - INFO - Epoch(train) [163][15/63] lr: 2.4428e-03 eta: 14:40:36 time: 0.9714 data_time: 0.0162 memory: 16131 loss: 2.5078 loss_prob: 1.5374 loss_thr: 0.7116 loss_db: 0.2588 2022/10/25 21:24:41 - mmengine - INFO - Epoch(train) [163][20/63] lr: 2.4428e-03 eta: 14:40:30 time: 0.8470 data_time: 0.0123 memory: 16131 loss: 2.4979 loss_prob: 1.5277 loss_thr: 0.7171 loss_db: 0.2531 2022/10/25 21:24:46 - mmengine - INFO - Epoch(train) [163][25/63] lr: 2.4428e-03 eta: 14:40:30 time: 0.9504 data_time: 0.0326 memory: 16131 loss: 2.5461 loss_prob: 1.5673 loss_thr: 0.7187 loss_db: 0.2601 2022/10/25 21:24:49 - mmengine - INFO - Epoch(train) [163][30/63] lr: 2.4428e-03 eta: 14:40:24 time: 0.8367 data_time: 0.0373 memory: 16131 loss: 2.4100 loss_prob: 1.4733 loss_thr: 0.6918 loss_db: 0.2449 2022/10/25 21:24:52 - mmengine - INFO - Epoch(train) [163][35/63] lr: 2.4428e-03 eta: 14:40:24 time: 0.5954 data_time: 0.0152 memory: 16131 loss: 2.2766 loss_prob: 1.3675 loss_thr: 0.6861 loss_db: 0.2230 2022/10/25 21:24:54 - mmengine - INFO - Epoch(train) [163][40/63] lr: 2.4428e-03 eta: 14:39:57 time: 0.5132 data_time: 0.0057 memory: 16131 loss: 2.5782 loss_prob: 1.5706 loss_thr: 0.7464 loss_db: 0.2612 2022/10/25 21:24:57 - mmengine - INFO - Epoch(train) [163][45/63] lr: 2.4428e-03 eta: 14:39:57 time: 0.5106 data_time: 0.0060 memory: 16131 loss: 2.6455 loss_prob: 1.6277 loss_thr: 0.7440 loss_db: 0.2739 2022/10/25 21:25:01 - mmengine - INFO - Epoch(train) [163][50/63] lr: 2.4428e-03 eta: 14:39:36 time: 0.6137 data_time: 0.0216 memory: 16131 loss: 2.4283 loss_prob: 1.4809 loss_thr: 0.7012 loss_db: 0.2462 2022/10/25 21:25:03 - mmengine - INFO - Epoch(train) [163][55/63] lr: 2.4428e-03 eta: 14:39:36 time: 0.6256 data_time: 0.0235 memory: 16131 loss: 2.4423 loss_prob: 1.4806 loss_thr: 0.7081 loss_db: 0.2536 2022/10/25 21:25:06 - mmengine - INFO - Epoch(train) [163][60/63] lr: 2.4428e-03 eta: 14:39:13 time: 0.5608 data_time: 0.0082 memory: 16131 loss: 2.5465 loss_prob: 1.5587 loss_thr: 0.7178 loss_db: 0.2699 2022/10/25 21:25:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:25:15 - mmengine - INFO - Epoch(train) [164][5/63] lr: 2.4578e-03 eta: 14:39:13 time: 1.0701 data_time: 0.2135 memory: 16131 loss: 2.6658 loss_prob: 1.6493 loss_thr: 0.7386 loss_db: 0.2780 2022/10/25 21:25:19 - mmengine - INFO - Epoch(train) [164][10/63] lr: 2.4578e-03 eta: 14:39:10 time: 1.1678 data_time: 0.2157 memory: 16131 loss: 2.5406 loss_prob: 1.5698 loss_thr: 0.7114 loss_db: 0.2594 2022/10/25 21:25:25 - mmengine - INFO - Epoch(train) [164][15/63] lr: 2.4578e-03 eta: 14:39:10 time: 0.9073 data_time: 0.0099 memory: 16131 loss: 2.4090 loss_prob: 1.4765 loss_thr: 0.6922 loss_db: 0.2403 2022/10/25 21:25:29 - mmengine - INFO - Epoch(train) [164][20/63] lr: 2.4578e-03 eta: 14:39:13 time: 0.9912 data_time: 0.0103 memory: 16131 loss: 2.5340 loss_prob: 1.5607 loss_thr: 0.7140 loss_db: 0.2593 2022/10/25 21:25:33 - mmengine - INFO - Epoch(train) [164][25/63] lr: 2.4578e-03 eta: 14:39:13 time: 0.8497 data_time: 0.0246 memory: 16131 loss: 2.4220 loss_prob: 1.4752 loss_thr: 0.7040 loss_db: 0.2428 2022/10/25 21:25:37 - mmengine - INFO - Epoch(train) [164][30/63] lr: 2.4578e-03 eta: 14:39:06 time: 0.8218 data_time: 0.0384 memory: 16131 loss: 2.6175 loss_prob: 1.6304 loss_thr: 0.7168 loss_db: 0.2703 2022/10/25 21:25:41 - mmengine - INFO - Epoch(train) [164][35/63] lr: 2.4578e-03 eta: 14:39:06 time: 0.7756 data_time: 0.0228 memory: 16131 loss: 2.8691 loss_prob: 1.8287 loss_thr: 0.7295 loss_db: 0.3109 2022/10/25 21:25:46 - mmengine - INFO - Epoch(train) [164][40/63] lr: 2.4578e-03 eta: 14:38:59 time: 0.8262 data_time: 0.0068 memory: 16131 loss: 2.8400 loss_prob: 1.8175 loss_thr: 0.7104 loss_db: 0.3121 2022/10/25 21:25:50 - mmengine - INFO - Epoch(train) [164][45/63] lr: 2.4578e-03 eta: 14:38:59 time: 0.9536 data_time: 0.0071 memory: 16131 loss: 2.8108 loss_prob: 1.8056 loss_thr: 0.7015 loss_db: 0.3037 2022/10/25 21:25:53 - mmengine - INFO - Epoch(train) [164][50/63] lr: 2.4578e-03 eta: 14:38:50 time: 0.7890 data_time: 0.0125 memory: 16131 loss: 2.6629 loss_prob: 1.6743 loss_thr: 0.7102 loss_db: 0.2784 2022/10/25 21:25:56 - mmengine - INFO - Epoch(train) [164][55/63] lr: 2.4578e-03 eta: 14:38:50 time: 0.6116 data_time: 0.0262 memory: 16131 loss: 2.5599 loss_prob: 1.5733 loss_thr: 0.7216 loss_db: 0.2651 2022/10/25 21:25:59 - mmengine - INFO - Epoch(train) [164][60/63] lr: 2.4578e-03 eta: 14:38:27 time: 0.5684 data_time: 0.0203 memory: 16131 loss: 2.4319 loss_prob: 1.4850 loss_thr: 0.7043 loss_db: 0.2426 2022/10/25 21:26:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:26:10 - mmengine - INFO - Epoch(train) [165][5/63] lr: 2.4729e-03 eta: 14:38:27 time: 1.1822 data_time: 0.1977 memory: 16131 loss: 2.2851 loss_prob: 1.3684 loss_thr: 0.6987 loss_db: 0.2181 2022/10/25 21:26:15 - mmengine - INFO - Epoch(train) [165][10/63] lr: 2.4729e-03 eta: 14:38:32 time: 1.3080 data_time: 0.2098 memory: 16131 loss: 2.4604 loss_prob: 1.5079 loss_thr: 0.7054 loss_db: 0.2471 2022/10/25 21:26:20 - mmengine - INFO - Epoch(train) [165][15/63] lr: 2.4729e-03 eta: 14:38:32 time: 1.0209 data_time: 0.0266 memory: 16131 loss: 2.5998 loss_prob: 1.6176 loss_thr: 0.7098 loss_db: 0.2724 2022/10/25 21:26:27 - mmengine - INFO - Epoch(train) [165][20/63] lr: 2.4729e-03 eta: 14:38:51 time: 1.2294 data_time: 0.0138 memory: 16131 loss: 2.5355 loss_prob: 1.5388 loss_thr: 0.7386 loss_db: 0.2581 2022/10/25 21:26:34 - mmengine - INFO - Epoch(train) [165][25/63] lr: 2.4729e-03 eta: 14:38:51 time: 1.3545 data_time: 0.0127 memory: 16131 loss: 2.3721 loss_prob: 1.4219 loss_thr: 0.7192 loss_db: 0.2310 2022/10/25 21:26:40 - mmengine - INFO - Epoch(train) [165][30/63] lr: 2.4729e-03 eta: 14:39:10 time: 1.2428 data_time: 0.0385 memory: 16131 loss: 2.4742 loss_prob: 1.5199 loss_thr: 0.7048 loss_db: 0.2495 2022/10/25 21:26:43 - mmengine - INFO - Epoch(train) [165][35/63] lr: 2.4729e-03 eta: 14:39:10 time: 0.9184 data_time: 0.0319 memory: 16131 loss: 2.6024 loss_prob: 1.6119 loss_thr: 0.7208 loss_db: 0.2698 2022/10/25 21:26:47 - mmengine - INFO - Epoch(train) [165][40/63] lr: 2.4729e-03 eta: 14:38:56 time: 0.7179 data_time: 0.0078 memory: 16131 loss: 2.6509 loss_prob: 1.6429 loss_thr: 0.7313 loss_db: 0.2767 2022/10/25 21:26:50 - mmengine - INFO - Epoch(train) [165][45/63] lr: 2.4729e-03 eta: 14:38:56 time: 0.7052 data_time: 0.0091 memory: 16131 loss: 2.6192 loss_prob: 1.6105 loss_thr: 0.7376 loss_db: 0.2711 2022/10/25 21:26:57 - mmengine - INFO - Epoch(train) [165][50/63] lr: 2.4729e-03 eta: 14:39:01 time: 1.0103 data_time: 0.0233 memory: 16131 loss: 2.5400 loss_prob: 1.5642 loss_thr: 0.7210 loss_db: 0.2548 2022/10/25 21:27:00 - mmengine - INFO - Epoch(train) [165][55/63] lr: 2.4729e-03 eta: 14:39:01 time: 0.9964 data_time: 0.0251 memory: 16131 loss: 2.6336 loss_prob: 1.6395 loss_thr: 0.7214 loss_db: 0.2727 2022/10/25 21:27:03 - mmengine - INFO - Epoch(train) [165][60/63] lr: 2.4729e-03 eta: 14:38:40 time: 0.6088 data_time: 0.0108 memory: 16131 loss: 2.8763 loss_prob: 1.8225 loss_thr: 0.7394 loss_db: 0.3144 2022/10/25 21:27:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:27:12 - mmengine - INFO - Epoch(train) [166][5/63] lr: 2.4879e-03 eta: 14:38:40 time: 1.0105 data_time: 0.1897 memory: 16131 loss: 2.7015 loss_prob: 1.6945 loss_thr: 0.7193 loss_db: 0.2877 2022/10/25 21:27:17 - mmengine - INFO - Epoch(train) [166][10/63] lr: 2.4879e-03 eta: 14:38:41 time: 1.2294 data_time: 0.1900 memory: 16131 loss: 2.5721 loss_prob: 1.5896 loss_thr: 0.7162 loss_db: 0.2663 2022/10/25 21:27:20 - mmengine - INFO - Epoch(train) [166][15/63] lr: 2.4879e-03 eta: 14:38:41 time: 0.7919 data_time: 0.0096 memory: 16131 loss: 2.6855 loss_prob: 1.6730 loss_thr: 0.7336 loss_db: 0.2789 2022/10/25 21:27:25 - mmengine - INFO - Epoch(train) [166][20/63] lr: 2.4879e-03 eta: 14:38:32 time: 0.7878 data_time: 0.0091 memory: 16131 loss: 2.6935 loss_prob: 1.6856 loss_thr: 0.7282 loss_db: 0.2797 2022/10/25 21:27:28 - mmengine - INFO - Epoch(train) [166][25/63] lr: 2.4879e-03 eta: 14:38:32 time: 0.7714 data_time: 0.0124 memory: 16131 loss: 2.6813 loss_prob: 1.6755 loss_thr: 0.7276 loss_db: 0.2782 2022/10/25 21:27:32 - mmengine - INFO - Epoch(train) [166][30/63] lr: 2.4879e-03 eta: 14:38:18 time: 0.7201 data_time: 0.0296 memory: 16131 loss: 2.5682 loss_prob: 1.5990 loss_thr: 0.7075 loss_db: 0.2617 2022/10/25 21:27:36 - mmengine - INFO - Epoch(train) [166][35/63] lr: 2.4879e-03 eta: 14:38:18 time: 0.8182 data_time: 0.0271 memory: 16131 loss: 2.4225 loss_prob: 1.4832 loss_thr: 0.6974 loss_db: 0.2419 2022/10/25 21:27:40 - mmengine - INFO - Epoch(train) [166][40/63] lr: 2.4879e-03 eta: 14:38:09 time: 0.7862 data_time: 0.0076 memory: 16131 loss: 2.3937 loss_prob: 1.4539 loss_thr: 0.7012 loss_db: 0.2386 2022/10/25 21:27:43 - mmengine - INFO - Epoch(train) [166][45/63] lr: 2.4879e-03 eta: 14:38:09 time: 0.6430 data_time: 0.0101 memory: 16131 loss: 2.4325 loss_prob: 1.4782 loss_thr: 0.7150 loss_db: 0.2393 2022/10/25 21:27:46 - mmengine - INFO - Epoch(train) [166][50/63] lr: 2.4879e-03 eta: 14:37:48 time: 0.6001 data_time: 0.0198 memory: 16131 loss: 2.6408 loss_prob: 1.6183 loss_thr: 0.7526 loss_db: 0.2699 2022/10/25 21:27:49 - mmengine - INFO - Epoch(train) [166][55/63] lr: 2.4879e-03 eta: 14:37:48 time: 0.6352 data_time: 0.0228 memory: 16131 loss: 2.6296 loss_prob: 1.6248 loss_thr: 0.7284 loss_db: 0.2764 2022/10/25 21:27:51 - mmengine - INFO - Epoch(train) [166][60/63] lr: 2.4879e-03 eta: 14:37:23 time: 0.5433 data_time: 0.0132 memory: 16131 loss: 2.3591 loss_prob: 1.4323 loss_thr: 0.6958 loss_db: 0.2310 2022/10/25 21:27:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:28:03 - mmengine - INFO - Epoch(train) [167][5/63] lr: 2.5030e-03 eta: 14:37:23 time: 1.2820 data_time: 0.1972 memory: 16131 loss: 2.3785 loss_prob: 1.4347 loss_thr: 0.7146 loss_db: 0.2292 2022/10/25 21:28:11 - mmengine - INFO - Epoch(train) [167][10/63] lr: 2.5030e-03 eta: 14:37:56 time: 1.7453 data_time: 0.1991 memory: 16131 loss: 2.4086 loss_prob: 1.4524 loss_thr: 0.7186 loss_db: 0.2376 2022/10/25 21:28:16 - mmengine - INFO - Epoch(train) [167][15/63] lr: 2.5030e-03 eta: 14:37:56 time: 1.2943 data_time: 0.0133 memory: 16131 loss: 2.5271 loss_prob: 1.5504 loss_thr: 0.7218 loss_db: 0.2548 2022/10/25 21:28:20 - mmengine - INFO - Epoch(train) [167][20/63] lr: 2.5030e-03 eta: 14:37:58 time: 0.9697 data_time: 0.0126 memory: 16131 loss: 2.4831 loss_prob: 1.5255 loss_thr: 0.7087 loss_db: 0.2489 2022/10/25 21:28:25 - mmengine - INFO - Epoch(train) [167][25/63] lr: 2.5030e-03 eta: 14:37:58 time: 0.9171 data_time: 0.0313 memory: 16131 loss: 2.3847 loss_prob: 1.4642 loss_thr: 0.6807 loss_db: 0.2398 2022/10/25 21:28:29 - mmengine - INFO - Epoch(train) [167][30/63] lr: 2.5030e-03 eta: 14:37:51 time: 0.8388 data_time: 0.0562 memory: 16131 loss: 2.4222 loss_prob: 1.4848 loss_thr: 0.6900 loss_db: 0.2473 2022/10/25 21:28:33 - mmengine - INFO - Epoch(train) [167][35/63] lr: 2.5030e-03 eta: 14:37:51 time: 0.7241 data_time: 0.0385 memory: 16131 loss: 2.3758 loss_prob: 1.4377 loss_thr: 0.6992 loss_db: 0.2389 2022/10/25 21:28:36 - mmengine - INFO - Epoch(train) [167][40/63] lr: 2.5030e-03 eta: 14:37:36 time: 0.6961 data_time: 0.0139 memory: 16131 loss: 2.3637 loss_prob: 1.4314 loss_thr: 0.6991 loss_db: 0.2332 2022/10/25 21:28:39 - mmengine - INFO - Epoch(train) [167][45/63] lr: 2.5030e-03 eta: 14:37:36 time: 0.6518 data_time: 0.0091 memory: 16131 loss: 2.4023 loss_prob: 1.4667 loss_thr: 0.6947 loss_db: 0.2409 2022/10/25 21:28:44 - mmengine - INFO - Epoch(train) [167][50/63] lr: 2.5030e-03 eta: 14:37:29 time: 0.8277 data_time: 0.0151 memory: 16131 loss: 2.3392 loss_prob: 1.4186 loss_thr: 0.6918 loss_db: 0.2288 2022/10/25 21:28:48 - mmengine - INFO - Epoch(train) [167][55/63] lr: 2.5030e-03 eta: 14:37:29 time: 0.9044 data_time: 0.0259 memory: 16131 loss: 2.4638 loss_prob: 1.4974 loss_thr: 0.7231 loss_db: 0.2433 2022/10/25 21:28:51 - mmengine - INFO - Epoch(train) [167][60/63] lr: 2.5030e-03 eta: 14:37:14 time: 0.6977 data_time: 0.0214 memory: 16131 loss: 2.3831 loss_prob: 1.4547 loss_thr: 0.6891 loss_db: 0.2393 2022/10/25 21:28:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:29:02 - mmengine - INFO - Epoch(train) [168][5/63] lr: 2.5181e-03 eta: 14:37:14 time: 1.2373 data_time: 0.2384 memory: 16131 loss: 2.3154 loss_prob: 1.4007 loss_thr: 0.6804 loss_db: 0.2342 2022/10/25 21:29:06 - mmengine - INFO - Epoch(train) [168][10/63] lr: 2.5181e-03 eta: 14:37:15 time: 1.2264 data_time: 0.2390 memory: 16131 loss: 2.4624 loss_prob: 1.5134 loss_thr: 0.6988 loss_db: 0.2501 2022/10/25 21:29:12 - mmengine - INFO - Epoch(train) [168][15/63] lr: 2.5181e-03 eta: 14:37:15 time: 0.9503 data_time: 0.0124 memory: 16131 loss: 2.3533 loss_prob: 1.4345 loss_thr: 0.6869 loss_db: 0.2319 2022/10/25 21:29:18 - mmengine - INFO - Epoch(train) [168][20/63] lr: 2.5181e-03 eta: 14:37:35 time: 1.2641 data_time: 0.0111 memory: 16131 loss: 2.2162 loss_prob: 1.3339 loss_thr: 0.6685 loss_db: 0.2138 2022/10/25 21:29:23 - mmengine - INFO - Epoch(train) [168][25/63] lr: 2.5181e-03 eta: 14:37:35 time: 1.0957 data_time: 0.0287 memory: 16131 loss: 2.3269 loss_prob: 1.4227 loss_thr: 0.6756 loss_db: 0.2287 2022/10/25 21:29:28 - mmengine - INFO - Epoch(train) [168][30/63] lr: 2.5181e-03 eta: 14:37:38 time: 0.9925 data_time: 0.0398 memory: 16131 loss: 2.4860 loss_prob: 1.5268 loss_thr: 0.7154 loss_db: 0.2438 2022/10/25 21:29:32 - mmengine - INFO - Epoch(train) [168][35/63] lr: 2.5181e-03 eta: 14:37:38 time: 0.9600 data_time: 0.0174 memory: 16131 loss: 2.4519 loss_prob: 1.4776 loss_thr: 0.7324 loss_db: 0.2419 2022/10/25 21:29:37 - mmengine - INFO - Epoch(train) [168][40/63] lr: 2.5181e-03 eta: 14:37:31 time: 0.8319 data_time: 0.0060 memory: 16131 loss: 2.3832 loss_prob: 1.4164 loss_thr: 0.7319 loss_db: 0.2349 2022/10/25 21:29:39 - mmengine - INFO - Epoch(train) [168][45/63] lr: 2.5181e-03 eta: 14:37:31 time: 0.7007 data_time: 0.0055 memory: 16131 loss: 2.6727 loss_prob: 1.6463 loss_thr: 0.7567 loss_db: 0.2697 2022/10/25 21:29:42 - mmengine - INFO - Epoch(train) [168][50/63] lr: 2.5181e-03 eta: 14:37:08 time: 0.5580 data_time: 0.0222 memory: 16131 loss: 2.6315 loss_prob: 1.6355 loss_thr: 0.7284 loss_db: 0.2676 2022/10/25 21:29:45 - mmengine - INFO - Epoch(train) [168][55/63] lr: 2.5181e-03 eta: 14:37:08 time: 0.5599 data_time: 0.0311 memory: 16131 loss: 2.3659 loss_prob: 1.4401 loss_thr: 0.6853 loss_db: 0.2405 2022/10/25 21:29:51 - mmengine - INFO - Epoch(train) [168][60/63] lr: 2.5181e-03 eta: 14:37:01 time: 0.8412 data_time: 0.0142 memory: 16131 loss: 2.3498 loss_prob: 1.4253 loss_thr: 0.6893 loss_db: 0.2353 2022/10/25 21:29:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:30:00 - mmengine - INFO - Epoch(train) [169][5/63] lr: 2.5331e-03 eta: 14:37:01 time: 1.0263 data_time: 0.1658 memory: 16131 loss: 2.6679 loss_prob: 1.6816 loss_thr: 0.7127 loss_db: 0.2736 2022/10/25 21:30:03 - mmengine - INFO - Epoch(train) [169][10/63] lr: 2.5331e-03 eta: 14:36:54 time: 1.1090 data_time: 0.1865 memory: 16131 loss: 2.6476 loss_prob: 1.6606 loss_thr: 0.7112 loss_db: 0.2758 2022/10/25 21:30:09 - mmengine - INFO - Epoch(train) [169][15/63] lr: 2.5331e-03 eta: 14:36:54 time: 0.9353 data_time: 0.0258 memory: 16131 loss: 2.4365 loss_prob: 1.5018 loss_thr: 0.6834 loss_db: 0.2513 2022/10/25 21:30:15 - mmengine - INFO - Epoch(train) [169][20/63] lr: 2.5331e-03 eta: 14:37:11 time: 1.2096 data_time: 0.0106 memory: 16131 loss: 2.3780 loss_prob: 1.4706 loss_thr: 0.6651 loss_db: 0.2423 2022/10/25 21:30:19 - mmengine - INFO - Epoch(train) [169][25/63] lr: 2.5331e-03 eta: 14:37:11 time: 1.0114 data_time: 0.0152 memory: 16131 loss: 2.3019 loss_prob: 1.4010 loss_thr: 0.6767 loss_db: 0.2242 2022/10/25 21:30:24 - mmengine - INFO - Epoch(train) [169][30/63] lr: 2.5331e-03 eta: 14:37:07 time: 0.8728 data_time: 0.0253 memory: 16131 loss: 2.4965 loss_prob: 1.5381 loss_thr: 0.7075 loss_db: 0.2510 2022/10/25 21:30:31 - mmengine - INFO - Epoch(train) [169][35/63] lr: 2.5331e-03 eta: 14:37:07 time: 1.1953 data_time: 0.0327 memory: 16131 loss: 2.8029 loss_prob: 1.7713 loss_thr: 0.7342 loss_db: 0.2974 2022/10/25 21:30:36 - mmengine - INFO - Epoch(train) [169][40/63] lr: 2.5331e-03 eta: 14:37:26 time: 1.2566 data_time: 0.0212 memory: 16131 loss: 2.8731 loss_prob: 1.8244 loss_thr: 0.7547 loss_db: 0.2940 2022/10/25 21:30:40 - mmengine - INFO - Epoch(train) [169][45/63] lr: 2.5331e-03 eta: 14:37:26 time: 0.8963 data_time: 0.0208 memory: 16131 loss: 2.8279 loss_prob: 1.7898 loss_thr: 0.7578 loss_db: 0.2802 2022/10/25 21:30:43 - mmengine - INFO - Epoch(train) [169][50/63] lr: 2.5331e-03 eta: 14:37:11 time: 0.7006 data_time: 0.0318 memory: 16131 loss: 2.6335 loss_prob: 1.6477 loss_thr: 0.7113 loss_db: 0.2745 2022/10/25 21:30:50 - mmengine - INFO - Epoch(train) [169][55/63] lr: 2.5331e-03 eta: 14:37:11 time: 0.9672 data_time: 0.0236 memory: 16131 loss: 2.4537 loss_prob: 1.5154 loss_thr: 0.6841 loss_db: 0.2542 2022/10/25 21:30:55 - mmengine - INFO - Epoch(train) [169][60/63] lr: 2.5331e-03 eta: 14:37:26 time: 1.1961 data_time: 0.0142 memory: 16131 loss: 2.6446 loss_prob: 1.6391 loss_thr: 0.7376 loss_db: 0.2680 2022/10/25 21:31:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:31:06 - mmengine - INFO - Epoch(train) [170][5/63] lr: 2.5482e-03 eta: 14:37:26 time: 1.2579 data_time: 0.1827 memory: 16131 loss: 2.3483 loss_prob: 1.4146 loss_thr: 0.7002 loss_db: 0.2334 2022/10/25 21:31:10 - mmengine - INFO - Epoch(train) [170][10/63] lr: 2.5482e-03 eta: 14:37:17 time: 1.0679 data_time: 0.1896 memory: 16131 loss: 2.4174 loss_prob: 1.4683 loss_thr: 0.7032 loss_db: 0.2459 2022/10/25 21:31:17 - mmengine - INFO - Epoch(train) [170][15/63] lr: 2.5482e-03 eta: 14:37:17 time: 1.1936 data_time: 0.0168 memory: 16131 loss: 2.4698 loss_prob: 1.5124 loss_thr: 0.7110 loss_db: 0.2465 2022/10/25 21:31:21 - mmengine - INFO - Epoch(train) [170][20/63] lr: 2.5482e-03 eta: 14:37:23 time: 1.0450 data_time: 0.0076 memory: 16131 loss: 2.5206 loss_prob: 1.5486 loss_thr: 0.7222 loss_db: 0.2498 2022/10/25 21:31:23 - mmengine - INFO - Epoch(train) [170][25/63] lr: 2.5482e-03 eta: 14:37:23 time: 0.5991 data_time: 0.0085 memory: 16131 loss: 2.7631 loss_prob: 1.7370 loss_thr: 0.7385 loss_db: 0.2877 2022/10/25 21:31:27 - mmengine - INFO - Epoch(train) [170][30/63] lr: 2.5482e-03 eta: 14:37:02 time: 0.6034 data_time: 0.0342 memory: 16131 loss: 2.6377 loss_prob: 1.6664 loss_thr: 0.6926 loss_db: 0.2788 2022/10/25 21:31:30 - mmengine - INFO - Epoch(train) [170][35/63] lr: 2.5482e-03 eta: 14:37:02 time: 0.6191 data_time: 0.0325 memory: 16131 loss: 2.5039 loss_prob: 1.5671 loss_thr: 0.6813 loss_db: 0.2555 2022/10/25 21:31:32 - mmengine - INFO - Epoch(train) [170][40/63] lr: 2.5482e-03 eta: 14:36:40 time: 0.5717 data_time: 0.0064 memory: 16131 loss: 2.5283 loss_prob: 1.5807 loss_thr: 0.6904 loss_db: 0.2571 2022/10/25 21:31:35 - mmengine - INFO - Epoch(train) [170][45/63] lr: 2.5482e-03 eta: 14:36:40 time: 0.5475 data_time: 0.0049 memory: 16131 loss: 2.4459 loss_prob: 1.5059 loss_thr: 0.6931 loss_db: 0.2469 2022/10/25 21:31:38 - mmengine - INFO - Epoch(train) [170][50/63] lr: 2.5482e-03 eta: 14:36:15 time: 0.5447 data_time: 0.0200 memory: 16131 loss: 2.4127 loss_prob: 1.4721 loss_thr: 0.7021 loss_db: 0.2384 2022/10/25 21:31:41 - mmengine - INFO - Epoch(train) [170][55/63] lr: 2.5482e-03 eta: 14:36:15 time: 0.5700 data_time: 0.0229 memory: 16131 loss: 2.4487 loss_prob: 1.5056 loss_thr: 0.6946 loss_db: 0.2484 2022/10/25 21:31:46 - mmengine - INFO - Epoch(train) [170][60/63] lr: 2.5482e-03 eta: 14:36:10 time: 0.8465 data_time: 0.0108 memory: 16131 loss: 2.5401 loss_prob: 1.5562 loss_thr: 0.7204 loss_db: 0.2634 2022/10/25 21:31:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:31:56 - mmengine - INFO - Epoch(train) [171][5/63] lr: 2.5633e-03 eta: 14:36:10 time: 1.1538 data_time: 0.2231 memory: 16131 loss: 2.4339 loss_prob: 1.4890 loss_thr: 0.7011 loss_db: 0.2438 2022/10/25 21:31:59 - mmengine - INFO - Epoch(train) [171][10/63] lr: 2.5633e-03 eta: 14:35:55 time: 0.9815 data_time: 0.2222 memory: 16131 loss: 2.3583 loss_prob: 1.4247 loss_thr: 0.7024 loss_db: 0.2313 2022/10/25 21:32:04 - mmengine - INFO - Epoch(train) [171][15/63] lr: 2.5633e-03 eta: 14:35:55 time: 0.7859 data_time: 0.0063 memory: 16131 loss: 2.3852 loss_prob: 1.4368 loss_thr: 0.7094 loss_db: 0.2390 2022/10/25 21:32:09 - mmengine - INFO - Epoch(train) [171][20/63] lr: 2.5633e-03 eta: 14:35:56 time: 0.9597 data_time: 0.0083 memory: 16131 loss: 2.3658 loss_prob: 1.4239 loss_thr: 0.7093 loss_db: 0.2326 2022/10/25 21:32:12 - mmengine - INFO - Epoch(train) [171][25/63] lr: 2.5633e-03 eta: 14:35:56 time: 0.8119 data_time: 0.0197 memory: 16131 loss: 2.2468 loss_prob: 1.3523 loss_thr: 0.6746 loss_db: 0.2199 2022/10/25 21:32:16 - mmengine - INFO - Epoch(train) [171][30/63] lr: 2.5633e-03 eta: 14:35:43 time: 0.7285 data_time: 0.0417 memory: 16131 loss: 2.1968 loss_prob: 1.3298 loss_thr: 0.6511 loss_db: 0.2159 2022/10/25 21:32:20 - mmengine - INFO - Epoch(train) [171][35/63] lr: 2.5633e-03 eta: 14:35:43 time: 0.8464 data_time: 0.0288 memory: 16131 loss: 2.2705 loss_prob: 1.3807 loss_thr: 0.6675 loss_db: 0.2223 2022/10/25 21:32:26 - mmengine - INFO - Epoch(train) [171][40/63] lr: 2.5633e-03 eta: 14:35:43 time: 0.9486 data_time: 0.0061 memory: 16131 loss: 2.4210 loss_prob: 1.4835 loss_thr: 0.7007 loss_db: 0.2368 2022/10/25 21:32:33 - mmengine - INFO - Epoch(train) [171][45/63] lr: 2.5633e-03 eta: 14:35:43 time: 1.2437 data_time: 0.0076 memory: 16131 loss: 2.6044 loss_prob: 1.6063 loss_thr: 0.7349 loss_db: 0.2633 2022/10/25 21:32:40 - mmengine - INFO - Epoch(train) [171][50/63] lr: 2.5633e-03 eta: 14:36:11 time: 1.4186 data_time: 0.0096 memory: 16131 loss: 2.7356 loss_prob: 1.6896 loss_thr: 0.7569 loss_db: 0.2891 2022/10/25 21:32:47 - mmengine - INFO - Epoch(train) [171][55/63] lr: 2.5633e-03 eta: 14:36:11 time: 1.4794 data_time: 0.0250 memory: 16131 loss: 2.5607 loss_prob: 1.5800 loss_thr: 0.7159 loss_db: 0.2648 2022/10/25 21:32:51 - mmengine - INFO - Epoch(train) [171][60/63] lr: 2.5633e-03 eta: 14:36:20 time: 1.0853 data_time: 0.0223 memory: 16131 loss: 2.3862 loss_prob: 1.4706 loss_thr: 0.6781 loss_db: 0.2375 2022/10/25 21:32:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:33:01 - mmengine - INFO - Epoch(train) [172][5/63] lr: 2.5783e-03 eta: 14:36:20 time: 1.1354 data_time: 0.2903 memory: 16131 loss: 2.7016 loss_prob: 1.6889 loss_thr: 0.7272 loss_db: 0.2855 2022/10/25 21:33:04 - mmengine - INFO - Epoch(train) [172][10/63] lr: 2.5783e-03 eta: 14:36:17 time: 1.1773 data_time: 0.2898 memory: 16131 loss: 2.5962 loss_prob: 1.6179 loss_thr: 0.7056 loss_db: 0.2727 2022/10/25 21:33:09 - mmengine - INFO - Epoch(train) [172][15/63] lr: 2.5783e-03 eta: 14:36:17 time: 0.7567 data_time: 0.0061 memory: 16131 loss: 2.4779 loss_prob: 1.5097 loss_thr: 0.7204 loss_db: 0.2479 2022/10/25 21:33:13 - mmengine - INFO - Epoch(train) [172][20/63] lr: 2.5783e-03 eta: 14:36:16 time: 0.9404 data_time: 0.0109 memory: 16131 loss: 2.5692 loss_prob: 1.5699 loss_thr: 0.7376 loss_db: 0.2617 2022/10/25 21:33:20 - mmengine - INFO - Epoch(train) [172][25/63] lr: 2.5783e-03 eta: 14:36:16 time: 1.1022 data_time: 0.0509 memory: 16131 loss: 2.5131 loss_prob: 1.5492 loss_thr: 0.6980 loss_db: 0.2658 2022/10/25 21:33:24 - mmengine - INFO - Epoch(train) [172][30/63] lr: 2.5783e-03 eta: 14:36:27 time: 1.1180 data_time: 0.0461 memory: 16131 loss: 2.5181 loss_prob: 1.5543 loss_thr: 0.6965 loss_db: 0.2673 2022/10/25 21:33:30 - mmengine - INFO - Epoch(train) [172][35/63] lr: 2.5783e-03 eta: 14:36:27 time: 0.9735 data_time: 0.0054 memory: 16131 loss: 2.5935 loss_prob: 1.6046 loss_thr: 0.7155 loss_db: 0.2735 2022/10/25 21:33:35 - mmengine - INFO - Epoch(train) [172][40/63] lr: 2.5783e-03 eta: 14:36:34 time: 1.0760 data_time: 0.0082 memory: 16131 loss: 2.6044 loss_prob: 1.6263 loss_thr: 0.7068 loss_db: 0.2714 2022/10/25 21:33:41 - mmengine - INFO - Epoch(train) [172][45/63] lr: 2.5783e-03 eta: 14:36:34 time: 1.1450 data_time: 0.0080 memory: 16131 loss: 2.7312 loss_prob: 1.7268 loss_thr: 0.7170 loss_db: 0.2874 2022/10/25 21:33:44 - mmengine - INFO - Epoch(train) [172][50/63] lr: 2.5783e-03 eta: 14:36:29 time: 0.8519 data_time: 0.0221 memory: 16131 loss: 2.6112 loss_prob: 1.6265 loss_thr: 0.7139 loss_db: 0.2708 2022/10/25 21:33:50 - mmengine - INFO - Epoch(train) [172][55/63] lr: 2.5783e-03 eta: 14:36:29 time: 0.9171 data_time: 0.0278 memory: 16131 loss: 2.3567 loss_prob: 1.4456 loss_thr: 0.6754 loss_db: 0.2357 2022/10/25 21:33:54 - mmengine - INFO - Epoch(train) [172][60/63] lr: 2.5783e-03 eta: 14:36:34 time: 1.0445 data_time: 0.0148 memory: 16131 loss: 2.2605 loss_prob: 1.3871 loss_thr: 0.6475 loss_db: 0.2259 2022/10/25 21:33:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:34:03 - mmengine - INFO - Epoch(train) [173][5/63] lr: 2.5934e-03 eta: 14:36:34 time: 1.0945 data_time: 0.1673 memory: 16131 loss: 2.6338 loss_prob: 1.6354 loss_thr: 0.7278 loss_db: 0.2706 2022/10/25 21:34:06 - mmengine - INFO - Epoch(train) [173][10/63] lr: 2.5934e-03 eta: 14:36:24 time: 1.0497 data_time: 0.1735 memory: 16131 loss: 2.7528 loss_prob: 1.7209 loss_thr: 0.7466 loss_db: 0.2852 2022/10/25 21:34:11 - mmengine - INFO - Epoch(train) [173][15/63] lr: 2.5934e-03 eta: 14:36:24 time: 0.8721 data_time: 0.0199 memory: 16131 loss: 2.5406 loss_prob: 1.5580 loss_thr: 0.7277 loss_db: 0.2549 2022/10/25 21:34:15 - mmengine - INFO - Epoch(train) [173][20/63] lr: 2.5934e-03 eta: 14:36:17 time: 0.8413 data_time: 0.0137 memory: 16131 loss: 2.3317 loss_prob: 1.4045 loss_thr: 0.6985 loss_db: 0.2287 2022/10/25 21:34:17 - mmengine - INFO - Epoch(train) [173][25/63] lr: 2.5934e-03 eta: 14:36:17 time: 0.5701 data_time: 0.0078 memory: 16131 loss: 2.3292 loss_prob: 1.3950 loss_thr: 0.7022 loss_db: 0.2320 2022/10/25 21:34:21 - mmengine - INFO - Epoch(train) [173][30/63] lr: 2.5934e-03 eta: 14:35:56 time: 0.5998 data_time: 0.0228 memory: 16131 loss: 2.4004 loss_prob: 1.4548 loss_thr: 0.6973 loss_db: 0.2482 2022/10/25 21:34:25 - mmengine - INFO - Epoch(train) [173][35/63] lr: 2.5934e-03 eta: 14:35:56 time: 0.7385 data_time: 0.0293 memory: 16131 loss: 2.5204 loss_prob: 1.5698 loss_thr: 0.6907 loss_db: 0.2598 2022/10/25 21:34:29 - mmengine - INFO - Epoch(train) [173][40/63] lr: 2.5934e-03 eta: 14:35:53 time: 0.8906 data_time: 0.0197 memory: 16131 loss: 2.4621 loss_prob: 1.5328 loss_thr: 0.6796 loss_db: 0.2496 2022/10/25 21:34:32 - mmengine - INFO - Epoch(train) [173][45/63] lr: 2.5934e-03 eta: 14:35:53 time: 0.7447 data_time: 0.0115 memory: 16131 loss: 2.3731 loss_prob: 1.4557 loss_thr: 0.6773 loss_db: 0.2401 2022/10/25 21:34:38 - mmengine - INFO - Epoch(train) [173][50/63] lr: 2.5934e-03 eta: 14:35:50 time: 0.8937 data_time: 0.0071 memory: 16131 loss: 2.5342 loss_prob: 1.5562 loss_thr: 0.7147 loss_db: 0.2633 2022/10/25 21:34:44 - mmengine - INFO - Epoch(train) [173][55/63] lr: 2.5934e-03 eta: 14:35:50 time: 1.1924 data_time: 0.0173 memory: 16131 loss: 2.6512 loss_prob: 1.6398 loss_thr: 0.7347 loss_db: 0.2766 2022/10/25 21:34:48 - mmengine - INFO - Epoch(train) [173][60/63] lr: 2.5934e-03 eta: 14:35:52 time: 0.9906 data_time: 0.0284 memory: 16131 loss: 2.4855 loss_prob: 1.5428 loss_thr: 0.6907 loss_db: 0.2520 2022/10/25 21:34:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:34:59 - mmengine - INFO - Epoch(train) [174][5/63] lr: 2.6084e-03 eta: 14:35:52 time: 1.2936 data_time: 0.2357 memory: 16131 loss: 2.6140 loss_prob: 1.6418 loss_thr: 0.7021 loss_db: 0.2701 2022/10/25 21:35:03 - mmengine - INFO - Epoch(train) [174][10/63] lr: 2.6084e-03 eta: 14:35:51 time: 1.2117 data_time: 0.2336 memory: 16131 loss: 2.6090 loss_prob: 1.6271 loss_thr: 0.7123 loss_db: 0.2696 2022/10/25 21:35:07 - mmengine - INFO - Epoch(train) [174][15/63] lr: 2.6084e-03 eta: 14:35:51 time: 0.8059 data_time: 0.0124 memory: 16131 loss: 2.5060 loss_prob: 1.5411 loss_thr: 0.7061 loss_db: 0.2588 2022/10/25 21:35:12 - mmengine - INFO - Epoch(train) [174][20/63] lr: 2.6084e-03 eta: 14:35:48 time: 0.9043 data_time: 0.0092 memory: 16131 loss: 2.5508 loss_prob: 1.5686 loss_thr: 0.7198 loss_db: 0.2624 2022/10/25 21:35:15 - mmengine - INFO - Epoch(train) [174][25/63] lr: 2.6084e-03 eta: 14:35:48 time: 0.7692 data_time: 0.0345 memory: 16131 loss: 2.7091 loss_prob: 1.6932 loss_thr: 0.7369 loss_db: 0.2790 2022/10/25 21:35:20 - mmengine - INFO - Epoch(train) [174][30/63] lr: 2.6084e-03 eta: 14:35:40 time: 0.8053 data_time: 0.0451 memory: 16131 loss: 2.6862 loss_prob: 1.6924 loss_thr: 0.7094 loss_db: 0.2844 2022/10/25 21:35:25 - mmengine - INFO - Epoch(train) [174][35/63] lr: 2.6084e-03 eta: 14:35:40 time: 1.0058 data_time: 0.0213 memory: 16131 loss: 2.5826 loss_prob: 1.6018 loss_thr: 0.7007 loss_db: 0.2801 2022/10/25 21:35:30 - mmengine - INFO - Epoch(train) [174][40/63] lr: 2.6084e-03 eta: 14:35:44 time: 1.0183 data_time: 0.0107 memory: 16131 loss: 2.5703 loss_prob: 1.5800 loss_thr: 0.7208 loss_db: 0.2695 2022/10/25 21:35:34 - mmengine - INFO - Epoch(train) [174][45/63] lr: 2.6084e-03 eta: 14:35:44 time: 0.8667 data_time: 0.0070 memory: 16131 loss: 2.5690 loss_prob: 1.5835 loss_thr: 0.7238 loss_db: 0.2617 2022/10/25 21:35:39 - mmengine - INFO - Epoch(train) [174][50/63] lr: 2.6084e-03 eta: 14:35:42 time: 0.9152 data_time: 0.0211 memory: 16131 loss: 2.4746 loss_prob: 1.5125 loss_thr: 0.7155 loss_db: 0.2466 2022/10/25 21:35:42 - mmengine - INFO - Epoch(train) [174][55/63] lr: 2.6084e-03 eta: 14:35:42 time: 0.8120 data_time: 0.0268 memory: 16131 loss: 2.4285 loss_prob: 1.4955 loss_thr: 0.6895 loss_db: 0.2434 2022/10/25 21:35:46 - mmengine - INFO - Epoch(train) [174][60/63] lr: 2.6084e-03 eta: 14:35:24 time: 0.6556 data_time: 0.0126 memory: 16131 loss: 2.4133 loss_prob: 1.4824 loss_thr: 0.6870 loss_db: 0.2439 2022/10/25 21:35:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:35:56 - mmengine - INFO - Epoch(train) [175][5/63] lr: 2.6235e-03 eta: 14:35:24 time: 1.2453 data_time: 0.2075 memory: 16131 loss: 2.5383 loss_prob: 1.5954 loss_thr: 0.6783 loss_db: 0.2647 2022/10/25 21:36:00 - mmengine - INFO - Epoch(train) [175][10/63] lr: 2.6235e-03 eta: 14:35:17 time: 1.1149 data_time: 0.2155 memory: 16131 loss: 2.7623 loss_prob: 1.7666 loss_thr: 0.6995 loss_db: 0.2962 2022/10/25 21:36:07 - mmengine - INFO - Epoch(train) [175][15/63] lr: 2.6235e-03 eta: 14:35:17 time: 1.1185 data_time: 0.0163 memory: 16131 loss: 3.0483 loss_prob: 1.9636 loss_thr: 0.7478 loss_db: 0.3369 2022/10/25 21:36:13 - mmengine - INFO - Epoch(train) [175][20/63] lr: 2.6235e-03 eta: 14:35:35 time: 1.2509 data_time: 0.0103 memory: 16131 loss: 2.9568 loss_prob: 1.8880 loss_thr: 0.7506 loss_db: 0.3182 2022/10/25 21:36:16 - mmengine - INFO - Epoch(train) [175][25/63] lr: 2.6235e-03 eta: 14:35:35 time: 0.8991 data_time: 0.0242 memory: 16131 loss: 2.7941 loss_prob: 1.7640 loss_thr: 0.7378 loss_db: 0.2924 2022/10/25 21:36:19 - mmengine - INFO - Epoch(train) [175][30/63] lr: 2.6235e-03 eta: 14:35:14 time: 0.6062 data_time: 0.0344 memory: 16131 loss: 2.6613 loss_prob: 1.6719 loss_thr: 0.7109 loss_db: 0.2786 2022/10/25 21:36:24 - mmengine - INFO - Epoch(train) [175][35/63] lr: 2.6235e-03 eta: 14:35:14 time: 0.7290 data_time: 0.0294 memory: 16131 loss: 2.6135 loss_prob: 1.6522 loss_thr: 0.6828 loss_db: 0.2785 2022/10/25 21:36:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:36:29 - mmengine - INFO - Epoch(train) [175][40/63] lr: 2.6235e-03 eta: 14:35:15 time: 0.9567 data_time: 0.0204 memory: 16131 loss: 2.4464 loss_prob: 1.5183 loss_thr: 0.6769 loss_db: 0.2512 2022/10/25 21:36:35 - mmengine - INFO - Epoch(train) [175][45/63] lr: 2.6235e-03 eta: 14:35:15 time: 1.0931 data_time: 0.0149 memory: 16131 loss: 2.2801 loss_prob: 1.3795 loss_thr: 0.6767 loss_db: 0.2238 2022/10/25 21:36:39 - mmengine - INFO - Epoch(train) [175][50/63] lr: 2.6235e-03 eta: 14:35:17 time: 0.9947 data_time: 0.0211 memory: 16131 loss: 2.3300 loss_prob: 1.4172 loss_thr: 0.6854 loss_db: 0.2273 2022/10/25 21:36:42 - mmengine - INFO - Epoch(train) [175][55/63] lr: 2.6235e-03 eta: 14:35:17 time: 0.7765 data_time: 0.0220 memory: 16131 loss: 2.5221 loss_prob: 1.5451 loss_thr: 0.7219 loss_db: 0.2552 2022/10/25 21:36:46 - mmengine - INFO - Epoch(train) [175][60/63] lr: 2.6235e-03 eta: 14:35:04 time: 0.7326 data_time: 0.0168 memory: 16131 loss: 2.6031 loss_prob: 1.6071 loss_thr: 0.7256 loss_db: 0.2704 2022/10/25 21:36:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:36:55 - mmengine - INFO - Epoch(train) [176][5/63] lr: 2.6386e-03 eta: 14:35:04 time: 1.0993 data_time: 0.2248 memory: 16131 loss: 2.5813 loss_prob: 1.6200 loss_thr: 0.6987 loss_db: 0.2626 2022/10/25 21:37:00 - mmengine - INFO - Epoch(train) [176][10/63] lr: 2.6386e-03 eta: 14:34:58 time: 1.1261 data_time: 0.2252 memory: 16131 loss: 2.4450 loss_prob: 1.5022 loss_thr: 0.6969 loss_db: 0.2460 2022/10/25 21:37:05 - mmengine - INFO - Epoch(train) [176][15/63] lr: 2.6386e-03 eta: 14:34:58 time: 0.9743 data_time: 0.0146 memory: 16131 loss: 2.4825 loss_prob: 1.5257 loss_thr: 0.6984 loss_db: 0.2585 2022/10/25 21:37:09 - mmengine - INFO - Epoch(train) [176][20/63] lr: 2.6386e-03 eta: 14:34:55 time: 0.8971 data_time: 0.0150 memory: 16131 loss: 2.5326 loss_prob: 1.5741 loss_thr: 0.6925 loss_db: 0.2659 2022/10/25 21:37:12 - mmengine - INFO - Epoch(train) [176][25/63] lr: 2.6386e-03 eta: 14:34:55 time: 0.6983 data_time: 0.0521 memory: 16131 loss: 2.6365 loss_prob: 1.6646 loss_thr: 0.6918 loss_db: 0.2801 2022/10/25 21:37:17 - mmengine - INFO - Epoch(train) [176][30/63] lr: 2.6386e-03 eta: 14:34:48 time: 0.8410 data_time: 0.0526 memory: 16131 loss: 2.6328 loss_prob: 1.6669 loss_thr: 0.6879 loss_db: 0.2779 2022/10/25 21:37:22 - mmengine - INFO - Epoch(train) [176][35/63] lr: 2.6386e-03 eta: 14:34:48 time: 1.0421 data_time: 0.0083 memory: 16131 loss: 2.6212 loss_prob: 1.6358 loss_thr: 0.7152 loss_db: 0.2702 2022/10/25 21:37:26 - mmengine - INFO - Epoch(train) [176][40/63] lr: 2.6386e-03 eta: 14:34:42 time: 0.8390 data_time: 0.0175 memory: 16131 loss: 2.5868 loss_prob: 1.6050 loss_thr: 0.7181 loss_db: 0.2636 2022/10/25 21:37:29 - mmengine - INFO - Epoch(train) [176][45/63] lr: 2.6386e-03 eta: 14:34:42 time: 0.6845 data_time: 0.0169 memory: 16131 loss: 2.9132 loss_prob: 1.8487 loss_thr: 0.7502 loss_db: 0.3142 2022/10/25 21:37:32 - mmengine - INFO - Epoch(train) [176][50/63] lr: 2.6386e-03 eta: 14:34:23 time: 0.6339 data_time: 0.0266 memory: 16131 loss: 2.9820 loss_prob: 1.8793 loss_thr: 0.7821 loss_db: 0.3206 2022/10/25 21:37:35 - mmengine - INFO - Epoch(train) [176][55/63] lr: 2.6386e-03 eta: 14:34:23 time: 0.5778 data_time: 0.0264 memory: 16131 loss: 2.6558 loss_prob: 1.6334 loss_thr: 0.7479 loss_db: 0.2745 2022/10/25 21:37:42 - mmengine - INFO - Epoch(train) [176][60/63] lr: 2.6386e-03 eta: 14:34:26 time: 1.0086 data_time: 0.0077 memory: 16131 loss: 2.5611 loss_prob: 1.5841 loss_thr: 0.7117 loss_db: 0.2653 2022/10/25 21:37:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:37:53 - mmengine - INFO - Epoch(train) [177][5/63] lr: 2.6536e-03 eta: 14:34:26 time: 1.4155 data_time: 0.2434 memory: 16131 loss: 2.2924 loss_prob: 1.3751 loss_thr: 0.6987 loss_db: 0.2186 2022/10/25 21:37:56 - mmengine - INFO - Epoch(train) [177][10/63] lr: 2.6536e-03 eta: 14:34:14 time: 1.0337 data_time: 0.2429 memory: 16131 loss: 2.3053 loss_prob: 1.3927 loss_thr: 0.6911 loss_db: 0.2215 2022/10/25 21:38:01 - mmengine - INFO - Epoch(train) [177][15/63] lr: 2.6536e-03 eta: 14:34:14 time: 0.7814 data_time: 0.0145 memory: 16131 loss: 2.3783 loss_prob: 1.4450 loss_thr: 0.7000 loss_db: 0.2333 2022/10/25 21:38:06 - mmengine - INFO - Epoch(train) [177][20/63] lr: 2.6536e-03 eta: 14:34:17 time: 0.9997 data_time: 0.0128 memory: 16131 loss: 2.4473 loss_prob: 1.5023 loss_thr: 0.6972 loss_db: 0.2478 2022/10/25 21:38:15 - mmengine - INFO - Epoch(train) [177][25/63] lr: 2.6536e-03 eta: 14:34:17 time: 1.4553 data_time: 0.0259 memory: 16131 loss: 2.4982 loss_prob: 1.5538 loss_thr: 0.6905 loss_db: 0.2538 2022/10/25 21:38:21 - mmengine - INFO - Epoch(train) [177][30/63] lr: 2.6536e-03 eta: 14:34:51 time: 1.5348 data_time: 0.0371 memory: 16131 loss: 2.3632 loss_prob: 1.4369 loss_thr: 0.6919 loss_db: 0.2344 2022/10/25 21:38:27 - mmengine - INFO - Epoch(train) [177][35/63] lr: 2.6536e-03 eta: 14:34:51 time: 1.2179 data_time: 0.0187 memory: 16131 loss: 2.3143 loss_prob: 1.3953 loss_thr: 0.6883 loss_db: 0.2307 2022/10/25 21:38:31 - mmengine - INFO - Epoch(train) [177][40/63] lr: 2.6536e-03 eta: 14:34:51 time: 0.9516 data_time: 0.0071 memory: 16131 loss: 2.3293 loss_prob: 1.4152 loss_thr: 0.6857 loss_db: 0.2284 2022/10/25 21:38:34 - mmengine - INFO - Epoch(train) [177][45/63] lr: 2.6536e-03 eta: 14:34:51 time: 0.6321 data_time: 0.0068 memory: 16131 loss: 2.5759 loss_prob: 1.5821 loss_thr: 0.7364 loss_db: 0.2573 2022/10/25 21:38:37 - mmengine - INFO - Epoch(train) [177][50/63] lr: 2.6536e-03 eta: 14:34:29 time: 0.5756 data_time: 0.0175 memory: 16131 loss: 2.6948 loss_prob: 1.6713 loss_thr: 0.7460 loss_db: 0.2775 2022/10/25 21:38:40 - mmengine - INFO - Epoch(train) [177][55/63] lr: 2.6536e-03 eta: 14:34:29 time: 0.6271 data_time: 0.0241 memory: 16131 loss: 2.5667 loss_prob: 1.5720 loss_thr: 0.7324 loss_db: 0.2623 2022/10/25 21:38:44 - mmengine - INFO - Epoch(train) [177][60/63] lr: 2.6536e-03 eta: 14:34:15 time: 0.7198 data_time: 0.0136 memory: 16131 loss: 2.5288 loss_prob: 1.5529 loss_thr: 0.7173 loss_db: 0.2586 2022/10/25 21:38:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:38:51 - mmengine - INFO - Epoch(train) [178][5/63] lr: 2.6687e-03 eta: 14:34:15 time: 0.8146 data_time: 0.1986 memory: 16131 loss: 2.7862 loss_prob: 1.7485 loss_thr: 0.7427 loss_db: 0.2951 2022/10/25 21:38:55 - mmengine - INFO - Epoch(train) [178][10/63] lr: 2.6687e-03 eta: 14:34:02 time: 1.0235 data_time: 0.2256 memory: 16131 loss: 2.7521 loss_prob: 1.7238 loss_thr: 0.7360 loss_db: 0.2923 2022/10/25 21:38:59 - mmengine - INFO - Epoch(train) [178][15/63] lr: 2.6687e-03 eta: 14:34:02 time: 0.8262 data_time: 0.0332 memory: 16131 loss: 2.4996 loss_prob: 1.5377 loss_thr: 0.7029 loss_db: 0.2590 2022/10/25 21:39:03 - mmengine - INFO - Epoch(train) [178][20/63] lr: 2.6687e-03 eta: 14:33:49 time: 0.7260 data_time: 0.0098 memory: 16131 loss: 2.3903 loss_prob: 1.4498 loss_thr: 0.7020 loss_db: 0.2385 2022/10/25 21:39:09 - mmengine - INFO - Epoch(train) [178][25/63] lr: 2.6687e-03 eta: 14:33:49 time: 0.9331 data_time: 0.0311 memory: 16131 loss: 2.3790 loss_prob: 1.4550 loss_thr: 0.6831 loss_db: 0.2410 2022/10/25 21:39:12 - mmengine - INFO - Epoch(train) [178][30/63] lr: 2.6687e-03 eta: 14:33:49 time: 0.9441 data_time: 0.0278 memory: 16131 loss: 2.4015 loss_prob: 1.5103 loss_thr: 0.6476 loss_db: 0.2437 2022/10/25 21:39:17 - mmengine - INFO - Epoch(train) [178][35/63] lr: 2.6687e-03 eta: 14:33:49 time: 0.7988 data_time: 0.0224 memory: 16131 loss: 2.5340 loss_prob: 1.5874 loss_thr: 0.6868 loss_db: 0.2597 2022/10/25 21:39:21 - mmengine - INFO - Epoch(train) [178][40/63] lr: 2.6687e-03 eta: 14:33:47 time: 0.9221 data_time: 0.0240 memory: 16131 loss: 2.5920 loss_prob: 1.6074 loss_thr: 0.7155 loss_db: 0.2691 2022/10/25 21:39:27 - mmengine - INFO - Epoch(train) [178][45/63] lr: 2.6687e-03 eta: 14:33:47 time: 1.0431 data_time: 0.0080 memory: 16131 loss: 2.4871 loss_prob: 1.5381 loss_thr: 0.6994 loss_db: 0.2495 2022/10/25 21:39:33 - mmengine - INFO - Epoch(train) [178][50/63] lr: 2.6687e-03 eta: 14:33:57 time: 1.1399 data_time: 0.0154 memory: 16131 loss: 2.3883 loss_prob: 1.4632 loss_thr: 0.6907 loss_db: 0.2343 2022/10/25 21:39:39 - mmengine - INFO - Epoch(train) [178][55/63] lr: 2.6687e-03 eta: 14:33:57 time: 1.1790 data_time: 0.0187 memory: 16131 loss: 2.4490 loss_prob: 1.5057 loss_thr: 0.6945 loss_db: 0.2488 2022/10/25 21:39:44 - mmengine - INFO - Epoch(train) [178][60/63] lr: 2.6687e-03 eta: 14:34:05 time: 1.0990 data_time: 0.0148 memory: 16131 loss: 2.4775 loss_prob: 1.5159 loss_thr: 0.7083 loss_db: 0.2532 2022/10/25 21:39:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:39:52 - mmengine - INFO - Epoch(train) [179][5/63] lr: 2.6837e-03 eta: 14:34:05 time: 0.9398 data_time: 0.2326 memory: 16131 loss: 2.3984 loss_prob: 1.4332 loss_thr: 0.7314 loss_db: 0.2338 2022/10/25 21:39:56 - mmengine - INFO - Epoch(train) [179][10/63] lr: 2.6837e-03 eta: 14:33:52 time: 1.0035 data_time: 0.2309 memory: 16131 loss: 2.3773 loss_prob: 1.4242 loss_thr: 0.7150 loss_db: 0.2380 2022/10/25 21:39:59 - mmengine - INFO - Epoch(train) [179][15/63] lr: 2.6837e-03 eta: 14:33:52 time: 0.7084 data_time: 0.0059 memory: 16131 loss: 2.2725 loss_prob: 1.3692 loss_thr: 0.6703 loss_db: 0.2329 2022/10/25 21:40:05 - mmengine - INFO - Epoch(train) [179][20/63] lr: 2.6837e-03 eta: 14:33:51 time: 0.9467 data_time: 0.0082 memory: 16131 loss: 2.1637 loss_prob: 1.2974 loss_thr: 0.6499 loss_db: 0.2163 2022/10/25 21:40:10 - mmengine - INFO - Epoch(train) [179][25/63] lr: 2.6837e-03 eta: 14:33:51 time: 1.1166 data_time: 0.0371 memory: 16131 loss: 2.2026 loss_prob: 1.3291 loss_thr: 0.6586 loss_db: 0.2149 2022/10/25 21:40:13 - mmengine - INFO - Epoch(train) [179][30/63] lr: 2.6837e-03 eta: 14:33:40 time: 0.7679 data_time: 0.0348 memory: 16131 loss: 2.2249 loss_prob: 1.3461 loss_thr: 0.6622 loss_db: 0.2166 2022/10/25 21:40:16 - mmengine - INFO - Epoch(train) [179][35/63] lr: 2.6837e-03 eta: 14:33:40 time: 0.5538 data_time: 0.0098 memory: 16131 loss: 2.2652 loss_prob: 1.3652 loss_thr: 0.6751 loss_db: 0.2248 2022/10/25 21:40:20 - mmengine - INFO - Epoch(train) [179][40/63] lr: 2.6837e-03 eta: 14:33:23 time: 0.6566 data_time: 0.0168 memory: 16131 loss: 2.3218 loss_prob: 1.3988 loss_thr: 0.6902 loss_db: 0.2328 2022/10/25 21:40:26 - mmengine - INFO - Epoch(train) [179][45/63] lr: 2.6837e-03 eta: 14:33:23 time: 1.0022 data_time: 0.0137 memory: 16131 loss: 2.3890 loss_prob: 1.4487 loss_thr: 0.6977 loss_db: 0.2427 2022/10/25 21:40:32 - mmengine - INFO - Epoch(train) [179][50/63] lr: 2.6837e-03 eta: 14:33:40 time: 1.2500 data_time: 0.0227 memory: 16131 loss: 2.5458 loss_prob: 1.5580 loss_thr: 0.7299 loss_db: 0.2579 2022/10/25 21:40:38 - mmengine - INFO - Epoch(train) [179][55/63] lr: 2.6837e-03 eta: 14:33:40 time: 1.2218 data_time: 0.0212 memory: 16131 loss: 2.5800 loss_prob: 1.5976 loss_thr: 0.7123 loss_db: 0.2700 2022/10/25 21:40:40 - mmengine - INFO - Epoch(train) [179][60/63] lr: 2.6837e-03 eta: 14:33:33 time: 0.8390 data_time: 0.0059 memory: 16131 loss: 2.7963 loss_prob: 1.7973 loss_thr: 0.6980 loss_db: 0.3010 2022/10/25 21:40:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:40:49 - mmengine - INFO - Epoch(train) [180][5/63] lr: 2.6988e-03 eta: 14:33:33 time: 0.9885 data_time: 0.2343 memory: 16131 loss: 2.5335 loss_prob: 1.5675 loss_thr: 0.7153 loss_db: 0.2507 2022/10/25 21:40:53 - mmengine - INFO - Epoch(train) [180][10/63] lr: 2.6988e-03 eta: 14:33:20 time: 1.0097 data_time: 0.2358 memory: 16131 loss: 2.5351 loss_prob: 1.5519 loss_thr: 0.7312 loss_db: 0.2520 2022/10/25 21:40:57 - mmengine - INFO - Epoch(train) [180][15/63] lr: 2.6988e-03 eta: 14:33:20 time: 0.7158 data_time: 0.0115 memory: 16131 loss: 2.7851 loss_prob: 1.7504 loss_thr: 0.7458 loss_db: 0.2889 2022/10/25 21:41:01 - mmengine - INFO - Epoch(train) [180][20/63] lr: 2.6988e-03 eta: 14:33:08 time: 0.7462 data_time: 0.0129 memory: 16131 loss: 3.0709 loss_prob: 1.9613 loss_thr: 0.7811 loss_db: 0.3285 2022/10/25 21:41:07 - mmengine - INFO - Epoch(train) [180][25/63] lr: 2.6988e-03 eta: 14:33:08 time: 1.0661 data_time: 0.0599 memory: 16131 loss: 2.8619 loss_prob: 1.8092 loss_thr: 0.7513 loss_db: 0.3013 2022/10/25 21:41:12 - mmengine - INFO - Epoch(train) [180][30/63] lr: 2.6988e-03 eta: 14:33:19 time: 1.1657 data_time: 0.0582 memory: 16131 loss: 2.6517 loss_prob: 1.6353 loss_thr: 0.7448 loss_db: 0.2716 2022/10/25 21:41:19 - mmengine - INFO - Epoch(train) [180][35/63] lr: 2.6988e-03 eta: 14:33:19 time: 1.1813 data_time: 0.0091 memory: 16131 loss: 2.8542 loss_prob: 1.7612 loss_thr: 0.7901 loss_db: 0.3029 2022/10/25 21:41:22 - mmengine - INFO - Epoch(train) [180][40/63] lr: 2.6988e-03 eta: 14:33:19 time: 0.9555 data_time: 0.0096 memory: 16131 loss: 2.9517 loss_prob: 1.8501 loss_thr: 0.7806 loss_db: 0.3211 2022/10/25 21:41:25 - mmengine - INFO - Epoch(train) [180][45/63] lr: 2.6988e-03 eta: 14:33:19 time: 0.5993 data_time: 0.0066 memory: 16131 loss: 2.7471 loss_prob: 1.7244 loss_thr: 0.7306 loss_db: 0.2921 2022/10/25 21:41:28 - mmengine - INFO - Epoch(train) [180][50/63] lr: 2.6988e-03 eta: 14:32:58 time: 0.5859 data_time: 0.0259 memory: 16131 loss: 2.7645 loss_prob: 1.7322 loss_thr: 0.7407 loss_db: 0.2915 2022/10/25 21:41:31 - mmengine - INFO - Epoch(train) [180][55/63] lr: 2.6988e-03 eta: 14:32:58 time: 0.5963 data_time: 0.0293 memory: 16131 loss: 2.6448 loss_prob: 1.6434 loss_thr: 0.7295 loss_db: 0.2720 2022/10/25 21:41:34 - mmengine - INFO - Epoch(train) [180][60/63] lr: 2.6988e-03 eta: 14:32:37 time: 0.5842 data_time: 0.0088 memory: 16131 loss: 2.4523 loss_prob: 1.5127 loss_thr: 0.6969 loss_db: 0.2427 2022/10/25 21:41:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:41:35 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/10/25 21:41:42 - mmengine - INFO - Epoch(val) [180][5/32] eta: 14:32:37 time: 0.5553 data_time: 0.0841 memory: 16131 2022/10/25 21:41:45 - mmengine - INFO - Epoch(val) [180][10/32] eta: 0:00:13 time: 0.6232 data_time: 0.1286 memory: 15724 2022/10/25 21:41:48 - mmengine - INFO - Epoch(val) [180][15/32] eta: 0:00:13 time: 0.5773 data_time: 0.0582 memory: 15724 2022/10/25 21:41:51 - mmengine - INFO - Epoch(val) [180][20/32] eta: 0:00:07 time: 0.5915 data_time: 0.0698 memory: 15724 2022/10/25 21:41:53 - mmengine - INFO - Epoch(val) [180][25/32] eta: 0:00:07 time: 0.5919 data_time: 0.0753 memory: 15724 2022/10/25 21:41:56 - mmengine - INFO - Epoch(val) [180][30/32] eta: 0:00:01 time: 0.5425 data_time: 0.0248 memory: 15724 2022/10/25 21:41:57 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7275, precision: 0.6954, hmean: 0.7111 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7270, precision: 0.7832, hmean: 0.7541 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7126, precision: 0.8516, hmean: 0.7759 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.6572, precision: 0.9022, hmean: 0.7604 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.4661, precision: 0.9575, hmean: 0.6269 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0404, precision: 1.0000, hmean: 0.0777 2022/10/25 21:41:57 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 21:41:57 - mmengine - INFO - Epoch(val) [180][32/32] icdar/precision: 0.8516 icdar/recall: 0.7126 icdar/hmean: 0.7759 2022/10/25 21:42:05 - mmengine - INFO - Epoch(train) [181][5/63] lr: 2.7139e-03 eta: 0:00:01 time: 1.0084 data_time: 0.1760 memory: 16131 loss: 2.3303 loss_prob: 1.4340 loss_thr: 0.6674 loss_db: 0.2289 2022/10/25 21:42:10 - mmengine - INFO - Epoch(train) [181][10/63] lr: 2.7139e-03 eta: 14:32:41 time: 1.3103 data_time: 0.1963 memory: 16131 loss: 2.4879 loss_prob: 1.5388 loss_thr: 0.6943 loss_db: 0.2548 2022/10/25 21:42:14 - mmengine - INFO - Epoch(train) [181][15/63] lr: 2.7139e-03 eta: 14:32:41 time: 0.9852 data_time: 0.0362 memory: 16131 loss: 2.4878 loss_prob: 1.5293 loss_thr: 0.7009 loss_db: 0.2576 2022/10/25 21:42:21 - mmengine - INFO - Epoch(train) [181][20/63] lr: 2.7139e-03 eta: 14:32:51 time: 1.1366 data_time: 0.0178 memory: 16131 loss: 2.4693 loss_prob: 1.5159 loss_thr: 0.6999 loss_db: 0.2535 2022/10/25 21:42:25 - mmengine - INFO - Epoch(train) [181][25/63] lr: 2.7139e-03 eta: 14:32:51 time: 1.0213 data_time: 0.0154 memory: 16131 loss: 2.6271 loss_prob: 1.6324 loss_thr: 0.7217 loss_db: 0.2730 2022/10/25 21:42:27 - mmengine - INFO - Epoch(train) [181][30/63] lr: 2.7139e-03 eta: 14:32:31 time: 0.6156 data_time: 0.0198 memory: 16131 loss: 2.4894 loss_prob: 1.5292 loss_thr: 0.7091 loss_db: 0.2512 2022/10/25 21:42:35 - mmengine - INFO - Epoch(train) [181][35/63] lr: 2.7139e-03 eta: 14:32:31 time: 1.0344 data_time: 0.0230 memory: 16131 loss: 2.4842 loss_prob: 1.5388 loss_thr: 0.6963 loss_db: 0.2492 2022/10/25 21:42:40 - mmengine - INFO - Epoch(train) [181][40/63] lr: 2.7139e-03 eta: 14:32:45 time: 1.2078 data_time: 0.0309 memory: 16131 loss: 2.4467 loss_prob: 1.5159 loss_thr: 0.6830 loss_db: 0.2478 2022/10/25 21:42:44 - mmengine - INFO - Epoch(train) [181][45/63] lr: 2.7139e-03 eta: 14:32:45 time: 0.9293 data_time: 0.0223 memory: 16131 loss: 2.1714 loss_prob: 1.3051 loss_thr: 0.6568 loss_db: 0.2095 2022/10/25 21:42:47 - mmengine - INFO - Epoch(train) [181][50/63] lr: 2.7139e-03 eta: 14:32:36 time: 0.7953 data_time: 0.0143 memory: 16131 loss: 2.3830 loss_prob: 1.4314 loss_thr: 0.7150 loss_db: 0.2366 2022/10/25 21:42:52 - mmengine - INFO - Epoch(train) [181][55/63] lr: 2.7139e-03 eta: 14:32:36 time: 0.8185 data_time: 0.0209 memory: 16131 loss: 2.5530 loss_prob: 1.5466 loss_thr: 0.7441 loss_db: 0.2624 2022/10/25 21:42:58 - mmengine - INFO - Epoch(train) [181][60/63] lr: 2.7139e-03 eta: 14:32:40 time: 1.0389 data_time: 0.0202 memory: 16131 loss: 2.4035 loss_prob: 1.4732 loss_thr: 0.6887 loss_db: 0.2417 2022/10/25 21:43:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:43:09 - mmengine - INFO - Epoch(train) [182][5/63] lr: 2.7289e-03 eta: 14:32:40 time: 1.3726 data_time: 0.2748 memory: 16131 loss: 2.4065 loss_prob: 1.4592 loss_thr: 0.7124 loss_db: 0.2349 2022/10/25 21:43:12 - mmengine - INFO - Epoch(train) [182][10/63] lr: 2.7289e-03 eta: 14:32:33 time: 1.1100 data_time: 0.2769 memory: 16131 loss: 2.3336 loss_prob: 1.4103 loss_thr: 0.6959 loss_db: 0.2274 2022/10/25 21:43:21 - mmengine - INFO - Epoch(train) [182][15/63] lr: 2.7289e-03 eta: 14:32:33 time: 1.1557 data_time: 0.0124 memory: 16131 loss: 2.3022 loss_prob: 1.3808 loss_thr: 0.6989 loss_db: 0.2225 2022/10/25 21:43:27 - mmengine - INFO - Epoch(train) [182][20/63] lr: 2.7289e-03 eta: 14:33:04 time: 1.5166 data_time: 0.0077 memory: 16131 loss: 2.3555 loss_prob: 1.4234 loss_thr: 0.7054 loss_db: 0.2268 2022/10/25 21:43:32 - mmengine - INFO - Epoch(train) [182][25/63] lr: 2.7289e-03 eta: 14:33:04 time: 1.1369 data_time: 0.0321 memory: 16131 loss: 2.2637 loss_prob: 1.3780 loss_thr: 0.6663 loss_db: 0.2194 2022/10/25 21:43:36 - mmengine - INFO - Epoch(train) [182][30/63] lr: 2.7289e-03 eta: 14:33:00 time: 0.8977 data_time: 0.0479 memory: 16131 loss: 2.2159 loss_prob: 1.3344 loss_thr: 0.6627 loss_db: 0.2188 2022/10/25 21:43:39 - mmengine - INFO - Epoch(train) [182][35/63] lr: 2.7289e-03 eta: 14:33:00 time: 0.7446 data_time: 0.0232 memory: 16131 loss: 2.4503 loss_prob: 1.5106 loss_thr: 0.6905 loss_db: 0.2492 2022/10/25 21:43:43 - mmengine - INFO - Epoch(train) [182][40/63] lr: 2.7289e-03 eta: 14:32:42 time: 0.6336 data_time: 0.0073 memory: 16131 loss: 2.4618 loss_prob: 1.5188 loss_thr: 0.6952 loss_db: 0.2478 2022/10/25 21:43:48 - mmengine - INFO - Epoch(train) [182][45/63] lr: 2.7289e-03 eta: 14:32:42 time: 0.8371 data_time: 0.0078 memory: 16131 loss: 2.6463 loss_prob: 1.6447 loss_thr: 0.7237 loss_db: 0.2779 2022/10/25 21:43:52 - mmengine - INFO - Epoch(train) [182][50/63] lr: 2.7289e-03 eta: 14:32:41 time: 0.9449 data_time: 0.0227 memory: 16131 loss: 2.6388 loss_prob: 1.6392 loss_thr: 0.7183 loss_db: 0.2813 2022/10/25 21:43:55 - mmengine - INFO - Epoch(train) [182][55/63] lr: 2.7289e-03 eta: 14:32:41 time: 0.7564 data_time: 0.0225 memory: 16131 loss: 2.3331 loss_prob: 1.4121 loss_thr: 0.6912 loss_db: 0.2297 2022/10/25 21:44:00 - mmengine - INFO - Epoch(train) [182][60/63] lr: 2.7289e-03 eta: 14:32:32 time: 0.7990 data_time: 0.0052 memory: 16131 loss: 2.2870 loss_prob: 1.3835 loss_thr: 0.6807 loss_db: 0.2228 2022/10/25 21:44:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:44:10 - mmengine - INFO - Epoch(train) [183][5/63] lr: 2.7440e-03 eta: 14:32:32 time: 1.2392 data_time: 0.2452 memory: 16131 loss: 2.2170 loss_prob: 1.3298 loss_thr: 0.6739 loss_db: 0.2132 2022/10/25 21:44:13 - mmengine - INFO - Epoch(train) [183][10/63] lr: 2.7440e-03 eta: 14:32:19 time: 1.0190 data_time: 0.2453 memory: 16131 loss: 2.5124 loss_prob: 1.5494 loss_thr: 0.7162 loss_db: 0.2469 2022/10/25 21:44:19 - mmengine - INFO - Epoch(train) [183][15/63] lr: 2.7440e-03 eta: 14:32:19 time: 0.8870 data_time: 0.0067 memory: 16131 loss: 2.4792 loss_prob: 1.5210 loss_thr: 0.7103 loss_db: 0.2479 2022/10/25 21:44:23 - mmengine - INFO - Epoch(train) [183][20/63] lr: 2.7440e-03 eta: 14:32:22 time: 1.0274 data_time: 0.0058 memory: 16131 loss: 2.2868 loss_prob: 1.3982 loss_thr: 0.6610 loss_db: 0.2276 2022/10/25 21:44:28 - mmengine - INFO - Epoch(train) [183][25/63] lr: 2.7440e-03 eta: 14:32:22 time: 0.9257 data_time: 0.0436 memory: 16131 loss: 2.4827 loss_prob: 1.5608 loss_thr: 0.6662 loss_db: 0.2557 2022/10/25 21:44:31 - mmengine - INFO - Epoch(train) [183][30/63] lr: 2.7440e-03 eta: 14:32:10 time: 0.7445 data_time: 0.0429 memory: 16131 loss: 2.4615 loss_prob: 1.5217 loss_thr: 0.6878 loss_db: 0.2520 2022/10/25 21:44:34 - mmengine - INFO - Epoch(train) [183][35/63] lr: 2.7440e-03 eta: 14:32:10 time: 0.5564 data_time: 0.0065 memory: 16131 loss: 2.4560 loss_prob: 1.4960 loss_thr: 0.7196 loss_db: 0.2404 2022/10/25 21:44:37 - mmengine - INFO - Epoch(train) [183][40/63] lr: 2.7440e-03 eta: 14:31:50 time: 0.6005 data_time: 0.0096 memory: 16131 loss: 2.2762 loss_prob: 1.3514 loss_thr: 0.7078 loss_db: 0.2170 2022/10/25 21:44:40 - mmengine - INFO - Epoch(train) [183][45/63] lr: 2.7440e-03 eta: 14:31:50 time: 0.6081 data_time: 0.0156 memory: 16131 loss: 2.0833 loss_prob: 1.2069 loss_thr: 0.6768 loss_db: 0.1996 2022/10/25 21:44:43 - mmengine - INFO - Epoch(train) [183][50/63] lr: 2.7440e-03 eta: 14:31:32 time: 0.6419 data_time: 0.0323 memory: 16131 loss: 2.2768 loss_prob: 1.3539 loss_thr: 0.7003 loss_db: 0.2225 2022/10/25 21:44:46 - mmengine - INFO - Epoch(train) [183][55/63] lr: 2.7440e-03 eta: 14:31:32 time: 0.6237 data_time: 0.0247 memory: 16131 loss: 2.2643 loss_prob: 1.3391 loss_thr: 0.7035 loss_db: 0.2217 2022/10/25 21:44:50 - mmengine - INFO - Epoch(train) [183][60/63] lr: 2.7440e-03 eta: 14:31:17 time: 0.6861 data_time: 0.0063 memory: 16131 loss: 2.0986 loss_prob: 1.2376 loss_thr: 0.6583 loss_db: 0.2027 2022/10/25 21:44:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:44:57 - mmengine - INFO - Epoch(train) [184][5/63] lr: 2.7590e-03 eta: 14:31:17 time: 0.8217 data_time: 0.1974 memory: 16131 loss: 2.0993 loss_prob: 1.2493 loss_thr: 0.6454 loss_db: 0.2047 2022/10/25 21:44:59 - mmengine - INFO - Epoch(train) [184][10/63] lr: 2.7590e-03 eta: 14:30:52 time: 0.8102 data_time: 0.1953 memory: 16131 loss: 2.4031 loss_prob: 1.4693 loss_thr: 0.6934 loss_db: 0.2404 2022/10/25 21:45:03 - mmengine - INFO - Epoch(train) [184][15/63] lr: 2.7590e-03 eta: 14:30:52 time: 0.5749 data_time: 0.0114 memory: 16131 loss: 2.4318 loss_prob: 1.4999 loss_thr: 0.6860 loss_db: 0.2459 2022/10/25 21:45:05 - mmengine - INFO - Epoch(train) [184][20/63] lr: 2.7590e-03 eta: 14:30:31 time: 0.5742 data_time: 0.0095 memory: 16131 loss: 2.3969 loss_prob: 1.4599 loss_thr: 0.6951 loss_db: 0.2419 2022/10/25 21:45:09 - mmengine - INFO - Epoch(train) [184][25/63] lr: 2.7590e-03 eta: 14:30:31 time: 0.6207 data_time: 0.0208 memory: 16131 loss: 2.3603 loss_prob: 1.4249 loss_thr: 0.7021 loss_db: 0.2334 2022/10/25 21:45:13 - mmengine - INFO - Epoch(train) [184][30/63] lr: 2.7590e-03 eta: 14:30:20 time: 0.7651 data_time: 0.0389 memory: 16131 loss: 2.2969 loss_prob: 1.3839 loss_thr: 0.6831 loss_db: 0.2299 2022/10/25 21:45:18 - mmengine - INFO - Epoch(train) [184][35/63] lr: 2.7590e-03 eta: 14:30:20 time: 0.8929 data_time: 0.0267 memory: 16131 loss: 2.4661 loss_prob: 1.5143 loss_thr: 0.7071 loss_db: 0.2446 2022/10/25 21:45:21 - mmengine - INFO - Epoch(train) [184][40/63] lr: 2.7590e-03 eta: 14:30:13 time: 0.8355 data_time: 0.0082 memory: 16131 loss: 2.4760 loss_prob: 1.5392 loss_thr: 0.6980 loss_db: 0.2388 2022/10/25 21:45:24 - mmengine - INFO - Epoch(train) [184][45/63] lr: 2.7590e-03 eta: 14:30:13 time: 0.5892 data_time: 0.0062 memory: 16131 loss: 2.4113 loss_prob: 1.4911 loss_thr: 0.6805 loss_db: 0.2398 2022/10/25 21:45:31 - mmengine - INFO - Epoch(train) [184][50/63] lr: 2.7590e-03 eta: 14:30:12 time: 0.9482 data_time: 0.0206 memory: 16131 loss: 2.4790 loss_prob: 1.5418 loss_thr: 0.6872 loss_db: 0.2499 2022/10/25 21:45:34 - mmengine - INFO - Epoch(train) [184][55/63] lr: 2.7590e-03 eta: 14:30:12 time: 1.0150 data_time: 0.0369 memory: 16131 loss: 2.5732 loss_prob: 1.5890 loss_thr: 0.7250 loss_db: 0.2592 2022/10/25 21:45:36 - mmengine - INFO - Epoch(train) [184][60/63] lr: 2.7590e-03 eta: 14:29:50 time: 0.5652 data_time: 0.0247 memory: 16131 loss: 2.4399 loss_prob: 1.4732 loss_thr: 0.7238 loss_db: 0.2428 2022/10/25 21:45:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:45:46 - mmengine - INFO - Epoch(train) [185][5/63] lr: 2.7741e-03 eta: 14:29:50 time: 1.0891 data_time: 0.2216 memory: 16131 loss: 2.2895 loss_prob: 1.3948 loss_thr: 0.6629 loss_db: 0.2319 2022/10/25 21:45:51 - mmengine - INFO - Epoch(train) [185][10/63] lr: 2.7741e-03 eta: 14:29:50 time: 1.2557 data_time: 0.2214 memory: 16131 loss: 2.4150 loss_prob: 1.4834 loss_thr: 0.6859 loss_db: 0.2457 2022/10/25 21:45:54 - mmengine - INFO - Epoch(train) [185][15/63] lr: 2.7741e-03 eta: 14:29:50 time: 0.7606 data_time: 0.0060 memory: 16131 loss: 2.5111 loss_prob: 1.5436 loss_thr: 0.7089 loss_db: 0.2586 2022/10/25 21:45:59 - mmengine - INFO - Epoch(train) [185][20/63] lr: 2.7741e-03 eta: 14:29:44 time: 0.8621 data_time: 0.0085 memory: 16131 loss: 2.3916 loss_prob: 1.4480 loss_thr: 0.7043 loss_db: 0.2393 2022/10/25 21:46:04 - mmengine - INFO - Epoch(train) [185][25/63] lr: 2.7741e-03 eta: 14:29:44 time: 0.9771 data_time: 0.0380 memory: 16131 loss: 2.2352 loss_prob: 1.3562 loss_thr: 0.6615 loss_db: 0.2175 2022/10/25 21:46:07 - mmengine - INFO - Epoch(train) [185][30/63] lr: 2.7741e-03 eta: 14:29:37 time: 0.8315 data_time: 0.0349 memory: 16131 loss: 2.3576 loss_prob: 1.4317 loss_thr: 0.6952 loss_db: 0.2308 2022/10/25 21:46:13 - mmengine - INFO - Epoch(train) [185][35/63] lr: 2.7741e-03 eta: 14:29:37 time: 0.9235 data_time: 0.0074 memory: 16131 loss: 2.5150 loss_prob: 1.5389 loss_thr: 0.7250 loss_db: 0.2511 2022/10/25 21:46:16 - mmengine - INFO - Epoch(train) [185][40/63] lr: 2.7741e-03 eta: 14:29:29 time: 0.8098 data_time: 0.0099 memory: 16131 loss: 2.7128 loss_prob: 1.7256 loss_thr: 0.7029 loss_db: 0.2843 2022/10/25 21:46:19 - mmengine - INFO - Epoch(train) [185][45/63] lr: 2.7741e-03 eta: 14:29:29 time: 0.6458 data_time: 0.0096 memory: 16131 loss: 2.6318 loss_prob: 1.6574 loss_thr: 0.7034 loss_db: 0.2710 2022/10/25 21:46:22 - mmengine - INFO - Epoch(train) [185][50/63] lr: 2.7741e-03 eta: 14:29:11 time: 0.6452 data_time: 0.0249 memory: 16131 loss: 2.3881 loss_prob: 1.4498 loss_thr: 0.6994 loss_db: 0.2389 2022/10/25 21:46:25 - mmengine - INFO - Epoch(train) [185][55/63] lr: 2.7741e-03 eta: 14:29:11 time: 0.5511 data_time: 0.0237 memory: 16131 loss: 2.3182 loss_prob: 1.4036 loss_thr: 0.6826 loss_db: 0.2321 2022/10/25 21:46:29 - mmengine - INFO - Epoch(train) [185][60/63] lr: 2.7741e-03 eta: 14:28:54 time: 0.6573 data_time: 0.0081 memory: 16131 loss: 2.2190 loss_prob: 1.3265 loss_thr: 0.6752 loss_db: 0.2173 2022/10/25 21:46:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:46:35 - mmengine - INFO - Epoch(train) [186][5/63] lr: 2.7892e-03 eta: 14:28:54 time: 0.8727 data_time: 0.2337 memory: 16131 loss: 2.2494 loss_prob: 1.3576 loss_thr: 0.6730 loss_db: 0.2188 2022/10/25 21:46:39 - mmengine - INFO - Epoch(train) [186][10/63] lr: 2.7892e-03 eta: 14:28:34 time: 0.8862 data_time: 0.2349 memory: 16131 loss: 2.3935 loss_prob: 1.4733 loss_thr: 0.6871 loss_db: 0.2331 2022/10/25 21:46:46 - mmengine - INFO - Epoch(train) [186][15/63] lr: 2.7892e-03 eta: 14:28:34 time: 1.0639 data_time: 0.0102 memory: 16131 loss: 2.3640 loss_prob: 1.4423 loss_thr: 0.6908 loss_db: 0.2309 2022/10/25 21:46:51 - mmengine - INFO - Epoch(train) [186][20/63] lr: 2.7892e-03 eta: 14:28:49 time: 1.2405 data_time: 0.0113 memory: 16131 loss: 2.3790 loss_prob: 1.4523 loss_thr: 0.6913 loss_db: 0.2353 2022/10/25 21:46:57 - mmengine - INFO - Epoch(train) [186][25/63] lr: 2.7892e-03 eta: 14:28:49 time: 1.0951 data_time: 0.0279 memory: 16131 loss: 2.4044 loss_prob: 1.4875 loss_thr: 0.6754 loss_db: 0.2414 2022/10/25 21:47:01 - mmengine - INFO - Epoch(train) [186][30/63] lr: 2.7892e-03 eta: 14:28:48 time: 0.9306 data_time: 0.0348 memory: 16131 loss: 2.3938 loss_prob: 1.4763 loss_thr: 0.6737 loss_db: 0.2437 2022/10/25 21:47:03 - mmengine - INFO - Epoch(train) [186][35/63] lr: 2.7892e-03 eta: 14:28:48 time: 0.6702 data_time: 0.0238 memory: 16131 loss: 2.3418 loss_prob: 1.4177 loss_thr: 0.6890 loss_db: 0.2352 2022/10/25 21:47:06 - mmengine - INFO - Epoch(train) [186][40/63] lr: 2.7892e-03 eta: 14:28:27 time: 0.5856 data_time: 0.0138 memory: 16131 loss: 2.3678 loss_prob: 1.4089 loss_thr: 0.7269 loss_db: 0.2321 2022/10/25 21:47:09 - mmengine - INFO - Epoch(train) [186][45/63] lr: 2.7892e-03 eta: 14:28:27 time: 0.5874 data_time: 0.0067 memory: 16131 loss: 2.3463 loss_prob: 1.4159 loss_thr: 0.7004 loss_db: 0.2300 2022/10/25 21:47:14 - mmengine - INFO - Epoch(train) [186][50/63] lr: 2.7892e-03 eta: 14:28:15 time: 0.7395 data_time: 0.0186 memory: 16131 loss: 2.2889 loss_prob: 1.4018 loss_thr: 0.6620 loss_db: 0.2251 2022/10/25 21:47:17 - mmengine - INFO - Epoch(train) [186][55/63] lr: 2.7892e-03 eta: 14:28:15 time: 0.7853 data_time: 0.0232 memory: 16131 loss: 2.4201 loss_prob: 1.5028 loss_thr: 0.6733 loss_db: 0.2440 2022/10/25 21:47:22 - mmengine - INFO - Epoch(train) [186][60/63] lr: 2.7892e-03 eta: 14:28:07 time: 0.8284 data_time: 0.0099 memory: 16131 loss: 2.4807 loss_prob: 1.5509 loss_thr: 0.6763 loss_db: 0.2535 2022/10/25 21:47:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:47:30 - mmengine - INFO - Epoch(train) [187][5/63] lr: 2.8042e-03 eta: 14:28:07 time: 0.9459 data_time: 0.2036 memory: 16131 loss: 2.4106 loss_prob: 1.4911 loss_thr: 0.6750 loss_db: 0.2445 2022/10/25 21:47:34 - mmengine - INFO - Epoch(train) [187][10/63] lr: 2.8042e-03 eta: 14:27:56 time: 1.0572 data_time: 0.2093 memory: 16131 loss: 2.5284 loss_prob: 1.5752 loss_thr: 0.6986 loss_db: 0.2546 2022/10/25 21:47:37 - mmengine - INFO - Epoch(train) [187][15/63] lr: 2.8042e-03 eta: 14:27:56 time: 0.7138 data_time: 0.0150 memory: 16131 loss: 2.3906 loss_prob: 1.4727 loss_thr: 0.6804 loss_db: 0.2374 2022/10/25 21:47:43 - mmengine - INFO - Epoch(train) [187][20/63] lr: 2.8042e-03 eta: 14:27:52 time: 0.8818 data_time: 0.0090 memory: 16131 loss: 2.1784 loss_prob: 1.3106 loss_thr: 0.6574 loss_db: 0.2103 2022/10/25 21:47:48 - mmengine - INFO - Epoch(train) [187][25/63] lr: 2.8042e-03 eta: 14:27:52 time: 1.0828 data_time: 0.0303 memory: 16131 loss: 2.2678 loss_prob: 1.3643 loss_thr: 0.6831 loss_db: 0.2204 2022/10/25 21:47:52 - mmengine - INFO - Epoch(train) [187][30/63] lr: 2.8042e-03 eta: 14:27:50 time: 0.9336 data_time: 0.0291 memory: 16131 loss: 2.4451 loss_prob: 1.4902 loss_thr: 0.7086 loss_db: 0.2463 2022/10/25 21:47:55 - mmengine - INFO - Epoch(train) [187][35/63] lr: 2.8042e-03 eta: 14:27:50 time: 0.7370 data_time: 0.0098 memory: 16131 loss: 2.3175 loss_prob: 1.3950 loss_thr: 0.6933 loss_db: 0.2292 2022/10/25 21:47:58 - mmengine - INFO - Epoch(train) [187][40/63] lr: 2.8042e-03 eta: 14:27:30 time: 0.6037 data_time: 0.0099 memory: 16131 loss: 2.1835 loss_prob: 1.2962 loss_thr: 0.6759 loss_db: 0.2114 2022/10/25 21:48:01 - mmengine - INFO - Epoch(train) [187][45/63] lr: 2.8042e-03 eta: 14:27:30 time: 0.5421 data_time: 0.0128 memory: 16131 loss: 2.2233 loss_prob: 1.3273 loss_thr: 0.6749 loss_db: 0.2210 2022/10/25 21:48:04 - mmengine - INFO - Epoch(train) [187][50/63] lr: 2.8042e-03 eta: 14:27:10 time: 0.5841 data_time: 0.0315 memory: 16131 loss: 2.3725 loss_prob: 1.4517 loss_thr: 0.6823 loss_db: 0.2385 2022/10/25 21:48:11 - mmengine - INFO - Epoch(train) [187][55/63] lr: 2.8042e-03 eta: 14:27:10 time: 0.9962 data_time: 0.0267 memory: 16131 loss: 2.4582 loss_prob: 1.5154 loss_thr: 0.6948 loss_db: 0.2480 2022/10/25 21:48:18 - mmengine - INFO - Epoch(train) [187][60/63] lr: 2.8042e-03 eta: 14:27:32 time: 1.3815 data_time: 0.0137 memory: 16131 loss: 2.3551 loss_prob: 1.4257 loss_thr: 0.6959 loss_db: 0.2336 2022/10/25 21:48:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:48:27 - mmengine - INFO - Epoch(train) [188][5/63] lr: 2.8193e-03 eta: 14:27:32 time: 1.1410 data_time: 0.1968 memory: 16131 loss: 2.6071 loss_prob: 1.6012 loss_thr: 0.7385 loss_db: 0.2674 2022/10/25 21:48:30 - mmengine - INFO - Epoch(train) [188][10/63] lr: 2.8193e-03 eta: 14:27:17 time: 0.9730 data_time: 0.2138 memory: 16131 loss: 2.8412 loss_prob: 1.7960 loss_thr: 0.7420 loss_db: 0.3032 2022/10/25 21:48:36 - mmengine - INFO - Epoch(train) [188][15/63] lr: 2.8193e-03 eta: 14:27:17 time: 0.9356 data_time: 0.0220 memory: 16131 loss: 2.6763 loss_prob: 1.6759 loss_thr: 0.7240 loss_db: 0.2763 2022/10/25 21:48:41 - mmengine - INFO - Epoch(train) [188][20/63] lr: 2.8193e-03 eta: 14:27:24 time: 1.1021 data_time: 0.0084 memory: 16131 loss: 2.4943 loss_prob: 1.5343 loss_thr: 0.7080 loss_db: 0.2519 2022/10/25 21:48:45 - mmengine - INFO - Epoch(train) [188][25/63] lr: 2.8193e-03 eta: 14:27:24 time: 0.8966 data_time: 0.0204 memory: 16131 loss: 2.5252 loss_prob: 1.5658 loss_thr: 0.7002 loss_db: 0.2591 2022/10/25 21:48:50 - mmengine - INFO - Epoch(train) [188][30/63] lr: 2.8193e-03 eta: 14:27:21 time: 0.9008 data_time: 0.0472 memory: 16131 loss: 2.6120 loss_prob: 1.6313 loss_thr: 0.7057 loss_db: 0.2750 2022/10/25 21:48:53 - mmengine - INFO - Epoch(train) [188][35/63] lr: 2.8193e-03 eta: 14:27:21 time: 0.7572 data_time: 0.0372 memory: 16131 loss: 2.5415 loss_prob: 1.5761 loss_thr: 0.7039 loss_db: 0.2615 2022/10/25 21:49:00 - mmengine - INFO - Epoch(train) [188][40/63] lr: 2.8193e-03 eta: 14:27:21 time: 0.9650 data_time: 0.0095 memory: 16131 loss: 2.5959 loss_prob: 1.6071 loss_thr: 0.7245 loss_db: 0.2643 2022/10/25 21:49:04 - mmengine - INFO - Epoch(train) [188][45/63] lr: 2.8193e-03 eta: 14:27:21 time: 1.1036 data_time: 0.0091 memory: 16131 loss: 2.5673 loss_prob: 1.5885 loss_thr: 0.7101 loss_db: 0.2686 2022/10/25 21:49:08 - mmengine - INFO - Epoch(train) [188][50/63] lr: 2.8193e-03 eta: 14:27:13 time: 0.8230 data_time: 0.0114 memory: 16131 loss: 2.2915 loss_prob: 1.3926 loss_thr: 0.6694 loss_db: 0.2294 2022/10/25 21:49:12 - mmengine - INFO - Epoch(train) [188][55/63] lr: 2.8193e-03 eta: 14:27:13 time: 0.8238 data_time: 0.0243 memory: 16131 loss: 2.3303 loss_prob: 1.4261 loss_thr: 0.6691 loss_db: 0.2351 2022/10/25 21:49:15 - mmengine - INFO - Epoch(train) [188][60/63] lr: 2.8193e-03 eta: 14:26:58 time: 0.6831 data_time: 0.0194 memory: 16131 loss: 2.4387 loss_prob: 1.5135 loss_thr: 0.6747 loss_db: 0.2506 2022/10/25 21:49:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:49:25 - mmengine - INFO - Epoch(train) [189][5/63] lr: 2.8343e-03 eta: 14:26:58 time: 1.1120 data_time: 0.2238 memory: 16131 loss: 2.1930 loss_prob: 1.3263 loss_thr: 0.6517 loss_db: 0.2149 2022/10/25 21:49:31 - mmengine - INFO - Epoch(train) [189][10/63] lr: 2.8343e-03 eta: 14:27:09 time: 1.4656 data_time: 0.2223 memory: 16131 loss: 2.1653 loss_prob: 1.3040 loss_thr: 0.6439 loss_db: 0.2174 2022/10/25 21:49:37 - mmengine - INFO - Epoch(train) [189][15/63] lr: 2.8343e-03 eta: 14:27:09 time: 1.2477 data_time: 0.0060 memory: 16131 loss: 2.1874 loss_prob: 1.3188 loss_thr: 0.6510 loss_db: 0.2176 2022/10/25 21:49:42 - mmengine - INFO - Epoch(train) [189][20/63] lr: 2.8343e-03 eta: 14:27:14 time: 1.0688 data_time: 0.0054 memory: 16131 loss: 2.2778 loss_prob: 1.3786 loss_thr: 0.6704 loss_db: 0.2288 2022/10/25 21:49:47 - mmengine - INFO - Epoch(train) [189][25/63] lr: 2.8343e-03 eta: 14:27:14 time: 0.9996 data_time: 0.0688 memory: 16131 loss: 2.2697 loss_prob: 1.3411 loss_thr: 0.7008 loss_db: 0.2277 2022/10/25 21:49:51 - mmengine - INFO - Epoch(train) [189][30/63] lr: 2.8343e-03 eta: 14:27:15 time: 0.9854 data_time: 0.0705 memory: 16131 loss: 2.0944 loss_prob: 1.2154 loss_thr: 0.6772 loss_db: 0.2019 2022/10/25 21:49:55 - mmengine - INFO - Epoch(train) [189][35/63] lr: 2.8343e-03 eta: 14:27:15 time: 0.8321 data_time: 0.0082 memory: 16131 loss: 2.2937 loss_prob: 1.3950 loss_thr: 0.6726 loss_db: 0.2261 2022/10/25 21:50:02 - mmengine - INFO - Epoch(train) [189][40/63] lr: 2.8343e-03 eta: 14:27:17 time: 1.0085 data_time: 0.0092 memory: 16131 loss: 2.4403 loss_prob: 1.5034 loss_thr: 0.6888 loss_db: 0.2481 2022/10/25 21:50:08 - mmengine - INFO - Epoch(train) [189][45/63] lr: 2.8343e-03 eta: 14:27:17 time: 1.2234 data_time: 0.0089 memory: 16131 loss: 2.3831 loss_prob: 1.4463 loss_thr: 0.6913 loss_db: 0.2454 2022/10/25 21:50:12 - mmengine - INFO - Epoch(train) [189][50/63] lr: 2.8343e-03 eta: 14:27:23 time: 1.0860 data_time: 0.0254 memory: 16131 loss: 2.4096 loss_prob: 1.4649 loss_thr: 0.6995 loss_db: 0.2452 2022/10/25 21:50:16 - mmengine - INFO - Epoch(train) [189][55/63] lr: 2.8343e-03 eta: 14:27:23 time: 0.8422 data_time: 0.0248 memory: 16131 loss: 2.4225 loss_prob: 1.4918 loss_thr: 0.6889 loss_db: 0.2418 2022/10/25 21:50:19 - mmengine - INFO - Epoch(train) [189][60/63] lr: 2.8343e-03 eta: 14:27:07 time: 0.6693 data_time: 0.0072 memory: 16131 loss: 2.4660 loss_prob: 1.5301 loss_thr: 0.6889 loss_db: 0.2470 2022/10/25 21:50:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:50:28 - mmengine - INFO - Epoch(train) [190][5/63] lr: 2.8494e-03 eta: 14:27:07 time: 1.0193 data_time: 0.2359 memory: 16131 loss: 2.4032 loss_prob: 1.4835 loss_thr: 0.6804 loss_db: 0.2394 2022/10/25 21:50:35 - mmengine - INFO - Epoch(train) [190][10/63] lr: 2.8494e-03 eta: 14:27:18 time: 1.4564 data_time: 0.2354 memory: 16131 loss: 2.2647 loss_prob: 1.3719 loss_thr: 0.6721 loss_db: 0.2207 2022/10/25 21:50:43 - mmengine - INFO - Epoch(train) [190][15/63] lr: 2.8494e-03 eta: 14:27:18 time: 1.4721 data_time: 0.0053 memory: 16131 loss: 2.1376 loss_prob: 1.2794 loss_thr: 0.6516 loss_db: 0.2065 2022/10/25 21:50:50 - mmengine - INFO - Epoch(train) [190][20/63] lr: 2.8494e-03 eta: 14:27:44 time: 1.4540 data_time: 0.0059 memory: 16131 loss: 2.0528 loss_prob: 1.2204 loss_thr: 0.6353 loss_db: 0.1971 2022/10/25 21:50:54 - mmengine - INFO - Epoch(train) [190][25/63] lr: 2.8494e-03 eta: 14:27:44 time: 1.0877 data_time: 0.0129 memory: 16131 loss: 2.2733 loss_prob: 1.3749 loss_thr: 0.6755 loss_db: 0.2228 2022/10/25 21:50:58 - mmengine - INFO - Epoch(train) [190][30/63] lr: 2.8494e-03 eta: 14:27:34 time: 0.7944 data_time: 0.0614 memory: 16131 loss: 2.3360 loss_prob: 1.4198 loss_thr: 0.6889 loss_db: 0.2273 2022/10/25 21:51:01 - mmengine - INFO - Epoch(train) [190][35/63] lr: 2.8494e-03 eta: 14:27:34 time: 0.7012 data_time: 0.0539 memory: 16131 loss: 2.1752 loss_prob: 1.2984 loss_thr: 0.6664 loss_db: 0.2103 2022/10/25 21:51:06 - mmengine - INFO - Epoch(train) [190][40/63] lr: 2.8494e-03 eta: 14:27:25 time: 0.8076 data_time: 0.0074 memory: 16131 loss: 2.2718 loss_prob: 1.3724 loss_thr: 0.6731 loss_db: 0.2264 2022/10/25 21:51:09 - mmengine - INFO - Epoch(train) [190][45/63] lr: 2.8494e-03 eta: 14:27:25 time: 0.8354 data_time: 0.0130 memory: 16131 loss: 2.1781 loss_prob: 1.3086 loss_thr: 0.6504 loss_db: 0.2190 2022/10/25 21:51:12 - mmengine - INFO - Epoch(train) [190][50/63] lr: 2.8494e-03 eta: 14:27:07 time: 0.6267 data_time: 0.0227 memory: 16131 loss: 2.5011 loss_prob: 1.5441 loss_thr: 0.7001 loss_db: 0.2569 2022/10/25 21:51:17 - mmengine - INFO - Epoch(train) [190][55/63] lr: 2.8494e-03 eta: 14:27:07 time: 0.7535 data_time: 0.0251 memory: 16131 loss: 2.6112 loss_prob: 1.6284 loss_thr: 0.7185 loss_db: 0.2643 2022/10/25 21:51:22 - mmengine - INFO - Epoch(train) [190][60/63] lr: 2.8494e-03 eta: 14:27:07 time: 0.9629 data_time: 0.0189 memory: 16131 loss: 2.3083 loss_prob: 1.3948 loss_thr: 0.6877 loss_db: 0.2257 2022/10/25 21:51:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:51:31 - mmengine - INFO - Epoch(train) [191][5/63] lr: 2.8645e-03 eta: 14:27:07 time: 1.1801 data_time: 0.2262 memory: 16131 loss: 2.4544 loss_prob: 1.4855 loss_thr: 0.7268 loss_db: 0.2422 2022/10/25 21:51:34 - mmengine - INFO - Epoch(train) [191][10/63] lr: 2.8645e-03 eta: 14:26:54 time: 1.0165 data_time: 0.2329 memory: 16131 loss: 2.3338 loss_prob: 1.3966 loss_thr: 0.7046 loss_db: 0.2326 2022/10/25 21:51:37 - mmengine - INFO - Epoch(train) [191][15/63] lr: 2.8645e-03 eta: 14:26:54 time: 0.5512 data_time: 0.0175 memory: 16131 loss: 2.3844 loss_prob: 1.4550 loss_thr: 0.6833 loss_db: 0.2461 2022/10/25 21:51:41 - mmengine - INFO - Epoch(train) [191][20/63] lr: 2.8645e-03 eta: 14:26:40 time: 0.7184 data_time: 0.0114 memory: 16131 loss: 2.3557 loss_prob: 1.4439 loss_thr: 0.6785 loss_db: 0.2333 2022/10/25 21:51:47 - mmengine - INFO - Epoch(train) [191][25/63] lr: 2.8645e-03 eta: 14:26:40 time: 1.0147 data_time: 0.0289 memory: 16131 loss: 2.3174 loss_prob: 1.4075 loss_thr: 0.6797 loss_db: 0.2303 2022/10/25 21:51:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:51:49 - mmengine - INFO - Epoch(train) [191][30/63] lr: 2.8645e-03 eta: 14:26:32 time: 0.8179 data_time: 0.0302 memory: 16131 loss: 2.3634 loss_prob: 1.4464 loss_thr: 0.6770 loss_db: 0.2399 2022/10/25 21:51:52 - mmengine - INFO - Epoch(train) [191][35/63] lr: 2.8645e-03 eta: 14:26:32 time: 0.5123 data_time: 0.0149 memory: 16131 loss: 2.2966 loss_prob: 1.3942 loss_thr: 0.6740 loss_db: 0.2284 2022/10/25 21:51:54 - mmengine - INFO - Epoch(train) [191][40/63] lr: 2.8645e-03 eta: 14:26:07 time: 0.5071 data_time: 0.0156 memory: 16131 loss: 2.3121 loss_prob: 1.4054 loss_thr: 0.6740 loss_db: 0.2327 2022/10/25 21:51:57 - mmengine - INFO - Epoch(train) [191][45/63] lr: 2.8645e-03 eta: 14:26:07 time: 0.5079 data_time: 0.0127 memory: 16131 loss: 2.4464 loss_prob: 1.4945 loss_thr: 0.7041 loss_db: 0.2478 2022/10/25 21:51:59 - mmengine - INFO - Epoch(train) [191][50/63] lr: 2.8645e-03 eta: 14:25:43 time: 0.5080 data_time: 0.0204 memory: 16131 loss: 2.3349 loss_prob: 1.4070 loss_thr: 0.6974 loss_db: 0.2305 2022/10/25 21:52:02 - mmengine - INFO - Epoch(train) [191][55/63] lr: 2.8645e-03 eta: 14:25:43 time: 0.5439 data_time: 0.0266 memory: 16131 loss: 2.2317 loss_prob: 1.3532 loss_thr: 0.6567 loss_db: 0.2217 2022/10/25 21:52:05 - mmengine - INFO - Epoch(train) [191][60/63] lr: 2.8645e-03 eta: 14:25:21 time: 0.5618 data_time: 0.0169 memory: 16131 loss: 2.4309 loss_prob: 1.5165 loss_thr: 0.6654 loss_db: 0.2490 2022/10/25 21:52:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:52:11 - mmengine - INFO - Epoch(train) [192][5/63] lr: 2.8795e-03 eta: 14:25:21 time: 0.7221 data_time: 0.1838 memory: 16131 loss: 2.3672 loss_prob: 1.4545 loss_thr: 0.6621 loss_db: 0.2506 2022/10/25 21:52:17 - mmengine - INFO - Epoch(train) [192][10/63] lr: 2.8795e-03 eta: 14:25:08 time: 1.0077 data_time: 0.1834 memory: 16131 loss: 2.5339 loss_prob: 1.6139 loss_thr: 0.6439 loss_db: 0.2761 2022/10/25 21:52:20 - mmengine - INFO - Epoch(train) [192][15/63] lr: 2.8795e-03 eta: 14:25:08 time: 0.8709 data_time: 0.0248 memory: 16131 loss: 2.6036 loss_prob: 1.6490 loss_thr: 0.6768 loss_db: 0.2778 2022/10/25 21:52:24 - mmengine - INFO - Epoch(train) [192][20/63] lr: 2.8795e-03 eta: 14:24:55 time: 0.7270 data_time: 0.0238 memory: 16131 loss: 2.5676 loss_prob: 1.5819 loss_thr: 0.7188 loss_db: 0.2670 2022/10/25 21:52:27 - mmengine - INFO - Epoch(train) [192][25/63] lr: 2.8795e-03 eta: 14:24:55 time: 0.7488 data_time: 0.0289 memory: 16131 loss: 2.4460 loss_prob: 1.4945 loss_thr: 0.7052 loss_db: 0.2463 2022/10/25 21:52:34 - mmengine - INFO - Epoch(train) [192][30/63] lr: 2.8795e-03 eta: 14:24:55 time: 0.9820 data_time: 0.0283 memory: 16131 loss: 2.3317 loss_prob: 1.4116 loss_thr: 0.6846 loss_db: 0.2354 2022/10/25 21:52:37 - mmengine - INFO - Epoch(train) [192][35/63] lr: 2.8795e-03 eta: 14:24:55 time: 1.0069 data_time: 0.0057 memory: 16131 loss: 2.2545 loss_prob: 1.3448 loss_thr: 0.6877 loss_db: 0.2221 2022/10/25 21:52:43 - mmengine - INFO - Epoch(train) [192][40/63] lr: 2.8795e-03 eta: 14:24:52 time: 0.9087 data_time: 0.0205 memory: 16131 loss: 2.3647 loss_prob: 1.4180 loss_thr: 0.7166 loss_db: 0.2301 2022/10/25 21:52:46 - mmengine - INFO - Epoch(train) [192][45/63] lr: 2.8795e-03 eta: 14:24:52 time: 0.8719 data_time: 0.0218 memory: 16131 loss: 2.3773 loss_prob: 1.4277 loss_thr: 0.7166 loss_db: 0.2329 2022/10/25 21:52:49 - mmengine - INFO - Epoch(train) [192][50/63] lr: 2.8795e-03 eta: 14:24:33 time: 0.6097 data_time: 0.0208 memory: 16131 loss: 2.3075 loss_prob: 1.3991 loss_thr: 0.6784 loss_db: 0.2300 2022/10/25 21:52:54 - mmengine - INFO - Epoch(train) [192][55/63] lr: 2.8795e-03 eta: 14:24:33 time: 0.7494 data_time: 0.0207 memory: 16131 loss: 2.1595 loss_prob: 1.3008 loss_thr: 0.6476 loss_db: 0.2111 2022/10/25 21:52:58 - mmengine - INFO - Epoch(train) [192][60/63] lr: 2.8795e-03 eta: 14:24:31 time: 0.9292 data_time: 0.0087 memory: 16131 loss: 2.1858 loss_prob: 1.3136 loss_thr: 0.6620 loss_db: 0.2102 2022/10/25 21:53:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:53:06 - mmengine - INFO - Epoch(train) [193][5/63] lr: 2.8946e-03 eta: 14:24:31 time: 1.0966 data_time: 0.2065 memory: 16131 loss: 2.3000 loss_prob: 1.3861 loss_thr: 0.6900 loss_db: 0.2239 2022/10/25 21:53:12 - mmengine - INFO - Epoch(train) [193][10/63] lr: 2.8946e-03 eta: 14:24:29 time: 1.2273 data_time: 0.2034 memory: 16131 loss: 2.2793 loss_prob: 1.3619 loss_thr: 0.6919 loss_db: 0.2256 2022/10/25 21:53:15 - mmengine - INFO - Epoch(train) [193][15/63] lr: 2.8946e-03 eta: 14:24:29 time: 0.8885 data_time: 0.0068 memory: 16131 loss: 2.3120 loss_prob: 1.3975 loss_thr: 0.6846 loss_db: 0.2299 2022/10/25 21:53:22 - mmengine - INFO - Epoch(train) [193][20/63] lr: 2.8946e-03 eta: 14:24:28 time: 0.9517 data_time: 0.0079 memory: 16131 loss: 2.2837 loss_prob: 1.3785 loss_thr: 0.6772 loss_db: 0.2280 2022/10/25 21:53:26 - mmengine - INFO - Epoch(train) [193][25/63] lr: 2.8946e-03 eta: 14:24:28 time: 1.0478 data_time: 0.0171 memory: 16131 loss: 2.3120 loss_prob: 1.4030 loss_thr: 0.6776 loss_db: 0.2314 2022/10/25 21:53:33 - mmengine - INFO - Epoch(train) [193][30/63] lr: 2.8946e-03 eta: 14:24:37 time: 1.1559 data_time: 0.0610 memory: 16131 loss: 2.2537 loss_prob: 1.3777 loss_thr: 0.6537 loss_db: 0.2223 2022/10/25 21:53:39 - mmengine - INFO - Epoch(train) [193][35/63] lr: 2.8946e-03 eta: 14:24:37 time: 1.3364 data_time: 0.0536 memory: 16131 loss: 2.5694 loss_prob: 1.6273 loss_thr: 0.6707 loss_db: 0.2715 2022/10/25 21:53:42 - mmengine - INFO - Epoch(train) [193][40/63] lr: 2.8946e-03 eta: 14:24:29 time: 0.8222 data_time: 0.0087 memory: 16131 loss: 2.8281 loss_prob: 1.8418 loss_thr: 0.6786 loss_db: 0.3077 2022/10/25 21:53:48 - mmengine - INFO - Epoch(train) [193][45/63] lr: 2.8946e-03 eta: 14:24:29 time: 0.9211 data_time: 0.0134 memory: 16131 loss: 2.5569 loss_prob: 1.6088 loss_thr: 0.6847 loss_db: 0.2634 2022/10/25 21:53:54 - mmengine - INFO - Epoch(train) [193][50/63] lr: 2.8946e-03 eta: 14:24:45 time: 1.2653 data_time: 0.0241 memory: 16131 loss: 2.3659 loss_prob: 1.4406 loss_thr: 0.6884 loss_db: 0.2369 2022/10/25 21:53:57 - mmengine - INFO - Epoch(train) [193][55/63] lr: 2.8946e-03 eta: 14:24:45 time: 0.9201 data_time: 0.0288 memory: 16131 loss: 2.3226 loss_prob: 1.4021 loss_thr: 0.6892 loss_db: 0.2313 2022/10/25 21:54:00 - mmengine - INFO - Epoch(train) [193][60/63] lr: 2.8946e-03 eta: 14:24:24 time: 0.5849 data_time: 0.0198 memory: 16131 loss: 2.2349 loss_prob: 1.3372 loss_thr: 0.6767 loss_db: 0.2210 2022/10/25 21:54:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:54:11 - mmengine - INFO - Epoch(train) [194][5/63] lr: 2.9096e-03 eta: 14:24:24 time: 1.2077 data_time: 0.1657 memory: 16131 loss: 2.3818 loss_prob: 1.4596 loss_thr: 0.6802 loss_db: 0.2421 2022/10/25 21:54:16 - mmengine - INFO - Epoch(train) [194][10/63] lr: 2.9096e-03 eta: 14:24:30 time: 1.3690 data_time: 0.1652 memory: 16131 loss: 2.1941 loss_prob: 1.3184 loss_thr: 0.6622 loss_db: 0.2135 2022/10/25 21:54:18 - mmengine - INFO - Epoch(train) [194][15/63] lr: 2.9096e-03 eta: 14:24:30 time: 0.7184 data_time: 0.0116 memory: 16131 loss: 2.1607 loss_prob: 1.2889 loss_thr: 0.6664 loss_db: 0.2055 2022/10/25 21:54:24 - mmengine - INFO - Epoch(train) [194][20/63] lr: 2.9096e-03 eta: 14:24:24 time: 0.8610 data_time: 0.0141 memory: 16131 loss: 2.3751 loss_prob: 1.4438 loss_thr: 0.6983 loss_db: 0.2330 2022/10/25 21:54:27 - mmengine - INFO - Epoch(train) [194][25/63] lr: 2.9096e-03 eta: 14:24:24 time: 0.8784 data_time: 0.0093 memory: 16131 loss: 2.4182 loss_prob: 1.4796 loss_thr: 0.6957 loss_db: 0.2430 2022/10/25 21:54:35 - mmengine - INFO - Epoch(train) [194][30/63] lr: 2.9096e-03 eta: 14:24:27 time: 1.0467 data_time: 0.0324 memory: 16131 loss: 2.3987 loss_prob: 1.4740 loss_thr: 0.6837 loss_db: 0.2410 2022/10/25 21:54:38 - mmengine - INFO - Epoch(train) [194][35/63] lr: 2.9096e-03 eta: 14:24:27 time: 1.1245 data_time: 0.0310 memory: 16131 loss: 2.3847 loss_prob: 1.4545 loss_thr: 0.6950 loss_db: 0.2352 2022/10/25 21:54:42 - mmengine - INFO - Epoch(train) [194][40/63] lr: 2.9096e-03 eta: 14:24:13 time: 0.7037 data_time: 0.0186 memory: 16131 loss: 2.4056 loss_prob: 1.4505 loss_thr: 0.7176 loss_db: 0.2375 2022/10/25 21:54:44 - mmengine - INFO - Epoch(train) [194][45/63] lr: 2.9096e-03 eta: 14:24:13 time: 0.5807 data_time: 0.0194 memory: 16131 loss: 2.4204 loss_prob: 1.4607 loss_thr: 0.7150 loss_db: 0.2447 2022/10/25 21:54:47 - mmengine - INFO - Epoch(train) [194][50/63] lr: 2.9096e-03 eta: 14:23:52 time: 0.5721 data_time: 0.0201 memory: 16131 loss: 2.2977 loss_prob: 1.3760 loss_thr: 0.6940 loss_db: 0.2277 2022/10/25 21:54:50 - mmengine - INFO - Epoch(train) [194][55/63] lr: 2.9096e-03 eta: 14:23:52 time: 0.6009 data_time: 0.0252 memory: 16131 loss: 2.2293 loss_prob: 1.3294 loss_thr: 0.6878 loss_db: 0.2121 2022/10/25 21:54:53 - mmengine - INFO - Epoch(train) [194][60/63] lr: 2.9096e-03 eta: 14:23:32 time: 0.5859 data_time: 0.0175 memory: 16131 loss: 2.3198 loss_prob: 1.3897 loss_thr: 0.7030 loss_db: 0.2271 2022/10/25 21:54:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:55:05 - mmengine - INFO - Epoch(train) [195][5/63] lr: 2.9247e-03 eta: 14:23:32 time: 1.2856 data_time: 0.2087 memory: 16131 loss: 2.4643 loss_prob: 1.5348 loss_thr: 0.6746 loss_db: 0.2549 2022/10/25 21:55:09 - mmengine - INFO - Epoch(train) [195][10/63] lr: 2.9247e-03 eta: 14:23:43 time: 1.4776 data_time: 0.2056 memory: 16131 loss: 2.4872 loss_prob: 1.5325 loss_thr: 0.7003 loss_db: 0.2544 2022/10/25 21:55:17 - mmengine - INFO - Epoch(train) [195][15/63] lr: 2.9247e-03 eta: 14:23:43 time: 1.1870 data_time: 0.0085 memory: 16131 loss: 2.4174 loss_prob: 1.4768 loss_thr: 0.6937 loss_db: 0.2468 2022/10/25 21:55:24 - mmengine - INFO - Epoch(train) [195][20/63] lr: 2.9247e-03 eta: 14:24:06 time: 1.4239 data_time: 0.0136 memory: 16131 loss: 2.4445 loss_prob: 1.5162 loss_thr: 0.6761 loss_db: 0.2522 2022/10/25 21:55:28 - mmengine - INFO - Epoch(train) [195][25/63] lr: 2.9247e-03 eta: 14:24:06 time: 1.0833 data_time: 0.0213 memory: 16131 loss: 2.5190 loss_prob: 1.5563 loss_thr: 0.7044 loss_db: 0.2583 2022/10/25 21:55:35 - mmengine - INFO - Epoch(train) [195][30/63] lr: 2.9247e-03 eta: 14:24:17 time: 1.1841 data_time: 0.0346 memory: 16131 loss: 2.5083 loss_prob: 1.5710 loss_thr: 0.6835 loss_db: 0.2538 2022/10/25 21:55:43 - mmengine - INFO - Epoch(train) [195][35/63] lr: 2.9247e-03 eta: 14:24:17 time: 1.5539 data_time: 0.0253 memory: 16131 loss: 2.4431 loss_prob: 1.5237 loss_thr: 0.6785 loss_db: 0.2409 2022/10/25 21:55:49 - mmengine - INFO - Epoch(train) [195][40/63] lr: 2.9247e-03 eta: 14:24:38 time: 1.3828 data_time: 0.0083 memory: 16131 loss: 2.4522 loss_prob: 1.5111 loss_thr: 0.7004 loss_db: 0.2407 2022/10/25 21:55:55 - mmengine - INFO - Epoch(train) [195][45/63] lr: 2.9247e-03 eta: 14:24:38 time: 1.1663 data_time: 0.0140 memory: 16131 loss: 2.3721 loss_prob: 1.4592 loss_thr: 0.6823 loss_db: 0.2306 2022/10/25 21:55:58 - mmengine - INFO - Epoch(train) [195][50/63] lr: 2.9247e-03 eta: 14:24:31 time: 0.8372 data_time: 0.0313 memory: 16131 loss: 2.2792 loss_prob: 1.3933 loss_thr: 0.6622 loss_db: 0.2237 2022/10/25 21:56:00 - mmengine - INFO - Epoch(train) [195][55/63] lr: 2.9247e-03 eta: 14:24:31 time: 0.5502 data_time: 0.0286 memory: 16131 loss: 2.2187 loss_prob: 1.3397 loss_thr: 0.6623 loss_db: 0.2167 2022/10/25 21:56:04 - mmengine - INFO - Epoch(train) [195][60/63] lr: 2.9247e-03 eta: 14:24:13 time: 0.6358 data_time: 0.0084 memory: 16131 loss: 2.3205 loss_prob: 1.3917 loss_thr: 0.7035 loss_db: 0.2253 2022/10/25 21:56:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:56:11 - mmengine - INFO - Epoch(train) [196][5/63] lr: 2.9398e-03 eta: 14:24:13 time: 0.8702 data_time: 0.2408 memory: 16131 loss: 2.4895 loss_prob: 1.5220 loss_thr: 0.7212 loss_db: 0.2463 2022/10/25 21:56:17 - mmengine - INFO - Epoch(train) [196][10/63] lr: 2.9398e-03 eta: 14:24:05 time: 1.1163 data_time: 0.2375 memory: 16131 loss: 2.4063 loss_prob: 1.4765 loss_thr: 0.6914 loss_db: 0.2385 2022/10/25 21:56:22 - mmengine - INFO - Epoch(train) [196][15/63] lr: 2.9398e-03 eta: 14:24:05 time: 1.1092 data_time: 0.0062 memory: 16131 loss: 2.3455 loss_prob: 1.4194 loss_thr: 0.6945 loss_db: 0.2316 2022/10/25 21:56:27 - mmengine - INFO - Epoch(train) [196][20/63] lr: 2.9398e-03 eta: 14:24:06 time: 0.9892 data_time: 0.0076 memory: 16131 loss: 2.4194 loss_prob: 1.4673 loss_thr: 0.7107 loss_db: 0.2414 2022/10/25 21:56:35 - mmengine - INFO - Epoch(train) [196][25/63] lr: 2.9398e-03 eta: 14:24:06 time: 1.2792 data_time: 0.0387 memory: 16131 loss: 2.7192 loss_prob: 1.7098 loss_thr: 0.7268 loss_db: 0.2826 2022/10/25 21:56:40 - mmengine - INFO - Epoch(train) [196][30/63] lr: 2.9398e-03 eta: 14:24:25 time: 1.3584 data_time: 0.0359 memory: 16131 loss: 2.7185 loss_prob: 1.7180 loss_thr: 0.7198 loss_db: 0.2807 2022/10/25 21:56:44 - mmengine - INFO - Epoch(train) [196][35/63] lr: 2.9398e-03 eta: 14:24:25 time: 0.9751 data_time: 0.0062 memory: 16131 loss: 2.5902 loss_prob: 1.6235 loss_thr: 0.7005 loss_db: 0.2662 2022/10/25 21:56:48 - mmengine - INFO - Epoch(train) [196][40/63] lr: 2.9398e-03 eta: 14:24:17 time: 0.8179 data_time: 0.0078 memory: 16131 loss: 2.5990 loss_prob: 1.6276 loss_thr: 0.6990 loss_db: 0.2724 2022/10/25 21:56:54 - mmengine - INFO - Epoch(train) [196][45/63] lr: 2.9398e-03 eta: 14:24:17 time: 1.0127 data_time: 0.0083 memory: 16131 loss: 2.5897 loss_prob: 1.6183 loss_thr: 0.7041 loss_db: 0.2673 2022/10/25 21:56:58 - mmengine - INFO - Epoch(train) [196][50/63] lr: 2.9398e-03 eta: 14:24:15 time: 0.9415 data_time: 0.0247 memory: 16131 loss: 2.6137 loss_prob: 1.6272 loss_thr: 0.7195 loss_db: 0.2669 2022/10/25 21:57:01 - mmengine - INFO - Epoch(train) [196][55/63] lr: 2.9398e-03 eta: 14:24:15 time: 0.6112 data_time: 0.0234 memory: 16131 loss: 2.4550 loss_prob: 1.5188 loss_thr: 0.6889 loss_db: 0.2473 2022/10/25 21:57:03 - mmengine - INFO - Epoch(train) [196][60/63] lr: 2.9398e-03 eta: 14:23:53 time: 0.5457 data_time: 0.0052 memory: 16131 loss: 2.4351 loss_prob: 1.5108 loss_thr: 0.6794 loss_db: 0.2448 2022/10/25 21:57:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:57:12 - mmengine - INFO - Epoch(train) [197][5/63] lr: 2.9548e-03 eta: 14:23:53 time: 0.9709 data_time: 0.2060 memory: 16131 loss: 2.4128 loss_prob: 1.4854 loss_thr: 0.6815 loss_db: 0.2458 2022/10/25 21:57:15 - mmengine - INFO - Epoch(train) [197][10/63] lr: 2.9548e-03 eta: 14:23:43 time: 1.0821 data_time: 0.2122 memory: 16131 loss: 2.4534 loss_prob: 1.5414 loss_thr: 0.6570 loss_db: 0.2551 2022/10/25 21:57:21 - mmengine - INFO - Epoch(train) [197][15/63] lr: 2.9548e-03 eta: 14:23:43 time: 0.8656 data_time: 0.0129 memory: 16131 loss: 2.6918 loss_prob: 1.6977 loss_thr: 0.7055 loss_db: 0.2886 2022/10/25 21:57:26 - mmengine - INFO - Epoch(train) [197][20/63] lr: 2.9548e-03 eta: 14:23:45 time: 1.0298 data_time: 0.0088 memory: 16131 loss: 2.6198 loss_prob: 1.6360 loss_thr: 0.7054 loss_db: 0.2783 2022/10/25 21:57:32 - mmengine - INFO - Epoch(train) [197][25/63] lr: 2.9548e-03 eta: 14:23:45 time: 1.1858 data_time: 0.0181 memory: 16131 loss: 2.5370 loss_prob: 1.5620 loss_thr: 0.7167 loss_db: 0.2582 2022/10/25 21:57:37 - mmengine - INFO - Epoch(train) [197][30/63] lr: 2.9548e-03 eta: 14:23:51 time: 1.0900 data_time: 0.0438 memory: 16131 loss: 2.4752 loss_prob: 1.5159 loss_thr: 0.7075 loss_db: 0.2518 2022/10/25 21:57:42 - mmengine - INFO - Epoch(train) [197][35/63] lr: 2.9548e-03 eta: 14:23:51 time: 0.9381 data_time: 0.0344 memory: 16131 loss: 2.6224 loss_prob: 1.6581 loss_thr: 0.6901 loss_db: 0.2742 2022/10/25 21:57:46 - mmengine - INFO - Epoch(train) [197][40/63] lr: 2.9548e-03 eta: 14:23:50 time: 0.9548 data_time: 0.0057 memory: 16131 loss: 2.6356 loss_prob: 1.6729 loss_thr: 0.6866 loss_db: 0.2760 2022/10/25 21:57:49 - mmengine - INFO - Epoch(train) [197][45/63] lr: 2.9548e-03 eta: 14:23:50 time: 0.7328 data_time: 0.0067 memory: 16131 loss: 2.4890 loss_prob: 1.5481 loss_thr: 0.6890 loss_db: 0.2519 2022/10/25 21:57:52 - mmengine - INFO - Epoch(train) [197][50/63] lr: 2.9548e-03 eta: 14:23:31 time: 0.6142 data_time: 0.0262 memory: 16131 loss: 2.6792 loss_prob: 1.6856 loss_thr: 0.7125 loss_db: 0.2812 2022/10/25 21:57:55 - mmengine - INFO - Epoch(train) [197][55/63] lr: 2.9548e-03 eta: 14:23:31 time: 0.5974 data_time: 0.0259 memory: 16131 loss: 2.5775 loss_prob: 1.6129 loss_thr: 0.6904 loss_db: 0.2741 2022/10/25 21:57:58 - mmengine - INFO - Epoch(train) [197][60/63] lr: 2.9548e-03 eta: 14:23:11 time: 0.5928 data_time: 0.0062 memory: 16131 loss: 2.4790 loss_prob: 1.5314 loss_thr: 0.6913 loss_db: 0.2563 2022/10/25 21:58:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:58:05 - mmengine - INFO - Epoch(train) [198][5/63] lr: 2.9699e-03 eta: 14:23:11 time: 0.8024 data_time: 0.2435 memory: 16131 loss: 2.6793 loss_prob: 1.6824 loss_thr: 0.7198 loss_db: 0.2771 2022/10/25 21:58:09 - mmengine - INFO - Epoch(train) [198][10/63] lr: 2.9699e-03 eta: 14:22:54 time: 0.9290 data_time: 0.2446 memory: 16131 loss: 2.4918 loss_prob: 1.5390 loss_thr: 0.7005 loss_db: 0.2524 2022/10/25 21:58:14 - mmengine - INFO - Epoch(train) [198][15/63] lr: 2.9699e-03 eta: 14:22:54 time: 0.8868 data_time: 0.0127 memory: 16131 loss: 2.2783 loss_prob: 1.3806 loss_thr: 0.6718 loss_db: 0.2259 2022/10/25 21:58:17 - mmengine - INFO - Epoch(train) [198][20/63] lr: 2.9699e-03 eta: 14:22:44 time: 0.7984 data_time: 0.0115 memory: 16131 loss: 2.3239 loss_prob: 1.4289 loss_thr: 0.6631 loss_db: 0.2320 2022/10/25 21:58:23 - mmengine - INFO - Epoch(train) [198][25/63] lr: 2.9699e-03 eta: 14:22:44 time: 0.9758 data_time: 0.0385 memory: 16131 loss: 2.4733 loss_prob: 1.5395 loss_thr: 0.6789 loss_db: 0.2549 2022/10/25 21:58:31 - mmengine - INFO - Epoch(train) [198][30/63] lr: 2.9699e-03 eta: 14:23:05 time: 1.3864 data_time: 0.0427 memory: 16131 loss: 2.4183 loss_prob: 1.4943 loss_thr: 0.6771 loss_db: 0.2469 2022/10/25 21:58:34 - mmengine - INFO - Epoch(train) [198][35/63] lr: 2.9699e-03 eta: 14:23:05 time: 1.0366 data_time: 0.0105 memory: 16131 loss: 2.3290 loss_prob: 1.4119 loss_thr: 0.6897 loss_db: 0.2274 2022/10/25 21:58:37 - mmengine - INFO - Epoch(train) [198][40/63] lr: 2.9699e-03 eta: 14:22:46 time: 0.6104 data_time: 0.0096 memory: 16131 loss: 2.5514 loss_prob: 1.5925 loss_thr: 0.7008 loss_db: 0.2582 2022/10/25 21:58:40 - mmengine - INFO - Epoch(train) [198][45/63] lr: 2.9699e-03 eta: 14:22:46 time: 0.5960 data_time: 0.0133 memory: 16131 loss: 2.5136 loss_prob: 1.5868 loss_thr: 0.6640 loss_db: 0.2628 2022/10/25 21:58:43 - mmengine - INFO - Epoch(train) [198][50/63] lr: 2.9699e-03 eta: 14:22:29 time: 0.6497 data_time: 0.0282 memory: 16131 loss: 2.3682 loss_prob: 1.4650 loss_thr: 0.6607 loss_db: 0.2425 2022/10/25 21:58:48 - mmengine - INFO - Epoch(train) [198][55/63] lr: 2.9699e-03 eta: 14:22:29 time: 0.8283 data_time: 0.0407 memory: 16131 loss: 2.5653 loss_prob: 1.5975 loss_thr: 0.7015 loss_db: 0.2663 2022/10/25 21:58:51 - mmengine - INFO - Epoch(train) [198][60/63] lr: 2.9699e-03 eta: 14:22:19 time: 0.7789 data_time: 0.0226 memory: 16131 loss: 2.5602 loss_prob: 1.5949 loss_thr: 0.6945 loss_db: 0.2708 2022/10/25 21:58:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 21:59:01 - mmengine - INFO - Epoch(train) [199][5/63] lr: 2.9849e-03 eta: 14:22:19 time: 1.0941 data_time: 0.2385 memory: 16131 loss: 2.3023 loss_prob: 1.4198 loss_thr: 0.6504 loss_db: 0.2321 2022/10/25 21:59:07 - mmengine - INFO - Epoch(train) [199][10/63] lr: 2.9849e-03 eta: 14:22:26 time: 1.4212 data_time: 0.2418 memory: 16131 loss: 2.4353 loss_prob: 1.5132 loss_thr: 0.6747 loss_db: 0.2474 2022/10/25 21:59:14 - mmengine - INFO - Epoch(train) [199][15/63] lr: 2.9849e-03 eta: 14:22:26 time: 1.2782 data_time: 0.0159 memory: 16131 loss: 2.3597 loss_prob: 1.4488 loss_thr: 0.6775 loss_db: 0.2334 2022/10/25 21:59:18 - mmengine - INFO - Epoch(train) [199][20/63] lr: 2.9849e-03 eta: 14:22:35 time: 1.1568 data_time: 0.0094 memory: 16131 loss: 2.2854 loss_prob: 1.3876 loss_thr: 0.6777 loss_db: 0.2201 2022/10/25 21:59:21 - mmengine - INFO - Epoch(train) [199][25/63] lr: 2.9849e-03 eta: 14:22:35 time: 0.7617 data_time: 0.0206 memory: 16131 loss: 2.3063 loss_prob: 1.4139 loss_thr: 0.6655 loss_db: 0.2269 2022/10/25 21:59:26 - mmengine - INFO - Epoch(train) [199][30/63] lr: 2.9849e-03 eta: 14:22:24 time: 0.7644 data_time: 0.0430 memory: 16131 loss: 2.4244 loss_prob: 1.4855 loss_thr: 0.6892 loss_db: 0.2497 2022/10/25 21:59:31 - mmengine - INFO - Epoch(train) [199][35/63] lr: 2.9849e-03 eta: 14:22:24 time: 0.9751 data_time: 0.0322 memory: 16131 loss: 2.4613 loss_prob: 1.5135 loss_thr: 0.6923 loss_db: 0.2554 2022/10/25 21:59:35 - mmengine - INFO - Epoch(train) [199][40/63] lr: 2.9849e-03 eta: 14:22:19 time: 0.8856 data_time: 0.0139 memory: 16131 loss: 2.3904 loss_prob: 1.4660 loss_thr: 0.6817 loss_db: 0.2427 2022/10/25 21:59:39 - mmengine - INFO - Epoch(train) [199][45/63] lr: 2.9849e-03 eta: 14:22:19 time: 0.7898 data_time: 0.0103 memory: 16131 loss: 2.2684 loss_prob: 1.3674 loss_thr: 0.6793 loss_db: 0.2217 2022/10/25 21:59:42 - mmengine - INFO - Epoch(train) [199][50/63] lr: 2.9849e-03 eta: 14:22:08 time: 0.7553 data_time: 0.0161 memory: 16131 loss: 2.1499 loss_prob: 1.2866 loss_thr: 0.6568 loss_db: 0.2065 2022/10/25 21:59:45 - mmengine - INFO - Epoch(train) [199][55/63] lr: 2.9849e-03 eta: 14:22:08 time: 0.6262 data_time: 0.0204 memory: 16131 loss: 2.2981 loss_prob: 1.3943 loss_thr: 0.6760 loss_db: 0.2279 2022/10/25 21:59:53 - mmengine - INFO - Epoch(train) [199][60/63] lr: 2.9849e-03 eta: 14:22:10 time: 1.0315 data_time: 0.0177 memory: 16131 loss: 2.3791 loss_prob: 1.4698 loss_thr: 0.6723 loss_db: 0.2371 2022/10/25 21:59:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:00:05 - mmengine - INFO - Epoch(train) [200][5/63] lr: 3.0000e-03 eta: 14:22:10 time: 1.4730 data_time: 0.1948 memory: 16131 loss: 2.1676 loss_prob: 1.3155 loss_thr: 0.6301 loss_db: 0.2220 2022/10/25 22:00:09 - mmengine - INFO - Epoch(train) [200][10/63] lr: 3.0000e-03 eta: 14:22:14 time: 1.3515 data_time: 0.1983 memory: 16131 loss: 2.3400 loss_prob: 1.4334 loss_thr: 0.6668 loss_db: 0.2398 2022/10/25 22:00:12 - mmengine - INFO - Epoch(train) [200][15/63] lr: 3.0000e-03 eta: 14:22:14 time: 0.7298 data_time: 0.0118 memory: 16131 loss: 2.2050 loss_prob: 1.3336 loss_thr: 0.6563 loss_db: 0.2152 2022/10/25 22:00:17 - mmengine - INFO - Epoch(train) [200][20/63] lr: 3.0000e-03 eta: 14:22:05 time: 0.7975 data_time: 0.0063 memory: 16131 loss: 2.0911 loss_prob: 1.2493 loss_thr: 0.6415 loss_db: 0.2004 2022/10/25 22:00:21 - mmengine - INFO - Epoch(train) [200][25/63] lr: 3.0000e-03 eta: 14:22:05 time: 0.8738 data_time: 0.0089 memory: 16131 loss: 2.3263 loss_prob: 1.4235 loss_thr: 0.6697 loss_db: 0.2331 2022/10/25 22:00:25 - mmengine - INFO - Epoch(train) [200][30/63] lr: 3.0000e-03 eta: 14:21:53 time: 0.7605 data_time: 0.0330 memory: 16131 loss: 2.7412 loss_prob: 1.7488 loss_thr: 0.7057 loss_db: 0.2867 2022/10/25 22:00:30 - mmengine - INFO - Epoch(train) [200][35/63] lr: 3.0000e-03 eta: 14:21:53 time: 0.9308 data_time: 0.0342 memory: 16131 loss: 2.9279 loss_prob: 1.8917 loss_thr: 0.7284 loss_db: 0.3078 2022/10/25 22:00:36 - mmengine - INFO - Epoch(train) [200][40/63] lr: 3.0000e-03 eta: 14:21:59 time: 1.0886 data_time: 0.0098 memory: 16131 loss: 2.6360 loss_prob: 1.6761 loss_thr: 0.6919 loss_db: 0.2680 2022/10/25 22:00:38 - mmengine - INFO - Epoch(train) [200][45/63] lr: 3.0000e-03 eta: 14:21:59 time: 0.8091 data_time: 0.0067 memory: 16131 loss: 2.3645 loss_prob: 1.4622 loss_thr: 0.6699 loss_db: 0.2324 2022/10/25 22:00:42 - mmengine - INFO - Epoch(train) [200][50/63] lr: 3.0000e-03 eta: 14:21:44 time: 0.6953 data_time: 0.0224 memory: 16131 loss: 2.4697 loss_prob: 1.5408 loss_thr: 0.6780 loss_db: 0.2510 2022/10/25 22:00:45 - mmengine - INFO - Epoch(train) [200][55/63] lr: 3.0000e-03 eta: 14:21:44 time: 0.6886 data_time: 0.0220 memory: 16131 loss: 2.5073 loss_prob: 1.5640 loss_thr: 0.6842 loss_db: 0.2590 2022/10/25 22:00:51 - mmengine - INFO - Epoch(train) [200][60/63] lr: 3.0000e-03 eta: 14:21:37 time: 0.8448 data_time: 0.0085 memory: 16131 loss: 2.3021 loss_prob: 1.4133 loss_thr: 0.6589 loss_db: 0.2298 2022/10/25 22:00:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:00:54 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/10/25 22:01:00 - mmengine - INFO - Epoch(val) [200][5/32] eta: 14:21:37 time: 0.5592 data_time: 0.0765 memory: 16131 2022/10/25 22:01:04 - mmengine - INFO - Epoch(val) [200][10/32] eta: 0:00:14 time: 0.6516 data_time: 0.1169 memory: 15724 2022/10/25 22:01:06 - mmengine - INFO - Epoch(val) [200][15/32] eta: 0:00:14 time: 0.6027 data_time: 0.0577 memory: 15724 2022/10/25 22:01:09 - mmengine - INFO - Epoch(val) [200][20/32] eta: 0:00:07 time: 0.5924 data_time: 0.0480 memory: 15724 2022/10/25 22:01:13 - mmengine - INFO - Epoch(val) [200][25/32] eta: 0:00:07 time: 0.6120 data_time: 0.0638 memory: 15724 2022/10/25 22:01:15 - mmengine - INFO - Epoch(val) [200][30/32] eta: 0:00:01 time: 0.5855 data_time: 0.0339 memory: 15724 2022/10/25 22:01:16 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7843, precision: 0.5898, hmean: 0.6733 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7838, precision: 0.6863, hmean: 0.7318 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7727, precision: 0.7632, hmean: 0.7679 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7285, precision: 0.8519, hmean: 0.7854 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.5253, precision: 0.9285, hmean: 0.6710 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0366, precision: 0.9620, hmean: 0.0705 2022/10/25 22:01:16 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 22:01:16 - mmengine - INFO - Epoch(val) [200][32/32] icdar/precision: 0.8519 icdar/recall: 0.7285 icdar/hmean: 0.7854 2022/10/25 22:01:23 - mmengine - INFO - Epoch(train) [201][5/63] lr: 3.0000e-03 eta: 0:00:01 time: 1.1849 data_time: 0.2235 memory: 16131 loss: 2.3976 loss_prob: 1.4725 loss_thr: 0.6817 loss_db: 0.2434 2022/10/25 22:01:26 - mmengine - INFO - Epoch(train) [201][10/63] lr: 3.0000e-03 eta: 14:21:24 time: 1.0178 data_time: 0.2309 memory: 16131 loss: 2.3847 loss_prob: 1.4601 loss_thr: 0.6852 loss_db: 0.2395 2022/10/25 22:01:30 - mmengine - INFO - Epoch(train) [201][15/63] lr: 3.0000e-03 eta: 14:21:24 time: 0.7928 data_time: 0.0138 memory: 16131 loss: 2.2361 loss_prob: 1.3591 loss_thr: 0.6617 loss_db: 0.2154 2022/10/25 22:01:33 - mmengine - INFO - Epoch(train) [201][20/63] lr: 3.0000e-03 eta: 14:21:09 time: 0.6902 data_time: 0.0071 memory: 16131 loss: 2.2791 loss_prob: 1.3896 loss_thr: 0.6651 loss_db: 0.2244 2022/10/25 22:01:38 - mmengine - INFO - Epoch(train) [201][25/63] lr: 3.0000e-03 eta: 14:21:09 time: 0.7914 data_time: 0.0150 memory: 16131 loss: 2.1608 loss_prob: 1.2973 loss_thr: 0.6508 loss_db: 0.2127 2022/10/25 22:01:42 - mmengine - INFO - Epoch(train) [201][30/63] lr: 3.0000e-03 eta: 14:21:03 time: 0.8555 data_time: 0.0383 memory: 16131 loss: 2.1671 loss_prob: 1.3012 loss_thr: 0.6498 loss_db: 0.2161 2022/10/25 22:01:48 - mmengine - INFO - Epoch(train) [201][35/63] lr: 3.0000e-03 eta: 14:21:03 time: 0.9167 data_time: 0.0298 memory: 16131 loss: 2.1906 loss_prob: 1.3081 loss_thr: 0.6635 loss_db: 0.2189 2022/10/25 22:01:51 - mmengine - INFO - Epoch(train) [201][40/63] lr: 3.0000e-03 eta: 14:20:59 time: 0.9037 data_time: 0.0084 memory: 16131 loss: 2.0807 loss_prob: 1.2276 loss_thr: 0.6502 loss_db: 0.2029 2022/10/25 22:01:55 - mmengine - INFO - Epoch(train) [201][45/63] lr: 3.0000e-03 eta: 14:20:59 time: 0.7560 data_time: 0.0079 memory: 16131 loss: 2.0811 loss_prob: 1.2296 loss_thr: 0.6494 loss_db: 0.2021 2022/10/25 22:01:59 - mmengine - INFO - Epoch(train) [201][50/63] lr: 3.0000e-03 eta: 14:20:51 time: 0.8335 data_time: 0.0170 memory: 16131 loss: 2.3117 loss_prob: 1.4035 loss_thr: 0.6757 loss_db: 0.2325 2022/10/25 22:02:03 - mmengine - INFO - Epoch(train) [201][55/63] lr: 3.0000e-03 eta: 14:20:51 time: 0.7700 data_time: 0.0236 memory: 16131 loss: 2.4799 loss_prob: 1.5308 loss_thr: 0.6962 loss_db: 0.2529 2022/10/25 22:02:08 - mmengine - INFO - Epoch(train) [201][60/63] lr: 3.0000e-03 eta: 14:20:46 time: 0.8736 data_time: 0.0121 memory: 16131 loss: 2.3353 loss_prob: 1.4156 loss_thr: 0.6838 loss_db: 0.2358 2022/10/25 22:02:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:02:18 - mmengine - INFO - Epoch(train) [202][5/63] lr: 2.9973e-03 eta: 14:20:46 time: 1.2326 data_time: 0.2167 memory: 16131 loss: 2.1072 loss_prob: 1.2550 loss_thr: 0.6472 loss_db: 0.2050 2022/10/25 22:02:20 - mmengine - INFO - Epoch(train) [202][10/63] lr: 2.9973e-03 eta: 14:20:31 time: 0.9786 data_time: 0.2238 memory: 16131 loss: 2.3196 loss_prob: 1.4311 loss_thr: 0.6500 loss_db: 0.2385 2022/10/25 22:02:24 - mmengine - INFO - Epoch(train) [202][15/63] lr: 2.9973e-03 eta: 14:20:31 time: 0.6107 data_time: 0.0161 memory: 16131 loss: 2.3638 loss_prob: 1.4499 loss_thr: 0.6697 loss_db: 0.2442 2022/10/25 22:02:27 - mmengine - INFO - Epoch(train) [202][20/63] lr: 2.9973e-03 eta: 14:20:12 time: 0.6172 data_time: 0.0089 memory: 16131 loss: 2.5114 loss_prob: 1.5748 loss_thr: 0.6780 loss_db: 0.2586 2022/10/25 22:02:30 - mmengine - INFO - Epoch(train) [202][25/63] lr: 2.9973e-03 eta: 14:20:12 time: 0.5758 data_time: 0.0199 memory: 16131 loss: 2.5349 loss_prob: 1.6044 loss_thr: 0.6685 loss_db: 0.2620 2022/10/25 22:02:33 - mmengine - INFO - Epoch(train) [202][30/63] lr: 2.9973e-03 eta: 14:19:54 time: 0.6162 data_time: 0.0286 memory: 16131 loss: 2.2795 loss_prob: 1.3964 loss_thr: 0.6572 loss_db: 0.2259 2022/10/25 22:02:36 - mmengine - INFO - Epoch(train) [202][35/63] lr: 2.9973e-03 eta: 14:19:54 time: 0.6263 data_time: 0.0204 memory: 16131 loss: 2.5494 loss_prob: 1.5973 loss_thr: 0.6975 loss_db: 0.2546 2022/10/25 22:02:40 - mmengine - INFO - Epoch(train) [202][40/63] lr: 2.9973e-03 eta: 14:19:41 time: 0.7203 data_time: 0.0127 memory: 16131 loss: 2.5829 loss_prob: 1.6044 loss_thr: 0.7186 loss_db: 0.2599 2022/10/25 22:02:44 - mmengine - INFO - Epoch(train) [202][45/63] lr: 2.9973e-03 eta: 14:19:41 time: 0.8036 data_time: 0.0089 memory: 16131 loss: 2.3818 loss_prob: 1.4633 loss_thr: 0.6793 loss_db: 0.2392 2022/10/25 22:02:50 - mmengine - INFO - Epoch(train) [202][50/63] lr: 2.9973e-03 eta: 14:19:44 time: 1.0438 data_time: 0.0189 memory: 16131 loss: 2.4087 loss_prob: 1.4890 loss_thr: 0.6720 loss_db: 0.2477 2022/10/25 22:02:54 - mmengine - INFO - Epoch(train) [202][55/63] lr: 2.9973e-03 eta: 14:19:44 time: 1.0440 data_time: 0.0235 memory: 16131 loss: 2.3053 loss_prob: 1.3940 loss_thr: 0.6792 loss_db: 0.2321 2022/10/25 22:02:59 - mmengine - INFO - Epoch(train) [202][60/63] lr: 2.9973e-03 eta: 14:19:38 time: 0.8707 data_time: 0.0137 memory: 16131 loss: 2.3716 loss_prob: 1.4550 loss_thr: 0.6818 loss_db: 0.2348 2022/10/25 22:03:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:03:09 - mmengine - INFO - Epoch(train) [203][5/63] lr: 2.9946e-03 eta: 14:19:38 time: 1.3514 data_time: 0.2326 memory: 16131 loss: 2.5103 loss_prob: 1.5675 loss_thr: 0.6920 loss_db: 0.2507 2022/10/25 22:03:13 - mmengine - INFO - Epoch(train) [203][10/63] lr: 2.9946e-03 eta: 14:19:29 time: 1.0919 data_time: 0.2283 memory: 16131 loss: 2.5028 loss_prob: 1.5532 loss_thr: 0.6933 loss_db: 0.2564 2022/10/25 22:03:19 - mmengine - INFO - Epoch(train) [203][15/63] lr: 2.9946e-03 eta: 14:19:29 time: 0.9469 data_time: 0.0095 memory: 16131 loss: 2.4502 loss_prob: 1.5115 loss_thr: 0.6899 loss_db: 0.2489 2022/10/25 22:03:22 - mmengine - INFO - Epoch(train) [203][20/63] lr: 2.9946e-03 eta: 14:19:20 time: 0.8199 data_time: 0.0114 memory: 16131 loss: 2.3506 loss_prob: 1.4305 loss_thr: 0.6853 loss_db: 0.2347 2022/10/25 22:03:27 - mmengine - INFO - Epoch(train) [203][25/63] lr: 2.9946e-03 eta: 14:19:20 time: 0.7821 data_time: 0.0118 memory: 16131 loss: 2.4503 loss_prob: 1.5038 loss_thr: 0.6961 loss_db: 0.2504 2022/10/25 22:03:35 - mmengine - INFO - Epoch(train) [203][30/63] lr: 2.9946e-03 eta: 14:19:40 time: 1.3794 data_time: 0.0362 memory: 16131 loss: 2.3623 loss_prob: 1.4276 loss_thr: 0.6975 loss_db: 0.2372 2022/10/25 22:03:38 - mmengine - INFO - Epoch(train) [203][35/63] lr: 2.9946e-03 eta: 14:19:40 time: 1.1661 data_time: 0.0331 memory: 16131 loss: 2.2239 loss_prob: 1.3172 loss_thr: 0.6912 loss_db: 0.2154 2022/10/25 22:03:44 - mmengine - INFO - Epoch(train) [203][40/63] lr: 2.9946e-03 eta: 14:19:33 time: 0.8550 data_time: 0.0077 memory: 16131 loss: 2.4156 loss_prob: 1.4830 loss_thr: 0.6956 loss_db: 0.2370 2022/10/25 22:03:46 - mmengine - INFO - Epoch(train) [203][45/63] lr: 2.9946e-03 eta: 14:19:33 time: 0.8164 data_time: 0.0084 memory: 16131 loss: 2.7339 loss_prob: 1.7570 loss_thr: 0.7008 loss_db: 0.2761 2022/10/25 22:03:49 - mmengine - INFO - Epoch(train) [203][50/63] lr: 2.9946e-03 eta: 14:19:10 time: 0.5221 data_time: 0.0148 memory: 16131 loss: 2.6259 loss_prob: 1.6618 loss_thr: 0.7000 loss_db: 0.2640 2022/10/25 22:03:52 - mmengine - INFO - Epoch(train) [203][55/63] lr: 2.9946e-03 eta: 14:19:10 time: 0.5225 data_time: 0.0251 memory: 16131 loss: 2.5131 loss_prob: 1.5388 loss_thr: 0.7248 loss_db: 0.2495 2022/10/25 22:03:55 - mmengine - INFO - Epoch(train) [203][60/63] lr: 2.9946e-03 eta: 14:18:49 time: 0.5532 data_time: 0.0166 memory: 16131 loss: 2.4579 loss_prob: 1.4950 loss_thr: 0.7185 loss_db: 0.2444 2022/10/25 22:03:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:04:01 - mmengine - INFO - Epoch(train) [204][5/63] lr: 2.9919e-03 eta: 14:18:49 time: 0.7424 data_time: 0.1717 memory: 16131 loss: 2.6270 loss_prob: 1.6423 loss_thr: 0.7114 loss_db: 0.2732 2022/10/25 22:04:05 - mmengine - INFO - Epoch(train) [204][10/63] lr: 2.9919e-03 eta: 14:18:30 time: 0.8871 data_time: 0.1730 memory: 16131 loss: 2.6563 loss_prob: 1.6783 loss_thr: 0.7037 loss_db: 0.2742 2022/10/25 22:04:10 - mmengine - INFO - Epoch(train) [204][15/63] lr: 2.9919e-03 eta: 14:18:30 time: 0.8958 data_time: 0.0122 memory: 16131 loss: 2.3428 loss_prob: 1.4259 loss_thr: 0.6890 loss_db: 0.2280 2022/10/25 22:04:13 - mmengine - INFO - Epoch(train) [204][20/63] lr: 2.9919e-03 eta: 14:18:21 time: 0.8222 data_time: 0.0111 memory: 16131 loss: 2.3797 loss_prob: 1.4445 loss_thr: 0.7058 loss_db: 0.2294 2022/10/25 22:04:17 - mmengine - INFO - Epoch(train) [204][25/63] lr: 2.9919e-03 eta: 14:18:21 time: 0.7119 data_time: 0.0296 memory: 16131 loss: 2.2756 loss_prob: 1.3770 loss_thr: 0.6815 loss_db: 0.2171 2022/10/25 22:04:22 - mmengine - INFO - Epoch(train) [204][30/63] lr: 2.9919e-03 eta: 14:18:16 time: 0.8857 data_time: 0.0469 memory: 16131 loss: 2.2383 loss_prob: 1.3397 loss_thr: 0.6843 loss_db: 0.2143 2022/10/25 22:04:29 - mmengine - INFO - Epoch(train) [204][35/63] lr: 2.9919e-03 eta: 14:18:16 time: 1.1630 data_time: 0.0268 memory: 16131 loss: 2.2028 loss_prob: 1.3338 loss_thr: 0.6551 loss_db: 0.2140 2022/10/25 22:04:32 - mmengine - INFO - Epoch(train) [204][40/63] lr: 2.9919e-03 eta: 14:18:15 time: 0.9586 data_time: 0.0086 memory: 16131 loss: 2.4372 loss_prob: 1.5211 loss_thr: 0.6739 loss_db: 0.2422 2022/10/25 22:04:36 - mmengine - INFO - Epoch(train) [204][45/63] lr: 2.9919e-03 eta: 14:18:15 time: 0.7489 data_time: 0.0069 memory: 16131 loss: 2.6334 loss_prob: 1.6609 loss_thr: 0.7029 loss_db: 0.2697 2022/10/25 22:04:42 - mmengine - INFO - Epoch(train) [204][50/63] lr: 2.9919e-03 eta: 14:18:20 time: 1.0971 data_time: 0.0128 memory: 16131 loss: 2.5566 loss_prob: 1.5907 loss_thr: 0.7034 loss_db: 0.2624 2022/10/25 22:04:50 - mmengine - INFO - Epoch(train) [204][55/63] lr: 2.9919e-03 eta: 14:18:20 time: 1.3480 data_time: 0.0230 memory: 16131 loss: 2.6679 loss_prob: 1.6724 loss_thr: 0.7185 loss_db: 0.2769 2022/10/25 22:04:52 - mmengine - INFO - Epoch(train) [204][60/63] lr: 2.9919e-03 eta: 14:18:20 time: 0.9836 data_time: 0.0195 memory: 16131 loss: 2.6578 loss_prob: 1.6754 loss_thr: 0.7003 loss_db: 0.2821 2022/10/25 22:04:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:05:01 - mmengine - INFO - Epoch(train) [205][5/63] lr: 2.9892e-03 eta: 14:18:20 time: 0.9700 data_time: 0.2321 memory: 16131 loss: 2.6499 loss_prob: 1.6666 loss_thr: 0.6999 loss_db: 0.2835 2022/10/25 22:05:06 - mmengine - INFO - Epoch(train) [205][10/63] lr: 2.9892e-03 eta: 14:18:20 time: 1.2929 data_time: 0.2295 memory: 16131 loss: 2.8346 loss_prob: 1.8077 loss_thr: 0.7179 loss_db: 0.3090 2022/10/25 22:05:12 - mmengine - INFO - Epoch(train) [205][15/63] lr: 2.9892e-03 eta: 14:18:20 time: 1.0877 data_time: 0.0068 memory: 16131 loss: 2.7318 loss_prob: 1.7344 loss_thr: 0.7081 loss_db: 0.2892 2022/10/25 22:05:18 - mmengine - INFO - Epoch(train) [205][20/63] lr: 2.9892e-03 eta: 14:18:29 time: 1.1690 data_time: 0.0087 memory: 16131 loss: 2.4963 loss_prob: 1.5586 loss_thr: 0.6731 loss_db: 0.2647 2022/10/25 22:05:24 - mmengine - INFO - Epoch(train) [205][25/63] lr: 2.9892e-03 eta: 14:18:29 time: 1.2076 data_time: 0.0381 memory: 16131 loss: 2.3177 loss_prob: 1.4282 loss_thr: 0.6474 loss_db: 0.2420 2022/10/25 22:05:29 - mmengine - INFO - Epoch(train) [205][30/63] lr: 2.9892e-03 eta: 14:18:32 time: 1.0396 data_time: 0.0393 memory: 16131 loss: 2.3433 loss_prob: 1.4297 loss_thr: 0.6797 loss_db: 0.2339 2022/10/25 22:05:34 - mmengine - INFO - Epoch(train) [205][35/63] lr: 2.9892e-03 eta: 14:18:32 time: 0.9613 data_time: 0.0078 memory: 16131 loss: 2.4599 loss_prob: 1.5096 loss_thr: 0.7017 loss_db: 0.2487 2022/10/25 22:05:37 - mmengine - INFO - Epoch(train) [205][40/63] lr: 2.9892e-03 eta: 14:18:27 time: 0.8899 data_time: 0.0053 memory: 16131 loss: 2.3659 loss_prob: 1.4621 loss_thr: 0.6647 loss_db: 0.2391 2022/10/25 22:05:40 - mmengine - INFO - Epoch(train) [205][45/63] lr: 2.9892e-03 eta: 14:18:27 time: 0.6698 data_time: 0.0054 memory: 16131 loss: 2.3883 loss_prob: 1.4698 loss_thr: 0.6815 loss_db: 0.2371 2022/10/25 22:05:47 - mmengine - INFO - Epoch(train) [205][50/63] lr: 2.9892e-03 eta: 14:18:26 time: 0.9691 data_time: 0.0252 memory: 16131 loss: 2.4087 loss_prob: 1.4870 loss_thr: 0.6797 loss_db: 0.2420 2022/10/25 22:05:51 - mmengine - INFO - Epoch(train) [205][55/63] lr: 2.9892e-03 eta: 14:18:26 time: 1.0392 data_time: 0.0266 memory: 16131 loss: 2.0796 loss_prob: 1.2567 loss_thr: 0.6249 loss_db: 0.1979 2022/10/25 22:05:55 - mmengine - INFO - Epoch(train) [205][60/63] lr: 2.9892e-03 eta: 14:18:17 time: 0.8153 data_time: 0.0086 memory: 16131 loss: 2.0276 loss_prob: 1.2158 loss_thr: 0.6204 loss_db: 0.1914 2022/10/25 22:05:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:06:05 - mmengine - INFO - Epoch(train) [206][5/63] lr: 2.9865e-03 eta: 14:18:17 time: 1.0960 data_time: 0.2314 memory: 16131 loss: 2.3234 loss_prob: 1.4141 loss_thr: 0.6736 loss_db: 0.2356 2022/10/25 22:06:11 - mmengine - INFO - Epoch(train) [206][10/63] lr: 2.9865e-03 eta: 14:18:22 time: 1.3810 data_time: 0.2300 memory: 16131 loss: 2.4172 loss_prob: 1.4896 loss_thr: 0.6834 loss_db: 0.2442 2022/10/25 22:06:15 - mmengine - INFO - Epoch(train) [206][15/63] lr: 2.9865e-03 eta: 14:18:22 time: 1.0051 data_time: 0.0066 memory: 16131 loss: 2.5992 loss_prob: 1.6450 loss_thr: 0.6842 loss_db: 0.2700 2022/10/25 22:06:21 - mmengine - INFO - Epoch(train) [206][20/63] lr: 2.9865e-03 eta: 14:18:21 time: 0.9685 data_time: 0.0094 memory: 16131 loss: 2.5652 loss_prob: 1.6124 loss_thr: 0.6894 loss_db: 0.2634 2022/10/25 22:06:27 - mmengine - INFO - Epoch(train) [206][25/63] lr: 2.9865e-03 eta: 14:18:21 time: 1.1515 data_time: 0.0321 memory: 16131 loss: 2.3145 loss_prob: 1.4178 loss_thr: 0.6665 loss_db: 0.2302 2022/10/25 22:06:29 - mmengine - INFO - Epoch(train) [206][30/63] lr: 2.9865e-03 eta: 14:18:13 time: 0.8297 data_time: 0.0364 memory: 16131 loss: 2.3449 loss_prob: 1.4396 loss_thr: 0.6685 loss_db: 0.2368 2022/10/25 22:06:32 - mmengine - INFO - Epoch(train) [206][35/63] lr: 2.9865e-03 eta: 14:18:13 time: 0.5762 data_time: 0.0143 memory: 16131 loss: 2.7876 loss_prob: 1.7796 loss_thr: 0.7127 loss_db: 0.2952 2022/10/25 22:06:37 - mmengine - INFO - Epoch(train) [206][40/63] lr: 2.9865e-03 eta: 14:18:01 time: 0.7543 data_time: 0.0073 memory: 16131 loss: 2.7132 loss_prob: 1.7296 loss_thr: 0.7009 loss_db: 0.2827 2022/10/25 22:06:41 - mmengine - INFO - Epoch(train) [206][45/63] lr: 2.9865e-03 eta: 14:18:01 time: 0.8734 data_time: 0.0100 memory: 16131 loss: 2.3053 loss_prob: 1.4083 loss_thr: 0.6697 loss_db: 0.2273 2022/10/25 22:06:47 - mmengine - INFO - Epoch(train) [206][50/63] lr: 2.9865e-03 eta: 14:18:04 time: 1.0393 data_time: 0.0201 memory: 16131 loss: 2.2218 loss_prob: 1.3534 loss_thr: 0.6496 loss_db: 0.2188 2022/10/25 22:06:50 - mmengine - INFO - Epoch(train) [206][55/63] lr: 2.9865e-03 eta: 14:18:04 time: 0.9134 data_time: 0.0218 memory: 16131 loss: 2.1949 loss_prob: 1.3198 loss_thr: 0.6593 loss_db: 0.2158 2022/10/25 22:06:54 - mmengine - INFO - Epoch(train) [206][60/63] lr: 2.9865e-03 eta: 14:17:49 time: 0.6987 data_time: 0.0106 memory: 16131 loss: 2.1875 loss_prob: 1.3032 loss_thr: 0.6721 loss_db: 0.2122 2022/10/25 22:06:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:07:03 - mmengine - INFO - Epoch(train) [207][5/63] lr: 2.9838e-03 eta: 14:17:49 time: 0.9709 data_time: 0.2075 memory: 16131 loss: 2.1612 loss_prob: 1.2962 loss_thr: 0.6544 loss_db: 0.2105 2022/10/25 22:07:09 - mmengine - INFO - Epoch(train) [207][10/63] lr: 2.9838e-03 eta: 14:17:49 time: 1.2718 data_time: 0.2077 memory: 16131 loss: 2.1639 loss_prob: 1.3056 loss_thr: 0.6431 loss_db: 0.2152 2022/10/25 22:07:14 - mmengine - INFO - Epoch(train) [207][15/63] lr: 2.9838e-03 eta: 14:17:49 time: 1.1256 data_time: 0.0058 memory: 16131 loss: 2.4343 loss_prob: 1.5004 loss_thr: 0.6848 loss_db: 0.2492 2022/10/25 22:07:17 - mmengine - INFO - Epoch(train) [207][20/63] lr: 2.9838e-03 eta: 14:17:42 time: 0.8568 data_time: 0.0068 memory: 16131 loss: 2.4675 loss_prob: 1.5183 loss_thr: 0.7008 loss_db: 0.2483 2022/10/25 22:07:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:07:22 - mmengine - INFO - Epoch(train) [207][25/63] lr: 2.9838e-03 eta: 14:17:42 time: 0.8276 data_time: 0.0139 memory: 16131 loss: 2.0369 loss_prob: 1.2058 loss_thr: 0.6373 loss_db: 0.1938 2022/10/25 22:07:26 - mmengine - INFO - Epoch(train) [207][30/63] lr: 2.9838e-03 eta: 14:17:36 time: 0.8614 data_time: 0.0351 memory: 16131 loss: 1.9939 loss_prob: 1.1817 loss_thr: 0.6195 loss_db: 0.1926 2022/10/25 22:07:30 - mmengine - INFO - Epoch(train) [207][35/63] lr: 2.9838e-03 eta: 14:17:36 time: 0.7954 data_time: 0.0285 memory: 16131 loss: 2.1837 loss_prob: 1.3221 loss_thr: 0.6445 loss_db: 0.2171 2022/10/25 22:07:34 - mmengine - INFO - Epoch(train) [207][40/63] lr: 2.9838e-03 eta: 14:17:28 time: 0.8365 data_time: 0.0069 memory: 16131 loss: 2.2663 loss_prob: 1.3881 loss_thr: 0.6516 loss_db: 0.2267 2022/10/25 22:07:38 - mmengine - INFO - Epoch(train) [207][45/63] lr: 2.9838e-03 eta: 14:17:28 time: 0.7959 data_time: 0.0080 memory: 16131 loss: 2.3009 loss_prob: 1.4217 loss_thr: 0.6473 loss_db: 0.2319 2022/10/25 22:07:42 - mmengine - INFO - Epoch(train) [207][50/63] lr: 2.9838e-03 eta: 14:17:17 time: 0.7645 data_time: 0.0108 memory: 16131 loss: 2.3736 loss_prob: 1.4676 loss_thr: 0.6676 loss_db: 0.2383 2022/10/25 22:07:49 - mmengine - INFO - Epoch(train) [207][55/63] lr: 2.9838e-03 eta: 14:17:17 time: 1.1297 data_time: 0.0543 memory: 16131 loss: 2.3388 loss_prob: 1.4359 loss_thr: 0.6688 loss_db: 0.2341 2022/10/25 22:07:53 - mmengine - INFO - Epoch(train) [207][60/63] lr: 2.9838e-03 eta: 14:17:24 time: 1.1315 data_time: 0.0512 memory: 16131 loss: 2.2793 loss_prob: 1.3984 loss_thr: 0.6533 loss_db: 0.2276 2022/10/25 22:07:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:08:05 - mmengine - INFO - Epoch(train) [208][5/63] lr: 2.9811e-03 eta: 14:17:24 time: 1.2740 data_time: 0.2161 memory: 16131 loss: 2.4160 loss_prob: 1.4766 loss_thr: 0.6930 loss_db: 0.2464 2022/10/25 22:08:10 - mmengine - INFO - Epoch(train) [208][10/63] lr: 2.9811e-03 eta: 14:17:29 time: 1.4066 data_time: 0.2155 memory: 16131 loss: 2.1569 loss_prob: 1.2874 loss_thr: 0.6610 loss_db: 0.2086 2022/10/25 22:08:15 - mmengine - INFO - Epoch(train) [208][15/63] lr: 2.9811e-03 eta: 14:17:29 time: 1.0081 data_time: 0.0131 memory: 16131 loss: 2.2526 loss_prob: 1.3770 loss_thr: 0.6563 loss_db: 0.2192 2022/10/25 22:08:19 - mmengine - INFO - Epoch(train) [208][20/63] lr: 2.9811e-03 eta: 14:17:23 time: 0.8725 data_time: 0.0123 memory: 16131 loss: 2.2915 loss_prob: 1.3995 loss_thr: 0.6650 loss_db: 0.2271 2022/10/25 22:08:24 - mmengine - INFO - Epoch(train) [208][25/63] lr: 2.9811e-03 eta: 14:17:23 time: 0.9493 data_time: 0.0205 memory: 16131 loss: 2.1996 loss_prob: 1.3213 loss_thr: 0.6657 loss_db: 0.2125 2022/10/25 22:08:29 - mmengine - INFO - Epoch(train) [208][30/63] lr: 2.9811e-03 eta: 14:17:23 time: 0.9834 data_time: 0.0452 memory: 16131 loss: 2.3119 loss_prob: 1.4079 loss_thr: 0.6814 loss_db: 0.2226 2022/10/25 22:08:33 - mmengine - INFO - Epoch(train) [208][35/63] lr: 2.9811e-03 eta: 14:17:23 time: 0.8508 data_time: 0.0299 memory: 16131 loss: 2.2810 loss_prob: 1.3798 loss_thr: 0.6824 loss_db: 0.2189 2022/10/25 22:08:39 - mmengine - INFO - Epoch(train) [208][40/63] lr: 2.9811e-03 eta: 14:17:22 time: 0.9830 data_time: 0.0114 memory: 16131 loss: 2.1522 loss_prob: 1.2906 loss_thr: 0.6543 loss_db: 0.2072 2022/10/25 22:08:43 - mmengine - INFO - Epoch(train) [208][45/63] lr: 2.9811e-03 eta: 14:17:22 time: 1.0011 data_time: 0.0115 memory: 16131 loss: 2.0793 loss_prob: 1.2446 loss_thr: 0.6314 loss_db: 0.2032 2022/10/25 22:08:47 - mmengine - INFO - Epoch(train) [208][50/63] lr: 2.9811e-03 eta: 14:17:15 time: 0.8416 data_time: 0.0150 memory: 16131 loss: 2.1894 loss_prob: 1.3091 loss_thr: 0.6646 loss_db: 0.2157 2022/10/25 22:08:51 - mmengine - INFO - Epoch(train) [208][55/63] lr: 2.9811e-03 eta: 14:17:15 time: 0.8196 data_time: 0.0245 memory: 16131 loss: 2.2129 loss_prob: 1.3229 loss_thr: 0.6751 loss_db: 0.2149 2022/10/25 22:08:55 - mmengine - INFO - Epoch(train) [208][60/63] lr: 2.9811e-03 eta: 14:17:06 time: 0.8058 data_time: 0.0167 memory: 16131 loss: 2.1023 loss_prob: 1.2471 loss_thr: 0.6521 loss_db: 0.2030 2022/10/25 22:08:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:09:03 - mmengine - INFO - Epoch(train) [209][5/63] lr: 2.9784e-03 eta: 14:17:06 time: 1.0090 data_time: 0.2290 memory: 16131 loss: 2.0281 loss_prob: 1.1919 loss_thr: 0.6502 loss_db: 0.1860 2022/10/25 22:09:09 - mmengine - INFO - Epoch(train) [209][10/63] lr: 2.9784e-03 eta: 14:16:59 time: 1.1463 data_time: 0.2282 memory: 16131 loss: 2.2799 loss_prob: 1.3838 loss_thr: 0.6810 loss_db: 0.2151 2022/10/25 22:09:12 - mmengine - INFO - Epoch(train) [209][15/63] lr: 2.9784e-03 eta: 14:16:59 time: 0.9372 data_time: 0.0126 memory: 16131 loss: 2.3349 loss_prob: 1.4218 loss_thr: 0.6858 loss_db: 0.2272 2022/10/25 22:09:15 - mmengine - INFO - Epoch(train) [209][20/63] lr: 2.9784e-03 eta: 14:16:39 time: 0.5772 data_time: 0.0106 memory: 16131 loss: 2.1877 loss_prob: 1.2965 loss_thr: 0.6763 loss_db: 0.2149 2022/10/25 22:09:19 - mmengine - INFO - Epoch(train) [209][25/63] lr: 2.9784e-03 eta: 14:16:39 time: 0.6779 data_time: 0.0246 memory: 16131 loss: 2.2138 loss_prob: 1.3072 loss_thr: 0.6899 loss_db: 0.2167 2022/10/25 22:09:22 - mmengine - INFO - Epoch(train) [209][30/63] lr: 2.9784e-03 eta: 14:16:25 time: 0.6945 data_time: 0.0411 memory: 16131 loss: 2.3450 loss_prob: 1.4086 loss_thr: 0.7056 loss_db: 0.2308 2022/10/25 22:09:28 - mmengine - INFO - Epoch(train) [209][35/63] lr: 2.9784e-03 eta: 14:16:25 time: 0.8950 data_time: 0.0279 memory: 16131 loss: 2.5058 loss_prob: 1.5716 loss_thr: 0.6842 loss_db: 0.2499 2022/10/25 22:09:31 - mmengine - INFO - Epoch(train) [209][40/63] lr: 2.9784e-03 eta: 14:16:20 time: 0.8904 data_time: 0.0198 memory: 16131 loss: 2.3401 loss_prob: 1.4620 loss_thr: 0.6485 loss_db: 0.2296 2022/10/25 22:09:33 - mmengine - INFO - Epoch(train) [209][45/63] lr: 2.9784e-03 eta: 14:16:20 time: 0.5496 data_time: 0.0141 memory: 16131 loss: 2.2253 loss_prob: 1.3472 loss_thr: 0.6632 loss_db: 0.2149 2022/10/25 22:09:37 - mmengine - INFO - Epoch(train) [209][50/63] lr: 2.9784e-03 eta: 14:16:03 time: 0.6543 data_time: 0.0355 memory: 16131 loss: 2.3135 loss_prob: 1.4005 loss_thr: 0.6849 loss_db: 0.2281 2022/10/25 22:09:40 - mmengine - INFO - Epoch(train) [209][55/63] lr: 2.9784e-03 eta: 14:16:03 time: 0.6696 data_time: 0.0419 memory: 16131 loss: 2.2412 loss_prob: 1.3300 loss_thr: 0.6908 loss_db: 0.2204 2022/10/25 22:09:44 - mmengine - INFO - Epoch(train) [209][60/63] lr: 2.9784e-03 eta: 14:15:47 time: 0.6400 data_time: 0.0117 memory: 16131 loss: 2.1328 loss_prob: 1.2617 loss_thr: 0.6645 loss_db: 0.2066 2022/10/25 22:09:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:09:55 - mmengine - INFO - Epoch(train) [210][5/63] lr: 2.9757e-03 eta: 14:15:47 time: 1.2975 data_time: 0.2033 memory: 16131 loss: 2.1811 loss_prob: 1.3163 loss_thr: 0.6526 loss_db: 0.2122 2022/10/25 22:10:01 - mmengine - INFO - Epoch(train) [210][10/63] lr: 2.9757e-03 eta: 14:15:51 time: 1.3946 data_time: 0.2045 memory: 16131 loss: 2.3286 loss_prob: 1.4204 loss_thr: 0.6790 loss_db: 0.2292 2022/10/25 22:10:05 - mmengine - INFO - Epoch(train) [210][15/63] lr: 2.9757e-03 eta: 14:15:51 time: 0.9961 data_time: 0.0120 memory: 16131 loss: 2.4006 loss_prob: 1.4808 loss_thr: 0.6761 loss_db: 0.2437 2022/10/25 22:10:10 - mmengine - INFO - Epoch(train) [210][20/63] lr: 2.9757e-03 eta: 14:15:46 time: 0.8947 data_time: 0.0094 memory: 16131 loss: 2.5100 loss_prob: 1.5469 loss_thr: 0.6998 loss_db: 0.2633 2022/10/25 22:10:16 - mmengine - INFO - Epoch(train) [210][25/63] lr: 2.9757e-03 eta: 14:15:46 time: 1.0956 data_time: 0.0638 memory: 16131 loss: 2.4775 loss_prob: 1.5447 loss_thr: 0.6782 loss_db: 0.2546 2022/10/25 22:10:20 - mmengine - INFO - Epoch(train) [210][30/63] lr: 2.9757e-03 eta: 14:15:45 time: 0.9646 data_time: 0.0647 memory: 16131 loss: 2.3925 loss_prob: 1.4946 loss_thr: 0.6581 loss_db: 0.2397 2022/10/25 22:10:22 - mmengine - INFO - Epoch(train) [210][35/63] lr: 2.9757e-03 eta: 14:15:45 time: 0.6081 data_time: 0.0069 memory: 16131 loss: 2.3417 loss_prob: 1.4371 loss_thr: 0.6715 loss_db: 0.2331 2022/10/25 22:10:27 - mmengine - INFO - Epoch(train) [210][40/63] lr: 2.9757e-03 eta: 14:15:32 time: 0.7235 data_time: 0.0106 memory: 16131 loss: 2.2308 loss_prob: 1.3507 loss_thr: 0.6645 loss_db: 0.2156 2022/10/25 22:10:33 - mmengine - INFO - Epoch(train) [210][45/63] lr: 2.9757e-03 eta: 14:15:32 time: 1.0337 data_time: 0.0097 memory: 16131 loss: 2.0930 loss_prob: 1.2471 loss_thr: 0.6468 loss_db: 0.1992 2022/10/25 22:10:36 - mmengine - INFO - Epoch(train) [210][50/63] lr: 2.9757e-03 eta: 14:15:28 time: 0.9072 data_time: 0.0385 memory: 16131 loss: 2.1006 loss_prob: 1.2396 loss_thr: 0.6590 loss_db: 0.2020 2022/10/25 22:10:39 - mmengine - INFO - Epoch(train) [210][55/63] lr: 2.9757e-03 eta: 14:15:28 time: 0.6078 data_time: 0.0379 memory: 16131 loss: 2.3083 loss_prob: 1.3883 loss_thr: 0.6931 loss_db: 0.2270 2022/10/25 22:10:41 - mmengine - INFO - Epoch(train) [210][60/63] lr: 2.9757e-03 eta: 14:15:07 time: 0.5517 data_time: 0.0055 memory: 16131 loss: 2.4661 loss_prob: 1.5329 loss_thr: 0.6874 loss_db: 0.2458 2022/10/25 22:10:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:10:47 - mmengine - INFO - Epoch(train) [211][5/63] lr: 2.9730e-03 eta: 14:15:07 time: 0.7133 data_time: 0.2216 memory: 16131 loss: 2.4916 loss_prob: 1.5669 loss_thr: 0.6727 loss_db: 0.2520 2022/10/25 22:10:52 - mmengine - INFO - Epoch(train) [211][10/63] lr: 2.9730e-03 eta: 14:14:48 time: 0.9072 data_time: 0.2228 memory: 16131 loss: 2.6029 loss_prob: 1.6551 loss_thr: 0.6870 loss_db: 0.2607 2022/10/25 22:10:56 - mmengine - INFO - Epoch(train) [211][15/63] lr: 2.9730e-03 eta: 14:14:48 time: 0.8149 data_time: 0.0096 memory: 16131 loss: 2.6193 loss_prob: 1.6611 loss_thr: 0.6982 loss_db: 0.2599 2022/10/25 22:11:00 - mmengine - INFO - Epoch(train) [211][20/63] lr: 2.9730e-03 eta: 14:14:38 time: 0.7755 data_time: 0.0067 memory: 16131 loss: 2.4990 loss_prob: 1.5578 loss_thr: 0.6887 loss_db: 0.2525 2022/10/25 22:11:02 - mmengine - INFO - Epoch(train) [211][25/63] lr: 2.9730e-03 eta: 14:14:38 time: 0.6663 data_time: 0.0117 memory: 16131 loss: 2.3408 loss_prob: 1.4300 loss_thr: 0.6747 loss_db: 0.2361 2022/10/25 22:11:07 - mmengine - INFO - Epoch(train) [211][30/63] lr: 2.9730e-03 eta: 14:14:28 time: 0.7887 data_time: 0.0395 memory: 16131 loss: 2.1778 loss_prob: 1.3111 loss_thr: 0.6530 loss_db: 0.2137 2022/10/25 22:11:10 - mmengine - INFO - Epoch(train) [211][35/63] lr: 2.9730e-03 eta: 14:14:28 time: 0.8158 data_time: 0.0349 memory: 16131 loss: 2.2386 loss_prob: 1.3499 loss_thr: 0.6661 loss_db: 0.2226 2022/10/25 22:11:16 - mmengine - INFO - Epoch(train) [211][40/63] lr: 2.9730e-03 eta: 14:14:19 time: 0.8088 data_time: 0.0099 memory: 16131 loss: 2.4339 loss_prob: 1.4927 loss_thr: 0.6952 loss_db: 0.2460 2022/10/25 22:11:19 - mmengine - INFO - Epoch(train) [211][45/63] lr: 2.9730e-03 eta: 14:14:19 time: 0.8222 data_time: 0.0083 memory: 16131 loss: 2.3361 loss_prob: 1.4371 loss_thr: 0.6677 loss_db: 0.2313 2022/10/25 22:11:22 - mmengine - INFO - Epoch(train) [211][50/63] lr: 2.9730e-03 eta: 14:14:04 time: 0.6759 data_time: 0.0238 memory: 16131 loss: 2.2261 loss_prob: 1.3616 loss_thr: 0.6416 loss_db: 0.2229 2022/10/25 22:11:26 - mmengine - INFO - Epoch(train) [211][55/63] lr: 2.9730e-03 eta: 14:14:04 time: 0.7641 data_time: 0.0312 memory: 16131 loss: 2.2570 loss_prob: 1.3770 loss_thr: 0.6488 loss_db: 0.2312 2022/10/25 22:11:32 - mmengine - INFO - Epoch(train) [211][60/63] lr: 2.9730e-03 eta: 14:14:03 time: 0.9738 data_time: 0.0161 memory: 16131 loss: 2.2637 loss_prob: 1.3641 loss_thr: 0.6758 loss_db: 0.2239 2022/10/25 22:11:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:11:44 - mmengine - INFO - Epoch(train) [212][5/63] lr: 2.9703e-03 eta: 14:14:03 time: 1.2518 data_time: 0.2565 memory: 16131 loss: 2.0758 loss_prob: 1.2350 loss_thr: 0.6434 loss_db: 0.1974 2022/10/25 22:11:48 - mmengine - INFO - Epoch(train) [212][10/63] lr: 2.9703e-03 eta: 14:14:11 time: 1.4569 data_time: 0.2585 memory: 16131 loss: 2.0841 loss_prob: 1.2520 loss_thr: 0.6299 loss_db: 0.2022 2022/10/25 22:11:52 - mmengine - INFO - Epoch(train) [212][15/63] lr: 2.9703e-03 eta: 14:14:11 time: 0.8660 data_time: 0.0080 memory: 16131 loss: 2.1197 loss_prob: 1.2588 loss_thr: 0.6601 loss_db: 0.2008 2022/10/25 22:11:57 - mmengine - INFO - Epoch(train) [212][20/63] lr: 2.9703e-03 eta: 14:14:07 time: 0.9118 data_time: 0.0068 memory: 16131 loss: 2.1820 loss_prob: 1.2959 loss_thr: 0.6820 loss_db: 0.2041 2022/10/25 22:12:02 - mmengine - INFO - Epoch(train) [212][25/63] lr: 2.9703e-03 eta: 14:14:07 time: 0.9694 data_time: 0.0332 memory: 16131 loss: 2.2029 loss_prob: 1.3074 loss_thr: 0.6838 loss_db: 0.2117 2022/10/25 22:12:07 - mmengine - INFO - Epoch(train) [212][30/63] lr: 2.9703e-03 eta: 14:14:05 time: 0.9580 data_time: 0.0325 memory: 16131 loss: 2.2850 loss_prob: 1.3813 loss_thr: 0.6770 loss_db: 0.2267 2022/10/25 22:12:10 - mmengine - INFO - Epoch(train) [212][35/63] lr: 2.9703e-03 eta: 14:14:05 time: 0.7877 data_time: 0.0051 memory: 16131 loss: 2.2232 loss_prob: 1.3464 loss_thr: 0.6584 loss_db: 0.2184 2022/10/25 22:12:14 - mmengine - INFO - Epoch(train) [212][40/63] lr: 2.9703e-03 eta: 14:13:49 time: 0.6751 data_time: 0.0060 memory: 16131 loss: 2.0701 loss_prob: 1.2141 loss_thr: 0.6602 loss_db: 0.1957 2022/10/25 22:12:17 - mmengine - INFO - Epoch(train) [212][45/63] lr: 2.9703e-03 eta: 14:13:49 time: 0.7130 data_time: 0.0060 memory: 16131 loss: 2.1152 loss_prob: 1.2532 loss_thr: 0.6577 loss_db: 0.2042 2022/10/25 22:12:20 - mmengine - INFO - Epoch(train) [212][50/63] lr: 2.9703e-03 eta: 14:13:32 time: 0.6271 data_time: 0.0229 memory: 16131 loss: 2.0312 loss_prob: 1.2120 loss_thr: 0.6252 loss_db: 0.1941 2022/10/25 22:12:24 - mmengine - INFO - Epoch(train) [212][55/63] lr: 2.9703e-03 eta: 14:13:32 time: 0.6973 data_time: 0.0228 memory: 16131 loss: 2.0312 loss_prob: 1.2031 loss_thr: 0.6353 loss_db: 0.1928 2022/10/25 22:12:27 - mmengine - INFO - Epoch(train) [212][60/63] lr: 2.9703e-03 eta: 14:13:20 time: 0.7292 data_time: 0.0057 memory: 16131 loss: 2.1796 loss_prob: 1.2958 loss_thr: 0.6675 loss_db: 0.2163 2022/10/25 22:12:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:12:33 - mmengine - INFO - Epoch(train) [213][5/63] lr: 2.9675e-03 eta: 14:13:20 time: 0.7227 data_time: 0.2129 memory: 16131 loss: 2.1355 loss_prob: 1.2616 loss_thr: 0.6651 loss_db: 0.2088 2022/10/25 22:12:37 - mmengine - INFO - Epoch(train) [213][10/63] lr: 2.9675e-03 eta: 14:12:59 time: 0.8505 data_time: 0.2129 memory: 16131 loss: 2.3346 loss_prob: 1.4256 loss_thr: 0.6722 loss_db: 0.2368 2022/10/25 22:12:43 - mmengine - INFO - Epoch(train) [213][15/63] lr: 2.9675e-03 eta: 14:12:59 time: 0.9650 data_time: 0.0091 memory: 16131 loss: 2.4689 loss_prob: 1.5458 loss_thr: 0.6720 loss_db: 0.2511 2022/10/25 22:12:49 - mmengine - INFO - Epoch(train) [213][20/63] lr: 2.9675e-03 eta: 14:13:08 time: 1.1924 data_time: 0.0124 memory: 16131 loss: 2.3753 loss_prob: 1.4684 loss_thr: 0.6697 loss_db: 0.2373 2022/10/25 22:12:54 - mmengine - INFO - Epoch(train) [213][25/63] lr: 2.9675e-03 eta: 14:13:08 time: 1.0595 data_time: 0.0398 memory: 16131 loss: 2.2562 loss_prob: 1.3672 loss_thr: 0.6661 loss_db: 0.2229 2022/10/25 22:12:57 - mmengine - INFO - Epoch(train) [213][30/63] lr: 2.9675e-03 eta: 14:12:59 time: 0.8231 data_time: 0.0375 memory: 16131 loss: 2.3109 loss_prob: 1.3973 loss_thr: 0.6848 loss_db: 0.2288 2022/10/25 22:13:02 - mmengine - INFO - Epoch(train) [213][35/63] lr: 2.9675e-03 eta: 14:12:59 time: 0.8132 data_time: 0.0113 memory: 16131 loss: 2.2403 loss_prob: 1.3602 loss_thr: 0.6608 loss_db: 0.2193 2022/10/25 22:13:05 - mmengine - INFO - Epoch(train) [213][40/63] lr: 2.9675e-03 eta: 14:12:51 time: 0.8112 data_time: 0.0080 memory: 16131 loss: 2.0294 loss_prob: 1.2099 loss_thr: 0.6272 loss_db: 0.1923 2022/10/25 22:13:10 - mmengine - INFO - Epoch(train) [213][45/63] lr: 2.9675e-03 eta: 14:12:51 time: 0.8095 data_time: 0.0082 memory: 16131 loss: 2.0830 loss_prob: 1.2384 loss_thr: 0.6411 loss_db: 0.2035 2022/10/25 22:13:16 - mmengine - INFO - Epoch(train) [213][50/63] lr: 2.9675e-03 eta: 14:12:54 time: 1.0817 data_time: 0.0274 memory: 16131 loss: 2.1611 loss_prob: 1.2995 loss_thr: 0.6469 loss_db: 0.2147 2022/10/25 22:13:20 - mmengine - INFO - Epoch(train) [213][55/63] lr: 2.9675e-03 eta: 14:12:54 time: 1.0476 data_time: 0.0243 memory: 16131 loss: 2.2790 loss_prob: 1.4021 loss_thr: 0.6459 loss_db: 0.2310 2022/10/25 22:13:26 - mmengine - INFO - Epoch(train) [213][60/63] lr: 2.9675e-03 eta: 14:12:55 time: 1.0174 data_time: 0.0062 memory: 16131 loss: 2.3596 loss_prob: 1.4578 loss_thr: 0.6637 loss_db: 0.2382 2022/10/25 22:13:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:13:37 - mmengine - INFO - Epoch(train) [214][5/63] lr: 2.9648e-03 eta: 14:12:55 time: 1.3239 data_time: 0.2303 memory: 16131 loss: 2.4468 loss_prob: 1.5303 loss_thr: 0.6686 loss_db: 0.2479 2022/10/25 22:13:43 - mmengine - INFO - Epoch(train) [214][10/63] lr: 2.9648e-03 eta: 14:13:04 time: 1.4916 data_time: 0.2311 memory: 16131 loss: 2.4036 loss_prob: 1.4823 loss_thr: 0.6792 loss_db: 0.2421 2022/10/25 22:13:48 - mmengine - INFO - Epoch(train) [214][15/63] lr: 2.9648e-03 eta: 14:13:04 time: 1.0987 data_time: 0.0084 memory: 16131 loss: 2.4843 loss_prob: 1.5480 loss_thr: 0.6844 loss_db: 0.2520 2022/10/25 22:13:56 - mmengine - INFO - Epoch(train) [214][20/63] lr: 2.9648e-03 eta: 14:13:16 time: 1.2619 data_time: 0.0071 memory: 16131 loss: 2.8838 loss_prob: 1.8509 loss_thr: 0.7322 loss_db: 0.3007 2022/10/25 22:14:00 - mmengine - INFO - Epoch(train) [214][25/63] lr: 2.9648e-03 eta: 14:13:16 time: 1.1357 data_time: 0.0200 memory: 16131 loss: 2.7493 loss_prob: 1.7454 loss_thr: 0.7223 loss_db: 0.2816 2022/10/25 22:14:03 - mmengine - INFO - Epoch(train) [214][30/63] lr: 2.9648e-03 eta: 14:13:02 time: 0.6869 data_time: 0.0326 memory: 16131 loss: 2.4110 loss_prob: 1.5032 loss_thr: 0.6688 loss_db: 0.2391 2022/10/25 22:14:06 - mmengine - INFO - Epoch(train) [214][35/63] lr: 2.9648e-03 eta: 14:13:02 time: 0.6513 data_time: 0.0273 memory: 16131 loss: 2.5504 loss_prob: 1.5937 loss_thr: 0.6976 loss_db: 0.2591 2022/10/25 22:14:11 - mmengine - INFO - Epoch(train) [214][40/63] lr: 2.9648e-03 eta: 14:12:55 time: 0.8551 data_time: 0.0140 memory: 16131 loss: 2.5406 loss_prob: 1.5804 loss_thr: 0.6994 loss_db: 0.2608 2022/10/25 22:14:14 - mmengine - INFO - Epoch(train) [214][45/63] lr: 2.9648e-03 eta: 14:12:55 time: 0.8129 data_time: 0.0100 memory: 16131 loss: 2.4511 loss_prob: 1.5045 loss_thr: 0.6991 loss_db: 0.2475 2022/10/25 22:14:18 - mmengine - INFO - Epoch(train) [214][50/63] lr: 2.9648e-03 eta: 14:12:39 time: 0.6608 data_time: 0.0246 memory: 16131 loss: 2.2715 loss_prob: 1.3643 loss_thr: 0.6870 loss_db: 0.2201 2022/10/25 22:14:24 - mmengine - INFO - Epoch(train) [214][55/63] lr: 2.9648e-03 eta: 14:12:39 time: 0.9303 data_time: 0.0223 memory: 16131 loss: 2.1050 loss_prob: 1.2507 loss_thr: 0.6577 loss_db: 0.1967 2022/10/25 22:14:30 - mmengine - INFO - Epoch(train) [214][60/63] lr: 2.9648e-03 eta: 14:12:48 time: 1.1902 data_time: 0.0098 memory: 16131 loss: 2.4334 loss_prob: 1.5077 loss_thr: 0.6879 loss_db: 0.2378 2022/10/25 22:14:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:14:40 - mmengine - INFO - Epoch(train) [215][5/63] lr: 2.9621e-03 eta: 14:12:48 time: 1.2631 data_time: 0.2546 memory: 16131 loss: 2.1774 loss_prob: 1.3033 loss_thr: 0.6651 loss_db: 0.2090 2022/10/25 22:14:45 - mmengine - INFO - Epoch(train) [215][10/63] lr: 2.9621e-03 eta: 14:12:47 time: 1.2921 data_time: 0.2537 memory: 16131 loss: 2.1309 loss_prob: 1.2801 loss_thr: 0.6470 loss_db: 0.2038 2022/10/25 22:14:50 - mmengine - INFO - Epoch(train) [215][15/63] lr: 2.9621e-03 eta: 14:12:47 time: 0.9896 data_time: 0.0066 memory: 16131 loss: 2.0221 loss_prob: 1.2024 loss_thr: 0.6282 loss_db: 0.1915 2022/10/25 22:14:56 - mmengine - INFO - Epoch(train) [215][20/63] lr: 2.9621e-03 eta: 14:12:53 time: 1.1197 data_time: 0.0084 memory: 16131 loss: 2.1062 loss_prob: 1.2583 loss_thr: 0.6475 loss_db: 0.2005 2022/10/25 22:15:01 - mmengine - INFO - Epoch(train) [215][25/63] lr: 2.9621e-03 eta: 14:12:53 time: 1.0341 data_time: 0.0437 memory: 16131 loss: 2.2749 loss_prob: 1.3773 loss_thr: 0.6770 loss_db: 0.2207 2022/10/25 22:15:06 - mmengine - INFO - Epoch(train) [215][30/63] lr: 2.9621e-03 eta: 14:12:53 time: 1.0178 data_time: 0.0429 memory: 16131 loss: 2.3585 loss_prob: 1.4330 loss_thr: 0.6977 loss_db: 0.2278 2022/10/25 22:15:12 - mmengine - INFO - Epoch(train) [215][35/63] lr: 2.9621e-03 eta: 14:12:53 time: 1.1815 data_time: 0.0098 memory: 16131 loss: 2.2670 loss_prob: 1.3639 loss_thr: 0.6869 loss_db: 0.2162 2022/10/25 22:15:17 - mmengine - INFO - Epoch(train) [215][40/63] lr: 2.9621e-03 eta: 14:12:58 time: 1.1061 data_time: 0.0085 memory: 16131 loss: 2.2472 loss_prob: 1.3411 loss_thr: 0.6866 loss_db: 0.2195 2022/10/25 22:15:24 - mmengine - INFO - Epoch(train) [215][45/63] lr: 2.9621e-03 eta: 14:12:58 time: 1.1582 data_time: 0.0113 memory: 16131 loss: 2.1920 loss_prob: 1.3117 loss_thr: 0.6655 loss_db: 0.2147 2022/10/25 22:15:27 - mmengine - INFO - Epoch(train) [215][50/63] lr: 2.9621e-03 eta: 14:12:58 time: 1.0083 data_time: 0.0316 memory: 16131 loss: 2.1604 loss_prob: 1.2988 loss_thr: 0.6560 loss_db: 0.2057 2022/10/25 22:15:30 - mmengine - INFO - Epoch(train) [215][55/63] lr: 2.9621e-03 eta: 14:12:58 time: 0.6385 data_time: 0.0253 memory: 16131 loss: 2.3033 loss_prob: 1.3944 loss_thr: 0.6804 loss_db: 0.2285 2022/10/25 22:15:36 - mmengine - INFO - Epoch(train) [215][60/63] lr: 2.9621e-03 eta: 14:12:52 time: 0.8725 data_time: 0.0046 memory: 16131 loss: 2.3708 loss_prob: 1.4595 loss_thr: 0.6764 loss_db: 0.2349 2022/10/25 22:15:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:15:46 - mmengine - INFO - Epoch(train) [216][5/63] lr: 2.9594e-03 eta: 14:12:52 time: 1.2197 data_time: 0.2548 memory: 16131 loss: 2.3988 loss_prob: 1.4757 loss_thr: 0.6837 loss_db: 0.2394 2022/10/25 22:15:53 - mmengine - INFO - Epoch(train) [216][10/63] lr: 2.9594e-03 eta: 14:12:56 time: 1.3933 data_time: 0.2583 memory: 16131 loss: 2.6093 loss_prob: 1.6214 loss_thr: 0.7162 loss_db: 0.2718 2022/10/25 22:16:00 - mmengine - INFO - Epoch(train) [216][15/63] lr: 2.9594e-03 eta: 14:12:56 time: 1.4222 data_time: 0.0089 memory: 16131 loss: 2.3736 loss_prob: 1.4574 loss_thr: 0.6751 loss_db: 0.2410 2022/10/25 22:16:06 - mmengine - INFO - Epoch(train) [216][20/63] lr: 2.9594e-03 eta: 14:13:10 time: 1.3066 data_time: 0.0075 memory: 16131 loss: 2.2572 loss_prob: 1.3777 loss_thr: 0.6572 loss_db: 0.2223 2022/10/25 22:16:12 - mmengine - INFO - Epoch(train) [216][25/63] lr: 2.9594e-03 eta: 14:13:10 time: 1.1950 data_time: 0.0217 memory: 16131 loss: 2.3023 loss_prob: 1.4036 loss_thr: 0.6728 loss_db: 0.2259 2022/10/25 22:16:16 - mmengine - INFO - Epoch(train) [216][30/63] lr: 2.9594e-03 eta: 14:13:11 time: 1.0380 data_time: 0.0499 memory: 16131 loss: 2.1437 loss_prob: 1.2772 loss_thr: 0.6618 loss_db: 0.2047 2022/10/25 22:16:20 - mmengine - INFO - Epoch(train) [216][35/63] lr: 2.9594e-03 eta: 14:13:11 time: 0.8015 data_time: 0.0355 memory: 16131 loss: 2.2120 loss_prob: 1.3474 loss_thr: 0.6500 loss_db: 0.2146 2022/10/25 22:16:23 - mmengine - INFO - Epoch(train) [216][40/63] lr: 2.9594e-03 eta: 14:12:58 time: 0.7086 data_time: 0.0055 memory: 16131 loss: 2.2699 loss_prob: 1.3945 loss_thr: 0.6524 loss_db: 0.2230 2022/10/25 22:16:27 - mmengine - INFO - Epoch(train) [216][45/63] lr: 2.9594e-03 eta: 14:12:58 time: 0.6997 data_time: 0.0070 memory: 16131 loss: 2.3507 loss_prob: 1.4307 loss_thr: 0.6852 loss_db: 0.2349 2022/10/25 22:16:31 - mmengine - INFO - Epoch(train) [216][50/63] lr: 2.9594e-03 eta: 14:12:47 time: 0.7750 data_time: 0.0184 memory: 16131 loss: 2.3850 loss_prob: 1.4530 loss_thr: 0.6961 loss_db: 0.2359 2022/10/25 22:16:34 - mmengine - INFO - Epoch(train) [216][55/63] lr: 2.9594e-03 eta: 14:12:47 time: 0.6786 data_time: 0.0298 memory: 16131 loss: 2.4557 loss_prob: 1.5263 loss_thr: 0.6860 loss_db: 0.2435 2022/10/25 22:16:38 - mmengine - INFO - Epoch(train) [216][60/63] lr: 2.9594e-03 eta: 14:12:35 time: 0.7319 data_time: 0.0218 memory: 16131 loss: 2.5664 loss_prob: 1.5973 loss_thr: 0.7064 loss_db: 0.2627 2022/10/25 22:16:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:16:46 - mmengine - INFO - Epoch(train) [217][5/63] lr: 2.9567e-03 eta: 14:12:35 time: 1.0424 data_time: 0.2159 memory: 16131 loss: 2.5210 loss_prob: 1.5431 loss_thr: 0.7227 loss_db: 0.2552 2022/10/25 22:16:51 - mmengine - INFO - Epoch(train) [217][10/63] lr: 2.9567e-03 eta: 14:12:27 time: 1.1397 data_time: 0.2164 memory: 16131 loss: 2.4759 loss_prob: 1.5312 loss_thr: 0.6907 loss_db: 0.2540 2022/10/25 22:16:58 - mmengine - INFO - Epoch(train) [217][15/63] lr: 2.9567e-03 eta: 14:12:27 time: 1.1439 data_time: 0.0067 memory: 16131 loss: 2.2839 loss_prob: 1.3911 loss_thr: 0.6642 loss_db: 0.2285 2022/10/25 22:17:04 - mmengine - INFO - Epoch(train) [217][20/63] lr: 2.9567e-03 eta: 14:12:41 time: 1.3246 data_time: 0.0096 memory: 16131 loss: 2.3827 loss_prob: 1.4494 loss_thr: 0.6935 loss_db: 0.2398 2022/10/25 22:17:07 - mmengine - INFO - Epoch(train) [217][25/63] lr: 2.9567e-03 eta: 14:12:41 time: 0.9294 data_time: 0.0343 memory: 16131 loss: 2.3389 loss_prob: 1.4151 loss_thr: 0.6938 loss_db: 0.2300 2022/10/25 22:17:11 - mmengine - INFO - Epoch(train) [217][30/63] lr: 2.9567e-03 eta: 14:12:28 time: 0.7049 data_time: 0.0491 memory: 16131 loss: 2.2018 loss_prob: 1.3306 loss_thr: 0.6539 loss_db: 0.2173 2022/10/25 22:17:15 - mmengine - INFO - Epoch(train) [217][35/63] lr: 2.9567e-03 eta: 14:12:28 time: 0.7480 data_time: 0.0237 memory: 16131 loss: 2.1100 loss_prob: 1.2609 loss_thr: 0.6364 loss_db: 0.2127 2022/10/25 22:17:19 - mmengine - INFO - Epoch(train) [217][40/63] lr: 2.9567e-03 eta: 14:12:18 time: 0.7917 data_time: 0.0108 memory: 16131 loss: 2.1807 loss_prob: 1.2949 loss_thr: 0.6711 loss_db: 0.2148 2022/10/25 22:17:26 - mmengine - INFO - Epoch(train) [217][45/63] lr: 2.9567e-03 eta: 14:12:18 time: 1.1272 data_time: 0.0122 memory: 16131 loss: 2.1822 loss_prob: 1.3083 loss_thr: 0.6570 loss_db: 0.2169 2022/10/25 22:17:33 - mmengine - INFO - Epoch(train) [217][50/63] lr: 2.9567e-03 eta: 14:12:32 time: 1.3250 data_time: 0.0230 memory: 16131 loss: 2.1699 loss_prob: 1.3145 loss_thr: 0.6408 loss_db: 0.2146 2022/10/25 22:17:37 - mmengine - INFO - Epoch(train) [217][55/63] lr: 2.9567e-03 eta: 14:12:32 time: 1.0994 data_time: 0.0233 memory: 16131 loss: 2.1831 loss_prob: 1.3128 loss_thr: 0.6560 loss_db: 0.2143 2022/10/25 22:17:40 - mmengine - INFO - Epoch(train) [217][60/63] lr: 2.9567e-03 eta: 14:12:20 time: 0.7327 data_time: 0.0087 memory: 16131 loss: 2.1382 loss_prob: 1.2629 loss_thr: 0.6671 loss_db: 0.2082 2022/10/25 22:17:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:17:47 - mmengine - INFO - Epoch(train) [218][5/63] lr: 2.9540e-03 eta: 14:12:20 time: 0.8660 data_time: 0.2049 memory: 16131 loss: 2.1255 loss_prob: 1.2674 loss_thr: 0.6515 loss_db: 0.2066 2022/10/25 22:17:51 - mmengine - INFO - Epoch(train) [218][10/63] lr: 2.9540e-03 eta: 14:12:05 time: 0.9892 data_time: 0.2174 memory: 16131 loss: 2.0690 loss_prob: 1.2382 loss_thr: 0.6330 loss_db: 0.1979 2022/10/25 22:17:58 - mmengine - INFO - Epoch(train) [218][15/63] lr: 2.9540e-03 eta: 14:12:05 time: 1.0175 data_time: 0.0455 memory: 16131 loss: 2.1839 loss_prob: 1.3075 loss_thr: 0.6656 loss_db: 0.2109 2022/10/25 22:18:04 - mmengine - INFO - Epoch(train) [218][20/63] lr: 2.9540e-03 eta: 14:12:18 time: 1.2864 data_time: 0.0324 memory: 16131 loss: 2.2471 loss_prob: 1.3524 loss_thr: 0.6757 loss_db: 0.2190 2022/10/25 22:18:11 - mmengine - INFO - Epoch(train) [218][25/63] lr: 2.9540e-03 eta: 14:12:18 time: 1.3247 data_time: 0.0073 memory: 16131 loss: 2.2250 loss_prob: 1.3501 loss_thr: 0.6586 loss_db: 0.2163 2022/10/25 22:18:14 - mmengine - INFO - Epoch(train) [218][30/63] lr: 2.9540e-03 eta: 14:12:18 time: 1.0195 data_time: 0.0113 memory: 16131 loss: 2.1642 loss_prob: 1.2944 loss_thr: 0.6615 loss_db: 0.2082 2022/10/25 22:18:22 - mmengine - INFO - Epoch(train) [218][35/63] lr: 2.9540e-03 eta: 14:12:18 time: 1.1150 data_time: 0.0240 memory: 16131 loss: 2.0765 loss_prob: 1.2217 loss_thr: 0.6548 loss_db: 0.1999 2022/10/25 22:18:27 - mmengine - INFO - Epoch(train) [218][40/63] lr: 2.9540e-03 eta: 14:12:30 time: 1.2563 data_time: 0.0196 memory: 16131 loss: 2.0309 loss_prob: 1.2010 loss_thr: 0.6352 loss_db: 0.1947 2022/10/25 22:18:32 - mmengine - INFO - Epoch(train) [218][45/63] lr: 2.9540e-03 eta: 14:12:30 time: 0.9622 data_time: 0.0050 memory: 16131 loss: 2.0688 loss_prob: 1.2237 loss_thr: 0.6446 loss_db: 0.2004 2022/10/25 22:18:37 - mmengine - INFO - Epoch(train) [218][50/63] lr: 2.9540e-03 eta: 14:12:30 time: 1.0238 data_time: 0.0063 memory: 16131 loss: 2.1141 loss_prob: 1.2481 loss_thr: 0.6568 loss_db: 0.2092 2022/10/25 22:18:41 - mmengine - INFO - Epoch(train) [218][55/63] lr: 2.9540e-03 eta: 14:12:30 time: 0.9847 data_time: 0.0138 memory: 16131 loss: 2.1509 loss_prob: 1.2820 loss_thr: 0.6611 loss_db: 0.2078 2022/10/25 22:18:46 - mmengine - INFO - Epoch(train) [218][60/63] lr: 2.9540e-03 eta: 14:12:24 time: 0.8783 data_time: 0.0155 memory: 16131 loss: 2.2283 loss_prob: 1.3294 loss_thr: 0.6817 loss_db: 0.2173 2022/10/25 22:18:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:18:56 - mmengine - INFO - Epoch(train) [219][5/63] lr: 2.9513e-03 eta: 14:12:24 time: 1.1604 data_time: 0.2519 memory: 16131 loss: 2.2370 loss_prob: 1.3836 loss_thr: 0.6289 loss_db: 0.2245 2022/10/25 22:19:03 - mmengine - INFO - Epoch(train) [219][10/63] lr: 2.9513e-03 eta: 14:12:34 time: 1.5264 data_time: 0.2557 memory: 16131 loss: 2.2361 loss_prob: 1.3927 loss_thr: 0.6143 loss_db: 0.2291 2022/10/25 22:19:07 - mmengine - INFO - Epoch(train) [219][15/63] lr: 2.9513e-03 eta: 14:12:34 time: 1.0846 data_time: 0.0162 memory: 16131 loss: 2.2738 loss_prob: 1.3904 loss_thr: 0.6499 loss_db: 0.2334 2022/10/25 22:19:12 - mmengine - INFO - Epoch(train) [219][20/63] lr: 2.9513e-03 eta: 14:12:30 time: 0.9277 data_time: 0.0111 memory: 16131 loss: 2.2401 loss_prob: 1.3458 loss_thr: 0.6735 loss_db: 0.2208 2022/10/25 22:19:16 - mmengine - INFO - Epoch(train) [219][25/63] lr: 2.9513e-03 eta: 14:12:30 time: 0.9058 data_time: 0.0406 memory: 16131 loss: 2.3197 loss_prob: 1.4059 loss_thr: 0.6857 loss_db: 0.2282 2022/10/25 22:19:23 - mmengine - INFO - Epoch(train) [219][30/63] lr: 2.9513e-03 eta: 14:12:30 time: 1.0069 data_time: 0.0421 memory: 16131 loss: 2.3568 loss_prob: 1.4298 loss_thr: 0.6954 loss_db: 0.2316 2022/10/25 22:19:29 - mmengine - INFO - Epoch(train) [219][35/63] lr: 2.9513e-03 eta: 14:12:30 time: 1.2376 data_time: 0.0188 memory: 16131 loss: 2.2399 loss_prob: 1.3584 loss_thr: 0.6619 loss_db: 0.2197 2022/10/25 22:19:34 - mmengine - INFO - Epoch(train) [219][40/63] lr: 2.9513e-03 eta: 14:12:37 time: 1.1729 data_time: 0.0184 memory: 16131 loss: 2.2630 loss_prob: 1.3826 loss_thr: 0.6564 loss_db: 0.2240 2022/10/25 22:19:38 - mmengine - INFO - Epoch(train) [219][45/63] lr: 2.9513e-03 eta: 14:12:37 time: 0.9502 data_time: 0.0069 memory: 16131 loss: 2.5527 loss_prob: 1.5892 loss_thr: 0.7043 loss_db: 0.2591 2022/10/25 22:19:41 - mmengine - INFO - Epoch(train) [219][50/63] lr: 2.9513e-03 eta: 14:12:22 time: 0.6655 data_time: 0.0236 memory: 16131 loss: 2.5102 loss_prob: 1.5479 loss_thr: 0.7041 loss_db: 0.2582 2022/10/25 22:19:46 - mmengine - INFO - Epoch(train) [219][55/63] lr: 2.9513e-03 eta: 14:12:22 time: 0.8274 data_time: 0.0273 memory: 16131 loss: 2.2819 loss_prob: 1.3756 loss_thr: 0.6761 loss_db: 0.2302 2022/10/25 22:19:49 - mmengine - INFO - Epoch(train) [219][60/63] lr: 2.9513e-03 eta: 14:12:13 time: 0.8311 data_time: 0.0096 memory: 16131 loss: 2.1310 loss_prob: 1.2775 loss_thr: 0.6480 loss_db: 0.2055 2022/10/25 22:19:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:19:59 - mmengine - INFO - Epoch(train) [220][5/63] lr: 2.9486e-03 eta: 14:12:13 time: 1.0413 data_time: 0.2302 memory: 16131 loss: 2.1081 loss_prob: 1.2484 loss_thr: 0.6576 loss_db: 0.2021 2022/10/25 22:20:03 - mmengine - INFO - Epoch(train) [220][10/63] lr: 2.9486e-03 eta: 14:12:05 time: 1.1325 data_time: 0.2321 memory: 16131 loss: 2.1283 loss_prob: 1.2736 loss_thr: 0.6463 loss_db: 0.2083 2022/10/25 22:20:08 - mmengine - INFO - Epoch(train) [220][15/63] lr: 2.9486e-03 eta: 14:12:05 time: 0.9300 data_time: 0.0119 memory: 16131 loss: 2.1233 loss_prob: 1.2781 loss_thr: 0.6387 loss_db: 0.2065 2022/10/25 22:20:13 - mmengine - INFO - Epoch(train) [220][20/63] lr: 2.9486e-03 eta: 14:12:03 time: 0.9556 data_time: 0.0110 memory: 16131 loss: 2.3069 loss_prob: 1.4165 loss_thr: 0.6564 loss_db: 0.2340 2022/10/25 22:20:18 - mmengine - INFO - Epoch(train) [220][25/63] lr: 2.9486e-03 eta: 14:12:03 time: 1.0236 data_time: 0.0275 memory: 16131 loss: 2.4147 loss_prob: 1.4945 loss_thr: 0.6756 loss_db: 0.2446 2022/10/25 22:20:22 - mmengine - INFO - Epoch(train) [220][30/63] lr: 2.9486e-03 eta: 14:12:01 time: 0.9731 data_time: 0.0375 memory: 16131 loss: 2.5476 loss_prob: 1.5953 loss_thr: 0.6938 loss_db: 0.2584 2022/10/25 22:20:27 - mmengine - INFO - Epoch(train) [220][35/63] lr: 2.9486e-03 eta: 14:12:01 time: 0.9231 data_time: 0.0195 memory: 16131 loss: 2.5859 loss_prob: 1.6162 loss_thr: 0.7014 loss_db: 0.2682 2022/10/25 22:20:33 - mmengine - INFO - Epoch(train) [220][40/63] lr: 2.9486e-03 eta: 14:12:01 time: 1.0187 data_time: 0.0087 memory: 16131 loss: 2.2839 loss_prob: 1.3985 loss_thr: 0.6557 loss_db: 0.2297 2022/10/25 22:20:35 - mmengine - INFO - Epoch(train) [220][45/63] lr: 2.9486e-03 eta: 14:12:01 time: 0.8069 data_time: 0.0079 memory: 16131 loss: 2.3698 loss_prob: 1.4811 loss_thr: 0.6489 loss_db: 0.2399 2022/10/25 22:20:40 - mmengine - INFO - Epoch(train) [220][50/63] lr: 2.9486e-03 eta: 14:11:51 time: 0.7785 data_time: 0.0250 memory: 16131 loss: 2.4886 loss_prob: 1.5347 loss_thr: 0.7019 loss_db: 0.2521 2022/10/25 22:20:45 - mmengine - INFO - Epoch(train) [220][55/63] lr: 2.9486e-03 eta: 14:11:51 time: 0.9873 data_time: 0.0252 memory: 16131 loss: 2.4639 loss_prob: 1.5132 loss_thr: 0.7047 loss_db: 0.2460 2022/10/25 22:20:52 - mmengine - INFO - Epoch(train) [220][60/63] lr: 2.9486e-03 eta: 14:11:57 time: 1.1527 data_time: 0.0198 memory: 16131 loss: 2.3524 loss_prob: 1.4381 loss_thr: 0.6798 loss_db: 0.2345 2022/10/25 22:20:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:20:55 - mmengine - INFO - Saving checkpoint at 220 epochs 2022/10/25 22:21:02 - mmengine - INFO - Epoch(val) [220][5/32] eta: 14:11:57 time: 0.5619 data_time: 0.0729 memory: 16131 2022/10/25 22:21:05 - mmengine - INFO - Epoch(val) [220][10/32] eta: 0:00:13 time: 0.6341 data_time: 0.0986 memory: 15724 2022/10/25 22:21:08 - mmengine - INFO - Epoch(val) [220][15/32] eta: 0:00:13 time: 0.5910 data_time: 0.0521 memory: 15724 2022/10/25 22:21:11 - mmengine - INFO - Epoch(val) [220][20/32] eta: 0:00:07 time: 0.5891 data_time: 0.0748 memory: 15724 2022/10/25 22:21:14 - mmengine - INFO - Epoch(val) [220][25/32] eta: 0:00:07 time: 0.5929 data_time: 0.0673 memory: 15724 2022/10/25 22:21:16 - mmengine - INFO - Epoch(val) [220][30/32] eta: 0:00:01 time: 0.5483 data_time: 0.0207 memory: 15724 2022/10/25 22:21:17 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7573, precision: 0.6195, hmean: 0.6815 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7573, precision: 0.7219, hmean: 0.7392 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7540, precision: 0.7881, hmean: 0.7707 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7285, precision: 0.8443, hmean: 0.7821 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.5970, precision: 0.9098, hmean: 0.7209 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1391, precision: 0.9698, hmean: 0.2434 2022/10/25 22:21:17 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 22:21:17 - mmengine - INFO - Epoch(val) [220][32/32] icdar/precision: 0.8443 icdar/recall: 0.7285 icdar/hmean: 0.7821 2022/10/25 22:21:23 - mmengine - INFO - Epoch(train) [221][5/63] lr: 2.9459e-03 eta: 0:00:01 time: 1.2324 data_time: 0.1797 memory: 16131 loss: 2.1265 loss_prob: 1.2625 loss_thr: 0.6546 loss_db: 0.2094 2022/10/25 22:21:27 - mmengine - INFO - Epoch(train) [221][10/63] lr: 2.9459e-03 eta: 14:11:42 time: 0.9722 data_time: 0.1819 memory: 16131 loss: 2.0917 loss_prob: 1.2531 loss_thr: 0.6365 loss_db: 0.2021 2022/10/25 22:21:36 - mmengine - INFO - Epoch(train) [221][15/63] lr: 2.9459e-03 eta: 14:11:42 time: 1.2620 data_time: 0.0112 memory: 16131 loss: 2.1809 loss_prob: 1.3173 loss_thr: 0.6495 loss_db: 0.2141 2022/10/25 22:21:43 - mmengine - INFO - Epoch(train) [221][20/63] lr: 2.9459e-03 eta: 14:12:08 time: 1.6107 data_time: 0.0088 memory: 16131 loss: 2.1757 loss_prob: 1.3071 loss_thr: 0.6518 loss_db: 0.2168 2022/10/25 22:21:46 - mmengine - INFO - Epoch(train) [221][25/63] lr: 2.9459e-03 eta: 14:12:08 time: 0.9721 data_time: 0.0223 memory: 16131 loss: 2.1500 loss_prob: 1.2862 loss_thr: 0.6509 loss_db: 0.2129 2022/10/25 22:21:49 - mmengine - INFO - Epoch(train) [221][30/63] lr: 2.9459e-03 eta: 14:11:48 time: 0.5715 data_time: 0.0426 memory: 16131 loss: 2.0847 loss_prob: 1.2378 loss_thr: 0.6442 loss_db: 0.2027 2022/10/25 22:21:56 - mmengine - INFO - Epoch(train) [221][35/63] lr: 2.9459e-03 eta: 14:11:48 time: 1.0417 data_time: 0.0293 memory: 16131 loss: 2.1092 loss_prob: 1.2650 loss_thr: 0.6434 loss_db: 0.2008 2022/10/25 22:22:01 - mmengine - INFO - Epoch(train) [221][40/63] lr: 2.9459e-03 eta: 14:11:57 time: 1.2015 data_time: 0.0084 memory: 16131 loss: 2.1443 loss_prob: 1.2696 loss_thr: 0.6690 loss_db: 0.2057 2022/10/25 22:22:05 - mmengine - INFO - Epoch(train) [221][45/63] lr: 2.9459e-03 eta: 14:11:57 time: 0.9127 data_time: 0.0108 memory: 16131 loss: 2.1335 loss_prob: 1.2686 loss_thr: 0.6562 loss_db: 0.2088 2022/10/25 22:22:10 - mmengine - INFO - Epoch(train) [221][50/63] lr: 2.9459e-03 eta: 14:11:52 time: 0.9183 data_time: 0.0239 memory: 16131 loss: 2.1829 loss_prob: 1.3210 loss_thr: 0.6496 loss_db: 0.2124 2022/10/25 22:22:13 - mmengine - INFO - Epoch(train) [221][55/63] lr: 2.9459e-03 eta: 14:11:52 time: 0.7559 data_time: 0.0292 memory: 16131 loss: 2.1723 loss_prob: 1.2981 loss_thr: 0.6615 loss_db: 0.2127 2022/10/25 22:22:16 - mmengine - INFO - Epoch(train) [221][60/63] lr: 2.9459e-03 eta: 14:11:35 time: 0.6161 data_time: 0.0191 memory: 16131 loss: 2.1758 loss_prob: 1.2967 loss_thr: 0.6640 loss_db: 0.2152 2022/10/25 22:22:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:22:24 - mmengine - INFO - Epoch(train) [222][5/63] lr: 2.9432e-03 eta: 14:11:35 time: 0.9343 data_time: 0.1947 memory: 16131 loss: 2.5045 loss_prob: 1.5445 loss_thr: 0.7044 loss_db: 0.2557 2022/10/25 22:22:27 - mmengine - INFO - Epoch(train) [222][10/63] lr: 2.9432e-03 eta: 14:11:18 time: 0.9393 data_time: 0.2018 memory: 16131 loss: 2.2768 loss_prob: 1.3632 loss_thr: 0.6885 loss_db: 0.2251 2022/10/25 22:22:30 - mmengine - INFO - Epoch(train) [222][15/63] lr: 2.9432e-03 eta: 14:11:18 time: 0.6228 data_time: 0.0163 memory: 16131 loss: 2.0880 loss_prob: 1.2391 loss_thr: 0.6455 loss_db: 0.2034 2022/10/25 22:22:34 - mmengine - INFO - Epoch(train) [222][20/63] lr: 2.9432e-03 eta: 14:11:01 time: 0.6370 data_time: 0.0080 memory: 16131 loss: 2.1626 loss_prob: 1.3114 loss_thr: 0.6409 loss_db: 0.2102 2022/10/25 22:22:38 - mmengine - INFO - Epoch(train) [222][25/63] lr: 2.9432e-03 eta: 14:11:01 time: 0.7862 data_time: 0.0166 memory: 16131 loss: 2.2044 loss_prob: 1.3354 loss_thr: 0.6555 loss_db: 0.2135 2022/10/25 22:22:41 - mmengine - INFO - Epoch(train) [222][30/63] lr: 2.9432e-03 eta: 14:10:50 time: 0.7533 data_time: 0.0379 memory: 16131 loss: 2.0336 loss_prob: 1.2045 loss_thr: 0.6324 loss_db: 0.1967 2022/10/25 22:22:48 - mmengine - INFO - Epoch(train) [222][35/63] lr: 2.9432e-03 eta: 14:10:50 time: 0.9490 data_time: 0.0338 memory: 16131 loss: 2.0724 loss_prob: 1.2444 loss_thr: 0.6238 loss_db: 0.2042 2022/10/25 22:22:53 - mmengine - INFO - Epoch(train) [222][40/63] lr: 2.9432e-03 eta: 14:10:56 time: 1.1552 data_time: 0.0104 memory: 16131 loss: 2.3253 loss_prob: 1.4472 loss_thr: 0.6458 loss_db: 0.2323 2022/10/25 22:22:57 - mmengine - INFO - Epoch(train) [222][45/63] lr: 2.9432e-03 eta: 14:10:56 time: 0.9646 data_time: 0.0084 memory: 16131 loss: 2.4585 loss_prob: 1.5329 loss_thr: 0.6845 loss_db: 0.2411 2022/10/25 22:23:02 - mmengine - INFO - Epoch(train) [222][50/63] lr: 2.9432e-03 eta: 14:10:51 time: 0.8993 data_time: 0.0179 memory: 16131 loss: 2.2322 loss_prob: 1.3551 loss_thr: 0.6562 loss_db: 0.2208 2022/10/25 22:23:07 - mmengine - INFO - Epoch(train) [222][55/63] lr: 2.9432e-03 eta: 14:10:51 time: 0.9476 data_time: 0.0229 memory: 16131 loss: 2.0725 loss_prob: 1.2371 loss_thr: 0.6267 loss_db: 0.2087 2022/10/25 22:23:11 - mmengine - INFO - Epoch(train) [222][60/63] lr: 2.9432e-03 eta: 14:10:47 time: 0.9459 data_time: 0.0162 memory: 16131 loss: 2.0277 loss_prob: 1.2059 loss_thr: 0.6248 loss_db: 0.1970 2022/10/25 22:23:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:23:21 - mmengine - INFO - Epoch(train) [223][5/63] lr: 2.9405e-03 eta: 14:10:47 time: 1.0313 data_time: 0.2041 memory: 16131 loss: 2.0493 loss_prob: 1.2248 loss_thr: 0.6290 loss_db: 0.1955 2022/10/25 22:23:23 - mmengine - INFO - Epoch(train) [223][10/63] lr: 2.9405e-03 eta: 14:10:35 time: 1.0338 data_time: 0.2062 memory: 16131 loss: 2.2038 loss_prob: 1.3057 loss_thr: 0.6822 loss_db: 0.2160 2022/10/25 22:23:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:23:29 - mmengine - INFO - Epoch(train) [223][15/63] lr: 2.9405e-03 eta: 14:10:35 time: 0.7879 data_time: 0.0135 memory: 16131 loss: 2.1914 loss_prob: 1.2892 loss_thr: 0.6895 loss_db: 0.2127 2022/10/25 22:23:34 - mmengine - INFO - Epoch(train) [223][20/63] lr: 2.9405e-03 eta: 14:10:35 time: 1.0269 data_time: 0.0116 memory: 16131 loss: 2.2346 loss_prob: 1.3283 loss_thr: 0.6920 loss_db: 0.2143 2022/10/25 22:23:38 - mmengine - INFO - Epoch(train) [223][25/63] lr: 2.9405e-03 eta: 14:10:35 time: 0.9725 data_time: 0.0342 memory: 16131 loss: 2.2214 loss_prob: 1.3308 loss_thr: 0.6768 loss_db: 0.2138 2022/10/25 22:23:42 - mmengine - INFO - Epoch(train) [223][30/63] lr: 2.9405e-03 eta: 14:10:27 time: 0.8297 data_time: 0.0338 memory: 16131 loss: 2.1243 loss_prob: 1.2798 loss_thr: 0.6297 loss_db: 0.2148 2022/10/25 22:23:48 - mmengine - INFO - Epoch(train) [223][35/63] lr: 2.9405e-03 eta: 14:10:27 time: 0.9721 data_time: 0.0071 memory: 16131 loss: 2.1888 loss_prob: 1.3428 loss_thr: 0.6217 loss_db: 0.2243 2022/10/25 22:23:50 - mmengine - INFO - Epoch(train) [223][40/63] lr: 2.9405e-03 eta: 14:10:20 time: 0.8525 data_time: 0.0069 memory: 16131 loss: 2.2536 loss_prob: 1.3822 loss_thr: 0.6435 loss_db: 0.2279 2022/10/25 22:23:54 - mmengine - INFO - Epoch(train) [223][45/63] lr: 2.9405e-03 eta: 14:10:20 time: 0.5880 data_time: 0.0055 memory: 16131 loss: 2.4429 loss_prob: 1.5209 loss_thr: 0.6728 loss_db: 0.2492 2022/10/25 22:23:57 - mmengine - INFO - Epoch(train) [223][50/63] lr: 2.9405e-03 eta: 14:10:03 time: 0.6367 data_time: 0.0245 memory: 16131 loss: 2.4343 loss_prob: 1.5072 loss_thr: 0.6853 loss_db: 0.2418 2022/10/25 22:24:00 - mmengine - INFO - Epoch(train) [223][55/63] lr: 2.9405e-03 eta: 14:10:03 time: 0.5952 data_time: 0.0240 memory: 16131 loss: 2.3136 loss_prob: 1.4178 loss_thr: 0.6566 loss_db: 0.2392 2022/10/25 22:24:02 - mmengine - INFO - Epoch(train) [223][60/63] lr: 2.9405e-03 eta: 14:09:43 time: 0.5545 data_time: 0.0066 memory: 16131 loss: 2.2199 loss_prob: 1.3535 loss_thr: 0.6386 loss_db: 0.2278 2022/10/25 22:24:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:24:09 - mmengine - INFO - Epoch(train) [224][5/63] lr: 2.9378e-03 eta: 14:09:43 time: 0.7393 data_time: 0.1612 memory: 16131 loss: 2.1037 loss_prob: 1.2504 loss_thr: 0.6507 loss_db: 0.2027 2022/10/25 22:24:12 - mmengine - INFO - Epoch(train) [224][10/63] lr: 2.9378e-03 eta: 14:09:21 time: 0.8250 data_time: 0.1670 memory: 16131 loss: 2.1402 loss_prob: 1.2725 loss_thr: 0.6553 loss_db: 0.2124 2022/10/25 22:24:17 - mmengine - INFO - Epoch(train) [224][15/63] lr: 2.9378e-03 eta: 14:09:21 time: 0.7857 data_time: 0.0155 memory: 16131 loss: 2.1273 loss_prob: 1.2613 loss_thr: 0.6578 loss_db: 0.2083 2022/10/25 22:24:20 - mmengine - INFO - Epoch(train) [224][20/63] lr: 2.9378e-03 eta: 14:09:13 time: 0.8433 data_time: 0.0069 memory: 16131 loss: 2.0827 loss_prob: 1.2209 loss_thr: 0.6667 loss_db: 0.1951 2022/10/25 22:24:23 - mmengine - INFO - Epoch(train) [224][25/63] lr: 2.9378e-03 eta: 14:09:13 time: 0.6703 data_time: 0.0155 memory: 16131 loss: 2.2140 loss_prob: 1.3298 loss_thr: 0.6669 loss_db: 0.2172 2022/10/25 22:24:28 - mmengine - INFO - Epoch(train) [224][30/63] lr: 2.9378e-03 eta: 14:09:03 time: 0.7859 data_time: 0.0452 memory: 16131 loss: 2.2406 loss_prob: 1.3604 loss_thr: 0.6597 loss_db: 0.2205 2022/10/25 22:24:31 - mmengine - INFO - Epoch(train) [224][35/63] lr: 2.9378e-03 eta: 14:09:03 time: 0.7583 data_time: 0.0423 memory: 16131 loss: 2.1873 loss_prob: 1.3166 loss_thr: 0.6591 loss_db: 0.2116 2022/10/25 22:24:38 - mmengine - INFO - Epoch(train) [224][40/63] lr: 2.9378e-03 eta: 14:09:03 time: 1.0090 data_time: 0.0131 memory: 16131 loss: 2.1175 loss_prob: 1.2635 loss_thr: 0.6506 loss_db: 0.2035 2022/10/25 22:24:44 - mmengine - INFO - Epoch(train) [224][45/63] lr: 2.9378e-03 eta: 14:09:03 time: 1.3576 data_time: 0.0064 memory: 16131 loss: 2.1480 loss_prob: 1.2880 loss_thr: 0.6536 loss_db: 0.2064 2022/10/25 22:24:49 - mmengine - INFO - Epoch(train) [224][50/63] lr: 2.9378e-03 eta: 14:09:05 time: 1.0761 data_time: 0.0154 memory: 16131 loss: 2.1200 loss_prob: 1.2803 loss_thr: 0.6360 loss_db: 0.2037 2022/10/25 22:24:52 - mmengine - INFO - Epoch(train) [224][55/63] lr: 2.9378e-03 eta: 14:09:05 time: 0.7666 data_time: 0.0313 memory: 16131 loss: 2.0382 loss_prob: 1.2261 loss_thr: 0.6166 loss_db: 0.1955 2022/10/25 22:24:57 - mmengine - INFO - Epoch(train) [224][60/63] lr: 2.9378e-03 eta: 14:08:57 time: 0.8323 data_time: 0.0256 memory: 16131 loss: 2.1274 loss_prob: 1.2724 loss_thr: 0.6482 loss_db: 0.2069 2022/10/25 22:24:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:25:05 - mmengine - INFO - Epoch(train) [225][5/63] lr: 2.9351e-03 eta: 14:08:57 time: 0.8627 data_time: 0.2188 memory: 16131 loss: 2.1784 loss_prob: 1.2971 loss_thr: 0.6688 loss_db: 0.2126 2022/10/25 22:25:08 - mmengine - INFO - Epoch(train) [225][10/63] lr: 2.9351e-03 eta: 14:08:36 time: 0.8320 data_time: 0.2295 memory: 16131 loss: 2.0296 loss_prob: 1.1964 loss_thr: 0.6389 loss_db: 0.1942 2022/10/25 22:25:13 - mmengine - INFO - Epoch(train) [225][15/63] lr: 2.9351e-03 eta: 14:08:36 time: 0.7940 data_time: 0.0174 memory: 16131 loss: 2.0894 loss_prob: 1.2314 loss_thr: 0.6590 loss_db: 0.1990 2022/10/25 22:25:19 - mmengine - INFO - Epoch(train) [225][20/63] lr: 2.9351e-03 eta: 14:08:41 time: 1.1472 data_time: 0.0099 memory: 16131 loss: 2.1807 loss_prob: 1.2813 loss_thr: 0.6938 loss_db: 0.2056 2022/10/25 22:25:23 - mmengine - INFO - Epoch(train) [225][25/63] lr: 2.9351e-03 eta: 14:08:41 time: 0.9747 data_time: 0.0242 memory: 16131 loss: 2.0637 loss_prob: 1.2160 loss_thr: 0.6475 loss_db: 0.2001 2022/10/25 22:25:29 - mmengine - INFO - Epoch(train) [225][30/63] lr: 2.9351e-03 eta: 14:08:39 time: 0.9544 data_time: 0.0256 memory: 16131 loss: 2.1368 loss_prob: 1.2762 loss_thr: 0.6520 loss_db: 0.2087 2022/10/25 22:25:35 - mmengine - INFO - Epoch(train) [225][35/63] lr: 2.9351e-03 eta: 14:08:39 time: 1.2177 data_time: 0.0200 memory: 16131 loss: 2.2359 loss_prob: 1.3364 loss_thr: 0.6800 loss_db: 0.2195 2022/10/25 22:25:40 - mmengine - INFO - Epoch(train) [225][40/63] lr: 2.9351e-03 eta: 14:08:42 time: 1.0897 data_time: 0.0154 memory: 16131 loss: 2.4366 loss_prob: 1.5159 loss_thr: 0.6668 loss_db: 0.2539 2022/10/25 22:25:45 - mmengine - INFO - Epoch(train) [225][45/63] lr: 2.9351e-03 eta: 14:08:42 time: 0.9825 data_time: 0.0063 memory: 16131 loss: 2.7297 loss_prob: 1.7577 loss_thr: 0.6793 loss_db: 0.2927 2022/10/25 22:25:49 - mmengine - INFO - Epoch(train) [225][50/63] lr: 2.9351e-03 eta: 14:08:38 time: 0.9332 data_time: 0.0150 memory: 16131 loss: 2.9126 loss_prob: 1.8830 loss_thr: 0.7215 loss_db: 0.3080 2022/10/25 22:25:53 - mmengine - INFO - Epoch(train) [225][55/63] lr: 2.9351e-03 eta: 14:08:38 time: 0.8680 data_time: 0.0188 memory: 16131 loss: 2.6650 loss_prob: 1.6726 loss_thr: 0.7205 loss_db: 0.2719 2022/10/25 22:25:56 - mmengine - INFO - Epoch(train) [225][60/63] lr: 2.9351e-03 eta: 14:08:24 time: 0.7099 data_time: 0.0161 memory: 16131 loss: 2.4140 loss_prob: 1.4658 loss_thr: 0.7064 loss_db: 0.2417 2022/10/25 22:25:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:26:06 - mmengine - INFO - Epoch(train) [226][5/63] lr: 2.9323e-03 eta: 14:08:24 time: 1.1108 data_time: 0.1943 memory: 16131 loss: 2.4824 loss_prob: 1.5433 loss_thr: 0.6849 loss_db: 0.2542 2022/10/25 22:26:09 - mmengine - INFO - Epoch(train) [226][10/63] lr: 2.9323e-03 eta: 14:08:16 time: 1.1278 data_time: 0.2051 memory: 16131 loss: 2.4498 loss_prob: 1.5087 loss_thr: 0.6971 loss_db: 0.2440 2022/10/25 22:26:15 - mmengine - INFO - Epoch(train) [226][15/63] lr: 2.9323e-03 eta: 14:08:16 time: 0.8778 data_time: 0.0184 memory: 16131 loss: 2.4085 loss_prob: 1.4822 loss_thr: 0.6850 loss_db: 0.2414 2022/10/25 22:26:19 - mmengine - INFO - Epoch(train) [226][20/63] lr: 2.9323e-03 eta: 14:08:15 time: 0.9949 data_time: 0.0084 memory: 16131 loss: 2.4068 loss_prob: 1.4737 loss_thr: 0.6941 loss_db: 0.2390 2022/10/25 22:26:22 - mmengine - INFO - Epoch(train) [226][25/63] lr: 2.9323e-03 eta: 14:08:15 time: 0.6959 data_time: 0.0228 memory: 16131 loss: 2.2500 loss_prob: 1.3497 loss_thr: 0.6836 loss_db: 0.2167 2022/10/25 22:26:27 - mmengine - INFO - Epoch(train) [226][30/63] lr: 2.9323e-03 eta: 14:08:03 time: 0.7544 data_time: 0.0420 memory: 16131 loss: 2.1827 loss_prob: 1.3027 loss_thr: 0.6697 loss_db: 0.2102 2022/10/25 22:26:31 - mmengine - INFO - Epoch(train) [226][35/63] lr: 2.9323e-03 eta: 14:08:03 time: 0.9332 data_time: 0.0390 memory: 16131 loss: 2.1404 loss_prob: 1.2698 loss_thr: 0.6652 loss_db: 0.2055 2022/10/25 22:26:35 - mmengine - INFO - Epoch(train) [226][40/63] lr: 2.9323e-03 eta: 14:07:56 time: 0.8566 data_time: 0.0190 memory: 16131 loss: 2.1253 loss_prob: 1.2464 loss_thr: 0.6787 loss_db: 0.2002 2022/10/25 22:26:40 - mmengine - INFO - Epoch(train) [226][45/63] lr: 2.9323e-03 eta: 14:07:56 time: 0.8498 data_time: 0.0086 memory: 16131 loss: 2.1192 loss_prob: 1.2561 loss_thr: 0.6583 loss_db: 0.2049 2022/10/25 22:26:42 - mmengine - INFO - Epoch(train) [226][50/63] lr: 2.9323e-03 eta: 14:07:43 time: 0.7184 data_time: 0.0143 memory: 16131 loss: 2.1099 loss_prob: 1.2630 loss_thr: 0.6359 loss_db: 0.2110 2022/10/25 22:26:46 - mmengine - INFO - Epoch(train) [226][55/63] lr: 2.9323e-03 eta: 14:07:43 time: 0.5904 data_time: 0.0270 memory: 16131 loss: 2.3892 loss_prob: 1.4784 loss_thr: 0.6713 loss_db: 0.2394 2022/10/25 22:26:48 - mmengine - INFO - Epoch(train) [226][60/63] lr: 2.9323e-03 eta: 14:07:26 time: 0.6229 data_time: 0.0202 memory: 16131 loss: 2.4587 loss_prob: 1.5464 loss_thr: 0.6625 loss_db: 0.2498 2022/10/25 22:26:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:26:58 - mmengine - INFO - Epoch(train) [227][5/63] lr: 2.9296e-03 eta: 14:07:26 time: 1.0150 data_time: 0.2057 memory: 16131 loss: 2.2257 loss_prob: 1.3557 loss_thr: 0.6485 loss_db: 0.2214 2022/10/25 22:27:02 - mmengine - INFO - Epoch(train) [227][10/63] lr: 2.9296e-03 eta: 14:07:22 time: 1.2301 data_time: 0.2063 memory: 16131 loss: 2.0774 loss_prob: 1.2308 loss_thr: 0.6490 loss_db: 0.1977 2022/10/25 22:27:07 - mmengine - INFO - Epoch(train) [227][15/63] lr: 2.9296e-03 eta: 14:07:22 time: 0.9079 data_time: 0.0146 memory: 16131 loss: 2.2014 loss_prob: 1.3195 loss_thr: 0.6678 loss_db: 0.2141 2022/10/25 22:27:12 - mmengine - INFO - Epoch(train) [227][20/63] lr: 2.9296e-03 eta: 14:07:21 time: 0.9995 data_time: 0.0124 memory: 16131 loss: 2.2059 loss_prob: 1.3337 loss_thr: 0.6554 loss_db: 0.2168 2022/10/25 22:27:15 - mmengine - INFO - Epoch(train) [227][25/63] lr: 2.9296e-03 eta: 14:07:21 time: 0.8840 data_time: 0.0325 memory: 16131 loss: 2.1860 loss_prob: 1.3085 loss_thr: 0.6672 loss_db: 0.2103 2022/10/25 22:27:23 - mmengine - INFO - Epoch(train) [227][30/63] lr: 2.9296e-03 eta: 14:07:21 time: 1.0252 data_time: 0.0315 memory: 16131 loss: 2.1993 loss_prob: 1.3250 loss_thr: 0.6631 loss_db: 0.2112 2022/10/25 22:27:29 - mmengine - INFO - Epoch(train) [227][35/63] lr: 2.9296e-03 eta: 14:07:21 time: 1.3119 data_time: 0.0043 memory: 16131 loss: 2.0537 loss_prob: 1.2284 loss_thr: 0.6233 loss_db: 0.2021 2022/10/25 22:27:33 - mmengine - INFO - Epoch(train) [227][40/63] lr: 2.9296e-03 eta: 14:07:22 time: 1.0541 data_time: 0.0145 memory: 16131 loss: 2.0069 loss_prob: 1.1829 loss_thr: 0.6274 loss_db: 0.1965 2022/10/25 22:27:36 - mmengine - INFO - Epoch(train) [227][45/63] lr: 2.9296e-03 eta: 14:07:22 time: 0.7560 data_time: 0.0183 memory: 16131 loss: 2.2285 loss_prob: 1.3492 loss_thr: 0.6627 loss_db: 0.2166 2022/10/25 22:27:39 - mmengine - INFO - Epoch(train) [227][50/63] lr: 2.9296e-03 eta: 14:07:03 time: 0.5827 data_time: 0.0247 memory: 16131 loss: 2.2974 loss_prob: 1.4118 loss_thr: 0.6634 loss_db: 0.2223 2022/10/25 22:27:44 - mmengine - INFO - Epoch(train) [227][55/63] lr: 2.9296e-03 eta: 14:07:03 time: 0.8027 data_time: 0.0212 memory: 16131 loss: 2.4384 loss_prob: 1.5101 loss_thr: 0.6860 loss_db: 0.2423 2022/10/25 22:27:49 - mmengine - INFO - Epoch(train) [227][60/63] lr: 2.9296e-03 eta: 14:07:03 time: 1.0163 data_time: 0.0070 memory: 16131 loss: 2.5456 loss_prob: 1.5923 loss_thr: 0.6919 loss_db: 0.2615 2022/10/25 22:27:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:27:59 - mmengine - INFO - Epoch(train) [228][5/63] lr: 2.9269e-03 eta: 14:07:03 time: 1.1577 data_time: 0.1662 memory: 16131 loss: 2.2203 loss_prob: 1.3452 loss_thr: 0.6542 loss_db: 0.2209 2022/10/25 22:28:05 - mmengine - INFO - Epoch(train) [228][10/63] lr: 2.9269e-03 eta: 14:07:07 time: 1.4249 data_time: 0.1733 memory: 16131 loss: 2.2076 loss_prob: 1.3402 loss_thr: 0.6464 loss_db: 0.2209 2022/10/25 22:28:12 - mmengine - INFO - Epoch(train) [228][15/63] lr: 2.9269e-03 eta: 14:07:07 time: 1.2431 data_time: 0.0172 memory: 16131 loss: 2.3883 loss_prob: 1.4693 loss_thr: 0.6719 loss_db: 0.2471 2022/10/25 22:28:20 - mmengine - INFO - Epoch(train) [228][20/63] lr: 2.9269e-03 eta: 14:07:28 time: 1.5121 data_time: 0.0071 memory: 16131 loss: 2.5299 loss_prob: 1.5894 loss_thr: 0.6778 loss_db: 0.2627 2022/10/25 22:28:24 - mmengine - INFO - Epoch(train) [228][25/63] lr: 2.9269e-03 eta: 14:07:28 time: 1.2261 data_time: 0.0145 memory: 16131 loss: 2.4605 loss_prob: 1.5304 loss_thr: 0.6816 loss_db: 0.2485 2022/10/25 22:28:29 - mmengine - INFO - Epoch(train) [228][30/63] lr: 2.9269e-03 eta: 14:07:24 time: 0.9215 data_time: 0.0280 memory: 16131 loss: 2.2680 loss_prob: 1.3782 loss_thr: 0.6651 loss_db: 0.2247 2022/10/25 22:28:32 - mmengine - INFO - Epoch(train) [228][35/63] lr: 2.9269e-03 eta: 14:07:24 time: 0.7582 data_time: 0.0277 memory: 16131 loss: 2.2256 loss_prob: 1.3294 loss_thr: 0.6758 loss_db: 0.2205 2022/10/25 22:28:37 - mmengine - INFO - Epoch(train) [228][40/63] lr: 2.9269e-03 eta: 14:07:13 time: 0.7693 data_time: 0.0138 memory: 16131 loss: 2.1686 loss_prob: 1.2796 loss_thr: 0.6756 loss_db: 0.2134 2022/10/25 22:28:43 - mmengine - INFO - Epoch(train) [228][45/63] lr: 2.9269e-03 eta: 14:07:13 time: 1.1210 data_time: 0.0098 memory: 16131 loss: 2.1892 loss_prob: 1.3000 loss_thr: 0.6770 loss_db: 0.2123 2022/10/25 22:28:51 - mmengine - INFO - Epoch(train) [228][50/63] lr: 2.9269e-03 eta: 14:07:30 time: 1.4173 data_time: 0.0149 memory: 16131 loss: 2.4161 loss_prob: 1.4805 loss_thr: 0.6960 loss_db: 0.2396 2022/10/25 22:28:56 - mmengine - INFO - Epoch(train) [228][55/63] lr: 2.9269e-03 eta: 14:07:30 time: 1.2750 data_time: 0.0202 memory: 16131 loss: 2.3823 loss_prob: 1.4438 loss_thr: 0.6981 loss_db: 0.2403 2022/10/25 22:29:01 - mmengine - INFO - Epoch(train) [228][60/63] lr: 2.9269e-03 eta: 14:07:29 time: 0.9975 data_time: 0.0181 memory: 16131 loss: 2.2319 loss_prob: 1.3380 loss_thr: 0.6742 loss_db: 0.2197 2022/10/25 22:29:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:29:12 - mmengine - INFO - Epoch(train) [229][5/63] lr: 2.9242e-03 eta: 14:07:29 time: 1.3833 data_time: 0.1738 memory: 16131 loss: 2.3227 loss_prob: 1.4150 loss_thr: 0.6800 loss_db: 0.2277 2022/10/25 22:29:16 - mmengine - INFO - Epoch(train) [229][10/63] lr: 2.9242e-03 eta: 14:07:31 time: 1.3815 data_time: 0.1906 memory: 16131 loss: 2.4272 loss_prob: 1.4891 loss_thr: 0.6963 loss_db: 0.2418 2022/10/25 22:29:20 - mmengine - INFO - Epoch(train) [229][15/63] lr: 2.9242e-03 eta: 14:07:31 time: 0.8118 data_time: 0.0257 memory: 16131 loss: 2.4223 loss_prob: 1.4748 loss_thr: 0.7045 loss_db: 0.2430 2022/10/25 22:29:24 - mmengine - INFO - Epoch(train) [229][20/63] lr: 2.9242e-03 eta: 14:07:19 time: 0.7588 data_time: 0.0163 memory: 16131 loss: 2.4727 loss_prob: 1.5102 loss_thr: 0.7116 loss_db: 0.2509 2022/10/25 22:29:27 - mmengine - INFO - Epoch(train) [229][25/63] lr: 2.9242e-03 eta: 14:07:19 time: 0.7214 data_time: 0.0256 memory: 16131 loss: 2.3857 loss_prob: 1.4598 loss_thr: 0.6818 loss_db: 0.2441 2022/10/25 22:29:32 - mmengine - INFO - Epoch(train) [229][30/63] lr: 2.9242e-03 eta: 14:07:09 time: 0.7917 data_time: 0.0249 memory: 16131 loss: 2.4656 loss_prob: 1.5220 loss_thr: 0.6855 loss_db: 0.2582 2022/10/25 22:29:36 - mmengine - INFO - Epoch(train) [229][35/63] lr: 2.9242e-03 eta: 14:07:09 time: 0.8644 data_time: 0.0281 memory: 16131 loss: 2.4735 loss_prob: 1.5255 loss_thr: 0.6894 loss_db: 0.2586 2022/10/25 22:29:43 - mmengine - INFO - Epoch(train) [229][40/63] lr: 2.9242e-03 eta: 14:07:14 time: 1.1318 data_time: 0.0216 memory: 16131 loss: 2.5986 loss_prob: 1.6303 loss_thr: 0.7012 loss_db: 0.2671 2022/10/25 22:29:49 - mmengine - INFO - Epoch(train) [229][45/63] lr: 2.9242e-03 eta: 14:07:14 time: 1.3307 data_time: 0.0110 memory: 16131 loss: 2.8104 loss_prob: 1.7693 loss_thr: 0.7475 loss_db: 0.2935 2022/10/25 22:29:52 - mmengine - INFO - Epoch(train) [229][50/63] lr: 2.9242e-03 eta: 14:07:10 time: 0.9320 data_time: 0.0251 memory: 16131 loss: 2.5812 loss_prob: 1.6010 loss_thr: 0.7154 loss_db: 0.2648 2022/10/25 22:29:55 - mmengine - INFO - Epoch(train) [229][55/63] lr: 2.9242e-03 eta: 14:07:10 time: 0.6253 data_time: 0.0267 memory: 16131 loss: 2.4992 loss_prob: 1.5639 loss_thr: 0.6838 loss_db: 0.2516 2022/10/25 22:29:59 - mmengine - INFO - Epoch(train) [229][60/63] lr: 2.9242e-03 eta: 14:06:54 time: 0.6443 data_time: 0.0167 memory: 16131 loss: 2.4460 loss_prob: 1.5314 loss_thr: 0.6708 loss_db: 0.2438 2022/10/25 22:30:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:30:08 - mmengine - INFO - Epoch(train) [230][5/63] lr: 2.9215e-03 eta: 14:06:54 time: 1.0883 data_time: 0.2233 memory: 16131 loss: 2.2991 loss_prob: 1.4115 loss_thr: 0.6753 loss_db: 0.2123 2022/10/25 22:30:16 - mmengine - INFO - Epoch(train) [230][10/63] lr: 2.9215e-03 eta: 14:07:04 time: 1.5709 data_time: 0.2203 memory: 16131 loss: 2.3683 loss_prob: 1.4471 loss_thr: 0.6988 loss_db: 0.2225 2022/10/25 22:30:23 - mmengine - INFO - Epoch(train) [230][15/63] lr: 2.9215e-03 eta: 14:07:04 time: 1.5276 data_time: 0.0096 memory: 16131 loss: 2.2785 loss_prob: 1.3853 loss_thr: 0.6690 loss_db: 0.2243 2022/10/25 22:30:28 - mmengine - INFO - Epoch(train) [230][20/63] lr: 2.9215e-03 eta: 14:07:08 time: 1.1264 data_time: 0.0103 memory: 16131 loss: 2.1602 loss_prob: 1.2930 loss_thr: 0.6545 loss_db: 0.2126 2022/10/25 22:30:30 - mmengine - INFO - Epoch(train) [230][25/63] lr: 2.9215e-03 eta: 14:07:08 time: 0.7133 data_time: 0.0255 memory: 16131 loss: 2.0906 loss_prob: 1.2449 loss_thr: 0.6442 loss_db: 0.2015 2022/10/25 22:30:36 - mmengine - INFO - Epoch(train) [230][30/63] lr: 2.9215e-03 eta: 14:06:59 time: 0.8238 data_time: 0.0424 memory: 16131 loss: 2.2013 loss_prob: 1.3194 loss_thr: 0.6649 loss_db: 0.2170 2022/10/25 22:30:41 - mmengine - INFO - Epoch(train) [230][35/63] lr: 2.9215e-03 eta: 14:06:59 time: 1.0877 data_time: 0.0250 memory: 16131 loss: 2.2383 loss_prob: 1.3639 loss_thr: 0.6515 loss_db: 0.2229 2022/10/25 22:30:46 - mmengine - INFO - Epoch(train) [230][40/63] lr: 2.9215e-03 eta: 14:07:01 time: 1.0749 data_time: 0.0111 memory: 16131 loss: 2.1864 loss_prob: 1.3441 loss_thr: 0.6259 loss_db: 0.2164 2022/10/25 22:30:52 - mmengine - INFO - Epoch(train) [230][45/63] lr: 2.9215e-03 eta: 14:07:01 time: 1.0360 data_time: 0.0094 memory: 16131 loss: 2.1683 loss_prob: 1.3088 loss_thr: 0.6454 loss_db: 0.2140 2022/10/25 22:30:55 - mmengine - INFO - Epoch(train) [230][50/63] lr: 2.9215e-03 eta: 14:06:55 time: 0.8896 data_time: 0.0218 memory: 16131 loss: 2.1590 loss_prob: 1.3102 loss_thr: 0.6377 loss_db: 0.2110 2022/10/25 22:31:00 - mmengine - INFO - Epoch(train) [230][55/63] lr: 2.9215e-03 eta: 14:06:55 time: 0.8171 data_time: 0.0378 memory: 16131 loss: 2.1485 loss_prob: 1.2975 loss_thr: 0.6414 loss_db: 0.2097 2022/10/25 22:31:04 - mmengine - INFO - Epoch(train) [230][60/63] lr: 2.9215e-03 eta: 14:06:49 time: 0.8736 data_time: 0.0215 memory: 16131 loss: 2.1283 loss_prob: 1.2734 loss_thr: 0.6456 loss_db: 0.2093 2022/10/25 22:31:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:31:16 - mmengine - INFO - Epoch(train) [231][5/63] lr: 2.9188e-03 eta: 14:06:49 time: 1.2989 data_time: 0.2206 memory: 16131 loss: 2.0895 loss_prob: 1.2485 loss_thr: 0.6369 loss_db: 0.2041 2022/10/25 22:31:23 - mmengine - INFO - Epoch(train) [231][10/63] lr: 2.9188e-03 eta: 14:06:58 time: 1.5566 data_time: 0.2221 memory: 16131 loss: 2.0081 loss_prob: 1.1891 loss_thr: 0.6263 loss_db: 0.1927 2022/10/25 22:31:28 - mmengine - INFO - Epoch(train) [231][15/63] lr: 2.9188e-03 eta: 14:06:58 time: 1.1851 data_time: 0.0145 memory: 16131 loss: 2.0105 loss_prob: 1.2014 loss_thr: 0.6173 loss_db: 0.1918 2022/10/25 22:31:32 - mmengine - INFO - Epoch(train) [231][20/63] lr: 2.9188e-03 eta: 14:06:55 time: 0.9501 data_time: 0.0170 memory: 16131 loss: 2.1498 loss_prob: 1.2944 loss_thr: 0.6538 loss_db: 0.2017 2022/10/25 22:31:35 - mmengine - INFO - Epoch(train) [231][25/63] lr: 2.9188e-03 eta: 14:06:55 time: 0.6808 data_time: 0.0330 memory: 16131 loss: 2.2681 loss_prob: 1.3648 loss_thr: 0.6873 loss_db: 0.2161 2022/10/25 22:31:38 - mmengine - INFO - Epoch(train) [231][30/63] lr: 2.9188e-03 eta: 14:06:34 time: 0.5479 data_time: 0.0266 memory: 16131 loss: 2.6244 loss_prob: 1.6507 loss_thr: 0.6954 loss_db: 0.2782 2022/10/25 22:31:40 - mmengine - INFO - Epoch(train) [231][35/63] lr: 2.9188e-03 eta: 14:06:34 time: 0.5474 data_time: 0.0144 memory: 16131 loss: 2.7552 loss_prob: 1.7795 loss_thr: 0.6715 loss_db: 0.3042 2022/10/25 22:31:43 - mmengine - INFO - Epoch(train) [231][40/63] lr: 2.9188e-03 eta: 14:06:14 time: 0.5429 data_time: 0.0146 memory: 16131 loss: 2.7108 loss_prob: 1.7240 loss_thr: 0.6987 loss_db: 0.2881 2022/10/25 22:31:45 - mmengine - INFO - Epoch(train) [231][45/63] lr: 2.9188e-03 eta: 14:06:14 time: 0.5201 data_time: 0.0059 memory: 16131 loss: 2.6262 loss_prob: 1.6288 loss_thr: 0.7269 loss_db: 0.2705 2022/10/25 22:31:48 - mmengine - INFO - Epoch(train) [231][50/63] lr: 2.9188e-03 eta: 14:05:53 time: 0.5250 data_time: 0.0186 memory: 16131 loss: 2.4956 loss_prob: 1.5228 loss_thr: 0.7198 loss_db: 0.2530 2022/10/25 22:31:52 - mmengine - INFO - Epoch(train) [231][55/63] lr: 2.9188e-03 eta: 14:05:53 time: 0.6501 data_time: 0.0265 memory: 16131 loss: 2.5185 loss_prob: 1.5526 loss_thr: 0.7063 loss_db: 0.2596 2022/10/25 22:31:55 - mmengine - INFO - Epoch(train) [231][60/63] lr: 2.9188e-03 eta: 14:05:37 time: 0.6620 data_time: 0.0193 memory: 16131 loss: 2.5150 loss_prob: 1.5612 loss_thr: 0.6968 loss_db: 0.2570 2022/10/25 22:31:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:32:04 - mmengine - INFO - Epoch(train) [232][5/63] lr: 2.9161e-03 eta: 14:05:37 time: 0.9978 data_time: 0.1821 memory: 16131 loss: 2.5079 loss_prob: 1.5382 loss_thr: 0.7204 loss_db: 0.2493 2022/10/25 22:32:07 - mmengine - INFO - Epoch(train) [232][10/63] lr: 2.9161e-03 eta: 14:05:21 time: 0.9413 data_time: 0.1826 memory: 16131 loss: 2.4843 loss_prob: 1.5313 loss_thr: 0.7092 loss_db: 0.2437 2022/10/25 22:32:09 - mmengine - INFO - Epoch(train) [232][15/63] lr: 2.9161e-03 eta: 14:05:21 time: 0.5494 data_time: 0.0083 memory: 16131 loss: 2.4815 loss_prob: 1.5160 loss_thr: 0.7215 loss_db: 0.2440 2022/10/25 22:32:14 - mmengine - INFO - Epoch(train) [232][20/63] lr: 2.9161e-03 eta: 14:05:10 time: 0.7658 data_time: 0.0086 memory: 16131 loss: 2.2128 loss_prob: 1.3092 loss_thr: 0.6917 loss_db: 0.2118 2022/10/25 22:32:17 - mmengine - INFO - Epoch(train) [232][25/63] lr: 2.9161e-03 eta: 14:05:10 time: 0.7730 data_time: 0.0169 memory: 16131 loss: 2.1014 loss_prob: 1.2471 loss_thr: 0.6539 loss_db: 0.2004 2022/10/25 22:32:21 - mmengine - INFO - Epoch(train) [232][30/63] lr: 2.9161e-03 eta: 14:04:53 time: 0.6206 data_time: 0.0442 memory: 16131 loss: 2.2070 loss_prob: 1.3159 loss_thr: 0.6792 loss_db: 0.2119 2022/10/25 22:32:23 - mmengine - INFO - Epoch(train) [232][35/63] lr: 2.9161e-03 eta: 14:04:53 time: 0.6211 data_time: 0.0366 memory: 16131 loss: 2.0018 loss_prob: 1.1736 loss_thr: 0.6408 loss_db: 0.1874 2022/10/25 22:32:27 - mmengine - INFO - Epoch(train) [232][40/63] lr: 2.9161e-03 eta: 14:04:35 time: 0.6041 data_time: 0.0056 memory: 16131 loss: 2.0547 loss_prob: 1.2185 loss_thr: 0.6374 loss_db: 0.1988 2022/10/25 22:32:29 - mmengine - INFO - Epoch(train) [232][45/63] lr: 2.9161e-03 eta: 14:04:35 time: 0.5762 data_time: 0.0073 memory: 16131 loss: 2.2040 loss_prob: 1.3335 loss_thr: 0.6522 loss_db: 0.2183 2022/10/25 22:32:32 - mmengine - INFO - Epoch(train) [232][50/63] lr: 2.9161e-03 eta: 14:04:14 time: 0.5419 data_time: 0.0228 memory: 16131 loss: 2.1524 loss_prob: 1.2913 loss_thr: 0.6519 loss_db: 0.2092 2022/10/25 22:32:36 - mmengine - INFO - Epoch(train) [232][55/63] lr: 2.9161e-03 eta: 14:04:14 time: 0.6761 data_time: 0.0245 memory: 16131 loss: 2.2945 loss_prob: 1.3800 loss_thr: 0.6923 loss_db: 0.2221 2022/10/25 22:32:40 - mmengine - INFO - Epoch(train) [232][60/63] lr: 2.9161e-03 eta: 14:04:03 time: 0.7577 data_time: 0.0125 memory: 16131 loss: 2.2502 loss_prob: 1.3472 loss_thr: 0.6832 loss_db: 0.2198 2022/10/25 22:32:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:32:46 - mmengine - INFO - Epoch(train) [233][5/63] lr: 2.9134e-03 eta: 14:04:03 time: 0.7669 data_time: 0.1757 memory: 16131 loss: 2.2106 loss_prob: 1.3418 loss_thr: 0.6514 loss_db: 0.2175 2022/10/25 22:32:49 - mmengine - INFO - Epoch(train) [233][10/63] lr: 2.9134e-03 eta: 14:03:38 time: 0.7426 data_time: 0.1710 memory: 16131 loss: 2.1294 loss_prob: 1.2983 loss_thr: 0.6218 loss_db: 0.2092 2022/10/25 22:32:52 - mmengine - INFO - Epoch(train) [233][15/63] lr: 2.9134e-03 eta: 14:03:38 time: 0.5527 data_time: 0.0085 memory: 16131 loss: 2.0648 loss_prob: 1.2410 loss_thr: 0.6186 loss_db: 0.2052 2022/10/25 22:32:55 - mmengine - INFO - Epoch(train) [233][20/63] lr: 2.9134e-03 eta: 14:03:20 time: 0.5871 data_time: 0.0092 memory: 16131 loss: 2.1979 loss_prob: 1.3426 loss_thr: 0.6357 loss_db: 0.2197 2022/10/25 22:32:58 - mmengine - INFO - Epoch(train) [233][25/63] lr: 2.9134e-03 eta: 14:03:20 time: 0.6252 data_time: 0.0278 memory: 16131 loss: 2.1713 loss_prob: 1.3221 loss_thr: 0.6379 loss_db: 0.2113 2022/10/25 22:33:02 - mmengine - INFO - Epoch(train) [233][30/63] lr: 2.9134e-03 eta: 14:03:09 time: 0.7595 data_time: 0.0365 memory: 16131 loss: 2.0683 loss_prob: 1.2172 loss_thr: 0.6537 loss_db: 0.1974 2022/10/25 22:33:05 - mmengine - INFO - Epoch(train) [233][35/63] lr: 2.9134e-03 eta: 14:03:09 time: 0.7427 data_time: 0.0140 memory: 16131 loss: 2.0874 loss_prob: 1.2308 loss_thr: 0.6551 loss_db: 0.2015 2022/10/25 22:33:08 - mmengine - INFO - Epoch(train) [233][40/63] lr: 2.9134e-03 eta: 14:02:49 time: 0.5486 data_time: 0.0047 memory: 16131 loss: 2.0831 loss_prob: 1.2245 loss_thr: 0.6595 loss_db: 0.1991 2022/10/25 22:33:11 - mmengine - INFO - Epoch(train) [233][45/63] lr: 2.9134e-03 eta: 14:02:49 time: 0.5592 data_time: 0.0047 memory: 16131 loss: 1.9677 loss_prob: 1.1533 loss_thr: 0.6275 loss_db: 0.1869 2022/10/25 22:33:15 - mmengine - INFO - Epoch(train) [233][50/63] lr: 2.9134e-03 eta: 14:02:36 time: 0.7363 data_time: 0.0237 memory: 16131 loss: 1.9562 loss_prob: 1.1540 loss_thr: 0.6131 loss_db: 0.1892 2022/10/25 22:33:20 - mmengine - INFO - Epoch(train) [233][55/63] lr: 2.9134e-03 eta: 14:02:36 time: 0.8965 data_time: 0.0260 memory: 16131 loss: 2.0964 loss_prob: 1.2340 loss_thr: 0.6540 loss_db: 0.2084 2022/10/25 22:33:22 - mmengine - INFO - Epoch(train) [233][60/63] lr: 2.9134e-03 eta: 14:02:24 time: 0.7242 data_time: 0.0069 memory: 16131 loss: 2.1079 loss_prob: 1.2414 loss_thr: 0.6562 loss_db: 0.2102 2022/10/25 22:33:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:33:28 - mmengine - INFO - Epoch(train) [234][5/63] lr: 2.9107e-03 eta: 14:02:24 time: 0.7055 data_time: 0.1944 memory: 16131 loss: 2.2668 loss_prob: 1.4056 loss_thr: 0.6350 loss_db: 0.2261 2022/10/25 22:33:31 - mmengine - INFO - Epoch(train) [234][10/63] lr: 2.9107e-03 eta: 14:01:59 time: 0.7340 data_time: 0.1965 memory: 16131 loss: 2.3544 loss_prob: 1.4539 loss_thr: 0.6657 loss_db: 0.2348 2022/10/25 22:33:34 - mmengine - INFO - Epoch(train) [234][15/63] lr: 2.9107e-03 eta: 14:01:59 time: 0.5872 data_time: 0.0084 memory: 16131 loss: 2.1689 loss_prob: 1.3096 loss_thr: 0.6456 loss_db: 0.2137 2022/10/25 22:33:38 - mmengine - INFO - Epoch(train) [234][20/63] lr: 2.9107e-03 eta: 14:01:44 time: 0.6639 data_time: 0.0080 memory: 16131 loss: 2.2522 loss_prob: 1.3780 loss_thr: 0.6509 loss_db: 0.2233 2022/10/25 22:33:40 - mmengine - INFO - Epoch(train) [234][25/63] lr: 2.9107e-03 eta: 14:01:44 time: 0.6150 data_time: 0.0340 memory: 16131 loss: 2.2936 loss_prob: 1.3911 loss_thr: 0.6753 loss_db: 0.2272 2022/10/25 22:33:43 - mmengine - INFO - Epoch(train) [234][30/63] lr: 2.9107e-03 eta: 14:01:23 time: 0.5413 data_time: 0.0346 memory: 16131 loss: 2.0273 loss_prob: 1.1991 loss_thr: 0.6321 loss_db: 0.1960 2022/10/25 22:33:45 - mmengine - INFO - Epoch(train) [234][35/63] lr: 2.9107e-03 eta: 14:01:23 time: 0.5039 data_time: 0.0072 memory: 16131 loss: 2.0284 loss_prob: 1.2093 loss_thr: 0.6208 loss_db: 0.1983 2022/10/25 22:33:48 - mmengine - INFO - Epoch(train) [234][40/63] lr: 2.9107e-03 eta: 14:01:02 time: 0.5075 data_time: 0.0071 memory: 16131 loss: 2.3839 loss_prob: 1.4636 loss_thr: 0.6807 loss_db: 0.2396 2022/10/25 22:33:51 - mmengine - INFO - Epoch(train) [234][45/63] lr: 2.9107e-03 eta: 14:01:02 time: 0.5707 data_time: 0.0089 memory: 16131 loss: 2.3974 loss_prob: 1.4709 loss_thr: 0.6848 loss_db: 0.2417 2022/10/25 22:33:56 - mmengine - INFO - Epoch(train) [234][50/63] lr: 2.9107e-03 eta: 14:00:50 time: 0.7492 data_time: 0.0206 memory: 16131 loss: 2.2059 loss_prob: 1.3359 loss_thr: 0.6458 loss_db: 0.2241 2022/10/25 22:33:59 - mmengine - INFO - Epoch(train) [234][55/63] lr: 2.9107e-03 eta: 14:00:50 time: 0.8214 data_time: 0.0209 memory: 16131 loss: 2.2391 loss_prob: 1.3548 loss_thr: 0.6574 loss_db: 0.2269 2022/10/25 22:34:02 - mmengine - INFO - Epoch(train) [234][60/63] lr: 2.9107e-03 eta: 14:00:36 time: 0.6818 data_time: 0.0066 memory: 16131 loss: 2.3555 loss_prob: 1.4475 loss_thr: 0.6653 loss_db: 0.2428 2022/10/25 22:34:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:34:10 - mmengine - INFO - Epoch(train) [235][5/63] lr: 2.9080e-03 eta: 14:00:36 time: 0.8940 data_time: 0.2000 memory: 16131 loss: 2.3046 loss_prob: 1.4159 loss_thr: 0.6639 loss_db: 0.2248 2022/10/25 22:34:16 - mmengine - INFO - Epoch(train) [235][10/63] lr: 2.9080e-03 eta: 14:00:32 time: 1.2501 data_time: 0.2011 memory: 16131 loss: 2.4739 loss_prob: 1.5415 loss_thr: 0.6776 loss_db: 0.2548 2022/10/25 22:34:22 - mmengine - INFO - Epoch(train) [235][15/63] lr: 2.9080e-03 eta: 14:00:32 time: 1.1534 data_time: 0.0067 memory: 16131 loss: 2.2770 loss_prob: 1.3908 loss_thr: 0.6556 loss_db: 0.2306 2022/10/25 22:34:25 - mmengine - INFO - Epoch(train) [235][20/63] lr: 2.9080e-03 eta: 14:00:23 time: 0.8180 data_time: 0.0094 memory: 16131 loss: 2.3551 loss_prob: 1.4577 loss_thr: 0.6594 loss_db: 0.2380 2022/10/25 22:34:29 - mmengine - INFO - Epoch(train) [235][25/63] lr: 2.9080e-03 eta: 14:00:23 time: 0.7230 data_time: 0.0201 memory: 16131 loss: 2.4615 loss_prob: 1.5490 loss_thr: 0.6499 loss_db: 0.2626 2022/10/25 22:34:32 - mmengine - INFO - Epoch(train) [235][30/63] lr: 2.9080e-03 eta: 14:00:11 time: 0.7188 data_time: 0.0273 memory: 16131 loss: 2.5732 loss_prob: 1.6246 loss_thr: 0.6761 loss_db: 0.2725 2022/10/25 22:34:35 - mmengine - INFO - Epoch(train) [235][35/63] lr: 2.9080e-03 eta: 14:00:11 time: 0.5629 data_time: 0.0200 memory: 16131 loss: 2.7685 loss_prob: 1.7673 loss_thr: 0.7132 loss_db: 0.2881 2022/10/25 22:34:38 - mmengine - INFO - Epoch(train) [235][40/63] lr: 2.9080e-03 eta: 13:59:52 time: 0.5795 data_time: 0.0117 memory: 16131 loss: 2.5804 loss_prob: 1.6238 loss_thr: 0.6935 loss_db: 0.2632 2022/10/25 22:34:43 - mmengine - INFO - Epoch(train) [235][45/63] lr: 2.9080e-03 eta: 13:59:52 time: 0.8847 data_time: 0.0101 memory: 16131 loss: 2.3348 loss_prob: 1.4520 loss_thr: 0.6474 loss_db: 0.2353 2022/10/25 22:34:46 - mmengine - INFO - Epoch(train) [235][50/63] lr: 2.9080e-03 eta: 13:59:45 time: 0.8649 data_time: 0.0188 memory: 16131 loss: 2.2282 loss_prob: 1.3782 loss_thr: 0.6246 loss_db: 0.2254 2022/10/25 22:34:49 - mmengine - INFO - Epoch(train) [235][55/63] lr: 2.9080e-03 eta: 13:59:45 time: 0.5580 data_time: 0.0200 memory: 16131 loss: 2.0984 loss_prob: 1.2625 loss_thr: 0.6292 loss_db: 0.2066 2022/10/25 22:34:52 - mmengine - INFO - Epoch(train) [235][60/63] lr: 2.9080e-03 eta: 13:59:27 time: 0.5748 data_time: 0.0140 memory: 16131 loss: 2.1996 loss_prob: 1.3269 loss_thr: 0.6510 loss_db: 0.2217 2022/10/25 22:34:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:35:01 - mmengine - INFO - Epoch(train) [236][5/63] lr: 2.9052e-03 eta: 13:59:27 time: 0.9989 data_time: 0.2072 memory: 16131 loss: 2.2266 loss_prob: 1.3543 loss_thr: 0.6534 loss_db: 0.2189 2022/10/25 22:35:05 - mmengine - INFO - Epoch(train) [236][10/63] lr: 2.9052e-03 eta: 13:59:15 time: 1.0642 data_time: 0.2109 memory: 16131 loss: 2.2346 loss_prob: 1.3588 loss_thr: 0.6619 loss_db: 0.2139 2022/10/25 22:35:08 - mmengine - INFO - Epoch(train) [236][15/63] lr: 2.9052e-03 eta: 13:59:15 time: 0.7038 data_time: 0.0095 memory: 16131 loss: 2.2210 loss_prob: 1.3552 loss_thr: 0.6459 loss_db: 0.2199 2022/10/25 22:35:14 - mmengine - INFO - Epoch(train) [236][20/63] lr: 2.9052e-03 eta: 13:59:10 time: 0.9141 data_time: 0.0091 memory: 16131 loss: 2.2054 loss_prob: 1.3482 loss_thr: 0.6296 loss_db: 0.2276 2022/10/25 22:35:17 - mmengine - INFO - Epoch(train) [236][25/63] lr: 2.9052e-03 eta: 13:59:10 time: 0.8829 data_time: 0.0282 memory: 16131 loss: 2.3444 loss_prob: 1.4502 loss_thr: 0.6543 loss_db: 0.2398 2022/10/25 22:35:19 - mmengine - INFO - Epoch(train) [236][30/63] lr: 2.9052e-03 eta: 13:58:52 time: 0.5707 data_time: 0.0391 memory: 16131 loss: 2.2774 loss_prob: 1.3959 loss_thr: 0.6576 loss_db: 0.2239 2022/10/25 22:35:22 - mmengine - INFO - Epoch(train) [236][35/63] lr: 2.9052e-03 eta: 13:58:52 time: 0.5589 data_time: 0.0194 memory: 16131 loss: 2.5031 loss_prob: 1.5669 loss_thr: 0.6821 loss_db: 0.2541 2022/10/25 22:35:25 - mmengine - INFO - Epoch(train) [236][40/63] lr: 2.9052e-03 eta: 13:58:32 time: 0.5443 data_time: 0.0052 memory: 16131 loss: 2.5363 loss_prob: 1.5913 loss_thr: 0.6840 loss_db: 0.2609 2022/10/25 22:35:28 - mmengine - INFO - Epoch(train) [236][45/63] lr: 2.9052e-03 eta: 13:58:32 time: 0.5709 data_time: 0.0051 memory: 16131 loss: 2.2433 loss_prob: 1.3634 loss_thr: 0.6524 loss_db: 0.2275 2022/10/25 22:35:34 - mmengine - INFO - Epoch(train) [236][50/63] lr: 2.9052e-03 eta: 13:58:29 time: 0.9590 data_time: 0.0145 memory: 16131 loss: 2.1397 loss_prob: 1.2910 loss_thr: 0.6362 loss_db: 0.2125 2022/10/25 22:35:37 - mmengine - INFO - Epoch(train) [236][55/63] lr: 2.9052e-03 eta: 13:58:29 time: 0.9161 data_time: 0.0255 memory: 16131 loss: 2.0626 loss_prob: 1.2374 loss_thr: 0.6272 loss_db: 0.1980 2022/10/25 22:35:40 - mmengine - INFO - Epoch(train) [236][60/63] lr: 2.9052e-03 eta: 13:58:09 time: 0.5375 data_time: 0.0215 memory: 16131 loss: 2.0331 loss_prob: 1.2046 loss_thr: 0.6351 loss_db: 0.1934 2022/10/25 22:35:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:35:49 - mmengine - INFO - Epoch(train) [237][5/63] lr: 2.9025e-03 eta: 13:58:09 time: 1.0338 data_time: 0.2105 memory: 16131 loss: 2.0282 loss_prob: 1.2144 loss_thr: 0.6194 loss_db: 0.1943 2022/10/25 22:35:52 - mmengine - INFO - Epoch(train) [237][10/63] lr: 2.9025e-03 eta: 13:57:57 time: 1.0543 data_time: 0.2096 memory: 16131 loss: 2.0752 loss_prob: 1.2574 loss_thr: 0.6197 loss_db: 0.1980 2022/10/25 22:35:56 - mmengine - INFO - Epoch(train) [237][15/63] lr: 2.9025e-03 eta: 13:57:57 time: 0.7005 data_time: 0.0073 memory: 16131 loss: 2.1419 loss_prob: 1.3253 loss_thr: 0.6101 loss_db: 0.2065 2022/10/25 22:36:01 - mmengine - INFO - Epoch(train) [237][20/63] lr: 2.9025e-03 eta: 13:57:54 time: 0.9635 data_time: 0.0087 memory: 16131 loss: 2.4071 loss_prob: 1.5228 loss_thr: 0.6424 loss_db: 0.2418 2022/10/25 22:36:04 - mmengine - INFO - Epoch(train) [237][25/63] lr: 2.9025e-03 eta: 13:57:54 time: 0.8299 data_time: 0.0369 memory: 16131 loss: 2.2518 loss_prob: 1.3746 loss_thr: 0.6539 loss_db: 0.2232 2022/10/25 22:36:07 - mmengine - INFO - Epoch(train) [237][30/63] lr: 2.9025e-03 eta: 13:57:35 time: 0.5551 data_time: 0.0352 memory: 16131 loss: 2.1917 loss_prob: 1.3028 loss_thr: 0.6771 loss_db: 0.2118 2022/10/25 22:36:10 - mmengine - INFO - Epoch(train) [237][35/63] lr: 2.9025e-03 eta: 13:57:35 time: 0.5264 data_time: 0.0071 memory: 16131 loss: 2.2733 loss_prob: 1.3615 loss_thr: 0.6927 loss_db: 0.2191 2022/10/25 22:36:12 - mmengine - INFO - Epoch(train) [237][40/63] lr: 2.9025e-03 eta: 13:57:14 time: 0.5159 data_time: 0.0082 memory: 16131 loss: 2.0765 loss_prob: 1.2374 loss_thr: 0.6379 loss_db: 0.2011 2022/10/25 22:36:16 - mmengine - INFO - Epoch(train) [237][45/63] lr: 2.9025e-03 eta: 13:57:14 time: 0.6581 data_time: 0.0104 memory: 16131 loss: 2.0605 loss_prob: 1.2364 loss_thr: 0.6218 loss_db: 0.2023 2022/10/25 22:36:21 - mmengine - INFO - Epoch(train) [237][50/63] lr: 2.9025e-03 eta: 13:57:09 time: 0.9132 data_time: 0.0424 memory: 16131 loss: 2.1514 loss_prob: 1.2991 loss_thr: 0.6414 loss_db: 0.2109 2022/10/25 22:36:25 - mmengine - INFO - Epoch(train) [237][55/63] lr: 2.9025e-03 eta: 13:57:09 time: 0.9011 data_time: 0.0414 memory: 16131 loss: 2.0502 loss_prob: 1.2240 loss_thr: 0.6285 loss_db: 0.1977 2022/10/25 22:36:28 - mmengine - INFO - Epoch(train) [237][60/63] lr: 2.9025e-03 eta: 13:56:54 time: 0.6653 data_time: 0.0088 memory: 16131 loss: 1.9346 loss_prob: 1.1383 loss_thr: 0.6125 loss_db: 0.1839 2022/10/25 22:36:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:36:35 - mmengine - INFO - Epoch(train) [238][5/63] lr: 2.8998e-03 eta: 13:56:54 time: 0.7860 data_time: 0.2391 memory: 16131 loss: 2.1268 loss_prob: 1.2834 loss_thr: 0.6318 loss_db: 0.2115 2022/10/25 22:36:38 - mmengine - INFO - Epoch(train) [238][10/63] lr: 2.8998e-03 eta: 13:56:37 time: 0.9087 data_time: 0.2389 memory: 16131 loss: 2.0189 loss_prob: 1.1958 loss_thr: 0.6281 loss_db: 0.1949 2022/10/25 22:36:45 - mmengine - INFO - Epoch(train) [238][15/63] lr: 2.8998e-03 eta: 13:56:37 time: 1.0883 data_time: 0.0072 memory: 16131 loss: 2.1607 loss_prob: 1.3036 loss_thr: 0.6523 loss_db: 0.2047 2022/10/25 22:36:51 - mmengine - INFO - Epoch(train) [238][20/63] lr: 2.8998e-03 eta: 13:56:45 time: 1.2369 data_time: 0.0069 memory: 16131 loss: 2.1229 loss_prob: 1.2719 loss_thr: 0.6496 loss_db: 0.2014 2022/10/25 22:36:55 - mmengine - INFO - Epoch(train) [238][25/63] lr: 2.8998e-03 eta: 13:56:45 time: 0.9572 data_time: 0.0214 memory: 16131 loss: 2.0330 loss_prob: 1.2050 loss_thr: 0.6290 loss_db: 0.1990 2022/10/25 22:36:58 - mmengine - INFO - Epoch(train) [238][30/63] lr: 2.8998e-03 eta: 13:56:33 time: 0.7266 data_time: 0.0321 memory: 16131 loss: 2.1490 loss_prob: 1.2735 loss_thr: 0.6666 loss_db: 0.2089 2022/10/25 22:37:04 - mmengine - INFO - Epoch(train) [238][35/63] lr: 2.8998e-03 eta: 13:56:33 time: 0.8448 data_time: 0.0180 memory: 16131 loss: 2.1148 loss_prob: 1.2586 loss_thr: 0.6513 loss_db: 0.2050 2022/10/25 22:37:06 - mmengine - INFO - Epoch(train) [238][40/63] lr: 2.8998e-03 eta: 13:56:24 time: 0.8217 data_time: 0.0094 memory: 16131 loss: 2.0885 loss_prob: 1.2621 loss_thr: 0.6231 loss_db: 0.2034 2022/10/25 22:37:12 - mmengine - INFO - Epoch(train) [238][45/63] lr: 2.8998e-03 eta: 13:56:24 time: 0.8682 data_time: 0.0074 memory: 16131 loss: 2.0503 loss_prob: 1.2201 loss_thr: 0.6332 loss_db: 0.1970 2022/10/25 22:37:18 - mmengine - INFO - Epoch(train) [238][50/63] lr: 2.8998e-03 eta: 13:56:32 time: 1.2272 data_time: 0.0235 memory: 16131 loss: 2.0870 loss_prob: 1.2547 loss_thr: 0.6335 loss_db: 0.1988 2022/10/25 22:37:23 - mmengine - INFO - Epoch(train) [238][55/63] lr: 2.8998e-03 eta: 13:56:32 time: 1.0890 data_time: 0.0245 memory: 16131 loss: 2.1618 loss_prob: 1.3032 loss_thr: 0.6516 loss_db: 0.2070 2022/10/25 22:37:29 - mmengine - INFO - Epoch(train) [238][60/63] lr: 2.8998e-03 eta: 13:56:31 time: 1.0106 data_time: 0.0068 memory: 16131 loss: 2.1984 loss_prob: 1.3198 loss_thr: 0.6610 loss_db: 0.2175 2022/10/25 22:37:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:37:42 - mmengine - INFO - Epoch(train) [239][5/63] lr: 2.8971e-03 eta: 13:56:31 time: 1.5310 data_time: 0.2034 memory: 16131 loss: 2.2004 loss_prob: 1.3363 loss_thr: 0.6423 loss_db: 0.2218 2022/10/25 22:37:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:37:48 - mmengine - INFO - Epoch(train) [239][10/63] lr: 2.8971e-03 eta: 13:56:44 time: 1.6567 data_time: 0.2128 memory: 16131 loss: 2.1269 loss_prob: 1.2808 loss_thr: 0.6388 loss_db: 0.2073 2022/10/25 22:37:56 - mmengine - INFO - Epoch(train) [239][15/63] lr: 2.8971e-03 eta: 13:56:44 time: 1.4093 data_time: 0.0172 memory: 16131 loss: 2.1800 loss_prob: 1.3303 loss_thr: 0.6342 loss_db: 0.2155 2022/10/25 22:38:02 - mmengine - INFO - Epoch(train) [239][20/63] lr: 2.8971e-03 eta: 13:56:56 time: 1.3481 data_time: 0.0143 memory: 16131 loss: 2.2290 loss_prob: 1.3696 loss_thr: 0.6346 loss_db: 0.2247 2022/10/25 22:38:09 - mmengine - INFO - Epoch(train) [239][25/63] lr: 2.8971e-03 eta: 13:56:56 time: 1.2973 data_time: 0.0367 memory: 16131 loss: 2.1345 loss_prob: 1.2718 loss_thr: 0.6567 loss_db: 0.2059 2022/10/25 22:38:19 - mmengine - INFO - Epoch(train) [239][30/63] lr: 2.8971e-03 eta: 13:57:23 time: 1.6907 data_time: 0.0345 memory: 16131 loss: 2.2861 loss_prob: 1.3790 loss_thr: 0.6754 loss_db: 0.2318 2022/10/25 22:38:26 - mmengine - INFO - Epoch(train) [239][35/63] lr: 2.8971e-03 eta: 13:57:23 time: 1.6434 data_time: 0.0197 memory: 16131 loss: 2.3884 loss_prob: 1.4602 loss_thr: 0.6813 loss_db: 0.2470 2022/10/25 22:38:32 - mmengine - INFO - Epoch(train) [239][40/63] lr: 2.8971e-03 eta: 13:57:33 time: 1.2835 data_time: 0.0151 memory: 16131 loss: 2.1140 loss_prob: 1.2599 loss_thr: 0.6503 loss_db: 0.2038 2022/10/25 22:38:37 - mmengine - INFO - Epoch(train) [239][45/63] lr: 2.8971e-03 eta: 13:57:33 time: 1.1558 data_time: 0.0072 memory: 16131 loss: 2.0334 loss_prob: 1.2213 loss_thr: 0.6182 loss_db: 0.1940 2022/10/25 22:38:44 - mmengine - INFO - Epoch(train) [239][50/63] lr: 2.8971e-03 eta: 13:57:39 time: 1.1964 data_time: 0.0207 memory: 16131 loss: 2.1005 loss_prob: 1.2547 loss_thr: 0.6458 loss_db: 0.1999 2022/10/25 22:38:50 - mmengine - INFO - Epoch(train) [239][55/63] lr: 2.8971e-03 eta: 13:57:39 time: 1.2589 data_time: 0.0284 memory: 16131 loss: 2.0763 loss_prob: 1.2319 loss_thr: 0.6453 loss_db: 0.1992 2022/10/25 22:38:56 - mmengine - INFO - Epoch(train) [239][60/63] lr: 2.8971e-03 eta: 13:57:47 time: 1.2328 data_time: 0.0170 memory: 16131 loss: 1.9682 loss_prob: 1.1749 loss_thr: 0.6039 loss_db: 0.1894 2022/10/25 22:38:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:39:06 - mmengine - INFO - Epoch(train) [240][5/63] lr: 2.8944e-03 eta: 13:57:47 time: 1.3412 data_time: 0.2052 memory: 16131 loss: 2.1228 loss_prob: 1.2800 loss_thr: 0.6388 loss_db: 0.2040 2022/10/25 22:39:11 - mmengine - INFO - Epoch(train) [240][10/63] lr: 2.8944e-03 eta: 13:57:44 time: 1.2780 data_time: 0.2047 memory: 16131 loss: 2.0597 loss_prob: 1.2237 loss_thr: 0.6432 loss_db: 0.1928 2022/10/25 22:39:18 - mmengine - INFO - Epoch(train) [240][15/63] lr: 2.8944e-03 eta: 13:57:44 time: 1.2049 data_time: 0.0119 memory: 16131 loss: 2.0567 loss_prob: 1.2186 loss_thr: 0.6356 loss_db: 0.2026 2022/10/25 22:39:23 - mmengine - INFO - Epoch(train) [240][20/63] lr: 2.8944e-03 eta: 13:57:50 time: 1.1773 data_time: 0.0123 memory: 16131 loss: 2.2636 loss_prob: 1.3832 loss_thr: 0.6514 loss_db: 0.2290 2022/10/25 22:39:29 - mmengine - INFO - Epoch(train) [240][25/63] lr: 2.8944e-03 eta: 13:57:50 time: 1.0942 data_time: 0.0232 memory: 16131 loss: 2.1534 loss_prob: 1.3098 loss_thr: 0.6332 loss_db: 0.2104 2022/10/25 22:39:35 - mmengine - INFO - Epoch(train) [240][30/63] lr: 2.8944e-03 eta: 13:57:58 time: 1.2249 data_time: 0.0502 memory: 16131 loss: 1.9655 loss_prob: 1.1545 loss_thr: 0.6261 loss_db: 0.1850 2022/10/25 22:39:41 - mmengine - INFO - Epoch(train) [240][35/63] lr: 2.8944e-03 eta: 13:57:58 time: 1.2117 data_time: 0.0333 memory: 16131 loss: 2.0041 loss_prob: 1.1672 loss_thr: 0.6480 loss_db: 0.1889 2022/10/25 22:39:45 - mmengine - INFO - Epoch(train) [240][40/63] lr: 2.8944e-03 eta: 13:57:56 time: 0.9886 data_time: 0.0063 memory: 16131 loss: 2.0325 loss_prob: 1.1931 loss_thr: 0.6439 loss_db: 0.1955 2022/10/25 22:39:52 - mmengine - INFO - Epoch(train) [240][45/63] lr: 2.8944e-03 eta: 13:57:56 time: 1.1717 data_time: 0.0070 memory: 16131 loss: 1.9628 loss_prob: 1.1497 loss_thr: 0.6291 loss_db: 0.1840 2022/10/25 22:39:57 - mmengine - INFO - Epoch(train) [240][50/63] lr: 2.8944e-03 eta: 13:58:02 time: 1.1914 data_time: 0.0222 memory: 16131 loss: 2.0155 loss_prob: 1.1915 loss_thr: 0.6331 loss_db: 0.1909 2022/10/25 22:40:02 - mmengine - INFO - Epoch(train) [240][55/63] lr: 2.8944e-03 eta: 13:58:02 time: 0.9980 data_time: 0.0289 memory: 16131 loss: 2.0293 loss_prob: 1.2103 loss_thr: 0.6221 loss_db: 0.1969 2022/10/25 22:40:08 - mmengine - INFO - Epoch(train) [240][60/63] lr: 2.8944e-03 eta: 13:58:04 time: 1.0999 data_time: 0.0139 memory: 16131 loss: 1.9178 loss_prob: 1.1321 loss_thr: 0.6021 loss_db: 0.1836 2022/10/25 22:40:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:40:11 - mmengine - INFO - Saving checkpoint at 240 epochs 2022/10/25 22:40:18 - mmengine - INFO - Epoch(val) [240][5/32] eta: 13:58:04 time: 0.5386 data_time: 0.0607 memory: 16131 2022/10/25 22:40:22 - mmengine - INFO - Epoch(val) [240][10/32] eta: 0:00:15 time: 0.7008 data_time: 0.1056 memory: 15724 2022/10/25 22:40:25 - mmengine - INFO - Epoch(val) [240][15/32] eta: 0:00:15 time: 0.6780 data_time: 0.0725 memory: 15724 2022/10/25 22:40:29 - mmengine - INFO - Epoch(val) [240][20/32] eta: 0:00:07 time: 0.6339 data_time: 0.0768 memory: 15724 2022/10/25 22:40:32 - mmengine - INFO - Epoch(val) [240][25/32] eta: 0:00:07 time: 0.6282 data_time: 0.0677 memory: 15724 2022/10/25 22:40:34 - mmengine - INFO - Epoch(val) [240][30/32] eta: 0:00:01 time: 0.5749 data_time: 0.0239 memory: 15724 2022/10/25 22:40:35 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8291, precision: 0.5444, hmean: 0.6573 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8291, precision: 0.6122, hmean: 0.7043 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8272, precision: 0.6788, hmean: 0.7457 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8146, precision: 0.7570, hmean: 0.7848 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7554, precision: 0.8467, hmean: 0.7985 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2971, precision: 0.9463, hmean: 0.4522 2022/10/25 22:40:35 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 22:40:35 - mmengine - INFO - Epoch(val) [240][32/32] icdar/precision: 0.8467 icdar/recall: 0.7554 icdar/hmean: 0.7985 2022/10/25 22:40:45 - mmengine - INFO - Epoch(train) [241][5/63] lr: 2.8917e-03 eta: 0:00:01 time: 1.6268 data_time: 0.2562 memory: 16131 loss: 2.2030 loss_prob: 1.3281 loss_thr: 0.6579 loss_db: 0.2170 2022/10/25 22:40:49 - mmengine - INFO - Epoch(train) [241][10/63] lr: 2.8917e-03 eta: 13:58:08 time: 1.4393 data_time: 0.2586 memory: 16131 loss: 2.2499 loss_prob: 1.3628 loss_thr: 0.6651 loss_db: 0.2220 2022/10/25 22:40:57 - mmengine - INFO - Epoch(train) [241][15/63] lr: 2.8917e-03 eta: 13:58:08 time: 1.1884 data_time: 0.0120 memory: 16131 loss: 2.0939 loss_prob: 1.2757 loss_thr: 0.6133 loss_db: 0.2048 2022/10/25 22:41:03 - mmengine - INFO - Epoch(train) [241][20/63] lr: 2.8917e-03 eta: 13:58:19 time: 1.3181 data_time: 0.0090 memory: 16131 loss: 2.0235 loss_prob: 1.2068 loss_thr: 0.6215 loss_db: 0.1951 2022/10/25 22:41:08 - mmengine - INFO - Epoch(train) [241][25/63] lr: 2.8917e-03 eta: 13:58:19 time: 1.1068 data_time: 0.0336 memory: 16131 loss: 2.0228 loss_prob: 1.1804 loss_thr: 0.6484 loss_db: 0.1940 2022/10/25 22:41:15 - mmengine - INFO - Epoch(train) [241][30/63] lr: 2.8917e-03 eta: 13:58:28 time: 1.2761 data_time: 0.0354 memory: 16131 loss: 2.0624 loss_prob: 1.2247 loss_thr: 0.6386 loss_db: 0.1990 2022/10/25 22:41:21 - mmengine - INFO - Epoch(train) [241][35/63] lr: 2.8917e-03 eta: 13:58:28 time: 1.3088 data_time: 0.0135 memory: 16131 loss: 2.1656 loss_prob: 1.3234 loss_thr: 0.6285 loss_db: 0.2138 2022/10/25 22:41:27 - mmengine - INFO - Epoch(train) [241][40/63] lr: 2.8917e-03 eta: 13:58:32 time: 1.1254 data_time: 0.0099 memory: 16131 loss: 2.0780 loss_prob: 1.2637 loss_thr: 0.6113 loss_db: 0.2030 2022/10/25 22:41:32 - mmengine - INFO - Epoch(train) [241][45/63] lr: 2.8917e-03 eta: 13:58:32 time: 1.1266 data_time: 0.0067 memory: 16131 loss: 1.9488 loss_prob: 1.1581 loss_thr: 0.6019 loss_db: 0.1888 2022/10/25 22:41:39 - mmengine - INFO - Epoch(train) [241][50/63] lr: 2.8917e-03 eta: 13:58:39 time: 1.2370 data_time: 0.0334 memory: 16131 loss: 1.9477 loss_prob: 1.1620 loss_thr: 0.5956 loss_db: 0.1901 2022/10/25 22:41:46 - mmengine - INFO - Epoch(train) [241][55/63] lr: 2.8917e-03 eta: 13:58:39 time: 1.3389 data_time: 0.0339 memory: 16131 loss: 2.0991 loss_prob: 1.2559 loss_thr: 0.6361 loss_db: 0.2072 2022/10/25 22:41:51 - mmengine - INFO - Epoch(train) [241][60/63] lr: 2.8917e-03 eta: 13:58:46 time: 1.2040 data_time: 0.0090 memory: 16131 loss: 2.1845 loss_prob: 1.3048 loss_thr: 0.6667 loss_db: 0.2129 2022/10/25 22:41:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:42:04 - mmengine - INFO - Epoch(train) [242][5/63] lr: 2.8890e-03 eta: 13:58:46 time: 1.5445 data_time: 0.2123 memory: 16131 loss: 2.0785 loss_prob: 1.2393 loss_thr: 0.6372 loss_db: 0.2019 2022/10/25 22:42:08 - mmengine - INFO - Epoch(train) [242][10/63] lr: 2.8890e-03 eta: 13:58:45 time: 1.3398 data_time: 0.2251 memory: 16131 loss: 1.9379 loss_prob: 1.1491 loss_thr: 0.6021 loss_db: 0.1868 2022/10/25 22:42:13 - mmengine - INFO - Epoch(train) [242][15/63] lr: 2.8890e-03 eta: 13:58:45 time: 0.8669 data_time: 0.0206 memory: 16131 loss: 1.9395 loss_prob: 1.1457 loss_thr: 0.6072 loss_db: 0.1866 2022/10/25 22:42:15 - mmengine - INFO - Epoch(train) [242][20/63] lr: 2.8890e-03 eta: 13:58:35 time: 0.7923 data_time: 0.0123 memory: 16131 loss: 2.0572 loss_prob: 1.2268 loss_thr: 0.6313 loss_db: 0.1990 2022/10/25 22:42:18 - mmengine - INFO - Epoch(train) [242][25/63] lr: 2.8890e-03 eta: 13:58:35 time: 0.5763 data_time: 0.0135 memory: 16131 loss: 2.1334 loss_prob: 1.2700 loss_thr: 0.6531 loss_db: 0.2103 2022/10/25 22:42:24 - mmengine - INFO - Epoch(train) [242][30/63] lr: 2.8890e-03 eta: 13:58:27 time: 0.8284 data_time: 0.0246 memory: 16131 loss: 2.1068 loss_prob: 1.2554 loss_thr: 0.6405 loss_db: 0.2109 2022/10/25 22:42:27 - mmengine - INFO - Epoch(train) [242][35/63] lr: 2.8890e-03 eta: 13:58:27 time: 0.9015 data_time: 0.0341 memory: 16131 loss: 2.0301 loss_prob: 1.2165 loss_thr: 0.6141 loss_db: 0.1995 2022/10/25 22:42:34 - mmengine - INFO - Epoch(train) [242][40/63] lr: 2.8890e-03 eta: 13:58:25 time: 1.0075 data_time: 0.0204 memory: 16131 loss: 2.1223 loss_prob: 1.2564 loss_thr: 0.6616 loss_db: 0.2043 2022/10/25 22:42:38 - mmengine - INFO - Epoch(train) [242][45/63] lr: 2.8890e-03 eta: 13:58:25 time: 1.0612 data_time: 0.0151 memory: 16131 loss: 2.4883 loss_prob: 1.5436 loss_thr: 0.6974 loss_db: 0.2473 2022/10/25 22:42:46 - mmengine - INFO - Epoch(train) [242][50/63] lr: 2.8890e-03 eta: 13:58:31 time: 1.1761 data_time: 0.0207 memory: 16131 loss: 2.4987 loss_prob: 1.5867 loss_thr: 0.6683 loss_db: 0.2436 2022/10/25 22:42:55 - mmengine - INFO - Epoch(train) [242][55/63] lr: 2.8890e-03 eta: 13:58:31 time: 1.6875 data_time: 0.0262 memory: 16131 loss: 2.3636 loss_prob: 1.4617 loss_thr: 0.6748 loss_db: 0.2271 2022/10/25 22:43:02 - mmengine - INFO - Epoch(train) [242][60/63] lr: 2.8890e-03 eta: 13:58:53 time: 1.6236 data_time: 0.0251 memory: 16131 loss: 2.2492 loss_prob: 1.3627 loss_thr: 0.6669 loss_db: 0.2196 2022/10/25 22:43:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:43:15 - mmengine - INFO - Epoch(train) [243][5/63] lr: 2.8862e-03 eta: 13:58:53 time: 1.7645 data_time: 0.2688 memory: 16131 loss: 2.1235 loss_prob: 1.2641 loss_thr: 0.6530 loss_db: 0.2063 2022/10/25 22:43:21 - mmengine - INFO - Epoch(train) [243][10/63] lr: 2.8862e-03 eta: 13:58:55 time: 1.4055 data_time: 0.2687 memory: 16131 loss: 2.1864 loss_prob: 1.3081 loss_thr: 0.6615 loss_db: 0.2168 2022/10/25 22:43:28 - mmengine - INFO - Epoch(train) [243][15/63] lr: 2.8862e-03 eta: 13:58:55 time: 1.2952 data_time: 0.0065 memory: 16131 loss: 2.3857 loss_prob: 1.4713 loss_thr: 0.6699 loss_db: 0.2444 2022/10/25 22:43:33 - mmengine - INFO - Epoch(train) [243][20/63] lr: 2.8862e-03 eta: 13:59:04 time: 1.2584 data_time: 0.0122 memory: 16131 loss: 2.3373 loss_prob: 1.4357 loss_thr: 0.6602 loss_db: 0.2414 2022/10/25 22:43:39 - mmengine - INFO - Epoch(train) [243][25/63] lr: 2.8862e-03 eta: 13:59:04 time: 1.1096 data_time: 0.0263 memory: 16131 loss: 2.1673 loss_prob: 1.3085 loss_thr: 0.6438 loss_db: 0.2150 2022/10/25 22:43:45 - mmengine - INFO - Epoch(train) [243][30/63] lr: 2.8862e-03 eta: 13:59:07 time: 1.1277 data_time: 0.0571 memory: 16131 loss: 2.3539 loss_prob: 1.4623 loss_thr: 0.6514 loss_db: 0.2402 2022/10/25 22:43:52 - mmengine - INFO - Epoch(train) [243][35/63] lr: 2.8862e-03 eta: 13:59:07 time: 1.2166 data_time: 0.0432 memory: 16131 loss: 2.5361 loss_prob: 1.6067 loss_thr: 0.6670 loss_db: 0.2624 2022/10/25 22:43:56 - mmengine - INFO - Epoch(train) [243][40/63] lr: 2.8862e-03 eta: 13:59:12 time: 1.1839 data_time: 0.0069 memory: 16131 loss: 2.5178 loss_prob: 1.5894 loss_thr: 0.6696 loss_db: 0.2588 2022/10/25 22:44:04 - mmengine - INFO - Epoch(train) [243][45/63] lr: 2.8862e-03 eta: 13:59:12 time: 1.2063 data_time: 0.0099 memory: 16131 loss: 2.3285 loss_prob: 1.4446 loss_thr: 0.6451 loss_db: 0.2388 2022/10/25 22:44:07 - mmengine - INFO - Epoch(train) [243][50/63] lr: 2.8862e-03 eta: 13:59:14 time: 1.0860 data_time: 0.0220 memory: 16131 loss: 2.2296 loss_prob: 1.3673 loss_thr: 0.6443 loss_db: 0.2180 2022/10/25 22:44:11 - mmengine - INFO - Epoch(train) [243][55/63] lr: 2.8862e-03 eta: 13:59:14 time: 0.7432 data_time: 0.0261 memory: 16131 loss: 2.2399 loss_prob: 1.3666 loss_thr: 0.6557 loss_db: 0.2176 2022/10/25 22:44:15 - mmengine - INFO - Epoch(train) [243][60/63] lr: 2.8862e-03 eta: 13:59:02 time: 0.7336 data_time: 0.0125 memory: 16131 loss: 2.2221 loss_prob: 1.3450 loss_thr: 0.6572 loss_db: 0.2199 2022/10/25 22:44:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:44:22 - mmengine - INFO - Epoch(train) [244][5/63] lr: 2.8835e-03 eta: 13:59:02 time: 0.8370 data_time: 0.2228 memory: 16131 loss: 2.4545 loss_prob: 1.5060 loss_thr: 0.7040 loss_db: 0.2445 2022/10/25 22:44:26 - mmengine - INFO - Epoch(train) [244][10/63] lr: 2.8835e-03 eta: 13:58:46 time: 0.9645 data_time: 0.2203 memory: 16131 loss: 2.3728 loss_prob: 1.4504 loss_thr: 0.6845 loss_db: 0.2379 2022/10/25 22:44:33 - mmengine - INFO - Epoch(train) [244][15/63] lr: 2.8835e-03 eta: 13:58:46 time: 1.1465 data_time: 0.0069 memory: 16131 loss: 2.3929 loss_prob: 1.4738 loss_thr: 0.6748 loss_db: 0.2443 2022/10/25 22:44:39 - mmengine - INFO - Epoch(train) [244][20/63] lr: 2.8835e-03 eta: 13:58:56 time: 1.3119 data_time: 0.0071 memory: 16131 loss: 2.2802 loss_prob: 1.3822 loss_thr: 0.6718 loss_db: 0.2263 2022/10/25 22:44:45 - mmengine - INFO - Epoch(train) [244][25/63] lr: 2.8835e-03 eta: 13:58:56 time: 1.1515 data_time: 0.0430 memory: 16131 loss: 2.1226 loss_prob: 1.2626 loss_thr: 0.6533 loss_db: 0.2067 2022/10/25 22:44:51 - mmengine - INFO - Epoch(train) [244][30/63] lr: 2.8835e-03 eta: 13:59:04 time: 1.2396 data_time: 0.0427 memory: 16131 loss: 1.9875 loss_prob: 1.1654 loss_thr: 0.6302 loss_db: 0.1919 2022/10/25 22:44:58 - mmengine - INFO - Epoch(train) [244][35/63] lr: 2.8835e-03 eta: 13:59:04 time: 1.2791 data_time: 0.0063 memory: 16131 loss: 1.9769 loss_prob: 1.1529 loss_thr: 0.6342 loss_db: 0.1897 2022/10/25 22:45:03 - mmengine - INFO - Epoch(train) [244][40/63] lr: 2.8835e-03 eta: 13:59:09 time: 1.1676 data_time: 0.0078 memory: 16131 loss: 1.9777 loss_prob: 1.1371 loss_thr: 0.6520 loss_db: 0.1886 2022/10/25 22:45:06 - mmengine - INFO - Epoch(train) [244][45/63] lr: 2.8835e-03 eta: 13:59:09 time: 0.8626 data_time: 0.0085 memory: 16131 loss: 2.0241 loss_prob: 1.1797 loss_thr: 0.6505 loss_db: 0.1938 2022/10/25 22:45:15 - mmengine - INFO - Epoch(train) [244][50/63] lr: 2.8835e-03 eta: 13:59:14 time: 1.1837 data_time: 0.0247 memory: 16131 loss: 2.0698 loss_prob: 1.2319 loss_thr: 0.6365 loss_db: 0.2014 2022/10/25 22:45:17 - mmengine - INFO - Epoch(train) [244][55/63] lr: 2.8835e-03 eta: 13:59:14 time: 1.0974 data_time: 0.0242 memory: 16131 loss: 1.9441 loss_prob: 1.1571 loss_thr: 0.5999 loss_db: 0.1872 2022/10/25 22:45:25 - mmengine - INFO - Epoch(train) [244][60/63] lr: 2.8835e-03 eta: 13:59:12 time: 0.9917 data_time: 0.0087 memory: 16131 loss: 2.2108 loss_prob: 1.3502 loss_thr: 0.6432 loss_db: 0.2174 2022/10/25 22:45:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:45:38 - mmengine - INFO - Epoch(train) [245][5/63] lr: 2.8808e-03 eta: 13:59:12 time: 1.6977 data_time: 0.2495 memory: 16131 loss: 2.0680 loss_prob: 1.2336 loss_thr: 0.6309 loss_db: 0.2034 2022/10/25 22:45:43 - mmengine - INFO - Epoch(train) [245][10/63] lr: 2.8808e-03 eta: 13:59:17 time: 1.4935 data_time: 0.2417 memory: 16131 loss: 2.1048 loss_prob: 1.2662 loss_thr: 0.6309 loss_db: 0.2076 2022/10/25 22:45:50 - mmengine - INFO - Epoch(train) [245][15/63] lr: 2.8808e-03 eta: 13:59:17 time: 1.1354 data_time: 0.0185 memory: 16131 loss: 2.1556 loss_prob: 1.3075 loss_thr: 0.6352 loss_db: 0.2128 2022/10/25 22:45:55 - mmengine - INFO - Epoch(train) [245][20/63] lr: 2.8808e-03 eta: 13:59:20 time: 1.1422 data_time: 0.0155 memory: 16131 loss: 2.1719 loss_prob: 1.3182 loss_thr: 0.6351 loss_db: 0.2186 2022/10/25 22:46:00 - mmengine - INFO - Epoch(train) [245][25/63] lr: 2.8808e-03 eta: 13:59:20 time: 1.0547 data_time: 0.0338 memory: 16131 loss: 2.2146 loss_prob: 1.3638 loss_thr: 0.6226 loss_db: 0.2282 2022/10/25 22:46:07 - mmengine - INFO - Epoch(train) [245][30/63] lr: 2.8808e-03 eta: 13:59:29 time: 1.2830 data_time: 0.0420 memory: 16131 loss: 2.5394 loss_prob: 1.6111 loss_thr: 0.6650 loss_db: 0.2633 2022/10/25 22:46:12 - mmengine - INFO - Epoch(train) [245][35/63] lr: 2.8808e-03 eta: 13:59:29 time: 1.1382 data_time: 0.0196 memory: 16131 loss: 2.4727 loss_prob: 1.5448 loss_thr: 0.6831 loss_db: 0.2447 2022/10/25 22:46:17 - mmengine - INFO - Epoch(train) [245][40/63] lr: 2.8808e-03 eta: 13:59:26 time: 0.9604 data_time: 0.0112 memory: 16131 loss: 2.2602 loss_prob: 1.3734 loss_thr: 0.6612 loss_db: 0.2256 2022/10/25 22:46:24 - mmengine - INFO - Epoch(train) [245][45/63] lr: 2.8808e-03 eta: 13:59:26 time: 1.2233 data_time: 0.0082 memory: 16131 loss: 2.3850 loss_prob: 1.4701 loss_thr: 0.6736 loss_db: 0.2413 2022/10/25 22:46:28 - mmengine - INFO - Epoch(train) [245][50/63] lr: 2.8808e-03 eta: 13:59:26 time: 1.0551 data_time: 0.0279 memory: 16131 loss: 2.2319 loss_prob: 1.3499 loss_thr: 0.6672 loss_db: 0.2148 2022/10/25 22:46:32 - mmengine - INFO - Epoch(train) [245][55/63] lr: 2.8808e-03 eta: 13:59:26 time: 0.7973 data_time: 0.0289 memory: 16131 loss: 2.2349 loss_prob: 1.3643 loss_thr: 0.6536 loss_db: 0.2170 2022/10/25 22:46:35 - mmengine - INFO - Epoch(train) [245][60/63] lr: 2.8808e-03 eta: 13:59:14 time: 0.7351 data_time: 0.0107 memory: 16131 loss: 2.2155 loss_prob: 1.3443 loss_thr: 0.6545 loss_db: 0.2167 2022/10/25 22:46:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:46:47 - mmengine - INFO - Epoch(train) [246][5/63] lr: 2.8781e-03 eta: 13:59:14 time: 1.3052 data_time: 0.2669 memory: 16131 loss: 2.0003 loss_prob: 1.1955 loss_thr: 0.6142 loss_db: 0.1906 2022/10/25 22:46:53 - mmengine - INFO - Epoch(train) [246][10/63] lr: 2.8781e-03 eta: 13:59:21 time: 1.5586 data_time: 0.2645 memory: 16131 loss: 1.8877 loss_prob: 1.1259 loss_thr: 0.5818 loss_db: 0.1801 2022/10/25 22:47:00 - mmengine - INFO - Epoch(train) [246][15/63] lr: 2.8781e-03 eta: 13:59:21 time: 1.2656 data_time: 0.0081 memory: 16131 loss: 2.0113 loss_prob: 1.2202 loss_thr: 0.5928 loss_db: 0.1983 2022/10/25 22:47:02 - mmengine - INFO - Epoch(train) [246][20/63] lr: 2.8781e-03 eta: 13:59:16 time: 0.9114 data_time: 0.0097 memory: 16131 loss: 2.1709 loss_prob: 1.3361 loss_thr: 0.6167 loss_db: 0.2181 2022/10/25 22:47:05 - mmengine - INFO - Epoch(train) [246][25/63] lr: 2.8781e-03 eta: 13:59:16 time: 0.5647 data_time: 0.0247 memory: 16131 loss: 2.1224 loss_prob: 1.2816 loss_thr: 0.6358 loss_db: 0.2050 2022/10/25 22:47:12 - mmengine - INFO - Epoch(train) [246][30/63] lr: 2.8781e-03 eta: 13:59:13 time: 0.9891 data_time: 0.0322 memory: 16131 loss: 2.1516 loss_prob: 1.3171 loss_thr: 0.6244 loss_db: 0.2101 2022/10/25 22:47:17 - mmengine - INFO - Epoch(train) [246][35/63] lr: 2.8781e-03 eta: 13:59:13 time: 1.2026 data_time: 0.0180 memory: 16131 loss: 2.2683 loss_prob: 1.3825 loss_thr: 0.6601 loss_db: 0.2258 2022/10/25 22:47:22 - mmengine - INFO - Epoch(train) [246][40/63] lr: 2.8781e-03 eta: 13:59:10 time: 0.9648 data_time: 0.0118 memory: 16131 loss: 2.2065 loss_prob: 1.3160 loss_thr: 0.6757 loss_db: 0.2147 2022/10/25 22:47:28 - mmengine - INFO - Epoch(train) [246][45/63] lr: 2.8781e-03 eta: 13:59:10 time: 1.0470 data_time: 0.0158 memory: 16131 loss: 2.2172 loss_prob: 1.3524 loss_thr: 0.6507 loss_db: 0.2141 2022/10/25 22:47:35 - mmengine - INFO - Epoch(train) [246][50/63] lr: 2.8781e-03 eta: 13:59:21 time: 1.3428 data_time: 0.0243 memory: 16131 loss: 2.2457 loss_prob: 1.3696 loss_thr: 0.6585 loss_db: 0.2176 2022/10/25 22:47:41 - mmengine - INFO - Epoch(train) [246][55/63] lr: 2.8781e-03 eta: 13:59:21 time: 1.3306 data_time: 0.0257 memory: 16131 loss: 2.1082 loss_prob: 1.2774 loss_thr: 0.6220 loss_db: 0.2088 2022/10/25 22:47:44 - mmengine - INFO - Epoch(train) [246][60/63] lr: 2.8781e-03 eta: 13:59:15 time: 0.8886 data_time: 0.0164 memory: 16131 loss: 2.0305 loss_prob: 1.2056 loss_thr: 0.6285 loss_db: 0.1965 2022/10/25 22:47:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:47:56 - mmengine - INFO - Epoch(train) [247][5/63] lr: 2.8754e-03 eta: 13:59:15 time: 1.2857 data_time: 0.2337 memory: 16131 loss: 1.9411 loss_prob: 1.1438 loss_thr: 0.6137 loss_db: 0.1836 2022/10/25 22:48:03 - mmengine - INFO - Epoch(train) [247][10/63] lr: 2.8754e-03 eta: 13:59:26 time: 1.6607 data_time: 0.2549 memory: 16131 loss: 2.3366 loss_prob: 1.4493 loss_thr: 0.6591 loss_db: 0.2282 2022/10/25 22:48:09 - mmengine - INFO - Epoch(train) [247][15/63] lr: 2.8754e-03 eta: 13:59:26 time: 1.2909 data_time: 0.0312 memory: 16131 loss: 2.4240 loss_prob: 1.5181 loss_thr: 0.6652 loss_db: 0.2407 2022/10/25 22:48:16 - mmengine - INFO - Epoch(train) [247][20/63] lr: 2.8754e-03 eta: 13:59:34 time: 1.2652 data_time: 0.0091 memory: 16131 loss: 2.0848 loss_prob: 1.2491 loss_thr: 0.6303 loss_db: 0.2053 2022/10/25 22:48:25 - mmengine - INFO - Epoch(train) [247][25/63] lr: 2.8754e-03 eta: 13:59:34 time: 1.6734 data_time: 0.0285 memory: 16131 loss: 2.0088 loss_prob: 1.1906 loss_thr: 0.6207 loss_db: 0.1975 2022/10/25 22:48:31 - mmengine - INFO - Epoch(train) [247][30/63] lr: 2.8754e-03 eta: 13:59:51 time: 1.5040 data_time: 0.0325 memory: 16131 loss: 2.0205 loss_prob: 1.1824 loss_thr: 0.6449 loss_db: 0.1932 2022/10/25 22:48:35 - mmengine - INFO - Epoch(train) [247][35/63] lr: 2.8754e-03 eta: 13:59:51 time: 0.9808 data_time: 0.0161 memory: 16131 loss: 2.0501 loss_prob: 1.1959 loss_thr: 0.6585 loss_db: 0.1956 2022/10/25 22:48:43 - mmengine - INFO - Epoch(train) [247][40/63] lr: 2.8754e-03 eta: 13:59:56 time: 1.1850 data_time: 0.0137 memory: 16131 loss: 1.9782 loss_prob: 1.1545 loss_thr: 0.6341 loss_db: 0.1895 2022/10/25 22:48:51 - mmengine - INFO - Epoch(train) [247][45/63] lr: 2.8754e-03 eta: 13:59:56 time: 1.6273 data_time: 0.0099 memory: 16131 loss: 1.9464 loss_prob: 1.1371 loss_thr: 0.6235 loss_db: 0.1858 2022/10/25 22:48:59 - mmengine - INFO - Epoch(train) [247][50/63] lr: 2.8754e-03 eta: 14:00:16 time: 1.5663 data_time: 0.0193 memory: 16131 loss: 1.9863 loss_prob: 1.1787 loss_thr: 0.6186 loss_db: 0.1890 2022/10/25 22:49:07 - mmengine - INFO - Epoch(train) [247][55/63] lr: 2.8754e-03 eta: 14:00:16 time: 1.5390 data_time: 0.0270 memory: 16131 loss: 1.9178 loss_prob: 1.1311 loss_thr: 0.6069 loss_db: 0.1798 2022/10/25 22:49:10 - mmengine - INFO - Epoch(train) [247][60/63] lr: 2.8754e-03 eta: 14:00:20 time: 1.1560 data_time: 0.0183 memory: 16131 loss: 1.8929 loss_prob: 1.0964 loss_thr: 0.6176 loss_db: 0.1789 2022/10/25 22:49:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:49:22 - mmengine - INFO - Epoch(train) [248][5/63] lr: 2.8727e-03 eta: 14:00:20 time: 1.3175 data_time: 0.2154 memory: 16131 loss: 1.9951 loss_prob: 1.1621 loss_thr: 0.6474 loss_db: 0.1856 2022/10/25 22:49:30 - mmengine - INFO - Epoch(train) [248][10/63] lr: 2.8727e-03 eta: 14:00:36 time: 1.8005 data_time: 0.2147 memory: 16131 loss: 2.0419 loss_prob: 1.2137 loss_thr: 0.6309 loss_db: 0.1973 2022/10/25 22:49:38 - mmengine - INFO - Epoch(train) [248][15/63] lr: 2.8727e-03 eta: 14:00:36 time: 1.6240 data_time: 0.0088 memory: 16131 loss: 1.9750 loss_prob: 1.1646 loss_thr: 0.6184 loss_db: 0.1921 2022/10/25 22:49:44 - mmengine - INFO - Epoch(train) [248][20/63] lr: 2.8727e-03 eta: 14:00:49 time: 1.3933 data_time: 0.0097 memory: 16131 loss: 1.9171 loss_prob: 1.1146 loss_thr: 0.6232 loss_db: 0.1794 2022/10/25 22:49:49 - mmengine - INFO - Epoch(train) [248][25/63] lr: 2.8727e-03 eta: 14:00:49 time: 1.0787 data_time: 0.0250 memory: 16131 loss: 1.8999 loss_prob: 1.0973 loss_thr: 0.6237 loss_db: 0.1789 2022/10/25 22:49:56 - mmengine - INFO - Epoch(train) [248][30/63] lr: 2.8727e-03 eta: 14:00:56 time: 1.2242 data_time: 0.0403 memory: 16131 loss: 1.8544 loss_prob: 1.0470 loss_thr: 0.6330 loss_db: 0.1744 2022/10/25 22:50:02 - mmengine - INFO - Epoch(train) [248][35/63] lr: 2.8727e-03 eta: 14:00:56 time: 1.2266 data_time: 0.0265 memory: 16131 loss: 1.9100 loss_prob: 1.0995 loss_thr: 0.6324 loss_db: 0.1780 2022/10/25 22:50:10 - mmengine - INFO - Epoch(train) [248][40/63] lr: 2.8727e-03 eta: 14:01:07 time: 1.3532 data_time: 0.0073 memory: 16131 loss: 1.9967 loss_prob: 1.1694 loss_thr: 0.6306 loss_db: 0.1967 2022/10/25 22:50:14 - mmengine - INFO - Epoch(train) [248][45/63] lr: 2.8727e-03 eta: 14:01:07 time: 1.2578 data_time: 0.0059 memory: 16131 loss: 2.1041 loss_prob: 1.2613 loss_thr: 0.6320 loss_db: 0.2108 2022/10/25 22:50:21 - mmengine - INFO - Epoch(train) [248][50/63] lr: 2.8727e-03 eta: 14:01:09 time: 1.1020 data_time: 0.0346 memory: 16131 loss: 2.2638 loss_prob: 1.3923 loss_thr: 0.6530 loss_db: 0.2184 2022/10/25 22:50:25 - mmengine - INFO - Epoch(train) [248][55/63] lr: 2.8727e-03 eta: 14:01:09 time: 1.1374 data_time: 0.0437 memory: 16131 loss: 2.2052 loss_prob: 1.3528 loss_thr: 0.6381 loss_db: 0.2143 2022/10/25 22:50:29 - mmengine - INFO - Epoch(train) [248][60/63] lr: 2.8727e-03 eta: 14:01:01 time: 0.8549 data_time: 0.0160 memory: 16131 loss: 2.1026 loss_prob: 1.2771 loss_thr: 0.6210 loss_db: 0.2045 2022/10/25 22:50:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:50:41 - mmengine - INFO - Epoch(train) [249][5/63] lr: 2.8700e-03 eta: 14:01:01 time: 1.2378 data_time: 0.2601 memory: 16131 loss: 2.2057 loss_prob: 1.3252 loss_thr: 0.6660 loss_db: 0.2145 2022/10/25 22:50:49 - mmengine - INFO - Epoch(train) [249][10/63] lr: 2.8700e-03 eta: 14:01:14 time: 1.7316 data_time: 0.2588 memory: 16131 loss: 2.1373 loss_prob: 1.2708 loss_thr: 0.6559 loss_db: 0.2106 2022/10/25 22:50:55 - mmengine - INFO - Epoch(train) [249][15/63] lr: 2.8700e-03 eta: 14:01:14 time: 1.4556 data_time: 0.0080 memory: 16131 loss: 2.0201 loss_prob: 1.1926 loss_thr: 0.6287 loss_db: 0.1988 2022/10/25 22:51:02 - mmengine - INFO - Epoch(train) [249][20/63] lr: 2.8700e-03 eta: 14:01:22 time: 1.2769 data_time: 0.0062 memory: 16131 loss: 1.9216 loss_prob: 1.1269 loss_thr: 0.6085 loss_db: 0.1862 2022/10/25 22:51:08 - mmengine - INFO - Epoch(train) [249][25/63] lr: 2.8700e-03 eta: 14:01:22 time: 1.3092 data_time: 0.0284 memory: 16131 loss: 2.0238 loss_prob: 1.1930 loss_thr: 0.6340 loss_db: 0.1968 2022/10/25 22:51:14 - mmengine - INFO - Epoch(train) [249][30/63] lr: 2.8700e-03 eta: 14:01:26 time: 1.1652 data_time: 0.0571 memory: 16131 loss: 2.0898 loss_prob: 1.2531 loss_thr: 0.6325 loss_db: 0.2041 2022/10/25 22:51:19 - mmengine - INFO - Epoch(train) [249][35/63] lr: 2.8700e-03 eta: 14:01:26 time: 1.1154 data_time: 0.0361 memory: 16131 loss: 2.1508 loss_prob: 1.3064 loss_thr: 0.6359 loss_db: 0.2085 2022/10/25 22:51:25 - mmengine - INFO - Epoch(train) [249][40/63] lr: 2.8700e-03 eta: 14:01:28 time: 1.0947 data_time: 0.0062 memory: 16131 loss: 2.1268 loss_prob: 1.2783 loss_thr: 0.6465 loss_db: 0.2019 2022/10/25 22:51:30 - mmengine - INFO - Epoch(train) [249][45/63] lr: 2.8700e-03 eta: 14:01:28 time: 1.0740 data_time: 0.0054 memory: 16131 loss: 1.9431 loss_prob: 1.1437 loss_thr: 0.6176 loss_db: 0.1818 2022/10/25 22:51:35 - mmengine - INFO - Epoch(train) [249][50/63] lr: 2.8700e-03 eta: 14:01:28 time: 1.0671 data_time: 0.0335 memory: 16131 loss: 1.9307 loss_prob: 1.1306 loss_thr: 0.6146 loss_db: 0.1855 2022/10/25 22:51:42 - mmengine - INFO - Epoch(train) [249][55/63] lr: 2.8700e-03 eta: 14:01:28 time: 1.2075 data_time: 0.0400 memory: 16131 loss: 2.0651 loss_prob: 1.2172 loss_thr: 0.6490 loss_db: 0.1989 2022/10/25 22:51:51 - mmengine - INFO - Epoch(train) [249][60/63] lr: 2.8700e-03 eta: 14:01:49 time: 1.6198 data_time: 0.0137 memory: 16131 loss: 2.4085 loss_prob: 1.5021 loss_thr: 0.6716 loss_db: 0.2347 2022/10/25 22:51:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:52:02 - mmengine - INFO - Epoch(train) [250][5/63] lr: 2.8672e-03 eta: 14:01:49 time: 1.4262 data_time: 0.1978 memory: 16131 loss: 2.1246 loss_prob: 1.2856 loss_thr: 0.6319 loss_db: 0.2071 2022/10/25 22:52:10 - mmengine - INFO - Epoch(train) [250][10/63] lr: 2.8672e-03 eta: 14:02:00 time: 1.6695 data_time: 0.1971 memory: 16131 loss: 1.9768 loss_prob: 1.1549 loss_thr: 0.6325 loss_db: 0.1894 2022/10/25 22:52:13 - mmengine - INFO - Epoch(train) [250][15/63] lr: 2.8672e-03 eta: 14:02:00 time: 1.1219 data_time: 0.0059 memory: 16131 loss: 1.9509 loss_prob: 1.1588 loss_thr: 0.5991 loss_db: 0.1930 2022/10/25 22:52:20 - mmengine - INFO - Epoch(train) [250][20/63] lr: 2.8672e-03 eta: 14:01:59 time: 1.0322 data_time: 0.0103 memory: 16131 loss: 1.8964 loss_prob: 1.1303 loss_thr: 0.5843 loss_db: 0.1818 2022/10/25 22:52:26 - mmengine - INFO - Epoch(train) [250][25/63] lr: 2.8672e-03 eta: 14:01:59 time: 1.3422 data_time: 0.0384 memory: 16131 loss: 1.8900 loss_prob: 1.1170 loss_thr: 0.5914 loss_db: 0.1816 2022/10/25 22:52:30 - mmengine - INFO - Epoch(train) [250][30/63] lr: 2.8672e-03 eta: 14:01:58 time: 1.0354 data_time: 0.0398 memory: 16131 loss: 1.8985 loss_prob: 1.1140 loss_thr: 0.5988 loss_db: 0.1857 2022/10/25 22:52:35 - mmengine - INFO - Epoch(train) [250][35/63] lr: 2.8672e-03 eta: 14:01:58 time: 0.8932 data_time: 0.0128 memory: 16131 loss: 1.9195 loss_prob: 1.1301 loss_thr: 0.6053 loss_db: 0.1842 2022/10/25 22:52:41 - mmengine - INFO - Epoch(train) [250][40/63] lr: 2.8672e-03 eta: 14:01:58 time: 1.0676 data_time: 0.0083 memory: 16131 loss: 1.9186 loss_prob: 1.1307 loss_thr: 0.6043 loss_db: 0.1836 2022/10/25 22:52:49 - mmengine - INFO - Epoch(train) [250][45/63] lr: 2.8672e-03 eta: 14:01:58 time: 1.3321 data_time: 0.0098 memory: 16131 loss: 1.8983 loss_prob: 1.1081 loss_thr: 0.6083 loss_db: 0.1819 2022/10/25 22:52:55 - mmengine - INFO - Epoch(train) [250][50/63] lr: 2.8672e-03 eta: 14:02:12 time: 1.4395 data_time: 0.0212 memory: 16131 loss: 1.9790 loss_prob: 1.1577 loss_thr: 0.6319 loss_db: 0.1894 2022/10/25 22:53:00 - mmengine - INFO - Epoch(train) [250][55/63] lr: 2.8672e-03 eta: 14:02:12 time: 1.1136 data_time: 0.0249 memory: 16131 loss: 2.0358 loss_prob: 1.2022 loss_thr: 0.6410 loss_db: 0.1927 2022/10/25 22:53:05 - mmengine - INFO - Epoch(train) [250][60/63] lr: 2.8672e-03 eta: 14:02:09 time: 0.9919 data_time: 0.0123 memory: 16131 loss: 2.1382 loss_prob: 1.2697 loss_thr: 0.6667 loss_db: 0.2018 2022/10/25 22:53:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:53:19 - mmengine - INFO - Epoch(train) [251][5/63] lr: 2.8645e-03 eta: 14:02:09 time: 1.6798 data_time: 0.2765 memory: 16131 loss: 2.1176 loss_prob: 1.2605 loss_thr: 0.6515 loss_db: 0.2056 2022/10/25 22:53:29 - mmengine - INFO - Epoch(train) [251][10/63] lr: 2.8645e-03 eta: 14:02:30 time: 1.9297 data_time: 0.2772 memory: 16131 loss: 1.9924 loss_prob: 1.1822 loss_thr: 0.6202 loss_db: 0.1900 2022/10/25 22:53:36 - mmengine - INFO - Epoch(train) [251][15/63] lr: 2.8645e-03 eta: 14:02:30 time: 1.6596 data_time: 0.0069 memory: 16131 loss: 1.9828 loss_prob: 1.1885 loss_thr: 0.6019 loss_db: 0.1924 2022/10/25 22:53:42 - mmengine - INFO - Epoch(train) [251][20/63] lr: 2.8645e-03 eta: 14:02:41 time: 1.3519 data_time: 0.0085 memory: 16131 loss: 1.9542 loss_prob: 1.1719 loss_thr: 0.5930 loss_db: 0.1893 2022/10/25 22:53:50 - mmengine - INFO - Epoch(train) [251][25/63] lr: 2.8645e-03 eta: 14:02:41 time: 1.3690 data_time: 0.0566 memory: 16131 loss: 1.9611 loss_prob: 1.1523 loss_thr: 0.6218 loss_db: 0.1870 2022/10/25 22:53:55 - mmengine - INFO - Epoch(train) [251][30/63] lr: 2.8645e-03 eta: 14:02:49 time: 1.2799 data_time: 0.0543 memory: 16131 loss: 1.9686 loss_prob: 1.1559 loss_thr: 0.6217 loss_db: 0.1910 2022/10/25 22:54:00 - mmengine - INFO - Epoch(train) [251][35/63] lr: 2.8645e-03 eta: 14:02:49 time: 1.0471 data_time: 0.0053 memory: 16131 loss: 2.0453 loss_prob: 1.2169 loss_thr: 0.6294 loss_db: 0.1991 2022/10/25 22:54:04 - mmengine - INFO - Epoch(train) [251][40/63] lr: 2.8645e-03 eta: 14:02:42 time: 0.8971 data_time: 0.0057 memory: 16131 loss: 2.0217 loss_prob: 1.2058 loss_thr: 0.6180 loss_db: 0.1979 2022/10/25 22:54:09 - mmengine - INFO - Epoch(train) [251][45/63] lr: 2.8645e-03 eta: 14:02:42 time: 0.9309 data_time: 0.0050 memory: 16131 loss: 1.9757 loss_prob: 1.1807 loss_thr: 0.5969 loss_db: 0.1980 2022/10/25 22:54:14 - mmengine - INFO - Epoch(train) [251][50/63] lr: 2.8645e-03 eta: 14:02:40 time: 1.0146 data_time: 0.0300 memory: 16131 loss: 2.0499 loss_prob: 1.2181 loss_thr: 0.6322 loss_db: 0.1996 2022/10/25 22:54:22 - mmengine - INFO - Epoch(train) [251][55/63] lr: 2.8645e-03 eta: 14:02:40 time: 1.2317 data_time: 0.0301 memory: 16131 loss: 1.9522 loss_prob: 1.1457 loss_thr: 0.6177 loss_db: 0.1888 2022/10/25 22:54:27 - mmengine - INFO - Epoch(train) [251][60/63] lr: 2.8645e-03 eta: 14:02:47 time: 1.2545 data_time: 0.0067 memory: 16131 loss: 1.9862 loss_prob: 1.1723 loss_thr: 0.6235 loss_db: 0.1904 2022/10/25 22:54:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:54:41 - mmengine - INFO - Epoch(train) [252][5/63] lr: 2.8618e-03 eta: 14:02:47 time: 1.5530 data_time: 0.2978 memory: 16131 loss: 1.9984 loss_prob: 1.1835 loss_thr: 0.6270 loss_db: 0.1879 2022/10/25 22:54:45 - mmengine - INFO - Epoch(train) [252][10/63] lr: 2.8618e-03 eta: 14:02:52 time: 1.5326 data_time: 0.2995 memory: 16131 loss: 2.0112 loss_prob: 1.2159 loss_thr: 0.6062 loss_db: 0.1892 2022/10/25 22:54:51 - mmengine - INFO - Epoch(train) [252][15/63] lr: 2.8618e-03 eta: 14:02:52 time: 1.0702 data_time: 0.0098 memory: 16131 loss: 1.9041 loss_prob: 1.1252 loss_thr: 0.6010 loss_db: 0.1779 2022/10/25 22:54:58 - mmengine - INFO - Epoch(train) [252][20/63] lr: 2.8618e-03 eta: 14:02:58 time: 1.2193 data_time: 0.0070 memory: 16131 loss: 1.9284 loss_prob: 1.1339 loss_thr: 0.6100 loss_db: 0.1845 2022/10/25 22:55:04 - mmengine - INFO - Epoch(train) [252][25/63] lr: 2.8618e-03 eta: 14:02:58 time: 1.2194 data_time: 0.0687 memory: 16131 loss: 1.9827 loss_prob: 1.1756 loss_thr: 0.6140 loss_db: 0.1931 2022/10/25 22:55:09 - mmengine - INFO - Epoch(train) [252][30/63] lr: 2.8618e-03 eta: 14:03:01 time: 1.1501 data_time: 0.0687 memory: 16131 loss: 1.9311 loss_prob: 1.1341 loss_thr: 0.6134 loss_db: 0.1837 2022/10/25 22:55:14 - mmengine - INFO - Epoch(train) [252][35/63] lr: 2.8618e-03 eta: 14:03:01 time: 1.0686 data_time: 0.0145 memory: 16131 loss: 1.9608 loss_prob: 1.1516 loss_thr: 0.6238 loss_db: 0.1854 2022/10/25 22:55:22 - mmengine - INFO - Epoch(train) [252][40/63] lr: 2.8618e-03 eta: 14:03:08 time: 1.2564 data_time: 0.0159 memory: 16131 loss: 2.0448 loss_prob: 1.2142 loss_thr: 0.6327 loss_db: 0.1979 2022/10/25 22:55:30 - mmengine - INFO - Epoch(train) [252][45/63] lr: 2.8618e-03 eta: 14:03:08 time: 1.5883 data_time: 0.0067 memory: 16131 loss: 2.3131 loss_prob: 1.4202 loss_thr: 0.6655 loss_db: 0.2274 2022/10/25 22:55:37 - mmengine - INFO - Epoch(train) [252][50/63] lr: 2.8618e-03 eta: 14:03:25 time: 1.5330 data_time: 0.0246 memory: 16131 loss: 2.1224 loss_prob: 1.2799 loss_thr: 0.6383 loss_db: 0.2042 2022/10/25 22:55:42 - mmengine - INFO - Epoch(train) [252][55/63] lr: 2.8618e-03 eta: 14:03:25 time: 1.2035 data_time: 0.0289 memory: 16131 loss: 1.8957 loss_prob: 1.1050 loss_thr: 0.6081 loss_db: 0.1826 2022/10/25 22:55:48 - mmengine - INFO - Epoch(train) [252][60/63] lr: 2.8618e-03 eta: 14:03:27 time: 1.1154 data_time: 0.0107 memory: 16131 loss: 2.0204 loss_prob: 1.2066 loss_thr: 0.6184 loss_db: 0.1954 2022/10/25 22:55:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:56:03 - mmengine - INFO - Epoch(train) [253][5/63] lr: 2.8591e-03 eta: 14:03:27 time: 1.7408 data_time: 0.2809 memory: 16131 loss: 1.9856 loss_prob: 1.1358 loss_thr: 0.6656 loss_db: 0.1842 2022/10/25 22:56:08 - mmengine - INFO - Epoch(train) [253][10/63] lr: 2.8591e-03 eta: 14:03:34 time: 1.5757 data_time: 0.2874 memory: 16131 loss: 1.8762 loss_prob: 1.0818 loss_thr: 0.6167 loss_db: 0.1777 2022/10/25 22:56:17 - mmengine - INFO - Epoch(train) [253][15/63] lr: 2.8591e-03 eta: 14:03:34 time: 1.4051 data_time: 0.0153 memory: 16131 loss: 1.9771 loss_prob: 1.1726 loss_thr: 0.6137 loss_db: 0.1908 2022/10/25 22:56:24 - mmengine - INFO - Epoch(train) [253][20/63] lr: 2.8591e-03 eta: 14:03:53 time: 1.5931 data_time: 0.0105 memory: 16131 loss: 1.9764 loss_prob: 1.1554 loss_thr: 0.6336 loss_db: 0.1874 2022/10/25 22:56:30 - mmengine - INFO - Epoch(train) [253][25/63] lr: 2.8591e-03 eta: 14:03:53 time: 1.3659 data_time: 0.0395 memory: 16131 loss: 1.8463 loss_prob: 1.0634 loss_thr: 0.6066 loss_db: 0.1764 2022/10/25 22:56:34 - mmengine - INFO - Epoch(train) [253][30/63] lr: 2.8591e-03 eta: 14:03:52 time: 1.0460 data_time: 0.0407 memory: 16131 loss: 1.8550 loss_prob: 1.0651 loss_thr: 0.6143 loss_db: 0.1756 2022/10/25 22:56:39 - mmengine - INFO - Epoch(train) [253][35/63] lr: 2.8591e-03 eta: 14:03:52 time: 0.8986 data_time: 0.0167 memory: 16131 loss: 2.0589 loss_prob: 1.2189 loss_thr: 0.6468 loss_db: 0.1932 2022/10/25 22:56:44 - mmengine - INFO - Epoch(train) [253][40/63] lr: 2.8591e-03 eta: 14:03:48 time: 0.9598 data_time: 0.0131 memory: 16131 loss: 2.2634 loss_prob: 1.3986 loss_thr: 0.6451 loss_db: 0.2197 2022/10/25 22:56:50 - mmengine - INFO - Epoch(train) [253][45/63] lr: 2.8591e-03 eta: 14:03:48 time: 1.0805 data_time: 0.0090 memory: 16131 loss: 2.1870 loss_prob: 1.3342 loss_thr: 0.6363 loss_db: 0.2166 2022/10/25 22:56:53 - mmengine - INFO - Epoch(train) [253][50/63] lr: 2.8591e-03 eta: 14:03:43 time: 0.9366 data_time: 0.0344 memory: 16131 loss: 2.0273 loss_prob: 1.2087 loss_thr: 0.6207 loss_db: 0.1979 2022/10/25 22:56:59 - mmengine - INFO - Epoch(train) [253][55/63] lr: 2.8591e-03 eta: 14:03:43 time: 0.8832 data_time: 0.0352 memory: 16131 loss: 2.1177 loss_prob: 1.2696 loss_thr: 0.6427 loss_db: 0.2054 2022/10/25 22:57:04 - mmengine - INFO - Epoch(train) [253][60/63] lr: 2.8591e-03 eta: 14:03:43 time: 1.0775 data_time: 0.0100 memory: 16131 loss: 2.0611 loss_prob: 1.2167 loss_thr: 0.6425 loss_db: 0.2019 2022/10/25 22:57:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:57:14 - mmengine - INFO - Epoch(train) [254][5/63] lr: 2.8564e-03 eta: 14:03:43 time: 1.0796 data_time: 0.2331 memory: 16131 loss: 2.0331 loss_prob: 1.2103 loss_thr: 0.6252 loss_db: 0.1976 2022/10/25 22:57:18 - mmengine - INFO - Epoch(train) [254][10/63] lr: 2.8564e-03 eta: 14:03:35 time: 1.1766 data_time: 0.2318 memory: 16131 loss: 2.0154 loss_prob: 1.2008 loss_thr: 0.6222 loss_db: 0.1925 2022/10/25 22:57:26 - mmengine - INFO - Epoch(train) [254][15/63] lr: 2.8564e-03 eta: 14:03:35 time: 1.2595 data_time: 0.0085 memory: 16131 loss: 1.9043 loss_prob: 1.1139 loss_thr: 0.6068 loss_db: 0.1835 2022/10/25 22:57:36 - mmengine - INFO - Epoch(train) [254][20/63] lr: 2.8564e-03 eta: 14:04:00 time: 1.7660 data_time: 0.0099 memory: 16131 loss: 1.7595 loss_prob: 1.0017 loss_thr: 0.5914 loss_db: 0.1664 2022/10/25 22:57:43 - mmengine - INFO - Epoch(train) [254][25/63] lr: 2.8564e-03 eta: 14:04:00 time: 1.6689 data_time: 0.0194 memory: 16131 loss: 1.7415 loss_prob: 0.9930 loss_thr: 0.5862 loss_db: 0.1624 2022/10/25 22:57:49 - mmengine - INFO - Epoch(train) [254][30/63] lr: 2.8564e-03 eta: 14:04:08 time: 1.2792 data_time: 0.0494 memory: 16131 loss: 1.7816 loss_prob: 1.0366 loss_thr: 0.5756 loss_db: 0.1694 2022/10/25 22:57:54 - mmengine - INFO - Epoch(train) [254][35/63] lr: 2.8564e-03 eta: 14:04:08 time: 1.1037 data_time: 0.0390 memory: 16131 loss: 1.7881 loss_prob: 1.0421 loss_thr: 0.5811 loss_db: 0.1649 2022/10/25 22:57:59 - mmengine - INFO - Epoch(train) [254][40/63] lr: 2.8564e-03 eta: 14:04:07 time: 1.0502 data_time: 0.0100 memory: 16131 loss: 1.8751 loss_prob: 1.0856 loss_thr: 0.6145 loss_db: 0.1751 2022/10/25 22:58:04 - mmengine - INFO - Epoch(train) [254][45/63] lr: 2.8564e-03 eta: 14:04:07 time: 1.0005 data_time: 0.0099 memory: 16131 loss: 2.0719 loss_prob: 1.2154 loss_thr: 0.6550 loss_db: 0.2015 2022/10/25 22:58:10 - mmengine - INFO - Epoch(train) [254][50/63] lr: 2.8564e-03 eta: 14:04:07 time: 1.0680 data_time: 0.0187 memory: 16131 loss: 2.0559 loss_prob: 1.2015 loss_thr: 0.6574 loss_db: 0.1969 2022/10/25 22:58:16 - mmengine - INFO - Epoch(train) [254][55/63] lr: 2.8564e-03 eta: 14:04:07 time: 1.1797 data_time: 0.0257 memory: 16131 loss: 2.1750 loss_prob: 1.3058 loss_thr: 0.6609 loss_db: 0.2082 2022/10/25 22:58:23 - mmengine - INFO - Epoch(train) [254][60/63] lr: 2.8564e-03 eta: 14:04:15 time: 1.3113 data_time: 0.0157 memory: 16131 loss: 2.1906 loss_prob: 1.3248 loss_thr: 0.6517 loss_db: 0.2141 2022/10/25 22:58:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:58:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:58:30 - mmengine - INFO - Epoch(train) [255][5/63] lr: 2.8537e-03 eta: 14:04:15 time: 1.1502 data_time: 0.2062 memory: 16131 loss: 1.9684 loss_prob: 1.1724 loss_thr: 0.6024 loss_db: 0.1936 2022/10/25 22:58:33 - mmengine - INFO - Epoch(train) [255][10/63] lr: 2.8537e-03 eta: 14:03:57 time: 0.8970 data_time: 0.2141 memory: 16131 loss: 2.0013 loss_prob: 1.2017 loss_thr: 0.6121 loss_db: 0.1876 2022/10/25 22:58:36 - mmengine - INFO - Epoch(train) [255][15/63] lr: 2.8537e-03 eta: 14:03:57 time: 0.5606 data_time: 0.0263 memory: 16131 loss: 2.1051 loss_prob: 1.2866 loss_thr: 0.6231 loss_db: 0.1954 2022/10/25 22:58:39 - mmengine - INFO - Epoch(train) [255][20/63] lr: 2.8537e-03 eta: 14:03:37 time: 0.5617 data_time: 0.0198 memory: 16131 loss: 2.1487 loss_prob: 1.3009 loss_thr: 0.6435 loss_db: 0.2043 2022/10/25 22:58:42 - mmengine - INFO - Epoch(train) [255][25/63] lr: 2.8537e-03 eta: 14:03:37 time: 0.5653 data_time: 0.0225 memory: 16131 loss: 2.0880 loss_prob: 1.2402 loss_thr: 0.6460 loss_db: 0.2019 2022/10/25 22:58:49 - mmengine - INFO - Epoch(train) [255][30/63] lr: 2.8537e-03 eta: 14:03:36 time: 1.0380 data_time: 0.0285 memory: 16131 loss: 2.0016 loss_prob: 1.1881 loss_thr: 0.6138 loss_db: 0.1997 2022/10/25 22:58:58 - mmengine - INFO - Epoch(train) [255][35/63] lr: 2.8537e-03 eta: 14:03:36 time: 1.5811 data_time: 0.0216 memory: 16131 loss: 2.0256 loss_prob: 1.2096 loss_thr: 0.6172 loss_db: 0.1987 2022/10/25 22:59:03 - mmengine - INFO - Epoch(train) [255][40/63] lr: 2.8537e-03 eta: 14:03:47 time: 1.3669 data_time: 0.0176 memory: 16131 loss: 2.0753 loss_prob: 1.2376 loss_thr: 0.6332 loss_db: 0.2046 2022/10/25 22:59:11 - mmengine - INFO - Epoch(train) [255][45/63] lr: 2.8537e-03 eta: 14:03:47 time: 1.2991 data_time: 0.0144 memory: 16131 loss: 2.0655 loss_prob: 1.2124 loss_thr: 0.6527 loss_db: 0.2003 2022/10/25 22:59:16 - mmengine - INFO - Epoch(train) [255][50/63] lr: 2.8537e-03 eta: 14:03:55 time: 1.3061 data_time: 0.0199 memory: 16131 loss: 2.1445 loss_prob: 1.2604 loss_thr: 0.6805 loss_db: 0.2037 2022/10/25 22:59:22 - mmengine - INFO - Epoch(train) [255][55/63] lr: 2.8537e-03 eta: 14:03:55 time: 1.1228 data_time: 0.0213 memory: 16131 loss: 2.0800 loss_prob: 1.2387 loss_thr: 0.6390 loss_db: 0.2023 2022/10/25 22:59:30 - mmengine - INFO - Epoch(train) [255][60/63] lr: 2.8537e-03 eta: 14:04:06 time: 1.3687 data_time: 0.0199 memory: 16131 loss: 1.8806 loss_prob: 1.1178 loss_thr: 0.5820 loss_db: 0.1809 2022/10/25 22:59:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 22:59:40 - mmengine - INFO - Epoch(train) [256][5/63] lr: 2.8509e-03 eta: 14:04:06 time: 1.4204 data_time: 0.2379 memory: 16131 loss: 1.9289 loss_prob: 1.1410 loss_thr: 0.6027 loss_db: 0.1853 2022/10/25 22:59:48 - mmengine - INFO - Epoch(train) [256][10/63] lr: 2.8509e-03 eta: 14:04:17 time: 1.7072 data_time: 0.2456 memory: 16131 loss: 1.9225 loss_prob: 1.1262 loss_thr: 0.6149 loss_db: 0.1813 2022/10/25 22:59:54 - mmengine - INFO - Epoch(train) [256][15/63] lr: 2.8509e-03 eta: 14:04:17 time: 1.3912 data_time: 0.0240 memory: 16131 loss: 1.9222 loss_prob: 1.1340 loss_thr: 0.6047 loss_db: 0.1835 2022/10/25 22:59:58 - mmengine - INFO - Epoch(train) [256][20/63] lr: 2.8509e-03 eta: 14:04:12 time: 0.9441 data_time: 0.0142 memory: 16131 loss: 1.9675 loss_prob: 1.1738 loss_thr: 0.6021 loss_db: 0.1916 2022/10/25 23:00:04 - mmengine - INFO - Epoch(train) [256][25/63] lr: 2.8509e-03 eta: 14:04:12 time: 1.0801 data_time: 0.0264 memory: 16131 loss: 2.0567 loss_prob: 1.2316 loss_thr: 0.6275 loss_db: 0.1976 2022/10/25 23:00:11 - mmengine - INFO - Epoch(train) [256][30/63] lr: 2.8509e-03 eta: 14:04:22 time: 1.3426 data_time: 0.0251 memory: 16131 loss: 2.0478 loss_prob: 1.2130 loss_thr: 0.6366 loss_db: 0.1982 2022/10/25 23:00:16 - mmengine - INFO - Epoch(train) [256][35/63] lr: 2.8509e-03 eta: 14:04:22 time: 1.2086 data_time: 0.0217 memory: 16131 loss: 2.0093 loss_prob: 1.1836 loss_thr: 0.6312 loss_db: 0.1945 2022/10/25 23:00:25 - mmengine - INFO - Epoch(train) [256][40/63] lr: 2.8509e-03 eta: 14:04:33 time: 1.3961 data_time: 0.0258 memory: 16131 loss: 1.9943 loss_prob: 1.1862 loss_thr: 0.6149 loss_db: 0.1932 2022/10/25 23:00:32 - mmengine - INFO - Epoch(train) [256][45/63] lr: 2.8509e-03 eta: 14:04:33 time: 1.5450 data_time: 0.0112 memory: 16131 loss: 1.8825 loss_prob: 1.1014 loss_thr: 0.5956 loss_db: 0.1855 2022/10/25 23:00:39 - mmengine - INFO - Epoch(train) [256][50/63] lr: 2.8509e-03 eta: 14:04:45 time: 1.3973 data_time: 0.0263 memory: 16131 loss: 1.9788 loss_prob: 1.1949 loss_thr: 0.5897 loss_db: 0.1942 2022/10/25 23:00:45 - mmengine - INFO - Epoch(train) [256][55/63] lr: 2.8509e-03 eta: 14:04:45 time: 1.3136 data_time: 0.0291 memory: 16131 loss: 2.1389 loss_prob: 1.3039 loss_thr: 0.6274 loss_db: 0.2076 2022/10/25 23:00:52 - mmengine - INFO - Epoch(train) [256][60/63] lr: 2.8509e-03 eta: 14:04:50 time: 1.2365 data_time: 0.0110 memory: 16131 loss: 2.0582 loss_prob: 1.2190 loss_thr: 0.6369 loss_db: 0.2023 2022/10/25 23:00:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:01:04 - mmengine - INFO - Epoch(train) [257][5/63] lr: 2.8482e-03 eta: 14:04:50 time: 1.3843 data_time: 0.2892 memory: 16131 loss: 1.9127 loss_prob: 1.1186 loss_thr: 0.6083 loss_db: 0.1858 2022/10/25 23:01:09 - mmengine - INFO - Epoch(train) [257][10/63] lr: 2.8482e-03 eta: 14:04:52 time: 1.4546 data_time: 0.2821 memory: 16131 loss: 1.8649 loss_prob: 1.0881 loss_thr: 0.5987 loss_db: 0.1781 2022/10/25 23:01:18 - mmengine - INFO - Epoch(train) [257][15/63] lr: 2.8482e-03 eta: 14:04:52 time: 1.4016 data_time: 0.0090 memory: 16131 loss: 1.8388 loss_prob: 1.0579 loss_thr: 0.6064 loss_db: 0.1745 2022/10/25 23:01:25 - mmengine - INFO - Epoch(train) [257][20/63] lr: 2.8482e-03 eta: 14:05:09 time: 1.5549 data_time: 0.0088 memory: 16131 loss: 1.8661 loss_prob: 1.0762 loss_thr: 0.6112 loss_db: 0.1786 2022/10/25 23:01:29 - mmengine - INFO - Epoch(train) [257][25/63] lr: 2.8482e-03 eta: 14:05:09 time: 1.1694 data_time: 0.0312 memory: 16131 loss: 1.9877 loss_prob: 1.1814 loss_thr: 0.6132 loss_db: 0.1932 2022/10/25 23:01:37 - mmengine - INFO - Epoch(train) [257][30/63] lr: 2.8482e-03 eta: 14:05:15 time: 1.2387 data_time: 0.0445 memory: 16131 loss: 1.9448 loss_prob: 1.1494 loss_thr: 0.6111 loss_db: 0.1843 2022/10/25 23:01:43 - mmengine - INFO - Epoch(train) [257][35/63] lr: 2.8482e-03 eta: 14:05:15 time: 1.3884 data_time: 0.0215 memory: 16131 loss: 1.8870 loss_prob: 1.1053 loss_thr: 0.6049 loss_db: 0.1769 2022/10/25 23:01:50 - mmengine - INFO - Epoch(train) [257][40/63] lr: 2.8482e-03 eta: 14:05:20 time: 1.2206 data_time: 0.0098 memory: 16131 loss: 1.9037 loss_prob: 1.1298 loss_thr: 0.5903 loss_db: 0.1836 2022/10/25 23:01:54 - mmengine - INFO - Epoch(train) [257][45/63] lr: 2.8482e-03 eta: 14:05:20 time: 1.0816 data_time: 0.0075 memory: 16131 loss: 1.9196 loss_prob: 1.1197 loss_thr: 0.6209 loss_db: 0.1789 2022/10/25 23:01:58 - mmengine - INFO - Epoch(train) [257][50/63] lr: 2.8482e-03 eta: 14:05:10 time: 0.8161 data_time: 0.0252 memory: 16131 loss: 1.9898 loss_prob: 1.1608 loss_thr: 0.6418 loss_db: 0.1871 2022/10/25 23:02:03 - mmengine - INFO - Epoch(train) [257][55/63] lr: 2.8482e-03 eta: 14:05:10 time: 0.8876 data_time: 0.0258 memory: 16131 loss: 2.1263 loss_prob: 1.2873 loss_thr: 0.6331 loss_db: 0.2059 2022/10/25 23:02:08 - mmengine - INFO - Epoch(train) [257][60/63] lr: 2.8482e-03 eta: 14:05:06 time: 0.9794 data_time: 0.0053 memory: 16131 loss: 2.0868 loss_prob: 1.2548 loss_thr: 0.6333 loss_db: 0.1986 2022/10/25 23:02:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:02:20 - mmengine - INFO - Epoch(train) [258][5/63] lr: 2.8455e-03 eta: 14:05:06 time: 1.4407 data_time: 0.2156 memory: 16131 loss: 1.9349 loss_prob: 1.1167 loss_thr: 0.6342 loss_db: 0.1840 2022/10/25 23:02:27 - mmengine - INFO - Epoch(train) [258][10/63] lr: 2.8455e-03 eta: 14:05:17 time: 1.6974 data_time: 0.2165 memory: 16131 loss: 1.9736 loss_prob: 1.1686 loss_thr: 0.6133 loss_db: 0.1917 2022/10/25 23:02:33 - mmengine - INFO - Epoch(train) [258][15/63] lr: 2.8455e-03 eta: 14:05:17 time: 1.2821 data_time: 0.0067 memory: 16131 loss: 1.9382 loss_prob: 1.1389 loss_thr: 0.6152 loss_db: 0.1841 2022/10/25 23:02:40 - mmengine - INFO - Epoch(train) [258][20/63] lr: 2.8455e-03 eta: 14:05:24 time: 1.2832 data_time: 0.0104 memory: 16131 loss: 1.9812 loss_prob: 1.1478 loss_thr: 0.6476 loss_db: 0.1857 2022/10/25 23:02:49 - mmengine - INFO - Epoch(train) [258][25/63] lr: 2.8455e-03 eta: 14:05:24 time: 1.6536 data_time: 0.0289 memory: 16131 loss: 1.9753 loss_prob: 1.1637 loss_thr: 0.6201 loss_db: 0.1914 2022/10/25 23:02:54 - mmengine - INFO - Epoch(train) [258][30/63] lr: 2.8455e-03 eta: 14:05:37 time: 1.4412 data_time: 0.0364 memory: 16131 loss: 1.9927 loss_prob: 1.1851 loss_thr: 0.6156 loss_db: 0.1919 2022/10/25 23:03:00 - mmengine - INFO - Epoch(train) [258][35/63] lr: 2.8455e-03 eta: 14:05:37 time: 1.1230 data_time: 0.0189 memory: 16131 loss: 1.9645 loss_prob: 1.1622 loss_thr: 0.6158 loss_db: 0.1865 2022/10/25 23:03:06 - mmengine - INFO - Epoch(train) [258][40/63] lr: 2.8455e-03 eta: 14:05:41 time: 1.2071 data_time: 0.0086 memory: 16131 loss: 1.9522 loss_prob: 1.1461 loss_thr: 0.6178 loss_db: 0.1883 2022/10/25 23:03:12 - mmengine - INFO - Epoch(train) [258][45/63] lr: 2.8455e-03 eta: 14:05:41 time: 1.1948 data_time: 0.0104 memory: 16131 loss: 2.0171 loss_prob: 1.1827 loss_thr: 0.6368 loss_db: 0.1977 2022/10/25 23:03:18 - mmengine - INFO - Epoch(train) [258][50/63] lr: 2.8455e-03 eta: 14:05:43 time: 1.1285 data_time: 0.0258 memory: 16131 loss: 1.9771 loss_prob: 1.1627 loss_thr: 0.6217 loss_db: 0.1928 2022/10/25 23:03:24 - mmengine - INFO - Epoch(train) [258][55/63] lr: 2.8455e-03 eta: 14:05:43 time: 1.1274 data_time: 0.0415 memory: 16131 loss: 2.2465 loss_prob: 1.3719 loss_thr: 0.6479 loss_db: 0.2267 2022/10/25 23:03:28 - mmengine - INFO - Epoch(train) [258][60/63] lr: 2.8455e-03 eta: 14:05:43 time: 1.0903 data_time: 0.0241 memory: 16131 loss: 2.4179 loss_prob: 1.5102 loss_thr: 0.6650 loss_db: 0.2427 2022/10/25 23:03:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:03:40 - mmengine - INFO - Epoch(train) [259][5/63] lr: 2.8428e-03 eta: 14:05:43 time: 1.2283 data_time: 0.1969 memory: 16131 loss: 2.7056 loss_prob: 1.6927 loss_thr: 0.7359 loss_db: 0.2770 2022/10/25 23:03:45 - mmengine - INFO - Epoch(train) [259][10/63] lr: 2.8428e-03 eta: 14:05:43 time: 1.4330 data_time: 0.1985 memory: 16131 loss: 2.8651 loss_prob: 1.8401 loss_thr: 0.7253 loss_db: 0.2996 2022/10/25 23:03:51 - mmengine - INFO - Epoch(train) [259][15/63] lr: 2.8428e-03 eta: 14:05:43 time: 1.1837 data_time: 0.0161 memory: 16131 loss: 2.9583 loss_prob: 1.9079 loss_thr: 0.7361 loss_db: 0.3143 2022/10/25 23:03:56 - mmengine - INFO - Epoch(train) [259][20/63] lr: 2.8428e-03 eta: 14:05:42 time: 1.0654 data_time: 0.0139 memory: 16131 loss: 2.7126 loss_prob: 1.7369 loss_thr: 0.6950 loss_db: 0.2807 2022/10/25 23:03:59 - mmengine - INFO - Epoch(train) [259][25/63] lr: 2.8428e-03 eta: 14:05:42 time: 0.7444 data_time: 0.0078 memory: 16131 loss: 2.4993 loss_prob: 1.5512 loss_thr: 0.7019 loss_db: 0.2462 2022/10/25 23:04:03 - mmengine - INFO - Epoch(train) [259][30/63] lr: 2.8428e-03 eta: 14:05:28 time: 0.6853 data_time: 0.0345 memory: 16131 loss: 2.4220 loss_prob: 1.4592 loss_thr: 0.7245 loss_db: 0.2383 2022/10/25 23:04:07 - mmengine - INFO - Epoch(train) [259][35/63] lr: 2.8428e-03 eta: 14:05:28 time: 0.8189 data_time: 0.0361 memory: 16131 loss: 2.3191 loss_prob: 1.4292 loss_thr: 0.6558 loss_db: 0.2341 2022/10/25 23:04:14 - mmengine - INFO - Epoch(train) [259][40/63] lr: 2.8428e-03 eta: 14:05:29 time: 1.1380 data_time: 0.0107 memory: 16131 loss: 2.4063 loss_prob: 1.5010 loss_thr: 0.6683 loss_db: 0.2369 2022/10/25 23:04:19 - mmengine - INFO - Epoch(train) [259][45/63] lr: 2.8428e-03 eta: 14:05:29 time: 1.2218 data_time: 0.0074 memory: 16131 loss: 2.4221 loss_prob: 1.5049 loss_thr: 0.6806 loss_db: 0.2366 2022/10/25 23:04:22 - mmengine - INFO - Epoch(train) [259][50/63] lr: 2.8428e-03 eta: 14:05:18 time: 0.7854 data_time: 0.0174 memory: 16131 loss: 2.3427 loss_prob: 1.4295 loss_thr: 0.6795 loss_db: 0.2336 2022/10/25 23:04:26 - mmengine - INFO - Epoch(train) [259][55/63] lr: 2.8428e-03 eta: 14:05:18 time: 0.7127 data_time: 0.0274 memory: 16131 loss: 2.2846 loss_prob: 1.3819 loss_thr: 0.6746 loss_db: 0.2281 2022/10/25 23:04:29 - mmengine - INFO - Epoch(train) [259][60/63] lr: 2.8428e-03 eta: 14:05:04 time: 0.6841 data_time: 0.0182 memory: 16131 loss: 2.2951 loss_prob: 1.4013 loss_thr: 0.6593 loss_db: 0.2346 2022/10/25 23:04:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:04:39 - mmengine - INFO - Epoch(train) [260][5/63] lr: 2.8401e-03 eta: 14:05:04 time: 1.0645 data_time: 0.2689 memory: 16131 loss: 2.2792 loss_prob: 1.3727 loss_thr: 0.6726 loss_db: 0.2339 2022/10/25 23:04:41 - mmengine - INFO - Epoch(train) [260][10/63] lr: 2.8401e-03 eta: 14:04:52 time: 1.0935 data_time: 0.2677 memory: 16131 loss: 2.2013 loss_prob: 1.3177 loss_thr: 0.6625 loss_db: 0.2211 2022/10/25 23:04:44 - mmengine - INFO - Epoch(train) [260][15/63] lr: 2.8401e-03 eta: 14:04:52 time: 0.5292 data_time: 0.0098 memory: 16131 loss: 2.1898 loss_prob: 1.3124 loss_thr: 0.6628 loss_db: 0.2146 2022/10/25 23:04:47 - mmengine - INFO - Epoch(train) [260][20/63] lr: 2.8401e-03 eta: 14:04:32 time: 0.5432 data_time: 0.0114 memory: 16131 loss: 2.3656 loss_prob: 1.4476 loss_thr: 0.6763 loss_db: 0.2418 2022/10/25 23:04:51 - mmengine - INFO - Epoch(train) [260][25/63] lr: 2.8401e-03 eta: 14:04:32 time: 0.6574 data_time: 0.0361 memory: 16131 loss: 2.3356 loss_prob: 1.4233 loss_thr: 0.6718 loss_db: 0.2404 2022/10/25 23:04:56 - mmengine - INFO - Epoch(train) [260][30/63] lr: 2.8401e-03 eta: 14:04:25 time: 0.9129 data_time: 0.0365 memory: 16131 loss: 2.2491 loss_prob: 1.3729 loss_thr: 0.6458 loss_db: 0.2304 2022/10/25 23:05:01 - mmengine - INFO - Epoch(train) [260][35/63] lr: 2.8401e-03 eta: 14:04:25 time: 1.0563 data_time: 0.0094 memory: 16131 loss: 2.1629 loss_prob: 1.3157 loss_thr: 0.6319 loss_db: 0.2153 2022/10/25 23:05:07 - mmengine - INFO - Epoch(train) [260][40/63] lr: 2.8401e-03 eta: 14:04:27 time: 1.1441 data_time: 0.0093 memory: 16131 loss: 2.1710 loss_prob: 1.3093 loss_thr: 0.6517 loss_db: 0.2100 2022/10/25 23:05:15 - mmengine - INFO - Epoch(train) [260][45/63] lr: 2.8401e-03 eta: 14:04:27 time: 1.3785 data_time: 0.0102 memory: 16131 loss: 2.3735 loss_prob: 1.4691 loss_thr: 0.6605 loss_db: 0.2439 2022/10/25 23:05:21 - mmengine - INFO - Epoch(train) [260][50/63] lr: 2.8401e-03 eta: 14:04:36 time: 1.3329 data_time: 0.0288 memory: 16131 loss: 2.3315 loss_prob: 1.4419 loss_thr: 0.6532 loss_db: 0.2365 2022/10/25 23:05:28 - mmengine - INFO - Epoch(train) [260][55/63] lr: 2.8401e-03 eta: 14:04:36 time: 1.3338 data_time: 0.0285 memory: 16131 loss: 2.3709 loss_prob: 1.4638 loss_thr: 0.6620 loss_db: 0.2451 2022/10/25 23:05:34 - mmengine - INFO - Epoch(train) [260][60/63] lr: 2.8401e-03 eta: 14:04:45 time: 1.3460 data_time: 0.0097 memory: 16131 loss: 2.4867 loss_prob: 1.5631 loss_thr: 0.6649 loss_db: 0.2587 2022/10/25 23:05:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:05:39 - mmengine - INFO - Saving checkpoint at 260 epochs 2022/10/25 23:05:46 - mmengine - INFO - Epoch(val) [260][5/32] eta: 14:04:45 time: 0.5613 data_time: 0.0655 memory: 16131 2022/10/25 23:05:49 - mmengine - INFO - Epoch(val) [260][10/32] eta: 0:00:13 time: 0.6312 data_time: 0.0995 memory: 15724 2022/10/25 23:05:52 - mmengine - INFO - Epoch(val) [260][15/32] eta: 0:00:13 time: 0.5993 data_time: 0.0524 memory: 15724 2022/10/25 23:05:55 - mmengine - INFO - Epoch(val) [260][20/32] eta: 0:00:07 time: 0.5859 data_time: 0.0471 memory: 15724 2022/10/25 23:05:58 - mmengine - INFO - Epoch(val) [260][25/32] eta: 0:00:07 time: 0.6010 data_time: 0.0661 memory: 15724 2022/10/25 23:06:00 - mmengine - INFO - Epoch(val) [260][30/32] eta: 0:00:01 time: 0.5733 data_time: 0.0402 memory: 15724 2022/10/25 23:06:01 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7838, precision: 0.6286, hmean: 0.6977 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7838, precision: 0.7223, hmean: 0.7518 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7776, precision: 0.7802, hmean: 0.7789 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7535, precision: 0.8356, hmean: 0.7924 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6649, precision: 0.8991, hmean: 0.7645 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2383, precision: 0.9763, hmean: 0.3831 2022/10/25 23:06:01 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 23:06:01 - mmengine - INFO - Epoch(val) [260][32/32] icdar/precision: 0.8356 icdar/recall: 0.7535 icdar/hmean: 0.7924 2022/10/25 23:06:09 - mmengine - INFO - Epoch(train) [261][5/63] lr: 2.8373e-03 eta: 0:00:01 time: 1.5541 data_time: 0.2648 memory: 16131 loss: 2.1611 loss_prob: 1.3253 loss_thr: 0.6235 loss_db: 0.2123 2022/10/25 23:06:18 - mmengine - INFO - Epoch(train) [261][10/63] lr: 2.8373e-03 eta: 14:04:54 time: 1.6703 data_time: 0.2682 memory: 16131 loss: 2.1265 loss_prob: 1.2871 loss_thr: 0.6296 loss_db: 0.2098 2022/10/25 23:06:26 - mmengine - INFO - Epoch(train) [261][15/63] lr: 2.8373e-03 eta: 14:04:54 time: 1.6512 data_time: 0.0127 memory: 16131 loss: 2.2117 loss_prob: 1.3363 loss_thr: 0.6563 loss_db: 0.2191 2022/10/25 23:06:32 - mmengine - INFO - Epoch(train) [261][20/63] lr: 2.8373e-03 eta: 14:05:05 time: 1.3994 data_time: 0.0064 memory: 16131 loss: 2.1603 loss_prob: 1.2911 loss_thr: 0.6602 loss_db: 0.2090 2022/10/25 23:06:38 - mmengine - INFO - Epoch(train) [261][25/63] lr: 2.8373e-03 eta: 14:05:05 time: 1.2081 data_time: 0.0094 memory: 16131 loss: 2.1538 loss_prob: 1.2847 loss_thr: 0.6607 loss_db: 0.2084 2022/10/25 23:06:44 - mmengine - INFO - Epoch(train) [261][30/63] lr: 2.8373e-03 eta: 14:05:09 time: 1.1863 data_time: 0.0533 memory: 16131 loss: 2.1638 loss_prob: 1.2868 loss_thr: 0.6636 loss_db: 0.2135 2022/10/25 23:06:51 - mmengine - INFO - Epoch(train) [261][35/63] lr: 2.8373e-03 eta: 14:05:09 time: 1.3751 data_time: 0.0500 memory: 16131 loss: 2.1027 loss_prob: 1.2330 loss_thr: 0.6675 loss_db: 0.2022 2022/10/25 23:06:58 - mmengine - INFO - Epoch(train) [261][40/63] lr: 2.8373e-03 eta: 14:05:21 time: 1.4384 data_time: 0.0071 memory: 16131 loss: 2.1230 loss_prob: 1.2582 loss_thr: 0.6608 loss_db: 0.2040 2022/10/25 23:07:04 - mmengine - INFO - Epoch(train) [261][45/63] lr: 2.8373e-03 eta: 14:05:21 time: 1.2426 data_time: 0.0084 memory: 16131 loss: 2.1930 loss_prob: 1.3239 loss_thr: 0.6525 loss_db: 0.2166 2022/10/25 23:07:09 - mmengine - INFO - Epoch(train) [261][50/63] lr: 2.8373e-03 eta: 14:05:20 time: 1.0687 data_time: 0.0337 memory: 16131 loss: 2.1759 loss_prob: 1.3158 loss_thr: 0.6423 loss_db: 0.2178 2022/10/25 23:07:15 - mmengine - INFO - Epoch(train) [261][55/63] lr: 2.8373e-03 eta: 14:05:20 time: 1.1485 data_time: 0.0407 memory: 16131 loss: 2.0682 loss_prob: 1.2325 loss_thr: 0.6348 loss_db: 0.2009 2022/10/25 23:07:19 - mmengine - INFO - Epoch(train) [261][60/63] lr: 2.8373e-03 eta: 14:05:17 time: 0.9973 data_time: 0.0190 memory: 16131 loss: 1.9380 loss_prob: 1.1375 loss_thr: 0.6186 loss_db: 0.1819 2022/10/25 23:07:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:07:27 - mmengine - INFO - Epoch(train) [262][5/63] lr: 2.8346e-03 eta: 14:05:17 time: 0.9112 data_time: 0.1953 memory: 16131 loss: 1.9854 loss_prob: 1.1841 loss_thr: 0.6135 loss_db: 0.1878 2022/10/25 23:07:30 - mmengine - INFO - Epoch(train) [262][10/63] lr: 2.8346e-03 eta: 14:05:01 time: 0.9968 data_time: 0.1950 memory: 16131 loss: 2.1665 loss_prob: 1.3273 loss_thr: 0.6281 loss_db: 0.2111 2022/10/25 23:07:38 - mmengine - INFO - Epoch(train) [262][15/63] lr: 2.8346e-03 eta: 14:05:01 time: 1.1179 data_time: 0.0092 memory: 16131 loss: 2.3852 loss_prob: 1.4982 loss_thr: 0.6503 loss_db: 0.2367 2022/10/25 23:07:43 - mmengine - INFO - Epoch(train) [262][20/63] lr: 2.8346e-03 eta: 14:05:08 time: 1.2983 data_time: 0.0099 memory: 16131 loss: 2.5001 loss_prob: 1.5736 loss_thr: 0.6835 loss_db: 0.2431 2022/10/25 23:07:52 - mmengine - INFO - Epoch(train) [262][25/63] lr: 2.8346e-03 eta: 14:05:08 time: 1.4154 data_time: 0.0405 memory: 16131 loss: 2.3528 loss_prob: 1.4685 loss_thr: 0.6450 loss_db: 0.2394 2022/10/25 23:08:00 - mmengine - INFO - Epoch(train) [262][30/63] lr: 2.8346e-03 eta: 14:05:29 time: 1.6786 data_time: 0.0417 memory: 16131 loss: 2.3547 loss_prob: 1.4715 loss_thr: 0.6399 loss_db: 0.2434 2022/10/25 23:08:07 - mmengine - INFO - Epoch(train) [262][35/63] lr: 2.8346e-03 eta: 14:05:29 time: 1.5087 data_time: 0.0108 memory: 16131 loss: 2.3186 loss_prob: 1.4333 loss_thr: 0.6576 loss_db: 0.2276 2022/10/25 23:08:14 - mmengine - INFO - Epoch(train) [262][40/63] lr: 2.8346e-03 eta: 14:05:41 time: 1.4148 data_time: 0.0116 memory: 16131 loss: 2.0343 loss_prob: 1.2074 loss_thr: 0.6314 loss_db: 0.1956 2022/10/25 23:08:22 - mmengine - INFO - Epoch(train) [262][45/63] lr: 2.8346e-03 eta: 14:05:41 time: 1.5030 data_time: 0.0103 memory: 16131 loss: 2.0775 loss_prob: 1.2446 loss_thr: 0.6312 loss_db: 0.2017 2022/10/25 23:08:28 - mmengine - INFO - Epoch(train) [262][50/63] lr: 2.8346e-03 eta: 14:05:50 time: 1.3623 data_time: 0.0262 memory: 16131 loss: 1.9698 loss_prob: 1.1753 loss_thr: 0.6053 loss_db: 0.1892 2022/10/25 23:08:32 - mmengine - INFO - Epoch(train) [262][55/63] lr: 2.8346e-03 eta: 14:05:50 time: 1.0178 data_time: 0.0235 memory: 16131 loss: 1.8412 loss_prob: 1.0897 loss_thr: 0.5739 loss_db: 0.1776 2022/10/25 23:08:37 - mmengine - INFO - Epoch(train) [262][60/63] lr: 2.8346e-03 eta: 14:05:45 time: 0.9629 data_time: 0.0065 memory: 16131 loss: 1.8828 loss_prob: 1.1014 loss_thr: 0.6003 loss_db: 0.1812 2022/10/25 23:08:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:08:50 - mmengine - INFO - Epoch(train) [263][5/63] lr: 2.8319e-03 eta: 14:05:45 time: 1.5364 data_time: 0.2268 memory: 16131 loss: 1.9802 loss_prob: 1.1666 loss_thr: 0.6277 loss_db: 0.1859 2022/10/25 23:08:56 - mmengine - INFO - Epoch(train) [263][10/63] lr: 2.8319e-03 eta: 14:05:51 time: 1.5982 data_time: 0.2257 memory: 16131 loss: 2.0470 loss_prob: 1.2206 loss_thr: 0.6319 loss_db: 0.1945 2022/10/25 23:09:06 - mmengine - INFO - Epoch(train) [263][15/63] lr: 2.8319e-03 eta: 14:05:51 time: 1.5971 data_time: 0.0102 memory: 16131 loss: 2.1374 loss_prob: 1.2704 loss_thr: 0.6574 loss_db: 0.2095 2022/10/25 23:09:09 - mmengine - INFO - Epoch(train) [263][20/63] lr: 2.8319e-03 eta: 14:05:59 time: 1.3164 data_time: 0.0099 memory: 16131 loss: 2.2330 loss_prob: 1.3621 loss_thr: 0.6478 loss_db: 0.2231 2022/10/25 23:09:13 - mmengine - INFO - Epoch(train) [263][25/63] lr: 2.8319e-03 eta: 14:05:59 time: 0.7252 data_time: 0.0191 memory: 16131 loss: 2.0416 loss_prob: 1.2241 loss_thr: 0.6181 loss_db: 0.1994 2022/10/25 23:09:17 - mmengine - INFO - Epoch(train) [263][30/63] lr: 2.8319e-03 eta: 14:05:47 time: 0.7661 data_time: 0.0396 memory: 16131 loss: 1.9450 loss_prob: 1.1345 loss_thr: 0.6218 loss_db: 0.1887 2022/10/25 23:09:21 - mmengine - INFO - Epoch(train) [263][35/63] lr: 2.8319e-03 eta: 14:05:47 time: 0.8175 data_time: 0.0274 memory: 16131 loss: 2.1275 loss_prob: 1.2582 loss_thr: 0.6585 loss_db: 0.2109 2022/10/25 23:09:25 - mmengine - INFO - Epoch(train) [263][40/63] lr: 2.8319e-03 eta: 14:05:36 time: 0.7908 data_time: 0.0081 memory: 16131 loss: 2.1561 loss_prob: 1.2738 loss_thr: 0.6697 loss_db: 0.2126 2022/10/25 23:09:29 - mmengine - INFO - Epoch(train) [263][45/63] lr: 2.8319e-03 eta: 14:05:36 time: 0.7823 data_time: 0.0063 memory: 16131 loss: 2.0658 loss_prob: 1.2306 loss_thr: 0.6359 loss_db: 0.1993 2022/10/25 23:09:32 - mmengine - INFO - Epoch(train) [263][50/63] lr: 2.8319e-03 eta: 14:05:22 time: 0.6989 data_time: 0.0164 memory: 16131 loss: 1.9840 loss_prob: 1.1795 loss_thr: 0.6125 loss_db: 0.1920 2022/10/25 23:09:38 - mmengine - INFO - Epoch(train) [263][55/63] lr: 2.8319e-03 eta: 14:05:22 time: 0.9377 data_time: 0.0226 memory: 16131 loss: 2.2013 loss_prob: 1.3269 loss_thr: 0.6575 loss_db: 0.2168 2022/10/25 23:09:43 - mmengine - INFO - Epoch(train) [263][60/63] lr: 2.8319e-03 eta: 14:05:24 time: 1.1559 data_time: 0.0144 memory: 16131 loss: 2.5734 loss_prob: 1.6119 loss_thr: 0.6982 loss_db: 0.2634 2022/10/25 23:09:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:09:56 - mmengine - INFO - Epoch(train) [264][5/63] lr: 2.8292e-03 eta: 14:05:24 time: 1.5063 data_time: 0.2198 memory: 16131 loss: 2.6994 loss_prob: 1.7239 loss_thr: 0.6966 loss_db: 0.2789 2022/10/25 23:10:03 - mmengine - INFO - Epoch(train) [264][10/63] lr: 2.8292e-03 eta: 14:05:28 time: 1.5550 data_time: 0.2213 memory: 16131 loss: 2.5677 loss_prob: 1.6251 loss_thr: 0.6790 loss_db: 0.2636 2022/10/25 23:10:07 - mmengine - INFO - Epoch(train) [264][15/63] lr: 2.8292e-03 eta: 14:05:28 time: 1.0844 data_time: 0.0134 memory: 16131 loss: 2.4982 loss_prob: 1.5846 loss_thr: 0.6584 loss_db: 0.2551 2022/10/25 23:10:13 - mmengine - INFO - Epoch(train) [264][20/63] lr: 2.8292e-03 eta: 14:05:25 time: 1.0200 data_time: 0.0082 memory: 16131 loss: 2.6498 loss_prob: 1.6844 loss_thr: 0.6971 loss_db: 0.2683 2022/10/25 23:10:19 - mmengine - INFO - Epoch(train) [264][25/63] lr: 2.8292e-03 eta: 14:05:25 time: 1.2313 data_time: 0.0118 memory: 16131 loss: 2.5253 loss_prob: 1.5779 loss_thr: 0.6941 loss_db: 0.2534 2022/10/25 23:10:27 - mmengine - INFO - Epoch(train) [264][30/63] lr: 2.8292e-03 eta: 14:05:36 time: 1.4006 data_time: 0.0417 memory: 16131 loss: 2.2432 loss_prob: 1.3687 loss_thr: 0.6569 loss_db: 0.2177 2022/10/25 23:10:33 - mmengine - INFO - Epoch(train) [264][35/63] lr: 2.8292e-03 eta: 14:05:36 time: 1.3193 data_time: 0.0387 memory: 16131 loss: 2.1979 loss_prob: 1.3542 loss_thr: 0.6300 loss_db: 0.2137 2022/10/25 23:10:38 - mmengine - INFO - Epoch(train) [264][40/63] lr: 2.8292e-03 eta: 14:05:38 time: 1.1436 data_time: 0.0109 memory: 16131 loss: 2.2528 loss_prob: 1.3896 loss_thr: 0.6405 loss_db: 0.2228 2022/10/25 23:10:43 - mmengine - INFO - Epoch(train) [264][45/63] lr: 2.8292e-03 eta: 14:05:38 time: 0.9849 data_time: 0.0105 memory: 16131 loss: 2.1662 loss_prob: 1.3113 loss_thr: 0.6418 loss_db: 0.2131 2022/10/25 23:10:49 - mmengine - INFO - Epoch(train) [264][50/63] lr: 2.8292e-03 eta: 14:05:35 time: 1.0281 data_time: 0.0248 memory: 16131 loss: 2.0642 loss_prob: 1.2302 loss_thr: 0.6333 loss_db: 0.2007 2022/10/25 23:10:54 - mmengine - INFO - Epoch(train) [264][55/63] lr: 2.8292e-03 eta: 14:05:35 time: 1.1791 data_time: 0.0236 memory: 16131 loss: 2.0784 loss_prob: 1.2380 loss_thr: 0.6373 loss_db: 0.2032 2022/10/25 23:11:02 - mmengine - INFO - Epoch(train) [264][60/63] lr: 2.8292e-03 eta: 14:05:43 time: 1.3426 data_time: 0.0133 memory: 16131 loss: 1.9904 loss_prob: 1.1831 loss_thr: 0.6159 loss_db: 0.1914 2022/10/25 23:11:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:11:15 - mmengine - INFO - Epoch(train) [265][5/63] lr: 2.8265e-03 eta: 14:05:43 time: 1.6094 data_time: 0.2563 memory: 16131 loss: 1.9638 loss_prob: 1.1567 loss_thr: 0.6182 loss_db: 0.1888 2022/10/25 23:11:23 - mmengine - INFO - Epoch(train) [265][10/63] lr: 2.8265e-03 eta: 14:05:57 time: 1.8101 data_time: 0.2573 memory: 16131 loss: 1.9771 loss_prob: 1.1751 loss_thr: 0.6136 loss_db: 0.1885 2022/10/25 23:11:29 - mmengine - INFO - Epoch(train) [265][15/63] lr: 2.8265e-03 eta: 14:05:57 time: 1.3637 data_time: 0.0114 memory: 16131 loss: 1.9801 loss_prob: 1.1770 loss_thr: 0.6165 loss_db: 0.1865 2022/10/25 23:11:35 - mmengine - INFO - Epoch(train) [265][20/63] lr: 2.8265e-03 eta: 14:06:00 time: 1.1876 data_time: 0.0143 memory: 16131 loss: 1.9310 loss_prob: 1.1168 loss_thr: 0.6350 loss_db: 0.1792 2022/10/25 23:11:43 - mmengine - INFO - Epoch(train) [265][25/63] lr: 2.8265e-03 eta: 14:06:00 time: 1.4623 data_time: 0.0380 memory: 16131 loss: 1.9176 loss_prob: 1.1120 loss_thr: 0.6246 loss_db: 0.1810 2022/10/25 23:11:50 - mmengine - INFO - Epoch(train) [265][30/63] lr: 2.8265e-03 eta: 14:06:12 time: 1.4650 data_time: 0.0384 memory: 16131 loss: 1.9977 loss_prob: 1.1676 loss_thr: 0.6401 loss_db: 0.1900 2022/10/25 23:11:58 - mmengine - INFO - Epoch(train) [265][35/63] lr: 2.8265e-03 eta: 14:06:12 time: 1.4325 data_time: 0.0149 memory: 16131 loss: 1.9649 loss_prob: 1.1464 loss_thr: 0.6299 loss_db: 0.1885 2022/10/25 23:12:03 - mmengine - INFO - Epoch(train) [265][40/63] lr: 2.8265e-03 eta: 14:06:21 time: 1.3586 data_time: 0.0161 memory: 16131 loss: 1.8970 loss_prob: 1.1140 loss_thr: 0.5986 loss_db: 0.1845 2022/10/25 23:12:08 - mmengine - INFO - Epoch(train) [265][45/63] lr: 2.8265e-03 eta: 14:06:21 time: 0.9730 data_time: 0.0125 memory: 16131 loss: 2.0614 loss_prob: 1.2413 loss_thr: 0.6204 loss_db: 0.1997 2022/10/25 23:12:12 - mmengine - INFO - Epoch(train) [265][50/63] lr: 2.8265e-03 eta: 14:06:14 time: 0.8967 data_time: 0.0477 memory: 16131 loss: 2.1033 loss_prob: 1.2676 loss_thr: 0.6326 loss_db: 0.2031 2022/10/25 23:12:17 - mmengine - INFO - Epoch(train) [265][55/63] lr: 2.8265e-03 eta: 14:06:14 time: 0.9039 data_time: 0.0473 memory: 16131 loss: 1.9962 loss_prob: 1.1809 loss_thr: 0.6233 loss_db: 0.1920 2022/10/25 23:12:21 - mmengine - INFO - Epoch(train) [265][60/63] lr: 2.8265e-03 eta: 14:06:05 time: 0.8491 data_time: 0.0121 memory: 16131 loss: 1.9378 loss_prob: 1.1395 loss_thr: 0.6119 loss_db: 0.1864 2022/10/25 23:12:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:12:32 - mmengine - INFO - Epoch(train) [266][5/63] lr: 2.8237e-03 eta: 14:06:05 time: 1.3502 data_time: 0.2176 memory: 16131 loss: 2.0961 loss_prob: 1.2372 loss_thr: 0.6523 loss_db: 0.2066 2022/10/25 23:12:38 - mmengine - INFO - Epoch(train) [266][10/63] lr: 2.8237e-03 eta: 14:06:10 time: 1.5743 data_time: 0.2174 memory: 16131 loss: 2.2257 loss_prob: 1.3345 loss_thr: 0.6710 loss_db: 0.2201 2022/10/25 23:12:45 - mmengine - INFO - Epoch(train) [266][15/63] lr: 2.8237e-03 eta: 14:06:10 time: 1.3253 data_time: 0.0070 memory: 16131 loss: 2.3339 loss_prob: 1.4396 loss_thr: 0.6580 loss_db: 0.2364 2022/10/25 23:12:48 - mmengine - INFO - Epoch(train) [266][20/63] lr: 2.8237e-03 eta: 14:06:06 time: 0.9850 data_time: 0.0072 memory: 16131 loss: 2.2806 loss_prob: 1.3959 loss_thr: 0.6554 loss_db: 0.2292 2022/10/25 23:12:56 - mmengine - INFO - Epoch(train) [266][25/63] lr: 2.8237e-03 eta: 14:06:06 time: 1.0751 data_time: 0.0110 memory: 16131 loss: 2.1306 loss_prob: 1.2641 loss_thr: 0.6626 loss_db: 0.2039 2022/10/25 23:13:02 - mmengine - INFO - Epoch(train) [266][30/63] lr: 2.8237e-03 eta: 14:06:16 time: 1.4184 data_time: 0.0212 memory: 16131 loss: 2.1331 loss_prob: 1.2671 loss_thr: 0.6641 loss_db: 0.2018 2022/10/25 23:13:07 - mmengine - INFO - Epoch(train) [266][35/63] lr: 2.8237e-03 eta: 14:06:16 time: 1.0812 data_time: 0.0184 memory: 16131 loss: 2.1033 loss_prob: 1.2538 loss_thr: 0.6492 loss_db: 0.2003 2022/10/25 23:13:14 - mmengine - INFO - Epoch(train) [266][40/63] lr: 2.8237e-03 eta: 14:06:18 time: 1.1605 data_time: 0.0083 memory: 16131 loss: 2.0389 loss_prob: 1.2136 loss_thr: 0.6262 loss_db: 0.1991 2022/10/25 23:13:17 - mmengine - INFO - Epoch(train) [266][45/63] lr: 2.8237e-03 eta: 14:06:18 time: 1.0852 data_time: 0.0076 memory: 16131 loss: 1.9843 loss_prob: 1.1782 loss_thr: 0.6140 loss_db: 0.1921 2022/10/25 23:13:24 - mmengine - INFO - Epoch(train) [266][50/63] lr: 2.8237e-03 eta: 14:06:14 time: 0.9828 data_time: 0.0077 memory: 16131 loss: 2.0297 loss_prob: 1.2024 loss_thr: 0.6342 loss_db: 0.1931 2022/10/25 23:13:28 - mmengine - INFO - Epoch(train) [266][55/63] lr: 2.8237e-03 eta: 14:06:14 time: 1.0932 data_time: 0.0286 memory: 16131 loss: 2.0128 loss_prob: 1.1745 loss_thr: 0.6474 loss_db: 0.1909 2022/10/25 23:13:35 - mmengine - INFO - Epoch(train) [266][60/63] lr: 2.8237e-03 eta: 14:06:14 time: 1.1152 data_time: 0.0279 memory: 16131 loss: 1.9900 loss_prob: 1.1672 loss_thr: 0.6296 loss_db: 0.1932 2022/10/25 23:13:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:13:50 - mmengine - INFO - Epoch(train) [267][5/63] lr: 2.8210e-03 eta: 14:06:14 time: 1.6532 data_time: 0.1811 memory: 16131 loss: 1.8802 loss_prob: 1.1108 loss_thr: 0.5901 loss_db: 0.1794 2022/10/25 23:13:55 - mmengine - INFO - Epoch(train) [267][10/63] lr: 2.8210e-03 eta: 14:06:20 time: 1.6135 data_time: 0.1846 memory: 16131 loss: 1.9727 loss_prob: 1.1713 loss_thr: 0.6148 loss_db: 0.1866 2022/10/25 23:14:02 - mmengine - INFO - Epoch(train) [267][15/63] lr: 2.8210e-03 eta: 14:06:20 time: 1.2275 data_time: 0.0154 memory: 16131 loss: 1.9999 loss_prob: 1.1921 loss_thr: 0.6164 loss_db: 0.1914 2022/10/25 23:14:08 - mmengine - INFO - Epoch(train) [267][20/63] lr: 2.8210e-03 eta: 14:06:24 time: 1.2130 data_time: 0.0141 memory: 16131 loss: 2.0419 loss_prob: 1.2223 loss_thr: 0.6247 loss_db: 0.1948 2022/10/25 23:14:16 - mmengine - INFO - Epoch(train) [267][25/63] lr: 2.8210e-03 eta: 14:06:24 time: 1.4330 data_time: 0.0119 memory: 16131 loss: 2.0097 loss_prob: 1.1969 loss_thr: 0.6213 loss_db: 0.1916 2022/10/25 23:14:23 - mmengine - INFO - Epoch(train) [267][30/63] lr: 2.8210e-03 eta: 14:06:38 time: 1.5054 data_time: 0.0390 memory: 16131 loss: 2.0053 loss_prob: 1.2030 loss_thr: 0.6039 loss_db: 0.1984 2022/10/25 23:14:28 - mmengine - INFO - Epoch(train) [267][35/63] lr: 2.8210e-03 eta: 14:06:38 time: 1.2148 data_time: 0.0359 memory: 16131 loss: 2.0476 loss_prob: 1.2293 loss_thr: 0.6154 loss_db: 0.2030 2022/10/25 23:14:35 - mmengine - INFO - Epoch(train) [267][40/63] lr: 2.8210e-03 eta: 14:06:43 time: 1.2653 data_time: 0.0069 memory: 16131 loss: 2.0380 loss_prob: 1.2187 loss_thr: 0.6230 loss_db: 0.1963 2022/10/25 23:14:38 - mmengine - INFO - Epoch(train) [267][45/63] lr: 2.8210e-03 eta: 14:06:43 time: 0.9796 data_time: 0.0139 memory: 16131 loss: 2.1680 loss_prob: 1.3289 loss_thr: 0.6282 loss_db: 0.2109 2022/10/25 23:14:44 - mmengine - INFO - Epoch(train) [267][50/63] lr: 2.8210e-03 eta: 14:06:35 time: 0.8748 data_time: 0.0369 memory: 16131 loss: 2.2129 loss_prob: 1.3486 loss_thr: 0.6441 loss_db: 0.2202 2022/10/25 23:14:50 - mmengine - INFO - Epoch(train) [267][55/63] lr: 2.8210e-03 eta: 14:06:35 time: 1.1614 data_time: 0.0349 memory: 16131 loss: 2.0324 loss_prob: 1.2058 loss_thr: 0.6269 loss_db: 0.1998 2022/10/25 23:14:57 - mmengine - INFO - Epoch(train) [267][60/63] lr: 2.8210e-03 eta: 14:06:40 time: 1.2662 data_time: 0.0133 memory: 16131 loss: 1.9449 loss_prob: 1.1503 loss_thr: 0.6057 loss_db: 0.1889 2022/10/25 23:14:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:15:07 - mmengine - INFO - Epoch(train) [268][5/63] lr: 2.8183e-03 eta: 14:06:40 time: 1.3931 data_time: 0.2347 memory: 16131 loss: 1.8723 loss_prob: 1.0831 loss_thr: 0.6138 loss_db: 0.1753 2022/10/25 23:15:13 - mmengine - INFO - Epoch(train) [268][10/63] lr: 2.8183e-03 eta: 14:06:43 time: 1.5357 data_time: 0.2362 memory: 16131 loss: 2.1010 loss_prob: 1.2685 loss_thr: 0.6347 loss_db: 0.1978 2022/10/25 23:15:20 - mmengine - INFO - Epoch(train) [268][15/63] lr: 2.8183e-03 eta: 14:06:43 time: 1.2741 data_time: 0.0093 memory: 16131 loss: 2.1707 loss_prob: 1.3070 loss_thr: 0.6541 loss_db: 0.2095 2022/10/25 23:15:25 - mmengine - INFO - Epoch(train) [268][20/63] lr: 2.8183e-03 eta: 14:06:46 time: 1.1766 data_time: 0.0063 memory: 16131 loss: 1.9707 loss_prob: 1.1348 loss_thr: 0.6448 loss_db: 0.1911 2022/10/25 23:15:29 - mmengine - INFO - Epoch(train) [268][25/63] lr: 2.8183e-03 eta: 14:06:46 time: 0.9365 data_time: 0.0089 memory: 16131 loss: 2.0087 loss_prob: 1.1674 loss_thr: 0.6480 loss_db: 0.1933 2022/10/25 23:15:37 - mmengine - INFO - Epoch(train) [268][30/63] lr: 2.8183e-03 eta: 14:06:48 time: 1.1872 data_time: 0.0582 memory: 16131 loss: 1.9913 loss_prob: 1.1764 loss_thr: 0.6229 loss_db: 0.1920 2022/10/25 23:15:45 - mmengine - INFO - Epoch(train) [268][35/63] lr: 2.8183e-03 eta: 14:06:48 time: 1.5652 data_time: 0.0564 memory: 16131 loss: 1.9188 loss_prob: 1.1121 loss_thr: 0.6254 loss_db: 0.1813 2022/10/25 23:15:51 - mmengine - INFO - Epoch(train) [268][40/63] lr: 2.8183e-03 eta: 14:06:58 time: 1.3977 data_time: 0.0068 memory: 16131 loss: 1.9463 loss_prob: 1.1236 loss_thr: 0.6423 loss_db: 0.1804 2022/10/25 23:15:56 - mmengine - INFO - Epoch(train) [268][45/63] lr: 2.8183e-03 eta: 14:06:58 time: 1.0661 data_time: 0.0068 memory: 16131 loss: 1.8338 loss_prob: 1.0617 loss_thr: 0.6024 loss_db: 0.1697 2022/10/25 23:16:02 - mmengine - INFO - Epoch(train) [268][50/63] lr: 2.8183e-03 eta: 14:06:58 time: 1.1000 data_time: 0.0138 memory: 16131 loss: 1.8425 loss_prob: 1.0748 loss_thr: 0.5941 loss_db: 0.1737 2022/10/25 23:16:07 - mmengine - INFO - Epoch(train) [268][55/63] lr: 2.8183e-03 eta: 14:06:58 time: 1.1067 data_time: 0.0272 memory: 16131 loss: 1.8953 loss_prob: 1.0975 loss_thr: 0.6201 loss_db: 0.1776 2022/10/25 23:16:14 - mmengine - INFO - Epoch(train) [268][60/63] lr: 2.8183e-03 eta: 14:07:02 time: 1.2473 data_time: 0.0196 memory: 16131 loss: 1.8046 loss_prob: 1.0251 loss_thr: 0.6130 loss_db: 0.1665 2022/10/25 23:16:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:16:24 - mmengine - INFO - Epoch(train) [269][5/63] lr: 2.8156e-03 eta: 14:07:02 time: 1.3472 data_time: 0.2028 memory: 16131 loss: 1.9190 loss_prob: 1.1412 loss_thr: 0.5921 loss_db: 0.1858 2022/10/25 23:16:30 - mmengine - INFO - Epoch(train) [269][10/63] lr: 2.8156e-03 eta: 14:06:59 time: 1.3611 data_time: 0.2052 memory: 16131 loss: 2.1578 loss_prob: 1.3312 loss_thr: 0.6152 loss_db: 0.2113 2022/10/25 23:16:35 - mmengine - INFO - Epoch(train) [269][15/63] lr: 2.8156e-03 eta: 14:06:59 time: 1.0849 data_time: 0.0095 memory: 16131 loss: 2.2438 loss_prob: 1.3843 loss_thr: 0.6392 loss_db: 0.2204 2022/10/25 23:16:42 - mmengine - INFO - Epoch(train) [269][20/63] lr: 2.8156e-03 eta: 14:07:03 time: 1.2248 data_time: 0.0103 memory: 16131 loss: 2.1640 loss_prob: 1.3000 loss_thr: 0.6511 loss_db: 0.2128 2022/10/25 23:16:49 - mmengine - INFO - Epoch(train) [269][25/63] lr: 2.8156e-03 eta: 14:07:03 time: 1.3773 data_time: 0.0106 memory: 16131 loss: 2.2646 loss_prob: 1.3644 loss_thr: 0.6776 loss_db: 0.2226 2022/10/25 23:16:57 - mmengine - INFO - Epoch(train) [269][30/63] lr: 2.8156e-03 eta: 14:07:16 time: 1.4997 data_time: 0.0388 memory: 16131 loss: 2.1931 loss_prob: 1.3198 loss_thr: 0.6577 loss_db: 0.2157 2022/10/25 23:17:04 - mmengine - INFO - Epoch(train) [269][35/63] lr: 2.8156e-03 eta: 14:07:16 time: 1.4906 data_time: 0.0380 memory: 16131 loss: 2.3381 loss_prob: 1.4447 loss_thr: 0.6593 loss_db: 0.2342 2022/10/25 23:17:10 - mmengine - INFO - Epoch(train) [269][40/63] lr: 2.8156e-03 eta: 14:07:24 time: 1.3270 data_time: 0.0075 memory: 16131 loss: 2.3944 loss_prob: 1.4860 loss_thr: 0.6691 loss_db: 0.2394 2022/10/25 23:17:16 - mmengine - INFO - Epoch(train) [269][45/63] lr: 2.8156e-03 eta: 14:07:24 time: 1.1693 data_time: 0.0114 memory: 16131 loss: 2.4556 loss_prob: 1.5184 loss_thr: 0.6929 loss_db: 0.2444 2022/10/25 23:17:22 - mmengine - INFO - Epoch(train) [269][50/63] lr: 2.8156e-03 eta: 14:07:25 time: 1.1613 data_time: 0.0218 memory: 16131 loss: 2.5671 loss_prob: 1.5906 loss_thr: 0.7186 loss_db: 0.2579 2022/10/25 23:17:26 - mmengine - INFO - Epoch(train) [269][55/63] lr: 2.8156e-03 eta: 14:07:25 time: 1.0344 data_time: 0.0387 memory: 16131 loss: 2.4367 loss_prob: 1.4886 loss_thr: 0.7010 loss_db: 0.2471 2022/10/25 23:17:30 - mmengine - INFO - Epoch(train) [269][60/63] lr: 2.8156e-03 eta: 14:07:16 time: 0.8404 data_time: 0.0267 memory: 16131 loss: 2.2983 loss_prob: 1.4015 loss_thr: 0.6674 loss_db: 0.2294 2022/10/25 23:17:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:17:43 - mmengine - INFO - Epoch(train) [270][5/63] lr: 2.8129e-03 eta: 14:07:16 time: 1.4650 data_time: 0.2194 memory: 16131 loss: 2.5828 loss_prob: 1.6429 loss_thr: 0.6703 loss_db: 0.2696 2022/10/25 23:17:52 - mmengine - INFO - Epoch(train) [270][10/63] lr: 2.8129e-03 eta: 14:07:35 time: 2.0131 data_time: 0.2267 memory: 16131 loss: 2.8636 loss_prob: 1.8367 loss_thr: 0.7185 loss_db: 0.3084 2022/10/25 23:18:00 - mmengine - INFO - Epoch(train) [270][15/63] lr: 2.8129e-03 eta: 14:07:35 time: 1.6038 data_time: 0.0159 memory: 16131 loss: 2.8084 loss_prob: 1.7783 loss_thr: 0.7377 loss_db: 0.2925 2022/10/25 23:18:05 - mmengine - INFO - Epoch(train) [270][20/63] lr: 2.8129e-03 eta: 14:07:43 time: 1.3342 data_time: 0.0088 memory: 16131 loss: 2.8287 loss_prob: 1.8053 loss_thr: 0.7214 loss_db: 0.3020 2022/10/25 23:18:11 - mmengine - INFO - Epoch(train) [270][25/63] lr: 2.8129e-03 eta: 14:07:43 time: 1.1636 data_time: 0.0277 memory: 16131 loss: 2.6411 loss_prob: 1.6609 loss_thr: 0.7018 loss_db: 0.2784 2022/10/25 23:18:19 - mmengine - INFO - Epoch(train) [270][30/63] lr: 2.8129e-03 eta: 14:07:52 time: 1.3775 data_time: 0.0381 memory: 16131 loss: 2.4525 loss_prob: 1.5092 loss_thr: 0.6909 loss_db: 0.2525 2022/10/25 23:18:22 - mmengine - INFO - Epoch(train) [270][35/63] lr: 2.8129e-03 eta: 14:07:52 time: 1.0815 data_time: 0.0160 memory: 16131 loss: 2.3955 loss_prob: 1.4818 loss_thr: 0.6628 loss_db: 0.2510 2022/10/25 23:18:29 - mmengine - INFO - Epoch(train) [270][40/63] lr: 2.8129e-03 eta: 14:07:48 time: 1.0163 data_time: 0.0066 memory: 16131 loss: 2.4680 loss_prob: 1.5430 loss_thr: 0.6723 loss_db: 0.2527 2022/10/25 23:18:37 - mmengine - INFO - Epoch(train) [270][45/63] lr: 2.8129e-03 eta: 14:07:48 time: 1.5429 data_time: 0.0075 memory: 16131 loss: 2.5203 loss_prob: 1.5668 loss_thr: 0.6996 loss_db: 0.2540 2022/10/25 23:18:45 - mmengine - INFO - Epoch(train) [270][50/63] lr: 2.8129e-03 eta: 14:08:04 time: 1.5717 data_time: 0.0344 memory: 16131 loss: 2.2976 loss_prob: 1.3989 loss_thr: 0.6755 loss_db: 0.2232 2022/10/25 23:18:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:18:49 - mmengine - INFO - Epoch(train) [270][55/63] lr: 2.8129e-03 eta: 14:08:04 time: 1.2045 data_time: 0.0333 memory: 16131 loss: 2.0782 loss_prob: 1.2325 loss_thr: 0.6486 loss_db: 0.1971 2022/10/25 23:18:55 - mmengine - INFO - Epoch(train) [270][60/63] lr: 2.8129e-03 eta: 14:07:59 time: 0.9972 data_time: 0.0053 memory: 16131 loss: 2.1246 loss_prob: 1.2862 loss_thr: 0.6315 loss_db: 0.2069 2022/10/25 23:18:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:19:05 - mmengine - INFO - Epoch(train) [271][5/63] lr: 2.8101e-03 eta: 14:07:59 time: 1.3276 data_time: 0.2905 memory: 16131 loss: 1.9896 loss_prob: 1.2013 loss_thr: 0.6046 loss_db: 0.1837 2022/10/25 23:19:14 - mmengine - INFO - Epoch(train) [271][10/63] lr: 2.8101e-03 eta: 14:08:03 time: 1.5771 data_time: 0.2939 memory: 16131 loss: 2.0495 loss_prob: 1.2232 loss_thr: 0.6283 loss_db: 0.1980 2022/10/25 23:19:21 - mmengine - INFO - Epoch(train) [271][15/63] lr: 2.8101e-03 eta: 14:08:03 time: 1.6678 data_time: 0.0115 memory: 16131 loss: 2.1894 loss_prob: 1.3117 loss_thr: 0.6588 loss_db: 0.2189 2022/10/25 23:19:28 - mmengine - INFO - Epoch(train) [271][20/63] lr: 2.8101e-03 eta: 14:08:15 time: 1.4438 data_time: 0.0056 memory: 16131 loss: 2.1566 loss_prob: 1.2864 loss_thr: 0.6575 loss_db: 0.2126 2022/10/25 23:19:35 - mmengine - INFO - Epoch(train) [271][25/63] lr: 2.8101e-03 eta: 14:08:15 time: 1.4059 data_time: 0.0547 memory: 16131 loss: 1.9933 loss_prob: 1.1893 loss_thr: 0.6121 loss_db: 0.1919 2022/10/25 23:19:41 - mmengine - INFO - Epoch(train) [271][30/63] lr: 2.8101e-03 eta: 14:08:20 time: 1.2943 data_time: 0.0552 memory: 16131 loss: 2.1134 loss_prob: 1.2563 loss_thr: 0.6520 loss_db: 0.2051 2022/10/25 23:19:48 - mmengine - INFO - Epoch(train) [271][35/63] lr: 2.8101e-03 eta: 14:08:20 time: 1.2493 data_time: 0.0057 memory: 16131 loss: 2.2311 loss_prob: 1.3309 loss_thr: 0.6828 loss_db: 0.2174 2022/10/25 23:19:51 - mmengine - INFO - Epoch(train) [271][40/63] lr: 2.8101e-03 eta: 14:08:14 time: 0.9470 data_time: 0.0052 memory: 16131 loss: 2.3347 loss_prob: 1.4251 loss_thr: 0.6772 loss_db: 0.2324 2022/10/25 23:19:56 - mmengine - INFO - Epoch(train) [271][45/63] lr: 2.8101e-03 eta: 14:08:14 time: 0.8554 data_time: 0.0090 memory: 16131 loss: 2.2525 loss_prob: 1.3632 loss_thr: 0.6630 loss_db: 0.2263 2022/10/25 23:20:02 - mmengine - INFO - Epoch(train) [271][50/63] lr: 2.8101e-03 eta: 14:08:14 time: 1.1143 data_time: 0.0346 memory: 16131 loss: 2.0282 loss_prob: 1.2031 loss_thr: 0.6274 loss_db: 0.1977 2022/10/25 23:20:06 - mmengine - INFO - Epoch(train) [271][55/63] lr: 2.8101e-03 eta: 14:08:14 time: 1.0134 data_time: 0.0309 memory: 16131 loss: 2.0068 loss_prob: 1.1939 loss_thr: 0.6185 loss_db: 0.1945 2022/10/25 23:20:12 - mmengine - INFO - Epoch(train) [271][60/63] lr: 2.8101e-03 eta: 14:08:10 time: 0.9923 data_time: 0.0064 memory: 16131 loss: 1.9662 loss_prob: 1.1612 loss_thr: 0.6153 loss_db: 0.1897 2022/10/25 23:20:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:20:23 - mmengine - INFO - Epoch(train) [272][5/63] lr: 2.8074e-03 eta: 14:08:10 time: 1.4750 data_time: 0.2542 memory: 16131 loss: 1.9593 loss_prob: 1.1625 loss_thr: 0.6083 loss_db: 0.1885 2022/10/25 23:20:29 - mmengine - INFO - Epoch(train) [272][10/63] lr: 2.8074e-03 eta: 14:08:08 time: 1.4027 data_time: 0.2527 memory: 16131 loss: 2.1492 loss_prob: 1.3356 loss_thr: 0.5973 loss_db: 0.2162 2022/10/25 23:20:36 - mmengine - INFO - Epoch(train) [272][15/63] lr: 2.8074e-03 eta: 14:08:08 time: 1.3383 data_time: 0.0163 memory: 16131 loss: 2.3271 loss_prob: 1.4471 loss_thr: 0.6452 loss_db: 0.2348 2022/10/25 23:20:43 - mmengine - INFO - Epoch(train) [272][20/63] lr: 2.8074e-03 eta: 14:08:19 time: 1.4527 data_time: 0.0133 memory: 16131 loss: 2.1988 loss_prob: 1.3265 loss_thr: 0.6513 loss_db: 0.2211 2022/10/25 23:20:50 - mmengine - INFO - Epoch(train) [272][25/63] lr: 2.8074e-03 eta: 14:08:19 time: 1.3997 data_time: 0.0299 memory: 16131 loss: 2.0363 loss_prob: 1.2065 loss_thr: 0.6291 loss_db: 0.2007 2022/10/25 23:20:58 - mmengine - INFO - Epoch(train) [272][30/63] lr: 2.8074e-03 eta: 14:08:31 time: 1.4619 data_time: 0.0425 memory: 16131 loss: 2.0558 loss_prob: 1.2141 loss_thr: 0.6423 loss_db: 0.1993 2022/10/25 23:21:06 - mmengine - INFO - Epoch(train) [272][35/63] lr: 2.8074e-03 eta: 14:08:31 time: 1.5324 data_time: 0.0195 memory: 16131 loss: 2.1334 loss_prob: 1.2708 loss_thr: 0.6540 loss_db: 0.2086 2022/10/25 23:21:10 - mmengine - INFO - Epoch(train) [272][40/63] lr: 2.8074e-03 eta: 14:08:33 time: 1.2095 data_time: 0.0074 memory: 16131 loss: 2.1832 loss_prob: 1.3006 loss_thr: 0.6701 loss_db: 0.2125 2022/10/25 23:21:15 - mmengine - INFO - Epoch(train) [272][45/63] lr: 2.8074e-03 eta: 14:08:33 time: 0.9009 data_time: 0.0082 memory: 16131 loss: 2.0306 loss_prob: 1.1866 loss_thr: 0.6515 loss_db: 0.1925 2022/10/25 23:21:21 - mmengine - INFO - Epoch(train) [272][50/63] lr: 2.8074e-03 eta: 14:08:32 time: 1.0876 data_time: 0.0207 memory: 16131 loss: 2.0311 loss_prob: 1.1930 loss_thr: 0.6449 loss_db: 0.1932 2022/10/25 23:21:26 - mmengine - INFO - Epoch(train) [272][55/63] lr: 2.8074e-03 eta: 14:08:32 time: 1.1304 data_time: 0.0281 memory: 16131 loss: 2.1531 loss_prob: 1.2809 loss_thr: 0.6648 loss_db: 0.2075 2022/10/25 23:21:31 - mmengine - INFO - Epoch(train) [272][60/63] lr: 2.8074e-03 eta: 14:08:27 time: 0.9781 data_time: 0.0174 memory: 16131 loss: 2.0250 loss_prob: 1.1907 loss_thr: 0.6378 loss_db: 0.1965 2022/10/25 23:21:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:21:42 - mmengine - INFO - Epoch(train) [273][5/63] lr: 2.8047e-03 eta: 14:08:27 time: 1.4177 data_time: 0.2361 memory: 16131 loss: 2.0386 loss_prob: 1.2226 loss_thr: 0.6123 loss_db: 0.2037 2022/10/25 23:21:49 - mmengine - INFO - Epoch(train) [273][10/63] lr: 2.8047e-03 eta: 14:08:32 time: 1.6168 data_time: 0.2381 memory: 16131 loss: 2.1610 loss_prob: 1.3287 loss_thr: 0.6174 loss_db: 0.2150 2022/10/25 23:21:55 - mmengine - INFO - Epoch(train) [273][15/63] lr: 2.8047e-03 eta: 14:08:32 time: 1.2478 data_time: 0.0102 memory: 16131 loss: 2.1615 loss_prob: 1.2989 loss_thr: 0.6528 loss_db: 0.2098 2022/10/25 23:21:59 - mmengine - INFO - Epoch(train) [273][20/63] lr: 2.8047e-03 eta: 14:08:30 time: 1.0561 data_time: 0.0068 memory: 16131 loss: 2.1986 loss_prob: 1.3104 loss_thr: 0.6755 loss_db: 0.2127 2022/10/25 23:22:04 - mmengine - INFO - Epoch(train) [273][25/63] lr: 2.8047e-03 eta: 14:08:30 time: 0.9326 data_time: 0.0402 memory: 16131 loss: 2.1032 loss_prob: 1.2544 loss_thr: 0.6446 loss_db: 0.2043 2022/10/25 23:22:10 - mmengine - INFO - Epoch(train) [273][30/63] lr: 2.8047e-03 eta: 14:08:27 time: 1.0556 data_time: 0.0412 memory: 16131 loss: 1.9130 loss_prob: 1.1091 loss_thr: 0.6229 loss_db: 0.1811 2022/10/25 23:22:15 - mmengine - INFO - Epoch(train) [273][35/63] lr: 2.8047e-03 eta: 14:08:27 time: 1.0536 data_time: 0.0091 memory: 16131 loss: 1.8965 loss_prob: 1.0997 loss_thr: 0.6188 loss_db: 0.1780 2022/10/25 23:22:21 - mmengine - INFO - Epoch(train) [273][40/63] lr: 2.8047e-03 eta: 14:08:27 time: 1.1002 data_time: 0.0140 memory: 16131 loss: 1.9340 loss_prob: 1.1397 loss_thr: 0.6089 loss_db: 0.1854 2022/10/25 23:22:26 - mmengine - INFO - Epoch(train) [273][45/63] lr: 2.8047e-03 eta: 14:08:27 time: 1.1330 data_time: 0.0167 memory: 16131 loss: 2.0376 loss_prob: 1.2179 loss_thr: 0.6232 loss_db: 0.1965 2022/10/25 23:22:30 - mmengine - INFO - Epoch(train) [273][50/63] lr: 2.8047e-03 eta: 14:08:20 time: 0.9246 data_time: 0.0262 memory: 16131 loss: 1.9912 loss_prob: 1.1690 loss_thr: 0.6296 loss_db: 0.1926 2022/10/25 23:22:36 - mmengine - INFO - Epoch(train) [273][55/63] lr: 2.8047e-03 eta: 14:08:20 time: 1.0214 data_time: 0.0247 memory: 16131 loss: 1.8285 loss_prob: 1.0585 loss_thr: 0.5957 loss_db: 0.1743 2022/10/25 23:22:42 - mmengine - INFO - Epoch(train) [273][60/63] lr: 2.8047e-03 eta: 14:08:23 time: 1.2184 data_time: 0.0103 memory: 16131 loss: 1.8550 loss_prob: 1.0839 loss_thr: 0.5971 loss_db: 0.1739 2022/10/25 23:22:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:22:53 - mmengine - INFO - Epoch(train) [274][5/63] lr: 2.8020e-03 eta: 14:08:23 time: 1.3042 data_time: 0.2254 memory: 16131 loss: 2.0154 loss_prob: 1.2220 loss_thr: 0.5973 loss_db: 0.1961 2022/10/25 23:22:58 - mmengine - INFO - Epoch(train) [274][10/63] lr: 2.8020e-03 eta: 14:08:21 time: 1.4102 data_time: 0.2257 memory: 16131 loss: 1.9788 loss_prob: 1.1814 loss_thr: 0.6068 loss_db: 0.1906 2022/10/25 23:23:05 - mmengine - INFO - Epoch(train) [274][15/63] lr: 2.8020e-03 eta: 14:08:21 time: 1.2099 data_time: 0.0159 memory: 16131 loss: 1.8948 loss_prob: 1.1046 loss_thr: 0.6085 loss_db: 0.1816 2022/10/25 23:23:11 - mmengine - INFO - Epoch(train) [274][20/63] lr: 2.8020e-03 eta: 14:08:27 time: 1.3036 data_time: 0.0158 memory: 16131 loss: 1.9854 loss_prob: 1.1515 loss_thr: 0.6432 loss_db: 0.1908 2022/10/25 23:23:15 - mmengine - INFO - Epoch(train) [274][25/63] lr: 2.8020e-03 eta: 14:08:27 time: 1.0083 data_time: 0.0272 memory: 16131 loss: 2.1106 loss_prob: 1.2393 loss_thr: 0.6693 loss_db: 0.2021 2022/10/25 23:23:21 - mmengine - INFO - Epoch(train) [274][30/63] lr: 2.8020e-03 eta: 14:08:22 time: 0.9790 data_time: 0.0383 memory: 16131 loss: 2.1307 loss_prob: 1.2697 loss_thr: 0.6520 loss_db: 0.2090 2022/10/25 23:23:26 - mmengine - INFO - Epoch(train) [274][35/63] lr: 2.8020e-03 eta: 14:08:22 time: 1.0190 data_time: 0.0163 memory: 16131 loss: 2.2593 loss_prob: 1.3868 loss_thr: 0.6498 loss_db: 0.2227 2022/10/25 23:23:34 - mmengine - INFO - Epoch(train) [274][40/63] lr: 2.8020e-03 eta: 14:08:27 time: 1.2803 data_time: 0.0110 memory: 16131 loss: 2.3450 loss_prob: 1.4717 loss_thr: 0.6471 loss_db: 0.2262 2022/10/25 23:23:41 - mmengine - INFO - Epoch(train) [274][45/63] lr: 2.8020e-03 eta: 14:08:27 time: 1.5092 data_time: 0.0134 memory: 16131 loss: 2.1565 loss_prob: 1.3229 loss_thr: 0.6219 loss_db: 0.2116 2022/10/25 23:23:45 - mmengine - INFO - Epoch(train) [274][50/63] lr: 2.8020e-03 eta: 14:08:26 time: 1.1151 data_time: 0.0261 memory: 16131 loss: 2.0150 loss_prob: 1.1901 loss_thr: 0.6259 loss_db: 0.1990 2022/10/25 23:23:52 - mmengine - INFO - Epoch(train) [274][55/63] lr: 2.8020e-03 eta: 14:08:26 time: 1.1245 data_time: 0.0391 memory: 16131 loss: 2.1001 loss_prob: 1.2408 loss_thr: 0.6520 loss_db: 0.2073 2022/10/25 23:23:59 - mmengine - INFO - Epoch(train) [274][60/63] lr: 2.8020e-03 eta: 14:08:36 time: 1.4320 data_time: 0.0207 memory: 16131 loss: 2.0968 loss_prob: 1.2468 loss_thr: 0.6412 loss_db: 0.2088 2022/10/25 23:24:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:24:09 - mmengine - INFO - Epoch(train) [275][5/63] lr: 2.7992e-03 eta: 14:08:36 time: 1.3130 data_time: 0.2000 memory: 16131 loss: 2.1163 loss_prob: 1.2866 loss_thr: 0.6201 loss_db: 0.2095 2022/10/25 23:24:16 - mmengine - INFO - Epoch(train) [275][10/63] lr: 2.7992e-03 eta: 14:08:34 time: 1.3998 data_time: 0.1993 memory: 16131 loss: 2.1421 loss_prob: 1.2915 loss_thr: 0.6434 loss_db: 0.2072 2022/10/25 23:24:23 - mmengine - INFO - Epoch(train) [275][15/63] lr: 2.7992e-03 eta: 14:08:34 time: 1.3764 data_time: 0.0109 memory: 16131 loss: 2.0374 loss_prob: 1.2142 loss_thr: 0.6334 loss_db: 0.1897 2022/10/25 23:24:29 - mmengine - INFO - Epoch(train) [275][20/63] lr: 2.7992e-03 eta: 14:08:41 time: 1.3299 data_time: 0.0101 memory: 16131 loss: 2.0102 loss_prob: 1.1950 loss_thr: 0.6252 loss_db: 0.1900 2022/10/25 23:24:32 - mmengine - INFO - Epoch(train) [275][25/63] lr: 2.7992e-03 eta: 14:08:41 time: 0.9188 data_time: 0.0111 memory: 16131 loss: 2.0767 loss_prob: 1.2410 loss_thr: 0.6318 loss_db: 0.2039 2022/10/25 23:24:39 - mmengine - INFO - Epoch(train) [275][30/63] lr: 2.7992e-03 eta: 14:08:36 time: 0.9924 data_time: 0.0350 memory: 16131 loss: 2.2362 loss_prob: 1.3658 loss_thr: 0.6470 loss_db: 0.2233 2022/10/25 23:24:45 - mmengine - INFO - Epoch(train) [275][35/63] lr: 2.7992e-03 eta: 14:08:36 time: 1.2335 data_time: 0.0338 memory: 16131 loss: 2.4935 loss_prob: 1.5523 loss_thr: 0.6897 loss_db: 0.2515 2022/10/25 23:24:50 - mmengine - INFO - Epoch(train) [275][40/63] lr: 2.7992e-03 eta: 14:08:35 time: 1.1107 data_time: 0.0188 memory: 16131 loss: 2.5058 loss_prob: 1.5492 loss_thr: 0.7085 loss_db: 0.2481 2022/10/25 23:24:53 - mmengine - INFO - Epoch(train) [275][45/63] lr: 2.7992e-03 eta: 14:08:35 time: 0.8351 data_time: 0.0148 memory: 16131 loss: 2.4392 loss_prob: 1.4876 loss_thr: 0.7141 loss_db: 0.2375 2022/10/25 23:24:57 - mmengine - INFO - Epoch(train) [275][50/63] lr: 2.7992e-03 eta: 14:08:21 time: 0.7128 data_time: 0.0266 memory: 16131 loss: 2.5259 loss_prob: 1.5556 loss_thr: 0.7228 loss_db: 0.2475 2022/10/25 23:25:00 - mmengine - INFO - Epoch(train) [275][55/63] lr: 2.7992e-03 eta: 14:08:21 time: 0.7222 data_time: 0.0263 memory: 16131 loss: 2.4020 loss_prob: 1.4635 loss_thr: 0.7054 loss_db: 0.2332 2022/10/25 23:25:03 - mmengine - INFO - Epoch(train) [275][60/63] lr: 2.7992e-03 eta: 14:08:03 time: 0.6093 data_time: 0.0055 memory: 16131 loss: 2.3066 loss_prob: 1.4086 loss_thr: 0.6845 loss_db: 0.2136 2022/10/25 23:25:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:25:09 - mmengine - INFO - Epoch(train) [276][5/63] lr: 2.7965e-03 eta: 14:08:03 time: 0.7094 data_time: 0.1890 memory: 16131 loss: 2.1010 loss_prob: 1.2712 loss_thr: 0.6319 loss_db: 0.1979 2022/10/25 23:25:12 - mmengine - INFO - Epoch(train) [276][10/63] lr: 2.7965e-03 eta: 14:07:39 time: 0.7364 data_time: 0.1924 memory: 16131 loss: 2.0280 loss_prob: 1.2102 loss_thr: 0.6209 loss_db: 0.1969 2022/10/25 23:25:15 - mmengine - INFO - Epoch(train) [276][15/63] lr: 2.7965e-03 eta: 14:07:39 time: 0.5769 data_time: 0.0105 memory: 16131 loss: 2.0603 loss_prob: 1.2226 loss_thr: 0.6414 loss_db: 0.1964 2022/10/25 23:25:20 - mmengine - INFO - Epoch(train) [276][20/63] lr: 2.7965e-03 eta: 14:07:28 time: 0.8001 data_time: 0.0052 memory: 16131 loss: 2.1143 loss_prob: 1.2616 loss_thr: 0.6450 loss_db: 0.2077 2022/10/25 23:25:24 - mmengine - INFO - Epoch(train) [276][25/63] lr: 2.7965e-03 eta: 14:07:28 time: 0.8864 data_time: 0.0260 memory: 16131 loss: 2.1559 loss_prob: 1.2936 loss_thr: 0.6479 loss_db: 0.2143 2022/10/25 23:25:30 - mmengine - INFO - Epoch(train) [276][30/63] lr: 2.7965e-03 eta: 14:07:21 time: 0.9416 data_time: 0.0363 memory: 16131 loss: 2.1526 loss_prob: 1.2814 loss_thr: 0.6598 loss_db: 0.2114 2022/10/25 23:25:34 - mmengine - INFO - Epoch(train) [276][35/63] lr: 2.7965e-03 eta: 14:07:21 time: 0.9740 data_time: 0.0214 memory: 16131 loss: 2.2054 loss_prob: 1.3376 loss_thr: 0.6509 loss_db: 0.2169 2022/10/25 23:25:37 - mmengine - INFO - Epoch(train) [276][40/63] lr: 2.7965e-03 eta: 14:07:09 time: 0.7810 data_time: 0.0154 memory: 16131 loss: 2.1738 loss_prob: 1.3132 loss_thr: 0.6505 loss_db: 0.2102 2022/10/25 23:25:44 - mmengine - INFO - Epoch(train) [276][45/63] lr: 2.7965e-03 eta: 14:07:09 time: 0.9955 data_time: 0.0103 memory: 16131 loss: 2.0397 loss_prob: 1.2034 loss_thr: 0.6416 loss_db: 0.1947 2022/10/25 23:25:51 - mmengine - INFO - Epoch(train) [276][50/63] lr: 2.7965e-03 eta: 14:07:15 time: 1.3151 data_time: 0.0367 memory: 16131 loss: 1.9264 loss_prob: 1.1384 loss_thr: 0.6045 loss_db: 0.1834 2022/10/25 23:25:57 - mmengine - INFO - Epoch(train) [276][55/63] lr: 2.7965e-03 eta: 14:07:15 time: 1.3644 data_time: 0.0410 memory: 16131 loss: 1.9308 loss_prob: 1.1459 loss_thr: 0.5990 loss_db: 0.1858 2022/10/25 23:26:03 - mmengine - INFO - Epoch(train) [276][60/63] lr: 2.7965e-03 eta: 14:07:20 time: 1.2717 data_time: 0.0178 memory: 16131 loss: 2.0118 loss_prob: 1.2004 loss_thr: 0.6123 loss_db: 0.1991 2022/10/25 23:26:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:26:14 - mmengine - INFO - Epoch(train) [277][5/63] lr: 2.7938e-03 eta: 14:07:20 time: 1.4094 data_time: 0.1734 memory: 16131 loss: 1.9173 loss_prob: 1.1274 loss_thr: 0.6067 loss_db: 0.1832 2022/10/25 23:26:18 - mmengine - INFO - Epoch(train) [277][10/63] lr: 2.7938e-03 eta: 14:07:11 time: 1.2031 data_time: 0.2041 memory: 16131 loss: 1.8184 loss_prob: 1.0387 loss_thr: 0.6093 loss_db: 0.1704 2022/10/25 23:26:23 - mmengine - INFO - Epoch(train) [277][15/63] lr: 2.7938e-03 eta: 14:07:11 time: 0.9095 data_time: 0.0429 memory: 16131 loss: 1.8180 loss_prob: 1.0457 loss_thr: 0.5998 loss_db: 0.1725 2022/10/25 23:26:29 - mmengine - INFO - Epoch(train) [277][20/63] lr: 2.7938e-03 eta: 14:07:09 time: 1.0647 data_time: 0.0161 memory: 16131 loss: 2.0022 loss_prob: 1.1771 loss_thr: 0.6377 loss_db: 0.1874 2022/10/25 23:26:33 - mmengine - INFO - Epoch(train) [277][25/63] lr: 2.7938e-03 eta: 14:07:09 time: 1.0061 data_time: 0.0169 memory: 16131 loss: 2.0278 loss_prob: 1.2052 loss_thr: 0.6293 loss_db: 0.1933 2022/10/25 23:26:36 - mmengine - INFO - Epoch(train) [277][30/63] lr: 2.7938e-03 eta: 14:06:55 time: 0.7212 data_time: 0.0365 memory: 16131 loss: 1.9071 loss_prob: 1.1239 loss_thr: 0.5964 loss_db: 0.1868 2022/10/25 23:26:39 - mmengine - INFO - Epoch(train) [277][35/63] lr: 2.7938e-03 eta: 14:06:55 time: 0.6023 data_time: 0.0372 memory: 16131 loss: 2.0343 loss_prob: 1.2065 loss_thr: 0.6289 loss_db: 0.1988 2022/10/25 23:26:43 - mmengine - INFO - Epoch(train) [277][40/63] lr: 2.7938e-03 eta: 14:06:40 time: 0.6962 data_time: 0.0138 memory: 16131 loss: 1.9363 loss_prob: 1.1557 loss_thr: 0.5934 loss_db: 0.1871 2022/10/25 23:26:47 - mmengine - INFO - Epoch(train) [277][45/63] lr: 2.7938e-03 eta: 14:06:40 time: 0.7351 data_time: 0.0094 memory: 16131 loss: 1.9487 loss_prob: 1.1620 loss_thr: 0.6007 loss_db: 0.1860 2022/10/25 23:26:50 - mmengine - INFO - Epoch(train) [277][50/63] lr: 2.7938e-03 eta: 14:06:26 time: 0.7017 data_time: 0.0168 memory: 16131 loss: 2.1542 loss_prob: 1.2942 loss_thr: 0.6537 loss_db: 0.2063 2022/10/25 23:26:56 - mmengine - INFO - Epoch(train) [277][55/63] lr: 2.7938e-03 eta: 14:06:26 time: 0.9151 data_time: 0.0263 memory: 16131 loss: 2.0089 loss_prob: 1.1878 loss_thr: 0.6307 loss_db: 0.1904 2022/10/25 23:27:01 - mmengine - INFO - Epoch(train) [277][60/63] lr: 2.7938e-03 eta: 14:06:25 time: 1.1287 data_time: 0.0149 memory: 16131 loss: 1.9864 loss_prob: 1.1737 loss_thr: 0.6201 loss_db: 0.1925 2022/10/25 23:27:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:27:08 - mmengine - INFO - Epoch(train) [278][5/63] lr: 2.7911e-03 eta: 14:06:25 time: 0.7631 data_time: 0.2111 memory: 16131 loss: 2.2160 loss_prob: 1.3642 loss_thr: 0.6249 loss_db: 0.2269 2022/10/25 23:27:12 - mmengine - INFO - Epoch(train) [278][10/63] lr: 2.7911e-03 eta: 14:06:06 time: 0.8895 data_time: 0.2119 memory: 16131 loss: 2.4671 loss_prob: 1.5504 loss_thr: 0.6645 loss_db: 0.2521 2022/10/25 23:27:16 - mmengine - INFO - Epoch(train) [278][15/63] lr: 2.7911e-03 eta: 14:06:06 time: 0.8126 data_time: 0.0101 memory: 16131 loss: 2.3491 loss_prob: 1.4458 loss_thr: 0.6731 loss_db: 0.2301 2022/10/25 23:27:22 - mmengine - INFO - Epoch(train) [278][20/63] lr: 2.7911e-03 eta: 14:06:03 time: 1.0562 data_time: 0.0104 memory: 16131 loss: 2.5065 loss_prob: 1.5505 loss_thr: 0.7041 loss_db: 0.2519 2022/10/25 23:27:25 - mmengine - INFO - Epoch(train) [278][25/63] lr: 2.7911e-03 eta: 14:06:03 time: 0.9576 data_time: 0.0421 memory: 16131 loss: 2.7754 loss_prob: 1.7630 loss_thr: 0.7287 loss_db: 0.2837 2022/10/25 23:27:31 - mmengine - INFO - Epoch(train) [278][30/63] lr: 2.7911e-03 eta: 14:05:54 time: 0.8598 data_time: 0.0425 memory: 16131 loss: 2.7154 loss_prob: 1.7165 loss_thr: 0.7233 loss_db: 0.2756 2022/10/25 23:27:36 - mmengine - INFO - Epoch(train) [278][35/63] lr: 2.7911e-03 eta: 14:05:54 time: 1.0199 data_time: 0.0075 memory: 16131 loss: 2.5714 loss_prob: 1.5922 loss_thr: 0.7163 loss_db: 0.2629 2022/10/25 23:27:38 - mmengine - INFO - Epoch(train) [278][40/63] lr: 2.7911e-03 eta: 14:05:41 time: 0.7465 data_time: 0.0064 memory: 16131 loss: 2.5223 loss_prob: 1.5588 loss_thr: 0.7060 loss_db: 0.2575 2022/10/25 23:27:43 - mmengine - INFO - Epoch(train) [278][45/63] lr: 2.7911e-03 eta: 14:05:41 time: 0.7159 data_time: 0.0063 memory: 16131 loss: 2.4890 loss_prob: 1.5462 loss_thr: 0.6948 loss_db: 0.2480 2022/10/25 23:27:46 - mmengine - INFO - Epoch(train) [278][50/63] lr: 2.7911e-03 eta: 14:05:30 time: 0.7910 data_time: 0.0242 memory: 16131 loss: 2.4477 loss_prob: 1.5154 loss_thr: 0.6841 loss_db: 0.2482 2022/10/25 23:27:50 - mmengine - INFO - Epoch(train) [278][55/63] lr: 2.7911e-03 eta: 14:05:30 time: 0.6705 data_time: 0.0240 memory: 16131 loss: 2.3772 loss_prob: 1.4587 loss_thr: 0.6740 loss_db: 0.2446 2022/10/25 23:27:52 - mmengine - INFO - Epoch(train) [278][60/63] lr: 2.7911e-03 eta: 14:05:12 time: 0.6004 data_time: 0.0059 memory: 16131 loss: 2.2248 loss_prob: 1.3370 loss_thr: 0.6702 loss_db: 0.2176 2022/10/25 23:27:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:28:00 - mmengine - INFO - Epoch(train) [279][5/63] lr: 2.7883e-03 eta: 14:05:12 time: 0.8947 data_time: 0.2146 memory: 16131 loss: 2.1179 loss_prob: 1.2598 loss_thr: 0.6481 loss_db: 0.2100 2022/10/25 23:28:05 - mmengine - INFO - Epoch(train) [279][10/63] lr: 2.7883e-03 eta: 14:05:01 time: 1.1598 data_time: 0.2163 memory: 16131 loss: 2.0318 loss_prob: 1.2019 loss_thr: 0.6347 loss_db: 0.1951 2022/10/25 23:28:09 - mmengine - INFO - Epoch(train) [279][15/63] lr: 2.7883e-03 eta: 14:05:01 time: 0.9029 data_time: 0.0067 memory: 16131 loss: 2.0606 loss_prob: 1.2207 loss_thr: 0.6437 loss_db: 0.1961 2022/10/25 23:28:13 - mmengine - INFO - Epoch(train) [279][20/63] lr: 2.7883e-03 eta: 14:04:50 time: 0.7914 data_time: 0.0075 memory: 16131 loss: 2.0149 loss_prob: 1.1927 loss_thr: 0.6262 loss_db: 0.1960 2022/10/25 23:28:17 - mmengine - INFO - Epoch(train) [279][25/63] lr: 2.7883e-03 eta: 14:04:50 time: 0.7967 data_time: 0.0313 memory: 16131 loss: 1.9988 loss_prob: 1.1990 loss_thr: 0.6009 loss_db: 0.1989 2022/10/25 23:28:22 - mmengine - INFO - Epoch(train) [279][30/63] lr: 2.7883e-03 eta: 14:04:41 time: 0.8521 data_time: 0.0367 memory: 16131 loss: 1.9831 loss_prob: 1.1900 loss_thr: 0.5959 loss_db: 0.1971 2022/10/25 23:28:26 - mmengine - INFO - Epoch(train) [279][35/63] lr: 2.7883e-03 eta: 14:04:41 time: 0.9273 data_time: 0.0142 memory: 16131 loss: 1.9770 loss_prob: 1.1735 loss_thr: 0.6125 loss_db: 0.1910 2022/10/25 23:28:29 - mmengine - INFO - Epoch(train) [279][40/63] lr: 2.7883e-03 eta: 14:04:28 time: 0.7659 data_time: 0.0110 memory: 16131 loss: 2.3990 loss_prob: 1.4932 loss_thr: 0.6641 loss_db: 0.2417 2022/10/25 23:28:35 - mmengine - INFO - Epoch(train) [279][45/63] lr: 2.7883e-03 eta: 14:04:28 time: 0.8963 data_time: 0.0108 memory: 16131 loss: 2.4515 loss_prob: 1.5300 loss_thr: 0.6719 loss_db: 0.2496 2022/10/25 23:28:40 - mmengine - INFO - Epoch(train) [279][50/63] lr: 2.7883e-03 eta: 14:04:25 time: 1.0525 data_time: 0.0228 memory: 16131 loss: 2.1527 loss_prob: 1.2946 loss_thr: 0.6486 loss_db: 0.2095 2022/10/25 23:28:43 - mmengine - INFO - Epoch(train) [279][55/63] lr: 2.7883e-03 eta: 14:04:25 time: 0.7499 data_time: 0.0247 memory: 16131 loss: 2.0314 loss_prob: 1.2015 loss_thr: 0.6370 loss_db: 0.1929 2022/10/25 23:28:46 - mmengine - INFO - Epoch(train) [279][60/63] lr: 2.7883e-03 eta: 14:04:09 time: 0.6443 data_time: 0.0091 memory: 16131 loss: 1.9143 loss_prob: 1.1185 loss_thr: 0.6146 loss_db: 0.1812 2022/10/25 23:28:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:28:56 - mmengine - INFO - Epoch(train) [280][5/63] lr: 2.7856e-03 eta: 14:04:09 time: 1.1284 data_time: 0.1593 memory: 16131 loss: 1.9239 loss_prob: 1.1362 loss_thr: 0.6005 loss_db: 0.1872 2022/10/25 23:28:58 - mmengine - INFO - Epoch(train) [280][10/63] lr: 2.7856e-03 eta: 14:03:50 time: 0.8830 data_time: 0.1633 memory: 16131 loss: 2.0414 loss_prob: 1.2048 loss_thr: 0.6395 loss_db: 0.1971 2022/10/25 23:29:03 - mmengine - INFO - Epoch(train) [280][15/63] lr: 2.7856e-03 eta: 14:03:50 time: 0.7743 data_time: 0.0129 memory: 16131 loss: 1.9198 loss_prob: 1.1044 loss_thr: 0.6371 loss_db: 0.1783 2022/10/25 23:29:06 - mmengine - INFO - Epoch(train) [280][20/63] lr: 2.7856e-03 eta: 14:03:39 time: 0.8060 data_time: 0.0124 memory: 16131 loss: 1.8655 loss_prob: 1.0698 loss_thr: 0.6229 loss_db: 0.1727 2022/10/25 23:29:10 - mmengine - INFO - Epoch(train) [280][25/63] lr: 2.7856e-03 eta: 14:03:39 time: 0.6119 data_time: 0.0192 memory: 16131 loss: 1.9422 loss_prob: 1.1291 loss_thr: 0.6298 loss_db: 0.1833 2022/10/25 23:29:14 - mmengine - INFO - Epoch(train) [280][30/63] lr: 2.7856e-03 eta: 14:03:27 time: 0.7797 data_time: 0.0290 memory: 16131 loss: 2.2234 loss_prob: 1.3556 loss_thr: 0.6505 loss_db: 0.2173 2022/10/25 23:29:19 - mmengine - INFO - Epoch(train) [280][35/63] lr: 2.7856e-03 eta: 14:03:27 time: 0.9242 data_time: 0.0231 memory: 16131 loss: 2.3673 loss_prob: 1.4595 loss_thr: 0.6739 loss_db: 0.2339 2022/10/25 23:29:21 - mmengine - INFO - Epoch(train) [280][40/63] lr: 2.7856e-03 eta: 14:03:13 time: 0.7271 data_time: 0.0151 memory: 16131 loss: 2.1499 loss_prob: 1.2857 loss_thr: 0.6587 loss_db: 0.2055 2022/10/25 23:29:24 - mmengine - INFO - Epoch(train) [280][45/63] lr: 2.7856e-03 eta: 14:03:13 time: 0.5405 data_time: 0.0133 memory: 16131 loss: 2.1435 loss_prob: 1.2836 loss_thr: 0.6566 loss_db: 0.2034 2022/10/25 23:29:27 - mmengine - INFO - Epoch(train) [280][50/63] lr: 2.7856e-03 eta: 14:02:54 time: 0.5619 data_time: 0.0205 memory: 16131 loss: 2.1207 loss_prob: 1.2613 loss_thr: 0.6551 loss_db: 0.2043 2022/10/25 23:29:30 - mmengine - INFO - Epoch(train) [280][55/63] lr: 2.7856e-03 eta: 14:02:54 time: 0.5774 data_time: 0.0224 memory: 16131 loss: 1.9554 loss_prob: 1.1634 loss_thr: 0.6004 loss_db: 0.1915 2022/10/25 23:29:33 - mmengine - INFO - Epoch(train) [280][60/63] lr: 2.7856e-03 eta: 14:02:36 time: 0.5901 data_time: 0.0123 memory: 16131 loss: 2.0717 loss_prob: 1.2463 loss_thr: 0.6178 loss_db: 0.2076 2022/10/25 23:29:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:29:34 - mmengine - INFO - Saving checkpoint at 280 epochs 2022/10/25 23:29:41 - mmengine - INFO - Epoch(val) [280][5/32] eta: 14:02:36 time: 0.5486 data_time: 0.0758 memory: 16131 2022/10/25 23:29:44 - mmengine - INFO - Epoch(val) [280][10/32] eta: 0:00:13 time: 0.6039 data_time: 0.1041 memory: 15724 2022/10/25 23:29:47 - mmengine - INFO - Epoch(val) [280][15/32] eta: 0:00:13 time: 0.5529 data_time: 0.0468 memory: 15724 2022/10/25 23:29:50 - mmengine - INFO - Epoch(val) [280][20/32] eta: 0:00:06 time: 0.5660 data_time: 0.0548 memory: 15724 2022/10/25 23:29:53 - mmengine - INFO - Epoch(val) [280][25/32] eta: 0:00:06 time: 0.5847 data_time: 0.0635 memory: 15724 2022/10/25 23:29:55 - mmengine - INFO - Epoch(val) [280][30/32] eta: 0:00:01 time: 0.5438 data_time: 0.0232 memory: 15724 2022/10/25 23:29:56 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7776, precision: 0.6991, hmean: 0.7363 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7771, precision: 0.7771, hmean: 0.7771 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7723, precision: 0.8247, hmean: 0.7976 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7424, precision: 0.8816, hmean: 0.8061 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6100, precision: 0.9275, hmean: 0.7360 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1358, precision: 0.9431, hmean: 0.2374 2022/10/25 23:29:56 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 23:29:56 - mmengine - INFO - Epoch(val) [280][32/32] icdar/precision: 0.8816 icdar/recall: 0.7424 icdar/hmean: 0.8061 2022/10/25 23:30:04 - mmengine - INFO - Epoch(train) [281][5/63] lr: 2.7829e-03 eta: 0:00:01 time: 1.0638 data_time: 0.2289 memory: 16131 loss: 1.9768 loss_prob: 1.1734 loss_thr: 0.6129 loss_db: 0.1906 2022/10/25 23:30:11 - mmengine - INFO - Epoch(train) [281][10/63] lr: 2.7829e-03 eta: 14:02:39 time: 1.5500 data_time: 0.2283 memory: 16131 loss: 1.9131 loss_prob: 1.1333 loss_thr: 0.5956 loss_db: 0.1842 2022/10/25 23:30:14 - mmengine - INFO - Epoch(train) [281][15/63] lr: 2.7829e-03 eta: 14:02:39 time: 0.9810 data_time: 0.0066 memory: 16131 loss: 2.0269 loss_prob: 1.2203 loss_thr: 0.6046 loss_db: 0.2021 2022/10/25 23:30:18 - mmengine - INFO - Epoch(train) [281][20/63] lr: 2.7829e-03 eta: 14:02:23 time: 0.6558 data_time: 0.0069 memory: 16131 loss: 1.9742 loss_prob: 1.1884 loss_thr: 0.5957 loss_db: 0.1901 2022/10/25 23:30:21 - mmengine - INFO - Epoch(train) [281][25/63] lr: 2.7829e-03 eta: 14:02:23 time: 0.6660 data_time: 0.0115 memory: 16131 loss: 1.9381 loss_prob: 1.1493 loss_thr: 0.6052 loss_db: 0.1837 2022/10/25 23:30:25 - mmengine - INFO - Epoch(train) [281][30/63] lr: 2.7829e-03 eta: 14:02:08 time: 0.6774 data_time: 0.0402 memory: 16131 loss: 1.9806 loss_prob: 1.1606 loss_thr: 0.6265 loss_db: 0.1935 2022/10/25 23:30:29 - mmengine - INFO - Epoch(train) [281][35/63] lr: 2.7829e-03 eta: 14:02:08 time: 0.8184 data_time: 0.0340 memory: 16131 loss: 2.2139 loss_prob: 1.3400 loss_thr: 0.6539 loss_db: 0.2200 2022/10/25 23:30:31 - mmengine - INFO - Epoch(train) [281][40/63] lr: 2.7829e-03 eta: 14:01:52 time: 0.6696 data_time: 0.0051 memory: 16131 loss: 2.3517 loss_prob: 1.4335 loss_thr: 0.6855 loss_db: 0.2327 2022/10/25 23:30:34 - mmengine - INFO - Epoch(train) [281][45/63] lr: 2.7829e-03 eta: 14:01:52 time: 0.5174 data_time: 0.0112 memory: 16131 loss: 2.0852 loss_prob: 1.2335 loss_thr: 0.6450 loss_db: 0.2067 2022/10/25 23:30:37 - mmengine - INFO - Epoch(train) [281][50/63] lr: 2.7829e-03 eta: 14:01:32 time: 0.5179 data_time: 0.0225 memory: 16131 loss: 1.9944 loss_prob: 1.1575 loss_thr: 0.6431 loss_db: 0.1939 2022/10/25 23:30:39 - mmengine - INFO - Epoch(train) [281][55/63] lr: 2.7829e-03 eta: 14:01:32 time: 0.5302 data_time: 0.0267 memory: 16131 loss: 2.0229 loss_prob: 1.1889 loss_thr: 0.6389 loss_db: 0.1951 2022/10/25 23:30:42 - mmengine - INFO - Epoch(train) [281][60/63] lr: 2.7829e-03 eta: 14:01:12 time: 0.5392 data_time: 0.0189 memory: 16131 loss: 2.2451 loss_prob: 1.3769 loss_thr: 0.6528 loss_db: 0.2155 2022/10/25 23:30:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:30:51 - mmengine - INFO - Epoch(train) [282][5/63] lr: 2.7802e-03 eta: 14:01:12 time: 0.9792 data_time: 0.2036 memory: 16131 loss: 2.3293 loss_prob: 1.4489 loss_thr: 0.6463 loss_db: 0.2341 2022/10/25 23:30:53 - mmengine - INFO - Epoch(train) [282][10/63] lr: 2.7802e-03 eta: 14:00:57 time: 0.9998 data_time: 0.2076 memory: 16131 loss: 2.1212 loss_prob: 1.2821 loss_thr: 0.6312 loss_db: 0.2079 2022/10/25 23:30:57 - mmengine - INFO - Epoch(train) [282][15/63] lr: 2.7802e-03 eta: 14:00:57 time: 0.5897 data_time: 0.0100 memory: 16131 loss: 2.0935 loss_prob: 1.2514 loss_thr: 0.6349 loss_db: 0.2071 2022/10/25 23:31:00 - mmengine - INFO - Epoch(train) [282][20/63] lr: 2.7802e-03 eta: 14:00:41 time: 0.6571 data_time: 0.0084 memory: 16131 loss: 2.1975 loss_prob: 1.3266 loss_thr: 0.6510 loss_db: 0.2198 2022/10/25 23:31:05 - mmengine - INFO - Epoch(train) [282][25/63] lr: 2.7802e-03 eta: 14:00:41 time: 0.8105 data_time: 0.0135 memory: 16131 loss: 2.0813 loss_prob: 1.2365 loss_thr: 0.6465 loss_db: 0.1984 2022/10/25 23:31:09 - mmengine - INFO - Epoch(train) [282][30/63] lr: 2.7802e-03 eta: 14:00:32 time: 0.8533 data_time: 0.0329 memory: 16131 loss: 1.9262 loss_prob: 1.1261 loss_thr: 0.6218 loss_db: 0.1783 2022/10/25 23:31:13 - mmengine - INFO - Epoch(train) [282][35/63] lr: 2.7802e-03 eta: 14:00:32 time: 0.8203 data_time: 0.0297 memory: 16131 loss: 1.9597 loss_prob: 1.1575 loss_thr: 0.6207 loss_db: 0.1815 2022/10/25 23:31:16 - mmengine - INFO - Epoch(train) [282][40/63] lr: 2.7802e-03 eta: 14:00:20 time: 0.7727 data_time: 0.0081 memory: 16131 loss: 1.9033 loss_prob: 1.1244 loss_thr: 0.5999 loss_db: 0.1790 2022/10/25 23:31:20 - mmengine - INFO - Epoch(train) [282][45/63] lr: 2.7802e-03 eta: 14:00:20 time: 0.7428 data_time: 0.0049 memory: 16131 loss: 1.8688 loss_prob: 1.0984 loss_thr: 0.5928 loss_db: 0.1776 2022/10/25 23:31:25 - mmengine - INFO - Epoch(train) [282][50/63] lr: 2.7802e-03 eta: 14:00:10 time: 0.8286 data_time: 0.0097 memory: 16131 loss: 2.0092 loss_prob: 1.2103 loss_thr: 0.5995 loss_db: 0.1994 2022/10/25 23:31:28 - mmengine - INFO - Epoch(train) [282][55/63] lr: 2.7802e-03 eta: 14:00:10 time: 0.7910 data_time: 0.0192 memory: 16131 loss: 2.0711 loss_prob: 1.2510 loss_thr: 0.6185 loss_db: 0.2016 2022/10/25 23:31:33 - mmengine - INFO - Epoch(train) [282][60/63] lr: 2.7802e-03 eta: 13:59:59 time: 0.8101 data_time: 0.0203 memory: 16131 loss: 1.9888 loss_prob: 1.1800 loss_thr: 0.6210 loss_db: 0.1879 2022/10/25 23:31:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:31:40 - mmengine - INFO - Epoch(train) [283][5/63] lr: 2.7774e-03 eta: 13:59:59 time: 1.0381 data_time: 0.1914 memory: 16131 loss: 2.2830 loss_prob: 1.4097 loss_thr: 0.6464 loss_db: 0.2269 2022/10/25 23:31:43 - mmengine - INFO - Epoch(train) [283][10/63] lr: 2.7774e-03 eta: 13:59:38 time: 0.8388 data_time: 0.1921 memory: 16131 loss: 2.3094 loss_prob: 1.4279 loss_thr: 0.6508 loss_db: 0.2307 2022/10/25 23:31:46 - mmengine - INFO - Epoch(train) [283][15/63] lr: 2.7774e-03 eta: 13:59:38 time: 0.5609 data_time: 0.0122 memory: 16131 loss: 2.0470 loss_prob: 1.2157 loss_thr: 0.6355 loss_db: 0.1958 2022/10/25 23:31:49 - mmengine - INFO - Epoch(train) [283][20/63] lr: 2.7774e-03 eta: 13:59:19 time: 0.5554 data_time: 0.0146 memory: 16131 loss: 1.9166 loss_prob: 1.1265 loss_thr: 0.6116 loss_db: 0.1785 2022/10/25 23:31:52 - mmengine - INFO - Epoch(train) [283][25/63] lr: 2.7774e-03 eta: 13:59:19 time: 0.5731 data_time: 0.0295 memory: 16131 loss: 1.7725 loss_prob: 1.0192 loss_thr: 0.5885 loss_db: 0.1649 2022/10/25 23:31:54 - mmengine - INFO - Epoch(train) [283][30/63] lr: 2.7774e-03 eta: 13:59:00 time: 0.5485 data_time: 0.0269 memory: 16131 loss: 1.9117 loss_prob: 1.1356 loss_thr: 0.5914 loss_db: 0.1847 2022/10/25 23:31:57 - mmengine - INFO - Epoch(train) [283][35/63] lr: 2.7774e-03 eta: 13:59:00 time: 0.4913 data_time: 0.0077 memory: 16131 loss: 2.0626 loss_prob: 1.2430 loss_thr: 0.6151 loss_db: 0.2046 2022/10/25 23:32:00 - mmengine - INFO - Epoch(train) [283][40/63] lr: 2.7774e-03 eta: 13:58:40 time: 0.5298 data_time: 0.0075 memory: 16131 loss: 2.0551 loss_prob: 1.2282 loss_thr: 0.6235 loss_db: 0.2033 2022/10/25 23:32:04 - mmengine - INFO - Epoch(train) [283][45/63] lr: 2.7774e-03 eta: 13:58:40 time: 0.7381 data_time: 0.0120 memory: 16131 loss: 1.9357 loss_prob: 1.1563 loss_thr: 0.5923 loss_db: 0.1871 2022/10/25 23:32:07 - mmengine - INFO - Epoch(train) [283][50/63] lr: 2.7774e-03 eta: 13:58:27 time: 0.7230 data_time: 0.0427 memory: 16131 loss: 1.9219 loss_prob: 1.1329 loss_thr: 0.6068 loss_db: 0.1823 2022/10/25 23:32:10 - mmengine - INFO - Epoch(train) [283][55/63] lr: 2.7774e-03 eta: 13:58:27 time: 0.6380 data_time: 0.0379 memory: 16131 loss: 2.0349 loss_prob: 1.2055 loss_thr: 0.6348 loss_db: 0.1946 2022/10/25 23:32:16 - mmengine - INFO - Epoch(train) [283][60/63] lr: 2.7774e-03 eta: 13:58:18 time: 0.8803 data_time: 0.0094 memory: 16131 loss: 1.9981 loss_prob: 1.1836 loss_thr: 0.6187 loss_db: 0.1958 2022/10/25 23:32:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:32:23 - mmengine - INFO - Epoch(train) [284][5/63] lr: 2.7747e-03 eta: 13:58:18 time: 0.9743 data_time: 0.1592 memory: 16131 loss: 2.1405 loss_prob: 1.2873 loss_thr: 0.6403 loss_db: 0.2130 2022/10/25 23:32:27 - mmengine - INFO - Epoch(train) [284][10/63] lr: 2.7747e-03 eta: 13:58:00 time: 0.9319 data_time: 0.1593 memory: 16131 loss: 2.1969 loss_prob: 1.3093 loss_thr: 0.6763 loss_db: 0.2113 2022/10/25 23:32:31 - mmengine - INFO - Epoch(train) [284][15/63] lr: 2.7747e-03 eta: 13:58:00 time: 0.7771 data_time: 0.0087 memory: 16131 loss: 2.0179 loss_prob: 1.1759 loss_thr: 0.6507 loss_db: 0.1913 2022/10/25 23:32:34 - mmengine - INFO - Epoch(train) [284][20/63] lr: 2.7747e-03 eta: 13:57:47 time: 0.7172 data_time: 0.0082 memory: 16131 loss: 2.0220 loss_prob: 1.2146 loss_thr: 0.6088 loss_db: 0.1986 2022/10/25 23:32:36 - mmengine - INFO - Epoch(train) [284][25/63] lr: 2.7747e-03 eta: 13:57:47 time: 0.5179 data_time: 0.0066 memory: 16131 loss: 2.0327 loss_prob: 1.2294 loss_thr: 0.6029 loss_db: 0.2004 2022/10/25 23:32:40 - mmengine - INFO - Epoch(train) [284][30/63] lr: 2.7747e-03 eta: 13:57:30 time: 0.6301 data_time: 0.0332 memory: 16131 loss: 1.9846 loss_prob: 1.1778 loss_thr: 0.6155 loss_db: 0.1913 2022/10/25 23:32:44 - mmengine - INFO - Epoch(train) [284][35/63] lr: 2.7747e-03 eta: 13:57:30 time: 0.7872 data_time: 0.0319 memory: 16131 loss: 2.0443 loss_prob: 1.2100 loss_thr: 0.6372 loss_db: 0.1971 2022/10/25 23:32:47 - mmengine - INFO - Epoch(train) [284][40/63] lr: 2.7747e-03 eta: 13:57:17 time: 0.7258 data_time: 0.0075 memory: 16131 loss: 2.0384 loss_prob: 1.2075 loss_thr: 0.6276 loss_db: 0.2032 2022/10/25 23:32:50 - mmengine - INFO - Epoch(train) [284][45/63] lr: 2.7747e-03 eta: 13:57:17 time: 0.6105 data_time: 0.0094 memory: 16131 loss: 2.0516 loss_prob: 1.2097 loss_thr: 0.6381 loss_db: 0.2038 2022/10/25 23:32:55 - mmengine - INFO - Epoch(train) [284][50/63] lr: 2.7747e-03 eta: 13:57:04 time: 0.7340 data_time: 0.0259 memory: 16131 loss: 1.9961 loss_prob: 1.1643 loss_thr: 0.6382 loss_db: 0.1936 2022/10/25 23:32:57 - mmengine - INFO - Epoch(train) [284][55/63] lr: 2.7747e-03 eta: 13:57:04 time: 0.7056 data_time: 0.0238 memory: 16131 loss: 1.9557 loss_prob: 1.1352 loss_thr: 0.6365 loss_db: 0.1840 2022/10/25 23:33:02 - mmengine - INFO - Epoch(train) [284][60/63] lr: 2.7747e-03 eta: 13:56:50 time: 0.7035 data_time: 0.0051 memory: 16131 loss: 2.0699 loss_prob: 1.2519 loss_thr: 0.6255 loss_db: 0.1925 2022/10/25 23:33:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:33:10 - mmengine - INFO - Epoch(train) [285][5/63] lr: 2.7720e-03 eta: 13:56:50 time: 1.0807 data_time: 0.1743 memory: 16131 loss: 1.9041 loss_prob: 1.1117 loss_thr: 0.6131 loss_db: 0.1793 2022/10/25 23:33:13 - mmengine - INFO - Epoch(train) [285][10/63] lr: 2.7720e-03 eta: 13:56:32 time: 0.9174 data_time: 0.1749 memory: 16131 loss: 1.9878 loss_prob: 1.1699 loss_thr: 0.6290 loss_db: 0.1888 2022/10/25 23:33:18 - mmengine - INFO - Epoch(train) [285][15/63] lr: 2.7720e-03 eta: 13:56:32 time: 0.7928 data_time: 0.0078 memory: 16131 loss: 1.8141 loss_prob: 1.0462 loss_thr: 0.5962 loss_db: 0.1717 2022/10/25 23:33:21 - mmengine - INFO - Epoch(train) [285][20/63] lr: 2.7720e-03 eta: 13:56:20 time: 0.7851 data_time: 0.0102 memory: 16131 loss: 1.8114 loss_prob: 1.0556 loss_thr: 0.5822 loss_db: 0.1736 2022/10/25 23:33:24 - mmengine - INFO - Epoch(train) [285][25/63] lr: 2.7720e-03 eta: 13:56:20 time: 0.5801 data_time: 0.0166 memory: 16131 loss: 1.8672 loss_prob: 1.1041 loss_thr: 0.5822 loss_db: 0.1809 2022/10/25 23:33:27 - mmengine - INFO - Epoch(train) [285][30/63] lr: 2.7720e-03 eta: 13:56:03 time: 0.6146 data_time: 0.0354 memory: 16131 loss: 1.9171 loss_prob: 1.1297 loss_thr: 0.6028 loss_db: 0.1846 2022/10/25 23:33:31 - mmengine - INFO - Epoch(train) [285][35/63] lr: 2.7720e-03 eta: 13:56:03 time: 0.6860 data_time: 0.0269 memory: 16131 loss: 1.8683 loss_prob: 1.0927 loss_thr: 0.5967 loss_db: 0.1789 2022/10/25 23:33:34 - mmengine - INFO - Epoch(train) [285][40/63] lr: 2.7720e-03 eta: 13:55:48 time: 0.6532 data_time: 0.0058 memory: 16131 loss: 1.8455 loss_prob: 1.0732 loss_thr: 0.5947 loss_db: 0.1776 2022/10/25 23:33:38 - mmengine - INFO - Epoch(train) [285][45/63] lr: 2.7720e-03 eta: 13:55:48 time: 0.7481 data_time: 0.0076 memory: 16131 loss: 1.9990 loss_prob: 1.1746 loss_thr: 0.6321 loss_db: 0.1923 2022/10/25 23:33:41 - mmengine - INFO - Epoch(train) [285][50/63] lr: 2.7720e-03 eta: 13:55:34 time: 0.7321 data_time: 0.0321 memory: 16131 loss: 1.9749 loss_prob: 1.1623 loss_thr: 0.6256 loss_db: 0.1870 2022/10/25 23:33:44 - mmengine - INFO - Epoch(train) [285][55/63] lr: 2.7720e-03 eta: 13:55:34 time: 0.6256 data_time: 0.0312 memory: 16131 loss: 1.8677 loss_prob: 1.0952 loss_thr: 0.5914 loss_db: 0.1810 2022/10/25 23:33:47 - mmengine - INFO - Epoch(train) [285][60/63] lr: 2.7720e-03 eta: 13:55:17 time: 0.6120 data_time: 0.0096 memory: 16131 loss: 1.9284 loss_prob: 1.1323 loss_thr: 0.6045 loss_db: 0.1916 2022/10/25 23:33:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:33:54 - mmengine - INFO - Epoch(train) [286][5/63] lr: 2.7693e-03 eta: 13:55:17 time: 0.8319 data_time: 0.1929 memory: 16131 loss: 2.1953 loss_prob: 1.3395 loss_thr: 0.6361 loss_db: 0.2197 2022/10/25 23:33:58 - mmengine - INFO - Epoch(train) [286][10/63] lr: 2.7693e-03 eta: 13:55:01 time: 0.9781 data_time: 0.1972 memory: 16131 loss: 1.9595 loss_prob: 1.1554 loss_thr: 0.6091 loss_db: 0.1950 2022/10/25 23:34:05 - mmengine - INFO - Epoch(train) [286][15/63] lr: 2.7693e-03 eta: 13:55:01 time: 1.0220 data_time: 0.0122 memory: 16131 loss: 1.8214 loss_prob: 1.0708 loss_thr: 0.5775 loss_db: 0.1731 2022/10/25 23:34:11 - mmengine - INFO - Epoch(train) [286][20/63] lr: 2.7693e-03 eta: 13:55:06 time: 1.2910 data_time: 0.0090 memory: 16131 loss: 1.9893 loss_prob: 1.1906 loss_thr: 0.6046 loss_db: 0.1940 2022/10/25 23:34:15 - mmengine - INFO - Epoch(train) [286][25/63] lr: 2.7693e-03 eta: 13:55:06 time: 1.0448 data_time: 0.0190 memory: 16131 loss: 2.1713 loss_prob: 1.2817 loss_thr: 0.6784 loss_db: 0.2113 2022/10/25 23:34:19 - mmengine - INFO - Epoch(train) [286][30/63] lr: 2.7693e-03 eta: 13:54:55 time: 0.8047 data_time: 0.0313 memory: 16131 loss: 1.9454 loss_prob: 1.1191 loss_thr: 0.6440 loss_db: 0.1823 2022/10/25 23:34:23 - mmengine - INFO - Epoch(train) [286][35/63] lr: 2.7693e-03 eta: 13:54:55 time: 0.7801 data_time: 0.0204 memory: 16131 loss: 1.8103 loss_prob: 1.0380 loss_thr: 0.6029 loss_db: 0.1694 2022/10/25 23:34:26 - mmengine - INFO - Epoch(train) [286][40/63] lr: 2.7693e-03 eta: 13:54:40 time: 0.6662 data_time: 0.0073 memory: 16131 loss: 1.8584 loss_prob: 1.0741 loss_thr: 0.6074 loss_db: 0.1769 2022/10/25 23:34:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:34:31 - mmengine - INFO - Epoch(train) [286][45/63] lr: 2.7693e-03 eta: 13:54:40 time: 0.7587 data_time: 0.0066 memory: 16131 loss: 1.9220 loss_prob: 1.1244 loss_thr: 0.6155 loss_db: 0.1821 2022/10/25 23:34:34 - mmengine - INFO - Epoch(train) [286][50/63] lr: 2.7693e-03 eta: 13:54:28 time: 0.7621 data_time: 0.0184 memory: 16131 loss: 2.0092 loss_prob: 1.1909 loss_thr: 0.6262 loss_db: 0.1921 2022/10/25 23:34:37 - mmengine - INFO - Epoch(train) [286][55/63] lr: 2.7693e-03 eta: 13:54:28 time: 0.6465 data_time: 0.0217 memory: 16131 loss: 1.9395 loss_prob: 1.1468 loss_thr: 0.6055 loss_db: 0.1872 2022/10/25 23:34:41 - mmengine - INFO - Epoch(train) [286][60/63] lr: 2.7693e-03 eta: 13:54:14 time: 0.7135 data_time: 0.0095 memory: 16131 loss: 1.9889 loss_prob: 1.1935 loss_thr: 0.6070 loss_db: 0.1884 2022/10/25 23:34:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:34:48 - mmengine - INFO - Epoch(train) [287][5/63] lr: 2.7665e-03 eta: 13:54:14 time: 0.9161 data_time: 0.1743 memory: 16131 loss: 2.3586 loss_prob: 1.4825 loss_thr: 0.6506 loss_db: 0.2255 2022/10/25 23:34:52 - mmengine - INFO - Epoch(train) [287][10/63] lr: 2.7665e-03 eta: 13:53:56 time: 0.8988 data_time: 0.1852 memory: 16131 loss: 1.9050 loss_prob: 1.1163 loss_thr: 0.6055 loss_db: 0.1831 2022/10/25 23:34:55 - mmengine - INFO - Epoch(train) [287][15/63] lr: 2.7665e-03 eta: 13:53:56 time: 0.6257 data_time: 0.0191 memory: 16131 loss: 1.9943 loss_prob: 1.1718 loss_thr: 0.6306 loss_db: 0.1920 2022/10/25 23:34:58 - mmengine - INFO - Epoch(train) [287][20/63] lr: 2.7665e-03 eta: 13:53:38 time: 0.5754 data_time: 0.0081 memory: 16131 loss: 1.9484 loss_prob: 1.1428 loss_thr: 0.6182 loss_db: 0.1874 2022/10/25 23:35:02 - mmengine - INFO - Epoch(train) [287][25/63] lr: 2.7665e-03 eta: 13:53:38 time: 0.6907 data_time: 0.0189 memory: 16131 loss: 1.9442 loss_prob: 1.1513 loss_thr: 0.6022 loss_db: 0.1906 2022/10/25 23:35:05 - mmengine - INFO - Epoch(train) [287][30/63] lr: 2.7665e-03 eta: 13:53:25 time: 0.7610 data_time: 0.0269 memory: 16131 loss: 2.0932 loss_prob: 1.2607 loss_thr: 0.6293 loss_db: 0.2032 2022/10/25 23:35:08 - mmengine - INFO - Epoch(train) [287][35/63] lr: 2.7665e-03 eta: 13:53:25 time: 0.6154 data_time: 0.0179 memory: 16131 loss: 2.0681 loss_prob: 1.2338 loss_thr: 0.6372 loss_db: 0.1971 2022/10/25 23:35:10 - mmengine - INFO - Epoch(train) [287][40/63] lr: 2.7665e-03 eta: 13:53:06 time: 0.5143 data_time: 0.0108 memory: 16131 loss: 1.8903 loss_prob: 1.0968 loss_thr: 0.6150 loss_db: 0.1785 2022/10/25 23:35:14 - mmengine - INFO - Epoch(train) [287][45/63] lr: 2.7665e-03 eta: 13:53:06 time: 0.6076 data_time: 0.0104 memory: 16131 loss: 1.7584 loss_prob: 1.0129 loss_thr: 0.5801 loss_db: 0.1654 2022/10/25 23:35:17 - mmengine - INFO - Epoch(train) [287][50/63] lr: 2.7665e-03 eta: 13:52:50 time: 0.6657 data_time: 0.0171 memory: 16131 loss: 1.7754 loss_prob: 1.0418 loss_thr: 0.5643 loss_db: 0.1693 2022/10/25 23:35:21 - mmengine - INFO - Epoch(train) [287][55/63] lr: 2.7665e-03 eta: 13:52:50 time: 0.6733 data_time: 0.0214 memory: 16131 loss: 1.9629 loss_prob: 1.1722 loss_thr: 0.6004 loss_db: 0.1904 2022/10/25 23:35:25 - mmengine - INFO - Epoch(train) [287][60/63] lr: 2.7665e-03 eta: 13:52:38 time: 0.7634 data_time: 0.0145 memory: 16131 loss: 1.9839 loss_prob: 1.1729 loss_thr: 0.6223 loss_db: 0.1887 2022/10/25 23:35:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:35:32 - mmengine - INFO - Epoch(train) [288][5/63] lr: 2.7638e-03 eta: 13:52:38 time: 1.0115 data_time: 0.1911 memory: 16131 loss: 1.7937 loss_prob: 1.0299 loss_thr: 0.5965 loss_db: 0.1672 2022/10/25 23:35:35 - mmengine - INFO - Epoch(train) [288][10/63] lr: 2.7638e-03 eta: 13:52:20 time: 0.9090 data_time: 0.1895 memory: 16131 loss: 1.8996 loss_prob: 1.1098 loss_thr: 0.6141 loss_db: 0.1757 2022/10/25 23:35:38 - mmengine - INFO - Epoch(train) [288][15/63] lr: 2.7638e-03 eta: 13:52:20 time: 0.5222 data_time: 0.0060 memory: 16131 loss: 1.8294 loss_prob: 1.0746 loss_thr: 0.5847 loss_db: 0.1701 2022/10/25 23:35:41 - mmengine - INFO - Epoch(train) [288][20/63] lr: 2.7638e-03 eta: 13:52:04 time: 0.6409 data_time: 0.0091 memory: 16131 loss: 1.7206 loss_prob: 0.9848 loss_thr: 0.5759 loss_db: 0.1598 2022/10/25 23:35:45 - mmengine - INFO - Epoch(train) [288][25/63] lr: 2.7638e-03 eta: 13:52:04 time: 0.7044 data_time: 0.0181 memory: 16131 loss: 1.8238 loss_prob: 1.0450 loss_thr: 0.6110 loss_db: 0.1678 2022/10/25 23:35:47 - mmengine - INFO - Epoch(train) [288][30/63] lr: 2.7638e-03 eta: 13:51:47 time: 0.5882 data_time: 0.0383 memory: 16131 loss: 1.8863 loss_prob: 1.0819 loss_thr: 0.6276 loss_db: 0.1767 2022/10/25 23:35:50 - mmengine - INFO - Epoch(train) [288][35/63] lr: 2.7638e-03 eta: 13:51:47 time: 0.5359 data_time: 0.0294 memory: 16131 loss: 1.8933 loss_prob: 1.0966 loss_thr: 0.6155 loss_db: 0.1813 2022/10/25 23:35:53 - mmengine - INFO - Epoch(train) [288][40/63] lr: 2.7638e-03 eta: 13:51:27 time: 0.5332 data_time: 0.0061 memory: 16131 loss: 1.8833 loss_prob: 1.1044 loss_thr: 0.5962 loss_db: 0.1827 2022/10/25 23:35:57 - mmengine - INFO - Epoch(train) [288][45/63] lr: 2.7638e-03 eta: 13:51:27 time: 0.7026 data_time: 0.0070 memory: 16131 loss: 1.8687 loss_prob: 1.0889 loss_thr: 0.5995 loss_db: 0.1802 2022/10/25 23:36:01 - mmengine - INFO - Epoch(train) [288][50/63] lr: 2.7638e-03 eta: 13:51:19 time: 0.8738 data_time: 0.0210 memory: 16131 loss: 1.9712 loss_prob: 1.1616 loss_thr: 0.6240 loss_db: 0.1856 2022/10/25 23:36:05 - mmengine - INFO - Epoch(train) [288][55/63] lr: 2.7638e-03 eta: 13:51:19 time: 0.8049 data_time: 0.0265 memory: 16131 loss: 2.1681 loss_prob: 1.2859 loss_thr: 0.6745 loss_db: 0.2078 2022/10/25 23:36:08 - mmengine - INFO - Epoch(train) [288][60/63] lr: 2.7638e-03 eta: 13:51:02 time: 0.6276 data_time: 0.0148 memory: 16131 loss: 2.1163 loss_prob: 1.2547 loss_thr: 0.6540 loss_db: 0.2075 2022/10/25 23:36:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:36:15 - mmengine - INFO - Epoch(train) [289][5/63] lr: 2.7611e-03 eta: 13:51:02 time: 0.8533 data_time: 0.1579 memory: 16131 loss: 1.9115 loss_prob: 1.1471 loss_thr: 0.5781 loss_db: 0.1862 2022/10/25 23:36:18 - mmengine - INFO - Epoch(train) [289][10/63] lr: 2.7611e-03 eta: 13:50:43 time: 0.8778 data_time: 0.1548 memory: 16131 loss: 1.9624 loss_prob: 1.1576 loss_thr: 0.6138 loss_db: 0.1909 2022/10/25 23:36:22 - mmengine - INFO - Epoch(train) [289][15/63] lr: 2.7611e-03 eta: 13:50:43 time: 0.6419 data_time: 0.0052 memory: 16131 loss: 1.9875 loss_prob: 1.1732 loss_thr: 0.6147 loss_db: 0.1996 2022/10/25 23:36:26 - mmengine - INFO - Epoch(train) [289][20/63] lr: 2.7611e-03 eta: 13:50:33 time: 0.8118 data_time: 0.0056 memory: 16131 loss: 1.9284 loss_prob: 1.1615 loss_thr: 0.5754 loss_db: 0.1915 2022/10/25 23:36:29 - mmengine - INFO - Epoch(train) [289][25/63] lr: 2.7611e-03 eta: 13:50:33 time: 0.7079 data_time: 0.0132 memory: 16131 loss: 1.9453 loss_prob: 1.1618 loss_thr: 0.5951 loss_db: 0.1883 2022/10/25 23:36:32 - mmengine - INFO - Epoch(train) [289][30/63] lr: 2.7611e-03 eta: 13:50:15 time: 0.5887 data_time: 0.0541 memory: 16131 loss: 2.1828 loss_prob: 1.3221 loss_thr: 0.6476 loss_db: 0.2131 2022/10/25 23:36:35 - mmengine - INFO - Epoch(train) [289][35/63] lr: 2.7611e-03 eta: 13:50:15 time: 0.6439 data_time: 0.0505 memory: 16131 loss: 2.2100 loss_prob: 1.3569 loss_thr: 0.6367 loss_db: 0.2164 2022/10/25 23:36:40 - mmengine - INFO - Epoch(train) [289][40/63] lr: 2.7611e-03 eta: 13:50:05 time: 0.8194 data_time: 0.0100 memory: 16131 loss: 1.9337 loss_prob: 1.1488 loss_thr: 0.5973 loss_db: 0.1876 2022/10/25 23:36:44 - mmengine - INFO - Epoch(train) [289][45/63] lr: 2.7611e-03 eta: 13:50:05 time: 0.9173 data_time: 0.0069 memory: 16131 loss: 1.8064 loss_prob: 1.0339 loss_thr: 0.6048 loss_db: 0.1677 2022/10/25 23:36:48 - mmengine - INFO - Epoch(train) [289][50/63] lr: 2.7611e-03 eta: 13:49:53 time: 0.7628 data_time: 0.0206 memory: 16131 loss: 1.9425 loss_prob: 1.1496 loss_thr: 0.6121 loss_db: 0.1808 2022/10/25 23:36:52 - mmengine - INFO - Epoch(train) [289][55/63] lr: 2.7611e-03 eta: 13:49:53 time: 0.8129 data_time: 0.0251 memory: 16131 loss: 1.9686 loss_prob: 1.1604 loss_thr: 0.6273 loss_db: 0.1809 2022/10/25 23:36:59 - mmengine - INFO - Epoch(train) [289][60/63] lr: 2.7611e-03 eta: 13:49:51 time: 1.0875 data_time: 0.0113 memory: 16131 loss: 1.9212 loss_prob: 1.1052 loss_thr: 0.6380 loss_db: 0.1780 2022/10/25 23:37:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:37:07 - mmengine - INFO - Epoch(train) [290][5/63] lr: 2.7584e-03 eta: 13:49:51 time: 1.1033 data_time: 0.1632 memory: 16131 loss: 1.9305 loss_prob: 1.1346 loss_thr: 0.6056 loss_db: 0.1903 2022/10/25 23:37:13 - mmengine - INFO - Epoch(train) [290][10/63] lr: 2.7584e-03 eta: 13:49:45 time: 1.2790 data_time: 0.1732 memory: 16131 loss: 1.9056 loss_prob: 1.1266 loss_thr: 0.5949 loss_db: 0.1841 2022/10/25 23:37:18 - mmengine - INFO - Epoch(train) [290][15/63] lr: 2.7584e-03 eta: 13:49:45 time: 1.0849 data_time: 0.0159 memory: 16131 loss: 1.7993 loss_prob: 1.0509 loss_thr: 0.5801 loss_db: 0.1683 2022/10/25 23:37:25 - mmengine - INFO - Epoch(train) [290][20/63] lr: 2.7584e-03 eta: 13:49:46 time: 1.1877 data_time: 0.0067 memory: 16131 loss: 1.7297 loss_prob: 0.9958 loss_thr: 0.5699 loss_db: 0.1640 2022/10/25 23:37:27 - mmengine - INFO - Epoch(train) [290][25/63] lr: 2.7584e-03 eta: 13:49:46 time: 0.9104 data_time: 0.0107 memory: 16131 loss: 1.7398 loss_prob: 1.0066 loss_thr: 0.5690 loss_db: 0.1642 2022/10/25 23:37:30 - mmengine - INFO - Epoch(train) [290][30/63] lr: 2.7584e-03 eta: 13:49:27 time: 0.5320 data_time: 0.0427 memory: 16131 loss: 1.8722 loss_prob: 1.0966 loss_thr: 0.6010 loss_db: 0.1746 2022/10/25 23:37:33 - mmengine - INFO - Epoch(train) [290][35/63] lr: 2.7584e-03 eta: 13:49:27 time: 0.6255 data_time: 0.0385 memory: 16131 loss: 1.9302 loss_prob: 1.1289 loss_thr: 0.6204 loss_db: 0.1809 2022/10/25 23:37:38 - mmengine - INFO - Epoch(train) [290][40/63] lr: 2.7584e-03 eta: 13:49:18 time: 0.8404 data_time: 0.0060 memory: 16131 loss: 2.0664 loss_prob: 1.2414 loss_thr: 0.6288 loss_db: 0.1963 2022/10/25 23:37:43 - mmengine - INFO - Epoch(train) [290][45/63] lr: 2.7584e-03 eta: 13:49:18 time: 0.9807 data_time: 0.0060 memory: 16131 loss: 1.9351 loss_prob: 1.1523 loss_thr: 0.5996 loss_db: 0.1832 2022/10/25 23:37:47 - mmengine - INFO - Epoch(train) [290][50/63] lr: 2.7584e-03 eta: 13:49:10 time: 0.8958 data_time: 0.0083 memory: 16131 loss: 1.7760 loss_prob: 1.0189 loss_thr: 0.5894 loss_db: 0.1677 2022/10/25 23:37:52 - mmengine - INFO - Epoch(train) [290][55/63] lr: 2.7584e-03 eta: 13:49:10 time: 0.8796 data_time: 0.0218 memory: 16131 loss: 1.8903 loss_prob: 1.1064 loss_thr: 0.6054 loss_db: 0.1786 2022/10/25 23:37:55 - mmengine - INFO - Epoch(train) [290][60/63] lr: 2.7584e-03 eta: 13:48:57 time: 0.7427 data_time: 0.0179 memory: 16131 loss: 1.8921 loss_prob: 1.0960 loss_thr: 0.6189 loss_db: 0.1772 2022/10/25 23:37:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:38:02 - mmengine - INFO - Epoch(train) [291][5/63] lr: 2.7556e-03 eta: 13:48:57 time: 0.8652 data_time: 0.2073 memory: 16131 loss: 1.9213 loss_prob: 1.1071 loss_thr: 0.6290 loss_db: 0.1852 2022/10/25 23:38:07 - mmengine - INFO - Epoch(train) [291][10/63] lr: 2.7556e-03 eta: 13:48:43 time: 1.0259 data_time: 0.2074 memory: 16131 loss: 1.8602 loss_prob: 1.0950 loss_thr: 0.5874 loss_db: 0.1778 2022/10/25 23:38:13 - mmengine - INFO - Epoch(train) [291][15/63] lr: 2.7556e-03 eta: 13:48:43 time: 1.0716 data_time: 0.0050 memory: 16131 loss: 1.8617 loss_prob: 1.0798 loss_thr: 0.6033 loss_db: 0.1786 2022/10/25 23:38:17 - mmengine - INFO - Epoch(train) [291][20/63] lr: 2.7556e-03 eta: 13:48:39 time: 1.0305 data_time: 0.0051 memory: 16131 loss: 1.8557 loss_prob: 1.0526 loss_thr: 0.6244 loss_db: 0.1787 2022/10/25 23:38:21 - mmengine - INFO - Epoch(train) [291][25/63] lr: 2.7556e-03 eta: 13:48:39 time: 0.7403 data_time: 0.0162 memory: 16131 loss: 1.7204 loss_prob: 0.9825 loss_thr: 0.5768 loss_db: 0.1611 2022/10/25 23:38:25 - mmengine - INFO - Epoch(train) [291][30/63] lr: 2.7556e-03 eta: 13:48:25 time: 0.7084 data_time: 0.0361 memory: 16131 loss: 1.7525 loss_prob: 1.0149 loss_thr: 0.5757 loss_db: 0.1619 2022/10/25 23:38:33 - mmengine - INFO - Epoch(train) [291][35/63] lr: 2.7556e-03 eta: 13:48:25 time: 1.2965 data_time: 0.0276 memory: 16131 loss: 1.7958 loss_prob: 1.0351 loss_thr: 0.5923 loss_db: 0.1685 2022/10/25 23:38:41 - mmengine - INFO - Epoch(train) [291][40/63] lr: 2.7556e-03 eta: 13:48:40 time: 1.6176 data_time: 0.0097 memory: 16131 loss: 1.7901 loss_prob: 1.0261 loss_thr: 0.5941 loss_db: 0.1699 2022/10/25 23:38:45 - mmengine - INFO - Epoch(train) [291][45/63] lr: 2.7556e-03 eta: 13:48:40 time: 1.1710 data_time: 0.0095 memory: 16131 loss: 1.9113 loss_prob: 1.1161 loss_thr: 0.6126 loss_db: 0.1826 2022/10/25 23:38:48 - mmengine - INFO - Epoch(train) [291][50/63] lr: 2.7556e-03 eta: 13:48:27 time: 0.7218 data_time: 0.0309 memory: 16131 loss: 1.8482 loss_prob: 1.0745 loss_thr: 0.6002 loss_db: 0.1735 2022/10/25 23:38:53 - mmengine - INFO - Epoch(train) [291][55/63] lr: 2.7556e-03 eta: 13:48:27 time: 0.7375 data_time: 0.0347 memory: 16131 loss: 1.8557 loss_prob: 1.0840 loss_thr: 0.5948 loss_db: 0.1769 2022/10/25 23:38:56 - mmengine - INFO - Epoch(train) [291][60/63] lr: 2.7556e-03 eta: 13:48:16 time: 0.7781 data_time: 0.0111 memory: 16131 loss: 1.9780 loss_prob: 1.1677 loss_thr: 0.6161 loss_db: 0.1943 2022/10/25 23:38:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:39:03 - mmengine - INFO - Epoch(train) [292][5/63] lr: 2.7529e-03 eta: 13:48:16 time: 0.9361 data_time: 0.2162 memory: 16131 loss: 1.8885 loss_prob: 1.1064 loss_thr: 0.5982 loss_db: 0.1840 2022/10/25 23:39:08 - mmengine - INFO - Epoch(train) [292][10/63] lr: 2.7529e-03 eta: 13:48:00 time: 0.9943 data_time: 0.2152 memory: 16131 loss: 1.9328 loss_prob: 1.1465 loss_thr: 0.5931 loss_db: 0.1932 2022/10/25 23:39:11 - mmengine - INFO - Epoch(train) [292][15/63] lr: 2.7529e-03 eta: 13:48:00 time: 0.7181 data_time: 0.0060 memory: 16131 loss: 1.9514 loss_prob: 1.1688 loss_thr: 0.5857 loss_db: 0.1969 2022/10/25 23:39:14 - mmengine - INFO - Epoch(train) [292][20/63] lr: 2.7529e-03 eta: 13:47:45 time: 0.6649 data_time: 0.0060 memory: 16131 loss: 1.8735 loss_prob: 1.1065 loss_thr: 0.5836 loss_db: 0.1834 2022/10/25 23:39:19 - mmengine - INFO - Epoch(train) [292][25/63] lr: 2.7529e-03 eta: 13:47:45 time: 0.8525 data_time: 0.0293 memory: 16131 loss: 2.0635 loss_prob: 1.2463 loss_thr: 0.6135 loss_db: 0.2037 2022/10/25 23:39:26 - mmengine - INFO - Epoch(train) [292][30/63] lr: 2.7529e-03 eta: 13:47:45 time: 1.1448 data_time: 0.0404 memory: 16131 loss: 2.0691 loss_prob: 1.2492 loss_thr: 0.6150 loss_db: 0.2049 2022/10/25 23:39:29 - mmengine - INFO - Epoch(train) [292][35/63] lr: 2.7529e-03 eta: 13:47:45 time: 0.9383 data_time: 0.0166 memory: 16131 loss: 1.9153 loss_prob: 1.1147 loss_thr: 0.6146 loss_db: 0.1860 2022/10/25 23:39:36 - mmengine - INFO - Epoch(train) [292][40/63] lr: 2.7529e-03 eta: 13:47:40 time: 0.9749 data_time: 0.0052 memory: 16131 loss: 2.1029 loss_prob: 1.2554 loss_thr: 0.6426 loss_db: 0.2050 2022/10/25 23:39:40 - mmengine - INFO - Epoch(train) [292][45/63] lr: 2.7529e-03 eta: 13:47:40 time: 1.1314 data_time: 0.0062 memory: 16131 loss: 2.0891 loss_prob: 1.2578 loss_thr: 0.6284 loss_db: 0.2028 2022/10/25 23:39:43 - mmengine - INFO - Epoch(train) [292][50/63] lr: 2.7529e-03 eta: 13:47:27 time: 0.7232 data_time: 0.0193 memory: 16131 loss: 1.9167 loss_prob: 1.1333 loss_thr: 0.5958 loss_db: 0.1877 2022/10/25 23:39:47 - mmengine - INFO - Epoch(train) [292][55/63] lr: 2.7529e-03 eta: 13:47:27 time: 0.7531 data_time: 0.0321 memory: 16131 loss: 2.3340 loss_prob: 1.4618 loss_thr: 0.6337 loss_db: 0.2385 2022/10/25 23:39:50 - mmengine - INFO - Epoch(train) [292][60/63] lr: 2.7529e-03 eta: 13:47:14 time: 0.7490 data_time: 0.0212 memory: 16131 loss: 2.8562 loss_prob: 1.8856 loss_thr: 0.6729 loss_db: 0.2977 2022/10/25 23:39:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:40:02 - mmengine - INFO - Epoch(train) [293][5/63] lr: 2.7502e-03 eta: 13:47:14 time: 1.2560 data_time: 0.2384 memory: 16131 loss: 2.4202 loss_prob: 1.4973 loss_thr: 0.6747 loss_db: 0.2482 2022/10/25 23:40:06 - mmengine - INFO - Epoch(train) [293][10/63] lr: 2.7502e-03 eta: 13:47:10 time: 1.3583 data_time: 0.2406 memory: 16131 loss: 2.2724 loss_prob: 1.3816 loss_thr: 0.6602 loss_db: 0.2306 2022/10/25 23:40:11 - mmengine - INFO - Epoch(train) [293][15/63] lr: 2.7502e-03 eta: 13:47:10 time: 0.9572 data_time: 0.0113 memory: 16131 loss: 2.0471 loss_prob: 1.2213 loss_thr: 0.6284 loss_db: 0.1975 2022/10/25 23:40:14 - mmengine - INFO - Epoch(train) [293][20/63] lr: 2.7502e-03 eta: 13:47:01 time: 0.8464 data_time: 0.0081 memory: 16131 loss: 2.1492 loss_prob: 1.3128 loss_thr: 0.6194 loss_db: 0.2171 2022/10/25 23:40:18 - mmengine - INFO - Epoch(train) [293][25/63] lr: 2.7502e-03 eta: 13:47:01 time: 0.6944 data_time: 0.0235 memory: 16131 loss: 2.2849 loss_prob: 1.4224 loss_thr: 0.6246 loss_db: 0.2379 2022/10/25 23:40:24 - mmengine - INFO - Epoch(train) [293][30/63] lr: 2.7502e-03 eta: 13:46:57 time: 1.0152 data_time: 0.0337 memory: 16131 loss: 2.1869 loss_prob: 1.3374 loss_thr: 0.6312 loss_db: 0.2183 2022/10/25 23:40:30 - mmengine - INFO - Epoch(train) [293][35/63] lr: 2.7502e-03 eta: 13:46:57 time: 1.1747 data_time: 0.0176 memory: 16131 loss: 2.2936 loss_prob: 1.3916 loss_thr: 0.6728 loss_db: 0.2292 2022/10/25 23:40:35 - mmengine - INFO - Epoch(train) [293][40/63] lr: 2.7502e-03 eta: 13:46:54 time: 1.0778 data_time: 0.0102 memory: 16131 loss: 2.2522 loss_prob: 1.3639 loss_thr: 0.6619 loss_db: 0.2263 2022/10/25 23:40:39 - mmengine - INFO - Epoch(train) [293][45/63] lr: 2.7502e-03 eta: 13:46:54 time: 0.9370 data_time: 0.0114 memory: 16131 loss: 2.0440 loss_prob: 1.2314 loss_thr: 0.6148 loss_db: 0.1978 2022/10/25 23:40:45 - mmengine - INFO - Epoch(train) [293][50/63] lr: 2.7502e-03 eta: 13:46:51 time: 1.0303 data_time: 0.0201 memory: 16131 loss: 2.2108 loss_prob: 1.3408 loss_thr: 0.6579 loss_db: 0.2121 2022/10/25 23:40:50 - mmengine - INFO - Epoch(train) [293][55/63] lr: 2.7502e-03 eta: 13:46:51 time: 1.0249 data_time: 0.0217 memory: 16131 loss: 2.2453 loss_prob: 1.3579 loss_thr: 0.6680 loss_db: 0.2193 2022/10/25 23:40:52 - mmengine - INFO - Epoch(train) [293][60/63] lr: 2.7502e-03 eta: 13:46:37 time: 0.7166 data_time: 0.0121 memory: 16131 loss: 2.0600 loss_prob: 1.2139 loss_thr: 0.6491 loss_db: 0.1969 2022/10/25 23:40:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:41:03 - mmengine - INFO - Epoch(train) [294][5/63] lr: 2.7474e-03 eta: 13:46:37 time: 1.2162 data_time: 0.1729 memory: 16131 loss: 1.8433 loss_prob: 1.0772 loss_thr: 0.5919 loss_db: 0.1742 2022/10/25 23:41:08 - mmengine - INFO - Epoch(train) [294][10/63] lr: 2.7474e-03 eta: 13:46:28 time: 1.1827 data_time: 0.1913 memory: 16131 loss: 1.9787 loss_prob: 1.1831 loss_thr: 0.5988 loss_db: 0.1968 2022/10/25 23:41:10 - mmengine - INFO - Epoch(train) [294][15/63] lr: 2.7474e-03 eta: 13:46:28 time: 0.7061 data_time: 0.0256 memory: 16131 loss: 2.0086 loss_prob: 1.2122 loss_thr: 0.5963 loss_db: 0.2000 2022/10/25 23:41:15 - mmengine - INFO - Epoch(train) [294][20/63] lr: 2.7474e-03 eta: 13:46:15 time: 0.7217 data_time: 0.0075 memory: 16131 loss: 1.9446 loss_prob: 1.1660 loss_thr: 0.5922 loss_db: 0.1863 2022/10/25 23:41:18 - mmengine - INFO - Epoch(train) [294][25/63] lr: 2.7474e-03 eta: 13:46:15 time: 0.7971 data_time: 0.0126 memory: 16131 loss: 2.0394 loss_prob: 1.2056 loss_thr: 0.6375 loss_db: 0.1962 2022/10/25 23:41:22 - mmengine - INFO - Epoch(train) [294][30/63] lr: 2.7474e-03 eta: 13:46:02 time: 0.7500 data_time: 0.0351 memory: 16131 loss: 2.0729 loss_prob: 1.2331 loss_thr: 0.6383 loss_db: 0.2014 2022/10/25 23:41:25 - mmengine - INFO - Epoch(train) [294][35/63] lr: 2.7474e-03 eta: 13:46:02 time: 0.7058 data_time: 0.0291 memory: 16131 loss: 2.0570 loss_prob: 1.2384 loss_thr: 0.6171 loss_db: 0.2015 2022/10/25 23:41:31 - mmengine - INFO - Epoch(train) [294][40/63] lr: 2.7474e-03 eta: 13:45:53 time: 0.8576 data_time: 0.0054 memory: 16131 loss: 2.1699 loss_prob: 1.3155 loss_thr: 0.6432 loss_db: 0.2112 2022/10/25 23:41:36 - mmengine - INFO - Epoch(train) [294][45/63] lr: 2.7474e-03 eta: 13:45:53 time: 1.0385 data_time: 0.0060 memory: 16131 loss: 2.2205 loss_prob: 1.3186 loss_thr: 0.6863 loss_db: 0.2155 2022/10/25 23:41:41 - mmengine - INFO - Epoch(train) [294][50/63] lr: 2.7474e-03 eta: 13:45:50 time: 1.0369 data_time: 0.0154 memory: 16131 loss: 2.1877 loss_prob: 1.2975 loss_thr: 0.6757 loss_db: 0.2145 2022/10/25 23:41:44 - mmengine - INFO - Epoch(train) [294][55/63] lr: 2.7474e-03 eta: 13:45:50 time: 0.8630 data_time: 0.0222 memory: 16131 loss: 2.1245 loss_prob: 1.2843 loss_thr: 0.6336 loss_db: 0.2066 2022/10/25 23:41:47 - mmengine - INFO - Epoch(train) [294][60/63] lr: 2.7474e-03 eta: 13:45:32 time: 0.5635 data_time: 0.0123 memory: 16131 loss: 2.1124 loss_prob: 1.2765 loss_thr: 0.6280 loss_db: 0.2079 2022/10/25 23:41:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:41:56 - mmengine - INFO - Epoch(train) [295][5/63] lr: 2.7447e-03 eta: 13:45:32 time: 0.9964 data_time: 0.2524 memory: 16131 loss: 2.1522 loss_prob: 1.3270 loss_thr: 0.6153 loss_db: 0.2098 2022/10/25 23:42:01 - mmengine - INFO - Epoch(train) [295][10/63] lr: 2.7447e-03 eta: 13:45:24 time: 1.2445 data_time: 0.2782 memory: 16131 loss: 2.1222 loss_prob: 1.2993 loss_thr: 0.6151 loss_db: 0.2078 2022/10/25 23:42:06 - mmengine - INFO - Epoch(train) [295][15/63] lr: 2.7447e-03 eta: 13:45:24 time: 1.0219 data_time: 0.0335 memory: 16131 loss: 1.9452 loss_prob: 1.1473 loss_thr: 0.6048 loss_db: 0.1931 2022/10/25 23:42:11 - mmengine - INFO - Epoch(train) [295][20/63] lr: 2.7447e-03 eta: 13:45:20 time: 1.0208 data_time: 0.0067 memory: 16131 loss: 2.0138 loss_prob: 1.2006 loss_thr: 0.6183 loss_db: 0.1948 2022/10/25 23:42:15 - mmengine - INFO - Epoch(train) [295][25/63] lr: 2.7447e-03 eta: 13:45:20 time: 0.9341 data_time: 0.0312 memory: 16131 loss: 2.2870 loss_prob: 1.4029 loss_thr: 0.6621 loss_db: 0.2220 2022/10/25 23:42:22 - mmengine - INFO - Epoch(train) [295][30/63] lr: 2.7447e-03 eta: 13:45:19 time: 1.1062 data_time: 0.0360 memory: 16131 loss: 2.2466 loss_prob: 1.3629 loss_thr: 0.6632 loss_db: 0.2205 2022/10/25 23:42:26 - mmengine - INFO - Epoch(train) [295][35/63] lr: 2.7447e-03 eta: 13:45:19 time: 1.0815 data_time: 0.0096 memory: 16131 loss: 2.0784 loss_prob: 1.2418 loss_thr: 0.6304 loss_db: 0.2062 2022/10/25 23:42:31 - mmengine - INFO - Epoch(train) [295][40/63] lr: 2.7447e-03 eta: 13:45:11 time: 0.8950 data_time: 0.0055 memory: 16131 loss: 2.1684 loss_prob: 1.3170 loss_thr: 0.6320 loss_db: 0.2194 2022/10/25 23:42:34 - mmengine - INFO - Epoch(train) [295][45/63] lr: 2.7447e-03 eta: 13:45:11 time: 0.8141 data_time: 0.0072 memory: 16131 loss: 2.1626 loss_prob: 1.3000 loss_thr: 0.6477 loss_db: 0.2148 2022/10/25 23:42:40 - mmengine - INFO - Epoch(train) [295][50/63] lr: 2.7447e-03 eta: 13:45:03 time: 0.8780 data_time: 0.0211 memory: 16131 loss: 2.3357 loss_prob: 1.4511 loss_thr: 0.6516 loss_db: 0.2330 2022/10/25 23:42:47 - mmengine - INFO - Epoch(train) [295][55/63] lr: 2.7447e-03 eta: 13:45:03 time: 1.2352 data_time: 0.0248 memory: 16131 loss: 2.3229 loss_prob: 1.4523 loss_thr: 0.6368 loss_db: 0.2339 2022/10/25 23:42:51 - mmengine - INFO - Epoch(train) [295][60/63] lr: 2.7447e-03 eta: 13:45:01 time: 1.0979 data_time: 0.0141 memory: 16131 loss: 2.2063 loss_prob: 1.3568 loss_thr: 0.6257 loss_db: 0.2238 2022/10/25 23:42:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:43:00 - mmengine - INFO - Epoch(train) [296][5/63] lr: 2.7420e-03 eta: 13:45:01 time: 1.1094 data_time: 0.2342 memory: 16131 loss: 2.2453 loss_prob: 1.4097 loss_thr: 0.6134 loss_db: 0.2223 2022/10/25 23:43:06 - mmengine - INFO - Epoch(train) [296][10/63] lr: 2.7420e-03 eta: 13:44:56 time: 1.3428 data_time: 0.2263 memory: 16131 loss: 2.2628 loss_prob: 1.4052 loss_thr: 0.6309 loss_db: 0.2266 2022/10/25 23:43:12 - mmengine - INFO - Epoch(train) [296][15/63] lr: 2.7420e-03 eta: 13:44:56 time: 1.2207 data_time: 0.0054 memory: 16131 loss: 2.0523 loss_prob: 1.2368 loss_thr: 0.6164 loss_db: 0.1991 2022/10/25 23:43:14 - mmengine - INFO - Epoch(train) [296][20/63] lr: 2.7420e-03 eta: 13:44:47 time: 0.8462 data_time: 0.0097 memory: 16131 loss: 2.0160 loss_prob: 1.2122 loss_thr: 0.6137 loss_db: 0.1901 2022/10/25 23:43:18 - mmengine - INFO - Epoch(train) [296][25/63] lr: 2.7420e-03 eta: 13:44:47 time: 0.6431 data_time: 0.0410 memory: 16131 loss: 2.1042 loss_prob: 1.2672 loss_thr: 0.6306 loss_db: 0.2065 2022/10/25 23:43:22 - mmengine - INFO - Epoch(train) [296][30/63] lr: 2.7420e-03 eta: 13:44:35 time: 0.7685 data_time: 0.0364 memory: 16131 loss: 2.2197 loss_prob: 1.3502 loss_thr: 0.6469 loss_db: 0.2226 2022/10/25 23:43:25 - mmengine - INFO - Epoch(train) [296][35/63] lr: 2.7420e-03 eta: 13:44:35 time: 0.6610 data_time: 0.0058 memory: 16131 loss: 2.3115 loss_prob: 1.4419 loss_thr: 0.6359 loss_db: 0.2337 2022/10/25 23:43:28 - mmengine - INFO - Epoch(train) [296][40/63] lr: 2.7420e-03 eta: 13:44:18 time: 0.5865 data_time: 0.0076 memory: 16131 loss: 2.1418 loss_prob: 1.3078 loss_thr: 0.6219 loss_db: 0.2122 2022/10/25 23:43:31 - mmengine - INFO - Epoch(train) [296][45/63] lr: 2.7420e-03 eta: 13:44:18 time: 0.5705 data_time: 0.0122 memory: 16131 loss: 1.9784 loss_prob: 1.1607 loss_thr: 0.6289 loss_db: 0.1889 2022/10/25 23:43:33 - mmengine - INFO - Epoch(train) [296][50/63] lr: 2.7420e-03 eta: 13:43:59 time: 0.5297 data_time: 0.0306 memory: 16131 loss: 1.9067 loss_prob: 1.1016 loss_thr: 0.6274 loss_db: 0.1776 2022/10/25 23:43:36 - mmengine - INFO - Epoch(train) [296][55/63] lr: 2.7420e-03 eta: 13:43:59 time: 0.5580 data_time: 0.0245 memory: 16131 loss: 1.8699 loss_prob: 1.0773 loss_thr: 0.6176 loss_db: 0.1750 2022/10/25 23:43:39 - mmengine - INFO - Epoch(train) [296][60/63] lr: 2.7420e-03 eta: 13:43:42 time: 0.5919 data_time: 0.0057 memory: 16131 loss: 1.9399 loss_prob: 1.1513 loss_thr: 0.5991 loss_db: 0.1896 2022/10/25 23:43:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:43:45 - mmengine - INFO - Epoch(train) [297][5/63] lr: 2.7393e-03 eta: 13:43:42 time: 0.7501 data_time: 0.1775 memory: 16131 loss: 1.9244 loss_prob: 1.1509 loss_thr: 0.5875 loss_db: 0.1860 2022/10/25 23:43:48 - mmengine - INFO - Epoch(train) [297][10/63] lr: 2.7393e-03 eta: 13:43:19 time: 0.7398 data_time: 0.1772 memory: 16131 loss: 1.8744 loss_prob: 1.1102 loss_thr: 0.5888 loss_db: 0.1755 2022/10/25 23:43:52 - mmengine - INFO - Epoch(train) [297][15/63] lr: 2.7393e-03 eta: 13:43:19 time: 0.6389 data_time: 0.0054 memory: 16131 loss: 1.9945 loss_prob: 1.1784 loss_thr: 0.6214 loss_db: 0.1947 2022/10/25 23:43:57 - mmengine - INFO - Epoch(train) [297][20/63] lr: 2.7393e-03 eta: 13:43:11 time: 0.8913 data_time: 0.0055 memory: 16131 loss: 1.9662 loss_prob: 1.1510 loss_thr: 0.6217 loss_db: 0.1935 2022/10/25 23:44:00 - mmengine - INFO - Epoch(train) [297][25/63] lr: 2.7393e-03 eta: 13:43:11 time: 0.8201 data_time: 0.0239 memory: 16131 loss: 2.0401 loss_prob: 1.2378 loss_thr: 0.6021 loss_db: 0.2002 2022/10/25 23:44:05 - mmengine - INFO - Epoch(train) [297][30/63] lr: 2.7393e-03 eta: 13:42:59 time: 0.7609 data_time: 0.0359 memory: 16131 loss: 2.0896 loss_prob: 1.2739 loss_thr: 0.6130 loss_db: 0.2027 2022/10/25 23:44:08 - mmengine - INFO - Epoch(train) [297][35/63] lr: 2.7393e-03 eta: 13:42:59 time: 0.8355 data_time: 0.0173 memory: 16131 loss: 1.9615 loss_prob: 1.1520 loss_thr: 0.6223 loss_db: 0.1872 2022/10/25 23:44:12 - mmengine - INFO - Epoch(train) [297][40/63] lr: 2.7393e-03 eta: 13:42:45 time: 0.7089 data_time: 0.0074 memory: 16131 loss: 1.7667 loss_prob: 1.0179 loss_thr: 0.5806 loss_db: 0.1682 2022/10/25 23:44:16 - mmengine - INFO - Epoch(train) [297][45/63] lr: 2.7393e-03 eta: 13:42:45 time: 0.7924 data_time: 0.0086 memory: 16131 loss: 1.7649 loss_prob: 1.0249 loss_thr: 0.5720 loss_db: 0.1681 2022/10/25 23:44:21 - mmengine - INFO - Epoch(train) [297][50/63] lr: 2.7393e-03 eta: 13:42:37 time: 0.8924 data_time: 0.0181 memory: 16131 loss: 1.9695 loss_prob: 1.1680 loss_thr: 0.6116 loss_db: 0.1899 2022/10/25 23:44:25 - mmengine - INFO - Epoch(train) [297][55/63] lr: 2.7393e-03 eta: 13:42:37 time: 0.8519 data_time: 0.0232 memory: 16131 loss: 1.9777 loss_prob: 1.1794 loss_thr: 0.6086 loss_db: 0.1897 2022/10/25 23:44:30 - mmengine - INFO - Epoch(train) [297][60/63] lr: 2.7393e-03 eta: 13:42:30 time: 0.9084 data_time: 0.0127 memory: 16131 loss: 1.8394 loss_prob: 1.0748 loss_thr: 0.5923 loss_db: 0.1723 2022/10/25 23:44:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:44:38 - mmengine - INFO - Epoch(train) [298][5/63] lr: 2.7365e-03 eta: 13:42:30 time: 1.0104 data_time: 0.2061 memory: 16131 loss: 1.8756 loss_prob: 1.1164 loss_thr: 0.5797 loss_db: 0.1796 2022/10/25 23:44:42 - mmengine - INFO - Epoch(train) [298][10/63] lr: 2.7365e-03 eta: 13:42:17 time: 1.0820 data_time: 0.2100 memory: 16131 loss: 1.9059 loss_prob: 1.1214 loss_thr: 0.6026 loss_db: 0.1819 2022/10/25 23:44:48 - mmengine - INFO - Epoch(train) [298][15/63] lr: 2.7365e-03 eta: 13:42:17 time: 1.0561 data_time: 0.0108 memory: 16131 loss: 1.9043 loss_prob: 1.1094 loss_thr: 0.6141 loss_db: 0.1808 2022/10/25 23:44:53 - mmengine - INFO - Epoch(train) [298][20/63] lr: 2.7365e-03 eta: 13:42:15 time: 1.0863 data_time: 0.0074 memory: 16131 loss: 1.8165 loss_prob: 1.0453 loss_thr: 0.6005 loss_db: 0.1707 2022/10/25 23:44:58 - mmengine - INFO - Epoch(train) [298][25/63] lr: 2.7365e-03 eta: 13:42:15 time: 0.9208 data_time: 0.0265 memory: 16131 loss: 1.9122 loss_prob: 1.1196 loss_thr: 0.6101 loss_db: 0.1825 2022/10/25 23:45:04 - mmengine - INFO - Epoch(train) [298][30/63] lr: 2.7365e-03 eta: 13:42:14 time: 1.1207 data_time: 0.0342 memory: 16131 loss: 1.8522 loss_prob: 1.0877 loss_thr: 0.5880 loss_db: 0.1765 2022/10/25 23:45:08 - mmengine - INFO - Epoch(train) [298][35/63] lr: 2.7365e-03 eta: 13:42:14 time: 1.0349 data_time: 0.0171 memory: 16131 loss: 1.7653 loss_prob: 1.0193 loss_thr: 0.5788 loss_db: 0.1672 2022/10/25 23:45:12 - mmengine - INFO - Epoch(train) [298][40/63] lr: 2.7365e-03 eta: 13:42:02 time: 0.7400 data_time: 0.0094 memory: 16131 loss: 1.8844 loss_prob: 1.0916 loss_thr: 0.6146 loss_db: 0.1783 2022/10/25 23:45:18 - mmengine - INFO - Epoch(train) [298][45/63] lr: 2.7365e-03 eta: 13:42:02 time: 1.0215 data_time: 0.0084 memory: 16131 loss: 1.9708 loss_prob: 1.1637 loss_thr: 0.6230 loss_db: 0.1842 2022/10/25 23:45:23 - mmengine - INFO - Epoch(train) [298][50/63] lr: 2.7365e-03 eta: 13:42:00 time: 1.1120 data_time: 0.0214 memory: 16131 loss: 2.0169 loss_prob: 1.2044 loss_thr: 0.6235 loss_db: 0.1890 2022/10/25 23:45:26 - mmengine - INFO - Epoch(train) [298][55/63] lr: 2.7365e-03 eta: 13:42:00 time: 0.7537 data_time: 0.0270 memory: 16131 loss: 1.8885 loss_prob: 1.0935 loss_thr: 0.6165 loss_db: 0.1785 2022/10/25 23:45:29 - mmengine - INFO - Epoch(train) [298][60/63] lr: 2.7365e-03 eta: 13:41:44 time: 0.6121 data_time: 0.0129 memory: 16131 loss: 1.7900 loss_prob: 1.0320 loss_thr: 0.5886 loss_db: 0.1694 2022/10/25 23:45:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:45:37 - mmengine - INFO - Epoch(train) [299][5/63] lr: 2.7338e-03 eta: 13:41:44 time: 0.9291 data_time: 0.2239 memory: 16131 loss: 2.1137 loss_prob: 1.2819 loss_thr: 0.6307 loss_db: 0.2011 2022/10/25 23:45:41 - mmengine - INFO - Epoch(train) [299][10/63] lr: 2.7338e-03 eta: 13:41:32 time: 1.0923 data_time: 0.2264 memory: 16131 loss: 1.8219 loss_prob: 1.0560 loss_thr: 0.5934 loss_db: 0.1725 2022/10/25 23:45:45 - mmengine - INFO - Epoch(train) [299][15/63] lr: 2.7338e-03 eta: 13:41:32 time: 0.7987 data_time: 0.0117 memory: 16131 loss: 1.8435 loss_prob: 1.0868 loss_thr: 0.5801 loss_db: 0.1766 2022/10/25 23:45:49 - mmengine - INFO - Epoch(train) [299][20/63] lr: 2.7338e-03 eta: 13:41:21 time: 0.8187 data_time: 0.0130 memory: 16131 loss: 1.8882 loss_prob: 1.1068 loss_thr: 0.5982 loss_db: 0.1832 2022/10/25 23:45:54 - mmengine - INFO - Epoch(train) [299][25/63] lr: 2.7338e-03 eta: 13:41:21 time: 0.9010 data_time: 0.0378 memory: 16131 loss: 1.7790 loss_prob: 1.0174 loss_thr: 0.5907 loss_db: 0.1710 2022/10/25 23:45:57 - mmengine - INFO - Epoch(train) [299][30/63] lr: 2.7338e-03 eta: 13:41:10 time: 0.7841 data_time: 0.0336 memory: 16131 loss: 1.8068 loss_prob: 1.0380 loss_thr: 0.5980 loss_db: 0.1708 2022/10/25 23:46:00 - mmengine - INFO - Epoch(train) [299][35/63] lr: 2.7338e-03 eta: 13:41:10 time: 0.5717 data_time: 0.0082 memory: 16131 loss: 1.9493 loss_prob: 1.1348 loss_thr: 0.6302 loss_db: 0.1843 2022/10/25 23:46:02 - mmengine - INFO - Epoch(train) [299][40/63] lr: 2.7338e-03 eta: 13:40:52 time: 0.5386 data_time: 0.0096 memory: 16131 loss: 1.9811 loss_prob: 1.1540 loss_thr: 0.6387 loss_db: 0.1884 2022/10/25 23:46:06 - mmengine - INFO - Epoch(train) [299][45/63] lr: 2.7338e-03 eta: 13:40:52 time: 0.6441 data_time: 0.0079 memory: 16131 loss: 1.9069 loss_prob: 1.0984 loss_thr: 0.6289 loss_db: 0.1797 2022/10/25 23:46:09 - mmengine - INFO - Epoch(train) [299][50/63] lr: 2.7338e-03 eta: 13:40:36 time: 0.6463 data_time: 0.0352 memory: 16131 loss: 1.8930 loss_prob: 1.0994 loss_thr: 0.6110 loss_db: 0.1826 2022/10/25 23:46:13 - mmengine - INFO - Epoch(train) [299][55/63] lr: 2.7338e-03 eta: 13:40:36 time: 0.7321 data_time: 0.0334 memory: 16131 loss: 1.9155 loss_prob: 1.1357 loss_thr: 0.5932 loss_db: 0.1866 2022/10/25 23:46:19 - mmengine - INFO - Epoch(train) [299][60/63] lr: 2.7338e-03 eta: 13:40:31 time: 0.9942 data_time: 0.0060 memory: 16131 loss: 2.0425 loss_prob: 1.2399 loss_thr: 0.6108 loss_db: 0.1919 2022/10/25 23:46:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:46:30 - mmengine - INFO - Epoch(train) [300][5/63] lr: 2.7311e-03 eta: 13:40:31 time: 1.3399 data_time: 0.2156 memory: 16131 loss: 1.7044 loss_prob: 0.9692 loss_thr: 0.5742 loss_db: 0.1610 2022/10/25 23:46:36 - mmengine - INFO - Epoch(train) [300][10/63] lr: 2.7311e-03 eta: 13:40:32 time: 1.5078 data_time: 0.2148 memory: 16131 loss: 1.7642 loss_prob: 1.0015 loss_thr: 0.5956 loss_db: 0.1672 2022/10/25 23:46:41 - mmengine - INFO - Epoch(train) [300][15/63] lr: 2.7311e-03 eta: 13:40:32 time: 1.0927 data_time: 0.0063 memory: 16131 loss: 1.8275 loss_prob: 1.0543 loss_thr: 0.5985 loss_db: 0.1747 2022/10/25 23:46:45 - mmengine - INFO - Epoch(train) [300][20/63] lr: 2.7311e-03 eta: 13:40:26 time: 0.9676 data_time: 0.0064 memory: 16131 loss: 2.0492 loss_prob: 1.2394 loss_thr: 0.6135 loss_db: 0.1963 2022/10/25 23:46:52 - mmengine - INFO - Epoch(train) [300][25/63] lr: 2.7311e-03 eta: 13:40:26 time: 1.1457 data_time: 0.0129 memory: 16131 loss: 2.0266 loss_prob: 1.2283 loss_thr: 0.6040 loss_db: 0.1942 2022/10/25 23:46:55 - mmengine - INFO - Epoch(train) [300][30/63] lr: 2.7311e-03 eta: 13:40:21 time: 0.9840 data_time: 0.0397 memory: 16131 loss: 2.1061 loss_prob: 1.2872 loss_thr: 0.6106 loss_db: 0.2084 2022/10/25 23:46:59 - mmengine - INFO - Epoch(train) [300][35/63] lr: 2.7311e-03 eta: 13:40:21 time: 0.6890 data_time: 0.0319 memory: 16131 loss: 2.1801 loss_prob: 1.3283 loss_thr: 0.6366 loss_db: 0.2152 2022/10/25 23:47:05 - mmengine - INFO - Epoch(train) [300][40/63] lr: 2.7311e-03 eta: 13:40:16 time: 1.0128 data_time: 0.0119 memory: 16131 loss: 1.9712 loss_prob: 1.1428 loss_thr: 0.6400 loss_db: 0.1883 2022/10/25 23:47:10 - mmengine - INFO - Epoch(train) [300][45/63] lr: 2.7311e-03 eta: 13:40:16 time: 1.1041 data_time: 0.0156 memory: 16131 loss: 1.8683 loss_prob: 1.0825 loss_thr: 0.6066 loss_db: 0.1792 2022/10/25 23:47:14 - mmengine - INFO - Epoch(train) [300][50/63] lr: 2.7311e-03 eta: 13:40:06 time: 0.8097 data_time: 0.0168 memory: 16131 loss: 1.8341 loss_prob: 1.0583 loss_thr: 0.6020 loss_db: 0.1737 2022/10/25 23:47:17 - mmengine - INFO - Epoch(train) [300][55/63] lr: 2.7311e-03 eta: 13:40:06 time: 0.6512 data_time: 0.0528 memory: 16131 loss: 1.9719 loss_prob: 1.1534 loss_thr: 0.6326 loss_db: 0.1859 2022/10/25 23:47:19 - mmengine - INFO - Epoch(train) [300][60/63] lr: 2.7311e-03 eta: 13:39:48 time: 0.5712 data_time: 0.0462 memory: 16131 loss: 1.8642 loss_prob: 1.0822 loss_thr: 0.6046 loss_db: 0.1774 2022/10/25 23:47:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:47:21 - mmengine - INFO - Saving checkpoint at 300 epochs 2022/10/25 23:47:27 - mmengine - INFO - Epoch(val) [300][5/32] eta: 13:39:48 time: 0.5477 data_time: 0.0774 memory: 16131 2022/10/25 23:47:30 - mmengine - INFO - Epoch(val) [300][10/32] eta: 0:00:12 time: 0.5784 data_time: 0.0867 memory: 15724 2022/10/25 23:47:33 - mmengine - INFO - Epoch(val) [300][15/32] eta: 0:00:12 time: 0.5486 data_time: 0.0456 memory: 15724 2022/10/25 23:47:36 - mmengine - INFO - Epoch(val) [300][20/32] eta: 0:00:07 time: 0.6148 data_time: 0.0873 memory: 15724 2022/10/25 23:47:39 - mmengine - INFO - Epoch(val) [300][25/32] eta: 0:00:07 time: 0.5960 data_time: 0.0660 memory: 15724 2022/10/25 23:47:41 - mmengine - INFO - Epoch(val) [300][30/32] eta: 0:00:01 time: 0.5171 data_time: 0.0212 memory: 15724 2022/10/25 23:47:42 - mmengine - INFO - Evaluating hmean-iou... 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7992, precision: 0.7236, hmean: 0.7596 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7992, precision: 0.7768, hmean: 0.7879 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7963, precision: 0.8132, hmean: 0.8047 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7756, precision: 0.8492, hmean: 0.8108 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7015, precision: 0.8895, hmean: 0.7844 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3000, precision: 0.9482, hmean: 0.4557 2022/10/25 23:47:42 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/25 23:47:42 - mmengine - INFO - Epoch(val) [300][32/32] icdar/precision: 0.8492 icdar/recall: 0.7756 icdar/hmean: 0.8108 2022/10/25 23:47:50 - mmengine - INFO - Epoch(train) [301][5/63] lr: 2.7283e-03 eta: 0:00:01 time: 1.0722 data_time: 0.1982 memory: 16131 loss: 1.8091 loss_prob: 1.0295 loss_thr: 0.6090 loss_db: 0.1706 2022/10/25 23:47:56 - mmengine - INFO - Epoch(train) [301][10/63] lr: 2.7283e-03 eta: 13:39:46 time: 1.4174 data_time: 0.1976 memory: 16131 loss: 1.8908 loss_prob: 1.0986 loss_thr: 0.6123 loss_db: 0.1799 2022/10/25 23:47:59 - mmengine - INFO - Epoch(train) [301][15/63] lr: 2.7283e-03 eta: 13:39:46 time: 0.8524 data_time: 0.0050 memory: 16131 loss: 1.7956 loss_prob: 1.0334 loss_thr: 0.5936 loss_db: 0.1686 2022/10/25 23:48:02 - mmengine - INFO - Epoch(train) [301][20/63] lr: 2.7283e-03 eta: 13:39:29 time: 0.5805 data_time: 0.0104 memory: 16131 loss: 1.9085 loss_prob: 1.1159 loss_thr: 0.6047 loss_db: 0.1878 2022/10/25 23:48:06 - mmengine - INFO - Epoch(train) [301][25/63] lr: 2.7283e-03 eta: 13:39:29 time: 0.7443 data_time: 0.0195 memory: 16131 loss: 1.9600 loss_prob: 1.1563 loss_thr: 0.6082 loss_db: 0.1955 2022/10/25 23:48:13 - mmengine - INFO - Epoch(train) [301][30/63] lr: 2.7283e-03 eta: 13:39:25 time: 1.0546 data_time: 0.0354 memory: 16131 loss: 1.8946 loss_prob: 1.0921 loss_thr: 0.6209 loss_db: 0.1816 2022/10/25 23:48:17 - mmengine - INFO - Epoch(train) [301][35/63] lr: 2.7283e-03 eta: 13:39:25 time: 1.0349 data_time: 0.0258 memory: 16131 loss: 1.9508 loss_prob: 1.1258 loss_thr: 0.6385 loss_db: 0.1865 2022/10/25 23:48:23 - mmengine - INFO - Epoch(train) [301][40/63] lr: 2.7283e-03 eta: 13:39:22 time: 1.0488 data_time: 0.0063 memory: 16131 loss: 1.8845 loss_prob: 1.0908 loss_thr: 0.6121 loss_db: 0.1815 2022/10/25 23:48:28 - mmengine - INFO - Epoch(train) [301][45/63] lr: 2.7283e-03 eta: 13:39:22 time: 1.1749 data_time: 0.0065 memory: 16131 loss: 1.9623 loss_prob: 1.1612 loss_thr: 0.6092 loss_db: 0.1919 2022/10/25 23:48:33 - mmengine - INFO - Epoch(train) [301][50/63] lr: 2.7283e-03 eta: 13:39:18 time: 1.0057 data_time: 0.0146 memory: 16131 loss: 1.9747 loss_prob: 1.1722 loss_thr: 0.6089 loss_db: 0.1936 2022/10/25 23:48:38 - mmengine - INFO - Epoch(train) [301][55/63] lr: 2.7283e-03 eta: 13:39:18 time: 1.0044 data_time: 0.0246 memory: 16131 loss: 1.9773 loss_prob: 1.1799 loss_thr: 0.6060 loss_db: 0.1915 2022/10/25 23:48:44 - mmengine - INFO - Epoch(train) [301][60/63] lr: 2.7283e-03 eta: 13:39:15 time: 1.0605 data_time: 0.0181 memory: 16131 loss: 2.1268 loss_prob: 1.3054 loss_thr: 0.6132 loss_db: 0.2081 2022/10/25 23:48:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:48:52 - mmengine - INFO - Epoch(train) [302][5/63] lr: 2.7256e-03 eta: 13:39:15 time: 1.1125 data_time: 0.2223 memory: 16131 loss: 1.9975 loss_prob: 1.2074 loss_thr: 0.5902 loss_db: 0.1999 2022/10/25 23:48:56 - mmengine - INFO - Epoch(train) [302][10/63] lr: 2.7256e-03 eta: 13:39:03 time: 1.1001 data_time: 0.2237 memory: 16131 loss: 2.0205 loss_prob: 1.2011 loss_thr: 0.6249 loss_db: 0.1945 2022/10/25 23:48:59 - mmengine - INFO - Epoch(train) [302][15/63] lr: 2.7256e-03 eta: 13:39:03 time: 0.6980 data_time: 0.0101 memory: 16131 loss: 1.9783 loss_prob: 1.1750 loss_thr: 0.6188 loss_db: 0.1845 2022/10/25 23:49:05 - mmengine - INFO - Epoch(train) [302][20/63] lr: 2.7256e-03 eta: 13:38:52 time: 0.8093 data_time: 0.0067 memory: 16131 loss: 1.8699 loss_prob: 1.0983 loss_thr: 0.5956 loss_db: 0.1760 2022/10/25 23:49:10 - mmengine - INFO - Epoch(train) [302][25/63] lr: 2.7256e-03 eta: 13:38:52 time: 1.0873 data_time: 0.0501 memory: 16131 loss: 1.7771 loss_prob: 1.0285 loss_thr: 0.5819 loss_db: 0.1667 2022/10/25 23:49:17 - mmengine - INFO - Epoch(train) [302][30/63] lr: 2.7256e-03 eta: 13:38:53 time: 1.1960 data_time: 0.0683 memory: 16131 loss: 1.7859 loss_prob: 1.0219 loss_thr: 0.5983 loss_db: 0.1657 2022/10/25 23:49:20 - mmengine - INFO - Epoch(train) [302][35/63] lr: 2.7256e-03 eta: 13:38:53 time: 0.9608 data_time: 0.0245 memory: 16131 loss: 1.8890 loss_prob: 1.0981 loss_thr: 0.6127 loss_db: 0.1782 2022/10/25 23:49:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:49:23 - mmengine - INFO - Epoch(train) [302][40/63] lr: 2.7256e-03 eta: 13:38:39 time: 0.6719 data_time: 0.0070 memory: 16131 loss: 1.8588 loss_prob: 1.0901 loss_thr: 0.5900 loss_db: 0.1786 2022/10/25 23:49:26 - mmengine - INFO - Epoch(train) [302][45/63] lr: 2.7256e-03 eta: 13:38:39 time: 0.6340 data_time: 0.0071 memory: 16131 loss: 1.9709 loss_prob: 1.1630 loss_thr: 0.6143 loss_db: 0.1936 2022/10/25 23:49:32 - mmengine - INFO - Epoch(train) [302][50/63] lr: 2.7256e-03 eta: 13:38:31 time: 0.8867 data_time: 0.0292 memory: 16131 loss: 2.0865 loss_prob: 1.2460 loss_thr: 0.6323 loss_db: 0.2081 2022/10/25 23:49:36 - mmengine - INFO - Epoch(train) [302][55/63] lr: 2.7256e-03 eta: 13:38:31 time: 0.9785 data_time: 0.0294 memory: 16131 loss: 1.9696 loss_prob: 1.1627 loss_thr: 0.6133 loss_db: 0.1936 2022/10/25 23:49:40 - mmengine - INFO - Epoch(train) [302][60/63] lr: 2.7256e-03 eta: 13:38:19 time: 0.7555 data_time: 0.0065 memory: 16131 loss: 1.7967 loss_prob: 1.0327 loss_thr: 0.5959 loss_db: 0.1681 2022/10/25 23:49:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:49:49 - mmengine - INFO - Epoch(train) [303][5/63] lr: 2.7229e-03 eta: 13:38:19 time: 1.1348 data_time: 0.1995 memory: 16131 loss: 2.0633 loss_prob: 1.2232 loss_thr: 0.6477 loss_db: 0.1924 2022/10/25 23:49:52 - mmengine - INFO - Epoch(train) [303][10/63] lr: 2.7229e-03 eta: 13:37:59 time: 0.8352 data_time: 0.2114 memory: 16131 loss: 2.2744 loss_prob: 1.3852 loss_thr: 0.6650 loss_db: 0.2242 2022/10/25 23:49:54 - mmengine - INFO - Epoch(train) [303][15/63] lr: 2.7229e-03 eta: 13:37:59 time: 0.5659 data_time: 0.0170 memory: 16131 loss: 2.0684 loss_prob: 1.2420 loss_thr: 0.6223 loss_db: 0.2041 2022/10/25 23:49:57 - mmengine - INFO - Epoch(train) [303][20/63] lr: 2.7229e-03 eta: 13:37:40 time: 0.5225 data_time: 0.0079 memory: 16131 loss: 1.9477 loss_prob: 1.1443 loss_thr: 0.6211 loss_db: 0.1823 2022/10/25 23:50:00 - mmengine - INFO - Epoch(train) [303][25/63] lr: 2.7229e-03 eta: 13:37:40 time: 0.5113 data_time: 0.0223 memory: 16131 loss: 2.0322 loss_prob: 1.2189 loss_thr: 0.6174 loss_db: 0.1959 2022/10/25 23:50:03 - mmengine - INFO - Epoch(train) [303][30/63] lr: 2.7229e-03 eta: 13:37:22 time: 0.5632 data_time: 0.0248 memory: 16131 loss: 2.1531 loss_prob: 1.3165 loss_thr: 0.6134 loss_db: 0.2232 2022/10/25 23:50:06 - mmengine - INFO - Epoch(train) [303][35/63] lr: 2.7229e-03 eta: 13:37:22 time: 0.6274 data_time: 0.0199 memory: 16131 loss: 2.2124 loss_prob: 1.3445 loss_thr: 0.6425 loss_db: 0.2255 2022/10/25 23:50:10 - mmengine - INFO - Epoch(train) [303][40/63] lr: 2.7229e-03 eta: 13:37:09 time: 0.7223 data_time: 0.0159 memory: 16131 loss: 2.0725 loss_prob: 1.2448 loss_thr: 0.6239 loss_db: 0.2038 2022/10/25 23:50:17 - mmengine - INFO - Epoch(train) [303][45/63] lr: 2.7229e-03 eta: 13:37:09 time: 1.1121 data_time: 0.0093 memory: 16131 loss: 1.9811 loss_prob: 1.1809 loss_thr: 0.6028 loss_db: 0.1974 2022/10/25 23:50:22 - mmengine - INFO - Epoch(train) [303][50/63] lr: 2.7229e-03 eta: 13:37:12 time: 1.2648 data_time: 0.0197 memory: 16131 loss: 2.0124 loss_prob: 1.1957 loss_thr: 0.6146 loss_db: 0.2020 2022/10/25 23:50:28 - mmengine - INFO - Epoch(train) [303][55/63] lr: 2.7229e-03 eta: 13:37:12 time: 1.0962 data_time: 0.0241 memory: 16131 loss: 2.0841 loss_prob: 1.2590 loss_thr: 0.6180 loss_db: 0.2071 2022/10/25 23:50:34 - mmengine - INFO - Epoch(train) [303][60/63] lr: 2.7229e-03 eta: 13:37:13 time: 1.1821 data_time: 0.0172 memory: 16131 loss: 2.3136 loss_prob: 1.4437 loss_thr: 0.6329 loss_db: 0.2371 2022/10/25 23:50:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:50:44 - mmengine - INFO - Epoch(train) [304][5/63] lr: 2.7201e-03 eta: 13:37:13 time: 1.2744 data_time: 0.2092 memory: 16131 loss: 2.0548 loss_prob: 1.2315 loss_thr: 0.6161 loss_db: 0.2072 2022/10/25 23:50:47 - mmengine - INFO - Epoch(train) [304][10/63] lr: 2.7201e-03 eta: 13:36:56 time: 0.9333 data_time: 0.2089 memory: 16131 loss: 2.1268 loss_prob: 1.2773 loss_thr: 0.6382 loss_db: 0.2113 2022/10/25 23:50:52 - mmengine - INFO - Epoch(train) [304][15/63] lr: 2.7201e-03 eta: 13:36:56 time: 0.7750 data_time: 0.0101 memory: 16131 loss: 2.1291 loss_prob: 1.2836 loss_thr: 0.6373 loss_db: 0.2081 2022/10/25 23:50:55 - mmengine - INFO - Epoch(train) [304][20/63] lr: 2.7201e-03 eta: 13:36:46 time: 0.8397 data_time: 0.0119 memory: 16131 loss: 2.1311 loss_prob: 1.2858 loss_thr: 0.6296 loss_db: 0.2156 2022/10/25 23:50:58 - mmengine - INFO - Epoch(train) [304][25/63] lr: 2.7201e-03 eta: 13:36:46 time: 0.6521 data_time: 0.0202 memory: 16131 loss: 2.5739 loss_prob: 1.6380 loss_thr: 0.6720 loss_db: 0.2638 2022/10/25 23:51:01 - mmengine - INFO - Epoch(train) [304][30/63] lr: 2.7201e-03 eta: 13:36:28 time: 0.5436 data_time: 0.0318 memory: 16131 loss: 2.8038 loss_prob: 1.8351 loss_thr: 0.6790 loss_db: 0.2897 2022/10/25 23:51:04 - mmengine - INFO - Epoch(train) [304][35/63] lr: 2.7201e-03 eta: 13:36:28 time: 0.5496 data_time: 0.0213 memory: 16131 loss: 2.6845 loss_prob: 1.7415 loss_thr: 0.6608 loss_db: 0.2822 2022/10/25 23:51:08 - mmengine - INFO - Epoch(train) [304][40/63] lr: 2.7201e-03 eta: 13:36:16 time: 0.7665 data_time: 0.0109 memory: 16131 loss: 2.8516 loss_prob: 1.8588 loss_thr: 0.6957 loss_db: 0.2971 2022/10/25 23:51:12 - mmengine - INFO - Epoch(train) [304][45/63] lr: 2.7201e-03 eta: 13:36:16 time: 0.8606 data_time: 0.0090 memory: 16131 loss: 2.6988 loss_prob: 1.7054 loss_thr: 0.7107 loss_db: 0.2827 2022/10/25 23:51:22 - mmengine - INFO - Epoch(train) [304][50/63] lr: 2.7201e-03 eta: 13:36:22 time: 1.3667 data_time: 0.0154 memory: 16131 loss: 2.3788 loss_prob: 1.4586 loss_thr: 0.6772 loss_db: 0.2430 2022/10/25 23:51:29 - mmengine - INFO - Epoch(train) [304][55/63] lr: 2.7201e-03 eta: 13:36:22 time: 1.6919 data_time: 0.0281 memory: 16131 loss: 2.3080 loss_prob: 1.4267 loss_thr: 0.6510 loss_db: 0.2302 2022/10/25 23:51:33 - mmengine - INFO - Epoch(train) [304][60/63] lr: 2.7201e-03 eta: 13:36:21 time: 1.1298 data_time: 0.0224 memory: 16131 loss: 2.1639 loss_prob: 1.3293 loss_thr: 0.6176 loss_db: 0.2170 2022/10/25 23:51:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:51:44 - mmengine - INFO - Epoch(train) [305][5/63] lr: 2.7174e-03 eta: 13:36:21 time: 1.1931 data_time: 0.2585 memory: 16131 loss: 2.0873 loss_prob: 1.2598 loss_thr: 0.6292 loss_db: 0.1983 2022/10/25 23:51:51 - mmengine - INFO - Epoch(train) [305][10/63] lr: 2.7174e-03 eta: 13:36:21 time: 1.5059 data_time: 0.2575 memory: 16131 loss: 2.0583 loss_prob: 1.2524 loss_thr: 0.6044 loss_db: 0.2015 2022/10/25 23:51:54 - mmengine - INFO - Epoch(train) [305][15/63] lr: 2.7174e-03 eta: 13:36:21 time: 0.9541 data_time: 0.0081 memory: 16131 loss: 2.0612 loss_prob: 1.2414 loss_thr: 0.6114 loss_db: 0.2084 2022/10/25 23:51:58 - mmengine - INFO - Epoch(train) [305][20/63] lr: 2.7174e-03 eta: 13:36:10 time: 0.7823 data_time: 0.0069 memory: 16131 loss: 2.1576 loss_prob: 1.2993 loss_thr: 0.6390 loss_db: 0.2193 2022/10/25 23:52:04 - mmengine - INFO - Epoch(train) [305][25/63] lr: 2.7174e-03 eta: 13:36:10 time: 1.0453 data_time: 0.0183 memory: 16131 loss: 2.2498 loss_prob: 1.3705 loss_thr: 0.6537 loss_db: 0.2255 2022/10/25 23:52:09 - mmengine - INFO - Epoch(train) [305][30/63] lr: 2.7174e-03 eta: 13:36:08 time: 1.1015 data_time: 0.0355 memory: 16131 loss: 2.1866 loss_prob: 1.3251 loss_thr: 0.6435 loss_db: 0.2180 2022/10/25 23:52:12 - mmengine - INFO - Epoch(train) [305][35/63] lr: 2.7174e-03 eta: 13:36:08 time: 0.8129 data_time: 0.0244 memory: 16131 loss: 2.2228 loss_prob: 1.3604 loss_thr: 0.6345 loss_db: 0.2279 2022/10/25 23:52:18 - mmengine - INFO - Epoch(train) [305][40/63] lr: 2.7174e-03 eta: 13:36:00 time: 0.8755 data_time: 0.0081 memory: 16131 loss: 2.2520 loss_prob: 1.3727 loss_thr: 0.6539 loss_db: 0.2254 2022/10/25 23:52:23 - mmengine - INFO - Epoch(train) [305][45/63] lr: 2.7174e-03 eta: 13:36:00 time: 1.0759 data_time: 0.0063 memory: 16131 loss: 2.1755 loss_prob: 1.3024 loss_thr: 0.6619 loss_db: 0.2112 2022/10/25 23:52:27 - mmengine - INFO - Epoch(train) [305][50/63] lr: 2.7174e-03 eta: 13:35:53 time: 0.9165 data_time: 0.0252 memory: 16131 loss: 2.1884 loss_prob: 1.3306 loss_thr: 0.6400 loss_db: 0.2178 2022/10/25 23:52:32 - mmengine - INFO - Epoch(train) [305][55/63] lr: 2.7174e-03 eta: 13:35:53 time: 0.8953 data_time: 0.0263 memory: 16131 loss: 2.2575 loss_prob: 1.3962 loss_thr: 0.6330 loss_db: 0.2283 2022/10/25 23:52:37 - mmengine - INFO - Epoch(train) [305][60/63] lr: 2.7174e-03 eta: 13:35:48 time: 1.0093 data_time: 0.0058 memory: 16131 loss: 2.1796 loss_prob: 1.3357 loss_thr: 0.6266 loss_db: 0.2174 2022/10/25 23:52:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:52:49 - mmengine - INFO - Epoch(train) [306][5/63] lr: 2.7147e-03 eta: 13:35:48 time: 1.3866 data_time: 0.1915 memory: 16131 loss: 2.0177 loss_prob: 1.2106 loss_thr: 0.6113 loss_db: 0.1957 2022/10/25 23:52:58 - mmengine - INFO - Epoch(train) [306][10/63] lr: 2.7147e-03 eta: 13:35:53 time: 1.6960 data_time: 0.1985 memory: 16131 loss: 2.0681 loss_prob: 1.2363 loss_thr: 0.6321 loss_db: 0.1997 2022/10/25 23:53:03 - mmengine - INFO - Epoch(train) [306][15/63] lr: 2.7147e-03 eta: 13:35:53 time: 1.4095 data_time: 0.0138 memory: 16131 loss: 2.1258 loss_prob: 1.2720 loss_thr: 0.6434 loss_db: 0.2104 2022/10/25 23:53:09 - mmengine - INFO - Epoch(train) [306][20/63] lr: 2.7147e-03 eta: 13:35:54 time: 1.1760 data_time: 0.0089 memory: 16131 loss: 2.0763 loss_prob: 1.2295 loss_thr: 0.6431 loss_db: 0.2038 2022/10/25 23:53:15 - mmengine - INFO - Epoch(train) [306][25/63] lr: 2.7147e-03 eta: 13:35:54 time: 1.2239 data_time: 0.0139 memory: 16131 loss: 2.0217 loss_prob: 1.1886 loss_thr: 0.6358 loss_db: 0.1973 2022/10/25 23:53:21 - mmengine - INFO - Epoch(train) [306][30/63] lr: 2.7147e-03 eta: 13:35:54 time: 1.1686 data_time: 0.0439 memory: 16131 loss: 1.9916 loss_prob: 1.1616 loss_thr: 0.6375 loss_db: 0.1925 2022/10/25 23:53:24 - mmengine - INFO - Epoch(train) [306][35/63] lr: 2.7147e-03 eta: 13:35:54 time: 0.8796 data_time: 0.0419 memory: 16131 loss: 1.9851 loss_prob: 1.1458 loss_thr: 0.6532 loss_db: 0.1860 2022/10/25 23:53:29 - mmengine - INFO - Epoch(train) [306][40/63] lr: 2.7147e-03 eta: 13:35:44 time: 0.8157 data_time: 0.0098 memory: 16131 loss: 1.9372 loss_prob: 1.1217 loss_thr: 0.6342 loss_db: 0.1813 2022/10/25 23:53:34 - mmengine - INFO - Epoch(train) [306][45/63] lr: 2.7147e-03 eta: 13:35:44 time: 1.0000 data_time: 0.0050 memory: 16131 loss: 1.8538 loss_prob: 1.0921 loss_thr: 0.5864 loss_db: 0.1753 2022/10/25 23:53:40 - mmengine - INFO - Epoch(train) [306][50/63] lr: 2.7147e-03 eta: 13:35:42 time: 1.0935 data_time: 0.0155 memory: 16131 loss: 1.8985 loss_prob: 1.1255 loss_thr: 0.5919 loss_db: 0.1811 2022/10/25 23:53:47 - mmengine - INFO - Epoch(train) [306][55/63] lr: 2.7147e-03 eta: 13:35:42 time: 1.2891 data_time: 0.0274 memory: 16131 loss: 2.0369 loss_prob: 1.2272 loss_thr: 0.6101 loss_db: 0.1996 2022/10/25 23:53:57 - mmengine - INFO - Epoch(train) [306][60/63] lr: 2.7147e-03 eta: 13:35:55 time: 1.6294 data_time: 0.0189 memory: 16131 loss: 2.0794 loss_prob: 1.2577 loss_thr: 0.6158 loss_db: 0.2059 2022/10/25 23:53:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:54:10 - mmengine - INFO - Epoch(train) [307][5/63] lr: 2.7119e-03 eta: 13:35:55 time: 1.6260 data_time: 0.2439 memory: 16131 loss: 1.9874 loss_prob: 1.1712 loss_thr: 0.6268 loss_db: 0.1893 2022/10/25 23:54:16 - mmengine - INFO - Epoch(train) [307][10/63] lr: 2.7119e-03 eta: 13:35:59 time: 1.6566 data_time: 0.2419 memory: 16131 loss: 1.9369 loss_prob: 1.1321 loss_thr: 0.6187 loss_db: 0.1861 2022/10/25 23:54:23 - mmengine - INFO - Epoch(train) [307][15/63] lr: 2.7119e-03 eta: 13:35:59 time: 1.3747 data_time: 0.0070 memory: 16131 loss: 1.9097 loss_prob: 1.0996 loss_thr: 0.6282 loss_db: 0.1819 2022/10/25 23:54:27 - mmengine - INFO - Epoch(train) [307][20/63] lr: 2.7119e-03 eta: 13:35:56 time: 1.0530 data_time: 0.0121 memory: 16131 loss: 2.0022 loss_prob: 1.1706 loss_thr: 0.6342 loss_db: 0.1974 2022/10/25 23:54:32 - mmengine - INFO - Epoch(train) [307][25/63] lr: 2.7119e-03 eta: 13:35:56 time: 0.9019 data_time: 0.0294 memory: 16131 loss: 1.8858 loss_prob: 1.1047 loss_thr: 0.6007 loss_db: 0.1804 2022/10/25 23:54:39 - mmengine - INFO - Epoch(train) [307][30/63] lr: 2.7119e-03 eta: 13:35:59 time: 1.2876 data_time: 0.0482 memory: 16131 loss: 1.9082 loss_prob: 1.1232 loss_thr: 0.6048 loss_db: 0.1803 2022/10/25 23:54:45 - mmengine - INFO - Epoch(train) [307][35/63] lr: 2.7119e-03 eta: 13:35:59 time: 1.2407 data_time: 0.0336 memory: 16131 loss: 2.0327 loss_prob: 1.1943 loss_thr: 0.6399 loss_db: 0.1984 2022/10/25 23:54:49 - mmengine - INFO - Epoch(train) [307][40/63] lr: 2.7119e-03 eta: 13:35:54 time: 0.9698 data_time: 0.0128 memory: 16131 loss: 2.0506 loss_prob: 1.2059 loss_thr: 0.6427 loss_db: 0.2020 2022/10/25 23:54:56 - mmengine - INFO - Epoch(train) [307][45/63] lr: 2.7119e-03 eta: 13:35:54 time: 1.0718 data_time: 0.0120 memory: 16131 loss: 2.0256 loss_prob: 1.2009 loss_thr: 0.6219 loss_db: 0.2028 2022/10/25 23:55:02 - mmengine - INFO - Epoch(train) [307][50/63] lr: 2.7119e-03 eta: 13:35:58 time: 1.3299 data_time: 0.0163 memory: 16131 loss: 2.1001 loss_prob: 1.2387 loss_thr: 0.6543 loss_db: 0.2071 2022/10/25 23:55:07 - mmengine - INFO - Epoch(train) [307][55/63] lr: 2.7119e-03 eta: 13:35:58 time: 1.1516 data_time: 0.0245 memory: 16131 loss: 2.0434 loss_prob: 1.1870 loss_thr: 0.6628 loss_db: 0.1937 2022/10/25 23:55:11 - mmengine - INFO - Epoch(train) [307][60/63] lr: 2.7119e-03 eta: 13:35:50 time: 0.8939 data_time: 0.0179 memory: 16131 loss: 1.8933 loss_prob: 1.0976 loss_thr: 0.6168 loss_db: 0.1789 2022/10/25 23:55:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:55:24 - mmengine - INFO - Epoch(train) [308][5/63] lr: 2.7092e-03 eta: 13:35:50 time: 1.3287 data_time: 0.2883 memory: 16131 loss: 1.9320 loss_prob: 1.1246 loss_thr: 0.6240 loss_db: 0.1834 2022/10/25 23:55:30 - mmengine - INFO - Epoch(train) [308][10/63] lr: 2.7092e-03 eta: 13:35:55 time: 1.6681 data_time: 0.2989 memory: 16131 loss: 1.9775 loss_prob: 1.1847 loss_thr: 0.6031 loss_db: 0.1897 2022/10/25 23:55:38 - mmengine - INFO - Epoch(train) [308][15/63] lr: 2.7092e-03 eta: 13:35:55 time: 1.3949 data_time: 0.0206 memory: 16131 loss: 1.9476 loss_prob: 1.1738 loss_thr: 0.5844 loss_db: 0.1895 2022/10/25 23:55:42 - mmengine - INFO - Epoch(train) [308][20/63] lr: 2.7092e-03 eta: 13:35:55 time: 1.1753 data_time: 0.0056 memory: 16131 loss: 1.8894 loss_prob: 1.1129 loss_thr: 0.5971 loss_db: 0.1794 2022/10/25 23:55:45 - mmengine - INFO - Epoch(train) [308][25/63] lr: 2.7092e-03 eta: 13:35:55 time: 0.7616 data_time: 0.0132 memory: 16131 loss: 1.9362 loss_prob: 1.1480 loss_thr: 0.5994 loss_db: 0.1888 2022/10/25 23:55:50 - mmengine - INFO - Epoch(train) [308][30/63] lr: 2.7092e-03 eta: 13:35:45 time: 0.8544 data_time: 0.0417 memory: 16131 loss: 1.9750 loss_prob: 1.1745 loss_thr: 0.6081 loss_db: 0.1923 2022/10/25 23:55:54 - mmengine - INFO - Epoch(train) [308][35/63] lr: 2.7092e-03 eta: 13:35:45 time: 0.9140 data_time: 0.0375 memory: 16131 loss: 1.9195 loss_prob: 1.1151 loss_thr: 0.6239 loss_db: 0.1805 2022/10/25 23:56:00 - mmengine - INFO - Epoch(train) [308][40/63] lr: 2.7092e-03 eta: 13:35:40 time: 0.9799 data_time: 0.0103 memory: 16131 loss: 1.9053 loss_prob: 1.0957 loss_thr: 0.6300 loss_db: 0.1795 2022/10/25 23:56:09 - mmengine - INFO - Epoch(train) [308][45/63] lr: 2.7092e-03 eta: 13:35:40 time: 1.4478 data_time: 0.0083 memory: 16131 loss: 2.1265 loss_prob: 1.2627 loss_thr: 0.6607 loss_db: 0.2031 2022/10/25 23:56:16 - mmengine - INFO - Epoch(train) [308][50/63] lr: 2.7092e-03 eta: 13:35:51 time: 1.5662 data_time: 0.0136 memory: 16131 loss: 2.1651 loss_prob: 1.2844 loss_thr: 0.6718 loss_db: 0.2089 2022/10/25 23:56:19 - mmengine - INFO - Epoch(train) [308][55/63] lr: 2.7092e-03 eta: 13:35:51 time: 1.0489 data_time: 0.0252 memory: 16131 loss: 1.9707 loss_prob: 1.1484 loss_thr: 0.6294 loss_db: 0.1930 2022/10/25 23:56:25 - mmengine - INFO - Epoch(train) [308][60/63] lr: 2.7092e-03 eta: 13:35:43 time: 0.8802 data_time: 0.0209 memory: 16131 loss: 1.8962 loss_prob: 1.1053 loss_thr: 0.6051 loss_db: 0.1858 2022/10/25 23:56:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:56:39 - mmengine - INFO - Epoch(train) [309][5/63] lr: 2.7065e-03 eta: 13:35:43 time: 1.7324 data_time: 0.2392 memory: 16131 loss: 1.9655 loss_prob: 1.1499 loss_thr: 0.6270 loss_db: 0.1885 2022/10/25 23:56:45 - mmengine - INFO - Epoch(train) [309][10/63] lr: 2.7065e-03 eta: 13:35:48 time: 1.6918 data_time: 0.2416 memory: 16131 loss: 1.9127 loss_prob: 1.1082 loss_thr: 0.6214 loss_db: 0.1831 2022/10/25 23:56:50 - mmengine - INFO - Epoch(train) [309][15/63] lr: 2.7065e-03 eta: 13:35:48 time: 1.0948 data_time: 0.0258 memory: 16131 loss: 1.8949 loss_prob: 1.1094 loss_thr: 0.6026 loss_db: 0.1829 2022/10/25 23:56:55 - mmengine - INFO - Epoch(train) [309][20/63] lr: 2.7065e-03 eta: 13:35:43 time: 1.0122 data_time: 0.0253 memory: 16131 loss: 1.8951 loss_prob: 1.1190 loss_thr: 0.5951 loss_db: 0.1810 2022/10/25 23:56:59 - mmengine - INFO - Epoch(train) [309][25/63] lr: 2.7065e-03 eta: 13:35:43 time: 0.9498 data_time: 0.0180 memory: 16131 loss: 1.8926 loss_prob: 1.1064 loss_thr: 0.6039 loss_db: 0.1823 2022/10/25 23:57:06 - mmengine - INFO - Epoch(train) [309][30/63] lr: 2.7065e-03 eta: 13:35:40 time: 1.0566 data_time: 0.0382 memory: 16131 loss: 1.8617 loss_prob: 1.0789 loss_thr: 0.6035 loss_db: 0.1793 2022/10/25 23:57:11 - mmengine - INFO - Epoch(train) [309][35/63] lr: 2.7065e-03 eta: 13:35:40 time: 1.1530 data_time: 0.0284 memory: 16131 loss: 1.8065 loss_prob: 1.0415 loss_thr: 0.5940 loss_db: 0.1710 2022/10/25 23:57:16 - mmengine - INFO - Epoch(train) [309][40/63] lr: 2.7065e-03 eta: 13:35:35 time: 0.9896 data_time: 0.0224 memory: 16131 loss: 1.9573 loss_prob: 1.1534 loss_thr: 0.6212 loss_db: 0.1827 2022/10/25 23:57:24 - mmengine - INFO - Epoch(train) [309][45/63] lr: 2.7065e-03 eta: 13:35:35 time: 1.3138 data_time: 0.0219 memory: 16131 loss: 1.9072 loss_prob: 1.1088 loss_thr: 0.6236 loss_db: 0.1748 2022/10/25 23:57:29 - mmengine - INFO - Epoch(train) [309][50/63] lr: 2.7065e-03 eta: 13:35:39 time: 1.3140 data_time: 0.0160 memory: 16131 loss: 1.9826 loss_prob: 1.1667 loss_thr: 0.6284 loss_db: 0.1875 2022/10/25 23:57:34 - mmengine - INFO - Epoch(train) [309][55/63] lr: 2.7065e-03 eta: 13:35:39 time: 1.0291 data_time: 0.0352 memory: 16131 loss: 2.1591 loss_prob: 1.2999 loss_thr: 0.6479 loss_db: 0.2114 2022/10/25 23:57:41 - mmengine - INFO - Epoch(train) [309][60/63] lr: 2.7065e-03 eta: 13:35:40 time: 1.2207 data_time: 0.0244 memory: 16131 loss: 2.0551 loss_prob: 1.2190 loss_thr: 0.6316 loss_db: 0.2044 2022/10/25 23:57:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:57:51 - mmengine - INFO - Epoch(train) [310][5/63] lr: 2.7037e-03 eta: 13:35:40 time: 1.2452 data_time: 0.3099 memory: 16131 loss: 1.9960 loss_prob: 1.1538 loss_thr: 0.6498 loss_db: 0.1924 2022/10/25 23:57:56 - mmengine - INFO - Epoch(train) [310][10/63] lr: 2.7037e-03 eta: 13:35:33 time: 1.2728 data_time: 0.3117 memory: 16131 loss: 1.9321 loss_prob: 1.1341 loss_thr: 0.6161 loss_db: 0.1820 2022/10/25 23:58:04 - mmengine - INFO - Epoch(train) [310][15/63] lr: 2.7037e-03 eta: 13:35:33 time: 1.2984 data_time: 0.0126 memory: 16131 loss: 1.9255 loss_prob: 1.1248 loss_thr: 0.6163 loss_db: 0.1844 2022/10/25 23:58:11 - mmengine - INFO - Epoch(train) [310][20/63] lr: 2.7037e-03 eta: 13:35:40 time: 1.4282 data_time: 0.0089 memory: 16131 loss: 2.0484 loss_prob: 1.2119 loss_thr: 0.6391 loss_db: 0.1974 2022/10/25 23:58:14 - mmengine - INFO - Epoch(train) [310][25/63] lr: 2.7037e-03 eta: 13:35:40 time: 0.9593 data_time: 0.0437 memory: 16131 loss: 2.0788 loss_prob: 1.2487 loss_thr: 0.6326 loss_db: 0.1975 2022/10/25 23:58:22 - mmengine - INFO - Epoch(train) [310][30/63] lr: 2.7037e-03 eta: 13:35:38 time: 1.0939 data_time: 0.0466 memory: 16131 loss: 2.0033 loss_prob: 1.2153 loss_thr: 0.5938 loss_db: 0.1941 2022/10/25 23:58:26 - mmengine - INFO - Epoch(train) [310][35/63] lr: 2.7037e-03 eta: 13:35:38 time: 1.1988 data_time: 0.0113 memory: 16131 loss: 1.9167 loss_prob: 1.1346 loss_thr: 0.5995 loss_db: 0.1826 2022/10/25 23:58:31 - mmengine - INFO - Epoch(train) [310][40/63] lr: 2.7037e-03 eta: 13:35:30 time: 0.9208 data_time: 0.0080 memory: 16131 loss: 1.8140 loss_prob: 1.0497 loss_thr: 0.5969 loss_db: 0.1674 2022/10/25 23:58:36 - mmengine - INFO - Epoch(train) [310][45/63] lr: 2.7037e-03 eta: 13:35:30 time: 0.9895 data_time: 0.0142 memory: 16131 loss: 1.8353 loss_prob: 1.0769 loss_thr: 0.5817 loss_db: 0.1768 2022/10/25 23:58:39 - mmengine - INFO - Epoch(train) [310][50/63] lr: 2.7037e-03 eta: 13:35:20 time: 0.8294 data_time: 0.0349 memory: 16131 loss: 1.8571 loss_prob: 1.0858 loss_thr: 0.5912 loss_db: 0.1801 2022/10/25 23:58:46 - mmengine - INFO - Epoch(train) [310][55/63] lr: 2.7037e-03 eta: 13:35:20 time: 1.0182 data_time: 0.0295 memory: 16131 loss: 1.9079 loss_prob: 1.1210 loss_thr: 0.6050 loss_db: 0.1819 2022/10/25 23:58:50 - mmengine - INFO - Epoch(train) [310][60/63] lr: 2.7037e-03 eta: 13:35:18 time: 1.1106 data_time: 0.0089 memory: 16131 loss: 2.0076 loss_prob: 1.1933 loss_thr: 0.6244 loss_db: 0.1900 2022/10/25 23:58:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/25 23:59:01 - mmengine - INFO - Epoch(train) [311][5/63] lr: 2.7010e-03 eta: 13:35:18 time: 1.1994 data_time: 0.2565 memory: 16131 loss: 1.8763 loss_prob: 1.0957 loss_thr: 0.5985 loss_db: 0.1822 2022/10/25 23:59:06 - mmengine - INFO - Epoch(train) [311][10/63] lr: 2.7010e-03 eta: 13:35:14 time: 1.3571 data_time: 0.2601 memory: 16131 loss: 1.9185 loss_prob: 1.1309 loss_thr: 0.6016 loss_db: 0.1860 2022/10/25 23:59:10 - mmengine - INFO - Epoch(train) [311][15/63] lr: 2.7010e-03 eta: 13:35:14 time: 0.9211 data_time: 0.0109 memory: 16131 loss: 1.9468 loss_prob: 1.1550 loss_thr: 0.6047 loss_db: 0.1871 2022/10/25 23:59:16 - mmengine - INFO - Epoch(train) [311][20/63] lr: 2.7010e-03 eta: 13:35:10 time: 1.0670 data_time: 0.0096 memory: 16131 loss: 1.8213 loss_prob: 1.0688 loss_thr: 0.5795 loss_db: 0.1730 2022/10/25 23:59:24 - mmengine - INFO - Epoch(train) [311][25/63] lr: 2.7010e-03 eta: 13:35:10 time: 1.4095 data_time: 0.0368 memory: 16131 loss: 1.7928 loss_prob: 1.0414 loss_thr: 0.5803 loss_db: 0.1712 2022/10/25 23:59:29 - mmengine - INFO - Epoch(train) [311][30/63] lr: 2.7010e-03 eta: 13:35:12 time: 1.2497 data_time: 0.0514 memory: 16131 loss: 1.7579 loss_prob: 1.0107 loss_thr: 0.5819 loss_db: 0.1653 2022/10/25 23:59:35 - mmengine - INFO - Epoch(train) [311][35/63] lr: 2.7010e-03 eta: 13:35:12 time: 1.0576 data_time: 0.0233 memory: 16131 loss: 1.8439 loss_prob: 1.0774 loss_thr: 0.5905 loss_db: 0.1760 2022/10/25 23:59:40 - mmengine - INFO - Epoch(train) [311][40/63] lr: 2.7010e-03 eta: 13:35:11 time: 1.1152 data_time: 0.0074 memory: 16131 loss: 1.8950 loss_prob: 1.1173 loss_thr: 0.5953 loss_db: 0.1823 2022/10/25 23:59:43 - mmengine - INFO - Epoch(train) [311][45/63] lr: 2.7010e-03 eta: 13:35:11 time: 0.8185 data_time: 0.0065 memory: 16131 loss: 1.8212 loss_prob: 1.0589 loss_thr: 0.5899 loss_db: 0.1724 2022/10/25 23:59:50 - mmengine - INFO - Epoch(train) [311][50/63] lr: 2.7010e-03 eta: 13:35:05 time: 0.9711 data_time: 0.0241 memory: 16131 loss: 1.8091 loss_prob: 1.0488 loss_thr: 0.5871 loss_db: 0.1732 2022/10/25 23:59:55 - mmengine - INFO - Epoch(train) [311][55/63] lr: 2.7010e-03 eta: 13:35:05 time: 1.1638 data_time: 0.0297 memory: 16131 loss: 1.8326 loss_prob: 1.0681 loss_thr: 0.5877 loss_db: 0.1768 2022/10/25 23:59:57 - mmengine - INFO - Epoch(train) [311][60/63] lr: 2.7010e-03 eta: 13:34:53 time: 0.7679 data_time: 0.0117 memory: 16131 loss: 1.9693 loss_prob: 1.1694 loss_thr: 0.6081 loss_db: 0.1918 2022/10/25 23:59:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:00:06 - mmengine - INFO - Epoch(train) [312][5/63] lr: 2.6983e-03 eta: 13:34:53 time: 0.9238 data_time: 0.1829 memory: 16131 loss: 2.0370 loss_prob: 1.2187 loss_thr: 0.6204 loss_db: 0.1979 2022/10/26 00:00:09 - mmengine - INFO - Epoch(train) [312][10/63] lr: 2.6983e-03 eta: 13:34:37 time: 0.9771 data_time: 0.1937 memory: 16131 loss: 2.1053 loss_prob: 1.2586 loss_thr: 0.6438 loss_db: 0.2029 2022/10/26 00:00:12 - mmengine - INFO - Epoch(train) [312][15/63] lr: 2.6983e-03 eta: 13:34:37 time: 0.6294 data_time: 0.0213 memory: 16131 loss: 1.9614 loss_prob: 1.1578 loss_thr: 0.6154 loss_db: 0.1882 2022/10/26 00:00:17 - mmengine - INFO - Epoch(train) [312][20/63] lr: 2.6983e-03 eta: 13:34:27 time: 0.8306 data_time: 0.0133 memory: 16131 loss: 1.8967 loss_prob: 1.1143 loss_thr: 0.5953 loss_db: 0.1870 2022/10/26 00:00:22 - mmengine - INFO - Epoch(train) [312][25/63] lr: 2.6983e-03 eta: 13:34:27 time: 0.9914 data_time: 0.0207 memory: 16131 loss: 1.8501 loss_prob: 1.0767 loss_thr: 0.5894 loss_db: 0.1839 2022/10/26 00:00:30 - mmengine - INFO - Epoch(train) [312][30/63] lr: 2.6983e-03 eta: 13:34:32 time: 1.3437 data_time: 0.0356 memory: 16131 loss: 1.8136 loss_prob: 1.0431 loss_thr: 0.5983 loss_db: 0.1722 2022/10/26 00:00:38 - mmengine - INFO - Epoch(train) [312][35/63] lr: 2.6983e-03 eta: 13:34:32 time: 1.6625 data_time: 0.0340 memory: 16131 loss: 2.0091 loss_prob: 1.1639 loss_thr: 0.6562 loss_db: 0.1890 2022/10/26 00:00:41 - mmengine - INFO - Epoch(train) [312][40/63] lr: 2.6983e-03 eta: 13:34:30 time: 1.1000 data_time: 0.0168 memory: 16131 loss: 2.0177 loss_prob: 1.2006 loss_thr: 0.6230 loss_db: 0.1942 2022/10/26 00:00:47 - mmengine - INFO - Epoch(train) [312][45/63] lr: 2.6983e-03 eta: 13:34:30 time: 0.8875 data_time: 0.0099 memory: 16131 loss: 1.7642 loss_prob: 1.0430 loss_thr: 0.5559 loss_db: 0.1653 2022/10/26 00:00:52 - mmengine - INFO - Epoch(train) [312][50/63] lr: 2.6983e-03 eta: 13:34:27 time: 1.0999 data_time: 0.0218 memory: 16131 loss: 1.8262 loss_prob: 1.0875 loss_thr: 0.5686 loss_db: 0.1701 2022/10/26 00:00:59 - mmengine - INFO - Epoch(train) [312][55/63] lr: 2.6983e-03 eta: 13:34:27 time: 1.1290 data_time: 0.0264 memory: 16131 loss: 2.2362 loss_prob: 1.3957 loss_thr: 0.6253 loss_db: 0.2152 2022/10/26 00:01:07 - mmengine - INFO - Epoch(train) [312][60/63] lr: 2.6983e-03 eta: 13:34:35 time: 1.4611 data_time: 0.0188 memory: 16131 loss: 2.2805 loss_prob: 1.4316 loss_thr: 0.6262 loss_db: 0.2227 2022/10/26 00:01:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:01:18 - mmengine - INFO - Epoch(train) [313][5/63] lr: 2.6955e-03 eta: 13:34:35 time: 1.5013 data_time: 0.2461 memory: 16131 loss: 1.9088 loss_prob: 1.1217 loss_thr: 0.6070 loss_db: 0.1801 2022/10/26 00:01:27 - mmengine - INFO - Epoch(train) [313][10/63] lr: 2.6955e-03 eta: 13:34:41 time: 1.7377 data_time: 0.2435 memory: 16131 loss: 1.8779 loss_prob: 1.1025 loss_thr: 0.6004 loss_db: 0.1749 2022/10/26 00:01:31 - mmengine - INFO - Epoch(train) [313][15/63] lr: 2.6955e-03 eta: 13:34:41 time: 1.3148 data_time: 0.0071 memory: 16131 loss: 1.9097 loss_prob: 1.1309 loss_thr: 0.5978 loss_db: 0.1810 2022/10/26 00:01:40 - mmengine - INFO - Epoch(train) [313][20/63] lr: 2.6955e-03 eta: 13:34:43 time: 1.2584 data_time: 0.0090 memory: 16131 loss: 1.9402 loss_prob: 1.1459 loss_thr: 0.6055 loss_db: 0.1888 2022/10/26 00:01:46 - mmengine - INFO - Epoch(train) [313][25/63] lr: 2.6955e-03 eta: 13:34:43 time: 1.4485 data_time: 0.0137 memory: 16131 loss: 2.1656 loss_prob: 1.3132 loss_thr: 0.6401 loss_db: 0.2123 2022/10/26 00:01:54 - mmengine - INFO - Epoch(train) [313][30/63] lr: 2.6955e-03 eta: 13:34:49 time: 1.3647 data_time: 0.0721 memory: 16131 loss: 2.1958 loss_prob: 1.3392 loss_thr: 0.6430 loss_db: 0.2136 2022/10/26 00:02:00 - mmengine - INFO - Epoch(train) [313][35/63] lr: 2.6955e-03 eta: 13:34:49 time: 1.3581 data_time: 0.0668 memory: 16131 loss: 1.9850 loss_prob: 1.1710 loss_thr: 0.6220 loss_db: 0.1920 2022/10/26 00:02:06 - mmengine - INFO - Epoch(train) [313][40/63] lr: 2.6955e-03 eta: 13:34:50 time: 1.2216 data_time: 0.0074 memory: 16131 loss: 1.9997 loss_prob: 1.1715 loss_thr: 0.6358 loss_db: 0.1924 2022/10/26 00:02:15 - mmengine - INFO - Epoch(train) [313][45/63] lr: 2.6955e-03 eta: 13:34:50 time: 1.5781 data_time: 0.0074 memory: 16131 loss: 2.2341 loss_prob: 1.3687 loss_thr: 0.6370 loss_db: 0.2284 2022/10/26 00:02:22 - mmengine - INFO - Epoch(train) [313][50/63] lr: 2.6955e-03 eta: 13:35:02 time: 1.6068 data_time: 0.0241 memory: 16131 loss: 3.0338 loss_prob: 2.0282 loss_thr: 0.6788 loss_db: 0.3268 2022/10/26 00:02:28 - mmengine - INFO - Epoch(train) [313][55/63] lr: 2.6955e-03 eta: 13:35:02 time: 1.2554 data_time: 0.0324 memory: 16131 loss: 3.0965 loss_prob: 2.0774 loss_thr: 0.6913 loss_db: 0.3279 2022/10/26 00:02:33 - mmengine - INFO - Epoch(train) [313][60/63] lr: 2.6955e-03 eta: 13:34:58 time: 1.0564 data_time: 0.0145 memory: 16131 loss: 2.4345 loss_prob: 1.5460 loss_thr: 0.6375 loss_db: 0.2510 2022/10/26 00:02:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:02:44 - mmengine - INFO - Epoch(train) [314][5/63] lr: 2.6928e-03 eta: 13:34:58 time: 1.3453 data_time: 0.1942 memory: 16131 loss: 2.1498 loss_prob: 1.3178 loss_thr: 0.6200 loss_db: 0.2120 2022/10/26 00:02:52 - mmengine - INFO - Epoch(train) [314][10/63] lr: 2.6928e-03 eta: 13:35:04 time: 1.7381 data_time: 0.2034 memory: 16131 loss: 2.0484 loss_prob: 1.2225 loss_thr: 0.6255 loss_db: 0.2004 2022/10/26 00:02:57 - mmengine - INFO - Epoch(train) [314][15/63] lr: 2.6928e-03 eta: 13:35:04 time: 1.2427 data_time: 0.0166 memory: 16131 loss: 2.0163 loss_prob: 1.2064 loss_thr: 0.6148 loss_db: 0.1951 2022/10/26 00:03:01 - mmengine - INFO - Epoch(train) [314][20/63] lr: 2.6928e-03 eta: 13:34:57 time: 0.9524 data_time: 0.0100 memory: 16131 loss: 2.1548 loss_prob: 1.3205 loss_thr: 0.6201 loss_db: 0.2142 2022/10/26 00:03:06 - mmengine - INFO - Epoch(train) [314][25/63] lr: 2.6928e-03 eta: 13:34:57 time: 0.9423 data_time: 0.0134 memory: 16131 loss: 2.2908 loss_prob: 1.4050 loss_thr: 0.6557 loss_db: 0.2300 2022/10/26 00:03:12 - mmengine - INFO - Epoch(train) [314][30/63] lr: 2.6928e-03 eta: 13:34:55 time: 1.1113 data_time: 0.0406 memory: 16131 loss: 2.2144 loss_prob: 1.3234 loss_thr: 0.6740 loss_db: 0.2170 2022/10/26 00:03:17 - mmengine - INFO - Epoch(train) [314][35/63] lr: 2.6928e-03 eta: 13:34:55 time: 1.0292 data_time: 0.0486 memory: 16131 loss: 2.0575 loss_prob: 1.2122 loss_thr: 0.6477 loss_db: 0.1976 2022/10/26 00:03:22 - mmengine - INFO - Epoch(train) [314][40/63] lr: 2.6928e-03 eta: 13:34:50 time: 1.0057 data_time: 0.0301 memory: 16131 loss: 1.8802 loss_prob: 1.1050 loss_thr: 0.5949 loss_db: 0.1803 2022/10/26 00:03:27 - mmengine - INFO - Epoch(train) [314][45/63] lr: 2.6928e-03 eta: 13:34:50 time: 1.0447 data_time: 0.0181 memory: 16131 loss: 1.7875 loss_prob: 1.0356 loss_thr: 0.5831 loss_db: 0.1688 2022/10/26 00:03:30 - mmengine - INFO - Epoch(train) [314][50/63] lr: 2.6928e-03 eta: 13:34:39 time: 0.7902 data_time: 0.0134 memory: 16131 loss: 1.9102 loss_prob: 1.1118 loss_thr: 0.6186 loss_db: 0.1799 2022/10/26 00:03:34 - mmengine - INFO - Epoch(train) [314][55/63] lr: 2.6928e-03 eta: 13:34:39 time: 0.6645 data_time: 0.0137 memory: 16131 loss: 2.0492 loss_prob: 1.2233 loss_thr: 0.6269 loss_db: 0.1990 2022/10/26 00:03:36 - mmengine - INFO - Epoch(train) [314][60/63] lr: 2.6928e-03 eta: 13:34:23 time: 0.6232 data_time: 0.0088 memory: 16131 loss: 2.0219 loss_prob: 1.2101 loss_thr: 0.6134 loss_db: 0.1984 2022/10/26 00:03:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:03:48 - mmengine - INFO - Epoch(train) [315][5/63] lr: 2.6901e-03 eta: 13:34:23 time: 1.2439 data_time: 0.2333 memory: 16131 loss: 2.0696 loss_prob: 1.2306 loss_thr: 0.6372 loss_db: 0.2019 2022/10/26 00:03:55 - mmengine - INFO - Epoch(train) [315][10/63] lr: 2.6901e-03 eta: 13:34:28 time: 1.7101 data_time: 0.2301 memory: 16131 loss: 2.2234 loss_prob: 1.3477 loss_thr: 0.6468 loss_db: 0.2289 2022/10/26 00:04:00 - mmengine - INFO - Epoch(train) [315][15/63] lr: 2.6901e-03 eta: 13:34:28 time: 1.2788 data_time: 0.0104 memory: 16131 loss: 2.0652 loss_prob: 1.2421 loss_thr: 0.6218 loss_db: 0.2014 2022/10/26 00:04:06 - mmengine - INFO - Epoch(train) [315][20/63] lr: 2.6901e-03 eta: 13:34:25 time: 1.0881 data_time: 0.0159 memory: 16131 loss: 1.9891 loss_prob: 1.1833 loss_thr: 0.6190 loss_db: 0.1868 2022/10/26 00:04:12 - mmengine - INFO - Epoch(train) [315][25/63] lr: 2.6901e-03 eta: 13:34:25 time: 1.1445 data_time: 0.0122 memory: 16131 loss: 2.0856 loss_prob: 1.2612 loss_thr: 0.6185 loss_db: 0.2059 2022/10/26 00:04:19 - mmengine - INFO - Epoch(train) [315][30/63] lr: 2.6901e-03 eta: 13:34:28 time: 1.3135 data_time: 0.0188 memory: 16131 loss: 2.0856 loss_prob: 1.2466 loss_thr: 0.6310 loss_db: 0.2080 2022/10/26 00:04:26 - mmengine - INFO - Epoch(train) [315][35/63] lr: 2.6901e-03 eta: 13:34:28 time: 1.3890 data_time: 0.0186 memory: 16131 loss: 2.0002 loss_prob: 1.1870 loss_thr: 0.6199 loss_db: 0.1933 2022/10/26 00:04:32 - mmengine - INFO - Epoch(train) [315][40/63] lr: 2.6901e-03 eta: 13:34:32 time: 1.3156 data_time: 0.0073 memory: 16131 loss: 1.9141 loss_prob: 1.1282 loss_thr: 0.6069 loss_db: 0.1790 2022/10/26 00:04:35 - mmengine - INFO - Epoch(train) [315][45/63] lr: 2.6901e-03 eta: 13:34:32 time: 0.9441 data_time: 0.0071 memory: 16131 loss: 1.8004 loss_prob: 1.0488 loss_thr: 0.5794 loss_db: 0.1723 2022/10/26 00:04:40 - mmengine - INFO - Epoch(train) [315][50/63] lr: 2.6901e-03 eta: 13:34:21 time: 0.8049 data_time: 0.0054 memory: 16131 loss: 1.8458 loss_prob: 1.0816 loss_thr: 0.5812 loss_db: 0.1830 2022/10/26 00:04:46 - mmengine - INFO - Epoch(train) [315][55/63] lr: 2.6901e-03 eta: 13:34:21 time: 1.0303 data_time: 0.0259 memory: 16131 loss: 2.1816 loss_prob: 1.3326 loss_thr: 0.6291 loss_db: 0.2198 2022/10/26 00:04:52 - mmengine - INFO - Epoch(train) [315][60/63] lr: 2.6901e-03 eta: 13:34:21 time: 1.1936 data_time: 0.0275 memory: 16131 loss: 2.2379 loss_prob: 1.3703 loss_thr: 0.6441 loss_db: 0.2235 2022/10/26 00:04:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:05:03 - mmengine - INFO - Epoch(train) [316][5/63] lr: 2.6873e-03 eta: 13:34:21 time: 1.4080 data_time: 0.1990 memory: 16131 loss: 2.1793 loss_prob: 1.3300 loss_thr: 0.6331 loss_db: 0.2162 2022/10/26 00:05:07 - mmengine - INFO - Epoch(train) [316][10/63] lr: 2.6873e-03 eta: 13:34:12 time: 1.2001 data_time: 0.2153 memory: 16131 loss: 2.0564 loss_prob: 1.2285 loss_thr: 0.6256 loss_db: 0.2023 2022/10/26 00:05:15 - mmengine - INFO - Epoch(train) [316][15/63] lr: 2.6873e-03 eta: 13:34:12 time: 1.2180 data_time: 0.0255 memory: 16131 loss: 1.9445 loss_prob: 1.1488 loss_thr: 0.6061 loss_db: 0.1897 2022/10/26 00:05:23 - mmengine - INFO - Epoch(train) [316][20/63] lr: 2.6873e-03 eta: 13:34:21 time: 1.5124 data_time: 0.0124 memory: 16131 loss: 2.0828 loss_prob: 1.2407 loss_thr: 0.6398 loss_db: 0.2023 2022/10/26 00:05:31 - mmengine - INFO - Epoch(train) [316][25/63] lr: 2.6873e-03 eta: 13:34:21 time: 1.5736 data_time: 0.0170 memory: 16131 loss: 2.0179 loss_prob: 1.1995 loss_thr: 0.6214 loss_db: 0.1970 2022/10/26 00:05:38 - mmengine - INFO - Epoch(train) [316][30/63] lr: 2.6873e-03 eta: 13:34:30 time: 1.4971 data_time: 0.0416 memory: 16131 loss: 1.9241 loss_prob: 1.1440 loss_thr: 0.5917 loss_db: 0.1885 2022/10/26 00:05:43 - mmengine - INFO - Epoch(train) [316][35/63] lr: 2.6873e-03 eta: 13:34:30 time: 1.2279 data_time: 0.0529 memory: 16131 loss: 2.0887 loss_prob: 1.2529 loss_thr: 0.6330 loss_db: 0.2028 2022/10/26 00:05:48 - mmengine - INFO - Epoch(train) [316][40/63] lr: 2.6873e-03 eta: 13:34:25 time: 1.0303 data_time: 0.0266 memory: 16131 loss: 2.1611 loss_prob: 1.3093 loss_thr: 0.6399 loss_db: 0.2119 2022/10/26 00:05:51 - mmengine - INFO - Epoch(train) [316][45/63] lr: 2.6873e-03 eta: 13:34:25 time: 0.7733 data_time: 0.0135 memory: 16131 loss: 2.1693 loss_prob: 1.3379 loss_thr: 0.6171 loss_db: 0.2144 2022/10/26 00:05:56 - mmengine - INFO - Epoch(train) [316][50/63] lr: 2.6873e-03 eta: 13:34:13 time: 0.7690 data_time: 0.0240 memory: 16131 loss: 2.1340 loss_prob: 1.2996 loss_thr: 0.6256 loss_db: 0.2089 2022/10/26 00:06:03 - mmengine - INFO - Epoch(train) [316][55/63] lr: 2.6873e-03 eta: 13:34:13 time: 1.2042 data_time: 0.0346 memory: 16131 loss: 1.9860 loss_prob: 1.1899 loss_thr: 0.6022 loss_db: 0.1939 2022/10/26 00:06:06 - mmengine - INFO - Epoch(train) [316][60/63] lr: 2.6873e-03 eta: 13:34:09 time: 1.0375 data_time: 0.0277 memory: 16131 loss: 1.9363 loss_prob: 1.1528 loss_thr: 0.5941 loss_db: 0.1894 2022/10/26 00:06:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:06:16 - mmengine - INFO - Epoch(train) [317][5/63] lr: 2.6846e-03 eta: 13:34:09 time: 1.1323 data_time: 0.2241 memory: 16131 loss: 2.0079 loss_prob: 1.2124 loss_thr: 0.6020 loss_db: 0.1935 2022/10/26 00:06:23 - mmengine - INFO - Epoch(train) [317][10/63] lr: 2.6846e-03 eta: 13:34:09 time: 1.5378 data_time: 0.2242 memory: 16131 loss: 1.9738 loss_prob: 1.1703 loss_thr: 0.6075 loss_db: 0.1959 2022/10/26 00:06:31 - mmengine - INFO - Epoch(train) [317][15/63] lr: 2.6846e-03 eta: 13:34:09 time: 1.4577 data_time: 0.0068 memory: 16131 loss: 2.1000 loss_prob: 1.2660 loss_thr: 0.6236 loss_db: 0.2104 2022/10/26 00:06:35 - mmengine - INFO - Epoch(train) [317][20/63] lr: 2.6846e-03 eta: 13:34:11 time: 1.2612 data_time: 0.0080 memory: 16131 loss: 2.0390 loss_prob: 1.2151 loss_thr: 0.6249 loss_db: 0.1990 2022/10/26 00:06:43 - mmengine - INFO - Epoch(train) [317][25/63] lr: 2.6846e-03 eta: 13:34:11 time: 1.2398 data_time: 0.0314 memory: 16131 loss: 1.9858 loss_prob: 1.1725 loss_thr: 0.6169 loss_db: 0.1964 2022/10/26 00:06:47 - mmengine - INFO - Epoch(train) [317][30/63] lr: 2.6846e-03 eta: 13:34:10 time: 1.1797 data_time: 0.0584 memory: 16131 loss: 2.0535 loss_prob: 1.2524 loss_thr: 0.6009 loss_db: 0.2003 2022/10/26 00:06:50 - mmengine - INFO - Epoch(train) [317][35/63] lr: 2.6846e-03 eta: 13:34:10 time: 0.6973 data_time: 0.0359 memory: 16131 loss: 2.3874 loss_prob: 1.5021 loss_thr: 0.6480 loss_db: 0.2372 2022/10/26 00:06:54 - mmengine - INFO - Epoch(train) [317][40/63] lr: 2.6846e-03 eta: 13:33:56 time: 0.6810 data_time: 0.0103 memory: 16131 loss: 2.2821 loss_prob: 1.4064 loss_thr: 0.6542 loss_db: 0.2215 2022/10/26 00:06:57 - mmengine - INFO - Epoch(train) [317][45/63] lr: 2.6846e-03 eta: 13:33:56 time: 0.6643 data_time: 0.0098 memory: 16131 loss: 1.9510 loss_prob: 1.1420 loss_thr: 0.6274 loss_db: 0.1816 2022/10/26 00:07:00 - mmengine - INFO - Epoch(train) [317][50/63] lr: 2.6846e-03 eta: 13:33:39 time: 0.5932 data_time: 0.0245 memory: 16131 loss: 1.9165 loss_prob: 1.1176 loss_thr: 0.6170 loss_db: 0.1819 2022/10/26 00:07:04 - mmengine - INFO - Epoch(train) [317][55/63] lr: 2.6846e-03 eta: 13:33:39 time: 0.6835 data_time: 0.0332 memory: 16131 loss: 1.9480 loss_prob: 1.1594 loss_thr: 0.5974 loss_db: 0.1911 2022/10/26 00:07:07 - mmengine - INFO - Epoch(train) [317][60/63] lr: 2.6846e-03 eta: 13:33:25 time: 0.6899 data_time: 0.0146 memory: 16131 loss: 2.0679 loss_prob: 1.2490 loss_thr: 0.6175 loss_db: 0.2015 2022/10/26 00:07:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:07:18 - mmengine - INFO - Epoch(train) [318][5/63] lr: 2.6819e-03 eta: 13:33:25 time: 1.2883 data_time: 0.2634 memory: 16131 loss: 1.8741 loss_prob: 1.0800 loss_thr: 0.6200 loss_db: 0.1741 2022/10/26 00:07:26 - mmengine - INFO - Epoch(train) [318][10/63] lr: 2.6819e-03 eta: 13:33:33 time: 1.8310 data_time: 0.2671 memory: 16131 loss: 1.9719 loss_prob: 1.1692 loss_thr: 0.6074 loss_db: 0.1952 2022/10/26 00:07:33 - mmengine - INFO - Epoch(train) [318][15/63] lr: 2.6819e-03 eta: 13:33:33 time: 1.4513 data_time: 0.0104 memory: 16131 loss: 1.9730 loss_prob: 1.1841 loss_thr: 0.5932 loss_db: 0.1957 2022/10/26 00:07:36 - mmengine - INFO - Epoch(train) [318][20/63] lr: 2.6819e-03 eta: 13:33:26 time: 0.9506 data_time: 0.0108 memory: 16131 loss: 2.0404 loss_prob: 1.2012 loss_thr: 0.6505 loss_db: 0.1887 2022/10/26 00:07:40 - mmengine - INFO - Epoch(train) [318][25/63] lr: 2.6819e-03 eta: 13:33:26 time: 0.6782 data_time: 0.0397 memory: 16131 loss: 2.1650 loss_prob: 1.3039 loss_thr: 0.6571 loss_db: 0.2040 2022/10/26 00:07:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:07:43 - mmengine - INFO - Epoch(train) [318][30/63] lr: 2.6819e-03 eta: 13:33:12 time: 0.6629 data_time: 0.0448 memory: 16131 loss: 2.1022 loss_prob: 1.2652 loss_thr: 0.6357 loss_db: 0.2013 2022/10/26 00:07:47 - mmengine - INFO - Epoch(train) [318][35/63] lr: 2.6819e-03 eta: 13:33:12 time: 0.7640 data_time: 0.0197 memory: 16131 loss: 1.9779 loss_prob: 1.1539 loss_thr: 0.6371 loss_db: 0.1869 2022/10/26 00:07:53 - mmengine - INFO - Epoch(train) [318][40/63] lr: 2.6819e-03 eta: 13:33:07 time: 1.0342 data_time: 0.0104 memory: 16131 loss: 1.8304 loss_prob: 1.0412 loss_thr: 0.6213 loss_db: 0.1679 2022/10/26 00:07:57 - mmengine - INFO - Epoch(train) [318][45/63] lr: 2.6819e-03 eta: 13:33:07 time: 0.9622 data_time: 0.0103 memory: 16131 loss: 1.8786 loss_prob: 1.0873 loss_thr: 0.6131 loss_db: 0.1781 2022/10/26 00:08:02 - mmengine - INFO - Epoch(train) [318][50/63] lr: 2.6819e-03 eta: 13:32:58 time: 0.8596 data_time: 0.0382 memory: 16131 loss: 2.1241 loss_prob: 1.2961 loss_thr: 0.6216 loss_db: 0.2064 2022/10/26 00:08:09 - mmengine - INFO - Epoch(train) [318][55/63] lr: 2.6819e-03 eta: 13:32:58 time: 1.1530 data_time: 0.0364 memory: 16131 loss: 2.1669 loss_prob: 1.3417 loss_thr: 0.6170 loss_db: 0.2082 2022/10/26 00:08:11 - mmengine - INFO - Epoch(train) [318][60/63] lr: 2.6819e-03 eta: 13:32:52 time: 0.9839 data_time: 0.0088 memory: 16131 loss: 2.0016 loss_prob: 1.2055 loss_thr: 0.6038 loss_db: 0.1923 2022/10/26 00:08:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:08:21 - mmengine - INFO - Epoch(train) [319][5/63] lr: 2.6791e-03 eta: 13:32:52 time: 1.0534 data_time: 0.2709 memory: 16131 loss: 1.8965 loss_prob: 1.1275 loss_thr: 0.5831 loss_db: 0.1858 2022/10/26 00:08:30 - mmengine - INFO - Epoch(train) [319][10/63] lr: 2.6791e-03 eta: 13:32:57 time: 1.7347 data_time: 0.2692 memory: 16131 loss: 1.7712 loss_prob: 1.0335 loss_thr: 0.5692 loss_db: 0.1685 2022/10/26 00:08:35 - mmengine - INFO - Epoch(train) [319][15/63] lr: 2.6791e-03 eta: 13:32:57 time: 1.4239 data_time: 0.0175 memory: 16131 loss: 1.7269 loss_prob: 1.0034 loss_thr: 0.5604 loss_db: 0.1630 2022/10/26 00:08:41 - mmengine - INFO - Epoch(train) [319][20/63] lr: 2.6791e-03 eta: 13:32:53 time: 1.0383 data_time: 0.0132 memory: 16131 loss: 1.7823 loss_prob: 1.0382 loss_thr: 0.5748 loss_db: 0.1693 2022/10/26 00:08:45 - mmengine - INFO - Epoch(train) [319][25/63] lr: 2.6791e-03 eta: 13:32:53 time: 0.9533 data_time: 0.0334 memory: 16131 loss: 1.8572 loss_prob: 1.0589 loss_thr: 0.6280 loss_db: 0.1702 2022/10/26 00:08:49 - mmengine - INFO - Epoch(train) [319][30/63] lr: 2.6791e-03 eta: 13:32:42 time: 0.8016 data_time: 0.0571 memory: 16131 loss: 1.7979 loss_prob: 1.0182 loss_thr: 0.6152 loss_db: 0.1646 2022/10/26 00:08:54 - mmengine - INFO - Epoch(train) [319][35/63] lr: 2.6791e-03 eta: 13:32:42 time: 0.8988 data_time: 0.0328 memory: 16131 loss: 1.8051 loss_prob: 1.0442 loss_thr: 0.5922 loss_db: 0.1687 2022/10/26 00:08:59 - mmengine - INFO - Epoch(train) [319][40/63] lr: 2.6791e-03 eta: 13:32:37 time: 1.0183 data_time: 0.0103 memory: 16131 loss: 1.9617 loss_prob: 1.1608 loss_thr: 0.6154 loss_db: 0.1855 2022/10/26 00:09:02 - mmengine - INFO - Epoch(train) [319][45/63] lr: 2.6791e-03 eta: 13:32:37 time: 0.8474 data_time: 0.0102 memory: 16131 loss: 1.8837 loss_prob: 1.0989 loss_thr: 0.6072 loss_db: 0.1776 2022/10/26 00:09:07 - mmengine - INFO - Epoch(train) [319][50/63] lr: 2.6791e-03 eta: 13:32:28 time: 0.8638 data_time: 0.0221 memory: 16131 loss: 1.8222 loss_prob: 1.0492 loss_thr: 0.5984 loss_db: 0.1747 2022/10/26 00:09:12 - mmengine - INFO - Epoch(train) [319][55/63] lr: 2.6791e-03 eta: 13:32:28 time: 0.9544 data_time: 0.0295 memory: 16131 loss: 1.9156 loss_prob: 1.1240 loss_thr: 0.6065 loss_db: 0.1851 2022/10/26 00:09:17 - mmengine - INFO - Epoch(train) [319][60/63] lr: 2.6791e-03 eta: 13:32:21 time: 0.9361 data_time: 0.0144 memory: 16131 loss: 1.9575 loss_prob: 1.1558 loss_thr: 0.6093 loss_db: 0.1924 2022/10/26 00:09:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:09:27 - mmengine - INFO - Epoch(train) [320][5/63] lr: 2.6764e-03 eta: 13:32:21 time: 1.2564 data_time: 0.2181 memory: 16131 loss: 1.7628 loss_prob: 1.0013 loss_thr: 0.5941 loss_db: 0.1673 2022/10/26 00:09:30 - mmengine - INFO - Epoch(train) [320][10/63] lr: 2.6764e-03 eta: 13:32:09 time: 1.1497 data_time: 0.2195 memory: 16131 loss: 1.9138 loss_prob: 1.1265 loss_thr: 0.6094 loss_db: 0.1778 2022/10/26 00:09:36 - mmengine - INFO - Epoch(train) [320][15/63] lr: 2.6764e-03 eta: 13:32:09 time: 0.9300 data_time: 0.0095 memory: 16131 loss: 1.9998 loss_prob: 1.1946 loss_thr: 0.6188 loss_db: 0.1864 2022/10/26 00:09:39 - mmengine - INFO - Epoch(train) [320][20/63] lr: 2.6764e-03 eta: 13:32:02 time: 0.9394 data_time: 0.0067 memory: 16131 loss: 1.9153 loss_prob: 1.1127 loss_thr: 0.6192 loss_db: 0.1834 2022/10/26 00:09:45 - mmengine - INFO - Epoch(train) [320][25/63] lr: 2.6764e-03 eta: 13:32:02 time: 0.8538 data_time: 0.0150 memory: 16131 loss: 1.8882 loss_prob: 1.0915 loss_thr: 0.6189 loss_db: 0.1779 2022/10/26 00:09:48 - mmengine - INFO - Epoch(train) [320][30/63] lr: 2.6764e-03 eta: 13:31:53 time: 0.8586 data_time: 0.0447 memory: 16131 loss: 1.9807 loss_prob: 1.1800 loss_thr: 0.6101 loss_db: 0.1906 2022/10/26 00:09:53 - mmengine - INFO - Epoch(train) [320][35/63] lr: 2.6764e-03 eta: 13:31:53 time: 0.8747 data_time: 0.0402 memory: 16131 loss: 2.0061 loss_prob: 1.2208 loss_thr: 0.5779 loss_db: 0.2073 2022/10/26 00:10:00 - mmengine - INFO - Epoch(train) [320][40/63] lr: 2.6764e-03 eta: 13:31:54 time: 1.2272 data_time: 0.0117 memory: 16131 loss: 1.9113 loss_prob: 1.1448 loss_thr: 0.5710 loss_db: 0.1955 2022/10/26 00:10:07 - mmengine - INFO - Epoch(train) [320][45/63] lr: 2.6764e-03 eta: 13:31:54 time: 1.3851 data_time: 0.0107 memory: 16131 loss: 1.8765 loss_prob: 1.1088 loss_thr: 0.5857 loss_db: 0.1820 2022/10/26 00:10:10 - mmengine - INFO - Epoch(train) [320][50/63] lr: 2.6764e-03 eta: 13:31:49 time: 1.0303 data_time: 0.0190 memory: 16131 loss: 2.0052 loss_prob: 1.2162 loss_thr: 0.5883 loss_db: 0.2007 2022/10/26 00:10:18 - mmengine - INFO - Epoch(train) [320][55/63] lr: 2.6764e-03 eta: 13:31:49 time: 1.1146 data_time: 0.0299 memory: 16131 loss: 2.2692 loss_prob: 1.4016 loss_thr: 0.6441 loss_db: 0.2235 2022/10/26 00:10:24 - mmengine - INFO - Epoch(train) [320][60/63] lr: 2.6764e-03 eta: 13:31:54 time: 1.3645 data_time: 0.0257 memory: 16131 loss: 2.2083 loss_prob: 1.3526 loss_thr: 0.6401 loss_db: 0.2156 2022/10/26 00:10:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:10:27 - mmengine - INFO - Saving checkpoint at 320 epochs 2022/10/26 00:10:34 - mmengine - INFO - Epoch(val) [320][5/32] eta: 13:31:54 time: 0.5373 data_time: 0.0761 memory: 16131 2022/10/26 00:10:37 - mmengine - INFO - Epoch(val) [320][10/32] eta: 0:00:13 time: 0.5981 data_time: 0.0892 memory: 15724 2022/10/26 00:10:40 - mmengine - INFO - Epoch(val) [320][15/32] eta: 0:00:13 time: 0.5736 data_time: 0.0405 memory: 15724 2022/10/26 00:10:43 - mmengine - INFO - Epoch(val) [320][20/32] eta: 0:00:07 time: 0.6110 data_time: 0.0584 memory: 15724 2022/10/26 00:10:46 - mmengine - INFO - Epoch(val) [320][25/32] eta: 0:00:07 time: 0.6263 data_time: 0.0699 memory: 15724 2022/10/26 00:10:49 - mmengine - INFO - Epoch(val) [320][30/32] eta: 0:00:01 time: 0.5780 data_time: 0.0513 memory: 15724 2022/10/26 00:10:49 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7530, precision: 0.6768, hmean: 0.7129 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7530, precision: 0.7716, hmean: 0.7622 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7472, precision: 0.8130, hmean: 0.7787 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7208, precision: 0.8569, hmean: 0.7829 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6317, precision: 0.9023, hmean: 0.7431 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2258, precision: 0.9670, hmean: 0.3661 2022/10/26 00:10:49 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/26 00:10:49 - mmengine - INFO - Epoch(val) [320][32/32] icdar/precision: 0.8569 icdar/recall: 0.7208 icdar/hmean: 0.7829 2022/10/26 00:11:00 - mmengine - INFO - Epoch(train) [321][5/63] lr: 2.6736e-03 eta: 0:00:01 time: 1.4450 data_time: 0.2417 memory: 16131 loss: 2.1234 loss_prob: 1.2776 loss_thr: 0.6345 loss_db: 0.2113 2022/10/26 00:11:06 - mmengine - INFO - Epoch(train) [321][10/63] lr: 2.6736e-03 eta: 13:31:58 time: 1.7097 data_time: 0.2492 memory: 16131 loss: 2.1228 loss_prob: 1.2780 loss_thr: 0.6393 loss_db: 0.2054 2022/10/26 00:11:12 - mmengine - INFO - Epoch(train) [321][15/63] lr: 2.6736e-03 eta: 13:31:58 time: 1.1862 data_time: 0.0353 memory: 16131 loss: 1.9196 loss_prob: 1.1329 loss_thr: 0.6062 loss_db: 0.1805 2022/10/26 00:11:16 - mmengine - INFO - Epoch(train) [321][20/63] lr: 2.6736e-03 eta: 13:31:52 time: 0.9957 data_time: 0.0283 memory: 16131 loss: 1.8049 loss_prob: 1.0486 loss_thr: 0.5826 loss_db: 0.1737 2022/10/26 00:11:22 - mmengine - INFO - Epoch(train) [321][25/63] lr: 2.6736e-03 eta: 13:31:52 time: 1.0338 data_time: 0.0395 memory: 16131 loss: 1.9721 loss_prob: 1.1753 loss_thr: 0.6079 loss_db: 0.1889 2022/10/26 00:11:26 - mmengine - INFO - Epoch(train) [321][30/63] lr: 2.6736e-03 eta: 13:31:47 time: 0.9854 data_time: 0.0418 memory: 16131 loss: 1.9943 loss_prob: 1.1898 loss_thr: 0.6140 loss_db: 0.1906 2022/10/26 00:11:34 - mmengine - INFO - Epoch(train) [321][35/63] lr: 2.6736e-03 eta: 13:31:47 time: 1.2063 data_time: 0.0170 memory: 16131 loss: 1.8041 loss_prob: 1.0442 loss_thr: 0.5882 loss_db: 0.1717 2022/10/26 00:11:39 - mmengine - INFO - Epoch(train) [321][40/63] lr: 2.6736e-03 eta: 13:31:50 time: 1.3090 data_time: 0.0184 memory: 16131 loss: 1.8023 loss_prob: 1.0596 loss_thr: 0.5689 loss_db: 0.1739 2022/10/26 00:11:43 - mmengine - INFO - Epoch(train) [321][45/63] lr: 2.6736e-03 eta: 13:31:50 time: 0.8608 data_time: 0.0148 memory: 16131 loss: 1.9157 loss_prob: 1.1458 loss_thr: 0.5822 loss_db: 0.1878 2022/10/26 00:11:47 - mmengine - INFO - Epoch(train) [321][50/63] lr: 2.6736e-03 eta: 13:31:39 time: 0.8062 data_time: 0.0240 memory: 16131 loss: 1.9223 loss_prob: 1.1307 loss_thr: 0.6078 loss_db: 0.1838 2022/10/26 00:11:50 - mmengine - INFO - Epoch(train) [321][55/63] lr: 2.6736e-03 eta: 13:31:39 time: 0.7524 data_time: 0.0262 memory: 16131 loss: 1.7426 loss_prob: 0.9922 loss_thr: 0.5886 loss_db: 0.1618 2022/10/26 00:11:53 - mmengine - INFO - Epoch(train) [321][60/63] lr: 2.6736e-03 eta: 13:31:22 time: 0.5696 data_time: 0.0089 memory: 16131 loss: 1.7572 loss_prob: 1.0078 loss_thr: 0.5847 loss_db: 0.1647 2022/10/26 00:11:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:12:04 - mmengine - INFO - Epoch(train) [322][5/63] lr: 2.6709e-03 eta: 13:31:22 time: 1.1643 data_time: 0.2307 memory: 16131 loss: 1.9666 loss_prob: 1.1830 loss_thr: 0.5960 loss_db: 0.1876 2022/10/26 00:12:10 - mmengine - INFO - Epoch(train) [322][10/63] lr: 2.6709e-03 eta: 13:31:22 time: 1.5615 data_time: 0.2302 memory: 16131 loss: 1.9763 loss_prob: 1.1675 loss_thr: 0.6201 loss_db: 0.1887 2022/10/26 00:12:13 - mmengine - INFO - Epoch(train) [322][15/63] lr: 2.6709e-03 eta: 13:31:22 time: 0.9640 data_time: 0.0069 memory: 16131 loss: 1.9265 loss_prob: 1.1229 loss_thr: 0.6210 loss_db: 0.1825 2022/10/26 00:12:16 - mmengine - INFO - Epoch(train) [322][20/63] lr: 2.6709e-03 eta: 13:31:05 time: 0.5894 data_time: 0.0104 memory: 16131 loss: 1.9379 loss_prob: 1.1445 loss_thr: 0.6094 loss_db: 0.1841 2022/10/26 00:12:21 - mmengine - INFO - Epoch(train) [322][25/63] lr: 2.6709e-03 eta: 13:31:05 time: 0.7710 data_time: 0.0206 memory: 16131 loss: 1.9832 loss_prob: 1.1797 loss_thr: 0.6110 loss_db: 0.1925 2022/10/26 00:12:24 - mmengine - INFO - Epoch(train) [322][30/63] lr: 2.6709e-03 eta: 13:30:53 time: 0.7715 data_time: 0.0454 memory: 16131 loss: 1.9686 loss_prob: 1.1675 loss_thr: 0.6114 loss_db: 0.1897 2022/10/26 00:12:31 - mmengine - INFO - Epoch(train) [322][35/63] lr: 2.6709e-03 eta: 13:30:53 time: 0.9644 data_time: 0.0381 memory: 16131 loss: 1.9239 loss_prob: 1.1413 loss_thr: 0.6013 loss_db: 0.1812 2022/10/26 00:12:35 - mmengine - INFO - Epoch(train) [322][40/63] lr: 2.6709e-03 eta: 13:30:49 time: 1.0675 data_time: 0.0093 memory: 16131 loss: 1.9923 loss_prob: 1.1851 loss_thr: 0.6219 loss_db: 0.1853 2022/10/26 00:12:40 - mmengine - INFO - Epoch(train) [322][45/63] lr: 2.6709e-03 eta: 13:30:49 time: 0.9584 data_time: 0.0100 memory: 16131 loss: 2.0685 loss_prob: 1.2277 loss_thr: 0.6428 loss_db: 0.1979 2022/10/26 00:12:46 - mmengine - INFO - Epoch(train) [322][50/63] lr: 2.6709e-03 eta: 13:30:49 time: 1.1821 data_time: 0.0395 memory: 16131 loss: 1.9293 loss_prob: 1.1085 loss_thr: 0.6356 loss_db: 0.1852 2022/10/26 00:12:52 - mmengine - INFO - Epoch(train) [322][55/63] lr: 2.6709e-03 eta: 13:30:49 time: 1.2378 data_time: 0.0394 memory: 16131 loss: 1.7848 loss_prob: 1.0132 loss_thr: 0.6048 loss_db: 0.1668 2022/10/26 00:13:00 - mmengine - INFO - Epoch(train) [322][60/63] lr: 2.6709e-03 eta: 13:30:53 time: 1.3552 data_time: 0.0099 memory: 16131 loss: 1.6476 loss_prob: 0.9434 loss_thr: 0.5520 loss_db: 0.1522 2022/10/26 00:13:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:13:08 - mmengine - INFO - Epoch(train) [323][5/63] lr: 2.6682e-03 eta: 13:30:53 time: 1.0519 data_time: 0.2320 memory: 16131 loss: 1.8499 loss_prob: 1.0881 loss_thr: 0.5828 loss_db: 0.1790 2022/10/26 00:13:11 - mmengine - INFO - Epoch(train) [323][10/63] lr: 2.6682e-03 eta: 13:30:34 time: 0.8551 data_time: 0.2312 memory: 16131 loss: 1.8306 loss_prob: 1.0581 loss_thr: 0.5994 loss_db: 0.1732 2022/10/26 00:13:14 - mmengine - INFO - Epoch(train) [323][15/63] lr: 2.6682e-03 eta: 13:30:34 time: 0.5968 data_time: 0.0056 memory: 16131 loss: 1.7787 loss_prob: 1.0165 loss_thr: 0.5993 loss_db: 0.1629 2022/10/26 00:13:17 - mmengine - INFO - Epoch(train) [323][20/63] lr: 2.6682e-03 eta: 13:30:16 time: 0.5565 data_time: 0.0097 memory: 16131 loss: 1.8592 loss_prob: 1.0900 loss_thr: 0.5945 loss_db: 0.1748 2022/10/26 00:13:20 - mmengine - INFO - Epoch(train) [323][25/63] lr: 2.6682e-03 eta: 13:30:16 time: 0.5818 data_time: 0.0197 memory: 16131 loss: 1.8965 loss_prob: 1.1264 loss_thr: 0.5912 loss_db: 0.1789 2022/10/26 00:13:23 - mmengine - INFO - Epoch(train) [323][30/63] lr: 2.6682e-03 eta: 13:30:01 time: 0.6570 data_time: 0.0387 memory: 16131 loss: 1.9195 loss_prob: 1.1303 loss_thr: 0.6061 loss_db: 0.1830 2022/10/26 00:13:26 - mmengine - INFO - Epoch(train) [323][35/63] lr: 2.6682e-03 eta: 13:30:01 time: 0.6196 data_time: 0.0297 memory: 16131 loss: 1.8541 loss_prob: 1.0845 loss_thr: 0.5889 loss_db: 0.1807 2022/10/26 00:13:31 - mmengine - INFO - Epoch(train) [323][40/63] lr: 2.6682e-03 eta: 13:29:49 time: 0.7620 data_time: 0.0060 memory: 16131 loss: 1.8300 loss_prob: 1.0668 loss_thr: 0.5836 loss_db: 0.1796 2022/10/26 00:13:38 - mmengine - INFO - Epoch(train) [323][45/63] lr: 2.6682e-03 eta: 13:29:49 time: 1.2343 data_time: 0.0078 memory: 16131 loss: 1.8672 loss_prob: 1.0801 loss_thr: 0.6085 loss_db: 0.1786 2022/10/26 00:13:45 - mmengine - INFO - Epoch(train) [323][50/63] lr: 2.6682e-03 eta: 13:29:56 time: 1.4378 data_time: 0.0173 memory: 16131 loss: 1.8210 loss_prob: 1.0586 loss_thr: 0.5888 loss_db: 0.1736 2022/10/26 00:13:49 - mmengine - INFO - Epoch(train) [323][55/63] lr: 2.6682e-03 eta: 13:29:56 time: 1.0365 data_time: 0.0354 memory: 16131 loss: 2.0760 loss_prob: 1.2575 loss_thr: 0.6081 loss_db: 0.2104 2022/10/26 00:13:53 - mmengine - INFO - Epoch(train) [323][60/63] lr: 2.6682e-03 eta: 13:29:45 time: 0.8143 data_time: 0.0263 memory: 16131 loss: 2.0374 loss_prob: 1.2209 loss_thr: 0.6132 loss_db: 0.2032 2022/10/26 00:13:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:14:03 - mmengine - INFO - Epoch(train) [324][5/63] lr: 2.6654e-03 eta: 13:29:45 time: 1.1322 data_time: 0.2524 memory: 16131 loss: 1.7434 loss_prob: 1.0104 loss_thr: 0.5668 loss_db: 0.1662 2022/10/26 00:14:06 - mmengine - INFO - Epoch(train) [324][10/63] lr: 2.6654e-03 eta: 13:29:30 time: 1.0092 data_time: 0.2527 memory: 16131 loss: 2.0303 loss_prob: 1.2386 loss_thr: 0.5963 loss_db: 0.1953 2022/10/26 00:14:12 - mmengine - INFO - Epoch(train) [324][15/63] lr: 2.6654e-03 eta: 13:29:30 time: 0.8255 data_time: 0.0233 memory: 16131 loss: 2.1397 loss_prob: 1.3133 loss_thr: 0.6198 loss_db: 0.2066 2022/10/26 00:14:17 - mmengine - INFO - Epoch(train) [324][20/63] lr: 2.6654e-03 eta: 13:29:25 time: 1.0250 data_time: 0.0252 memory: 16131 loss: 1.9922 loss_prob: 1.1988 loss_thr: 0.6066 loss_db: 0.1868 2022/10/26 00:14:22 - mmengine - INFO - Epoch(train) [324][25/63] lr: 2.6654e-03 eta: 13:29:25 time: 1.0496 data_time: 0.0341 memory: 16131 loss: 1.8999 loss_prob: 1.1347 loss_thr: 0.5873 loss_db: 0.1778 2022/10/26 00:14:29 - mmengine - INFO - Epoch(train) [324][30/63] lr: 2.6654e-03 eta: 13:29:27 time: 1.2685 data_time: 0.0325 memory: 16131 loss: 1.8929 loss_prob: 1.1164 loss_thr: 0.5916 loss_db: 0.1848 2022/10/26 00:14:36 - mmengine - INFO - Epoch(train) [324][35/63] lr: 2.6654e-03 eta: 13:29:27 time: 1.3677 data_time: 0.0094 memory: 16131 loss: 1.9147 loss_prob: 1.1249 loss_thr: 0.6051 loss_db: 0.1848 2022/10/26 00:14:41 - mmengine - INFO - Epoch(train) [324][40/63] lr: 2.6654e-03 eta: 13:29:25 time: 1.1340 data_time: 0.0213 memory: 16131 loss: 1.7597 loss_prob: 1.0104 loss_thr: 0.5864 loss_db: 0.1629 2022/10/26 00:14:46 - mmengine - INFO - Epoch(train) [324][45/63] lr: 2.6654e-03 eta: 13:29:25 time: 1.0084 data_time: 0.0180 memory: 16131 loss: 1.8539 loss_prob: 1.1003 loss_thr: 0.5834 loss_db: 0.1702 2022/10/26 00:14:53 - mmengine - INFO - Epoch(train) [324][50/63] lr: 2.6654e-03 eta: 13:29:27 time: 1.2534 data_time: 0.0299 memory: 16131 loss: 1.9837 loss_prob: 1.2008 loss_thr: 0.5956 loss_db: 0.1872 2022/10/26 00:15:02 - mmengine - INFO - Epoch(train) [324][55/63] lr: 2.6654e-03 eta: 13:29:27 time: 1.5798 data_time: 0.0316 memory: 16131 loss: 1.8655 loss_prob: 1.0997 loss_thr: 0.5885 loss_db: 0.1773 2022/10/26 00:15:07 - mmengine - INFO - Epoch(train) [324][60/63] lr: 2.6654e-03 eta: 13:29:30 time: 1.3472 data_time: 0.0098 memory: 16131 loss: 1.8833 loss_prob: 1.1069 loss_thr: 0.5973 loss_db: 0.1791 2022/10/26 00:15:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:15:20 - mmengine - INFO - Epoch(train) [325][5/63] lr: 2.6627e-03 eta: 13:29:30 time: 1.4683 data_time: 0.2544 memory: 16131 loss: 1.7077 loss_prob: 0.9853 loss_thr: 0.5634 loss_db: 0.1589 2022/10/26 00:15:25 - mmengine - INFO - Epoch(train) [325][10/63] lr: 2.6627e-03 eta: 13:29:30 time: 1.5550 data_time: 0.2503 memory: 16131 loss: 1.6715 loss_prob: 0.9675 loss_thr: 0.5455 loss_db: 0.1585 2022/10/26 00:15:33 - mmengine - INFO - Epoch(train) [325][15/63] lr: 2.6627e-03 eta: 13:29:30 time: 1.3258 data_time: 0.0113 memory: 16131 loss: 1.7764 loss_prob: 1.0360 loss_thr: 0.5692 loss_db: 0.1713 2022/10/26 00:15:39 - mmengine - INFO - Epoch(train) [325][20/63] lr: 2.6627e-03 eta: 13:29:35 time: 1.3947 data_time: 0.0162 memory: 16131 loss: 1.8727 loss_prob: 1.1109 loss_thr: 0.5810 loss_db: 0.1807 2022/10/26 00:15:47 - mmengine - INFO - Epoch(train) [325][25/63] lr: 2.6627e-03 eta: 13:29:35 time: 1.4385 data_time: 0.0222 memory: 16131 loss: 1.9723 loss_prob: 1.1874 loss_thr: 0.5909 loss_db: 0.1940 2022/10/26 00:15:51 - mmengine - INFO - Epoch(train) [325][30/63] lr: 2.6627e-03 eta: 13:29:34 time: 1.1779 data_time: 0.0492 memory: 16131 loss: 1.9149 loss_prob: 1.1505 loss_thr: 0.5728 loss_db: 0.1917 2022/10/26 00:15:58 - mmengine - INFO - Epoch(train) [325][35/63] lr: 2.6627e-03 eta: 13:29:34 time: 1.0297 data_time: 0.0396 memory: 16131 loss: 2.0103 loss_prob: 1.2285 loss_thr: 0.5831 loss_db: 0.1987 2022/10/26 00:16:02 - mmengine - INFO - Epoch(train) [325][40/63] lr: 2.6627e-03 eta: 13:29:31 time: 1.1004 data_time: 0.0099 memory: 16131 loss: 2.1196 loss_prob: 1.2968 loss_thr: 0.6136 loss_db: 0.2092 2022/10/26 00:16:06 - mmengine - INFO - Epoch(train) [325][45/63] lr: 2.6627e-03 eta: 13:29:31 time: 0.8613 data_time: 0.0081 memory: 16131 loss: 2.0747 loss_prob: 1.2287 loss_thr: 0.6427 loss_db: 0.2032 2022/10/26 00:16:12 - mmengine - INFO - Epoch(train) [325][50/63] lr: 2.6627e-03 eta: 13:29:26 time: 1.0128 data_time: 0.0198 memory: 16131 loss: 2.0898 loss_prob: 1.2240 loss_thr: 0.6640 loss_db: 0.2018 2022/10/26 00:16:17 - mmengine - INFO - Epoch(train) [325][55/63] lr: 2.6627e-03 eta: 13:29:26 time: 1.1334 data_time: 0.0346 memory: 16131 loss: 2.0070 loss_prob: 1.1854 loss_thr: 0.6274 loss_db: 0.1942 2022/10/26 00:16:21 - mmengine - INFO - Epoch(train) [325][60/63] lr: 2.6627e-03 eta: 13:29:18 time: 0.9180 data_time: 0.0253 memory: 16131 loss: 1.8521 loss_prob: 1.0864 loss_thr: 0.5919 loss_db: 0.1738 2022/10/26 00:16:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:16:35 - mmengine - INFO - Epoch(train) [326][5/63] lr: 2.6600e-03 eta: 13:29:18 time: 1.4864 data_time: 0.3164 memory: 16131 loss: 1.7480 loss_prob: 1.0084 loss_thr: 0.5776 loss_db: 0.1620 2022/10/26 00:16:43 - mmengine - INFO - Epoch(train) [326][10/63] lr: 2.6600e-03 eta: 13:29:29 time: 1.9673 data_time: 0.3175 memory: 16131 loss: 1.9435 loss_prob: 1.1425 loss_thr: 0.6173 loss_db: 0.1837 2022/10/26 00:16:48 - mmengine - INFO - Epoch(train) [326][15/63] lr: 2.6600e-03 eta: 13:29:29 time: 1.3284 data_time: 0.0080 memory: 16131 loss: 2.0258 loss_prob: 1.2128 loss_thr: 0.6170 loss_db: 0.1961 2022/10/26 00:16:53 - mmengine - INFO - Epoch(train) [326][20/63] lr: 2.6600e-03 eta: 13:29:25 time: 1.0405 data_time: 0.0067 memory: 16131 loss: 1.9327 loss_prob: 1.1367 loss_thr: 0.6122 loss_db: 0.1839 2022/10/26 00:16:56 - mmengine - INFO - Epoch(train) [326][25/63] lr: 2.6600e-03 eta: 13:29:25 time: 0.8494 data_time: 0.0456 memory: 16131 loss: 1.7808 loss_prob: 1.0148 loss_thr: 0.5995 loss_db: 0.1664 2022/10/26 00:17:00 - mmengine - INFO - Epoch(train) [326][30/63] lr: 2.6600e-03 eta: 13:29:10 time: 0.6664 data_time: 0.0463 memory: 16131 loss: 1.8741 loss_prob: 1.0929 loss_thr: 0.6009 loss_db: 0.1803 2022/10/26 00:17:05 - mmengine - INFO - Epoch(train) [326][35/63] lr: 2.6600e-03 eta: 13:29:10 time: 0.8260 data_time: 0.0073 memory: 16131 loss: 1.8201 loss_prob: 1.0633 loss_thr: 0.5757 loss_db: 0.1811 2022/10/26 00:17:09 - mmengine - INFO - Epoch(train) [326][40/63] lr: 2.6600e-03 eta: 13:29:01 time: 0.8709 data_time: 0.0069 memory: 16131 loss: 1.9679 loss_prob: 1.1921 loss_thr: 0.5765 loss_db: 0.1993 2022/10/26 00:17:15 - mmengine - INFO - Epoch(train) [326][45/63] lr: 2.6600e-03 eta: 13:29:01 time: 0.9919 data_time: 0.0133 memory: 16131 loss: 2.1895 loss_prob: 1.3631 loss_thr: 0.6083 loss_db: 0.2181 2022/10/26 00:17:20 - mmengine - INFO - Epoch(train) [326][50/63] lr: 2.6600e-03 eta: 13:28:59 time: 1.1373 data_time: 0.0341 memory: 16131 loss: 2.3401 loss_prob: 1.4594 loss_thr: 0.6469 loss_db: 0.2338 2022/10/26 00:17:24 - mmengine - INFO - Epoch(train) [326][55/63] lr: 2.6600e-03 eta: 13:28:59 time: 0.9263 data_time: 0.0275 memory: 16131 loss: 2.3815 loss_prob: 1.4838 loss_thr: 0.6544 loss_db: 0.2433 2022/10/26 00:17:28 - mmengine - INFO - Epoch(train) [326][60/63] lr: 2.6600e-03 eta: 13:28:49 time: 0.8442 data_time: 0.0099 memory: 16131 loss: 2.3571 loss_prob: 1.4590 loss_thr: 0.6644 loss_db: 0.2337 2022/10/26 00:17:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:17:40 - mmengine - INFO - Epoch(train) [327][5/63] lr: 2.6572e-03 eta: 13:28:49 time: 1.3251 data_time: 0.2178 memory: 16131 loss: 2.2220 loss_prob: 1.3696 loss_thr: 0.6350 loss_db: 0.2174 2022/10/26 00:17:44 - mmengine - INFO - Epoch(train) [327][10/63] lr: 2.6572e-03 eta: 13:28:45 time: 1.4055 data_time: 0.2210 memory: 16131 loss: 2.1511 loss_prob: 1.3163 loss_thr: 0.6192 loss_db: 0.2155 2022/10/26 00:17:48 - mmengine - INFO - Epoch(train) [327][15/63] lr: 2.6572e-03 eta: 13:28:45 time: 0.7809 data_time: 0.0173 memory: 16131 loss: 2.0626 loss_prob: 1.2419 loss_thr: 0.6164 loss_db: 0.2043 2022/10/26 00:17:52 - mmengine - INFO - Epoch(train) [327][20/63] lr: 2.6572e-03 eta: 13:28:33 time: 0.7912 data_time: 0.0106 memory: 16131 loss: 1.9316 loss_prob: 1.1344 loss_thr: 0.6095 loss_db: 0.1877 2022/10/26 00:17:59 - mmengine - INFO - Epoch(train) [327][25/63] lr: 2.6572e-03 eta: 13:28:33 time: 1.1396 data_time: 0.0177 memory: 16131 loss: 1.9340 loss_prob: 1.1411 loss_thr: 0.6088 loss_db: 0.1841 2022/10/26 00:18:05 - mmengine - INFO - Epoch(train) [327][30/63] lr: 2.6572e-03 eta: 13:28:35 time: 1.2861 data_time: 0.0273 memory: 16131 loss: 1.8427 loss_prob: 1.0879 loss_thr: 0.5819 loss_db: 0.1729 2022/10/26 00:18:10 - mmengine - INFO - Epoch(train) [327][35/63] lr: 2.6572e-03 eta: 13:28:35 time: 1.0753 data_time: 0.0286 memory: 16131 loss: 1.8913 loss_prob: 1.1201 loss_thr: 0.5883 loss_db: 0.1829 2022/10/26 00:18:16 - mmengine - INFO - Epoch(train) [327][40/63] lr: 2.6572e-03 eta: 13:28:33 time: 1.1114 data_time: 0.0169 memory: 16131 loss: 1.8956 loss_prob: 1.1059 loss_thr: 0.6052 loss_db: 0.1845 2022/10/26 00:18:21 - mmengine - INFO - Epoch(train) [327][45/63] lr: 2.6572e-03 eta: 13:28:33 time: 1.0946 data_time: 0.0147 memory: 16131 loss: 1.7623 loss_prob: 1.0073 loss_thr: 0.5903 loss_db: 0.1647 2022/10/26 00:18:27 - mmengine - INFO - Epoch(train) [327][50/63] lr: 2.6572e-03 eta: 13:28:30 time: 1.1216 data_time: 0.0238 memory: 16131 loss: 1.8980 loss_prob: 1.1082 loss_thr: 0.6116 loss_db: 0.1782 2022/10/26 00:18:34 - mmengine - INFO - Epoch(train) [327][55/63] lr: 2.6572e-03 eta: 13:28:30 time: 1.3693 data_time: 0.0237 memory: 16131 loss: 1.9839 loss_prob: 1.1632 loss_thr: 0.6250 loss_db: 0.1957 2022/10/26 00:18:40 - mmengine - INFO - Epoch(train) [327][60/63] lr: 2.6572e-03 eta: 13:28:33 time: 1.2981 data_time: 0.0229 memory: 16131 loss: 1.8584 loss_prob: 1.0818 loss_thr: 0.5912 loss_db: 0.1854 2022/10/26 00:18:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:18:50 - mmengine - INFO - Epoch(train) [328][5/63] lr: 2.6545e-03 eta: 13:28:33 time: 1.1347 data_time: 0.1968 memory: 16131 loss: 1.8692 loss_prob: 1.0990 loss_thr: 0.5921 loss_db: 0.1781 2022/10/26 00:18:56 - mmengine - INFO - Epoch(train) [328][10/63] lr: 2.6545e-03 eta: 13:28:27 time: 1.3786 data_time: 0.1949 memory: 16131 loss: 1.7841 loss_prob: 1.0395 loss_thr: 0.5756 loss_db: 0.1690 2022/10/26 00:19:04 - mmengine - INFO - Epoch(train) [328][15/63] lr: 2.6545e-03 eta: 13:28:27 time: 1.3979 data_time: 0.0051 memory: 16131 loss: 1.8273 loss_prob: 1.0656 loss_thr: 0.5870 loss_db: 0.1748 2022/10/26 00:19:08 - mmengine - INFO - Epoch(train) [328][20/63] lr: 2.6545e-03 eta: 13:28:28 time: 1.2281 data_time: 0.0067 memory: 16131 loss: 1.8401 loss_prob: 1.0733 loss_thr: 0.5962 loss_db: 0.1706 2022/10/26 00:19:15 - mmengine - INFO - Epoch(train) [328][25/63] lr: 2.6545e-03 eta: 13:28:28 time: 1.1592 data_time: 0.0149 memory: 16131 loss: 1.8695 loss_prob: 1.0874 loss_thr: 0.6091 loss_db: 0.1730 2022/10/26 00:19:19 - mmengine - INFO - Epoch(train) [328][30/63] lr: 2.6545e-03 eta: 13:28:24 time: 1.0888 data_time: 0.0450 memory: 16131 loss: 1.8765 loss_prob: 1.0917 loss_thr: 0.6084 loss_db: 0.1764 2022/10/26 00:19:22 - mmengine - INFO - Epoch(train) [328][35/63] lr: 2.6545e-03 eta: 13:28:24 time: 0.6885 data_time: 0.0367 memory: 16131 loss: 1.9094 loss_prob: 1.1350 loss_thr: 0.5887 loss_db: 0.1857 2022/10/26 00:19:27 - mmengine - INFO - Epoch(train) [328][40/63] lr: 2.6545e-03 eta: 13:28:15 time: 0.8667 data_time: 0.0066 memory: 16131 loss: 1.8637 loss_prob: 1.1026 loss_thr: 0.5832 loss_db: 0.1780 2022/10/26 00:19:33 - mmengine - INFO - Epoch(train) [328][45/63] lr: 2.6545e-03 eta: 13:28:15 time: 1.0821 data_time: 0.0095 memory: 16131 loss: 1.8113 loss_prob: 1.0490 loss_thr: 0.5922 loss_db: 0.1702 2022/10/26 00:19:40 - mmengine - INFO - Epoch(train) [328][50/63] lr: 2.6545e-03 eta: 13:28:17 time: 1.2906 data_time: 0.0248 memory: 16131 loss: 1.9411 loss_prob: 1.1435 loss_thr: 0.6079 loss_db: 0.1896 2022/10/26 00:19:43 - mmengine - INFO - Epoch(train) [328][55/63] lr: 2.6545e-03 eta: 13:28:17 time: 1.0303 data_time: 0.0400 memory: 16131 loss: 2.2192 loss_prob: 1.3832 loss_thr: 0.6190 loss_db: 0.2170 2022/10/26 00:19:48 - mmengine - INFO - Epoch(train) [328][60/63] lr: 2.6545e-03 eta: 13:28:05 time: 0.7543 data_time: 0.0232 memory: 16131 loss: 2.1609 loss_prob: 1.3478 loss_thr: 0.6023 loss_db: 0.2108 2022/10/26 00:19:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:19:59 - mmengine - INFO - Epoch(train) [329][5/63] lr: 2.6517e-03 eta: 13:28:05 time: 1.2195 data_time: 0.2440 memory: 16131 loss: 2.0514 loss_prob: 1.2177 loss_thr: 0.6416 loss_db: 0.1921 2022/10/26 00:20:07 - mmengine - INFO - Epoch(train) [329][10/63] lr: 2.6517e-03 eta: 13:28:09 time: 1.7448 data_time: 0.2437 memory: 16131 loss: 1.9728 loss_prob: 1.1643 loss_thr: 0.6226 loss_db: 0.1859 2022/10/26 00:20:14 - mmengine - INFO - Epoch(train) [329][15/63] lr: 2.6517e-03 eta: 13:28:09 time: 1.5144 data_time: 0.0081 memory: 16131 loss: 1.8483 loss_prob: 1.0694 loss_thr: 0.6045 loss_db: 0.1743 2022/10/26 00:20:20 - mmengine - INFO - Epoch(train) [329][20/63] lr: 2.6517e-03 eta: 13:28:11 time: 1.2760 data_time: 0.0085 memory: 16131 loss: 1.9520 loss_prob: 1.1454 loss_thr: 0.6210 loss_db: 0.1856 2022/10/26 00:20:28 - mmengine - INFO - Epoch(train) [329][25/63] lr: 2.6517e-03 eta: 13:28:11 time: 1.3690 data_time: 0.0548 memory: 16131 loss: 1.8073 loss_prob: 1.0452 loss_thr: 0.5900 loss_db: 0.1721 2022/10/26 00:20:31 - mmengine - INFO - Epoch(train) [329][30/63] lr: 2.6517e-03 eta: 13:28:09 time: 1.1495 data_time: 0.0764 memory: 16131 loss: 1.6714 loss_prob: 0.9542 loss_thr: 0.5604 loss_db: 0.1568 2022/10/26 00:20:39 - mmengine - INFO - Epoch(train) [329][35/63] lr: 2.6517e-03 eta: 13:28:09 time: 1.1456 data_time: 0.0277 memory: 16131 loss: 1.8548 loss_prob: 1.0956 loss_thr: 0.5885 loss_db: 0.1707 2022/10/26 00:20:45 - mmengine - INFO - Epoch(train) [329][40/63] lr: 2.6517e-03 eta: 13:28:15 time: 1.4170 data_time: 0.0072 memory: 16131 loss: 2.1058 loss_prob: 1.2768 loss_thr: 0.6297 loss_db: 0.1992 2022/10/26 00:20:50 - mmengine - INFO - Epoch(train) [329][45/63] lr: 2.6517e-03 eta: 13:28:15 time: 1.0527 data_time: 0.0089 memory: 16131 loss: 1.9707 loss_prob: 1.1750 loss_thr: 0.6027 loss_db: 0.1931 2022/10/26 00:20:53 - mmengine - INFO - Epoch(train) [329][50/63] lr: 2.6517e-03 eta: 13:28:03 time: 0.7937 data_time: 0.0208 memory: 16131 loss: 1.8123 loss_prob: 1.0650 loss_thr: 0.5678 loss_db: 0.1795 2022/10/26 00:20:59 - mmengine - INFO - Epoch(train) [329][55/63] lr: 2.6517e-03 eta: 13:28:03 time: 0.8974 data_time: 0.0256 memory: 16131 loss: 1.8006 loss_prob: 1.0530 loss_thr: 0.5736 loss_db: 0.1739 2022/10/26 00:21:07 - mmengine - INFO - Epoch(train) [329][60/63] lr: 2.6517e-03 eta: 13:28:08 time: 1.3829 data_time: 0.0116 memory: 16131 loss: 1.8152 loss_prob: 1.0611 loss_thr: 0.5791 loss_db: 0.1750 2022/10/26 00:21:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:21:17 - mmengine - INFO - Epoch(train) [330][5/63] lr: 2.6490e-03 eta: 13:28:08 time: 1.3065 data_time: 0.2187 memory: 16131 loss: 1.8347 loss_prob: 1.0979 loss_thr: 0.5569 loss_db: 0.1799 2022/10/26 00:21:24 - mmengine - INFO - Epoch(train) [330][10/63] lr: 2.6490e-03 eta: 13:28:04 time: 1.4322 data_time: 0.2199 memory: 16131 loss: 1.8880 loss_prob: 1.1056 loss_thr: 0.5993 loss_db: 0.1832 2022/10/26 00:21:30 - mmengine - INFO - Epoch(train) [330][15/63] lr: 2.6490e-03 eta: 13:28:04 time: 1.2795 data_time: 0.0120 memory: 16131 loss: 1.8407 loss_prob: 1.0512 loss_thr: 0.6164 loss_db: 0.1732 2022/10/26 00:21:33 - mmengine - INFO - Epoch(train) [330][20/63] lr: 2.6490e-03 eta: 13:27:54 time: 0.8617 data_time: 0.0124 memory: 16131 loss: 1.7195 loss_prob: 0.9763 loss_thr: 0.5791 loss_db: 0.1642 2022/10/26 00:21:36 - mmengine - INFO - Epoch(train) [330][25/63] lr: 2.6490e-03 eta: 13:27:54 time: 0.6593 data_time: 0.0517 memory: 16131 loss: 1.7317 loss_prob: 0.9896 loss_thr: 0.5769 loss_db: 0.1653 2022/10/26 00:21:43 - mmengine - INFO - Epoch(train) [330][30/63] lr: 2.6490e-03 eta: 13:27:48 time: 0.9875 data_time: 0.0569 memory: 16131 loss: 1.8523 loss_prob: 1.0717 loss_thr: 0.6058 loss_db: 0.1748 2022/10/26 00:21:46 - mmengine - INFO - Epoch(train) [330][35/63] lr: 2.6490e-03 eta: 13:27:48 time: 0.9679 data_time: 0.0205 memory: 16131 loss: 1.8599 loss_prob: 1.0822 loss_thr: 0.6025 loss_db: 0.1752 2022/10/26 00:21:52 - mmengine - INFO - Epoch(train) [330][40/63] lr: 2.6490e-03 eta: 13:27:40 time: 0.9041 data_time: 0.0096 memory: 16131 loss: 1.7528 loss_prob: 1.0118 loss_thr: 0.5782 loss_db: 0.1627 2022/10/26 00:21:55 - mmengine - INFO - Epoch(train) [330][45/63] lr: 2.6490e-03 eta: 13:27:40 time: 0.9044 data_time: 0.0078 memory: 16131 loss: 1.7078 loss_prob: 0.9801 loss_thr: 0.5676 loss_db: 0.1601 2022/10/26 00:22:03 - mmengine - INFO - Epoch(train) [330][50/63] lr: 2.6490e-03 eta: 13:27:38 time: 1.1425 data_time: 0.0226 memory: 16131 loss: 1.7931 loss_prob: 1.0419 loss_thr: 0.5813 loss_db: 0.1699 2022/10/26 00:22:08 - mmengine - INFO - Epoch(train) [330][55/63] lr: 2.6490e-03 eta: 13:27:38 time: 1.2745 data_time: 0.0287 memory: 16131 loss: 1.9856 loss_prob: 1.2160 loss_thr: 0.5830 loss_db: 0.1866 2022/10/26 00:22:13 - mmengine - INFO - Epoch(train) [330][60/63] lr: 2.6490e-03 eta: 13:27:32 time: 0.9908 data_time: 0.0227 memory: 16131 loss: 2.0963 loss_prob: 1.3089 loss_thr: 0.5902 loss_db: 0.1972 2022/10/26 00:22:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:22:27 - mmengine - INFO - Epoch(train) [331][5/63] lr: 2.6463e-03 eta: 13:27:32 time: 1.6290 data_time: 0.2392 memory: 16131 loss: 1.7318 loss_prob: 0.9762 loss_thr: 0.5957 loss_db: 0.1599 2022/10/26 00:22:30 - mmengine - INFO - Epoch(train) [331][10/63] lr: 2.6463e-03 eta: 13:27:25 time: 1.3378 data_time: 0.2388 memory: 16131 loss: 1.7562 loss_prob: 1.0140 loss_thr: 0.5744 loss_db: 0.1678 2022/10/26 00:22:36 - mmengine - INFO - Epoch(train) [331][15/63] lr: 2.6463e-03 eta: 13:27:25 time: 0.8946 data_time: 0.0085 memory: 16131 loss: 1.7492 loss_prob: 1.0041 loss_thr: 0.5772 loss_db: 0.1679 2022/10/26 00:22:40 - mmengine - INFO - Epoch(train) [331][20/63] lr: 2.6463e-03 eta: 13:27:20 time: 1.0308 data_time: 0.0094 memory: 16131 loss: 1.6918 loss_prob: 0.9596 loss_thr: 0.5744 loss_db: 0.1578 2022/10/26 00:22:47 - mmengine - INFO - Epoch(train) [331][25/63] lr: 2.6463e-03 eta: 13:27:20 time: 1.1054 data_time: 0.0317 memory: 16131 loss: 1.6983 loss_prob: 0.9673 loss_thr: 0.5747 loss_db: 0.1562 2022/10/26 00:22:52 - mmengine - INFO - Epoch(train) [331][30/63] lr: 2.6463e-03 eta: 13:27:19 time: 1.1537 data_time: 0.0389 memory: 16131 loss: 1.7764 loss_prob: 1.0187 loss_thr: 0.5924 loss_db: 0.1652 2022/10/26 00:22:57 - mmengine - INFO - Epoch(train) [331][35/63] lr: 2.6463e-03 eta: 13:27:19 time: 0.9775 data_time: 0.0220 memory: 16131 loss: 1.7664 loss_prob: 1.0219 loss_thr: 0.5782 loss_db: 0.1663 2022/10/26 00:23:02 - mmengine - INFO - Epoch(train) [331][40/63] lr: 2.6463e-03 eta: 13:27:13 time: 1.0020 data_time: 0.0156 memory: 16131 loss: 1.8018 loss_prob: 1.0595 loss_thr: 0.5695 loss_db: 0.1728 2022/10/26 00:23:07 - mmengine - INFO - Epoch(train) [331][45/63] lr: 2.6463e-03 eta: 13:27:13 time: 0.9760 data_time: 0.0080 memory: 16131 loss: 1.8614 loss_prob: 1.0595 loss_thr: 0.6256 loss_db: 0.1763 2022/10/26 00:23:14 - mmengine - INFO - Epoch(train) [331][50/63] lr: 2.6463e-03 eta: 13:27:12 time: 1.1909 data_time: 0.0158 memory: 16131 loss: 1.8439 loss_prob: 1.0323 loss_thr: 0.6370 loss_db: 0.1746 2022/10/26 00:23:18 - mmengine - INFO - Epoch(train) [331][55/63] lr: 2.6463e-03 eta: 13:27:12 time: 1.1198 data_time: 0.0235 memory: 16131 loss: 1.7664 loss_prob: 1.0074 loss_thr: 0.5924 loss_db: 0.1666 2022/10/26 00:23:21 - mmengine - INFO - Epoch(train) [331][60/63] lr: 2.6463e-03 eta: 13:26:58 time: 0.6677 data_time: 0.0133 memory: 16131 loss: 1.7734 loss_prob: 1.0290 loss_thr: 0.5785 loss_db: 0.1659 2022/10/26 00:23:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:23:32 - mmengine - INFO - Epoch(train) [332][5/63] lr: 2.6435e-03 eta: 13:26:58 time: 1.2864 data_time: 0.1941 memory: 16131 loss: 1.9194 loss_prob: 1.1583 loss_thr: 0.5681 loss_db: 0.1931 2022/10/26 00:23:38 - mmengine - INFO - Epoch(train) [332][10/63] lr: 2.6435e-03 eta: 13:26:58 time: 1.6092 data_time: 0.1940 memory: 16131 loss: 1.8330 loss_prob: 1.0908 loss_thr: 0.5646 loss_db: 0.1775 2022/10/26 00:23:46 - mmengine - INFO - Epoch(train) [332][15/63] lr: 2.6435e-03 eta: 13:26:58 time: 1.3356 data_time: 0.0061 memory: 16131 loss: 1.8858 loss_prob: 1.1216 loss_thr: 0.5852 loss_db: 0.1790 2022/10/26 00:23:51 - mmengine - INFO - Epoch(train) [332][20/63] lr: 2.6435e-03 eta: 13:27:00 time: 1.2904 data_time: 0.0069 memory: 16131 loss: 2.0012 loss_prob: 1.2017 loss_thr: 0.6029 loss_db: 0.1967 2022/10/26 00:23:59 - mmengine - INFO - Epoch(train) [332][25/63] lr: 2.6435e-03 eta: 13:27:00 time: 1.2913 data_time: 0.0089 memory: 16131 loss: 2.0035 loss_prob: 1.1718 loss_thr: 0.6411 loss_db: 0.1905 2022/10/26 00:24:02 - mmengine - INFO - Epoch(train) [332][30/63] lr: 2.6435e-03 eta: 13:26:57 time: 1.1067 data_time: 0.0462 memory: 16131 loss: 1.8644 loss_prob: 1.0618 loss_thr: 0.6318 loss_db: 0.1709 2022/10/26 00:24:06 - mmengine - INFO - Epoch(train) [332][35/63] lr: 2.6435e-03 eta: 13:26:57 time: 0.7467 data_time: 0.0443 memory: 16131 loss: 1.8048 loss_prob: 1.0288 loss_thr: 0.6054 loss_db: 0.1705 2022/10/26 00:24:11 - mmengine - INFO - Epoch(train) [332][40/63] lr: 2.6435e-03 eta: 13:26:46 time: 0.8185 data_time: 0.0056 memory: 16131 loss: 1.8254 loss_prob: 1.0548 loss_thr: 0.5967 loss_db: 0.1739 2022/10/26 00:24:17 - mmengine - INFO - Epoch(train) [332][45/63] lr: 2.6435e-03 eta: 13:26:46 time: 1.0953 data_time: 0.0096 memory: 16131 loss: 1.8623 loss_prob: 1.0897 loss_thr: 0.5966 loss_db: 0.1760 2022/10/26 00:24:24 - mmengine - INFO - Epoch(train) [332][50/63] lr: 2.6435e-03 eta: 13:26:48 time: 1.3026 data_time: 0.0293 memory: 16131 loss: 2.0627 loss_prob: 1.2480 loss_thr: 0.6091 loss_db: 0.2056 2022/10/26 00:24:27 - mmengine - INFO - Epoch(train) [332][55/63] lr: 2.6435e-03 eta: 13:26:48 time: 0.9911 data_time: 0.0297 memory: 16131 loss: 1.9240 loss_prob: 1.1525 loss_thr: 0.5804 loss_db: 0.1912 2022/10/26 00:24:32 - mmengine - INFO - Epoch(train) [332][60/63] lr: 2.6435e-03 eta: 13:26:37 time: 0.8025 data_time: 0.0177 memory: 16131 loss: 1.7068 loss_prob: 0.9785 loss_thr: 0.5676 loss_db: 0.1608 2022/10/26 00:24:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:24:40 - mmengine - INFO - Epoch(train) [333][5/63] lr: 2.6408e-03 eta: 13:26:37 time: 1.1607 data_time: 0.2388 memory: 16131 loss: 1.7857 loss_prob: 1.0387 loss_thr: 0.5808 loss_db: 0.1661 2022/10/26 00:24:45 - mmengine - INFO - Epoch(train) [333][10/63] lr: 2.6408e-03 eta: 13:26:25 time: 1.1218 data_time: 0.2413 memory: 16131 loss: 1.8469 loss_prob: 1.0855 loss_thr: 0.5860 loss_db: 0.1754 2022/10/26 00:24:49 - mmengine - INFO - Epoch(train) [333][15/63] lr: 2.6408e-03 eta: 13:26:25 time: 0.8851 data_time: 0.0125 memory: 16131 loss: 1.8710 loss_prob: 1.1059 loss_thr: 0.5838 loss_db: 0.1813 2022/10/26 00:24:55 - mmengine - INFO - Epoch(train) [333][20/63] lr: 2.6408e-03 eta: 13:26:18 time: 0.9491 data_time: 0.0152 memory: 16131 loss: 1.9355 loss_prob: 1.1647 loss_thr: 0.5826 loss_db: 0.1882 2022/10/26 00:24:58 - mmengine - INFO - Epoch(train) [333][25/63] lr: 2.6408e-03 eta: 13:26:18 time: 0.8612 data_time: 0.0254 memory: 16131 loss: 1.9283 loss_prob: 1.1575 loss_thr: 0.5874 loss_db: 0.1834 2022/10/26 00:25:04 - mmengine - INFO - Epoch(train) [333][30/63] lr: 2.6408e-03 eta: 13:26:11 time: 0.9538 data_time: 0.0652 memory: 16131 loss: 1.8281 loss_prob: 1.0521 loss_thr: 0.6036 loss_db: 0.1724 2022/10/26 00:25:07 - mmengine - INFO - Epoch(train) [333][35/63] lr: 2.6408e-03 eta: 13:26:11 time: 0.9295 data_time: 0.0506 memory: 16131 loss: 1.8961 loss_prob: 1.0949 loss_thr: 0.6173 loss_db: 0.1839 2022/10/26 00:25:12 - mmengine - INFO - Epoch(train) [333][40/63] lr: 2.6408e-03 eta: 13:26:00 time: 0.8180 data_time: 0.0093 memory: 16131 loss: 1.8410 loss_prob: 1.0697 loss_thr: 0.5963 loss_db: 0.1749 2022/10/26 00:25:18 - mmengine - INFO - Epoch(train) [333][45/63] lr: 2.6408e-03 eta: 13:26:00 time: 1.1183 data_time: 0.0124 memory: 16131 loss: 1.7514 loss_prob: 1.0142 loss_thr: 0.5741 loss_db: 0.1631 2022/10/26 00:25:26 - mmengine - INFO - Epoch(train) [333][50/63] lr: 2.6408e-03 eta: 13:26:05 time: 1.3861 data_time: 0.0211 memory: 16131 loss: 1.8001 loss_prob: 1.0456 loss_thr: 0.5860 loss_db: 0.1686 2022/10/26 00:25:31 - mmengine - INFO - Epoch(train) [333][55/63] lr: 2.6408e-03 eta: 13:26:05 time: 1.2985 data_time: 0.0330 memory: 16131 loss: 1.7627 loss_prob: 1.0081 loss_thr: 0.5873 loss_db: 0.1673 2022/10/26 00:25:36 - mmengine - INFO - Epoch(train) [333][60/63] lr: 2.6408e-03 eta: 13:25:58 time: 0.9745 data_time: 0.0213 memory: 16131 loss: 1.7232 loss_prob: 0.9799 loss_thr: 0.5785 loss_db: 0.1648 2022/10/26 00:25:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:25:49 - mmengine - INFO - Epoch(train) [334][5/63] lr: 2.6380e-03 eta: 13:25:58 time: 1.4704 data_time: 0.2429 memory: 16131 loss: 1.6162 loss_prob: 0.9071 loss_thr: 0.5550 loss_db: 0.1541 2022/10/26 00:25:52 - mmengine - INFO - Epoch(train) [334][10/63] lr: 2.6380e-03 eta: 13:25:51 time: 1.3285 data_time: 0.2394 memory: 16131 loss: 1.7763 loss_prob: 1.0253 loss_thr: 0.5824 loss_db: 0.1685 2022/10/26 00:25:55 - mmengine - INFO - Epoch(train) [334][15/63] lr: 2.6380e-03 eta: 13:25:51 time: 0.6216 data_time: 0.0100 memory: 16131 loss: 1.8499 loss_prob: 1.0651 loss_thr: 0.6121 loss_db: 0.1726 2022/10/26 00:26:01 - mmengine - INFO - Epoch(train) [334][20/63] lr: 2.6380e-03 eta: 13:25:41 time: 0.8398 data_time: 0.0062 memory: 16131 loss: 1.8239 loss_prob: 1.0343 loss_thr: 0.6191 loss_db: 0.1706 2022/10/26 00:26:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:26:04 - mmengine - INFO - Epoch(train) [334][25/63] lr: 2.6380e-03 eta: 13:25:41 time: 0.9170 data_time: 0.0449 memory: 16131 loss: 1.8675 loss_prob: 1.0806 loss_thr: 0.6108 loss_db: 0.1761 2022/10/26 00:26:08 - mmengine - INFO - Epoch(train) [334][30/63] lr: 2.6380e-03 eta: 13:25:29 time: 0.7558 data_time: 0.0534 memory: 16131 loss: 1.8404 loss_prob: 1.0726 loss_thr: 0.5960 loss_db: 0.1718 2022/10/26 00:26:13 - mmengine - INFO - Epoch(train) [334][35/63] lr: 2.6380e-03 eta: 13:25:29 time: 0.8298 data_time: 0.0160 memory: 16131 loss: 1.7437 loss_prob: 1.0036 loss_thr: 0.5755 loss_db: 0.1646 2022/10/26 00:26:18 - mmengine - INFO - Epoch(train) [334][40/63] lr: 2.6380e-03 eta: 13:25:23 time: 1.0036 data_time: 0.0077 memory: 16131 loss: 1.7580 loss_prob: 0.9967 loss_thr: 0.5941 loss_db: 0.1671 2022/10/26 00:26:23 - mmengine - INFO - Epoch(train) [334][45/63] lr: 2.6380e-03 eta: 13:25:23 time: 1.0049 data_time: 0.0069 memory: 16131 loss: 1.8036 loss_prob: 1.0383 loss_thr: 0.5931 loss_db: 0.1722 2022/10/26 00:26:29 - mmengine - INFO - Epoch(train) [334][50/63] lr: 2.6380e-03 eta: 13:25:19 time: 1.0877 data_time: 0.0359 memory: 16131 loss: 1.8038 loss_prob: 1.0524 loss_thr: 0.5798 loss_db: 0.1716 2022/10/26 00:26:33 - mmengine - INFO - Epoch(train) [334][55/63] lr: 2.6380e-03 eta: 13:25:19 time: 1.0507 data_time: 0.0369 memory: 16131 loss: 1.8386 loss_prob: 1.0703 loss_thr: 0.5946 loss_db: 0.1738 2022/10/26 00:26:37 - mmengine - INFO - Epoch(train) [334][60/63] lr: 2.6380e-03 eta: 13:25:10 time: 0.8456 data_time: 0.0111 memory: 16131 loss: 1.8751 loss_prob: 1.0970 loss_thr: 0.5960 loss_db: 0.1821 2022/10/26 00:26:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:26:47 - mmengine - INFO - Epoch(train) [335][5/63] lr: 2.6353e-03 eta: 13:25:10 time: 1.2491 data_time: 0.1891 memory: 16131 loss: 1.7141 loss_prob: 0.9747 loss_thr: 0.5800 loss_db: 0.1594 2022/10/26 00:26:53 - mmengine - INFO - Epoch(train) [335][10/63] lr: 2.6353e-03 eta: 13:25:05 time: 1.4215 data_time: 0.1890 memory: 16131 loss: 1.6937 loss_prob: 0.9711 loss_thr: 0.5646 loss_db: 0.1579 2022/10/26 00:26:58 - mmengine - INFO - Epoch(train) [335][15/63] lr: 2.6353e-03 eta: 13:25:05 time: 1.1183 data_time: 0.0089 memory: 16131 loss: 1.8382 loss_prob: 1.0692 loss_thr: 0.5945 loss_db: 0.1745 2022/10/26 00:27:01 - mmengine - INFO - Epoch(train) [335][20/63] lr: 2.6353e-03 eta: 13:24:54 time: 0.8146 data_time: 0.0116 memory: 16131 loss: 1.7792 loss_prob: 1.0228 loss_thr: 0.5896 loss_db: 0.1668 2022/10/26 00:27:05 - mmengine - INFO - Epoch(train) [335][25/63] lr: 2.6353e-03 eta: 13:24:54 time: 0.6902 data_time: 0.0237 memory: 16131 loss: 1.6808 loss_prob: 0.9492 loss_thr: 0.5759 loss_db: 0.1557 2022/10/26 00:27:09 - mmengine - INFO - Epoch(train) [335][30/63] lr: 2.6353e-03 eta: 13:24:43 time: 0.7935 data_time: 0.1026 memory: 16131 loss: 1.6946 loss_prob: 0.9628 loss_thr: 0.5744 loss_db: 0.1573 2022/10/26 00:27:14 - mmengine - INFO - Epoch(train) [335][35/63] lr: 2.6353e-03 eta: 13:24:43 time: 0.9105 data_time: 0.0920 memory: 16131 loss: 1.7888 loss_prob: 1.0321 loss_thr: 0.5855 loss_db: 0.1712 2022/10/26 00:27:20 - mmengine - INFO - Epoch(train) [335][40/63] lr: 2.6353e-03 eta: 13:24:38 time: 1.0398 data_time: 0.0128 memory: 16131 loss: 1.7530 loss_prob: 0.9917 loss_thr: 0.5961 loss_db: 0.1653 2022/10/26 00:27:25 - mmengine - INFO - Epoch(train) [335][45/63] lr: 2.6353e-03 eta: 13:24:38 time: 1.1060 data_time: 0.0108 memory: 16131 loss: 1.8477 loss_prob: 1.0719 loss_thr: 0.6004 loss_db: 0.1755 2022/10/26 00:27:31 - mmengine - INFO - Epoch(train) [335][50/63] lr: 2.6353e-03 eta: 13:24:36 time: 1.1419 data_time: 0.0143 memory: 16131 loss: 2.0411 loss_prob: 1.2297 loss_thr: 0.6128 loss_db: 0.1986 2022/10/26 00:27:36 - mmengine - INFO - Epoch(train) [335][55/63] lr: 2.6353e-03 eta: 13:24:36 time: 1.0945 data_time: 0.0330 memory: 16131 loss: 1.9020 loss_prob: 1.1332 loss_thr: 0.5893 loss_db: 0.1796 2022/10/26 00:27:40 - mmengine - INFO - Epoch(train) [335][60/63] lr: 2.6353e-03 eta: 13:24:26 time: 0.8581 data_time: 0.0278 memory: 16131 loss: 1.7788 loss_prob: 1.0369 loss_thr: 0.5750 loss_db: 0.1669 2022/10/26 00:27:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:27:47 - mmengine - INFO - Epoch(train) [336][5/63] lr: 2.6326e-03 eta: 13:24:26 time: 0.8834 data_time: 0.2137 memory: 16131 loss: 1.7603 loss_prob: 1.0070 loss_thr: 0.5845 loss_db: 0.1687 2022/10/26 00:27:52 - mmengine - INFO - Epoch(train) [336][10/63] lr: 2.6326e-03 eta: 13:24:14 time: 1.0979 data_time: 0.2130 memory: 16131 loss: 1.8959 loss_prob: 1.1269 loss_thr: 0.5880 loss_db: 0.1810 2022/10/26 00:27:57 - mmengine - INFO - Epoch(train) [336][15/63] lr: 2.6326e-03 eta: 13:24:14 time: 0.9203 data_time: 0.0113 memory: 16131 loss: 1.9958 loss_prob: 1.2030 loss_thr: 0.5996 loss_db: 0.1932 2022/10/26 00:28:00 - mmengine - INFO - Epoch(train) [336][20/63] lr: 2.6326e-03 eta: 13:24:03 time: 0.8323 data_time: 0.0234 memory: 16131 loss: 2.1583 loss_prob: 1.3428 loss_thr: 0.5940 loss_db: 0.2215 2022/10/26 00:28:07 - mmengine - INFO - Epoch(train) [336][25/63] lr: 2.6326e-03 eta: 13:24:03 time: 1.0661 data_time: 0.0519 memory: 16131 loss: 2.3225 loss_prob: 1.4863 loss_thr: 0.5992 loss_db: 0.2370 2022/10/26 00:28:12 - mmengine - INFO - Epoch(train) [336][30/63] lr: 2.6326e-03 eta: 13:24:02 time: 1.1790 data_time: 0.0440 memory: 16131 loss: 2.2913 loss_prob: 1.4113 loss_thr: 0.6572 loss_db: 0.2229 2022/10/26 00:28:15 - mmengine - INFO - Epoch(train) [336][35/63] lr: 2.6326e-03 eta: 13:24:02 time: 0.8262 data_time: 0.0170 memory: 16131 loss: 2.3724 loss_prob: 1.4529 loss_thr: 0.6868 loss_db: 0.2328 2022/10/26 00:28:26 - mmengine - INFO - Epoch(train) [336][40/63] lr: 2.6326e-03 eta: 13:24:05 time: 1.3494 data_time: 0.0128 memory: 16131 loss: 2.2330 loss_prob: 1.3692 loss_thr: 0.6467 loss_db: 0.2171 2022/10/26 00:28:33 - mmengine - INFO - Epoch(train) [336][45/63] lr: 2.6326e-03 eta: 13:24:05 time: 1.7738 data_time: 0.0122 memory: 16131 loss: 2.0708 loss_prob: 1.2577 loss_thr: 0.6059 loss_db: 0.2072 2022/10/26 00:28:39 - mmengine - INFO - Epoch(train) [336][50/63] lr: 2.6326e-03 eta: 13:24:09 time: 1.3745 data_time: 0.0271 memory: 16131 loss: 2.0757 loss_prob: 1.2414 loss_thr: 0.6288 loss_db: 0.2055 2022/10/26 00:28:44 - mmengine - INFO - Epoch(train) [336][55/63] lr: 2.6326e-03 eta: 13:24:09 time: 1.0466 data_time: 0.0284 memory: 16131 loss: 2.2050 loss_prob: 1.3418 loss_thr: 0.6465 loss_db: 0.2168 2022/10/26 00:28:47 - mmengine - INFO - Epoch(train) [336][60/63] lr: 2.6326e-03 eta: 13:23:57 time: 0.7868 data_time: 0.0164 memory: 16131 loss: 2.6354 loss_prob: 1.6974 loss_thr: 0.6584 loss_db: 0.2796 2022/10/26 00:28:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:28:57 - mmengine - INFO - Epoch(train) [337][5/63] lr: 2.6298e-03 eta: 13:23:57 time: 1.0915 data_time: 0.2182 memory: 16131 loss: 2.6815 loss_prob: 1.7394 loss_thr: 0.6666 loss_db: 0.2755 2022/10/26 00:29:02 - mmengine - INFO - Epoch(train) [337][10/63] lr: 2.6298e-03 eta: 13:23:50 time: 1.3164 data_time: 0.2170 memory: 16131 loss: 2.2151 loss_prob: 1.3774 loss_thr: 0.6148 loss_db: 0.2228 2022/10/26 00:29:07 - mmengine - INFO - Epoch(train) [337][15/63] lr: 2.6298e-03 eta: 13:23:50 time: 1.0726 data_time: 0.0055 memory: 16131 loss: 2.3422 loss_prob: 1.4521 loss_thr: 0.6505 loss_db: 0.2395 2022/10/26 00:29:12 - mmengine - INFO - Epoch(train) [337][20/63] lr: 2.6298e-03 eta: 13:23:45 time: 1.0349 data_time: 0.0060 memory: 16131 loss: 2.1434 loss_prob: 1.3027 loss_thr: 0.6293 loss_db: 0.2114 2022/10/26 00:29:16 - mmengine - INFO - Epoch(train) [337][25/63] lr: 2.6298e-03 eta: 13:23:45 time: 0.9092 data_time: 0.0107 memory: 16131 loss: 2.1079 loss_prob: 1.2847 loss_thr: 0.6104 loss_db: 0.2127 2022/10/26 00:29:21 - mmengine - INFO - Epoch(train) [337][30/63] lr: 2.6298e-03 eta: 13:23:37 time: 0.9145 data_time: 0.0544 memory: 16131 loss: 2.1057 loss_prob: 1.2924 loss_thr: 0.6044 loss_db: 0.2089 2022/10/26 00:29:27 - mmengine - INFO - Epoch(train) [337][35/63] lr: 2.6298e-03 eta: 13:23:37 time: 1.0964 data_time: 0.0497 memory: 16131 loss: 1.9461 loss_prob: 1.1662 loss_thr: 0.5994 loss_db: 0.1806 2022/10/26 00:29:33 - mmengine - INFO - Epoch(train) [337][40/63] lr: 2.6298e-03 eta: 13:23:34 time: 1.1266 data_time: 0.0059 memory: 16131 loss: 1.9228 loss_prob: 1.1268 loss_thr: 0.6122 loss_db: 0.1838 2022/10/26 00:29:39 - mmengine - INFO - Epoch(train) [337][45/63] lr: 2.6298e-03 eta: 13:23:34 time: 1.1798 data_time: 0.0112 memory: 16131 loss: 2.0634 loss_prob: 1.2498 loss_thr: 0.6113 loss_db: 0.2023 2022/10/26 00:29:45 - mmengine - INFO - Epoch(train) [337][50/63] lr: 2.6298e-03 eta: 13:23:35 time: 1.2620 data_time: 0.0164 memory: 16131 loss: 2.0325 loss_prob: 1.2228 loss_thr: 0.6166 loss_db: 0.1931 2022/10/26 00:29:49 - mmengine - INFO - Epoch(train) [337][55/63] lr: 2.6298e-03 eta: 13:23:35 time: 1.0150 data_time: 0.0275 memory: 16131 loss: 1.9600 loss_prob: 1.1424 loss_thr: 0.6308 loss_db: 0.1868 2022/10/26 00:29:54 - mmengine - INFO - Epoch(train) [337][60/63] lr: 2.6298e-03 eta: 13:23:26 time: 0.8899 data_time: 0.0232 memory: 16131 loss: 1.9776 loss_prob: 1.1697 loss_thr: 0.6180 loss_db: 0.1899 2022/10/26 00:29:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:30:04 - mmengine - INFO - Epoch(train) [338][5/63] lr: 2.6271e-03 eta: 13:23:26 time: 1.2047 data_time: 0.2578 memory: 16131 loss: 1.8549 loss_prob: 1.0808 loss_thr: 0.5966 loss_db: 0.1774 2022/10/26 00:30:09 - mmengine - INFO - Epoch(train) [338][10/63] lr: 2.6271e-03 eta: 13:23:18 time: 1.2682 data_time: 0.2561 memory: 16131 loss: 1.8231 loss_prob: 1.0726 loss_thr: 0.5761 loss_db: 0.1744 2022/10/26 00:30:18 - mmengine - INFO - Epoch(train) [338][15/63] lr: 2.6271e-03 eta: 13:23:18 time: 1.4211 data_time: 0.0092 memory: 16131 loss: 1.8952 loss_prob: 1.1273 loss_thr: 0.5824 loss_db: 0.1854 2022/10/26 00:30:23 - mmengine - INFO - Epoch(train) [338][20/63] lr: 2.6271e-03 eta: 13:23:22 time: 1.3851 data_time: 0.0116 memory: 16131 loss: 1.9250 loss_prob: 1.1264 loss_thr: 0.6115 loss_db: 0.1871 2022/10/26 00:30:30 - mmengine - INFO - Epoch(train) [338][25/63] lr: 2.6271e-03 eta: 13:23:22 time: 1.1829 data_time: 0.0318 memory: 16131 loss: 1.8464 loss_prob: 1.0660 loss_thr: 0.5994 loss_db: 0.1810 2022/10/26 00:30:35 - mmengine - INFO - Epoch(train) [338][30/63] lr: 2.6271e-03 eta: 13:23:20 time: 1.1754 data_time: 0.0464 memory: 16131 loss: 1.8453 loss_prob: 1.0780 loss_thr: 0.5837 loss_db: 0.1836 2022/10/26 00:30:41 - mmengine - INFO - Epoch(train) [338][35/63] lr: 2.6271e-03 eta: 13:23:20 time: 1.1541 data_time: 0.0222 memory: 16131 loss: 1.8871 loss_prob: 1.1272 loss_thr: 0.5807 loss_db: 0.1793 2022/10/26 00:30:44 - mmengine - INFO - Epoch(train) [338][40/63] lr: 2.6271e-03 eta: 13:23:12 time: 0.9381 data_time: 0.0070 memory: 16131 loss: 2.0914 loss_prob: 1.2749 loss_thr: 0.6195 loss_db: 0.1970 2022/10/26 00:30:47 - mmengine - INFO - Epoch(train) [338][45/63] lr: 2.6271e-03 eta: 13:23:12 time: 0.5980 data_time: 0.0083 memory: 16131 loss: 2.0551 loss_prob: 1.2231 loss_thr: 0.6359 loss_db: 0.1961 2022/10/26 00:30:50 - mmengine - INFO - Epoch(train) [338][50/63] lr: 2.6271e-03 eta: 13:22:55 time: 0.5558 data_time: 0.0266 memory: 16131 loss: 1.9550 loss_prob: 1.1490 loss_thr: 0.6162 loss_db: 0.1898 2022/10/26 00:30:52 - mmengine - INFO - Epoch(train) [338][55/63] lr: 2.6271e-03 eta: 13:22:55 time: 0.5349 data_time: 0.0260 memory: 16131 loss: 1.9908 loss_prob: 1.1837 loss_thr: 0.6147 loss_db: 0.1923 2022/10/26 00:30:56 - mmengine - INFO - Epoch(train) [338][60/63] lr: 2.6271e-03 eta: 13:22:38 time: 0.5775 data_time: 0.0067 memory: 16131 loss: 2.1140 loss_prob: 1.2672 loss_thr: 0.6418 loss_db: 0.2050 2022/10/26 00:30:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:31:06 - mmengine - INFO - Epoch(train) [339][5/63] lr: 2.6243e-03 eta: 13:22:38 time: 1.1476 data_time: 0.2319 memory: 16131 loss: 1.8699 loss_prob: 1.0923 loss_thr: 0.5973 loss_db: 0.1803 2022/10/26 00:31:10 - mmengine - INFO - Epoch(train) [339][10/63] lr: 2.6243e-03 eta: 13:22:30 time: 1.2808 data_time: 0.2352 memory: 16131 loss: 1.7546 loss_prob: 1.0212 loss_thr: 0.5674 loss_db: 0.1661 2022/10/26 00:31:15 - mmengine - INFO - Epoch(train) [339][15/63] lr: 2.6243e-03 eta: 13:22:30 time: 0.8643 data_time: 0.0153 memory: 16131 loss: 1.8069 loss_prob: 1.0481 loss_thr: 0.5868 loss_db: 0.1720 2022/10/26 00:31:18 - mmengine - INFO - Epoch(train) [339][20/63] lr: 2.6243e-03 eta: 13:22:19 time: 0.7870 data_time: 0.0106 memory: 16131 loss: 1.7500 loss_prob: 1.0105 loss_thr: 0.5734 loss_db: 0.1661 2022/10/26 00:31:21 - mmengine - INFO - Epoch(train) [339][25/63] lr: 2.6243e-03 eta: 13:22:19 time: 0.6489 data_time: 0.0345 memory: 16131 loss: 1.8314 loss_prob: 1.0516 loss_thr: 0.6043 loss_db: 0.1755 2022/10/26 00:31:26 - mmengine - INFO - Epoch(train) [339][30/63] lr: 2.6243e-03 eta: 13:22:08 time: 0.8283 data_time: 0.0429 memory: 16131 loss: 1.8184 loss_prob: 1.0488 loss_thr: 0.5950 loss_db: 0.1746 2022/10/26 00:31:31 - mmengine - INFO - Epoch(train) [339][35/63] lr: 2.6243e-03 eta: 13:22:08 time: 0.9551 data_time: 0.0174 memory: 16131 loss: 1.8615 loss_prob: 1.1083 loss_thr: 0.5744 loss_db: 0.1789 2022/10/26 00:31:36 - mmengine - INFO - Epoch(train) [339][40/63] lr: 2.6243e-03 eta: 13:22:02 time: 0.9707 data_time: 0.0108 memory: 16131 loss: 1.9314 loss_prob: 1.1468 loss_thr: 0.5988 loss_db: 0.1858 2022/10/26 00:31:41 - mmengine - INFO - Epoch(train) [339][45/63] lr: 2.6243e-03 eta: 13:22:02 time: 1.0073 data_time: 0.0079 memory: 16131 loss: 1.8466 loss_prob: 1.0740 loss_thr: 0.5951 loss_db: 0.1775 2022/10/26 00:31:46 - mmengine - INFO - Epoch(train) [339][50/63] lr: 2.6243e-03 eta: 13:21:57 time: 1.0618 data_time: 0.0297 memory: 16131 loss: 1.8456 loss_prob: 1.0754 loss_thr: 0.5932 loss_db: 0.1770 2022/10/26 00:31:51 - mmengine - INFO - Epoch(train) [339][55/63] lr: 2.6243e-03 eta: 13:21:57 time: 1.0335 data_time: 0.0353 memory: 16131 loss: 1.8151 loss_prob: 1.0640 loss_thr: 0.5775 loss_db: 0.1736 2022/10/26 00:31:55 - mmengine - INFO - Epoch(train) [339][60/63] lr: 2.6243e-03 eta: 13:21:47 time: 0.8397 data_time: 0.0129 memory: 16131 loss: 1.8550 loss_prob: 1.0823 loss_thr: 0.5970 loss_db: 0.1757 2022/10/26 00:31:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:32:06 - mmengine - INFO - Epoch(train) [340][5/63] lr: 2.6216e-03 eta: 13:21:47 time: 1.2437 data_time: 0.2129 memory: 16131 loss: 2.0399 loss_prob: 1.2119 loss_thr: 0.6312 loss_db: 0.1968 2022/10/26 00:32:13 - mmengine - INFO - Epoch(train) [340][10/63] lr: 2.6216e-03 eta: 13:21:42 time: 1.4227 data_time: 0.2175 memory: 16131 loss: 1.8074 loss_prob: 1.0516 loss_thr: 0.5803 loss_db: 0.1755 2022/10/26 00:32:22 - mmengine - INFO - Epoch(train) [340][15/63] lr: 2.6216e-03 eta: 13:21:42 time: 1.6829 data_time: 0.0180 memory: 16131 loss: 1.8232 loss_prob: 1.0664 loss_thr: 0.5847 loss_db: 0.1721 2022/10/26 00:32:29 - mmengine - INFO - Epoch(train) [340][20/63] lr: 2.6216e-03 eta: 13:21:52 time: 1.6017 data_time: 0.0111 memory: 16131 loss: 1.8175 loss_prob: 1.0610 loss_thr: 0.5866 loss_db: 0.1699 2022/10/26 00:32:36 - mmengine - INFO - Epoch(train) [340][25/63] lr: 2.6216e-03 eta: 13:21:52 time: 1.3127 data_time: 0.0282 memory: 16131 loss: 1.9282 loss_prob: 1.1541 loss_thr: 0.5875 loss_db: 0.1866 2022/10/26 00:32:40 - mmengine - INFO - Epoch(train) [340][30/63] lr: 2.6216e-03 eta: 13:21:48 time: 1.0710 data_time: 0.0594 memory: 16131 loss: 2.4993 loss_prob: 1.6086 loss_thr: 0.6499 loss_db: 0.2408 2022/10/26 00:32:47 - mmengine - INFO - Epoch(train) [340][35/63] lr: 2.6216e-03 eta: 13:21:48 time: 1.1091 data_time: 0.0401 memory: 16131 loss: 2.5331 loss_prob: 1.6005 loss_thr: 0.6946 loss_db: 0.2379 2022/10/26 00:32:53 - mmengine - INFO - Epoch(train) [340][40/63] lr: 2.6216e-03 eta: 13:21:50 time: 1.3336 data_time: 0.0156 memory: 16131 loss: 2.0918 loss_prob: 1.2374 loss_thr: 0.6571 loss_db: 0.1973 2022/10/26 00:32:58 - mmengine - INFO - Epoch(train) [340][45/63] lr: 2.6216e-03 eta: 13:21:50 time: 1.1761 data_time: 0.0125 memory: 16131 loss: 2.0031 loss_prob: 1.1889 loss_thr: 0.6204 loss_db: 0.1939 2022/10/26 00:33:03 - mmengine - INFO - Epoch(train) [340][50/63] lr: 2.6216e-03 eta: 13:21:42 time: 0.9151 data_time: 0.0181 memory: 16131 loss: 2.0258 loss_prob: 1.2060 loss_thr: 0.6219 loss_db: 0.1979 2022/10/26 00:33:10 - mmengine - INFO - Epoch(train) [340][55/63] lr: 2.6216e-03 eta: 13:21:42 time: 1.1415 data_time: 0.0329 memory: 16131 loss: 1.9299 loss_prob: 1.1322 loss_thr: 0.6140 loss_db: 0.1837 2022/10/26 00:33:18 - mmengine - INFO - Epoch(train) [340][60/63] lr: 2.6216e-03 eta: 13:21:49 time: 1.5397 data_time: 0.0218 memory: 16131 loss: 1.8341 loss_prob: 1.0736 loss_thr: 0.5834 loss_db: 0.1771 2022/10/26 00:33:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:33:20 - mmengine - INFO - Saving checkpoint at 340 epochs 2022/10/26 00:33:28 - mmengine - INFO - Epoch(val) [340][5/32] eta: 13:21:49 time: 0.5921 data_time: 0.0885 memory: 16131 2022/10/26 00:33:32 - mmengine - INFO - Epoch(val) [340][10/32] eta: 0:00:14 time: 0.6730 data_time: 0.1101 memory: 15724 2022/10/26 00:33:35 - mmengine - INFO - Epoch(val) [340][15/32] eta: 0:00:14 time: 0.6068 data_time: 0.0711 memory: 15724 2022/10/26 00:33:38 - mmengine - INFO - Epoch(val) [340][20/32] eta: 0:00:07 time: 0.5993 data_time: 0.0694 memory: 15724 2022/10/26 00:33:41 - mmengine - INFO - Epoch(val) [340][25/32] eta: 0:00:07 time: 0.6112 data_time: 0.0557 memory: 15724 2022/10/26 00:33:43 - mmengine - INFO - Epoch(val) [340][30/32] eta: 0:00:01 time: 0.5788 data_time: 0.0400 memory: 15724 2022/10/26 00:33:44 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8151, precision: 0.6141, hmean: 0.7005 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8151, precision: 0.7307, hmean: 0.7706 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8093, precision: 0.7877, hmean: 0.7984 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7920, precision: 0.8346, hmean: 0.8127 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7275, precision: 0.8873, hmean: 0.7995 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3736, precision: 0.9652, hmean: 0.5387 2022/10/26 00:33:44 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/26 00:33:44 - mmengine - INFO - Epoch(val) [340][32/32] icdar/precision: 0.8346 icdar/recall: 0.7920 icdar/hmean: 0.8127 2022/10/26 00:33:54 - mmengine - INFO - Epoch(train) [341][5/63] lr: 2.6188e-03 eta: 0:00:01 time: 1.5045 data_time: 0.2441 memory: 16131 loss: 2.2335 loss_prob: 1.3512 loss_thr: 0.6544 loss_db: 0.2279 2022/10/26 00:34:01 - mmengine - INFO - Epoch(train) [341][10/63] lr: 2.6188e-03 eta: 13:21:51 time: 1.6857 data_time: 0.2487 memory: 16131 loss: 2.0369 loss_prob: 1.1990 loss_thr: 0.6427 loss_db: 0.1952 2022/10/26 00:34:09 - mmengine - INFO - Epoch(train) [341][15/63] lr: 2.6188e-03 eta: 13:21:51 time: 1.5297 data_time: 0.0111 memory: 16131 loss: 1.8783 loss_prob: 1.1008 loss_thr: 0.5999 loss_db: 0.1776 2022/10/26 00:34:13 - mmengine - INFO - Epoch(train) [341][20/63] lr: 2.6188e-03 eta: 13:21:51 time: 1.2416 data_time: 0.0114 memory: 16131 loss: 1.9005 loss_prob: 1.0968 loss_thr: 0.6258 loss_db: 0.1778 2022/10/26 00:34:17 - mmengine - INFO - Epoch(train) [341][25/63] lr: 2.6188e-03 eta: 13:21:51 time: 0.7954 data_time: 0.0346 memory: 16131 loss: 1.9140 loss_prob: 1.1159 loss_thr: 0.6203 loss_db: 0.1779 2022/10/26 00:34:21 - mmengine - INFO - Epoch(train) [341][30/63] lr: 2.6188e-03 eta: 13:21:38 time: 0.7148 data_time: 0.0405 memory: 16131 loss: 1.8215 loss_prob: 1.0692 loss_thr: 0.5823 loss_db: 0.1700 2022/10/26 00:34:27 - mmengine - INFO - Epoch(train) [341][35/63] lr: 2.6188e-03 eta: 13:21:38 time: 0.9844 data_time: 0.0176 memory: 16131 loss: 1.8492 loss_prob: 1.0874 loss_thr: 0.5883 loss_db: 0.1735 2022/10/26 00:34:35 - mmengine - INFO - Epoch(train) [341][40/63] lr: 2.6188e-03 eta: 13:21:44 time: 1.4953 data_time: 0.0069 memory: 16131 loss: 1.8931 loss_prob: 1.1174 loss_thr: 0.5999 loss_db: 0.1759 2022/10/26 00:34:46 - mmengine - INFO - Epoch(train) [341][45/63] lr: 2.6188e-03 eta: 13:21:44 time: 1.8934 data_time: 0.0093 memory: 16131 loss: 1.8962 loss_prob: 1.1175 loss_thr: 0.6009 loss_db: 0.1778 2022/10/26 00:34:55 - mmengine - INFO - Epoch(train) [341][50/63] lr: 2.6188e-03 eta: 13:22:03 time: 1.9933 data_time: 0.0252 memory: 16131 loss: 1.9910 loss_prob: 1.1903 loss_thr: 0.6077 loss_db: 0.1929 2022/10/26 00:35:00 - mmengine - INFO - Epoch(train) [341][55/63] lr: 2.6188e-03 eta: 13:22:03 time: 1.3999 data_time: 0.0296 memory: 16131 loss: 1.8507 loss_prob: 1.0959 loss_thr: 0.5717 loss_db: 0.1831 2022/10/26 00:35:04 - mmengine - INFO - Epoch(train) [341][60/63] lr: 2.6188e-03 eta: 13:21:54 time: 0.8799 data_time: 0.0183 memory: 16131 loss: 1.7393 loss_prob: 1.0103 loss_thr: 0.5594 loss_db: 0.1696 2022/10/26 00:35:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:35:18 - mmengine - INFO - Epoch(train) [342][5/63] lr: 2.6161e-03 eta: 13:21:54 time: 1.4660 data_time: 0.2781 memory: 16131 loss: 1.7580 loss_prob: 1.0284 loss_thr: 0.5674 loss_db: 0.1622 2022/10/26 00:35:25 - mmengine - INFO - Epoch(train) [342][10/63] lr: 2.6161e-03 eta: 13:21:57 time: 1.7322 data_time: 0.2781 memory: 16131 loss: 1.7045 loss_prob: 0.9836 loss_thr: 0.5636 loss_db: 0.1573 2022/10/26 00:35:31 - mmengine - INFO - Epoch(train) [342][15/63] lr: 2.6161e-03 eta: 13:21:57 time: 1.3010 data_time: 0.0084 memory: 16131 loss: 1.6279 loss_prob: 0.9312 loss_thr: 0.5449 loss_db: 0.1519 2022/10/26 00:35:36 - mmengine - INFO - Epoch(train) [342][20/63] lr: 2.6161e-03 eta: 13:21:55 time: 1.1475 data_time: 0.0168 memory: 16131 loss: 1.7570 loss_prob: 1.0192 loss_thr: 0.5684 loss_db: 0.1693 2022/10/26 00:35:42 - mmengine - INFO - Epoch(train) [342][25/63] lr: 2.6161e-03 eta: 13:21:55 time: 1.0859 data_time: 0.0425 memory: 16131 loss: 2.3038 loss_prob: 1.4272 loss_thr: 0.6420 loss_db: 0.2346 2022/10/26 00:35:47 - mmengine - INFO - Epoch(train) [342][30/63] lr: 2.6161e-03 eta: 13:21:51 time: 1.0717 data_time: 0.0384 memory: 16131 loss: 2.4223 loss_prob: 1.5135 loss_thr: 0.6632 loss_db: 0.2455 2022/10/26 00:35:52 - mmengine - INFO - Epoch(train) [342][35/63] lr: 2.6161e-03 eta: 13:21:51 time: 0.9933 data_time: 0.0108 memory: 16131 loss: 2.1959 loss_prob: 1.3430 loss_thr: 0.6333 loss_db: 0.2196 2022/10/26 00:35:59 - mmengine - INFO - Epoch(train) [342][40/63] lr: 2.6161e-03 eta: 13:21:50 time: 1.2138 data_time: 0.0189 memory: 16131 loss: 2.1248 loss_prob: 1.2884 loss_thr: 0.6239 loss_db: 0.2125 2022/10/26 00:36:03 - mmengine - INFO - Epoch(train) [342][45/63] lr: 2.6161e-03 eta: 13:21:50 time: 1.1292 data_time: 0.0291 memory: 16131 loss: 1.9415 loss_prob: 1.1465 loss_thr: 0.6070 loss_db: 0.1880 2022/10/26 00:36:11 - mmengine - INFO - Epoch(train) [342][50/63] lr: 2.6161e-03 eta: 13:21:49 time: 1.2176 data_time: 0.0334 memory: 16131 loss: 2.0742 loss_prob: 1.2664 loss_thr: 0.6045 loss_db: 0.2033 2022/10/26 00:36:16 - mmengine - INFO - Epoch(train) [342][55/63] lr: 2.6161e-03 eta: 13:21:49 time: 1.3439 data_time: 0.0254 memory: 16131 loss: 2.1604 loss_prob: 1.3320 loss_thr: 0.6127 loss_db: 0.2157 2022/10/26 00:36:20 - mmengine - INFO - Epoch(train) [342][60/63] lr: 2.6161e-03 eta: 13:21:40 time: 0.8622 data_time: 0.0088 memory: 16131 loss: 1.9768 loss_prob: 1.1879 loss_thr: 0.5958 loss_db: 0.1931 2022/10/26 00:36:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:36:26 - mmengine - INFO - Epoch(train) [343][5/63] lr: 2.6133e-03 eta: 13:21:40 time: 0.7509 data_time: 0.2053 memory: 16131 loss: 1.8095 loss_prob: 1.0541 loss_thr: 0.5801 loss_db: 0.1753 2022/10/26 00:36:29 - mmengine - INFO - Epoch(train) [343][10/63] lr: 2.6133e-03 eta: 13:21:18 time: 0.7454 data_time: 0.2047 memory: 16131 loss: 1.9530 loss_prob: 1.1473 loss_thr: 0.6170 loss_db: 0.1887 2022/10/26 00:36:32 - mmengine - INFO - Epoch(train) [343][15/63] lr: 2.6133e-03 eta: 13:21:18 time: 0.5970 data_time: 0.0100 memory: 16131 loss: 1.8911 loss_prob: 1.1091 loss_thr: 0.6004 loss_db: 0.1816 2022/10/26 00:36:35 - mmengine - INFO - Epoch(train) [343][20/63] lr: 2.6133e-03 eta: 13:21:02 time: 0.6242 data_time: 0.0089 memory: 16131 loss: 1.9192 loss_prob: 1.1414 loss_thr: 0.5931 loss_db: 0.1847 2022/10/26 00:36:38 - mmengine - INFO - Epoch(train) [343][25/63] lr: 2.6133e-03 eta: 13:21:02 time: 0.5962 data_time: 0.0138 memory: 16131 loss: 1.8834 loss_prob: 1.1151 loss_thr: 0.5902 loss_db: 0.1781 2022/10/26 00:36:42 - mmengine - INFO - Epoch(train) [343][30/63] lr: 2.6133e-03 eta: 13:20:49 time: 0.7038 data_time: 0.0358 memory: 16131 loss: 1.7551 loss_prob: 1.0127 loss_thr: 0.5799 loss_db: 0.1625 2022/10/26 00:36:51 - mmengine - INFO - Epoch(train) [343][35/63] lr: 2.6133e-03 eta: 13:20:49 time: 1.3185 data_time: 0.0408 memory: 16131 loss: 1.9024 loss_prob: 1.1196 loss_thr: 0.6029 loss_db: 0.1799 2022/10/26 00:37:03 - mmengine - INFO - Epoch(train) [343][40/63] lr: 2.6133e-03 eta: 13:21:09 time: 2.0689 data_time: 0.0216 memory: 16131 loss: 2.0831 loss_prob: 1.2561 loss_thr: 0.6248 loss_db: 0.2022 2022/10/26 00:37:17 - mmengine - INFO - Epoch(train) [343][45/63] lr: 2.6133e-03 eta: 13:21:09 time: 2.5849 data_time: 0.0097 memory: 16131 loss: 1.9783 loss_prob: 1.1823 loss_thr: 0.6039 loss_db: 0.1921 2022/10/26 00:37:29 - mmengine - INFO - Epoch(train) [343][50/63] lr: 2.6133e-03 eta: 13:21:44 time: 2.6266 data_time: 0.0189 memory: 16131 loss: 1.7857 loss_prob: 1.0363 loss_thr: 0.5811 loss_db: 0.1684 2022/10/26 00:37:41 - mmengine - INFO - Epoch(train) [343][55/63] lr: 2.6133e-03 eta: 13:21:44 time: 2.3833 data_time: 0.0393 memory: 16131 loss: 1.7752 loss_prob: 1.0281 loss_thr: 0.5792 loss_db: 0.1679 2022/10/26 00:37:48 - mmengine - INFO - Epoch(train) [343][60/63] lr: 2.6133e-03 eta: 13:21:59 time: 1.8752 data_time: 0.0316 memory: 16131 loss: 1.7506 loss_prob: 1.0201 loss_thr: 0.5624 loss_db: 0.1681 2022/10/26 00:37:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:38:01 - mmengine - INFO - Epoch(train) [344][5/63] lr: 2.6106e-03 eta: 13:21:59 time: 1.3501 data_time: 0.1939 memory: 16131 loss: 1.9207 loss_prob: 1.1357 loss_thr: 0.6065 loss_db: 0.1785 2022/10/26 00:38:04 - mmengine - INFO - Epoch(train) [344][10/63] lr: 2.6106e-03 eta: 13:21:49 time: 1.1859 data_time: 0.1926 memory: 16131 loss: 2.0074 loss_prob: 1.2052 loss_thr: 0.6111 loss_db: 0.1911 2022/10/26 00:38:06 - mmengine - INFO - Epoch(train) [344][15/63] lr: 2.6106e-03 eta: 13:21:49 time: 0.5906 data_time: 0.0093 memory: 16131 loss: 1.9705 loss_prob: 1.1798 loss_thr: 0.6031 loss_db: 0.1876 2022/10/26 00:38:10 - mmengine - INFO - Epoch(train) [344][20/63] lr: 2.6106e-03 eta: 13:21:34 time: 0.6479 data_time: 0.0139 memory: 16131 loss: 1.8865 loss_prob: 1.1003 loss_thr: 0.6064 loss_db: 0.1799 2022/10/26 00:38:17 - mmengine - INFO - Epoch(train) [344][25/63] lr: 2.6106e-03 eta: 13:21:34 time: 1.0526 data_time: 0.0218 memory: 16131 loss: 1.9766 loss_prob: 1.1718 loss_thr: 0.6153 loss_db: 0.1895 2022/10/26 00:38:20 - mmengine - INFO - Epoch(train) [344][30/63] lr: 2.6106e-03 eta: 13:21:28 time: 1.0416 data_time: 0.0334 memory: 16131 loss: 1.8949 loss_prob: 1.1215 loss_thr: 0.5918 loss_db: 0.1816 2022/10/26 00:38:25 - mmengine - INFO - Epoch(train) [344][35/63] lr: 2.6106e-03 eta: 13:21:28 time: 0.7690 data_time: 0.0233 memory: 16131 loss: 1.8815 loss_prob: 1.1094 loss_thr: 0.5945 loss_db: 0.1777 2022/10/26 00:38:28 - mmengine - INFO - Epoch(train) [344][40/63] lr: 2.6106e-03 eta: 13:21:17 time: 0.8011 data_time: 0.0086 memory: 16131 loss: 1.6951 loss_prob: 0.9778 loss_thr: 0.5605 loss_db: 0.1568 2022/10/26 00:38:33 - mmengine - INFO - Epoch(train) [344][45/63] lr: 2.6106e-03 eta: 13:21:17 time: 0.7920 data_time: 0.0064 memory: 16131 loss: 1.6162 loss_prob: 0.9135 loss_thr: 0.5505 loss_db: 0.1522 2022/10/26 00:38:37 - mmengine - INFO - Epoch(train) [344][50/63] lr: 2.6106e-03 eta: 13:21:07 time: 0.8452 data_time: 0.0176 memory: 16131 loss: 1.6728 loss_prob: 0.9418 loss_thr: 0.5766 loss_db: 0.1543 2022/10/26 00:38:42 - mmengine - INFO - Epoch(train) [344][55/63] lr: 2.6106e-03 eta: 13:21:07 time: 0.9167 data_time: 0.0259 memory: 16131 loss: 1.7658 loss_prob: 1.0215 loss_thr: 0.5827 loss_db: 0.1616 2022/10/26 00:38:46 - mmengine - INFO - Epoch(train) [344][60/63] lr: 2.6106e-03 eta: 13:20:58 time: 0.8812 data_time: 0.0149 memory: 16131 loss: 1.8620 loss_prob: 1.0953 loss_thr: 0.5871 loss_db: 0.1795 2022/10/26 00:38:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:38:57 - mmengine - INFO - Epoch(train) [345][5/63] lr: 2.6079e-03 eta: 13:20:58 time: 1.2673 data_time: 0.2038 memory: 16131 loss: 1.8980 loss_prob: 1.1241 loss_thr: 0.5879 loss_db: 0.1860 2022/10/26 00:39:10 - mmengine - INFO - Epoch(train) [345][10/63] lr: 2.6079e-03 eta: 13:21:12 time: 2.1954 data_time: 0.2048 memory: 16131 loss: 1.7776 loss_prob: 1.0396 loss_thr: 0.5678 loss_db: 0.1701 2022/10/26 00:39:23 - mmengine - INFO - Epoch(train) [345][15/63] lr: 2.6079e-03 eta: 13:21:12 time: 2.5874 data_time: 0.0151 memory: 16131 loss: 1.8083 loss_prob: 1.0481 loss_thr: 0.5888 loss_db: 0.1714 2022/10/26 00:39:33 - mmengine - INFO - Epoch(train) [345][20/63] lr: 2.6079e-03 eta: 13:21:37 time: 2.2545 data_time: 0.0144 memory: 16131 loss: 1.8663 loss_prob: 1.0759 loss_thr: 0.6135 loss_db: 0.1768 2022/10/26 00:39:48 - mmengine - INFO - Epoch(train) [345][25/63] lr: 2.6079e-03 eta: 13:21:37 time: 2.4618 data_time: 0.0550 memory: 16131 loss: 1.7819 loss_prob: 1.0204 loss_thr: 0.5915 loss_db: 0.1700 2022/10/26 00:39:59 - mmengine - INFO - Epoch(train) [345][30/63] lr: 2.6079e-03 eta: 13:22:11 time: 2.5935 data_time: 0.0656 memory: 16131 loss: 1.7192 loss_prob: 0.9763 loss_thr: 0.5769 loss_db: 0.1660 2022/10/26 00:40:07 - mmengine - INFO - Epoch(train) [345][35/63] lr: 2.6079e-03 eta: 13:22:11 time: 1.9473 data_time: 0.0245 memory: 16131 loss: 1.7021 loss_prob: 0.9600 loss_thr: 0.5832 loss_db: 0.1589 2022/10/26 00:40:12 - mmengine - INFO - Epoch(train) [345][40/63] lr: 2.6079e-03 eta: 13:22:13 time: 1.3607 data_time: 0.0167 memory: 16131 loss: 1.6955 loss_prob: 0.9562 loss_thr: 0.5830 loss_db: 0.1564 2022/10/26 00:40:17 - mmengine - INFO - Epoch(train) [345][45/63] lr: 2.6079e-03 eta: 13:22:13 time: 0.9206 data_time: 0.0099 memory: 16131 loss: 1.8473 loss_prob: 1.0794 loss_thr: 0.5917 loss_db: 0.1762 2022/10/26 00:40:20 - mmengine - INFO - Epoch(train) [345][50/63] lr: 2.6079e-03 eta: 13:22:02 time: 0.8106 data_time: 0.0183 memory: 16131 loss: 1.8084 loss_prob: 1.0563 loss_thr: 0.5787 loss_db: 0.1734 2022/10/26 00:40:25 - mmengine - INFO - Epoch(train) [345][55/63] lr: 2.6079e-03 eta: 13:22:02 time: 0.8849 data_time: 0.0196 memory: 16131 loss: 1.7066 loss_prob: 0.9696 loss_thr: 0.5748 loss_db: 0.1621 2022/10/26 00:40:29 - mmengine - INFO - Epoch(train) [345][60/63] lr: 2.6079e-03 eta: 13:21:52 time: 0.8513 data_time: 0.0147 memory: 16131 loss: 1.8087 loss_prob: 1.0440 loss_thr: 0.5931 loss_db: 0.1716 2022/10/26 00:40:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:40:39 - mmengine - INFO - Epoch(train) [346][5/63] lr: 2.6051e-03 eta: 13:21:52 time: 1.1433 data_time: 0.2118 memory: 16131 loss: 1.8228 loss_prob: 1.0560 loss_thr: 0.5920 loss_db: 0.1749 2022/10/26 00:40:43 - mmengine - INFO - Epoch(train) [346][10/63] lr: 2.6051e-03 eta: 13:21:39 time: 1.0898 data_time: 0.2036 memory: 16131 loss: 1.8192 loss_prob: 1.0372 loss_thr: 0.6122 loss_db: 0.1697 2022/10/26 00:40:45 - mmengine - INFO - Epoch(train) [346][15/63] lr: 2.6051e-03 eta: 13:21:39 time: 0.6496 data_time: 0.0067 memory: 16131 loss: 2.0250 loss_prob: 1.1938 loss_thr: 0.6382 loss_db: 0.1931 2022/10/26 00:40:50 - mmengine - INFO - Epoch(train) [346][20/63] lr: 2.6051e-03 eta: 13:21:27 time: 0.7600 data_time: 0.0066 memory: 16131 loss: 1.9197 loss_prob: 1.1415 loss_thr: 0.5923 loss_db: 0.1860 2022/10/26 00:40:56 - mmengine - INFO - Epoch(train) [346][25/63] lr: 2.6051e-03 eta: 13:21:27 time: 1.0402 data_time: 0.0332 memory: 16131 loss: 1.9213 loss_prob: 1.1357 loss_thr: 0.6019 loss_db: 0.1837 2022/10/26 00:40:59 - mmengine - INFO - Epoch(train) [346][30/63] lr: 2.6051e-03 eta: 13:21:17 time: 0.8536 data_time: 0.0344 memory: 16131 loss: 1.8583 loss_prob: 1.0756 loss_thr: 0.6105 loss_db: 0.1723 2022/10/26 00:41:02 - mmengine - INFO - Epoch(train) [346][35/63] lr: 2.6051e-03 eta: 13:21:17 time: 0.6409 data_time: 0.0123 memory: 16131 loss: 1.9764 loss_prob: 1.1890 loss_thr: 0.6036 loss_db: 0.1838 2022/10/26 00:41:06 - mmengine - INFO - Epoch(train) [346][40/63] lr: 2.6051e-03 eta: 13:21:03 time: 0.6854 data_time: 0.0137 memory: 16131 loss: 2.0192 loss_prob: 1.2222 loss_thr: 0.6062 loss_db: 0.1908 2022/10/26 00:41:08 - mmengine - INFO - Epoch(train) [346][45/63] lr: 2.6051e-03 eta: 13:21:03 time: 0.6013 data_time: 0.0076 memory: 16131 loss: 1.7307 loss_prob: 0.9910 loss_thr: 0.5783 loss_db: 0.1615 2022/10/26 00:41:15 - mmengine - INFO - Epoch(train) [346][50/63] lr: 2.6051e-03 eta: 13:20:54 time: 0.9117 data_time: 0.0216 memory: 16131 loss: 1.7448 loss_prob: 1.0015 loss_thr: 0.5800 loss_db: 0.1632 2022/10/26 00:41:20 - mmengine - INFO - Epoch(train) [346][55/63] lr: 2.6051e-03 eta: 13:20:54 time: 1.1929 data_time: 0.0220 memory: 16131 loss: 1.8079 loss_prob: 1.0493 loss_thr: 0.5864 loss_db: 0.1722 2022/10/26 00:41:26 - mmengine - INFO - Epoch(train) [346][60/63] lr: 2.6051e-03 eta: 13:20:52 time: 1.1809 data_time: 0.0080 memory: 16131 loss: 1.7740 loss_prob: 1.0353 loss_thr: 0.5715 loss_db: 0.1673 2022/10/26 00:41:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:41:37 - mmengine - INFO - Epoch(train) [347][5/63] lr: 2.6024e-03 eta: 13:20:52 time: 1.3032 data_time: 0.2514 memory: 16131 loss: 1.7659 loss_prob: 1.0309 loss_thr: 0.5664 loss_db: 0.1686 2022/10/26 00:41:41 - mmengine - INFO - Epoch(train) [347][10/63] lr: 2.6024e-03 eta: 13:20:40 time: 1.1407 data_time: 0.2484 memory: 16131 loss: 1.8119 loss_prob: 1.0469 loss_thr: 0.5964 loss_db: 0.1686 2022/10/26 00:41:46 - mmengine - INFO - Epoch(train) [347][15/63] lr: 2.6024e-03 eta: 13:20:40 time: 0.9422 data_time: 0.0059 memory: 16131 loss: 1.7798 loss_prob: 1.0150 loss_thr: 0.5988 loss_db: 0.1660 2022/10/26 00:41:50 - mmengine - INFO - Epoch(train) [347][20/63] lr: 2.6024e-03 eta: 13:20:32 time: 0.9047 data_time: 0.0070 memory: 16131 loss: 1.7132 loss_prob: 0.9856 loss_thr: 0.5652 loss_db: 0.1624 2022/10/26 00:41:56 - mmengine - INFO - Epoch(train) [347][25/63] lr: 2.6024e-03 eta: 13:20:32 time: 0.9922 data_time: 0.0378 memory: 16131 loss: 1.8075 loss_prob: 1.0507 loss_thr: 0.5836 loss_db: 0.1732 2022/10/26 00:41:59 - mmengine - INFO - Epoch(train) [347][30/63] lr: 2.6024e-03 eta: 13:20:22 time: 0.8757 data_time: 0.0361 memory: 16131 loss: 1.7595 loss_prob: 1.0122 loss_thr: 0.5837 loss_db: 0.1637 2022/10/26 00:42:02 - mmengine - INFO - Epoch(train) [347][35/63] lr: 2.6024e-03 eta: 13:20:22 time: 0.5560 data_time: 0.0075 memory: 16131 loss: 1.6589 loss_prob: 0.9555 loss_thr: 0.5493 loss_db: 0.1541 2022/10/26 00:42:04 - mmengine - INFO - Epoch(train) [347][40/63] lr: 2.6024e-03 eta: 13:20:05 time: 0.5505 data_time: 0.0079 memory: 16131 loss: 1.7550 loss_prob: 1.0075 loss_thr: 0.5810 loss_db: 0.1665 2022/10/26 00:42:07 - mmengine - INFO - Epoch(train) [347][45/63] lr: 2.6024e-03 eta: 13:20:05 time: 0.5372 data_time: 0.0072 memory: 16131 loss: 1.7490 loss_prob: 0.9930 loss_thr: 0.5925 loss_db: 0.1635 2022/10/26 00:42:11 - mmengine - INFO - Epoch(train) [347][50/63] lr: 2.6024e-03 eta: 13:19:51 time: 0.7057 data_time: 0.0244 memory: 16131 loss: 1.8023 loss_prob: 1.0385 loss_thr: 0.5938 loss_db: 0.1700 2022/10/26 00:42:15 - mmengine - INFO - Epoch(train) [347][55/63] lr: 2.6024e-03 eta: 13:19:51 time: 0.7463 data_time: 0.0227 memory: 16131 loss: 1.8586 loss_prob: 1.0789 loss_thr: 0.6039 loss_db: 0.1759 2022/10/26 00:42:20 - mmengine - INFO - Epoch(train) [347][60/63] lr: 2.6024e-03 eta: 13:19:42 time: 0.8565 data_time: 0.0062 memory: 16131 loss: 1.7885 loss_prob: 1.0345 loss_thr: 0.5826 loss_db: 0.1714 2022/10/26 00:42:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:42:30 - mmengine - INFO - Epoch(train) [348][5/63] lr: 2.5996e-03 eta: 13:19:42 time: 1.2545 data_time: 0.2386 memory: 16131 loss: 1.9743 loss_prob: 1.1952 loss_thr: 0.5944 loss_db: 0.1847 2022/10/26 00:42:36 - mmengine - INFO - Epoch(train) [348][10/63] lr: 2.5996e-03 eta: 13:19:34 time: 1.3199 data_time: 0.2393 memory: 16131 loss: 1.9135 loss_prob: 1.1246 loss_thr: 0.6106 loss_db: 0.1784 2022/10/26 00:42:38 - mmengine - INFO - Epoch(train) [348][15/63] lr: 2.5996e-03 eta: 13:19:34 time: 0.8038 data_time: 0.0088 memory: 16131 loss: 1.8183 loss_prob: 1.0555 loss_thr: 0.5922 loss_db: 0.1707 2022/10/26 00:42:41 - mmengine - INFO - Epoch(train) [348][20/63] lr: 2.5996e-03 eta: 13:19:16 time: 0.5308 data_time: 0.0057 memory: 16131 loss: 1.8300 loss_prob: 1.0714 loss_thr: 0.5811 loss_db: 0.1775 2022/10/26 00:42:45 - mmengine - INFO - Epoch(train) [348][25/63] lr: 2.5996e-03 eta: 13:19:16 time: 0.6779 data_time: 0.0307 memory: 16131 loss: 1.8277 loss_prob: 1.0655 loss_thr: 0.5852 loss_db: 0.1770 2022/10/26 00:42:48 - mmengine - INFO - Epoch(train) [348][30/63] lr: 2.5996e-03 eta: 13:19:03 time: 0.7259 data_time: 0.0454 memory: 16131 loss: 1.7586 loss_prob: 1.0229 loss_thr: 0.5710 loss_db: 0.1648 2022/10/26 00:42:52 - mmengine - INFO - Epoch(train) [348][35/63] lr: 2.5996e-03 eta: 13:19:03 time: 0.7379 data_time: 0.0242 memory: 16131 loss: 1.6197 loss_prob: 0.9223 loss_thr: 0.5455 loss_db: 0.1519 2022/10/26 00:42:55 - mmengine - INFO - Epoch(train) [348][40/63] lr: 2.5996e-03 eta: 13:18:49 time: 0.6977 data_time: 0.0141 memory: 16131 loss: 1.5748 loss_prob: 0.8911 loss_thr: 0.5355 loss_db: 0.1482 2022/10/26 00:42:58 - mmengine - INFO - Epoch(train) [348][45/63] lr: 2.5996e-03 eta: 13:18:49 time: 0.5394 data_time: 0.0100 memory: 16131 loss: 1.6395 loss_prob: 0.9309 loss_thr: 0.5552 loss_db: 0.1534 2022/10/26 00:43:01 - mmengine - INFO - Epoch(train) [348][50/63] lr: 2.5996e-03 eta: 13:18:34 time: 0.6225 data_time: 0.0157 memory: 16131 loss: 1.5961 loss_prob: 0.8902 loss_thr: 0.5614 loss_db: 0.1445 2022/10/26 00:43:06 - mmengine - INFO - Epoch(train) [348][55/63] lr: 2.5996e-03 eta: 13:18:34 time: 0.8152 data_time: 0.0206 memory: 16131 loss: 1.5892 loss_prob: 0.8947 loss_thr: 0.5465 loss_db: 0.1480 2022/10/26 00:43:09 - mmengine - INFO - Epoch(train) [348][60/63] lr: 2.5996e-03 eta: 13:18:22 time: 0.7838 data_time: 0.0122 memory: 16131 loss: 1.6365 loss_prob: 0.9321 loss_thr: 0.5495 loss_db: 0.1550 2022/10/26 00:43:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:43:17 - mmengine - INFO - Epoch(train) [349][5/63] lr: 2.5969e-03 eta: 13:18:22 time: 0.9104 data_time: 0.2261 memory: 16131 loss: 1.7363 loss_prob: 1.0223 loss_thr: 0.5505 loss_db: 0.1635 2022/10/26 00:43:19 - mmengine - INFO - Epoch(train) [349][10/63] lr: 2.5969e-03 eta: 13:18:02 time: 0.8011 data_time: 0.2293 memory: 16131 loss: 1.8112 loss_prob: 1.0741 loss_thr: 0.5674 loss_db: 0.1697 2022/10/26 00:43:22 - mmengine - INFO - Epoch(train) [349][15/63] lr: 2.5969e-03 eta: 13:18:02 time: 0.5335 data_time: 0.0093 memory: 16131 loss: 1.6975 loss_prob: 0.9706 loss_thr: 0.5692 loss_db: 0.1577 2022/10/26 00:43:26 - mmengine - INFO - Epoch(train) [349][20/63] lr: 2.5969e-03 eta: 13:17:48 time: 0.7083 data_time: 0.0056 memory: 16131 loss: 1.6861 loss_prob: 0.9506 loss_thr: 0.5800 loss_db: 0.1555 2022/10/26 00:43:31 - mmengine - INFO - Epoch(train) [349][25/63] lr: 2.5969e-03 eta: 13:17:48 time: 0.8562 data_time: 0.0437 memory: 16131 loss: 1.5890 loss_prob: 0.8953 loss_thr: 0.5462 loss_db: 0.1476 2022/10/26 00:43:33 - mmengine - INFO - Epoch(train) [349][30/63] lr: 2.5969e-03 eta: 13:17:34 time: 0.6754 data_time: 0.0502 memory: 16131 loss: 1.6339 loss_prob: 0.9365 loss_thr: 0.5461 loss_db: 0.1513 2022/10/26 00:43:37 - mmengine - INFO - Epoch(train) [349][35/63] lr: 2.5969e-03 eta: 13:17:34 time: 0.6588 data_time: 0.0198 memory: 16131 loss: 1.7097 loss_prob: 0.9851 loss_thr: 0.5644 loss_db: 0.1602 2022/10/26 00:43:41 - mmengine - INFO - Epoch(train) [349][40/63] lr: 2.5969e-03 eta: 13:17:22 time: 0.7443 data_time: 0.0145 memory: 16131 loss: 1.6683 loss_prob: 0.9571 loss_thr: 0.5537 loss_db: 0.1575 2022/10/26 00:43:45 - mmengine - INFO - Epoch(train) [349][45/63] lr: 2.5969e-03 eta: 13:17:22 time: 0.7970 data_time: 0.0060 memory: 16131 loss: 1.7062 loss_prob: 0.9704 loss_thr: 0.5761 loss_db: 0.1597 2022/10/26 00:43:48 - mmengine - INFO - Epoch(train) [349][50/63] lr: 2.5969e-03 eta: 13:17:08 time: 0.7072 data_time: 0.0111 memory: 16131 loss: 1.8455 loss_prob: 1.0879 loss_thr: 0.5795 loss_db: 0.1781 2022/10/26 00:43:51 - mmengine - INFO - Epoch(train) [349][55/63] lr: 2.5969e-03 eta: 13:17:08 time: 0.6157 data_time: 0.0157 memory: 16131 loss: 1.8464 loss_prob: 1.0928 loss_thr: 0.5789 loss_db: 0.1748 2022/10/26 00:43:56 - mmengine - INFO - Epoch(train) [349][60/63] lr: 2.5969e-03 eta: 13:16:58 time: 0.8480 data_time: 0.0097 memory: 16131 loss: 1.8037 loss_prob: 1.0431 loss_thr: 0.5909 loss_db: 0.1698 2022/10/26 00:43:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:44:05 - mmengine - INFO - Epoch(train) [350][5/63] lr: 2.5941e-03 eta: 13:16:58 time: 1.1488 data_time: 0.1741 memory: 16131 loss: 1.6791 loss_prob: 0.9559 loss_thr: 0.5713 loss_db: 0.1520 2022/10/26 00:44:08 - mmengine - INFO - Epoch(train) [350][10/63] lr: 2.5941e-03 eta: 13:16:43 time: 1.0130 data_time: 0.1766 memory: 16131 loss: 1.7512 loss_prob: 1.0221 loss_thr: 0.5637 loss_db: 0.1654 2022/10/26 00:44:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:44:14 - mmengine - INFO - Epoch(train) [350][15/63] lr: 2.5941e-03 eta: 13:16:43 time: 0.8283 data_time: 0.0080 memory: 16131 loss: 1.7200 loss_prob: 1.0068 loss_thr: 0.5464 loss_db: 0.1668 2022/10/26 00:44:16 - mmengine - INFO - Epoch(train) [350][20/63] lr: 2.5941e-03 eta: 13:16:33 time: 0.8273 data_time: 0.0139 memory: 16131 loss: 1.8415 loss_prob: 1.0800 loss_thr: 0.5851 loss_db: 0.1765 2022/10/26 00:44:19 - mmengine - INFO - Epoch(train) [350][25/63] lr: 2.5941e-03 eta: 13:16:33 time: 0.5592 data_time: 0.0239 memory: 16131 loss: 1.8884 loss_prob: 1.0926 loss_thr: 0.6188 loss_db: 0.1770 2022/10/26 00:44:22 - mmengine - INFO - Epoch(train) [350][30/63] lr: 2.5941e-03 eta: 13:16:16 time: 0.5893 data_time: 0.0321 memory: 16131 loss: 1.8927 loss_prob: 1.0976 loss_thr: 0.6179 loss_db: 0.1772 2022/10/26 00:44:26 - mmengine - INFO - Epoch(train) [350][35/63] lr: 2.5941e-03 eta: 13:16:16 time: 0.7092 data_time: 0.0240 memory: 16131 loss: 1.7963 loss_prob: 1.0378 loss_thr: 0.5891 loss_db: 0.1694 2022/10/26 00:44:31 - mmengine - INFO - Epoch(train) [350][40/63] lr: 2.5941e-03 eta: 13:16:08 time: 0.9078 data_time: 0.0078 memory: 16131 loss: 1.6807 loss_prob: 0.9565 loss_thr: 0.5659 loss_db: 0.1583 2022/10/26 00:44:34 - mmengine - INFO - Epoch(train) [350][45/63] lr: 2.5941e-03 eta: 13:16:08 time: 0.7865 data_time: 0.0087 memory: 16131 loss: 1.7242 loss_prob: 0.9856 loss_thr: 0.5778 loss_db: 0.1608 2022/10/26 00:44:40 - mmengine - INFO - Epoch(train) [350][50/63] lr: 2.5941e-03 eta: 13:15:57 time: 0.8244 data_time: 0.0228 memory: 16131 loss: 1.6987 loss_prob: 0.9739 loss_thr: 0.5617 loss_db: 0.1632 2022/10/26 00:44:43 - mmengine - INFO - Epoch(train) [350][55/63] lr: 2.5941e-03 eta: 13:15:57 time: 0.9051 data_time: 0.0204 memory: 16131 loss: 1.6737 loss_prob: 0.9527 loss_thr: 0.5616 loss_db: 0.1594 2022/10/26 00:44:47 - mmengine - INFO - Epoch(train) [350][60/63] lr: 2.5941e-03 eta: 13:15:44 time: 0.7160 data_time: 0.0095 memory: 16131 loss: 1.7889 loss_prob: 1.0214 loss_thr: 0.6015 loss_db: 0.1660 2022/10/26 00:44:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:44:54 - mmengine - INFO - Epoch(train) [351][5/63] lr: 2.5914e-03 eta: 13:15:44 time: 0.8277 data_time: 0.2076 memory: 16131 loss: 1.8866 loss_prob: 1.0982 loss_thr: 0.6042 loss_db: 0.1842 2022/10/26 00:44:57 - mmengine - INFO - Epoch(train) [351][10/63] lr: 2.5914e-03 eta: 13:15:24 time: 0.8305 data_time: 0.2075 memory: 16131 loss: 1.8181 loss_prob: 1.0690 loss_thr: 0.5719 loss_db: 0.1773 2022/10/26 00:44:59 - mmengine - INFO - Epoch(train) [351][15/63] lr: 2.5914e-03 eta: 13:15:24 time: 0.5526 data_time: 0.0144 memory: 16131 loss: 1.7944 loss_prob: 1.0606 loss_thr: 0.5645 loss_db: 0.1692 2022/10/26 00:45:03 - mmengine - INFO - Epoch(train) [351][20/63] lr: 2.5914e-03 eta: 13:15:10 time: 0.6563 data_time: 0.0115 memory: 16131 loss: 1.8315 loss_prob: 1.0791 loss_thr: 0.5735 loss_db: 0.1789 2022/10/26 00:45:09 - mmengine - INFO - Epoch(train) [351][25/63] lr: 2.5914e-03 eta: 13:15:10 time: 1.0073 data_time: 0.0409 memory: 16131 loss: 1.8880 loss_prob: 1.1069 loss_thr: 0.5953 loss_db: 0.1857 2022/10/26 00:45:12 - mmengine - INFO - Epoch(train) [351][30/63] lr: 2.5914e-03 eta: 13:15:01 time: 0.8738 data_time: 0.0406 memory: 16131 loss: 1.7827 loss_prob: 1.0319 loss_thr: 0.5791 loss_db: 0.1717 2022/10/26 00:45:16 - mmengine - INFO - Epoch(train) [351][35/63] lr: 2.5914e-03 eta: 13:15:01 time: 0.6732 data_time: 0.0075 memory: 16131 loss: 1.8346 loss_prob: 1.0793 loss_thr: 0.5813 loss_db: 0.1740 2022/10/26 00:45:21 - mmengine - INFO - Epoch(train) [351][40/63] lr: 2.5914e-03 eta: 13:14:52 time: 0.8903 data_time: 0.0065 memory: 16131 loss: 1.8827 loss_prob: 1.0974 loss_thr: 0.6083 loss_db: 0.1770 2022/10/26 00:45:24 - mmengine - INFO - Epoch(train) [351][45/63] lr: 2.5914e-03 eta: 13:14:52 time: 0.7558 data_time: 0.0056 memory: 16131 loss: 1.6458 loss_prob: 0.9218 loss_thr: 0.5705 loss_db: 0.1536 2022/10/26 00:45:27 - mmengine - INFO - Epoch(train) [351][50/63] lr: 2.5914e-03 eta: 13:14:36 time: 0.6128 data_time: 0.0674 memory: 16131 loss: 1.6219 loss_prob: 0.9161 loss_thr: 0.5535 loss_db: 0.1522 2022/10/26 00:45:33 - mmengine - INFO - Epoch(train) [351][55/63] lr: 2.5914e-03 eta: 13:14:36 time: 0.9048 data_time: 0.0673 memory: 16131 loss: 1.6399 loss_prob: 0.9346 loss_thr: 0.5525 loss_db: 0.1528 2022/10/26 00:45:37 - mmengine - INFO - Epoch(train) [351][60/63] lr: 2.5914e-03 eta: 13:14:30 time: 1.0317 data_time: 0.0069 memory: 16131 loss: 1.5521 loss_prob: 0.8794 loss_thr: 0.5280 loss_db: 0.1447 2022/10/26 00:45:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:45:44 - mmengine - INFO - Epoch(train) [352][5/63] lr: 2.5886e-03 eta: 13:14:30 time: 0.8225 data_time: 0.2596 memory: 16131 loss: 1.7210 loss_prob: 0.9825 loss_thr: 0.5739 loss_db: 0.1646 2022/10/26 00:45:47 - mmengine - INFO - Epoch(train) [352][10/63] lr: 2.5886e-03 eta: 13:14:11 time: 0.8433 data_time: 0.2591 memory: 16131 loss: 1.7034 loss_prob: 0.9727 loss_thr: 0.5698 loss_db: 0.1609 2022/10/26 00:45:51 - mmengine - INFO - Epoch(train) [352][15/63] lr: 2.5886e-03 eta: 13:14:11 time: 0.6923 data_time: 0.0056 memory: 16131 loss: 1.6759 loss_prob: 0.9592 loss_thr: 0.5589 loss_db: 0.1578 2022/10/26 00:45:54 - mmengine - INFO - Epoch(train) [352][20/63] lr: 2.5886e-03 eta: 13:13:57 time: 0.6892 data_time: 0.0069 memory: 16131 loss: 1.7497 loss_prob: 1.0202 loss_thr: 0.5576 loss_db: 0.1718 2022/10/26 00:45:57 - mmengine - INFO - Epoch(train) [352][25/63] lr: 2.5886e-03 eta: 13:13:57 time: 0.5944 data_time: 0.0364 memory: 16131 loss: 1.9591 loss_prob: 1.1736 loss_thr: 0.5922 loss_db: 0.1934 2022/10/26 00:46:01 - mmengine - INFO - Epoch(train) [352][30/63] lr: 2.5886e-03 eta: 13:13:44 time: 0.6894 data_time: 0.0357 memory: 16131 loss: 2.0391 loss_prob: 1.2195 loss_thr: 0.6187 loss_db: 0.2008 2022/10/26 00:46:04 - mmengine - INFO - Epoch(train) [352][35/63] lr: 2.5886e-03 eta: 13:13:44 time: 0.6492 data_time: 0.0086 memory: 16131 loss: 2.5800 loss_prob: 1.6512 loss_thr: 0.6610 loss_db: 0.2678 2022/10/26 00:46:07 - mmengine - INFO - Epoch(train) [352][40/63] lr: 2.5886e-03 eta: 13:13:27 time: 0.5698 data_time: 0.0075 memory: 16131 loss: 2.7230 loss_prob: 1.7797 loss_thr: 0.6617 loss_db: 0.2817 2022/10/26 00:46:11 - mmengine - INFO - Epoch(train) [352][45/63] lr: 2.5886e-03 eta: 13:13:27 time: 0.7105 data_time: 0.0084 memory: 16131 loss: 2.1820 loss_prob: 1.3375 loss_thr: 0.6284 loss_db: 0.2161 2022/10/26 00:46:14 - mmengine - INFO - Epoch(train) [352][50/63] lr: 2.5886e-03 eta: 13:13:15 time: 0.7750 data_time: 0.0301 memory: 16131 loss: 2.2458 loss_prob: 1.3696 loss_thr: 0.6529 loss_db: 0.2233 2022/10/26 00:46:19 - mmengine - INFO - Epoch(train) [352][55/63] lr: 2.5886e-03 eta: 13:13:15 time: 0.8473 data_time: 0.0268 memory: 16131 loss: 2.1716 loss_prob: 1.3257 loss_thr: 0.6263 loss_db: 0.2196 2022/10/26 00:46:22 - mmengine - INFO - Epoch(train) [352][60/63] lr: 2.5886e-03 eta: 13:13:02 time: 0.7241 data_time: 0.0046 memory: 16131 loss: 1.9772 loss_prob: 1.1935 loss_thr: 0.5848 loss_db: 0.1990 2022/10/26 00:46:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:46:33 - mmengine - INFO - Epoch(train) [353][5/63] lr: 2.5859e-03 eta: 13:13:02 time: 1.2540 data_time: 0.1924 memory: 16131 loss: 2.0881 loss_prob: 1.2751 loss_thr: 0.6064 loss_db: 0.2066 2022/10/26 00:46:39 - mmengine - INFO - Epoch(train) [353][10/63] lr: 2.5859e-03 eta: 13:13:00 time: 1.5401 data_time: 0.1931 memory: 16131 loss: 2.0068 loss_prob: 1.1937 loss_thr: 0.6162 loss_db: 0.1968 2022/10/26 00:46:42 - mmengine - INFO - Epoch(train) [353][15/63] lr: 2.5859e-03 eta: 13:13:00 time: 0.9317 data_time: 0.0072 memory: 16131 loss: 1.9587 loss_prob: 1.1510 loss_thr: 0.6159 loss_db: 0.1918 2022/10/26 00:46:45 - mmengine - INFO - Epoch(train) [353][20/63] lr: 2.5859e-03 eta: 13:12:44 time: 0.5942 data_time: 0.0062 memory: 16131 loss: 1.9236 loss_prob: 1.1330 loss_thr: 0.6102 loss_db: 0.1803 2022/10/26 00:46:48 - mmengine - INFO - Epoch(train) [353][25/63] lr: 2.5859e-03 eta: 13:12:44 time: 0.5858 data_time: 0.0117 memory: 16131 loss: 1.9964 loss_prob: 1.1980 loss_thr: 0.6099 loss_db: 0.1885 2022/10/26 00:46:53 - mmengine - INFO - Epoch(train) [353][30/63] lr: 2.5859e-03 eta: 13:12:33 time: 0.7986 data_time: 0.0338 memory: 16131 loss: 2.1400 loss_prob: 1.2843 loss_thr: 0.6426 loss_db: 0.2131 2022/10/26 00:46:57 - mmengine - INFO - Epoch(train) [353][35/63] lr: 2.5859e-03 eta: 13:12:33 time: 0.8816 data_time: 0.0281 memory: 16131 loss: 2.0585 loss_prob: 1.2129 loss_thr: 0.6421 loss_db: 0.2035 2022/10/26 00:47:00 - mmengine - INFO - Epoch(train) [353][40/63] lr: 2.5859e-03 eta: 13:12:19 time: 0.6888 data_time: 0.0055 memory: 16131 loss: 2.0141 loss_prob: 1.2052 loss_thr: 0.6089 loss_db: 0.2000 2022/10/26 00:47:02 - mmengine - INFO - Epoch(train) [353][45/63] lr: 2.5859e-03 eta: 13:12:19 time: 0.5415 data_time: 0.0061 memory: 16131 loss: 2.0496 loss_prob: 1.2327 loss_thr: 0.6126 loss_db: 0.2043 2022/10/26 00:47:07 - mmengine - INFO - Epoch(train) [353][50/63] lr: 2.5859e-03 eta: 13:12:05 time: 0.6749 data_time: 0.0288 memory: 16131 loss: 1.9697 loss_prob: 1.1623 loss_thr: 0.6199 loss_db: 0.1875 2022/10/26 00:47:11 - mmengine - INFO - Epoch(train) [353][55/63] lr: 2.5859e-03 eta: 13:12:05 time: 0.8304 data_time: 0.0327 memory: 16131 loss: 2.0150 loss_prob: 1.2049 loss_thr: 0.6213 loss_db: 0.1889 2022/10/26 00:47:14 - mmengine - INFO - Epoch(train) [353][60/63] lr: 2.5859e-03 eta: 13:11:51 time: 0.6872 data_time: 0.0095 memory: 16131 loss: 2.0228 loss_prob: 1.2080 loss_thr: 0.6238 loss_db: 0.1909 2022/10/26 00:47:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:47:21 - mmengine - INFO - Epoch(train) [354][5/63] lr: 2.5831e-03 eta: 13:11:51 time: 0.8895 data_time: 0.1996 memory: 16131 loss: 1.9169 loss_prob: 1.1253 loss_thr: 0.6091 loss_db: 0.1825 2022/10/26 00:47:28 - mmengine - INFO - Epoch(train) [354][10/63] lr: 2.5831e-03 eta: 13:11:43 time: 1.2835 data_time: 0.2061 memory: 16131 loss: 1.9343 loss_prob: 1.1291 loss_thr: 0.6188 loss_db: 0.1864 2022/10/26 00:47:31 - mmengine - INFO - Epoch(train) [354][15/63] lr: 2.5831e-03 eta: 13:11:43 time: 0.9581 data_time: 0.0183 memory: 16131 loss: 1.8840 loss_prob: 1.1067 loss_thr: 0.5913 loss_db: 0.1860 2022/10/26 00:47:36 - mmengine - INFO - Epoch(train) [354][20/63] lr: 2.5831e-03 eta: 13:11:31 time: 0.7863 data_time: 0.0171 memory: 16131 loss: 1.7352 loss_prob: 1.0268 loss_thr: 0.5434 loss_db: 0.1651 2022/10/26 00:47:39 - mmengine - INFO - Epoch(train) [354][25/63] lr: 2.5831e-03 eta: 13:11:31 time: 0.7861 data_time: 0.0350 memory: 16131 loss: 1.8294 loss_prob: 1.0867 loss_thr: 0.5669 loss_db: 0.1758 2022/10/26 00:47:42 - mmengine - INFO - Epoch(train) [354][30/63] lr: 2.5831e-03 eta: 13:11:16 time: 0.6271 data_time: 0.0342 memory: 16131 loss: 2.0605 loss_prob: 1.2352 loss_thr: 0.6157 loss_db: 0.2096 2022/10/26 00:47:46 - mmengine - INFO - Epoch(train) [354][35/63] lr: 2.5831e-03 eta: 13:11:16 time: 0.7238 data_time: 0.0108 memory: 16131 loss: 2.2062 loss_prob: 1.3380 loss_thr: 0.6484 loss_db: 0.2198 2022/10/26 00:47:49 - mmengine - INFO - Epoch(train) [354][40/63] lr: 2.5831e-03 eta: 13:11:03 time: 0.7214 data_time: 0.0065 memory: 16131 loss: 2.1285 loss_prob: 1.2854 loss_thr: 0.6388 loss_db: 0.2043 2022/10/26 00:47:53 - mmengine - INFO - Epoch(train) [354][45/63] lr: 2.5831e-03 eta: 13:11:03 time: 0.7052 data_time: 0.0075 memory: 16131 loss: 2.0434 loss_prob: 1.2134 loss_thr: 0.6350 loss_db: 0.1950 2022/10/26 00:47:58 - mmengine - INFO - Epoch(train) [354][50/63] lr: 2.5831e-03 eta: 13:10:54 time: 0.8964 data_time: 0.0213 memory: 16131 loss: 2.1158 loss_prob: 1.2810 loss_thr: 0.6210 loss_db: 0.2139 2022/10/26 00:48:01 - mmengine - INFO - Epoch(train) [354][55/63] lr: 2.5831e-03 eta: 13:10:54 time: 0.7906 data_time: 0.0211 memory: 16131 loss: 2.1954 loss_prob: 1.3371 loss_thr: 0.6380 loss_db: 0.2204 2022/10/26 00:48:04 - mmengine - INFO - Epoch(train) [354][60/63] lr: 2.5831e-03 eta: 13:10:38 time: 0.5774 data_time: 0.0120 memory: 16131 loss: 2.1764 loss_prob: 1.3223 loss_thr: 0.6450 loss_db: 0.2091 2022/10/26 00:48:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:48:13 - mmengine - INFO - Epoch(train) [355][5/63] lr: 2.5804e-03 eta: 13:10:38 time: 1.0306 data_time: 0.1926 memory: 16131 loss: 1.9313 loss_prob: 1.1269 loss_thr: 0.6208 loss_db: 0.1837 2022/10/26 00:48:18 - mmengine - INFO - Epoch(train) [355][10/63] lr: 2.5804e-03 eta: 13:10:28 time: 1.2418 data_time: 0.1898 memory: 16131 loss: 1.9205 loss_prob: 1.1249 loss_thr: 0.6089 loss_db: 0.1867 2022/10/26 00:48:22 - mmengine - INFO - Epoch(train) [355][15/63] lr: 2.5804e-03 eta: 13:10:28 time: 0.8433 data_time: 0.0111 memory: 16131 loss: 2.0515 loss_prob: 1.2340 loss_thr: 0.6106 loss_db: 0.2070 2022/10/26 00:48:25 - mmengine - INFO - Epoch(train) [355][20/63] lr: 2.5804e-03 eta: 13:10:17 time: 0.7717 data_time: 0.0109 memory: 16131 loss: 1.9060 loss_prob: 1.1375 loss_thr: 0.5826 loss_db: 0.1859 2022/10/26 00:48:28 - mmengine - INFO - Epoch(train) [355][25/63] lr: 2.5804e-03 eta: 13:10:17 time: 0.6634 data_time: 0.0158 memory: 16131 loss: 1.7007 loss_prob: 0.9728 loss_thr: 0.5719 loss_db: 0.1561 2022/10/26 00:48:31 - mmengine - INFO - Epoch(train) [355][30/63] lr: 2.5804e-03 eta: 13:10:00 time: 0.5758 data_time: 0.0392 memory: 16131 loss: 1.8652 loss_prob: 1.0917 loss_thr: 0.5935 loss_db: 0.1800 2022/10/26 00:48:34 - mmengine - INFO - Epoch(train) [355][35/63] lr: 2.5804e-03 eta: 13:10:00 time: 0.5838 data_time: 0.0299 memory: 16131 loss: 2.0464 loss_prob: 1.2397 loss_thr: 0.6088 loss_db: 0.1979 2022/10/26 00:48:40 - mmengine - INFO - Epoch(train) [355][40/63] lr: 2.5804e-03 eta: 13:09:51 time: 0.8559 data_time: 0.0082 memory: 16131 loss: 2.0163 loss_prob: 1.2159 loss_thr: 0.6068 loss_db: 0.1936 2022/10/26 00:48:46 - mmengine - INFO - Epoch(train) [355][45/63] lr: 2.5804e-03 eta: 13:09:51 time: 1.2205 data_time: 0.0067 memory: 16131 loss: 1.8971 loss_prob: 1.1155 loss_thr: 0.5987 loss_db: 0.1829 2022/10/26 00:48:52 - mmengine - INFO - Epoch(train) [355][50/63] lr: 2.5804e-03 eta: 13:09:50 time: 1.2459 data_time: 0.0156 memory: 16131 loss: 1.7918 loss_prob: 1.0432 loss_thr: 0.5764 loss_db: 0.1722 2022/10/26 00:48:55 - mmengine - INFO - Epoch(train) [355][55/63] lr: 2.5804e-03 eta: 13:09:50 time: 0.8682 data_time: 0.0238 memory: 16131 loss: 1.8033 loss_prob: 1.0577 loss_thr: 0.5730 loss_db: 0.1725 2022/10/26 00:48:58 - mmengine - INFO - Epoch(train) [355][60/63] lr: 2.5804e-03 eta: 13:09:33 time: 0.5543 data_time: 0.0133 memory: 16131 loss: 1.8545 loss_prob: 1.0894 loss_thr: 0.5907 loss_db: 0.1745 2022/10/26 00:48:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:49:06 - mmengine - INFO - Epoch(train) [356][5/63] lr: 2.5776e-03 eta: 13:09:33 time: 0.9301 data_time: 0.2161 memory: 16131 loss: 2.0425 loss_prob: 1.2082 loss_thr: 0.6317 loss_db: 0.2027 2022/10/26 00:49:09 - mmengine - INFO - Epoch(train) [356][10/63] lr: 2.5776e-03 eta: 13:09:17 time: 0.9537 data_time: 0.2144 memory: 16131 loss: 2.1479 loss_prob: 1.3131 loss_thr: 0.6260 loss_db: 0.2088 2022/10/26 00:49:14 - mmengine - INFO - Epoch(train) [356][15/63] lr: 2.5776e-03 eta: 13:09:17 time: 0.8351 data_time: 0.0062 memory: 16131 loss: 2.2010 loss_prob: 1.3648 loss_thr: 0.6226 loss_db: 0.2137 2022/10/26 00:49:17 - mmengine - INFO - Epoch(train) [356][20/63] lr: 2.5776e-03 eta: 13:09:06 time: 0.8182 data_time: 0.0104 memory: 16131 loss: 2.2053 loss_prob: 1.3593 loss_thr: 0.6251 loss_db: 0.2209 2022/10/26 00:49:21 - mmengine - INFO - Epoch(train) [356][25/63] lr: 2.5776e-03 eta: 13:09:06 time: 0.6195 data_time: 0.0322 memory: 16131 loss: 2.0911 loss_prob: 1.2730 loss_thr: 0.6085 loss_db: 0.2096 2022/10/26 00:49:23 - mmengine - INFO - Epoch(train) [356][30/63] lr: 2.5776e-03 eta: 13:08:52 time: 0.6685 data_time: 0.0394 memory: 16131 loss: 1.8706 loss_prob: 1.0848 loss_thr: 0.6041 loss_db: 0.1817 2022/10/26 00:49:26 - mmengine - INFO - Epoch(train) [356][35/63] lr: 2.5776e-03 eta: 13:08:52 time: 0.5579 data_time: 0.0165 memory: 16131 loss: 1.8577 loss_prob: 1.0742 loss_thr: 0.6048 loss_db: 0.1786 2022/10/26 00:49:30 - mmengine - INFO - Epoch(train) [356][40/63] lr: 2.5776e-03 eta: 13:08:38 time: 0.6820 data_time: 0.0050 memory: 16131 loss: 1.9075 loss_prob: 1.1101 loss_thr: 0.6134 loss_db: 0.1840 2022/10/26 00:49:34 - mmengine - INFO - Epoch(train) [356][45/63] lr: 2.5776e-03 eta: 13:08:38 time: 0.8406 data_time: 0.0063 memory: 16131 loss: 1.9840 loss_prob: 1.1652 loss_thr: 0.6309 loss_db: 0.1879 2022/10/26 00:49:38 - mmengine - INFO - Epoch(train) [356][50/63] lr: 2.5776e-03 eta: 13:08:26 time: 0.7465 data_time: 0.0362 memory: 16131 loss: 1.9773 loss_prob: 1.1853 loss_thr: 0.6035 loss_db: 0.1884 2022/10/26 00:49:40 - mmengine - INFO - Epoch(train) [356][55/63] lr: 2.5776e-03 eta: 13:08:26 time: 0.5874 data_time: 0.0351 memory: 16131 loss: 1.9967 loss_prob: 1.1979 loss_thr: 0.6012 loss_db: 0.1977 2022/10/26 00:49:43 - mmengine - INFO - Epoch(train) [356][60/63] lr: 2.5776e-03 eta: 13:08:09 time: 0.5352 data_time: 0.0049 memory: 16131 loss: 2.1587 loss_prob: 1.3135 loss_thr: 0.6211 loss_db: 0.2240 2022/10/26 00:49:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:49:50 - mmengine - INFO - Epoch(train) [357][5/63] lr: 2.5749e-03 eta: 13:08:09 time: 0.8270 data_time: 0.1512 memory: 16131 loss: 2.0602 loss_prob: 1.2482 loss_thr: 0.6092 loss_db: 0.2028 2022/10/26 00:49:53 - mmengine - INFO - Epoch(train) [357][10/63] lr: 2.5749e-03 eta: 13:07:50 time: 0.8481 data_time: 0.1613 memory: 16131 loss: 2.0342 loss_prob: 1.2217 loss_thr: 0.6137 loss_db: 0.1988 2022/10/26 00:49:58 - mmengine - INFO - Epoch(train) [357][15/63] lr: 2.5749e-03 eta: 13:07:50 time: 0.7985 data_time: 0.0185 memory: 16131 loss: 2.0835 loss_prob: 1.2508 loss_thr: 0.6329 loss_db: 0.1998 2022/10/26 00:50:01 - mmengine - INFO - Epoch(train) [357][20/63] lr: 2.5749e-03 eta: 13:07:39 time: 0.7932 data_time: 0.0100 memory: 16131 loss: 2.4099 loss_prob: 1.5214 loss_thr: 0.6580 loss_db: 0.2305 2022/10/26 00:50:04 - mmengine - INFO - Epoch(train) [357][25/63] lr: 2.5749e-03 eta: 13:07:39 time: 0.5958 data_time: 0.0178 memory: 16131 loss: 2.3124 loss_prob: 1.4545 loss_thr: 0.6302 loss_db: 0.2277 2022/10/26 00:50:07 - mmengine - INFO - Epoch(train) [357][30/63] lr: 2.5749e-03 eta: 13:07:23 time: 0.6108 data_time: 0.0262 memory: 16131 loss: 1.9873 loss_prob: 1.1906 loss_thr: 0.6021 loss_db: 0.1946 2022/10/26 00:50:11 - mmengine - INFO - Epoch(train) [357][35/63] lr: 2.5749e-03 eta: 13:07:23 time: 0.7251 data_time: 0.0326 memory: 16131 loss: 1.9652 loss_prob: 1.1758 loss_thr: 0.6002 loss_db: 0.1891 2022/10/26 00:50:16 - mmengine - INFO - Epoch(train) [357][40/63] lr: 2.5749e-03 eta: 13:07:14 time: 0.8574 data_time: 0.0256 memory: 16131 loss: 1.9057 loss_prob: 1.1339 loss_thr: 0.5878 loss_db: 0.1840 2022/10/26 00:50:21 - mmengine - INFO - Epoch(train) [357][45/63] lr: 2.5749e-03 eta: 13:07:14 time: 0.9664 data_time: 0.0076 memory: 16131 loss: 1.8000 loss_prob: 1.0468 loss_thr: 0.5825 loss_db: 0.1706 2022/10/26 00:50:24 - mmengine - INFO - Epoch(train) [357][50/63] lr: 2.5749e-03 eta: 13:07:04 time: 0.8387 data_time: 0.0137 memory: 16131 loss: 1.7840 loss_prob: 1.0362 loss_thr: 0.5801 loss_db: 0.1677 2022/10/26 00:50:27 - mmengine - INFO - Epoch(train) [357][55/63] lr: 2.5749e-03 eta: 13:07:04 time: 0.5561 data_time: 0.0187 memory: 16131 loss: 1.7892 loss_prob: 1.0476 loss_thr: 0.5771 loss_db: 0.1644 2022/10/26 00:50:29 - mmengine - INFO - Epoch(train) [357][60/63] lr: 2.5749e-03 eta: 13:06:46 time: 0.5375 data_time: 0.0142 memory: 16131 loss: 1.7580 loss_prob: 1.0155 loss_thr: 0.5790 loss_db: 0.1635 2022/10/26 00:50:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:50:37 - mmengine - INFO - Epoch(train) [358][5/63] lr: 2.5721e-03 eta: 13:06:46 time: 0.9189 data_time: 0.2284 memory: 16131 loss: 1.9619 loss_prob: 1.1818 loss_thr: 0.5865 loss_db: 0.1936 2022/10/26 00:50:42 - mmengine - INFO - Epoch(train) [358][10/63] lr: 2.5721e-03 eta: 13:06:35 time: 1.1447 data_time: 0.2263 memory: 16131 loss: 1.9720 loss_prob: 1.1910 loss_thr: 0.5868 loss_db: 0.1942 2022/10/26 00:50:45 - mmengine - INFO - Epoch(train) [358][15/63] lr: 2.5721e-03 eta: 13:06:35 time: 0.7922 data_time: 0.0086 memory: 16131 loss: 1.8060 loss_prob: 1.0672 loss_thr: 0.5654 loss_db: 0.1733 2022/10/26 00:50:49 - mmengine - INFO - Epoch(train) [358][20/63] lr: 2.5721e-03 eta: 13:06:20 time: 0.6435 data_time: 0.0078 memory: 16131 loss: 1.7363 loss_prob: 1.0108 loss_thr: 0.5603 loss_db: 0.1652 2022/10/26 00:50:52 - mmengine - INFO - Epoch(train) [358][25/63] lr: 2.5721e-03 eta: 13:06:20 time: 0.7060 data_time: 0.0329 memory: 16131 loss: 1.8137 loss_prob: 1.0647 loss_thr: 0.5787 loss_db: 0.1703 2022/10/26 00:50:55 - mmengine - INFO - Epoch(train) [358][30/63] lr: 2.5721e-03 eta: 13:06:05 time: 0.6260 data_time: 0.0343 memory: 16131 loss: 1.8965 loss_prob: 1.1215 loss_thr: 0.5930 loss_db: 0.1820 2022/10/26 00:50:59 - mmengine - INFO - Epoch(train) [358][35/63] lr: 2.5721e-03 eta: 13:06:05 time: 0.6409 data_time: 0.0066 memory: 16131 loss: 1.8199 loss_prob: 1.0680 loss_thr: 0.5787 loss_db: 0.1731 2022/10/26 00:51:03 - mmengine - INFO - Epoch(train) [358][40/63] lr: 2.5721e-03 eta: 13:05:54 time: 0.8273 data_time: 0.0054 memory: 16131 loss: 1.7321 loss_prob: 1.0227 loss_thr: 0.5433 loss_db: 0.1661 2022/10/26 00:51:09 - mmengine - INFO - Epoch(train) [358][45/63] lr: 2.5721e-03 eta: 13:05:54 time: 1.0131 data_time: 0.0064 memory: 16131 loss: 1.7162 loss_prob: 0.9996 loss_thr: 0.5528 loss_db: 0.1639 2022/10/26 00:51:13 - mmengine - INFO - Epoch(train) [358][50/63] lr: 2.5721e-03 eta: 13:05:48 time: 1.0011 data_time: 0.0373 memory: 16131 loss: 1.7920 loss_prob: 1.0325 loss_thr: 0.5951 loss_db: 0.1644 2022/10/26 00:51:16 - mmengine - INFO - Epoch(train) [358][55/63] lr: 2.5721e-03 eta: 13:05:48 time: 0.7181 data_time: 0.0380 memory: 16131 loss: 1.7889 loss_prob: 1.0314 loss_thr: 0.5921 loss_db: 0.1654 2022/10/26 00:51:21 - mmengine - INFO - Epoch(train) [358][60/63] lr: 2.5721e-03 eta: 13:05:35 time: 0.7220 data_time: 0.0073 memory: 16131 loss: 1.7957 loss_prob: 1.0379 loss_thr: 0.5899 loss_db: 0.1678 2022/10/26 00:51:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:51:28 - mmengine - INFO - Epoch(train) [359][5/63] lr: 2.5694e-03 eta: 13:05:35 time: 0.8257 data_time: 0.2352 memory: 16131 loss: 1.7622 loss_prob: 0.9900 loss_thr: 0.6106 loss_db: 0.1616 2022/10/26 00:51:33 - mmengine - INFO - Epoch(train) [359][10/63] lr: 2.5694e-03 eta: 13:05:23 time: 1.1301 data_time: 0.2363 memory: 16131 loss: 1.7954 loss_prob: 1.0248 loss_thr: 0.6022 loss_db: 0.1684 2022/10/26 00:51:40 - mmengine - INFO - Epoch(train) [359][15/63] lr: 2.5694e-03 eta: 13:05:23 time: 1.1907 data_time: 0.0093 memory: 16131 loss: 1.7732 loss_prob: 1.0204 loss_thr: 0.5853 loss_db: 0.1676 2022/10/26 00:51:43 - mmengine - INFO - Epoch(train) [359][20/63] lr: 2.5694e-03 eta: 13:05:15 time: 0.9198 data_time: 0.0090 memory: 16131 loss: 1.8925 loss_prob: 1.1118 loss_thr: 0.6011 loss_db: 0.1795 2022/10/26 00:51:45 - mmengine - INFO - Epoch(train) [359][25/63] lr: 2.5694e-03 eta: 13:05:15 time: 0.5659 data_time: 0.0351 memory: 16131 loss: 1.8917 loss_prob: 1.1100 loss_thr: 0.5994 loss_db: 0.1824 2022/10/26 00:51:48 - mmengine - INFO - Epoch(train) [359][30/63] lr: 2.5694e-03 eta: 13:04:58 time: 0.5300 data_time: 0.0337 memory: 16131 loss: 1.7670 loss_prob: 1.0140 loss_thr: 0.5855 loss_db: 0.1676 2022/10/26 00:51:50 - mmengine - INFO - Epoch(train) [359][35/63] lr: 2.5694e-03 eta: 13:04:58 time: 0.4910 data_time: 0.0094 memory: 16131 loss: 1.7402 loss_prob: 1.0067 loss_thr: 0.5650 loss_db: 0.1685 2022/10/26 00:51:53 - mmengine - INFO - Epoch(train) [359][40/63] lr: 2.5694e-03 eta: 13:04:41 time: 0.5392 data_time: 0.0113 memory: 16131 loss: 1.8032 loss_prob: 1.0563 loss_thr: 0.5712 loss_db: 0.1757 2022/10/26 00:51:56 - mmengine - INFO - Epoch(train) [359][45/63] lr: 2.5694e-03 eta: 13:04:41 time: 0.5429 data_time: 0.0085 memory: 16131 loss: 1.8377 loss_prob: 1.0795 loss_thr: 0.5845 loss_db: 0.1738 2022/10/26 00:51:58 - mmengine - INFO - Epoch(train) [359][50/63] lr: 2.5694e-03 eta: 13:04:23 time: 0.5198 data_time: 0.0219 memory: 16131 loss: 1.7797 loss_prob: 1.0389 loss_thr: 0.5740 loss_db: 0.1668 2022/10/26 00:52:01 - mmengine - INFO - Epoch(train) [359][55/63] lr: 2.5694e-03 eta: 13:04:23 time: 0.5295 data_time: 0.0202 memory: 16131 loss: 1.7852 loss_prob: 1.0441 loss_thr: 0.5671 loss_db: 0.1740 2022/10/26 00:52:05 - mmengine - INFO - Epoch(train) [359][60/63] lr: 2.5694e-03 eta: 13:04:09 time: 0.6524 data_time: 0.0064 memory: 16131 loss: 1.6948 loss_prob: 0.9740 loss_thr: 0.5571 loss_db: 0.1636 2022/10/26 00:52:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:52:13 - mmengine - INFO - Epoch(train) [360][5/63] lr: 2.5666e-03 eta: 13:04:09 time: 0.9258 data_time: 0.1912 memory: 16131 loss: 1.7652 loss_prob: 1.0227 loss_thr: 0.5767 loss_db: 0.1658 2022/10/26 00:52:17 - mmengine - INFO - Epoch(train) [360][10/63] lr: 2.5666e-03 eta: 13:03:55 time: 1.0413 data_time: 0.1907 memory: 16131 loss: 1.7061 loss_prob: 0.9710 loss_thr: 0.5776 loss_db: 0.1576 2022/10/26 00:52:21 - mmengine - INFO - Epoch(train) [360][15/63] lr: 2.5666e-03 eta: 13:03:55 time: 0.7657 data_time: 0.0138 memory: 16131 loss: 1.6520 loss_prob: 0.9319 loss_thr: 0.5673 loss_db: 0.1528 2022/10/26 00:52:24 - mmengine - INFO - Epoch(train) [360][20/63] lr: 2.5666e-03 eta: 13:03:42 time: 0.7229 data_time: 0.0125 memory: 16131 loss: 1.8547 loss_prob: 1.0964 loss_thr: 0.5813 loss_db: 0.1769 2022/10/26 00:52:28 - mmengine - INFO - Epoch(train) [360][25/63] lr: 2.5666e-03 eta: 13:03:42 time: 0.7076 data_time: 0.0210 memory: 16131 loss: 1.8200 loss_prob: 1.0698 loss_thr: 0.5751 loss_db: 0.1751 2022/10/26 00:52:31 - mmengine - INFO - Epoch(train) [360][30/63] lr: 2.5666e-03 eta: 13:03:28 time: 0.6638 data_time: 0.0287 memory: 16131 loss: 1.6376 loss_prob: 0.9309 loss_thr: 0.5523 loss_db: 0.1543 2022/10/26 00:52:33 - mmengine - INFO - Epoch(train) [360][35/63] lr: 2.5666e-03 eta: 13:03:28 time: 0.5412 data_time: 0.0145 memory: 16131 loss: 1.7122 loss_prob: 0.9893 loss_thr: 0.5593 loss_db: 0.1636 2022/10/26 00:52:38 - mmengine - INFO - Epoch(train) [360][40/63] lr: 2.5666e-03 eta: 13:03:16 time: 0.7468 data_time: 0.0151 memory: 16131 loss: 1.8065 loss_prob: 1.0558 loss_thr: 0.5770 loss_db: 0.1737 2022/10/26 00:52:41 - mmengine - INFO - Epoch(train) [360][45/63] lr: 2.5666e-03 eta: 13:03:16 time: 0.7387 data_time: 0.0139 memory: 16131 loss: 1.6969 loss_prob: 0.9793 loss_thr: 0.5580 loss_db: 0.1596 2022/10/26 00:52:47 - mmengine - INFO - Epoch(train) [360][50/63] lr: 2.5666e-03 eta: 13:03:08 time: 0.9293 data_time: 0.0181 memory: 16131 loss: 1.6934 loss_prob: 0.9704 loss_thr: 0.5622 loss_db: 0.1607 2022/10/26 00:52:51 - mmengine - INFO - Epoch(train) [360][55/63] lr: 2.5666e-03 eta: 13:03:08 time: 1.0636 data_time: 0.0232 memory: 16131 loss: 1.8390 loss_prob: 1.0626 loss_thr: 0.6005 loss_db: 0.1760 2022/10/26 00:52:56 - mmengine - INFO - Epoch(train) [360][60/63] lr: 2.5666e-03 eta: 13:02:58 time: 0.8368 data_time: 0.0106 memory: 16131 loss: 1.8107 loss_prob: 1.0419 loss_thr: 0.5987 loss_db: 0.1701 2022/10/26 00:52:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:52:57 - mmengine - INFO - Saving checkpoint at 360 epochs 2022/10/26 00:53:04 - mmengine - INFO - Epoch(val) [360][5/32] eta: 13:02:58 time: 0.5475 data_time: 0.0821 memory: 16131 2022/10/26 00:53:07 - mmengine - INFO - Epoch(val) [360][10/32] eta: 0:00:13 time: 0.6185 data_time: 0.1182 memory: 15724 2022/10/26 00:53:10 - mmengine - INFO - Epoch(val) [360][15/32] eta: 0:00:13 time: 0.5604 data_time: 0.0521 memory: 15724 2022/10/26 00:53:13 - mmengine - INFO - Epoch(val) [360][20/32] eta: 0:00:06 time: 0.5606 data_time: 0.0534 memory: 15724 2022/10/26 00:53:15 - mmengine - INFO - Epoch(val) [360][25/32] eta: 0:00:06 time: 0.5727 data_time: 0.0555 memory: 15724 2022/10/26 00:53:18 - mmengine - INFO - Epoch(val) [360][30/32] eta: 0:00:01 time: 0.5367 data_time: 0.0217 memory: 15724 2022/10/26 00:53:19 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8276, precision: 0.7060, hmean: 0.7620 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8276, precision: 0.7681, hmean: 0.7968 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8267, precision: 0.8126, hmean: 0.8196 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8156, precision: 0.8495, hmean: 0.8322 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7675, precision: 0.8980, hmean: 0.8276 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4362, precision: 0.9659, hmean: 0.6010 2022/10/26 00:53:19 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/26 00:53:19 - mmengine - INFO - Epoch(val) [360][32/32] icdar/precision: 0.8495 icdar/recall: 0.8156 icdar/hmean: 0.8322 2022/10/26 00:53:27 - mmengine - INFO - Epoch(train) [361][5/63] lr: 2.5639e-03 eta: 0:00:01 time: 1.2893 data_time: 0.2076 memory: 16131 loss: 1.8687 loss_prob: 1.0987 loss_thr: 0.5857 loss_db: 0.1844 2022/10/26 00:53:30 - mmengine - INFO - Epoch(train) [361][10/63] lr: 2.5639e-03 eta: 13:02:46 time: 1.1404 data_time: 0.2050 memory: 16131 loss: 1.9098 loss_prob: 1.1277 loss_thr: 0.6039 loss_db: 0.1782 2022/10/26 00:53:35 - mmengine - INFO - Epoch(train) [361][15/63] lr: 2.5639e-03 eta: 13:02:46 time: 0.8132 data_time: 0.0084 memory: 16131 loss: 1.7828 loss_prob: 1.0406 loss_thr: 0.5788 loss_db: 0.1634 2022/10/26 00:53:40 - mmengine - INFO - Epoch(train) [361][20/63] lr: 2.5639e-03 eta: 13:02:40 time: 1.0066 data_time: 0.0098 memory: 16131 loss: 1.5755 loss_prob: 0.8909 loss_thr: 0.5338 loss_db: 0.1508 2022/10/26 00:53:44 - mmengine - INFO - Epoch(train) [361][25/63] lr: 2.5639e-03 eta: 13:02:40 time: 0.8823 data_time: 0.0196 memory: 16131 loss: 1.8032 loss_prob: 1.0493 loss_thr: 0.5821 loss_db: 0.1718 2022/10/26 00:53:48 - mmengine - INFO - Epoch(train) [361][30/63] lr: 2.5639e-03 eta: 13:02:28 time: 0.7476 data_time: 0.0468 memory: 16131 loss: 1.8162 loss_prob: 1.0486 loss_thr: 0.5976 loss_db: 0.1699 2022/10/26 00:53:50 - mmengine - INFO - Epoch(train) [361][35/63] lr: 2.5639e-03 eta: 13:02:28 time: 0.5993 data_time: 0.0336 memory: 16131 loss: 1.6471 loss_prob: 0.9383 loss_thr: 0.5517 loss_db: 0.1571 2022/10/26 00:53:53 - mmengine - INFO - Epoch(train) [361][40/63] lr: 2.5639e-03 eta: 13:02:10 time: 0.5241 data_time: 0.0059 memory: 16131 loss: 1.6619 loss_prob: 0.9519 loss_thr: 0.5497 loss_db: 0.1602 2022/10/26 00:53:57 - mmengine - INFO - Epoch(train) [361][45/63] lr: 2.5639e-03 eta: 13:02:10 time: 0.6309 data_time: 0.0076 memory: 16131 loss: 1.7877 loss_prob: 1.0373 loss_thr: 0.5766 loss_db: 0.1738 2022/10/26 00:54:00 - mmengine - INFO - Epoch(train) [361][50/63] lr: 2.5639e-03 eta: 13:01:57 time: 0.6861 data_time: 0.0222 memory: 16131 loss: 1.8198 loss_prob: 1.0664 loss_thr: 0.5744 loss_db: 0.1790 2022/10/26 00:54:03 - mmengine - INFO - Epoch(train) [361][55/63] lr: 2.5639e-03 eta: 13:01:57 time: 0.6628 data_time: 0.0205 memory: 16131 loss: 1.7217 loss_prob: 0.9931 loss_thr: 0.5632 loss_db: 0.1654 2022/10/26 00:54:07 - mmengine - INFO - Epoch(train) [361][60/63] lr: 2.5639e-03 eta: 13:01:44 time: 0.7051 data_time: 0.0048 memory: 16131 loss: 1.8065 loss_prob: 1.0453 loss_thr: 0.5899 loss_db: 0.1713 2022/10/26 00:54:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:54:15 - mmengine - INFO - Epoch(train) [362][5/63] lr: 2.5611e-03 eta: 13:01:44 time: 0.9096 data_time: 0.1951 memory: 16131 loss: 1.8691 loss_prob: 1.1055 loss_thr: 0.5785 loss_db: 0.1851 2022/10/26 00:54:18 - mmengine - INFO - Epoch(train) [362][10/63] lr: 2.5611e-03 eta: 13:01:25 time: 0.8476 data_time: 0.1993 memory: 16131 loss: 1.9045 loss_prob: 1.1429 loss_thr: 0.5802 loss_db: 0.1815 2022/10/26 00:54:21 - mmengine - INFO - Epoch(train) [362][15/63] lr: 2.5611e-03 eta: 13:01:25 time: 0.6154 data_time: 0.0134 memory: 16131 loss: 1.9133 loss_prob: 1.1326 loss_thr: 0.5958 loss_db: 0.1848 2022/10/26 00:54:24 - mmengine - INFO - Epoch(train) [362][20/63] lr: 2.5611e-03 eta: 13:01:09 time: 0.5856 data_time: 0.0085 memory: 16131 loss: 1.8934 loss_prob: 1.0982 loss_thr: 0.6122 loss_db: 0.1830 2022/10/26 00:54:28 - mmengine - INFO - Epoch(train) [362][25/63] lr: 2.5611e-03 eta: 13:01:09 time: 0.6630 data_time: 0.0140 memory: 16131 loss: 2.2632 loss_prob: 1.3882 loss_thr: 0.6513 loss_db: 0.2237 2022/10/26 00:54:31 - mmengine - INFO - Epoch(train) [362][30/63] lr: 2.5611e-03 eta: 13:00:55 time: 0.6487 data_time: 0.0296 memory: 16131 loss: 2.2898 loss_prob: 1.4190 loss_thr: 0.6456 loss_db: 0.2252 2022/10/26 00:54:34 - mmengine - INFO - Epoch(train) [362][35/63] lr: 2.5611e-03 eta: 13:00:55 time: 0.5848 data_time: 0.0275 memory: 16131 loss: 2.0028 loss_prob: 1.1851 loss_thr: 0.6247 loss_db: 0.1930 2022/10/26 00:54:38 - mmengine - INFO - Epoch(train) [362][40/63] lr: 2.5611e-03 eta: 13:00:41 time: 0.6780 data_time: 0.0114 memory: 16131 loss: 1.8664 loss_prob: 1.0808 loss_thr: 0.6085 loss_db: 0.1771 2022/10/26 00:54:44 - mmengine - INFO - Epoch(train) [362][45/63] lr: 2.5611e-03 eta: 13:00:41 time: 1.0169 data_time: 0.0070 memory: 16131 loss: 1.8100 loss_prob: 1.0555 loss_thr: 0.5842 loss_db: 0.1702 2022/10/26 00:54:49 - mmengine - INFO - Epoch(train) [362][50/63] lr: 2.5611e-03 eta: 13:00:38 time: 1.1598 data_time: 0.0153 memory: 16131 loss: 1.8784 loss_prob: 1.1101 loss_thr: 0.5923 loss_db: 0.1761 2022/10/26 00:54:52 - mmengine - INFO - Epoch(train) [362][55/63] lr: 2.5611e-03 eta: 13:00:38 time: 0.8139 data_time: 0.0225 memory: 16131 loss: 1.8433 loss_prob: 1.0683 loss_thr: 0.5992 loss_db: 0.1758 2022/10/26 00:54:54 - mmengine - INFO - Epoch(train) [362][60/63] lr: 2.5611e-03 eta: 13:00:21 time: 0.5195 data_time: 0.0146 memory: 16131 loss: 1.7918 loss_prob: 1.0374 loss_thr: 0.5815 loss_db: 0.1730 2022/10/26 00:54:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:55:00 - mmengine - INFO - Epoch(train) [363][5/63] lr: 2.5584e-03 eta: 13:00:21 time: 0.7036 data_time: 0.1819 memory: 16131 loss: 1.8664 loss_prob: 1.0984 loss_thr: 0.5930 loss_db: 0.1750 2022/10/26 00:55:03 - mmengine - INFO - Epoch(train) [363][10/63] lr: 2.5584e-03 eta: 12:59:59 time: 0.7118 data_time: 0.1819 memory: 16131 loss: 1.9124 loss_prob: 1.1192 loss_thr: 0.6094 loss_db: 0.1838 2022/10/26 00:55:06 - mmengine - INFO - Epoch(train) [363][15/63] lr: 2.5584e-03 eta: 12:59:59 time: 0.5527 data_time: 0.0053 memory: 16131 loss: 1.9509 loss_prob: 1.1536 loss_thr: 0.6071 loss_db: 0.1903 2022/10/26 00:55:09 - mmengine - INFO - Epoch(train) [363][20/63] lr: 2.5584e-03 eta: 12:59:44 time: 0.5898 data_time: 0.0063 memory: 16131 loss: 1.9632 loss_prob: 1.1817 loss_thr: 0.5851 loss_db: 0.1964 2022/10/26 00:55:12 - mmengine - INFO - Epoch(train) [363][25/63] lr: 2.5584e-03 eta: 12:59:44 time: 0.5710 data_time: 0.0279 memory: 16131 loss: 1.9679 loss_prob: 1.1863 loss_thr: 0.5865 loss_db: 0.1951 2022/10/26 00:55:15 - mmengine - INFO - Epoch(train) [363][30/63] lr: 2.5584e-03 eta: 12:59:28 time: 0.6146 data_time: 0.0396 memory: 16131 loss: 1.9767 loss_prob: 1.1885 loss_thr: 0.5988 loss_db: 0.1894 2022/10/26 00:55:21 - mmengine - INFO - Epoch(train) [363][35/63] lr: 2.5584e-03 eta: 12:59:28 time: 0.9130 data_time: 0.0176 memory: 16131 loss: 2.0279 loss_prob: 1.2228 loss_thr: 0.6004 loss_db: 0.2048 2022/10/26 00:55:26 - mmengine - INFO - Epoch(train) [363][40/63] lr: 2.5584e-03 eta: 12:59:24 time: 1.0994 data_time: 0.0051 memory: 16131 loss: 1.9593 loss_prob: 1.1776 loss_thr: 0.5843 loss_db: 0.1974 2022/10/26 00:55:30 - mmengine - INFO - Epoch(train) [363][45/63] lr: 2.5584e-03 eta: 12:59:24 time: 0.9578 data_time: 0.0068 memory: 16131 loss: 1.8824 loss_prob: 1.1331 loss_thr: 0.5699 loss_db: 0.1794 2022/10/26 00:55:35 - mmengine - INFO - Epoch(train) [363][50/63] lr: 2.5584e-03 eta: 12:59:15 time: 0.8806 data_time: 0.0169 memory: 16131 loss: 1.8553 loss_prob: 1.1068 loss_thr: 0.5709 loss_db: 0.1776 2022/10/26 00:55:39 - mmengine - INFO - Epoch(train) [363][55/63] lr: 2.5584e-03 eta: 12:59:15 time: 0.8364 data_time: 0.0228 memory: 16131 loss: 1.8034 loss_prob: 1.0506 loss_thr: 0.5823 loss_db: 0.1704 2022/10/26 00:55:43 - mmengine - INFO - Epoch(train) [363][60/63] lr: 2.5584e-03 eta: 12:59:04 time: 0.7950 data_time: 0.0128 memory: 16131 loss: 1.8429 loss_prob: 1.0683 loss_thr: 0.5961 loss_db: 0.1785 2022/10/26 00:55:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:55:52 - mmengine - INFO - Epoch(train) [364][5/63] lr: 2.5556e-03 eta: 12:59:04 time: 1.1683 data_time: 0.2133 memory: 16131 loss: 1.9775 loss_prob: 1.1896 loss_thr: 0.5931 loss_db: 0.1948 2022/10/26 00:55:55 - mmengine - INFO - Epoch(train) [364][10/63] lr: 2.5556e-03 eta: 12:58:48 time: 0.9379 data_time: 0.2129 memory: 16131 loss: 1.8340 loss_prob: 1.0616 loss_thr: 0.5982 loss_db: 0.1742 2022/10/26 00:55:57 - mmengine - INFO - Epoch(train) [364][15/63] lr: 2.5556e-03 eta: 12:58:48 time: 0.5391 data_time: 0.0051 memory: 16131 loss: 1.8344 loss_prob: 1.0624 loss_thr: 0.5979 loss_db: 0.1741 2022/10/26 00:56:00 - mmengine - INFO - Epoch(train) [364][20/63] lr: 2.5556e-03 eta: 12:58:32 time: 0.5611 data_time: 0.0070 memory: 16131 loss: 1.7637 loss_prob: 1.0168 loss_thr: 0.5789 loss_db: 0.1680 2022/10/26 00:56:04 - mmengine - INFO - Epoch(train) [364][25/63] lr: 2.5556e-03 eta: 12:58:32 time: 0.6219 data_time: 0.0307 memory: 16131 loss: 1.6608 loss_prob: 0.9344 loss_thr: 0.5735 loss_db: 0.1529 2022/10/26 00:56:07 - mmengine - INFO - Epoch(train) [364][30/63] lr: 2.5556e-03 eta: 12:58:19 time: 0.7021 data_time: 0.0287 memory: 16131 loss: 1.6969 loss_prob: 0.9528 loss_thr: 0.5870 loss_db: 0.1571 2022/10/26 00:56:12 - mmengine - INFO - Epoch(train) [364][35/63] lr: 2.5556e-03 eta: 12:58:19 time: 0.8618 data_time: 0.0202 memory: 16131 loss: 1.7675 loss_prob: 1.0244 loss_thr: 0.5714 loss_db: 0.1717 2022/10/26 00:56:15 - mmengine - INFO - Epoch(train) [364][40/63] lr: 2.5556e-03 eta: 12:58:06 time: 0.7461 data_time: 0.0233 memory: 16131 loss: 1.7752 loss_prob: 1.0405 loss_thr: 0.5652 loss_db: 0.1695 2022/10/26 00:56:18 - mmengine - INFO - Epoch(train) [364][45/63] lr: 2.5556e-03 eta: 12:58:06 time: 0.5492 data_time: 0.0117 memory: 16131 loss: 1.7242 loss_prob: 0.9853 loss_thr: 0.5809 loss_db: 0.1580 2022/10/26 00:56:21 - mmengine - INFO - Epoch(train) [364][50/63] lr: 2.5556e-03 eta: 12:57:51 time: 0.6118 data_time: 0.0245 memory: 16131 loss: 1.7858 loss_prob: 1.0311 loss_thr: 0.5902 loss_db: 0.1644 2022/10/26 00:56:23 - mmengine - INFO - Epoch(train) [364][55/63] lr: 2.5556e-03 eta: 12:57:51 time: 0.5699 data_time: 0.0222 memory: 16131 loss: 1.7827 loss_prob: 1.0426 loss_thr: 0.5715 loss_db: 0.1686 2022/10/26 00:56:28 - mmengine - INFO - Epoch(train) [364][60/63] lr: 2.5556e-03 eta: 12:57:38 time: 0.6978 data_time: 0.0078 memory: 16131 loss: 1.7771 loss_prob: 1.0287 loss_thr: 0.5785 loss_db: 0.1698 2022/10/26 00:56:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:56:35 - mmengine - INFO - Epoch(train) [365][5/63] lr: 2.5529e-03 eta: 12:57:38 time: 0.8119 data_time: 0.2311 memory: 16131 loss: 1.5805 loss_prob: 0.8941 loss_thr: 0.5388 loss_db: 0.1476 2022/10/26 00:56:39 - mmengine - INFO - Epoch(train) [365][10/63] lr: 2.5529e-03 eta: 12:57:22 time: 0.9719 data_time: 0.2268 memory: 16131 loss: 1.6406 loss_prob: 0.9460 loss_thr: 0.5410 loss_db: 0.1536 2022/10/26 00:56:44 - mmengine - INFO - Epoch(train) [365][15/63] lr: 2.5529e-03 eta: 12:57:22 time: 0.8899 data_time: 0.0054 memory: 16131 loss: 1.7131 loss_prob: 0.9929 loss_thr: 0.5582 loss_db: 0.1619 2022/10/26 00:56:46 - mmengine - INFO - Epoch(train) [365][20/63] lr: 2.5529e-03 eta: 12:57:10 time: 0.7364 data_time: 0.0053 memory: 16131 loss: 1.7637 loss_prob: 1.0199 loss_thr: 0.5805 loss_db: 0.1633 2022/10/26 00:56:49 - mmengine - INFO - Epoch(train) [365][25/63] lr: 2.5529e-03 eta: 12:57:10 time: 0.5684 data_time: 0.0363 memory: 16131 loss: 1.7212 loss_prob: 0.9897 loss_thr: 0.5732 loss_db: 0.1583 2022/10/26 00:56:53 - mmengine - INFO - Epoch(train) [365][30/63] lr: 2.5529e-03 eta: 12:56:56 time: 0.6534 data_time: 0.0386 memory: 16131 loss: 1.7122 loss_prob: 0.9846 loss_thr: 0.5651 loss_db: 0.1625 2022/10/26 00:56:56 - mmengine - INFO - Epoch(train) [365][35/63] lr: 2.5529e-03 eta: 12:56:56 time: 0.6319 data_time: 0.0112 memory: 16131 loss: 1.7495 loss_prob: 1.0043 loss_thr: 0.5789 loss_db: 0.1663 2022/10/26 00:57:00 - mmengine - INFO - Epoch(train) [365][40/63] lr: 2.5529e-03 eta: 12:56:42 time: 0.6548 data_time: 0.0100 memory: 16131 loss: 1.7135 loss_prob: 0.9717 loss_thr: 0.5792 loss_db: 0.1626 2022/10/26 00:57:04 - mmengine - INFO - Epoch(train) [365][45/63] lr: 2.5529e-03 eta: 12:56:42 time: 0.8753 data_time: 0.0070 memory: 16131 loss: 1.7864 loss_prob: 1.0112 loss_thr: 0.6053 loss_db: 0.1699 2022/10/26 00:57:09 - mmengine - INFO - Epoch(train) [365][50/63] lr: 2.5529e-03 eta: 12:56:34 time: 0.9439 data_time: 0.0181 memory: 16131 loss: 1.6842 loss_prob: 0.9494 loss_thr: 0.5760 loss_db: 0.1588 2022/10/26 00:57:12 - mmengine - INFO - Epoch(train) [365][55/63] lr: 2.5529e-03 eta: 12:56:34 time: 0.7474 data_time: 0.0190 memory: 16131 loss: 1.5804 loss_prob: 0.8929 loss_thr: 0.5409 loss_db: 0.1466 2022/10/26 00:57:16 - mmengine - INFO - Epoch(train) [365][60/63] lr: 2.5529e-03 eta: 12:56:22 time: 0.7144 data_time: 0.0106 memory: 16131 loss: 1.7439 loss_prob: 1.0149 loss_thr: 0.5633 loss_db: 0.1657 2022/10/26 00:57:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:57:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:57:27 - mmengine - INFO - Epoch(train) [366][5/63] lr: 2.5501e-03 eta: 12:56:22 time: 1.1890 data_time: 0.2514 memory: 16131 loss: 1.7962 loss_prob: 1.0511 loss_thr: 0.5751 loss_db: 0.1700 2022/10/26 00:57:32 - mmengine - INFO - Epoch(train) [366][10/63] lr: 2.5501e-03 eta: 12:56:17 time: 1.4556 data_time: 0.2499 memory: 16131 loss: 1.8174 loss_prob: 1.0615 loss_thr: 0.5833 loss_db: 0.1727 2022/10/26 00:57:35 - mmengine - INFO - Epoch(train) [366][15/63] lr: 2.5501e-03 eta: 12:56:17 time: 0.8642 data_time: 0.0052 memory: 16131 loss: 1.7885 loss_prob: 1.0185 loss_thr: 0.5992 loss_db: 0.1709 2022/10/26 00:57:39 - mmengine - INFO - Epoch(train) [366][20/63] lr: 2.5501e-03 eta: 12:56:05 time: 0.7258 data_time: 0.0063 memory: 16131 loss: 1.7788 loss_prob: 1.0107 loss_thr: 0.6014 loss_db: 0.1667 2022/10/26 00:57:44 - mmengine - INFO - Epoch(train) [366][25/63] lr: 2.5501e-03 eta: 12:56:05 time: 0.8691 data_time: 0.0361 memory: 16131 loss: 1.8465 loss_prob: 1.0717 loss_thr: 0.5993 loss_db: 0.1755 2022/10/26 00:57:48 - mmengine - INFO - Epoch(train) [366][30/63] lr: 2.5501e-03 eta: 12:55:55 time: 0.8528 data_time: 0.0358 memory: 16131 loss: 1.8349 loss_prob: 1.0677 loss_thr: 0.5921 loss_db: 0.1751 2022/10/26 00:57:51 - mmengine - INFO - Epoch(train) [366][35/63] lr: 2.5501e-03 eta: 12:55:55 time: 0.7282 data_time: 0.0093 memory: 16131 loss: 1.8262 loss_prob: 1.0536 loss_thr: 0.6002 loss_db: 0.1724 2022/10/26 00:57:55 - mmengine - INFO - Epoch(train) [366][40/63] lr: 2.5501e-03 eta: 12:55:43 time: 0.7450 data_time: 0.0093 memory: 16131 loss: 1.8215 loss_prob: 1.0642 loss_thr: 0.5818 loss_db: 0.1756 2022/10/26 00:58:01 - mmengine - INFO - Epoch(train) [366][45/63] lr: 2.5501e-03 eta: 12:55:43 time: 0.9354 data_time: 0.0074 memory: 16131 loss: 2.0636 loss_prob: 1.2746 loss_thr: 0.5941 loss_db: 0.1948 2022/10/26 00:58:05 - mmengine - INFO - Epoch(train) [366][50/63] lr: 2.5501e-03 eta: 12:55:36 time: 0.9879 data_time: 0.0241 memory: 16131 loss: 2.0053 loss_prob: 1.2211 loss_thr: 0.5968 loss_db: 0.1874 2022/10/26 00:58:09 - mmengine - INFO - Epoch(train) [366][55/63] lr: 2.5501e-03 eta: 12:55:36 time: 0.8107 data_time: 0.0225 memory: 16131 loss: 1.8495 loss_prob: 1.0812 loss_thr: 0.5932 loss_db: 0.1751 2022/10/26 00:58:11 - mmengine - INFO - Epoch(train) [366][60/63] lr: 2.5501e-03 eta: 12:55:21 time: 0.6215 data_time: 0.0057 memory: 16131 loss: 1.8558 loss_prob: 1.0840 loss_thr: 0.5965 loss_db: 0.1753 2022/10/26 00:58:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:58:21 - mmengine - INFO - Epoch(train) [367][5/63] lr: 2.5474e-03 eta: 12:55:21 time: 1.0361 data_time: 0.2259 memory: 16131 loss: 1.6661 loss_prob: 0.9518 loss_thr: 0.5571 loss_db: 0.1572 2022/10/26 00:58:25 - mmengine - INFO - Epoch(train) [367][10/63] lr: 2.5474e-03 eta: 12:55:09 time: 1.0888 data_time: 0.2248 memory: 16131 loss: 1.7106 loss_prob: 0.9896 loss_thr: 0.5560 loss_db: 0.1650 2022/10/26 00:58:28 - mmengine - INFO - Epoch(train) [367][15/63] lr: 2.5474e-03 eta: 12:55:09 time: 0.6956 data_time: 0.0061 memory: 16131 loss: 1.7955 loss_prob: 1.0497 loss_thr: 0.5714 loss_db: 0.1744 2022/10/26 00:58:30 - mmengine - INFO - Epoch(train) [367][20/63] lr: 2.5474e-03 eta: 12:54:52 time: 0.5450 data_time: 0.0050 memory: 16131 loss: 1.6909 loss_prob: 0.9603 loss_thr: 0.5746 loss_db: 0.1560 2022/10/26 00:58:34 - mmengine - INFO - Epoch(train) [367][25/63] lr: 2.5474e-03 eta: 12:54:52 time: 0.6649 data_time: 0.0252 memory: 16131 loss: 1.5828 loss_prob: 0.8773 loss_thr: 0.5617 loss_db: 0.1437 2022/10/26 00:58:37 - mmengine - INFO - Epoch(train) [367][30/63] lr: 2.5474e-03 eta: 12:54:39 time: 0.7051 data_time: 0.0371 memory: 16131 loss: 1.6446 loss_prob: 0.9345 loss_thr: 0.5543 loss_db: 0.1558 2022/10/26 00:58:42 - mmengine - INFO - Epoch(train) [367][35/63] lr: 2.5474e-03 eta: 12:54:39 time: 0.7227 data_time: 0.0183 memory: 16131 loss: 1.7032 loss_prob: 0.9739 loss_thr: 0.5693 loss_db: 0.1600 2022/10/26 00:58:45 - mmengine - INFO - Epoch(train) [367][40/63] lr: 2.5474e-03 eta: 12:54:27 time: 0.7438 data_time: 0.0073 memory: 16131 loss: 1.6967 loss_prob: 0.9579 loss_thr: 0.5835 loss_db: 0.1553 2022/10/26 00:58:48 - mmengine - INFO - Epoch(train) [367][45/63] lr: 2.5474e-03 eta: 12:54:27 time: 0.6308 data_time: 0.0060 memory: 16131 loss: 1.7148 loss_prob: 0.9838 loss_thr: 0.5679 loss_db: 0.1630 2022/10/26 00:58:51 - mmengine - INFO - Epoch(train) [367][50/63] lr: 2.5474e-03 eta: 12:54:11 time: 0.5945 data_time: 0.0217 memory: 16131 loss: 1.7069 loss_prob: 0.9918 loss_thr: 0.5502 loss_db: 0.1649 2022/10/26 00:58:56 - mmengine - INFO - Epoch(train) [367][55/63] lr: 2.5474e-03 eta: 12:54:11 time: 0.7814 data_time: 0.0225 memory: 16131 loss: 1.6984 loss_prob: 0.9795 loss_thr: 0.5578 loss_db: 0.1612 2022/10/26 00:59:00 - mmengine - INFO - Epoch(train) [367][60/63] lr: 2.5474e-03 eta: 12:54:04 time: 0.9285 data_time: 0.0083 memory: 16131 loss: 1.6771 loss_prob: 0.9644 loss_thr: 0.5545 loss_db: 0.1582 2022/10/26 00:59:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:59:07 - mmengine - INFO - Epoch(train) [368][5/63] lr: 2.5446e-03 eta: 12:54:04 time: 0.8463 data_time: 0.1729 memory: 16131 loss: 1.6992 loss_prob: 0.9809 loss_thr: 0.5577 loss_db: 0.1606 2022/10/26 00:59:10 - mmengine - INFO - Epoch(train) [368][10/63] lr: 2.5446e-03 eta: 12:53:45 time: 0.8355 data_time: 0.1747 memory: 16131 loss: 1.6782 loss_prob: 0.9626 loss_thr: 0.5607 loss_db: 0.1550 2022/10/26 00:59:13 - mmengine - INFO - Epoch(train) [368][15/63] lr: 2.5446e-03 eta: 12:53:45 time: 0.5572 data_time: 0.0090 memory: 16131 loss: 1.6961 loss_prob: 0.9685 loss_thr: 0.5727 loss_db: 0.1549 2022/10/26 00:59:15 - mmengine - INFO - Epoch(train) [368][20/63] lr: 2.5446e-03 eta: 12:53:29 time: 0.5519 data_time: 0.0079 memory: 16131 loss: 1.6546 loss_prob: 0.9311 loss_thr: 0.5708 loss_db: 0.1527 2022/10/26 00:59:18 - mmengine - INFO - Epoch(train) [368][25/63] lr: 2.5446e-03 eta: 12:53:29 time: 0.5361 data_time: 0.0104 memory: 16131 loss: 1.6075 loss_prob: 0.8976 loss_thr: 0.5596 loss_db: 0.1503 2022/10/26 00:59:21 - mmengine - INFO - Epoch(train) [368][30/63] lr: 2.5446e-03 eta: 12:53:13 time: 0.5702 data_time: 0.0393 memory: 16131 loss: 1.8751 loss_prob: 1.1246 loss_thr: 0.5748 loss_db: 0.1756 2022/10/26 00:59:24 - mmengine - INFO - Epoch(train) [368][35/63] lr: 2.5446e-03 eta: 12:53:13 time: 0.5833 data_time: 0.0348 memory: 16131 loss: 1.8256 loss_prob: 1.0911 loss_thr: 0.5652 loss_db: 0.1693 2022/10/26 00:59:28 - mmengine - INFO - Epoch(train) [368][40/63] lr: 2.5446e-03 eta: 12:52:59 time: 0.6894 data_time: 0.0051 memory: 16131 loss: 1.5690 loss_prob: 0.8805 loss_thr: 0.5403 loss_db: 0.1482 2022/10/26 00:59:32 - mmengine - INFO - Epoch(train) [368][45/63] lr: 2.5446e-03 eta: 12:52:59 time: 0.8279 data_time: 0.0061 memory: 16131 loss: 1.7717 loss_prob: 1.0208 loss_thr: 0.5807 loss_db: 0.1702 2022/10/26 00:59:38 - mmengine - INFO - Epoch(train) [368][50/63] lr: 2.5446e-03 eta: 12:52:53 time: 0.9869 data_time: 0.0246 memory: 16131 loss: 1.8042 loss_prob: 1.0436 loss_thr: 0.5848 loss_db: 0.1759 2022/10/26 00:59:44 - mmengine - INFO - Epoch(train) [368][55/63] lr: 2.5446e-03 eta: 12:52:53 time: 1.2243 data_time: 0.0238 memory: 16131 loss: 1.6681 loss_prob: 0.9500 loss_thr: 0.5599 loss_db: 0.1582 2022/10/26 00:59:48 - mmengine - INFO - Epoch(train) [368][60/63] lr: 2.5446e-03 eta: 12:52:48 time: 1.0634 data_time: 0.0055 memory: 16131 loss: 1.7181 loss_prob: 0.9855 loss_thr: 0.5726 loss_db: 0.1601 2022/10/26 00:59:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 00:59:57 - mmengine - INFO - Epoch(train) [369][5/63] lr: 2.5419e-03 eta: 12:52:48 time: 0.9770 data_time: 0.1988 memory: 16131 loss: 1.7170 loss_prob: 0.9743 loss_thr: 0.5850 loss_db: 0.1577 2022/10/26 01:00:00 - mmengine - INFO - Epoch(train) [369][10/63] lr: 2.5419e-03 eta: 12:52:31 time: 0.9167 data_time: 0.2008 memory: 16131 loss: 1.6636 loss_prob: 0.9276 loss_thr: 0.5841 loss_db: 0.1519 2022/10/26 01:00:04 - mmengine - INFO - Epoch(train) [369][15/63] lr: 2.5419e-03 eta: 12:52:31 time: 0.6946 data_time: 0.0098 memory: 16131 loss: 1.5700 loss_prob: 0.8846 loss_thr: 0.5390 loss_db: 0.1463 2022/10/26 01:00:06 - mmengine - INFO - Epoch(train) [369][20/63] lr: 2.5419e-03 eta: 12:52:17 time: 0.6255 data_time: 0.0075 memory: 16131 loss: 1.5638 loss_prob: 0.8888 loss_thr: 0.5287 loss_db: 0.1463 2022/10/26 01:00:09 - mmengine - INFO - Epoch(train) [369][25/63] lr: 2.5419e-03 eta: 12:52:17 time: 0.5436 data_time: 0.0277 memory: 16131 loss: 1.5991 loss_prob: 0.9051 loss_thr: 0.5444 loss_db: 0.1496 2022/10/26 01:00:12 - mmengine - INFO - Epoch(train) [369][30/63] lr: 2.5419e-03 eta: 12:52:00 time: 0.5375 data_time: 0.0377 memory: 16131 loss: 1.7325 loss_prob: 1.0096 loss_thr: 0.5583 loss_db: 0.1646 2022/10/26 01:00:17 - mmengine - INFO - Epoch(train) [369][35/63] lr: 2.5419e-03 eta: 12:52:00 time: 0.7700 data_time: 0.0187 memory: 16131 loss: 1.9171 loss_prob: 1.1400 loss_thr: 0.5964 loss_db: 0.1808 2022/10/26 01:00:22 - mmengine - INFO - Epoch(train) [369][40/63] lr: 2.5419e-03 eta: 12:51:56 time: 1.0859 data_time: 0.0133 memory: 16131 loss: 1.7893 loss_prob: 1.0340 loss_thr: 0.5897 loss_db: 0.1655 2022/10/26 01:00:25 - mmengine - INFO - Epoch(train) [369][45/63] lr: 2.5419e-03 eta: 12:51:56 time: 0.8621 data_time: 0.0105 memory: 16131 loss: 1.6892 loss_prob: 0.9664 loss_thr: 0.5626 loss_db: 0.1603 2022/10/26 01:00:30 - mmengine - INFO - Epoch(train) [369][50/63] lr: 2.5419e-03 eta: 12:51:43 time: 0.7190 data_time: 0.0225 memory: 16131 loss: 1.7690 loss_prob: 1.0139 loss_thr: 0.5894 loss_db: 0.1658 2022/10/26 01:00:32 - mmengine - INFO - Epoch(train) [369][55/63] lr: 2.5419e-03 eta: 12:51:43 time: 0.7221 data_time: 0.0240 memory: 16131 loss: 1.9083 loss_prob: 1.1146 loss_thr: 0.6103 loss_db: 0.1835 2022/10/26 01:00:35 - mmengine - INFO - Epoch(train) [369][60/63] lr: 2.5419e-03 eta: 12:51:27 time: 0.5629 data_time: 0.0089 memory: 16131 loss: 1.9473 loss_prob: 1.1551 loss_thr: 0.5974 loss_db: 0.1948 2022/10/26 01:00:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:00:42 - mmengine - INFO - Epoch(train) [370][5/63] lr: 2.5391e-03 eta: 12:51:27 time: 0.8116 data_time: 0.1509 memory: 16131 loss: 1.7992 loss_prob: 1.0558 loss_thr: 0.5741 loss_db: 0.1692 2022/10/26 01:00:46 - mmengine - INFO - Epoch(train) [370][10/63] lr: 2.5391e-03 eta: 12:51:11 time: 0.9345 data_time: 0.1720 memory: 16131 loss: 1.7814 loss_prob: 1.0418 loss_thr: 0.5653 loss_db: 0.1743 2022/10/26 01:00:51 - mmengine - INFO - Epoch(train) [370][15/63] lr: 2.5391e-03 eta: 12:51:11 time: 0.8929 data_time: 0.0271 memory: 16131 loss: 1.7255 loss_prob: 0.9922 loss_thr: 0.5658 loss_db: 0.1676 2022/10/26 01:00:54 - mmengine - INFO - Epoch(train) [370][20/63] lr: 2.5391e-03 eta: 12:51:00 time: 0.8051 data_time: 0.0055 memory: 16131 loss: 1.7175 loss_prob: 0.9917 loss_thr: 0.5687 loss_db: 0.1571 2022/10/26 01:00:57 - mmengine - INFO - Epoch(train) [370][25/63] lr: 2.5391e-03 eta: 12:51:00 time: 0.5522 data_time: 0.0126 memory: 16131 loss: 1.9066 loss_prob: 1.1316 loss_thr: 0.5948 loss_db: 0.1802 2022/10/26 01:00:59 - mmengine - INFO - Epoch(train) [370][30/63] lr: 2.5391e-03 eta: 12:50:43 time: 0.5416 data_time: 0.0289 memory: 16131 loss: 1.9290 loss_prob: 1.1487 loss_thr: 0.5904 loss_db: 0.1899 2022/10/26 01:01:02 - mmengine - INFO - Epoch(train) [370][35/63] lr: 2.5391e-03 eta: 12:50:43 time: 0.5782 data_time: 0.0312 memory: 16131 loss: 1.8386 loss_prob: 1.0817 loss_thr: 0.5767 loss_db: 0.1802 2022/10/26 01:01:05 - mmengine - INFO - Epoch(train) [370][40/63] lr: 2.5391e-03 eta: 12:50:28 time: 0.5902 data_time: 0.0162 memory: 16131 loss: 2.0256 loss_prob: 1.2211 loss_thr: 0.6088 loss_db: 0.1957 2022/10/26 01:01:11 - mmengine - INFO - Epoch(train) [370][45/63] lr: 2.5391e-03 eta: 12:50:28 time: 0.8227 data_time: 0.0093 memory: 16131 loss: 2.0367 loss_prob: 1.2352 loss_thr: 0.6029 loss_db: 0.1986 2022/10/26 01:01:15 - mmengine - INFO - Epoch(train) [370][50/63] lr: 2.5391e-03 eta: 12:50:20 time: 0.9382 data_time: 0.0179 memory: 16131 loss: 1.9042 loss_prob: 1.1321 loss_thr: 0.5816 loss_db: 0.1906 2022/10/26 01:01:20 - mmengine - INFO - Epoch(train) [370][55/63] lr: 2.5391e-03 eta: 12:50:20 time: 0.9545 data_time: 0.0208 memory: 16131 loss: 2.0087 loss_prob: 1.2010 loss_thr: 0.6082 loss_db: 0.1995 2022/10/26 01:01:23 - mmengine - INFO - Epoch(train) [370][60/63] lr: 2.5391e-03 eta: 12:50:11 time: 0.8489 data_time: 0.0143 memory: 16131 loss: 2.0808 loss_prob: 1.2637 loss_thr: 0.6141 loss_db: 0.2029 2022/10/26 01:01:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:01:31 - mmengine - INFO - Epoch(train) [371][5/63] lr: 2.5364e-03 eta: 12:50:11 time: 0.9068 data_time: 0.2070 memory: 16131 loss: 1.9162 loss_prob: 1.1268 loss_thr: 0.6064 loss_db: 0.1830 2022/10/26 01:01:36 - mmengine - INFO - Epoch(train) [371][10/63] lr: 2.5364e-03 eta: 12:49:59 time: 1.1173 data_time: 0.2077 memory: 16131 loss: 1.9330 loss_prob: 1.1354 loss_thr: 0.6164 loss_db: 0.1811 2022/10/26 01:01:42 - mmengine - INFO - Epoch(train) [371][15/63] lr: 2.5364e-03 eta: 12:49:59 time: 1.0669 data_time: 0.0114 memory: 16131 loss: 1.9492 loss_prob: 1.1534 loss_thr: 0.6095 loss_db: 0.1862 2022/10/26 01:01:45 - mmengine - INFO - Epoch(train) [371][20/63] lr: 2.5364e-03 eta: 12:49:50 time: 0.8912 data_time: 0.0134 memory: 16131 loss: 1.7244 loss_prob: 0.9887 loss_thr: 0.5742 loss_db: 0.1616 2022/10/26 01:01:48 - mmengine - INFO - Epoch(train) [371][25/63] lr: 2.5364e-03 eta: 12:49:50 time: 0.6586 data_time: 0.0171 memory: 16131 loss: 1.8889 loss_prob: 1.1250 loss_thr: 0.5826 loss_db: 0.1813 2022/10/26 01:01:53 - mmengine - INFO - Epoch(train) [371][30/63] lr: 2.5364e-03 eta: 12:49:39 time: 0.7922 data_time: 0.0363 memory: 16131 loss: 1.9214 loss_prob: 1.1444 loss_thr: 0.5869 loss_db: 0.1902 2022/10/26 01:01:56 - mmengine - INFO - Epoch(train) [371][35/63] lr: 2.5364e-03 eta: 12:49:39 time: 0.7979 data_time: 0.0321 memory: 16131 loss: 1.7867 loss_prob: 1.0396 loss_thr: 0.5721 loss_db: 0.1750 2022/10/26 01:02:00 - mmengine - INFO - Epoch(train) [371][40/63] lr: 2.5364e-03 eta: 12:49:27 time: 0.7215 data_time: 0.0093 memory: 16131 loss: 1.8426 loss_prob: 1.0908 loss_thr: 0.5767 loss_db: 0.1750 2022/10/26 01:02:04 - mmengine - INFO - Epoch(train) [371][45/63] lr: 2.5364e-03 eta: 12:49:27 time: 0.7505 data_time: 0.0078 memory: 16131 loss: 1.7033 loss_prob: 0.9898 loss_thr: 0.5545 loss_db: 0.1590 2022/10/26 01:02:07 - mmengine - INFO - Epoch(train) [371][50/63] lr: 2.5364e-03 eta: 12:49:13 time: 0.6795 data_time: 0.0164 memory: 16131 loss: 1.6581 loss_prob: 0.9596 loss_thr: 0.5391 loss_db: 0.1594 2022/10/26 01:02:11 - mmengine - INFO - Epoch(train) [371][55/63] lr: 2.5364e-03 eta: 12:49:13 time: 0.7090 data_time: 0.0290 memory: 16131 loss: 1.7368 loss_prob: 1.0138 loss_thr: 0.5557 loss_db: 0.1673 2022/10/26 01:02:15 - mmengine - INFO - Epoch(train) [371][60/63] lr: 2.5364e-03 eta: 12:49:03 time: 0.8051 data_time: 0.0236 memory: 16131 loss: 1.7173 loss_prob: 0.9897 loss_thr: 0.5635 loss_db: 0.1641 2022/10/26 01:02:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:02:24 - mmengine - INFO - Epoch(train) [372][5/63] lr: 2.5336e-03 eta: 12:49:03 time: 1.1680 data_time: 0.2041 memory: 16131 loss: 1.6742 loss_prob: 0.9557 loss_thr: 0.5567 loss_db: 0.1617 2022/10/26 01:02:28 - mmengine - INFO - Epoch(train) [372][10/63] lr: 2.5336e-03 eta: 12:48:50 time: 1.1151 data_time: 0.2015 memory: 16131 loss: 1.6781 loss_prob: 0.9576 loss_thr: 0.5633 loss_db: 0.1572 2022/10/26 01:02:33 - mmengine - INFO - Epoch(train) [372][15/63] lr: 2.5336e-03 eta: 12:48:50 time: 0.8399 data_time: 0.0084 memory: 16131 loss: 1.8125 loss_prob: 1.0554 loss_thr: 0.5842 loss_db: 0.1729 2022/10/26 01:02:35 - mmengine - INFO - Epoch(train) [372][20/63] lr: 2.5336e-03 eta: 12:48:37 time: 0.6989 data_time: 0.0095 memory: 16131 loss: 1.8022 loss_prob: 1.0574 loss_thr: 0.5660 loss_db: 0.1788 2022/10/26 01:02:40 - mmengine - INFO - Epoch(train) [372][25/63] lr: 2.5336e-03 eta: 12:48:37 time: 0.7092 data_time: 0.0354 memory: 16131 loss: 1.7140 loss_prob: 0.9870 loss_thr: 0.5573 loss_db: 0.1697 2022/10/26 01:02:43 - mmengine - INFO - Epoch(train) [372][30/63] lr: 2.5336e-03 eta: 12:48:26 time: 0.7567 data_time: 0.0343 memory: 16131 loss: 1.7733 loss_prob: 1.0164 loss_thr: 0.5842 loss_db: 0.1728 2022/10/26 01:02:46 - mmengine - INFO - Epoch(train) [372][35/63] lr: 2.5336e-03 eta: 12:48:26 time: 0.6174 data_time: 0.0064 memory: 16131 loss: 1.8904 loss_prob: 1.0982 loss_thr: 0.6075 loss_db: 0.1846 2022/10/26 01:02:49 - mmengine - INFO - Epoch(train) [372][40/63] lr: 2.5336e-03 eta: 12:48:10 time: 0.5880 data_time: 0.0061 memory: 16131 loss: 1.7993 loss_prob: 1.0340 loss_thr: 0.5933 loss_db: 0.1720 2022/10/26 01:02:52 - mmengine - INFO - Epoch(train) [372][45/63] lr: 2.5336e-03 eta: 12:48:10 time: 0.5791 data_time: 0.0049 memory: 16131 loss: 1.6399 loss_prob: 0.9213 loss_thr: 0.5682 loss_db: 0.1505 2022/10/26 01:02:57 - mmengine - INFO - Epoch(train) [372][50/63] lr: 2.5336e-03 eta: 12:48:01 time: 0.8448 data_time: 0.0660 memory: 16131 loss: 1.6876 loss_prob: 0.9599 loss_thr: 0.5679 loss_db: 0.1599 2022/10/26 01:03:02 - mmengine - INFO - Epoch(train) [372][55/63] lr: 2.5336e-03 eta: 12:48:01 time: 1.0209 data_time: 0.0666 memory: 16131 loss: 1.6253 loss_prob: 0.9233 loss_thr: 0.5457 loss_db: 0.1563 2022/10/26 01:03:07 - mmengine - INFO - Epoch(train) [372][60/63] lr: 2.5336e-03 eta: 12:47:53 time: 0.9438 data_time: 0.0078 memory: 16131 loss: 1.6093 loss_prob: 0.9116 loss_thr: 0.5479 loss_db: 0.1497 2022/10/26 01:03:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:03:17 - mmengine - INFO - Epoch(train) [373][5/63] lr: 2.5309e-03 eta: 12:47:53 time: 1.1327 data_time: 0.1589 memory: 16131 loss: 1.5803 loss_prob: 0.8843 loss_thr: 0.5483 loss_db: 0.1476 2022/10/26 01:03:23 - mmengine - INFO - Epoch(train) [373][10/63] lr: 2.5309e-03 eta: 12:47:47 time: 1.4030 data_time: 0.1683 memory: 16131 loss: 1.6201 loss_prob: 0.9165 loss_thr: 0.5489 loss_db: 0.1546 2022/10/26 01:03:28 - mmengine - INFO - Epoch(train) [373][15/63] lr: 2.5309e-03 eta: 12:47:47 time: 1.1219 data_time: 0.0222 memory: 16131 loss: 1.6595 loss_prob: 0.9410 loss_thr: 0.5600 loss_db: 0.1585 2022/10/26 01:03:31 - mmengine - INFO - Epoch(train) [373][20/63] lr: 2.5309e-03 eta: 12:47:38 time: 0.8497 data_time: 0.0081 memory: 16131 loss: 1.7460 loss_prob: 1.0133 loss_thr: 0.5639 loss_db: 0.1688 2022/10/26 01:03:34 - mmengine - INFO - Epoch(train) [373][25/63] lr: 2.5309e-03 eta: 12:47:38 time: 0.5999 data_time: 0.0094 memory: 16131 loss: 1.7675 loss_prob: 1.0335 loss_thr: 0.5621 loss_db: 0.1720 2022/10/26 01:03:37 - mmengine - INFO - Epoch(train) [373][30/63] lr: 2.5309e-03 eta: 12:47:22 time: 0.5520 data_time: 0.0221 memory: 16131 loss: 1.7915 loss_prob: 1.0548 loss_thr: 0.5672 loss_db: 0.1694 2022/10/26 01:03:41 - mmengine - INFO - Epoch(train) [373][35/63] lr: 2.5309e-03 eta: 12:47:22 time: 0.6917 data_time: 0.0314 memory: 16131 loss: 1.7993 loss_prob: 1.0648 loss_thr: 0.5618 loss_db: 0.1727 2022/10/26 01:03:44 - mmengine - INFO - Epoch(train) [373][40/63] lr: 2.5309e-03 eta: 12:47:09 time: 0.7180 data_time: 0.0205 memory: 16131 loss: 1.7440 loss_prob: 1.0075 loss_thr: 0.5673 loss_db: 0.1691 2022/10/26 01:03:47 - mmengine - INFO - Epoch(train) [373][45/63] lr: 2.5309e-03 eta: 12:47:09 time: 0.6450 data_time: 0.0064 memory: 16131 loss: 1.6593 loss_prob: 0.9397 loss_thr: 0.5633 loss_db: 0.1562 2022/10/26 01:03:53 - mmengine - INFO - Epoch(train) [373][50/63] lr: 2.5309e-03 eta: 12:47:00 time: 0.8517 data_time: 0.0087 memory: 16131 loss: 1.6923 loss_prob: 0.9654 loss_thr: 0.5661 loss_db: 0.1608 2022/10/26 01:03:57 - mmengine - INFO - Epoch(train) [373][55/63] lr: 2.5309e-03 eta: 12:47:00 time: 0.9661 data_time: 0.0182 memory: 16131 loss: 1.6966 loss_prob: 0.9777 loss_thr: 0.5557 loss_db: 0.1632 2022/10/26 01:04:05 - mmengine - INFO - Epoch(train) [373][60/63] lr: 2.5309e-03 eta: 12:46:59 time: 1.2351 data_time: 0.0193 memory: 16131 loss: 1.6835 loss_prob: 0.9713 loss_thr: 0.5558 loss_db: 0.1564 2022/10/26 01:04:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:04:14 - mmengine - INFO - Epoch(train) [374][5/63] lr: 2.5281e-03 eta: 12:46:59 time: 1.1767 data_time: 0.1757 memory: 16131 loss: 1.6505 loss_prob: 0.9343 loss_thr: 0.5638 loss_db: 0.1523 2022/10/26 01:04:17 - mmengine - INFO - Epoch(train) [374][10/63] lr: 2.5281e-03 eta: 12:46:42 time: 0.9378 data_time: 0.1726 memory: 16131 loss: 1.7160 loss_prob: 0.9732 loss_thr: 0.5854 loss_db: 0.1574 2022/10/26 01:04:21 - mmengine - INFO - Epoch(train) [374][15/63] lr: 2.5281e-03 eta: 12:46:42 time: 0.7199 data_time: 0.0053 memory: 16131 loss: 1.7328 loss_prob: 0.9824 loss_thr: 0.5877 loss_db: 0.1626 2022/10/26 01:04:25 - mmengine - INFO - Epoch(train) [374][20/63] lr: 2.5281e-03 eta: 12:46:33 time: 0.8492 data_time: 0.0081 memory: 16131 loss: 1.7366 loss_prob: 0.9959 loss_thr: 0.5794 loss_db: 0.1613 2022/10/26 01:04:28 - mmengine - INFO - Epoch(train) [374][25/63] lr: 2.5281e-03 eta: 12:46:33 time: 0.7352 data_time: 0.0329 memory: 16131 loss: 1.7020 loss_prob: 0.9756 loss_thr: 0.5667 loss_db: 0.1597 2022/10/26 01:04:31 - mmengine - INFO - Epoch(train) [374][30/63] lr: 2.5281e-03 eta: 12:46:17 time: 0.5467 data_time: 0.0383 memory: 16131 loss: 1.6688 loss_prob: 0.9434 loss_thr: 0.5650 loss_db: 0.1603 2022/10/26 01:04:33 - mmengine - INFO - Epoch(train) [374][35/63] lr: 2.5281e-03 eta: 12:46:17 time: 0.5230 data_time: 0.0132 memory: 16131 loss: 1.8550 loss_prob: 1.1004 loss_thr: 0.5770 loss_db: 0.1777 2022/10/26 01:04:36 - mmengine - INFO - Epoch(train) [374][40/63] lr: 2.5281e-03 eta: 12:46:00 time: 0.5502 data_time: 0.0055 memory: 16131 loss: 1.7720 loss_prob: 1.0353 loss_thr: 0.5747 loss_db: 0.1619 2022/10/26 01:04:39 - mmengine - INFO - Epoch(train) [374][45/63] lr: 2.5281e-03 eta: 12:46:00 time: 0.5311 data_time: 0.0084 memory: 16131 loss: 1.6919 loss_prob: 0.9752 loss_thr: 0.5610 loss_db: 0.1556 2022/10/26 01:04:42 - mmengine - INFO - Epoch(train) [374][50/63] lr: 2.5281e-03 eta: 12:45:44 time: 0.5287 data_time: 0.0227 memory: 16131 loss: 1.7103 loss_prob: 1.0035 loss_thr: 0.5429 loss_db: 0.1640 2022/10/26 01:04:45 - mmengine - INFO - Epoch(train) [374][55/63] lr: 2.5281e-03 eta: 12:45:44 time: 0.6395 data_time: 0.0314 memory: 16131 loss: 1.5830 loss_prob: 0.8843 loss_thr: 0.5478 loss_db: 0.1508 2022/10/26 01:04:50 - mmengine - INFO - Epoch(train) [374][60/63] lr: 2.5281e-03 eta: 12:45:34 time: 0.8601 data_time: 0.0210 memory: 16131 loss: 1.6780 loss_prob: 0.9537 loss_thr: 0.5648 loss_db: 0.1595 2022/10/26 01:04:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:04:59 - mmengine - INFO - Epoch(train) [375][5/63] lr: 2.5254e-03 eta: 12:45:34 time: 1.0745 data_time: 0.1645 memory: 16131 loss: 1.8574 loss_prob: 1.0807 loss_thr: 0.6002 loss_db: 0.1765 2022/10/26 01:05:02 - mmengine - INFO - Epoch(train) [375][10/63] lr: 2.5254e-03 eta: 12:45:21 time: 1.0461 data_time: 0.1642 memory: 16131 loss: 1.6601 loss_prob: 0.9304 loss_thr: 0.5717 loss_db: 0.1579 2022/10/26 01:05:07 - mmengine - INFO - Epoch(train) [375][15/63] lr: 2.5254e-03 eta: 12:45:21 time: 0.8047 data_time: 0.0056 memory: 16131 loss: 1.6242 loss_prob: 0.9190 loss_thr: 0.5503 loss_db: 0.1549 2022/10/26 01:05:10 - mmengine - INFO - Epoch(train) [375][20/63] lr: 2.5254e-03 eta: 12:45:10 time: 0.7973 data_time: 0.0107 memory: 16131 loss: 1.5898 loss_prob: 0.8954 loss_thr: 0.5475 loss_db: 0.1469 2022/10/26 01:05:13 - mmengine - INFO - Epoch(train) [375][25/63] lr: 2.5254e-03 eta: 12:45:10 time: 0.5529 data_time: 0.0207 memory: 16131 loss: 1.7236 loss_prob: 0.9978 loss_thr: 0.5698 loss_db: 0.1560 2022/10/26 01:05:17 - mmengine - INFO - Epoch(train) [375][30/63] lr: 2.5254e-03 eta: 12:44:57 time: 0.6924 data_time: 0.0356 memory: 16131 loss: 1.8750 loss_prob: 1.1107 loss_thr: 0.5909 loss_db: 0.1734 2022/10/26 01:05:22 - mmengine - INFO - Epoch(train) [375][35/63] lr: 2.5254e-03 eta: 12:44:57 time: 0.9242 data_time: 0.0255 memory: 16131 loss: 1.6996 loss_prob: 0.9822 loss_thr: 0.5572 loss_db: 0.1602 2022/10/26 01:05:28 - mmengine - INFO - Epoch(train) [375][40/63] lr: 2.5254e-03 eta: 12:44:52 time: 1.0673 data_time: 0.0124 memory: 16131 loss: 1.6687 loss_prob: 0.9571 loss_thr: 0.5542 loss_db: 0.1574 2022/10/26 01:05:31 - mmengine - INFO - Epoch(train) [375][45/63] lr: 2.5254e-03 eta: 12:44:52 time: 0.8627 data_time: 0.0124 memory: 16131 loss: 1.7106 loss_prob: 0.9819 loss_thr: 0.5640 loss_db: 0.1648 2022/10/26 01:05:33 - mmengine - INFO - Epoch(train) [375][50/63] lr: 2.5254e-03 eta: 12:44:36 time: 0.5647 data_time: 0.0123 memory: 16131 loss: 1.6483 loss_prob: 0.9447 loss_thr: 0.5471 loss_db: 0.1565 2022/10/26 01:05:36 - mmengine - INFO - Epoch(train) [375][55/63] lr: 2.5254e-03 eta: 12:44:36 time: 0.5717 data_time: 0.0231 memory: 16131 loss: 1.6921 loss_prob: 0.9734 loss_thr: 0.5618 loss_db: 0.1569 2022/10/26 01:05:42 - mmengine - INFO - Epoch(train) [375][60/63] lr: 2.5254e-03 eta: 12:44:27 time: 0.8456 data_time: 0.0165 memory: 16131 loss: 1.6885 loss_prob: 0.9727 loss_thr: 0.5556 loss_db: 0.1603 2022/10/26 01:05:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:05:52 - mmengine - INFO - Epoch(train) [376][5/63] lr: 2.5226e-03 eta: 12:44:27 time: 1.4006 data_time: 0.2164 memory: 16131 loss: 1.7144 loss_prob: 0.9850 loss_thr: 0.5662 loss_db: 0.1632 2022/10/26 01:06:00 - mmengine - INFO - Epoch(train) [376][10/63] lr: 2.5226e-03 eta: 12:44:23 time: 1.5167 data_time: 0.2147 memory: 16131 loss: 1.6531 loss_prob: 0.9347 loss_thr: 0.5641 loss_db: 0.1544 2022/10/26 01:06:06 - mmengine - INFO - Epoch(train) [376][15/63] lr: 2.5226e-03 eta: 12:44:23 time: 1.3284 data_time: 0.0059 memory: 16131 loss: 1.6179 loss_prob: 0.9135 loss_thr: 0.5503 loss_db: 0.1541 2022/10/26 01:06:12 - mmengine - INFO - Epoch(train) [376][20/63] lr: 2.5226e-03 eta: 12:44:22 time: 1.2292 data_time: 0.0049 memory: 16131 loss: 1.6177 loss_prob: 0.9192 loss_thr: 0.5409 loss_db: 0.1576 2022/10/26 01:06:15 - mmengine - INFO - Epoch(train) [376][25/63] lr: 2.5226e-03 eta: 12:44:22 time: 0.8987 data_time: 0.0323 memory: 16131 loss: 1.7158 loss_prob: 0.9751 loss_thr: 0.5786 loss_db: 0.1621 2022/10/26 01:06:20 - mmengine - INFO - Epoch(train) [376][30/63] lr: 2.5226e-03 eta: 12:44:12 time: 0.8121 data_time: 0.0377 memory: 16131 loss: 1.7578 loss_prob: 1.0000 loss_thr: 0.5942 loss_db: 0.1636 2022/10/26 01:06:23 - mmengine - INFO - Epoch(train) [376][35/63] lr: 2.5226e-03 eta: 12:44:12 time: 0.7966 data_time: 0.0117 memory: 16131 loss: 1.6715 loss_prob: 0.9657 loss_thr: 0.5469 loss_db: 0.1589 2022/10/26 01:06:27 - mmengine - INFO - Epoch(train) [376][40/63] lr: 2.5226e-03 eta: 12:43:58 time: 0.6612 data_time: 0.0067 memory: 16131 loss: 1.6779 loss_prob: 0.9846 loss_thr: 0.5338 loss_db: 0.1594 2022/10/26 01:06:30 - mmengine - INFO - Epoch(train) [376][45/63] lr: 2.5226e-03 eta: 12:43:58 time: 0.7121 data_time: 0.0051 memory: 16131 loss: 1.7319 loss_prob: 1.0169 loss_thr: 0.5516 loss_db: 0.1634 2022/10/26 01:06:33 - mmengine - INFO - Epoch(train) [376][50/63] lr: 2.5226e-03 eta: 12:43:44 time: 0.6304 data_time: 0.0267 memory: 16131 loss: 1.7194 loss_prob: 0.9900 loss_thr: 0.5642 loss_db: 0.1652 2022/10/26 01:06:38 - mmengine - INFO - Epoch(train) [376][55/63] lr: 2.5226e-03 eta: 12:43:44 time: 0.8473 data_time: 0.0284 memory: 16131 loss: 1.7074 loss_prob: 0.9791 loss_thr: 0.5638 loss_db: 0.1644 2022/10/26 01:06:42 - mmengine - INFO - Epoch(train) [376][60/63] lr: 2.5226e-03 eta: 12:43:35 time: 0.9080 data_time: 0.0066 memory: 16131 loss: 1.6550 loss_prob: 0.9611 loss_thr: 0.5367 loss_db: 0.1573 2022/10/26 01:06:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:06:50 - mmengine - INFO - Epoch(train) [377][5/63] lr: 2.5199e-03 eta: 12:43:35 time: 0.8736 data_time: 0.2598 memory: 16131 loss: 1.5930 loss_prob: 0.9172 loss_thr: 0.5223 loss_db: 0.1535 2022/10/26 01:06:54 - mmengine - INFO - Epoch(train) [377][10/63] lr: 2.5199e-03 eta: 12:43:22 time: 1.0414 data_time: 0.2606 memory: 16131 loss: 1.4880 loss_prob: 0.8347 loss_thr: 0.5130 loss_db: 0.1403 2022/10/26 01:06:57 - mmengine - INFO - Epoch(train) [377][15/63] lr: 2.5199e-03 eta: 12:43:22 time: 0.7423 data_time: 0.0115 memory: 16131 loss: 1.5122 loss_prob: 0.8376 loss_thr: 0.5336 loss_db: 0.1410 2022/10/26 01:07:01 - mmengine - INFO - Epoch(train) [377][20/63] lr: 2.5199e-03 eta: 12:43:09 time: 0.6849 data_time: 0.0100 memory: 16131 loss: 1.8026 loss_prob: 1.0415 loss_thr: 0.5941 loss_db: 0.1670 2022/10/26 01:07:06 - mmengine - INFO - Epoch(train) [377][25/63] lr: 2.5199e-03 eta: 12:43:09 time: 0.8540 data_time: 0.0324 memory: 16131 loss: 1.8328 loss_prob: 1.0803 loss_thr: 0.5812 loss_db: 0.1713 2022/10/26 01:07:09 - mmengine - INFO - Epoch(train) [377][30/63] lr: 2.5199e-03 eta: 12:42:59 time: 0.8579 data_time: 0.0498 memory: 16131 loss: 1.7398 loss_prob: 1.0012 loss_thr: 0.5750 loss_db: 0.1636 2022/10/26 01:07:15 - mmengine - INFO - Epoch(train) [377][35/63] lr: 2.5199e-03 eta: 12:42:59 time: 0.9085 data_time: 0.0217 memory: 16131 loss: 1.7026 loss_prob: 0.9737 loss_thr: 0.5703 loss_db: 0.1585 2022/10/26 01:07:19 - mmengine - INFO - Epoch(train) [377][40/63] lr: 2.5199e-03 eta: 12:42:53 time: 1.0218 data_time: 0.0045 memory: 16131 loss: 1.6480 loss_prob: 0.9380 loss_thr: 0.5590 loss_db: 0.1509 2022/10/26 01:07:23 - mmengine - INFO - Epoch(train) [377][45/63] lr: 2.5199e-03 eta: 12:42:53 time: 0.8592 data_time: 0.0052 memory: 16131 loss: 1.7270 loss_prob: 0.9911 loss_thr: 0.5744 loss_db: 0.1616 2022/10/26 01:07:28 - mmengine - INFO - Epoch(train) [377][50/63] lr: 2.5199e-03 eta: 12:42:43 time: 0.8196 data_time: 0.0235 memory: 16131 loss: 1.6463 loss_prob: 0.9298 loss_thr: 0.5596 loss_db: 0.1569 2022/10/26 01:07:32 - mmengine - INFO - Epoch(train) [377][55/63] lr: 2.5199e-03 eta: 12:42:43 time: 0.8102 data_time: 0.0234 memory: 16131 loss: 1.8486 loss_prob: 1.0899 loss_thr: 0.5896 loss_db: 0.1691 2022/10/26 01:07:35 - mmengine - INFO - Epoch(train) [377][60/63] lr: 2.5199e-03 eta: 12:42:30 time: 0.6843 data_time: 0.0046 memory: 16131 loss: 1.9395 loss_prob: 1.1668 loss_thr: 0.5923 loss_db: 0.1803 2022/10/26 01:07:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:07:43 - mmengine - INFO - Epoch(train) [378][5/63] lr: 2.5171e-03 eta: 12:42:30 time: 1.0110 data_time: 0.1964 memory: 16131 loss: 1.5762 loss_prob: 0.8909 loss_thr: 0.5402 loss_db: 0.1450 2022/10/26 01:07:46 - mmengine - INFO - Epoch(train) [378][10/63] lr: 2.5171e-03 eta: 12:42:14 time: 0.9604 data_time: 0.1958 memory: 16131 loss: 1.6056 loss_prob: 0.9008 loss_thr: 0.5575 loss_db: 0.1474 2022/10/26 01:07:49 - mmengine - INFO - Epoch(train) [378][15/63] lr: 2.5171e-03 eta: 12:42:14 time: 0.6183 data_time: 0.0088 memory: 16131 loss: 1.5632 loss_prob: 0.8645 loss_thr: 0.5539 loss_db: 0.1448 2022/10/26 01:07:52 - mmengine - INFO - Epoch(train) [378][20/63] lr: 2.5171e-03 eta: 12:41:59 time: 0.5747 data_time: 0.0080 memory: 16131 loss: 1.6178 loss_prob: 0.9104 loss_thr: 0.5564 loss_db: 0.1510 2022/10/26 01:07:55 - mmengine - INFO - Epoch(train) [378][25/63] lr: 2.5171e-03 eta: 12:41:59 time: 0.5941 data_time: 0.0407 memory: 16131 loss: 1.6724 loss_prob: 0.9478 loss_thr: 0.5699 loss_db: 0.1546 2022/10/26 01:07:58 - mmengine - INFO - Epoch(train) [378][30/63] lr: 2.5171e-03 eta: 12:41:45 time: 0.6268 data_time: 0.0475 memory: 16131 loss: 1.6481 loss_prob: 0.9264 loss_thr: 0.5669 loss_db: 0.1548 2022/10/26 01:08:03 - mmengine - INFO - Epoch(train) [378][35/63] lr: 2.5171e-03 eta: 12:41:45 time: 0.7681 data_time: 0.0132 memory: 16131 loss: 1.7117 loss_prob: 0.9814 loss_thr: 0.5709 loss_db: 0.1593 2022/10/26 01:08:09 - mmengine - INFO - Epoch(train) [378][40/63] lr: 2.5171e-03 eta: 12:41:40 time: 1.0583 data_time: 0.0109 memory: 16131 loss: 1.6671 loss_prob: 0.9614 loss_thr: 0.5514 loss_db: 0.1543 2022/10/26 01:08:12 - mmengine - INFO - Epoch(train) [378][45/63] lr: 2.5171e-03 eta: 12:41:40 time: 0.9151 data_time: 0.0109 memory: 16131 loss: 1.6374 loss_prob: 0.9296 loss_thr: 0.5525 loss_db: 0.1553 2022/10/26 01:08:15 - mmengine - INFO - Epoch(train) [378][50/63] lr: 2.5171e-03 eta: 12:41:26 time: 0.6496 data_time: 0.0245 memory: 16131 loss: 1.6634 loss_prob: 0.9392 loss_thr: 0.5685 loss_db: 0.1556 2022/10/26 01:08:18 - mmengine - INFO - Epoch(train) [378][55/63] lr: 2.5171e-03 eta: 12:41:26 time: 0.5818 data_time: 0.0264 memory: 16131 loss: 1.7297 loss_prob: 1.0141 loss_thr: 0.5579 loss_db: 0.1577 2022/10/26 01:08:23 - mmengine - INFO - Epoch(train) [378][60/63] lr: 2.5171e-03 eta: 12:41:16 time: 0.8264 data_time: 0.0120 memory: 16131 loss: 1.8873 loss_prob: 1.1639 loss_thr: 0.5498 loss_db: 0.1736 2022/10/26 01:08:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:08:32 - mmengine - INFO - Epoch(train) [379][5/63] lr: 2.5143e-03 eta: 12:41:16 time: 1.0859 data_time: 0.2247 memory: 16131 loss: 1.7078 loss_prob: 1.0040 loss_thr: 0.5411 loss_db: 0.1628 2022/10/26 01:08:37 - mmengine - INFO - Epoch(train) [379][10/63] lr: 2.5143e-03 eta: 12:41:06 time: 1.2059 data_time: 0.2420 memory: 16131 loss: 1.6796 loss_prob: 0.9739 loss_thr: 0.5455 loss_db: 0.1601 2022/10/26 01:08:40 - mmengine - INFO - Epoch(train) [379][15/63] lr: 2.5143e-03 eta: 12:41:06 time: 0.7923 data_time: 0.0251 memory: 16131 loss: 1.7784 loss_prob: 1.0310 loss_thr: 0.5798 loss_db: 0.1676 2022/10/26 01:08:45 - mmengine - INFO - Epoch(train) [379][20/63] lr: 2.5143e-03 eta: 12:40:56 time: 0.8664 data_time: 0.0067 memory: 16131 loss: 1.8184 loss_prob: 1.0592 loss_thr: 0.5855 loss_db: 0.1737 2022/10/26 01:08:50 - mmengine - INFO - Epoch(train) [379][25/63] lr: 2.5143e-03 eta: 12:40:56 time: 0.9680 data_time: 0.0419 memory: 16131 loss: 1.7521 loss_prob: 1.0175 loss_thr: 0.5691 loss_db: 0.1654 2022/10/26 01:08:54 - mmengine - INFO - Epoch(train) [379][30/63] lr: 2.5143e-03 eta: 12:40:48 time: 0.8983 data_time: 0.0444 memory: 16131 loss: 1.7809 loss_prob: 1.0460 loss_thr: 0.5670 loss_db: 0.1679 2022/10/26 01:08:58 - mmengine - INFO - Epoch(train) [379][35/63] lr: 2.5143e-03 eta: 12:40:48 time: 0.8229 data_time: 0.0083 memory: 16131 loss: 1.7941 loss_prob: 1.0420 loss_thr: 0.5799 loss_db: 0.1723 2022/10/26 01:09:02 - mmengine - INFO - Epoch(train) [379][40/63] lr: 2.5143e-03 eta: 12:40:37 time: 0.7812 data_time: 0.0051 memory: 16131 loss: 1.7907 loss_prob: 1.0309 loss_thr: 0.5907 loss_db: 0.1692 2022/10/26 01:09:06 - mmengine - INFO - Epoch(train) [379][45/63] lr: 2.5143e-03 eta: 12:40:37 time: 0.7336 data_time: 0.0080 memory: 16131 loss: 1.7797 loss_prob: 1.0182 loss_thr: 0.5927 loss_db: 0.1688 2022/10/26 01:09:10 - mmengine - INFO - Epoch(train) [379][50/63] lr: 2.5143e-03 eta: 12:40:26 time: 0.8064 data_time: 0.0248 memory: 16131 loss: 1.7837 loss_prob: 1.0241 loss_thr: 0.5889 loss_db: 0.1708 2022/10/26 01:09:14 - mmengine - INFO - Epoch(train) [379][55/63] lr: 2.5143e-03 eta: 12:40:26 time: 0.8480 data_time: 0.0240 memory: 16131 loss: 1.8134 loss_prob: 1.0617 loss_thr: 0.5793 loss_db: 0.1724 2022/10/26 01:09:17 - mmengine - INFO - Epoch(train) [379][60/63] lr: 2.5143e-03 eta: 12:40:12 time: 0.6303 data_time: 0.0068 memory: 16131 loss: 1.9051 loss_prob: 1.1407 loss_thr: 0.5875 loss_db: 0.1768 2022/10/26 01:09:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:09:23 - mmengine - INFO - Epoch(train) [380][5/63] lr: 2.5116e-03 eta: 12:40:12 time: 0.7530 data_time: 0.2020 memory: 16131 loss: 1.5520 loss_prob: 0.8659 loss_thr: 0.5406 loss_db: 0.1455 2022/10/26 01:09:26 - mmengine - INFO - Epoch(train) [380][10/63] lr: 2.5116e-03 eta: 12:39:53 time: 0.7967 data_time: 0.2017 memory: 16131 loss: 1.5919 loss_prob: 0.9016 loss_thr: 0.5408 loss_db: 0.1494 2022/10/26 01:09:28 - mmengine - INFO - Epoch(train) [380][15/63] lr: 2.5116e-03 eta: 12:39:53 time: 0.5152 data_time: 0.0127 memory: 16131 loss: 1.6507 loss_prob: 0.9438 loss_thr: 0.5498 loss_db: 0.1571 2022/10/26 01:09:31 - mmengine - INFO - Epoch(train) [380][20/63] lr: 2.5116e-03 eta: 12:39:36 time: 0.5041 data_time: 0.0148 memory: 16131 loss: 1.7936 loss_prob: 1.0552 loss_thr: 0.5661 loss_db: 0.1722 2022/10/26 01:09:33 - mmengine - INFO - Epoch(train) [380][25/63] lr: 2.5116e-03 eta: 12:39:36 time: 0.5037 data_time: 0.0106 memory: 16131 loss: 1.7288 loss_prob: 0.9989 loss_thr: 0.5700 loss_db: 0.1598 2022/10/26 01:09:36 - mmengine - INFO - Epoch(train) [380][30/63] lr: 2.5116e-03 eta: 12:39:19 time: 0.5119 data_time: 0.0302 memory: 16131 loss: 1.6033 loss_prob: 0.8883 loss_thr: 0.5704 loss_db: 0.1446 2022/10/26 01:09:39 - mmengine - INFO - Epoch(train) [380][35/63] lr: 2.5116e-03 eta: 12:39:19 time: 0.5501 data_time: 0.0337 memory: 16131 loss: 1.6045 loss_prob: 0.8891 loss_thr: 0.5686 loss_db: 0.1469 2022/10/26 01:09:42 - mmengine - INFO - Epoch(train) [380][40/63] lr: 2.5116e-03 eta: 12:39:04 time: 0.5650 data_time: 0.0111 memory: 16131 loss: 1.6262 loss_prob: 0.9212 loss_thr: 0.5504 loss_db: 0.1546 2022/10/26 01:09:44 - mmengine - INFO - Epoch(train) [380][45/63] lr: 2.5116e-03 eta: 12:39:04 time: 0.5343 data_time: 0.0097 memory: 16131 loss: 1.6335 loss_prob: 0.9308 loss_thr: 0.5461 loss_db: 0.1566 2022/10/26 01:09:49 - mmengine - INFO - Epoch(train) [380][50/63] lr: 2.5116e-03 eta: 12:38:51 time: 0.7225 data_time: 0.0281 memory: 16131 loss: 1.7475 loss_prob: 1.0027 loss_thr: 0.5790 loss_db: 0.1658 2022/10/26 01:09:51 - mmengine - INFO - Epoch(train) [380][55/63] lr: 2.5116e-03 eta: 12:38:51 time: 0.7316 data_time: 0.0253 memory: 16131 loss: 1.7327 loss_prob: 0.9992 loss_thr: 0.5697 loss_db: 0.1639 2022/10/26 01:09:54 - mmengine - INFO - Epoch(train) [380][60/63] lr: 2.5116e-03 eta: 12:38:35 time: 0.5489 data_time: 0.0143 memory: 16131 loss: 1.5605 loss_prob: 0.8862 loss_thr: 0.5269 loss_db: 0.1474 2022/10/26 01:09:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:09:56 - mmengine - INFO - Saving checkpoint at 380 epochs 2022/10/26 01:10:03 - mmengine - INFO - Epoch(val) [380][5/32] eta: 12:38:35 time: 0.5632 data_time: 0.0782 memory: 16131 2022/10/26 01:10:06 - mmengine - INFO - Epoch(val) [380][10/32] eta: 0:00:13 time: 0.6156 data_time: 0.0892 memory: 15724 2022/10/26 01:10:09 - mmengine - INFO - Epoch(val) [380][15/32] eta: 0:00:13 time: 0.5652 data_time: 0.0449 memory: 15724 2022/10/26 01:10:12 - mmengine - INFO - Epoch(val) [380][20/32] eta: 0:00:07 time: 0.5841 data_time: 0.0665 memory: 15724 2022/10/26 01:10:14 - mmengine - INFO - Epoch(val) [380][25/32] eta: 0:00:07 time: 0.5933 data_time: 0.0527 memory: 15724 2022/10/26 01:10:17 - mmengine - INFO - Epoch(val) [380][30/32] eta: 0:00:01 time: 0.5593 data_time: 0.0284 memory: 15724 2022/10/26 01:10:18 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8397, precision: 0.6398, hmean: 0.7262 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8397, precision: 0.7390, hmean: 0.7861 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8363, precision: 0.7979, hmean: 0.8166 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8310, precision: 0.8486, hmean: 0.8397 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7853, precision: 0.8971, hmean: 0.8375 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5012, precision: 0.9550, hmean: 0.6574 2022/10/26 01:10:18 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0019, precision: 1.0000, hmean: 0.0038 2022/10/26 01:10:18 - mmengine - INFO - Epoch(val) [380][32/32] icdar/precision: 0.8486 icdar/recall: 0.8310 icdar/hmean: 0.8397 2022/10/26 01:10:24 - mmengine - INFO - Epoch(train) [381][5/63] lr: 2.5088e-03 eta: 0:00:01 time: 0.8587 data_time: 0.2252 memory: 16131 loss: 1.7759 loss_prob: 1.0384 loss_thr: 0.5699 loss_db: 0.1676 2022/10/26 01:10:30 - mmengine - INFO - Epoch(train) [381][10/63] lr: 2.5088e-03 eta: 12:38:25 time: 1.2067 data_time: 0.2282 memory: 16131 loss: 1.7723 loss_prob: 1.0347 loss_thr: 0.5711 loss_db: 0.1666 2022/10/26 01:10:33 - mmengine - INFO - Epoch(train) [381][15/63] lr: 2.5088e-03 eta: 12:38:25 time: 0.9365 data_time: 0.0149 memory: 16131 loss: 1.7247 loss_prob: 0.9998 loss_thr: 0.5600 loss_db: 0.1650 2022/10/26 01:10:37 - mmengine - INFO - Epoch(train) [381][20/63] lr: 2.5088e-03 eta: 12:38:13 time: 0.7201 data_time: 0.0098 memory: 16131 loss: 1.6124 loss_prob: 0.9230 loss_thr: 0.5353 loss_db: 0.1541 2022/10/26 01:10:40 - mmengine - INFO - Epoch(train) [381][25/63] lr: 2.5088e-03 eta: 12:38:13 time: 0.7065 data_time: 0.0123 memory: 16131 loss: 1.5658 loss_prob: 0.8869 loss_thr: 0.5319 loss_db: 0.1470 2022/10/26 01:10:46 - mmengine - INFO - Epoch(train) [381][30/63] lr: 2.5088e-03 eta: 12:38:04 time: 0.8629 data_time: 0.0322 memory: 16131 loss: 1.7507 loss_prob: 1.0108 loss_thr: 0.5753 loss_db: 0.1647 2022/10/26 01:10:50 - mmengine - INFO - Epoch(train) [381][35/63] lr: 2.5088e-03 eta: 12:38:04 time: 0.9779 data_time: 0.0270 memory: 16131 loss: 1.8282 loss_prob: 1.0635 loss_thr: 0.5909 loss_db: 0.1738 2022/10/26 01:10:53 - mmengine - INFO - Epoch(train) [381][40/63] lr: 2.5088e-03 eta: 12:37:51 time: 0.6888 data_time: 0.0125 memory: 16131 loss: 1.7393 loss_prob: 1.0020 loss_thr: 0.5726 loss_db: 0.1647 2022/10/26 01:10:56 - mmengine - INFO - Epoch(train) [381][45/63] lr: 2.5088e-03 eta: 12:37:51 time: 0.6053 data_time: 0.0118 memory: 16131 loss: 1.7683 loss_prob: 1.0146 loss_thr: 0.5862 loss_db: 0.1676 2022/10/26 01:11:01 - mmengine - INFO - Epoch(train) [381][50/63] lr: 2.5088e-03 eta: 12:37:41 time: 0.8470 data_time: 0.0112 memory: 16131 loss: 1.7335 loss_prob: 0.9841 loss_thr: 0.5849 loss_db: 0.1645 2022/10/26 01:11:04 - mmengine - INFO - Epoch(train) [381][55/63] lr: 2.5088e-03 eta: 12:37:41 time: 0.8622 data_time: 0.0215 memory: 16131 loss: 1.5931 loss_prob: 0.9052 loss_thr: 0.5383 loss_db: 0.1496 2022/10/26 01:11:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:11:08 - mmengine - INFO - Epoch(train) [381][60/63] lr: 2.5088e-03 eta: 12:37:29 time: 0.7191 data_time: 0.0181 memory: 16131 loss: 1.5713 loss_prob: 0.8948 loss_thr: 0.5275 loss_db: 0.1490 2022/10/26 01:11:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:11:16 - mmengine - INFO - Epoch(train) [382][5/63] lr: 2.5061e-03 eta: 12:37:29 time: 0.9311 data_time: 0.2166 memory: 16131 loss: 1.5582 loss_prob: 0.8810 loss_thr: 0.5328 loss_db: 0.1443 2022/10/26 01:11:20 - mmengine - INFO - Epoch(train) [382][10/63] lr: 2.5061e-03 eta: 12:37:15 time: 1.0056 data_time: 0.2206 memory: 16131 loss: 1.6522 loss_prob: 0.9555 loss_thr: 0.5429 loss_db: 0.1538 2022/10/26 01:11:24 - mmengine - INFO - Epoch(train) [382][15/63] lr: 2.5061e-03 eta: 12:37:15 time: 0.7142 data_time: 0.0140 memory: 16131 loss: 1.7279 loss_prob: 0.9974 loss_thr: 0.5668 loss_db: 0.1637 2022/10/26 01:11:28 - mmengine - INFO - Epoch(train) [382][20/63] lr: 2.5061e-03 eta: 12:37:04 time: 0.8066 data_time: 0.0068 memory: 16131 loss: 1.6426 loss_prob: 0.9274 loss_thr: 0.5587 loss_db: 0.1566 2022/10/26 01:11:32 - mmengine - INFO - Epoch(train) [382][25/63] lr: 2.5061e-03 eta: 12:37:04 time: 0.8405 data_time: 0.0140 memory: 16131 loss: 1.5542 loss_prob: 0.8724 loss_thr: 0.5341 loss_db: 0.1477 2022/10/26 01:11:36 - mmengine - INFO - Epoch(train) [382][30/63] lr: 2.5061e-03 eta: 12:36:55 time: 0.8465 data_time: 0.0268 memory: 16131 loss: 1.4804 loss_prob: 0.8224 loss_thr: 0.5204 loss_db: 0.1376 2022/10/26 01:11:40 - mmengine - INFO - Epoch(train) [382][35/63] lr: 2.5061e-03 eta: 12:36:55 time: 0.7718 data_time: 0.0257 memory: 16131 loss: 1.7725 loss_prob: 1.0435 loss_thr: 0.5524 loss_db: 0.1767 2022/10/26 01:11:44 - mmengine - INFO - Epoch(train) [382][40/63] lr: 2.5061e-03 eta: 12:36:43 time: 0.7566 data_time: 0.0127 memory: 16131 loss: 1.9936 loss_prob: 1.2008 loss_thr: 0.5872 loss_db: 0.2055 2022/10/26 01:11:48 - mmengine - INFO - Epoch(train) [382][45/63] lr: 2.5061e-03 eta: 12:36:43 time: 0.8198 data_time: 0.0060 memory: 16131 loss: 1.9524 loss_prob: 1.1663 loss_thr: 0.5961 loss_db: 0.1900 2022/10/26 01:11:51 - mmengine - INFO - Epoch(train) [382][50/63] lr: 2.5061e-03 eta: 12:36:30 time: 0.6761 data_time: 0.0120 memory: 16131 loss: 2.0059 loss_prob: 1.2015 loss_thr: 0.6164 loss_db: 0.1880 2022/10/26 01:11:54 - mmengine - INFO - Epoch(train) [382][55/63] lr: 2.5061e-03 eta: 12:36:30 time: 0.6453 data_time: 0.0299 memory: 16131 loss: 1.9056 loss_prob: 1.1196 loss_thr: 0.6051 loss_db: 0.1809 2022/10/26 01:11:57 - mmengine - INFO - Epoch(train) [382][60/63] lr: 2.5061e-03 eta: 12:36:17 time: 0.6745 data_time: 0.0250 memory: 16131 loss: 1.8997 loss_prob: 1.1132 loss_thr: 0.6000 loss_db: 0.1865 2022/10/26 01:11:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:12:03 - mmengine - INFO - Epoch(train) [383][5/63] lr: 2.5033e-03 eta: 12:36:17 time: 0.6858 data_time: 0.1828 memory: 16131 loss: 1.8853 loss_prob: 1.1090 loss_thr: 0.5934 loss_db: 0.1830 2022/10/26 01:12:06 - mmengine - INFO - Epoch(train) [383][10/63] lr: 2.5033e-03 eta: 12:35:56 time: 0.7000 data_time: 0.1921 memory: 16131 loss: 1.7398 loss_prob: 1.0041 loss_thr: 0.5704 loss_db: 0.1654 2022/10/26 01:12:09 - mmengine - INFO - Epoch(train) [383][15/63] lr: 2.5033e-03 eta: 12:35:56 time: 0.5761 data_time: 0.0185 memory: 16131 loss: 1.8200 loss_prob: 1.0576 loss_thr: 0.5879 loss_db: 0.1745 2022/10/26 01:12:11 - mmengine - INFO - Epoch(train) [383][20/63] lr: 2.5033e-03 eta: 12:35:40 time: 0.5684 data_time: 0.0105 memory: 16131 loss: 1.7595 loss_prob: 1.0211 loss_thr: 0.5706 loss_db: 0.1677 2022/10/26 01:12:14 - mmengine - INFO - Epoch(train) [383][25/63] lr: 2.5033e-03 eta: 12:35:40 time: 0.5267 data_time: 0.0138 memory: 16131 loss: 1.7381 loss_prob: 1.0057 loss_thr: 0.5676 loss_db: 0.1648 2022/10/26 01:12:17 - mmengine - INFO - Epoch(train) [383][30/63] lr: 2.5033e-03 eta: 12:35:25 time: 0.5614 data_time: 0.0310 memory: 16131 loss: 1.7718 loss_prob: 1.0253 loss_thr: 0.5817 loss_db: 0.1647 2022/10/26 01:12:20 - mmengine - INFO - Epoch(train) [383][35/63] lr: 2.5033e-03 eta: 12:35:25 time: 0.5610 data_time: 0.0274 memory: 16131 loss: 1.9211 loss_prob: 1.1336 loss_thr: 0.6045 loss_db: 0.1829 2022/10/26 01:12:25 - mmengine - INFO - Epoch(train) [383][40/63] lr: 2.5033e-03 eta: 12:35:14 time: 0.8021 data_time: 0.0108 memory: 16131 loss: 2.0774 loss_prob: 1.2780 loss_thr: 0.5995 loss_db: 0.1998 2022/10/26 01:12:28 - mmengine - INFO - Epoch(train) [383][45/63] lr: 2.5033e-03 eta: 12:35:14 time: 0.8225 data_time: 0.0068 memory: 16131 loss: 1.9713 loss_prob: 1.2071 loss_thr: 0.5786 loss_db: 0.1855 2022/10/26 01:12:30 - mmengine - INFO - Epoch(train) [383][50/63] lr: 2.5033e-03 eta: 12:34:59 time: 0.5582 data_time: 0.0221 memory: 16131 loss: 1.8373 loss_prob: 1.0715 loss_thr: 0.5920 loss_db: 0.1738 2022/10/26 01:12:33 - mmengine - INFO - Epoch(train) [383][55/63] lr: 2.5033e-03 eta: 12:34:59 time: 0.5517 data_time: 0.0312 memory: 16131 loss: 1.8235 loss_prob: 1.0546 loss_thr: 0.5977 loss_db: 0.1712 2022/10/26 01:12:39 - mmengine - INFO - Epoch(train) [383][60/63] lr: 2.5033e-03 eta: 12:34:49 time: 0.8498 data_time: 0.0164 memory: 16131 loss: 1.7808 loss_prob: 1.0487 loss_thr: 0.5596 loss_db: 0.1724 2022/10/26 01:12:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:12:45 - mmengine - INFO - Epoch(train) [384][5/63] lr: 2.5006e-03 eta: 12:34:49 time: 0.8995 data_time: 0.1901 memory: 16131 loss: 1.8358 loss_prob: 1.0877 loss_thr: 0.5718 loss_db: 0.1763 2022/10/26 01:12:48 - mmengine - INFO - Epoch(train) [384][10/63] lr: 2.5006e-03 eta: 12:34:30 time: 0.7740 data_time: 0.1941 memory: 16131 loss: 1.8418 loss_prob: 1.0956 loss_thr: 0.5694 loss_db: 0.1767 2022/10/26 01:12:52 - mmengine - INFO - Epoch(train) [384][15/63] lr: 2.5006e-03 eta: 12:34:30 time: 0.6727 data_time: 0.0156 memory: 16131 loss: 1.8672 loss_prob: 1.1076 loss_thr: 0.5818 loss_db: 0.1778 2022/10/26 01:12:55 - mmengine - INFO - Epoch(train) [384][20/63] lr: 2.5006e-03 eta: 12:34:16 time: 0.6447 data_time: 0.0133 memory: 16131 loss: 1.9625 loss_prob: 1.1623 loss_thr: 0.6181 loss_db: 0.1822 2022/10/26 01:13:01 - mmengine - INFO - Epoch(train) [384][25/63] lr: 2.5006e-03 eta: 12:34:16 time: 0.8644 data_time: 0.0267 memory: 16131 loss: 1.7602 loss_prob: 1.0071 loss_thr: 0.5890 loss_db: 0.1641 2022/10/26 01:13:04 - mmengine - INFO - Epoch(train) [384][30/63] lr: 2.5006e-03 eta: 12:34:09 time: 0.9509 data_time: 0.0274 memory: 16131 loss: 1.7283 loss_prob: 0.9820 loss_thr: 0.5834 loss_db: 0.1628 2022/10/26 01:13:08 - mmengine - INFO - Epoch(train) [384][35/63] lr: 2.5006e-03 eta: 12:34:09 time: 0.6880 data_time: 0.0136 memory: 16131 loss: 1.6492 loss_prob: 0.9162 loss_thr: 0.5818 loss_db: 0.1513 2022/10/26 01:13:12 - mmengine - INFO - Epoch(train) [384][40/63] lr: 2.5006e-03 eta: 12:33:58 time: 0.7830 data_time: 0.0177 memory: 16131 loss: 1.6531 loss_prob: 0.9250 loss_thr: 0.5766 loss_db: 0.1516 2022/10/26 01:13:16 - mmengine - INFO - Epoch(train) [384][45/63] lr: 2.5006e-03 eta: 12:33:58 time: 0.8437 data_time: 0.0142 memory: 16131 loss: 1.7025 loss_prob: 0.9655 loss_thr: 0.5770 loss_db: 0.1600 2022/10/26 01:13:20 - mmengine - INFO - Epoch(train) [384][50/63] lr: 2.5006e-03 eta: 12:33:47 time: 0.7949 data_time: 0.0186 memory: 16131 loss: 1.6963 loss_prob: 0.9687 loss_thr: 0.5659 loss_db: 0.1617 2022/10/26 01:13:23 - mmengine - INFO - Epoch(train) [384][55/63] lr: 2.5006e-03 eta: 12:33:47 time: 0.6748 data_time: 0.0251 memory: 16131 loss: 1.7364 loss_prob: 1.0144 loss_thr: 0.5551 loss_db: 0.1669 2022/10/26 01:13:28 - mmengine - INFO - Epoch(train) [384][60/63] lr: 2.5006e-03 eta: 12:33:36 time: 0.7554 data_time: 0.0152 memory: 16131 loss: 1.7421 loss_prob: 1.0124 loss_thr: 0.5628 loss_db: 0.1669 2022/10/26 01:13:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:13:34 - mmengine - INFO - Epoch(train) [385][5/63] lr: 2.4978e-03 eta: 12:33:36 time: 0.8511 data_time: 0.1949 memory: 16131 loss: 1.7061 loss_prob: 0.9970 loss_thr: 0.5498 loss_db: 0.1594 2022/10/26 01:13:38 - mmengine - INFO - Epoch(train) [385][10/63] lr: 2.4978e-03 eta: 12:33:18 time: 0.8403 data_time: 0.2036 memory: 16131 loss: 1.8311 loss_prob: 1.1067 loss_thr: 0.5456 loss_db: 0.1788 2022/10/26 01:13:40 - mmengine - INFO - Epoch(train) [385][15/63] lr: 2.4978e-03 eta: 12:33:18 time: 0.6648 data_time: 0.0178 memory: 16131 loss: 1.8412 loss_prob: 1.0973 loss_thr: 0.5645 loss_db: 0.1794 2022/10/26 01:13:44 - mmengine - INFO - Epoch(train) [385][20/63] lr: 2.4978e-03 eta: 12:33:03 time: 0.6020 data_time: 0.0073 memory: 16131 loss: 1.8955 loss_prob: 1.1372 loss_thr: 0.5734 loss_db: 0.1848 2022/10/26 01:13:46 - mmengine - INFO - Epoch(train) [385][25/63] lr: 2.4978e-03 eta: 12:33:03 time: 0.5934 data_time: 0.0226 memory: 16131 loss: 1.8954 loss_prob: 1.1295 loss_thr: 0.5794 loss_db: 0.1865 2022/10/26 01:13:49 - mmengine - INFO - Epoch(train) [385][30/63] lr: 2.4978e-03 eta: 12:32:48 time: 0.5519 data_time: 0.0288 memory: 16131 loss: 1.7921 loss_prob: 1.0344 loss_thr: 0.5880 loss_db: 0.1698 2022/10/26 01:13:52 - mmengine - INFO - Epoch(train) [385][35/63] lr: 2.4978e-03 eta: 12:32:48 time: 0.5852 data_time: 0.0385 memory: 16131 loss: 1.7949 loss_prob: 1.0351 loss_thr: 0.5924 loss_db: 0.1675 2022/10/26 01:13:56 - mmengine - INFO - Epoch(train) [385][40/63] lr: 2.4978e-03 eta: 12:32:35 time: 0.7088 data_time: 0.0318 memory: 16131 loss: 1.8598 loss_prob: 1.0736 loss_thr: 0.6105 loss_db: 0.1757 2022/10/26 01:14:01 - mmengine - INFO - Epoch(train) [385][45/63] lr: 2.4978e-03 eta: 12:32:35 time: 0.8821 data_time: 0.0064 memory: 16131 loss: 1.7177 loss_prob: 0.9760 loss_thr: 0.5789 loss_db: 0.1628 2022/10/26 01:14:09 - mmengine - INFO - Epoch(train) [385][50/63] lr: 2.4978e-03 eta: 12:32:35 time: 1.2664 data_time: 0.0186 memory: 16131 loss: 1.6563 loss_prob: 0.9368 loss_thr: 0.5639 loss_db: 0.1557 2022/10/26 01:14:13 - mmengine - INFO - Epoch(train) [385][55/63] lr: 2.4978e-03 eta: 12:32:35 time: 1.2108 data_time: 0.0196 memory: 16131 loss: 1.6186 loss_prob: 0.9204 loss_thr: 0.5469 loss_db: 0.1512 2022/10/26 01:14:18 - mmengine - INFO - Epoch(train) [385][60/63] lr: 2.4978e-03 eta: 12:32:27 time: 0.9305 data_time: 0.0122 memory: 16131 loss: 1.6091 loss_prob: 0.9358 loss_thr: 0.5227 loss_db: 0.1505 2022/10/26 01:14:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:14:30 - mmengine - INFO - Epoch(train) [386][5/63] lr: 2.4950e-03 eta: 12:32:27 time: 1.3774 data_time: 0.1996 memory: 16131 loss: 2.0333 loss_prob: 1.2565 loss_thr: 0.5775 loss_db: 0.1993 2022/10/26 01:14:35 - mmengine - INFO - Epoch(train) [386][10/63] lr: 2.4950e-03 eta: 12:32:21 time: 1.3817 data_time: 0.1996 memory: 16131 loss: 1.9377 loss_prob: 1.1485 loss_thr: 0.6024 loss_db: 0.1868 2022/10/26 01:14:38 - mmengine - INFO - Epoch(train) [386][15/63] lr: 2.4950e-03 eta: 12:32:21 time: 0.7991 data_time: 0.0055 memory: 16131 loss: 1.8304 loss_prob: 1.0586 loss_thr: 0.5974 loss_db: 0.1744 2022/10/26 01:14:41 - mmengine - INFO - Epoch(train) [386][20/63] lr: 2.4950e-03 eta: 12:32:07 time: 0.6500 data_time: 0.0062 memory: 16131 loss: 1.9957 loss_prob: 1.2360 loss_thr: 0.5597 loss_db: 0.2000 2022/10/26 01:14:44 - mmengine - INFO - Epoch(train) [386][25/63] lr: 2.4950e-03 eta: 12:32:07 time: 0.6038 data_time: 0.0113 memory: 16131 loss: 2.0137 loss_prob: 1.2627 loss_thr: 0.5521 loss_db: 0.1989 2022/10/26 01:14:49 - mmengine - INFO - Epoch(train) [386][30/63] lr: 2.4950e-03 eta: 12:31:55 time: 0.7465 data_time: 0.0462 memory: 16131 loss: 1.6536 loss_prob: 0.9504 loss_thr: 0.5489 loss_db: 0.1543 2022/10/26 01:14:52 - mmengine - INFO - Epoch(train) [386][35/63] lr: 2.4950e-03 eta: 12:31:55 time: 0.8170 data_time: 0.0404 memory: 16131 loss: 1.7232 loss_prob: 0.9913 loss_thr: 0.5668 loss_db: 0.1651 2022/10/26 01:14:57 - mmengine - INFO - Epoch(train) [386][40/63] lr: 2.4950e-03 eta: 12:31:46 time: 0.8572 data_time: 0.0068 memory: 16131 loss: 2.0173 loss_prob: 1.2228 loss_thr: 0.5975 loss_db: 0.1970 2022/10/26 01:15:02 - mmengine - INFO - Epoch(train) [386][45/63] lr: 2.4950e-03 eta: 12:31:46 time: 0.9491 data_time: 0.0078 memory: 16131 loss: 1.8904 loss_prob: 1.1259 loss_thr: 0.5865 loss_db: 0.1780 2022/10/26 01:15:06 - mmengine - INFO - Epoch(train) [386][50/63] lr: 2.4950e-03 eta: 12:31:36 time: 0.8312 data_time: 0.0098 memory: 16131 loss: 1.7560 loss_prob: 1.0067 loss_thr: 0.5856 loss_db: 0.1638 2022/10/26 01:15:11 - mmengine - INFO - Epoch(train) [386][55/63] lr: 2.4950e-03 eta: 12:31:36 time: 0.9329 data_time: 0.0222 memory: 16131 loss: 1.8676 loss_prob: 1.0916 loss_thr: 0.5908 loss_db: 0.1851 2022/10/26 01:15:16 - mmengine - INFO - Epoch(train) [386][60/63] lr: 2.4950e-03 eta: 12:31:31 time: 1.0280 data_time: 0.0188 memory: 16131 loss: 1.8297 loss_prob: 1.0719 loss_thr: 0.5775 loss_db: 0.1803 2022/10/26 01:15:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:15:26 - mmengine - INFO - Epoch(train) [387][5/63] lr: 2.4923e-03 eta: 12:31:31 time: 1.2457 data_time: 0.1640 memory: 16131 loss: 1.6846 loss_prob: 0.9649 loss_thr: 0.5606 loss_db: 0.1591 2022/10/26 01:15:31 - mmengine - INFO - Epoch(train) [387][10/63] lr: 2.4923e-03 eta: 12:31:24 time: 1.3721 data_time: 0.1709 memory: 16131 loss: 1.8246 loss_prob: 1.0712 loss_thr: 0.5794 loss_db: 0.1740 2022/10/26 01:15:34 - mmengine - INFO - Epoch(train) [387][15/63] lr: 2.4923e-03 eta: 12:31:24 time: 0.7332 data_time: 0.0218 memory: 16131 loss: 1.7507 loss_prob: 1.0265 loss_thr: 0.5602 loss_db: 0.1640 2022/10/26 01:15:39 - mmengine - INFO - Epoch(train) [387][20/63] lr: 2.4923e-03 eta: 12:31:14 time: 0.8269 data_time: 0.0161 memory: 16131 loss: 1.6188 loss_prob: 0.9237 loss_thr: 0.5437 loss_db: 0.1515 2022/10/26 01:15:44 - mmengine - INFO - Epoch(train) [387][25/63] lr: 2.4923e-03 eta: 12:31:14 time: 1.0350 data_time: 0.0134 memory: 16131 loss: 1.5997 loss_prob: 0.9136 loss_thr: 0.5365 loss_db: 0.1496 2022/10/26 01:15:48 - mmengine - INFO - Epoch(train) [387][30/63] lr: 2.4923e-03 eta: 12:31:06 time: 0.9069 data_time: 0.0307 memory: 16131 loss: 1.5067 loss_prob: 0.8618 loss_thr: 0.5019 loss_db: 0.1429 2022/10/26 01:15:54 - mmengine - INFO - Epoch(train) [387][35/63] lr: 2.4923e-03 eta: 12:31:06 time: 0.9799 data_time: 0.0281 memory: 16131 loss: 1.5352 loss_prob: 0.8872 loss_thr: 0.5038 loss_db: 0.1441 2022/10/26 01:15:57 - mmengine - INFO - Epoch(train) [387][40/63] lr: 2.4923e-03 eta: 12:30:58 time: 0.9184 data_time: 0.0164 memory: 16131 loss: 1.8638 loss_prob: 1.0995 loss_thr: 0.5864 loss_db: 0.1780 2022/10/26 01:16:00 - mmengine - INFO - Epoch(train) [387][45/63] lr: 2.4923e-03 eta: 12:30:58 time: 0.6353 data_time: 0.0128 memory: 16131 loss: 1.9122 loss_prob: 1.1205 loss_thr: 0.6054 loss_db: 0.1863 2022/10/26 01:16:03 - mmengine - INFO - Epoch(train) [387][50/63] lr: 2.4923e-03 eta: 12:30:42 time: 0.5263 data_time: 0.0128 memory: 16131 loss: 1.7931 loss_prob: 1.0435 loss_thr: 0.5765 loss_db: 0.1731 2022/10/26 01:16:06 - mmengine - INFO - Epoch(train) [387][55/63] lr: 2.4923e-03 eta: 12:30:42 time: 0.5484 data_time: 0.0190 memory: 16131 loss: 1.7822 loss_prob: 1.0383 loss_thr: 0.5752 loss_db: 0.1687 2022/10/26 01:16:09 - mmengine - INFO - Epoch(train) [387][60/63] lr: 2.4923e-03 eta: 12:30:27 time: 0.5837 data_time: 0.0150 memory: 16131 loss: 1.7249 loss_prob: 0.9819 loss_thr: 0.5857 loss_db: 0.1573 2022/10/26 01:16:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:16:18 - mmengine - INFO - Epoch(train) [388][5/63] lr: 2.4895e-03 eta: 12:30:27 time: 1.0448 data_time: 0.1691 memory: 16131 loss: 2.0914 loss_prob: 1.2481 loss_thr: 0.6344 loss_db: 0.2088 2022/10/26 01:16:22 - mmengine - INFO - Epoch(train) [388][10/63] lr: 2.4895e-03 eta: 12:30:16 time: 1.1941 data_time: 0.1673 memory: 16131 loss: 1.6586 loss_prob: 0.9707 loss_thr: 0.5251 loss_db: 0.1628 2022/10/26 01:16:26 - mmengine - INFO - Epoch(train) [388][15/63] lr: 2.4895e-03 eta: 12:30:16 time: 0.8278 data_time: 0.0122 memory: 16131 loss: 1.6301 loss_prob: 0.9330 loss_thr: 0.5412 loss_db: 0.1560 2022/10/26 01:16:30 - mmengine - INFO - Epoch(train) [388][20/63] lr: 2.4895e-03 eta: 12:30:07 time: 0.8493 data_time: 0.0113 memory: 16131 loss: 1.8580 loss_prob: 1.1013 loss_thr: 0.5785 loss_db: 0.1782 2022/10/26 01:16:33 - mmengine - INFO - Epoch(train) [388][25/63] lr: 2.4895e-03 eta: 12:30:07 time: 0.7228 data_time: 0.0151 memory: 16131 loss: 1.9672 loss_prob: 1.1692 loss_thr: 0.6040 loss_db: 0.1940 2022/10/26 01:16:37 - mmengine - INFO - Epoch(train) [388][30/63] lr: 2.4895e-03 eta: 12:29:53 time: 0.6193 data_time: 0.0428 memory: 16131 loss: 1.9466 loss_prob: 1.1563 loss_thr: 0.6010 loss_db: 0.1893 2022/10/26 01:16:41 - mmengine - INFO - Epoch(train) [388][35/63] lr: 2.4895e-03 eta: 12:29:53 time: 0.7914 data_time: 0.0332 memory: 16131 loss: 1.7636 loss_prob: 1.0403 loss_thr: 0.5557 loss_db: 0.1676 2022/10/26 01:16:46 - mmengine - INFO - Epoch(train) [388][40/63] lr: 2.4895e-03 eta: 12:29:44 time: 0.8908 data_time: 0.0070 memory: 16131 loss: 1.7503 loss_prob: 1.0094 loss_thr: 0.5713 loss_db: 0.1695 2022/10/26 01:16:50 - mmengine - INFO - Epoch(train) [388][45/63] lr: 2.4895e-03 eta: 12:29:44 time: 0.8406 data_time: 0.0064 memory: 16131 loss: 1.8696 loss_prob: 1.0855 loss_thr: 0.6045 loss_db: 0.1796 2022/10/26 01:16:55 - mmengine - INFO - Epoch(train) [388][50/63] lr: 2.4895e-03 eta: 12:29:36 time: 0.9271 data_time: 0.0085 memory: 16131 loss: 1.8955 loss_prob: 1.1289 loss_thr: 0.5826 loss_db: 0.1840 2022/10/26 01:16:59 - mmengine - INFO - Epoch(train) [388][55/63] lr: 2.4895e-03 eta: 12:29:36 time: 0.9120 data_time: 0.0201 memory: 16131 loss: 1.8888 loss_prob: 1.1336 loss_thr: 0.5727 loss_db: 0.1825 2022/10/26 01:17:02 - mmengine - INFO - Epoch(train) [388][60/63] lr: 2.4895e-03 eta: 12:29:25 time: 0.7370 data_time: 0.0172 memory: 16131 loss: 1.7401 loss_prob: 1.0241 loss_thr: 0.5490 loss_db: 0.1670 2022/10/26 01:17:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:17:10 - mmengine - INFO - Epoch(train) [389][5/63] lr: 2.4868e-03 eta: 12:29:25 time: 0.9284 data_time: 0.1731 memory: 16131 loss: 1.5413 loss_prob: 0.8720 loss_thr: 0.5279 loss_db: 0.1414 2022/10/26 01:17:13 - mmengine - INFO - Epoch(train) [389][10/63] lr: 2.4868e-03 eta: 12:29:10 time: 0.9893 data_time: 0.1815 memory: 16131 loss: 1.5932 loss_prob: 0.8977 loss_thr: 0.5501 loss_db: 0.1454 2022/10/26 01:17:16 - mmengine - INFO - Epoch(train) [389][15/63] lr: 2.4868e-03 eta: 12:29:10 time: 0.5546 data_time: 0.0136 memory: 16131 loss: 1.7137 loss_prob: 0.9750 loss_thr: 0.5787 loss_db: 0.1599 2022/10/26 01:17:19 - mmengine - INFO - Epoch(train) [389][20/63] lr: 2.4868e-03 eta: 12:28:54 time: 0.5372 data_time: 0.0058 memory: 16131 loss: 1.6836 loss_prob: 0.9656 loss_thr: 0.5588 loss_db: 0.1591 2022/10/26 01:17:23 - mmengine - INFO - Epoch(train) [389][25/63] lr: 2.4868e-03 eta: 12:28:54 time: 0.7096 data_time: 0.0149 memory: 16131 loss: 1.7484 loss_prob: 1.0172 loss_thr: 0.5649 loss_db: 0.1663 2022/10/26 01:17:27 - mmengine - INFO - Epoch(train) [389][30/63] lr: 2.4868e-03 eta: 12:28:44 time: 0.8126 data_time: 0.0376 memory: 16131 loss: 1.7638 loss_prob: 1.0125 loss_thr: 0.5844 loss_db: 0.1669 2022/10/26 01:17:32 - mmengine - INFO - Epoch(train) [389][35/63] lr: 2.4868e-03 eta: 12:28:44 time: 0.8791 data_time: 0.0317 memory: 16131 loss: 1.7940 loss_prob: 1.0368 loss_thr: 0.5899 loss_db: 0.1673 2022/10/26 01:17:36 - mmengine - INFO - Epoch(train) [389][40/63] lr: 2.4868e-03 eta: 12:28:36 time: 0.9328 data_time: 0.0082 memory: 16131 loss: 1.8001 loss_prob: 1.0376 loss_thr: 0.5974 loss_db: 0.1651 2022/10/26 01:17:39 - mmengine - INFO - Epoch(train) [389][45/63] lr: 2.4868e-03 eta: 12:28:36 time: 0.7095 data_time: 0.0076 memory: 16131 loss: 1.7385 loss_prob: 0.9847 loss_thr: 0.5933 loss_db: 0.1604 2022/10/26 01:17:45 - mmengine - INFO - Epoch(train) [389][50/63] lr: 2.4868e-03 eta: 12:28:27 time: 0.8694 data_time: 0.0202 memory: 16131 loss: 1.8848 loss_prob: 1.0826 loss_thr: 0.6215 loss_db: 0.1808 2022/10/26 01:17:49 - mmengine - INFO - Epoch(train) [389][55/63] lr: 2.4868e-03 eta: 12:28:27 time: 1.0549 data_time: 0.0234 memory: 16131 loss: 2.0466 loss_prob: 1.2053 loss_thr: 0.6439 loss_db: 0.1973 2022/10/26 01:17:52 - mmengine - INFO - Epoch(train) [389][60/63] lr: 2.4868e-03 eta: 12:28:15 time: 0.7266 data_time: 0.0107 memory: 16131 loss: 1.8819 loss_prob: 1.1078 loss_thr: 0.5962 loss_db: 0.1780 2022/10/26 01:17:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:17:58 - mmengine - INFO - Epoch(train) [390][5/63] lr: 2.4840e-03 eta: 12:28:15 time: 0.6513 data_time: 0.1568 memory: 16131 loss: 1.7090 loss_prob: 0.9817 loss_thr: 0.5639 loss_db: 0.1634 2022/10/26 01:18:02 - mmengine - INFO - Epoch(train) [390][10/63] lr: 2.4840e-03 eta: 12:27:58 time: 0.8418 data_time: 0.1607 memory: 16131 loss: 1.7142 loss_prob: 0.9780 loss_thr: 0.5760 loss_db: 0.1602 2022/10/26 01:18:05 - mmengine - INFO - Epoch(train) [390][15/63] lr: 2.4840e-03 eta: 12:27:58 time: 0.7470 data_time: 0.0169 memory: 16131 loss: 1.6570 loss_prob: 0.9425 loss_thr: 0.5601 loss_db: 0.1543 2022/10/26 01:18:10 - mmengine - INFO - Epoch(train) [390][20/63] lr: 2.4840e-03 eta: 12:27:49 time: 0.8819 data_time: 0.0154 memory: 16131 loss: 1.6024 loss_prob: 0.9055 loss_thr: 0.5484 loss_db: 0.1485 2022/10/26 01:18:15 - mmengine - INFO - Epoch(train) [390][25/63] lr: 2.4840e-03 eta: 12:27:49 time: 1.0020 data_time: 0.0148 memory: 16131 loss: 1.5588 loss_prob: 0.8709 loss_thr: 0.5457 loss_db: 0.1423 2022/10/26 01:18:21 - mmengine - INFO - Epoch(train) [390][30/63] lr: 2.4840e-03 eta: 12:27:44 time: 1.0846 data_time: 0.0281 memory: 16131 loss: 1.6399 loss_prob: 0.9359 loss_thr: 0.5492 loss_db: 0.1548 2022/10/26 01:18:25 - mmengine - INFO - Epoch(train) [390][35/63] lr: 2.4840e-03 eta: 12:27:44 time: 0.9973 data_time: 0.0205 memory: 16131 loss: 1.7372 loss_prob: 1.0140 loss_thr: 0.5582 loss_db: 0.1650 2022/10/26 01:18:30 - mmengine - INFO - Epoch(train) [390][40/63] lr: 2.4840e-03 eta: 12:27:35 time: 0.8395 data_time: 0.0165 memory: 16131 loss: 1.7840 loss_prob: 1.0389 loss_thr: 0.5787 loss_db: 0.1664 2022/10/26 01:18:32 - mmengine - INFO - Epoch(train) [390][45/63] lr: 2.4840e-03 eta: 12:27:35 time: 0.7459 data_time: 0.0197 memory: 16131 loss: 1.8515 loss_prob: 1.0905 loss_thr: 0.5870 loss_db: 0.1741 2022/10/26 01:18:36 - mmengine - INFO - Epoch(train) [390][50/63] lr: 2.4840e-03 eta: 12:27:20 time: 0.5997 data_time: 0.0170 memory: 16131 loss: 1.7332 loss_prob: 1.0013 loss_thr: 0.5710 loss_db: 0.1608 2022/10/26 01:18:38 - mmengine - INFO - Epoch(train) [390][55/63] lr: 2.4840e-03 eta: 12:27:20 time: 0.5916 data_time: 0.0218 memory: 16131 loss: 1.6077 loss_prob: 0.8942 loss_thr: 0.5647 loss_db: 0.1488 2022/10/26 01:18:41 - mmengine - INFO - Epoch(train) [390][60/63] lr: 2.4840e-03 eta: 12:27:04 time: 0.5327 data_time: 0.0142 memory: 16131 loss: 1.5475 loss_prob: 0.8590 loss_thr: 0.5433 loss_db: 0.1452 2022/10/26 01:18:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:18:48 - mmengine - INFO - Epoch(train) [391][5/63] lr: 2.4812e-03 eta: 12:27:04 time: 0.7579 data_time: 0.1817 memory: 16131 loss: 1.5164 loss_prob: 0.8509 loss_thr: 0.5239 loss_db: 0.1416 2022/10/26 01:18:50 - mmengine - INFO - Epoch(train) [391][10/63] lr: 2.4812e-03 eta: 12:26:45 time: 0.7497 data_time: 0.1784 memory: 16131 loss: 1.9186 loss_prob: 1.1210 loss_thr: 0.6180 loss_db: 0.1796 2022/10/26 01:18:56 - mmengine - INFO - Epoch(train) [391][15/63] lr: 2.4812e-03 eta: 12:26:45 time: 0.8369 data_time: 0.0065 memory: 16131 loss: 1.9066 loss_prob: 1.1124 loss_thr: 0.6168 loss_db: 0.1774 2022/10/26 01:18:59 - mmengine - INFO - Epoch(train) [391][20/63] lr: 2.4812e-03 eta: 12:26:35 time: 0.8379 data_time: 0.0092 memory: 16131 loss: 1.6575 loss_prob: 0.9484 loss_thr: 0.5531 loss_db: 0.1560 2022/10/26 01:19:02 - mmengine - INFO - Epoch(train) [391][25/63] lr: 2.4812e-03 eta: 12:26:35 time: 0.5685 data_time: 0.0222 memory: 16131 loss: 1.7526 loss_prob: 1.0009 loss_thr: 0.5887 loss_db: 0.1630 2022/10/26 01:19:04 - mmengine - INFO - Epoch(train) [391][30/63] lr: 2.4812e-03 eta: 12:26:20 time: 0.5977 data_time: 0.0337 memory: 16131 loss: 1.7772 loss_prob: 1.0054 loss_thr: 0.6052 loss_db: 0.1666 2022/10/26 01:19:08 - mmengine - INFO - Epoch(train) [391][35/63] lr: 2.4812e-03 eta: 12:26:20 time: 0.6507 data_time: 0.0193 memory: 16131 loss: 1.7856 loss_prob: 1.0098 loss_thr: 0.6059 loss_db: 0.1699 2022/10/26 01:19:13 - mmengine - INFO - Epoch(train) [391][40/63] lr: 2.4812e-03 eta: 12:26:11 time: 0.8487 data_time: 0.0102 memory: 16131 loss: 1.8028 loss_prob: 1.0250 loss_thr: 0.6119 loss_db: 0.1659 2022/10/26 01:19:16 - mmengine - INFO - Epoch(train) [391][45/63] lr: 2.4812e-03 eta: 12:26:11 time: 0.7805 data_time: 0.0112 memory: 16131 loss: 1.8342 loss_prob: 1.0515 loss_thr: 0.6135 loss_db: 0.1691 2022/10/26 01:19:20 - mmengine - INFO - Epoch(train) [391][50/63] lr: 2.4812e-03 eta: 12:25:58 time: 0.6543 data_time: 0.0143 memory: 16131 loss: 1.7986 loss_prob: 1.0366 loss_thr: 0.5880 loss_db: 0.1740 2022/10/26 01:19:26 - mmengine - INFO - Epoch(train) [391][55/63] lr: 2.4812e-03 eta: 12:25:58 time: 0.9755 data_time: 0.0405 memory: 16131 loss: 1.8534 loss_prob: 1.0875 loss_thr: 0.5862 loss_db: 0.1797 2022/10/26 01:19:32 - mmengine - INFO - Epoch(train) [391][60/63] lr: 2.4812e-03 eta: 12:25:56 time: 1.2420 data_time: 0.0324 memory: 16131 loss: 1.8317 loss_prob: 1.0688 loss_thr: 0.5917 loss_db: 0.1713 2022/10/26 01:19:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:19:41 - mmengine - INFO - Epoch(train) [392][5/63] lr: 2.4785e-03 eta: 12:25:56 time: 1.0954 data_time: 0.1550 memory: 16131 loss: 1.7887 loss_prob: 1.0468 loss_thr: 0.5698 loss_db: 0.1721 2022/10/26 01:19:45 - mmengine - INFO - Epoch(train) [392][10/63] lr: 2.4785e-03 eta: 12:25:41 time: 0.9536 data_time: 0.1573 memory: 16131 loss: 1.8075 loss_prob: 1.0650 loss_thr: 0.5684 loss_db: 0.1740 2022/10/26 01:19:47 - mmengine - INFO - Epoch(train) [392][15/63] lr: 2.4785e-03 eta: 12:25:41 time: 0.6657 data_time: 0.0095 memory: 16131 loss: 1.7498 loss_prob: 1.0024 loss_thr: 0.5828 loss_db: 0.1645 2022/10/26 01:19:50 - mmengine - INFO - Epoch(train) [392][20/63] lr: 2.4785e-03 eta: 12:25:25 time: 0.5403 data_time: 0.0088 memory: 16131 loss: 1.8222 loss_prob: 1.0773 loss_thr: 0.5753 loss_db: 0.1696 2022/10/26 01:19:53 - mmengine - INFO - Epoch(train) [392][25/63] lr: 2.4785e-03 eta: 12:25:25 time: 0.5282 data_time: 0.0104 memory: 16131 loss: 1.8059 loss_prob: 1.0706 loss_thr: 0.5671 loss_db: 0.1682 2022/10/26 01:19:56 - mmengine - INFO - Epoch(train) [392][30/63] lr: 2.4785e-03 eta: 12:25:11 time: 0.6287 data_time: 0.0323 memory: 16131 loss: 1.7079 loss_prob: 0.9793 loss_thr: 0.5673 loss_db: 0.1613 2022/10/26 01:19:59 - mmengine - INFO - Epoch(train) [392][35/63] lr: 2.4785e-03 eta: 12:25:11 time: 0.6358 data_time: 0.0332 memory: 16131 loss: 1.7233 loss_prob: 0.9695 loss_thr: 0.5918 loss_db: 0.1620 2022/10/26 01:20:02 - mmengine - INFO - Epoch(train) [392][40/63] lr: 2.4785e-03 eta: 12:24:57 time: 0.5805 data_time: 0.0138 memory: 16131 loss: 1.6569 loss_prob: 0.9237 loss_thr: 0.5799 loss_db: 0.1533 2022/10/26 01:20:06 - mmengine - INFO - Epoch(train) [392][45/63] lr: 2.4785e-03 eta: 12:24:57 time: 0.7101 data_time: 0.0095 memory: 16131 loss: 1.5580 loss_prob: 0.8785 loss_thr: 0.5353 loss_db: 0.1442 2022/10/26 01:20:10 - mmengine - INFO - Epoch(train) [392][50/63] lr: 2.4785e-03 eta: 12:24:47 time: 0.8287 data_time: 0.0165 memory: 16131 loss: 1.5574 loss_prob: 0.8741 loss_thr: 0.5398 loss_db: 0.1435 2022/10/26 01:20:14 - mmengine - INFO - Epoch(train) [392][55/63] lr: 2.4785e-03 eta: 12:24:47 time: 0.7349 data_time: 0.0193 memory: 16131 loss: 1.6370 loss_prob: 0.9090 loss_thr: 0.5784 loss_db: 0.1496 2022/10/26 01:20:16 - mmengine - INFO - Epoch(train) [392][60/63] lr: 2.4785e-03 eta: 12:24:32 time: 0.5992 data_time: 0.0135 memory: 16131 loss: 1.6072 loss_prob: 0.8968 loss_thr: 0.5604 loss_db: 0.1500 2022/10/26 01:20:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:20:26 - mmengine - INFO - Epoch(train) [393][5/63] lr: 2.4757e-03 eta: 12:24:32 time: 1.0451 data_time: 0.1999 memory: 16131 loss: 1.5156 loss_prob: 0.8409 loss_thr: 0.5343 loss_db: 0.1404 2022/10/26 01:20:31 - mmengine - INFO - Epoch(train) [393][10/63] lr: 2.4757e-03 eta: 12:24:24 time: 1.2806 data_time: 0.2000 memory: 16131 loss: 1.6774 loss_prob: 0.9477 loss_thr: 0.5737 loss_db: 0.1560 2022/10/26 01:20:37 - mmengine - INFO - Epoch(train) [393][15/63] lr: 2.4757e-03 eta: 12:24:24 time: 1.1403 data_time: 0.0097 memory: 16131 loss: 1.6997 loss_prob: 0.9689 loss_thr: 0.5719 loss_db: 0.1588 2022/10/26 01:20:42 - mmengine - INFO - Epoch(train) [393][20/63] lr: 2.4757e-03 eta: 12:24:19 time: 1.0777 data_time: 0.0106 memory: 16131 loss: 1.5601 loss_prob: 0.8662 loss_thr: 0.5488 loss_db: 0.1451 2022/10/26 01:20:45 - mmengine - INFO - Epoch(train) [393][25/63] lr: 2.4757e-03 eta: 12:24:19 time: 0.8310 data_time: 0.0205 memory: 16131 loss: 1.5437 loss_prob: 0.8680 loss_thr: 0.5341 loss_db: 0.1416 2022/10/26 01:20:48 - mmengine - INFO - Epoch(train) [393][30/63] lr: 2.4757e-03 eta: 12:24:06 time: 0.6612 data_time: 0.0307 memory: 16131 loss: 1.6223 loss_prob: 0.9362 loss_thr: 0.5361 loss_db: 0.1500 2022/10/26 01:20:52 - mmengine - INFO - Epoch(train) [393][35/63] lr: 2.4757e-03 eta: 12:24:06 time: 0.6536 data_time: 0.0200 memory: 16131 loss: 1.6050 loss_prob: 0.9288 loss_thr: 0.5264 loss_db: 0.1498 2022/10/26 01:20:56 - mmengine - INFO - Epoch(train) [393][40/63] lr: 2.4757e-03 eta: 12:23:55 time: 0.7729 data_time: 0.0112 memory: 16131 loss: 1.6278 loss_prob: 0.9359 loss_thr: 0.5381 loss_db: 0.1539 2022/10/26 01:21:00 - mmengine - INFO - Epoch(train) [393][45/63] lr: 2.4757e-03 eta: 12:23:55 time: 0.7943 data_time: 0.0124 memory: 16131 loss: 1.5853 loss_prob: 0.9005 loss_thr: 0.5345 loss_db: 0.1503 2022/10/26 01:21:03 - mmengine - INFO - Epoch(train) [393][50/63] lr: 2.4757e-03 eta: 12:23:42 time: 0.6936 data_time: 0.0192 memory: 16131 loss: 1.6896 loss_prob: 0.9861 loss_thr: 0.5432 loss_db: 0.1603 2022/10/26 01:21:10 - mmengine - INFO - Epoch(train) [393][55/63] lr: 2.4757e-03 eta: 12:23:42 time: 1.0231 data_time: 0.0209 memory: 16131 loss: 1.8689 loss_prob: 1.1084 loss_thr: 0.5799 loss_db: 0.1806 2022/10/26 01:21:14 - mmengine - INFO - Epoch(train) [393][60/63] lr: 2.4757e-03 eta: 12:23:39 time: 1.1563 data_time: 0.0101 memory: 16131 loss: 1.8862 loss_prob: 1.1096 loss_thr: 0.5947 loss_db: 0.1818 2022/10/26 01:21:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:21:21 - mmengine - INFO - Epoch(train) [394][5/63] lr: 2.4730e-03 eta: 12:23:39 time: 0.7897 data_time: 0.2259 memory: 16131 loss: 1.7093 loss_prob: 0.9772 loss_thr: 0.5654 loss_db: 0.1667 2022/10/26 01:21:24 - mmengine - INFO - Epoch(train) [394][10/63] lr: 2.4730e-03 eta: 12:23:21 time: 0.8259 data_time: 0.2237 memory: 16131 loss: 1.6434 loss_prob: 0.9233 loss_thr: 0.5694 loss_db: 0.1507 2022/10/26 01:21:28 - mmengine - INFO - Epoch(train) [394][15/63] lr: 2.4730e-03 eta: 12:23:21 time: 0.6440 data_time: 0.0115 memory: 16131 loss: 1.5015 loss_prob: 0.8334 loss_thr: 0.5325 loss_db: 0.1355 2022/10/26 01:21:34 - mmengine - INFO - Epoch(train) [394][20/63] lr: 2.4730e-03 eta: 12:23:14 time: 0.9461 data_time: 0.0130 memory: 16131 loss: 1.5614 loss_prob: 0.8834 loss_thr: 0.5265 loss_db: 0.1514 2022/10/26 01:21:36 - mmengine - INFO - Epoch(train) [394][25/63] lr: 2.4730e-03 eta: 12:23:14 time: 0.8518 data_time: 0.0318 memory: 16131 loss: 1.7286 loss_prob: 0.9929 loss_thr: 0.5670 loss_db: 0.1687 2022/10/26 01:21:39 - mmengine - INFO - Epoch(train) [394][30/63] lr: 2.4730e-03 eta: 12:22:59 time: 0.5702 data_time: 0.0308 memory: 16131 loss: 1.7053 loss_prob: 0.9699 loss_thr: 0.5747 loss_db: 0.1607 2022/10/26 01:21:45 - mmengine - INFO - Epoch(train) [394][35/63] lr: 2.4730e-03 eta: 12:22:59 time: 0.9008 data_time: 0.0062 memory: 16131 loss: 1.8223 loss_prob: 1.0541 loss_thr: 0.5946 loss_db: 0.1736 2022/10/26 01:21:51 - mmengine - INFO - Epoch(train) [394][40/63] lr: 2.4730e-03 eta: 12:22:57 time: 1.1911 data_time: 0.0080 memory: 16131 loss: 1.9016 loss_prob: 1.1071 loss_thr: 0.6104 loss_db: 0.1841 2022/10/26 01:21:54 - mmengine - INFO - Epoch(train) [394][45/63] lr: 2.4730e-03 eta: 12:22:57 time: 0.8706 data_time: 0.0130 memory: 16131 loss: 1.7963 loss_prob: 1.0253 loss_thr: 0.6011 loss_db: 0.1700 2022/10/26 01:21:59 - mmengine - INFO - Epoch(train) [394][50/63] lr: 2.4730e-03 eta: 12:22:45 time: 0.7518 data_time: 0.0370 memory: 16131 loss: 1.7274 loss_prob: 0.9832 loss_thr: 0.5839 loss_db: 0.1603 2022/10/26 01:22:02 - mmengine - INFO - Epoch(train) [394][55/63] lr: 2.4730e-03 eta: 12:22:45 time: 0.8294 data_time: 0.0314 memory: 16131 loss: 1.6666 loss_prob: 0.9475 loss_thr: 0.5624 loss_db: 0.1567 2022/10/26 01:22:07 - mmengine - INFO - Epoch(train) [394][60/63] lr: 2.4730e-03 eta: 12:22:35 time: 0.7951 data_time: 0.0053 memory: 16131 loss: 1.5790 loss_prob: 0.8893 loss_thr: 0.5400 loss_db: 0.1497 2022/10/26 01:22:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:22:14 - mmengine - INFO - Epoch(train) [395][5/63] lr: 2.4702e-03 eta: 12:22:35 time: 0.8865 data_time: 0.2101 memory: 16131 loss: 1.6398 loss_prob: 0.9304 loss_thr: 0.5518 loss_db: 0.1575 2022/10/26 01:22:17 - mmengine - INFO - Epoch(train) [395][10/63] lr: 2.4702e-03 eta: 12:22:16 time: 0.7932 data_time: 0.2047 memory: 16131 loss: 1.7133 loss_prob: 0.9912 loss_thr: 0.5573 loss_db: 0.1648 2022/10/26 01:22:19 - mmengine - INFO - Epoch(train) [395][15/63] lr: 2.4702e-03 eta: 12:22:16 time: 0.5486 data_time: 0.0065 memory: 16131 loss: 1.8132 loss_prob: 1.0645 loss_thr: 0.5805 loss_db: 0.1681 2022/10/26 01:22:22 - mmengine - INFO - Epoch(train) [395][20/63] lr: 2.4702e-03 eta: 12:22:01 time: 0.5671 data_time: 0.0053 memory: 16131 loss: 1.9744 loss_prob: 1.2063 loss_thr: 0.5811 loss_db: 0.1870 2022/10/26 01:22:27 - mmengine - INFO - Epoch(train) [395][25/63] lr: 2.4702e-03 eta: 12:22:01 time: 0.7473 data_time: 0.0093 memory: 16131 loss: 1.9087 loss_prob: 1.1471 loss_thr: 0.5764 loss_db: 0.1852 2022/10/26 01:22:32 - mmengine - INFO - Epoch(train) [395][30/63] lr: 2.4702e-03 eta: 12:21:54 time: 0.9365 data_time: 0.0597 memory: 16131 loss: 1.7318 loss_prob: 0.9856 loss_thr: 0.5787 loss_db: 0.1675 2022/10/26 01:22:35 - mmengine - INFO - Epoch(train) [395][35/63] lr: 2.4702e-03 eta: 12:21:54 time: 0.8515 data_time: 0.0558 memory: 16131 loss: 1.7288 loss_prob: 0.9853 loss_thr: 0.5775 loss_db: 0.1660 2022/10/26 01:22:41 - mmengine - INFO - Epoch(train) [395][40/63] lr: 2.4702e-03 eta: 12:21:46 time: 0.9414 data_time: 0.0093 memory: 16131 loss: 1.6571 loss_prob: 0.9421 loss_thr: 0.5578 loss_db: 0.1572 2022/10/26 01:22:44 - mmengine - INFO - Epoch(train) [395][45/63] lr: 2.4702e-03 eta: 12:21:46 time: 0.8764 data_time: 0.0103 memory: 16131 loss: 1.5953 loss_prob: 0.9090 loss_thr: 0.5341 loss_db: 0.1522 2022/10/26 01:22:47 - mmengine - INFO - Epoch(train) [395][50/63] lr: 2.4702e-03 eta: 12:21:32 time: 0.6030 data_time: 0.0128 memory: 16131 loss: 1.5836 loss_prob: 0.9099 loss_thr: 0.5225 loss_db: 0.1513 2022/10/26 01:22:50 - mmengine - INFO - Epoch(train) [395][55/63] lr: 2.4702e-03 eta: 12:21:32 time: 0.6102 data_time: 0.0236 memory: 16131 loss: 1.5590 loss_prob: 0.8819 loss_thr: 0.5318 loss_db: 0.1452 2022/10/26 01:22:56 - mmengine - INFO - Epoch(train) [395][60/63] lr: 2.4702e-03 eta: 12:21:23 time: 0.8741 data_time: 0.0175 memory: 16131 loss: 1.6443 loss_prob: 0.9311 loss_thr: 0.5607 loss_db: 0.1525 2022/10/26 01:22:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:23:03 - mmengine - INFO - Epoch(train) [396][5/63] lr: 2.4674e-03 eta: 12:21:23 time: 1.0155 data_time: 0.1762 memory: 16131 loss: 1.6885 loss_prob: 0.9691 loss_thr: 0.5586 loss_db: 0.1608 2022/10/26 01:23:08 - mmengine - INFO - Epoch(train) [396][10/63] lr: 2.4674e-03 eta: 12:21:09 time: 0.9944 data_time: 0.1882 memory: 16131 loss: 1.6954 loss_prob: 0.9876 loss_thr: 0.5481 loss_db: 0.1597 2022/10/26 01:23:11 - mmengine - INFO - Epoch(train) [396][15/63] lr: 2.4674e-03 eta: 12:21:09 time: 0.8396 data_time: 0.0176 memory: 16131 loss: 1.7135 loss_prob: 1.0002 loss_thr: 0.5556 loss_db: 0.1578 2022/10/26 01:23:17 - mmengine - INFO - Epoch(train) [396][20/63] lr: 2.4674e-03 eta: 12:20:59 time: 0.8405 data_time: 0.0096 memory: 16131 loss: 1.8320 loss_prob: 1.0803 loss_thr: 0.5776 loss_db: 0.1741 2022/10/26 01:23:21 - mmengine - INFO - Epoch(train) [396][25/63] lr: 2.4674e-03 eta: 12:20:59 time: 1.0341 data_time: 0.0153 memory: 16131 loss: 1.7751 loss_prob: 1.0220 loss_thr: 0.5836 loss_db: 0.1695 2022/10/26 01:23:26 - mmengine - INFO - Epoch(train) [396][30/63] lr: 2.4674e-03 eta: 12:20:52 time: 0.9656 data_time: 0.0321 memory: 16131 loss: 1.6735 loss_prob: 0.9588 loss_thr: 0.5549 loss_db: 0.1598 2022/10/26 01:23:29 - mmengine - INFO - Epoch(train) [396][35/63] lr: 2.4674e-03 eta: 12:20:52 time: 0.7536 data_time: 0.0276 memory: 16131 loss: 1.6787 loss_prob: 0.9723 loss_thr: 0.5471 loss_db: 0.1593 2022/10/26 01:23:33 - mmengine - INFO - Epoch(train) [396][40/63] lr: 2.4674e-03 eta: 12:20:39 time: 0.6406 data_time: 0.0097 memory: 16131 loss: 1.5677 loss_prob: 0.8848 loss_thr: 0.5380 loss_db: 0.1449 2022/10/26 01:23:37 - mmengine - INFO - Epoch(train) [396][45/63] lr: 2.4674e-03 eta: 12:20:39 time: 0.8243 data_time: 0.0106 memory: 16131 loss: 1.5470 loss_prob: 0.8706 loss_thr: 0.5327 loss_db: 0.1437 2022/10/26 01:23:40 - mmengine - INFO - Epoch(train) [396][50/63] lr: 2.4674e-03 eta: 12:20:27 time: 0.7341 data_time: 0.0161 memory: 16131 loss: 1.7108 loss_prob: 0.9799 loss_thr: 0.5687 loss_db: 0.1622 2022/10/26 01:23:46 - mmengine - INFO - Epoch(train) [396][55/63] lr: 2.4674e-03 eta: 12:20:27 time: 0.8737 data_time: 0.0242 memory: 16131 loss: 1.8638 loss_prob: 1.0923 loss_thr: 0.5885 loss_db: 0.1829 2022/10/26 01:23:49 - mmengine - INFO - Epoch(train) [396][60/63] lr: 2.4674e-03 eta: 12:20:18 time: 0.8767 data_time: 0.0150 memory: 16131 loss: 1.7156 loss_prob: 0.9905 loss_thr: 0.5570 loss_db: 0.1680 2022/10/26 01:23:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:23:57 - mmengine - INFO - Epoch(train) [397][5/63] lr: 2.4647e-03 eta: 12:20:18 time: 0.9574 data_time: 0.1793 memory: 16131 loss: 1.6423 loss_prob: 0.9353 loss_thr: 0.5516 loss_db: 0.1554 2022/10/26 01:24:01 - mmengine - INFO - Epoch(train) [397][10/63] lr: 2.4647e-03 eta: 12:20:05 time: 1.0326 data_time: 0.1872 memory: 16131 loss: 1.6320 loss_prob: 0.9204 loss_thr: 0.5561 loss_db: 0.1555 2022/10/26 01:24:03 - mmengine - INFO - Epoch(train) [397][15/63] lr: 2.4647e-03 eta: 12:20:05 time: 0.6078 data_time: 0.0167 memory: 16131 loss: 1.7508 loss_prob: 1.0112 loss_thr: 0.5696 loss_db: 0.1700 2022/10/26 01:24:06 - mmengine - INFO - Epoch(train) [397][20/63] lr: 2.4647e-03 eta: 12:19:48 time: 0.5106 data_time: 0.0075 memory: 16131 loss: 1.7668 loss_prob: 1.0417 loss_thr: 0.5524 loss_db: 0.1727 2022/10/26 01:24:11 - mmengine - INFO - Epoch(train) [397][25/63] lr: 2.4647e-03 eta: 12:19:48 time: 0.8195 data_time: 0.0379 memory: 16131 loss: 1.6448 loss_prob: 0.9490 loss_thr: 0.5375 loss_db: 0.1584 2022/10/26 01:24:15 - mmengine - INFO - Epoch(train) [397][30/63] lr: 2.4647e-03 eta: 12:19:39 time: 0.8674 data_time: 0.0548 memory: 16131 loss: 1.6729 loss_prob: 0.9602 loss_thr: 0.5510 loss_db: 0.1618 2022/10/26 01:24:18 - mmengine - INFO - Epoch(train) [397][35/63] lr: 2.4647e-03 eta: 12:19:39 time: 0.6750 data_time: 0.0253 memory: 16131 loss: 1.7679 loss_prob: 1.0426 loss_thr: 0.5581 loss_db: 0.1673 2022/10/26 01:24:22 - mmengine - INFO - Epoch(train) [397][40/63] lr: 2.4647e-03 eta: 12:19:28 time: 0.7453 data_time: 0.0093 memory: 16131 loss: 1.8010 loss_prob: 1.0896 loss_thr: 0.5365 loss_db: 0.1749 2022/10/26 01:24:29 - mmengine - INFO - Epoch(train) [397][45/63] lr: 2.4647e-03 eta: 12:19:28 time: 1.0809 data_time: 0.0076 memory: 16131 loss: 1.7899 loss_prob: 1.0729 loss_thr: 0.5427 loss_db: 0.1743 2022/10/26 01:24:35 - mmengine - INFO - Epoch(train) [397][50/63] lr: 2.4647e-03 eta: 12:19:28 time: 1.2929 data_time: 0.0167 memory: 16131 loss: 1.6911 loss_prob: 0.9686 loss_thr: 0.5617 loss_db: 0.1607 2022/10/26 01:24:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:24:40 - mmengine - INFO - Epoch(train) [397][55/63] lr: 2.4647e-03 eta: 12:19:28 time: 1.1028 data_time: 0.0235 memory: 16131 loss: 1.7457 loss_prob: 0.9910 loss_thr: 0.5888 loss_db: 0.1659 2022/10/26 01:24:43 - mmengine - INFO - Epoch(train) [397][60/63] lr: 2.4647e-03 eta: 12:19:17 time: 0.8090 data_time: 0.0140 memory: 16131 loss: 1.8442 loss_prob: 1.0682 loss_thr: 0.6032 loss_db: 0.1729 2022/10/26 01:24:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:24:53 - mmengine - INFO - Epoch(train) [398][5/63] lr: 2.4619e-03 eta: 12:19:17 time: 1.0987 data_time: 0.1754 memory: 16131 loss: 1.6623 loss_prob: 0.9448 loss_thr: 0.5595 loss_db: 0.1580 2022/10/26 01:24:57 - mmengine - INFO - Epoch(train) [398][10/63] lr: 2.4619e-03 eta: 12:19:08 time: 1.2490 data_time: 0.1798 memory: 16131 loss: 1.6120 loss_prob: 0.9133 loss_thr: 0.5464 loss_db: 0.1523 2022/10/26 01:25:00 - mmengine - INFO - Epoch(train) [398][15/63] lr: 2.4619e-03 eta: 12:19:08 time: 0.7588 data_time: 0.0158 memory: 16131 loss: 1.6513 loss_prob: 0.9349 loss_thr: 0.5610 loss_db: 0.1555 2022/10/26 01:25:05 - mmengine - INFO - Epoch(train) [398][20/63] lr: 2.4619e-03 eta: 12:18:58 time: 0.7965 data_time: 0.0063 memory: 16131 loss: 1.6664 loss_prob: 0.9465 loss_thr: 0.5656 loss_db: 0.1544 2022/10/26 01:25:09 - mmengine - INFO - Epoch(train) [398][25/63] lr: 2.4619e-03 eta: 12:18:58 time: 0.9050 data_time: 0.0125 memory: 16131 loss: 1.7263 loss_prob: 0.9905 loss_thr: 0.5728 loss_db: 0.1631 2022/10/26 01:25:13 - mmengine - INFO - Epoch(train) [398][30/63] lr: 2.4619e-03 eta: 12:18:47 time: 0.7632 data_time: 0.0270 memory: 16131 loss: 1.7113 loss_prob: 0.9791 loss_thr: 0.5687 loss_db: 0.1636 2022/10/26 01:25:15 - mmengine - INFO - Epoch(train) [398][35/63] lr: 2.4619e-03 eta: 12:18:47 time: 0.5718 data_time: 0.0273 memory: 16131 loss: 1.6030 loss_prob: 0.9093 loss_thr: 0.5425 loss_db: 0.1512 2022/10/26 01:25:20 - mmengine - INFO - Epoch(train) [398][40/63] lr: 2.4619e-03 eta: 12:18:35 time: 0.7486 data_time: 0.0165 memory: 16131 loss: 1.6627 loss_prob: 0.9518 loss_thr: 0.5512 loss_db: 0.1597 2022/10/26 01:25:24 - mmengine - INFO - Epoch(train) [398][45/63] lr: 2.4619e-03 eta: 12:18:35 time: 0.8785 data_time: 0.0086 memory: 16131 loss: 1.7926 loss_prob: 1.0456 loss_thr: 0.5685 loss_db: 0.1785 2022/10/26 01:25:26 - mmengine - INFO - Epoch(train) [398][50/63] lr: 2.4619e-03 eta: 12:18:22 time: 0.6484 data_time: 0.0171 memory: 16131 loss: 1.7478 loss_prob: 1.0147 loss_thr: 0.5603 loss_db: 0.1728 2022/10/26 01:25:29 - mmengine - INFO - Epoch(train) [398][55/63] lr: 2.4619e-03 eta: 12:18:22 time: 0.5464 data_time: 0.0249 memory: 16131 loss: 1.6417 loss_prob: 0.9333 loss_thr: 0.5525 loss_db: 0.1559 2022/10/26 01:25:33 - mmengine - INFO - Epoch(train) [398][60/63] lr: 2.4619e-03 eta: 12:18:09 time: 0.6550 data_time: 0.0129 memory: 16131 loss: 1.7151 loss_prob: 0.9864 loss_thr: 0.5692 loss_db: 0.1595 2022/10/26 01:25:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:25:41 - mmengine - INFO - Epoch(train) [399][5/63] lr: 2.4591e-03 eta: 12:18:09 time: 0.9795 data_time: 0.1886 memory: 16131 loss: 1.7998 loss_prob: 1.0491 loss_thr: 0.5819 loss_db: 0.1688 2022/10/26 01:25:46 - mmengine - INFO - Epoch(train) [399][10/63] lr: 2.4591e-03 eta: 12:17:58 time: 1.1520 data_time: 0.1885 memory: 16131 loss: 1.7528 loss_prob: 1.0147 loss_thr: 0.5779 loss_db: 0.1602 2022/10/26 01:25:49 - mmengine - INFO - Epoch(train) [399][15/63] lr: 2.4591e-03 eta: 12:17:58 time: 0.7887 data_time: 0.0068 memory: 16131 loss: 1.6474 loss_prob: 0.9362 loss_thr: 0.5612 loss_db: 0.1500 2022/10/26 01:25:52 - mmengine - INFO - Epoch(train) [399][20/63] lr: 2.4591e-03 eta: 12:17:44 time: 0.6300 data_time: 0.0081 memory: 16131 loss: 1.7146 loss_prob: 0.9818 loss_thr: 0.5769 loss_db: 0.1559 2022/10/26 01:25:56 - mmengine - INFO - Epoch(train) [399][25/63] lr: 2.4591e-03 eta: 12:17:44 time: 0.6485 data_time: 0.0176 memory: 16131 loss: 1.6850 loss_prob: 0.9602 loss_thr: 0.5691 loss_db: 0.1557 2022/10/26 01:26:01 - mmengine - INFO - Epoch(train) [399][30/63] lr: 2.4591e-03 eta: 12:17:35 time: 0.8633 data_time: 0.0422 memory: 16131 loss: 1.7098 loss_prob: 0.9822 loss_thr: 0.5660 loss_db: 0.1616 2022/10/26 01:26:04 - mmengine - INFO - Epoch(train) [399][35/63] lr: 2.4591e-03 eta: 12:17:35 time: 0.8120 data_time: 0.0339 memory: 16131 loss: 1.6946 loss_prob: 0.9681 loss_thr: 0.5674 loss_db: 0.1591 2022/10/26 01:26:07 - mmengine - INFO - Epoch(train) [399][40/63] lr: 2.4591e-03 eta: 12:17:22 time: 0.6691 data_time: 0.0062 memory: 16131 loss: 1.6533 loss_prob: 0.9504 loss_thr: 0.5445 loss_db: 0.1584 2022/10/26 01:26:11 - mmengine - INFO - Epoch(train) [399][45/63] lr: 2.4591e-03 eta: 12:17:22 time: 0.7729 data_time: 0.0090 memory: 16131 loss: 1.5752 loss_prob: 0.8920 loss_thr: 0.5358 loss_db: 0.1473 2022/10/26 01:26:14 - mmengine - INFO - Epoch(train) [399][50/63] lr: 2.4591e-03 eta: 12:17:09 time: 0.6773 data_time: 0.0204 memory: 16131 loss: 1.5019 loss_prob: 0.8305 loss_thr: 0.5348 loss_db: 0.1366 2022/10/26 01:26:17 - mmengine - INFO - Epoch(train) [399][55/63] lr: 2.4591e-03 eta: 12:17:09 time: 0.5310 data_time: 0.0230 memory: 16131 loss: 1.5348 loss_prob: 0.8566 loss_thr: 0.5334 loss_db: 0.1449 2022/10/26 01:26:19 - mmengine - INFO - Epoch(train) [399][60/63] lr: 2.4591e-03 eta: 12:16:53 time: 0.5268 data_time: 0.0146 memory: 16131 loss: 1.5874 loss_prob: 0.8917 loss_thr: 0.5451 loss_db: 0.1506 2022/10/26 01:26:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:26:30 - mmengine - INFO - Epoch(train) [400][5/63] lr: 2.4564e-03 eta: 12:16:53 time: 1.1905 data_time: 0.1639 memory: 16131 loss: 1.6459 loss_prob: 0.9319 loss_thr: 0.5604 loss_db: 0.1536 2022/10/26 01:26:33 - mmengine - INFO - Epoch(train) [400][10/63] lr: 2.4564e-03 eta: 12:16:42 time: 1.1145 data_time: 0.1783 memory: 16131 loss: 1.5647 loss_prob: 0.8784 loss_thr: 0.5398 loss_db: 0.1465 2022/10/26 01:26:37 - mmengine - INFO - Epoch(train) [400][15/63] lr: 2.4564e-03 eta: 12:16:42 time: 0.6311 data_time: 0.0203 memory: 16131 loss: 1.6111 loss_prob: 0.9154 loss_thr: 0.5396 loss_db: 0.1561 2022/10/26 01:26:40 - mmengine - INFO - Epoch(train) [400][20/63] lr: 2.4564e-03 eta: 12:16:30 time: 0.7359 data_time: 0.0117 memory: 16131 loss: 1.5594 loss_prob: 0.8855 loss_thr: 0.5238 loss_db: 0.1501 2022/10/26 01:26:44 - mmengine - INFO - Epoch(train) [400][25/63] lr: 2.4564e-03 eta: 12:16:30 time: 0.6984 data_time: 0.0227 memory: 16131 loss: 1.5700 loss_prob: 0.8841 loss_thr: 0.5370 loss_db: 0.1489 2022/10/26 01:26:48 - mmengine - INFO - Epoch(train) [400][30/63] lr: 2.4564e-03 eta: 12:16:19 time: 0.7561 data_time: 0.0205 memory: 16131 loss: 1.6037 loss_prob: 0.8994 loss_thr: 0.5547 loss_db: 0.1496 2022/10/26 01:26:52 - mmengine - INFO - Epoch(train) [400][35/63] lr: 2.4564e-03 eta: 12:16:19 time: 0.8254 data_time: 0.0178 memory: 16131 loss: 1.6730 loss_prob: 0.9476 loss_thr: 0.5686 loss_db: 0.1568 2022/10/26 01:26:54 - mmengine - INFO - Epoch(train) [400][40/63] lr: 2.4564e-03 eta: 12:16:05 time: 0.6422 data_time: 0.0209 memory: 16131 loss: 1.6347 loss_prob: 0.9292 loss_thr: 0.5502 loss_db: 0.1553 2022/10/26 01:26:57 - mmengine - INFO - Epoch(train) [400][45/63] lr: 2.4564e-03 eta: 12:16:05 time: 0.5356 data_time: 0.0119 memory: 16131 loss: 1.5166 loss_prob: 0.8448 loss_thr: 0.5314 loss_db: 0.1404 2022/10/26 01:27:01 - mmengine - INFO - Epoch(train) [400][50/63] lr: 2.4564e-03 eta: 12:15:53 time: 0.7107 data_time: 0.0168 memory: 16131 loss: 1.5782 loss_prob: 0.8716 loss_thr: 0.5629 loss_db: 0.1437 2022/10/26 01:27:04 - mmengine - INFO - Epoch(train) [400][55/63] lr: 2.4564e-03 eta: 12:15:53 time: 0.7191 data_time: 0.0207 memory: 16131 loss: 1.5676 loss_prob: 0.8651 loss_thr: 0.5584 loss_db: 0.1440 2022/10/26 01:27:08 - mmengine - INFO - Epoch(train) [400][60/63] lr: 2.4564e-03 eta: 12:15:40 time: 0.6223 data_time: 0.0142 memory: 16131 loss: 1.5759 loss_prob: 0.8702 loss_thr: 0.5573 loss_db: 0.1483 2022/10/26 01:27:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:27:09 - mmengine - INFO - Saving checkpoint at 400 epochs 2022/10/26 01:27:16 - mmengine - INFO - Epoch(val) [400][5/32] eta: 12:15:40 time: 0.5276 data_time: 0.0636 memory: 16131 2022/10/26 01:27:19 - mmengine - INFO - Epoch(val) [400][10/32] eta: 0:00:12 time: 0.5875 data_time: 0.0932 memory: 15724 2022/10/26 01:27:21 - mmengine - INFO - Epoch(val) [400][15/32] eta: 0:00:12 time: 0.5351 data_time: 0.0453 memory: 15724 2022/10/26 01:27:24 - mmengine - INFO - Epoch(val) [400][20/32] eta: 0:00:06 time: 0.5333 data_time: 0.0470 memory: 15724 2022/10/26 01:27:27 - mmengine - INFO - Epoch(val) [400][25/32] eta: 0:00:06 time: 0.5638 data_time: 0.0473 memory: 15724 2022/10/26 01:27:30 - mmengine - INFO - Epoch(val) [400][30/32] eta: 0:00:01 time: 0.5462 data_time: 0.0249 memory: 15724 2022/10/26 01:27:30 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8151, precision: 0.7752, hmean: 0.7946 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8151, precision: 0.8295, hmean: 0.8222 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8122, precision: 0.8647, hmean: 0.8376 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8007, precision: 0.8970, hmean: 0.8461 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7492, precision: 0.9262, hmean: 0.8283 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4569, precision: 0.9743, hmean: 0.6221 2022/10/26 01:27:30 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0019, precision: 1.0000, hmean: 0.0038 2022/10/26 01:27:30 - mmengine - INFO - Epoch(val) [400][32/32] icdar/precision: 0.8970 icdar/recall: 0.8007 icdar/hmean: 0.8461 2022/10/26 01:27:36 - mmengine - INFO - Epoch(train) [401][5/63] lr: 2.4536e-03 eta: 0:00:01 time: 0.9219 data_time: 0.2096 memory: 16131 loss: 1.6227 loss_prob: 0.9091 loss_thr: 0.5633 loss_db: 0.1503 2022/10/26 01:27:39 - mmengine - INFO - Epoch(train) [401][10/63] lr: 2.4536e-03 eta: 12:15:23 time: 0.8688 data_time: 0.2206 memory: 16131 loss: 1.6626 loss_prob: 0.9410 loss_thr: 0.5648 loss_db: 0.1568 2022/10/26 01:27:42 - mmengine - INFO - Epoch(train) [401][15/63] lr: 2.4536e-03 eta: 12:15:23 time: 0.5784 data_time: 0.0159 memory: 16131 loss: 1.6643 loss_prob: 0.9419 loss_thr: 0.5637 loss_db: 0.1588 2022/10/26 01:27:45 - mmengine - INFO - Epoch(train) [401][20/63] lr: 2.4536e-03 eta: 12:15:09 time: 0.6211 data_time: 0.0060 memory: 16131 loss: 1.5567 loss_prob: 0.8751 loss_thr: 0.5337 loss_db: 0.1479 2022/10/26 01:27:50 - mmengine - INFO - Epoch(train) [401][25/63] lr: 2.4536e-03 eta: 12:15:09 time: 0.7971 data_time: 0.0181 memory: 16131 loss: 1.6770 loss_prob: 0.9781 loss_thr: 0.5388 loss_db: 0.1602 2022/10/26 01:27:54 - mmengine - INFO - Epoch(train) [401][30/63] lr: 2.4536e-03 eta: 12:15:01 time: 0.9248 data_time: 0.0351 memory: 16131 loss: 1.7879 loss_prob: 1.0484 loss_thr: 0.5700 loss_db: 0.1695 2022/10/26 01:27:59 - mmengine - INFO - Epoch(train) [401][35/63] lr: 2.4536e-03 eta: 12:15:01 time: 0.9169 data_time: 0.0251 memory: 16131 loss: 1.6246 loss_prob: 0.9156 loss_thr: 0.5585 loss_db: 0.1505 2022/10/26 01:28:03 - mmengine - INFO - Epoch(train) [401][40/63] lr: 2.4536e-03 eta: 12:14:51 time: 0.8102 data_time: 0.0078 memory: 16131 loss: 1.5380 loss_prob: 0.8577 loss_thr: 0.5380 loss_db: 0.1423 2022/10/26 01:28:07 - mmengine - INFO - Epoch(train) [401][45/63] lr: 2.4536e-03 eta: 12:14:51 time: 0.8103 data_time: 0.0053 memory: 16131 loss: 1.5104 loss_prob: 0.8497 loss_thr: 0.5215 loss_db: 0.1392 2022/10/26 01:28:10 - mmengine - INFO - Epoch(train) [401][50/63] lr: 2.4536e-03 eta: 12:14:40 time: 0.7499 data_time: 0.0143 memory: 16131 loss: 1.5468 loss_prob: 0.8731 loss_thr: 0.5328 loss_db: 0.1410 2022/10/26 01:28:15 - mmengine - INFO - Epoch(train) [401][55/63] lr: 2.4536e-03 eta: 12:14:40 time: 0.7778 data_time: 0.0328 memory: 16131 loss: 1.7192 loss_prob: 0.9876 loss_thr: 0.5733 loss_db: 0.1583 2022/10/26 01:28:20 - mmengine - INFO - Epoch(train) [401][60/63] lr: 2.4536e-03 eta: 12:14:33 time: 0.9778 data_time: 0.0248 memory: 16131 loss: 1.7217 loss_prob: 0.9787 loss_thr: 0.5835 loss_db: 0.1595 2022/10/26 01:28:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:28:31 - mmengine - INFO - Epoch(train) [402][5/63] lr: 2.4509e-03 eta: 12:14:33 time: 1.2029 data_time: 0.2413 memory: 16131 loss: 1.6366 loss_prob: 0.9280 loss_thr: 0.5548 loss_db: 0.1538 2022/10/26 01:28:37 - mmengine - INFO - Epoch(train) [402][10/63] lr: 2.4509e-03 eta: 12:14:31 time: 1.5791 data_time: 0.2426 memory: 16131 loss: 1.5355 loss_prob: 0.8561 loss_thr: 0.5358 loss_db: 0.1436 2022/10/26 01:28:41 - mmengine - INFO - Epoch(train) [402][15/63] lr: 2.4509e-03 eta: 12:14:31 time: 1.0607 data_time: 0.0122 memory: 16131 loss: 1.5970 loss_prob: 0.8950 loss_thr: 0.5532 loss_db: 0.1488 2022/10/26 01:28:47 - mmengine - INFO - Epoch(train) [402][20/63] lr: 2.4509e-03 eta: 12:14:25 time: 1.0185 data_time: 0.0102 memory: 16131 loss: 1.6542 loss_prob: 0.9334 loss_thr: 0.5668 loss_db: 0.1540 2022/10/26 01:28:52 - mmengine - INFO - Epoch(train) [402][25/63] lr: 2.4509e-03 eta: 12:14:25 time: 1.0380 data_time: 0.0170 memory: 16131 loss: 1.6023 loss_prob: 0.8917 loss_thr: 0.5623 loss_db: 0.1482 2022/10/26 01:28:55 - mmengine - INFO - Epoch(train) [402][30/63] lr: 2.4509e-03 eta: 12:14:13 time: 0.7274 data_time: 0.0274 memory: 16131 loss: 1.6072 loss_prob: 0.8927 loss_thr: 0.5671 loss_db: 0.1475 2022/10/26 01:28:58 - mmengine - INFO - Epoch(train) [402][35/63] lr: 2.4509e-03 eta: 12:14:13 time: 0.6159 data_time: 0.0253 memory: 16131 loss: 1.5617 loss_prob: 0.8654 loss_thr: 0.5511 loss_db: 0.1452 2022/10/26 01:29:01 - mmengine - INFO - Epoch(train) [402][40/63] lr: 2.4509e-03 eta: 12:13:59 time: 0.6392 data_time: 0.0121 memory: 16131 loss: 1.6135 loss_prob: 0.9074 loss_thr: 0.5554 loss_db: 0.1507 2022/10/26 01:29:07 - mmengine - INFO - Epoch(train) [402][45/63] lr: 2.4509e-03 eta: 12:13:59 time: 0.8831 data_time: 0.0044 memory: 16131 loss: 1.6851 loss_prob: 0.9758 loss_thr: 0.5547 loss_db: 0.1546 2022/10/26 01:29:11 - mmengine - INFO - Epoch(train) [402][50/63] lr: 2.4509e-03 eta: 12:13:54 time: 1.0325 data_time: 0.0176 memory: 16131 loss: 1.6237 loss_prob: 0.9331 loss_thr: 0.5397 loss_db: 0.1508 2022/10/26 01:29:14 - mmengine - INFO - Epoch(train) [402][55/63] lr: 2.4509e-03 eta: 12:13:54 time: 0.7173 data_time: 0.0180 memory: 16131 loss: 1.5113 loss_prob: 0.8459 loss_thr: 0.5227 loss_db: 0.1427 2022/10/26 01:29:16 - mmengine - INFO - Epoch(train) [402][60/63] lr: 2.4509e-03 eta: 12:13:38 time: 0.4974 data_time: 0.0076 memory: 16131 loss: 1.4676 loss_prob: 0.8181 loss_thr: 0.5126 loss_db: 0.1369 2022/10/26 01:29:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:29:23 - mmengine - INFO - Epoch(train) [403][5/63] lr: 2.4481e-03 eta: 12:13:38 time: 0.7330 data_time: 0.1849 memory: 16131 loss: 1.5170 loss_prob: 0.8517 loss_thr: 0.5236 loss_db: 0.1417 2022/10/26 01:29:26 - mmengine - INFO - Epoch(train) [403][10/63] lr: 2.4481e-03 eta: 12:13:20 time: 0.8209 data_time: 0.1934 memory: 16131 loss: 1.5491 loss_prob: 0.8717 loss_thr: 0.5326 loss_db: 0.1448 2022/10/26 01:29:29 - mmengine - INFO - Epoch(train) [403][15/63] lr: 2.4481e-03 eta: 12:13:20 time: 0.5860 data_time: 0.0152 memory: 16131 loss: 1.5435 loss_prob: 0.8700 loss_thr: 0.5287 loss_db: 0.1449 2022/10/26 01:29:31 - mmengine - INFO - Epoch(train) [403][20/63] lr: 2.4481e-03 eta: 12:13:04 time: 0.5378 data_time: 0.0068 memory: 16131 loss: 1.5016 loss_prob: 0.8298 loss_thr: 0.5332 loss_db: 0.1386 2022/10/26 01:29:34 - mmengine - INFO - Epoch(train) [403][25/63] lr: 2.4481e-03 eta: 12:13:04 time: 0.5089 data_time: 0.0137 memory: 16131 loss: 1.4573 loss_prob: 0.7999 loss_thr: 0.5236 loss_db: 0.1338 2022/10/26 01:29:37 - mmengine - INFO - Epoch(train) [403][30/63] lr: 2.4481e-03 eta: 12:12:50 time: 0.5740 data_time: 0.0316 memory: 16131 loss: 1.5430 loss_prob: 0.8703 loss_thr: 0.5259 loss_db: 0.1468 2022/10/26 01:29:42 - mmengine - INFO - Epoch(train) [403][35/63] lr: 2.4481e-03 eta: 12:12:50 time: 0.8107 data_time: 0.0315 memory: 16131 loss: 1.6209 loss_prob: 0.9400 loss_thr: 0.5240 loss_db: 0.1568 2022/10/26 01:29:45 - mmengine - INFO - Epoch(train) [403][40/63] lr: 2.4481e-03 eta: 12:12:39 time: 0.7761 data_time: 0.0138 memory: 16131 loss: 1.6527 loss_prob: 0.9626 loss_thr: 0.5360 loss_db: 0.1542 2022/10/26 01:29:47 - mmengine - INFO - Epoch(train) [403][45/63] lr: 2.4481e-03 eta: 12:12:39 time: 0.5430 data_time: 0.0069 memory: 16131 loss: 1.6568 loss_prob: 0.9445 loss_thr: 0.5602 loss_db: 0.1522 2022/10/26 01:29:50 - mmengine - INFO - Epoch(train) [403][50/63] lr: 2.4481e-03 eta: 12:12:23 time: 0.5259 data_time: 0.0182 memory: 16131 loss: 1.6127 loss_prob: 0.9123 loss_thr: 0.5473 loss_db: 0.1531 2022/10/26 01:29:53 - mmengine - INFO - Epoch(train) [403][55/63] lr: 2.4481e-03 eta: 12:12:23 time: 0.5368 data_time: 0.0266 memory: 16131 loss: 1.6173 loss_prob: 0.9169 loss_thr: 0.5483 loss_db: 0.1521 2022/10/26 01:29:58 - mmengine - INFO - Epoch(train) [403][60/63] lr: 2.4481e-03 eta: 12:12:12 time: 0.7693 data_time: 0.0145 memory: 16131 loss: 1.5246 loss_prob: 0.8624 loss_thr: 0.5218 loss_db: 0.1404 2022/10/26 01:29:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:30:08 - mmengine - INFO - Epoch(train) [404][5/63] lr: 2.4453e-03 eta: 12:12:12 time: 1.2679 data_time: 0.2030 memory: 16131 loss: 1.6663 loss_prob: 0.9516 loss_thr: 0.5550 loss_db: 0.1597 2022/10/26 01:30:14 - mmengine - INFO - Epoch(train) [404][10/63] lr: 2.4453e-03 eta: 12:12:06 time: 1.4048 data_time: 0.2140 memory: 16131 loss: 1.6070 loss_prob: 0.9074 loss_thr: 0.5480 loss_db: 0.1516 2022/10/26 01:30:17 - mmengine - INFO - Epoch(train) [404][15/63] lr: 2.4453e-03 eta: 12:12:06 time: 0.9361 data_time: 0.0172 memory: 16131 loss: 1.6555 loss_prob: 0.9309 loss_thr: 0.5713 loss_db: 0.1534 2022/10/26 01:30:23 - mmengine - INFO - Epoch(train) [404][20/63] lr: 2.4453e-03 eta: 12:11:58 time: 0.9094 data_time: 0.0057 memory: 16131 loss: 1.7164 loss_prob: 0.9576 loss_thr: 0.5983 loss_db: 0.1605 2022/10/26 01:30:28 - mmengine - INFO - Epoch(train) [404][25/63] lr: 2.4453e-03 eta: 12:11:58 time: 1.0639 data_time: 0.0198 memory: 16131 loss: 1.6556 loss_prob: 0.9289 loss_thr: 0.5722 loss_db: 0.1545 2022/10/26 01:30:33 - mmengine - INFO - Epoch(train) [404][30/63] lr: 2.4453e-03 eta: 12:11:52 time: 1.0210 data_time: 0.0354 memory: 16131 loss: 1.5990 loss_prob: 0.9115 loss_thr: 0.5397 loss_db: 0.1477 2022/10/26 01:30:37 - mmengine - INFO - Epoch(train) [404][35/63] lr: 2.4453e-03 eta: 12:11:52 time: 0.9356 data_time: 0.0232 memory: 16131 loss: 1.6380 loss_prob: 0.9459 loss_thr: 0.5381 loss_db: 0.1540 2022/10/26 01:30:40 - mmengine - INFO - Epoch(train) [404][40/63] lr: 2.4453e-03 eta: 12:11:40 time: 0.7055 data_time: 0.0086 memory: 16131 loss: 1.5632 loss_prob: 0.8848 loss_thr: 0.5318 loss_db: 0.1466 2022/10/26 01:30:43 - mmengine - INFO - Epoch(train) [404][45/63] lr: 2.4453e-03 eta: 12:11:40 time: 0.5377 data_time: 0.0068 memory: 16131 loss: 1.4457 loss_prob: 0.7963 loss_thr: 0.5161 loss_db: 0.1333 2022/10/26 01:30:47 - mmengine - INFO - Epoch(train) [404][50/63] lr: 2.4453e-03 eta: 12:11:29 time: 0.7307 data_time: 0.0185 memory: 16131 loss: 1.5109 loss_prob: 0.8276 loss_thr: 0.5453 loss_db: 0.1380 2022/10/26 01:30:51 - mmengine - INFO - Epoch(train) [404][55/63] lr: 2.4453e-03 eta: 12:11:29 time: 0.8778 data_time: 0.0230 memory: 16131 loss: 1.6472 loss_prob: 0.9383 loss_thr: 0.5490 loss_db: 0.1599 2022/10/26 01:30:56 - mmengine - INFO - Epoch(train) [404][60/63] lr: 2.4453e-03 eta: 12:11:20 time: 0.8543 data_time: 0.0139 memory: 16131 loss: 1.8690 loss_prob: 1.1302 loss_thr: 0.5538 loss_db: 0.1850 2022/10/26 01:30:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:31:05 - mmengine - INFO - Epoch(train) [405][5/63] lr: 2.4426e-03 eta: 12:11:20 time: 1.1581 data_time: 0.1856 memory: 16131 loss: 1.7792 loss_prob: 1.0663 loss_thr: 0.5437 loss_db: 0.1692 2022/10/26 01:31:08 - mmengine - INFO - Epoch(train) [405][10/63] lr: 2.4426e-03 eta: 12:11:04 time: 0.9301 data_time: 0.1981 memory: 16131 loss: 1.6320 loss_prob: 0.9422 loss_thr: 0.5357 loss_db: 0.1541 2022/10/26 01:31:11 - mmengine - INFO - Epoch(train) [405][15/63] lr: 2.4426e-03 eta: 12:11:04 time: 0.6752 data_time: 0.0227 memory: 16131 loss: 1.7039 loss_prob: 0.9846 loss_thr: 0.5563 loss_db: 0.1630 2022/10/26 01:31:14 - mmengine - INFO - Epoch(train) [405][20/63] lr: 2.4426e-03 eta: 12:10:51 time: 0.6752 data_time: 0.0104 memory: 16131 loss: 1.6261 loss_prob: 0.9303 loss_thr: 0.5403 loss_db: 0.1556 2022/10/26 01:31:17 - mmengine - INFO - Epoch(train) [405][25/63] lr: 2.4426e-03 eta: 12:10:51 time: 0.6033 data_time: 0.0271 memory: 16131 loss: 1.6445 loss_prob: 0.9389 loss_thr: 0.5479 loss_db: 0.1578 2022/10/26 01:31:20 - mmengine - INFO - Epoch(train) [405][30/63] lr: 2.4426e-03 eta: 12:10:37 time: 0.5937 data_time: 0.0485 memory: 16131 loss: 1.7411 loss_prob: 0.9965 loss_thr: 0.5792 loss_db: 0.1654 2022/10/26 01:31:24 - mmengine - INFO - Epoch(train) [405][35/63] lr: 2.4426e-03 eta: 12:10:37 time: 0.6881 data_time: 0.0340 memory: 16131 loss: 1.8430 loss_prob: 1.0870 loss_thr: 0.5799 loss_db: 0.1761 2022/10/26 01:31:27 - mmengine - INFO - Epoch(train) [405][40/63] lr: 2.4426e-03 eta: 12:10:24 time: 0.6595 data_time: 0.0154 memory: 16131 loss: 1.7387 loss_prob: 1.0168 loss_thr: 0.5544 loss_db: 0.1675 2022/10/26 01:31:29 - mmengine - INFO - Epoch(train) [405][45/63] lr: 2.4426e-03 eta: 12:10:24 time: 0.5094 data_time: 0.0090 memory: 16131 loss: 1.6612 loss_prob: 0.9459 loss_thr: 0.5578 loss_db: 0.1574 2022/10/26 01:31:33 - mmengine - INFO - Epoch(train) [405][50/63] lr: 2.4426e-03 eta: 12:10:09 time: 0.5669 data_time: 0.0223 memory: 16131 loss: 1.7279 loss_prob: 0.9853 loss_thr: 0.5813 loss_db: 0.1613 2022/10/26 01:31:35 - mmengine - INFO - Epoch(train) [405][55/63] lr: 2.4426e-03 eta: 12:10:09 time: 0.5969 data_time: 0.0217 memory: 16131 loss: 1.7490 loss_prob: 1.0214 loss_thr: 0.5643 loss_db: 0.1633 2022/10/26 01:31:38 - mmengine - INFO - Epoch(train) [405][60/63] lr: 2.4426e-03 eta: 12:09:54 time: 0.5489 data_time: 0.0132 memory: 16131 loss: 1.6769 loss_prob: 0.9668 loss_thr: 0.5514 loss_db: 0.1586 2022/10/26 01:31:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:31:47 - mmengine - INFO - Epoch(train) [406][5/63] lr: 2.4398e-03 eta: 12:09:54 time: 0.9443 data_time: 0.2069 memory: 16131 loss: 1.6274 loss_prob: 0.9249 loss_thr: 0.5486 loss_db: 0.1538 2022/10/26 01:31:49 - mmengine - INFO - Epoch(train) [406][10/63] lr: 2.4398e-03 eta: 12:09:38 time: 0.8742 data_time: 0.2075 memory: 16131 loss: 1.6640 loss_prob: 0.9533 loss_thr: 0.5516 loss_db: 0.1592 2022/10/26 01:31:54 - mmengine - INFO - Epoch(train) [406][15/63] lr: 2.4398e-03 eta: 12:09:38 time: 0.7164 data_time: 0.0135 memory: 16131 loss: 1.5573 loss_prob: 0.8825 loss_thr: 0.5257 loss_db: 0.1490 2022/10/26 01:31:57 - mmengine - INFO - Epoch(train) [406][20/63] lr: 2.4398e-03 eta: 12:09:27 time: 0.7761 data_time: 0.0110 memory: 16131 loss: 1.5458 loss_prob: 0.8847 loss_thr: 0.5140 loss_db: 0.1471 2022/10/26 01:32:00 - mmengine - INFO - Epoch(train) [406][25/63] lr: 2.4398e-03 eta: 12:09:27 time: 0.6120 data_time: 0.0287 memory: 16131 loss: 1.6041 loss_prob: 0.9198 loss_thr: 0.5354 loss_db: 0.1489 2022/10/26 01:32:05 - mmengine - INFO - Epoch(train) [406][30/63] lr: 2.4398e-03 eta: 12:09:18 time: 0.8460 data_time: 0.0318 memory: 16131 loss: 1.5795 loss_prob: 0.8849 loss_thr: 0.5503 loss_db: 0.1444 2022/10/26 01:32:09 - mmengine - INFO - Epoch(train) [406][35/63] lr: 2.4398e-03 eta: 12:09:18 time: 0.9076 data_time: 0.0183 memory: 16131 loss: 1.6958 loss_prob: 0.9836 loss_thr: 0.5501 loss_db: 0.1620 2022/10/26 01:32:13 - mmengine - INFO - Epoch(train) [406][40/63] lr: 2.4398e-03 eta: 12:09:06 time: 0.7421 data_time: 0.0153 memory: 16131 loss: 1.7886 loss_prob: 1.0561 loss_thr: 0.5582 loss_db: 0.1743 2022/10/26 01:32:17 - mmengine - INFO - Epoch(train) [406][45/63] lr: 2.4398e-03 eta: 12:09:06 time: 0.8283 data_time: 0.0047 memory: 16131 loss: 1.6780 loss_prob: 0.9577 loss_thr: 0.5597 loss_db: 0.1607 2022/10/26 01:32:23 - mmengine - INFO - Epoch(train) [406][50/63] lr: 2.4398e-03 eta: 12:09:00 time: 1.0022 data_time: 0.0190 memory: 16131 loss: 1.6474 loss_prob: 0.9269 loss_thr: 0.5638 loss_db: 0.1567 2022/10/26 01:32:27 - mmengine - INFO - Epoch(train) [406][55/63] lr: 2.4398e-03 eta: 12:09:00 time: 1.0173 data_time: 0.0215 memory: 16131 loss: 1.5976 loss_prob: 0.9028 loss_thr: 0.5448 loss_db: 0.1500 2022/10/26 01:32:30 - mmengine - INFO - Epoch(train) [406][60/63] lr: 2.4398e-03 eta: 12:08:49 time: 0.7494 data_time: 0.0103 memory: 16131 loss: 1.6257 loss_prob: 0.9259 loss_thr: 0.5479 loss_db: 0.1518 2022/10/26 01:32:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:32:40 - mmengine - INFO - Epoch(train) [407][5/63] lr: 2.4370e-03 eta: 12:08:49 time: 1.0426 data_time: 0.2280 memory: 16131 loss: 1.5138 loss_prob: 0.8407 loss_thr: 0.5327 loss_db: 0.1404 2022/10/26 01:32:44 - mmengine - INFO - Epoch(train) [407][10/63] lr: 2.4370e-03 eta: 12:08:38 time: 1.1773 data_time: 0.2252 memory: 16131 loss: 1.6047 loss_prob: 0.9034 loss_thr: 0.5507 loss_db: 0.1506 2022/10/26 01:32:49 - mmengine - INFO - Epoch(train) [407][15/63] lr: 2.4370e-03 eta: 12:08:38 time: 0.9090 data_time: 0.0051 memory: 16131 loss: 1.5779 loss_prob: 0.8678 loss_thr: 0.5664 loss_db: 0.1437 2022/10/26 01:32:53 - mmengine - INFO - Epoch(train) [407][20/63] lr: 2.4370e-03 eta: 12:08:31 time: 0.9396 data_time: 0.0061 memory: 16131 loss: 1.5054 loss_prob: 0.8225 loss_thr: 0.5477 loss_db: 0.1352 2022/10/26 01:33:00 - mmengine - INFO - Epoch(train) [407][25/63] lr: 2.4370e-03 eta: 12:08:31 time: 1.1516 data_time: 0.0367 memory: 16131 loss: 1.5330 loss_prob: 0.8540 loss_thr: 0.5381 loss_db: 0.1409 2022/10/26 01:33:04 - mmengine - INFO - Epoch(train) [407][30/63] lr: 2.4370e-03 eta: 12:08:27 time: 1.0949 data_time: 0.0571 memory: 16131 loss: 1.5503 loss_prob: 0.8699 loss_thr: 0.5384 loss_db: 0.1420 2022/10/26 01:33:07 - mmengine - INFO - Epoch(train) [407][35/63] lr: 2.4370e-03 eta: 12:08:27 time: 0.6548 data_time: 0.0288 memory: 16131 loss: 1.6921 loss_prob: 0.9793 loss_thr: 0.5571 loss_db: 0.1556 2022/10/26 01:33:11 - mmengine - INFO - Epoch(train) [407][40/63] lr: 2.4370e-03 eta: 12:08:15 time: 0.7203 data_time: 0.0074 memory: 16131 loss: 1.7577 loss_prob: 1.0183 loss_thr: 0.5724 loss_db: 0.1670 2022/10/26 01:33:16 - mmengine - INFO - Epoch(train) [407][45/63] lr: 2.4370e-03 eta: 12:08:15 time: 0.8891 data_time: 0.0043 memory: 16131 loss: 1.7492 loss_prob: 1.0173 loss_thr: 0.5657 loss_db: 0.1663 2022/10/26 01:33:19 - mmengine - INFO - Epoch(train) [407][50/63] lr: 2.4370e-03 eta: 12:08:04 time: 0.7792 data_time: 0.0183 memory: 16131 loss: 1.6409 loss_prob: 0.9491 loss_thr: 0.5419 loss_db: 0.1499 2022/10/26 01:33:21 - mmengine - INFO - Epoch(train) [407][55/63] lr: 2.4370e-03 eta: 12:08:04 time: 0.5766 data_time: 0.0219 memory: 16131 loss: 1.5782 loss_prob: 0.8993 loss_thr: 0.5324 loss_db: 0.1465 2022/10/26 01:33:24 - mmengine - INFO - Epoch(train) [407][60/63] lr: 2.4370e-03 eta: 12:07:49 time: 0.5329 data_time: 0.0077 memory: 16131 loss: 1.7027 loss_prob: 0.9792 loss_thr: 0.5576 loss_db: 0.1659 2022/10/26 01:33:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:33:32 - mmengine - INFO - Epoch(train) [408][5/63] lr: 2.4343e-03 eta: 12:07:49 time: 0.8600 data_time: 0.1670 memory: 16131 loss: 1.9188 loss_prob: 1.1414 loss_thr: 0.5973 loss_db: 0.1801 2022/10/26 01:33:35 - mmengine - INFO - Epoch(train) [408][10/63] lr: 2.4343e-03 eta: 12:07:34 time: 0.9385 data_time: 0.1704 memory: 16131 loss: 1.9513 loss_prob: 1.1480 loss_thr: 0.6209 loss_db: 0.1824 2022/10/26 01:33:40 - mmengine - INFO - Epoch(train) [408][15/63] lr: 2.4343e-03 eta: 12:07:34 time: 0.7818 data_time: 0.0152 memory: 16131 loss: 1.8465 loss_prob: 1.0655 loss_thr: 0.6064 loss_db: 0.1746 2022/10/26 01:33:44 - mmengine - INFO - Epoch(train) [408][20/63] lr: 2.4343e-03 eta: 12:07:25 time: 0.8675 data_time: 0.0185 memory: 16131 loss: 1.7462 loss_prob: 1.0194 loss_thr: 0.5590 loss_db: 0.1678 2022/10/26 01:33:48 - mmengine - INFO - Epoch(train) [408][25/63] lr: 2.4343e-03 eta: 12:07:25 time: 0.8246 data_time: 0.0184 memory: 16131 loss: 1.7421 loss_prob: 1.0231 loss_thr: 0.5517 loss_db: 0.1673 2022/10/26 01:33:51 - mmengine - INFO - Epoch(train) [408][30/63] lr: 2.4343e-03 eta: 12:07:13 time: 0.7006 data_time: 0.0316 memory: 16131 loss: 1.7289 loss_prob: 0.9981 loss_thr: 0.5692 loss_db: 0.1617 2022/10/26 01:33:56 - mmengine - INFO - Epoch(train) [408][35/63] lr: 2.4343e-03 eta: 12:07:13 time: 0.7825 data_time: 0.0323 memory: 16131 loss: 1.7215 loss_prob: 0.9789 loss_thr: 0.5815 loss_db: 0.1612 2022/10/26 01:33:59 - mmengine - INFO - Epoch(train) [408][40/63] lr: 2.4343e-03 eta: 12:07:03 time: 0.8043 data_time: 0.0143 memory: 16131 loss: 1.7662 loss_prob: 1.0039 loss_thr: 0.5930 loss_db: 0.1692 2022/10/26 01:34:02 - mmengine - INFO - Epoch(train) [408][45/63] lr: 2.4343e-03 eta: 12:07:03 time: 0.5849 data_time: 0.0067 memory: 16131 loss: 1.6831 loss_prob: 0.9582 loss_thr: 0.5645 loss_db: 0.1604 2022/10/26 01:34:05 - mmengine - INFO - Epoch(train) [408][50/63] lr: 2.4343e-03 eta: 12:06:49 time: 0.6008 data_time: 0.0074 memory: 16131 loss: 1.5751 loss_prob: 0.8973 loss_thr: 0.5304 loss_db: 0.1475 2022/10/26 01:34:08 - mmengine - INFO - Epoch(train) [408][55/63] lr: 2.4343e-03 eta: 12:06:49 time: 0.6129 data_time: 0.0204 memory: 16131 loss: 1.6565 loss_prob: 0.9421 loss_thr: 0.5558 loss_db: 0.1586 2022/10/26 01:34:11 - mmengine - INFO - Epoch(train) [408][60/63] lr: 2.4343e-03 eta: 12:06:34 time: 0.5747 data_time: 0.0235 memory: 16131 loss: 1.6717 loss_prob: 0.9412 loss_thr: 0.5721 loss_db: 0.1584 2022/10/26 01:34:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:34:18 - mmengine - INFO - Epoch(train) [409][5/63] lr: 2.4315e-03 eta: 12:06:34 time: 0.8748 data_time: 0.2111 memory: 16131 loss: 1.6948 loss_prob: 0.9677 loss_thr: 0.5649 loss_db: 0.1622 2022/10/26 01:34:21 - mmengine - INFO - Epoch(train) [409][10/63] lr: 2.4315e-03 eta: 12:06:17 time: 0.8412 data_time: 0.2107 memory: 16131 loss: 1.7088 loss_prob: 0.9697 loss_thr: 0.5746 loss_db: 0.1646 2022/10/26 01:34:24 - mmengine - INFO - Epoch(train) [409][15/63] lr: 2.4315e-03 eta: 12:06:17 time: 0.5228 data_time: 0.0134 memory: 16131 loss: 1.7123 loss_prob: 0.9772 loss_thr: 0.5733 loss_db: 0.1618 2022/10/26 01:34:26 - mmengine - INFO - Epoch(train) [409][20/63] lr: 2.4315e-03 eta: 12:06:02 time: 0.5353 data_time: 0.0107 memory: 16131 loss: 1.6763 loss_prob: 0.9554 loss_thr: 0.5660 loss_db: 0.1549 2022/10/26 01:34:31 - mmengine - INFO - Epoch(train) [409][25/63] lr: 2.4315e-03 eta: 12:06:02 time: 0.7872 data_time: 0.0323 memory: 16131 loss: 1.7422 loss_prob: 1.0016 loss_thr: 0.5756 loss_db: 0.1650 2022/10/26 01:34:35 - mmengine - INFO - Epoch(train) [409][30/63] lr: 2.4315e-03 eta: 12:05:53 time: 0.8855 data_time: 0.0319 memory: 16131 loss: 1.8933 loss_prob: 1.1114 loss_thr: 0.5982 loss_db: 0.1837 2022/10/26 01:34:40 - mmengine - INFO - Epoch(train) [409][35/63] lr: 2.4315e-03 eta: 12:05:53 time: 0.8426 data_time: 0.0060 memory: 16131 loss: 1.8319 loss_prob: 1.0464 loss_thr: 0.6121 loss_db: 0.1734 2022/10/26 01:34:42 - mmengine - INFO - Epoch(train) [409][40/63] lr: 2.4315e-03 eta: 12:05:41 time: 0.7235 data_time: 0.0118 memory: 16131 loss: 1.6767 loss_prob: 0.9451 loss_thr: 0.5709 loss_db: 0.1607 2022/10/26 01:34:46 - mmengine - INFO - Epoch(train) [409][45/63] lr: 2.4315e-03 eta: 12:05:41 time: 0.5593 data_time: 0.0104 memory: 16131 loss: 1.5874 loss_prob: 0.9030 loss_thr: 0.5306 loss_db: 0.1538 2022/10/26 01:34:49 - mmengine - INFO - Epoch(train) [409][50/63] lr: 2.4315e-03 eta: 12:05:29 time: 0.6612 data_time: 0.0192 memory: 16131 loss: 1.6570 loss_prob: 0.9504 loss_thr: 0.5510 loss_db: 0.1557 2022/10/26 01:34:54 - mmengine - INFO - Epoch(train) [409][55/63] lr: 2.4315e-03 eta: 12:05:29 time: 0.8803 data_time: 0.0222 memory: 16131 loss: 1.6810 loss_prob: 0.9633 loss_thr: 0.5573 loss_db: 0.1604 2022/10/26 01:34:57 - mmengine - INFO - Epoch(train) [409][60/63] lr: 2.4315e-03 eta: 12:05:19 time: 0.8367 data_time: 0.0077 memory: 16131 loss: 1.6138 loss_prob: 0.9055 loss_thr: 0.5534 loss_db: 0.1548 2022/10/26 01:34:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:35:07 - mmengine - INFO - Epoch(train) [410][5/63] lr: 2.4287e-03 eta: 12:05:19 time: 1.1391 data_time: 0.1860 memory: 16131 loss: 1.5425 loss_prob: 0.8709 loss_thr: 0.5292 loss_db: 0.1424 2022/10/26 01:35:11 - mmengine - INFO - Epoch(train) [410][10/63] lr: 2.4287e-03 eta: 12:05:10 time: 1.2507 data_time: 0.1868 memory: 16131 loss: 1.5944 loss_prob: 0.9038 loss_thr: 0.5412 loss_db: 0.1494 2022/10/26 01:35:14 - mmengine - INFO - Epoch(train) [410][15/63] lr: 2.4287e-03 eta: 12:05:10 time: 0.6971 data_time: 0.0076 memory: 16131 loss: 1.6103 loss_prob: 0.9119 loss_thr: 0.5445 loss_db: 0.1539 2022/10/26 01:35:17 - mmengine - INFO - Epoch(train) [410][20/63] lr: 2.4287e-03 eta: 12:04:56 time: 0.5750 data_time: 0.0085 memory: 16131 loss: 1.5915 loss_prob: 0.9023 loss_thr: 0.5358 loss_db: 0.1534 2022/10/26 01:35:21 - mmengine - INFO - Epoch(train) [410][25/63] lr: 2.4287e-03 eta: 12:04:56 time: 0.6246 data_time: 0.0244 memory: 16131 loss: 1.6828 loss_prob: 0.9626 loss_thr: 0.5576 loss_db: 0.1626 2022/10/26 01:35:25 - mmengine - INFO - Epoch(train) [410][30/63] lr: 2.4287e-03 eta: 12:04:45 time: 0.7524 data_time: 0.0434 memory: 16131 loss: 1.6358 loss_prob: 0.9204 loss_thr: 0.5590 loss_db: 0.1564 2022/10/26 01:35:27 - mmengine - INFO - Epoch(train) [410][35/63] lr: 2.4287e-03 eta: 12:04:45 time: 0.6542 data_time: 0.0265 memory: 16131 loss: 1.6385 loss_prob: 0.9219 loss_thr: 0.5604 loss_db: 0.1562 2022/10/26 01:35:31 - mmengine - INFO - Epoch(train) [410][40/63] lr: 2.4287e-03 eta: 12:04:31 time: 0.6161 data_time: 0.0073 memory: 16131 loss: 1.5802 loss_prob: 0.8772 loss_thr: 0.5570 loss_db: 0.1459 2022/10/26 01:35:34 - mmengine - INFO - Epoch(train) [410][45/63] lr: 2.4287e-03 eta: 12:04:31 time: 0.7125 data_time: 0.0069 memory: 16131 loss: 1.5204 loss_prob: 0.8370 loss_thr: 0.5458 loss_db: 0.1376 2022/10/26 01:35:38 - mmengine - INFO - Epoch(train) [410][50/63] lr: 2.4287e-03 eta: 12:04:18 time: 0.6794 data_time: 0.0142 memory: 16131 loss: 1.5833 loss_prob: 0.8874 loss_thr: 0.5499 loss_db: 0.1460 2022/10/26 01:35:41 - mmengine - INFO - Epoch(train) [410][55/63] lr: 2.4287e-03 eta: 12:04:18 time: 0.6348 data_time: 0.0249 memory: 16131 loss: 1.5702 loss_prob: 0.8779 loss_thr: 0.5468 loss_db: 0.1455 2022/10/26 01:35:43 - mmengine - INFO - Epoch(train) [410][60/63] lr: 2.4287e-03 eta: 12:04:04 time: 0.5656 data_time: 0.0164 memory: 16131 loss: 1.5990 loss_prob: 0.8928 loss_thr: 0.5538 loss_db: 0.1524 2022/10/26 01:35:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:35:51 - mmengine - INFO - Epoch(train) [411][5/63] lr: 2.4260e-03 eta: 12:04:04 time: 0.8940 data_time: 0.1858 memory: 16131 loss: 1.5905 loss_prob: 0.9007 loss_thr: 0.5435 loss_db: 0.1462 2022/10/26 01:35:54 - mmengine - INFO - Epoch(train) [411][10/63] lr: 2.4260e-03 eta: 12:03:49 time: 0.9365 data_time: 0.1850 memory: 16131 loss: 1.5516 loss_prob: 0.8720 loss_thr: 0.5356 loss_db: 0.1441 2022/10/26 01:35:57 - mmengine - INFO - Epoch(train) [411][15/63] lr: 2.4260e-03 eta: 12:03:49 time: 0.6034 data_time: 0.0246 memory: 16131 loss: 1.6381 loss_prob: 0.9235 loss_thr: 0.5553 loss_db: 0.1593 2022/10/26 01:36:01 - mmengine - INFO - Epoch(train) [411][20/63] lr: 2.4260e-03 eta: 12:03:36 time: 0.6987 data_time: 0.0267 memory: 16131 loss: 1.6032 loss_prob: 0.9009 loss_thr: 0.5488 loss_db: 0.1535 2022/10/26 01:36:06 - mmengine - INFO - Epoch(train) [411][25/63] lr: 2.4260e-03 eta: 12:03:36 time: 0.8992 data_time: 0.0233 memory: 16131 loss: 1.5982 loss_prob: 0.9025 loss_thr: 0.5484 loss_db: 0.1472 2022/10/26 01:36:10 - mmengine - INFO - Epoch(train) [411][30/63] lr: 2.4260e-03 eta: 12:03:29 time: 0.9230 data_time: 0.0519 memory: 16131 loss: 1.5906 loss_prob: 0.8971 loss_thr: 0.5459 loss_db: 0.1476 2022/10/26 01:36:13 - mmengine - INFO - Epoch(train) [411][35/63] lr: 2.4260e-03 eta: 12:03:29 time: 0.7129 data_time: 0.0360 memory: 16131 loss: 1.5287 loss_prob: 0.8463 loss_thr: 0.5410 loss_db: 0.1415 2022/10/26 01:36:17 - mmengine - INFO - Epoch(train) [411][40/63] lr: 2.4260e-03 eta: 12:03:16 time: 0.6624 data_time: 0.0116 memory: 16131 loss: 1.4992 loss_prob: 0.8274 loss_thr: 0.5322 loss_db: 0.1396 2022/10/26 01:36:20 - mmengine - INFO - Epoch(train) [411][45/63] lr: 2.4260e-03 eta: 12:03:16 time: 0.6568 data_time: 0.0115 memory: 16131 loss: 1.4811 loss_prob: 0.8241 loss_thr: 0.5183 loss_db: 0.1387 2022/10/26 01:36:22 - mmengine - INFO - Epoch(train) [411][50/63] lr: 2.4260e-03 eta: 12:03:01 time: 0.5529 data_time: 0.0161 memory: 16131 loss: 1.6265 loss_prob: 0.9163 loss_thr: 0.5560 loss_db: 0.1541 2022/10/26 01:36:25 - mmengine - INFO - Epoch(train) [411][55/63] lr: 2.4260e-03 eta: 12:03:01 time: 0.5221 data_time: 0.0259 memory: 16131 loss: 1.5983 loss_prob: 0.9083 loss_thr: 0.5366 loss_db: 0.1533 2022/10/26 01:36:28 - mmengine - INFO - Epoch(train) [411][60/63] lr: 2.4260e-03 eta: 12:02:46 time: 0.5336 data_time: 0.0176 memory: 16131 loss: 1.4918 loss_prob: 0.8452 loss_thr: 0.5035 loss_db: 0.1431 2022/10/26 01:36:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:36:37 - mmengine - INFO - Epoch(train) [412][5/63] lr: 2.4232e-03 eta: 12:02:46 time: 1.0588 data_time: 0.2384 memory: 16131 loss: 1.4809 loss_prob: 0.8285 loss_thr: 0.5107 loss_db: 0.1416 2022/10/26 01:36:40 - mmengine - INFO - Epoch(train) [412][10/63] lr: 2.4232e-03 eta: 12:02:31 time: 0.9559 data_time: 0.2378 memory: 16131 loss: 1.5861 loss_prob: 0.9007 loss_thr: 0.5375 loss_db: 0.1479 2022/10/26 01:36:44 - mmengine - INFO - Epoch(train) [412][15/63] lr: 2.4232e-03 eta: 12:02:31 time: 0.6250 data_time: 0.0069 memory: 16131 loss: 1.6389 loss_prob: 0.9308 loss_thr: 0.5539 loss_db: 0.1541 2022/10/26 01:36:46 - mmengine - INFO - Epoch(train) [412][20/63] lr: 2.4232e-03 eta: 12:02:17 time: 0.5765 data_time: 0.0057 memory: 16131 loss: 1.5785 loss_prob: 0.8915 loss_thr: 0.5407 loss_db: 0.1463 2022/10/26 01:36:52 - mmengine - INFO - Epoch(train) [412][25/63] lr: 2.4232e-03 eta: 12:02:17 time: 0.8609 data_time: 0.0464 memory: 16131 loss: 1.6171 loss_prob: 0.9173 loss_thr: 0.5508 loss_db: 0.1490 2022/10/26 01:36:55 - mmengine - INFO - Epoch(train) [412][30/63] lr: 2.4232e-03 eta: 12:02:08 time: 0.8964 data_time: 0.0524 memory: 16131 loss: 1.5728 loss_prob: 0.8748 loss_thr: 0.5501 loss_db: 0.1480 2022/10/26 01:37:00 - mmengine - INFO - Epoch(train) [412][35/63] lr: 2.4232e-03 eta: 12:02:08 time: 0.7339 data_time: 0.0121 memory: 16131 loss: 1.5489 loss_prob: 0.8700 loss_thr: 0.5323 loss_db: 0.1466 2022/10/26 01:37:02 - mmengine - INFO - Epoch(train) [412][40/63] lr: 2.4232e-03 eta: 12:01:56 time: 0.7044 data_time: 0.0051 memory: 16131 loss: 1.7050 loss_prob: 0.9865 loss_thr: 0.5562 loss_db: 0.1623 2022/10/26 01:37:05 - mmengine - INFO - Epoch(train) [412][45/63] lr: 2.4232e-03 eta: 12:01:56 time: 0.5308 data_time: 0.0062 memory: 16131 loss: 1.7467 loss_prob: 1.0120 loss_thr: 0.5702 loss_db: 0.1646 2022/10/26 01:37:08 - mmengine - INFO - Epoch(train) [412][50/63] lr: 2.4232e-03 eta: 12:01:42 time: 0.5867 data_time: 0.0250 memory: 16131 loss: 1.7146 loss_prob: 0.9961 loss_thr: 0.5594 loss_db: 0.1591 2022/10/26 01:37:11 - mmengine - INFO - Epoch(train) [412][55/63] lr: 2.4232e-03 eta: 12:01:42 time: 0.5859 data_time: 0.0248 memory: 16131 loss: 1.6614 loss_prob: 0.9574 loss_thr: 0.5484 loss_db: 0.1556 2022/10/26 01:37:14 - mmengine - INFO - Epoch(train) [412][60/63] lr: 2.4232e-03 eta: 12:01:29 time: 0.6107 data_time: 0.0059 memory: 16131 loss: 1.6153 loss_prob: 0.9191 loss_thr: 0.5412 loss_db: 0.1551 2022/10/26 01:37:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:37:23 - mmengine - INFO - Epoch(train) [413][5/63] lr: 2.4204e-03 eta: 12:01:29 time: 1.0294 data_time: 0.1555 memory: 16131 loss: 1.5695 loss_prob: 0.8883 loss_thr: 0.5373 loss_db: 0.1439 2022/10/26 01:37:27 - mmengine - INFO - Epoch(train) [413][10/63] lr: 2.4204e-03 eta: 12:01:15 time: 0.9964 data_time: 0.1683 memory: 16131 loss: 1.5447 loss_prob: 0.8630 loss_thr: 0.5348 loss_db: 0.1469 2022/10/26 01:37:29 - mmengine - INFO - Epoch(train) [413][15/63] lr: 2.4204e-03 eta: 12:01:15 time: 0.6501 data_time: 0.0179 memory: 16131 loss: 1.5833 loss_prob: 0.8865 loss_thr: 0.5396 loss_db: 0.1572 2022/10/26 01:37:32 - mmengine - INFO - Epoch(train) [413][20/63] lr: 2.4204e-03 eta: 12:01:00 time: 0.5373 data_time: 0.0122 memory: 16131 loss: 1.5455 loss_prob: 0.8631 loss_thr: 0.5319 loss_db: 0.1505 2022/10/26 01:37:36 - mmengine - INFO - Epoch(train) [413][25/63] lr: 2.4204e-03 eta: 12:01:00 time: 0.6682 data_time: 0.0283 memory: 16131 loss: 1.5825 loss_prob: 0.8767 loss_thr: 0.5585 loss_db: 0.1472 2022/10/26 01:37:40 - mmengine - INFO - Epoch(train) [413][30/63] lr: 2.4204e-03 eta: 12:00:49 time: 0.7998 data_time: 0.0339 memory: 16131 loss: 1.6339 loss_prob: 0.9180 loss_thr: 0.5651 loss_db: 0.1508 2022/10/26 01:37:43 - mmengine - INFO - Epoch(train) [413][35/63] lr: 2.4204e-03 eta: 12:00:49 time: 0.6986 data_time: 0.0289 memory: 16131 loss: 1.6295 loss_prob: 0.9294 loss_thr: 0.5481 loss_db: 0.1519 2022/10/26 01:37:46 - mmengine - INFO - Epoch(train) [413][40/63] lr: 2.4204e-03 eta: 12:00:35 time: 0.5684 data_time: 0.0170 memory: 16131 loss: 1.6233 loss_prob: 0.9220 loss_thr: 0.5507 loss_db: 0.1506 2022/10/26 01:37:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:37:48 - mmengine - INFO - Epoch(train) [413][45/63] lr: 2.4204e-03 eta: 12:00:35 time: 0.5319 data_time: 0.0065 memory: 16131 loss: 1.7128 loss_prob: 0.9828 loss_thr: 0.5653 loss_db: 0.1647 2022/10/26 01:37:51 - mmengine - INFO - Epoch(train) [413][50/63] lr: 2.4204e-03 eta: 12:00:19 time: 0.5192 data_time: 0.0151 memory: 16131 loss: 1.7340 loss_prob: 0.9883 loss_thr: 0.5777 loss_db: 0.1680 2022/10/26 01:37:54 - mmengine - INFO - Epoch(train) [413][55/63] lr: 2.4204e-03 eta: 12:00:19 time: 0.5292 data_time: 0.0229 memory: 16131 loss: 1.5614 loss_prob: 0.8668 loss_thr: 0.5506 loss_db: 0.1440 2022/10/26 01:37:56 - mmengine - INFO - Epoch(train) [413][60/63] lr: 2.4204e-03 eta: 12:00:05 time: 0.5489 data_time: 0.0196 memory: 16131 loss: 1.4799 loss_prob: 0.8262 loss_thr: 0.5141 loss_db: 0.1396 2022/10/26 01:37:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:38:07 - mmengine - INFO - Epoch(train) [414][5/63] lr: 2.4177e-03 eta: 12:00:05 time: 1.1799 data_time: 0.1820 memory: 16131 loss: 1.6228 loss_prob: 0.9061 loss_thr: 0.5623 loss_db: 0.1544 2022/10/26 01:38:12 - mmengine - INFO - Epoch(train) [414][10/63] lr: 2.4177e-03 eta: 11:59:58 time: 1.3731 data_time: 0.1890 memory: 16131 loss: 1.6240 loss_prob: 0.9101 loss_thr: 0.5600 loss_db: 0.1539 2022/10/26 01:38:15 - mmengine - INFO - Epoch(train) [414][15/63] lr: 2.4177e-03 eta: 11:59:58 time: 0.8109 data_time: 0.0132 memory: 16131 loss: 1.5325 loss_prob: 0.8478 loss_thr: 0.5390 loss_db: 0.1456 2022/10/26 01:38:20 - mmengine - INFO - Epoch(train) [414][20/63] lr: 2.4177e-03 eta: 11:59:46 time: 0.7222 data_time: 0.0081 memory: 16131 loss: 1.5728 loss_prob: 0.8900 loss_thr: 0.5317 loss_db: 0.1511 2022/10/26 01:38:24 - mmengine - INFO - Epoch(train) [414][25/63] lr: 2.4177e-03 eta: 11:59:46 time: 0.8835 data_time: 0.0266 memory: 16131 loss: 1.6012 loss_prob: 0.9279 loss_thr: 0.5238 loss_db: 0.1495 2022/10/26 01:38:27 - mmengine - INFO - Epoch(train) [414][30/63] lr: 2.4177e-03 eta: 11:59:35 time: 0.7288 data_time: 0.0283 memory: 16131 loss: 1.5808 loss_prob: 0.9053 loss_thr: 0.5314 loss_db: 0.1441 2022/10/26 01:38:29 - mmengine - INFO - Epoch(train) [414][35/63] lr: 2.4177e-03 eta: 11:59:35 time: 0.5460 data_time: 0.0140 memory: 16131 loss: 1.5332 loss_prob: 0.8682 loss_thr: 0.5168 loss_db: 0.1482 2022/10/26 01:38:34 - mmengine - INFO - Epoch(train) [414][40/63] lr: 2.4177e-03 eta: 11:59:23 time: 0.6863 data_time: 0.0120 memory: 16131 loss: 1.6464 loss_prob: 0.9602 loss_thr: 0.5267 loss_db: 0.1595 2022/10/26 01:38:38 - mmengine - INFO - Epoch(train) [414][45/63] lr: 2.4177e-03 eta: 11:59:23 time: 0.8299 data_time: 0.0158 memory: 16131 loss: 1.7100 loss_prob: 0.9964 loss_thr: 0.5527 loss_db: 0.1610 2022/10/26 01:38:42 - mmengine - INFO - Epoch(train) [414][50/63] lr: 2.4177e-03 eta: 11:59:12 time: 0.7843 data_time: 0.0247 memory: 16131 loss: 1.6285 loss_prob: 0.9232 loss_thr: 0.5533 loss_db: 0.1519 2022/10/26 01:38:45 - mmengine - INFO - Epoch(train) [414][55/63] lr: 2.4177e-03 eta: 11:59:12 time: 0.6967 data_time: 0.0240 memory: 16131 loss: 1.7437 loss_prob: 1.0088 loss_thr: 0.5701 loss_db: 0.1648 2022/10/26 01:38:47 - mmengine - INFO - Epoch(train) [414][60/63] lr: 2.4177e-03 eta: 11:58:58 time: 0.5869 data_time: 0.0173 memory: 16131 loss: 1.7110 loss_prob: 0.9918 loss_thr: 0.5556 loss_db: 0.1636 2022/10/26 01:38:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:38:57 - mmengine - INFO - Epoch(train) [415][5/63] lr: 2.4149e-03 eta: 11:58:58 time: 1.1226 data_time: 0.1665 memory: 16131 loss: 1.4971 loss_prob: 0.8270 loss_thr: 0.5311 loss_db: 0.1389 2022/10/26 01:39:02 - mmengine - INFO - Epoch(train) [415][10/63] lr: 2.4149e-03 eta: 11:58:50 time: 1.2957 data_time: 0.1881 memory: 16131 loss: 1.5859 loss_prob: 0.9026 loss_thr: 0.5340 loss_db: 0.1493 2022/10/26 01:39:05 - mmengine - INFO - Epoch(train) [415][15/63] lr: 2.4149e-03 eta: 11:58:50 time: 0.7553 data_time: 0.0321 memory: 16131 loss: 1.6064 loss_prob: 0.9198 loss_thr: 0.5328 loss_db: 0.1538 2022/10/26 01:39:08 - mmengine - INFO - Epoch(train) [415][20/63] lr: 2.4149e-03 eta: 11:58:36 time: 0.6009 data_time: 0.0062 memory: 16131 loss: 1.5475 loss_prob: 0.8689 loss_thr: 0.5335 loss_db: 0.1450 2022/10/26 01:39:13 - mmengine - INFO - Epoch(train) [415][25/63] lr: 2.4149e-03 eta: 11:58:36 time: 0.8259 data_time: 0.0105 memory: 16131 loss: 1.5537 loss_prob: 0.8807 loss_thr: 0.5293 loss_db: 0.1437 2022/10/26 01:39:16 - mmengine - INFO - Epoch(train) [415][30/63] lr: 2.4149e-03 eta: 11:58:27 time: 0.8261 data_time: 0.0155 memory: 16131 loss: 1.5199 loss_prob: 0.8627 loss_thr: 0.5162 loss_db: 0.1410 2022/10/26 01:39:19 - mmengine - INFO - Epoch(train) [415][35/63] lr: 2.4149e-03 eta: 11:58:27 time: 0.5671 data_time: 0.0323 memory: 16131 loss: 1.5078 loss_prob: 0.8387 loss_thr: 0.5304 loss_db: 0.1387 2022/10/26 01:39:22 - mmengine - INFO - Epoch(train) [415][40/63] lr: 2.4149e-03 eta: 11:58:13 time: 0.6196 data_time: 0.0271 memory: 16131 loss: 1.4970 loss_prob: 0.8210 loss_thr: 0.5386 loss_db: 0.1374 2022/10/26 01:39:27 - mmengine - INFO - Epoch(train) [415][45/63] lr: 2.4149e-03 eta: 11:58:13 time: 0.8503 data_time: 0.0081 memory: 16131 loss: 1.4962 loss_prob: 0.8248 loss_thr: 0.5325 loss_db: 0.1389 2022/10/26 01:39:31 - mmengine - INFO - Epoch(train) [415][50/63] lr: 2.4149e-03 eta: 11:58:04 time: 0.8301 data_time: 0.0130 memory: 16131 loss: 1.5260 loss_prob: 0.8524 loss_thr: 0.5328 loss_db: 0.1408 2022/10/26 01:39:33 - mmengine - INFO - Epoch(train) [415][55/63] lr: 2.4149e-03 eta: 11:58:04 time: 0.5763 data_time: 0.0233 memory: 16131 loss: 1.6004 loss_prob: 0.8949 loss_thr: 0.5581 loss_db: 0.1473 2022/10/26 01:39:36 - mmengine - INFO - Epoch(train) [415][60/63] lr: 2.4149e-03 eta: 11:57:49 time: 0.5609 data_time: 0.0172 memory: 16131 loss: 1.5280 loss_prob: 0.8477 loss_thr: 0.5422 loss_db: 0.1381 2022/10/26 01:39:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:39:44 - mmengine - INFO - Epoch(train) [416][5/63] lr: 2.4121e-03 eta: 11:57:49 time: 0.9165 data_time: 0.1909 memory: 16131 loss: 1.5912 loss_prob: 0.9090 loss_thr: 0.5320 loss_db: 0.1502 2022/10/26 01:39:47 - mmengine - INFO - Epoch(train) [416][10/63] lr: 2.4121e-03 eta: 11:57:31 time: 0.7622 data_time: 0.1905 memory: 16131 loss: 1.7654 loss_prob: 1.0347 loss_thr: 0.5653 loss_db: 0.1654 2022/10/26 01:39:52 - mmengine - INFO - Epoch(train) [416][15/63] lr: 2.4121e-03 eta: 11:57:31 time: 0.8460 data_time: 0.0081 memory: 16131 loss: 1.7274 loss_prob: 1.0093 loss_thr: 0.5574 loss_db: 0.1608 2022/10/26 01:39:57 - mmengine - INFO - Epoch(train) [416][20/63] lr: 2.4121e-03 eta: 11:57:25 time: 1.0408 data_time: 0.0071 memory: 16131 loss: 1.5841 loss_prob: 0.8910 loss_thr: 0.5451 loss_db: 0.1480 2022/10/26 01:40:01 - mmengine - INFO - Epoch(train) [416][25/63] lr: 2.4121e-03 eta: 11:57:25 time: 0.8992 data_time: 0.0182 memory: 16131 loss: 1.6597 loss_prob: 0.9348 loss_thr: 0.5718 loss_db: 0.1530 2022/10/26 01:40:04 - mmengine - INFO - Epoch(train) [416][30/63] lr: 2.4121e-03 eta: 11:57:13 time: 0.6875 data_time: 0.0323 memory: 16131 loss: 1.6611 loss_prob: 0.9511 loss_thr: 0.5528 loss_db: 0.1572 2022/10/26 01:40:07 - mmengine - INFO - Epoch(train) [416][35/63] lr: 2.4121e-03 eta: 11:57:13 time: 0.5673 data_time: 0.0214 memory: 16131 loss: 1.6027 loss_prob: 0.9146 loss_thr: 0.5322 loss_db: 0.1559 2022/10/26 01:40:10 - mmengine - INFO - Epoch(train) [416][40/63] lr: 2.4121e-03 eta: 11:56:58 time: 0.5535 data_time: 0.0060 memory: 16131 loss: 1.6186 loss_prob: 0.9117 loss_thr: 0.5516 loss_db: 0.1552 2022/10/26 01:40:14 - mmengine - INFO - Epoch(train) [416][45/63] lr: 2.4121e-03 eta: 11:56:58 time: 0.6694 data_time: 0.0078 memory: 16131 loss: 1.6140 loss_prob: 0.9129 loss_thr: 0.5501 loss_db: 0.1510 2022/10/26 01:40:17 - mmengine - INFO - Epoch(train) [416][50/63] lr: 2.4121e-03 eta: 11:56:46 time: 0.6764 data_time: 0.0164 memory: 16131 loss: 1.6969 loss_prob: 0.9659 loss_thr: 0.5703 loss_db: 0.1606 2022/10/26 01:40:20 - mmengine - INFO - Epoch(train) [416][55/63] lr: 2.4121e-03 eta: 11:56:46 time: 0.6113 data_time: 0.0213 memory: 16131 loss: 1.6371 loss_prob: 0.9156 loss_thr: 0.5660 loss_db: 0.1554 2022/10/26 01:40:24 - mmengine - INFO - Epoch(train) [416][60/63] lr: 2.4121e-03 eta: 11:56:35 time: 0.7277 data_time: 0.0158 memory: 16131 loss: 1.5229 loss_prob: 0.8446 loss_thr: 0.5352 loss_db: 0.1431 2022/10/26 01:40:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:40:32 - mmengine - INFO - Epoch(train) [417][5/63] lr: 2.4094e-03 eta: 11:56:35 time: 0.9607 data_time: 0.1862 memory: 16131 loss: 1.6137 loss_prob: 0.9142 loss_thr: 0.5497 loss_db: 0.1498 2022/10/26 01:40:35 - mmengine - INFO - Epoch(train) [417][10/63] lr: 2.4094e-03 eta: 11:56:20 time: 0.9811 data_time: 0.1876 memory: 16131 loss: 1.5868 loss_prob: 0.8854 loss_thr: 0.5547 loss_db: 0.1467 2022/10/26 01:40:38 - mmengine - INFO - Epoch(train) [417][15/63] lr: 2.4094e-03 eta: 11:56:20 time: 0.5432 data_time: 0.0083 memory: 16131 loss: 1.6006 loss_prob: 0.8899 loss_thr: 0.5603 loss_db: 0.1503 2022/10/26 01:40:43 - mmengine - INFO - Epoch(train) [417][20/63] lr: 2.4094e-03 eta: 11:56:11 time: 0.8323 data_time: 0.0076 memory: 16131 loss: 1.6419 loss_prob: 0.9363 loss_thr: 0.5478 loss_db: 0.1577 2022/10/26 01:40:47 - mmengine - INFO - Epoch(train) [417][25/63] lr: 2.4094e-03 eta: 11:56:11 time: 0.9734 data_time: 0.0136 memory: 16131 loss: 1.6811 loss_prob: 0.9618 loss_thr: 0.5534 loss_db: 0.1659 2022/10/26 01:40:52 - mmengine - INFO - Epoch(train) [417][30/63] lr: 2.4094e-03 eta: 11:56:03 time: 0.9057 data_time: 0.0298 memory: 16131 loss: 1.7290 loss_prob: 0.9983 loss_thr: 0.5660 loss_db: 0.1646 2022/10/26 01:40:55 - mmengine - INFO - Epoch(train) [417][35/63] lr: 2.4094e-03 eta: 11:56:03 time: 0.7393 data_time: 0.0240 memory: 16131 loss: 1.6891 loss_prob: 0.9779 loss_thr: 0.5577 loss_db: 0.1535 2022/10/26 01:40:59 - mmengine - INFO - Epoch(train) [417][40/63] lr: 2.4094e-03 eta: 11:55:50 time: 0.6684 data_time: 0.0096 memory: 16131 loss: 1.6028 loss_prob: 0.9160 loss_thr: 0.5357 loss_db: 0.1512 2022/10/26 01:41:02 - mmengine - INFO - Epoch(train) [417][45/63] lr: 2.4094e-03 eta: 11:55:50 time: 0.6923 data_time: 0.0070 memory: 16131 loss: 1.5673 loss_prob: 0.8980 loss_thr: 0.5166 loss_db: 0.1527 2022/10/26 01:41:05 - mmengine - INFO - Epoch(train) [417][50/63] lr: 2.4094e-03 eta: 11:55:37 time: 0.6271 data_time: 0.0180 memory: 16131 loss: 1.6989 loss_prob: 1.0046 loss_thr: 0.5345 loss_db: 0.1598 2022/10/26 01:41:08 - mmengine - INFO - Epoch(train) [417][55/63] lr: 2.4094e-03 eta: 11:55:37 time: 0.6024 data_time: 0.0257 memory: 16131 loss: 1.7855 loss_prob: 1.0589 loss_thr: 0.5606 loss_db: 0.1660 2022/10/26 01:41:11 - mmengine - INFO - Epoch(train) [417][60/63] lr: 2.4094e-03 eta: 11:55:23 time: 0.5927 data_time: 0.0139 memory: 16131 loss: 1.7351 loss_prob: 0.9974 loss_thr: 0.5705 loss_db: 0.1672 2022/10/26 01:41:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:41:17 - mmengine - INFO - Epoch(train) [418][5/63] lr: 2.4066e-03 eta: 11:55:23 time: 0.7791 data_time: 0.2224 memory: 16131 loss: 1.7182 loss_prob: 0.9820 loss_thr: 0.5681 loss_db: 0.1681 2022/10/26 01:41:20 - mmengine - INFO - Epoch(train) [418][10/63] lr: 2.4066e-03 eta: 11:55:05 time: 0.7343 data_time: 0.2206 memory: 16131 loss: 1.9013 loss_prob: 1.1379 loss_thr: 0.5889 loss_db: 0.1744 2022/10/26 01:41:23 - mmengine - INFO - Epoch(train) [418][15/63] lr: 2.4066e-03 eta: 11:55:05 time: 0.5741 data_time: 0.0051 memory: 16131 loss: 1.8186 loss_prob: 1.0854 loss_thr: 0.5664 loss_db: 0.1667 2022/10/26 01:41:27 - mmengine - INFO - Epoch(train) [418][20/63] lr: 2.4066e-03 eta: 11:54:54 time: 0.7585 data_time: 0.0056 memory: 16131 loss: 1.5367 loss_prob: 0.8647 loss_thr: 0.5267 loss_db: 0.1453 2022/10/26 01:41:30 - mmengine - INFO - Epoch(train) [418][25/63] lr: 2.4066e-03 eta: 11:54:54 time: 0.7534 data_time: 0.0268 memory: 16131 loss: 2.0217 loss_prob: 1.2431 loss_thr: 0.5927 loss_db: 0.1859 2022/10/26 01:41:33 - mmengine - INFO - Epoch(train) [418][30/63] lr: 2.4066e-03 eta: 11:54:40 time: 0.5821 data_time: 0.0394 memory: 16131 loss: 2.0566 loss_prob: 1.2652 loss_thr: 0.5981 loss_db: 0.1934 2022/10/26 01:41:37 - mmengine - INFO - Epoch(train) [418][35/63] lr: 2.4066e-03 eta: 11:54:40 time: 0.6792 data_time: 0.0176 memory: 16131 loss: 1.6389 loss_prob: 0.9419 loss_thr: 0.5379 loss_db: 0.1591 2022/10/26 01:41:44 - mmengine - INFO - Epoch(train) [418][40/63] lr: 2.4066e-03 eta: 11:54:34 time: 1.0550 data_time: 0.0073 memory: 16131 loss: 1.7215 loss_prob: 1.0006 loss_thr: 0.5570 loss_db: 0.1639 2022/10/26 01:41:48 - mmengine - INFO - Epoch(train) [418][45/63] lr: 2.4066e-03 eta: 11:54:34 time: 1.1151 data_time: 0.0076 memory: 16131 loss: 1.6104 loss_prob: 0.9275 loss_thr: 0.5307 loss_db: 0.1523 2022/10/26 01:41:51 - mmengine - INFO - Epoch(train) [418][50/63] lr: 2.4066e-03 eta: 11:54:24 time: 0.7853 data_time: 0.0206 memory: 16131 loss: 1.5101 loss_prob: 0.8610 loss_thr: 0.5075 loss_db: 0.1417 2022/10/26 01:41:55 - mmengine - INFO - Epoch(train) [418][55/63] lr: 2.4066e-03 eta: 11:54:24 time: 0.6810 data_time: 0.0266 memory: 16131 loss: 1.5955 loss_prob: 0.9026 loss_thr: 0.5440 loss_db: 0.1489 2022/10/26 01:42:00 - mmengine - INFO - Epoch(train) [418][60/63] lr: 2.4066e-03 eta: 11:54:15 time: 0.8712 data_time: 0.0128 memory: 16131 loss: 1.5881 loss_prob: 0.8941 loss_thr: 0.5452 loss_db: 0.1489 2022/10/26 01:42:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:42:11 - mmengine - INFO - Epoch(train) [419][5/63] lr: 2.4038e-03 eta: 11:54:15 time: 1.1712 data_time: 0.2294 memory: 16131 loss: 1.5989 loss_prob: 0.8973 loss_thr: 0.5518 loss_db: 0.1497 2022/10/26 01:42:13 - mmengine - INFO - Epoch(train) [419][10/63] lr: 2.4038e-03 eta: 11:54:03 time: 1.0878 data_time: 0.2293 memory: 16131 loss: 1.5245 loss_prob: 0.8475 loss_thr: 0.5345 loss_db: 0.1424 2022/10/26 01:42:16 - mmengine - INFO - Epoch(train) [419][15/63] lr: 2.4038e-03 eta: 11:54:03 time: 0.5613 data_time: 0.0106 memory: 16131 loss: 1.5390 loss_prob: 0.8790 loss_thr: 0.5153 loss_db: 0.1446 2022/10/26 01:42:22 - mmengine - INFO - Epoch(train) [419][20/63] lr: 2.4038e-03 eta: 11:53:55 time: 0.8660 data_time: 0.0129 memory: 16131 loss: 1.6018 loss_prob: 0.9197 loss_thr: 0.5304 loss_db: 0.1517 2022/10/26 01:42:24 - mmengine - INFO - Epoch(train) [419][25/63] lr: 2.4038e-03 eta: 11:53:55 time: 0.8324 data_time: 0.0173 memory: 16131 loss: 1.6698 loss_prob: 0.9564 loss_thr: 0.5554 loss_db: 0.1579 2022/10/26 01:42:27 - mmengine - INFO - Epoch(train) [419][30/63] lr: 2.4038e-03 eta: 11:53:39 time: 0.5221 data_time: 0.0297 memory: 16131 loss: 1.5663 loss_prob: 0.8824 loss_thr: 0.5389 loss_db: 0.1450 2022/10/26 01:42:30 - mmengine - INFO - Epoch(train) [419][35/63] lr: 2.4038e-03 eta: 11:53:39 time: 0.5732 data_time: 0.0229 memory: 16131 loss: 1.4908 loss_prob: 0.8388 loss_thr: 0.5120 loss_db: 0.1400 2022/10/26 01:42:33 - mmengine - INFO - Epoch(train) [419][40/63] lr: 2.4038e-03 eta: 11:53:25 time: 0.5789 data_time: 0.0101 memory: 16131 loss: 1.5566 loss_prob: 0.8860 loss_thr: 0.5215 loss_db: 0.1491 2022/10/26 01:42:36 - mmengine - INFO - Epoch(train) [419][45/63] lr: 2.4038e-03 eta: 11:53:25 time: 0.5357 data_time: 0.0101 memory: 16131 loss: 1.5650 loss_prob: 0.8891 loss_thr: 0.5270 loss_db: 0.1489 2022/10/26 01:42:42 - mmengine - INFO - Epoch(train) [419][50/63] lr: 2.4038e-03 eta: 11:53:17 time: 0.8706 data_time: 0.0207 memory: 16131 loss: 1.5887 loss_prob: 0.9067 loss_thr: 0.5323 loss_db: 0.1497 2022/10/26 01:42:44 - mmengine - INFO - Epoch(train) [419][55/63] lr: 2.4038e-03 eta: 11:53:17 time: 0.8632 data_time: 0.0201 memory: 16131 loss: 1.6390 loss_prob: 0.9354 loss_thr: 0.5500 loss_db: 0.1535 2022/10/26 01:42:48 - mmengine - INFO - Epoch(train) [419][60/63] lr: 2.4038e-03 eta: 11:53:03 time: 0.6063 data_time: 0.0084 memory: 16131 loss: 1.6473 loss_prob: 0.9234 loss_thr: 0.5680 loss_db: 0.1560 2022/10/26 01:42:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:42:59 - mmengine - INFO - Epoch(train) [420][5/63] lr: 2.4010e-03 eta: 11:53:03 time: 1.3578 data_time: 0.2133 memory: 16131 loss: 1.6443 loss_prob: 0.9444 loss_thr: 0.5406 loss_db: 0.1593 2022/10/26 01:43:03 - mmengine - INFO - Epoch(train) [420][10/63] lr: 2.4010e-03 eta: 11:52:55 time: 1.3109 data_time: 0.2114 memory: 16131 loss: 1.6212 loss_prob: 0.9258 loss_thr: 0.5436 loss_db: 0.1517 2022/10/26 01:43:06 - mmengine - INFO - Epoch(train) [420][15/63] lr: 2.4010e-03 eta: 11:52:55 time: 0.6868 data_time: 0.0086 memory: 16131 loss: 1.6294 loss_prob: 0.9281 loss_thr: 0.5491 loss_db: 0.1523 2022/10/26 01:43:10 - mmengine - INFO - Epoch(train) [420][20/63] lr: 2.4010e-03 eta: 11:52:44 time: 0.7289 data_time: 0.0100 memory: 16131 loss: 1.7031 loss_prob: 0.9821 loss_thr: 0.5596 loss_db: 0.1615 2022/10/26 01:43:13 - mmengine - INFO - Epoch(train) [420][25/63] lr: 2.4010e-03 eta: 11:52:44 time: 0.6756 data_time: 0.0147 memory: 16131 loss: 1.6447 loss_prob: 0.9328 loss_thr: 0.5581 loss_db: 0.1538 2022/10/26 01:43:17 - mmengine - INFO - Epoch(train) [420][30/63] lr: 2.4010e-03 eta: 11:52:31 time: 0.6261 data_time: 0.0420 memory: 16131 loss: 1.5372 loss_prob: 0.8514 loss_thr: 0.5448 loss_db: 0.1410 2022/10/26 01:43:19 - mmengine - INFO - Epoch(train) [420][35/63] lr: 2.4010e-03 eta: 11:52:31 time: 0.6535 data_time: 0.0337 memory: 16131 loss: 1.5977 loss_prob: 0.8994 loss_thr: 0.5454 loss_db: 0.1529 2022/10/26 01:43:22 - mmengine - INFO - Epoch(train) [420][40/63] lr: 2.4010e-03 eta: 11:52:16 time: 0.5630 data_time: 0.0059 memory: 16131 loss: 1.8116 loss_prob: 1.0821 loss_thr: 0.5594 loss_db: 0.1701 2022/10/26 01:43:26 - mmengine - INFO - Epoch(train) [420][45/63] lr: 2.4010e-03 eta: 11:52:16 time: 0.6122 data_time: 0.0062 memory: 16131 loss: 1.7620 loss_prob: 1.0554 loss_thr: 0.5464 loss_db: 0.1602 2022/10/26 01:43:30 - mmengine - INFO - Epoch(train) [420][50/63] lr: 2.4010e-03 eta: 11:52:05 time: 0.7342 data_time: 0.0205 memory: 16131 loss: 1.6192 loss_prob: 0.9111 loss_thr: 0.5575 loss_db: 0.1505 2022/10/26 01:43:33 - mmengine - INFO - Epoch(train) [420][55/63] lr: 2.4010e-03 eta: 11:52:05 time: 0.7865 data_time: 0.0220 memory: 16131 loss: 1.6409 loss_prob: 0.9047 loss_thr: 0.5833 loss_db: 0.1530 2022/10/26 01:43:36 - mmengine - INFO - Epoch(train) [420][60/63] lr: 2.4010e-03 eta: 11:51:52 time: 0.6400 data_time: 0.0081 memory: 16131 loss: 1.5958 loss_prob: 0.8895 loss_thr: 0.5539 loss_db: 0.1523 2022/10/26 01:43:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:43:38 - mmengine - INFO - Saving checkpoint at 420 epochs 2022/10/26 01:43:45 - mmengine - INFO - Epoch(val) [420][5/32] eta: 11:51:52 time: 0.5191 data_time: 0.0566 memory: 16131 2022/10/26 01:43:48 - mmengine - INFO - Epoch(val) [420][10/32] eta: 0:00:13 time: 0.5985 data_time: 0.0884 memory: 15724 2022/10/26 01:43:51 - mmengine - INFO - Epoch(val) [420][15/32] eta: 0:00:13 time: 0.5606 data_time: 0.0484 memory: 15724 2022/10/26 01:43:54 - mmengine - INFO - Epoch(val) [420][20/32] eta: 0:00:06 time: 0.5641 data_time: 0.0558 memory: 15724 2022/10/26 01:43:56 - mmengine - INFO - Epoch(val) [420][25/32] eta: 0:00:06 time: 0.5876 data_time: 0.0749 memory: 15724 2022/10/26 01:43:59 - mmengine - INFO - Epoch(val) [420][30/32] eta: 0:00:01 time: 0.5360 data_time: 0.0354 memory: 15724 2022/10/26 01:44:00 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7987, precision: 0.7315, hmean: 0.7636 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7983, precision: 0.8037, hmean: 0.8010 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7949, precision: 0.8484, hmean: 0.8208 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7780, precision: 0.8802, hmean: 0.8260 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7169, precision: 0.9118, hmean: 0.8027 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4083, precision: 0.9528, hmean: 0.5716 2022/10/26 01:44:00 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0029, precision: 1.0000, hmean: 0.0058 2022/10/26 01:44:00 - mmengine - INFO - Epoch(val) [420][32/32] icdar/precision: 0.8802 icdar/recall: 0.7780 icdar/hmean: 0.8260 2022/10/26 01:44:05 - mmengine - INFO - Epoch(train) [421][5/63] lr: 2.3983e-03 eta: 0:00:01 time: 0.8915 data_time: 0.1978 memory: 16131 loss: 1.7806 loss_prob: 1.0705 loss_thr: 0.5465 loss_db: 0.1635 2022/10/26 01:44:11 - mmengine - INFO - Epoch(train) [421][10/63] lr: 2.3983e-03 eta: 11:51:41 time: 1.1382 data_time: 0.1946 memory: 16131 loss: 1.5999 loss_prob: 0.9109 loss_thr: 0.5376 loss_db: 0.1513 2022/10/26 01:44:17 - mmengine - INFO - Epoch(train) [421][15/63] lr: 2.3983e-03 eta: 11:51:41 time: 1.1674 data_time: 0.0061 memory: 16131 loss: 1.5780 loss_prob: 0.8848 loss_thr: 0.5450 loss_db: 0.1482 2022/10/26 01:44:20 - mmengine - INFO - Epoch(train) [421][20/63] lr: 2.3983e-03 eta: 11:51:32 time: 0.8815 data_time: 0.0077 memory: 16131 loss: 1.6061 loss_prob: 0.8977 loss_thr: 0.5576 loss_db: 0.1508 2022/10/26 01:44:22 - mmengine - INFO - Epoch(train) [421][25/63] lr: 2.3983e-03 eta: 11:51:32 time: 0.5376 data_time: 0.0214 memory: 16131 loss: 1.6802 loss_prob: 0.9539 loss_thr: 0.5675 loss_db: 0.1588 2022/10/26 01:44:25 - mmengine - INFO - Epoch(train) [421][30/63] lr: 2.3983e-03 eta: 11:51:18 time: 0.5433 data_time: 0.0390 memory: 16131 loss: 1.7391 loss_prob: 1.0199 loss_thr: 0.5552 loss_db: 0.1640 2022/10/26 01:44:28 - mmengine - INFO - Epoch(train) [421][35/63] lr: 2.3983e-03 eta: 11:51:18 time: 0.5300 data_time: 0.0245 memory: 16131 loss: 1.7173 loss_prob: 1.0105 loss_thr: 0.5447 loss_db: 0.1621 2022/10/26 01:44:30 - mmengine - INFO - Epoch(train) [421][40/63] lr: 2.3983e-03 eta: 11:51:02 time: 0.4955 data_time: 0.0048 memory: 16131 loss: 1.6674 loss_prob: 0.9539 loss_thr: 0.5556 loss_db: 0.1580 2022/10/26 01:44:33 - mmengine - INFO - Epoch(train) [421][45/63] lr: 2.3983e-03 eta: 11:51:02 time: 0.5430 data_time: 0.0064 memory: 16131 loss: 1.6929 loss_prob: 0.9704 loss_thr: 0.5593 loss_db: 0.1632 2022/10/26 01:44:36 - mmengine - INFO - Epoch(train) [421][50/63] lr: 2.3983e-03 eta: 11:50:48 time: 0.5988 data_time: 0.0175 memory: 16131 loss: 1.6442 loss_prob: 0.9389 loss_thr: 0.5479 loss_db: 0.1574 2022/10/26 01:44:39 - mmengine - INFO - Epoch(train) [421][55/63] lr: 2.3983e-03 eta: 11:50:48 time: 0.5707 data_time: 0.0260 memory: 16131 loss: 1.5067 loss_prob: 0.8365 loss_thr: 0.5303 loss_db: 0.1399 2022/10/26 01:44:43 - mmengine - INFO - Epoch(train) [421][60/63] lr: 2.3983e-03 eta: 11:50:37 time: 0.7154 data_time: 0.0151 memory: 16131 loss: 1.5624 loss_prob: 0.8699 loss_thr: 0.5466 loss_db: 0.1459 2022/10/26 01:44:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:44:52 - mmengine - INFO - Epoch(train) [422][5/63] lr: 2.3955e-03 eta: 11:50:37 time: 1.0446 data_time: 0.1837 memory: 16131 loss: 1.7861 loss_prob: 1.0505 loss_thr: 0.5652 loss_db: 0.1704 2022/10/26 01:44:58 - mmengine - INFO - Epoch(train) [422][10/63] lr: 2.3955e-03 eta: 11:50:27 time: 1.2222 data_time: 0.1883 memory: 16131 loss: 1.7796 loss_prob: 1.0545 loss_thr: 0.5532 loss_db: 0.1719 2022/10/26 01:45:04 - mmengine - INFO - Epoch(train) [422][15/63] lr: 2.3955e-03 eta: 11:50:27 time: 1.2279 data_time: 0.0138 memory: 16131 loss: 1.5257 loss_prob: 0.8549 loss_thr: 0.5295 loss_db: 0.1414 2022/10/26 01:45:09 - mmengine - INFO - Epoch(train) [422][20/63] lr: 2.3955e-03 eta: 11:50:23 time: 1.1035 data_time: 0.0084 memory: 16131 loss: 1.5305 loss_prob: 0.8645 loss_thr: 0.5205 loss_db: 0.1455 2022/10/26 01:45:12 - mmengine - INFO - Epoch(train) [422][25/63] lr: 2.3955e-03 eta: 11:50:23 time: 0.7800 data_time: 0.0172 memory: 16131 loss: 1.5636 loss_prob: 0.8988 loss_thr: 0.5135 loss_db: 0.1512 2022/10/26 01:45:15 - mmengine - INFO - Epoch(train) [422][30/63] lr: 2.3955e-03 eta: 11:50:09 time: 0.5968 data_time: 0.0436 memory: 16131 loss: 1.5699 loss_prob: 0.8867 loss_thr: 0.5364 loss_db: 0.1468 2022/10/26 01:45:18 - mmengine - INFO - Epoch(train) [422][35/63] lr: 2.3955e-03 eta: 11:50:09 time: 0.5592 data_time: 0.0350 memory: 16131 loss: 1.4819 loss_prob: 0.8162 loss_thr: 0.5318 loss_db: 0.1338 2022/10/26 01:45:22 - mmengine - INFO - Epoch(train) [422][40/63] lr: 2.3955e-03 eta: 11:49:57 time: 0.6569 data_time: 0.0082 memory: 16131 loss: 1.4794 loss_prob: 0.8266 loss_thr: 0.5157 loss_db: 0.1371 2022/10/26 01:45:26 - mmengine - INFO - Epoch(train) [422][45/63] lr: 2.3955e-03 eta: 11:49:57 time: 0.8616 data_time: 0.0045 memory: 16131 loss: 1.5886 loss_prob: 0.8925 loss_thr: 0.5468 loss_db: 0.1493 2022/10/26 01:45:29 - mmengine - INFO - Epoch(train) [422][50/63] lr: 2.3955e-03 eta: 11:49:45 time: 0.7169 data_time: 0.0107 memory: 16131 loss: 1.5426 loss_prob: 0.8572 loss_thr: 0.5413 loss_db: 0.1441 2022/10/26 01:45:32 - mmengine - INFO - Epoch(train) [422][55/63] lr: 2.3955e-03 eta: 11:49:45 time: 0.5362 data_time: 0.0211 memory: 16131 loss: 1.4743 loss_prob: 0.8291 loss_thr: 0.5060 loss_db: 0.1392 2022/10/26 01:45:34 - mmengine - INFO - Epoch(train) [422][60/63] lr: 2.3955e-03 eta: 11:49:30 time: 0.5443 data_time: 0.0164 memory: 16131 loss: 1.4809 loss_prob: 0.8220 loss_thr: 0.5213 loss_db: 0.1376 2022/10/26 01:45:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:45:40 - mmengine - INFO - Epoch(train) [423][5/63] lr: 2.3927e-03 eta: 11:49:30 time: 0.7118 data_time: 0.1725 memory: 16131 loss: 1.5757 loss_prob: 0.8719 loss_thr: 0.5563 loss_db: 0.1475 2022/10/26 01:45:43 - mmengine - INFO - Epoch(train) [423][10/63] lr: 2.3927e-03 eta: 11:49:12 time: 0.7538 data_time: 0.1770 memory: 16131 loss: 1.5440 loss_prob: 0.8498 loss_thr: 0.5494 loss_db: 0.1449 2022/10/26 01:45:46 - mmengine - INFO - Epoch(train) [423][15/63] lr: 2.3927e-03 eta: 11:49:12 time: 0.5867 data_time: 0.0155 memory: 16131 loss: 1.5729 loss_prob: 0.8950 loss_thr: 0.5303 loss_db: 0.1476 2022/10/26 01:45:49 - mmengine - INFO - Epoch(train) [423][20/63] lr: 2.3927e-03 eta: 11:48:59 time: 0.5963 data_time: 0.0119 memory: 16131 loss: 1.5559 loss_prob: 0.8745 loss_thr: 0.5380 loss_db: 0.1434 2022/10/26 01:45:52 - mmengine - INFO - Epoch(train) [423][25/63] lr: 2.3927e-03 eta: 11:48:59 time: 0.5536 data_time: 0.0178 memory: 16131 loss: 1.5681 loss_prob: 0.8713 loss_thr: 0.5501 loss_db: 0.1467 2022/10/26 01:45:54 - mmengine - INFO - Epoch(train) [423][30/63] lr: 2.3927e-03 eta: 11:48:43 time: 0.5193 data_time: 0.0296 memory: 16131 loss: 1.6191 loss_prob: 0.9173 loss_thr: 0.5498 loss_db: 0.1521 2022/10/26 01:45:57 - mmengine - INFO - Epoch(train) [423][35/63] lr: 2.3927e-03 eta: 11:48:43 time: 0.5167 data_time: 0.0199 memory: 16131 loss: 1.5796 loss_prob: 0.8911 loss_thr: 0.5401 loss_db: 0.1484 2022/10/26 01:46:00 - mmengine - INFO - Epoch(train) [423][40/63] lr: 2.3927e-03 eta: 11:48:29 time: 0.5443 data_time: 0.0155 memory: 16131 loss: 1.5576 loss_prob: 0.8787 loss_thr: 0.5352 loss_db: 0.1437 2022/10/26 01:46:03 - mmengine - INFO - Epoch(train) [423][45/63] lr: 2.3927e-03 eta: 11:48:29 time: 0.5725 data_time: 0.0155 memory: 16131 loss: 1.5099 loss_prob: 0.8511 loss_thr: 0.5220 loss_db: 0.1367 2022/10/26 01:46:05 - mmengine - INFO - Epoch(train) [423][50/63] lr: 2.3927e-03 eta: 11:48:14 time: 0.5392 data_time: 0.0200 memory: 16131 loss: 1.5727 loss_prob: 0.8919 loss_thr: 0.5371 loss_db: 0.1436 2022/10/26 01:46:08 - mmengine - INFO - Epoch(train) [423][55/63] lr: 2.3927e-03 eta: 11:48:14 time: 0.4987 data_time: 0.0207 memory: 16131 loss: 1.6912 loss_prob: 0.9637 loss_thr: 0.5698 loss_db: 0.1577 2022/10/26 01:46:10 - mmengine - INFO - Epoch(train) [423][60/63] lr: 2.3927e-03 eta: 11:47:59 time: 0.5090 data_time: 0.0091 memory: 16131 loss: 1.7764 loss_prob: 1.0217 loss_thr: 0.5795 loss_db: 0.1752 2022/10/26 01:46:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:46:17 - mmengine - INFO - Epoch(train) [424][5/63] lr: 2.3900e-03 eta: 11:47:59 time: 0.7954 data_time: 0.2127 memory: 16131 loss: 1.8791 loss_prob: 1.1126 loss_thr: 0.5791 loss_db: 0.1874 2022/10/26 01:46:20 - mmengine - INFO - Epoch(train) [424][10/63] lr: 2.3900e-03 eta: 11:47:43 time: 0.8745 data_time: 0.2150 memory: 16131 loss: 1.8147 loss_prob: 1.0681 loss_thr: 0.5693 loss_db: 0.1773 2022/10/26 01:46:23 - mmengine - INFO - Epoch(train) [424][15/63] lr: 2.3900e-03 eta: 11:47:43 time: 0.6007 data_time: 0.0088 memory: 16131 loss: 1.7474 loss_prob: 0.9876 loss_thr: 0.5950 loss_db: 0.1649 2022/10/26 01:46:26 - mmengine - INFO - Epoch(train) [424][20/63] lr: 2.3900e-03 eta: 11:47:28 time: 0.5512 data_time: 0.0054 memory: 16131 loss: 1.7990 loss_prob: 1.0145 loss_thr: 0.6203 loss_db: 0.1642 2022/10/26 01:46:28 - mmengine - INFO - Epoch(train) [424][25/63] lr: 2.3900e-03 eta: 11:47:28 time: 0.4958 data_time: 0.0118 memory: 16131 loss: 1.6890 loss_prob: 0.9660 loss_thr: 0.5652 loss_db: 0.1578 2022/10/26 01:46:31 - mmengine - INFO - Epoch(train) [424][30/63] lr: 2.3900e-03 eta: 11:47:13 time: 0.5240 data_time: 0.0302 memory: 16131 loss: 1.6356 loss_prob: 0.9398 loss_thr: 0.5336 loss_db: 0.1622 2022/10/26 01:46:34 - mmengine - INFO - Epoch(train) [424][35/63] lr: 2.3900e-03 eta: 11:47:13 time: 0.5564 data_time: 0.0271 memory: 16131 loss: 1.8754 loss_prob: 1.1441 loss_thr: 0.5509 loss_db: 0.1805 2022/10/26 01:46:36 - mmengine - INFO - Epoch(train) [424][40/63] lr: 2.3900e-03 eta: 11:46:59 time: 0.5343 data_time: 0.0093 memory: 16131 loss: 1.9411 loss_prob: 1.1924 loss_thr: 0.5679 loss_db: 0.1808 2022/10/26 01:46:39 - mmengine - INFO - Epoch(train) [424][45/63] lr: 2.3900e-03 eta: 11:46:59 time: 0.4947 data_time: 0.0080 memory: 16131 loss: 1.7223 loss_prob: 0.9961 loss_thr: 0.5604 loss_db: 0.1658 2022/10/26 01:46:42 - mmengine - INFO - Epoch(train) [424][50/63] lr: 2.3900e-03 eta: 11:46:44 time: 0.5445 data_time: 0.0234 memory: 16131 loss: 1.6803 loss_prob: 0.9561 loss_thr: 0.5657 loss_db: 0.1586 2022/10/26 01:46:44 - mmengine - INFO - Epoch(train) [424][55/63] lr: 2.3900e-03 eta: 11:46:44 time: 0.5384 data_time: 0.0212 memory: 16131 loss: 1.8775 loss_prob: 1.1093 loss_thr: 0.5920 loss_db: 0.1762 2022/10/26 01:46:47 - mmengine - INFO - Epoch(train) [424][60/63] lr: 2.3900e-03 eta: 11:46:28 time: 0.4852 data_time: 0.0061 memory: 16131 loss: 2.0475 loss_prob: 1.2568 loss_thr: 0.5870 loss_db: 0.2037 2022/10/26 01:46:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:46:54 - mmengine - INFO - Epoch(train) [425][5/63] lr: 2.3872e-03 eta: 11:46:28 time: 0.7692 data_time: 0.2240 memory: 16131 loss: 1.7629 loss_prob: 1.0484 loss_thr: 0.5419 loss_db: 0.1726 2022/10/26 01:46:56 - mmengine - INFO - Epoch(train) [425][10/63] lr: 2.3872e-03 eta: 11:46:11 time: 0.7915 data_time: 0.2257 memory: 16131 loss: 1.6405 loss_prob: 0.9486 loss_thr: 0.5394 loss_db: 0.1525 2022/10/26 01:46:58 - mmengine - INFO - Epoch(train) [425][15/63] lr: 2.3872e-03 eta: 11:46:11 time: 0.4947 data_time: 0.0099 memory: 16131 loss: 1.6920 loss_prob: 0.9680 loss_thr: 0.5567 loss_db: 0.1673 2022/10/26 01:47:01 - mmengine - INFO - Epoch(train) [425][20/63] lr: 2.3872e-03 eta: 11:45:56 time: 0.5119 data_time: 0.0086 memory: 16131 loss: 1.5949 loss_prob: 0.9041 loss_thr: 0.5355 loss_db: 0.1552 2022/10/26 01:47:04 - mmengine - INFO - Epoch(train) [425][25/63] lr: 2.3872e-03 eta: 11:45:56 time: 0.5481 data_time: 0.0284 memory: 16131 loss: 1.6249 loss_prob: 0.9218 loss_thr: 0.5540 loss_db: 0.1491 2022/10/26 01:47:07 - mmengine - INFO - Epoch(train) [425][30/63] lr: 2.3872e-03 eta: 11:45:42 time: 0.5637 data_time: 0.0316 memory: 16131 loss: 1.7584 loss_prob: 1.0173 loss_thr: 0.5759 loss_db: 0.1651 2022/10/26 01:47:09 - mmengine - INFO - Epoch(train) [425][35/63] lr: 2.3872e-03 eta: 11:45:42 time: 0.5282 data_time: 0.0109 memory: 16131 loss: 1.6811 loss_prob: 0.9628 loss_thr: 0.5587 loss_db: 0.1596 2022/10/26 01:47:12 - mmengine - INFO - Epoch(train) [425][40/63] lr: 2.3872e-03 eta: 11:45:26 time: 0.5032 data_time: 0.0087 memory: 16131 loss: 1.5801 loss_prob: 0.8773 loss_thr: 0.5551 loss_db: 0.1477 2022/10/26 01:47:14 - mmengine - INFO - Epoch(train) [425][45/63] lr: 2.3872e-03 eta: 11:45:26 time: 0.5216 data_time: 0.0075 memory: 16131 loss: 1.6793 loss_prob: 0.9449 loss_thr: 0.5814 loss_db: 0.1531 2022/10/26 01:47:17 - mmengine - INFO - Epoch(train) [425][50/63] lr: 2.3872e-03 eta: 11:45:11 time: 0.5195 data_time: 0.0195 memory: 16131 loss: 1.7337 loss_prob: 0.9888 loss_thr: 0.5845 loss_db: 0.1604 2022/10/26 01:47:19 - mmengine - INFO - Epoch(train) [425][55/63] lr: 2.3872e-03 eta: 11:45:11 time: 0.4994 data_time: 0.0228 memory: 16131 loss: 1.7456 loss_prob: 1.0194 loss_thr: 0.5583 loss_db: 0.1679 2022/10/26 01:47:22 - mmengine - INFO - Epoch(train) [425][60/63] lr: 2.3872e-03 eta: 11:44:56 time: 0.5184 data_time: 0.0114 memory: 16131 loss: 1.6913 loss_prob: 0.9836 loss_thr: 0.5461 loss_db: 0.1617 2022/10/26 01:47:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:47:29 - mmengine - INFO - Epoch(train) [426][5/63] lr: 2.3844e-03 eta: 11:44:56 time: 0.7510 data_time: 0.2159 memory: 16131 loss: 1.5654 loss_prob: 0.8760 loss_thr: 0.5416 loss_db: 0.1479 2022/10/26 01:47:32 - mmengine - INFO - Epoch(train) [426][10/63] lr: 2.3844e-03 eta: 11:44:40 time: 0.8330 data_time: 0.2173 memory: 16131 loss: 1.7027 loss_prob: 0.9788 loss_thr: 0.5616 loss_db: 0.1624 2022/10/26 01:47:35 - mmengine - INFO - Epoch(train) [426][15/63] lr: 2.3844e-03 eta: 11:44:40 time: 0.5902 data_time: 0.0072 memory: 16131 loss: 1.6918 loss_prob: 0.9858 loss_thr: 0.5434 loss_db: 0.1626 2022/10/26 01:47:37 - mmengine - INFO - Epoch(train) [426][20/63] lr: 2.3844e-03 eta: 11:44:25 time: 0.5144 data_time: 0.0059 memory: 16131 loss: 1.5386 loss_prob: 0.8770 loss_thr: 0.5181 loss_db: 0.1435 2022/10/26 01:47:40 - mmengine - INFO - Epoch(train) [426][25/63] lr: 2.3844e-03 eta: 11:44:25 time: 0.5138 data_time: 0.0234 memory: 16131 loss: 1.6057 loss_prob: 0.9128 loss_thr: 0.5422 loss_db: 0.1508 2022/10/26 01:47:42 - mmengine - INFO - Epoch(train) [426][30/63] lr: 2.3844e-03 eta: 11:44:10 time: 0.5150 data_time: 0.0359 memory: 16131 loss: 1.5646 loss_prob: 0.8710 loss_thr: 0.5447 loss_db: 0.1488 2022/10/26 01:47:45 - mmengine - INFO - Epoch(train) [426][35/63] lr: 2.3844e-03 eta: 11:44:10 time: 0.5239 data_time: 0.0179 memory: 16131 loss: 1.6665 loss_prob: 0.9449 loss_thr: 0.5620 loss_db: 0.1595 2022/10/26 01:47:47 - mmengine - INFO - Epoch(train) [426][40/63] lr: 2.3844e-03 eta: 11:43:54 time: 0.5124 data_time: 0.0062 memory: 16131 loss: 1.6974 loss_prob: 0.9712 loss_thr: 0.5631 loss_db: 0.1630 2022/10/26 01:47:50 - mmengine - INFO - Epoch(train) [426][45/63] lr: 2.3844e-03 eta: 11:43:54 time: 0.4946 data_time: 0.0071 memory: 16131 loss: 1.5662 loss_prob: 0.8651 loss_thr: 0.5575 loss_db: 0.1436 2022/10/26 01:47:53 - mmengine - INFO - Epoch(train) [426][50/63] lr: 2.3844e-03 eta: 11:43:39 time: 0.5166 data_time: 0.0173 memory: 16131 loss: 1.6782 loss_prob: 0.9513 loss_thr: 0.5725 loss_db: 0.1545 2022/10/26 01:47:55 - mmengine - INFO - Epoch(train) [426][55/63] lr: 2.3844e-03 eta: 11:43:39 time: 0.5348 data_time: 0.0233 memory: 16131 loss: 1.7138 loss_prob: 0.9908 loss_thr: 0.5612 loss_db: 0.1618 2022/10/26 01:47:58 - mmengine - INFO - Epoch(train) [426][60/63] lr: 2.3844e-03 eta: 11:43:25 time: 0.5501 data_time: 0.0135 memory: 16131 loss: 1.5825 loss_prob: 0.8990 loss_thr: 0.5334 loss_db: 0.1501 2022/10/26 01:47:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:48:04 - mmengine - INFO - Epoch(train) [427][5/63] lr: 2.3816e-03 eta: 11:43:25 time: 0.6648 data_time: 0.1839 memory: 16131 loss: 1.5969 loss_prob: 0.9097 loss_thr: 0.5404 loss_db: 0.1469 2022/10/26 01:48:06 - mmengine - INFO - Epoch(train) [427][10/63] lr: 2.3816e-03 eta: 11:43:06 time: 0.7134 data_time: 0.1912 memory: 16131 loss: 1.6314 loss_prob: 0.9221 loss_thr: 0.5558 loss_db: 0.1535 2022/10/26 01:48:10 - mmengine - INFO - Epoch(train) [427][15/63] lr: 2.3816e-03 eta: 11:43:06 time: 0.6242 data_time: 0.0143 memory: 16131 loss: 1.5494 loss_prob: 0.8749 loss_thr: 0.5270 loss_db: 0.1475 2022/10/26 01:48:12 - mmengine - INFO - Epoch(train) [427][20/63] lr: 2.3816e-03 eta: 11:42:53 time: 0.6098 data_time: 0.0080 memory: 16131 loss: 1.5272 loss_prob: 0.8615 loss_thr: 0.5221 loss_db: 0.1435 2022/10/26 01:48:15 - mmengine - INFO - Epoch(train) [427][25/63] lr: 2.3816e-03 eta: 11:42:53 time: 0.5032 data_time: 0.0189 memory: 16131 loss: 1.5915 loss_prob: 0.8900 loss_thr: 0.5542 loss_db: 0.1473 2022/10/26 01:48:18 - mmengine - INFO - Epoch(train) [427][30/63] lr: 2.3816e-03 eta: 11:42:38 time: 0.5141 data_time: 0.0380 memory: 16131 loss: 1.4669 loss_prob: 0.8158 loss_thr: 0.5126 loss_db: 0.1385 2022/10/26 01:48:20 - mmengine - INFO - Epoch(train) [427][35/63] lr: 2.3816e-03 eta: 11:42:38 time: 0.5256 data_time: 0.0273 memory: 16131 loss: 1.4486 loss_prob: 0.8184 loss_thr: 0.4928 loss_db: 0.1375 2022/10/26 01:48:23 - mmengine - INFO - Epoch(train) [427][40/63] lr: 2.3816e-03 eta: 11:42:23 time: 0.5096 data_time: 0.0069 memory: 16131 loss: 1.6177 loss_prob: 0.9341 loss_thr: 0.5317 loss_db: 0.1520 2022/10/26 01:48:25 - mmengine - INFO - Epoch(train) [427][45/63] lr: 2.3816e-03 eta: 11:42:23 time: 0.4913 data_time: 0.0080 memory: 16131 loss: 1.8186 loss_prob: 1.0679 loss_thr: 0.5733 loss_db: 0.1774 2022/10/26 01:48:28 - mmengine - INFO - Epoch(train) [427][50/63] lr: 2.3816e-03 eta: 11:42:08 time: 0.5124 data_time: 0.0117 memory: 16131 loss: 1.7829 loss_prob: 1.0325 loss_thr: 0.5772 loss_db: 0.1731 2022/10/26 01:48:30 - mmengine - INFO - Epoch(train) [427][55/63] lr: 2.3816e-03 eta: 11:42:08 time: 0.5298 data_time: 0.0252 memory: 16131 loss: 1.6755 loss_prob: 0.9518 loss_thr: 0.5627 loss_db: 0.1611 2022/10/26 01:48:33 - mmengine - INFO - Epoch(train) [427][60/63] lr: 2.3816e-03 eta: 11:41:53 time: 0.5381 data_time: 0.0209 memory: 16131 loss: 1.6587 loss_prob: 0.9430 loss_thr: 0.5569 loss_db: 0.1588 2022/10/26 01:48:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:48:39 - mmengine - INFO - Epoch(train) [428][5/63] lr: 2.3789e-03 eta: 11:41:53 time: 0.6892 data_time: 0.1984 memory: 16131 loss: 1.6083 loss_prob: 0.9069 loss_thr: 0.5487 loss_db: 0.1526 2022/10/26 01:48:42 - mmengine - INFO - Epoch(train) [428][10/63] lr: 2.3789e-03 eta: 11:41:34 time: 0.6950 data_time: 0.1938 memory: 16131 loss: 1.6232 loss_prob: 0.9092 loss_thr: 0.5632 loss_db: 0.1508 2022/10/26 01:48:44 - mmengine - INFO - Epoch(train) [428][15/63] lr: 2.3789e-03 eta: 11:41:34 time: 0.5153 data_time: 0.0066 memory: 16131 loss: 1.6782 loss_prob: 0.9541 loss_thr: 0.5678 loss_db: 0.1563 2022/10/26 01:48:47 - mmengine - INFO - Epoch(train) [428][20/63] lr: 2.3789e-03 eta: 11:41:19 time: 0.5076 data_time: 0.0071 memory: 16131 loss: 1.7117 loss_prob: 0.9990 loss_thr: 0.5516 loss_db: 0.1611 2022/10/26 01:48:49 - mmengine - INFO - Epoch(train) [428][25/63] lr: 2.3789e-03 eta: 11:41:19 time: 0.4991 data_time: 0.0108 memory: 16131 loss: 1.7284 loss_prob: 1.0076 loss_thr: 0.5584 loss_db: 0.1623 2022/10/26 01:48:52 - mmengine - INFO - Epoch(train) [428][30/63] lr: 2.3789e-03 eta: 11:41:05 time: 0.5572 data_time: 0.0530 memory: 16131 loss: 1.5903 loss_prob: 0.8925 loss_thr: 0.5525 loss_db: 0.1454 2022/10/26 01:48:55 - mmengine - INFO - Epoch(train) [428][35/63] lr: 2.3789e-03 eta: 11:41:05 time: 0.5445 data_time: 0.0494 memory: 16131 loss: 1.5784 loss_prob: 0.8854 loss_thr: 0.5481 loss_db: 0.1449 2022/10/26 01:48:57 - mmengine - INFO - Epoch(train) [428][40/63] lr: 2.3789e-03 eta: 11:40:49 time: 0.4764 data_time: 0.0067 memory: 16131 loss: 1.6865 loss_prob: 0.9775 loss_thr: 0.5488 loss_db: 0.1602 2022/10/26 01:49:00 - mmengine - INFO - Epoch(train) [428][45/63] lr: 2.3789e-03 eta: 11:40:49 time: 0.4852 data_time: 0.0096 memory: 16131 loss: 1.6202 loss_prob: 0.9229 loss_thr: 0.5447 loss_db: 0.1526 2022/10/26 01:49:02 - mmengine - INFO - Epoch(train) [428][50/63] lr: 2.3789e-03 eta: 11:40:34 time: 0.5126 data_time: 0.0227 memory: 16131 loss: 1.5156 loss_prob: 0.8412 loss_thr: 0.5333 loss_db: 0.1412 2022/10/26 01:49:05 - mmengine - INFO - Epoch(train) [428][55/63] lr: 2.3789e-03 eta: 11:40:34 time: 0.5226 data_time: 0.0238 memory: 16131 loss: 1.5207 loss_prob: 0.8564 loss_thr: 0.5200 loss_db: 0.1443 2022/10/26 01:49:07 - mmengine - INFO - Epoch(train) [428][60/63] lr: 2.3789e-03 eta: 11:40:20 time: 0.5241 data_time: 0.0106 memory: 16131 loss: 1.5643 loss_prob: 0.8866 loss_thr: 0.5320 loss_db: 0.1456 2022/10/26 01:49:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:49:13 - mmengine - INFO - Epoch(train) [429][5/63] lr: 2.3761e-03 eta: 11:40:20 time: 0.6468 data_time: 0.1619 memory: 16131 loss: 1.5477 loss_prob: 0.8597 loss_thr: 0.5424 loss_db: 0.1455 2022/10/26 01:49:15 - mmengine - INFO - Epoch(train) [429][10/63] lr: 2.3761e-03 eta: 11:40:00 time: 0.6675 data_time: 0.1653 memory: 16131 loss: 1.5770 loss_prob: 0.8774 loss_thr: 0.5539 loss_db: 0.1457 2022/10/26 01:49:18 - mmengine - INFO - Epoch(train) [429][15/63] lr: 2.3761e-03 eta: 11:40:00 time: 0.4894 data_time: 0.0079 memory: 16131 loss: 1.5949 loss_prob: 0.9020 loss_thr: 0.5466 loss_db: 0.1463 2022/10/26 01:49:20 - mmengine - INFO - Epoch(train) [429][20/63] lr: 2.3761e-03 eta: 11:39:45 time: 0.5099 data_time: 0.0084 memory: 16131 loss: 1.5457 loss_prob: 0.8756 loss_thr: 0.5275 loss_db: 0.1426 2022/10/26 01:49:23 - mmengine - INFO - Epoch(train) [429][25/63] lr: 2.3761e-03 eta: 11:39:45 time: 0.5601 data_time: 0.0130 memory: 16131 loss: 1.4991 loss_prob: 0.8428 loss_thr: 0.5182 loss_db: 0.1382 2022/10/26 01:49:26 - mmengine - INFO - Epoch(train) [429][30/63] lr: 2.3761e-03 eta: 11:39:32 time: 0.5870 data_time: 0.0301 memory: 16131 loss: 1.5723 loss_prob: 0.8843 loss_thr: 0.5423 loss_db: 0.1457 2022/10/26 01:49:29 - mmengine - INFO - Epoch(train) [429][35/63] lr: 2.3761e-03 eta: 11:39:32 time: 0.5430 data_time: 0.0275 memory: 16131 loss: 1.4894 loss_prob: 0.8332 loss_thr: 0.5170 loss_db: 0.1392 2022/10/26 01:49:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:49:31 - mmengine - INFO - Epoch(train) [429][40/63] lr: 2.3761e-03 eta: 11:39:16 time: 0.4965 data_time: 0.0065 memory: 16131 loss: 1.5271 loss_prob: 0.8677 loss_thr: 0.5164 loss_db: 0.1429 2022/10/26 01:49:34 - mmengine - INFO - Epoch(train) [429][45/63] lr: 2.3761e-03 eta: 11:39:16 time: 0.5123 data_time: 0.0048 memory: 16131 loss: 1.5657 loss_prob: 0.8749 loss_thr: 0.5463 loss_db: 0.1446 2022/10/26 01:49:36 - mmengine - INFO - Epoch(train) [429][50/63] lr: 2.3761e-03 eta: 11:39:01 time: 0.5129 data_time: 0.0098 memory: 16131 loss: 1.5747 loss_prob: 0.8710 loss_thr: 0.5589 loss_db: 0.1448 2022/10/26 01:49:39 - mmengine - INFO - Epoch(train) [429][55/63] lr: 2.3761e-03 eta: 11:39:01 time: 0.5123 data_time: 0.0235 memory: 16131 loss: 1.6299 loss_prob: 0.9207 loss_thr: 0.5549 loss_db: 0.1544 2022/10/26 01:49:42 - mmengine - INFO - Epoch(train) [429][60/63] lr: 2.3761e-03 eta: 11:38:47 time: 0.5356 data_time: 0.0188 memory: 16131 loss: 1.5474 loss_prob: 0.8684 loss_thr: 0.5329 loss_db: 0.1462 2022/10/26 01:49:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:49:48 - mmengine - INFO - Epoch(train) [430][5/63] lr: 2.3733e-03 eta: 11:38:47 time: 0.7869 data_time: 0.1743 memory: 16131 loss: 1.5628 loss_prob: 0.8896 loss_thr: 0.5277 loss_db: 0.1455 2022/10/26 01:49:51 - mmengine - INFO - Epoch(train) [430][10/63] lr: 2.3733e-03 eta: 11:38:30 time: 0.8070 data_time: 0.1816 memory: 16131 loss: 1.5546 loss_prob: 0.8816 loss_thr: 0.5245 loss_db: 0.1485 2022/10/26 01:49:54 - mmengine - INFO - Epoch(train) [430][15/63] lr: 2.3733e-03 eta: 11:38:30 time: 0.5181 data_time: 0.0139 memory: 16131 loss: 1.5679 loss_prob: 0.8851 loss_thr: 0.5325 loss_db: 0.1504 2022/10/26 01:49:56 - mmengine - INFO - Epoch(train) [430][20/63] lr: 2.3733e-03 eta: 11:38:15 time: 0.5124 data_time: 0.0060 memory: 16131 loss: 1.5489 loss_prob: 0.8687 loss_thr: 0.5327 loss_db: 0.1476 2022/10/26 01:49:59 - mmengine - INFO - Epoch(train) [430][25/63] lr: 2.3733e-03 eta: 11:38:15 time: 0.5405 data_time: 0.0118 memory: 16131 loss: 1.6017 loss_prob: 0.9070 loss_thr: 0.5450 loss_db: 0.1497 2022/10/26 01:50:02 - mmengine - INFO - Epoch(train) [430][30/63] lr: 2.3733e-03 eta: 11:38:01 time: 0.5718 data_time: 0.0284 memory: 16131 loss: 1.6049 loss_prob: 0.9158 loss_thr: 0.5419 loss_db: 0.1471 2022/10/26 01:50:04 - mmengine - INFO - Epoch(train) [430][35/63] lr: 2.3733e-03 eta: 11:38:01 time: 0.5324 data_time: 0.0272 memory: 16131 loss: 1.6713 loss_prob: 0.9573 loss_thr: 0.5495 loss_db: 0.1645 2022/10/26 01:50:07 - mmengine - INFO - Epoch(train) [430][40/63] lr: 2.3733e-03 eta: 11:37:46 time: 0.5218 data_time: 0.0140 memory: 16131 loss: 1.6770 loss_prob: 0.9533 loss_thr: 0.5576 loss_db: 0.1661 2022/10/26 01:50:10 - mmengine - INFO - Epoch(train) [430][45/63] lr: 2.3733e-03 eta: 11:37:46 time: 0.5199 data_time: 0.0080 memory: 16131 loss: 2.0125 loss_prob: 1.2577 loss_thr: 0.5663 loss_db: 0.1885 2022/10/26 01:50:13 - mmengine - INFO - Epoch(train) [430][50/63] lr: 2.3733e-03 eta: 11:37:32 time: 0.5627 data_time: 0.0181 memory: 16131 loss: 2.1854 loss_prob: 1.3859 loss_thr: 0.5952 loss_db: 0.2043 2022/10/26 01:50:15 - mmengine - INFO - Epoch(train) [430][55/63] lr: 2.3733e-03 eta: 11:37:32 time: 0.5515 data_time: 0.0205 memory: 16131 loss: 2.0530 loss_prob: 1.2409 loss_thr: 0.6062 loss_db: 0.2059 2022/10/26 01:50:18 - mmengine - INFO - Epoch(train) [430][60/63] lr: 2.3733e-03 eta: 11:37:17 time: 0.5040 data_time: 0.0085 memory: 16131 loss: 2.4038 loss_prob: 1.5436 loss_thr: 0.6221 loss_db: 0.2380 2022/10/26 01:50:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:50:24 - mmengine - INFO - Epoch(train) [431][5/63] lr: 2.3706e-03 eta: 11:37:17 time: 0.6984 data_time: 0.1833 memory: 16131 loss: 2.4799 loss_prob: 1.5651 loss_thr: 0.6834 loss_db: 0.2314 2022/10/26 01:50:26 - mmengine - INFO - Epoch(train) [431][10/63] lr: 2.3706e-03 eta: 11:36:59 time: 0.7294 data_time: 0.1835 memory: 16131 loss: 2.3681 loss_prob: 1.4388 loss_thr: 0.6985 loss_db: 0.2308 2022/10/26 01:50:29 - mmengine - INFO - Epoch(train) [431][15/63] lr: 2.3706e-03 eta: 11:36:59 time: 0.5240 data_time: 0.0106 memory: 16131 loss: 2.0454 loss_prob: 1.2034 loss_thr: 0.6416 loss_db: 0.2003 2022/10/26 01:50:32 - mmengine - INFO - Epoch(train) [431][20/63] lr: 2.3706e-03 eta: 11:36:45 time: 0.5275 data_time: 0.0115 memory: 16131 loss: 1.8991 loss_prob: 1.1134 loss_thr: 0.6035 loss_db: 0.1822 2022/10/26 01:50:35 - mmengine - INFO - Epoch(train) [431][25/63] lr: 2.3706e-03 eta: 11:36:45 time: 0.5663 data_time: 0.0213 memory: 16131 loss: 1.7832 loss_prob: 1.0380 loss_thr: 0.5791 loss_db: 0.1661 2022/10/26 01:50:38 - mmengine - INFO - Epoch(train) [431][30/63] lr: 2.3706e-03 eta: 11:36:31 time: 0.6122 data_time: 0.0404 memory: 16131 loss: 1.7258 loss_prob: 0.9899 loss_thr: 0.5745 loss_db: 0.1614 2022/10/26 01:50:40 - mmengine - INFO - Epoch(train) [431][35/63] lr: 2.3706e-03 eta: 11:36:31 time: 0.5726 data_time: 0.0248 memory: 16131 loss: 1.8308 loss_prob: 1.0747 loss_thr: 0.5784 loss_db: 0.1778 2022/10/26 01:50:43 - mmengine - INFO - Epoch(train) [431][40/63] lr: 2.3706e-03 eta: 11:36:17 time: 0.5088 data_time: 0.0044 memory: 16131 loss: 1.8540 loss_prob: 1.0926 loss_thr: 0.5780 loss_db: 0.1834 2022/10/26 01:50:45 - mmengine - INFO - Epoch(train) [431][45/63] lr: 2.3706e-03 eta: 11:36:17 time: 0.5105 data_time: 0.0131 memory: 16131 loss: 1.7634 loss_prob: 1.0266 loss_thr: 0.5644 loss_db: 0.1723 2022/10/26 01:50:48 - mmengine - INFO - Epoch(train) [431][50/63] lr: 2.3706e-03 eta: 11:36:02 time: 0.5234 data_time: 0.0192 memory: 16131 loss: 1.7396 loss_prob: 1.0143 loss_thr: 0.5557 loss_db: 0.1696 2022/10/26 01:50:51 - mmengine - INFO - Epoch(train) [431][55/63] lr: 2.3706e-03 eta: 11:36:02 time: 0.5481 data_time: 0.0237 memory: 16131 loss: 1.7555 loss_prob: 1.0214 loss_thr: 0.5580 loss_db: 0.1761 2022/10/26 01:50:53 - mmengine - INFO - Epoch(train) [431][60/63] lr: 2.3706e-03 eta: 11:35:47 time: 0.5341 data_time: 0.0180 memory: 16131 loss: 1.7057 loss_prob: 0.9806 loss_thr: 0.5573 loss_db: 0.1678 2022/10/26 01:50:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:51:00 - mmengine - INFO - Epoch(train) [432][5/63] lr: 2.3678e-03 eta: 11:35:47 time: 0.7686 data_time: 0.2006 memory: 16131 loss: 1.8198 loss_prob: 1.0626 loss_thr: 0.5881 loss_db: 0.1691 2022/10/26 01:51:03 - mmengine - INFO - Epoch(train) [432][10/63] lr: 2.3678e-03 eta: 11:35:31 time: 0.8164 data_time: 0.2029 memory: 16131 loss: 1.9284 loss_prob: 1.1554 loss_thr: 0.5868 loss_db: 0.1862 2022/10/26 01:51:05 - mmengine - INFO - Epoch(train) [432][15/63] lr: 2.3678e-03 eta: 11:35:31 time: 0.5448 data_time: 0.0094 memory: 16131 loss: 1.8483 loss_prob: 1.1142 loss_thr: 0.5543 loss_db: 0.1797 2022/10/26 01:51:08 - mmengine - INFO - Epoch(train) [432][20/63] lr: 2.3678e-03 eta: 11:35:16 time: 0.5039 data_time: 0.0058 memory: 16131 loss: 1.7469 loss_prob: 1.0268 loss_thr: 0.5499 loss_db: 0.1703 2022/10/26 01:51:10 - mmengine - INFO - Epoch(train) [432][25/63] lr: 2.3678e-03 eta: 11:35:16 time: 0.4997 data_time: 0.0079 memory: 16131 loss: 1.8123 loss_prob: 1.0894 loss_thr: 0.5417 loss_db: 0.1811 2022/10/26 01:51:14 - mmengine - INFO - Epoch(train) [432][30/63] lr: 2.3678e-03 eta: 11:35:02 time: 0.5944 data_time: 0.0107 memory: 16131 loss: 1.8161 loss_prob: 1.0870 loss_thr: 0.5475 loss_db: 0.1816 2022/10/26 01:51:16 - mmengine - INFO - Epoch(train) [432][35/63] lr: 2.3678e-03 eta: 11:35:02 time: 0.5763 data_time: 0.0087 memory: 16131 loss: 1.7117 loss_prob: 0.9730 loss_thr: 0.5739 loss_db: 0.1648 2022/10/26 01:51:19 - mmengine - INFO - Epoch(train) [432][40/63] lr: 2.3678e-03 eta: 11:34:47 time: 0.4984 data_time: 0.0047 memory: 16131 loss: 1.6790 loss_prob: 0.9433 loss_thr: 0.5788 loss_db: 0.1568 2022/10/26 01:51:21 - mmengine - INFO - Epoch(train) [432][45/63] lr: 2.3678e-03 eta: 11:34:47 time: 0.4995 data_time: 0.0062 memory: 16131 loss: 1.7648 loss_prob: 1.0118 loss_thr: 0.5871 loss_db: 0.1659 2022/10/26 01:51:24 - mmengine - INFO - Epoch(train) [432][50/63] lr: 2.3678e-03 eta: 11:34:32 time: 0.5024 data_time: 0.0083 memory: 16131 loss: 1.7577 loss_prob: 1.0227 loss_thr: 0.5730 loss_db: 0.1620 2022/10/26 01:51:26 - mmengine - INFO - Epoch(train) [432][55/63] lr: 2.3678e-03 eta: 11:34:32 time: 0.5203 data_time: 0.0208 memory: 16131 loss: 1.6927 loss_prob: 0.9790 loss_thr: 0.5576 loss_db: 0.1561 2022/10/26 01:51:29 - mmengine - INFO - Epoch(train) [432][60/63] lr: 2.3678e-03 eta: 11:34:18 time: 0.5152 data_time: 0.0185 memory: 16131 loss: 1.7348 loss_prob: 0.9976 loss_thr: 0.5726 loss_db: 0.1646 2022/10/26 01:51:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:51:35 - mmengine - INFO - Epoch(train) [433][5/63] lr: 2.3650e-03 eta: 11:34:18 time: 0.7484 data_time: 0.2066 memory: 16131 loss: 1.8488 loss_prob: 1.0989 loss_thr: 0.5706 loss_db: 0.1793 2022/10/26 01:51:38 - mmengine - INFO - Epoch(train) [433][10/63] lr: 2.3650e-03 eta: 11:34:00 time: 0.7769 data_time: 0.2083 memory: 16131 loss: 1.7907 loss_prob: 1.0531 loss_thr: 0.5701 loss_db: 0.1674 2022/10/26 01:51:40 - mmengine - INFO - Epoch(train) [433][15/63] lr: 2.3650e-03 eta: 11:34:00 time: 0.4964 data_time: 0.0062 memory: 16131 loss: 1.7281 loss_prob: 0.9809 loss_thr: 0.5848 loss_db: 0.1623 2022/10/26 01:51:44 - mmengine - INFO - Epoch(train) [433][20/63] lr: 2.3650e-03 eta: 11:33:46 time: 0.5609 data_time: 0.0094 memory: 16131 loss: 1.7731 loss_prob: 1.0157 loss_thr: 0.5911 loss_db: 0.1664 2022/10/26 01:51:46 - mmengine - INFO - Epoch(train) [433][25/63] lr: 2.3650e-03 eta: 11:33:46 time: 0.5560 data_time: 0.0118 memory: 16131 loss: 1.6892 loss_prob: 0.9654 loss_thr: 0.5688 loss_db: 0.1549 2022/10/26 01:51:49 - mmengine - INFO - Epoch(train) [433][30/63] lr: 2.3650e-03 eta: 11:33:32 time: 0.5497 data_time: 0.0327 memory: 16131 loss: 1.6626 loss_prob: 0.9439 loss_thr: 0.5635 loss_db: 0.1552 2022/10/26 01:51:52 - mmengine - INFO - Epoch(train) [433][35/63] lr: 2.3650e-03 eta: 11:33:32 time: 0.5848 data_time: 0.0307 memory: 16131 loss: 1.5577 loss_prob: 0.8817 loss_thr: 0.5281 loss_db: 0.1479 2022/10/26 01:51:55 - mmengine - INFO - Epoch(train) [433][40/63] lr: 2.3650e-03 eta: 11:33:19 time: 0.5874 data_time: 0.0048 memory: 16131 loss: 1.5717 loss_prob: 0.8931 loss_thr: 0.5288 loss_db: 0.1498 2022/10/26 01:51:58 - mmengine - INFO - Epoch(train) [433][45/63] lr: 2.3650e-03 eta: 11:33:19 time: 0.5801 data_time: 0.0051 memory: 16131 loss: 1.7726 loss_prob: 1.0343 loss_thr: 0.5699 loss_db: 0.1685 2022/10/26 01:52:00 - mmengine - INFO - Epoch(train) [433][50/63] lr: 2.3650e-03 eta: 11:33:04 time: 0.5200 data_time: 0.0189 memory: 16131 loss: 1.6775 loss_prob: 0.9747 loss_thr: 0.5437 loss_db: 0.1590 2022/10/26 01:52:03 - mmengine - INFO - Epoch(train) [433][55/63] lr: 2.3650e-03 eta: 11:33:04 time: 0.5108 data_time: 0.0270 memory: 16131 loss: 1.5946 loss_prob: 0.9097 loss_thr: 0.5336 loss_db: 0.1514 2022/10/26 01:52:05 - mmengine - INFO - Epoch(train) [433][60/63] lr: 2.3650e-03 eta: 11:32:49 time: 0.5053 data_time: 0.0157 memory: 16131 loss: 1.6591 loss_prob: 0.9574 loss_thr: 0.5423 loss_db: 0.1594 2022/10/26 01:52:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:52:11 - mmengine - INFO - Epoch(train) [434][5/63] lr: 2.3622e-03 eta: 11:32:49 time: 0.7043 data_time: 0.1601 memory: 16131 loss: 1.6069 loss_prob: 0.9150 loss_thr: 0.5433 loss_db: 0.1486 2022/10/26 01:52:14 - mmengine - INFO - Epoch(train) [434][10/63] lr: 2.3622e-03 eta: 11:32:31 time: 0.7272 data_time: 0.1613 memory: 16131 loss: 1.6424 loss_prob: 0.9321 loss_thr: 0.5564 loss_db: 0.1539 2022/10/26 01:52:16 - mmengine - INFO - Epoch(train) [434][15/63] lr: 2.3622e-03 eta: 11:32:31 time: 0.4982 data_time: 0.0100 memory: 16131 loss: 1.5946 loss_prob: 0.8870 loss_thr: 0.5552 loss_db: 0.1523 2022/10/26 01:52:19 - mmengine - INFO - Epoch(train) [434][20/63] lr: 2.3622e-03 eta: 11:32:17 time: 0.5208 data_time: 0.0087 memory: 16131 loss: 1.5729 loss_prob: 0.8750 loss_thr: 0.5499 loss_db: 0.1480 2022/10/26 01:52:21 - mmengine - INFO - Epoch(train) [434][25/63] lr: 2.3622e-03 eta: 11:32:17 time: 0.5185 data_time: 0.0151 memory: 16131 loss: 1.8591 loss_prob: 1.1084 loss_thr: 0.5763 loss_db: 0.1744 2022/10/26 01:52:24 - mmengine - INFO - Epoch(train) [434][30/63] lr: 2.3622e-03 eta: 11:32:02 time: 0.5209 data_time: 0.0292 memory: 16131 loss: 1.7538 loss_prob: 1.0498 loss_thr: 0.5385 loss_db: 0.1654 2022/10/26 01:52:27 - mmengine - INFO - Epoch(train) [434][35/63] lr: 2.3622e-03 eta: 11:32:02 time: 0.5521 data_time: 0.0240 memory: 16131 loss: 1.4303 loss_prob: 0.8024 loss_thr: 0.4930 loss_db: 0.1349 2022/10/26 01:52:30 - mmengine - INFO - Epoch(train) [434][40/63] lr: 2.3622e-03 eta: 11:31:49 time: 0.5939 data_time: 0.0157 memory: 16131 loss: 1.4906 loss_prob: 0.8308 loss_thr: 0.5214 loss_db: 0.1384 2022/10/26 01:52:33 - mmengine - INFO - Epoch(train) [434][45/63] lr: 2.3622e-03 eta: 11:31:49 time: 0.5650 data_time: 0.0108 memory: 16131 loss: 1.6185 loss_prob: 0.9167 loss_thr: 0.5508 loss_db: 0.1509 2022/10/26 01:52:35 - mmengine - INFO - Epoch(train) [434][50/63] lr: 2.3622e-03 eta: 11:31:34 time: 0.5304 data_time: 0.0159 memory: 16131 loss: 1.7096 loss_prob: 0.9820 loss_thr: 0.5650 loss_db: 0.1626 2022/10/26 01:52:38 - mmengine - INFO - Epoch(train) [434][55/63] lr: 2.3622e-03 eta: 11:31:34 time: 0.5267 data_time: 0.0223 memory: 16131 loss: 1.7404 loss_prob: 1.0046 loss_thr: 0.5716 loss_db: 0.1642 2022/10/26 01:52:40 - mmengine - INFO - Epoch(train) [434][60/63] lr: 2.3622e-03 eta: 11:31:19 time: 0.4974 data_time: 0.0125 memory: 16131 loss: 1.6690 loss_prob: 0.9541 loss_thr: 0.5611 loss_db: 0.1539 2022/10/26 01:52:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:52:47 - mmengine - INFO - Epoch(train) [435][5/63] lr: 2.3595e-03 eta: 11:31:19 time: 0.7232 data_time: 0.1907 memory: 16131 loss: 1.6229 loss_prob: 0.9098 loss_thr: 0.5625 loss_db: 0.1507 2022/10/26 01:52:49 - mmengine - INFO - Epoch(train) [435][10/63] lr: 2.3595e-03 eta: 11:31:02 time: 0.7544 data_time: 0.1898 memory: 16131 loss: 1.6656 loss_prob: 0.9474 loss_thr: 0.5653 loss_db: 0.1530 2022/10/26 01:52:52 - mmengine - INFO - Epoch(train) [435][15/63] lr: 2.3595e-03 eta: 11:31:02 time: 0.5499 data_time: 0.0053 memory: 16131 loss: 1.6180 loss_prob: 0.9326 loss_thr: 0.5356 loss_db: 0.1498 2022/10/26 01:52:55 - mmengine - INFO - Epoch(train) [435][20/63] lr: 2.3595e-03 eta: 11:30:47 time: 0.5296 data_time: 0.0050 memory: 16131 loss: 1.5257 loss_prob: 0.8600 loss_thr: 0.5227 loss_db: 0.1431 2022/10/26 01:52:57 - mmengine - INFO - Epoch(train) [435][25/63] lr: 2.3595e-03 eta: 11:30:47 time: 0.5158 data_time: 0.0208 memory: 16131 loss: 1.4992 loss_prob: 0.8334 loss_thr: 0.5280 loss_db: 0.1379 2022/10/26 01:53:00 - mmengine - INFO - Epoch(train) [435][30/63] lr: 2.3595e-03 eta: 11:30:33 time: 0.5361 data_time: 0.0346 memory: 16131 loss: 1.4943 loss_prob: 0.8170 loss_thr: 0.5418 loss_db: 0.1355 2022/10/26 01:53:03 - mmengine - INFO - Epoch(train) [435][35/63] lr: 2.3595e-03 eta: 11:30:33 time: 0.5464 data_time: 0.0184 memory: 16131 loss: 1.5246 loss_prob: 0.8365 loss_thr: 0.5451 loss_db: 0.1430 2022/10/26 01:53:06 - mmengine - INFO - Epoch(train) [435][40/63] lr: 2.3595e-03 eta: 11:30:19 time: 0.5595 data_time: 0.0057 memory: 16131 loss: 1.5970 loss_prob: 0.9034 loss_thr: 0.5424 loss_db: 0.1512 2022/10/26 01:53:08 - mmengine - INFO - Epoch(train) [435][45/63] lr: 2.3595e-03 eta: 11:30:19 time: 0.5156 data_time: 0.0075 memory: 16131 loss: 1.5670 loss_prob: 0.8802 loss_thr: 0.5418 loss_db: 0.1450 2022/10/26 01:53:11 - mmengine - INFO - Epoch(train) [435][50/63] lr: 2.3595e-03 eta: 11:30:04 time: 0.5052 data_time: 0.0229 memory: 16131 loss: 1.5982 loss_prob: 0.9038 loss_thr: 0.5453 loss_db: 0.1491 2022/10/26 01:53:13 - mmengine - INFO - Epoch(train) [435][55/63] lr: 2.3595e-03 eta: 11:30:04 time: 0.5250 data_time: 0.0283 memory: 16131 loss: 1.6498 loss_prob: 0.9504 loss_thr: 0.5424 loss_db: 0.1570 2022/10/26 01:53:16 - mmengine - INFO - Epoch(train) [435][60/63] lr: 2.3595e-03 eta: 11:29:50 time: 0.5124 data_time: 0.0125 memory: 16131 loss: 1.5599 loss_prob: 0.8780 loss_thr: 0.5348 loss_db: 0.1470 2022/10/26 01:53:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:53:21 - mmengine - INFO - Epoch(train) [436][5/63] lr: 2.3567e-03 eta: 11:29:50 time: 0.6043 data_time: 0.1414 memory: 16131 loss: 1.4694 loss_prob: 0.8193 loss_thr: 0.5142 loss_db: 0.1359 2022/10/26 01:53:24 - mmengine - INFO - Epoch(train) [436][10/63] lr: 2.3567e-03 eta: 11:29:30 time: 0.6628 data_time: 0.1570 memory: 16131 loss: 1.5421 loss_prob: 0.8654 loss_thr: 0.5318 loss_db: 0.1449 2022/10/26 01:53:26 - mmengine - INFO - Epoch(train) [436][15/63] lr: 2.3567e-03 eta: 11:29:30 time: 0.5208 data_time: 0.0218 memory: 16131 loss: 1.6157 loss_prob: 0.9295 loss_thr: 0.5337 loss_db: 0.1525 2022/10/26 01:53:29 - mmengine - INFO - Epoch(train) [436][20/63] lr: 2.3567e-03 eta: 11:29:16 time: 0.5222 data_time: 0.0057 memory: 16131 loss: 1.6568 loss_prob: 0.9667 loss_thr: 0.5321 loss_db: 0.1580 2022/10/26 01:53:31 - mmengine - INFO - Epoch(train) [436][25/63] lr: 2.3567e-03 eta: 11:29:16 time: 0.5364 data_time: 0.0177 memory: 16131 loss: 1.5993 loss_prob: 0.9054 loss_thr: 0.5417 loss_db: 0.1522 2022/10/26 01:53:34 - mmengine - INFO - Epoch(train) [436][30/63] lr: 2.3567e-03 eta: 11:29:01 time: 0.5148 data_time: 0.0318 memory: 16131 loss: 1.5524 loss_prob: 0.8600 loss_thr: 0.5484 loss_db: 0.1440 2022/10/26 01:53:36 - mmengine - INFO - Epoch(train) [436][35/63] lr: 2.3567e-03 eta: 11:29:01 time: 0.5118 data_time: 0.0198 memory: 16131 loss: 1.6121 loss_prob: 0.9036 loss_thr: 0.5567 loss_db: 0.1518 2022/10/26 01:53:39 - mmengine - INFO - Epoch(train) [436][40/63] lr: 2.3567e-03 eta: 11:28:47 time: 0.4998 data_time: 0.0056 memory: 16131 loss: 1.5772 loss_prob: 0.8784 loss_thr: 0.5492 loss_db: 0.1496 2022/10/26 01:53:41 - mmengine - INFO - Epoch(train) [436][45/63] lr: 2.3567e-03 eta: 11:28:47 time: 0.4927 data_time: 0.0062 memory: 16131 loss: 1.5073 loss_prob: 0.8360 loss_thr: 0.5304 loss_db: 0.1409 2022/10/26 01:53:44 - mmengine - INFO - Epoch(train) [436][50/63] lr: 2.3567e-03 eta: 11:28:32 time: 0.5165 data_time: 0.0140 memory: 16131 loss: 1.4527 loss_prob: 0.8017 loss_thr: 0.5185 loss_db: 0.1324 2022/10/26 01:53:47 - mmengine - INFO - Epoch(train) [436][55/63] lr: 2.3567e-03 eta: 11:28:32 time: 0.5401 data_time: 0.0239 memory: 16131 loss: 1.4748 loss_prob: 0.8222 loss_thr: 0.5153 loss_db: 0.1373 2022/10/26 01:53:49 - mmengine - INFO - Epoch(train) [436][60/63] lr: 2.3567e-03 eta: 11:28:18 time: 0.5279 data_time: 0.0173 memory: 16131 loss: 1.5721 loss_prob: 0.8893 loss_thr: 0.5302 loss_db: 0.1526 2022/10/26 01:53:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:53:55 - mmengine - INFO - Epoch(train) [437][5/63] lr: 2.3539e-03 eta: 11:28:18 time: 0.6852 data_time: 0.1705 memory: 16131 loss: 1.4258 loss_prob: 0.7939 loss_thr: 0.5003 loss_db: 0.1317 2022/10/26 01:53:58 - mmengine - INFO - Epoch(train) [437][10/63] lr: 2.3539e-03 eta: 11:27:59 time: 0.7080 data_time: 0.1710 memory: 16131 loss: 1.4662 loss_prob: 0.8125 loss_thr: 0.5212 loss_db: 0.1325 2022/10/26 01:54:00 - mmengine - INFO - Epoch(train) [437][15/63] lr: 2.3539e-03 eta: 11:27:59 time: 0.4988 data_time: 0.0055 memory: 16131 loss: 1.5632 loss_prob: 0.8778 loss_thr: 0.5401 loss_db: 0.1454 2022/10/26 01:54:03 - mmengine - INFO - Epoch(train) [437][20/63] lr: 2.3539e-03 eta: 11:27:45 time: 0.5181 data_time: 0.0058 memory: 16131 loss: 1.5000 loss_prob: 0.8399 loss_thr: 0.5201 loss_db: 0.1399 2022/10/26 01:54:06 - mmengine - INFO - Epoch(train) [437][25/63] lr: 2.3539e-03 eta: 11:27:45 time: 0.5313 data_time: 0.0152 memory: 16131 loss: 1.5232 loss_prob: 0.8522 loss_thr: 0.5276 loss_db: 0.1435 2022/10/26 01:54:08 - mmengine - INFO - Epoch(train) [437][30/63] lr: 2.3539e-03 eta: 11:27:31 time: 0.5612 data_time: 0.0386 memory: 16131 loss: 1.6558 loss_prob: 0.9459 loss_thr: 0.5476 loss_db: 0.1622 2022/10/26 01:54:11 - mmengine - INFO - Epoch(train) [437][35/63] lr: 2.3539e-03 eta: 11:27:31 time: 0.5406 data_time: 0.0286 memory: 16131 loss: 1.6784 loss_prob: 0.9610 loss_thr: 0.5524 loss_db: 0.1650 2022/10/26 01:54:14 - mmengine - INFO - Epoch(train) [437][40/63] lr: 2.3539e-03 eta: 11:27:16 time: 0.5094 data_time: 0.0063 memory: 16131 loss: 1.6651 loss_prob: 0.9505 loss_thr: 0.5590 loss_db: 0.1556 2022/10/26 01:54:16 - mmengine - INFO - Epoch(train) [437][45/63] lr: 2.3539e-03 eta: 11:27:16 time: 0.5272 data_time: 0.0067 memory: 16131 loss: 1.6408 loss_prob: 0.9380 loss_thr: 0.5507 loss_db: 0.1521 2022/10/26 01:54:19 - mmengine - INFO - Epoch(train) [437][50/63] lr: 2.3539e-03 eta: 11:27:02 time: 0.5425 data_time: 0.0126 memory: 16131 loss: 1.6646 loss_prob: 0.9448 loss_thr: 0.5646 loss_db: 0.1551 2022/10/26 01:54:22 - mmengine - INFO - Epoch(train) [437][55/63] lr: 2.3539e-03 eta: 11:27:02 time: 0.5371 data_time: 0.0221 memory: 16131 loss: 1.6175 loss_prob: 0.9090 loss_thr: 0.5581 loss_db: 0.1504 2022/10/26 01:54:24 - mmengine - INFO - Epoch(train) [437][60/63] lr: 2.3539e-03 eta: 11:26:47 time: 0.5040 data_time: 0.0172 memory: 16131 loss: 1.5231 loss_prob: 0.8577 loss_thr: 0.5220 loss_db: 0.1433 2022/10/26 01:54:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:54:30 - mmengine - INFO - Epoch(train) [438][5/63] lr: 2.3511e-03 eta: 11:26:47 time: 0.7051 data_time: 0.1648 memory: 16131 loss: 1.6579 loss_prob: 0.9605 loss_thr: 0.5490 loss_db: 0.1484 2022/10/26 01:54:33 - mmengine - INFO - Epoch(train) [438][10/63] lr: 2.3511e-03 eta: 11:26:30 time: 0.7750 data_time: 0.1668 memory: 16131 loss: 1.6742 loss_prob: 0.9685 loss_thr: 0.5506 loss_db: 0.1551 2022/10/26 01:54:36 - mmengine - INFO - Epoch(train) [438][15/63] lr: 2.3511e-03 eta: 11:26:30 time: 0.5507 data_time: 0.0131 memory: 16131 loss: 1.6190 loss_prob: 0.9223 loss_thr: 0.5437 loss_db: 0.1530 2022/10/26 01:54:38 - mmengine - INFO - Epoch(train) [438][20/63] lr: 2.3511e-03 eta: 11:26:16 time: 0.5115 data_time: 0.0062 memory: 16131 loss: 1.5819 loss_prob: 0.9067 loss_thr: 0.5301 loss_db: 0.1450 2022/10/26 01:54:41 - mmengine - INFO - Epoch(train) [438][25/63] lr: 2.3511e-03 eta: 11:26:16 time: 0.5308 data_time: 0.0070 memory: 16131 loss: 1.6058 loss_prob: 0.9238 loss_thr: 0.5366 loss_db: 0.1455 2022/10/26 01:54:44 - mmengine - INFO - Epoch(train) [438][30/63] lr: 2.3511e-03 eta: 11:26:02 time: 0.5737 data_time: 0.0298 memory: 16131 loss: 1.7041 loss_prob: 0.9852 loss_thr: 0.5549 loss_db: 0.1640 2022/10/26 01:54:47 - mmengine - INFO - Epoch(train) [438][35/63] lr: 2.3511e-03 eta: 11:26:02 time: 0.5757 data_time: 0.0378 memory: 16131 loss: 1.6899 loss_prob: 0.9541 loss_thr: 0.5741 loss_db: 0.1618 2022/10/26 01:54:49 - mmengine - INFO - Epoch(train) [438][40/63] lr: 2.3511e-03 eta: 11:25:48 time: 0.5188 data_time: 0.0163 memory: 16131 loss: 1.6798 loss_prob: 0.9366 loss_thr: 0.5860 loss_db: 0.1572 2022/10/26 01:54:52 - mmengine - INFO - Epoch(train) [438][45/63] lr: 2.3511e-03 eta: 11:25:48 time: 0.4913 data_time: 0.0061 memory: 16131 loss: 2.0149 loss_prob: 1.2291 loss_thr: 0.5941 loss_db: 0.1917 2022/10/26 01:54:54 - mmengine - INFO - Epoch(train) [438][50/63] lr: 2.3511e-03 eta: 11:25:33 time: 0.5030 data_time: 0.0115 memory: 16131 loss: 1.9285 loss_prob: 1.1831 loss_thr: 0.5600 loss_db: 0.1853 2022/10/26 01:54:57 - mmengine - INFO - Epoch(train) [438][55/63] lr: 2.3511e-03 eta: 11:25:33 time: 0.5344 data_time: 0.0242 memory: 16131 loss: 1.5555 loss_prob: 0.8715 loss_thr: 0.5373 loss_db: 0.1467 2022/10/26 01:55:00 - mmengine - INFO - Epoch(train) [438][60/63] lr: 2.3511e-03 eta: 11:25:19 time: 0.5549 data_time: 0.0194 memory: 16131 loss: 1.5975 loss_prob: 0.9192 loss_thr: 0.5310 loss_db: 0.1473 2022/10/26 01:55:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:55:05 - mmengine - INFO - Epoch(train) [439][5/63] lr: 2.3483e-03 eta: 11:25:19 time: 0.6769 data_time: 0.1908 memory: 16131 loss: 1.5409 loss_prob: 0.8799 loss_thr: 0.5145 loss_db: 0.1465 2022/10/26 01:55:08 - mmengine - INFO - Epoch(train) [439][10/63] lr: 2.3483e-03 eta: 11:25:01 time: 0.7083 data_time: 0.1928 memory: 16131 loss: 1.5821 loss_prob: 0.9090 loss_thr: 0.5214 loss_db: 0.1517 2022/10/26 01:55:11 - mmengine - INFO - Epoch(train) [439][15/63] lr: 2.3483e-03 eta: 11:25:01 time: 0.5162 data_time: 0.0089 memory: 16131 loss: 1.6830 loss_prob: 0.9743 loss_thr: 0.5490 loss_db: 0.1597 2022/10/26 01:55:14 - mmengine - INFO - Epoch(train) [439][20/63] lr: 2.3483e-03 eta: 11:24:47 time: 0.5525 data_time: 0.0083 memory: 16131 loss: 1.6185 loss_prob: 0.9214 loss_thr: 0.5479 loss_db: 0.1491 2022/10/26 01:55:16 - mmengine - INFO - Epoch(train) [439][25/63] lr: 2.3483e-03 eta: 11:24:47 time: 0.5727 data_time: 0.0344 memory: 16131 loss: 1.7577 loss_prob: 0.9907 loss_thr: 0.6028 loss_db: 0.1642 2022/10/26 01:55:19 - mmengine - INFO - Epoch(train) [439][30/63] lr: 2.3483e-03 eta: 11:24:33 time: 0.5488 data_time: 0.0375 memory: 16131 loss: 1.7966 loss_prob: 1.0136 loss_thr: 0.6154 loss_db: 0.1675 2022/10/26 01:55:21 - mmengine - INFO - Epoch(train) [439][35/63] lr: 2.3483e-03 eta: 11:24:33 time: 0.5118 data_time: 0.0087 memory: 16131 loss: 1.6299 loss_prob: 0.9243 loss_thr: 0.5541 loss_db: 0.1515 2022/10/26 01:55:24 - mmengine - INFO - Epoch(train) [439][40/63] lr: 2.3483e-03 eta: 11:24:19 time: 0.4972 data_time: 0.0050 memory: 16131 loss: 1.5890 loss_prob: 0.8983 loss_thr: 0.5409 loss_db: 0.1499 2022/10/26 01:55:27 - mmengine - INFO - Epoch(train) [439][45/63] lr: 2.3483e-03 eta: 11:24:19 time: 0.5077 data_time: 0.0071 memory: 16131 loss: 1.5806 loss_prob: 0.8955 loss_thr: 0.5393 loss_db: 0.1458 2022/10/26 01:55:29 - mmengine - INFO - Epoch(train) [439][50/63] lr: 2.3483e-03 eta: 11:24:04 time: 0.5164 data_time: 0.0225 memory: 16131 loss: 1.5644 loss_prob: 0.8865 loss_thr: 0.5339 loss_db: 0.1439 2022/10/26 01:55:32 - mmengine - INFO - Epoch(train) [439][55/63] lr: 2.3483e-03 eta: 11:24:04 time: 0.5097 data_time: 0.0241 memory: 16131 loss: 1.5945 loss_prob: 0.8965 loss_thr: 0.5512 loss_db: 0.1467 2022/10/26 01:55:34 - mmengine - INFO - Epoch(train) [439][60/63] lr: 2.3483e-03 eta: 11:23:50 time: 0.5167 data_time: 0.0123 memory: 16131 loss: 1.6218 loss_prob: 0.9129 loss_thr: 0.5606 loss_db: 0.1483 2022/10/26 01:55:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:55:40 - mmengine - INFO - Epoch(train) [440][5/63] lr: 2.3456e-03 eta: 11:23:50 time: 0.6766 data_time: 0.1771 memory: 16131 loss: 1.7265 loss_prob: 1.0160 loss_thr: 0.5481 loss_db: 0.1624 2022/10/26 01:55:43 - mmengine - INFO - Epoch(train) [440][10/63] lr: 2.3456e-03 eta: 11:23:31 time: 0.6913 data_time: 0.1843 memory: 16131 loss: 1.5887 loss_prob: 0.9213 loss_thr: 0.5225 loss_db: 0.1449 2022/10/26 01:55:45 - mmengine - INFO - Epoch(train) [440][15/63] lr: 2.3456e-03 eta: 11:23:31 time: 0.5346 data_time: 0.0154 memory: 16131 loss: 1.6435 loss_prob: 0.9528 loss_thr: 0.5398 loss_db: 0.1509 2022/10/26 01:55:49 - mmengine - INFO - Epoch(train) [440][20/63] lr: 2.3456e-03 eta: 11:23:18 time: 0.5976 data_time: 0.0079 memory: 16131 loss: 1.7590 loss_prob: 1.0281 loss_thr: 0.5641 loss_db: 0.1669 2022/10/26 01:55:51 - mmengine - INFO - Epoch(train) [440][25/63] lr: 2.3456e-03 eta: 11:23:18 time: 0.6044 data_time: 0.0171 memory: 16131 loss: 1.6443 loss_prob: 0.9400 loss_thr: 0.5473 loss_db: 0.1571 2022/10/26 01:55:54 - mmengine - INFO - Epoch(train) [440][30/63] lr: 2.3456e-03 eta: 11:23:05 time: 0.5602 data_time: 0.0332 memory: 16131 loss: 1.6303 loss_prob: 0.9288 loss_thr: 0.5475 loss_db: 0.1541 2022/10/26 01:55:57 - mmengine - INFO - Epoch(train) [440][35/63] lr: 2.3456e-03 eta: 11:23:05 time: 0.5207 data_time: 0.0249 memory: 16131 loss: 1.5915 loss_prob: 0.9084 loss_thr: 0.5330 loss_db: 0.1501 2022/10/26 01:55:59 - mmengine - INFO - Epoch(train) [440][40/63] lr: 2.3456e-03 eta: 11:22:50 time: 0.5043 data_time: 0.0162 memory: 16131 loss: 1.6387 loss_prob: 0.9479 loss_thr: 0.5390 loss_db: 0.1518 2022/10/26 01:56:02 - mmengine - INFO - Epoch(train) [440][45/63] lr: 2.3456e-03 eta: 11:22:50 time: 0.5143 data_time: 0.0133 memory: 16131 loss: 1.7250 loss_prob: 1.0091 loss_thr: 0.5545 loss_db: 0.1615 2022/10/26 01:56:04 - mmengine - INFO - Epoch(train) [440][50/63] lr: 2.3456e-03 eta: 11:22:36 time: 0.5197 data_time: 0.0226 memory: 16131 loss: 1.7495 loss_prob: 1.0257 loss_thr: 0.5520 loss_db: 0.1719 2022/10/26 01:56:07 - mmengine - INFO - Epoch(train) [440][55/63] lr: 2.3456e-03 eta: 11:22:36 time: 0.5004 data_time: 0.0243 memory: 16131 loss: 1.9245 loss_prob: 1.1598 loss_thr: 0.5739 loss_db: 0.1908 2022/10/26 01:56:09 - mmengine - INFO - Epoch(train) [440][60/63] lr: 2.3456e-03 eta: 11:22:21 time: 0.5060 data_time: 0.0076 memory: 16131 loss: 1.9368 loss_prob: 1.1705 loss_thr: 0.5801 loss_db: 0.1862 2022/10/26 01:56:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:56:11 - mmengine - INFO - Saving checkpoint at 440 epochs 2022/10/26 01:56:18 - mmengine - INFO - Epoch(val) [440][5/32] eta: 11:22:21 time: 0.5259 data_time: 0.0642 memory: 16131 2022/10/26 01:56:21 - mmengine - INFO - Epoch(val) [440][10/32] eta: 0:00:13 time: 0.6040 data_time: 0.0939 memory: 15724 2022/10/26 01:56:23 - mmengine - INFO - Epoch(val) [440][15/32] eta: 0:00:13 time: 0.5714 data_time: 0.0570 memory: 15724 2022/10/26 01:56:26 - mmengine - INFO - Epoch(val) [440][20/32] eta: 0:00:06 time: 0.5554 data_time: 0.0402 memory: 15724 2022/10/26 01:56:29 - mmengine - INFO - Epoch(val) [440][25/32] eta: 0:00:06 time: 0.5831 data_time: 0.0518 memory: 15724 2022/10/26 01:56:32 - mmengine - INFO - Epoch(val) [440][30/32] eta: 0:00:01 time: 0.5701 data_time: 0.0421 memory: 15724 2022/10/26 01:56:32 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8137, precision: 0.6159, hmean: 0.7011 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8137, precision: 0.7219, hmean: 0.7651 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8103, precision: 0.7835, hmean: 0.7967 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7968, precision: 0.8329, hmean: 0.8145 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7525, precision: 0.8896, hmean: 0.8153 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4377, precision: 0.9629, hmean: 0.6018 2022/10/26 01:56:32 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0005, precision: 1.0000, hmean: 0.0010 2022/10/26 01:56:32 - mmengine - INFO - Epoch(val) [440][32/32] icdar/precision: 0.8896 icdar/recall: 0.7525 icdar/hmean: 0.8153 2022/10/26 01:56:37 - mmengine - INFO - Epoch(train) [441][5/63] lr: 2.3428e-03 eta: 0:00:01 time: 0.7100 data_time: 0.1886 memory: 16131 loss: 1.9134 loss_prob: 1.1210 loss_thr: 0.6058 loss_db: 0.1866 2022/10/26 01:56:40 - mmengine - INFO - Epoch(train) [441][10/63] lr: 2.3428e-03 eta: 11:22:03 time: 0.7039 data_time: 0.2041 memory: 16131 loss: 1.8375 loss_prob: 1.0701 loss_thr: 0.5904 loss_db: 0.1770 2022/10/26 01:56:42 - mmengine - INFO - Epoch(train) [441][15/63] lr: 2.3428e-03 eta: 11:22:03 time: 0.5231 data_time: 0.0223 memory: 16131 loss: 1.6074 loss_prob: 0.9137 loss_thr: 0.5427 loss_db: 0.1511 2022/10/26 01:56:45 - mmengine - INFO - Epoch(train) [441][20/63] lr: 2.3428e-03 eta: 11:21:50 time: 0.5822 data_time: 0.0068 memory: 16131 loss: 1.7231 loss_prob: 0.9941 loss_thr: 0.5573 loss_db: 0.1717 2022/10/26 01:56:48 - mmengine - INFO - Epoch(train) [441][25/63] lr: 2.3428e-03 eta: 11:21:50 time: 0.6222 data_time: 0.0227 memory: 16131 loss: 1.7341 loss_prob: 1.0049 loss_thr: 0.5544 loss_db: 0.1748 2022/10/26 01:56:51 - mmengine - INFO - Epoch(train) [441][30/63] lr: 2.3428e-03 eta: 11:21:36 time: 0.5501 data_time: 0.0350 memory: 16131 loss: 1.7414 loss_prob: 1.0055 loss_thr: 0.5692 loss_db: 0.1667 2022/10/26 01:56:53 - mmengine - INFO - Epoch(train) [441][35/63] lr: 2.3428e-03 eta: 11:21:36 time: 0.4954 data_time: 0.0225 memory: 16131 loss: 1.7468 loss_prob: 1.0132 loss_thr: 0.5683 loss_db: 0.1653 2022/10/26 01:56:56 - mmengine - INFO - Epoch(train) [441][40/63] lr: 2.3428e-03 eta: 11:21:22 time: 0.5504 data_time: 0.0094 memory: 16131 loss: 1.6922 loss_prob: 0.9727 loss_thr: 0.5596 loss_db: 0.1599 2022/10/26 01:56:59 - mmengine - INFO - Epoch(train) [441][45/63] lr: 2.3428e-03 eta: 11:21:22 time: 0.5461 data_time: 0.0052 memory: 16131 loss: 1.6743 loss_prob: 0.9502 loss_thr: 0.5688 loss_db: 0.1553 2022/10/26 01:57:01 - mmengine - INFO - Epoch(train) [441][50/63] lr: 2.3428e-03 eta: 11:21:07 time: 0.4898 data_time: 0.0112 memory: 16131 loss: 1.5830 loss_prob: 0.8904 loss_thr: 0.5473 loss_db: 0.1453 2022/10/26 01:57:04 - mmengine - INFO - Epoch(train) [441][55/63] lr: 2.3428e-03 eta: 11:21:07 time: 0.4990 data_time: 0.0196 memory: 16131 loss: 1.7344 loss_prob: 1.0179 loss_thr: 0.5548 loss_db: 0.1617 2022/10/26 01:57:06 - mmengine - INFO - Epoch(train) [441][60/63] lr: 2.3428e-03 eta: 11:20:53 time: 0.5135 data_time: 0.0154 memory: 16131 loss: 1.7304 loss_prob: 1.0206 loss_thr: 0.5463 loss_db: 0.1634 2022/10/26 01:57:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:57:12 - mmengine - INFO - Epoch(train) [442][5/63] lr: 2.3400e-03 eta: 11:20:53 time: 0.6889 data_time: 0.1772 memory: 16131 loss: 1.5762 loss_prob: 0.8998 loss_thr: 0.5287 loss_db: 0.1478 2022/10/26 01:57:15 - mmengine - INFO - Epoch(train) [442][10/63] lr: 2.3400e-03 eta: 11:20:34 time: 0.6761 data_time: 0.1779 memory: 16131 loss: 1.5483 loss_prob: 0.8784 loss_thr: 0.5248 loss_db: 0.1451 2022/10/26 01:57:17 - mmengine - INFO - Epoch(train) [442][15/63] lr: 2.3400e-03 eta: 11:20:34 time: 0.5237 data_time: 0.0068 memory: 16131 loss: 1.5264 loss_prob: 0.8506 loss_thr: 0.5348 loss_db: 0.1411 2022/10/26 01:57:20 - mmengine - INFO - Epoch(train) [442][20/63] lr: 2.3400e-03 eta: 11:20:20 time: 0.5290 data_time: 0.0066 memory: 16131 loss: 1.5966 loss_prob: 0.8949 loss_thr: 0.5537 loss_db: 0.1480 2022/10/26 01:57:22 - mmengine - INFO - Epoch(train) [442][25/63] lr: 2.3400e-03 eta: 11:20:20 time: 0.4997 data_time: 0.0146 memory: 16131 loss: 1.7665 loss_prob: 1.0237 loss_thr: 0.5815 loss_db: 0.1614 2022/10/26 01:57:25 - mmengine - INFO - Epoch(train) [442][30/63] lr: 2.3400e-03 eta: 11:20:06 time: 0.5081 data_time: 0.0315 memory: 16131 loss: 1.7376 loss_prob: 1.0108 loss_thr: 0.5672 loss_db: 0.1596 2022/10/26 01:57:27 - mmengine - INFO - Epoch(train) [442][35/63] lr: 2.3400e-03 eta: 11:20:06 time: 0.5028 data_time: 0.0250 memory: 16131 loss: 1.5441 loss_prob: 0.8717 loss_thr: 0.5297 loss_db: 0.1428 2022/10/26 01:57:30 - mmengine - INFO - Epoch(train) [442][40/63] lr: 2.3400e-03 eta: 11:19:51 time: 0.4974 data_time: 0.0077 memory: 16131 loss: 1.5600 loss_prob: 0.8824 loss_thr: 0.5352 loss_db: 0.1424 2022/10/26 01:57:32 - mmengine - INFO - Epoch(train) [442][45/63] lr: 2.3400e-03 eta: 11:19:51 time: 0.4997 data_time: 0.0079 memory: 16131 loss: 1.5271 loss_prob: 0.8597 loss_thr: 0.5275 loss_db: 0.1400 2022/10/26 01:57:35 - mmengine - INFO - Epoch(train) [442][50/63] lr: 2.3400e-03 eta: 11:19:36 time: 0.5037 data_time: 0.0147 memory: 16131 loss: 1.4988 loss_prob: 0.8222 loss_thr: 0.5420 loss_db: 0.1345 2022/10/26 01:57:37 - mmengine - INFO - Epoch(train) [442][55/63] lr: 2.3400e-03 eta: 11:19:36 time: 0.5101 data_time: 0.0228 memory: 16131 loss: 1.4495 loss_prob: 0.7823 loss_thr: 0.5366 loss_db: 0.1306 2022/10/26 01:57:40 - mmengine - INFO - Epoch(train) [442][60/63] lr: 2.3400e-03 eta: 11:19:22 time: 0.5113 data_time: 0.0158 memory: 16131 loss: 1.5182 loss_prob: 0.8485 loss_thr: 0.5280 loss_db: 0.1417 2022/10/26 01:57:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:57:47 - mmengine - INFO - Epoch(train) [443][5/63] lr: 2.3372e-03 eta: 11:19:22 time: 0.7559 data_time: 0.2207 memory: 16131 loss: 1.7172 loss_prob: 0.9932 loss_thr: 0.5606 loss_db: 0.1634 2022/10/26 01:57:49 - mmengine - INFO - Epoch(train) [443][10/63] lr: 2.3372e-03 eta: 11:19:05 time: 0.7834 data_time: 0.2190 memory: 16131 loss: 1.5097 loss_prob: 0.8586 loss_thr: 0.5067 loss_db: 0.1444 2022/10/26 01:57:52 - mmengine - INFO - Epoch(train) [443][15/63] lr: 2.3372e-03 eta: 11:19:05 time: 0.5113 data_time: 0.0086 memory: 16131 loss: 1.4741 loss_prob: 0.8311 loss_thr: 0.5068 loss_db: 0.1362 2022/10/26 01:57:54 - mmengine - INFO - Epoch(train) [443][20/63] lr: 2.3372e-03 eta: 11:18:51 time: 0.5255 data_time: 0.0106 memory: 16131 loss: 1.5194 loss_prob: 0.8485 loss_thr: 0.5320 loss_db: 0.1390 2022/10/26 01:57:57 - mmengine - INFO - Epoch(train) [443][25/63] lr: 2.3372e-03 eta: 11:18:51 time: 0.5786 data_time: 0.0269 memory: 16131 loss: 1.5782 loss_prob: 0.9016 loss_thr: 0.5300 loss_db: 0.1466 2022/10/26 01:58:00 - mmengine - INFO - Epoch(train) [443][30/63] lr: 2.3372e-03 eta: 11:18:37 time: 0.5426 data_time: 0.0259 memory: 16131 loss: 1.6284 loss_prob: 0.9344 loss_thr: 0.5416 loss_db: 0.1524 2022/10/26 01:58:03 - mmengine - INFO - Epoch(train) [443][35/63] lr: 2.3372e-03 eta: 11:18:37 time: 0.5189 data_time: 0.0086 memory: 16131 loss: 1.7337 loss_prob: 1.0023 loss_thr: 0.5675 loss_db: 0.1640 2022/10/26 01:58:05 - mmengine - INFO - Epoch(train) [443][40/63] lr: 2.3372e-03 eta: 11:18:24 time: 0.5553 data_time: 0.0115 memory: 16131 loss: 1.6391 loss_prob: 0.9338 loss_thr: 0.5507 loss_db: 0.1545 2022/10/26 01:58:08 - mmengine - INFO - Epoch(train) [443][45/63] lr: 2.3372e-03 eta: 11:18:24 time: 0.5260 data_time: 0.0127 memory: 16131 loss: 1.5290 loss_prob: 0.8549 loss_thr: 0.5308 loss_db: 0.1433 2022/10/26 01:58:11 - mmengine - INFO - Epoch(train) [443][50/63] lr: 2.3372e-03 eta: 11:18:09 time: 0.5080 data_time: 0.0191 memory: 16131 loss: 1.6121 loss_prob: 0.9174 loss_thr: 0.5422 loss_db: 0.1525 2022/10/26 01:58:13 - mmengine - INFO - Epoch(train) [443][55/63] lr: 2.3372e-03 eta: 11:18:09 time: 0.5105 data_time: 0.0175 memory: 16131 loss: 1.5252 loss_prob: 0.8599 loss_thr: 0.5212 loss_db: 0.1441 2022/10/26 01:58:16 - mmengine - INFO - Epoch(train) [443][60/63] lr: 2.3372e-03 eta: 11:17:55 time: 0.5043 data_time: 0.0085 memory: 16131 loss: 1.4320 loss_prob: 0.7973 loss_thr: 0.4995 loss_db: 0.1351 2022/10/26 01:58:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:58:22 - mmengine - INFO - Epoch(train) [444][5/63] lr: 2.3345e-03 eta: 11:17:55 time: 0.7241 data_time: 0.2021 memory: 16131 loss: 1.4946 loss_prob: 0.8351 loss_thr: 0.5218 loss_db: 0.1376 2022/10/26 01:58:24 - mmengine - INFO - Epoch(train) [444][10/63] lr: 2.3345e-03 eta: 11:17:38 time: 0.7504 data_time: 0.2052 memory: 16131 loss: 1.5294 loss_prob: 0.8597 loss_thr: 0.5281 loss_db: 0.1416 2022/10/26 01:58:27 - mmengine - INFO - Epoch(train) [444][15/63] lr: 2.3345e-03 eta: 11:17:38 time: 0.5210 data_time: 0.0122 memory: 16131 loss: 1.5448 loss_prob: 0.8653 loss_thr: 0.5342 loss_db: 0.1452 2022/10/26 01:58:29 - mmengine - INFO - Epoch(train) [444][20/63] lr: 2.3345e-03 eta: 11:17:23 time: 0.5027 data_time: 0.0071 memory: 16131 loss: 1.5821 loss_prob: 0.8837 loss_thr: 0.5516 loss_db: 0.1467 2022/10/26 01:58:32 - mmengine - INFO - Epoch(train) [444][25/63] lr: 2.3345e-03 eta: 11:17:23 time: 0.4883 data_time: 0.0065 memory: 16131 loss: 1.4744 loss_prob: 0.8088 loss_thr: 0.5310 loss_db: 0.1346 2022/10/26 01:58:35 - mmengine - INFO - Epoch(train) [444][30/63] lr: 2.3345e-03 eta: 11:17:09 time: 0.5229 data_time: 0.0246 memory: 16131 loss: 1.4870 loss_prob: 0.8274 loss_thr: 0.5224 loss_db: 0.1373 2022/10/26 01:58:37 - mmengine - INFO - Epoch(train) [444][35/63] lr: 2.3345e-03 eta: 11:17:09 time: 0.5345 data_time: 0.0320 memory: 16131 loss: 1.4932 loss_prob: 0.8359 loss_thr: 0.5182 loss_db: 0.1391 2022/10/26 01:58:40 - mmengine - INFO - Epoch(train) [444][40/63] lr: 2.3345e-03 eta: 11:16:54 time: 0.5047 data_time: 0.0163 memory: 16131 loss: 1.3732 loss_prob: 0.7490 loss_thr: 0.4964 loss_db: 0.1278 2022/10/26 01:58:42 - mmengine - INFO - Epoch(train) [444][45/63] lr: 2.3345e-03 eta: 11:16:54 time: 0.5133 data_time: 0.0072 memory: 16131 loss: 1.4394 loss_prob: 0.7911 loss_thr: 0.5146 loss_db: 0.1336 2022/10/26 01:58:45 - mmengine - INFO - Epoch(train) [444][50/63] lr: 2.3345e-03 eta: 11:16:40 time: 0.5250 data_time: 0.0138 memory: 16131 loss: 1.4663 loss_prob: 0.8099 loss_thr: 0.5212 loss_db: 0.1352 2022/10/26 01:58:47 - mmengine - INFO - Epoch(train) [444][55/63] lr: 2.3345e-03 eta: 11:16:40 time: 0.5093 data_time: 0.0179 memory: 16131 loss: 1.5039 loss_prob: 0.8296 loss_thr: 0.5363 loss_db: 0.1381 2022/10/26 01:58:50 - mmengine - INFO - Epoch(train) [444][60/63] lr: 2.3345e-03 eta: 11:16:26 time: 0.5107 data_time: 0.0131 memory: 16131 loss: 1.5052 loss_prob: 0.8231 loss_thr: 0.5441 loss_db: 0.1380 2022/10/26 01:58:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:58:57 - mmengine - INFO - Epoch(train) [445][5/63] lr: 2.3317e-03 eta: 11:16:26 time: 0.7618 data_time: 0.1939 memory: 16131 loss: 1.5272 loss_prob: 0.8622 loss_thr: 0.5242 loss_db: 0.1408 2022/10/26 01:58:59 - mmengine - INFO - Epoch(train) [445][10/63] lr: 2.3317e-03 eta: 11:16:10 time: 0.8060 data_time: 0.1928 memory: 16131 loss: 1.9149 loss_prob: 1.1647 loss_thr: 0.5703 loss_db: 0.1800 2022/10/26 01:59:02 - mmengine - INFO - Epoch(train) [445][15/63] lr: 2.3317e-03 eta: 11:16:10 time: 0.5465 data_time: 0.0075 memory: 16131 loss: 1.8488 loss_prob: 1.1165 loss_thr: 0.5538 loss_db: 0.1785 2022/10/26 01:59:05 - mmengine - INFO - Epoch(train) [445][20/63] lr: 2.3317e-03 eta: 11:15:55 time: 0.5120 data_time: 0.0059 memory: 16131 loss: 1.6117 loss_prob: 0.9308 loss_thr: 0.5250 loss_db: 0.1558 2022/10/26 01:59:08 - mmengine - INFO - Epoch(train) [445][25/63] lr: 2.3317e-03 eta: 11:15:55 time: 0.5386 data_time: 0.0074 memory: 16131 loss: 1.7410 loss_prob: 1.0518 loss_thr: 0.5256 loss_db: 0.1635 2022/10/26 01:59:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:59:11 - mmengine - INFO - Epoch(train) [445][30/63] lr: 2.3317e-03 eta: 11:15:43 time: 0.5988 data_time: 0.0430 memory: 16131 loss: 1.7769 loss_prob: 1.0645 loss_thr: 0.5452 loss_db: 0.1672 2022/10/26 01:59:13 - mmengine - INFO - Epoch(train) [445][35/63] lr: 2.3317e-03 eta: 11:15:43 time: 0.5788 data_time: 0.0418 memory: 16131 loss: 1.7126 loss_prob: 0.9961 loss_thr: 0.5525 loss_db: 0.1641 2022/10/26 01:59:16 - mmengine - INFO - Epoch(train) [445][40/63] lr: 2.3317e-03 eta: 11:15:29 time: 0.5311 data_time: 0.0056 memory: 16131 loss: 1.6407 loss_prob: 0.9586 loss_thr: 0.5238 loss_db: 0.1584 2022/10/26 01:59:19 - mmengine - INFO - Epoch(train) [445][45/63] lr: 2.3317e-03 eta: 11:15:29 time: 0.5181 data_time: 0.0052 memory: 16131 loss: 1.6686 loss_prob: 0.9628 loss_thr: 0.5438 loss_db: 0.1620 2022/10/26 01:59:21 - mmengine - INFO - Epoch(train) [445][50/63] lr: 2.3317e-03 eta: 11:15:15 time: 0.5531 data_time: 0.0268 memory: 16131 loss: 1.6605 loss_prob: 0.9415 loss_thr: 0.5603 loss_db: 0.1586 2022/10/26 01:59:24 - mmengine - INFO - Epoch(train) [445][55/63] lr: 2.3317e-03 eta: 11:15:15 time: 0.5538 data_time: 0.0305 memory: 16131 loss: 1.6955 loss_prob: 0.9646 loss_thr: 0.5712 loss_db: 0.1597 2022/10/26 01:59:26 - mmengine - INFO - Epoch(train) [445][60/63] lr: 2.3317e-03 eta: 11:15:01 time: 0.5119 data_time: 0.0091 memory: 16131 loss: 1.6859 loss_prob: 0.9511 loss_thr: 0.5760 loss_db: 0.1588 2022/10/26 01:59:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 01:59:33 - mmengine - INFO - Epoch(train) [446][5/63] lr: 2.3289e-03 eta: 11:15:01 time: 0.7690 data_time: 0.1681 memory: 16131 loss: 1.5939 loss_prob: 0.8922 loss_thr: 0.5549 loss_db: 0.1469 2022/10/26 01:59:36 - mmengine - INFO - Epoch(train) [446][10/63] lr: 2.3289e-03 eta: 11:14:45 time: 0.7961 data_time: 0.1683 memory: 16131 loss: 1.6989 loss_prob: 0.9901 loss_thr: 0.5475 loss_db: 0.1613 2022/10/26 01:59:39 - mmengine - INFO - Epoch(train) [446][15/63] lr: 2.3289e-03 eta: 11:14:45 time: 0.5356 data_time: 0.0061 memory: 16131 loss: 1.7281 loss_prob: 0.9938 loss_thr: 0.5668 loss_db: 0.1674 2022/10/26 01:59:41 - mmengine - INFO - Epoch(train) [446][20/63] lr: 2.3289e-03 eta: 11:14:30 time: 0.5067 data_time: 0.0054 memory: 16131 loss: 1.7644 loss_prob: 1.0081 loss_thr: 0.5796 loss_db: 0.1766 2022/10/26 01:59:44 - mmengine - INFO - Epoch(train) [446][25/63] lr: 2.3289e-03 eta: 11:14:30 time: 0.5002 data_time: 0.0143 memory: 16131 loss: 1.8091 loss_prob: 1.0548 loss_thr: 0.5695 loss_db: 0.1848 2022/10/26 01:59:46 - mmengine - INFO - Epoch(train) [446][30/63] lr: 2.3289e-03 eta: 11:14:16 time: 0.5146 data_time: 0.0328 memory: 16131 loss: 1.9114 loss_prob: 1.1684 loss_thr: 0.5601 loss_db: 0.1829 2022/10/26 01:59:49 - mmengine - INFO - Epoch(train) [446][35/63] lr: 2.3289e-03 eta: 11:14:16 time: 0.5083 data_time: 0.0240 memory: 16131 loss: 1.9570 loss_prob: 1.1952 loss_thr: 0.5724 loss_db: 0.1895 2022/10/26 01:59:51 - mmengine - INFO - Epoch(train) [446][40/63] lr: 2.3289e-03 eta: 11:14:01 time: 0.4870 data_time: 0.0070 memory: 16131 loss: 1.9990 loss_prob: 1.2097 loss_thr: 0.5899 loss_db: 0.1994 2022/10/26 01:59:54 - mmengine - INFO - Epoch(train) [446][45/63] lr: 2.3289e-03 eta: 11:14:01 time: 0.4964 data_time: 0.0092 memory: 16131 loss: 2.0902 loss_prob: 1.2730 loss_thr: 0.6108 loss_db: 0.2064 2022/10/26 01:59:56 - mmengine - INFO - Epoch(train) [446][50/63] lr: 2.3289e-03 eta: 11:13:47 time: 0.5314 data_time: 0.0249 memory: 16131 loss: 1.9656 loss_prob: 1.1746 loss_thr: 0.5969 loss_db: 0.1941 2022/10/26 01:59:59 - mmengine - INFO - Epoch(train) [446][55/63] lr: 2.3289e-03 eta: 11:13:47 time: 0.5172 data_time: 0.0216 memory: 16131 loss: 1.9172 loss_prob: 1.1403 loss_thr: 0.5931 loss_db: 0.1838 2022/10/26 02:00:01 - mmengine - INFO - Epoch(train) [446][60/63] lr: 2.3289e-03 eta: 11:13:33 time: 0.4862 data_time: 0.0057 memory: 16131 loss: 1.8810 loss_prob: 1.1175 loss_thr: 0.5855 loss_db: 0.1780 2022/10/26 02:00:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:00:08 - mmengine - INFO - Epoch(train) [447][5/63] lr: 2.3261e-03 eta: 11:13:33 time: 0.7952 data_time: 0.1666 memory: 16131 loss: 1.7371 loss_prob: 1.0253 loss_thr: 0.5446 loss_db: 0.1672 2022/10/26 02:00:11 - mmengine - INFO - Epoch(train) [447][10/63] lr: 2.3261e-03 eta: 11:13:18 time: 0.8711 data_time: 0.1710 memory: 16131 loss: 1.6816 loss_prob: 0.9776 loss_thr: 0.5439 loss_db: 0.1600 2022/10/26 02:00:15 - mmengine - INFO - Epoch(train) [447][15/63] lr: 2.3261e-03 eta: 11:13:18 time: 0.7010 data_time: 0.0124 memory: 16131 loss: 1.6323 loss_prob: 0.9320 loss_thr: 0.5443 loss_db: 0.1560 2022/10/26 02:00:18 - mmengine - INFO - Epoch(train) [447][20/63] lr: 2.3261e-03 eta: 11:13:06 time: 0.6778 data_time: 0.0081 memory: 16131 loss: 1.6847 loss_prob: 0.9655 loss_thr: 0.5617 loss_db: 0.1575 2022/10/26 02:00:21 - mmengine - INFO - Epoch(train) [447][25/63] lr: 2.3261e-03 eta: 11:13:06 time: 0.5627 data_time: 0.0130 memory: 16131 loss: 1.7015 loss_prob: 0.9918 loss_thr: 0.5514 loss_db: 0.1582 2022/10/26 02:00:24 - mmengine - INFO - Epoch(train) [447][30/63] lr: 2.3261e-03 eta: 11:12:53 time: 0.5449 data_time: 0.0320 memory: 16131 loss: 1.6524 loss_prob: 0.9463 loss_thr: 0.5502 loss_db: 0.1558 2022/10/26 02:00:26 - mmengine - INFO - Epoch(train) [447][35/63] lr: 2.3261e-03 eta: 11:12:53 time: 0.5362 data_time: 0.0290 memory: 16131 loss: 1.7320 loss_prob: 0.9936 loss_thr: 0.5709 loss_db: 0.1675 2022/10/26 02:00:29 - mmengine - INFO - Epoch(train) [447][40/63] lr: 2.3261e-03 eta: 11:12:39 time: 0.5491 data_time: 0.0097 memory: 16131 loss: 1.6748 loss_prob: 0.9549 loss_thr: 0.5568 loss_db: 0.1631 2022/10/26 02:00:31 - mmengine - INFO - Epoch(train) [447][45/63] lr: 2.3261e-03 eta: 11:12:39 time: 0.5201 data_time: 0.0058 memory: 16131 loss: 1.5565 loss_prob: 0.8656 loss_thr: 0.5450 loss_db: 0.1459 2022/10/26 02:00:34 - mmengine - INFO - Epoch(train) [447][50/63] lr: 2.3261e-03 eta: 11:12:25 time: 0.4998 data_time: 0.0073 memory: 16131 loss: 1.6373 loss_prob: 0.9296 loss_thr: 0.5497 loss_db: 0.1580 2022/10/26 02:00:37 - mmengine - INFO - Epoch(train) [447][55/63] lr: 2.3261e-03 eta: 11:12:25 time: 0.5156 data_time: 0.0208 memory: 16131 loss: 1.6854 loss_prob: 0.9725 loss_thr: 0.5507 loss_db: 0.1621 2022/10/26 02:00:39 - mmengine - INFO - Epoch(train) [447][60/63] lr: 2.3261e-03 eta: 11:12:10 time: 0.5039 data_time: 0.0196 memory: 16131 loss: 1.5982 loss_prob: 0.9069 loss_thr: 0.5457 loss_db: 0.1456 2022/10/26 02:00:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:00:45 - mmengine - INFO - Epoch(train) [448][5/63] lr: 2.3233e-03 eta: 11:12:10 time: 0.6460 data_time: 0.1729 memory: 16131 loss: 1.5953 loss_prob: 0.9029 loss_thr: 0.5412 loss_db: 0.1513 2022/10/26 02:00:47 - mmengine - INFO - Epoch(train) [448][10/63] lr: 2.3233e-03 eta: 11:11:52 time: 0.6735 data_time: 0.1731 memory: 16131 loss: 1.5281 loss_prob: 0.8660 loss_thr: 0.5193 loss_db: 0.1427 2022/10/26 02:00:50 - mmengine - INFO - Epoch(train) [448][15/63] lr: 2.3233e-03 eta: 11:11:52 time: 0.5134 data_time: 0.0107 memory: 16131 loss: 1.5878 loss_prob: 0.9134 loss_thr: 0.5258 loss_db: 0.1486 2022/10/26 02:00:53 - mmengine - INFO - Epoch(train) [448][20/63] lr: 2.3233e-03 eta: 11:11:40 time: 0.6289 data_time: 0.0126 memory: 16131 loss: 1.7230 loss_prob: 1.0073 loss_thr: 0.5496 loss_db: 0.1661 2022/10/26 02:00:56 - mmengine - INFO - Epoch(train) [448][25/63] lr: 2.3233e-03 eta: 11:11:40 time: 0.6428 data_time: 0.0198 memory: 16131 loss: 1.7772 loss_prob: 1.0386 loss_thr: 0.5649 loss_db: 0.1737 2022/10/26 02:00:59 - mmengine - INFO - Epoch(train) [448][30/63] lr: 2.3233e-03 eta: 11:11:26 time: 0.5306 data_time: 0.0290 memory: 16131 loss: 1.7193 loss_prob: 0.9999 loss_thr: 0.5482 loss_db: 0.1712 2022/10/26 02:01:01 - mmengine - INFO - Epoch(train) [448][35/63] lr: 2.3233e-03 eta: 11:11:26 time: 0.5146 data_time: 0.0217 memory: 16131 loss: 1.6727 loss_prob: 0.9575 loss_thr: 0.5519 loss_db: 0.1633 2022/10/26 02:01:04 - mmengine - INFO - Epoch(train) [448][40/63] lr: 2.3233e-03 eta: 11:11:12 time: 0.5065 data_time: 0.0096 memory: 16131 loss: 1.6289 loss_prob: 0.9164 loss_thr: 0.5597 loss_db: 0.1528 2022/10/26 02:01:06 - mmengine - INFO - Epoch(train) [448][45/63] lr: 2.3233e-03 eta: 11:11:12 time: 0.5133 data_time: 0.0046 memory: 16131 loss: 1.6897 loss_prob: 0.9885 loss_thr: 0.5393 loss_db: 0.1619 2022/10/26 02:01:09 - mmengine - INFO - Epoch(train) [448][50/63] lr: 2.3233e-03 eta: 11:10:58 time: 0.5665 data_time: 0.0157 memory: 16131 loss: 1.6964 loss_prob: 0.9909 loss_thr: 0.5419 loss_db: 0.1635 2022/10/26 02:01:12 - mmengine - INFO - Epoch(train) [448][55/63] lr: 2.3233e-03 eta: 11:10:58 time: 0.5917 data_time: 0.0251 memory: 16131 loss: 1.6313 loss_prob: 0.9108 loss_thr: 0.5629 loss_db: 0.1576 2022/10/26 02:01:15 - mmengine - INFO - Epoch(train) [448][60/63] lr: 2.3233e-03 eta: 11:10:45 time: 0.5354 data_time: 0.0156 memory: 16131 loss: 1.7360 loss_prob: 0.9872 loss_thr: 0.5802 loss_db: 0.1685 2022/10/26 02:01:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:01:20 - mmengine - INFO - Epoch(train) [449][5/63] lr: 2.3206e-03 eta: 11:10:45 time: 0.6489 data_time: 0.1784 memory: 16131 loss: 1.6517 loss_prob: 0.9451 loss_thr: 0.5472 loss_db: 0.1593 2022/10/26 02:01:23 - mmengine - INFO - Epoch(train) [449][10/63] lr: 2.3206e-03 eta: 11:10:27 time: 0.6996 data_time: 0.1834 memory: 16131 loss: 1.7309 loss_prob: 1.0160 loss_thr: 0.5501 loss_db: 0.1648 2022/10/26 02:01:25 - mmengine - INFO - Epoch(train) [449][15/63] lr: 2.3206e-03 eta: 11:10:27 time: 0.5052 data_time: 0.0126 memory: 16131 loss: 1.9179 loss_prob: 1.1500 loss_thr: 0.5866 loss_db: 0.1814 2022/10/26 02:01:28 - mmengine - INFO - Epoch(train) [449][20/63] lr: 2.3206e-03 eta: 11:10:13 time: 0.5189 data_time: 0.0066 memory: 16131 loss: 1.8252 loss_prob: 1.0778 loss_thr: 0.5762 loss_db: 0.1713 2022/10/26 02:01:31 - mmengine - INFO - Epoch(train) [449][25/63] lr: 2.3206e-03 eta: 11:10:13 time: 0.5728 data_time: 0.0303 memory: 16131 loss: 1.6511 loss_prob: 0.9621 loss_thr: 0.5361 loss_db: 0.1528 2022/10/26 02:01:34 - mmengine - INFO - Epoch(train) [449][30/63] lr: 2.3206e-03 eta: 11:09:59 time: 0.5519 data_time: 0.0328 memory: 16131 loss: 1.6218 loss_prob: 0.9413 loss_thr: 0.5275 loss_db: 0.1529 2022/10/26 02:01:36 - mmengine - INFO - Epoch(train) [449][35/63] lr: 2.3206e-03 eta: 11:09:59 time: 0.5121 data_time: 0.0128 memory: 16131 loss: 1.5631 loss_prob: 0.8827 loss_thr: 0.5341 loss_db: 0.1462 2022/10/26 02:01:39 - mmengine - INFO - Epoch(train) [449][40/63] lr: 2.3206e-03 eta: 11:09:45 time: 0.5118 data_time: 0.0093 memory: 16131 loss: 1.5659 loss_prob: 0.8794 loss_thr: 0.5396 loss_db: 0.1468 2022/10/26 02:01:41 - mmengine - INFO - Epoch(train) [449][45/63] lr: 2.3206e-03 eta: 11:09:45 time: 0.5011 data_time: 0.0055 memory: 16131 loss: 1.6022 loss_prob: 0.9024 loss_thr: 0.5464 loss_db: 0.1534 2022/10/26 02:01:44 - mmengine - INFO - Epoch(train) [449][50/63] lr: 2.3206e-03 eta: 11:09:32 time: 0.5470 data_time: 0.0169 memory: 16131 loss: 1.5368 loss_prob: 0.8517 loss_thr: 0.5423 loss_db: 0.1428 2022/10/26 02:01:47 - mmengine - INFO - Epoch(train) [449][55/63] lr: 2.3206e-03 eta: 11:09:32 time: 0.5767 data_time: 0.0224 memory: 16131 loss: 1.5227 loss_prob: 0.8448 loss_thr: 0.5386 loss_db: 0.1393 2022/10/26 02:01:50 - mmengine - INFO - Epoch(train) [449][60/63] lr: 2.3206e-03 eta: 11:09:18 time: 0.5264 data_time: 0.0105 memory: 16131 loss: 1.5119 loss_prob: 0.8426 loss_thr: 0.5289 loss_db: 0.1404 2022/10/26 02:01:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:01:56 - mmengine - INFO - Epoch(train) [450][5/63] lr: 2.3178e-03 eta: 11:09:18 time: 0.7186 data_time: 0.2020 memory: 16131 loss: 1.5818 loss_prob: 0.9141 loss_thr: 0.5177 loss_db: 0.1501 2022/10/26 02:01:58 - mmengine - INFO - Epoch(train) [450][10/63] lr: 2.3178e-03 eta: 11:09:01 time: 0.7427 data_time: 0.1929 memory: 16131 loss: 1.6237 loss_prob: 0.9371 loss_thr: 0.5319 loss_db: 0.1547 2022/10/26 02:02:01 - mmengine - INFO - Epoch(train) [450][15/63] lr: 2.3178e-03 eta: 11:09:01 time: 0.5076 data_time: 0.0058 memory: 16131 loss: 1.7009 loss_prob: 0.9650 loss_thr: 0.5753 loss_db: 0.1606 2022/10/26 02:02:03 - mmengine - INFO - Epoch(train) [450][20/63] lr: 2.3178e-03 eta: 11:08:46 time: 0.5043 data_time: 0.0087 memory: 16131 loss: 1.6341 loss_prob: 0.9257 loss_thr: 0.5564 loss_db: 0.1521 2022/10/26 02:02:06 - mmengine - INFO - Epoch(train) [450][25/63] lr: 2.3178e-03 eta: 11:08:46 time: 0.5309 data_time: 0.0298 memory: 16131 loss: 1.5878 loss_prob: 0.9025 loss_thr: 0.5369 loss_db: 0.1483 2022/10/26 02:02:09 - mmengine - INFO - Epoch(train) [450][30/63] lr: 2.3178e-03 eta: 11:08:33 time: 0.5691 data_time: 0.0392 memory: 16131 loss: 1.6020 loss_prob: 0.9085 loss_thr: 0.5407 loss_db: 0.1528 2022/10/26 02:02:11 - mmengine - INFO - Epoch(train) [450][35/63] lr: 2.3178e-03 eta: 11:08:33 time: 0.5306 data_time: 0.0176 memory: 16131 loss: 1.5281 loss_prob: 0.8544 loss_thr: 0.5303 loss_db: 0.1435 2022/10/26 02:02:14 - mmengine - INFO - Epoch(train) [450][40/63] lr: 2.3178e-03 eta: 11:08:19 time: 0.4975 data_time: 0.0082 memory: 16131 loss: 1.5143 loss_prob: 0.8342 loss_thr: 0.5408 loss_db: 0.1394 2022/10/26 02:02:16 - mmengine - INFO - Epoch(train) [450][45/63] lr: 2.3178e-03 eta: 11:08:19 time: 0.5012 data_time: 0.0089 memory: 16131 loss: 1.5280 loss_prob: 0.8332 loss_thr: 0.5524 loss_db: 0.1423 2022/10/26 02:02:19 - mmengine - INFO - Epoch(train) [450][50/63] lr: 2.3178e-03 eta: 11:08:05 time: 0.5144 data_time: 0.0156 memory: 16131 loss: 1.5092 loss_prob: 0.8300 loss_thr: 0.5397 loss_db: 0.1395 2022/10/26 02:02:22 - mmengine - INFO - Epoch(train) [450][55/63] lr: 2.3178e-03 eta: 11:08:05 time: 0.5845 data_time: 0.0206 memory: 16131 loss: 1.5543 loss_prob: 0.8674 loss_thr: 0.5435 loss_db: 0.1435 2022/10/26 02:02:25 - mmengine - INFO - Epoch(train) [450][60/63] lr: 2.3178e-03 eta: 11:07:52 time: 0.5994 data_time: 0.0119 memory: 16131 loss: 1.5564 loss_prob: 0.8653 loss_thr: 0.5455 loss_db: 0.1456 2022/10/26 02:02:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:02:31 - mmengine - INFO - Epoch(train) [451][5/63] lr: 2.3150e-03 eta: 11:07:52 time: 0.6715 data_time: 0.1971 memory: 16131 loss: 1.6309 loss_prob: 0.9237 loss_thr: 0.5560 loss_db: 0.1513 2022/10/26 02:02:33 - mmengine - INFO - Epoch(train) [451][10/63] lr: 2.3150e-03 eta: 11:07:35 time: 0.7179 data_time: 0.1986 memory: 16131 loss: 1.5386 loss_prob: 0.8591 loss_thr: 0.5379 loss_db: 0.1416 2022/10/26 02:02:36 - mmengine - INFO - Epoch(train) [451][15/63] lr: 2.3150e-03 eta: 11:07:35 time: 0.5330 data_time: 0.0127 memory: 16131 loss: 1.5248 loss_prob: 0.8476 loss_thr: 0.5338 loss_db: 0.1434 2022/10/26 02:02:39 - mmengine - INFO - Epoch(train) [451][20/63] lr: 2.3150e-03 eta: 11:07:21 time: 0.5391 data_time: 0.0135 memory: 16131 loss: 1.4853 loss_prob: 0.8290 loss_thr: 0.5170 loss_db: 0.1394 2022/10/26 02:02:42 - mmengine - INFO - Epoch(train) [451][25/63] lr: 2.3150e-03 eta: 11:07:21 time: 0.5383 data_time: 0.0278 memory: 16131 loss: 1.5025 loss_prob: 0.8380 loss_thr: 0.5239 loss_db: 0.1406 2022/10/26 02:02:45 - mmengine - INFO - Epoch(train) [451][30/63] lr: 2.3150e-03 eta: 11:07:08 time: 0.5777 data_time: 0.0327 memory: 16131 loss: 1.5892 loss_prob: 0.8902 loss_thr: 0.5516 loss_db: 0.1475 2022/10/26 02:02:47 - mmengine - INFO - Epoch(train) [451][35/63] lr: 2.3150e-03 eta: 11:07:08 time: 0.5565 data_time: 0.0130 memory: 16131 loss: 1.4973 loss_prob: 0.8263 loss_thr: 0.5350 loss_db: 0.1359 2022/10/26 02:02:50 - mmengine - INFO - Epoch(train) [451][40/63] lr: 2.3150e-03 eta: 11:06:54 time: 0.5155 data_time: 0.0123 memory: 16131 loss: 1.4401 loss_prob: 0.7971 loss_thr: 0.5099 loss_db: 0.1332 2022/10/26 02:02:52 - mmengine - INFO - Epoch(train) [451][45/63] lr: 2.3150e-03 eta: 11:06:54 time: 0.5152 data_time: 0.0124 memory: 16131 loss: 1.5214 loss_prob: 0.8561 loss_thr: 0.5220 loss_db: 0.1434 2022/10/26 02:02:55 - mmengine - INFO - Epoch(train) [451][50/63] lr: 2.3150e-03 eta: 11:06:40 time: 0.5268 data_time: 0.0304 memory: 16131 loss: 1.6202 loss_prob: 0.9241 loss_thr: 0.5461 loss_db: 0.1501 2022/10/26 02:02:58 - mmengine - INFO - Epoch(train) [451][55/63] lr: 2.3150e-03 eta: 11:06:40 time: 0.5322 data_time: 0.0343 memory: 16131 loss: 1.6180 loss_prob: 0.9368 loss_thr: 0.5304 loss_db: 0.1509 2022/10/26 02:03:00 - mmengine - INFO - Epoch(train) [451][60/63] lr: 2.3150e-03 eta: 11:06:26 time: 0.5027 data_time: 0.0111 memory: 16131 loss: 1.5380 loss_prob: 0.8912 loss_thr: 0.5013 loss_db: 0.1455 2022/10/26 02:03:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:03:06 - mmengine - INFO - Epoch(train) [452][5/63] lr: 2.3122e-03 eta: 11:06:26 time: 0.7097 data_time: 0.1972 memory: 16131 loss: 1.6565 loss_prob: 0.9291 loss_thr: 0.5744 loss_db: 0.1530 2022/10/26 02:03:09 - mmengine - INFO - Epoch(train) [452][10/63] lr: 2.3122e-03 eta: 11:06:09 time: 0.7081 data_time: 0.1927 memory: 16131 loss: 1.8081 loss_prob: 1.0510 loss_thr: 0.5818 loss_db: 0.1753 2022/10/26 02:03:11 - mmengine - INFO - Epoch(train) [452][15/63] lr: 2.3122e-03 eta: 11:06:09 time: 0.4900 data_time: 0.0078 memory: 16131 loss: 1.7823 loss_prob: 1.0404 loss_thr: 0.5676 loss_db: 0.1744 2022/10/26 02:03:14 - mmengine - INFO - Epoch(train) [452][20/63] lr: 2.3122e-03 eta: 11:05:54 time: 0.5065 data_time: 0.0081 memory: 16131 loss: 1.7019 loss_prob: 0.9864 loss_thr: 0.5533 loss_db: 0.1621 2022/10/26 02:03:16 - mmengine - INFO - Epoch(train) [452][25/63] lr: 2.3122e-03 eta: 11:05:54 time: 0.5394 data_time: 0.0321 memory: 16131 loss: 1.6812 loss_prob: 0.9820 loss_thr: 0.5392 loss_db: 0.1601 2022/10/26 02:03:19 - mmengine - INFO - Epoch(train) [452][30/63] lr: 2.3122e-03 eta: 11:05:41 time: 0.5397 data_time: 0.0319 memory: 16131 loss: 1.6211 loss_prob: 0.9125 loss_thr: 0.5560 loss_db: 0.1525 2022/10/26 02:03:22 - mmengine - INFO - Epoch(train) [452][35/63] lr: 2.3122e-03 eta: 11:05:41 time: 0.5290 data_time: 0.0058 memory: 16131 loss: 1.7036 loss_prob: 0.9645 loss_thr: 0.5777 loss_db: 0.1614 2022/10/26 02:03:24 - mmengine - INFO - Epoch(train) [452][40/63] lr: 2.3122e-03 eta: 11:05:27 time: 0.5350 data_time: 0.0061 memory: 16131 loss: 1.5637 loss_prob: 0.8846 loss_thr: 0.5309 loss_db: 0.1483 2022/10/26 02:03:27 - mmengine - INFO - Epoch(train) [452][45/63] lr: 2.3122e-03 eta: 11:05:27 time: 0.5245 data_time: 0.0072 memory: 16131 loss: 1.4745 loss_prob: 0.8366 loss_thr: 0.4976 loss_db: 0.1403 2022/10/26 02:03:30 - mmengine - INFO - Epoch(train) [452][50/63] lr: 2.3122e-03 eta: 11:05:13 time: 0.5155 data_time: 0.0214 memory: 16131 loss: 1.5222 loss_prob: 0.8664 loss_thr: 0.5129 loss_db: 0.1429 2022/10/26 02:03:32 - mmengine - INFO - Epoch(train) [452][55/63] lr: 2.3122e-03 eta: 11:05:13 time: 0.5110 data_time: 0.0274 memory: 16131 loss: 1.4669 loss_prob: 0.8168 loss_thr: 0.5133 loss_db: 0.1368 2022/10/26 02:03:35 - mmengine - INFO - Epoch(train) [452][60/63] lr: 2.3122e-03 eta: 11:04:59 time: 0.5184 data_time: 0.0191 memory: 16131 loss: 1.5707 loss_prob: 0.9018 loss_thr: 0.5189 loss_db: 0.1501 2022/10/26 02:03:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:03:41 - mmengine - INFO - Epoch(train) [453][5/63] lr: 2.3094e-03 eta: 11:04:59 time: 0.7121 data_time: 0.2070 memory: 16131 loss: 1.5673 loss_prob: 0.8835 loss_thr: 0.5405 loss_db: 0.1433 2022/10/26 02:03:43 - mmengine - INFO - Epoch(train) [453][10/63] lr: 2.3094e-03 eta: 11:04:42 time: 0.7083 data_time: 0.2061 memory: 16131 loss: 1.5249 loss_prob: 0.8388 loss_thr: 0.5460 loss_db: 0.1401 2022/10/26 02:03:46 - mmengine - INFO - Epoch(train) [453][15/63] lr: 2.3094e-03 eta: 11:04:42 time: 0.4957 data_time: 0.0049 memory: 16131 loss: 1.5541 loss_prob: 0.8633 loss_thr: 0.5455 loss_db: 0.1453 2022/10/26 02:03:48 - mmengine - INFO - Epoch(train) [453][20/63] lr: 2.3094e-03 eta: 11:04:28 time: 0.5021 data_time: 0.0058 memory: 16131 loss: 1.4845 loss_prob: 0.8332 loss_thr: 0.5123 loss_db: 0.1390 2022/10/26 02:03:51 - mmengine - INFO - Epoch(train) [453][25/63] lr: 2.3094e-03 eta: 11:04:28 time: 0.5113 data_time: 0.0193 memory: 16131 loss: 1.4494 loss_prob: 0.8059 loss_thr: 0.5125 loss_db: 0.1310 2022/10/26 02:03:53 - mmengine - INFO - Epoch(train) [453][30/63] lr: 2.3094e-03 eta: 11:04:14 time: 0.5247 data_time: 0.0318 memory: 16131 loss: 1.5597 loss_prob: 0.8739 loss_thr: 0.5413 loss_db: 0.1445 2022/10/26 02:03:56 - mmengine - INFO - Epoch(train) [453][35/63] lr: 2.3094e-03 eta: 11:04:14 time: 0.5518 data_time: 0.0192 memory: 16131 loss: 1.6853 loss_prob: 0.9626 loss_thr: 0.5630 loss_db: 0.1597 2022/10/26 02:03:59 - mmengine - INFO - Epoch(train) [453][40/63] lr: 2.3094e-03 eta: 11:04:00 time: 0.5293 data_time: 0.0055 memory: 16131 loss: 1.6422 loss_prob: 0.9453 loss_thr: 0.5466 loss_db: 0.1503 2022/10/26 02:04:01 - mmengine - INFO - Epoch(train) [453][45/63] lr: 2.3094e-03 eta: 11:04:00 time: 0.4942 data_time: 0.0071 memory: 16131 loss: 1.6235 loss_prob: 0.9287 loss_thr: 0.5464 loss_db: 0.1483 2022/10/26 02:04:04 - mmengine - INFO - Epoch(train) [453][50/63] lr: 2.3094e-03 eta: 11:03:47 time: 0.5312 data_time: 0.0157 memory: 16131 loss: 1.5933 loss_prob: 0.8925 loss_thr: 0.5522 loss_db: 0.1486 2022/10/26 02:04:07 - mmengine - INFO - Epoch(train) [453][55/63] lr: 2.3094e-03 eta: 11:03:47 time: 0.5672 data_time: 0.0220 memory: 16131 loss: 1.5862 loss_prob: 0.9042 loss_thr: 0.5293 loss_db: 0.1527 2022/10/26 02:04:09 - mmengine - INFO - Epoch(train) [453][60/63] lr: 2.3094e-03 eta: 11:03:33 time: 0.5372 data_time: 0.0135 memory: 16131 loss: 1.5407 loss_prob: 0.8780 loss_thr: 0.5158 loss_db: 0.1469 2022/10/26 02:04:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:04:18 - mmengine - INFO - Epoch(train) [454][5/63] lr: 2.3066e-03 eta: 11:03:33 time: 0.9155 data_time: 0.2220 memory: 16131 loss: 1.4753 loss_prob: 0.8340 loss_thr: 0.5058 loss_db: 0.1355 2022/10/26 02:04:21 - mmengine - INFO - Epoch(train) [454][10/63] lr: 2.3066e-03 eta: 11:03:20 time: 0.9666 data_time: 0.2206 memory: 16131 loss: 1.5286 loss_prob: 0.8711 loss_thr: 0.5151 loss_db: 0.1424 2022/10/26 02:04:23 - mmengine - INFO - Epoch(train) [454][15/63] lr: 2.3066e-03 eta: 11:03:20 time: 0.5907 data_time: 0.0056 memory: 16131 loss: 1.4661 loss_prob: 0.8224 loss_thr: 0.5065 loss_db: 0.1371 2022/10/26 02:04:26 - mmengine - INFO - Epoch(train) [454][20/63] lr: 2.3066e-03 eta: 11:03:06 time: 0.5430 data_time: 0.0077 memory: 16131 loss: 1.5698 loss_prob: 0.8811 loss_thr: 0.5435 loss_db: 0.1452 2022/10/26 02:04:29 - mmengine - INFO - Epoch(train) [454][25/63] lr: 2.3066e-03 eta: 11:03:06 time: 0.5158 data_time: 0.0126 memory: 16131 loss: 1.6775 loss_prob: 0.9454 loss_thr: 0.5767 loss_db: 0.1554 2022/10/26 02:04:31 - mmengine - INFO - Epoch(train) [454][30/63] lr: 2.3066e-03 eta: 11:02:53 time: 0.5194 data_time: 0.0342 memory: 16131 loss: 1.5946 loss_prob: 0.9028 loss_thr: 0.5440 loss_db: 0.1478 2022/10/26 02:04:34 - mmengine - INFO - Epoch(train) [454][35/63] lr: 2.3066e-03 eta: 11:02:53 time: 0.5336 data_time: 0.0293 memory: 16131 loss: 1.5058 loss_prob: 0.8524 loss_thr: 0.5135 loss_db: 0.1399 2022/10/26 02:04:37 - mmengine - INFO - Epoch(train) [454][40/63] lr: 2.3066e-03 eta: 11:02:39 time: 0.5361 data_time: 0.0092 memory: 16131 loss: 1.5033 loss_prob: 0.8452 loss_thr: 0.5178 loss_db: 0.1403 2022/10/26 02:04:39 - mmengine - INFO - Epoch(train) [454][45/63] lr: 2.3066e-03 eta: 11:02:39 time: 0.5149 data_time: 0.0085 memory: 16131 loss: 1.6055 loss_prob: 0.9230 loss_thr: 0.5294 loss_db: 0.1531 2022/10/26 02:04:42 - mmengine - INFO - Epoch(train) [454][50/63] lr: 2.3066e-03 eta: 11:02:25 time: 0.5007 data_time: 0.0193 memory: 16131 loss: 1.6590 loss_prob: 0.9545 loss_thr: 0.5456 loss_db: 0.1588 2022/10/26 02:04:44 - mmengine - INFO - Epoch(train) [454][55/63] lr: 2.3066e-03 eta: 11:02:25 time: 0.5196 data_time: 0.0264 memory: 16131 loss: 1.5988 loss_prob: 0.9053 loss_thr: 0.5458 loss_db: 0.1478 2022/10/26 02:04:47 - mmengine - INFO - Epoch(train) [454][60/63] lr: 2.3066e-03 eta: 11:02:11 time: 0.5136 data_time: 0.0130 memory: 16131 loss: 1.5192 loss_prob: 0.8579 loss_thr: 0.5234 loss_db: 0.1380 2022/10/26 02:04:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:04:53 - mmengine - INFO - Epoch(train) [455][5/63] lr: 2.3039e-03 eta: 11:02:11 time: 0.6828 data_time: 0.1873 memory: 16131 loss: 1.5798 loss_prob: 0.9040 loss_thr: 0.5268 loss_db: 0.1489 2022/10/26 02:04:55 - mmengine - INFO - Epoch(train) [455][10/63] lr: 2.3039e-03 eta: 11:01:54 time: 0.7121 data_time: 0.1892 memory: 16131 loss: 1.5548 loss_prob: 0.8655 loss_thr: 0.5448 loss_db: 0.1445 2022/10/26 02:04:58 - mmengine - INFO - Epoch(train) [455][15/63] lr: 2.3039e-03 eta: 11:01:54 time: 0.4911 data_time: 0.0075 memory: 16131 loss: 1.6709 loss_prob: 0.9436 loss_thr: 0.5688 loss_db: 0.1584 2022/10/26 02:05:00 - mmengine - INFO - Epoch(train) [455][20/63] lr: 2.3039e-03 eta: 11:01:39 time: 0.4854 data_time: 0.0057 memory: 16131 loss: 1.7336 loss_prob: 1.0039 loss_thr: 0.5652 loss_db: 0.1644 2022/10/26 02:05:03 - mmengine - INFO - Epoch(train) [455][25/63] lr: 2.3039e-03 eta: 11:01:39 time: 0.5158 data_time: 0.0150 memory: 16131 loss: 1.7538 loss_prob: 1.0416 loss_thr: 0.5438 loss_db: 0.1684 2022/10/26 02:05:06 - mmengine - INFO - Epoch(train) [455][30/63] lr: 2.3039e-03 eta: 11:01:26 time: 0.5635 data_time: 0.0295 memory: 16131 loss: 1.8850 loss_prob: 1.1318 loss_thr: 0.5690 loss_db: 0.1842 2022/10/26 02:05:08 - mmengine - INFO - Epoch(train) [455][35/63] lr: 2.3039e-03 eta: 11:01:26 time: 0.5817 data_time: 0.0213 memory: 16131 loss: 1.8533 loss_prob: 1.0924 loss_thr: 0.5792 loss_db: 0.1817 2022/10/26 02:05:12 - mmengine - INFO - Epoch(train) [455][40/63] lr: 2.3039e-03 eta: 11:01:14 time: 0.5914 data_time: 0.0073 memory: 16131 loss: 1.7083 loss_prob: 0.9823 loss_thr: 0.5597 loss_db: 0.1663 2022/10/26 02:05:14 - mmengine - INFO - Epoch(train) [455][45/63] lr: 2.3039e-03 eta: 11:01:14 time: 0.5528 data_time: 0.0068 memory: 16131 loss: 1.6178 loss_prob: 0.9305 loss_thr: 0.5326 loss_db: 0.1547 2022/10/26 02:05:17 - mmengine - INFO - Epoch(train) [455][50/63] lr: 2.3039e-03 eta: 11:01:00 time: 0.5168 data_time: 0.0142 memory: 16131 loss: 1.5020 loss_prob: 0.8484 loss_thr: 0.5116 loss_db: 0.1420 2022/10/26 02:05:19 - mmengine - INFO - Epoch(train) [455][55/63] lr: 2.3039e-03 eta: 11:01:00 time: 0.5343 data_time: 0.0258 memory: 16131 loss: 1.6130 loss_prob: 0.9178 loss_thr: 0.5446 loss_db: 0.1506 2022/10/26 02:05:22 - mmengine - INFO - Epoch(train) [455][60/63] lr: 2.3039e-03 eta: 11:00:46 time: 0.5472 data_time: 0.0165 memory: 16131 loss: 1.5111 loss_prob: 0.8569 loss_thr: 0.5140 loss_db: 0.1403 2022/10/26 02:05:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:05:29 - mmengine - INFO - Epoch(train) [456][5/63] lr: 2.3011e-03 eta: 11:00:46 time: 0.7462 data_time: 0.1830 memory: 16131 loss: 1.4592 loss_prob: 0.8271 loss_thr: 0.4923 loss_db: 0.1398 2022/10/26 02:05:31 - mmengine - INFO - Epoch(train) [456][10/63] lr: 2.3011e-03 eta: 11:00:30 time: 0.7625 data_time: 0.1864 memory: 16131 loss: 1.5952 loss_prob: 0.9312 loss_thr: 0.5167 loss_db: 0.1473 2022/10/26 02:05:34 - mmengine - INFO - Epoch(train) [456][15/63] lr: 2.3011e-03 eta: 11:00:30 time: 0.5041 data_time: 0.0079 memory: 16131 loss: 1.6251 loss_prob: 0.9383 loss_thr: 0.5371 loss_db: 0.1496 2022/10/26 02:05:36 - mmengine - INFO - Epoch(train) [456][20/63] lr: 2.3011e-03 eta: 11:00:16 time: 0.5291 data_time: 0.0061 memory: 16131 loss: 1.5156 loss_prob: 0.8417 loss_thr: 0.5336 loss_db: 0.1403 2022/10/26 02:05:39 - mmengine - INFO - Epoch(train) [456][25/63] lr: 2.3011e-03 eta: 11:00:16 time: 0.5717 data_time: 0.0213 memory: 16131 loss: 1.4353 loss_prob: 0.8028 loss_thr: 0.5006 loss_db: 0.1319 2022/10/26 02:05:42 - mmengine - INFO - Epoch(train) [456][30/63] lr: 2.3011e-03 eta: 11:00:03 time: 0.5584 data_time: 0.0303 memory: 16131 loss: 1.3659 loss_prob: 0.7568 loss_thr: 0.4837 loss_db: 0.1253 2022/10/26 02:05:44 - mmengine - INFO - Epoch(train) [456][35/63] lr: 2.3011e-03 eta: 11:00:03 time: 0.5163 data_time: 0.0156 memory: 16131 loss: 1.4539 loss_prob: 0.8081 loss_thr: 0.5126 loss_db: 0.1332 2022/10/26 02:05:47 - mmengine - INFO - Epoch(train) [456][40/63] lr: 2.3011e-03 eta: 10:59:49 time: 0.4951 data_time: 0.0064 memory: 16131 loss: 1.6378 loss_prob: 0.9341 loss_thr: 0.5515 loss_db: 0.1522 2022/10/26 02:05:50 - mmengine - INFO - Epoch(train) [456][45/63] lr: 2.3011e-03 eta: 10:59:49 time: 0.5384 data_time: 0.0075 memory: 16131 loss: 1.6291 loss_prob: 0.9311 loss_thr: 0.5434 loss_db: 0.1546 2022/10/26 02:05:53 - mmengine - INFO - Epoch(train) [456][50/63] lr: 2.3011e-03 eta: 10:59:36 time: 0.5809 data_time: 0.0222 memory: 16131 loss: 1.5418 loss_prob: 0.8545 loss_thr: 0.5434 loss_db: 0.1439 2022/10/26 02:05:56 - mmengine - INFO - Epoch(train) [456][55/63] lr: 2.3011e-03 eta: 10:59:36 time: 0.5975 data_time: 0.0222 memory: 16131 loss: 1.6066 loss_prob: 0.9127 loss_thr: 0.5471 loss_db: 0.1469 2022/10/26 02:05:59 - mmengine - INFO - Epoch(train) [456][60/63] lr: 2.3011e-03 eta: 10:59:24 time: 0.6100 data_time: 0.0083 memory: 16131 loss: 1.6188 loss_prob: 0.9368 loss_thr: 0.5318 loss_db: 0.1502 2022/10/26 02:06:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:06:05 - mmengine - INFO - Epoch(train) [457][5/63] lr: 2.2983e-03 eta: 10:59:24 time: 0.7143 data_time: 0.2194 memory: 16131 loss: 1.6266 loss_prob: 0.9194 loss_thr: 0.5552 loss_db: 0.1521 2022/10/26 02:06:08 - mmengine - INFO - Epoch(train) [457][10/63] lr: 2.2983e-03 eta: 10:59:08 time: 0.8049 data_time: 0.2157 memory: 16131 loss: 1.4897 loss_prob: 0.8211 loss_thr: 0.5332 loss_db: 0.1353 2022/10/26 02:06:11 - mmengine - INFO - Epoch(train) [457][15/63] lr: 2.2983e-03 eta: 10:59:08 time: 0.5640 data_time: 0.0061 memory: 16131 loss: 1.4898 loss_prob: 0.8217 loss_thr: 0.5281 loss_db: 0.1400 2022/10/26 02:06:13 - mmengine - INFO - Epoch(train) [457][20/63] lr: 2.2983e-03 eta: 10:58:55 time: 0.5198 data_time: 0.0074 memory: 16131 loss: 1.5591 loss_prob: 0.8780 loss_thr: 0.5340 loss_db: 0.1470 2022/10/26 02:06:16 - mmengine - INFO - Epoch(train) [457][25/63] lr: 2.2983e-03 eta: 10:58:55 time: 0.5446 data_time: 0.0215 memory: 16131 loss: 1.5327 loss_prob: 0.8711 loss_thr: 0.5201 loss_db: 0.1416 2022/10/26 02:06:19 - mmengine - INFO - Epoch(train) [457][30/63] lr: 2.2983e-03 eta: 10:58:41 time: 0.5348 data_time: 0.0307 memory: 16131 loss: 1.5099 loss_prob: 0.8546 loss_thr: 0.5144 loss_db: 0.1409 2022/10/26 02:06:21 - mmengine - INFO - Epoch(train) [457][35/63] lr: 2.2983e-03 eta: 10:58:41 time: 0.5351 data_time: 0.0170 memory: 16131 loss: 1.5413 loss_prob: 0.8627 loss_thr: 0.5343 loss_db: 0.1443 2022/10/26 02:06:24 - mmengine - INFO - Epoch(train) [457][40/63] lr: 2.2983e-03 eta: 10:58:28 time: 0.5738 data_time: 0.0054 memory: 16131 loss: 1.4635 loss_prob: 0.8044 loss_thr: 0.5218 loss_db: 0.1373 2022/10/26 02:06:27 - mmengine - INFO - Epoch(train) [457][45/63] lr: 2.2983e-03 eta: 10:58:28 time: 0.5821 data_time: 0.0071 memory: 16131 loss: 1.4369 loss_prob: 0.7798 loss_thr: 0.5232 loss_db: 0.1338 2022/10/26 02:06:31 - mmengine - INFO - Epoch(train) [457][50/63] lr: 2.2983e-03 eta: 10:58:16 time: 0.6318 data_time: 0.0194 memory: 16131 loss: 1.5146 loss_prob: 0.8319 loss_thr: 0.5427 loss_db: 0.1400 2022/10/26 02:06:34 - mmengine - INFO - Epoch(train) [457][55/63] lr: 2.2983e-03 eta: 10:58:16 time: 0.6402 data_time: 0.0205 memory: 16131 loss: 1.5910 loss_prob: 0.8816 loss_thr: 0.5625 loss_db: 0.1468 2022/10/26 02:06:36 - mmengine - INFO - Epoch(train) [457][60/63] lr: 2.2983e-03 eta: 10:58:03 time: 0.5457 data_time: 0.0096 memory: 16131 loss: 1.5492 loss_prob: 0.8566 loss_thr: 0.5481 loss_db: 0.1445 2022/10/26 02:06:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:06:42 - mmengine - INFO - Epoch(train) [458][5/63] lr: 2.2955e-03 eta: 10:58:03 time: 0.7116 data_time: 0.1831 memory: 16131 loss: 1.4415 loss_prob: 0.8093 loss_thr: 0.4979 loss_db: 0.1342 2022/10/26 02:06:45 - mmengine - INFO - Epoch(train) [458][10/63] lr: 2.2955e-03 eta: 10:57:46 time: 0.7426 data_time: 0.1845 memory: 16131 loss: 1.4598 loss_prob: 0.8173 loss_thr: 0.5069 loss_db: 0.1356 2022/10/26 02:06:47 - mmengine - INFO - Epoch(train) [458][15/63] lr: 2.2955e-03 eta: 10:57:46 time: 0.5038 data_time: 0.0078 memory: 16131 loss: 1.5721 loss_prob: 0.8924 loss_thr: 0.5289 loss_db: 0.1508 2022/10/26 02:06:50 - mmengine - INFO - Epoch(train) [458][20/63] lr: 2.2955e-03 eta: 10:57:32 time: 0.5008 data_time: 0.0054 memory: 16131 loss: 1.6103 loss_prob: 0.9281 loss_thr: 0.5292 loss_db: 0.1530 2022/10/26 02:06:53 - mmengine - INFO - Epoch(train) [458][25/63] lr: 2.2955e-03 eta: 10:57:32 time: 0.5188 data_time: 0.0236 memory: 16131 loss: 1.5386 loss_prob: 0.8606 loss_thr: 0.5389 loss_db: 0.1391 2022/10/26 02:06:55 - mmengine - INFO - Epoch(train) [458][30/63] lr: 2.2955e-03 eta: 10:57:19 time: 0.5048 data_time: 0.0303 memory: 16131 loss: 1.4121 loss_prob: 0.7648 loss_thr: 0.5210 loss_db: 0.1262 2022/10/26 02:06:58 - mmengine - INFO - Epoch(train) [458][35/63] lr: 2.2955e-03 eta: 10:57:19 time: 0.5028 data_time: 0.0145 memory: 16131 loss: 1.4338 loss_prob: 0.7850 loss_thr: 0.5138 loss_db: 0.1350 2022/10/26 02:07:00 - mmengine - INFO - Epoch(train) [458][40/63] lr: 2.2955e-03 eta: 10:57:05 time: 0.5155 data_time: 0.0076 memory: 16131 loss: 1.6665 loss_prob: 0.9499 loss_thr: 0.5566 loss_db: 0.1600 2022/10/26 02:07:03 - mmengine - INFO - Epoch(train) [458][45/63] lr: 2.2955e-03 eta: 10:57:05 time: 0.5014 data_time: 0.0058 memory: 16131 loss: 1.7717 loss_prob: 1.0455 loss_thr: 0.5603 loss_db: 0.1659 2022/10/26 02:07:05 - mmengine - INFO - Epoch(train) [458][50/63] lr: 2.2955e-03 eta: 10:56:51 time: 0.5312 data_time: 0.0245 memory: 16131 loss: 1.6099 loss_prob: 0.9289 loss_thr: 0.5323 loss_db: 0.1487 2022/10/26 02:07:08 - mmengine - INFO - Epoch(train) [458][55/63] lr: 2.2955e-03 eta: 10:56:51 time: 0.5440 data_time: 0.0258 memory: 16131 loss: 1.5248 loss_prob: 0.8440 loss_thr: 0.5418 loss_db: 0.1389 2022/10/26 02:07:11 - mmengine - INFO - Epoch(train) [458][60/63] lr: 2.2955e-03 eta: 10:56:37 time: 0.5079 data_time: 0.0103 memory: 16131 loss: 1.6256 loss_prob: 0.9395 loss_thr: 0.5359 loss_db: 0.1503 2022/10/26 02:07:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:07:17 - mmengine - INFO - Epoch(train) [459][5/63] lr: 2.2927e-03 eta: 10:56:37 time: 0.7171 data_time: 0.1882 memory: 16131 loss: 1.5882 loss_prob: 0.9379 loss_thr: 0.5067 loss_db: 0.1437 2022/10/26 02:07:19 - mmengine - INFO - Epoch(train) [459][10/63] lr: 2.2927e-03 eta: 10:56:21 time: 0.7366 data_time: 0.1920 memory: 16131 loss: 1.6303 loss_prob: 0.9246 loss_thr: 0.5524 loss_db: 0.1533 2022/10/26 02:07:22 - mmengine - INFO - Epoch(train) [459][15/63] lr: 2.2927e-03 eta: 10:56:21 time: 0.5042 data_time: 0.0107 memory: 16131 loss: 1.6723 loss_prob: 0.9433 loss_thr: 0.5720 loss_db: 0.1569 2022/10/26 02:07:24 - mmengine - INFO - Epoch(train) [459][20/63] lr: 2.2927e-03 eta: 10:56:07 time: 0.4948 data_time: 0.0102 memory: 16131 loss: 1.5324 loss_prob: 0.8680 loss_thr: 0.5216 loss_db: 0.1428 2022/10/26 02:07:27 - mmengine - INFO - Epoch(train) [459][25/63] lr: 2.2927e-03 eta: 10:56:07 time: 0.5201 data_time: 0.0300 memory: 16131 loss: 1.6928 loss_prob: 1.0149 loss_thr: 0.5154 loss_db: 0.1625 2022/10/26 02:07:29 - mmengine - INFO - Epoch(train) [459][30/63] lr: 2.2927e-03 eta: 10:55:53 time: 0.5281 data_time: 0.0287 memory: 16131 loss: 1.7437 loss_prob: 1.0465 loss_thr: 0.5302 loss_db: 0.1669 2022/10/26 02:07:32 - mmengine - INFO - Epoch(train) [459][35/63] lr: 2.2927e-03 eta: 10:55:53 time: 0.4989 data_time: 0.0089 memory: 16131 loss: 1.7355 loss_prob: 1.0185 loss_thr: 0.5502 loss_db: 0.1668 2022/10/26 02:07:35 - mmengine - INFO - Epoch(train) [459][40/63] lr: 2.2927e-03 eta: 10:55:40 time: 0.5345 data_time: 0.0075 memory: 16131 loss: 1.6890 loss_prob: 0.9792 loss_thr: 0.5471 loss_db: 0.1627 2022/10/26 02:07:38 - mmengine - INFO - Epoch(train) [459][45/63] lr: 2.2927e-03 eta: 10:55:40 time: 0.5625 data_time: 0.0099 memory: 16131 loss: 1.5510 loss_prob: 0.8638 loss_thr: 0.5436 loss_db: 0.1436 2022/10/26 02:07:40 - mmengine - INFO - Epoch(train) [459][50/63] lr: 2.2927e-03 eta: 10:55:27 time: 0.5500 data_time: 0.0283 memory: 16131 loss: 1.5889 loss_prob: 0.8855 loss_thr: 0.5589 loss_db: 0.1445 2022/10/26 02:07:43 - mmengine - INFO - Epoch(train) [459][55/63] lr: 2.2927e-03 eta: 10:55:27 time: 0.5364 data_time: 0.0245 memory: 16131 loss: 1.6533 loss_prob: 0.9480 loss_thr: 0.5501 loss_db: 0.1552 2022/10/26 02:07:45 - mmengine - INFO - Epoch(train) [459][60/63] lr: 2.2927e-03 eta: 10:55:13 time: 0.5104 data_time: 0.0112 memory: 16131 loss: 1.6204 loss_prob: 0.9266 loss_thr: 0.5380 loss_db: 0.1558 2022/10/26 02:07:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:07:52 - mmengine - INFO - Epoch(train) [460][5/63] lr: 2.2899e-03 eta: 10:55:13 time: 0.7187 data_time: 0.1963 memory: 16131 loss: 1.5264 loss_prob: 0.8455 loss_thr: 0.5388 loss_db: 0.1421 2022/10/26 02:07:54 - mmengine - INFO - Epoch(train) [460][10/63] lr: 2.2899e-03 eta: 10:54:56 time: 0.7349 data_time: 0.1987 memory: 16131 loss: 1.5003 loss_prob: 0.8259 loss_thr: 0.5370 loss_db: 0.1374 2022/10/26 02:07:57 - mmengine - INFO - Epoch(train) [460][15/63] lr: 2.2899e-03 eta: 10:54:56 time: 0.5085 data_time: 0.0148 memory: 16131 loss: 1.5632 loss_prob: 0.8723 loss_thr: 0.5468 loss_db: 0.1441 2022/10/26 02:07:59 - mmengine - INFO - Epoch(train) [460][20/63] lr: 2.2899e-03 eta: 10:54:43 time: 0.5330 data_time: 0.0187 memory: 16131 loss: 1.5790 loss_prob: 0.8778 loss_thr: 0.5562 loss_db: 0.1450 2022/10/26 02:08:02 - mmengine - INFO - Epoch(train) [460][25/63] lr: 2.2899e-03 eta: 10:54:43 time: 0.5200 data_time: 0.0157 memory: 16131 loss: 1.5029 loss_prob: 0.8346 loss_thr: 0.5290 loss_db: 0.1393 2022/10/26 02:08:05 - mmengine - INFO - Epoch(train) [460][30/63] lr: 2.2899e-03 eta: 10:54:29 time: 0.5214 data_time: 0.0405 memory: 16131 loss: 1.4999 loss_prob: 0.8338 loss_thr: 0.5238 loss_db: 0.1422 2022/10/26 02:08:07 - mmengine - INFO - Epoch(train) [460][35/63] lr: 2.2899e-03 eta: 10:54:29 time: 0.5239 data_time: 0.0380 memory: 16131 loss: 1.5413 loss_prob: 0.8720 loss_thr: 0.5237 loss_db: 0.1455 2022/10/26 02:08:10 - mmengine - INFO - Epoch(train) [460][40/63] lr: 2.2899e-03 eta: 10:54:15 time: 0.5036 data_time: 0.0049 memory: 16131 loss: 1.6161 loss_prob: 0.9285 loss_thr: 0.5352 loss_db: 0.1524 2022/10/26 02:08:12 - mmengine - INFO - Epoch(train) [460][45/63] lr: 2.2899e-03 eta: 10:54:15 time: 0.5074 data_time: 0.0045 memory: 16131 loss: 1.5036 loss_prob: 0.8414 loss_thr: 0.5211 loss_db: 0.1412 2022/10/26 02:08:15 - mmengine - INFO - Epoch(train) [460][50/63] lr: 2.2899e-03 eta: 10:54:01 time: 0.5037 data_time: 0.0189 memory: 16131 loss: 1.4464 loss_prob: 0.7949 loss_thr: 0.5168 loss_db: 0.1347 2022/10/26 02:08:18 - mmengine - INFO - Epoch(train) [460][55/63] lr: 2.2899e-03 eta: 10:54:01 time: 0.5834 data_time: 0.0228 memory: 16131 loss: 1.4361 loss_prob: 0.7940 loss_thr: 0.5079 loss_db: 0.1342 2022/10/26 02:08:20 - mmengine - INFO - Epoch(train) [460][60/63] lr: 2.2899e-03 eta: 10:53:49 time: 0.5736 data_time: 0.0091 memory: 16131 loss: 1.4736 loss_prob: 0.8290 loss_thr: 0.5061 loss_db: 0.1384 2022/10/26 02:08:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:08:22 - mmengine - INFO - Saving checkpoint at 460 epochs 2022/10/26 02:08:28 - mmengine - INFO - Epoch(val) [460][5/32] eta: 10:53:49 time: 0.5367 data_time: 0.0732 memory: 16131 2022/10/26 02:08:31 - mmengine - INFO - Epoch(val) [460][10/32] eta: 0:00:12 time: 0.5779 data_time: 0.0908 memory: 15724 2022/10/26 02:08:34 - mmengine - INFO - Epoch(val) [460][15/32] eta: 0:00:12 time: 0.5227 data_time: 0.0428 memory: 15724 2022/10/26 02:08:36 - mmengine - INFO - Epoch(val) [460][20/32] eta: 0:00:06 time: 0.5402 data_time: 0.0596 memory: 15724 2022/10/26 02:08:39 - mmengine - INFO - Epoch(val) [460][25/32] eta: 0:00:06 time: 0.5482 data_time: 0.0518 memory: 15724 2022/10/26 02:08:42 - mmengine - INFO - Epoch(val) [460][30/32] eta: 0:00:01 time: 0.5069 data_time: 0.0204 memory: 15724 2022/10/26 02:08:42 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7939, precision: 0.7656, hmean: 0.7795 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7939, precision: 0.8204, hmean: 0.8069 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7901, precision: 0.8538, hmean: 0.8207 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7761, precision: 0.8790, hmean: 0.8243 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7400, precision: 0.9073, hmean: 0.8152 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5291, precision: 0.9540, hmean: 0.6807 2022/10/26 02:08:42 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0034, precision: 1.0000, hmean: 0.0067 2022/10/26 02:08:42 - mmengine - INFO - Epoch(val) [460][32/32] icdar/precision: 0.8790 icdar/recall: 0.7761 icdar/hmean: 0.8243 2022/10/26 02:08:47 - mmengine - INFO - Epoch(train) [461][5/63] lr: 2.2872e-03 eta: 0:00:01 time: 0.6816 data_time: 0.1969 memory: 16131 loss: 1.4973 loss_prob: 0.8276 loss_thr: 0.5309 loss_db: 0.1387 2022/10/26 02:08:49 - mmengine - INFO - Epoch(train) [461][10/63] lr: 2.2872e-03 eta: 10:53:32 time: 0.7107 data_time: 0.1998 memory: 16131 loss: 1.3740 loss_prob: 0.7508 loss_thr: 0.4958 loss_db: 0.1274 2022/10/26 02:08:52 - mmengine - INFO - Epoch(train) [461][15/63] lr: 2.2872e-03 eta: 10:53:32 time: 0.5166 data_time: 0.0072 memory: 16131 loss: 1.5043 loss_prob: 0.8316 loss_thr: 0.5326 loss_db: 0.1402 2022/10/26 02:08:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:08:55 - mmengine - INFO - Epoch(train) [461][20/63] lr: 2.2872e-03 eta: 10:53:18 time: 0.5492 data_time: 0.0063 memory: 16131 loss: 1.5799 loss_prob: 0.8735 loss_thr: 0.5600 loss_db: 0.1464 2022/10/26 02:08:58 - mmengine - INFO - Epoch(train) [461][25/63] lr: 2.2872e-03 eta: 10:53:18 time: 0.5683 data_time: 0.0267 memory: 16131 loss: 1.6621 loss_prob: 0.9463 loss_thr: 0.5618 loss_db: 0.1540 2022/10/26 02:09:01 - mmengine - INFO - Epoch(train) [461][30/63] lr: 2.2872e-03 eta: 10:53:06 time: 0.5893 data_time: 0.0342 memory: 16131 loss: 1.6648 loss_prob: 0.9654 loss_thr: 0.5425 loss_db: 0.1568 2022/10/26 02:09:03 - mmengine - INFO - Epoch(train) [461][35/63] lr: 2.2872e-03 eta: 10:53:06 time: 0.5839 data_time: 0.0138 memory: 16131 loss: 1.4974 loss_prob: 0.8387 loss_thr: 0.5175 loss_db: 0.1412 2022/10/26 02:09:06 - mmengine - INFO - Epoch(train) [461][40/63] lr: 2.2872e-03 eta: 10:52:53 time: 0.5268 data_time: 0.0079 memory: 16131 loss: 1.5040 loss_prob: 0.8255 loss_thr: 0.5395 loss_db: 0.1390 2022/10/26 02:09:08 - mmengine - INFO - Epoch(train) [461][45/63] lr: 2.2872e-03 eta: 10:52:53 time: 0.4919 data_time: 0.0091 memory: 16131 loss: 1.5000 loss_prob: 0.8353 loss_thr: 0.5258 loss_db: 0.1389 2022/10/26 02:09:11 - mmengine - INFO - Epoch(train) [461][50/63] lr: 2.2872e-03 eta: 10:52:39 time: 0.5303 data_time: 0.0224 memory: 16131 loss: 1.4782 loss_prob: 0.8263 loss_thr: 0.5160 loss_db: 0.1358 2022/10/26 02:09:14 - mmengine - INFO - Epoch(train) [461][55/63] lr: 2.2872e-03 eta: 10:52:39 time: 0.5308 data_time: 0.0211 memory: 16131 loss: 1.5704 loss_prob: 0.9047 loss_thr: 0.5199 loss_db: 0.1458 2022/10/26 02:09:16 - mmengine - INFO - Epoch(train) [461][60/63] lr: 2.2872e-03 eta: 10:52:25 time: 0.5069 data_time: 0.0062 memory: 16131 loss: 1.6437 loss_prob: 0.9845 loss_thr: 0.4998 loss_db: 0.1594 2022/10/26 02:09:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:09:23 - mmengine - INFO - Epoch(train) [462][5/63] lr: 2.2844e-03 eta: 10:52:25 time: 0.7318 data_time: 0.1746 memory: 16131 loss: 2.0848 loss_prob: 1.3019 loss_thr: 0.5670 loss_db: 0.2159 2022/10/26 02:09:25 - mmengine - INFO - Epoch(train) [462][10/63] lr: 2.2844e-03 eta: 10:52:09 time: 0.7343 data_time: 0.1785 memory: 16131 loss: 1.9107 loss_prob: 1.1614 loss_thr: 0.5645 loss_db: 0.1848 2022/10/26 02:09:28 - mmengine - INFO - Epoch(train) [462][15/63] lr: 2.2844e-03 eta: 10:52:09 time: 0.5193 data_time: 0.0124 memory: 16131 loss: 1.6641 loss_prob: 0.9732 loss_thr: 0.5343 loss_db: 0.1567 2022/10/26 02:09:30 - mmengine - INFO - Epoch(train) [462][20/63] lr: 2.2844e-03 eta: 10:51:55 time: 0.5115 data_time: 0.0063 memory: 16131 loss: 1.6141 loss_prob: 0.9217 loss_thr: 0.5420 loss_db: 0.1504 2022/10/26 02:09:33 - mmengine - INFO - Epoch(train) [462][25/63] lr: 2.2844e-03 eta: 10:51:55 time: 0.5354 data_time: 0.0192 memory: 16131 loss: 1.6683 loss_prob: 0.9572 loss_thr: 0.5577 loss_db: 0.1534 2022/10/26 02:09:36 - mmengine - INFO - Epoch(train) [462][30/63] lr: 2.2844e-03 eta: 10:51:42 time: 0.5499 data_time: 0.0382 memory: 16131 loss: 1.6591 loss_prob: 0.9447 loss_thr: 0.5569 loss_db: 0.1575 2022/10/26 02:09:39 - mmengine - INFO - Epoch(train) [462][35/63] lr: 2.2844e-03 eta: 10:51:42 time: 0.5446 data_time: 0.0248 memory: 16131 loss: 1.5896 loss_prob: 0.8928 loss_thr: 0.5456 loss_db: 0.1512 2022/10/26 02:09:41 - mmengine - INFO - Epoch(train) [462][40/63] lr: 2.2844e-03 eta: 10:51:29 time: 0.5701 data_time: 0.0106 memory: 16131 loss: 1.5603 loss_prob: 0.8715 loss_thr: 0.5462 loss_db: 0.1426 2022/10/26 02:09:44 - mmengine - INFO - Epoch(train) [462][45/63] lr: 2.2844e-03 eta: 10:51:29 time: 0.5315 data_time: 0.0114 memory: 16131 loss: 1.5466 loss_prob: 0.8700 loss_thr: 0.5361 loss_db: 0.1405 2022/10/26 02:09:47 - mmengine - INFO - Epoch(train) [462][50/63] lr: 2.2844e-03 eta: 10:51:16 time: 0.5202 data_time: 0.0123 memory: 16131 loss: 1.5583 loss_prob: 0.8778 loss_thr: 0.5364 loss_db: 0.1440 2022/10/26 02:09:50 - mmengine - INFO - Epoch(train) [462][55/63] lr: 2.2844e-03 eta: 10:51:16 time: 0.5664 data_time: 0.0239 memory: 16131 loss: 1.5736 loss_prob: 0.8885 loss_thr: 0.5354 loss_db: 0.1497 2022/10/26 02:09:52 - mmengine - INFO - Epoch(train) [462][60/63] lr: 2.2844e-03 eta: 10:51:03 time: 0.5743 data_time: 0.0169 memory: 16131 loss: 1.5971 loss_prob: 0.9040 loss_thr: 0.5429 loss_db: 0.1502 2022/10/26 02:09:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:09:58 - mmengine - INFO - Epoch(train) [463][5/63] lr: 2.2816e-03 eta: 10:51:03 time: 0.6816 data_time: 0.1802 memory: 16131 loss: 1.7184 loss_prob: 0.9992 loss_thr: 0.5572 loss_db: 0.1621 2022/10/26 02:10:01 - mmengine - INFO - Epoch(train) [463][10/63] lr: 2.2816e-03 eta: 10:50:47 time: 0.7489 data_time: 0.1810 memory: 16131 loss: 1.5583 loss_prob: 0.8893 loss_thr: 0.5204 loss_db: 0.1487 2022/10/26 02:10:04 - mmengine - INFO - Epoch(train) [463][15/63] lr: 2.2816e-03 eta: 10:50:47 time: 0.5372 data_time: 0.0051 memory: 16131 loss: 1.5041 loss_prob: 0.8441 loss_thr: 0.5192 loss_db: 0.1408 2022/10/26 02:10:07 - mmengine - INFO - Epoch(train) [463][20/63] lr: 2.2816e-03 eta: 10:50:34 time: 0.5568 data_time: 0.0060 memory: 16131 loss: 1.6092 loss_prob: 0.9157 loss_thr: 0.5436 loss_db: 0.1499 2022/10/26 02:10:09 - mmengine - INFO - Epoch(train) [463][25/63] lr: 2.2816e-03 eta: 10:50:34 time: 0.5702 data_time: 0.0164 memory: 16131 loss: 1.6361 loss_prob: 0.9626 loss_thr: 0.5168 loss_db: 0.1567 2022/10/26 02:10:12 - mmengine - INFO - Epoch(train) [463][30/63] lr: 2.2816e-03 eta: 10:50:21 time: 0.5427 data_time: 0.0463 memory: 16131 loss: 1.5751 loss_prob: 0.9237 loss_thr: 0.5032 loss_db: 0.1483 2022/10/26 02:10:15 - mmengine - INFO - Epoch(train) [463][35/63] lr: 2.2816e-03 eta: 10:50:21 time: 0.5330 data_time: 0.0408 memory: 16131 loss: 1.5998 loss_prob: 0.8884 loss_thr: 0.5683 loss_db: 0.1431 2022/10/26 02:10:17 - mmengine - INFO - Epoch(train) [463][40/63] lr: 2.2816e-03 eta: 10:50:07 time: 0.4863 data_time: 0.0105 memory: 16131 loss: 1.6837 loss_prob: 0.9349 loss_thr: 0.5914 loss_db: 0.1573 2022/10/26 02:10:19 - mmengine - INFO - Epoch(train) [463][45/63] lr: 2.2816e-03 eta: 10:50:07 time: 0.4855 data_time: 0.0068 memory: 16131 loss: 1.6146 loss_prob: 0.9158 loss_thr: 0.5473 loss_db: 0.1514 2022/10/26 02:10:22 - mmengine - INFO - Epoch(train) [463][50/63] lr: 2.2816e-03 eta: 10:49:53 time: 0.4950 data_time: 0.0122 memory: 16131 loss: 1.4880 loss_prob: 0.8271 loss_thr: 0.5259 loss_db: 0.1351 2022/10/26 02:10:24 - mmengine - INFO - Epoch(train) [463][55/63] lr: 2.2816e-03 eta: 10:49:53 time: 0.4972 data_time: 0.0233 memory: 16131 loss: 1.5142 loss_prob: 0.8425 loss_thr: 0.5307 loss_db: 0.1410 2022/10/26 02:10:27 - mmengine - INFO - Epoch(train) [463][60/63] lr: 2.2816e-03 eta: 10:49:39 time: 0.4993 data_time: 0.0176 memory: 16131 loss: 1.6102 loss_prob: 0.9102 loss_thr: 0.5474 loss_db: 0.1527 2022/10/26 02:10:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:10:34 - mmengine - INFO - Epoch(train) [464][5/63] lr: 2.2788e-03 eta: 10:49:39 time: 0.7820 data_time: 0.1531 memory: 16131 loss: 1.8368 loss_prob: 1.0994 loss_thr: 0.5712 loss_db: 0.1662 2022/10/26 02:10:37 - mmengine - INFO - Epoch(train) [464][10/63] lr: 2.2788e-03 eta: 10:49:23 time: 0.8128 data_time: 0.1512 memory: 16131 loss: 1.6458 loss_prob: 0.9699 loss_thr: 0.5274 loss_db: 0.1485 2022/10/26 02:10:40 - mmengine - INFO - Epoch(train) [464][15/63] lr: 2.2788e-03 eta: 10:49:23 time: 0.6512 data_time: 0.0079 memory: 16131 loss: 1.3986 loss_prob: 0.7636 loss_thr: 0.5059 loss_db: 0.1290 2022/10/26 02:10:43 - mmengine - INFO - Epoch(train) [464][20/63] lr: 2.2788e-03 eta: 10:49:12 time: 0.6226 data_time: 0.0068 memory: 16131 loss: 1.4958 loss_prob: 0.8454 loss_thr: 0.5101 loss_db: 0.1402 2022/10/26 02:10:45 - mmengine - INFO - Epoch(train) [464][25/63] lr: 2.2788e-03 eta: 10:49:12 time: 0.5196 data_time: 0.0121 memory: 16131 loss: 1.4897 loss_prob: 0.8345 loss_thr: 0.5179 loss_db: 0.1374 2022/10/26 02:10:48 - mmengine - INFO - Epoch(train) [464][30/63] lr: 2.2788e-03 eta: 10:48:59 time: 0.5444 data_time: 0.0351 memory: 16131 loss: 1.5820 loss_prob: 0.8895 loss_thr: 0.5481 loss_db: 0.1443 2022/10/26 02:10:51 - mmengine - INFO - Epoch(train) [464][35/63] lr: 2.2788e-03 eta: 10:48:59 time: 0.5574 data_time: 0.0281 memory: 16131 loss: 1.6473 loss_prob: 0.9339 loss_thr: 0.5606 loss_db: 0.1528 2022/10/26 02:10:53 - mmengine - INFO - Epoch(train) [464][40/63] lr: 2.2788e-03 eta: 10:48:45 time: 0.5108 data_time: 0.0079 memory: 16131 loss: 1.5251 loss_prob: 0.8349 loss_thr: 0.5496 loss_db: 0.1406 2022/10/26 02:10:56 - mmengine - INFO - Epoch(train) [464][45/63] lr: 2.2788e-03 eta: 10:48:45 time: 0.5099 data_time: 0.0079 memory: 16131 loss: 1.4806 loss_prob: 0.8039 loss_thr: 0.5439 loss_db: 0.1328 2022/10/26 02:10:59 - mmengine - INFO - Epoch(train) [464][50/63] lr: 2.2788e-03 eta: 10:48:32 time: 0.5417 data_time: 0.0090 memory: 16131 loss: 1.5207 loss_prob: 0.8420 loss_thr: 0.5392 loss_db: 0.1395 2022/10/26 02:11:02 - mmengine - INFO - Epoch(train) [464][55/63] lr: 2.2788e-03 eta: 10:48:32 time: 0.5607 data_time: 0.0220 memory: 16131 loss: 1.5580 loss_prob: 0.8719 loss_thr: 0.5402 loss_db: 0.1460 2022/10/26 02:11:04 - mmengine - INFO - Epoch(train) [464][60/63] lr: 2.2788e-03 eta: 10:48:19 time: 0.5464 data_time: 0.0229 memory: 16131 loss: 1.7485 loss_prob: 1.0170 loss_thr: 0.5626 loss_db: 0.1689 2022/10/26 02:11:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:11:11 - mmengine - INFO - Epoch(train) [465][5/63] lr: 2.2760e-03 eta: 10:48:19 time: 0.7607 data_time: 0.2190 memory: 16131 loss: 1.7036 loss_prob: 0.9722 loss_thr: 0.5652 loss_db: 0.1661 2022/10/26 02:11:14 - mmengine - INFO - Epoch(train) [465][10/63] lr: 2.2760e-03 eta: 10:48:03 time: 0.8105 data_time: 0.2176 memory: 16131 loss: 1.4556 loss_prob: 0.8059 loss_thr: 0.5119 loss_db: 0.1379 2022/10/26 02:11:17 - mmengine - INFO - Epoch(train) [465][15/63] lr: 2.2760e-03 eta: 10:48:03 time: 0.5772 data_time: 0.0048 memory: 16131 loss: 1.5255 loss_prob: 0.8607 loss_thr: 0.5150 loss_db: 0.1498 2022/10/26 02:11:19 - mmengine - INFO - Epoch(train) [465][20/63] lr: 2.2760e-03 eta: 10:47:51 time: 0.5809 data_time: 0.0050 memory: 16131 loss: 1.8172 loss_prob: 1.0828 loss_thr: 0.5629 loss_db: 0.1715 2022/10/26 02:11:22 - mmengine - INFO - Epoch(train) [465][25/63] lr: 2.2760e-03 eta: 10:47:51 time: 0.5372 data_time: 0.0160 memory: 16131 loss: 1.7978 loss_prob: 1.0716 loss_thr: 0.5593 loss_db: 0.1669 2022/10/26 02:11:25 - mmengine - INFO - Epoch(train) [465][30/63] lr: 2.2760e-03 eta: 10:47:38 time: 0.5168 data_time: 0.0327 memory: 16131 loss: 1.6030 loss_prob: 0.9145 loss_thr: 0.5367 loss_db: 0.1518 2022/10/26 02:11:27 - mmengine - INFO - Epoch(train) [465][35/63] lr: 2.2760e-03 eta: 10:47:38 time: 0.5359 data_time: 0.0215 memory: 16131 loss: 1.6582 loss_prob: 0.9471 loss_thr: 0.5567 loss_db: 0.1544 2022/10/26 02:11:30 - mmengine - INFO - Epoch(train) [465][40/63] lr: 2.2760e-03 eta: 10:47:24 time: 0.5112 data_time: 0.0042 memory: 16131 loss: 1.7386 loss_prob: 1.0172 loss_thr: 0.5571 loss_db: 0.1643 2022/10/26 02:11:32 - mmengine - INFO - Epoch(train) [465][45/63] lr: 2.2760e-03 eta: 10:47:24 time: 0.5042 data_time: 0.0046 memory: 16131 loss: 1.9131 loss_prob: 1.1567 loss_thr: 0.5681 loss_db: 0.1883 2022/10/26 02:11:35 - mmengine - INFO - Epoch(train) [465][50/63] lr: 2.2760e-03 eta: 10:47:11 time: 0.5301 data_time: 0.0199 memory: 16131 loss: 1.8299 loss_prob: 1.0853 loss_thr: 0.5645 loss_db: 0.1801 2022/10/26 02:11:38 - mmengine - INFO - Epoch(train) [465][55/63] lr: 2.2760e-03 eta: 10:47:11 time: 0.5181 data_time: 0.0230 memory: 16131 loss: 1.5799 loss_prob: 0.9001 loss_thr: 0.5302 loss_db: 0.1496 2022/10/26 02:11:40 - mmengine - INFO - Epoch(train) [465][60/63] lr: 2.2760e-03 eta: 10:46:57 time: 0.5055 data_time: 0.0079 memory: 16131 loss: 1.4499 loss_prob: 0.8111 loss_thr: 0.5036 loss_db: 0.1351 2022/10/26 02:11:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:11:46 - mmengine - INFO - Epoch(train) [466][5/63] lr: 2.2732e-03 eta: 10:46:57 time: 0.7042 data_time: 0.2200 memory: 16131 loss: 1.5069 loss_prob: 0.8407 loss_thr: 0.5299 loss_db: 0.1364 2022/10/26 02:11:49 - mmengine - INFO - Epoch(train) [466][10/63] lr: 2.2732e-03 eta: 10:46:41 time: 0.7380 data_time: 0.2223 memory: 16131 loss: 1.5609 loss_prob: 0.8704 loss_thr: 0.5467 loss_db: 0.1438 2022/10/26 02:11:51 - mmengine - INFO - Epoch(train) [466][15/63] lr: 2.2732e-03 eta: 10:46:41 time: 0.5110 data_time: 0.0084 memory: 16131 loss: 1.6085 loss_prob: 0.9039 loss_thr: 0.5543 loss_db: 0.1502 2022/10/26 02:11:54 - mmengine - INFO - Epoch(train) [466][20/63] lr: 2.2732e-03 eta: 10:46:27 time: 0.5362 data_time: 0.0068 memory: 16131 loss: 1.6735 loss_prob: 0.9843 loss_thr: 0.5302 loss_db: 0.1590 2022/10/26 02:11:57 - mmengine - INFO - Epoch(train) [466][25/63] lr: 2.2732e-03 eta: 10:46:27 time: 0.5551 data_time: 0.0287 memory: 16131 loss: 1.7988 loss_prob: 1.0611 loss_thr: 0.5575 loss_db: 0.1802 2022/10/26 02:11:59 - mmengine - INFO - Epoch(train) [466][30/63] lr: 2.2732e-03 eta: 10:46:14 time: 0.5184 data_time: 0.0335 memory: 16131 loss: 1.7147 loss_prob: 0.9804 loss_thr: 0.5618 loss_db: 0.1725 2022/10/26 02:12:02 - mmengine - INFO - Epoch(train) [466][35/63] lr: 2.2732e-03 eta: 10:46:14 time: 0.5077 data_time: 0.0099 memory: 16131 loss: 1.6976 loss_prob: 0.9734 loss_thr: 0.5588 loss_db: 0.1654 2022/10/26 02:12:04 - mmengine - INFO - Epoch(train) [466][40/63] lr: 2.2732e-03 eta: 10:46:00 time: 0.5040 data_time: 0.0047 memory: 16131 loss: 1.7257 loss_prob: 0.9978 loss_thr: 0.5610 loss_db: 0.1670 2022/10/26 02:12:07 - mmengine - INFO - Epoch(train) [466][45/63] lr: 2.2732e-03 eta: 10:46:00 time: 0.5056 data_time: 0.0047 memory: 16131 loss: 1.6060 loss_prob: 0.9143 loss_thr: 0.5349 loss_db: 0.1567 2022/10/26 02:12:10 - mmengine - INFO - Epoch(train) [466][50/63] lr: 2.2732e-03 eta: 10:45:47 time: 0.5203 data_time: 0.0180 memory: 16131 loss: 1.5584 loss_prob: 0.8743 loss_thr: 0.5329 loss_db: 0.1512 2022/10/26 02:12:12 - mmengine - INFO - Epoch(train) [466][55/63] lr: 2.2732e-03 eta: 10:45:47 time: 0.5018 data_time: 0.0214 memory: 16131 loss: 1.5219 loss_prob: 0.8403 loss_thr: 0.5417 loss_db: 0.1399 2022/10/26 02:12:15 - mmengine - INFO - Epoch(train) [466][60/63] lr: 2.2732e-03 eta: 10:45:34 time: 0.5203 data_time: 0.0096 memory: 16131 loss: 1.5083 loss_prob: 0.8282 loss_thr: 0.5404 loss_db: 0.1396 2022/10/26 02:12:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:12:21 - mmengine - INFO - Epoch(train) [467][5/63] lr: 2.2704e-03 eta: 10:45:34 time: 0.7023 data_time: 0.1804 memory: 16131 loss: 1.5642 loss_prob: 0.8945 loss_thr: 0.5235 loss_db: 0.1462 2022/10/26 02:12:24 - mmengine - INFO - Epoch(train) [467][10/63] lr: 2.2704e-03 eta: 10:45:18 time: 0.7695 data_time: 0.1940 memory: 16131 loss: 1.6641 loss_prob: 0.9534 loss_thr: 0.5565 loss_db: 0.1543 2022/10/26 02:12:26 - mmengine - INFO - Epoch(train) [467][15/63] lr: 2.2704e-03 eta: 10:45:18 time: 0.5578 data_time: 0.0185 memory: 16131 loss: 1.6658 loss_prob: 0.9444 loss_thr: 0.5648 loss_db: 0.1566 2022/10/26 02:12:29 - mmengine - INFO - Epoch(train) [467][20/63] lr: 2.2704e-03 eta: 10:45:04 time: 0.5147 data_time: 0.0065 memory: 16131 loss: 1.5620 loss_prob: 0.8733 loss_thr: 0.5413 loss_db: 0.1473 2022/10/26 02:12:31 - mmengine - INFO - Epoch(train) [467][25/63] lr: 2.2704e-03 eta: 10:45:04 time: 0.5072 data_time: 0.0219 memory: 16131 loss: 1.6542 loss_prob: 0.9655 loss_thr: 0.5339 loss_db: 0.1548 2022/10/26 02:12:34 - mmengine - INFO - Epoch(train) [467][30/63] lr: 2.2704e-03 eta: 10:44:51 time: 0.5067 data_time: 0.0288 memory: 16131 loss: 1.6529 loss_prob: 0.9681 loss_thr: 0.5308 loss_db: 0.1541 2022/10/26 02:12:36 - mmengine - INFO - Epoch(train) [467][35/63] lr: 2.2704e-03 eta: 10:44:51 time: 0.5168 data_time: 0.0241 memory: 16131 loss: 1.4386 loss_prob: 0.7974 loss_thr: 0.5088 loss_db: 0.1323 2022/10/26 02:12:39 - mmengine - INFO - Epoch(train) [467][40/63] lr: 2.2704e-03 eta: 10:44:37 time: 0.5116 data_time: 0.0157 memory: 16131 loss: 1.4018 loss_prob: 0.7724 loss_thr: 0.5013 loss_db: 0.1281 2022/10/26 02:12:42 - mmengine - INFO - Epoch(train) [467][45/63] lr: 2.2704e-03 eta: 10:44:37 time: 0.5031 data_time: 0.0053 memory: 16131 loss: 1.5083 loss_prob: 0.8348 loss_thr: 0.5347 loss_db: 0.1389 2022/10/26 02:12:44 - mmengine - INFO - Epoch(train) [467][50/63] lr: 2.2704e-03 eta: 10:44:24 time: 0.5212 data_time: 0.0156 memory: 16131 loss: 1.6252 loss_prob: 0.9060 loss_thr: 0.5694 loss_db: 0.1498 2022/10/26 02:12:47 - mmengine - INFO - Epoch(train) [467][55/63] lr: 2.2704e-03 eta: 10:44:24 time: 0.5384 data_time: 0.0231 memory: 16131 loss: 1.6241 loss_prob: 0.8977 loss_thr: 0.5768 loss_db: 0.1496 2022/10/26 02:12:50 - mmengine - INFO - Epoch(train) [467][60/63] lr: 2.2704e-03 eta: 10:44:11 time: 0.5461 data_time: 0.0140 memory: 16131 loss: 1.6035 loss_prob: 0.8911 loss_thr: 0.5666 loss_db: 0.1458 2022/10/26 02:12:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:12:56 - mmengine - INFO - Epoch(train) [468][5/63] lr: 2.2677e-03 eta: 10:44:11 time: 0.6923 data_time: 0.1950 memory: 16131 loss: 1.4349 loss_prob: 0.7993 loss_thr: 0.5049 loss_db: 0.1307 2022/10/26 02:12:58 - mmengine - INFO - Epoch(train) [468][10/63] lr: 2.2677e-03 eta: 10:43:54 time: 0.7066 data_time: 0.1958 memory: 16131 loss: 1.4599 loss_prob: 0.8131 loss_thr: 0.5117 loss_db: 0.1351 2022/10/26 02:13:01 - mmengine - INFO - Epoch(train) [468][15/63] lr: 2.2677e-03 eta: 10:43:54 time: 0.5346 data_time: 0.0149 memory: 16131 loss: 1.5884 loss_prob: 0.8910 loss_thr: 0.5477 loss_db: 0.1497 2022/10/26 02:13:03 - mmengine - INFO - Epoch(train) [468][20/63] lr: 2.2677e-03 eta: 10:43:41 time: 0.5363 data_time: 0.0215 memory: 16131 loss: 1.5299 loss_prob: 0.8539 loss_thr: 0.5292 loss_db: 0.1468 2022/10/26 02:13:06 - mmengine - INFO - Epoch(train) [468][25/63] lr: 2.2677e-03 eta: 10:43:41 time: 0.5117 data_time: 0.0215 memory: 16131 loss: 1.4380 loss_prob: 0.7977 loss_thr: 0.5049 loss_db: 0.1353 2022/10/26 02:13:09 - mmengine - INFO - Epoch(train) [468][30/63] lr: 2.2677e-03 eta: 10:43:28 time: 0.5613 data_time: 0.0305 memory: 16131 loss: 1.5292 loss_prob: 0.8569 loss_thr: 0.5313 loss_db: 0.1411 2022/10/26 02:13:12 - mmengine - INFO - Epoch(train) [468][35/63] lr: 2.2677e-03 eta: 10:43:28 time: 0.5715 data_time: 0.0221 memory: 16131 loss: 1.5606 loss_prob: 0.8750 loss_thr: 0.5426 loss_db: 0.1430 2022/10/26 02:13:14 - mmengine - INFO - Epoch(train) [468][40/63] lr: 2.2677e-03 eta: 10:43:15 time: 0.5267 data_time: 0.0119 memory: 16131 loss: 1.5483 loss_prob: 0.8657 loss_thr: 0.5388 loss_db: 0.1438 2022/10/26 02:13:17 - mmengine - INFO - Epoch(train) [468][45/63] lr: 2.2677e-03 eta: 10:43:15 time: 0.5255 data_time: 0.0108 memory: 16131 loss: 1.4760 loss_prob: 0.8273 loss_thr: 0.5087 loss_db: 0.1400 2022/10/26 02:13:20 - mmengine - INFO - Epoch(train) [468][50/63] lr: 2.2677e-03 eta: 10:43:02 time: 0.5250 data_time: 0.0131 memory: 16131 loss: 1.4147 loss_prob: 0.7760 loss_thr: 0.5052 loss_db: 0.1334 2022/10/26 02:13:22 - mmengine - INFO - Epoch(train) [468][55/63] lr: 2.2677e-03 eta: 10:43:02 time: 0.4993 data_time: 0.0196 memory: 16131 loss: 1.4993 loss_prob: 0.8223 loss_thr: 0.5356 loss_db: 0.1414 2022/10/26 02:13:25 - mmengine - INFO - Epoch(train) [468][60/63] lr: 2.2677e-03 eta: 10:42:48 time: 0.4954 data_time: 0.0124 memory: 16131 loss: 1.7722 loss_prob: 1.0546 loss_thr: 0.5544 loss_db: 0.1632 2022/10/26 02:13:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:13:30 - mmengine - INFO - Epoch(train) [469][5/63] lr: 2.2649e-03 eta: 10:42:48 time: 0.6775 data_time: 0.1968 memory: 16131 loss: 1.4750 loss_prob: 0.8257 loss_thr: 0.5077 loss_db: 0.1416 2022/10/26 02:13:33 - mmengine - INFO - Epoch(train) [469][10/63] lr: 2.2649e-03 eta: 10:42:31 time: 0.7002 data_time: 0.1995 memory: 16131 loss: 1.5746 loss_prob: 0.8998 loss_thr: 0.5287 loss_db: 0.1461 2022/10/26 02:13:36 - mmengine - INFO - Epoch(train) [469][15/63] lr: 2.2649e-03 eta: 10:42:31 time: 0.5486 data_time: 0.0119 memory: 16131 loss: 1.6360 loss_prob: 0.9384 loss_thr: 0.5478 loss_db: 0.1498 2022/10/26 02:13:39 - mmengine - INFO - Epoch(train) [469][20/63] lr: 2.2649e-03 eta: 10:42:19 time: 0.5879 data_time: 0.0052 memory: 16131 loss: 1.6183 loss_prob: 0.9181 loss_thr: 0.5448 loss_db: 0.1554 2022/10/26 02:13:42 - mmengine - INFO - Epoch(train) [469][25/63] lr: 2.2649e-03 eta: 10:42:19 time: 0.5811 data_time: 0.0235 memory: 16131 loss: 1.5939 loss_prob: 0.9028 loss_thr: 0.5382 loss_db: 0.1529 2022/10/26 02:13:44 - mmengine - INFO - Epoch(train) [469][30/63] lr: 2.2649e-03 eta: 10:42:06 time: 0.5290 data_time: 0.0297 memory: 16131 loss: 1.5323 loss_prob: 0.8631 loss_thr: 0.5249 loss_db: 0.1443 2022/10/26 02:13:47 - mmengine - INFO - Epoch(train) [469][35/63] lr: 2.2649e-03 eta: 10:42:06 time: 0.5036 data_time: 0.0170 memory: 16131 loss: 1.6530 loss_prob: 0.9577 loss_thr: 0.5372 loss_db: 0.1582 2022/10/26 02:13:49 - mmengine - INFO - Epoch(train) [469][40/63] lr: 2.2649e-03 eta: 10:41:52 time: 0.5034 data_time: 0.0127 memory: 16131 loss: 1.8263 loss_prob: 1.0796 loss_thr: 0.5651 loss_db: 0.1816 2022/10/26 02:13:52 - mmengine - INFO - Epoch(train) [469][45/63] lr: 2.2649e-03 eta: 10:41:52 time: 0.5111 data_time: 0.0106 memory: 16131 loss: 1.7143 loss_prob: 0.9890 loss_thr: 0.5585 loss_db: 0.1669 2022/10/26 02:13:55 - mmengine - INFO - Epoch(train) [469][50/63] lr: 2.2649e-03 eta: 10:41:39 time: 0.5375 data_time: 0.0264 memory: 16131 loss: 1.6493 loss_prob: 0.9379 loss_thr: 0.5549 loss_db: 0.1565 2022/10/26 02:13:57 - mmengine - INFO - Epoch(train) [469][55/63] lr: 2.2649e-03 eta: 10:41:39 time: 0.5086 data_time: 0.0262 memory: 16131 loss: 1.5701 loss_prob: 0.8795 loss_thr: 0.5432 loss_db: 0.1475 2022/10/26 02:14:00 - mmengine - INFO - Epoch(train) [469][60/63] lr: 2.2649e-03 eta: 10:41:26 time: 0.5010 data_time: 0.0106 memory: 16131 loss: 1.5967 loss_prob: 0.8988 loss_thr: 0.5487 loss_db: 0.1492 2022/10/26 02:14:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:14:05 - mmengine - INFO - Epoch(train) [470][5/63] lr: 2.2621e-03 eta: 10:41:26 time: 0.6951 data_time: 0.2023 memory: 16131 loss: 1.6628 loss_prob: 0.9591 loss_thr: 0.5494 loss_db: 0.1543 2022/10/26 02:14:08 - mmengine - INFO - Epoch(train) [470][10/63] lr: 2.2621e-03 eta: 10:41:09 time: 0.7197 data_time: 0.2019 memory: 16131 loss: 1.5339 loss_prob: 0.8672 loss_thr: 0.5250 loss_db: 0.1416 2022/10/26 02:14:11 - mmengine - INFO - Epoch(train) [470][15/63] lr: 2.2621e-03 eta: 10:41:09 time: 0.5225 data_time: 0.0062 memory: 16131 loss: 1.4103 loss_prob: 0.7872 loss_thr: 0.4949 loss_db: 0.1281 2022/10/26 02:14:14 - mmengine - INFO - Epoch(train) [470][20/63] lr: 2.2621e-03 eta: 10:40:57 time: 0.5650 data_time: 0.0112 memory: 16131 loss: 1.5264 loss_prob: 0.8637 loss_thr: 0.5245 loss_db: 0.1383 2022/10/26 02:14:16 - mmengine - INFO - Epoch(train) [470][25/63] lr: 2.2621e-03 eta: 10:40:57 time: 0.5659 data_time: 0.0321 memory: 16131 loss: 1.5212 loss_prob: 0.8524 loss_thr: 0.5270 loss_db: 0.1419 2022/10/26 02:14:19 - mmengine - INFO - Epoch(train) [470][30/63] lr: 2.2621e-03 eta: 10:40:43 time: 0.5282 data_time: 0.0351 memory: 16131 loss: 1.4442 loss_prob: 0.7974 loss_thr: 0.5123 loss_db: 0.1344 2022/10/26 02:14:22 - mmengine - INFO - Epoch(train) [470][35/63] lr: 2.2621e-03 eta: 10:40:43 time: 0.5181 data_time: 0.0135 memory: 16131 loss: 1.6086 loss_prob: 0.9089 loss_thr: 0.5513 loss_db: 0.1484 2022/10/26 02:14:24 - mmengine - INFO - Epoch(train) [470][40/63] lr: 2.2621e-03 eta: 10:40:30 time: 0.5039 data_time: 0.0060 memory: 16131 loss: 1.6376 loss_prob: 0.9327 loss_thr: 0.5539 loss_db: 0.1510 2022/10/26 02:14:27 - mmengine - INFO - Epoch(train) [470][45/63] lr: 2.2621e-03 eta: 10:40:30 time: 0.5151 data_time: 0.0120 memory: 16131 loss: 1.6271 loss_prob: 0.9216 loss_thr: 0.5554 loss_db: 0.1501 2022/10/26 02:14:30 - mmengine - INFO - Epoch(train) [470][50/63] lr: 2.2621e-03 eta: 10:40:17 time: 0.5620 data_time: 0.0274 memory: 16131 loss: 1.5614 loss_prob: 0.8777 loss_thr: 0.5375 loss_db: 0.1462 2022/10/26 02:14:32 - mmengine - INFO - Epoch(train) [470][55/63] lr: 2.2621e-03 eta: 10:40:17 time: 0.5343 data_time: 0.0228 memory: 16131 loss: 1.4568 loss_prob: 0.8063 loss_thr: 0.5157 loss_db: 0.1348 2022/10/26 02:14:35 - mmengine - INFO - Epoch(train) [470][60/63] lr: 2.2621e-03 eta: 10:40:04 time: 0.5028 data_time: 0.0068 memory: 16131 loss: 1.5004 loss_prob: 0.8285 loss_thr: 0.5329 loss_db: 0.1390 2022/10/26 02:14:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:14:41 - mmengine - INFO - Epoch(train) [471][5/63] lr: 2.2593e-03 eta: 10:40:04 time: 0.7148 data_time: 0.1932 memory: 16131 loss: 1.5163 loss_prob: 0.8418 loss_thr: 0.5321 loss_db: 0.1425 2022/10/26 02:14:43 - mmengine - INFO - Epoch(train) [471][10/63] lr: 2.2593e-03 eta: 10:39:47 time: 0.7127 data_time: 0.1934 memory: 16131 loss: 1.4760 loss_prob: 0.8109 loss_thr: 0.5267 loss_db: 0.1384 2022/10/26 02:14:46 - mmengine - INFO - Epoch(train) [471][15/63] lr: 2.2593e-03 eta: 10:39:47 time: 0.5186 data_time: 0.0077 memory: 16131 loss: 1.5302 loss_prob: 0.8573 loss_thr: 0.5255 loss_db: 0.1474 2022/10/26 02:14:49 - mmengine - INFO - Epoch(train) [471][20/63] lr: 2.2593e-03 eta: 10:39:34 time: 0.5405 data_time: 0.0096 memory: 16131 loss: 1.5686 loss_prob: 0.8823 loss_thr: 0.5372 loss_db: 0.1490 2022/10/26 02:14:51 - mmengine - INFO - Epoch(train) [471][25/63] lr: 2.2593e-03 eta: 10:39:34 time: 0.5365 data_time: 0.0206 memory: 16131 loss: 1.4941 loss_prob: 0.8290 loss_thr: 0.5257 loss_db: 0.1394 2022/10/26 02:14:54 - mmengine - INFO - Epoch(train) [471][30/63] lr: 2.2593e-03 eta: 10:39:21 time: 0.5194 data_time: 0.0330 memory: 16131 loss: 1.5427 loss_prob: 0.8658 loss_thr: 0.5327 loss_db: 0.1442 2022/10/26 02:14:57 - mmengine - INFO - Epoch(train) [471][35/63] lr: 2.2593e-03 eta: 10:39:21 time: 0.5450 data_time: 0.0200 memory: 16131 loss: 1.4555 loss_prob: 0.8084 loss_thr: 0.5118 loss_db: 0.1353 2022/10/26 02:14:59 - mmengine - INFO - Epoch(train) [471][40/63] lr: 2.2593e-03 eta: 10:39:08 time: 0.5436 data_time: 0.0066 memory: 16131 loss: 1.3454 loss_prob: 0.7317 loss_thr: 0.4911 loss_db: 0.1227 2022/10/26 02:15:02 - mmengine - INFO - Epoch(train) [471][45/63] lr: 2.2593e-03 eta: 10:39:08 time: 0.5513 data_time: 0.0082 memory: 16131 loss: 1.4246 loss_prob: 0.7835 loss_thr: 0.5127 loss_db: 0.1284 2022/10/26 02:15:05 - mmengine - INFO - Epoch(train) [471][50/63] lr: 2.2593e-03 eta: 10:38:55 time: 0.5467 data_time: 0.0264 memory: 16131 loss: 1.4902 loss_prob: 0.8218 loss_thr: 0.5314 loss_db: 0.1370 2022/10/26 02:15:08 - mmengine - INFO - Epoch(train) [471][55/63] lr: 2.2593e-03 eta: 10:38:55 time: 0.5661 data_time: 0.0242 memory: 16131 loss: 1.5053 loss_prob: 0.8278 loss_thr: 0.5372 loss_db: 0.1404 2022/10/26 02:15:11 - mmengine - INFO - Epoch(train) [471][60/63] lr: 2.2593e-03 eta: 10:38:43 time: 0.5835 data_time: 0.0052 memory: 16131 loss: 1.5078 loss_prob: 0.8340 loss_thr: 0.5319 loss_db: 0.1419 2022/10/26 02:15:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:15:16 - mmengine - INFO - Epoch(train) [472][5/63] lr: 2.2565e-03 eta: 10:38:43 time: 0.6490 data_time: 0.1647 memory: 16131 loss: 1.4699 loss_prob: 0.8184 loss_thr: 0.5126 loss_db: 0.1389 2022/10/26 02:15:19 - mmengine - INFO - Epoch(train) [472][10/63] lr: 2.2565e-03 eta: 10:38:27 time: 0.7152 data_time: 0.1738 memory: 16131 loss: 1.4703 loss_prob: 0.8196 loss_thr: 0.5167 loss_db: 0.1339 2022/10/26 02:15:21 - mmengine - INFO - Epoch(train) [472][15/63] lr: 2.2565e-03 eta: 10:38:27 time: 0.5361 data_time: 0.0198 memory: 16131 loss: 1.5385 loss_prob: 0.8686 loss_thr: 0.5292 loss_db: 0.1407 2022/10/26 02:15:24 - mmengine - INFO - Epoch(train) [472][20/63] lr: 2.2565e-03 eta: 10:38:13 time: 0.4933 data_time: 0.0085 memory: 16131 loss: 1.5174 loss_prob: 0.8446 loss_thr: 0.5318 loss_db: 0.1410 2022/10/26 02:15:27 - mmengine - INFO - Epoch(train) [472][25/63] lr: 2.2565e-03 eta: 10:38:13 time: 0.5506 data_time: 0.0204 memory: 16131 loss: 1.4790 loss_prob: 0.8277 loss_thr: 0.5138 loss_db: 0.1374 2022/10/26 02:15:29 - mmengine - INFO - Epoch(train) [472][30/63] lr: 2.2565e-03 eta: 10:38:00 time: 0.5472 data_time: 0.0236 memory: 16131 loss: 1.4977 loss_prob: 0.8390 loss_thr: 0.5191 loss_db: 0.1396 2022/10/26 02:15:32 - mmengine - INFO - Epoch(train) [472][35/63] lr: 2.2565e-03 eta: 10:38:00 time: 0.5519 data_time: 0.0212 memory: 16131 loss: 1.4674 loss_prob: 0.8017 loss_thr: 0.5315 loss_db: 0.1341 2022/10/26 02:15:35 - mmengine - INFO - Epoch(train) [472][40/63] lr: 2.2565e-03 eta: 10:37:48 time: 0.5693 data_time: 0.0182 memory: 16131 loss: 1.4852 loss_prob: 0.8225 loss_thr: 0.5246 loss_db: 0.1381 2022/10/26 02:15:37 - mmengine - INFO - Epoch(train) [472][45/63] lr: 2.2565e-03 eta: 10:37:48 time: 0.4988 data_time: 0.0075 memory: 16131 loss: 1.5861 loss_prob: 0.9082 loss_thr: 0.5244 loss_db: 0.1535 2022/10/26 02:15:40 - mmengine - INFO - Epoch(train) [472][50/63] lr: 2.2565e-03 eta: 10:37:34 time: 0.5107 data_time: 0.0183 memory: 16131 loss: 1.6463 loss_prob: 0.9517 loss_thr: 0.5388 loss_db: 0.1558 2022/10/26 02:15:43 - mmengine - INFO - Epoch(train) [472][55/63] lr: 2.2565e-03 eta: 10:37:34 time: 0.5291 data_time: 0.0170 memory: 16131 loss: 1.5639 loss_prob: 0.8924 loss_thr: 0.5257 loss_db: 0.1457 2022/10/26 02:15:45 - mmengine - INFO - Epoch(train) [472][60/63] lr: 2.2565e-03 eta: 10:37:21 time: 0.5074 data_time: 0.0133 memory: 16131 loss: 1.5387 loss_prob: 0.8827 loss_thr: 0.5054 loss_db: 0.1506 2022/10/26 02:15:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:15:52 - mmengine - INFO - Epoch(train) [473][5/63] lr: 2.2537e-03 eta: 10:37:21 time: 0.7354 data_time: 0.2369 memory: 16131 loss: 1.5908 loss_prob: 0.9027 loss_thr: 0.5401 loss_db: 0.1481 2022/10/26 02:15:54 - mmengine - INFO - Epoch(train) [473][10/63] lr: 2.2537e-03 eta: 10:37:05 time: 0.7651 data_time: 0.2382 memory: 16131 loss: 1.6054 loss_prob: 0.9103 loss_thr: 0.5481 loss_db: 0.1471 2022/10/26 02:15:57 - mmengine - INFO - Epoch(train) [473][15/63] lr: 2.2537e-03 eta: 10:37:05 time: 0.5536 data_time: 0.0064 memory: 16131 loss: 1.5170 loss_prob: 0.8586 loss_thr: 0.5139 loss_db: 0.1446 2022/10/26 02:16:00 - mmengine - INFO - Epoch(train) [473][20/63] lr: 2.2537e-03 eta: 10:36:53 time: 0.5850 data_time: 0.0082 memory: 16131 loss: 1.6868 loss_prob: 0.9773 loss_thr: 0.5519 loss_db: 0.1576 2022/10/26 02:16:03 - mmengine - INFO - Epoch(train) [473][25/63] lr: 2.2537e-03 eta: 10:36:53 time: 0.5964 data_time: 0.0391 memory: 16131 loss: 1.6407 loss_prob: 0.9416 loss_thr: 0.5518 loss_db: 0.1473 2022/10/26 02:16:06 - mmengine - INFO - Epoch(train) [473][30/63] lr: 2.2537e-03 eta: 10:36:40 time: 0.5529 data_time: 0.0364 memory: 16131 loss: 1.4839 loss_prob: 0.8323 loss_thr: 0.5141 loss_db: 0.1375 2022/10/26 02:16:08 - mmengine - INFO - Epoch(train) [473][35/63] lr: 2.2537e-03 eta: 10:36:40 time: 0.5101 data_time: 0.0062 memory: 16131 loss: 1.4933 loss_prob: 0.8404 loss_thr: 0.5134 loss_db: 0.1395 2022/10/26 02:16:11 - mmengine - INFO - Epoch(train) [473][40/63] lr: 2.2537e-03 eta: 10:36:27 time: 0.5160 data_time: 0.0074 memory: 16131 loss: 1.6907 loss_prob: 0.9766 loss_thr: 0.5608 loss_db: 0.1533 2022/10/26 02:16:13 - mmengine - INFO - Epoch(train) [473][45/63] lr: 2.2537e-03 eta: 10:36:27 time: 0.5085 data_time: 0.0059 memory: 16131 loss: 1.8105 loss_prob: 1.0467 loss_thr: 0.5962 loss_db: 0.1676 2022/10/26 02:16:16 - mmengine - INFO - Epoch(train) [473][50/63] lr: 2.2537e-03 eta: 10:36:14 time: 0.5173 data_time: 0.0219 memory: 16131 loss: 1.6367 loss_prob: 0.9273 loss_thr: 0.5541 loss_db: 0.1554 2022/10/26 02:16:18 - mmengine - INFO - Epoch(train) [473][55/63] lr: 2.2537e-03 eta: 10:36:14 time: 0.5154 data_time: 0.0243 memory: 16131 loss: 1.4806 loss_prob: 0.8366 loss_thr: 0.5059 loss_db: 0.1382 2022/10/26 02:16:21 - mmengine - INFO - Epoch(train) [473][60/63] lr: 2.2537e-03 eta: 10:36:01 time: 0.5186 data_time: 0.0071 memory: 16131 loss: 1.5503 loss_prob: 0.8883 loss_thr: 0.5162 loss_db: 0.1458 2022/10/26 02:16:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:16:27 - mmengine - INFO - Epoch(train) [474][5/63] lr: 2.2509e-03 eta: 10:36:01 time: 0.6509 data_time: 0.1545 memory: 16131 loss: 1.6070 loss_prob: 0.9099 loss_thr: 0.5441 loss_db: 0.1531 2022/10/26 02:16:29 - mmengine - INFO - Epoch(train) [474][10/63] lr: 2.2509e-03 eta: 10:35:43 time: 0.6462 data_time: 0.1637 memory: 16131 loss: 1.4642 loss_prob: 0.8153 loss_thr: 0.5111 loss_db: 0.1378 2022/10/26 02:16:31 - mmengine - INFO - Epoch(train) [474][15/63] lr: 2.2509e-03 eta: 10:35:43 time: 0.4988 data_time: 0.0213 memory: 16131 loss: 1.4731 loss_prob: 0.8162 loss_thr: 0.5229 loss_db: 0.1341 2022/10/26 02:16:34 - mmengine - INFO - Epoch(train) [474][20/63] lr: 2.2509e-03 eta: 10:35:30 time: 0.4915 data_time: 0.0079 memory: 16131 loss: 1.5047 loss_prob: 0.8450 loss_thr: 0.5220 loss_db: 0.1376 2022/10/26 02:16:36 - mmengine - INFO - Epoch(train) [474][25/63] lr: 2.2509e-03 eta: 10:35:30 time: 0.4973 data_time: 0.0190 memory: 16131 loss: 1.4286 loss_prob: 0.8035 loss_thr: 0.4897 loss_db: 0.1354 2022/10/26 02:16:39 - mmengine - INFO - Epoch(train) [474][30/63] lr: 2.2509e-03 eta: 10:35:16 time: 0.5019 data_time: 0.0211 memory: 16131 loss: 1.4269 loss_prob: 0.7901 loss_thr: 0.5022 loss_db: 0.1345 2022/10/26 02:16:42 - mmengine - INFO - Epoch(train) [474][35/63] lr: 2.2509e-03 eta: 10:35:16 time: 0.5278 data_time: 0.0241 memory: 16131 loss: 1.5073 loss_prob: 0.8349 loss_thr: 0.5308 loss_db: 0.1416 2022/10/26 02:16:44 - mmengine - INFO - Epoch(train) [474][40/63] lr: 2.2509e-03 eta: 10:35:04 time: 0.5407 data_time: 0.0237 memory: 16131 loss: 1.5170 loss_prob: 0.8497 loss_thr: 0.5234 loss_db: 0.1438 2022/10/26 02:16:47 - mmengine - INFO - Epoch(train) [474][45/63] lr: 2.2509e-03 eta: 10:35:04 time: 0.5169 data_time: 0.0071 memory: 16131 loss: 1.4570 loss_prob: 0.8127 loss_thr: 0.5098 loss_db: 0.1345 2022/10/26 02:16:50 - mmengine - INFO - Epoch(train) [474][50/63] lr: 2.2509e-03 eta: 10:34:51 time: 0.5458 data_time: 0.0120 memory: 16131 loss: 1.5442 loss_prob: 0.8561 loss_thr: 0.5498 loss_db: 0.1383 2022/10/26 02:16:52 - mmengine - INFO - Epoch(train) [474][55/63] lr: 2.2509e-03 eta: 10:34:51 time: 0.5362 data_time: 0.0223 memory: 16131 loss: 1.7255 loss_prob: 0.9898 loss_thr: 0.5708 loss_db: 0.1649 2022/10/26 02:16:55 - mmengine - INFO - Epoch(train) [474][60/63] lr: 2.2509e-03 eta: 10:34:37 time: 0.4972 data_time: 0.0164 memory: 16131 loss: 1.7490 loss_prob: 1.0096 loss_thr: 0.5654 loss_db: 0.1741 2022/10/26 02:16:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:17:01 - mmengine - INFO - Epoch(train) [475][5/63] lr: 2.2481e-03 eta: 10:34:37 time: 0.7117 data_time: 0.2038 memory: 16131 loss: 1.5376 loss_prob: 0.8678 loss_thr: 0.5325 loss_db: 0.1373 2022/10/26 02:17:04 - mmengine - INFO - Epoch(train) [475][10/63] lr: 2.2481e-03 eta: 10:34:21 time: 0.7494 data_time: 0.2005 memory: 16131 loss: 1.6470 loss_prob: 0.9437 loss_thr: 0.5511 loss_db: 0.1521 2022/10/26 02:17:06 - mmengine - INFO - Epoch(train) [475][15/63] lr: 2.2481e-03 eta: 10:34:21 time: 0.5016 data_time: 0.0050 memory: 16131 loss: 1.5427 loss_prob: 0.8554 loss_thr: 0.5406 loss_db: 0.1467 2022/10/26 02:17:09 - mmengine - INFO - Epoch(train) [475][20/63] lr: 2.2481e-03 eta: 10:34:08 time: 0.4946 data_time: 0.0053 memory: 16131 loss: 1.5625 loss_prob: 0.8911 loss_thr: 0.5233 loss_db: 0.1480 2022/10/26 02:17:11 - mmengine - INFO - Epoch(train) [475][25/63] lr: 2.2481e-03 eta: 10:34:08 time: 0.5263 data_time: 0.0237 memory: 16131 loss: 1.5313 loss_prob: 0.8788 loss_thr: 0.5077 loss_db: 0.1449 2022/10/26 02:17:14 - mmengine - INFO - Epoch(train) [475][30/63] lr: 2.2481e-03 eta: 10:33:55 time: 0.5300 data_time: 0.0309 memory: 16131 loss: 1.4562 loss_prob: 0.8094 loss_thr: 0.5100 loss_db: 0.1368 2022/10/26 02:17:16 - mmengine - INFO - Epoch(train) [475][35/63] lr: 2.2481e-03 eta: 10:33:55 time: 0.5209 data_time: 0.0124 memory: 16131 loss: 1.5108 loss_prob: 0.8439 loss_thr: 0.5235 loss_db: 0.1433 2022/10/26 02:17:19 - mmengine - INFO - Epoch(train) [475][40/63] lr: 2.2481e-03 eta: 10:33:42 time: 0.5369 data_time: 0.0106 memory: 16131 loss: 1.6080 loss_prob: 0.9114 loss_thr: 0.5439 loss_db: 0.1527 2022/10/26 02:17:22 - mmengine - INFO - Epoch(train) [475][45/63] lr: 2.2481e-03 eta: 10:33:42 time: 0.5675 data_time: 0.0115 memory: 16131 loss: 1.7148 loss_prob: 0.9725 loss_thr: 0.5811 loss_db: 0.1612 2022/10/26 02:17:25 - mmengine - INFO - Epoch(train) [475][50/63] lr: 2.2481e-03 eta: 10:33:30 time: 0.5646 data_time: 0.0217 memory: 16131 loss: 1.6171 loss_prob: 0.9076 loss_thr: 0.5603 loss_db: 0.1492 2022/10/26 02:17:27 - mmengine - INFO - Epoch(train) [475][55/63] lr: 2.2481e-03 eta: 10:33:30 time: 0.5118 data_time: 0.0211 memory: 16131 loss: 1.4752 loss_prob: 0.8282 loss_thr: 0.5118 loss_db: 0.1353 2022/10/26 02:17:30 - mmengine - INFO - Epoch(train) [475][60/63] lr: 2.2481e-03 eta: 10:33:17 time: 0.5108 data_time: 0.0098 memory: 16131 loss: 1.3414 loss_prob: 0.7392 loss_thr: 0.4796 loss_db: 0.1226 2022/10/26 02:17:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:17:36 - mmengine - INFO - Epoch(train) [476][5/63] lr: 2.2453e-03 eta: 10:33:17 time: 0.7463 data_time: 0.1769 memory: 16131 loss: 1.5151 loss_prob: 0.8365 loss_thr: 0.5416 loss_db: 0.1370 2022/10/26 02:17:39 - mmengine - INFO - Epoch(train) [476][10/63] lr: 2.2453e-03 eta: 10:33:01 time: 0.7453 data_time: 0.1758 memory: 16131 loss: 1.5669 loss_prob: 0.8671 loss_thr: 0.5560 loss_db: 0.1438 2022/10/26 02:17:41 - mmengine - INFO - Epoch(train) [476][15/63] lr: 2.2453e-03 eta: 10:33:01 time: 0.4906 data_time: 0.0093 memory: 16131 loss: 1.5315 loss_prob: 0.8537 loss_thr: 0.5326 loss_db: 0.1452 2022/10/26 02:17:44 - mmengine - INFO - Epoch(train) [476][20/63] lr: 2.2453e-03 eta: 10:32:47 time: 0.5058 data_time: 0.0104 memory: 16131 loss: 1.5813 loss_prob: 0.8976 loss_thr: 0.5360 loss_db: 0.1477 2022/10/26 02:17:46 - mmengine - INFO - Epoch(train) [476][25/63] lr: 2.2453e-03 eta: 10:32:47 time: 0.5213 data_time: 0.0274 memory: 16131 loss: 1.5174 loss_prob: 0.8543 loss_thr: 0.5232 loss_db: 0.1400 2022/10/26 02:17:49 - mmengine - INFO - Epoch(train) [476][30/63] lr: 2.2453e-03 eta: 10:32:34 time: 0.5133 data_time: 0.0310 memory: 16131 loss: 1.4892 loss_prob: 0.8326 loss_thr: 0.5153 loss_db: 0.1413 2022/10/26 02:17:52 - mmengine - INFO - Epoch(train) [476][35/63] lr: 2.2453e-03 eta: 10:32:34 time: 0.5340 data_time: 0.0101 memory: 16131 loss: 1.4634 loss_prob: 0.8115 loss_thr: 0.5160 loss_db: 0.1358 2022/10/26 02:17:55 - mmengine - INFO - Epoch(train) [476][40/63] lr: 2.2453e-03 eta: 10:32:23 time: 0.6434 data_time: 0.0095 memory: 16131 loss: 1.4523 loss_prob: 0.8056 loss_thr: 0.5140 loss_db: 0.1327 2022/10/26 02:17:58 - mmengine - INFO - Epoch(train) [476][45/63] lr: 2.2453e-03 eta: 10:32:23 time: 0.6044 data_time: 0.0087 memory: 16131 loss: 1.3926 loss_prob: 0.7683 loss_thr: 0.4946 loss_db: 0.1297 2022/10/26 02:18:00 - mmengine - INFO - Epoch(train) [476][50/63] lr: 2.2453e-03 eta: 10:32:10 time: 0.5077 data_time: 0.0194 memory: 16131 loss: 1.3469 loss_prob: 0.7259 loss_thr: 0.4957 loss_db: 0.1253 2022/10/26 02:18:03 - mmengine - INFO - Epoch(train) [476][55/63] lr: 2.2453e-03 eta: 10:32:10 time: 0.5237 data_time: 0.0213 memory: 16131 loss: 1.4148 loss_prob: 0.7672 loss_thr: 0.5178 loss_db: 0.1298 2022/10/26 02:18:05 - mmengine - INFO - Epoch(train) [476][60/63] lr: 2.2453e-03 eta: 10:31:56 time: 0.5073 data_time: 0.0079 memory: 16131 loss: 1.4568 loss_prob: 0.8165 loss_thr: 0.5050 loss_db: 0.1354 2022/10/26 02:18:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:18:12 - mmengine - INFO - Epoch(train) [477][5/63] lr: 2.2425e-03 eta: 10:31:56 time: 0.7187 data_time: 0.2110 memory: 16131 loss: 1.5991 loss_prob: 0.9156 loss_thr: 0.5334 loss_db: 0.1501 2022/10/26 02:18:15 - mmengine - INFO - Epoch(train) [477][10/63] lr: 2.2425e-03 eta: 10:31:42 time: 0.8551 data_time: 0.2096 memory: 16131 loss: 1.5337 loss_prob: 0.8723 loss_thr: 0.5142 loss_db: 0.1471 2022/10/26 02:18:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:18:18 - mmengine - INFO - Epoch(train) [477][15/63] lr: 2.2425e-03 eta: 10:31:42 time: 0.6172 data_time: 0.0057 memory: 16131 loss: 1.4838 loss_prob: 0.8421 loss_thr: 0.4989 loss_db: 0.1428 2022/10/26 02:18:20 - mmengine - INFO - Epoch(train) [477][20/63] lr: 2.2425e-03 eta: 10:31:29 time: 0.5027 data_time: 0.0051 memory: 16131 loss: 1.4110 loss_prob: 0.7782 loss_thr: 0.5008 loss_db: 0.1320 2022/10/26 02:18:23 - mmengine - INFO - Epoch(train) [477][25/63] lr: 2.2425e-03 eta: 10:31:29 time: 0.5201 data_time: 0.0247 memory: 16131 loss: 1.4095 loss_prob: 0.7606 loss_thr: 0.5181 loss_db: 0.1308 2022/10/26 02:18:26 - mmengine - INFO - Epoch(train) [477][30/63] lr: 2.2425e-03 eta: 10:31:16 time: 0.5355 data_time: 0.0297 memory: 16131 loss: 1.5854 loss_prob: 0.8911 loss_thr: 0.5483 loss_db: 0.1460 2022/10/26 02:18:28 - mmengine - INFO - Epoch(train) [477][35/63] lr: 2.2425e-03 eta: 10:31:16 time: 0.5132 data_time: 0.0117 memory: 16131 loss: 1.5513 loss_prob: 0.8780 loss_thr: 0.5306 loss_db: 0.1427 2022/10/26 02:18:32 - mmengine - INFO - Epoch(train) [477][40/63] lr: 2.2425e-03 eta: 10:31:05 time: 0.6157 data_time: 0.0084 memory: 16131 loss: 1.3420 loss_prob: 0.7294 loss_thr: 0.4889 loss_db: 0.1237 2022/10/26 02:18:35 - mmengine - INFO - Epoch(train) [477][45/63] lr: 2.2425e-03 eta: 10:31:05 time: 0.6730 data_time: 0.0104 memory: 16131 loss: 1.3609 loss_prob: 0.7507 loss_thr: 0.4830 loss_db: 0.1272 2022/10/26 02:18:38 - mmengine - INFO - Epoch(train) [477][50/63] lr: 2.2425e-03 eta: 10:30:53 time: 0.5850 data_time: 0.0232 memory: 16131 loss: 1.4802 loss_prob: 0.8399 loss_thr: 0.5010 loss_db: 0.1393 2022/10/26 02:18:41 - mmengine - INFO - Epoch(train) [477][55/63] lr: 2.2425e-03 eta: 10:30:53 time: 0.5567 data_time: 0.0192 memory: 16131 loss: 1.4986 loss_prob: 0.8450 loss_thr: 0.5138 loss_db: 0.1399 2022/10/26 02:18:43 - mmengine - INFO - Epoch(train) [477][60/63] lr: 2.2425e-03 eta: 10:30:40 time: 0.5403 data_time: 0.0058 memory: 16131 loss: 1.5135 loss_prob: 0.8423 loss_thr: 0.5335 loss_db: 0.1377 2022/10/26 02:18:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:18:49 - mmengine - INFO - Epoch(train) [478][5/63] lr: 2.2398e-03 eta: 10:30:40 time: 0.6892 data_time: 0.1873 memory: 16131 loss: 1.6219 loss_prob: 0.9248 loss_thr: 0.5470 loss_db: 0.1502 2022/10/26 02:18:52 - mmengine - INFO - Epoch(train) [478][10/63] lr: 2.2398e-03 eta: 10:30:24 time: 0.7286 data_time: 0.1887 memory: 16131 loss: 1.5297 loss_prob: 0.8722 loss_thr: 0.5142 loss_db: 0.1432 2022/10/26 02:18:54 - mmengine - INFO - Epoch(train) [478][15/63] lr: 2.2398e-03 eta: 10:30:24 time: 0.5426 data_time: 0.0106 memory: 16131 loss: 1.5817 loss_prob: 0.8880 loss_thr: 0.5478 loss_db: 0.1459 2022/10/26 02:18:57 - mmengine - INFO - Epoch(train) [478][20/63] lr: 2.2398e-03 eta: 10:30:11 time: 0.5146 data_time: 0.0109 memory: 16131 loss: 1.6959 loss_prob: 0.9568 loss_thr: 0.5797 loss_db: 0.1594 2022/10/26 02:19:00 - mmengine - INFO - Epoch(train) [478][25/63] lr: 2.2398e-03 eta: 10:30:11 time: 0.5469 data_time: 0.0384 memory: 16131 loss: 1.6029 loss_prob: 0.9057 loss_thr: 0.5429 loss_db: 0.1543 2022/10/26 02:19:03 - mmengine - INFO - Epoch(train) [478][30/63] lr: 2.2398e-03 eta: 10:29:58 time: 0.5718 data_time: 0.0398 memory: 16131 loss: 1.4069 loss_prob: 0.7792 loss_thr: 0.4999 loss_db: 0.1278 2022/10/26 02:19:05 - mmengine - INFO - Epoch(train) [478][35/63] lr: 2.2398e-03 eta: 10:29:58 time: 0.5378 data_time: 0.0135 memory: 16131 loss: 1.4252 loss_prob: 0.7889 loss_thr: 0.5040 loss_db: 0.1323 2022/10/26 02:19:08 - mmengine - INFO - Epoch(train) [478][40/63] lr: 2.2398e-03 eta: 10:29:46 time: 0.5322 data_time: 0.0103 memory: 16131 loss: 1.5716 loss_prob: 0.8940 loss_thr: 0.5261 loss_db: 0.1515 2022/10/26 02:19:11 - mmengine - INFO - Epoch(train) [478][45/63] lr: 2.2398e-03 eta: 10:29:46 time: 0.5302 data_time: 0.0110 memory: 16131 loss: 1.5584 loss_prob: 0.8857 loss_thr: 0.5281 loss_db: 0.1446 2022/10/26 02:19:14 - mmengine - INFO - Epoch(train) [478][50/63] lr: 2.2398e-03 eta: 10:29:33 time: 0.5767 data_time: 0.0195 memory: 16131 loss: 1.5217 loss_prob: 0.8532 loss_thr: 0.5274 loss_db: 0.1412 2022/10/26 02:19:16 - mmengine - INFO - Epoch(train) [478][55/63] lr: 2.2398e-03 eta: 10:29:33 time: 0.5732 data_time: 0.0203 memory: 16131 loss: 1.5076 loss_prob: 0.8435 loss_thr: 0.5220 loss_db: 0.1421 2022/10/26 02:19:19 - mmengine - INFO - Epoch(train) [478][60/63] lr: 2.2398e-03 eta: 10:29:20 time: 0.5091 data_time: 0.0129 memory: 16131 loss: 1.4012 loss_prob: 0.7701 loss_thr: 0.5015 loss_db: 0.1297 2022/10/26 02:19:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:19:25 - mmengine - INFO - Epoch(train) [479][5/63] lr: 2.2370e-03 eta: 10:29:20 time: 0.7096 data_time: 0.1559 memory: 16131 loss: 1.5350 loss_prob: 0.8494 loss_thr: 0.5430 loss_db: 0.1426 2022/10/26 02:19:27 - mmengine - INFO - Epoch(train) [479][10/63] lr: 2.2370e-03 eta: 10:29:04 time: 0.7171 data_time: 0.1597 memory: 16131 loss: 1.5653 loss_prob: 0.8783 loss_thr: 0.5425 loss_db: 0.1445 2022/10/26 02:19:30 - mmengine - INFO - Epoch(train) [479][15/63] lr: 2.2370e-03 eta: 10:29:04 time: 0.5044 data_time: 0.0144 memory: 16131 loss: 1.5320 loss_prob: 0.8579 loss_thr: 0.5291 loss_db: 0.1450 2022/10/26 02:19:33 - mmengine - INFO - Epoch(train) [479][20/63] lr: 2.2370e-03 eta: 10:28:51 time: 0.5227 data_time: 0.0090 memory: 16131 loss: 1.4821 loss_prob: 0.8231 loss_thr: 0.5173 loss_db: 0.1417 2022/10/26 02:19:36 - mmengine - INFO - Epoch(train) [479][25/63] lr: 2.2370e-03 eta: 10:28:51 time: 0.5722 data_time: 0.0093 memory: 16131 loss: 1.4204 loss_prob: 0.7980 loss_thr: 0.4867 loss_db: 0.1357 2022/10/26 02:19:39 - mmengine - INFO - Epoch(train) [479][30/63] lr: 2.2370e-03 eta: 10:28:39 time: 0.6032 data_time: 0.0281 memory: 16131 loss: 1.4580 loss_prob: 0.8162 loss_thr: 0.5072 loss_db: 0.1347 2022/10/26 02:19:41 - mmengine - INFO - Epoch(train) [479][35/63] lr: 2.2370e-03 eta: 10:28:39 time: 0.5508 data_time: 0.0257 memory: 16131 loss: 1.5150 loss_prob: 0.8484 loss_thr: 0.5273 loss_db: 0.1393 2022/10/26 02:19:44 - mmengine - INFO - Epoch(train) [479][40/63] lr: 2.2370e-03 eta: 10:28:26 time: 0.4972 data_time: 0.0093 memory: 16131 loss: 1.4465 loss_prob: 0.8047 loss_thr: 0.5066 loss_db: 0.1352 2022/10/26 02:19:46 - mmengine - INFO - Epoch(train) [479][45/63] lr: 2.2370e-03 eta: 10:28:26 time: 0.5109 data_time: 0.0070 memory: 16131 loss: 1.4868 loss_prob: 0.8314 loss_thr: 0.5154 loss_db: 0.1400 2022/10/26 02:19:49 - mmengine - INFO - Epoch(train) [479][50/63] lr: 2.2370e-03 eta: 10:28:13 time: 0.5341 data_time: 0.0093 memory: 16131 loss: 1.5588 loss_prob: 0.8833 loss_thr: 0.5288 loss_db: 0.1468 2022/10/26 02:19:52 - mmengine - INFO - Epoch(train) [479][55/63] lr: 2.2370e-03 eta: 10:28:13 time: 0.5571 data_time: 0.0214 memory: 16131 loss: 1.4794 loss_prob: 0.8255 loss_thr: 0.5138 loss_db: 0.1402 2022/10/26 02:19:54 - mmengine - INFO - Epoch(train) [479][60/63] lr: 2.2370e-03 eta: 10:28:01 time: 0.5453 data_time: 0.0195 memory: 16131 loss: 1.3717 loss_prob: 0.7487 loss_thr: 0.4962 loss_db: 0.1268 2022/10/26 02:19:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:20:00 - mmengine - INFO - Epoch(train) [480][5/63] lr: 2.2342e-03 eta: 10:28:01 time: 0.6732 data_time: 0.1891 memory: 16131 loss: 1.4451 loss_prob: 0.8033 loss_thr: 0.5098 loss_db: 0.1320 2022/10/26 02:20:03 - mmengine - INFO - Epoch(train) [480][10/63] lr: 2.2342e-03 eta: 10:27:44 time: 0.6900 data_time: 0.1918 memory: 16131 loss: 1.5113 loss_prob: 0.8442 loss_thr: 0.5270 loss_db: 0.1401 2022/10/26 02:20:05 - mmengine - INFO - Epoch(train) [480][15/63] lr: 2.2342e-03 eta: 10:27:44 time: 0.4980 data_time: 0.0108 memory: 16131 loss: 1.4207 loss_prob: 0.7899 loss_thr: 0.4984 loss_db: 0.1324 2022/10/26 02:20:08 - mmengine - INFO - Epoch(train) [480][20/63] lr: 2.2342e-03 eta: 10:27:31 time: 0.5044 data_time: 0.0113 memory: 16131 loss: 1.4204 loss_prob: 0.7761 loss_thr: 0.5107 loss_db: 0.1336 2022/10/26 02:20:10 - mmengine - INFO - Epoch(train) [480][25/63] lr: 2.2342e-03 eta: 10:27:31 time: 0.5390 data_time: 0.0206 memory: 16131 loss: 1.4585 loss_prob: 0.8013 loss_thr: 0.5213 loss_db: 0.1360 2022/10/26 02:20:13 - mmengine - INFO - Epoch(train) [480][30/63] lr: 2.2342e-03 eta: 10:27:19 time: 0.5802 data_time: 0.0340 memory: 16131 loss: 1.4587 loss_prob: 0.8076 loss_thr: 0.5164 loss_db: 0.1347 2022/10/26 02:20:16 - mmengine - INFO - Epoch(train) [480][35/63] lr: 2.2342e-03 eta: 10:27:19 time: 0.5835 data_time: 0.0277 memory: 16131 loss: 1.5220 loss_prob: 0.8529 loss_thr: 0.5290 loss_db: 0.1401 2022/10/26 02:20:19 - mmengine - INFO - Epoch(train) [480][40/63] lr: 2.2342e-03 eta: 10:27:06 time: 0.5338 data_time: 0.0105 memory: 16131 loss: 1.5873 loss_prob: 0.9011 loss_thr: 0.5388 loss_db: 0.1474 2022/10/26 02:20:21 - mmengine - INFO - Epoch(train) [480][45/63] lr: 2.2342e-03 eta: 10:27:06 time: 0.4974 data_time: 0.0087 memory: 16131 loss: 1.7102 loss_prob: 0.9890 loss_thr: 0.5532 loss_db: 0.1680 2022/10/26 02:20:24 - mmengine - INFO - Epoch(train) [480][50/63] lr: 2.2342e-03 eta: 10:26:53 time: 0.4957 data_time: 0.0105 memory: 16131 loss: 1.7590 loss_prob: 1.0285 loss_thr: 0.5582 loss_db: 0.1722 2022/10/26 02:20:27 - mmengine - INFO - Epoch(train) [480][55/63] lr: 2.2342e-03 eta: 10:26:53 time: 0.6239 data_time: 0.0195 memory: 16131 loss: 1.8991 loss_prob: 1.1612 loss_thr: 0.5579 loss_db: 0.1799 2022/10/26 02:20:30 - mmengine - INFO - Epoch(train) [480][60/63] lr: 2.2342e-03 eta: 10:26:42 time: 0.6343 data_time: 0.0189 memory: 16131 loss: 1.8301 loss_prob: 1.1019 loss_thr: 0.5564 loss_db: 0.1719 2022/10/26 02:20:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:20:31 - mmengine - INFO - Saving checkpoint at 480 epochs 2022/10/26 02:20:38 - mmengine - INFO - Epoch(val) [480][5/32] eta: 10:26:42 time: 0.5370 data_time: 0.0917 memory: 16131 2022/10/26 02:20:41 - mmengine - INFO - Epoch(val) [480][10/32] eta: 0:00:13 time: 0.6094 data_time: 0.1102 memory: 15724 2022/10/26 02:20:44 - mmengine - INFO - Epoch(val) [480][15/32] eta: 0:00:13 time: 0.5486 data_time: 0.0437 memory: 15724 2022/10/26 02:20:46 - mmengine - INFO - Epoch(val) [480][20/32] eta: 0:00:06 time: 0.5537 data_time: 0.0554 memory: 15724 2022/10/26 02:20:49 - mmengine - INFO - Epoch(val) [480][25/32] eta: 0:00:06 time: 0.5555 data_time: 0.0469 memory: 15724 2022/10/26 02:20:52 - mmengine - INFO - Epoch(val) [480][30/32] eta: 0:00:01 time: 0.5271 data_time: 0.0223 memory: 15724 2022/10/26 02:20:52 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7963, precision: 0.6751, hmean: 0.7307 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7963, precision: 0.7556, hmean: 0.7754 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7920, precision: 0.8044, hmean: 0.7982 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7790, precision: 0.8511, hmean: 0.8135 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7323, precision: 0.9043, hmean: 0.8093 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3746, precision: 0.9665, hmean: 0.5399 2022/10/26 02:20:52 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/10/26 02:20:52 - mmengine - INFO - Epoch(val) [480][32/32] icdar/precision: 0.8511 icdar/recall: 0.7790 icdar/hmean: 0.8135 2022/10/26 02:20:57 - mmengine - INFO - Epoch(train) [481][5/63] lr: 2.2314e-03 eta: 0:00:01 time: 0.6757 data_time: 0.1957 memory: 16131 loss: 1.6966 loss_prob: 0.9750 loss_thr: 0.5640 loss_db: 0.1576 2022/10/26 02:21:00 - mmengine - INFO - Epoch(train) [481][10/63] lr: 2.2314e-03 eta: 10:26:25 time: 0.7106 data_time: 0.1954 memory: 16131 loss: 1.8876 loss_prob: 1.0867 loss_thr: 0.6208 loss_db: 0.1801 2022/10/26 02:21:02 - mmengine - INFO - Epoch(train) [481][15/63] lr: 2.2314e-03 eta: 10:26:25 time: 0.5205 data_time: 0.0073 memory: 16131 loss: 1.6422 loss_prob: 0.9137 loss_thr: 0.5767 loss_db: 0.1518 2022/10/26 02:21:05 - mmengine - INFO - Epoch(train) [481][20/63] lr: 2.2314e-03 eta: 10:26:13 time: 0.5679 data_time: 0.0139 memory: 16131 loss: 1.5362 loss_prob: 0.8463 loss_thr: 0.5533 loss_db: 0.1366 2022/10/26 02:21:08 - mmengine - INFO - Epoch(train) [481][25/63] lr: 2.2314e-03 eta: 10:26:13 time: 0.5505 data_time: 0.0128 memory: 16131 loss: 1.5358 loss_prob: 0.8570 loss_thr: 0.5358 loss_db: 0.1430 2022/10/26 02:21:11 - mmengine - INFO - Epoch(train) [481][30/63] lr: 2.2314e-03 eta: 10:26:00 time: 0.5341 data_time: 0.0271 memory: 16131 loss: 1.5141 loss_prob: 0.8535 loss_thr: 0.5150 loss_db: 0.1457 2022/10/26 02:21:13 - mmengine - INFO - Epoch(train) [481][35/63] lr: 2.2314e-03 eta: 10:26:00 time: 0.5340 data_time: 0.0286 memory: 16131 loss: 1.5157 loss_prob: 0.8458 loss_thr: 0.5264 loss_db: 0.1435 2022/10/26 02:21:16 - mmengine - INFO - Epoch(train) [481][40/63] lr: 2.2314e-03 eta: 10:25:47 time: 0.4992 data_time: 0.0099 memory: 16131 loss: 1.4307 loss_prob: 0.7807 loss_thr: 0.5183 loss_db: 0.1317 2022/10/26 02:21:18 - mmengine - INFO - Epoch(train) [481][45/63] lr: 2.2314e-03 eta: 10:25:47 time: 0.4993 data_time: 0.0123 memory: 16131 loss: 1.5823 loss_prob: 0.8992 loss_thr: 0.5357 loss_db: 0.1474 2022/10/26 02:21:21 - mmengine - INFO - Epoch(train) [481][50/63] lr: 2.2314e-03 eta: 10:25:34 time: 0.5123 data_time: 0.0242 memory: 16131 loss: 1.6316 loss_prob: 0.9421 loss_thr: 0.5345 loss_db: 0.1550 2022/10/26 02:21:23 - mmengine - INFO - Epoch(train) [481][55/63] lr: 2.2314e-03 eta: 10:25:34 time: 0.5030 data_time: 0.0204 memory: 16131 loss: 1.5519 loss_prob: 0.8754 loss_thr: 0.5251 loss_db: 0.1513 2022/10/26 02:21:26 - mmengine - INFO - Epoch(train) [481][60/63] lr: 2.2314e-03 eta: 10:25:21 time: 0.4987 data_time: 0.0090 memory: 16131 loss: 1.5636 loss_prob: 0.8846 loss_thr: 0.5311 loss_db: 0.1479 2022/10/26 02:21:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:21:32 - mmengine - INFO - Epoch(train) [482][5/63] lr: 2.2286e-03 eta: 10:25:21 time: 0.7133 data_time: 0.1961 memory: 16131 loss: 1.5676 loss_prob: 0.8722 loss_thr: 0.5496 loss_db: 0.1458 2022/10/26 02:21:35 - mmengine - INFO - Epoch(train) [482][10/63] lr: 2.2286e-03 eta: 10:25:06 time: 0.7603 data_time: 0.1984 memory: 16131 loss: 1.6244 loss_prob: 0.9264 loss_thr: 0.5430 loss_db: 0.1550 2022/10/26 02:21:37 - mmengine - INFO - Epoch(train) [482][15/63] lr: 2.2286e-03 eta: 10:25:06 time: 0.5269 data_time: 0.0088 memory: 16131 loss: 1.6906 loss_prob: 0.9741 loss_thr: 0.5560 loss_db: 0.1605 2022/10/26 02:21:40 - mmengine - INFO - Epoch(train) [482][20/63] lr: 2.2286e-03 eta: 10:24:53 time: 0.5193 data_time: 0.0062 memory: 16131 loss: 1.6293 loss_prob: 0.9251 loss_thr: 0.5504 loss_db: 0.1537 2022/10/26 02:21:42 - mmengine - INFO - Epoch(train) [482][25/63] lr: 2.2286e-03 eta: 10:24:53 time: 0.5360 data_time: 0.0112 memory: 16131 loss: 1.5087 loss_prob: 0.8285 loss_thr: 0.5397 loss_db: 0.1404 2022/10/26 02:21:46 - mmengine - INFO - Epoch(train) [482][30/63] lr: 2.2286e-03 eta: 10:24:41 time: 0.5889 data_time: 0.0367 memory: 16131 loss: 1.4223 loss_prob: 0.7658 loss_thr: 0.5248 loss_db: 0.1318 2022/10/26 02:21:48 - mmengine - INFO - Epoch(train) [482][35/63] lr: 2.2286e-03 eta: 10:24:41 time: 0.5731 data_time: 0.0327 memory: 16131 loss: 1.4005 loss_prob: 0.7730 loss_thr: 0.4950 loss_db: 0.1325 2022/10/26 02:21:51 - mmengine - INFO - Epoch(train) [482][40/63] lr: 2.2286e-03 eta: 10:24:28 time: 0.5191 data_time: 0.0077 memory: 16131 loss: 1.3474 loss_prob: 0.7443 loss_thr: 0.4769 loss_db: 0.1262 2022/10/26 02:21:54 - mmengine - INFO - Epoch(train) [482][45/63] lr: 2.2286e-03 eta: 10:24:28 time: 0.5297 data_time: 0.0079 memory: 16131 loss: 1.3995 loss_prob: 0.7752 loss_thr: 0.4962 loss_db: 0.1282 2022/10/26 02:21:56 - mmengine - INFO - Epoch(train) [482][50/63] lr: 2.2286e-03 eta: 10:24:15 time: 0.5163 data_time: 0.0177 memory: 16131 loss: 1.5565 loss_prob: 0.8716 loss_thr: 0.5397 loss_db: 0.1452 2022/10/26 02:21:59 - mmengine - INFO - Epoch(train) [482][55/63] lr: 2.2286e-03 eta: 10:24:15 time: 0.5110 data_time: 0.0238 memory: 16131 loss: 1.5807 loss_prob: 0.8809 loss_thr: 0.5505 loss_db: 0.1493 2022/10/26 02:22:01 - mmengine - INFO - Epoch(train) [482][60/63] lr: 2.2286e-03 eta: 10:24:02 time: 0.5285 data_time: 0.0128 memory: 16131 loss: 1.5125 loss_prob: 0.8486 loss_thr: 0.5215 loss_db: 0.1424 2022/10/26 02:22:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:22:07 - mmengine - INFO - Epoch(train) [483][5/63] lr: 2.2258e-03 eta: 10:24:02 time: 0.6753 data_time: 0.1802 memory: 16131 loss: 1.5090 loss_prob: 0.8602 loss_thr: 0.5110 loss_db: 0.1379 2022/10/26 02:22:10 - mmengine - INFO - Epoch(train) [483][10/63] lr: 2.2258e-03 eta: 10:23:46 time: 0.7037 data_time: 0.1834 memory: 16131 loss: 1.4570 loss_prob: 0.8332 loss_thr: 0.4897 loss_db: 0.1341 2022/10/26 02:22:12 - mmengine - INFO - Epoch(train) [483][15/63] lr: 2.2258e-03 eta: 10:23:46 time: 0.5226 data_time: 0.0113 memory: 16131 loss: 1.4161 loss_prob: 0.7886 loss_thr: 0.4944 loss_db: 0.1330 2022/10/26 02:22:15 - mmengine - INFO - Epoch(train) [483][20/63] lr: 2.2258e-03 eta: 10:23:33 time: 0.5202 data_time: 0.0079 memory: 16131 loss: 1.3883 loss_prob: 0.7540 loss_thr: 0.5078 loss_db: 0.1265 2022/10/26 02:22:17 - mmengine - INFO - Epoch(train) [483][25/63] lr: 2.2258e-03 eta: 10:23:33 time: 0.5319 data_time: 0.0141 memory: 16131 loss: 1.3670 loss_prob: 0.7423 loss_thr: 0.5016 loss_db: 0.1232 2022/10/26 02:22:20 - mmengine - INFO - Epoch(train) [483][30/63] lr: 2.2258e-03 eta: 10:23:20 time: 0.5308 data_time: 0.0318 memory: 16131 loss: 1.4282 loss_prob: 0.7747 loss_thr: 0.5219 loss_db: 0.1316 2022/10/26 02:22:23 - mmengine - INFO - Epoch(train) [483][35/63] lr: 2.2258e-03 eta: 10:23:20 time: 0.5499 data_time: 0.0304 memory: 16131 loss: 1.4985 loss_prob: 0.8313 loss_thr: 0.5280 loss_db: 0.1393 2022/10/26 02:22:26 - mmengine - INFO - Epoch(train) [483][40/63] lr: 2.2258e-03 eta: 10:23:08 time: 0.5442 data_time: 0.0112 memory: 16131 loss: 1.4778 loss_prob: 0.8289 loss_thr: 0.5109 loss_db: 0.1380 2022/10/26 02:22:28 - mmengine - INFO - Epoch(train) [483][45/63] lr: 2.2258e-03 eta: 10:23:08 time: 0.5211 data_time: 0.0081 memory: 16131 loss: 1.4288 loss_prob: 0.7818 loss_thr: 0.5136 loss_db: 0.1335 2022/10/26 02:22:31 - mmengine - INFO - Epoch(train) [483][50/63] lr: 2.2258e-03 eta: 10:22:55 time: 0.5103 data_time: 0.0221 memory: 16131 loss: 1.4146 loss_prob: 0.7722 loss_thr: 0.5123 loss_db: 0.1302 2022/10/26 02:22:33 - mmengine - INFO - Epoch(train) [483][55/63] lr: 2.2258e-03 eta: 10:22:55 time: 0.4876 data_time: 0.0200 memory: 16131 loss: 1.3729 loss_prob: 0.7486 loss_thr: 0.5002 loss_db: 0.1242 2022/10/26 02:22:36 - mmengine - INFO - Epoch(train) [483][60/63] lr: 2.2258e-03 eta: 10:22:42 time: 0.4924 data_time: 0.0068 memory: 16131 loss: 1.4530 loss_prob: 0.8153 loss_thr: 0.5046 loss_db: 0.1331 2022/10/26 02:22:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:22:42 - mmengine - INFO - Epoch(train) [484][5/63] lr: 2.2230e-03 eta: 10:22:42 time: 0.7365 data_time: 0.1791 memory: 16131 loss: 1.6892 loss_prob: 0.9707 loss_thr: 0.5580 loss_db: 0.1605 2022/10/26 02:22:44 - mmengine - INFO - Epoch(train) [484][10/63] lr: 2.2230e-03 eta: 10:22:26 time: 0.7575 data_time: 0.1794 memory: 16131 loss: 1.6155 loss_prob: 0.9059 loss_thr: 0.5597 loss_db: 0.1500 2022/10/26 02:22:47 - mmengine - INFO - Epoch(train) [484][15/63] lr: 2.2230e-03 eta: 10:22:26 time: 0.5116 data_time: 0.0064 memory: 16131 loss: 1.5564 loss_prob: 0.8828 loss_thr: 0.5263 loss_db: 0.1473 2022/10/26 02:22:50 - mmengine - INFO - Epoch(train) [484][20/63] lr: 2.2230e-03 eta: 10:22:13 time: 0.5197 data_time: 0.0064 memory: 16131 loss: 1.4279 loss_prob: 0.7928 loss_thr: 0.5003 loss_db: 0.1348 2022/10/26 02:22:52 - mmengine - INFO - Epoch(train) [484][25/63] lr: 2.2230e-03 eta: 10:22:13 time: 0.5133 data_time: 0.0161 memory: 16131 loss: 1.3820 loss_prob: 0.7586 loss_thr: 0.4966 loss_db: 0.1267 2022/10/26 02:22:55 - mmengine - INFO - Epoch(train) [484][30/63] lr: 2.2230e-03 eta: 10:22:00 time: 0.5079 data_time: 0.0333 memory: 16131 loss: 1.5292 loss_prob: 0.8527 loss_thr: 0.5372 loss_db: 0.1394 2022/10/26 02:22:57 - mmengine - INFO - Epoch(train) [484][35/63] lr: 2.2230e-03 eta: 10:22:00 time: 0.4962 data_time: 0.0231 memory: 16131 loss: 1.6055 loss_prob: 0.8978 loss_thr: 0.5597 loss_db: 0.1480 2022/10/26 02:23:00 - mmengine - INFO - Epoch(train) [484][40/63] lr: 2.2230e-03 eta: 10:21:47 time: 0.4909 data_time: 0.0081 memory: 16131 loss: 1.6077 loss_prob: 0.9124 loss_thr: 0.5451 loss_db: 0.1502 2022/10/26 02:23:02 - mmengine - INFO - Epoch(train) [484][45/63] lr: 2.2230e-03 eta: 10:21:47 time: 0.5063 data_time: 0.0092 memory: 16131 loss: 1.6741 loss_prob: 0.9798 loss_thr: 0.5305 loss_db: 0.1638 2022/10/26 02:23:05 - mmengine - INFO - Epoch(train) [484][50/63] lr: 2.2230e-03 eta: 10:21:34 time: 0.5064 data_time: 0.0235 memory: 16131 loss: 1.6433 loss_prob: 0.9623 loss_thr: 0.5211 loss_db: 0.1599 2022/10/26 02:23:07 - mmengine - INFO - Epoch(train) [484][55/63] lr: 2.2230e-03 eta: 10:21:34 time: 0.4953 data_time: 0.0243 memory: 16131 loss: 1.6111 loss_prob: 0.9278 loss_thr: 0.5344 loss_db: 0.1488 2022/10/26 02:23:10 - mmengine - INFO - Epoch(train) [484][60/63] lr: 2.2230e-03 eta: 10:21:21 time: 0.4899 data_time: 0.0119 memory: 16131 loss: 1.5830 loss_prob: 0.9042 loss_thr: 0.5322 loss_db: 0.1466 2022/10/26 02:23:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:23:16 - mmengine - INFO - Epoch(train) [485][5/63] lr: 2.2202e-03 eta: 10:21:21 time: 0.7348 data_time: 0.1996 memory: 16131 loss: 1.6117 loss_prob: 0.9149 loss_thr: 0.5426 loss_db: 0.1542 2022/10/26 02:23:19 - mmengine - INFO - Epoch(train) [485][10/63] lr: 2.2202e-03 eta: 10:21:06 time: 0.8172 data_time: 0.2024 memory: 16131 loss: 1.6358 loss_prob: 0.9367 loss_thr: 0.5435 loss_db: 0.1556 2022/10/26 02:23:22 - mmengine - INFO - Epoch(train) [485][15/63] lr: 2.2202e-03 eta: 10:21:06 time: 0.5903 data_time: 0.0138 memory: 16131 loss: 1.7015 loss_prob: 0.9785 loss_thr: 0.5620 loss_db: 0.1611 2022/10/26 02:23:24 - mmengine - INFO - Epoch(train) [485][20/63] lr: 2.2202e-03 eta: 10:20:54 time: 0.5271 data_time: 0.0130 memory: 16131 loss: 1.6988 loss_prob: 0.9870 loss_thr: 0.5437 loss_db: 0.1681 2022/10/26 02:23:27 - mmengine - INFO - Epoch(train) [485][25/63] lr: 2.2202e-03 eta: 10:20:54 time: 0.5064 data_time: 0.0182 memory: 16131 loss: 1.7112 loss_prob: 0.9885 loss_thr: 0.5550 loss_db: 0.1676 2022/10/26 02:23:30 - mmengine - INFO - Epoch(train) [485][30/63] lr: 2.2202e-03 eta: 10:20:41 time: 0.5316 data_time: 0.0283 memory: 16131 loss: 1.9576 loss_prob: 1.1645 loss_thr: 0.6058 loss_db: 0.1873 2022/10/26 02:23:32 - mmengine - INFO - Epoch(train) [485][35/63] lr: 2.2202e-03 eta: 10:20:41 time: 0.5242 data_time: 0.0229 memory: 16131 loss: 1.9610 loss_prob: 1.1693 loss_thr: 0.6005 loss_db: 0.1912 2022/10/26 02:23:35 - mmengine - INFO - Epoch(train) [485][40/63] lr: 2.2202e-03 eta: 10:20:28 time: 0.5223 data_time: 0.0103 memory: 16131 loss: 1.6723 loss_prob: 0.9442 loss_thr: 0.5719 loss_db: 0.1562 2022/10/26 02:23:38 - mmengine - INFO - Epoch(train) [485][45/63] lr: 2.2202e-03 eta: 10:20:28 time: 0.5414 data_time: 0.0129 memory: 16131 loss: 1.6207 loss_prob: 0.9115 loss_thr: 0.5613 loss_db: 0.1479 2022/10/26 02:23:40 - mmengine - INFO - Epoch(train) [485][50/63] lr: 2.2202e-03 eta: 10:20:16 time: 0.5238 data_time: 0.0181 memory: 16131 loss: 1.5368 loss_prob: 0.8625 loss_thr: 0.5320 loss_db: 0.1423 2022/10/26 02:23:43 - mmengine - INFO - Epoch(train) [485][55/63] lr: 2.2202e-03 eta: 10:20:16 time: 0.5205 data_time: 0.0214 memory: 16131 loss: 1.8319 loss_prob: 1.1081 loss_thr: 0.5562 loss_db: 0.1675 2022/10/26 02:23:46 - mmengine - INFO - Epoch(train) [485][60/63] lr: 2.2202e-03 eta: 10:20:03 time: 0.5591 data_time: 0.0157 memory: 16131 loss: 1.9094 loss_prob: 1.1590 loss_thr: 0.5767 loss_db: 0.1736 2022/10/26 02:23:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:23:53 - mmengine - INFO - Epoch(train) [486][5/63] lr: 2.2174e-03 eta: 10:20:03 time: 0.8399 data_time: 0.1992 memory: 16131 loss: 1.5551 loss_prob: 0.8905 loss_thr: 0.5222 loss_db: 0.1424 2022/10/26 02:23:55 - mmengine - INFO - Epoch(train) [486][10/63] lr: 2.2174e-03 eta: 10:19:49 time: 0.8344 data_time: 0.2010 memory: 16131 loss: 1.5348 loss_prob: 0.8688 loss_thr: 0.5207 loss_db: 0.1453 2022/10/26 02:23:58 - mmengine - INFO - Epoch(train) [486][15/63] lr: 2.2174e-03 eta: 10:19:49 time: 0.5071 data_time: 0.0090 memory: 16131 loss: 1.6001 loss_prob: 0.9080 loss_thr: 0.5381 loss_db: 0.1539 2022/10/26 02:24:01 - mmengine - INFO - Epoch(train) [486][20/63] lr: 2.2174e-03 eta: 10:19:37 time: 0.5337 data_time: 0.0118 memory: 16131 loss: 1.5910 loss_prob: 0.9045 loss_thr: 0.5336 loss_db: 0.1529 2022/10/26 02:24:04 - mmengine - INFO - Epoch(train) [486][25/63] lr: 2.2174e-03 eta: 10:19:37 time: 0.5671 data_time: 0.0336 memory: 16131 loss: 1.5692 loss_prob: 0.8902 loss_thr: 0.5260 loss_db: 0.1530 2022/10/26 02:24:06 - mmengine - INFO - Epoch(train) [486][30/63] lr: 2.2174e-03 eta: 10:19:24 time: 0.5395 data_time: 0.0302 memory: 16131 loss: 1.5019 loss_prob: 0.8506 loss_thr: 0.5065 loss_db: 0.1447 2022/10/26 02:24:09 - mmengine - INFO - Epoch(train) [486][35/63] lr: 2.2174e-03 eta: 10:19:24 time: 0.5047 data_time: 0.0072 memory: 16131 loss: 1.5270 loss_prob: 0.8658 loss_thr: 0.5182 loss_db: 0.1431 2022/10/26 02:24:11 - mmengine - INFO - Epoch(train) [486][40/63] lr: 2.2174e-03 eta: 10:19:11 time: 0.5103 data_time: 0.0047 memory: 16131 loss: 1.5276 loss_prob: 0.8539 loss_thr: 0.5312 loss_db: 0.1425 2022/10/26 02:24:14 - mmengine - INFO - Epoch(train) [486][45/63] lr: 2.2174e-03 eta: 10:19:11 time: 0.5328 data_time: 0.0093 memory: 16131 loss: 1.5084 loss_prob: 0.8414 loss_thr: 0.5258 loss_db: 0.1413 2022/10/26 02:24:17 - mmengine - INFO - Epoch(train) [486][50/63] lr: 2.2174e-03 eta: 10:18:59 time: 0.5429 data_time: 0.0232 memory: 16131 loss: 1.5092 loss_prob: 0.8507 loss_thr: 0.5169 loss_db: 0.1416 2022/10/26 02:24:19 - mmengine - INFO - Epoch(train) [486][55/63] lr: 2.2174e-03 eta: 10:18:59 time: 0.5258 data_time: 0.0210 memory: 16131 loss: 1.4140 loss_prob: 0.7740 loss_thr: 0.5116 loss_db: 0.1284 2022/10/26 02:24:22 - mmengine - INFO - Epoch(train) [486][60/63] lr: 2.2174e-03 eta: 10:18:46 time: 0.5177 data_time: 0.0070 memory: 16131 loss: 1.4473 loss_prob: 0.7981 loss_thr: 0.5139 loss_db: 0.1353 2022/10/26 02:24:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:24:28 - mmengine - INFO - Epoch(train) [487][5/63] lr: 2.2146e-03 eta: 10:18:46 time: 0.7295 data_time: 0.2212 memory: 16131 loss: 1.4928 loss_prob: 0.8298 loss_thr: 0.5239 loss_db: 0.1391 2022/10/26 02:24:31 - mmengine - INFO - Epoch(train) [487][10/63] lr: 2.2146e-03 eta: 10:18:31 time: 0.7755 data_time: 0.2219 memory: 16131 loss: 1.5710 loss_prob: 0.8858 loss_thr: 0.5389 loss_db: 0.1462 2022/10/26 02:24:34 - mmengine - INFO - Epoch(train) [487][15/63] lr: 2.2146e-03 eta: 10:18:31 time: 0.5259 data_time: 0.0059 memory: 16131 loss: 1.6791 loss_prob: 0.9913 loss_thr: 0.5307 loss_db: 0.1571 2022/10/26 02:24:37 - mmengine - INFO - Epoch(train) [487][20/63] lr: 2.2146e-03 eta: 10:18:19 time: 0.5709 data_time: 0.0059 memory: 16131 loss: 1.6431 loss_prob: 0.9808 loss_thr: 0.5125 loss_db: 0.1497 2022/10/26 02:24:39 - mmengine - INFO - Epoch(train) [487][25/63] lr: 2.2146e-03 eta: 10:18:19 time: 0.5848 data_time: 0.0263 memory: 16131 loss: 1.5590 loss_prob: 0.8997 loss_thr: 0.5167 loss_db: 0.1426 2022/10/26 02:24:42 - mmengine - INFO - Epoch(train) [487][30/63] lr: 2.2146e-03 eta: 10:18:06 time: 0.5372 data_time: 0.0347 memory: 16131 loss: 1.7717 loss_prob: 1.0358 loss_thr: 0.5646 loss_db: 0.1714 2022/10/26 02:24:44 - mmengine - INFO - Epoch(train) [487][35/63] lr: 2.2146e-03 eta: 10:18:06 time: 0.4947 data_time: 0.0140 memory: 16131 loss: 2.0004 loss_prob: 1.1943 loss_thr: 0.6086 loss_db: 0.1975 2022/10/26 02:24:47 - mmengine - INFO - Epoch(train) [487][40/63] lr: 2.2146e-03 eta: 10:17:53 time: 0.4877 data_time: 0.0067 memory: 16131 loss: 1.9705 loss_prob: 1.1834 loss_thr: 0.6006 loss_db: 0.1865 2022/10/26 02:24:49 - mmengine - INFO - Epoch(train) [487][45/63] lr: 2.2146e-03 eta: 10:17:53 time: 0.5099 data_time: 0.0069 memory: 16131 loss: 1.8477 loss_prob: 1.0941 loss_thr: 0.5798 loss_db: 0.1738 2022/10/26 02:24:52 - mmengine - INFO - Epoch(train) [487][50/63] lr: 2.2146e-03 eta: 10:17:41 time: 0.5195 data_time: 0.0158 memory: 16131 loss: 1.8938 loss_prob: 1.1161 loss_thr: 0.5972 loss_db: 0.1806 2022/10/26 02:24:54 - mmengine - INFO - Epoch(train) [487][55/63] lr: 2.2146e-03 eta: 10:17:41 time: 0.5070 data_time: 0.0198 memory: 16131 loss: 1.8327 loss_prob: 1.0702 loss_thr: 0.5853 loss_db: 0.1772 2022/10/26 02:24:57 - mmengine - INFO - Epoch(train) [487][60/63] lr: 2.2146e-03 eta: 10:17:27 time: 0.4846 data_time: 0.0085 memory: 16131 loss: 1.5988 loss_prob: 0.9084 loss_thr: 0.5361 loss_db: 0.1544 2022/10/26 02:24:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:25:03 - mmengine - INFO - Epoch(train) [488][5/63] lr: 2.2118e-03 eta: 10:17:27 time: 0.6979 data_time: 0.1816 memory: 16131 loss: 1.6153 loss_prob: 0.9248 loss_thr: 0.5361 loss_db: 0.1544 2022/10/26 02:25:06 - mmengine - INFO - Epoch(train) [488][10/63] lr: 2.2118e-03 eta: 10:17:12 time: 0.7394 data_time: 0.1833 memory: 16131 loss: 1.6963 loss_prob: 0.9839 loss_thr: 0.5508 loss_db: 0.1616 2022/10/26 02:25:08 - mmengine - INFO - Epoch(train) [488][15/63] lr: 2.2118e-03 eta: 10:17:12 time: 0.5227 data_time: 0.0137 memory: 16131 loss: 1.6194 loss_prob: 0.9148 loss_thr: 0.5535 loss_db: 0.1511 2022/10/26 02:25:11 - mmengine - INFO - Epoch(train) [488][20/63] lr: 2.2118e-03 eta: 10:16:59 time: 0.5205 data_time: 0.0097 memory: 16131 loss: 1.5476 loss_prob: 0.8651 loss_thr: 0.5399 loss_db: 0.1427 2022/10/26 02:25:14 - mmengine - INFO - Epoch(train) [488][25/63] lr: 2.2118e-03 eta: 10:16:59 time: 0.6021 data_time: 0.0117 memory: 16131 loss: 1.5813 loss_prob: 0.8901 loss_thr: 0.5442 loss_db: 0.1471 2022/10/26 02:25:18 - mmengine - INFO - Epoch(train) [488][30/63] lr: 2.2118e-03 eta: 10:16:49 time: 0.6829 data_time: 0.0336 memory: 16131 loss: 1.5601 loss_prob: 0.8811 loss_thr: 0.5295 loss_db: 0.1495 2022/10/26 02:25:20 - mmengine - INFO - Epoch(train) [488][35/63] lr: 2.2118e-03 eta: 10:16:49 time: 0.5983 data_time: 0.0300 memory: 16131 loss: 1.6854 loss_prob: 0.9868 loss_thr: 0.5439 loss_db: 0.1546 2022/10/26 02:25:23 - mmengine - INFO - Epoch(train) [488][40/63] lr: 2.2118e-03 eta: 10:16:36 time: 0.5074 data_time: 0.0081 memory: 16131 loss: 1.6483 loss_prob: 0.9686 loss_thr: 0.5328 loss_db: 0.1470 2022/10/26 02:25:25 - mmengine - INFO - Epoch(train) [488][45/63] lr: 2.2118e-03 eta: 10:16:36 time: 0.5191 data_time: 0.0071 memory: 16131 loss: 1.7126 loss_prob: 1.0396 loss_thr: 0.5123 loss_db: 0.1607 2022/10/26 02:25:28 - mmengine - INFO - Epoch(train) [488][50/63] lr: 2.2118e-03 eta: 10:16:23 time: 0.5230 data_time: 0.0140 memory: 16131 loss: 1.8202 loss_prob: 1.1000 loss_thr: 0.5480 loss_db: 0.1722 2022/10/26 02:25:31 - mmengine - INFO - Epoch(train) [488][55/63] lr: 2.2118e-03 eta: 10:16:23 time: 0.5414 data_time: 0.0219 memory: 16131 loss: 1.6267 loss_prob: 0.9219 loss_thr: 0.5514 loss_db: 0.1534 2022/10/26 02:25:34 - mmengine - INFO - Epoch(train) [488][60/63] lr: 2.2118e-03 eta: 10:16:12 time: 0.6038 data_time: 0.0190 memory: 16131 loss: 1.5246 loss_prob: 0.8576 loss_thr: 0.5240 loss_db: 0.1430 2022/10/26 02:25:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:25:41 - mmengine - INFO - Epoch(train) [489][5/63] lr: 2.2090e-03 eta: 10:16:12 time: 0.8348 data_time: 0.1883 memory: 16131 loss: 1.4628 loss_prob: 0.8241 loss_thr: 0.5021 loss_db: 0.1366 2022/10/26 02:25:43 - mmengine - INFO - Epoch(train) [489][10/63] lr: 2.2090e-03 eta: 10:15:57 time: 0.7770 data_time: 0.1875 memory: 16131 loss: 1.6318 loss_prob: 0.9484 loss_thr: 0.5277 loss_db: 0.1558 2022/10/26 02:25:46 - mmengine - INFO - Epoch(train) [489][15/63] lr: 2.2090e-03 eta: 10:15:57 time: 0.5144 data_time: 0.0068 memory: 16131 loss: 1.7455 loss_prob: 1.0160 loss_thr: 0.5630 loss_db: 0.1665 2022/10/26 02:25:49 - mmengine - INFO - Epoch(train) [489][20/63] lr: 2.2090e-03 eta: 10:15:44 time: 0.5425 data_time: 0.0064 memory: 16131 loss: 1.6167 loss_prob: 0.9187 loss_thr: 0.5450 loss_db: 0.1530 2022/10/26 02:25:51 - mmengine - INFO - Epoch(train) [489][25/63] lr: 2.2090e-03 eta: 10:15:44 time: 0.5553 data_time: 0.0326 memory: 16131 loss: 1.5485 loss_prob: 0.8781 loss_thr: 0.5241 loss_db: 0.1463 2022/10/26 02:25:54 - mmengine - INFO - Epoch(train) [489][30/63] lr: 2.2090e-03 eta: 10:15:32 time: 0.5553 data_time: 0.0348 memory: 16131 loss: 1.5553 loss_prob: 0.8935 loss_thr: 0.5139 loss_db: 0.1479 2022/10/26 02:25:57 - mmengine - INFO - Epoch(train) [489][35/63] lr: 2.2090e-03 eta: 10:15:32 time: 0.5390 data_time: 0.0115 memory: 16131 loss: 1.5274 loss_prob: 0.8679 loss_thr: 0.5196 loss_db: 0.1400 2022/10/26 02:25:59 - mmengine - INFO - Epoch(train) [489][40/63] lr: 2.2090e-03 eta: 10:15:20 time: 0.5184 data_time: 0.0083 memory: 16131 loss: 1.5119 loss_prob: 0.8422 loss_thr: 0.5305 loss_db: 0.1392 2022/10/26 02:26:02 - mmengine - INFO - Epoch(train) [489][45/63] lr: 2.2090e-03 eta: 10:15:20 time: 0.5063 data_time: 0.0043 memory: 16131 loss: 1.4722 loss_prob: 0.8099 loss_thr: 0.5250 loss_db: 0.1373 2022/10/26 02:26:05 - mmengine - INFO - Epoch(train) [489][50/63] lr: 2.2090e-03 eta: 10:15:07 time: 0.5215 data_time: 0.0240 memory: 16131 loss: 1.4098 loss_prob: 0.7707 loss_thr: 0.5083 loss_db: 0.1308 2022/10/26 02:26:07 - mmengine - INFO - Epoch(train) [489][55/63] lr: 2.2090e-03 eta: 10:15:07 time: 0.5212 data_time: 0.0251 memory: 16131 loss: 1.3900 loss_prob: 0.7635 loss_thr: 0.4952 loss_db: 0.1313 2022/10/26 02:26:10 - mmengine - INFO - Epoch(train) [489][60/63] lr: 2.2090e-03 eta: 10:14:54 time: 0.5316 data_time: 0.0070 memory: 16131 loss: 1.5000 loss_prob: 0.8367 loss_thr: 0.5261 loss_db: 0.1373 2022/10/26 02:26:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:26:17 - mmengine - INFO - Epoch(train) [490][5/63] lr: 2.2062e-03 eta: 10:14:54 time: 0.7777 data_time: 0.1813 memory: 16131 loss: 1.5762 loss_prob: 0.9057 loss_thr: 0.5179 loss_db: 0.1526 2022/10/26 02:26:19 - mmengine - INFO - Epoch(train) [490][10/63] lr: 2.2062e-03 eta: 10:14:40 time: 0.8238 data_time: 0.1809 memory: 16131 loss: 1.6852 loss_prob: 0.9870 loss_thr: 0.5379 loss_db: 0.1603 2022/10/26 02:26:22 - mmengine - INFO - Epoch(train) [490][15/63] lr: 2.2062e-03 eta: 10:14:40 time: 0.5737 data_time: 0.0104 memory: 16131 loss: 1.9659 loss_prob: 1.1994 loss_thr: 0.5780 loss_db: 0.1885 2022/10/26 02:26:25 - mmengine - INFO - Epoch(train) [490][20/63] lr: 2.2062e-03 eta: 10:14:29 time: 0.5995 data_time: 0.0126 memory: 16131 loss: 2.0992 loss_prob: 1.3048 loss_thr: 0.5854 loss_db: 0.2091 2022/10/26 02:26:28 - mmengine - INFO - Epoch(train) [490][25/63] lr: 2.2062e-03 eta: 10:14:29 time: 0.5771 data_time: 0.0235 memory: 16131 loss: 2.0317 loss_prob: 1.2619 loss_thr: 0.5689 loss_db: 0.2009 2022/10/26 02:26:31 - mmengine - INFO - Epoch(train) [490][30/63] lr: 2.2062e-03 eta: 10:14:16 time: 0.5313 data_time: 0.0318 memory: 16131 loss: 1.8537 loss_prob: 1.1259 loss_thr: 0.5541 loss_db: 0.1738 2022/10/26 02:26:33 - mmengine - INFO - Epoch(train) [490][35/63] lr: 2.2062e-03 eta: 10:14:16 time: 0.5110 data_time: 0.0168 memory: 16131 loss: 1.7452 loss_prob: 1.0398 loss_thr: 0.5349 loss_db: 0.1705 2022/10/26 02:26:36 - mmengine - INFO - Epoch(train) [490][40/63] lr: 2.2062e-03 eta: 10:14:03 time: 0.5015 data_time: 0.0077 memory: 16131 loss: 1.6222 loss_prob: 0.9323 loss_thr: 0.5341 loss_db: 0.1558 2022/10/26 02:26:38 - mmengine - INFO - Epoch(train) [490][45/63] lr: 2.2062e-03 eta: 10:14:03 time: 0.4930 data_time: 0.0073 memory: 16131 loss: 1.8325 loss_prob: 1.0875 loss_thr: 0.5586 loss_db: 0.1865 2022/10/26 02:26:41 - mmengine - INFO - Epoch(train) [490][50/63] lr: 2.2062e-03 eta: 10:13:51 time: 0.5228 data_time: 0.0192 memory: 16131 loss: 1.9189 loss_prob: 1.1621 loss_thr: 0.5605 loss_db: 0.1962 2022/10/26 02:26:43 - mmengine - INFO - Epoch(train) [490][55/63] lr: 2.2062e-03 eta: 10:13:51 time: 0.5315 data_time: 0.0184 memory: 16131 loss: 1.7566 loss_prob: 1.0412 loss_thr: 0.5533 loss_db: 0.1621 2022/10/26 02:26:46 - mmengine - INFO - Epoch(train) [490][60/63] lr: 2.2062e-03 eta: 10:13:38 time: 0.4918 data_time: 0.0060 memory: 16131 loss: 1.7613 loss_prob: 1.0240 loss_thr: 0.5718 loss_db: 0.1654 2022/10/26 02:26:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:26:52 - mmengine - INFO - Epoch(train) [491][5/63] lr: 2.2034e-03 eta: 10:13:38 time: 0.7339 data_time: 0.1897 memory: 16131 loss: 1.7163 loss_prob: 0.9984 loss_thr: 0.5620 loss_db: 0.1559 2022/10/26 02:26:55 - mmengine - INFO - Epoch(train) [491][10/63] lr: 2.2034e-03 eta: 10:13:23 time: 0.7732 data_time: 0.1881 memory: 16131 loss: 1.7304 loss_prob: 1.0138 loss_thr: 0.5609 loss_db: 0.1557 2022/10/26 02:26:58 - mmengine - INFO - Epoch(train) [491][15/63] lr: 2.2034e-03 eta: 10:13:23 time: 0.5818 data_time: 0.0119 memory: 16131 loss: 1.6250 loss_prob: 0.9192 loss_thr: 0.5522 loss_db: 0.1536 2022/10/26 02:27:00 - mmengine - INFO - Epoch(train) [491][20/63] lr: 2.2034e-03 eta: 10:13:10 time: 0.5422 data_time: 0.0123 memory: 16131 loss: 1.5675 loss_prob: 0.8777 loss_thr: 0.5386 loss_db: 0.1512 2022/10/26 02:27:03 - mmengine - INFO - Epoch(train) [491][25/63] lr: 2.2034e-03 eta: 10:13:10 time: 0.5161 data_time: 0.0186 memory: 16131 loss: 1.6104 loss_prob: 0.9005 loss_thr: 0.5639 loss_db: 0.1460 2022/10/26 02:27:06 - mmengine - INFO - Epoch(train) [491][30/63] lr: 2.2034e-03 eta: 10:12:58 time: 0.5282 data_time: 0.0323 memory: 16131 loss: 1.6964 loss_prob: 0.9578 loss_thr: 0.5873 loss_db: 0.1514 2022/10/26 02:27:08 - mmengine - INFO - Epoch(train) [491][35/63] lr: 2.2034e-03 eta: 10:12:58 time: 0.5231 data_time: 0.0276 memory: 16131 loss: 1.5899 loss_prob: 0.8973 loss_thr: 0.5429 loss_db: 0.1497 2022/10/26 02:27:11 - mmengine - INFO - Epoch(train) [491][40/63] lr: 2.2034e-03 eta: 10:12:45 time: 0.5155 data_time: 0.0194 memory: 16131 loss: 1.4389 loss_prob: 0.8004 loss_thr: 0.5020 loss_db: 0.1365 2022/10/26 02:27:14 - mmengine - INFO - Epoch(train) [491][45/63] lr: 2.2034e-03 eta: 10:12:45 time: 0.5312 data_time: 0.0109 memory: 16131 loss: 1.5484 loss_prob: 0.8771 loss_thr: 0.5220 loss_db: 0.1494 2022/10/26 02:27:16 - mmengine - INFO - Epoch(train) [491][50/63] lr: 2.2034e-03 eta: 10:12:33 time: 0.5571 data_time: 0.0186 memory: 16131 loss: 2.3577 loss_prob: 1.5719 loss_thr: 0.5646 loss_db: 0.2212 2022/10/26 02:27:19 - mmengine - INFO - Epoch(train) [491][55/63] lr: 2.2034e-03 eta: 10:12:33 time: 0.5429 data_time: 0.0185 memory: 16131 loss: 2.7920 loss_prob: 1.9197 loss_thr: 0.6095 loss_db: 0.2628 2022/10/26 02:27:22 - mmengine - INFO - Epoch(train) [491][60/63] lr: 2.2034e-03 eta: 10:12:21 time: 0.5345 data_time: 0.0094 memory: 16131 loss: 2.3701 loss_prob: 1.5152 loss_thr: 0.6160 loss_db: 0.2389 2022/10/26 02:27:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:27:28 - mmengine - INFO - Epoch(train) [492][5/63] lr: 2.2006e-03 eta: 10:12:21 time: 0.6982 data_time: 0.1722 memory: 16131 loss: 2.0834 loss_prob: 1.2777 loss_thr: 0.5908 loss_db: 0.2149 2022/10/26 02:27:30 - mmengine - INFO - Epoch(train) [492][10/63] lr: 2.2006e-03 eta: 10:12:05 time: 0.7117 data_time: 0.1659 memory: 16131 loss: 2.1016 loss_prob: 1.2810 loss_thr: 0.6098 loss_db: 0.2108 2022/10/26 02:27:33 - mmengine - INFO - Epoch(train) [492][15/63] lr: 2.2006e-03 eta: 10:12:05 time: 0.4923 data_time: 0.0106 memory: 16131 loss: 2.0101 loss_prob: 1.2200 loss_thr: 0.5909 loss_db: 0.1992 2022/10/26 02:27:35 - mmengine - INFO - Epoch(train) [492][20/63] lr: 2.2006e-03 eta: 10:11:52 time: 0.5006 data_time: 0.0098 memory: 16131 loss: 1.8798 loss_prob: 1.1210 loss_thr: 0.5779 loss_db: 0.1810 2022/10/26 02:27:38 - mmengine - INFO - Epoch(train) [492][25/63] lr: 2.2006e-03 eta: 10:11:52 time: 0.5261 data_time: 0.0178 memory: 16131 loss: 2.2716 loss_prob: 1.4048 loss_thr: 0.6389 loss_db: 0.2279 2022/10/26 02:27:41 - mmengine - INFO - Epoch(train) [492][30/63] lr: 2.2006e-03 eta: 10:11:40 time: 0.5750 data_time: 0.0333 memory: 16131 loss: 2.4032 loss_prob: 1.5082 loss_thr: 0.6367 loss_db: 0.2583 2022/10/26 02:27:44 - mmengine - INFO - Epoch(train) [492][35/63] lr: 2.2006e-03 eta: 10:11:40 time: 0.5595 data_time: 0.0235 memory: 16131 loss: 2.0727 loss_prob: 1.2560 loss_thr: 0.6006 loss_db: 0.2161 2022/10/26 02:27:46 - mmengine - INFO - Epoch(train) [492][40/63] lr: 2.2006e-03 eta: 10:11:27 time: 0.4942 data_time: 0.0063 memory: 16131 loss: 1.8819 loss_prob: 1.1181 loss_thr: 0.5858 loss_db: 0.1780 2022/10/26 02:27:48 - mmengine - INFO - Epoch(train) [492][45/63] lr: 2.2006e-03 eta: 10:11:27 time: 0.4895 data_time: 0.0058 memory: 16131 loss: 1.8334 loss_prob: 1.0772 loss_thr: 0.5848 loss_db: 0.1714 2022/10/26 02:27:51 - mmengine - INFO - Epoch(train) [492][50/63] lr: 2.2006e-03 eta: 10:11:15 time: 0.5143 data_time: 0.0130 memory: 16131 loss: 1.7978 loss_prob: 1.0485 loss_thr: 0.5787 loss_db: 0.1706 2022/10/26 02:27:54 - mmengine - INFO - Epoch(train) [492][55/63] lr: 2.2006e-03 eta: 10:11:15 time: 0.5309 data_time: 0.0189 memory: 16131 loss: 1.7167 loss_prob: 0.9884 loss_thr: 0.5702 loss_db: 0.1580 2022/10/26 02:27:56 - mmengine - INFO - Epoch(train) [492][60/63] lr: 2.2006e-03 eta: 10:11:02 time: 0.5443 data_time: 0.0162 memory: 16131 loss: 1.6942 loss_prob: 0.9768 loss_thr: 0.5589 loss_db: 0.1584 2022/10/26 02:27:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:28:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:28:02 - mmengine - INFO - Epoch(train) [493][5/63] lr: 2.1978e-03 eta: 10:11:02 time: 0.6682 data_time: 0.1701 memory: 16131 loss: 1.6604 loss_prob: 0.9680 loss_thr: 0.5326 loss_db: 0.1598 2022/10/26 02:28:05 - mmengine - INFO - Epoch(train) [493][10/63] lr: 2.1978e-03 eta: 10:10:46 time: 0.6932 data_time: 0.1747 memory: 16131 loss: 1.5573 loss_prob: 0.8876 loss_thr: 0.5252 loss_db: 0.1445 2022/10/26 02:28:07 - mmengine - INFO - Epoch(train) [493][15/63] lr: 2.1978e-03 eta: 10:10:46 time: 0.5303 data_time: 0.0109 memory: 16131 loss: 1.5655 loss_prob: 0.8876 loss_thr: 0.5294 loss_db: 0.1485 2022/10/26 02:28:10 - mmengine - INFO - Epoch(train) [493][20/63] lr: 2.1978e-03 eta: 10:10:34 time: 0.5202 data_time: 0.0045 memory: 16131 loss: 1.5183 loss_prob: 0.8498 loss_thr: 0.5266 loss_db: 0.1419 2022/10/26 02:28:12 - mmengine - INFO - Epoch(train) [493][25/63] lr: 2.1978e-03 eta: 10:10:34 time: 0.5041 data_time: 0.0266 memory: 16131 loss: 1.5921 loss_prob: 0.8938 loss_thr: 0.5474 loss_db: 0.1508 2022/10/26 02:28:15 - mmengine - INFO - Epoch(train) [493][30/63] lr: 2.1978e-03 eta: 10:10:21 time: 0.5180 data_time: 0.0395 memory: 16131 loss: 1.6597 loss_prob: 0.9539 loss_thr: 0.5511 loss_db: 0.1547 2022/10/26 02:28:18 - mmengine - INFO - Epoch(train) [493][35/63] lr: 2.1978e-03 eta: 10:10:21 time: 0.5122 data_time: 0.0189 memory: 16131 loss: 1.5815 loss_prob: 0.9051 loss_thr: 0.5324 loss_db: 0.1440 2022/10/26 02:28:20 - mmengine - INFO - Epoch(train) [493][40/63] lr: 2.1978e-03 eta: 10:10:09 time: 0.5184 data_time: 0.0073 memory: 16131 loss: 1.5971 loss_prob: 0.9027 loss_thr: 0.5434 loss_db: 0.1511 2022/10/26 02:28:23 - mmengine - INFO - Epoch(train) [493][45/63] lr: 2.1978e-03 eta: 10:10:09 time: 0.5239 data_time: 0.0069 memory: 16131 loss: 1.7221 loss_prob: 0.9698 loss_thr: 0.5883 loss_db: 0.1639 2022/10/26 02:28:25 - mmengine - INFO - Epoch(train) [493][50/63] lr: 2.1978e-03 eta: 10:09:56 time: 0.5054 data_time: 0.0143 memory: 16131 loss: 1.6580 loss_prob: 0.9274 loss_thr: 0.5778 loss_db: 0.1527 2022/10/26 02:28:28 - mmengine - INFO - Epoch(train) [493][55/63] lr: 2.1978e-03 eta: 10:09:56 time: 0.4983 data_time: 0.0198 memory: 16131 loss: 1.5509 loss_prob: 0.8722 loss_thr: 0.5361 loss_db: 0.1426 2022/10/26 02:28:30 - mmengine - INFO - Epoch(train) [493][60/63] lr: 2.1978e-03 eta: 10:09:43 time: 0.5038 data_time: 0.0122 memory: 16131 loss: 1.5527 loss_prob: 0.8749 loss_thr: 0.5315 loss_db: 0.1463 2022/10/26 02:28:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:28:38 - mmengine - INFO - Epoch(train) [494][5/63] lr: 2.1950e-03 eta: 10:09:43 time: 0.8148 data_time: 0.1971 memory: 16131 loss: 1.4664 loss_prob: 0.8228 loss_thr: 0.5058 loss_db: 0.1378 2022/10/26 02:28:40 - mmengine - INFO - Epoch(train) [494][10/63] lr: 2.1950e-03 eta: 10:09:29 time: 0.8532 data_time: 0.1972 memory: 16131 loss: 1.4503 loss_prob: 0.8066 loss_thr: 0.5091 loss_db: 0.1346 2022/10/26 02:28:43 - mmengine - INFO - Epoch(train) [494][15/63] lr: 2.1950e-03 eta: 10:09:29 time: 0.4963 data_time: 0.0048 memory: 16131 loss: 1.4983 loss_prob: 0.8399 loss_thr: 0.5188 loss_db: 0.1396 2022/10/26 02:28:45 - mmengine - INFO - Epoch(train) [494][20/63] lr: 2.1950e-03 eta: 10:09:16 time: 0.4850 data_time: 0.0051 memory: 16131 loss: 1.4516 loss_prob: 0.8117 loss_thr: 0.5068 loss_db: 0.1331 2022/10/26 02:28:47 - mmengine - INFO - Epoch(train) [494][25/63] lr: 2.1950e-03 eta: 10:09:16 time: 0.4922 data_time: 0.0202 memory: 16131 loss: 1.4490 loss_prob: 0.7997 loss_thr: 0.5174 loss_db: 0.1319 2022/10/26 02:28:50 - mmengine - INFO - Epoch(train) [494][30/63] lr: 2.1950e-03 eta: 10:09:04 time: 0.5155 data_time: 0.0340 memory: 16131 loss: 1.4554 loss_prob: 0.7928 loss_thr: 0.5285 loss_db: 0.1341 2022/10/26 02:28:53 - mmengine - INFO - Epoch(train) [494][35/63] lr: 2.1950e-03 eta: 10:09:04 time: 0.5581 data_time: 0.0190 memory: 16131 loss: 1.4686 loss_prob: 0.8052 loss_thr: 0.5277 loss_db: 0.1356 2022/10/26 02:28:56 - mmengine - INFO - Epoch(train) [494][40/63] lr: 2.1950e-03 eta: 10:08:52 time: 0.5486 data_time: 0.0051 memory: 16131 loss: 1.5862 loss_prob: 0.8845 loss_thr: 0.5556 loss_db: 0.1462 2022/10/26 02:28:59 - mmengine - INFO - Epoch(train) [494][45/63] lr: 2.1950e-03 eta: 10:08:52 time: 0.5776 data_time: 0.0062 memory: 16131 loss: 1.5146 loss_prob: 0.8412 loss_thr: 0.5328 loss_db: 0.1406 2022/10/26 02:29:02 - mmengine - INFO - Epoch(train) [494][50/63] lr: 2.1950e-03 eta: 10:08:40 time: 0.6010 data_time: 0.0201 memory: 16131 loss: 1.5168 loss_prob: 0.8614 loss_thr: 0.5092 loss_db: 0.1461 2022/10/26 02:29:04 - mmengine - INFO - Epoch(train) [494][55/63] lr: 2.1950e-03 eta: 10:08:40 time: 0.5312 data_time: 0.0206 memory: 16131 loss: 1.5324 loss_prob: 0.8732 loss_thr: 0.5159 loss_db: 0.1433 2022/10/26 02:29:07 - mmengine - INFO - Epoch(train) [494][60/63] lr: 2.1950e-03 eta: 10:08:28 time: 0.5051 data_time: 0.0063 memory: 16131 loss: 1.4638 loss_prob: 0.8148 loss_thr: 0.5138 loss_db: 0.1352 2022/10/26 02:29:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:29:13 - mmengine - INFO - Epoch(train) [495][5/63] lr: 2.1922e-03 eta: 10:08:28 time: 0.7479 data_time: 0.1892 memory: 16131 loss: 1.5832 loss_prob: 0.8808 loss_thr: 0.5570 loss_db: 0.1455 2022/10/26 02:29:16 - mmengine - INFO - Epoch(train) [495][10/63] lr: 2.1922e-03 eta: 10:08:13 time: 0.7738 data_time: 0.1906 memory: 16131 loss: 1.5741 loss_prob: 0.8769 loss_thr: 0.5533 loss_db: 0.1438 2022/10/26 02:29:18 - mmengine - INFO - Epoch(train) [495][15/63] lr: 2.1922e-03 eta: 10:08:13 time: 0.5168 data_time: 0.0098 memory: 16131 loss: 1.5264 loss_prob: 0.8646 loss_thr: 0.5169 loss_db: 0.1449 2022/10/26 02:29:21 - mmengine - INFO - Epoch(train) [495][20/63] lr: 2.1922e-03 eta: 10:08:00 time: 0.5038 data_time: 0.0093 memory: 16131 loss: 1.5389 loss_prob: 0.8632 loss_thr: 0.5302 loss_db: 0.1456 2022/10/26 02:29:24 - mmengine - INFO - Epoch(train) [495][25/63] lr: 2.1922e-03 eta: 10:08:00 time: 0.5297 data_time: 0.0204 memory: 16131 loss: 1.5007 loss_prob: 0.8299 loss_thr: 0.5312 loss_db: 0.1396 2022/10/26 02:29:26 - mmengine - INFO - Epoch(train) [495][30/63] lr: 2.1922e-03 eta: 10:07:48 time: 0.5454 data_time: 0.0286 memory: 16131 loss: 1.5260 loss_prob: 0.8509 loss_thr: 0.5333 loss_db: 0.1418 2022/10/26 02:29:30 - mmengine - INFO - Epoch(train) [495][35/63] lr: 2.1922e-03 eta: 10:07:48 time: 0.5989 data_time: 0.0138 memory: 16131 loss: 1.5399 loss_prob: 0.8666 loss_thr: 0.5286 loss_db: 0.1446 2022/10/26 02:29:33 - mmengine - INFO - Epoch(train) [495][40/63] lr: 2.1922e-03 eta: 10:07:37 time: 0.6344 data_time: 0.0113 memory: 16131 loss: 1.4449 loss_prob: 0.7958 loss_thr: 0.5145 loss_db: 0.1346 2022/10/26 02:29:35 - mmengine - INFO - Epoch(train) [495][45/63] lr: 2.1922e-03 eta: 10:07:37 time: 0.5654 data_time: 0.0136 memory: 16131 loss: 1.4585 loss_prob: 0.7982 loss_thr: 0.5249 loss_db: 0.1354 2022/10/26 02:29:38 - mmengine - INFO - Epoch(train) [495][50/63] lr: 2.1922e-03 eta: 10:07:25 time: 0.5309 data_time: 0.0261 memory: 16131 loss: 1.4374 loss_prob: 0.7924 loss_thr: 0.5132 loss_db: 0.1318 2022/10/26 02:29:40 - mmengine - INFO - Epoch(train) [495][55/63] lr: 2.1922e-03 eta: 10:07:25 time: 0.5023 data_time: 0.0236 memory: 16131 loss: 1.4444 loss_prob: 0.8009 loss_thr: 0.5128 loss_db: 0.1307 2022/10/26 02:29:43 - mmengine - INFO - Epoch(train) [495][60/63] lr: 2.1922e-03 eta: 10:07:12 time: 0.5075 data_time: 0.0069 memory: 16131 loss: 1.4748 loss_prob: 0.8161 loss_thr: 0.5244 loss_db: 0.1342 2022/10/26 02:29:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:29:49 - mmengine - INFO - Epoch(train) [496][5/63] lr: 2.1894e-03 eta: 10:07:12 time: 0.7088 data_time: 0.2001 memory: 16131 loss: 1.5207 loss_prob: 0.8342 loss_thr: 0.5502 loss_db: 0.1363 2022/10/26 02:29:52 - mmengine - INFO - Epoch(train) [496][10/63] lr: 2.1894e-03 eta: 10:06:57 time: 0.7735 data_time: 0.2006 memory: 16131 loss: 1.4457 loss_prob: 0.7921 loss_thr: 0.5202 loss_db: 0.1334 2022/10/26 02:29:57 - mmengine - INFO - Epoch(train) [496][15/63] lr: 2.1894e-03 eta: 10:06:57 time: 0.8098 data_time: 0.0158 memory: 16131 loss: 1.4925 loss_prob: 0.8317 loss_thr: 0.5213 loss_db: 0.1394 2022/10/26 02:30:01 - mmengine - INFO - Epoch(train) [496][20/63] lr: 2.1894e-03 eta: 10:06:50 time: 0.8901 data_time: 0.0144 memory: 16131 loss: 1.4802 loss_prob: 0.8273 loss_thr: 0.5149 loss_db: 0.1380 2022/10/26 02:30:03 - mmengine - INFO - Epoch(train) [496][25/63] lr: 2.1894e-03 eta: 10:06:50 time: 0.6444 data_time: 0.0235 memory: 16131 loss: 1.4337 loss_prob: 0.7963 loss_thr: 0.5061 loss_db: 0.1312 2022/10/26 02:30:07 - mmengine - INFO - Epoch(train) [496][30/63] lr: 2.1894e-03 eta: 10:06:38 time: 0.5704 data_time: 0.0564 memory: 16131 loss: 1.4240 loss_prob: 0.7899 loss_thr: 0.5041 loss_db: 0.1301 2022/10/26 02:30:09 - mmengine - INFO - Epoch(train) [496][35/63] lr: 2.1894e-03 eta: 10:06:38 time: 0.5717 data_time: 0.0462 memory: 16131 loss: 1.4088 loss_prob: 0.7733 loss_thr: 0.5040 loss_db: 0.1315 2022/10/26 02:30:12 - mmengine - INFO - Epoch(train) [496][40/63] lr: 2.1894e-03 eta: 10:06:26 time: 0.5274 data_time: 0.0147 memory: 16131 loss: 1.4958 loss_prob: 0.8260 loss_thr: 0.5325 loss_db: 0.1373 2022/10/26 02:30:14 - mmengine - INFO - Epoch(train) [496][45/63] lr: 2.1894e-03 eta: 10:06:26 time: 0.5093 data_time: 0.0083 memory: 16131 loss: 1.4991 loss_prob: 0.8289 loss_thr: 0.5352 loss_db: 0.1351 2022/10/26 02:30:17 - mmengine - INFO - Epoch(train) [496][50/63] lr: 2.1894e-03 eta: 10:06:13 time: 0.5175 data_time: 0.0163 memory: 16131 loss: 1.4330 loss_prob: 0.7759 loss_thr: 0.5275 loss_db: 0.1296 2022/10/26 02:30:20 - mmengine - INFO - Epoch(train) [496][55/63] lr: 2.1894e-03 eta: 10:06:13 time: 0.5547 data_time: 0.0203 memory: 16131 loss: 1.5999 loss_prob: 0.8934 loss_thr: 0.5533 loss_db: 0.1532 2022/10/26 02:30:22 - mmengine - INFO - Epoch(train) [496][60/63] lr: 2.1894e-03 eta: 10:06:01 time: 0.5387 data_time: 0.0111 memory: 16131 loss: 1.6346 loss_prob: 0.9262 loss_thr: 0.5535 loss_db: 0.1549 2022/10/26 02:30:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:30:28 - mmengine - INFO - Epoch(train) [497][5/63] lr: 2.1866e-03 eta: 10:06:01 time: 0.6688 data_time: 0.1700 memory: 16131 loss: 1.6566 loss_prob: 0.9690 loss_thr: 0.5221 loss_db: 0.1656 2022/10/26 02:30:30 - mmengine - INFO - Epoch(train) [497][10/63] lr: 2.1866e-03 eta: 10:05:45 time: 0.6823 data_time: 0.1671 memory: 16131 loss: 1.6738 loss_prob: 0.9713 loss_thr: 0.5393 loss_db: 0.1632 2022/10/26 02:30:33 - mmengine - INFO - Epoch(train) [497][15/63] lr: 2.1866e-03 eta: 10:05:45 time: 0.4886 data_time: 0.0091 memory: 16131 loss: 1.6924 loss_prob: 0.9768 loss_thr: 0.5557 loss_db: 0.1599 2022/10/26 02:30:35 - mmengine - INFO - Epoch(train) [497][20/63] lr: 2.1866e-03 eta: 10:05:32 time: 0.4949 data_time: 0.0160 memory: 16131 loss: 1.7208 loss_prob: 0.9971 loss_thr: 0.5585 loss_db: 0.1653 2022/10/26 02:30:38 - mmengine - INFO - Epoch(train) [497][25/63] lr: 2.1866e-03 eta: 10:05:32 time: 0.5049 data_time: 0.0284 memory: 16131 loss: 1.6268 loss_prob: 0.9308 loss_thr: 0.5413 loss_db: 0.1547 2022/10/26 02:30:41 - mmengine - INFO - Epoch(train) [497][30/63] lr: 2.1866e-03 eta: 10:05:20 time: 0.5211 data_time: 0.0253 memory: 16131 loss: 1.6474 loss_prob: 0.9527 loss_thr: 0.5380 loss_db: 0.1567 2022/10/26 02:30:43 - mmengine - INFO - Epoch(train) [497][35/63] lr: 2.1866e-03 eta: 10:05:20 time: 0.5111 data_time: 0.0134 memory: 16131 loss: 1.7797 loss_prob: 1.0635 loss_thr: 0.5419 loss_db: 0.1743 2022/10/26 02:30:46 - mmengine - INFO - Epoch(train) [497][40/63] lr: 2.1866e-03 eta: 10:05:07 time: 0.5126 data_time: 0.0123 memory: 16131 loss: 1.6690 loss_prob: 0.9800 loss_thr: 0.5292 loss_db: 0.1598 2022/10/26 02:30:48 - mmengine - INFO - Epoch(train) [497][45/63] lr: 2.1866e-03 eta: 10:05:07 time: 0.5238 data_time: 0.0133 memory: 16131 loss: 1.5490 loss_prob: 0.8780 loss_thr: 0.5253 loss_db: 0.1457 2022/10/26 02:30:51 - mmengine - INFO - Epoch(train) [497][50/63] lr: 2.1866e-03 eta: 10:04:55 time: 0.5375 data_time: 0.0226 memory: 16131 loss: 1.5817 loss_prob: 0.8915 loss_thr: 0.5380 loss_db: 0.1522 2022/10/26 02:30:53 - mmengine - INFO - Epoch(train) [497][55/63] lr: 2.1866e-03 eta: 10:04:55 time: 0.5183 data_time: 0.0183 memory: 16131 loss: 1.5447 loss_prob: 0.8795 loss_thr: 0.5203 loss_db: 0.1450 2022/10/26 02:30:56 - mmengine - INFO - Epoch(train) [497][60/63] lr: 2.1866e-03 eta: 10:04:42 time: 0.5026 data_time: 0.0108 memory: 16131 loss: 1.5462 loss_prob: 0.8908 loss_thr: 0.5112 loss_db: 0.1442 2022/10/26 02:30:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:31:02 - mmengine - INFO - Epoch(train) [498][5/63] lr: 2.1838e-03 eta: 10:04:42 time: 0.6906 data_time: 0.2165 memory: 16131 loss: 1.5627 loss_prob: 0.8760 loss_thr: 0.5417 loss_db: 0.1450 2022/10/26 02:31:05 - mmengine - INFO - Epoch(train) [498][10/63] lr: 2.1838e-03 eta: 10:04:28 time: 0.7739 data_time: 0.2150 memory: 16131 loss: 1.5871 loss_prob: 0.9038 loss_thr: 0.5312 loss_db: 0.1522 2022/10/26 02:31:08 - mmengine - INFO - Epoch(train) [498][15/63] lr: 2.1838e-03 eta: 10:04:28 time: 0.5558 data_time: 0.0058 memory: 16131 loss: 1.5589 loss_prob: 0.8795 loss_thr: 0.5335 loss_db: 0.1459 2022/10/26 02:31:10 - mmengine - INFO - Epoch(train) [498][20/63] lr: 2.1838e-03 eta: 10:04:15 time: 0.4851 data_time: 0.0072 memory: 16131 loss: 1.6849 loss_prob: 0.9750 loss_thr: 0.5563 loss_db: 0.1536 2022/10/26 02:31:13 - mmengine - INFO - Epoch(train) [498][25/63] lr: 2.1838e-03 eta: 10:04:15 time: 0.5326 data_time: 0.0340 memory: 16131 loss: 1.6716 loss_prob: 0.9555 loss_thr: 0.5613 loss_db: 0.1548 2022/10/26 02:31:15 - mmengine - INFO - Epoch(train) [498][30/63] lr: 2.1838e-03 eta: 10:04:03 time: 0.5434 data_time: 0.0324 memory: 16131 loss: 1.6025 loss_prob: 0.9006 loss_thr: 0.5488 loss_db: 0.1531 2022/10/26 02:31:18 - mmengine - INFO - Epoch(train) [498][35/63] lr: 2.1838e-03 eta: 10:04:03 time: 0.5214 data_time: 0.0054 memory: 16131 loss: 1.6470 loss_prob: 0.9494 loss_thr: 0.5413 loss_db: 0.1563 2022/10/26 02:31:20 - mmengine - INFO - Epoch(train) [498][40/63] lr: 2.1838e-03 eta: 10:03:50 time: 0.5085 data_time: 0.0042 memory: 16131 loss: 1.7539 loss_prob: 1.0443 loss_thr: 0.5393 loss_db: 0.1703 2022/10/26 02:31:23 - mmengine - INFO - Epoch(train) [498][45/63] lr: 2.1838e-03 eta: 10:03:50 time: 0.4882 data_time: 0.0046 memory: 16131 loss: 2.1545 loss_prob: 1.3653 loss_thr: 0.5708 loss_db: 0.2184 2022/10/26 02:31:26 - mmengine - INFO - Epoch(train) [498][50/63] lr: 2.1838e-03 eta: 10:03:38 time: 0.5205 data_time: 0.0203 memory: 16131 loss: 2.0959 loss_prob: 1.3277 loss_thr: 0.5684 loss_db: 0.1999 2022/10/26 02:31:28 - mmengine - INFO - Epoch(train) [498][55/63] lr: 2.1838e-03 eta: 10:03:38 time: 0.5159 data_time: 0.0211 memory: 16131 loss: 1.8937 loss_prob: 1.1502 loss_thr: 0.5716 loss_db: 0.1718 2022/10/26 02:31:31 - mmengine - INFO - Epoch(train) [498][60/63] lr: 2.1838e-03 eta: 10:03:25 time: 0.4900 data_time: 0.0054 memory: 16131 loss: 1.8919 loss_prob: 1.1291 loss_thr: 0.5880 loss_db: 0.1749 2022/10/26 02:31:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:31:37 - mmengine - INFO - Epoch(train) [499][5/63] lr: 2.1810e-03 eta: 10:03:25 time: 0.7355 data_time: 0.1994 memory: 16131 loss: 1.6821 loss_prob: 0.9664 loss_thr: 0.5606 loss_db: 0.1551 2022/10/26 02:31:39 - mmengine - INFO - Epoch(train) [499][10/63] lr: 2.1810e-03 eta: 10:03:10 time: 0.7621 data_time: 0.1995 memory: 16131 loss: 1.8518 loss_prob: 1.0754 loss_thr: 0.6018 loss_db: 0.1746 2022/10/26 02:31:42 - mmengine - INFO - Epoch(train) [499][15/63] lr: 2.1810e-03 eta: 10:03:10 time: 0.5009 data_time: 0.0068 memory: 16131 loss: 1.8375 loss_prob: 1.0848 loss_thr: 0.5747 loss_db: 0.1780 2022/10/26 02:31:45 - mmengine - INFO - Epoch(train) [499][20/63] lr: 2.1810e-03 eta: 10:02:58 time: 0.5285 data_time: 0.0073 memory: 16131 loss: 1.6053 loss_prob: 0.9229 loss_thr: 0.5320 loss_db: 0.1503 2022/10/26 02:31:47 - mmengine - INFO - Epoch(train) [499][25/63] lr: 2.1810e-03 eta: 10:02:58 time: 0.5509 data_time: 0.0268 memory: 16131 loss: 1.7005 loss_prob: 0.9724 loss_thr: 0.5701 loss_db: 0.1581 2022/10/26 02:31:50 - mmengine - INFO - Epoch(train) [499][30/63] lr: 2.1810e-03 eta: 10:02:46 time: 0.5404 data_time: 0.0307 memory: 16131 loss: 1.7256 loss_prob: 0.9958 loss_thr: 0.5648 loss_db: 0.1650 2022/10/26 02:31:53 - mmengine - INFO - Epoch(train) [499][35/63] lr: 2.1810e-03 eta: 10:02:46 time: 0.5122 data_time: 0.0140 memory: 16131 loss: 1.6132 loss_prob: 0.9166 loss_thr: 0.5386 loss_db: 0.1580 2022/10/26 02:31:56 - mmengine - INFO - Epoch(train) [499][40/63] lr: 2.1810e-03 eta: 10:02:34 time: 0.5386 data_time: 0.0100 memory: 16131 loss: 1.5448 loss_prob: 0.8764 loss_thr: 0.5210 loss_db: 0.1474 2022/10/26 02:31:59 - mmengine - INFO - Epoch(train) [499][45/63] lr: 2.1810e-03 eta: 10:02:34 time: 0.6250 data_time: 0.0064 memory: 16131 loss: 1.6587 loss_prob: 0.9572 loss_thr: 0.5480 loss_db: 0.1534 2022/10/26 02:32:02 - mmengine - INFO - Epoch(train) [499][50/63] lr: 2.1810e-03 eta: 10:02:23 time: 0.6469 data_time: 0.0291 memory: 16131 loss: 1.7269 loss_prob: 0.9892 loss_thr: 0.5786 loss_db: 0.1592 2022/10/26 02:32:05 - mmengine - INFO - Epoch(train) [499][55/63] lr: 2.1810e-03 eta: 10:02:23 time: 0.5729 data_time: 0.0303 memory: 16131 loss: 1.7529 loss_prob: 1.0012 loss_thr: 0.5864 loss_db: 0.1653 2022/10/26 02:32:07 - mmengine - INFO - Epoch(train) [499][60/63] lr: 2.1810e-03 eta: 10:02:11 time: 0.5205 data_time: 0.0078 memory: 16131 loss: 1.7307 loss_prob: 0.9936 loss_thr: 0.5714 loss_db: 0.1657 2022/10/26 02:32:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:32:13 - mmengine - INFO - Epoch(train) [500][5/63] lr: 2.1782e-03 eta: 10:02:11 time: 0.6833 data_time: 0.1997 memory: 16131 loss: 1.6430 loss_prob: 0.9387 loss_thr: 0.5498 loss_db: 0.1546 2022/10/26 02:32:16 - mmengine - INFO - Epoch(train) [500][10/63] lr: 2.1782e-03 eta: 10:01:55 time: 0.7157 data_time: 0.1981 memory: 16131 loss: 1.6286 loss_prob: 0.9326 loss_thr: 0.5408 loss_db: 0.1552 2022/10/26 02:32:18 - mmengine - INFO - Epoch(train) [500][15/63] lr: 2.1782e-03 eta: 10:01:55 time: 0.5021 data_time: 0.0054 memory: 16131 loss: 1.5442 loss_prob: 0.8669 loss_thr: 0.5309 loss_db: 0.1464 2022/10/26 02:32:21 - mmengine - INFO - Epoch(train) [500][20/63] lr: 2.1782e-03 eta: 10:01:42 time: 0.4959 data_time: 0.0063 memory: 16131 loss: 1.4875 loss_prob: 0.8343 loss_thr: 0.5118 loss_db: 0.1414 2022/10/26 02:32:23 - mmengine - INFO - Epoch(train) [500][25/63] lr: 2.1782e-03 eta: 10:01:42 time: 0.5082 data_time: 0.0134 memory: 16131 loss: 1.5253 loss_prob: 0.8632 loss_thr: 0.5202 loss_db: 0.1419 2022/10/26 02:32:26 - mmengine - INFO - Epoch(train) [500][30/63] lr: 2.1782e-03 eta: 10:01:30 time: 0.5179 data_time: 0.0326 memory: 16131 loss: 1.8742 loss_prob: 1.1276 loss_thr: 0.5689 loss_db: 0.1777 2022/10/26 02:32:28 - mmengine - INFO - Epoch(train) [500][35/63] lr: 2.1782e-03 eta: 10:01:30 time: 0.4987 data_time: 0.0257 memory: 16131 loss: 1.9338 loss_prob: 1.1749 loss_thr: 0.5728 loss_db: 0.1861 2022/10/26 02:32:31 - mmengine - INFO - Epoch(train) [500][40/63] lr: 2.1782e-03 eta: 10:01:17 time: 0.5064 data_time: 0.0055 memory: 16131 loss: 1.5505 loss_prob: 0.8864 loss_thr: 0.5178 loss_db: 0.1463 2022/10/26 02:32:33 - mmengine - INFO - Epoch(train) [500][45/63] lr: 2.1782e-03 eta: 10:01:17 time: 0.5061 data_time: 0.0043 memory: 16131 loss: 1.6879 loss_prob: 0.9731 loss_thr: 0.5518 loss_db: 0.1630 2022/10/26 02:32:36 - mmengine - INFO - Epoch(train) [500][50/63] lr: 2.1782e-03 eta: 10:01:05 time: 0.5119 data_time: 0.0201 memory: 16131 loss: 1.7555 loss_prob: 1.0228 loss_thr: 0.5659 loss_db: 0.1669 2022/10/26 02:32:39 - mmengine - INFO - Epoch(train) [500][55/63] lr: 2.1782e-03 eta: 10:01:05 time: 0.5886 data_time: 0.0236 memory: 16131 loss: 1.4973 loss_prob: 0.8445 loss_thr: 0.5171 loss_db: 0.1357 2022/10/26 02:32:42 - mmengine - INFO - Epoch(train) [500][60/63] lr: 2.1782e-03 eta: 10:00:53 time: 0.5791 data_time: 0.0106 memory: 16131 loss: 1.4808 loss_prob: 0.8178 loss_thr: 0.5271 loss_db: 0.1359 2022/10/26 02:32:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:32:43 - mmengine - INFO - Saving checkpoint at 500 epochs 2022/10/26 02:32:50 - mmengine - INFO - Epoch(val) [500][5/32] eta: 10:00:53 time: 0.5239 data_time: 0.0703 memory: 16131 2022/10/26 02:32:53 - mmengine - INFO - Epoch(val) [500][10/32] eta: 0:00:13 time: 0.5914 data_time: 0.0945 memory: 15724 2022/10/26 02:32:55 - mmengine - INFO - Epoch(val) [500][15/32] eta: 0:00:13 time: 0.5437 data_time: 0.0443 memory: 15724 2022/10/26 02:32:58 - mmengine - INFO - Epoch(val) [500][20/32] eta: 0:00:06 time: 0.5225 data_time: 0.0357 memory: 15724 2022/10/26 02:33:01 - mmengine - INFO - Epoch(val) [500][25/32] eta: 0:00:06 time: 0.5496 data_time: 0.0460 memory: 15724 2022/10/26 02:33:03 - mmengine - INFO - Epoch(val) [500][30/32] eta: 0:00:01 time: 0.5380 data_time: 0.0301 memory: 15724 2022/10/26 02:33:04 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8190, precision: 0.6988, hmean: 0.7542 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8190, precision: 0.7676, hmean: 0.7925 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8166, precision: 0.8197, hmean: 0.8181 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8026, precision: 0.8637, hmean: 0.8320 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7487, precision: 0.9046, hmean: 0.8193 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4506, precision: 0.9532, hmean: 0.6120 2022/10/26 02:33:04 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0014, precision: 1.0000, hmean: 0.0029 2022/10/26 02:33:04 - mmengine - INFO - Epoch(val) [500][32/32] icdar/precision: 0.8637 icdar/recall: 0.8026 icdar/hmean: 0.8320 2022/10/26 02:33:08 - mmengine - INFO - Epoch(train) [501][5/63] lr: 2.1754e-03 eta: 0:00:01 time: 0.6717 data_time: 0.1756 memory: 16131 loss: 1.5954 loss_prob: 0.8970 loss_thr: 0.5513 loss_db: 0.1471 2022/10/26 02:33:11 - mmengine - INFO - Epoch(train) [501][10/63] lr: 2.1754e-03 eta: 10:00:38 time: 0.6949 data_time: 0.1872 memory: 16131 loss: 1.6227 loss_prob: 0.9051 loss_thr: 0.5713 loss_db: 0.1463 2022/10/26 02:33:14 - mmengine - INFO - Epoch(train) [501][15/63] lr: 2.1754e-03 eta: 10:00:38 time: 0.5484 data_time: 0.0174 memory: 16131 loss: 1.6523 loss_prob: 0.9332 loss_thr: 0.5699 loss_db: 0.1492 2022/10/26 02:33:16 - mmengine - INFO - Epoch(train) [501][20/63] lr: 2.1754e-03 eta: 10:00:26 time: 0.5371 data_time: 0.0080 memory: 16131 loss: 1.6091 loss_prob: 0.9306 loss_thr: 0.5262 loss_db: 0.1523 2022/10/26 02:33:19 - mmengine - INFO - Epoch(train) [501][25/63] lr: 2.1754e-03 eta: 10:00:26 time: 0.5015 data_time: 0.0107 memory: 16131 loss: 1.5605 loss_prob: 0.8856 loss_thr: 0.5253 loss_db: 0.1496 2022/10/26 02:33:21 - mmengine - INFO - Epoch(train) [501][30/63] lr: 2.1754e-03 eta: 10:00:13 time: 0.5227 data_time: 0.0321 memory: 16131 loss: 1.5319 loss_prob: 0.8587 loss_thr: 0.5311 loss_db: 0.1421 2022/10/26 02:33:24 - mmengine - INFO - Epoch(train) [501][35/63] lr: 2.1754e-03 eta: 10:00:13 time: 0.5215 data_time: 0.0290 memory: 16131 loss: 1.5241 loss_prob: 0.8423 loss_thr: 0.5410 loss_db: 0.1408 2022/10/26 02:33:26 - mmengine - INFO - Epoch(train) [501][40/63] lr: 2.1754e-03 eta: 10:00:01 time: 0.5065 data_time: 0.0071 memory: 16131 loss: 1.5668 loss_prob: 0.8707 loss_thr: 0.5465 loss_db: 0.1495 2022/10/26 02:33:29 - mmengine - INFO - Epoch(train) [501][45/63] lr: 2.1754e-03 eta: 10:00:01 time: 0.5088 data_time: 0.0089 memory: 16131 loss: 1.5708 loss_prob: 0.8955 loss_thr: 0.5265 loss_db: 0.1489 2022/10/26 02:33:32 - mmengine - INFO - Epoch(train) [501][50/63] lr: 2.1754e-03 eta: 9:59:48 time: 0.5201 data_time: 0.0170 memory: 16131 loss: 1.6206 loss_prob: 0.9380 loss_thr: 0.5326 loss_db: 0.1500 2022/10/26 02:33:35 - mmengine - INFO - Epoch(train) [501][55/63] lr: 2.1754e-03 eta: 9:59:48 time: 0.5597 data_time: 0.0218 memory: 16131 loss: 1.6291 loss_prob: 0.9346 loss_thr: 0.5416 loss_db: 0.1528 2022/10/26 02:33:37 - mmengine - INFO - Epoch(train) [501][60/63] lr: 2.1754e-03 eta: 9:59:37 time: 0.5493 data_time: 0.0111 memory: 16131 loss: 1.4933 loss_prob: 0.8373 loss_thr: 0.5158 loss_db: 0.1401 2022/10/26 02:33:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:33:44 - mmengine - INFO - Epoch(train) [502][5/63] lr: 2.1726e-03 eta: 9:59:37 time: 0.7367 data_time: 0.1937 memory: 16131 loss: 1.4149 loss_prob: 0.7819 loss_thr: 0.5030 loss_db: 0.1301 2022/10/26 02:33:46 - mmengine - INFO - Epoch(train) [502][10/63] lr: 2.1726e-03 eta: 9:59:22 time: 0.7855 data_time: 0.1918 memory: 16131 loss: 1.5097 loss_prob: 0.8406 loss_thr: 0.5290 loss_db: 0.1402 2022/10/26 02:33:49 - mmengine - INFO - Epoch(train) [502][15/63] lr: 2.1726e-03 eta: 9:59:22 time: 0.5609 data_time: 0.0047 memory: 16131 loss: 1.5121 loss_prob: 0.8506 loss_thr: 0.5206 loss_db: 0.1409 2022/10/26 02:33:53 - mmengine - INFO - Epoch(train) [502][20/63] lr: 2.1726e-03 eta: 9:59:11 time: 0.6290 data_time: 0.0090 memory: 16131 loss: 1.4225 loss_prob: 0.7886 loss_thr: 0.5017 loss_db: 0.1321 2022/10/26 02:33:56 - mmengine - INFO - Epoch(train) [502][25/63] lr: 2.1726e-03 eta: 9:59:11 time: 0.6502 data_time: 0.0142 memory: 16131 loss: 1.4802 loss_prob: 0.8342 loss_thr: 0.5083 loss_db: 0.1377 2022/10/26 02:33:59 - mmengine - INFO - Epoch(train) [502][30/63] lr: 2.1726e-03 eta: 9:59:00 time: 0.5979 data_time: 0.0332 memory: 16131 loss: 1.5630 loss_prob: 0.8890 loss_thr: 0.5270 loss_db: 0.1470 2022/10/26 02:34:01 - mmengine - INFO - Epoch(train) [502][35/63] lr: 2.1726e-03 eta: 9:59:00 time: 0.5408 data_time: 0.0277 memory: 16131 loss: 1.4683 loss_prob: 0.8154 loss_thr: 0.5127 loss_db: 0.1402 2022/10/26 02:34:04 - mmengine - INFO - Epoch(train) [502][40/63] lr: 2.1726e-03 eta: 9:58:48 time: 0.5145 data_time: 0.0055 memory: 16131 loss: 1.3993 loss_prob: 0.7700 loss_thr: 0.4984 loss_db: 0.1309 2022/10/26 02:34:06 - mmengine - INFO - Epoch(train) [502][45/63] lr: 2.1726e-03 eta: 9:58:48 time: 0.5170 data_time: 0.0081 memory: 16131 loss: 1.4431 loss_prob: 0.7980 loss_thr: 0.5133 loss_db: 0.1317 2022/10/26 02:34:09 - mmengine - INFO - Epoch(train) [502][50/63] lr: 2.1726e-03 eta: 9:58:35 time: 0.5262 data_time: 0.0192 memory: 16131 loss: 1.4610 loss_prob: 0.8082 loss_thr: 0.5159 loss_db: 0.1369 2022/10/26 02:34:12 - mmengine - INFO - Epoch(train) [502][55/63] lr: 2.1726e-03 eta: 9:58:35 time: 0.5460 data_time: 0.0209 memory: 16131 loss: 1.4445 loss_prob: 0.7939 loss_thr: 0.5138 loss_db: 0.1368 2022/10/26 02:34:14 - mmengine - INFO - Epoch(train) [502][60/63] lr: 2.1726e-03 eta: 9:58:23 time: 0.5197 data_time: 0.0091 memory: 16131 loss: 1.5346 loss_prob: 0.8567 loss_thr: 0.5374 loss_db: 0.1405 2022/10/26 02:34:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:34:20 - mmengine - INFO - Epoch(train) [503][5/63] lr: 2.1698e-03 eta: 9:58:23 time: 0.6737 data_time: 0.1915 memory: 16131 loss: 1.7160 loss_prob: 1.0034 loss_thr: 0.5491 loss_db: 0.1635 2022/10/26 02:34:23 - mmengine - INFO - Epoch(train) [503][10/63] lr: 2.1698e-03 eta: 9:58:08 time: 0.7166 data_time: 0.1929 memory: 16131 loss: 1.6598 loss_prob: 0.9442 loss_thr: 0.5559 loss_db: 0.1597 2022/10/26 02:34:25 - mmengine - INFO - Epoch(train) [503][15/63] lr: 2.1698e-03 eta: 9:58:08 time: 0.5002 data_time: 0.0125 memory: 16131 loss: 1.6685 loss_prob: 0.9509 loss_thr: 0.5595 loss_db: 0.1581 2022/10/26 02:34:28 - mmengine - INFO - Epoch(train) [503][20/63] lr: 2.1698e-03 eta: 9:57:55 time: 0.5106 data_time: 0.0054 memory: 16131 loss: 1.5535 loss_prob: 0.8763 loss_thr: 0.5318 loss_db: 0.1454 2022/10/26 02:34:30 - mmengine - INFO - Epoch(train) [503][25/63] lr: 2.1698e-03 eta: 9:57:55 time: 0.5435 data_time: 0.0247 memory: 16131 loss: 1.5266 loss_prob: 0.8509 loss_thr: 0.5301 loss_db: 0.1456 2022/10/26 02:34:33 - mmengine - INFO - Epoch(train) [503][30/63] lr: 2.1698e-03 eta: 9:57:43 time: 0.5031 data_time: 0.0246 memory: 16131 loss: 1.5517 loss_prob: 0.8799 loss_thr: 0.5239 loss_db: 0.1479 2022/10/26 02:34:35 - mmengine - INFO - Epoch(train) [503][35/63] lr: 2.1698e-03 eta: 9:57:43 time: 0.5006 data_time: 0.0135 memory: 16131 loss: 1.6664 loss_prob: 0.9700 loss_thr: 0.5326 loss_db: 0.1638 2022/10/26 02:34:38 - mmengine - INFO - Epoch(train) [503][40/63] lr: 2.1698e-03 eta: 9:57:31 time: 0.5422 data_time: 0.0130 memory: 16131 loss: 1.6394 loss_prob: 0.9461 loss_thr: 0.5325 loss_db: 0.1609 2022/10/26 02:34:41 - mmengine - INFO - Epoch(train) [503][45/63] lr: 2.1698e-03 eta: 9:57:31 time: 0.5210 data_time: 0.0055 memory: 16131 loss: 1.6815 loss_prob: 0.9699 loss_thr: 0.5506 loss_db: 0.1610 2022/10/26 02:34:43 - mmengine - INFO - Epoch(train) [503][50/63] lr: 2.1698e-03 eta: 9:57:19 time: 0.5196 data_time: 0.0186 memory: 16131 loss: 1.7551 loss_prob: 1.0245 loss_thr: 0.5618 loss_db: 0.1688 2022/10/26 02:34:46 - mmengine - INFO - Epoch(train) [503][55/63] lr: 2.1698e-03 eta: 9:57:19 time: 0.5563 data_time: 0.0212 memory: 16131 loss: 1.5680 loss_prob: 0.8910 loss_thr: 0.5292 loss_db: 0.1478 2022/10/26 02:34:49 - mmengine - INFO - Epoch(train) [503][60/63] lr: 2.1698e-03 eta: 9:57:07 time: 0.5400 data_time: 0.0117 memory: 16131 loss: 1.5372 loss_prob: 0.8546 loss_thr: 0.5414 loss_db: 0.1412 2022/10/26 02:34:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:34:55 - mmengine - INFO - Epoch(train) [504][5/63] lr: 2.1670e-03 eta: 9:57:07 time: 0.6798 data_time: 0.1800 memory: 16131 loss: 1.3848 loss_prob: 0.7570 loss_thr: 0.4956 loss_db: 0.1321 2022/10/26 02:34:57 - mmengine - INFO - Epoch(train) [504][10/63] lr: 2.1670e-03 eta: 9:56:51 time: 0.7090 data_time: 0.1872 memory: 16131 loss: 1.3816 loss_prob: 0.7526 loss_thr: 0.4998 loss_db: 0.1291 2022/10/26 02:35:00 - mmengine - INFO - Epoch(train) [504][15/63] lr: 2.1670e-03 eta: 9:56:51 time: 0.5119 data_time: 0.0140 memory: 16131 loss: 1.5748 loss_prob: 0.9066 loss_thr: 0.5285 loss_db: 0.1396 2022/10/26 02:35:02 - mmengine - INFO - Epoch(train) [504][20/63] lr: 2.1670e-03 eta: 9:56:39 time: 0.5197 data_time: 0.0090 memory: 16131 loss: 1.6081 loss_prob: 0.9322 loss_thr: 0.5313 loss_db: 0.1445 2022/10/26 02:35:05 - mmengine - INFO - Epoch(train) [504][25/63] lr: 2.1670e-03 eta: 9:56:39 time: 0.5744 data_time: 0.0294 memory: 16131 loss: 1.5434 loss_prob: 0.8859 loss_thr: 0.5104 loss_db: 0.1471 2022/10/26 02:35:09 - mmengine - INFO - Epoch(train) [504][30/63] lr: 2.1670e-03 eta: 9:56:28 time: 0.6169 data_time: 0.0312 memory: 16131 loss: 1.5374 loss_prob: 0.8760 loss_thr: 0.5172 loss_db: 0.1443 2022/10/26 02:35:14 - mmengine - INFO - Epoch(train) [504][35/63] lr: 2.1670e-03 eta: 9:56:28 time: 0.8565 data_time: 0.0198 memory: 16131 loss: 1.4300 loss_prob: 0.7804 loss_thr: 0.5204 loss_db: 0.1292 2022/10/26 02:35:17 - mmengine - INFO - Epoch(train) [504][40/63] lr: 2.1670e-03 eta: 9:56:20 time: 0.8236 data_time: 0.0178 memory: 16131 loss: 1.5025 loss_prob: 0.8378 loss_thr: 0.5258 loss_db: 0.1389 2022/10/26 02:35:19 - mmengine - INFO - Epoch(train) [504][45/63] lr: 2.1670e-03 eta: 9:56:20 time: 0.5253 data_time: 0.0084 memory: 16131 loss: 1.4616 loss_prob: 0.8171 loss_thr: 0.5077 loss_db: 0.1368 2022/10/26 02:35:22 - mmengine - INFO - Epoch(train) [504][50/63] lr: 2.1670e-03 eta: 9:56:08 time: 0.5165 data_time: 0.0165 memory: 16131 loss: 1.5007 loss_prob: 0.8439 loss_thr: 0.5136 loss_db: 0.1431 2022/10/26 02:35:25 - mmengine - INFO - Epoch(train) [504][55/63] lr: 2.1670e-03 eta: 9:56:08 time: 0.5215 data_time: 0.0185 memory: 16131 loss: 1.6479 loss_prob: 0.9446 loss_thr: 0.5475 loss_db: 0.1558 2022/10/26 02:35:27 - mmengine - INFO - Epoch(train) [504][60/63] lr: 2.1670e-03 eta: 9:55:55 time: 0.5111 data_time: 0.0105 memory: 16131 loss: 1.5394 loss_prob: 0.8728 loss_thr: 0.5240 loss_db: 0.1426 2022/10/26 02:35:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:35:33 - mmengine - INFO - Epoch(train) [505][5/63] lr: 2.1642e-03 eta: 9:55:55 time: 0.6797 data_time: 0.1527 memory: 16131 loss: 1.5274 loss_prob: 0.8611 loss_thr: 0.5111 loss_db: 0.1552 2022/10/26 02:35:36 - mmengine - INFO - Epoch(train) [505][10/63] lr: 2.1642e-03 eta: 9:55:40 time: 0.7253 data_time: 0.1671 memory: 16131 loss: 1.6072 loss_prob: 0.9153 loss_thr: 0.5293 loss_db: 0.1626 2022/10/26 02:35:39 - mmengine - INFO - Epoch(train) [505][15/63] lr: 2.1642e-03 eta: 9:55:40 time: 0.5680 data_time: 0.0209 memory: 16131 loss: 1.5168 loss_prob: 0.8599 loss_thr: 0.5156 loss_db: 0.1413 2022/10/26 02:35:41 - mmengine - INFO - Epoch(train) [505][20/63] lr: 2.1642e-03 eta: 9:55:28 time: 0.5407 data_time: 0.0095 memory: 16131 loss: 1.5498 loss_prob: 0.8830 loss_thr: 0.5204 loss_db: 0.1464 2022/10/26 02:35:43 - mmengine - INFO - Epoch(train) [505][25/63] lr: 2.1642e-03 eta: 9:55:28 time: 0.4853 data_time: 0.0109 memory: 16131 loss: 1.4608 loss_prob: 0.8117 loss_thr: 0.5110 loss_db: 0.1381 2022/10/26 02:35:46 - mmengine - INFO - Epoch(train) [505][30/63] lr: 2.1642e-03 eta: 9:55:16 time: 0.5108 data_time: 0.0316 memory: 16131 loss: 1.4672 loss_prob: 0.8299 loss_thr: 0.4962 loss_db: 0.1410 2022/10/26 02:35:49 - mmengine - INFO - Epoch(train) [505][35/63] lr: 2.1642e-03 eta: 9:55:16 time: 0.5125 data_time: 0.0310 memory: 16131 loss: 1.4996 loss_prob: 0.8470 loss_thr: 0.5086 loss_db: 0.1441 2022/10/26 02:35:51 - mmengine - INFO - Epoch(train) [505][40/63] lr: 2.1642e-03 eta: 9:55:03 time: 0.4918 data_time: 0.0070 memory: 16131 loss: 1.5171 loss_prob: 0.8411 loss_thr: 0.5337 loss_db: 0.1423 2022/10/26 02:35:53 - mmengine - INFO - Epoch(train) [505][45/63] lr: 2.1642e-03 eta: 9:55:03 time: 0.4873 data_time: 0.0050 memory: 16131 loss: 1.5228 loss_prob: 0.8587 loss_thr: 0.5236 loss_db: 0.1406 2022/10/26 02:35:56 - mmengine - INFO - Epoch(train) [505][50/63] lr: 2.1642e-03 eta: 9:54:51 time: 0.4874 data_time: 0.0102 memory: 16131 loss: 1.4496 loss_prob: 0.8109 loss_thr: 0.5054 loss_db: 0.1333 2022/10/26 02:35:58 - mmengine - INFO - Epoch(train) [505][55/63] lr: 2.1642e-03 eta: 9:54:51 time: 0.4972 data_time: 0.0209 memory: 16131 loss: 1.3732 loss_prob: 0.7594 loss_thr: 0.4852 loss_db: 0.1285 2022/10/26 02:36:01 - mmengine - INFO - Epoch(train) [505][60/63] lr: 2.1642e-03 eta: 9:54:38 time: 0.4980 data_time: 0.0173 memory: 16131 loss: 1.3109 loss_prob: 0.7235 loss_thr: 0.4654 loss_db: 0.1221 2022/10/26 02:36:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:36:07 - mmengine - INFO - Epoch(train) [506][5/63] lr: 2.1614e-03 eta: 9:54:38 time: 0.7220 data_time: 0.2114 memory: 16131 loss: 1.3037 loss_prob: 0.7093 loss_thr: 0.4745 loss_db: 0.1199 2022/10/26 02:36:10 - mmengine - INFO - Epoch(train) [506][10/63] lr: 2.1614e-03 eta: 9:54:23 time: 0.7526 data_time: 0.2196 memory: 16131 loss: 1.3803 loss_prob: 0.7759 loss_thr: 0.4747 loss_db: 0.1297 2022/10/26 02:36:12 - mmengine - INFO - Epoch(train) [506][15/63] lr: 2.1614e-03 eta: 9:54:23 time: 0.5189 data_time: 0.0131 memory: 16131 loss: 1.4285 loss_prob: 0.8076 loss_thr: 0.4880 loss_db: 0.1328 2022/10/26 02:36:15 - mmengine - INFO - Epoch(train) [506][20/63] lr: 2.1614e-03 eta: 9:54:11 time: 0.5385 data_time: 0.0061 memory: 16131 loss: 1.5898 loss_prob: 0.9082 loss_thr: 0.5343 loss_db: 0.1474 2022/10/26 02:36:18 - mmengine - INFO - Epoch(train) [506][25/63] lr: 2.1614e-03 eta: 9:54:11 time: 0.5350 data_time: 0.0268 memory: 16131 loss: 1.6489 loss_prob: 0.9372 loss_thr: 0.5590 loss_db: 0.1528 2022/10/26 02:36:20 - mmengine - INFO - Epoch(train) [506][30/63] lr: 2.1614e-03 eta: 9:53:59 time: 0.5429 data_time: 0.0355 memory: 16131 loss: 1.6333 loss_prob: 0.9330 loss_thr: 0.5468 loss_db: 0.1534 2022/10/26 02:36:23 - mmengine - INFO - Epoch(train) [506][35/63] lr: 2.1614e-03 eta: 9:53:59 time: 0.5248 data_time: 0.0155 memory: 16131 loss: 1.6936 loss_prob: 0.9979 loss_thr: 0.5353 loss_db: 0.1604 2022/10/26 02:36:25 - mmengine - INFO - Epoch(train) [506][40/63] lr: 2.1614e-03 eta: 9:53:47 time: 0.4968 data_time: 0.0085 memory: 16131 loss: 1.6500 loss_prob: 0.9689 loss_thr: 0.5194 loss_db: 0.1618 2022/10/26 02:36:28 - mmengine - INFO - Epoch(train) [506][45/63] lr: 2.1614e-03 eta: 9:53:47 time: 0.5322 data_time: 0.0074 memory: 16131 loss: 1.6032 loss_prob: 0.9266 loss_thr: 0.5199 loss_db: 0.1567 2022/10/26 02:36:31 - mmengine - INFO - Epoch(train) [506][50/63] lr: 2.1614e-03 eta: 9:53:35 time: 0.5601 data_time: 0.0158 memory: 16131 loss: 1.7650 loss_prob: 1.0624 loss_thr: 0.5338 loss_db: 0.1688 2022/10/26 02:36:34 - mmengine - INFO - Epoch(train) [506][55/63] lr: 2.1614e-03 eta: 9:53:35 time: 0.5319 data_time: 0.0199 memory: 16131 loss: 2.0925 loss_prob: 1.2989 loss_thr: 0.5890 loss_db: 0.2046 2022/10/26 02:36:36 - mmengine - INFO - Epoch(train) [506][60/63] lr: 2.1614e-03 eta: 9:53:23 time: 0.5273 data_time: 0.0087 memory: 16131 loss: 2.0255 loss_prob: 1.2187 loss_thr: 0.6072 loss_db: 0.1996 2022/10/26 02:36:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:36:43 - mmengine - INFO - Epoch(train) [507][5/63] lr: 2.1586e-03 eta: 9:53:23 time: 0.8160 data_time: 0.2245 memory: 16131 loss: 1.6877 loss_prob: 0.9788 loss_thr: 0.5442 loss_db: 0.1647 2022/10/26 02:36:46 - mmengine - INFO - Epoch(train) [507][10/63] lr: 2.1586e-03 eta: 9:53:09 time: 0.8132 data_time: 0.2252 memory: 16131 loss: 1.7150 loss_prob: 1.0085 loss_thr: 0.5444 loss_db: 0.1621 2022/10/26 02:36:48 - mmengine - INFO - Epoch(train) [507][15/63] lr: 2.1586e-03 eta: 9:53:09 time: 0.5213 data_time: 0.0083 memory: 16131 loss: 1.7193 loss_prob: 1.0071 loss_thr: 0.5522 loss_db: 0.1600 2022/10/26 02:36:51 - mmengine - INFO - Epoch(train) [507][20/63] lr: 2.1586e-03 eta: 9:52:57 time: 0.5044 data_time: 0.0092 memory: 16131 loss: 1.6277 loss_prob: 0.9362 loss_thr: 0.5370 loss_db: 0.1544 2022/10/26 02:36:54 - mmengine - INFO - Epoch(train) [507][25/63] lr: 2.1586e-03 eta: 9:52:57 time: 0.5505 data_time: 0.0395 memory: 16131 loss: 1.5581 loss_prob: 0.8860 loss_thr: 0.5252 loss_db: 0.1469 2022/10/26 02:36:57 - mmengine - INFO - Epoch(train) [507][30/63] lr: 2.1586e-03 eta: 9:52:45 time: 0.5475 data_time: 0.0388 memory: 16131 loss: 1.6270 loss_prob: 0.9230 loss_thr: 0.5521 loss_db: 0.1518 2022/10/26 02:36:59 - mmengine - INFO - Epoch(train) [507][35/63] lr: 2.1586e-03 eta: 9:52:45 time: 0.5078 data_time: 0.0057 memory: 16131 loss: 1.6670 loss_prob: 0.9471 loss_thr: 0.5636 loss_db: 0.1563 2022/10/26 02:37:02 - mmengine - INFO - Epoch(train) [507][40/63] lr: 2.1586e-03 eta: 9:52:34 time: 0.5847 data_time: 0.0048 memory: 16131 loss: 1.6817 loss_prob: 0.9820 loss_thr: 0.5403 loss_db: 0.1593 2022/10/26 02:37:05 - mmengine - INFO - Epoch(train) [507][45/63] lr: 2.1586e-03 eta: 9:52:34 time: 0.5891 data_time: 0.0055 memory: 16131 loss: 1.8074 loss_prob: 1.0678 loss_thr: 0.5668 loss_db: 0.1728 2022/10/26 02:37:08 - mmengine - INFO - Epoch(train) [507][50/63] lr: 2.1586e-03 eta: 9:52:22 time: 0.5286 data_time: 0.0242 memory: 16131 loss: 1.6945 loss_prob: 0.9792 loss_thr: 0.5553 loss_db: 0.1599 2022/10/26 02:37:10 - mmengine - INFO - Epoch(train) [507][55/63] lr: 2.1586e-03 eta: 9:52:22 time: 0.5162 data_time: 0.0235 memory: 16131 loss: 1.4844 loss_prob: 0.8475 loss_thr: 0.4962 loss_db: 0.1408 2022/10/26 02:37:14 - mmengine - INFO - Epoch(train) [507][60/63] lr: 2.1586e-03 eta: 9:52:11 time: 0.5943 data_time: 0.0065 memory: 16131 loss: 1.5054 loss_prob: 0.8551 loss_thr: 0.5073 loss_db: 0.1430 2022/10/26 02:37:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:37:25 - mmengine - INFO - Epoch(train) [508][5/63] lr: 2.1558e-03 eta: 9:52:11 time: 1.3549 data_time: 0.2828 memory: 16131 loss: 1.5895 loss_prob: 0.9120 loss_thr: 0.5258 loss_db: 0.1517 2022/10/26 02:37:30 - mmengine - INFO - Epoch(train) [508][10/63] lr: 2.1558e-03 eta: 9:52:04 time: 1.3857 data_time: 0.2798 memory: 16131 loss: 1.6873 loss_prob: 0.9721 loss_thr: 0.5553 loss_db: 0.1599 2022/10/26 02:37:32 - mmengine - INFO - Epoch(train) [508][15/63] lr: 2.1558e-03 eta: 9:52:04 time: 0.7180 data_time: 0.0103 memory: 16131 loss: 1.7279 loss_prob: 0.9974 loss_thr: 0.5716 loss_db: 0.1589 2022/10/26 02:37:35 - mmengine - INFO - Epoch(train) [508][20/63] lr: 2.1558e-03 eta: 9:51:52 time: 0.5237 data_time: 0.0097 memory: 16131 loss: 1.5698 loss_prob: 0.8947 loss_thr: 0.5297 loss_db: 0.1454 2022/10/26 02:37:38 - mmengine - INFO - Epoch(train) [508][25/63] lr: 2.1558e-03 eta: 9:51:52 time: 0.5750 data_time: 0.0167 memory: 16131 loss: 1.5433 loss_prob: 0.8759 loss_thr: 0.5202 loss_db: 0.1472 2022/10/26 02:37:41 - mmengine - INFO - Epoch(train) [508][30/63] lr: 2.1558e-03 eta: 9:51:41 time: 0.5988 data_time: 0.0349 memory: 16131 loss: 1.5738 loss_prob: 0.8971 loss_thr: 0.5288 loss_db: 0.1479 2022/10/26 02:37:44 - mmengine - INFO - Epoch(train) [508][35/63] lr: 2.1558e-03 eta: 9:51:41 time: 0.5420 data_time: 0.0263 memory: 16131 loss: 1.6184 loss_prob: 0.9180 loss_thr: 0.5487 loss_db: 0.1517 2022/10/26 02:37:46 - mmengine - INFO - Epoch(train) [508][40/63] lr: 2.1558e-03 eta: 9:51:29 time: 0.5355 data_time: 0.0104 memory: 16131 loss: 1.5868 loss_prob: 0.8900 loss_thr: 0.5479 loss_db: 0.1489 2022/10/26 02:37:49 - mmengine - INFO - Epoch(train) [508][45/63] lr: 2.1558e-03 eta: 9:51:29 time: 0.5178 data_time: 0.0080 memory: 16131 loss: 1.5207 loss_prob: 0.8556 loss_thr: 0.5229 loss_db: 0.1422 2022/10/26 02:37:51 - mmengine - INFO - Epoch(train) [508][50/63] lr: 2.1558e-03 eta: 9:51:17 time: 0.5187 data_time: 0.0182 memory: 16131 loss: 1.4986 loss_prob: 0.8414 loss_thr: 0.5182 loss_db: 0.1390 2022/10/26 02:37:54 - mmengine - INFO - Epoch(train) [508][55/63] lr: 2.1558e-03 eta: 9:51:17 time: 0.5457 data_time: 0.0191 memory: 16131 loss: 1.5205 loss_prob: 0.8606 loss_thr: 0.5185 loss_db: 0.1414 2022/10/26 02:37:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:37:57 - mmengine - INFO - Epoch(train) [508][60/63] lr: 2.1558e-03 eta: 9:51:05 time: 0.5350 data_time: 0.0066 memory: 16131 loss: 1.4865 loss_prob: 0.8340 loss_thr: 0.5119 loss_db: 0.1407 2022/10/26 02:37:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:38:02 - mmengine - INFO - Epoch(train) [509][5/63] lr: 2.1530e-03 eta: 9:51:05 time: 0.6744 data_time: 0.1814 memory: 16131 loss: 1.4302 loss_prob: 0.8022 loss_thr: 0.4947 loss_db: 0.1333 2022/10/26 02:38:05 - mmengine - INFO - Epoch(train) [509][10/63] lr: 2.1530e-03 eta: 9:50:50 time: 0.7043 data_time: 0.1862 memory: 16131 loss: 1.4744 loss_prob: 0.8380 loss_thr: 0.4998 loss_db: 0.1365 2022/10/26 02:38:08 - mmengine - INFO - Epoch(train) [509][15/63] lr: 2.1530e-03 eta: 9:50:50 time: 0.5471 data_time: 0.0129 memory: 16131 loss: 1.5653 loss_prob: 0.8942 loss_thr: 0.5275 loss_db: 0.1437 2022/10/26 02:38:10 - mmengine - INFO - Epoch(train) [509][20/63] lr: 2.1530e-03 eta: 9:50:38 time: 0.5206 data_time: 0.0108 memory: 16131 loss: 1.6997 loss_prob: 0.9709 loss_thr: 0.5703 loss_db: 0.1585 2022/10/26 02:38:13 - mmengine - INFO - Epoch(train) [509][25/63] lr: 2.1530e-03 eta: 9:50:38 time: 0.5216 data_time: 0.0366 memory: 16131 loss: 1.6353 loss_prob: 0.9140 loss_thr: 0.5683 loss_db: 0.1529 2022/10/26 02:38:16 - mmengine - INFO - Epoch(train) [509][30/63] lr: 2.1530e-03 eta: 9:50:26 time: 0.5557 data_time: 0.0346 memory: 16131 loss: 1.4637 loss_prob: 0.8074 loss_thr: 0.5223 loss_db: 0.1340 2022/10/26 02:38:19 - mmengine - INFO - Epoch(train) [509][35/63] lr: 2.1530e-03 eta: 9:50:26 time: 0.5474 data_time: 0.0168 memory: 16131 loss: 1.3925 loss_prob: 0.7637 loss_thr: 0.4995 loss_db: 0.1293 2022/10/26 02:38:21 - mmengine - INFO - Epoch(train) [509][40/63] lr: 2.1530e-03 eta: 9:50:14 time: 0.5319 data_time: 0.0136 memory: 16131 loss: 1.4539 loss_prob: 0.8013 loss_thr: 0.5158 loss_db: 0.1368 2022/10/26 02:38:24 - mmengine - INFO - Epoch(train) [509][45/63] lr: 2.1530e-03 eta: 9:50:14 time: 0.5228 data_time: 0.0052 memory: 16131 loss: 1.4290 loss_prob: 0.7790 loss_thr: 0.5170 loss_db: 0.1330 2022/10/26 02:38:26 - mmengine - INFO - Epoch(train) [509][50/63] lr: 2.1530e-03 eta: 9:50:02 time: 0.5173 data_time: 0.0187 memory: 16131 loss: 1.3595 loss_prob: 0.7383 loss_thr: 0.4973 loss_db: 0.1238 2022/10/26 02:38:29 - mmengine - INFO - Epoch(train) [509][55/63] lr: 2.1530e-03 eta: 9:50:02 time: 0.5114 data_time: 0.0227 memory: 16131 loss: 1.3591 loss_prob: 0.7517 loss_thr: 0.4835 loss_db: 0.1239 2022/10/26 02:38:32 - mmengine - INFO - Epoch(train) [509][60/63] lr: 2.1530e-03 eta: 9:49:50 time: 0.5189 data_time: 0.0099 memory: 16131 loss: 1.4722 loss_prob: 0.8432 loss_thr: 0.4910 loss_db: 0.1380 2022/10/26 02:38:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:38:37 - mmengine - INFO - Epoch(train) [510][5/63] lr: 2.1502e-03 eta: 9:49:50 time: 0.6802 data_time: 0.2072 memory: 16131 loss: 1.6143 loss_prob: 0.9485 loss_thr: 0.5232 loss_db: 0.1426 2022/10/26 02:38:40 - mmengine - INFO - Epoch(train) [510][10/63] lr: 2.1502e-03 eta: 9:49:35 time: 0.6997 data_time: 0.2073 memory: 16131 loss: 1.7174 loss_prob: 1.0066 loss_thr: 0.5565 loss_db: 0.1543 2022/10/26 02:38:42 - mmengine - INFO - Epoch(train) [510][15/63] lr: 2.1502e-03 eta: 9:49:35 time: 0.5192 data_time: 0.0068 memory: 16131 loss: 1.5328 loss_prob: 0.8519 loss_thr: 0.5331 loss_db: 0.1478 2022/10/26 02:38:45 - mmengine - INFO - Epoch(train) [510][20/63] lr: 2.1502e-03 eta: 9:49:22 time: 0.5211 data_time: 0.0073 memory: 16131 loss: 1.5314 loss_prob: 0.8699 loss_thr: 0.5146 loss_db: 0.1470 2022/10/26 02:38:48 - mmengine - INFO - Epoch(train) [510][25/63] lr: 2.1502e-03 eta: 9:49:22 time: 0.5618 data_time: 0.0411 memory: 16131 loss: 1.5271 loss_prob: 0.8604 loss_thr: 0.5284 loss_db: 0.1383 2022/10/26 02:38:51 - mmengine - INFO - Epoch(train) [510][30/63] lr: 2.1502e-03 eta: 9:49:11 time: 0.5630 data_time: 0.0407 memory: 16131 loss: 1.4702 loss_prob: 0.8232 loss_thr: 0.5079 loss_db: 0.1391 2022/10/26 02:38:53 - mmengine - INFO - Epoch(train) [510][35/63] lr: 2.1502e-03 eta: 9:49:11 time: 0.4966 data_time: 0.0046 memory: 16131 loss: 1.4940 loss_prob: 0.8477 loss_thr: 0.5019 loss_db: 0.1445 2022/10/26 02:38:56 - mmengine - INFO - Epoch(train) [510][40/63] lr: 2.1502e-03 eta: 9:48:58 time: 0.4919 data_time: 0.0050 memory: 16131 loss: 1.5423 loss_prob: 0.8836 loss_thr: 0.5154 loss_db: 0.1434 2022/10/26 02:38:58 - mmengine - INFO - Epoch(train) [510][45/63] lr: 2.1502e-03 eta: 9:48:58 time: 0.5047 data_time: 0.0054 memory: 16131 loss: 1.6111 loss_prob: 0.9427 loss_thr: 0.5183 loss_db: 0.1500 2022/10/26 02:39:01 - mmengine - INFO - Epoch(train) [510][50/63] lr: 2.1502e-03 eta: 9:48:47 time: 0.5336 data_time: 0.0223 memory: 16131 loss: 1.5301 loss_prob: 0.8789 loss_thr: 0.5061 loss_db: 0.1450 2022/10/26 02:39:03 - mmengine - INFO - Epoch(train) [510][55/63] lr: 2.1502e-03 eta: 9:48:47 time: 0.5324 data_time: 0.0222 memory: 16131 loss: 1.4128 loss_prob: 0.7813 loss_thr: 0.4980 loss_db: 0.1335 2022/10/26 02:39:06 - mmengine - INFO - Epoch(train) [510][60/63] lr: 2.1502e-03 eta: 9:48:34 time: 0.4993 data_time: 0.0047 memory: 16131 loss: 1.6540 loss_prob: 0.9506 loss_thr: 0.5509 loss_db: 0.1525 2022/10/26 02:39:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:39:12 - mmengine - INFO - Epoch(train) [511][5/63] lr: 2.1474e-03 eta: 9:48:34 time: 0.6701 data_time: 0.1648 memory: 16131 loss: 1.4728 loss_prob: 0.8089 loss_thr: 0.5276 loss_db: 0.1363 2022/10/26 02:39:14 - mmengine - INFO - Epoch(train) [511][10/63] lr: 2.1474e-03 eta: 9:48:19 time: 0.6910 data_time: 0.1647 memory: 16131 loss: 1.5569 loss_prob: 0.8743 loss_thr: 0.5370 loss_db: 0.1455 2022/10/26 02:39:17 - mmengine - INFO - Epoch(train) [511][15/63] lr: 2.1474e-03 eta: 9:48:19 time: 0.4929 data_time: 0.0048 memory: 16131 loss: 1.5623 loss_prob: 0.8868 loss_thr: 0.5289 loss_db: 0.1466 2022/10/26 02:39:19 - mmengine - INFO - Epoch(train) [511][20/63] lr: 2.1474e-03 eta: 9:48:07 time: 0.5291 data_time: 0.0070 memory: 16131 loss: 1.5477 loss_prob: 0.8659 loss_thr: 0.5382 loss_db: 0.1436 2022/10/26 02:39:22 - mmengine - INFO - Epoch(train) [511][25/63] lr: 2.1474e-03 eta: 9:48:07 time: 0.5270 data_time: 0.0196 memory: 16131 loss: 1.4665 loss_prob: 0.8056 loss_thr: 0.5236 loss_db: 0.1373 2022/10/26 02:39:24 - mmengine - INFO - Epoch(train) [511][30/63] lr: 2.1474e-03 eta: 9:47:54 time: 0.4998 data_time: 0.0363 memory: 16131 loss: 1.3731 loss_prob: 0.7484 loss_thr: 0.4960 loss_db: 0.1287 2022/10/26 02:39:27 - mmengine - INFO - Epoch(train) [511][35/63] lr: 2.1474e-03 eta: 9:47:54 time: 0.5215 data_time: 0.0245 memory: 16131 loss: 1.4367 loss_prob: 0.8004 loss_thr: 0.5033 loss_db: 0.1329 2022/10/26 02:39:30 - mmengine - INFO - Epoch(train) [511][40/63] lr: 2.1474e-03 eta: 9:47:42 time: 0.5257 data_time: 0.0066 memory: 16131 loss: 1.5006 loss_prob: 0.8439 loss_thr: 0.5186 loss_db: 0.1381 2022/10/26 02:39:32 - mmengine - INFO - Epoch(train) [511][45/63] lr: 2.1474e-03 eta: 9:47:42 time: 0.5137 data_time: 0.0072 memory: 16131 loss: 1.4671 loss_prob: 0.8270 loss_thr: 0.5040 loss_db: 0.1362 2022/10/26 02:39:35 - mmengine - INFO - Epoch(train) [511][50/63] lr: 2.1474e-03 eta: 9:47:30 time: 0.4993 data_time: 0.0129 memory: 16131 loss: 1.4901 loss_prob: 0.8451 loss_thr: 0.5085 loss_db: 0.1365 2022/10/26 02:39:37 - mmengine - INFO - Epoch(train) [511][55/63] lr: 2.1474e-03 eta: 9:47:30 time: 0.4983 data_time: 0.0202 memory: 16131 loss: 1.5125 loss_prob: 0.8472 loss_thr: 0.5285 loss_db: 0.1369 2022/10/26 02:39:40 - mmengine - INFO - Epoch(train) [511][60/63] lr: 2.1474e-03 eta: 9:47:18 time: 0.5066 data_time: 0.0144 memory: 16131 loss: 1.3844 loss_prob: 0.7481 loss_thr: 0.5106 loss_db: 0.1258 2022/10/26 02:39:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:39:46 - mmengine - INFO - Epoch(train) [512][5/63] lr: 2.1446e-03 eta: 9:47:18 time: 0.7272 data_time: 0.2163 memory: 16131 loss: 1.4424 loss_prob: 0.7961 loss_thr: 0.5160 loss_db: 0.1304 2022/10/26 02:39:48 - mmengine - INFO - Epoch(train) [512][10/63] lr: 2.1446e-03 eta: 9:47:03 time: 0.7411 data_time: 0.2155 memory: 16131 loss: 1.5205 loss_prob: 0.8546 loss_thr: 0.5255 loss_db: 0.1405 2022/10/26 02:39:51 - mmengine - INFO - Epoch(train) [512][15/63] lr: 2.1446e-03 eta: 9:47:03 time: 0.4996 data_time: 0.0050 memory: 16131 loss: 1.5072 loss_prob: 0.8443 loss_thr: 0.5212 loss_db: 0.1417 2022/10/26 02:39:54 - mmengine - INFO - Epoch(train) [512][20/63] lr: 2.1446e-03 eta: 9:46:51 time: 0.5173 data_time: 0.0048 memory: 16131 loss: 1.4928 loss_prob: 0.8337 loss_thr: 0.5189 loss_db: 0.1402 2022/10/26 02:39:57 - mmengine - INFO - Epoch(train) [512][25/63] lr: 2.1446e-03 eta: 9:46:51 time: 0.5630 data_time: 0.0385 memory: 16131 loss: 1.5085 loss_prob: 0.8441 loss_thr: 0.5222 loss_db: 0.1421 2022/10/26 02:39:59 - mmengine - INFO - Epoch(train) [512][30/63] lr: 2.1446e-03 eta: 9:46:39 time: 0.5489 data_time: 0.0386 memory: 16131 loss: 1.4501 loss_prob: 0.8044 loss_thr: 0.5083 loss_db: 0.1374 2022/10/26 02:40:02 - mmengine - INFO - Epoch(train) [512][35/63] lr: 2.1446e-03 eta: 9:46:39 time: 0.5132 data_time: 0.0047 memory: 16131 loss: 1.3402 loss_prob: 0.7241 loss_thr: 0.4885 loss_db: 0.1277 2022/10/26 02:40:05 - mmengine - INFO - Epoch(train) [512][40/63] lr: 2.1446e-03 eta: 9:46:28 time: 0.5435 data_time: 0.0048 memory: 16131 loss: 1.4232 loss_prob: 0.7862 loss_thr: 0.5034 loss_db: 0.1336 2022/10/26 02:40:07 - mmengine - INFO - Epoch(train) [512][45/63] lr: 2.1446e-03 eta: 9:46:28 time: 0.5566 data_time: 0.0071 memory: 16131 loss: 1.4970 loss_prob: 0.8475 loss_thr: 0.5108 loss_db: 0.1387 2022/10/26 02:40:10 - mmengine - INFO - Epoch(train) [512][50/63] lr: 2.1446e-03 eta: 9:46:16 time: 0.5552 data_time: 0.0315 memory: 16131 loss: 1.3738 loss_prob: 0.7548 loss_thr: 0.4948 loss_db: 0.1241 2022/10/26 02:40:13 - mmengine - INFO - Epoch(train) [512][55/63] lr: 2.1446e-03 eta: 9:46:16 time: 0.5231 data_time: 0.0299 memory: 16131 loss: 1.4100 loss_prob: 0.7714 loss_thr: 0.5115 loss_db: 0.1271 2022/10/26 02:40:15 - mmengine - INFO - Epoch(train) [512][60/63] lr: 2.1446e-03 eta: 9:46:04 time: 0.5046 data_time: 0.0056 memory: 16131 loss: 1.5282 loss_prob: 0.8567 loss_thr: 0.5291 loss_db: 0.1424 2022/10/26 02:40:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:40:21 - mmengine - INFO - Epoch(train) [513][5/63] lr: 2.1418e-03 eta: 9:46:04 time: 0.6559 data_time: 0.1832 memory: 16131 loss: 1.4213 loss_prob: 0.7895 loss_thr: 0.5014 loss_db: 0.1304 2022/10/26 02:40:23 - mmengine - INFO - Epoch(train) [513][10/63] lr: 2.1418e-03 eta: 9:45:48 time: 0.6909 data_time: 0.2011 memory: 16131 loss: 1.3085 loss_prob: 0.7095 loss_thr: 0.4791 loss_db: 0.1199 2022/10/26 02:40:26 - mmengine - INFO - Epoch(train) [513][15/63] lr: 2.1418e-03 eta: 9:45:48 time: 0.5242 data_time: 0.0249 memory: 16131 loss: 1.3351 loss_prob: 0.7340 loss_thr: 0.4760 loss_db: 0.1252 2022/10/26 02:40:29 - mmengine - INFO - Epoch(train) [513][20/63] lr: 2.1418e-03 eta: 9:45:37 time: 0.5930 data_time: 0.0105 memory: 16131 loss: 1.3896 loss_prob: 0.7620 loss_thr: 0.4983 loss_db: 0.1293 2022/10/26 02:40:32 - mmengine - INFO - Epoch(train) [513][25/63] lr: 2.1418e-03 eta: 9:45:37 time: 0.6301 data_time: 0.0246 memory: 16131 loss: 1.5231 loss_prob: 0.8614 loss_thr: 0.5211 loss_db: 0.1406 2022/10/26 02:40:35 - mmengine - INFO - Epoch(train) [513][30/63] lr: 2.1418e-03 eta: 9:45:26 time: 0.5761 data_time: 0.0306 memory: 16131 loss: 1.5772 loss_prob: 0.9083 loss_thr: 0.5219 loss_db: 0.1471 2022/10/26 02:40:38 - mmengine - INFO - Epoch(train) [513][35/63] lr: 2.1418e-03 eta: 9:45:26 time: 0.5402 data_time: 0.0226 memory: 16131 loss: 1.5212 loss_prob: 0.8532 loss_thr: 0.5246 loss_db: 0.1435 2022/10/26 02:40:41 - mmengine - INFO - Epoch(train) [513][40/63] lr: 2.1418e-03 eta: 9:45:15 time: 0.5601 data_time: 0.0129 memory: 16131 loss: 1.4973 loss_prob: 0.8162 loss_thr: 0.5393 loss_db: 0.1419 2022/10/26 02:40:43 - mmengine - INFO - Epoch(train) [513][45/63] lr: 2.1418e-03 eta: 9:45:15 time: 0.5550 data_time: 0.0052 memory: 16131 loss: 1.5700 loss_prob: 0.8862 loss_thr: 0.5343 loss_db: 0.1496 2022/10/26 02:40:46 - mmengine - INFO - Epoch(train) [513][50/63] lr: 2.1418e-03 eta: 9:45:03 time: 0.5153 data_time: 0.0167 memory: 16131 loss: 1.5796 loss_prob: 0.9054 loss_thr: 0.5279 loss_db: 0.1464 2022/10/26 02:40:48 - mmengine - INFO - Epoch(train) [513][55/63] lr: 2.1418e-03 eta: 9:45:03 time: 0.5037 data_time: 0.0157 memory: 16131 loss: 1.4840 loss_prob: 0.8223 loss_thr: 0.5287 loss_db: 0.1330 2022/10/26 02:40:51 - mmengine - INFO - Epoch(train) [513][60/63] lr: 2.1418e-03 eta: 9:44:50 time: 0.5056 data_time: 0.0095 memory: 16131 loss: 1.5801 loss_prob: 0.8868 loss_thr: 0.5448 loss_db: 0.1485 2022/10/26 02:40:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:40:57 - mmengine - INFO - Epoch(train) [514][5/63] lr: 2.1390e-03 eta: 9:44:50 time: 0.6953 data_time: 0.1977 memory: 16131 loss: 1.5105 loss_prob: 0.8381 loss_thr: 0.5273 loss_db: 0.1451 2022/10/26 02:40:59 - mmengine - INFO - Epoch(train) [514][10/63] lr: 2.1390e-03 eta: 9:44:35 time: 0.7308 data_time: 0.1967 memory: 16131 loss: 1.5725 loss_prob: 0.8900 loss_thr: 0.5350 loss_db: 0.1474 2022/10/26 02:41:02 - mmengine - INFO - Epoch(train) [514][15/63] lr: 2.1390e-03 eta: 9:44:35 time: 0.5201 data_time: 0.0048 memory: 16131 loss: 1.5477 loss_prob: 0.8657 loss_thr: 0.5408 loss_db: 0.1412 2022/10/26 02:41:05 - mmengine - INFO - Epoch(train) [514][20/63] lr: 2.1390e-03 eta: 9:44:24 time: 0.5405 data_time: 0.0048 memory: 16131 loss: 1.5316 loss_prob: 0.8596 loss_thr: 0.5270 loss_db: 0.1450 2022/10/26 02:41:08 - mmengine - INFO - Epoch(train) [514][25/63] lr: 2.1390e-03 eta: 9:44:24 time: 0.5575 data_time: 0.0367 memory: 16131 loss: 1.5415 loss_prob: 0.8714 loss_thr: 0.5209 loss_db: 0.1492 2022/10/26 02:41:11 - mmengine - INFO - Epoch(train) [514][30/63] lr: 2.1390e-03 eta: 9:44:13 time: 0.5986 data_time: 0.0373 memory: 16131 loss: 1.4708 loss_prob: 0.8279 loss_thr: 0.5058 loss_db: 0.1371 2022/10/26 02:41:13 - mmengine - INFO - Epoch(train) [514][35/63] lr: 2.1390e-03 eta: 9:44:13 time: 0.5813 data_time: 0.0061 memory: 16131 loss: 1.4353 loss_prob: 0.8050 loss_thr: 0.4998 loss_db: 0.1305 2022/10/26 02:41:16 - mmengine - INFO - Epoch(train) [514][40/63] lr: 2.1390e-03 eta: 9:44:01 time: 0.4992 data_time: 0.0061 memory: 16131 loss: 1.4865 loss_prob: 0.8318 loss_thr: 0.5150 loss_db: 0.1397 2022/10/26 02:41:19 - mmengine - INFO - Epoch(train) [514][45/63] lr: 2.1390e-03 eta: 9:44:01 time: 0.5776 data_time: 0.0061 memory: 16131 loss: 1.4830 loss_prob: 0.8327 loss_thr: 0.5087 loss_db: 0.1417 2022/10/26 02:41:22 - mmengine - INFO - Epoch(train) [514][50/63] lr: 2.1390e-03 eta: 9:43:50 time: 0.6569 data_time: 0.0234 memory: 16131 loss: 1.4940 loss_prob: 0.8278 loss_thr: 0.5244 loss_db: 0.1418 2022/10/26 02:41:25 - mmengine - INFO - Epoch(train) [514][55/63] lr: 2.1390e-03 eta: 9:43:50 time: 0.5696 data_time: 0.0228 memory: 16131 loss: 1.5683 loss_prob: 0.8814 loss_thr: 0.5367 loss_db: 0.1503 2022/10/26 02:41:27 - mmengine - INFO - Epoch(train) [514][60/63] lr: 2.1390e-03 eta: 9:43:38 time: 0.5087 data_time: 0.0062 memory: 16131 loss: 1.4629 loss_prob: 0.8204 loss_thr: 0.5069 loss_db: 0.1356 2022/10/26 02:41:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:41:34 - mmengine - INFO - Epoch(train) [515][5/63] lr: 2.1362e-03 eta: 9:43:38 time: 0.7988 data_time: 0.2036 memory: 16131 loss: 1.6057 loss_prob: 0.9270 loss_thr: 0.5348 loss_db: 0.1439 2022/10/26 02:41:37 - mmengine - INFO - Epoch(train) [515][10/63] lr: 2.1362e-03 eta: 9:43:24 time: 0.8065 data_time: 0.2025 memory: 16131 loss: 1.7088 loss_prob: 1.0052 loss_thr: 0.5439 loss_db: 0.1597 2022/10/26 02:41:40 - mmengine - INFO - Epoch(train) [515][15/63] lr: 2.1362e-03 eta: 9:43:24 time: 0.5204 data_time: 0.0043 memory: 16131 loss: 1.5621 loss_prob: 0.8875 loss_thr: 0.5251 loss_db: 0.1496 2022/10/26 02:41:42 - mmengine - INFO - Epoch(train) [515][20/63] lr: 2.1362e-03 eta: 9:43:12 time: 0.5037 data_time: 0.0056 memory: 16131 loss: 1.4952 loss_prob: 0.8345 loss_thr: 0.5234 loss_db: 0.1373 2022/10/26 02:41:45 - mmengine - INFO - Epoch(train) [515][25/63] lr: 2.1362e-03 eta: 9:43:12 time: 0.5054 data_time: 0.0162 memory: 16131 loss: 1.5255 loss_prob: 0.8542 loss_thr: 0.5285 loss_db: 0.1428 2022/10/26 02:41:47 - mmengine - INFO - Epoch(train) [515][30/63] lr: 2.1362e-03 eta: 9:43:01 time: 0.5480 data_time: 0.0335 memory: 16131 loss: 1.5085 loss_prob: 0.8284 loss_thr: 0.5396 loss_db: 0.1404 2022/10/26 02:41:50 - mmengine - INFO - Epoch(train) [515][35/63] lr: 2.1362e-03 eta: 9:43:01 time: 0.5580 data_time: 0.0295 memory: 16131 loss: 1.4867 loss_prob: 0.8091 loss_thr: 0.5412 loss_db: 0.1364 2022/10/26 02:41:53 - mmengine - INFO - Epoch(train) [515][40/63] lr: 2.1362e-03 eta: 9:42:49 time: 0.5400 data_time: 0.0111 memory: 16131 loss: 1.4034 loss_prob: 0.7767 loss_thr: 0.4984 loss_db: 0.1283 2022/10/26 02:41:55 - mmengine - INFO - Epoch(train) [515][45/63] lr: 2.1362e-03 eta: 9:42:49 time: 0.5092 data_time: 0.0047 memory: 16131 loss: 1.5052 loss_prob: 0.8689 loss_thr: 0.4966 loss_db: 0.1398 2022/10/26 02:41:58 - mmengine - INFO - Epoch(train) [515][50/63] lr: 2.1362e-03 eta: 9:42:37 time: 0.5133 data_time: 0.0114 memory: 16131 loss: 1.5658 loss_prob: 0.8997 loss_thr: 0.5166 loss_db: 0.1495 2022/10/26 02:42:01 - mmengine - INFO - Epoch(train) [515][55/63] lr: 2.1362e-03 eta: 9:42:37 time: 0.5382 data_time: 0.0248 memory: 16131 loss: 1.4430 loss_prob: 0.7931 loss_thr: 0.5147 loss_db: 0.1351 2022/10/26 02:42:03 - mmengine - INFO - Epoch(train) [515][60/63] lr: 2.1362e-03 eta: 9:42:25 time: 0.5216 data_time: 0.0190 memory: 16131 loss: 1.4598 loss_prob: 0.8022 loss_thr: 0.5213 loss_db: 0.1364 2022/10/26 02:42:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:42:09 - mmengine - INFO - Epoch(train) [516][5/63] lr: 2.1334e-03 eta: 9:42:25 time: 0.7143 data_time: 0.1686 memory: 16131 loss: 1.6381 loss_prob: 0.9461 loss_thr: 0.5341 loss_db: 0.1579 2022/10/26 02:42:12 - mmengine - INFO - Epoch(train) [516][10/63] lr: 2.1334e-03 eta: 9:42:10 time: 0.7438 data_time: 0.1779 memory: 16131 loss: 1.7807 loss_prob: 1.0704 loss_thr: 0.5334 loss_db: 0.1769 2022/10/26 02:42:14 - mmengine - INFO - Epoch(train) [516][15/63] lr: 2.1334e-03 eta: 9:42:10 time: 0.5128 data_time: 0.0193 memory: 16131 loss: 1.7292 loss_prob: 1.0230 loss_thr: 0.5408 loss_db: 0.1655 2022/10/26 02:42:18 - mmengine - INFO - Epoch(train) [516][20/63] lr: 2.1334e-03 eta: 9:41:59 time: 0.5914 data_time: 0.0072 memory: 16131 loss: 1.6528 loss_prob: 0.9526 loss_thr: 0.5502 loss_db: 0.1500 2022/10/26 02:42:20 - mmengine - INFO - Epoch(train) [516][25/63] lr: 2.1334e-03 eta: 9:41:59 time: 0.5952 data_time: 0.0110 memory: 16131 loss: 1.4787 loss_prob: 0.8462 loss_thr: 0.4944 loss_db: 0.1381 2022/10/26 02:42:23 - mmengine - INFO - Epoch(train) [516][30/63] lr: 2.1334e-03 eta: 9:41:47 time: 0.5038 data_time: 0.0210 memory: 16131 loss: 1.4283 loss_prob: 0.8121 loss_thr: 0.4773 loss_db: 0.1389 2022/10/26 02:42:25 - mmengine - INFO - Epoch(train) [516][35/63] lr: 2.1334e-03 eta: 9:41:47 time: 0.5005 data_time: 0.0258 memory: 16131 loss: 1.5040 loss_prob: 0.8567 loss_thr: 0.5034 loss_db: 0.1439 2022/10/26 02:42:28 - mmengine - INFO - Epoch(train) [516][40/63] lr: 2.1334e-03 eta: 9:41:35 time: 0.5356 data_time: 0.0182 memory: 16131 loss: 1.5294 loss_prob: 0.8649 loss_thr: 0.5238 loss_db: 0.1407 2022/10/26 02:42:31 - mmengine - INFO - Epoch(train) [516][45/63] lr: 2.1334e-03 eta: 9:41:35 time: 0.5333 data_time: 0.0083 memory: 16131 loss: 1.5933 loss_prob: 0.8965 loss_thr: 0.5483 loss_db: 0.1486 2022/10/26 02:42:34 - mmengine - INFO - Epoch(train) [516][50/63] lr: 2.1334e-03 eta: 9:41:24 time: 0.5632 data_time: 0.0141 memory: 16131 loss: 1.5684 loss_prob: 0.8806 loss_thr: 0.5397 loss_db: 0.1481 2022/10/26 02:42:37 - mmengine - INFO - Epoch(train) [516][55/63] lr: 2.1334e-03 eta: 9:41:24 time: 0.6003 data_time: 0.0199 memory: 16131 loss: 1.7178 loss_prob: 1.0079 loss_thr: 0.5402 loss_db: 0.1697 2022/10/26 02:42:40 - mmengine - INFO - Epoch(train) [516][60/63] lr: 2.1334e-03 eta: 9:41:13 time: 0.5882 data_time: 0.0156 memory: 16131 loss: 1.8165 loss_prob: 1.0882 loss_thr: 0.5476 loss_db: 0.1807 2022/10/26 02:42:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:42:46 - mmengine - INFO - Epoch(train) [517][5/63] lr: 2.1306e-03 eta: 9:41:13 time: 0.7078 data_time: 0.1764 memory: 16131 loss: 1.6499 loss_prob: 0.9540 loss_thr: 0.5394 loss_db: 0.1565 2022/10/26 02:42:48 - mmengine - INFO - Epoch(train) [517][10/63] lr: 2.1306e-03 eta: 9:40:58 time: 0.7135 data_time: 0.1835 memory: 16131 loss: 1.5036 loss_prob: 0.8339 loss_thr: 0.5294 loss_db: 0.1403 2022/10/26 02:42:51 - mmengine - INFO - Epoch(train) [517][15/63] lr: 2.1306e-03 eta: 9:40:58 time: 0.5296 data_time: 0.0189 memory: 16131 loss: 1.4898 loss_prob: 0.8354 loss_thr: 0.5153 loss_db: 0.1391 2022/10/26 02:42:53 - mmengine - INFO - Epoch(train) [517][20/63] lr: 2.1306e-03 eta: 9:40:46 time: 0.4931 data_time: 0.0061 memory: 16131 loss: 1.4935 loss_prob: 0.8526 loss_thr: 0.4991 loss_db: 0.1418 2022/10/26 02:42:56 - mmengine - INFO - Epoch(train) [517][25/63] lr: 2.1306e-03 eta: 9:40:46 time: 0.5135 data_time: 0.0145 memory: 16131 loss: 1.4703 loss_prob: 0.8311 loss_thr: 0.5015 loss_db: 0.1377 2022/10/26 02:42:59 - mmengine - INFO - Epoch(train) [517][30/63] lr: 2.1306e-03 eta: 9:40:34 time: 0.5387 data_time: 0.0285 memory: 16131 loss: 1.5387 loss_prob: 0.8637 loss_thr: 0.5297 loss_db: 0.1453 2022/10/26 02:43:01 - mmengine - INFO - Epoch(train) [517][35/63] lr: 2.1306e-03 eta: 9:40:34 time: 0.5130 data_time: 0.0239 memory: 16131 loss: 1.5718 loss_prob: 0.8897 loss_thr: 0.5351 loss_db: 0.1471 2022/10/26 02:43:04 - mmengine - INFO - Epoch(train) [517][40/63] lr: 2.1306e-03 eta: 9:40:22 time: 0.5181 data_time: 0.0097 memory: 16131 loss: 1.4814 loss_prob: 0.8302 loss_thr: 0.5147 loss_db: 0.1366 2022/10/26 02:43:06 - mmengine - INFO - Epoch(train) [517][45/63] lr: 2.1306e-03 eta: 9:40:22 time: 0.5361 data_time: 0.0092 memory: 16131 loss: 1.5512 loss_prob: 0.8554 loss_thr: 0.5540 loss_db: 0.1418 2022/10/26 02:43:09 - mmengine - INFO - Epoch(train) [517][50/63] lr: 2.1306e-03 eta: 9:40:11 time: 0.5369 data_time: 0.0145 memory: 16131 loss: 1.6321 loss_prob: 0.9141 loss_thr: 0.5661 loss_db: 0.1519 2022/10/26 02:43:12 - mmengine - INFO - Epoch(train) [517][55/63] lr: 2.1306e-03 eta: 9:40:11 time: 0.5222 data_time: 0.0210 memory: 16131 loss: 1.5591 loss_prob: 0.8806 loss_thr: 0.5301 loss_db: 0.1484 2022/10/26 02:43:14 - mmengine - INFO - Epoch(train) [517][60/63] lr: 2.1306e-03 eta: 9:39:58 time: 0.4939 data_time: 0.0145 memory: 16131 loss: 1.5644 loss_prob: 0.8638 loss_thr: 0.5561 loss_db: 0.1445 2022/10/26 02:43:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:43:20 - mmengine - INFO - Epoch(train) [518][5/63] lr: 2.1278e-03 eta: 9:39:58 time: 0.6796 data_time: 0.2019 memory: 16131 loss: 1.5822 loss_prob: 0.8919 loss_thr: 0.5424 loss_db: 0.1479 2022/10/26 02:43:23 - mmengine - INFO - Epoch(train) [518][10/63] lr: 2.1278e-03 eta: 9:39:43 time: 0.7086 data_time: 0.2151 memory: 16131 loss: 1.7847 loss_prob: 1.0334 loss_thr: 0.5867 loss_db: 0.1646 2022/10/26 02:43:25 - mmengine - INFO - Epoch(train) [518][15/63] lr: 2.1278e-03 eta: 9:39:43 time: 0.5205 data_time: 0.0212 memory: 16131 loss: 1.7056 loss_prob: 0.9718 loss_thr: 0.5736 loss_db: 0.1602 2022/10/26 02:43:28 - mmengine - INFO - Epoch(train) [518][20/63] lr: 2.1278e-03 eta: 9:39:31 time: 0.5261 data_time: 0.0114 memory: 16131 loss: 1.4902 loss_prob: 0.8077 loss_thr: 0.5450 loss_db: 0.1375 2022/10/26 02:43:30 - mmengine - INFO - Epoch(train) [518][25/63] lr: 2.1278e-03 eta: 9:39:31 time: 0.5297 data_time: 0.0210 memory: 16131 loss: 1.5074 loss_prob: 0.8138 loss_thr: 0.5569 loss_db: 0.1366 2022/10/26 02:43:33 - mmengine - INFO - Epoch(train) [518][30/63] lr: 2.1278e-03 eta: 9:39:20 time: 0.5319 data_time: 0.0352 memory: 16131 loss: 1.4226 loss_prob: 0.7880 loss_thr: 0.5032 loss_db: 0.1313 2022/10/26 02:43:36 - mmengine - INFO - Epoch(train) [518][35/63] lr: 2.1278e-03 eta: 9:39:20 time: 0.5206 data_time: 0.0302 memory: 16131 loss: 1.3773 loss_prob: 0.7446 loss_thr: 0.5073 loss_db: 0.1255 2022/10/26 02:43:38 - mmengine - INFO - Epoch(train) [518][40/63] lr: 2.1278e-03 eta: 9:39:08 time: 0.5040 data_time: 0.0100 memory: 16131 loss: 1.4096 loss_prob: 0.7658 loss_thr: 0.5132 loss_db: 0.1306 2022/10/26 02:43:41 - mmengine - INFO - Epoch(train) [518][45/63] lr: 2.1278e-03 eta: 9:39:08 time: 0.5414 data_time: 0.0052 memory: 16131 loss: 1.5416 loss_prob: 0.8824 loss_thr: 0.5126 loss_db: 0.1467 2022/10/26 02:43:44 - mmengine - INFO - Epoch(train) [518][50/63] lr: 2.1278e-03 eta: 9:38:56 time: 0.5566 data_time: 0.0203 memory: 16131 loss: 1.5297 loss_prob: 0.8649 loss_thr: 0.5225 loss_db: 0.1422 2022/10/26 02:43:46 - mmengine - INFO - Epoch(train) [518][55/63] lr: 2.1278e-03 eta: 9:38:56 time: 0.5106 data_time: 0.0200 memory: 16131 loss: 1.4424 loss_prob: 0.8020 loss_thr: 0.5080 loss_db: 0.1325 2022/10/26 02:43:49 - mmengine - INFO - Epoch(train) [518][60/63] lr: 2.1278e-03 eta: 9:38:45 time: 0.5499 data_time: 0.0084 memory: 16131 loss: 1.3789 loss_prob: 0.7592 loss_thr: 0.4938 loss_db: 0.1259 2022/10/26 02:43:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:43:55 - mmengine - INFO - Epoch(train) [519][5/63] lr: 2.1250e-03 eta: 9:38:45 time: 0.7261 data_time: 0.2112 memory: 16131 loss: 1.4267 loss_prob: 0.7823 loss_thr: 0.5146 loss_db: 0.1299 2022/10/26 02:43:58 - mmengine - INFO - Epoch(train) [519][10/63] lr: 2.1250e-03 eta: 9:38:30 time: 0.7600 data_time: 0.2121 memory: 16131 loss: 1.4377 loss_prob: 0.7976 loss_thr: 0.5062 loss_db: 0.1339 2022/10/26 02:44:01 - mmengine - INFO - Epoch(train) [519][15/63] lr: 2.1250e-03 eta: 9:38:30 time: 0.5605 data_time: 0.0106 memory: 16131 loss: 1.3559 loss_prob: 0.7484 loss_thr: 0.4783 loss_db: 0.1292 2022/10/26 02:44:03 - mmengine - INFO - Epoch(train) [519][20/63] lr: 2.1250e-03 eta: 9:38:18 time: 0.5137 data_time: 0.0122 memory: 16131 loss: 1.4590 loss_prob: 0.8176 loss_thr: 0.5042 loss_db: 0.1371 2022/10/26 02:44:06 - mmengine - INFO - Epoch(train) [519][25/63] lr: 2.1250e-03 eta: 9:38:18 time: 0.5595 data_time: 0.0320 memory: 16131 loss: 1.5781 loss_prob: 0.9019 loss_thr: 0.5288 loss_db: 0.1474 2022/10/26 02:44:09 - mmengine - INFO - Epoch(train) [519][30/63] lr: 2.1250e-03 eta: 9:38:07 time: 0.5810 data_time: 0.0293 memory: 16131 loss: 1.6184 loss_prob: 0.9431 loss_thr: 0.5147 loss_db: 0.1607 2022/10/26 02:44:12 - mmengine - INFO - Epoch(train) [519][35/63] lr: 2.1250e-03 eta: 9:38:07 time: 0.5248 data_time: 0.0045 memory: 16131 loss: 1.8442 loss_prob: 1.1058 loss_thr: 0.5510 loss_db: 0.1874 2022/10/26 02:44:14 - mmengine - INFO - Epoch(train) [519][40/63] lr: 2.1250e-03 eta: 9:37:55 time: 0.4964 data_time: 0.0056 memory: 16131 loss: 1.8194 loss_prob: 1.0794 loss_thr: 0.5636 loss_db: 0.1763 2022/10/26 02:44:16 - mmengine - INFO - Epoch(train) [519][45/63] lr: 2.1250e-03 eta: 9:37:55 time: 0.4940 data_time: 0.0079 memory: 16131 loss: 1.6114 loss_prob: 0.9188 loss_thr: 0.5418 loss_db: 0.1509 2022/10/26 02:44:19 - mmengine - INFO - Epoch(train) [519][50/63] lr: 2.1250e-03 eta: 9:37:44 time: 0.5382 data_time: 0.0281 memory: 16131 loss: 1.6451 loss_prob: 0.9450 loss_thr: 0.5392 loss_db: 0.1609 2022/10/26 02:44:22 - mmengine - INFO - Epoch(train) [519][55/63] lr: 2.1250e-03 eta: 9:37:44 time: 0.5504 data_time: 0.0260 memory: 16131 loss: 1.8334 loss_prob: 1.1111 loss_thr: 0.5400 loss_db: 0.1823 2022/10/26 02:44:24 - mmengine - INFO - Epoch(train) [519][60/63] lr: 2.1250e-03 eta: 9:37:32 time: 0.5031 data_time: 0.0050 memory: 16131 loss: 1.8253 loss_prob: 1.0962 loss_thr: 0.5531 loss_db: 0.1760 2022/10/26 02:44:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:44:30 - mmengine - INFO - Epoch(train) [520][5/63] lr: 2.1222e-03 eta: 9:37:32 time: 0.6482 data_time: 0.1622 memory: 16131 loss: 1.6341 loss_prob: 0.9365 loss_thr: 0.5405 loss_db: 0.1571 2022/10/26 02:44:33 - mmengine - INFO - Epoch(train) [520][10/63] lr: 2.1222e-03 eta: 9:37:17 time: 0.7260 data_time: 0.1794 memory: 16131 loss: 1.5809 loss_prob: 0.8926 loss_thr: 0.5368 loss_db: 0.1516 2022/10/26 02:44:36 - mmengine - INFO - Epoch(train) [520][15/63] lr: 2.1222e-03 eta: 9:37:17 time: 0.5823 data_time: 0.0226 memory: 16131 loss: 1.5526 loss_prob: 0.8813 loss_thr: 0.5257 loss_db: 0.1455 2022/10/26 02:44:38 - mmengine - INFO - Epoch(train) [520][20/63] lr: 2.1222e-03 eta: 9:37:05 time: 0.5269 data_time: 0.0065 memory: 16131 loss: 1.4720 loss_prob: 0.8190 loss_thr: 0.5158 loss_db: 0.1371 2022/10/26 02:44:41 - mmengine - INFO - Epoch(train) [520][25/63] lr: 2.1222e-03 eta: 9:37:05 time: 0.5150 data_time: 0.0122 memory: 16131 loss: 1.5254 loss_prob: 0.8535 loss_thr: 0.5267 loss_db: 0.1452 2022/10/26 02:44:44 - mmengine - INFO - Epoch(train) [520][30/63] lr: 2.1222e-03 eta: 9:36:53 time: 0.5444 data_time: 0.0199 memory: 16131 loss: 1.5419 loss_prob: 0.8658 loss_thr: 0.5281 loss_db: 0.1481 2022/10/26 02:44:46 - mmengine - INFO - Epoch(train) [520][35/63] lr: 2.1222e-03 eta: 9:36:53 time: 0.5443 data_time: 0.0315 memory: 16131 loss: 1.6148 loss_prob: 0.9317 loss_thr: 0.5261 loss_db: 0.1570 2022/10/26 02:44:49 - mmengine - INFO - Epoch(train) [520][40/63] lr: 2.1222e-03 eta: 9:36:42 time: 0.5166 data_time: 0.0233 memory: 16131 loss: 1.7558 loss_prob: 1.0230 loss_thr: 0.5628 loss_db: 0.1700 2022/10/26 02:44:51 - mmengine - INFO - Epoch(train) [520][45/63] lr: 2.1222e-03 eta: 9:36:42 time: 0.5007 data_time: 0.0055 memory: 16131 loss: 1.6393 loss_prob: 0.9257 loss_thr: 0.5602 loss_db: 0.1535 2022/10/26 02:44:54 - mmengine - INFO - Epoch(train) [520][50/63] lr: 2.1222e-03 eta: 9:36:30 time: 0.5126 data_time: 0.0085 memory: 16131 loss: 1.4991 loss_prob: 0.8448 loss_thr: 0.5128 loss_db: 0.1416 2022/10/26 02:44:56 - mmengine - INFO - Epoch(train) [520][55/63] lr: 2.1222e-03 eta: 9:36:30 time: 0.5204 data_time: 0.0213 memory: 16131 loss: 1.5466 loss_prob: 0.8753 loss_thr: 0.5255 loss_db: 0.1458 2022/10/26 02:44:59 - mmengine - INFO - Epoch(train) [520][60/63] lr: 2.1222e-03 eta: 9:36:18 time: 0.5123 data_time: 0.0206 memory: 16131 loss: 1.7838 loss_prob: 1.0671 loss_thr: 0.5513 loss_db: 0.1654 2022/10/26 02:45:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:45:00 - mmengine - INFO - Saving checkpoint at 520 epochs 2022/10/26 02:45:08 - mmengine - INFO - Epoch(val) [520][5/32] eta: 9:36:18 time: 0.5663 data_time: 0.0680 memory: 16131 2022/10/26 02:45:11 - mmengine - INFO - Epoch(val) [520][10/32] eta: 0:00:14 time: 0.6816 data_time: 0.0898 memory: 15724 2022/10/26 02:45:14 - mmengine - INFO - Epoch(val) [520][15/32] eta: 0:00:14 time: 0.6227 data_time: 0.0384 memory: 15724 2022/10/26 02:45:17 - mmengine - INFO - Epoch(val) [520][20/32] eta: 0:00:07 time: 0.6266 data_time: 0.0383 memory: 15724 2022/10/26 02:45:20 - mmengine - INFO - Epoch(val) [520][25/32] eta: 0:00:07 time: 0.6429 data_time: 0.0391 memory: 15724 2022/10/26 02:45:23 - mmengine - INFO - Epoch(val) [520][30/32] eta: 0:00:01 time: 0.6013 data_time: 0.0201 memory: 15724 2022/10/26 02:45:24 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8252, precision: 0.3811, hmean: 0.5214 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8252, precision: 0.7260, hmean: 0.7724 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8223, precision: 0.7889, hmean: 0.8053 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8117, precision: 0.8342, hmean: 0.8228 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7761, precision: 0.8911, hmean: 0.8296 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5325, precision: 0.9461, hmean: 0.6815 2022/10/26 02:45:24 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0034, precision: 1.0000, hmean: 0.0067 2022/10/26 02:45:24 - mmengine - INFO - Epoch(val) [520][32/32] icdar/precision: 0.8911 icdar/recall: 0.7761 icdar/hmean: 0.8296 2022/10/26 02:45:29 - mmengine - INFO - Epoch(train) [521][5/63] lr: 2.1193e-03 eta: 0:00:01 time: 0.6960 data_time: 0.1792 memory: 16131 loss: 1.5003 loss_prob: 0.8532 loss_thr: 0.4975 loss_db: 0.1496 2022/10/26 02:45:32 - mmengine - INFO - Epoch(train) [521][10/63] lr: 2.1193e-03 eta: 9:36:04 time: 0.7878 data_time: 0.1948 memory: 16131 loss: 1.5253 loss_prob: 0.8737 loss_thr: 0.5041 loss_db: 0.1475 2022/10/26 02:45:34 - mmengine - INFO - Epoch(train) [521][15/63] lr: 2.1193e-03 eta: 9:36:04 time: 0.5671 data_time: 0.0230 memory: 16131 loss: 1.4891 loss_prob: 0.8303 loss_thr: 0.5239 loss_db: 0.1349 2022/10/26 02:45:37 - mmengine - INFO - Epoch(train) [521][20/63] lr: 2.1193e-03 eta: 9:35:52 time: 0.5018 data_time: 0.0061 memory: 16131 loss: 1.6161 loss_prob: 0.9218 loss_thr: 0.5451 loss_db: 0.1492 2022/10/26 02:45:40 - mmengine - INFO - Epoch(train) [521][25/63] lr: 2.1193e-03 eta: 9:35:52 time: 0.5722 data_time: 0.0120 memory: 16131 loss: 1.7828 loss_prob: 1.0332 loss_thr: 0.5825 loss_db: 0.1671 2022/10/26 02:45:43 - mmengine - INFO - Epoch(train) [521][30/63] lr: 2.1193e-03 eta: 9:35:41 time: 0.6087 data_time: 0.0227 memory: 16131 loss: 1.7549 loss_prob: 1.0125 loss_thr: 0.5768 loss_db: 0.1656 2022/10/26 02:45:46 - mmengine - INFO - Epoch(train) [521][35/63] lr: 2.1193e-03 eta: 9:35:41 time: 0.5698 data_time: 0.0306 memory: 16131 loss: 1.6746 loss_prob: 0.9673 loss_thr: 0.5491 loss_db: 0.1582 2022/10/26 02:45:48 - mmengine - INFO - Epoch(train) [521][40/63] lr: 2.1193e-03 eta: 9:35:30 time: 0.5584 data_time: 0.0194 memory: 16131 loss: 1.7260 loss_prob: 1.0126 loss_thr: 0.5511 loss_db: 0.1623 2022/10/26 02:45:51 - mmengine - INFO - Epoch(train) [521][45/63] lr: 2.1193e-03 eta: 9:35:30 time: 0.5291 data_time: 0.0050 memory: 16131 loss: 1.6854 loss_prob: 0.9984 loss_thr: 0.5306 loss_db: 0.1564 2022/10/26 02:45:53 - mmengine - INFO - Epoch(train) [521][50/63] lr: 2.1193e-03 eta: 9:35:18 time: 0.4895 data_time: 0.0095 memory: 16131 loss: 1.5699 loss_prob: 0.9049 loss_thr: 0.5219 loss_db: 0.1431 2022/10/26 02:45:56 - mmengine - INFO - Epoch(train) [521][55/63] lr: 2.1193e-03 eta: 9:35:18 time: 0.5065 data_time: 0.0224 memory: 16131 loss: 1.5398 loss_prob: 0.8736 loss_thr: 0.5230 loss_db: 0.1432 2022/10/26 02:45:59 - mmengine - INFO - Epoch(train) [521][60/63] lr: 2.1193e-03 eta: 9:35:06 time: 0.5194 data_time: 0.0186 memory: 16131 loss: 1.6108 loss_prob: 0.9220 loss_thr: 0.5338 loss_db: 0.1550 2022/10/26 02:46:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:46:05 - mmengine - INFO - Epoch(train) [522][5/63] lr: 2.1165e-03 eta: 9:35:06 time: 0.7549 data_time: 0.2177 memory: 16131 loss: 1.6101 loss_prob: 0.9170 loss_thr: 0.5477 loss_db: 0.1454 2022/10/26 02:46:08 - mmengine - INFO - Epoch(train) [522][10/63] lr: 2.1165e-03 eta: 9:34:53 time: 0.8389 data_time: 0.2180 memory: 16131 loss: 1.5383 loss_prob: 0.8718 loss_thr: 0.5267 loss_db: 0.1398 2022/10/26 02:46:11 - mmengine - INFO - Epoch(train) [522][15/63] lr: 2.1165e-03 eta: 9:34:53 time: 0.5908 data_time: 0.0058 memory: 16131 loss: 1.5088 loss_prob: 0.8430 loss_thr: 0.5229 loss_db: 0.1428 2022/10/26 02:46:13 - mmengine - INFO - Epoch(train) [522][20/63] lr: 2.1165e-03 eta: 9:34:41 time: 0.5130 data_time: 0.0065 memory: 16131 loss: 1.6093 loss_prob: 0.9079 loss_thr: 0.5429 loss_db: 0.1585 2022/10/26 02:46:16 - mmengine - INFO - Epoch(train) [522][25/63] lr: 2.1165e-03 eta: 9:34:41 time: 0.5242 data_time: 0.0345 memory: 16131 loss: 1.7690 loss_prob: 1.0298 loss_thr: 0.5668 loss_db: 0.1723 2022/10/26 02:46:19 - mmengine - INFO - Epoch(train) [522][30/63] lr: 2.1165e-03 eta: 9:34:29 time: 0.5264 data_time: 0.0332 memory: 16131 loss: 1.7146 loss_prob: 1.0086 loss_thr: 0.5445 loss_db: 0.1614 2022/10/26 02:46:21 - mmengine - INFO - Epoch(train) [522][35/63] lr: 2.1165e-03 eta: 9:34:29 time: 0.4943 data_time: 0.0088 memory: 16131 loss: 1.6879 loss_prob: 0.9701 loss_thr: 0.5603 loss_db: 0.1575 2022/10/26 02:46:24 - mmengine - INFO - Epoch(train) [522][40/63] lr: 2.1165e-03 eta: 9:34:17 time: 0.5017 data_time: 0.0098 memory: 16131 loss: 1.7417 loss_prob: 0.9912 loss_thr: 0.5874 loss_db: 0.1630 2022/10/26 02:46:26 - mmengine - INFO - Epoch(train) [522][45/63] lr: 2.1165e-03 eta: 9:34:17 time: 0.4948 data_time: 0.0066 memory: 16131 loss: 1.6357 loss_prob: 0.9203 loss_thr: 0.5630 loss_db: 0.1525 2022/10/26 02:46:29 - mmengine - INFO - Epoch(train) [522][50/63] lr: 2.1165e-03 eta: 9:34:06 time: 0.5469 data_time: 0.0212 memory: 16131 loss: 1.5272 loss_prob: 0.8571 loss_thr: 0.5268 loss_db: 0.1433 2022/10/26 02:46:32 - mmengine - INFO - Epoch(train) [522][55/63] lr: 2.1165e-03 eta: 9:34:06 time: 0.5752 data_time: 0.0205 memory: 16131 loss: 1.4167 loss_prob: 0.7891 loss_thr: 0.4937 loss_db: 0.1339 2022/10/26 02:46:34 - mmengine - INFO - Epoch(train) [522][60/63] lr: 2.1165e-03 eta: 9:33:54 time: 0.5200 data_time: 0.0072 memory: 16131 loss: 1.3740 loss_prob: 0.7626 loss_thr: 0.4838 loss_db: 0.1276 2022/10/26 02:46:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:46:41 - mmengine - INFO - Epoch(train) [523][5/63] lr: 2.1137e-03 eta: 9:33:54 time: 0.7371 data_time: 0.2367 memory: 16131 loss: 1.4168 loss_prob: 0.7888 loss_thr: 0.4966 loss_db: 0.1314 2022/10/26 02:46:43 - mmengine - INFO - Epoch(train) [523][10/63] lr: 2.1137e-03 eta: 9:33:39 time: 0.7522 data_time: 0.2379 memory: 16131 loss: 1.4901 loss_prob: 0.8273 loss_thr: 0.5267 loss_db: 0.1361 2022/10/26 02:46:46 - mmengine - INFO - Epoch(train) [523][15/63] lr: 2.1137e-03 eta: 9:33:39 time: 0.5121 data_time: 0.0109 memory: 16131 loss: 1.4587 loss_prob: 0.8113 loss_thr: 0.5116 loss_db: 0.1357 2022/10/26 02:46:48 - mmengine - INFO - Epoch(train) [523][20/63] lr: 2.1137e-03 eta: 9:33:28 time: 0.5337 data_time: 0.0102 memory: 16131 loss: 1.4600 loss_prob: 0.8217 loss_thr: 0.4996 loss_db: 0.1387 2022/10/26 02:46:51 - mmengine - INFO - Epoch(train) [523][25/63] lr: 2.1137e-03 eta: 9:33:28 time: 0.5386 data_time: 0.0216 memory: 16131 loss: 1.4796 loss_prob: 0.8446 loss_thr: 0.4933 loss_db: 0.1418 2022/10/26 02:46:54 - mmengine - INFO - Epoch(train) [523][30/63] lr: 2.1137e-03 eta: 9:33:17 time: 0.5633 data_time: 0.0289 memory: 16131 loss: 1.4738 loss_prob: 0.8413 loss_thr: 0.4894 loss_db: 0.1430 2022/10/26 02:46:57 - mmengine - INFO - Epoch(train) [523][35/63] lr: 2.1137e-03 eta: 9:33:17 time: 0.5269 data_time: 0.0147 memory: 16131 loss: 1.4707 loss_prob: 0.8297 loss_thr: 0.5018 loss_db: 0.1392 2022/10/26 02:46:59 - mmengine - INFO - Epoch(train) [523][40/63] lr: 2.1137e-03 eta: 9:33:05 time: 0.5066 data_time: 0.0203 memory: 16131 loss: 1.5363 loss_prob: 0.8635 loss_thr: 0.5251 loss_db: 0.1477 2022/10/26 02:47:02 - mmengine - INFO - Epoch(train) [523][45/63] lr: 2.1137e-03 eta: 9:33:05 time: 0.5586 data_time: 0.0186 memory: 16131 loss: 1.6740 loss_prob: 0.9621 loss_thr: 0.5460 loss_db: 0.1659 2022/10/26 02:47:05 - mmengine - INFO - Epoch(train) [523][50/63] lr: 2.1137e-03 eta: 9:32:53 time: 0.5421 data_time: 0.0143 memory: 16131 loss: 1.9680 loss_prob: 1.2055 loss_thr: 0.5722 loss_db: 0.1903 2022/10/26 02:47:07 - mmengine - INFO - Epoch(train) [523][55/63] lr: 2.1137e-03 eta: 9:32:53 time: 0.5041 data_time: 0.0199 memory: 16131 loss: 2.0892 loss_prob: 1.3041 loss_thr: 0.5850 loss_db: 0.2001 2022/10/26 02:47:10 - mmengine - INFO - Epoch(train) [523][60/63] lr: 2.1137e-03 eta: 9:32:42 time: 0.5311 data_time: 0.0185 memory: 16131 loss: 1.8187 loss_prob: 1.0831 loss_thr: 0.5580 loss_db: 0.1776 2022/10/26 02:47:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:47:16 - mmengine - INFO - Epoch(train) [524][5/63] lr: 2.1109e-03 eta: 9:32:42 time: 0.7007 data_time: 0.1598 memory: 16131 loss: 1.5850 loss_prob: 0.9068 loss_thr: 0.5334 loss_db: 0.1447 2022/10/26 02:47:19 - mmengine - INFO - Epoch(train) [524][10/63] lr: 2.1109e-03 eta: 9:32:27 time: 0.7337 data_time: 0.1589 memory: 16131 loss: 1.6833 loss_prob: 0.9592 loss_thr: 0.5684 loss_db: 0.1556 2022/10/26 02:47:21 - mmengine - INFO - Epoch(train) [524][15/63] lr: 2.1109e-03 eta: 9:32:27 time: 0.5167 data_time: 0.0084 memory: 16131 loss: 1.5436 loss_prob: 0.8789 loss_thr: 0.5206 loss_db: 0.1442 2022/10/26 02:47:24 - mmengine - INFO - Epoch(train) [524][20/63] lr: 2.1109e-03 eta: 9:32:15 time: 0.5158 data_time: 0.0106 memory: 16131 loss: 1.4803 loss_prob: 0.8360 loss_thr: 0.5054 loss_db: 0.1389 2022/10/26 02:47:27 - mmengine - INFO - Epoch(train) [524][25/63] lr: 2.1109e-03 eta: 9:32:15 time: 0.5397 data_time: 0.0149 memory: 16131 loss: 1.5409 loss_prob: 0.8822 loss_thr: 0.5127 loss_db: 0.1460 2022/10/26 02:47:30 - mmengine - INFO - Epoch(train) [524][30/63] lr: 2.1109e-03 eta: 9:32:04 time: 0.5780 data_time: 0.0455 memory: 16131 loss: 1.5563 loss_prob: 0.8902 loss_thr: 0.5209 loss_db: 0.1452 2022/10/26 02:47:32 - mmengine - INFO - Epoch(train) [524][35/63] lr: 2.1109e-03 eta: 9:32:04 time: 0.5447 data_time: 0.0446 memory: 16131 loss: 1.6098 loss_prob: 0.9147 loss_thr: 0.5474 loss_db: 0.1477 2022/10/26 02:47:34 - mmengine - INFO - Epoch(train) [524][40/63] lr: 2.1109e-03 eta: 9:31:52 time: 0.4921 data_time: 0.0092 memory: 16131 loss: 1.5336 loss_prob: 0.8733 loss_thr: 0.5164 loss_db: 0.1440 2022/10/26 02:47:37 - mmengine - INFO - Epoch(train) [524][45/63] lr: 2.1109e-03 eta: 9:31:52 time: 0.4958 data_time: 0.0075 memory: 16131 loss: 1.4997 loss_prob: 0.8400 loss_thr: 0.5170 loss_db: 0.1427 2022/10/26 02:47:40 - mmengine - INFO - Epoch(train) [524][50/63] lr: 2.1109e-03 eta: 9:31:40 time: 0.5211 data_time: 0.0138 memory: 16131 loss: 1.5270 loss_prob: 0.8407 loss_thr: 0.5445 loss_db: 0.1418 2022/10/26 02:47:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:47:42 - mmengine - INFO - Epoch(train) [524][55/63] lr: 2.1109e-03 eta: 9:31:40 time: 0.5384 data_time: 0.0208 memory: 16131 loss: 1.5632 loss_prob: 0.8890 loss_thr: 0.5239 loss_db: 0.1504 2022/10/26 02:47:45 - mmengine - INFO - Epoch(train) [524][60/63] lr: 2.1109e-03 eta: 9:31:29 time: 0.5245 data_time: 0.0152 memory: 16131 loss: 1.6303 loss_prob: 0.9490 loss_thr: 0.5207 loss_db: 0.1606 2022/10/26 02:47:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:47:51 - mmengine - INFO - Epoch(train) [525][5/63] lr: 2.1081e-03 eta: 9:31:29 time: 0.6752 data_time: 0.1939 memory: 16131 loss: 1.5002 loss_prob: 0.8492 loss_thr: 0.5103 loss_db: 0.1407 2022/10/26 02:47:53 - mmengine - INFO - Epoch(train) [525][10/63] lr: 2.1081e-03 eta: 9:31:14 time: 0.7252 data_time: 0.1980 memory: 16131 loss: 1.4610 loss_prob: 0.8186 loss_thr: 0.5076 loss_db: 0.1347 2022/10/26 02:47:56 - mmengine - INFO - Epoch(train) [525][15/63] lr: 2.1081e-03 eta: 9:31:14 time: 0.5266 data_time: 0.0119 memory: 16131 loss: 1.4564 loss_prob: 0.8157 loss_thr: 0.5067 loss_db: 0.1340 2022/10/26 02:47:59 - mmengine - INFO - Epoch(train) [525][20/63] lr: 2.1081e-03 eta: 9:31:02 time: 0.5198 data_time: 0.0082 memory: 16131 loss: 1.5144 loss_prob: 0.8585 loss_thr: 0.5139 loss_db: 0.1420 2022/10/26 02:48:01 - mmengine - INFO - Epoch(train) [525][25/63] lr: 2.1081e-03 eta: 9:31:02 time: 0.5471 data_time: 0.0278 memory: 16131 loss: 1.7032 loss_prob: 0.9858 loss_thr: 0.5496 loss_db: 0.1677 2022/10/26 02:48:04 - mmengine - INFO - Epoch(train) [525][30/63] lr: 2.1081e-03 eta: 9:30:51 time: 0.5545 data_time: 0.0341 memory: 16131 loss: 1.7594 loss_prob: 1.0340 loss_thr: 0.5554 loss_db: 0.1700 2022/10/26 02:48:07 - mmengine - INFO - Epoch(train) [525][35/63] lr: 2.1081e-03 eta: 9:30:51 time: 0.5584 data_time: 0.0145 memory: 16131 loss: 1.7286 loss_prob: 1.0115 loss_thr: 0.5549 loss_db: 0.1622 2022/10/26 02:48:10 - mmengine - INFO - Epoch(train) [525][40/63] lr: 2.1081e-03 eta: 9:30:40 time: 0.5776 data_time: 0.0113 memory: 16131 loss: 1.5728 loss_prob: 0.8851 loss_thr: 0.5389 loss_db: 0.1488 2022/10/26 02:48:12 - mmengine - INFO - Epoch(train) [525][45/63] lr: 2.1081e-03 eta: 9:30:40 time: 0.5370 data_time: 0.0091 memory: 16131 loss: 1.5744 loss_prob: 0.8862 loss_thr: 0.5399 loss_db: 0.1483 2022/10/26 02:48:15 - mmengine - INFO - Epoch(train) [525][50/63] lr: 2.1081e-03 eta: 9:30:28 time: 0.5118 data_time: 0.0174 memory: 16131 loss: 1.6404 loss_prob: 0.9303 loss_thr: 0.5546 loss_db: 0.1555 2022/10/26 02:48:18 - mmengine - INFO - Epoch(train) [525][55/63] lr: 2.1081e-03 eta: 9:30:28 time: 0.5450 data_time: 0.0208 memory: 16131 loss: 1.4893 loss_prob: 0.8345 loss_thr: 0.5149 loss_db: 0.1400 2022/10/26 02:48:20 - mmengine - INFO - Epoch(train) [525][60/63] lr: 2.1081e-03 eta: 9:30:17 time: 0.5375 data_time: 0.0111 memory: 16131 loss: 1.4929 loss_prob: 0.8386 loss_thr: 0.5115 loss_db: 0.1428 2022/10/26 02:48:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:48:26 - mmengine - INFO - Epoch(train) [526][5/63] lr: 2.1053e-03 eta: 9:30:17 time: 0.6576 data_time: 0.1726 memory: 16131 loss: 1.6027 loss_prob: 0.9095 loss_thr: 0.5412 loss_db: 0.1520 2022/10/26 02:48:29 - mmengine - INFO - Epoch(train) [526][10/63] lr: 2.1053e-03 eta: 9:30:02 time: 0.6654 data_time: 0.1651 memory: 16131 loss: 1.4936 loss_prob: 0.8369 loss_thr: 0.5182 loss_db: 0.1385 2022/10/26 02:48:31 - mmengine - INFO - Epoch(train) [526][15/63] lr: 2.1053e-03 eta: 9:30:02 time: 0.5266 data_time: 0.0157 memory: 16131 loss: 1.6681 loss_prob: 0.9643 loss_thr: 0.5467 loss_db: 0.1571 2022/10/26 02:48:34 - mmengine - INFO - Epoch(train) [526][20/63] lr: 2.1053e-03 eta: 9:29:50 time: 0.5294 data_time: 0.0145 memory: 16131 loss: 1.5262 loss_prob: 0.8753 loss_thr: 0.5086 loss_db: 0.1423 2022/10/26 02:48:37 - mmengine - INFO - Epoch(train) [526][25/63] lr: 2.1053e-03 eta: 9:29:50 time: 0.5372 data_time: 0.0215 memory: 16131 loss: 1.2691 loss_prob: 0.6925 loss_thr: 0.4591 loss_db: 0.1175 2022/10/26 02:48:39 - mmengine - INFO - Epoch(train) [526][30/63] lr: 2.1053e-03 eta: 9:29:38 time: 0.5326 data_time: 0.0251 memory: 16131 loss: 1.4890 loss_prob: 0.8396 loss_thr: 0.5090 loss_db: 0.1404 2022/10/26 02:48:42 - mmengine - INFO - Epoch(train) [526][35/63] lr: 2.1053e-03 eta: 9:29:38 time: 0.5227 data_time: 0.0233 memory: 16131 loss: 1.5453 loss_prob: 0.8783 loss_thr: 0.5192 loss_db: 0.1478 2022/10/26 02:48:44 - mmengine - INFO - Epoch(train) [526][40/63] lr: 2.1053e-03 eta: 9:29:27 time: 0.5164 data_time: 0.0194 memory: 16131 loss: 1.4900 loss_prob: 0.8228 loss_thr: 0.5264 loss_db: 0.1408 2022/10/26 02:48:47 - mmengine - INFO - Epoch(train) [526][45/63] lr: 2.1053e-03 eta: 9:29:27 time: 0.4942 data_time: 0.0049 memory: 16131 loss: 1.6088 loss_prob: 0.9130 loss_thr: 0.5481 loss_db: 0.1477 2022/10/26 02:48:49 - mmengine - INFO - Epoch(train) [526][50/63] lr: 2.1053e-03 eta: 9:29:15 time: 0.4985 data_time: 0.0170 memory: 16131 loss: 1.6325 loss_prob: 0.9406 loss_thr: 0.5419 loss_db: 0.1500 2022/10/26 02:48:52 - mmengine - INFO - Epoch(train) [526][55/63] lr: 2.1053e-03 eta: 9:29:15 time: 0.5009 data_time: 0.0186 memory: 16131 loss: 1.5643 loss_prob: 0.8789 loss_thr: 0.5386 loss_db: 0.1468 2022/10/26 02:48:54 - mmengine - INFO - Epoch(train) [526][60/63] lr: 2.1053e-03 eta: 9:29:03 time: 0.4960 data_time: 0.0110 memory: 16131 loss: 1.4916 loss_prob: 0.8321 loss_thr: 0.5208 loss_db: 0.1387 2022/10/26 02:48:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:49:01 - mmengine - INFO - Epoch(train) [527][5/63] lr: 2.1025e-03 eta: 9:29:03 time: 0.7797 data_time: 0.2268 memory: 16131 loss: 1.4090 loss_prob: 0.7748 loss_thr: 0.5022 loss_db: 0.1320 2022/10/26 02:49:04 - mmengine - INFO - Epoch(train) [527][10/63] lr: 2.1025e-03 eta: 9:28:49 time: 0.7992 data_time: 0.2213 memory: 16131 loss: 1.4278 loss_prob: 0.7989 loss_thr: 0.4925 loss_db: 0.1364 2022/10/26 02:49:08 - mmengine - INFO - Epoch(train) [527][15/63] lr: 2.1025e-03 eta: 9:28:49 time: 0.7111 data_time: 0.0052 memory: 16131 loss: 1.3559 loss_prob: 0.7410 loss_thr: 0.4911 loss_db: 0.1238 2022/10/26 02:49:15 - mmengine - INFO - Epoch(train) [527][20/63] lr: 2.1025e-03 eta: 9:28:45 time: 1.1167 data_time: 0.0120 memory: 16131 loss: 1.3612 loss_prob: 0.7318 loss_thr: 0.5064 loss_db: 0.1230 2022/10/26 02:49:19 - mmengine - INFO - Epoch(train) [527][25/63] lr: 2.1025e-03 eta: 9:28:45 time: 1.1214 data_time: 0.0411 memory: 16131 loss: 1.3982 loss_prob: 0.7608 loss_thr: 0.5070 loss_db: 0.1304 2022/10/26 02:49:22 - mmengine - INFO - Epoch(train) [527][30/63] lr: 2.1025e-03 eta: 9:28:36 time: 0.7274 data_time: 0.0359 memory: 16131 loss: 1.3512 loss_prob: 0.7378 loss_thr: 0.4880 loss_db: 0.1254 2022/10/26 02:49:25 - mmengine - INFO - Epoch(train) [527][35/63] lr: 2.1025e-03 eta: 9:28:36 time: 0.5426 data_time: 0.0079 memory: 16131 loss: 1.3291 loss_prob: 0.7239 loss_thr: 0.4851 loss_db: 0.1202 2022/10/26 02:49:27 - mmengine - INFO - Epoch(train) [527][40/63] lr: 2.1025e-03 eta: 9:28:25 time: 0.5261 data_time: 0.0092 memory: 16131 loss: 1.4714 loss_prob: 0.8178 loss_thr: 0.5194 loss_db: 0.1342 2022/10/26 02:49:30 - mmengine - INFO - Epoch(train) [527][45/63] lr: 2.1025e-03 eta: 9:28:25 time: 0.5145 data_time: 0.0106 memory: 16131 loss: 1.4432 loss_prob: 0.7956 loss_thr: 0.5151 loss_db: 0.1326 2022/10/26 02:49:33 - mmengine - INFO - Epoch(train) [527][50/63] lr: 2.1025e-03 eta: 9:28:13 time: 0.5146 data_time: 0.0256 memory: 16131 loss: 1.3409 loss_prob: 0.7324 loss_thr: 0.4851 loss_db: 0.1234 2022/10/26 02:49:35 - mmengine - INFO - Epoch(train) [527][55/63] lr: 2.1025e-03 eta: 9:28:13 time: 0.5015 data_time: 0.0236 memory: 16131 loss: 1.4620 loss_prob: 0.8310 loss_thr: 0.4982 loss_db: 0.1329 2022/10/26 02:49:38 - mmengine - INFO - Epoch(train) [527][60/63] lr: 2.1025e-03 eta: 9:28:01 time: 0.4971 data_time: 0.0058 memory: 16131 loss: 1.4508 loss_prob: 0.8194 loss_thr: 0.5018 loss_db: 0.1295 2022/10/26 02:49:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:49:44 - mmengine - INFO - Epoch(train) [528][5/63] lr: 2.0997e-03 eta: 9:28:01 time: 0.7540 data_time: 0.1755 memory: 16131 loss: 1.4324 loss_prob: 0.7898 loss_thr: 0.5073 loss_db: 0.1354 2022/10/26 02:49:47 - mmengine - INFO - Epoch(train) [528][10/63] lr: 2.0997e-03 eta: 9:27:47 time: 0.7739 data_time: 0.1863 memory: 16131 loss: 1.3847 loss_prob: 0.7542 loss_thr: 0.5018 loss_db: 0.1288 2022/10/26 02:49:49 - mmengine - INFO - Epoch(train) [528][15/63] lr: 2.0997e-03 eta: 9:27:47 time: 0.4981 data_time: 0.0167 memory: 16131 loss: 1.5497 loss_prob: 0.8618 loss_thr: 0.5448 loss_db: 0.1431 2022/10/26 02:49:52 - mmengine - INFO - Epoch(train) [528][20/63] lr: 2.0997e-03 eta: 9:27:35 time: 0.5152 data_time: 0.0133 memory: 16131 loss: 1.5402 loss_prob: 0.8528 loss_thr: 0.5446 loss_db: 0.1428 2022/10/26 02:49:54 - mmengine - INFO - Epoch(train) [528][25/63] lr: 2.0997e-03 eta: 9:27:35 time: 0.5380 data_time: 0.0207 memory: 16131 loss: 1.4413 loss_prob: 0.7915 loss_thr: 0.5155 loss_db: 0.1343 2022/10/26 02:49:57 - mmengine - INFO - Epoch(train) [528][30/63] lr: 2.0997e-03 eta: 9:27:24 time: 0.5397 data_time: 0.0226 memory: 16131 loss: 1.4466 loss_prob: 0.7964 loss_thr: 0.5151 loss_db: 0.1351 2022/10/26 02:50:00 - mmengine - INFO - Epoch(train) [528][35/63] lr: 2.0997e-03 eta: 9:27:24 time: 0.5488 data_time: 0.0235 memory: 16131 loss: 1.5151 loss_prob: 0.8548 loss_thr: 0.5157 loss_db: 0.1446 2022/10/26 02:50:03 - mmengine - INFO - Epoch(train) [528][40/63] lr: 2.0997e-03 eta: 9:27:12 time: 0.5471 data_time: 0.0171 memory: 16131 loss: 1.7129 loss_prob: 1.0200 loss_thr: 0.5292 loss_db: 0.1637 2022/10/26 02:50:05 - mmengine - INFO - Epoch(train) [528][45/63] lr: 2.0997e-03 eta: 9:27:12 time: 0.5132 data_time: 0.0124 memory: 16131 loss: 1.6476 loss_prob: 0.9665 loss_thr: 0.5258 loss_db: 0.1553 2022/10/26 02:50:08 - mmengine - INFO - Epoch(train) [528][50/63] lr: 2.0997e-03 eta: 9:27:00 time: 0.4921 data_time: 0.0189 memory: 16131 loss: 1.6543 loss_prob: 0.9530 loss_thr: 0.5399 loss_db: 0.1614 2022/10/26 02:50:10 - mmengine - INFO - Epoch(train) [528][55/63] lr: 2.0997e-03 eta: 9:27:00 time: 0.5212 data_time: 0.0182 memory: 16131 loss: 1.6165 loss_prob: 0.9262 loss_thr: 0.5342 loss_db: 0.1561 2022/10/26 02:50:13 - mmengine - INFO - Epoch(train) [528][60/63] lr: 2.0997e-03 eta: 9:26:49 time: 0.5634 data_time: 0.0119 memory: 16131 loss: 1.4381 loss_prob: 0.7985 loss_thr: 0.5066 loss_db: 0.1330 2022/10/26 02:50:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:50:19 - mmengine - INFO - Epoch(train) [529][5/63] lr: 2.0969e-03 eta: 9:26:49 time: 0.7045 data_time: 0.2009 memory: 16131 loss: 1.5426 loss_prob: 0.8888 loss_thr: 0.5072 loss_db: 0.1466 2022/10/26 02:50:22 - mmengine - INFO - Epoch(train) [529][10/63] lr: 2.0969e-03 eta: 9:26:35 time: 0.7613 data_time: 0.2013 memory: 16131 loss: 1.6446 loss_prob: 0.9502 loss_thr: 0.5423 loss_db: 0.1521 2022/10/26 02:50:25 - mmengine - INFO - Epoch(train) [529][15/63] lr: 2.0969e-03 eta: 9:26:35 time: 0.5470 data_time: 0.0058 memory: 16131 loss: 1.6314 loss_prob: 0.9353 loss_thr: 0.5426 loss_db: 0.1535 2022/10/26 02:50:27 - mmengine - INFO - Epoch(train) [529][20/63] lr: 2.0969e-03 eta: 9:26:24 time: 0.5260 data_time: 0.0094 memory: 16131 loss: 1.5559 loss_prob: 0.8835 loss_thr: 0.5263 loss_db: 0.1462 2022/10/26 02:50:30 - mmengine - INFO - Epoch(train) [529][25/63] lr: 2.0969e-03 eta: 9:26:24 time: 0.5547 data_time: 0.0286 memory: 16131 loss: 1.5042 loss_prob: 0.8507 loss_thr: 0.5136 loss_db: 0.1399 2022/10/26 02:50:33 - mmengine - INFO - Epoch(train) [529][30/63] lr: 2.0969e-03 eta: 9:26:13 time: 0.5549 data_time: 0.0341 memory: 16131 loss: 1.4348 loss_prob: 0.8093 loss_thr: 0.4935 loss_db: 0.1320 2022/10/26 02:50:35 - mmengine - INFO - Epoch(train) [529][35/63] lr: 2.0969e-03 eta: 9:26:13 time: 0.5160 data_time: 0.0152 memory: 16131 loss: 1.4961 loss_prob: 0.8397 loss_thr: 0.5185 loss_db: 0.1378 2022/10/26 02:50:38 - mmengine - INFO - Epoch(train) [529][40/63] lr: 2.0969e-03 eta: 9:26:01 time: 0.5165 data_time: 0.0068 memory: 16131 loss: 1.5058 loss_prob: 0.8490 loss_thr: 0.5162 loss_db: 0.1405 2022/10/26 02:50:40 - mmengine - INFO - Epoch(train) [529][45/63] lr: 2.0969e-03 eta: 9:26:01 time: 0.4968 data_time: 0.0101 memory: 16131 loss: 1.3831 loss_prob: 0.7701 loss_thr: 0.4862 loss_db: 0.1268 2022/10/26 02:50:43 - mmengine - INFO - Epoch(train) [529][50/63] lr: 2.0969e-03 eta: 9:25:49 time: 0.4978 data_time: 0.0249 memory: 16131 loss: 1.4208 loss_prob: 0.7870 loss_thr: 0.5008 loss_db: 0.1330 2022/10/26 02:50:46 - mmengine - INFO - Epoch(train) [529][55/63] lr: 2.0969e-03 eta: 9:25:49 time: 0.5149 data_time: 0.0289 memory: 16131 loss: 1.4127 loss_prob: 0.7822 loss_thr: 0.4976 loss_db: 0.1329 2022/10/26 02:50:48 - mmengine - INFO - Epoch(train) [529][60/63] lr: 2.0969e-03 eta: 9:25:37 time: 0.4996 data_time: 0.0148 memory: 16131 loss: 1.4238 loss_prob: 0.7847 loss_thr: 0.5059 loss_db: 0.1332 2022/10/26 02:50:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:50:54 - mmengine - INFO - Epoch(train) [530][5/63] lr: 2.0940e-03 eta: 9:25:37 time: 0.6742 data_time: 0.1716 memory: 16131 loss: 1.4719 loss_prob: 0.8384 loss_thr: 0.4902 loss_db: 0.1433 2022/10/26 02:50:57 - mmengine - INFO - Epoch(train) [530][10/63] lr: 2.0940e-03 eta: 9:25:24 time: 0.8106 data_time: 0.1707 memory: 16131 loss: 1.3906 loss_prob: 0.7809 loss_thr: 0.4803 loss_db: 0.1294 2022/10/26 02:51:00 - mmengine - INFO - Epoch(train) [530][15/63] lr: 2.0940e-03 eta: 9:25:24 time: 0.6477 data_time: 0.0124 memory: 16131 loss: 1.2666 loss_prob: 0.6847 loss_thr: 0.4647 loss_db: 0.1173 2022/10/26 02:51:03 - mmengine - INFO - Epoch(train) [530][20/63] lr: 2.0940e-03 eta: 9:25:12 time: 0.5348 data_time: 0.0103 memory: 16131 loss: 1.5168 loss_prob: 0.8681 loss_thr: 0.5079 loss_db: 0.1408 2022/10/26 02:51:05 - mmengine - INFO - Epoch(train) [530][25/63] lr: 2.0940e-03 eta: 9:25:12 time: 0.4901 data_time: 0.0149 memory: 16131 loss: 1.6869 loss_prob: 0.9890 loss_thr: 0.5407 loss_db: 0.1571 2022/10/26 02:51:08 - mmengine - INFO - Epoch(train) [530][30/63] lr: 2.0940e-03 eta: 9:25:01 time: 0.5224 data_time: 0.0312 memory: 16131 loss: 1.4727 loss_prob: 0.8251 loss_thr: 0.5110 loss_db: 0.1367 2022/10/26 02:51:10 - mmengine - INFO - Epoch(train) [530][35/63] lr: 2.0940e-03 eta: 9:25:01 time: 0.5244 data_time: 0.0232 memory: 16131 loss: 1.4148 loss_prob: 0.7733 loss_thr: 0.5102 loss_db: 0.1312 2022/10/26 02:51:13 - mmengine - INFO - Epoch(train) [530][40/63] lr: 2.0940e-03 eta: 9:24:49 time: 0.4978 data_time: 0.0086 memory: 16131 loss: 1.5168 loss_prob: 0.8542 loss_thr: 0.5182 loss_db: 0.1444 2022/10/26 02:51:15 - mmengine - INFO - Epoch(train) [530][45/63] lr: 2.0940e-03 eta: 9:24:49 time: 0.5022 data_time: 0.0068 memory: 16131 loss: 1.5146 loss_prob: 0.8609 loss_thr: 0.5109 loss_db: 0.1429 2022/10/26 02:51:18 - mmengine - INFO - Epoch(train) [530][50/63] lr: 2.0940e-03 eta: 9:24:37 time: 0.5279 data_time: 0.0213 memory: 16131 loss: 1.4632 loss_prob: 0.8167 loss_thr: 0.5118 loss_db: 0.1347 2022/10/26 02:51:21 - mmengine - INFO - Epoch(train) [530][55/63] lr: 2.0940e-03 eta: 9:24:37 time: 0.5329 data_time: 0.0233 memory: 16131 loss: 1.4234 loss_prob: 0.7820 loss_thr: 0.5097 loss_db: 0.1317 2022/10/26 02:51:23 - mmengine - INFO - Epoch(train) [530][60/63] lr: 2.0940e-03 eta: 9:24:26 time: 0.5254 data_time: 0.0086 memory: 16131 loss: 1.4159 loss_prob: 0.7729 loss_thr: 0.5111 loss_db: 0.1320 2022/10/26 02:51:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:51:29 - mmengine - INFO - Epoch(train) [531][5/63] lr: 2.0912e-03 eta: 9:24:26 time: 0.7159 data_time: 0.2036 memory: 16131 loss: 1.4284 loss_prob: 0.7887 loss_thr: 0.5059 loss_db: 0.1338 2022/10/26 02:51:33 - mmengine - INFO - Epoch(train) [531][10/63] lr: 2.0912e-03 eta: 9:24:12 time: 0.7847 data_time: 0.2053 memory: 16131 loss: 1.5434 loss_prob: 0.8590 loss_thr: 0.5370 loss_db: 0.1473 2022/10/26 02:51:35 - mmengine - INFO - Epoch(train) [531][15/63] lr: 2.0912e-03 eta: 9:24:12 time: 0.5883 data_time: 0.0110 memory: 16131 loss: 1.5144 loss_prob: 0.8436 loss_thr: 0.5253 loss_db: 0.1455 2022/10/26 02:51:38 - mmengine - INFO - Epoch(train) [531][20/63] lr: 2.0912e-03 eta: 9:24:01 time: 0.5622 data_time: 0.0093 memory: 16131 loss: 1.4080 loss_prob: 0.7841 loss_thr: 0.4921 loss_db: 0.1319 2022/10/26 02:51:41 - mmengine - INFO - Epoch(train) [531][25/63] lr: 2.0912e-03 eta: 9:24:01 time: 0.5570 data_time: 0.0144 memory: 16131 loss: 1.4078 loss_prob: 0.7800 loss_thr: 0.4992 loss_db: 0.1285 2022/10/26 02:51:44 - mmengine - INFO - Epoch(train) [531][30/63] lr: 2.0912e-03 eta: 9:23:50 time: 0.5315 data_time: 0.0302 memory: 16131 loss: 1.4667 loss_prob: 0.8200 loss_thr: 0.5129 loss_db: 0.1338 2022/10/26 02:51:46 - mmengine - INFO - Epoch(train) [531][35/63] lr: 2.0912e-03 eta: 9:23:50 time: 0.5292 data_time: 0.0242 memory: 16131 loss: 1.5629 loss_prob: 0.8686 loss_thr: 0.5512 loss_db: 0.1430 2022/10/26 02:51:49 - mmengine - INFO - Epoch(train) [531][40/63] lr: 2.0912e-03 eta: 9:23:38 time: 0.5064 data_time: 0.0084 memory: 16131 loss: 1.5219 loss_prob: 0.8398 loss_thr: 0.5446 loss_db: 0.1375 2022/10/26 02:51:51 - mmengine - INFO - Epoch(train) [531][45/63] lr: 2.0912e-03 eta: 9:23:38 time: 0.4973 data_time: 0.0066 memory: 16131 loss: 1.4959 loss_prob: 0.8492 loss_thr: 0.5101 loss_db: 0.1366 2022/10/26 02:51:54 - mmengine - INFO - Epoch(train) [531][50/63] lr: 2.0912e-03 eta: 9:23:27 time: 0.5426 data_time: 0.0204 memory: 16131 loss: 1.5030 loss_prob: 0.8533 loss_thr: 0.5069 loss_db: 0.1427 2022/10/26 02:51:57 - mmengine - INFO - Epoch(train) [531][55/63] lr: 2.0912e-03 eta: 9:23:27 time: 0.5461 data_time: 0.0208 memory: 16131 loss: 1.6201 loss_prob: 0.9308 loss_thr: 0.5354 loss_db: 0.1538 2022/10/26 02:51:59 - mmengine - INFO - Epoch(train) [531][60/63] lr: 2.0912e-03 eta: 9:23:15 time: 0.4950 data_time: 0.0066 memory: 16131 loss: 1.5923 loss_prob: 0.9097 loss_thr: 0.5339 loss_db: 0.1487 2022/10/26 02:52:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:52:06 - mmengine - INFO - Epoch(train) [532][5/63] lr: 2.0884e-03 eta: 9:23:15 time: 0.7450 data_time: 0.2002 memory: 16131 loss: 1.6983 loss_prob: 1.0140 loss_thr: 0.5269 loss_db: 0.1574 2022/10/26 02:52:09 - mmengine - INFO - Epoch(train) [532][10/63] lr: 2.0884e-03 eta: 9:23:01 time: 0.8062 data_time: 0.1991 memory: 16131 loss: 1.6346 loss_prob: 0.9693 loss_thr: 0.5178 loss_db: 0.1475 2022/10/26 02:52:11 - mmengine - INFO - Epoch(train) [532][15/63] lr: 2.0884e-03 eta: 9:23:01 time: 0.5628 data_time: 0.0065 memory: 16131 loss: 1.4121 loss_prob: 0.7716 loss_thr: 0.5127 loss_db: 0.1278 2022/10/26 02:52:14 - mmengine - INFO - Epoch(train) [532][20/63] lr: 2.0884e-03 eta: 9:22:50 time: 0.5346 data_time: 0.0064 memory: 16131 loss: 1.4160 loss_prob: 0.7657 loss_thr: 0.5216 loss_db: 0.1287 2022/10/26 02:52:17 - mmengine - INFO - Epoch(train) [532][25/63] lr: 2.0884e-03 eta: 9:22:50 time: 0.5410 data_time: 0.0250 memory: 16131 loss: 1.3496 loss_prob: 0.7324 loss_thr: 0.4917 loss_db: 0.1255 2022/10/26 02:52:19 - mmengine - INFO - Epoch(train) [532][30/63] lr: 2.0884e-03 eta: 9:22:39 time: 0.5269 data_time: 0.0356 memory: 16131 loss: 1.4237 loss_prob: 0.7925 loss_thr: 0.5002 loss_db: 0.1309 2022/10/26 02:52:22 - mmengine - INFO - Epoch(train) [532][35/63] lr: 2.0884e-03 eta: 9:22:39 time: 0.5095 data_time: 0.0150 memory: 16131 loss: 1.3928 loss_prob: 0.7736 loss_thr: 0.4916 loss_db: 0.1277 2022/10/26 02:52:24 - mmengine - INFO - Epoch(train) [532][40/63] lr: 2.0884e-03 eta: 9:22:27 time: 0.5105 data_time: 0.0057 memory: 16131 loss: 1.3991 loss_prob: 0.7710 loss_thr: 0.4987 loss_db: 0.1295 2022/10/26 02:52:27 - mmengine - INFO - Epoch(train) [532][45/63] lr: 2.0884e-03 eta: 9:22:27 time: 0.4988 data_time: 0.0063 memory: 16131 loss: 1.5717 loss_prob: 0.8895 loss_thr: 0.5337 loss_db: 0.1486 2022/10/26 02:52:30 - mmengine - INFO - Epoch(train) [532][50/63] lr: 2.0884e-03 eta: 9:22:16 time: 0.5522 data_time: 0.0189 memory: 16131 loss: 1.5465 loss_prob: 0.8794 loss_thr: 0.5200 loss_db: 0.1471 2022/10/26 02:52:32 - mmengine - INFO - Epoch(train) [532][55/63] lr: 2.0884e-03 eta: 9:22:16 time: 0.5807 data_time: 0.0212 memory: 16131 loss: 1.5691 loss_prob: 0.8862 loss_thr: 0.5302 loss_db: 0.1527 2022/10/26 02:52:35 - mmengine - INFO - Epoch(train) [532][60/63] lr: 2.0884e-03 eta: 9:22:04 time: 0.5189 data_time: 0.0080 memory: 16131 loss: 1.6090 loss_prob: 0.9236 loss_thr: 0.5274 loss_db: 0.1580 2022/10/26 02:52:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:52:41 - mmengine - INFO - Epoch(train) [533][5/63] lr: 2.0856e-03 eta: 9:22:04 time: 0.7144 data_time: 0.1641 memory: 16131 loss: 1.5213 loss_prob: 0.8642 loss_thr: 0.5164 loss_db: 0.1407 2022/10/26 02:52:44 - mmengine - INFO - Epoch(train) [533][10/63] lr: 2.0856e-03 eta: 9:21:50 time: 0.7691 data_time: 0.1590 memory: 16131 loss: 1.6790 loss_prob: 0.9787 loss_thr: 0.5394 loss_db: 0.1609 2022/10/26 02:52:47 - mmengine - INFO - Epoch(train) [533][15/63] lr: 2.0856e-03 eta: 9:21:50 time: 0.6320 data_time: 0.0125 memory: 16131 loss: 1.7201 loss_prob: 1.0043 loss_thr: 0.5469 loss_db: 0.1689 2022/10/26 02:52:50 - mmengine - INFO - Epoch(train) [533][20/63] lr: 2.0856e-03 eta: 9:21:40 time: 0.5978 data_time: 0.0162 memory: 16131 loss: 1.5627 loss_prob: 0.8847 loss_thr: 0.5325 loss_db: 0.1455 2022/10/26 02:52:52 - mmengine - INFO - Epoch(train) [533][25/63] lr: 2.0856e-03 eta: 9:21:40 time: 0.4954 data_time: 0.0139 memory: 16131 loss: 1.4674 loss_prob: 0.8069 loss_thr: 0.5275 loss_db: 0.1330 2022/10/26 02:52:55 - mmengine - INFO - Epoch(train) [533][30/63] lr: 2.0856e-03 eta: 9:21:28 time: 0.5430 data_time: 0.0245 memory: 16131 loss: 1.3998 loss_prob: 0.7649 loss_thr: 0.5085 loss_db: 0.1264 2022/10/26 02:52:58 - mmengine - INFO - Epoch(train) [533][35/63] lr: 2.0856e-03 eta: 9:21:28 time: 0.5489 data_time: 0.0206 memory: 16131 loss: 1.4038 loss_prob: 0.7713 loss_thr: 0.5038 loss_db: 0.1287 2022/10/26 02:53:01 - mmengine - INFO - Epoch(train) [533][40/63] lr: 2.0856e-03 eta: 9:21:17 time: 0.5382 data_time: 0.0131 memory: 16131 loss: 1.5093 loss_prob: 0.8347 loss_thr: 0.5349 loss_db: 0.1397 2022/10/26 02:53:04 - mmengine - INFO - Epoch(train) [533][45/63] lr: 2.0856e-03 eta: 9:21:17 time: 0.5650 data_time: 0.0140 memory: 16131 loss: 1.4307 loss_prob: 0.7870 loss_thr: 0.5105 loss_db: 0.1332 2022/10/26 02:53:06 - mmengine - INFO - Epoch(train) [533][50/63] lr: 2.0856e-03 eta: 9:21:06 time: 0.5264 data_time: 0.0135 memory: 16131 loss: 1.3877 loss_prob: 0.7647 loss_thr: 0.4962 loss_db: 0.1268 2022/10/26 02:53:10 - mmengine - INFO - Epoch(train) [533][55/63] lr: 2.0856e-03 eta: 9:21:06 time: 0.5938 data_time: 0.0178 memory: 16131 loss: 1.4838 loss_prob: 0.8299 loss_thr: 0.5177 loss_db: 0.1362 2022/10/26 02:53:12 - mmengine - INFO - Epoch(train) [533][60/63] lr: 2.0856e-03 eta: 9:20:55 time: 0.5882 data_time: 0.0125 memory: 16131 loss: 1.4792 loss_prob: 0.8189 loss_thr: 0.5207 loss_db: 0.1397 2022/10/26 02:53:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:53:17 - mmengine - INFO - Epoch(train) [534][5/63] lr: 2.0828e-03 eta: 9:20:55 time: 0.6367 data_time: 0.1766 memory: 16131 loss: 1.4540 loss_prob: 0.8161 loss_thr: 0.4986 loss_db: 0.1392 2022/10/26 02:53:20 - mmengine - INFO - Epoch(train) [534][10/63] lr: 2.0828e-03 eta: 9:20:40 time: 0.6835 data_time: 0.1781 memory: 16131 loss: 1.3650 loss_prob: 0.7481 loss_thr: 0.4908 loss_db: 0.1261 2022/10/26 02:53:23 - mmengine - INFO - Epoch(train) [534][15/63] lr: 2.0828e-03 eta: 9:20:40 time: 0.5378 data_time: 0.0176 memory: 16131 loss: 1.3565 loss_prob: 0.7429 loss_thr: 0.4888 loss_db: 0.1247 2022/10/26 02:53:25 - mmengine - INFO - Epoch(train) [534][20/63] lr: 2.0828e-03 eta: 9:20:29 time: 0.5449 data_time: 0.0114 memory: 16131 loss: 1.4463 loss_prob: 0.8086 loss_thr: 0.5004 loss_db: 0.1373 2022/10/26 02:53:28 - mmengine - INFO - Epoch(train) [534][25/63] lr: 2.0828e-03 eta: 9:20:29 time: 0.5491 data_time: 0.0238 memory: 16131 loss: 1.3537 loss_prob: 0.7442 loss_thr: 0.4840 loss_db: 0.1254 2022/10/26 02:53:31 - mmengine - INFO - Epoch(train) [534][30/63] lr: 2.0828e-03 eta: 9:20:18 time: 0.5490 data_time: 0.0221 memory: 16131 loss: 1.2516 loss_prob: 0.6783 loss_thr: 0.4603 loss_db: 0.1130 2022/10/26 02:53:34 - mmengine - INFO - Epoch(train) [534][35/63] lr: 2.0828e-03 eta: 9:20:18 time: 0.5470 data_time: 0.0134 memory: 16131 loss: 1.3679 loss_prob: 0.7482 loss_thr: 0.4929 loss_db: 0.1268 2022/10/26 02:53:36 - mmengine - INFO - Epoch(train) [534][40/63] lr: 2.0828e-03 eta: 9:20:06 time: 0.5183 data_time: 0.0159 memory: 16131 loss: 1.4206 loss_prob: 0.7851 loss_thr: 0.5042 loss_db: 0.1312 2022/10/26 02:53:39 - mmengine - INFO - Epoch(train) [534][45/63] lr: 2.0828e-03 eta: 9:20:06 time: 0.5166 data_time: 0.0074 memory: 16131 loss: 1.3897 loss_prob: 0.7717 loss_thr: 0.4887 loss_db: 0.1293 2022/10/26 02:53:41 - mmengine - INFO - Epoch(train) [534][50/63] lr: 2.0828e-03 eta: 9:19:55 time: 0.5215 data_time: 0.0166 memory: 16131 loss: 1.4217 loss_prob: 0.7840 loss_thr: 0.5048 loss_db: 0.1329 2022/10/26 02:53:44 - mmengine - INFO - Epoch(train) [534][55/63] lr: 2.0828e-03 eta: 9:19:55 time: 0.4905 data_time: 0.0163 memory: 16131 loss: 1.4367 loss_prob: 0.7910 loss_thr: 0.5117 loss_db: 0.1340 2022/10/26 02:53:46 - mmengine - INFO - Epoch(train) [534][60/63] lr: 2.0828e-03 eta: 9:19:43 time: 0.5029 data_time: 0.0096 memory: 16131 loss: 1.4182 loss_prob: 0.7934 loss_thr: 0.4899 loss_db: 0.1349 2022/10/26 02:53:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:53:53 - mmengine - INFO - Epoch(train) [535][5/63] lr: 2.0800e-03 eta: 9:19:43 time: 0.7399 data_time: 0.1742 memory: 16131 loss: 1.4161 loss_prob: 0.7799 loss_thr: 0.5061 loss_db: 0.1301 2022/10/26 02:53:55 - mmengine - INFO - Epoch(train) [535][10/63] lr: 2.0800e-03 eta: 9:19:29 time: 0.7653 data_time: 0.1735 memory: 16131 loss: 1.4713 loss_prob: 0.8277 loss_thr: 0.5050 loss_db: 0.1386 2022/10/26 02:53:58 - mmengine - INFO - Epoch(train) [535][15/63] lr: 2.0800e-03 eta: 9:19:29 time: 0.5276 data_time: 0.0085 memory: 16131 loss: 1.4658 loss_prob: 0.8281 loss_thr: 0.5011 loss_db: 0.1366 2022/10/26 02:54:00 - mmengine - INFO - Epoch(train) [535][20/63] lr: 2.0800e-03 eta: 9:19:17 time: 0.4927 data_time: 0.0070 memory: 16131 loss: 1.4240 loss_prob: 0.7879 loss_thr: 0.5046 loss_db: 0.1315 2022/10/26 02:54:03 - mmengine - INFO - Epoch(train) [535][25/63] lr: 2.0800e-03 eta: 9:19:17 time: 0.5397 data_time: 0.0077 memory: 16131 loss: 1.4063 loss_prob: 0.7688 loss_thr: 0.5061 loss_db: 0.1315 2022/10/26 02:54:06 - mmengine - INFO - Epoch(train) [535][30/63] lr: 2.0800e-03 eta: 9:19:07 time: 0.5676 data_time: 0.0311 memory: 16131 loss: 1.3030 loss_prob: 0.7032 loss_thr: 0.4790 loss_db: 0.1209 2022/10/26 02:54:09 - mmengine - INFO - Epoch(train) [535][35/63] lr: 2.0800e-03 eta: 9:19:07 time: 0.5556 data_time: 0.0291 memory: 16131 loss: 1.2977 loss_prob: 0.7022 loss_thr: 0.4748 loss_db: 0.1207 2022/10/26 02:54:11 - mmengine - INFO - Epoch(train) [535][40/63] lr: 2.0800e-03 eta: 9:18:55 time: 0.5208 data_time: 0.0070 memory: 16131 loss: 1.4943 loss_prob: 0.8429 loss_thr: 0.5131 loss_db: 0.1383 2022/10/26 02:54:14 - mmengine - INFO - Epoch(train) [535][45/63] lr: 2.0800e-03 eta: 9:18:55 time: 0.4847 data_time: 0.0060 memory: 16131 loss: 1.7249 loss_prob: 1.0332 loss_thr: 0.5308 loss_db: 0.1610 2022/10/26 02:54:16 - mmengine - INFO - Epoch(train) [535][50/63] lr: 2.0800e-03 eta: 9:18:43 time: 0.5137 data_time: 0.0114 memory: 16131 loss: 1.8196 loss_prob: 1.1011 loss_thr: 0.5404 loss_db: 0.1781 2022/10/26 02:54:19 - mmengine - INFO - Epoch(train) [535][55/63] lr: 2.0800e-03 eta: 9:18:43 time: 0.5384 data_time: 0.0212 memory: 16131 loss: 1.6871 loss_prob: 0.9897 loss_thr: 0.5352 loss_db: 0.1623 2022/10/26 02:54:22 - mmengine - INFO - Epoch(train) [535][60/63] lr: 2.0800e-03 eta: 9:18:32 time: 0.5348 data_time: 0.0177 memory: 16131 loss: 1.6637 loss_prob: 0.9751 loss_thr: 0.5344 loss_db: 0.1541 2022/10/26 02:54:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:54:28 - mmengine - INFO - Epoch(train) [536][5/63] lr: 2.0772e-03 eta: 9:18:32 time: 0.7090 data_time: 0.1607 memory: 16131 loss: 1.5555 loss_prob: 0.8848 loss_thr: 0.5181 loss_db: 0.1527 2022/10/26 02:54:31 - mmengine - INFO - Epoch(train) [536][10/63] lr: 2.0772e-03 eta: 9:18:18 time: 0.7577 data_time: 0.1637 memory: 16131 loss: 1.5438 loss_prob: 0.8839 loss_thr: 0.5093 loss_db: 0.1507 2022/10/26 02:54:33 - mmengine - INFO - Epoch(train) [536][15/63] lr: 2.0772e-03 eta: 9:18:18 time: 0.5282 data_time: 0.0110 memory: 16131 loss: 1.5835 loss_prob: 0.9094 loss_thr: 0.5230 loss_db: 0.1511 2022/10/26 02:54:36 - mmengine - INFO - Epoch(train) [536][20/63] lr: 2.0772e-03 eta: 9:18:07 time: 0.5347 data_time: 0.0061 memory: 16131 loss: 1.6699 loss_prob: 0.9661 loss_thr: 0.5391 loss_db: 0.1648 2022/10/26 02:54:39 - mmengine - INFO - Epoch(train) [536][25/63] lr: 2.0772e-03 eta: 9:18:07 time: 0.5510 data_time: 0.0296 memory: 16131 loss: 1.5909 loss_prob: 0.8974 loss_thr: 0.5382 loss_db: 0.1552 2022/10/26 02:54:42 - mmengine - INFO - Epoch(train) [536][30/63] lr: 2.0772e-03 eta: 9:17:57 time: 0.6528 data_time: 0.0409 memory: 16131 loss: 1.5356 loss_prob: 0.8611 loss_thr: 0.5318 loss_db: 0.1426 2022/10/26 02:54:45 - mmengine - INFO - Epoch(train) [536][35/63] lr: 2.0772e-03 eta: 9:17:57 time: 0.6227 data_time: 0.0164 memory: 16131 loss: 1.4557 loss_prob: 0.8132 loss_thr: 0.5064 loss_db: 0.1361 2022/10/26 02:54:48 - mmengine - INFO - Epoch(train) [536][40/63] lr: 2.0772e-03 eta: 9:17:46 time: 0.5286 data_time: 0.0064 memory: 16131 loss: 1.3494 loss_prob: 0.7314 loss_thr: 0.4931 loss_db: 0.1250 2022/10/26 02:54:50 - mmengine - INFO - Epoch(train) [536][45/63] lr: 2.0772e-03 eta: 9:17:46 time: 0.5482 data_time: 0.0068 memory: 16131 loss: 1.4553 loss_prob: 0.8054 loss_thr: 0.5162 loss_db: 0.1337 2022/10/26 02:54:53 - mmengine - INFO - Epoch(train) [536][50/63] lr: 2.0772e-03 eta: 9:17:35 time: 0.5341 data_time: 0.0180 memory: 16131 loss: 1.4526 loss_prob: 0.8125 loss_thr: 0.5065 loss_db: 0.1335 2022/10/26 02:54:56 - mmengine - INFO - Epoch(train) [536][55/63] lr: 2.0772e-03 eta: 9:17:35 time: 0.5429 data_time: 0.0227 memory: 16131 loss: 1.3887 loss_prob: 0.7713 loss_thr: 0.4884 loss_db: 0.1290 2022/10/26 02:54:58 - mmengine - INFO - Epoch(train) [536][60/63] lr: 2.0772e-03 eta: 9:17:23 time: 0.5357 data_time: 0.0101 memory: 16131 loss: 1.5485 loss_prob: 0.8883 loss_thr: 0.5119 loss_db: 0.1483 2022/10/26 02:55:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:55:04 - mmengine - INFO - Epoch(train) [537][5/63] lr: 2.0743e-03 eta: 9:17:23 time: 0.7055 data_time: 0.1844 memory: 16131 loss: 1.3468 loss_prob: 0.7318 loss_thr: 0.4930 loss_db: 0.1221 2022/10/26 02:55:07 - mmengine - INFO - Epoch(train) [537][10/63] lr: 2.0743e-03 eta: 9:17:09 time: 0.7466 data_time: 0.1901 memory: 16131 loss: 1.4404 loss_prob: 0.8051 loss_thr: 0.5035 loss_db: 0.1319 2022/10/26 02:55:10 - mmengine - INFO - Epoch(train) [537][15/63] lr: 2.0743e-03 eta: 9:17:09 time: 0.5280 data_time: 0.0187 memory: 16131 loss: 1.5528 loss_prob: 0.8773 loss_thr: 0.5315 loss_db: 0.1441 2022/10/26 02:55:12 - mmengine - INFO - Epoch(train) [537][20/63] lr: 2.0743e-03 eta: 9:16:58 time: 0.4977 data_time: 0.0131 memory: 16131 loss: 1.5249 loss_prob: 0.8536 loss_thr: 0.5329 loss_db: 0.1384 2022/10/26 02:55:15 - mmengine - INFO - Epoch(train) [537][25/63] lr: 2.0743e-03 eta: 9:16:58 time: 0.5387 data_time: 0.0104 memory: 16131 loss: 1.5728 loss_prob: 0.8895 loss_thr: 0.5413 loss_db: 0.1420 2022/10/26 02:55:18 - mmengine - INFO - Epoch(train) [537][30/63] lr: 2.0743e-03 eta: 9:16:47 time: 0.6234 data_time: 0.0290 memory: 16131 loss: 1.5284 loss_prob: 0.8554 loss_thr: 0.5326 loss_db: 0.1404 2022/10/26 02:55:21 - mmengine - INFO - Epoch(train) [537][35/63] lr: 2.0743e-03 eta: 9:16:47 time: 0.5751 data_time: 0.0306 memory: 16131 loss: 1.4209 loss_prob: 0.7853 loss_thr: 0.5058 loss_db: 0.1298 2022/10/26 02:55:23 - mmengine - INFO - Epoch(train) [537][40/63] lr: 2.0743e-03 eta: 9:16:36 time: 0.4923 data_time: 0.0111 memory: 16131 loss: 1.3976 loss_prob: 0.7810 loss_thr: 0.4892 loss_db: 0.1274 2022/10/26 02:55:26 - mmengine - INFO - Epoch(train) [537][45/63] lr: 2.0743e-03 eta: 9:16:36 time: 0.5337 data_time: 0.0060 memory: 16131 loss: 1.4374 loss_prob: 0.8032 loss_thr: 0.4983 loss_db: 0.1359 2022/10/26 02:55:29 - mmengine - INFO - Epoch(train) [537][50/63] lr: 2.0743e-03 eta: 9:16:25 time: 0.5554 data_time: 0.0120 memory: 16131 loss: 1.5597 loss_prob: 0.8888 loss_thr: 0.5195 loss_db: 0.1514 2022/10/26 02:55:32 - mmengine - INFO - Epoch(train) [537][55/63] lr: 2.0743e-03 eta: 9:16:25 time: 0.5362 data_time: 0.0196 memory: 16131 loss: 1.5942 loss_prob: 0.9271 loss_thr: 0.5125 loss_db: 0.1545 2022/10/26 02:55:34 - mmengine - INFO - Epoch(train) [537][60/63] lr: 2.0743e-03 eta: 9:16:13 time: 0.5371 data_time: 0.0180 memory: 16131 loss: 1.4992 loss_prob: 0.8415 loss_thr: 0.5137 loss_db: 0.1439 2022/10/26 02:55:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:55:40 - mmengine - INFO - Epoch(train) [538][5/63] lr: 2.0715e-03 eta: 9:16:13 time: 0.7148 data_time: 0.2054 memory: 16131 loss: 1.3839 loss_prob: 0.7603 loss_thr: 0.4922 loss_db: 0.1313 2022/10/26 02:55:43 - mmengine - INFO - Epoch(train) [538][10/63] lr: 2.0715e-03 eta: 9:15:59 time: 0.7047 data_time: 0.2070 memory: 16131 loss: 1.3108 loss_prob: 0.7073 loss_thr: 0.4835 loss_db: 0.1201 2022/10/26 02:55:46 - mmengine - INFO - Epoch(train) [538][15/63] lr: 2.0715e-03 eta: 9:15:59 time: 0.5257 data_time: 0.0075 memory: 16131 loss: 1.4963 loss_prob: 0.8520 loss_thr: 0.5041 loss_db: 0.1402 2022/10/26 02:55:48 - mmengine - INFO - Epoch(train) [538][20/63] lr: 2.0715e-03 eta: 9:15:47 time: 0.5275 data_time: 0.0075 memory: 16131 loss: 1.6685 loss_prob: 0.9681 loss_thr: 0.5438 loss_db: 0.1566 2022/10/26 02:55:51 - mmengine - INFO - Epoch(train) [538][25/63] lr: 2.0715e-03 eta: 9:15:47 time: 0.4984 data_time: 0.0214 memory: 16131 loss: 1.8705 loss_prob: 1.1088 loss_thr: 0.5792 loss_db: 0.1824 2022/10/26 02:55:53 - mmengine - INFO - Epoch(train) [538][30/63] lr: 2.0715e-03 eta: 9:15:36 time: 0.5159 data_time: 0.0330 memory: 16131 loss: 2.0133 loss_prob: 1.2211 loss_thr: 0.5887 loss_db: 0.2034 2022/10/26 02:55:56 - mmengine - INFO - Epoch(train) [538][35/63] lr: 2.0715e-03 eta: 9:15:36 time: 0.5234 data_time: 0.0184 memory: 16131 loss: 1.8715 loss_prob: 1.1078 loss_thr: 0.5804 loss_db: 0.1832 2022/10/26 02:55:58 - mmengine - INFO - Epoch(train) [538][40/63] lr: 2.0715e-03 eta: 9:15:24 time: 0.5023 data_time: 0.0063 memory: 16131 loss: 1.7528 loss_prob: 1.0108 loss_thr: 0.5763 loss_db: 0.1658 2022/10/26 02:56:01 - mmengine - INFO - Epoch(train) [538][45/63] lr: 2.0715e-03 eta: 9:15:24 time: 0.5003 data_time: 0.0059 memory: 16131 loss: 1.6906 loss_prob: 0.9759 loss_thr: 0.5523 loss_db: 0.1624 2022/10/26 02:56:04 - mmengine - INFO - Epoch(train) [538][50/63] lr: 2.0715e-03 eta: 9:15:14 time: 0.5814 data_time: 0.0227 memory: 16131 loss: 1.7461 loss_prob: 1.0343 loss_thr: 0.5418 loss_db: 0.1700 2022/10/26 02:56:07 - mmengine - INFO - Epoch(train) [538][55/63] lr: 2.0715e-03 eta: 9:15:14 time: 0.5984 data_time: 0.0235 memory: 16131 loss: 1.6667 loss_prob: 0.9797 loss_thr: 0.5296 loss_db: 0.1574 2022/10/26 02:56:09 - mmengine - INFO - Epoch(train) [538][60/63] lr: 2.0715e-03 eta: 9:15:02 time: 0.5152 data_time: 0.0074 memory: 16131 loss: 1.5714 loss_prob: 0.9098 loss_thr: 0.5138 loss_db: 0.1477 2022/10/26 02:56:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:56:15 - mmengine - INFO - Epoch(train) [539][5/63] lr: 2.0687e-03 eta: 9:15:02 time: 0.6499 data_time: 0.1776 memory: 16131 loss: 1.5403 loss_prob: 0.8982 loss_thr: 0.5022 loss_db: 0.1399 2022/10/26 02:56:17 - mmengine - INFO - Epoch(train) [539][10/63] lr: 2.0687e-03 eta: 9:14:47 time: 0.6772 data_time: 0.1876 memory: 16131 loss: 1.5985 loss_prob: 0.9269 loss_thr: 0.5259 loss_db: 0.1458 2022/10/26 02:56:20 - mmengine - INFO - Epoch(train) [539][15/63] lr: 2.0687e-03 eta: 9:14:47 time: 0.5308 data_time: 0.0175 memory: 16131 loss: 1.5335 loss_prob: 0.8564 loss_thr: 0.5340 loss_db: 0.1432 2022/10/26 02:56:23 - mmengine - INFO - Epoch(train) [539][20/63] lr: 2.0687e-03 eta: 9:14:36 time: 0.5238 data_time: 0.0105 memory: 16131 loss: 1.4698 loss_prob: 0.8078 loss_thr: 0.5229 loss_db: 0.1390 2022/10/26 02:56:25 - mmengine - INFO - Epoch(train) [539][25/63] lr: 2.0687e-03 eta: 9:14:36 time: 0.5282 data_time: 0.0244 memory: 16131 loss: 1.4536 loss_prob: 0.8041 loss_thr: 0.5119 loss_db: 0.1377 2022/10/26 02:56:28 - mmengine - INFO - Epoch(train) [539][30/63] lr: 2.0687e-03 eta: 9:14:25 time: 0.5561 data_time: 0.0386 memory: 16131 loss: 1.3998 loss_prob: 0.7732 loss_thr: 0.4971 loss_db: 0.1295 2022/10/26 02:56:31 - mmengine - INFO - Epoch(train) [539][35/63] lr: 2.0687e-03 eta: 9:14:25 time: 0.5344 data_time: 0.0238 memory: 16131 loss: 1.4778 loss_prob: 0.8267 loss_thr: 0.5150 loss_db: 0.1361 2022/10/26 02:56:33 - mmengine - INFO - Epoch(train) [539][40/63] lr: 2.0687e-03 eta: 9:14:14 time: 0.5315 data_time: 0.0073 memory: 16131 loss: 1.6034 loss_prob: 0.9161 loss_thr: 0.5387 loss_db: 0.1487 2022/10/26 02:56:36 - mmengine - INFO - Epoch(train) [539][45/63] lr: 2.0687e-03 eta: 9:14:14 time: 0.5567 data_time: 0.0072 memory: 16131 loss: 1.4970 loss_prob: 0.8309 loss_thr: 0.5281 loss_db: 0.1381 2022/10/26 02:56:39 - mmengine - INFO - Epoch(train) [539][50/63] lr: 2.0687e-03 eta: 9:14:03 time: 0.5369 data_time: 0.0114 memory: 16131 loss: 1.4100 loss_prob: 0.7640 loss_thr: 0.5164 loss_db: 0.1296 2022/10/26 02:56:41 - mmengine - INFO - Epoch(train) [539][55/63] lr: 2.0687e-03 eta: 9:14:03 time: 0.5171 data_time: 0.0217 memory: 16131 loss: 1.3984 loss_prob: 0.7664 loss_thr: 0.5050 loss_db: 0.1269 2022/10/26 02:56:44 - mmengine - INFO - Epoch(train) [539][60/63] lr: 2.0687e-03 eta: 9:13:51 time: 0.5010 data_time: 0.0162 memory: 16131 loss: 1.3652 loss_prob: 0.7431 loss_thr: 0.4982 loss_db: 0.1239 2022/10/26 02:56:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:56:50 - mmengine - INFO - Epoch(train) [540][5/63] lr: 2.0659e-03 eta: 9:13:51 time: 0.7425 data_time: 0.1708 memory: 16131 loss: 1.3671 loss_prob: 0.7357 loss_thr: 0.5070 loss_db: 0.1243 2022/10/26 02:56:53 - mmengine - INFO - Epoch(train) [540][10/63] lr: 2.0659e-03 eta: 9:13:38 time: 0.8134 data_time: 0.1720 memory: 16131 loss: 1.3245 loss_prob: 0.7059 loss_thr: 0.4985 loss_db: 0.1201 2022/10/26 02:56:56 - mmengine - INFO - Epoch(train) [540][15/63] lr: 2.0659e-03 eta: 9:13:38 time: 0.5463 data_time: 0.0070 memory: 16131 loss: 1.3471 loss_prob: 0.7214 loss_thr: 0.5040 loss_db: 0.1217 2022/10/26 02:56:58 - mmengine - INFO - Epoch(train) [540][20/63] lr: 2.0659e-03 eta: 9:13:26 time: 0.4939 data_time: 0.0055 memory: 16131 loss: 1.3621 loss_prob: 0.7337 loss_thr: 0.5071 loss_db: 0.1213 2022/10/26 02:57:01 - mmengine - INFO - Epoch(train) [540][25/63] lr: 2.0659e-03 eta: 9:13:26 time: 0.5088 data_time: 0.0142 memory: 16131 loss: 1.3550 loss_prob: 0.7307 loss_thr: 0.5018 loss_db: 0.1225 2022/10/26 02:57:03 - mmengine - INFO - Epoch(train) [540][30/63] lr: 2.0659e-03 eta: 9:13:15 time: 0.5310 data_time: 0.0293 memory: 16131 loss: 1.4583 loss_prob: 0.7999 loss_thr: 0.5223 loss_db: 0.1361 2022/10/26 02:57:06 - mmengine - INFO - Epoch(train) [540][35/63] lr: 2.0659e-03 eta: 9:13:15 time: 0.5086 data_time: 0.0220 memory: 16131 loss: 1.4241 loss_prob: 0.7746 loss_thr: 0.5190 loss_db: 0.1305 2022/10/26 02:57:09 - mmengine - INFO - Epoch(train) [540][40/63] lr: 2.0659e-03 eta: 9:13:04 time: 0.5347 data_time: 0.0072 memory: 16131 loss: 1.3627 loss_prob: 0.7459 loss_thr: 0.4945 loss_db: 0.1223 2022/10/26 02:57:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:57:12 - mmengine - INFO - Epoch(train) [540][45/63] lr: 2.0659e-03 eta: 9:13:04 time: 0.6100 data_time: 0.0081 memory: 16131 loss: 1.4806 loss_prob: 0.8259 loss_thr: 0.5191 loss_db: 0.1356 2022/10/26 02:57:15 - mmengine - INFO - Epoch(train) [540][50/63] lr: 2.0659e-03 eta: 9:12:54 time: 0.6445 data_time: 0.0122 memory: 16131 loss: 1.4983 loss_prob: 0.8225 loss_thr: 0.5367 loss_db: 0.1391 2022/10/26 02:57:18 - mmengine - INFO - Epoch(train) [540][55/63] lr: 2.0659e-03 eta: 9:12:54 time: 0.6268 data_time: 0.0205 memory: 16131 loss: 1.3579 loss_prob: 0.7355 loss_thr: 0.4961 loss_db: 0.1264 2022/10/26 02:57:21 - mmengine - INFO - Epoch(train) [540][60/63] lr: 2.0659e-03 eta: 9:12:43 time: 0.5771 data_time: 0.0162 memory: 16131 loss: 1.4162 loss_prob: 0.7989 loss_thr: 0.4869 loss_db: 0.1304 2022/10/26 02:57:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:57:22 - mmengine - INFO - Saving checkpoint at 540 epochs 2022/10/26 02:57:29 - mmengine - INFO - Epoch(val) [540][5/32] eta: 9:12:43 time: 0.5557 data_time: 0.0604 memory: 16131 2022/10/26 02:57:31 - mmengine - INFO - Epoch(val) [540][10/32] eta: 0:00:12 time: 0.5764 data_time: 0.0873 memory: 15724 2022/10/26 02:57:34 - mmengine - INFO - Epoch(val) [540][15/32] eta: 0:00:12 time: 0.5293 data_time: 0.0414 memory: 15724 2022/10/26 02:57:37 - mmengine - INFO - Epoch(val) [540][20/32] eta: 0:00:06 time: 0.5347 data_time: 0.0466 memory: 15724 2022/10/26 02:57:40 - mmengine - INFO - Epoch(val) [540][25/32] eta: 0:00:06 time: 0.5566 data_time: 0.0472 memory: 15724 2022/10/26 02:57:42 - mmengine - INFO - Epoch(val) [540][30/32] eta: 0:00:01 time: 0.5245 data_time: 0.0200 memory: 15724 2022/10/26 02:57:43 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8459, precision: 0.7102, hmean: 0.7721 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8459, precision: 0.7743, hmean: 0.8086 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8435, precision: 0.8134, hmean: 0.8282 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8377, precision: 0.8517, hmean: 0.8447 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8093, precision: 0.8932, hmean: 0.8492 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6038, precision: 0.9450, hmean: 0.7368 2022/10/26 02:57:43 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0067, precision: 1.0000, hmean: 0.0134 2022/10/26 02:57:43 - mmengine - INFO - Epoch(val) [540][32/32] icdar/precision: 0.8932 icdar/recall: 0.8093 icdar/hmean: 0.8492 2022/10/26 02:57:48 - mmengine - INFO - Epoch(train) [541][5/63] lr: 2.0631e-03 eta: 0:00:01 time: 0.7126 data_time: 0.1953 memory: 16131 loss: 1.4229 loss_prob: 0.7983 loss_thr: 0.4912 loss_db: 0.1333 2022/10/26 02:57:51 - mmengine - INFO - Epoch(train) [541][10/63] lr: 2.0631e-03 eta: 9:12:31 time: 0.8445 data_time: 0.2017 memory: 16131 loss: 1.4131 loss_prob: 0.7882 loss_thr: 0.4905 loss_db: 0.1343 2022/10/26 02:57:54 - mmengine - INFO - Epoch(train) [541][15/63] lr: 2.0631e-03 eta: 9:12:31 time: 0.5927 data_time: 0.0111 memory: 16131 loss: 1.3337 loss_prob: 0.7277 loss_thr: 0.4800 loss_db: 0.1259 2022/10/26 02:57:56 - mmengine - INFO - Epoch(train) [541][20/63] lr: 2.0631e-03 eta: 9:12:19 time: 0.5181 data_time: 0.0061 memory: 16131 loss: 1.3421 loss_prob: 0.7305 loss_thr: 0.4907 loss_db: 0.1209 2022/10/26 02:57:59 - mmengine - INFO - Epoch(train) [541][25/63] lr: 2.0631e-03 eta: 9:12:19 time: 0.5541 data_time: 0.0282 memory: 16131 loss: 1.4785 loss_prob: 0.8168 loss_thr: 0.5254 loss_db: 0.1364 2022/10/26 02:58:02 - mmengine - INFO - Epoch(train) [541][30/63] lr: 2.0631e-03 eta: 9:12:08 time: 0.5316 data_time: 0.0276 memory: 16131 loss: 1.4980 loss_prob: 0.8276 loss_thr: 0.5309 loss_db: 0.1395 2022/10/26 02:58:04 - mmengine - INFO - Epoch(train) [541][35/63] lr: 2.0631e-03 eta: 9:12:08 time: 0.5086 data_time: 0.0132 memory: 16131 loss: 1.5299 loss_prob: 0.8653 loss_thr: 0.5186 loss_db: 0.1460 2022/10/26 02:58:07 - mmengine - INFO - Epoch(train) [541][40/63] lr: 2.0631e-03 eta: 9:11:57 time: 0.5452 data_time: 0.0127 memory: 16131 loss: 1.5095 loss_prob: 0.8713 loss_thr: 0.4876 loss_db: 0.1506 2022/10/26 02:58:10 - mmengine - INFO - Epoch(train) [541][45/63] lr: 2.0631e-03 eta: 9:11:57 time: 0.5828 data_time: 0.0077 memory: 16131 loss: 1.5689 loss_prob: 0.9271 loss_thr: 0.4909 loss_db: 0.1509 2022/10/26 02:58:14 - mmengine - INFO - Epoch(train) [541][50/63] lr: 2.0631e-03 eta: 9:11:47 time: 0.6456 data_time: 0.0238 memory: 16131 loss: 1.6280 loss_prob: 0.9511 loss_thr: 0.5263 loss_db: 0.1506 2022/10/26 02:58:16 - mmengine - INFO - Epoch(train) [541][55/63] lr: 2.0631e-03 eta: 9:11:47 time: 0.6335 data_time: 0.0217 memory: 16131 loss: 1.5384 loss_prob: 0.8652 loss_thr: 0.5282 loss_db: 0.1450 2022/10/26 02:58:19 - mmengine - INFO - Epoch(train) [541][60/63] lr: 2.0631e-03 eta: 9:11:36 time: 0.5240 data_time: 0.0109 memory: 16131 loss: 1.4697 loss_prob: 0.8167 loss_thr: 0.5137 loss_db: 0.1393 2022/10/26 02:58:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:58:25 - mmengine - INFO - Epoch(train) [542][5/63] lr: 2.0603e-03 eta: 9:11:36 time: 0.6926 data_time: 0.1480 memory: 16131 loss: 1.4852 loss_prob: 0.8325 loss_thr: 0.5129 loss_db: 0.1398 2022/10/26 02:58:29 - mmengine - INFO - Epoch(train) [542][10/63] lr: 2.0603e-03 eta: 9:11:24 time: 0.9140 data_time: 0.1603 memory: 16131 loss: 1.4201 loss_prob: 0.7944 loss_thr: 0.4918 loss_db: 0.1339 2022/10/26 02:58:32 - mmengine - INFO - Epoch(train) [542][15/63] lr: 2.0603e-03 eta: 9:11:24 time: 0.7552 data_time: 0.0196 memory: 16131 loss: 1.4098 loss_prob: 0.7762 loss_thr: 0.5030 loss_db: 0.1306 2022/10/26 02:58:35 - mmengine - INFO - Epoch(train) [542][20/63] lr: 2.0603e-03 eta: 9:11:13 time: 0.5590 data_time: 0.0085 memory: 16131 loss: 1.5332 loss_prob: 0.8653 loss_thr: 0.5163 loss_db: 0.1515 2022/10/26 02:58:37 - mmengine - INFO - Epoch(train) [542][25/63] lr: 2.0603e-03 eta: 9:11:13 time: 0.5161 data_time: 0.0127 memory: 16131 loss: 1.5193 loss_prob: 0.8581 loss_thr: 0.5141 loss_db: 0.1471 2022/10/26 02:58:42 - mmengine - INFO - Epoch(train) [542][30/63] lr: 2.0603e-03 eta: 9:11:05 time: 0.7589 data_time: 0.0440 memory: 16131 loss: 1.4780 loss_prob: 0.8114 loss_thr: 0.5324 loss_db: 0.1342 2022/10/26 02:58:49 - mmengine - INFO - Epoch(train) [542][35/63] lr: 2.0603e-03 eta: 9:11:05 time: 1.1158 data_time: 0.0453 memory: 16131 loss: 1.5788 loss_prob: 0.8873 loss_thr: 0.5414 loss_db: 0.1501 2022/10/26 02:58:53 - mmengine - INFO - Epoch(train) [542][40/63] lr: 2.0603e-03 eta: 9:11:00 time: 1.1005 data_time: 0.0145 memory: 16131 loss: 1.5681 loss_prob: 0.9031 loss_thr: 0.5152 loss_db: 0.1498 2022/10/26 02:58:57 - mmengine - INFO - Epoch(train) [542][45/63] lr: 2.0603e-03 eta: 9:11:00 time: 0.8364 data_time: 0.0071 memory: 16131 loss: 1.5767 loss_prob: 0.9163 loss_thr: 0.5132 loss_db: 0.1472 2022/10/26 02:59:00 - mmengine - INFO - Epoch(train) [542][50/63] lr: 2.0603e-03 eta: 9:10:51 time: 0.6736 data_time: 0.0282 memory: 16131 loss: 1.6205 loss_prob: 0.9201 loss_thr: 0.5474 loss_db: 0.1530 2022/10/26 02:59:03 - mmengine - INFO - Epoch(train) [542][55/63] lr: 2.0603e-03 eta: 9:10:51 time: 0.6027 data_time: 0.0355 memory: 16131 loss: 1.5631 loss_prob: 0.8693 loss_thr: 0.5449 loss_db: 0.1489 2022/10/26 02:59:06 - mmengine - INFO - Epoch(train) [542][60/63] lr: 2.0603e-03 eta: 9:10:41 time: 0.6253 data_time: 0.0157 memory: 16131 loss: 1.6757 loss_prob: 0.9656 loss_thr: 0.5539 loss_db: 0.1563 2022/10/26 02:59:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 02:59:17 - mmengine - INFO - Epoch(train) [543][5/63] lr: 2.0574e-03 eta: 9:10:41 time: 1.2119 data_time: 0.2460 memory: 16131 loss: 1.6436 loss_prob: 0.9483 loss_thr: 0.5411 loss_db: 0.1543 2022/10/26 02:59:22 - mmengine - INFO - Epoch(train) [543][10/63] lr: 2.0574e-03 eta: 9:10:36 time: 1.4575 data_time: 0.2473 memory: 16131 loss: 1.4750 loss_prob: 0.8159 loss_thr: 0.5202 loss_db: 0.1389 2022/10/26 02:59:25 - mmengine - INFO - Epoch(train) [543][15/63] lr: 2.0574e-03 eta: 9:10:36 time: 0.7927 data_time: 0.0131 memory: 16131 loss: 1.5637 loss_prob: 0.8721 loss_thr: 0.5429 loss_db: 0.1487 2022/10/26 02:59:28 - mmengine - INFO - Epoch(train) [543][20/63] lr: 2.0574e-03 eta: 9:10:25 time: 0.5927 data_time: 0.0139 memory: 16131 loss: 1.6230 loss_prob: 0.9350 loss_thr: 0.5293 loss_db: 0.1587 2022/10/26 02:59:32 - mmengine - INFO - Epoch(train) [543][25/63] lr: 2.0574e-03 eta: 9:10:25 time: 0.6702 data_time: 0.0264 memory: 16131 loss: 1.6174 loss_prob: 0.9473 loss_thr: 0.5172 loss_db: 0.1529 2022/10/26 02:59:36 - mmengine - INFO - Epoch(train) [543][30/63] lr: 2.0574e-03 eta: 9:10:16 time: 0.7339 data_time: 0.0424 memory: 16131 loss: 1.6801 loss_prob: 0.9894 loss_thr: 0.5328 loss_db: 0.1580 2022/10/26 02:59:40 - mmengine - INFO - Epoch(train) [543][35/63] lr: 2.0574e-03 eta: 9:10:16 time: 0.7500 data_time: 0.0314 memory: 16131 loss: 1.8205 loss_prob: 1.0868 loss_thr: 0.5560 loss_db: 0.1777 2022/10/26 02:59:44 - mmengine - INFO - Epoch(train) [543][40/63] lr: 2.0574e-03 eta: 9:10:09 time: 0.8178 data_time: 0.0112 memory: 16131 loss: 1.8676 loss_prob: 1.1110 loss_thr: 0.5788 loss_db: 0.1778 2022/10/26 02:59:47 - mmengine - INFO - Epoch(train) [543][45/63] lr: 2.0574e-03 eta: 9:10:09 time: 0.6996 data_time: 0.0054 memory: 16131 loss: 1.7902 loss_prob: 1.0451 loss_thr: 0.5776 loss_db: 0.1675 2022/10/26 02:59:50 - mmengine - INFO - Epoch(train) [543][50/63] lr: 2.0574e-03 eta: 9:09:58 time: 0.5629 data_time: 0.0234 memory: 16131 loss: 1.8896 loss_prob: 1.1207 loss_thr: 0.5900 loss_db: 0.1789 2022/10/26 02:59:53 - mmengine - INFO - Epoch(train) [543][55/63] lr: 2.0574e-03 eta: 9:09:58 time: 0.6375 data_time: 0.0278 memory: 16131 loss: 1.7294 loss_prob: 1.0081 loss_thr: 0.5586 loss_db: 0.1626 2022/10/26 02:59:56 - mmengine - INFO - Epoch(train) [543][60/63] lr: 2.0574e-03 eta: 9:09:48 time: 0.6271 data_time: 0.0158 memory: 16131 loss: 1.5671 loss_prob: 0.8945 loss_thr: 0.5225 loss_db: 0.1501 2022/10/26 02:59:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:00:03 - mmengine - INFO - Epoch(train) [544][5/63] lr: 2.0546e-03 eta: 9:09:48 time: 0.8514 data_time: 0.2346 memory: 16131 loss: 1.5055 loss_prob: 0.8430 loss_thr: 0.5178 loss_db: 0.1447 2022/10/26 03:00:09 - mmengine - INFO - Epoch(train) [544][10/63] lr: 2.0546e-03 eta: 9:09:39 time: 1.2008 data_time: 0.2374 memory: 16131 loss: 1.6257 loss_prob: 0.9277 loss_thr: 0.5446 loss_db: 0.1535 2022/10/26 03:00:12 - mmengine - INFO - Epoch(train) [544][15/63] lr: 2.0546e-03 eta: 9:09:39 time: 0.9121 data_time: 0.0170 memory: 16131 loss: 1.6583 loss_prob: 0.9425 loss_thr: 0.5612 loss_db: 0.1546 2022/10/26 03:00:17 - mmengine - INFO - Epoch(train) [544][20/63] lr: 2.0546e-03 eta: 9:09:31 time: 0.7308 data_time: 0.0121 memory: 16131 loss: 1.6591 loss_prob: 0.9455 loss_thr: 0.5567 loss_db: 0.1569 2022/10/26 03:00:20 - mmengine - INFO - Epoch(train) [544][25/63] lr: 2.0546e-03 eta: 9:09:31 time: 0.8052 data_time: 0.0424 memory: 16131 loss: 1.6158 loss_prob: 0.9325 loss_thr: 0.5293 loss_db: 0.1541 2022/10/26 03:00:23 - mmengine - INFO - Epoch(train) [544][30/63] lr: 2.0546e-03 eta: 9:09:21 time: 0.6541 data_time: 0.0431 memory: 16131 loss: 1.4360 loss_prob: 0.8122 loss_thr: 0.4893 loss_db: 0.1346 2022/10/26 03:00:28 - mmengine - INFO - Epoch(train) [544][35/63] lr: 2.0546e-03 eta: 9:09:21 time: 0.7215 data_time: 0.0091 memory: 16131 loss: 1.4898 loss_prob: 0.8383 loss_thr: 0.5138 loss_db: 0.1378 2022/10/26 03:00:31 - mmengine - INFO - Epoch(train) [544][40/63] lr: 2.0546e-03 eta: 9:09:13 time: 0.8214 data_time: 0.0117 memory: 16131 loss: 1.5558 loss_prob: 0.8671 loss_thr: 0.5440 loss_db: 0.1447 2022/10/26 03:00:34 - mmengine - INFO - Epoch(train) [544][45/63] lr: 2.0546e-03 eta: 9:09:13 time: 0.6803 data_time: 0.0113 memory: 16131 loss: 1.4541 loss_prob: 0.8026 loss_thr: 0.5181 loss_db: 0.1334 2022/10/26 03:00:39 - mmengine - INFO - Epoch(train) [544][50/63] lr: 2.0546e-03 eta: 9:09:05 time: 0.7824 data_time: 0.0224 memory: 16131 loss: 1.4659 loss_prob: 0.8137 loss_thr: 0.5144 loss_db: 0.1378 2022/10/26 03:00:43 - mmengine - INFO - Epoch(train) [544][55/63] lr: 2.0546e-03 eta: 9:09:05 time: 0.8144 data_time: 0.0213 memory: 16131 loss: 1.4433 loss_prob: 0.7991 loss_thr: 0.5094 loss_db: 0.1348 2022/10/26 03:00:45 - mmengine - INFO - Epoch(train) [544][60/63] lr: 2.0546e-03 eta: 9:08:55 time: 0.6025 data_time: 0.0087 memory: 16131 loss: 1.5198 loss_prob: 0.8629 loss_thr: 0.5183 loss_db: 0.1386 2022/10/26 03:00:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:00:53 - mmengine - INFO - Epoch(train) [545][5/63] lr: 2.0518e-03 eta: 9:08:55 time: 0.8943 data_time: 0.2081 memory: 16131 loss: 1.4539 loss_prob: 0.8237 loss_thr: 0.4955 loss_db: 0.1347 2022/10/26 03:00:57 - mmengine - INFO - Epoch(train) [545][10/63] lr: 2.0518e-03 eta: 9:08:45 time: 1.0790 data_time: 0.2162 memory: 16131 loss: 1.3281 loss_prob: 0.7244 loss_thr: 0.4832 loss_db: 0.1205 2022/10/26 03:01:01 - mmengine - INFO - Epoch(train) [545][15/63] lr: 2.0518e-03 eta: 9:08:45 time: 0.7650 data_time: 0.0196 memory: 16131 loss: 1.3704 loss_prob: 0.7574 loss_thr: 0.4856 loss_db: 0.1274 2022/10/26 03:01:04 - mmengine - INFO - Epoch(train) [545][20/63] lr: 2.0518e-03 eta: 9:08:35 time: 0.6233 data_time: 0.0071 memory: 16131 loss: 1.4615 loss_prob: 0.8040 loss_thr: 0.5199 loss_db: 0.1376 2022/10/26 03:01:06 - mmengine - INFO - Epoch(train) [545][25/63] lr: 2.0518e-03 eta: 9:08:35 time: 0.5473 data_time: 0.0212 memory: 16131 loss: 1.5932 loss_prob: 0.8831 loss_thr: 0.5641 loss_db: 0.1459 2022/10/26 03:01:09 - mmengine - INFO - Epoch(train) [545][30/63] lr: 2.0518e-03 eta: 9:08:24 time: 0.5272 data_time: 0.0346 memory: 16131 loss: 1.6363 loss_prob: 0.9277 loss_thr: 0.5590 loss_db: 0.1496 2022/10/26 03:01:12 - mmengine - INFO - Epoch(train) [545][35/63] lr: 2.0518e-03 eta: 9:08:24 time: 0.5402 data_time: 0.0244 memory: 16131 loss: 1.5306 loss_prob: 0.8745 loss_thr: 0.5113 loss_db: 0.1448 2022/10/26 03:01:14 - mmengine - INFO - Epoch(train) [545][40/63] lr: 2.0518e-03 eta: 9:08:13 time: 0.5426 data_time: 0.0101 memory: 16131 loss: 1.5354 loss_prob: 0.8849 loss_thr: 0.5017 loss_db: 0.1488 2022/10/26 03:01:17 - mmengine - INFO - Epoch(train) [545][45/63] lr: 2.0518e-03 eta: 9:08:13 time: 0.5410 data_time: 0.0067 memory: 16131 loss: 1.6465 loss_prob: 0.9841 loss_thr: 0.5082 loss_db: 0.1541 2022/10/26 03:01:20 - mmengine - INFO - Epoch(train) [545][50/63] lr: 2.0518e-03 eta: 9:08:02 time: 0.5337 data_time: 0.0227 memory: 16131 loss: 1.6718 loss_prob: 0.9912 loss_thr: 0.5196 loss_db: 0.1610 2022/10/26 03:01:23 - mmengine - INFO - Epoch(train) [545][55/63] lr: 2.0518e-03 eta: 9:08:02 time: 0.6291 data_time: 0.0286 memory: 16131 loss: 1.7102 loss_prob: 1.0006 loss_thr: 0.5456 loss_db: 0.1640 2022/10/26 03:01:29 - mmengine - INFO - Epoch(train) [545][60/63] lr: 2.0518e-03 eta: 9:07:55 time: 0.8917 data_time: 0.0167 memory: 16131 loss: 1.7403 loss_prob: 1.0258 loss_thr: 0.5538 loss_db: 0.1608 2022/10/26 03:01:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:01:37 - mmengine - INFO - Epoch(train) [546][5/63] lr: 2.0490e-03 eta: 9:07:55 time: 0.9430 data_time: 0.2610 memory: 16131 loss: 1.8191 loss_prob: 1.0913 loss_thr: 0.5543 loss_db: 0.1736 2022/10/26 03:01:39 - mmengine - INFO - Epoch(train) [546][10/63] lr: 2.0490e-03 eta: 9:07:42 time: 0.8396 data_time: 0.2601 memory: 16131 loss: 1.5060 loss_prob: 0.8479 loss_thr: 0.5175 loss_db: 0.1406 2022/10/26 03:01:42 - mmengine - INFO - Epoch(train) [546][15/63] lr: 2.0490e-03 eta: 9:07:42 time: 0.5373 data_time: 0.0069 memory: 16131 loss: 1.6183 loss_prob: 0.9305 loss_thr: 0.5409 loss_db: 0.1469 2022/10/26 03:01:47 - mmengine - INFO - Epoch(train) [546][20/63] lr: 2.0490e-03 eta: 9:07:34 time: 0.8054 data_time: 0.0079 memory: 16131 loss: 1.6724 loss_prob: 0.9653 loss_thr: 0.5518 loss_db: 0.1553 2022/10/26 03:01:56 - mmengine - INFO - Epoch(train) [546][25/63] lr: 2.0490e-03 eta: 9:07:34 time: 1.3473 data_time: 0.0301 memory: 16131 loss: 1.5361 loss_prob: 0.8648 loss_thr: 0.5272 loss_db: 0.1442 2022/10/26 03:02:01 - mmengine - INFO - Epoch(train) [546][30/63] lr: 2.0490e-03 eta: 9:07:33 time: 1.3537 data_time: 0.0535 memory: 16131 loss: 1.4695 loss_prob: 0.8196 loss_thr: 0.5134 loss_db: 0.1365 2022/10/26 03:02:05 - mmengine - INFO - Epoch(train) [546][35/63] lr: 2.0490e-03 eta: 9:07:33 time: 0.9376 data_time: 0.0321 memory: 16131 loss: 1.4952 loss_prob: 0.8400 loss_thr: 0.5157 loss_db: 0.1395 2022/10/26 03:02:08 - mmengine - INFO - Epoch(train) [546][40/63] lr: 2.0490e-03 eta: 9:07:24 time: 0.7010 data_time: 0.0081 memory: 16131 loss: 1.4277 loss_prob: 0.8055 loss_thr: 0.4886 loss_db: 0.1336 2022/10/26 03:02:14 - mmengine - INFO - Epoch(train) [546][45/63] lr: 2.0490e-03 eta: 9:07:24 time: 0.8537 data_time: 0.0100 memory: 16131 loss: 1.3570 loss_prob: 0.7567 loss_thr: 0.4726 loss_db: 0.1276 2022/10/26 03:02:18 - mmengine - INFO - Epoch(train) [546][50/63] lr: 2.0490e-03 eta: 9:07:18 time: 0.9587 data_time: 0.0226 memory: 16131 loss: 1.3966 loss_prob: 0.7640 loss_thr: 0.5032 loss_db: 0.1293 2022/10/26 03:02:21 - mmengine - INFO - Epoch(train) [546][55/63] lr: 2.0490e-03 eta: 9:07:18 time: 0.6987 data_time: 0.0248 memory: 16131 loss: 1.4579 loss_prob: 0.8045 loss_thr: 0.5209 loss_db: 0.1326 2022/10/26 03:02:25 - mmengine - INFO - Epoch(train) [546][60/63] lr: 2.0490e-03 eta: 9:07:09 time: 0.7456 data_time: 0.0122 memory: 16131 loss: 1.4623 loss_prob: 0.8113 loss_thr: 0.5154 loss_db: 0.1356 2022/10/26 03:02:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:02:34 - mmengine - INFO - Epoch(train) [547][5/63] lr: 2.0462e-03 eta: 9:07:09 time: 0.9889 data_time: 0.2034 memory: 16131 loss: 1.4823 loss_prob: 0.8219 loss_thr: 0.5217 loss_db: 0.1387 2022/10/26 03:02:37 - mmengine - INFO - Epoch(train) [547][10/63] lr: 2.0462e-03 eta: 9:06:59 time: 1.0137 data_time: 0.2058 memory: 16131 loss: 1.4516 loss_prob: 0.8200 loss_thr: 0.4962 loss_db: 0.1353 2022/10/26 03:02:40 - mmengine - INFO - Epoch(train) [547][15/63] lr: 2.0462e-03 eta: 9:06:59 time: 0.5991 data_time: 0.0119 memory: 16131 loss: 1.4110 loss_prob: 0.7987 loss_thr: 0.4822 loss_db: 0.1301 2022/10/26 03:02:42 - mmengine - INFO - Epoch(train) [547][20/63] lr: 2.0462e-03 eta: 9:06:48 time: 0.5503 data_time: 0.0085 memory: 16131 loss: 1.4368 loss_prob: 0.8008 loss_thr: 0.5007 loss_db: 0.1353 2022/10/26 03:02:45 - mmengine - INFO - Epoch(train) [547][25/63] lr: 2.0462e-03 eta: 9:06:48 time: 0.5352 data_time: 0.0154 memory: 16131 loss: 1.4884 loss_prob: 0.8314 loss_thr: 0.5177 loss_db: 0.1393 2022/10/26 03:02:48 - mmengine - INFO - Epoch(train) [547][30/63] lr: 2.0462e-03 eta: 9:06:37 time: 0.5714 data_time: 0.0422 memory: 16131 loss: 1.4808 loss_prob: 0.8373 loss_thr: 0.5034 loss_db: 0.1401 2022/10/26 03:02:50 - mmengine - INFO - Epoch(train) [547][35/63] lr: 2.0462e-03 eta: 9:06:37 time: 0.5541 data_time: 0.0341 memory: 16131 loss: 1.4504 loss_prob: 0.8283 loss_thr: 0.4809 loss_db: 0.1412 2022/10/26 03:02:53 - mmengine - INFO - Epoch(train) [547][40/63] lr: 2.0462e-03 eta: 9:06:26 time: 0.5215 data_time: 0.0107 memory: 16131 loss: 1.4319 loss_prob: 0.8129 loss_thr: 0.4840 loss_db: 0.1350 2022/10/26 03:02:56 - mmengine - INFO - Epoch(train) [547][45/63] lr: 2.0462e-03 eta: 9:06:26 time: 0.5150 data_time: 0.0089 memory: 16131 loss: 1.4440 loss_prob: 0.8096 loss_thr: 0.5010 loss_db: 0.1334 2022/10/26 03:02:59 - mmengine - INFO - Epoch(train) [547][50/63] lr: 2.0462e-03 eta: 9:06:15 time: 0.5450 data_time: 0.0189 memory: 16131 loss: 1.5049 loss_prob: 0.8443 loss_thr: 0.5210 loss_db: 0.1396 2022/10/26 03:03:03 - mmengine - INFO - Epoch(train) [547][55/63] lr: 2.0462e-03 eta: 9:06:15 time: 0.7101 data_time: 0.0309 memory: 16131 loss: 1.4365 loss_prob: 0.8079 loss_thr: 0.4976 loss_db: 0.1310 2022/10/26 03:03:07 - mmengine - INFO - Epoch(train) [547][60/63] lr: 2.0462e-03 eta: 9:06:07 time: 0.8159 data_time: 0.0277 memory: 16131 loss: 1.3307 loss_prob: 0.7403 loss_thr: 0.4733 loss_db: 0.1171 2022/10/26 03:03:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:03:13 - mmengine - INFO - Epoch(train) [548][5/63] lr: 2.0433e-03 eta: 9:06:07 time: 0.7227 data_time: 0.2165 memory: 16131 loss: 1.5034 loss_prob: 0.8308 loss_thr: 0.5319 loss_db: 0.1407 2022/10/26 03:03:16 - mmengine - INFO - Epoch(train) [548][10/63] lr: 2.0433e-03 eta: 9:05:53 time: 0.7544 data_time: 0.2153 memory: 16131 loss: 1.4348 loss_prob: 0.7857 loss_thr: 0.5145 loss_db: 0.1347 2022/10/26 03:03:18 - mmengine - INFO - Epoch(train) [548][15/63] lr: 2.0433e-03 eta: 9:05:53 time: 0.5379 data_time: 0.0077 memory: 16131 loss: 1.3277 loss_prob: 0.7185 loss_thr: 0.4881 loss_db: 0.1211 2022/10/26 03:03:21 - mmengine - INFO - Epoch(train) [548][20/63] lr: 2.0433e-03 eta: 9:05:42 time: 0.4944 data_time: 0.0080 memory: 16131 loss: 1.2790 loss_prob: 0.6895 loss_thr: 0.4733 loss_db: 0.1161 2022/10/26 03:03:24 - mmengine - INFO - Epoch(train) [548][25/63] lr: 2.0433e-03 eta: 9:05:42 time: 0.5468 data_time: 0.0457 memory: 16131 loss: 1.3899 loss_prob: 0.7576 loss_thr: 0.5040 loss_db: 0.1282 2022/10/26 03:03:26 - mmengine - INFO - Epoch(train) [548][30/63] lr: 2.0433e-03 eta: 9:05:31 time: 0.5393 data_time: 0.0455 memory: 16131 loss: 1.4310 loss_prob: 0.7797 loss_thr: 0.5196 loss_db: 0.1318 2022/10/26 03:03:29 - mmengine - INFO - Epoch(train) [548][35/63] lr: 2.0433e-03 eta: 9:05:31 time: 0.5342 data_time: 0.0066 memory: 16131 loss: 1.4177 loss_prob: 0.7887 loss_thr: 0.4956 loss_db: 0.1333 2022/10/26 03:03:31 - mmengine - INFO - Epoch(train) [548][40/63] lr: 2.0433e-03 eta: 9:05:20 time: 0.5245 data_time: 0.0065 memory: 16131 loss: 1.4132 loss_prob: 0.7971 loss_thr: 0.4797 loss_db: 0.1364 2022/10/26 03:03:34 - mmengine - INFO - Epoch(train) [548][45/63] lr: 2.0433e-03 eta: 9:05:20 time: 0.4945 data_time: 0.0097 memory: 16131 loss: 1.3586 loss_prob: 0.7619 loss_thr: 0.4674 loss_db: 0.1293 2022/10/26 03:03:37 - mmengine - INFO - Epoch(train) [548][50/63] lr: 2.0433e-03 eta: 9:05:08 time: 0.5242 data_time: 0.0231 memory: 16131 loss: 1.3538 loss_prob: 0.7553 loss_thr: 0.4695 loss_db: 0.1290 2022/10/26 03:03:40 - mmengine - INFO - Epoch(train) [548][55/63] lr: 2.0433e-03 eta: 9:05:08 time: 0.5649 data_time: 0.0205 memory: 16131 loss: 1.3230 loss_prob: 0.7221 loss_thr: 0.4760 loss_db: 0.1248 2022/10/26 03:03:42 - mmengine - INFO - Epoch(train) [548][60/63] lr: 2.0433e-03 eta: 9:04:57 time: 0.5459 data_time: 0.0065 memory: 16131 loss: 1.2958 loss_prob: 0.7002 loss_thr: 0.4767 loss_db: 0.1189 2022/10/26 03:03:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:03:48 - mmengine - INFO - Epoch(train) [549][5/63] lr: 2.0405e-03 eta: 9:04:57 time: 0.6602 data_time: 0.1631 memory: 16131 loss: 1.4203 loss_prob: 0.7955 loss_thr: 0.4920 loss_db: 0.1328 2022/10/26 03:03:50 - mmengine - INFO - Epoch(train) [549][10/63] lr: 2.0405e-03 eta: 9:04:43 time: 0.6949 data_time: 0.1688 memory: 16131 loss: 1.4358 loss_prob: 0.7747 loss_thr: 0.5289 loss_db: 0.1322 2022/10/26 03:03:53 - mmengine - INFO - Epoch(train) [549][15/63] lr: 2.0405e-03 eta: 9:04:43 time: 0.5105 data_time: 0.0115 memory: 16131 loss: 1.4279 loss_prob: 0.7666 loss_thr: 0.5302 loss_db: 0.1310 2022/10/26 03:03:55 - mmengine - INFO - Epoch(train) [549][20/63] lr: 2.0405e-03 eta: 9:04:32 time: 0.4981 data_time: 0.0086 memory: 16131 loss: 1.3964 loss_prob: 0.7591 loss_thr: 0.5065 loss_db: 0.1308 2022/10/26 03:03:58 - mmengine - INFO - Epoch(train) [549][25/63] lr: 2.0405e-03 eta: 9:04:32 time: 0.5513 data_time: 0.0224 memory: 16131 loss: 1.4137 loss_prob: 0.7775 loss_thr: 0.5044 loss_db: 0.1318 2022/10/26 03:04:01 - mmengine - INFO - Epoch(train) [549][30/63] lr: 2.0405e-03 eta: 9:04:21 time: 0.5627 data_time: 0.0273 memory: 16131 loss: 1.4434 loss_prob: 0.8018 loss_thr: 0.5065 loss_db: 0.1352 2022/10/26 03:04:03 - mmengine - INFO - Epoch(train) [549][35/63] lr: 2.0405e-03 eta: 9:04:21 time: 0.4985 data_time: 0.0130 memory: 16131 loss: 1.2793 loss_prob: 0.6904 loss_thr: 0.4718 loss_db: 0.1171 2022/10/26 03:04:06 - mmengine - INFO - Epoch(train) [549][40/63] lr: 2.0405e-03 eta: 9:04:09 time: 0.5016 data_time: 0.0138 memory: 16131 loss: 1.2569 loss_prob: 0.6765 loss_thr: 0.4650 loss_db: 0.1154 2022/10/26 03:04:08 - mmengine - INFO - Epoch(train) [549][45/63] lr: 2.0405e-03 eta: 9:04:09 time: 0.5070 data_time: 0.0145 memory: 16131 loss: 1.4188 loss_prob: 0.7861 loss_thr: 0.5008 loss_db: 0.1319 2022/10/26 03:04:11 - mmengine - INFO - Epoch(train) [549][50/63] lr: 2.0405e-03 eta: 9:03:58 time: 0.5050 data_time: 0.0163 memory: 16131 loss: 1.4352 loss_prob: 0.7981 loss_thr: 0.5051 loss_db: 0.1320 2022/10/26 03:04:13 - mmengine - INFO - Epoch(train) [549][55/63] lr: 2.0405e-03 eta: 9:03:58 time: 0.5132 data_time: 0.0225 memory: 16131 loss: 1.4002 loss_prob: 0.7582 loss_thr: 0.5130 loss_db: 0.1290 2022/10/26 03:04:16 - mmengine - INFO - Epoch(train) [549][60/63] lr: 2.0405e-03 eta: 9:03:47 time: 0.5186 data_time: 0.0118 memory: 16131 loss: 1.3279 loss_prob: 0.7142 loss_thr: 0.4923 loss_db: 0.1214 2022/10/26 03:04:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:04:22 - mmengine - INFO - Epoch(train) [550][5/63] lr: 2.0377e-03 eta: 9:03:47 time: 0.6792 data_time: 0.1776 memory: 16131 loss: 1.2334 loss_prob: 0.6627 loss_thr: 0.4590 loss_db: 0.1117 2022/10/26 03:04:25 - mmengine - INFO - Epoch(train) [550][10/63] lr: 2.0377e-03 eta: 9:03:33 time: 0.7226 data_time: 0.1774 memory: 16131 loss: 1.2849 loss_prob: 0.6987 loss_thr: 0.4656 loss_db: 0.1205 2022/10/26 03:04:27 - mmengine - INFO - Epoch(train) [550][15/63] lr: 2.0377e-03 eta: 9:03:33 time: 0.5507 data_time: 0.0103 memory: 16131 loss: 1.3453 loss_prob: 0.7311 loss_thr: 0.4897 loss_db: 0.1245 2022/10/26 03:04:30 - mmengine - INFO - Epoch(train) [550][20/63] lr: 2.0377e-03 eta: 9:03:22 time: 0.5463 data_time: 0.0090 memory: 16131 loss: 1.3124 loss_prob: 0.7025 loss_thr: 0.4908 loss_db: 0.1190 2022/10/26 03:04:33 - mmengine - INFO - Epoch(train) [550][25/63] lr: 2.0377e-03 eta: 9:03:22 time: 0.5354 data_time: 0.0134 memory: 16131 loss: 1.3335 loss_prob: 0.7288 loss_thr: 0.4816 loss_db: 0.1231 2022/10/26 03:04:35 - mmengine - INFO - Epoch(train) [550][30/63] lr: 2.0377e-03 eta: 9:03:11 time: 0.5420 data_time: 0.0247 memory: 16131 loss: 1.4020 loss_prob: 0.7781 loss_thr: 0.4934 loss_db: 0.1305 2022/10/26 03:04:38 - mmengine - INFO - Epoch(train) [550][35/63] lr: 2.0377e-03 eta: 9:03:11 time: 0.5150 data_time: 0.0160 memory: 16131 loss: 1.4921 loss_prob: 0.8655 loss_thr: 0.4925 loss_db: 0.1341 2022/10/26 03:04:40 - mmengine - INFO - Epoch(train) [550][40/63] lr: 2.0377e-03 eta: 9:02:59 time: 0.4989 data_time: 0.0161 memory: 16131 loss: 1.4643 loss_prob: 0.8517 loss_thr: 0.4822 loss_db: 0.1305 2022/10/26 03:04:43 - mmengine - INFO - Epoch(train) [550][45/63] lr: 2.0377e-03 eta: 9:02:59 time: 0.5065 data_time: 0.0165 memory: 16131 loss: 1.3884 loss_prob: 0.7679 loss_thr: 0.4910 loss_db: 0.1295 2022/10/26 03:04:46 - mmengine - INFO - Epoch(train) [550][50/63] lr: 2.0377e-03 eta: 9:02:48 time: 0.5484 data_time: 0.0175 memory: 16131 loss: 1.5010 loss_prob: 0.8473 loss_thr: 0.5126 loss_db: 0.1411 2022/10/26 03:04:48 - mmengine - INFO - Epoch(train) [550][55/63] lr: 2.0377e-03 eta: 9:02:48 time: 0.5518 data_time: 0.0205 memory: 16131 loss: 1.4710 loss_prob: 0.8343 loss_thr: 0.4986 loss_db: 0.1381 2022/10/26 03:04:51 - mmengine - INFO - Epoch(train) [550][60/63] lr: 2.0377e-03 eta: 9:02:37 time: 0.5051 data_time: 0.0086 memory: 16131 loss: 1.5012 loss_prob: 0.8420 loss_thr: 0.5143 loss_db: 0.1448 2022/10/26 03:04:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:04:57 - mmengine - INFO - Epoch(train) [551][5/63] lr: 2.0349e-03 eta: 9:02:37 time: 0.7050 data_time: 0.1522 memory: 16131 loss: 1.5029 loss_prob: 0.8345 loss_thr: 0.5307 loss_db: 0.1377 2022/10/26 03:05:00 - mmengine - INFO - Epoch(train) [551][10/63] lr: 2.0349e-03 eta: 9:02:23 time: 0.6798 data_time: 0.1618 memory: 16131 loss: 1.3865 loss_prob: 0.7641 loss_thr: 0.4955 loss_db: 0.1270 2022/10/26 03:05:02 - mmengine - INFO - Epoch(train) [551][15/63] lr: 2.0349e-03 eta: 9:02:23 time: 0.5117 data_time: 0.0187 memory: 16131 loss: 1.3845 loss_prob: 0.7541 loss_thr: 0.5022 loss_db: 0.1283 2022/10/26 03:05:05 - mmengine - INFO - Epoch(train) [551][20/63] lr: 2.0349e-03 eta: 9:02:11 time: 0.4901 data_time: 0.0059 memory: 16131 loss: 1.3066 loss_prob: 0.7027 loss_thr: 0.4839 loss_db: 0.1200 2022/10/26 03:05:07 - mmengine - INFO - Epoch(train) [551][25/63] lr: 2.0349e-03 eta: 9:02:11 time: 0.5020 data_time: 0.0086 memory: 16131 loss: 1.3450 loss_prob: 0.7376 loss_thr: 0.4820 loss_db: 0.1253 2022/10/26 03:05:10 - mmengine - INFO - Epoch(train) [551][30/63] lr: 2.0349e-03 eta: 9:02:00 time: 0.5570 data_time: 0.0197 memory: 16131 loss: 1.4108 loss_prob: 0.7808 loss_thr: 0.4983 loss_db: 0.1317 2022/10/26 03:05:13 - mmengine - INFO - Epoch(train) [551][35/63] lr: 2.0349e-03 eta: 9:02:00 time: 0.5535 data_time: 0.0278 memory: 16131 loss: 1.3092 loss_prob: 0.7186 loss_thr: 0.4699 loss_db: 0.1207 2022/10/26 03:05:15 - mmengine - INFO - Epoch(train) [551][40/63] lr: 2.0349e-03 eta: 9:01:49 time: 0.5002 data_time: 0.0163 memory: 16131 loss: 1.4444 loss_prob: 0.8145 loss_thr: 0.4937 loss_db: 0.1361 2022/10/26 03:05:18 - mmengine - INFO - Epoch(train) [551][45/63] lr: 2.0349e-03 eta: 9:01:49 time: 0.5215 data_time: 0.0045 memory: 16131 loss: 1.5102 loss_prob: 0.8533 loss_thr: 0.5123 loss_db: 0.1446 2022/10/26 03:05:21 - mmengine - INFO - Epoch(train) [551][50/63] lr: 2.0349e-03 eta: 9:01:39 time: 0.6024 data_time: 0.0095 memory: 16131 loss: 1.3840 loss_prob: 0.7584 loss_thr: 0.4969 loss_db: 0.1287 2022/10/26 03:05:24 - mmengine - INFO - Epoch(train) [551][55/63] lr: 2.0349e-03 eta: 9:01:39 time: 0.5764 data_time: 0.0193 memory: 16131 loss: 1.4093 loss_prob: 0.7643 loss_thr: 0.5172 loss_db: 0.1278 2022/10/26 03:05:26 - mmengine - INFO - Epoch(train) [551][60/63] lr: 2.0349e-03 eta: 9:01:27 time: 0.5028 data_time: 0.0170 memory: 16131 loss: 1.4620 loss_prob: 0.7971 loss_thr: 0.5307 loss_db: 0.1343 2022/10/26 03:05:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:05:33 - mmengine - INFO - Epoch(train) [552][5/63] lr: 2.0321e-03 eta: 9:01:27 time: 0.8280 data_time: 0.2248 memory: 16131 loss: 1.3466 loss_prob: 0.7326 loss_thr: 0.4877 loss_db: 0.1263 2022/10/26 03:05:36 - mmengine - INFO - Epoch(train) [552][10/63] lr: 2.0321e-03 eta: 9:01:15 time: 0.8509 data_time: 0.2241 memory: 16131 loss: 1.5116 loss_prob: 0.8653 loss_thr: 0.5014 loss_db: 0.1449 2022/10/26 03:05:39 - mmengine - INFO - Epoch(train) [552][15/63] lr: 2.0321e-03 eta: 9:01:15 time: 0.5312 data_time: 0.0055 memory: 16131 loss: 1.5399 loss_prob: 0.8952 loss_thr: 0.4996 loss_db: 0.1451 2022/10/26 03:05:41 - mmengine - INFO - Epoch(train) [552][20/63] lr: 2.0321e-03 eta: 9:01:04 time: 0.5412 data_time: 0.0076 memory: 16131 loss: 1.4359 loss_prob: 0.8041 loss_thr: 0.4967 loss_db: 0.1351 2022/10/26 03:05:44 - mmengine - INFO - Epoch(train) [552][25/63] lr: 2.0321e-03 eta: 9:01:04 time: 0.5207 data_time: 0.0325 memory: 16131 loss: 1.3271 loss_prob: 0.7254 loss_thr: 0.4756 loss_db: 0.1262 2022/10/26 03:05:47 - mmengine - INFO - Epoch(train) [552][30/63] lr: 2.0321e-03 eta: 9:00:53 time: 0.5280 data_time: 0.0429 memory: 16131 loss: 1.2660 loss_prob: 0.6953 loss_thr: 0.4529 loss_db: 0.1178 2022/10/26 03:05:49 - mmengine - INFO - Epoch(train) [552][35/63] lr: 2.0321e-03 eta: 9:00:53 time: 0.5310 data_time: 0.0170 memory: 16131 loss: 1.3775 loss_prob: 0.7562 loss_thr: 0.4987 loss_db: 0.1226 2022/10/26 03:05:52 - mmengine - INFO - Epoch(train) [552][40/63] lr: 2.0321e-03 eta: 9:00:42 time: 0.5159 data_time: 0.0046 memory: 16131 loss: 1.4119 loss_prob: 0.7712 loss_thr: 0.5115 loss_db: 0.1292 2022/10/26 03:05:54 - mmengine - INFO - Epoch(train) [552][45/63] lr: 2.0321e-03 eta: 9:00:42 time: 0.5132 data_time: 0.0050 memory: 16131 loss: 1.3729 loss_prob: 0.7585 loss_thr: 0.4846 loss_db: 0.1297 2022/10/26 03:05:57 - mmengine - INFO - Epoch(train) [552][50/63] lr: 2.0321e-03 eta: 9:00:31 time: 0.5306 data_time: 0.0189 memory: 16131 loss: 1.4004 loss_prob: 0.7781 loss_thr: 0.4900 loss_db: 0.1323 2022/10/26 03:06:00 - mmengine - INFO - Epoch(train) [552][55/63] lr: 2.0321e-03 eta: 9:00:31 time: 0.5273 data_time: 0.0263 memory: 16131 loss: 1.4434 loss_prob: 0.8059 loss_thr: 0.5022 loss_db: 0.1352 2022/10/26 03:06:02 - mmengine - INFO - Epoch(train) [552][60/63] lr: 2.0321e-03 eta: 9:00:20 time: 0.5374 data_time: 0.0135 memory: 16131 loss: 1.4687 loss_prob: 0.8204 loss_thr: 0.5127 loss_db: 0.1356 2022/10/26 03:06:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:06:08 - mmengine - INFO - Epoch(train) [553][5/63] lr: 2.0292e-03 eta: 9:00:20 time: 0.7051 data_time: 0.1721 memory: 16131 loss: 1.4479 loss_prob: 0.8156 loss_thr: 0.4939 loss_db: 0.1384 2022/10/26 03:06:11 - mmengine - INFO - Epoch(train) [553][10/63] lr: 2.0292e-03 eta: 9:00:06 time: 0.7177 data_time: 0.1787 memory: 16131 loss: 1.4199 loss_prob: 0.8021 loss_thr: 0.4858 loss_db: 0.1320 2022/10/26 03:06:14 - mmengine - INFO - Epoch(train) [553][15/63] lr: 2.0292e-03 eta: 9:00:06 time: 0.5249 data_time: 0.0166 memory: 16131 loss: 1.4328 loss_prob: 0.7945 loss_thr: 0.5051 loss_db: 0.1332 2022/10/26 03:06:17 - mmengine - INFO - Epoch(train) [553][20/63] lr: 2.0292e-03 eta: 8:59:55 time: 0.5357 data_time: 0.0084 memory: 16131 loss: 1.4405 loss_prob: 0.7865 loss_thr: 0.5215 loss_db: 0.1325 2022/10/26 03:06:20 - mmengine - INFO - Epoch(train) [553][25/63] lr: 2.0292e-03 eta: 8:59:55 time: 0.5851 data_time: 0.0216 memory: 16131 loss: 1.4010 loss_prob: 0.7639 loss_thr: 0.5066 loss_db: 0.1305 2022/10/26 03:06:22 - mmengine - INFO - Epoch(train) [553][30/63] lr: 2.0292e-03 eta: 8:59:44 time: 0.5460 data_time: 0.0271 memory: 16131 loss: 1.4292 loss_prob: 0.7947 loss_thr: 0.4988 loss_db: 0.1358 2022/10/26 03:06:25 - mmengine - INFO - Epoch(train) [553][35/63] lr: 2.0292e-03 eta: 8:59:44 time: 0.5069 data_time: 0.0188 memory: 16131 loss: 1.3863 loss_prob: 0.7665 loss_thr: 0.4890 loss_db: 0.1307 2022/10/26 03:06:27 - mmengine - INFO - Epoch(train) [553][40/63] lr: 2.0292e-03 eta: 8:59:32 time: 0.5038 data_time: 0.0134 memory: 16131 loss: 1.2896 loss_prob: 0.7113 loss_thr: 0.4580 loss_db: 0.1202 2022/10/26 03:06:30 - mmengine - INFO - Epoch(train) [553][45/63] lr: 2.0292e-03 eta: 8:59:32 time: 0.5411 data_time: 0.0078 memory: 16131 loss: 1.3785 loss_prob: 0.7733 loss_thr: 0.4823 loss_db: 0.1229 2022/10/26 03:06:33 - mmengine - INFO - Epoch(train) [553][50/63] lr: 2.0292e-03 eta: 8:59:22 time: 0.5900 data_time: 0.0160 memory: 16131 loss: 1.4551 loss_prob: 0.8095 loss_thr: 0.5172 loss_db: 0.1283 2022/10/26 03:06:36 - mmengine - INFO - Epoch(train) [553][55/63] lr: 2.0292e-03 eta: 8:59:22 time: 0.5780 data_time: 0.0189 memory: 16131 loss: 1.3868 loss_prob: 0.7523 loss_thr: 0.5071 loss_db: 0.1274 2022/10/26 03:06:38 - mmengine - INFO - Epoch(train) [553][60/63] lr: 2.0292e-03 eta: 8:59:11 time: 0.5392 data_time: 0.0135 memory: 16131 loss: 1.3967 loss_prob: 0.7553 loss_thr: 0.5106 loss_db: 0.1308 2022/10/26 03:06:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:06:45 - mmengine - INFO - Epoch(train) [554][5/63] lr: 2.0264e-03 eta: 8:59:11 time: 0.7441 data_time: 0.2143 memory: 16131 loss: 1.7707 loss_prob: 1.0610 loss_thr: 0.5429 loss_db: 0.1668 2022/10/26 03:06:48 - mmengine - INFO - Epoch(train) [554][10/63] lr: 2.0264e-03 eta: 8:58:58 time: 0.8027 data_time: 0.2146 memory: 16131 loss: 2.1489 loss_prob: 1.3861 loss_thr: 0.5450 loss_db: 0.2179 2022/10/26 03:06:51 - mmengine - INFO - Epoch(train) [554][15/63] lr: 2.0264e-03 eta: 8:58:58 time: 0.5938 data_time: 0.0126 memory: 16131 loss: 2.6805 loss_prob: 1.8150 loss_thr: 0.6108 loss_db: 0.2547 2022/10/26 03:06:53 - mmengine - INFO - Epoch(train) [554][20/63] lr: 2.0264e-03 eta: 8:58:47 time: 0.5427 data_time: 0.0117 memory: 16131 loss: 2.7594 loss_prob: 1.8435 loss_thr: 0.6624 loss_db: 0.2534 2022/10/26 03:06:56 - mmengine - INFO - Epoch(train) [554][25/63] lr: 2.0264e-03 eta: 8:58:47 time: 0.5389 data_time: 0.0237 memory: 16131 loss: 2.1668 loss_prob: 1.3444 loss_thr: 0.6160 loss_db: 0.2065 2022/10/26 03:06:59 - mmengine - INFO - Epoch(train) [554][30/63] lr: 2.0264e-03 eta: 8:58:36 time: 0.5384 data_time: 0.0215 memory: 16131 loss: 2.0224 loss_prob: 1.2261 loss_thr: 0.6000 loss_db: 0.1963 2022/10/26 03:07:01 - mmengine - INFO - Epoch(train) [554][35/63] lr: 2.0264e-03 eta: 8:58:36 time: 0.5041 data_time: 0.0094 memory: 16131 loss: 1.9578 loss_prob: 1.1602 loss_thr: 0.6096 loss_db: 0.1881 2022/10/26 03:07:04 - mmengine - INFO - Epoch(train) [554][40/63] lr: 2.0264e-03 eta: 8:58:25 time: 0.5326 data_time: 0.0162 memory: 16131 loss: 1.8815 loss_prob: 1.1010 loss_thr: 0.6030 loss_db: 0.1774 2022/10/26 03:07:06 - mmengine - INFO - Epoch(train) [554][45/63] lr: 2.0264e-03 eta: 8:58:25 time: 0.5283 data_time: 0.0120 memory: 16131 loss: 1.9983 loss_prob: 1.2147 loss_thr: 0.5880 loss_db: 0.1955 2022/10/26 03:07:09 - mmengine - INFO - Epoch(train) [554][50/63] lr: 2.0264e-03 eta: 8:58:14 time: 0.5128 data_time: 0.0176 memory: 16131 loss: 2.0872 loss_prob: 1.2829 loss_thr: 0.5931 loss_db: 0.2112 2022/10/26 03:07:11 - mmengine - INFO - Epoch(train) [554][55/63] lr: 2.0264e-03 eta: 8:58:14 time: 0.4998 data_time: 0.0174 memory: 16131 loss: 1.9729 loss_prob: 1.1848 loss_thr: 0.5890 loss_db: 0.1991 2022/10/26 03:07:14 - mmengine - INFO - Epoch(train) [554][60/63] lr: 2.0264e-03 eta: 8:58:03 time: 0.4998 data_time: 0.0107 memory: 16131 loss: 1.6608 loss_prob: 0.9517 loss_thr: 0.5545 loss_db: 0.1546 2022/10/26 03:07:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:07:20 - mmengine - INFO - Epoch(train) [555][5/63] lr: 2.0236e-03 eta: 8:58:03 time: 0.6646 data_time: 0.1856 memory: 16131 loss: 1.5755 loss_prob: 0.9045 loss_thr: 0.5227 loss_db: 0.1482 2022/10/26 03:07:22 - mmengine - INFO - Epoch(train) [555][10/63] lr: 2.0236e-03 eta: 8:57:49 time: 0.7240 data_time: 0.1905 memory: 16131 loss: 1.8331 loss_prob: 1.0824 loss_thr: 0.5756 loss_db: 0.1750 2022/10/26 03:07:25 - mmengine - INFO - Epoch(train) [555][15/63] lr: 2.0236e-03 eta: 8:57:49 time: 0.5597 data_time: 0.0187 memory: 16131 loss: 2.0207 loss_prob: 1.2085 loss_thr: 0.6141 loss_db: 0.1980 2022/10/26 03:07:28 - mmengine - INFO - Epoch(train) [555][20/63] lr: 2.0236e-03 eta: 8:57:38 time: 0.5667 data_time: 0.0097 memory: 16131 loss: 1.9680 loss_prob: 1.1561 loss_thr: 0.6190 loss_db: 0.1930 2022/10/26 03:07:31 - mmengine - INFO - Epoch(train) [555][25/63] lr: 2.0236e-03 eta: 8:57:38 time: 0.5856 data_time: 0.0252 memory: 16131 loss: 1.8445 loss_prob: 1.0761 loss_thr: 0.5925 loss_db: 0.1759 2022/10/26 03:07:34 - mmengine - INFO - Epoch(train) [555][30/63] lr: 2.0236e-03 eta: 8:57:28 time: 0.5874 data_time: 0.0347 memory: 16131 loss: 1.7999 loss_prob: 1.0559 loss_thr: 0.5721 loss_db: 0.1719 2022/10/26 03:07:37 - mmengine - INFO - Epoch(train) [555][35/63] lr: 2.0236e-03 eta: 8:57:28 time: 0.5400 data_time: 0.0184 memory: 16131 loss: 1.8446 loss_prob: 1.0953 loss_thr: 0.5729 loss_db: 0.1763 2022/10/26 03:07:39 - mmengine - INFO - Epoch(train) [555][40/63] lr: 2.0236e-03 eta: 8:57:17 time: 0.5023 data_time: 0.0116 memory: 16131 loss: 1.8482 loss_prob: 1.1096 loss_thr: 0.5598 loss_db: 0.1788 2022/10/26 03:07:41 - mmengine - INFO - Epoch(train) [555][45/63] lr: 2.0236e-03 eta: 8:57:17 time: 0.4832 data_time: 0.0079 memory: 16131 loss: 1.7667 loss_prob: 1.0509 loss_thr: 0.5425 loss_db: 0.1732 2022/10/26 03:07:44 - mmengine - INFO - Epoch(train) [555][50/63] lr: 2.0236e-03 eta: 8:57:06 time: 0.5322 data_time: 0.0120 memory: 16131 loss: 1.6704 loss_prob: 0.9777 loss_thr: 0.5283 loss_db: 0.1645 2022/10/26 03:07:47 - mmengine - INFO - Epoch(train) [555][55/63] lr: 2.0236e-03 eta: 8:57:06 time: 0.5857 data_time: 0.0200 memory: 16131 loss: 1.7109 loss_prob: 0.9729 loss_thr: 0.5745 loss_db: 0.1635 2022/10/26 03:07:50 - mmengine - INFO - Epoch(train) [555][60/63] lr: 2.0236e-03 eta: 8:56:55 time: 0.5220 data_time: 0.0148 memory: 16131 loss: 1.7474 loss_prob: 0.9901 loss_thr: 0.5908 loss_db: 0.1664 2022/10/26 03:07:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:07:56 - mmengine - INFO - Epoch(train) [556][5/63] lr: 2.0208e-03 eta: 8:56:55 time: 0.7095 data_time: 0.1675 memory: 16131 loss: 1.7501 loss_prob: 1.0376 loss_thr: 0.5453 loss_db: 0.1671 2022/10/26 03:07:59 - mmengine - INFO - Epoch(train) [556][10/63] lr: 2.0208e-03 eta: 8:56:41 time: 0.7478 data_time: 0.1813 memory: 16131 loss: 2.0321 loss_prob: 1.2867 loss_thr: 0.5457 loss_db: 0.1997 2022/10/26 03:08:01 - mmengine - INFO - Epoch(train) [556][15/63] lr: 2.0208e-03 eta: 8:56:41 time: 0.5567 data_time: 0.0235 memory: 16131 loss: 2.0309 loss_prob: 1.2629 loss_thr: 0.5629 loss_db: 0.2051 2022/10/26 03:08:04 - mmengine - INFO - Epoch(train) [556][20/63] lr: 2.0208e-03 eta: 8:56:30 time: 0.5383 data_time: 0.0129 memory: 16131 loss: 1.7998 loss_prob: 1.0725 loss_thr: 0.5438 loss_db: 0.1835 2022/10/26 03:08:07 - mmengine - INFO - Epoch(train) [556][25/63] lr: 2.0208e-03 eta: 8:56:30 time: 0.5519 data_time: 0.0150 memory: 16131 loss: 1.5889 loss_prob: 0.9138 loss_thr: 0.5215 loss_db: 0.1537 2022/10/26 03:08:10 - mmengine - INFO - Epoch(train) [556][30/63] lr: 2.0208e-03 eta: 8:56:20 time: 0.5953 data_time: 0.0342 memory: 16131 loss: 1.5653 loss_prob: 0.8820 loss_thr: 0.5383 loss_db: 0.1450 2022/10/26 03:08:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:08:12 - mmengine - INFO - Epoch(train) [556][35/63] lr: 2.0208e-03 eta: 8:56:20 time: 0.5561 data_time: 0.0290 memory: 16131 loss: 1.5982 loss_prob: 0.9187 loss_thr: 0.5288 loss_db: 0.1507 2022/10/26 03:08:15 - mmengine - INFO - Epoch(train) [556][40/63] lr: 2.0208e-03 eta: 8:56:09 time: 0.5148 data_time: 0.0046 memory: 16131 loss: 1.6095 loss_prob: 0.9297 loss_thr: 0.5242 loss_db: 0.1555 2022/10/26 03:08:18 - mmengine - INFO - Epoch(train) [556][45/63] lr: 2.0208e-03 eta: 8:56:09 time: 0.5239 data_time: 0.0047 memory: 16131 loss: 1.5359 loss_prob: 0.8777 loss_thr: 0.5136 loss_db: 0.1447 2022/10/26 03:08:20 - mmengine - INFO - Epoch(train) [556][50/63] lr: 2.0208e-03 eta: 8:55:58 time: 0.5095 data_time: 0.0079 memory: 16131 loss: 1.4701 loss_prob: 0.8257 loss_thr: 0.5069 loss_db: 0.1375 2022/10/26 03:08:23 - mmengine - INFO - Epoch(train) [556][55/63] lr: 2.0208e-03 eta: 8:55:58 time: 0.4949 data_time: 0.0224 memory: 16131 loss: 1.5136 loss_prob: 0.8428 loss_thr: 0.5287 loss_db: 0.1421 2022/10/26 03:08:25 - mmengine - INFO - Epoch(train) [556][60/63] lr: 2.0208e-03 eta: 8:55:46 time: 0.5068 data_time: 0.0199 memory: 16131 loss: 1.5027 loss_prob: 0.8412 loss_thr: 0.5224 loss_db: 0.1391 2022/10/26 03:08:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:08:31 - mmengine - INFO - Epoch(train) [557][5/63] lr: 2.0179e-03 eta: 8:55:46 time: 0.6769 data_time: 0.1806 memory: 16131 loss: 1.4157 loss_prob: 0.7922 loss_thr: 0.4933 loss_db: 0.1302 2022/10/26 03:08:34 - mmengine - INFO - Epoch(train) [557][10/63] lr: 2.0179e-03 eta: 8:55:32 time: 0.6901 data_time: 0.1810 memory: 16131 loss: 1.4244 loss_prob: 0.7858 loss_thr: 0.5103 loss_db: 0.1284 2022/10/26 03:08:36 - mmengine - INFO - Epoch(train) [557][15/63] lr: 2.0179e-03 eta: 8:55:32 time: 0.5122 data_time: 0.0060 memory: 16131 loss: 1.4960 loss_prob: 0.8200 loss_thr: 0.5397 loss_db: 0.1362 2022/10/26 03:08:39 - mmengine - INFO - Epoch(train) [557][20/63] lr: 2.0179e-03 eta: 8:55:21 time: 0.5045 data_time: 0.0069 memory: 16131 loss: 1.5006 loss_prob: 0.8331 loss_thr: 0.5268 loss_db: 0.1407 2022/10/26 03:08:41 - mmengine - INFO - Epoch(train) [557][25/63] lr: 2.0179e-03 eta: 8:55:21 time: 0.5460 data_time: 0.0247 memory: 16131 loss: 1.4981 loss_prob: 0.8473 loss_thr: 0.5124 loss_db: 0.1383 2022/10/26 03:08:44 - mmengine - INFO - Epoch(train) [557][30/63] lr: 2.0179e-03 eta: 8:55:10 time: 0.5401 data_time: 0.0361 memory: 16131 loss: 1.5682 loss_prob: 0.8942 loss_thr: 0.5266 loss_db: 0.1475 2022/10/26 03:08:46 - mmengine - INFO - Epoch(train) [557][35/63] lr: 2.0179e-03 eta: 8:55:10 time: 0.5006 data_time: 0.0197 memory: 16131 loss: 1.5281 loss_prob: 0.8533 loss_thr: 0.5292 loss_db: 0.1456 2022/10/26 03:08:49 - mmengine - INFO - Epoch(train) [557][40/63] lr: 2.0179e-03 eta: 8:54:59 time: 0.5049 data_time: 0.0074 memory: 16131 loss: 1.4080 loss_prob: 0.7800 loss_thr: 0.4942 loss_db: 0.1338 2022/10/26 03:08:52 - mmengine - INFO - Epoch(train) [557][45/63] lr: 2.0179e-03 eta: 8:54:59 time: 0.5186 data_time: 0.0071 memory: 16131 loss: 1.4170 loss_prob: 0.7923 loss_thr: 0.4909 loss_db: 0.1338 2022/10/26 03:08:54 - mmengine - INFO - Epoch(train) [557][50/63] lr: 2.0179e-03 eta: 8:54:48 time: 0.5212 data_time: 0.0168 memory: 16131 loss: 1.4218 loss_prob: 0.7895 loss_thr: 0.5007 loss_db: 0.1316 2022/10/26 03:08:57 - mmengine - INFO - Epoch(train) [557][55/63] lr: 2.0179e-03 eta: 8:54:48 time: 0.5710 data_time: 0.0235 memory: 16131 loss: 1.5284 loss_prob: 0.8557 loss_thr: 0.5317 loss_db: 0.1411 2022/10/26 03:09:00 - mmengine - INFO - Epoch(train) [557][60/63] lr: 2.0179e-03 eta: 8:54:37 time: 0.5627 data_time: 0.0146 memory: 16131 loss: 1.7919 loss_prob: 1.0702 loss_thr: 0.5558 loss_db: 0.1658 2022/10/26 03:09:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:09:06 - mmengine - INFO - Epoch(train) [558][5/63] lr: 2.0151e-03 eta: 8:54:37 time: 0.6775 data_time: 0.1859 memory: 16131 loss: 1.6385 loss_prob: 0.9684 loss_thr: 0.5190 loss_db: 0.1510 2022/10/26 03:09:08 - mmengine - INFO - Epoch(train) [558][10/63] lr: 2.0151e-03 eta: 8:54:23 time: 0.7170 data_time: 0.1893 memory: 16131 loss: 1.4659 loss_prob: 0.8324 loss_thr: 0.4925 loss_db: 0.1409 2022/10/26 03:09:11 - mmengine - INFO - Epoch(train) [558][15/63] lr: 2.0151e-03 eta: 8:54:23 time: 0.5497 data_time: 0.0118 memory: 16131 loss: 1.4269 loss_prob: 0.8018 loss_thr: 0.4918 loss_db: 0.1332 2022/10/26 03:09:14 - mmengine - INFO - Epoch(train) [558][20/63] lr: 2.0151e-03 eta: 8:54:12 time: 0.5222 data_time: 0.0056 memory: 16131 loss: 1.4093 loss_prob: 0.7628 loss_thr: 0.5193 loss_db: 0.1273 2022/10/26 03:09:17 - mmengine - INFO - Epoch(train) [558][25/63] lr: 2.0151e-03 eta: 8:54:12 time: 0.5329 data_time: 0.0380 memory: 16131 loss: 1.4410 loss_prob: 0.7791 loss_thr: 0.5292 loss_db: 0.1327 2022/10/26 03:09:19 - mmengine - INFO - Epoch(train) [558][30/63] lr: 2.0151e-03 eta: 8:54:02 time: 0.5579 data_time: 0.0405 memory: 16131 loss: 1.3923 loss_prob: 0.7690 loss_thr: 0.4946 loss_db: 0.1286 2022/10/26 03:09:22 - mmengine - INFO - Epoch(train) [558][35/63] lr: 2.0151e-03 eta: 8:54:02 time: 0.5472 data_time: 0.0108 memory: 16131 loss: 1.4685 loss_prob: 0.8320 loss_thr: 0.5002 loss_db: 0.1363 2022/10/26 03:09:25 - mmengine - INFO - Epoch(train) [558][40/63] lr: 2.0151e-03 eta: 8:53:51 time: 0.5287 data_time: 0.0093 memory: 16131 loss: 1.5552 loss_prob: 0.8960 loss_thr: 0.5169 loss_db: 0.1423 2022/10/26 03:09:27 - mmengine - INFO - Epoch(train) [558][45/63] lr: 2.0151e-03 eta: 8:53:51 time: 0.5119 data_time: 0.0074 memory: 16131 loss: 1.5031 loss_prob: 0.8462 loss_thr: 0.5221 loss_db: 0.1348 2022/10/26 03:09:30 - mmengine - INFO - Epoch(train) [558][50/63] lr: 2.0151e-03 eta: 8:53:40 time: 0.5325 data_time: 0.0269 memory: 16131 loss: 1.3868 loss_prob: 0.7540 loss_thr: 0.5063 loss_db: 0.1264 2022/10/26 03:09:32 - mmengine - INFO - Epoch(train) [558][55/63] lr: 2.0151e-03 eta: 8:53:40 time: 0.5340 data_time: 0.0281 memory: 16131 loss: 1.4274 loss_prob: 0.7741 loss_thr: 0.5197 loss_db: 0.1336 2022/10/26 03:09:35 - mmengine - INFO - Epoch(train) [558][60/63] lr: 2.0151e-03 eta: 8:53:29 time: 0.5050 data_time: 0.0096 memory: 16131 loss: 1.4947 loss_prob: 0.8265 loss_thr: 0.5267 loss_db: 0.1415 2022/10/26 03:09:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:09:41 - mmengine - INFO - Epoch(train) [559][5/63] lr: 2.0123e-03 eta: 8:53:29 time: 0.6860 data_time: 0.1942 memory: 16131 loss: 1.4451 loss_prob: 0.8062 loss_thr: 0.5048 loss_db: 0.1341 2022/10/26 03:09:43 - mmengine - INFO - Epoch(train) [559][10/63] lr: 2.0123e-03 eta: 8:53:15 time: 0.7067 data_time: 0.1947 memory: 16131 loss: 1.4321 loss_prob: 0.8021 loss_thr: 0.4963 loss_db: 0.1337 2022/10/26 03:09:46 - mmengine - INFO - Epoch(train) [559][15/63] lr: 2.0123e-03 eta: 8:53:15 time: 0.4988 data_time: 0.0069 memory: 16131 loss: 1.4139 loss_prob: 0.7789 loss_thr: 0.5038 loss_db: 0.1312 2022/10/26 03:09:48 - mmengine - INFO - Epoch(train) [559][20/63] lr: 2.0123e-03 eta: 8:53:03 time: 0.5019 data_time: 0.0068 memory: 16131 loss: 1.4703 loss_prob: 0.8101 loss_thr: 0.5251 loss_db: 0.1351 2022/10/26 03:09:51 - mmengine - INFO - Epoch(train) [559][25/63] lr: 2.0123e-03 eta: 8:53:03 time: 0.5225 data_time: 0.0215 memory: 16131 loss: 1.4996 loss_prob: 0.8298 loss_thr: 0.5333 loss_db: 0.1365 2022/10/26 03:09:54 - mmengine - INFO - Epoch(train) [559][30/63] lr: 2.0123e-03 eta: 8:52:53 time: 0.5618 data_time: 0.0302 memory: 16131 loss: 1.4230 loss_prob: 0.7942 loss_thr: 0.4975 loss_db: 0.1313 2022/10/26 03:09:56 - mmengine - INFO - Epoch(train) [559][35/63] lr: 2.0123e-03 eta: 8:52:53 time: 0.5509 data_time: 0.0158 memory: 16131 loss: 1.4555 loss_prob: 0.8172 loss_thr: 0.4996 loss_db: 0.1387 2022/10/26 03:09:59 - mmengine - INFO - Epoch(train) [559][40/63] lr: 2.0123e-03 eta: 8:52:42 time: 0.5304 data_time: 0.0098 memory: 16131 loss: 1.4676 loss_prob: 0.8134 loss_thr: 0.5158 loss_db: 0.1384 2022/10/26 03:10:02 - mmengine - INFO - Epoch(train) [559][45/63] lr: 2.0123e-03 eta: 8:52:42 time: 0.5217 data_time: 0.0092 memory: 16131 loss: 1.5054 loss_prob: 0.8426 loss_thr: 0.5220 loss_db: 0.1408 2022/10/26 03:10:04 - mmengine - INFO - Epoch(train) [559][50/63] lr: 2.0123e-03 eta: 8:52:31 time: 0.5239 data_time: 0.0196 memory: 16131 loss: 1.5550 loss_prob: 0.8794 loss_thr: 0.5267 loss_db: 0.1489 2022/10/26 03:10:07 - mmengine - INFO - Epoch(train) [559][55/63] lr: 2.0123e-03 eta: 8:52:31 time: 0.5238 data_time: 0.0198 memory: 16131 loss: 1.4421 loss_prob: 0.8120 loss_thr: 0.4950 loss_db: 0.1351 2022/10/26 03:10:10 - mmengine - INFO - Epoch(train) [559][60/63] lr: 2.0123e-03 eta: 8:52:20 time: 0.5182 data_time: 0.0089 memory: 16131 loss: 1.4733 loss_prob: 0.8248 loss_thr: 0.5130 loss_db: 0.1355 2022/10/26 03:10:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:10:16 - mmengine - INFO - Epoch(train) [560][5/63] lr: 2.0095e-03 eta: 8:52:20 time: 0.7032 data_time: 0.2162 memory: 16131 loss: 1.3900 loss_prob: 0.7672 loss_thr: 0.4937 loss_db: 0.1291 2022/10/26 03:10:19 - mmengine - INFO - Epoch(train) [560][10/63] lr: 2.0095e-03 eta: 8:52:07 time: 0.7873 data_time: 0.2177 memory: 16131 loss: 1.4169 loss_prob: 0.7820 loss_thr: 0.5011 loss_db: 0.1338 2022/10/26 03:10:21 - mmengine - INFO - Epoch(train) [560][15/63] lr: 2.0095e-03 eta: 8:52:07 time: 0.5658 data_time: 0.0106 memory: 16131 loss: 1.3699 loss_prob: 0.7523 loss_thr: 0.4903 loss_db: 0.1274 2022/10/26 03:10:24 - mmengine - INFO - Epoch(train) [560][20/63] lr: 2.0095e-03 eta: 8:51:56 time: 0.5359 data_time: 0.0082 memory: 16131 loss: 1.3140 loss_prob: 0.7221 loss_thr: 0.4687 loss_db: 0.1233 2022/10/26 03:10:27 - mmengine - INFO - Epoch(train) [560][25/63] lr: 2.0095e-03 eta: 8:51:56 time: 0.5666 data_time: 0.0309 memory: 16131 loss: 1.3353 loss_prob: 0.7290 loss_thr: 0.4825 loss_db: 0.1238 2022/10/26 03:10:29 - mmengine - INFO - Epoch(train) [560][30/63] lr: 2.0095e-03 eta: 8:51:45 time: 0.5366 data_time: 0.0403 memory: 16131 loss: 1.4115 loss_prob: 0.7736 loss_thr: 0.5095 loss_db: 0.1285 2022/10/26 03:10:32 - mmengine - INFO - Epoch(train) [560][35/63] lr: 2.0095e-03 eta: 8:51:45 time: 0.5213 data_time: 0.0159 memory: 16131 loss: 1.4919 loss_prob: 0.8524 loss_thr: 0.4980 loss_db: 0.1415 2022/10/26 03:10:35 - mmengine - INFO - Epoch(train) [560][40/63] lr: 2.0095e-03 eta: 8:51:35 time: 0.5583 data_time: 0.0081 memory: 16131 loss: 1.4864 loss_prob: 0.8500 loss_thr: 0.4917 loss_db: 0.1447 2022/10/26 03:10:38 - mmengine - INFO - Epoch(train) [560][45/63] lr: 2.0095e-03 eta: 8:51:35 time: 0.5595 data_time: 0.0117 memory: 16131 loss: 1.6639 loss_prob: 0.9695 loss_thr: 0.5341 loss_db: 0.1603 2022/10/26 03:10:40 - mmengine - INFO - Epoch(train) [560][50/63] lr: 2.0095e-03 eta: 8:51:24 time: 0.5415 data_time: 0.0256 memory: 16131 loss: 1.8288 loss_prob: 1.0876 loss_thr: 0.5659 loss_db: 0.1754 2022/10/26 03:10:43 - mmengine - INFO - Epoch(train) [560][55/63] lr: 2.0095e-03 eta: 8:51:24 time: 0.5234 data_time: 0.0276 memory: 16131 loss: 1.9015 loss_prob: 1.1106 loss_thr: 0.6120 loss_db: 0.1788 2022/10/26 03:10:46 - mmengine - INFO - Epoch(train) [560][60/63] lr: 2.0095e-03 eta: 8:51:13 time: 0.5094 data_time: 0.0109 memory: 16131 loss: 1.9635 loss_prob: 1.1468 loss_thr: 0.6279 loss_db: 0.1888 2022/10/26 03:10:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:10:47 - mmengine - INFO - Saving checkpoint at 560 epochs 2022/10/26 03:10:53 - mmengine - INFO - Epoch(val) [560][5/32] eta: 8:51:13 time: 0.5271 data_time: 0.0527 memory: 16131 2022/10/26 03:10:56 - mmengine - INFO - Epoch(val) [560][10/32] eta: 0:00:13 time: 0.6246 data_time: 0.0706 memory: 15724 2022/10/26 03:10:59 - mmengine - INFO - Epoch(val) [560][15/32] eta: 0:00:13 time: 0.6053 data_time: 0.0434 memory: 15724 2022/10/26 03:11:03 - mmengine - INFO - Epoch(val) [560][20/32] eta: 0:00:07 time: 0.6210 data_time: 0.0578 memory: 15724 2022/10/26 03:11:06 - mmengine - INFO - Epoch(val) [560][25/32] eta: 0:00:07 time: 0.6485 data_time: 0.0496 memory: 15724 2022/10/26 03:11:09 - mmengine - INFO - Epoch(val) [560][30/32] eta: 0:00:01 time: 0.6133 data_time: 0.0223 memory: 15724 2022/10/26 03:11:09 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7631, precision: 0.4174, hmean: 0.5397 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7631, precision: 0.6979, hmean: 0.7291 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7593, precision: 0.7607, hmean: 0.7600 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7429, precision: 0.8186, hmean: 0.7789 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6870, precision: 0.8825, hmean: 0.7726 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3457, precision: 0.9523, hmean: 0.5072 2022/10/26 03:11:09 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0014, precision: 1.0000, hmean: 0.0029 2022/10/26 03:11:09 - mmengine - INFO - Epoch(val) [560][32/32] icdar/precision: 0.8186 icdar/recall: 0.7429 icdar/hmean: 0.7789 2022/10/26 03:11:14 - mmengine - INFO - Epoch(train) [561][5/63] lr: 2.0066e-03 eta: 0:00:01 time: 0.7175 data_time: 0.1767 memory: 16131 loss: 1.8006 loss_prob: 1.0794 loss_thr: 0.5460 loss_db: 0.1752 2022/10/26 03:11:17 - mmengine - INFO - Epoch(train) [561][10/63] lr: 2.0066e-03 eta: 8:51:00 time: 0.7539 data_time: 0.1840 memory: 16131 loss: 1.7492 loss_prob: 1.0171 loss_thr: 0.5657 loss_db: 0.1663 2022/10/26 03:11:19 - mmengine - INFO - Epoch(train) [561][15/63] lr: 2.0066e-03 eta: 8:51:00 time: 0.5127 data_time: 0.0157 memory: 16131 loss: 1.6748 loss_prob: 0.9457 loss_thr: 0.5738 loss_db: 0.1553 2022/10/26 03:11:22 - mmengine - INFO - Epoch(train) [561][20/63] lr: 2.0066e-03 eta: 8:50:48 time: 0.4997 data_time: 0.0071 memory: 16131 loss: 1.6831 loss_prob: 0.9586 loss_thr: 0.5657 loss_db: 0.1589 2022/10/26 03:11:24 - mmengine - INFO - Epoch(train) [561][25/63] lr: 2.0066e-03 eta: 8:50:48 time: 0.5005 data_time: 0.0102 memory: 16131 loss: 1.6423 loss_prob: 0.9486 loss_thr: 0.5372 loss_db: 0.1566 2022/10/26 03:11:27 - mmengine - INFO - Epoch(train) [561][30/63] lr: 2.0066e-03 eta: 8:50:37 time: 0.5177 data_time: 0.0362 memory: 16131 loss: 1.5285 loss_prob: 0.8802 loss_thr: 0.5086 loss_db: 0.1398 2022/10/26 03:11:30 - mmengine - INFO - Epoch(train) [561][35/63] lr: 2.0066e-03 eta: 8:50:37 time: 0.5249 data_time: 0.0335 memory: 16131 loss: 1.4847 loss_prob: 0.8481 loss_thr: 0.4989 loss_db: 0.1377 2022/10/26 03:11:32 - mmengine - INFO - Epoch(train) [561][40/63] lr: 2.0066e-03 eta: 8:50:26 time: 0.5108 data_time: 0.0108 memory: 16131 loss: 1.5720 loss_prob: 0.8993 loss_thr: 0.5205 loss_db: 0.1522 2022/10/26 03:11:35 - mmengine - INFO - Epoch(train) [561][45/63] lr: 2.0066e-03 eta: 8:50:26 time: 0.5233 data_time: 0.0084 memory: 16131 loss: 1.7468 loss_prob: 1.0446 loss_thr: 0.5396 loss_db: 0.1626 2022/10/26 03:11:38 - mmengine - INFO - Epoch(train) [561][50/63] lr: 2.0066e-03 eta: 8:50:16 time: 0.5701 data_time: 0.0111 memory: 16131 loss: 1.6435 loss_prob: 0.9705 loss_thr: 0.5246 loss_db: 0.1484 2022/10/26 03:11:41 - mmengine - INFO - Epoch(train) [561][55/63] lr: 2.0066e-03 eta: 8:50:16 time: 0.5691 data_time: 0.0213 memory: 16131 loss: 1.4585 loss_prob: 0.8194 loss_thr: 0.5018 loss_db: 0.1372 2022/10/26 03:11:43 - mmengine - INFO - Epoch(train) [561][60/63] lr: 2.0066e-03 eta: 8:50:05 time: 0.5113 data_time: 0.0148 memory: 16131 loss: 1.4367 loss_prob: 0.7975 loss_thr: 0.5020 loss_db: 0.1372 2022/10/26 03:11:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:11:49 - mmengine - INFO - Epoch(train) [562][5/63] lr: 2.0038e-03 eta: 8:50:05 time: 0.7169 data_time: 0.2106 memory: 16131 loss: 1.4166 loss_prob: 0.7873 loss_thr: 0.4990 loss_db: 0.1303 2022/10/26 03:11:52 - mmengine - INFO - Epoch(train) [562][10/63] lr: 2.0038e-03 eta: 8:49:52 time: 0.8099 data_time: 0.2104 memory: 16131 loss: 1.4557 loss_prob: 0.8104 loss_thr: 0.5095 loss_db: 0.1358 2022/10/26 03:11:55 - mmengine - INFO - Epoch(train) [562][15/63] lr: 2.0038e-03 eta: 8:49:52 time: 0.5648 data_time: 0.0069 memory: 16131 loss: 1.4562 loss_prob: 0.8164 loss_thr: 0.5054 loss_db: 0.1344 2022/10/26 03:11:57 - mmengine - INFO - Epoch(train) [562][20/63] lr: 2.0038e-03 eta: 8:49:41 time: 0.5044 data_time: 0.0067 memory: 16131 loss: 1.4471 loss_prob: 0.8118 loss_thr: 0.5018 loss_db: 0.1334 2022/10/26 03:12:00 - mmengine - INFO - Epoch(train) [562][25/63] lr: 2.0038e-03 eta: 8:49:41 time: 0.5293 data_time: 0.0203 memory: 16131 loss: 1.3857 loss_prob: 0.7548 loss_thr: 0.5036 loss_db: 0.1273 2022/10/26 03:12:03 - mmengine - INFO - Epoch(train) [562][30/63] lr: 2.0038e-03 eta: 8:49:30 time: 0.5411 data_time: 0.0361 memory: 16131 loss: 1.4092 loss_prob: 0.7603 loss_thr: 0.5229 loss_db: 0.1260 2022/10/26 03:12:06 - mmengine - INFO - Epoch(train) [562][35/63] lr: 2.0038e-03 eta: 8:49:30 time: 0.5355 data_time: 0.0230 memory: 16131 loss: 1.3901 loss_prob: 0.7558 loss_thr: 0.5071 loss_db: 0.1272 2022/10/26 03:12:08 - mmengine - INFO - Epoch(train) [562][40/63] lr: 2.0038e-03 eta: 8:49:19 time: 0.5189 data_time: 0.0058 memory: 16131 loss: 1.3797 loss_prob: 0.7578 loss_thr: 0.4921 loss_db: 0.1298 2022/10/26 03:12:11 - mmengine - INFO - Epoch(train) [562][45/63] lr: 2.0038e-03 eta: 8:49:19 time: 0.4999 data_time: 0.0067 memory: 16131 loss: 1.4230 loss_prob: 0.7823 loss_thr: 0.5071 loss_db: 0.1337 2022/10/26 03:12:13 - mmengine - INFO - Epoch(train) [562][50/63] lr: 2.0038e-03 eta: 8:49:08 time: 0.5119 data_time: 0.0229 memory: 16131 loss: 1.3912 loss_prob: 0.7633 loss_thr: 0.4980 loss_db: 0.1299 2022/10/26 03:12:16 - mmengine - INFO - Epoch(train) [562][55/63] lr: 2.0038e-03 eta: 8:49:08 time: 0.5051 data_time: 0.0234 memory: 16131 loss: 1.4395 loss_prob: 0.8051 loss_thr: 0.4964 loss_db: 0.1380 2022/10/26 03:12:18 - mmengine - INFO - Epoch(train) [562][60/63] lr: 2.0038e-03 eta: 8:48:57 time: 0.5053 data_time: 0.0077 memory: 16131 loss: 1.4644 loss_prob: 0.8230 loss_thr: 0.5015 loss_db: 0.1399 2022/10/26 03:12:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:12:25 - mmengine - INFO - Epoch(train) [563][5/63] lr: 2.0010e-03 eta: 8:48:57 time: 0.7697 data_time: 0.1810 memory: 16131 loss: 1.6485 loss_prob: 0.9496 loss_thr: 0.5468 loss_db: 0.1520 2022/10/26 03:12:28 - mmengine - INFO - Epoch(train) [563][10/63] lr: 2.0010e-03 eta: 8:48:44 time: 0.8054 data_time: 0.1847 memory: 16131 loss: 1.4320 loss_prob: 0.7979 loss_thr: 0.5010 loss_db: 0.1331 2022/10/26 03:12:30 - mmengine - INFO - Epoch(train) [563][15/63] lr: 2.0010e-03 eta: 8:48:44 time: 0.5347 data_time: 0.0124 memory: 16131 loss: 1.7502 loss_prob: 1.0586 loss_thr: 0.5340 loss_db: 0.1576 2022/10/26 03:12:33 - mmengine - INFO - Epoch(train) [563][20/63] lr: 2.0010e-03 eta: 8:48:33 time: 0.5250 data_time: 0.0056 memory: 16131 loss: 1.7320 loss_prob: 1.0419 loss_thr: 0.5352 loss_db: 0.1548 2022/10/26 03:12:36 - mmengine - INFO - Epoch(train) [563][25/63] lr: 2.0010e-03 eta: 8:48:33 time: 0.5564 data_time: 0.0197 memory: 16131 loss: 1.3823 loss_prob: 0.7658 loss_thr: 0.4887 loss_db: 0.1278 2022/10/26 03:12:38 - mmengine - INFO - Epoch(train) [563][30/63] lr: 2.0010e-03 eta: 8:48:22 time: 0.5354 data_time: 0.0304 memory: 16131 loss: 1.4671 loss_prob: 0.8224 loss_thr: 0.5058 loss_db: 0.1389 2022/10/26 03:12:41 - mmengine - INFO - Epoch(train) [563][35/63] lr: 2.0010e-03 eta: 8:48:22 time: 0.4966 data_time: 0.0215 memory: 16131 loss: 1.7526 loss_prob: 1.0523 loss_thr: 0.5325 loss_db: 0.1678 2022/10/26 03:12:43 - mmengine - INFO - Epoch(train) [563][40/63] lr: 2.0010e-03 eta: 8:48:12 time: 0.5190 data_time: 0.0114 memory: 16131 loss: 1.6721 loss_prob: 0.9944 loss_thr: 0.5231 loss_db: 0.1546 2022/10/26 03:12:46 - mmengine - INFO - Epoch(train) [563][45/63] lr: 2.0010e-03 eta: 8:48:12 time: 0.5397 data_time: 0.0097 memory: 16131 loss: 1.6167 loss_prob: 0.9226 loss_thr: 0.5407 loss_db: 0.1534 2022/10/26 03:12:49 - mmengine - INFO - Epoch(train) [563][50/63] lr: 2.0010e-03 eta: 8:48:01 time: 0.5371 data_time: 0.0187 memory: 16131 loss: 1.7011 loss_prob: 0.9829 loss_thr: 0.5525 loss_db: 0.1656 2022/10/26 03:12:51 - mmengine - INFO - Epoch(train) [563][55/63] lr: 2.0010e-03 eta: 8:48:01 time: 0.5245 data_time: 0.0255 memory: 16131 loss: 1.4990 loss_prob: 0.8370 loss_thr: 0.5214 loss_db: 0.1406 2022/10/26 03:12:54 - mmengine - INFO - Epoch(train) [563][60/63] lr: 2.0010e-03 eta: 8:47:50 time: 0.5029 data_time: 0.0174 memory: 16131 loss: 1.5207 loss_prob: 0.8563 loss_thr: 0.5201 loss_db: 0.1443 2022/10/26 03:12:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:13:01 - mmengine - INFO - Epoch(train) [564][5/63] lr: 1.9982e-03 eta: 8:47:50 time: 0.8429 data_time: 0.2086 memory: 16131 loss: 1.5536 loss_prob: 0.8715 loss_thr: 0.5365 loss_db: 0.1456 2022/10/26 03:13:04 - mmengine - INFO - Epoch(train) [564][10/63] lr: 1.9982e-03 eta: 8:47:37 time: 0.8559 data_time: 0.2068 memory: 16131 loss: 1.5124 loss_prob: 0.8407 loss_thr: 0.5311 loss_db: 0.1406 2022/10/26 03:13:06 - mmengine - INFO - Epoch(train) [564][15/63] lr: 1.9982e-03 eta: 8:47:37 time: 0.5027 data_time: 0.0061 memory: 16131 loss: 1.4381 loss_prob: 0.8039 loss_thr: 0.5014 loss_db: 0.1328 2022/10/26 03:13:09 - mmengine - INFO - Epoch(train) [564][20/63] lr: 1.9982e-03 eta: 8:47:27 time: 0.5565 data_time: 0.0109 memory: 16131 loss: 1.3695 loss_prob: 0.7643 loss_thr: 0.4769 loss_db: 0.1283 2022/10/26 03:13:12 - mmengine - INFO - Epoch(train) [564][25/63] lr: 1.9982e-03 eta: 8:47:27 time: 0.5475 data_time: 0.0115 memory: 16131 loss: 1.4775 loss_prob: 0.8354 loss_thr: 0.5013 loss_db: 0.1408 2022/10/26 03:13:14 - mmengine - INFO - Epoch(train) [564][30/63] lr: 1.9982e-03 eta: 8:47:16 time: 0.5013 data_time: 0.0178 memory: 16131 loss: 1.4754 loss_prob: 0.8238 loss_thr: 0.5130 loss_db: 0.1386 2022/10/26 03:13:17 - mmengine - INFO - Epoch(train) [564][35/63] lr: 1.9982e-03 eta: 8:47:16 time: 0.5133 data_time: 0.0158 memory: 16131 loss: 1.4922 loss_prob: 0.8291 loss_thr: 0.5237 loss_db: 0.1395 2022/10/26 03:13:19 - mmengine - INFO - Epoch(train) [564][40/63] lr: 1.9982e-03 eta: 8:47:05 time: 0.5104 data_time: 0.0105 memory: 16131 loss: 1.4121 loss_prob: 0.7811 loss_thr: 0.5011 loss_db: 0.1299 2022/10/26 03:13:22 - mmengine - INFO - Epoch(train) [564][45/63] lr: 1.9982e-03 eta: 8:47:05 time: 0.5058 data_time: 0.0117 memory: 16131 loss: 1.3089 loss_prob: 0.7176 loss_thr: 0.4690 loss_db: 0.1224 2022/10/26 03:13:25 - mmengine - INFO - Epoch(train) [564][50/63] lr: 1.9982e-03 eta: 8:46:54 time: 0.5389 data_time: 0.0135 memory: 16131 loss: 1.3961 loss_prob: 0.7704 loss_thr: 0.4948 loss_db: 0.1309 2022/10/26 03:13:28 - mmengine - INFO - Epoch(train) [564][55/63] lr: 1.9982e-03 eta: 8:46:54 time: 0.5527 data_time: 0.0265 memory: 16131 loss: 1.5512 loss_prob: 0.8655 loss_thr: 0.5429 loss_db: 0.1428 2022/10/26 03:13:31 - mmengine - INFO - Epoch(train) [564][60/63] lr: 1.9982e-03 eta: 8:46:44 time: 0.5667 data_time: 0.0197 memory: 16131 loss: 1.5254 loss_prob: 0.8521 loss_thr: 0.5337 loss_db: 0.1396 2022/10/26 03:13:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:13:36 - mmengine - INFO - Epoch(train) [565][5/63] lr: 1.9953e-03 eta: 8:46:44 time: 0.6784 data_time: 0.1787 memory: 16131 loss: 1.5021 loss_prob: 0.8351 loss_thr: 0.5236 loss_db: 0.1434 2022/10/26 03:13:39 - mmengine - INFO - Epoch(train) [565][10/63] lr: 1.9953e-03 eta: 8:46:30 time: 0.7216 data_time: 0.1820 memory: 16131 loss: 1.4010 loss_prob: 0.7687 loss_thr: 0.4989 loss_db: 0.1334 2022/10/26 03:13:42 - mmengine - INFO - Epoch(train) [565][15/63] lr: 1.9953e-03 eta: 8:46:30 time: 0.5398 data_time: 0.0098 memory: 16131 loss: 1.3906 loss_prob: 0.7760 loss_thr: 0.4883 loss_db: 0.1263 2022/10/26 03:13:44 - mmengine - INFO - Epoch(train) [565][20/63] lr: 1.9953e-03 eta: 8:46:19 time: 0.5416 data_time: 0.0053 memory: 16131 loss: 1.3400 loss_prob: 0.7457 loss_thr: 0.4727 loss_db: 0.1215 2022/10/26 03:13:47 - mmengine - INFO - Epoch(train) [565][25/63] lr: 1.9953e-03 eta: 8:46:19 time: 0.5394 data_time: 0.0199 memory: 16131 loss: 1.3556 loss_prob: 0.7475 loss_thr: 0.4819 loss_db: 0.1262 2022/10/26 03:13:50 - mmengine - INFO - Epoch(train) [565][30/63] lr: 1.9953e-03 eta: 8:46:09 time: 0.5322 data_time: 0.0349 memory: 16131 loss: 1.4984 loss_prob: 0.8295 loss_thr: 0.5310 loss_db: 0.1379 2022/10/26 03:13:52 - mmengine - INFO - Epoch(train) [565][35/63] lr: 1.9953e-03 eta: 8:46:09 time: 0.5144 data_time: 0.0197 memory: 16131 loss: 1.4264 loss_prob: 0.7851 loss_thr: 0.5088 loss_db: 0.1325 2022/10/26 03:13:55 - mmengine - INFO - Epoch(train) [565][40/63] lr: 1.9953e-03 eta: 8:45:57 time: 0.4986 data_time: 0.0047 memory: 16131 loss: 1.3188 loss_prob: 0.7257 loss_thr: 0.4710 loss_db: 0.1221 2022/10/26 03:13:57 - mmengine - INFO - Epoch(train) [565][45/63] lr: 1.9953e-03 eta: 8:45:57 time: 0.5018 data_time: 0.0069 memory: 16131 loss: 1.3821 loss_prob: 0.7532 loss_thr: 0.5039 loss_db: 0.1249 2022/10/26 03:14:00 - mmengine - INFO - Epoch(train) [565][50/63] lr: 1.9953e-03 eta: 8:45:47 time: 0.5195 data_time: 0.0176 memory: 16131 loss: 1.5602 loss_prob: 0.8777 loss_thr: 0.5387 loss_db: 0.1438 2022/10/26 03:14:03 - mmengine - INFO - Epoch(train) [565][55/63] lr: 1.9953e-03 eta: 8:45:47 time: 0.5661 data_time: 0.0287 memory: 16131 loss: 1.5797 loss_prob: 0.8924 loss_thr: 0.5401 loss_db: 0.1471 2022/10/26 03:14:05 - mmengine - INFO - Epoch(train) [565][60/63] lr: 1.9953e-03 eta: 8:45:36 time: 0.5383 data_time: 0.0184 memory: 16131 loss: 1.4573 loss_prob: 0.8106 loss_thr: 0.5112 loss_db: 0.1355 2022/10/26 03:14:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:14:11 - mmengine - INFO - Epoch(train) [566][5/63] lr: 1.9925e-03 eta: 8:45:36 time: 0.7068 data_time: 0.1753 memory: 16131 loss: 1.5959 loss_prob: 0.9339 loss_thr: 0.5103 loss_db: 0.1517 2022/10/26 03:14:14 - mmengine - INFO - Epoch(train) [566][10/63] lr: 1.9925e-03 eta: 8:45:22 time: 0.7287 data_time: 0.1761 memory: 16131 loss: 1.5503 loss_prob: 0.8910 loss_thr: 0.5056 loss_db: 0.1537 2022/10/26 03:14:17 - mmengine - INFO - Epoch(train) [566][15/63] lr: 1.9925e-03 eta: 8:45:22 time: 0.5707 data_time: 0.0082 memory: 16131 loss: 1.5485 loss_prob: 0.8920 loss_thr: 0.5044 loss_db: 0.1521 2022/10/26 03:14:20 - mmengine - INFO - Epoch(train) [566][20/63] lr: 1.9925e-03 eta: 8:45:12 time: 0.5704 data_time: 0.0063 memory: 16131 loss: 1.4348 loss_prob: 0.8141 loss_thr: 0.4878 loss_db: 0.1329 2022/10/26 03:14:23 - mmengine - INFO - Epoch(train) [566][25/63] lr: 1.9925e-03 eta: 8:45:12 time: 0.5361 data_time: 0.0122 memory: 16131 loss: 1.4363 loss_prob: 0.8218 loss_thr: 0.4808 loss_db: 0.1337 2022/10/26 03:14:25 - mmengine - INFO - Epoch(train) [566][30/63] lr: 1.9925e-03 eta: 8:45:02 time: 0.5763 data_time: 0.0304 memory: 16131 loss: 1.4787 loss_prob: 0.8282 loss_thr: 0.5107 loss_db: 0.1398 2022/10/26 03:14:28 - mmengine - INFO - Epoch(train) [566][35/63] lr: 1.9925e-03 eta: 8:45:02 time: 0.5550 data_time: 0.0255 memory: 16131 loss: 1.6392 loss_prob: 0.9397 loss_thr: 0.5374 loss_db: 0.1621 2022/10/26 03:14:31 - mmengine - INFO - Epoch(train) [566][40/63] lr: 1.9925e-03 eta: 8:44:51 time: 0.5190 data_time: 0.0070 memory: 16131 loss: 1.6626 loss_prob: 0.9690 loss_thr: 0.5297 loss_db: 0.1639 2022/10/26 03:14:33 - mmengine - INFO - Epoch(train) [566][45/63] lr: 1.9925e-03 eta: 8:44:51 time: 0.5022 data_time: 0.0056 memory: 16131 loss: 1.5288 loss_prob: 0.8709 loss_thr: 0.5159 loss_db: 0.1420 2022/10/26 03:14:36 - mmengine - INFO - Epoch(train) [566][50/63] lr: 1.9925e-03 eta: 8:44:40 time: 0.5101 data_time: 0.0209 memory: 16131 loss: 1.5547 loss_prob: 0.8848 loss_thr: 0.5263 loss_db: 0.1436 2022/10/26 03:14:38 - mmengine - INFO - Epoch(train) [566][55/63] lr: 1.9925e-03 eta: 8:44:40 time: 0.5283 data_time: 0.0297 memory: 16131 loss: 1.7207 loss_prob: 1.0199 loss_thr: 0.5356 loss_db: 0.1652 2022/10/26 03:14:41 - mmengine - INFO - Epoch(train) [566][60/63] lr: 1.9925e-03 eta: 8:44:29 time: 0.5271 data_time: 0.0155 memory: 16131 loss: 1.6418 loss_prob: 0.9598 loss_thr: 0.5224 loss_db: 0.1595 2022/10/26 03:14:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:14:47 - mmengine - INFO - Epoch(train) [567][5/63] lr: 1.9897e-03 eta: 8:44:29 time: 0.6576 data_time: 0.1890 memory: 16131 loss: 1.5791 loss_prob: 0.8878 loss_thr: 0.5426 loss_db: 0.1487 2022/10/26 03:14:49 - mmengine - INFO - Epoch(train) [567][10/63] lr: 1.9897e-03 eta: 8:44:15 time: 0.6985 data_time: 0.1935 memory: 16131 loss: 1.5364 loss_prob: 0.8669 loss_thr: 0.5252 loss_db: 0.1443 2022/10/26 03:14:52 - mmengine - INFO - Epoch(train) [567][15/63] lr: 1.9897e-03 eta: 8:44:15 time: 0.5029 data_time: 0.0090 memory: 16131 loss: 1.5853 loss_prob: 0.9113 loss_thr: 0.5274 loss_db: 0.1466 2022/10/26 03:14:54 - mmengine - INFO - Epoch(train) [567][20/63] lr: 1.9897e-03 eta: 8:44:04 time: 0.5235 data_time: 0.0050 memory: 16131 loss: 1.5804 loss_prob: 0.8962 loss_thr: 0.5364 loss_db: 0.1478 2022/10/26 03:14:58 - mmengine - INFO - Epoch(train) [567][25/63] lr: 1.9897e-03 eta: 8:44:04 time: 0.6134 data_time: 0.0159 memory: 16131 loss: 1.4607 loss_prob: 0.8163 loss_thr: 0.5066 loss_db: 0.1378 2022/10/26 03:15:01 - mmengine - INFO - Epoch(train) [567][30/63] lr: 1.9897e-03 eta: 8:43:55 time: 0.6295 data_time: 0.0296 memory: 16131 loss: 1.4320 loss_prob: 0.8009 loss_thr: 0.4964 loss_db: 0.1348 2022/10/26 03:15:03 - mmengine - INFO - Epoch(train) [567][35/63] lr: 1.9897e-03 eta: 8:43:55 time: 0.5505 data_time: 0.0236 memory: 16131 loss: 1.5237 loss_prob: 0.8578 loss_thr: 0.5239 loss_db: 0.1419 2022/10/26 03:15:06 - mmengine - INFO - Epoch(train) [567][40/63] lr: 1.9897e-03 eta: 8:43:44 time: 0.5463 data_time: 0.0107 memory: 16131 loss: 1.5514 loss_prob: 0.8773 loss_thr: 0.5298 loss_db: 0.1442 2022/10/26 03:15:09 - mmengine - INFO - Epoch(train) [567][45/63] lr: 1.9897e-03 eta: 8:43:44 time: 0.5393 data_time: 0.0079 memory: 16131 loss: 1.4141 loss_prob: 0.7773 loss_thr: 0.5027 loss_db: 0.1341 2022/10/26 03:15:11 - mmengine - INFO - Epoch(train) [567][50/63] lr: 1.9897e-03 eta: 8:43:33 time: 0.5122 data_time: 0.0178 memory: 16131 loss: 1.5688 loss_prob: 0.9035 loss_thr: 0.5166 loss_db: 0.1488 2022/10/26 03:15:14 - mmengine - INFO - Epoch(train) [567][55/63] lr: 1.9897e-03 eta: 8:43:33 time: 0.5079 data_time: 0.0197 memory: 16131 loss: 1.5354 loss_prob: 0.8938 loss_thr: 0.5005 loss_db: 0.1410 2022/10/26 03:15:16 - mmengine - INFO - Epoch(train) [567][60/63] lr: 1.9897e-03 eta: 8:43:22 time: 0.5056 data_time: 0.0104 memory: 16131 loss: 1.3235 loss_prob: 0.7357 loss_thr: 0.4650 loss_db: 0.1228 2022/10/26 03:15:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:15:22 - mmengine - INFO - Epoch(train) [568][5/63] lr: 1.9868e-03 eta: 8:43:22 time: 0.6860 data_time: 0.1848 memory: 16131 loss: 1.5383 loss_prob: 0.8767 loss_thr: 0.5141 loss_db: 0.1476 2022/10/26 03:15:25 - mmengine - INFO - Epoch(train) [568][10/63] lr: 1.9868e-03 eta: 8:43:08 time: 0.6944 data_time: 0.1823 memory: 16131 loss: 1.5541 loss_prob: 0.8677 loss_thr: 0.5422 loss_db: 0.1443 2022/10/26 03:15:27 - mmengine - INFO - Epoch(train) [568][15/63] lr: 1.9868e-03 eta: 8:43:08 time: 0.4920 data_time: 0.0077 memory: 16131 loss: 1.5573 loss_prob: 0.8637 loss_thr: 0.5527 loss_db: 0.1409 2022/10/26 03:15:30 - mmengine - INFO - Epoch(train) [568][20/63] lr: 1.9868e-03 eta: 8:42:57 time: 0.4944 data_time: 0.0077 memory: 16131 loss: 1.4252 loss_prob: 0.7798 loss_thr: 0.5150 loss_db: 0.1303 2022/10/26 03:15:32 - mmengine - INFO - Epoch(train) [568][25/63] lr: 1.9868e-03 eta: 8:42:57 time: 0.5021 data_time: 0.0166 memory: 16131 loss: 1.4125 loss_prob: 0.7771 loss_thr: 0.5046 loss_db: 0.1308 2022/10/26 03:15:35 - mmengine - INFO - Epoch(train) [568][30/63] lr: 1.9868e-03 eta: 8:42:46 time: 0.5141 data_time: 0.0286 memory: 16131 loss: 1.4295 loss_prob: 0.7816 loss_thr: 0.5172 loss_db: 0.1308 2022/10/26 03:15:37 - mmengine - INFO - Epoch(train) [568][35/63] lr: 1.9868e-03 eta: 8:42:46 time: 0.4988 data_time: 0.0184 memory: 16131 loss: 1.4082 loss_prob: 0.7647 loss_thr: 0.5136 loss_db: 0.1299 2022/10/26 03:15:40 - mmengine - INFO - Epoch(train) [568][40/63] lr: 1.9868e-03 eta: 8:42:35 time: 0.4792 data_time: 0.0066 memory: 16131 loss: 1.4172 loss_prob: 0.7755 loss_thr: 0.5081 loss_db: 0.1336 2022/10/26 03:15:42 - mmengine - INFO - Epoch(train) [568][45/63] lr: 1.9868e-03 eta: 8:42:35 time: 0.5137 data_time: 0.0051 memory: 16131 loss: 1.7098 loss_prob: 1.0043 loss_thr: 0.5434 loss_db: 0.1621 2022/10/26 03:15:45 - mmengine - INFO - Epoch(train) [568][50/63] lr: 1.9868e-03 eta: 8:42:24 time: 0.5074 data_time: 0.0128 memory: 16131 loss: 1.6835 loss_prob: 1.0043 loss_thr: 0.5220 loss_db: 0.1572 2022/10/26 03:15:47 - mmengine - INFO - Epoch(train) [568][55/63] lr: 1.9868e-03 eta: 8:42:24 time: 0.4895 data_time: 0.0205 memory: 16131 loss: 1.3062 loss_prob: 0.7291 loss_thr: 0.4590 loss_db: 0.1181 2022/10/26 03:15:50 - mmengine - INFO - Epoch(train) [568][60/63] lr: 1.9868e-03 eta: 8:42:13 time: 0.5232 data_time: 0.0162 memory: 16131 loss: 1.3563 loss_prob: 0.7526 loss_thr: 0.4817 loss_db: 0.1220 2022/10/26 03:15:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:15:56 - mmengine - INFO - Epoch(train) [569][5/63] lr: 1.9840e-03 eta: 8:42:13 time: 0.6889 data_time: 0.1689 memory: 16131 loss: 1.5276 loss_prob: 0.8723 loss_thr: 0.5141 loss_db: 0.1411 2022/10/26 03:15:58 - mmengine - INFO - Epoch(train) [569][10/63] lr: 1.9840e-03 eta: 8:41:59 time: 0.6974 data_time: 0.1682 memory: 16131 loss: 1.4034 loss_prob: 0.7767 loss_thr: 0.4994 loss_db: 0.1273 2022/10/26 03:16:01 - mmengine - INFO - Epoch(train) [569][15/63] lr: 1.9840e-03 eta: 8:41:59 time: 0.5116 data_time: 0.0048 memory: 16131 loss: 1.4023 loss_prob: 0.7817 loss_thr: 0.4931 loss_db: 0.1275 2022/10/26 03:16:03 - mmengine - INFO - Epoch(train) [569][20/63] lr: 1.9840e-03 eta: 8:41:48 time: 0.5137 data_time: 0.0082 memory: 16131 loss: 1.2871 loss_prob: 0.7032 loss_thr: 0.4663 loss_db: 0.1176 2022/10/26 03:16:06 - mmengine - INFO - Epoch(train) [569][25/63] lr: 1.9840e-03 eta: 8:41:48 time: 0.5283 data_time: 0.0111 memory: 16131 loss: 1.2983 loss_prob: 0.7034 loss_thr: 0.4763 loss_db: 0.1186 2022/10/26 03:16:09 - mmengine - INFO - Epoch(train) [569][30/63] lr: 1.9840e-03 eta: 8:41:38 time: 0.5792 data_time: 0.0275 memory: 16131 loss: 1.4426 loss_prob: 0.8104 loss_thr: 0.4973 loss_db: 0.1350 2022/10/26 03:16:12 - mmengine - INFO - Epoch(train) [569][35/63] lr: 1.9840e-03 eta: 8:41:38 time: 0.5562 data_time: 0.0249 memory: 16131 loss: 1.4242 loss_prob: 0.8031 loss_thr: 0.4875 loss_db: 0.1336 2022/10/26 03:16:14 - mmengine - INFO - Epoch(train) [569][40/63] lr: 1.9840e-03 eta: 8:41:27 time: 0.4977 data_time: 0.0048 memory: 16131 loss: 1.3738 loss_prob: 0.7563 loss_thr: 0.4901 loss_db: 0.1274 2022/10/26 03:16:17 - mmengine - INFO - Epoch(train) [569][45/63] lr: 1.9840e-03 eta: 8:41:27 time: 0.5190 data_time: 0.0075 memory: 16131 loss: 1.4717 loss_prob: 0.8364 loss_thr: 0.4985 loss_db: 0.1368 2022/10/26 03:16:19 - mmengine - INFO - Epoch(train) [569][50/63] lr: 1.9840e-03 eta: 8:41:16 time: 0.5289 data_time: 0.0194 memory: 16131 loss: 1.4332 loss_prob: 0.8051 loss_thr: 0.4953 loss_db: 0.1327 2022/10/26 03:16:22 - mmengine - INFO - Epoch(train) [569][55/63] lr: 1.9840e-03 eta: 8:41:16 time: 0.5130 data_time: 0.0260 memory: 16131 loss: 1.3403 loss_prob: 0.7273 loss_thr: 0.4863 loss_db: 0.1267 2022/10/26 03:16:24 - mmengine - INFO - Epoch(train) [569][60/63] lr: 1.9840e-03 eta: 8:41:05 time: 0.5115 data_time: 0.0195 memory: 16131 loss: 1.4062 loss_prob: 0.7734 loss_thr: 0.5029 loss_db: 0.1299 2022/10/26 03:16:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:16:30 - mmengine - INFO - Epoch(train) [570][5/63] lr: 1.9812e-03 eta: 8:41:05 time: 0.6713 data_time: 0.1693 memory: 16131 loss: 1.4135 loss_prob: 0.7738 loss_thr: 0.5105 loss_db: 0.1292 2022/10/26 03:16:33 - mmengine - INFO - Epoch(train) [570][10/63] lr: 1.9812e-03 eta: 8:40:52 time: 0.6977 data_time: 0.1830 memory: 16131 loss: 1.4395 loss_prob: 0.7984 loss_thr: 0.5086 loss_db: 0.1325 2022/10/26 03:16:36 - mmengine - INFO - Epoch(train) [570][15/63] lr: 1.9812e-03 eta: 8:40:52 time: 0.5338 data_time: 0.0219 memory: 16131 loss: 1.4555 loss_prob: 0.8144 loss_thr: 0.5022 loss_db: 0.1389 2022/10/26 03:16:38 - mmengine - INFO - Epoch(train) [570][20/63] lr: 1.9812e-03 eta: 8:40:40 time: 0.4990 data_time: 0.0060 memory: 16131 loss: 1.5461 loss_prob: 0.8526 loss_thr: 0.5517 loss_db: 0.1418 2022/10/26 03:16:41 - mmengine - INFO - Epoch(train) [570][25/63] lr: 1.9812e-03 eta: 8:40:40 time: 0.5079 data_time: 0.0142 memory: 16131 loss: 1.4730 loss_prob: 0.8055 loss_thr: 0.5348 loss_db: 0.1327 2022/10/26 03:16:43 - mmengine - INFO - Epoch(train) [570][30/63] lr: 1.9812e-03 eta: 8:40:30 time: 0.5512 data_time: 0.0360 memory: 16131 loss: 1.5315 loss_prob: 0.8916 loss_thr: 0.4919 loss_db: 0.1480 2022/10/26 03:16:46 - mmengine - INFO - Epoch(train) [570][35/63] lr: 1.9812e-03 eta: 8:40:30 time: 0.5518 data_time: 0.0262 memory: 16131 loss: 1.5260 loss_prob: 0.8867 loss_thr: 0.4939 loss_db: 0.1453 2022/10/26 03:16:49 - mmengine - INFO - Epoch(train) [570][40/63] lr: 1.9812e-03 eta: 8:40:20 time: 0.5516 data_time: 0.0106 memory: 16131 loss: 1.3537 loss_prob: 0.7413 loss_thr: 0.4871 loss_db: 0.1253 2022/10/26 03:16:52 - mmengine - INFO - Epoch(train) [570][45/63] lr: 1.9812e-03 eta: 8:40:20 time: 0.5862 data_time: 0.0107 memory: 16131 loss: 1.3705 loss_prob: 0.7577 loss_thr: 0.4836 loss_db: 0.1292 2022/10/26 03:16:54 - mmengine - INFO - Epoch(train) [570][50/63] lr: 1.9812e-03 eta: 8:40:09 time: 0.5542 data_time: 0.0113 memory: 16131 loss: 1.4753 loss_prob: 0.8407 loss_thr: 0.4964 loss_db: 0.1382 2022/10/26 03:16:57 - mmengine - INFO - Epoch(train) [570][55/63] lr: 1.9812e-03 eta: 8:40:09 time: 0.5193 data_time: 0.0203 memory: 16131 loss: 1.5250 loss_prob: 0.8829 loss_thr: 0.4992 loss_db: 0.1429 2022/10/26 03:17:00 - mmengine - INFO - Epoch(train) [570][60/63] lr: 1.9812e-03 eta: 8:39:58 time: 0.5285 data_time: 0.0140 memory: 16131 loss: 1.3913 loss_prob: 0.7760 loss_thr: 0.4861 loss_db: 0.1292 2022/10/26 03:17:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:17:07 - mmengine - INFO - Epoch(train) [571][5/63] lr: 1.9784e-03 eta: 8:39:58 time: 0.8018 data_time: 0.1813 memory: 16131 loss: 1.3416 loss_prob: 0.7286 loss_thr: 0.4867 loss_db: 0.1263 2022/10/26 03:17:10 - mmengine - INFO - Epoch(train) [571][10/63] lr: 1.9784e-03 eta: 8:39:46 time: 0.8486 data_time: 0.1789 memory: 16131 loss: 1.3288 loss_prob: 0.7154 loss_thr: 0.4901 loss_db: 0.1233 2022/10/26 03:17:12 - mmengine - INFO - Epoch(train) [571][15/63] lr: 1.9784e-03 eta: 8:39:46 time: 0.5178 data_time: 0.0051 memory: 16131 loss: 1.4176 loss_prob: 0.7869 loss_thr: 0.4950 loss_db: 0.1357 2022/10/26 03:17:15 - mmengine - INFO - Epoch(train) [571][20/63] lr: 1.9784e-03 eta: 8:39:35 time: 0.5129 data_time: 0.0078 memory: 16131 loss: 1.4593 loss_prob: 0.8169 loss_thr: 0.5024 loss_db: 0.1400 2022/10/26 03:17:17 - mmengine - INFO - Epoch(train) [571][25/63] lr: 1.9784e-03 eta: 8:39:35 time: 0.5231 data_time: 0.0123 memory: 16131 loss: 1.5743 loss_prob: 0.9029 loss_thr: 0.5218 loss_db: 0.1496 2022/10/26 03:17:20 - mmengine - INFO - Epoch(train) [571][30/63] lr: 1.9784e-03 eta: 8:39:25 time: 0.5193 data_time: 0.0318 memory: 16131 loss: 1.5622 loss_prob: 0.9004 loss_thr: 0.5092 loss_db: 0.1527 2022/10/26 03:17:23 - mmengine - INFO - Epoch(train) [571][35/63] lr: 1.9784e-03 eta: 8:39:25 time: 0.5421 data_time: 0.0270 memory: 16131 loss: 1.4126 loss_prob: 0.7932 loss_thr: 0.4849 loss_db: 0.1345 2022/10/26 03:17:25 - mmengine - INFO - Epoch(train) [571][40/63] lr: 1.9784e-03 eta: 8:39:14 time: 0.5607 data_time: 0.0048 memory: 16131 loss: 1.4605 loss_prob: 0.8399 loss_thr: 0.4845 loss_db: 0.1361 2022/10/26 03:17:28 - mmengine - INFO - Epoch(train) [571][45/63] lr: 1.9784e-03 eta: 8:39:14 time: 0.5415 data_time: 0.0079 memory: 16131 loss: 1.4666 loss_prob: 0.8429 loss_thr: 0.4843 loss_db: 0.1394 2022/10/26 03:17:30 - mmengine - INFO - Epoch(train) [571][50/63] lr: 1.9784e-03 eta: 8:39:03 time: 0.5046 data_time: 0.0104 memory: 16131 loss: 1.5442 loss_prob: 0.8824 loss_thr: 0.5146 loss_db: 0.1471 2022/10/26 03:17:33 - mmengine - INFO - Epoch(train) [571][55/63] lr: 1.9784e-03 eta: 8:39:03 time: 0.5214 data_time: 0.0217 memory: 16131 loss: 1.7097 loss_prob: 0.9993 loss_thr: 0.5465 loss_db: 0.1640 2022/10/26 03:17:36 - mmengine - INFO - Epoch(train) [571][60/63] lr: 1.9784e-03 eta: 8:38:52 time: 0.5138 data_time: 0.0191 memory: 16131 loss: 1.5736 loss_prob: 0.9056 loss_thr: 0.5186 loss_db: 0.1494 2022/10/26 03:17:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:17:41 - mmengine - INFO - Epoch(train) [572][5/63] lr: 1.9755e-03 eta: 8:38:52 time: 0.6696 data_time: 0.1945 memory: 16131 loss: 1.6367 loss_prob: 0.9593 loss_thr: 0.5253 loss_db: 0.1522 2022/10/26 03:17:44 - mmengine - INFO - Epoch(train) [572][10/63] lr: 1.9755e-03 eta: 8:38:39 time: 0.7299 data_time: 0.1946 memory: 16131 loss: 1.5574 loss_prob: 0.9068 loss_thr: 0.5058 loss_db: 0.1448 2022/10/26 03:17:47 - mmengine - INFO - Epoch(train) [572][15/63] lr: 1.9755e-03 eta: 8:38:39 time: 0.5314 data_time: 0.0056 memory: 16131 loss: 1.4169 loss_prob: 0.7826 loss_thr: 0.5036 loss_db: 0.1307 2022/10/26 03:17:49 - mmengine - INFO - Epoch(train) [572][20/63] lr: 1.9755e-03 eta: 8:38:28 time: 0.5001 data_time: 0.0057 memory: 16131 loss: 1.3864 loss_prob: 0.7593 loss_thr: 0.5006 loss_db: 0.1265 2022/10/26 03:17:52 - mmengine - INFO - Epoch(train) [572][25/63] lr: 1.9755e-03 eta: 8:38:28 time: 0.5396 data_time: 0.0208 memory: 16131 loss: 1.3773 loss_prob: 0.7601 loss_thr: 0.4895 loss_db: 0.1276 2022/10/26 03:17:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:17:55 - mmengine - INFO - Epoch(train) [572][30/63] lr: 1.9755e-03 eta: 8:38:18 time: 0.5815 data_time: 0.0415 memory: 16131 loss: 1.4549 loss_prob: 0.8147 loss_thr: 0.5030 loss_db: 0.1372 2022/10/26 03:17:58 - mmengine - INFO - Epoch(train) [572][35/63] lr: 1.9755e-03 eta: 8:38:18 time: 0.5594 data_time: 0.0254 memory: 16131 loss: 1.4343 loss_prob: 0.8050 loss_thr: 0.4940 loss_db: 0.1354 2022/10/26 03:18:01 - mmengine - INFO - Epoch(train) [572][40/63] lr: 1.9755e-03 eta: 8:38:08 time: 0.5550 data_time: 0.0044 memory: 16131 loss: 1.3379 loss_prob: 0.7410 loss_thr: 0.4744 loss_db: 0.1225 2022/10/26 03:18:03 - mmengine - INFO - Epoch(train) [572][45/63] lr: 1.9755e-03 eta: 8:38:08 time: 0.5365 data_time: 0.0090 memory: 16131 loss: 1.3662 loss_prob: 0.7582 loss_thr: 0.4822 loss_db: 0.1257 2022/10/26 03:18:06 - mmengine - INFO - Epoch(train) [572][50/63] lr: 1.9755e-03 eta: 8:37:57 time: 0.5438 data_time: 0.0260 memory: 16131 loss: 1.4559 loss_prob: 0.8221 loss_thr: 0.4965 loss_db: 0.1373 2022/10/26 03:18:08 - mmengine - INFO - Epoch(train) [572][55/63] lr: 1.9755e-03 eta: 8:37:57 time: 0.5328 data_time: 0.0223 memory: 16131 loss: 1.4958 loss_prob: 0.8525 loss_thr: 0.5059 loss_db: 0.1373 2022/10/26 03:18:11 - mmengine - INFO - Epoch(train) [572][60/63] lr: 1.9755e-03 eta: 8:37:46 time: 0.4883 data_time: 0.0051 memory: 16131 loss: 1.5489 loss_prob: 0.8872 loss_thr: 0.5191 loss_db: 0.1426 2022/10/26 03:18:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:18:17 - mmengine - INFO - Epoch(train) [573][5/63] lr: 1.9727e-03 eta: 8:37:46 time: 0.6911 data_time: 0.1993 memory: 16131 loss: 1.4577 loss_prob: 0.8130 loss_thr: 0.5138 loss_db: 0.1309 2022/10/26 03:18:20 - mmengine - INFO - Epoch(train) [573][10/63] lr: 1.9727e-03 eta: 8:37:33 time: 0.7375 data_time: 0.2091 memory: 16131 loss: 1.5335 loss_prob: 0.8628 loss_thr: 0.5294 loss_db: 0.1413 2022/10/26 03:18:22 - mmengine - INFO - Epoch(train) [573][15/63] lr: 1.9727e-03 eta: 8:37:33 time: 0.5359 data_time: 0.0157 memory: 16131 loss: 1.4995 loss_prob: 0.8407 loss_thr: 0.5169 loss_db: 0.1418 2022/10/26 03:18:25 - mmengine - INFO - Epoch(train) [573][20/63] lr: 1.9727e-03 eta: 8:37:22 time: 0.5151 data_time: 0.0066 memory: 16131 loss: 1.4106 loss_prob: 0.7742 loss_thr: 0.5040 loss_db: 0.1324 2022/10/26 03:18:27 - mmengine - INFO - Epoch(train) [573][25/63] lr: 1.9727e-03 eta: 8:37:22 time: 0.5175 data_time: 0.0310 memory: 16131 loss: 1.4316 loss_prob: 0.8005 loss_thr: 0.4940 loss_db: 0.1371 2022/10/26 03:18:30 - mmengine - INFO - Epoch(train) [573][30/63] lr: 1.9727e-03 eta: 8:37:11 time: 0.5062 data_time: 0.0298 memory: 16131 loss: 1.4063 loss_prob: 0.7870 loss_thr: 0.4846 loss_db: 0.1348 2022/10/26 03:18:33 - mmengine - INFO - Epoch(train) [573][35/63] lr: 1.9727e-03 eta: 8:37:11 time: 0.5158 data_time: 0.0094 memory: 16131 loss: 1.4396 loss_prob: 0.8087 loss_thr: 0.4933 loss_db: 0.1376 2022/10/26 03:18:35 - mmengine - INFO - Epoch(train) [573][40/63] lr: 1.9727e-03 eta: 8:37:00 time: 0.5219 data_time: 0.0093 memory: 16131 loss: 1.7084 loss_prob: 0.9948 loss_thr: 0.5501 loss_db: 0.1635 2022/10/26 03:18:38 - mmengine - INFO - Epoch(train) [573][45/63] lr: 1.9727e-03 eta: 8:37:00 time: 0.5078 data_time: 0.0087 memory: 16131 loss: 1.8476 loss_prob: 1.0935 loss_thr: 0.5834 loss_db: 0.1707 2022/10/26 03:18:40 - mmengine - INFO - Epoch(train) [573][50/63] lr: 1.9727e-03 eta: 8:36:50 time: 0.5376 data_time: 0.0232 memory: 16131 loss: 1.7177 loss_prob: 1.0197 loss_thr: 0.5356 loss_db: 0.1624 2022/10/26 03:18:43 - mmengine - INFO - Epoch(train) [573][55/63] lr: 1.9727e-03 eta: 8:36:50 time: 0.5397 data_time: 0.0191 memory: 16131 loss: 1.7036 loss_prob: 1.0319 loss_thr: 0.5081 loss_db: 0.1636 2022/10/26 03:18:45 - mmengine - INFO - Epoch(train) [573][60/63] lr: 1.9727e-03 eta: 8:36:39 time: 0.5093 data_time: 0.0078 memory: 16131 loss: 1.6003 loss_prob: 0.9442 loss_thr: 0.5088 loss_db: 0.1473 2022/10/26 03:18:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:18:51 - mmengine - INFO - Epoch(train) [574][5/63] lr: 1.9699e-03 eta: 8:36:39 time: 0.6866 data_time: 0.2083 memory: 16131 loss: 1.4474 loss_prob: 0.8103 loss_thr: 0.4998 loss_db: 0.1373 2022/10/26 03:18:54 - mmengine - INFO - Epoch(train) [574][10/63] lr: 1.9699e-03 eta: 8:36:25 time: 0.7241 data_time: 0.2081 memory: 16131 loss: 1.4844 loss_prob: 0.8337 loss_thr: 0.5086 loss_db: 0.1421 2022/10/26 03:18:57 - mmengine - INFO - Epoch(train) [574][15/63] lr: 1.9699e-03 eta: 8:36:25 time: 0.5408 data_time: 0.0067 memory: 16131 loss: 1.4246 loss_prob: 0.7933 loss_thr: 0.4979 loss_db: 0.1335 2022/10/26 03:18:59 - mmengine - INFO - Epoch(train) [574][20/63] lr: 1.9699e-03 eta: 8:36:15 time: 0.5336 data_time: 0.0069 memory: 16131 loss: 1.3479 loss_prob: 0.7470 loss_thr: 0.4783 loss_db: 0.1226 2022/10/26 03:19:02 - mmengine - INFO - Epoch(train) [574][25/63] lr: 1.9699e-03 eta: 8:36:15 time: 0.5588 data_time: 0.0421 memory: 16131 loss: 1.3282 loss_prob: 0.7316 loss_thr: 0.4743 loss_db: 0.1223 2022/10/26 03:19:05 - mmengine - INFO - Epoch(train) [574][30/63] lr: 1.9699e-03 eta: 8:36:05 time: 0.5767 data_time: 0.0413 memory: 16131 loss: 1.4725 loss_prob: 0.8245 loss_thr: 0.5078 loss_db: 0.1402 2022/10/26 03:19:08 - mmengine - INFO - Epoch(train) [574][35/63] lr: 1.9699e-03 eta: 8:36:05 time: 0.5326 data_time: 0.0043 memory: 16131 loss: 1.4234 loss_prob: 0.7829 loss_thr: 0.5073 loss_db: 0.1333 2022/10/26 03:19:10 - mmengine - INFO - Epoch(train) [574][40/63] lr: 1.9699e-03 eta: 8:35:54 time: 0.5062 data_time: 0.0043 memory: 16131 loss: 1.4027 loss_prob: 0.7715 loss_thr: 0.5013 loss_db: 0.1299 2022/10/26 03:19:13 - mmengine - INFO - Epoch(train) [574][45/63] lr: 1.9699e-03 eta: 8:35:54 time: 0.4956 data_time: 0.0043 memory: 16131 loss: 1.4601 loss_prob: 0.8095 loss_thr: 0.5152 loss_db: 0.1355 2022/10/26 03:19:15 - mmengine - INFO - Epoch(train) [574][50/63] lr: 1.9699e-03 eta: 8:35:43 time: 0.5200 data_time: 0.0233 memory: 16131 loss: 1.3785 loss_prob: 0.7522 loss_thr: 0.4987 loss_db: 0.1277 2022/10/26 03:19:18 - mmengine - INFO - Epoch(train) [574][55/63] lr: 1.9699e-03 eta: 8:35:43 time: 0.5361 data_time: 0.0236 memory: 16131 loss: 1.4393 loss_prob: 0.8087 loss_thr: 0.4945 loss_db: 0.1361 2022/10/26 03:19:20 - mmengine - INFO - Epoch(train) [574][60/63] lr: 1.9699e-03 eta: 8:35:32 time: 0.5028 data_time: 0.0060 memory: 16131 loss: 1.4045 loss_prob: 0.7869 loss_thr: 0.4873 loss_db: 0.1304 2022/10/26 03:19:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:19:26 - mmengine - INFO - Epoch(train) [575][5/63] lr: 1.9670e-03 eta: 8:35:32 time: 0.6815 data_time: 0.1982 memory: 16131 loss: 1.2880 loss_prob: 0.7129 loss_thr: 0.4565 loss_db: 0.1185 2022/10/26 03:19:29 - mmengine - INFO - Epoch(train) [575][10/63] lr: 1.9670e-03 eta: 8:35:18 time: 0.6929 data_time: 0.2012 memory: 16131 loss: 1.3325 loss_prob: 0.7312 loss_thr: 0.4790 loss_db: 0.1223 2022/10/26 03:19:31 - mmengine - INFO - Epoch(train) [575][15/63] lr: 1.9670e-03 eta: 8:35:18 time: 0.5258 data_time: 0.0097 memory: 16131 loss: 1.4871 loss_prob: 0.8321 loss_thr: 0.5194 loss_db: 0.1356 2022/10/26 03:19:34 - mmengine - INFO - Epoch(train) [575][20/63] lr: 1.9670e-03 eta: 8:35:08 time: 0.5580 data_time: 0.0074 memory: 16131 loss: 1.5299 loss_prob: 0.8722 loss_thr: 0.5168 loss_db: 0.1409 2022/10/26 03:19:37 - mmengine - INFO - Epoch(train) [575][25/63] lr: 1.9670e-03 eta: 8:35:08 time: 0.5623 data_time: 0.0270 memory: 16131 loss: 1.4259 loss_prob: 0.7983 loss_thr: 0.4954 loss_db: 0.1322 2022/10/26 03:19:40 - mmengine - INFO - Epoch(train) [575][30/63] lr: 1.9670e-03 eta: 8:34:57 time: 0.5353 data_time: 0.0279 memory: 16131 loss: 1.4358 loss_prob: 0.7976 loss_thr: 0.5056 loss_db: 0.1325 2022/10/26 03:19:42 - mmengine - INFO - Epoch(train) [575][35/63] lr: 1.9670e-03 eta: 8:34:57 time: 0.5053 data_time: 0.0164 memory: 16131 loss: 1.8693 loss_prob: 1.1517 loss_thr: 0.5477 loss_db: 0.1699 2022/10/26 03:19:45 - mmengine - INFO - Epoch(train) [575][40/63] lr: 1.9670e-03 eta: 8:34:47 time: 0.5010 data_time: 0.0157 memory: 16131 loss: 1.7075 loss_prob: 1.0502 loss_thr: 0.5048 loss_db: 0.1524 2022/10/26 03:19:47 - mmengine - INFO - Epoch(train) [575][45/63] lr: 1.9670e-03 eta: 8:34:47 time: 0.4924 data_time: 0.0059 memory: 16131 loss: 1.3199 loss_prob: 0.7322 loss_thr: 0.4649 loss_db: 0.1229 2022/10/26 03:19:50 - mmengine - INFO - Epoch(train) [575][50/63] lr: 1.9670e-03 eta: 8:34:36 time: 0.4972 data_time: 0.0185 memory: 16131 loss: 1.3404 loss_prob: 0.7394 loss_thr: 0.4768 loss_db: 0.1242 2022/10/26 03:19:52 - mmengine - INFO - Epoch(train) [575][55/63] lr: 1.9670e-03 eta: 8:34:36 time: 0.5031 data_time: 0.0242 memory: 16131 loss: 1.3251 loss_prob: 0.7266 loss_thr: 0.4758 loss_db: 0.1227 2022/10/26 03:19:55 - mmengine - INFO - Epoch(train) [575][60/63] lr: 1.9670e-03 eta: 8:34:25 time: 0.5382 data_time: 0.0125 memory: 16131 loss: 1.3840 loss_prob: 0.7604 loss_thr: 0.4925 loss_db: 0.1310 2022/10/26 03:19:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:20:01 - mmengine - INFO - Epoch(train) [576][5/63] lr: 1.9642e-03 eta: 8:34:25 time: 0.7622 data_time: 0.1896 memory: 16131 loss: 1.3564 loss_prob: 0.7458 loss_thr: 0.4840 loss_db: 0.1266 2022/10/26 03:20:04 - mmengine - INFO - Epoch(train) [576][10/63] lr: 1.9642e-03 eta: 8:34:12 time: 0.7765 data_time: 0.1850 memory: 16131 loss: 1.4076 loss_prob: 0.7845 loss_thr: 0.4895 loss_db: 0.1337 2022/10/26 03:20:07 - mmengine - INFO - Epoch(train) [576][15/63] lr: 1.9642e-03 eta: 8:34:12 time: 0.5142 data_time: 0.0047 memory: 16131 loss: 1.4190 loss_prob: 0.7856 loss_thr: 0.4986 loss_db: 0.1348 2022/10/26 03:20:10 - mmengine - INFO - Epoch(train) [576][20/63] lr: 1.9642e-03 eta: 8:34:02 time: 0.5584 data_time: 0.0118 memory: 16131 loss: 1.3010 loss_prob: 0.7015 loss_thr: 0.4780 loss_db: 0.1215 2022/10/26 03:20:12 - mmengine - INFO - Epoch(train) [576][25/63] lr: 1.9642e-03 eta: 8:34:02 time: 0.5627 data_time: 0.0254 memory: 16131 loss: 1.3003 loss_prob: 0.7081 loss_thr: 0.4715 loss_db: 0.1207 2022/10/26 03:20:15 - mmengine - INFO - Epoch(train) [576][30/63] lr: 1.9642e-03 eta: 8:33:51 time: 0.5089 data_time: 0.0324 memory: 16131 loss: 1.4239 loss_prob: 0.7949 loss_thr: 0.4956 loss_db: 0.1334 2022/10/26 03:20:17 - mmengine - INFO - Epoch(train) [576][35/63] lr: 1.9642e-03 eta: 8:33:51 time: 0.5112 data_time: 0.0201 memory: 16131 loss: 1.4509 loss_prob: 0.8095 loss_thr: 0.5058 loss_db: 0.1356 2022/10/26 03:20:20 - mmengine - INFO - Epoch(train) [576][40/63] lr: 1.9642e-03 eta: 8:33:41 time: 0.5324 data_time: 0.0061 memory: 16131 loss: 1.3704 loss_prob: 0.7494 loss_thr: 0.4947 loss_db: 0.1262 2022/10/26 03:20:23 - mmengine - INFO - Epoch(train) [576][45/63] lr: 1.9642e-03 eta: 8:33:41 time: 0.5744 data_time: 0.0085 memory: 16131 loss: 1.3181 loss_prob: 0.7130 loss_thr: 0.4837 loss_db: 0.1214 2022/10/26 03:20:26 - mmengine - INFO - Epoch(train) [576][50/63] lr: 1.9642e-03 eta: 8:33:31 time: 0.5800 data_time: 0.0199 memory: 16131 loss: 1.3185 loss_prob: 0.7236 loss_thr: 0.4737 loss_db: 0.1212 2022/10/26 03:20:29 - mmengine - INFO - Epoch(train) [576][55/63] lr: 1.9642e-03 eta: 8:33:31 time: 0.5588 data_time: 0.0227 memory: 16131 loss: 1.3846 loss_prob: 0.7606 loss_thr: 0.4962 loss_db: 0.1278 2022/10/26 03:20:31 - mmengine - INFO - Epoch(train) [576][60/63] lr: 1.9642e-03 eta: 8:33:20 time: 0.5234 data_time: 0.0113 memory: 16131 loss: 1.4430 loss_prob: 0.7894 loss_thr: 0.5208 loss_db: 0.1327 2022/10/26 03:20:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:20:37 - mmengine - INFO - Epoch(train) [577][5/63] lr: 1.9614e-03 eta: 8:33:20 time: 0.6624 data_time: 0.1913 memory: 16131 loss: 1.3496 loss_prob: 0.7452 loss_thr: 0.4763 loss_db: 0.1281 2022/10/26 03:20:39 - mmengine - INFO - Epoch(train) [577][10/63] lr: 1.9614e-03 eta: 8:33:06 time: 0.7047 data_time: 0.1927 memory: 16131 loss: 1.3172 loss_prob: 0.7083 loss_thr: 0.4909 loss_db: 0.1180 2022/10/26 03:20:42 - mmengine - INFO - Epoch(train) [577][15/63] lr: 1.9614e-03 eta: 8:33:06 time: 0.5257 data_time: 0.0066 memory: 16131 loss: 1.3599 loss_prob: 0.7284 loss_thr: 0.5097 loss_db: 0.1218 2022/10/26 03:20:45 - mmengine - INFO - Epoch(train) [577][20/63] lr: 1.9614e-03 eta: 8:32:56 time: 0.5379 data_time: 0.0084 memory: 16131 loss: 1.4383 loss_prob: 0.7872 loss_thr: 0.5163 loss_db: 0.1348 2022/10/26 03:20:48 - mmengine - INFO - Epoch(train) [577][25/63] lr: 1.9614e-03 eta: 8:32:56 time: 0.6026 data_time: 0.0149 memory: 16131 loss: 1.4013 loss_prob: 0.7624 loss_thr: 0.5067 loss_db: 0.1322 2022/10/26 03:20:51 - mmengine - INFO - Epoch(train) [577][30/63] lr: 1.9614e-03 eta: 8:32:46 time: 0.6206 data_time: 0.0345 memory: 16131 loss: 1.3738 loss_prob: 0.7477 loss_thr: 0.4986 loss_db: 0.1275 2022/10/26 03:20:53 - mmengine - INFO - Epoch(train) [577][35/63] lr: 1.9614e-03 eta: 8:32:46 time: 0.5411 data_time: 0.0280 memory: 16131 loss: 1.3502 loss_prob: 0.7439 loss_thr: 0.4823 loss_db: 0.1240 2022/10/26 03:20:56 - mmengine - INFO - Epoch(train) [577][40/63] lr: 1.9614e-03 eta: 8:32:35 time: 0.4904 data_time: 0.0060 memory: 16131 loss: 1.3852 loss_prob: 0.7690 loss_thr: 0.4880 loss_db: 0.1282 2022/10/26 03:20:58 - mmengine - INFO - Epoch(train) [577][45/63] lr: 1.9614e-03 eta: 8:32:35 time: 0.4837 data_time: 0.0054 memory: 16131 loss: 1.3681 loss_prob: 0.7477 loss_thr: 0.4930 loss_db: 0.1274 2022/10/26 03:21:01 - mmengine - INFO - Epoch(train) [577][50/63] lr: 1.9614e-03 eta: 8:32:24 time: 0.4989 data_time: 0.0117 memory: 16131 loss: 1.2610 loss_prob: 0.6772 loss_thr: 0.4694 loss_db: 0.1145 2022/10/26 03:21:03 - mmengine - INFO - Epoch(train) [577][55/63] lr: 1.9614e-03 eta: 8:32:24 time: 0.5152 data_time: 0.0215 memory: 16131 loss: 1.3513 loss_prob: 0.7489 loss_thr: 0.4789 loss_db: 0.1235 2022/10/26 03:21:06 - mmengine - INFO - Epoch(train) [577][60/63] lr: 1.9614e-03 eta: 8:32:14 time: 0.5315 data_time: 0.0143 memory: 16131 loss: 1.4141 loss_prob: 0.7832 loss_thr: 0.4996 loss_db: 0.1313 2022/10/26 03:21:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:21:12 - mmengine - INFO - Epoch(train) [578][5/63] lr: 1.9585e-03 eta: 8:32:14 time: 0.6932 data_time: 0.1897 memory: 16131 loss: 1.3876 loss_prob: 0.7583 loss_thr: 0.4976 loss_db: 0.1316 2022/10/26 03:21:15 - mmengine - INFO - Epoch(train) [578][10/63] lr: 1.9585e-03 eta: 8:32:01 time: 0.7652 data_time: 0.1900 memory: 16131 loss: 1.3483 loss_prob: 0.7356 loss_thr: 0.4847 loss_db: 0.1280 2022/10/26 03:21:18 - mmengine - INFO - Epoch(train) [578][15/63] lr: 1.9585e-03 eta: 8:32:01 time: 0.5533 data_time: 0.0070 memory: 16131 loss: 1.3844 loss_prob: 0.7801 loss_thr: 0.4724 loss_db: 0.1318 2022/10/26 03:21:20 - mmengine - INFO - Epoch(train) [578][20/63] lr: 1.9585e-03 eta: 8:31:50 time: 0.5092 data_time: 0.0096 memory: 16131 loss: 1.3784 loss_prob: 0.7686 loss_thr: 0.4793 loss_db: 0.1305 2022/10/26 03:21:23 - mmengine - INFO - Epoch(train) [578][25/63] lr: 1.9585e-03 eta: 8:31:50 time: 0.5380 data_time: 0.0133 memory: 16131 loss: 1.3180 loss_prob: 0.7156 loss_thr: 0.4806 loss_db: 0.1218 2022/10/26 03:21:26 - mmengine - INFO - Epoch(train) [578][30/63] lr: 1.9585e-03 eta: 8:31:40 time: 0.5572 data_time: 0.0366 memory: 16131 loss: 1.4650 loss_prob: 0.8212 loss_thr: 0.5027 loss_db: 0.1411 2022/10/26 03:21:28 - mmengine - INFO - Epoch(train) [578][35/63] lr: 1.9585e-03 eta: 8:31:40 time: 0.5189 data_time: 0.0327 memory: 16131 loss: 1.5698 loss_prob: 0.8989 loss_thr: 0.5232 loss_db: 0.1476 2022/10/26 03:21:31 - mmengine - INFO - Epoch(train) [578][40/63] lr: 1.9585e-03 eta: 8:31:29 time: 0.5249 data_time: 0.0070 memory: 16131 loss: 1.5818 loss_prob: 0.9133 loss_thr: 0.5243 loss_db: 0.1442 2022/10/26 03:21:33 - mmengine - INFO - Epoch(train) [578][45/63] lr: 1.9585e-03 eta: 8:31:29 time: 0.5173 data_time: 0.0055 memory: 16131 loss: 1.4183 loss_prob: 0.8122 loss_thr: 0.4727 loss_db: 0.1334 2022/10/26 03:21:36 - mmengine - INFO - Epoch(train) [578][50/63] lr: 1.9585e-03 eta: 8:31:18 time: 0.5041 data_time: 0.0084 memory: 16131 loss: 1.3638 loss_prob: 0.7720 loss_thr: 0.4648 loss_db: 0.1270 2022/10/26 03:21:39 - mmengine - INFO - Epoch(train) [578][55/63] lr: 1.9585e-03 eta: 8:31:18 time: 0.5441 data_time: 0.0216 memory: 16131 loss: 1.4142 loss_prob: 0.7893 loss_thr: 0.4918 loss_db: 0.1331 2022/10/26 03:21:41 - mmengine - INFO - Epoch(train) [578][60/63] lr: 1.9585e-03 eta: 8:31:08 time: 0.5209 data_time: 0.0189 memory: 16131 loss: 1.3908 loss_prob: 0.7677 loss_thr: 0.4917 loss_db: 0.1314 2022/10/26 03:21:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:21:48 - mmengine - INFO - Epoch(train) [579][5/63] lr: 1.9557e-03 eta: 8:31:08 time: 0.7478 data_time: 0.1792 memory: 16131 loss: 1.3782 loss_prob: 0.7387 loss_thr: 0.5141 loss_db: 0.1254 2022/10/26 03:21:50 - mmengine - INFO - Epoch(train) [579][10/63] lr: 1.9557e-03 eta: 8:30:55 time: 0.7916 data_time: 0.1753 memory: 16131 loss: 1.4149 loss_prob: 0.7646 loss_thr: 0.5187 loss_db: 0.1316 2022/10/26 03:21:53 - mmengine - INFO - Epoch(train) [579][15/63] lr: 1.9557e-03 eta: 8:30:55 time: 0.5297 data_time: 0.0053 memory: 16131 loss: 1.4049 loss_prob: 0.7724 loss_thr: 0.5000 loss_db: 0.1325 2022/10/26 03:21:56 - mmengine - INFO - Epoch(train) [579][20/63] lr: 1.9557e-03 eta: 8:30:45 time: 0.5211 data_time: 0.0064 memory: 16131 loss: 1.3904 loss_prob: 0.7799 loss_thr: 0.4788 loss_db: 0.1316 2022/10/26 03:21:58 - mmengine - INFO - Epoch(train) [579][25/63] lr: 1.9557e-03 eta: 8:30:45 time: 0.5374 data_time: 0.0211 memory: 16131 loss: 1.4010 loss_prob: 0.7875 loss_thr: 0.4834 loss_db: 0.1302 2022/10/26 03:22:01 - mmengine - INFO - Epoch(train) [579][30/63] lr: 1.9557e-03 eta: 8:30:34 time: 0.5576 data_time: 0.0407 memory: 16131 loss: 1.3331 loss_prob: 0.7386 loss_thr: 0.4716 loss_db: 0.1230 2022/10/26 03:22:04 - mmengine - INFO - Epoch(train) [579][35/63] lr: 1.9557e-03 eta: 8:30:34 time: 0.5444 data_time: 0.0308 memory: 16131 loss: 1.2812 loss_prob: 0.6977 loss_thr: 0.4650 loss_db: 0.1185 2022/10/26 03:22:06 - mmengine - INFO - Epoch(train) [579][40/63] lr: 1.9557e-03 eta: 8:30:24 time: 0.5136 data_time: 0.0107 memory: 16131 loss: 1.2557 loss_prob: 0.6855 loss_thr: 0.4558 loss_db: 0.1145 2022/10/26 03:22:09 - mmengine - INFO - Epoch(train) [579][45/63] lr: 1.9557e-03 eta: 8:30:24 time: 0.4997 data_time: 0.0061 memory: 16131 loss: 1.3145 loss_prob: 0.7245 loss_thr: 0.4701 loss_db: 0.1199 2022/10/26 03:22:11 - mmengine - INFO - Epoch(train) [579][50/63] lr: 1.9557e-03 eta: 8:30:13 time: 0.4968 data_time: 0.0147 memory: 16131 loss: 1.3615 loss_prob: 0.7468 loss_thr: 0.4873 loss_db: 0.1274 2022/10/26 03:22:14 - mmengine - INFO - Epoch(train) [579][55/63] lr: 1.9557e-03 eta: 8:30:13 time: 0.5298 data_time: 0.0234 memory: 16131 loss: 1.3264 loss_prob: 0.7257 loss_thr: 0.4755 loss_db: 0.1252 2022/10/26 03:22:17 - mmengine - INFO - Epoch(train) [579][60/63] lr: 1.9557e-03 eta: 8:30:02 time: 0.5235 data_time: 0.0157 memory: 16131 loss: 1.3738 loss_prob: 0.7602 loss_thr: 0.4875 loss_db: 0.1261 2022/10/26 03:22:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:22:22 - mmengine - INFO - Epoch(train) [580][5/63] lr: 1.9529e-03 eta: 8:30:02 time: 0.6549 data_time: 0.1709 memory: 16131 loss: 1.3701 loss_prob: 0.7440 loss_thr: 0.5005 loss_db: 0.1257 2022/10/26 03:22:25 - mmengine - INFO - Epoch(train) [580][10/63] lr: 1.9529e-03 eta: 8:29:49 time: 0.6982 data_time: 0.1707 memory: 16131 loss: 1.2879 loss_prob: 0.6922 loss_thr: 0.4761 loss_db: 0.1196 2022/10/26 03:22:27 - mmengine - INFO - Epoch(train) [580][15/63] lr: 1.9529e-03 eta: 8:29:49 time: 0.5229 data_time: 0.0070 memory: 16131 loss: 1.2951 loss_prob: 0.7101 loss_thr: 0.4628 loss_db: 0.1221 2022/10/26 03:22:30 - mmengine - INFO - Epoch(train) [580][20/63] lr: 1.9529e-03 eta: 8:29:38 time: 0.5309 data_time: 0.0076 memory: 16131 loss: 1.3172 loss_prob: 0.7293 loss_thr: 0.4628 loss_db: 0.1251 2022/10/26 03:22:33 - mmengine - INFO - Epoch(train) [580][25/63] lr: 1.9529e-03 eta: 8:29:38 time: 0.5654 data_time: 0.0089 memory: 16131 loss: 1.2966 loss_prob: 0.7066 loss_thr: 0.4704 loss_db: 0.1196 2022/10/26 03:22:36 - mmengine - INFO - Epoch(train) [580][30/63] lr: 1.9529e-03 eta: 8:29:28 time: 0.5744 data_time: 0.0319 memory: 16131 loss: 1.2415 loss_prob: 0.6635 loss_thr: 0.4650 loss_db: 0.1131 2022/10/26 03:22:38 - mmengine - INFO - Epoch(train) [580][35/63] lr: 1.9529e-03 eta: 8:29:28 time: 0.5352 data_time: 0.0289 memory: 16131 loss: 1.2211 loss_prob: 0.6498 loss_thr: 0.4604 loss_db: 0.1108 2022/10/26 03:22:41 - mmengine - INFO - Epoch(train) [580][40/63] lr: 1.9529e-03 eta: 8:29:17 time: 0.5123 data_time: 0.0095 memory: 16131 loss: 1.4197 loss_prob: 0.7906 loss_thr: 0.4983 loss_db: 0.1308 2022/10/26 03:22:44 - mmengine - INFO - Epoch(train) [580][45/63] lr: 1.9529e-03 eta: 8:29:17 time: 0.5322 data_time: 0.0093 memory: 16131 loss: 1.4432 loss_prob: 0.8090 loss_thr: 0.4987 loss_db: 0.1354 2022/10/26 03:22:46 - mmengine - INFO - Epoch(train) [580][50/63] lr: 1.9529e-03 eta: 8:29:07 time: 0.5175 data_time: 0.0133 memory: 16131 loss: 1.3504 loss_prob: 0.7448 loss_thr: 0.4801 loss_db: 0.1254 2022/10/26 03:22:49 - mmengine - INFO - Epoch(train) [580][55/63] lr: 1.9529e-03 eta: 8:29:07 time: 0.4958 data_time: 0.0206 memory: 16131 loss: 1.3865 loss_prob: 0.7601 loss_thr: 0.5004 loss_db: 0.1259 2022/10/26 03:22:51 - mmengine - INFO - Epoch(train) [580][60/63] lr: 1.9529e-03 eta: 8:28:56 time: 0.4923 data_time: 0.0130 memory: 16131 loss: 1.4031 loss_prob: 0.7648 loss_thr: 0.5086 loss_db: 0.1297 2022/10/26 03:22:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:22:52 - mmengine - INFO - Saving checkpoint at 580 epochs 2022/10/26 03:22:59 - mmengine - INFO - Epoch(val) [580][5/32] eta: 8:28:56 time: 0.5466 data_time: 0.0692 memory: 16131 2022/10/26 03:23:01 - mmengine - INFO - Epoch(val) [580][10/32] eta: 0:00:12 time: 0.5620 data_time: 0.0691 memory: 15724 2022/10/26 03:23:04 - mmengine - INFO - Epoch(val) [580][15/32] eta: 0:00:12 time: 0.5326 data_time: 0.0385 memory: 15724 2022/10/26 03:23:07 - mmengine - INFO - Epoch(val) [580][20/32] eta: 0:00:06 time: 0.5610 data_time: 0.0666 memory: 15724 2022/10/26 03:23:10 - mmengine - INFO - Epoch(val) [580][25/32] eta: 0:00:06 time: 0.5646 data_time: 0.0455 memory: 15724 2022/10/26 03:23:13 - mmengine - INFO - Epoch(val) [580][30/32] eta: 0:00:01 time: 0.5511 data_time: 0.0215 memory: 15724 2022/10/26 03:23:13 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8344, precision: 0.6741, hmean: 0.7457 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8344, precision: 0.7518, hmean: 0.7910 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8329, precision: 0.7910, hmean: 0.8114 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8276, precision: 0.8229, hmean: 0.8253 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8040, precision: 0.8653, hmean: 0.8335 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6076, precision: 0.9286, hmean: 0.7346 2022/10/26 03:23:13 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0178, precision: 1.0000, hmean: 0.0350 2022/10/26 03:23:13 - mmengine - INFO - Epoch(val) [580][32/32] icdar/precision: 0.8653 icdar/recall: 0.8040 icdar/hmean: 0.8335 2022/10/26 03:23:18 - mmengine - INFO - Epoch(train) [581][5/63] lr: 1.9500e-03 eta: 0:00:01 time: 0.6495 data_time: 0.1587 memory: 16131 loss: 1.3508 loss_prob: 0.7360 loss_thr: 0.4900 loss_db: 0.1248 2022/10/26 03:23:20 - mmengine - INFO - Epoch(train) [581][10/63] lr: 1.9500e-03 eta: 8:28:42 time: 0.7148 data_time: 0.1638 memory: 16131 loss: 1.3240 loss_prob: 0.7247 loss_thr: 0.4770 loss_db: 0.1224 2022/10/26 03:23:23 - mmengine - INFO - Epoch(train) [581][15/63] lr: 1.9500e-03 eta: 8:28:42 time: 0.5365 data_time: 0.0132 memory: 16131 loss: 1.3382 loss_prob: 0.7393 loss_thr: 0.4757 loss_db: 0.1231 2022/10/26 03:23:26 - mmengine - INFO - Epoch(train) [581][20/63] lr: 1.9500e-03 eta: 8:28:32 time: 0.5134 data_time: 0.0124 memory: 16131 loss: 1.4024 loss_prob: 0.7828 loss_thr: 0.4866 loss_db: 0.1329 2022/10/26 03:23:28 - mmengine - INFO - Epoch(train) [581][25/63] lr: 1.9500e-03 eta: 8:28:32 time: 0.5339 data_time: 0.0265 memory: 16131 loss: 1.4094 loss_prob: 0.7713 loss_thr: 0.5105 loss_db: 0.1277 2022/10/26 03:23:31 - mmengine - INFO - Epoch(train) [581][30/63] lr: 1.9500e-03 eta: 8:28:21 time: 0.5234 data_time: 0.0206 memory: 16131 loss: 1.4379 loss_prob: 0.7972 loss_thr: 0.5135 loss_db: 0.1272 2022/10/26 03:23:34 - mmengine - INFO - Epoch(train) [581][35/63] lr: 1.9500e-03 eta: 8:28:21 time: 0.5227 data_time: 0.0130 memory: 16131 loss: 1.4200 loss_prob: 0.7943 loss_thr: 0.4941 loss_db: 0.1315 2022/10/26 03:23:36 - mmengine - INFO - Epoch(train) [581][40/63] lr: 1.9500e-03 eta: 8:28:11 time: 0.5414 data_time: 0.0170 memory: 16131 loss: 1.4424 loss_prob: 0.8024 loss_thr: 0.5053 loss_db: 0.1347 2022/10/26 03:23:39 - mmengine - INFO - Epoch(train) [581][45/63] lr: 1.9500e-03 eta: 8:28:11 time: 0.5215 data_time: 0.0129 memory: 16131 loss: 1.4961 loss_prob: 0.8474 loss_thr: 0.5054 loss_db: 0.1432 2022/10/26 03:23:41 - mmengine - INFO - Epoch(train) [581][50/63] lr: 1.9500e-03 eta: 8:28:00 time: 0.5222 data_time: 0.0179 memory: 16131 loss: 1.3998 loss_prob: 0.7802 loss_thr: 0.4878 loss_db: 0.1318 2022/10/26 03:23:44 - mmengine - INFO - Epoch(train) [581][55/63] lr: 1.9500e-03 eta: 8:28:00 time: 0.5407 data_time: 0.0133 memory: 16131 loss: 1.2918 loss_prob: 0.6885 loss_thr: 0.4876 loss_db: 0.1157 2022/10/26 03:23:47 - mmengine - INFO - Epoch(train) [581][60/63] lr: 1.9500e-03 eta: 8:27:50 time: 0.5278 data_time: 0.0109 memory: 16131 loss: 1.3827 loss_prob: 0.7385 loss_thr: 0.5184 loss_db: 0.1259 2022/10/26 03:23:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:23:53 - mmengine - INFO - Epoch(train) [582][5/63] lr: 1.9472e-03 eta: 8:27:50 time: 0.7032 data_time: 0.2010 memory: 16131 loss: 1.4902 loss_prob: 0.8308 loss_thr: 0.5190 loss_db: 0.1404 2022/10/26 03:23:55 - mmengine - INFO - Epoch(train) [582][10/63] lr: 1.9472e-03 eta: 8:27:36 time: 0.7274 data_time: 0.2110 memory: 16131 loss: 1.4894 loss_prob: 0.8388 loss_thr: 0.5101 loss_db: 0.1405 2022/10/26 03:23:58 - mmengine - INFO - Epoch(train) [582][15/63] lr: 1.9472e-03 eta: 8:27:36 time: 0.5227 data_time: 0.0176 memory: 16131 loss: 1.4652 loss_prob: 0.8284 loss_thr: 0.4961 loss_db: 0.1407 2022/10/26 03:24:01 - mmengine - INFO - Epoch(train) [582][20/63] lr: 1.9472e-03 eta: 8:27:26 time: 0.5164 data_time: 0.0062 memory: 16131 loss: 1.3001 loss_prob: 0.7187 loss_thr: 0.4602 loss_db: 0.1212 2022/10/26 03:24:03 - mmengine - INFO - Epoch(train) [582][25/63] lr: 1.9472e-03 eta: 8:27:26 time: 0.5350 data_time: 0.0184 memory: 16131 loss: 1.3213 loss_prob: 0.7216 loss_thr: 0.4780 loss_db: 0.1217 2022/10/26 03:24:06 - mmengine - INFO - Epoch(train) [582][30/63] lr: 1.9472e-03 eta: 8:27:16 time: 0.5665 data_time: 0.0247 memory: 16131 loss: 1.4650 loss_prob: 0.8140 loss_thr: 0.5163 loss_db: 0.1346 2022/10/26 03:24:09 - mmengine - INFO - Epoch(train) [582][35/63] lr: 1.9472e-03 eta: 8:27:16 time: 0.5510 data_time: 0.0248 memory: 16131 loss: 1.3861 loss_prob: 0.7647 loss_thr: 0.4943 loss_db: 0.1271 2022/10/26 03:24:12 - mmengine - INFO - Epoch(train) [582][40/63] lr: 1.9472e-03 eta: 8:27:05 time: 0.5587 data_time: 0.0180 memory: 16131 loss: 1.3812 loss_prob: 0.7684 loss_thr: 0.4819 loss_db: 0.1308 2022/10/26 03:24:15 - mmengine - INFO - Epoch(train) [582][45/63] lr: 1.9472e-03 eta: 8:27:05 time: 0.5788 data_time: 0.0050 memory: 16131 loss: 1.3342 loss_prob: 0.7467 loss_thr: 0.4645 loss_db: 0.1230 2022/10/26 03:24:17 - mmengine - INFO - Epoch(train) [582][50/63] lr: 1.9472e-03 eta: 8:26:55 time: 0.5622 data_time: 0.0127 memory: 16131 loss: 1.3035 loss_prob: 0.7164 loss_thr: 0.4675 loss_db: 0.1196 2022/10/26 03:24:20 - mmengine - INFO - Epoch(train) [582][55/63] lr: 1.9472e-03 eta: 8:26:55 time: 0.5325 data_time: 0.0185 memory: 16131 loss: 1.4551 loss_prob: 0.8154 loss_thr: 0.5016 loss_db: 0.1382 2022/10/26 03:24:22 - mmengine - INFO - Epoch(train) [582][60/63] lr: 1.9472e-03 eta: 8:26:45 time: 0.4999 data_time: 0.0151 memory: 16131 loss: 1.5075 loss_prob: 0.8348 loss_thr: 0.5299 loss_db: 0.1428 2022/10/26 03:24:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:24:29 - mmengine - INFO - Epoch(train) [583][5/63] lr: 1.9444e-03 eta: 8:26:45 time: 0.7228 data_time: 0.2137 memory: 16131 loss: 1.4317 loss_prob: 0.7760 loss_thr: 0.5241 loss_db: 0.1317 2022/10/26 03:24:31 - mmengine - INFO - Epoch(train) [583][10/63] lr: 1.9444e-03 eta: 8:26:32 time: 0.7472 data_time: 0.2131 memory: 16131 loss: 1.3651 loss_prob: 0.7458 loss_thr: 0.4906 loss_db: 0.1287 2022/10/26 03:24:34 - mmengine - INFO - Epoch(train) [583][15/63] lr: 1.9444e-03 eta: 8:26:32 time: 0.5095 data_time: 0.0101 memory: 16131 loss: 1.4795 loss_prob: 0.8491 loss_thr: 0.4921 loss_db: 0.1383 2022/10/26 03:24:36 - mmengine - INFO - Epoch(train) [583][20/63] lr: 1.9444e-03 eta: 8:26:21 time: 0.5218 data_time: 0.0161 memory: 16131 loss: 1.5632 loss_prob: 0.9101 loss_thr: 0.5049 loss_db: 0.1482 2022/10/26 03:24:39 - mmengine - INFO - Epoch(train) [583][25/63] lr: 1.9444e-03 eta: 8:26:21 time: 0.5220 data_time: 0.0229 memory: 16131 loss: 1.5069 loss_prob: 0.8541 loss_thr: 0.5076 loss_db: 0.1451 2022/10/26 03:24:42 - mmengine - INFO - Epoch(train) [583][30/63] lr: 1.9444e-03 eta: 8:26:11 time: 0.5363 data_time: 0.0417 memory: 16131 loss: 1.4996 loss_prob: 0.8343 loss_thr: 0.5251 loss_db: 0.1402 2022/10/26 03:24:44 - mmengine - INFO - Epoch(train) [583][35/63] lr: 1.9444e-03 eta: 8:26:11 time: 0.5426 data_time: 0.0325 memory: 16131 loss: 1.4597 loss_prob: 0.8080 loss_thr: 0.5148 loss_db: 0.1369 2022/10/26 03:24:47 - mmengine - INFO - Epoch(train) [583][40/63] lr: 1.9444e-03 eta: 8:26:00 time: 0.5238 data_time: 0.0086 memory: 16131 loss: 1.4273 loss_prob: 0.7924 loss_thr: 0.4997 loss_db: 0.1352 2022/10/26 03:24:50 - mmengine - INFO - Epoch(train) [583][45/63] lr: 1.9444e-03 eta: 8:26:00 time: 0.5030 data_time: 0.0091 memory: 16131 loss: 1.4034 loss_prob: 0.7774 loss_thr: 0.4935 loss_db: 0.1325 2022/10/26 03:24:52 - mmengine - INFO - Epoch(train) [583][50/63] lr: 1.9444e-03 eta: 8:25:49 time: 0.5057 data_time: 0.0247 memory: 16131 loss: 1.3043 loss_prob: 0.7143 loss_thr: 0.4704 loss_db: 0.1196 2022/10/26 03:24:55 - mmengine - INFO - Epoch(train) [583][55/63] lr: 1.9444e-03 eta: 8:25:49 time: 0.5221 data_time: 0.0223 memory: 16131 loss: 1.2910 loss_prob: 0.6880 loss_thr: 0.4877 loss_db: 0.1153 2022/10/26 03:24:57 - mmengine - INFO - Epoch(train) [583][60/63] lr: 1.9444e-03 eta: 8:25:39 time: 0.4988 data_time: 0.0044 memory: 16131 loss: 1.3252 loss_prob: 0.7060 loss_thr: 0.5010 loss_db: 0.1182 2022/10/26 03:24:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:25:03 - mmengine - INFO - Epoch(train) [584][5/63] lr: 1.9415e-03 eta: 8:25:39 time: 0.6976 data_time: 0.1817 memory: 16131 loss: 1.3501 loss_prob: 0.7505 loss_thr: 0.4769 loss_db: 0.1227 2022/10/26 03:25:06 - mmengine - INFO - Epoch(train) [584][10/63] lr: 1.9415e-03 eta: 8:25:25 time: 0.7264 data_time: 0.1824 memory: 16131 loss: 1.2953 loss_prob: 0.7020 loss_thr: 0.4748 loss_db: 0.1186 2022/10/26 03:25:08 - mmengine - INFO - Epoch(train) [584][15/63] lr: 1.9415e-03 eta: 8:25:25 time: 0.5263 data_time: 0.0079 memory: 16131 loss: 1.2140 loss_prob: 0.6500 loss_thr: 0.4510 loss_db: 0.1129 2022/10/26 03:25:11 - mmengine - INFO - Epoch(train) [584][20/63] lr: 1.9415e-03 eta: 8:25:15 time: 0.4958 data_time: 0.0080 memory: 16131 loss: 1.3622 loss_prob: 0.7392 loss_thr: 0.4976 loss_db: 0.1254 2022/10/26 03:25:14 - mmengine - INFO - Epoch(train) [584][25/63] lr: 1.9415e-03 eta: 8:25:15 time: 0.5201 data_time: 0.0128 memory: 16131 loss: 1.4147 loss_prob: 0.7757 loss_thr: 0.5083 loss_db: 0.1306 2022/10/26 03:25:16 - mmengine - INFO - Epoch(train) [584][30/63] lr: 1.9415e-03 eta: 8:25:04 time: 0.5309 data_time: 0.0293 memory: 16131 loss: 1.3615 loss_prob: 0.7455 loss_thr: 0.4869 loss_db: 0.1292 2022/10/26 03:25:19 - mmengine - INFO - Epoch(train) [584][35/63] lr: 1.9415e-03 eta: 8:25:04 time: 0.5192 data_time: 0.0219 memory: 16131 loss: 1.3125 loss_prob: 0.7196 loss_thr: 0.4674 loss_db: 0.1256 2022/10/26 03:25:22 - mmengine - INFO - Epoch(train) [584][40/63] lr: 1.9415e-03 eta: 8:24:54 time: 0.5386 data_time: 0.0081 memory: 16131 loss: 1.3599 loss_prob: 0.7451 loss_thr: 0.4877 loss_db: 0.1271 2022/10/26 03:25:24 - mmengine - INFO - Epoch(train) [584][45/63] lr: 1.9415e-03 eta: 8:24:54 time: 0.5212 data_time: 0.0101 memory: 16131 loss: 1.3509 loss_prob: 0.7387 loss_thr: 0.4873 loss_db: 0.1249 2022/10/26 03:25:27 - mmengine - INFO - Epoch(train) [584][50/63] lr: 1.9415e-03 eta: 8:24:43 time: 0.5134 data_time: 0.0162 memory: 16131 loss: 1.3916 loss_prob: 0.7734 loss_thr: 0.4865 loss_db: 0.1316 2022/10/26 03:25:30 - mmengine - INFO - Epoch(train) [584][55/63] lr: 1.9415e-03 eta: 8:24:43 time: 0.5581 data_time: 0.0193 memory: 16131 loss: 1.4584 loss_prob: 0.8059 loss_thr: 0.5122 loss_db: 0.1403 2022/10/26 03:25:32 - mmengine - INFO - Epoch(train) [584][60/63] lr: 1.9415e-03 eta: 8:24:33 time: 0.5523 data_time: 0.0105 memory: 16131 loss: 1.3797 loss_prob: 0.7559 loss_thr: 0.4932 loss_db: 0.1307 2022/10/26 03:25:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:25:38 - mmengine - INFO - Epoch(train) [585][5/63] lr: 1.9387e-03 eta: 8:24:33 time: 0.6663 data_time: 0.1722 memory: 16131 loss: 1.3988 loss_prob: 0.7916 loss_thr: 0.4771 loss_db: 0.1301 2022/10/26 03:25:41 - mmengine - INFO - Epoch(train) [585][10/63] lr: 1.9387e-03 eta: 8:24:20 time: 0.7178 data_time: 0.1754 memory: 16131 loss: 1.2864 loss_prob: 0.7083 loss_thr: 0.4590 loss_db: 0.1192 2022/10/26 03:25:43 - mmengine - INFO - Epoch(train) [585][15/63] lr: 1.9387e-03 eta: 8:24:20 time: 0.5175 data_time: 0.0107 memory: 16131 loss: 1.3036 loss_prob: 0.6856 loss_thr: 0.5010 loss_db: 0.1169 2022/10/26 03:25:45 - mmengine - INFO - Epoch(train) [585][20/63] lr: 1.9387e-03 eta: 8:24:09 time: 0.4804 data_time: 0.0060 memory: 16131 loss: 1.3244 loss_prob: 0.7048 loss_thr: 0.4973 loss_db: 0.1224 2022/10/26 03:25:48 - mmengine - INFO - Epoch(train) [585][25/63] lr: 1.9387e-03 eta: 8:24:09 time: 0.4961 data_time: 0.0138 memory: 16131 loss: 1.2598 loss_prob: 0.6799 loss_thr: 0.4650 loss_db: 0.1148 2022/10/26 03:25:51 - mmengine - INFO - Epoch(train) [585][30/63] lr: 1.9387e-03 eta: 8:23:58 time: 0.5310 data_time: 0.0332 memory: 16131 loss: 1.3102 loss_prob: 0.7063 loss_thr: 0.4850 loss_db: 0.1190 2022/10/26 03:25:53 - mmengine - INFO - Epoch(train) [585][35/63] lr: 1.9387e-03 eta: 8:23:58 time: 0.5230 data_time: 0.0244 memory: 16131 loss: 1.3558 loss_prob: 0.7440 loss_thr: 0.4853 loss_db: 0.1266 2022/10/26 03:25:56 - mmengine - INFO - Epoch(train) [585][40/63] lr: 1.9387e-03 eta: 8:23:48 time: 0.5113 data_time: 0.0056 memory: 16131 loss: 1.2968 loss_prob: 0.7035 loss_thr: 0.4737 loss_db: 0.1195 2022/10/26 03:25:59 - mmengine - INFO - Epoch(train) [585][45/63] lr: 1.9387e-03 eta: 8:23:48 time: 0.5225 data_time: 0.0063 memory: 16131 loss: 1.3899 loss_prob: 0.7559 loss_thr: 0.5031 loss_db: 0.1310 2022/10/26 03:26:01 - mmengine - INFO - Epoch(train) [585][50/63] lr: 1.9387e-03 eta: 8:23:37 time: 0.5123 data_time: 0.0106 memory: 16131 loss: 1.4069 loss_prob: 0.7683 loss_thr: 0.5064 loss_db: 0.1322 2022/10/26 03:26:04 - mmengine - INFO - Epoch(train) [585][55/63] lr: 1.9387e-03 eta: 8:23:37 time: 0.5087 data_time: 0.0205 memory: 16131 loss: 1.4038 loss_prob: 0.7736 loss_thr: 0.5002 loss_db: 0.1300 2022/10/26 03:26:06 - mmengine - INFO - Epoch(train) [585][60/63] lr: 1.9387e-03 eta: 8:23:26 time: 0.5107 data_time: 0.0165 memory: 16131 loss: 1.3440 loss_prob: 0.7370 loss_thr: 0.4798 loss_db: 0.1272 2022/10/26 03:26:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:26:12 - mmengine - INFO - Epoch(train) [586][5/63] lr: 1.9359e-03 eta: 8:23:26 time: 0.6591 data_time: 0.1705 memory: 16131 loss: 1.2700 loss_prob: 0.6953 loss_thr: 0.4570 loss_db: 0.1177 2022/10/26 03:26:14 - mmengine - INFO - Epoch(train) [586][10/63] lr: 1.9359e-03 eta: 8:23:13 time: 0.6835 data_time: 0.1705 memory: 16131 loss: 1.3460 loss_prob: 0.7406 loss_thr: 0.4818 loss_db: 0.1235 2022/10/26 03:26:17 - mmengine - INFO - Epoch(train) [586][15/63] lr: 1.9359e-03 eta: 8:23:13 time: 0.5573 data_time: 0.0061 memory: 16131 loss: 1.4246 loss_prob: 0.7923 loss_thr: 0.5022 loss_db: 0.1302 2022/10/26 03:26:20 - mmengine - INFO - Epoch(train) [586][20/63] lr: 1.9359e-03 eta: 8:23:03 time: 0.5475 data_time: 0.0072 memory: 16131 loss: 1.4082 loss_prob: 0.7768 loss_thr: 0.5033 loss_db: 0.1281 2022/10/26 03:26:22 - mmengine - INFO - Epoch(train) [586][25/63] lr: 1.9359e-03 eta: 8:23:03 time: 0.5216 data_time: 0.0227 memory: 16131 loss: 1.2868 loss_prob: 0.6995 loss_thr: 0.4685 loss_db: 0.1188 2022/10/26 03:26:25 - mmengine - INFO - Epoch(train) [586][30/63] lr: 1.9359e-03 eta: 8:22:52 time: 0.5199 data_time: 0.0326 memory: 16131 loss: 1.3086 loss_prob: 0.7165 loss_thr: 0.4693 loss_db: 0.1228 2022/10/26 03:26:28 - mmengine - INFO - Epoch(train) [586][35/63] lr: 1.9359e-03 eta: 8:22:52 time: 0.5141 data_time: 0.0164 memory: 16131 loss: 1.3703 loss_prob: 0.7574 loss_thr: 0.4849 loss_db: 0.1279 2022/10/26 03:26:30 - mmengine - INFO - Epoch(train) [586][40/63] lr: 1.9359e-03 eta: 8:22:42 time: 0.5273 data_time: 0.0137 memory: 16131 loss: 1.3162 loss_prob: 0.7209 loss_thr: 0.4726 loss_db: 0.1227 2022/10/26 03:26:33 - mmengine - INFO - Epoch(train) [586][45/63] lr: 1.9359e-03 eta: 8:22:42 time: 0.5146 data_time: 0.0127 memory: 16131 loss: 1.2642 loss_prob: 0.6805 loss_thr: 0.4670 loss_db: 0.1167 2022/10/26 03:26:36 - mmengine - INFO - Epoch(train) [586][50/63] lr: 1.9359e-03 eta: 8:22:31 time: 0.5314 data_time: 0.0198 memory: 16131 loss: 1.3235 loss_prob: 0.7241 loss_thr: 0.4755 loss_db: 0.1238 2022/10/26 03:26:38 - mmengine - INFO - Epoch(train) [586][55/63] lr: 1.9359e-03 eta: 8:22:31 time: 0.5653 data_time: 0.0219 memory: 16131 loss: 1.5816 loss_prob: 0.9209 loss_thr: 0.5118 loss_db: 0.1490 2022/10/26 03:26:41 - mmengine - INFO - Epoch(train) [586][60/63] lr: 1.9359e-03 eta: 8:22:21 time: 0.5232 data_time: 0.0066 memory: 16131 loss: 1.5350 loss_prob: 0.8821 loss_thr: 0.5108 loss_db: 0.1420 2022/10/26 03:26:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:26:47 - mmengine - INFO - Epoch(train) [587][5/63] lr: 1.9330e-03 eta: 8:22:21 time: 0.6942 data_time: 0.1919 memory: 16131 loss: 1.3499 loss_prob: 0.7266 loss_thr: 0.5027 loss_db: 0.1206 2022/10/26 03:26:49 - mmengine - INFO - Epoch(train) [587][10/63] lr: 1.9330e-03 eta: 8:22:08 time: 0.7291 data_time: 0.1920 memory: 16131 loss: 1.4343 loss_prob: 0.7887 loss_thr: 0.5128 loss_db: 0.1327 2022/10/26 03:26:52 - mmengine - INFO - Epoch(train) [587][15/63] lr: 1.9330e-03 eta: 8:22:08 time: 0.5318 data_time: 0.0067 memory: 16131 loss: 1.2924 loss_prob: 0.6960 loss_thr: 0.4769 loss_db: 0.1195 2022/10/26 03:26:55 - mmengine - INFO - Epoch(train) [587][20/63] lr: 1.9330e-03 eta: 8:21:58 time: 0.5843 data_time: 0.0080 memory: 16131 loss: 1.2556 loss_prob: 0.6812 loss_thr: 0.4599 loss_db: 0.1145 2022/10/26 03:26:58 - mmengine - INFO - Epoch(train) [587][25/63] lr: 1.9330e-03 eta: 8:21:58 time: 0.6002 data_time: 0.0323 memory: 16131 loss: 1.2961 loss_prob: 0.7207 loss_thr: 0.4541 loss_db: 0.1213 2022/10/26 03:27:01 - mmengine - INFO - Epoch(train) [587][30/63] lr: 1.9330e-03 eta: 8:21:48 time: 0.5401 data_time: 0.0318 memory: 16131 loss: 1.2525 loss_prob: 0.6880 loss_thr: 0.4472 loss_db: 0.1173 2022/10/26 03:27:03 - mmengine - INFO - Epoch(train) [587][35/63] lr: 1.9330e-03 eta: 8:21:48 time: 0.4985 data_time: 0.0071 memory: 16131 loss: 1.2565 loss_prob: 0.6762 loss_thr: 0.4650 loss_db: 0.1153 2022/10/26 03:27:06 - mmengine - INFO - Epoch(train) [587][40/63] lr: 1.9330e-03 eta: 8:21:37 time: 0.4986 data_time: 0.0072 memory: 16131 loss: 1.2718 loss_prob: 0.6764 loss_thr: 0.4790 loss_db: 0.1164 2022/10/26 03:27:08 - mmengine - INFO - Epoch(train) [587][45/63] lr: 1.9330e-03 eta: 8:21:37 time: 0.4908 data_time: 0.0061 memory: 16131 loss: 1.3008 loss_prob: 0.7049 loss_thr: 0.4755 loss_db: 0.1204 2022/10/26 03:27:11 - mmengine - INFO - Epoch(train) [587][50/63] lr: 1.9330e-03 eta: 8:21:26 time: 0.5218 data_time: 0.0221 memory: 16131 loss: 1.3523 loss_prob: 0.7429 loss_thr: 0.4837 loss_db: 0.1258 2022/10/26 03:27:13 - mmengine - INFO - Epoch(train) [587][55/63] lr: 1.9330e-03 eta: 8:21:26 time: 0.5214 data_time: 0.0222 memory: 16131 loss: 1.4570 loss_prob: 0.8144 loss_thr: 0.5064 loss_db: 0.1362 2022/10/26 03:27:16 - mmengine - INFO - Epoch(train) [587][60/63] lr: 1.9330e-03 eta: 8:21:16 time: 0.4997 data_time: 0.0079 memory: 16131 loss: 1.4915 loss_prob: 0.8515 loss_thr: 0.5020 loss_db: 0.1380 2022/10/26 03:27:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:27:21 - mmengine - INFO - Epoch(train) [588][5/63] lr: 1.9302e-03 eta: 8:21:16 time: 0.6388 data_time: 0.1631 memory: 16131 loss: 1.4223 loss_prob: 0.7805 loss_thr: 0.5089 loss_db: 0.1329 2022/10/26 03:27:24 - mmengine - INFO - Epoch(train) [588][10/63] lr: 1.9302e-03 eta: 8:21:02 time: 0.6579 data_time: 0.1630 memory: 16131 loss: 1.3556 loss_prob: 0.7376 loss_thr: 0.4908 loss_db: 0.1271 2022/10/26 03:27:26 - mmengine - INFO - Epoch(train) [588][15/63] lr: 1.9302e-03 eta: 8:21:02 time: 0.5182 data_time: 0.0056 memory: 16131 loss: 1.2694 loss_prob: 0.6839 loss_thr: 0.4667 loss_db: 0.1188 2022/10/26 03:27:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:27:29 - mmengine - INFO - Epoch(train) [588][20/63] lr: 1.9302e-03 eta: 8:20:52 time: 0.5661 data_time: 0.0166 memory: 16131 loss: 1.2792 loss_prob: 0.7015 loss_thr: 0.4594 loss_db: 0.1183 2022/10/26 03:27:32 - mmengine - INFO - Epoch(train) [588][25/63] lr: 1.9302e-03 eta: 8:20:52 time: 0.5756 data_time: 0.0239 memory: 16131 loss: 1.2930 loss_prob: 0.7059 loss_thr: 0.4718 loss_db: 0.1153 2022/10/26 03:27:35 - mmengine - INFO - Epoch(train) [588][30/63] lr: 1.9302e-03 eta: 8:20:42 time: 0.5611 data_time: 0.0333 memory: 16131 loss: 1.2503 loss_prob: 0.6788 loss_thr: 0.4594 loss_db: 0.1122 2022/10/26 03:27:38 - mmengine - INFO - Epoch(train) [588][35/63] lr: 1.9302e-03 eta: 8:20:42 time: 0.5560 data_time: 0.0259 memory: 16131 loss: 1.2657 loss_prob: 0.7053 loss_thr: 0.4379 loss_db: 0.1226 2022/10/26 03:27:40 - mmengine - INFO - Epoch(train) [588][40/63] lr: 1.9302e-03 eta: 8:20:31 time: 0.5208 data_time: 0.0044 memory: 16131 loss: 1.4387 loss_prob: 0.8021 loss_thr: 0.4991 loss_db: 0.1375 2022/10/26 03:27:43 - mmengine - INFO - Epoch(train) [588][45/63] lr: 1.9302e-03 eta: 8:20:31 time: 0.5260 data_time: 0.0076 memory: 16131 loss: 1.3906 loss_prob: 0.7524 loss_thr: 0.5135 loss_db: 0.1247 2022/10/26 03:27:46 - mmengine - INFO - Epoch(train) [588][50/63] lr: 1.9302e-03 eta: 8:20:21 time: 0.5289 data_time: 0.0151 memory: 16131 loss: 1.2727 loss_prob: 0.6786 loss_thr: 0.4785 loss_db: 0.1156 2022/10/26 03:27:48 - mmengine - INFO - Epoch(train) [588][55/63] lr: 1.9302e-03 eta: 8:20:21 time: 0.5040 data_time: 0.0228 memory: 16131 loss: 1.3457 loss_prob: 0.7248 loss_thr: 0.4950 loss_db: 0.1259 2022/10/26 03:27:51 - mmengine - INFO - Epoch(train) [588][60/63] lr: 1.9302e-03 eta: 8:20:10 time: 0.5195 data_time: 0.0152 memory: 16131 loss: 1.3373 loss_prob: 0.7302 loss_thr: 0.4806 loss_db: 0.1265 2022/10/26 03:27:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:27:57 - mmengine - INFO - Epoch(train) [589][5/63] lr: 1.9273e-03 eta: 8:20:10 time: 0.7435 data_time: 0.1970 memory: 16131 loss: 1.3932 loss_prob: 0.7743 loss_thr: 0.4905 loss_db: 0.1283 2022/10/26 03:28:00 - mmengine - INFO - Epoch(train) [589][10/63] lr: 1.9273e-03 eta: 8:19:58 time: 0.7560 data_time: 0.1996 memory: 16131 loss: 1.3680 loss_prob: 0.7527 loss_thr: 0.4876 loss_db: 0.1277 2022/10/26 03:28:02 - mmengine - INFO - Epoch(train) [589][15/63] lr: 1.9273e-03 eta: 8:19:58 time: 0.5005 data_time: 0.0080 memory: 16131 loss: 1.3243 loss_prob: 0.7239 loss_thr: 0.4768 loss_db: 0.1236 2022/10/26 03:28:05 - mmengine - INFO - Epoch(train) [589][20/63] lr: 1.9273e-03 eta: 8:19:47 time: 0.5290 data_time: 0.0067 memory: 16131 loss: 1.4058 loss_prob: 0.7687 loss_thr: 0.5067 loss_db: 0.1304 2022/10/26 03:28:08 - mmengine - INFO - Epoch(train) [589][25/63] lr: 1.9273e-03 eta: 8:19:47 time: 0.5618 data_time: 0.0357 memory: 16131 loss: 1.4228 loss_prob: 0.7866 loss_thr: 0.5020 loss_db: 0.1341 2022/10/26 03:28:10 - mmengine - INFO - Epoch(train) [589][30/63] lr: 1.9273e-03 eta: 8:19:37 time: 0.5298 data_time: 0.0347 memory: 16131 loss: 1.3220 loss_prob: 0.7200 loss_thr: 0.4778 loss_db: 0.1242 2022/10/26 03:28:13 - mmengine - INFO - Epoch(train) [589][35/63] lr: 1.9273e-03 eta: 8:19:37 time: 0.4908 data_time: 0.0048 memory: 16131 loss: 1.3654 loss_prob: 0.7514 loss_thr: 0.4884 loss_db: 0.1256 2022/10/26 03:28:15 - mmengine - INFO - Epoch(train) [589][40/63] lr: 1.9273e-03 eta: 8:19:26 time: 0.4787 data_time: 0.0071 memory: 16131 loss: 1.4301 loss_prob: 0.8066 loss_thr: 0.4897 loss_db: 0.1338 2022/10/26 03:28:17 - mmengine - INFO - Epoch(train) [589][45/63] lr: 1.9273e-03 eta: 8:19:26 time: 0.4869 data_time: 0.0105 memory: 16131 loss: 1.3073 loss_prob: 0.7215 loss_thr: 0.4646 loss_db: 0.1212 2022/10/26 03:28:20 - mmengine - INFO - Epoch(train) [589][50/63] lr: 1.9273e-03 eta: 8:19:16 time: 0.5138 data_time: 0.0309 memory: 16131 loss: 1.2281 loss_prob: 0.6657 loss_thr: 0.4531 loss_db: 0.1093 2022/10/26 03:28:23 - mmengine - INFO - Epoch(train) [589][55/63] lr: 1.9273e-03 eta: 8:19:16 time: 0.5212 data_time: 0.0279 memory: 16131 loss: 1.2436 loss_prob: 0.6773 loss_thr: 0.4509 loss_db: 0.1154 2022/10/26 03:28:26 - mmengine - INFO - Epoch(train) [589][60/63] lr: 1.9273e-03 eta: 8:19:05 time: 0.5609 data_time: 0.0053 memory: 16131 loss: 1.2695 loss_prob: 0.7018 loss_thr: 0.4474 loss_db: 0.1203 2022/10/26 03:28:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:28:32 - mmengine - INFO - Epoch(train) [590][5/63] lr: 1.9245e-03 eta: 8:19:05 time: 0.8014 data_time: 0.1813 memory: 16131 loss: 1.3739 loss_prob: 0.7635 loss_thr: 0.4853 loss_db: 0.1251 2022/10/26 03:28:35 - mmengine - INFO - Epoch(train) [590][10/63] lr: 1.9245e-03 eta: 8:18:53 time: 0.7804 data_time: 0.1805 memory: 16131 loss: 1.3800 loss_prob: 0.7653 loss_thr: 0.4863 loss_db: 0.1284 2022/10/26 03:28:37 - mmengine - INFO - Epoch(train) [590][15/63] lr: 1.9245e-03 eta: 8:18:53 time: 0.5038 data_time: 0.0054 memory: 16131 loss: 1.3531 loss_prob: 0.7493 loss_thr: 0.4776 loss_db: 0.1262 2022/10/26 03:28:40 - mmengine - INFO - Epoch(train) [590][20/63] lr: 1.9245e-03 eta: 8:18:43 time: 0.5233 data_time: 0.0051 memory: 16131 loss: 1.4354 loss_prob: 0.8040 loss_thr: 0.4984 loss_db: 0.1330 2022/10/26 03:28:43 - mmengine - INFO - Epoch(train) [590][25/63] lr: 1.9245e-03 eta: 8:18:43 time: 0.5441 data_time: 0.0188 memory: 16131 loss: 1.4595 loss_prob: 0.8142 loss_thr: 0.5106 loss_db: 0.1347 2022/10/26 03:28:45 - mmengine - INFO - Epoch(train) [590][30/63] lr: 1.9245e-03 eta: 8:18:32 time: 0.5145 data_time: 0.0304 memory: 16131 loss: 1.3951 loss_prob: 0.7732 loss_thr: 0.4938 loss_db: 0.1280 2022/10/26 03:28:48 - mmengine - INFO - Epoch(train) [590][35/63] lr: 1.9245e-03 eta: 8:18:32 time: 0.4981 data_time: 0.0224 memory: 16131 loss: 1.3777 loss_prob: 0.7635 loss_thr: 0.4858 loss_db: 0.1284 2022/10/26 03:28:50 - mmengine - INFO - Epoch(train) [590][40/63] lr: 1.9245e-03 eta: 8:18:22 time: 0.5136 data_time: 0.0108 memory: 16131 loss: 1.3310 loss_prob: 0.7229 loss_thr: 0.4821 loss_db: 0.1260 2022/10/26 03:28:53 - mmengine - INFO - Epoch(train) [590][45/63] lr: 1.9245e-03 eta: 8:18:22 time: 0.5142 data_time: 0.0058 memory: 16131 loss: 1.3682 loss_prob: 0.7610 loss_thr: 0.4785 loss_db: 0.1287 2022/10/26 03:28:55 - mmengine - INFO - Epoch(train) [590][50/63] lr: 1.9245e-03 eta: 8:18:11 time: 0.5018 data_time: 0.0178 memory: 16131 loss: 1.4230 loss_prob: 0.8088 loss_thr: 0.4819 loss_db: 0.1324 2022/10/26 03:28:58 - mmengine - INFO - Epoch(train) [590][55/63] lr: 1.9245e-03 eta: 8:18:11 time: 0.5069 data_time: 0.0204 memory: 16131 loss: 1.4115 loss_prob: 0.7831 loss_thr: 0.4982 loss_db: 0.1302 2022/10/26 03:29:00 - mmengine - INFO - Epoch(train) [590][60/63] lr: 1.9245e-03 eta: 8:18:00 time: 0.4911 data_time: 0.0122 memory: 16131 loss: 1.4495 loss_prob: 0.8012 loss_thr: 0.5145 loss_db: 0.1338 2022/10/26 03:29:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:29:07 - mmengine - INFO - Epoch(train) [591][5/63] lr: 1.9217e-03 eta: 8:18:00 time: 0.7133 data_time: 0.2356 memory: 16131 loss: 1.3413 loss_prob: 0.7367 loss_thr: 0.4799 loss_db: 0.1247 2022/10/26 03:29:09 - mmengine - INFO - Epoch(train) [591][10/63] lr: 1.9217e-03 eta: 8:17:47 time: 0.7489 data_time: 0.2360 memory: 16131 loss: 1.3164 loss_prob: 0.7191 loss_thr: 0.4775 loss_db: 0.1199 2022/10/26 03:29:12 - mmengine - INFO - Epoch(train) [591][15/63] lr: 1.9217e-03 eta: 8:17:47 time: 0.5353 data_time: 0.0060 memory: 16131 loss: 1.3673 loss_prob: 0.7472 loss_thr: 0.4940 loss_db: 0.1261 2022/10/26 03:29:14 - mmengine - INFO - Epoch(train) [591][20/63] lr: 1.9217e-03 eta: 8:17:37 time: 0.5252 data_time: 0.0050 memory: 16131 loss: 1.3491 loss_prob: 0.7361 loss_thr: 0.4869 loss_db: 0.1262 2022/10/26 03:29:17 - mmengine - INFO - Epoch(train) [591][25/63] lr: 1.9217e-03 eta: 8:17:37 time: 0.5214 data_time: 0.0315 memory: 16131 loss: 1.3505 loss_prob: 0.7391 loss_thr: 0.4873 loss_db: 0.1241 2022/10/26 03:29:20 - mmengine - INFO - Epoch(train) [591][30/63] lr: 1.9217e-03 eta: 8:17:27 time: 0.5507 data_time: 0.0353 memory: 16131 loss: 1.3785 loss_prob: 0.7549 loss_thr: 0.4970 loss_db: 0.1265 2022/10/26 03:29:23 - mmengine - INFO - Epoch(train) [591][35/63] lr: 1.9217e-03 eta: 8:17:27 time: 0.5437 data_time: 0.0082 memory: 16131 loss: 1.2941 loss_prob: 0.6985 loss_thr: 0.4762 loss_db: 0.1194 2022/10/26 03:29:25 - mmengine - INFO - Epoch(train) [591][40/63] lr: 1.9217e-03 eta: 8:17:16 time: 0.5131 data_time: 0.0041 memory: 16131 loss: 1.2893 loss_prob: 0.7009 loss_thr: 0.4690 loss_db: 0.1194 2022/10/26 03:29:28 - mmengine - INFO - Epoch(train) [591][45/63] lr: 1.9217e-03 eta: 8:17:16 time: 0.5030 data_time: 0.0051 memory: 16131 loss: 1.2968 loss_prob: 0.7055 loss_thr: 0.4685 loss_db: 0.1228 2022/10/26 03:29:30 - mmengine - INFO - Epoch(train) [591][50/63] lr: 1.9217e-03 eta: 8:17:06 time: 0.5093 data_time: 0.0275 memory: 16131 loss: 1.3775 loss_prob: 0.7638 loss_thr: 0.4831 loss_db: 0.1306 2022/10/26 03:29:33 - mmengine - INFO - Epoch(train) [591][55/63] lr: 1.9217e-03 eta: 8:17:06 time: 0.5173 data_time: 0.0266 memory: 16131 loss: 1.4196 loss_prob: 0.8032 loss_thr: 0.4846 loss_db: 0.1318 2022/10/26 03:29:35 - mmengine - INFO - Epoch(train) [591][60/63] lr: 1.9217e-03 eta: 8:16:55 time: 0.5119 data_time: 0.0043 memory: 16131 loss: 1.2721 loss_prob: 0.7042 loss_thr: 0.4522 loss_db: 0.1158 2022/10/26 03:29:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:29:42 - mmengine - INFO - Epoch(train) [592][5/63] lr: 1.9188e-03 eta: 8:16:55 time: 0.7608 data_time: 0.2234 memory: 16131 loss: 1.1805 loss_prob: 0.6233 loss_thr: 0.4493 loss_db: 0.1079 2022/10/26 03:29:44 - mmengine - INFO - Epoch(train) [592][10/63] lr: 1.9188e-03 eta: 8:16:43 time: 0.8044 data_time: 0.2240 memory: 16131 loss: 1.2747 loss_prob: 0.6749 loss_thr: 0.4845 loss_db: 0.1153 2022/10/26 03:29:47 - mmengine - INFO - Epoch(train) [592][15/63] lr: 1.9188e-03 eta: 8:16:43 time: 0.5377 data_time: 0.0076 memory: 16131 loss: 1.4834 loss_prob: 0.8468 loss_thr: 0.5014 loss_db: 0.1352 2022/10/26 03:29:50 - mmengine - INFO - Epoch(train) [592][20/63] lr: 1.9188e-03 eta: 8:16:33 time: 0.5749 data_time: 0.0084 memory: 16131 loss: 1.5042 loss_prob: 0.8649 loss_thr: 0.5014 loss_db: 0.1379 2022/10/26 03:29:53 - mmengine - INFO - Epoch(train) [592][25/63] lr: 1.9188e-03 eta: 8:16:33 time: 0.5695 data_time: 0.0221 memory: 16131 loss: 1.3007 loss_prob: 0.7064 loss_thr: 0.4737 loss_db: 0.1206 2022/10/26 03:29:56 - mmengine - INFO - Epoch(train) [592][30/63] lr: 1.9188e-03 eta: 8:16:23 time: 0.5561 data_time: 0.0338 memory: 16131 loss: 1.2887 loss_prob: 0.7050 loss_thr: 0.4626 loss_db: 0.1211 2022/10/26 03:29:59 - mmengine - INFO - Epoch(train) [592][35/63] lr: 1.9188e-03 eta: 8:16:23 time: 0.5623 data_time: 0.0230 memory: 16131 loss: 1.3839 loss_prob: 0.7694 loss_thr: 0.4867 loss_db: 0.1277 2022/10/26 03:30:01 - mmengine - INFO - Epoch(train) [592][40/63] lr: 1.9188e-03 eta: 8:16:13 time: 0.5250 data_time: 0.0101 memory: 16131 loss: 1.3925 loss_prob: 0.7719 loss_thr: 0.4921 loss_db: 0.1285 2022/10/26 03:30:04 - mmengine - INFO - Epoch(train) [592][45/63] lr: 1.9188e-03 eta: 8:16:13 time: 0.5300 data_time: 0.0060 memory: 16131 loss: 1.2396 loss_prob: 0.6751 loss_thr: 0.4508 loss_db: 0.1137 2022/10/26 03:30:07 - mmengine - INFO - Epoch(train) [592][50/63] lr: 1.9188e-03 eta: 8:16:03 time: 0.5542 data_time: 0.0218 memory: 16131 loss: 1.2010 loss_prob: 0.6466 loss_thr: 0.4449 loss_db: 0.1096 2022/10/26 03:30:09 - mmengine - INFO - Epoch(train) [592][55/63] lr: 1.9188e-03 eta: 8:16:03 time: 0.5414 data_time: 0.0206 memory: 16131 loss: 1.3918 loss_prob: 0.7716 loss_thr: 0.4926 loss_db: 0.1276 2022/10/26 03:30:12 - mmengine - INFO - Epoch(train) [592][60/63] lr: 1.9188e-03 eta: 8:15:53 time: 0.5439 data_time: 0.0048 memory: 16131 loss: 1.3886 loss_prob: 0.7700 loss_thr: 0.4923 loss_db: 0.1263 2022/10/26 03:30:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:30:18 - mmengine - INFO - Epoch(train) [593][5/63] lr: 1.9160e-03 eta: 8:15:53 time: 0.6808 data_time: 0.1821 memory: 16131 loss: 1.3733 loss_prob: 0.7856 loss_thr: 0.4575 loss_db: 0.1301 2022/10/26 03:30:21 - mmengine - INFO - Epoch(train) [593][10/63] lr: 1.9160e-03 eta: 8:15:40 time: 0.7441 data_time: 0.1869 memory: 16131 loss: 1.3981 loss_prob: 0.7791 loss_thr: 0.4878 loss_db: 0.1313 2022/10/26 03:30:23 - mmengine - INFO - Epoch(train) [593][15/63] lr: 1.9160e-03 eta: 8:15:40 time: 0.5328 data_time: 0.0104 memory: 16131 loss: 1.3366 loss_prob: 0.7301 loss_thr: 0.4837 loss_db: 0.1229 2022/10/26 03:30:26 - mmengine - INFO - Epoch(train) [593][20/63] lr: 1.9160e-03 eta: 8:15:29 time: 0.5035 data_time: 0.0083 memory: 16131 loss: 1.3109 loss_prob: 0.7255 loss_thr: 0.4622 loss_db: 0.1232 2022/10/26 03:30:29 - mmengine - INFO - Epoch(train) [593][25/63] lr: 1.9160e-03 eta: 8:15:29 time: 0.5422 data_time: 0.0140 memory: 16131 loss: 1.2954 loss_prob: 0.7143 loss_thr: 0.4600 loss_db: 0.1212 2022/10/26 03:30:31 - mmengine - INFO - Epoch(train) [593][30/63] lr: 1.9160e-03 eta: 8:15:19 time: 0.5741 data_time: 0.0393 memory: 16131 loss: 1.3125 loss_prob: 0.7238 loss_thr: 0.4679 loss_db: 0.1208 2022/10/26 03:30:34 - mmengine - INFO - Epoch(train) [593][35/63] lr: 1.9160e-03 eta: 8:15:19 time: 0.5275 data_time: 0.0347 memory: 16131 loss: 1.3403 loss_prob: 0.7418 loss_thr: 0.4732 loss_db: 0.1253 2022/10/26 03:30:36 - mmengine - INFO - Epoch(train) [593][40/63] lr: 1.9160e-03 eta: 8:15:09 time: 0.4981 data_time: 0.0069 memory: 16131 loss: 1.3848 loss_prob: 0.7632 loss_thr: 0.4929 loss_db: 0.1287 2022/10/26 03:30:39 - mmengine - INFO - Epoch(train) [593][45/63] lr: 1.9160e-03 eta: 8:15:09 time: 0.5565 data_time: 0.0045 memory: 16131 loss: 1.3954 loss_prob: 0.7631 loss_thr: 0.5035 loss_db: 0.1287 2022/10/26 03:30:42 - mmengine - INFO - Epoch(train) [593][50/63] lr: 1.9160e-03 eta: 8:14:59 time: 0.5601 data_time: 0.0141 memory: 16131 loss: 1.2830 loss_prob: 0.7017 loss_thr: 0.4622 loss_db: 0.1190 2022/10/26 03:30:45 - mmengine - INFO - Epoch(train) [593][55/63] lr: 1.9160e-03 eta: 8:14:59 time: 0.5163 data_time: 0.0190 memory: 16131 loss: 1.2929 loss_prob: 0.6994 loss_thr: 0.4746 loss_db: 0.1189 2022/10/26 03:30:47 - mmengine - INFO - Epoch(train) [593][60/63] lr: 1.9160e-03 eta: 8:14:48 time: 0.5235 data_time: 0.0114 memory: 16131 loss: 1.3461 loss_prob: 0.7290 loss_thr: 0.4942 loss_db: 0.1229 2022/10/26 03:30:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:30:53 - mmengine - INFO - Epoch(train) [594][5/63] lr: 1.9131e-03 eta: 8:14:48 time: 0.6891 data_time: 0.2067 memory: 16131 loss: 1.1947 loss_prob: 0.6439 loss_thr: 0.4424 loss_db: 0.1084 2022/10/26 03:30:56 - mmengine - INFO - Epoch(train) [594][10/63] lr: 1.9131e-03 eta: 8:14:35 time: 0.7137 data_time: 0.2041 memory: 16131 loss: 1.2572 loss_prob: 0.6785 loss_thr: 0.4641 loss_db: 0.1146 2022/10/26 03:30:58 - mmengine - INFO - Epoch(train) [594][15/63] lr: 1.9131e-03 eta: 8:14:35 time: 0.5356 data_time: 0.0089 memory: 16131 loss: 1.2286 loss_prob: 0.6520 loss_thr: 0.4651 loss_db: 0.1115 2022/10/26 03:31:01 - mmengine - INFO - Epoch(train) [594][20/63] lr: 1.9131e-03 eta: 8:14:25 time: 0.5125 data_time: 0.0096 memory: 16131 loss: 1.3274 loss_prob: 0.7263 loss_thr: 0.4787 loss_db: 0.1224 2022/10/26 03:31:04 - mmengine - INFO - Epoch(train) [594][25/63] lr: 1.9131e-03 eta: 8:14:25 time: 0.5273 data_time: 0.0169 memory: 16131 loss: 1.3506 loss_prob: 0.7683 loss_thr: 0.4540 loss_db: 0.1283 2022/10/26 03:31:06 - mmengine - INFO - Epoch(train) [594][30/63] lr: 1.9131e-03 eta: 8:14:15 time: 0.5725 data_time: 0.0368 memory: 16131 loss: 1.3276 loss_prob: 0.7438 loss_thr: 0.4589 loss_db: 0.1249 2022/10/26 03:31:09 - mmengine - INFO - Epoch(train) [594][35/63] lr: 1.9131e-03 eta: 8:14:15 time: 0.5417 data_time: 0.0261 memory: 16131 loss: 1.3691 loss_prob: 0.7528 loss_thr: 0.4885 loss_db: 0.1278 2022/10/26 03:31:11 - mmengine - INFO - Epoch(train) [594][40/63] lr: 1.9131e-03 eta: 8:14:04 time: 0.4988 data_time: 0.0068 memory: 16131 loss: 1.3998 loss_prob: 0.7756 loss_thr: 0.4921 loss_db: 0.1321 2022/10/26 03:31:14 - mmengine - INFO - Epoch(train) [594][45/63] lr: 1.9131e-03 eta: 8:14:04 time: 0.5073 data_time: 0.0079 memory: 16131 loss: 1.3655 loss_prob: 0.7482 loss_thr: 0.4905 loss_db: 0.1268 2022/10/26 03:31:17 - mmengine - INFO - Epoch(train) [594][50/63] lr: 1.9131e-03 eta: 8:13:55 time: 0.5652 data_time: 0.0162 memory: 16131 loss: 1.2819 loss_prob: 0.6843 loss_thr: 0.4798 loss_db: 0.1178 2022/10/26 03:31:20 - mmengine - INFO - Epoch(train) [594][55/63] lr: 1.9131e-03 eta: 8:13:55 time: 0.5561 data_time: 0.0239 memory: 16131 loss: 1.3507 loss_prob: 0.7263 loss_thr: 0.5001 loss_db: 0.1244 2022/10/26 03:31:22 - mmengine - INFO - Epoch(train) [594][60/63] lr: 1.9131e-03 eta: 8:13:44 time: 0.5050 data_time: 0.0149 memory: 16131 loss: 1.3380 loss_prob: 0.7301 loss_thr: 0.4833 loss_db: 0.1246 2022/10/26 03:31:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:31:28 - mmengine - INFO - Epoch(train) [595][5/63] lr: 1.9103e-03 eta: 8:13:44 time: 0.7306 data_time: 0.1916 memory: 16131 loss: 1.3115 loss_prob: 0.7212 loss_thr: 0.4665 loss_db: 0.1237 2022/10/26 03:31:31 - mmengine - INFO - Epoch(train) [595][10/63] lr: 1.9103e-03 eta: 8:13:31 time: 0.7479 data_time: 0.1919 memory: 16131 loss: 1.2698 loss_prob: 0.6955 loss_thr: 0.4579 loss_db: 0.1164 2022/10/26 03:31:34 - mmengine - INFO - Epoch(train) [595][15/63] lr: 1.9103e-03 eta: 8:13:31 time: 0.5792 data_time: 0.0081 memory: 16131 loss: 1.3497 loss_prob: 0.7445 loss_thr: 0.4817 loss_db: 0.1235 2022/10/26 03:31:37 - mmengine - INFO - Epoch(train) [595][20/63] lr: 1.9103e-03 eta: 8:13:21 time: 0.5683 data_time: 0.0062 memory: 16131 loss: 1.3634 loss_prob: 0.7482 loss_thr: 0.4926 loss_db: 0.1226 2022/10/26 03:31:39 - mmengine - INFO - Epoch(train) [595][25/63] lr: 1.9103e-03 eta: 8:13:21 time: 0.5184 data_time: 0.0149 memory: 16131 loss: 1.4104 loss_prob: 0.7798 loss_thr: 0.5011 loss_db: 0.1295 2022/10/26 03:31:42 - mmengine - INFO - Epoch(train) [595][30/63] lr: 1.9103e-03 eta: 8:13:11 time: 0.5416 data_time: 0.0298 memory: 16131 loss: 1.3690 loss_prob: 0.7562 loss_thr: 0.4835 loss_db: 0.1293 2022/10/26 03:31:45 - mmengine - INFO - Epoch(train) [595][35/63] lr: 1.9103e-03 eta: 8:13:11 time: 0.5168 data_time: 0.0223 memory: 16131 loss: 1.2728 loss_prob: 0.6908 loss_thr: 0.4637 loss_db: 0.1183 2022/10/26 03:31:47 - mmengine - INFO - Epoch(train) [595][40/63] lr: 1.9103e-03 eta: 8:13:01 time: 0.5136 data_time: 0.0088 memory: 16131 loss: 1.3447 loss_prob: 0.7378 loss_thr: 0.4813 loss_db: 0.1255 2022/10/26 03:31:50 - mmengine - INFO - Epoch(train) [595][45/63] lr: 1.9103e-03 eta: 8:13:01 time: 0.5216 data_time: 0.0066 memory: 16131 loss: 1.3879 loss_prob: 0.7684 loss_thr: 0.4910 loss_db: 0.1284 2022/10/26 03:31:52 - mmengine - INFO - Epoch(train) [595][50/63] lr: 1.9103e-03 eta: 8:12:50 time: 0.5010 data_time: 0.0106 memory: 16131 loss: 1.2644 loss_prob: 0.6828 loss_thr: 0.4681 loss_db: 0.1136 2022/10/26 03:31:55 - mmengine - INFO - Epoch(train) [595][55/63] lr: 1.9103e-03 eta: 8:12:50 time: 0.5223 data_time: 0.0192 memory: 16131 loss: 1.2746 loss_prob: 0.6864 loss_thr: 0.4742 loss_db: 0.1139 2022/10/26 03:31:58 - mmengine - INFO - Epoch(train) [595][60/63] lr: 1.9103e-03 eta: 8:12:40 time: 0.5584 data_time: 0.0156 memory: 16131 loss: 1.3921 loss_prob: 0.7771 loss_thr: 0.4842 loss_db: 0.1308 2022/10/26 03:31:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:32:04 - mmengine - INFO - Epoch(train) [596][5/63] lr: 1.9075e-03 eta: 8:12:40 time: 0.7192 data_time: 0.2088 memory: 16131 loss: 1.4106 loss_prob: 0.7998 loss_thr: 0.4762 loss_db: 0.1346 2022/10/26 03:32:06 - mmengine - INFO - Epoch(train) [596][10/63] lr: 1.9075e-03 eta: 8:12:27 time: 0.7161 data_time: 0.2087 memory: 16131 loss: 1.4283 loss_prob: 0.8076 loss_thr: 0.4837 loss_db: 0.1371 2022/10/26 03:32:09 - mmengine - INFO - Epoch(train) [596][15/63] lr: 1.9075e-03 eta: 8:12:27 time: 0.5178 data_time: 0.0051 memory: 16131 loss: 1.3171 loss_prob: 0.7213 loss_thr: 0.4720 loss_db: 0.1238 2022/10/26 03:32:12 - mmengine - INFO - Epoch(train) [596][20/63] lr: 1.9075e-03 eta: 8:12:17 time: 0.5693 data_time: 0.0058 memory: 16131 loss: 1.3050 loss_prob: 0.7019 loss_thr: 0.4847 loss_db: 0.1185 2022/10/26 03:32:15 - mmengine - INFO - Epoch(train) [596][25/63] lr: 1.9075e-03 eta: 8:12:17 time: 0.5917 data_time: 0.0299 memory: 16131 loss: 1.3600 loss_prob: 0.7481 loss_thr: 0.4879 loss_db: 0.1240 2022/10/26 03:32:18 - mmengine - INFO - Epoch(train) [596][30/63] lr: 1.9075e-03 eta: 8:12:08 time: 0.5736 data_time: 0.0293 memory: 16131 loss: 1.3427 loss_prob: 0.7440 loss_thr: 0.4722 loss_db: 0.1265 2022/10/26 03:32:20 - mmengine - INFO - Epoch(train) [596][35/63] lr: 1.9075e-03 eta: 8:12:08 time: 0.5170 data_time: 0.0073 memory: 16131 loss: 1.3600 loss_prob: 0.7457 loss_thr: 0.4848 loss_db: 0.1294 2022/10/26 03:32:23 - mmengine - INFO - Epoch(train) [596][40/63] lr: 1.9075e-03 eta: 8:11:57 time: 0.5168 data_time: 0.0089 memory: 16131 loss: 1.3660 loss_prob: 0.7544 loss_thr: 0.4790 loss_db: 0.1326 2022/10/26 03:32:25 - mmengine - INFO - Epoch(train) [596][45/63] lr: 1.9075e-03 eta: 8:11:57 time: 0.5315 data_time: 0.0066 memory: 16131 loss: 1.3030 loss_prob: 0.7159 loss_thr: 0.4623 loss_db: 0.1248 2022/10/26 03:32:28 - mmengine - INFO - Epoch(train) [596][50/63] lr: 1.9075e-03 eta: 8:11:47 time: 0.5243 data_time: 0.0235 memory: 16131 loss: 1.2901 loss_prob: 0.6982 loss_thr: 0.4723 loss_db: 0.1196 2022/10/26 03:32:31 - mmengine - INFO - Epoch(train) [596][55/63] lr: 1.9075e-03 eta: 8:11:47 time: 0.5213 data_time: 0.0234 memory: 16131 loss: 1.2767 loss_prob: 0.6951 loss_thr: 0.4608 loss_db: 0.1208 2022/10/26 03:32:33 - mmengine - INFO - Epoch(train) [596][60/63] lr: 1.9075e-03 eta: 8:11:37 time: 0.5175 data_time: 0.0057 memory: 16131 loss: 1.3749 loss_prob: 0.7715 loss_thr: 0.4764 loss_db: 0.1269 2022/10/26 03:32:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:32:39 - mmengine - INFO - Epoch(train) [597][5/63] lr: 1.9046e-03 eta: 8:11:37 time: 0.6867 data_time: 0.2210 memory: 16131 loss: 1.4722 loss_prob: 0.8307 loss_thr: 0.5024 loss_db: 0.1391 2022/10/26 03:32:42 - mmengine - INFO - Epoch(train) [597][10/63] lr: 1.9046e-03 eta: 8:11:24 time: 0.7233 data_time: 0.2137 memory: 16131 loss: 1.3937 loss_prob: 0.7656 loss_thr: 0.5012 loss_db: 0.1270 2022/10/26 03:32:45 - mmengine - INFO - Epoch(train) [597][15/63] lr: 1.9046e-03 eta: 8:11:24 time: 0.5656 data_time: 0.0055 memory: 16131 loss: 1.3049 loss_prob: 0.6986 loss_thr: 0.4893 loss_db: 0.1171 2022/10/26 03:32:47 - mmengine - INFO - Epoch(train) [597][20/63] lr: 1.9046e-03 eta: 8:11:14 time: 0.5476 data_time: 0.0067 memory: 16131 loss: 1.3056 loss_prob: 0.7103 loss_thr: 0.4736 loss_db: 0.1217 2022/10/26 03:32:50 - mmengine - INFO - Epoch(train) [597][25/63] lr: 1.9046e-03 eta: 8:11:14 time: 0.5508 data_time: 0.0358 memory: 16131 loss: 1.2704 loss_prob: 0.6930 loss_thr: 0.4603 loss_db: 0.1172 2022/10/26 03:32:53 - mmengine - INFO - Epoch(train) [597][30/63] lr: 1.9046e-03 eta: 8:11:04 time: 0.5713 data_time: 0.0363 memory: 16131 loss: 1.2633 loss_prob: 0.6857 loss_thr: 0.4610 loss_db: 0.1166 2022/10/26 03:32:55 - mmengine - INFO - Epoch(train) [597][35/63] lr: 1.9046e-03 eta: 8:11:04 time: 0.5147 data_time: 0.0065 memory: 16131 loss: 1.2750 loss_prob: 0.6983 loss_thr: 0.4560 loss_db: 0.1206 2022/10/26 03:32:58 - mmengine - INFO - Epoch(train) [597][40/63] lr: 1.9046e-03 eta: 8:10:53 time: 0.4871 data_time: 0.0058 memory: 16131 loss: 1.3636 loss_prob: 0.7619 loss_thr: 0.4755 loss_db: 0.1263 2022/10/26 03:33:01 - mmengine - INFO - Epoch(train) [597][45/63] lr: 1.9046e-03 eta: 8:10:53 time: 0.5305 data_time: 0.0064 memory: 16131 loss: 1.4710 loss_prob: 0.8337 loss_thr: 0.5022 loss_db: 0.1351 2022/10/26 03:33:03 - mmengine - INFO - Epoch(train) [597][50/63] lr: 1.9046e-03 eta: 8:10:43 time: 0.5420 data_time: 0.0221 memory: 16131 loss: 1.4258 loss_prob: 0.8021 loss_thr: 0.4905 loss_db: 0.1332 2022/10/26 03:33:06 - mmengine - INFO - Epoch(train) [597][55/63] lr: 1.9046e-03 eta: 8:10:43 time: 0.5172 data_time: 0.0249 memory: 16131 loss: 1.3576 loss_prob: 0.7548 loss_thr: 0.4761 loss_db: 0.1267 2022/10/26 03:33:10 - mmengine - INFO - Epoch(train) [597][60/63] lr: 1.9046e-03 eta: 8:10:34 time: 0.6935 data_time: 0.0090 memory: 16131 loss: 1.2928 loss_prob: 0.7116 loss_thr: 0.4608 loss_db: 0.1204 2022/10/26 03:33:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:33:16 - mmengine - INFO - Epoch(train) [598][5/63] lr: 1.9018e-03 eta: 8:10:34 time: 0.8666 data_time: 0.1701 memory: 16131 loss: 1.2501 loss_prob: 0.6772 loss_thr: 0.4560 loss_db: 0.1169 2022/10/26 03:33:19 - mmengine - INFO - Epoch(train) [598][10/63] lr: 1.9018e-03 eta: 8:10:22 time: 0.7739 data_time: 0.1733 memory: 16131 loss: 1.2086 loss_prob: 0.6448 loss_thr: 0.4511 loss_db: 0.1127 2022/10/26 03:33:22 - mmengine - INFO - Epoch(train) [598][15/63] lr: 1.9018e-03 eta: 8:10:22 time: 0.5288 data_time: 0.0141 memory: 16131 loss: 1.2957 loss_prob: 0.7163 loss_thr: 0.4594 loss_db: 0.1199 2022/10/26 03:33:24 - mmengine - INFO - Epoch(train) [598][20/63] lr: 1.9018e-03 eta: 8:10:12 time: 0.5163 data_time: 0.0096 memory: 16131 loss: 1.3092 loss_prob: 0.7298 loss_thr: 0.4574 loss_db: 0.1220 2022/10/26 03:33:27 - mmengine - INFO - Epoch(train) [598][25/63] lr: 1.9018e-03 eta: 8:10:12 time: 0.5260 data_time: 0.0207 memory: 16131 loss: 1.2439 loss_prob: 0.6859 loss_thr: 0.4441 loss_db: 0.1138 2022/10/26 03:33:30 - mmengine - INFO - Epoch(train) [598][30/63] lr: 1.9018e-03 eta: 8:10:02 time: 0.6155 data_time: 0.0347 memory: 16131 loss: 1.2669 loss_prob: 0.6947 loss_thr: 0.4567 loss_db: 0.1155 2022/10/26 03:33:33 - mmengine - INFO - Epoch(train) [598][35/63] lr: 1.9018e-03 eta: 8:10:02 time: 0.6064 data_time: 0.0195 memory: 16131 loss: 1.2899 loss_prob: 0.6981 loss_thr: 0.4709 loss_db: 0.1209 2022/10/26 03:33:36 - mmengine - INFO - Epoch(train) [598][40/63] lr: 1.9018e-03 eta: 8:09:52 time: 0.5473 data_time: 0.0182 memory: 16131 loss: 1.2485 loss_prob: 0.6690 loss_thr: 0.4626 loss_db: 0.1169 2022/10/26 03:33:38 - mmengine - INFO - Epoch(train) [598][45/63] lr: 1.9018e-03 eta: 8:09:52 time: 0.5215 data_time: 0.0190 memory: 16131 loss: 1.3542 loss_prob: 0.7678 loss_thr: 0.4632 loss_db: 0.1233 2022/10/26 03:33:41 - mmengine - INFO - Epoch(train) [598][50/63] lr: 1.9018e-03 eta: 8:09:42 time: 0.5301 data_time: 0.0151 memory: 16131 loss: 1.3651 loss_prob: 0.7784 loss_thr: 0.4629 loss_db: 0.1237 2022/10/26 03:33:44 - mmengine - INFO - Epoch(train) [598][55/63] lr: 1.9018e-03 eta: 8:09:42 time: 0.5358 data_time: 0.0208 memory: 16131 loss: 1.2847 loss_prob: 0.6999 loss_thr: 0.4643 loss_db: 0.1206 2022/10/26 03:33:46 - mmengine - INFO - Epoch(train) [598][60/63] lr: 1.9018e-03 eta: 8:09:32 time: 0.5292 data_time: 0.0136 memory: 16131 loss: 1.3448 loss_prob: 0.7424 loss_thr: 0.4765 loss_db: 0.1259 2022/10/26 03:33:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:33:52 - mmengine - INFO - Epoch(train) [599][5/63] lr: 1.8989e-03 eta: 8:09:32 time: 0.6683 data_time: 0.1929 memory: 16131 loss: 1.3134 loss_prob: 0.7236 loss_thr: 0.4691 loss_db: 0.1207 2022/10/26 03:33:55 - mmengine - INFO - Epoch(train) [599][10/63] lr: 1.8989e-03 eta: 8:09:19 time: 0.7053 data_time: 0.1964 memory: 16131 loss: 1.2102 loss_prob: 0.6585 loss_thr: 0.4412 loss_db: 0.1105 2022/10/26 03:33:57 - mmengine - INFO - Epoch(train) [599][15/63] lr: 1.8989e-03 eta: 8:09:19 time: 0.5150 data_time: 0.0117 memory: 16131 loss: 1.1654 loss_prob: 0.6322 loss_thr: 0.4273 loss_db: 0.1060 2022/10/26 03:34:00 - mmengine - INFO - Epoch(train) [599][20/63] lr: 1.8989e-03 eta: 8:09:08 time: 0.5128 data_time: 0.0085 memory: 16131 loss: 1.2315 loss_prob: 0.6753 loss_thr: 0.4424 loss_db: 0.1138 2022/10/26 03:34:03 - mmengine - INFO - Epoch(train) [599][25/63] lr: 1.8989e-03 eta: 8:09:08 time: 0.5800 data_time: 0.0312 memory: 16131 loss: 1.2650 loss_prob: 0.6806 loss_thr: 0.4695 loss_db: 0.1149 2022/10/26 03:34:06 - mmengine - INFO - Epoch(train) [599][30/63] lr: 1.8989e-03 eta: 8:08:59 time: 0.5838 data_time: 0.0291 memory: 16131 loss: 1.2504 loss_prob: 0.6642 loss_thr: 0.4720 loss_db: 0.1142 2022/10/26 03:34:08 - mmengine - INFO - Epoch(train) [599][35/63] lr: 1.8989e-03 eta: 8:08:59 time: 0.5426 data_time: 0.0048 memory: 16131 loss: 1.3147 loss_prob: 0.7169 loss_thr: 0.4749 loss_db: 0.1230 2022/10/26 03:34:11 - mmengine - INFO - Epoch(train) [599][40/63] lr: 1.8989e-03 eta: 8:08:48 time: 0.5234 data_time: 0.0065 memory: 16131 loss: 1.4226 loss_prob: 0.7970 loss_thr: 0.4922 loss_db: 0.1335 2022/10/26 03:34:13 - mmengine - INFO - Epoch(train) [599][45/63] lr: 1.8989e-03 eta: 8:08:48 time: 0.4950 data_time: 0.0074 memory: 16131 loss: 1.4431 loss_prob: 0.8090 loss_thr: 0.4978 loss_db: 0.1363 2022/10/26 03:34:16 - mmengine - INFO - Epoch(train) [599][50/63] lr: 1.8989e-03 eta: 8:08:38 time: 0.5086 data_time: 0.0231 memory: 16131 loss: 1.4147 loss_prob: 0.7882 loss_thr: 0.4919 loss_db: 0.1346 2022/10/26 03:34:19 - mmengine - INFO - Epoch(train) [599][55/63] lr: 1.8989e-03 eta: 8:08:38 time: 0.5282 data_time: 0.0222 memory: 16131 loss: 1.3765 loss_prob: 0.7623 loss_thr: 0.4869 loss_db: 0.1273 2022/10/26 03:34:21 - mmengine - INFO - Epoch(train) [599][60/63] lr: 1.8989e-03 eta: 8:08:28 time: 0.5119 data_time: 0.0082 memory: 16131 loss: 1.3547 loss_prob: 0.7407 loss_thr: 0.4876 loss_db: 0.1264 2022/10/26 03:34:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:34:28 - mmengine - INFO - Epoch(train) [600][5/63] lr: 1.8961e-03 eta: 8:08:28 time: 0.7892 data_time: 0.1992 memory: 16131 loss: 1.3018 loss_prob: 0.7234 loss_thr: 0.4553 loss_db: 0.1231 2022/10/26 03:34:31 - mmengine - INFO - Epoch(train) [600][10/63] lr: 1.8961e-03 eta: 8:08:16 time: 0.8301 data_time: 0.2006 memory: 16131 loss: 1.3406 loss_prob: 0.7373 loss_thr: 0.4778 loss_db: 0.1254 2022/10/26 03:34:33 - mmengine - INFO - Epoch(train) [600][15/63] lr: 1.8961e-03 eta: 8:08:16 time: 0.5128 data_time: 0.0094 memory: 16131 loss: 1.2642 loss_prob: 0.6808 loss_thr: 0.4656 loss_db: 0.1178 2022/10/26 03:34:36 - mmengine - INFO - Epoch(train) [600][20/63] lr: 1.8961e-03 eta: 8:08:05 time: 0.4971 data_time: 0.0130 memory: 16131 loss: 1.2119 loss_prob: 0.6569 loss_thr: 0.4437 loss_db: 0.1113 2022/10/26 03:34:39 - mmengine - INFO - Epoch(train) [600][25/63] lr: 1.8961e-03 eta: 8:08:05 time: 0.5338 data_time: 0.0342 memory: 16131 loss: 1.2119 loss_prob: 0.6550 loss_thr: 0.4472 loss_db: 0.1097 2022/10/26 03:34:41 - mmengine - INFO - Epoch(train) [600][30/63] lr: 1.8961e-03 eta: 8:07:55 time: 0.5504 data_time: 0.0319 memory: 16131 loss: 1.1644 loss_prob: 0.6177 loss_thr: 0.4405 loss_db: 0.1062 2022/10/26 03:34:44 - mmengine - INFO - Epoch(train) [600][35/63] lr: 1.8961e-03 eta: 8:07:55 time: 0.5436 data_time: 0.0076 memory: 16131 loss: 1.2305 loss_prob: 0.6683 loss_thr: 0.4498 loss_db: 0.1124 2022/10/26 03:34:47 - mmengine - INFO - Epoch(train) [600][40/63] lr: 1.8961e-03 eta: 8:07:45 time: 0.5380 data_time: 0.0091 memory: 16131 loss: 1.2980 loss_prob: 0.7061 loss_thr: 0.4727 loss_db: 0.1192 2022/10/26 03:34:49 - mmengine - INFO - Epoch(train) [600][45/63] lr: 1.8961e-03 eta: 8:07:45 time: 0.5043 data_time: 0.0092 memory: 16131 loss: 1.2841 loss_prob: 0.6915 loss_thr: 0.4732 loss_db: 0.1194 2022/10/26 03:34:52 - mmengine - INFO - Epoch(train) [600][50/63] lr: 1.8961e-03 eta: 8:07:35 time: 0.5478 data_time: 0.0278 memory: 16131 loss: 1.2405 loss_prob: 0.6719 loss_thr: 0.4556 loss_db: 0.1130 2022/10/26 03:34:54 - mmengine - INFO - Epoch(train) [600][55/63] lr: 1.8961e-03 eta: 8:07:35 time: 0.5410 data_time: 0.0287 memory: 16131 loss: 1.2860 loss_prob: 0.6893 loss_thr: 0.4801 loss_db: 0.1166 2022/10/26 03:34:57 - mmengine - INFO - Epoch(train) [600][60/63] lr: 1.8961e-03 eta: 8:07:25 time: 0.4967 data_time: 0.0058 memory: 16131 loss: 1.2450 loss_prob: 0.6650 loss_thr: 0.4642 loss_db: 0.1157 2022/10/26 03:34:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:34:58 - mmengine - INFO - Saving checkpoint at 600 epochs 2022/10/26 03:35:05 - mmengine - INFO - Epoch(val) [600][5/32] eta: 8:07:25 time: 0.5341 data_time: 0.0757 memory: 16131 2022/10/26 03:35:07 - mmengine - INFO - Epoch(val) [600][10/32] eta: 0:00:12 time: 0.5879 data_time: 0.0941 memory: 15724 2022/10/26 03:35:10 - mmengine - INFO - Epoch(val) [600][15/32] eta: 0:00:12 time: 0.5436 data_time: 0.0432 memory: 15724 2022/10/26 03:35:13 - mmengine - INFO - Epoch(val) [600][20/32] eta: 0:00:06 time: 0.5347 data_time: 0.0479 memory: 15724 2022/10/26 03:35:16 - mmengine - INFO - Epoch(val) [600][25/32] eta: 0:00:06 time: 0.5492 data_time: 0.0493 memory: 15724 2022/10/26 03:35:18 - mmengine - INFO - Epoch(val) [600][30/32] eta: 0:00:01 time: 0.5346 data_time: 0.0330 memory: 15724 2022/10/26 03:35:19 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8358, precision: 0.7365, hmean: 0.7830 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8358, precision: 0.7898, hmean: 0.8122 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8349, precision: 0.8175, hmean: 0.8261 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8252, precision: 0.8481, hmean: 0.8365 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7963, precision: 0.8892, hmean: 0.8402 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6413, precision: 0.9361, hmean: 0.7611 2022/10/26 03:35:19 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0270, precision: 1.0000, hmean: 0.0525 2022/10/26 03:35:19 - mmengine - INFO - Epoch(val) [600][32/32] icdar/precision: 0.8892 icdar/recall: 0.7963 icdar/hmean: 0.8402 2022/10/26 03:35:23 - mmengine - INFO - Epoch(train) [601][5/63] lr: 1.8932e-03 eta: 0:00:01 time: 0.6660 data_time: 0.1823 memory: 16131 loss: 1.2784 loss_prob: 0.7099 loss_thr: 0.4505 loss_db: 0.1180 2022/10/26 03:35:26 - mmengine - INFO - Epoch(train) [601][10/63] lr: 1.8932e-03 eta: 8:07:12 time: 0.7048 data_time: 0.1866 memory: 16131 loss: 1.3013 loss_prob: 0.7185 loss_thr: 0.4616 loss_db: 0.1212 2022/10/26 03:35:29 - mmengine - INFO - Epoch(train) [601][15/63] lr: 1.8932e-03 eta: 8:07:12 time: 0.5365 data_time: 0.0087 memory: 16131 loss: 1.2871 loss_prob: 0.7021 loss_thr: 0.4662 loss_db: 0.1187 2022/10/26 03:35:31 - mmengine - INFO - Epoch(train) [601][20/63] lr: 1.8932e-03 eta: 8:07:01 time: 0.5101 data_time: 0.0090 memory: 16131 loss: 1.2818 loss_prob: 0.6948 loss_thr: 0.4663 loss_db: 0.1207 2022/10/26 03:35:34 - mmengine - INFO - Epoch(train) [601][25/63] lr: 1.8932e-03 eta: 8:07:01 time: 0.5507 data_time: 0.0349 memory: 16131 loss: 1.2947 loss_prob: 0.7067 loss_thr: 0.4655 loss_db: 0.1225 2022/10/26 03:35:37 - mmengine - INFO - Epoch(train) [601][30/63] lr: 1.8932e-03 eta: 8:06:52 time: 0.5820 data_time: 0.0311 memory: 16131 loss: 1.3315 loss_prob: 0.7287 loss_thr: 0.4795 loss_db: 0.1233 2022/10/26 03:35:39 - mmengine - INFO - Epoch(train) [601][35/63] lr: 1.8932e-03 eta: 8:06:52 time: 0.5117 data_time: 0.0077 memory: 16131 loss: 1.3749 loss_prob: 0.7734 loss_thr: 0.4730 loss_db: 0.1285 2022/10/26 03:35:42 - mmengine - INFO - Epoch(train) [601][40/63] lr: 1.8932e-03 eta: 8:06:41 time: 0.5163 data_time: 0.0092 memory: 16131 loss: 1.4724 loss_prob: 0.8414 loss_thr: 0.4917 loss_db: 0.1392 2022/10/26 03:35:45 - mmengine - INFO - Epoch(train) [601][45/63] lr: 1.8932e-03 eta: 8:06:41 time: 0.5563 data_time: 0.0075 memory: 16131 loss: 1.4509 loss_prob: 0.8050 loss_thr: 0.5089 loss_db: 0.1370 2022/10/26 03:35:47 - mmengine - INFO - Epoch(train) [601][50/63] lr: 1.8932e-03 eta: 8:06:31 time: 0.5475 data_time: 0.0222 memory: 16131 loss: 1.2997 loss_prob: 0.7025 loss_thr: 0.4754 loss_db: 0.1217 2022/10/26 03:35:50 - mmengine - INFO - Epoch(train) [601][55/63] lr: 1.8932e-03 eta: 8:06:31 time: 0.5402 data_time: 0.0213 memory: 16131 loss: 1.3486 loss_prob: 0.7491 loss_thr: 0.4765 loss_db: 0.1230 2022/10/26 03:35:53 - mmengine - INFO - Epoch(train) [601][60/63] lr: 1.8932e-03 eta: 8:06:21 time: 0.5330 data_time: 0.0067 memory: 16131 loss: 1.3477 loss_prob: 0.7471 loss_thr: 0.4761 loss_db: 0.1245 2022/10/26 03:35:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:35:59 - mmengine - INFO - Epoch(train) [602][5/63] lr: 1.8904e-03 eta: 8:06:21 time: 0.7194 data_time: 0.2097 memory: 16131 loss: 1.2951 loss_prob: 0.7174 loss_thr: 0.4541 loss_db: 0.1237 2022/10/26 03:36:02 - mmengine - INFO - Epoch(train) [602][10/63] lr: 1.8904e-03 eta: 8:06:09 time: 0.7556 data_time: 0.2121 memory: 16131 loss: 1.2029 loss_prob: 0.6501 loss_thr: 0.4453 loss_db: 0.1074 2022/10/26 03:36:04 - mmengine - INFO - Epoch(train) [602][15/63] lr: 1.8904e-03 eta: 8:06:09 time: 0.5179 data_time: 0.0084 memory: 16131 loss: 1.1990 loss_prob: 0.6560 loss_thr: 0.4315 loss_db: 0.1114 2022/10/26 03:36:07 - mmengine - INFO - Epoch(train) [602][20/63] lr: 1.8904e-03 eta: 8:05:58 time: 0.5064 data_time: 0.0058 memory: 16131 loss: 1.3219 loss_prob: 0.7338 loss_thr: 0.4605 loss_db: 0.1276 2022/10/26 03:36:09 - mmengine - INFO - Epoch(train) [602][25/63] lr: 1.8904e-03 eta: 8:05:58 time: 0.5164 data_time: 0.0214 memory: 16131 loss: 1.2982 loss_prob: 0.7046 loss_thr: 0.4723 loss_db: 0.1212 2022/10/26 03:36:12 - mmengine - INFO - Epoch(train) [602][30/63] lr: 1.8904e-03 eta: 8:05:48 time: 0.5251 data_time: 0.0352 memory: 16131 loss: 1.2376 loss_prob: 0.6787 loss_thr: 0.4434 loss_db: 0.1155 2022/10/26 03:36:15 - mmengine - INFO - Epoch(train) [602][35/63] lr: 1.8904e-03 eta: 8:05:48 time: 0.5256 data_time: 0.0240 memory: 16131 loss: 1.2881 loss_prob: 0.7241 loss_thr: 0.4444 loss_db: 0.1196 2022/10/26 03:36:17 - mmengine - INFO - Epoch(train) [602][40/63] lr: 1.8904e-03 eta: 8:05:38 time: 0.5344 data_time: 0.0095 memory: 16131 loss: 1.2433 loss_prob: 0.6785 loss_thr: 0.4525 loss_db: 0.1123 2022/10/26 03:36:20 - mmengine - INFO - Epoch(train) [602][45/63] lr: 1.8904e-03 eta: 8:05:38 time: 0.5529 data_time: 0.0047 memory: 16131 loss: 1.3429 loss_prob: 0.7289 loss_thr: 0.4928 loss_db: 0.1212 2022/10/26 03:36:23 - mmengine - INFO - Epoch(train) [602][50/63] lr: 1.8904e-03 eta: 8:05:28 time: 0.5448 data_time: 0.0151 memory: 16131 loss: 1.4058 loss_prob: 0.7738 loss_thr: 0.5034 loss_db: 0.1287 2022/10/26 03:36:25 - mmengine - INFO - Epoch(train) [602][55/63] lr: 1.8904e-03 eta: 8:05:28 time: 0.5103 data_time: 0.0236 memory: 16131 loss: 1.3482 loss_prob: 0.7417 loss_thr: 0.4856 loss_db: 0.1209 2022/10/26 03:36:28 - mmengine - INFO - Epoch(train) [602][60/63] lr: 1.8904e-03 eta: 8:05:18 time: 0.5248 data_time: 0.0130 memory: 16131 loss: 1.3458 loss_prob: 0.7343 loss_thr: 0.4907 loss_db: 0.1208 2022/10/26 03:36:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:36:35 - mmengine - INFO - Epoch(train) [603][5/63] lr: 1.8875e-03 eta: 8:05:18 time: 0.7815 data_time: 0.2286 memory: 16131 loss: 1.3391 loss_prob: 0.7235 loss_thr: 0.4920 loss_db: 0.1236 2022/10/26 03:36:37 - mmengine - INFO - Epoch(train) [603][10/63] lr: 1.8875e-03 eta: 8:05:06 time: 0.7921 data_time: 0.2273 memory: 16131 loss: 1.3171 loss_prob: 0.7123 loss_thr: 0.4860 loss_db: 0.1188 2022/10/26 03:36:40 - mmengine - INFO - Epoch(train) [603][15/63] lr: 1.8875e-03 eta: 8:05:06 time: 0.5241 data_time: 0.0074 memory: 16131 loss: 1.2794 loss_prob: 0.6941 loss_thr: 0.4677 loss_db: 0.1177 2022/10/26 03:36:43 - mmengine - INFO - Epoch(train) [603][20/63] lr: 1.8875e-03 eta: 8:04:56 time: 0.5390 data_time: 0.0071 memory: 16131 loss: 1.3418 loss_prob: 0.7527 loss_thr: 0.4634 loss_db: 0.1258 2022/10/26 03:36:45 - mmengine - INFO - Epoch(train) [603][25/63] lr: 1.8875e-03 eta: 8:04:56 time: 0.5425 data_time: 0.0174 memory: 16131 loss: 1.3009 loss_prob: 0.7238 loss_thr: 0.4577 loss_db: 0.1195 2022/10/26 03:36:48 - mmengine - INFO - Epoch(train) [603][30/63] lr: 1.8875e-03 eta: 8:04:46 time: 0.5667 data_time: 0.0323 memory: 16131 loss: 1.3260 loss_prob: 0.7071 loss_thr: 0.5027 loss_db: 0.1162 2022/10/26 03:36:51 - mmengine - INFO - Epoch(train) [603][35/63] lr: 1.8875e-03 eta: 8:04:46 time: 0.5379 data_time: 0.0201 memory: 16131 loss: 1.3782 loss_prob: 0.7362 loss_thr: 0.5184 loss_db: 0.1236 2022/10/26 03:36:53 - mmengine - INFO - Epoch(train) [603][40/63] lr: 1.8875e-03 eta: 8:04:35 time: 0.5026 data_time: 0.0067 memory: 16131 loss: 1.2846 loss_prob: 0.6898 loss_thr: 0.4757 loss_db: 0.1191 2022/10/26 03:36:56 - mmengine - INFO - Epoch(train) [603][45/63] lr: 1.8875e-03 eta: 8:04:35 time: 0.5213 data_time: 0.0076 memory: 16131 loss: 1.2969 loss_prob: 0.7074 loss_thr: 0.4694 loss_db: 0.1201 2022/10/26 03:36:59 - mmengine - INFO - Epoch(train) [603][50/63] lr: 1.8875e-03 eta: 8:04:26 time: 0.5585 data_time: 0.0145 memory: 16131 loss: 1.3626 loss_prob: 0.7571 loss_thr: 0.4790 loss_db: 0.1265 2022/10/26 03:37:02 - mmengine - INFO - Epoch(train) [603][55/63] lr: 1.8875e-03 eta: 8:04:26 time: 0.5561 data_time: 0.0261 memory: 16131 loss: 1.3174 loss_prob: 0.7174 loss_thr: 0.4797 loss_db: 0.1203 2022/10/26 03:37:04 - mmengine - INFO - Epoch(train) [603][60/63] lr: 1.8875e-03 eta: 8:04:15 time: 0.4934 data_time: 0.0188 memory: 16131 loss: 1.2770 loss_prob: 0.6910 loss_thr: 0.4680 loss_db: 0.1180 2022/10/26 03:37:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:37:10 - mmengine - INFO - Epoch(train) [604][5/63] lr: 1.8847e-03 eta: 8:04:15 time: 0.6926 data_time: 0.2044 memory: 16131 loss: 1.3766 loss_prob: 0.7485 loss_thr: 0.5056 loss_db: 0.1225 2022/10/26 03:37:13 - mmengine - INFO - Epoch(train) [604][10/63] lr: 1.8847e-03 eta: 8:04:02 time: 0.7275 data_time: 0.2038 memory: 16131 loss: 1.5007 loss_prob: 0.8856 loss_thr: 0.4827 loss_db: 0.1324 2022/10/26 03:37:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:37:15 - mmengine - INFO - Epoch(train) [604][15/63] lr: 1.8847e-03 eta: 8:04:02 time: 0.5073 data_time: 0.0062 memory: 16131 loss: 1.4744 loss_prob: 0.8701 loss_thr: 0.4738 loss_db: 0.1305 2022/10/26 03:37:18 - mmengine - INFO - Epoch(train) [604][20/63] lr: 1.8847e-03 eta: 8:03:52 time: 0.4980 data_time: 0.0081 memory: 16131 loss: 1.4240 loss_prob: 0.7985 loss_thr: 0.4953 loss_db: 0.1302 2022/10/26 03:37:20 - mmengine - INFO - Epoch(train) [604][25/63] lr: 1.8847e-03 eta: 8:03:52 time: 0.5200 data_time: 0.0203 memory: 16131 loss: 1.4332 loss_prob: 0.8040 loss_thr: 0.4949 loss_db: 0.1343 2022/10/26 03:37:23 - mmengine - INFO - Epoch(train) [604][30/63] lr: 1.8847e-03 eta: 8:03:42 time: 0.5665 data_time: 0.0460 memory: 16131 loss: 1.2896 loss_prob: 0.7037 loss_thr: 0.4649 loss_db: 0.1210 2022/10/26 03:37:26 - mmengine - INFO - Epoch(train) [604][35/63] lr: 1.8847e-03 eta: 8:03:42 time: 0.5732 data_time: 0.0346 memory: 16131 loss: 1.2695 loss_prob: 0.6775 loss_thr: 0.4775 loss_db: 0.1144 2022/10/26 03:37:28 - mmengine - INFO - Epoch(train) [604][40/63] lr: 1.8847e-03 eta: 8:03:32 time: 0.5090 data_time: 0.0075 memory: 16131 loss: 1.2623 loss_prob: 0.6690 loss_thr: 0.4807 loss_db: 0.1126 2022/10/26 03:37:31 - mmengine - INFO - Epoch(train) [604][45/63] lr: 1.8847e-03 eta: 8:03:32 time: 0.4981 data_time: 0.0071 memory: 16131 loss: 1.2796 loss_prob: 0.6884 loss_thr: 0.4742 loss_db: 0.1171 2022/10/26 03:37:33 - mmengine - INFO - Epoch(train) [604][50/63] lr: 1.8847e-03 eta: 8:03:21 time: 0.5023 data_time: 0.0235 memory: 16131 loss: 1.3627 loss_prob: 0.7486 loss_thr: 0.4903 loss_db: 0.1238 2022/10/26 03:37:36 - mmengine - INFO - Epoch(train) [604][55/63] lr: 1.8847e-03 eta: 8:03:21 time: 0.5082 data_time: 0.0267 memory: 16131 loss: 1.5380 loss_prob: 0.8826 loss_thr: 0.5163 loss_db: 0.1391 2022/10/26 03:37:39 - mmengine - INFO - Epoch(train) [604][60/63] lr: 1.8847e-03 eta: 8:03:11 time: 0.5382 data_time: 0.0083 memory: 16131 loss: 1.4204 loss_prob: 0.8027 loss_thr: 0.4881 loss_db: 0.1297 2022/10/26 03:37:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:37:45 - mmengine - INFO - Epoch(train) [605][5/63] lr: 1.8819e-03 eta: 8:03:11 time: 0.6893 data_time: 0.2128 memory: 16131 loss: 1.2579 loss_prob: 0.6940 loss_thr: 0.4478 loss_db: 0.1161 2022/10/26 03:37:47 - mmengine - INFO - Epoch(train) [605][10/63] lr: 1.8819e-03 eta: 8:02:59 time: 0.7138 data_time: 0.2090 memory: 16131 loss: 1.3117 loss_prob: 0.7049 loss_thr: 0.4861 loss_db: 0.1206 2022/10/26 03:37:50 - mmengine - INFO - Epoch(train) [605][15/63] lr: 1.8819e-03 eta: 8:02:59 time: 0.5239 data_time: 0.0068 memory: 16131 loss: 1.2991 loss_prob: 0.7078 loss_thr: 0.4673 loss_db: 0.1240 2022/10/26 03:37:53 - mmengine - INFO - Epoch(train) [605][20/63] lr: 1.8819e-03 eta: 8:02:49 time: 0.5445 data_time: 0.0070 memory: 16131 loss: 1.2839 loss_prob: 0.7124 loss_thr: 0.4505 loss_db: 0.1210 2022/10/26 03:37:55 - mmengine - INFO - Epoch(train) [605][25/63] lr: 1.8819e-03 eta: 8:02:49 time: 0.5231 data_time: 0.0190 memory: 16131 loss: 1.2389 loss_prob: 0.6684 loss_thr: 0.4588 loss_db: 0.1116 2022/10/26 03:37:58 - mmengine - INFO - Epoch(train) [605][30/63] lr: 1.8819e-03 eta: 8:02:38 time: 0.5339 data_time: 0.0361 memory: 16131 loss: 1.3038 loss_prob: 0.7129 loss_thr: 0.4701 loss_db: 0.1209 2022/10/26 03:38:00 - mmengine - INFO - Epoch(train) [605][35/63] lr: 1.8819e-03 eta: 8:02:38 time: 0.5246 data_time: 0.0257 memory: 16131 loss: 1.2675 loss_prob: 0.6941 loss_thr: 0.4560 loss_db: 0.1173 2022/10/26 03:38:03 - mmengine - INFO - Epoch(train) [605][40/63] lr: 1.8819e-03 eta: 8:02:28 time: 0.5148 data_time: 0.0103 memory: 16131 loss: 1.1871 loss_prob: 0.6419 loss_thr: 0.4363 loss_db: 0.1089 2022/10/26 03:38:06 - mmengine - INFO - Epoch(train) [605][45/63] lr: 1.8819e-03 eta: 8:02:28 time: 0.5143 data_time: 0.0080 memory: 16131 loss: 1.3694 loss_prob: 0.7788 loss_thr: 0.4630 loss_db: 0.1276 2022/10/26 03:38:08 - mmengine - INFO - Epoch(train) [605][50/63] lr: 1.8819e-03 eta: 8:02:18 time: 0.5007 data_time: 0.0196 memory: 16131 loss: 1.4632 loss_prob: 0.8355 loss_thr: 0.4922 loss_db: 0.1355 2022/10/26 03:38:11 - mmengine - INFO - Epoch(train) [605][55/63] lr: 1.8819e-03 eta: 8:02:18 time: 0.5330 data_time: 0.0256 memory: 16131 loss: 1.3092 loss_prob: 0.7122 loss_thr: 0.4768 loss_db: 0.1202 2022/10/26 03:38:13 - mmengine - INFO - Epoch(train) [605][60/63] lr: 1.8819e-03 eta: 8:02:08 time: 0.5233 data_time: 0.0137 memory: 16131 loss: 1.2839 loss_prob: 0.7005 loss_thr: 0.4674 loss_db: 0.1160 2022/10/26 03:38:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:38:19 - mmengine - INFO - Epoch(train) [606][5/63] lr: 1.8790e-03 eta: 8:02:08 time: 0.6757 data_time: 0.1967 memory: 16131 loss: 1.2646 loss_prob: 0.6834 loss_thr: 0.4661 loss_db: 0.1151 2022/10/26 03:38:22 - mmengine - INFO - Epoch(train) [606][10/63] lr: 1.8790e-03 eta: 8:01:55 time: 0.7169 data_time: 0.1955 memory: 16131 loss: 1.2386 loss_prob: 0.6775 loss_thr: 0.4464 loss_db: 0.1146 2022/10/26 03:38:25 - mmengine - INFO - Epoch(train) [606][15/63] lr: 1.8790e-03 eta: 8:01:55 time: 0.5545 data_time: 0.0116 memory: 16131 loss: 1.2364 loss_prob: 0.6788 loss_thr: 0.4421 loss_db: 0.1155 2022/10/26 03:38:27 - mmengine - INFO - Epoch(train) [606][20/63] lr: 1.8790e-03 eta: 8:01:45 time: 0.5413 data_time: 0.0121 memory: 16131 loss: 1.2879 loss_prob: 0.7097 loss_thr: 0.4582 loss_db: 0.1201 2022/10/26 03:38:30 - mmengine - INFO - Epoch(train) [606][25/63] lr: 1.8790e-03 eta: 8:01:45 time: 0.5207 data_time: 0.0231 memory: 16131 loss: 1.2491 loss_prob: 0.6783 loss_thr: 0.4534 loss_db: 0.1174 2022/10/26 03:38:32 - mmengine - INFO - Epoch(train) [606][30/63] lr: 1.8790e-03 eta: 8:01:35 time: 0.5157 data_time: 0.0340 memory: 16131 loss: 1.3634 loss_prob: 0.7659 loss_thr: 0.4729 loss_db: 0.1246 2022/10/26 03:38:35 - mmengine - INFO - Epoch(train) [606][35/63] lr: 1.8790e-03 eta: 8:01:35 time: 0.5187 data_time: 0.0162 memory: 16131 loss: 1.4000 loss_prob: 0.7893 loss_thr: 0.4869 loss_db: 0.1238 2022/10/26 03:38:38 - mmengine - INFO - Epoch(train) [606][40/63] lr: 1.8790e-03 eta: 8:01:25 time: 0.5277 data_time: 0.0051 memory: 16131 loss: 1.2349 loss_prob: 0.6550 loss_thr: 0.4708 loss_db: 0.1091 2022/10/26 03:38:40 - mmengine - INFO - Epoch(train) [606][45/63] lr: 1.8790e-03 eta: 8:01:25 time: 0.5037 data_time: 0.0073 memory: 16131 loss: 1.2269 loss_prob: 0.6583 loss_thr: 0.4550 loss_db: 0.1136 2022/10/26 03:38:43 - mmengine - INFO - Epoch(train) [606][50/63] lr: 1.8790e-03 eta: 8:01:14 time: 0.5042 data_time: 0.0233 memory: 16131 loss: 1.2346 loss_prob: 0.6717 loss_thr: 0.4477 loss_db: 0.1152 2022/10/26 03:38:45 - mmengine - INFO - Epoch(train) [606][55/63] lr: 1.8790e-03 eta: 8:01:14 time: 0.5210 data_time: 0.0220 memory: 16131 loss: 1.2588 loss_prob: 0.6856 loss_thr: 0.4582 loss_db: 0.1150 2022/10/26 03:38:48 - mmengine - INFO - Epoch(train) [606][60/63] lr: 1.8790e-03 eta: 8:01:04 time: 0.5314 data_time: 0.0052 memory: 16131 loss: 1.2670 loss_prob: 0.6847 loss_thr: 0.4656 loss_db: 0.1167 2022/10/26 03:38:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:38:54 - mmengine - INFO - Epoch(train) [607][5/63] lr: 1.8762e-03 eta: 8:01:04 time: 0.6657 data_time: 0.1880 memory: 16131 loss: 1.2347 loss_prob: 0.6651 loss_thr: 0.4566 loss_db: 0.1130 2022/10/26 03:38:56 - mmengine - INFO - Epoch(train) [607][10/63] lr: 1.8762e-03 eta: 8:00:51 time: 0.6759 data_time: 0.1877 memory: 16131 loss: 1.2785 loss_prob: 0.6992 loss_thr: 0.4630 loss_db: 0.1163 2022/10/26 03:38:59 - mmengine - INFO - Epoch(train) [607][15/63] lr: 1.8762e-03 eta: 8:00:51 time: 0.5081 data_time: 0.0055 memory: 16131 loss: 1.2898 loss_prob: 0.7001 loss_thr: 0.4731 loss_db: 0.1166 2022/10/26 03:39:01 - mmengine - INFO - Epoch(train) [607][20/63] lr: 1.8762e-03 eta: 8:00:41 time: 0.5419 data_time: 0.0064 memory: 16131 loss: 1.2942 loss_prob: 0.7014 loss_thr: 0.4739 loss_db: 0.1189 2022/10/26 03:39:05 - mmengine - INFO - Epoch(train) [607][25/63] lr: 1.8762e-03 eta: 8:00:41 time: 0.6069 data_time: 0.0223 memory: 16131 loss: 1.5290 loss_prob: 0.9117 loss_thr: 0.4805 loss_db: 0.1368 2022/10/26 03:39:07 - mmengine - INFO - Epoch(train) [607][30/63] lr: 1.8762e-03 eta: 8:00:31 time: 0.5724 data_time: 0.0341 memory: 16131 loss: 1.5465 loss_prob: 0.9235 loss_thr: 0.4824 loss_db: 0.1407 2022/10/26 03:39:10 - mmengine - INFO - Epoch(train) [607][35/63] lr: 1.8762e-03 eta: 8:00:31 time: 0.5074 data_time: 0.0184 memory: 16131 loss: 1.3694 loss_prob: 0.7631 loss_thr: 0.4770 loss_db: 0.1293 2022/10/26 03:39:12 - mmengine - INFO - Epoch(train) [607][40/63] lr: 1.8762e-03 eta: 8:00:21 time: 0.5193 data_time: 0.0065 memory: 16131 loss: 1.3738 loss_prob: 0.7607 loss_thr: 0.4845 loss_db: 0.1286 2022/10/26 03:39:15 - mmengine - INFO - Epoch(train) [607][45/63] lr: 1.8762e-03 eta: 8:00:21 time: 0.5031 data_time: 0.0065 memory: 16131 loss: 1.3274 loss_prob: 0.7249 loss_thr: 0.4775 loss_db: 0.1251 2022/10/26 03:39:18 - mmengine - INFO - Epoch(train) [607][50/63] lr: 1.8762e-03 eta: 8:00:11 time: 0.5530 data_time: 0.0140 memory: 16131 loss: 1.2973 loss_prob: 0.7039 loss_thr: 0.4733 loss_db: 0.1201 2022/10/26 03:39:20 - mmengine - INFO - Epoch(train) [607][55/63] lr: 1.8762e-03 eta: 8:00:11 time: 0.5656 data_time: 0.0252 memory: 16131 loss: 1.3926 loss_prob: 0.7796 loss_thr: 0.4885 loss_db: 0.1244 2022/10/26 03:39:23 - mmengine - INFO - Epoch(train) [607][60/63] lr: 1.8762e-03 eta: 8:00:01 time: 0.5035 data_time: 0.0172 memory: 16131 loss: 1.3236 loss_prob: 0.7436 loss_thr: 0.4587 loss_db: 0.1213 2022/10/26 03:39:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:39:29 - mmengine - INFO - Epoch(train) [608][5/63] lr: 1.8733e-03 eta: 8:00:01 time: 0.7566 data_time: 0.1977 memory: 16131 loss: 1.3056 loss_prob: 0.7185 loss_thr: 0.4647 loss_db: 0.1224 2022/10/26 03:39:32 - mmengine - INFO - Epoch(train) [608][10/63] lr: 1.8733e-03 eta: 7:59:49 time: 0.7644 data_time: 0.1968 memory: 16131 loss: 1.3272 loss_prob: 0.7350 loss_thr: 0.4704 loss_db: 0.1219 2022/10/26 03:39:34 - mmengine - INFO - Epoch(train) [608][15/63] lr: 1.8733e-03 eta: 7:59:49 time: 0.4972 data_time: 0.0063 memory: 16131 loss: 1.2859 loss_prob: 0.7004 loss_thr: 0.4673 loss_db: 0.1182 2022/10/26 03:39:37 - mmengine - INFO - Epoch(train) [608][20/63] lr: 1.8733e-03 eta: 7:59:39 time: 0.5356 data_time: 0.0070 memory: 16131 loss: 1.2386 loss_prob: 0.6721 loss_thr: 0.4514 loss_db: 0.1151 2022/10/26 03:39:41 - mmengine - INFO - Epoch(train) [608][25/63] lr: 1.8733e-03 eta: 7:59:39 time: 0.6097 data_time: 0.0320 memory: 16131 loss: 1.3013 loss_prob: 0.7125 loss_thr: 0.4666 loss_db: 0.1222 2022/10/26 03:39:43 - mmengine - INFO - Epoch(train) [608][30/63] lr: 1.8733e-03 eta: 7:59:29 time: 0.6189 data_time: 0.0319 memory: 16131 loss: 1.2537 loss_prob: 0.6803 loss_thr: 0.4585 loss_db: 0.1149 2022/10/26 03:39:46 - mmengine - INFO - Epoch(train) [608][35/63] lr: 1.8733e-03 eta: 7:59:29 time: 0.5289 data_time: 0.0065 memory: 16131 loss: 1.1857 loss_prob: 0.6282 loss_thr: 0.4491 loss_db: 0.1083 2022/10/26 03:39:48 - mmengine - INFO - Epoch(train) [608][40/63] lr: 1.8733e-03 eta: 7:59:19 time: 0.4824 data_time: 0.0058 memory: 16131 loss: 1.3022 loss_prob: 0.7025 loss_thr: 0.4794 loss_db: 0.1204 2022/10/26 03:39:51 - mmengine - INFO - Epoch(train) [608][45/63] lr: 1.8733e-03 eta: 7:59:19 time: 0.5000 data_time: 0.0045 memory: 16131 loss: 1.2360 loss_prob: 0.6725 loss_thr: 0.4513 loss_db: 0.1122 2022/10/26 03:39:54 - mmengine - INFO - Epoch(train) [608][50/63] lr: 1.8733e-03 eta: 7:59:09 time: 0.5252 data_time: 0.0216 memory: 16131 loss: 1.1900 loss_prob: 0.6469 loss_thr: 0.4327 loss_db: 0.1105 2022/10/26 03:39:56 - mmengine - INFO - Epoch(train) [608][55/63] lr: 1.8733e-03 eta: 7:59:09 time: 0.5325 data_time: 0.0215 memory: 16131 loss: 1.3852 loss_prob: 0.7722 loss_thr: 0.4842 loss_db: 0.1288 2022/10/26 03:39:59 - mmengine - INFO - Epoch(train) [608][60/63] lr: 1.8733e-03 eta: 7:58:59 time: 0.5680 data_time: 0.0069 memory: 16131 loss: 1.4050 loss_prob: 0.7812 loss_thr: 0.4931 loss_db: 0.1307 2022/10/26 03:40:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:40:06 - mmengine - INFO - Epoch(train) [609][5/63] lr: 1.8705e-03 eta: 7:58:59 time: 0.7661 data_time: 0.2034 memory: 16131 loss: 1.3303 loss_prob: 0.7282 loss_thr: 0.4820 loss_db: 0.1202 2022/10/26 03:40:08 - mmengine - INFO - Epoch(train) [609][10/63] lr: 1.8705e-03 eta: 7:58:47 time: 0.7512 data_time: 0.2068 memory: 16131 loss: 1.3106 loss_prob: 0.7062 loss_thr: 0.4842 loss_db: 0.1203 2022/10/26 03:40:11 - mmengine - INFO - Epoch(train) [609][15/63] lr: 1.8705e-03 eta: 7:58:47 time: 0.5554 data_time: 0.0088 memory: 16131 loss: 1.3390 loss_prob: 0.7264 loss_thr: 0.4898 loss_db: 0.1227 2022/10/26 03:40:14 - mmengine - INFO - Epoch(train) [609][20/63] lr: 1.8705e-03 eta: 7:58:37 time: 0.5457 data_time: 0.0063 memory: 16131 loss: 1.3373 loss_prob: 0.7359 loss_thr: 0.4780 loss_db: 0.1235 2022/10/26 03:40:16 - mmengine - INFO - Epoch(train) [609][25/63] lr: 1.8705e-03 eta: 7:58:37 time: 0.5267 data_time: 0.0232 memory: 16131 loss: 1.3306 loss_prob: 0.7365 loss_thr: 0.4692 loss_db: 0.1249 2022/10/26 03:40:19 - mmengine - INFO - Epoch(train) [609][30/63] lr: 1.8705e-03 eta: 7:58:27 time: 0.5719 data_time: 0.0309 memory: 16131 loss: 1.2651 loss_prob: 0.6776 loss_thr: 0.4733 loss_db: 0.1142 2022/10/26 03:40:22 - mmengine - INFO - Epoch(train) [609][35/63] lr: 1.8705e-03 eta: 7:58:27 time: 0.5810 data_time: 0.0209 memory: 16131 loss: 1.2088 loss_prob: 0.6303 loss_thr: 0.4700 loss_db: 0.1085 2022/10/26 03:40:25 - mmengine - INFO - Epoch(train) [609][40/63] lr: 1.8705e-03 eta: 7:58:17 time: 0.5680 data_time: 0.0165 memory: 16131 loss: 1.2630 loss_prob: 0.6810 loss_thr: 0.4659 loss_db: 0.1161 2022/10/26 03:40:28 - mmengine - INFO - Epoch(train) [609][45/63] lr: 1.8705e-03 eta: 7:58:17 time: 0.5434 data_time: 0.0111 memory: 16131 loss: 1.2830 loss_prob: 0.6958 loss_thr: 0.4702 loss_db: 0.1170 2022/10/26 03:40:30 - mmengine - INFO - Epoch(train) [609][50/63] lr: 1.8705e-03 eta: 7:58:07 time: 0.5238 data_time: 0.0168 memory: 16131 loss: 1.2148 loss_prob: 0.6505 loss_thr: 0.4513 loss_db: 0.1130 2022/10/26 03:40:33 - mmengine - INFO - Epoch(train) [609][55/63] lr: 1.8705e-03 eta: 7:58:07 time: 0.5474 data_time: 0.0216 memory: 16131 loss: 1.2189 loss_prob: 0.6529 loss_thr: 0.4529 loss_db: 0.1131 2022/10/26 03:40:36 - mmengine - INFO - Epoch(train) [609][60/63] lr: 1.8705e-03 eta: 7:57:58 time: 0.5663 data_time: 0.0127 memory: 16131 loss: 1.2585 loss_prob: 0.6758 loss_thr: 0.4669 loss_db: 0.1158 2022/10/26 03:40:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:40:41 - mmengine - INFO - Epoch(train) [610][5/63] lr: 1.8676e-03 eta: 7:57:58 time: 0.6619 data_time: 0.1736 memory: 16131 loss: 1.2118 loss_prob: 0.6519 loss_thr: 0.4497 loss_db: 0.1103 2022/10/26 03:40:44 - mmengine - INFO - Epoch(train) [610][10/63] lr: 1.8676e-03 eta: 7:57:45 time: 0.6925 data_time: 0.1748 memory: 16131 loss: 1.3017 loss_prob: 0.7092 loss_thr: 0.4713 loss_db: 0.1212 2022/10/26 03:40:47 - mmengine - INFO - Epoch(train) [610][15/63] lr: 1.8676e-03 eta: 7:57:45 time: 0.5148 data_time: 0.0083 memory: 16131 loss: 1.3881 loss_prob: 0.7609 loss_thr: 0.4998 loss_db: 0.1273 2022/10/26 03:40:49 - mmengine - INFO - Epoch(train) [610][20/63] lr: 1.8676e-03 eta: 7:57:35 time: 0.5213 data_time: 0.0049 memory: 16131 loss: 1.2632 loss_prob: 0.6711 loss_thr: 0.4806 loss_db: 0.1115 2022/10/26 03:40:52 - mmengine - INFO - Epoch(train) [610][25/63] lr: 1.8676e-03 eta: 7:57:35 time: 0.5228 data_time: 0.0102 memory: 16131 loss: 1.2753 loss_prob: 0.6748 loss_thr: 0.4859 loss_db: 0.1145 2022/10/26 03:40:55 - mmengine - INFO - Epoch(train) [610][30/63] lr: 1.8676e-03 eta: 7:57:24 time: 0.5187 data_time: 0.0322 memory: 16131 loss: 1.3524 loss_prob: 0.7293 loss_thr: 0.4986 loss_db: 0.1245 2022/10/26 03:40:57 - mmengine - INFO - Epoch(train) [610][35/63] lr: 1.8676e-03 eta: 7:57:24 time: 0.5283 data_time: 0.0389 memory: 16131 loss: 1.3717 loss_prob: 0.7553 loss_thr: 0.4888 loss_db: 0.1275 2022/10/26 03:41:00 - mmengine - INFO - Epoch(train) [610][40/63] lr: 1.8676e-03 eta: 7:57:14 time: 0.5041 data_time: 0.0166 memory: 16131 loss: 1.3801 loss_prob: 0.7748 loss_thr: 0.4760 loss_db: 0.1294 2022/10/26 03:41:02 - mmengine - INFO - Epoch(train) [610][45/63] lr: 1.8676e-03 eta: 7:57:14 time: 0.4804 data_time: 0.0044 memory: 16131 loss: 1.3548 loss_prob: 0.7479 loss_thr: 0.4801 loss_db: 0.1268 2022/10/26 03:41:05 - mmengine - INFO - Epoch(train) [610][50/63] lr: 1.8676e-03 eta: 7:57:04 time: 0.5011 data_time: 0.0165 memory: 16131 loss: 1.2445 loss_prob: 0.6729 loss_thr: 0.4576 loss_db: 0.1140 2022/10/26 03:41:07 - mmengine - INFO - Epoch(train) [610][55/63] lr: 1.8676e-03 eta: 7:57:04 time: 0.5057 data_time: 0.0195 memory: 16131 loss: 1.2548 loss_prob: 0.6928 loss_thr: 0.4501 loss_db: 0.1120 2022/10/26 03:41:09 - mmengine - INFO - Epoch(train) [610][60/63] lr: 1.8676e-03 eta: 7:56:53 time: 0.4814 data_time: 0.0076 memory: 16131 loss: 1.2875 loss_prob: 0.7163 loss_thr: 0.4539 loss_db: 0.1173 2022/10/26 03:41:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:41:16 - mmengine - INFO - Epoch(train) [611][5/63] lr: 1.8648e-03 eta: 7:56:53 time: 0.7339 data_time: 0.2416 memory: 16131 loss: 1.3786 loss_prob: 0.7453 loss_thr: 0.5053 loss_db: 0.1279 2022/10/26 03:41:18 - mmengine - INFO - Epoch(train) [611][10/63] lr: 1.8648e-03 eta: 7:56:41 time: 0.7598 data_time: 0.2419 memory: 16131 loss: 1.3709 loss_prob: 0.7437 loss_thr: 0.4990 loss_db: 0.1282 2022/10/26 03:41:21 - mmengine - INFO - Epoch(train) [611][15/63] lr: 1.8648e-03 eta: 7:56:41 time: 0.4955 data_time: 0.0054 memory: 16131 loss: 1.2430 loss_prob: 0.6727 loss_thr: 0.4539 loss_db: 0.1164 2022/10/26 03:41:24 - mmengine - INFO - Epoch(train) [611][20/63] lr: 1.8648e-03 eta: 7:56:31 time: 0.5256 data_time: 0.0128 memory: 16131 loss: 1.2269 loss_prob: 0.6539 loss_thr: 0.4600 loss_db: 0.1130 2022/10/26 03:41:27 - mmengine - INFO - Epoch(train) [611][25/63] lr: 1.8648e-03 eta: 7:56:31 time: 0.5754 data_time: 0.0279 memory: 16131 loss: 1.2758 loss_prob: 0.6851 loss_thr: 0.4727 loss_db: 0.1180 2022/10/26 03:41:29 - mmengine - INFO - Epoch(train) [611][30/63] lr: 1.8648e-03 eta: 7:56:21 time: 0.5501 data_time: 0.0291 memory: 16131 loss: 1.2157 loss_prob: 0.6588 loss_thr: 0.4441 loss_db: 0.1128 2022/10/26 03:41:32 - mmengine - INFO - Epoch(train) [611][35/63] lr: 1.8648e-03 eta: 7:56:21 time: 0.5609 data_time: 0.0145 memory: 16131 loss: 1.2770 loss_prob: 0.7132 loss_thr: 0.4457 loss_db: 0.1182 2022/10/26 03:41:35 - mmengine - INFO - Epoch(train) [611][40/63] lr: 1.8648e-03 eta: 7:56:12 time: 0.5947 data_time: 0.0075 memory: 16131 loss: 1.2598 loss_prob: 0.6957 loss_thr: 0.4495 loss_db: 0.1147 2022/10/26 03:41:38 - mmengine - INFO - Epoch(train) [611][45/63] lr: 1.8648e-03 eta: 7:56:12 time: 0.5570 data_time: 0.0151 memory: 16131 loss: 1.2093 loss_prob: 0.6479 loss_thr: 0.4511 loss_db: 0.1103 2022/10/26 03:41:41 - mmengine - INFO - Epoch(train) [611][50/63] lr: 1.8648e-03 eta: 7:56:02 time: 0.5614 data_time: 0.0228 memory: 16131 loss: 1.2882 loss_prob: 0.7008 loss_thr: 0.4664 loss_db: 0.1210 2022/10/26 03:41:43 - mmengine - INFO - Epoch(train) [611][55/63] lr: 1.8648e-03 eta: 7:56:02 time: 0.5412 data_time: 0.0210 memory: 16131 loss: 1.4535 loss_prob: 0.8021 loss_thr: 0.5153 loss_db: 0.1362 2022/10/26 03:41:46 - mmengine - INFO - Epoch(train) [611][60/63] lr: 1.8648e-03 eta: 7:55:52 time: 0.4985 data_time: 0.0116 memory: 16131 loss: 1.4662 loss_prob: 0.8141 loss_thr: 0.5156 loss_db: 0.1364 2022/10/26 03:41:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:41:51 - mmengine - INFO - Epoch(train) [612][5/63] lr: 1.8619e-03 eta: 7:55:52 time: 0.6779 data_time: 0.1627 memory: 16131 loss: 1.3117 loss_prob: 0.7074 loss_thr: 0.4840 loss_db: 0.1203 2022/10/26 03:41:54 - mmengine - INFO - Epoch(train) [612][10/63] lr: 1.8619e-03 eta: 7:55:39 time: 0.7219 data_time: 0.1629 memory: 16131 loss: 1.2729 loss_prob: 0.6888 loss_thr: 0.4657 loss_db: 0.1183 2022/10/26 03:41:57 - mmengine - INFO - Epoch(train) [612][15/63] lr: 1.8619e-03 eta: 7:55:39 time: 0.5394 data_time: 0.0127 memory: 16131 loss: 1.3521 loss_prob: 0.7392 loss_thr: 0.4888 loss_db: 0.1240 2022/10/26 03:41:59 - mmengine - INFO - Epoch(train) [612][20/63] lr: 1.8619e-03 eta: 7:55:29 time: 0.5164 data_time: 0.0126 memory: 16131 loss: 1.3457 loss_prob: 0.7292 loss_thr: 0.4921 loss_db: 0.1245 2022/10/26 03:42:02 - mmengine - INFO - Epoch(train) [612][25/63] lr: 1.8619e-03 eta: 7:55:29 time: 0.5169 data_time: 0.0069 memory: 16131 loss: 1.2400 loss_prob: 0.6674 loss_thr: 0.4565 loss_db: 0.1162 2022/10/26 03:42:05 - mmengine - INFO - Epoch(train) [612][30/63] lr: 1.8619e-03 eta: 7:55:19 time: 0.5474 data_time: 0.0300 memory: 16131 loss: 1.2469 loss_prob: 0.6769 loss_thr: 0.4559 loss_db: 0.1141 2022/10/26 03:42:07 - mmengine - INFO - Epoch(train) [612][35/63] lr: 1.8619e-03 eta: 7:55:19 time: 0.5366 data_time: 0.0318 memory: 16131 loss: 1.4156 loss_prob: 0.7915 loss_thr: 0.4938 loss_db: 0.1303 2022/10/26 03:42:10 - mmengine - INFO - Epoch(train) [612][40/63] lr: 1.8619e-03 eta: 7:55:09 time: 0.5012 data_time: 0.0144 memory: 16131 loss: 1.3746 loss_prob: 0.7593 loss_thr: 0.4899 loss_db: 0.1254 2022/10/26 03:42:12 - mmengine - INFO - Epoch(train) [612][45/63] lr: 1.8619e-03 eta: 7:55:09 time: 0.5182 data_time: 0.0104 memory: 16131 loss: 1.2533 loss_prob: 0.6786 loss_thr: 0.4606 loss_db: 0.1140 2022/10/26 03:42:15 - mmengine - INFO - Epoch(train) [612][50/63] lr: 1.8619e-03 eta: 7:54:59 time: 0.5229 data_time: 0.0112 memory: 16131 loss: 1.3219 loss_prob: 0.7243 loss_thr: 0.4757 loss_db: 0.1218 2022/10/26 03:42:17 - mmengine - INFO - Epoch(train) [612][55/63] lr: 1.8619e-03 eta: 7:54:59 time: 0.5076 data_time: 0.0166 memory: 16131 loss: 1.2977 loss_prob: 0.7113 loss_thr: 0.4700 loss_db: 0.1165 2022/10/26 03:42:20 - mmengine - INFO - Epoch(train) [612][60/63] lr: 1.8619e-03 eta: 7:54:49 time: 0.5199 data_time: 0.0151 memory: 16131 loss: 1.2293 loss_prob: 0.6728 loss_thr: 0.4455 loss_db: 0.1110 2022/10/26 03:42:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:42:27 - mmengine - INFO - Epoch(train) [613][5/63] lr: 1.8591e-03 eta: 7:54:49 time: 0.7551 data_time: 0.2168 memory: 16131 loss: 1.2742 loss_prob: 0.7091 loss_thr: 0.4456 loss_db: 0.1194 2022/10/26 03:42:30 - mmengine - INFO - Epoch(train) [613][10/63] lr: 1.8591e-03 eta: 7:54:37 time: 0.8214 data_time: 0.2126 memory: 16131 loss: 1.3384 loss_prob: 0.7477 loss_thr: 0.4644 loss_db: 0.1263 2022/10/26 03:42:33 - mmengine - INFO - Epoch(train) [613][15/63] lr: 1.8591e-03 eta: 7:54:37 time: 0.6150 data_time: 0.0097 memory: 16131 loss: 1.2992 loss_prob: 0.7121 loss_thr: 0.4666 loss_db: 0.1204 2022/10/26 03:42:35 - mmengine - INFO - Epoch(train) [613][20/63] lr: 1.8591e-03 eta: 7:54:27 time: 0.5309 data_time: 0.0092 memory: 16131 loss: 1.2639 loss_prob: 0.6867 loss_thr: 0.4611 loss_db: 0.1161 2022/10/26 03:42:38 - mmengine - INFO - Epoch(train) [613][25/63] lr: 1.8591e-03 eta: 7:54:27 time: 0.5245 data_time: 0.0304 memory: 16131 loss: 1.2513 loss_prob: 0.6749 loss_thr: 0.4619 loss_db: 0.1145 2022/10/26 03:42:41 - mmengine - INFO - Epoch(train) [613][30/63] lr: 1.8591e-03 eta: 7:54:17 time: 0.5594 data_time: 0.0326 memory: 16131 loss: 1.2659 loss_prob: 0.6863 loss_thr: 0.4603 loss_db: 0.1193 2022/10/26 03:42:43 - mmengine - INFO - Epoch(train) [613][35/63] lr: 1.8591e-03 eta: 7:54:17 time: 0.5268 data_time: 0.0071 memory: 16131 loss: 1.1778 loss_prob: 0.6357 loss_thr: 0.4327 loss_db: 0.1094 2022/10/26 03:42:46 - mmengine - INFO - Epoch(train) [613][40/63] lr: 1.8591e-03 eta: 7:54:07 time: 0.5403 data_time: 0.0057 memory: 16131 loss: 1.2181 loss_prob: 0.6543 loss_thr: 0.4568 loss_db: 0.1070 2022/10/26 03:42:48 - mmengine - INFO - Epoch(train) [613][45/63] lr: 1.8591e-03 eta: 7:54:07 time: 0.5290 data_time: 0.0059 memory: 16131 loss: 1.3761 loss_prob: 0.7538 loss_thr: 0.4985 loss_db: 0.1238 2022/10/26 03:42:51 - mmengine - INFO - Epoch(train) [613][50/63] lr: 1.8591e-03 eta: 7:53:57 time: 0.5162 data_time: 0.0205 memory: 16131 loss: 1.4807 loss_prob: 0.8388 loss_thr: 0.5057 loss_db: 0.1362 2022/10/26 03:42:54 - mmengine - INFO - Epoch(train) [613][55/63] lr: 1.8591e-03 eta: 7:53:57 time: 0.5158 data_time: 0.0215 memory: 16131 loss: 1.4636 loss_prob: 0.8281 loss_thr: 0.4994 loss_db: 0.1361 2022/10/26 03:42:56 - mmengine - INFO - Epoch(train) [613][60/63] lr: 1.8591e-03 eta: 7:53:47 time: 0.4942 data_time: 0.0060 memory: 16131 loss: 1.4590 loss_prob: 0.8208 loss_thr: 0.4999 loss_db: 0.1383 2022/10/26 03:42:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:43:02 - mmengine - INFO - Epoch(train) [614][5/63] lr: 1.8562e-03 eta: 7:53:47 time: 0.7035 data_time: 0.2038 memory: 16131 loss: 1.4138 loss_prob: 0.7751 loss_thr: 0.5088 loss_db: 0.1299 2022/10/26 03:43:05 - mmengine - INFO - Epoch(train) [614][10/63] lr: 1.8562e-03 eta: 7:53:34 time: 0.7312 data_time: 0.2055 memory: 16131 loss: 1.3773 loss_prob: 0.7527 loss_thr: 0.4974 loss_db: 0.1271 2022/10/26 03:43:08 - mmengine - INFO - Epoch(train) [614][15/63] lr: 1.8562e-03 eta: 7:53:34 time: 0.5527 data_time: 0.0074 memory: 16131 loss: 1.3810 loss_prob: 0.7630 loss_thr: 0.4882 loss_db: 0.1298 2022/10/26 03:43:10 - mmengine - INFO - Epoch(train) [614][20/63] lr: 1.8562e-03 eta: 7:53:25 time: 0.5667 data_time: 0.0116 memory: 16131 loss: 1.3624 loss_prob: 0.7699 loss_thr: 0.4641 loss_db: 0.1284 2022/10/26 03:43:14 - mmengine - INFO - Epoch(train) [614][25/63] lr: 1.8562e-03 eta: 7:53:25 time: 0.6500 data_time: 0.0394 memory: 16131 loss: 1.3892 loss_prob: 0.7738 loss_thr: 0.4855 loss_db: 0.1299 2022/10/26 03:43:17 - mmengine - INFO - Epoch(train) [614][30/63] lr: 1.8562e-03 eta: 7:53:16 time: 0.6302 data_time: 0.0337 memory: 16131 loss: 1.4073 loss_prob: 0.7776 loss_thr: 0.4993 loss_db: 0.1304 2022/10/26 03:43:19 - mmengine - INFO - Epoch(train) [614][35/63] lr: 1.8562e-03 eta: 7:53:16 time: 0.5116 data_time: 0.0058 memory: 16131 loss: 1.4309 loss_prob: 0.7973 loss_thr: 0.5003 loss_db: 0.1333 2022/10/26 03:43:22 - mmengine - INFO - Epoch(train) [614][40/63] lr: 1.8562e-03 eta: 7:53:06 time: 0.5435 data_time: 0.0058 memory: 16131 loss: 1.3984 loss_prob: 0.7770 loss_thr: 0.4905 loss_db: 0.1309 2022/10/26 03:43:25 - mmengine - INFO - Epoch(train) [614][45/63] lr: 1.8562e-03 eta: 7:53:06 time: 0.5716 data_time: 0.0122 memory: 16131 loss: 1.4112 loss_prob: 0.7958 loss_thr: 0.4827 loss_db: 0.1326 2022/10/26 03:43:28 - mmengine - INFO - Epoch(train) [614][50/63] lr: 1.8562e-03 eta: 7:52:56 time: 0.5674 data_time: 0.0275 memory: 16131 loss: 1.4560 loss_prob: 0.8136 loss_thr: 0.5054 loss_db: 0.1370 2022/10/26 03:43:30 - mmengine - INFO - Epoch(train) [614][55/63] lr: 1.8562e-03 eta: 7:52:56 time: 0.5364 data_time: 0.0198 memory: 16131 loss: 1.3976 loss_prob: 0.7744 loss_thr: 0.4946 loss_db: 0.1285 2022/10/26 03:43:33 - mmengine - INFO - Epoch(train) [614][60/63] lr: 1.8562e-03 eta: 7:52:46 time: 0.5194 data_time: 0.0103 memory: 16131 loss: 1.3146 loss_prob: 0.7221 loss_thr: 0.4745 loss_db: 0.1180 2022/10/26 03:43:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:43:39 - mmengine - INFO - Epoch(train) [615][5/63] lr: 1.8534e-03 eta: 7:52:46 time: 0.6474 data_time: 0.1668 memory: 16131 loss: 1.2626 loss_prob: 0.6859 loss_thr: 0.4624 loss_db: 0.1143 2022/10/26 03:43:41 - mmengine - INFO - Epoch(train) [615][10/63] lr: 1.8534e-03 eta: 7:52:33 time: 0.6913 data_time: 0.1708 memory: 16131 loss: 1.2934 loss_prob: 0.7029 loss_thr: 0.4718 loss_db: 0.1186 2022/10/26 03:43:44 - mmengine - INFO - Epoch(train) [615][15/63] lr: 1.8534e-03 eta: 7:52:33 time: 0.5211 data_time: 0.0122 memory: 16131 loss: 1.3303 loss_prob: 0.7333 loss_thr: 0.4702 loss_db: 0.1268 2022/10/26 03:43:46 - mmengine - INFO - Epoch(train) [615][20/63] lr: 1.8534e-03 eta: 7:52:23 time: 0.5253 data_time: 0.0078 memory: 16131 loss: 1.2424 loss_prob: 0.6845 loss_thr: 0.4415 loss_db: 0.1163 2022/10/26 03:43:49 - mmengine - INFO - Epoch(train) [615][25/63] lr: 1.8534e-03 eta: 7:52:23 time: 0.5387 data_time: 0.0272 memory: 16131 loss: 1.2385 loss_prob: 0.6771 loss_thr: 0.4476 loss_db: 0.1138 2022/10/26 03:43:52 - mmengine - INFO - Epoch(train) [615][30/63] lr: 1.8534e-03 eta: 7:52:13 time: 0.5274 data_time: 0.0349 memory: 16131 loss: 1.2621 loss_prob: 0.6941 loss_thr: 0.4514 loss_db: 0.1166 2022/10/26 03:43:54 - mmengine - INFO - Epoch(train) [615][35/63] lr: 1.8534e-03 eta: 7:52:13 time: 0.5188 data_time: 0.0150 memory: 16131 loss: 1.2550 loss_prob: 0.6927 loss_thr: 0.4446 loss_db: 0.1178 2022/10/26 03:43:57 - mmengine - INFO - Epoch(train) [615][40/63] lr: 1.8534e-03 eta: 7:52:03 time: 0.5135 data_time: 0.0055 memory: 16131 loss: 1.2799 loss_prob: 0.7123 loss_thr: 0.4462 loss_db: 0.1214 2022/10/26 03:44:00 - mmengine - INFO - Epoch(train) [615][45/63] lr: 1.8534e-03 eta: 7:52:03 time: 0.5076 data_time: 0.0053 memory: 16131 loss: 1.3655 loss_prob: 0.7712 loss_thr: 0.4626 loss_db: 0.1317 2022/10/26 03:44:02 - mmengine - INFO - Epoch(train) [615][50/63] lr: 1.8534e-03 eta: 7:51:53 time: 0.5234 data_time: 0.0198 memory: 16131 loss: 1.3786 loss_prob: 0.7776 loss_thr: 0.4650 loss_db: 0.1360 2022/10/26 03:44:05 - mmengine - INFO - Epoch(train) [615][55/63] lr: 1.8534e-03 eta: 7:51:53 time: 0.5064 data_time: 0.0209 memory: 16131 loss: 1.3656 loss_prob: 0.7591 loss_thr: 0.4763 loss_db: 0.1302 2022/10/26 03:44:07 - mmengine - INFO - Epoch(train) [615][60/63] lr: 1.8534e-03 eta: 7:51:43 time: 0.5042 data_time: 0.0090 memory: 16131 loss: 1.3776 loss_prob: 0.7593 loss_thr: 0.4922 loss_db: 0.1261 2022/10/26 03:44:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:44:13 - mmengine - INFO - Epoch(train) [616][5/63] lr: 1.8505e-03 eta: 7:51:43 time: 0.7061 data_time: 0.2118 memory: 16131 loss: 1.3594 loss_prob: 0.7463 loss_thr: 0.4841 loss_db: 0.1290 2022/10/26 03:44:16 - mmengine - INFO - Epoch(train) [616][10/63] lr: 1.8505e-03 eta: 7:51:31 time: 0.7389 data_time: 0.2116 memory: 16131 loss: 1.3161 loss_prob: 0.7064 loss_thr: 0.4854 loss_db: 0.1242 2022/10/26 03:44:18 - mmengine - INFO - Epoch(train) [616][15/63] lr: 1.8505e-03 eta: 7:51:31 time: 0.5103 data_time: 0.0115 memory: 16131 loss: 1.3304 loss_prob: 0.7185 loss_thr: 0.4876 loss_db: 0.1242 2022/10/26 03:44:21 - mmengine - INFO - Epoch(train) [616][20/63] lr: 1.8505e-03 eta: 7:51:21 time: 0.5422 data_time: 0.0136 memory: 16131 loss: 1.4383 loss_prob: 0.8127 loss_thr: 0.4869 loss_db: 0.1387 2022/10/26 03:44:24 - mmengine - INFO - Epoch(train) [616][25/63] lr: 1.8505e-03 eta: 7:51:21 time: 0.6033 data_time: 0.0261 memory: 16131 loss: 1.4569 loss_prob: 0.8224 loss_thr: 0.4920 loss_db: 0.1425 2022/10/26 03:44:27 - mmengine - INFO - Epoch(train) [616][30/63] lr: 1.8505e-03 eta: 7:51:11 time: 0.5771 data_time: 0.0344 memory: 16131 loss: 1.4075 loss_prob: 0.7903 loss_thr: 0.4838 loss_db: 0.1334 2022/10/26 03:44:30 - mmengine - INFO - Epoch(train) [616][35/63] lr: 1.8505e-03 eta: 7:51:11 time: 0.5181 data_time: 0.0163 memory: 16131 loss: 1.4972 loss_prob: 0.8738 loss_thr: 0.4810 loss_db: 0.1423 2022/10/26 03:44:32 - mmengine - INFO - Epoch(train) [616][40/63] lr: 1.8505e-03 eta: 7:51:01 time: 0.4956 data_time: 0.0060 memory: 16131 loss: 1.4442 loss_prob: 0.8268 loss_thr: 0.4807 loss_db: 0.1367 2022/10/26 03:44:34 - mmengine - INFO - Epoch(train) [616][45/63] lr: 1.8505e-03 eta: 7:51:01 time: 0.4879 data_time: 0.0063 memory: 16131 loss: 1.3641 loss_prob: 0.7439 loss_thr: 0.4941 loss_db: 0.1261 2022/10/26 03:44:37 - mmengine - INFO - Epoch(train) [616][50/63] lr: 1.8505e-03 eta: 7:50:51 time: 0.5150 data_time: 0.0329 memory: 16131 loss: 1.4129 loss_prob: 0.7753 loss_thr: 0.5085 loss_db: 0.1291 2022/10/26 03:44:40 - mmengine - INFO - Epoch(train) [616][55/63] lr: 1.8505e-03 eta: 7:50:51 time: 0.5156 data_time: 0.0352 memory: 16131 loss: 1.3926 loss_prob: 0.7711 loss_thr: 0.4927 loss_db: 0.1288 2022/10/26 03:44:42 - mmengine - INFO - Epoch(train) [616][60/63] lr: 1.8505e-03 eta: 7:50:41 time: 0.4948 data_time: 0.0080 memory: 16131 loss: 1.3018 loss_prob: 0.7123 loss_thr: 0.4690 loss_db: 0.1205 2022/10/26 03:44:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:44:49 - mmengine - INFO - Epoch(train) [617][5/63] lr: 1.8477e-03 eta: 7:50:41 time: 0.7547 data_time: 0.2035 memory: 16131 loss: 1.1973 loss_prob: 0.6359 loss_thr: 0.4538 loss_db: 0.1076 2022/10/26 03:44:51 - mmengine - INFO - Epoch(train) [617][10/63] lr: 1.8477e-03 eta: 7:50:28 time: 0.7511 data_time: 0.2036 memory: 16131 loss: 1.1999 loss_prob: 0.6334 loss_thr: 0.4589 loss_db: 0.1076 2022/10/26 03:44:54 - mmengine - INFO - Epoch(train) [617][15/63] lr: 1.8477e-03 eta: 7:50:28 time: 0.5218 data_time: 0.0058 memory: 16131 loss: 1.2456 loss_prob: 0.6663 loss_thr: 0.4657 loss_db: 0.1136 2022/10/26 03:44:57 - mmengine - INFO - Epoch(train) [617][20/63] lr: 1.8477e-03 eta: 7:50:19 time: 0.5374 data_time: 0.0065 memory: 16131 loss: 1.2628 loss_prob: 0.6892 loss_thr: 0.4554 loss_db: 0.1182 2022/10/26 03:45:00 - mmengine - INFO - Epoch(train) [617][25/63] lr: 1.8477e-03 eta: 7:50:19 time: 0.5816 data_time: 0.0298 memory: 16131 loss: 1.3139 loss_prob: 0.7287 loss_thr: 0.4636 loss_db: 0.1217 2022/10/26 03:45:03 - mmengine - INFO - Epoch(train) [617][30/63] lr: 1.8477e-03 eta: 7:50:09 time: 0.5899 data_time: 0.0325 memory: 16131 loss: 1.4850 loss_prob: 0.8387 loss_thr: 0.5098 loss_db: 0.1365 2022/10/26 03:45:05 - mmengine - INFO - Epoch(train) [617][35/63] lr: 1.8477e-03 eta: 7:50:09 time: 0.5637 data_time: 0.0080 memory: 16131 loss: 1.3738 loss_prob: 0.7615 loss_thr: 0.4834 loss_db: 0.1289 2022/10/26 03:45:08 - mmengine - INFO - Epoch(train) [617][40/63] lr: 1.8477e-03 eta: 7:49:59 time: 0.5348 data_time: 0.0068 memory: 16131 loss: 1.2632 loss_prob: 0.6764 loss_thr: 0.4692 loss_db: 0.1175 2022/10/26 03:45:10 - mmengine - INFO - Epoch(train) [617][45/63] lr: 1.8477e-03 eta: 7:49:59 time: 0.4930 data_time: 0.0066 memory: 16131 loss: 1.3963 loss_prob: 0.7674 loss_thr: 0.4946 loss_db: 0.1343 2022/10/26 03:45:13 - mmengine - INFO - Epoch(train) [617][50/63] lr: 1.8477e-03 eta: 7:49:49 time: 0.5216 data_time: 0.0180 memory: 16131 loss: 1.4177 loss_prob: 0.7926 loss_thr: 0.4867 loss_db: 0.1384 2022/10/26 03:45:16 - mmengine - INFO - Epoch(train) [617][55/63] lr: 1.8477e-03 eta: 7:49:49 time: 0.5412 data_time: 0.0214 memory: 16131 loss: 1.5994 loss_prob: 0.9158 loss_thr: 0.5344 loss_db: 0.1492 2022/10/26 03:45:18 - mmengine - INFO - Epoch(train) [617][60/63] lr: 1.8477e-03 eta: 7:49:39 time: 0.4956 data_time: 0.0077 memory: 16131 loss: 1.5751 loss_prob: 0.8959 loss_thr: 0.5344 loss_db: 0.1448 2022/10/26 03:45:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:45:24 - mmengine - INFO - Epoch(train) [618][5/63] lr: 1.8448e-03 eta: 7:49:39 time: 0.6969 data_time: 0.1545 memory: 16131 loss: 1.4688 loss_prob: 0.8229 loss_thr: 0.5099 loss_db: 0.1360 2022/10/26 03:45:27 - mmengine - INFO - Epoch(train) [618][10/63] lr: 1.8448e-03 eta: 7:49:27 time: 0.7352 data_time: 0.1529 memory: 16131 loss: 1.4264 loss_prob: 0.8058 loss_thr: 0.4860 loss_db: 0.1347 2022/10/26 03:45:29 - mmengine - INFO - Epoch(train) [618][15/63] lr: 1.8448e-03 eta: 7:49:27 time: 0.5156 data_time: 0.0046 memory: 16131 loss: 1.3512 loss_prob: 0.7485 loss_thr: 0.4755 loss_db: 0.1272 2022/10/26 03:45:32 - mmengine - INFO - Epoch(train) [618][20/63] lr: 1.8448e-03 eta: 7:49:16 time: 0.4922 data_time: 0.0053 memory: 16131 loss: 1.4636 loss_prob: 0.8133 loss_thr: 0.5127 loss_db: 0.1376 2022/10/26 03:45:35 - mmengine - INFO - Epoch(train) [618][25/63] lr: 1.8448e-03 eta: 7:49:16 time: 0.5417 data_time: 0.0127 memory: 16131 loss: 1.4606 loss_prob: 0.8089 loss_thr: 0.5157 loss_db: 0.1359 2022/10/26 03:45:37 - mmengine - INFO - Epoch(train) [618][30/63] lr: 1.8448e-03 eta: 7:49:07 time: 0.5746 data_time: 0.0376 memory: 16131 loss: 1.3975 loss_prob: 0.7728 loss_thr: 0.4938 loss_db: 0.1309 2022/10/26 03:45:40 - mmengine - INFO - Epoch(train) [618][35/63] lr: 1.8448e-03 eta: 7:49:07 time: 0.5411 data_time: 0.0307 memory: 16131 loss: 1.3948 loss_prob: 0.7804 loss_thr: 0.4820 loss_db: 0.1324 2022/10/26 03:45:43 - mmengine - INFO - Epoch(train) [618][40/63] lr: 1.8448e-03 eta: 7:48:57 time: 0.5201 data_time: 0.0065 memory: 16131 loss: 1.5085 loss_prob: 0.8768 loss_thr: 0.4827 loss_db: 0.1491 2022/10/26 03:45:45 - mmengine - INFO - Epoch(train) [618][45/63] lr: 1.8448e-03 eta: 7:48:57 time: 0.5208 data_time: 0.0064 memory: 16131 loss: 1.4849 loss_prob: 0.8520 loss_thr: 0.4900 loss_db: 0.1428 2022/10/26 03:45:48 - mmengine - INFO - Epoch(train) [618][50/63] lr: 1.8448e-03 eta: 7:48:47 time: 0.5131 data_time: 0.0088 memory: 16131 loss: 1.3765 loss_prob: 0.7501 loss_thr: 0.5021 loss_db: 0.1242 2022/10/26 03:45:51 - mmengine - INFO - Epoch(train) [618][55/63] lr: 1.8448e-03 eta: 7:48:47 time: 0.5265 data_time: 0.0200 memory: 16131 loss: 1.4389 loss_prob: 0.7922 loss_thr: 0.5134 loss_db: 0.1332 2022/10/26 03:45:53 - mmengine - INFO - Epoch(train) [618][60/63] lr: 1.8448e-03 eta: 7:48:37 time: 0.5375 data_time: 0.0163 memory: 16131 loss: 1.4166 loss_prob: 0.7778 loss_thr: 0.5062 loss_db: 0.1326 2022/10/26 03:45:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:45:59 - mmengine - INFO - Epoch(train) [619][5/63] lr: 1.8420e-03 eta: 7:48:37 time: 0.6794 data_time: 0.1799 memory: 16131 loss: 1.3319 loss_prob: 0.7315 loss_thr: 0.4812 loss_db: 0.1192 2022/10/26 03:46:01 - mmengine - INFO - Epoch(train) [619][10/63] lr: 1.8420e-03 eta: 7:48:24 time: 0.7197 data_time: 0.1839 memory: 16131 loss: 1.4086 loss_prob: 0.7713 loss_thr: 0.5088 loss_db: 0.1286 2022/10/26 03:46:04 - mmengine - INFO - Epoch(train) [619][15/63] lr: 1.8420e-03 eta: 7:48:24 time: 0.5239 data_time: 0.0097 memory: 16131 loss: 1.4718 loss_prob: 0.8141 loss_thr: 0.5196 loss_db: 0.1381 2022/10/26 03:46:07 - mmengine - INFO - Epoch(train) [619][20/63] lr: 1.8420e-03 eta: 7:48:14 time: 0.5117 data_time: 0.0066 memory: 16131 loss: 1.4856 loss_prob: 0.8293 loss_thr: 0.5185 loss_db: 0.1378 2022/10/26 03:46:09 - mmengine - INFO - Epoch(train) [619][25/63] lr: 1.8420e-03 eta: 7:48:14 time: 0.5237 data_time: 0.0258 memory: 16131 loss: 1.3931 loss_prob: 0.7759 loss_thr: 0.4875 loss_db: 0.1297 2022/10/26 03:46:12 - mmengine - INFO - Epoch(train) [619][30/63] lr: 1.8420e-03 eta: 7:48:05 time: 0.5395 data_time: 0.0344 memory: 16131 loss: 1.3199 loss_prob: 0.7270 loss_thr: 0.4698 loss_db: 0.1232 2022/10/26 03:46:15 - mmengine - INFO - Epoch(train) [619][35/63] lr: 1.8420e-03 eta: 7:48:05 time: 0.5499 data_time: 0.0163 memory: 16131 loss: 1.3484 loss_prob: 0.7411 loss_thr: 0.4817 loss_db: 0.1256 2022/10/26 03:46:18 - mmengine - INFO - Epoch(train) [619][40/63] lr: 1.8420e-03 eta: 7:47:55 time: 0.5813 data_time: 0.0083 memory: 16131 loss: 1.2757 loss_prob: 0.7018 loss_thr: 0.4547 loss_db: 0.1192 2022/10/26 03:46:20 - mmengine - INFO - Epoch(train) [619][45/63] lr: 1.8420e-03 eta: 7:47:55 time: 0.5424 data_time: 0.0073 memory: 16131 loss: 1.2069 loss_prob: 0.6590 loss_thr: 0.4376 loss_db: 0.1103 2022/10/26 03:46:23 - mmengine - INFO - Epoch(train) [619][50/63] lr: 1.8420e-03 eta: 7:47:45 time: 0.5033 data_time: 0.0212 memory: 16131 loss: 1.2118 loss_prob: 0.6572 loss_thr: 0.4442 loss_db: 0.1104 2022/10/26 03:46:26 - mmengine - INFO - Epoch(train) [619][55/63] lr: 1.8420e-03 eta: 7:47:45 time: 0.5249 data_time: 0.0224 memory: 16131 loss: 1.2744 loss_prob: 0.6935 loss_thr: 0.4649 loss_db: 0.1159 2022/10/26 03:46:28 - mmengine - INFO - Epoch(train) [619][60/63] lr: 1.8420e-03 eta: 7:47:35 time: 0.5188 data_time: 0.0107 memory: 16131 loss: 1.3554 loss_prob: 0.7601 loss_thr: 0.4723 loss_db: 0.1230 2022/10/26 03:46:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:46:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:46:35 - mmengine - INFO - Epoch(train) [620][5/63] lr: 1.8391e-03 eta: 7:47:35 time: 0.7620 data_time: 0.1541 memory: 16131 loss: 1.2840 loss_prob: 0.7031 loss_thr: 0.4594 loss_db: 0.1215 2022/10/26 03:46:37 - mmengine - INFO - Epoch(train) [620][10/63] lr: 1.8391e-03 eta: 7:47:23 time: 0.7937 data_time: 0.1622 memory: 16131 loss: 1.4715 loss_prob: 0.8375 loss_thr: 0.4988 loss_db: 0.1352 2022/10/26 03:46:40 - mmengine - INFO - Epoch(train) [620][15/63] lr: 1.8391e-03 eta: 7:47:23 time: 0.5161 data_time: 0.0153 memory: 16131 loss: 1.4173 loss_prob: 0.8086 loss_thr: 0.4767 loss_db: 0.1321 2022/10/26 03:46:42 - mmengine - INFO - Epoch(train) [620][20/63] lr: 1.8391e-03 eta: 7:47:13 time: 0.5002 data_time: 0.0056 memory: 16131 loss: 1.2052 loss_prob: 0.6548 loss_thr: 0.4390 loss_db: 0.1114 2022/10/26 03:46:45 - mmengine - INFO - Epoch(train) [620][25/63] lr: 1.8391e-03 eta: 7:47:13 time: 0.5124 data_time: 0.0138 memory: 16131 loss: 1.2863 loss_prob: 0.7010 loss_thr: 0.4665 loss_db: 0.1188 2022/10/26 03:46:48 - mmengine - INFO - Epoch(train) [620][30/63] lr: 1.8391e-03 eta: 7:47:03 time: 0.5551 data_time: 0.0378 memory: 16131 loss: 1.3758 loss_prob: 0.7526 loss_thr: 0.4951 loss_db: 0.1282 2022/10/26 03:46:50 - mmengine - INFO - Epoch(train) [620][35/63] lr: 1.8391e-03 eta: 7:47:03 time: 0.5548 data_time: 0.0319 memory: 16131 loss: 1.2626 loss_prob: 0.6799 loss_thr: 0.4658 loss_db: 0.1170 2022/10/26 03:46:53 - mmengine - INFO - Epoch(train) [620][40/63] lr: 1.8391e-03 eta: 7:46:54 time: 0.5371 data_time: 0.0082 memory: 16131 loss: 1.2464 loss_prob: 0.6613 loss_thr: 0.4720 loss_db: 0.1131 2022/10/26 03:46:56 - mmengine - INFO - Epoch(train) [620][45/63] lr: 1.8391e-03 eta: 7:46:54 time: 0.5510 data_time: 0.0098 memory: 16131 loss: 1.3459 loss_prob: 0.7322 loss_thr: 0.4903 loss_db: 0.1234 2022/10/26 03:46:59 - mmengine - INFO - Epoch(train) [620][50/63] lr: 1.8391e-03 eta: 7:46:44 time: 0.5316 data_time: 0.0154 memory: 16131 loss: 1.3704 loss_prob: 0.7517 loss_thr: 0.4892 loss_db: 0.1295 2022/10/26 03:47:01 - mmengine - INFO - Epoch(train) [620][55/63] lr: 1.8391e-03 eta: 7:46:44 time: 0.5074 data_time: 0.0233 memory: 16131 loss: 1.3090 loss_prob: 0.7085 loss_thr: 0.4789 loss_db: 0.1216 2022/10/26 03:47:04 - mmengine - INFO - Epoch(train) [620][60/63] lr: 1.8391e-03 eta: 7:46:34 time: 0.5000 data_time: 0.0180 memory: 16131 loss: 1.2311 loss_prob: 0.6627 loss_thr: 0.4581 loss_db: 0.1102 2022/10/26 03:47:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:47:05 - mmengine - INFO - Saving checkpoint at 620 epochs 2022/10/26 03:47:12 - mmengine - INFO - Epoch(val) [620][5/32] eta: 7:46:34 time: 0.5459 data_time: 0.0828 memory: 16131 2022/10/26 03:47:14 - mmengine - INFO - Epoch(val) [620][10/32] eta: 0:00:13 time: 0.6080 data_time: 0.1084 memory: 15724 2022/10/26 03:47:17 - mmengine - INFO - Epoch(val) [620][15/32] eta: 0:00:13 time: 0.5470 data_time: 0.0447 memory: 15724 2022/10/26 03:47:20 - mmengine - INFO - Epoch(val) [620][20/32] eta: 0:00:06 time: 0.5419 data_time: 0.0449 memory: 15724 2022/10/26 03:47:23 - mmengine - INFO - Epoch(val) [620][25/32] eta: 0:00:06 time: 0.5614 data_time: 0.0453 memory: 15724 2022/10/26 03:47:25 - mmengine - INFO - Epoch(val) [620][30/32] eta: 0:00:01 time: 0.5439 data_time: 0.0226 memory: 15724 2022/10/26 03:47:26 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8272, precision: 0.7194, hmean: 0.7695 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8272, precision: 0.7791, hmean: 0.8024 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8247, precision: 0.8196, hmean: 0.8222 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8166, precision: 0.8514, hmean: 0.8336 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7857, precision: 0.8894, hmean: 0.8344 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6066, precision: 0.9368, hmean: 0.7364 2022/10/26 03:47:26 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0144, precision: 1.0000, hmean: 0.0285 2022/10/26 03:47:26 - mmengine - INFO - Epoch(val) [620][32/32] icdar/precision: 0.8894 icdar/recall: 0.7857 icdar/hmean: 0.8344 2022/10/26 03:47:30 - mmengine - INFO - Epoch(train) [621][5/63] lr: 1.8363e-03 eta: 0:00:01 time: 0.6645 data_time: 0.1797 memory: 16131 loss: 1.3291 loss_prob: 0.7345 loss_thr: 0.4676 loss_db: 0.1271 2022/10/26 03:47:33 - mmengine - INFO - Epoch(train) [621][10/63] lr: 1.8363e-03 eta: 7:46:21 time: 0.6961 data_time: 0.1855 memory: 16131 loss: 1.4225 loss_prob: 0.7984 loss_thr: 0.4888 loss_db: 0.1352 2022/10/26 03:47:36 - mmengine - INFO - Epoch(train) [621][15/63] lr: 1.8363e-03 eta: 7:46:21 time: 0.5129 data_time: 0.0102 memory: 16131 loss: 1.5642 loss_prob: 0.9306 loss_thr: 0.4908 loss_db: 0.1428 2022/10/26 03:47:38 - mmengine - INFO - Epoch(train) [621][20/63] lr: 1.8363e-03 eta: 7:46:11 time: 0.5100 data_time: 0.0070 memory: 16131 loss: 1.4369 loss_prob: 0.8342 loss_thr: 0.4716 loss_db: 0.1312 2022/10/26 03:47:41 - mmengine - INFO - Epoch(train) [621][25/63] lr: 1.8363e-03 eta: 7:46:11 time: 0.5104 data_time: 0.0297 memory: 16131 loss: 1.2569 loss_prob: 0.6889 loss_thr: 0.4493 loss_db: 0.1186 2022/10/26 03:47:43 - mmengine - INFO - Epoch(train) [621][30/63] lr: 1.8363e-03 eta: 7:46:01 time: 0.5154 data_time: 0.0329 memory: 16131 loss: 1.2725 loss_prob: 0.6928 loss_thr: 0.4614 loss_db: 0.1183 2022/10/26 03:47:46 - mmengine - INFO - Epoch(train) [621][35/63] lr: 1.8363e-03 eta: 7:46:01 time: 0.5007 data_time: 0.0107 memory: 16131 loss: 1.2105 loss_prob: 0.6364 loss_thr: 0.4641 loss_db: 0.1101 2022/10/26 03:47:48 - mmengine - INFO - Epoch(train) [621][40/63] lr: 1.8363e-03 eta: 7:45:51 time: 0.4877 data_time: 0.0055 memory: 16131 loss: 1.2200 loss_prob: 0.6503 loss_thr: 0.4578 loss_db: 0.1118 2022/10/26 03:47:51 - mmengine - INFO - Epoch(train) [621][45/63] lr: 1.8363e-03 eta: 7:45:51 time: 0.5219 data_time: 0.0067 memory: 16131 loss: 1.3356 loss_prob: 0.7291 loss_thr: 0.4818 loss_db: 0.1247 2022/10/26 03:47:53 - mmengine - INFO - Epoch(train) [621][50/63] lr: 1.8363e-03 eta: 7:45:41 time: 0.5391 data_time: 0.0196 memory: 16131 loss: 1.3270 loss_prob: 0.7203 loss_thr: 0.4832 loss_db: 0.1236 2022/10/26 03:47:56 - mmengine - INFO - Epoch(train) [621][55/63] lr: 1.8363e-03 eta: 7:45:41 time: 0.5267 data_time: 0.0334 memory: 16131 loss: 1.4626 loss_prob: 0.8352 loss_thr: 0.4911 loss_db: 0.1363 2022/10/26 03:47:59 - mmengine - INFO - Epoch(train) [621][60/63] lr: 1.8363e-03 eta: 7:45:31 time: 0.5160 data_time: 0.0244 memory: 16131 loss: 1.5913 loss_prob: 0.9229 loss_thr: 0.5194 loss_db: 0.1490 2022/10/26 03:48:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:48:05 - mmengine - INFO - Epoch(train) [622][5/63] lr: 1.8334e-03 eta: 7:45:31 time: 0.7380 data_time: 0.2134 memory: 16131 loss: 1.4344 loss_prob: 0.8081 loss_thr: 0.4826 loss_db: 0.1437 2022/10/26 03:48:08 - mmengine - INFO - Epoch(train) [622][10/63] lr: 1.8334e-03 eta: 7:45:19 time: 0.8037 data_time: 0.2140 memory: 16131 loss: 1.3400 loss_prob: 0.7399 loss_thr: 0.4780 loss_db: 0.1221 2022/10/26 03:48:11 - mmengine - INFO - Epoch(train) [622][15/63] lr: 1.8334e-03 eta: 7:45:19 time: 0.5799 data_time: 0.0182 memory: 16131 loss: 1.4513 loss_prob: 0.7973 loss_thr: 0.5211 loss_db: 0.1329 2022/10/26 03:48:14 - mmengine - INFO - Epoch(train) [622][20/63] lr: 1.8334e-03 eta: 7:45:09 time: 0.5472 data_time: 0.0121 memory: 16131 loss: 1.4251 loss_prob: 0.7786 loss_thr: 0.5125 loss_db: 0.1339 2022/10/26 03:48:16 - mmengine - INFO - Epoch(train) [622][25/63] lr: 1.8334e-03 eta: 7:45:09 time: 0.5403 data_time: 0.0181 memory: 16131 loss: 1.4407 loss_prob: 0.8023 loss_thr: 0.5048 loss_db: 0.1335 2022/10/26 03:48:19 - mmengine - INFO - Epoch(train) [622][30/63] lr: 1.8334e-03 eta: 7:45:00 time: 0.5487 data_time: 0.0322 memory: 16131 loss: 1.3945 loss_prob: 0.7737 loss_thr: 0.4916 loss_db: 0.1292 2022/10/26 03:48:22 - mmengine - INFO - Epoch(train) [622][35/63] lr: 1.8334e-03 eta: 7:45:00 time: 0.5385 data_time: 0.0209 memory: 16131 loss: 1.2832 loss_prob: 0.7016 loss_thr: 0.4616 loss_db: 0.1200 2022/10/26 03:48:24 - mmengine - INFO - Epoch(train) [622][40/63] lr: 1.8334e-03 eta: 7:44:50 time: 0.5085 data_time: 0.0076 memory: 16131 loss: 1.3136 loss_prob: 0.7261 loss_thr: 0.4671 loss_db: 0.1204 2022/10/26 03:48:27 - mmengine - INFO - Epoch(train) [622][45/63] lr: 1.8334e-03 eta: 7:44:50 time: 0.5121 data_time: 0.0110 memory: 16131 loss: 1.4770 loss_prob: 0.8586 loss_thr: 0.4836 loss_db: 0.1348 2022/10/26 03:48:29 - mmengine - INFO - Epoch(train) [622][50/63] lr: 1.8334e-03 eta: 7:44:40 time: 0.5049 data_time: 0.0232 memory: 16131 loss: 1.5390 loss_prob: 0.9047 loss_thr: 0.4903 loss_db: 0.1440 2022/10/26 03:48:32 - mmengine - INFO - Epoch(train) [622][55/63] lr: 1.8334e-03 eta: 7:44:40 time: 0.5132 data_time: 0.0235 memory: 16131 loss: 1.5399 loss_prob: 0.8929 loss_thr: 0.4980 loss_db: 0.1490 2022/10/26 03:48:35 - mmengine - INFO - Epoch(train) [622][60/63] lr: 1.8334e-03 eta: 7:44:30 time: 0.5377 data_time: 0.0129 memory: 16131 loss: 1.5625 loss_prob: 0.8978 loss_thr: 0.5145 loss_db: 0.1503 2022/10/26 03:48:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:48:41 - mmengine - INFO - Epoch(train) [623][5/63] lr: 1.8305e-03 eta: 7:44:30 time: 0.7669 data_time: 0.1941 memory: 16131 loss: 1.6519 loss_prob: 0.9930 loss_thr: 0.5046 loss_db: 0.1543 2022/10/26 03:48:44 - mmengine - INFO - Epoch(train) [623][10/63] lr: 1.8305e-03 eta: 7:44:18 time: 0.8170 data_time: 0.1938 memory: 16131 loss: 1.5824 loss_prob: 0.9452 loss_thr: 0.4888 loss_db: 0.1484 2022/10/26 03:48:47 - mmengine - INFO - Epoch(train) [623][15/63] lr: 1.8305e-03 eta: 7:44:18 time: 0.5725 data_time: 0.0130 memory: 16131 loss: 1.4039 loss_prob: 0.7764 loss_thr: 0.4958 loss_db: 0.1317 2022/10/26 03:48:49 - mmengine - INFO - Epoch(train) [623][20/63] lr: 1.8305e-03 eta: 7:44:08 time: 0.5002 data_time: 0.0117 memory: 16131 loss: 1.4175 loss_prob: 0.7897 loss_thr: 0.4976 loss_db: 0.1301 2022/10/26 03:48:52 - mmengine - INFO - Epoch(train) [623][25/63] lr: 1.8305e-03 eta: 7:44:08 time: 0.4855 data_time: 0.0122 memory: 16131 loss: 1.2941 loss_prob: 0.7086 loss_thr: 0.4680 loss_db: 0.1175 2022/10/26 03:48:55 - mmengine - INFO - Epoch(train) [623][30/63] lr: 1.8305e-03 eta: 7:43:58 time: 0.5504 data_time: 0.0271 memory: 16131 loss: 1.2688 loss_prob: 0.6898 loss_thr: 0.4620 loss_db: 0.1170 2022/10/26 03:48:57 - mmengine - INFO - Epoch(train) [623][35/63] lr: 1.8305e-03 eta: 7:43:58 time: 0.5438 data_time: 0.0263 memory: 16131 loss: 1.2705 loss_prob: 0.6882 loss_thr: 0.4649 loss_db: 0.1174 2022/10/26 03:49:00 - mmengine - INFO - Epoch(train) [623][40/63] lr: 1.8305e-03 eta: 7:43:48 time: 0.4971 data_time: 0.0147 memory: 16131 loss: 1.3436 loss_prob: 0.7312 loss_thr: 0.4897 loss_db: 0.1226 2022/10/26 03:49:02 - mmengine - INFO - Epoch(train) [623][45/63] lr: 1.8305e-03 eta: 7:43:48 time: 0.5127 data_time: 0.0131 memory: 16131 loss: 1.4779 loss_prob: 0.8239 loss_thr: 0.5144 loss_db: 0.1395 2022/10/26 03:49:05 - mmengine - INFO - Epoch(train) [623][50/63] lr: 1.8305e-03 eta: 7:43:38 time: 0.5186 data_time: 0.0096 memory: 16131 loss: 1.4165 loss_prob: 0.7927 loss_thr: 0.4893 loss_db: 0.1345 2022/10/26 03:49:08 - mmengine - INFO - Epoch(train) [623][55/63] lr: 1.8305e-03 eta: 7:43:38 time: 0.5191 data_time: 0.0217 memory: 16131 loss: 1.3050 loss_prob: 0.7195 loss_thr: 0.4656 loss_db: 0.1199 2022/10/26 03:49:10 - mmengine - INFO - Epoch(train) [623][60/63] lr: 1.8305e-03 eta: 7:43:28 time: 0.5180 data_time: 0.0202 memory: 16131 loss: 1.2574 loss_prob: 0.6809 loss_thr: 0.4624 loss_db: 0.1141 2022/10/26 03:49:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:49:16 - mmengine - INFO - Epoch(train) [624][5/63] lr: 1.8277e-03 eta: 7:43:28 time: 0.7225 data_time: 0.1803 memory: 16131 loss: 1.2527 loss_prob: 0.6771 loss_thr: 0.4617 loss_db: 0.1138 2022/10/26 03:49:19 - mmengine - INFO - Epoch(train) [624][10/63] lr: 1.8277e-03 eta: 7:43:16 time: 0.7618 data_time: 0.1809 memory: 16131 loss: 1.3166 loss_prob: 0.7267 loss_thr: 0.4709 loss_db: 0.1190 2022/10/26 03:49:22 - mmengine - INFO - Epoch(train) [624][15/63] lr: 1.8277e-03 eta: 7:43:16 time: 0.5312 data_time: 0.0101 memory: 16131 loss: 1.4533 loss_prob: 0.8300 loss_thr: 0.4859 loss_db: 0.1373 2022/10/26 03:49:24 - mmengine - INFO - Epoch(train) [624][20/63] lr: 1.8277e-03 eta: 7:43:06 time: 0.5246 data_time: 0.0101 memory: 16131 loss: 1.3935 loss_prob: 0.7748 loss_thr: 0.4844 loss_db: 0.1342 2022/10/26 03:49:27 - mmengine - INFO - Epoch(train) [624][25/63] lr: 1.8277e-03 eta: 7:43:06 time: 0.5832 data_time: 0.0260 memory: 16131 loss: 1.3468 loss_prob: 0.7373 loss_thr: 0.4809 loss_db: 0.1287 2022/10/26 03:49:30 - mmengine - INFO - Epoch(train) [624][30/63] lr: 1.8277e-03 eta: 7:42:57 time: 0.5789 data_time: 0.0327 memory: 16131 loss: 1.4311 loss_prob: 0.7985 loss_thr: 0.4960 loss_db: 0.1366 2022/10/26 03:49:33 - mmengine - INFO - Epoch(train) [624][35/63] lr: 1.8277e-03 eta: 7:42:57 time: 0.5169 data_time: 0.0147 memory: 16131 loss: 1.3899 loss_prob: 0.7664 loss_thr: 0.4914 loss_db: 0.1321 2022/10/26 03:49:35 - mmengine - INFO - Epoch(train) [624][40/63] lr: 1.8277e-03 eta: 7:42:47 time: 0.5306 data_time: 0.0111 memory: 16131 loss: 1.3946 loss_prob: 0.7662 loss_thr: 0.4964 loss_db: 0.1319 2022/10/26 03:49:38 - mmengine - INFO - Epoch(train) [624][45/63] lr: 1.8277e-03 eta: 7:42:47 time: 0.5459 data_time: 0.0093 memory: 16131 loss: 1.4315 loss_prob: 0.7889 loss_thr: 0.5082 loss_db: 0.1344 2022/10/26 03:49:41 - mmengine - INFO - Epoch(train) [624][50/63] lr: 1.8277e-03 eta: 7:42:37 time: 0.5302 data_time: 0.0173 memory: 16131 loss: 1.4864 loss_prob: 0.8398 loss_thr: 0.5032 loss_db: 0.1435 2022/10/26 03:49:43 - mmengine - INFO - Epoch(train) [624][55/63] lr: 1.8277e-03 eta: 7:42:37 time: 0.5222 data_time: 0.0219 memory: 16131 loss: 1.4915 loss_prob: 0.8465 loss_thr: 0.5012 loss_db: 0.1438 2022/10/26 03:49:46 - mmengine - INFO - Epoch(train) [624][60/63] lr: 1.8277e-03 eta: 7:42:27 time: 0.5053 data_time: 0.0093 memory: 16131 loss: 1.3730 loss_prob: 0.7657 loss_thr: 0.4760 loss_db: 0.1313 2022/10/26 03:49:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:49:52 - mmengine - INFO - Epoch(train) [625][5/63] lr: 1.8248e-03 eta: 7:42:27 time: 0.7030 data_time: 0.1848 memory: 16131 loss: 1.5159 loss_prob: 0.8779 loss_thr: 0.4962 loss_db: 0.1418 2022/10/26 03:49:56 - mmengine - INFO - Epoch(train) [625][10/63] lr: 1.8248e-03 eta: 7:42:16 time: 0.8656 data_time: 0.1839 memory: 16131 loss: 1.4489 loss_prob: 0.8266 loss_thr: 0.4827 loss_db: 0.1396 2022/10/26 03:49:58 - mmengine - INFO - Epoch(train) [625][15/63] lr: 1.8248e-03 eta: 7:42:16 time: 0.6381 data_time: 0.0127 memory: 16131 loss: 1.4269 loss_prob: 0.7989 loss_thr: 0.4911 loss_db: 0.1369 2022/10/26 03:50:01 - mmengine - INFO - Epoch(train) [625][20/63] lr: 1.8248e-03 eta: 7:42:06 time: 0.4971 data_time: 0.0127 memory: 16131 loss: 1.4783 loss_prob: 0.8290 loss_thr: 0.5104 loss_db: 0.1389 2022/10/26 03:50:04 - mmengine - INFO - Epoch(train) [625][25/63] lr: 1.8248e-03 eta: 7:42:06 time: 0.5255 data_time: 0.0213 memory: 16131 loss: 1.4642 loss_prob: 0.8233 loss_thr: 0.5040 loss_db: 0.1369 2022/10/26 03:50:06 - mmengine - INFO - Epoch(train) [625][30/63] lr: 1.8248e-03 eta: 7:41:57 time: 0.5680 data_time: 0.0257 memory: 16131 loss: 1.4090 loss_prob: 0.7908 loss_thr: 0.4857 loss_db: 0.1324 2022/10/26 03:50:09 - mmengine - INFO - Epoch(train) [625][35/63] lr: 1.8248e-03 eta: 7:41:57 time: 0.5405 data_time: 0.0105 memory: 16131 loss: 1.3910 loss_prob: 0.7758 loss_thr: 0.4827 loss_db: 0.1325 2022/10/26 03:50:11 - mmengine - INFO - Epoch(train) [625][40/63] lr: 1.8248e-03 eta: 7:41:47 time: 0.5090 data_time: 0.0114 memory: 16131 loss: 1.3491 loss_prob: 0.7498 loss_thr: 0.4726 loss_db: 0.1267 2022/10/26 03:50:14 - mmengine - INFO - Epoch(train) [625][45/63] lr: 1.8248e-03 eta: 7:41:47 time: 0.5002 data_time: 0.0112 memory: 16131 loss: 1.3766 loss_prob: 0.7651 loss_thr: 0.4819 loss_db: 0.1295 2022/10/26 03:50:16 - mmengine - INFO - Epoch(train) [625][50/63] lr: 1.8248e-03 eta: 7:41:37 time: 0.4994 data_time: 0.0138 memory: 16131 loss: 1.3613 loss_prob: 0.7476 loss_thr: 0.4849 loss_db: 0.1288 2022/10/26 03:50:19 - mmengine - INFO - Epoch(train) [625][55/63] lr: 1.8248e-03 eta: 7:41:37 time: 0.5111 data_time: 0.0191 memory: 16131 loss: 1.2415 loss_prob: 0.6690 loss_thr: 0.4570 loss_db: 0.1155 2022/10/26 03:50:22 - mmengine - INFO - Epoch(train) [625][60/63] lr: 1.8248e-03 eta: 7:41:27 time: 0.5199 data_time: 0.0108 memory: 16131 loss: 1.3665 loss_prob: 0.7393 loss_thr: 0.5005 loss_db: 0.1267 2022/10/26 03:50:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:50:27 - mmengine - INFO - Epoch(train) [626][5/63] lr: 1.8220e-03 eta: 7:41:27 time: 0.6585 data_time: 0.1520 memory: 16131 loss: 1.2934 loss_prob: 0.7147 loss_thr: 0.4576 loss_db: 0.1211 2022/10/26 03:50:30 - mmengine - INFO - Epoch(train) [626][10/63] lr: 1.8220e-03 eta: 7:41:14 time: 0.6926 data_time: 0.1576 memory: 16131 loss: 1.3241 loss_prob: 0.7277 loss_thr: 0.4792 loss_db: 0.1172 2022/10/26 03:50:33 - mmengine - INFO - Epoch(train) [626][15/63] lr: 1.8220e-03 eta: 7:41:14 time: 0.5935 data_time: 0.0160 memory: 16131 loss: 1.3950 loss_prob: 0.7701 loss_thr: 0.4968 loss_db: 0.1281 2022/10/26 03:50:36 - mmengine - INFO - Epoch(train) [626][20/63] lr: 1.8220e-03 eta: 7:41:05 time: 0.6258 data_time: 0.0113 memory: 16131 loss: 1.3779 loss_prob: 0.7620 loss_thr: 0.4841 loss_db: 0.1318 2022/10/26 03:50:39 - mmengine - INFO - Epoch(train) [626][25/63] lr: 1.8220e-03 eta: 7:41:05 time: 0.5502 data_time: 0.0138 memory: 16131 loss: 1.3072 loss_prob: 0.7198 loss_thr: 0.4656 loss_db: 0.1218 2022/10/26 03:50:41 - mmengine - INFO - Epoch(train) [626][30/63] lr: 1.8220e-03 eta: 7:40:55 time: 0.5292 data_time: 0.0246 memory: 16131 loss: 1.2924 loss_prob: 0.7148 loss_thr: 0.4587 loss_db: 0.1189 2022/10/26 03:50:44 - mmengine - INFO - Epoch(train) [626][35/63] lr: 1.8220e-03 eta: 7:40:55 time: 0.5164 data_time: 0.0279 memory: 16131 loss: 1.4269 loss_prob: 0.8001 loss_thr: 0.4900 loss_db: 0.1368 2022/10/26 03:50:47 - mmengine - INFO - Epoch(train) [626][40/63] lr: 1.8220e-03 eta: 7:40:45 time: 0.5137 data_time: 0.0142 memory: 16131 loss: 1.4749 loss_prob: 0.8251 loss_thr: 0.5089 loss_db: 0.1409 2022/10/26 03:50:49 - mmengine - INFO - Epoch(train) [626][45/63] lr: 1.8220e-03 eta: 7:40:45 time: 0.5004 data_time: 0.0085 memory: 16131 loss: 1.4384 loss_prob: 0.8082 loss_thr: 0.4934 loss_db: 0.1368 2022/10/26 03:50:52 - mmengine - INFO - Epoch(train) [626][50/63] lr: 1.8220e-03 eta: 7:40:35 time: 0.4926 data_time: 0.0133 memory: 16131 loss: 1.3931 loss_prob: 0.7802 loss_thr: 0.4796 loss_db: 0.1332 2022/10/26 03:50:54 - mmengine - INFO - Epoch(train) [626][55/63] lr: 1.8220e-03 eta: 7:40:35 time: 0.5458 data_time: 0.0187 memory: 16131 loss: 1.3365 loss_prob: 0.7313 loss_thr: 0.4799 loss_db: 0.1254 2022/10/26 03:50:57 - mmengine - INFO - Epoch(train) [626][60/63] lr: 1.8220e-03 eta: 7:40:26 time: 0.5326 data_time: 0.0167 memory: 16131 loss: 1.3288 loss_prob: 0.7261 loss_thr: 0.4793 loss_db: 0.1234 2022/10/26 03:50:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:51:03 - mmengine - INFO - Epoch(train) [627][5/63] lr: 1.8191e-03 eta: 7:40:26 time: 0.6748 data_time: 0.2042 memory: 16131 loss: 1.2711 loss_prob: 0.6810 loss_thr: 0.4740 loss_db: 0.1161 2022/10/26 03:51:05 - mmengine - INFO - Epoch(train) [627][10/63] lr: 1.8191e-03 eta: 7:40:13 time: 0.7118 data_time: 0.2057 memory: 16131 loss: 1.3153 loss_prob: 0.7095 loss_thr: 0.4841 loss_db: 0.1217 2022/10/26 03:51:08 - mmengine - INFO - Epoch(train) [627][15/63] lr: 1.8191e-03 eta: 7:40:13 time: 0.5640 data_time: 0.0103 memory: 16131 loss: 1.3680 loss_prob: 0.7497 loss_thr: 0.4910 loss_db: 0.1272 2022/10/26 03:51:11 - mmengine - INFO - Epoch(train) [627][20/63] lr: 1.8191e-03 eta: 7:40:04 time: 0.5966 data_time: 0.0099 memory: 16131 loss: 1.3779 loss_prob: 0.7496 loss_thr: 0.5022 loss_db: 0.1261 2022/10/26 03:51:15 - mmengine - INFO - Epoch(train) [627][25/63] lr: 1.8191e-03 eta: 7:40:04 time: 0.6396 data_time: 0.0471 memory: 16131 loss: 1.3328 loss_prob: 0.7238 loss_thr: 0.4880 loss_db: 0.1210 2022/10/26 03:51:17 - mmengine - INFO - Epoch(train) [627][30/63] lr: 1.8191e-03 eta: 7:39:55 time: 0.6030 data_time: 0.0448 memory: 16131 loss: 1.4374 loss_prob: 0.7995 loss_thr: 0.5031 loss_db: 0.1349 2022/10/26 03:51:20 - mmengine - INFO - Epoch(train) [627][35/63] lr: 1.8191e-03 eta: 7:39:55 time: 0.4944 data_time: 0.0042 memory: 16131 loss: 1.4804 loss_prob: 0.8196 loss_thr: 0.5183 loss_db: 0.1425 2022/10/26 03:51:22 - mmengine - INFO - Epoch(train) [627][40/63] lr: 1.8191e-03 eta: 7:39:44 time: 0.4801 data_time: 0.0046 memory: 16131 loss: 1.3998 loss_prob: 0.7666 loss_thr: 0.5009 loss_db: 0.1323 2022/10/26 03:51:25 - mmengine - INFO - Epoch(train) [627][45/63] lr: 1.8191e-03 eta: 7:39:44 time: 0.4903 data_time: 0.0045 memory: 16131 loss: 1.3799 loss_prob: 0.7592 loss_thr: 0.4918 loss_db: 0.1290 2022/10/26 03:51:27 - mmengine - INFO - Epoch(train) [627][50/63] lr: 1.8191e-03 eta: 7:39:35 time: 0.5212 data_time: 0.0223 memory: 16131 loss: 1.2330 loss_prob: 0.6651 loss_thr: 0.4539 loss_db: 0.1140 2022/10/26 03:51:30 - mmengine - INFO - Epoch(train) [627][55/63] lr: 1.8191e-03 eta: 7:39:35 time: 0.5220 data_time: 0.0223 memory: 16131 loss: 1.1997 loss_prob: 0.6394 loss_thr: 0.4526 loss_db: 0.1077 2022/10/26 03:51:32 - mmengine - INFO - Epoch(train) [627][60/63] lr: 1.8191e-03 eta: 7:39:25 time: 0.5030 data_time: 0.0050 memory: 16131 loss: 1.8743 loss_prob: 1.1796 loss_thr: 0.5253 loss_db: 0.1694 2022/10/26 03:51:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:51:39 - mmengine - INFO - Epoch(train) [628][5/63] lr: 1.8163e-03 eta: 7:39:25 time: 0.8099 data_time: 0.2124 memory: 16131 loss: 1.3674 loss_prob: 0.7483 loss_thr: 0.4875 loss_db: 0.1316 2022/10/26 03:51:42 - mmengine - INFO - Epoch(train) [628][10/63] lr: 1.8163e-03 eta: 7:39:13 time: 0.8425 data_time: 0.2125 memory: 16131 loss: 1.2945 loss_prob: 0.6998 loss_thr: 0.4735 loss_db: 0.1213 2022/10/26 03:51:44 - mmengine - INFO - Epoch(train) [628][15/63] lr: 1.8163e-03 eta: 7:39:13 time: 0.5022 data_time: 0.0139 memory: 16131 loss: 1.3407 loss_prob: 0.7365 loss_thr: 0.4812 loss_db: 0.1230 2022/10/26 03:51:47 - mmengine - INFO - Epoch(train) [628][20/63] lr: 1.8163e-03 eta: 7:39:04 time: 0.5335 data_time: 0.0083 memory: 16131 loss: 1.4700 loss_prob: 0.8071 loss_thr: 0.5290 loss_db: 0.1338 2022/10/26 03:51:50 - mmengine - INFO - Epoch(train) [628][25/63] lr: 1.8163e-03 eta: 7:39:04 time: 0.5538 data_time: 0.0253 memory: 16131 loss: 1.4192 loss_prob: 0.7722 loss_thr: 0.5171 loss_db: 0.1299 2022/10/26 03:51:52 - mmengine - INFO - Epoch(train) [628][30/63] lr: 1.8163e-03 eta: 7:38:54 time: 0.5174 data_time: 0.0304 memory: 16131 loss: 1.3437 loss_prob: 0.7290 loss_thr: 0.4893 loss_db: 0.1253 2022/10/26 03:51:55 - mmengine - INFO - Epoch(train) [628][35/63] lr: 1.8163e-03 eta: 7:38:54 time: 0.4993 data_time: 0.0166 memory: 16131 loss: 1.3718 loss_prob: 0.7556 loss_thr: 0.4906 loss_db: 0.1255 2022/10/26 03:51:58 - mmengine - INFO - Epoch(train) [628][40/63] lr: 1.8163e-03 eta: 7:38:44 time: 0.5310 data_time: 0.0116 memory: 16131 loss: 1.3349 loss_prob: 0.7257 loss_thr: 0.4890 loss_db: 0.1202 2022/10/26 03:52:00 - mmengine - INFO - Epoch(train) [628][45/63] lr: 1.8163e-03 eta: 7:38:44 time: 0.5394 data_time: 0.0064 memory: 16131 loss: 1.2698 loss_prob: 0.6710 loss_thr: 0.4852 loss_db: 0.1137 2022/10/26 03:52:03 - mmengine - INFO - Epoch(train) [628][50/63] lr: 1.8163e-03 eta: 7:38:34 time: 0.5213 data_time: 0.0137 memory: 16131 loss: 1.2697 loss_prob: 0.6762 loss_thr: 0.4791 loss_db: 0.1144 2022/10/26 03:52:05 - mmengine - INFO - Epoch(train) [628][55/63] lr: 1.8163e-03 eta: 7:38:34 time: 0.5096 data_time: 0.0211 memory: 16131 loss: 1.2704 loss_prob: 0.6857 loss_thr: 0.4703 loss_db: 0.1143 2022/10/26 03:52:08 - mmengine - INFO - Epoch(train) [628][60/63] lr: 1.8163e-03 eta: 7:38:24 time: 0.4873 data_time: 0.0165 memory: 16131 loss: 1.2656 loss_prob: 0.6906 loss_thr: 0.4600 loss_db: 0.1151 2022/10/26 03:52:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:52:14 - mmengine - INFO - Epoch(train) [629][5/63] lr: 1.8134e-03 eta: 7:38:24 time: 0.7071 data_time: 0.1825 memory: 16131 loss: 1.2018 loss_prob: 0.6443 loss_thr: 0.4465 loss_db: 0.1109 2022/10/26 03:52:16 - mmengine - INFO - Epoch(train) [629][10/63] lr: 1.8134e-03 eta: 7:38:12 time: 0.7171 data_time: 0.1897 memory: 16131 loss: 1.2157 loss_prob: 0.6531 loss_thr: 0.4516 loss_db: 0.1109 2022/10/26 03:52:19 - mmengine - INFO - Epoch(train) [629][15/63] lr: 1.8134e-03 eta: 7:38:12 time: 0.4996 data_time: 0.0171 memory: 16131 loss: 1.2268 loss_prob: 0.6582 loss_thr: 0.4542 loss_db: 0.1145 2022/10/26 03:52:21 - mmengine - INFO - Epoch(train) [629][20/63] lr: 1.8134e-03 eta: 7:38:01 time: 0.4975 data_time: 0.0093 memory: 16131 loss: 1.3046 loss_prob: 0.7084 loss_thr: 0.4722 loss_db: 0.1241 2022/10/26 03:52:24 - mmengine - INFO - Epoch(train) [629][25/63] lr: 1.8134e-03 eta: 7:38:01 time: 0.5279 data_time: 0.0250 memory: 16131 loss: 1.2709 loss_prob: 0.6806 loss_thr: 0.4756 loss_db: 0.1147 2022/10/26 03:52:27 - mmengine - INFO - Epoch(train) [629][30/63] lr: 1.8134e-03 eta: 7:37:52 time: 0.5204 data_time: 0.0221 memory: 16131 loss: 1.2457 loss_prob: 0.6649 loss_thr: 0.4709 loss_db: 0.1099 2022/10/26 03:52:29 - mmengine - INFO - Epoch(train) [629][35/63] lr: 1.8134e-03 eta: 7:37:52 time: 0.5190 data_time: 0.0175 memory: 16131 loss: 1.3194 loss_prob: 0.7181 loss_thr: 0.4823 loss_db: 0.1190 2022/10/26 03:52:32 - mmengine - INFO - Epoch(train) [629][40/63] lr: 1.8134e-03 eta: 7:37:42 time: 0.5758 data_time: 0.0203 memory: 16131 loss: 1.2742 loss_prob: 0.6909 loss_thr: 0.4658 loss_db: 0.1176 2022/10/26 03:52:35 - mmengine - INFO - Epoch(train) [629][45/63] lr: 1.8134e-03 eta: 7:37:42 time: 0.5533 data_time: 0.0085 memory: 16131 loss: 1.3122 loss_prob: 0.7185 loss_thr: 0.4723 loss_db: 0.1214 2022/10/26 03:52:38 - mmengine - INFO - Epoch(train) [629][50/63] lr: 1.8134e-03 eta: 7:37:32 time: 0.5131 data_time: 0.0171 memory: 16131 loss: 1.3900 loss_prob: 0.7852 loss_thr: 0.4761 loss_db: 0.1287 2022/10/26 03:52:40 - mmengine - INFO - Epoch(train) [629][55/63] lr: 1.8134e-03 eta: 7:37:32 time: 0.5246 data_time: 0.0283 memory: 16131 loss: 1.3437 loss_prob: 0.7585 loss_thr: 0.4605 loss_db: 0.1247 2022/10/26 03:52:43 - mmengine - INFO - Epoch(train) [629][60/63] lr: 1.8134e-03 eta: 7:37:22 time: 0.5054 data_time: 0.0180 memory: 16131 loss: 1.3218 loss_prob: 0.7227 loss_thr: 0.4775 loss_db: 0.1216 2022/10/26 03:52:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:52:49 - mmengine - INFO - Epoch(train) [630][5/63] lr: 1.8105e-03 eta: 7:37:22 time: 0.7241 data_time: 0.2010 memory: 16131 loss: 1.3189 loss_prob: 0.7264 loss_thr: 0.4680 loss_db: 0.1245 2022/10/26 03:52:51 - mmengine - INFO - Epoch(train) [630][10/63] lr: 1.8105e-03 eta: 7:37:11 time: 0.7708 data_time: 0.1983 memory: 16131 loss: 1.2679 loss_prob: 0.6892 loss_thr: 0.4616 loss_db: 0.1172 2022/10/26 03:52:54 - mmengine - INFO - Epoch(train) [630][15/63] lr: 1.8105e-03 eta: 7:37:11 time: 0.5177 data_time: 0.0073 memory: 16131 loss: 1.3388 loss_prob: 0.7365 loss_thr: 0.4783 loss_db: 0.1240 2022/10/26 03:52:57 - mmengine - INFO - Epoch(train) [630][20/63] lr: 1.8105e-03 eta: 7:37:01 time: 0.5068 data_time: 0.0083 memory: 16131 loss: 1.4241 loss_prob: 0.8027 loss_thr: 0.4877 loss_db: 0.1337 2022/10/26 03:52:59 - mmengine - INFO - Epoch(train) [630][25/63] lr: 1.8105e-03 eta: 7:37:01 time: 0.5206 data_time: 0.0284 memory: 16131 loss: 1.3877 loss_prob: 0.7782 loss_thr: 0.4806 loss_db: 0.1289 2022/10/26 03:53:02 - mmengine - INFO - Epoch(train) [630][30/63] lr: 1.8105e-03 eta: 7:36:51 time: 0.5379 data_time: 0.0398 memory: 16131 loss: 1.3354 loss_prob: 0.7312 loss_thr: 0.4815 loss_db: 0.1226 2022/10/26 03:53:05 - mmengine - INFO - Epoch(train) [630][35/63] lr: 1.8105e-03 eta: 7:36:51 time: 0.5636 data_time: 0.0194 memory: 16131 loss: 1.3646 loss_prob: 0.7415 loss_thr: 0.4969 loss_db: 0.1262 2022/10/26 03:53:08 - mmengine - INFO - Epoch(train) [630][40/63] lr: 1.8105e-03 eta: 7:36:42 time: 0.5753 data_time: 0.0059 memory: 16131 loss: 1.3194 loss_prob: 0.7310 loss_thr: 0.4686 loss_db: 0.1198 2022/10/26 03:53:10 - mmengine - INFO - Epoch(train) [630][45/63] lr: 1.8105e-03 eta: 7:36:42 time: 0.5314 data_time: 0.0069 memory: 16131 loss: 1.3472 loss_prob: 0.7678 loss_thr: 0.4581 loss_db: 0.1213 2022/10/26 03:53:13 - mmengine - INFO - Epoch(train) [630][50/63] lr: 1.8105e-03 eta: 7:36:32 time: 0.5047 data_time: 0.0218 memory: 16131 loss: 1.3757 loss_prob: 0.7688 loss_thr: 0.4797 loss_db: 0.1273 2022/10/26 03:53:16 - mmengine - INFO - Epoch(train) [630][55/63] lr: 1.8105e-03 eta: 7:36:32 time: 0.5371 data_time: 0.0245 memory: 16131 loss: 1.2771 loss_prob: 0.6947 loss_thr: 0.4610 loss_db: 0.1214 2022/10/26 03:53:18 - mmengine - INFO - Epoch(train) [630][60/63] lr: 1.8105e-03 eta: 7:36:22 time: 0.5360 data_time: 0.0112 memory: 16131 loss: 1.2194 loss_prob: 0.6589 loss_thr: 0.4473 loss_db: 0.1132 2022/10/26 03:53:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:53:24 - mmengine - INFO - Epoch(train) [631][5/63] lr: 1.8077e-03 eta: 7:36:22 time: 0.6624 data_time: 0.1878 memory: 16131 loss: 1.2164 loss_prob: 0.6594 loss_thr: 0.4477 loss_db: 0.1093 2022/10/26 03:53:26 - mmengine - INFO - Epoch(train) [631][10/63] lr: 1.8077e-03 eta: 7:36:09 time: 0.6922 data_time: 0.1895 memory: 16131 loss: 1.2782 loss_prob: 0.6996 loss_thr: 0.4614 loss_db: 0.1172 2022/10/26 03:53:29 - mmengine - INFO - Epoch(train) [631][15/63] lr: 1.8077e-03 eta: 7:36:09 time: 0.5076 data_time: 0.0086 memory: 16131 loss: 1.2327 loss_prob: 0.6515 loss_thr: 0.4718 loss_db: 0.1094 2022/10/26 03:53:31 - mmengine - INFO - Epoch(train) [631][20/63] lr: 1.8077e-03 eta: 7:35:59 time: 0.5123 data_time: 0.0048 memory: 16131 loss: 1.2785 loss_prob: 0.6795 loss_thr: 0.4842 loss_db: 0.1148 2022/10/26 03:53:34 - mmengine - INFO - Epoch(train) [631][25/63] lr: 1.8077e-03 eta: 7:35:59 time: 0.5315 data_time: 0.0324 memory: 16131 loss: 1.3041 loss_prob: 0.7009 loss_thr: 0.4823 loss_db: 0.1210 2022/10/26 03:53:37 - mmengine - INFO - Epoch(train) [631][30/63] lr: 1.8077e-03 eta: 7:35:50 time: 0.5281 data_time: 0.0402 memory: 16131 loss: 1.2517 loss_prob: 0.6602 loss_thr: 0.4783 loss_db: 0.1131 2022/10/26 03:53:39 - mmengine - INFO - Epoch(train) [631][35/63] lr: 1.8077e-03 eta: 7:35:50 time: 0.5033 data_time: 0.0174 memory: 16131 loss: 1.2194 loss_prob: 0.6469 loss_thr: 0.4619 loss_db: 0.1106 2022/10/26 03:53:42 - mmengine - INFO - Epoch(train) [631][40/63] lr: 1.8077e-03 eta: 7:35:40 time: 0.4904 data_time: 0.0105 memory: 16131 loss: 1.2331 loss_prob: 0.6577 loss_thr: 0.4621 loss_db: 0.1132 2022/10/26 03:53:44 - mmengine - INFO - Epoch(train) [631][45/63] lr: 1.8077e-03 eta: 7:35:40 time: 0.4761 data_time: 0.0055 memory: 16131 loss: 1.2386 loss_prob: 0.6693 loss_thr: 0.4556 loss_db: 0.1137 2022/10/26 03:53:47 - mmengine - INFO - Epoch(train) [631][50/63] lr: 1.8077e-03 eta: 7:35:30 time: 0.5013 data_time: 0.0167 memory: 16131 loss: 1.3384 loss_prob: 0.7256 loss_thr: 0.4907 loss_db: 0.1220 2022/10/26 03:53:49 - mmengine - INFO - Epoch(train) [631][55/63] lr: 1.8077e-03 eta: 7:35:30 time: 0.5090 data_time: 0.0211 memory: 16131 loss: 1.3847 loss_prob: 0.7571 loss_thr: 0.4999 loss_db: 0.1277 2022/10/26 03:53:51 - mmengine - INFO - Epoch(train) [631][60/63] lr: 1.8077e-03 eta: 7:35:20 time: 0.4907 data_time: 0.0114 memory: 16131 loss: 1.2415 loss_prob: 0.6796 loss_thr: 0.4448 loss_db: 0.1171 2022/10/26 03:53:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:53:58 - mmengine - INFO - Epoch(train) [632][5/63] lr: 1.8048e-03 eta: 7:35:20 time: 0.7452 data_time: 0.2154 memory: 16131 loss: 1.2995 loss_prob: 0.7129 loss_thr: 0.4670 loss_db: 0.1197 2022/10/26 03:54:01 - mmengine - INFO - Epoch(train) [632][10/63] lr: 1.8048e-03 eta: 7:35:08 time: 0.7770 data_time: 0.2154 memory: 16131 loss: 1.2877 loss_prob: 0.7108 loss_thr: 0.4572 loss_db: 0.1198 2022/10/26 03:54:03 - mmengine - INFO - Epoch(train) [632][15/63] lr: 1.8048e-03 eta: 7:35:08 time: 0.5199 data_time: 0.0063 memory: 16131 loss: 1.1975 loss_prob: 0.6425 loss_thr: 0.4452 loss_db: 0.1098 2022/10/26 03:54:06 - mmengine - INFO - Epoch(train) [632][20/63] lr: 1.8048e-03 eta: 7:34:58 time: 0.5531 data_time: 0.0079 memory: 16131 loss: 1.3024 loss_prob: 0.7062 loss_thr: 0.4767 loss_db: 0.1196 2022/10/26 03:54:09 - mmengine - INFO - Epoch(train) [632][25/63] lr: 1.8048e-03 eta: 7:34:58 time: 0.5940 data_time: 0.0219 memory: 16131 loss: 1.3613 loss_prob: 0.7429 loss_thr: 0.4927 loss_db: 0.1257 2022/10/26 03:54:12 - mmengine - INFO - Epoch(train) [632][30/63] lr: 1.8048e-03 eta: 7:34:49 time: 0.5968 data_time: 0.0368 memory: 16131 loss: 1.4517 loss_prob: 0.8340 loss_thr: 0.4892 loss_db: 0.1284 2022/10/26 03:54:15 - mmengine - INFO - Epoch(train) [632][35/63] lr: 1.8048e-03 eta: 7:34:49 time: 0.5569 data_time: 0.0221 memory: 16131 loss: 1.3834 loss_prob: 0.7878 loss_thr: 0.4729 loss_db: 0.1227 2022/10/26 03:54:17 - mmengine - INFO - Epoch(train) [632][40/63] lr: 1.8048e-03 eta: 7:34:39 time: 0.5109 data_time: 0.0076 memory: 16131 loss: 1.2878 loss_prob: 0.6985 loss_thr: 0.4688 loss_db: 0.1205 2022/10/26 03:54:20 - mmengine - INFO - Epoch(train) [632][45/63] lr: 1.8048e-03 eta: 7:34:39 time: 0.5066 data_time: 0.0077 memory: 16131 loss: 1.3897 loss_prob: 0.7708 loss_thr: 0.4906 loss_db: 0.1283 2022/10/26 03:54:22 - mmengine - INFO - Epoch(train) [632][50/63] lr: 1.8048e-03 eta: 7:34:29 time: 0.5136 data_time: 0.0118 memory: 16131 loss: 1.3728 loss_prob: 0.7582 loss_thr: 0.4839 loss_db: 0.1307 2022/10/26 03:54:25 - mmengine - INFO - Epoch(train) [632][55/63] lr: 1.8048e-03 eta: 7:34:29 time: 0.5067 data_time: 0.0231 memory: 16131 loss: 1.3001 loss_prob: 0.7092 loss_thr: 0.4673 loss_db: 0.1237 2022/10/26 03:54:27 - mmengine - INFO - Epoch(train) [632][60/63] lr: 1.8048e-03 eta: 7:34:20 time: 0.5048 data_time: 0.0170 memory: 16131 loss: 1.3787 loss_prob: 0.7760 loss_thr: 0.4792 loss_db: 0.1234 2022/10/26 03:54:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:54:33 - mmengine - INFO - Epoch(train) [633][5/63] lr: 1.8020e-03 eta: 7:34:20 time: 0.7015 data_time: 0.2049 memory: 16131 loss: 1.4516 loss_prob: 0.8068 loss_thr: 0.5120 loss_db: 0.1328 2022/10/26 03:54:36 - mmengine - INFO - Epoch(train) [633][10/63] lr: 1.8020e-03 eta: 7:34:07 time: 0.7189 data_time: 0.2122 memory: 16131 loss: 1.3291 loss_prob: 0.7163 loss_thr: 0.4904 loss_db: 0.1224 2022/10/26 03:54:38 - mmengine - INFO - Epoch(train) [633][15/63] lr: 1.8020e-03 eta: 7:34:07 time: 0.5058 data_time: 0.0137 memory: 16131 loss: 1.2663 loss_prob: 0.6786 loss_thr: 0.4724 loss_db: 0.1152 2022/10/26 03:54:41 - mmengine - INFO - Epoch(train) [633][20/63] lr: 1.8020e-03 eta: 7:33:57 time: 0.5193 data_time: 0.0070 memory: 16131 loss: 1.2737 loss_prob: 0.6899 loss_thr: 0.4656 loss_db: 0.1182 2022/10/26 03:54:44 - mmengine - INFO - Epoch(train) [633][25/63] lr: 1.8020e-03 eta: 7:33:57 time: 0.5602 data_time: 0.0347 memory: 16131 loss: 1.3039 loss_prob: 0.7095 loss_thr: 0.4714 loss_db: 0.1231 2022/10/26 03:54:47 - mmengine - INFO - Epoch(train) [633][30/63] lr: 1.8020e-03 eta: 7:33:48 time: 0.5478 data_time: 0.0393 memory: 16131 loss: 1.3294 loss_prob: 0.7336 loss_thr: 0.4713 loss_db: 0.1245 2022/10/26 03:54:49 - mmengine - INFO - Epoch(train) [633][35/63] lr: 1.8020e-03 eta: 7:33:48 time: 0.5074 data_time: 0.0194 memory: 16131 loss: 1.2167 loss_prob: 0.6612 loss_thr: 0.4468 loss_db: 0.1087 2022/10/26 03:54:52 - mmengine - INFO - Epoch(train) [633][40/63] lr: 1.8020e-03 eta: 7:33:38 time: 0.5275 data_time: 0.0135 memory: 16131 loss: 1.2045 loss_prob: 0.6504 loss_thr: 0.4449 loss_db: 0.1092 2022/10/26 03:54:55 - mmengine - INFO - Epoch(train) [633][45/63] lr: 1.8020e-03 eta: 7:33:38 time: 0.5511 data_time: 0.0058 memory: 16131 loss: 1.3617 loss_prob: 0.7563 loss_thr: 0.4761 loss_db: 0.1293 2022/10/26 03:54:57 - mmengine - INFO - Epoch(train) [633][50/63] lr: 1.8020e-03 eta: 7:33:29 time: 0.5464 data_time: 0.0214 memory: 16131 loss: 1.5441 loss_prob: 0.9192 loss_thr: 0.4833 loss_db: 0.1417 2022/10/26 03:55:00 - mmengine - INFO - Epoch(train) [633][55/63] lr: 1.8020e-03 eta: 7:33:29 time: 0.5144 data_time: 0.0210 memory: 16131 loss: 1.4785 loss_prob: 0.8799 loss_thr: 0.4644 loss_db: 0.1342 2022/10/26 03:55:02 - mmengine - INFO - Epoch(train) [633][60/63] lr: 1.8020e-03 eta: 7:33:18 time: 0.4861 data_time: 0.0084 memory: 16131 loss: 1.4863 loss_prob: 0.8454 loss_thr: 0.4919 loss_db: 0.1489 2022/10/26 03:55:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:55:08 - mmengine - INFO - Epoch(train) [634][5/63] lr: 1.7991e-03 eta: 7:33:18 time: 0.6442 data_time: 0.1676 memory: 16131 loss: 1.4120 loss_prob: 0.7947 loss_thr: 0.4748 loss_db: 0.1424 2022/10/26 03:55:10 - mmengine - INFO - Epoch(train) [634][10/63] lr: 1.7991e-03 eta: 7:33:06 time: 0.7010 data_time: 0.1785 memory: 16131 loss: 1.4334 loss_prob: 0.7932 loss_thr: 0.5051 loss_db: 0.1351 2022/10/26 03:55:13 - mmengine - INFO - Epoch(train) [634][15/63] lr: 1.7991e-03 eta: 7:33:06 time: 0.5134 data_time: 0.0173 memory: 16131 loss: 1.4147 loss_prob: 0.7833 loss_thr: 0.4985 loss_db: 0.1329 2022/10/26 03:55:15 - mmengine - INFO - Epoch(train) [634][20/63] lr: 1.7991e-03 eta: 7:32:56 time: 0.4867 data_time: 0.0066 memory: 16131 loss: 1.4546 loss_prob: 0.8041 loss_thr: 0.5149 loss_db: 0.1355 2022/10/26 03:55:18 - mmengine - INFO - Epoch(train) [634][25/63] lr: 1.7991e-03 eta: 7:32:56 time: 0.5406 data_time: 0.0374 memory: 16131 loss: 1.4390 loss_prob: 0.7905 loss_thr: 0.5146 loss_db: 0.1339 2022/10/26 03:55:21 - mmengine - INFO - Epoch(train) [634][30/63] lr: 1.7991e-03 eta: 7:32:46 time: 0.5360 data_time: 0.0409 memory: 16131 loss: 1.3533 loss_prob: 0.7462 loss_thr: 0.4825 loss_db: 0.1245 2022/10/26 03:55:23 - mmengine - INFO - Epoch(train) [634][35/63] lr: 1.7991e-03 eta: 7:32:46 time: 0.5060 data_time: 0.0209 memory: 16131 loss: 1.4060 loss_prob: 0.7829 loss_thr: 0.4939 loss_db: 0.1291 2022/10/26 03:55:26 - mmengine - INFO - Epoch(train) [634][40/63] lr: 1.7991e-03 eta: 7:32:36 time: 0.5105 data_time: 0.0168 memory: 16131 loss: 1.3880 loss_prob: 0.7850 loss_thr: 0.4748 loss_db: 0.1281 2022/10/26 03:55:28 - mmengine - INFO - Epoch(train) [634][45/63] lr: 1.7991e-03 eta: 7:32:36 time: 0.4973 data_time: 0.0089 memory: 16131 loss: 1.4670 loss_prob: 0.8431 loss_thr: 0.4910 loss_db: 0.1329 2022/10/26 03:55:31 - mmengine - INFO - Epoch(train) [634][50/63] lr: 1.7991e-03 eta: 7:32:27 time: 0.5605 data_time: 0.0268 memory: 16131 loss: 1.4784 loss_prob: 0.8343 loss_thr: 0.5092 loss_db: 0.1349 2022/10/26 03:55:34 - mmengine - INFO - Epoch(train) [634][55/63] lr: 1.7991e-03 eta: 7:32:27 time: 0.5742 data_time: 0.0261 memory: 16131 loss: 1.3931 loss_prob: 0.7753 loss_thr: 0.4875 loss_db: 0.1304 2022/10/26 03:55:37 - mmengine - INFO - Epoch(train) [634][60/63] lr: 1.7991e-03 eta: 7:32:17 time: 0.5322 data_time: 0.0122 memory: 16131 loss: 1.3714 loss_prob: 0.7522 loss_thr: 0.4902 loss_db: 0.1289 2022/10/26 03:55:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:55:43 - mmengine - INFO - Epoch(train) [635][5/63] lr: 1.7962e-03 eta: 7:32:17 time: 0.7034 data_time: 0.2053 memory: 16131 loss: 1.5350 loss_prob: 0.9049 loss_thr: 0.4908 loss_db: 0.1393 2022/10/26 03:55:46 - mmengine - INFO - Epoch(train) [635][10/63] lr: 1.7962e-03 eta: 7:32:05 time: 0.7606 data_time: 0.2121 memory: 16131 loss: 1.4799 loss_prob: 0.8748 loss_thr: 0.4712 loss_db: 0.1340 2022/10/26 03:55:48 - mmengine - INFO - Epoch(train) [635][15/63] lr: 1.7962e-03 eta: 7:32:05 time: 0.5513 data_time: 0.0143 memory: 16131 loss: 1.2658 loss_prob: 0.6755 loss_thr: 0.4768 loss_db: 0.1135 2022/10/26 03:55:51 - mmengine - INFO - Epoch(train) [635][20/63] lr: 1.7962e-03 eta: 7:31:56 time: 0.5020 data_time: 0.0054 memory: 16131 loss: 1.3520 loss_prob: 0.7375 loss_thr: 0.4914 loss_db: 0.1231 2022/10/26 03:55:53 - mmengine - INFO - Epoch(train) [635][25/63] lr: 1.7962e-03 eta: 7:31:56 time: 0.5147 data_time: 0.0257 memory: 16131 loss: 1.3392 loss_prob: 0.7434 loss_thr: 0.4700 loss_db: 0.1258 2022/10/26 03:55:56 - mmengine - INFO - Epoch(train) [635][30/63] lr: 1.7962e-03 eta: 7:31:46 time: 0.5094 data_time: 0.0302 memory: 16131 loss: 1.2617 loss_prob: 0.6985 loss_thr: 0.4460 loss_db: 0.1172 2022/10/26 03:55:58 - mmengine - INFO - Epoch(train) [635][35/63] lr: 1.7962e-03 eta: 7:31:46 time: 0.5003 data_time: 0.0177 memory: 16131 loss: 1.2697 loss_prob: 0.7019 loss_thr: 0.4502 loss_db: 0.1177 2022/10/26 03:56:01 - mmengine - INFO - Epoch(train) [635][40/63] lr: 1.7962e-03 eta: 7:31:36 time: 0.5128 data_time: 0.0154 memory: 16131 loss: 1.2971 loss_prob: 0.7084 loss_thr: 0.4692 loss_db: 0.1195 2022/10/26 03:56:03 - mmengine - INFO - Epoch(train) [635][45/63] lr: 1.7962e-03 eta: 7:31:36 time: 0.5222 data_time: 0.0077 memory: 16131 loss: 1.2624 loss_prob: 0.6825 loss_thr: 0.4631 loss_db: 0.1168 2022/10/26 03:56:06 - mmengine - INFO - Epoch(train) [635][50/63] lr: 1.7962e-03 eta: 7:31:26 time: 0.5196 data_time: 0.0189 memory: 16131 loss: 1.3671 loss_prob: 0.7628 loss_thr: 0.4783 loss_db: 0.1260 2022/10/26 03:56:08 - mmengine - INFO - Epoch(train) [635][55/63] lr: 1.7962e-03 eta: 7:31:26 time: 0.5059 data_time: 0.0205 memory: 16131 loss: 1.4001 loss_prob: 0.7750 loss_thr: 0.4994 loss_db: 0.1257 2022/10/26 03:56:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:56:11 - mmengine - INFO - Epoch(train) [635][60/63] lr: 1.7962e-03 eta: 7:31:16 time: 0.4974 data_time: 0.0102 memory: 16131 loss: 1.2299 loss_prob: 0.6486 loss_thr: 0.4711 loss_db: 0.1103 2022/10/26 03:56:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:56:17 - mmengine - INFO - Epoch(train) [636][5/63] lr: 1.7934e-03 eta: 7:31:16 time: 0.7375 data_time: 0.1958 memory: 16131 loss: 1.2076 loss_prob: 0.6391 loss_thr: 0.4588 loss_db: 0.1097 2022/10/26 03:56:20 - mmengine - INFO - Epoch(train) [636][10/63] lr: 1.7934e-03 eta: 7:31:04 time: 0.7667 data_time: 0.1939 memory: 16131 loss: 1.3046 loss_prob: 0.7087 loss_thr: 0.4750 loss_db: 0.1210 2022/10/26 03:56:23 - mmengine - INFO - Epoch(train) [636][15/63] lr: 1.7934e-03 eta: 7:31:04 time: 0.5247 data_time: 0.0165 memory: 16131 loss: 1.6352 loss_prob: 0.9778 loss_thr: 0.5027 loss_db: 0.1547 2022/10/26 03:56:25 - mmengine - INFO - Epoch(train) [636][20/63] lr: 1.7934e-03 eta: 7:30:55 time: 0.5245 data_time: 0.0168 memory: 16131 loss: 1.6707 loss_prob: 1.0121 loss_thr: 0.4962 loss_db: 0.1625 2022/10/26 03:56:28 - mmengine - INFO - Epoch(train) [636][25/63] lr: 1.7934e-03 eta: 7:30:55 time: 0.5477 data_time: 0.0322 memory: 16131 loss: 1.3801 loss_prob: 0.7829 loss_thr: 0.4657 loss_db: 0.1316 2022/10/26 03:56:31 - mmengine - INFO - Epoch(train) [636][30/63] lr: 1.7934e-03 eta: 7:30:45 time: 0.5409 data_time: 0.0337 memory: 16131 loss: 1.2902 loss_prob: 0.7113 loss_thr: 0.4623 loss_db: 0.1166 2022/10/26 03:56:33 - mmengine - INFO - Epoch(train) [636][35/63] lr: 1.7934e-03 eta: 7:30:45 time: 0.4988 data_time: 0.0069 memory: 16131 loss: 1.2213 loss_prob: 0.6491 loss_thr: 0.4635 loss_db: 0.1087 2022/10/26 03:56:36 - mmengine - INFO - Epoch(train) [636][40/63] lr: 1.7934e-03 eta: 7:30:35 time: 0.5045 data_time: 0.0089 memory: 16131 loss: 1.1973 loss_prob: 0.6258 loss_thr: 0.4641 loss_db: 0.1075 2022/10/26 03:56:38 - mmengine - INFO - Epoch(train) [636][45/63] lr: 1.7934e-03 eta: 7:30:35 time: 0.5100 data_time: 0.0094 memory: 16131 loss: 1.3809 loss_prob: 0.7597 loss_thr: 0.4951 loss_db: 0.1261 2022/10/26 03:56:41 - mmengine - INFO - Epoch(train) [636][50/63] lr: 1.7934e-03 eta: 7:30:25 time: 0.5148 data_time: 0.0224 memory: 16131 loss: 1.4068 loss_prob: 0.7834 loss_thr: 0.4950 loss_db: 0.1284 2022/10/26 03:56:43 - mmengine - INFO - Epoch(train) [636][55/63] lr: 1.7934e-03 eta: 7:30:25 time: 0.5200 data_time: 0.0223 memory: 16131 loss: 1.2773 loss_prob: 0.6907 loss_thr: 0.4683 loss_db: 0.1183 2022/10/26 03:56:46 - mmengine - INFO - Epoch(train) [636][60/63] lr: 1.7934e-03 eta: 7:30:16 time: 0.5267 data_time: 0.0059 memory: 16131 loss: 1.2261 loss_prob: 0.6629 loss_thr: 0.4481 loss_db: 0.1150 2022/10/26 03:56:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:56:52 - mmengine - INFO - Epoch(train) [637][5/63] lr: 1.7905e-03 eta: 7:30:16 time: 0.6698 data_time: 0.1801 memory: 16131 loss: 1.2079 loss_prob: 0.6594 loss_thr: 0.4372 loss_db: 0.1113 2022/10/26 03:56:54 - mmengine - INFO - Epoch(train) [637][10/63] lr: 1.7905e-03 eta: 7:30:03 time: 0.6932 data_time: 0.1814 memory: 16131 loss: 1.2458 loss_prob: 0.6708 loss_thr: 0.4612 loss_db: 0.1138 2022/10/26 03:56:57 - mmengine - INFO - Epoch(train) [637][15/63] lr: 1.7905e-03 eta: 7:30:03 time: 0.5224 data_time: 0.0080 memory: 16131 loss: 1.2598 loss_prob: 0.6834 loss_thr: 0.4593 loss_db: 0.1172 2022/10/26 03:57:00 - mmengine - INFO - Epoch(train) [637][20/63] lr: 1.7905e-03 eta: 7:29:54 time: 0.5343 data_time: 0.0112 memory: 16131 loss: 1.1979 loss_prob: 0.6463 loss_thr: 0.4414 loss_db: 0.1102 2022/10/26 03:57:02 - mmengine - INFO - Epoch(train) [637][25/63] lr: 1.7905e-03 eta: 7:29:54 time: 0.5256 data_time: 0.0244 memory: 16131 loss: 1.1814 loss_prob: 0.6371 loss_thr: 0.4374 loss_db: 0.1068 2022/10/26 03:57:05 - mmengine - INFO - Epoch(train) [637][30/63] lr: 1.7905e-03 eta: 7:29:44 time: 0.5108 data_time: 0.0234 memory: 16131 loss: 1.1682 loss_prob: 0.6330 loss_thr: 0.4288 loss_db: 0.1064 2022/10/26 03:57:07 - mmengine - INFO - Epoch(train) [637][35/63] lr: 1.7905e-03 eta: 7:29:44 time: 0.4967 data_time: 0.0154 memory: 16131 loss: 1.2442 loss_prob: 0.6706 loss_thr: 0.4602 loss_db: 0.1134 2022/10/26 03:57:10 - mmengine - INFO - Epoch(train) [637][40/63] lr: 1.7905e-03 eta: 7:29:34 time: 0.5148 data_time: 0.0147 memory: 16131 loss: 1.2440 loss_prob: 0.6683 loss_thr: 0.4600 loss_db: 0.1157 2022/10/26 03:57:12 - mmengine - INFO - Epoch(train) [637][45/63] lr: 1.7905e-03 eta: 7:29:34 time: 0.5291 data_time: 0.0120 memory: 16131 loss: 1.2706 loss_prob: 0.6862 loss_thr: 0.4651 loss_db: 0.1193 2022/10/26 03:57:15 - mmengine - INFO - Epoch(train) [637][50/63] lr: 1.7905e-03 eta: 7:29:25 time: 0.5524 data_time: 0.0230 memory: 16131 loss: 1.2499 loss_prob: 0.6726 loss_thr: 0.4643 loss_db: 0.1130 2022/10/26 03:57:18 - mmengine - INFO - Epoch(train) [637][55/63] lr: 1.7905e-03 eta: 7:29:25 time: 0.5587 data_time: 0.0238 memory: 16131 loss: 1.1739 loss_prob: 0.6327 loss_thr: 0.4357 loss_db: 0.1056 2022/10/26 03:57:20 - mmengine - INFO - Epoch(train) [637][60/63] lr: 1.7905e-03 eta: 7:29:15 time: 0.5103 data_time: 0.0128 memory: 16131 loss: 1.2619 loss_prob: 0.6922 loss_thr: 0.4539 loss_db: 0.1158 2022/10/26 03:57:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:57:26 - mmengine - INFO - Epoch(train) [638][5/63] lr: 1.7877e-03 eta: 7:29:15 time: 0.6650 data_time: 0.1941 memory: 16131 loss: 1.3736 loss_prob: 0.7516 loss_thr: 0.4962 loss_db: 0.1258 2022/10/26 03:57:29 - mmengine - INFO - Epoch(train) [638][10/63] lr: 1.7877e-03 eta: 7:29:02 time: 0.7032 data_time: 0.1923 memory: 16131 loss: 1.4258 loss_prob: 0.7789 loss_thr: 0.5173 loss_db: 0.1297 2022/10/26 03:57:31 - mmengine - INFO - Epoch(train) [638][15/63] lr: 1.7877e-03 eta: 7:29:02 time: 0.5257 data_time: 0.0074 memory: 16131 loss: 1.3639 loss_prob: 0.7489 loss_thr: 0.4890 loss_db: 0.1260 2022/10/26 03:57:34 - mmengine - INFO - Epoch(train) [638][20/63] lr: 1.7877e-03 eta: 7:28:53 time: 0.5580 data_time: 0.0093 memory: 16131 loss: 1.3658 loss_prob: 0.7429 loss_thr: 0.4958 loss_db: 0.1271 2022/10/26 03:57:37 - mmengine - INFO - Epoch(train) [638][25/63] lr: 1.7877e-03 eta: 7:28:53 time: 0.5814 data_time: 0.0364 memory: 16131 loss: 1.4365 loss_prob: 0.7696 loss_thr: 0.5363 loss_db: 0.1306 2022/10/26 03:57:40 - mmengine - INFO - Epoch(train) [638][30/63] lr: 1.7877e-03 eta: 7:28:44 time: 0.5812 data_time: 0.0342 memory: 16131 loss: 1.4701 loss_prob: 0.8132 loss_thr: 0.5239 loss_db: 0.1331 2022/10/26 03:57:42 - mmengine - INFO - Epoch(train) [638][35/63] lr: 1.7877e-03 eta: 7:28:44 time: 0.5279 data_time: 0.0069 memory: 16131 loss: 1.3318 loss_prob: 0.7355 loss_thr: 0.4741 loss_db: 0.1222 2022/10/26 03:57:45 - mmengine - INFO - Epoch(train) [638][40/63] lr: 1.7877e-03 eta: 7:28:34 time: 0.5064 data_time: 0.0097 memory: 16131 loss: 1.2144 loss_prob: 0.6532 loss_thr: 0.4463 loss_db: 0.1149 2022/10/26 03:57:48 - mmengine - INFO - Epoch(train) [638][45/63] lr: 1.7877e-03 eta: 7:28:34 time: 0.5163 data_time: 0.0099 memory: 16131 loss: 1.2983 loss_prob: 0.7175 loss_thr: 0.4582 loss_db: 0.1226 2022/10/26 03:57:50 - mmengine - INFO - Epoch(train) [638][50/63] lr: 1.7877e-03 eta: 7:28:24 time: 0.5268 data_time: 0.0258 memory: 16131 loss: 1.2637 loss_prob: 0.6842 loss_thr: 0.4662 loss_db: 0.1134 2022/10/26 03:57:53 - mmengine - INFO - Epoch(train) [638][55/63] lr: 1.7877e-03 eta: 7:28:24 time: 0.5140 data_time: 0.0247 memory: 16131 loss: 1.2139 loss_prob: 0.6354 loss_thr: 0.4709 loss_db: 0.1076 2022/10/26 03:57:55 - mmengine - INFO - Epoch(train) [638][60/63] lr: 1.7877e-03 eta: 7:28:14 time: 0.4865 data_time: 0.0072 memory: 16131 loss: 1.2339 loss_prob: 0.6586 loss_thr: 0.4617 loss_db: 0.1136 2022/10/26 03:57:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:58:01 - mmengine - INFO - Epoch(train) [639][5/63] lr: 1.7848e-03 eta: 7:28:14 time: 0.7049 data_time: 0.2229 memory: 16131 loss: 1.2561 loss_prob: 0.6836 loss_thr: 0.4615 loss_db: 0.1110 2022/10/26 03:58:04 - mmengine - INFO - Epoch(train) [639][10/63] lr: 1.7848e-03 eta: 7:28:02 time: 0.7371 data_time: 0.2234 memory: 16131 loss: 1.3197 loss_prob: 0.7252 loss_thr: 0.4772 loss_db: 0.1173 2022/10/26 03:58:06 - mmengine - INFO - Epoch(train) [639][15/63] lr: 1.7848e-03 eta: 7:28:02 time: 0.4964 data_time: 0.0058 memory: 16131 loss: 1.2167 loss_prob: 0.6631 loss_thr: 0.4400 loss_db: 0.1136 2022/10/26 03:58:09 - mmengine - INFO - Epoch(train) [639][20/63] lr: 1.7848e-03 eta: 7:27:53 time: 0.5316 data_time: 0.0087 memory: 16131 loss: 1.1842 loss_prob: 0.6330 loss_thr: 0.4418 loss_db: 0.1095 2022/10/26 03:58:12 - mmengine - INFO - Epoch(train) [639][25/63] lr: 1.7848e-03 eta: 7:27:53 time: 0.5403 data_time: 0.0151 memory: 16131 loss: 1.2609 loss_prob: 0.6882 loss_thr: 0.4588 loss_db: 0.1139 2022/10/26 03:58:15 - mmengine - INFO - Epoch(train) [639][30/63] lr: 1.7848e-03 eta: 7:27:44 time: 0.5817 data_time: 0.0349 memory: 16131 loss: 1.2621 loss_prob: 0.6916 loss_thr: 0.4544 loss_db: 0.1161 2022/10/26 03:58:18 - mmengine - INFO - Epoch(train) [639][35/63] lr: 1.7848e-03 eta: 7:27:44 time: 0.6100 data_time: 0.0282 memory: 16131 loss: 1.2676 loss_prob: 0.6934 loss_thr: 0.4557 loss_db: 0.1185 2022/10/26 03:58:20 - mmengine - INFO - Epoch(train) [639][40/63] lr: 1.7848e-03 eta: 7:27:34 time: 0.5242 data_time: 0.0064 memory: 16131 loss: 1.2176 loss_prob: 0.6634 loss_thr: 0.4432 loss_db: 0.1111 2022/10/26 03:58:23 - mmengine - INFO - Epoch(train) [639][45/63] lr: 1.7848e-03 eta: 7:27:34 time: 0.4879 data_time: 0.0087 memory: 16131 loss: 1.2159 loss_prob: 0.6473 loss_thr: 0.4621 loss_db: 0.1064 2022/10/26 03:58:25 - mmengine - INFO - Epoch(train) [639][50/63] lr: 1.7848e-03 eta: 7:27:24 time: 0.5143 data_time: 0.0261 memory: 16131 loss: 1.2920 loss_prob: 0.7024 loss_thr: 0.4763 loss_db: 0.1133 2022/10/26 03:58:28 - mmengine - INFO - Epoch(train) [639][55/63] lr: 1.7848e-03 eta: 7:27:24 time: 0.5030 data_time: 0.0235 memory: 16131 loss: 1.2378 loss_prob: 0.6714 loss_thr: 0.4531 loss_db: 0.1133 2022/10/26 03:58:30 - mmengine - INFO - Epoch(train) [639][60/63] lr: 1.7848e-03 eta: 7:27:14 time: 0.5101 data_time: 0.0047 memory: 16131 loss: 1.2584 loss_prob: 0.6885 loss_thr: 0.4526 loss_db: 0.1173 2022/10/26 03:58:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:58:36 - mmengine - INFO - Epoch(train) [640][5/63] lr: 1.7819e-03 eta: 7:27:14 time: 0.6896 data_time: 0.1873 memory: 16131 loss: 1.2033 loss_prob: 0.6616 loss_thr: 0.4286 loss_db: 0.1131 2022/10/26 03:58:39 - mmengine - INFO - Epoch(train) [640][10/63] lr: 1.7819e-03 eta: 7:27:02 time: 0.6989 data_time: 0.1866 memory: 16131 loss: 1.1834 loss_prob: 0.6367 loss_thr: 0.4383 loss_db: 0.1084 2022/10/26 03:58:41 - mmengine - INFO - Epoch(train) [640][15/63] lr: 1.7819e-03 eta: 7:27:02 time: 0.5005 data_time: 0.0060 memory: 16131 loss: 1.2149 loss_prob: 0.6467 loss_thr: 0.4569 loss_db: 0.1113 2022/10/26 03:58:44 - mmengine - INFO - Epoch(train) [640][20/63] lr: 1.7819e-03 eta: 7:26:52 time: 0.5105 data_time: 0.0079 memory: 16131 loss: 1.2288 loss_prob: 0.6583 loss_thr: 0.4572 loss_db: 0.1133 2022/10/26 03:58:47 - mmengine - INFO - Epoch(train) [640][25/63] lr: 1.7819e-03 eta: 7:26:52 time: 0.5518 data_time: 0.0322 memory: 16131 loss: 1.1863 loss_prob: 0.6283 loss_thr: 0.4527 loss_db: 0.1053 2022/10/26 03:58:49 - mmengine - INFO - Epoch(train) [640][30/63] lr: 1.7819e-03 eta: 7:26:43 time: 0.5338 data_time: 0.0360 memory: 16131 loss: 1.2585 loss_prob: 0.6825 loss_thr: 0.4617 loss_db: 0.1143 2022/10/26 03:58:52 - mmengine - INFO - Epoch(train) [640][35/63] lr: 1.7819e-03 eta: 7:26:43 time: 0.5484 data_time: 0.0166 memory: 16131 loss: 1.3615 loss_prob: 0.7669 loss_thr: 0.4650 loss_db: 0.1296 2022/10/26 03:58:55 - mmengine - INFO - Epoch(train) [640][40/63] lr: 1.7819e-03 eta: 7:26:33 time: 0.5711 data_time: 0.0108 memory: 16131 loss: 1.4015 loss_prob: 0.7944 loss_thr: 0.4765 loss_db: 0.1306 2022/10/26 03:58:57 - mmengine - INFO - Epoch(train) [640][45/63] lr: 1.7819e-03 eta: 7:26:33 time: 0.5194 data_time: 0.0059 memory: 16131 loss: 1.4121 loss_prob: 0.7983 loss_thr: 0.4863 loss_db: 0.1276 2022/10/26 03:59:00 - mmengine - INFO - Epoch(train) [640][50/63] lr: 1.7819e-03 eta: 7:26:24 time: 0.5158 data_time: 0.0236 memory: 16131 loss: 1.3086 loss_prob: 0.7183 loss_thr: 0.4724 loss_db: 0.1179 2022/10/26 03:59:03 - mmengine - INFO - Epoch(train) [640][55/63] lr: 1.7819e-03 eta: 7:26:24 time: 0.5365 data_time: 0.0261 memory: 16131 loss: 1.2776 loss_prob: 0.6939 loss_thr: 0.4656 loss_db: 0.1181 2022/10/26 03:59:05 - mmengine - INFO - Epoch(train) [640][60/63] lr: 1.7819e-03 eta: 7:26:14 time: 0.5255 data_time: 0.0094 memory: 16131 loss: 1.2774 loss_prob: 0.7025 loss_thr: 0.4558 loss_db: 0.1190 2022/10/26 03:59:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 03:59:07 - mmengine - INFO - Saving checkpoint at 640 epochs 2022/10/26 03:59:13 - mmengine - INFO - Epoch(val) [640][5/32] eta: 7:26:14 time: 0.5544 data_time: 0.0902 memory: 16131 2022/10/26 03:59:16 - mmengine - INFO - Epoch(val) [640][10/32] eta: 0:00:13 time: 0.6127 data_time: 0.1204 memory: 15724 2022/10/26 03:59:19 - mmengine - INFO - Epoch(val) [640][15/32] eta: 0:00:13 time: 0.5489 data_time: 0.0541 memory: 15724 2022/10/26 03:59:22 - mmengine - INFO - Epoch(val) [640][20/32] eta: 0:00:06 time: 0.5570 data_time: 0.0580 memory: 15724 2022/10/26 03:59:25 - mmengine - INFO - Epoch(val) [640][25/32] eta: 0:00:06 time: 0.5634 data_time: 0.0522 memory: 15724 2022/10/26 03:59:27 - mmengine - INFO - Epoch(val) [640][30/32] eta: 0:00:01 time: 0.5173 data_time: 0.0227 memory: 15724 2022/10/26 03:59:28 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8223, precision: 0.7296, hmean: 0.7732 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8223, precision: 0.7926, hmean: 0.8072 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8209, precision: 0.8249, hmean: 0.8229 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8122, precision: 0.8642, hmean: 0.8374 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7872, precision: 0.9008, hmean: 0.8402 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6192, precision: 0.9456, hmean: 0.7483 2022/10/26 03:59:28 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0226, precision: 1.0000, hmean: 0.0443 2022/10/26 03:59:28 - mmengine - INFO - Epoch(val) [640][32/32] icdar/precision: 0.9008 icdar/recall: 0.7872 icdar/hmean: 0.8402 2022/10/26 03:59:32 - mmengine - INFO - Epoch(train) [641][5/63] lr: 1.7791e-03 eta: 0:00:01 time: 0.6618 data_time: 0.2073 memory: 16131 loss: 1.3159 loss_prob: 0.7317 loss_thr: 0.4599 loss_db: 0.1243 2022/10/26 03:59:35 - mmengine - INFO - Epoch(train) [641][10/63] lr: 1.7791e-03 eta: 7:26:02 time: 0.7014 data_time: 0.2083 memory: 16131 loss: 1.2997 loss_prob: 0.7131 loss_thr: 0.4668 loss_db: 0.1198 2022/10/26 03:59:37 - mmengine - INFO - Epoch(train) [641][15/63] lr: 1.7791e-03 eta: 7:26:02 time: 0.5000 data_time: 0.0106 memory: 16131 loss: 1.2335 loss_prob: 0.6611 loss_thr: 0.4575 loss_db: 0.1149 2022/10/26 03:59:40 - mmengine - INFO - Epoch(train) [641][20/63] lr: 1.7791e-03 eta: 7:25:52 time: 0.5156 data_time: 0.0113 memory: 16131 loss: 1.2108 loss_prob: 0.6425 loss_thr: 0.4550 loss_db: 0.1134 2022/10/26 03:59:43 - mmengine - INFO - Epoch(train) [641][25/63] lr: 1.7791e-03 eta: 7:25:52 time: 0.5718 data_time: 0.0376 memory: 16131 loss: 1.2396 loss_prob: 0.6621 loss_thr: 0.4648 loss_db: 0.1127 2022/10/26 03:59:45 - mmengine - INFO - Epoch(train) [641][30/63] lr: 1.7791e-03 eta: 7:25:43 time: 0.5471 data_time: 0.0347 memory: 16131 loss: 1.2956 loss_prob: 0.6975 loss_thr: 0.4818 loss_db: 0.1163 2022/10/26 03:59:48 - mmengine - INFO - Epoch(train) [641][35/63] lr: 1.7791e-03 eta: 7:25:43 time: 0.4878 data_time: 0.0054 memory: 16131 loss: 1.2613 loss_prob: 0.6817 loss_thr: 0.4626 loss_db: 0.1169 2022/10/26 03:59:50 - mmengine - INFO - Epoch(train) [641][40/63] lr: 1.7791e-03 eta: 7:25:33 time: 0.5024 data_time: 0.0055 memory: 16131 loss: 1.2020 loss_prob: 0.6475 loss_thr: 0.4425 loss_db: 0.1120 2022/10/26 03:59:53 - mmengine - INFO - Epoch(train) [641][45/63] lr: 1.7791e-03 eta: 7:25:33 time: 0.5066 data_time: 0.0054 memory: 16131 loss: 1.1995 loss_prob: 0.6391 loss_thr: 0.4505 loss_db: 0.1098 2022/10/26 03:59:55 - mmengine - INFO - Epoch(train) [641][50/63] lr: 1.7791e-03 eta: 7:25:23 time: 0.4996 data_time: 0.0225 memory: 16131 loss: 1.1940 loss_prob: 0.6466 loss_thr: 0.4391 loss_db: 0.1083 2022/10/26 03:59:58 - mmengine - INFO - Epoch(train) [641][55/63] lr: 1.7791e-03 eta: 7:25:23 time: 0.5014 data_time: 0.0223 memory: 16131 loss: 1.2574 loss_prob: 0.6927 loss_thr: 0.4484 loss_db: 0.1162 2022/10/26 04:00:00 - mmengine - INFO - Epoch(train) [641][60/63] lr: 1.7791e-03 eta: 7:25:13 time: 0.4929 data_time: 0.0062 memory: 16131 loss: 1.2282 loss_prob: 0.6639 loss_thr: 0.4481 loss_db: 0.1163 2022/10/26 04:00:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:00:06 - mmengine - INFO - Epoch(train) [642][5/63] lr: 1.7762e-03 eta: 7:25:13 time: 0.6811 data_time: 0.1771 memory: 16131 loss: 1.1361 loss_prob: 0.6068 loss_thr: 0.4246 loss_db: 0.1047 2022/10/26 04:00:09 - mmengine - INFO - Epoch(train) [642][10/63] lr: 1.7762e-03 eta: 7:25:01 time: 0.7283 data_time: 0.1773 memory: 16131 loss: 1.1317 loss_prob: 0.6019 loss_thr: 0.4270 loss_db: 0.1028 2022/10/26 04:00:11 - mmengine - INFO - Epoch(train) [642][15/63] lr: 1.7762e-03 eta: 7:25:01 time: 0.5372 data_time: 0.0055 memory: 16131 loss: 1.2505 loss_prob: 0.6848 loss_thr: 0.4498 loss_db: 0.1159 2022/10/26 04:00:14 - mmengine - INFO - Epoch(train) [642][20/63] lr: 1.7762e-03 eta: 7:24:51 time: 0.5075 data_time: 0.0060 memory: 16131 loss: 1.3349 loss_prob: 0.7456 loss_thr: 0.4630 loss_db: 0.1263 2022/10/26 04:00:16 - mmengine - INFO - Epoch(train) [642][25/63] lr: 1.7762e-03 eta: 7:24:51 time: 0.4951 data_time: 0.0168 memory: 16131 loss: 1.2821 loss_prob: 0.7049 loss_thr: 0.4588 loss_db: 0.1183 2022/10/26 04:00:19 - mmengine - INFO - Epoch(train) [642][30/63] lr: 1.7762e-03 eta: 7:24:42 time: 0.5474 data_time: 0.0600 memory: 16131 loss: 1.2470 loss_prob: 0.6838 loss_thr: 0.4466 loss_db: 0.1166 2022/10/26 04:00:22 - mmengine - INFO - Epoch(train) [642][35/63] lr: 1.7762e-03 eta: 7:24:42 time: 0.5395 data_time: 0.0488 memory: 16131 loss: 1.2888 loss_prob: 0.7072 loss_thr: 0.4607 loss_db: 0.1209 2022/10/26 04:00:24 - mmengine - INFO - Epoch(train) [642][40/63] lr: 1.7762e-03 eta: 7:24:32 time: 0.4997 data_time: 0.0045 memory: 16131 loss: 1.2388 loss_prob: 0.6714 loss_thr: 0.4556 loss_db: 0.1118 2022/10/26 04:00:27 - mmengine - INFO - Epoch(train) [642][45/63] lr: 1.7762e-03 eta: 7:24:32 time: 0.5167 data_time: 0.0056 memory: 16131 loss: 1.2520 loss_prob: 0.6774 loss_thr: 0.4616 loss_db: 0.1130 2022/10/26 04:00:30 - mmengine - INFO - Epoch(train) [642][50/63] lr: 1.7762e-03 eta: 7:24:22 time: 0.5171 data_time: 0.0139 memory: 16131 loss: 1.2705 loss_prob: 0.6837 loss_thr: 0.4695 loss_db: 0.1173 2022/10/26 04:00:32 - mmengine - INFO - Epoch(train) [642][55/63] lr: 1.7762e-03 eta: 7:24:22 time: 0.5370 data_time: 0.0238 memory: 16131 loss: 1.2252 loss_prob: 0.6690 loss_thr: 0.4379 loss_db: 0.1183 2022/10/26 04:00:35 - mmengine - INFO - Epoch(train) [642][60/63] lr: 1.7762e-03 eta: 7:24:13 time: 0.5752 data_time: 0.0188 memory: 16131 loss: 1.1984 loss_prob: 0.6491 loss_thr: 0.4370 loss_db: 0.1123 2022/10/26 04:00:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:00:42 - mmengine - INFO - Epoch(train) [643][5/63] lr: 1.7733e-03 eta: 7:24:13 time: 0.7546 data_time: 0.2131 memory: 16131 loss: 1.3196 loss_prob: 0.7256 loss_thr: 0.4676 loss_db: 0.1264 2022/10/26 04:00:44 - mmengine - INFO - Epoch(train) [643][10/63] lr: 1.7733e-03 eta: 7:24:01 time: 0.7711 data_time: 0.2158 memory: 16131 loss: 1.2969 loss_prob: 0.7071 loss_thr: 0.4680 loss_db: 0.1218 2022/10/26 04:00:47 - mmengine - INFO - Epoch(train) [643][15/63] lr: 1.7733e-03 eta: 7:24:01 time: 0.5129 data_time: 0.0091 memory: 16131 loss: 1.2128 loss_prob: 0.6622 loss_thr: 0.4375 loss_db: 0.1131 2022/10/26 04:00:50 - mmengine - INFO - Epoch(train) [643][20/63] lr: 1.7733e-03 eta: 7:23:52 time: 0.5198 data_time: 0.0055 memory: 16131 loss: 1.1658 loss_prob: 0.6280 loss_thr: 0.4308 loss_db: 0.1070 2022/10/26 04:00:52 - mmengine - INFO - Epoch(train) [643][25/63] lr: 1.7733e-03 eta: 7:23:52 time: 0.5245 data_time: 0.0128 memory: 16131 loss: 1.2347 loss_prob: 0.6624 loss_thr: 0.4594 loss_db: 0.1129 2022/10/26 04:00:55 - mmengine - INFO - Epoch(train) [643][30/63] lr: 1.7733e-03 eta: 7:23:42 time: 0.5327 data_time: 0.0311 memory: 16131 loss: 1.2357 loss_prob: 0.6612 loss_thr: 0.4611 loss_db: 0.1133 2022/10/26 04:00:57 - mmengine - INFO - Epoch(train) [643][35/63] lr: 1.7733e-03 eta: 7:23:42 time: 0.5189 data_time: 0.0247 memory: 16131 loss: 1.2899 loss_prob: 0.6954 loss_thr: 0.4778 loss_db: 0.1166 2022/10/26 04:01:00 - mmengine - INFO - Epoch(train) [643][40/63] lr: 1.7733e-03 eta: 7:23:32 time: 0.4909 data_time: 0.0073 memory: 16131 loss: 1.2883 loss_prob: 0.6984 loss_thr: 0.4708 loss_db: 0.1192 2022/10/26 04:01:03 - mmengine - INFO - Epoch(train) [643][45/63] lr: 1.7733e-03 eta: 7:23:32 time: 0.5437 data_time: 0.0084 memory: 16131 loss: 1.2353 loss_prob: 0.6550 loss_thr: 0.4629 loss_db: 0.1174 2022/10/26 04:01:06 - mmengine - INFO - Epoch(train) [643][50/63] lr: 1.7733e-03 eta: 7:23:24 time: 0.6346 data_time: 0.0136 memory: 16131 loss: 1.2594 loss_prob: 0.6702 loss_thr: 0.4721 loss_db: 0.1171 2022/10/26 04:01:09 - mmengine - INFO - Epoch(train) [643][55/63] lr: 1.7733e-03 eta: 7:23:24 time: 0.6177 data_time: 0.0212 memory: 16131 loss: 1.2287 loss_prob: 0.6677 loss_thr: 0.4501 loss_db: 0.1109 2022/10/26 04:01:12 - mmengine - INFO - Epoch(train) [643][60/63] lr: 1.7733e-03 eta: 7:23:14 time: 0.5503 data_time: 0.0176 memory: 16131 loss: 1.2041 loss_prob: 0.6480 loss_thr: 0.4482 loss_db: 0.1079 2022/10/26 04:01:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:01:18 - mmengine - INFO - Epoch(train) [644][5/63] lr: 1.7705e-03 eta: 7:23:14 time: 0.7320 data_time: 0.1756 memory: 16131 loss: 1.2760 loss_prob: 0.6865 loss_thr: 0.4764 loss_db: 0.1131 2022/10/26 04:01:21 - mmengine - INFO - Epoch(train) [644][10/63] lr: 1.7705e-03 eta: 7:23:02 time: 0.7493 data_time: 0.1746 memory: 16131 loss: 1.2694 loss_prob: 0.6970 loss_thr: 0.4593 loss_db: 0.1131 2022/10/26 04:01:23 - mmengine - INFO - Epoch(train) [644][15/63] lr: 1.7705e-03 eta: 7:23:02 time: 0.5349 data_time: 0.0048 memory: 16131 loss: 1.3105 loss_prob: 0.7151 loss_thr: 0.4750 loss_db: 0.1204 2022/10/26 04:01:26 - mmengine - INFO - Epoch(train) [644][20/63] lr: 1.7705e-03 eta: 7:22:53 time: 0.5166 data_time: 0.0077 memory: 16131 loss: 1.2693 loss_prob: 0.6843 loss_thr: 0.4683 loss_db: 0.1167 2022/10/26 04:01:28 - mmengine - INFO - Epoch(train) [644][25/63] lr: 1.7705e-03 eta: 7:22:53 time: 0.5090 data_time: 0.0116 memory: 16131 loss: 1.2107 loss_prob: 0.6462 loss_thr: 0.4523 loss_db: 0.1122 2022/10/26 04:01:31 - mmengine - INFO - Epoch(train) [644][30/63] lr: 1.7705e-03 eta: 7:22:43 time: 0.5071 data_time: 0.0302 memory: 16131 loss: 1.2064 loss_prob: 0.6508 loss_thr: 0.4425 loss_db: 0.1131 2022/10/26 04:01:33 - mmengine - INFO - Epoch(train) [644][35/63] lr: 1.7705e-03 eta: 7:22:43 time: 0.5108 data_time: 0.0262 memory: 16131 loss: 1.2454 loss_prob: 0.6740 loss_thr: 0.4562 loss_db: 0.1153 2022/10/26 04:01:36 - mmengine - INFO - Epoch(train) [644][40/63] lr: 1.7705e-03 eta: 7:22:33 time: 0.5129 data_time: 0.0090 memory: 16131 loss: 1.2345 loss_prob: 0.6604 loss_thr: 0.4625 loss_db: 0.1116 2022/10/26 04:01:39 - mmengine - INFO - Epoch(train) [644][45/63] lr: 1.7705e-03 eta: 7:22:33 time: 0.5286 data_time: 0.0089 memory: 16131 loss: 1.2583 loss_prob: 0.6806 loss_thr: 0.4621 loss_db: 0.1157 2022/10/26 04:01:41 - mmengine - INFO - Epoch(train) [644][50/63] lr: 1.7705e-03 eta: 7:22:24 time: 0.5395 data_time: 0.0350 memory: 16131 loss: 1.2053 loss_prob: 0.6537 loss_thr: 0.4418 loss_db: 0.1098 2022/10/26 04:01:44 - mmengine - INFO - Epoch(train) [644][55/63] lr: 1.7705e-03 eta: 7:22:24 time: 0.5311 data_time: 0.0415 memory: 16131 loss: 1.1763 loss_prob: 0.6340 loss_thr: 0.4361 loss_db: 0.1062 2022/10/26 04:01:46 - mmengine - INFO - Epoch(train) [644][60/63] lr: 1.7705e-03 eta: 7:22:14 time: 0.5007 data_time: 0.0105 memory: 16131 loss: 1.2404 loss_prob: 0.6680 loss_thr: 0.4599 loss_db: 0.1125 2022/10/26 04:01:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:01:53 - mmengine - INFO - Epoch(train) [645][5/63] lr: 1.7676e-03 eta: 7:22:14 time: 0.7574 data_time: 0.2004 memory: 16131 loss: 1.2151 loss_prob: 0.6488 loss_thr: 0.4542 loss_db: 0.1121 2022/10/26 04:01:56 - mmengine - INFO - Epoch(train) [645][10/63] lr: 1.7676e-03 eta: 7:22:02 time: 0.7271 data_time: 0.2001 memory: 16131 loss: 1.2552 loss_prob: 0.6788 loss_thr: 0.4607 loss_db: 0.1158 2022/10/26 04:01:58 - mmengine - INFO - Epoch(train) [645][15/63] lr: 1.7676e-03 eta: 7:22:02 time: 0.5088 data_time: 0.0114 memory: 16131 loss: 1.2821 loss_prob: 0.6946 loss_thr: 0.4709 loss_db: 0.1166 2022/10/26 04:02:01 - mmengine - INFO - Epoch(train) [645][20/63] lr: 1.7676e-03 eta: 7:21:52 time: 0.5219 data_time: 0.0071 memory: 16131 loss: 1.3200 loss_prob: 0.7321 loss_thr: 0.4659 loss_db: 0.1220 2022/10/26 04:02:04 - mmengine - INFO - Epoch(train) [645][25/63] lr: 1.7676e-03 eta: 7:21:52 time: 0.5533 data_time: 0.0273 memory: 16131 loss: 1.2834 loss_prob: 0.7156 loss_thr: 0.4462 loss_db: 0.1215 2022/10/26 04:02:06 - mmengine - INFO - Epoch(train) [645][30/63] lr: 1.7676e-03 eta: 7:21:43 time: 0.5316 data_time: 0.0319 memory: 16131 loss: 1.3059 loss_prob: 0.7329 loss_thr: 0.4559 loss_db: 0.1171 2022/10/26 04:02:09 - mmengine - INFO - Epoch(train) [645][35/63] lr: 1.7676e-03 eta: 7:21:43 time: 0.5038 data_time: 0.0153 memory: 16131 loss: 1.2708 loss_prob: 0.7151 loss_thr: 0.4436 loss_db: 0.1122 2022/10/26 04:02:11 - mmengine - INFO - Epoch(train) [645][40/63] lr: 1.7676e-03 eta: 7:21:33 time: 0.5192 data_time: 0.0100 memory: 16131 loss: 1.1437 loss_prob: 0.6244 loss_thr: 0.4173 loss_db: 0.1021 2022/10/26 04:02:14 - mmengine - INFO - Epoch(train) [645][45/63] lr: 1.7676e-03 eta: 7:21:33 time: 0.5138 data_time: 0.0044 memory: 16131 loss: 1.2958 loss_prob: 0.7306 loss_thr: 0.4457 loss_db: 0.1195 2022/10/26 04:02:16 - mmengine - INFO - Epoch(train) [645][50/63] lr: 1.7676e-03 eta: 7:21:23 time: 0.5210 data_time: 0.0198 memory: 16131 loss: 1.3180 loss_prob: 0.7346 loss_thr: 0.4589 loss_db: 0.1245 2022/10/26 04:02:20 - mmengine - INFO - Epoch(train) [645][55/63] lr: 1.7676e-03 eta: 7:21:23 time: 0.6026 data_time: 0.0205 memory: 16131 loss: 1.1939 loss_prob: 0.6407 loss_thr: 0.4427 loss_db: 0.1105 2022/10/26 04:02:23 - mmengine - INFO - Epoch(train) [645][60/63] lr: 1.7676e-03 eta: 7:21:15 time: 0.6159 data_time: 0.0087 memory: 16131 loss: 1.2434 loss_prob: 0.6766 loss_thr: 0.4531 loss_db: 0.1137 2022/10/26 04:02:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:02:28 - mmengine - INFO - Epoch(train) [646][5/63] lr: 1.7647e-03 eta: 7:21:15 time: 0.6683 data_time: 0.1851 memory: 16131 loss: 1.3493 loss_prob: 0.7402 loss_thr: 0.4857 loss_db: 0.1234 2022/10/26 04:02:31 - mmengine - INFO - Epoch(train) [646][10/63] lr: 1.7647e-03 eta: 7:21:02 time: 0.7077 data_time: 0.1949 memory: 16131 loss: 1.2409 loss_prob: 0.6735 loss_thr: 0.4520 loss_db: 0.1154 2022/10/26 04:02:33 - mmengine - INFO - Epoch(train) [646][15/63] lr: 1.7647e-03 eta: 7:21:02 time: 0.5124 data_time: 0.0167 memory: 16131 loss: 1.2629 loss_prob: 0.6969 loss_thr: 0.4494 loss_db: 0.1166 2022/10/26 04:02:36 - mmengine - INFO - Epoch(train) [646][20/63] lr: 1.7647e-03 eta: 7:20:53 time: 0.5284 data_time: 0.0068 memory: 16131 loss: 1.3180 loss_prob: 0.7212 loss_thr: 0.4795 loss_db: 0.1173 2022/10/26 04:02:39 - mmengine - INFO - Epoch(train) [646][25/63] lr: 1.7647e-03 eta: 7:20:53 time: 0.5701 data_time: 0.0177 memory: 16131 loss: 1.3144 loss_prob: 0.7228 loss_thr: 0.4696 loss_db: 0.1220 2022/10/26 04:02:42 - mmengine - INFO - Epoch(train) [646][30/63] lr: 1.7647e-03 eta: 7:20:44 time: 0.5601 data_time: 0.0356 memory: 16131 loss: 1.3223 loss_prob: 0.7303 loss_thr: 0.4686 loss_db: 0.1234 2022/10/26 04:02:44 - mmengine - INFO - Epoch(train) [646][35/63] lr: 1.7647e-03 eta: 7:20:44 time: 0.5200 data_time: 0.0264 memory: 16131 loss: 1.3939 loss_prob: 0.7813 loss_thr: 0.4861 loss_db: 0.1265 2022/10/26 04:02:47 - mmengine - INFO - Epoch(train) [646][40/63] lr: 1.7647e-03 eta: 7:20:34 time: 0.5157 data_time: 0.0094 memory: 16131 loss: 1.3947 loss_prob: 0.7836 loss_thr: 0.4841 loss_db: 0.1270 2022/10/26 04:02:49 - mmengine - INFO - Epoch(train) [646][45/63] lr: 1.7647e-03 eta: 7:20:34 time: 0.5025 data_time: 0.0059 memory: 16131 loss: 1.2850 loss_prob: 0.7034 loss_thr: 0.4621 loss_db: 0.1195 2022/10/26 04:02:52 - mmengine - INFO - Epoch(train) [646][50/63] lr: 1.7647e-03 eta: 7:20:25 time: 0.5319 data_time: 0.0199 memory: 16131 loss: 1.2330 loss_prob: 0.6721 loss_thr: 0.4472 loss_db: 0.1137 2022/10/26 04:02:55 - mmengine - INFO - Epoch(train) [646][55/63] lr: 1.7647e-03 eta: 7:20:25 time: 0.5753 data_time: 0.0288 memory: 16131 loss: 1.2956 loss_prob: 0.7032 loss_thr: 0.4696 loss_db: 0.1228 2022/10/26 04:02:58 - mmengine - INFO - Epoch(train) [646][60/63] lr: 1.7647e-03 eta: 7:20:15 time: 0.5411 data_time: 0.0138 memory: 16131 loss: 1.4372 loss_prob: 0.7854 loss_thr: 0.5187 loss_db: 0.1331 2022/10/26 04:02:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:03:03 - mmengine - INFO - Epoch(train) [647][5/63] lr: 1.7619e-03 eta: 7:20:15 time: 0.6520 data_time: 0.1595 memory: 16131 loss: 1.4422 loss_prob: 0.8029 loss_thr: 0.5071 loss_db: 0.1322 2022/10/26 04:03:06 - mmengine - INFO - Epoch(train) [647][10/63] lr: 1.7619e-03 eta: 7:20:03 time: 0.7135 data_time: 0.1728 memory: 16131 loss: 1.3134 loss_prob: 0.7187 loss_thr: 0.4750 loss_db: 0.1196 2022/10/26 04:03:09 - mmengine - INFO - Epoch(train) [647][15/63] lr: 1.7619e-03 eta: 7:20:03 time: 0.5441 data_time: 0.0230 memory: 16131 loss: 1.1877 loss_prob: 0.6225 loss_thr: 0.4586 loss_db: 0.1066 2022/10/26 04:03:11 - mmengine - INFO - Epoch(train) [647][20/63] lr: 1.7619e-03 eta: 7:19:53 time: 0.5204 data_time: 0.0095 memory: 16131 loss: 1.2469 loss_prob: 0.6536 loss_thr: 0.4822 loss_db: 0.1111 2022/10/26 04:03:14 - mmengine - INFO - Epoch(train) [647][25/63] lr: 1.7619e-03 eta: 7:19:53 time: 0.5067 data_time: 0.0097 memory: 16131 loss: 1.3440 loss_prob: 0.7225 loss_thr: 0.4997 loss_db: 0.1218 2022/10/26 04:03:16 - mmengine - INFO - Epoch(train) [647][30/63] lr: 1.7619e-03 eta: 7:19:44 time: 0.5272 data_time: 0.0316 memory: 16131 loss: 1.3309 loss_prob: 0.7290 loss_thr: 0.4794 loss_db: 0.1225 2022/10/26 04:03:19 - mmengine - INFO - Epoch(train) [647][35/63] lr: 1.7619e-03 eta: 7:19:44 time: 0.5143 data_time: 0.0296 memory: 16131 loss: 1.2566 loss_prob: 0.6813 loss_thr: 0.4601 loss_db: 0.1152 2022/10/26 04:03:21 - mmengine - INFO - Epoch(train) [647][40/63] lr: 1.7619e-03 eta: 7:19:34 time: 0.4951 data_time: 0.0086 memory: 16131 loss: 1.2352 loss_prob: 0.6652 loss_thr: 0.4566 loss_db: 0.1135 2022/10/26 04:03:24 - mmengine - INFO - Epoch(train) [647][45/63] lr: 1.7619e-03 eta: 7:19:34 time: 0.5203 data_time: 0.0089 memory: 16131 loss: 1.1917 loss_prob: 0.6432 loss_thr: 0.4384 loss_db: 0.1100 2022/10/26 04:03:27 - mmengine - INFO - Epoch(train) [647][50/63] lr: 1.7619e-03 eta: 7:19:25 time: 0.5388 data_time: 0.0102 memory: 16131 loss: 1.1991 loss_prob: 0.6471 loss_thr: 0.4424 loss_db: 0.1096 2022/10/26 04:03:29 - mmengine - INFO - Epoch(train) [647][55/63] lr: 1.7619e-03 eta: 7:19:25 time: 0.5313 data_time: 0.0202 memory: 16131 loss: 1.2455 loss_prob: 0.6735 loss_thr: 0.4569 loss_db: 0.1151 2022/10/26 04:03:32 - mmengine - INFO - Epoch(train) [647][60/63] lr: 1.7619e-03 eta: 7:19:15 time: 0.5182 data_time: 0.0222 memory: 16131 loss: 1.1874 loss_prob: 0.6403 loss_thr: 0.4369 loss_db: 0.1102 2022/10/26 04:03:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:03:38 - mmengine - INFO - Epoch(train) [648][5/63] lr: 1.7590e-03 eta: 7:19:15 time: 0.6983 data_time: 0.2089 memory: 16131 loss: 1.2453 loss_prob: 0.6753 loss_thr: 0.4546 loss_db: 0.1155 2022/10/26 04:03:41 - mmengine - INFO - Epoch(train) [648][10/63] lr: 1.7590e-03 eta: 7:19:03 time: 0.7481 data_time: 0.1990 memory: 16131 loss: 1.2230 loss_prob: 0.6523 loss_thr: 0.4570 loss_db: 0.1137 2022/10/26 04:03:44 - mmengine - INFO - Epoch(train) [648][15/63] lr: 1.7590e-03 eta: 7:19:03 time: 0.6100 data_time: 0.0085 memory: 16131 loss: 1.2059 loss_prob: 0.6431 loss_thr: 0.4533 loss_db: 0.1094 2022/10/26 04:03:47 - mmengine - INFO - Epoch(train) [648][20/63] lr: 1.7590e-03 eta: 7:18:54 time: 0.6032 data_time: 0.0054 memory: 16131 loss: 1.1916 loss_prob: 0.6377 loss_thr: 0.4438 loss_db: 0.1101 2022/10/26 04:03:49 - mmengine - INFO - Epoch(train) [648][25/63] lr: 1.7590e-03 eta: 7:18:54 time: 0.5370 data_time: 0.0225 memory: 16131 loss: 1.2025 loss_prob: 0.6499 loss_thr: 0.4400 loss_db: 0.1127 2022/10/26 04:03:52 - mmengine - INFO - Epoch(train) [648][30/63] lr: 1.7590e-03 eta: 7:18:45 time: 0.5219 data_time: 0.0362 memory: 16131 loss: 1.3069 loss_prob: 0.7049 loss_thr: 0.4803 loss_db: 0.1217 2022/10/26 04:03:54 - mmengine - INFO - Epoch(train) [648][35/63] lr: 1.7590e-03 eta: 7:18:45 time: 0.4996 data_time: 0.0214 memory: 16131 loss: 1.2448 loss_prob: 0.6618 loss_thr: 0.4692 loss_db: 0.1139 2022/10/26 04:03:57 - mmengine - INFO - Epoch(train) [648][40/63] lr: 1.7590e-03 eta: 7:18:35 time: 0.4955 data_time: 0.0074 memory: 16131 loss: 1.2265 loss_prob: 0.6573 loss_thr: 0.4566 loss_db: 0.1126 2022/10/26 04:04:00 - mmengine - INFO - Epoch(train) [648][45/63] lr: 1.7590e-03 eta: 7:18:35 time: 0.5052 data_time: 0.0054 memory: 16131 loss: 1.2708 loss_prob: 0.6954 loss_thr: 0.4571 loss_db: 0.1183 2022/10/26 04:04:02 - mmengine - INFO - Epoch(train) [648][50/63] lr: 1.7590e-03 eta: 7:18:25 time: 0.5210 data_time: 0.0157 memory: 16131 loss: 1.2169 loss_prob: 0.6591 loss_thr: 0.4465 loss_db: 0.1114 2022/10/26 04:04:05 - mmengine - INFO - Epoch(train) [648][55/63] lr: 1.7590e-03 eta: 7:18:25 time: 0.5228 data_time: 0.0243 memory: 16131 loss: 1.3042 loss_prob: 0.7098 loss_thr: 0.4742 loss_db: 0.1202 2022/10/26 04:04:07 - mmengine - INFO - Epoch(train) [648][60/63] lr: 1.7590e-03 eta: 7:18:16 time: 0.4966 data_time: 0.0138 memory: 16131 loss: 1.3555 loss_prob: 0.7426 loss_thr: 0.4865 loss_db: 0.1263 2022/10/26 04:04:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:04:13 - mmengine - INFO - Epoch(train) [649][5/63] lr: 1.7561e-03 eta: 7:18:16 time: 0.7012 data_time: 0.1807 memory: 16131 loss: 1.1392 loss_prob: 0.6147 loss_thr: 0.4175 loss_db: 0.1071 2022/10/26 04:04:16 - mmengine - INFO - Epoch(train) [649][10/63] lr: 1.7561e-03 eta: 7:18:03 time: 0.7045 data_time: 0.1800 memory: 16131 loss: 1.1867 loss_prob: 0.6334 loss_thr: 0.4436 loss_db: 0.1098 2022/10/26 04:04:18 - mmengine - INFO - Epoch(train) [649][15/63] lr: 1.7561e-03 eta: 7:18:03 time: 0.5014 data_time: 0.0060 memory: 16131 loss: 1.2891 loss_prob: 0.6977 loss_thr: 0.4738 loss_db: 0.1175 2022/10/26 04:04:21 - mmengine - INFO - Epoch(train) [649][20/63] lr: 1.7561e-03 eta: 7:17:54 time: 0.5070 data_time: 0.0069 memory: 16131 loss: 1.2122 loss_prob: 0.6539 loss_thr: 0.4471 loss_db: 0.1112 2022/10/26 04:04:24 - mmengine - INFO - Epoch(train) [649][25/63] lr: 1.7561e-03 eta: 7:17:54 time: 0.5534 data_time: 0.0231 memory: 16131 loss: 1.1859 loss_prob: 0.6305 loss_thr: 0.4472 loss_db: 0.1083 2022/10/26 04:04:27 - mmengine - INFO - Epoch(train) [649][30/63] lr: 1.7561e-03 eta: 7:17:45 time: 0.5888 data_time: 0.0587 memory: 16131 loss: 1.1855 loss_prob: 0.6392 loss_thr: 0.4387 loss_db: 0.1076 2022/10/26 04:04:29 - mmengine - INFO - Epoch(train) [649][35/63] lr: 1.7561e-03 eta: 7:17:45 time: 0.5322 data_time: 0.0415 memory: 16131 loss: 1.2090 loss_prob: 0.6571 loss_thr: 0.4394 loss_db: 0.1126 2022/10/26 04:04:32 - mmengine - INFO - Epoch(train) [649][40/63] lr: 1.7561e-03 eta: 7:17:35 time: 0.5069 data_time: 0.0081 memory: 16131 loss: 1.2179 loss_prob: 0.6504 loss_thr: 0.4548 loss_db: 0.1127 2022/10/26 04:04:34 - mmengine - INFO - Epoch(train) [649][45/63] lr: 1.7561e-03 eta: 7:17:35 time: 0.5349 data_time: 0.0078 memory: 16131 loss: 1.1916 loss_prob: 0.6299 loss_thr: 0.4533 loss_db: 0.1083 2022/10/26 04:04:37 - mmengine - INFO - Epoch(train) [649][50/63] lr: 1.7561e-03 eta: 7:17:26 time: 0.5548 data_time: 0.0139 memory: 16131 loss: 1.2341 loss_prob: 0.6621 loss_thr: 0.4575 loss_db: 0.1145 2022/10/26 04:04:40 - mmengine - INFO - Epoch(train) [649][55/63] lr: 1.7561e-03 eta: 7:17:26 time: 0.5391 data_time: 0.0243 memory: 16131 loss: 1.1724 loss_prob: 0.6276 loss_thr: 0.4373 loss_db: 0.1075 2022/10/26 04:04:42 - mmengine - INFO - Epoch(train) [649][60/63] lr: 1.7561e-03 eta: 7:17:16 time: 0.5069 data_time: 0.0162 memory: 16131 loss: 1.2754 loss_prob: 0.6949 loss_thr: 0.4627 loss_db: 0.1178 2022/10/26 04:04:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:04:48 - mmengine - INFO - Epoch(train) [650][5/63] lr: 1.7533e-03 eta: 7:17:16 time: 0.6998 data_time: 0.2199 memory: 16131 loss: 1.2565 loss_prob: 0.6838 loss_thr: 0.4561 loss_db: 0.1165 2022/10/26 04:04:51 - mmengine - INFO - Epoch(train) [650][10/63] lr: 1.7533e-03 eta: 7:17:04 time: 0.7170 data_time: 0.2198 memory: 16131 loss: 1.1969 loss_prob: 0.6402 loss_thr: 0.4473 loss_db: 0.1094 2022/10/26 04:04:54 - mmengine - INFO - Epoch(train) [650][15/63] lr: 1.7533e-03 eta: 7:17:04 time: 0.5725 data_time: 0.0064 memory: 16131 loss: 1.1922 loss_prob: 0.6267 loss_thr: 0.4544 loss_db: 0.1110 2022/10/26 04:04:57 - mmengine - INFO - Epoch(train) [650][20/63] lr: 1.7533e-03 eta: 7:16:55 time: 0.5805 data_time: 0.0068 memory: 16131 loss: 1.2641 loss_prob: 0.6759 loss_thr: 0.4700 loss_db: 0.1182 2022/10/26 04:04:59 - mmengine - INFO - Epoch(train) [650][25/63] lr: 1.7533e-03 eta: 7:16:55 time: 0.5206 data_time: 0.0190 memory: 16131 loss: 1.2377 loss_prob: 0.6758 loss_thr: 0.4479 loss_db: 0.1141 2022/10/26 04:05:02 - mmengine - INFO - Epoch(train) [650][30/63] lr: 1.7533e-03 eta: 7:16:46 time: 0.5473 data_time: 0.0367 memory: 16131 loss: 1.1555 loss_prob: 0.6249 loss_thr: 0.4239 loss_db: 0.1066 2022/10/26 04:05:05 - mmengine - INFO - Epoch(train) [650][35/63] lr: 1.7533e-03 eta: 7:16:46 time: 0.5286 data_time: 0.0276 memory: 16131 loss: 1.2883 loss_prob: 0.7082 loss_thr: 0.4600 loss_db: 0.1201 2022/10/26 04:05:07 - mmengine - INFO - Epoch(train) [650][40/63] lr: 1.7533e-03 eta: 7:16:36 time: 0.4987 data_time: 0.0090 memory: 16131 loss: 1.2967 loss_prob: 0.7123 loss_thr: 0.4644 loss_db: 0.1200 2022/10/26 04:05:09 - mmengine - INFO - Epoch(train) [650][45/63] lr: 1.7533e-03 eta: 7:16:36 time: 0.4901 data_time: 0.0071 memory: 16131 loss: 1.1923 loss_prob: 0.6457 loss_thr: 0.4367 loss_db: 0.1098 2022/10/26 04:05:12 - mmengine - INFO - Epoch(train) [650][50/63] lr: 1.7533e-03 eta: 7:16:26 time: 0.5046 data_time: 0.0190 memory: 16131 loss: 1.2073 loss_prob: 0.6581 loss_thr: 0.4383 loss_db: 0.1109 2022/10/26 04:05:15 - mmengine - INFO - Epoch(train) [650][55/63] lr: 1.7533e-03 eta: 7:16:26 time: 0.5227 data_time: 0.0227 memory: 16131 loss: 1.2134 loss_prob: 0.6604 loss_thr: 0.4411 loss_db: 0.1119 2022/10/26 04:05:17 - mmengine - INFO - Epoch(train) [650][60/63] lr: 1.7533e-03 eta: 7:16:17 time: 0.5195 data_time: 0.0119 memory: 16131 loss: 1.1943 loss_prob: 0.6396 loss_thr: 0.4455 loss_db: 0.1092 2022/10/26 04:05:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:05:23 - mmengine - INFO - Epoch(train) [651][5/63] lr: 1.7504e-03 eta: 7:16:17 time: 0.7081 data_time: 0.1748 memory: 16131 loss: 1.2758 loss_prob: 0.6870 loss_thr: 0.4702 loss_db: 0.1186 2022/10/26 04:05:26 - mmengine - INFO - Epoch(train) [651][10/63] lr: 1.7504e-03 eta: 7:16:05 time: 0.7254 data_time: 0.1760 memory: 16131 loss: 1.2383 loss_prob: 0.6619 loss_thr: 0.4632 loss_db: 0.1132 2022/10/26 04:05:28 - mmengine - INFO - Epoch(train) [651][15/63] lr: 1.7504e-03 eta: 7:16:05 time: 0.5259 data_time: 0.0081 memory: 16131 loss: 1.3007 loss_prob: 0.7018 loss_thr: 0.4798 loss_db: 0.1191 2022/10/26 04:05:32 - mmengine - INFO - Epoch(train) [651][20/63] lr: 1.7504e-03 eta: 7:15:56 time: 0.5952 data_time: 0.0075 memory: 16131 loss: 1.2180 loss_prob: 0.6593 loss_thr: 0.4456 loss_db: 0.1131 2022/10/26 04:05:35 - mmengine - INFO - Epoch(train) [651][25/63] lr: 1.7504e-03 eta: 7:15:56 time: 0.6161 data_time: 0.0119 memory: 16131 loss: 1.1777 loss_prob: 0.6347 loss_thr: 0.4343 loss_db: 0.1087 2022/10/26 04:05:37 - mmengine - INFO - Epoch(train) [651][30/63] lr: 1.7504e-03 eta: 7:15:47 time: 0.5654 data_time: 0.0327 memory: 16131 loss: 1.2586 loss_prob: 0.6794 loss_thr: 0.4638 loss_db: 0.1154 2022/10/26 04:05:40 - mmengine - INFO - Epoch(train) [651][35/63] lr: 1.7504e-03 eta: 7:15:47 time: 0.5692 data_time: 0.0267 memory: 16131 loss: 1.1728 loss_prob: 0.6236 loss_thr: 0.4412 loss_db: 0.1081 2022/10/26 04:05:43 - mmengine - INFO - Epoch(train) [651][40/63] lr: 1.7504e-03 eta: 7:15:37 time: 0.5514 data_time: 0.0052 memory: 16131 loss: 1.0657 loss_prob: 0.5615 loss_thr: 0.4054 loss_db: 0.0987 2022/10/26 04:05:46 - mmengine - INFO - Epoch(train) [651][45/63] lr: 1.7504e-03 eta: 7:15:37 time: 0.5358 data_time: 0.0067 memory: 16131 loss: 1.1508 loss_prob: 0.6196 loss_thr: 0.4246 loss_db: 0.1066 2022/10/26 04:05:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:05:48 - mmengine - INFO - Epoch(train) [651][50/63] lr: 1.7504e-03 eta: 7:15:28 time: 0.5329 data_time: 0.0146 memory: 16131 loss: 1.2033 loss_prob: 0.6530 loss_thr: 0.4415 loss_db: 0.1088 2022/10/26 04:05:51 - mmengine - INFO - Epoch(train) [651][55/63] lr: 1.7504e-03 eta: 7:15:28 time: 0.5076 data_time: 0.0228 memory: 16131 loss: 1.2139 loss_prob: 0.6548 loss_thr: 0.4492 loss_db: 0.1099 2022/10/26 04:05:53 - mmengine - INFO - Epoch(train) [651][60/63] lr: 1.7504e-03 eta: 7:15:18 time: 0.5013 data_time: 0.0151 memory: 16131 loss: 1.2447 loss_prob: 0.6682 loss_thr: 0.4618 loss_db: 0.1146 2022/10/26 04:05:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:05:59 - mmengine - INFO - Epoch(train) [652][5/63] lr: 1.7475e-03 eta: 7:15:18 time: 0.6781 data_time: 0.1920 memory: 16131 loss: 1.1587 loss_prob: 0.6186 loss_thr: 0.4363 loss_db: 0.1037 2022/10/26 04:06:02 - mmengine - INFO - Epoch(train) [652][10/63] lr: 1.7475e-03 eta: 7:15:06 time: 0.7219 data_time: 0.1920 memory: 16131 loss: 1.1639 loss_prob: 0.6143 loss_thr: 0.4438 loss_db: 0.1058 2022/10/26 04:06:04 - mmengine - INFO - Epoch(train) [652][15/63] lr: 1.7475e-03 eta: 7:15:06 time: 0.5338 data_time: 0.0062 memory: 16131 loss: 1.2298 loss_prob: 0.6611 loss_thr: 0.4544 loss_db: 0.1143 2022/10/26 04:06:07 - mmengine - INFO - Epoch(train) [652][20/63] lr: 1.7475e-03 eta: 7:14:57 time: 0.5027 data_time: 0.0076 memory: 16131 loss: 1.2548 loss_prob: 0.6772 loss_thr: 0.4605 loss_db: 0.1170 2022/10/26 04:06:09 - mmengine - INFO - Epoch(train) [652][25/63] lr: 1.7475e-03 eta: 7:14:57 time: 0.4995 data_time: 0.0150 memory: 16131 loss: 1.3443 loss_prob: 0.7275 loss_thr: 0.4973 loss_db: 0.1195 2022/10/26 04:06:12 - mmengine - INFO - Epoch(train) [652][30/63] lr: 1.7475e-03 eta: 7:14:47 time: 0.5064 data_time: 0.0307 memory: 16131 loss: 1.4284 loss_prob: 0.7830 loss_thr: 0.5151 loss_db: 0.1303 2022/10/26 04:06:14 - mmengine - INFO - Epoch(train) [652][35/63] lr: 1.7475e-03 eta: 7:14:47 time: 0.4980 data_time: 0.0220 memory: 16131 loss: 1.3028 loss_prob: 0.7088 loss_thr: 0.4699 loss_db: 0.1241 2022/10/26 04:06:17 - mmengine - INFO - Epoch(train) [652][40/63] lr: 1.7475e-03 eta: 7:14:37 time: 0.4928 data_time: 0.0049 memory: 16131 loss: 1.2552 loss_prob: 0.6848 loss_thr: 0.4536 loss_db: 0.1168 2022/10/26 04:06:19 - mmengine - INFO - Epoch(train) [652][45/63] lr: 1.7475e-03 eta: 7:14:37 time: 0.4824 data_time: 0.0065 memory: 16131 loss: 1.2665 loss_prob: 0.7004 loss_thr: 0.4473 loss_db: 0.1187 2022/10/26 04:06:22 - mmengine - INFO - Epoch(train) [652][50/63] lr: 1.7475e-03 eta: 7:14:27 time: 0.4897 data_time: 0.0164 memory: 16131 loss: 1.2940 loss_prob: 0.7105 loss_thr: 0.4606 loss_db: 0.1228 2022/10/26 04:06:24 - mmengine - INFO - Epoch(train) [652][55/63] lr: 1.7475e-03 eta: 7:14:27 time: 0.5229 data_time: 0.0216 memory: 16131 loss: 1.2507 loss_prob: 0.6778 loss_thr: 0.4549 loss_db: 0.1180 2022/10/26 04:06:28 - mmengine - INFO - Epoch(train) [652][60/63] lr: 1.7475e-03 eta: 7:14:18 time: 0.5890 data_time: 0.0124 memory: 16131 loss: 1.1374 loss_prob: 0.6151 loss_thr: 0.4160 loss_db: 0.1063 2022/10/26 04:06:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:06:34 - mmengine - INFO - Epoch(train) [653][5/63] lr: 1.7447e-03 eta: 7:14:18 time: 0.7568 data_time: 0.1652 memory: 16131 loss: 1.3310 loss_prob: 0.7279 loss_thr: 0.4824 loss_db: 0.1207 2022/10/26 04:06:37 - mmengine - INFO - Epoch(train) [653][10/63] lr: 1.7447e-03 eta: 7:14:07 time: 0.7620 data_time: 0.1676 memory: 16131 loss: 1.2992 loss_prob: 0.7095 loss_thr: 0.4686 loss_db: 0.1211 2022/10/26 04:06:39 - mmengine - INFO - Epoch(train) [653][15/63] lr: 1.7447e-03 eta: 7:14:07 time: 0.5217 data_time: 0.0155 memory: 16131 loss: 1.2195 loss_prob: 0.6686 loss_thr: 0.4367 loss_db: 0.1142 2022/10/26 04:06:42 - mmengine - INFO - Epoch(train) [653][20/63] lr: 1.7447e-03 eta: 7:13:57 time: 0.5151 data_time: 0.0135 memory: 16131 loss: 1.2409 loss_prob: 0.6786 loss_thr: 0.4468 loss_db: 0.1155 2022/10/26 04:06:44 - mmengine - INFO - Epoch(train) [653][25/63] lr: 1.7447e-03 eta: 7:13:57 time: 0.5134 data_time: 0.0169 memory: 16131 loss: 1.2184 loss_prob: 0.6554 loss_thr: 0.4496 loss_db: 0.1133 2022/10/26 04:06:47 - mmengine - INFO - Epoch(train) [653][30/63] lr: 1.7447e-03 eta: 7:13:48 time: 0.4941 data_time: 0.0245 memory: 16131 loss: 1.1435 loss_prob: 0.6052 loss_thr: 0.4331 loss_db: 0.1052 2022/10/26 04:06:49 - mmengine - INFO - Epoch(train) [653][35/63] lr: 1.7447e-03 eta: 7:13:48 time: 0.4944 data_time: 0.0128 memory: 16131 loss: 1.2233 loss_prob: 0.6593 loss_thr: 0.4526 loss_db: 0.1114 2022/10/26 04:06:52 - mmengine - INFO - Epoch(train) [653][40/63] lr: 1.7447e-03 eta: 7:13:38 time: 0.5122 data_time: 0.0125 memory: 16131 loss: 1.2458 loss_prob: 0.6839 loss_thr: 0.4494 loss_db: 0.1125 2022/10/26 04:06:54 - mmengine - INFO - Epoch(train) [653][45/63] lr: 1.7447e-03 eta: 7:13:38 time: 0.5226 data_time: 0.0120 memory: 16131 loss: 1.2183 loss_prob: 0.6616 loss_thr: 0.4471 loss_db: 0.1097 2022/10/26 04:06:57 - mmengine - INFO - Epoch(train) [653][50/63] lr: 1.7447e-03 eta: 7:13:28 time: 0.5253 data_time: 0.0211 memory: 16131 loss: 1.2080 loss_prob: 0.6623 loss_thr: 0.4377 loss_db: 0.1081 2022/10/26 04:06:59 - mmengine - INFO - Epoch(train) [653][55/63] lr: 1.7447e-03 eta: 7:13:28 time: 0.4991 data_time: 0.0213 memory: 16131 loss: 1.2927 loss_prob: 0.7190 loss_thr: 0.4588 loss_db: 0.1148 2022/10/26 04:07:02 - mmengine - INFO - Epoch(train) [653][60/63] lr: 1.7447e-03 eta: 7:13:19 time: 0.4935 data_time: 0.0062 memory: 16131 loss: 1.3128 loss_prob: 0.7184 loss_thr: 0.4756 loss_db: 0.1188 2022/10/26 04:07:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:07:08 - mmengine - INFO - Epoch(train) [654][5/63] lr: 1.7418e-03 eta: 7:13:19 time: 0.7162 data_time: 0.2035 memory: 16131 loss: 1.2406 loss_prob: 0.6634 loss_thr: 0.4650 loss_db: 0.1123 2022/10/26 04:07:11 - mmengine - INFO - Epoch(train) [654][10/63] lr: 1.7418e-03 eta: 7:13:07 time: 0.7442 data_time: 0.1994 memory: 16131 loss: 1.1982 loss_prob: 0.6381 loss_thr: 0.4512 loss_db: 0.1089 2022/10/26 04:07:13 - mmengine - INFO - Epoch(train) [654][15/63] lr: 1.7418e-03 eta: 7:13:07 time: 0.5091 data_time: 0.0083 memory: 16131 loss: 1.1297 loss_prob: 0.5995 loss_thr: 0.4267 loss_db: 0.1035 2022/10/26 04:07:16 - mmengine - INFO - Epoch(train) [654][20/63] lr: 1.7418e-03 eta: 7:12:57 time: 0.5134 data_time: 0.0084 memory: 16131 loss: 1.1131 loss_prob: 0.5843 loss_thr: 0.4288 loss_db: 0.1000 2022/10/26 04:07:19 - mmengine - INFO - Epoch(train) [654][25/63] lr: 1.7418e-03 eta: 7:12:57 time: 0.5541 data_time: 0.0299 memory: 16131 loss: 1.1179 loss_prob: 0.5762 loss_thr: 0.4438 loss_db: 0.0980 2022/10/26 04:07:21 - mmengine - INFO - Epoch(train) [654][30/63] lr: 1.7418e-03 eta: 7:12:48 time: 0.5448 data_time: 0.0318 memory: 16131 loss: 1.2059 loss_prob: 0.6399 loss_thr: 0.4571 loss_db: 0.1090 2022/10/26 04:07:24 - mmengine - INFO - Epoch(train) [654][35/63] lr: 1.7418e-03 eta: 7:12:48 time: 0.5182 data_time: 0.0105 memory: 16131 loss: 1.2077 loss_prob: 0.6612 loss_thr: 0.4363 loss_db: 0.1102 2022/10/26 04:07:26 - mmengine - INFO - Epoch(train) [654][40/63] lr: 1.7418e-03 eta: 7:12:39 time: 0.5130 data_time: 0.0116 memory: 16131 loss: 1.1766 loss_prob: 0.6370 loss_thr: 0.4337 loss_db: 0.1059 2022/10/26 04:07:29 - mmengine - INFO - Epoch(train) [654][45/63] lr: 1.7418e-03 eta: 7:12:39 time: 0.5145 data_time: 0.0150 memory: 16131 loss: 1.1420 loss_prob: 0.6105 loss_thr: 0.4272 loss_db: 0.1043 2022/10/26 04:07:32 - mmengine - INFO - Epoch(train) [654][50/63] lr: 1.7418e-03 eta: 7:12:29 time: 0.5312 data_time: 0.0243 memory: 16131 loss: 1.1476 loss_prob: 0.6179 loss_thr: 0.4225 loss_db: 0.1072 2022/10/26 04:07:34 - mmengine - INFO - Epoch(train) [654][55/63] lr: 1.7418e-03 eta: 7:12:29 time: 0.5203 data_time: 0.0200 memory: 16131 loss: 1.1979 loss_prob: 0.6472 loss_thr: 0.4396 loss_db: 0.1111 2022/10/26 04:07:37 - mmengine - INFO - Epoch(train) [654][60/63] lr: 1.7418e-03 eta: 7:12:19 time: 0.5031 data_time: 0.0081 memory: 16131 loss: 1.1562 loss_prob: 0.6247 loss_thr: 0.4268 loss_db: 0.1047 2022/10/26 04:07:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:07:43 - mmengine - INFO - Epoch(train) [655][5/63] lr: 1.7389e-03 eta: 7:12:19 time: 0.7247 data_time: 0.2157 memory: 16131 loss: 1.1982 loss_prob: 0.6398 loss_thr: 0.4503 loss_db: 0.1081 2022/10/26 04:07:46 - mmengine - INFO - Epoch(train) [655][10/63] lr: 1.7389e-03 eta: 7:12:08 time: 0.7435 data_time: 0.2189 memory: 16131 loss: 1.2312 loss_prob: 0.6565 loss_thr: 0.4609 loss_db: 0.1139 2022/10/26 04:07:48 - mmengine - INFO - Epoch(train) [655][15/63] lr: 1.7389e-03 eta: 7:12:08 time: 0.5461 data_time: 0.0139 memory: 16131 loss: 1.2857 loss_prob: 0.7002 loss_thr: 0.4650 loss_db: 0.1205 2022/10/26 04:07:51 - mmengine - INFO - Epoch(train) [655][20/63] lr: 1.7389e-03 eta: 7:11:58 time: 0.5301 data_time: 0.0088 memory: 16131 loss: 1.1527 loss_prob: 0.6296 loss_thr: 0.4178 loss_db: 0.1053 2022/10/26 04:07:54 - mmengine - INFO - Epoch(train) [655][25/63] lr: 1.7389e-03 eta: 7:11:58 time: 0.5068 data_time: 0.0165 memory: 16131 loss: 1.1246 loss_prob: 0.6120 loss_thr: 0.4109 loss_db: 0.1018 2022/10/26 04:07:56 - mmengine - INFO - Epoch(train) [655][30/63] lr: 1.7389e-03 eta: 7:11:49 time: 0.5416 data_time: 0.0340 memory: 16131 loss: 1.2512 loss_prob: 0.6894 loss_thr: 0.4448 loss_db: 0.1170 2022/10/26 04:07:59 - mmengine - INFO - Epoch(train) [655][35/63] lr: 1.7389e-03 eta: 7:11:49 time: 0.5537 data_time: 0.0266 memory: 16131 loss: 1.3118 loss_prob: 0.7192 loss_thr: 0.4686 loss_db: 0.1240 2022/10/26 04:08:02 - mmengine - INFO - Epoch(train) [655][40/63] lr: 1.7389e-03 eta: 7:11:40 time: 0.5218 data_time: 0.0091 memory: 16131 loss: 1.3452 loss_prob: 0.7410 loss_thr: 0.4774 loss_db: 0.1268 2022/10/26 04:08:04 - mmengine - INFO - Epoch(train) [655][45/63] lr: 1.7389e-03 eta: 7:11:40 time: 0.5032 data_time: 0.0063 memory: 16131 loss: 1.3261 loss_prob: 0.7334 loss_thr: 0.4681 loss_db: 0.1245 2022/10/26 04:08:07 - mmengine - INFO - Epoch(train) [655][50/63] lr: 1.7389e-03 eta: 7:11:30 time: 0.5214 data_time: 0.0120 memory: 16131 loss: 1.2953 loss_prob: 0.7081 loss_thr: 0.4648 loss_db: 0.1224 2022/10/26 04:08:10 - mmengine - INFO - Epoch(train) [655][55/63] lr: 1.7389e-03 eta: 7:11:30 time: 0.5459 data_time: 0.0215 memory: 16131 loss: 1.3285 loss_prob: 0.7311 loss_thr: 0.4697 loss_db: 0.1277 2022/10/26 04:08:12 - mmengine - INFO - Epoch(train) [655][60/63] lr: 1.7389e-03 eta: 7:11:21 time: 0.5153 data_time: 0.0160 memory: 16131 loss: 1.2888 loss_prob: 0.7150 loss_thr: 0.4534 loss_db: 0.1204 2022/10/26 04:08:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:08:18 - mmengine - INFO - Epoch(train) [656][5/63] lr: 1.7360e-03 eta: 7:11:21 time: 0.7256 data_time: 0.2035 memory: 16131 loss: 1.2535 loss_prob: 0.6872 loss_thr: 0.4502 loss_db: 0.1161 2022/10/26 04:08:21 - mmengine - INFO - Epoch(train) [656][10/63] lr: 1.7360e-03 eta: 7:11:09 time: 0.7627 data_time: 0.2037 memory: 16131 loss: 1.2637 loss_prob: 0.6961 loss_thr: 0.4473 loss_db: 0.1203 2022/10/26 04:08:24 - mmengine - INFO - Epoch(train) [656][15/63] lr: 1.7360e-03 eta: 7:11:09 time: 0.5270 data_time: 0.0071 memory: 16131 loss: 1.3204 loss_prob: 0.7314 loss_thr: 0.4636 loss_db: 0.1254 2022/10/26 04:08:26 - mmengine - INFO - Epoch(train) [656][20/63] lr: 1.7360e-03 eta: 7:10:59 time: 0.5059 data_time: 0.0082 memory: 16131 loss: 1.2496 loss_prob: 0.6778 loss_thr: 0.4578 loss_db: 0.1139 2022/10/26 04:08:29 - mmengine - INFO - Epoch(train) [656][25/63] lr: 1.7360e-03 eta: 7:10:59 time: 0.5184 data_time: 0.0305 memory: 16131 loss: 1.2392 loss_prob: 0.6748 loss_thr: 0.4527 loss_db: 0.1117 2022/10/26 04:08:31 - mmengine - INFO - Epoch(train) [656][30/63] lr: 1.7360e-03 eta: 7:10:50 time: 0.5078 data_time: 0.0300 memory: 16131 loss: 1.3019 loss_prob: 0.7228 loss_thr: 0.4574 loss_db: 0.1217 2022/10/26 04:08:34 - mmengine - INFO - Epoch(train) [656][35/63] lr: 1.7360e-03 eta: 7:10:50 time: 0.4830 data_time: 0.0052 memory: 16131 loss: 1.1704 loss_prob: 0.6320 loss_thr: 0.4298 loss_db: 0.1086 2022/10/26 04:08:37 - mmengine - INFO - Epoch(train) [656][40/63] lr: 1.7360e-03 eta: 7:10:41 time: 0.5720 data_time: 0.0084 memory: 16131 loss: 1.2052 loss_prob: 0.6561 loss_thr: 0.4376 loss_db: 0.1115 2022/10/26 04:08:40 - mmengine - INFO - Epoch(train) [656][45/63] lr: 1.7360e-03 eta: 7:10:41 time: 0.6160 data_time: 0.0097 memory: 16131 loss: 1.3042 loss_prob: 0.7105 loss_thr: 0.4734 loss_db: 0.1202 2022/10/26 04:08:42 - mmengine - INFO - Epoch(train) [656][50/63] lr: 1.7360e-03 eta: 7:10:31 time: 0.5472 data_time: 0.0216 memory: 16131 loss: 1.2730 loss_prob: 0.6792 loss_thr: 0.4791 loss_db: 0.1147 2022/10/26 04:08:45 - mmengine - INFO - Epoch(train) [656][55/63] lr: 1.7360e-03 eta: 7:10:31 time: 0.5195 data_time: 0.0201 memory: 16131 loss: 1.2312 loss_prob: 0.6582 loss_thr: 0.4605 loss_db: 0.1124 2022/10/26 04:08:47 - mmengine - INFO - Epoch(train) [656][60/63] lr: 1.7360e-03 eta: 7:10:22 time: 0.5052 data_time: 0.0055 memory: 16131 loss: 1.2518 loss_prob: 0.6725 loss_thr: 0.4639 loss_db: 0.1154 2022/10/26 04:08:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:08:54 - mmengine - INFO - Epoch(train) [657][5/63] lr: 1.7332e-03 eta: 7:10:22 time: 0.7216 data_time: 0.2136 memory: 16131 loss: 1.2115 loss_prob: 0.6545 loss_thr: 0.4480 loss_db: 0.1091 2022/10/26 04:08:56 - mmengine - INFO - Epoch(train) [657][10/63] lr: 1.7332e-03 eta: 7:10:10 time: 0.7504 data_time: 0.2124 memory: 16131 loss: 1.2317 loss_prob: 0.6592 loss_thr: 0.4612 loss_db: 0.1113 2022/10/26 04:08:59 - mmengine - INFO - Epoch(train) [657][15/63] lr: 1.7332e-03 eta: 7:10:10 time: 0.5251 data_time: 0.0063 memory: 16131 loss: 1.1869 loss_prob: 0.6442 loss_thr: 0.4290 loss_db: 0.1138 2022/10/26 04:09:02 - mmengine - INFO - Epoch(train) [657][20/63] lr: 1.7332e-03 eta: 7:10:01 time: 0.5620 data_time: 0.0059 memory: 16131 loss: 1.1874 loss_prob: 0.6440 loss_thr: 0.4300 loss_db: 0.1133 2022/10/26 04:09:05 - mmengine - INFO - Epoch(train) [657][25/63] lr: 1.7332e-03 eta: 7:10:01 time: 0.6170 data_time: 0.0345 memory: 16131 loss: 1.2147 loss_prob: 0.6516 loss_thr: 0.4523 loss_db: 0.1108 2022/10/26 04:09:08 - mmengine - INFO - Epoch(train) [657][30/63] lr: 1.7332e-03 eta: 7:09:52 time: 0.5844 data_time: 0.0394 memory: 16131 loss: 1.2543 loss_prob: 0.6740 loss_thr: 0.4665 loss_db: 0.1138 2022/10/26 04:09:10 - mmengine - INFO - Epoch(train) [657][35/63] lr: 1.7332e-03 eta: 7:09:52 time: 0.5172 data_time: 0.0096 memory: 16131 loss: 1.2185 loss_prob: 0.6518 loss_thr: 0.4539 loss_db: 0.1128 2022/10/26 04:09:13 - mmengine - INFO - Epoch(train) [657][40/63] lr: 1.7332e-03 eta: 7:09:43 time: 0.5035 data_time: 0.0045 memory: 16131 loss: 1.1792 loss_prob: 0.6351 loss_thr: 0.4332 loss_db: 0.1109 2022/10/26 04:09:15 - mmengine - INFO - Epoch(train) [657][45/63] lr: 1.7332e-03 eta: 7:09:43 time: 0.5020 data_time: 0.0081 memory: 16131 loss: 1.2492 loss_prob: 0.6709 loss_thr: 0.4669 loss_db: 0.1113 2022/10/26 04:09:18 - mmengine - INFO - Epoch(train) [657][50/63] lr: 1.7332e-03 eta: 7:09:33 time: 0.5280 data_time: 0.0241 memory: 16131 loss: 1.2648 loss_prob: 0.6823 loss_thr: 0.4682 loss_db: 0.1143 2022/10/26 04:09:21 - mmengine - INFO - Epoch(train) [657][55/63] lr: 1.7332e-03 eta: 7:09:33 time: 0.5601 data_time: 0.0244 memory: 16131 loss: 1.2527 loss_prob: 0.6825 loss_thr: 0.4521 loss_db: 0.1181 2022/10/26 04:09:23 - mmengine - INFO - Epoch(train) [657][60/63] lr: 1.7332e-03 eta: 7:09:24 time: 0.5357 data_time: 0.0096 memory: 16131 loss: 1.2576 loss_prob: 0.6791 loss_thr: 0.4620 loss_db: 0.1165 2022/10/26 04:09:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:09:29 - mmengine - INFO - Epoch(train) [658][5/63] lr: 1.7303e-03 eta: 7:09:24 time: 0.6444 data_time: 0.1686 memory: 16131 loss: 1.1864 loss_prob: 0.6262 loss_thr: 0.4537 loss_db: 0.1066 2022/10/26 04:09:31 - mmengine - INFO - Epoch(train) [658][10/63] lr: 1.7303e-03 eta: 7:09:11 time: 0.6734 data_time: 0.1739 memory: 16131 loss: 1.2706 loss_prob: 0.6807 loss_thr: 0.4735 loss_db: 0.1164 2022/10/26 04:09:34 - mmengine - INFO - Epoch(train) [658][15/63] lr: 1.7303e-03 eta: 7:09:11 time: 0.5287 data_time: 0.0123 memory: 16131 loss: 1.2833 loss_prob: 0.6990 loss_thr: 0.4639 loss_db: 0.1204 2022/10/26 04:09:37 - mmengine - INFO - Epoch(train) [658][20/63] lr: 1.7303e-03 eta: 7:09:02 time: 0.5359 data_time: 0.0063 memory: 16131 loss: 1.2189 loss_prob: 0.6539 loss_thr: 0.4514 loss_db: 0.1136 2022/10/26 04:09:40 - mmengine - INFO - Epoch(train) [658][25/63] lr: 1.7303e-03 eta: 7:09:02 time: 0.5709 data_time: 0.0169 memory: 16131 loss: 1.2129 loss_prob: 0.6506 loss_thr: 0.4500 loss_db: 0.1122 2022/10/26 04:09:42 - mmengine - INFO - Epoch(train) [658][30/63] lr: 1.7303e-03 eta: 7:08:53 time: 0.5551 data_time: 0.0271 memory: 16131 loss: 1.2606 loss_prob: 0.6896 loss_thr: 0.4525 loss_db: 0.1186 2022/10/26 04:09:45 - mmengine - INFO - Epoch(train) [658][35/63] lr: 1.7303e-03 eta: 7:08:53 time: 0.5305 data_time: 0.0208 memory: 16131 loss: 1.3948 loss_prob: 0.7980 loss_thr: 0.4580 loss_db: 0.1388 2022/10/26 04:09:48 - mmengine - INFO - Epoch(train) [658][40/63] lr: 1.7303e-03 eta: 7:08:44 time: 0.5224 data_time: 0.0105 memory: 16131 loss: 1.4231 loss_prob: 0.8220 loss_thr: 0.4539 loss_db: 0.1472 2022/10/26 04:09:50 - mmengine - INFO - Epoch(train) [658][45/63] lr: 1.7303e-03 eta: 7:08:44 time: 0.5126 data_time: 0.0044 memory: 16131 loss: 1.2826 loss_prob: 0.7080 loss_thr: 0.4521 loss_db: 0.1226 2022/10/26 04:09:53 - mmengine - INFO - Epoch(train) [658][50/63] lr: 1.7303e-03 eta: 7:08:34 time: 0.5208 data_time: 0.0133 memory: 16131 loss: 1.2172 loss_prob: 0.6596 loss_thr: 0.4476 loss_db: 0.1099 2022/10/26 04:09:55 - mmengine - INFO - Epoch(train) [658][55/63] lr: 1.7303e-03 eta: 7:08:34 time: 0.5113 data_time: 0.0211 memory: 16131 loss: 1.2201 loss_prob: 0.6532 loss_thr: 0.4533 loss_db: 0.1136 2022/10/26 04:09:58 - mmengine - INFO - Epoch(train) [658][60/63] lr: 1.7303e-03 eta: 7:08:25 time: 0.5043 data_time: 0.0126 memory: 16131 loss: 1.2809 loss_prob: 0.6822 loss_thr: 0.4812 loss_db: 0.1176 2022/10/26 04:09:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:10:03 - mmengine - INFO - Epoch(train) [659][5/63] lr: 1.7274e-03 eta: 7:08:25 time: 0.6669 data_time: 0.1971 memory: 16131 loss: 1.4895 loss_prob: 0.8671 loss_thr: 0.4769 loss_db: 0.1455 2022/10/26 04:10:06 - mmengine - INFO - Epoch(train) [659][10/63] lr: 1.7274e-03 eta: 7:08:12 time: 0.7007 data_time: 0.1965 memory: 16131 loss: 1.2973 loss_prob: 0.7213 loss_thr: 0.4550 loss_db: 0.1211 2022/10/26 04:10:09 - mmengine - INFO - Epoch(train) [659][15/63] lr: 1.7274e-03 eta: 7:08:12 time: 0.5081 data_time: 0.0052 memory: 16131 loss: 1.4287 loss_prob: 0.8071 loss_thr: 0.4845 loss_db: 0.1371 2022/10/26 04:10:12 - mmengine - INFO - Epoch(train) [659][20/63] lr: 1.7274e-03 eta: 7:08:04 time: 0.5793 data_time: 0.0071 memory: 16131 loss: 1.6235 loss_prob: 0.9520 loss_thr: 0.5121 loss_db: 0.1593 2022/10/26 04:10:14 - mmengine - INFO - Epoch(train) [659][25/63] lr: 1.7274e-03 eta: 7:08:04 time: 0.5703 data_time: 0.0157 memory: 16131 loss: 1.4912 loss_prob: 0.8520 loss_thr: 0.4946 loss_db: 0.1446 2022/10/26 04:10:17 - mmengine - INFO - Epoch(train) [659][30/63] lr: 1.7274e-03 eta: 7:07:54 time: 0.5003 data_time: 0.0340 memory: 16131 loss: 1.3702 loss_prob: 0.7598 loss_thr: 0.4807 loss_db: 0.1298 2022/10/26 04:10:19 - mmengine - INFO - Epoch(train) [659][35/63] lr: 1.7274e-03 eta: 7:07:54 time: 0.5093 data_time: 0.0252 memory: 16131 loss: 1.3631 loss_prob: 0.7429 loss_thr: 0.4962 loss_db: 0.1241 2022/10/26 04:10:22 - mmengine - INFO - Epoch(train) [659][40/63] lr: 1.7274e-03 eta: 7:07:44 time: 0.5194 data_time: 0.0047 memory: 16131 loss: 1.4146 loss_prob: 0.7717 loss_thr: 0.5153 loss_db: 0.1276 2022/10/26 04:10:25 - mmengine - INFO - Epoch(train) [659][45/63] lr: 1.7274e-03 eta: 7:07:44 time: 0.5151 data_time: 0.0069 memory: 16131 loss: 1.3294 loss_prob: 0.7407 loss_thr: 0.4656 loss_db: 0.1230 2022/10/26 04:10:27 - mmengine - INFO - Epoch(train) [659][50/63] lr: 1.7274e-03 eta: 7:07:35 time: 0.5216 data_time: 0.0225 memory: 16131 loss: 1.1749 loss_prob: 0.6448 loss_thr: 0.4215 loss_db: 0.1086 2022/10/26 04:10:30 - mmengine - INFO - Epoch(train) [659][55/63] lr: 1.7274e-03 eta: 7:07:35 time: 0.5263 data_time: 0.0244 memory: 16131 loss: 1.2008 loss_prob: 0.6543 loss_thr: 0.4340 loss_db: 0.1125 2022/10/26 04:10:32 - mmengine - INFO - Epoch(train) [659][60/63] lr: 1.7274e-03 eta: 7:07:26 time: 0.5144 data_time: 0.0093 memory: 16131 loss: 1.2728 loss_prob: 0.6879 loss_thr: 0.4695 loss_db: 0.1154 2022/10/26 04:10:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:10:38 - mmengine - INFO - Epoch(train) [660][5/63] lr: 1.7246e-03 eta: 7:07:26 time: 0.6851 data_time: 0.1828 memory: 16131 loss: 1.2651 loss_prob: 0.6794 loss_thr: 0.4696 loss_db: 0.1162 2022/10/26 04:10:41 - mmengine - INFO - Epoch(train) [660][10/63] lr: 1.7246e-03 eta: 7:07:13 time: 0.6894 data_time: 0.1881 memory: 16131 loss: 1.2749 loss_prob: 0.6852 loss_thr: 0.4719 loss_db: 0.1178 2022/10/26 04:10:44 - mmengine - INFO - Epoch(train) [660][15/63] lr: 1.7246e-03 eta: 7:07:13 time: 0.5522 data_time: 0.0126 memory: 16131 loss: 1.3167 loss_prob: 0.7169 loss_thr: 0.4789 loss_db: 0.1209 2022/10/26 04:10:46 - mmengine - INFO - Epoch(train) [660][20/63] lr: 1.7246e-03 eta: 7:07:04 time: 0.5777 data_time: 0.0084 memory: 16131 loss: 1.2192 loss_prob: 0.6630 loss_thr: 0.4445 loss_db: 0.1117 2022/10/26 04:10:49 - mmengine - INFO - Epoch(train) [660][25/63] lr: 1.7246e-03 eta: 7:07:04 time: 0.5475 data_time: 0.0228 memory: 16131 loss: 1.1528 loss_prob: 0.6152 loss_thr: 0.4319 loss_db: 0.1057 2022/10/26 04:10:52 - mmengine - INFO - Epoch(train) [660][30/63] lr: 1.7246e-03 eta: 7:06:55 time: 0.5205 data_time: 0.0292 memory: 16131 loss: 1.2458 loss_prob: 0.6613 loss_thr: 0.4693 loss_db: 0.1151 2022/10/26 04:10:54 - mmengine - INFO - Epoch(train) [660][35/63] lr: 1.7246e-03 eta: 7:06:55 time: 0.5221 data_time: 0.0184 memory: 16131 loss: 1.2103 loss_prob: 0.6449 loss_thr: 0.4544 loss_db: 0.1110 2022/10/26 04:10:57 - mmengine - INFO - Epoch(train) [660][40/63] lr: 1.7246e-03 eta: 7:06:46 time: 0.5185 data_time: 0.0107 memory: 16131 loss: 1.1819 loss_prob: 0.6328 loss_thr: 0.4442 loss_db: 0.1049 2022/10/26 04:11:00 - mmengine - INFO - Epoch(train) [660][45/63] lr: 1.7246e-03 eta: 7:06:46 time: 0.5313 data_time: 0.0065 memory: 16131 loss: 1.2855 loss_prob: 0.6992 loss_thr: 0.4694 loss_db: 0.1170 2022/10/26 04:11:02 - mmengine - INFO - Epoch(train) [660][50/63] lr: 1.7246e-03 eta: 7:06:36 time: 0.5386 data_time: 0.0158 memory: 16131 loss: 1.3385 loss_prob: 0.7365 loss_thr: 0.4754 loss_db: 0.1266 2022/10/26 04:11:05 - mmengine - INFO - Epoch(train) [660][55/63] lr: 1.7246e-03 eta: 7:06:36 time: 0.5080 data_time: 0.0211 memory: 16131 loss: 1.2891 loss_prob: 0.7056 loss_thr: 0.4649 loss_db: 0.1186 2022/10/26 04:11:08 - mmengine - INFO - Epoch(train) [660][60/63] lr: 1.7246e-03 eta: 7:06:27 time: 0.5600 data_time: 0.0139 memory: 16131 loss: 1.1698 loss_prob: 0.6246 loss_thr: 0.4401 loss_db: 0.1051 2022/10/26 04:11:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:11:09 - mmengine - INFO - Saving checkpoint at 660 epochs 2022/10/26 04:11:16 - mmengine - INFO - Epoch(val) [660][5/32] eta: 7:06:27 time: 0.5394 data_time: 0.0842 memory: 16131 2022/10/26 04:11:19 - mmengine - INFO - Epoch(val) [660][10/32] eta: 0:00:13 time: 0.6207 data_time: 0.1234 memory: 15724 2022/10/26 04:11:22 - mmengine - INFO - Epoch(val) [660][15/32] eta: 0:00:13 time: 0.5587 data_time: 0.0554 memory: 15724 2022/10/26 04:11:25 - mmengine - INFO - Epoch(val) [660][20/32] eta: 0:00:06 time: 0.5586 data_time: 0.0542 memory: 15724 2022/10/26 04:11:28 - mmengine - INFO - Epoch(val) [660][25/32] eta: 0:00:06 time: 0.5673 data_time: 0.0560 memory: 15724 2022/10/26 04:11:30 - mmengine - INFO - Epoch(val) [660][30/32] eta: 0:00:01 time: 0.5250 data_time: 0.0235 memory: 15724 2022/10/26 04:11:31 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8151, precision: 0.7351, hmean: 0.7731 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8146, precision: 0.7962, hmean: 0.8053 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8142, precision: 0.8281, hmean: 0.8211 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8055, precision: 0.8602, hmean: 0.8319 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7853, precision: 0.8893, hmean: 0.8341 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6538, precision: 0.9340, hmean: 0.7692 2022/10/26 04:11:31 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0342, precision: 1.0000, hmean: 0.0661 2022/10/26 04:11:31 - mmengine - INFO - Epoch(val) [660][32/32] icdar/precision: 0.8893 icdar/recall: 0.7853 icdar/hmean: 0.8341 2022/10/26 04:11:35 - mmengine - INFO - Epoch(train) [661][5/63] lr: 1.7217e-03 eta: 0:00:01 time: 0.6840 data_time: 0.1686 memory: 16131 loss: 1.2298 loss_prob: 0.6569 loss_thr: 0.4591 loss_db: 0.1138 2022/10/26 04:11:38 - mmengine - INFO - Epoch(train) [661][10/63] lr: 1.7217e-03 eta: 7:06:15 time: 0.7240 data_time: 0.1721 memory: 16131 loss: 1.2543 loss_prob: 0.6669 loss_thr: 0.4710 loss_db: 0.1165 2022/10/26 04:11:41 - mmengine - INFO - Epoch(train) [661][15/63] lr: 1.7217e-03 eta: 7:06:15 time: 0.5735 data_time: 0.0137 memory: 16131 loss: 1.1752 loss_prob: 0.6213 loss_thr: 0.4465 loss_db: 0.1074 2022/10/26 04:11:43 - mmengine - INFO - Epoch(train) [661][20/63] lr: 1.7217e-03 eta: 7:06:06 time: 0.5157 data_time: 0.0091 memory: 16131 loss: 1.1322 loss_prob: 0.5879 loss_thr: 0.4418 loss_db: 0.1024 2022/10/26 04:11:46 - mmengine - INFO - Epoch(train) [661][25/63] lr: 1.7217e-03 eta: 7:06:06 time: 0.5252 data_time: 0.0204 memory: 16131 loss: 1.1960 loss_prob: 0.6325 loss_thr: 0.4547 loss_db: 0.1088 2022/10/26 04:11:49 - mmengine - INFO - Epoch(train) [661][30/63] lr: 1.7217e-03 eta: 7:05:57 time: 0.5403 data_time: 0.0298 memory: 16131 loss: 1.1768 loss_prob: 0.6354 loss_thr: 0.4327 loss_db: 0.1087 2022/10/26 04:11:51 - mmengine - INFO - Epoch(train) [661][35/63] lr: 1.7217e-03 eta: 7:05:57 time: 0.5526 data_time: 0.0216 memory: 16131 loss: 1.1675 loss_prob: 0.6172 loss_thr: 0.4419 loss_db: 0.1084 2022/10/26 04:11:54 - mmengine - INFO - Epoch(train) [661][40/63] lr: 1.7217e-03 eta: 7:05:48 time: 0.5714 data_time: 0.0108 memory: 16131 loss: 1.3198 loss_prob: 0.7153 loss_thr: 0.4830 loss_db: 0.1216 2022/10/26 04:11:57 - mmengine - INFO - Epoch(train) [661][45/63] lr: 1.7217e-03 eta: 7:05:48 time: 0.5454 data_time: 0.0060 memory: 16131 loss: 1.3039 loss_prob: 0.7063 loss_thr: 0.4783 loss_db: 0.1193 2022/10/26 04:12:00 - mmengine - INFO - Epoch(train) [661][50/63] lr: 1.7217e-03 eta: 7:05:39 time: 0.5567 data_time: 0.0141 memory: 16131 loss: 1.2221 loss_prob: 0.6486 loss_thr: 0.4604 loss_db: 0.1131 2022/10/26 04:12:02 - mmengine - INFO - Epoch(train) [661][55/63] lr: 1.7217e-03 eta: 7:05:39 time: 0.5577 data_time: 0.0198 memory: 16131 loss: 1.2650 loss_prob: 0.6805 loss_thr: 0.4687 loss_db: 0.1158 2022/10/26 04:12:05 - mmengine - INFO - Epoch(train) [661][60/63] lr: 1.7217e-03 eta: 7:05:29 time: 0.5449 data_time: 0.0164 memory: 16131 loss: 1.2611 loss_prob: 0.6747 loss_thr: 0.4710 loss_db: 0.1153 2022/10/26 04:12:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:12:11 - mmengine - INFO - Epoch(train) [662][5/63] lr: 1.7188e-03 eta: 7:05:29 time: 0.7160 data_time: 0.1955 memory: 16131 loss: 1.2938 loss_prob: 0.7032 loss_thr: 0.4713 loss_db: 0.1193 2022/10/26 04:12:14 - mmengine - INFO - Epoch(train) [662][10/63] lr: 1.7188e-03 eta: 7:05:18 time: 0.7733 data_time: 0.1989 memory: 16131 loss: 1.3142 loss_prob: 0.7151 loss_thr: 0.4770 loss_db: 0.1221 2022/10/26 04:12:17 - mmengine - INFO - Epoch(train) [662][15/63] lr: 1.7188e-03 eta: 7:05:18 time: 0.5718 data_time: 0.0120 memory: 16131 loss: 1.1980 loss_prob: 0.6353 loss_thr: 0.4519 loss_db: 0.1109 2022/10/26 04:12:20 - mmengine - INFO - Epoch(train) [662][20/63] lr: 1.7188e-03 eta: 7:05:09 time: 0.5266 data_time: 0.0124 memory: 16131 loss: 1.1780 loss_prob: 0.6278 loss_thr: 0.4427 loss_db: 0.1075 2022/10/26 04:12:22 - mmengine - INFO - Epoch(train) [662][25/63] lr: 1.7188e-03 eta: 7:05:09 time: 0.5208 data_time: 0.0145 memory: 16131 loss: 1.2400 loss_prob: 0.6658 loss_thr: 0.4591 loss_db: 0.1151 2022/10/26 04:12:25 - mmengine - INFO - Epoch(train) [662][30/63] lr: 1.7188e-03 eta: 7:04:59 time: 0.5209 data_time: 0.0289 memory: 16131 loss: 1.1959 loss_prob: 0.6469 loss_thr: 0.4367 loss_db: 0.1123 2022/10/26 04:12:27 - mmengine - INFO - Epoch(train) [662][35/63] lr: 1.7188e-03 eta: 7:04:59 time: 0.5165 data_time: 0.0286 memory: 16131 loss: 1.1941 loss_prob: 0.6503 loss_thr: 0.4336 loss_db: 0.1102 2022/10/26 04:12:30 - mmengine - INFO - Epoch(train) [662][40/63] lr: 1.7188e-03 eta: 7:04:50 time: 0.5271 data_time: 0.0105 memory: 16131 loss: 1.2492 loss_prob: 0.6738 loss_thr: 0.4605 loss_db: 0.1149 2022/10/26 04:12:33 - mmengine - INFO - Epoch(train) [662][45/63] lr: 1.7188e-03 eta: 7:04:50 time: 0.5392 data_time: 0.0084 memory: 16131 loss: 1.2786 loss_prob: 0.6866 loss_thr: 0.4746 loss_db: 0.1174 2022/10/26 04:12:35 - mmengine - INFO - Epoch(train) [662][50/63] lr: 1.7188e-03 eta: 7:04:41 time: 0.5301 data_time: 0.0221 memory: 16131 loss: 1.2069 loss_prob: 0.6505 loss_thr: 0.4443 loss_db: 0.1122 2022/10/26 04:12:38 - mmengine - INFO - Epoch(train) [662][55/63] lr: 1.7188e-03 eta: 7:04:41 time: 0.5586 data_time: 0.0213 memory: 16131 loss: 1.1952 loss_prob: 0.6447 loss_thr: 0.4384 loss_db: 0.1120 2022/10/26 04:12:41 - mmengine - INFO - Epoch(train) [662][60/63] lr: 1.7188e-03 eta: 7:04:31 time: 0.5608 data_time: 0.0091 memory: 16131 loss: 1.2600 loss_prob: 0.6776 loss_thr: 0.4666 loss_db: 0.1158 2022/10/26 04:12:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:12:47 - mmengine - INFO - Epoch(train) [663][5/63] lr: 1.7159e-03 eta: 7:04:31 time: 0.6543 data_time: 0.1733 memory: 16131 loss: 1.3072 loss_prob: 0.7181 loss_thr: 0.4672 loss_db: 0.1219 2022/10/26 04:12:49 - mmengine - INFO - Epoch(train) [663][10/63] lr: 1.7159e-03 eta: 7:04:19 time: 0.6989 data_time: 0.1772 memory: 16131 loss: 1.3216 loss_prob: 0.7330 loss_thr: 0.4655 loss_db: 0.1231 2022/10/26 04:12:52 - mmengine - INFO - Epoch(train) [663][15/63] lr: 1.7159e-03 eta: 7:04:19 time: 0.5425 data_time: 0.0153 memory: 16131 loss: 1.2149 loss_prob: 0.6620 loss_thr: 0.4422 loss_db: 0.1107 2022/10/26 04:12:55 - mmengine - INFO - Epoch(train) [663][20/63] lr: 1.7159e-03 eta: 7:04:10 time: 0.5304 data_time: 0.0092 memory: 16131 loss: 1.1419 loss_prob: 0.6095 loss_thr: 0.4288 loss_db: 0.1036 2022/10/26 04:12:57 - mmengine - INFO - Epoch(train) [663][25/63] lr: 1.7159e-03 eta: 7:04:10 time: 0.5022 data_time: 0.0074 memory: 16131 loss: 1.1233 loss_prob: 0.6013 loss_thr: 0.4175 loss_db: 0.1046 2022/10/26 04:13:00 - mmengine - INFO - Epoch(train) [663][30/63] lr: 1.7159e-03 eta: 7:04:01 time: 0.5159 data_time: 0.0302 memory: 16131 loss: 1.1350 loss_prob: 0.6044 loss_thr: 0.4253 loss_db: 0.1052 2022/10/26 04:13:02 - mmengine - INFO - Epoch(train) [663][35/63] lr: 1.7159e-03 eta: 7:04:01 time: 0.5055 data_time: 0.0340 memory: 16131 loss: 1.2184 loss_prob: 0.6569 loss_thr: 0.4487 loss_db: 0.1128 2022/10/26 04:13:05 - mmengine - INFO - Epoch(train) [663][40/63] lr: 1.7159e-03 eta: 7:03:51 time: 0.4858 data_time: 0.0160 memory: 16131 loss: 1.2118 loss_prob: 0.6557 loss_thr: 0.4452 loss_db: 0.1110 2022/10/26 04:13:07 - mmengine - INFO - Epoch(train) [663][45/63] lr: 1.7159e-03 eta: 7:03:51 time: 0.4999 data_time: 0.0099 memory: 16131 loss: 1.2400 loss_prob: 0.6640 loss_thr: 0.4661 loss_db: 0.1099 2022/10/26 04:13:10 - mmengine - INFO - Epoch(train) [663][50/63] lr: 1.7159e-03 eta: 7:03:42 time: 0.5105 data_time: 0.0097 memory: 16131 loss: 1.2722 loss_prob: 0.6807 loss_thr: 0.4755 loss_db: 0.1160 2022/10/26 04:13:12 - mmengine - INFO - Epoch(train) [663][55/63] lr: 1.7159e-03 eta: 7:03:42 time: 0.5316 data_time: 0.0196 memory: 16131 loss: 1.2874 loss_prob: 0.7088 loss_thr: 0.4567 loss_db: 0.1218 2022/10/26 04:13:15 - mmengine - INFO - Epoch(train) [663][60/63] lr: 1.7159e-03 eta: 7:03:33 time: 0.5705 data_time: 0.0185 memory: 16131 loss: 1.3750 loss_prob: 0.7659 loss_thr: 0.4828 loss_db: 0.1263 2022/10/26 04:13:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:13:21 - mmengine - INFO - Epoch(train) [664][5/63] lr: 1.7131e-03 eta: 7:03:33 time: 0.6912 data_time: 0.1917 memory: 16131 loss: 1.3800 loss_prob: 0.7492 loss_thr: 0.5007 loss_db: 0.1301 2022/10/26 04:13:24 - mmengine - INFO - Epoch(train) [664][10/63] lr: 1.7131e-03 eta: 7:03:21 time: 0.6916 data_time: 0.1933 memory: 16131 loss: 1.2836 loss_prob: 0.6966 loss_thr: 0.4654 loss_db: 0.1215 2022/10/26 04:13:26 - mmengine - INFO - Epoch(train) [664][15/63] lr: 1.7131e-03 eta: 7:03:21 time: 0.5333 data_time: 0.0097 memory: 16131 loss: 1.3309 loss_prob: 0.7225 loss_thr: 0.4863 loss_db: 0.1222 2022/10/26 04:13:29 - mmengine - INFO - Epoch(train) [664][20/63] lr: 1.7131e-03 eta: 7:03:11 time: 0.5297 data_time: 0.0086 memory: 16131 loss: 1.2715 loss_prob: 0.6799 loss_thr: 0.4734 loss_db: 0.1183 2022/10/26 04:13:31 - mmengine - INFO - Epoch(train) [664][25/63] lr: 1.7131e-03 eta: 7:03:11 time: 0.5072 data_time: 0.0184 memory: 16131 loss: 1.1817 loss_prob: 0.6273 loss_thr: 0.4441 loss_db: 0.1102 2022/10/26 04:13:34 - mmengine - INFO - Epoch(train) [664][30/63] lr: 1.7131e-03 eta: 7:03:02 time: 0.5276 data_time: 0.0342 memory: 16131 loss: 1.2657 loss_prob: 0.7016 loss_thr: 0.4502 loss_db: 0.1139 2022/10/26 04:13:37 - mmengine - INFO - Epoch(train) [664][35/63] lr: 1.7131e-03 eta: 7:03:02 time: 0.5110 data_time: 0.0245 memory: 16131 loss: 1.2476 loss_prob: 0.6858 loss_thr: 0.4504 loss_db: 0.1114 2022/10/26 04:13:39 - mmengine - INFO - Epoch(train) [664][40/63] lr: 1.7131e-03 eta: 7:02:53 time: 0.5303 data_time: 0.0051 memory: 16131 loss: 1.2183 loss_prob: 0.6593 loss_thr: 0.4472 loss_db: 0.1118 2022/10/26 04:13:42 - mmengine - INFO - Epoch(train) [664][45/63] lr: 1.7131e-03 eta: 7:02:53 time: 0.5529 data_time: 0.0048 memory: 16131 loss: 1.2664 loss_prob: 0.6887 loss_thr: 0.4647 loss_db: 0.1131 2022/10/26 04:13:45 - mmengine - INFO - Epoch(train) [664][50/63] lr: 1.7131e-03 eta: 7:02:44 time: 0.5505 data_time: 0.0223 memory: 16131 loss: 1.2490 loss_prob: 0.6624 loss_thr: 0.4734 loss_db: 0.1132 2022/10/26 04:13:48 - mmengine - INFO - Epoch(train) [664][55/63] lr: 1.7131e-03 eta: 7:02:44 time: 0.5581 data_time: 0.0255 memory: 16131 loss: 1.2496 loss_prob: 0.6712 loss_thr: 0.4588 loss_db: 0.1196 2022/10/26 04:13:50 - mmengine - INFO - Epoch(train) [664][60/63] lr: 1.7131e-03 eta: 7:02:34 time: 0.5447 data_time: 0.0093 memory: 16131 loss: 1.3060 loss_prob: 0.7420 loss_thr: 0.4449 loss_db: 0.1191 2022/10/26 04:13:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:13:57 - mmengine - INFO - Epoch(train) [665][5/63] lr: 1.7102e-03 eta: 7:02:34 time: 0.7432 data_time: 0.1857 memory: 16131 loss: 1.3500 loss_prob: 0.7575 loss_thr: 0.4720 loss_db: 0.1205 2022/10/26 04:13:59 - mmengine - INFO - Epoch(train) [665][10/63] lr: 1.7102e-03 eta: 7:02:22 time: 0.7142 data_time: 0.1843 memory: 16131 loss: 1.2136 loss_prob: 0.6560 loss_thr: 0.4460 loss_db: 0.1117 2022/10/26 04:14:02 - mmengine - INFO - Epoch(train) [665][15/63] lr: 1.7102e-03 eta: 7:02:22 time: 0.5015 data_time: 0.0050 memory: 16131 loss: 1.2048 loss_prob: 0.6560 loss_thr: 0.4386 loss_db: 0.1102 2022/10/26 04:14:05 - mmengine - INFO - Epoch(train) [665][20/63] lr: 1.7102e-03 eta: 7:02:13 time: 0.5469 data_time: 0.0081 memory: 16131 loss: 1.2144 loss_prob: 0.6523 loss_thr: 0.4504 loss_db: 0.1117 2022/10/26 04:14:07 - mmengine - INFO - Epoch(train) [665][25/63] lr: 1.7102e-03 eta: 7:02:13 time: 0.5711 data_time: 0.0277 memory: 16131 loss: 1.1613 loss_prob: 0.6220 loss_thr: 0.4303 loss_db: 0.1091 2022/10/26 04:14:10 - mmengine - INFO - Epoch(train) [665][30/63] lr: 1.7102e-03 eta: 7:02:04 time: 0.5628 data_time: 0.0304 memory: 16131 loss: 1.0657 loss_prob: 0.5636 loss_thr: 0.4048 loss_db: 0.0973 2022/10/26 04:14:13 - mmengine - INFO - Epoch(train) [665][35/63] lr: 1.7102e-03 eta: 7:02:04 time: 0.5149 data_time: 0.0102 memory: 16131 loss: 1.1341 loss_prob: 0.6048 loss_thr: 0.4267 loss_db: 0.1026 2022/10/26 04:14:15 - mmengine - INFO - Epoch(train) [665][40/63] lr: 1.7102e-03 eta: 7:01:55 time: 0.4893 data_time: 0.0048 memory: 16131 loss: 1.2748 loss_prob: 0.7006 loss_thr: 0.4570 loss_db: 0.1171 2022/10/26 04:14:18 - mmengine - INFO - Epoch(train) [665][45/63] lr: 1.7102e-03 eta: 7:01:55 time: 0.5560 data_time: 0.0049 memory: 16131 loss: 1.3773 loss_prob: 0.7775 loss_thr: 0.4730 loss_db: 0.1268 2022/10/26 04:14:21 - mmengine - INFO - Epoch(train) [665][50/63] lr: 1.7102e-03 eta: 7:01:46 time: 0.5540 data_time: 0.0202 memory: 16131 loss: 1.3034 loss_prob: 0.7152 loss_thr: 0.4704 loss_db: 0.1179 2022/10/26 04:14:23 - mmengine - INFO - Epoch(train) [665][55/63] lr: 1.7102e-03 eta: 7:01:46 time: 0.4962 data_time: 0.0224 memory: 16131 loss: 1.2004 loss_prob: 0.6392 loss_thr: 0.4521 loss_db: 0.1091 2022/10/26 04:14:26 - mmengine - INFO - Epoch(train) [665][60/63] lr: 1.7102e-03 eta: 7:01:36 time: 0.5135 data_time: 0.0077 memory: 16131 loss: 1.3350 loss_prob: 0.7576 loss_thr: 0.4515 loss_db: 0.1260 2022/10/26 04:14:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:14:32 - mmengine - INFO - Epoch(train) [666][5/63] lr: 1.7073e-03 eta: 7:01:36 time: 0.7325 data_time: 0.1884 memory: 16131 loss: 1.3714 loss_prob: 0.7683 loss_thr: 0.4782 loss_db: 0.1249 2022/10/26 04:14:35 - mmengine - INFO - Epoch(train) [666][10/63] lr: 1.7073e-03 eta: 7:01:25 time: 0.7547 data_time: 0.1884 memory: 16131 loss: 1.2590 loss_prob: 0.6961 loss_thr: 0.4482 loss_db: 0.1147 2022/10/26 04:14:37 - mmengine - INFO - Epoch(train) [666][15/63] lr: 1.7073e-03 eta: 7:01:25 time: 0.5149 data_time: 0.0048 memory: 16131 loss: 1.1908 loss_prob: 0.6450 loss_thr: 0.4372 loss_db: 0.1086 2022/10/26 04:14:40 - mmengine - INFO - Epoch(train) [666][20/63] lr: 1.7073e-03 eta: 7:01:15 time: 0.4988 data_time: 0.0056 memory: 16131 loss: 1.1883 loss_prob: 0.6420 loss_thr: 0.4361 loss_db: 0.1102 2022/10/26 04:14:42 - mmengine - INFO - Epoch(train) [666][25/63] lr: 1.7073e-03 eta: 7:01:15 time: 0.4924 data_time: 0.0140 memory: 16131 loss: 1.2789 loss_prob: 0.7170 loss_thr: 0.4411 loss_db: 0.1207 2022/10/26 04:14:45 - mmengine - INFO - Epoch(train) [666][30/63] lr: 1.7073e-03 eta: 7:01:06 time: 0.5131 data_time: 0.0349 memory: 16131 loss: 1.3224 loss_prob: 0.7427 loss_thr: 0.4528 loss_db: 0.1269 2022/10/26 04:14:47 - mmengine - INFO - Epoch(train) [666][35/63] lr: 1.7073e-03 eta: 7:01:06 time: 0.5213 data_time: 0.0263 memory: 16131 loss: 1.3396 loss_prob: 0.7497 loss_thr: 0.4639 loss_db: 0.1261 2022/10/26 04:14:50 - mmengine - INFO - Epoch(train) [666][40/63] lr: 1.7073e-03 eta: 7:00:56 time: 0.4971 data_time: 0.0055 memory: 16131 loss: 1.3612 loss_prob: 0.7599 loss_thr: 0.4772 loss_db: 0.1240 2022/10/26 04:14:52 - mmengine - INFO - Epoch(train) [666][45/63] lr: 1.7073e-03 eta: 7:00:56 time: 0.4876 data_time: 0.0071 memory: 16131 loss: 1.3424 loss_prob: 0.7342 loss_thr: 0.4850 loss_db: 0.1231 2022/10/26 04:14:55 - mmengine - INFO - Epoch(train) [666][50/63] lr: 1.7073e-03 eta: 7:00:47 time: 0.5397 data_time: 0.0140 memory: 16131 loss: 1.3306 loss_prob: 0.7278 loss_thr: 0.4786 loss_db: 0.1242 2022/10/26 04:14:58 - mmengine - INFO - Epoch(train) [666][55/63] lr: 1.7073e-03 eta: 7:00:47 time: 0.6035 data_time: 0.0216 memory: 16131 loss: 1.3103 loss_prob: 0.7178 loss_thr: 0.4706 loss_db: 0.1218 2022/10/26 04:15:01 - mmengine - INFO - Epoch(train) [666][60/63] lr: 1.7073e-03 eta: 7:00:38 time: 0.5720 data_time: 0.0137 memory: 16131 loss: 1.3496 loss_prob: 0.7492 loss_thr: 0.4757 loss_db: 0.1248 2022/10/26 04:15:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:15:07 - mmengine - INFO - Epoch(train) [667][5/63] lr: 1.7044e-03 eta: 7:00:38 time: 0.7328 data_time: 0.2004 memory: 16131 loss: 1.1716 loss_prob: 0.6424 loss_thr: 0.4190 loss_db: 0.1103 2022/10/26 04:15:10 - mmengine - INFO - Epoch(train) [667][10/63] lr: 1.7044e-03 eta: 7:00:27 time: 0.8363 data_time: 0.2073 memory: 16131 loss: 1.2411 loss_prob: 0.6771 loss_thr: 0.4459 loss_db: 0.1181 2022/10/26 04:15:13 - mmengine - INFO - Epoch(train) [667][15/63] lr: 1.7044e-03 eta: 7:00:27 time: 0.5651 data_time: 0.0117 memory: 16131 loss: 1.3643 loss_prob: 0.7597 loss_thr: 0.4751 loss_db: 0.1295 2022/10/26 04:15:16 - mmengine - INFO - Epoch(train) [667][20/63] lr: 1.7044e-03 eta: 7:00:18 time: 0.5165 data_time: 0.0057 memory: 16131 loss: 1.2866 loss_prob: 0.7074 loss_thr: 0.4586 loss_db: 0.1206 2022/10/26 04:15:19 - mmengine - INFO - Epoch(train) [667][25/63] lr: 1.7044e-03 eta: 7:00:18 time: 0.5747 data_time: 0.0330 memory: 16131 loss: 1.2590 loss_prob: 0.6856 loss_thr: 0.4568 loss_db: 0.1165 2022/10/26 04:15:22 - mmengine - INFO - Epoch(train) [667][30/63] lr: 1.7044e-03 eta: 7:00:09 time: 0.5913 data_time: 0.0495 memory: 16131 loss: 1.1821 loss_prob: 0.6368 loss_thr: 0.4366 loss_db: 0.1088 2022/10/26 04:15:24 - mmengine - INFO - Epoch(train) [667][35/63] lr: 1.7044e-03 eta: 7:00:09 time: 0.5557 data_time: 0.0219 memory: 16131 loss: 1.2111 loss_prob: 0.6502 loss_thr: 0.4482 loss_db: 0.1128 2022/10/26 04:15:27 - mmengine - INFO - Epoch(train) [667][40/63] lr: 1.7044e-03 eta: 7:00:00 time: 0.5439 data_time: 0.0047 memory: 16131 loss: 1.2767 loss_prob: 0.6889 loss_thr: 0.4700 loss_db: 0.1177 2022/10/26 04:15:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:15:30 - mmengine - INFO - Epoch(train) [667][45/63] lr: 1.7044e-03 eta: 7:00:00 time: 0.5289 data_time: 0.0062 memory: 16131 loss: 1.2795 loss_prob: 0.7011 loss_thr: 0.4609 loss_db: 0.1175 2022/10/26 04:15:32 - mmengine - INFO - Epoch(train) [667][50/63] lr: 1.7044e-03 eta: 6:59:50 time: 0.5065 data_time: 0.0148 memory: 16131 loss: 1.2661 loss_prob: 0.6975 loss_thr: 0.4504 loss_db: 0.1182 2022/10/26 04:15:35 - mmengine - INFO - Epoch(train) [667][55/63] lr: 1.7044e-03 eta: 6:59:50 time: 0.5025 data_time: 0.0243 memory: 16131 loss: 1.2963 loss_prob: 0.7147 loss_thr: 0.4584 loss_db: 0.1232 2022/10/26 04:15:37 - mmengine - INFO - Epoch(train) [667][60/63] lr: 1.7044e-03 eta: 6:59:41 time: 0.5132 data_time: 0.0156 memory: 16131 loss: 1.2367 loss_prob: 0.6755 loss_thr: 0.4461 loss_db: 0.1151 2022/10/26 04:15:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:15:43 - mmengine - INFO - Epoch(train) [668][5/63] lr: 1.7015e-03 eta: 6:59:41 time: 0.7223 data_time: 0.1918 memory: 16131 loss: 1.2102 loss_prob: 0.6513 loss_thr: 0.4443 loss_db: 0.1146 2022/10/26 04:15:46 - mmengine - INFO - Epoch(train) [668][10/63] lr: 1.7015e-03 eta: 6:59:30 time: 0.7672 data_time: 0.1979 memory: 16131 loss: 1.2503 loss_prob: 0.6771 loss_thr: 0.4545 loss_db: 0.1186 2022/10/26 04:15:49 - mmengine - INFO - Epoch(train) [668][15/63] lr: 1.7015e-03 eta: 6:59:30 time: 0.5507 data_time: 0.0108 memory: 16131 loss: 1.1710 loss_prob: 0.6118 loss_thr: 0.4535 loss_db: 0.1057 2022/10/26 04:15:52 - mmengine - INFO - Epoch(train) [668][20/63] lr: 1.7015e-03 eta: 6:59:21 time: 0.5583 data_time: 0.0056 memory: 16131 loss: 1.1747 loss_prob: 0.6154 loss_thr: 0.4522 loss_db: 0.1071 2022/10/26 04:15:54 - mmengine - INFO - Epoch(train) [668][25/63] lr: 1.7015e-03 eta: 6:59:21 time: 0.5482 data_time: 0.0276 memory: 16131 loss: 1.2626 loss_prob: 0.6918 loss_thr: 0.4537 loss_db: 0.1171 2022/10/26 04:15:57 - mmengine - INFO - Epoch(train) [668][30/63] lr: 1.7015e-03 eta: 6:59:11 time: 0.5314 data_time: 0.0357 memory: 16131 loss: 1.2695 loss_prob: 0.7045 loss_thr: 0.4493 loss_db: 0.1157 2022/10/26 04:16:00 - mmengine - INFO - Epoch(train) [668][35/63] lr: 1.7015e-03 eta: 6:59:11 time: 0.5279 data_time: 0.0136 memory: 16131 loss: 1.2661 loss_prob: 0.6881 loss_thr: 0.4627 loss_db: 0.1153 2022/10/26 04:16:02 - mmengine - INFO - Epoch(train) [668][40/63] lr: 1.7015e-03 eta: 6:59:02 time: 0.5407 data_time: 0.0048 memory: 16131 loss: 1.2232 loss_prob: 0.6527 loss_thr: 0.4591 loss_db: 0.1114 2022/10/26 04:16:05 - mmengine - INFO - Epoch(train) [668][45/63] lr: 1.7015e-03 eta: 6:59:02 time: 0.5280 data_time: 0.0044 memory: 16131 loss: 1.1697 loss_prob: 0.6096 loss_thr: 0.4552 loss_db: 0.1049 2022/10/26 04:16:07 - mmengine - INFO - Epoch(train) [668][50/63] lr: 1.7015e-03 eta: 6:58:53 time: 0.5029 data_time: 0.0165 memory: 16131 loss: 1.2333 loss_prob: 0.6492 loss_thr: 0.4711 loss_db: 0.1129 2022/10/26 04:16:10 - mmengine - INFO - Epoch(train) [668][55/63] lr: 1.7015e-03 eta: 6:58:53 time: 0.5145 data_time: 0.0244 memory: 16131 loss: 1.2373 loss_prob: 0.6708 loss_thr: 0.4513 loss_db: 0.1152 2022/10/26 04:16:13 - mmengine - INFO - Epoch(train) [668][60/63] lr: 1.7015e-03 eta: 6:58:44 time: 0.5473 data_time: 0.0123 memory: 16131 loss: 1.1540 loss_prob: 0.6172 loss_thr: 0.4322 loss_db: 0.1046 2022/10/26 04:16:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:16:19 - mmengine - INFO - Epoch(train) [669][5/63] lr: 1.6987e-03 eta: 6:58:44 time: 0.7397 data_time: 0.1623 memory: 16131 loss: 1.4055 loss_prob: 0.7956 loss_thr: 0.4855 loss_db: 0.1245 2022/10/26 04:16:22 - mmengine - INFO - Epoch(train) [669][10/63] lr: 1.6987e-03 eta: 6:58:32 time: 0.7527 data_time: 0.1724 memory: 16131 loss: 1.2617 loss_prob: 0.6760 loss_thr: 0.4708 loss_db: 0.1149 2022/10/26 04:16:24 - mmengine - INFO - Epoch(train) [669][15/63] lr: 1.6987e-03 eta: 6:58:32 time: 0.5270 data_time: 0.0164 memory: 16131 loss: 1.2173 loss_prob: 0.6577 loss_thr: 0.4476 loss_db: 0.1120 2022/10/26 04:16:27 - mmengine - INFO - Epoch(train) [669][20/63] lr: 1.6987e-03 eta: 6:58:23 time: 0.5209 data_time: 0.0050 memory: 16131 loss: 1.1695 loss_prob: 0.6292 loss_thr: 0.4353 loss_db: 0.1050 2022/10/26 04:16:30 - mmengine - INFO - Epoch(train) [669][25/63] lr: 1.6987e-03 eta: 6:58:23 time: 0.5552 data_time: 0.0181 memory: 16131 loss: 1.0783 loss_prob: 0.5613 loss_thr: 0.4206 loss_db: 0.0965 2022/10/26 04:16:33 - mmengine - INFO - Epoch(train) [669][30/63] lr: 1.6987e-03 eta: 6:58:14 time: 0.5556 data_time: 0.0376 memory: 16131 loss: 1.1172 loss_prob: 0.5880 loss_thr: 0.4256 loss_db: 0.1036 2022/10/26 04:16:35 - mmengine - INFO - Epoch(train) [669][35/63] lr: 1.6987e-03 eta: 6:58:14 time: 0.5264 data_time: 0.0321 memory: 16131 loss: 1.2091 loss_prob: 0.6476 loss_thr: 0.4474 loss_db: 0.1141 2022/10/26 04:16:38 - mmengine - INFO - Epoch(train) [669][40/63] lr: 1.6987e-03 eta: 6:58:04 time: 0.4952 data_time: 0.0131 memory: 16131 loss: 1.2349 loss_prob: 0.6633 loss_thr: 0.4572 loss_db: 0.1144 2022/10/26 04:16:40 - mmengine - INFO - Epoch(train) [669][45/63] lr: 1.6987e-03 eta: 6:58:04 time: 0.4876 data_time: 0.0092 memory: 16131 loss: 1.1853 loss_prob: 0.6378 loss_thr: 0.4396 loss_db: 0.1079 2022/10/26 04:16:43 - mmengine - INFO - Epoch(train) [669][50/63] lr: 1.6987e-03 eta: 6:57:55 time: 0.5163 data_time: 0.0188 memory: 16131 loss: 1.2534 loss_prob: 0.6762 loss_thr: 0.4621 loss_db: 0.1151 2022/10/26 04:16:45 - mmengine - INFO - Epoch(train) [669][55/63] lr: 1.6987e-03 eta: 6:57:55 time: 0.5373 data_time: 0.0192 memory: 16131 loss: 1.2272 loss_prob: 0.6601 loss_thr: 0.4539 loss_db: 0.1133 2022/10/26 04:16:48 - mmengine - INFO - Epoch(train) [669][60/63] lr: 1.6987e-03 eta: 6:57:46 time: 0.5249 data_time: 0.0122 memory: 16131 loss: 1.1611 loss_prob: 0.6282 loss_thr: 0.4258 loss_db: 0.1070 2022/10/26 04:16:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:16:54 - mmengine - INFO - Epoch(train) [670][5/63] lr: 1.6958e-03 eta: 6:57:46 time: 0.7094 data_time: 0.1936 memory: 16131 loss: 1.2241 loss_prob: 0.6617 loss_thr: 0.4485 loss_db: 0.1140 2022/10/26 04:16:57 - mmengine - INFO - Epoch(train) [670][10/63] lr: 1.6958e-03 eta: 6:57:34 time: 0.7731 data_time: 0.2028 memory: 16131 loss: 1.1454 loss_prob: 0.6091 loss_thr: 0.4289 loss_db: 0.1075 2022/10/26 04:17:00 - mmengine - INFO - Epoch(train) [670][15/63] lr: 1.6958e-03 eta: 6:57:34 time: 0.5428 data_time: 0.0164 memory: 16131 loss: 1.1693 loss_prob: 0.6256 loss_thr: 0.4347 loss_db: 0.1090 2022/10/26 04:17:02 - mmengine - INFO - Epoch(train) [670][20/63] lr: 1.6958e-03 eta: 6:57:25 time: 0.5016 data_time: 0.0075 memory: 16131 loss: 1.1578 loss_prob: 0.6066 loss_thr: 0.4488 loss_db: 0.1023 2022/10/26 04:17:05 - mmengine - INFO - Epoch(train) [670][25/63] lr: 1.6958e-03 eta: 6:57:25 time: 0.5448 data_time: 0.0287 memory: 16131 loss: 1.2194 loss_prob: 0.6396 loss_thr: 0.4712 loss_db: 0.1087 2022/10/26 04:17:08 - mmengine - INFO - Epoch(train) [670][30/63] lr: 1.6958e-03 eta: 6:57:16 time: 0.5489 data_time: 0.0289 memory: 16131 loss: 1.1672 loss_prob: 0.6202 loss_thr: 0.4401 loss_db: 0.1069 2022/10/26 04:17:10 - mmengine - INFO - Epoch(train) [670][35/63] lr: 1.6958e-03 eta: 6:57:16 time: 0.5162 data_time: 0.0117 memory: 16131 loss: 1.2683 loss_prob: 0.6903 loss_thr: 0.4572 loss_db: 0.1209 2022/10/26 04:17:13 - mmengine - INFO - Epoch(train) [670][40/63] lr: 1.6958e-03 eta: 6:57:06 time: 0.5103 data_time: 0.0127 memory: 16131 loss: 1.3298 loss_prob: 0.7295 loss_thr: 0.4737 loss_db: 0.1267 2022/10/26 04:17:15 - mmengine - INFO - Epoch(train) [670][45/63] lr: 1.6958e-03 eta: 6:57:06 time: 0.5091 data_time: 0.0087 memory: 16131 loss: 1.1281 loss_prob: 0.5975 loss_thr: 0.4269 loss_db: 0.1037 2022/10/26 04:17:18 - mmengine - INFO - Epoch(train) [670][50/63] lr: 1.6958e-03 eta: 6:56:57 time: 0.5394 data_time: 0.0226 memory: 16131 loss: 1.2157 loss_prob: 0.6672 loss_thr: 0.4364 loss_db: 0.1121 2022/10/26 04:17:20 - mmengine - INFO - Epoch(train) [670][55/63] lr: 1.6958e-03 eta: 6:56:57 time: 0.5102 data_time: 0.0233 memory: 16131 loss: 1.3193 loss_prob: 0.7356 loss_thr: 0.4604 loss_db: 0.1233 2022/10/26 04:17:24 - mmengine - INFO - Epoch(train) [670][60/63] lr: 1.6958e-03 eta: 6:56:48 time: 0.5510 data_time: 0.0132 memory: 16131 loss: 1.2447 loss_prob: 0.6665 loss_thr: 0.4624 loss_db: 0.1158 2022/10/26 04:17:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:17:29 - mmengine - INFO - Epoch(train) [671][5/63] lr: 1.6929e-03 eta: 6:56:48 time: 0.7379 data_time: 0.1999 memory: 16131 loss: 1.2251 loss_prob: 0.6531 loss_thr: 0.4604 loss_db: 0.1116 2022/10/26 04:17:32 - mmengine - INFO - Epoch(train) [671][10/63] lr: 1.6929e-03 eta: 6:56:36 time: 0.7142 data_time: 0.1996 memory: 16131 loss: 1.2057 loss_prob: 0.6423 loss_thr: 0.4544 loss_db: 0.1091 2022/10/26 04:17:35 - mmengine - INFO - Epoch(train) [671][15/63] lr: 1.6929e-03 eta: 6:56:36 time: 0.5439 data_time: 0.0068 memory: 16131 loss: 1.3857 loss_prob: 0.7953 loss_thr: 0.4702 loss_db: 0.1202 2022/10/26 04:17:37 - mmengine - INFO - Epoch(train) [671][20/63] lr: 1.6929e-03 eta: 6:56:27 time: 0.5208 data_time: 0.0067 memory: 16131 loss: 1.4349 loss_prob: 0.8315 loss_thr: 0.4753 loss_db: 0.1281 2022/10/26 04:17:40 - mmengine - INFO - Epoch(train) [671][25/63] lr: 1.6929e-03 eta: 6:56:27 time: 0.5275 data_time: 0.0368 memory: 16131 loss: 1.2436 loss_prob: 0.6807 loss_thr: 0.4484 loss_db: 0.1146 2022/10/26 04:17:43 - mmengine - INFO - Epoch(train) [671][30/63] lr: 1.6929e-03 eta: 6:56:18 time: 0.5400 data_time: 0.0368 memory: 16131 loss: 1.1979 loss_prob: 0.6515 loss_thr: 0.4372 loss_db: 0.1092 2022/10/26 04:17:45 - mmengine - INFO - Epoch(train) [671][35/63] lr: 1.6929e-03 eta: 6:56:18 time: 0.5018 data_time: 0.0045 memory: 16131 loss: 1.1374 loss_prob: 0.6146 loss_thr: 0.4176 loss_db: 0.1053 2022/10/26 04:17:48 - mmengine - INFO - Epoch(train) [671][40/63] lr: 1.6929e-03 eta: 6:56:09 time: 0.5166 data_time: 0.0055 memory: 16131 loss: 1.1853 loss_prob: 0.6501 loss_thr: 0.4254 loss_db: 0.1098 2022/10/26 04:17:50 - mmengine - INFO - Epoch(train) [671][45/63] lr: 1.6929e-03 eta: 6:56:09 time: 0.5006 data_time: 0.0064 memory: 16131 loss: 1.2791 loss_prob: 0.7017 loss_thr: 0.4600 loss_db: 0.1173 2022/10/26 04:17:53 - mmengine - INFO - Epoch(train) [671][50/63] lr: 1.6929e-03 eta: 6:55:59 time: 0.5026 data_time: 0.0251 memory: 16131 loss: 1.2211 loss_prob: 0.6604 loss_thr: 0.4492 loss_db: 0.1115 2022/10/26 04:17:55 - mmengine - INFO - Epoch(train) [671][55/63] lr: 1.6929e-03 eta: 6:55:59 time: 0.5227 data_time: 0.0246 memory: 16131 loss: 1.2345 loss_prob: 0.6667 loss_thr: 0.4558 loss_db: 0.1120 2022/10/26 04:17:58 - mmengine - INFO - Epoch(train) [671][60/63] lr: 1.6929e-03 eta: 6:55:50 time: 0.5437 data_time: 0.0048 memory: 16131 loss: 1.2060 loss_prob: 0.6544 loss_thr: 0.4405 loss_db: 0.1110 2022/10/26 04:18:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:18:04 - mmengine - INFO - Epoch(train) [672][5/63] lr: 1.6900e-03 eta: 6:55:50 time: 0.7098 data_time: 0.1799 memory: 16131 loss: 1.2178 loss_prob: 0.6598 loss_thr: 0.4444 loss_db: 0.1136 2022/10/26 04:18:07 - mmengine - INFO - Epoch(train) [672][10/63] lr: 1.6900e-03 eta: 6:55:39 time: 0.7464 data_time: 0.1888 memory: 16131 loss: 1.2511 loss_prob: 0.6799 loss_thr: 0.4552 loss_db: 0.1160 2022/10/26 04:18:10 - mmengine - INFO - Epoch(train) [672][15/63] lr: 1.6900e-03 eta: 6:55:39 time: 0.5477 data_time: 0.0215 memory: 16131 loss: 1.1818 loss_prob: 0.6384 loss_thr: 0.4325 loss_db: 0.1109 2022/10/26 04:18:12 - mmengine - INFO - Epoch(train) [672][20/63] lr: 1.6900e-03 eta: 6:55:29 time: 0.5253 data_time: 0.0104 memory: 16131 loss: 1.0747 loss_prob: 0.5708 loss_thr: 0.4042 loss_db: 0.0996 2022/10/26 04:18:15 - mmengine - INFO - Epoch(train) [672][25/63] lr: 1.6900e-03 eta: 6:55:29 time: 0.5260 data_time: 0.0205 memory: 16131 loss: 1.1345 loss_prob: 0.6025 loss_thr: 0.4294 loss_db: 0.1026 2022/10/26 04:18:18 - mmengine - INFO - Epoch(train) [672][30/63] lr: 1.6900e-03 eta: 6:55:20 time: 0.5370 data_time: 0.0238 memory: 16131 loss: 1.1747 loss_prob: 0.6293 loss_thr: 0.4386 loss_db: 0.1068 2022/10/26 04:18:21 - mmengine - INFO - Epoch(train) [672][35/63] lr: 1.6900e-03 eta: 6:55:20 time: 0.5638 data_time: 0.0211 memory: 16131 loss: 1.1564 loss_prob: 0.6189 loss_thr: 0.4297 loss_db: 0.1078 2022/10/26 04:18:23 - mmengine - INFO - Epoch(train) [672][40/63] lr: 1.6900e-03 eta: 6:55:11 time: 0.5337 data_time: 0.0149 memory: 16131 loss: 1.1603 loss_prob: 0.6207 loss_thr: 0.4314 loss_db: 0.1083 2022/10/26 04:18:26 - mmengine - INFO - Epoch(train) [672][45/63] lr: 1.6900e-03 eta: 6:55:11 time: 0.4955 data_time: 0.0052 memory: 16131 loss: 1.2418 loss_prob: 0.6746 loss_thr: 0.4535 loss_db: 0.1138 2022/10/26 04:18:28 - mmengine - INFO - Epoch(train) [672][50/63] lr: 1.6900e-03 eta: 6:55:02 time: 0.4948 data_time: 0.0143 memory: 16131 loss: 1.3198 loss_prob: 0.7302 loss_thr: 0.4694 loss_db: 0.1202 2022/10/26 04:18:31 - mmengine - INFO - Epoch(train) [672][55/63] lr: 1.6900e-03 eta: 6:55:02 time: 0.5664 data_time: 0.0179 memory: 16131 loss: 1.2185 loss_prob: 0.6633 loss_thr: 0.4439 loss_db: 0.1113 2022/10/26 04:18:34 - mmengine - INFO - Epoch(train) [672][60/63] lr: 1.6900e-03 eta: 6:54:53 time: 0.6060 data_time: 0.0297 memory: 16131 loss: 1.1998 loss_prob: 0.6335 loss_thr: 0.4556 loss_db: 0.1107 2022/10/26 04:18:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:18:40 - mmengine - INFO - Epoch(train) [673][5/63] lr: 1.6871e-03 eta: 6:54:53 time: 0.7274 data_time: 0.1985 memory: 16131 loss: 1.2425 loss_prob: 0.6633 loss_thr: 0.4633 loss_db: 0.1159 2022/10/26 04:18:43 - mmengine - INFO - Epoch(train) [673][10/63] lr: 1.6871e-03 eta: 6:54:41 time: 0.7334 data_time: 0.1969 memory: 16131 loss: 1.2659 loss_prob: 0.6809 loss_thr: 0.4669 loss_db: 0.1181 2022/10/26 04:18:46 - mmengine - INFO - Epoch(train) [673][15/63] lr: 1.6871e-03 eta: 6:54:41 time: 0.5241 data_time: 0.0053 memory: 16131 loss: 1.2196 loss_prob: 0.6455 loss_thr: 0.4624 loss_db: 0.1117 2022/10/26 04:18:48 - mmengine - INFO - Epoch(train) [673][20/63] lr: 1.6871e-03 eta: 6:54:32 time: 0.5332 data_time: 0.0066 memory: 16131 loss: 1.1907 loss_prob: 0.6257 loss_thr: 0.4578 loss_db: 0.1071 2022/10/26 04:18:51 - mmengine - INFO - Epoch(train) [673][25/63] lr: 1.6871e-03 eta: 6:54:32 time: 0.5228 data_time: 0.0166 memory: 16131 loss: 1.1649 loss_prob: 0.6199 loss_thr: 0.4401 loss_db: 0.1049 2022/10/26 04:18:53 - mmengine - INFO - Epoch(train) [673][30/63] lr: 1.6871e-03 eta: 6:54:23 time: 0.5238 data_time: 0.0362 memory: 16131 loss: 1.1829 loss_prob: 0.6458 loss_thr: 0.4295 loss_db: 0.1076 2022/10/26 04:18:56 - mmengine - INFO - Epoch(train) [673][35/63] lr: 1.6871e-03 eta: 6:54:23 time: 0.5029 data_time: 0.0254 memory: 16131 loss: 1.2268 loss_prob: 0.6651 loss_thr: 0.4505 loss_db: 0.1112 2022/10/26 04:18:58 - mmengine - INFO - Epoch(train) [673][40/63] lr: 1.6871e-03 eta: 6:54:13 time: 0.4757 data_time: 0.0044 memory: 16131 loss: 1.2172 loss_prob: 0.6594 loss_thr: 0.4434 loss_db: 0.1144 2022/10/26 04:19:01 - mmengine - INFO - Epoch(train) [673][45/63] lr: 1.6871e-03 eta: 6:54:13 time: 0.4816 data_time: 0.0044 memory: 16131 loss: 1.2389 loss_prob: 0.6847 loss_thr: 0.4371 loss_db: 0.1171 2022/10/26 04:19:03 - mmengine - INFO - Epoch(train) [673][50/63] lr: 1.6871e-03 eta: 6:54:04 time: 0.5221 data_time: 0.0182 memory: 16131 loss: 1.2068 loss_prob: 0.6553 loss_thr: 0.4408 loss_db: 0.1108 2022/10/26 04:19:06 - mmengine - INFO - Epoch(train) [673][55/63] lr: 1.6871e-03 eta: 6:54:04 time: 0.5195 data_time: 0.0231 memory: 16131 loss: 1.1992 loss_prob: 0.6370 loss_thr: 0.4526 loss_db: 0.1096 2022/10/26 04:19:09 - mmengine - INFO - Epoch(train) [673][60/63] lr: 1.6871e-03 eta: 6:53:55 time: 0.5386 data_time: 0.0121 memory: 16131 loss: 1.2321 loss_prob: 0.6557 loss_thr: 0.4641 loss_db: 0.1123 2022/10/26 04:19:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:19:14 - mmengine - INFO - Epoch(train) [674][5/63] lr: 1.6843e-03 eta: 6:53:55 time: 0.6712 data_time: 0.1908 memory: 16131 loss: 1.1674 loss_prob: 0.6196 loss_thr: 0.4407 loss_db: 0.1071 2022/10/26 04:19:17 - mmengine - INFO - Epoch(train) [674][10/63] lr: 1.6843e-03 eta: 6:53:43 time: 0.6842 data_time: 0.1909 memory: 16131 loss: 1.1932 loss_prob: 0.6388 loss_thr: 0.4476 loss_db: 0.1067 2022/10/26 04:19:19 - mmengine - INFO - Epoch(train) [674][15/63] lr: 1.6843e-03 eta: 6:53:43 time: 0.4999 data_time: 0.0104 memory: 16131 loss: 1.1938 loss_prob: 0.6482 loss_thr: 0.4385 loss_db: 0.1072 2022/10/26 04:19:22 - mmengine - INFO - Epoch(train) [674][20/63] lr: 1.6843e-03 eta: 6:53:34 time: 0.5142 data_time: 0.0121 memory: 16131 loss: 1.2215 loss_prob: 0.6672 loss_thr: 0.4402 loss_db: 0.1141 2022/10/26 04:19:25 - mmengine - INFO - Epoch(train) [674][25/63] lr: 1.6843e-03 eta: 6:53:34 time: 0.5286 data_time: 0.0126 memory: 16131 loss: 1.2313 loss_prob: 0.6679 loss_thr: 0.4480 loss_db: 0.1153 2022/10/26 04:19:28 - mmengine - INFO - Epoch(train) [674][30/63] lr: 1.6843e-03 eta: 6:53:25 time: 0.5769 data_time: 0.0284 memory: 16131 loss: 1.1992 loss_prob: 0.6461 loss_thr: 0.4408 loss_db: 0.1123 2022/10/26 04:19:30 - mmengine - INFO - Epoch(train) [674][35/63] lr: 1.6843e-03 eta: 6:53:25 time: 0.5795 data_time: 0.0253 memory: 16131 loss: 1.2403 loss_prob: 0.6742 loss_thr: 0.4490 loss_db: 0.1172 2022/10/26 04:19:33 - mmengine - INFO - Epoch(train) [674][40/63] lr: 1.6843e-03 eta: 6:53:16 time: 0.5182 data_time: 0.0074 memory: 16131 loss: 1.3177 loss_prob: 0.7182 loss_thr: 0.4789 loss_db: 0.1206 2022/10/26 04:19:35 - mmengine - INFO - Epoch(train) [674][45/63] lr: 1.6843e-03 eta: 6:53:16 time: 0.5080 data_time: 0.0075 memory: 16131 loss: 1.2801 loss_prob: 0.6885 loss_thr: 0.4770 loss_db: 0.1146 2022/10/26 04:19:39 - mmengine - INFO - Epoch(train) [674][50/63] lr: 1.6843e-03 eta: 6:53:07 time: 0.5638 data_time: 0.0160 memory: 16131 loss: 1.2004 loss_prob: 0.6352 loss_thr: 0.4574 loss_db: 0.1078 2022/10/26 04:19:41 - mmengine - INFO - Epoch(train) [674][55/63] lr: 1.6843e-03 eta: 6:53:07 time: 0.5756 data_time: 0.0200 memory: 16131 loss: 1.2950 loss_prob: 0.7130 loss_thr: 0.4601 loss_db: 0.1219 2022/10/26 04:19:44 - mmengine - INFO - Epoch(train) [674][60/63] lr: 1.6843e-03 eta: 6:52:58 time: 0.5413 data_time: 0.0119 memory: 16131 loss: 1.3611 loss_prob: 0.7688 loss_thr: 0.4605 loss_db: 0.1317 2022/10/26 04:19:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:19:51 - mmengine - INFO - Epoch(train) [675][5/63] lr: 1.6814e-03 eta: 6:52:58 time: 0.7753 data_time: 0.1750 memory: 16131 loss: 1.2769 loss_prob: 0.6822 loss_thr: 0.4753 loss_db: 0.1194 2022/10/26 04:19:53 - mmengine - INFO - Epoch(train) [675][10/63] lr: 1.6814e-03 eta: 6:52:47 time: 0.7947 data_time: 0.1740 memory: 16131 loss: 1.2463 loss_prob: 0.6880 loss_thr: 0.4419 loss_db: 0.1164 2022/10/26 04:19:56 - mmengine - INFO - Epoch(train) [675][15/63] lr: 1.6814e-03 eta: 6:52:47 time: 0.5184 data_time: 0.0102 memory: 16131 loss: 1.2363 loss_prob: 0.6781 loss_thr: 0.4417 loss_db: 0.1166 2022/10/26 04:19:58 - mmengine - INFO - Epoch(train) [675][20/63] lr: 1.6814e-03 eta: 6:52:37 time: 0.5175 data_time: 0.0107 memory: 16131 loss: 1.1851 loss_prob: 0.6311 loss_thr: 0.4436 loss_db: 0.1104 2022/10/26 04:20:01 - mmengine - INFO - Epoch(train) [675][25/63] lr: 1.6814e-03 eta: 6:52:37 time: 0.5193 data_time: 0.0189 memory: 16131 loss: 1.2052 loss_prob: 0.6482 loss_thr: 0.4459 loss_db: 0.1111 2022/10/26 04:20:04 - mmengine - INFO - Epoch(train) [675][30/63] lr: 1.6814e-03 eta: 6:52:28 time: 0.5562 data_time: 0.0295 memory: 16131 loss: 1.1489 loss_prob: 0.6124 loss_thr: 0.4300 loss_db: 0.1065 2022/10/26 04:20:07 - mmengine - INFO - Epoch(train) [675][35/63] lr: 1.6814e-03 eta: 6:52:28 time: 0.5454 data_time: 0.0196 memory: 16131 loss: 1.1904 loss_prob: 0.6440 loss_thr: 0.4356 loss_db: 0.1108 2022/10/26 04:20:09 - mmengine - INFO - Epoch(train) [675][40/63] lr: 1.6814e-03 eta: 6:52:19 time: 0.5089 data_time: 0.0078 memory: 16131 loss: 1.3532 loss_prob: 0.7543 loss_thr: 0.4738 loss_db: 0.1251 2022/10/26 04:20:12 - mmengine - INFO - Epoch(train) [675][45/63] lr: 1.6814e-03 eta: 6:52:19 time: 0.5269 data_time: 0.0046 memory: 16131 loss: 1.3488 loss_prob: 0.7557 loss_thr: 0.4687 loss_db: 0.1243 2022/10/26 04:20:15 - mmengine - INFO - Epoch(train) [675][50/63] lr: 1.6814e-03 eta: 6:52:10 time: 0.5681 data_time: 0.0177 memory: 16131 loss: 1.2566 loss_prob: 0.6850 loss_thr: 0.4571 loss_db: 0.1146 2022/10/26 04:20:17 - mmengine - INFO - Epoch(train) [675][55/63] lr: 1.6814e-03 eta: 6:52:10 time: 0.5426 data_time: 0.0217 memory: 16131 loss: 1.2536 loss_prob: 0.6673 loss_thr: 0.4721 loss_db: 0.1143 2022/10/26 04:20:20 - mmengine - INFO - Epoch(train) [675][60/63] lr: 1.6814e-03 eta: 6:52:01 time: 0.5129 data_time: 0.0099 memory: 16131 loss: 1.2792 loss_prob: 0.7053 loss_thr: 0.4555 loss_db: 0.1184 2022/10/26 04:20:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:20:27 - mmengine - INFO - Epoch(train) [676][5/63] lr: 1.6785e-03 eta: 6:52:01 time: 0.7939 data_time: 0.2152 memory: 16131 loss: 1.1790 loss_prob: 0.6467 loss_thr: 0.4259 loss_db: 0.1064 2022/10/26 04:20:29 - mmengine - INFO - Epoch(train) [676][10/63] lr: 1.6785e-03 eta: 6:51:50 time: 0.7967 data_time: 0.2173 memory: 16131 loss: 1.1241 loss_prob: 0.6007 loss_thr: 0.4205 loss_db: 0.1028 2022/10/26 04:20:32 - mmengine - INFO - Epoch(train) [676][15/63] lr: 1.6785e-03 eta: 6:51:50 time: 0.5007 data_time: 0.0133 memory: 16131 loss: 1.1569 loss_prob: 0.6106 loss_thr: 0.4397 loss_db: 0.1066 2022/10/26 04:20:34 - mmengine - INFO - Epoch(train) [676][20/63] lr: 1.6785e-03 eta: 6:51:40 time: 0.5144 data_time: 0.0111 memory: 16131 loss: 1.2018 loss_prob: 0.6331 loss_thr: 0.4599 loss_db: 0.1087 2022/10/26 04:20:37 - mmengine - INFO - Epoch(train) [676][25/63] lr: 1.6785e-03 eta: 6:51:40 time: 0.5422 data_time: 0.0290 memory: 16131 loss: 1.1985 loss_prob: 0.6333 loss_thr: 0.4555 loss_db: 0.1098 2022/10/26 04:20:40 - mmengine - INFO - Epoch(train) [676][30/63] lr: 1.6785e-03 eta: 6:51:31 time: 0.5242 data_time: 0.0278 memory: 16131 loss: 1.1634 loss_prob: 0.6174 loss_thr: 0.4377 loss_db: 0.1083 2022/10/26 04:20:42 - mmengine - INFO - Epoch(train) [676][35/63] lr: 1.6785e-03 eta: 6:51:31 time: 0.4999 data_time: 0.0079 memory: 16131 loss: 1.2800 loss_prob: 0.7091 loss_thr: 0.4479 loss_db: 0.1230 2022/10/26 04:20:45 - mmengine - INFO - Epoch(train) [676][40/63] lr: 1.6785e-03 eta: 6:51:22 time: 0.5052 data_time: 0.0124 memory: 16131 loss: 1.4307 loss_prob: 0.8060 loss_thr: 0.4879 loss_db: 0.1369 2022/10/26 04:20:47 - mmengine - INFO - Epoch(train) [676][45/63] lr: 1.6785e-03 eta: 6:51:22 time: 0.5066 data_time: 0.0127 memory: 16131 loss: 1.3593 loss_prob: 0.7450 loss_thr: 0.4901 loss_db: 0.1243 2022/10/26 04:20:50 - mmengine - INFO - Epoch(train) [676][50/63] lr: 1.6785e-03 eta: 6:51:13 time: 0.5174 data_time: 0.0217 memory: 16131 loss: 1.3409 loss_prob: 0.7376 loss_thr: 0.4782 loss_db: 0.1252 2022/10/26 04:20:53 - mmengine - INFO - Epoch(train) [676][55/63] lr: 1.6785e-03 eta: 6:51:13 time: 0.5240 data_time: 0.0198 memory: 16131 loss: 1.3347 loss_prob: 0.7417 loss_thr: 0.4684 loss_db: 0.1245 2022/10/26 04:20:55 - mmengine - INFO - Epoch(train) [676][60/63] lr: 1.6785e-03 eta: 6:51:03 time: 0.5002 data_time: 0.0069 memory: 16131 loss: 1.2897 loss_prob: 0.7108 loss_thr: 0.4622 loss_db: 0.1167 2022/10/26 04:20:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:21:01 - mmengine - INFO - Epoch(train) [677][5/63] lr: 1.6756e-03 eta: 6:51:03 time: 0.7230 data_time: 0.1975 memory: 16131 loss: 1.3139 loss_prob: 0.7127 loss_thr: 0.4783 loss_db: 0.1229 2022/10/26 04:21:04 - mmengine - INFO - Epoch(train) [677][10/63] lr: 1.6756e-03 eta: 6:50:52 time: 0.7618 data_time: 0.1985 memory: 16131 loss: 1.4054 loss_prob: 0.7777 loss_thr: 0.4967 loss_db: 0.1309 2022/10/26 04:21:06 - mmengine - INFO - Epoch(train) [677][15/63] lr: 1.6756e-03 eta: 6:50:52 time: 0.5150 data_time: 0.0143 memory: 16131 loss: 1.3095 loss_prob: 0.7200 loss_thr: 0.4692 loss_db: 0.1203 2022/10/26 04:21:09 - mmengine - INFO - Epoch(train) [677][20/63] lr: 1.6756e-03 eta: 6:50:43 time: 0.5041 data_time: 0.0120 memory: 16131 loss: 1.2344 loss_prob: 0.6577 loss_thr: 0.4647 loss_db: 0.1121 2022/10/26 04:21:12 - mmengine - INFO - Epoch(train) [677][25/63] lr: 1.6756e-03 eta: 6:50:43 time: 0.5365 data_time: 0.0212 memory: 16131 loss: 1.2006 loss_prob: 0.6374 loss_thr: 0.4525 loss_db: 0.1106 2022/10/26 04:21:14 - mmengine - INFO - Epoch(train) [677][30/63] lr: 1.6756e-03 eta: 6:50:33 time: 0.5369 data_time: 0.0252 memory: 16131 loss: 1.1553 loss_prob: 0.6200 loss_thr: 0.4291 loss_db: 0.1061 2022/10/26 04:21:17 - mmengine - INFO - Epoch(train) [677][35/63] lr: 1.6756e-03 eta: 6:50:33 time: 0.4997 data_time: 0.0145 memory: 16131 loss: 1.2535 loss_prob: 0.6805 loss_thr: 0.4581 loss_db: 0.1150 2022/10/26 04:21:19 - mmengine - INFO - Epoch(train) [677][40/63] lr: 1.6756e-03 eta: 6:50:24 time: 0.4947 data_time: 0.0135 memory: 16131 loss: 1.2719 loss_prob: 0.6995 loss_thr: 0.4529 loss_db: 0.1195 2022/10/26 04:21:22 - mmengine - INFO - Epoch(train) [677][45/63] lr: 1.6756e-03 eta: 6:50:24 time: 0.4923 data_time: 0.0089 memory: 16131 loss: 1.2357 loss_prob: 0.6677 loss_thr: 0.4529 loss_db: 0.1151 2022/10/26 04:21:24 - mmengine - INFO - Epoch(train) [677][50/63] lr: 1.6756e-03 eta: 6:50:15 time: 0.5219 data_time: 0.0137 memory: 16131 loss: 1.2064 loss_prob: 0.6346 loss_thr: 0.4622 loss_db: 0.1096 2022/10/26 04:21:27 - mmengine - INFO - Epoch(train) [677][55/63] lr: 1.6756e-03 eta: 6:50:15 time: 0.5276 data_time: 0.0197 memory: 16131 loss: 1.2775 loss_prob: 0.6944 loss_thr: 0.4700 loss_db: 0.1131 2022/10/26 04:21:29 - mmengine - INFO - Epoch(train) [677][60/63] lr: 1.6756e-03 eta: 6:50:05 time: 0.4986 data_time: 0.0122 memory: 16131 loss: 1.3076 loss_prob: 0.7283 loss_thr: 0.4602 loss_db: 0.1191 2022/10/26 04:21:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:21:36 - mmengine - INFO - Epoch(train) [678][5/63] lr: 1.6727e-03 eta: 6:50:05 time: 0.7376 data_time: 0.2188 memory: 16131 loss: 1.2150 loss_prob: 0.6477 loss_thr: 0.4544 loss_db: 0.1129 2022/10/26 04:21:39 - mmengine - INFO - Epoch(train) [678][10/63] lr: 1.6727e-03 eta: 6:49:54 time: 0.7942 data_time: 0.2200 memory: 16131 loss: 1.1980 loss_prob: 0.6445 loss_thr: 0.4416 loss_db: 0.1119 2022/10/26 04:21:42 - mmengine - INFO - Epoch(train) [678][15/63] lr: 1.6727e-03 eta: 6:49:54 time: 0.5901 data_time: 0.0086 memory: 16131 loss: 1.2457 loss_prob: 0.6800 loss_thr: 0.4477 loss_db: 0.1180 2022/10/26 04:21:44 - mmengine - INFO - Epoch(train) [678][20/63] lr: 1.6727e-03 eta: 6:49:45 time: 0.5501 data_time: 0.0071 memory: 16131 loss: 1.3176 loss_prob: 0.7195 loss_thr: 0.4762 loss_db: 0.1219 2022/10/26 04:21:47 - mmengine - INFO - Epoch(train) [678][25/63] lr: 1.6727e-03 eta: 6:49:45 time: 0.5036 data_time: 0.0167 memory: 16131 loss: 1.2258 loss_prob: 0.6580 loss_thr: 0.4559 loss_db: 0.1119 2022/10/26 04:21:49 - mmengine - INFO - Epoch(train) [678][30/63] lr: 1.6727e-03 eta: 6:49:36 time: 0.4982 data_time: 0.0321 memory: 16131 loss: 1.2180 loss_prob: 0.6492 loss_thr: 0.4571 loss_db: 0.1118 2022/10/26 04:21:52 - mmengine - INFO - Epoch(train) [678][35/63] lr: 1.6727e-03 eta: 6:49:36 time: 0.5116 data_time: 0.0216 memory: 16131 loss: 1.2472 loss_prob: 0.6706 loss_thr: 0.4627 loss_db: 0.1139 2022/10/26 04:21:54 - mmengine - INFO - Epoch(train) [678][40/63] lr: 1.6727e-03 eta: 6:49:27 time: 0.4999 data_time: 0.0048 memory: 16131 loss: 1.2207 loss_prob: 0.6657 loss_thr: 0.4428 loss_db: 0.1121 2022/10/26 04:21:57 - mmengine - INFO - Epoch(train) [678][45/63] lr: 1.6727e-03 eta: 6:49:27 time: 0.4976 data_time: 0.0056 memory: 16131 loss: 1.1691 loss_prob: 0.6280 loss_thr: 0.4351 loss_db: 0.1061 2022/10/26 04:22:00 - mmengine - INFO - Epoch(train) [678][50/63] lr: 1.6727e-03 eta: 6:49:18 time: 0.5400 data_time: 0.0214 memory: 16131 loss: 1.2329 loss_prob: 0.6655 loss_thr: 0.4520 loss_db: 0.1154 2022/10/26 04:22:02 - mmengine - INFO - Epoch(train) [678][55/63] lr: 1.6727e-03 eta: 6:49:18 time: 0.5384 data_time: 0.0216 memory: 16131 loss: 1.2484 loss_prob: 0.6862 loss_thr: 0.4432 loss_db: 0.1189 2022/10/26 04:22:05 - mmengine - INFO - Epoch(train) [678][60/63] lr: 1.6727e-03 eta: 6:49:08 time: 0.5107 data_time: 0.0055 memory: 16131 loss: 1.1902 loss_prob: 0.6439 loss_thr: 0.4373 loss_db: 0.1090 2022/10/26 04:22:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:22:10 - mmengine - INFO - Epoch(train) [679][5/63] lr: 1.6699e-03 eta: 6:49:08 time: 0.6664 data_time: 0.1859 memory: 16131 loss: 1.2030 loss_prob: 0.6489 loss_thr: 0.4429 loss_db: 0.1112 2022/10/26 04:22:13 - mmengine - INFO - Epoch(train) [679][10/63] lr: 1.6699e-03 eta: 6:48:57 time: 0.7004 data_time: 0.1943 memory: 16131 loss: 1.2814 loss_prob: 0.7031 loss_thr: 0.4613 loss_db: 0.1170 2022/10/26 04:22:16 - mmengine - INFO - Epoch(train) [679][15/63] lr: 1.6699e-03 eta: 6:48:57 time: 0.5188 data_time: 0.0136 memory: 16131 loss: 1.1990 loss_prob: 0.6527 loss_thr: 0.4362 loss_db: 0.1102 2022/10/26 04:22:18 - mmengine - INFO - Epoch(train) [679][20/63] lr: 1.6699e-03 eta: 6:48:47 time: 0.5009 data_time: 0.0053 memory: 16131 loss: 1.1686 loss_prob: 0.6299 loss_thr: 0.4301 loss_db: 0.1086 2022/10/26 04:22:21 - mmengine - INFO - Epoch(train) [679][25/63] lr: 1.6699e-03 eta: 6:48:47 time: 0.5601 data_time: 0.0128 memory: 16131 loss: 1.2834 loss_prob: 0.6957 loss_thr: 0.4673 loss_db: 0.1204 2022/10/26 04:22:24 - mmengine - INFO - Epoch(train) [679][30/63] lr: 1.6699e-03 eta: 6:48:39 time: 0.5926 data_time: 0.0280 memory: 16131 loss: 1.2827 loss_prob: 0.6953 loss_thr: 0.4674 loss_db: 0.1200 2022/10/26 04:22:27 - mmengine - INFO - Epoch(train) [679][35/63] lr: 1.6699e-03 eta: 6:48:39 time: 0.5940 data_time: 0.0262 memory: 16131 loss: 1.1507 loss_prob: 0.6112 loss_thr: 0.4339 loss_db: 0.1056 2022/10/26 04:22:30 - mmengine - INFO - Epoch(train) [679][40/63] lr: 1.6699e-03 eta: 6:48:30 time: 0.5773 data_time: 0.0175 memory: 16131 loss: 1.1534 loss_prob: 0.6126 loss_thr: 0.4373 loss_db: 0.1034 2022/10/26 04:22:32 - mmengine - INFO - Epoch(train) [679][45/63] lr: 1.6699e-03 eta: 6:48:30 time: 0.5043 data_time: 0.0116 memory: 16131 loss: 1.1649 loss_prob: 0.6315 loss_thr: 0.4262 loss_db: 0.1072 2022/10/26 04:22:35 - mmengine - INFO - Epoch(train) [679][50/63] lr: 1.6699e-03 eta: 6:48:21 time: 0.5170 data_time: 0.0151 memory: 16131 loss: 1.1439 loss_prob: 0.6174 loss_thr: 0.4219 loss_db: 0.1046 2022/10/26 04:22:38 - mmengine - INFO - Epoch(train) [679][55/63] lr: 1.6699e-03 eta: 6:48:21 time: 0.5438 data_time: 0.0231 memory: 16131 loss: 1.1813 loss_prob: 0.6294 loss_thr: 0.4460 loss_db: 0.1058 2022/10/26 04:22:40 - mmengine - INFO - Epoch(train) [679][60/63] lr: 1.6699e-03 eta: 6:48:11 time: 0.5283 data_time: 0.0138 memory: 16131 loss: 1.1977 loss_prob: 0.6442 loss_thr: 0.4438 loss_db: 0.1097 2022/10/26 04:22:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:22:47 - mmengine - INFO - Epoch(train) [680][5/63] lr: 1.6670e-03 eta: 6:48:11 time: 0.7523 data_time: 0.2194 memory: 16131 loss: 1.1873 loss_prob: 0.6419 loss_thr: 0.4348 loss_db: 0.1105 2022/10/26 04:22:49 - mmengine - INFO - Epoch(train) [680][10/63] lr: 1.6670e-03 eta: 6:48:00 time: 0.7557 data_time: 0.2179 memory: 16131 loss: 1.1495 loss_prob: 0.6098 loss_thr: 0.4354 loss_db: 0.1042 2022/10/26 04:22:52 - mmengine - INFO - Epoch(train) [680][15/63] lr: 1.6670e-03 eta: 6:48:00 time: 0.5046 data_time: 0.0060 memory: 16131 loss: 1.0992 loss_prob: 0.5728 loss_thr: 0.4280 loss_db: 0.0983 2022/10/26 04:22:54 - mmengine - INFO - Epoch(train) [680][20/63] lr: 1.6670e-03 eta: 6:47:51 time: 0.5130 data_time: 0.0069 memory: 16131 loss: 1.1511 loss_prob: 0.6126 loss_thr: 0.4336 loss_db: 0.1049 2022/10/26 04:22:57 - mmengine - INFO - Epoch(train) [680][25/63] lr: 1.6670e-03 eta: 6:47:51 time: 0.5291 data_time: 0.0379 memory: 16131 loss: 1.1541 loss_prob: 0.6144 loss_thr: 0.4361 loss_db: 0.1036 2022/10/26 04:22:59 - mmengine - INFO - Epoch(train) [680][30/63] lr: 1.6670e-03 eta: 6:47:42 time: 0.5299 data_time: 0.0364 memory: 16131 loss: 1.2198 loss_prob: 0.6599 loss_thr: 0.4485 loss_db: 0.1114 2022/10/26 04:23:02 - mmengine - INFO - Epoch(train) [680][35/63] lr: 1.6670e-03 eta: 6:47:42 time: 0.4865 data_time: 0.0053 memory: 16131 loss: 1.3273 loss_prob: 0.7295 loss_thr: 0.4733 loss_db: 0.1245 2022/10/26 04:23:05 - mmengine - INFO - Epoch(train) [680][40/63] lr: 1.6670e-03 eta: 6:47:32 time: 0.5086 data_time: 0.0063 memory: 16131 loss: 1.2774 loss_prob: 0.6814 loss_thr: 0.4798 loss_db: 0.1161 2022/10/26 04:23:07 - mmengine - INFO - Epoch(train) [680][45/63] lr: 1.6670e-03 eta: 6:47:32 time: 0.5116 data_time: 0.0056 memory: 16131 loss: 1.2208 loss_prob: 0.6424 loss_thr: 0.4687 loss_db: 0.1097 2022/10/26 04:23:10 - mmengine - INFO - Epoch(train) [680][50/63] lr: 1.6670e-03 eta: 6:47:23 time: 0.5078 data_time: 0.0219 memory: 16131 loss: 1.2632 loss_prob: 0.6852 loss_thr: 0.4557 loss_db: 0.1224 2022/10/26 04:23:12 - mmengine - INFO - Epoch(train) [680][55/63] lr: 1.6670e-03 eta: 6:47:23 time: 0.5168 data_time: 0.0229 memory: 16131 loss: 1.2391 loss_prob: 0.6715 loss_thr: 0.4466 loss_db: 0.1210 2022/10/26 04:23:15 - mmengine - INFO - Epoch(train) [680][60/63] lr: 1.6670e-03 eta: 6:47:14 time: 0.5295 data_time: 0.0102 memory: 16131 loss: 1.2985 loss_prob: 0.7342 loss_thr: 0.4472 loss_db: 0.1171 2022/10/26 04:23:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:23:16 - mmengine - INFO - Saving checkpoint at 680 epochs 2022/10/26 04:23:25 - mmengine - INFO - Epoch(val) [680][5/32] eta: 6:47:14 time: 0.5390 data_time: 0.0844 memory: 16131 2022/10/26 04:23:28 - mmengine - INFO - Epoch(val) [680][10/32] eta: 0:00:13 time: 0.6283 data_time: 0.1261 memory: 15724 2022/10/26 04:23:31 - mmengine - INFO - Epoch(val) [680][15/32] eta: 0:00:13 time: 0.5574 data_time: 0.0540 memory: 15724 2022/10/26 04:23:34 - mmengine - INFO - Epoch(val) [680][20/32] eta: 0:00:06 time: 0.5550 data_time: 0.0531 memory: 15724 2022/10/26 04:23:36 - mmengine - INFO - Epoch(val) [680][25/32] eta: 0:00:06 time: 0.5797 data_time: 0.0576 memory: 15724 2022/10/26 04:23:39 - mmengine - INFO - Epoch(val) [680][30/32] eta: 0:00:01 time: 0.5350 data_time: 0.0226 memory: 15724 2022/10/26 04:23:40 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8286, precision: 0.7286, hmean: 0.7754 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8286, precision: 0.7876, hmean: 0.8076 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8276, precision: 0.8197, hmean: 0.8237 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8228, precision: 0.8498, hmean: 0.8361 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8016, precision: 0.8885, hmean: 0.8428 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6668, precision: 0.9403, hmean: 0.7803 2022/10/26 04:23:40 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0448, precision: 0.9894, hmean: 0.0857 2022/10/26 04:23:40 - mmengine - INFO - Epoch(val) [680][32/32] icdar/precision: 0.8885 icdar/recall: 0.8016 icdar/hmean: 0.8428 2022/10/26 04:23:45 - mmengine - INFO - Epoch(train) [681][5/63] lr: 1.6641e-03 eta: 0:00:01 time: 0.7549 data_time: 0.1963 memory: 16131 loss: 1.3443 loss_prob: 0.7630 loss_thr: 0.4597 loss_db: 0.1216 2022/10/26 04:23:48 - mmengine - INFO - Epoch(train) [681][10/63] lr: 1.6641e-03 eta: 6:47:03 time: 0.7948 data_time: 0.1942 memory: 16131 loss: 1.2155 loss_prob: 0.6653 loss_thr: 0.4353 loss_db: 0.1149 2022/10/26 04:23:50 - mmengine - INFO - Epoch(train) [681][15/63] lr: 1.6641e-03 eta: 6:47:03 time: 0.5644 data_time: 0.0052 memory: 16131 loss: 1.2076 loss_prob: 0.6629 loss_thr: 0.4292 loss_db: 0.1155 2022/10/26 04:23:53 - mmengine - INFO - Epoch(train) [681][20/63] lr: 1.6641e-03 eta: 6:46:54 time: 0.5244 data_time: 0.0053 memory: 16131 loss: 1.2438 loss_prob: 0.6764 loss_thr: 0.4513 loss_db: 0.1161 2022/10/26 04:23:56 - mmengine - INFO - Epoch(train) [681][25/63] lr: 1.6641e-03 eta: 6:46:54 time: 0.5206 data_time: 0.0198 memory: 16131 loss: 1.2943 loss_prob: 0.7055 loss_thr: 0.4690 loss_db: 0.1199 2022/10/26 04:23:59 - mmengine - INFO - Epoch(train) [681][30/63] lr: 1.6641e-03 eta: 6:46:45 time: 0.5666 data_time: 0.0344 memory: 16131 loss: 1.2670 loss_prob: 0.6895 loss_thr: 0.4592 loss_db: 0.1182 2022/10/26 04:24:01 - mmengine - INFO - Epoch(train) [681][35/63] lr: 1.6641e-03 eta: 6:46:45 time: 0.5742 data_time: 0.0193 memory: 16131 loss: 1.1012 loss_prob: 0.5816 loss_thr: 0.4199 loss_db: 0.0997 2022/10/26 04:24:04 - mmengine - INFO - Epoch(train) [681][40/63] lr: 1.6641e-03 eta: 6:46:36 time: 0.5676 data_time: 0.0059 memory: 16131 loss: 1.1103 loss_prob: 0.5923 loss_thr: 0.4185 loss_db: 0.0995 2022/10/26 04:24:07 - mmengine - INFO - Epoch(train) [681][45/63] lr: 1.6641e-03 eta: 6:46:36 time: 0.5719 data_time: 0.0065 memory: 16131 loss: 1.2112 loss_prob: 0.6585 loss_thr: 0.4411 loss_db: 0.1116 2022/10/26 04:24:10 - mmengine - INFO - Epoch(train) [681][50/63] lr: 1.6641e-03 eta: 6:46:27 time: 0.5343 data_time: 0.0118 memory: 16131 loss: 1.1598 loss_prob: 0.6198 loss_thr: 0.4331 loss_db: 0.1069 2022/10/26 04:24:12 - mmengine - INFO - Epoch(train) [681][55/63] lr: 1.6641e-03 eta: 6:46:27 time: 0.5159 data_time: 0.0236 memory: 16131 loss: 1.1067 loss_prob: 0.5743 loss_thr: 0.4341 loss_db: 0.0983 2022/10/26 04:24:15 - mmengine - INFO - Epoch(train) [681][60/63] lr: 1.6641e-03 eta: 6:46:18 time: 0.5091 data_time: 0.0204 memory: 16131 loss: 1.2898 loss_prob: 0.7299 loss_thr: 0.4445 loss_db: 0.1154 2022/10/26 04:24:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:24:21 - mmengine - INFO - Epoch(train) [682][5/63] lr: 1.6612e-03 eta: 6:46:18 time: 0.6863 data_time: 0.2030 memory: 16131 loss: 1.2101 loss_prob: 0.6547 loss_thr: 0.4442 loss_db: 0.1112 2022/10/26 04:24:23 - mmengine - INFO - Epoch(train) [682][10/63] lr: 1.6612e-03 eta: 6:46:06 time: 0.6988 data_time: 0.2013 memory: 16131 loss: 1.2359 loss_prob: 0.6651 loss_thr: 0.4589 loss_db: 0.1120 2022/10/26 04:24:26 - mmengine - INFO - Epoch(train) [682][15/63] lr: 1.6612e-03 eta: 6:46:06 time: 0.5163 data_time: 0.0051 memory: 16131 loss: 1.1848 loss_prob: 0.6275 loss_thr: 0.4495 loss_db: 0.1078 2022/10/26 04:24:28 - mmengine - INFO - Epoch(train) [682][20/63] lr: 1.6612e-03 eta: 6:45:57 time: 0.5097 data_time: 0.0076 memory: 16131 loss: 1.2528 loss_prob: 0.6798 loss_thr: 0.4552 loss_db: 0.1179 2022/10/26 04:24:31 - mmengine - INFO - Epoch(train) [682][25/63] lr: 1.6612e-03 eta: 6:45:57 time: 0.5100 data_time: 0.0252 memory: 16131 loss: 1.3377 loss_prob: 0.7345 loss_thr: 0.4748 loss_db: 0.1284 2022/10/26 04:24:33 - mmengine - INFO - Epoch(train) [682][30/63] lr: 1.6612e-03 eta: 6:45:48 time: 0.5094 data_time: 0.0323 memory: 16131 loss: 1.1855 loss_prob: 0.6334 loss_thr: 0.4406 loss_db: 0.1116 2022/10/26 04:24:36 - mmengine - INFO - Epoch(train) [682][35/63] lr: 1.6612e-03 eta: 6:45:48 time: 0.5139 data_time: 0.0159 memory: 16131 loss: 1.2114 loss_prob: 0.6519 loss_thr: 0.4454 loss_db: 0.1141 2022/10/26 04:24:39 - mmengine - INFO - Epoch(train) [682][40/63] lr: 1.6612e-03 eta: 6:45:38 time: 0.5187 data_time: 0.0091 memory: 16131 loss: 1.2694 loss_prob: 0.6878 loss_thr: 0.4647 loss_db: 0.1168 2022/10/26 04:24:42 - mmengine - INFO - Epoch(train) [682][45/63] lr: 1.6612e-03 eta: 6:45:38 time: 0.5680 data_time: 0.0082 memory: 16131 loss: 1.2922 loss_prob: 0.7030 loss_thr: 0.4714 loss_db: 0.1178 2022/10/26 04:24:44 - mmengine - INFO - Epoch(train) [682][50/63] lr: 1.6612e-03 eta: 6:45:30 time: 0.5774 data_time: 0.0184 memory: 16131 loss: 1.2451 loss_prob: 0.6765 loss_thr: 0.4517 loss_db: 0.1169 2022/10/26 04:24:47 - mmengine - INFO - Epoch(train) [682][55/63] lr: 1.6612e-03 eta: 6:45:30 time: 0.5228 data_time: 0.0235 memory: 16131 loss: 1.1688 loss_prob: 0.6379 loss_thr: 0.4219 loss_db: 0.1089 2022/10/26 04:24:50 - mmengine - INFO - Epoch(train) [682][60/63] lr: 1.6612e-03 eta: 6:45:21 time: 0.5313 data_time: 0.0115 memory: 16131 loss: 1.1957 loss_prob: 0.6607 loss_thr: 0.4235 loss_db: 0.1115 2022/10/26 04:24:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:24:56 - mmengine - INFO - Epoch(train) [683][5/63] lr: 1.6583e-03 eta: 6:45:21 time: 0.7250 data_time: 0.1959 memory: 16131 loss: 1.3247 loss_prob: 0.7239 loss_thr: 0.4808 loss_db: 0.1200 2022/10/26 04:24:59 - mmengine - INFO - Epoch(train) [683][10/63] lr: 1.6583e-03 eta: 6:45:09 time: 0.7496 data_time: 0.1950 memory: 16131 loss: 1.3242 loss_prob: 0.7265 loss_thr: 0.4802 loss_db: 0.1176 2022/10/26 04:25:01 - mmengine - INFO - Epoch(train) [683][15/63] lr: 1.6583e-03 eta: 6:45:09 time: 0.5262 data_time: 0.0095 memory: 16131 loss: 1.2064 loss_prob: 0.6505 loss_thr: 0.4415 loss_db: 0.1144 2022/10/26 04:25:03 - mmengine - INFO - Epoch(train) [683][20/63] lr: 1.6583e-03 eta: 6:45:00 time: 0.4942 data_time: 0.0102 memory: 16131 loss: 1.1980 loss_prob: 0.6485 loss_thr: 0.4369 loss_db: 0.1126 2022/10/26 04:25:06 - mmengine - INFO - Epoch(train) [683][25/63] lr: 1.6583e-03 eta: 6:45:00 time: 0.5192 data_time: 0.0311 memory: 16131 loss: 1.2465 loss_prob: 0.6871 loss_thr: 0.4481 loss_db: 0.1113 2022/10/26 04:25:09 - mmengine - INFO - Epoch(train) [683][30/63] lr: 1.6583e-03 eta: 6:44:51 time: 0.5387 data_time: 0.0442 memory: 16131 loss: 1.2050 loss_prob: 0.6576 loss_thr: 0.4368 loss_db: 0.1105 2022/10/26 04:25:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:25:11 - mmengine - INFO - Epoch(train) [683][35/63] lr: 1.6583e-03 eta: 6:44:51 time: 0.5163 data_time: 0.0216 memory: 16131 loss: 1.2382 loss_prob: 0.6687 loss_thr: 0.4512 loss_db: 0.1183 2022/10/26 04:25:14 - mmengine - INFO - Epoch(train) [683][40/63] lr: 1.6583e-03 eta: 6:44:42 time: 0.4930 data_time: 0.0058 memory: 16131 loss: 1.2676 loss_prob: 0.6861 loss_thr: 0.4623 loss_db: 0.1193 2022/10/26 04:25:18 - mmengine - INFO - Epoch(train) [683][45/63] lr: 1.6583e-03 eta: 6:44:42 time: 0.6194 data_time: 0.0093 memory: 16131 loss: 1.1824 loss_prob: 0.6335 loss_thr: 0.4398 loss_db: 0.1090 2022/10/26 04:25:20 - mmengine - INFO - Epoch(train) [683][50/63] lr: 1.6583e-03 eta: 6:44:33 time: 0.6440 data_time: 0.0280 memory: 16131 loss: 1.2425 loss_prob: 0.6772 loss_thr: 0.4476 loss_db: 0.1177 2022/10/26 04:25:23 - mmengine - INFO - Epoch(train) [683][55/63] lr: 1.6583e-03 eta: 6:44:33 time: 0.5688 data_time: 0.0245 memory: 16131 loss: 1.2981 loss_prob: 0.7101 loss_thr: 0.4651 loss_db: 0.1230 2022/10/26 04:25:26 - mmengine - INFO - Epoch(train) [683][60/63] lr: 1.6583e-03 eta: 6:44:24 time: 0.5397 data_time: 0.0052 memory: 16131 loss: 1.2302 loss_prob: 0.6657 loss_thr: 0.4525 loss_db: 0.1120 2022/10/26 04:25:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:25:31 - mmengine - INFO - Epoch(train) [684][5/63] lr: 1.6554e-03 eta: 6:44:24 time: 0.6767 data_time: 0.1501 memory: 16131 loss: 1.1938 loss_prob: 0.6326 loss_thr: 0.4524 loss_db: 0.1089 2022/10/26 04:25:35 - mmengine - INFO - Epoch(train) [684][10/63] lr: 1.6554e-03 eta: 6:44:13 time: 0.7606 data_time: 0.1637 memory: 16131 loss: 1.2302 loss_prob: 0.6590 loss_thr: 0.4602 loss_db: 0.1110 2022/10/26 04:25:37 - mmengine - INFO - Epoch(train) [684][15/63] lr: 1.6554e-03 eta: 6:44:13 time: 0.5699 data_time: 0.0186 memory: 16131 loss: 1.2322 loss_prob: 0.6655 loss_thr: 0.4558 loss_db: 0.1109 2022/10/26 04:25:40 - mmengine - INFO - Epoch(train) [684][20/63] lr: 1.6554e-03 eta: 6:44:04 time: 0.5124 data_time: 0.0046 memory: 16131 loss: 1.2201 loss_prob: 0.6578 loss_thr: 0.4498 loss_db: 0.1125 2022/10/26 04:25:42 - mmengine - INFO - Epoch(train) [684][25/63] lr: 1.6554e-03 eta: 6:44:04 time: 0.4996 data_time: 0.0075 memory: 16131 loss: 1.2421 loss_prob: 0.6807 loss_thr: 0.4465 loss_db: 0.1149 2022/10/26 04:25:45 - mmengine - INFO - Epoch(train) [684][30/63] lr: 1.6554e-03 eta: 6:43:55 time: 0.5525 data_time: 0.0245 memory: 16131 loss: 1.2249 loss_prob: 0.6702 loss_thr: 0.4449 loss_db: 0.1099 2022/10/26 04:25:48 - mmengine - INFO - Epoch(train) [684][35/63] lr: 1.6554e-03 eta: 6:43:55 time: 0.5877 data_time: 0.0329 memory: 16131 loss: 1.2083 loss_prob: 0.6552 loss_thr: 0.4417 loss_db: 0.1113 2022/10/26 04:25:51 - mmengine - INFO - Epoch(train) [684][40/63] lr: 1.6554e-03 eta: 6:43:46 time: 0.5370 data_time: 0.0165 memory: 16131 loss: 1.2316 loss_prob: 0.6624 loss_thr: 0.4531 loss_db: 0.1161 2022/10/26 04:25:53 - mmengine - INFO - Epoch(train) [684][45/63] lr: 1.6554e-03 eta: 6:43:46 time: 0.5053 data_time: 0.0069 memory: 16131 loss: 1.1480 loss_prob: 0.6087 loss_thr: 0.4349 loss_db: 0.1043 2022/10/26 04:25:56 - mmengine - INFO - Epoch(train) [684][50/63] lr: 1.6554e-03 eta: 6:43:37 time: 0.5285 data_time: 0.0107 memory: 16131 loss: 1.3184 loss_prob: 0.7258 loss_thr: 0.4721 loss_db: 0.1205 2022/10/26 04:25:59 - mmengine - INFO - Epoch(train) [684][55/63] lr: 1.6554e-03 eta: 6:43:37 time: 0.5497 data_time: 0.0183 memory: 16131 loss: 1.5314 loss_prob: 0.8676 loss_thr: 0.5215 loss_db: 0.1422 2022/10/26 04:26:01 - mmengine - INFO - Epoch(train) [684][60/63] lr: 1.6554e-03 eta: 6:43:28 time: 0.5407 data_time: 0.0191 memory: 16131 loss: 2.2964 loss_prob: 1.5322 loss_thr: 0.5675 loss_db: 0.1967 2022/10/26 04:26:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:26:07 - mmengine - INFO - Epoch(train) [685][5/63] lr: 1.6525e-03 eta: 6:43:28 time: 0.7221 data_time: 0.1870 memory: 16131 loss: 2.7465 loss_prob: 1.8100 loss_thr: 0.6784 loss_db: 0.2581 2022/10/26 04:26:10 - mmengine - INFO - Epoch(train) [685][10/63] lr: 1.6525e-03 eta: 6:43:17 time: 0.7524 data_time: 0.1899 memory: 16131 loss: 2.3003 loss_prob: 1.4280 loss_thr: 0.6445 loss_db: 0.2278 2022/10/26 04:26:13 - mmengine - INFO - Epoch(train) [685][15/63] lr: 1.6525e-03 eta: 6:43:17 time: 0.5263 data_time: 0.0101 memory: 16131 loss: 2.1816 loss_prob: 1.3433 loss_thr: 0.6233 loss_db: 0.2150 2022/10/26 04:26:15 - mmengine - INFO - Epoch(train) [685][20/63] lr: 1.6525e-03 eta: 6:43:07 time: 0.5173 data_time: 0.0059 memory: 16131 loss: 1.9384 loss_prob: 1.1529 loss_thr: 0.5973 loss_db: 0.1882 2022/10/26 04:26:18 - mmengine - INFO - Epoch(train) [685][25/63] lr: 1.6525e-03 eta: 6:43:07 time: 0.4951 data_time: 0.0136 memory: 16131 loss: 1.7095 loss_prob: 0.9981 loss_thr: 0.5473 loss_db: 0.1641 2022/10/26 04:26:20 - mmengine - INFO - Epoch(train) [685][30/63] lr: 1.6525e-03 eta: 6:42:58 time: 0.5247 data_time: 0.0330 memory: 16131 loss: 1.5272 loss_prob: 0.8766 loss_thr: 0.5049 loss_db: 0.1456 2022/10/26 04:26:23 - mmengine - INFO - Epoch(train) [685][35/63] lr: 1.6525e-03 eta: 6:42:58 time: 0.5254 data_time: 0.0285 memory: 16131 loss: 1.4862 loss_prob: 0.8327 loss_thr: 0.5139 loss_db: 0.1396 2022/10/26 04:26:26 - mmengine - INFO - Epoch(train) [685][40/63] lr: 1.6525e-03 eta: 6:42:49 time: 0.5385 data_time: 0.0081 memory: 16131 loss: 1.4539 loss_prob: 0.8098 loss_thr: 0.5100 loss_db: 0.1341 2022/10/26 04:26:28 - mmengine - INFO - Epoch(train) [685][45/63] lr: 1.6525e-03 eta: 6:42:49 time: 0.5475 data_time: 0.0078 memory: 16131 loss: 1.3678 loss_prob: 0.7616 loss_thr: 0.4824 loss_db: 0.1239 2022/10/26 04:26:31 - mmengine - INFO - Epoch(train) [685][50/63] lr: 1.6525e-03 eta: 6:42:40 time: 0.5308 data_time: 0.0143 memory: 16131 loss: 1.3547 loss_prob: 0.7583 loss_thr: 0.4709 loss_db: 0.1255 2022/10/26 04:26:34 - mmengine - INFO - Epoch(train) [685][55/63] lr: 1.6525e-03 eta: 6:42:40 time: 0.5384 data_time: 0.0231 memory: 16131 loss: 1.4458 loss_prob: 0.8217 loss_thr: 0.4853 loss_db: 0.1389 2022/10/26 04:26:37 - mmengine - INFO - Epoch(train) [685][60/63] lr: 1.6525e-03 eta: 6:42:31 time: 0.5493 data_time: 0.0187 memory: 16131 loss: 1.5461 loss_prob: 0.8819 loss_thr: 0.5167 loss_db: 0.1474 2022/10/26 04:26:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:26:43 - mmengine - INFO - Epoch(train) [686][5/63] lr: 1.6496e-03 eta: 6:42:31 time: 0.7679 data_time: 0.2131 memory: 16131 loss: 1.3344 loss_prob: 0.7350 loss_thr: 0.4753 loss_db: 0.1241 2022/10/26 04:26:46 - mmengine - INFO - Epoch(train) [686][10/63] lr: 1.6496e-03 eta: 6:42:20 time: 0.7813 data_time: 0.2128 memory: 16131 loss: 1.3267 loss_prob: 0.7324 loss_thr: 0.4724 loss_db: 0.1218 2022/10/26 04:26:48 - mmengine - INFO - Epoch(train) [686][15/63] lr: 1.6496e-03 eta: 6:42:20 time: 0.5372 data_time: 0.0053 memory: 16131 loss: 1.3552 loss_prob: 0.7607 loss_thr: 0.4711 loss_db: 0.1234 2022/10/26 04:26:51 - mmengine - INFO - Epoch(train) [686][20/63] lr: 1.6496e-03 eta: 6:42:11 time: 0.5216 data_time: 0.0056 memory: 16131 loss: 1.2163 loss_prob: 0.6702 loss_thr: 0.4362 loss_db: 0.1099 2022/10/26 04:26:54 - mmengine - INFO - Epoch(train) [686][25/63] lr: 1.6496e-03 eta: 6:42:11 time: 0.5194 data_time: 0.0264 memory: 16131 loss: 1.2679 loss_prob: 0.7065 loss_thr: 0.4447 loss_db: 0.1167 2022/10/26 04:26:56 - mmengine - INFO - Epoch(train) [686][30/63] lr: 1.6496e-03 eta: 6:42:02 time: 0.5264 data_time: 0.0378 memory: 16131 loss: 1.3121 loss_prob: 0.7363 loss_thr: 0.4520 loss_db: 0.1239 2022/10/26 04:26:59 - mmengine - INFO - Epoch(train) [686][35/63] lr: 1.6496e-03 eta: 6:42:02 time: 0.5115 data_time: 0.0166 memory: 16131 loss: 1.3181 loss_prob: 0.7427 loss_thr: 0.4500 loss_db: 0.1253 2022/10/26 04:27:02 - mmengine - INFO - Epoch(train) [686][40/63] lr: 1.6496e-03 eta: 6:41:53 time: 0.5269 data_time: 0.0048 memory: 16131 loss: 1.4521 loss_prob: 0.8191 loss_thr: 0.4945 loss_db: 0.1385 2022/10/26 04:27:04 - mmengine - INFO - Epoch(train) [686][45/63] lr: 1.6496e-03 eta: 6:41:53 time: 0.5256 data_time: 0.0066 memory: 16131 loss: 1.3482 loss_prob: 0.7351 loss_thr: 0.4850 loss_db: 0.1281 2022/10/26 04:27:07 - mmengine - INFO - Epoch(train) [686][50/63] lr: 1.6496e-03 eta: 6:41:44 time: 0.5368 data_time: 0.0257 memory: 16131 loss: 1.2460 loss_prob: 0.6753 loss_thr: 0.4548 loss_db: 0.1158 2022/10/26 04:27:10 - mmengine - INFO - Epoch(train) [686][55/63] lr: 1.6496e-03 eta: 6:41:44 time: 0.5933 data_time: 0.0241 memory: 16131 loss: 1.2802 loss_prob: 0.6976 loss_thr: 0.4656 loss_db: 0.1170 2022/10/26 04:27:13 - mmengine - INFO - Epoch(train) [686][60/63] lr: 1.6496e-03 eta: 6:41:35 time: 0.5904 data_time: 0.0049 memory: 16131 loss: 1.2993 loss_prob: 0.7095 loss_thr: 0.4683 loss_db: 0.1216 2022/10/26 04:27:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:27:18 - mmengine - INFO - Epoch(train) [687][5/63] lr: 1.6468e-03 eta: 6:41:35 time: 0.6719 data_time: 0.1803 memory: 16131 loss: 1.2904 loss_prob: 0.7098 loss_thr: 0.4598 loss_db: 0.1209 2022/10/26 04:27:21 - mmengine - INFO - Epoch(train) [687][10/63] lr: 1.6468e-03 eta: 6:41:24 time: 0.7119 data_time: 0.1804 memory: 16131 loss: 1.3017 loss_prob: 0.7246 loss_thr: 0.4594 loss_db: 0.1178 2022/10/26 04:27:24 - mmengine - INFO - Epoch(train) [687][15/63] lr: 1.6468e-03 eta: 6:41:24 time: 0.5278 data_time: 0.0069 memory: 16131 loss: 1.3887 loss_prob: 0.7744 loss_thr: 0.4831 loss_db: 0.1312 2022/10/26 04:27:26 - mmengine - INFO - Epoch(train) [687][20/63] lr: 1.6468e-03 eta: 6:41:15 time: 0.5273 data_time: 0.0071 memory: 16131 loss: 1.3467 loss_prob: 0.7519 loss_thr: 0.4644 loss_db: 0.1305 2022/10/26 04:27:29 - mmengine - INFO - Epoch(train) [687][25/63] lr: 1.6468e-03 eta: 6:41:15 time: 0.5276 data_time: 0.0171 memory: 16131 loss: 1.2336 loss_prob: 0.6774 loss_thr: 0.4421 loss_db: 0.1140 2022/10/26 04:27:32 - mmengine - INFO - Epoch(train) [687][30/63] lr: 1.6468e-03 eta: 6:41:06 time: 0.5230 data_time: 0.0380 memory: 16131 loss: 1.3191 loss_prob: 0.7235 loss_thr: 0.4723 loss_db: 0.1233 2022/10/26 04:27:34 - mmengine - INFO - Epoch(train) [687][35/63] lr: 1.6468e-03 eta: 6:41:06 time: 0.5158 data_time: 0.0270 memory: 16131 loss: 1.2805 loss_prob: 0.7013 loss_thr: 0.4601 loss_db: 0.1191 2022/10/26 04:27:37 - mmengine - INFO - Epoch(train) [687][40/63] lr: 1.6468e-03 eta: 6:40:57 time: 0.5170 data_time: 0.0070 memory: 16131 loss: 1.2408 loss_prob: 0.6765 loss_thr: 0.4529 loss_db: 0.1114 2022/10/26 04:27:39 - mmengine - INFO - Epoch(train) [687][45/63] lr: 1.6468e-03 eta: 6:40:57 time: 0.5063 data_time: 0.0075 memory: 16131 loss: 1.3536 loss_prob: 0.7635 loss_thr: 0.4679 loss_db: 0.1221 2022/10/26 04:27:42 - mmengine - INFO - Epoch(train) [687][50/63] lr: 1.6468e-03 eta: 6:40:47 time: 0.5243 data_time: 0.0223 memory: 16131 loss: 1.2339 loss_prob: 0.6726 loss_thr: 0.4499 loss_db: 0.1115 2022/10/26 04:27:45 - mmengine - INFO - Epoch(train) [687][55/63] lr: 1.6468e-03 eta: 6:40:47 time: 0.5473 data_time: 0.0247 memory: 16131 loss: 1.1906 loss_prob: 0.6226 loss_thr: 0.4598 loss_db: 0.1082 2022/10/26 04:27:47 - mmengine - INFO - Epoch(train) [687][60/63] lr: 1.6468e-03 eta: 6:40:38 time: 0.5235 data_time: 0.0095 memory: 16131 loss: 1.3470 loss_prob: 0.7403 loss_thr: 0.4841 loss_db: 0.1227 2022/10/26 04:27:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:27:54 - mmengine - INFO - Epoch(train) [688][5/63] lr: 1.6439e-03 eta: 6:40:38 time: 0.7677 data_time: 0.1906 memory: 16131 loss: 1.4129 loss_prob: 0.7745 loss_thr: 0.5103 loss_db: 0.1281 2022/10/26 04:27:57 - mmengine - INFO - Epoch(train) [688][10/63] lr: 1.6439e-03 eta: 6:40:27 time: 0.7907 data_time: 0.1904 memory: 16131 loss: 1.3611 loss_prob: 0.7430 loss_thr: 0.4908 loss_db: 0.1274 2022/10/26 04:27:59 - mmengine - INFO - Epoch(train) [688][15/63] lr: 1.6439e-03 eta: 6:40:27 time: 0.5126 data_time: 0.0084 memory: 16131 loss: 1.2954 loss_prob: 0.6994 loss_thr: 0.4742 loss_db: 0.1218 2022/10/26 04:28:02 - mmengine - INFO - Epoch(train) [688][20/63] lr: 1.6439e-03 eta: 6:40:19 time: 0.5606 data_time: 0.0085 memory: 16131 loss: 1.2497 loss_prob: 0.6847 loss_thr: 0.4502 loss_db: 0.1147 2022/10/26 04:28:05 - mmengine - INFO - Epoch(train) [688][25/63] lr: 1.6439e-03 eta: 6:40:19 time: 0.5738 data_time: 0.0232 memory: 16131 loss: 1.2415 loss_prob: 0.6824 loss_thr: 0.4450 loss_db: 0.1141 2022/10/26 04:28:08 - mmengine - INFO - Epoch(train) [688][30/63] lr: 1.6439e-03 eta: 6:40:10 time: 0.5844 data_time: 0.0328 memory: 16131 loss: 1.2455 loss_prob: 0.6867 loss_thr: 0.4422 loss_db: 0.1166 2022/10/26 04:28:10 - mmengine - INFO - Epoch(train) [688][35/63] lr: 1.6439e-03 eta: 6:40:10 time: 0.5569 data_time: 0.0191 memory: 16131 loss: 1.2023 loss_prob: 0.6476 loss_thr: 0.4440 loss_db: 0.1107 2022/10/26 04:28:13 - mmengine - INFO - Epoch(train) [688][40/63] lr: 1.6439e-03 eta: 6:40:01 time: 0.5002 data_time: 0.0083 memory: 16131 loss: 1.2485 loss_prob: 0.6620 loss_thr: 0.4717 loss_db: 0.1147 2022/10/26 04:28:16 - mmengine - INFO - Epoch(train) [688][45/63] lr: 1.6439e-03 eta: 6:40:01 time: 0.5224 data_time: 0.0089 memory: 16131 loss: 1.2521 loss_prob: 0.6766 loss_thr: 0.4580 loss_db: 0.1174 2022/10/26 04:28:18 - mmengine - INFO - Epoch(train) [688][50/63] lr: 1.6439e-03 eta: 6:39:52 time: 0.5270 data_time: 0.0280 memory: 16131 loss: 1.2514 loss_prob: 0.6731 loss_thr: 0.4645 loss_db: 0.1137 2022/10/26 04:28:21 - mmengine - INFO - Epoch(train) [688][55/63] lr: 1.6439e-03 eta: 6:39:52 time: 0.5005 data_time: 0.0238 memory: 16131 loss: 1.2580 loss_prob: 0.6838 loss_thr: 0.4583 loss_db: 0.1160 2022/10/26 04:28:24 - mmengine - INFO - Epoch(train) [688][60/63] lr: 1.6439e-03 eta: 6:39:43 time: 0.5474 data_time: 0.0057 memory: 16131 loss: 1.2670 loss_prob: 0.7027 loss_thr: 0.4448 loss_db: 0.1195 2022/10/26 04:28:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:28:30 - mmengine - INFO - Epoch(train) [689][5/63] lr: 1.6410e-03 eta: 6:39:43 time: 0.7594 data_time: 0.1737 memory: 16131 loss: 1.2627 loss_prob: 0.6961 loss_thr: 0.4504 loss_db: 0.1162 2022/10/26 04:28:33 - mmengine - INFO - Epoch(train) [689][10/63] lr: 1.6410e-03 eta: 6:39:31 time: 0.7338 data_time: 0.1711 memory: 16131 loss: 1.2792 loss_prob: 0.7028 loss_thr: 0.4584 loss_db: 0.1180 2022/10/26 04:28:35 - mmengine - INFO - Epoch(train) [689][15/63] lr: 1.6410e-03 eta: 6:39:31 time: 0.5077 data_time: 0.0114 memory: 16131 loss: 1.2565 loss_prob: 0.6846 loss_thr: 0.4564 loss_db: 0.1155 2022/10/26 04:28:38 - mmengine - INFO - Epoch(train) [689][20/63] lr: 1.6410e-03 eta: 6:39:22 time: 0.5012 data_time: 0.0115 memory: 16131 loss: 1.2263 loss_prob: 0.6598 loss_thr: 0.4527 loss_db: 0.1139 2022/10/26 04:28:40 - mmengine - INFO - Epoch(train) [689][25/63] lr: 1.6410e-03 eta: 6:39:22 time: 0.5334 data_time: 0.0177 memory: 16131 loss: 1.2825 loss_prob: 0.6959 loss_thr: 0.4667 loss_db: 0.1199 2022/10/26 04:28:43 - mmengine - INFO - Epoch(train) [689][30/63] lr: 1.6410e-03 eta: 6:39:13 time: 0.5274 data_time: 0.0264 memory: 16131 loss: 1.3559 loss_prob: 0.7485 loss_thr: 0.4838 loss_db: 0.1235 2022/10/26 04:28:45 - mmengine - INFO - Epoch(train) [689][35/63] lr: 1.6410e-03 eta: 6:39:13 time: 0.4970 data_time: 0.0159 memory: 16131 loss: 1.2889 loss_prob: 0.7035 loss_thr: 0.4676 loss_db: 0.1178 2022/10/26 04:28:48 - mmengine - INFO - Epoch(train) [689][40/63] lr: 1.6410e-03 eta: 6:39:04 time: 0.4930 data_time: 0.0103 memory: 16131 loss: 1.1872 loss_prob: 0.6406 loss_thr: 0.4357 loss_db: 0.1109 2022/10/26 04:28:50 - mmengine - INFO - Epoch(train) [689][45/63] lr: 1.6410e-03 eta: 6:39:04 time: 0.5179 data_time: 0.0104 memory: 16131 loss: 1.0954 loss_prob: 0.5830 loss_thr: 0.4127 loss_db: 0.0998 2022/10/26 04:28:53 - mmengine - INFO - Epoch(train) [689][50/63] lr: 1.6410e-03 eta: 6:38:55 time: 0.5269 data_time: 0.0190 memory: 16131 loss: 1.1035 loss_prob: 0.5880 loss_thr: 0.4138 loss_db: 0.1017 2022/10/26 04:28:55 - mmengine - INFO - Epoch(train) [689][55/63] lr: 1.6410e-03 eta: 6:38:55 time: 0.4972 data_time: 0.0210 memory: 16131 loss: 1.2446 loss_prob: 0.6823 loss_thr: 0.4447 loss_db: 0.1176 2022/10/26 04:28:58 - mmengine - INFO - Epoch(train) [689][60/63] lr: 1.6410e-03 eta: 6:38:46 time: 0.5035 data_time: 0.0098 memory: 16131 loss: 1.3041 loss_prob: 0.7141 loss_thr: 0.4687 loss_db: 0.1213 2022/10/26 04:29:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:29:04 - mmengine - INFO - Epoch(train) [690][5/63] lr: 1.6381e-03 eta: 6:38:46 time: 0.7300 data_time: 0.2170 memory: 16131 loss: 1.3262 loss_prob: 0.7243 loss_thr: 0.4777 loss_db: 0.1243 2022/10/26 04:29:07 - mmengine - INFO - Epoch(train) [690][10/63] lr: 1.6381e-03 eta: 6:38:34 time: 0.7473 data_time: 0.2162 memory: 16131 loss: 1.2870 loss_prob: 0.6989 loss_thr: 0.4696 loss_db: 0.1185 2022/10/26 04:29:10 - mmengine - INFO - Epoch(train) [690][15/63] lr: 1.6381e-03 eta: 6:38:34 time: 0.5381 data_time: 0.0098 memory: 16131 loss: 1.2956 loss_prob: 0.6914 loss_thr: 0.4855 loss_db: 0.1187 2022/10/26 04:29:12 - mmengine - INFO - Epoch(train) [690][20/63] lr: 1.6381e-03 eta: 6:38:25 time: 0.5096 data_time: 0.0141 memory: 16131 loss: 1.2535 loss_prob: 0.6757 loss_thr: 0.4613 loss_db: 0.1165 2022/10/26 04:29:15 - mmengine - INFO - Epoch(train) [690][25/63] lr: 1.6381e-03 eta: 6:38:25 time: 0.4927 data_time: 0.0167 memory: 16131 loss: 1.2069 loss_prob: 0.6529 loss_thr: 0.4403 loss_db: 0.1137 2022/10/26 04:29:17 - mmengine - INFO - Epoch(train) [690][30/63] lr: 1.6381e-03 eta: 6:38:16 time: 0.5066 data_time: 0.0267 memory: 16131 loss: 1.2027 loss_prob: 0.6539 loss_thr: 0.4372 loss_db: 0.1117 2022/10/26 04:29:20 - mmengine - INFO - Epoch(train) [690][35/63] lr: 1.6381e-03 eta: 6:38:16 time: 0.5218 data_time: 0.0309 memory: 16131 loss: 1.1219 loss_prob: 0.5980 loss_thr: 0.4238 loss_db: 0.1002 2022/10/26 04:29:22 - mmengine - INFO - Epoch(train) [690][40/63] lr: 1.6381e-03 eta: 6:38:07 time: 0.5155 data_time: 0.0152 memory: 16131 loss: 1.1053 loss_prob: 0.5767 loss_thr: 0.4290 loss_db: 0.0996 2022/10/26 04:29:25 - mmengine - INFO - Epoch(train) [690][45/63] lr: 1.6381e-03 eta: 6:38:07 time: 0.5539 data_time: 0.0056 memory: 16131 loss: 1.1462 loss_prob: 0.6051 loss_thr: 0.4393 loss_db: 0.1018 2022/10/26 04:29:28 - mmengine - INFO - Epoch(train) [690][50/63] lr: 1.6381e-03 eta: 6:37:58 time: 0.5701 data_time: 0.0161 memory: 16131 loss: 1.1348 loss_prob: 0.5932 loss_thr: 0.4447 loss_db: 0.0969 2022/10/26 04:29:31 - mmengine - INFO - Epoch(train) [690][55/63] lr: 1.6381e-03 eta: 6:37:58 time: 0.5176 data_time: 0.0172 memory: 16131 loss: 1.1957 loss_prob: 0.6321 loss_thr: 0.4570 loss_db: 0.1067 2022/10/26 04:29:33 - mmengine - INFO - Epoch(train) [690][60/63] lr: 1.6381e-03 eta: 6:37:49 time: 0.4951 data_time: 0.0121 memory: 16131 loss: 1.3077 loss_prob: 0.7145 loss_thr: 0.4726 loss_db: 0.1205 2022/10/26 04:29:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:29:40 - mmengine - INFO - Epoch(train) [691][5/63] lr: 1.6352e-03 eta: 6:37:49 time: 0.8042 data_time: 0.1684 memory: 16131 loss: 1.2482 loss_prob: 0.6689 loss_thr: 0.4666 loss_db: 0.1127 2022/10/26 04:29:43 - mmengine - INFO - Epoch(train) [691][10/63] lr: 1.6352e-03 eta: 6:37:38 time: 0.8499 data_time: 0.1699 memory: 16131 loss: 1.1819 loss_prob: 0.6249 loss_thr: 0.4518 loss_db: 0.1052 2022/10/26 04:29:45 - mmengine - INFO - Epoch(train) [691][15/63] lr: 1.6352e-03 eta: 6:37:38 time: 0.5284 data_time: 0.0142 memory: 16131 loss: 1.2110 loss_prob: 0.6655 loss_thr: 0.4345 loss_db: 0.1109 2022/10/26 04:29:48 - mmengine - INFO - Epoch(train) [691][20/63] lr: 1.6352e-03 eta: 6:37:29 time: 0.4953 data_time: 0.0130 memory: 16131 loss: 1.2381 loss_prob: 0.6868 loss_thr: 0.4370 loss_db: 0.1143 2022/10/26 04:29:51 - mmengine - INFO - Epoch(train) [691][25/63] lr: 1.6352e-03 eta: 6:37:29 time: 0.5239 data_time: 0.0115 memory: 16131 loss: 1.2135 loss_prob: 0.6534 loss_thr: 0.4494 loss_db: 0.1107 2022/10/26 04:29:53 - mmengine - INFO - Epoch(train) [691][30/63] lr: 1.6352e-03 eta: 6:37:20 time: 0.5624 data_time: 0.0255 memory: 16131 loss: 1.2983 loss_prob: 0.7060 loss_thr: 0.4718 loss_db: 0.1206 2022/10/26 04:29:56 - mmengine - INFO - Epoch(train) [691][35/63] lr: 1.6352e-03 eta: 6:37:20 time: 0.5342 data_time: 0.0211 memory: 16131 loss: 1.3560 loss_prob: 0.7445 loss_thr: 0.4809 loss_db: 0.1306 2022/10/26 04:29:58 - mmengine - INFO - Epoch(train) [691][40/63] lr: 1.6352e-03 eta: 6:37:11 time: 0.5027 data_time: 0.0134 memory: 16131 loss: 1.2320 loss_prob: 0.6609 loss_thr: 0.4540 loss_db: 0.1170 2022/10/26 04:30:01 - mmengine - INFO - Epoch(train) [691][45/63] lr: 1.6352e-03 eta: 6:37:11 time: 0.5006 data_time: 0.0133 memory: 16131 loss: 1.2255 loss_prob: 0.6534 loss_thr: 0.4588 loss_db: 0.1133 2022/10/26 04:30:04 - mmengine - INFO - Epoch(train) [691][50/63] lr: 1.6352e-03 eta: 6:37:02 time: 0.5227 data_time: 0.0193 memory: 16131 loss: 1.3209 loss_prob: 0.7163 loss_thr: 0.4844 loss_db: 0.1203 2022/10/26 04:30:07 - mmengine - INFO - Epoch(train) [691][55/63] lr: 1.6352e-03 eta: 6:37:02 time: 0.5554 data_time: 0.0228 memory: 16131 loss: 1.3115 loss_prob: 0.7279 loss_thr: 0.4629 loss_db: 0.1207 2022/10/26 04:30:09 - mmengine - INFO - Epoch(train) [691][60/63] lr: 1.6352e-03 eta: 6:36:53 time: 0.5434 data_time: 0.0107 memory: 16131 loss: 1.2607 loss_prob: 0.6966 loss_thr: 0.4453 loss_db: 0.1188 2022/10/26 04:30:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:30:15 - mmengine - INFO - Epoch(train) [692][5/63] lr: 1.6323e-03 eta: 6:36:53 time: 0.6806 data_time: 0.1855 memory: 16131 loss: 1.2418 loss_prob: 0.6739 loss_thr: 0.4524 loss_db: 0.1154 2022/10/26 04:30:18 - mmengine - INFO - Epoch(train) [692][10/63] lr: 1.6323e-03 eta: 6:36:42 time: 0.7648 data_time: 0.1821 memory: 16131 loss: 1.1898 loss_prob: 0.6356 loss_thr: 0.4473 loss_db: 0.1069 2022/10/26 04:30:21 - mmengine - INFO - Epoch(train) [692][15/63] lr: 1.6323e-03 eta: 6:36:42 time: 0.5736 data_time: 0.0053 memory: 16131 loss: 1.1930 loss_prob: 0.6430 loss_thr: 0.4357 loss_db: 0.1143 2022/10/26 04:30:23 - mmengine - INFO - Epoch(train) [692][20/63] lr: 1.6323e-03 eta: 6:36:33 time: 0.5181 data_time: 0.0062 memory: 16131 loss: 1.2948 loss_prob: 0.7227 loss_thr: 0.4515 loss_db: 0.1207 2022/10/26 04:30:26 - mmengine - INFO - Epoch(train) [692][25/63] lr: 1.6323e-03 eta: 6:36:33 time: 0.5211 data_time: 0.0198 memory: 16131 loss: 1.3804 loss_prob: 0.7825 loss_thr: 0.4736 loss_db: 0.1243 2022/10/26 04:30:29 - mmengine - INFO - Epoch(train) [692][30/63] lr: 1.6323e-03 eta: 6:36:24 time: 0.5343 data_time: 0.0366 memory: 16131 loss: 1.3306 loss_prob: 0.7384 loss_thr: 0.4669 loss_db: 0.1253 2022/10/26 04:30:31 - mmengine - INFO - Epoch(train) [692][35/63] lr: 1.6323e-03 eta: 6:36:24 time: 0.5264 data_time: 0.0224 memory: 16131 loss: 1.2586 loss_prob: 0.6786 loss_thr: 0.4612 loss_db: 0.1188 2022/10/26 04:30:34 - mmengine - INFO - Epoch(train) [692][40/63] lr: 1.6323e-03 eta: 6:36:15 time: 0.5079 data_time: 0.0045 memory: 16131 loss: 1.1995 loss_prob: 0.6421 loss_thr: 0.4481 loss_db: 0.1093 2022/10/26 04:30:36 - mmengine - INFO - Epoch(train) [692][45/63] lr: 1.6323e-03 eta: 6:36:15 time: 0.5025 data_time: 0.0062 memory: 16131 loss: 1.2300 loss_prob: 0.6718 loss_thr: 0.4482 loss_db: 0.1100 2022/10/26 04:30:39 - mmengine - INFO - Epoch(train) [692][50/63] lr: 1.6323e-03 eta: 6:36:06 time: 0.5339 data_time: 0.0178 memory: 16131 loss: 1.3212 loss_prob: 0.7304 loss_thr: 0.4701 loss_db: 0.1208 2022/10/26 04:30:42 - mmengine - INFO - Epoch(train) [692][55/63] lr: 1.6323e-03 eta: 6:36:06 time: 0.5628 data_time: 0.0237 memory: 16131 loss: 1.2974 loss_prob: 0.7101 loss_thr: 0.4660 loss_db: 0.1214 2022/10/26 04:30:44 - mmengine - INFO - Epoch(train) [692][60/63] lr: 1.6323e-03 eta: 6:35:57 time: 0.5349 data_time: 0.0121 memory: 16131 loss: 1.2817 loss_prob: 0.6902 loss_thr: 0.4747 loss_db: 0.1167 2022/10/26 04:30:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:30:51 - mmengine - INFO - Epoch(train) [693][5/63] lr: 1.6294e-03 eta: 6:35:57 time: 0.7355 data_time: 0.2173 memory: 16131 loss: 1.4167 loss_prob: 0.7631 loss_thr: 0.5271 loss_db: 0.1265 2022/10/26 04:30:53 - mmengine - INFO - Epoch(train) [693][10/63] lr: 1.6294e-03 eta: 6:35:46 time: 0.7708 data_time: 0.2163 memory: 16131 loss: 1.3269 loss_prob: 0.7259 loss_thr: 0.4820 loss_db: 0.1190 2022/10/26 04:30:56 - mmengine - INFO - Epoch(train) [693][15/63] lr: 1.6294e-03 eta: 6:35:46 time: 0.5614 data_time: 0.0095 memory: 16131 loss: 1.1976 loss_prob: 0.6382 loss_thr: 0.4536 loss_db: 0.1058 2022/10/26 04:30:59 - mmengine - INFO - Epoch(train) [693][20/63] lr: 1.6294e-03 eta: 6:35:37 time: 0.5469 data_time: 0.0085 memory: 16131 loss: 1.1144 loss_prob: 0.5848 loss_thr: 0.4297 loss_db: 0.0999 2022/10/26 04:31:01 - mmengine - INFO - Epoch(train) [693][25/63] lr: 1.6294e-03 eta: 6:35:37 time: 0.5194 data_time: 0.0169 memory: 16131 loss: 1.1493 loss_prob: 0.6222 loss_thr: 0.4213 loss_db: 0.1057 2022/10/26 04:31:04 - mmengine - INFO - Epoch(train) [693][30/63] lr: 1.6294e-03 eta: 6:35:28 time: 0.5490 data_time: 0.0321 memory: 16131 loss: 1.2282 loss_prob: 0.6778 loss_thr: 0.4374 loss_db: 0.1129 2022/10/26 04:31:07 - mmengine - INFO - Epoch(train) [693][35/63] lr: 1.6294e-03 eta: 6:35:28 time: 0.5353 data_time: 0.0224 memory: 16131 loss: 1.2625 loss_prob: 0.6912 loss_thr: 0.4548 loss_db: 0.1166 2022/10/26 04:31:09 - mmengine - INFO - Epoch(train) [693][40/63] lr: 1.6294e-03 eta: 6:35:19 time: 0.5099 data_time: 0.0090 memory: 16131 loss: 1.3554 loss_prob: 0.7707 loss_thr: 0.4621 loss_db: 0.1226 2022/10/26 04:31:12 - mmengine - INFO - Epoch(train) [693][45/63] lr: 1.6294e-03 eta: 6:35:19 time: 0.5114 data_time: 0.0080 memory: 16131 loss: 1.4335 loss_prob: 0.8162 loss_thr: 0.4861 loss_db: 0.1312 2022/10/26 04:31:15 - mmengine - INFO - Epoch(train) [693][50/63] lr: 1.6294e-03 eta: 6:35:10 time: 0.5084 data_time: 0.0131 memory: 16131 loss: 1.2866 loss_prob: 0.7021 loss_thr: 0.4640 loss_db: 0.1205 2022/10/26 04:31:17 - mmengine - INFO - Epoch(train) [693][55/63] lr: 1.6294e-03 eta: 6:35:10 time: 0.5150 data_time: 0.0226 memory: 16131 loss: 1.1880 loss_prob: 0.6428 loss_thr: 0.4346 loss_db: 0.1107 2022/10/26 04:31:20 - mmengine - INFO - Epoch(train) [693][60/63] lr: 1.6294e-03 eta: 6:35:01 time: 0.5204 data_time: 0.0163 memory: 16131 loss: 1.2025 loss_prob: 0.6601 loss_thr: 0.4315 loss_db: 0.1108 2022/10/26 04:31:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:31:26 - mmengine - INFO - Epoch(train) [694][5/63] lr: 1.6265e-03 eta: 6:35:01 time: 0.7276 data_time: 0.1864 memory: 16131 loss: 1.3810 loss_prob: 0.7962 loss_thr: 0.4547 loss_db: 0.1300 2022/10/26 04:31:28 - mmengine - INFO - Epoch(train) [694][10/63] lr: 1.6265e-03 eta: 6:34:50 time: 0.7228 data_time: 0.1883 memory: 16131 loss: 1.4924 loss_prob: 0.8813 loss_thr: 0.4749 loss_db: 0.1362 2022/10/26 04:31:31 - mmengine - INFO - Epoch(train) [694][15/63] lr: 1.6265e-03 eta: 6:34:50 time: 0.4747 data_time: 0.0089 memory: 16131 loss: 1.3015 loss_prob: 0.7284 loss_thr: 0.4544 loss_db: 0.1187 2022/10/26 04:31:33 - mmengine - INFO - Epoch(train) [694][20/63] lr: 1.6265e-03 eta: 6:34:40 time: 0.4890 data_time: 0.0073 memory: 16131 loss: 1.1537 loss_prob: 0.6174 loss_thr: 0.4310 loss_db: 0.1053 2022/10/26 04:31:36 - mmengine - INFO - Epoch(train) [694][25/63] lr: 1.6265e-03 eta: 6:34:40 time: 0.5214 data_time: 0.0280 memory: 16131 loss: 1.1053 loss_prob: 0.5807 loss_thr: 0.4252 loss_db: 0.0993 2022/10/26 04:31:38 - mmengine - INFO - Epoch(train) [694][30/63] lr: 1.6265e-03 eta: 6:34:31 time: 0.5134 data_time: 0.0362 memory: 16131 loss: 1.1727 loss_prob: 0.6240 loss_thr: 0.4442 loss_db: 0.1044 2022/10/26 04:31:41 - mmengine - INFO - Epoch(train) [694][35/63] lr: 1.6265e-03 eta: 6:34:31 time: 0.4957 data_time: 0.0162 memory: 16131 loss: 1.3663 loss_prob: 0.7692 loss_thr: 0.4689 loss_db: 0.1282 2022/10/26 04:31:43 - mmengine - INFO - Epoch(train) [694][40/63] lr: 1.6265e-03 eta: 6:34:22 time: 0.4937 data_time: 0.0069 memory: 16131 loss: 1.3502 loss_prob: 0.7667 loss_thr: 0.4565 loss_db: 0.1270 2022/10/26 04:31:46 - mmengine - INFO - Epoch(train) [694][45/63] lr: 1.6265e-03 eta: 6:34:22 time: 0.5184 data_time: 0.0046 memory: 16131 loss: 1.2387 loss_prob: 0.6777 loss_thr: 0.4498 loss_db: 0.1112 2022/10/26 04:31:49 - mmengine - INFO - Epoch(train) [694][50/63] lr: 1.6265e-03 eta: 6:34:13 time: 0.5615 data_time: 0.0225 memory: 16131 loss: 1.3310 loss_prob: 0.7346 loss_thr: 0.4726 loss_db: 0.1237 2022/10/26 04:31:52 - mmengine - INFO - Epoch(train) [694][55/63] lr: 1.6265e-03 eta: 6:34:13 time: 0.5874 data_time: 0.0253 memory: 16131 loss: 1.2912 loss_prob: 0.7087 loss_thr: 0.4615 loss_db: 0.1210 2022/10/26 04:31:54 - mmengine - INFO - Epoch(train) [694][60/63] lr: 1.6265e-03 eta: 6:34:04 time: 0.5501 data_time: 0.0113 memory: 16131 loss: 1.2202 loss_prob: 0.6585 loss_thr: 0.4476 loss_db: 0.1141 2022/10/26 04:31:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:32:00 - mmengine - INFO - Epoch(train) [695][5/63] lr: 1.6236e-03 eta: 6:34:04 time: 0.6860 data_time: 0.1814 memory: 16131 loss: 1.2375 loss_prob: 0.6646 loss_thr: 0.4593 loss_db: 0.1136 2022/10/26 04:32:03 - mmengine - INFO - Epoch(train) [695][10/63] lr: 1.6236e-03 eta: 6:33:53 time: 0.7197 data_time: 0.1808 memory: 16131 loss: 1.2480 loss_prob: 0.6613 loss_thr: 0.4736 loss_db: 0.1130 2022/10/26 04:32:06 - mmengine - INFO - Epoch(train) [695][15/63] lr: 1.6236e-03 eta: 6:33:53 time: 0.5280 data_time: 0.0098 memory: 16131 loss: 1.3355 loss_prob: 0.7281 loss_thr: 0.4833 loss_db: 0.1241 2022/10/26 04:32:08 - mmengine - INFO - Epoch(train) [695][20/63] lr: 1.6236e-03 eta: 6:33:44 time: 0.5098 data_time: 0.0084 memory: 16131 loss: 1.2720 loss_prob: 0.6937 loss_thr: 0.4601 loss_db: 0.1182 2022/10/26 04:32:11 - mmengine - INFO - Epoch(train) [695][25/63] lr: 1.6236e-03 eta: 6:33:44 time: 0.5159 data_time: 0.0274 memory: 16131 loss: 1.2467 loss_prob: 0.6649 loss_thr: 0.4666 loss_db: 0.1152 2022/10/26 04:32:14 - mmengine - INFO - Epoch(train) [695][30/63] lr: 1.6236e-03 eta: 6:33:35 time: 0.5633 data_time: 0.0373 memory: 16131 loss: 1.2893 loss_prob: 0.7003 loss_thr: 0.4693 loss_db: 0.1197 2022/10/26 04:32:16 - mmengine - INFO - Epoch(train) [695][35/63] lr: 1.6236e-03 eta: 6:33:35 time: 0.5505 data_time: 0.0162 memory: 16131 loss: 1.2671 loss_prob: 0.6988 loss_thr: 0.4505 loss_db: 0.1178 2022/10/26 04:32:19 - mmengine - INFO - Epoch(train) [695][40/63] lr: 1.6236e-03 eta: 6:33:26 time: 0.5200 data_time: 0.0068 memory: 16131 loss: 1.3220 loss_prob: 0.7329 loss_thr: 0.4676 loss_db: 0.1216 2022/10/26 04:32:21 - mmengine - INFO - Epoch(train) [695][45/63] lr: 1.6236e-03 eta: 6:33:26 time: 0.5146 data_time: 0.0102 memory: 16131 loss: 1.2757 loss_prob: 0.7028 loss_thr: 0.4567 loss_db: 0.1162 2022/10/26 04:32:25 - mmengine - INFO - Epoch(train) [695][50/63] lr: 1.6236e-03 eta: 6:33:17 time: 0.5726 data_time: 0.0252 memory: 16131 loss: 1.2070 loss_prob: 0.6581 loss_thr: 0.4376 loss_db: 0.1114 2022/10/26 04:32:27 - mmengine - INFO - Epoch(train) [695][55/63] lr: 1.6236e-03 eta: 6:33:17 time: 0.6013 data_time: 0.0318 memory: 16131 loss: 1.3470 loss_prob: 0.7674 loss_thr: 0.4609 loss_db: 0.1186 2022/10/26 04:32:30 - mmengine - INFO - Epoch(train) [695][60/63] lr: 1.6236e-03 eta: 6:33:09 time: 0.5286 data_time: 0.0164 memory: 16131 loss: 1.3239 loss_prob: 0.7513 loss_thr: 0.4569 loss_db: 0.1158 2022/10/26 04:32:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:32:35 - mmengine - INFO - Epoch(train) [696][5/63] lr: 1.6207e-03 eta: 6:33:09 time: 0.6481 data_time: 0.1740 memory: 16131 loss: 1.1884 loss_prob: 0.6336 loss_thr: 0.4473 loss_db: 0.1075 2022/10/26 04:32:38 - mmengine - INFO - Epoch(train) [696][10/63] lr: 1.6207e-03 eta: 6:32:57 time: 0.6965 data_time: 0.1855 memory: 16131 loss: 1.1688 loss_prob: 0.6149 loss_thr: 0.4490 loss_db: 0.1049 2022/10/26 04:32:41 - mmengine - INFO - Epoch(train) [696][15/63] lr: 1.6207e-03 eta: 6:32:57 time: 0.5264 data_time: 0.0166 memory: 16131 loss: 1.2024 loss_prob: 0.6371 loss_thr: 0.4560 loss_db: 0.1094 2022/10/26 04:32:43 - mmengine - INFO - Epoch(train) [696][20/63] lr: 1.6207e-03 eta: 6:32:48 time: 0.4949 data_time: 0.0056 memory: 16131 loss: 1.1817 loss_prob: 0.6200 loss_thr: 0.4554 loss_db: 0.1063 2022/10/26 04:32:46 - mmengine - INFO - Epoch(train) [696][25/63] lr: 1.6207e-03 eta: 6:32:48 time: 0.5306 data_time: 0.0155 memory: 16131 loss: 1.2605 loss_prob: 0.6852 loss_thr: 0.4575 loss_db: 0.1178 2022/10/26 04:32:49 - mmengine - INFO - Epoch(train) [696][30/63] lr: 1.6207e-03 eta: 6:32:39 time: 0.5787 data_time: 0.0291 memory: 16131 loss: 1.2452 loss_prob: 0.6875 loss_thr: 0.4402 loss_db: 0.1174 2022/10/26 04:32:52 - mmengine - INFO - Epoch(train) [696][35/63] lr: 1.6207e-03 eta: 6:32:39 time: 0.5641 data_time: 0.0267 memory: 16131 loss: 1.2870 loss_prob: 0.6911 loss_thr: 0.4788 loss_db: 0.1171 2022/10/26 04:32:54 - mmengine - INFO - Epoch(train) [696][40/63] lr: 1.6207e-03 eta: 6:32:30 time: 0.5226 data_time: 0.0128 memory: 16131 loss: 1.2667 loss_prob: 0.6853 loss_thr: 0.4623 loss_db: 0.1190 2022/10/26 04:32:57 - mmengine - INFO - Epoch(train) [696][45/63] lr: 1.6207e-03 eta: 6:32:30 time: 0.5200 data_time: 0.0063 memory: 16131 loss: 1.2770 loss_prob: 0.7081 loss_thr: 0.4497 loss_db: 0.1192 2022/10/26 04:32:59 - mmengine - INFO - Epoch(train) [696][50/63] lr: 1.6207e-03 eta: 6:32:21 time: 0.5279 data_time: 0.0112 memory: 16131 loss: 1.3280 loss_prob: 0.7280 loss_thr: 0.4820 loss_db: 0.1181 2022/10/26 04:33:03 - mmengine - INFO - Epoch(train) [696][55/63] lr: 1.6207e-03 eta: 6:32:21 time: 0.5682 data_time: 0.0258 memory: 16131 loss: 1.1817 loss_prob: 0.6327 loss_thr: 0.4417 loss_db: 0.1073 2022/10/26 04:33:06 - mmengine - INFO - Epoch(train) [696][60/63] lr: 1.6207e-03 eta: 6:32:13 time: 0.6152 data_time: 0.0223 memory: 16131 loss: 1.1448 loss_prob: 0.6125 loss_thr: 0.4249 loss_db: 0.1073 2022/10/26 04:33:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:33:11 - mmengine - INFO - Epoch(train) [697][5/63] lr: 1.6178e-03 eta: 6:32:13 time: 0.6980 data_time: 0.1551 memory: 16131 loss: 1.3574 loss_prob: 0.7794 loss_thr: 0.4571 loss_db: 0.1208 2022/10/26 04:33:14 - mmengine - INFO - Epoch(train) [697][10/63] lr: 1.6178e-03 eta: 6:32:01 time: 0.6639 data_time: 0.1585 memory: 16131 loss: 1.1233 loss_prob: 0.5938 loss_thr: 0.4255 loss_db: 0.1040 2022/10/26 04:33:17 - mmengine - INFO - Epoch(train) [697][15/63] lr: 1.6178e-03 eta: 6:32:01 time: 0.5240 data_time: 0.0225 memory: 16131 loss: 1.2465 loss_prob: 0.6768 loss_thr: 0.4552 loss_db: 0.1145 2022/10/26 04:33:19 - mmengine - INFO - Epoch(train) [697][20/63] lr: 1.6178e-03 eta: 6:31:52 time: 0.5204 data_time: 0.0183 memory: 16131 loss: 1.3234 loss_prob: 0.7197 loss_thr: 0.4809 loss_db: 0.1227 2022/10/26 04:33:22 - mmengine - INFO - Epoch(train) [697][25/63] lr: 1.6178e-03 eta: 6:31:52 time: 0.5230 data_time: 0.0093 memory: 16131 loss: 1.2281 loss_prob: 0.6549 loss_thr: 0.4607 loss_db: 0.1125 2022/10/26 04:33:25 - mmengine - INFO - Epoch(train) [697][30/63] lr: 1.6178e-03 eta: 6:31:43 time: 0.5722 data_time: 0.0222 memory: 16131 loss: 1.2168 loss_prob: 0.6566 loss_thr: 0.4491 loss_db: 0.1112 2022/10/26 04:33:27 - mmengine - INFO - Epoch(train) [697][35/63] lr: 1.6178e-03 eta: 6:31:43 time: 0.5617 data_time: 0.0209 memory: 16131 loss: 1.1806 loss_prob: 0.6325 loss_thr: 0.4401 loss_db: 0.1081 2022/10/26 04:33:30 - mmengine - INFO - Epoch(train) [697][40/63] lr: 1.6178e-03 eta: 6:31:34 time: 0.5200 data_time: 0.0157 memory: 16131 loss: 1.1267 loss_prob: 0.5910 loss_thr: 0.4353 loss_db: 0.1004 2022/10/26 04:33:33 - mmengine - INFO - Epoch(train) [697][45/63] lr: 1.6178e-03 eta: 6:31:34 time: 0.5207 data_time: 0.0122 memory: 16131 loss: 1.2276 loss_prob: 0.6546 loss_thr: 0.4608 loss_db: 0.1122 2022/10/26 04:33:35 - mmengine - INFO - Epoch(train) [697][50/63] lr: 1.6178e-03 eta: 6:31:25 time: 0.5171 data_time: 0.0097 memory: 16131 loss: 1.2602 loss_prob: 0.6813 loss_thr: 0.4618 loss_db: 0.1171 2022/10/26 04:33:38 - mmengine - INFO - Epoch(train) [697][55/63] lr: 1.6178e-03 eta: 6:31:25 time: 0.4983 data_time: 0.0168 memory: 16131 loss: 1.2549 loss_prob: 0.6792 loss_thr: 0.4605 loss_db: 0.1152 2022/10/26 04:33:40 - mmengine - INFO - Epoch(train) [697][60/63] lr: 1.6178e-03 eta: 6:31:16 time: 0.5211 data_time: 0.0211 memory: 16131 loss: 1.2115 loss_prob: 0.6554 loss_thr: 0.4441 loss_db: 0.1120 2022/10/26 04:33:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:33:46 - mmengine - INFO - Epoch(train) [698][5/63] lr: 1.6149e-03 eta: 6:31:16 time: 0.7287 data_time: 0.1521 memory: 16131 loss: 1.2275 loss_prob: 0.6654 loss_thr: 0.4524 loss_db: 0.1097 2022/10/26 04:33:49 - mmengine - INFO - Epoch(train) [698][10/63] lr: 1.6149e-03 eta: 6:31:05 time: 0.7522 data_time: 0.1624 memory: 16131 loss: 1.1928 loss_prob: 0.6398 loss_thr: 0.4486 loss_db: 0.1044 2022/10/26 04:33:52 - mmengine - INFO - Epoch(train) [698][15/63] lr: 1.6149e-03 eta: 6:31:05 time: 0.5307 data_time: 0.0226 memory: 16131 loss: 1.1674 loss_prob: 0.6239 loss_thr: 0.4371 loss_db: 0.1064 2022/10/26 04:33:54 - mmengine - INFO - Epoch(train) [698][20/63] lr: 1.6149e-03 eta: 6:30:56 time: 0.5035 data_time: 0.0074 memory: 16131 loss: 1.1570 loss_prob: 0.6259 loss_thr: 0.4241 loss_db: 0.1070 2022/10/26 04:33:57 - mmengine - INFO - Epoch(train) [698][25/63] lr: 1.6149e-03 eta: 6:30:56 time: 0.5149 data_time: 0.0096 memory: 16131 loss: 1.1225 loss_prob: 0.6000 loss_thr: 0.4196 loss_db: 0.1030 2022/10/26 04:34:00 - mmengine - INFO - Epoch(train) [698][30/63] lr: 1.6149e-03 eta: 6:30:47 time: 0.5444 data_time: 0.0216 memory: 16131 loss: 1.1534 loss_prob: 0.6039 loss_thr: 0.4444 loss_db: 0.1050 2022/10/26 04:34:02 - mmengine - INFO - Epoch(train) [698][35/63] lr: 1.6149e-03 eta: 6:30:47 time: 0.5294 data_time: 0.0325 memory: 16131 loss: 1.2480 loss_prob: 0.6664 loss_thr: 0.4681 loss_db: 0.1135 2022/10/26 04:34:05 - mmengine - INFO - Epoch(train) [698][40/63] lr: 1.6149e-03 eta: 6:30:39 time: 0.5455 data_time: 0.0194 memory: 16131 loss: 1.2385 loss_prob: 0.6698 loss_thr: 0.4556 loss_db: 0.1131 2022/10/26 04:34:08 - mmengine - INFO - Epoch(train) [698][45/63] lr: 1.6149e-03 eta: 6:30:39 time: 0.5547 data_time: 0.0058 memory: 16131 loss: 1.3093 loss_prob: 0.7197 loss_thr: 0.4715 loss_db: 0.1181 2022/10/26 04:34:10 - mmengine - INFO - Epoch(train) [698][50/63] lr: 1.6149e-03 eta: 6:30:30 time: 0.5213 data_time: 0.0161 memory: 16131 loss: 1.3638 loss_prob: 0.7563 loss_thr: 0.4819 loss_db: 0.1257 2022/10/26 04:34:13 - mmengine - INFO - Epoch(train) [698][55/63] lr: 1.6149e-03 eta: 6:30:30 time: 0.5096 data_time: 0.0175 memory: 16131 loss: 1.3297 loss_prob: 0.7218 loss_thr: 0.4838 loss_db: 0.1240 2022/10/26 04:34:15 - mmengine - INFO - Epoch(train) [698][60/63] lr: 1.6149e-03 eta: 6:30:20 time: 0.5089 data_time: 0.0122 memory: 16131 loss: 1.3236 loss_prob: 0.7179 loss_thr: 0.4833 loss_db: 0.1224 2022/10/26 04:34:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:34:22 - mmengine - INFO - Epoch(train) [699][5/63] lr: 1.6121e-03 eta: 6:30:20 time: 0.7621 data_time: 0.2204 memory: 16131 loss: 1.1619 loss_prob: 0.6196 loss_thr: 0.4359 loss_db: 0.1064 2022/10/26 04:34:24 - mmengine - INFO - Epoch(train) [699][10/63] lr: 1.6121e-03 eta: 6:30:10 time: 0.7786 data_time: 0.2200 memory: 16131 loss: 1.2914 loss_prob: 0.7111 loss_thr: 0.4624 loss_db: 0.1179 2022/10/26 04:34:27 - mmengine - INFO - Epoch(train) [699][15/63] lr: 1.6121e-03 eta: 6:30:10 time: 0.4965 data_time: 0.0047 memory: 16131 loss: 1.2557 loss_prob: 0.6925 loss_thr: 0.4482 loss_db: 0.1151 2022/10/26 04:34:29 - mmengine - INFO - Epoch(train) [699][20/63] lr: 1.6121e-03 eta: 6:30:00 time: 0.4963 data_time: 0.0072 memory: 16131 loss: 1.1699 loss_prob: 0.6214 loss_thr: 0.4413 loss_db: 0.1073 2022/10/26 04:34:32 - mmengine - INFO - Epoch(train) [699][25/63] lr: 1.6121e-03 eta: 6:30:00 time: 0.4958 data_time: 0.0110 memory: 16131 loss: 1.2492 loss_prob: 0.6651 loss_thr: 0.4683 loss_db: 0.1157 2022/10/26 04:34:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:34:35 - mmengine - INFO - Epoch(train) [699][30/63] lr: 1.6121e-03 eta: 6:29:51 time: 0.5378 data_time: 0.0333 memory: 16131 loss: 1.2377 loss_prob: 0.6504 loss_thr: 0.4761 loss_db: 0.1112 2022/10/26 04:34:38 - mmengine - INFO - Epoch(train) [699][35/63] lr: 1.6121e-03 eta: 6:29:51 time: 0.5654 data_time: 0.0294 memory: 16131 loss: 1.2097 loss_prob: 0.6438 loss_thr: 0.4572 loss_db: 0.1087 2022/10/26 04:34:40 - mmengine - INFO - Epoch(train) [699][40/63] lr: 1.6121e-03 eta: 6:29:43 time: 0.5298 data_time: 0.0061 memory: 16131 loss: 1.2762 loss_prob: 0.6977 loss_thr: 0.4595 loss_db: 0.1190 2022/10/26 04:34:43 - mmengine - INFO - Epoch(train) [699][45/63] lr: 1.6121e-03 eta: 6:29:43 time: 0.5318 data_time: 0.0060 memory: 16131 loss: 1.2529 loss_prob: 0.6785 loss_thr: 0.4602 loss_db: 0.1141 2022/10/26 04:34:45 - mmengine - INFO - Epoch(train) [699][50/63] lr: 1.6121e-03 eta: 6:29:34 time: 0.5322 data_time: 0.0118 memory: 16131 loss: 1.1889 loss_prob: 0.6260 loss_thr: 0.4562 loss_db: 0.1067 2022/10/26 04:34:48 - mmengine - INFO - Epoch(train) [699][55/63] lr: 1.6121e-03 eta: 6:29:34 time: 0.5211 data_time: 0.0212 memory: 16131 loss: 1.1761 loss_prob: 0.6107 loss_thr: 0.4595 loss_db: 0.1059 2022/10/26 04:34:50 - mmengine - INFO - Epoch(train) [699][60/63] lr: 1.6121e-03 eta: 6:29:25 time: 0.5100 data_time: 0.0156 memory: 16131 loss: 1.1443 loss_prob: 0.6019 loss_thr: 0.4386 loss_db: 0.1038 2022/10/26 04:34:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:34:58 - mmengine - INFO - Epoch(train) [700][5/63] lr: 1.6092e-03 eta: 6:29:25 time: 0.8642 data_time: 0.2194 memory: 16131 loss: 1.1588 loss_prob: 0.6149 loss_thr: 0.4359 loss_db: 0.1080 2022/10/26 04:35:02 - mmengine - INFO - Epoch(train) [700][10/63] lr: 1.6092e-03 eta: 6:29:15 time: 0.9647 data_time: 0.2193 memory: 16131 loss: 1.2136 loss_prob: 0.6585 loss_thr: 0.4418 loss_db: 0.1133 2022/10/26 04:35:04 - mmengine - INFO - Epoch(train) [700][15/63] lr: 1.6092e-03 eta: 6:29:15 time: 0.6138 data_time: 0.0056 memory: 16131 loss: 1.1764 loss_prob: 0.6349 loss_thr: 0.4351 loss_db: 0.1064 2022/10/26 04:35:07 - mmengine - INFO - Epoch(train) [700][20/63] lr: 1.6092e-03 eta: 6:29:06 time: 0.4971 data_time: 0.0060 memory: 16131 loss: 1.1958 loss_prob: 0.6422 loss_thr: 0.4463 loss_db: 0.1073 2022/10/26 04:35:09 - mmengine - INFO - Epoch(train) [700][25/63] lr: 1.6092e-03 eta: 6:29:06 time: 0.5086 data_time: 0.0201 memory: 16131 loss: 1.2268 loss_prob: 0.6639 loss_thr: 0.4490 loss_db: 0.1140 2022/10/26 04:35:12 - mmengine - INFO - Epoch(train) [700][30/63] lr: 1.6092e-03 eta: 6:28:57 time: 0.5404 data_time: 0.0352 memory: 16131 loss: 1.1965 loss_prob: 0.6370 loss_thr: 0.4473 loss_db: 0.1122 2022/10/26 04:35:15 - mmengine - INFO - Epoch(train) [700][35/63] lr: 1.6092e-03 eta: 6:28:57 time: 0.5302 data_time: 0.0252 memory: 16131 loss: 1.1800 loss_prob: 0.6269 loss_thr: 0.4440 loss_db: 0.1092 2022/10/26 04:35:17 - mmengine - INFO - Epoch(train) [700][40/63] lr: 1.6092e-03 eta: 6:28:48 time: 0.5051 data_time: 0.0098 memory: 16131 loss: 1.1699 loss_prob: 0.6281 loss_thr: 0.4334 loss_db: 0.1084 2022/10/26 04:35:20 - mmengine - INFO - Epoch(train) [700][45/63] lr: 1.6092e-03 eta: 6:28:48 time: 0.5051 data_time: 0.0051 memory: 16131 loss: 1.2090 loss_prob: 0.6529 loss_thr: 0.4459 loss_db: 0.1101 2022/10/26 04:35:22 - mmengine - INFO - Epoch(train) [700][50/63] lr: 1.6092e-03 eta: 6:28:39 time: 0.5035 data_time: 0.0196 memory: 16131 loss: 1.1787 loss_prob: 0.6348 loss_thr: 0.4366 loss_db: 0.1073 2022/10/26 04:35:25 - mmengine - INFO - Epoch(train) [700][55/63] lr: 1.6092e-03 eta: 6:28:39 time: 0.5106 data_time: 0.0207 memory: 16131 loss: 1.1401 loss_prob: 0.6184 loss_thr: 0.4146 loss_db: 0.1070 2022/10/26 04:35:27 - mmengine - INFO - Epoch(train) [700][60/63] lr: 1.6092e-03 eta: 6:28:30 time: 0.5105 data_time: 0.0074 memory: 16131 loss: 1.1962 loss_prob: 0.6466 loss_thr: 0.4385 loss_db: 0.1111 2022/10/26 04:35:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:35:28 - mmengine - INFO - Saving checkpoint at 700 epochs 2022/10/26 04:35:35 - mmengine - INFO - Epoch(val) [700][5/32] eta: 6:28:30 time: 0.5139 data_time: 0.0583 memory: 16131 2022/10/26 04:35:38 - mmengine - INFO - Epoch(val) [700][10/32] eta: 0:00:13 time: 0.6052 data_time: 0.0833 memory: 15724 2022/10/26 04:35:41 - mmengine - INFO - Epoch(val) [700][15/32] eta: 0:00:13 time: 0.5548 data_time: 0.0394 memory: 15724 2022/10/26 04:35:43 - mmengine - INFO - Epoch(val) [700][20/32] eta: 0:00:06 time: 0.5190 data_time: 0.0370 memory: 15724 2022/10/26 04:35:46 - mmengine - INFO - Epoch(val) [700][25/32] eta: 0:00:06 time: 0.5307 data_time: 0.0392 memory: 15724 2022/10/26 04:35:48 - mmengine - INFO - Epoch(val) [700][30/32] eta: 0:00:01 time: 0.5052 data_time: 0.0199 memory: 15724 2022/10/26 04:35:49 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8382, precision: 0.7553, hmean: 0.7946 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8377, precision: 0.8011, hmean: 0.8190 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8377, precision: 0.8313, hmean: 0.8345 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8325, precision: 0.8602, hmean: 0.8461 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8074, precision: 0.8911, hmean: 0.8472 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6707, precision: 0.9343, hmean: 0.7808 2022/10/26 04:35:49 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0448, precision: 1.0000, hmean: 0.0857 2022/10/26 04:35:49 - mmengine - INFO - Epoch(val) [700][32/32] icdar/precision: 0.8911 icdar/recall: 0.8074 icdar/hmean: 0.8472 2022/10/26 04:35:54 - mmengine - INFO - Epoch(train) [701][5/63] lr: 1.6063e-03 eta: 0:00:01 time: 0.6913 data_time: 0.1758 memory: 16131 loss: 1.1896 loss_prob: 0.6343 loss_thr: 0.4471 loss_db: 0.1082 2022/10/26 04:35:56 - mmengine - INFO - Epoch(train) [701][10/63] lr: 1.6063e-03 eta: 6:28:19 time: 0.7208 data_time: 0.1823 memory: 16131 loss: 1.1651 loss_prob: 0.6250 loss_thr: 0.4347 loss_db: 0.1055 2022/10/26 04:35:59 - mmengine - INFO - Epoch(train) [701][15/63] lr: 1.6063e-03 eta: 6:28:19 time: 0.5104 data_time: 0.0133 memory: 16131 loss: 1.1684 loss_prob: 0.6232 loss_thr: 0.4389 loss_db: 0.1063 2022/10/26 04:36:01 - mmengine - INFO - Epoch(train) [701][20/63] lr: 1.6063e-03 eta: 6:28:09 time: 0.4892 data_time: 0.0058 memory: 16131 loss: 1.1005 loss_prob: 0.5836 loss_thr: 0.4164 loss_db: 0.1006 2022/10/26 04:36:04 - mmengine - INFO - Epoch(train) [701][25/63] lr: 1.6063e-03 eta: 6:28:09 time: 0.5040 data_time: 0.0194 memory: 16131 loss: 1.1407 loss_prob: 0.6185 loss_thr: 0.4144 loss_db: 0.1078 2022/10/26 04:36:06 - mmengine - INFO - Epoch(train) [701][30/63] lr: 1.6063e-03 eta: 6:28:00 time: 0.5241 data_time: 0.0273 memory: 16131 loss: 1.1043 loss_prob: 0.5989 loss_thr: 0.4008 loss_db: 0.1046 2022/10/26 04:36:09 - mmengine - INFO - Epoch(train) [701][35/63] lr: 1.6063e-03 eta: 6:28:00 time: 0.5709 data_time: 0.0203 memory: 16131 loss: 1.0708 loss_prob: 0.5701 loss_thr: 0.4034 loss_db: 0.0973 2022/10/26 04:36:12 - mmengine - INFO - Epoch(train) [701][40/63] lr: 1.6063e-03 eta: 6:27:52 time: 0.5623 data_time: 0.0125 memory: 16131 loss: 1.2558 loss_prob: 0.6737 loss_thr: 0.4694 loss_db: 0.1127 2022/10/26 04:36:14 - mmengine - INFO - Epoch(train) [701][45/63] lr: 1.6063e-03 eta: 6:27:52 time: 0.5007 data_time: 0.0046 memory: 16131 loss: 1.3287 loss_prob: 0.7208 loss_thr: 0.4868 loss_db: 0.1211 2022/10/26 04:36:17 - mmengine - INFO - Epoch(train) [701][50/63] lr: 1.6063e-03 eta: 6:27:43 time: 0.5422 data_time: 0.0168 memory: 16131 loss: 1.1842 loss_prob: 0.6308 loss_thr: 0.4452 loss_db: 0.1083 2022/10/26 04:36:20 - mmengine - INFO - Epoch(train) [701][55/63] lr: 1.6063e-03 eta: 6:27:43 time: 0.5550 data_time: 0.0189 memory: 16131 loss: 1.1249 loss_prob: 0.5844 loss_thr: 0.4377 loss_db: 0.1028 2022/10/26 04:36:23 - mmengine - INFO - Epoch(train) [701][60/63] lr: 1.6063e-03 eta: 6:27:34 time: 0.5267 data_time: 0.0102 memory: 16131 loss: 1.1305 loss_prob: 0.5941 loss_thr: 0.4344 loss_db: 0.1021 2022/10/26 04:36:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:36:28 - mmengine - INFO - Epoch(train) [702][5/63] lr: 1.6034e-03 eta: 6:27:34 time: 0.6710 data_time: 0.1753 memory: 16131 loss: 1.1856 loss_prob: 0.6375 loss_thr: 0.4371 loss_db: 0.1110 2022/10/26 04:36:31 - mmengine - INFO - Epoch(train) [702][10/63] lr: 1.6034e-03 eta: 6:27:23 time: 0.7066 data_time: 0.1757 memory: 16131 loss: 1.1576 loss_prob: 0.6201 loss_thr: 0.4283 loss_db: 0.1093 2022/10/26 04:36:34 - mmengine - INFO - Epoch(train) [702][15/63] lr: 1.6034e-03 eta: 6:27:23 time: 0.5846 data_time: 0.0080 memory: 16131 loss: 1.2352 loss_prob: 0.6707 loss_thr: 0.4539 loss_db: 0.1106 2022/10/26 04:36:37 - mmengine - INFO - Epoch(train) [702][20/63] lr: 1.6034e-03 eta: 6:27:14 time: 0.5745 data_time: 0.0114 memory: 16131 loss: 1.2554 loss_prob: 0.6786 loss_thr: 0.4617 loss_db: 0.1151 2022/10/26 04:36:40 - mmengine - INFO - Epoch(train) [702][25/63] lr: 1.6034e-03 eta: 6:27:14 time: 0.5506 data_time: 0.0307 memory: 16131 loss: 1.1491 loss_prob: 0.6114 loss_thr: 0.4308 loss_db: 0.1069 2022/10/26 04:36:42 - mmengine - INFO - Epoch(train) [702][30/63] lr: 1.6034e-03 eta: 6:27:05 time: 0.5639 data_time: 0.0308 memory: 16131 loss: 1.1940 loss_prob: 0.6474 loss_thr: 0.4347 loss_db: 0.1119 2022/10/26 04:36:45 - mmengine - INFO - Epoch(train) [702][35/63] lr: 1.6034e-03 eta: 6:27:05 time: 0.5264 data_time: 0.0111 memory: 16131 loss: 1.1588 loss_prob: 0.6233 loss_thr: 0.4262 loss_db: 0.1093 2022/10/26 04:36:48 - mmengine - INFO - Epoch(train) [702][40/63] lr: 1.6034e-03 eta: 6:26:56 time: 0.5225 data_time: 0.0141 memory: 16131 loss: 1.0886 loss_prob: 0.5778 loss_thr: 0.4119 loss_db: 0.0990 2022/10/26 04:36:50 - mmengine - INFO - Epoch(train) [702][45/63] lr: 1.6034e-03 eta: 6:26:56 time: 0.5422 data_time: 0.0122 memory: 16131 loss: 1.1742 loss_prob: 0.6350 loss_thr: 0.4308 loss_db: 0.1083 2022/10/26 04:36:53 - mmengine - INFO - Epoch(train) [702][50/63] lr: 1.6034e-03 eta: 6:26:48 time: 0.5317 data_time: 0.0211 memory: 16131 loss: 1.1811 loss_prob: 0.6392 loss_thr: 0.4318 loss_db: 0.1100 2022/10/26 04:36:55 - mmengine - INFO - Epoch(train) [702][55/63] lr: 1.6034e-03 eta: 6:26:48 time: 0.5084 data_time: 0.0218 memory: 16131 loss: 1.2591 loss_prob: 0.6967 loss_thr: 0.4504 loss_db: 0.1120 2022/10/26 04:36:58 - mmengine - INFO - Epoch(train) [702][60/63] lr: 1.6034e-03 eta: 6:26:39 time: 0.5112 data_time: 0.0112 memory: 16131 loss: 1.2332 loss_prob: 0.6765 loss_thr: 0.4458 loss_db: 0.1109 2022/10/26 04:36:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:37:04 - mmengine - INFO - Epoch(train) [703][5/63] lr: 1.6005e-03 eta: 6:26:39 time: 0.7102 data_time: 0.1808 memory: 16131 loss: 1.2432 loss_prob: 0.6612 loss_thr: 0.4674 loss_db: 0.1147 2022/10/26 04:37:06 - mmengine - INFO - Epoch(train) [703][10/63] lr: 1.6005e-03 eta: 6:26:27 time: 0.6939 data_time: 0.1840 memory: 16131 loss: 1.1506 loss_prob: 0.6207 loss_thr: 0.4266 loss_db: 0.1033 2022/10/26 04:37:09 - mmengine - INFO - Epoch(train) [703][15/63] lr: 1.6005e-03 eta: 6:26:27 time: 0.5130 data_time: 0.0100 memory: 16131 loss: 1.1889 loss_prob: 0.6565 loss_thr: 0.4266 loss_db: 0.1058 2022/10/26 04:37:12 - mmengine - INFO - Epoch(train) [703][20/63] lr: 1.6005e-03 eta: 6:26:18 time: 0.5308 data_time: 0.0113 memory: 16131 loss: 1.3160 loss_prob: 0.7305 loss_thr: 0.4651 loss_db: 0.1205 2022/10/26 04:37:14 - mmengine - INFO - Epoch(train) [703][25/63] lr: 1.6005e-03 eta: 6:26:18 time: 0.5322 data_time: 0.0268 memory: 16131 loss: 1.2113 loss_prob: 0.6511 loss_thr: 0.4478 loss_db: 0.1124 2022/10/26 04:37:17 - mmengine - INFO - Epoch(train) [703][30/63] lr: 1.6005e-03 eta: 6:26:09 time: 0.5338 data_time: 0.0270 memory: 16131 loss: 1.1340 loss_prob: 0.5991 loss_thr: 0.4310 loss_db: 0.1039 2022/10/26 04:37:20 - mmengine - INFO - Epoch(train) [703][35/63] lr: 1.6005e-03 eta: 6:26:09 time: 0.5289 data_time: 0.0142 memory: 16131 loss: 1.3020 loss_prob: 0.7368 loss_thr: 0.4474 loss_db: 0.1179 2022/10/26 04:37:22 - mmengine - INFO - Epoch(train) [703][40/63] lr: 1.6005e-03 eta: 6:26:01 time: 0.5423 data_time: 0.0116 memory: 16131 loss: 1.2828 loss_prob: 0.7282 loss_thr: 0.4362 loss_db: 0.1184 2022/10/26 04:37:25 - mmengine - INFO - Epoch(train) [703][45/63] lr: 1.6005e-03 eta: 6:26:01 time: 0.5435 data_time: 0.0126 memory: 16131 loss: 1.1721 loss_prob: 0.6296 loss_thr: 0.4331 loss_db: 0.1094 2022/10/26 04:37:28 - mmengine - INFO - Epoch(train) [703][50/63] lr: 1.6005e-03 eta: 6:25:52 time: 0.5405 data_time: 0.0229 memory: 16131 loss: 1.2454 loss_prob: 0.6652 loss_thr: 0.4678 loss_db: 0.1124 2022/10/26 04:37:30 - mmengine - INFO - Epoch(train) [703][55/63] lr: 1.6005e-03 eta: 6:25:52 time: 0.5231 data_time: 0.0224 memory: 16131 loss: 1.2677 loss_prob: 0.6893 loss_thr: 0.4615 loss_db: 0.1169 2022/10/26 04:37:33 - mmengine - INFO - Epoch(train) [703][60/63] lr: 1.6005e-03 eta: 6:25:43 time: 0.5103 data_time: 0.0119 memory: 16131 loss: 1.2631 loss_prob: 0.6919 loss_thr: 0.4541 loss_db: 0.1171 2022/10/26 04:37:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:37:39 - mmengine - INFO - Epoch(train) [704][5/63] lr: 1.5976e-03 eta: 6:25:43 time: 0.6765 data_time: 0.1869 memory: 16131 loss: 1.2932 loss_prob: 0.6986 loss_thr: 0.4755 loss_db: 0.1191 2022/10/26 04:37:42 - mmengine - INFO - Epoch(train) [704][10/63] lr: 1.5976e-03 eta: 6:25:31 time: 0.7318 data_time: 0.1907 memory: 16131 loss: 1.2880 loss_prob: 0.6995 loss_thr: 0.4710 loss_db: 0.1175 2022/10/26 04:37:44 - mmengine - INFO - Epoch(train) [704][15/63] lr: 1.5976e-03 eta: 6:25:31 time: 0.5205 data_time: 0.0092 memory: 16131 loss: 1.1652 loss_prob: 0.6247 loss_thr: 0.4339 loss_db: 0.1066 2022/10/26 04:37:46 - mmengine - INFO - Epoch(train) [704][20/63] lr: 1.5976e-03 eta: 6:25:22 time: 0.4904 data_time: 0.0057 memory: 16131 loss: 1.4480 loss_prob: 0.8619 loss_thr: 0.4573 loss_db: 0.1288 2022/10/26 04:37:49 - mmengine - INFO - Epoch(train) [704][25/63] lr: 1.5976e-03 eta: 6:25:22 time: 0.5447 data_time: 0.0219 memory: 16131 loss: 1.5293 loss_prob: 0.9161 loss_thr: 0.4766 loss_db: 0.1366 2022/10/26 04:37:52 - mmengine - INFO - Epoch(train) [704][30/63] lr: 1.5976e-03 eta: 6:25:14 time: 0.5585 data_time: 0.0329 memory: 16131 loss: 1.2278 loss_prob: 0.6697 loss_thr: 0.4442 loss_db: 0.1139 2022/10/26 04:37:55 - mmengine - INFO - Epoch(train) [704][35/63] lr: 1.5976e-03 eta: 6:25:14 time: 0.5131 data_time: 0.0167 memory: 16131 loss: 1.1718 loss_prob: 0.6338 loss_thr: 0.4314 loss_db: 0.1066 2022/10/26 04:37:57 - mmengine - INFO - Epoch(train) [704][40/63] lr: 1.5976e-03 eta: 6:25:05 time: 0.5295 data_time: 0.0047 memory: 16131 loss: 1.2416 loss_prob: 0.6773 loss_thr: 0.4535 loss_db: 0.1108 2022/10/26 04:38:00 - mmengine - INFO - Epoch(train) [704][45/63] lr: 1.5976e-03 eta: 6:25:05 time: 0.5586 data_time: 0.0045 memory: 16131 loss: 1.2838 loss_prob: 0.6988 loss_thr: 0.4695 loss_db: 0.1155 2022/10/26 04:38:03 - mmengine - INFO - Epoch(train) [704][50/63] lr: 1.5976e-03 eta: 6:24:56 time: 0.5430 data_time: 0.0223 memory: 16131 loss: 1.2342 loss_prob: 0.6668 loss_thr: 0.4526 loss_db: 0.1148 2022/10/26 04:38:05 - mmengine - INFO - Epoch(train) [704][55/63] lr: 1.5976e-03 eta: 6:24:56 time: 0.5078 data_time: 0.0224 memory: 16131 loss: 1.1837 loss_prob: 0.6390 loss_thr: 0.4355 loss_db: 0.1091 2022/10/26 04:38:08 - mmengine - INFO - Epoch(train) [704][60/63] lr: 1.5976e-03 eta: 6:24:47 time: 0.5338 data_time: 0.0059 memory: 16131 loss: 1.0839 loss_prob: 0.5756 loss_thr: 0.4100 loss_db: 0.0983 2022/10/26 04:38:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:38:15 - mmengine - INFO - Epoch(train) [705][5/63] lr: 1.5947e-03 eta: 6:24:47 time: 0.7949 data_time: 0.2278 memory: 16131 loss: 1.1794 loss_prob: 0.6294 loss_thr: 0.4418 loss_db: 0.1082 2022/10/26 04:38:17 - mmengine - INFO - Epoch(train) [705][10/63] lr: 1.5947e-03 eta: 6:24:36 time: 0.7787 data_time: 0.2285 memory: 16131 loss: 1.2499 loss_prob: 0.6821 loss_thr: 0.4512 loss_db: 0.1166 2022/10/26 04:38:20 - mmengine - INFO - Epoch(train) [705][15/63] lr: 1.5947e-03 eta: 6:24:36 time: 0.5164 data_time: 0.0121 memory: 16131 loss: 1.2253 loss_prob: 0.6669 loss_thr: 0.4444 loss_db: 0.1141 2022/10/26 04:38:22 - mmengine - INFO - Epoch(train) [705][20/63] lr: 1.5947e-03 eta: 6:24:27 time: 0.5001 data_time: 0.0110 memory: 16131 loss: 1.1762 loss_prob: 0.6346 loss_thr: 0.4314 loss_db: 0.1102 2022/10/26 04:38:25 - mmengine - INFO - Epoch(train) [705][25/63] lr: 1.5947e-03 eta: 6:24:27 time: 0.5236 data_time: 0.0197 memory: 16131 loss: 1.1719 loss_prob: 0.6286 loss_thr: 0.4330 loss_db: 0.1103 2022/10/26 04:38:28 - mmengine - INFO - Epoch(train) [705][30/63] lr: 1.5947e-03 eta: 6:24:19 time: 0.5805 data_time: 0.0376 memory: 16131 loss: 1.1981 loss_prob: 0.6437 loss_thr: 0.4451 loss_db: 0.1093 2022/10/26 04:38:31 - mmengine - INFO - Epoch(train) [705][35/63] lr: 1.5947e-03 eta: 6:24:19 time: 0.5475 data_time: 0.0231 memory: 16131 loss: 1.1469 loss_prob: 0.6086 loss_thr: 0.4359 loss_db: 0.1023 2022/10/26 04:38:33 - mmengine - INFO - Epoch(train) [705][40/63] lr: 1.5947e-03 eta: 6:24:10 time: 0.4920 data_time: 0.0049 memory: 16131 loss: 1.2582 loss_prob: 0.6910 loss_thr: 0.4500 loss_db: 0.1172 2022/10/26 04:38:36 - mmengine - INFO - Epoch(train) [705][45/63] lr: 1.5947e-03 eta: 6:24:10 time: 0.4922 data_time: 0.0047 memory: 16131 loss: 1.3339 loss_prob: 0.7493 loss_thr: 0.4597 loss_db: 0.1250 2022/10/26 04:38:39 - mmengine - INFO - Epoch(train) [705][50/63] lr: 1.5947e-03 eta: 6:24:01 time: 0.6260 data_time: 0.0215 memory: 16131 loss: 1.1772 loss_prob: 0.6425 loss_thr: 0.4264 loss_db: 0.1083 2022/10/26 04:38:42 - mmengine - INFO - Epoch(train) [705][55/63] lr: 1.5947e-03 eta: 6:24:01 time: 0.6259 data_time: 0.0226 memory: 16131 loss: 1.1629 loss_prob: 0.6272 loss_thr: 0.4280 loss_db: 0.1077 2022/10/26 04:38:45 - mmengine - INFO - Epoch(train) [705][60/63] lr: 1.5947e-03 eta: 6:23:53 time: 0.5214 data_time: 0.0060 memory: 16131 loss: 1.2082 loss_prob: 0.6529 loss_thr: 0.4461 loss_db: 0.1092 2022/10/26 04:38:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:38:50 - mmengine - INFO - Epoch(train) [706][5/63] lr: 1.5918e-03 eta: 6:23:53 time: 0.6892 data_time: 0.1896 memory: 16131 loss: 1.3672 loss_prob: 0.7807 loss_thr: 0.4637 loss_db: 0.1229 2022/10/26 04:38:53 - mmengine - INFO - Epoch(train) [706][10/63] lr: 1.5918e-03 eta: 6:23:41 time: 0.7405 data_time: 0.1924 memory: 16131 loss: 1.2832 loss_prob: 0.7331 loss_thr: 0.4361 loss_db: 0.1140 2022/10/26 04:38:56 - mmengine - INFO - Epoch(train) [706][15/63] lr: 1.5918e-03 eta: 6:23:41 time: 0.5345 data_time: 0.0075 memory: 16131 loss: 1.1680 loss_prob: 0.6355 loss_thr: 0.4280 loss_db: 0.1045 2022/10/26 04:38:58 - mmengine - INFO - Epoch(train) [706][20/63] lr: 1.5918e-03 eta: 6:23:32 time: 0.4980 data_time: 0.0063 memory: 16131 loss: 1.1809 loss_prob: 0.6531 loss_thr: 0.4217 loss_db: 0.1061 2022/10/26 04:39:01 - mmengine - INFO - Epoch(train) [706][25/63] lr: 1.5918e-03 eta: 6:23:32 time: 0.5325 data_time: 0.0348 memory: 16131 loss: 1.1444 loss_prob: 0.6238 loss_thr: 0.4164 loss_db: 0.1042 2022/10/26 04:39:04 - mmengine - INFO - Epoch(train) [706][30/63] lr: 1.5918e-03 eta: 6:23:24 time: 0.5434 data_time: 0.0430 memory: 16131 loss: 1.2484 loss_prob: 0.6850 loss_thr: 0.4477 loss_db: 0.1157 2022/10/26 04:39:06 - mmengine - INFO - Epoch(train) [706][35/63] lr: 1.5918e-03 eta: 6:23:24 time: 0.5042 data_time: 0.0149 memory: 16131 loss: 1.3159 loss_prob: 0.7195 loss_thr: 0.4752 loss_db: 0.1212 2022/10/26 04:39:08 - mmengine - INFO - Epoch(train) [706][40/63] lr: 1.5918e-03 eta: 6:23:14 time: 0.4825 data_time: 0.0050 memory: 16131 loss: 1.3216 loss_prob: 0.7233 loss_thr: 0.4787 loss_db: 0.1197 2022/10/26 04:39:11 - mmengine - INFO - Epoch(train) [706][45/63] lr: 1.5918e-03 eta: 6:23:14 time: 0.4852 data_time: 0.0067 memory: 16131 loss: 1.2369 loss_prob: 0.6743 loss_thr: 0.4501 loss_db: 0.1125 2022/10/26 04:39:14 - mmengine - INFO - Epoch(train) [706][50/63] lr: 1.5918e-03 eta: 6:23:05 time: 0.5144 data_time: 0.0251 memory: 16131 loss: 1.1937 loss_prob: 0.6375 loss_thr: 0.4446 loss_db: 0.1116 2022/10/26 04:39:16 - mmengine - INFO - Epoch(train) [706][55/63] lr: 1.5918e-03 eta: 6:23:05 time: 0.5507 data_time: 0.0230 memory: 16131 loss: 1.2718 loss_prob: 0.6847 loss_thr: 0.4691 loss_db: 0.1181 2022/10/26 04:39:19 - mmengine - INFO - Epoch(train) [706][60/63] lr: 1.5918e-03 eta: 6:22:57 time: 0.5500 data_time: 0.0057 memory: 16131 loss: 1.2353 loss_prob: 0.6597 loss_thr: 0.4636 loss_db: 0.1121 2022/10/26 04:39:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:39:25 - mmengine - INFO - Epoch(train) [707][5/63] lr: 1.5889e-03 eta: 6:22:57 time: 0.7047 data_time: 0.1733 memory: 16131 loss: 1.1389 loss_prob: 0.5965 loss_thr: 0.4395 loss_db: 0.1029 2022/10/26 04:39:28 - mmengine - INFO - Epoch(train) [707][10/63] lr: 1.5889e-03 eta: 6:22:46 time: 0.7266 data_time: 0.1756 memory: 16131 loss: 1.2554 loss_prob: 0.6721 loss_thr: 0.4690 loss_db: 0.1143 2022/10/26 04:39:31 - mmengine - INFO - Epoch(train) [707][15/63] lr: 1.5889e-03 eta: 6:22:46 time: 0.5624 data_time: 0.0093 memory: 16131 loss: 1.2140 loss_prob: 0.6517 loss_thr: 0.4511 loss_db: 0.1112 2022/10/26 04:39:33 - mmengine - INFO - Epoch(train) [707][20/63] lr: 1.5889e-03 eta: 6:22:37 time: 0.5605 data_time: 0.0071 memory: 16131 loss: 1.0916 loss_prob: 0.5741 loss_thr: 0.4169 loss_db: 0.1006 2022/10/26 04:39:36 - mmengine - INFO - Epoch(train) [707][25/63] lr: 1.5889e-03 eta: 6:22:37 time: 0.5346 data_time: 0.0118 memory: 16131 loss: 1.0748 loss_prob: 0.5688 loss_thr: 0.4072 loss_db: 0.0988 2022/10/26 04:39:39 - mmengine - INFO - Epoch(train) [707][30/63] lr: 1.5889e-03 eta: 6:22:28 time: 0.5338 data_time: 0.0293 memory: 16131 loss: 1.1671 loss_prob: 0.6316 loss_thr: 0.4304 loss_db: 0.1051 2022/10/26 04:39:41 - mmengine - INFO - Epoch(train) [707][35/63] lr: 1.5889e-03 eta: 6:22:28 time: 0.5236 data_time: 0.0274 memory: 16131 loss: 1.2287 loss_prob: 0.6611 loss_thr: 0.4558 loss_db: 0.1118 2022/10/26 04:39:44 - mmengine - INFO - Epoch(train) [707][40/63] lr: 1.5889e-03 eta: 6:22:19 time: 0.5061 data_time: 0.0100 memory: 16131 loss: 1.2350 loss_prob: 0.6715 loss_thr: 0.4518 loss_db: 0.1116 2022/10/26 04:39:46 - mmengine - INFO - Epoch(train) [707][45/63] lr: 1.5889e-03 eta: 6:22:19 time: 0.5002 data_time: 0.0121 memory: 16131 loss: 1.2367 loss_prob: 0.6805 loss_thr: 0.4444 loss_db: 0.1119 2022/10/26 04:39:49 - mmengine - INFO - Epoch(train) [707][50/63] lr: 1.5889e-03 eta: 6:22:10 time: 0.5217 data_time: 0.0153 memory: 16131 loss: 1.2398 loss_prob: 0.6822 loss_thr: 0.4423 loss_db: 0.1153 2022/10/26 04:39:52 - mmengine - INFO - Epoch(train) [707][55/63] lr: 1.5889e-03 eta: 6:22:10 time: 0.5437 data_time: 0.0210 memory: 16131 loss: 1.2619 loss_prob: 0.6881 loss_thr: 0.4569 loss_db: 0.1168 2022/10/26 04:39:54 - mmengine - INFO - Epoch(train) [707][60/63] lr: 1.5889e-03 eta: 6:22:01 time: 0.5366 data_time: 0.0172 memory: 16131 loss: 1.1845 loss_prob: 0.6296 loss_thr: 0.4463 loss_db: 0.1086 2022/10/26 04:39:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:40:00 - mmengine - INFO - Epoch(train) [708][5/63] lr: 1.5860e-03 eta: 6:22:01 time: 0.6839 data_time: 0.1891 memory: 16131 loss: 1.2048 loss_prob: 0.6532 loss_thr: 0.4395 loss_db: 0.1121 2022/10/26 04:40:03 - mmengine - INFO - Epoch(train) [708][10/63] lr: 1.5860e-03 eta: 6:21:50 time: 0.7009 data_time: 0.1912 memory: 16131 loss: 1.2496 loss_prob: 0.6699 loss_thr: 0.4632 loss_db: 0.1165 2022/10/26 04:40:05 - mmengine - INFO - Epoch(train) [708][15/63] lr: 1.5860e-03 eta: 6:21:50 time: 0.5303 data_time: 0.0114 memory: 16131 loss: 1.1891 loss_prob: 0.6303 loss_thr: 0.4489 loss_db: 0.1100 2022/10/26 04:40:08 - mmengine - INFO - Epoch(train) [708][20/63] lr: 1.5860e-03 eta: 6:21:41 time: 0.5524 data_time: 0.0079 memory: 16131 loss: 1.1476 loss_prob: 0.6115 loss_thr: 0.4288 loss_db: 0.1073 2022/10/26 04:40:11 - mmengine - INFO - Epoch(train) [708][25/63] lr: 1.5860e-03 eta: 6:21:41 time: 0.5675 data_time: 0.0280 memory: 16131 loss: 1.1592 loss_prob: 0.6249 loss_thr: 0.4276 loss_db: 0.1067 2022/10/26 04:40:14 - mmengine - INFO - Epoch(train) [708][30/63] lr: 1.5860e-03 eta: 6:21:33 time: 0.5451 data_time: 0.0323 memory: 16131 loss: 1.2376 loss_prob: 0.6700 loss_thr: 0.4562 loss_db: 0.1114 2022/10/26 04:40:17 - mmengine - INFO - Epoch(train) [708][35/63] lr: 1.5860e-03 eta: 6:21:33 time: 0.5536 data_time: 0.0138 memory: 16131 loss: 1.2374 loss_prob: 0.6691 loss_thr: 0.4565 loss_db: 0.1118 2022/10/26 04:40:19 - mmengine - INFO - Epoch(train) [708][40/63] lr: 1.5860e-03 eta: 6:21:24 time: 0.5445 data_time: 0.0107 memory: 16131 loss: 1.1772 loss_prob: 0.6349 loss_thr: 0.4354 loss_db: 0.1068 2022/10/26 04:40:22 - mmengine - INFO - Epoch(train) [708][45/63] lr: 1.5860e-03 eta: 6:21:24 time: 0.5136 data_time: 0.0074 memory: 16131 loss: 1.1718 loss_prob: 0.6328 loss_thr: 0.4304 loss_db: 0.1086 2022/10/26 04:40:24 - mmengine - INFO - Epoch(train) [708][50/63] lr: 1.5860e-03 eta: 6:21:15 time: 0.5351 data_time: 0.0180 memory: 16131 loss: 1.2315 loss_prob: 0.6783 loss_thr: 0.4362 loss_db: 0.1169 2022/10/26 04:40:27 - mmengine - INFO - Epoch(train) [708][55/63] lr: 1.5860e-03 eta: 6:21:15 time: 0.5058 data_time: 0.0180 memory: 16131 loss: 1.2089 loss_prob: 0.6581 loss_thr: 0.4398 loss_db: 0.1110 2022/10/26 04:40:29 - mmengine - INFO - Epoch(train) [708][60/63] lr: 1.5860e-03 eta: 6:21:06 time: 0.4915 data_time: 0.0095 memory: 16131 loss: 1.2058 loss_prob: 0.6476 loss_thr: 0.4474 loss_db: 0.1107 2022/10/26 04:40:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:40:36 - mmengine - INFO - Epoch(train) [709][5/63] lr: 1.5831e-03 eta: 6:21:06 time: 0.7442 data_time: 0.1787 memory: 16131 loss: 1.2592 loss_prob: 0.6855 loss_thr: 0.4568 loss_db: 0.1168 2022/10/26 04:40:38 - mmengine - INFO - Epoch(train) [709][10/63] lr: 1.5831e-03 eta: 6:20:55 time: 0.7408 data_time: 0.1772 memory: 16131 loss: 1.1630 loss_prob: 0.6301 loss_thr: 0.4257 loss_db: 0.1071 2022/10/26 04:40:41 - mmengine - INFO - Epoch(train) [709][15/63] lr: 1.5831e-03 eta: 6:20:55 time: 0.5472 data_time: 0.0146 memory: 16131 loss: 1.1385 loss_prob: 0.6111 loss_thr: 0.4231 loss_db: 0.1043 2022/10/26 04:40:44 - mmengine - INFO - Epoch(train) [709][20/63] lr: 1.5831e-03 eta: 6:20:46 time: 0.5478 data_time: 0.0125 memory: 16131 loss: 1.2242 loss_prob: 0.6648 loss_thr: 0.4450 loss_db: 0.1144 2022/10/26 04:40:46 - mmengine - INFO - Epoch(train) [709][25/63] lr: 1.5831e-03 eta: 6:20:46 time: 0.5137 data_time: 0.0100 memory: 16131 loss: 1.1970 loss_prob: 0.6474 loss_thr: 0.4384 loss_db: 0.1112 2022/10/26 04:40:49 - mmengine - INFO - Epoch(train) [709][30/63] lr: 1.5831e-03 eta: 6:20:37 time: 0.5234 data_time: 0.0261 memory: 16131 loss: 1.1403 loss_prob: 0.6011 loss_thr: 0.4367 loss_db: 0.1025 2022/10/26 04:40:52 - mmengine - INFO - Epoch(train) [709][35/63] lr: 1.5831e-03 eta: 6:20:37 time: 0.5191 data_time: 0.0225 memory: 16131 loss: 1.1959 loss_prob: 0.6416 loss_thr: 0.4435 loss_db: 0.1107 2022/10/26 04:40:54 - mmengine - INFO - Epoch(train) [709][40/63] lr: 1.5831e-03 eta: 6:20:28 time: 0.5072 data_time: 0.0143 memory: 16131 loss: 1.1774 loss_prob: 0.6377 loss_thr: 0.4316 loss_db: 0.1081 2022/10/26 04:40:57 - mmengine - INFO - Epoch(train) [709][45/63] lr: 1.5831e-03 eta: 6:20:28 time: 0.5202 data_time: 0.0142 memory: 16131 loss: 1.2090 loss_prob: 0.6610 loss_thr: 0.4373 loss_db: 0.1107 2022/10/26 04:41:00 - mmengine - INFO - Epoch(train) [709][50/63] lr: 1.5831e-03 eta: 6:20:20 time: 0.5469 data_time: 0.0222 memory: 16131 loss: 1.2090 loss_prob: 0.6651 loss_thr: 0.4298 loss_db: 0.1141 2022/10/26 04:41:02 - mmengine - INFO - Epoch(train) [709][55/63] lr: 1.5831e-03 eta: 6:20:20 time: 0.5209 data_time: 0.0203 memory: 16131 loss: 1.1175 loss_prob: 0.5919 loss_thr: 0.4215 loss_db: 0.1041 2022/10/26 04:41:05 - mmengine - INFO - Epoch(train) [709][60/63] lr: 1.5831e-03 eta: 6:20:11 time: 0.4983 data_time: 0.0043 memory: 16131 loss: 1.1849 loss_prob: 0.6230 loss_thr: 0.4535 loss_db: 0.1084 2022/10/26 04:41:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:41:11 - mmengine - INFO - Epoch(train) [710][5/63] lr: 1.5802e-03 eta: 6:20:11 time: 0.7579 data_time: 0.2388 memory: 16131 loss: 1.1951 loss_prob: 0.6473 loss_thr: 0.4381 loss_db: 0.1096 2022/10/26 04:41:14 - mmengine - INFO - Epoch(train) [710][10/63] lr: 1.5802e-03 eta: 6:20:00 time: 0.8091 data_time: 0.2364 memory: 16131 loss: 1.1777 loss_prob: 0.6381 loss_thr: 0.4308 loss_db: 0.1088 2022/10/26 04:41:16 - mmengine - INFO - Epoch(train) [710][15/63] lr: 1.5802e-03 eta: 6:20:00 time: 0.5155 data_time: 0.0065 memory: 16131 loss: 1.1723 loss_prob: 0.6366 loss_thr: 0.4266 loss_db: 0.1091 2022/10/26 04:41:19 - mmengine - INFO - Epoch(train) [710][20/63] lr: 1.5802e-03 eta: 6:19:51 time: 0.4974 data_time: 0.0080 memory: 16131 loss: 1.1363 loss_prob: 0.6091 loss_thr: 0.4236 loss_db: 0.1037 2022/10/26 04:41:21 - mmengine - INFO - Epoch(train) [710][25/63] lr: 1.5802e-03 eta: 6:19:51 time: 0.5045 data_time: 0.0121 memory: 16131 loss: 1.0795 loss_prob: 0.5658 loss_thr: 0.4172 loss_db: 0.0965 2022/10/26 04:41:24 - mmengine - INFO - Epoch(train) [710][30/63] lr: 1.5802e-03 eta: 6:19:42 time: 0.5478 data_time: 0.0355 memory: 16131 loss: 1.0106 loss_prob: 0.5263 loss_thr: 0.3947 loss_db: 0.0897 2022/10/26 04:41:27 - mmengine - INFO - Epoch(train) [710][35/63] lr: 1.5802e-03 eta: 6:19:42 time: 0.5447 data_time: 0.0293 memory: 16131 loss: 1.0436 loss_prob: 0.5408 loss_thr: 0.4096 loss_db: 0.0933 2022/10/26 04:41:30 - mmengine - INFO - Epoch(train) [710][40/63] lr: 1.5802e-03 eta: 6:19:34 time: 0.5269 data_time: 0.0044 memory: 16131 loss: 1.1463 loss_prob: 0.6029 loss_thr: 0.4413 loss_db: 0.1021 2022/10/26 04:41:33 - mmengine - INFO - Epoch(train) [710][45/63] lr: 1.5802e-03 eta: 6:19:34 time: 0.5994 data_time: 0.0055 memory: 16131 loss: 1.1347 loss_prob: 0.6009 loss_thr: 0.4316 loss_db: 0.1022 2022/10/26 04:41:35 - mmengine - INFO - Epoch(train) [710][50/63] lr: 1.5802e-03 eta: 6:19:25 time: 0.5860 data_time: 0.0193 memory: 16131 loss: 1.0982 loss_prob: 0.5790 loss_thr: 0.4179 loss_db: 0.1013 2022/10/26 04:41:38 - mmengine - INFO - Epoch(train) [710][55/63] lr: 1.5802e-03 eta: 6:19:25 time: 0.5172 data_time: 0.0248 memory: 16131 loss: 1.1811 loss_prob: 0.6407 loss_thr: 0.4313 loss_db: 0.1092 2022/10/26 04:41:41 - mmengine - INFO - Epoch(train) [710][60/63] lr: 1.5802e-03 eta: 6:19:16 time: 0.5434 data_time: 0.0126 memory: 16131 loss: 1.2682 loss_prob: 0.6985 loss_thr: 0.4522 loss_db: 0.1176 2022/10/26 04:41:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:41:48 - mmengine - INFO - Epoch(train) [711][5/63] lr: 1.5773e-03 eta: 6:19:16 time: 0.8088 data_time: 0.2135 memory: 16131 loss: 1.1950 loss_prob: 0.6443 loss_thr: 0.4423 loss_db: 0.1084 2022/10/26 04:41:50 - mmengine - INFO - Epoch(train) [711][10/63] lr: 1.5773e-03 eta: 6:19:06 time: 0.8260 data_time: 0.2127 memory: 16131 loss: 1.1513 loss_prob: 0.6120 loss_thr: 0.4341 loss_db: 0.1052 2022/10/26 04:41:53 - mmengine - INFO - Epoch(train) [711][15/63] lr: 1.5773e-03 eta: 6:19:06 time: 0.5143 data_time: 0.0052 memory: 16131 loss: 1.1682 loss_prob: 0.6251 loss_thr: 0.4351 loss_db: 0.1080 2022/10/26 04:41:55 - mmengine - INFO - Epoch(train) [711][20/63] lr: 1.5773e-03 eta: 6:18:57 time: 0.5012 data_time: 0.0063 memory: 16131 loss: 1.1862 loss_prob: 0.6483 loss_thr: 0.4299 loss_db: 0.1080 2022/10/26 04:41:58 - mmengine - INFO - Epoch(train) [711][25/63] lr: 1.5773e-03 eta: 6:18:57 time: 0.5323 data_time: 0.0071 memory: 16131 loss: 1.3127 loss_prob: 0.7414 loss_thr: 0.4551 loss_db: 0.1162 2022/10/26 04:42:01 - mmengine - INFO - Epoch(train) [711][30/63] lr: 1.5773e-03 eta: 6:18:48 time: 0.5592 data_time: 0.0356 memory: 16131 loss: 1.3696 loss_prob: 0.7842 loss_thr: 0.4658 loss_db: 0.1196 2022/10/26 04:42:03 - mmengine - INFO - Epoch(train) [711][35/63] lr: 1.5773e-03 eta: 6:18:48 time: 0.5265 data_time: 0.0346 memory: 16131 loss: 1.1743 loss_prob: 0.6408 loss_thr: 0.4292 loss_db: 0.1044 2022/10/26 04:42:06 - mmengine - INFO - Epoch(train) [711][40/63] lr: 1.5773e-03 eta: 6:18:39 time: 0.5253 data_time: 0.0050 memory: 16131 loss: 1.1186 loss_prob: 0.5957 loss_thr: 0.4198 loss_db: 0.1031 2022/10/26 04:42:09 - mmengine - INFO - Epoch(train) [711][45/63] lr: 1.5773e-03 eta: 6:18:39 time: 0.5494 data_time: 0.0049 memory: 16131 loss: 1.1892 loss_prob: 0.6416 loss_thr: 0.4390 loss_db: 0.1086 2022/10/26 04:42:12 - mmengine - INFO - Epoch(train) [711][50/63] lr: 1.5773e-03 eta: 6:18:31 time: 0.5268 data_time: 0.0228 memory: 16131 loss: 1.2012 loss_prob: 0.6450 loss_thr: 0.4460 loss_db: 0.1101 2022/10/26 04:42:14 - mmengine - INFO - Epoch(train) [711][55/63] lr: 1.5773e-03 eta: 6:18:31 time: 0.5242 data_time: 0.0293 memory: 16131 loss: 1.1430 loss_prob: 0.6120 loss_thr: 0.4251 loss_db: 0.1060 2022/10/26 04:42:17 - mmengine - INFO - Epoch(train) [711][60/63] lr: 1.5773e-03 eta: 6:18:22 time: 0.5199 data_time: 0.0107 memory: 16131 loss: 1.1310 loss_prob: 0.6025 loss_thr: 0.4256 loss_db: 0.1029 2022/10/26 04:42:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:42:23 - mmengine - INFO - Epoch(train) [712][5/63] lr: 1.5744e-03 eta: 6:18:22 time: 0.7212 data_time: 0.1964 memory: 16131 loss: 1.1852 loss_prob: 0.6387 loss_thr: 0.4362 loss_db: 0.1103 2022/10/26 04:42:26 - mmengine - INFO - Epoch(train) [712][10/63] lr: 1.5744e-03 eta: 6:18:11 time: 0.7836 data_time: 0.1945 memory: 16131 loss: 1.1658 loss_prob: 0.6355 loss_thr: 0.4246 loss_db: 0.1058 2022/10/26 04:42:29 - mmengine - INFO - Epoch(train) [712][15/63] lr: 1.5744e-03 eta: 6:18:11 time: 0.5637 data_time: 0.0054 memory: 16131 loss: 1.0891 loss_prob: 0.5814 loss_thr: 0.4106 loss_db: 0.0971 2022/10/26 04:42:31 - mmengine - INFO - Epoch(train) [712][20/63] lr: 1.5744e-03 eta: 6:18:02 time: 0.5282 data_time: 0.0078 memory: 16131 loss: 1.1009 loss_prob: 0.5831 loss_thr: 0.4150 loss_db: 0.1029 2022/10/26 04:42:34 - mmengine - INFO - Epoch(train) [712][25/63] lr: 1.5744e-03 eta: 6:18:02 time: 0.5457 data_time: 0.0358 memory: 16131 loss: 1.1347 loss_prob: 0.6095 loss_thr: 0.4195 loss_db: 0.1057 2022/10/26 04:42:37 - mmengine - INFO - Epoch(train) [712][30/63] lr: 1.5744e-03 eta: 6:17:53 time: 0.5302 data_time: 0.0326 memory: 16131 loss: 1.1131 loss_prob: 0.6004 loss_thr: 0.4098 loss_db: 0.1029 2022/10/26 04:42:39 - mmengine - INFO - Epoch(train) [712][35/63] lr: 1.5744e-03 eta: 6:17:53 time: 0.5070 data_time: 0.0063 memory: 16131 loss: 1.1596 loss_prob: 0.6173 loss_thr: 0.4366 loss_db: 0.1057 2022/10/26 04:42:41 - mmengine - INFO - Epoch(train) [712][40/63] lr: 1.5744e-03 eta: 6:17:44 time: 0.4933 data_time: 0.0076 memory: 16131 loss: 1.2760 loss_prob: 0.6835 loss_thr: 0.4781 loss_db: 0.1144 2022/10/26 04:42:44 - mmengine - INFO - Epoch(train) [712][45/63] lr: 1.5744e-03 eta: 6:17:44 time: 0.5225 data_time: 0.0093 memory: 16131 loss: 1.2615 loss_prob: 0.6781 loss_thr: 0.4720 loss_db: 0.1114 2022/10/26 04:42:47 - mmengine - INFO - Epoch(train) [712][50/63] lr: 1.5744e-03 eta: 6:17:36 time: 0.5356 data_time: 0.0269 memory: 16131 loss: 1.2373 loss_prob: 0.6677 loss_thr: 0.4564 loss_db: 0.1132 2022/10/26 04:42:49 - mmengine - INFO - Epoch(train) [712][55/63] lr: 1.5744e-03 eta: 6:17:36 time: 0.5095 data_time: 0.0231 memory: 16131 loss: 1.1906 loss_prob: 0.6426 loss_thr: 0.4378 loss_db: 0.1101 2022/10/26 04:42:52 - mmengine - INFO - Epoch(train) [712][60/63] lr: 1.5744e-03 eta: 6:17:27 time: 0.5038 data_time: 0.0084 memory: 16131 loss: 1.0912 loss_prob: 0.5839 loss_thr: 0.4076 loss_db: 0.0997 2022/10/26 04:42:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:42:58 - mmengine - INFO - Epoch(train) [713][5/63] lr: 1.5715e-03 eta: 6:17:27 time: 0.7254 data_time: 0.1943 memory: 16131 loss: 1.0859 loss_prob: 0.5760 loss_thr: 0.4104 loss_db: 0.0994 2022/10/26 04:43:01 - mmengine - INFO - Epoch(train) [713][10/63] lr: 1.5715e-03 eta: 6:17:16 time: 0.7558 data_time: 0.1937 memory: 16131 loss: 1.1974 loss_prob: 0.6390 loss_thr: 0.4489 loss_db: 0.1095 2022/10/26 04:43:03 - mmengine - INFO - Epoch(train) [713][15/63] lr: 1.5715e-03 eta: 6:17:16 time: 0.5345 data_time: 0.0140 memory: 16131 loss: 1.2715 loss_prob: 0.6913 loss_thr: 0.4634 loss_db: 0.1168 2022/10/26 04:43:06 - mmengine - INFO - Epoch(train) [713][20/63] lr: 1.5715e-03 eta: 6:17:07 time: 0.5513 data_time: 0.0138 memory: 16131 loss: 1.1710 loss_prob: 0.6287 loss_thr: 0.4354 loss_db: 0.1069 2022/10/26 04:43:09 - mmengine - INFO - Epoch(train) [713][25/63] lr: 1.5715e-03 eta: 6:17:07 time: 0.5593 data_time: 0.0202 memory: 16131 loss: 1.1868 loss_prob: 0.6319 loss_thr: 0.4460 loss_db: 0.1090 2022/10/26 04:43:12 - mmengine - INFO - Epoch(train) [713][30/63] lr: 1.5715e-03 eta: 6:16:59 time: 0.5768 data_time: 0.0276 memory: 16131 loss: 1.1833 loss_prob: 0.6369 loss_thr: 0.4359 loss_db: 0.1105 2022/10/26 04:43:14 - mmengine - INFO - Epoch(train) [713][35/63] lr: 1.5715e-03 eta: 6:16:59 time: 0.5452 data_time: 0.0186 memory: 16131 loss: 1.0666 loss_prob: 0.5698 loss_thr: 0.3991 loss_db: 0.0977 2022/10/26 04:43:18 - mmengine - INFO - Epoch(train) [713][40/63] lr: 1.5715e-03 eta: 6:16:50 time: 0.6192 data_time: 0.0153 memory: 16131 loss: 1.2287 loss_prob: 0.6849 loss_thr: 0.4326 loss_db: 0.1112 2022/10/26 04:43:21 - mmengine - INFO - Epoch(train) [713][45/63] lr: 1.5715e-03 eta: 6:16:50 time: 0.6265 data_time: 0.0140 memory: 16131 loss: 1.4079 loss_prob: 0.7823 loss_thr: 0.4955 loss_db: 0.1301 2022/10/26 04:43:23 - mmengine - INFO - Epoch(train) [713][50/63] lr: 1.5715e-03 eta: 6:16:42 time: 0.5236 data_time: 0.0210 memory: 16131 loss: 1.2659 loss_prob: 0.6680 loss_thr: 0.4818 loss_db: 0.1161 2022/10/26 04:43:26 - mmengine - INFO - Epoch(train) [713][55/63] lr: 1.5715e-03 eta: 6:16:42 time: 0.5045 data_time: 0.0232 memory: 16131 loss: 1.1373 loss_prob: 0.5986 loss_thr: 0.4357 loss_db: 0.1030 2022/10/26 04:43:29 - mmengine - INFO - Epoch(train) [713][60/63] lr: 1.5715e-03 eta: 6:16:33 time: 0.5189 data_time: 0.0097 memory: 16131 loss: 1.1292 loss_prob: 0.5884 loss_thr: 0.4386 loss_db: 0.1022 2022/10/26 04:43:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:43:34 - mmengine - INFO - Epoch(train) [714][5/63] lr: 1.5685e-03 eta: 6:16:33 time: 0.6415 data_time: 0.1536 memory: 16131 loss: 1.2882 loss_prob: 0.7080 loss_thr: 0.4614 loss_db: 0.1188 2022/10/26 04:43:37 - mmengine - INFO - Epoch(train) [714][10/63] lr: 1.5685e-03 eta: 6:16:22 time: 0.7074 data_time: 0.1656 memory: 16131 loss: 1.2417 loss_prob: 0.6751 loss_thr: 0.4535 loss_db: 0.1131 2022/10/26 04:43:40 - mmengine - INFO - Epoch(train) [714][15/63] lr: 1.5685e-03 eta: 6:16:22 time: 0.5832 data_time: 0.0209 memory: 16131 loss: 1.1606 loss_prob: 0.6129 loss_thr: 0.4431 loss_db: 0.1046 2022/10/26 04:43:43 - mmengine - INFO - Epoch(train) [714][20/63] lr: 1.5685e-03 eta: 6:16:13 time: 0.5727 data_time: 0.0072 memory: 16131 loss: 1.2360 loss_prob: 0.6658 loss_thr: 0.4564 loss_db: 0.1138 2022/10/26 04:43:45 - mmengine - INFO - Epoch(train) [714][25/63] lr: 1.5685e-03 eta: 6:16:13 time: 0.5414 data_time: 0.0095 memory: 16131 loss: 1.1918 loss_prob: 0.6375 loss_thr: 0.4455 loss_db: 0.1088 2022/10/26 04:43:48 - mmengine - INFO - Epoch(train) [714][30/63] lr: 1.5685e-03 eta: 6:16:04 time: 0.5177 data_time: 0.0188 memory: 16131 loss: 1.0947 loss_prob: 0.5770 loss_thr: 0.4174 loss_db: 0.1003 2022/10/26 04:43:50 - mmengine - INFO - Epoch(train) [714][35/63] lr: 1.5685e-03 eta: 6:16:04 time: 0.5354 data_time: 0.0301 memory: 16131 loss: 1.1425 loss_prob: 0.6049 loss_thr: 0.4328 loss_db: 0.1048 2022/10/26 04:43:53 - mmengine - INFO - Epoch(train) [714][40/63] lr: 1.5685e-03 eta: 6:15:55 time: 0.5284 data_time: 0.0192 memory: 16131 loss: 1.2139 loss_prob: 0.6489 loss_thr: 0.4549 loss_db: 0.1101 2022/10/26 04:43:55 - mmengine - INFO - Epoch(train) [714][45/63] lr: 1.5685e-03 eta: 6:15:55 time: 0.4875 data_time: 0.0042 memory: 16131 loss: 1.1913 loss_prob: 0.6451 loss_thr: 0.4367 loss_db: 0.1095 2022/10/26 04:43:58 - mmengine - INFO - Epoch(train) [714][50/63] lr: 1.5685e-03 eta: 6:15:46 time: 0.4866 data_time: 0.0070 memory: 16131 loss: 1.2989 loss_prob: 0.7133 loss_thr: 0.4657 loss_db: 0.1199 2022/10/26 04:44:01 - mmengine - INFO - Epoch(train) [714][55/63] lr: 1.5685e-03 eta: 6:15:46 time: 0.5257 data_time: 0.0196 memory: 16131 loss: 1.2114 loss_prob: 0.6488 loss_thr: 0.4518 loss_db: 0.1108 2022/10/26 04:44:03 - mmengine - INFO - Epoch(train) [714][60/63] lr: 1.5685e-03 eta: 6:15:38 time: 0.5187 data_time: 0.0218 memory: 16131 loss: 1.0958 loss_prob: 0.5710 loss_thr: 0.4258 loss_db: 0.0989 2022/10/26 04:44:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:44:09 - mmengine - INFO - Epoch(train) [715][5/63] lr: 1.5656e-03 eta: 6:15:38 time: 0.6760 data_time: 0.1949 memory: 16131 loss: 1.1525 loss_prob: 0.6084 loss_thr: 0.4407 loss_db: 0.1035 2022/10/26 04:44:12 - mmengine - INFO - Epoch(train) [715][10/63] lr: 1.5656e-03 eta: 6:15:26 time: 0.7199 data_time: 0.1948 memory: 16131 loss: 1.1098 loss_prob: 0.5905 loss_thr: 0.4188 loss_db: 0.1005 2022/10/26 04:44:14 - mmengine - INFO - Epoch(train) [715][15/63] lr: 1.5656e-03 eta: 6:15:26 time: 0.5100 data_time: 0.0072 memory: 16131 loss: 1.1687 loss_prob: 0.6312 loss_thr: 0.4320 loss_db: 0.1056 2022/10/26 04:44:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:44:16 - mmengine - INFO - Epoch(train) [715][20/63] lr: 1.5656e-03 eta: 6:15:17 time: 0.4766 data_time: 0.0068 memory: 16131 loss: 1.1839 loss_prob: 0.6382 loss_thr: 0.4365 loss_db: 0.1092 2022/10/26 04:44:19 - mmengine - INFO - Epoch(train) [715][25/63] lr: 1.5656e-03 eta: 6:15:17 time: 0.5082 data_time: 0.0272 memory: 16131 loss: 1.2098 loss_prob: 0.6527 loss_thr: 0.4441 loss_db: 0.1130 2022/10/26 04:44:22 - mmengine - INFO - Epoch(train) [715][30/63] lr: 1.5656e-03 eta: 6:15:08 time: 0.5194 data_time: 0.0319 memory: 16131 loss: 1.2571 loss_prob: 0.6745 loss_thr: 0.4669 loss_db: 0.1157 2022/10/26 04:44:24 - mmengine - INFO - Epoch(train) [715][35/63] lr: 1.5656e-03 eta: 6:15:08 time: 0.5011 data_time: 0.0118 memory: 16131 loss: 1.0968 loss_prob: 0.5609 loss_thr: 0.4372 loss_db: 0.0986 2022/10/26 04:44:26 - mmengine - INFO - Epoch(train) [715][40/63] lr: 1.5656e-03 eta: 6:14:59 time: 0.4816 data_time: 0.0055 memory: 16131 loss: 1.0986 loss_prob: 0.5715 loss_thr: 0.4289 loss_db: 0.0981 2022/10/26 04:44:29 - mmengine - INFO - Epoch(train) [715][45/63] lr: 1.5656e-03 eta: 6:14:59 time: 0.4784 data_time: 0.0060 memory: 16131 loss: 1.2012 loss_prob: 0.6496 loss_thr: 0.4416 loss_db: 0.1101 2022/10/26 04:44:31 - mmengine - INFO - Epoch(train) [715][50/63] lr: 1.5656e-03 eta: 6:14:50 time: 0.4996 data_time: 0.0191 memory: 16131 loss: 1.1919 loss_prob: 0.6384 loss_thr: 0.4433 loss_db: 0.1102 2022/10/26 04:44:34 - mmengine - INFO - Epoch(train) [715][55/63] lr: 1.5656e-03 eta: 6:14:50 time: 0.5117 data_time: 0.0223 memory: 16131 loss: 1.1459 loss_prob: 0.6102 loss_thr: 0.4291 loss_db: 0.1067 2022/10/26 04:44:37 - mmengine - INFO - Epoch(train) [715][60/63] lr: 1.5656e-03 eta: 6:14:42 time: 0.5390 data_time: 0.0090 memory: 16131 loss: 1.1118 loss_prob: 0.5904 loss_thr: 0.4174 loss_db: 0.1039 2022/10/26 04:44:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:44:43 - mmengine - INFO - Epoch(train) [716][5/63] lr: 1.5627e-03 eta: 6:14:42 time: 0.6977 data_time: 0.1686 memory: 16131 loss: 1.1364 loss_prob: 0.6047 loss_thr: 0.4302 loss_db: 0.1015 2022/10/26 04:44:45 - mmengine - INFO - Epoch(train) [716][10/63] lr: 1.5627e-03 eta: 6:14:30 time: 0.7038 data_time: 0.1739 memory: 16131 loss: 1.1327 loss_prob: 0.6022 loss_thr: 0.4284 loss_db: 0.1021 2022/10/26 04:44:48 - mmengine - INFO - Epoch(train) [716][15/63] lr: 1.5627e-03 eta: 6:14:30 time: 0.5175 data_time: 0.0144 memory: 16131 loss: 1.1218 loss_prob: 0.5951 loss_thr: 0.4245 loss_db: 0.1023 2022/10/26 04:44:50 - mmengine - INFO - Epoch(train) [716][20/63] lr: 1.5627e-03 eta: 6:14:22 time: 0.5132 data_time: 0.0089 memory: 16131 loss: 1.2398 loss_prob: 0.6690 loss_thr: 0.4580 loss_db: 0.1128 2022/10/26 04:44:53 - mmengine - INFO - Epoch(train) [716][25/63] lr: 1.5627e-03 eta: 6:14:22 time: 0.5482 data_time: 0.0188 memory: 16131 loss: 1.1963 loss_prob: 0.6461 loss_thr: 0.4402 loss_db: 0.1100 2022/10/26 04:44:56 - mmengine - INFO - Epoch(train) [716][30/63] lr: 1.5627e-03 eta: 6:14:13 time: 0.5435 data_time: 0.0219 memory: 16131 loss: 1.1011 loss_prob: 0.5840 loss_thr: 0.4153 loss_db: 0.1019 2022/10/26 04:44:58 - mmengine - INFO - Epoch(train) [716][35/63] lr: 1.5627e-03 eta: 6:14:13 time: 0.5156 data_time: 0.0195 memory: 16131 loss: 1.0868 loss_prob: 0.5707 loss_thr: 0.4158 loss_db: 0.1003 2022/10/26 04:45:01 - mmengine - INFO - Epoch(train) [716][40/63] lr: 1.5627e-03 eta: 6:14:04 time: 0.5215 data_time: 0.0200 memory: 16131 loss: 1.0764 loss_prob: 0.5661 loss_thr: 0.4119 loss_db: 0.0984 2022/10/26 04:45:04 - mmengine - INFO - Epoch(train) [716][45/63] lr: 1.5627e-03 eta: 6:14:04 time: 0.5317 data_time: 0.0101 memory: 16131 loss: 1.1214 loss_prob: 0.5947 loss_thr: 0.4253 loss_db: 0.1014 2022/10/26 04:45:06 - mmengine - INFO - Epoch(train) [716][50/63] lr: 1.5627e-03 eta: 6:13:55 time: 0.5356 data_time: 0.0147 memory: 16131 loss: 1.2997 loss_prob: 0.7181 loss_thr: 0.4647 loss_db: 0.1169 2022/10/26 04:45:09 - mmengine - INFO - Epoch(train) [716][55/63] lr: 1.5627e-03 eta: 6:13:55 time: 0.4935 data_time: 0.0164 memory: 16131 loss: 1.3186 loss_prob: 0.7272 loss_thr: 0.4722 loss_db: 0.1192 2022/10/26 04:45:12 - mmengine - INFO - Epoch(train) [716][60/63] lr: 1.5627e-03 eta: 6:13:47 time: 0.5293 data_time: 0.0126 memory: 16131 loss: 1.1843 loss_prob: 0.6402 loss_thr: 0.4366 loss_db: 0.1075 2022/10/26 04:45:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:45:18 - mmengine - INFO - Epoch(train) [717][5/63] lr: 1.5598e-03 eta: 6:13:47 time: 0.7367 data_time: 0.1888 memory: 16131 loss: 1.2802 loss_prob: 0.7146 loss_thr: 0.4426 loss_db: 0.1229 2022/10/26 04:45:20 - mmengine - INFO - Epoch(train) [717][10/63] lr: 1.5598e-03 eta: 6:13:35 time: 0.7104 data_time: 0.1885 memory: 16131 loss: 1.2550 loss_prob: 0.7004 loss_thr: 0.4346 loss_db: 0.1200 2022/10/26 04:45:23 - mmengine - INFO - Epoch(train) [717][15/63] lr: 1.5598e-03 eta: 6:13:35 time: 0.5241 data_time: 0.0061 memory: 16131 loss: 1.1436 loss_prob: 0.6244 loss_thr: 0.4168 loss_db: 0.1025 2022/10/26 04:45:25 - mmengine - INFO - Epoch(train) [717][20/63] lr: 1.5598e-03 eta: 6:13:27 time: 0.5203 data_time: 0.0087 memory: 16131 loss: 1.1068 loss_prob: 0.5878 loss_thr: 0.4176 loss_db: 0.1015 2022/10/26 04:45:28 - mmengine - INFO - Epoch(train) [717][25/63] lr: 1.5598e-03 eta: 6:13:27 time: 0.5604 data_time: 0.0290 memory: 16131 loss: 1.2069 loss_prob: 0.6378 loss_thr: 0.4571 loss_db: 0.1120 2022/10/26 04:45:31 - mmengine - INFO - Epoch(train) [717][30/63] lr: 1.5598e-03 eta: 6:13:18 time: 0.5660 data_time: 0.0330 memory: 16131 loss: 1.2216 loss_prob: 0.6507 loss_thr: 0.4597 loss_db: 0.1113 2022/10/26 04:45:34 - mmengine - INFO - Epoch(train) [717][35/63] lr: 1.5598e-03 eta: 6:13:18 time: 0.5295 data_time: 0.0176 memory: 16131 loss: 1.1786 loss_prob: 0.6301 loss_thr: 0.4389 loss_db: 0.1095 2022/10/26 04:45:36 - mmengine - INFO - Epoch(train) [717][40/63] lr: 1.5598e-03 eta: 6:13:09 time: 0.5153 data_time: 0.0106 memory: 16131 loss: 1.2017 loss_prob: 0.6453 loss_thr: 0.4452 loss_db: 0.1113 2022/10/26 04:45:39 - mmengine - INFO - Epoch(train) [717][45/63] lr: 1.5598e-03 eta: 6:13:09 time: 0.5272 data_time: 0.0081 memory: 16131 loss: 1.1975 loss_prob: 0.6437 loss_thr: 0.4462 loss_db: 0.1076 2022/10/26 04:45:42 - mmengine - INFO - Epoch(train) [717][50/63] lr: 1.5598e-03 eta: 6:13:01 time: 0.5760 data_time: 0.0343 memory: 16131 loss: 1.1477 loss_prob: 0.6230 loss_thr: 0.4200 loss_db: 0.1046 2022/10/26 04:45:45 - mmengine - INFO - Epoch(train) [717][55/63] lr: 1.5598e-03 eta: 6:13:01 time: 0.5778 data_time: 0.0365 memory: 16131 loss: 1.1159 loss_prob: 0.5978 loss_thr: 0.4149 loss_db: 0.1032 2022/10/26 04:45:47 - mmengine - INFO - Epoch(train) [717][60/63] lr: 1.5598e-03 eta: 6:12:52 time: 0.5628 data_time: 0.0135 memory: 16131 loss: 1.1618 loss_prob: 0.6197 loss_thr: 0.4342 loss_db: 0.1079 2022/10/26 04:45:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:45:54 - mmengine - INFO - Epoch(train) [718][5/63] lr: 1.5569e-03 eta: 6:12:52 time: 0.7152 data_time: 0.2195 memory: 16131 loss: 1.1160 loss_prob: 0.6001 loss_thr: 0.4132 loss_db: 0.1027 2022/10/26 04:45:56 - mmengine - INFO - Epoch(train) [718][10/63] lr: 1.5569e-03 eta: 6:12:41 time: 0.7167 data_time: 0.2177 memory: 16131 loss: 1.0556 loss_prob: 0.5612 loss_thr: 0.3992 loss_db: 0.0952 2022/10/26 04:45:59 - mmengine - INFO - Epoch(train) [718][15/63] lr: 1.5569e-03 eta: 6:12:41 time: 0.4987 data_time: 0.0050 memory: 16131 loss: 1.0965 loss_prob: 0.5791 loss_thr: 0.4193 loss_db: 0.0981 2022/10/26 04:46:01 - mmengine - INFO - Epoch(train) [718][20/63] lr: 1.5569e-03 eta: 6:12:32 time: 0.5052 data_time: 0.0063 memory: 16131 loss: 1.1291 loss_prob: 0.5971 loss_thr: 0.4286 loss_db: 0.1034 2022/10/26 04:46:04 - mmengine - INFO - Epoch(train) [718][25/63] lr: 1.5569e-03 eta: 6:12:32 time: 0.5381 data_time: 0.0303 memory: 16131 loss: 1.1836 loss_prob: 0.6318 loss_thr: 0.4386 loss_db: 0.1132 2022/10/26 04:46:07 - mmengine - INFO - Epoch(train) [718][30/63] lr: 1.5569e-03 eta: 6:12:24 time: 0.5421 data_time: 0.0351 memory: 16131 loss: 1.1594 loss_prob: 0.6205 loss_thr: 0.4296 loss_db: 0.1093 2022/10/26 04:46:09 - mmengine - INFO - Epoch(train) [718][35/63] lr: 1.5569e-03 eta: 6:12:24 time: 0.4905 data_time: 0.0107 memory: 16131 loss: 1.1197 loss_prob: 0.6122 loss_thr: 0.4040 loss_db: 0.1035 2022/10/26 04:46:11 - mmengine - INFO - Epoch(train) [718][40/63] lr: 1.5569e-03 eta: 6:12:15 time: 0.4812 data_time: 0.0044 memory: 16131 loss: 1.2360 loss_prob: 0.6835 loss_thr: 0.4383 loss_db: 0.1142 2022/10/26 04:46:14 - mmengine - INFO - Epoch(train) [718][45/63] lr: 1.5569e-03 eta: 6:12:15 time: 0.4830 data_time: 0.0047 memory: 16131 loss: 1.2634 loss_prob: 0.6844 loss_thr: 0.4634 loss_db: 0.1156 2022/10/26 04:46:17 - mmengine - INFO - Epoch(train) [718][50/63] lr: 1.5569e-03 eta: 6:12:06 time: 0.5344 data_time: 0.0187 memory: 16131 loss: 1.2804 loss_prob: 0.6967 loss_thr: 0.4663 loss_db: 0.1174 2022/10/26 04:46:20 - mmengine - INFO - Epoch(train) [718][55/63] lr: 1.5569e-03 eta: 6:12:06 time: 0.5944 data_time: 0.0235 memory: 16131 loss: 1.2817 loss_prob: 0.6977 loss_thr: 0.4674 loss_db: 0.1165 2022/10/26 04:46:23 - mmengine - INFO - Epoch(train) [718][60/63] lr: 1.5569e-03 eta: 6:11:58 time: 0.5910 data_time: 0.0110 memory: 16131 loss: 1.1838 loss_prob: 0.6324 loss_thr: 0.4436 loss_db: 0.1077 2022/10/26 04:46:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:46:30 - mmengine - INFO - Epoch(train) [719][5/63] lr: 1.5540e-03 eta: 6:11:58 time: 0.7964 data_time: 0.2140 memory: 16131 loss: 1.1899 loss_prob: 0.6452 loss_thr: 0.4340 loss_db: 0.1106 2022/10/26 04:46:32 - mmengine - INFO - Epoch(train) [719][10/63] lr: 1.5540e-03 eta: 6:11:47 time: 0.8365 data_time: 0.2265 memory: 16131 loss: 1.1872 loss_prob: 0.6504 loss_thr: 0.4256 loss_db: 0.1112 2022/10/26 04:46:35 - mmengine - INFO - Epoch(train) [719][15/63] lr: 1.5540e-03 eta: 6:11:47 time: 0.5506 data_time: 0.0194 memory: 16131 loss: 1.1402 loss_prob: 0.6132 loss_thr: 0.4201 loss_db: 0.1069 2022/10/26 04:46:38 - mmengine - INFO - Epoch(train) [719][20/63] lr: 1.5540e-03 eta: 6:11:38 time: 0.5266 data_time: 0.0071 memory: 16131 loss: 1.1078 loss_prob: 0.5853 loss_thr: 0.4193 loss_db: 0.1031 2022/10/26 04:46:40 - mmengine - INFO - Epoch(train) [719][25/63] lr: 1.5540e-03 eta: 6:11:38 time: 0.5309 data_time: 0.0242 memory: 16131 loss: 1.1764 loss_prob: 0.6365 loss_thr: 0.4312 loss_db: 0.1086 2022/10/26 04:46:43 - mmengine - INFO - Epoch(train) [719][30/63] lr: 1.5540e-03 eta: 6:11:30 time: 0.5644 data_time: 0.0344 memory: 16131 loss: 1.2436 loss_prob: 0.6678 loss_thr: 0.4612 loss_db: 0.1147 2022/10/26 04:46:46 - mmengine - INFO - Epoch(train) [719][35/63] lr: 1.5540e-03 eta: 6:11:30 time: 0.5520 data_time: 0.0171 memory: 16131 loss: 1.1578 loss_prob: 0.6089 loss_thr: 0.4417 loss_db: 0.1072 2022/10/26 04:46:49 - mmengine - INFO - Epoch(train) [719][40/63] lr: 1.5540e-03 eta: 6:11:21 time: 0.5287 data_time: 0.0095 memory: 16131 loss: 1.1407 loss_prob: 0.6085 loss_thr: 0.4268 loss_db: 0.1055 2022/10/26 04:46:51 - mmengine - INFO - Epoch(train) [719][45/63] lr: 1.5540e-03 eta: 6:11:21 time: 0.5217 data_time: 0.0100 memory: 16131 loss: 1.1855 loss_prob: 0.6308 loss_thr: 0.4474 loss_db: 0.1073 2022/10/26 04:46:54 - mmengine - INFO - Epoch(train) [719][50/63] lr: 1.5540e-03 eta: 6:11:12 time: 0.5126 data_time: 0.0187 memory: 16131 loss: 1.1808 loss_prob: 0.6278 loss_thr: 0.4443 loss_db: 0.1087 2022/10/26 04:46:56 - mmengine - INFO - Epoch(train) [719][55/63] lr: 1.5540e-03 eta: 6:11:12 time: 0.5142 data_time: 0.0223 memory: 16131 loss: 1.1048 loss_prob: 0.5876 loss_thr: 0.4150 loss_db: 0.1023 2022/10/26 04:46:59 - mmengine - INFO - Epoch(train) [719][60/63] lr: 1.5540e-03 eta: 6:11:03 time: 0.5057 data_time: 0.0126 memory: 16131 loss: 1.0691 loss_prob: 0.5726 loss_thr: 0.3991 loss_db: 0.0974 2022/10/26 04:47:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:47:05 - mmengine - INFO - Epoch(train) [720][5/63] lr: 1.5511e-03 eta: 6:11:03 time: 0.7534 data_time: 0.2201 memory: 16131 loss: 1.3133 loss_prob: 0.7375 loss_thr: 0.4576 loss_db: 0.1182 2022/10/26 04:47:08 - mmengine - INFO - Epoch(train) [720][10/63] lr: 1.5511e-03 eta: 6:10:53 time: 0.8020 data_time: 0.2183 memory: 16131 loss: 1.2387 loss_prob: 0.6735 loss_thr: 0.4548 loss_db: 0.1104 2022/10/26 04:47:11 - mmengine - INFO - Epoch(train) [720][15/63] lr: 1.5511e-03 eta: 6:10:53 time: 0.5430 data_time: 0.0094 memory: 16131 loss: 1.1919 loss_prob: 0.6343 loss_thr: 0.4486 loss_db: 0.1090 2022/10/26 04:47:13 - mmengine - INFO - Epoch(train) [720][20/63] lr: 1.5511e-03 eta: 6:10:44 time: 0.5144 data_time: 0.0086 memory: 16131 loss: 1.1748 loss_prob: 0.6336 loss_thr: 0.4349 loss_db: 0.1063 2022/10/26 04:47:16 - mmengine - INFO - Epoch(train) [720][25/63] lr: 1.5511e-03 eta: 6:10:44 time: 0.5189 data_time: 0.0082 memory: 16131 loss: 1.2030 loss_prob: 0.6476 loss_thr: 0.4471 loss_db: 0.1083 2022/10/26 04:47:19 - mmengine - INFO - Epoch(train) [720][30/63] lr: 1.5511e-03 eta: 6:10:35 time: 0.5469 data_time: 0.0300 memory: 16131 loss: 1.2683 loss_prob: 0.6768 loss_thr: 0.4757 loss_db: 0.1158 2022/10/26 04:47:21 - mmengine - INFO - Epoch(train) [720][35/63] lr: 1.5511e-03 eta: 6:10:35 time: 0.5385 data_time: 0.0323 memory: 16131 loss: 1.2000 loss_prob: 0.6291 loss_thr: 0.4600 loss_db: 0.1109 2022/10/26 04:47:24 - mmengine - INFO - Epoch(train) [720][40/63] lr: 1.5511e-03 eta: 6:10:27 time: 0.5169 data_time: 0.0115 memory: 16131 loss: 1.2216 loss_prob: 0.6605 loss_thr: 0.4501 loss_db: 0.1109 2022/10/26 04:47:27 - mmengine - INFO - Epoch(train) [720][45/63] lr: 1.5511e-03 eta: 6:10:27 time: 0.5421 data_time: 0.0059 memory: 16131 loss: 1.2648 loss_prob: 0.6898 loss_thr: 0.4629 loss_db: 0.1121 2022/10/26 04:47:30 - mmengine - INFO - Epoch(train) [720][50/63] lr: 1.5511e-03 eta: 6:10:18 time: 0.5953 data_time: 0.0145 memory: 16131 loss: 1.2575 loss_prob: 0.6744 loss_thr: 0.4679 loss_db: 0.1152 2022/10/26 04:47:32 - mmengine - INFO - Epoch(train) [720][55/63] lr: 1.5511e-03 eta: 6:10:18 time: 0.5629 data_time: 0.0205 memory: 16131 loss: 1.2661 loss_prob: 0.6870 loss_thr: 0.4599 loss_db: 0.1192 2022/10/26 04:47:35 - mmengine - INFO - Epoch(train) [720][60/63] lr: 1.5511e-03 eta: 6:10:10 time: 0.5327 data_time: 0.0141 memory: 16131 loss: 1.3073 loss_prob: 0.7439 loss_thr: 0.4458 loss_db: 0.1176 2022/10/26 04:47:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:47:36 - mmengine - INFO - Saving checkpoint at 720 epochs 2022/10/26 04:47:43 - mmengine - INFO - Epoch(val) [720][5/32] eta: 6:10:10 time: 0.5377 data_time: 0.0727 memory: 16131 2022/10/26 04:47:46 - mmengine - INFO - Epoch(val) [720][10/32] eta: 0:00:13 time: 0.5964 data_time: 0.0840 memory: 15724 2022/10/26 04:47:49 - mmengine - INFO - Epoch(val) [720][15/32] eta: 0:00:13 time: 0.5418 data_time: 0.0459 memory: 15724 2022/10/26 04:47:52 - mmengine - INFO - Epoch(val) [720][20/32] eta: 0:00:06 time: 0.5654 data_time: 0.0743 memory: 15724 2022/10/26 04:47:54 - mmengine - INFO - Epoch(val) [720][25/32] eta: 0:00:06 time: 0.5548 data_time: 0.0547 memory: 15724 2022/10/26 04:47:57 - mmengine - INFO - Epoch(val) [720][30/32] eta: 0:00:01 time: 0.5162 data_time: 0.0200 memory: 15724 2022/10/26 04:47:57 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8243, precision: 0.7411, hmean: 0.7805 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8243, precision: 0.8068, hmean: 0.8154 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8233, precision: 0.8358, hmean: 0.8295 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8185, precision: 0.8638, hmean: 0.8405 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7939, precision: 0.8894, hmean: 0.8390 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6736, precision: 0.9345, hmean: 0.7829 2022/10/26 04:47:57 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0221, precision: 1.0000, hmean: 0.0433 2022/10/26 04:47:57 - mmengine - INFO - Epoch(val) [720][32/32] icdar/precision: 0.8638 icdar/recall: 0.8185 icdar/hmean: 0.8405 2022/10/26 04:48:03 - mmengine - INFO - Epoch(train) [721][5/63] lr: 1.5482e-03 eta: 0:00:01 time: 0.7662 data_time: 0.1696 memory: 16131 loss: 1.2952 loss_prob: 0.7222 loss_thr: 0.4566 loss_db: 0.1164 2022/10/26 04:48:05 - mmengine - INFO - Epoch(train) [721][10/63] lr: 1.5482e-03 eta: 6:09:59 time: 0.7786 data_time: 0.1683 memory: 16131 loss: 1.2238 loss_prob: 0.6551 loss_thr: 0.4555 loss_db: 0.1131 2022/10/26 04:48:08 - mmengine - INFO - Epoch(train) [721][15/63] lr: 1.5482e-03 eta: 6:09:59 time: 0.4944 data_time: 0.0097 memory: 16131 loss: 1.1907 loss_prob: 0.6395 loss_thr: 0.4395 loss_db: 0.1117 2022/10/26 04:48:10 - mmengine - INFO - Epoch(train) [721][20/63] lr: 1.5482e-03 eta: 6:09:50 time: 0.4934 data_time: 0.0104 memory: 16131 loss: 1.1890 loss_prob: 0.6397 loss_thr: 0.4385 loss_db: 0.1108 2022/10/26 04:48:13 - mmengine - INFO - Epoch(train) [721][25/63] lr: 1.5482e-03 eta: 6:09:50 time: 0.5082 data_time: 0.0095 memory: 16131 loss: 1.1988 loss_prob: 0.6478 loss_thr: 0.4413 loss_db: 0.1097 2022/10/26 04:48:16 - mmengine - INFO - Epoch(train) [721][30/63] lr: 1.5482e-03 eta: 6:09:42 time: 0.5538 data_time: 0.0349 memory: 16131 loss: 1.2062 loss_prob: 0.6519 loss_thr: 0.4417 loss_db: 0.1126 2022/10/26 04:48:19 - mmengine - INFO - Epoch(train) [721][35/63] lr: 1.5482e-03 eta: 6:09:42 time: 0.6198 data_time: 0.0360 memory: 16131 loss: 1.1739 loss_prob: 0.6331 loss_thr: 0.4328 loss_db: 0.1080 2022/10/26 04:48:22 - mmengine - INFO - Epoch(train) [721][40/63] lr: 1.5482e-03 eta: 6:09:33 time: 0.5937 data_time: 0.0132 memory: 16131 loss: 1.1456 loss_prob: 0.6159 loss_thr: 0.4243 loss_db: 0.1054 2022/10/26 04:48:24 - mmengine - INFO - Epoch(train) [721][45/63] lr: 1.5482e-03 eta: 6:09:33 time: 0.5195 data_time: 0.0094 memory: 16131 loss: 1.1432 loss_prob: 0.6130 loss_thr: 0.4235 loss_db: 0.1067 2022/10/26 04:48:27 - mmengine - INFO - Epoch(train) [721][50/63] lr: 1.5482e-03 eta: 6:09:24 time: 0.5174 data_time: 0.0101 memory: 16131 loss: 1.1446 loss_prob: 0.6139 loss_thr: 0.4264 loss_db: 0.1043 2022/10/26 04:48:30 - mmengine - INFO - Epoch(train) [721][55/63] lr: 1.5482e-03 eta: 6:09:24 time: 0.5403 data_time: 0.0227 memory: 16131 loss: 1.1332 loss_prob: 0.6062 loss_thr: 0.4252 loss_db: 0.1018 2022/10/26 04:48:32 - mmengine - INFO - Epoch(train) [721][60/63] lr: 1.5482e-03 eta: 6:09:16 time: 0.5174 data_time: 0.0201 memory: 16131 loss: 1.2198 loss_prob: 0.6680 loss_thr: 0.4402 loss_db: 0.1117 2022/10/26 04:48:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:48:38 - mmengine - INFO - Epoch(train) [722][5/63] lr: 1.5453e-03 eta: 6:09:16 time: 0.6807 data_time: 0.1848 memory: 16131 loss: 1.3277 loss_prob: 0.7330 loss_thr: 0.4681 loss_db: 0.1267 2022/10/26 04:48:40 - mmengine - INFO - Epoch(train) [722][10/63] lr: 1.5453e-03 eta: 6:09:05 time: 0.7304 data_time: 0.1897 memory: 16131 loss: 1.2315 loss_prob: 0.6853 loss_thr: 0.4264 loss_db: 0.1198 2022/10/26 04:48:43 - mmengine - INFO - Epoch(train) [722][15/63] lr: 1.5453e-03 eta: 6:09:05 time: 0.5436 data_time: 0.0112 memory: 16131 loss: 1.1502 loss_prob: 0.6196 loss_thr: 0.4238 loss_db: 0.1068 2022/10/26 04:48:46 - mmengine - INFO - Epoch(train) [722][20/63] lr: 1.5453e-03 eta: 6:08:56 time: 0.5296 data_time: 0.0079 memory: 16131 loss: 1.1344 loss_prob: 0.6068 loss_thr: 0.4231 loss_db: 0.1046 2022/10/26 04:48:49 - mmengine - INFO - Epoch(train) [722][25/63] lr: 1.5453e-03 eta: 6:08:56 time: 0.5319 data_time: 0.0341 memory: 16131 loss: 1.1562 loss_prob: 0.6214 loss_thr: 0.4273 loss_db: 0.1075 2022/10/26 04:48:51 - mmengine - INFO - Epoch(train) [722][30/63] lr: 1.5453e-03 eta: 6:08:47 time: 0.5534 data_time: 0.0325 memory: 16131 loss: 1.2575 loss_prob: 0.6783 loss_thr: 0.4649 loss_db: 0.1143 2022/10/26 04:48:54 - mmengine - INFO - Epoch(train) [722][35/63] lr: 1.5453e-03 eta: 6:08:47 time: 0.5509 data_time: 0.0053 memory: 16131 loss: 1.3638 loss_prob: 0.7515 loss_thr: 0.4863 loss_db: 0.1259 2022/10/26 04:48:57 - mmengine - INFO - Epoch(train) [722][40/63] lr: 1.5453e-03 eta: 6:08:39 time: 0.5545 data_time: 0.0097 memory: 16131 loss: 1.3596 loss_prob: 0.7432 loss_thr: 0.4908 loss_db: 0.1256 2022/10/26 04:48:59 - mmengine - INFO - Epoch(train) [722][45/63] lr: 1.5453e-03 eta: 6:08:39 time: 0.5269 data_time: 0.0093 memory: 16131 loss: 1.2366 loss_prob: 0.6705 loss_thr: 0.4512 loss_db: 0.1149 2022/10/26 04:49:02 - mmengine - INFO - Epoch(train) [722][50/63] lr: 1.5453e-03 eta: 6:08:30 time: 0.5321 data_time: 0.0229 memory: 16131 loss: 1.2069 loss_prob: 0.6593 loss_thr: 0.4331 loss_db: 0.1144 2022/10/26 04:49:05 - mmengine - INFO - Epoch(train) [722][55/63] lr: 1.5453e-03 eta: 6:08:30 time: 0.5370 data_time: 0.0245 memory: 16131 loss: 1.2015 loss_prob: 0.6523 loss_thr: 0.4388 loss_db: 0.1105 2022/10/26 04:49:07 - mmengine - INFO - Epoch(train) [722][60/63] lr: 1.5453e-03 eta: 6:08:21 time: 0.5027 data_time: 0.0071 memory: 16131 loss: 1.1973 loss_prob: 0.6441 loss_thr: 0.4461 loss_db: 0.1071 2022/10/26 04:49:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:49:13 - mmengine - INFO - Epoch(train) [723][5/63] lr: 1.5424e-03 eta: 6:08:21 time: 0.7104 data_time: 0.1613 memory: 16131 loss: 1.1852 loss_prob: 0.6304 loss_thr: 0.4470 loss_db: 0.1077 2022/10/26 04:49:16 - mmengine - INFO - Epoch(train) [723][10/63] lr: 1.5424e-03 eta: 6:08:10 time: 0.7512 data_time: 0.1634 memory: 16131 loss: 1.1860 loss_prob: 0.6163 loss_thr: 0.4645 loss_db: 0.1051 2022/10/26 04:49:18 - mmengine - INFO - Epoch(train) [723][15/63] lr: 1.5424e-03 eta: 6:08:10 time: 0.5103 data_time: 0.0153 memory: 16131 loss: 1.1869 loss_prob: 0.6178 loss_thr: 0.4634 loss_db: 0.1057 2022/10/26 04:49:21 - mmengine - INFO - Epoch(train) [723][20/63] lr: 1.5424e-03 eta: 6:08:02 time: 0.5135 data_time: 0.0124 memory: 16131 loss: 1.2138 loss_prob: 0.6752 loss_thr: 0.4276 loss_db: 0.1109 2022/10/26 04:49:24 - mmengine - INFO - Epoch(train) [723][25/63] lr: 1.5424e-03 eta: 6:08:02 time: 0.5297 data_time: 0.0169 memory: 16131 loss: 1.2065 loss_prob: 0.6681 loss_thr: 0.4266 loss_db: 0.1118 2022/10/26 04:49:27 - mmengine - INFO - Epoch(train) [723][30/63] lr: 1.5424e-03 eta: 6:07:53 time: 0.5511 data_time: 0.0291 memory: 16131 loss: 1.0499 loss_prob: 0.5509 loss_thr: 0.4026 loss_db: 0.0963 2022/10/26 04:49:29 - mmengine - INFO - Epoch(train) [723][35/63] lr: 1.5424e-03 eta: 6:07:53 time: 0.5332 data_time: 0.0236 memory: 16131 loss: 1.0890 loss_prob: 0.5772 loss_thr: 0.4127 loss_db: 0.0991 2022/10/26 04:49:32 - mmengine - INFO - Epoch(train) [723][40/63] lr: 1.5424e-03 eta: 6:07:44 time: 0.5054 data_time: 0.0146 memory: 16131 loss: 1.2071 loss_prob: 0.6521 loss_thr: 0.4448 loss_db: 0.1102 2022/10/26 04:49:35 - mmengine - INFO - Epoch(train) [723][45/63] lr: 1.5424e-03 eta: 6:07:44 time: 0.6017 data_time: 0.0121 memory: 16131 loss: 1.1964 loss_prob: 0.6470 loss_thr: 0.4417 loss_db: 0.1077 2022/10/26 04:49:38 - mmengine - INFO - Epoch(train) [723][50/63] lr: 1.5424e-03 eta: 6:07:36 time: 0.5941 data_time: 0.0137 memory: 16131 loss: 1.1703 loss_prob: 0.6271 loss_thr: 0.4376 loss_db: 0.1055 2022/10/26 04:49:40 - mmengine - INFO - Epoch(train) [723][55/63] lr: 1.5424e-03 eta: 6:07:36 time: 0.5114 data_time: 0.0209 memory: 16131 loss: 1.1249 loss_prob: 0.5973 loss_thr: 0.4242 loss_db: 0.1034 2022/10/26 04:49:43 - mmengine - INFO - Epoch(train) [723][60/63] lr: 1.5424e-03 eta: 6:07:27 time: 0.5052 data_time: 0.0170 memory: 16131 loss: 1.1194 loss_prob: 0.5971 loss_thr: 0.4193 loss_db: 0.1030 2022/10/26 04:49:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:49:48 - mmengine - INFO - Epoch(train) [724][5/63] lr: 1.5395e-03 eta: 6:07:27 time: 0.6692 data_time: 0.1952 memory: 16131 loss: 1.1876 loss_prob: 0.6300 loss_thr: 0.4488 loss_db: 0.1089 2022/10/26 04:49:51 - mmengine - INFO - Epoch(train) [724][10/63] lr: 1.5395e-03 eta: 6:07:16 time: 0.6996 data_time: 0.1997 memory: 16131 loss: 1.2957 loss_prob: 0.7215 loss_thr: 0.4592 loss_db: 0.1150 2022/10/26 04:49:53 - mmengine - INFO - Epoch(train) [724][15/63] lr: 1.5395e-03 eta: 6:07:16 time: 0.4923 data_time: 0.0107 memory: 16131 loss: 1.2174 loss_prob: 0.6794 loss_thr: 0.4294 loss_db: 0.1086 2022/10/26 04:49:56 - mmengine - INFO - Epoch(train) [724][20/63] lr: 1.5395e-03 eta: 6:07:07 time: 0.5004 data_time: 0.0052 memory: 16131 loss: 1.0296 loss_prob: 0.5416 loss_thr: 0.3952 loss_db: 0.0929 2022/10/26 04:49:59 - mmengine - INFO - Epoch(train) [724][25/63] lr: 1.5395e-03 eta: 6:07:07 time: 0.5906 data_time: 0.0511 memory: 16131 loss: 1.0992 loss_prob: 0.5809 loss_thr: 0.4209 loss_db: 0.0975 2022/10/26 04:50:02 - mmengine - INFO - Epoch(train) [724][30/63] lr: 1.5395e-03 eta: 6:06:59 time: 0.5960 data_time: 0.0530 memory: 16131 loss: 1.1899 loss_prob: 0.6366 loss_thr: 0.4422 loss_db: 0.1112 2022/10/26 04:50:05 - mmengine - INFO - Epoch(train) [724][35/63] lr: 1.5395e-03 eta: 6:06:59 time: 0.5749 data_time: 0.0134 memory: 16131 loss: 1.2047 loss_prob: 0.6512 loss_thr: 0.4382 loss_db: 0.1153 2022/10/26 04:50:08 - mmengine - INFO - Epoch(train) [724][40/63] lr: 1.5395e-03 eta: 6:06:50 time: 0.5769 data_time: 0.0113 memory: 16131 loss: 1.1612 loss_prob: 0.6287 loss_thr: 0.4261 loss_db: 0.1064 2022/10/26 04:50:10 - mmengine - INFO - Epoch(train) [724][45/63] lr: 1.5395e-03 eta: 6:06:50 time: 0.5426 data_time: 0.0065 memory: 16131 loss: 1.1114 loss_prob: 0.6008 loss_thr: 0.4089 loss_db: 0.1017 2022/10/26 04:50:13 - mmengine - INFO - Epoch(train) [724][50/63] lr: 1.5395e-03 eta: 6:06:42 time: 0.5427 data_time: 0.0189 memory: 16131 loss: 1.1034 loss_prob: 0.5952 loss_thr: 0.4036 loss_db: 0.1046 2022/10/26 04:50:16 - mmengine - INFO - Epoch(train) [724][55/63] lr: 1.5395e-03 eta: 6:06:42 time: 0.5112 data_time: 0.0216 memory: 16131 loss: 1.1024 loss_prob: 0.5833 loss_thr: 0.4171 loss_db: 0.1019 2022/10/26 04:50:18 - mmengine - INFO - Epoch(train) [724][60/63] lr: 1.5395e-03 eta: 6:06:33 time: 0.4934 data_time: 0.0101 memory: 16131 loss: 1.1178 loss_prob: 0.5868 loss_thr: 0.4301 loss_db: 0.1009 2022/10/26 04:50:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:50:24 - mmengine - INFO - Epoch(train) [725][5/63] lr: 1.5366e-03 eta: 6:06:33 time: 0.6865 data_time: 0.1630 memory: 16131 loss: 1.1646 loss_prob: 0.6074 loss_thr: 0.4505 loss_db: 0.1067 2022/10/26 04:50:27 - mmengine - INFO - Epoch(train) [725][10/63] lr: 1.5366e-03 eta: 6:06:22 time: 0.7085 data_time: 0.1639 memory: 16131 loss: 1.2098 loss_prob: 0.6351 loss_thr: 0.4655 loss_db: 0.1092 2022/10/26 04:50:29 - mmengine - INFO - Epoch(train) [725][15/63] lr: 1.5366e-03 eta: 6:06:22 time: 0.5346 data_time: 0.0101 memory: 16131 loss: 1.2308 loss_prob: 0.6488 loss_thr: 0.4703 loss_db: 0.1117 2022/10/26 04:50:32 - mmengine - INFO - Epoch(train) [725][20/63] lr: 1.5366e-03 eta: 6:06:13 time: 0.5288 data_time: 0.0075 memory: 16131 loss: 1.1782 loss_prob: 0.6220 loss_thr: 0.4486 loss_db: 0.1076 2022/10/26 04:50:34 - mmengine - INFO - Epoch(train) [725][25/63] lr: 1.5366e-03 eta: 6:06:13 time: 0.5050 data_time: 0.0127 memory: 16131 loss: 1.1806 loss_prob: 0.6315 loss_thr: 0.4403 loss_db: 0.1088 2022/10/26 04:50:37 - mmengine - INFO - Epoch(train) [725][30/63] lr: 1.5366e-03 eta: 6:06:04 time: 0.5054 data_time: 0.0315 memory: 16131 loss: 1.1028 loss_prob: 0.5801 loss_thr: 0.4220 loss_db: 0.1007 2022/10/26 04:50:40 - mmengine - INFO - Epoch(train) [725][35/63] lr: 1.5366e-03 eta: 6:06:04 time: 0.5300 data_time: 0.0288 memory: 16131 loss: 1.0979 loss_prob: 0.5838 loss_thr: 0.4145 loss_db: 0.0996 2022/10/26 04:50:42 - mmengine - INFO - Epoch(train) [725][40/63] lr: 1.5366e-03 eta: 6:05:56 time: 0.5209 data_time: 0.0095 memory: 16131 loss: 1.1577 loss_prob: 0.6258 loss_thr: 0.4238 loss_db: 0.1081 2022/10/26 04:50:45 - mmengine - INFO - Epoch(train) [725][45/63] lr: 1.5366e-03 eta: 6:05:56 time: 0.4948 data_time: 0.0056 memory: 16131 loss: 1.1867 loss_prob: 0.6515 loss_thr: 0.4283 loss_db: 0.1069 2022/10/26 04:50:48 - mmengine - INFO - Epoch(train) [725][50/63] lr: 1.5366e-03 eta: 6:05:48 time: 0.6217 data_time: 0.0104 memory: 16131 loss: 1.1826 loss_prob: 0.6487 loss_thr: 0.4267 loss_db: 0.1071 2022/10/26 04:50:51 - mmengine - INFO - Epoch(train) [725][55/63] lr: 1.5366e-03 eta: 6:05:48 time: 0.6621 data_time: 0.0204 memory: 16131 loss: 1.1405 loss_prob: 0.6149 loss_thr: 0.4188 loss_db: 0.1068 2022/10/26 04:50:54 - mmengine - INFO - Epoch(train) [725][60/63] lr: 1.5366e-03 eta: 6:05:39 time: 0.5518 data_time: 0.0190 memory: 16131 loss: 1.1463 loss_prob: 0.6109 loss_thr: 0.4330 loss_db: 0.1024 2022/10/26 04:50:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:51:00 - mmengine - INFO - Epoch(train) [726][5/63] lr: 1.5337e-03 eta: 6:05:39 time: 0.7194 data_time: 0.1903 memory: 16131 loss: 1.2117 loss_prob: 0.6638 loss_thr: 0.4387 loss_db: 0.1093 2022/10/26 04:51:03 - mmengine - INFO - Epoch(train) [726][10/63] lr: 1.5337e-03 eta: 6:05:28 time: 0.7576 data_time: 0.1910 memory: 16131 loss: 1.2013 loss_prob: 0.6656 loss_thr: 0.4256 loss_db: 0.1101 2022/10/26 04:51:05 - mmengine - INFO - Epoch(train) [726][15/63] lr: 1.5337e-03 eta: 6:05:28 time: 0.5222 data_time: 0.0095 memory: 16131 loss: 1.0540 loss_prob: 0.5610 loss_thr: 0.3959 loss_db: 0.0972 2022/10/26 04:51:08 - mmengine - INFO - Epoch(train) [726][20/63] lr: 1.5337e-03 eta: 6:05:19 time: 0.5110 data_time: 0.0102 memory: 16131 loss: 1.0200 loss_prob: 0.5353 loss_thr: 0.3929 loss_db: 0.0917 2022/10/26 04:51:10 - mmengine - INFO - Epoch(train) [726][25/63] lr: 1.5337e-03 eta: 6:05:19 time: 0.5336 data_time: 0.0249 memory: 16131 loss: 1.1848 loss_prob: 0.6389 loss_thr: 0.4393 loss_db: 0.1065 2022/10/26 04:51:13 - mmengine - INFO - Epoch(train) [726][30/63] lr: 1.5337e-03 eta: 6:05:11 time: 0.5513 data_time: 0.0294 memory: 16131 loss: 1.2111 loss_prob: 0.6573 loss_thr: 0.4425 loss_db: 0.1112 2022/10/26 04:51:16 - mmengine - INFO - Epoch(train) [726][35/63] lr: 1.5337e-03 eta: 6:05:11 time: 0.5218 data_time: 0.0132 memory: 16131 loss: 1.1116 loss_prob: 0.5818 loss_thr: 0.4297 loss_db: 0.1000 2022/10/26 04:51:19 - mmengine - INFO - Epoch(train) [726][40/63] lr: 1.5337e-03 eta: 6:05:02 time: 0.5353 data_time: 0.0081 memory: 16131 loss: 1.0839 loss_prob: 0.5637 loss_thr: 0.4223 loss_db: 0.0980 2022/10/26 04:51:21 - mmengine - INFO - Epoch(train) [726][45/63] lr: 1.5337e-03 eta: 6:05:02 time: 0.5771 data_time: 0.0085 memory: 16131 loss: 1.0572 loss_prob: 0.5614 loss_thr: 0.4001 loss_db: 0.0957 2022/10/26 04:51:24 - mmengine - INFO - Epoch(train) [726][50/63] lr: 1.5337e-03 eta: 6:04:54 time: 0.5794 data_time: 0.0295 memory: 16131 loss: 1.1293 loss_prob: 0.6060 loss_thr: 0.4222 loss_db: 0.1012 2022/10/26 04:51:27 - mmengine - INFO - Epoch(train) [726][55/63] lr: 1.5337e-03 eta: 6:04:54 time: 0.6015 data_time: 0.0316 memory: 16131 loss: 1.1534 loss_prob: 0.6102 loss_thr: 0.4375 loss_db: 0.1056 2022/10/26 04:51:30 - mmengine - INFO - Epoch(train) [726][60/63] lr: 1.5337e-03 eta: 6:04:45 time: 0.5566 data_time: 0.0090 memory: 16131 loss: 1.1251 loss_prob: 0.5855 loss_thr: 0.4385 loss_db: 0.1012 2022/10/26 04:51:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:51:36 - mmengine - INFO - Epoch(train) [727][5/63] lr: 1.5307e-03 eta: 6:04:45 time: 0.7306 data_time: 0.1758 memory: 16131 loss: 1.0984 loss_prob: 0.5838 loss_thr: 0.4112 loss_db: 0.1033 2022/10/26 04:51:39 - mmengine - INFO - Epoch(train) [727][10/63] lr: 1.5307e-03 eta: 6:04:35 time: 0.7508 data_time: 0.1814 memory: 16131 loss: 1.0656 loss_prob: 0.5622 loss_thr: 0.4057 loss_db: 0.0977 2022/10/26 04:51:42 - mmengine - INFO - Epoch(train) [727][15/63] lr: 1.5307e-03 eta: 6:04:35 time: 0.5206 data_time: 0.0125 memory: 16131 loss: 1.1242 loss_prob: 0.5998 loss_thr: 0.4234 loss_db: 0.1010 2022/10/26 04:51:44 - mmengine - INFO - Epoch(train) [727][20/63] lr: 1.5307e-03 eta: 6:04:26 time: 0.5305 data_time: 0.0063 memory: 16131 loss: 1.1311 loss_prob: 0.6040 loss_thr: 0.4251 loss_db: 0.1020 2022/10/26 04:51:47 - mmengine - INFO - Epoch(train) [727][25/63] lr: 1.5307e-03 eta: 6:04:26 time: 0.5174 data_time: 0.0171 memory: 16131 loss: 1.0764 loss_prob: 0.5748 loss_thr: 0.4017 loss_db: 0.0998 2022/10/26 04:51:49 - mmengine - INFO - Epoch(train) [727][30/63] lr: 1.5307e-03 eta: 6:04:17 time: 0.5227 data_time: 0.0302 memory: 16131 loss: 1.0974 loss_prob: 0.5866 loss_thr: 0.4096 loss_db: 0.1013 2022/10/26 04:51:52 - mmengine - INFO - Epoch(train) [727][35/63] lr: 1.5307e-03 eta: 6:04:17 time: 0.5079 data_time: 0.0210 memory: 16131 loss: 1.1116 loss_prob: 0.5950 loss_thr: 0.4156 loss_db: 0.1010 2022/10/26 04:51:54 - mmengine - INFO - Epoch(train) [727][40/63] lr: 1.5307e-03 eta: 6:04:08 time: 0.4966 data_time: 0.0067 memory: 16131 loss: 1.1705 loss_prob: 0.6275 loss_thr: 0.4339 loss_db: 0.1092 2022/10/26 04:51:57 - mmengine - INFO - Epoch(train) [727][45/63] lr: 1.5307e-03 eta: 6:04:08 time: 0.5222 data_time: 0.0074 memory: 16131 loss: 1.2244 loss_prob: 0.6577 loss_thr: 0.4523 loss_db: 0.1144 2022/10/26 04:52:00 - mmengine - INFO - Epoch(train) [727][50/63] lr: 1.5307e-03 eta: 6:04:00 time: 0.5235 data_time: 0.0146 memory: 16131 loss: 1.1183 loss_prob: 0.5961 loss_thr: 0.4212 loss_db: 0.1009 2022/10/26 04:52:02 - mmengine - INFO - Epoch(train) [727][55/63] lr: 1.5307e-03 eta: 6:04:00 time: 0.5119 data_time: 0.0219 memory: 16131 loss: 1.0395 loss_prob: 0.5450 loss_thr: 0.4027 loss_db: 0.0919 2022/10/26 04:52:05 - mmengine - INFO - Epoch(train) [727][60/63] lr: 1.5307e-03 eta: 6:03:51 time: 0.5446 data_time: 0.0160 memory: 16131 loss: 1.1877 loss_prob: 0.6239 loss_thr: 0.4567 loss_db: 0.1072 2022/10/26 04:52:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:52:11 - mmengine - INFO - Epoch(train) [728][5/63] lr: 1.5278e-03 eta: 6:03:51 time: 0.7121 data_time: 0.1474 memory: 16131 loss: 1.0284 loss_prob: 0.5280 loss_thr: 0.4065 loss_db: 0.0939 2022/10/26 04:52:14 - mmengine - INFO - Epoch(train) [728][10/63] lr: 1.5278e-03 eta: 6:03:40 time: 0.7589 data_time: 0.1598 memory: 16131 loss: 1.0192 loss_prob: 0.5276 loss_thr: 0.4000 loss_db: 0.0916 2022/10/26 04:52:16 - mmengine - INFO - Epoch(train) [728][15/63] lr: 1.5278e-03 eta: 6:03:40 time: 0.5440 data_time: 0.0227 memory: 16131 loss: 1.0842 loss_prob: 0.5784 loss_thr: 0.4121 loss_db: 0.0938 2022/10/26 04:52:19 - mmengine - INFO - Epoch(train) [728][20/63] lr: 1.5278e-03 eta: 6:03:32 time: 0.5019 data_time: 0.0111 memory: 16131 loss: 1.0814 loss_prob: 0.5763 loss_thr: 0.4079 loss_db: 0.0972 2022/10/26 04:52:21 - mmengine - INFO - Epoch(train) [728][25/63] lr: 1.5278e-03 eta: 6:03:32 time: 0.4954 data_time: 0.0116 memory: 16131 loss: 1.0633 loss_prob: 0.5590 loss_thr: 0.4055 loss_db: 0.0988 2022/10/26 04:52:24 - mmengine - INFO - Epoch(train) [728][30/63] lr: 1.5278e-03 eta: 6:03:23 time: 0.5170 data_time: 0.0283 memory: 16131 loss: 1.1748 loss_prob: 0.6278 loss_thr: 0.4397 loss_db: 0.1073 2022/10/26 04:52:27 - mmengine - INFO - Epoch(train) [728][35/63] lr: 1.5278e-03 eta: 6:03:23 time: 0.5188 data_time: 0.0306 memory: 16131 loss: 1.1501 loss_prob: 0.6217 loss_thr: 0.4219 loss_db: 0.1066 2022/10/26 04:52:29 - mmengine - INFO - Epoch(train) [728][40/63] lr: 1.5278e-03 eta: 6:03:14 time: 0.5128 data_time: 0.0163 memory: 16131 loss: 1.0628 loss_prob: 0.5647 loss_thr: 0.4001 loss_db: 0.0981 2022/10/26 04:52:32 - mmengine - INFO - Epoch(train) [728][45/63] lr: 1.5278e-03 eta: 6:03:14 time: 0.5124 data_time: 0.0088 memory: 16131 loss: 1.0331 loss_prob: 0.5372 loss_thr: 0.4044 loss_db: 0.0915 2022/10/26 04:52:35 - mmengine - INFO - Epoch(train) [728][50/63] lr: 1.5278e-03 eta: 6:03:06 time: 0.5350 data_time: 0.0144 memory: 16131 loss: 1.1486 loss_prob: 0.6100 loss_thr: 0.4329 loss_db: 0.1057 2022/10/26 04:52:37 - mmengine - INFO - Epoch(train) [728][55/63] lr: 1.5278e-03 eta: 6:03:06 time: 0.5436 data_time: 0.0227 memory: 16131 loss: 1.2274 loss_prob: 0.6645 loss_thr: 0.4455 loss_db: 0.1173 2022/10/26 04:52:40 - mmengine - INFO - Epoch(train) [728][60/63] lr: 1.5278e-03 eta: 6:02:57 time: 0.5270 data_time: 0.0201 memory: 16131 loss: 1.1636 loss_prob: 0.6330 loss_thr: 0.4205 loss_db: 0.1101 2022/10/26 04:52:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:52:46 - mmengine - INFO - Epoch(train) [729][5/63] lr: 1.5249e-03 eta: 6:02:57 time: 0.7018 data_time: 0.1758 memory: 16131 loss: 1.2791 loss_prob: 0.6874 loss_thr: 0.4728 loss_db: 0.1190 2022/10/26 04:52:48 - mmengine - INFO - Epoch(train) [729][10/63] lr: 1.5249e-03 eta: 6:02:46 time: 0.7042 data_time: 0.1752 memory: 16131 loss: 1.1355 loss_prob: 0.6001 loss_thr: 0.4306 loss_db: 0.1048 2022/10/26 04:52:51 - mmengine - INFO - Epoch(train) [729][15/63] lr: 1.5249e-03 eta: 6:02:46 time: 0.5408 data_time: 0.0062 memory: 16131 loss: 1.0776 loss_prob: 0.5707 loss_thr: 0.4073 loss_db: 0.0997 2022/10/26 04:52:54 - mmengine - INFO - Epoch(train) [729][20/63] lr: 1.5249e-03 eta: 6:02:37 time: 0.5494 data_time: 0.0062 memory: 16131 loss: 1.1355 loss_prob: 0.5985 loss_thr: 0.4349 loss_db: 0.1022 2022/10/26 04:52:56 - mmengine - INFO - Epoch(train) [729][25/63] lr: 1.5249e-03 eta: 6:02:37 time: 0.5198 data_time: 0.0194 memory: 16131 loss: 1.2435 loss_prob: 0.6710 loss_thr: 0.4603 loss_db: 0.1121 2022/10/26 04:52:59 - mmengine - INFO - Epoch(train) [729][30/63] lr: 1.5249e-03 eta: 6:02:29 time: 0.5244 data_time: 0.0311 memory: 16131 loss: 1.2183 loss_prob: 0.6598 loss_thr: 0.4468 loss_db: 0.1117 2022/10/26 04:53:02 - mmengine - INFO - Epoch(train) [729][35/63] lr: 1.5249e-03 eta: 6:02:29 time: 0.5201 data_time: 0.0170 memory: 16131 loss: 1.1249 loss_prob: 0.5945 loss_thr: 0.4281 loss_db: 0.1023 2022/10/26 04:53:04 - mmengine - INFO - Epoch(train) [729][40/63] lr: 1.5249e-03 eta: 6:02:20 time: 0.5260 data_time: 0.0045 memory: 16131 loss: 1.0722 loss_prob: 0.5686 loss_thr: 0.4053 loss_db: 0.0984 2022/10/26 04:53:07 - mmengine - INFO - Epoch(train) [729][45/63] lr: 1.5249e-03 eta: 6:02:20 time: 0.5334 data_time: 0.0116 memory: 16131 loss: 1.0533 loss_prob: 0.5542 loss_thr: 0.4032 loss_db: 0.0958 2022/10/26 04:53:09 - mmengine - INFO - Epoch(train) [729][50/63] lr: 1.5249e-03 eta: 6:02:11 time: 0.5160 data_time: 0.0221 memory: 16131 loss: 1.0535 loss_prob: 0.5499 loss_thr: 0.4098 loss_db: 0.0938 2022/10/26 04:53:12 - mmengine - INFO - Epoch(train) [729][55/63] lr: 1.5249e-03 eta: 6:02:11 time: 0.5190 data_time: 0.0231 memory: 16131 loss: 1.0121 loss_prob: 0.5345 loss_thr: 0.3860 loss_db: 0.0916 2022/10/26 04:53:15 - mmengine - INFO - Epoch(train) [729][60/63] lr: 1.5249e-03 eta: 6:02:02 time: 0.5127 data_time: 0.0129 memory: 16131 loss: 1.2532 loss_prob: 0.7117 loss_thr: 0.4283 loss_db: 0.1133 2022/10/26 04:53:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:53:21 - mmengine - INFO - Epoch(train) [730][5/63] lr: 1.5220e-03 eta: 6:02:02 time: 0.7760 data_time: 0.1941 memory: 16131 loss: 1.4071 loss_prob: 0.7896 loss_thr: 0.5003 loss_db: 0.1171 2022/10/26 04:53:24 - mmengine - INFO - Epoch(train) [730][10/63] lr: 1.5220e-03 eta: 6:01:52 time: 0.7960 data_time: 0.1985 memory: 16131 loss: 1.2927 loss_prob: 0.7047 loss_thr: 0.4751 loss_db: 0.1129 2022/10/26 04:53:26 - mmengine - INFO - Epoch(train) [730][15/63] lr: 1.5220e-03 eta: 6:01:52 time: 0.5181 data_time: 0.0148 memory: 16131 loss: 1.1592 loss_prob: 0.6164 loss_thr: 0.4326 loss_db: 0.1102 2022/10/26 04:53:29 - mmengine - INFO - Epoch(train) [730][20/63] lr: 1.5220e-03 eta: 6:01:43 time: 0.5472 data_time: 0.0097 memory: 16131 loss: 1.1855 loss_prob: 0.6342 loss_thr: 0.4417 loss_db: 0.1096 2022/10/26 04:53:32 - mmengine - INFO - Epoch(train) [730][25/63] lr: 1.5220e-03 eta: 6:01:43 time: 0.5670 data_time: 0.0094 memory: 16131 loss: 1.1982 loss_prob: 0.6424 loss_thr: 0.4479 loss_db: 0.1079 2022/10/26 04:53:35 - mmengine - INFO - Epoch(train) [730][30/63] lr: 1.5220e-03 eta: 6:01:35 time: 0.5491 data_time: 0.0307 memory: 16131 loss: 1.2159 loss_prob: 0.6553 loss_thr: 0.4500 loss_db: 0.1106 2022/10/26 04:53:38 - mmengine - INFO - Epoch(train) [730][35/63] lr: 1.5220e-03 eta: 6:01:35 time: 0.5495 data_time: 0.0455 memory: 16131 loss: 1.2115 loss_prob: 0.6429 loss_thr: 0.4583 loss_db: 0.1104 2022/10/26 04:53:40 - mmengine - INFO - Epoch(train) [730][40/63] lr: 1.5220e-03 eta: 6:01:26 time: 0.5414 data_time: 0.0239 memory: 16131 loss: 1.2057 loss_prob: 0.6349 loss_thr: 0.4603 loss_db: 0.1106 2022/10/26 04:53:43 - mmengine - INFO - Epoch(train) [730][45/63] lr: 1.5220e-03 eta: 6:01:26 time: 0.4992 data_time: 0.0052 memory: 16131 loss: 1.1769 loss_prob: 0.6275 loss_thr: 0.4396 loss_db: 0.1098 2022/10/26 04:53:45 - mmengine - INFO - Epoch(train) [730][50/63] lr: 1.5220e-03 eta: 6:01:18 time: 0.5066 data_time: 0.0051 memory: 16131 loss: 1.1016 loss_prob: 0.5833 loss_thr: 0.4149 loss_db: 0.1034 2022/10/26 04:53:48 - mmengine - INFO - Epoch(train) [730][55/63] lr: 1.5220e-03 eta: 6:01:18 time: 0.5181 data_time: 0.0095 memory: 16131 loss: 1.1371 loss_prob: 0.6018 loss_thr: 0.4295 loss_db: 0.1058 2022/10/26 04:53:50 - mmengine - INFO - Epoch(train) [730][60/63] lr: 1.5220e-03 eta: 6:01:09 time: 0.4951 data_time: 0.0134 memory: 16131 loss: 1.1739 loss_prob: 0.6306 loss_thr: 0.4365 loss_db: 0.1068 2022/10/26 04:53:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:53:57 - mmengine - INFO - Epoch(train) [731][5/63] lr: 1.5191e-03 eta: 6:01:09 time: 0.7213 data_time: 0.2110 memory: 16131 loss: 1.2703 loss_prob: 0.6973 loss_thr: 0.4537 loss_db: 0.1193 2022/10/26 04:53:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:53:59 - mmengine - INFO - Epoch(train) [731][10/63] lr: 1.5191e-03 eta: 6:00:58 time: 0.7666 data_time: 0.2200 memory: 16131 loss: 1.3725 loss_prob: 0.7685 loss_thr: 0.4751 loss_db: 0.1289 2022/10/26 04:54:02 - mmengine - INFO - Epoch(train) [731][15/63] lr: 1.5191e-03 eta: 6:00:58 time: 0.5250 data_time: 0.0155 memory: 16131 loss: 1.3176 loss_prob: 0.7365 loss_thr: 0.4590 loss_db: 0.1221 2022/10/26 04:54:04 - mmengine - INFO - Epoch(train) [731][20/63] lr: 1.5191e-03 eta: 6:00:49 time: 0.5191 data_time: 0.0099 memory: 16131 loss: 1.2250 loss_prob: 0.6713 loss_thr: 0.4403 loss_db: 0.1135 2022/10/26 04:54:07 - mmengine - INFO - Epoch(train) [731][25/63] lr: 1.5191e-03 eta: 6:00:49 time: 0.5571 data_time: 0.0224 memory: 16131 loss: 1.3025 loss_prob: 0.7229 loss_thr: 0.4587 loss_db: 0.1209 2022/10/26 04:54:10 - mmengine - INFO - Epoch(train) [731][30/63] lr: 1.5191e-03 eta: 6:00:41 time: 0.5653 data_time: 0.0310 memory: 16131 loss: 1.2701 loss_prob: 0.6889 loss_thr: 0.4671 loss_db: 0.1141 2022/10/26 04:54:12 - mmengine - INFO - Epoch(train) [731][35/63] lr: 1.5191e-03 eta: 6:00:41 time: 0.5080 data_time: 0.0238 memory: 16131 loss: 1.3015 loss_prob: 0.7305 loss_thr: 0.4558 loss_db: 0.1151 2022/10/26 04:54:15 - mmengine - INFO - Epoch(train) [731][40/63] lr: 1.5191e-03 eta: 6:00:32 time: 0.5060 data_time: 0.0098 memory: 16131 loss: 1.2693 loss_prob: 0.7198 loss_thr: 0.4322 loss_db: 0.1174 2022/10/26 04:54:18 - mmengine - INFO - Epoch(train) [731][45/63] lr: 1.5191e-03 eta: 6:00:32 time: 0.5125 data_time: 0.0043 memory: 16131 loss: 1.1556 loss_prob: 0.6175 loss_thr: 0.4307 loss_db: 0.1074 2022/10/26 04:54:20 - mmengine - INFO - Epoch(train) [731][50/63] lr: 1.5191e-03 eta: 6:00:23 time: 0.5078 data_time: 0.0149 memory: 16131 loss: 1.1262 loss_prob: 0.5947 loss_thr: 0.4319 loss_db: 0.0997 2022/10/26 04:54:23 - mmengine - INFO - Epoch(train) [731][55/63] lr: 1.5191e-03 eta: 6:00:23 time: 0.5056 data_time: 0.0192 memory: 16131 loss: 1.1204 loss_prob: 0.5965 loss_thr: 0.4238 loss_db: 0.1001 2022/10/26 04:54:25 - mmengine - INFO - Epoch(train) [731][60/63] lr: 1.5191e-03 eta: 6:00:15 time: 0.5063 data_time: 0.0119 memory: 16131 loss: 1.1978 loss_prob: 0.6463 loss_thr: 0.4436 loss_db: 0.1078 2022/10/26 04:54:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:54:32 - mmengine - INFO - Epoch(train) [732][5/63] lr: 1.5162e-03 eta: 6:00:15 time: 0.7847 data_time: 0.1755 memory: 16131 loss: 1.1486 loss_prob: 0.6074 loss_thr: 0.4353 loss_db: 0.1059 2022/10/26 04:54:35 - mmengine - INFO - Epoch(train) [732][10/63] lr: 1.5162e-03 eta: 6:00:04 time: 0.8192 data_time: 0.1814 memory: 16131 loss: 1.1742 loss_prob: 0.6408 loss_thr: 0.4223 loss_db: 0.1111 2022/10/26 04:54:38 - mmengine - INFO - Epoch(train) [732][15/63] lr: 1.5162e-03 eta: 6:00:04 time: 0.5489 data_time: 0.0105 memory: 16131 loss: 1.1945 loss_prob: 0.6539 loss_thr: 0.4281 loss_db: 0.1124 2022/10/26 04:54:40 - mmengine - INFO - Epoch(train) [732][20/63] lr: 1.5162e-03 eta: 5:59:56 time: 0.5844 data_time: 0.0069 memory: 16131 loss: 1.2110 loss_prob: 0.6534 loss_thr: 0.4475 loss_db: 0.1101 2022/10/26 04:54:43 - mmengine - INFO - Epoch(train) [732][25/63] lr: 1.5162e-03 eta: 5:59:56 time: 0.5542 data_time: 0.0217 memory: 16131 loss: 1.2780 loss_prob: 0.6833 loss_thr: 0.4782 loss_db: 0.1165 2022/10/26 04:54:46 - mmengine - INFO - Epoch(train) [732][30/63] lr: 1.5162e-03 eta: 5:59:47 time: 0.5260 data_time: 0.0244 memory: 16131 loss: 1.1717 loss_prob: 0.6155 loss_thr: 0.4479 loss_db: 0.1082 2022/10/26 04:54:48 - mmengine - INFO - Epoch(train) [732][35/63] lr: 1.5162e-03 eta: 5:59:47 time: 0.5121 data_time: 0.0155 memory: 16131 loss: 1.1238 loss_prob: 0.5929 loss_thr: 0.4275 loss_db: 0.1034 2022/10/26 04:54:51 - mmengine - INFO - Epoch(train) [732][40/63] lr: 1.5162e-03 eta: 5:59:39 time: 0.5302 data_time: 0.0103 memory: 16131 loss: 1.1319 loss_prob: 0.5984 loss_thr: 0.4294 loss_db: 0.1041 2022/10/26 04:54:54 - mmengine - INFO - Epoch(train) [732][45/63] lr: 1.5162e-03 eta: 5:59:39 time: 0.5350 data_time: 0.0070 memory: 16131 loss: 1.0954 loss_prob: 0.5740 loss_thr: 0.4228 loss_db: 0.0987 2022/10/26 04:54:56 - mmengine - INFO - Epoch(train) [732][50/63] lr: 1.5162e-03 eta: 5:59:30 time: 0.5088 data_time: 0.0194 memory: 16131 loss: 1.1819 loss_prob: 0.6346 loss_thr: 0.4389 loss_db: 0.1083 2022/10/26 04:54:59 - mmengine - INFO - Epoch(train) [732][55/63] lr: 1.5162e-03 eta: 5:59:30 time: 0.5016 data_time: 0.0191 memory: 16131 loss: 1.1189 loss_prob: 0.5961 loss_thr: 0.4194 loss_db: 0.1034 2022/10/26 04:55:01 - mmengine - INFO - Epoch(train) [732][60/63] lr: 1.5162e-03 eta: 5:59:21 time: 0.4959 data_time: 0.0093 memory: 16131 loss: 1.0388 loss_prob: 0.5470 loss_thr: 0.3981 loss_db: 0.0937 2022/10/26 04:55:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:55:07 - mmengine - INFO - Epoch(train) [733][5/63] lr: 1.5133e-03 eta: 5:59:21 time: 0.7288 data_time: 0.1899 memory: 16131 loss: 1.2074 loss_prob: 0.6524 loss_thr: 0.4453 loss_db: 0.1096 2022/10/26 04:55:10 - mmengine - INFO - Epoch(train) [733][10/63] lr: 1.5133e-03 eta: 5:59:10 time: 0.7285 data_time: 0.1896 memory: 16131 loss: 1.2433 loss_prob: 0.6791 loss_thr: 0.4486 loss_db: 0.1156 2022/10/26 04:55:13 - mmengine - INFO - Epoch(train) [733][15/63] lr: 1.5133e-03 eta: 5:59:10 time: 0.5504 data_time: 0.0077 memory: 16131 loss: 1.1407 loss_prob: 0.6114 loss_thr: 0.4229 loss_db: 0.1064 2022/10/26 04:55:16 - mmengine - INFO - Epoch(train) [733][20/63] lr: 1.5133e-03 eta: 5:59:02 time: 0.5449 data_time: 0.0073 memory: 16131 loss: 1.0754 loss_prob: 0.5648 loss_thr: 0.4117 loss_db: 0.0989 2022/10/26 04:55:18 - mmengine - INFO - Epoch(train) [733][25/63] lr: 1.5133e-03 eta: 5:59:02 time: 0.5481 data_time: 0.0324 memory: 16131 loss: 1.1689 loss_prob: 0.6405 loss_thr: 0.4214 loss_db: 0.1070 2022/10/26 04:55:21 - mmengine - INFO - Epoch(train) [733][30/63] lr: 1.5133e-03 eta: 5:58:53 time: 0.5308 data_time: 0.0469 memory: 16131 loss: 1.2159 loss_prob: 0.6735 loss_thr: 0.4311 loss_db: 0.1113 2022/10/26 04:55:23 - mmengine - INFO - Epoch(train) [733][35/63] lr: 1.5133e-03 eta: 5:58:53 time: 0.5053 data_time: 0.0227 memory: 16131 loss: 1.1061 loss_prob: 0.5878 loss_thr: 0.4186 loss_db: 0.0997 2022/10/26 04:55:26 - mmengine - INFO - Epoch(train) [733][40/63] lr: 1.5133e-03 eta: 5:58:44 time: 0.4834 data_time: 0.0088 memory: 16131 loss: 1.1886 loss_prob: 0.6443 loss_thr: 0.4330 loss_db: 0.1113 2022/10/26 04:55:28 - mmengine - INFO - Epoch(train) [733][45/63] lr: 1.5133e-03 eta: 5:58:44 time: 0.4966 data_time: 0.0069 memory: 16131 loss: 1.2222 loss_prob: 0.6683 loss_thr: 0.4383 loss_db: 0.1156 2022/10/26 04:55:31 - mmengine - INFO - Epoch(train) [733][50/63] lr: 1.5133e-03 eta: 5:58:36 time: 0.5389 data_time: 0.0166 memory: 16131 loss: 1.1309 loss_prob: 0.6021 loss_thr: 0.4267 loss_db: 0.1021 2022/10/26 04:55:34 - mmengine - INFO - Epoch(train) [733][55/63] lr: 1.5133e-03 eta: 5:58:36 time: 0.5533 data_time: 0.0215 memory: 16131 loss: 1.0846 loss_prob: 0.5698 loss_thr: 0.4175 loss_db: 0.0973 2022/10/26 04:55:36 - mmengine - INFO - Epoch(train) [733][60/63] lr: 1.5133e-03 eta: 5:58:27 time: 0.5207 data_time: 0.0111 memory: 16131 loss: 1.1565 loss_prob: 0.6157 loss_thr: 0.4371 loss_db: 0.1037 2022/10/26 04:55:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:55:42 - mmengine - INFO - Epoch(train) [734][5/63] lr: 1.5103e-03 eta: 5:58:27 time: 0.6947 data_time: 0.1759 memory: 16131 loss: 1.1894 loss_prob: 0.6513 loss_thr: 0.4289 loss_db: 0.1091 2022/10/26 04:55:45 - mmengine - INFO - Epoch(train) [734][10/63] lr: 1.5103e-03 eta: 5:58:16 time: 0.7154 data_time: 0.1747 memory: 16131 loss: 1.1984 loss_prob: 0.6463 loss_thr: 0.4430 loss_db: 0.1091 2022/10/26 04:55:48 - mmengine - INFO - Epoch(train) [734][15/63] lr: 1.5103e-03 eta: 5:58:16 time: 0.5423 data_time: 0.0137 memory: 16131 loss: 1.2025 loss_prob: 0.6449 loss_thr: 0.4489 loss_db: 0.1086 2022/10/26 04:55:51 - mmengine - INFO - Epoch(train) [734][20/63] lr: 1.5103e-03 eta: 5:58:08 time: 0.5626 data_time: 0.0118 memory: 16131 loss: 1.2345 loss_prob: 0.6745 loss_thr: 0.4464 loss_db: 0.1136 2022/10/26 04:55:53 - mmengine - INFO - Epoch(train) [734][25/63] lr: 1.5103e-03 eta: 5:58:08 time: 0.5390 data_time: 0.0118 memory: 16131 loss: 1.1196 loss_prob: 0.6017 loss_thr: 0.4151 loss_db: 0.1028 2022/10/26 04:55:56 - mmengine - INFO - Epoch(train) [734][30/63] lr: 1.5103e-03 eta: 5:57:59 time: 0.5524 data_time: 0.0382 memory: 16131 loss: 1.0922 loss_prob: 0.5861 loss_thr: 0.4059 loss_db: 0.1002 2022/10/26 04:55:59 - mmengine - INFO - Epoch(train) [734][35/63] lr: 1.5103e-03 eta: 5:57:59 time: 0.5354 data_time: 0.0320 memory: 16131 loss: 1.1806 loss_prob: 0.6439 loss_thr: 0.4299 loss_db: 0.1068 2022/10/26 04:56:01 - mmengine - INFO - Epoch(train) [734][40/63] lr: 1.5103e-03 eta: 5:57:51 time: 0.4893 data_time: 0.0073 memory: 16131 loss: 1.3304 loss_prob: 0.7433 loss_thr: 0.4654 loss_db: 0.1217 2022/10/26 04:56:04 - mmengine - INFO - Epoch(train) [734][45/63] lr: 1.5103e-03 eta: 5:57:51 time: 0.5033 data_time: 0.0086 memory: 16131 loss: 1.3490 loss_prob: 0.7502 loss_thr: 0.4700 loss_db: 0.1289 2022/10/26 04:56:07 - mmengine - INFO - Epoch(train) [734][50/63] lr: 1.5103e-03 eta: 5:57:42 time: 0.5613 data_time: 0.0195 memory: 16131 loss: 1.2318 loss_prob: 0.6621 loss_thr: 0.4516 loss_db: 0.1182 2022/10/26 04:56:09 - mmengine - INFO - Epoch(train) [734][55/63] lr: 1.5103e-03 eta: 5:57:42 time: 0.5730 data_time: 0.0180 memory: 16131 loss: 1.2863 loss_prob: 0.7059 loss_thr: 0.4639 loss_db: 0.1166 2022/10/26 04:56:12 - mmengine - INFO - Epoch(train) [734][60/63] lr: 1.5103e-03 eta: 5:57:33 time: 0.5055 data_time: 0.0055 memory: 16131 loss: 1.2946 loss_prob: 0.7133 loss_thr: 0.4648 loss_db: 0.1165 2022/10/26 04:56:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:56:18 - mmengine - INFO - Epoch(train) [735][5/63] lr: 1.5074e-03 eta: 5:57:33 time: 0.6819 data_time: 0.1792 memory: 16131 loss: 1.1418 loss_prob: 0.6120 loss_thr: 0.4243 loss_db: 0.1055 2022/10/26 04:56:20 - mmengine - INFO - Epoch(train) [735][10/63] lr: 1.5074e-03 eta: 5:57:22 time: 0.7007 data_time: 0.1877 memory: 16131 loss: 1.2098 loss_prob: 0.6551 loss_thr: 0.4433 loss_db: 0.1114 2022/10/26 04:56:23 - mmengine - INFO - Epoch(train) [735][15/63] lr: 1.5074e-03 eta: 5:57:22 time: 0.5300 data_time: 0.0195 memory: 16131 loss: 1.2329 loss_prob: 0.6722 loss_thr: 0.4472 loss_db: 0.1135 2022/10/26 04:56:26 - mmengine - INFO - Epoch(train) [735][20/63] lr: 1.5074e-03 eta: 5:57:14 time: 0.5373 data_time: 0.0148 memory: 16131 loss: 1.1621 loss_prob: 0.6185 loss_thr: 0.4384 loss_db: 0.1052 2022/10/26 04:56:29 - mmengine - INFO - Epoch(train) [735][25/63] lr: 1.5074e-03 eta: 5:57:14 time: 0.5676 data_time: 0.0248 memory: 16131 loss: 1.1985 loss_prob: 0.6440 loss_thr: 0.4466 loss_db: 0.1079 2022/10/26 04:56:31 - mmengine - INFO - Epoch(train) [735][30/63] lr: 1.5074e-03 eta: 5:57:06 time: 0.5849 data_time: 0.0332 memory: 16131 loss: 1.3481 loss_prob: 0.7569 loss_thr: 0.4704 loss_db: 0.1209 2022/10/26 04:56:34 - mmengine - INFO - Epoch(train) [735][35/63] lr: 1.5074e-03 eta: 5:57:06 time: 0.5567 data_time: 0.0270 memory: 16131 loss: 1.2284 loss_prob: 0.6745 loss_thr: 0.4438 loss_db: 0.1101 2022/10/26 04:56:37 - mmengine - INFO - Epoch(train) [735][40/63] lr: 1.5074e-03 eta: 5:56:57 time: 0.5143 data_time: 0.0139 memory: 16131 loss: 1.1365 loss_prob: 0.6035 loss_thr: 0.4289 loss_db: 0.1041 2022/10/26 04:56:39 - mmengine - INFO - Epoch(train) [735][45/63] lr: 1.5074e-03 eta: 5:56:57 time: 0.5084 data_time: 0.0061 memory: 16131 loss: 1.1298 loss_prob: 0.6048 loss_thr: 0.4223 loss_db: 0.1027 2022/10/26 04:56:42 - mmengine - INFO - Epoch(train) [735][50/63] lr: 1.5074e-03 eta: 5:56:48 time: 0.5258 data_time: 0.0168 memory: 16131 loss: 1.1100 loss_prob: 0.5885 loss_thr: 0.4212 loss_db: 0.1003 2022/10/26 04:56:45 - mmengine - INFO - Epoch(train) [735][55/63] lr: 1.5074e-03 eta: 5:56:48 time: 0.5284 data_time: 0.0245 memory: 16131 loss: 1.1410 loss_prob: 0.6146 loss_thr: 0.4219 loss_db: 0.1045 2022/10/26 04:56:47 - mmengine - INFO - Epoch(train) [735][60/63] lr: 1.5074e-03 eta: 5:56:40 time: 0.5540 data_time: 0.0147 memory: 16131 loss: 1.1138 loss_prob: 0.5929 loss_thr: 0.4199 loss_db: 0.1009 2022/10/26 04:56:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:56:53 - mmengine - INFO - Epoch(train) [736][5/63] lr: 1.5045e-03 eta: 5:56:40 time: 0.7089 data_time: 0.2014 memory: 16131 loss: 1.1715 loss_prob: 0.6239 loss_thr: 0.4384 loss_db: 0.1091 2022/10/26 04:56:56 - mmengine - INFO - Epoch(train) [736][10/63] lr: 1.5045e-03 eta: 5:56:29 time: 0.7364 data_time: 0.1960 memory: 16131 loss: 1.1970 loss_prob: 0.6549 loss_thr: 0.4307 loss_db: 0.1114 2022/10/26 04:56:59 - mmengine - INFO - Epoch(train) [736][15/63] lr: 1.5045e-03 eta: 5:56:29 time: 0.5094 data_time: 0.0056 memory: 16131 loss: 1.2046 loss_prob: 0.6477 loss_thr: 0.4481 loss_db: 0.1088 2022/10/26 04:57:01 - mmengine - INFO - Epoch(train) [736][20/63] lr: 1.5045e-03 eta: 5:56:20 time: 0.4737 data_time: 0.0050 memory: 16131 loss: 1.1330 loss_prob: 0.5956 loss_thr: 0.4348 loss_db: 0.1026 2022/10/26 04:57:04 - mmengine - INFO - Epoch(train) [736][25/63] lr: 1.5045e-03 eta: 5:56:20 time: 0.5026 data_time: 0.0323 memory: 16131 loss: 1.1223 loss_prob: 0.6019 loss_thr: 0.4172 loss_db: 0.1032 2022/10/26 04:57:06 - mmengine - INFO - Epoch(train) [736][30/63] lr: 1.5045e-03 eta: 5:56:12 time: 0.5238 data_time: 0.0345 memory: 16131 loss: 1.1619 loss_prob: 0.6296 loss_thr: 0.4249 loss_db: 0.1075 2022/10/26 04:57:08 - mmengine - INFO - Epoch(train) [736][35/63] lr: 1.5045e-03 eta: 5:56:12 time: 0.4903 data_time: 0.0071 memory: 16131 loss: 1.0774 loss_prob: 0.5660 loss_thr: 0.4143 loss_db: 0.0971 2022/10/26 04:57:11 - mmengine - INFO - Epoch(train) [736][40/63] lr: 1.5045e-03 eta: 5:56:03 time: 0.4809 data_time: 0.0048 memory: 16131 loss: 1.0190 loss_prob: 0.5306 loss_thr: 0.3965 loss_db: 0.0919 2022/10/26 04:57:13 - mmengine - INFO - Epoch(train) [736][45/63] lr: 1.5045e-03 eta: 5:56:03 time: 0.5003 data_time: 0.0060 memory: 16131 loss: 1.0255 loss_prob: 0.5386 loss_thr: 0.3936 loss_db: 0.0933 2022/10/26 04:57:16 - mmengine - INFO - Epoch(train) [736][50/63] lr: 1.5045e-03 eta: 5:55:54 time: 0.5154 data_time: 0.0228 memory: 16131 loss: 1.1215 loss_prob: 0.5991 loss_thr: 0.4200 loss_db: 0.1024 2022/10/26 04:57:19 - mmengine - INFO - Epoch(train) [736][55/63] lr: 1.5045e-03 eta: 5:55:54 time: 0.5369 data_time: 0.0223 memory: 16131 loss: 1.1632 loss_prob: 0.6245 loss_thr: 0.4315 loss_db: 0.1071 2022/10/26 04:57:22 - mmengine - INFO - Epoch(train) [736][60/63] lr: 1.5045e-03 eta: 5:55:46 time: 0.5499 data_time: 0.0094 memory: 16131 loss: 1.2040 loss_prob: 0.6550 loss_thr: 0.4404 loss_db: 0.1086 2022/10/26 04:57:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:57:27 - mmengine - INFO - Epoch(train) [737][5/63] lr: 1.5016e-03 eta: 5:55:46 time: 0.6762 data_time: 0.2004 memory: 16131 loss: 1.2707 loss_prob: 0.6932 loss_thr: 0.4535 loss_db: 0.1241 2022/10/26 04:57:30 - mmengine - INFO - Epoch(train) [737][10/63] lr: 1.5016e-03 eta: 5:55:35 time: 0.7103 data_time: 0.1997 memory: 16131 loss: 1.2965 loss_prob: 0.7181 loss_thr: 0.4522 loss_db: 0.1262 2022/10/26 04:57:32 - mmengine - INFO - Epoch(train) [737][15/63] lr: 1.5016e-03 eta: 5:55:35 time: 0.5097 data_time: 0.0142 memory: 16131 loss: 1.2526 loss_prob: 0.6916 loss_thr: 0.4473 loss_db: 0.1137 2022/10/26 04:57:35 - mmengine - INFO - Epoch(train) [737][20/63] lr: 1.5016e-03 eta: 5:55:26 time: 0.5122 data_time: 0.0128 memory: 16131 loss: 1.2297 loss_prob: 0.6753 loss_thr: 0.4402 loss_db: 0.1142 2022/10/26 04:57:38 - mmengine - INFO - Epoch(train) [737][25/63] lr: 1.5016e-03 eta: 5:55:26 time: 0.5215 data_time: 0.0149 memory: 16131 loss: 1.2237 loss_prob: 0.6664 loss_thr: 0.4419 loss_db: 0.1154 2022/10/26 04:57:40 - mmengine - INFO - Epoch(train) [737][30/63] lr: 1.5016e-03 eta: 5:55:17 time: 0.5235 data_time: 0.0330 memory: 16131 loss: 1.2385 loss_prob: 0.6784 loss_thr: 0.4461 loss_db: 0.1140 2022/10/26 04:57:43 - mmengine - INFO - Epoch(train) [737][35/63] lr: 1.5016e-03 eta: 5:55:17 time: 0.4994 data_time: 0.0236 memory: 16131 loss: 1.1438 loss_prob: 0.6183 loss_thr: 0.4222 loss_db: 0.1033 2022/10/26 04:57:45 - mmengine - INFO - Epoch(train) [737][40/63] lr: 1.5016e-03 eta: 5:55:09 time: 0.5141 data_time: 0.0072 memory: 16131 loss: 1.1072 loss_prob: 0.5965 loss_thr: 0.4093 loss_db: 0.1014 2022/10/26 04:57:48 - mmengine - INFO - Epoch(train) [737][45/63] lr: 1.5016e-03 eta: 5:55:09 time: 0.5473 data_time: 0.0071 memory: 16131 loss: 1.2668 loss_prob: 0.7108 loss_thr: 0.4380 loss_db: 0.1181 2022/10/26 04:57:51 - mmengine - INFO - Epoch(train) [737][50/63] lr: 1.5016e-03 eta: 5:55:00 time: 0.5311 data_time: 0.0202 memory: 16131 loss: 1.2611 loss_prob: 0.6973 loss_thr: 0.4472 loss_db: 0.1166 2022/10/26 04:57:53 - mmengine - INFO - Epoch(train) [737][55/63] lr: 1.5016e-03 eta: 5:55:00 time: 0.5112 data_time: 0.0202 memory: 16131 loss: 1.1619 loss_prob: 0.6078 loss_thr: 0.4487 loss_db: 0.1054 2022/10/26 04:57:56 - mmengine - INFO - Epoch(train) [737][60/63] lr: 1.5016e-03 eta: 5:54:52 time: 0.5440 data_time: 0.0062 memory: 16131 loss: 1.1477 loss_prob: 0.6053 loss_thr: 0.4380 loss_db: 0.1044 2022/10/26 04:57:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:58:02 - mmengine - INFO - Epoch(train) [738][5/63] lr: 1.4987e-03 eta: 5:54:52 time: 0.7463 data_time: 0.1727 memory: 16131 loss: 1.1113 loss_prob: 0.5891 loss_thr: 0.4223 loss_db: 0.0999 2022/10/26 04:58:05 - mmengine - INFO - Epoch(train) [738][10/63] lr: 1.4987e-03 eta: 5:54:41 time: 0.7497 data_time: 0.1713 memory: 16131 loss: 1.1416 loss_prob: 0.6021 loss_thr: 0.4350 loss_db: 0.1046 2022/10/26 04:58:08 - mmengine - INFO - Epoch(train) [738][15/63] lr: 1.4987e-03 eta: 5:54:41 time: 0.5130 data_time: 0.0046 memory: 16131 loss: 1.1416 loss_prob: 0.6027 loss_thr: 0.4337 loss_db: 0.1052 2022/10/26 04:58:10 - mmengine - INFO - Epoch(train) [738][20/63] lr: 1.4987e-03 eta: 5:54:32 time: 0.5412 data_time: 0.0069 memory: 16131 loss: 1.1744 loss_prob: 0.6285 loss_thr: 0.4377 loss_db: 0.1082 2022/10/26 04:58:13 - mmengine - INFO - Epoch(train) [738][25/63] lr: 1.4987e-03 eta: 5:54:32 time: 0.5399 data_time: 0.0180 memory: 16131 loss: 1.2058 loss_prob: 0.6451 loss_thr: 0.4518 loss_db: 0.1089 2022/10/26 04:58:15 - mmengine - INFO - Epoch(train) [738][30/63] lr: 1.4987e-03 eta: 5:54:24 time: 0.5007 data_time: 0.0301 memory: 16131 loss: 1.2385 loss_prob: 0.6717 loss_thr: 0.4537 loss_db: 0.1132 2022/10/26 04:58:18 - mmengine - INFO - Epoch(train) [738][35/63] lr: 1.4987e-03 eta: 5:54:24 time: 0.5386 data_time: 0.0196 memory: 16131 loss: 1.3006 loss_prob: 0.7219 loss_thr: 0.4578 loss_db: 0.1209 2022/10/26 04:58:21 - mmengine - INFO - Epoch(train) [738][40/63] lr: 1.4987e-03 eta: 5:54:15 time: 0.5786 data_time: 0.0087 memory: 16131 loss: 1.3198 loss_prob: 0.7310 loss_thr: 0.4671 loss_db: 0.1218 2022/10/26 04:58:24 - mmengine - INFO - Epoch(train) [738][45/63] lr: 1.4987e-03 eta: 5:54:15 time: 0.5870 data_time: 0.0150 memory: 16131 loss: 1.1682 loss_prob: 0.6274 loss_thr: 0.4331 loss_db: 0.1078 2022/10/26 04:58:27 - mmengine - INFO - Epoch(train) [738][50/63] lr: 1.4987e-03 eta: 5:54:07 time: 0.5563 data_time: 0.0188 memory: 16131 loss: 1.1246 loss_prob: 0.6010 loss_thr: 0.4233 loss_db: 0.1004 2022/10/26 04:58:29 - mmengine - INFO - Epoch(train) [738][55/63] lr: 1.4987e-03 eta: 5:54:07 time: 0.5088 data_time: 0.0204 memory: 16131 loss: 1.1558 loss_prob: 0.6207 loss_thr: 0.4335 loss_db: 0.1016 2022/10/26 04:58:32 - mmengine - INFO - Epoch(train) [738][60/63] lr: 1.4987e-03 eta: 5:53:58 time: 0.5001 data_time: 0.0144 memory: 16131 loss: 1.1331 loss_prob: 0.5972 loss_thr: 0.4334 loss_db: 0.1025 2022/10/26 04:58:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:58:39 - mmengine - INFO - Epoch(train) [739][5/63] lr: 1.4957e-03 eta: 5:53:58 time: 0.7739 data_time: 0.1985 memory: 16131 loss: 1.1690 loss_prob: 0.6347 loss_thr: 0.4259 loss_db: 0.1084 2022/10/26 04:58:41 - mmengine - INFO - Epoch(train) [739][10/63] lr: 1.4957e-03 eta: 5:53:48 time: 0.8250 data_time: 0.1968 memory: 16131 loss: 1.1155 loss_prob: 0.5971 loss_thr: 0.4177 loss_db: 0.1007 2022/10/26 04:58:44 - mmengine - INFO - Epoch(train) [739][15/63] lr: 1.4957e-03 eta: 5:53:48 time: 0.5318 data_time: 0.0048 memory: 16131 loss: 1.1110 loss_prob: 0.6018 loss_thr: 0.4054 loss_db: 0.1038 2022/10/26 04:58:46 - mmengine - INFO - Epoch(train) [739][20/63] lr: 1.4957e-03 eta: 5:53:39 time: 0.5078 data_time: 0.0065 memory: 16131 loss: 1.1119 loss_prob: 0.5920 loss_thr: 0.4181 loss_db: 0.1019 2022/10/26 04:58:49 - mmengine - INFO - Epoch(train) [739][25/63] lr: 1.4957e-03 eta: 5:53:39 time: 0.5506 data_time: 0.0166 memory: 16131 loss: 1.1387 loss_prob: 0.6034 loss_thr: 0.4333 loss_db: 0.1020 2022/10/26 04:58:52 - mmengine - INFO - Epoch(train) [739][30/63] lr: 1.4957e-03 eta: 5:53:31 time: 0.5690 data_time: 0.0313 memory: 16131 loss: 1.1744 loss_prob: 0.6322 loss_thr: 0.4346 loss_db: 0.1076 2022/10/26 04:58:55 - mmengine - INFO - Epoch(train) [739][35/63] lr: 1.4957e-03 eta: 5:53:31 time: 0.5312 data_time: 0.0220 memory: 16131 loss: 1.1804 loss_prob: 0.6341 loss_thr: 0.4378 loss_db: 0.1085 2022/10/26 04:58:57 - mmengine - INFO - Epoch(train) [739][40/63] lr: 1.4957e-03 eta: 5:53:22 time: 0.5086 data_time: 0.0081 memory: 16131 loss: 1.2549 loss_prob: 0.6849 loss_thr: 0.4527 loss_db: 0.1173 2022/10/26 04:59:00 - mmengine - INFO - Epoch(train) [739][45/63] lr: 1.4957e-03 eta: 5:53:22 time: 0.5069 data_time: 0.0113 memory: 16131 loss: 1.2871 loss_prob: 0.7119 loss_thr: 0.4555 loss_db: 0.1197 2022/10/26 04:59:02 - mmengine - INFO - Epoch(train) [739][50/63] lr: 1.4957e-03 eta: 5:53:14 time: 0.4999 data_time: 0.0155 memory: 16131 loss: 1.1773 loss_prob: 0.6390 loss_thr: 0.4290 loss_db: 0.1093 2022/10/26 04:59:05 - mmengine - INFO - Epoch(train) [739][55/63] lr: 1.4957e-03 eta: 5:53:14 time: 0.5035 data_time: 0.0273 memory: 16131 loss: 1.1794 loss_prob: 0.6366 loss_thr: 0.4314 loss_db: 0.1113 2022/10/26 04:59:07 - mmengine - INFO - Epoch(train) [739][60/63] lr: 1.4957e-03 eta: 5:53:05 time: 0.5010 data_time: 0.0218 memory: 16131 loss: 1.2340 loss_prob: 0.6600 loss_thr: 0.4591 loss_db: 0.1149 2022/10/26 04:59:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:59:14 - mmengine - INFO - Epoch(train) [740][5/63] lr: 1.4928e-03 eta: 5:53:05 time: 0.8207 data_time: 0.2357 memory: 16131 loss: 1.0688 loss_prob: 0.5608 loss_thr: 0.4105 loss_db: 0.0975 2022/10/26 04:59:17 - mmengine - INFO - Epoch(train) [740][10/63] lr: 1.4928e-03 eta: 5:52:55 time: 0.8335 data_time: 0.2359 memory: 16131 loss: 1.0809 loss_prob: 0.5688 loss_thr: 0.4141 loss_db: 0.0980 2022/10/26 04:59:20 - mmengine - INFO - Epoch(train) [740][15/63] lr: 1.4928e-03 eta: 5:52:55 time: 0.5222 data_time: 0.0121 memory: 16131 loss: 1.1049 loss_prob: 0.5923 loss_thr: 0.4122 loss_db: 0.1004 2022/10/26 04:59:22 - mmengine - INFO - Epoch(train) [740][20/63] lr: 1.4928e-03 eta: 5:52:46 time: 0.5257 data_time: 0.0084 memory: 16131 loss: 1.0944 loss_prob: 0.5737 loss_thr: 0.4235 loss_db: 0.0972 2022/10/26 04:59:25 - mmengine - INFO - Epoch(train) [740][25/63] lr: 1.4928e-03 eta: 5:52:46 time: 0.5380 data_time: 0.0272 memory: 16131 loss: 1.1521 loss_prob: 0.5967 loss_thr: 0.4539 loss_db: 0.1016 2022/10/26 04:59:28 - mmengine - INFO - Epoch(train) [740][30/63] lr: 1.4928e-03 eta: 5:52:38 time: 0.5579 data_time: 0.0329 memory: 16131 loss: 1.2401 loss_prob: 0.6668 loss_thr: 0.4605 loss_db: 0.1128 2022/10/26 04:59:30 - mmengine - INFO - Epoch(train) [740][35/63] lr: 1.4928e-03 eta: 5:52:38 time: 0.5135 data_time: 0.0109 memory: 16131 loss: 1.1992 loss_prob: 0.6617 loss_thr: 0.4293 loss_db: 0.1081 2022/10/26 04:59:33 - mmengine - INFO - Epoch(train) [740][40/63] lr: 1.4928e-03 eta: 5:52:29 time: 0.4965 data_time: 0.0057 memory: 16131 loss: 1.1859 loss_prob: 0.6686 loss_thr: 0.4123 loss_db: 0.1050 2022/10/26 04:59:35 - mmengine - INFO - Epoch(train) [740][45/63] lr: 1.4928e-03 eta: 5:52:29 time: 0.5153 data_time: 0.0066 memory: 16131 loss: 1.2347 loss_prob: 0.7011 loss_thr: 0.4225 loss_db: 0.1111 2022/10/26 04:59:38 - mmengine - INFO - Epoch(train) [740][50/63] lr: 1.4928e-03 eta: 5:52:21 time: 0.5474 data_time: 0.0221 memory: 16131 loss: 1.1254 loss_prob: 0.6171 loss_thr: 0.4052 loss_db: 0.1031 2022/10/26 04:59:41 - mmengine - INFO - Epoch(train) [740][55/63] lr: 1.4928e-03 eta: 5:52:21 time: 0.5369 data_time: 0.0237 memory: 16131 loss: 1.0871 loss_prob: 0.5866 loss_thr: 0.3985 loss_db: 0.1020 2022/10/26 04:59:43 - mmengine - INFO - Epoch(train) [740][60/63] lr: 1.4928e-03 eta: 5:52:12 time: 0.5064 data_time: 0.0087 memory: 16131 loss: 1.2898 loss_prob: 0.7060 loss_thr: 0.4651 loss_db: 0.1187 2022/10/26 04:59:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 04:59:45 - mmengine - INFO - Saving checkpoint at 740 epochs 2022/10/26 04:59:51 - mmengine - INFO - Epoch(val) [740][5/32] eta: 5:52:12 time: 0.5229 data_time: 0.0685 memory: 16131 2022/10/26 04:59:54 - mmengine - INFO - Epoch(val) [740][10/32] eta: 0:00:12 time: 0.5837 data_time: 0.0924 memory: 15724 2022/10/26 04:59:57 - mmengine - INFO - Epoch(val) [740][15/32] eta: 0:00:12 time: 0.5297 data_time: 0.0444 memory: 15724 2022/10/26 04:59:59 - mmengine - INFO - Epoch(val) [740][20/32] eta: 0:00:06 time: 0.5247 data_time: 0.0442 memory: 15724 2022/10/26 05:00:02 - mmengine - INFO - Epoch(val) [740][25/32] eta: 0:00:06 time: 0.5668 data_time: 0.0576 memory: 15724 2022/10/26 05:00:05 - mmengine - INFO - Epoch(val) [740][30/32] eta: 0:00:01 time: 0.5419 data_time: 0.0347 memory: 15724 2022/10/26 05:00:05 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8252, precision: 0.7561, hmean: 0.7891 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8252, precision: 0.8217, hmean: 0.8234 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8233, precision: 0.8533, hmean: 0.8380 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8195, precision: 0.8796, hmean: 0.8485 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7935, precision: 0.9055, hmean: 0.8458 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6558, precision: 0.9426, hmean: 0.7734 2022/10/26 05:00:05 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0467, precision: 1.0000, hmean: 0.0892 2022/10/26 05:00:05 - mmengine - INFO - Epoch(val) [740][32/32] icdar/precision: 0.8796 icdar/recall: 0.8195 icdar/hmean: 0.8485 2022/10/26 05:00:10 - mmengine - INFO - Epoch(train) [741][5/63] lr: 1.4899e-03 eta: 0:00:01 time: 0.7377 data_time: 0.1855 memory: 16131 loss: 1.2356 loss_prob: 0.6719 loss_thr: 0.4515 loss_db: 0.1122 2022/10/26 05:00:13 - mmengine - INFO - Epoch(train) [741][10/63] lr: 1.4899e-03 eta: 5:52:01 time: 0.7823 data_time: 0.1826 memory: 16131 loss: 1.0253 loss_prob: 0.5344 loss_thr: 0.3981 loss_db: 0.0928 2022/10/26 05:00:16 - mmengine - INFO - Epoch(train) [741][15/63] lr: 1.4899e-03 eta: 5:52:01 time: 0.5662 data_time: 0.0091 memory: 16131 loss: 1.1477 loss_prob: 0.6081 loss_thr: 0.4326 loss_db: 0.1070 2022/10/26 05:00:19 - mmengine - INFO - Epoch(train) [741][20/63] lr: 1.4899e-03 eta: 5:51:53 time: 0.5384 data_time: 0.0096 memory: 16131 loss: 1.1969 loss_prob: 0.6453 loss_thr: 0.4401 loss_db: 0.1115 2022/10/26 05:00:22 - mmengine - INFO - Epoch(train) [741][25/63] lr: 1.4899e-03 eta: 5:51:53 time: 0.5692 data_time: 0.0219 memory: 16131 loss: 1.1784 loss_prob: 0.6417 loss_thr: 0.4326 loss_db: 0.1041 2022/10/26 05:00:24 - mmengine - INFO - Epoch(train) [741][30/63] lr: 1.4899e-03 eta: 5:51:45 time: 0.5780 data_time: 0.0321 memory: 16131 loss: 1.2463 loss_prob: 0.7070 loss_thr: 0.4296 loss_db: 0.1097 2022/10/26 05:00:27 - mmengine - INFO - Epoch(train) [741][35/63] lr: 1.4899e-03 eta: 5:51:45 time: 0.5573 data_time: 0.0158 memory: 16131 loss: 1.1984 loss_prob: 0.6735 loss_thr: 0.4169 loss_db: 0.1079 2022/10/26 05:00:30 - mmengine - INFO - Epoch(train) [741][40/63] lr: 1.4899e-03 eta: 5:51:36 time: 0.5696 data_time: 0.0104 memory: 16131 loss: 1.1503 loss_prob: 0.6174 loss_thr: 0.4276 loss_db: 0.1053 2022/10/26 05:00:33 - mmengine - INFO - Epoch(train) [741][45/63] lr: 1.4899e-03 eta: 5:51:36 time: 0.5719 data_time: 0.0118 memory: 16131 loss: 1.1770 loss_prob: 0.6373 loss_thr: 0.4306 loss_db: 0.1091 2022/10/26 05:00:36 - mmengine - INFO - Epoch(train) [741][50/63] lr: 1.4899e-03 eta: 5:51:28 time: 0.5460 data_time: 0.0167 memory: 16131 loss: 1.2065 loss_prob: 0.6550 loss_thr: 0.4407 loss_db: 0.1109 2022/10/26 05:00:38 - mmengine - INFO - Epoch(train) [741][55/63] lr: 1.4899e-03 eta: 5:51:28 time: 0.5126 data_time: 0.0222 memory: 16131 loss: 1.2009 loss_prob: 0.6519 loss_thr: 0.4394 loss_db: 0.1096 2022/10/26 05:00:41 - mmengine - INFO - Epoch(train) [741][60/63] lr: 1.4899e-03 eta: 5:51:19 time: 0.5259 data_time: 0.0125 memory: 16131 loss: 1.1152 loss_prob: 0.6021 loss_thr: 0.4112 loss_db: 0.1019 2022/10/26 05:00:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:00:47 - mmengine - INFO - Epoch(train) [742][5/63] lr: 1.4870e-03 eta: 5:51:19 time: 0.7033 data_time: 0.2013 memory: 16131 loss: 1.2069 loss_prob: 0.6684 loss_thr: 0.4247 loss_db: 0.1138 2022/10/26 05:00:49 - mmengine - INFO - Epoch(train) [742][10/63] lr: 1.4870e-03 eta: 5:51:08 time: 0.6976 data_time: 0.1997 memory: 16131 loss: 1.1720 loss_prob: 0.6369 loss_thr: 0.4269 loss_db: 0.1081 2022/10/26 05:00:52 - mmengine - INFO - Epoch(train) [742][15/63] lr: 1.4870e-03 eta: 5:51:08 time: 0.4997 data_time: 0.0080 memory: 16131 loss: 1.1533 loss_prob: 0.6177 loss_thr: 0.4280 loss_db: 0.1076 2022/10/26 05:00:54 - mmengine - INFO - Epoch(train) [742][20/63] lr: 1.4870e-03 eta: 5:51:00 time: 0.5086 data_time: 0.0066 memory: 16131 loss: 1.1939 loss_prob: 0.6493 loss_thr: 0.4317 loss_db: 0.1130 2022/10/26 05:00:57 - mmengine - INFO - Epoch(train) [742][25/63] lr: 1.4870e-03 eta: 5:51:00 time: 0.5064 data_time: 0.0098 memory: 16131 loss: 1.1329 loss_prob: 0.6060 loss_thr: 0.4237 loss_db: 0.1031 2022/10/26 05:01:00 - mmengine - INFO - Epoch(train) [742][30/63] lr: 1.4870e-03 eta: 5:50:51 time: 0.5284 data_time: 0.0336 memory: 16131 loss: 1.0931 loss_prob: 0.5795 loss_thr: 0.4126 loss_db: 0.1010 2022/10/26 05:01:02 - mmengine - INFO - Epoch(train) [742][35/63] lr: 1.4870e-03 eta: 5:50:51 time: 0.5331 data_time: 0.0325 memory: 16131 loss: 1.2108 loss_prob: 0.6574 loss_thr: 0.4414 loss_db: 0.1120 2022/10/26 05:01:05 - mmengine - INFO - Epoch(train) [742][40/63] lr: 1.4870e-03 eta: 5:50:43 time: 0.5382 data_time: 0.0088 memory: 16131 loss: 1.2908 loss_prob: 0.7125 loss_thr: 0.4580 loss_db: 0.1202 2022/10/26 05:01:07 - mmengine - INFO - Epoch(train) [742][45/63] lr: 1.4870e-03 eta: 5:50:43 time: 0.5242 data_time: 0.0079 memory: 16131 loss: 1.2243 loss_prob: 0.6763 loss_thr: 0.4341 loss_db: 0.1138 2022/10/26 05:01:10 - mmengine - INFO - Epoch(train) [742][50/63] lr: 1.4870e-03 eta: 5:50:34 time: 0.5321 data_time: 0.0255 memory: 16131 loss: 1.1770 loss_prob: 0.6428 loss_thr: 0.4272 loss_db: 0.1069 2022/10/26 05:01:13 - mmengine - INFO - Epoch(train) [742][55/63] lr: 1.4870e-03 eta: 5:50:34 time: 0.5618 data_time: 0.0248 memory: 16131 loss: 1.1444 loss_prob: 0.6064 loss_thr: 0.4349 loss_db: 0.1032 2022/10/26 05:01:16 - mmengine - INFO - Epoch(train) [742][60/63] lr: 1.4870e-03 eta: 5:50:26 time: 0.5390 data_time: 0.0093 memory: 16131 loss: 1.1603 loss_prob: 0.6194 loss_thr: 0.4343 loss_db: 0.1066 2022/10/26 05:01:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:01:22 - mmengine - INFO - Epoch(train) [743][5/63] lr: 1.4841e-03 eta: 5:50:26 time: 0.7147 data_time: 0.1974 memory: 16131 loss: 1.1593 loss_prob: 0.6190 loss_thr: 0.4333 loss_db: 0.1070 2022/10/26 05:01:24 - mmengine - INFO - Epoch(train) [743][10/63] lr: 1.4841e-03 eta: 5:50:15 time: 0.7409 data_time: 0.1975 memory: 16131 loss: 1.1598 loss_prob: 0.6197 loss_thr: 0.4357 loss_db: 0.1045 2022/10/26 05:01:27 - mmengine - INFO - Epoch(train) [743][15/63] lr: 1.4841e-03 eta: 5:50:15 time: 0.5177 data_time: 0.0067 memory: 16131 loss: 1.1061 loss_prob: 0.5910 loss_thr: 0.4139 loss_db: 0.1012 2022/10/26 05:01:29 - mmengine - INFO - Epoch(train) [743][20/63] lr: 1.4841e-03 eta: 5:50:07 time: 0.5312 data_time: 0.0086 memory: 16131 loss: 1.0513 loss_prob: 0.5549 loss_thr: 0.3979 loss_db: 0.0985 2022/10/26 05:01:32 - mmengine - INFO - Epoch(train) [743][25/63] lr: 1.4841e-03 eta: 5:50:07 time: 0.5164 data_time: 0.0295 memory: 16131 loss: 1.0759 loss_prob: 0.5668 loss_thr: 0.4088 loss_db: 0.1002 2022/10/26 05:01:34 - mmengine - INFO - Epoch(train) [743][30/63] lr: 1.4841e-03 eta: 5:49:58 time: 0.5031 data_time: 0.0297 memory: 16131 loss: 1.0661 loss_prob: 0.5681 loss_thr: 0.3983 loss_db: 0.0998 2022/10/26 05:01:37 - mmengine - INFO - Epoch(train) [743][35/63] lr: 1.4841e-03 eta: 5:49:58 time: 0.5090 data_time: 0.0112 memory: 16131 loss: 1.1180 loss_prob: 0.5945 loss_thr: 0.4221 loss_db: 0.1014 2022/10/26 05:01:41 - mmengine - INFO - Epoch(train) [743][40/63] lr: 1.4841e-03 eta: 5:49:50 time: 0.6068 data_time: 0.0077 memory: 16131 loss: 1.1907 loss_prob: 0.6399 loss_thr: 0.4429 loss_db: 0.1079 2022/10/26 05:01:44 - mmengine - INFO - Epoch(train) [743][45/63] lr: 1.4841e-03 eta: 5:49:50 time: 0.6543 data_time: 0.0075 memory: 16131 loss: 1.2816 loss_prob: 0.7119 loss_thr: 0.4515 loss_db: 0.1182 2022/10/26 05:01:47 - mmengine - INFO - Epoch(train) [743][50/63] lr: 1.4841e-03 eta: 5:49:42 time: 0.6200 data_time: 0.0222 memory: 16131 loss: 1.2648 loss_prob: 0.7111 loss_thr: 0.4345 loss_db: 0.1192 2022/10/26 05:01:49 - mmengine - INFO - Epoch(train) [743][55/63] lr: 1.4841e-03 eta: 5:49:42 time: 0.5721 data_time: 0.0210 memory: 16131 loss: 1.1808 loss_prob: 0.6426 loss_thr: 0.4287 loss_db: 0.1095 2022/10/26 05:01:52 - mmengine - INFO - Epoch(train) [743][60/63] lr: 1.4841e-03 eta: 5:49:33 time: 0.5169 data_time: 0.0080 memory: 16131 loss: 1.1442 loss_prob: 0.6104 loss_thr: 0.4307 loss_db: 0.1030 2022/10/26 05:01:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:01:58 - mmengine - INFO - Epoch(train) [744][5/63] lr: 1.4811e-03 eta: 5:49:33 time: 0.6808 data_time: 0.1907 memory: 16131 loss: 1.1201 loss_prob: 0.5959 loss_thr: 0.4218 loss_db: 0.1023 2022/10/26 05:02:01 - mmengine - INFO - Epoch(train) [744][10/63] lr: 1.4811e-03 eta: 5:49:23 time: 0.7426 data_time: 0.1956 memory: 16131 loss: 1.1262 loss_prob: 0.5937 loss_thr: 0.4292 loss_db: 0.1033 2022/10/26 05:02:03 - mmengine - INFO - Epoch(train) [744][15/63] lr: 1.4811e-03 eta: 5:49:23 time: 0.5355 data_time: 0.0105 memory: 16131 loss: 1.0972 loss_prob: 0.5838 loss_thr: 0.4107 loss_db: 0.1027 2022/10/26 05:02:06 - mmengine - INFO - Epoch(train) [744][20/63] lr: 1.4811e-03 eta: 5:49:14 time: 0.4983 data_time: 0.0061 memory: 16131 loss: 1.0085 loss_prob: 0.5338 loss_thr: 0.3834 loss_db: 0.0912 2022/10/26 05:02:08 - mmengine - INFO - Epoch(train) [744][25/63] lr: 1.4811e-03 eta: 5:49:14 time: 0.5205 data_time: 0.0337 memory: 16131 loss: 1.1087 loss_prob: 0.5869 loss_thr: 0.4220 loss_db: 0.0998 2022/10/26 05:02:11 - mmengine - INFO - Epoch(train) [744][30/63] lr: 1.4811e-03 eta: 5:49:06 time: 0.5426 data_time: 0.0325 memory: 16131 loss: 1.1704 loss_prob: 0.6131 loss_thr: 0.4521 loss_db: 0.1051 2022/10/26 05:02:14 - mmengine - INFO - Epoch(train) [744][35/63] lr: 1.4811e-03 eta: 5:49:06 time: 0.5660 data_time: 0.0048 memory: 16131 loss: 1.0444 loss_prob: 0.5455 loss_thr: 0.4040 loss_db: 0.0949 2022/10/26 05:02:17 - mmengine - INFO - Epoch(train) [744][40/63] lr: 1.4811e-03 eta: 5:48:57 time: 0.5617 data_time: 0.0062 memory: 16131 loss: 1.0571 loss_prob: 0.5634 loss_thr: 0.3953 loss_db: 0.0984 2022/10/26 05:02:19 - mmengine - INFO - Epoch(train) [744][45/63] lr: 1.4811e-03 eta: 5:48:57 time: 0.5476 data_time: 0.0092 memory: 16131 loss: 1.1689 loss_prob: 0.6265 loss_thr: 0.4356 loss_db: 0.1068 2022/10/26 05:02:22 - mmengine - INFO - Epoch(train) [744][50/63] lr: 1.4811e-03 eta: 5:48:49 time: 0.5404 data_time: 0.0237 memory: 16131 loss: 1.2991 loss_prob: 0.7104 loss_thr: 0.4708 loss_db: 0.1178 2022/10/26 05:02:25 - mmengine - INFO - Epoch(train) [744][55/63] lr: 1.4811e-03 eta: 5:48:49 time: 0.5127 data_time: 0.0206 memory: 16131 loss: 1.2909 loss_prob: 0.7142 loss_thr: 0.4569 loss_db: 0.1198 2022/10/26 05:02:27 - mmengine - INFO - Epoch(train) [744][60/63] lr: 1.4811e-03 eta: 5:48:40 time: 0.5020 data_time: 0.0045 memory: 16131 loss: 1.1434 loss_prob: 0.6163 loss_thr: 0.4198 loss_db: 0.1073 2022/10/26 05:02:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:02:33 - mmengine - INFO - Epoch(train) [745][5/63] lr: 1.4782e-03 eta: 5:48:40 time: 0.7347 data_time: 0.1914 memory: 16131 loss: 1.1173 loss_prob: 0.6100 loss_thr: 0.4028 loss_db: 0.1045 2022/10/26 05:02:36 - mmengine - INFO - Epoch(train) [745][10/63] lr: 1.4782e-03 eta: 5:48:29 time: 0.7419 data_time: 0.1925 memory: 16131 loss: 1.0962 loss_prob: 0.6048 loss_thr: 0.3891 loss_db: 0.1023 2022/10/26 05:02:38 - mmengine - INFO - Epoch(train) [745][15/63] lr: 1.4782e-03 eta: 5:48:29 time: 0.5030 data_time: 0.0065 memory: 16131 loss: 1.2768 loss_prob: 0.7485 loss_thr: 0.4174 loss_db: 0.1109 2022/10/26 05:02:41 - mmengine - INFO - Epoch(train) [745][20/63] lr: 1.4782e-03 eta: 5:48:21 time: 0.5568 data_time: 0.0052 memory: 16131 loss: 1.3153 loss_prob: 0.7672 loss_thr: 0.4317 loss_db: 0.1165 2022/10/26 05:02:44 - mmengine - INFO - Epoch(train) [745][25/63] lr: 1.4782e-03 eta: 5:48:21 time: 0.5672 data_time: 0.0223 memory: 16131 loss: 1.1605 loss_prob: 0.6313 loss_thr: 0.4191 loss_db: 0.1101 2022/10/26 05:02:47 - mmengine - INFO - Epoch(train) [745][30/63] lr: 1.4782e-03 eta: 5:48:13 time: 0.5260 data_time: 0.0324 memory: 16131 loss: 1.1993 loss_prob: 0.6571 loss_thr: 0.4313 loss_db: 0.1109 2022/10/26 05:02:49 - mmengine - INFO - Epoch(train) [745][35/63] lr: 1.4782e-03 eta: 5:48:13 time: 0.5204 data_time: 0.0149 memory: 16131 loss: 1.1300 loss_prob: 0.6069 loss_thr: 0.4220 loss_db: 0.1012 2022/10/26 05:02:52 - mmengine - INFO - Epoch(train) [745][40/63] lr: 1.4782e-03 eta: 5:48:04 time: 0.5258 data_time: 0.0051 memory: 16131 loss: 1.1081 loss_prob: 0.5772 loss_thr: 0.4309 loss_db: 0.0999 2022/10/26 05:02:55 - mmengine - INFO - Epoch(train) [745][45/63] lr: 1.4782e-03 eta: 5:48:04 time: 0.5193 data_time: 0.0064 memory: 16131 loss: 1.1617 loss_prob: 0.6118 loss_thr: 0.4429 loss_db: 0.1069 2022/10/26 05:02:57 - mmengine - INFO - Epoch(train) [745][50/63] lr: 1.4782e-03 eta: 5:47:56 time: 0.5344 data_time: 0.0226 memory: 16131 loss: 1.2522 loss_prob: 0.6797 loss_thr: 0.4543 loss_db: 0.1181 2022/10/26 05:03:00 - mmengine - INFO - Epoch(train) [745][55/63] lr: 1.4782e-03 eta: 5:47:56 time: 0.5161 data_time: 0.0216 memory: 16131 loss: 1.2836 loss_prob: 0.7023 loss_thr: 0.4629 loss_db: 0.1184 2022/10/26 05:03:02 - mmengine - INFO - Epoch(train) [745][60/63] lr: 1.4782e-03 eta: 5:47:47 time: 0.4878 data_time: 0.0053 memory: 16131 loss: 1.2197 loss_prob: 0.6606 loss_thr: 0.4490 loss_db: 0.1101 2022/10/26 05:03:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:03:08 - mmengine - INFO - Epoch(train) [746][5/63] lr: 1.4753e-03 eta: 5:47:47 time: 0.6816 data_time: 0.1998 memory: 16131 loss: 1.3155 loss_prob: 0.7423 loss_thr: 0.4486 loss_db: 0.1246 2022/10/26 05:03:11 - mmengine - INFO - Epoch(train) [746][10/63] lr: 1.4753e-03 eta: 5:47:36 time: 0.7267 data_time: 0.1999 memory: 16131 loss: 1.2988 loss_prob: 0.7212 loss_thr: 0.4537 loss_db: 0.1239 2022/10/26 05:03:13 - mmengine - INFO - Epoch(train) [746][15/63] lr: 1.4753e-03 eta: 5:47:36 time: 0.5143 data_time: 0.0067 memory: 16131 loss: 1.3234 loss_prob: 0.7395 loss_thr: 0.4558 loss_db: 0.1280 2022/10/26 05:03:16 - mmengine - INFO - Epoch(train) [746][20/63] lr: 1.4753e-03 eta: 5:47:27 time: 0.4986 data_time: 0.0064 memory: 16131 loss: 1.3010 loss_prob: 0.7299 loss_thr: 0.4461 loss_db: 0.1250 2022/10/26 05:03:18 - mmengine - INFO - Epoch(train) [746][25/63] lr: 1.4753e-03 eta: 5:47:27 time: 0.5199 data_time: 0.0203 memory: 16131 loss: 1.3157 loss_prob: 0.7459 loss_thr: 0.4453 loss_db: 0.1245 2022/10/26 05:03:21 - mmengine - INFO - Epoch(train) [746][30/63] lr: 1.4753e-03 eta: 5:47:19 time: 0.5232 data_time: 0.0250 memory: 16131 loss: 1.2956 loss_prob: 0.7324 loss_thr: 0.4398 loss_db: 0.1234 2022/10/26 05:03:24 - mmengine - INFO - Epoch(train) [746][35/63] lr: 1.4753e-03 eta: 5:47:19 time: 0.5174 data_time: 0.0160 memory: 16131 loss: 1.2206 loss_prob: 0.6613 loss_thr: 0.4454 loss_db: 0.1139 2022/10/26 05:03:26 - mmengine - INFO - Epoch(train) [746][40/63] lr: 1.4753e-03 eta: 5:47:10 time: 0.5574 data_time: 0.0183 memory: 16131 loss: 1.2294 loss_prob: 0.6622 loss_thr: 0.4535 loss_db: 0.1137 2022/10/26 05:03:29 - mmengine - INFO - Epoch(train) [746][45/63] lr: 1.4753e-03 eta: 5:47:10 time: 0.5393 data_time: 0.0149 memory: 16131 loss: 1.1859 loss_prob: 0.6341 loss_thr: 0.4433 loss_db: 0.1085 2022/10/26 05:03:32 - mmengine - INFO - Epoch(train) [746][50/63] lr: 1.4753e-03 eta: 5:47:02 time: 0.5804 data_time: 0.0215 memory: 16131 loss: 1.2267 loss_prob: 0.6625 loss_thr: 0.4530 loss_db: 0.1112 2022/10/26 05:03:35 - mmengine - INFO - Epoch(train) [746][55/63] lr: 1.4753e-03 eta: 5:47:02 time: 0.6019 data_time: 0.0286 memory: 16131 loss: 1.1892 loss_prob: 0.6331 loss_thr: 0.4484 loss_db: 0.1077 2022/10/26 05:03:37 - mmengine - INFO - Epoch(train) [746][60/63] lr: 1.4753e-03 eta: 5:46:54 time: 0.5088 data_time: 0.0184 memory: 16131 loss: 1.1680 loss_prob: 0.6122 loss_thr: 0.4487 loss_db: 0.1071 2022/10/26 05:03:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:03:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:03:43 - mmengine - INFO - Epoch(train) [747][5/63] lr: 1.4724e-03 eta: 5:46:54 time: 0.6592 data_time: 0.1882 memory: 16131 loss: 1.2306 loss_prob: 0.6475 loss_thr: 0.4736 loss_db: 0.1095 2022/10/26 05:03:46 - mmengine - INFO - Epoch(train) [747][10/63] lr: 1.4724e-03 eta: 5:46:43 time: 0.7146 data_time: 0.1919 memory: 16131 loss: 1.1086 loss_prob: 0.5906 loss_thr: 0.4149 loss_db: 0.1031 2022/10/26 05:03:48 - mmengine - INFO - Epoch(train) [747][15/63] lr: 1.4724e-03 eta: 5:46:43 time: 0.5486 data_time: 0.0132 memory: 16131 loss: 1.1038 loss_prob: 0.5878 loss_thr: 0.4117 loss_db: 0.1043 2022/10/26 05:03:51 - mmengine - INFO - Epoch(train) [747][20/63] lr: 1.4724e-03 eta: 5:46:34 time: 0.5218 data_time: 0.0082 memory: 16131 loss: 1.1751 loss_prob: 0.6291 loss_thr: 0.4378 loss_db: 0.1083 2022/10/26 05:03:54 - mmengine - INFO - Epoch(train) [747][25/63] lr: 1.4724e-03 eta: 5:46:34 time: 0.5280 data_time: 0.0260 memory: 16131 loss: 1.3224 loss_prob: 0.7366 loss_thr: 0.4647 loss_db: 0.1211 2022/10/26 05:03:56 - mmengine - INFO - Epoch(train) [747][30/63] lr: 1.4724e-03 eta: 5:46:26 time: 0.5389 data_time: 0.0352 memory: 16131 loss: 1.3348 loss_prob: 0.7412 loss_thr: 0.4710 loss_db: 0.1227 2022/10/26 05:03:59 - mmengine - INFO - Epoch(train) [747][35/63] lr: 1.4724e-03 eta: 5:46:26 time: 0.5365 data_time: 0.0235 memory: 16131 loss: 1.2405 loss_prob: 0.6704 loss_thr: 0.4569 loss_db: 0.1132 2022/10/26 05:04:02 - mmengine - INFO - Epoch(train) [747][40/63] lr: 1.4724e-03 eta: 5:46:17 time: 0.5304 data_time: 0.0177 memory: 16131 loss: 1.2118 loss_prob: 0.6544 loss_thr: 0.4476 loss_db: 0.1098 2022/10/26 05:04:04 - mmengine - INFO - Epoch(train) [747][45/63] lr: 1.4724e-03 eta: 5:46:17 time: 0.5239 data_time: 0.0200 memory: 16131 loss: 1.2466 loss_prob: 0.6795 loss_thr: 0.4538 loss_db: 0.1134 2022/10/26 05:04:07 - mmengine - INFO - Epoch(train) [747][50/63] lr: 1.4724e-03 eta: 5:46:09 time: 0.5377 data_time: 0.0329 memory: 16131 loss: 1.2370 loss_prob: 0.6736 loss_thr: 0.4521 loss_db: 0.1114 2022/10/26 05:04:10 - mmengine - INFO - Epoch(train) [747][55/63] lr: 1.4724e-03 eta: 5:46:09 time: 0.5802 data_time: 0.0311 memory: 16131 loss: 1.2095 loss_prob: 0.6465 loss_thr: 0.4529 loss_db: 0.1101 2022/10/26 05:04:13 - mmengine - INFO - Epoch(train) [747][60/63] lr: 1.4724e-03 eta: 5:46:01 time: 0.6032 data_time: 0.0142 memory: 16131 loss: 1.1688 loss_prob: 0.6234 loss_thr: 0.4373 loss_db: 0.1082 2022/10/26 05:04:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:04:19 - mmengine - INFO - Epoch(train) [748][5/63] lr: 1.4694e-03 eta: 5:46:01 time: 0.6757 data_time: 0.1850 memory: 16131 loss: 1.1615 loss_prob: 0.6279 loss_thr: 0.4277 loss_db: 0.1059 2022/10/26 05:04:21 - mmengine - INFO - Epoch(train) [748][10/63] lr: 1.4694e-03 eta: 5:45:50 time: 0.6951 data_time: 0.1939 memory: 16131 loss: 1.1858 loss_prob: 0.6344 loss_thr: 0.4443 loss_db: 0.1071 2022/10/26 05:04:24 - mmengine - INFO - Epoch(train) [748][15/63] lr: 1.4694e-03 eta: 5:45:50 time: 0.5375 data_time: 0.0146 memory: 16131 loss: 1.1198 loss_prob: 0.5908 loss_thr: 0.4259 loss_db: 0.1031 2022/10/26 05:04:26 - mmengine - INFO - Epoch(train) [748][20/63] lr: 1.4694e-03 eta: 5:45:41 time: 0.5178 data_time: 0.0058 memory: 16131 loss: 1.1092 loss_prob: 0.5860 loss_thr: 0.4203 loss_db: 0.1029 2022/10/26 05:04:29 - mmengine - INFO - Epoch(train) [748][25/63] lr: 1.4694e-03 eta: 5:45:41 time: 0.5205 data_time: 0.0327 memory: 16131 loss: 1.0913 loss_prob: 0.5721 loss_thr: 0.4220 loss_db: 0.0971 2022/10/26 05:04:32 - mmengine - INFO - Epoch(train) [748][30/63] lr: 1.4694e-03 eta: 5:45:33 time: 0.5652 data_time: 0.0316 memory: 16131 loss: 1.0974 loss_prob: 0.5611 loss_thr: 0.4396 loss_db: 0.0967 2022/10/26 05:04:35 - mmengine - INFO - Epoch(train) [748][35/63] lr: 1.4694e-03 eta: 5:45:33 time: 0.5485 data_time: 0.0090 memory: 16131 loss: 1.0903 loss_prob: 0.5626 loss_thr: 0.4308 loss_db: 0.0969 2022/10/26 05:04:37 - mmengine - INFO - Epoch(train) [748][40/63] lr: 1.4694e-03 eta: 5:45:25 time: 0.5103 data_time: 0.0099 memory: 16131 loss: 1.1333 loss_prob: 0.6081 loss_thr: 0.4190 loss_db: 0.1062 2022/10/26 05:04:40 - mmengine - INFO - Epoch(train) [748][45/63] lr: 1.4694e-03 eta: 5:45:25 time: 0.5101 data_time: 0.0056 memory: 16131 loss: 1.1968 loss_prob: 0.6423 loss_thr: 0.4420 loss_db: 0.1125 2022/10/26 05:04:43 - mmengine - INFO - Epoch(train) [748][50/63] lr: 1.4694e-03 eta: 5:45:16 time: 0.5460 data_time: 0.0192 memory: 16131 loss: 1.1469 loss_prob: 0.6099 loss_thr: 0.4330 loss_db: 0.1040 2022/10/26 05:04:45 - mmengine - INFO - Epoch(train) [748][55/63] lr: 1.4694e-03 eta: 5:45:16 time: 0.5395 data_time: 0.0215 memory: 16131 loss: 1.1667 loss_prob: 0.6227 loss_thr: 0.4377 loss_db: 0.1063 2022/10/26 05:04:48 - mmengine - INFO - Epoch(train) [748][60/63] lr: 1.4694e-03 eta: 5:45:08 time: 0.5216 data_time: 0.0099 memory: 16131 loss: 1.2244 loss_prob: 0.6679 loss_thr: 0.4418 loss_db: 0.1147 2022/10/26 05:04:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:04:54 - mmengine - INFO - Epoch(train) [749][5/63] lr: 1.4665e-03 eta: 5:45:08 time: 0.7182 data_time: 0.2016 memory: 16131 loss: 1.0548 loss_prob: 0.5590 loss_thr: 0.3995 loss_db: 0.0963 2022/10/26 05:04:57 - mmengine - INFO - Epoch(train) [749][10/63] lr: 1.4665e-03 eta: 5:44:57 time: 0.7497 data_time: 0.1964 memory: 16131 loss: 1.0842 loss_prob: 0.5691 loss_thr: 0.4159 loss_db: 0.0992 2022/10/26 05:04:59 - mmengine - INFO - Epoch(train) [749][15/63] lr: 1.4665e-03 eta: 5:44:57 time: 0.5211 data_time: 0.0062 memory: 16131 loss: 1.1350 loss_prob: 0.5983 loss_thr: 0.4339 loss_db: 0.1028 2022/10/26 05:05:02 - mmengine - INFO - Epoch(train) [749][20/63] lr: 1.4665e-03 eta: 5:44:49 time: 0.5210 data_time: 0.0080 memory: 16131 loss: 1.3319 loss_prob: 0.7696 loss_thr: 0.4406 loss_db: 0.1217 2022/10/26 05:05:05 - mmengine - INFO - Epoch(train) [749][25/63] lr: 1.4665e-03 eta: 5:44:49 time: 0.5859 data_time: 0.0394 memory: 16131 loss: 1.4794 loss_prob: 0.8998 loss_thr: 0.4487 loss_db: 0.1309 2022/10/26 05:05:08 - mmengine - INFO - Epoch(train) [749][30/63] lr: 1.4665e-03 eta: 5:44:40 time: 0.5621 data_time: 0.0395 memory: 16131 loss: 1.5826 loss_prob: 0.9811 loss_thr: 0.4536 loss_db: 0.1479 2022/10/26 05:05:10 - mmengine - INFO - Epoch(train) [749][35/63] lr: 1.4665e-03 eta: 5:44:40 time: 0.5083 data_time: 0.0083 memory: 16131 loss: 1.4784 loss_prob: 0.8913 loss_thr: 0.4472 loss_db: 0.1399 2022/10/26 05:05:13 - mmengine - INFO - Epoch(train) [749][40/63] lr: 1.4665e-03 eta: 5:44:32 time: 0.5064 data_time: 0.0127 memory: 16131 loss: 1.2757 loss_prob: 0.7130 loss_thr: 0.4499 loss_db: 0.1128 2022/10/26 05:05:15 - mmengine - INFO - Epoch(train) [749][45/63] lr: 1.4665e-03 eta: 5:44:32 time: 0.5113 data_time: 0.0117 memory: 16131 loss: 1.3462 loss_prob: 0.7586 loss_thr: 0.4579 loss_db: 0.1297 2022/10/26 05:05:18 - mmengine - INFO - Epoch(train) [749][50/63] lr: 1.4665e-03 eta: 5:44:23 time: 0.5573 data_time: 0.0196 memory: 16131 loss: 1.4096 loss_prob: 0.7908 loss_thr: 0.4826 loss_db: 0.1362 2022/10/26 05:05:21 - mmengine - INFO - Epoch(train) [749][55/63] lr: 1.4665e-03 eta: 5:44:23 time: 0.5574 data_time: 0.0210 memory: 16131 loss: 1.4500 loss_prob: 0.8096 loss_thr: 0.5066 loss_db: 0.1337 2022/10/26 05:05:24 - mmengine - INFO - Epoch(train) [749][60/63] lr: 1.4665e-03 eta: 5:44:15 time: 0.5471 data_time: 0.0112 memory: 16131 loss: 1.4170 loss_prob: 0.7797 loss_thr: 0.5069 loss_db: 0.1304 2022/10/26 05:05:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:05:30 - mmengine - INFO - Epoch(train) [750][5/63] lr: 1.4636e-03 eta: 5:44:15 time: 0.7184 data_time: 0.1869 memory: 16131 loss: 1.4104 loss_prob: 0.7730 loss_thr: 0.5070 loss_db: 0.1304 2022/10/26 05:05:32 - mmengine - INFO - Epoch(train) [750][10/63] lr: 1.4636e-03 eta: 5:44:04 time: 0.7425 data_time: 0.1878 memory: 16131 loss: 1.3186 loss_prob: 0.7259 loss_thr: 0.4686 loss_db: 0.1241 2022/10/26 05:05:35 - mmengine - INFO - Epoch(train) [750][15/63] lr: 1.4636e-03 eta: 5:44:04 time: 0.4929 data_time: 0.0089 memory: 16131 loss: 1.1658 loss_prob: 0.6381 loss_thr: 0.4239 loss_db: 0.1039 2022/10/26 05:05:37 - mmengine - INFO - Epoch(train) [750][20/63] lr: 1.4636e-03 eta: 5:43:56 time: 0.4938 data_time: 0.0062 memory: 16131 loss: 1.1990 loss_prob: 0.6695 loss_thr: 0.4190 loss_db: 0.1105 2022/10/26 05:05:40 - mmengine - INFO - Epoch(train) [750][25/63] lr: 1.4636e-03 eta: 5:43:56 time: 0.5566 data_time: 0.0301 memory: 16131 loss: 1.2043 loss_prob: 0.6591 loss_thr: 0.4301 loss_db: 0.1150 2022/10/26 05:05:43 - mmengine - INFO - Epoch(train) [750][30/63] lr: 1.4636e-03 eta: 5:43:48 time: 0.5782 data_time: 0.0285 memory: 16131 loss: 1.1058 loss_prob: 0.5835 loss_thr: 0.4204 loss_db: 0.1019 2022/10/26 05:05:46 - mmengine - INFO - Epoch(train) [750][35/63] lr: 1.4636e-03 eta: 5:43:48 time: 0.5323 data_time: 0.0078 memory: 16131 loss: 1.1518 loss_prob: 0.6194 loss_thr: 0.4257 loss_db: 0.1067 2022/10/26 05:05:48 - mmengine - INFO - Epoch(train) [750][40/63] lr: 1.4636e-03 eta: 5:43:39 time: 0.4929 data_time: 0.0082 memory: 16131 loss: 1.2544 loss_prob: 0.6951 loss_thr: 0.4433 loss_db: 0.1160 2022/10/26 05:05:51 - mmengine - INFO - Epoch(train) [750][45/63] lr: 1.4636e-03 eta: 5:43:39 time: 0.4937 data_time: 0.0061 memory: 16131 loss: 1.2874 loss_prob: 0.7149 loss_thr: 0.4558 loss_db: 0.1167 2022/10/26 05:05:53 - mmengine - INFO - Epoch(train) [750][50/63] lr: 1.4636e-03 eta: 5:43:30 time: 0.5140 data_time: 0.0208 memory: 16131 loss: 1.2235 loss_prob: 0.6611 loss_thr: 0.4503 loss_db: 0.1122 2022/10/26 05:05:56 - mmengine - INFO - Epoch(train) [750][55/63] lr: 1.4636e-03 eta: 5:43:30 time: 0.5053 data_time: 0.0204 memory: 16131 loss: 1.2071 loss_prob: 0.6415 loss_thr: 0.4545 loss_db: 0.1111 2022/10/26 05:05:58 - mmengine - INFO - Epoch(train) [750][60/63] lr: 1.4636e-03 eta: 5:43:22 time: 0.5060 data_time: 0.0063 memory: 16131 loss: 1.1689 loss_prob: 0.6214 loss_thr: 0.4396 loss_db: 0.1080 2022/10/26 05:06:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:06:04 - mmengine - INFO - Epoch(train) [751][5/63] lr: 1.4607e-03 eta: 5:43:22 time: 0.7057 data_time: 0.1998 memory: 16131 loss: 1.2077 loss_prob: 0.6557 loss_thr: 0.4407 loss_db: 0.1113 2022/10/26 05:06:07 - mmengine - INFO - Epoch(train) [751][10/63] lr: 1.4607e-03 eta: 5:43:11 time: 0.7240 data_time: 0.1997 memory: 16131 loss: 1.1132 loss_prob: 0.5959 loss_thr: 0.4162 loss_db: 0.1010 2022/10/26 05:06:09 - mmengine - INFO - Epoch(train) [751][15/63] lr: 1.4607e-03 eta: 5:43:11 time: 0.5115 data_time: 0.0075 memory: 16131 loss: 1.1721 loss_prob: 0.6301 loss_thr: 0.4365 loss_db: 0.1056 2022/10/26 05:06:12 - mmengine - INFO - Epoch(train) [751][20/63] lr: 1.4607e-03 eta: 5:43:03 time: 0.5323 data_time: 0.0073 memory: 16131 loss: 1.1406 loss_prob: 0.6137 loss_thr: 0.4225 loss_db: 0.1044 2022/10/26 05:06:15 - mmengine - INFO - Epoch(train) [751][25/63] lr: 1.4607e-03 eta: 5:43:03 time: 0.5512 data_time: 0.0088 memory: 16131 loss: 1.0906 loss_prob: 0.5773 loss_thr: 0.4149 loss_db: 0.0985 2022/10/26 05:06:18 - mmengine - INFO - Epoch(train) [751][30/63] lr: 1.4607e-03 eta: 5:42:54 time: 0.5309 data_time: 0.0332 memory: 16131 loss: 1.1878 loss_prob: 0.6392 loss_thr: 0.4426 loss_db: 0.1060 2022/10/26 05:06:20 - mmengine - INFO - Epoch(train) [751][35/63] lr: 1.4607e-03 eta: 5:42:54 time: 0.5202 data_time: 0.0321 memory: 16131 loss: 1.2183 loss_prob: 0.6597 loss_thr: 0.4469 loss_db: 0.1117 2022/10/26 05:06:23 - mmengine - INFO - Epoch(train) [751][40/63] lr: 1.4607e-03 eta: 5:42:46 time: 0.5537 data_time: 0.0078 memory: 16131 loss: 1.2039 loss_prob: 0.6459 loss_thr: 0.4465 loss_db: 0.1115 2022/10/26 05:06:26 - mmengine - INFO - Epoch(train) [751][45/63] lr: 1.4607e-03 eta: 5:42:46 time: 0.5715 data_time: 0.0056 memory: 16131 loss: 1.2225 loss_prob: 0.6640 loss_thr: 0.4477 loss_db: 0.1108 2022/10/26 05:06:28 - mmengine - INFO - Epoch(train) [751][50/63] lr: 1.4607e-03 eta: 5:42:37 time: 0.5323 data_time: 0.0084 memory: 16131 loss: 1.2678 loss_prob: 0.6996 loss_thr: 0.4511 loss_db: 0.1172 2022/10/26 05:06:31 - mmengine - INFO - Epoch(train) [751][55/63] lr: 1.4607e-03 eta: 5:42:37 time: 0.5364 data_time: 0.0282 memory: 16131 loss: 1.3443 loss_prob: 0.7724 loss_thr: 0.4500 loss_db: 0.1219 2022/10/26 05:06:34 - mmengine - INFO - Epoch(train) [751][60/63] lr: 1.4607e-03 eta: 5:42:29 time: 0.5870 data_time: 0.0259 memory: 16131 loss: 1.3767 loss_prob: 0.7952 loss_thr: 0.4591 loss_db: 0.1225 2022/10/26 05:06:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:06:41 - mmengine - INFO - Epoch(train) [752][5/63] lr: 1.4577e-03 eta: 5:42:29 time: 0.7861 data_time: 0.2312 memory: 16131 loss: 1.2984 loss_prob: 0.7254 loss_thr: 0.4480 loss_db: 0.1250 2022/10/26 05:06:44 - mmengine - INFO - Epoch(train) [752][10/63] lr: 1.4577e-03 eta: 5:42:19 time: 0.8219 data_time: 0.2306 memory: 16131 loss: 1.1830 loss_prob: 0.6522 loss_thr: 0.4167 loss_db: 0.1141 2022/10/26 05:06:47 - mmengine - INFO - Epoch(train) [752][15/63] lr: 1.4577e-03 eta: 5:42:19 time: 0.6072 data_time: 0.0074 memory: 16131 loss: 1.1486 loss_prob: 0.6238 loss_thr: 0.4175 loss_db: 0.1073 2022/10/26 05:06:50 - mmengine - INFO - Epoch(train) [752][20/63] lr: 1.4577e-03 eta: 5:42:11 time: 0.5728 data_time: 0.0056 memory: 16131 loss: 1.1915 loss_prob: 0.6383 loss_thr: 0.4427 loss_db: 0.1104 2022/10/26 05:06:52 - mmengine - INFO - Epoch(train) [752][25/63] lr: 1.4577e-03 eta: 5:42:11 time: 0.5255 data_time: 0.0331 memory: 16131 loss: 1.1941 loss_prob: 0.6319 loss_thr: 0.4537 loss_db: 0.1085 2022/10/26 05:06:55 - mmengine - INFO - Epoch(train) [752][30/63] lr: 1.4577e-03 eta: 5:42:03 time: 0.5352 data_time: 0.0332 memory: 16131 loss: 1.1934 loss_prob: 0.6366 loss_thr: 0.4499 loss_db: 0.1069 2022/10/26 05:06:57 - mmengine - INFO - Epoch(train) [752][35/63] lr: 1.4577e-03 eta: 5:42:03 time: 0.5053 data_time: 0.0047 memory: 16131 loss: 1.1520 loss_prob: 0.6159 loss_thr: 0.4307 loss_db: 0.1055 2022/10/26 05:07:00 - mmengine - INFO - Epoch(train) [752][40/63] lr: 1.4577e-03 eta: 5:41:54 time: 0.5087 data_time: 0.0054 memory: 16131 loss: 1.1095 loss_prob: 0.5872 loss_thr: 0.4165 loss_db: 0.1057 2022/10/26 05:07:03 - mmengine - INFO - Epoch(train) [752][45/63] lr: 1.4577e-03 eta: 5:41:54 time: 0.5475 data_time: 0.0061 memory: 16131 loss: 1.1851 loss_prob: 0.6375 loss_thr: 0.4379 loss_db: 0.1097 2022/10/26 05:07:06 - mmengine - INFO - Epoch(train) [752][50/63] lr: 1.4577e-03 eta: 5:41:46 time: 0.5652 data_time: 0.0230 memory: 16131 loss: 1.1947 loss_prob: 0.6396 loss_thr: 0.4501 loss_db: 0.1050 2022/10/26 05:07:08 - mmengine - INFO - Epoch(train) [752][55/63] lr: 1.4577e-03 eta: 5:41:46 time: 0.5162 data_time: 0.0232 memory: 16131 loss: 1.1357 loss_prob: 0.6036 loss_thr: 0.4310 loss_db: 0.1010 2022/10/26 05:07:11 - mmengine - INFO - Epoch(train) [752][60/63] lr: 1.4577e-03 eta: 5:41:37 time: 0.5010 data_time: 0.0060 memory: 16131 loss: 1.1805 loss_prob: 0.6387 loss_thr: 0.4327 loss_db: 0.1091 2022/10/26 05:07:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:07:17 - mmengine - INFO - Epoch(train) [753][5/63] lr: 1.4548e-03 eta: 5:41:37 time: 0.7136 data_time: 0.1832 memory: 16131 loss: 1.1993 loss_prob: 0.6522 loss_thr: 0.4361 loss_db: 0.1110 2022/10/26 05:07:20 - mmengine - INFO - Epoch(train) [753][10/63] lr: 1.4548e-03 eta: 5:41:27 time: 0.7814 data_time: 0.1841 memory: 16131 loss: 1.2112 loss_prob: 0.6605 loss_thr: 0.4376 loss_db: 0.1131 2022/10/26 05:07:23 - mmengine - INFO - Epoch(train) [753][15/63] lr: 1.4548e-03 eta: 5:41:27 time: 0.6335 data_time: 0.0074 memory: 16131 loss: 1.1161 loss_prob: 0.5983 loss_thr: 0.4123 loss_db: 0.1055 2022/10/26 05:07:26 - mmengine - INFO - Epoch(train) [753][20/63] lr: 1.4548e-03 eta: 5:41:19 time: 0.5921 data_time: 0.0096 memory: 16131 loss: 1.2140 loss_prob: 0.6674 loss_thr: 0.4302 loss_db: 0.1164 2022/10/26 05:07:28 - mmengine - INFO - Epoch(train) [753][25/63] lr: 1.4548e-03 eta: 5:41:19 time: 0.5115 data_time: 0.0129 memory: 16131 loss: 1.2121 loss_prob: 0.6723 loss_thr: 0.4252 loss_db: 0.1147 2022/10/26 05:07:31 - mmengine - INFO - Epoch(train) [753][30/63] lr: 1.4548e-03 eta: 5:41:10 time: 0.5616 data_time: 0.0416 memory: 16131 loss: 1.0394 loss_prob: 0.5614 loss_thr: 0.3805 loss_db: 0.0974 2022/10/26 05:07:34 - mmengine - INFO - Epoch(train) [753][35/63] lr: 1.4548e-03 eta: 5:41:10 time: 0.5467 data_time: 0.0381 memory: 16131 loss: 1.1010 loss_prob: 0.5922 loss_thr: 0.4057 loss_db: 0.1030 2022/10/26 05:07:36 - mmengine - INFO - Epoch(train) [753][40/63] lr: 1.4548e-03 eta: 5:41:02 time: 0.5056 data_time: 0.0067 memory: 16131 loss: 1.1595 loss_prob: 0.6218 loss_thr: 0.4302 loss_db: 0.1074 2022/10/26 05:07:39 - mmengine - INFO - Epoch(train) [753][45/63] lr: 1.4548e-03 eta: 5:41:02 time: 0.5116 data_time: 0.0060 memory: 16131 loss: 1.1477 loss_prob: 0.6167 loss_thr: 0.4261 loss_db: 0.1049 2022/10/26 05:07:41 - mmengine - INFO - Epoch(train) [753][50/63] lr: 1.4548e-03 eta: 5:40:53 time: 0.4960 data_time: 0.0082 memory: 16131 loss: 1.1942 loss_prob: 0.6492 loss_thr: 0.4354 loss_db: 0.1096 2022/10/26 05:07:44 - mmengine - INFO - Epoch(train) [753][55/63] lr: 1.4548e-03 eta: 5:40:53 time: 0.5135 data_time: 0.0214 memory: 16131 loss: 1.1626 loss_prob: 0.6264 loss_thr: 0.4303 loss_db: 0.1059 2022/10/26 05:07:46 - mmengine - INFO - Epoch(train) [753][60/63] lr: 1.4548e-03 eta: 5:40:45 time: 0.5134 data_time: 0.0211 memory: 16131 loss: 1.1338 loss_prob: 0.6019 loss_thr: 0.4294 loss_db: 0.1026 2022/10/26 05:07:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:07:52 - mmengine - INFO - Epoch(train) [754][5/63] lr: 1.4519e-03 eta: 5:40:45 time: 0.7006 data_time: 0.2113 memory: 16131 loss: 1.0380 loss_prob: 0.5421 loss_thr: 0.4012 loss_db: 0.0948 2022/10/26 05:07:55 - mmengine - INFO - Epoch(train) [754][10/63] lr: 1.4519e-03 eta: 5:40:34 time: 0.7542 data_time: 0.2124 memory: 16131 loss: 1.1466 loss_prob: 0.6086 loss_thr: 0.4313 loss_db: 0.1066 2022/10/26 05:07:58 - mmengine - INFO - Epoch(train) [754][15/63] lr: 1.4519e-03 eta: 5:40:34 time: 0.5640 data_time: 0.0081 memory: 16131 loss: 1.1481 loss_prob: 0.6136 loss_thr: 0.4280 loss_db: 0.1065 2022/10/26 05:08:01 - mmengine - INFO - Epoch(train) [754][20/63] lr: 1.4519e-03 eta: 5:40:26 time: 0.5345 data_time: 0.0053 memory: 16131 loss: 1.3025 loss_prob: 0.7473 loss_thr: 0.4337 loss_db: 0.1215 2022/10/26 05:08:03 - mmengine - INFO - Epoch(train) [754][25/63] lr: 1.4519e-03 eta: 5:40:26 time: 0.5230 data_time: 0.0234 memory: 16131 loss: 1.3843 loss_prob: 0.7925 loss_thr: 0.4622 loss_db: 0.1296 2022/10/26 05:08:06 - mmengine - INFO - Epoch(train) [754][30/63] lr: 1.4519e-03 eta: 5:40:17 time: 0.5124 data_time: 0.0287 memory: 16131 loss: 1.4127 loss_prob: 0.8143 loss_thr: 0.4573 loss_db: 0.1410 2022/10/26 05:08:09 - mmengine - INFO - Epoch(train) [754][35/63] lr: 1.4519e-03 eta: 5:40:17 time: 0.5140 data_time: 0.0150 memory: 16131 loss: 1.3725 loss_prob: 0.7951 loss_thr: 0.4414 loss_db: 0.1360 2022/10/26 05:08:11 - mmengine - INFO - Epoch(train) [754][40/63] lr: 1.4519e-03 eta: 5:40:09 time: 0.5146 data_time: 0.0095 memory: 16131 loss: 1.6628 loss_prob: 1.0160 loss_thr: 0.4989 loss_db: 0.1479 2022/10/26 05:08:13 - mmengine - INFO - Epoch(train) [754][45/63] lr: 1.4519e-03 eta: 5:40:09 time: 0.4761 data_time: 0.0045 memory: 16131 loss: 1.9628 loss_prob: 1.2296 loss_thr: 0.5561 loss_db: 0.1771 2022/10/26 05:08:16 - mmengine - INFO - Epoch(train) [754][50/63] lr: 1.4519e-03 eta: 5:40:00 time: 0.5210 data_time: 0.0184 memory: 16131 loss: 1.8994 loss_prob: 1.1461 loss_thr: 0.5780 loss_db: 0.1753 2022/10/26 05:08:19 - mmengine - INFO - Epoch(train) [754][55/63] lr: 1.4519e-03 eta: 5:40:00 time: 0.5640 data_time: 0.0214 memory: 16131 loss: 1.8390 loss_prob: 1.0715 loss_thr: 0.5974 loss_db: 0.1701 2022/10/26 05:08:22 - mmengine - INFO - Epoch(train) [754][60/63] lr: 1.4519e-03 eta: 5:39:52 time: 0.5689 data_time: 0.0093 memory: 16131 loss: 1.6012 loss_prob: 0.9098 loss_thr: 0.5376 loss_db: 0.1538 2022/10/26 05:08:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:08:28 - mmengine - INFO - Epoch(train) [755][5/63] lr: 1.4489e-03 eta: 5:39:52 time: 0.6878 data_time: 0.2108 memory: 16131 loss: 1.2950 loss_prob: 0.7120 loss_thr: 0.4628 loss_db: 0.1201 2022/10/26 05:08:30 - mmengine - INFO - Epoch(train) [755][10/63] lr: 1.4489e-03 eta: 5:39:41 time: 0.6832 data_time: 0.2052 memory: 16131 loss: 1.2828 loss_prob: 0.7112 loss_thr: 0.4539 loss_db: 0.1176 2022/10/26 05:08:33 - mmengine - INFO - Epoch(train) [755][15/63] lr: 1.4489e-03 eta: 5:39:41 time: 0.5500 data_time: 0.0057 memory: 16131 loss: 1.2871 loss_prob: 0.7189 loss_thr: 0.4480 loss_db: 0.1202 2022/10/26 05:08:36 - mmengine - INFO - Epoch(train) [755][20/63] lr: 1.4489e-03 eta: 5:39:33 time: 0.5941 data_time: 0.0090 memory: 16131 loss: 1.3254 loss_prob: 0.7456 loss_thr: 0.4538 loss_db: 0.1260 2022/10/26 05:08:39 - mmengine - INFO - Epoch(train) [755][25/63] lr: 1.4489e-03 eta: 5:39:33 time: 0.5735 data_time: 0.0363 memory: 16131 loss: 1.3685 loss_prob: 0.7614 loss_thr: 0.4801 loss_db: 0.1271 2022/10/26 05:08:41 - mmengine - INFO - Epoch(train) [755][30/63] lr: 1.4489e-03 eta: 5:39:25 time: 0.5553 data_time: 0.0331 memory: 16131 loss: 1.2937 loss_prob: 0.7102 loss_thr: 0.4655 loss_db: 0.1180 2022/10/26 05:08:44 - mmengine - INFO - Epoch(train) [755][35/63] lr: 1.4489e-03 eta: 5:39:25 time: 0.5206 data_time: 0.0077 memory: 16131 loss: 1.2877 loss_prob: 0.6991 loss_thr: 0.4693 loss_db: 0.1193 2022/10/26 05:08:47 - mmengine - INFO - Epoch(train) [755][40/63] lr: 1.4489e-03 eta: 5:39:16 time: 0.5128 data_time: 0.0077 memory: 16131 loss: 1.2894 loss_prob: 0.6882 loss_thr: 0.4851 loss_db: 0.1160 2022/10/26 05:08:49 - mmengine - INFO - Epoch(train) [755][45/63] lr: 1.4489e-03 eta: 5:39:16 time: 0.5261 data_time: 0.0052 memory: 16131 loss: 1.1730 loss_prob: 0.6196 loss_thr: 0.4484 loss_db: 0.1050 2022/10/26 05:08:52 - mmengine - INFO - Epoch(train) [755][50/63] lr: 1.4489e-03 eta: 5:39:08 time: 0.5428 data_time: 0.0204 memory: 16131 loss: 1.2296 loss_prob: 0.6709 loss_thr: 0.4436 loss_db: 0.1151 2022/10/26 05:08:55 - mmengine - INFO - Epoch(train) [755][55/63] lr: 1.4489e-03 eta: 5:39:08 time: 0.5200 data_time: 0.0200 memory: 16131 loss: 1.2738 loss_prob: 0.7027 loss_thr: 0.4522 loss_db: 0.1189 2022/10/26 05:08:57 - mmengine - INFO - Epoch(train) [755][60/63] lr: 1.4489e-03 eta: 5:38:59 time: 0.4992 data_time: 0.0044 memory: 16131 loss: 1.2572 loss_prob: 0.6891 loss_thr: 0.4498 loss_db: 0.1183 2022/10/26 05:08:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:09:03 - mmengine - INFO - Epoch(train) [756][5/63] lr: 1.4460e-03 eta: 5:38:59 time: 0.6786 data_time: 0.1873 memory: 16131 loss: 1.1982 loss_prob: 0.6459 loss_thr: 0.4412 loss_db: 0.1111 2022/10/26 05:09:05 - mmengine - INFO - Epoch(train) [756][10/63] lr: 1.4460e-03 eta: 5:38:49 time: 0.6992 data_time: 0.1933 memory: 16131 loss: 1.1713 loss_prob: 0.6311 loss_thr: 0.4316 loss_db: 0.1086 2022/10/26 05:09:08 - mmengine - INFO - Epoch(train) [756][15/63] lr: 1.4460e-03 eta: 5:38:49 time: 0.5391 data_time: 0.0115 memory: 16131 loss: 1.0998 loss_prob: 0.5862 loss_thr: 0.4123 loss_db: 0.1013 2022/10/26 05:09:11 - mmengine - INFO - Epoch(train) [756][20/63] lr: 1.4460e-03 eta: 5:38:41 time: 0.6020 data_time: 0.0055 memory: 16131 loss: 1.2045 loss_prob: 0.6603 loss_thr: 0.4300 loss_db: 0.1142 2022/10/26 05:09:14 - mmengine - INFO - Epoch(train) [756][25/63] lr: 1.4460e-03 eta: 5:38:41 time: 0.5828 data_time: 0.0214 memory: 16131 loss: 1.2129 loss_prob: 0.6648 loss_thr: 0.4358 loss_db: 0.1123 2022/10/26 05:09:17 - mmengine - INFO - Epoch(train) [756][30/63] lr: 1.4460e-03 eta: 5:38:32 time: 0.5290 data_time: 0.0301 memory: 16131 loss: 1.1449 loss_prob: 0.6147 loss_thr: 0.4265 loss_db: 0.1037 2022/10/26 05:09:19 - mmengine - INFO - Epoch(train) [756][35/63] lr: 1.4460e-03 eta: 5:38:32 time: 0.5079 data_time: 0.0161 memory: 16131 loss: 1.1792 loss_prob: 0.6324 loss_thr: 0.4405 loss_db: 0.1063 2022/10/26 05:09:22 - mmengine - INFO - Epoch(train) [756][40/63] lr: 1.4460e-03 eta: 5:38:24 time: 0.5069 data_time: 0.0067 memory: 16131 loss: 1.1378 loss_prob: 0.6056 loss_thr: 0.4298 loss_db: 0.1025 2022/10/26 05:09:24 - mmengine - INFO - Epoch(train) [756][45/63] lr: 1.4460e-03 eta: 5:38:24 time: 0.5180 data_time: 0.0047 memory: 16131 loss: 1.1181 loss_prob: 0.5940 loss_thr: 0.4209 loss_db: 0.1033 2022/10/26 05:09:27 - mmengine - INFO - Epoch(train) [756][50/63] lr: 1.4460e-03 eta: 5:38:15 time: 0.5075 data_time: 0.0143 memory: 16131 loss: 1.2200 loss_prob: 0.6632 loss_thr: 0.4417 loss_db: 0.1150 2022/10/26 05:09:29 - mmengine - INFO - Epoch(train) [756][55/63] lr: 1.4460e-03 eta: 5:38:15 time: 0.4848 data_time: 0.0187 memory: 16131 loss: 1.2649 loss_prob: 0.6942 loss_thr: 0.4526 loss_db: 0.1181 2022/10/26 05:09:32 - mmengine - INFO - Epoch(train) [756][60/63] lr: 1.4460e-03 eta: 5:38:06 time: 0.5039 data_time: 0.0100 memory: 16131 loss: 1.1430 loss_prob: 0.6168 loss_thr: 0.4228 loss_db: 0.1034 2022/10/26 05:09:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:09:37 - mmengine - INFO - Epoch(train) [757][5/63] lr: 1.4431e-03 eta: 5:38:06 time: 0.6658 data_time: 0.1685 memory: 16131 loss: 1.1516 loss_prob: 0.6108 loss_thr: 0.4343 loss_db: 0.1064 2022/10/26 05:09:40 - mmengine - INFO - Epoch(train) [757][10/63] lr: 1.4431e-03 eta: 5:37:56 time: 0.6893 data_time: 0.1698 memory: 16131 loss: 1.2880 loss_prob: 0.7018 loss_thr: 0.4677 loss_db: 0.1185 2022/10/26 05:09:42 - mmengine - INFO - Epoch(train) [757][15/63] lr: 1.4431e-03 eta: 5:37:56 time: 0.5016 data_time: 0.0076 memory: 16131 loss: 1.3788 loss_prob: 0.7681 loss_thr: 0.4837 loss_db: 0.1269 2022/10/26 05:09:45 - mmengine - INFO - Epoch(train) [757][20/63] lr: 1.4431e-03 eta: 5:37:47 time: 0.4871 data_time: 0.0053 memory: 16131 loss: 1.2769 loss_prob: 0.6972 loss_thr: 0.4604 loss_db: 0.1193 2022/10/26 05:09:47 - mmengine - INFO - Epoch(train) [757][25/63] lr: 1.4431e-03 eta: 5:37:47 time: 0.4834 data_time: 0.0072 memory: 16131 loss: 1.2369 loss_prob: 0.6697 loss_thr: 0.4504 loss_db: 0.1168 2022/10/26 05:09:50 - mmengine - INFO - Epoch(train) [757][30/63] lr: 1.4431e-03 eta: 5:37:38 time: 0.5187 data_time: 0.0326 memory: 16131 loss: 1.1937 loss_prob: 0.6441 loss_thr: 0.4382 loss_db: 0.1115 2022/10/26 05:09:52 - mmengine - INFO - Epoch(train) [757][35/63] lr: 1.4431e-03 eta: 5:37:38 time: 0.5266 data_time: 0.0320 memory: 16131 loss: 1.1853 loss_prob: 0.6435 loss_thr: 0.4320 loss_db: 0.1098 2022/10/26 05:09:55 - mmengine - INFO - Epoch(train) [757][40/63] lr: 1.4431e-03 eta: 5:37:30 time: 0.4826 data_time: 0.0068 memory: 16131 loss: 1.2335 loss_prob: 0.6743 loss_thr: 0.4425 loss_db: 0.1167 2022/10/26 05:09:57 - mmengine - INFO - Epoch(train) [757][45/63] lr: 1.4431e-03 eta: 5:37:30 time: 0.4706 data_time: 0.0055 memory: 16131 loss: 1.1898 loss_prob: 0.6435 loss_thr: 0.4349 loss_db: 0.1115 2022/10/26 05:10:00 - mmengine - INFO - Epoch(train) [757][50/63] lr: 1.4431e-03 eta: 5:37:21 time: 0.4939 data_time: 0.0153 memory: 16131 loss: 1.0937 loss_prob: 0.5839 loss_thr: 0.4109 loss_db: 0.0989 2022/10/26 05:10:02 - mmengine - INFO - Epoch(train) [757][55/63] lr: 1.4431e-03 eta: 5:37:21 time: 0.5172 data_time: 0.0238 memory: 16131 loss: 1.0301 loss_prob: 0.5417 loss_thr: 0.3944 loss_db: 0.0940 2022/10/26 05:10:05 - mmengine - INFO - Epoch(train) [757][60/63] lr: 1.4431e-03 eta: 5:37:13 time: 0.5508 data_time: 0.0143 memory: 16131 loss: 1.0952 loss_prob: 0.5848 loss_thr: 0.4080 loss_db: 0.1024 2022/10/26 05:10:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:10:12 - mmengine - INFO - Epoch(train) [758][5/63] lr: 1.4402e-03 eta: 5:37:13 time: 0.7799 data_time: 0.1834 memory: 16131 loss: 1.1308 loss_prob: 0.6058 loss_thr: 0.4215 loss_db: 0.1035 2022/10/26 05:10:15 - mmengine - INFO - Epoch(train) [758][10/63] lr: 1.4402e-03 eta: 5:37:03 time: 0.7997 data_time: 0.1883 memory: 16131 loss: 1.1619 loss_prob: 0.6106 loss_thr: 0.4467 loss_db: 0.1047 2022/10/26 05:10:18 - mmengine - INFO - Epoch(train) [758][15/63] lr: 1.4402e-03 eta: 5:37:03 time: 0.5894 data_time: 0.0160 memory: 16131 loss: 1.1838 loss_prob: 0.6262 loss_thr: 0.4492 loss_db: 0.1084 2022/10/26 05:10:20 - mmengine - INFO - Epoch(train) [758][20/63] lr: 1.4402e-03 eta: 5:36:54 time: 0.5433 data_time: 0.0112 memory: 16131 loss: 1.1788 loss_prob: 0.6326 loss_thr: 0.4356 loss_db: 0.1106 2022/10/26 05:10:23 - mmengine - INFO - Epoch(train) [758][25/63] lr: 1.4402e-03 eta: 5:36:54 time: 0.5513 data_time: 0.0079 memory: 16131 loss: 1.1654 loss_prob: 0.6280 loss_thr: 0.4298 loss_db: 0.1076 2022/10/26 05:10:26 - mmengine - INFO - Epoch(train) [758][30/63] lr: 1.4402e-03 eta: 5:36:46 time: 0.5848 data_time: 0.0247 memory: 16131 loss: 1.1850 loss_prob: 0.6432 loss_thr: 0.4332 loss_db: 0.1085 2022/10/26 05:10:28 - mmengine - INFO - Epoch(train) [758][35/63] lr: 1.4402e-03 eta: 5:36:46 time: 0.5261 data_time: 0.0291 memory: 16131 loss: 1.1392 loss_prob: 0.6100 loss_thr: 0.4266 loss_db: 0.1026 2022/10/26 05:10:31 - mmengine - INFO - Epoch(train) [758][40/63] lr: 1.4402e-03 eta: 5:36:38 time: 0.5141 data_time: 0.0166 memory: 16131 loss: 1.1479 loss_prob: 0.6156 loss_thr: 0.4280 loss_db: 0.1043 2022/10/26 05:10:34 - mmengine - INFO - Epoch(train) [758][45/63] lr: 1.4402e-03 eta: 5:36:38 time: 0.5257 data_time: 0.0103 memory: 16131 loss: 1.1212 loss_prob: 0.6002 loss_thr: 0.4162 loss_db: 0.1049 2022/10/26 05:10:36 - mmengine - INFO - Epoch(train) [758][50/63] lr: 1.4402e-03 eta: 5:36:29 time: 0.5184 data_time: 0.0225 memory: 16131 loss: 1.0947 loss_prob: 0.5763 loss_thr: 0.4184 loss_db: 0.1001 2022/10/26 05:10:39 - mmengine - INFO - Epoch(train) [758][55/63] lr: 1.4402e-03 eta: 5:36:29 time: 0.5003 data_time: 0.0215 memory: 16131 loss: 1.1480 loss_prob: 0.6104 loss_thr: 0.4314 loss_db: 0.1062 2022/10/26 05:10:42 - mmengine - INFO - Epoch(train) [758][60/63] lr: 1.4402e-03 eta: 5:36:21 time: 0.5365 data_time: 0.0130 memory: 16131 loss: 1.0950 loss_prob: 0.5752 loss_thr: 0.4179 loss_db: 0.1019 2022/10/26 05:10:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:10:48 - mmengine - INFO - Epoch(train) [759][5/63] lr: 1.4372e-03 eta: 5:36:21 time: 0.7275 data_time: 0.1829 memory: 16131 loss: 1.1273 loss_prob: 0.6024 loss_thr: 0.4196 loss_db: 0.1053 2022/10/26 05:10:51 - mmengine - INFO - Epoch(train) [759][10/63] lr: 1.4372e-03 eta: 5:36:11 time: 0.7713 data_time: 0.1820 memory: 16131 loss: 1.1381 loss_prob: 0.6086 loss_thr: 0.4251 loss_db: 0.1044 2022/10/26 05:10:54 - mmengine - INFO - Epoch(train) [759][15/63] lr: 1.4372e-03 eta: 5:36:11 time: 0.5797 data_time: 0.0060 memory: 16131 loss: 1.2051 loss_prob: 0.6522 loss_thr: 0.4422 loss_db: 0.1107 2022/10/26 05:10:56 - mmengine - INFO - Epoch(train) [759][20/63] lr: 1.4372e-03 eta: 5:36:02 time: 0.5238 data_time: 0.0063 memory: 16131 loss: 1.2281 loss_prob: 0.6660 loss_thr: 0.4486 loss_db: 0.1135 2022/10/26 05:10:59 - mmengine - INFO - Epoch(train) [759][25/63] lr: 1.4372e-03 eta: 5:36:02 time: 0.5148 data_time: 0.0213 memory: 16131 loss: 1.1699 loss_prob: 0.6257 loss_thr: 0.4368 loss_db: 0.1073 2022/10/26 05:11:02 - mmengine - INFO - Epoch(train) [759][30/63] lr: 1.4372e-03 eta: 5:35:54 time: 0.5623 data_time: 0.0306 memory: 16131 loss: 1.1287 loss_prob: 0.6049 loss_thr: 0.4199 loss_db: 0.1039 2022/10/26 05:11:04 - mmengine - INFO - Epoch(train) [759][35/63] lr: 1.4372e-03 eta: 5:35:54 time: 0.5528 data_time: 0.0149 memory: 16131 loss: 1.0812 loss_prob: 0.5779 loss_thr: 0.4057 loss_db: 0.0975 2022/10/26 05:11:07 - mmengine - INFO - Epoch(train) [759][40/63] lr: 1.4372e-03 eta: 5:35:45 time: 0.4982 data_time: 0.0043 memory: 16131 loss: 1.0510 loss_prob: 0.5558 loss_thr: 0.4033 loss_db: 0.0918 2022/10/26 05:11:09 - mmengine - INFO - Epoch(train) [759][45/63] lr: 1.4372e-03 eta: 5:35:45 time: 0.5215 data_time: 0.0045 memory: 16131 loss: 1.1579 loss_prob: 0.6456 loss_thr: 0.4094 loss_db: 0.1029 2022/10/26 05:11:12 - mmengine - INFO - Epoch(train) [759][50/63] lr: 1.4372e-03 eta: 5:35:37 time: 0.5379 data_time: 0.0160 memory: 16131 loss: 1.2791 loss_prob: 0.7223 loss_thr: 0.4418 loss_db: 0.1151 2022/10/26 05:11:15 - mmengine - INFO - Epoch(train) [759][55/63] lr: 1.4372e-03 eta: 5:35:37 time: 0.5146 data_time: 0.0204 memory: 16131 loss: 1.2156 loss_prob: 0.6600 loss_thr: 0.4459 loss_db: 0.1097 2022/10/26 05:11:17 - mmengine - INFO - Epoch(train) [759][60/63] lr: 1.4372e-03 eta: 5:35:29 time: 0.5065 data_time: 0.0099 memory: 16131 loss: 1.1420 loss_prob: 0.6098 loss_thr: 0.4275 loss_db: 0.1047 2022/10/26 05:11:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:11:23 - mmengine - INFO - Epoch(train) [760][5/63] lr: 1.4343e-03 eta: 5:35:29 time: 0.7169 data_time: 0.2068 memory: 16131 loss: 1.1203 loss_prob: 0.5971 loss_thr: 0.4207 loss_db: 0.1026 2022/10/26 05:11:26 - mmengine - INFO - Epoch(train) [760][10/63] lr: 1.4343e-03 eta: 5:35:18 time: 0.7135 data_time: 0.2053 memory: 16131 loss: 1.1318 loss_prob: 0.6117 loss_thr: 0.4131 loss_db: 0.1070 2022/10/26 05:11:28 - mmengine - INFO - Epoch(train) [760][15/63] lr: 1.4343e-03 eta: 5:35:18 time: 0.5152 data_time: 0.0058 memory: 16131 loss: 1.1367 loss_prob: 0.6205 loss_thr: 0.4118 loss_db: 0.1043 2022/10/26 05:11:31 - mmengine - INFO - Epoch(train) [760][20/63] lr: 1.4343e-03 eta: 5:35:10 time: 0.5486 data_time: 0.0069 memory: 16131 loss: 1.1634 loss_prob: 0.6265 loss_thr: 0.4320 loss_db: 0.1049 2022/10/26 05:11:34 - mmengine - INFO - Epoch(train) [760][25/63] lr: 1.4343e-03 eta: 5:35:10 time: 0.5591 data_time: 0.0201 memory: 16131 loss: 1.2155 loss_prob: 0.6475 loss_thr: 0.4567 loss_db: 0.1113 2022/10/26 05:11:37 - mmengine - INFO - Epoch(train) [760][30/63] lr: 1.4343e-03 eta: 5:35:01 time: 0.5738 data_time: 0.0303 memory: 16131 loss: 1.1330 loss_prob: 0.6034 loss_thr: 0.4264 loss_db: 0.1031 2022/10/26 05:11:39 - mmengine - INFO - Epoch(train) [760][35/63] lr: 1.4343e-03 eta: 5:35:01 time: 0.5377 data_time: 0.0160 memory: 16131 loss: 1.1652 loss_prob: 0.6283 loss_thr: 0.4317 loss_db: 0.1053 2022/10/26 05:11:42 - mmengine - INFO - Epoch(train) [760][40/63] lr: 1.4343e-03 eta: 5:34:53 time: 0.4874 data_time: 0.0049 memory: 16131 loss: 1.2181 loss_prob: 0.6574 loss_thr: 0.4487 loss_db: 0.1120 2022/10/26 05:11:44 - mmengine - INFO - Epoch(train) [760][45/63] lr: 1.4343e-03 eta: 5:34:53 time: 0.5215 data_time: 0.0071 memory: 16131 loss: 1.1664 loss_prob: 0.6226 loss_thr: 0.4358 loss_db: 0.1080 2022/10/26 05:11:47 - mmengine - INFO - Epoch(train) [760][50/63] lr: 1.4343e-03 eta: 5:34:44 time: 0.5318 data_time: 0.0230 memory: 16131 loss: 1.0752 loss_prob: 0.5706 loss_thr: 0.4063 loss_db: 0.0983 2022/10/26 05:11:49 - mmengine - INFO - Epoch(train) [760][55/63] lr: 1.4343e-03 eta: 5:34:44 time: 0.4912 data_time: 0.0209 memory: 16131 loss: 1.0659 loss_prob: 0.5675 loss_thr: 0.4016 loss_db: 0.0968 2022/10/26 05:11:52 - mmengine - INFO - Epoch(train) [760][60/63] lr: 1.4343e-03 eta: 5:34:36 time: 0.5307 data_time: 0.0053 memory: 16131 loss: 1.1525 loss_prob: 0.6245 loss_thr: 0.4222 loss_db: 0.1058 2022/10/26 05:11:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:11:54 - mmengine - INFO - Saving checkpoint at 760 epochs 2022/10/26 05:12:00 - mmengine - INFO - Epoch(val) [760][5/32] eta: 5:34:36 time: 0.5252 data_time: 0.0772 memory: 16131 2022/10/26 05:12:03 - mmengine - INFO - Epoch(val) [760][10/32] eta: 0:00:13 time: 0.6189 data_time: 0.1210 memory: 15724 2022/10/26 05:12:06 - mmengine - INFO - Epoch(val) [760][15/32] eta: 0:00:13 time: 0.5527 data_time: 0.0574 memory: 15724 2022/10/26 05:12:09 - mmengine - INFO - Epoch(val) [760][20/32] eta: 0:00:06 time: 0.5433 data_time: 0.0518 memory: 15724 2022/10/26 05:12:12 - mmengine - INFO - Epoch(val) [760][25/32] eta: 0:00:06 time: 0.5609 data_time: 0.0552 memory: 15724 2022/10/26 05:12:14 - mmengine - INFO - Epoch(val) [760][30/32] eta: 0:00:01 time: 0.5211 data_time: 0.0200 memory: 15724 2022/10/26 05:12:15 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8353, precision: 0.7527, hmean: 0.7919 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8353, precision: 0.8010, hmean: 0.8178 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8334, precision: 0.8302, hmean: 0.8318 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8267, precision: 0.8594, hmean: 0.8427 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8060, precision: 0.8876, hmean: 0.8448 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6981, precision: 0.9337, hmean: 0.7989 2022/10/26 05:12:15 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0438, precision: 1.0000, hmean: 0.0839 2022/10/26 05:12:15 - mmengine - INFO - Epoch(val) [760][32/32] icdar/precision: 0.8876 icdar/recall: 0.8060 icdar/hmean: 0.8448 2022/10/26 05:12:19 - mmengine - INFO - Epoch(train) [761][5/63] lr: 1.4314e-03 eta: 0:00:01 time: 0.7168 data_time: 0.1943 memory: 16131 loss: 1.1788 loss_prob: 0.6399 loss_thr: 0.4293 loss_db: 0.1096 2022/10/26 05:12:22 - mmengine - INFO - Epoch(train) [761][10/63] lr: 1.4314e-03 eta: 5:34:25 time: 0.7073 data_time: 0.1941 memory: 16131 loss: 1.1830 loss_prob: 0.6447 loss_thr: 0.4265 loss_db: 0.1118 2022/10/26 05:12:25 - mmengine - INFO - Epoch(train) [761][15/63] lr: 1.4314e-03 eta: 5:34:25 time: 0.5146 data_time: 0.0053 memory: 16131 loss: 1.2188 loss_prob: 0.6880 loss_thr: 0.4174 loss_db: 0.1134 2022/10/26 05:12:27 - mmengine - INFO - Epoch(train) [761][20/63] lr: 1.4314e-03 eta: 5:34:17 time: 0.5241 data_time: 0.0086 memory: 16131 loss: 1.3135 loss_prob: 0.7404 loss_thr: 0.4487 loss_db: 0.1244 2022/10/26 05:12:30 - mmengine - INFO - Epoch(train) [761][25/63] lr: 1.4314e-03 eta: 5:34:17 time: 0.5339 data_time: 0.0316 memory: 16131 loss: 1.2096 loss_prob: 0.6532 loss_thr: 0.4445 loss_db: 0.1119 2022/10/26 05:12:33 - mmengine - INFO - Epoch(train) [761][30/63] lr: 1.4314e-03 eta: 5:34:09 time: 0.5963 data_time: 0.0407 memory: 16131 loss: 1.1201 loss_prob: 0.6023 loss_thr: 0.4170 loss_db: 0.1008 2022/10/26 05:12:36 - mmengine - INFO - Epoch(train) [761][35/63] lr: 1.4314e-03 eta: 5:34:09 time: 0.6053 data_time: 0.0202 memory: 16131 loss: 1.2276 loss_prob: 0.6670 loss_thr: 0.4475 loss_db: 0.1131 2022/10/26 05:12:39 - mmengine - INFO - Epoch(train) [761][40/63] lr: 1.4314e-03 eta: 5:34:01 time: 0.5495 data_time: 0.0088 memory: 16131 loss: 1.2006 loss_prob: 0.6444 loss_thr: 0.4465 loss_db: 0.1097 2022/10/26 05:12:41 - mmengine - INFO - Epoch(train) [761][45/63] lr: 1.4314e-03 eta: 5:34:01 time: 0.5205 data_time: 0.0079 memory: 16131 loss: 1.1435 loss_prob: 0.6122 loss_thr: 0.4278 loss_db: 0.1035 2022/10/26 05:12:44 - mmengine - INFO - Epoch(train) [761][50/63] lr: 1.4314e-03 eta: 5:33:52 time: 0.5155 data_time: 0.0169 memory: 16131 loss: 1.1317 loss_prob: 0.6124 loss_thr: 0.4139 loss_db: 0.1054 2022/10/26 05:12:46 - mmengine - INFO - Epoch(train) [761][55/63] lr: 1.4314e-03 eta: 5:33:52 time: 0.5109 data_time: 0.0208 memory: 16131 loss: 1.1356 loss_prob: 0.6143 loss_thr: 0.4148 loss_db: 0.1065 2022/10/26 05:12:49 - mmengine - INFO - Epoch(train) [761][60/63] lr: 1.4314e-03 eta: 5:33:44 time: 0.5021 data_time: 0.0119 memory: 16131 loss: 1.1575 loss_prob: 0.6222 loss_thr: 0.4285 loss_db: 0.1069 2022/10/26 05:12:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:12:55 - mmengine - INFO - Epoch(train) [762][5/63] lr: 1.4284e-03 eta: 5:33:44 time: 0.7166 data_time: 0.1656 memory: 16131 loss: 1.0958 loss_prob: 0.5838 loss_thr: 0.4114 loss_db: 0.1006 2022/10/26 05:12:58 - mmengine - INFO - Epoch(train) [762][10/63] lr: 1.4284e-03 eta: 5:33:33 time: 0.7480 data_time: 0.1683 memory: 16131 loss: 1.1667 loss_prob: 0.6331 loss_thr: 0.4264 loss_db: 0.1073 2022/10/26 05:13:00 - mmengine - INFO - Epoch(train) [762][15/63] lr: 1.4284e-03 eta: 5:33:33 time: 0.5244 data_time: 0.0124 memory: 16131 loss: 1.2678 loss_prob: 0.6924 loss_thr: 0.4560 loss_db: 0.1193 2022/10/26 05:13:03 - mmengine - INFO - Epoch(train) [762][20/63] lr: 1.4284e-03 eta: 5:33:25 time: 0.5204 data_time: 0.0100 memory: 16131 loss: 1.1673 loss_prob: 0.6287 loss_thr: 0.4296 loss_db: 0.1091 2022/10/26 05:13:06 - mmengine - INFO - Epoch(train) [762][25/63] lr: 1.4284e-03 eta: 5:33:25 time: 0.5647 data_time: 0.0194 memory: 16131 loss: 1.1069 loss_prob: 0.5992 loss_thr: 0.4053 loss_db: 0.1023 2022/10/26 05:13:09 - mmengine - INFO - Epoch(train) [762][30/63] lr: 1.4284e-03 eta: 5:33:17 time: 0.5792 data_time: 0.0347 memory: 16131 loss: 1.1122 loss_prob: 0.6018 loss_thr: 0.4090 loss_db: 0.1015 2022/10/26 05:13:12 - mmengine - INFO - Epoch(train) [762][35/63] lr: 1.4284e-03 eta: 5:33:17 time: 0.6276 data_time: 0.0257 memory: 16131 loss: 1.1998 loss_prob: 0.6495 loss_thr: 0.4409 loss_db: 0.1093 2022/10/26 05:13:15 - mmengine - INFO - Epoch(train) [762][40/63] lr: 1.4284e-03 eta: 5:33:09 time: 0.6251 data_time: 0.0127 memory: 16131 loss: 1.2142 loss_prob: 0.6611 loss_thr: 0.4381 loss_db: 0.1149 2022/10/26 05:13:17 - mmengine - INFO - Epoch(train) [762][45/63] lr: 1.4284e-03 eta: 5:33:09 time: 0.5237 data_time: 0.0086 memory: 16131 loss: 1.1716 loss_prob: 0.6393 loss_thr: 0.4199 loss_db: 0.1123 2022/10/26 05:13:20 - mmengine - INFO - Epoch(train) [762][50/63] lr: 1.4284e-03 eta: 5:33:01 time: 0.5303 data_time: 0.0125 memory: 16131 loss: 1.2540 loss_prob: 0.6841 loss_thr: 0.4520 loss_db: 0.1180 2022/10/26 05:13:23 - mmengine - INFO - Epoch(train) [762][55/63] lr: 1.4284e-03 eta: 5:33:01 time: 0.5535 data_time: 0.0173 memory: 16131 loss: 1.1993 loss_prob: 0.6493 loss_thr: 0.4376 loss_db: 0.1124 2022/10/26 05:13:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:13:26 - mmengine - INFO - Epoch(train) [762][60/63] lr: 1.4284e-03 eta: 5:32:52 time: 0.5399 data_time: 0.0171 memory: 16131 loss: 1.0998 loss_prob: 0.5849 loss_thr: 0.4103 loss_db: 0.1047 2022/10/26 05:13:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:13:31 - mmengine - INFO - Epoch(train) [763][5/63] lr: 1.4255e-03 eta: 5:32:52 time: 0.6860 data_time: 0.1838 memory: 16131 loss: 1.0413 loss_prob: 0.5474 loss_thr: 0.4006 loss_db: 0.0933 2022/10/26 05:13:34 - mmengine - INFO - Epoch(train) [763][10/63] lr: 1.4255e-03 eta: 5:32:42 time: 0.7042 data_time: 0.1820 memory: 16131 loss: 1.1188 loss_prob: 0.5998 loss_thr: 0.4188 loss_db: 0.1003 2022/10/26 05:13:37 - mmengine - INFO - Epoch(train) [763][15/63] lr: 1.4255e-03 eta: 5:32:42 time: 0.5658 data_time: 0.0129 memory: 16131 loss: 1.1661 loss_prob: 0.6234 loss_thr: 0.4351 loss_db: 0.1077 2022/10/26 05:13:39 - mmengine - INFO - Epoch(train) [763][20/63] lr: 1.4255e-03 eta: 5:32:33 time: 0.5487 data_time: 0.0108 memory: 16131 loss: 1.1150 loss_prob: 0.5877 loss_thr: 0.4263 loss_db: 0.1009 2022/10/26 05:13:42 - mmengine - INFO - Epoch(train) [763][25/63] lr: 1.4255e-03 eta: 5:32:33 time: 0.5227 data_time: 0.0260 memory: 16131 loss: 1.1647 loss_prob: 0.6247 loss_thr: 0.4357 loss_db: 0.1044 2022/10/26 05:13:45 - mmengine - INFO - Epoch(train) [763][30/63] lr: 1.4255e-03 eta: 5:32:25 time: 0.5122 data_time: 0.0260 memory: 16131 loss: 1.1987 loss_prob: 0.6449 loss_thr: 0.4412 loss_db: 0.1126 2022/10/26 05:13:47 - mmengine - INFO - Epoch(train) [763][35/63] lr: 1.4255e-03 eta: 5:32:25 time: 0.5007 data_time: 0.0087 memory: 16131 loss: 1.2147 loss_prob: 0.6527 loss_thr: 0.4477 loss_db: 0.1143 2022/10/26 05:13:51 - mmengine - INFO - Epoch(train) [763][40/63] lr: 1.4255e-03 eta: 5:32:17 time: 0.6151 data_time: 0.0127 memory: 16131 loss: 1.2624 loss_prob: 0.6867 loss_thr: 0.4594 loss_db: 0.1162 2022/10/26 05:13:53 - mmengine - INFO - Epoch(train) [763][45/63] lr: 1.4255e-03 eta: 5:32:17 time: 0.6205 data_time: 0.0086 memory: 16131 loss: 1.2257 loss_prob: 0.6607 loss_thr: 0.4531 loss_db: 0.1119 2022/10/26 05:13:56 - mmengine - INFO - Epoch(train) [763][50/63] lr: 1.4255e-03 eta: 5:32:09 time: 0.5385 data_time: 0.0257 memory: 16131 loss: 1.2370 loss_prob: 0.6651 loss_thr: 0.4587 loss_db: 0.1133 2022/10/26 05:13:59 - mmengine - INFO - Epoch(train) [763][55/63] lr: 1.4255e-03 eta: 5:32:09 time: 0.5313 data_time: 0.0274 memory: 16131 loss: 1.2072 loss_prob: 0.6504 loss_thr: 0.4449 loss_db: 0.1119 2022/10/26 05:14:01 - mmengine - INFO - Epoch(train) [763][60/63] lr: 1.4255e-03 eta: 5:32:00 time: 0.5026 data_time: 0.0096 memory: 16131 loss: 1.1309 loss_prob: 0.6021 loss_thr: 0.4281 loss_db: 0.1006 2022/10/26 05:14:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:14:07 - mmengine - INFO - Epoch(train) [764][5/63] lr: 1.4225e-03 eta: 5:32:00 time: 0.7087 data_time: 0.2071 memory: 16131 loss: 1.1067 loss_prob: 0.5824 loss_thr: 0.4248 loss_db: 0.0995 2022/10/26 05:14:10 - mmengine - INFO - Epoch(train) [764][10/63] lr: 1.4225e-03 eta: 5:31:50 time: 0.7185 data_time: 0.2025 memory: 16131 loss: 1.1169 loss_prob: 0.5869 loss_thr: 0.4271 loss_db: 0.1029 2022/10/26 05:14:12 - mmengine - INFO - Epoch(train) [764][15/63] lr: 1.4225e-03 eta: 5:31:50 time: 0.5049 data_time: 0.0085 memory: 16131 loss: 1.0933 loss_prob: 0.5775 loss_thr: 0.4156 loss_db: 0.1002 2022/10/26 05:14:15 - mmengine - INFO - Epoch(train) [764][20/63] lr: 1.4225e-03 eta: 5:31:41 time: 0.5227 data_time: 0.0054 memory: 16131 loss: 1.0880 loss_prob: 0.5775 loss_thr: 0.4111 loss_db: 0.0994 2022/10/26 05:14:18 - mmengine - INFO - Epoch(train) [764][25/63] lr: 1.4225e-03 eta: 5:31:41 time: 0.5292 data_time: 0.0120 memory: 16131 loss: 1.0078 loss_prob: 0.5207 loss_thr: 0.3958 loss_db: 0.0913 2022/10/26 05:14:20 - mmengine - INFO - Epoch(train) [764][30/63] lr: 1.4225e-03 eta: 5:31:33 time: 0.5270 data_time: 0.0371 memory: 16131 loss: 1.0472 loss_prob: 0.5511 loss_thr: 0.3997 loss_db: 0.0964 2022/10/26 05:14:23 - mmengine - INFO - Epoch(train) [764][35/63] lr: 1.4225e-03 eta: 5:31:33 time: 0.5374 data_time: 0.0297 memory: 16131 loss: 1.0811 loss_prob: 0.5773 loss_thr: 0.4053 loss_db: 0.0985 2022/10/26 05:14:26 - mmengine - INFO - Epoch(train) [764][40/63] lr: 1.4225e-03 eta: 5:31:25 time: 0.5623 data_time: 0.0052 memory: 16131 loss: 1.0704 loss_prob: 0.5655 loss_thr: 0.4082 loss_db: 0.0967 2022/10/26 05:14:29 - mmengine - INFO - Epoch(train) [764][45/63] lr: 1.4225e-03 eta: 5:31:25 time: 0.5571 data_time: 0.0055 memory: 16131 loss: 1.0787 loss_prob: 0.5732 loss_thr: 0.4055 loss_db: 0.1000 2022/10/26 05:14:31 - mmengine - INFO - Epoch(train) [764][50/63] lr: 1.4225e-03 eta: 5:31:16 time: 0.5418 data_time: 0.0224 memory: 16131 loss: 1.1219 loss_prob: 0.6010 loss_thr: 0.4164 loss_db: 0.1045 2022/10/26 05:14:34 - mmengine - INFO - Epoch(train) [764][55/63] lr: 1.4225e-03 eta: 5:31:16 time: 0.5623 data_time: 0.0222 memory: 16131 loss: 1.1266 loss_prob: 0.5974 loss_thr: 0.4262 loss_db: 0.1031 2022/10/26 05:14:37 - mmengine - INFO - Epoch(train) [764][60/63] lr: 1.4225e-03 eta: 5:31:08 time: 0.5219 data_time: 0.0051 memory: 16131 loss: 1.0538 loss_prob: 0.5506 loss_thr: 0.4088 loss_db: 0.0944 2022/10/26 05:14:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:14:42 - mmengine - INFO - Epoch(train) [765][5/63] lr: 1.4196e-03 eta: 5:31:08 time: 0.6671 data_time: 0.1828 memory: 16131 loss: 1.0462 loss_prob: 0.5452 loss_thr: 0.4061 loss_db: 0.0950 2022/10/26 05:14:45 - mmengine - INFO - Epoch(train) [765][10/63] lr: 1.4196e-03 eta: 5:30:57 time: 0.7190 data_time: 0.1802 memory: 16131 loss: 1.1494 loss_prob: 0.6110 loss_thr: 0.4322 loss_db: 0.1062 2022/10/26 05:14:48 - mmengine - INFO - Epoch(train) [765][15/63] lr: 1.4196e-03 eta: 5:30:57 time: 0.5575 data_time: 0.0086 memory: 16131 loss: 1.1294 loss_prob: 0.6066 loss_thr: 0.4193 loss_db: 0.1034 2022/10/26 05:14:50 - mmengine - INFO - Epoch(train) [765][20/63] lr: 1.4196e-03 eta: 5:30:49 time: 0.5172 data_time: 0.0086 memory: 16131 loss: 1.1757 loss_prob: 0.6308 loss_thr: 0.4365 loss_db: 0.1084 2022/10/26 05:14:53 - mmengine - INFO - Epoch(train) [765][25/63] lr: 1.4196e-03 eta: 5:30:49 time: 0.4985 data_time: 0.0147 memory: 16131 loss: 1.1849 loss_prob: 0.6280 loss_thr: 0.4480 loss_db: 0.1090 2022/10/26 05:14:56 - mmengine - INFO - Epoch(train) [765][30/63] lr: 1.4196e-03 eta: 5:30:41 time: 0.5480 data_time: 0.0260 memory: 16131 loss: 1.1536 loss_prob: 0.6290 loss_thr: 0.4192 loss_db: 0.1054 2022/10/26 05:14:58 - mmengine - INFO - Epoch(train) [765][35/63] lr: 1.4196e-03 eta: 5:30:41 time: 0.5275 data_time: 0.0169 memory: 16131 loss: 1.2127 loss_prob: 0.6753 loss_thr: 0.4269 loss_db: 0.1106 2022/10/26 05:15:01 - mmengine - INFO - Epoch(train) [765][40/63] lr: 1.4196e-03 eta: 5:30:32 time: 0.4917 data_time: 0.0146 memory: 16131 loss: 1.1329 loss_prob: 0.6035 loss_thr: 0.4278 loss_db: 0.1017 2022/10/26 05:15:03 - mmengine - INFO - Epoch(train) [765][45/63] lr: 1.4196e-03 eta: 5:30:32 time: 0.5117 data_time: 0.0189 memory: 16131 loss: 1.0511 loss_prob: 0.5501 loss_thr: 0.4043 loss_db: 0.0967 2022/10/26 05:15:06 - mmengine - INFO - Epoch(train) [765][50/63] lr: 1.4196e-03 eta: 5:30:24 time: 0.5273 data_time: 0.0273 memory: 16131 loss: 1.1042 loss_prob: 0.5947 loss_thr: 0.4079 loss_db: 0.1016 2022/10/26 05:15:08 - mmengine - INFO - Epoch(train) [765][55/63] lr: 1.4196e-03 eta: 5:30:24 time: 0.5106 data_time: 0.0224 memory: 16131 loss: 1.1237 loss_prob: 0.6038 loss_thr: 0.4193 loss_db: 0.1005 2022/10/26 05:15:11 - mmengine - INFO - Epoch(train) [765][60/63] lr: 1.4196e-03 eta: 5:30:15 time: 0.4920 data_time: 0.0161 memory: 16131 loss: 1.1294 loss_prob: 0.5935 loss_thr: 0.4340 loss_db: 0.1019 2022/10/26 05:15:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:15:17 - mmengine - INFO - Epoch(train) [766][5/63] lr: 1.4167e-03 eta: 5:30:15 time: 0.7086 data_time: 0.2296 memory: 16131 loss: 1.1973 loss_prob: 0.6521 loss_thr: 0.4273 loss_db: 0.1180 2022/10/26 05:15:20 - mmengine - INFO - Epoch(train) [766][10/63] lr: 1.4167e-03 eta: 5:30:05 time: 0.7548 data_time: 0.2278 memory: 16131 loss: 1.1777 loss_prob: 0.6484 loss_thr: 0.4128 loss_db: 0.1165 2022/10/26 05:15:22 - mmengine - INFO - Epoch(train) [766][15/63] lr: 1.4167e-03 eta: 5:30:05 time: 0.5197 data_time: 0.0090 memory: 16131 loss: 1.1102 loss_prob: 0.5958 loss_thr: 0.4138 loss_db: 0.1006 2022/10/26 05:15:25 - mmengine - INFO - Epoch(train) [766][20/63] lr: 1.4167e-03 eta: 5:29:56 time: 0.5260 data_time: 0.0100 memory: 16131 loss: 1.0864 loss_prob: 0.5794 loss_thr: 0.4075 loss_db: 0.0995 2022/10/26 05:15:28 - mmengine - INFO - Epoch(train) [766][25/63] lr: 1.4167e-03 eta: 5:29:56 time: 0.5633 data_time: 0.0361 memory: 16131 loss: 1.2289 loss_prob: 0.6857 loss_thr: 0.4340 loss_db: 0.1092 2022/10/26 05:15:30 - mmengine - INFO - Epoch(train) [766][30/63] lr: 1.4167e-03 eta: 5:29:48 time: 0.5391 data_time: 0.0326 memory: 16131 loss: 1.2516 loss_prob: 0.7077 loss_thr: 0.4328 loss_db: 0.1111 2022/10/26 05:15:33 - mmengine - INFO - Epoch(train) [766][35/63] lr: 1.4167e-03 eta: 5:29:48 time: 0.4931 data_time: 0.0054 memory: 16131 loss: 1.1227 loss_prob: 0.5988 loss_thr: 0.4216 loss_db: 0.1023 2022/10/26 05:15:36 - mmengine - INFO - Epoch(train) [766][40/63] lr: 1.4167e-03 eta: 5:29:40 time: 0.5127 data_time: 0.0060 memory: 16131 loss: 1.0639 loss_prob: 0.5640 loss_thr: 0.4042 loss_db: 0.0957 2022/10/26 05:15:38 - mmengine - INFO - Epoch(train) [766][45/63] lr: 1.4167e-03 eta: 5:29:40 time: 0.5450 data_time: 0.0057 memory: 16131 loss: 1.1052 loss_prob: 0.5964 loss_thr: 0.4086 loss_db: 0.1001 2022/10/26 05:15:41 - mmengine - INFO - Epoch(train) [766][50/63] lr: 1.4167e-03 eta: 5:29:32 time: 0.5632 data_time: 0.0223 memory: 16131 loss: 1.1973 loss_prob: 0.6469 loss_thr: 0.4403 loss_db: 0.1101 2022/10/26 05:15:44 - mmengine - INFO - Epoch(train) [766][55/63] lr: 1.4167e-03 eta: 5:29:32 time: 0.5391 data_time: 0.0261 memory: 16131 loss: 1.1701 loss_prob: 0.6244 loss_thr: 0.4373 loss_db: 0.1084 2022/10/26 05:15:46 - mmengine - INFO - Epoch(train) [766][60/63] lr: 1.4167e-03 eta: 5:29:23 time: 0.4927 data_time: 0.0088 memory: 16131 loss: 1.1375 loss_prob: 0.6051 loss_thr: 0.4283 loss_db: 0.1041 2022/10/26 05:15:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:15:52 - mmengine - INFO - Epoch(train) [767][5/63] lr: 1.4137e-03 eta: 5:29:23 time: 0.6758 data_time: 0.1870 memory: 16131 loss: 1.1815 loss_prob: 0.6353 loss_thr: 0.4371 loss_db: 0.1090 2022/10/26 05:15:55 - mmengine - INFO - Epoch(train) [767][10/63] lr: 1.4137e-03 eta: 5:29:13 time: 0.7442 data_time: 0.1892 memory: 16131 loss: 1.1579 loss_prob: 0.6228 loss_thr: 0.4268 loss_db: 0.1083 2022/10/26 05:15:57 - mmengine - INFO - Epoch(train) [767][15/63] lr: 1.4137e-03 eta: 5:29:13 time: 0.5558 data_time: 0.0097 memory: 16131 loss: 1.1457 loss_prob: 0.6171 loss_thr: 0.4228 loss_db: 0.1058 2022/10/26 05:16:00 - mmengine - INFO - Epoch(train) [767][20/63] lr: 1.4137e-03 eta: 5:29:04 time: 0.4979 data_time: 0.0099 memory: 16131 loss: 1.1830 loss_prob: 0.6372 loss_thr: 0.4356 loss_db: 0.1102 2022/10/26 05:16:03 - mmengine - INFO - Epoch(train) [767][25/63] lr: 1.4137e-03 eta: 5:29:04 time: 0.5134 data_time: 0.0128 memory: 16131 loss: 1.1220 loss_prob: 0.5947 loss_thr: 0.4234 loss_db: 0.1040 2022/10/26 05:16:05 - mmengine - INFO - Epoch(train) [767][30/63] lr: 1.4137e-03 eta: 5:28:56 time: 0.5354 data_time: 0.0329 memory: 16131 loss: 1.0267 loss_prob: 0.5434 loss_thr: 0.3893 loss_db: 0.0940 2022/10/26 05:16:08 - mmengine - INFO - Epoch(train) [767][35/63] lr: 1.4137e-03 eta: 5:28:56 time: 0.5351 data_time: 0.0292 memory: 16131 loss: 1.1279 loss_prob: 0.6225 loss_thr: 0.4026 loss_db: 0.1028 2022/10/26 05:16:10 - mmengine - INFO - Epoch(train) [767][40/63] lr: 1.4137e-03 eta: 5:28:47 time: 0.5137 data_time: 0.0075 memory: 16131 loss: 1.2562 loss_prob: 0.7086 loss_thr: 0.4340 loss_db: 0.1136 2022/10/26 05:16:13 - mmengine - INFO - Epoch(train) [767][45/63] lr: 1.4137e-03 eta: 5:28:47 time: 0.5336 data_time: 0.0093 memory: 16131 loss: 1.2686 loss_prob: 0.7011 loss_thr: 0.4532 loss_db: 0.1143 2022/10/26 05:16:16 - mmengine - INFO - Epoch(train) [767][50/63] lr: 1.4137e-03 eta: 5:28:39 time: 0.5557 data_time: 0.0263 memory: 16131 loss: 1.2810 loss_prob: 0.6987 loss_thr: 0.4658 loss_db: 0.1165 2022/10/26 05:16:18 - mmengine - INFO - Epoch(train) [767][55/63] lr: 1.4137e-03 eta: 5:28:39 time: 0.5196 data_time: 0.0235 memory: 16131 loss: 1.1920 loss_prob: 0.6383 loss_thr: 0.4445 loss_db: 0.1092 2022/10/26 05:16:21 - mmengine - INFO - Epoch(train) [767][60/63] lr: 1.4137e-03 eta: 5:28:31 time: 0.4999 data_time: 0.0047 memory: 16131 loss: 1.1909 loss_prob: 0.6359 loss_thr: 0.4446 loss_db: 0.1104 2022/10/26 05:16:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:16:27 - mmengine - INFO - Epoch(train) [768][5/63] lr: 1.4108e-03 eta: 5:28:31 time: 0.6655 data_time: 0.1811 memory: 16131 loss: 1.2397 loss_prob: 0.6937 loss_thr: 0.4294 loss_db: 0.1167 2022/10/26 05:16:29 - mmengine - INFO - Epoch(train) [768][10/63] lr: 1.4108e-03 eta: 5:28:20 time: 0.6780 data_time: 0.1804 memory: 16131 loss: 1.3062 loss_prob: 0.7374 loss_thr: 0.4480 loss_db: 0.1208 2022/10/26 05:16:32 - mmengine - INFO - Epoch(train) [768][15/63] lr: 1.4108e-03 eta: 5:28:20 time: 0.4917 data_time: 0.0075 memory: 16131 loss: 1.3730 loss_prob: 0.7559 loss_thr: 0.4923 loss_db: 0.1247 2022/10/26 05:16:34 - mmengine - INFO - Epoch(train) [768][20/63] lr: 1.4108e-03 eta: 5:28:11 time: 0.5021 data_time: 0.0074 memory: 16131 loss: 1.3281 loss_prob: 0.7260 loss_thr: 0.4793 loss_db: 0.1228 2022/10/26 05:16:37 - mmengine - INFO - Epoch(train) [768][25/63] lr: 1.4108e-03 eta: 5:28:11 time: 0.5049 data_time: 0.0265 memory: 16131 loss: 1.2272 loss_prob: 0.6750 loss_thr: 0.4353 loss_db: 0.1169 2022/10/26 05:16:39 - mmengine - INFO - Epoch(train) [768][30/63] lr: 1.4108e-03 eta: 5:28:03 time: 0.4945 data_time: 0.0358 memory: 16131 loss: 1.2623 loss_prob: 0.7017 loss_thr: 0.4390 loss_db: 0.1216 2022/10/26 05:16:42 - mmengine - INFO - Epoch(train) [768][35/63] lr: 1.4108e-03 eta: 5:28:03 time: 0.5006 data_time: 0.0177 memory: 16131 loss: 1.2054 loss_prob: 0.6722 loss_thr: 0.4211 loss_db: 0.1122 2022/10/26 05:16:44 - mmengine - INFO - Epoch(train) [768][40/63] lr: 1.4108e-03 eta: 5:27:54 time: 0.4973 data_time: 0.0110 memory: 16131 loss: 1.1737 loss_prob: 0.6516 loss_thr: 0.4157 loss_db: 0.1064 2022/10/26 05:16:47 - mmengine - INFO - Epoch(train) [768][45/63] lr: 1.4108e-03 eta: 5:27:54 time: 0.4989 data_time: 0.0081 memory: 16131 loss: 1.1856 loss_prob: 0.6450 loss_thr: 0.4304 loss_db: 0.1101 2022/10/26 05:16:49 - mmengine - INFO - Epoch(train) [768][50/63] lr: 1.4108e-03 eta: 5:27:46 time: 0.5257 data_time: 0.0160 memory: 16131 loss: 1.1440 loss_prob: 0.6168 loss_thr: 0.4203 loss_db: 0.1070 2022/10/26 05:16:52 - mmengine - INFO - Epoch(train) [768][55/63] lr: 1.4108e-03 eta: 5:27:46 time: 0.5288 data_time: 0.0223 memory: 16131 loss: 1.1281 loss_prob: 0.5989 loss_thr: 0.4259 loss_db: 0.1033 2022/10/26 05:16:54 - mmengine - INFO - Epoch(train) [768][60/63] lr: 1.4108e-03 eta: 5:27:38 time: 0.5192 data_time: 0.0145 memory: 16131 loss: 1.1339 loss_prob: 0.5958 loss_thr: 0.4355 loss_db: 0.1026 2022/10/26 05:16:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:17:00 - mmengine - INFO - Epoch(train) [769][5/63] lr: 1.4079e-03 eta: 5:27:38 time: 0.6651 data_time: 0.1710 memory: 16131 loss: 1.0569 loss_prob: 0.5457 loss_thr: 0.4156 loss_db: 0.0955 2022/10/26 05:17:03 - mmengine - INFO - Epoch(train) [769][10/63] lr: 1.4079e-03 eta: 5:27:27 time: 0.6948 data_time: 0.1791 memory: 16131 loss: 1.1428 loss_prob: 0.6065 loss_thr: 0.4307 loss_db: 0.1056 2022/10/26 05:17:06 - mmengine - INFO - Epoch(train) [769][15/63] lr: 1.4079e-03 eta: 5:27:27 time: 0.5500 data_time: 0.0173 memory: 16131 loss: 1.3728 loss_prob: 0.7893 loss_thr: 0.4579 loss_db: 0.1256 2022/10/26 05:17:08 - mmengine - INFO - Epoch(train) [769][20/63] lr: 1.4079e-03 eta: 5:27:19 time: 0.5313 data_time: 0.0123 memory: 16131 loss: 1.3458 loss_prob: 0.7722 loss_thr: 0.4491 loss_db: 0.1246 2022/10/26 05:17:11 - mmengine - INFO - Epoch(train) [769][25/63] lr: 1.4079e-03 eta: 5:27:19 time: 0.5201 data_time: 0.0248 memory: 16131 loss: 1.1629 loss_prob: 0.6342 loss_thr: 0.4192 loss_db: 0.1095 2022/10/26 05:17:13 - mmengine - INFO - Epoch(train) [769][30/63] lr: 1.4079e-03 eta: 5:27:10 time: 0.5272 data_time: 0.0301 memory: 16131 loss: 1.1565 loss_prob: 0.6233 loss_thr: 0.4251 loss_db: 0.1081 2022/10/26 05:17:16 - mmengine - INFO - Epoch(train) [769][35/63] lr: 1.4079e-03 eta: 5:27:10 time: 0.5201 data_time: 0.0248 memory: 16131 loss: 1.1383 loss_prob: 0.6080 loss_thr: 0.4229 loss_db: 0.1074 2022/10/26 05:17:18 - mmengine - INFO - Epoch(train) [769][40/63] lr: 1.4079e-03 eta: 5:27:02 time: 0.4965 data_time: 0.0160 memory: 16131 loss: 1.1816 loss_prob: 0.6411 loss_thr: 0.4345 loss_db: 0.1060 2022/10/26 05:17:21 - mmengine - INFO - Epoch(train) [769][45/63] lr: 1.4079e-03 eta: 5:27:02 time: 0.5047 data_time: 0.0060 memory: 16131 loss: 1.1868 loss_prob: 0.6454 loss_thr: 0.4358 loss_db: 0.1056 2022/10/26 05:17:24 - mmengine - INFO - Epoch(train) [769][50/63] lr: 1.4079e-03 eta: 5:26:54 time: 0.5247 data_time: 0.0119 memory: 16131 loss: 1.1368 loss_prob: 0.6087 loss_thr: 0.4228 loss_db: 0.1052 2022/10/26 05:17:26 - mmengine - INFO - Epoch(train) [769][55/63] lr: 1.4079e-03 eta: 5:26:54 time: 0.5087 data_time: 0.0177 memory: 16131 loss: 1.1792 loss_prob: 0.6309 loss_thr: 0.4392 loss_db: 0.1091 2022/10/26 05:17:29 - mmengine - INFO - Epoch(train) [769][60/63] lr: 1.4079e-03 eta: 5:26:45 time: 0.5126 data_time: 0.0177 memory: 16131 loss: 1.2069 loss_prob: 0.6492 loss_thr: 0.4459 loss_db: 0.1118 2022/10/26 05:17:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:17:36 - mmengine - INFO - Epoch(train) [770][5/63] lr: 1.4049e-03 eta: 5:26:45 time: 0.8039 data_time: 0.1839 memory: 16131 loss: 1.1438 loss_prob: 0.6157 loss_thr: 0.4210 loss_db: 0.1072 2022/10/26 05:17:38 - mmengine - INFO - Epoch(train) [770][10/63] lr: 1.4049e-03 eta: 5:26:35 time: 0.7748 data_time: 0.1813 memory: 16131 loss: 1.0628 loss_prob: 0.5701 loss_thr: 0.3931 loss_db: 0.0996 2022/10/26 05:17:41 - mmengine - INFO - Epoch(train) [770][15/63] lr: 1.4049e-03 eta: 5:26:35 time: 0.5099 data_time: 0.0092 memory: 16131 loss: 1.1826 loss_prob: 0.6474 loss_thr: 0.4279 loss_db: 0.1073 2022/10/26 05:17:43 - mmengine - INFO - Epoch(train) [770][20/63] lr: 1.4049e-03 eta: 5:26:26 time: 0.5154 data_time: 0.0088 memory: 16131 loss: 1.2417 loss_prob: 0.6810 loss_thr: 0.4497 loss_db: 0.1110 2022/10/26 05:17:46 - mmengine - INFO - Epoch(train) [770][25/63] lr: 1.4049e-03 eta: 5:26:26 time: 0.5159 data_time: 0.0083 memory: 16131 loss: 1.1854 loss_prob: 0.6374 loss_thr: 0.4404 loss_db: 0.1076 2022/10/26 05:17:49 - mmengine - INFO - Epoch(train) [770][30/63] lr: 1.4049e-03 eta: 5:26:18 time: 0.5664 data_time: 0.0325 memory: 16131 loss: 1.2373 loss_prob: 0.6737 loss_thr: 0.4500 loss_db: 0.1136 2022/10/26 05:17:52 - mmengine - INFO - Epoch(train) [770][35/63] lr: 1.4049e-03 eta: 5:26:18 time: 0.5814 data_time: 0.0315 memory: 16131 loss: 1.1917 loss_prob: 0.6492 loss_thr: 0.4353 loss_db: 0.1072 2022/10/26 05:17:54 - mmengine - INFO - Epoch(train) [770][40/63] lr: 1.4049e-03 eta: 5:26:10 time: 0.5443 data_time: 0.0075 memory: 16131 loss: 1.1057 loss_prob: 0.5801 loss_thr: 0.4266 loss_db: 0.0990 2022/10/26 05:17:57 - mmengine - INFO - Epoch(train) [770][45/63] lr: 1.4049e-03 eta: 5:26:10 time: 0.5063 data_time: 0.0090 memory: 16131 loss: 1.1636 loss_prob: 0.6177 loss_thr: 0.4382 loss_db: 0.1077 2022/10/26 05:17:59 - mmengine - INFO - Epoch(train) [770][50/63] lr: 1.4049e-03 eta: 5:26:02 time: 0.5099 data_time: 0.0216 memory: 16131 loss: 1.1538 loss_prob: 0.6185 loss_thr: 0.4294 loss_db: 0.1059 2022/10/26 05:18:02 - mmengine - INFO - Epoch(train) [770][55/63] lr: 1.4049e-03 eta: 5:26:02 time: 0.5171 data_time: 0.0293 memory: 16131 loss: 1.0976 loss_prob: 0.5839 loss_thr: 0.4148 loss_db: 0.0989 2022/10/26 05:18:04 - mmengine - INFO - Epoch(train) [770][60/63] lr: 1.4049e-03 eta: 5:25:53 time: 0.4942 data_time: 0.0152 memory: 16131 loss: 1.0448 loss_prob: 0.5504 loss_thr: 0.3979 loss_db: 0.0964 2022/10/26 05:18:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:18:11 - mmengine - INFO - Epoch(train) [771][5/63] lr: 1.4020e-03 eta: 5:25:53 time: 0.7252 data_time: 0.2307 memory: 16131 loss: 1.1923 loss_prob: 0.6545 loss_thr: 0.4304 loss_db: 0.1074 2022/10/26 05:18:13 - mmengine - INFO - Epoch(train) [771][10/63] lr: 1.4020e-03 eta: 5:25:43 time: 0.7400 data_time: 0.2288 memory: 16131 loss: 1.0989 loss_prob: 0.5850 loss_thr: 0.4132 loss_db: 0.1007 2022/10/26 05:18:16 - mmengine - INFO - Epoch(train) [771][15/63] lr: 1.4020e-03 eta: 5:25:43 time: 0.5023 data_time: 0.0067 memory: 16131 loss: 1.0890 loss_prob: 0.5758 loss_thr: 0.4127 loss_db: 0.1005 2022/10/26 05:18:18 - mmengine - INFO - Epoch(train) [771][20/63] lr: 1.4020e-03 eta: 5:25:34 time: 0.5268 data_time: 0.0108 memory: 16131 loss: 1.1344 loss_prob: 0.6013 loss_thr: 0.4303 loss_db: 0.1028 2022/10/26 05:18:21 - mmengine - INFO - Epoch(train) [771][25/63] lr: 1.4020e-03 eta: 5:25:34 time: 0.5372 data_time: 0.0172 memory: 16131 loss: 1.1575 loss_prob: 0.6163 loss_thr: 0.4367 loss_db: 0.1046 2022/10/26 05:18:24 - mmengine - INFO - Epoch(train) [771][30/63] lr: 1.4020e-03 eta: 5:25:26 time: 0.5360 data_time: 0.0364 memory: 16131 loss: 1.2054 loss_prob: 0.6411 loss_thr: 0.4539 loss_db: 0.1104 2022/10/26 05:18:26 - mmengine - INFO - Epoch(train) [771][35/63] lr: 1.4020e-03 eta: 5:25:26 time: 0.5162 data_time: 0.0284 memory: 16131 loss: 1.1814 loss_prob: 0.6311 loss_thr: 0.4426 loss_db: 0.1078 2022/10/26 05:18:29 - mmengine - INFO - Epoch(train) [771][40/63] lr: 1.4020e-03 eta: 5:25:18 time: 0.5270 data_time: 0.0065 memory: 16131 loss: 1.1371 loss_prob: 0.5986 loss_thr: 0.4361 loss_db: 0.1024 2022/10/26 05:18:32 - mmengine - INFO - Epoch(train) [771][45/63] lr: 1.4020e-03 eta: 5:25:18 time: 0.5282 data_time: 0.0097 memory: 16131 loss: 1.1494 loss_prob: 0.5997 loss_thr: 0.4453 loss_db: 0.1044 2022/10/26 05:18:34 - mmengine - INFO - Epoch(train) [771][50/63] lr: 1.4020e-03 eta: 5:25:10 time: 0.5273 data_time: 0.0204 memory: 16131 loss: 1.1300 loss_prob: 0.5987 loss_thr: 0.4291 loss_db: 0.1021 2022/10/26 05:18:37 - mmengine - INFO - Epoch(train) [771][55/63] lr: 1.4020e-03 eta: 5:25:10 time: 0.5636 data_time: 0.0227 memory: 16131 loss: 1.3706 loss_prob: 0.7973 loss_thr: 0.4447 loss_db: 0.1286 2022/10/26 05:18:40 - mmengine - INFO - Epoch(train) [771][60/63] lr: 1.4020e-03 eta: 5:25:01 time: 0.5455 data_time: 0.0102 memory: 16131 loss: 1.4482 loss_prob: 0.8467 loss_thr: 0.4631 loss_db: 0.1384 2022/10/26 05:18:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:18:46 - mmengine - INFO - Epoch(train) [772][5/63] lr: 1.3990e-03 eta: 5:25:01 time: 0.7633 data_time: 0.1667 memory: 16131 loss: 1.2610 loss_prob: 0.6909 loss_thr: 0.4530 loss_db: 0.1170 2022/10/26 05:18:49 - mmengine - INFO - Epoch(train) [772][10/63] lr: 1.3990e-03 eta: 5:24:51 time: 0.8386 data_time: 0.1873 memory: 16131 loss: 1.2423 loss_prob: 0.6808 loss_thr: 0.4466 loss_db: 0.1149 2022/10/26 05:18:52 - mmengine - INFO - Epoch(train) [772][15/63] lr: 1.3990e-03 eta: 5:24:51 time: 0.5486 data_time: 0.0262 memory: 16131 loss: 1.2924 loss_prob: 0.7234 loss_thr: 0.4487 loss_db: 0.1203 2022/10/26 05:18:54 - mmengine - INFO - Epoch(train) [772][20/63] lr: 1.3990e-03 eta: 5:24:43 time: 0.5088 data_time: 0.0060 memory: 16131 loss: 1.2289 loss_prob: 0.6764 loss_thr: 0.4374 loss_db: 0.1151 2022/10/26 05:18:57 - mmengine - INFO - Epoch(train) [772][25/63] lr: 1.3990e-03 eta: 5:24:43 time: 0.5149 data_time: 0.0180 memory: 16131 loss: 1.3211 loss_prob: 0.7314 loss_thr: 0.4627 loss_db: 0.1271 2022/10/26 05:19:00 - mmengine - INFO - Epoch(train) [772][30/63] lr: 1.3990e-03 eta: 5:24:35 time: 0.5480 data_time: 0.0364 memory: 16131 loss: 1.3140 loss_prob: 0.7369 loss_thr: 0.4533 loss_db: 0.1239 2022/10/26 05:19:03 - mmengine - INFO - Epoch(train) [772][35/63] lr: 1.3990e-03 eta: 5:24:35 time: 0.5526 data_time: 0.0239 memory: 16131 loss: 1.1497 loss_prob: 0.6157 loss_thr: 0.4244 loss_db: 0.1097 2022/10/26 05:19:05 - mmengine - INFO - Epoch(train) [772][40/63] lr: 1.3990e-03 eta: 5:24:27 time: 0.5171 data_time: 0.0057 memory: 16131 loss: 1.2109 loss_prob: 0.6531 loss_thr: 0.4405 loss_db: 0.1174 2022/10/26 05:19:08 - mmengine - INFO - Epoch(train) [772][45/63] lr: 1.3990e-03 eta: 5:24:27 time: 0.5123 data_time: 0.0066 memory: 16131 loss: 1.1868 loss_prob: 0.6385 loss_thr: 0.4397 loss_db: 0.1086 2022/10/26 05:19:11 - mmengine - INFO - Epoch(train) [772][50/63] lr: 1.3990e-03 eta: 5:24:18 time: 0.5475 data_time: 0.0133 memory: 16131 loss: 1.1502 loss_prob: 0.6133 loss_thr: 0.4325 loss_db: 0.1043 2022/10/26 05:19:13 - mmengine - INFO - Epoch(train) [772][55/63] lr: 1.3990e-03 eta: 5:24:18 time: 0.5412 data_time: 0.0239 memory: 16131 loss: 1.1158 loss_prob: 0.5884 loss_thr: 0.4256 loss_db: 0.1017 2022/10/26 05:19:16 - mmengine - INFO - Epoch(train) [772][60/63] lr: 1.3990e-03 eta: 5:24:10 time: 0.5403 data_time: 0.0175 memory: 16131 loss: 1.1116 loss_prob: 0.5890 loss_thr: 0.4200 loss_db: 0.1026 2022/10/26 05:19:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:19:22 - mmengine - INFO - Epoch(train) [773][5/63] lr: 1.3961e-03 eta: 5:24:10 time: 0.7658 data_time: 0.1911 memory: 16131 loss: 1.1389 loss_prob: 0.6259 loss_thr: 0.4093 loss_db: 0.1037 2022/10/26 05:19:25 - mmengine - INFO - Epoch(train) [773][10/63] lr: 1.3961e-03 eta: 5:24:00 time: 0.7524 data_time: 0.1955 memory: 16131 loss: 1.1530 loss_prob: 0.6193 loss_thr: 0.4293 loss_db: 0.1044 2022/10/26 05:19:28 - mmengine - INFO - Epoch(train) [773][15/63] lr: 1.3961e-03 eta: 5:24:00 time: 0.5096 data_time: 0.0102 memory: 16131 loss: 1.1283 loss_prob: 0.5919 loss_thr: 0.4332 loss_db: 0.1032 2022/10/26 05:19:30 - mmengine - INFO - Epoch(train) [773][20/63] lr: 1.3961e-03 eta: 5:23:51 time: 0.5179 data_time: 0.0067 memory: 16131 loss: 1.1129 loss_prob: 0.5908 loss_thr: 0.4198 loss_db: 0.1024 2022/10/26 05:19:33 - mmengine - INFO - Epoch(train) [773][25/63] lr: 1.3961e-03 eta: 5:23:51 time: 0.5454 data_time: 0.0296 memory: 16131 loss: 1.1680 loss_prob: 0.6237 loss_thr: 0.4372 loss_db: 0.1071 2022/10/26 05:19:36 - mmengine - INFO - Epoch(train) [773][30/63] lr: 1.3961e-03 eta: 5:23:43 time: 0.5418 data_time: 0.0351 memory: 16131 loss: 1.1643 loss_prob: 0.6128 loss_thr: 0.4461 loss_db: 0.1055 2022/10/26 05:19:38 - mmengine - INFO - Epoch(train) [773][35/63] lr: 1.3961e-03 eta: 5:23:43 time: 0.5092 data_time: 0.0128 memory: 16131 loss: 1.0819 loss_prob: 0.5637 loss_thr: 0.4200 loss_db: 0.0982 2022/10/26 05:19:41 - mmengine - INFO - Epoch(train) [773][40/63] lr: 1.3961e-03 eta: 5:23:35 time: 0.5029 data_time: 0.0075 memory: 16131 loss: 1.0907 loss_prob: 0.5772 loss_thr: 0.4136 loss_db: 0.0999 2022/10/26 05:19:43 - mmengine - INFO - Epoch(train) [773][45/63] lr: 1.3961e-03 eta: 5:23:35 time: 0.5353 data_time: 0.0077 memory: 16131 loss: 1.1187 loss_prob: 0.6025 loss_thr: 0.4155 loss_db: 0.1006 2022/10/26 05:19:46 - mmengine - INFO - Epoch(train) [773][50/63] lr: 1.3961e-03 eta: 5:23:27 time: 0.5561 data_time: 0.0252 memory: 16131 loss: 1.0885 loss_prob: 0.5794 loss_thr: 0.4114 loss_db: 0.0977 2022/10/26 05:19:49 - mmengine - INFO - Epoch(train) [773][55/63] lr: 1.3961e-03 eta: 5:23:27 time: 0.5453 data_time: 0.0270 memory: 16131 loss: 1.1099 loss_prob: 0.5790 loss_thr: 0.4309 loss_db: 0.1000 2022/10/26 05:19:51 - mmengine - INFO - Epoch(train) [773][60/63] lr: 1.3961e-03 eta: 5:23:18 time: 0.5180 data_time: 0.0097 memory: 16131 loss: 1.0817 loss_prob: 0.5691 loss_thr: 0.4139 loss_db: 0.0988 2022/10/26 05:19:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:19:57 - mmengine - INFO - Epoch(train) [774][5/63] lr: 1.3931e-03 eta: 5:23:18 time: 0.6704 data_time: 0.1997 memory: 16131 loss: 1.0136 loss_prob: 0.5287 loss_thr: 0.3925 loss_db: 0.0924 2022/10/26 05:20:00 - mmengine - INFO - Epoch(train) [774][10/63] lr: 1.3931e-03 eta: 5:23:08 time: 0.7109 data_time: 0.2018 memory: 16131 loss: 1.1110 loss_prob: 0.5907 loss_thr: 0.4162 loss_db: 0.1041 2022/10/26 05:20:02 - mmengine - INFO - Epoch(train) [774][15/63] lr: 1.3931e-03 eta: 5:23:08 time: 0.5018 data_time: 0.0082 memory: 16131 loss: 1.0635 loss_prob: 0.5680 loss_thr: 0.3974 loss_db: 0.0981 2022/10/26 05:20:05 - mmengine - INFO - Epoch(train) [774][20/63] lr: 1.3931e-03 eta: 5:22:59 time: 0.5231 data_time: 0.0059 memory: 16131 loss: 1.0142 loss_prob: 0.5380 loss_thr: 0.3850 loss_db: 0.0912 2022/10/26 05:20:08 - mmengine - INFO - Epoch(train) [774][25/63] lr: 1.3931e-03 eta: 5:22:59 time: 0.5738 data_time: 0.0229 memory: 16131 loss: 1.1067 loss_prob: 0.5945 loss_thr: 0.4108 loss_db: 0.1014 2022/10/26 05:20:10 - mmengine - INFO - Epoch(train) [774][30/63] lr: 1.3931e-03 eta: 5:22:51 time: 0.5556 data_time: 0.0395 memory: 16131 loss: 1.2073 loss_prob: 0.6465 loss_thr: 0.4497 loss_db: 0.1111 2022/10/26 05:20:13 - mmengine - INFO - Epoch(train) [774][35/63] lr: 1.3931e-03 eta: 5:22:51 time: 0.5245 data_time: 0.0219 memory: 16131 loss: 1.1512 loss_prob: 0.6079 loss_thr: 0.4386 loss_db: 0.1048 2022/10/26 05:20:16 - mmengine - INFO - Epoch(train) [774][40/63] lr: 1.3931e-03 eta: 5:22:43 time: 0.5043 data_time: 0.0059 memory: 16131 loss: 1.0510 loss_prob: 0.5533 loss_thr: 0.4022 loss_db: 0.0954 2022/10/26 05:20:18 - mmengine - INFO - Epoch(train) [774][45/63] lr: 1.3931e-03 eta: 5:22:43 time: 0.5181 data_time: 0.0060 memory: 16131 loss: 1.0417 loss_prob: 0.5455 loss_thr: 0.4024 loss_db: 0.0938 2022/10/26 05:20:21 - mmengine - INFO - Epoch(train) [774][50/63] lr: 1.3931e-03 eta: 5:22:35 time: 0.5631 data_time: 0.0200 memory: 16131 loss: 1.0936 loss_prob: 0.5878 loss_thr: 0.4064 loss_db: 0.0994 2022/10/26 05:20:24 - mmengine - INFO - Epoch(train) [774][55/63] lr: 1.3931e-03 eta: 5:22:35 time: 0.5587 data_time: 0.0225 memory: 16131 loss: 1.0727 loss_prob: 0.5811 loss_thr: 0.3911 loss_db: 0.1005 2022/10/26 05:20:26 - mmengine - INFO - Epoch(train) [774][60/63] lr: 1.3931e-03 eta: 5:22:27 time: 0.5313 data_time: 0.0134 memory: 16131 loss: 1.1723 loss_prob: 0.6297 loss_thr: 0.4318 loss_db: 0.1108 2022/10/26 05:20:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:20:32 - mmengine - INFO - Epoch(train) [775][5/63] lr: 1.3902e-03 eta: 5:22:27 time: 0.7009 data_time: 0.2065 memory: 16131 loss: 1.1738 loss_prob: 0.6309 loss_thr: 0.4383 loss_db: 0.1046 2022/10/26 05:20:35 - mmengine - INFO - Epoch(train) [775][10/63] lr: 1.3902e-03 eta: 5:22:16 time: 0.7437 data_time: 0.2050 memory: 16131 loss: 1.1162 loss_prob: 0.5967 loss_thr: 0.4174 loss_db: 0.1020 2022/10/26 05:20:38 - mmengine - INFO - Epoch(train) [775][15/63] lr: 1.3902e-03 eta: 5:22:16 time: 0.5650 data_time: 0.0051 memory: 16131 loss: 1.1667 loss_prob: 0.6266 loss_thr: 0.4302 loss_db: 0.1099 2022/10/26 05:20:41 - mmengine - INFO - Epoch(train) [775][20/63] lr: 1.3902e-03 eta: 5:22:08 time: 0.5173 data_time: 0.0056 memory: 16131 loss: 1.2185 loss_prob: 0.6653 loss_thr: 0.4413 loss_db: 0.1119 2022/10/26 05:20:44 - mmengine - INFO - Epoch(train) [775][25/63] lr: 1.3902e-03 eta: 5:22:08 time: 0.5523 data_time: 0.0503 memory: 16131 loss: 1.2094 loss_prob: 0.6524 loss_thr: 0.4489 loss_db: 0.1081 2022/10/26 05:20:46 - mmengine - INFO - Epoch(train) [775][30/63] lr: 1.3902e-03 eta: 5:22:00 time: 0.5408 data_time: 0.0494 memory: 16131 loss: 1.1028 loss_prob: 0.5794 loss_thr: 0.4221 loss_db: 0.1013 2022/10/26 05:20:48 - mmengine - INFO - Epoch(train) [775][35/63] lr: 1.3902e-03 eta: 5:22:00 time: 0.4824 data_time: 0.0043 memory: 16131 loss: 1.0588 loss_prob: 0.5582 loss_thr: 0.4017 loss_db: 0.0990 2022/10/26 05:20:51 - mmengine - INFO - Epoch(train) [775][40/63] lr: 1.3902e-03 eta: 5:21:51 time: 0.5202 data_time: 0.0082 memory: 16131 loss: 1.1080 loss_prob: 0.5898 loss_thr: 0.4196 loss_db: 0.0987 2022/10/26 05:20:55 - mmengine - INFO - Epoch(train) [775][45/63] lr: 1.3902e-03 eta: 5:21:51 time: 0.6197 data_time: 0.0096 memory: 16131 loss: 1.2008 loss_prob: 0.6571 loss_thr: 0.4352 loss_db: 0.1085 2022/10/26 05:20:58 - mmengine - INFO - Epoch(train) [775][50/63] lr: 1.3902e-03 eta: 5:21:44 time: 0.6398 data_time: 0.0229 memory: 16131 loss: 1.2123 loss_prob: 0.6562 loss_thr: 0.4451 loss_db: 0.1109 2022/10/26 05:21:00 - mmengine - INFO - Epoch(train) [775][55/63] lr: 1.3902e-03 eta: 5:21:44 time: 0.5416 data_time: 0.0220 memory: 16131 loss: 1.2596 loss_prob: 0.6881 loss_thr: 0.4522 loss_db: 0.1192 2022/10/26 05:21:03 - mmengine - INFO - Epoch(train) [775][60/63] lr: 1.3902e-03 eta: 5:21:35 time: 0.5195 data_time: 0.0059 memory: 16131 loss: 1.2225 loss_prob: 0.6735 loss_thr: 0.4329 loss_db: 0.1161 2022/10/26 05:21:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:21:09 - mmengine - INFO - Epoch(train) [776][5/63] lr: 1.3873e-03 eta: 5:21:35 time: 0.7081 data_time: 0.1775 memory: 16131 loss: 1.2244 loss_prob: 0.6689 loss_thr: 0.4392 loss_db: 0.1163 2022/10/26 05:21:11 - mmengine - INFO - Epoch(train) [776][10/63] lr: 1.3873e-03 eta: 5:21:25 time: 0.7320 data_time: 0.1781 memory: 16131 loss: 1.2002 loss_prob: 0.6495 loss_thr: 0.4408 loss_db: 0.1099 2022/10/26 05:21:14 - mmengine - INFO - Epoch(train) [776][15/63] lr: 1.3873e-03 eta: 5:21:25 time: 0.5369 data_time: 0.0119 memory: 16131 loss: 1.1036 loss_prob: 0.5858 loss_thr: 0.4170 loss_db: 0.1008 2022/10/26 05:21:17 - mmengine - INFO - Epoch(train) [776][20/63] lr: 1.3873e-03 eta: 5:21:17 time: 0.5279 data_time: 0.0089 memory: 16131 loss: 1.1023 loss_prob: 0.5800 loss_thr: 0.4209 loss_db: 0.1013 2022/10/26 05:21:19 - mmengine - INFO - Epoch(train) [776][25/63] lr: 1.3873e-03 eta: 5:21:17 time: 0.4994 data_time: 0.0177 memory: 16131 loss: 1.0906 loss_prob: 0.5790 loss_thr: 0.4128 loss_db: 0.0988 2022/10/26 05:21:22 - mmengine - INFO - Epoch(train) [776][30/63] lr: 1.3873e-03 eta: 5:21:08 time: 0.5176 data_time: 0.0346 memory: 16131 loss: 1.0477 loss_prob: 0.5599 loss_thr: 0.3953 loss_db: 0.0924 2022/10/26 05:21:24 - mmengine - INFO - Epoch(train) [776][35/63] lr: 1.3873e-03 eta: 5:21:08 time: 0.5214 data_time: 0.0248 memory: 16131 loss: 1.1110 loss_prob: 0.5911 loss_thr: 0.4201 loss_db: 0.0998 2022/10/26 05:21:27 - mmengine - INFO - Epoch(train) [776][40/63] lr: 1.3873e-03 eta: 5:21:00 time: 0.5416 data_time: 0.0108 memory: 16131 loss: 1.1369 loss_prob: 0.6053 loss_thr: 0.4284 loss_db: 0.1032 2022/10/26 05:21:30 - mmengine - INFO - Epoch(train) [776][45/63] lr: 1.3873e-03 eta: 5:21:00 time: 0.5470 data_time: 0.0098 memory: 16131 loss: 1.0944 loss_prob: 0.5785 loss_thr: 0.4168 loss_db: 0.0991 2022/10/26 05:21:32 - mmengine - INFO - Epoch(train) [776][50/63] lr: 1.3873e-03 eta: 5:20:52 time: 0.5171 data_time: 0.0131 memory: 16131 loss: 1.0544 loss_prob: 0.5508 loss_thr: 0.4080 loss_db: 0.0956 2022/10/26 05:21:35 - mmengine - INFO - Epoch(train) [776][55/63] lr: 1.3873e-03 eta: 5:20:52 time: 0.4996 data_time: 0.0189 memory: 16131 loss: 1.1046 loss_prob: 0.5875 loss_thr: 0.4171 loss_db: 0.1000 2022/10/26 05:21:37 - mmengine - INFO - Epoch(train) [776][60/63] lr: 1.3873e-03 eta: 5:20:43 time: 0.4971 data_time: 0.0144 memory: 16131 loss: 1.2490 loss_prob: 0.6775 loss_thr: 0.4564 loss_db: 0.1151 2022/10/26 05:21:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:21:43 - mmengine - INFO - Epoch(train) [777][5/63] lr: 1.3843e-03 eta: 5:20:43 time: 0.7015 data_time: 0.1953 memory: 16131 loss: 1.2550 loss_prob: 0.6951 loss_thr: 0.4413 loss_db: 0.1186 2022/10/26 05:21:46 - mmengine - INFO - Epoch(train) [777][10/63] lr: 1.3843e-03 eta: 5:20:33 time: 0.7442 data_time: 0.1979 memory: 16131 loss: 1.2301 loss_prob: 0.6766 loss_thr: 0.4417 loss_db: 0.1119 2022/10/26 05:21:49 - mmengine - INFO - Epoch(train) [777][15/63] lr: 1.3843e-03 eta: 5:20:33 time: 0.5552 data_time: 0.0088 memory: 16131 loss: 1.0706 loss_prob: 0.5718 loss_thr: 0.4025 loss_db: 0.0962 2022/10/26 05:21:52 - mmengine - INFO - Epoch(train) [777][20/63] lr: 1.3843e-03 eta: 5:20:25 time: 0.5549 data_time: 0.0115 memory: 16131 loss: 1.1442 loss_prob: 0.6227 loss_thr: 0.4155 loss_db: 0.1060 2022/10/26 05:21:54 - mmengine - INFO - Epoch(train) [777][25/63] lr: 1.3843e-03 eta: 5:20:25 time: 0.5417 data_time: 0.0394 memory: 16131 loss: 1.1791 loss_prob: 0.6401 loss_thr: 0.4286 loss_db: 0.1104 2022/10/26 05:21:57 - mmengine - INFO - Epoch(train) [777][30/63] lr: 1.3843e-03 eta: 5:20:17 time: 0.5222 data_time: 0.0401 memory: 16131 loss: 1.1018 loss_prob: 0.5961 loss_thr: 0.4040 loss_db: 0.1016 2022/10/26 05:22:00 - mmengine - INFO - Epoch(train) [777][35/63] lr: 1.3843e-03 eta: 5:20:17 time: 0.5165 data_time: 0.0111 memory: 16131 loss: 1.1739 loss_prob: 0.6543 loss_thr: 0.4102 loss_db: 0.1095 2022/10/26 05:22:02 - mmengine - INFO - Epoch(train) [777][40/63] lr: 1.3843e-03 eta: 5:20:08 time: 0.5340 data_time: 0.0072 memory: 16131 loss: 1.2370 loss_prob: 0.6730 loss_thr: 0.4503 loss_db: 0.1137 2022/10/26 05:22:05 - mmengine - INFO - Epoch(train) [777][45/63] lr: 1.3843e-03 eta: 5:20:08 time: 0.5460 data_time: 0.0084 memory: 16131 loss: 1.1791 loss_prob: 0.6195 loss_thr: 0.4518 loss_db: 0.1078 2022/10/26 05:22:08 - mmengine - INFO - Epoch(train) [777][50/63] lr: 1.3843e-03 eta: 5:20:00 time: 0.5495 data_time: 0.0227 memory: 16131 loss: 1.1432 loss_prob: 0.6100 loss_thr: 0.4254 loss_db: 0.1077 2022/10/26 05:22:10 - mmengine - INFO - Epoch(train) [777][55/63] lr: 1.3843e-03 eta: 5:20:00 time: 0.5207 data_time: 0.0210 memory: 16131 loss: 1.1194 loss_prob: 0.6000 loss_thr: 0.4163 loss_db: 0.1030 2022/10/26 05:22:13 - mmengine - INFO - Epoch(train) [777][60/63] lr: 1.3843e-03 eta: 5:19:52 time: 0.5400 data_time: 0.0046 memory: 16131 loss: 1.0539 loss_prob: 0.5640 loss_thr: 0.3951 loss_db: 0.0948 2022/10/26 05:22:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:22:19 - mmengine - INFO - Epoch(train) [778][5/63] lr: 1.3814e-03 eta: 5:19:52 time: 0.7229 data_time: 0.1781 memory: 16131 loss: 1.0041 loss_prob: 0.5212 loss_thr: 0.3928 loss_db: 0.0902 2022/10/26 05:22:22 - mmengine - INFO - Epoch(train) [778][10/63] lr: 1.3814e-03 eta: 5:19:42 time: 0.7316 data_time: 0.1831 memory: 16131 loss: 1.1146 loss_prob: 0.5841 loss_thr: 0.4300 loss_db: 0.1005 2022/10/26 05:22:25 - mmengine - INFO - Epoch(train) [778][15/63] lr: 1.3814e-03 eta: 5:19:42 time: 0.5531 data_time: 0.0107 memory: 16131 loss: 1.2544 loss_prob: 0.6923 loss_thr: 0.4471 loss_db: 0.1150 2022/10/26 05:22:27 - mmengine - INFO - Epoch(train) [778][20/63] lr: 1.3814e-03 eta: 5:19:33 time: 0.5395 data_time: 0.0089 memory: 16131 loss: 1.2352 loss_prob: 0.6797 loss_thr: 0.4419 loss_db: 0.1136 2022/10/26 05:22:30 - mmengine - INFO - Epoch(train) [778][25/63] lr: 1.3814e-03 eta: 5:19:33 time: 0.4929 data_time: 0.0204 memory: 16131 loss: 1.1508 loss_prob: 0.6147 loss_thr: 0.4302 loss_db: 0.1059 2022/10/26 05:22:32 - mmengine - INFO - Epoch(train) [778][30/63] lr: 1.3814e-03 eta: 5:19:25 time: 0.4937 data_time: 0.0248 memory: 16131 loss: 1.1675 loss_prob: 0.6254 loss_thr: 0.4368 loss_db: 0.1053 2022/10/26 05:22:35 - mmengine - INFO - Epoch(train) [778][35/63] lr: 1.3814e-03 eta: 5:19:25 time: 0.5158 data_time: 0.0168 memory: 16131 loss: 1.1323 loss_prob: 0.6037 loss_thr: 0.4246 loss_db: 0.1041 2022/10/26 05:22:37 - mmengine - INFO - Epoch(train) [778][40/63] lr: 1.3814e-03 eta: 5:19:17 time: 0.5212 data_time: 0.0107 memory: 16131 loss: 1.1065 loss_prob: 0.5830 loss_thr: 0.4205 loss_db: 0.1031 2022/10/26 05:22:40 - mmengine - INFO - Epoch(train) [778][45/63] lr: 1.3814e-03 eta: 5:19:17 time: 0.4989 data_time: 0.0086 memory: 16131 loss: 1.1696 loss_prob: 0.6189 loss_thr: 0.4437 loss_db: 0.1070 2022/10/26 05:22:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:22:42 - mmengine - INFO - Epoch(train) [778][50/63] lr: 1.3814e-03 eta: 5:19:08 time: 0.4953 data_time: 0.0144 memory: 16131 loss: 1.1957 loss_prob: 0.6419 loss_thr: 0.4456 loss_db: 0.1082 2022/10/26 05:22:45 - mmengine - INFO - Epoch(train) [778][55/63] lr: 1.3814e-03 eta: 5:19:08 time: 0.5131 data_time: 0.0224 memory: 16131 loss: 1.2004 loss_prob: 0.6515 loss_thr: 0.4402 loss_db: 0.1087 2022/10/26 05:22:48 - mmengine - INFO - Epoch(train) [778][60/63] lr: 1.3814e-03 eta: 5:19:00 time: 0.5780 data_time: 0.0208 memory: 16131 loss: 1.2023 loss_prob: 0.6525 loss_thr: 0.4389 loss_db: 0.1109 2022/10/26 05:22:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:22:54 - mmengine - INFO - Epoch(train) [779][5/63] lr: 1.3784e-03 eta: 5:19:00 time: 0.6885 data_time: 0.1868 memory: 16131 loss: 1.0882 loss_prob: 0.5760 loss_thr: 0.4125 loss_db: 0.0997 2022/10/26 05:22:56 - mmengine - INFO - Epoch(train) [779][10/63] lr: 1.3784e-03 eta: 5:18:50 time: 0.7083 data_time: 0.1866 memory: 16131 loss: 1.1274 loss_prob: 0.6061 loss_thr: 0.4195 loss_db: 0.1018 2022/10/26 05:22:59 - mmengine - INFO - Epoch(train) [779][15/63] lr: 1.3784e-03 eta: 5:18:50 time: 0.4959 data_time: 0.0058 memory: 16131 loss: 1.1457 loss_prob: 0.6216 loss_thr: 0.4174 loss_db: 0.1066 2022/10/26 05:23:01 - mmengine - INFO - Epoch(train) [779][20/63] lr: 1.3784e-03 eta: 5:18:41 time: 0.5080 data_time: 0.0101 memory: 16131 loss: 1.0587 loss_prob: 0.5614 loss_thr: 0.3994 loss_db: 0.0979 2022/10/26 05:23:04 - mmengine - INFO - Epoch(train) [779][25/63] lr: 1.3784e-03 eta: 5:18:41 time: 0.5280 data_time: 0.0239 memory: 16131 loss: 1.1938 loss_prob: 0.6598 loss_thr: 0.4235 loss_db: 0.1105 2022/10/26 05:23:07 - mmengine - INFO - Epoch(train) [779][30/63] lr: 1.3784e-03 eta: 5:18:33 time: 0.5327 data_time: 0.0287 memory: 16131 loss: 1.2947 loss_prob: 0.7164 loss_thr: 0.4608 loss_db: 0.1175 2022/10/26 05:23:09 - mmengine - INFO - Epoch(train) [779][35/63] lr: 1.3784e-03 eta: 5:18:33 time: 0.5178 data_time: 0.0146 memory: 16131 loss: 1.1275 loss_prob: 0.5939 loss_thr: 0.4365 loss_db: 0.0971 2022/10/26 05:23:12 - mmengine - INFO - Epoch(train) [779][40/63] lr: 1.3784e-03 eta: 5:18:25 time: 0.5156 data_time: 0.0068 memory: 16131 loss: 1.0756 loss_prob: 0.5768 loss_thr: 0.3981 loss_db: 0.1007 2022/10/26 05:23:15 - mmengine - INFO - Epoch(train) [779][45/63] lr: 1.3784e-03 eta: 5:18:25 time: 0.5363 data_time: 0.0122 memory: 16131 loss: 1.1515 loss_prob: 0.6218 loss_thr: 0.4197 loss_db: 0.1100 2022/10/26 05:23:18 - mmengine - INFO - Epoch(train) [779][50/63] lr: 1.3784e-03 eta: 5:18:17 time: 0.5771 data_time: 0.0248 memory: 16131 loss: 1.1349 loss_prob: 0.6055 loss_thr: 0.4252 loss_db: 0.1041 2022/10/26 05:23:20 - mmengine - INFO - Epoch(train) [779][55/63] lr: 1.3784e-03 eta: 5:18:17 time: 0.5717 data_time: 0.0225 memory: 16131 loss: 1.0690 loss_prob: 0.5651 loss_thr: 0.4032 loss_db: 0.1008 2022/10/26 05:23:23 - mmengine - INFO - Epoch(train) [779][60/63] lr: 1.3784e-03 eta: 5:18:09 time: 0.5708 data_time: 0.0077 memory: 16131 loss: 1.2361 loss_prob: 0.6762 loss_thr: 0.4404 loss_db: 0.1195 2022/10/26 05:23:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:23:31 - mmengine - INFO - Epoch(train) [780][5/63] lr: 1.3755e-03 eta: 5:18:09 time: 0.8423 data_time: 0.1814 memory: 16131 loss: 1.0965 loss_prob: 0.5819 loss_thr: 0.4139 loss_db: 0.1007 2022/10/26 05:23:33 - mmengine - INFO - Epoch(train) [780][10/63] lr: 1.3755e-03 eta: 5:17:59 time: 0.8183 data_time: 0.1846 memory: 16131 loss: 1.0600 loss_prob: 0.5612 loss_thr: 0.4023 loss_db: 0.0965 2022/10/26 05:23:36 - mmengine - INFO - Epoch(train) [780][15/63] lr: 1.3755e-03 eta: 5:17:59 time: 0.5012 data_time: 0.0088 memory: 16131 loss: 1.2868 loss_prob: 0.7373 loss_thr: 0.4277 loss_db: 0.1218 2022/10/26 05:23:39 - mmengine - INFO - Epoch(train) [780][20/63] lr: 1.3755e-03 eta: 5:17:51 time: 0.5272 data_time: 0.0051 memory: 16131 loss: 1.3041 loss_prob: 0.7428 loss_thr: 0.4368 loss_db: 0.1245 2022/10/26 05:23:41 - mmengine - INFO - Epoch(train) [780][25/63] lr: 1.3755e-03 eta: 5:17:51 time: 0.5619 data_time: 0.0332 memory: 16131 loss: 1.4627 loss_prob: 0.8635 loss_thr: 0.4466 loss_db: 0.1526 2022/10/26 05:23:44 - mmengine - INFO - Epoch(train) [780][30/63] lr: 1.3755e-03 eta: 5:17:42 time: 0.5183 data_time: 0.0333 memory: 16131 loss: 1.6643 loss_prob: 0.9958 loss_thr: 0.4990 loss_db: 0.1695 2022/10/26 05:23:46 - mmengine - INFO - Epoch(train) [780][35/63] lr: 1.3755e-03 eta: 5:17:42 time: 0.5078 data_time: 0.0101 memory: 16131 loss: 1.4536 loss_prob: 0.8072 loss_thr: 0.5126 loss_db: 0.1337 2022/10/26 05:23:49 - mmengine - INFO - Epoch(train) [780][40/63] lr: 1.3755e-03 eta: 5:17:34 time: 0.5486 data_time: 0.0098 memory: 16131 loss: 1.3965 loss_prob: 0.7769 loss_thr: 0.4902 loss_db: 0.1294 2022/10/26 05:23:52 - mmengine - INFO - Epoch(train) [780][45/63] lr: 1.3755e-03 eta: 5:17:34 time: 0.5474 data_time: 0.0058 memory: 16131 loss: 1.3482 loss_prob: 0.7587 loss_thr: 0.4679 loss_db: 0.1216 2022/10/26 05:23:54 - mmengine - INFO - Epoch(train) [780][50/63] lr: 1.3755e-03 eta: 5:17:26 time: 0.5196 data_time: 0.0198 memory: 16131 loss: 1.2709 loss_prob: 0.6883 loss_thr: 0.4694 loss_db: 0.1133 2022/10/26 05:23:57 - mmengine - INFO - Epoch(train) [780][55/63] lr: 1.3755e-03 eta: 5:17:26 time: 0.5029 data_time: 0.0186 memory: 16131 loss: 1.1867 loss_prob: 0.6386 loss_thr: 0.4399 loss_db: 0.1082 2022/10/26 05:24:00 - mmengine - INFO - Epoch(train) [780][60/63] lr: 1.3755e-03 eta: 5:17:18 time: 0.5206 data_time: 0.0091 memory: 16131 loss: 1.1855 loss_prob: 0.6437 loss_thr: 0.4336 loss_db: 0.1081 2022/10/26 05:24:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:24:01 - mmengine - INFO - Saving checkpoint at 780 epochs 2022/10/26 05:24:09 - mmengine - INFO - Epoch(val) [780][5/32] eta: 5:17:18 time: 0.5292 data_time: 0.0775 memory: 16131 2022/10/26 05:24:11 - mmengine - INFO - Epoch(val) [780][10/32] eta: 0:00:12 time: 0.5770 data_time: 0.0879 memory: 15724 2022/10/26 05:24:14 - mmengine - INFO - Epoch(val) [780][15/32] eta: 0:00:12 time: 0.5554 data_time: 0.0607 memory: 15724 2022/10/26 05:24:17 - mmengine - INFO - Epoch(val) [780][20/32] eta: 0:00:07 time: 0.5931 data_time: 0.0854 memory: 15724 2022/10/26 05:24:20 - mmengine - INFO - Epoch(val) [780][25/32] eta: 0:00:07 time: 0.5804 data_time: 0.0575 memory: 15724 2022/10/26 05:24:22 - mmengine - INFO - Epoch(val) [780][30/32] eta: 0:00:01 time: 0.5409 data_time: 0.0302 memory: 15724 2022/10/26 05:24:23 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8406, precision: 0.6992, hmean: 0.7634 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8406, precision: 0.7709, hmean: 0.8042 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8397, precision: 0.8082, hmean: 0.8236 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8334, precision: 0.8391, hmean: 0.8362 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8161, precision: 0.8733, hmean: 0.8437 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6793, precision: 0.9307, hmean: 0.7854 2022/10/26 05:24:23 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0481, precision: 1.0000, hmean: 0.0919 2022/10/26 05:24:23 - mmengine - INFO - Epoch(val) [780][32/32] icdar/precision: 0.8733 icdar/recall: 0.8161 icdar/hmean: 0.8437 2022/10/26 05:24:28 - mmengine - INFO - Epoch(train) [781][5/63] lr: 1.3725e-03 eta: 0:00:01 time: 0.7095 data_time: 0.1672 memory: 16131 loss: 1.1257 loss_prob: 0.5967 loss_thr: 0.4260 loss_db: 0.1030 2022/10/26 05:24:30 - mmengine - INFO - Epoch(train) [781][10/63] lr: 1.3725e-03 eta: 5:17:07 time: 0.7119 data_time: 0.1662 memory: 16131 loss: 1.1240 loss_prob: 0.6105 loss_thr: 0.4068 loss_db: 0.1067 2022/10/26 05:24:33 - mmengine - INFO - Epoch(train) [781][15/63] lr: 1.3725e-03 eta: 5:17:07 time: 0.5232 data_time: 0.0066 memory: 16131 loss: 1.2377 loss_prob: 0.6974 loss_thr: 0.4218 loss_db: 0.1186 2022/10/26 05:24:36 - mmengine - INFO - Epoch(train) [781][20/63] lr: 1.3725e-03 eta: 5:16:59 time: 0.5585 data_time: 0.0077 memory: 16131 loss: 1.2968 loss_prob: 0.7342 loss_thr: 0.4398 loss_db: 0.1228 2022/10/26 05:24:39 - mmengine - INFO - Epoch(train) [781][25/63] lr: 1.3725e-03 eta: 5:16:59 time: 0.5859 data_time: 0.0219 memory: 16131 loss: 1.3317 loss_prob: 0.7464 loss_thr: 0.4600 loss_db: 0.1253 2022/10/26 05:24:42 - mmengine - INFO - Epoch(train) [781][30/63] lr: 1.3725e-03 eta: 5:16:51 time: 0.5833 data_time: 0.0411 memory: 16131 loss: 1.2616 loss_prob: 0.6772 loss_thr: 0.4687 loss_db: 0.1158 2022/10/26 05:24:44 - mmengine - INFO - Epoch(train) [781][35/63] lr: 1.3725e-03 eta: 5:16:51 time: 0.5353 data_time: 0.0254 memory: 16131 loss: 1.2524 loss_prob: 0.6644 loss_thr: 0.4726 loss_db: 0.1154 2022/10/26 05:24:47 - mmengine - INFO - Epoch(train) [781][40/63] lr: 1.3725e-03 eta: 5:16:43 time: 0.5155 data_time: 0.0062 memory: 16131 loss: 1.2738 loss_prob: 0.6921 loss_thr: 0.4637 loss_db: 0.1180 2022/10/26 05:24:50 - mmengine - INFO - Epoch(train) [781][45/63] lr: 1.3725e-03 eta: 5:16:43 time: 0.5417 data_time: 0.0065 memory: 16131 loss: 1.1954 loss_prob: 0.6542 loss_thr: 0.4309 loss_db: 0.1103 2022/10/26 05:24:52 - mmengine - INFO - Epoch(train) [781][50/63] lr: 1.3725e-03 eta: 5:16:35 time: 0.5591 data_time: 0.0150 memory: 16131 loss: 1.2148 loss_prob: 0.6549 loss_thr: 0.4494 loss_db: 0.1105 2022/10/26 05:24:55 - mmengine - INFO - Epoch(train) [781][55/63] lr: 1.3725e-03 eta: 5:16:35 time: 0.5541 data_time: 0.0217 memory: 16131 loss: 1.2096 loss_prob: 0.6591 loss_thr: 0.4392 loss_db: 0.1114 2022/10/26 05:24:58 - mmengine - INFO - Epoch(train) [781][60/63] lr: 1.3725e-03 eta: 5:16:27 time: 0.5593 data_time: 0.0117 memory: 16131 loss: 1.1747 loss_prob: 0.6457 loss_thr: 0.4188 loss_db: 0.1103 2022/10/26 05:25:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:25:05 - mmengine - INFO - Epoch(train) [782][5/63] lr: 1.3696e-03 eta: 5:16:27 time: 0.7661 data_time: 0.1302 memory: 16131 loss: 1.1931 loss_prob: 0.6443 loss_thr: 0.4385 loss_db: 0.1104 2022/10/26 05:25:08 - mmengine - INFO - Epoch(train) [782][10/63] lr: 1.3696e-03 eta: 5:16:17 time: 0.7945 data_time: 0.1449 memory: 16131 loss: 1.1709 loss_prob: 0.6242 loss_thr: 0.4388 loss_db: 0.1079 2022/10/26 05:25:10 - mmengine - INFO - Epoch(train) [782][15/63] lr: 1.3696e-03 eta: 5:16:17 time: 0.5853 data_time: 0.0242 memory: 16131 loss: 1.2655 loss_prob: 0.6805 loss_thr: 0.4696 loss_db: 0.1154 2022/10/26 05:25:13 - mmengine - INFO - Epoch(train) [782][20/63] lr: 1.3696e-03 eta: 5:16:08 time: 0.5305 data_time: 0.0097 memory: 16131 loss: 1.1782 loss_prob: 0.6307 loss_thr: 0.4394 loss_db: 0.1081 2022/10/26 05:25:16 - mmengine - INFO - Epoch(train) [782][25/63] lr: 1.3696e-03 eta: 5:16:08 time: 0.5298 data_time: 0.0130 memory: 16131 loss: 1.0983 loss_prob: 0.5855 loss_thr: 0.4116 loss_db: 0.1012 2022/10/26 05:25:19 - mmengine - INFO - Epoch(train) [782][30/63] lr: 1.3696e-03 eta: 5:16:01 time: 0.6376 data_time: 0.0288 memory: 16131 loss: 1.1500 loss_prob: 0.6240 loss_thr: 0.4175 loss_db: 0.1085 2022/10/26 05:25:22 - mmengine - INFO - Epoch(train) [782][35/63] lr: 1.3696e-03 eta: 5:16:01 time: 0.6489 data_time: 0.0270 memory: 16131 loss: 1.0995 loss_prob: 0.5927 loss_thr: 0.4041 loss_db: 0.1027 2022/10/26 05:25:25 - mmengine - INFO - Epoch(train) [782][40/63] lr: 1.3696e-03 eta: 5:15:53 time: 0.5369 data_time: 0.0112 memory: 16131 loss: 1.0871 loss_prob: 0.5743 loss_thr: 0.4161 loss_db: 0.0967 2022/10/26 05:25:27 - mmengine - INFO - Epoch(train) [782][45/63] lr: 1.3696e-03 eta: 5:15:53 time: 0.4925 data_time: 0.0074 memory: 16131 loss: 1.2002 loss_prob: 0.6487 loss_thr: 0.4438 loss_db: 0.1076 2022/10/26 05:25:30 - mmengine - INFO - Epoch(train) [782][50/63] lr: 1.3696e-03 eta: 5:15:44 time: 0.5124 data_time: 0.0101 memory: 16131 loss: 1.2284 loss_prob: 0.6682 loss_thr: 0.4493 loss_db: 0.1109 2022/10/26 05:25:33 - mmengine - INFO - Epoch(train) [782][55/63] lr: 1.3696e-03 eta: 5:15:44 time: 0.5498 data_time: 0.0179 memory: 16131 loss: 1.1568 loss_prob: 0.6174 loss_thr: 0.4343 loss_db: 0.1052 2022/10/26 05:25:35 - mmengine - INFO - Epoch(train) [782][60/63] lr: 1.3696e-03 eta: 5:15:36 time: 0.5278 data_time: 0.0188 memory: 16131 loss: 1.1990 loss_prob: 0.6636 loss_thr: 0.4283 loss_db: 0.1071 2022/10/26 05:25:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:25:41 - mmengine - INFO - Epoch(train) [783][5/63] lr: 1.3666e-03 eta: 5:15:36 time: 0.6794 data_time: 0.1758 memory: 16131 loss: 1.1773 loss_prob: 0.6536 loss_thr: 0.4198 loss_db: 0.1039 2022/10/26 05:25:44 - mmengine - INFO - Epoch(train) [783][10/63] lr: 1.3666e-03 eta: 5:15:26 time: 0.7533 data_time: 0.1718 memory: 16131 loss: 1.0422 loss_prob: 0.5436 loss_thr: 0.4058 loss_db: 0.0927 2022/10/26 05:25:46 - mmengine - INFO - Epoch(train) [783][15/63] lr: 1.3666e-03 eta: 5:15:26 time: 0.5380 data_time: 0.0047 memory: 16131 loss: 1.0145 loss_prob: 0.5222 loss_thr: 0.4018 loss_db: 0.0906 2022/10/26 05:25:49 - mmengine - INFO - Epoch(train) [783][20/63] lr: 1.3666e-03 eta: 5:15:17 time: 0.5041 data_time: 0.0102 memory: 16131 loss: 1.1260 loss_prob: 0.5888 loss_thr: 0.4350 loss_db: 0.1022 2022/10/26 05:25:52 - mmengine - INFO - Epoch(train) [783][25/63] lr: 1.3666e-03 eta: 5:15:17 time: 0.5629 data_time: 0.0280 memory: 16131 loss: 1.1768 loss_prob: 0.6280 loss_thr: 0.4407 loss_db: 0.1081 2022/10/26 05:25:55 - mmengine - INFO - Epoch(train) [783][30/63] lr: 1.3666e-03 eta: 5:15:10 time: 0.6181 data_time: 0.0468 memory: 16131 loss: 1.1289 loss_prob: 0.6031 loss_thr: 0.4204 loss_db: 0.1054 2022/10/26 05:25:58 - mmengine - INFO - Epoch(train) [783][35/63] lr: 1.3666e-03 eta: 5:15:10 time: 0.5926 data_time: 0.0296 memory: 16131 loss: 1.1549 loss_prob: 0.6209 loss_thr: 0.4249 loss_db: 0.1091 2022/10/26 05:26:00 - mmengine - INFO - Epoch(train) [783][40/63] lr: 1.3666e-03 eta: 5:15:01 time: 0.5169 data_time: 0.0059 memory: 16131 loss: 1.1850 loss_prob: 0.6448 loss_thr: 0.4283 loss_db: 0.1119 2022/10/26 05:26:03 - mmengine - INFO - Epoch(train) [783][45/63] lr: 1.3666e-03 eta: 5:15:01 time: 0.4960 data_time: 0.0094 memory: 16131 loss: 1.1798 loss_prob: 0.6357 loss_thr: 0.4330 loss_db: 0.1111 2022/10/26 05:26:06 - mmengine - INFO - Epoch(train) [783][50/63] lr: 1.3666e-03 eta: 5:14:53 time: 0.5410 data_time: 0.0233 memory: 16131 loss: 1.0798 loss_prob: 0.5774 loss_thr: 0.4027 loss_db: 0.0997 2022/10/26 05:26:08 - mmengine - INFO - Epoch(train) [783][55/63] lr: 1.3666e-03 eta: 5:14:53 time: 0.5587 data_time: 0.0216 memory: 16131 loss: 0.9906 loss_prob: 0.5243 loss_thr: 0.3767 loss_db: 0.0896 2022/10/26 05:26:11 - mmengine - INFO - Epoch(train) [783][60/63] lr: 1.3666e-03 eta: 5:14:45 time: 0.5174 data_time: 0.0071 memory: 16131 loss: 1.0340 loss_prob: 0.5529 loss_thr: 0.3870 loss_db: 0.0941 2022/10/26 05:26:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:26:17 - mmengine - INFO - Epoch(train) [784][5/63] lr: 1.3637e-03 eta: 5:14:45 time: 0.7195 data_time: 0.2037 memory: 16131 loss: 1.2327 loss_prob: 0.6836 loss_thr: 0.4352 loss_db: 0.1140 2022/10/26 05:26:20 - mmengine - INFO - Epoch(train) [784][10/63] lr: 1.3637e-03 eta: 5:14:35 time: 0.7602 data_time: 0.2030 memory: 16131 loss: 1.1354 loss_prob: 0.6251 loss_thr: 0.4051 loss_db: 0.1051 2022/10/26 05:26:22 - mmengine - INFO - Epoch(train) [784][15/63] lr: 1.3637e-03 eta: 5:14:35 time: 0.5362 data_time: 0.0045 memory: 16131 loss: 1.0651 loss_prob: 0.5632 loss_thr: 0.4040 loss_db: 0.0979 2022/10/26 05:26:25 - mmengine - INFO - Epoch(train) [784][20/63] lr: 1.3637e-03 eta: 5:14:27 time: 0.5110 data_time: 0.0052 memory: 16131 loss: 1.2080 loss_prob: 0.6489 loss_thr: 0.4487 loss_db: 0.1104 2022/10/26 05:26:28 - mmengine - INFO - Epoch(train) [784][25/63] lr: 1.3637e-03 eta: 5:14:27 time: 0.5416 data_time: 0.0346 memory: 16131 loss: 1.1865 loss_prob: 0.6402 loss_thr: 0.4368 loss_db: 0.1094 2022/10/26 05:26:30 - mmengine - INFO - Epoch(train) [784][30/63] lr: 1.3637e-03 eta: 5:14:18 time: 0.5560 data_time: 0.0355 memory: 16131 loss: 1.0259 loss_prob: 0.5367 loss_thr: 0.3946 loss_db: 0.0946 2022/10/26 05:26:33 - mmengine - INFO - Epoch(train) [784][35/63] lr: 1.3637e-03 eta: 5:14:18 time: 0.5254 data_time: 0.0065 memory: 16131 loss: 1.1168 loss_prob: 0.6008 loss_thr: 0.4131 loss_db: 0.1029 2022/10/26 05:26:36 - mmengine - INFO - Epoch(train) [784][40/63] lr: 1.3637e-03 eta: 5:14:10 time: 0.5390 data_time: 0.0098 memory: 16131 loss: 1.2382 loss_prob: 0.6834 loss_thr: 0.4413 loss_db: 0.1135 2022/10/26 05:26:38 - mmengine - INFO - Epoch(train) [784][45/63] lr: 1.3637e-03 eta: 5:14:10 time: 0.5213 data_time: 0.0101 memory: 16131 loss: 1.1613 loss_prob: 0.6262 loss_thr: 0.4296 loss_db: 0.1055 2022/10/26 05:26:41 - mmengine - INFO - Epoch(train) [784][50/63] lr: 1.3637e-03 eta: 5:14:02 time: 0.5135 data_time: 0.0241 memory: 16131 loss: 1.0649 loss_prob: 0.5521 loss_thr: 0.4174 loss_db: 0.0953 2022/10/26 05:26:44 - mmengine - INFO - Epoch(train) [784][55/63] lr: 1.3637e-03 eta: 5:14:02 time: 0.5185 data_time: 0.0250 memory: 16131 loss: 1.1037 loss_prob: 0.5752 loss_thr: 0.4286 loss_db: 0.0999 2022/10/26 05:26:46 - mmengine - INFO - Epoch(train) [784][60/63] lr: 1.3637e-03 eta: 5:13:54 time: 0.5075 data_time: 0.0061 memory: 16131 loss: 1.1054 loss_prob: 0.5856 loss_thr: 0.4177 loss_db: 0.1021 2022/10/26 05:26:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:26:52 - mmengine - INFO - Epoch(train) [785][5/63] lr: 1.3607e-03 eta: 5:13:54 time: 0.6631 data_time: 0.1476 memory: 16131 loss: 1.0522 loss_prob: 0.5548 loss_thr: 0.4004 loss_db: 0.0969 2022/10/26 05:26:54 - mmengine - INFO - Epoch(train) [785][10/63] lr: 1.3607e-03 eta: 5:13:43 time: 0.7149 data_time: 0.1609 memory: 16131 loss: 1.0789 loss_prob: 0.5758 loss_thr: 0.4039 loss_db: 0.0992 2022/10/26 05:26:57 - mmengine - INFO - Epoch(train) [785][15/63] lr: 1.3607e-03 eta: 5:13:43 time: 0.5095 data_time: 0.0180 memory: 16131 loss: 1.1118 loss_prob: 0.6034 loss_thr: 0.4061 loss_db: 0.1023 2022/10/26 05:27:00 - mmengine - INFO - Epoch(train) [785][20/63] lr: 1.3607e-03 eta: 5:13:35 time: 0.5212 data_time: 0.0069 memory: 16131 loss: 1.0808 loss_prob: 0.5833 loss_thr: 0.3989 loss_db: 0.0985 2022/10/26 05:27:02 - mmengine - INFO - Epoch(train) [785][25/63] lr: 1.3607e-03 eta: 5:13:35 time: 0.5449 data_time: 0.0283 memory: 16131 loss: 1.1381 loss_prob: 0.6056 loss_thr: 0.4307 loss_db: 0.1018 2022/10/26 05:27:05 - mmengine - INFO - Epoch(train) [785][30/63] lr: 1.3607e-03 eta: 5:13:27 time: 0.5215 data_time: 0.0272 memory: 16131 loss: 1.1376 loss_prob: 0.5982 loss_thr: 0.4371 loss_db: 0.1023 2022/10/26 05:27:07 - mmengine - INFO - Epoch(train) [785][35/63] lr: 1.3607e-03 eta: 5:13:27 time: 0.5098 data_time: 0.0105 memory: 16131 loss: 1.0385 loss_prob: 0.5406 loss_thr: 0.4020 loss_db: 0.0959 2022/10/26 05:27:10 - mmengine - INFO - Epoch(train) [785][40/63] lr: 1.3607e-03 eta: 5:13:19 time: 0.5303 data_time: 0.0101 memory: 16131 loss: 1.0759 loss_prob: 0.5664 loss_thr: 0.4107 loss_db: 0.0988 2022/10/26 05:27:13 - mmengine - INFO - Epoch(train) [785][45/63] lr: 1.3607e-03 eta: 5:13:19 time: 0.5271 data_time: 0.0110 memory: 16131 loss: 1.1105 loss_prob: 0.6015 loss_thr: 0.4060 loss_db: 0.1030 2022/10/26 05:27:15 - mmengine - INFO - Epoch(train) [785][50/63] lr: 1.3607e-03 eta: 5:13:10 time: 0.5236 data_time: 0.0268 memory: 16131 loss: 1.1432 loss_prob: 0.6175 loss_thr: 0.4225 loss_db: 0.1032 2022/10/26 05:27:18 - mmengine - INFO - Epoch(train) [785][55/63] lr: 1.3607e-03 eta: 5:13:10 time: 0.5184 data_time: 0.0241 memory: 16131 loss: 1.1314 loss_prob: 0.6056 loss_thr: 0.4230 loss_db: 0.1027 2022/10/26 05:27:21 - mmengine - INFO - Epoch(train) [785][60/63] lr: 1.3607e-03 eta: 5:13:02 time: 0.5119 data_time: 0.0077 memory: 16131 loss: 1.0788 loss_prob: 0.5795 loss_thr: 0.3979 loss_db: 0.1014 2022/10/26 05:27:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:27:26 - mmengine - INFO - Epoch(train) [786][5/63] lr: 1.3578e-03 eta: 5:13:02 time: 0.6716 data_time: 0.1637 memory: 16131 loss: 1.1634 loss_prob: 0.6233 loss_thr: 0.4342 loss_db: 0.1059 2022/10/26 05:27:29 - mmengine - INFO - Epoch(train) [786][10/63] lr: 1.3578e-03 eta: 5:12:51 time: 0.6903 data_time: 0.1706 memory: 16131 loss: 1.1817 loss_prob: 0.6422 loss_thr: 0.4329 loss_db: 0.1066 2022/10/26 05:27:31 - mmengine - INFO - Epoch(train) [786][15/63] lr: 1.3578e-03 eta: 5:12:51 time: 0.5189 data_time: 0.0126 memory: 16131 loss: 1.1819 loss_prob: 0.6490 loss_thr: 0.4239 loss_db: 0.1090 2022/10/26 05:27:34 - mmengine - INFO - Epoch(train) [786][20/63] lr: 1.3578e-03 eta: 5:12:43 time: 0.4991 data_time: 0.0064 memory: 16131 loss: 1.0846 loss_prob: 0.5817 loss_thr: 0.4005 loss_db: 0.1024 2022/10/26 05:27:37 - mmengine - INFO - Epoch(train) [786][25/63] lr: 1.3578e-03 eta: 5:12:43 time: 0.5505 data_time: 0.0309 memory: 16131 loss: 1.0825 loss_prob: 0.5767 loss_thr: 0.4059 loss_db: 0.1000 2022/10/26 05:27:39 - mmengine - INFO - Epoch(train) [786][30/63] lr: 1.3578e-03 eta: 5:12:35 time: 0.5719 data_time: 0.0361 memory: 16131 loss: 1.0702 loss_prob: 0.5627 loss_thr: 0.4109 loss_db: 0.0965 2022/10/26 05:27:42 - mmengine - INFO - Epoch(train) [786][35/63] lr: 1.3578e-03 eta: 5:12:35 time: 0.5198 data_time: 0.0125 memory: 16131 loss: 1.1483 loss_prob: 0.6149 loss_thr: 0.4285 loss_db: 0.1049 2022/10/26 05:27:45 - mmengine - INFO - Epoch(train) [786][40/63] lr: 1.3578e-03 eta: 5:12:27 time: 0.5216 data_time: 0.0080 memory: 16131 loss: 1.2012 loss_prob: 0.6536 loss_thr: 0.4353 loss_db: 0.1123 2022/10/26 05:27:48 - mmengine - INFO - Epoch(train) [786][45/63] lr: 1.3578e-03 eta: 5:12:27 time: 0.5636 data_time: 0.0060 memory: 16131 loss: 1.1518 loss_prob: 0.6160 loss_thr: 0.4289 loss_db: 0.1070 2022/10/26 05:27:51 - mmengine - INFO - Epoch(train) [786][50/63] lr: 1.3578e-03 eta: 5:12:19 time: 0.5819 data_time: 0.0182 memory: 16131 loss: 1.1932 loss_prob: 0.6389 loss_thr: 0.4468 loss_db: 0.1075 2022/10/26 05:27:53 - mmengine - INFO - Epoch(train) [786][55/63] lr: 1.3578e-03 eta: 5:12:19 time: 0.5696 data_time: 0.0222 memory: 16131 loss: 1.1970 loss_prob: 0.6459 loss_thr: 0.4436 loss_db: 0.1074 2022/10/26 05:27:56 - mmengine - INFO - Epoch(train) [786][60/63] lr: 1.3578e-03 eta: 5:12:11 time: 0.5340 data_time: 0.0103 memory: 16131 loss: 1.1083 loss_prob: 0.5874 loss_thr: 0.4197 loss_db: 0.1011 2022/10/26 05:27:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:28:02 - mmengine - INFO - Epoch(train) [787][5/63] lr: 1.3548e-03 eta: 5:12:11 time: 0.7182 data_time: 0.1993 memory: 16131 loss: 1.1938 loss_prob: 0.6497 loss_thr: 0.4362 loss_db: 0.1080 2022/10/26 05:28:05 - mmengine - INFO - Epoch(train) [787][10/63] lr: 1.3548e-03 eta: 5:12:01 time: 0.7482 data_time: 0.1961 memory: 16131 loss: 1.1768 loss_prob: 0.6384 loss_thr: 0.4299 loss_db: 0.1085 2022/10/26 05:28:07 - mmengine - INFO - Epoch(train) [787][15/63] lr: 1.3548e-03 eta: 5:12:01 time: 0.5044 data_time: 0.0073 memory: 16131 loss: 1.1026 loss_prob: 0.5838 loss_thr: 0.4177 loss_db: 0.1011 2022/10/26 05:28:10 - mmengine - INFO - Epoch(train) [787][20/63] lr: 1.3548e-03 eta: 5:11:52 time: 0.5344 data_time: 0.0095 memory: 16131 loss: 1.0828 loss_prob: 0.5748 loss_thr: 0.4098 loss_db: 0.0982 2022/10/26 05:28:13 - mmengine - INFO - Epoch(train) [787][25/63] lr: 1.3548e-03 eta: 5:11:52 time: 0.5646 data_time: 0.0300 memory: 16131 loss: 1.0683 loss_prob: 0.5613 loss_thr: 0.4097 loss_db: 0.0972 2022/10/26 05:28:15 - mmengine - INFO - Epoch(train) [787][30/63] lr: 1.3548e-03 eta: 5:11:44 time: 0.5467 data_time: 0.0300 memory: 16131 loss: 1.1679 loss_prob: 0.6260 loss_thr: 0.4366 loss_db: 0.1053 2022/10/26 05:28:18 - mmengine - INFO - Epoch(train) [787][35/63] lr: 1.3548e-03 eta: 5:11:44 time: 0.5109 data_time: 0.0074 memory: 16131 loss: 1.1160 loss_prob: 0.5973 loss_thr: 0.4181 loss_db: 0.1007 2022/10/26 05:28:21 - mmengine - INFO - Epoch(train) [787][40/63] lr: 1.3548e-03 eta: 5:11:36 time: 0.5184 data_time: 0.0074 memory: 16131 loss: 1.0617 loss_prob: 0.5610 loss_thr: 0.4030 loss_db: 0.0978 2022/10/26 05:28:23 - mmengine - INFO - Epoch(train) [787][45/63] lr: 1.3548e-03 eta: 5:11:36 time: 0.5320 data_time: 0.0069 memory: 16131 loss: 1.1647 loss_prob: 0.6246 loss_thr: 0.4324 loss_db: 0.1077 2022/10/26 05:28:26 - mmengine - INFO - Epoch(train) [787][50/63] lr: 1.3548e-03 eta: 5:11:28 time: 0.5712 data_time: 0.0207 memory: 16131 loss: 1.1066 loss_prob: 0.5862 loss_thr: 0.4193 loss_db: 0.1011 2022/10/26 05:28:29 - mmengine - INFO - Epoch(train) [787][55/63] lr: 1.3548e-03 eta: 5:11:28 time: 0.5534 data_time: 0.0222 memory: 16131 loss: 1.1040 loss_prob: 0.5808 loss_thr: 0.4236 loss_db: 0.0996 2022/10/26 05:28:32 - mmengine - INFO - Epoch(train) [787][60/63] lr: 1.3548e-03 eta: 5:11:20 time: 0.5206 data_time: 0.0060 memory: 16131 loss: 1.0925 loss_prob: 0.5778 loss_thr: 0.4157 loss_db: 0.0990 2022/10/26 05:28:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:28:38 - mmengine - INFO - Epoch(train) [788][5/63] lr: 1.3519e-03 eta: 5:11:20 time: 0.7251 data_time: 0.1749 memory: 16131 loss: 1.0862 loss_prob: 0.5748 loss_thr: 0.4125 loss_db: 0.0989 2022/10/26 05:28:40 - mmengine - INFO - Epoch(train) [788][10/63] lr: 1.3519e-03 eta: 5:11:10 time: 0.7187 data_time: 0.1705 memory: 16131 loss: 1.0731 loss_prob: 0.5690 loss_thr: 0.4087 loss_db: 0.0954 2022/10/26 05:28:43 - mmengine - INFO - Epoch(train) [788][15/63] lr: 1.3519e-03 eta: 5:11:10 time: 0.4986 data_time: 0.0061 memory: 16131 loss: 1.1491 loss_prob: 0.6203 loss_thr: 0.4242 loss_db: 0.1046 2022/10/26 05:28:45 - mmengine - INFO - Epoch(train) [788][20/63] lr: 1.3519e-03 eta: 5:11:01 time: 0.5094 data_time: 0.0062 memory: 16131 loss: 1.1279 loss_prob: 0.6009 loss_thr: 0.4224 loss_db: 0.1046 2022/10/26 05:28:48 - mmengine - INFO - Epoch(train) [788][25/63] lr: 1.3519e-03 eta: 5:11:01 time: 0.5129 data_time: 0.0146 memory: 16131 loss: 1.1711 loss_prob: 0.6289 loss_thr: 0.4360 loss_db: 0.1062 2022/10/26 05:28:50 - mmengine - INFO - Epoch(train) [788][30/63] lr: 1.3519e-03 eta: 5:10:53 time: 0.5147 data_time: 0.0355 memory: 16131 loss: 1.1721 loss_prob: 0.6293 loss_thr: 0.4384 loss_db: 0.1044 2022/10/26 05:28:53 - mmengine - INFO - Epoch(train) [788][35/63] lr: 1.3519e-03 eta: 5:10:53 time: 0.5089 data_time: 0.0267 memory: 16131 loss: 1.0187 loss_prob: 0.5329 loss_thr: 0.3939 loss_db: 0.0919 2022/10/26 05:28:55 - mmengine - INFO - Epoch(train) [788][40/63] lr: 1.3519e-03 eta: 5:10:45 time: 0.4927 data_time: 0.0044 memory: 16131 loss: 1.0252 loss_prob: 0.5316 loss_thr: 0.3991 loss_db: 0.0945 2022/10/26 05:28:58 - mmengine - INFO - Epoch(train) [788][45/63] lr: 1.3519e-03 eta: 5:10:45 time: 0.5090 data_time: 0.0045 memory: 16131 loss: 1.0534 loss_prob: 0.5406 loss_thr: 0.4190 loss_db: 0.0938 2022/10/26 05:29:01 - mmengine - INFO - Epoch(train) [788][50/63] lr: 1.3519e-03 eta: 5:10:37 time: 0.5528 data_time: 0.0365 memory: 16131 loss: 1.0744 loss_prob: 0.5639 loss_thr: 0.4140 loss_db: 0.0964 2022/10/26 05:29:03 - mmengine - INFO - Epoch(train) [788][55/63] lr: 1.3519e-03 eta: 5:10:37 time: 0.5433 data_time: 0.0445 memory: 16131 loss: 1.1772 loss_prob: 0.6303 loss_thr: 0.4391 loss_db: 0.1078 2022/10/26 05:29:06 - mmengine - INFO - Epoch(train) [788][60/63] lr: 1.3519e-03 eta: 5:10:29 time: 0.5456 data_time: 0.0135 memory: 16131 loss: 1.1661 loss_prob: 0.6171 loss_thr: 0.4435 loss_db: 0.1055 2022/10/26 05:29:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:29:12 - mmengine - INFO - Epoch(train) [789][5/63] lr: 1.3489e-03 eta: 5:10:29 time: 0.7177 data_time: 0.1906 memory: 16131 loss: 1.1686 loss_prob: 0.6232 loss_thr: 0.4395 loss_db: 0.1059 2022/10/26 05:29:15 - mmengine - INFO - Epoch(train) [789][10/63] lr: 1.3489e-03 eta: 5:10:18 time: 0.7168 data_time: 0.1942 memory: 16131 loss: 1.0910 loss_prob: 0.5825 loss_thr: 0.4072 loss_db: 0.1014 2022/10/26 05:29:17 - mmengine - INFO - Epoch(train) [789][15/63] lr: 1.3489e-03 eta: 5:10:18 time: 0.5124 data_time: 0.0092 memory: 16131 loss: 1.0694 loss_prob: 0.5775 loss_thr: 0.3935 loss_db: 0.0984 2022/10/26 05:29:20 - mmengine - INFO - Epoch(train) [789][20/63] lr: 1.3489e-03 eta: 5:10:10 time: 0.5213 data_time: 0.0061 memory: 16131 loss: 1.0440 loss_prob: 0.5587 loss_thr: 0.3926 loss_db: 0.0927 2022/10/26 05:29:23 - mmengine - INFO - Epoch(train) [789][25/63] lr: 1.3489e-03 eta: 5:10:10 time: 0.5562 data_time: 0.0265 memory: 16131 loss: 1.0073 loss_prob: 0.5316 loss_thr: 0.3845 loss_db: 0.0912 2022/10/26 05:29:26 - mmengine - INFO - Epoch(train) [789][30/63] lr: 1.3489e-03 eta: 5:10:02 time: 0.5907 data_time: 0.0347 memory: 16131 loss: 1.0350 loss_prob: 0.5458 loss_thr: 0.3913 loss_db: 0.0979 2022/10/26 05:29:28 - mmengine - INFO - Epoch(train) [789][35/63] lr: 1.3489e-03 eta: 5:10:02 time: 0.5470 data_time: 0.0176 memory: 16131 loss: 1.1844 loss_prob: 0.6462 loss_thr: 0.4287 loss_db: 0.1095 2022/10/26 05:29:31 - mmengine - INFO - Epoch(train) [789][40/63] lr: 1.3489e-03 eta: 5:09:54 time: 0.5203 data_time: 0.0094 memory: 16131 loss: 1.2121 loss_prob: 0.6637 loss_thr: 0.4378 loss_db: 0.1106 2022/10/26 05:29:34 - mmengine - INFO - Epoch(train) [789][45/63] lr: 1.3489e-03 eta: 5:09:54 time: 0.5647 data_time: 0.0054 memory: 16131 loss: 1.0756 loss_prob: 0.5649 loss_thr: 0.4127 loss_db: 0.0980 2022/10/26 05:29:37 - mmengine - INFO - Epoch(train) [789][50/63] lr: 1.3489e-03 eta: 5:09:46 time: 0.5544 data_time: 0.0151 memory: 16131 loss: 1.0784 loss_prob: 0.5578 loss_thr: 0.4239 loss_db: 0.0967 2022/10/26 05:29:39 - mmengine - INFO - Epoch(train) [789][55/63] lr: 1.3489e-03 eta: 5:09:46 time: 0.5220 data_time: 0.0275 memory: 16131 loss: 1.1334 loss_prob: 0.6108 loss_thr: 0.4210 loss_db: 0.1016 2022/10/26 05:29:42 - mmengine - INFO - Epoch(train) [789][60/63] lr: 1.3489e-03 eta: 5:09:38 time: 0.5186 data_time: 0.0176 memory: 16131 loss: 1.2240 loss_prob: 0.6709 loss_thr: 0.4378 loss_db: 0.1154 2022/10/26 05:29:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:29:48 - mmengine - INFO - Epoch(train) [790][5/63] lr: 1.3460e-03 eta: 5:09:38 time: 0.7360 data_time: 0.2130 memory: 16131 loss: 1.1613 loss_prob: 0.6262 loss_thr: 0.4270 loss_db: 0.1081 2022/10/26 05:29:51 - mmengine - INFO - Epoch(train) [790][10/63] lr: 1.3460e-03 eta: 5:09:27 time: 0.7446 data_time: 0.2176 memory: 16131 loss: 1.2376 loss_prob: 0.6942 loss_thr: 0.4289 loss_db: 0.1145 2022/10/26 05:29:53 - mmengine - INFO - Epoch(train) [790][15/63] lr: 1.3460e-03 eta: 5:09:27 time: 0.5234 data_time: 0.0102 memory: 16131 loss: 1.2067 loss_prob: 0.6638 loss_thr: 0.4309 loss_db: 0.1120 2022/10/26 05:29:56 - mmengine - INFO - Epoch(train) [790][20/63] lr: 1.3460e-03 eta: 5:09:19 time: 0.5139 data_time: 0.0069 memory: 16131 loss: 1.0392 loss_prob: 0.5372 loss_thr: 0.4069 loss_db: 0.0951 2022/10/26 05:29:59 - mmengine - INFO - Epoch(train) [790][25/63] lr: 1.3460e-03 eta: 5:09:19 time: 0.5499 data_time: 0.0361 memory: 16131 loss: 1.0724 loss_prob: 0.5698 loss_thr: 0.4047 loss_db: 0.0979 2022/10/26 05:30:02 - mmengine - INFO - Epoch(train) [790][30/63] lr: 1.3460e-03 eta: 5:09:11 time: 0.5718 data_time: 0.0360 memory: 16131 loss: 1.1118 loss_prob: 0.5999 loss_thr: 0.4102 loss_db: 0.1017 2022/10/26 05:30:04 - mmengine - INFO - Epoch(train) [790][35/63] lr: 1.3460e-03 eta: 5:09:11 time: 0.5514 data_time: 0.0064 memory: 16131 loss: 1.1323 loss_prob: 0.6116 loss_thr: 0.4157 loss_db: 0.1050 2022/10/26 05:30:07 - mmengine - INFO - Epoch(train) [790][40/63] lr: 1.3460e-03 eta: 5:09:03 time: 0.5527 data_time: 0.0045 memory: 16131 loss: 1.1892 loss_prob: 0.6407 loss_thr: 0.4373 loss_db: 0.1112 2022/10/26 05:30:10 - mmengine - INFO - Epoch(train) [790][45/63] lr: 1.3460e-03 eta: 5:09:03 time: 0.5148 data_time: 0.0049 memory: 16131 loss: 1.1121 loss_prob: 0.5939 loss_thr: 0.4170 loss_db: 0.1013 2022/10/26 05:30:12 - mmengine - INFO - Epoch(train) [790][50/63] lr: 1.3460e-03 eta: 5:08:55 time: 0.5083 data_time: 0.0203 memory: 16131 loss: 1.1305 loss_prob: 0.6106 loss_thr: 0.4174 loss_db: 0.1025 2022/10/26 05:30:15 - mmengine - INFO - Epoch(train) [790][55/63] lr: 1.3460e-03 eta: 5:08:55 time: 0.5091 data_time: 0.0203 memory: 16131 loss: 1.1235 loss_prob: 0.6036 loss_thr: 0.4159 loss_db: 0.1041 2022/10/26 05:30:18 - mmengine - INFO - Epoch(train) [790][60/63] lr: 1.3460e-03 eta: 5:08:47 time: 0.5675 data_time: 0.0054 memory: 16131 loss: 1.1030 loss_prob: 0.5866 loss_thr: 0.4144 loss_db: 0.1020 2022/10/26 05:30:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:30:24 - mmengine - INFO - Epoch(train) [791][5/63] lr: 1.3430e-03 eta: 5:08:47 time: 0.6858 data_time: 0.1989 memory: 16131 loss: 1.1382 loss_prob: 0.6093 loss_thr: 0.4239 loss_db: 0.1050 2022/10/26 05:30:26 - mmengine - INFO - Epoch(train) [791][10/63] lr: 1.3430e-03 eta: 5:08:36 time: 0.7155 data_time: 0.1995 memory: 16131 loss: 1.1860 loss_prob: 0.6355 loss_thr: 0.4393 loss_db: 0.1112 2022/10/26 05:30:29 - mmengine - INFO - Epoch(train) [791][15/63] lr: 1.3430e-03 eta: 5:08:36 time: 0.5315 data_time: 0.0091 memory: 16131 loss: 1.1513 loss_prob: 0.6194 loss_thr: 0.4258 loss_db: 0.1060 2022/10/26 05:30:32 - mmengine - INFO - Epoch(train) [791][20/63] lr: 1.3430e-03 eta: 5:08:28 time: 0.5209 data_time: 0.0063 memory: 16131 loss: 1.0380 loss_prob: 0.5523 loss_thr: 0.3928 loss_db: 0.0929 2022/10/26 05:30:34 - mmengine - INFO - Epoch(train) [791][25/63] lr: 1.3430e-03 eta: 5:08:28 time: 0.5065 data_time: 0.0113 memory: 16131 loss: 1.1303 loss_prob: 0.6208 loss_thr: 0.4060 loss_db: 0.1035 2022/10/26 05:30:37 - mmengine - INFO - Epoch(train) [791][30/63] lr: 1.3430e-03 eta: 5:08:20 time: 0.5213 data_time: 0.0346 memory: 16131 loss: 1.2186 loss_prob: 0.6869 loss_thr: 0.4193 loss_db: 0.1124 2022/10/26 05:30:39 - mmengine - INFO - Epoch(train) [791][35/63] lr: 1.3430e-03 eta: 5:08:20 time: 0.5476 data_time: 0.0289 memory: 16131 loss: 1.1390 loss_prob: 0.6192 loss_thr: 0.4169 loss_db: 0.1029 2022/10/26 05:30:42 - mmengine - INFO - Epoch(train) [791][40/63] lr: 1.3430e-03 eta: 5:08:12 time: 0.5098 data_time: 0.0054 memory: 16131 loss: 1.0617 loss_prob: 0.5548 loss_thr: 0.4093 loss_db: 0.0976 2022/10/26 05:30:44 - mmengine - INFO - Epoch(train) [791][45/63] lr: 1.3430e-03 eta: 5:08:12 time: 0.4751 data_time: 0.0056 memory: 16131 loss: 1.0633 loss_prob: 0.5556 loss_thr: 0.4103 loss_db: 0.0974 2022/10/26 05:30:47 - mmengine - INFO - Epoch(train) [791][50/63] lr: 1.3430e-03 eta: 5:08:04 time: 0.5355 data_time: 0.0228 memory: 16131 loss: 1.0596 loss_prob: 0.5572 loss_thr: 0.4079 loss_db: 0.0946 2022/10/26 05:30:50 - mmengine - INFO - Epoch(train) [791][55/63] lr: 1.3430e-03 eta: 5:08:04 time: 0.5632 data_time: 0.0239 memory: 16131 loss: 1.0314 loss_prob: 0.5410 loss_thr: 0.3975 loss_db: 0.0929 2022/10/26 05:30:52 - mmengine - INFO - Epoch(train) [791][60/63] lr: 1.3430e-03 eta: 5:07:56 time: 0.5145 data_time: 0.0063 memory: 16131 loss: 1.0899 loss_prob: 0.5721 loss_thr: 0.4199 loss_db: 0.0979 2022/10/26 05:30:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:30:59 - mmengine - INFO - Epoch(train) [792][5/63] lr: 1.3401e-03 eta: 5:07:56 time: 0.7331 data_time: 0.1993 memory: 16131 loss: 1.1555 loss_prob: 0.6189 loss_thr: 0.4317 loss_db: 0.1049 2022/10/26 05:31:01 - mmengine - INFO - Epoch(train) [792][10/63] lr: 1.3401e-03 eta: 5:07:45 time: 0.7200 data_time: 0.1960 memory: 16131 loss: 1.0969 loss_prob: 0.5753 loss_thr: 0.4212 loss_db: 0.1004 2022/10/26 05:31:04 - mmengine - INFO - Epoch(train) [792][15/63] lr: 1.3401e-03 eta: 5:07:45 time: 0.5170 data_time: 0.0147 memory: 16131 loss: 1.1205 loss_prob: 0.5980 loss_thr: 0.4188 loss_db: 0.1038 2022/10/26 05:31:07 - mmengine - INFO - Epoch(train) [792][20/63] lr: 1.3401e-03 eta: 5:07:37 time: 0.5447 data_time: 0.0147 memory: 16131 loss: 1.1796 loss_prob: 0.6453 loss_thr: 0.4261 loss_db: 0.1083 2022/10/26 05:31:09 - mmengine - INFO - Epoch(train) [792][25/63] lr: 1.3401e-03 eta: 5:07:37 time: 0.5506 data_time: 0.0229 memory: 16131 loss: 1.1205 loss_prob: 0.6134 loss_thr: 0.4043 loss_db: 0.1027 2022/10/26 05:31:12 - mmengine - INFO - Epoch(train) [792][30/63] lr: 1.3401e-03 eta: 5:07:29 time: 0.5224 data_time: 0.0299 memory: 16131 loss: 1.0515 loss_prob: 0.5685 loss_thr: 0.3842 loss_db: 0.0988 2022/10/26 05:31:15 - mmengine - INFO - Epoch(train) [792][35/63] lr: 1.3401e-03 eta: 5:07:29 time: 0.5267 data_time: 0.0194 memory: 16131 loss: 1.1410 loss_prob: 0.6199 loss_thr: 0.4156 loss_db: 0.1054 2022/10/26 05:31:17 - mmengine - INFO - Epoch(train) [792][40/63] lr: 1.3401e-03 eta: 5:07:21 time: 0.5314 data_time: 0.0125 memory: 16131 loss: 1.1615 loss_prob: 0.6248 loss_thr: 0.4301 loss_db: 0.1067 2022/10/26 05:31:20 - mmengine - INFO - Epoch(train) [792][45/63] lr: 1.3401e-03 eta: 5:07:21 time: 0.5306 data_time: 0.0058 memory: 16131 loss: 1.1279 loss_prob: 0.6055 loss_thr: 0.4174 loss_db: 0.1049 2022/10/26 05:31:23 - mmengine - INFO - Epoch(train) [792][50/63] lr: 1.3401e-03 eta: 5:07:13 time: 0.5406 data_time: 0.0220 memory: 16131 loss: 1.1850 loss_prob: 0.6474 loss_thr: 0.4258 loss_db: 0.1117 2022/10/26 05:31:25 - mmengine - INFO - Epoch(train) [792][55/63] lr: 1.3401e-03 eta: 5:07:13 time: 0.5132 data_time: 0.0217 memory: 16131 loss: 1.1204 loss_prob: 0.6015 loss_thr: 0.4156 loss_db: 0.1033 2022/10/26 05:31:28 - mmengine - INFO - Epoch(train) [792][60/63] lr: 1.3401e-03 eta: 5:07:05 time: 0.5273 data_time: 0.0081 memory: 16131 loss: 1.0141 loss_prob: 0.5326 loss_thr: 0.3893 loss_db: 0.0922 2022/10/26 05:31:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:31:34 - mmengine - INFO - Epoch(train) [793][5/63] lr: 1.3371e-03 eta: 5:07:05 time: 0.7160 data_time: 0.2353 memory: 16131 loss: 1.1588 loss_prob: 0.6286 loss_thr: 0.4250 loss_db: 0.1052 2022/10/26 05:31:37 - mmengine - INFO - Epoch(train) [793][10/63] lr: 1.3371e-03 eta: 5:06:54 time: 0.7355 data_time: 0.2337 memory: 16131 loss: 1.0271 loss_prob: 0.5344 loss_thr: 0.4022 loss_db: 0.0905 2022/10/26 05:31:39 - mmengine - INFO - Epoch(train) [793][15/63] lr: 1.3371e-03 eta: 5:06:54 time: 0.5184 data_time: 0.0059 memory: 16131 loss: 1.0653 loss_prob: 0.5653 loss_thr: 0.4025 loss_db: 0.0975 2022/10/26 05:31:42 - mmengine - INFO - Epoch(train) [793][20/63] lr: 1.3371e-03 eta: 5:06:46 time: 0.5325 data_time: 0.0063 memory: 16131 loss: 1.1153 loss_prob: 0.5987 loss_thr: 0.4132 loss_db: 0.1034 2022/10/26 05:31:44 - mmengine - INFO - Epoch(train) [793][25/63] lr: 1.3371e-03 eta: 5:06:46 time: 0.5301 data_time: 0.0097 memory: 16131 loss: 1.1641 loss_prob: 0.6189 loss_thr: 0.4390 loss_db: 0.1062 2022/10/26 05:31:47 - mmengine - INFO - Epoch(train) [793][30/63] lr: 1.3371e-03 eta: 5:06:38 time: 0.5265 data_time: 0.0367 memory: 16131 loss: 1.1299 loss_prob: 0.6009 loss_thr: 0.4229 loss_db: 0.1062 2022/10/26 05:31:50 - mmengine - INFO - Epoch(train) [793][35/63] lr: 1.3371e-03 eta: 5:06:38 time: 0.5093 data_time: 0.0385 memory: 16131 loss: 1.1958 loss_prob: 0.6497 loss_thr: 0.4341 loss_db: 0.1120 2022/10/26 05:31:52 - mmengine - INFO - Epoch(train) [793][40/63] lr: 1.3371e-03 eta: 5:06:30 time: 0.4795 data_time: 0.0123 memory: 16131 loss: 1.2045 loss_prob: 0.6537 loss_thr: 0.4405 loss_db: 0.1102 2022/10/26 05:31:55 - mmengine - INFO - Epoch(train) [793][45/63] lr: 1.3371e-03 eta: 5:06:30 time: 0.4914 data_time: 0.0082 memory: 16131 loss: 1.1135 loss_prob: 0.5918 loss_thr: 0.4191 loss_db: 0.1026 2022/10/26 05:31:57 - mmengine - INFO - Epoch(train) [793][50/63] lr: 1.3371e-03 eta: 5:06:21 time: 0.5103 data_time: 0.0211 memory: 16131 loss: 1.0600 loss_prob: 0.5546 loss_thr: 0.4093 loss_db: 0.0960 2022/10/26 05:32:00 - mmengine - INFO - Epoch(train) [793][55/63] lr: 1.3371e-03 eta: 5:06:21 time: 0.5033 data_time: 0.0237 memory: 16131 loss: 1.0748 loss_prob: 0.5719 loss_thr: 0.4033 loss_db: 0.0996 2022/10/26 05:32:02 - mmengine - INFO - Epoch(train) [793][60/63] lr: 1.3371e-03 eta: 5:06:13 time: 0.5159 data_time: 0.0090 memory: 16131 loss: 1.0934 loss_prob: 0.5947 loss_thr: 0.3975 loss_db: 0.1012 2022/10/26 05:32:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:32:09 - mmengine - INFO - Epoch(train) [794][5/63] lr: 1.3341e-03 eta: 5:06:13 time: 0.7585 data_time: 0.2201 memory: 16131 loss: 1.1766 loss_prob: 0.6333 loss_thr: 0.4377 loss_db: 0.1056 2022/10/26 05:32:12 - mmengine - INFO - Epoch(train) [794][10/63] lr: 1.3341e-03 eta: 5:06:03 time: 0.7816 data_time: 0.2282 memory: 16131 loss: 1.1177 loss_prob: 0.5985 loss_thr: 0.4157 loss_db: 0.1034 2022/10/26 05:32:14 - mmengine - INFO - Epoch(train) [794][15/63] lr: 1.3341e-03 eta: 5:06:03 time: 0.5185 data_time: 0.0141 memory: 16131 loss: 1.1247 loss_prob: 0.6098 loss_thr: 0.4085 loss_db: 0.1064 2022/10/26 05:32:17 - mmengine - INFO - Epoch(train) [794][20/63] lr: 1.3341e-03 eta: 5:05:55 time: 0.5149 data_time: 0.0075 memory: 16131 loss: 1.2037 loss_prob: 0.6517 loss_thr: 0.4410 loss_db: 0.1110 2022/10/26 05:32:19 - mmengine - INFO - Epoch(train) [794][25/63] lr: 1.3341e-03 eta: 5:05:55 time: 0.5298 data_time: 0.0141 memory: 16131 loss: 1.1492 loss_prob: 0.6196 loss_thr: 0.4233 loss_db: 0.1063 2022/10/26 05:32:22 - mmengine - INFO - Epoch(train) [794][30/63] lr: 1.3341e-03 eta: 5:05:47 time: 0.5289 data_time: 0.0316 memory: 16131 loss: 1.0647 loss_prob: 0.5652 loss_thr: 0.4017 loss_db: 0.0977 2022/10/26 05:32:25 - mmengine - INFO - Epoch(train) [794][35/63] lr: 1.3341e-03 eta: 5:05:47 time: 0.5324 data_time: 0.0264 memory: 16131 loss: 1.0653 loss_prob: 0.5521 loss_thr: 0.4181 loss_db: 0.0951 2022/10/26 05:32:27 - mmengine - INFO - Epoch(train) [794][40/63] lr: 1.3341e-03 eta: 5:05:39 time: 0.5325 data_time: 0.0072 memory: 16131 loss: 1.0286 loss_prob: 0.5400 loss_thr: 0.3943 loss_db: 0.0943 2022/10/26 05:32:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:32:30 - mmengine - INFO - Epoch(train) [794][45/63] lr: 1.3341e-03 eta: 5:05:39 time: 0.5260 data_time: 0.0074 memory: 16131 loss: 1.0248 loss_prob: 0.5413 loss_thr: 0.3883 loss_db: 0.0952 2022/10/26 05:32:32 - mmengine - INFO - Epoch(train) [794][50/63] lr: 1.3341e-03 eta: 5:05:30 time: 0.4991 data_time: 0.0159 memory: 16131 loss: 1.0444 loss_prob: 0.5453 loss_thr: 0.4045 loss_db: 0.0947 2022/10/26 05:32:35 - mmengine - INFO - Epoch(train) [794][55/63] lr: 1.3341e-03 eta: 5:05:30 time: 0.5169 data_time: 0.0208 memory: 16131 loss: 1.1145 loss_prob: 0.5877 loss_thr: 0.4258 loss_db: 0.1010 2022/10/26 05:32:38 - mmengine - INFO - Epoch(train) [794][60/63] lr: 1.3341e-03 eta: 5:05:22 time: 0.5481 data_time: 0.0138 memory: 16131 loss: 1.2179 loss_prob: 0.6555 loss_thr: 0.4521 loss_db: 0.1103 2022/10/26 05:32:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:32:44 - mmengine - INFO - Epoch(train) [795][5/63] lr: 1.3312e-03 eta: 5:05:22 time: 0.7220 data_time: 0.1821 memory: 16131 loss: 1.1443 loss_prob: 0.6024 loss_thr: 0.4383 loss_db: 0.1035 2022/10/26 05:32:47 - mmengine - INFO - Epoch(train) [795][10/63] lr: 1.3312e-03 eta: 5:05:12 time: 0.7363 data_time: 0.1805 memory: 16131 loss: 1.0808 loss_prob: 0.5587 loss_thr: 0.4251 loss_db: 0.0970 2022/10/26 05:32:49 - mmengine - INFO - Epoch(train) [795][15/63] lr: 1.3312e-03 eta: 5:05:12 time: 0.5273 data_time: 0.0062 memory: 16131 loss: 0.9931 loss_prob: 0.5198 loss_thr: 0.3826 loss_db: 0.0907 2022/10/26 05:32:52 - mmengine - INFO - Epoch(train) [795][20/63] lr: 1.3312e-03 eta: 5:05:04 time: 0.5276 data_time: 0.0077 memory: 16131 loss: 1.0283 loss_prob: 0.5488 loss_thr: 0.3851 loss_db: 0.0945 2022/10/26 05:32:55 - mmengine - INFO - Epoch(train) [795][25/63] lr: 1.3312e-03 eta: 5:05:04 time: 0.5209 data_time: 0.0208 memory: 16131 loss: 1.0659 loss_prob: 0.5581 loss_thr: 0.4127 loss_db: 0.0952 2022/10/26 05:32:57 - mmengine - INFO - Epoch(train) [795][30/63] lr: 1.3312e-03 eta: 5:04:56 time: 0.5269 data_time: 0.0356 memory: 16131 loss: 1.0655 loss_prob: 0.5637 loss_thr: 0.4053 loss_db: 0.0965 2022/10/26 05:33:00 - mmengine - INFO - Epoch(train) [795][35/63] lr: 1.3312e-03 eta: 5:04:56 time: 0.5362 data_time: 0.0262 memory: 16131 loss: 1.0616 loss_prob: 0.5616 loss_thr: 0.4041 loss_db: 0.0959 2022/10/26 05:33:02 - mmengine - INFO - Epoch(train) [795][40/63] lr: 1.3312e-03 eta: 5:04:48 time: 0.5147 data_time: 0.0144 memory: 16131 loss: 1.0538 loss_prob: 0.5482 loss_thr: 0.4126 loss_db: 0.0929 2022/10/26 05:33:05 - mmengine - INFO - Epoch(train) [795][45/63] lr: 1.3312e-03 eta: 5:04:48 time: 0.4959 data_time: 0.0118 memory: 16131 loss: 1.1146 loss_prob: 0.5945 loss_thr: 0.4167 loss_db: 0.1034 2022/10/26 05:33:08 - mmengine - INFO - Epoch(train) [795][50/63] lr: 1.3312e-03 eta: 5:04:39 time: 0.5172 data_time: 0.0164 memory: 16131 loss: 1.1419 loss_prob: 0.6196 loss_thr: 0.4154 loss_db: 0.1068 2022/10/26 05:33:10 - mmengine - INFO - Epoch(train) [795][55/63] lr: 1.3312e-03 eta: 5:04:39 time: 0.5428 data_time: 0.0241 memory: 16131 loss: 1.1603 loss_prob: 0.6367 loss_thr: 0.4177 loss_db: 0.1059 2022/10/26 05:33:13 - mmengine - INFO - Epoch(train) [795][60/63] lr: 1.3312e-03 eta: 5:04:31 time: 0.5514 data_time: 0.0183 memory: 16131 loss: 1.1818 loss_prob: 0.6527 loss_thr: 0.4199 loss_db: 0.1091 2022/10/26 05:33:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:33:19 - mmengine - INFO - Epoch(train) [796][5/63] lr: 1.3282e-03 eta: 5:04:31 time: 0.6873 data_time: 0.2026 memory: 16131 loss: 1.1121 loss_prob: 0.5822 loss_thr: 0.4302 loss_db: 0.0997 2022/10/26 05:33:22 - mmengine - INFO - Epoch(train) [796][10/63] lr: 1.3282e-03 eta: 5:04:21 time: 0.7171 data_time: 0.2020 memory: 16131 loss: 1.0792 loss_prob: 0.5714 loss_thr: 0.4094 loss_db: 0.0984 2022/10/26 05:33:24 - mmengine - INFO - Epoch(train) [796][15/63] lr: 1.3282e-03 eta: 5:04:21 time: 0.5361 data_time: 0.0102 memory: 16131 loss: 1.0511 loss_prob: 0.5610 loss_thr: 0.3938 loss_db: 0.0963 2022/10/26 05:33:27 - mmengine - INFO - Epoch(train) [796][20/63] lr: 1.3282e-03 eta: 5:04:13 time: 0.5408 data_time: 0.0116 memory: 16131 loss: 1.0517 loss_prob: 0.5610 loss_thr: 0.3938 loss_db: 0.0968 2022/10/26 05:33:30 - mmengine - INFO - Epoch(train) [796][25/63] lr: 1.3282e-03 eta: 5:04:13 time: 0.5301 data_time: 0.0248 memory: 16131 loss: 1.0812 loss_prob: 0.5751 loss_thr: 0.4076 loss_db: 0.0986 2022/10/26 05:33:32 - mmengine - INFO - Epoch(train) [796][30/63] lr: 1.3282e-03 eta: 5:04:05 time: 0.5174 data_time: 0.0305 memory: 16131 loss: 1.0553 loss_prob: 0.5592 loss_thr: 0.4018 loss_db: 0.0943 2022/10/26 05:33:35 - mmengine - INFO - Epoch(train) [796][35/63] lr: 1.3282e-03 eta: 5:04:05 time: 0.5202 data_time: 0.0128 memory: 16131 loss: 1.0689 loss_prob: 0.5713 loss_thr: 0.4009 loss_db: 0.0967 2022/10/26 05:33:38 - mmengine - INFO - Epoch(train) [796][40/63] lr: 1.3282e-03 eta: 5:03:57 time: 0.5629 data_time: 0.0093 memory: 16131 loss: 1.0943 loss_prob: 0.5916 loss_thr: 0.4013 loss_db: 0.1013 2022/10/26 05:33:40 - mmengine - INFO - Epoch(train) [796][45/63] lr: 1.3282e-03 eta: 5:03:57 time: 0.5550 data_time: 0.0114 memory: 16131 loss: 1.0989 loss_prob: 0.5952 loss_thr: 0.4034 loss_db: 0.1003 2022/10/26 05:33:43 - mmengine - INFO - Epoch(train) [796][50/63] lr: 1.3282e-03 eta: 5:03:49 time: 0.5319 data_time: 0.0248 memory: 16131 loss: 1.1228 loss_prob: 0.6026 loss_thr: 0.4190 loss_db: 0.1013 2022/10/26 05:33:46 - mmengine - INFO - Epoch(train) [796][55/63] lr: 1.3282e-03 eta: 5:03:49 time: 0.5131 data_time: 0.0228 memory: 16131 loss: 1.0701 loss_prob: 0.5647 loss_thr: 0.4075 loss_db: 0.0978 2022/10/26 05:33:48 - mmengine - INFO - Epoch(train) [796][60/63] lr: 1.3282e-03 eta: 5:03:40 time: 0.4943 data_time: 0.0061 memory: 16131 loss: 1.0633 loss_prob: 0.5591 loss_thr: 0.4061 loss_db: 0.0982 2022/10/26 05:33:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:33:55 - mmengine - INFO - Epoch(train) [797][5/63] lr: 1.3253e-03 eta: 5:03:40 time: 0.7505 data_time: 0.2146 memory: 16131 loss: 1.0463 loss_prob: 0.5506 loss_thr: 0.4002 loss_db: 0.0955 2022/10/26 05:33:57 - mmengine - INFO - Epoch(train) [797][10/63] lr: 1.3253e-03 eta: 5:03:30 time: 0.7900 data_time: 0.2142 memory: 16131 loss: 1.0744 loss_prob: 0.5672 loss_thr: 0.4099 loss_db: 0.0972 2022/10/26 05:34:00 - mmengine - INFO - Epoch(train) [797][15/63] lr: 1.3253e-03 eta: 5:03:30 time: 0.5465 data_time: 0.0061 memory: 16131 loss: 1.1304 loss_prob: 0.5992 loss_thr: 0.4271 loss_db: 0.1041 2022/10/26 05:34:03 - mmengine - INFO - Epoch(train) [797][20/63] lr: 1.3253e-03 eta: 5:03:22 time: 0.5245 data_time: 0.0060 memory: 16131 loss: 1.1338 loss_prob: 0.6016 loss_thr: 0.4279 loss_db: 0.1042 2022/10/26 05:34:05 - mmengine - INFO - Epoch(train) [797][25/63] lr: 1.3253e-03 eta: 5:03:22 time: 0.5268 data_time: 0.0276 memory: 16131 loss: 1.0048 loss_prob: 0.5287 loss_thr: 0.3861 loss_db: 0.0899 2022/10/26 05:34:08 - mmengine - INFO - Epoch(train) [797][30/63] lr: 1.3253e-03 eta: 5:03:15 time: 0.5864 data_time: 0.0454 memory: 16131 loss: 0.9923 loss_prob: 0.5198 loss_thr: 0.3829 loss_db: 0.0895 2022/10/26 05:34:11 - mmengine - INFO - Epoch(train) [797][35/63] lr: 1.3253e-03 eta: 5:03:15 time: 0.5665 data_time: 0.0226 memory: 16131 loss: 1.0617 loss_prob: 0.5508 loss_thr: 0.4144 loss_db: 0.0965 2022/10/26 05:34:13 - mmengine - INFO - Epoch(train) [797][40/63] lr: 1.3253e-03 eta: 5:03:06 time: 0.4929 data_time: 0.0055 memory: 16131 loss: 1.0612 loss_prob: 0.5524 loss_thr: 0.4134 loss_db: 0.0954 2022/10/26 05:34:16 - mmengine - INFO - Epoch(train) [797][45/63] lr: 1.3253e-03 eta: 5:03:06 time: 0.4932 data_time: 0.0079 memory: 16131 loss: 1.0838 loss_prob: 0.5766 loss_thr: 0.4110 loss_db: 0.0962 2022/10/26 05:34:19 - mmengine - INFO - Epoch(train) [797][50/63] lr: 1.3253e-03 eta: 5:02:58 time: 0.5359 data_time: 0.0280 memory: 16131 loss: 1.0668 loss_prob: 0.5717 loss_thr: 0.4021 loss_db: 0.0931 2022/10/26 05:34:21 - mmengine - INFO - Epoch(train) [797][55/63] lr: 1.3253e-03 eta: 5:02:58 time: 0.5408 data_time: 0.0267 memory: 16131 loss: 1.1055 loss_prob: 0.6002 loss_thr: 0.4041 loss_db: 0.1012 2022/10/26 05:34:24 - mmengine - INFO - Epoch(train) [797][60/63] lr: 1.3253e-03 eta: 5:02:50 time: 0.5141 data_time: 0.0060 memory: 16131 loss: 1.0636 loss_prob: 0.5623 loss_thr: 0.4031 loss_db: 0.0982 2022/10/26 05:34:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:34:30 - mmengine - INFO - Epoch(train) [798][5/63] lr: 1.3223e-03 eta: 5:02:50 time: 0.7506 data_time: 0.2270 memory: 16131 loss: 1.1141 loss_prob: 0.5969 loss_thr: 0.4134 loss_db: 0.1038 2022/10/26 05:34:33 - mmengine - INFO - Epoch(train) [798][10/63] lr: 1.3223e-03 eta: 5:02:40 time: 0.7239 data_time: 0.2325 memory: 16131 loss: 1.1207 loss_prob: 0.6050 loss_thr: 0.4142 loss_db: 0.1015 2022/10/26 05:34:36 - mmengine - INFO - Epoch(train) [798][15/63] lr: 1.3223e-03 eta: 5:02:40 time: 0.5153 data_time: 0.0126 memory: 16131 loss: 1.1450 loss_prob: 0.6175 loss_thr: 0.4217 loss_db: 0.1059 2022/10/26 05:34:38 - mmengine - INFO - Epoch(train) [798][20/63] lr: 1.3223e-03 eta: 5:02:32 time: 0.5344 data_time: 0.0077 memory: 16131 loss: 1.1346 loss_prob: 0.6035 loss_thr: 0.4224 loss_db: 0.1088 2022/10/26 05:34:41 - mmengine - INFO - Epoch(train) [798][25/63] lr: 1.3223e-03 eta: 5:02:32 time: 0.5843 data_time: 0.0254 memory: 16131 loss: 1.1993 loss_prob: 0.6511 loss_thr: 0.4343 loss_db: 0.1138 2022/10/26 05:34:44 - mmengine - INFO - Epoch(train) [798][30/63] lr: 1.3223e-03 eta: 5:02:24 time: 0.6005 data_time: 0.0303 memory: 16131 loss: 1.1820 loss_prob: 0.6508 loss_thr: 0.4237 loss_db: 0.1075 2022/10/26 05:34:47 - mmengine - INFO - Epoch(train) [798][35/63] lr: 1.3223e-03 eta: 5:02:24 time: 0.5436 data_time: 0.0106 memory: 16131 loss: 1.0341 loss_prob: 0.5502 loss_thr: 0.3926 loss_db: 0.0914 2022/10/26 05:34:49 - mmengine - INFO - Epoch(train) [798][40/63] lr: 1.3223e-03 eta: 5:02:16 time: 0.5019 data_time: 0.0069 memory: 16131 loss: 1.0717 loss_prob: 0.5695 loss_thr: 0.4057 loss_db: 0.0965 2022/10/26 05:34:52 - mmengine - INFO - Epoch(train) [798][45/63] lr: 1.3223e-03 eta: 5:02:16 time: 0.5048 data_time: 0.0087 memory: 16131 loss: 1.1200 loss_prob: 0.6007 loss_thr: 0.4153 loss_db: 0.1039 2022/10/26 05:34:54 - mmengine - INFO - Epoch(train) [798][50/63] lr: 1.3223e-03 eta: 5:02:07 time: 0.5192 data_time: 0.0197 memory: 16131 loss: 1.0959 loss_prob: 0.5805 loss_thr: 0.4148 loss_db: 0.1007 2022/10/26 05:34:57 - mmengine - INFO - Epoch(train) [798][55/63] lr: 1.3223e-03 eta: 5:02:07 time: 0.5188 data_time: 0.0217 memory: 16131 loss: 1.0933 loss_prob: 0.5707 loss_thr: 0.4256 loss_db: 0.0971 2022/10/26 05:35:00 - mmengine - INFO - Epoch(train) [798][60/63] lr: 1.3223e-03 eta: 5:01:59 time: 0.5381 data_time: 0.0093 memory: 16131 loss: 1.0673 loss_prob: 0.5628 loss_thr: 0.4060 loss_db: 0.0985 2022/10/26 05:35:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:35:06 - mmengine - INFO - Epoch(train) [799][5/63] lr: 1.3194e-03 eta: 5:01:59 time: 0.7460 data_time: 0.2080 memory: 16131 loss: 1.0264 loss_prob: 0.5462 loss_thr: 0.3871 loss_db: 0.0931 2022/10/26 05:35:09 - mmengine - INFO - Epoch(train) [799][10/63] lr: 1.3194e-03 eta: 5:01:49 time: 0.7358 data_time: 0.2065 memory: 16131 loss: 1.1266 loss_prob: 0.6180 loss_thr: 0.4074 loss_db: 0.1011 2022/10/26 05:35:11 - mmengine - INFO - Epoch(train) [799][15/63] lr: 1.3194e-03 eta: 5:01:49 time: 0.5150 data_time: 0.0082 memory: 16131 loss: 1.0693 loss_prob: 0.5844 loss_thr: 0.3875 loss_db: 0.0975 2022/10/26 05:35:14 - mmengine - INFO - Epoch(train) [799][20/63] lr: 1.3194e-03 eta: 5:01:41 time: 0.5052 data_time: 0.0061 memory: 16131 loss: 1.0340 loss_prob: 0.5448 loss_thr: 0.3955 loss_db: 0.0937 2022/10/26 05:35:16 - mmengine - INFO - Epoch(train) [799][25/63] lr: 1.3194e-03 eta: 5:01:41 time: 0.4959 data_time: 0.0213 memory: 16131 loss: 1.1139 loss_prob: 0.5912 loss_thr: 0.4220 loss_db: 0.1007 2022/10/26 05:35:19 - mmengine - INFO - Epoch(train) [799][30/63] lr: 1.3194e-03 eta: 5:01:33 time: 0.5115 data_time: 0.0313 memory: 16131 loss: 1.0958 loss_prob: 0.5847 loss_thr: 0.4112 loss_db: 0.0999 2022/10/26 05:35:21 - mmengine - INFO - Epoch(train) [799][35/63] lr: 1.3194e-03 eta: 5:01:33 time: 0.5025 data_time: 0.0166 memory: 16131 loss: 1.0989 loss_prob: 0.5896 loss_thr: 0.4077 loss_db: 0.1016 2022/10/26 05:35:24 - mmengine - INFO - Epoch(train) [799][40/63] lr: 1.3194e-03 eta: 5:01:24 time: 0.4910 data_time: 0.0071 memory: 16131 loss: 1.1881 loss_prob: 0.6385 loss_thr: 0.4392 loss_db: 0.1104 2022/10/26 05:35:26 - mmengine - INFO - Epoch(train) [799][45/63] lr: 1.3194e-03 eta: 5:01:24 time: 0.4977 data_time: 0.0055 memory: 16131 loss: 1.1062 loss_prob: 0.5836 loss_thr: 0.4212 loss_db: 0.1013 2022/10/26 05:35:29 - mmengine - INFO - Epoch(train) [799][50/63] lr: 1.3194e-03 eta: 5:01:16 time: 0.5016 data_time: 0.0190 memory: 16131 loss: 0.9978 loss_prob: 0.5229 loss_thr: 0.3831 loss_db: 0.0918 2022/10/26 05:35:32 - mmengine - INFO - Epoch(train) [799][55/63] lr: 1.3194e-03 eta: 5:01:16 time: 0.5298 data_time: 0.0216 memory: 16131 loss: 1.0249 loss_prob: 0.5446 loss_thr: 0.3851 loss_db: 0.0952 2022/10/26 05:35:34 - mmengine - INFO - Epoch(train) [799][60/63] lr: 1.3194e-03 eta: 5:01:08 time: 0.5355 data_time: 0.0171 memory: 16131 loss: 1.0364 loss_prob: 0.5453 loss_thr: 0.3967 loss_db: 0.0944 2022/10/26 05:35:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:35:40 - mmengine - INFO - Epoch(train) [800][5/63] lr: 1.3164e-03 eta: 5:01:08 time: 0.7340 data_time: 0.1825 memory: 16131 loss: 1.1517 loss_prob: 0.6223 loss_thr: 0.4247 loss_db: 0.1047 2022/10/26 05:35:43 - mmengine - INFO - Epoch(train) [800][10/63] lr: 1.3164e-03 eta: 5:00:58 time: 0.7986 data_time: 0.1886 memory: 16131 loss: 1.2000 loss_prob: 0.6487 loss_thr: 0.4401 loss_db: 0.1112 2022/10/26 05:35:46 - mmengine - INFO - Epoch(train) [800][15/63] lr: 1.3164e-03 eta: 5:00:58 time: 0.5363 data_time: 0.0136 memory: 16131 loss: 1.1235 loss_prob: 0.5940 loss_thr: 0.4258 loss_db: 0.1038 2022/10/26 05:35:49 - mmengine - INFO - Epoch(train) [800][20/63] lr: 1.3164e-03 eta: 5:00:50 time: 0.5385 data_time: 0.0084 memory: 16131 loss: 1.1208 loss_prob: 0.5901 loss_thr: 0.4303 loss_db: 0.1004 2022/10/26 05:35:51 - mmengine - INFO - Epoch(train) [800][25/63] lr: 1.3164e-03 eta: 5:00:50 time: 0.5493 data_time: 0.0244 memory: 16131 loss: 1.0196 loss_prob: 0.5361 loss_thr: 0.3905 loss_db: 0.0930 2022/10/26 05:35:54 - mmengine - INFO - Epoch(train) [800][30/63] lr: 1.3164e-03 eta: 5:00:42 time: 0.5115 data_time: 0.0231 memory: 16131 loss: 1.0330 loss_prob: 0.5428 loss_thr: 0.3951 loss_db: 0.0951 2022/10/26 05:35:56 - mmengine - INFO - Epoch(train) [800][35/63] lr: 1.3164e-03 eta: 5:00:42 time: 0.5069 data_time: 0.0155 memory: 16131 loss: 1.1402 loss_prob: 0.6060 loss_thr: 0.4301 loss_db: 0.1041 2022/10/26 05:35:59 - mmengine - INFO - Epoch(train) [800][40/63] lr: 1.3164e-03 eta: 5:00:34 time: 0.5275 data_time: 0.0137 memory: 16131 loss: 1.0950 loss_prob: 0.5813 loss_thr: 0.4125 loss_db: 0.1013 2022/10/26 05:36:02 - mmengine - INFO - Epoch(train) [800][45/63] lr: 1.3164e-03 eta: 5:00:34 time: 0.5265 data_time: 0.0053 memory: 16131 loss: 0.9963 loss_prob: 0.5275 loss_thr: 0.3764 loss_db: 0.0924 2022/10/26 05:36:04 - mmengine - INFO - Epoch(train) [800][50/63] lr: 1.3164e-03 eta: 5:00:26 time: 0.5132 data_time: 0.0162 memory: 16131 loss: 1.0539 loss_prob: 0.5614 loss_thr: 0.3973 loss_db: 0.0952 2022/10/26 05:36:07 - mmengine - INFO - Epoch(train) [800][55/63] lr: 1.3164e-03 eta: 5:00:26 time: 0.5172 data_time: 0.0217 memory: 16131 loss: 1.1807 loss_prob: 0.6274 loss_thr: 0.4471 loss_db: 0.1063 2022/10/26 05:36:10 - mmengine - INFO - Epoch(train) [800][60/63] lr: 1.3164e-03 eta: 5:00:18 time: 0.5715 data_time: 0.0176 memory: 16131 loss: 1.0953 loss_prob: 0.5810 loss_thr: 0.4150 loss_db: 0.0993 2022/10/26 05:36:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:36:11 - mmengine - INFO - Saving checkpoint at 800 epochs 2022/10/26 05:36:18 - mmengine - INFO - Epoch(val) [800][5/32] eta: 5:00:18 time: 0.5222 data_time: 0.0706 memory: 16131 2022/10/26 05:36:20 - mmengine - INFO - Epoch(val) [800][10/32] eta: 0:00:12 time: 0.5702 data_time: 0.0802 memory: 15724 2022/10/26 05:36:23 - mmengine - INFO - Epoch(val) [800][15/32] eta: 0:00:12 time: 0.5344 data_time: 0.0434 memory: 15724 2022/10/26 05:36:26 - mmengine - INFO - Epoch(val) [800][20/32] eta: 0:00:06 time: 0.5568 data_time: 0.0717 memory: 15724 2022/10/26 05:36:29 - mmengine - INFO - Epoch(val) [800][25/32] eta: 0:00:06 time: 0.5491 data_time: 0.0551 memory: 15724 2022/10/26 05:36:31 - mmengine - INFO - Epoch(val) [800][30/32] eta: 0:00:01 time: 0.5071 data_time: 0.0203 memory: 15724 2022/10/26 05:36:32 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8349, precision: 0.7738, hmean: 0.8031 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8349, precision: 0.8195, hmean: 0.8271 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8334, precision: 0.8481, hmean: 0.8407 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8296, precision: 0.8728, hmean: 0.8507 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8122, precision: 0.8954, hmean: 0.8518 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6943, precision: 0.9339, hmean: 0.7965 2022/10/26 05:36:32 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0674, precision: 1.0000, hmean: 0.1263 2022/10/26 05:36:32 - mmengine - INFO - Epoch(val) [800][32/32] icdar/precision: 0.8954 icdar/recall: 0.8122 icdar/hmean: 0.8518 2022/10/26 05:36:36 - mmengine - INFO - Epoch(train) [801][5/63] lr: 1.3134e-03 eta: 0:00:01 time: 0.7231 data_time: 0.2094 memory: 16131 loss: 1.1267 loss_prob: 0.6081 loss_thr: 0.4151 loss_db: 0.1034 2022/10/26 05:36:39 - mmengine - INFO - Epoch(train) [801][10/63] lr: 1.3134e-03 eta: 5:00:08 time: 0.7329 data_time: 0.2089 memory: 16131 loss: 1.0885 loss_prob: 0.5740 loss_thr: 0.4150 loss_db: 0.0995 2022/10/26 05:36:42 - mmengine - INFO - Epoch(train) [801][15/63] lr: 1.3134e-03 eta: 5:00:08 time: 0.5107 data_time: 0.0067 memory: 16131 loss: 1.0967 loss_prob: 0.5857 loss_thr: 0.4105 loss_db: 0.1005 2022/10/26 05:36:44 - mmengine - INFO - Epoch(train) [801][20/63] lr: 1.3134e-03 eta: 4:59:59 time: 0.5107 data_time: 0.0081 memory: 16131 loss: 1.1294 loss_prob: 0.6151 loss_thr: 0.4119 loss_db: 0.1025 2022/10/26 05:36:47 - mmengine - INFO - Epoch(train) [801][25/63] lr: 1.3134e-03 eta: 4:59:59 time: 0.5570 data_time: 0.0281 memory: 16131 loss: 1.0160 loss_prob: 0.5401 loss_thr: 0.3814 loss_db: 0.0944 2022/10/26 05:36:50 - mmengine - INFO - Epoch(train) [801][30/63] lr: 1.3134e-03 eta: 4:59:52 time: 0.5756 data_time: 0.0336 memory: 16131 loss: 1.2370 loss_prob: 0.6952 loss_thr: 0.4291 loss_db: 0.1127 2022/10/26 05:36:52 - mmengine - INFO - Epoch(train) [801][35/63] lr: 1.3134e-03 eta: 4:59:52 time: 0.5371 data_time: 0.0128 memory: 16131 loss: 1.3598 loss_prob: 0.7732 loss_thr: 0.4634 loss_db: 0.1232 2022/10/26 05:36:55 - mmengine - INFO - Epoch(train) [801][40/63] lr: 1.3134e-03 eta: 4:59:43 time: 0.5032 data_time: 0.0057 memory: 16131 loss: 1.1176 loss_prob: 0.5983 loss_thr: 0.4152 loss_db: 0.1042 2022/10/26 05:36:57 - mmengine - INFO - Epoch(train) [801][45/63] lr: 1.3134e-03 eta: 4:59:43 time: 0.4986 data_time: 0.0062 memory: 16131 loss: 1.0619 loss_prob: 0.5563 loss_thr: 0.4089 loss_db: 0.0967 2022/10/26 05:37:00 - mmengine - INFO - Epoch(train) [801][50/63] lr: 1.3134e-03 eta: 4:59:35 time: 0.5313 data_time: 0.0224 memory: 16131 loss: 1.0832 loss_prob: 0.5679 loss_thr: 0.4173 loss_db: 0.0980 2022/10/26 05:37:03 - mmengine - INFO - Epoch(train) [801][55/63] lr: 1.3134e-03 eta: 4:59:35 time: 0.5216 data_time: 0.0250 memory: 16131 loss: 1.1177 loss_prob: 0.6038 loss_thr: 0.4091 loss_db: 0.1048 2022/10/26 05:37:05 - mmengine - INFO - Epoch(train) [801][60/63] lr: 1.3134e-03 eta: 4:59:27 time: 0.4887 data_time: 0.0084 memory: 16131 loss: 1.2285 loss_prob: 0.6890 loss_thr: 0.4227 loss_db: 0.1169 2022/10/26 05:37:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:37:11 - mmengine - INFO - Epoch(train) [802][5/63] lr: 1.3105e-03 eta: 4:59:27 time: 0.6973 data_time: 0.2010 memory: 16131 loss: 1.2669 loss_prob: 0.7036 loss_thr: 0.4491 loss_db: 0.1142 2022/10/26 05:37:14 - mmengine - INFO - Epoch(train) [802][10/63] lr: 1.3105e-03 eta: 4:59:17 time: 0.7209 data_time: 0.2056 memory: 16131 loss: 1.1417 loss_prob: 0.6128 loss_thr: 0.4254 loss_db: 0.1034 2022/10/26 05:37:16 - mmengine - INFO - Epoch(train) [802][15/63] lr: 1.3105e-03 eta: 4:59:17 time: 0.5268 data_time: 0.0096 memory: 16131 loss: 1.1083 loss_prob: 0.5883 loss_thr: 0.4168 loss_db: 0.1032 2022/10/26 05:37:19 - mmengine - INFO - Epoch(train) [802][20/63] lr: 1.3105e-03 eta: 4:59:09 time: 0.5253 data_time: 0.0050 memory: 16131 loss: 1.1053 loss_prob: 0.5894 loss_thr: 0.4128 loss_db: 0.1031 2022/10/26 05:37:22 - mmengine - INFO - Epoch(train) [802][25/63] lr: 1.3105e-03 eta: 4:59:09 time: 0.5442 data_time: 0.0201 memory: 16131 loss: 1.1350 loss_prob: 0.6077 loss_thr: 0.4214 loss_db: 0.1059 2022/10/26 05:37:25 - mmengine - INFO - Epoch(train) [802][30/63] lr: 1.3105e-03 eta: 4:59:01 time: 0.6106 data_time: 0.0398 memory: 16131 loss: 1.0829 loss_prob: 0.5767 loss_thr: 0.4090 loss_db: 0.0973 2022/10/26 05:37:28 - mmengine - INFO - Epoch(train) [802][35/63] lr: 1.3105e-03 eta: 4:59:01 time: 0.5679 data_time: 0.0291 memory: 16131 loss: 1.0499 loss_prob: 0.5550 loss_thr: 0.4023 loss_db: 0.0926 2022/10/26 05:37:30 - mmengine - INFO - Epoch(train) [802][40/63] lr: 1.3105e-03 eta: 4:58:53 time: 0.4972 data_time: 0.0093 memory: 16131 loss: 1.0751 loss_prob: 0.5704 loss_thr: 0.4063 loss_db: 0.0985 2022/10/26 05:37:33 - mmengine - INFO - Epoch(train) [802][45/63] lr: 1.3105e-03 eta: 4:58:53 time: 0.4947 data_time: 0.0060 memory: 16131 loss: 1.0997 loss_prob: 0.5914 loss_thr: 0.4053 loss_db: 0.1030 2022/10/26 05:37:35 - mmengine - INFO - Epoch(train) [802][50/63] lr: 1.3105e-03 eta: 4:58:45 time: 0.5359 data_time: 0.0263 memory: 16131 loss: 1.0562 loss_prob: 0.5659 loss_thr: 0.3932 loss_db: 0.0970 2022/10/26 05:37:38 - mmengine - INFO - Epoch(train) [802][55/63] lr: 1.3105e-03 eta: 4:58:45 time: 0.5382 data_time: 0.0282 memory: 16131 loss: 1.1078 loss_prob: 0.6014 loss_thr: 0.4061 loss_db: 0.1004 2022/10/26 05:37:40 - mmengine - INFO - Epoch(train) [802][60/63] lr: 1.3105e-03 eta: 4:58:37 time: 0.5063 data_time: 0.0108 memory: 16131 loss: 1.2056 loss_prob: 0.6512 loss_thr: 0.4441 loss_db: 0.1103 2022/10/26 05:37:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:37:47 - mmengine - INFO - Epoch(train) [803][5/63] lr: 1.3075e-03 eta: 4:58:37 time: 0.7114 data_time: 0.1969 memory: 16131 loss: 1.2177 loss_prob: 0.6578 loss_thr: 0.4456 loss_db: 0.1143 2022/10/26 05:37:49 - mmengine - INFO - Epoch(train) [803][10/63] lr: 1.3075e-03 eta: 4:58:26 time: 0.7418 data_time: 0.1961 memory: 16131 loss: 1.2075 loss_prob: 0.6515 loss_thr: 0.4442 loss_db: 0.1118 2022/10/26 05:37:52 - mmengine - INFO - Epoch(train) [803][15/63] lr: 1.3075e-03 eta: 4:58:26 time: 0.5866 data_time: 0.0063 memory: 16131 loss: 1.1315 loss_prob: 0.6029 loss_thr: 0.4262 loss_db: 0.1024 2022/10/26 05:37:55 - mmengine - INFO - Epoch(train) [803][20/63] lr: 1.3075e-03 eta: 4:58:19 time: 0.5815 data_time: 0.0067 memory: 16131 loss: 1.0508 loss_prob: 0.5578 loss_thr: 0.3982 loss_db: 0.0948 2022/10/26 05:37:58 - mmengine - INFO - Epoch(train) [803][25/63] lr: 1.3075e-03 eta: 4:58:19 time: 0.5504 data_time: 0.0289 memory: 16131 loss: 1.0134 loss_prob: 0.5302 loss_thr: 0.3923 loss_db: 0.0909 2022/10/26 05:38:00 - mmengine - INFO - Epoch(train) [803][30/63] lr: 1.3075e-03 eta: 4:58:11 time: 0.5404 data_time: 0.0409 memory: 16131 loss: 1.0337 loss_prob: 0.5412 loss_thr: 0.4007 loss_db: 0.0918 2022/10/26 05:38:03 - mmengine - INFO - Epoch(train) [803][35/63] lr: 1.3075e-03 eta: 4:58:11 time: 0.5211 data_time: 0.0171 memory: 16131 loss: 1.0884 loss_prob: 0.5802 loss_thr: 0.4079 loss_db: 0.1003 2022/10/26 05:38:06 - mmengine - INFO - Epoch(train) [803][40/63] lr: 1.3075e-03 eta: 4:58:02 time: 0.5133 data_time: 0.0045 memory: 16131 loss: 1.1922 loss_prob: 0.6445 loss_thr: 0.4389 loss_db: 0.1088 2022/10/26 05:38:08 - mmengine - INFO - Epoch(train) [803][45/63] lr: 1.3075e-03 eta: 4:58:02 time: 0.4832 data_time: 0.0051 memory: 16131 loss: 1.2162 loss_prob: 0.6543 loss_thr: 0.4534 loss_db: 0.1085 2022/10/26 05:38:11 - mmengine - INFO - Epoch(train) [803][50/63] lr: 1.3075e-03 eta: 4:57:54 time: 0.5073 data_time: 0.0236 memory: 16131 loss: 1.0990 loss_prob: 0.5800 loss_thr: 0.4202 loss_db: 0.0988 2022/10/26 05:38:13 - mmengine - INFO - Epoch(train) [803][55/63] lr: 1.3075e-03 eta: 4:57:54 time: 0.5127 data_time: 0.0238 memory: 16131 loss: 1.1127 loss_prob: 0.6031 loss_thr: 0.4090 loss_db: 0.1007 2022/10/26 05:38:16 - mmengine - INFO - Epoch(train) [803][60/63] lr: 1.3075e-03 eta: 4:57:46 time: 0.5113 data_time: 0.0092 memory: 16131 loss: 1.1726 loss_prob: 0.6405 loss_thr: 0.4252 loss_db: 0.1069 2022/10/26 05:38:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:38:22 - mmengine - INFO - Epoch(train) [804][5/63] lr: 1.3045e-03 eta: 4:57:46 time: 0.7306 data_time: 0.1968 memory: 16131 loss: 1.0669 loss_prob: 0.5680 loss_thr: 0.4010 loss_db: 0.0980 2022/10/26 05:38:24 - mmengine - INFO - Epoch(train) [804][10/63] lr: 1.3045e-03 eta: 4:57:36 time: 0.7264 data_time: 0.2019 memory: 16131 loss: 1.1184 loss_prob: 0.6017 loss_thr: 0.4127 loss_db: 0.1041 2022/10/26 05:38:27 - mmengine - INFO - Epoch(train) [804][15/63] lr: 1.3045e-03 eta: 4:57:36 time: 0.5249 data_time: 0.0096 memory: 16131 loss: 1.1327 loss_prob: 0.6104 loss_thr: 0.4170 loss_db: 0.1052 2022/10/26 05:38:30 - mmengine - INFO - Epoch(train) [804][20/63] lr: 1.3045e-03 eta: 4:57:28 time: 0.5310 data_time: 0.0089 memory: 16131 loss: 1.0959 loss_prob: 0.5834 loss_thr: 0.4103 loss_db: 0.1022 2022/10/26 05:38:32 - mmengine - INFO - Epoch(train) [804][25/63] lr: 1.3045e-03 eta: 4:57:28 time: 0.5184 data_time: 0.0150 memory: 16131 loss: 1.1461 loss_prob: 0.6112 loss_thr: 0.4282 loss_db: 0.1067 2022/10/26 05:38:36 - mmengine - INFO - Epoch(train) [804][30/63] lr: 1.3045e-03 eta: 4:57:20 time: 0.5768 data_time: 0.0361 memory: 16131 loss: 1.0998 loss_prob: 0.5840 loss_thr: 0.4150 loss_db: 0.1007 2022/10/26 05:38:39 - mmengine - INFO - Epoch(train) [804][35/63] lr: 1.3045e-03 eta: 4:57:20 time: 0.6525 data_time: 0.0462 memory: 16131 loss: 1.0547 loss_prob: 0.5590 loss_thr: 0.3973 loss_db: 0.0983 2022/10/26 05:38:41 - mmengine - INFO - Epoch(train) [804][40/63] lr: 1.3045e-03 eta: 4:57:12 time: 0.5922 data_time: 0.0218 memory: 16131 loss: 1.0881 loss_prob: 0.5823 loss_thr: 0.4033 loss_db: 0.1024 2022/10/26 05:38:44 - mmengine - INFO - Epoch(train) [804][45/63] lr: 1.3045e-03 eta: 4:57:12 time: 0.5201 data_time: 0.0077 memory: 16131 loss: 1.0962 loss_prob: 0.5709 loss_thr: 0.4264 loss_db: 0.0988 2022/10/26 05:38:47 - mmengine - INFO - Epoch(train) [804][50/63] lr: 1.3045e-03 eta: 4:57:04 time: 0.5032 data_time: 0.0072 memory: 16131 loss: 1.0584 loss_prob: 0.5420 loss_thr: 0.4230 loss_db: 0.0935 2022/10/26 05:38:49 - mmengine - INFO - Epoch(train) [804][55/63] lr: 1.3045e-03 eta: 4:57:04 time: 0.5209 data_time: 0.0148 memory: 16131 loss: 1.0360 loss_prob: 0.5455 loss_thr: 0.3958 loss_db: 0.0947 2022/10/26 05:38:52 - mmengine - INFO - Epoch(train) [804][60/63] lr: 1.3045e-03 eta: 4:56:56 time: 0.5376 data_time: 0.0159 memory: 16131 loss: 1.0592 loss_prob: 0.5588 loss_thr: 0.4026 loss_db: 0.0977 2022/10/26 05:38:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:38:58 - mmengine - INFO - Epoch(train) [805][5/63] lr: 1.3016e-03 eta: 4:56:56 time: 0.6608 data_time: 0.1805 memory: 16131 loss: 1.0302 loss_prob: 0.5382 loss_thr: 0.4008 loss_db: 0.0912 2022/10/26 05:39:00 - mmengine - INFO - Epoch(train) [805][10/63] lr: 1.3016e-03 eta: 4:56:46 time: 0.6882 data_time: 0.1819 memory: 16131 loss: 1.0880 loss_prob: 0.5772 loss_thr: 0.4138 loss_db: 0.0970 2022/10/26 05:39:03 - mmengine - INFO - Epoch(train) [805][15/63] lr: 1.3016e-03 eta: 4:56:46 time: 0.5566 data_time: 0.0096 memory: 16131 loss: 1.0829 loss_prob: 0.5682 loss_thr: 0.4170 loss_db: 0.0978 2022/10/26 05:39:06 - mmengine - INFO - Epoch(train) [805][20/63] lr: 1.3016e-03 eta: 4:56:38 time: 0.5481 data_time: 0.0099 memory: 16131 loss: 1.0548 loss_prob: 0.5555 loss_thr: 0.4025 loss_db: 0.0968 2022/10/26 05:39:08 - mmengine - INFO - Epoch(train) [805][25/63] lr: 1.3016e-03 eta: 4:56:38 time: 0.5197 data_time: 0.0308 memory: 16131 loss: 1.0874 loss_prob: 0.5753 loss_thr: 0.4128 loss_db: 0.0993 2022/10/26 05:39:11 - mmengine - INFO - Epoch(train) [805][30/63] lr: 1.3016e-03 eta: 4:56:30 time: 0.5589 data_time: 0.0288 memory: 16131 loss: 1.0605 loss_prob: 0.5517 loss_thr: 0.4125 loss_db: 0.0963 2022/10/26 05:39:14 - mmengine - INFO - Epoch(train) [805][35/63] lr: 1.3016e-03 eta: 4:56:30 time: 0.5360 data_time: 0.0085 memory: 16131 loss: 1.0503 loss_prob: 0.5465 loss_thr: 0.4071 loss_db: 0.0968 2022/10/26 05:39:16 - mmengine - INFO - Epoch(train) [805][40/63] lr: 1.3016e-03 eta: 4:56:22 time: 0.5310 data_time: 0.0095 memory: 16131 loss: 0.9968 loss_prob: 0.5177 loss_thr: 0.3912 loss_db: 0.0879 2022/10/26 05:39:19 - mmengine - INFO - Epoch(train) [805][45/63] lr: 1.3016e-03 eta: 4:56:22 time: 0.5263 data_time: 0.0115 memory: 16131 loss: 1.0200 loss_prob: 0.5449 loss_thr: 0.3836 loss_db: 0.0915 2022/10/26 05:39:22 - mmengine - INFO - Epoch(train) [805][50/63] lr: 1.3016e-03 eta: 4:56:13 time: 0.5091 data_time: 0.0265 memory: 16131 loss: 1.0333 loss_prob: 0.5533 loss_thr: 0.3844 loss_db: 0.0955 2022/10/26 05:39:25 - mmengine - INFO - Epoch(train) [805][55/63] lr: 1.3016e-03 eta: 4:56:13 time: 0.5591 data_time: 0.0216 memory: 16131 loss: 1.0480 loss_prob: 0.5600 loss_thr: 0.3931 loss_db: 0.0950 2022/10/26 05:39:27 - mmengine - INFO - Epoch(train) [805][60/63] lr: 1.3016e-03 eta: 4:56:06 time: 0.5509 data_time: 0.0084 memory: 16131 loss: 1.0931 loss_prob: 0.5799 loss_thr: 0.4157 loss_db: 0.0976 2022/10/26 05:39:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:39:34 - mmengine - INFO - Epoch(train) [806][5/63] lr: 1.2986e-03 eta: 4:56:06 time: 0.7547 data_time: 0.1762 memory: 16131 loss: 1.2420 loss_prob: 0.6762 loss_thr: 0.4549 loss_db: 0.1109 2022/10/26 05:39:37 - mmengine - INFO - Epoch(train) [806][10/63] lr: 1.2986e-03 eta: 4:55:56 time: 0.8192 data_time: 0.1757 memory: 16131 loss: 1.2611 loss_prob: 0.6970 loss_thr: 0.4527 loss_db: 0.1114 2022/10/26 05:39:39 - mmengine - INFO - Epoch(train) [806][15/63] lr: 1.2986e-03 eta: 4:55:56 time: 0.5450 data_time: 0.0062 memory: 16131 loss: 1.1483 loss_prob: 0.6242 loss_thr: 0.4177 loss_db: 0.1064 2022/10/26 05:39:42 - mmengine - INFO - Epoch(train) [806][20/63] lr: 1.2986e-03 eta: 4:55:48 time: 0.5187 data_time: 0.0102 memory: 16131 loss: 1.1784 loss_prob: 0.6346 loss_thr: 0.4347 loss_db: 0.1091 2022/10/26 05:39:44 - mmengine - INFO - Epoch(train) [806][25/63] lr: 1.2986e-03 eta: 4:55:48 time: 0.5238 data_time: 0.0322 memory: 16131 loss: 1.1475 loss_prob: 0.6101 loss_thr: 0.4323 loss_db: 0.1051 2022/10/26 05:39:47 - mmengine - INFO - Epoch(train) [806][30/63] lr: 1.2986e-03 eta: 4:55:40 time: 0.5247 data_time: 0.0325 memory: 16131 loss: 1.0708 loss_prob: 0.5622 loss_thr: 0.4107 loss_db: 0.0979 2022/10/26 05:39:50 - mmengine - INFO - Epoch(train) [806][35/63] lr: 1.2986e-03 eta: 4:55:40 time: 0.5191 data_time: 0.0108 memory: 16131 loss: 1.0695 loss_prob: 0.5696 loss_thr: 0.4012 loss_db: 0.0988 2022/10/26 05:39:52 - mmengine - INFO - Epoch(train) [806][40/63] lr: 1.2986e-03 eta: 4:55:31 time: 0.5134 data_time: 0.0060 memory: 16131 loss: 1.1453 loss_prob: 0.6174 loss_thr: 0.4223 loss_db: 0.1056 2022/10/26 05:39:55 - mmengine - INFO - Epoch(train) [806][45/63] lr: 1.2986e-03 eta: 4:55:31 time: 0.5459 data_time: 0.0053 memory: 16131 loss: 1.0764 loss_prob: 0.5727 loss_thr: 0.4045 loss_db: 0.0993 2022/10/26 05:39:58 - mmengine - INFO - Epoch(train) [806][50/63] lr: 1.2986e-03 eta: 4:55:24 time: 0.5855 data_time: 0.0196 memory: 16131 loss: 1.0033 loss_prob: 0.5256 loss_thr: 0.3860 loss_db: 0.0917 2022/10/26 05:40:01 - mmengine - INFO - Epoch(train) [806][55/63] lr: 1.2986e-03 eta: 4:55:24 time: 0.5643 data_time: 0.0189 memory: 16131 loss: 1.0682 loss_prob: 0.5675 loss_thr: 0.4039 loss_db: 0.0968 2022/10/26 05:40:03 - mmengine - INFO - Epoch(train) [806][60/63] lr: 1.2986e-03 eta: 4:55:16 time: 0.5369 data_time: 0.0054 memory: 16131 loss: 1.0690 loss_prob: 0.5669 loss_thr: 0.4064 loss_db: 0.0958 2022/10/26 05:40:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:40:09 - mmengine - INFO - Epoch(train) [807][5/63] lr: 1.2956e-03 eta: 4:55:16 time: 0.7231 data_time: 0.2091 memory: 16131 loss: 1.0092 loss_prob: 0.5258 loss_thr: 0.3927 loss_db: 0.0908 2022/10/26 05:40:12 - mmengine - INFO - Epoch(train) [807][10/63] lr: 1.2956e-03 eta: 4:55:05 time: 0.7131 data_time: 0.2082 memory: 16131 loss: 1.0465 loss_prob: 0.5496 loss_thr: 0.4014 loss_db: 0.0954 2022/10/26 05:40:14 - mmengine - INFO - Epoch(train) [807][15/63] lr: 1.2956e-03 eta: 4:55:05 time: 0.4917 data_time: 0.0052 memory: 16131 loss: 1.1214 loss_prob: 0.6033 loss_thr: 0.4125 loss_db: 0.1056 2022/10/26 05:40:17 - mmengine - INFO - Epoch(train) [807][20/63] lr: 1.2956e-03 eta: 4:54:57 time: 0.5286 data_time: 0.0060 memory: 16131 loss: 1.1210 loss_prob: 0.6057 loss_thr: 0.4104 loss_db: 0.1048 2022/10/26 05:40:20 - mmengine - INFO - Epoch(train) [807][25/63] lr: 1.2956e-03 eta: 4:54:57 time: 0.5576 data_time: 0.0195 memory: 16131 loss: 1.0888 loss_prob: 0.5798 loss_thr: 0.4112 loss_db: 0.0979 2022/10/26 05:40:23 - mmengine - INFO - Epoch(train) [807][30/63] lr: 1.2956e-03 eta: 4:54:49 time: 0.5500 data_time: 0.0338 memory: 16131 loss: 1.1058 loss_prob: 0.5879 loss_thr: 0.4156 loss_db: 0.1022 2022/10/26 05:40:25 - mmengine - INFO - Epoch(train) [807][35/63] lr: 1.2956e-03 eta: 4:54:49 time: 0.5258 data_time: 0.0238 memory: 16131 loss: 1.1190 loss_prob: 0.5939 loss_thr: 0.4208 loss_db: 0.1043 2022/10/26 05:40:28 - mmengine - INFO - Epoch(train) [807][40/63] lr: 1.2956e-03 eta: 4:54:41 time: 0.5394 data_time: 0.0097 memory: 16131 loss: 1.0510 loss_prob: 0.5547 loss_thr: 0.4012 loss_db: 0.0951 2022/10/26 05:40:30 - mmengine - INFO - Epoch(train) [807][45/63] lr: 1.2956e-03 eta: 4:54:41 time: 0.5405 data_time: 0.0053 memory: 16131 loss: 1.0336 loss_prob: 0.5475 loss_thr: 0.3892 loss_db: 0.0968 2022/10/26 05:40:33 - mmengine - INFO - Epoch(train) [807][50/63] lr: 1.2956e-03 eta: 4:54:33 time: 0.5153 data_time: 0.0215 memory: 16131 loss: 1.0891 loss_prob: 0.5795 loss_thr: 0.4076 loss_db: 0.1020 2022/10/26 05:40:36 - mmengine - INFO - Epoch(train) [807][55/63] lr: 1.2956e-03 eta: 4:54:33 time: 0.5070 data_time: 0.0215 memory: 16131 loss: 1.0653 loss_prob: 0.5606 loss_thr: 0.4102 loss_db: 0.0945 2022/10/26 05:40:38 - mmengine - INFO - Epoch(train) [807][60/63] lr: 1.2956e-03 eta: 4:54:25 time: 0.5013 data_time: 0.0062 memory: 16131 loss: 1.0047 loss_prob: 0.5212 loss_thr: 0.3933 loss_db: 0.0902 2022/10/26 05:40:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:40:44 - mmengine - INFO - Epoch(train) [808][5/63] lr: 1.2927e-03 eta: 4:54:25 time: 0.6914 data_time: 0.1855 memory: 16131 loss: 1.0836 loss_prob: 0.5717 loss_thr: 0.4124 loss_db: 0.0995 2022/10/26 05:40:47 - mmengine - INFO - Epoch(train) [808][10/63] lr: 1.2927e-03 eta: 4:54:15 time: 0.7237 data_time: 0.1862 memory: 16131 loss: 0.9985 loss_prob: 0.5261 loss_thr: 0.3823 loss_db: 0.0901 2022/10/26 05:40:49 - mmengine - INFO - Epoch(train) [808][15/63] lr: 1.2927e-03 eta: 4:54:15 time: 0.5296 data_time: 0.0102 memory: 16131 loss: 0.9687 loss_prob: 0.5096 loss_thr: 0.3702 loss_db: 0.0889 2022/10/26 05:40:52 - mmengine - INFO - Epoch(train) [808][20/63] lr: 1.2927e-03 eta: 4:54:07 time: 0.5089 data_time: 0.0099 memory: 16131 loss: 1.0181 loss_prob: 0.5381 loss_thr: 0.3857 loss_db: 0.0944 2022/10/26 05:40:55 - mmengine - INFO - Epoch(train) [808][25/63] lr: 1.2927e-03 eta: 4:54:07 time: 0.5349 data_time: 0.0184 memory: 16131 loss: 1.1035 loss_prob: 0.5902 loss_thr: 0.4111 loss_db: 0.1022 2022/10/26 05:40:58 - mmengine - INFO - Epoch(train) [808][30/63] lr: 1.2927e-03 eta: 4:53:59 time: 0.5768 data_time: 0.0359 memory: 16131 loss: 1.0636 loss_prob: 0.5666 loss_thr: 0.3989 loss_db: 0.0981 2022/10/26 05:41:00 - mmengine - INFO - Epoch(train) [808][35/63] lr: 1.2927e-03 eta: 4:53:59 time: 0.5710 data_time: 0.0274 memory: 16131 loss: 1.0953 loss_prob: 0.5815 loss_thr: 0.4164 loss_db: 0.0974 2022/10/26 05:41:03 - mmengine - INFO - Epoch(train) [808][40/63] lr: 1.2927e-03 eta: 4:53:51 time: 0.5376 data_time: 0.0085 memory: 16131 loss: 1.1152 loss_prob: 0.5937 loss_thr: 0.4206 loss_db: 0.1008 2022/10/26 05:41:06 - mmengine - INFO - Epoch(train) [808][45/63] lr: 1.2927e-03 eta: 4:53:51 time: 0.5566 data_time: 0.0049 memory: 16131 loss: 1.3865 loss_prob: 0.8335 loss_thr: 0.4286 loss_db: 0.1244 2022/10/26 05:41:08 - mmengine - INFO - Epoch(train) [808][50/63] lr: 1.2927e-03 eta: 4:53:43 time: 0.5550 data_time: 0.0178 memory: 16131 loss: 1.4455 loss_prob: 0.8745 loss_thr: 0.4382 loss_db: 0.1328 2022/10/26 05:41:11 - mmengine - INFO - Epoch(train) [808][55/63] lr: 1.2927e-03 eta: 4:53:43 time: 0.5034 data_time: 0.0208 memory: 16131 loss: 1.2421 loss_prob: 0.6819 loss_thr: 0.4421 loss_db: 0.1181 2022/10/26 05:41:14 - mmengine - INFO - Epoch(train) [808][60/63] lr: 1.2927e-03 eta: 4:53:35 time: 0.5308 data_time: 0.0115 memory: 16131 loss: 1.2723 loss_prob: 0.7045 loss_thr: 0.4522 loss_db: 0.1155 2022/10/26 05:41:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:41:20 - mmengine - INFO - Epoch(train) [809][5/63] lr: 1.2897e-03 eta: 4:53:35 time: 0.7320 data_time: 0.1838 memory: 16131 loss: 1.1670 loss_prob: 0.6211 loss_thr: 0.4382 loss_db: 0.1077 2022/10/26 05:41:22 - mmengine - INFO - Epoch(train) [809][10/63] lr: 1.2897e-03 eta: 4:53:25 time: 0.7152 data_time: 0.1826 memory: 16131 loss: 1.1830 loss_prob: 0.6399 loss_thr: 0.4359 loss_db: 0.1072 2022/10/26 05:41:25 - mmengine - INFO - Epoch(train) [809][15/63] lr: 1.2897e-03 eta: 4:53:25 time: 0.5009 data_time: 0.0122 memory: 16131 loss: 1.1639 loss_prob: 0.6253 loss_thr: 0.4345 loss_db: 0.1041 2022/10/26 05:41:28 - mmengine - INFO - Epoch(train) [809][20/63] lr: 1.2897e-03 eta: 4:53:17 time: 0.5434 data_time: 0.0097 memory: 16131 loss: 1.1145 loss_prob: 0.5944 loss_thr: 0.4177 loss_db: 0.1024 2022/10/26 05:41:31 - mmengine - INFO - Epoch(train) [809][25/63] lr: 1.2897e-03 eta: 4:53:17 time: 0.6005 data_time: 0.0270 memory: 16131 loss: 1.1707 loss_prob: 0.6341 loss_thr: 0.4274 loss_db: 0.1092 2022/10/26 05:41:33 - mmengine - INFO - Epoch(train) [809][30/63] lr: 1.2897e-03 eta: 4:53:09 time: 0.5471 data_time: 0.0279 memory: 16131 loss: 1.1476 loss_prob: 0.6162 loss_thr: 0.4237 loss_db: 0.1076 2022/10/26 05:41:36 - mmengine - INFO - Epoch(train) [809][35/63] lr: 1.2897e-03 eta: 4:53:09 time: 0.4922 data_time: 0.0065 memory: 16131 loss: 1.0125 loss_prob: 0.5338 loss_thr: 0.3862 loss_db: 0.0926 2022/10/26 05:41:38 - mmengine - INFO - Epoch(train) [809][40/63] lr: 1.2897e-03 eta: 4:53:01 time: 0.5008 data_time: 0.0062 memory: 16131 loss: 1.0067 loss_prob: 0.5307 loss_thr: 0.3841 loss_db: 0.0918 2022/10/26 05:41:41 - mmengine - INFO - Epoch(train) [809][45/63] lr: 1.2897e-03 eta: 4:53:01 time: 0.5057 data_time: 0.0090 memory: 16131 loss: 1.1259 loss_prob: 0.6113 loss_thr: 0.4078 loss_db: 0.1068 2022/10/26 05:41:44 - mmengine - INFO - Epoch(train) [809][50/63] lr: 1.2897e-03 eta: 4:52:53 time: 0.5585 data_time: 0.0244 memory: 16131 loss: 1.2366 loss_prob: 0.6769 loss_thr: 0.4456 loss_db: 0.1141 2022/10/26 05:41:46 - mmengine - INFO - Epoch(train) [809][55/63] lr: 1.2897e-03 eta: 4:52:53 time: 0.5731 data_time: 0.0237 memory: 16131 loss: 1.1673 loss_prob: 0.6100 loss_thr: 0.4535 loss_db: 0.1037 2022/10/26 05:41:49 - mmengine - INFO - Epoch(train) [809][60/63] lr: 1.2897e-03 eta: 4:52:45 time: 0.5566 data_time: 0.0086 memory: 16131 loss: 1.1280 loss_prob: 0.5860 loss_thr: 0.4378 loss_db: 0.1042 2022/10/26 05:41:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:41:55 - mmengine - INFO - Epoch(train) [810][5/63] lr: 1.2867e-03 eta: 4:52:45 time: 0.7099 data_time: 0.1953 memory: 16131 loss: 1.0418 loss_prob: 0.5534 loss_thr: 0.3935 loss_db: 0.0949 2022/10/26 05:41:58 - mmengine - INFO - Epoch(train) [810][10/63] lr: 1.2867e-03 eta: 4:52:35 time: 0.6883 data_time: 0.1944 memory: 16131 loss: 0.9838 loss_prob: 0.5173 loss_thr: 0.3779 loss_db: 0.0886 2022/10/26 05:42:00 - mmengine - INFO - Epoch(train) [810][15/63] lr: 1.2867e-03 eta: 4:52:35 time: 0.5315 data_time: 0.0054 memory: 16131 loss: 0.9946 loss_prob: 0.5244 loss_thr: 0.3798 loss_db: 0.0904 2022/10/26 05:42:03 - mmengine - INFO - Epoch(train) [810][20/63] lr: 1.2867e-03 eta: 4:52:26 time: 0.5285 data_time: 0.0072 memory: 16131 loss: 1.0144 loss_prob: 0.5297 loss_thr: 0.3938 loss_db: 0.0909 2022/10/26 05:42:05 - mmengine - INFO - Epoch(train) [810][25/63] lr: 1.2867e-03 eta: 4:52:26 time: 0.4964 data_time: 0.0174 memory: 16131 loss: 1.1389 loss_prob: 0.6111 loss_thr: 0.4216 loss_db: 0.1062 2022/10/26 05:42:08 - mmengine - INFO - Epoch(train) [810][30/63] lr: 1.2867e-03 eta: 4:52:18 time: 0.5231 data_time: 0.0409 memory: 16131 loss: 1.1873 loss_prob: 0.6464 loss_thr: 0.4290 loss_db: 0.1120 2022/10/26 05:42:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:42:11 - mmengine - INFO - Epoch(train) [810][35/63] lr: 1.2867e-03 eta: 4:52:18 time: 0.5251 data_time: 0.0298 memory: 16131 loss: 1.1116 loss_prob: 0.5934 loss_thr: 0.4165 loss_db: 0.1017 2022/10/26 05:42:13 - mmengine - INFO - Epoch(train) [810][40/63] lr: 1.2867e-03 eta: 4:52:10 time: 0.5030 data_time: 0.0043 memory: 16131 loss: 1.1210 loss_prob: 0.5988 loss_thr: 0.4207 loss_db: 0.1014 2022/10/26 05:42:16 - mmengine - INFO - Epoch(train) [810][45/63] lr: 1.2867e-03 eta: 4:52:10 time: 0.5029 data_time: 0.0085 memory: 16131 loss: 1.1007 loss_prob: 0.5876 loss_thr: 0.4119 loss_db: 0.1011 2022/10/26 05:42:18 - mmengine - INFO - Epoch(train) [810][50/63] lr: 1.2867e-03 eta: 4:52:02 time: 0.5285 data_time: 0.0171 memory: 16131 loss: 1.0476 loss_prob: 0.5497 loss_thr: 0.4017 loss_db: 0.0963 2022/10/26 05:42:21 - mmengine - INFO - Epoch(train) [810][55/63] lr: 1.2867e-03 eta: 4:52:02 time: 0.5356 data_time: 0.0264 memory: 16131 loss: 1.0738 loss_prob: 0.5678 loss_thr: 0.4088 loss_db: 0.0972 2022/10/26 05:42:24 - mmengine - INFO - Epoch(train) [810][60/63] lr: 1.2867e-03 eta: 4:51:54 time: 0.5316 data_time: 0.0180 memory: 16131 loss: 1.1438 loss_prob: 0.6177 loss_thr: 0.4224 loss_db: 0.1036 2022/10/26 05:42:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:42:30 - mmengine - INFO - Epoch(train) [811][5/63] lr: 1.2838e-03 eta: 4:51:54 time: 0.7084 data_time: 0.1714 memory: 16131 loss: 1.0114 loss_prob: 0.5281 loss_thr: 0.3925 loss_db: 0.0908 2022/10/26 05:42:32 - mmengine - INFO - Epoch(train) [811][10/63] lr: 1.2838e-03 eta: 4:51:44 time: 0.7443 data_time: 0.1720 memory: 16131 loss: 1.0179 loss_prob: 0.5300 loss_thr: 0.3969 loss_db: 0.0910 2022/10/26 05:42:35 - mmengine - INFO - Epoch(train) [811][15/63] lr: 1.2838e-03 eta: 4:51:44 time: 0.5210 data_time: 0.0061 memory: 16131 loss: 1.0633 loss_prob: 0.5607 loss_thr: 0.4051 loss_db: 0.0976 2022/10/26 05:42:38 - mmengine - INFO - Epoch(train) [811][20/63] lr: 1.2838e-03 eta: 4:51:36 time: 0.5285 data_time: 0.0048 memory: 16131 loss: 1.0606 loss_prob: 0.5594 loss_thr: 0.4024 loss_db: 0.0988 2022/10/26 05:42:40 - mmengine - INFO - Epoch(train) [811][25/63] lr: 1.2838e-03 eta: 4:51:36 time: 0.5204 data_time: 0.0191 memory: 16131 loss: 1.0519 loss_prob: 0.5565 loss_thr: 0.3994 loss_db: 0.0960 2022/10/26 05:42:43 - mmengine - INFO - Epoch(train) [811][30/63] lr: 1.2838e-03 eta: 4:51:28 time: 0.5096 data_time: 0.0318 memory: 16131 loss: 1.0587 loss_prob: 0.5722 loss_thr: 0.3900 loss_db: 0.0965 2022/10/26 05:42:45 - mmengine - INFO - Epoch(train) [811][35/63] lr: 1.2838e-03 eta: 4:51:28 time: 0.4918 data_time: 0.0170 memory: 16131 loss: 1.0547 loss_prob: 0.5679 loss_thr: 0.3898 loss_db: 0.0971 2022/10/26 05:42:48 - mmengine - INFO - Epoch(train) [811][40/63] lr: 1.2838e-03 eta: 4:51:20 time: 0.4877 data_time: 0.0044 memory: 16131 loss: 1.0802 loss_prob: 0.5718 loss_thr: 0.4093 loss_db: 0.0990 2022/10/26 05:42:50 - mmengine - INFO - Epoch(train) [811][45/63] lr: 1.2838e-03 eta: 4:51:20 time: 0.4942 data_time: 0.0059 memory: 16131 loss: 1.1482 loss_prob: 0.6093 loss_thr: 0.4346 loss_db: 0.1044 2022/10/26 05:42:53 - mmengine - INFO - Epoch(train) [811][50/63] lr: 1.2838e-03 eta: 4:51:12 time: 0.4978 data_time: 0.0153 memory: 16131 loss: 1.0947 loss_prob: 0.5824 loss_thr: 0.4117 loss_db: 0.1006 2022/10/26 05:42:55 - mmengine - INFO - Epoch(train) [811][55/63] lr: 1.2838e-03 eta: 4:51:12 time: 0.5247 data_time: 0.0251 memory: 16131 loss: 1.0363 loss_prob: 0.5470 loss_thr: 0.3941 loss_db: 0.0952 2022/10/26 05:42:58 - mmengine - INFO - Epoch(train) [811][60/63] lr: 1.2838e-03 eta: 4:51:04 time: 0.5148 data_time: 0.0179 memory: 16131 loss: 1.1077 loss_prob: 0.5868 loss_thr: 0.4195 loss_db: 0.1014 2022/10/26 05:42:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:43:04 - mmengine - INFO - Epoch(train) [812][5/63] lr: 1.2808e-03 eta: 4:51:04 time: 0.6760 data_time: 0.1628 memory: 16131 loss: 1.1113 loss_prob: 0.5992 loss_thr: 0.4089 loss_db: 0.1031 2022/10/26 05:43:06 - mmengine - INFO - Epoch(train) [812][10/63] lr: 1.2808e-03 eta: 4:50:53 time: 0.7269 data_time: 0.1700 memory: 16131 loss: 1.0412 loss_prob: 0.5530 loss_thr: 0.3913 loss_db: 0.0969 2022/10/26 05:43:09 - mmengine - INFO - Epoch(train) [812][15/63] lr: 1.2808e-03 eta: 4:50:53 time: 0.5322 data_time: 0.0119 memory: 16131 loss: 1.0467 loss_prob: 0.5499 loss_thr: 0.4017 loss_db: 0.0951 2022/10/26 05:43:12 - mmengine - INFO - Epoch(train) [812][20/63] lr: 1.2808e-03 eta: 4:50:45 time: 0.5074 data_time: 0.0063 memory: 16131 loss: 1.1302 loss_prob: 0.6016 loss_thr: 0.4257 loss_db: 0.1029 2022/10/26 05:43:14 - mmengine - INFO - Epoch(train) [812][25/63] lr: 1.2808e-03 eta: 4:50:45 time: 0.4961 data_time: 0.0127 memory: 16131 loss: 1.1150 loss_prob: 0.5952 loss_thr: 0.4164 loss_db: 0.1034 2022/10/26 05:43:17 - mmengine - INFO - Epoch(train) [812][30/63] lr: 1.2808e-03 eta: 4:50:37 time: 0.5017 data_time: 0.0230 memory: 16131 loss: 1.0407 loss_prob: 0.5464 loss_thr: 0.3991 loss_db: 0.0952 2022/10/26 05:43:19 - mmengine - INFO - Epoch(train) [812][35/63] lr: 1.2808e-03 eta: 4:50:37 time: 0.5092 data_time: 0.0248 memory: 16131 loss: 1.0675 loss_prob: 0.5594 loss_thr: 0.4120 loss_db: 0.0962 2022/10/26 05:43:22 - mmengine - INFO - Epoch(train) [812][40/63] lr: 1.2808e-03 eta: 4:50:29 time: 0.5108 data_time: 0.0131 memory: 16131 loss: 1.0659 loss_prob: 0.5707 loss_thr: 0.3979 loss_db: 0.0972 2022/10/26 05:43:24 - mmengine - INFO - Epoch(train) [812][45/63] lr: 1.2808e-03 eta: 4:50:29 time: 0.5350 data_time: 0.0073 memory: 16131 loss: 0.9934 loss_prob: 0.5250 loss_thr: 0.3775 loss_db: 0.0909 2022/10/26 05:43:27 - mmengine - INFO - Epoch(train) [812][50/63] lr: 1.2808e-03 eta: 4:50:21 time: 0.5242 data_time: 0.0149 memory: 16131 loss: 1.0123 loss_prob: 0.5301 loss_thr: 0.3918 loss_db: 0.0905 2022/10/26 05:43:30 - mmengine - INFO - Epoch(train) [812][55/63] lr: 1.2808e-03 eta: 4:50:21 time: 0.5449 data_time: 0.0201 memory: 16131 loss: 1.0674 loss_prob: 0.5644 loss_thr: 0.4055 loss_db: 0.0975 2022/10/26 05:43:32 - mmengine - INFO - Epoch(train) [812][60/63] lr: 1.2808e-03 eta: 4:50:13 time: 0.5534 data_time: 0.0133 memory: 16131 loss: 1.0791 loss_prob: 0.5714 loss_thr: 0.4078 loss_db: 0.0999 2022/10/26 05:43:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:43:38 - mmengine - INFO - Epoch(train) [813][5/63] lr: 1.2778e-03 eta: 4:50:13 time: 0.6758 data_time: 0.2090 memory: 16131 loss: 1.1510 loss_prob: 0.6108 loss_thr: 0.4363 loss_db: 0.1038 2022/10/26 05:43:41 - mmengine - INFO - Epoch(train) [813][10/63] lr: 1.2778e-03 eta: 4:50:03 time: 0.7212 data_time: 0.2091 memory: 16131 loss: 1.2129 loss_prob: 0.6722 loss_thr: 0.4371 loss_db: 0.1037 2022/10/26 05:43:44 - mmengine - INFO - Epoch(train) [813][15/63] lr: 1.2778e-03 eta: 4:50:03 time: 0.5520 data_time: 0.0049 memory: 16131 loss: 1.2273 loss_prob: 0.6860 loss_thr: 0.4363 loss_db: 0.1050 2022/10/26 05:43:46 - mmengine - INFO - Epoch(train) [813][20/63] lr: 1.2778e-03 eta: 4:49:55 time: 0.5573 data_time: 0.0121 memory: 16131 loss: 1.0365 loss_prob: 0.5472 loss_thr: 0.3956 loss_db: 0.0937 2022/10/26 05:43:50 - mmengine - INFO - Epoch(train) [813][25/63] lr: 1.2778e-03 eta: 4:49:55 time: 0.5734 data_time: 0.0477 memory: 16131 loss: 1.0313 loss_prob: 0.5381 loss_thr: 0.3997 loss_db: 0.0935 2022/10/26 05:43:52 - mmengine - INFO - Epoch(train) [813][30/63] lr: 1.2778e-03 eta: 4:49:47 time: 0.5705 data_time: 0.0438 memory: 16131 loss: 1.0210 loss_prob: 0.5333 loss_thr: 0.3951 loss_db: 0.0926 2022/10/26 05:43:55 - mmengine - INFO - Epoch(train) [813][35/63] lr: 1.2778e-03 eta: 4:49:47 time: 0.5394 data_time: 0.0079 memory: 16131 loss: 1.0660 loss_prob: 0.5805 loss_thr: 0.3880 loss_db: 0.0975 2022/10/26 05:43:57 - mmengine - INFO - Epoch(train) [813][40/63] lr: 1.2778e-03 eta: 4:49:39 time: 0.5244 data_time: 0.0041 memory: 16131 loss: 1.1154 loss_prob: 0.5927 loss_thr: 0.4232 loss_db: 0.0995 2022/10/26 05:44:00 - mmengine - INFO - Epoch(train) [813][45/63] lr: 1.2778e-03 eta: 4:49:39 time: 0.5100 data_time: 0.0097 memory: 16131 loss: 1.0725 loss_prob: 0.5569 loss_thr: 0.4189 loss_db: 0.0967 2022/10/26 05:44:03 - mmengine - INFO - Epoch(train) [813][50/63] lr: 1.2778e-03 eta: 4:49:31 time: 0.5207 data_time: 0.0274 memory: 16131 loss: 1.0747 loss_prob: 0.5739 loss_thr: 0.4031 loss_db: 0.0977 2022/10/26 05:44:05 - mmengine - INFO - Epoch(train) [813][55/63] lr: 1.2778e-03 eta: 4:49:31 time: 0.5110 data_time: 0.0218 memory: 16131 loss: 1.0915 loss_prob: 0.5755 loss_thr: 0.4171 loss_db: 0.0989 2022/10/26 05:44:08 - mmengine - INFO - Epoch(train) [813][60/63] lr: 1.2778e-03 eta: 4:49:23 time: 0.5299 data_time: 0.0047 memory: 16131 loss: 1.1107 loss_prob: 0.5901 loss_thr: 0.4170 loss_db: 0.1037 2022/10/26 05:44:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:44:14 - mmengine - INFO - Epoch(train) [814][5/63] lr: 1.2749e-03 eta: 4:49:23 time: 0.7055 data_time: 0.1908 memory: 16131 loss: 1.0925 loss_prob: 0.5849 loss_thr: 0.4079 loss_db: 0.0997 2022/10/26 05:44:16 - mmengine - INFO - Epoch(train) [814][10/63] lr: 1.2749e-03 eta: 4:49:13 time: 0.7210 data_time: 0.1937 memory: 16131 loss: 1.1703 loss_prob: 0.6402 loss_thr: 0.4252 loss_db: 0.1050 2022/10/26 05:44:19 - mmengine - INFO - Epoch(train) [814][15/63] lr: 1.2749e-03 eta: 4:49:13 time: 0.5176 data_time: 0.0102 memory: 16131 loss: 1.2176 loss_prob: 0.6690 loss_thr: 0.4363 loss_db: 0.1124 2022/10/26 05:44:22 - mmengine - INFO - Epoch(train) [814][20/63] lr: 1.2749e-03 eta: 4:49:05 time: 0.5102 data_time: 0.0097 memory: 16131 loss: 1.1208 loss_prob: 0.6157 loss_thr: 0.3992 loss_db: 0.1059 2022/10/26 05:44:24 - mmengine - INFO - Epoch(train) [814][25/63] lr: 1.2749e-03 eta: 4:49:05 time: 0.5322 data_time: 0.0256 memory: 16131 loss: 1.1583 loss_prob: 0.6383 loss_thr: 0.4111 loss_db: 0.1089 2022/10/26 05:44:27 - mmengine - INFO - Epoch(train) [814][30/63] lr: 1.2749e-03 eta: 4:48:57 time: 0.5286 data_time: 0.0242 memory: 16131 loss: 1.1078 loss_prob: 0.5890 loss_thr: 0.4166 loss_db: 0.1021 2022/10/26 05:44:29 - mmengine - INFO - Epoch(train) [814][35/63] lr: 1.2749e-03 eta: 4:48:57 time: 0.4964 data_time: 0.0152 memory: 16131 loss: 1.1055 loss_prob: 0.5845 loss_thr: 0.4168 loss_db: 0.1041 2022/10/26 05:44:32 - mmengine - INFO - Epoch(train) [814][40/63] lr: 1.2749e-03 eta: 4:48:49 time: 0.5060 data_time: 0.0138 memory: 16131 loss: 1.1067 loss_prob: 0.5872 loss_thr: 0.4155 loss_db: 0.1041 2022/10/26 05:44:35 - mmengine - INFO - Epoch(train) [814][45/63] lr: 1.2749e-03 eta: 4:48:49 time: 0.5175 data_time: 0.0067 memory: 16131 loss: 1.0291 loss_prob: 0.5382 loss_thr: 0.3968 loss_db: 0.0942 2022/10/26 05:44:37 - mmengine - INFO - Epoch(train) [814][50/63] lr: 1.2749e-03 eta: 4:48:41 time: 0.5242 data_time: 0.0195 memory: 16131 loss: 1.0047 loss_prob: 0.5275 loss_thr: 0.3849 loss_db: 0.0923 2022/10/26 05:44:40 - mmengine - INFO - Epoch(train) [814][55/63] lr: 1.2749e-03 eta: 4:48:41 time: 0.5107 data_time: 0.0208 memory: 16131 loss: 1.1140 loss_prob: 0.6072 loss_thr: 0.4045 loss_db: 0.1022 2022/10/26 05:44:42 - mmengine - INFO - Epoch(train) [814][60/63] lr: 1.2749e-03 eta: 4:48:33 time: 0.5026 data_time: 0.0073 memory: 16131 loss: 1.1127 loss_prob: 0.6012 loss_thr: 0.4122 loss_db: 0.0993 2022/10/26 05:44:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:44:48 - mmengine - INFO - Epoch(train) [815][5/63] lr: 1.2719e-03 eta: 4:48:33 time: 0.7265 data_time: 0.1877 memory: 16131 loss: 1.0903 loss_prob: 0.5915 loss_thr: 0.4012 loss_db: 0.0976 2022/10/26 05:44:51 - mmengine - INFO - Epoch(train) [815][10/63] lr: 1.2719e-03 eta: 4:48:23 time: 0.7690 data_time: 0.1875 memory: 16131 loss: 1.0978 loss_prob: 0.5899 loss_thr: 0.4072 loss_db: 0.1007 2022/10/26 05:44:54 - mmengine - INFO - Epoch(train) [815][15/63] lr: 1.2719e-03 eta: 4:48:23 time: 0.5423 data_time: 0.0079 memory: 16131 loss: 1.0812 loss_prob: 0.5723 loss_thr: 0.4112 loss_db: 0.0977 2022/10/26 05:44:57 - mmengine - INFO - Epoch(train) [815][20/63] lr: 1.2719e-03 eta: 4:48:15 time: 0.5506 data_time: 0.0085 memory: 16131 loss: 1.0814 loss_prob: 0.5673 loss_thr: 0.4181 loss_db: 0.0959 2022/10/26 05:44:59 - mmengine - INFO - Epoch(train) [815][25/63] lr: 1.2719e-03 eta: 4:48:15 time: 0.5548 data_time: 0.0191 memory: 16131 loss: 1.0436 loss_prob: 0.5451 loss_thr: 0.4043 loss_db: 0.0941 2022/10/26 05:45:02 - mmengine - INFO - Epoch(train) [815][30/63] lr: 1.2719e-03 eta: 4:48:07 time: 0.5546 data_time: 0.0367 memory: 16131 loss: 1.0336 loss_prob: 0.5441 loss_thr: 0.3949 loss_db: 0.0947 2022/10/26 05:45:05 - mmengine - INFO - Epoch(train) [815][35/63] lr: 1.2719e-03 eta: 4:48:07 time: 0.5924 data_time: 0.0306 memory: 16131 loss: 1.0319 loss_prob: 0.5410 loss_thr: 0.3978 loss_db: 0.0931 2022/10/26 05:45:08 - mmengine - INFO - Epoch(train) [815][40/63] lr: 1.2719e-03 eta: 4:47:59 time: 0.5533 data_time: 0.0104 memory: 16131 loss: 1.0001 loss_prob: 0.5272 loss_thr: 0.3829 loss_db: 0.0900 2022/10/26 05:45:10 - mmengine - INFO - Epoch(train) [815][45/63] lr: 1.2719e-03 eta: 4:47:59 time: 0.4918 data_time: 0.0065 memory: 16131 loss: 0.9787 loss_prob: 0.5107 loss_thr: 0.3786 loss_db: 0.0894 2022/10/26 05:45:13 - mmengine - INFO - Epoch(train) [815][50/63] lr: 1.2719e-03 eta: 4:47:51 time: 0.5227 data_time: 0.0127 memory: 16131 loss: 1.0484 loss_prob: 0.5502 loss_thr: 0.4027 loss_db: 0.0955 2022/10/26 05:45:16 - mmengine - INFO - Epoch(train) [815][55/63] lr: 1.2719e-03 eta: 4:47:51 time: 0.5413 data_time: 0.0203 memory: 16131 loss: 1.0802 loss_prob: 0.5724 loss_thr: 0.4111 loss_db: 0.0967 2022/10/26 05:45:18 - mmengine - INFO - Epoch(train) [815][60/63] lr: 1.2719e-03 eta: 4:47:43 time: 0.5158 data_time: 0.0184 memory: 16131 loss: 1.0427 loss_prob: 0.5447 loss_thr: 0.4056 loss_db: 0.0925 2022/10/26 05:45:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:45:24 - mmengine - INFO - Epoch(train) [816][5/63] lr: 1.2689e-03 eta: 4:47:43 time: 0.7293 data_time: 0.2184 memory: 16131 loss: 0.9831 loss_prob: 0.5264 loss_thr: 0.3650 loss_db: 0.0917 2022/10/26 05:45:27 - mmengine - INFO - Epoch(train) [816][10/63] lr: 1.2689e-03 eta: 4:47:33 time: 0.7558 data_time: 0.2186 memory: 16131 loss: 1.0189 loss_prob: 0.5426 loss_thr: 0.3859 loss_db: 0.0904 2022/10/26 05:45:29 - mmengine - INFO - Epoch(train) [816][15/63] lr: 1.2689e-03 eta: 4:47:33 time: 0.5027 data_time: 0.0108 memory: 16131 loss: 1.0875 loss_prob: 0.5890 loss_thr: 0.4010 loss_db: 0.0975 2022/10/26 05:45:32 - mmengine - INFO - Epoch(train) [816][20/63] lr: 1.2689e-03 eta: 4:47:25 time: 0.4920 data_time: 0.0174 memory: 16131 loss: 1.0859 loss_prob: 0.5849 loss_thr: 0.3999 loss_db: 0.1010 2022/10/26 05:45:35 - mmengine - INFO - Epoch(train) [816][25/63] lr: 1.2689e-03 eta: 4:47:25 time: 0.5432 data_time: 0.0421 memory: 16131 loss: 1.0764 loss_prob: 0.5690 loss_thr: 0.4081 loss_db: 0.0993 2022/10/26 05:45:38 - mmengine - INFO - Epoch(train) [816][30/63] lr: 1.2689e-03 eta: 4:47:17 time: 0.5709 data_time: 0.0355 memory: 16131 loss: 1.0657 loss_prob: 0.5571 loss_thr: 0.4109 loss_db: 0.0977 2022/10/26 05:45:40 - mmengine - INFO - Epoch(train) [816][35/63] lr: 1.2689e-03 eta: 4:47:17 time: 0.5280 data_time: 0.0058 memory: 16131 loss: 0.9991 loss_prob: 0.5186 loss_thr: 0.3891 loss_db: 0.0914 2022/10/26 05:45:43 - mmengine - INFO - Epoch(train) [816][40/63] lr: 1.2689e-03 eta: 4:47:09 time: 0.5003 data_time: 0.0058 memory: 16131 loss: 1.0294 loss_prob: 0.5497 loss_thr: 0.3855 loss_db: 0.0941 2022/10/26 05:45:45 - mmengine - INFO - Epoch(train) [816][45/63] lr: 1.2689e-03 eta: 4:47:09 time: 0.5265 data_time: 0.0047 memory: 16131 loss: 1.0074 loss_prob: 0.5346 loss_thr: 0.3812 loss_db: 0.0916 2022/10/26 05:45:48 - mmengine - INFO - Epoch(train) [816][50/63] lr: 1.2689e-03 eta: 4:47:01 time: 0.5494 data_time: 0.0233 memory: 16131 loss: 0.9480 loss_prob: 0.4934 loss_thr: 0.3679 loss_db: 0.0867 2022/10/26 05:45:51 - mmengine - INFO - Epoch(train) [816][55/63] lr: 1.2689e-03 eta: 4:47:01 time: 0.5262 data_time: 0.0252 memory: 16131 loss: 0.9785 loss_prob: 0.5115 loss_thr: 0.3776 loss_db: 0.0894 2022/10/26 05:45:53 - mmengine - INFO - Epoch(train) [816][60/63] lr: 1.2689e-03 eta: 4:46:53 time: 0.4968 data_time: 0.0073 memory: 16131 loss: 1.0199 loss_prob: 0.5375 loss_thr: 0.3904 loss_db: 0.0920 2022/10/26 05:45:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:46:00 - mmengine - INFO - Epoch(train) [817][5/63] lr: 1.2659e-03 eta: 4:46:53 time: 0.7459 data_time: 0.1884 memory: 16131 loss: 1.0116 loss_prob: 0.5365 loss_thr: 0.3816 loss_db: 0.0935 2022/10/26 05:46:02 - mmengine - INFO - Epoch(train) [817][10/63] lr: 1.2659e-03 eta: 4:46:43 time: 0.7876 data_time: 0.2007 memory: 16131 loss: 1.0530 loss_prob: 0.5593 loss_thr: 0.3971 loss_db: 0.0966 2022/10/26 05:46:05 - mmengine - INFO - Epoch(train) [817][15/63] lr: 1.2659e-03 eta: 4:46:43 time: 0.5227 data_time: 0.0174 memory: 16131 loss: 0.9891 loss_prob: 0.5167 loss_thr: 0.3835 loss_db: 0.0889 2022/10/26 05:46:08 - mmengine - INFO - Epoch(train) [817][20/63] lr: 1.2659e-03 eta: 4:46:35 time: 0.5225 data_time: 0.0069 memory: 16131 loss: 0.9685 loss_prob: 0.4948 loss_thr: 0.3878 loss_db: 0.0859 2022/10/26 05:46:11 - mmengine - INFO - Epoch(train) [817][25/63] lr: 1.2659e-03 eta: 4:46:35 time: 0.5747 data_time: 0.0238 memory: 16131 loss: 1.0596 loss_prob: 0.5450 loss_thr: 0.4202 loss_db: 0.0944 2022/10/26 05:46:13 - mmengine - INFO - Epoch(train) [817][30/63] lr: 1.2659e-03 eta: 4:46:27 time: 0.5587 data_time: 0.0255 memory: 16131 loss: 1.1203 loss_prob: 0.5845 loss_thr: 0.4353 loss_db: 0.1005 2022/10/26 05:46:16 - mmengine - INFO - Epoch(train) [817][35/63] lr: 1.2659e-03 eta: 4:46:27 time: 0.5184 data_time: 0.0151 memory: 16131 loss: 1.1213 loss_prob: 0.5844 loss_thr: 0.4353 loss_db: 0.1016 2022/10/26 05:46:18 - mmengine - INFO - Epoch(train) [817][40/63] lr: 1.2659e-03 eta: 4:46:19 time: 0.5108 data_time: 0.0134 memory: 16131 loss: 1.0870 loss_prob: 0.5700 loss_thr: 0.4158 loss_db: 0.1012 2022/10/26 05:46:21 - mmengine - INFO - Epoch(train) [817][45/63] lr: 1.2659e-03 eta: 4:46:19 time: 0.5047 data_time: 0.0068 memory: 16131 loss: 1.0534 loss_prob: 0.5593 loss_thr: 0.3985 loss_db: 0.0956 2022/10/26 05:46:23 - mmengine - INFO - Epoch(train) [817][50/63] lr: 1.2659e-03 eta: 4:46:11 time: 0.5184 data_time: 0.0193 memory: 16131 loss: 1.0068 loss_prob: 0.5421 loss_thr: 0.3749 loss_db: 0.0897 2022/10/26 05:46:26 - mmengine - INFO - Epoch(train) [817][55/63] lr: 1.2659e-03 eta: 4:46:11 time: 0.5001 data_time: 0.0315 memory: 16131 loss: 1.0270 loss_prob: 0.5457 loss_thr: 0.3863 loss_db: 0.0950 2022/10/26 05:46:28 - mmengine - INFO - Epoch(train) [817][60/63] lr: 1.2659e-03 eta: 4:46:03 time: 0.4975 data_time: 0.0167 memory: 16131 loss: 1.0621 loss_prob: 0.5558 loss_thr: 0.4096 loss_db: 0.0967 2022/10/26 05:46:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:46:34 - mmengine - INFO - Epoch(train) [818][5/63] lr: 1.2630e-03 eta: 4:46:03 time: 0.6710 data_time: 0.1930 memory: 16131 loss: 1.0550 loss_prob: 0.5617 loss_thr: 0.3978 loss_db: 0.0954 2022/10/26 05:46:37 - mmengine - INFO - Epoch(train) [818][10/63] lr: 1.2630e-03 eta: 4:45:53 time: 0.7519 data_time: 0.2013 memory: 16131 loss: 1.1178 loss_prob: 0.6006 loss_thr: 0.4142 loss_db: 0.1030 2022/10/26 05:46:40 - mmengine - INFO - Epoch(train) [818][15/63] lr: 1.2630e-03 eta: 4:45:53 time: 0.5662 data_time: 0.0137 memory: 16131 loss: 1.1511 loss_prob: 0.6260 loss_thr: 0.4187 loss_db: 0.1064 2022/10/26 05:46:43 - mmengine - INFO - Epoch(train) [818][20/63] lr: 1.2630e-03 eta: 4:45:45 time: 0.5446 data_time: 0.0055 memory: 16131 loss: 1.0747 loss_prob: 0.5763 loss_thr: 0.3986 loss_db: 0.0999 2022/10/26 05:46:45 - mmengine - INFO - Epoch(train) [818][25/63] lr: 1.2630e-03 eta: 4:45:45 time: 0.5635 data_time: 0.0190 memory: 16131 loss: 1.1057 loss_prob: 0.6016 loss_thr: 0.4027 loss_db: 0.1014 2022/10/26 05:46:48 - mmengine - INFO - Epoch(train) [818][30/63] lr: 1.2630e-03 eta: 4:45:37 time: 0.5500 data_time: 0.0314 memory: 16131 loss: 1.1094 loss_prob: 0.6006 loss_thr: 0.4094 loss_db: 0.0995 2022/10/26 05:46:51 - mmengine - INFO - Epoch(train) [818][35/63] lr: 1.2630e-03 eta: 4:45:37 time: 0.5155 data_time: 0.0235 memory: 16131 loss: 1.0227 loss_prob: 0.5355 loss_thr: 0.3959 loss_db: 0.0913 2022/10/26 05:46:53 - mmengine - INFO - Epoch(train) [818][40/63] lr: 1.2630e-03 eta: 4:45:29 time: 0.5110 data_time: 0.0109 memory: 16131 loss: 1.1946 loss_prob: 0.6852 loss_thr: 0.3964 loss_db: 0.1130 2022/10/26 05:46:56 - mmengine - INFO - Epoch(train) [818][45/63] lr: 1.2630e-03 eta: 4:45:29 time: 0.5113 data_time: 0.0066 memory: 16131 loss: 1.3760 loss_prob: 0.8357 loss_thr: 0.4035 loss_db: 0.1368 2022/10/26 05:46:59 - mmengine - INFO - Epoch(train) [818][50/63] lr: 1.2630e-03 eta: 4:45:21 time: 0.5350 data_time: 0.0184 memory: 16131 loss: 1.2863 loss_prob: 0.7444 loss_thr: 0.4183 loss_db: 0.1236 2022/10/26 05:47:01 - mmengine - INFO - Epoch(train) [818][55/63] lr: 1.2630e-03 eta: 4:45:21 time: 0.5489 data_time: 0.0286 memory: 16131 loss: 1.3235 loss_prob: 0.7343 loss_thr: 0.4694 loss_db: 0.1198 2022/10/26 05:47:04 - mmengine - INFO - Epoch(train) [818][60/63] lr: 1.2630e-03 eta: 4:45:13 time: 0.5344 data_time: 0.0168 memory: 16131 loss: 1.3523 loss_prob: 0.7489 loss_thr: 0.4803 loss_db: 0.1232 2022/10/26 05:47:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:47:10 - mmengine - INFO - Epoch(train) [819][5/63] lr: 1.2600e-03 eta: 4:45:13 time: 0.6772 data_time: 0.1843 memory: 16131 loss: 1.1967 loss_prob: 0.6457 loss_thr: 0.4389 loss_db: 0.1121 2022/10/26 05:47:12 - mmengine - INFO - Epoch(train) [819][10/63] lr: 1.2600e-03 eta: 4:45:03 time: 0.7102 data_time: 0.1851 memory: 16131 loss: 1.1366 loss_prob: 0.6064 loss_thr: 0.4250 loss_db: 0.1053 2022/10/26 05:47:15 - mmengine - INFO - Epoch(train) [819][15/63] lr: 1.2600e-03 eta: 4:45:03 time: 0.5534 data_time: 0.0097 memory: 16131 loss: 1.1304 loss_prob: 0.6019 loss_thr: 0.4255 loss_db: 0.1030 2022/10/26 05:47:18 - mmengine - INFO - Epoch(train) [819][20/63] lr: 1.2600e-03 eta: 4:44:55 time: 0.5373 data_time: 0.0100 memory: 16131 loss: 1.1547 loss_prob: 0.6198 loss_thr: 0.4297 loss_db: 0.1052 2022/10/26 05:47:20 - mmengine - INFO - Epoch(train) [819][25/63] lr: 1.2600e-03 eta: 4:44:55 time: 0.5293 data_time: 0.0211 memory: 16131 loss: 1.1241 loss_prob: 0.6104 loss_thr: 0.4109 loss_db: 0.1028 2022/10/26 05:47:23 - mmengine - INFO - Epoch(train) [819][30/63] lr: 1.2600e-03 eta: 4:44:47 time: 0.5621 data_time: 0.0307 memory: 16131 loss: 1.1504 loss_prob: 0.6134 loss_thr: 0.4343 loss_db: 0.1028 2022/10/26 05:47:26 - mmengine - INFO - Epoch(train) [819][35/63] lr: 1.2600e-03 eta: 4:44:47 time: 0.5369 data_time: 0.0156 memory: 16131 loss: 1.0970 loss_prob: 0.5712 loss_thr: 0.4296 loss_db: 0.0963 2022/10/26 05:47:28 - mmengine - INFO - Epoch(train) [819][40/63] lr: 1.2600e-03 eta: 4:44:39 time: 0.5171 data_time: 0.0101 memory: 16131 loss: 0.9856 loss_prob: 0.5132 loss_thr: 0.3838 loss_db: 0.0886 2022/10/26 05:47:31 - mmengine - INFO - Epoch(train) [819][45/63] lr: 1.2600e-03 eta: 4:44:39 time: 0.5341 data_time: 0.0135 memory: 16131 loss: 1.0949 loss_prob: 0.5826 loss_thr: 0.4105 loss_db: 0.1019 2022/10/26 05:47:34 - mmengine - INFO - Epoch(train) [819][50/63] lr: 1.2600e-03 eta: 4:44:31 time: 0.5230 data_time: 0.0168 memory: 16131 loss: 1.2380 loss_prob: 0.6625 loss_thr: 0.4617 loss_db: 0.1139 2022/10/26 05:47:36 - mmengine - INFO - Epoch(train) [819][55/63] lr: 1.2600e-03 eta: 4:44:31 time: 0.5019 data_time: 0.0194 memory: 16131 loss: 1.2721 loss_prob: 0.6812 loss_thr: 0.4729 loss_db: 0.1180 2022/10/26 05:47:39 - mmengine - INFO - Epoch(train) [819][60/63] lr: 1.2600e-03 eta: 4:44:23 time: 0.5330 data_time: 0.0108 memory: 16131 loss: 1.1580 loss_prob: 0.6236 loss_thr: 0.4272 loss_db: 0.1072 2022/10/26 05:47:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:47:45 - mmengine - INFO - Epoch(train) [820][5/63] lr: 1.2570e-03 eta: 4:44:23 time: 0.7075 data_time: 0.2049 memory: 16131 loss: 1.0280 loss_prob: 0.5480 loss_thr: 0.3885 loss_db: 0.0915 2022/10/26 05:47:47 - mmengine - INFO - Epoch(train) [820][10/63] lr: 1.2570e-03 eta: 4:44:13 time: 0.7075 data_time: 0.2007 memory: 16131 loss: 1.1162 loss_prob: 0.5920 loss_thr: 0.4203 loss_db: 0.1039 2022/10/26 05:47:50 - mmengine - INFO - Epoch(train) [820][15/63] lr: 1.2570e-03 eta: 4:44:13 time: 0.4898 data_time: 0.0044 memory: 16131 loss: 1.1633 loss_prob: 0.6137 loss_thr: 0.4446 loss_db: 0.1050 2022/10/26 05:47:52 - mmengine - INFO - Epoch(train) [820][20/63] lr: 1.2570e-03 eta: 4:44:05 time: 0.4974 data_time: 0.0044 memory: 16131 loss: 1.0856 loss_prob: 0.5664 loss_thr: 0.4222 loss_db: 0.0970 2022/10/26 05:47:55 - mmengine - INFO - Epoch(train) [820][25/63] lr: 1.2570e-03 eta: 4:44:05 time: 0.5071 data_time: 0.0155 memory: 16131 loss: 0.9924 loss_prob: 0.5144 loss_thr: 0.3850 loss_db: 0.0929 2022/10/26 05:47:58 - mmengine - INFO - Epoch(train) [820][30/63] lr: 1.2570e-03 eta: 4:43:57 time: 0.5119 data_time: 0.0304 memory: 16131 loss: 1.0475 loss_prob: 0.5713 loss_thr: 0.3826 loss_db: 0.0936 2022/10/26 05:48:00 - mmengine - INFO - Epoch(train) [820][35/63] lr: 1.2570e-03 eta: 4:43:57 time: 0.5068 data_time: 0.0212 memory: 16131 loss: 1.4665 loss_prob: 0.8951 loss_thr: 0.4413 loss_db: 0.1301 2022/10/26 05:48:03 - mmengine - INFO - Epoch(train) [820][40/63] lr: 1.2570e-03 eta: 4:43:49 time: 0.5006 data_time: 0.0070 memory: 16131 loss: 1.4920 loss_prob: 0.9099 loss_thr: 0.4400 loss_db: 0.1420 2022/10/26 05:48:05 - mmengine - INFO - Epoch(train) [820][45/63] lr: 1.2570e-03 eta: 4:43:49 time: 0.4955 data_time: 0.0056 memory: 16131 loss: 1.1758 loss_prob: 0.6611 loss_thr: 0.4013 loss_db: 0.1134 2022/10/26 05:48:08 - mmengine - INFO - Epoch(train) [820][50/63] lr: 1.2570e-03 eta: 4:43:41 time: 0.5092 data_time: 0.0135 memory: 16131 loss: 1.1228 loss_prob: 0.6166 loss_thr: 0.4029 loss_db: 0.1033 2022/10/26 05:48:11 - mmengine - INFO - Epoch(train) [820][55/63] lr: 1.2570e-03 eta: 4:43:41 time: 0.5948 data_time: 0.0252 memory: 16131 loss: 1.1041 loss_prob: 0.5891 loss_thr: 0.4137 loss_db: 0.1013 2022/10/26 05:48:13 - mmengine - INFO - Epoch(train) [820][60/63] lr: 1.2570e-03 eta: 4:43:33 time: 0.5787 data_time: 0.0173 memory: 16131 loss: 1.0938 loss_prob: 0.5797 loss_thr: 0.4143 loss_db: 0.0998 2022/10/26 05:48:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:48:15 - mmengine - INFO - Saving checkpoint at 820 epochs 2022/10/26 05:48:21 - mmengine - INFO - Epoch(val) [820][5/32] eta: 4:43:33 time: 0.4936 data_time: 0.0539 memory: 16131 2022/10/26 05:48:24 - mmengine - INFO - Epoch(val) [820][10/32] eta: 0:00:12 time: 0.5822 data_time: 0.0875 memory: 15724 2022/10/26 05:48:27 - mmengine - INFO - Epoch(val) [820][15/32] eta: 0:00:12 time: 0.5489 data_time: 0.0490 memory: 15724 2022/10/26 05:48:29 - mmengine - INFO - Epoch(val) [820][20/32] eta: 0:00:06 time: 0.5272 data_time: 0.0408 memory: 15724 2022/10/26 05:48:32 - mmengine - INFO - Epoch(val) [820][25/32] eta: 0:00:06 time: 0.5635 data_time: 0.0564 memory: 15724 2022/10/26 05:48:35 - mmengine - INFO - Epoch(val) [820][30/32] eta: 0:00:01 time: 0.5367 data_time: 0.0310 memory: 15724 2022/10/26 05:48:35 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8363, precision: 0.7519, hmean: 0.7919 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8363, precision: 0.8117, hmean: 0.8238 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8339, precision: 0.8478, hmean: 0.8408 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8276, precision: 0.8682, hmean: 0.8474 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8089, precision: 0.8946, hmean: 0.8496 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7106, precision: 0.9289, hmean: 0.8052 2022/10/26 05:48:35 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0722, precision: 0.9934, hmean: 0.1346 2022/10/26 05:48:35 - mmengine - INFO - Epoch(val) [820][32/32] icdar/precision: 0.8946 icdar/recall: 0.8089 icdar/hmean: 0.8496 2022/10/26 05:48:40 - mmengine - INFO - Epoch(train) [821][5/63] lr: 1.2540e-03 eta: 0:00:01 time: 0.6858 data_time: 0.1797 memory: 16131 loss: 1.1576 loss_prob: 0.6181 loss_thr: 0.4345 loss_db: 0.1050 2022/10/26 05:48:43 - mmengine - INFO - Epoch(train) [821][10/63] lr: 1.2540e-03 eta: 4:43:23 time: 0.7283 data_time: 0.1802 memory: 16131 loss: 1.1250 loss_prob: 0.6058 loss_thr: 0.4127 loss_db: 0.1066 2022/10/26 05:48:46 - mmengine - INFO - Epoch(train) [821][15/63] lr: 1.2540e-03 eta: 4:43:23 time: 0.5579 data_time: 0.0077 memory: 16131 loss: 1.1025 loss_prob: 0.5920 loss_thr: 0.4049 loss_db: 0.1056 2022/10/26 05:48:49 - mmengine - INFO - Epoch(train) [821][20/63] lr: 1.2540e-03 eta: 4:43:15 time: 0.6126 data_time: 0.0076 memory: 16131 loss: 1.1180 loss_prob: 0.5985 loss_thr: 0.4163 loss_db: 0.1032 2022/10/26 05:48:51 - mmengine - INFO - Epoch(train) [821][25/63] lr: 1.2540e-03 eta: 4:43:15 time: 0.5685 data_time: 0.0099 memory: 16131 loss: 1.1431 loss_prob: 0.6231 loss_thr: 0.4159 loss_db: 0.1041 2022/10/26 05:48:54 - mmengine - INFO - Epoch(train) [821][30/63] lr: 1.2540e-03 eta: 4:43:07 time: 0.5089 data_time: 0.0276 memory: 16131 loss: 1.1224 loss_prob: 0.6054 loss_thr: 0.4135 loss_db: 0.1035 2022/10/26 05:48:57 - mmengine - INFO - Epoch(train) [821][35/63] lr: 1.2540e-03 eta: 4:43:07 time: 0.5311 data_time: 0.0280 memory: 16131 loss: 1.1347 loss_prob: 0.6006 loss_thr: 0.4299 loss_db: 0.1042 2022/10/26 05:48:59 - mmengine - INFO - Epoch(train) [821][40/63] lr: 1.2540e-03 eta: 4:42:59 time: 0.5108 data_time: 0.0100 memory: 16131 loss: 1.1262 loss_prob: 0.5975 loss_thr: 0.4268 loss_db: 0.1018 2022/10/26 05:49:02 - mmengine - INFO - Epoch(train) [821][45/63] lr: 1.2540e-03 eta: 4:42:59 time: 0.4951 data_time: 0.0048 memory: 16131 loss: 1.0956 loss_prob: 0.5881 loss_thr: 0.4086 loss_db: 0.0989 2022/10/26 05:49:04 - mmengine - INFO - Epoch(train) [821][50/63] lr: 1.2540e-03 eta: 4:42:51 time: 0.5245 data_time: 0.0185 memory: 16131 loss: 1.0985 loss_prob: 0.5898 loss_thr: 0.4085 loss_db: 0.1001 2022/10/26 05:49:07 - mmengine - INFO - Epoch(train) [821][55/63] lr: 1.2540e-03 eta: 4:42:51 time: 0.5183 data_time: 0.0195 memory: 16131 loss: 1.1737 loss_prob: 0.6372 loss_thr: 0.4282 loss_db: 0.1083 2022/10/26 05:49:10 - mmengine - INFO - Epoch(train) [821][60/63] lr: 1.2540e-03 eta: 4:42:44 time: 0.5459 data_time: 0.0121 memory: 16131 loss: 1.1594 loss_prob: 0.6267 loss_thr: 0.4253 loss_db: 0.1075 2022/10/26 05:49:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:49:15 - mmengine - INFO - Epoch(train) [822][5/63] lr: 1.2511e-03 eta: 4:42:44 time: 0.6838 data_time: 0.1896 memory: 16131 loss: 1.0912 loss_prob: 0.5813 loss_thr: 0.4077 loss_db: 0.1021 2022/10/26 05:49:18 - mmengine - INFO - Epoch(train) [822][10/63] lr: 1.2511e-03 eta: 4:42:33 time: 0.6931 data_time: 0.1930 memory: 16131 loss: 1.0957 loss_prob: 0.5914 loss_thr: 0.4011 loss_db: 0.1032 2022/10/26 05:49:20 - mmengine - INFO - Epoch(train) [822][15/63] lr: 1.2511e-03 eta: 4:42:33 time: 0.5059 data_time: 0.0111 memory: 16131 loss: 1.1021 loss_prob: 0.5929 loss_thr: 0.4061 loss_db: 0.1031 2022/10/26 05:49:23 - mmengine - INFO - Epoch(train) [822][20/63] lr: 1.2511e-03 eta: 4:42:25 time: 0.5185 data_time: 0.0052 memory: 16131 loss: 1.1220 loss_prob: 0.5974 loss_thr: 0.4212 loss_db: 0.1034 2022/10/26 05:49:26 - mmengine - INFO - Epoch(train) [822][25/63] lr: 1.2511e-03 eta: 4:42:25 time: 0.5661 data_time: 0.0144 memory: 16131 loss: 1.1533 loss_prob: 0.6267 loss_thr: 0.4217 loss_db: 0.1050 2022/10/26 05:49:29 - mmengine - INFO - Epoch(train) [822][30/63] lr: 1.2511e-03 eta: 4:42:18 time: 0.5658 data_time: 0.0316 memory: 16131 loss: 1.2751 loss_prob: 0.6911 loss_thr: 0.4726 loss_db: 0.1114 2022/10/26 05:49:31 - mmengine - INFO - Epoch(train) [822][35/63] lr: 1.2511e-03 eta: 4:42:18 time: 0.5120 data_time: 0.0277 memory: 16131 loss: 1.1727 loss_prob: 0.6227 loss_thr: 0.4456 loss_db: 0.1045 2022/10/26 05:49:34 - mmengine - INFO - Epoch(train) [822][40/63] lr: 1.2511e-03 eta: 4:42:09 time: 0.5052 data_time: 0.0098 memory: 16131 loss: 1.0110 loss_prob: 0.5309 loss_thr: 0.3863 loss_db: 0.0939 2022/10/26 05:49:37 - mmengine - INFO - Epoch(train) [822][45/63] lr: 1.2511e-03 eta: 4:42:09 time: 0.5272 data_time: 0.0043 memory: 16131 loss: 1.0651 loss_prob: 0.5605 loss_thr: 0.4066 loss_db: 0.0981 2022/10/26 05:49:39 - mmengine - INFO - Epoch(train) [822][50/63] lr: 1.2511e-03 eta: 4:42:02 time: 0.5314 data_time: 0.0129 memory: 16131 loss: 1.0395 loss_prob: 0.5542 loss_thr: 0.3906 loss_db: 0.0946 2022/10/26 05:49:42 - mmengine - INFO - Epoch(train) [822][55/63] lr: 1.2511e-03 eta: 4:42:02 time: 0.5658 data_time: 0.0255 memory: 16131 loss: 1.0418 loss_prob: 0.5636 loss_thr: 0.3862 loss_db: 0.0920 2022/10/26 05:49:45 - mmengine - INFO - Epoch(train) [822][60/63] lr: 1.2511e-03 eta: 4:41:54 time: 0.5840 data_time: 0.0167 memory: 16131 loss: 1.0663 loss_prob: 0.5697 loss_thr: 0.4021 loss_db: 0.0945 2022/10/26 05:49:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:49:51 - mmengine - INFO - Epoch(train) [823][5/63] lr: 1.2481e-03 eta: 4:41:54 time: 0.6900 data_time: 0.2040 memory: 16131 loss: 1.0034 loss_prob: 0.5266 loss_thr: 0.3853 loss_db: 0.0915 2022/10/26 05:49:54 - mmengine - INFO - Epoch(train) [823][10/63] lr: 1.2481e-03 eta: 4:41:44 time: 0.7408 data_time: 0.2053 memory: 16131 loss: 1.0428 loss_prob: 0.5517 loss_thr: 0.3956 loss_db: 0.0955 2022/10/26 05:49:56 - mmengine - INFO - Epoch(train) [823][15/63] lr: 1.2481e-03 eta: 4:41:44 time: 0.5302 data_time: 0.0088 memory: 16131 loss: 1.1676 loss_prob: 0.6383 loss_thr: 0.4196 loss_db: 0.1097 2022/10/26 05:49:59 - mmengine - INFO - Epoch(train) [823][20/63] lr: 1.2481e-03 eta: 4:41:36 time: 0.5020 data_time: 0.0142 memory: 16131 loss: 1.1744 loss_prob: 0.6384 loss_thr: 0.4261 loss_db: 0.1100 2022/10/26 05:50:01 - mmengine - INFO - Epoch(train) [823][25/63] lr: 1.2481e-03 eta: 4:41:36 time: 0.5336 data_time: 0.0381 memory: 16131 loss: 1.1865 loss_prob: 0.6400 loss_thr: 0.4369 loss_db: 0.1096 2022/10/26 05:50:05 - mmengine - INFO - Epoch(train) [823][30/63] lr: 1.2481e-03 eta: 4:41:28 time: 0.6174 data_time: 0.0529 memory: 16131 loss: 1.2089 loss_prob: 0.6611 loss_thr: 0.4367 loss_db: 0.1111 2022/10/26 05:50:08 - mmengine - INFO - Epoch(train) [823][35/63] lr: 1.2481e-03 eta: 4:41:28 time: 0.6097 data_time: 0.0272 memory: 16131 loss: 1.1201 loss_prob: 0.6085 loss_thr: 0.4093 loss_db: 0.1023 2022/10/26 05:50:10 - mmengine - INFO - Epoch(train) [823][40/63] lr: 1.2481e-03 eta: 4:41:20 time: 0.5109 data_time: 0.0060 memory: 16131 loss: 1.0412 loss_prob: 0.5592 loss_thr: 0.3836 loss_db: 0.0985 2022/10/26 05:50:13 - mmengine - INFO - Epoch(train) [823][45/63] lr: 1.2481e-03 eta: 4:41:20 time: 0.5025 data_time: 0.0156 memory: 16131 loss: 1.0207 loss_prob: 0.5426 loss_thr: 0.3826 loss_db: 0.0955 2022/10/26 05:50:15 - mmengine - INFO - Epoch(train) [823][50/63] lr: 1.2481e-03 eta: 4:41:12 time: 0.5389 data_time: 0.0282 memory: 16131 loss: 1.0520 loss_prob: 0.5627 loss_thr: 0.3923 loss_db: 0.0970 2022/10/26 05:50:18 - mmengine - INFO - Epoch(train) [823][55/63] lr: 1.2481e-03 eta: 4:41:12 time: 0.5332 data_time: 0.0208 memory: 16131 loss: 1.0210 loss_prob: 0.5377 loss_thr: 0.3892 loss_db: 0.0940 2022/10/26 05:50:20 - mmengine - INFO - Epoch(train) [823][60/63] lr: 1.2481e-03 eta: 4:41:04 time: 0.5023 data_time: 0.0086 memory: 16131 loss: 1.0950 loss_prob: 0.5814 loss_thr: 0.4138 loss_db: 0.0998 2022/10/26 05:50:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:50:26 - mmengine - INFO - Epoch(train) [824][5/63] lr: 1.2451e-03 eta: 4:41:04 time: 0.6946 data_time: 0.2015 memory: 16131 loss: 1.0729 loss_prob: 0.5809 loss_thr: 0.3948 loss_db: 0.0973 2022/10/26 05:50:29 - mmengine - INFO - Epoch(train) [824][10/63] lr: 1.2451e-03 eta: 4:40:54 time: 0.7023 data_time: 0.2013 memory: 16131 loss: 1.0401 loss_prob: 0.5575 loss_thr: 0.3885 loss_db: 0.0941 2022/10/26 05:50:31 - mmengine - INFO - Epoch(train) [824][15/63] lr: 1.2451e-03 eta: 4:40:54 time: 0.5010 data_time: 0.0096 memory: 16131 loss: 1.1084 loss_prob: 0.5994 loss_thr: 0.4037 loss_db: 0.1053 2022/10/26 05:50:34 - mmengine - INFO - Epoch(train) [824][20/63] lr: 1.2451e-03 eta: 4:40:46 time: 0.5089 data_time: 0.0082 memory: 16131 loss: 1.1492 loss_prob: 0.6267 loss_thr: 0.4120 loss_db: 0.1105 2022/10/26 05:50:37 - mmengine - INFO - Epoch(train) [824][25/63] lr: 1.2451e-03 eta: 4:40:46 time: 0.5683 data_time: 0.0303 memory: 16131 loss: 1.1192 loss_prob: 0.6029 loss_thr: 0.4126 loss_db: 0.1038 2022/10/26 05:50:40 - mmengine - INFO - Epoch(train) [824][30/63] lr: 1.2451e-03 eta: 4:40:38 time: 0.5726 data_time: 0.0408 memory: 16131 loss: 1.1137 loss_prob: 0.5910 loss_thr: 0.4228 loss_db: 0.0999 2022/10/26 05:50:42 - mmengine - INFO - Epoch(train) [824][35/63] lr: 1.2451e-03 eta: 4:40:38 time: 0.5121 data_time: 0.0165 memory: 16131 loss: 1.1556 loss_prob: 0.6087 loss_thr: 0.4430 loss_db: 0.1039 2022/10/26 05:50:45 - mmengine - INFO - Epoch(train) [824][40/63] lr: 1.2451e-03 eta: 4:40:30 time: 0.5012 data_time: 0.0067 memory: 16131 loss: 1.1028 loss_prob: 0.5923 loss_thr: 0.4116 loss_db: 0.0989 2022/10/26 05:50:47 - mmengine - INFO - Epoch(train) [824][45/63] lr: 1.2451e-03 eta: 4:40:30 time: 0.4978 data_time: 0.0069 memory: 16131 loss: 1.0675 loss_prob: 0.5728 loss_thr: 0.4003 loss_db: 0.0944 2022/10/26 05:50:50 - mmengine - INFO - Epoch(train) [824][50/63] lr: 1.2451e-03 eta: 4:40:22 time: 0.5365 data_time: 0.0234 memory: 16131 loss: 1.1451 loss_prob: 0.6034 loss_thr: 0.4373 loss_db: 0.1044 2022/10/26 05:50:53 - mmengine - INFO - Epoch(train) [824][55/63] lr: 1.2451e-03 eta: 4:40:22 time: 0.5547 data_time: 0.0240 memory: 16131 loss: 1.1390 loss_prob: 0.5972 loss_thr: 0.4372 loss_db: 0.1045 2022/10/26 05:50:55 - mmengine - INFO - Epoch(train) [824][60/63] lr: 1.2451e-03 eta: 4:40:14 time: 0.5192 data_time: 0.0081 memory: 16131 loss: 1.1017 loss_prob: 0.5797 loss_thr: 0.4205 loss_db: 0.1015 2022/10/26 05:50:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:51:01 - mmengine - INFO - Epoch(train) [825][5/63] lr: 1.2421e-03 eta: 4:40:14 time: 0.6936 data_time: 0.2078 memory: 16131 loss: 1.2181 loss_prob: 0.6553 loss_thr: 0.4483 loss_db: 0.1145 2022/10/26 05:51:04 - mmengine - INFO - Epoch(train) [825][10/63] lr: 1.2421e-03 eta: 4:40:04 time: 0.7620 data_time: 0.2068 memory: 16131 loss: 1.1212 loss_prob: 0.5940 loss_thr: 0.4211 loss_db: 0.1061 2022/10/26 05:51:07 - mmengine - INFO - Epoch(train) [825][15/63] lr: 1.2421e-03 eta: 4:40:04 time: 0.5362 data_time: 0.0125 memory: 16131 loss: 1.1116 loss_prob: 0.6003 loss_thr: 0.4061 loss_db: 0.1052 2022/10/26 05:51:09 - mmengine - INFO - Epoch(train) [825][20/63] lr: 1.2421e-03 eta: 4:39:56 time: 0.5301 data_time: 0.0122 memory: 16131 loss: 1.1079 loss_prob: 0.5983 loss_thr: 0.4074 loss_db: 0.1022 2022/10/26 05:51:12 - mmengine - INFO - Epoch(train) [825][25/63] lr: 1.2421e-03 eta: 4:39:56 time: 0.5523 data_time: 0.0156 memory: 16131 loss: 1.1209 loss_prob: 0.5918 loss_thr: 0.4281 loss_db: 0.1010 2022/10/26 05:51:15 - mmengine - INFO - Epoch(train) [825][30/63] lr: 1.2421e-03 eta: 4:39:49 time: 0.5601 data_time: 0.0339 memory: 16131 loss: 1.1238 loss_prob: 0.6051 loss_thr: 0.4181 loss_db: 0.1005 2022/10/26 05:51:17 - mmengine - INFO - Epoch(train) [825][35/63] lr: 1.2421e-03 eta: 4:39:49 time: 0.5404 data_time: 0.0305 memory: 16131 loss: 1.0213 loss_prob: 0.5530 loss_thr: 0.3765 loss_db: 0.0919 2022/10/26 05:51:20 - mmengine - INFO - Epoch(train) [825][40/63] lr: 1.2421e-03 eta: 4:39:41 time: 0.5266 data_time: 0.0150 memory: 16131 loss: 0.9862 loss_prob: 0.5207 loss_thr: 0.3749 loss_db: 0.0906 2022/10/26 05:51:23 - mmengine - INFO - Epoch(train) [825][45/63] lr: 1.2421e-03 eta: 4:39:41 time: 0.5108 data_time: 0.0104 memory: 16131 loss: 1.0100 loss_prob: 0.5287 loss_thr: 0.3895 loss_db: 0.0919 2022/10/26 05:51:25 - mmengine - INFO - Epoch(train) [825][50/63] lr: 1.2421e-03 eta: 4:39:33 time: 0.5070 data_time: 0.0141 memory: 16131 loss: 1.0642 loss_prob: 0.5551 loss_thr: 0.4136 loss_db: 0.0955 2022/10/26 05:51:28 - mmengine - INFO - Epoch(train) [825][55/63] lr: 1.2421e-03 eta: 4:39:33 time: 0.5338 data_time: 0.0168 memory: 16131 loss: 1.0683 loss_prob: 0.5630 loss_thr: 0.4077 loss_db: 0.0976 2022/10/26 05:51:30 - mmengine - INFO - Epoch(train) [825][60/63] lr: 1.2421e-03 eta: 4:39:25 time: 0.5191 data_time: 0.0116 memory: 16131 loss: 1.0220 loss_prob: 0.5362 loss_thr: 0.3950 loss_db: 0.0908 2022/10/26 05:51:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:51:36 - mmengine - INFO - Epoch(train) [826][5/63] lr: 1.2391e-03 eta: 4:39:25 time: 0.6889 data_time: 0.2022 memory: 16131 loss: 1.0500 loss_prob: 0.5514 loss_thr: 0.4034 loss_db: 0.0951 2022/10/26 05:51:39 - mmengine - INFO - Epoch(train) [826][10/63] lr: 1.2391e-03 eta: 4:39:15 time: 0.7220 data_time: 0.2055 memory: 16131 loss: 0.9671 loss_prob: 0.5040 loss_thr: 0.3736 loss_db: 0.0895 2022/10/26 05:51:41 - mmengine - INFO - Epoch(train) [826][15/63] lr: 1.2391e-03 eta: 4:39:15 time: 0.5117 data_time: 0.0151 memory: 16131 loss: 1.0269 loss_prob: 0.5430 loss_thr: 0.3873 loss_db: 0.0967 2022/10/26 05:51:44 - mmengine - INFO - Epoch(train) [826][20/63] lr: 1.2391e-03 eta: 4:39:07 time: 0.5337 data_time: 0.0107 memory: 16131 loss: 1.1377 loss_prob: 0.6092 loss_thr: 0.4224 loss_db: 0.1061 2022/10/26 05:51:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:51:47 - mmengine - INFO - Epoch(train) [826][25/63] lr: 1.2391e-03 eta: 4:39:07 time: 0.5830 data_time: 0.0412 memory: 16131 loss: 1.1751 loss_prob: 0.6322 loss_thr: 0.4349 loss_db: 0.1080 2022/10/26 05:51:50 - mmengine - INFO - Epoch(train) [826][30/63] lr: 1.2391e-03 eta: 4:38:59 time: 0.5612 data_time: 0.0406 memory: 16131 loss: 1.0784 loss_prob: 0.5754 loss_thr: 0.4040 loss_db: 0.0990 2022/10/26 05:51:53 - mmengine - INFO - Epoch(train) [826][35/63] lr: 1.2391e-03 eta: 4:38:59 time: 0.5537 data_time: 0.0074 memory: 16131 loss: 1.0539 loss_prob: 0.5618 loss_thr: 0.3951 loss_db: 0.0971 2022/10/26 05:51:56 - mmengine - INFO - Epoch(train) [826][40/63] lr: 1.2391e-03 eta: 4:38:51 time: 0.5882 data_time: 0.0061 memory: 16131 loss: 1.0940 loss_prob: 0.5795 loss_thr: 0.4142 loss_db: 0.1002 2022/10/26 05:51:58 - mmengine - INFO - Epoch(train) [826][45/63] lr: 1.2391e-03 eta: 4:38:51 time: 0.5351 data_time: 0.0055 memory: 16131 loss: 1.1314 loss_prob: 0.5989 loss_thr: 0.4296 loss_db: 0.1028 2022/10/26 05:52:01 - mmengine - INFO - Epoch(train) [826][50/63] lr: 1.2391e-03 eta: 4:38:43 time: 0.5068 data_time: 0.0256 memory: 16131 loss: 1.0977 loss_prob: 0.5820 loss_thr: 0.4166 loss_db: 0.0991 2022/10/26 05:52:03 - mmengine - INFO - Epoch(train) [826][55/63] lr: 1.2391e-03 eta: 4:38:43 time: 0.5161 data_time: 0.0259 memory: 16131 loss: 0.9892 loss_prob: 0.5132 loss_thr: 0.3870 loss_db: 0.0890 2022/10/26 05:52:06 - mmengine - INFO - Epoch(train) [826][60/63] lr: 1.2391e-03 eta: 4:38:35 time: 0.4914 data_time: 0.0060 memory: 16131 loss: 1.0503 loss_prob: 0.5498 loss_thr: 0.4043 loss_db: 0.0962 2022/10/26 05:52:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:52:11 - mmengine - INFO - Epoch(train) [827][5/63] lr: 1.2361e-03 eta: 4:38:35 time: 0.6679 data_time: 0.1598 memory: 16131 loss: 1.1561 loss_prob: 0.6224 loss_thr: 0.4286 loss_db: 0.1050 2022/10/26 05:52:14 - mmengine - INFO - Epoch(train) [827][10/63] lr: 1.2361e-03 eta: 4:38:25 time: 0.6941 data_time: 0.1606 memory: 16131 loss: 1.0782 loss_prob: 0.5712 loss_thr: 0.4069 loss_db: 0.1001 2022/10/26 05:52:16 - mmengine - INFO - Epoch(train) [827][15/63] lr: 1.2361e-03 eta: 4:38:25 time: 0.4987 data_time: 0.0103 memory: 16131 loss: 1.0921 loss_prob: 0.5809 loss_thr: 0.4094 loss_db: 0.1018 2022/10/26 05:52:19 - mmengine - INFO - Epoch(train) [827][20/63] lr: 1.2361e-03 eta: 4:38:17 time: 0.5068 data_time: 0.0080 memory: 16131 loss: 1.1003 loss_prob: 0.5850 loss_thr: 0.4147 loss_db: 0.1005 2022/10/26 05:52:21 - mmengine - INFO - Epoch(train) [827][25/63] lr: 1.2361e-03 eta: 4:38:17 time: 0.4975 data_time: 0.0067 memory: 16131 loss: 1.1112 loss_prob: 0.5925 loss_thr: 0.4173 loss_db: 0.1014 2022/10/26 05:52:24 - mmengine - INFO - Epoch(train) [827][30/63] lr: 1.2361e-03 eta: 4:38:09 time: 0.5065 data_time: 0.0333 memory: 16131 loss: 1.1346 loss_prob: 0.6060 loss_thr: 0.4242 loss_db: 0.1044 2022/10/26 05:52:27 - mmengine - INFO - Epoch(train) [827][35/63] lr: 1.2361e-03 eta: 4:38:09 time: 0.5342 data_time: 0.0342 memory: 16131 loss: 1.0946 loss_prob: 0.5776 loss_thr: 0.4176 loss_db: 0.0994 2022/10/26 05:52:30 - mmengine - INFO - Epoch(train) [827][40/63] lr: 1.2361e-03 eta: 4:38:01 time: 0.5522 data_time: 0.0083 memory: 16131 loss: 1.0904 loss_prob: 0.5726 loss_thr: 0.4196 loss_db: 0.0982 2022/10/26 05:52:32 - mmengine - INFO - Epoch(train) [827][45/63] lr: 1.2361e-03 eta: 4:38:01 time: 0.5384 data_time: 0.0076 memory: 16131 loss: 1.0519 loss_prob: 0.5561 loss_thr: 0.4007 loss_db: 0.0951 2022/10/26 05:52:35 - mmengine - INFO - Epoch(train) [827][50/63] lr: 1.2361e-03 eta: 4:37:53 time: 0.5066 data_time: 0.0164 memory: 16131 loss: 1.1162 loss_prob: 0.6163 loss_thr: 0.3981 loss_db: 0.1018 2022/10/26 05:52:37 - mmengine - INFO - Epoch(train) [827][55/63] lr: 1.2361e-03 eta: 4:37:53 time: 0.5028 data_time: 0.0217 memory: 16131 loss: 1.1252 loss_prob: 0.6244 loss_thr: 0.3969 loss_db: 0.1039 2022/10/26 05:52:40 - mmengine - INFO - Epoch(train) [827][60/63] lr: 1.2361e-03 eta: 4:37:45 time: 0.5028 data_time: 0.0168 memory: 16131 loss: 1.1217 loss_prob: 0.6055 loss_thr: 0.4084 loss_db: 0.1078 2022/10/26 05:52:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:52:45 - mmengine - INFO - Epoch(train) [828][5/63] lr: 1.2332e-03 eta: 4:37:45 time: 0.6738 data_time: 0.1962 memory: 16131 loss: 1.1423 loss_prob: 0.6113 loss_thr: 0.4257 loss_db: 0.1053 2022/10/26 05:52:48 - mmengine - INFO - Epoch(train) [828][10/63] lr: 1.2332e-03 eta: 4:37:35 time: 0.7098 data_time: 0.1943 memory: 16131 loss: 1.0839 loss_prob: 0.5823 loss_thr: 0.4016 loss_db: 0.0999 2022/10/26 05:52:51 - mmengine - INFO - Epoch(train) [828][15/63] lr: 1.2332e-03 eta: 4:37:35 time: 0.5526 data_time: 0.0059 memory: 16131 loss: 1.0355 loss_prob: 0.5551 loss_thr: 0.3854 loss_db: 0.0950 2022/10/26 05:52:53 - mmengine - INFO - Epoch(train) [828][20/63] lr: 1.2332e-03 eta: 4:37:27 time: 0.5296 data_time: 0.0052 memory: 16131 loss: 1.0798 loss_prob: 0.5734 loss_thr: 0.4071 loss_db: 0.0994 2022/10/26 05:52:56 - mmengine - INFO - Epoch(train) [828][25/63] lr: 1.2332e-03 eta: 4:37:27 time: 0.5200 data_time: 0.0299 memory: 16131 loss: 1.2654 loss_prob: 0.6963 loss_thr: 0.4553 loss_db: 0.1138 2022/10/26 05:52:59 - mmengine - INFO - Epoch(train) [828][30/63] lr: 1.2332e-03 eta: 4:37:19 time: 0.5207 data_time: 0.0304 memory: 16131 loss: 1.2149 loss_prob: 0.6732 loss_thr: 0.4307 loss_db: 0.1111 2022/10/26 05:53:01 - mmengine - INFO - Epoch(train) [828][35/63] lr: 1.2332e-03 eta: 4:37:19 time: 0.5044 data_time: 0.0128 memory: 16131 loss: 1.0726 loss_prob: 0.5761 loss_thr: 0.3995 loss_db: 0.0970 2022/10/26 05:53:04 - mmengine - INFO - Epoch(train) [828][40/63] lr: 1.2332e-03 eta: 4:37:11 time: 0.5064 data_time: 0.0134 memory: 16131 loss: 1.0494 loss_prob: 0.5625 loss_thr: 0.3937 loss_db: 0.0931 2022/10/26 05:53:07 - mmengine - INFO - Epoch(train) [828][45/63] lr: 1.2332e-03 eta: 4:37:11 time: 0.5372 data_time: 0.0081 memory: 16131 loss: 1.0317 loss_prob: 0.5425 loss_thr: 0.3969 loss_db: 0.0923 2022/10/26 05:53:10 - mmengine - INFO - Epoch(train) [828][50/63] lr: 1.2332e-03 eta: 4:37:04 time: 0.5945 data_time: 0.0366 memory: 16131 loss: 1.0706 loss_prob: 0.5688 loss_thr: 0.4048 loss_db: 0.0970 2022/10/26 05:53:13 - mmengine - INFO - Epoch(train) [828][55/63] lr: 1.2332e-03 eta: 4:37:04 time: 0.5991 data_time: 0.0358 memory: 16131 loss: 1.0687 loss_prob: 0.5685 loss_thr: 0.4017 loss_db: 0.0984 2022/10/26 05:53:15 - mmengine - INFO - Epoch(train) [828][60/63] lr: 1.2332e-03 eta: 4:36:56 time: 0.5503 data_time: 0.0069 memory: 16131 loss: 1.0973 loss_prob: 0.5845 loss_thr: 0.4144 loss_db: 0.0984 2022/10/26 05:53:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:53:21 - mmengine - INFO - Epoch(train) [829][5/63] lr: 1.2302e-03 eta: 4:36:56 time: 0.6583 data_time: 0.1825 memory: 16131 loss: 0.9956 loss_prob: 0.5295 loss_thr: 0.3733 loss_db: 0.0928 2022/10/26 05:53:24 - mmengine - INFO - Epoch(train) [829][10/63] lr: 1.2302e-03 eta: 4:36:46 time: 0.7871 data_time: 0.1821 memory: 16131 loss: 1.0684 loss_prob: 0.5772 loss_thr: 0.3913 loss_db: 0.0999 2022/10/26 05:53:27 - mmengine - INFO - Epoch(train) [829][15/63] lr: 1.2302e-03 eta: 4:36:46 time: 0.6096 data_time: 0.0094 memory: 16131 loss: 1.0628 loss_prob: 0.5768 loss_thr: 0.3876 loss_db: 0.0984 2022/10/26 05:53:29 - mmengine - INFO - Epoch(train) [829][20/63] lr: 1.2302e-03 eta: 4:36:38 time: 0.5115 data_time: 0.0087 memory: 16131 loss: 1.1028 loss_prob: 0.5996 loss_thr: 0.4029 loss_db: 0.1002 2022/10/26 05:53:32 - mmengine - INFO - Epoch(train) [829][25/63] lr: 1.2302e-03 eta: 4:36:38 time: 0.5409 data_time: 0.0167 memory: 16131 loss: 1.0658 loss_prob: 0.5700 loss_thr: 0.3994 loss_db: 0.0964 2022/10/26 05:53:35 - mmengine - INFO - Epoch(train) [829][30/63] lr: 1.2302e-03 eta: 4:36:30 time: 0.6023 data_time: 0.0330 memory: 16131 loss: 1.0561 loss_prob: 0.5611 loss_thr: 0.3960 loss_db: 0.0991 2022/10/26 05:53:38 - mmengine - INFO - Epoch(train) [829][35/63] lr: 1.2302e-03 eta: 4:36:30 time: 0.6051 data_time: 0.0238 memory: 16131 loss: 1.0826 loss_prob: 0.5754 loss_thr: 0.4071 loss_db: 0.1001 2022/10/26 05:53:41 - mmengine - INFO - Epoch(train) [829][40/63] lr: 1.2302e-03 eta: 4:36:22 time: 0.5322 data_time: 0.0062 memory: 16131 loss: 1.1111 loss_prob: 0.5969 loss_thr: 0.4118 loss_db: 0.1024 2022/10/26 05:53:43 - mmengine - INFO - Epoch(train) [829][45/63] lr: 1.2302e-03 eta: 4:36:22 time: 0.5022 data_time: 0.0074 memory: 16131 loss: 1.2190 loss_prob: 0.6636 loss_thr: 0.4410 loss_db: 0.1144 2022/10/26 05:53:46 - mmengine - INFO - Epoch(train) [829][50/63] lr: 1.2302e-03 eta: 4:36:15 time: 0.5505 data_time: 0.0195 memory: 16131 loss: 1.3352 loss_prob: 0.7488 loss_thr: 0.4640 loss_db: 0.1223 2022/10/26 05:53:49 - mmengine - INFO - Epoch(train) [829][55/63] lr: 1.2302e-03 eta: 4:36:15 time: 0.5394 data_time: 0.0248 memory: 16131 loss: 1.1678 loss_prob: 0.6493 loss_thr: 0.4131 loss_db: 0.1054 2022/10/26 05:53:51 - mmengine - INFO - Epoch(train) [829][60/63] lr: 1.2302e-03 eta: 4:36:07 time: 0.5022 data_time: 0.0149 memory: 16131 loss: 1.0159 loss_prob: 0.5376 loss_thr: 0.3840 loss_db: 0.0942 2022/10/26 05:53:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:53:57 - mmengine - INFO - Epoch(train) [830][5/63] lr: 1.2272e-03 eta: 4:36:07 time: 0.7016 data_time: 0.2151 memory: 16131 loss: 1.0326 loss_prob: 0.5456 loss_thr: 0.3931 loss_db: 0.0939 2022/10/26 05:54:00 - mmengine - INFO - Epoch(train) [830][10/63] lr: 1.2272e-03 eta: 4:35:57 time: 0.7230 data_time: 0.2192 memory: 16131 loss: 1.0721 loss_prob: 0.5740 loss_thr: 0.4008 loss_db: 0.0973 2022/10/26 05:54:02 - mmengine - INFO - Epoch(train) [830][15/63] lr: 1.2272e-03 eta: 4:35:57 time: 0.5237 data_time: 0.0105 memory: 16131 loss: 1.1055 loss_prob: 0.5892 loss_thr: 0.4161 loss_db: 0.1003 2022/10/26 05:54:05 - mmengine - INFO - Epoch(train) [830][20/63] lr: 1.2272e-03 eta: 4:35:49 time: 0.5355 data_time: 0.0062 memory: 16131 loss: 1.0209 loss_prob: 0.5352 loss_thr: 0.3924 loss_db: 0.0933 2022/10/26 05:54:08 - mmengine - INFO - Epoch(train) [830][25/63] lr: 1.2272e-03 eta: 4:35:49 time: 0.5323 data_time: 0.0326 memory: 16131 loss: 1.4134 loss_prob: 0.8256 loss_thr: 0.4529 loss_db: 0.1350 2022/10/26 05:54:10 - mmengine - INFO - Epoch(train) [830][30/63] lr: 1.2272e-03 eta: 4:35:41 time: 0.5183 data_time: 0.0321 memory: 16131 loss: 1.5153 loss_prob: 0.9033 loss_thr: 0.4645 loss_db: 0.1475 2022/10/26 05:54:13 - mmengine - INFO - Epoch(train) [830][35/63] lr: 1.2272e-03 eta: 4:35:41 time: 0.5030 data_time: 0.0088 memory: 16131 loss: 1.3175 loss_prob: 0.7647 loss_thr: 0.4121 loss_db: 0.1406 2022/10/26 05:54:15 - mmengine - INFO - Epoch(train) [830][40/63] lr: 1.2272e-03 eta: 4:35:33 time: 0.4892 data_time: 0.0095 memory: 16131 loss: 1.3293 loss_prob: 0.7596 loss_thr: 0.4318 loss_db: 0.1379 2022/10/26 05:54:18 - mmengine - INFO - Epoch(train) [830][45/63] lr: 1.2272e-03 eta: 4:35:33 time: 0.4879 data_time: 0.0080 memory: 16131 loss: 1.2770 loss_prob: 0.7192 loss_thr: 0.4406 loss_db: 0.1172 2022/10/26 05:54:21 - mmengine - INFO - Epoch(train) [830][50/63] lr: 1.2272e-03 eta: 4:35:25 time: 0.6052 data_time: 0.0253 memory: 16131 loss: 1.3443 loss_prob: 0.7598 loss_thr: 0.4610 loss_db: 0.1234 2022/10/26 05:54:24 - mmengine - INFO - Epoch(train) [830][55/63] lr: 1.2272e-03 eta: 4:35:25 time: 0.6298 data_time: 0.0227 memory: 16131 loss: 1.3144 loss_prob: 0.7336 loss_thr: 0.4643 loss_db: 0.1165 2022/10/26 05:54:26 - mmengine - INFO - Epoch(train) [830][60/63] lr: 1.2272e-03 eta: 4:35:17 time: 0.5230 data_time: 0.0056 memory: 16131 loss: 1.2068 loss_prob: 0.6647 loss_thr: 0.4364 loss_db: 0.1058 2022/10/26 05:54:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:54:33 - mmengine - INFO - Epoch(train) [831][5/63] lr: 1.2242e-03 eta: 4:35:17 time: 0.7374 data_time: 0.2020 memory: 16131 loss: 1.3457 loss_prob: 0.7822 loss_thr: 0.4418 loss_db: 0.1217 2022/10/26 05:54:36 - mmengine - INFO - Epoch(train) [831][10/63] lr: 1.2242e-03 eta: 4:35:07 time: 0.7919 data_time: 0.2022 memory: 16131 loss: 1.2258 loss_prob: 0.7069 loss_thr: 0.4094 loss_db: 0.1095 2022/10/26 05:54:38 - mmengine - INFO - Epoch(train) [831][15/63] lr: 1.2242e-03 eta: 4:35:07 time: 0.5448 data_time: 0.0062 memory: 16131 loss: 1.1360 loss_prob: 0.6121 loss_thr: 0.4198 loss_db: 0.1040 2022/10/26 05:54:41 - mmengine - INFO - Epoch(train) [831][20/63] lr: 1.2242e-03 eta: 4:34:59 time: 0.5037 data_time: 0.0071 memory: 16131 loss: 1.1699 loss_prob: 0.6284 loss_thr: 0.4350 loss_db: 0.1064 2022/10/26 05:54:43 - mmengine - INFO - Epoch(train) [831][25/63] lr: 1.2242e-03 eta: 4:34:59 time: 0.5161 data_time: 0.0400 memory: 16131 loss: 1.1344 loss_prob: 0.6078 loss_thr: 0.4240 loss_db: 0.1025 2022/10/26 05:54:46 - mmengine - INFO - Epoch(train) [831][30/63] lr: 1.2242e-03 eta: 4:34:52 time: 0.5349 data_time: 0.0410 memory: 16131 loss: 1.3281 loss_prob: 0.7271 loss_thr: 0.4810 loss_db: 0.1200 2022/10/26 05:54:49 - mmengine - INFO - Epoch(train) [831][35/63] lr: 1.2242e-03 eta: 4:34:52 time: 0.5077 data_time: 0.0082 memory: 16131 loss: 1.3218 loss_prob: 0.7234 loss_thr: 0.4773 loss_db: 0.1212 2022/10/26 05:54:51 - mmengine - INFO - Epoch(train) [831][40/63] lr: 1.2242e-03 eta: 4:34:44 time: 0.5070 data_time: 0.0063 memory: 16131 loss: 1.1723 loss_prob: 0.6354 loss_thr: 0.4294 loss_db: 0.1075 2022/10/26 05:54:54 - mmengine - INFO - Epoch(train) [831][45/63] lr: 1.2242e-03 eta: 4:34:44 time: 0.5033 data_time: 0.0058 memory: 16131 loss: 1.1516 loss_prob: 0.6200 loss_thr: 0.4264 loss_db: 0.1052 2022/10/26 05:54:56 - mmengine - INFO - Epoch(train) [831][50/63] lr: 1.2242e-03 eta: 4:34:36 time: 0.5030 data_time: 0.0245 memory: 16131 loss: 1.1020 loss_prob: 0.5891 loss_thr: 0.4108 loss_db: 0.1021 2022/10/26 05:54:59 - mmengine - INFO - Epoch(train) [831][55/63] lr: 1.2242e-03 eta: 4:34:36 time: 0.5380 data_time: 0.0242 memory: 16131 loss: 1.1042 loss_prob: 0.5882 loss_thr: 0.4143 loss_db: 0.1017 2022/10/26 05:55:01 - mmengine - INFO - Epoch(train) [831][60/63] lr: 1.2242e-03 eta: 4:34:28 time: 0.5265 data_time: 0.0056 memory: 16131 loss: 1.1218 loss_prob: 0.5937 loss_thr: 0.4246 loss_db: 0.1034 2022/10/26 05:55:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:55:08 - mmengine - INFO - Epoch(train) [832][5/63] lr: 1.2212e-03 eta: 4:34:28 time: 0.7482 data_time: 0.2214 memory: 16131 loss: 1.1132 loss_prob: 0.5995 loss_thr: 0.4085 loss_db: 0.1052 2022/10/26 05:55:10 - mmengine - INFO - Epoch(train) [832][10/63] lr: 1.2212e-03 eta: 4:34:18 time: 0.7587 data_time: 0.2254 memory: 16131 loss: 1.0744 loss_prob: 0.5719 loss_thr: 0.4014 loss_db: 0.1011 2022/10/26 05:55:13 - mmengine - INFO - Epoch(train) [832][15/63] lr: 1.2212e-03 eta: 4:34:18 time: 0.5282 data_time: 0.0138 memory: 16131 loss: 1.0519 loss_prob: 0.5545 loss_thr: 0.4027 loss_db: 0.0947 2022/10/26 05:55:16 - mmengine - INFO - Epoch(train) [832][20/63] lr: 1.2212e-03 eta: 4:34:10 time: 0.5425 data_time: 0.0124 memory: 16131 loss: 1.0797 loss_prob: 0.5745 loss_thr: 0.4062 loss_db: 0.0990 2022/10/26 05:55:18 - mmengine - INFO - Epoch(train) [832][25/63] lr: 1.2212e-03 eta: 4:34:10 time: 0.5160 data_time: 0.0299 memory: 16131 loss: 1.0531 loss_prob: 0.5580 loss_thr: 0.3969 loss_db: 0.0982 2022/10/26 05:55:21 - mmengine - INFO - Epoch(train) [832][30/63] lr: 1.2212e-03 eta: 4:34:02 time: 0.5045 data_time: 0.0279 memory: 16131 loss: 1.0563 loss_prob: 0.5626 loss_thr: 0.3948 loss_db: 0.0989 2022/10/26 05:55:23 - mmengine - INFO - Epoch(train) [832][35/63] lr: 1.2212e-03 eta: 4:34:02 time: 0.5112 data_time: 0.0092 memory: 16131 loss: 1.1562 loss_prob: 0.6206 loss_thr: 0.4301 loss_db: 0.1054 2022/10/26 05:55:26 - mmengine - INFO - Epoch(train) [832][40/63] lr: 1.2212e-03 eta: 4:33:54 time: 0.5193 data_time: 0.0115 memory: 16131 loss: 1.1824 loss_prob: 0.6326 loss_thr: 0.4426 loss_db: 0.1072 2022/10/26 05:55:29 - mmengine - INFO - Epoch(train) [832][45/63] lr: 1.2212e-03 eta: 4:33:54 time: 0.5071 data_time: 0.0103 memory: 16131 loss: 1.0996 loss_prob: 0.5882 loss_thr: 0.4107 loss_db: 0.1007 2022/10/26 05:55:31 - mmengine - INFO - Epoch(train) [832][50/63] lr: 1.2212e-03 eta: 4:33:46 time: 0.5077 data_time: 0.0173 memory: 16131 loss: 1.1559 loss_prob: 0.6318 loss_thr: 0.4191 loss_db: 0.1051 2022/10/26 05:55:34 - mmengine - INFO - Epoch(train) [832][55/63] lr: 1.2212e-03 eta: 4:33:46 time: 0.5504 data_time: 0.0183 memory: 16131 loss: 1.1524 loss_prob: 0.6191 loss_thr: 0.4293 loss_db: 0.1039 2022/10/26 05:55:37 - mmengine - INFO - Epoch(train) [832][60/63] lr: 1.2212e-03 eta: 4:33:38 time: 0.5556 data_time: 0.0123 memory: 16131 loss: 1.1319 loss_prob: 0.5934 loss_thr: 0.4357 loss_db: 0.1029 2022/10/26 05:55:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:55:43 - mmengine - INFO - Epoch(train) [833][5/63] lr: 1.2182e-03 eta: 4:33:38 time: 0.7166 data_time: 0.2188 memory: 16131 loss: 1.0780 loss_prob: 0.5679 loss_thr: 0.4102 loss_db: 0.0999 2022/10/26 05:55:45 - mmengine - INFO - Epoch(train) [833][10/63] lr: 1.2182e-03 eta: 4:33:28 time: 0.7292 data_time: 0.2166 memory: 16131 loss: 1.0438 loss_prob: 0.5647 loss_thr: 0.3833 loss_db: 0.0958 2022/10/26 05:55:48 - mmengine - INFO - Epoch(train) [833][15/63] lr: 1.2182e-03 eta: 4:33:28 time: 0.5439 data_time: 0.0064 memory: 16131 loss: 1.1241 loss_prob: 0.6130 loss_thr: 0.4080 loss_db: 0.1032 2022/10/26 05:55:51 - mmengine - INFO - Epoch(train) [833][20/63] lr: 1.2182e-03 eta: 4:33:21 time: 0.5525 data_time: 0.0082 memory: 16131 loss: 1.1444 loss_prob: 0.6166 loss_thr: 0.4206 loss_db: 0.1073 2022/10/26 05:55:54 - mmengine - INFO - Epoch(train) [833][25/63] lr: 1.2182e-03 eta: 4:33:21 time: 0.5378 data_time: 0.0155 memory: 16131 loss: 1.0424 loss_prob: 0.5450 loss_thr: 0.4021 loss_db: 0.0953 2022/10/26 05:55:56 - mmengine - INFO - Epoch(train) [833][30/63] lr: 1.2182e-03 eta: 4:33:13 time: 0.5233 data_time: 0.0350 memory: 16131 loss: 1.0214 loss_prob: 0.5343 loss_thr: 0.3950 loss_db: 0.0922 2022/10/26 05:55:59 - mmengine - INFO - Epoch(train) [833][35/63] lr: 1.2182e-03 eta: 4:33:13 time: 0.5104 data_time: 0.0270 memory: 16131 loss: 1.0635 loss_prob: 0.5641 loss_thr: 0.4014 loss_db: 0.0980 2022/10/26 05:56:01 - mmengine - INFO - Epoch(train) [833][40/63] lr: 1.2182e-03 eta: 4:33:05 time: 0.5023 data_time: 0.0046 memory: 16131 loss: 1.0236 loss_prob: 0.5383 loss_thr: 0.3918 loss_db: 0.0935 2022/10/26 05:56:04 - mmengine - INFO - Epoch(train) [833][45/63] lr: 1.2182e-03 eta: 4:33:05 time: 0.4952 data_time: 0.0052 memory: 16131 loss: 1.0768 loss_prob: 0.5725 loss_thr: 0.4055 loss_db: 0.0987 2022/10/26 05:56:06 - mmengine - INFO - Epoch(train) [833][50/63] lr: 1.2182e-03 eta: 4:32:57 time: 0.5227 data_time: 0.0212 memory: 16131 loss: 1.1615 loss_prob: 0.6342 loss_thr: 0.4189 loss_db: 0.1084 2022/10/26 05:56:09 - mmengine - INFO - Epoch(train) [833][55/63] lr: 1.2182e-03 eta: 4:32:57 time: 0.5426 data_time: 0.0267 memory: 16131 loss: 1.0411 loss_prob: 0.5594 loss_thr: 0.3869 loss_db: 0.0948 2022/10/26 05:56:12 - mmengine - INFO - Epoch(train) [833][60/63] lr: 1.2182e-03 eta: 4:32:49 time: 0.5154 data_time: 0.0108 memory: 16131 loss: 1.0299 loss_prob: 0.5418 loss_thr: 0.3968 loss_db: 0.0913 2022/10/26 05:56:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:56:18 - mmengine - INFO - Epoch(train) [834][5/63] lr: 1.2153e-03 eta: 4:32:49 time: 0.7402 data_time: 0.2127 memory: 16131 loss: 1.0525 loss_prob: 0.5546 loss_thr: 0.4020 loss_db: 0.0959 2022/10/26 05:56:21 - mmengine - INFO - Epoch(train) [834][10/63] lr: 1.2153e-03 eta: 4:32:39 time: 0.7860 data_time: 0.2114 memory: 16131 loss: 1.1170 loss_prob: 0.5926 loss_thr: 0.4209 loss_db: 0.1034 2022/10/26 05:56:23 - mmengine - INFO - Epoch(train) [834][15/63] lr: 1.2153e-03 eta: 4:32:39 time: 0.5291 data_time: 0.0091 memory: 16131 loss: 1.0756 loss_prob: 0.5673 loss_thr: 0.4113 loss_db: 0.0970 2022/10/26 05:56:26 - mmengine - INFO - Epoch(train) [834][20/63] lr: 1.2153e-03 eta: 4:32:31 time: 0.5221 data_time: 0.0072 memory: 16131 loss: 0.9517 loss_prob: 0.4972 loss_thr: 0.3696 loss_db: 0.0849 2022/10/26 05:56:29 - mmengine - INFO - Epoch(train) [834][25/63] lr: 1.2153e-03 eta: 4:32:31 time: 0.5379 data_time: 0.0300 memory: 16131 loss: 1.0362 loss_prob: 0.5445 loss_thr: 0.3971 loss_db: 0.0946 2022/10/26 05:56:31 - mmengine - INFO - Epoch(train) [834][30/63] lr: 1.2153e-03 eta: 4:32:23 time: 0.5202 data_time: 0.0291 memory: 16131 loss: 1.1138 loss_prob: 0.5917 loss_thr: 0.4203 loss_db: 0.1018 2022/10/26 05:56:34 - mmengine - INFO - Epoch(train) [834][35/63] lr: 1.2153e-03 eta: 4:32:23 time: 0.5636 data_time: 0.0043 memory: 16131 loss: 1.0529 loss_prob: 0.5579 loss_thr: 0.3999 loss_db: 0.0951 2022/10/26 05:56:37 - mmengine - INFO - Epoch(train) [834][40/63] lr: 1.2153e-03 eta: 4:32:15 time: 0.5502 data_time: 0.0065 memory: 16131 loss: 1.0373 loss_prob: 0.5494 loss_thr: 0.3935 loss_db: 0.0943 2022/10/26 05:56:39 - mmengine - INFO - Epoch(train) [834][45/63] lr: 1.2153e-03 eta: 4:32:15 time: 0.4944 data_time: 0.0091 memory: 16131 loss: 1.0465 loss_prob: 0.5618 loss_thr: 0.3860 loss_db: 0.0986 2022/10/26 05:56:42 - mmengine - INFO - Epoch(train) [834][50/63] lr: 1.2153e-03 eta: 4:32:08 time: 0.5413 data_time: 0.0236 memory: 16131 loss: 0.9969 loss_prob: 0.5320 loss_thr: 0.3701 loss_db: 0.0948 2022/10/26 05:56:45 - mmengine - INFO - Epoch(train) [834][55/63] lr: 1.2153e-03 eta: 4:32:08 time: 0.5823 data_time: 0.0219 memory: 16131 loss: 1.0230 loss_prob: 0.5466 loss_thr: 0.3812 loss_db: 0.0952 2022/10/26 05:56:48 - mmengine - INFO - Epoch(train) [834][60/63] lr: 1.2153e-03 eta: 4:32:00 time: 0.5361 data_time: 0.0073 memory: 16131 loss: 1.0661 loss_prob: 0.5680 loss_thr: 0.4021 loss_db: 0.0960 2022/10/26 05:56:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:56:54 - mmengine - INFO - Epoch(train) [835][5/63] lr: 1.2123e-03 eta: 4:32:00 time: 0.7185 data_time: 0.2377 memory: 16131 loss: 1.0684 loss_prob: 0.5762 loss_thr: 0.3959 loss_db: 0.0963 2022/10/26 05:56:56 - mmengine - INFO - Epoch(train) [835][10/63] lr: 1.2123e-03 eta: 4:31:50 time: 0.7656 data_time: 0.2388 memory: 16131 loss: 1.0358 loss_prob: 0.5563 loss_thr: 0.3860 loss_db: 0.0935 2022/10/26 05:56:59 - mmengine - INFO - Epoch(train) [835][15/63] lr: 1.2123e-03 eta: 4:31:50 time: 0.5557 data_time: 0.0098 memory: 16131 loss: 1.1282 loss_prob: 0.6099 loss_thr: 0.4140 loss_db: 0.1044 2022/10/26 05:57:02 - mmengine - INFO - Epoch(train) [835][20/63] lr: 1.2123e-03 eta: 4:31:42 time: 0.5448 data_time: 0.0055 memory: 16131 loss: 1.1674 loss_prob: 0.6437 loss_thr: 0.4167 loss_db: 0.1070 2022/10/26 05:57:05 - mmengine - INFO - Epoch(train) [835][25/63] lr: 1.2123e-03 eta: 4:31:42 time: 0.5300 data_time: 0.0247 memory: 16131 loss: 1.0464 loss_prob: 0.5566 loss_thr: 0.3953 loss_db: 0.0945 2022/10/26 05:57:07 - mmengine - INFO - Epoch(train) [835][30/63] lr: 1.2123e-03 eta: 4:31:34 time: 0.5443 data_time: 0.0379 memory: 16131 loss: 1.0543 loss_prob: 0.5576 loss_thr: 0.3989 loss_db: 0.0978 2022/10/26 05:57:10 - mmengine - INFO - Epoch(train) [835][35/63] lr: 1.2123e-03 eta: 4:31:34 time: 0.5205 data_time: 0.0176 memory: 16131 loss: 1.0745 loss_prob: 0.5727 loss_thr: 0.4031 loss_db: 0.0987 2022/10/26 05:57:12 - mmengine - INFO - Epoch(train) [835][40/63] lr: 1.2123e-03 eta: 4:31:26 time: 0.4921 data_time: 0.0060 memory: 16131 loss: 1.1001 loss_prob: 0.5827 loss_thr: 0.4172 loss_db: 0.1001 2022/10/26 05:57:15 - mmengine - INFO - Epoch(train) [835][45/63] lr: 1.2123e-03 eta: 4:31:26 time: 0.5235 data_time: 0.0067 memory: 16131 loss: 1.1695 loss_prob: 0.6330 loss_thr: 0.4315 loss_db: 0.1050 2022/10/26 05:57:18 - mmengine - INFO - Epoch(train) [835][50/63] lr: 1.2123e-03 eta: 4:31:19 time: 0.5692 data_time: 0.0148 memory: 16131 loss: 1.1662 loss_prob: 0.6350 loss_thr: 0.4243 loss_db: 0.1069 2022/10/26 05:57:20 - mmengine - INFO - Epoch(train) [835][55/63] lr: 1.2123e-03 eta: 4:31:19 time: 0.5451 data_time: 0.0206 memory: 16131 loss: 1.0545 loss_prob: 0.5572 loss_thr: 0.3990 loss_db: 0.0983 2022/10/26 05:57:23 - mmengine - INFO - Epoch(train) [835][60/63] lr: 1.2123e-03 eta: 4:31:11 time: 0.5010 data_time: 0.0154 memory: 16131 loss: 1.0248 loss_prob: 0.5370 loss_thr: 0.3945 loss_db: 0.0934 2022/10/26 05:57:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:57:30 - mmengine - INFO - Epoch(train) [836][5/63] lr: 1.2093e-03 eta: 4:31:11 time: 0.7765 data_time: 0.2168 memory: 16131 loss: 1.0863 loss_prob: 0.5787 loss_thr: 0.4082 loss_db: 0.0994 2022/10/26 05:57:32 - mmengine - INFO - Epoch(train) [836][10/63] lr: 1.2093e-03 eta: 4:31:01 time: 0.8247 data_time: 0.2162 memory: 16131 loss: 1.0523 loss_prob: 0.5643 loss_thr: 0.3889 loss_db: 0.0990 2022/10/26 05:57:35 - mmengine - INFO - Epoch(train) [836][15/63] lr: 1.2093e-03 eta: 4:31:01 time: 0.5503 data_time: 0.0085 memory: 16131 loss: 1.0241 loss_prob: 0.5468 loss_thr: 0.3821 loss_db: 0.0952 2022/10/26 05:57:38 - mmengine - INFO - Epoch(train) [836][20/63] lr: 1.2093e-03 eta: 4:30:53 time: 0.5615 data_time: 0.0081 memory: 16131 loss: 1.0321 loss_prob: 0.5525 loss_thr: 0.3849 loss_db: 0.0947 2022/10/26 05:57:41 - mmengine - INFO - Epoch(train) [836][25/63] lr: 1.2093e-03 eta: 4:30:53 time: 0.5844 data_time: 0.0318 memory: 16131 loss: 1.0034 loss_prob: 0.5350 loss_thr: 0.3758 loss_db: 0.0926 2022/10/26 05:57:44 - mmengine - INFO - Epoch(train) [836][30/63] lr: 1.2093e-03 eta: 4:30:46 time: 0.5552 data_time: 0.0318 memory: 16131 loss: 1.0039 loss_prob: 0.5322 loss_thr: 0.3799 loss_db: 0.0918 2022/10/26 05:57:46 - mmengine - INFO - Epoch(train) [836][35/63] lr: 1.2093e-03 eta: 4:30:46 time: 0.5046 data_time: 0.0172 memory: 16131 loss: 0.9939 loss_prob: 0.5186 loss_thr: 0.3861 loss_db: 0.0892 2022/10/26 05:57:49 - mmengine - INFO - Epoch(train) [836][40/63] lr: 1.2093e-03 eta: 4:30:38 time: 0.5105 data_time: 0.0210 memory: 16131 loss: 1.0041 loss_prob: 0.5210 loss_thr: 0.3934 loss_db: 0.0897 2022/10/26 05:57:51 - mmengine - INFO - Epoch(train) [836][45/63] lr: 1.2093e-03 eta: 4:30:38 time: 0.5031 data_time: 0.0093 memory: 16131 loss: 1.1100 loss_prob: 0.5926 loss_thr: 0.4172 loss_db: 0.1002 2022/10/26 05:57:54 - mmengine - INFO - Epoch(train) [836][50/63] lr: 1.2093e-03 eta: 4:30:30 time: 0.5114 data_time: 0.0199 memory: 16131 loss: 1.1276 loss_prob: 0.6071 loss_thr: 0.4190 loss_db: 0.1015 2022/10/26 05:57:56 - mmengine - INFO - Epoch(train) [836][55/63] lr: 1.2093e-03 eta: 4:30:30 time: 0.5045 data_time: 0.0188 memory: 16131 loss: 1.0892 loss_prob: 0.5809 loss_thr: 0.4099 loss_db: 0.0984 2022/10/26 05:57:59 - mmengine - INFO - Epoch(train) [836][60/63] lr: 1.2093e-03 eta: 4:30:22 time: 0.5013 data_time: 0.0058 memory: 16131 loss: 1.1360 loss_prob: 0.6161 loss_thr: 0.4146 loss_db: 0.1053 2022/10/26 05:58:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:58:05 - mmengine - INFO - Epoch(train) [837][5/63] lr: 1.2063e-03 eta: 4:30:22 time: 0.6849 data_time: 0.2024 memory: 16131 loss: 1.0152 loss_prob: 0.5427 loss_thr: 0.3793 loss_db: 0.0931 2022/10/26 05:58:07 - mmengine - INFO - Epoch(train) [837][10/63] lr: 1.2063e-03 eta: 4:30:12 time: 0.7414 data_time: 0.2092 memory: 16131 loss: 1.0623 loss_prob: 0.5721 loss_thr: 0.3933 loss_db: 0.0969 2022/10/26 05:58:10 - mmengine - INFO - Epoch(train) [837][15/63] lr: 1.2063e-03 eta: 4:30:12 time: 0.5367 data_time: 0.0132 memory: 16131 loss: 1.0978 loss_prob: 0.5869 loss_thr: 0.4108 loss_db: 0.1001 2022/10/26 05:58:13 - mmengine - INFO - Epoch(train) [837][20/63] lr: 1.2063e-03 eta: 4:30:04 time: 0.5199 data_time: 0.0067 memory: 16131 loss: 0.9914 loss_prob: 0.5186 loss_thr: 0.3835 loss_db: 0.0893 2022/10/26 05:58:15 - mmengine - INFO - Epoch(train) [837][25/63] lr: 1.2063e-03 eta: 4:30:04 time: 0.5427 data_time: 0.0219 memory: 16131 loss: 0.9707 loss_prob: 0.5118 loss_thr: 0.3707 loss_db: 0.0882 2022/10/26 05:58:18 - mmengine - INFO - Epoch(train) [837][30/63] lr: 1.2063e-03 eta: 4:29:56 time: 0.5559 data_time: 0.0360 memory: 16131 loss: 0.9913 loss_prob: 0.5248 loss_thr: 0.3762 loss_db: 0.0903 2022/10/26 05:58:21 - mmengine - INFO - Epoch(train) [837][35/63] lr: 1.2063e-03 eta: 4:29:56 time: 0.5516 data_time: 0.0279 memory: 16131 loss: 1.0462 loss_prob: 0.5610 loss_thr: 0.3888 loss_db: 0.0964 2022/10/26 05:58:23 - mmengine - INFO - Epoch(train) [837][40/63] lr: 1.2063e-03 eta: 4:29:48 time: 0.5196 data_time: 0.0148 memory: 16131 loss: 1.1668 loss_prob: 0.6397 loss_thr: 0.4202 loss_db: 0.1069 2022/10/26 05:58:27 - mmengine - INFO - Epoch(train) [837][45/63] lr: 1.2063e-03 eta: 4:29:48 time: 0.5590 data_time: 0.0091 memory: 16131 loss: 1.1282 loss_prob: 0.6142 loss_thr: 0.4120 loss_db: 0.1020 2022/10/26 05:58:29 - mmengine - INFO - Epoch(train) [837][50/63] lr: 1.2063e-03 eta: 4:29:41 time: 0.5894 data_time: 0.0233 memory: 16131 loss: 1.0593 loss_prob: 0.5742 loss_thr: 0.3883 loss_db: 0.0968 2022/10/26 05:58:32 - mmengine - INFO - Epoch(train) [837][55/63] lr: 1.2063e-03 eta: 4:29:41 time: 0.5653 data_time: 0.0243 memory: 16131 loss: 1.0455 loss_prob: 0.5605 loss_thr: 0.3879 loss_db: 0.0970 2022/10/26 05:58:35 - mmengine - INFO - Epoch(train) [837][60/63] lr: 1.2063e-03 eta: 4:29:33 time: 0.5516 data_time: 0.0076 memory: 16131 loss: 1.0667 loss_prob: 0.5630 loss_thr: 0.4066 loss_db: 0.0971 2022/10/26 05:58:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:58:40 - mmengine - INFO - Epoch(train) [838][5/63] lr: 1.2033e-03 eta: 4:29:33 time: 0.6496 data_time: 0.1684 memory: 16131 loss: 1.0854 loss_prob: 0.5856 loss_thr: 0.4019 loss_db: 0.0978 2022/10/26 05:58:43 - mmengine - INFO - Epoch(train) [838][10/63] lr: 1.2033e-03 eta: 4:29:23 time: 0.6901 data_time: 0.1734 memory: 16131 loss: 0.9869 loss_prob: 0.5125 loss_thr: 0.3815 loss_db: 0.0929 2022/10/26 05:58:46 - mmengine - INFO - Epoch(train) [838][15/63] lr: 1.2033e-03 eta: 4:29:23 time: 0.5223 data_time: 0.0120 memory: 16131 loss: 1.1148 loss_prob: 0.6092 loss_thr: 0.4045 loss_db: 0.1011 2022/10/26 05:58:48 - mmengine - INFO - Epoch(train) [838][20/63] lr: 1.2033e-03 eta: 4:29:15 time: 0.4990 data_time: 0.0081 memory: 16131 loss: 1.1806 loss_prob: 0.6604 loss_thr: 0.4148 loss_db: 0.1054 2022/10/26 05:58:51 - mmengine - INFO - Epoch(train) [838][25/63] lr: 1.2033e-03 eta: 4:29:15 time: 0.5158 data_time: 0.0146 memory: 16131 loss: 1.1291 loss_prob: 0.6072 loss_thr: 0.4180 loss_db: 0.1039 2022/10/26 05:58:54 - mmengine - INFO - Epoch(train) [838][30/63] lr: 1.2033e-03 eta: 4:29:07 time: 0.5771 data_time: 0.0361 memory: 16131 loss: 1.1225 loss_prob: 0.5944 loss_thr: 0.4219 loss_db: 0.1062 2022/10/26 05:58:56 - mmengine - INFO - Epoch(train) [838][35/63] lr: 1.2033e-03 eta: 4:29:07 time: 0.5763 data_time: 0.0299 memory: 16131 loss: 1.1460 loss_prob: 0.6131 loss_thr: 0.4269 loss_db: 0.1061 2022/10/26 05:58:59 - mmengine - INFO - Epoch(train) [838][40/63] lr: 1.2033e-03 eta: 4:28:59 time: 0.5142 data_time: 0.0065 memory: 16131 loss: 1.1402 loss_prob: 0.6099 loss_thr: 0.4277 loss_db: 0.1026 2022/10/26 05:59:01 - mmengine - INFO - Epoch(train) [838][45/63] lr: 1.2033e-03 eta: 4:28:59 time: 0.5039 data_time: 0.0077 memory: 16131 loss: 1.1671 loss_prob: 0.6268 loss_thr: 0.4336 loss_db: 0.1067 2022/10/26 05:59:04 - mmengine - INFO - Epoch(train) [838][50/63] lr: 1.2033e-03 eta: 4:28:51 time: 0.5107 data_time: 0.0208 memory: 16131 loss: 1.1358 loss_prob: 0.6045 loss_thr: 0.4281 loss_db: 0.1033 2022/10/26 05:59:06 - mmengine - INFO - Epoch(train) [838][55/63] lr: 1.2033e-03 eta: 4:28:51 time: 0.4986 data_time: 0.0216 memory: 16131 loss: 1.0265 loss_prob: 0.5361 loss_thr: 0.3991 loss_db: 0.0914 2022/10/26 05:59:09 - mmengine - INFO - Epoch(train) [838][60/63] lr: 1.2033e-03 eta: 4:28:43 time: 0.5151 data_time: 0.0111 memory: 16131 loss: 1.0040 loss_prob: 0.5354 loss_thr: 0.3785 loss_db: 0.0901 2022/10/26 05:59:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:59:15 - mmengine - INFO - Epoch(train) [839][5/63] lr: 1.2003e-03 eta: 4:28:43 time: 0.7430 data_time: 0.2366 memory: 16131 loss: 1.0719 loss_prob: 0.5709 loss_thr: 0.4028 loss_db: 0.0981 2022/10/26 05:59:18 - mmengine - INFO - Epoch(train) [839][10/63] lr: 1.2003e-03 eta: 4:28:33 time: 0.7287 data_time: 0.2277 memory: 16131 loss: 0.9921 loss_prob: 0.5225 loss_thr: 0.3793 loss_db: 0.0903 2022/10/26 05:59:21 - mmengine - INFO - Epoch(train) [839][15/63] lr: 1.2003e-03 eta: 4:28:33 time: 0.5980 data_time: 0.0063 memory: 16131 loss: 1.0988 loss_prob: 0.5867 loss_thr: 0.4119 loss_db: 0.1002 2022/10/26 05:59:24 - mmengine - INFO - Epoch(train) [839][20/63] lr: 1.2003e-03 eta: 4:28:26 time: 0.6117 data_time: 0.0071 memory: 16131 loss: 1.1309 loss_prob: 0.6101 loss_thr: 0.4164 loss_db: 0.1044 2022/10/26 05:59:27 - mmengine - INFO - Epoch(train) [839][25/63] lr: 1.2003e-03 eta: 4:28:26 time: 0.5581 data_time: 0.0239 memory: 16131 loss: 1.0613 loss_prob: 0.5672 loss_thr: 0.3973 loss_db: 0.0968 2022/10/26 05:59:30 - mmengine - INFO - Epoch(train) [839][30/63] lr: 1.2003e-03 eta: 4:28:18 time: 0.5735 data_time: 0.0354 memory: 16131 loss: 0.9538 loss_prob: 0.4969 loss_thr: 0.3715 loss_db: 0.0854 2022/10/26 05:59:32 - mmengine - INFO - Epoch(train) [839][35/63] lr: 1.2003e-03 eta: 4:28:18 time: 0.5385 data_time: 0.0181 memory: 16131 loss: 0.9427 loss_prob: 0.4883 loss_thr: 0.3690 loss_db: 0.0854 2022/10/26 05:59:35 - mmengine - INFO - Epoch(train) [839][40/63] lr: 1.2003e-03 eta: 4:28:10 time: 0.5156 data_time: 0.0057 memory: 16131 loss: 1.0344 loss_prob: 0.5410 loss_thr: 0.3983 loss_db: 0.0950 2022/10/26 05:59:38 - mmengine - INFO - Epoch(train) [839][45/63] lr: 1.2003e-03 eta: 4:28:10 time: 0.5194 data_time: 0.0048 memory: 16131 loss: 1.1428 loss_prob: 0.6091 loss_thr: 0.4268 loss_db: 0.1069 2022/10/26 05:59:41 - mmengine - INFO - Epoch(train) [839][50/63] lr: 1.2003e-03 eta: 4:28:03 time: 0.5534 data_time: 0.0155 memory: 16131 loss: 1.1756 loss_prob: 0.6316 loss_thr: 0.4361 loss_db: 0.1078 2022/10/26 05:59:43 - mmengine - INFO - Epoch(train) [839][55/63] lr: 1.2003e-03 eta: 4:28:03 time: 0.5858 data_time: 0.0213 memory: 16131 loss: 1.1132 loss_prob: 0.5916 loss_thr: 0.4189 loss_db: 0.1027 2022/10/26 05:59:46 - mmengine - INFO - Epoch(train) [839][60/63] lr: 1.2003e-03 eta: 4:27:55 time: 0.5345 data_time: 0.0130 memory: 16131 loss: 1.1329 loss_prob: 0.6130 loss_thr: 0.4151 loss_db: 0.1049 2022/10/26 05:59:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 05:59:52 - mmengine - INFO - Epoch(train) [840][5/63] lr: 1.1973e-03 eta: 4:27:55 time: 0.7090 data_time: 0.2103 memory: 16131 loss: 1.1303 loss_prob: 0.6107 loss_thr: 0.4181 loss_db: 0.1015 2022/10/26 05:59:54 - mmengine - INFO - Epoch(train) [840][10/63] lr: 1.1973e-03 eta: 4:27:45 time: 0.7304 data_time: 0.2118 memory: 16131 loss: 1.0373 loss_prob: 0.5525 loss_thr: 0.3925 loss_db: 0.0923 2022/10/26 05:59:58 - mmengine - INFO - Epoch(train) [840][15/63] lr: 1.1973e-03 eta: 4:27:45 time: 0.5728 data_time: 0.0093 memory: 16131 loss: 1.0194 loss_prob: 0.5387 loss_thr: 0.3854 loss_db: 0.0953 2022/10/26 06:00:00 - mmengine - INFO - Epoch(train) [840][20/63] lr: 1.1973e-03 eta: 4:27:37 time: 0.6003 data_time: 0.0060 memory: 16131 loss: 1.0521 loss_prob: 0.5582 loss_thr: 0.3969 loss_db: 0.0970 2022/10/26 06:00:03 - mmengine - INFO - Epoch(train) [840][25/63] lr: 1.1973e-03 eta: 4:27:37 time: 0.5607 data_time: 0.0301 memory: 16131 loss: 1.0133 loss_prob: 0.5318 loss_thr: 0.3916 loss_db: 0.0899 2022/10/26 06:00:06 - mmengine - INFO - Epoch(train) [840][30/63] lr: 1.1973e-03 eta: 4:27:30 time: 0.5509 data_time: 0.0351 memory: 16131 loss: 1.0647 loss_prob: 0.5577 loss_thr: 0.4089 loss_db: 0.0980 2022/10/26 06:00:08 - mmengine - INFO - Epoch(train) [840][35/63] lr: 1.1973e-03 eta: 4:27:30 time: 0.5112 data_time: 0.0105 memory: 16131 loss: 1.0631 loss_prob: 0.5575 loss_thr: 0.4074 loss_db: 0.0982 2022/10/26 06:00:11 - mmengine - INFO - Epoch(train) [840][40/63] lr: 1.1973e-03 eta: 4:27:22 time: 0.5096 data_time: 0.0053 memory: 16131 loss: 1.0641 loss_prob: 0.5662 loss_thr: 0.3999 loss_db: 0.0980 2022/10/26 06:00:14 - mmengine - INFO - Epoch(train) [840][45/63] lr: 1.1973e-03 eta: 4:27:22 time: 0.5309 data_time: 0.0090 memory: 16131 loss: 1.0714 loss_prob: 0.5763 loss_thr: 0.3953 loss_db: 0.0998 2022/10/26 06:00:17 - mmengine - INFO - Epoch(train) [840][50/63] lr: 1.1973e-03 eta: 4:27:14 time: 0.5536 data_time: 0.0259 memory: 16131 loss: 0.9920 loss_prob: 0.5202 loss_thr: 0.3800 loss_db: 0.0917 2022/10/26 06:00:19 - mmengine - INFO - Epoch(train) [840][55/63] lr: 1.1973e-03 eta: 4:27:14 time: 0.5406 data_time: 0.0226 memory: 16131 loss: 1.0262 loss_prob: 0.5394 loss_thr: 0.3891 loss_db: 0.0977 2022/10/26 06:00:22 - mmengine - INFO - Epoch(train) [840][60/63] lr: 1.1973e-03 eta: 4:27:06 time: 0.5069 data_time: 0.0064 memory: 16131 loss: 1.0866 loss_prob: 0.5703 loss_thr: 0.4156 loss_db: 0.1007 2022/10/26 06:00:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:00:23 - mmengine - INFO - Saving checkpoint at 840 epochs 2022/10/26 06:00:29 - mmengine - INFO - Epoch(val) [840][5/32] eta: 4:27:06 time: 0.5119 data_time: 0.0552 memory: 16131 2022/10/26 06:00:32 - mmengine - INFO - Epoch(val) [840][10/32] eta: 0:00:12 time: 0.5782 data_time: 0.0849 memory: 15724 2022/10/26 06:00:35 - mmengine - INFO - Epoch(val) [840][15/32] eta: 0:00:12 time: 0.5295 data_time: 0.0460 memory: 15724 2022/10/26 06:00:38 - mmengine - INFO - Epoch(val) [840][20/32] eta: 0:00:06 time: 0.5269 data_time: 0.0476 memory: 15724 2022/10/26 06:00:40 - mmengine - INFO - Epoch(val) [840][25/32] eta: 0:00:06 time: 0.5567 data_time: 0.0620 memory: 15724 2022/10/26 06:00:43 - mmengine - INFO - Epoch(val) [840][30/32] eta: 0:00:01 time: 0.5188 data_time: 0.0301 memory: 15724 2022/10/26 06:00:43 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8406, precision: 0.7542, hmean: 0.7951 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8406, precision: 0.8054, hmean: 0.8226 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8402, precision: 0.8397, hmean: 0.8400 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8377, precision: 0.8635, hmean: 0.8504 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8214, precision: 0.8913, hmean: 0.8549 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7203, precision: 0.9286, hmean: 0.8113 2022/10/26 06:00:43 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0833, precision: 1.0000, hmean: 0.1538 2022/10/26 06:00:43 - mmengine - INFO - Epoch(val) [840][32/32] icdar/precision: 0.8913 icdar/recall: 0.8214 icdar/hmean: 0.8549 2022/10/26 06:00:48 - mmengine - INFO - Epoch(train) [841][5/63] lr: 1.1943e-03 eta: 0:00:01 time: 0.6450 data_time: 0.1731 memory: 16131 loss: 1.1166 loss_prob: 0.5829 loss_thr: 0.4331 loss_db: 0.1006 2022/10/26 06:00:50 - mmengine - INFO - Epoch(train) [841][10/63] lr: 1.1943e-03 eta: 4:26:56 time: 0.6789 data_time: 0.1750 memory: 16131 loss: 1.0590 loss_prob: 0.5578 loss_thr: 0.4067 loss_db: 0.0945 2022/10/26 06:00:53 - mmengine - INFO - Epoch(train) [841][15/63] lr: 1.1943e-03 eta: 4:26:56 time: 0.5165 data_time: 0.0093 memory: 16131 loss: 1.1253 loss_prob: 0.6026 loss_thr: 0.4163 loss_db: 0.1065 2022/10/26 06:00:55 - mmengine - INFO - Epoch(train) [841][20/63] lr: 1.1943e-03 eta: 4:26:48 time: 0.5125 data_time: 0.0059 memory: 16131 loss: 1.1490 loss_prob: 0.6202 loss_thr: 0.4189 loss_db: 0.1099 2022/10/26 06:00:58 - mmengine - INFO - Epoch(train) [841][25/63] lr: 1.1943e-03 eta: 4:26:48 time: 0.5477 data_time: 0.0083 memory: 16131 loss: 1.0346 loss_prob: 0.5473 loss_thr: 0.3941 loss_db: 0.0932 2022/10/26 06:01:01 - mmengine - INFO - Epoch(train) [841][30/63] lr: 1.1943e-03 eta: 4:26:40 time: 0.5971 data_time: 0.0326 memory: 16131 loss: 1.0309 loss_prob: 0.5485 loss_thr: 0.3883 loss_db: 0.0941 2022/10/26 06:01:04 - mmengine - INFO - Epoch(train) [841][35/63] lr: 1.1943e-03 eta: 4:26:40 time: 0.5878 data_time: 0.0328 memory: 16131 loss: 1.0655 loss_prob: 0.5700 loss_thr: 0.3952 loss_db: 0.1004 2022/10/26 06:01:07 - mmengine - INFO - Epoch(train) [841][40/63] lr: 1.1943e-03 eta: 4:26:33 time: 0.5469 data_time: 0.0094 memory: 16131 loss: 1.0287 loss_prob: 0.5441 loss_thr: 0.3894 loss_db: 0.0952 2022/10/26 06:01:09 - mmengine - INFO - Epoch(train) [841][45/63] lr: 1.1943e-03 eta: 4:26:33 time: 0.5184 data_time: 0.0059 memory: 16131 loss: 1.0361 loss_prob: 0.5493 loss_thr: 0.3936 loss_db: 0.0932 2022/10/26 06:01:12 - mmengine - INFO - Epoch(train) [841][50/63] lr: 1.1943e-03 eta: 4:26:25 time: 0.5160 data_time: 0.0117 memory: 16131 loss: 1.0690 loss_prob: 0.5770 loss_thr: 0.3967 loss_db: 0.0953 2022/10/26 06:01:14 - mmengine - INFO - Epoch(train) [841][55/63] lr: 1.1943e-03 eta: 4:26:25 time: 0.5109 data_time: 0.0212 memory: 16131 loss: 1.0646 loss_prob: 0.5805 loss_thr: 0.3877 loss_db: 0.0964 2022/10/26 06:01:17 - mmengine - INFO - Epoch(train) [841][60/63] lr: 1.1943e-03 eta: 4:26:17 time: 0.5075 data_time: 0.0173 memory: 16131 loss: 1.0654 loss_prob: 0.5707 loss_thr: 0.3958 loss_db: 0.0988 2022/10/26 06:01:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:01:23 - mmengine - INFO - Epoch(train) [842][5/63] lr: 1.1913e-03 eta: 4:26:17 time: 0.6655 data_time: 0.1903 memory: 16131 loss: 1.0764 loss_prob: 0.5770 loss_thr: 0.4059 loss_db: 0.0935 2022/10/26 06:01:25 - mmengine - INFO - Epoch(train) [842][10/63] lr: 1.1913e-03 eta: 4:26:07 time: 0.6972 data_time: 0.1891 memory: 16131 loss: 1.1229 loss_prob: 0.6072 loss_thr: 0.4144 loss_db: 0.1014 2022/10/26 06:01:28 - mmengine - INFO - Epoch(train) [842][15/63] lr: 1.1913e-03 eta: 4:26:07 time: 0.5131 data_time: 0.0053 memory: 16131 loss: 1.0355 loss_prob: 0.5464 loss_thr: 0.3922 loss_db: 0.0969 2022/10/26 06:01:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:01:31 - mmengine - INFO - Epoch(train) [842][20/63] lr: 1.1913e-03 eta: 4:25:59 time: 0.5488 data_time: 0.0066 memory: 16131 loss: 0.9843 loss_prob: 0.5101 loss_thr: 0.3847 loss_db: 0.0894 2022/10/26 06:01:33 - mmengine - INFO - Epoch(train) [842][25/63] lr: 1.1913e-03 eta: 4:25:59 time: 0.5463 data_time: 0.0179 memory: 16131 loss: 1.0745 loss_prob: 0.5769 loss_thr: 0.4024 loss_db: 0.0952 2022/10/26 06:01:36 - mmengine - INFO - Epoch(train) [842][30/63] lr: 1.1913e-03 eta: 4:25:51 time: 0.5121 data_time: 0.0360 memory: 16131 loss: 1.1368 loss_prob: 0.6092 loss_thr: 0.4270 loss_db: 0.1007 2022/10/26 06:01:39 - mmengine - INFO - Epoch(train) [842][35/63] lr: 1.1913e-03 eta: 4:25:51 time: 0.5261 data_time: 0.0244 memory: 16131 loss: 1.0972 loss_prob: 0.5797 loss_thr: 0.4212 loss_db: 0.0963 2022/10/26 06:01:42 - mmengine - INFO - Epoch(train) [842][40/63] lr: 1.1913e-03 eta: 4:25:44 time: 0.5769 data_time: 0.0051 memory: 16131 loss: 1.0725 loss_prob: 0.5758 loss_thr: 0.4012 loss_db: 0.0956 2022/10/26 06:01:44 - mmengine - INFO - Epoch(train) [842][45/63] lr: 1.1913e-03 eta: 4:25:44 time: 0.5751 data_time: 0.0069 memory: 16131 loss: 1.0032 loss_prob: 0.5226 loss_thr: 0.3890 loss_db: 0.0915 2022/10/26 06:01:47 - mmengine - INFO - Epoch(train) [842][50/63] lr: 1.1913e-03 eta: 4:25:36 time: 0.5508 data_time: 0.0159 memory: 16131 loss: 1.0060 loss_prob: 0.5248 loss_thr: 0.3905 loss_db: 0.0907 2022/10/26 06:01:50 - mmengine - INFO - Epoch(train) [842][55/63] lr: 1.1913e-03 eta: 4:25:36 time: 0.5935 data_time: 0.0237 memory: 16131 loss: 1.0285 loss_prob: 0.5390 loss_thr: 0.3971 loss_db: 0.0924 2022/10/26 06:01:53 - mmengine - INFO - Epoch(train) [842][60/63] lr: 1.1913e-03 eta: 4:25:28 time: 0.5778 data_time: 0.0147 memory: 16131 loss: 0.9869 loss_prob: 0.5244 loss_thr: 0.3718 loss_db: 0.0906 2022/10/26 06:01:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:01:59 - mmengine - INFO - Epoch(train) [843][5/63] lr: 1.1883e-03 eta: 4:25:28 time: 0.6931 data_time: 0.1995 memory: 16131 loss: 1.0011 loss_prob: 0.5328 loss_thr: 0.3781 loss_db: 0.0902 2022/10/26 06:02:02 - mmengine - INFO - Epoch(train) [843][10/63] lr: 1.1883e-03 eta: 4:25:18 time: 0.7334 data_time: 0.2024 memory: 16131 loss: 1.0150 loss_prob: 0.5293 loss_thr: 0.3945 loss_db: 0.0911 2022/10/26 06:02:04 - mmengine - INFO - Epoch(train) [843][15/63] lr: 1.1883e-03 eta: 4:25:18 time: 0.5108 data_time: 0.0100 memory: 16131 loss: 1.0134 loss_prob: 0.5194 loss_thr: 0.4029 loss_db: 0.0910 2022/10/26 06:02:07 - mmengine - INFO - Epoch(train) [843][20/63] lr: 1.1883e-03 eta: 4:25:11 time: 0.5435 data_time: 0.0076 memory: 16131 loss: 1.0041 loss_prob: 0.5205 loss_thr: 0.3924 loss_db: 0.0912 2022/10/26 06:02:10 - mmengine - INFO - Epoch(train) [843][25/63] lr: 1.1883e-03 eta: 4:25:11 time: 0.5906 data_time: 0.0162 memory: 16131 loss: 1.0698 loss_prob: 0.5732 loss_thr: 0.3965 loss_db: 0.1001 2022/10/26 06:02:13 - mmengine - INFO - Epoch(train) [843][30/63] lr: 1.1883e-03 eta: 4:25:03 time: 0.5878 data_time: 0.0412 memory: 16131 loss: 1.0798 loss_prob: 0.5775 loss_thr: 0.4026 loss_db: 0.0997 2022/10/26 06:02:15 - mmengine - INFO - Epoch(train) [843][35/63] lr: 1.1883e-03 eta: 4:25:03 time: 0.5579 data_time: 0.0314 memory: 16131 loss: 0.9969 loss_prob: 0.5186 loss_thr: 0.3887 loss_db: 0.0896 2022/10/26 06:02:18 - mmengine - INFO - Epoch(train) [843][40/63] lr: 1.1883e-03 eta: 4:24:55 time: 0.5078 data_time: 0.0062 memory: 16131 loss: 1.0581 loss_prob: 0.5494 loss_thr: 0.4138 loss_db: 0.0949 2022/10/26 06:02:20 - mmengine - INFO - Epoch(train) [843][45/63] lr: 1.1883e-03 eta: 4:24:55 time: 0.5007 data_time: 0.0080 memory: 16131 loss: 1.1063 loss_prob: 0.5801 loss_thr: 0.4271 loss_db: 0.0991 2022/10/26 06:02:23 - mmengine - INFO - Epoch(train) [843][50/63] lr: 1.1883e-03 eta: 4:24:47 time: 0.5116 data_time: 0.0171 memory: 16131 loss: 0.9771 loss_prob: 0.5104 loss_thr: 0.3790 loss_db: 0.0877 2022/10/26 06:02:26 - mmengine - INFO - Epoch(train) [843][55/63] lr: 1.1883e-03 eta: 4:24:47 time: 0.5172 data_time: 0.0259 memory: 16131 loss: 0.9700 loss_prob: 0.5110 loss_thr: 0.3704 loss_db: 0.0886 2022/10/26 06:02:28 - mmengine - INFO - Epoch(train) [843][60/63] lr: 1.1883e-03 eta: 4:24:39 time: 0.5179 data_time: 0.0158 memory: 16131 loss: 1.1157 loss_prob: 0.6046 loss_thr: 0.4076 loss_db: 0.1036 2022/10/26 06:02:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:02:34 - mmengine - INFO - Epoch(train) [844][5/63] lr: 1.1853e-03 eta: 4:24:39 time: 0.6948 data_time: 0.1949 memory: 16131 loss: 1.0585 loss_prob: 0.5649 loss_thr: 0.3962 loss_db: 0.0973 2022/10/26 06:02:37 - mmengine - INFO - Epoch(train) [844][10/63] lr: 1.1853e-03 eta: 4:24:30 time: 0.7666 data_time: 0.2093 memory: 16131 loss: 1.0449 loss_prob: 0.5548 loss_thr: 0.3951 loss_db: 0.0950 2022/10/26 06:02:40 - mmengine - INFO - Epoch(train) [844][15/63] lr: 1.1853e-03 eta: 4:24:30 time: 0.5430 data_time: 0.0190 memory: 16131 loss: 1.0681 loss_prob: 0.5783 loss_thr: 0.3919 loss_db: 0.0979 2022/10/26 06:02:42 - mmengine - INFO - Epoch(train) [844][20/63] lr: 1.1853e-03 eta: 4:24:22 time: 0.4961 data_time: 0.0054 memory: 16131 loss: 1.0907 loss_prob: 0.5812 loss_thr: 0.4110 loss_db: 0.0985 2022/10/26 06:02:45 - mmengine - INFO - Epoch(train) [844][25/63] lr: 1.1853e-03 eta: 4:24:22 time: 0.5299 data_time: 0.0212 memory: 16131 loss: 0.9997 loss_prob: 0.5210 loss_thr: 0.3886 loss_db: 0.0901 2022/10/26 06:02:47 - mmengine - INFO - Epoch(train) [844][30/63] lr: 1.1853e-03 eta: 4:24:14 time: 0.5335 data_time: 0.0362 memory: 16131 loss: 1.0205 loss_prob: 0.5429 loss_thr: 0.3823 loss_db: 0.0953 2022/10/26 06:02:50 - mmengine - INFO - Epoch(train) [844][35/63] lr: 1.1853e-03 eta: 4:24:14 time: 0.5418 data_time: 0.0217 memory: 16131 loss: 1.0976 loss_prob: 0.5835 loss_thr: 0.4133 loss_db: 0.1008 2022/10/26 06:02:53 - mmengine - INFO - Epoch(train) [844][40/63] lr: 1.1853e-03 eta: 4:24:06 time: 0.5324 data_time: 0.0078 memory: 16131 loss: 1.0626 loss_prob: 0.5631 loss_thr: 0.4043 loss_db: 0.0953 2022/10/26 06:02:55 - mmengine - INFO - Epoch(train) [844][45/63] lr: 1.1853e-03 eta: 4:24:06 time: 0.4912 data_time: 0.0075 memory: 16131 loss: 1.0232 loss_prob: 0.5421 loss_thr: 0.3893 loss_db: 0.0918 2022/10/26 06:02:58 - mmengine - INFO - Epoch(train) [844][50/63] lr: 1.1853e-03 eta: 4:23:58 time: 0.5259 data_time: 0.0142 memory: 16131 loss: 1.0648 loss_prob: 0.5577 loss_thr: 0.4111 loss_db: 0.0959 2022/10/26 06:03:01 - mmengine - INFO - Epoch(train) [844][55/63] lr: 1.1853e-03 eta: 4:23:58 time: 0.5501 data_time: 0.0204 memory: 16131 loss: 1.0883 loss_prob: 0.5885 loss_thr: 0.4004 loss_db: 0.0995 2022/10/26 06:03:03 - mmengine - INFO - Epoch(train) [844][60/63] lr: 1.1853e-03 eta: 4:23:50 time: 0.5215 data_time: 0.0166 memory: 16131 loss: 1.0350 loss_prob: 0.5576 loss_thr: 0.3841 loss_db: 0.0933 2022/10/26 06:03:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:03:09 - mmengine - INFO - Epoch(train) [845][5/63] lr: 1.1823e-03 eta: 4:23:50 time: 0.7108 data_time: 0.1487 memory: 16131 loss: 1.0280 loss_prob: 0.5442 loss_thr: 0.3933 loss_db: 0.0905 2022/10/26 06:03:12 - mmengine - INFO - Epoch(train) [845][10/63] lr: 1.1823e-03 eta: 4:23:41 time: 0.7720 data_time: 0.1633 memory: 16131 loss: 0.9625 loss_prob: 0.5067 loss_thr: 0.3685 loss_db: 0.0873 2022/10/26 06:03:15 - mmengine - INFO - Epoch(train) [845][15/63] lr: 1.1823e-03 eta: 4:23:41 time: 0.5357 data_time: 0.0260 memory: 16131 loss: 1.0116 loss_prob: 0.5321 loss_thr: 0.3872 loss_db: 0.0923 2022/10/26 06:03:17 - mmengine - INFO - Epoch(train) [845][20/63] lr: 1.1823e-03 eta: 4:23:33 time: 0.4961 data_time: 0.0098 memory: 16131 loss: 1.0423 loss_prob: 0.5516 loss_thr: 0.3949 loss_db: 0.0957 2022/10/26 06:03:20 - mmengine - INFO - Epoch(train) [845][25/63] lr: 1.1823e-03 eta: 4:23:33 time: 0.5060 data_time: 0.0176 memory: 16131 loss: 1.0132 loss_prob: 0.5392 loss_thr: 0.3803 loss_db: 0.0938 2022/10/26 06:03:23 - mmengine - INFO - Epoch(train) [845][30/63] lr: 1.1823e-03 eta: 4:23:25 time: 0.5519 data_time: 0.0378 memory: 16131 loss: 1.0358 loss_prob: 0.5513 loss_thr: 0.3904 loss_db: 0.0941 2022/10/26 06:03:25 - mmengine - INFO - Epoch(train) [845][35/63] lr: 1.1823e-03 eta: 4:23:25 time: 0.5492 data_time: 0.0266 memory: 16131 loss: 1.0194 loss_prob: 0.5438 loss_thr: 0.3805 loss_db: 0.0951 2022/10/26 06:03:28 - mmengine - INFO - Epoch(train) [845][40/63] lr: 1.1823e-03 eta: 4:23:17 time: 0.5657 data_time: 0.0081 memory: 16131 loss: 1.0074 loss_prob: 0.5301 loss_thr: 0.3827 loss_db: 0.0945 2022/10/26 06:03:31 - mmengine - INFO - Epoch(train) [845][45/63] lr: 1.1823e-03 eta: 4:23:17 time: 0.6037 data_time: 0.0082 memory: 16131 loss: 0.9826 loss_prob: 0.5085 loss_thr: 0.3862 loss_db: 0.0878 2022/10/26 06:03:34 - mmengine - INFO - Epoch(train) [845][50/63] lr: 1.1823e-03 eta: 4:23:09 time: 0.5388 data_time: 0.0114 memory: 16131 loss: 0.9852 loss_prob: 0.5146 loss_thr: 0.3820 loss_db: 0.0886 2022/10/26 06:03:36 - mmengine - INFO - Epoch(train) [845][55/63] lr: 1.1823e-03 eta: 4:23:09 time: 0.4949 data_time: 0.0217 memory: 16131 loss: 0.9769 loss_prob: 0.5120 loss_thr: 0.3753 loss_db: 0.0895 2022/10/26 06:03:39 - mmengine - INFO - Epoch(train) [845][60/63] lr: 1.1823e-03 eta: 4:23:02 time: 0.5465 data_time: 0.0180 memory: 16131 loss: 1.2192 loss_prob: 0.7103 loss_thr: 0.4085 loss_db: 0.1004 2022/10/26 06:03:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:03:45 - mmengine - INFO - Epoch(train) [846][5/63] lr: 1.1793e-03 eta: 4:23:02 time: 0.6893 data_time: 0.1788 memory: 16131 loss: 1.0859 loss_prob: 0.5679 loss_thr: 0.4200 loss_db: 0.0979 2022/10/26 06:03:47 - mmengine - INFO - Epoch(train) [846][10/63] lr: 1.1793e-03 eta: 4:22:52 time: 0.7076 data_time: 0.1759 memory: 16131 loss: 1.0102 loss_prob: 0.5268 loss_thr: 0.3913 loss_db: 0.0920 2022/10/26 06:03:50 - mmengine - INFO - Epoch(train) [846][15/63] lr: 1.1793e-03 eta: 4:22:52 time: 0.5120 data_time: 0.0078 memory: 16131 loss: 1.0091 loss_prob: 0.5235 loss_thr: 0.3951 loss_db: 0.0906 2022/10/26 06:03:53 - mmengine - INFO - Epoch(train) [846][20/63] lr: 1.1793e-03 eta: 4:22:44 time: 0.5402 data_time: 0.0082 memory: 16131 loss: 0.9949 loss_prob: 0.5214 loss_thr: 0.3836 loss_db: 0.0900 2022/10/26 06:03:55 - mmengine - INFO - Epoch(train) [846][25/63] lr: 1.1793e-03 eta: 4:22:44 time: 0.5428 data_time: 0.0136 memory: 16131 loss: 1.0532 loss_prob: 0.5646 loss_thr: 0.3909 loss_db: 0.0976 2022/10/26 06:03:58 - mmengine - INFO - Epoch(train) [846][30/63] lr: 1.1793e-03 eta: 4:22:36 time: 0.5487 data_time: 0.0314 memory: 16131 loss: 1.0985 loss_prob: 0.5953 loss_thr: 0.3991 loss_db: 0.1041 2022/10/26 06:04:01 - mmengine - INFO - Epoch(train) [846][35/63] lr: 1.1793e-03 eta: 4:22:36 time: 0.5561 data_time: 0.0239 memory: 16131 loss: 1.0584 loss_prob: 0.5638 loss_thr: 0.3955 loss_db: 0.0991 2022/10/26 06:04:04 - mmengine - INFO - Epoch(train) [846][40/63] lr: 1.1793e-03 eta: 4:22:28 time: 0.5242 data_time: 0.0075 memory: 16131 loss: 1.0452 loss_prob: 0.5477 loss_thr: 0.4029 loss_db: 0.0945 2022/10/26 06:04:06 - mmengine - INFO - Epoch(train) [846][45/63] lr: 1.1793e-03 eta: 4:22:28 time: 0.5249 data_time: 0.0083 memory: 16131 loss: 1.0487 loss_prob: 0.5519 loss_thr: 0.4006 loss_db: 0.0961 2022/10/26 06:04:09 - mmengine - INFO - Epoch(train) [846][50/63] lr: 1.1793e-03 eta: 4:22:21 time: 0.5230 data_time: 0.0115 memory: 16131 loss: 1.0230 loss_prob: 0.5397 loss_thr: 0.3891 loss_db: 0.0942 2022/10/26 06:04:11 - mmengine - INFO - Epoch(train) [846][55/63] lr: 1.1793e-03 eta: 4:22:21 time: 0.5047 data_time: 0.0205 memory: 16131 loss: 0.9670 loss_prob: 0.5089 loss_thr: 0.3696 loss_db: 0.0884 2022/10/26 06:04:14 - mmengine - INFO - Epoch(train) [846][60/63] lr: 1.1793e-03 eta: 4:22:13 time: 0.5175 data_time: 0.0215 memory: 16131 loss: 0.9806 loss_prob: 0.5223 loss_thr: 0.3681 loss_db: 0.0903 2022/10/26 06:04:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:04:20 - mmengine - INFO - Epoch(train) [847][5/63] lr: 1.1763e-03 eta: 4:22:13 time: 0.6555 data_time: 0.1822 memory: 16131 loss: 1.1144 loss_prob: 0.6013 loss_thr: 0.4113 loss_db: 0.1018 2022/10/26 06:04:22 - mmengine - INFO - Epoch(train) [847][10/63] lr: 1.1763e-03 eta: 4:22:03 time: 0.6756 data_time: 0.1847 memory: 16131 loss: 1.0880 loss_prob: 0.5858 loss_thr: 0.4020 loss_db: 0.1002 2022/10/26 06:04:25 - mmengine - INFO - Epoch(train) [847][15/63] lr: 1.1763e-03 eta: 4:22:03 time: 0.5117 data_time: 0.0088 memory: 16131 loss: 1.0557 loss_prob: 0.5654 loss_thr: 0.3932 loss_db: 0.0972 2022/10/26 06:04:27 - mmengine - INFO - Epoch(train) [847][20/63] lr: 1.1763e-03 eta: 4:21:55 time: 0.5259 data_time: 0.0046 memory: 16131 loss: 1.0879 loss_prob: 0.5894 loss_thr: 0.3996 loss_db: 0.0988 2022/10/26 06:04:30 - mmengine - INFO - Epoch(train) [847][25/63] lr: 1.1763e-03 eta: 4:21:55 time: 0.5312 data_time: 0.0270 memory: 16131 loss: 1.0989 loss_prob: 0.5927 loss_thr: 0.4062 loss_db: 0.1000 2022/10/26 06:04:32 - mmengine - INFO - Epoch(train) [847][30/63] lr: 1.1763e-03 eta: 4:21:47 time: 0.5055 data_time: 0.0278 memory: 16131 loss: 1.1053 loss_prob: 0.5846 loss_thr: 0.4192 loss_db: 0.1015 2022/10/26 06:04:36 - mmengine - INFO - Epoch(train) [847][35/63] lr: 1.1763e-03 eta: 4:21:47 time: 0.5812 data_time: 0.0087 memory: 16131 loss: 0.9966 loss_prob: 0.5215 loss_thr: 0.3863 loss_db: 0.0887 2022/10/26 06:04:38 - mmengine - INFO - Epoch(train) [847][40/63] lr: 1.1763e-03 eta: 4:21:39 time: 0.6093 data_time: 0.0104 memory: 16131 loss: 0.9979 loss_prob: 0.5279 loss_thr: 0.3814 loss_db: 0.0885 2022/10/26 06:04:41 - mmengine - INFO - Epoch(train) [847][45/63] lr: 1.1763e-03 eta: 4:21:39 time: 0.5129 data_time: 0.0069 memory: 16131 loss: 1.0693 loss_prob: 0.5678 loss_thr: 0.4049 loss_db: 0.0966 2022/10/26 06:04:44 - mmengine - INFO - Epoch(train) [847][50/63] lr: 1.1763e-03 eta: 4:21:32 time: 0.5144 data_time: 0.0193 memory: 16131 loss: 1.1539 loss_prob: 0.6294 loss_thr: 0.4204 loss_db: 0.1041 2022/10/26 06:04:46 - mmengine - INFO - Epoch(train) [847][55/63] lr: 1.1763e-03 eta: 4:21:32 time: 0.5345 data_time: 0.0227 memory: 16131 loss: 1.2196 loss_prob: 0.6745 loss_thr: 0.4353 loss_db: 0.1099 2022/10/26 06:04:49 - mmengine - INFO - Epoch(train) [847][60/63] lr: 1.1763e-03 eta: 4:21:24 time: 0.5339 data_time: 0.0075 memory: 16131 loss: 1.0964 loss_prob: 0.5897 loss_thr: 0.4079 loss_db: 0.0988 2022/10/26 06:04:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:04:56 - mmengine - INFO - Epoch(train) [848][5/63] lr: 1.1733e-03 eta: 4:21:24 time: 0.7715 data_time: 0.2304 memory: 16131 loss: 1.0036 loss_prob: 0.5362 loss_thr: 0.3754 loss_db: 0.0920 2022/10/26 06:04:58 - mmengine - INFO - Epoch(train) [848][10/63] lr: 1.1733e-03 eta: 4:21:14 time: 0.7881 data_time: 0.2273 memory: 16131 loss: 0.9919 loss_prob: 0.5272 loss_thr: 0.3740 loss_db: 0.0907 2022/10/26 06:05:01 - mmengine - INFO - Epoch(train) [848][15/63] lr: 1.1733e-03 eta: 4:21:14 time: 0.4987 data_time: 0.0051 memory: 16131 loss: 0.9871 loss_prob: 0.5150 loss_thr: 0.3831 loss_db: 0.0890 2022/10/26 06:05:03 - mmengine - INFO - Epoch(train) [848][20/63] lr: 1.1733e-03 eta: 4:21:06 time: 0.5270 data_time: 0.0049 memory: 16131 loss: 0.9553 loss_prob: 0.4914 loss_thr: 0.3785 loss_db: 0.0854 2022/10/26 06:05:06 - mmengine - INFO - Epoch(train) [848][25/63] lr: 1.1733e-03 eta: 4:21:06 time: 0.5772 data_time: 0.0376 memory: 16131 loss: 1.0565 loss_prob: 0.5707 loss_thr: 0.3916 loss_db: 0.0942 2022/10/26 06:05:09 - mmengine - INFO - Epoch(train) [848][30/63] lr: 1.1733e-03 eta: 4:20:59 time: 0.5781 data_time: 0.0402 memory: 16131 loss: 1.1209 loss_prob: 0.6168 loss_thr: 0.4029 loss_db: 0.1012 2022/10/26 06:05:12 - mmengine - INFO - Epoch(train) [848][35/63] lr: 1.1733e-03 eta: 4:20:59 time: 0.5210 data_time: 0.0082 memory: 16131 loss: 1.0220 loss_prob: 0.5422 loss_thr: 0.3852 loss_db: 0.0946 2022/10/26 06:05:15 - mmengine - INFO - Epoch(train) [848][40/63] lr: 1.1733e-03 eta: 4:20:51 time: 0.5508 data_time: 0.0065 memory: 16131 loss: 1.0179 loss_prob: 0.5336 loss_thr: 0.3915 loss_db: 0.0927 2022/10/26 06:05:18 - mmengine - INFO - Epoch(train) [848][45/63] lr: 1.1733e-03 eta: 4:20:51 time: 0.5957 data_time: 0.0061 memory: 16131 loss: 1.0053 loss_prob: 0.5286 loss_thr: 0.3871 loss_db: 0.0896 2022/10/26 06:05:20 - mmengine - INFO - Epoch(train) [848][50/63] lr: 1.1733e-03 eta: 4:20:43 time: 0.5687 data_time: 0.0227 memory: 16131 loss: 1.0038 loss_prob: 0.5291 loss_thr: 0.3836 loss_db: 0.0912 2022/10/26 06:05:23 - mmengine - INFO - Epoch(train) [848][55/63] lr: 1.1733e-03 eta: 4:20:43 time: 0.5303 data_time: 0.0223 memory: 16131 loss: 1.0503 loss_prob: 0.5571 loss_thr: 0.4009 loss_db: 0.0923 2022/10/26 06:05:26 - mmengine - INFO - Epoch(train) [848][60/63] lr: 1.1733e-03 eta: 4:20:36 time: 0.5284 data_time: 0.0050 memory: 16131 loss: 1.0315 loss_prob: 0.5409 loss_thr: 0.4006 loss_db: 0.0900 2022/10/26 06:05:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:05:32 - mmengine - INFO - Epoch(train) [849][5/63] lr: 1.1703e-03 eta: 4:20:36 time: 0.7154 data_time: 0.1834 memory: 16131 loss: 1.0330 loss_prob: 0.5435 loss_thr: 0.3952 loss_db: 0.0942 2022/10/26 06:05:34 - mmengine - INFO - Epoch(train) [849][10/63] lr: 1.1703e-03 eta: 4:20:26 time: 0.7398 data_time: 0.1915 memory: 16131 loss: 1.0309 loss_prob: 0.5361 loss_thr: 0.4041 loss_db: 0.0908 2022/10/26 06:05:37 - mmengine - INFO - Epoch(train) [849][15/63] lr: 1.1703e-03 eta: 4:20:26 time: 0.5221 data_time: 0.0156 memory: 16131 loss: 1.0416 loss_prob: 0.5441 loss_thr: 0.4046 loss_db: 0.0929 2022/10/26 06:05:39 - mmengine - INFO - Epoch(train) [849][20/63] lr: 1.1703e-03 eta: 4:20:18 time: 0.5058 data_time: 0.0075 memory: 16131 loss: 1.0405 loss_prob: 0.5525 loss_thr: 0.3919 loss_db: 0.0962 2022/10/26 06:05:42 - mmengine - INFO - Epoch(train) [849][25/63] lr: 1.1703e-03 eta: 4:20:18 time: 0.5183 data_time: 0.0114 memory: 16131 loss: 1.0976 loss_prob: 0.5931 loss_thr: 0.4035 loss_db: 0.1010 2022/10/26 06:05:45 - mmengine - INFO - Epoch(train) [849][30/63] lr: 1.1703e-03 eta: 4:20:10 time: 0.5118 data_time: 0.0239 memory: 16131 loss: 1.1043 loss_prob: 0.5939 loss_thr: 0.4095 loss_db: 0.1008 2022/10/26 06:05:47 - mmengine - INFO - Epoch(train) [849][35/63] lr: 1.1703e-03 eta: 4:20:10 time: 0.5094 data_time: 0.0252 memory: 16131 loss: 1.0273 loss_prob: 0.5376 loss_thr: 0.3970 loss_db: 0.0927 2022/10/26 06:05:50 - mmengine - INFO - Epoch(train) [849][40/63] lr: 1.1703e-03 eta: 4:20:02 time: 0.5201 data_time: 0.0148 memory: 16131 loss: 1.0415 loss_prob: 0.5459 loss_thr: 0.4023 loss_db: 0.0933 2022/10/26 06:05:52 - mmengine - INFO - Epoch(train) [849][45/63] lr: 1.1703e-03 eta: 4:20:02 time: 0.5021 data_time: 0.0073 memory: 16131 loss: 1.0727 loss_prob: 0.5619 loss_thr: 0.4133 loss_db: 0.0975 2022/10/26 06:05:55 - mmengine - INFO - Epoch(train) [849][50/63] lr: 1.1703e-03 eta: 4:19:54 time: 0.4977 data_time: 0.0155 memory: 16131 loss: 1.0313 loss_prob: 0.5467 loss_thr: 0.3890 loss_db: 0.0957 2022/10/26 06:05:57 - mmengine - INFO - Epoch(train) [849][55/63] lr: 1.1703e-03 eta: 4:19:54 time: 0.5049 data_time: 0.0164 memory: 16131 loss: 0.9924 loss_prob: 0.5274 loss_thr: 0.3739 loss_db: 0.0912 2022/10/26 06:06:00 - mmengine - INFO - Epoch(train) [849][60/63] lr: 1.1703e-03 eta: 4:19:47 time: 0.5204 data_time: 0.0138 memory: 16131 loss: 1.0000 loss_prob: 0.5240 loss_thr: 0.3846 loss_db: 0.0914 2022/10/26 06:06:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:06:06 - mmengine - INFO - Epoch(train) [850][5/63] lr: 1.1673e-03 eta: 4:19:47 time: 0.6642 data_time: 0.1611 memory: 16131 loss: 0.9926 loss_prob: 0.5325 loss_thr: 0.3671 loss_db: 0.0930 2022/10/26 06:06:09 - mmengine - INFO - Epoch(train) [850][10/63] lr: 1.1673e-03 eta: 4:19:37 time: 0.7550 data_time: 0.1887 memory: 16131 loss: 1.0072 loss_prob: 0.5424 loss_thr: 0.3737 loss_db: 0.0911 2022/10/26 06:06:12 - mmengine - INFO - Epoch(train) [850][15/63] lr: 1.1673e-03 eta: 4:19:37 time: 0.6418 data_time: 0.0387 memory: 16131 loss: 1.0451 loss_prob: 0.5592 loss_thr: 0.3924 loss_db: 0.0936 2022/10/26 06:06:15 - mmengine - INFO - Epoch(train) [850][20/63] lr: 1.1673e-03 eta: 4:19:29 time: 0.5835 data_time: 0.0071 memory: 16131 loss: 1.0762 loss_prob: 0.5767 loss_thr: 0.4027 loss_db: 0.0967 2022/10/26 06:06:17 - mmengine - INFO - Epoch(train) [850][25/63] lr: 1.1673e-03 eta: 4:19:29 time: 0.5161 data_time: 0.0110 memory: 16131 loss: 1.0472 loss_prob: 0.5560 loss_thr: 0.3961 loss_db: 0.0951 2022/10/26 06:06:20 - mmengine - INFO - Epoch(train) [850][30/63] lr: 1.1673e-03 eta: 4:19:21 time: 0.5233 data_time: 0.0360 memory: 16131 loss: 0.9546 loss_prob: 0.4842 loss_thr: 0.3861 loss_db: 0.0843 2022/10/26 06:06:22 - mmengine - INFO - Epoch(train) [850][35/63] lr: 1.1673e-03 eta: 4:19:21 time: 0.5231 data_time: 0.0306 memory: 16131 loss: 1.0405 loss_prob: 0.5239 loss_thr: 0.4262 loss_db: 0.0905 2022/10/26 06:06:26 - mmengine - INFO - Epoch(train) [850][40/63] lr: 1.1673e-03 eta: 4:19:14 time: 0.5741 data_time: 0.0059 memory: 16131 loss: 1.1302 loss_prob: 0.5957 loss_thr: 0.4286 loss_db: 0.1059 2022/10/26 06:06:28 - mmengine - INFO - Epoch(train) [850][45/63] lr: 1.1673e-03 eta: 4:19:14 time: 0.5828 data_time: 0.0058 memory: 16131 loss: 1.1037 loss_prob: 0.5906 loss_thr: 0.4103 loss_db: 0.1028 2022/10/26 06:06:31 - mmengine - INFO - Epoch(train) [850][50/63] lr: 1.1673e-03 eta: 4:19:06 time: 0.5509 data_time: 0.0156 memory: 16131 loss: 1.0804 loss_prob: 0.5744 loss_thr: 0.4098 loss_db: 0.0963 2022/10/26 06:06:34 - mmengine - INFO - Epoch(train) [850][55/63] lr: 1.1673e-03 eta: 4:19:06 time: 0.5527 data_time: 0.0239 memory: 16131 loss: 1.0344 loss_prob: 0.5555 loss_thr: 0.3843 loss_db: 0.0947 2022/10/26 06:06:37 - mmengine - INFO - Epoch(train) [850][60/63] lr: 1.1673e-03 eta: 4:18:58 time: 0.5604 data_time: 0.0152 memory: 16131 loss: 1.1096 loss_prob: 0.6060 loss_thr: 0.4013 loss_db: 0.1023 2022/10/26 06:06:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:06:42 - mmengine - INFO - Epoch(train) [851][5/63] lr: 1.1643e-03 eta: 4:18:58 time: 0.7047 data_time: 0.1931 memory: 16131 loss: 1.0529 loss_prob: 0.5555 loss_thr: 0.4033 loss_db: 0.0941 2022/10/26 06:06:46 - mmengine - INFO - Epoch(train) [851][10/63] lr: 1.1643e-03 eta: 4:18:49 time: 0.7530 data_time: 0.1923 memory: 16131 loss: 0.9565 loss_prob: 0.4903 loss_thr: 0.3820 loss_db: 0.0842 2022/10/26 06:06:48 - mmengine - INFO - Epoch(train) [851][15/63] lr: 1.1643e-03 eta: 4:18:49 time: 0.5678 data_time: 0.0133 memory: 16131 loss: 1.0265 loss_prob: 0.5368 loss_thr: 0.3951 loss_db: 0.0947 2022/10/26 06:06:51 - mmengine - INFO - Epoch(train) [851][20/63] lr: 1.1643e-03 eta: 4:18:41 time: 0.5209 data_time: 0.0150 memory: 16131 loss: 1.0912 loss_prob: 0.5763 loss_thr: 0.4127 loss_db: 0.1022 2022/10/26 06:06:53 - mmengine - INFO - Epoch(train) [851][25/63] lr: 1.1643e-03 eta: 4:18:41 time: 0.5306 data_time: 0.0170 memory: 16131 loss: 1.0564 loss_prob: 0.5572 loss_thr: 0.4030 loss_db: 0.0962 2022/10/26 06:06:57 - mmengine - INFO - Epoch(train) [851][30/63] lr: 1.1643e-03 eta: 4:18:33 time: 0.5727 data_time: 0.0312 memory: 16131 loss: 1.0644 loss_prob: 0.5662 loss_thr: 0.4019 loss_db: 0.0962 2022/10/26 06:06:59 - mmengine - INFO - Epoch(train) [851][35/63] lr: 1.1643e-03 eta: 4:18:33 time: 0.5697 data_time: 0.0240 memory: 16131 loss: 1.0121 loss_prob: 0.5297 loss_thr: 0.3923 loss_db: 0.0901 2022/10/26 06:07:02 - mmengine - INFO - Epoch(train) [851][40/63] lr: 1.1643e-03 eta: 4:18:25 time: 0.5311 data_time: 0.0055 memory: 16131 loss: 0.9874 loss_prob: 0.5152 loss_thr: 0.3843 loss_db: 0.0879 2022/10/26 06:07:04 - mmengine - INFO - Epoch(train) [851][45/63] lr: 1.1643e-03 eta: 4:18:25 time: 0.5198 data_time: 0.0075 memory: 16131 loss: 1.0190 loss_prob: 0.5409 loss_thr: 0.3834 loss_db: 0.0946 2022/10/26 06:07:07 - mmengine - INFO - Epoch(train) [851][50/63] lr: 1.1643e-03 eta: 4:18:18 time: 0.5398 data_time: 0.0258 memory: 16131 loss: 1.0229 loss_prob: 0.5422 loss_thr: 0.3873 loss_db: 0.0934 2022/10/26 06:07:10 - mmengine - INFO - Epoch(train) [851][55/63] lr: 1.1643e-03 eta: 4:18:18 time: 0.5733 data_time: 0.0269 memory: 16131 loss: 1.0057 loss_prob: 0.5380 loss_thr: 0.3783 loss_db: 0.0894 2022/10/26 06:07:13 - mmengine - INFO - Epoch(train) [851][60/63] lr: 1.1643e-03 eta: 4:18:10 time: 0.5435 data_time: 0.0115 memory: 16131 loss: 0.9619 loss_prob: 0.5101 loss_thr: 0.3649 loss_db: 0.0870 2022/10/26 06:07:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:07:19 - mmengine - INFO - Epoch(train) [852][5/63] lr: 1.1613e-03 eta: 4:18:10 time: 0.7398 data_time: 0.1895 memory: 16131 loss: 1.0128 loss_prob: 0.5333 loss_thr: 0.3871 loss_db: 0.0924 2022/10/26 06:07:21 - mmengine - INFO - Epoch(train) [852][10/63] lr: 1.1613e-03 eta: 4:18:00 time: 0.7348 data_time: 0.1881 memory: 16131 loss: 1.0928 loss_prob: 0.5817 loss_thr: 0.4103 loss_db: 0.1008 2022/10/26 06:07:24 - mmengine - INFO - Epoch(train) [852][15/63] lr: 1.1613e-03 eta: 4:18:00 time: 0.4917 data_time: 0.0068 memory: 16131 loss: 1.0717 loss_prob: 0.5686 loss_thr: 0.4051 loss_db: 0.0980 2022/10/26 06:07:27 - mmengine - INFO - Epoch(train) [852][20/63] lr: 1.1613e-03 eta: 4:17:52 time: 0.5220 data_time: 0.0069 memory: 16131 loss: 1.0464 loss_prob: 0.5670 loss_thr: 0.3866 loss_db: 0.0928 2022/10/26 06:07:29 - mmengine - INFO - Epoch(train) [852][25/63] lr: 1.1613e-03 eta: 4:17:52 time: 0.5224 data_time: 0.0115 memory: 16131 loss: 1.0696 loss_prob: 0.5696 loss_thr: 0.4039 loss_db: 0.0961 2022/10/26 06:07:32 - mmengine - INFO - Epoch(train) [852][30/63] lr: 1.1613e-03 eta: 4:17:45 time: 0.5212 data_time: 0.0273 memory: 16131 loss: 1.0496 loss_prob: 0.5533 loss_thr: 0.3986 loss_db: 0.0977 2022/10/26 06:07:34 - mmengine - INFO - Epoch(train) [852][35/63] lr: 1.1613e-03 eta: 4:17:45 time: 0.5242 data_time: 0.0235 memory: 16131 loss: 1.0278 loss_prob: 0.5420 loss_thr: 0.3913 loss_db: 0.0944 2022/10/26 06:07:37 - mmengine - INFO - Epoch(train) [852][40/63] lr: 1.1613e-03 eta: 4:17:37 time: 0.5092 data_time: 0.0097 memory: 16131 loss: 1.0703 loss_prob: 0.5649 loss_thr: 0.4081 loss_db: 0.0973 2022/10/26 06:07:40 - mmengine - INFO - Epoch(train) [852][45/63] lr: 1.1613e-03 eta: 4:17:37 time: 0.5198 data_time: 0.0083 memory: 16131 loss: 1.1110 loss_prob: 0.5980 loss_thr: 0.4099 loss_db: 0.1030 2022/10/26 06:07:42 - mmengine - INFO - Epoch(train) [852][50/63] lr: 1.1613e-03 eta: 4:17:29 time: 0.5430 data_time: 0.0187 memory: 16131 loss: 1.0165 loss_prob: 0.5386 loss_thr: 0.3828 loss_db: 0.0951 2022/10/26 06:07:45 - mmengine - INFO - Epoch(train) [852][55/63] lr: 1.1613e-03 eta: 4:17:29 time: 0.5629 data_time: 0.0237 memory: 16131 loss: 0.9906 loss_prob: 0.5249 loss_thr: 0.3734 loss_db: 0.0923 2022/10/26 06:07:48 - mmengine - INFO - Epoch(train) [852][60/63] lr: 1.1613e-03 eta: 4:17:21 time: 0.5361 data_time: 0.0163 memory: 16131 loss: 1.0401 loss_prob: 0.5587 loss_thr: 0.3863 loss_db: 0.0952 2022/10/26 06:07:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:07:53 - mmengine - INFO - Epoch(train) [853][5/63] lr: 1.1583e-03 eta: 4:17:21 time: 0.6736 data_time: 0.1693 memory: 16131 loss: 0.9702 loss_prob: 0.5126 loss_thr: 0.3706 loss_db: 0.0870 2022/10/26 06:07:56 - mmengine - INFO - Epoch(train) [853][10/63] lr: 1.1583e-03 eta: 4:17:11 time: 0.6685 data_time: 0.1677 memory: 16131 loss: 0.9860 loss_prob: 0.5212 loss_thr: 0.3733 loss_db: 0.0914 2022/10/26 06:07:58 - mmengine - INFO - Epoch(train) [853][15/63] lr: 1.1583e-03 eta: 4:17:11 time: 0.4927 data_time: 0.0058 memory: 16131 loss: 0.9841 loss_prob: 0.5208 loss_thr: 0.3726 loss_db: 0.0908 2022/10/26 06:08:01 - mmengine - INFO - Epoch(train) [853][20/63] lr: 1.1583e-03 eta: 4:17:03 time: 0.4936 data_time: 0.0088 memory: 16131 loss: 1.0142 loss_prob: 0.5444 loss_thr: 0.3761 loss_db: 0.0938 2022/10/26 06:08:04 - mmengine - INFO - Epoch(train) [853][25/63] lr: 1.1583e-03 eta: 4:17:03 time: 0.5250 data_time: 0.0251 memory: 16131 loss: 1.0768 loss_prob: 0.5837 loss_thr: 0.3925 loss_db: 0.1006 2022/10/26 06:08:06 - mmengine - INFO - Epoch(train) [853][30/63] lr: 1.1583e-03 eta: 4:16:55 time: 0.5255 data_time: 0.0309 memory: 16131 loss: 1.0516 loss_prob: 0.5600 loss_thr: 0.3962 loss_db: 0.0954 2022/10/26 06:08:09 - mmengine - INFO - Epoch(train) [853][35/63] lr: 1.1583e-03 eta: 4:16:55 time: 0.5130 data_time: 0.0137 memory: 16131 loss: 1.0474 loss_prob: 0.5566 loss_thr: 0.3941 loss_db: 0.0966 2022/10/26 06:08:11 - mmengine - INFO - Epoch(train) [853][40/63] lr: 1.1583e-03 eta: 4:16:48 time: 0.5214 data_time: 0.0047 memory: 16131 loss: 1.0928 loss_prob: 0.5881 loss_thr: 0.4051 loss_db: 0.0996 2022/10/26 06:08:14 - mmengine - INFO - Epoch(train) [853][45/63] lr: 1.1583e-03 eta: 4:16:48 time: 0.5210 data_time: 0.0085 memory: 16131 loss: 1.0614 loss_prob: 0.5651 loss_thr: 0.4015 loss_db: 0.0948 2022/10/26 06:08:17 - mmengine - INFO - Epoch(train) [853][50/63] lr: 1.1583e-03 eta: 4:16:40 time: 0.5259 data_time: 0.0195 memory: 16131 loss: 0.9828 loss_prob: 0.5127 loss_thr: 0.3799 loss_db: 0.0902 2022/10/26 06:08:19 - mmengine - INFO - Epoch(train) [853][55/63] lr: 1.1583e-03 eta: 4:16:40 time: 0.5132 data_time: 0.0224 memory: 16131 loss: 1.0179 loss_prob: 0.5331 loss_thr: 0.3931 loss_db: 0.0917 2022/10/26 06:08:22 - mmengine - INFO - Epoch(train) [853][60/63] lr: 1.1583e-03 eta: 4:16:32 time: 0.5605 data_time: 0.0126 memory: 16131 loss: 1.1169 loss_prob: 0.6015 loss_thr: 0.4169 loss_db: 0.0985 2022/10/26 06:08:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:08:28 - mmengine - INFO - Epoch(train) [854][5/63] lr: 1.1553e-03 eta: 4:16:32 time: 0.7622 data_time: 0.1687 memory: 16131 loss: 1.1329 loss_prob: 0.6154 loss_thr: 0.4148 loss_db: 0.1027 2022/10/26 06:08:31 - mmengine - INFO - Epoch(train) [854][10/63] lr: 1.1553e-03 eta: 4:16:22 time: 0.7630 data_time: 0.1852 memory: 16131 loss: 1.1003 loss_prob: 0.5797 loss_thr: 0.4182 loss_db: 0.1024 2022/10/26 06:08:34 - mmengine - INFO - Epoch(train) [854][15/63] lr: 1.1553e-03 eta: 4:16:22 time: 0.5221 data_time: 0.0226 memory: 16131 loss: 1.0504 loss_prob: 0.5595 loss_thr: 0.3929 loss_db: 0.0979 2022/10/26 06:08:36 - mmengine - INFO - Epoch(train) [854][20/63] lr: 1.1553e-03 eta: 4:16:15 time: 0.5104 data_time: 0.0052 memory: 16131 loss: 1.1689 loss_prob: 0.6477 loss_thr: 0.4126 loss_db: 0.1085 2022/10/26 06:08:39 - mmengine - INFO - Epoch(train) [854][25/63] lr: 1.1553e-03 eta: 4:16:15 time: 0.5059 data_time: 0.0167 memory: 16131 loss: 1.1895 loss_prob: 0.6610 loss_thr: 0.4198 loss_db: 0.1086 2022/10/26 06:08:41 - mmengine - INFO - Epoch(train) [854][30/63] lr: 1.1553e-03 eta: 4:16:07 time: 0.5035 data_time: 0.0221 memory: 16131 loss: 1.0557 loss_prob: 0.5607 loss_thr: 0.3991 loss_db: 0.0960 2022/10/26 06:08:44 - mmengine - INFO - Epoch(train) [854][35/63] lr: 1.1553e-03 eta: 4:16:07 time: 0.5280 data_time: 0.0224 memory: 16131 loss: 0.9669 loss_prob: 0.5031 loss_thr: 0.3744 loss_db: 0.0894 2022/10/26 06:08:47 - mmengine - INFO - Epoch(train) [854][40/63] lr: 1.1553e-03 eta: 4:15:59 time: 0.5455 data_time: 0.0169 memory: 16131 loss: 0.9986 loss_prob: 0.5253 loss_thr: 0.3823 loss_db: 0.0910 2022/10/26 06:08:49 - mmengine - INFO - Epoch(train) [854][45/63] lr: 1.1553e-03 eta: 4:15:59 time: 0.5181 data_time: 0.0057 memory: 16131 loss: 1.0361 loss_prob: 0.5437 loss_thr: 0.4001 loss_db: 0.0923 2022/10/26 06:08:52 - mmengine - INFO - Epoch(train) [854][50/63] lr: 1.1553e-03 eta: 4:15:51 time: 0.5052 data_time: 0.0132 memory: 16131 loss: 0.9767 loss_prob: 0.5081 loss_thr: 0.3809 loss_db: 0.0877 2022/10/26 06:08:54 - mmengine - INFO - Epoch(train) [854][55/63] lr: 1.1553e-03 eta: 4:15:51 time: 0.5139 data_time: 0.0160 memory: 16131 loss: 0.9515 loss_prob: 0.5019 loss_thr: 0.3608 loss_db: 0.0888 2022/10/26 06:08:57 - mmengine - INFO - Epoch(train) [854][60/63] lr: 1.1553e-03 eta: 4:15:44 time: 0.5254 data_time: 0.0152 memory: 16131 loss: 0.9687 loss_prob: 0.5097 loss_thr: 0.3702 loss_db: 0.0888 2022/10/26 06:08:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:09:03 - mmengine - INFO - Epoch(train) [855][5/63] lr: 1.1523e-03 eta: 4:15:44 time: 0.7406 data_time: 0.1853 memory: 16131 loss: 1.0978 loss_prob: 0.5866 loss_thr: 0.4111 loss_db: 0.1002 2022/10/26 06:09:06 - mmengine - INFO - Epoch(train) [855][10/63] lr: 1.1523e-03 eta: 4:15:34 time: 0.7932 data_time: 0.1853 memory: 16131 loss: 1.0021 loss_prob: 0.5224 loss_thr: 0.3877 loss_db: 0.0919 2022/10/26 06:09:09 - mmengine - INFO - Epoch(train) [855][15/63] lr: 1.1523e-03 eta: 4:15:34 time: 0.5822 data_time: 0.0094 memory: 16131 loss: 0.9411 loss_prob: 0.4888 loss_thr: 0.3668 loss_db: 0.0854 2022/10/26 06:09:12 - mmengine - INFO - Epoch(train) [855][20/63] lr: 1.1523e-03 eta: 4:15:26 time: 0.5523 data_time: 0.0046 memory: 16131 loss: 1.0509 loss_prob: 0.5567 loss_thr: 0.3995 loss_db: 0.0947 2022/10/26 06:09:15 - mmengine - INFO - Epoch(train) [855][25/63] lr: 1.1523e-03 eta: 4:15:26 time: 0.5406 data_time: 0.0211 memory: 16131 loss: 1.0966 loss_prob: 0.5810 loss_thr: 0.4179 loss_db: 0.0977 2022/10/26 06:09:17 - mmengine - INFO - Epoch(train) [855][30/63] lr: 1.1523e-03 eta: 4:15:19 time: 0.5437 data_time: 0.0338 memory: 16131 loss: 1.0171 loss_prob: 0.5301 loss_thr: 0.3948 loss_db: 0.0922 2022/10/26 06:09:20 - mmengine - INFO - Epoch(train) [855][35/63] lr: 1.1523e-03 eta: 4:15:19 time: 0.5373 data_time: 0.0176 memory: 16131 loss: 0.9787 loss_prob: 0.5083 loss_thr: 0.3820 loss_db: 0.0884 2022/10/26 06:09:23 - mmengine - INFO - Epoch(train) [855][40/63] lr: 1.1523e-03 eta: 4:15:11 time: 0.5249 data_time: 0.0048 memory: 16131 loss: 1.0000 loss_prob: 0.5285 loss_thr: 0.3828 loss_db: 0.0887 2022/10/26 06:09:25 - mmengine - INFO - Epoch(train) [855][45/63] lr: 1.1523e-03 eta: 4:15:11 time: 0.5171 data_time: 0.0048 memory: 16131 loss: 1.0228 loss_prob: 0.5448 loss_thr: 0.3857 loss_db: 0.0923 2022/10/26 06:09:28 - mmengine - INFO - Epoch(train) [855][50/63] lr: 1.1523e-03 eta: 4:15:03 time: 0.5194 data_time: 0.0193 memory: 16131 loss: 1.0202 loss_prob: 0.5387 loss_thr: 0.3884 loss_db: 0.0931 2022/10/26 06:09:30 - mmengine - INFO - Epoch(train) [855][55/63] lr: 1.1523e-03 eta: 4:15:03 time: 0.5243 data_time: 0.0234 memory: 16131 loss: 1.0135 loss_prob: 0.5334 loss_thr: 0.3872 loss_db: 0.0929 2022/10/26 06:09:33 - mmengine - INFO - Epoch(train) [855][60/63] lr: 1.1523e-03 eta: 4:14:55 time: 0.5357 data_time: 0.0090 memory: 16131 loss: 1.1077 loss_prob: 0.5902 loss_thr: 0.4156 loss_db: 0.1019 2022/10/26 06:09:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:09:39 - mmengine - INFO - Epoch(train) [856][5/63] lr: 1.1493e-03 eta: 4:14:55 time: 0.7408 data_time: 0.2228 memory: 16131 loss: 1.0234 loss_prob: 0.5433 loss_thr: 0.3871 loss_db: 0.0930 2022/10/26 06:09:42 - mmengine - INFO - Epoch(train) [856][10/63] lr: 1.1493e-03 eta: 4:14:46 time: 0.7640 data_time: 0.2237 memory: 16131 loss: 1.0318 loss_prob: 0.5480 loss_thr: 0.3881 loss_db: 0.0957 2022/10/26 06:09:44 - mmengine - INFO - Epoch(train) [856][15/63] lr: 1.1493e-03 eta: 4:14:46 time: 0.4992 data_time: 0.0079 memory: 16131 loss: 1.0188 loss_prob: 0.5412 loss_thr: 0.3830 loss_db: 0.0946 2022/10/26 06:09:47 - mmengine - INFO - Epoch(train) [856][20/63] lr: 1.1493e-03 eta: 4:14:38 time: 0.5191 data_time: 0.0102 memory: 16131 loss: 0.9808 loss_prob: 0.5140 loss_thr: 0.3791 loss_db: 0.0876 2022/10/26 06:09:50 - mmengine - INFO - Epoch(train) [856][25/63] lr: 1.1493e-03 eta: 4:14:38 time: 0.5862 data_time: 0.0322 memory: 16131 loss: 0.9915 loss_prob: 0.5247 loss_thr: 0.3761 loss_db: 0.0907 2022/10/26 06:09:53 - mmengine - INFO - Epoch(train) [856][30/63] lr: 1.1493e-03 eta: 4:14:30 time: 0.5608 data_time: 0.0327 memory: 16131 loss: 1.0500 loss_prob: 0.5653 loss_thr: 0.3876 loss_db: 0.0972 2022/10/26 06:09:55 - mmengine - INFO - Epoch(train) [856][35/63] lr: 1.1493e-03 eta: 4:14:30 time: 0.5030 data_time: 0.0109 memory: 16131 loss: 1.0558 loss_prob: 0.5533 loss_thr: 0.4100 loss_db: 0.0925 2022/10/26 06:09:58 - mmengine - INFO - Epoch(train) [856][40/63] lr: 1.1493e-03 eta: 4:14:22 time: 0.5145 data_time: 0.0093 memory: 16131 loss: 1.0495 loss_prob: 0.5380 loss_thr: 0.4197 loss_db: 0.0918 2022/10/26 06:10:00 - mmengine - INFO - Epoch(train) [856][45/63] lr: 1.1493e-03 eta: 4:14:22 time: 0.5067 data_time: 0.0107 memory: 16131 loss: 0.9974 loss_prob: 0.5167 loss_thr: 0.3887 loss_db: 0.0920 2022/10/26 06:10:03 - mmengine - INFO - Epoch(train) [856][50/63] lr: 1.1493e-03 eta: 4:14:15 time: 0.5218 data_time: 0.0255 memory: 16131 loss: 1.0078 loss_prob: 0.5231 loss_thr: 0.3924 loss_db: 0.0923 2022/10/26 06:10:06 - mmengine - INFO - Epoch(train) [856][55/63] lr: 1.1493e-03 eta: 4:14:15 time: 0.5402 data_time: 0.0241 memory: 16131 loss: 1.0344 loss_prob: 0.5405 loss_thr: 0.4021 loss_db: 0.0917 2022/10/26 06:10:09 - mmengine - INFO - Epoch(train) [856][60/63] lr: 1.1493e-03 eta: 4:14:07 time: 0.5668 data_time: 0.0105 memory: 16131 loss: 1.0263 loss_prob: 0.5391 loss_thr: 0.3967 loss_db: 0.0906 2022/10/26 06:10:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:10:15 - mmengine - INFO - Epoch(train) [857][5/63] lr: 1.1463e-03 eta: 4:14:07 time: 0.7783 data_time: 0.2018 memory: 16131 loss: 1.1285 loss_prob: 0.6034 loss_thr: 0.4218 loss_db: 0.1033 2022/10/26 06:10:18 - mmengine - INFO - Epoch(train) [857][10/63] lr: 1.1463e-03 eta: 4:13:57 time: 0.7443 data_time: 0.2034 memory: 16131 loss: 1.1629 loss_prob: 0.6285 loss_thr: 0.4285 loss_db: 0.1059 2022/10/26 06:10:21 - mmengine - INFO - Epoch(train) [857][15/63] lr: 1.1463e-03 eta: 4:13:57 time: 0.5344 data_time: 0.0094 memory: 16131 loss: 1.0249 loss_prob: 0.5418 loss_thr: 0.3910 loss_db: 0.0920 2022/10/26 06:10:23 - mmengine - INFO - Epoch(train) [857][20/63] lr: 1.1463e-03 eta: 4:13:49 time: 0.5238 data_time: 0.0074 memory: 16131 loss: 1.0343 loss_prob: 0.5464 loss_thr: 0.3971 loss_db: 0.0908 2022/10/26 06:10:25 - mmengine - INFO - Epoch(train) [857][25/63] lr: 1.1463e-03 eta: 4:13:49 time: 0.4947 data_time: 0.0191 memory: 16131 loss: 1.0611 loss_prob: 0.5642 loss_thr: 0.4003 loss_db: 0.0966 2022/10/26 06:10:28 - mmengine - INFO - Epoch(train) [857][30/63] lr: 1.1463e-03 eta: 4:13:42 time: 0.5067 data_time: 0.0350 memory: 16131 loss: 1.0511 loss_prob: 0.5581 loss_thr: 0.3954 loss_db: 0.0976 2022/10/26 06:10:31 - mmengine - INFO - Epoch(train) [857][35/63] lr: 1.1463e-03 eta: 4:13:42 time: 0.5294 data_time: 0.0228 memory: 16131 loss: 1.1037 loss_prob: 0.5820 loss_thr: 0.4232 loss_db: 0.0985 2022/10/26 06:10:33 - mmengine - INFO - Epoch(train) [857][40/63] lr: 1.1463e-03 eta: 4:13:34 time: 0.5202 data_time: 0.0113 memory: 16131 loss: 1.0526 loss_prob: 0.5550 loss_thr: 0.4029 loss_db: 0.0947 2022/10/26 06:10:36 - mmengine - INFO - Epoch(train) [857][45/63] lr: 1.1463e-03 eta: 4:13:34 time: 0.4950 data_time: 0.0132 memory: 16131 loss: 1.0316 loss_prob: 0.5526 loss_thr: 0.3826 loss_db: 0.0963 2022/10/26 06:10:39 - mmengine - INFO - Epoch(train) [857][50/63] lr: 1.1463e-03 eta: 4:13:26 time: 0.5340 data_time: 0.0143 memory: 16131 loss: 1.0457 loss_prob: 0.5614 loss_thr: 0.3883 loss_db: 0.0960 2022/10/26 06:10:41 - mmengine - INFO - Epoch(train) [857][55/63] lr: 1.1463e-03 eta: 4:13:26 time: 0.5731 data_time: 0.0206 memory: 16131 loss: 1.0217 loss_prob: 0.5393 loss_thr: 0.3903 loss_db: 0.0921 2022/10/26 06:10:44 - mmengine - INFO - Epoch(train) [857][60/63] lr: 1.1463e-03 eta: 4:13:18 time: 0.5522 data_time: 0.0153 memory: 16131 loss: 0.9385 loss_prob: 0.4847 loss_thr: 0.3683 loss_db: 0.0855 2022/10/26 06:10:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:10:50 - mmengine - INFO - Epoch(train) [858][5/63] lr: 1.1433e-03 eta: 4:13:18 time: 0.6342 data_time: 0.1596 memory: 16131 loss: 0.9699 loss_prob: 0.5151 loss_thr: 0.3650 loss_db: 0.0898 2022/10/26 06:10:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:10:52 - mmengine - INFO - Epoch(train) [858][10/63] lr: 1.1433e-03 eta: 4:13:09 time: 0.7058 data_time: 0.1728 memory: 16131 loss: 1.0984 loss_prob: 0.6243 loss_thr: 0.3777 loss_db: 0.0964 2022/10/26 06:10:55 - mmengine - INFO - Epoch(train) [858][15/63] lr: 1.1433e-03 eta: 4:13:09 time: 0.5413 data_time: 0.0209 memory: 16131 loss: 1.1510 loss_prob: 0.6582 loss_thr: 0.3894 loss_db: 0.1034 2022/10/26 06:10:58 - mmengine - INFO - Epoch(train) [858][20/63] lr: 1.1433e-03 eta: 4:13:01 time: 0.5104 data_time: 0.0062 memory: 16131 loss: 1.0234 loss_prob: 0.5405 loss_thr: 0.3880 loss_db: 0.0950 2022/10/26 06:11:00 - mmengine - INFO - Epoch(train) [858][25/63] lr: 1.1433e-03 eta: 4:13:01 time: 0.5444 data_time: 0.0090 memory: 16131 loss: 1.0520 loss_prob: 0.5540 loss_thr: 0.4012 loss_db: 0.0968 2022/10/26 06:11:03 - mmengine - INFO - Epoch(train) [858][30/63] lr: 1.1433e-03 eta: 4:12:53 time: 0.5465 data_time: 0.0181 memory: 16131 loss: 1.0519 loss_prob: 0.5488 loss_thr: 0.4071 loss_db: 0.0960 2022/10/26 06:11:06 - mmengine - INFO - Epoch(train) [858][35/63] lr: 1.1433e-03 eta: 4:12:53 time: 0.5548 data_time: 0.0324 memory: 16131 loss: 1.0522 loss_prob: 0.5497 loss_thr: 0.4081 loss_db: 0.0944 2022/10/26 06:11:08 - mmengine - INFO - Epoch(train) [858][40/63] lr: 1.1433e-03 eta: 4:12:45 time: 0.5456 data_time: 0.0244 memory: 16131 loss: 1.0771 loss_prob: 0.5753 loss_thr: 0.4035 loss_db: 0.0983 2022/10/26 06:11:11 - mmengine - INFO - Epoch(train) [858][45/63] lr: 1.1433e-03 eta: 4:12:45 time: 0.5120 data_time: 0.0059 memory: 16131 loss: 1.0525 loss_prob: 0.5582 loss_thr: 0.3987 loss_db: 0.0956 2022/10/26 06:11:14 - mmengine - INFO - Epoch(train) [858][50/63] lr: 1.1433e-03 eta: 4:12:38 time: 0.5101 data_time: 0.0124 memory: 16131 loss: 0.9165 loss_prob: 0.4738 loss_thr: 0.3617 loss_db: 0.0810 2022/10/26 06:11:16 - mmengine - INFO - Epoch(train) [858][55/63] lr: 1.1433e-03 eta: 4:12:38 time: 0.5438 data_time: 0.0256 memory: 16131 loss: 0.9672 loss_prob: 0.5098 loss_thr: 0.3694 loss_db: 0.0881 2022/10/26 06:11:19 - mmengine - INFO - Epoch(train) [858][60/63] lr: 1.1433e-03 eta: 4:12:30 time: 0.5692 data_time: 0.0181 memory: 16131 loss: 1.1096 loss_prob: 0.5881 loss_thr: 0.4208 loss_db: 0.1007 2022/10/26 06:11:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:11:25 - mmengine - INFO - Epoch(train) [859][5/63] lr: 1.1403e-03 eta: 4:12:30 time: 0.6499 data_time: 0.1659 memory: 16131 loss: 1.1049 loss_prob: 0.5732 loss_thr: 0.4327 loss_db: 0.0990 2022/10/26 06:11:28 - mmengine - INFO - Epoch(train) [859][10/63] lr: 1.1403e-03 eta: 4:12:20 time: 0.7043 data_time: 0.1831 memory: 16131 loss: 1.1346 loss_prob: 0.6028 loss_thr: 0.4271 loss_db: 0.1047 2022/10/26 06:11:30 - mmengine - INFO - Epoch(train) [859][15/63] lr: 1.1403e-03 eta: 4:12:20 time: 0.5599 data_time: 0.0238 memory: 16131 loss: 1.1218 loss_prob: 0.6014 loss_thr: 0.4173 loss_db: 0.1031 2022/10/26 06:11:33 - mmengine - INFO - Epoch(train) [859][20/63] lr: 1.1403e-03 eta: 4:12:12 time: 0.5628 data_time: 0.0074 memory: 16131 loss: 1.0036 loss_prob: 0.5305 loss_thr: 0.3828 loss_db: 0.0903 2022/10/26 06:11:36 - mmengine - INFO - Epoch(train) [859][25/63] lr: 1.1403e-03 eta: 4:12:12 time: 0.5605 data_time: 0.0102 memory: 16131 loss: 1.0337 loss_prob: 0.5469 loss_thr: 0.3916 loss_db: 0.0951 2022/10/26 06:11:39 - mmengine - INFO - Epoch(train) [859][30/63] lr: 1.1403e-03 eta: 4:12:05 time: 0.5301 data_time: 0.0212 memory: 16131 loss: 1.0236 loss_prob: 0.5330 loss_thr: 0.3984 loss_db: 0.0923 2022/10/26 06:11:41 - mmengine - INFO - Epoch(train) [859][35/63] lr: 1.1403e-03 eta: 4:12:05 time: 0.5114 data_time: 0.0309 memory: 16131 loss: 1.0618 loss_prob: 0.5632 loss_thr: 0.4022 loss_db: 0.0964 2022/10/26 06:11:44 - mmengine - INFO - Epoch(train) [859][40/63] lr: 1.1403e-03 eta: 4:11:57 time: 0.5008 data_time: 0.0177 memory: 16131 loss: 1.1354 loss_prob: 0.6011 loss_thr: 0.4298 loss_db: 0.1045 2022/10/26 06:11:46 - mmengine - INFO - Epoch(train) [859][45/63] lr: 1.1403e-03 eta: 4:11:57 time: 0.4891 data_time: 0.0058 memory: 16131 loss: 1.0953 loss_prob: 0.5710 loss_thr: 0.4247 loss_db: 0.0996 2022/10/26 06:11:49 - mmengine - INFO - Epoch(train) [859][50/63] lr: 1.1403e-03 eta: 4:11:49 time: 0.5262 data_time: 0.0130 memory: 16131 loss: 1.0249 loss_prob: 0.5383 loss_thr: 0.3939 loss_db: 0.0926 2022/10/26 06:11:52 - mmengine - INFO - Epoch(train) [859][55/63] lr: 1.1403e-03 eta: 4:11:49 time: 0.5679 data_time: 0.0215 memory: 16131 loss: 0.9775 loss_prob: 0.5047 loss_thr: 0.3862 loss_db: 0.0867 2022/10/26 06:11:54 - mmengine - INFO - Epoch(train) [859][60/63] lr: 1.1403e-03 eta: 4:11:41 time: 0.5348 data_time: 0.0191 memory: 16131 loss: 0.9980 loss_prob: 0.5224 loss_thr: 0.3866 loss_db: 0.0890 2022/10/26 06:11:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:12:01 - mmengine - INFO - Epoch(train) [860][5/63] lr: 1.1373e-03 eta: 4:11:41 time: 0.7395 data_time: 0.2075 memory: 16131 loss: 0.9833 loss_prob: 0.5175 loss_thr: 0.3770 loss_db: 0.0888 2022/10/26 06:12:03 - mmengine - INFO - Epoch(train) [860][10/63] lr: 1.1373e-03 eta: 4:11:32 time: 0.7446 data_time: 0.2078 memory: 16131 loss: 0.9521 loss_prob: 0.4995 loss_thr: 0.3675 loss_db: 0.0850 2022/10/26 06:12:06 - mmengine - INFO - Epoch(train) [860][15/63] lr: 1.1373e-03 eta: 4:11:32 time: 0.5024 data_time: 0.0058 memory: 16131 loss: 0.9688 loss_prob: 0.5044 loss_thr: 0.3778 loss_db: 0.0866 2022/10/26 06:12:08 - mmengine - INFO - Epoch(train) [860][20/63] lr: 1.1373e-03 eta: 4:11:24 time: 0.5444 data_time: 0.0068 memory: 16131 loss: 0.9972 loss_prob: 0.5205 loss_thr: 0.3846 loss_db: 0.0921 2022/10/26 06:12:11 - mmengine - INFO - Epoch(train) [860][25/63] lr: 1.1373e-03 eta: 4:11:24 time: 0.5736 data_time: 0.0270 memory: 16131 loss: 0.9610 loss_prob: 0.4938 loss_thr: 0.3799 loss_db: 0.0872 2022/10/26 06:12:14 - mmengine - INFO - Epoch(train) [860][30/63] lr: 1.1373e-03 eta: 4:11:17 time: 0.5832 data_time: 0.0342 memory: 16131 loss: 1.0253 loss_prob: 0.5381 loss_thr: 0.3956 loss_db: 0.0916 2022/10/26 06:12:17 - mmengine - INFO - Epoch(train) [860][35/63] lr: 1.1373e-03 eta: 4:11:17 time: 0.5824 data_time: 0.0149 memory: 16131 loss: 1.1138 loss_prob: 0.5987 loss_thr: 0.4140 loss_db: 0.1011 2022/10/26 06:12:20 - mmengine - INFO - Epoch(train) [860][40/63] lr: 1.1373e-03 eta: 4:11:09 time: 0.5318 data_time: 0.0078 memory: 16131 loss: 1.0264 loss_prob: 0.5461 loss_thr: 0.3858 loss_db: 0.0944 2022/10/26 06:12:22 - mmengine - INFO - Epoch(train) [860][45/63] lr: 1.1373e-03 eta: 4:11:09 time: 0.5006 data_time: 0.0070 memory: 16131 loss: 1.0097 loss_prob: 0.5373 loss_thr: 0.3795 loss_db: 0.0930 2022/10/26 06:12:25 - mmengine - INFO - Epoch(train) [860][50/63] lr: 1.1373e-03 eta: 4:11:01 time: 0.5161 data_time: 0.0161 memory: 16131 loss: 1.0168 loss_prob: 0.5371 loss_thr: 0.3872 loss_db: 0.0925 2022/10/26 06:12:28 - mmengine - INFO - Epoch(train) [860][55/63] lr: 1.1373e-03 eta: 4:11:01 time: 0.5982 data_time: 0.0196 memory: 16131 loss: 0.9895 loss_prob: 0.5234 loss_thr: 0.3771 loss_db: 0.0890 2022/10/26 06:12:31 - mmengine - INFO - Epoch(train) [860][60/63] lr: 1.1373e-03 eta: 4:10:54 time: 0.6174 data_time: 0.0106 memory: 16131 loss: 0.9991 loss_prob: 0.5280 loss_thr: 0.3827 loss_db: 0.0883 2022/10/26 06:12:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:12:32 - mmengine - INFO - Saving checkpoint at 860 epochs 2022/10/26 06:12:39 - mmengine - INFO - Epoch(val) [860][5/32] eta: 4:10:54 time: 0.5115 data_time: 0.0645 memory: 16131 2022/10/26 06:12:42 - mmengine - INFO - Epoch(val) [860][10/32] eta: 0:00:12 time: 0.5806 data_time: 0.0921 memory: 15724 2022/10/26 06:12:44 - mmengine - INFO - Epoch(val) [860][15/32] eta: 0:00:12 time: 0.5465 data_time: 0.0432 memory: 15724 2022/10/26 06:12:47 - mmengine - INFO - Epoch(val) [860][20/32] eta: 0:00:06 time: 0.5435 data_time: 0.0438 memory: 15724 2022/10/26 06:12:50 - mmengine - INFO - Epoch(val) [860][25/32] eta: 0:00:06 time: 0.5468 data_time: 0.0493 memory: 15724 2022/10/26 06:12:52 - mmengine - INFO - Epoch(val) [860][30/32] eta: 0:00:01 time: 0.5068 data_time: 0.0193 memory: 15724 2022/10/26 06:12:53 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8426, precision: 0.7572, hmean: 0.7976 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8426, precision: 0.8102, hmean: 0.8261 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8421, precision: 0.8393, hmean: 0.8407 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8392, precision: 0.8650, hmean: 0.8519 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8228, precision: 0.8948, hmean: 0.8573 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7328, precision: 0.9303, hmean: 0.8198 2022/10/26 06:12:53 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1358, precision: 0.9965, hmean: 0.2390 2022/10/26 06:12:53 - mmengine - INFO - Epoch(val) [860][32/32] icdar/precision: 0.8948 icdar/recall: 0.8228 icdar/hmean: 0.8573 2022/10/26 06:12:58 - mmengine - INFO - Epoch(train) [861][5/63] lr: 1.1343e-03 eta: 0:00:01 time: 0.7120 data_time: 0.1949 memory: 16131 loss: 1.0657 loss_prob: 0.5619 loss_thr: 0.4059 loss_db: 0.0978 2022/10/26 06:13:00 - mmengine - INFO - Epoch(train) [861][10/63] lr: 1.1343e-03 eta: 4:10:44 time: 0.7406 data_time: 0.1978 memory: 16131 loss: 0.9556 loss_prob: 0.5018 loss_thr: 0.3671 loss_db: 0.0867 2022/10/26 06:13:03 - mmengine - INFO - Epoch(train) [861][15/63] lr: 1.1343e-03 eta: 4:10:44 time: 0.5139 data_time: 0.0081 memory: 16131 loss: 0.9710 loss_prob: 0.5090 loss_thr: 0.3756 loss_db: 0.0864 2022/10/26 06:13:06 - mmengine - INFO - Epoch(train) [861][20/63] lr: 1.1343e-03 eta: 4:10:36 time: 0.5333 data_time: 0.0047 memory: 16131 loss: 0.9991 loss_prob: 0.5217 loss_thr: 0.3859 loss_db: 0.0915 2022/10/26 06:13:09 - mmengine - INFO - Epoch(train) [861][25/63] lr: 1.1343e-03 eta: 4:10:36 time: 0.5922 data_time: 0.0297 memory: 16131 loss: 0.9946 loss_prob: 0.5238 loss_thr: 0.3777 loss_db: 0.0931 2022/10/26 06:13:11 - mmengine - INFO - Epoch(train) [861][30/63] lr: 1.1343e-03 eta: 4:10:29 time: 0.5663 data_time: 0.0308 memory: 16131 loss: 1.0012 loss_prob: 0.5308 loss_thr: 0.3776 loss_db: 0.0928 2022/10/26 06:13:14 - mmengine - INFO - Epoch(train) [861][35/63] lr: 1.1343e-03 eta: 4:10:29 time: 0.5304 data_time: 0.0080 memory: 16131 loss: 1.0760 loss_prob: 0.5919 loss_thr: 0.3855 loss_db: 0.0986 2022/10/26 06:13:17 - mmengine - INFO - Epoch(train) [861][40/63] lr: 1.1343e-03 eta: 4:10:21 time: 0.5555 data_time: 0.0070 memory: 16131 loss: 1.0777 loss_prob: 0.5920 loss_thr: 0.3886 loss_db: 0.0971 2022/10/26 06:13:19 - mmengine - INFO - Epoch(train) [861][45/63] lr: 1.1343e-03 eta: 4:10:21 time: 0.5252 data_time: 0.0051 memory: 16131 loss: 1.0713 loss_prob: 0.5659 loss_thr: 0.4089 loss_db: 0.0966 2022/10/26 06:13:22 - mmengine - INFO - Epoch(train) [861][50/63] lr: 1.1343e-03 eta: 4:10:13 time: 0.5250 data_time: 0.0205 memory: 16131 loss: 1.0889 loss_prob: 0.5692 loss_thr: 0.4196 loss_db: 0.1001 2022/10/26 06:13:24 - mmengine - INFO - Epoch(train) [861][55/63] lr: 1.1343e-03 eta: 4:10:13 time: 0.5084 data_time: 0.0218 memory: 16131 loss: 1.1040 loss_prob: 0.5893 loss_thr: 0.4110 loss_db: 0.1038 2022/10/26 06:13:27 - mmengine - INFO - Epoch(train) [861][60/63] lr: 1.1343e-03 eta: 4:10:05 time: 0.4852 data_time: 0.0095 memory: 16131 loss: 1.1555 loss_prob: 0.6230 loss_thr: 0.4245 loss_db: 0.1080 2022/10/26 06:13:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:13:33 - mmengine - INFO - Epoch(train) [862][5/63] lr: 1.1313e-03 eta: 4:10:05 time: 0.6866 data_time: 0.1865 memory: 16131 loss: 0.9884 loss_prob: 0.5209 loss_thr: 0.3781 loss_db: 0.0894 2022/10/26 06:13:35 - mmengine - INFO - Epoch(train) [862][10/63] lr: 1.1313e-03 eta: 4:09:55 time: 0.7138 data_time: 0.1947 memory: 16131 loss: 1.0094 loss_prob: 0.5253 loss_thr: 0.3917 loss_db: 0.0924 2022/10/26 06:13:38 - mmengine - INFO - Epoch(train) [862][15/63] lr: 1.1313e-03 eta: 4:09:55 time: 0.4876 data_time: 0.0148 memory: 16131 loss: 1.0261 loss_prob: 0.5451 loss_thr: 0.3872 loss_db: 0.0938 2022/10/26 06:13:40 - mmengine - INFO - Epoch(train) [862][20/63] lr: 1.1313e-03 eta: 4:09:48 time: 0.4935 data_time: 0.0079 memory: 16131 loss: 0.9691 loss_prob: 0.5176 loss_thr: 0.3648 loss_db: 0.0867 2022/10/26 06:13:43 - mmengine - INFO - Epoch(train) [862][25/63] lr: 1.1313e-03 eta: 4:09:48 time: 0.5026 data_time: 0.0084 memory: 16131 loss: 0.9564 loss_prob: 0.5017 loss_thr: 0.3681 loss_db: 0.0865 2022/10/26 06:13:46 - mmengine - INFO - Epoch(train) [862][30/63] lr: 1.1313e-03 eta: 4:09:40 time: 0.5475 data_time: 0.0394 memory: 16131 loss: 1.0129 loss_prob: 0.5313 loss_thr: 0.3899 loss_db: 0.0917 2022/10/26 06:13:49 - mmengine - INFO - Epoch(train) [862][35/63] lr: 1.1313e-03 eta: 4:09:40 time: 0.5837 data_time: 0.0463 memory: 16131 loss: 0.9798 loss_prob: 0.5022 loss_thr: 0.3903 loss_db: 0.0872 2022/10/26 06:13:51 - mmengine - INFO - Epoch(train) [862][40/63] lr: 1.1313e-03 eta: 4:09:32 time: 0.5364 data_time: 0.0135 memory: 16131 loss: 0.9493 loss_prob: 0.4880 loss_thr: 0.3753 loss_db: 0.0860 2022/10/26 06:13:54 - mmengine - INFO - Epoch(train) [862][45/63] lr: 1.1313e-03 eta: 4:09:32 time: 0.5067 data_time: 0.0053 memory: 16131 loss: 0.9690 loss_prob: 0.5086 loss_thr: 0.3728 loss_db: 0.0877 2022/10/26 06:13:56 - mmengine - INFO - Epoch(train) [862][50/63] lr: 1.1313e-03 eta: 4:09:25 time: 0.5459 data_time: 0.0174 memory: 16131 loss: 0.9891 loss_prob: 0.5151 loss_thr: 0.3848 loss_db: 0.0893 2022/10/26 06:13:59 - mmengine - INFO - Epoch(train) [862][55/63] lr: 1.1313e-03 eta: 4:09:25 time: 0.5427 data_time: 0.0185 memory: 16131 loss: 1.0502 loss_prob: 0.5479 loss_thr: 0.4061 loss_db: 0.0962 2022/10/26 06:14:02 - mmengine - INFO - Epoch(train) [862][60/63] lr: 1.1313e-03 eta: 4:09:17 time: 0.5066 data_time: 0.0091 memory: 16131 loss: 1.0198 loss_prob: 0.5328 loss_thr: 0.3930 loss_db: 0.0940 2022/10/26 06:14:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:14:08 - mmengine - INFO - Epoch(train) [863][5/63] lr: 1.1282e-03 eta: 4:09:17 time: 0.7911 data_time: 0.1709 memory: 16131 loss: 1.0475 loss_prob: 0.5661 loss_thr: 0.3843 loss_db: 0.0971 2022/10/26 06:14:11 - mmengine - INFO - Epoch(train) [863][10/63] lr: 1.1282e-03 eta: 4:09:07 time: 0.7989 data_time: 0.1703 memory: 16131 loss: 0.9966 loss_prob: 0.5245 loss_thr: 0.3800 loss_db: 0.0920 2022/10/26 06:14:14 - mmengine - INFO - Epoch(train) [863][15/63] lr: 1.1282e-03 eta: 4:09:07 time: 0.5332 data_time: 0.0080 memory: 16131 loss: 0.9776 loss_prob: 0.5164 loss_thr: 0.3721 loss_db: 0.0891 2022/10/26 06:14:16 - mmengine - INFO - Epoch(train) [863][20/63] lr: 1.1282e-03 eta: 4:09:00 time: 0.5249 data_time: 0.0089 memory: 16131 loss: 0.9972 loss_prob: 0.5214 loss_thr: 0.3854 loss_db: 0.0904 2022/10/26 06:14:19 - mmengine - INFO - Epoch(train) [863][25/63] lr: 1.1282e-03 eta: 4:09:00 time: 0.5178 data_time: 0.0172 memory: 16131 loss: 0.9948 loss_prob: 0.5195 loss_thr: 0.3845 loss_db: 0.0908 2022/10/26 06:14:22 - mmengine - INFO - Epoch(train) [863][30/63] lr: 1.1282e-03 eta: 4:08:52 time: 0.5298 data_time: 0.0265 memory: 16131 loss: 0.9713 loss_prob: 0.5096 loss_thr: 0.3740 loss_db: 0.0878 2022/10/26 06:14:24 - mmengine - INFO - Epoch(train) [863][35/63] lr: 1.1282e-03 eta: 4:08:52 time: 0.5556 data_time: 0.0194 memory: 16131 loss: 1.0001 loss_prob: 0.5292 loss_thr: 0.3796 loss_db: 0.0913 2022/10/26 06:14:27 - mmengine - INFO - Epoch(train) [863][40/63] lr: 1.1282e-03 eta: 4:08:44 time: 0.5805 data_time: 0.0147 memory: 16131 loss: 1.0420 loss_prob: 0.5489 loss_thr: 0.3968 loss_db: 0.0963 2022/10/26 06:14:30 - mmengine - INFO - Epoch(train) [863][45/63] lr: 1.1282e-03 eta: 4:08:44 time: 0.5443 data_time: 0.0129 memory: 16131 loss: 1.1790 loss_prob: 0.6348 loss_thr: 0.4369 loss_db: 0.1073 2022/10/26 06:14:33 - mmengine - INFO - Epoch(train) [863][50/63] lr: 1.1282e-03 eta: 4:08:37 time: 0.5171 data_time: 0.0205 memory: 16131 loss: 1.1653 loss_prob: 0.6327 loss_thr: 0.4259 loss_db: 0.1067 2022/10/26 06:14:35 - mmengine - INFO - Epoch(train) [863][55/63] lr: 1.1282e-03 eta: 4:08:37 time: 0.5139 data_time: 0.0191 memory: 16131 loss: 1.1046 loss_prob: 0.5955 loss_thr: 0.4054 loss_db: 0.1037 2022/10/26 06:14:38 - mmengine - INFO - Epoch(train) [863][60/63] lr: 1.1282e-03 eta: 4:08:29 time: 0.5258 data_time: 0.0067 memory: 16131 loss: 1.1791 loss_prob: 0.6545 loss_thr: 0.4175 loss_db: 0.1071 2022/10/26 06:14:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:14:44 - mmengine - INFO - Epoch(train) [864][5/63] lr: 1.1252e-03 eta: 4:08:29 time: 0.7313 data_time: 0.1871 memory: 16131 loss: 1.1457 loss_prob: 0.6149 loss_thr: 0.4286 loss_db: 0.1021 2022/10/26 06:14:47 - mmengine - INFO - Epoch(train) [864][10/63] lr: 1.1252e-03 eta: 4:08:19 time: 0.7534 data_time: 0.1878 memory: 16131 loss: 1.0366 loss_prob: 0.5464 loss_thr: 0.3950 loss_db: 0.0952 2022/10/26 06:14:49 - mmengine - INFO - Epoch(train) [864][15/63] lr: 1.1252e-03 eta: 4:08:19 time: 0.5404 data_time: 0.0090 memory: 16131 loss: 0.9836 loss_prob: 0.5156 loss_thr: 0.3801 loss_db: 0.0879 2022/10/26 06:14:52 - mmengine - INFO - Epoch(train) [864][20/63] lr: 1.1252e-03 eta: 4:08:11 time: 0.5313 data_time: 0.0067 memory: 16131 loss: 1.0290 loss_prob: 0.5494 loss_thr: 0.3865 loss_db: 0.0932 2022/10/26 06:14:55 - mmengine - INFO - Epoch(train) [864][25/63] lr: 1.1252e-03 eta: 4:08:11 time: 0.5392 data_time: 0.0188 memory: 16131 loss: 1.0214 loss_prob: 0.5435 loss_thr: 0.3834 loss_db: 0.0945 2022/10/26 06:14:57 - mmengine - INFO - Epoch(train) [864][30/63] lr: 1.1252e-03 eta: 4:08:04 time: 0.5210 data_time: 0.0304 memory: 16131 loss: 0.9249 loss_prob: 0.4836 loss_thr: 0.3556 loss_db: 0.0857 2022/10/26 06:15:00 - mmengine - INFO - Epoch(train) [864][35/63] lr: 1.1252e-03 eta: 4:08:04 time: 0.5394 data_time: 0.0193 memory: 16131 loss: 0.9059 loss_prob: 0.4733 loss_thr: 0.3511 loss_db: 0.0815 2022/10/26 06:15:03 - mmengine - INFO - Epoch(train) [864][40/63] lr: 1.1252e-03 eta: 4:07:56 time: 0.5537 data_time: 0.0070 memory: 16131 loss: 0.9507 loss_prob: 0.4947 loss_thr: 0.3704 loss_db: 0.0856 2022/10/26 06:15:05 - mmengine - INFO - Epoch(train) [864][45/63] lr: 1.1252e-03 eta: 4:07:56 time: 0.5146 data_time: 0.0046 memory: 16131 loss: 1.0151 loss_prob: 0.5360 loss_thr: 0.3859 loss_db: 0.0932 2022/10/26 06:15:08 - mmengine - INFO - Epoch(train) [864][50/63] lr: 1.1252e-03 eta: 4:07:48 time: 0.5125 data_time: 0.0152 memory: 16131 loss: 1.0318 loss_prob: 0.5472 loss_thr: 0.3910 loss_db: 0.0936 2022/10/26 06:15:11 - mmengine - INFO - Epoch(train) [864][55/63] lr: 1.1252e-03 eta: 4:07:48 time: 0.5138 data_time: 0.0226 memory: 16131 loss: 1.0353 loss_prob: 0.5405 loss_thr: 0.4040 loss_db: 0.0909 2022/10/26 06:15:13 - mmengine - INFO - Epoch(train) [864][60/63] lr: 1.1252e-03 eta: 4:07:41 time: 0.5435 data_time: 0.0123 memory: 16131 loss: 1.0684 loss_prob: 0.5596 loss_thr: 0.4147 loss_db: 0.0940 2022/10/26 06:15:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:15:20 - mmengine - INFO - Epoch(train) [865][5/63] lr: 1.1222e-03 eta: 4:07:41 time: 0.7341 data_time: 0.2271 memory: 16131 loss: 1.0120 loss_prob: 0.5379 loss_thr: 0.3808 loss_db: 0.0933 2022/10/26 06:15:22 - mmengine - INFO - Epoch(train) [865][10/63] lr: 1.1222e-03 eta: 4:07:31 time: 0.7292 data_time: 0.2268 memory: 16131 loss: 0.9179 loss_prob: 0.4735 loss_thr: 0.3620 loss_db: 0.0824 2022/10/26 06:15:25 - mmengine - INFO - Epoch(train) [865][15/63] lr: 1.1222e-03 eta: 4:07:31 time: 0.4992 data_time: 0.0088 memory: 16131 loss: 0.9693 loss_prob: 0.4947 loss_thr: 0.3893 loss_db: 0.0853 2022/10/26 06:15:27 - mmengine - INFO - Epoch(train) [865][20/63] lr: 1.1222e-03 eta: 4:07:23 time: 0.5280 data_time: 0.0090 memory: 16131 loss: 0.9771 loss_prob: 0.5043 loss_thr: 0.3840 loss_db: 0.0889 2022/10/26 06:15:30 - mmengine - INFO - Epoch(train) [865][25/63] lr: 1.1222e-03 eta: 4:07:23 time: 0.5587 data_time: 0.0237 memory: 16131 loss: 0.9750 loss_prob: 0.5178 loss_thr: 0.3648 loss_db: 0.0925 2022/10/26 06:15:33 - mmengine - INFO - Epoch(train) [865][30/63] lr: 1.1222e-03 eta: 4:07:16 time: 0.5637 data_time: 0.0380 memory: 16131 loss: 0.9910 loss_prob: 0.5264 loss_thr: 0.3738 loss_db: 0.0908 2022/10/26 06:15:36 - mmengine - INFO - Epoch(train) [865][35/63] lr: 1.1222e-03 eta: 4:07:16 time: 0.5722 data_time: 0.0198 memory: 16131 loss: 1.0483 loss_prob: 0.5509 loss_thr: 0.4029 loss_db: 0.0945 2022/10/26 06:15:39 - mmengine - INFO - Epoch(train) [865][40/63] lr: 1.1222e-03 eta: 4:07:08 time: 0.5942 data_time: 0.0051 memory: 16131 loss: 1.1597 loss_prob: 0.6265 loss_thr: 0.4275 loss_db: 0.1057 2022/10/26 06:15:42 - mmengine - INFO - Epoch(train) [865][45/63] lr: 1.1222e-03 eta: 4:07:08 time: 0.5637 data_time: 0.0055 memory: 16131 loss: 1.1555 loss_prob: 0.6318 loss_thr: 0.4188 loss_db: 0.1049 2022/10/26 06:15:44 - mmengine - INFO - Epoch(train) [865][50/63] lr: 1.1222e-03 eta: 4:07:01 time: 0.5215 data_time: 0.0146 memory: 16131 loss: 1.0689 loss_prob: 0.5684 loss_thr: 0.4019 loss_db: 0.0986 2022/10/26 06:15:47 - mmengine - INFO - Epoch(train) [865][55/63] lr: 1.1222e-03 eta: 4:07:01 time: 0.5281 data_time: 0.0233 memory: 16131 loss: 1.0420 loss_prob: 0.5532 loss_thr: 0.3925 loss_db: 0.0963 2022/10/26 06:15:50 - mmengine - INFO - Epoch(train) [865][60/63] lr: 1.1222e-03 eta: 4:06:53 time: 0.5363 data_time: 0.0138 memory: 16131 loss: 1.0205 loss_prob: 0.5427 loss_thr: 0.3835 loss_db: 0.0943 2022/10/26 06:15:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:15:55 - mmengine - INFO - Epoch(train) [866][5/63] lr: 1.1192e-03 eta: 4:06:53 time: 0.6945 data_time: 0.1568 memory: 16131 loss: 0.8666 loss_prob: 0.4397 loss_thr: 0.3496 loss_db: 0.0773 2022/10/26 06:15:58 - mmengine - INFO - Epoch(train) [866][10/63] lr: 1.1192e-03 eta: 4:06:43 time: 0.7224 data_time: 0.1657 memory: 16131 loss: 0.8885 loss_prob: 0.4458 loss_thr: 0.3631 loss_db: 0.0796 2022/10/26 06:16:01 - mmengine - INFO - Epoch(train) [866][15/63] lr: 1.1192e-03 eta: 4:06:43 time: 0.5130 data_time: 0.0158 memory: 16131 loss: 0.9984 loss_prob: 0.5240 loss_thr: 0.3827 loss_db: 0.0917 2022/10/26 06:16:03 - mmengine - INFO - Epoch(train) [866][20/63] lr: 1.1192e-03 eta: 4:06:35 time: 0.5090 data_time: 0.0072 memory: 16131 loss: 1.0494 loss_prob: 0.5566 loss_thr: 0.3970 loss_db: 0.0958 2022/10/26 06:16:06 - mmengine - INFO - Epoch(train) [866][25/63] lr: 1.1192e-03 eta: 4:06:35 time: 0.5460 data_time: 0.0242 memory: 16131 loss: 1.1283 loss_prob: 0.6026 loss_thr: 0.4204 loss_db: 0.1052 2022/10/26 06:16:09 - mmengine - INFO - Epoch(train) [866][30/63] lr: 1.1192e-03 eta: 4:06:28 time: 0.5376 data_time: 0.0315 memory: 16131 loss: 1.0809 loss_prob: 0.5826 loss_thr: 0.3963 loss_db: 0.1020 2022/10/26 06:16:11 - mmengine - INFO - Epoch(train) [866][35/63] lr: 1.1192e-03 eta: 4:06:28 time: 0.5091 data_time: 0.0178 memory: 16131 loss: 1.0136 loss_prob: 0.5520 loss_thr: 0.3708 loss_db: 0.0908 2022/10/26 06:16:14 - mmengine - INFO - Epoch(train) [866][40/63] lr: 1.1192e-03 eta: 4:06:20 time: 0.5051 data_time: 0.0085 memory: 16131 loss: 0.9986 loss_prob: 0.5439 loss_thr: 0.3660 loss_db: 0.0886 2022/10/26 06:16:16 - mmengine - INFO - Epoch(train) [866][45/63] lr: 1.1192e-03 eta: 4:06:20 time: 0.5189 data_time: 0.0070 memory: 16131 loss: 0.9451 loss_prob: 0.4947 loss_thr: 0.3659 loss_db: 0.0846 2022/10/26 06:16:19 - mmengine - INFO - Epoch(train) [866][50/63] lr: 1.1192e-03 eta: 4:06:12 time: 0.5160 data_time: 0.0174 memory: 16131 loss: 0.9845 loss_prob: 0.5182 loss_thr: 0.3769 loss_db: 0.0893 2022/10/26 06:16:21 - mmengine - INFO - Epoch(train) [866][55/63] lr: 1.1192e-03 eta: 4:06:12 time: 0.5184 data_time: 0.0238 memory: 16131 loss: 1.0297 loss_prob: 0.5555 loss_thr: 0.3788 loss_db: 0.0955 2022/10/26 06:16:24 - mmengine - INFO - Epoch(train) [866][60/63] lr: 1.1192e-03 eta: 4:06:04 time: 0.5286 data_time: 0.0159 memory: 16131 loss: 1.0371 loss_prob: 0.5619 loss_thr: 0.3781 loss_db: 0.0972 2022/10/26 06:16:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:16:30 - mmengine - INFO - Epoch(train) [867][5/63] lr: 1.1162e-03 eta: 4:06:04 time: 0.6721 data_time: 0.1883 memory: 16131 loss: 1.0281 loss_prob: 0.5524 loss_thr: 0.3802 loss_db: 0.0955 2022/10/26 06:16:33 - mmengine - INFO - Epoch(train) [867][10/63] lr: 1.1162e-03 eta: 4:05:55 time: 0.7217 data_time: 0.1878 memory: 16131 loss: 0.9508 loss_prob: 0.4989 loss_thr: 0.3660 loss_db: 0.0858 2022/10/26 06:16:35 - mmengine - INFO - Epoch(train) [867][15/63] lr: 1.1162e-03 eta: 4:05:55 time: 0.5358 data_time: 0.0053 memory: 16131 loss: 0.9346 loss_prob: 0.4870 loss_thr: 0.3643 loss_db: 0.0833 2022/10/26 06:16:38 - mmengine - INFO - Epoch(train) [867][20/63] lr: 1.1162e-03 eta: 4:05:47 time: 0.5010 data_time: 0.0049 memory: 16131 loss: 0.9942 loss_prob: 0.5171 loss_thr: 0.3875 loss_db: 0.0897 2022/10/26 06:16:41 - mmengine - INFO - Epoch(train) [867][25/63] lr: 1.1162e-03 eta: 4:05:47 time: 0.5499 data_time: 0.0464 memory: 16131 loss: 1.0266 loss_prob: 0.5381 loss_thr: 0.3932 loss_db: 0.0953 2022/10/26 06:16:43 - mmengine - INFO - Epoch(train) [867][30/63] lr: 1.1162e-03 eta: 4:05:39 time: 0.5547 data_time: 0.0472 memory: 16131 loss: 1.0348 loss_prob: 0.5509 loss_thr: 0.3878 loss_db: 0.0961 2022/10/26 06:16:46 - mmengine - INFO - Epoch(train) [867][35/63] lr: 1.1162e-03 eta: 4:05:39 time: 0.5097 data_time: 0.0067 memory: 16131 loss: 1.0474 loss_prob: 0.5532 loss_thr: 0.3979 loss_db: 0.0964 2022/10/26 06:16:48 - mmengine - INFO - Epoch(train) [867][40/63] lr: 1.1162e-03 eta: 4:05:31 time: 0.5232 data_time: 0.0058 memory: 16131 loss: 1.0798 loss_prob: 0.5705 loss_thr: 0.4073 loss_db: 0.1020 2022/10/26 06:16:51 - mmengine - INFO - Epoch(train) [867][45/63] lr: 1.1162e-03 eta: 4:05:31 time: 0.5465 data_time: 0.0052 memory: 16131 loss: 1.0963 loss_prob: 0.5774 loss_thr: 0.4191 loss_db: 0.0998 2022/10/26 06:16:54 - mmengine - INFO - Epoch(train) [867][50/63] lr: 1.1162e-03 eta: 4:05:24 time: 0.5503 data_time: 0.0231 memory: 16131 loss: 1.0328 loss_prob: 0.5384 loss_thr: 0.4038 loss_db: 0.0905 2022/10/26 06:16:56 - mmengine - INFO - Epoch(train) [867][55/63] lr: 1.1162e-03 eta: 4:05:24 time: 0.5329 data_time: 0.0234 memory: 16131 loss: 0.9952 loss_prob: 0.5236 loss_thr: 0.3803 loss_db: 0.0913 2022/10/26 06:16:59 - mmengine - INFO - Epoch(train) [867][60/63] lr: 1.1162e-03 eta: 4:05:16 time: 0.5070 data_time: 0.0065 memory: 16131 loss: 1.0243 loss_prob: 0.5408 loss_thr: 0.3880 loss_db: 0.0956 2022/10/26 06:17:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:17:05 - mmengine - INFO - Epoch(train) [868][5/63] lr: 1.1132e-03 eta: 4:05:16 time: 0.6644 data_time: 0.1645 memory: 16131 loss: 0.9752 loss_prob: 0.5086 loss_thr: 0.3784 loss_db: 0.0882 2022/10/26 06:17:07 - mmengine - INFO - Epoch(train) [868][10/63] lr: 1.1132e-03 eta: 4:05:06 time: 0.6732 data_time: 0.1647 memory: 16131 loss: 0.9530 loss_prob: 0.4976 loss_thr: 0.3690 loss_db: 0.0863 2022/10/26 06:17:10 - mmengine - INFO - Epoch(train) [868][15/63] lr: 1.1132e-03 eta: 4:05:06 time: 0.4998 data_time: 0.0073 memory: 16131 loss: 1.0256 loss_prob: 0.5378 loss_thr: 0.3951 loss_db: 0.0927 2022/10/26 06:17:12 - mmengine - INFO - Epoch(train) [868][20/63] lr: 1.1132e-03 eta: 4:04:58 time: 0.5055 data_time: 0.0108 memory: 16131 loss: 1.1581 loss_prob: 0.6207 loss_thr: 0.4334 loss_db: 0.1040 2022/10/26 06:17:15 - mmengine - INFO - Epoch(train) [868][25/63] lr: 1.1132e-03 eta: 4:04:58 time: 0.5247 data_time: 0.0190 memory: 16131 loss: 1.0910 loss_prob: 0.5851 loss_thr: 0.4055 loss_db: 0.1004 2022/10/26 06:17:18 - mmengine - INFO - Epoch(train) [868][30/63] lr: 1.1132e-03 eta: 4:04:51 time: 0.5489 data_time: 0.0275 memory: 16131 loss: 0.9145 loss_prob: 0.4742 loss_thr: 0.3560 loss_db: 0.0842 2022/10/26 06:17:20 - mmengine - INFO - Epoch(train) [868][35/63] lr: 1.1132e-03 eta: 4:04:51 time: 0.5209 data_time: 0.0182 memory: 16131 loss: 0.9213 loss_prob: 0.4793 loss_thr: 0.3578 loss_db: 0.0843 2022/10/26 06:17:23 - mmengine - INFO - Epoch(train) [868][40/63] lr: 1.1132e-03 eta: 4:04:43 time: 0.5060 data_time: 0.0081 memory: 16131 loss: 1.0341 loss_prob: 0.5410 loss_thr: 0.3997 loss_db: 0.0935 2022/10/26 06:17:25 - mmengine - INFO - Epoch(train) [868][45/63] lr: 1.1132e-03 eta: 4:04:43 time: 0.5027 data_time: 0.0093 memory: 16131 loss: 1.0341 loss_prob: 0.5383 loss_thr: 0.4026 loss_db: 0.0932 2022/10/26 06:17:28 - mmengine - INFO - Epoch(train) [868][50/63] lr: 1.1132e-03 eta: 4:04:35 time: 0.5018 data_time: 0.0125 memory: 16131 loss: 0.9432 loss_prob: 0.4897 loss_thr: 0.3686 loss_db: 0.0850 2022/10/26 06:17:31 - mmengine - INFO - Epoch(train) [868][55/63] lr: 1.1132e-03 eta: 4:04:35 time: 0.5615 data_time: 0.0221 memory: 16131 loss: 0.9593 loss_prob: 0.4979 loss_thr: 0.3764 loss_db: 0.0851 2022/10/26 06:17:33 - mmengine - INFO - Epoch(train) [868][60/63] lr: 1.1132e-03 eta: 4:04:28 time: 0.5706 data_time: 0.0211 memory: 16131 loss: 0.9854 loss_prob: 0.5194 loss_thr: 0.3773 loss_db: 0.0887 2022/10/26 06:17:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:17:40 - mmengine - INFO - Epoch(train) [869][5/63] lr: 1.1102e-03 eta: 4:04:28 time: 0.7307 data_time: 0.2328 memory: 16131 loss: 0.8826 loss_prob: 0.4623 loss_thr: 0.3381 loss_db: 0.0821 2022/10/26 06:17:42 - mmengine - INFO - Epoch(train) [869][10/63] lr: 1.1102e-03 eta: 4:04:18 time: 0.7553 data_time: 0.2326 memory: 16131 loss: 0.9604 loss_prob: 0.5011 loss_thr: 0.3714 loss_db: 0.0879 2022/10/26 06:17:45 - mmengine - INFO - Epoch(train) [869][15/63] lr: 1.1102e-03 eta: 4:04:18 time: 0.5180 data_time: 0.0096 memory: 16131 loss: 1.0716 loss_prob: 0.5807 loss_thr: 0.3945 loss_db: 0.0964 2022/10/26 06:17:47 - mmengine - INFO - Epoch(train) [869][20/63] lr: 1.1102e-03 eta: 4:04:10 time: 0.5187 data_time: 0.0106 memory: 16131 loss: 1.0149 loss_prob: 0.5460 loss_thr: 0.3772 loss_db: 0.0917 2022/10/26 06:17:50 - mmengine - INFO - Epoch(train) [869][25/63] lr: 1.1102e-03 eta: 4:04:10 time: 0.5240 data_time: 0.0325 memory: 16131 loss: 0.9869 loss_prob: 0.5076 loss_thr: 0.3902 loss_db: 0.0891 2022/10/26 06:17:53 - mmengine - INFO - Epoch(train) [869][30/63] lr: 1.1102e-03 eta: 4:04:03 time: 0.5239 data_time: 0.0306 memory: 16131 loss: 1.0542 loss_prob: 0.5622 loss_thr: 0.3961 loss_db: 0.0959 2022/10/26 06:17:55 - mmengine - INFO - Epoch(train) [869][35/63] lr: 1.1102e-03 eta: 4:04:03 time: 0.5004 data_time: 0.0094 memory: 16131 loss: 1.0278 loss_prob: 0.5467 loss_thr: 0.3882 loss_db: 0.0930 2022/10/26 06:17:58 - mmengine - INFO - Epoch(train) [869][40/63] lr: 1.1102e-03 eta: 4:03:55 time: 0.5104 data_time: 0.0078 memory: 16131 loss: 1.0090 loss_prob: 0.5254 loss_thr: 0.3924 loss_db: 0.0912 2022/10/26 06:18:00 - mmengine - INFO - Epoch(train) [869][45/63] lr: 1.1102e-03 eta: 4:03:55 time: 0.5078 data_time: 0.0064 memory: 16131 loss: 1.0204 loss_prob: 0.5355 loss_thr: 0.3912 loss_db: 0.0936 2022/10/26 06:18:03 - mmengine - INFO - Epoch(train) [869][50/63] lr: 1.1102e-03 eta: 4:03:47 time: 0.5089 data_time: 0.0211 memory: 16131 loss: 0.9960 loss_prob: 0.5279 loss_thr: 0.3758 loss_db: 0.0923 2022/10/26 06:18:05 - mmengine - INFO - Epoch(train) [869][55/63] lr: 1.1102e-03 eta: 4:03:47 time: 0.5124 data_time: 0.0248 memory: 16131 loss: 1.0009 loss_prob: 0.5283 loss_thr: 0.3821 loss_db: 0.0905 2022/10/26 06:18:08 - mmengine - INFO - Epoch(train) [869][60/63] lr: 1.1102e-03 eta: 4:03:40 time: 0.5566 data_time: 0.0113 memory: 16131 loss: 0.9942 loss_prob: 0.5202 loss_thr: 0.3874 loss_db: 0.0866 2022/10/26 06:18:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:18:15 - mmengine - INFO - Epoch(train) [870][5/63] lr: 1.1071e-03 eta: 4:03:40 time: 0.7565 data_time: 0.1770 memory: 16131 loss: 1.0685 loss_prob: 0.5673 loss_thr: 0.4041 loss_db: 0.0971 2022/10/26 06:18:18 - mmengine - INFO - Epoch(train) [870][10/63] lr: 1.1071e-03 eta: 4:03:30 time: 0.7573 data_time: 0.1783 memory: 16131 loss: 1.1223 loss_prob: 0.6035 loss_thr: 0.4158 loss_db: 0.1030 2022/10/26 06:18:20 - mmengine - INFO - Epoch(train) [870][15/63] lr: 1.1071e-03 eta: 4:03:30 time: 0.5117 data_time: 0.0101 memory: 16131 loss: 1.0534 loss_prob: 0.5524 loss_thr: 0.4047 loss_db: 0.0963 2022/10/26 06:18:23 - mmengine - INFO - Epoch(train) [870][20/63] lr: 1.1071e-03 eta: 4:03:22 time: 0.5378 data_time: 0.0098 memory: 16131 loss: 0.9783 loss_prob: 0.5102 loss_thr: 0.3788 loss_db: 0.0893 2022/10/26 06:18:25 - mmengine - INFO - Epoch(train) [870][25/63] lr: 1.1071e-03 eta: 4:03:22 time: 0.5432 data_time: 0.0173 memory: 16131 loss: 1.0394 loss_prob: 0.5630 loss_thr: 0.3796 loss_db: 0.0968 2022/10/26 06:18:29 - mmengine - INFO - Epoch(train) [870][30/63] lr: 1.1071e-03 eta: 4:03:15 time: 0.5779 data_time: 0.0376 memory: 16131 loss: 1.0376 loss_prob: 0.5621 loss_thr: 0.3790 loss_db: 0.0965 2022/10/26 06:18:31 - mmengine - INFO - Epoch(train) [870][35/63] lr: 1.1071e-03 eta: 4:03:15 time: 0.5823 data_time: 0.0338 memory: 16131 loss: 1.1021 loss_prob: 0.6008 loss_thr: 0.4007 loss_db: 0.1006 2022/10/26 06:18:34 - mmengine - INFO - Epoch(train) [870][40/63] lr: 1.1071e-03 eta: 4:03:07 time: 0.5037 data_time: 0.0103 memory: 16131 loss: 1.1102 loss_prob: 0.6007 loss_thr: 0.4100 loss_db: 0.0995 2022/10/26 06:18:36 - mmengine - INFO - Epoch(train) [870][45/63] lr: 1.1071e-03 eta: 4:03:07 time: 0.5068 data_time: 0.0061 memory: 16131 loss: 0.9683 loss_prob: 0.5054 loss_thr: 0.3751 loss_db: 0.0878 2022/10/26 06:18:39 - mmengine - INFO - Epoch(train) [870][50/63] lr: 1.1071e-03 eta: 4:02:59 time: 0.5428 data_time: 0.0161 memory: 16131 loss: 0.9941 loss_prob: 0.5246 loss_thr: 0.3758 loss_db: 0.0937 2022/10/26 06:18:42 - mmengine - INFO - Epoch(train) [870][55/63] lr: 1.1071e-03 eta: 4:02:59 time: 0.5589 data_time: 0.0190 memory: 16131 loss: 1.0788 loss_prob: 0.5731 loss_thr: 0.4081 loss_db: 0.0976 2022/10/26 06:18:45 - mmengine - INFO - Epoch(train) [870][60/63] lr: 1.1071e-03 eta: 4:02:52 time: 0.6227 data_time: 0.0120 memory: 16131 loss: 1.1147 loss_prob: 0.5807 loss_thr: 0.4387 loss_db: 0.0953 2022/10/26 06:18:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:18:51 - mmengine - INFO - Epoch(train) [871][5/63] lr: 1.1041e-03 eta: 4:02:52 time: 0.7713 data_time: 0.1728 memory: 16131 loss: 1.0233 loss_prob: 0.5361 loss_thr: 0.3926 loss_db: 0.0947 2022/10/26 06:18:54 - mmengine - INFO - Epoch(train) [871][10/63] lr: 1.1041e-03 eta: 4:02:42 time: 0.7399 data_time: 0.1787 memory: 16131 loss: 0.9158 loss_prob: 0.4701 loss_thr: 0.3629 loss_db: 0.0828 2022/10/26 06:18:56 - mmengine - INFO - Epoch(train) [871][15/63] lr: 1.1041e-03 eta: 4:02:42 time: 0.5215 data_time: 0.0126 memory: 16131 loss: 1.0440 loss_prob: 0.5487 loss_thr: 0.3995 loss_db: 0.0958 2022/10/26 06:18:59 - mmengine - INFO - Epoch(train) [871][20/63] lr: 1.1041e-03 eta: 4:02:35 time: 0.5086 data_time: 0.0067 memory: 16131 loss: 1.0221 loss_prob: 0.5337 loss_thr: 0.3947 loss_db: 0.0937 2022/10/26 06:19:02 - mmengine - INFO - Epoch(train) [871][25/63] lr: 1.1041e-03 eta: 4:02:35 time: 0.5165 data_time: 0.0141 memory: 16131 loss: 0.9615 loss_prob: 0.5000 loss_thr: 0.3741 loss_db: 0.0874 2022/10/26 06:19:04 - mmengine - INFO - Epoch(train) [871][30/63] lr: 1.1041e-03 eta: 4:02:27 time: 0.5216 data_time: 0.0290 memory: 16131 loss: 1.0540 loss_prob: 0.5590 loss_thr: 0.3982 loss_db: 0.0968 2022/10/26 06:19:07 - mmengine - INFO - Epoch(train) [871][35/63] lr: 1.1041e-03 eta: 4:02:27 time: 0.5490 data_time: 0.0343 memory: 16131 loss: 1.0835 loss_prob: 0.5797 loss_thr: 0.4034 loss_db: 0.1004 2022/10/26 06:19:10 - mmengine - INFO - Epoch(train) [871][40/63] lr: 1.1041e-03 eta: 4:02:19 time: 0.5301 data_time: 0.0191 memory: 16131 loss: 1.1325 loss_prob: 0.6196 loss_thr: 0.4069 loss_db: 0.1061 2022/10/26 06:19:12 - mmengine - INFO - Epoch(train) [871][45/63] lr: 1.1041e-03 eta: 4:02:19 time: 0.5272 data_time: 0.0065 memory: 16131 loss: 1.1116 loss_prob: 0.6086 loss_thr: 0.3998 loss_db: 0.1032 2022/10/26 06:19:16 - mmengine - INFO - Epoch(train) [871][50/63] lr: 1.1041e-03 eta: 4:02:12 time: 0.5999 data_time: 0.0114 memory: 16131 loss: 1.0638 loss_prob: 0.5713 loss_thr: 0.3936 loss_db: 0.0989 2022/10/26 06:19:19 - mmengine - INFO - Epoch(train) [871][55/63] lr: 1.1041e-03 eta: 4:02:12 time: 0.6366 data_time: 0.0246 memory: 16131 loss: 1.0248 loss_prob: 0.5468 loss_thr: 0.3834 loss_db: 0.0947 2022/10/26 06:19:21 - mmengine - INFO - Epoch(train) [871][60/63] lr: 1.1041e-03 eta: 4:02:04 time: 0.5656 data_time: 0.0189 memory: 16131 loss: 0.9766 loss_prob: 0.5117 loss_thr: 0.3794 loss_db: 0.0855 2022/10/26 06:19:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:19:28 - mmengine - INFO - Epoch(train) [872][5/63] lr: 1.1011e-03 eta: 4:02:04 time: 0.7605 data_time: 0.2517 memory: 16131 loss: 1.0446 loss_prob: 0.5579 loss_thr: 0.3915 loss_db: 0.0952 2022/10/26 06:19:31 - mmengine - INFO - Epoch(train) [872][10/63] lr: 1.1011e-03 eta: 4:01:55 time: 0.7912 data_time: 0.2527 memory: 16131 loss: 1.0246 loss_prob: 0.5406 loss_thr: 0.3888 loss_db: 0.0952 2022/10/26 06:19:34 - mmengine - INFO - Epoch(train) [872][15/63] lr: 1.1011e-03 eta: 4:01:55 time: 0.5673 data_time: 0.0096 memory: 16131 loss: 0.9517 loss_prob: 0.4950 loss_thr: 0.3686 loss_db: 0.0881 2022/10/26 06:19:36 - mmengine - INFO - Epoch(train) [872][20/63] lr: 1.1011e-03 eta: 4:01:47 time: 0.5498 data_time: 0.0090 memory: 16131 loss: 0.9212 loss_prob: 0.4768 loss_thr: 0.3614 loss_db: 0.0830 2022/10/26 06:19:39 - mmengine - INFO - Epoch(train) [872][25/63] lr: 1.1011e-03 eta: 4:01:47 time: 0.5242 data_time: 0.0266 memory: 16131 loss: 0.9867 loss_prob: 0.5168 loss_thr: 0.3814 loss_db: 0.0886 2022/10/26 06:19:42 - mmengine - INFO - Epoch(train) [872][30/63] lr: 1.1011e-03 eta: 4:01:40 time: 0.5624 data_time: 0.0334 memory: 16131 loss: 1.0029 loss_prob: 0.5298 loss_thr: 0.3803 loss_db: 0.0929 2022/10/26 06:19:44 - mmengine - INFO - Epoch(train) [872][35/63] lr: 1.1011e-03 eta: 4:01:40 time: 0.5430 data_time: 0.0126 memory: 16131 loss: 1.0134 loss_prob: 0.5435 loss_thr: 0.3758 loss_db: 0.0941 2022/10/26 06:19:47 - mmengine - INFO - Epoch(train) [872][40/63] lr: 1.1011e-03 eta: 4:01:32 time: 0.5091 data_time: 0.0060 memory: 16131 loss: 1.0071 loss_prob: 0.5321 loss_thr: 0.3843 loss_db: 0.0907 2022/10/26 06:19:49 - mmengine - INFO - Epoch(train) [872][45/63] lr: 1.1011e-03 eta: 4:01:32 time: 0.5240 data_time: 0.0060 memory: 16131 loss: 0.9838 loss_prob: 0.5067 loss_thr: 0.3882 loss_db: 0.0890 2022/10/26 06:19:52 - mmengine - INFO - Epoch(train) [872][50/63] lr: 1.1011e-03 eta: 4:01:24 time: 0.5251 data_time: 0.0205 memory: 16131 loss: 0.9369 loss_prob: 0.4744 loss_thr: 0.3784 loss_db: 0.0842 2022/10/26 06:19:55 - mmengine - INFO - Epoch(train) [872][55/63] lr: 1.1011e-03 eta: 4:01:24 time: 0.5098 data_time: 0.0215 memory: 16131 loss: 0.9231 loss_prob: 0.4696 loss_thr: 0.3721 loss_db: 0.0814 2022/10/26 06:19:57 - mmengine - INFO - Epoch(train) [872][60/63] lr: 1.1011e-03 eta: 4:01:17 time: 0.5232 data_time: 0.0072 memory: 16131 loss: 1.0465 loss_prob: 0.5565 loss_thr: 0.3932 loss_db: 0.0967 2022/10/26 06:19:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:20:04 - mmengine - INFO - Epoch(train) [873][5/63] lr: 1.0981e-03 eta: 4:01:17 time: 0.7824 data_time: 0.2428 memory: 16131 loss: 1.0649 loss_prob: 0.5597 loss_thr: 0.4083 loss_db: 0.0969 2022/10/26 06:20:07 - mmengine - INFO - Epoch(train) [873][10/63] lr: 1.0981e-03 eta: 4:01:07 time: 0.8690 data_time: 0.2497 memory: 16131 loss: 0.9357 loss_prob: 0.4883 loss_thr: 0.3649 loss_db: 0.0825 2022/10/26 06:20:10 - mmengine - INFO - Epoch(train) [873][15/63] lr: 1.0981e-03 eta: 4:01:07 time: 0.6238 data_time: 0.0136 memory: 16131 loss: 1.0095 loss_prob: 0.5388 loss_thr: 0.3807 loss_db: 0.0900 2022/10/26 06:20:13 - mmengine - INFO - Epoch(train) [873][20/63] lr: 1.0981e-03 eta: 4:01:00 time: 0.5237 data_time: 0.0055 memory: 16131 loss: 0.9860 loss_prob: 0.5292 loss_thr: 0.3661 loss_db: 0.0906 2022/10/26 06:20:15 - mmengine - INFO - Epoch(train) [873][25/63] lr: 1.0981e-03 eta: 4:01:00 time: 0.5046 data_time: 0.0291 memory: 16131 loss: 1.0804 loss_prob: 0.5729 loss_thr: 0.4074 loss_db: 0.1002 2022/10/26 06:20:18 - mmengine - INFO - Epoch(train) [873][30/63] lr: 1.0981e-03 eta: 4:00:52 time: 0.5507 data_time: 0.0392 memory: 16131 loss: 1.0834 loss_prob: 0.5695 loss_thr: 0.4144 loss_db: 0.0995 2022/10/26 06:20:21 - mmengine - INFO - Epoch(train) [873][35/63] lr: 1.0981e-03 eta: 4:00:52 time: 0.5671 data_time: 0.0167 memory: 16131 loss: 0.8913 loss_prob: 0.4517 loss_thr: 0.3617 loss_db: 0.0779 2022/10/26 06:20:23 - mmengine - INFO - Epoch(train) [873][40/63] lr: 1.0981e-03 eta: 4:00:44 time: 0.5279 data_time: 0.0064 memory: 16131 loss: 0.9153 loss_prob: 0.4738 loss_thr: 0.3596 loss_db: 0.0819 2022/10/26 06:20:26 - mmengine - INFO - Epoch(train) [873][45/63] lr: 1.0981e-03 eta: 4:00:44 time: 0.5201 data_time: 0.0079 memory: 16131 loss: 0.9972 loss_prob: 0.5285 loss_thr: 0.3773 loss_db: 0.0914 2022/10/26 06:20:29 - mmengine - INFO - Epoch(train) [873][50/63] lr: 1.0981e-03 eta: 4:00:37 time: 0.5459 data_time: 0.0207 memory: 16131 loss: 1.0541 loss_prob: 0.5620 loss_thr: 0.3968 loss_db: 0.0953 2022/10/26 06:20:32 - mmengine - INFO - Epoch(train) [873][55/63] lr: 1.0981e-03 eta: 4:00:37 time: 0.5504 data_time: 0.0215 memory: 16131 loss: 0.9814 loss_prob: 0.5220 loss_thr: 0.3699 loss_db: 0.0894 2022/10/26 06:20:34 - mmengine - INFO - Epoch(train) [873][60/63] lr: 1.0981e-03 eta: 4:00:29 time: 0.5228 data_time: 0.0109 memory: 16131 loss: 0.8993 loss_prob: 0.4714 loss_thr: 0.3461 loss_db: 0.0818 2022/10/26 06:20:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:20:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:20:40 - mmengine - INFO - Epoch(train) [874][5/63] lr: 1.0950e-03 eta: 4:00:29 time: 0.7133 data_time: 0.2195 memory: 16131 loss: 0.9821 loss_prob: 0.5142 loss_thr: 0.3782 loss_db: 0.0897 2022/10/26 06:20:43 - mmengine - INFO - Epoch(train) [874][10/63] lr: 1.0950e-03 eta: 4:00:20 time: 0.7677 data_time: 0.2181 memory: 16131 loss: 0.9588 loss_prob: 0.4950 loss_thr: 0.3774 loss_db: 0.0865 2022/10/26 06:20:46 - mmengine - INFO - Epoch(train) [874][15/63] lr: 1.0950e-03 eta: 4:00:20 time: 0.5337 data_time: 0.0077 memory: 16131 loss: 0.9895 loss_prob: 0.5155 loss_thr: 0.3836 loss_db: 0.0904 2022/10/26 06:20:48 - mmengine - INFO - Epoch(train) [874][20/63] lr: 1.0950e-03 eta: 4:00:12 time: 0.5070 data_time: 0.0077 memory: 16131 loss: 0.9780 loss_prob: 0.5112 loss_thr: 0.3778 loss_db: 0.0890 2022/10/26 06:20:51 - mmengine - INFO - Epoch(train) [874][25/63] lr: 1.0950e-03 eta: 4:00:12 time: 0.5154 data_time: 0.0243 memory: 16131 loss: 0.9555 loss_prob: 0.5049 loss_thr: 0.3607 loss_db: 0.0899 2022/10/26 06:20:54 - mmengine - INFO - Epoch(train) [874][30/63] lr: 1.0950e-03 eta: 4:00:04 time: 0.5797 data_time: 0.0240 memory: 16131 loss: 1.1004 loss_prob: 0.6027 loss_thr: 0.3938 loss_db: 0.1039 2022/10/26 06:20:56 - mmengine - INFO - Epoch(train) [874][35/63] lr: 1.0950e-03 eta: 4:00:04 time: 0.5505 data_time: 0.0101 memory: 16131 loss: 1.1176 loss_prob: 0.6074 loss_thr: 0.4073 loss_db: 0.1029 2022/10/26 06:20:59 - mmengine - INFO - Epoch(train) [874][40/63] lr: 1.0950e-03 eta: 3:59:57 time: 0.5220 data_time: 0.0152 memory: 16131 loss: 0.9659 loss_prob: 0.5023 loss_thr: 0.3772 loss_db: 0.0864 2022/10/26 06:21:02 - mmengine - INFO - Epoch(train) [874][45/63] lr: 1.0950e-03 eta: 3:59:57 time: 0.5417 data_time: 0.0112 memory: 16131 loss: 1.0518 loss_prob: 0.5635 loss_thr: 0.3958 loss_db: 0.0925 2022/10/26 06:21:05 - mmengine - INFO - Epoch(train) [874][50/63] lr: 1.0950e-03 eta: 3:59:49 time: 0.5622 data_time: 0.0181 memory: 16131 loss: 1.0440 loss_prob: 0.5680 loss_thr: 0.3834 loss_db: 0.0926 2022/10/26 06:21:07 - mmengine - INFO - Epoch(train) [874][55/63] lr: 1.0950e-03 eta: 3:59:49 time: 0.5698 data_time: 0.0237 memory: 16131 loss: 1.0143 loss_prob: 0.5378 loss_thr: 0.3864 loss_db: 0.0901 2022/10/26 06:21:10 - mmengine - INFO - Epoch(train) [874][60/63] lr: 1.0950e-03 eta: 3:59:41 time: 0.5210 data_time: 0.0109 memory: 16131 loss: 1.0814 loss_prob: 0.5717 loss_thr: 0.4097 loss_db: 0.1001 2022/10/26 06:21:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:21:16 - mmengine - INFO - Epoch(train) [875][5/63] lr: 1.0920e-03 eta: 3:59:41 time: 0.7103 data_time: 0.1907 memory: 16131 loss: 1.2361 loss_prob: 0.6881 loss_thr: 0.4371 loss_db: 0.1108 2022/10/26 06:21:19 - mmengine - INFO - Epoch(train) [875][10/63] lr: 1.0920e-03 eta: 3:59:32 time: 0.7356 data_time: 0.1883 memory: 16131 loss: 1.1382 loss_prob: 0.6259 loss_thr: 0.4119 loss_db: 0.1004 2022/10/26 06:21:22 - mmengine - INFO - Epoch(train) [875][15/63] lr: 1.0920e-03 eta: 3:59:32 time: 0.5600 data_time: 0.0077 memory: 16131 loss: 1.0606 loss_prob: 0.5503 loss_thr: 0.4143 loss_db: 0.0960 2022/10/26 06:21:24 - mmengine - INFO - Epoch(train) [875][20/63] lr: 1.0920e-03 eta: 3:59:24 time: 0.5466 data_time: 0.0056 memory: 16131 loss: 1.0978 loss_prob: 0.5809 loss_thr: 0.4151 loss_db: 0.1018 2022/10/26 06:21:27 - mmengine - INFO - Epoch(train) [875][25/63] lr: 1.0920e-03 eta: 3:59:24 time: 0.5161 data_time: 0.0111 memory: 16131 loss: 1.1456 loss_prob: 0.6143 loss_thr: 0.4259 loss_db: 0.1054 2022/10/26 06:21:30 - mmengine - INFO - Epoch(train) [875][30/63] lr: 1.0920e-03 eta: 3:59:17 time: 0.5351 data_time: 0.0387 memory: 16131 loss: 1.1979 loss_prob: 0.6618 loss_thr: 0.4224 loss_db: 0.1137 2022/10/26 06:21:32 - mmengine - INFO - Epoch(train) [875][35/63] lr: 1.0920e-03 eta: 3:59:17 time: 0.5184 data_time: 0.0333 memory: 16131 loss: 1.0868 loss_prob: 0.5973 loss_thr: 0.3853 loss_db: 0.1042 2022/10/26 06:21:35 - mmengine - INFO - Epoch(train) [875][40/63] lr: 1.0920e-03 eta: 3:59:09 time: 0.4947 data_time: 0.0060 memory: 16131 loss: 0.9299 loss_prob: 0.4907 loss_thr: 0.3547 loss_db: 0.0845 2022/10/26 06:21:37 - mmengine - INFO - Epoch(train) [875][45/63] lr: 1.0920e-03 eta: 3:59:09 time: 0.4949 data_time: 0.0114 memory: 16131 loss: 0.9760 loss_prob: 0.5131 loss_thr: 0.3732 loss_db: 0.0896 2022/10/26 06:21:40 - mmengine - INFO - Epoch(train) [875][50/63] lr: 1.0920e-03 eta: 3:59:01 time: 0.5256 data_time: 0.0257 memory: 16131 loss: 1.0156 loss_prob: 0.5293 loss_thr: 0.3923 loss_db: 0.0940 2022/10/26 06:21:43 - mmengine - INFO - Epoch(train) [875][55/63] lr: 1.0920e-03 eta: 3:59:01 time: 0.5577 data_time: 0.0233 memory: 16131 loss: 1.0627 loss_prob: 0.5698 loss_thr: 0.3946 loss_db: 0.0983 2022/10/26 06:21:45 - mmengine - INFO - Epoch(train) [875][60/63] lr: 1.0920e-03 eta: 3:58:54 time: 0.5399 data_time: 0.0091 memory: 16131 loss: 1.0385 loss_prob: 0.5551 loss_thr: 0.3879 loss_db: 0.0955 2022/10/26 06:21:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:21:51 - mmengine - INFO - Epoch(train) [876][5/63] lr: 1.0890e-03 eta: 3:58:54 time: 0.6903 data_time: 0.1947 memory: 16131 loss: 1.0987 loss_prob: 0.5834 loss_thr: 0.4155 loss_db: 0.0998 2022/10/26 06:21:54 - mmengine - INFO - Epoch(train) [876][10/63] lr: 1.0890e-03 eta: 3:58:44 time: 0.7534 data_time: 0.1970 memory: 16131 loss: 1.1360 loss_prob: 0.6150 loss_thr: 0.4166 loss_db: 0.1043 2022/10/26 06:21:57 - mmengine - INFO - Epoch(train) [876][15/63] lr: 1.0890e-03 eta: 3:58:44 time: 0.5638 data_time: 0.0088 memory: 16131 loss: 1.1057 loss_prob: 0.6049 loss_thr: 0.3966 loss_db: 0.1043 2022/10/26 06:21:59 - mmengine - INFO - Epoch(train) [876][20/63] lr: 1.0890e-03 eta: 3:58:36 time: 0.5202 data_time: 0.0068 memory: 16131 loss: 1.0659 loss_prob: 0.5830 loss_thr: 0.3863 loss_db: 0.0966 2022/10/26 06:22:02 - mmengine - INFO - Epoch(train) [876][25/63] lr: 1.0890e-03 eta: 3:58:36 time: 0.4953 data_time: 0.0151 memory: 16131 loss: 0.9979 loss_prob: 0.5358 loss_thr: 0.3721 loss_db: 0.0900 2022/10/26 06:22:04 - mmengine - INFO - Epoch(train) [876][30/63] lr: 1.0890e-03 eta: 3:58:29 time: 0.5128 data_time: 0.0344 memory: 16131 loss: 0.9371 loss_prob: 0.4789 loss_thr: 0.3728 loss_db: 0.0854 2022/10/26 06:22:07 - mmengine - INFO - Epoch(train) [876][35/63] lr: 1.0890e-03 eta: 3:58:29 time: 0.5247 data_time: 0.0284 memory: 16131 loss: 1.0878 loss_prob: 0.5680 loss_thr: 0.4207 loss_db: 0.0991 2022/10/26 06:22:10 - mmengine - INFO - Epoch(train) [876][40/63] lr: 1.0890e-03 eta: 3:58:21 time: 0.5368 data_time: 0.0100 memory: 16131 loss: 1.0073 loss_prob: 0.5292 loss_thr: 0.3875 loss_db: 0.0906 2022/10/26 06:22:12 - mmengine - INFO - Epoch(train) [876][45/63] lr: 1.0890e-03 eta: 3:58:21 time: 0.5319 data_time: 0.0062 memory: 16131 loss: 0.9078 loss_prob: 0.4677 loss_thr: 0.3591 loss_db: 0.0810 2022/10/26 06:22:15 - mmengine - INFO - Epoch(train) [876][50/63] lr: 1.0890e-03 eta: 3:58:13 time: 0.5120 data_time: 0.0127 memory: 16131 loss: 0.9748 loss_prob: 0.5127 loss_thr: 0.3738 loss_db: 0.0883 2022/10/26 06:22:17 - mmengine - INFO - Epoch(train) [876][55/63] lr: 1.0890e-03 eta: 3:58:13 time: 0.5182 data_time: 0.0257 memory: 16131 loss: 0.9736 loss_prob: 0.5150 loss_thr: 0.3705 loss_db: 0.0882 2022/10/26 06:22:20 - mmengine - INFO - Epoch(train) [876][60/63] lr: 1.0890e-03 eta: 3:58:06 time: 0.5229 data_time: 0.0184 memory: 16131 loss: 0.9989 loss_prob: 0.5261 loss_thr: 0.3809 loss_db: 0.0919 2022/10/26 06:22:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:22:26 - mmengine - INFO - Epoch(train) [877][5/63] lr: 1.0860e-03 eta: 3:58:06 time: 0.6837 data_time: 0.1857 memory: 16131 loss: 1.0661 loss_prob: 0.5639 loss_thr: 0.4053 loss_db: 0.0969 2022/10/26 06:22:29 - mmengine - INFO - Epoch(train) [877][10/63] lr: 1.0860e-03 eta: 3:57:56 time: 0.7519 data_time: 0.1860 memory: 16131 loss: 0.9616 loss_prob: 0.4988 loss_thr: 0.3779 loss_db: 0.0849 2022/10/26 06:22:32 - mmengine - INFO - Epoch(train) [877][15/63] lr: 1.0860e-03 eta: 3:57:56 time: 0.6043 data_time: 0.0096 memory: 16131 loss: 0.9678 loss_prob: 0.5086 loss_thr: 0.3722 loss_db: 0.0869 2022/10/26 06:22:34 - mmengine - INFO - Epoch(train) [877][20/63] lr: 1.0860e-03 eta: 3:57:48 time: 0.5571 data_time: 0.0103 memory: 16131 loss: 1.0211 loss_prob: 0.5366 loss_thr: 0.3900 loss_db: 0.0945 2022/10/26 06:22:37 - mmengine - INFO - Epoch(train) [877][25/63] lr: 1.0860e-03 eta: 3:57:48 time: 0.5144 data_time: 0.0138 memory: 16131 loss: 1.0004 loss_prob: 0.5171 loss_thr: 0.3917 loss_db: 0.0916 2022/10/26 06:22:40 - mmengine - INFO - Epoch(train) [877][30/63] lr: 1.0860e-03 eta: 3:57:41 time: 0.5935 data_time: 0.0381 memory: 16131 loss: 0.9321 loss_prob: 0.4864 loss_thr: 0.3629 loss_db: 0.0827 2022/10/26 06:22:43 - mmengine - INFO - Epoch(train) [877][35/63] lr: 1.0860e-03 eta: 3:57:41 time: 0.5942 data_time: 0.0298 memory: 16131 loss: 0.9865 loss_prob: 0.5228 loss_thr: 0.3740 loss_db: 0.0897 2022/10/26 06:22:45 - mmengine - INFO - Epoch(train) [877][40/63] lr: 1.0860e-03 eta: 3:57:33 time: 0.5028 data_time: 0.0066 memory: 16131 loss: 1.0419 loss_prob: 0.5532 loss_thr: 0.3927 loss_db: 0.0961 2022/10/26 06:22:48 - mmengine - INFO - Epoch(train) [877][45/63] lr: 1.0860e-03 eta: 3:57:33 time: 0.5144 data_time: 0.0106 memory: 16131 loss: 1.0081 loss_prob: 0.5314 loss_thr: 0.3849 loss_db: 0.0918 2022/10/26 06:22:50 - mmengine - INFO - Epoch(train) [877][50/63] lr: 1.0860e-03 eta: 3:57:26 time: 0.5126 data_time: 0.0145 memory: 16131 loss: 1.0947 loss_prob: 0.5705 loss_thr: 0.4238 loss_db: 0.1004 2022/10/26 06:22:53 - mmengine - INFO - Epoch(train) [877][55/63] lr: 1.0860e-03 eta: 3:57:26 time: 0.5063 data_time: 0.0207 memory: 16131 loss: 1.1172 loss_prob: 0.5909 loss_thr: 0.4253 loss_db: 0.1010 2022/10/26 06:22:56 - mmengine - INFO - Epoch(train) [877][60/63] lr: 1.0860e-03 eta: 3:57:18 time: 0.5050 data_time: 0.0151 memory: 16131 loss: 1.0283 loss_prob: 0.5472 loss_thr: 0.3897 loss_db: 0.0914 2022/10/26 06:22:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:23:02 - mmengine - INFO - Epoch(train) [878][5/63] lr: 1.0829e-03 eta: 3:57:18 time: 0.7071 data_time: 0.1659 memory: 16131 loss: 0.9960 loss_prob: 0.5212 loss_thr: 0.3831 loss_db: 0.0917 2022/10/26 06:23:04 - mmengine - INFO - Epoch(train) [878][10/63] lr: 1.0829e-03 eta: 3:57:08 time: 0.7467 data_time: 0.1674 memory: 16131 loss: 0.9715 loss_prob: 0.5054 loss_thr: 0.3766 loss_db: 0.0895 2022/10/26 06:23:07 - mmengine - INFO - Epoch(train) [878][15/63] lr: 1.0829e-03 eta: 3:57:08 time: 0.5473 data_time: 0.0148 memory: 16131 loss: 1.0620 loss_prob: 0.5553 loss_thr: 0.4087 loss_db: 0.0980 2022/10/26 06:23:10 - mmengine - INFO - Epoch(train) [878][20/63] lr: 1.0829e-03 eta: 3:57:01 time: 0.5331 data_time: 0.0139 memory: 16131 loss: 1.0087 loss_prob: 0.5240 loss_thr: 0.3933 loss_db: 0.0914 2022/10/26 06:23:12 - mmengine - INFO - Epoch(train) [878][25/63] lr: 1.0829e-03 eta: 3:57:01 time: 0.5338 data_time: 0.0154 memory: 16131 loss: 0.9812 loss_prob: 0.5098 loss_thr: 0.3844 loss_db: 0.0870 2022/10/26 06:23:15 - mmengine - INFO - Epoch(train) [878][30/63] lr: 1.0829e-03 eta: 3:56:53 time: 0.5312 data_time: 0.0414 memory: 16131 loss: 1.0343 loss_prob: 0.5532 loss_thr: 0.3859 loss_db: 0.0952 2022/10/26 06:23:18 - mmengine - INFO - Epoch(train) [878][35/63] lr: 1.0829e-03 eta: 3:56:53 time: 0.5196 data_time: 0.0421 memory: 16131 loss: 1.0693 loss_prob: 0.5801 loss_thr: 0.3900 loss_db: 0.0992 2022/10/26 06:23:20 - mmengine - INFO - Epoch(train) [878][40/63] lr: 1.0829e-03 eta: 3:56:45 time: 0.5030 data_time: 0.0138 memory: 16131 loss: 1.0831 loss_prob: 0.5862 loss_thr: 0.3991 loss_db: 0.0978 2022/10/26 06:23:23 - mmengine - INFO - Epoch(train) [878][45/63] lr: 1.0829e-03 eta: 3:56:45 time: 0.5193 data_time: 0.0046 memory: 16131 loss: 1.0981 loss_prob: 0.5951 loss_thr: 0.4032 loss_db: 0.0999 2022/10/26 06:23:25 - mmengine - INFO - Epoch(train) [878][50/63] lr: 1.0829e-03 eta: 3:56:38 time: 0.5220 data_time: 0.0088 memory: 16131 loss: 0.9890 loss_prob: 0.5205 loss_thr: 0.3797 loss_db: 0.0887 2022/10/26 06:23:28 - mmengine - INFO - Epoch(train) [878][55/63] lr: 1.0829e-03 eta: 3:56:38 time: 0.5026 data_time: 0.0197 memory: 16131 loss: 0.9579 loss_prob: 0.4977 loss_thr: 0.3740 loss_db: 0.0862 2022/10/26 06:23:30 - mmengine - INFO - Epoch(train) [878][60/63] lr: 1.0829e-03 eta: 3:56:30 time: 0.5088 data_time: 0.0193 memory: 16131 loss: 0.9895 loss_prob: 0.5222 loss_thr: 0.3754 loss_db: 0.0919 2022/10/26 06:23:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:23:37 - mmengine - INFO - Epoch(train) [879][5/63] lr: 1.0799e-03 eta: 3:56:30 time: 0.7179 data_time: 0.1868 memory: 16131 loss: 1.0132 loss_prob: 0.5294 loss_thr: 0.3930 loss_db: 0.0909 2022/10/26 06:23:39 - mmengine - INFO - Epoch(train) [879][10/63] lr: 1.0799e-03 eta: 3:56:20 time: 0.7210 data_time: 0.1870 memory: 16131 loss: 1.1439 loss_prob: 0.6114 loss_thr: 0.4296 loss_db: 0.1029 2022/10/26 06:23:42 - mmengine - INFO - Epoch(train) [879][15/63] lr: 1.0799e-03 eta: 3:56:20 time: 0.5297 data_time: 0.0118 memory: 16131 loss: 1.0499 loss_prob: 0.5596 loss_thr: 0.3941 loss_db: 0.0962 2022/10/26 06:23:44 - mmengine - INFO - Epoch(train) [879][20/63] lr: 1.0799e-03 eta: 3:56:12 time: 0.5034 data_time: 0.0098 memory: 16131 loss: 0.9734 loss_prob: 0.5155 loss_thr: 0.3657 loss_db: 0.0922 2022/10/26 06:23:47 - mmengine - INFO - Epoch(train) [879][25/63] lr: 1.0799e-03 eta: 3:56:12 time: 0.5011 data_time: 0.0177 memory: 16131 loss: 1.0979 loss_prob: 0.5929 loss_thr: 0.4027 loss_db: 0.1023 2022/10/26 06:23:50 - mmengine - INFO - Epoch(train) [879][30/63] lr: 1.0799e-03 eta: 3:56:05 time: 0.5873 data_time: 0.0355 memory: 16131 loss: 1.0791 loss_prob: 0.5774 loss_thr: 0.4033 loss_db: 0.0983 2022/10/26 06:23:53 - mmengine - INFO - Epoch(train) [879][35/63] lr: 1.0799e-03 eta: 3:56:05 time: 0.5850 data_time: 0.0226 memory: 16131 loss: 1.0503 loss_prob: 0.5587 loss_thr: 0.3961 loss_db: 0.0956 2022/10/26 06:23:55 - mmengine - INFO - Epoch(train) [879][40/63] lr: 1.0799e-03 eta: 3:55:57 time: 0.5027 data_time: 0.0062 memory: 16131 loss: 0.9657 loss_prob: 0.5028 loss_thr: 0.3768 loss_db: 0.0861 2022/10/26 06:23:58 - mmengine - INFO - Epoch(train) [879][45/63] lr: 1.0799e-03 eta: 3:55:57 time: 0.5126 data_time: 0.0074 memory: 16131 loss: 0.9697 loss_prob: 0.5098 loss_thr: 0.3721 loss_db: 0.0878 2022/10/26 06:24:01 - mmengine - INFO - Epoch(train) [879][50/63] lr: 1.0799e-03 eta: 3:55:50 time: 0.5561 data_time: 0.0222 memory: 16131 loss: 1.0085 loss_prob: 0.5409 loss_thr: 0.3766 loss_db: 0.0910 2022/10/26 06:24:03 - mmengine - INFO - Epoch(train) [879][55/63] lr: 1.0799e-03 eta: 3:55:50 time: 0.5484 data_time: 0.0280 memory: 16131 loss: 0.9529 loss_prob: 0.4996 loss_thr: 0.3670 loss_db: 0.0864 2022/10/26 06:24:06 - mmengine - INFO - Epoch(train) [879][60/63] lr: 1.0799e-03 eta: 3:55:42 time: 0.5077 data_time: 0.0117 memory: 16131 loss: 0.9921 loss_prob: 0.5207 loss_thr: 0.3808 loss_db: 0.0906 2022/10/26 06:24:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:24:11 - mmengine - INFO - Epoch(train) [880][5/63] lr: 1.0769e-03 eta: 3:55:42 time: 0.6601 data_time: 0.1794 memory: 16131 loss: 0.8934 loss_prob: 0.4649 loss_thr: 0.3487 loss_db: 0.0797 2022/10/26 06:24:14 - mmengine - INFO - Epoch(train) [880][10/63] lr: 1.0769e-03 eta: 3:55:32 time: 0.6947 data_time: 0.1841 memory: 16131 loss: 0.9216 loss_prob: 0.4767 loss_thr: 0.3623 loss_db: 0.0826 2022/10/26 06:24:17 - mmengine - INFO - Epoch(train) [880][15/63] lr: 1.0769e-03 eta: 3:55:32 time: 0.5082 data_time: 0.0100 memory: 16131 loss: 0.9618 loss_prob: 0.4971 loss_thr: 0.3783 loss_db: 0.0864 2022/10/26 06:24:19 - mmengine - INFO - Epoch(train) [880][20/63] lr: 1.0769e-03 eta: 3:55:24 time: 0.5056 data_time: 0.0054 memory: 16131 loss: 1.0540 loss_prob: 0.5544 loss_thr: 0.4047 loss_db: 0.0949 2022/10/26 06:24:22 - mmengine - INFO - Epoch(train) [880][25/63] lr: 1.0769e-03 eta: 3:55:24 time: 0.5326 data_time: 0.0188 memory: 16131 loss: 1.0646 loss_prob: 0.5718 loss_thr: 0.3942 loss_db: 0.0986 2022/10/26 06:24:25 - mmengine - INFO - Epoch(train) [880][30/63] lr: 1.0769e-03 eta: 3:55:17 time: 0.6120 data_time: 0.0381 memory: 16131 loss: 0.9571 loss_prob: 0.5096 loss_thr: 0.3597 loss_db: 0.0878 2022/10/26 06:24:28 - mmengine - INFO - Epoch(train) [880][35/63] lr: 1.0769e-03 eta: 3:55:17 time: 0.5911 data_time: 0.0292 memory: 16131 loss: 1.0128 loss_prob: 0.5372 loss_thr: 0.3834 loss_db: 0.0922 2022/10/26 06:24:31 - mmengine - INFO - Epoch(train) [880][40/63] lr: 1.0769e-03 eta: 3:55:10 time: 0.5519 data_time: 0.0106 memory: 16131 loss: 1.0567 loss_prob: 0.5593 loss_thr: 0.4003 loss_db: 0.0971 2022/10/26 06:24:33 - mmengine - INFO - Epoch(train) [880][45/63] lr: 1.0769e-03 eta: 3:55:10 time: 0.5536 data_time: 0.0074 memory: 16131 loss: 0.9693 loss_prob: 0.5100 loss_thr: 0.3713 loss_db: 0.0881 2022/10/26 06:24:36 - mmengine - INFO - Epoch(train) [880][50/63] lr: 1.0769e-03 eta: 3:55:02 time: 0.5148 data_time: 0.0185 memory: 16131 loss: 0.9529 loss_prob: 0.4954 loss_thr: 0.3732 loss_db: 0.0844 2022/10/26 06:24:39 - mmengine - INFO - Epoch(train) [880][55/63] lr: 1.0769e-03 eta: 3:55:02 time: 0.5238 data_time: 0.0201 memory: 16131 loss: 0.9436 loss_prob: 0.4880 loss_thr: 0.3713 loss_db: 0.0844 2022/10/26 06:24:41 - mmengine - INFO - Epoch(train) [880][60/63] lr: 1.0769e-03 eta: 3:54:54 time: 0.5246 data_time: 0.0089 memory: 16131 loss: 0.9573 loss_prob: 0.5045 loss_thr: 0.3652 loss_db: 0.0876 2022/10/26 06:24:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:24:42 - mmengine - INFO - Saving checkpoint at 880 epochs 2022/10/26 06:24:49 - mmengine - INFO - Epoch(val) [880][5/32] eta: 3:54:54 time: 0.5100 data_time: 0.0586 memory: 16131 2022/10/26 06:24:52 - mmengine - INFO - Epoch(val) [880][10/32] eta: 0:00:12 time: 0.5764 data_time: 0.0869 memory: 15724 2022/10/26 06:24:54 - mmengine - INFO - Epoch(val) [880][15/32] eta: 0:00:12 time: 0.5258 data_time: 0.0441 memory: 15724 2022/10/26 06:24:57 - mmengine - INFO - Epoch(val) [880][20/32] eta: 0:00:06 time: 0.5224 data_time: 0.0413 memory: 15724 2022/10/26 06:25:00 - mmengine - INFO - Epoch(val) [880][25/32] eta: 0:00:06 time: 0.5684 data_time: 0.0590 memory: 15724 2022/10/26 06:25:02 - mmengine - INFO - Epoch(val) [880][30/32] eta: 0:00:01 time: 0.5416 data_time: 0.0352 memory: 15724 2022/10/26 06:25:03 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8373, precision: 0.7460, hmean: 0.7890 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8373, precision: 0.7952, hmean: 0.8157 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8368, precision: 0.8272, hmean: 0.8320 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8344, precision: 0.8575, hmean: 0.8458 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8272, precision: 0.8856, hmean: 0.8554 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7482, precision: 0.9261, hmean: 0.8277 2022/10/26 06:25:03 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1603, precision: 0.9737, hmean: 0.2753 2022/10/26 06:25:03 - mmengine - INFO - Epoch(val) [880][32/32] icdar/precision: 0.8856 icdar/recall: 0.8272 icdar/hmean: 0.8554 2022/10/26 06:25:08 - mmengine - INFO - Epoch(train) [881][5/63] lr: 1.0739e-03 eta: 0:00:01 time: 0.7240 data_time: 0.1869 memory: 16131 loss: 1.0264 loss_prob: 0.5453 loss_thr: 0.3858 loss_db: 0.0953 2022/10/26 06:25:10 - mmengine - INFO - Epoch(train) [881][10/63] lr: 1.0739e-03 eta: 3:54:45 time: 0.7565 data_time: 0.1900 memory: 16131 loss: 1.0087 loss_prob: 0.5408 loss_thr: 0.3745 loss_db: 0.0935 2022/10/26 06:25:13 - mmengine - INFO - Epoch(train) [881][15/63] lr: 1.0739e-03 eta: 3:54:45 time: 0.5053 data_time: 0.0089 memory: 16131 loss: 1.0119 loss_prob: 0.5334 loss_thr: 0.3863 loss_db: 0.0921 2022/10/26 06:25:15 - mmengine - INFO - Epoch(train) [881][20/63] lr: 1.0739e-03 eta: 3:54:37 time: 0.4986 data_time: 0.0062 memory: 16131 loss: 0.9886 loss_prob: 0.5108 loss_thr: 0.3886 loss_db: 0.0893 2022/10/26 06:25:18 - mmengine - INFO - Epoch(train) [881][25/63] lr: 1.0739e-03 eta: 3:54:37 time: 0.5345 data_time: 0.0131 memory: 16131 loss: 0.9984 loss_prob: 0.5129 loss_thr: 0.3965 loss_db: 0.0890 2022/10/26 06:25:21 - mmengine - INFO - Epoch(train) [881][30/63] lr: 1.0739e-03 eta: 3:54:30 time: 0.5729 data_time: 0.0333 memory: 16131 loss: 0.9751 loss_prob: 0.5057 loss_thr: 0.3808 loss_db: 0.0887 2022/10/26 06:25:24 - mmengine - INFO - Epoch(train) [881][35/63] lr: 1.0739e-03 eta: 3:54:30 time: 0.5918 data_time: 0.0271 memory: 16131 loss: 1.0605 loss_prob: 0.5754 loss_thr: 0.3884 loss_db: 0.0967 2022/10/26 06:25:27 - mmengine - INFO - Epoch(train) [881][40/63] lr: 1.0739e-03 eta: 3:54:22 time: 0.5691 data_time: 0.0069 memory: 16131 loss: 1.1059 loss_prob: 0.6054 loss_thr: 0.3991 loss_db: 0.1014 2022/10/26 06:25:29 - mmengine - INFO - Epoch(train) [881][45/63] lr: 1.0739e-03 eta: 3:54:22 time: 0.5110 data_time: 0.0058 memory: 16131 loss: 0.9784 loss_prob: 0.5161 loss_thr: 0.3722 loss_db: 0.0900 2022/10/26 06:25:32 - mmengine - INFO - Epoch(train) [881][50/63] lr: 1.0739e-03 eta: 3:54:15 time: 0.5371 data_time: 0.0262 memory: 16131 loss: 0.9765 loss_prob: 0.5121 loss_thr: 0.3748 loss_db: 0.0897 2022/10/26 06:25:35 - mmengine - INFO - Epoch(train) [881][55/63] lr: 1.0739e-03 eta: 3:54:15 time: 0.5224 data_time: 0.0270 memory: 16131 loss: 1.0209 loss_prob: 0.5368 loss_thr: 0.3895 loss_db: 0.0945 2022/10/26 06:25:37 - mmengine - INFO - Epoch(train) [881][60/63] lr: 1.0739e-03 eta: 3:54:07 time: 0.4888 data_time: 0.0084 memory: 16131 loss: 0.9814 loss_prob: 0.5168 loss_thr: 0.3741 loss_db: 0.0905 2022/10/26 06:25:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:25:43 - mmengine - INFO - Epoch(train) [882][5/63] lr: 1.0708e-03 eta: 3:54:07 time: 0.6682 data_time: 0.1813 memory: 16131 loss: 1.0227 loss_prob: 0.5413 loss_thr: 0.3878 loss_db: 0.0936 2022/10/26 06:25:45 - mmengine - INFO - Epoch(train) [882][10/63] lr: 1.0708e-03 eta: 3:53:57 time: 0.6913 data_time: 0.1845 memory: 16131 loss: 1.0562 loss_prob: 0.5602 loss_thr: 0.4004 loss_db: 0.0957 2022/10/26 06:25:48 - mmengine - INFO - Epoch(train) [882][15/63] lr: 1.0708e-03 eta: 3:53:57 time: 0.5288 data_time: 0.0123 memory: 16131 loss: 1.0153 loss_prob: 0.5402 loss_thr: 0.3829 loss_db: 0.0921 2022/10/26 06:25:51 - mmengine - INFO - Epoch(train) [882][20/63] lr: 1.0708e-03 eta: 3:53:49 time: 0.5048 data_time: 0.0109 memory: 16131 loss: 0.9674 loss_prob: 0.5128 loss_thr: 0.3674 loss_db: 0.0872 2022/10/26 06:25:53 - mmengine - INFO - Epoch(train) [882][25/63] lr: 1.0708e-03 eta: 3:53:49 time: 0.5243 data_time: 0.0308 memory: 16131 loss: 0.8963 loss_prob: 0.4711 loss_thr: 0.3447 loss_db: 0.0805 2022/10/26 06:25:56 - mmengine - INFO - Epoch(train) [882][30/63] lr: 1.0708e-03 eta: 3:53:42 time: 0.5350 data_time: 0.0280 memory: 16131 loss: 1.0829 loss_prob: 0.5863 loss_thr: 0.3957 loss_db: 0.1009 2022/10/26 06:25:58 - mmengine - INFO - Epoch(train) [882][35/63] lr: 1.0708e-03 eta: 3:53:42 time: 0.5037 data_time: 0.0105 memory: 16131 loss: 1.1370 loss_prob: 0.6155 loss_thr: 0.4154 loss_db: 0.1061 2022/10/26 06:26:01 - mmengine - INFO - Epoch(train) [882][40/63] lr: 1.0708e-03 eta: 3:53:34 time: 0.5458 data_time: 0.0108 memory: 16131 loss: 0.9882 loss_prob: 0.5240 loss_thr: 0.3724 loss_db: 0.0918 2022/10/26 06:26:04 - mmengine - INFO - Epoch(train) [882][45/63] lr: 1.0708e-03 eta: 3:53:34 time: 0.5811 data_time: 0.0165 memory: 16131 loss: 1.0127 loss_prob: 0.5426 loss_thr: 0.3751 loss_db: 0.0950 2022/10/26 06:26:07 - mmengine - INFO - Epoch(train) [882][50/63] lr: 1.0708e-03 eta: 3:53:27 time: 0.5602 data_time: 0.0296 memory: 16131 loss: 0.9786 loss_prob: 0.5235 loss_thr: 0.3643 loss_db: 0.0908 2022/10/26 06:26:09 - mmengine - INFO - Epoch(train) [882][55/63] lr: 1.0708e-03 eta: 3:53:27 time: 0.5271 data_time: 0.0192 memory: 16131 loss: 1.0128 loss_prob: 0.5412 loss_thr: 0.3795 loss_db: 0.0921 2022/10/26 06:26:12 - mmengine - INFO - Epoch(train) [882][60/63] lr: 1.0708e-03 eta: 3:53:19 time: 0.5051 data_time: 0.0101 memory: 16131 loss: 1.0334 loss_prob: 0.5488 loss_thr: 0.3903 loss_db: 0.0943 2022/10/26 06:26:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:26:18 - mmengine - INFO - Epoch(train) [883][5/63] lr: 1.0678e-03 eta: 3:53:19 time: 0.6559 data_time: 0.1681 memory: 16131 loss: 0.9279 loss_prob: 0.4808 loss_thr: 0.3623 loss_db: 0.0848 2022/10/26 06:26:20 - mmengine - INFO - Epoch(train) [883][10/63] lr: 1.0678e-03 eta: 3:53:09 time: 0.6794 data_time: 0.1694 memory: 16131 loss: 0.9860 loss_prob: 0.5111 loss_thr: 0.3846 loss_db: 0.0903 2022/10/26 06:26:23 - mmengine - INFO - Epoch(train) [883][15/63] lr: 1.0678e-03 eta: 3:53:09 time: 0.4983 data_time: 0.0086 memory: 16131 loss: 1.0155 loss_prob: 0.5264 loss_thr: 0.3978 loss_db: 0.0913 2022/10/26 06:26:25 - mmengine - INFO - Epoch(train) [883][20/63] lr: 1.0678e-03 eta: 3:53:01 time: 0.4915 data_time: 0.0061 memory: 16131 loss: 0.9323 loss_prob: 0.4744 loss_thr: 0.3763 loss_db: 0.0816 2022/10/26 06:26:28 - mmengine - INFO - Epoch(train) [883][25/63] lr: 1.0678e-03 eta: 3:53:01 time: 0.4989 data_time: 0.0223 memory: 16131 loss: 0.9722 loss_prob: 0.5088 loss_thr: 0.3762 loss_db: 0.0872 2022/10/26 06:26:30 - mmengine - INFO - Epoch(train) [883][30/63] lr: 1.0678e-03 eta: 3:52:54 time: 0.5226 data_time: 0.0439 memory: 16131 loss: 0.9863 loss_prob: 0.5243 loss_thr: 0.3719 loss_db: 0.0901 2022/10/26 06:26:33 - mmengine - INFO - Epoch(train) [883][35/63] lr: 1.0678e-03 eta: 3:52:54 time: 0.5965 data_time: 0.0288 memory: 16131 loss: 0.9347 loss_prob: 0.4912 loss_thr: 0.3569 loss_db: 0.0866 2022/10/26 06:26:36 - mmengine - INFO - Epoch(train) [883][40/63] lr: 1.0678e-03 eta: 3:52:46 time: 0.5872 data_time: 0.0075 memory: 16131 loss: 0.9997 loss_prob: 0.5313 loss_thr: 0.3759 loss_db: 0.0925 2022/10/26 06:26:39 - mmengine - INFO - Epoch(train) [883][45/63] lr: 1.0678e-03 eta: 3:52:46 time: 0.5037 data_time: 0.0090 memory: 16131 loss: 1.0488 loss_prob: 0.5589 loss_thr: 0.3926 loss_db: 0.0973 2022/10/26 06:26:41 - mmengine - INFO - Epoch(train) [883][50/63] lr: 1.0678e-03 eta: 3:52:39 time: 0.5151 data_time: 0.0253 memory: 16131 loss: 0.9828 loss_prob: 0.5209 loss_thr: 0.3728 loss_db: 0.0890 2022/10/26 06:26:44 - mmengine - INFO - Epoch(train) [883][55/63] lr: 1.0678e-03 eta: 3:52:39 time: 0.5219 data_time: 0.0228 memory: 16131 loss: 0.9153 loss_prob: 0.4759 loss_thr: 0.3583 loss_db: 0.0811 2022/10/26 06:26:47 - mmengine - INFO - Epoch(train) [883][60/63] lr: 1.0678e-03 eta: 3:52:31 time: 0.5380 data_time: 0.0062 memory: 16131 loss: 1.0180 loss_prob: 0.5328 loss_thr: 0.3925 loss_db: 0.0927 2022/10/26 06:26:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:26:53 - mmengine - INFO - Epoch(train) [884][5/63] lr: 1.0648e-03 eta: 3:52:31 time: 0.7195 data_time: 0.1926 memory: 16131 loss: 1.0090 loss_prob: 0.5341 loss_thr: 0.3819 loss_db: 0.0930 2022/10/26 06:26:55 - mmengine - INFO - Epoch(train) [884][10/63] lr: 1.0648e-03 eta: 3:52:21 time: 0.7342 data_time: 0.1928 memory: 16131 loss: 1.3217 loss_prob: 0.7555 loss_thr: 0.4386 loss_db: 0.1277 2022/10/26 06:26:58 - mmengine - INFO - Epoch(train) [884][15/63] lr: 1.0648e-03 eta: 3:52:21 time: 0.5013 data_time: 0.0057 memory: 16131 loss: 1.2767 loss_prob: 0.7269 loss_thr: 0.4274 loss_db: 0.1224 2022/10/26 06:27:00 - mmengine - INFO - Epoch(train) [884][20/63] lr: 1.0648e-03 eta: 3:52:14 time: 0.4969 data_time: 0.0049 memory: 16131 loss: 1.1041 loss_prob: 0.5985 loss_thr: 0.4016 loss_db: 0.1039 2022/10/26 06:27:03 - mmengine - INFO - Epoch(train) [884][25/63] lr: 1.0648e-03 eta: 3:52:14 time: 0.5140 data_time: 0.0230 memory: 16131 loss: 1.0733 loss_prob: 0.5858 loss_thr: 0.3884 loss_db: 0.0990 2022/10/26 06:27:06 - mmengine - INFO - Epoch(train) [884][30/63] lr: 1.0648e-03 eta: 3:52:06 time: 0.5436 data_time: 0.0359 memory: 16131 loss: 0.9900 loss_prob: 0.5332 loss_thr: 0.3682 loss_db: 0.0887 2022/10/26 06:27:08 - mmengine - INFO - Epoch(train) [884][35/63] lr: 1.0648e-03 eta: 3:52:06 time: 0.5312 data_time: 0.0175 memory: 16131 loss: 1.0311 loss_prob: 0.5521 loss_thr: 0.3834 loss_db: 0.0956 2022/10/26 06:27:11 - mmengine - INFO - Epoch(train) [884][40/63] lr: 1.0648e-03 eta: 3:51:58 time: 0.5219 data_time: 0.0058 memory: 16131 loss: 1.0747 loss_prob: 0.5768 loss_thr: 0.3990 loss_db: 0.0989 2022/10/26 06:27:13 - mmengine - INFO - Epoch(train) [884][45/63] lr: 1.0648e-03 eta: 3:51:58 time: 0.5127 data_time: 0.0078 memory: 16131 loss: 1.0759 loss_prob: 0.5752 loss_thr: 0.4037 loss_db: 0.0970 2022/10/26 06:27:16 - mmengine - INFO - Epoch(train) [884][50/63] lr: 1.0648e-03 eta: 3:51:51 time: 0.5359 data_time: 0.0208 memory: 16131 loss: 1.1353 loss_prob: 0.6079 loss_thr: 0.4238 loss_db: 0.1035 2022/10/26 06:27:19 - mmengine - INFO - Epoch(train) [884][55/63] lr: 1.0648e-03 eta: 3:51:51 time: 0.5549 data_time: 0.0264 memory: 16131 loss: 1.0982 loss_prob: 0.5877 loss_thr: 0.4097 loss_db: 0.1008 2022/10/26 06:27:21 - mmengine - INFO - Epoch(train) [884][60/63] lr: 1.0648e-03 eta: 3:51:43 time: 0.5134 data_time: 0.0123 memory: 16131 loss: 0.9332 loss_prob: 0.4922 loss_thr: 0.3553 loss_db: 0.0857 2022/10/26 06:27:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:27:27 - mmengine - INFO - Epoch(train) [885][5/63] lr: 1.0617e-03 eta: 3:51:43 time: 0.6680 data_time: 0.1879 memory: 16131 loss: 1.0188 loss_prob: 0.5446 loss_thr: 0.3823 loss_db: 0.0919 2022/10/26 06:27:30 - mmengine - INFO - Epoch(train) [885][10/63] lr: 1.0617e-03 eta: 3:51:33 time: 0.6930 data_time: 0.1944 memory: 16131 loss: 1.0402 loss_prob: 0.5470 loss_thr: 0.3991 loss_db: 0.0942 2022/10/26 06:27:32 - mmengine - INFO - Epoch(train) [885][15/63] lr: 1.0617e-03 eta: 3:51:33 time: 0.4973 data_time: 0.0159 memory: 16131 loss: 0.9910 loss_prob: 0.5158 loss_thr: 0.3836 loss_db: 0.0916 2022/10/26 06:27:35 - mmengine - INFO - Epoch(train) [885][20/63] lr: 1.0617e-03 eta: 3:51:26 time: 0.5214 data_time: 0.0130 memory: 16131 loss: 0.9387 loss_prob: 0.4905 loss_thr: 0.3632 loss_db: 0.0851 2022/10/26 06:27:38 - mmengine - INFO - Epoch(train) [885][25/63] lr: 1.0617e-03 eta: 3:51:26 time: 0.5402 data_time: 0.0262 memory: 16131 loss: 1.0104 loss_prob: 0.5377 loss_thr: 0.3802 loss_db: 0.0926 2022/10/26 06:27:40 - mmengine - INFO - Epoch(train) [885][30/63] lr: 1.0617e-03 eta: 3:51:18 time: 0.5243 data_time: 0.0256 memory: 16131 loss: 1.0464 loss_prob: 0.5580 loss_thr: 0.3907 loss_db: 0.0977 2022/10/26 06:27:43 - mmengine - INFO - Epoch(train) [885][35/63] lr: 1.0617e-03 eta: 3:51:18 time: 0.5146 data_time: 0.0212 memory: 16131 loss: 0.9805 loss_prob: 0.5137 loss_thr: 0.3774 loss_db: 0.0894 2022/10/26 06:27:45 - mmengine - INFO - Epoch(train) [885][40/63] lr: 1.0617e-03 eta: 3:51:11 time: 0.5393 data_time: 0.0187 memory: 16131 loss: 0.9495 loss_prob: 0.4927 loss_thr: 0.3718 loss_db: 0.0850 2022/10/26 06:27:48 - mmengine - INFO - Epoch(train) [885][45/63] lr: 1.0617e-03 eta: 3:51:11 time: 0.5436 data_time: 0.0100 memory: 16131 loss: 0.9738 loss_prob: 0.5068 loss_thr: 0.3772 loss_db: 0.0898 2022/10/26 06:27:51 - mmengine - INFO - Epoch(train) [885][50/63] lr: 1.0617e-03 eta: 3:51:03 time: 0.5158 data_time: 0.0188 memory: 16131 loss: 0.9769 loss_prob: 0.5163 loss_thr: 0.3704 loss_db: 0.0902 2022/10/26 06:27:53 - mmengine - INFO - Epoch(train) [885][55/63] lr: 1.0617e-03 eta: 3:51:03 time: 0.5164 data_time: 0.0171 memory: 16131 loss: 0.9570 loss_prob: 0.5108 loss_thr: 0.3580 loss_db: 0.0883 2022/10/26 06:27:56 - mmengine - INFO - Epoch(train) [885][60/63] lr: 1.0617e-03 eta: 3:50:56 time: 0.5427 data_time: 0.0099 memory: 16131 loss: 1.0144 loss_prob: 0.5424 loss_thr: 0.3799 loss_db: 0.0920 2022/10/26 06:27:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:28:02 - mmengine - INFO - Epoch(train) [886][5/63] lr: 1.0587e-03 eta: 3:50:56 time: 0.6673 data_time: 0.1658 memory: 16131 loss: 1.0991 loss_prob: 0.5931 loss_thr: 0.4061 loss_db: 0.0999 2022/10/26 06:28:05 - mmengine - INFO - Epoch(train) [886][10/63] lr: 1.0587e-03 eta: 3:50:46 time: 0.7371 data_time: 0.1714 memory: 16131 loss: 1.0910 loss_prob: 0.5883 loss_thr: 0.4016 loss_db: 0.1011 2022/10/26 06:28:07 - mmengine - INFO - Epoch(train) [886][15/63] lr: 1.0587e-03 eta: 3:50:46 time: 0.5363 data_time: 0.0122 memory: 16131 loss: 1.0561 loss_prob: 0.5686 loss_thr: 0.3918 loss_db: 0.0956 2022/10/26 06:28:10 - mmengine - INFO - Epoch(train) [886][20/63] lr: 1.0587e-03 eta: 3:50:38 time: 0.4972 data_time: 0.0113 memory: 16131 loss: 0.9724 loss_prob: 0.5132 loss_thr: 0.3701 loss_db: 0.0891 2022/10/26 06:28:12 - mmengine - INFO - Epoch(train) [886][25/63] lr: 1.0587e-03 eta: 3:50:38 time: 0.5107 data_time: 0.0287 memory: 16131 loss: 0.9888 loss_prob: 0.5191 loss_thr: 0.3781 loss_db: 0.0916 2022/10/26 06:28:15 - mmengine - INFO - Epoch(train) [886][30/63] lr: 1.0587e-03 eta: 3:50:31 time: 0.5232 data_time: 0.0330 memory: 16131 loss: 0.9648 loss_prob: 0.4996 loss_thr: 0.3795 loss_db: 0.0857 2022/10/26 06:28:17 - mmengine - INFO - Epoch(train) [886][35/63] lr: 1.0587e-03 eta: 3:50:31 time: 0.5194 data_time: 0.0186 memory: 16131 loss: 1.0168 loss_prob: 0.5322 loss_thr: 0.3947 loss_db: 0.0899 2022/10/26 06:28:20 - mmengine - INFO - Epoch(train) [886][40/63] lr: 1.0587e-03 eta: 3:50:23 time: 0.5101 data_time: 0.0115 memory: 16131 loss: 1.0394 loss_prob: 0.5453 loss_thr: 0.4005 loss_db: 0.0936 2022/10/26 06:28:23 - mmengine - INFO - Epoch(train) [886][45/63] lr: 1.0587e-03 eta: 3:50:23 time: 0.5155 data_time: 0.0091 memory: 16131 loss: 0.9797 loss_prob: 0.5125 loss_thr: 0.3777 loss_db: 0.0894 2022/10/26 06:28:25 - mmengine - INFO - Epoch(train) [886][50/63] lr: 1.0587e-03 eta: 3:50:15 time: 0.5434 data_time: 0.0130 memory: 16131 loss: 1.0163 loss_prob: 0.5443 loss_thr: 0.3780 loss_db: 0.0940 2022/10/26 06:28:28 - mmengine - INFO - Epoch(train) [886][55/63] lr: 1.0587e-03 eta: 3:50:15 time: 0.5466 data_time: 0.0214 memory: 16131 loss: 1.0045 loss_prob: 0.5352 loss_thr: 0.3774 loss_db: 0.0919 2022/10/26 06:28:31 - mmengine - INFO - Epoch(train) [886][60/63] lr: 1.0587e-03 eta: 3:50:08 time: 0.5141 data_time: 0.0159 memory: 16131 loss: 0.9259 loss_prob: 0.4823 loss_thr: 0.3611 loss_db: 0.0826 2022/10/26 06:28:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:28:36 - mmengine - INFO - Epoch(train) [887][5/63] lr: 1.0557e-03 eta: 3:50:08 time: 0.6566 data_time: 0.1615 memory: 16131 loss: 1.0745 loss_prob: 0.5755 loss_thr: 0.3998 loss_db: 0.0992 2022/10/26 06:28:39 - mmengine - INFO - Epoch(train) [887][10/63] lr: 1.0557e-03 eta: 3:49:58 time: 0.7194 data_time: 0.1605 memory: 16131 loss: 1.0632 loss_prob: 0.5619 loss_thr: 0.4041 loss_db: 0.0973 2022/10/26 06:28:41 - mmengine - INFO - Epoch(train) [887][15/63] lr: 1.0557e-03 eta: 3:49:58 time: 0.5291 data_time: 0.0068 memory: 16131 loss: 1.0671 loss_prob: 0.5592 loss_thr: 0.4093 loss_db: 0.0987 2022/10/26 06:28:44 - mmengine - INFO - Epoch(train) [887][20/63] lr: 1.0557e-03 eta: 3:49:50 time: 0.4947 data_time: 0.0103 memory: 16131 loss: 1.0165 loss_prob: 0.5362 loss_thr: 0.3871 loss_db: 0.0931 2022/10/26 06:28:47 - mmengine - INFO - Epoch(train) [887][25/63] lr: 1.0557e-03 eta: 3:49:50 time: 0.5166 data_time: 0.0245 memory: 16131 loss: 0.9043 loss_prob: 0.4670 loss_thr: 0.3575 loss_db: 0.0797 2022/10/26 06:28:49 - mmengine - INFO - Epoch(train) [887][30/63] lr: 1.0557e-03 eta: 3:49:43 time: 0.5231 data_time: 0.0299 memory: 16131 loss: 0.9017 loss_prob: 0.4738 loss_thr: 0.3472 loss_db: 0.0808 2022/10/26 06:28:52 - mmengine - INFO - Epoch(train) [887][35/63] lr: 1.0557e-03 eta: 3:49:43 time: 0.5020 data_time: 0.0133 memory: 16131 loss: 1.0263 loss_prob: 0.5526 loss_thr: 0.3795 loss_db: 0.0942 2022/10/26 06:28:54 - mmengine - INFO - Epoch(train) [887][40/63] lr: 1.0557e-03 eta: 3:49:35 time: 0.4880 data_time: 0.0119 memory: 16131 loss: 0.9828 loss_prob: 0.5202 loss_thr: 0.3704 loss_db: 0.0922 2022/10/26 06:28:57 - mmengine - INFO - Epoch(train) [887][45/63] lr: 1.0557e-03 eta: 3:49:35 time: 0.4972 data_time: 0.0129 memory: 16131 loss: 0.8930 loss_prob: 0.4647 loss_thr: 0.3466 loss_db: 0.0818 2022/10/26 06:29:00 - mmengine - INFO - Epoch(train) [887][50/63] lr: 1.0557e-03 eta: 3:49:28 time: 0.5605 data_time: 0.0189 memory: 16131 loss: 0.9771 loss_prob: 0.5167 loss_thr: 0.3744 loss_db: 0.0861 2022/10/26 06:29:02 - mmengine - INFO - Epoch(train) [887][55/63] lr: 1.0557e-03 eta: 3:49:28 time: 0.5883 data_time: 0.0258 memory: 16131 loss: 1.0720 loss_prob: 0.5656 loss_thr: 0.4125 loss_db: 0.0939 2022/10/26 06:29:05 - mmengine - INFO - Epoch(train) [887][60/63] lr: 1.0557e-03 eta: 3:49:20 time: 0.5206 data_time: 0.0120 memory: 16131 loss: 1.0683 loss_prob: 0.5545 loss_thr: 0.4188 loss_db: 0.0949 2022/10/26 06:29:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:29:11 - mmengine - INFO - Epoch(train) [888][5/63] lr: 1.0526e-03 eta: 3:49:20 time: 0.6909 data_time: 0.2068 memory: 16131 loss: 1.0102 loss_prob: 0.5340 loss_thr: 0.3828 loss_db: 0.0935 2022/10/26 06:29:14 - mmengine - INFO - Epoch(train) [888][10/63] lr: 1.0526e-03 eta: 3:49:10 time: 0.7476 data_time: 0.2112 memory: 16131 loss: 1.0214 loss_prob: 0.5399 loss_thr: 0.3868 loss_db: 0.0947 2022/10/26 06:29:16 - mmengine - INFO - Epoch(train) [888][15/63] lr: 1.0526e-03 eta: 3:49:10 time: 0.5137 data_time: 0.0109 memory: 16131 loss: 1.0249 loss_prob: 0.5395 loss_thr: 0.3916 loss_db: 0.0939 2022/10/26 06:29:19 - mmengine - INFO - Epoch(train) [888][20/63] lr: 1.0526e-03 eta: 3:49:03 time: 0.5371 data_time: 0.0051 memory: 16131 loss: 0.9378 loss_prob: 0.4901 loss_thr: 0.3628 loss_db: 0.0849 2022/10/26 06:29:22 - mmengine - INFO - Epoch(train) [888][25/63] lr: 1.0526e-03 eta: 3:49:03 time: 0.5808 data_time: 0.0331 memory: 16131 loss: 0.9471 loss_prob: 0.4967 loss_thr: 0.3646 loss_db: 0.0858 2022/10/26 06:29:24 - mmengine - INFO - Epoch(train) [888][30/63] lr: 1.0526e-03 eta: 3:48:55 time: 0.5422 data_time: 0.0326 memory: 16131 loss: 1.0292 loss_prob: 0.5476 loss_thr: 0.3890 loss_db: 0.0926 2022/10/26 06:29:27 - mmengine - INFO - Epoch(train) [888][35/63] lr: 1.0526e-03 eta: 3:48:55 time: 0.5179 data_time: 0.0054 memory: 16131 loss: 1.0724 loss_prob: 0.5765 loss_thr: 0.3983 loss_db: 0.0976 2022/10/26 06:29:29 - mmengine - INFO - Epoch(train) [888][40/63] lr: 1.0526e-03 eta: 3:48:48 time: 0.5167 data_time: 0.0052 memory: 16131 loss: 1.0288 loss_prob: 0.5455 loss_thr: 0.3886 loss_db: 0.0947 2022/10/26 06:29:32 - mmengine - INFO - Epoch(train) [888][45/63] lr: 1.0526e-03 eta: 3:48:48 time: 0.5072 data_time: 0.0059 memory: 16131 loss: 1.0130 loss_prob: 0.5352 loss_thr: 0.3868 loss_db: 0.0911 2022/10/26 06:29:35 - mmengine - INFO - Epoch(train) [888][50/63] lr: 1.0526e-03 eta: 3:48:40 time: 0.5299 data_time: 0.0246 memory: 16131 loss: 0.9476 loss_prob: 0.4951 loss_thr: 0.3674 loss_db: 0.0851 2022/10/26 06:29:37 - mmengine - INFO - Epoch(train) [888][55/63] lr: 1.0526e-03 eta: 3:48:40 time: 0.5350 data_time: 0.0271 memory: 16131 loss: 0.9738 loss_prob: 0.5109 loss_thr: 0.3745 loss_db: 0.0885 2022/10/26 06:29:40 - mmengine - INFO - Epoch(train) [888][60/63] lr: 1.0526e-03 eta: 3:48:32 time: 0.5134 data_time: 0.0090 memory: 16131 loss: 1.0663 loss_prob: 0.5616 loss_thr: 0.4099 loss_db: 0.0948 2022/10/26 06:29:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:29:46 - mmengine - INFO - Epoch(train) [889][5/63] lr: 1.0496e-03 eta: 3:48:32 time: 0.6868 data_time: 0.1847 memory: 16131 loss: 1.1226 loss_prob: 0.6149 loss_thr: 0.4073 loss_db: 0.1004 2022/10/26 06:29:48 - mmengine - INFO - Epoch(train) [889][10/63] lr: 1.0496e-03 eta: 3:48:23 time: 0.6889 data_time: 0.1928 memory: 16131 loss: 1.1432 loss_prob: 0.6227 loss_thr: 0.4163 loss_db: 0.1041 2022/10/26 06:29:51 - mmengine - INFO - Epoch(train) [889][15/63] lr: 1.0496e-03 eta: 3:48:23 time: 0.5033 data_time: 0.0136 memory: 16131 loss: 1.0384 loss_prob: 0.5463 loss_thr: 0.3958 loss_db: 0.0964 2022/10/26 06:29:53 - mmengine - INFO - Epoch(train) [889][20/63] lr: 1.0496e-03 eta: 3:48:15 time: 0.5193 data_time: 0.0061 memory: 16131 loss: 1.0417 loss_prob: 0.5476 loss_thr: 0.3981 loss_db: 0.0960 2022/10/26 06:29:56 - mmengine - INFO - Epoch(train) [889][25/63] lr: 1.0496e-03 eta: 3:48:15 time: 0.5292 data_time: 0.0236 memory: 16131 loss: 0.9922 loss_prob: 0.5247 loss_thr: 0.3772 loss_db: 0.0903 2022/10/26 06:29:59 - mmengine - INFO - Epoch(train) [889][30/63] lr: 1.0496e-03 eta: 3:48:07 time: 0.5334 data_time: 0.0323 memory: 16131 loss: 1.0530 loss_prob: 0.5607 loss_thr: 0.3970 loss_db: 0.0953 2022/10/26 06:30:01 - mmengine - INFO - Epoch(train) [889][35/63] lr: 1.0496e-03 eta: 3:48:07 time: 0.5156 data_time: 0.0159 memory: 16131 loss: 1.0987 loss_prob: 0.5774 loss_thr: 0.4211 loss_db: 0.1002 2022/10/26 06:30:04 - mmengine - INFO - Epoch(train) [889][40/63] lr: 1.0496e-03 eta: 3:48:00 time: 0.5025 data_time: 0.0073 memory: 16131 loss: 0.9751 loss_prob: 0.5078 loss_thr: 0.3782 loss_db: 0.0891 2022/10/26 06:30:06 - mmengine - INFO - Epoch(train) [889][45/63] lr: 1.0496e-03 eta: 3:48:00 time: 0.5080 data_time: 0.0061 memory: 16131 loss: 1.0530 loss_prob: 0.5656 loss_thr: 0.3923 loss_db: 0.0952 2022/10/26 06:30:09 - mmengine - INFO - Epoch(train) [889][50/63] lr: 1.0496e-03 eta: 3:47:52 time: 0.5188 data_time: 0.0180 memory: 16131 loss: 1.1230 loss_prob: 0.6084 loss_thr: 0.4140 loss_db: 0.1005 2022/10/26 06:30:12 - mmengine - INFO - Epoch(train) [889][55/63] lr: 1.0496e-03 eta: 3:47:52 time: 0.5351 data_time: 0.0216 memory: 16131 loss: 1.0460 loss_prob: 0.5471 loss_thr: 0.4063 loss_db: 0.0926 2022/10/26 06:30:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:30:15 - mmengine - INFO - Epoch(train) [889][60/63] lr: 1.0496e-03 eta: 3:47:45 time: 0.5584 data_time: 0.0089 memory: 16131 loss: 0.9981 loss_prob: 0.5217 loss_thr: 0.3859 loss_db: 0.0906 2022/10/26 06:30:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:30:20 - mmengine - INFO - Epoch(train) [890][5/63] lr: 1.0466e-03 eta: 3:47:45 time: 0.6769 data_time: 0.1886 memory: 16131 loss: 1.0926 loss_prob: 0.5815 loss_thr: 0.4087 loss_db: 0.1024 2022/10/26 06:30:23 - mmengine - INFO - Epoch(train) [890][10/63] lr: 1.0466e-03 eta: 3:47:35 time: 0.6924 data_time: 0.1904 memory: 16131 loss: 1.0099 loss_prob: 0.5405 loss_thr: 0.3784 loss_db: 0.0910 2022/10/26 06:30:25 - mmengine - INFO - Epoch(train) [890][15/63] lr: 1.0466e-03 eta: 3:47:35 time: 0.5031 data_time: 0.0072 memory: 16131 loss: 0.9801 loss_prob: 0.5144 loss_thr: 0.3797 loss_db: 0.0860 2022/10/26 06:30:28 - mmengine - INFO - Epoch(train) [890][20/63] lr: 1.0466e-03 eta: 3:47:27 time: 0.4867 data_time: 0.0059 memory: 16131 loss: 1.0775 loss_prob: 0.5694 loss_thr: 0.4084 loss_db: 0.0997 2022/10/26 06:30:31 - mmengine - INFO - Epoch(train) [890][25/63] lr: 1.0466e-03 eta: 3:47:27 time: 0.5427 data_time: 0.0112 memory: 16131 loss: 1.0173 loss_prob: 0.5390 loss_thr: 0.3848 loss_db: 0.0936 2022/10/26 06:30:34 - mmengine - INFO - Epoch(train) [890][30/63] lr: 1.0466e-03 eta: 3:47:20 time: 0.5883 data_time: 0.0328 memory: 16131 loss: 0.9641 loss_prob: 0.5121 loss_thr: 0.3647 loss_db: 0.0873 2022/10/26 06:30:36 - mmengine - INFO - Epoch(train) [890][35/63] lr: 1.0466e-03 eta: 3:47:20 time: 0.5333 data_time: 0.0275 memory: 16131 loss: 0.9822 loss_prob: 0.5199 loss_thr: 0.3722 loss_db: 0.0901 2022/10/26 06:30:39 - mmengine - INFO - Epoch(train) [890][40/63] lr: 1.0466e-03 eta: 3:47:12 time: 0.5055 data_time: 0.0063 memory: 16131 loss: 0.9706 loss_prob: 0.5051 loss_thr: 0.3770 loss_db: 0.0885 2022/10/26 06:30:41 - mmengine - INFO - Epoch(train) [890][45/63] lr: 1.0466e-03 eta: 3:47:12 time: 0.5131 data_time: 0.0055 memory: 16131 loss: 0.9629 loss_prob: 0.5187 loss_thr: 0.3539 loss_db: 0.0903 2022/10/26 06:30:44 - mmengine - INFO - Epoch(train) [890][50/63] lr: 1.0466e-03 eta: 3:47:05 time: 0.5355 data_time: 0.0218 memory: 16131 loss: 1.0022 loss_prob: 0.5408 loss_thr: 0.3686 loss_db: 0.0928 2022/10/26 06:30:46 - mmengine - INFO - Epoch(train) [890][55/63] lr: 1.0466e-03 eta: 3:47:05 time: 0.5147 data_time: 0.0232 memory: 16131 loss: 1.0454 loss_prob: 0.5465 loss_thr: 0.4042 loss_db: 0.0948 2022/10/26 06:30:49 - mmengine - INFO - Epoch(train) [890][60/63] lr: 1.0466e-03 eta: 3:46:57 time: 0.4944 data_time: 0.0116 memory: 16131 loss: 1.0187 loss_prob: 0.5262 loss_thr: 0.4008 loss_db: 0.0917 2022/10/26 06:30:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:30:55 - mmengine - INFO - Epoch(train) [891][5/63] lr: 1.0435e-03 eta: 3:46:57 time: 0.7130 data_time: 0.2165 memory: 16131 loss: 1.0878 loss_prob: 0.5771 loss_thr: 0.4115 loss_db: 0.0993 2022/10/26 06:30:58 - mmengine - INFO - Epoch(train) [891][10/63] lr: 1.0435e-03 eta: 3:46:47 time: 0.7303 data_time: 0.2158 memory: 16131 loss: 0.9833 loss_prob: 0.5180 loss_thr: 0.3754 loss_db: 0.0899 2022/10/26 06:31:00 - mmengine - INFO - Epoch(train) [891][15/63] lr: 1.0435e-03 eta: 3:46:47 time: 0.5301 data_time: 0.0059 memory: 16131 loss: 0.9446 loss_prob: 0.5001 loss_thr: 0.3570 loss_db: 0.0875 2022/10/26 06:31:03 - mmengine - INFO - Epoch(train) [891][20/63] lr: 1.0435e-03 eta: 3:46:40 time: 0.5464 data_time: 0.0069 memory: 16131 loss: 0.9575 loss_prob: 0.5066 loss_thr: 0.3633 loss_db: 0.0876 2022/10/26 06:31:06 - mmengine - INFO - Epoch(train) [891][25/63] lr: 1.0435e-03 eta: 3:46:40 time: 0.5452 data_time: 0.0288 memory: 16131 loss: 0.9984 loss_prob: 0.5285 loss_thr: 0.3776 loss_db: 0.0923 2022/10/26 06:31:08 - mmengine - INFO - Epoch(train) [891][30/63] lr: 1.0435e-03 eta: 3:46:32 time: 0.5111 data_time: 0.0316 memory: 16131 loss: 0.9967 loss_prob: 0.5301 loss_thr: 0.3744 loss_db: 0.0922 2022/10/26 06:31:11 - mmengine - INFO - Epoch(train) [891][35/63] lr: 1.0435e-03 eta: 3:46:32 time: 0.5106 data_time: 0.0100 memory: 16131 loss: 0.9812 loss_prob: 0.5097 loss_thr: 0.3824 loss_db: 0.0891 2022/10/26 06:31:14 - mmengine - INFO - Epoch(train) [891][40/63] lr: 1.0435e-03 eta: 3:46:25 time: 0.5283 data_time: 0.0062 memory: 16131 loss: 0.9988 loss_prob: 0.5129 loss_thr: 0.3954 loss_db: 0.0906 2022/10/26 06:31:16 - mmengine - INFO - Epoch(train) [891][45/63] lr: 1.0435e-03 eta: 3:46:25 time: 0.5113 data_time: 0.0087 memory: 16131 loss: 1.0029 loss_prob: 0.5239 loss_thr: 0.3880 loss_db: 0.0910 2022/10/26 06:31:19 - mmengine - INFO - Epoch(train) [891][50/63] lr: 1.0435e-03 eta: 3:46:17 time: 0.5333 data_time: 0.0238 memory: 16131 loss: 0.9535 loss_prob: 0.5012 loss_thr: 0.3648 loss_db: 0.0875 2022/10/26 06:31:22 - mmengine - INFO - Epoch(train) [891][55/63] lr: 1.0435e-03 eta: 3:46:17 time: 0.5632 data_time: 0.0207 memory: 16131 loss: 0.9339 loss_prob: 0.4871 loss_thr: 0.3618 loss_db: 0.0850 2022/10/26 06:31:24 - mmengine - INFO - Epoch(train) [891][60/63] lr: 1.0435e-03 eta: 3:46:10 time: 0.5327 data_time: 0.0065 memory: 16131 loss: 0.9549 loss_prob: 0.4957 loss_thr: 0.3726 loss_db: 0.0866 2022/10/26 06:31:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:31:31 - mmengine - INFO - Epoch(train) [892][5/63] lr: 1.0405e-03 eta: 3:46:10 time: 0.7862 data_time: 0.2261 memory: 16131 loss: 0.9824 loss_prob: 0.5114 loss_thr: 0.3817 loss_db: 0.0893 2022/10/26 06:31:34 - mmengine - INFO - Epoch(train) [892][10/63] lr: 1.0405e-03 eta: 3:46:00 time: 0.7824 data_time: 0.2260 memory: 16131 loss: 1.0474 loss_prob: 0.5533 loss_thr: 0.3999 loss_db: 0.0942 2022/10/26 06:31:36 - mmengine - INFO - Epoch(train) [892][15/63] lr: 1.0405e-03 eta: 3:46:00 time: 0.5162 data_time: 0.0109 memory: 16131 loss: 1.1069 loss_prob: 0.5883 loss_thr: 0.4174 loss_db: 0.1013 2022/10/26 06:31:39 - mmengine - INFO - Epoch(train) [892][20/63] lr: 1.0405e-03 eta: 3:45:52 time: 0.5128 data_time: 0.0123 memory: 16131 loss: 1.0266 loss_prob: 0.5463 loss_thr: 0.3862 loss_db: 0.0940 2022/10/26 06:31:41 - mmengine - INFO - Epoch(train) [892][25/63] lr: 1.0405e-03 eta: 3:45:52 time: 0.4927 data_time: 0.0118 memory: 16131 loss: 1.0059 loss_prob: 0.5430 loss_thr: 0.3695 loss_db: 0.0933 2022/10/26 06:31:44 - mmengine - INFO - Epoch(train) [892][30/63] lr: 1.0405e-03 eta: 3:45:45 time: 0.5183 data_time: 0.0330 memory: 16131 loss: 1.0264 loss_prob: 0.5460 loss_thr: 0.3857 loss_db: 0.0946 2022/10/26 06:31:46 - mmengine - INFO - Epoch(train) [892][35/63] lr: 1.0405e-03 eta: 3:45:45 time: 0.5209 data_time: 0.0276 memory: 16131 loss: 1.0445 loss_prob: 0.5366 loss_thr: 0.4162 loss_db: 0.0917 2022/10/26 06:31:49 - mmengine - INFO - Epoch(train) [892][40/63] lr: 1.0405e-03 eta: 3:45:37 time: 0.5114 data_time: 0.0082 memory: 16131 loss: 1.0476 loss_prob: 0.5454 loss_thr: 0.4089 loss_db: 0.0933 2022/10/26 06:31:52 - mmengine - INFO - Epoch(train) [892][45/63] lr: 1.0405e-03 eta: 3:45:37 time: 0.5340 data_time: 0.0081 memory: 16131 loss: 0.9794 loss_prob: 0.5108 loss_thr: 0.3808 loss_db: 0.0878 2022/10/26 06:31:54 - mmengine - INFO - Epoch(train) [892][50/63] lr: 1.0405e-03 eta: 3:45:30 time: 0.5379 data_time: 0.0147 memory: 16131 loss: 0.9603 loss_prob: 0.5031 loss_thr: 0.3722 loss_db: 0.0851 2022/10/26 06:31:57 - mmengine - INFO - Epoch(train) [892][55/63] lr: 1.0405e-03 eta: 3:45:30 time: 0.5181 data_time: 0.0229 memory: 16131 loss: 0.9844 loss_prob: 0.5221 loss_thr: 0.3736 loss_db: 0.0887 2022/10/26 06:31:59 - mmengine - INFO - Epoch(train) [892][60/63] lr: 1.0405e-03 eta: 3:45:22 time: 0.5096 data_time: 0.0139 memory: 16131 loss: 0.9449 loss_prob: 0.4866 loss_thr: 0.3740 loss_db: 0.0843 2022/10/26 06:32:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:32:06 - mmengine - INFO - Epoch(train) [893][5/63] lr: 1.0374e-03 eta: 3:45:22 time: 0.7251 data_time: 0.2126 memory: 16131 loss: 1.0844 loss_prob: 0.5800 loss_thr: 0.4049 loss_db: 0.0995 2022/10/26 06:32:08 - mmengine - INFO - Epoch(train) [893][10/63] lr: 1.0374e-03 eta: 3:45:13 time: 0.7782 data_time: 0.2115 memory: 16131 loss: 1.1360 loss_prob: 0.6216 loss_thr: 0.4089 loss_db: 0.1055 2022/10/26 06:32:11 - mmengine - INFO - Epoch(train) [893][15/63] lr: 1.0374e-03 eta: 3:45:13 time: 0.5335 data_time: 0.0050 memory: 16131 loss: 1.0102 loss_prob: 0.5381 loss_thr: 0.3796 loss_db: 0.0925 2022/10/26 06:32:13 - mmengine - INFO - Epoch(train) [893][20/63] lr: 1.0374e-03 eta: 3:45:05 time: 0.4991 data_time: 0.0069 memory: 16131 loss: 0.9723 loss_prob: 0.5093 loss_thr: 0.3739 loss_db: 0.0891 2022/10/26 06:32:16 - mmengine - INFO - Epoch(train) [893][25/63] lr: 1.0374e-03 eta: 3:45:05 time: 0.5288 data_time: 0.0121 memory: 16131 loss: 0.9829 loss_prob: 0.5136 loss_thr: 0.3789 loss_db: 0.0904 2022/10/26 06:32:19 - mmengine - INFO - Epoch(train) [893][30/63] lr: 1.0374e-03 eta: 3:44:58 time: 0.5715 data_time: 0.0350 memory: 16131 loss: 0.9917 loss_prob: 0.5223 loss_thr: 0.3797 loss_db: 0.0896 2022/10/26 06:32:22 - mmengine - INFO - Epoch(train) [893][35/63] lr: 1.0374e-03 eta: 3:44:58 time: 0.5561 data_time: 0.0293 memory: 16131 loss: 0.9740 loss_prob: 0.5146 loss_thr: 0.3711 loss_db: 0.0883 2022/10/26 06:32:24 - mmengine - INFO - Epoch(train) [893][40/63] lr: 1.0374e-03 eta: 3:44:50 time: 0.5210 data_time: 0.0064 memory: 16131 loss: 0.9410 loss_prob: 0.4931 loss_thr: 0.3612 loss_db: 0.0866 2022/10/26 06:32:27 - mmengine - INFO - Epoch(train) [893][45/63] lr: 1.0374e-03 eta: 3:44:50 time: 0.4993 data_time: 0.0080 memory: 16131 loss: 0.9720 loss_prob: 0.5133 loss_thr: 0.3687 loss_db: 0.0899 2022/10/26 06:32:30 - mmengine - INFO - Epoch(train) [893][50/63] lr: 1.0374e-03 eta: 3:44:42 time: 0.5159 data_time: 0.0110 memory: 16131 loss: 1.0004 loss_prob: 0.5349 loss_thr: 0.3754 loss_db: 0.0901 2022/10/26 06:32:33 - mmengine - INFO - Epoch(train) [893][55/63] lr: 1.0374e-03 eta: 3:44:42 time: 0.5727 data_time: 0.0260 memory: 16131 loss: 1.0037 loss_prob: 0.5369 loss_thr: 0.3762 loss_db: 0.0905 2022/10/26 06:32:35 - mmengine - INFO - Epoch(train) [893][60/63] lr: 1.0374e-03 eta: 3:44:35 time: 0.5372 data_time: 0.0217 memory: 16131 loss: 1.0513 loss_prob: 0.5631 loss_thr: 0.3901 loss_db: 0.0981 2022/10/26 06:32:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:32:43 - mmengine - INFO - Epoch(train) [894][5/63] lr: 1.0344e-03 eta: 3:44:35 time: 0.9075 data_time: 0.2690 memory: 16131 loss: 1.0462 loss_prob: 0.5583 loss_thr: 0.3913 loss_db: 0.0966 2022/10/26 06:32:46 - mmengine - INFO - Epoch(train) [894][10/63] lr: 1.0344e-03 eta: 3:44:26 time: 0.9394 data_time: 0.2689 memory: 16131 loss: 1.0040 loss_prob: 0.5399 loss_thr: 0.3704 loss_db: 0.0938 2022/10/26 06:32:48 - mmengine - INFO - Epoch(train) [894][15/63] lr: 1.0344e-03 eta: 3:44:26 time: 0.5100 data_time: 0.0065 memory: 16131 loss: 0.9986 loss_prob: 0.5313 loss_thr: 0.3757 loss_db: 0.0915 2022/10/26 06:32:51 - mmengine - INFO - Epoch(train) [894][20/63] lr: 1.0344e-03 eta: 3:44:18 time: 0.5175 data_time: 0.0064 memory: 16131 loss: 0.9001 loss_prob: 0.4649 loss_thr: 0.3545 loss_db: 0.0807 2022/10/26 06:32:54 - mmengine - INFO - Epoch(train) [894][25/63] lr: 1.0344e-03 eta: 3:44:18 time: 0.5697 data_time: 0.0460 memory: 16131 loss: 0.9462 loss_prob: 0.4931 loss_thr: 0.3685 loss_db: 0.0846 2022/10/26 06:32:56 - mmengine - INFO - Epoch(train) [894][30/63] lr: 1.0344e-03 eta: 3:44:11 time: 0.5556 data_time: 0.0460 memory: 16131 loss: 1.0197 loss_prob: 0.5363 loss_thr: 0.3899 loss_db: 0.0935 2022/10/26 06:32:59 - mmengine - INFO - Epoch(train) [894][35/63] lr: 1.0344e-03 eta: 3:44:11 time: 0.4888 data_time: 0.0046 memory: 16131 loss: 0.9746 loss_prob: 0.5136 loss_thr: 0.3719 loss_db: 0.0891 2022/10/26 06:33:01 - mmengine - INFO - Epoch(train) [894][40/63] lr: 1.0344e-03 eta: 3:44:03 time: 0.4971 data_time: 0.0049 memory: 16131 loss: 0.9050 loss_prob: 0.4685 loss_thr: 0.3565 loss_db: 0.0800 2022/10/26 06:33:04 - mmengine - INFO - Epoch(train) [894][45/63] lr: 1.0344e-03 eta: 3:44:03 time: 0.5115 data_time: 0.0083 memory: 16131 loss: 0.9846 loss_prob: 0.5136 loss_thr: 0.3821 loss_db: 0.0889 2022/10/26 06:33:07 - mmengine - INFO - Epoch(train) [894][50/63] lr: 1.0344e-03 eta: 3:43:56 time: 0.5200 data_time: 0.0247 memory: 16131 loss: 1.0378 loss_prob: 0.5444 loss_thr: 0.3983 loss_db: 0.0951 2022/10/26 06:33:09 - mmengine - INFO - Epoch(train) [894][55/63] lr: 1.0344e-03 eta: 3:43:56 time: 0.5279 data_time: 0.0225 memory: 16131 loss: 0.9424 loss_prob: 0.4914 loss_thr: 0.3647 loss_db: 0.0863 2022/10/26 06:33:12 - mmengine - INFO - Epoch(train) [894][60/63] lr: 1.0344e-03 eta: 3:43:48 time: 0.5445 data_time: 0.0058 memory: 16131 loss: 0.9241 loss_prob: 0.4859 loss_thr: 0.3532 loss_db: 0.0849 2022/10/26 06:33:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:33:19 - mmengine - INFO - Epoch(train) [895][5/63] lr: 1.0314e-03 eta: 3:43:48 time: 0.8109 data_time: 0.1963 memory: 16131 loss: 1.0262 loss_prob: 0.5514 loss_thr: 0.3802 loss_db: 0.0946 2022/10/26 06:33:22 - mmengine - INFO - Epoch(train) [895][10/63] lr: 1.0314e-03 eta: 3:43:39 time: 0.8586 data_time: 0.1967 memory: 16131 loss: 1.0144 loss_prob: 0.5391 loss_thr: 0.3822 loss_db: 0.0931 2022/10/26 06:33:24 - mmengine - INFO - Epoch(train) [895][15/63] lr: 1.0314e-03 eta: 3:43:39 time: 0.5426 data_time: 0.0052 memory: 16131 loss: 0.9796 loss_prob: 0.5082 loss_thr: 0.3830 loss_db: 0.0884 2022/10/26 06:33:27 - mmengine - INFO - Epoch(train) [895][20/63] lr: 1.0314e-03 eta: 3:43:31 time: 0.5210 data_time: 0.0057 memory: 16131 loss: 1.0169 loss_prob: 0.5431 loss_thr: 0.3799 loss_db: 0.0939 2022/10/26 06:33:30 - mmengine - INFO - Epoch(train) [895][25/63] lr: 1.0314e-03 eta: 3:43:31 time: 0.5350 data_time: 0.0105 memory: 16131 loss: 1.0326 loss_prob: 0.5590 loss_thr: 0.3784 loss_db: 0.0952 2022/10/26 06:33:33 - mmengine - INFO - Epoch(train) [895][30/63] lr: 1.0314e-03 eta: 3:43:24 time: 0.5492 data_time: 0.0354 memory: 16131 loss: 0.9842 loss_prob: 0.5191 loss_thr: 0.3760 loss_db: 0.0891 2022/10/26 06:33:35 - mmengine - INFO - Epoch(train) [895][35/63] lr: 1.0314e-03 eta: 3:43:24 time: 0.5372 data_time: 0.0341 memory: 16131 loss: 0.9919 loss_prob: 0.5212 loss_thr: 0.3824 loss_db: 0.0883 2022/10/26 06:33:38 - mmengine - INFO - Epoch(train) [895][40/63] lr: 1.0314e-03 eta: 3:43:16 time: 0.4974 data_time: 0.0107 memory: 16131 loss: 1.0235 loss_prob: 0.5433 loss_thr: 0.3865 loss_db: 0.0937 2022/10/26 06:33:40 - mmengine - INFO - Epoch(train) [895][45/63] lr: 1.0314e-03 eta: 3:43:16 time: 0.5248 data_time: 0.0129 memory: 16131 loss: 1.0662 loss_prob: 0.5828 loss_thr: 0.3892 loss_db: 0.0942 2022/10/26 06:33:43 - mmengine - INFO - Epoch(train) [895][50/63] lr: 1.0314e-03 eta: 3:43:09 time: 0.5668 data_time: 0.0189 memory: 16131 loss: 1.0874 loss_prob: 0.5993 loss_thr: 0.3928 loss_db: 0.0952 2022/10/26 06:33:46 - mmengine - INFO - Epoch(train) [895][55/63] lr: 1.0314e-03 eta: 3:43:09 time: 0.5541 data_time: 0.0240 memory: 16131 loss: 1.0566 loss_prob: 0.5665 loss_thr: 0.3927 loss_db: 0.0974 2022/10/26 06:33:48 - mmengine - INFO - Epoch(train) [895][60/63] lr: 1.0314e-03 eta: 3:43:01 time: 0.5157 data_time: 0.0157 memory: 16131 loss: 0.9566 loss_prob: 0.5039 loss_thr: 0.3651 loss_db: 0.0877 2022/10/26 06:33:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:33:54 - mmengine - INFO - Epoch(train) [896][5/63] lr: 1.0283e-03 eta: 3:43:01 time: 0.7089 data_time: 0.1625 memory: 16131 loss: 1.0458 loss_prob: 0.5524 loss_thr: 0.3996 loss_db: 0.0939 2022/10/26 06:33:58 - mmengine - INFO - Epoch(train) [896][10/63] lr: 1.0283e-03 eta: 3:42:52 time: 0.8165 data_time: 0.1827 memory: 16131 loss: 0.9968 loss_prob: 0.5244 loss_thr: 0.3813 loss_db: 0.0910 2022/10/26 06:34:01 - mmengine - INFO - Epoch(train) [896][15/63] lr: 1.0283e-03 eta: 3:42:52 time: 0.6171 data_time: 0.0253 memory: 16131 loss: 0.9934 loss_prob: 0.5250 loss_thr: 0.3770 loss_db: 0.0915 2022/10/26 06:34:04 - mmengine - INFO - Epoch(train) [896][20/63] lr: 1.0283e-03 eta: 3:42:45 time: 0.6055 data_time: 0.0051 memory: 16131 loss: 0.9426 loss_prob: 0.4928 loss_thr: 0.3644 loss_db: 0.0854 2022/10/26 06:34:07 - mmengine - INFO - Epoch(train) [896][25/63] lr: 1.0283e-03 eta: 3:42:45 time: 0.6305 data_time: 0.0131 memory: 16131 loss: 0.9623 loss_prob: 0.4995 loss_thr: 0.3755 loss_db: 0.0874 2022/10/26 06:34:10 - mmengine - INFO - Epoch(train) [896][30/63] lr: 1.0283e-03 eta: 3:42:37 time: 0.5750 data_time: 0.0250 memory: 16131 loss: 0.9967 loss_prob: 0.5229 loss_thr: 0.3809 loss_db: 0.0928 2022/10/26 06:34:13 - mmengine - INFO - Epoch(train) [896][35/63] lr: 1.0283e-03 eta: 3:42:37 time: 0.5544 data_time: 0.0286 memory: 16131 loss: 0.9800 loss_prob: 0.5177 loss_thr: 0.3718 loss_db: 0.0905 2022/10/26 06:34:15 - mmengine - INFO - Epoch(train) [896][40/63] lr: 1.0283e-03 eta: 3:42:30 time: 0.5450 data_time: 0.0168 memory: 16131 loss: 1.0542 loss_prob: 0.5635 loss_thr: 0.3963 loss_db: 0.0943 2022/10/26 06:34:18 - mmengine - INFO - Epoch(train) [896][45/63] lr: 1.0283e-03 eta: 3:42:30 time: 0.5513 data_time: 0.0059 memory: 16131 loss: 1.0018 loss_prob: 0.5264 loss_thr: 0.3861 loss_db: 0.0893 2022/10/26 06:34:21 - mmengine - INFO - Epoch(train) [896][50/63] lr: 1.0283e-03 eta: 3:42:22 time: 0.5656 data_time: 0.0141 memory: 16131 loss: 1.0195 loss_prob: 0.5416 loss_thr: 0.3860 loss_db: 0.0918 2022/10/26 06:34:24 - mmengine - INFO - Epoch(train) [896][55/63] lr: 1.0283e-03 eta: 3:42:22 time: 0.6048 data_time: 0.0189 memory: 16131 loss: 1.0231 loss_prob: 0.5451 loss_thr: 0.3866 loss_db: 0.0913 2022/10/26 06:34:27 - mmengine - INFO - Epoch(train) [896][60/63] lr: 1.0283e-03 eta: 3:42:15 time: 0.5768 data_time: 0.0173 memory: 16131 loss: 1.0045 loss_prob: 0.5218 loss_thr: 0.3923 loss_db: 0.0905 2022/10/26 06:34:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:34:32 - mmengine - INFO - Epoch(train) [897][5/63] lr: 1.0253e-03 eta: 3:42:15 time: 0.6666 data_time: 0.1789 memory: 16131 loss: 0.9667 loss_prob: 0.5054 loss_thr: 0.3742 loss_db: 0.0871 2022/10/26 06:34:35 - mmengine - INFO - Epoch(train) [897][10/63] lr: 1.0253e-03 eta: 3:42:05 time: 0.7060 data_time: 0.1822 memory: 16131 loss: 0.9330 loss_prob: 0.4840 loss_thr: 0.3657 loss_db: 0.0833 2022/10/26 06:34:38 - mmengine - INFO - Epoch(train) [897][15/63] lr: 1.0253e-03 eta: 3:42:05 time: 0.5981 data_time: 0.0117 memory: 16131 loss: 1.1016 loss_prob: 0.6028 loss_thr: 0.3981 loss_db: 0.1007 2022/10/26 06:34:41 - mmengine - INFO - Epoch(train) [897][20/63] lr: 1.0253e-03 eta: 3:41:58 time: 0.5843 data_time: 0.0093 memory: 16131 loss: 1.1229 loss_prob: 0.6110 loss_thr: 0.4086 loss_db: 0.1033 2022/10/26 06:34:44 - mmengine - INFO - Epoch(train) [897][25/63] lr: 1.0253e-03 eta: 3:41:58 time: 0.5299 data_time: 0.0316 memory: 16131 loss: 0.9723 loss_prob: 0.5047 loss_thr: 0.3785 loss_db: 0.0892 2022/10/26 06:34:46 - mmengine - INFO - Epoch(train) [897][30/63] lr: 1.0253e-03 eta: 3:41:50 time: 0.5239 data_time: 0.0342 memory: 16131 loss: 0.9490 loss_prob: 0.4967 loss_thr: 0.3672 loss_db: 0.0851 2022/10/26 06:34:49 - mmengine - INFO - Epoch(train) [897][35/63] lr: 1.0253e-03 eta: 3:41:50 time: 0.5006 data_time: 0.0129 memory: 16131 loss: 1.0059 loss_prob: 0.5263 loss_thr: 0.3882 loss_db: 0.0913 2022/10/26 06:34:51 - mmengine - INFO - Epoch(train) [897][40/63] lr: 1.0253e-03 eta: 3:41:43 time: 0.5018 data_time: 0.0112 memory: 16131 loss: 1.0472 loss_prob: 0.5531 loss_thr: 0.3962 loss_db: 0.0978 2022/10/26 06:34:53 - mmengine - INFO - Epoch(train) [897][45/63] lr: 1.0253e-03 eta: 3:41:43 time: 0.4842 data_time: 0.0082 memory: 16131 loss: 0.9822 loss_prob: 0.5236 loss_thr: 0.3675 loss_db: 0.0910 2022/10/26 06:34:56 - mmengine - INFO - Epoch(train) [897][50/63] lr: 1.0253e-03 eta: 3:41:35 time: 0.5039 data_time: 0.0242 memory: 16131 loss: 1.0428 loss_prob: 0.5556 loss_thr: 0.3935 loss_db: 0.0938 2022/10/26 06:34:59 - mmengine - INFO - Epoch(train) [897][55/63] lr: 1.0253e-03 eta: 3:41:35 time: 0.5375 data_time: 0.0252 memory: 16131 loss: 1.0188 loss_prob: 0.5286 loss_thr: 0.3986 loss_db: 0.0915 2022/10/26 06:35:01 - mmengine - INFO - Epoch(train) [897][60/63] lr: 1.0253e-03 eta: 3:41:28 time: 0.5064 data_time: 0.0074 memory: 16131 loss: 0.9399 loss_prob: 0.4769 loss_thr: 0.3789 loss_db: 0.0841 2022/10/26 06:35:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:35:07 - mmengine - INFO - Epoch(train) [898][5/63] lr: 1.0222e-03 eta: 3:41:28 time: 0.6526 data_time: 0.1815 memory: 16131 loss: 0.9781 loss_prob: 0.5062 loss_thr: 0.3857 loss_db: 0.0863 2022/10/26 06:35:09 - mmengine - INFO - Epoch(train) [898][10/63] lr: 1.0222e-03 eta: 3:41:18 time: 0.6854 data_time: 0.1852 memory: 16131 loss: 1.0451 loss_prob: 0.5546 loss_thr: 0.3935 loss_db: 0.0970 2022/10/26 06:35:12 - mmengine - INFO - Epoch(train) [898][15/63] lr: 1.0222e-03 eta: 3:41:18 time: 0.5478 data_time: 0.0089 memory: 16131 loss: 1.0845 loss_prob: 0.5747 loss_thr: 0.4097 loss_db: 0.1001 2022/10/26 06:35:15 - mmengine - INFO - Epoch(train) [898][20/63] lr: 1.0222e-03 eta: 3:41:10 time: 0.5614 data_time: 0.0097 memory: 16131 loss: 1.0716 loss_prob: 0.5745 loss_thr: 0.4001 loss_db: 0.0970 2022/10/26 06:35:17 - mmengine - INFO - Epoch(train) [898][25/63] lr: 1.0222e-03 eta: 3:41:10 time: 0.5036 data_time: 0.0130 memory: 16131 loss: 0.9969 loss_prob: 0.5349 loss_thr: 0.3704 loss_db: 0.0916 2022/10/26 06:35:20 - mmengine - INFO - Epoch(train) [898][30/63] lr: 1.0222e-03 eta: 3:41:03 time: 0.5169 data_time: 0.0309 memory: 16131 loss: 0.9017 loss_prob: 0.4603 loss_thr: 0.3583 loss_db: 0.0830 2022/10/26 06:35:23 - mmengine - INFO - Epoch(train) [898][35/63] lr: 1.0222e-03 eta: 3:41:03 time: 0.5234 data_time: 0.0312 memory: 16131 loss: 0.9785 loss_prob: 0.4994 loss_thr: 0.3910 loss_db: 0.0881 2022/10/26 06:35:25 - mmengine - INFO - Epoch(train) [898][40/63] lr: 1.0222e-03 eta: 3:40:55 time: 0.4998 data_time: 0.0089 memory: 16131 loss: 1.0272 loss_prob: 0.5307 loss_thr: 0.4066 loss_db: 0.0899 2022/10/26 06:35:27 - mmengine - INFO - Epoch(train) [898][45/63] lr: 1.0222e-03 eta: 3:40:55 time: 0.4974 data_time: 0.0057 memory: 16131 loss: 1.0523 loss_prob: 0.5559 loss_thr: 0.4003 loss_db: 0.0961 2022/10/26 06:35:30 - mmengine - INFO - Epoch(train) [898][50/63] lr: 1.0222e-03 eta: 3:40:48 time: 0.5058 data_time: 0.0211 memory: 16131 loss: 1.0106 loss_prob: 0.5380 loss_thr: 0.3784 loss_db: 0.0942 2022/10/26 06:35:33 - mmengine - INFO - Epoch(train) [898][55/63] lr: 1.0222e-03 eta: 3:40:48 time: 0.5005 data_time: 0.0253 memory: 16131 loss: 0.9535 loss_prob: 0.4978 loss_thr: 0.3692 loss_db: 0.0864 2022/10/26 06:35:35 - mmengine - INFO - Epoch(train) [898][60/63] lr: 1.0222e-03 eta: 3:40:40 time: 0.4956 data_time: 0.0111 memory: 16131 loss: 0.9807 loss_prob: 0.5147 loss_thr: 0.3779 loss_db: 0.0881 2022/10/26 06:35:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:35:41 - mmengine - INFO - Epoch(train) [899][5/63] lr: 1.0192e-03 eta: 3:40:40 time: 0.6696 data_time: 0.1838 memory: 16131 loss: 0.9832 loss_prob: 0.5276 loss_thr: 0.3671 loss_db: 0.0884 2022/10/26 06:35:43 - mmengine - INFO - Epoch(train) [899][10/63] lr: 1.0192e-03 eta: 3:40:30 time: 0.7116 data_time: 0.1861 memory: 16131 loss: 0.9918 loss_prob: 0.5148 loss_thr: 0.3868 loss_db: 0.0902 2022/10/26 06:35:46 - mmengine - INFO - Epoch(train) [899][15/63] lr: 1.0192e-03 eta: 3:40:30 time: 0.5655 data_time: 0.0097 memory: 16131 loss: 1.0005 loss_prob: 0.5230 loss_thr: 0.3853 loss_db: 0.0922 2022/10/26 06:35:49 - mmengine - INFO - Epoch(train) [899][20/63] lr: 1.0192e-03 eta: 3:40:23 time: 0.5841 data_time: 0.0104 memory: 16131 loss: 1.0028 loss_prob: 0.5316 loss_thr: 0.3787 loss_db: 0.0924 2022/10/26 06:35:53 - mmengine - INFO - Epoch(train) [899][25/63] lr: 1.0192e-03 eta: 3:40:23 time: 0.6243 data_time: 0.0365 memory: 16131 loss: 0.9753 loss_prob: 0.5062 loss_thr: 0.3831 loss_db: 0.0859 2022/10/26 06:35:55 - mmengine - INFO - Epoch(train) [899][30/63] lr: 1.0192e-03 eta: 3:40:16 time: 0.5891 data_time: 0.0333 memory: 16131 loss: 1.0774 loss_prob: 0.5854 loss_thr: 0.3957 loss_db: 0.0963 2022/10/26 06:35:58 - mmengine - INFO - Epoch(train) [899][35/63] lr: 1.0192e-03 eta: 3:40:16 time: 0.4992 data_time: 0.0047 memory: 16131 loss: 1.1889 loss_prob: 0.6585 loss_thr: 0.4197 loss_db: 0.1107 2022/10/26 06:36:01 - mmengine - INFO - Epoch(train) [899][40/63] lr: 1.0192e-03 eta: 3:40:08 time: 0.5377 data_time: 0.0042 memory: 16131 loss: 1.0748 loss_prob: 0.5691 loss_thr: 0.4071 loss_db: 0.0986 2022/10/26 06:36:03 - mmengine - INFO - Epoch(train) [899][45/63] lr: 1.0192e-03 eta: 3:40:08 time: 0.5752 data_time: 0.0062 memory: 16131 loss: 0.9992 loss_prob: 0.5258 loss_thr: 0.3830 loss_db: 0.0904 2022/10/26 06:36:06 - mmengine - INFO - Epoch(train) [899][50/63] lr: 1.0192e-03 eta: 3:40:01 time: 0.5690 data_time: 0.0239 memory: 16131 loss: 1.0133 loss_prob: 0.5344 loss_thr: 0.3863 loss_db: 0.0927 2022/10/26 06:36:09 - mmengine - INFO - Epoch(train) [899][55/63] lr: 1.0192e-03 eta: 3:40:01 time: 0.5410 data_time: 0.0220 memory: 16131 loss: 0.9765 loss_prob: 0.5061 loss_thr: 0.3831 loss_db: 0.0873 2022/10/26 06:36:11 - mmengine - INFO - Epoch(train) [899][60/63] lr: 1.0192e-03 eta: 3:39:53 time: 0.5033 data_time: 0.0071 memory: 16131 loss: 0.9942 loss_prob: 0.5164 loss_thr: 0.3874 loss_db: 0.0904 2022/10/26 06:36:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:36:17 - mmengine - INFO - Epoch(train) [900][5/63] lr: 1.0161e-03 eta: 3:39:53 time: 0.6778 data_time: 0.1907 memory: 16131 loss: 1.0705 loss_prob: 0.5612 loss_thr: 0.4130 loss_db: 0.0963 2022/10/26 06:36:20 - mmengine - INFO - Epoch(train) [900][10/63] lr: 1.0161e-03 eta: 3:39:43 time: 0.6982 data_time: 0.1903 memory: 16131 loss: 0.9669 loss_prob: 0.4985 loss_thr: 0.3827 loss_db: 0.0856 2022/10/26 06:36:22 - mmengine - INFO - Epoch(train) [900][15/63] lr: 1.0161e-03 eta: 3:39:43 time: 0.5080 data_time: 0.0091 memory: 16131 loss: 0.9162 loss_prob: 0.4736 loss_thr: 0.3601 loss_db: 0.0825 2022/10/26 06:36:25 - mmengine - INFO - Epoch(train) [900][20/63] lr: 1.0161e-03 eta: 3:39:36 time: 0.5053 data_time: 0.0077 memory: 16131 loss: 0.9332 loss_prob: 0.4868 loss_thr: 0.3604 loss_db: 0.0861 2022/10/26 06:36:28 - mmengine - INFO - Epoch(train) [900][25/63] lr: 1.0161e-03 eta: 3:39:36 time: 0.5724 data_time: 0.0515 memory: 16131 loss: 0.9203 loss_prob: 0.4795 loss_thr: 0.3580 loss_db: 0.0828 2022/10/26 06:36:30 - mmengine - INFO - Epoch(train) [900][30/63] lr: 1.0161e-03 eta: 3:39:29 time: 0.5789 data_time: 0.0545 memory: 16131 loss: 0.9641 loss_prob: 0.5012 loss_thr: 0.3774 loss_db: 0.0855 2022/10/26 06:36:33 - mmengine - INFO - Epoch(train) [900][35/63] lr: 1.0161e-03 eta: 3:39:29 time: 0.4945 data_time: 0.0113 memory: 16131 loss: 1.0392 loss_prob: 0.5502 loss_thr: 0.3938 loss_db: 0.0952 2022/10/26 06:36:35 - mmengine - INFO - Epoch(train) [900][40/63] lr: 1.0161e-03 eta: 3:39:21 time: 0.5061 data_time: 0.0062 memory: 16131 loss: 0.9856 loss_prob: 0.5253 loss_thr: 0.3689 loss_db: 0.0914 2022/10/26 06:36:38 - mmengine - INFO - Epoch(train) [900][45/63] lr: 1.0161e-03 eta: 3:39:21 time: 0.5038 data_time: 0.0052 memory: 16131 loss: 0.9190 loss_prob: 0.4855 loss_thr: 0.3491 loss_db: 0.0844 2022/10/26 06:36:41 - mmengine - INFO - Epoch(train) [900][50/63] lr: 1.0161e-03 eta: 3:39:13 time: 0.5213 data_time: 0.0273 memory: 16131 loss: 0.9476 loss_prob: 0.4996 loss_thr: 0.3617 loss_db: 0.0863 2022/10/26 06:36:43 - mmengine - INFO - Epoch(train) [900][55/63] lr: 1.0161e-03 eta: 3:39:13 time: 0.5298 data_time: 0.0263 memory: 16131 loss: 1.0388 loss_prob: 0.5553 loss_thr: 0.3891 loss_db: 0.0944 2022/10/26 06:36:46 - mmengine - INFO - Epoch(train) [900][60/63] lr: 1.0161e-03 eta: 3:39:06 time: 0.4930 data_time: 0.0056 memory: 16131 loss: 0.9930 loss_prob: 0.5307 loss_thr: 0.3727 loss_db: 0.0897 2022/10/26 06:36:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:36:47 - mmengine - INFO - Saving checkpoint at 900 epochs 2022/10/26 06:36:53 - mmengine - INFO - Epoch(val) [900][5/32] eta: 3:39:06 time: 0.5212 data_time: 0.0693 memory: 16131 2022/10/26 06:36:56 - mmengine - INFO - Epoch(val) [900][10/32] eta: 0:00:12 time: 0.5826 data_time: 0.0964 memory: 15724 2022/10/26 06:36:59 - mmengine - INFO - Epoch(val) [900][15/32] eta: 0:00:12 time: 0.5390 data_time: 0.0540 memory: 15724 2022/10/26 06:37:02 - mmengine - INFO - Epoch(val) [900][20/32] eta: 0:00:06 time: 0.5485 data_time: 0.0559 memory: 15724 2022/10/26 06:37:05 - mmengine - INFO - Epoch(val) [900][25/32] eta: 0:00:06 time: 0.5782 data_time: 0.0604 memory: 15724 2022/10/26 06:37:07 - mmengine - INFO - Epoch(val) [900][30/32] eta: 0:00:01 time: 0.5364 data_time: 0.0311 memory: 15724 2022/10/26 06:37:08 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8411, precision: 0.7569, hmean: 0.7968 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8411, precision: 0.7948, hmean: 0.8173 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8402, precision: 0.8317, hmean: 0.8359 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8368, precision: 0.8566, hmean: 0.8466 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8195, precision: 0.8865, hmean: 0.8516 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7511, precision: 0.9286, hmean: 0.8304 2022/10/26 06:37:08 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1348, precision: 0.9859, hmean: 0.2372 2022/10/26 06:37:08 - mmengine - INFO - Epoch(val) [900][32/32] icdar/precision: 0.8865 icdar/recall: 0.8195 icdar/hmean: 0.8516 2022/10/26 06:37:13 - mmengine - INFO - Epoch(train) [901][5/63] lr: 1.0131e-03 eta: 0:00:01 time: 0.7226 data_time: 0.1903 memory: 16131 loss: 1.0186 loss_prob: 0.5390 loss_thr: 0.3836 loss_db: 0.0960 2022/10/26 06:37:15 - mmengine - INFO - Epoch(train) [901][10/63] lr: 1.0131e-03 eta: 3:38:56 time: 0.7381 data_time: 0.1954 memory: 16131 loss: 1.0575 loss_prob: 0.5647 loss_thr: 0.3937 loss_db: 0.0991 2022/10/26 06:37:18 - mmengine - INFO - Epoch(train) [901][15/63] lr: 1.0131e-03 eta: 3:38:56 time: 0.5212 data_time: 0.0178 memory: 16131 loss: 1.0130 loss_prob: 0.5455 loss_thr: 0.3762 loss_db: 0.0912 2022/10/26 06:37:21 - mmengine - INFO - Epoch(train) [901][20/63] lr: 1.0131e-03 eta: 3:38:49 time: 0.5693 data_time: 0.0146 memory: 16131 loss: 1.0094 loss_prob: 0.5394 loss_thr: 0.3797 loss_db: 0.0904 2022/10/26 06:37:24 - mmengine - INFO - Epoch(train) [901][25/63] lr: 1.0131e-03 eta: 3:38:49 time: 0.5793 data_time: 0.0294 memory: 16131 loss: 0.9768 loss_prob: 0.5127 loss_thr: 0.3742 loss_db: 0.0900 2022/10/26 06:37:27 - mmengine - INFO - Epoch(train) [901][30/63] lr: 1.0131e-03 eta: 3:38:41 time: 0.5701 data_time: 0.0322 memory: 16131 loss: 0.9459 loss_prob: 0.4949 loss_thr: 0.3633 loss_db: 0.0877 2022/10/26 06:37:29 - mmengine - INFO - Epoch(train) [901][35/63] lr: 1.0131e-03 eta: 3:38:41 time: 0.5687 data_time: 0.0155 memory: 16131 loss: 0.9151 loss_prob: 0.4782 loss_thr: 0.3543 loss_db: 0.0826 2022/10/26 06:37:32 - mmengine - INFO - Epoch(train) [901][40/63] lr: 1.0131e-03 eta: 3:38:34 time: 0.5530 data_time: 0.0130 memory: 16131 loss: 0.9768 loss_prob: 0.5187 loss_thr: 0.3705 loss_db: 0.0876 2022/10/26 06:37:35 - mmengine - INFO - Epoch(train) [901][45/63] lr: 1.0131e-03 eta: 3:38:34 time: 0.5301 data_time: 0.0101 memory: 16131 loss: 0.9985 loss_prob: 0.5292 loss_thr: 0.3787 loss_db: 0.0906 2022/10/26 06:37:37 - mmengine - INFO - Epoch(train) [901][50/63] lr: 1.0131e-03 eta: 3:38:26 time: 0.5169 data_time: 0.0179 memory: 16131 loss: 0.9463 loss_prob: 0.4780 loss_thr: 0.3835 loss_db: 0.0847 2022/10/26 06:37:40 - mmengine - INFO - Epoch(train) [901][55/63] lr: 1.0131e-03 eta: 3:38:26 time: 0.5238 data_time: 0.0191 memory: 16131 loss: 0.9665 loss_prob: 0.4922 loss_thr: 0.3897 loss_db: 0.0846 2022/10/26 06:37:44 - mmengine - INFO - Epoch(train) [901][60/63] lr: 1.0131e-03 eta: 3:38:19 time: 0.6284 data_time: 0.0118 memory: 16131 loss: 1.0140 loss_prob: 0.5354 loss_thr: 0.3890 loss_db: 0.0897 2022/10/26 06:37:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:37:50 - mmengine - INFO - Epoch(train) [902][5/63] lr: 1.0100e-03 eta: 3:38:19 time: 0.7461 data_time: 0.2008 memory: 16131 loss: 0.9700 loss_prob: 0.5035 loss_thr: 0.3802 loss_db: 0.0862 2022/10/26 06:37:53 - mmengine - INFO - Epoch(train) [902][10/63] lr: 1.0100e-03 eta: 3:38:10 time: 0.8233 data_time: 0.1940 memory: 16131 loss: 0.9491 loss_prob: 0.4985 loss_thr: 0.3639 loss_db: 0.0867 2022/10/26 06:37:55 - mmengine - INFO - Epoch(train) [902][15/63] lr: 1.0100e-03 eta: 3:38:10 time: 0.5505 data_time: 0.0083 memory: 16131 loss: 0.9809 loss_prob: 0.5178 loss_thr: 0.3727 loss_db: 0.0904 2022/10/26 06:37:58 - mmengine - INFO - Epoch(train) [902][20/63] lr: 1.0100e-03 eta: 3:38:02 time: 0.4917 data_time: 0.0093 memory: 16131 loss: 0.9601 loss_prob: 0.5120 loss_thr: 0.3576 loss_db: 0.0905 2022/10/26 06:38:01 - mmengine - INFO - Epoch(train) [902][25/63] lr: 1.0100e-03 eta: 3:38:02 time: 0.5004 data_time: 0.0227 memory: 16131 loss: 0.9743 loss_prob: 0.5295 loss_thr: 0.3543 loss_db: 0.0906 2022/10/26 06:38:03 - mmengine - INFO - Epoch(train) [902][30/63] lr: 1.0100e-03 eta: 3:37:55 time: 0.5128 data_time: 0.0340 memory: 16131 loss: 0.9951 loss_prob: 0.5290 loss_thr: 0.3771 loss_db: 0.0890 2022/10/26 06:38:06 - mmengine - INFO - Epoch(train) [902][35/63] lr: 1.0100e-03 eta: 3:37:55 time: 0.5447 data_time: 0.0196 memory: 16131 loss: 0.9909 loss_prob: 0.5213 loss_thr: 0.3805 loss_db: 0.0891 2022/10/26 06:38:09 - mmengine - INFO - Epoch(train) [902][40/63] lr: 1.0100e-03 eta: 3:37:47 time: 0.5670 data_time: 0.0051 memory: 16131 loss: 1.0249 loss_prob: 0.5500 loss_thr: 0.3796 loss_db: 0.0954 2022/10/26 06:38:11 - mmengine - INFO - Epoch(train) [902][45/63] lr: 1.0100e-03 eta: 3:37:47 time: 0.5288 data_time: 0.0058 memory: 16131 loss: 1.0604 loss_prob: 0.5636 loss_thr: 0.3989 loss_db: 0.0980 2022/10/26 06:38:14 - mmengine - INFO - Epoch(train) [902][50/63] lr: 1.0100e-03 eta: 3:37:40 time: 0.5248 data_time: 0.0175 memory: 16131 loss: 0.9897 loss_prob: 0.5215 loss_thr: 0.3787 loss_db: 0.0895 2022/10/26 06:38:17 - mmengine - INFO - Epoch(train) [902][55/63] lr: 1.0100e-03 eta: 3:37:40 time: 0.6030 data_time: 0.0304 memory: 16131 loss: 0.9194 loss_prob: 0.4793 loss_thr: 0.3571 loss_db: 0.0831 2022/10/26 06:38:20 - mmengine - INFO - Epoch(train) [902][60/63] lr: 1.0100e-03 eta: 3:37:33 time: 0.5871 data_time: 0.0200 memory: 16131 loss: 1.0118 loss_prob: 0.5359 loss_thr: 0.3841 loss_db: 0.0918 2022/10/26 06:38:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:38:26 - mmengine - INFO - Epoch(train) [903][5/63] lr: 1.0070e-03 eta: 3:37:33 time: 0.6796 data_time: 0.1789 memory: 16131 loss: 1.0544 loss_prob: 0.5589 loss_thr: 0.4001 loss_db: 0.0954 2022/10/26 06:38:28 - mmengine - INFO - Epoch(train) [903][10/63] lr: 1.0070e-03 eta: 3:37:23 time: 0.7105 data_time: 0.1821 memory: 16131 loss: 0.9877 loss_prob: 0.5219 loss_thr: 0.3770 loss_db: 0.0887 2022/10/26 06:38:31 - mmengine - INFO - Epoch(train) [903][15/63] lr: 1.0070e-03 eta: 3:37:23 time: 0.5222 data_time: 0.0100 memory: 16131 loss: 0.9985 loss_prob: 0.5265 loss_thr: 0.3825 loss_db: 0.0894 2022/10/26 06:38:33 - mmengine - INFO - Epoch(train) [903][20/63] lr: 1.0070e-03 eta: 3:37:15 time: 0.5029 data_time: 0.0113 memory: 16131 loss: 1.0527 loss_prob: 0.5612 loss_thr: 0.3948 loss_db: 0.0967 2022/10/26 06:38:36 - mmengine - INFO - Epoch(train) [903][25/63] lr: 1.0070e-03 eta: 3:37:15 time: 0.5125 data_time: 0.0286 memory: 16131 loss: 0.9887 loss_prob: 0.5272 loss_thr: 0.3698 loss_db: 0.0917 2022/10/26 06:38:39 - mmengine - INFO - Epoch(train) [903][30/63] lr: 1.0070e-03 eta: 3:37:08 time: 0.5542 data_time: 0.0335 memory: 16131 loss: 0.9173 loss_prob: 0.4908 loss_thr: 0.3432 loss_db: 0.0833 2022/10/26 06:38:42 - mmengine - INFO - Epoch(train) [903][35/63] lr: 1.0070e-03 eta: 3:37:08 time: 0.5638 data_time: 0.0145 memory: 16131 loss: 0.9153 loss_prob: 0.4818 loss_thr: 0.3526 loss_db: 0.0809 2022/10/26 06:38:45 - mmengine - INFO - Epoch(train) [903][40/63] lr: 1.0070e-03 eta: 3:37:01 time: 0.5598 data_time: 0.0105 memory: 16131 loss: 0.9323 loss_prob: 0.4828 loss_thr: 0.3648 loss_db: 0.0847 2022/10/26 06:38:47 - mmengine - INFO - Epoch(train) [903][45/63] lr: 1.0070e-03 eta: 3:37:01 time: 0.5391 data_time: 0.0139 memory: 16131 loss: 0.9393 loss_prob: 0.4905 loss_thr: 0.3624 loss_db: 0.0864 2022/10/26 06:38:50 - mmengine - INFO - Epoch(train) [903][50/63] lr: 1.0070e-03 eta: 3:36:53 time: 0.5277 data_time: 0.0186 memory: 16131 loss: 0.9398 loss_prob: 0.4909 loss_thr: 0.3638 loss_db: 0.0852 2022/10/26 06:38:53 - mmengine - INFO - Epoch(train) [903][55/63] lr: 1.0070e-03 eta: 3:36:53 time: 0.5641 data_time: 0.0225 memory: 16131 loss: 0.9886 loss_prob: 0.5202 loss_thr: 0.3798 loss_db: 0.0886 2022/10/26 06:38:55 - mmengine - INFO - Epoch(train) [903][60/63] lr: 1.0070e-03 eta: 3:36:46 time: 0.5399 data_time: 0.0129 memory: 16131 loss: 0.9994 loss_prob: 0.5274 loss_thr: 0.3830 loss_db: 0.0889 2022/10/26 06:38:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:39:01 - mmengine - INFO - Epoch(train) [904][5/63] lr: 1.0039e-03 eta: 3:36:46 time: 0.6787 data_time: 0.2067 memory: 16131 loss: 0.9882 loss_prob: 0.5223 loss_thr: 0.3758 loss_db: 0.0900 2022/10/26 06:39:03 - mmengine - INFO - Epoch(train) [904][10/63] lr: 1.0039e-03 eta: 3:36:36 time: 0.6959 data_time: 0.2092 memory: 16131 loss: 0.9491 loss_prob: 0.4974 loss_thr: 0.3666 loss_db: 0.0851 2022/10/26 06:39:06 - mmengine - INFO - Epoch(train) [904][15/63] lr: 1.0039e-03 eta: 3:36:36 time: 0.4941 data_time: 0.0117 memory: 16131 loss: 0.9100 loss_prob: 0.4721 loss_thr: 0.3561 loss_db: 0.0818 2022/10/26 06:39:08 - mmengine - INFO - Epoch(train) [904][20/63] lr: 1.0039e-03 eta: 3:36:28 time: 0.4971 data_time: 0.0080 memory: 16131 loss: 0.9279 loss_prob: 0.4808 loss_thr: 0.3626 loss_db: 0.0845 2022/10/26 06:39:11 - mmengine - INFO - Epoch(train) [904][25/63] lr: 1.0039e-03 eta: 3:36:28 time: 0.5094 data_time: 0.0213 memory: 16131 loss: 1.0029 loss_prob: 0.5335 loss_thr: 0.3752 loss_db: 0.0942 2022/10/26 06:39:14 - mmengine - INFO - Epoch(train) [904][30/63] lr: 1.0039e-03 eta: 3:36:21 time: 0.5083 data_time: 0.0321 memory: 16131 loss: 1.0513 loss_prob: 0.5654 loss_thr: 0.3876 loss_db: 0.0983 2022/10/26 06:39:16 - mmengine - INFO - Epoch(train) [904][35/63] lr: 1.0039e-03 eta: 3:36:21 time: 0.5199 data_time: 0.0199 memory: 16131 loss: 1.0022 loss_prob: 0.5330 loss_thr: 0.3773 loss_db: 0.0918 2022/10/26 06:39:19 - mmengine - INFO - Epoch(train) [904][40/63] lr: 1.0039e-03 eta: 3:36:13 time: 0.5267 data_time: 0.0103 memory: 16131 loss: 0.9793 loss_prob: 0.5141 loss_thr: 0.3746 loss_db: 0.0906 2022/10/26 06:39:22 - mmengine - INFO - Epoch(train) [904][45/63] lr: 1.0039e-03 eta: 3:36:13 time: 0.5476 data_time: 0.0071 memory: 16131 loss: 0.9271 loss_prob: 0.4866 loss_thr: 0.3554 loss_db: 0.0851 2022/10/26 06:39:25 - mmengine - INFO - Epoch(train) [904][50/63] lr: 1.0039e-03 eta: 3:36:06 time: 0.5778 data_time: 0.0185 memory: 16131 loss: 0.8789 loss_prob: 0.4656 loss_thr: 0.3339 loss_db: 0.0795 2022/10/26 06:39:27 - mmengine - INFO - Epoch(train) [904][55/63] lr: 1.0039e-03 eta: 3:36:06 time: 0.5541 data_time: 0.0299 memory: 16131 loss: 0.8952 loss_prob: 0.4699 loss_thr: 0.3437 loss_db: 0.0815 2022/10/26 06:39:30 - mmengine - INFO - Epoch(train) [904][60/63] lr: 1.0039e-03 eta: 3:35:58 time: 0.5110 data_time: 0.0172 memory: 16131 loss: 1.0405 loss_prob: 0.5596 loss_thr: 0.3855 loss_db: 0.0954 2022/10/26 06:39:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:39:35 - mmengine - INFO - Epoch(train) [905][5/63] lr: 1.0009e-03 eta: 3:35:58 time: 0.6753 data_time: 0.1832 memory: 16131 loss: 1.0110 loss_prob: 0.5391 loss_thr: 0.3800 loss_db: 0.0919 2022/10/26 06:39:38 - mmengine - INFO - Epoch(train) [905][10/63] lr: 1.0009e-03 eta: 3:35:49 time: 0.7298 data_time: 0.1895 memory: 16131 loss: 1.0404 loss_prob: 0.5607 loss_thr: 0.3850 loss_db: 0.0948 2022/10/26 06:39:41 - mmengine - INFO - Epoch(train) [905][15/63] lr: 1.0009e-03 eta: 3:35:49 time: 0.5140 data_time: 0.0148 memory: 16131 loss: 1.0239 loss_prob: 0.5493 loss_thr: 0.3808 loss_db: 0.0937 2022/10/26 06:39:43 - mmengine - INFO - Epoch(train) [905][20/63] lr: 1.0009e-03 eta: 3:35:41 time: 0.5099 data_time: 0.0097 memory: 16131 loss: 0.9823 loss_prob: 0.5083 loss_thr: 0.3849 loss_db: 0.0891 2022/10/26 06:39:46 - mmengine - INFO - Epoch(train) [905][25/63] lr: 1.0009e-03 eta: 3:35:41 time: 0.5254 data_time: 0.0211 memory: 16131 loss: 0.9713 loss_prob: 0.4934 loss_thr: 0.3921 loss_db: 0.0857 2022/10/26 06:39:48 - mmengine - INFO - Epoch(train) [905][30/63] lr: 1.0009e-03 eta: 3:35:34 time: 0.5108 data_time: 0.0294 memory: 16131 loss: 0.9403 loss_prob: 0.4828 loss_thr: 0.3732 loss_db: 0.0843 2022/10/26 06:39:51 - mmengine - INFO - Epoch(train) [905][35/63] lr: 1.0009e-03 eta: 3:35:34 time: 0.5059 data_time: 0.0195 memory: 16131 loss: 0.8888 loss_prob: 0.4571 loss_thr: 0.3502 loss_db: 0.0816 2022/10/26 06:39:54 - mmengine - INFO - Epoch(train) [905][40/63] lr: 1.0009e-03 eta: 3:35:26 time: 0.5648 data_time: 0.0099 memory: 16131 loss: 0.9166 loss_prob: 0.4771 loss_thr: 0.3558 loss_db: 0.0837 2022/10/26 06:39:57 - mmengine - INFO - Epoch(train) [905][45/63] lr: 1.0009e-03 eta: 3:35:26 time: 0.5585 data_time: 0.0090 memory: 16131 loss: 1.0294 loss_prob: 0.5588 loss_thr: 0.3760 loss_db: 0.0946 2022/10/26 06:39:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:39:59 - mmengine - INFO - Epoch(train) [905][50/63] lr: 1.0009e-03 eta: 3:35:19 time: 0.5042 data_time: 0.0252 memory: 16131 loss: 1.0900 loss_prob: 0.6051 loss_thr: 0.3862 loss_db: 0.0987 2022/10/26 06:40:02 - mmengine - INFO - Epoch(train) [905][55/63] lr: 1.0009e-03 eta: 3:35:19 time: 0.5108 data_time: 0.0237 memory: 16131 loss: 1.0539 loss_prob: 0.5646 loss_thr: 0.3939 loss_db: 0.0954 2022/10/26 06:40:04 - mmengine - INFO - Epoch(train) [905][60/63] lr: 1.0009e-03 eta: 3:35:11 time: 0.5247 data_time: 0.0078 memory: 16131 loss: 0.9788 loss_prob: 0.5085 loss_thr: 0.3806 loss_db: 0.0896 2022/10/26 06:40:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:40:10 - mmengine - INFO - Epoch(train) [906][5/63] lr: 9.9782e-04 eta: 3:35:11 time: 0.6970 data_time: 0.1509 memory: 16131 loss: 1.0322 loss_prob: 0.5442 loss_thr: 0.3966 loss_db: 0.0915 2022/10/26 06:40:13 - mmengine - INFO - Epoch(train) [906][10/63] lr: 9.9782e-04 eta: 3:35:02 time: 0.7596 data_time: 0.1589 memory: 16131 loss: 1.0188 loss_prob: 0.5296 loss_thr: 0.3972 loss_db: 0.0921 2022/10/26 06:40:16 - mmengine - INFO - Epoch(train) [906][15/63] lr: 9.9782e-04 eta: 3:35:02 time: 0.5641 data_time: 0.0137 memory: 16131 loss: 0.9506 loss_prob: 0.4862 loss_thr: 0.3781 loss_db: 0.0863 2022/10/26 06:40:18 - mmengine - INFO - Epoch(train) [906][20/63] lr: 9.9782e-04 eta: 3:34:54 time: 0.5093 data_time: 0.0065 memory: 16131 loss: 1.0007 loss_prob: 0.5222 loss_thr: 0.3882 loss_db: 0.0904 2022/10/26 06:40:21 - mmengine - INFO - Epoch(train) [906][25/63] lr: 9.9782e-04 eta: 3:34:54 time: 0.4995 data_time: 0.0081 memory: 16131 loss: 0.9773 loss_prob: 0.5119 loss_thr: 0.3767 loss_db: 0.0888 2022/10/26 06:40:24 - mmengine - INFO - Epoch(train) [906][30/63] lr: 9.9782e-04 eta: 3:34:47 time: 0.5284 data_time: 0.0417 memory: 16131 loss: 0.9514 loss_prob: 0.4955 loss_thr: 0.3689 loss_db: 0.0870 2022/10/26 06:40:26 - mmengine - INFO - Epoch(train) [906][35/63] lr: 9.9782e-04 eta: 3:34:47 time: 0.5396 data_time: 0.0391 memory: 16131 loss: 1.0138 loss_prob: 0.5406 loss_thr: 0.3814 loss_db: 0.0918 2022/10/26 06:40:29 - mmengine - INFO - Epoch(train) [906][40/63] lr: 9.9782e-04 eta: 3:34:39 time: 0.5064 data_time: 0.0044 memory: 16131 loss: 1.0488 loss_prob: 0.5583 loss_thr: 0.3951 loss_db: 0.0953 2022/10/26 06:40:32 - mmengine - INFO - Epoch(train) [906][45/63] lr: 9.9782e-04 eta: 3:34:39 time: 0.5407 data_time: 0.0108 memory: 16131 loss: 1.0640 loss_prob: 0.5536 loss_thr: 0.4120 loss_db: 0.0984 2022/10/26 06:40:35 - mmengine - INFO - Epoch(train) [906][50/63] lr: 9.9782e-04 eta: 3:34:32 time: 0.5902 data_time: 0.0186 memory: 16131 loss: 1.0607 loss_prob: 0.5550 loss_thr: 0.4086 loss_db: 0.0971 2022/10/26 06:40:38 - mmengine - INFO - Epoch(train) [906][55/63] lr: 9.9782e-04 eta: 3:34:32 time: 0.5883 data_time: 0.0252 memory: 16131 loss: 0.9688 loss_prob: 0.5077 loss_thr: 0.3724 loss_db: 0.0887 2022/10/26 06:40:41 - mmengine - INFO - Epoch(train) [906][60/63] lr: 9.9782e-04 eta: 3:34:25 time: 0.5881 data_time: 0.0195 memory: 16131 loss: 0.9770 loss_prob: 0.5213 loss_thr: 0.3677 loss_db: 0.0880 2022/10/26 06:40:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:40:46 - mmengine - INFO - Epoch(train) [907][5/63] lr: 9.9477e-04 eta: 3:34:25 time: 0.7280 data_time: 0.1945 memory: 16131 loss: 1.0875 loss_prob: 0.5899 loss_thr: 0.3985 loss_db: 0.0991 2022/10/26 06:40:49 - mmengine - INFO - Epoch(train) [907][10/63] lr: 9.9477e-04 eta: 3:34:15 time: 0.7048 data_time: 0.1988 memory: 16131 loss: 1.0467 loss_prob: 0.5534 loss_thr: 0.3983 loss_db: 0.0950 2022/10/26 06:40:51 - mmengine - INFO - Epoch(train) [907][15/63] lr: 9.9477e-04 eta: 3:34:15 time: 0.4988 data_time: 0.0122 memory: 16131 loss: 1.0111 loss_prob: 0.5301 loss_thr: 0.3872 loss_db: 0.0938 2022/10/26 06:40:54 - mmengine - INFO - Epoch(train) [907][20/63] lr: 9.9477e-04 eta: 3:34:07 time: 0.5253 data_time: 0.0079 memory: 16131 loss: 1.0073 loss_prob: 0.5314 loss_thr: 0.3820 loss_db: 0.0939 2022/10/26 06:40:57 - mmengine - INFO - Epoch(train) [907][25/63] lr: 9.9477e-04 eta: 3:34:07 time: 0.5430 data_time: 0.0114 memory: 16131 loss: 0.9434 loss_prob: 0.4977 loss_thr: 0.3610 loss_db: 0.0847 2022/10/26 06:40:59 - mmengine - INFO - Epoch(train) [907][30/63] lr: 9.9477e-04 eta: 3:34:00 time: 0.5166 data_time: 0.0192 memory: 16131 loss: 0.9681 loss_prob: 0.5166 loss_thr: 0.3639 loss_db: 0.0876 2022/10/26 06:41:03 - mmengine - INFO - Epoch(train) [907][35/63] lr: 9.9477e-04 eta: 3:34:00 time: 0.5628 data_time: 0.0248 memory: 16131 loss: 1.0134 loss_prob: 0.5409 loss_thr: 0.3809 loss_db: 0.0916 2022/10/26 06:41:06 - mmengine - INFO - Epoch(train) [907][40/63] lr: 9.9477e-04 eta: 3:33:53 time: 0.6434 data_time: 0.0246 memory: 16131 loss: 1.0530 loss_prob: 0.5573 loss_thr: 0.4002 loss_db: 0.0954 2022/10/26 06:41:09 - mmengine - INFO - Epoch(train) [907][45/63] lr: 9.9477e-04 eta: 3:33:53 time: 0.6357 data_time: 0.0137 memory: 16131 loss: 1.0330 loss_prob: 0.5404 loss_thr: 0.3996 loss_db: 0.0930 2022/10/26 06:41:12 - mmengine - INFO - Epoch(train) [907][50/63] lr: 9.9477e-04 eta: 3:33:45 time: 0.5976 data_time: 0.0142 memory: 16131 loss: 1.1269 loss_prob: 0.6007 loss_thr: 0.4235 loss_db: 0.1028 2022/10/26 06:41:14 - mmengine - INFO - Epoch(train) [907][55/63] lr: 9.9477e-04 eta: 3:33:45 time: 0.5511 data_time: 0.0182 memory: 16131 loss: 1.0879 loss_prob: 0.5787 loss_thr: 0.4080 loss_db: 0.1011 2022/10/26 06:41:17 - mmengine - INFO - Epoch(train) [907][60/63] lr: 9.9477e-04 eta: 3:33:38 time: 0.5064 data_time: 0.0127 memory: 16131 loss: 0.9771 loss_prob: 0.5139 loss_thr: 0.3727 loss_db: 0.0906 2022/10/26 06:41:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:41:23 - mmengine - INFO - Epoch(train) [908][5/63] lr: 9.9171e-04 eta: 3:33:38 time: 0.7034 data_time: 0.1994 memory: 16131 loss: 0.9985 loss_prob: 0.5226 loss_thr: 0.3849 loss_db: 0.0910 2022/10/26 06:41:25 - mmengine - INFO - Epoch(train) [908][10/63] lr: 9.9171e-04 eta: 3:33:28 time: 0.7079 data_time: 0.1952 memory: 16131 loss: 1.0696 loss_prob: 0.5839 loss_thr: 0.3891 loss_db: 0.0966 2022/10/26 06:41:28 - mmengine - INFO - Epoch(train) [908][15/63] lr: 9.9171e-04 eta: 3:33:28 time: 0.5584 data_time: 0.0058 memory: 16131 loss: 1.0677 loss_prob: 0.5856 loss_thr: 0.3832 loss_db: 0.0989 2022/10/26 06:41:31 - mmengine - INFO - Epoch(train) [908][20/63] lr: 9.9171e-04 eta: 3:33:21 time: 0.5519 data_time: 0.0046 memory: 16131 loss: 0.9815 loss_prob: 0.5135 loss_thr: 0.3773 loss_db: 0.0906 2022/10/26 06:41:34 - mmengine - INFO - Epoch(train) [908][25/63] lr: 9.9171e-04 eta: 3:33:21 time: 0.5059 data_time: 0.0197 memory: 16131 loss: 0.9617 loss_prob: 0.4956 loss_thr: 0.3782 loss_db: 0.0879 2022/10/26 06:41:36 - mmengine - INFO - Epoch(train) [908][30/63] lr: 9.9171e-04 eta: 3:33:13 time: 0.5128 data_time: 0.0309 memory: 16131 loss: 0.9890 loss_prob: 0.5124 loss_thr: 0.3872 loss_db: 0.0894 2022/10/26 06:41:39 - mmengine - INFO - Epoch(train) [908][35/63] lr: 9.9171e-04 eta: 3:33:13 time: 0.5271 data_time: 0.0187 memory: 16131 loss: 0.9624 loss_prob: 0.5032 loss_thr: 0.3726 loss_db: 0.0866 2022/10/26 06:41:42 - mmengine - INFO - Epoch(train) [908][40/63] lr: 9.9171e-04 eta: 3:33:06 time: 0.5517 data_time: 0.0119 memory: 16131 loss: 0.9274 loss_prob: 0.4978 loss_thr: 0.3439 loss_db: 0.0857 2022/10/26 06:41:44 - mmengine - INFO - Epoch(train) [908][45/63] lr: 9.9171e-04 eta: 3:33:06 time: 0.5403 data_time: 0.0092 memory: 16131 loss: 0.9099 loss_prob: 0.4820 loss_thr: 0.3451 loss_db: 0.0828 2022/10/26 06:41:47 - mmengine - INFO - Epoch(train) [908][50/63] lr: 9.9171e-04 eta: 3:32:59 time: 0.5577 data_time: 0.0157 memory: 16131 loss: 0.9232 loss_prob: 0.4784 loss_thr: 0.3613 loss_db: 0.0835 2022/10/26 06:41:50 - mmengine - INFO - Epoch(train) [908][55/63] lr: 9.9171e-04 eta: 3:32:59 time: 0.5450 data_time: 0.0230 memory: 16131 loss: 1.0132 loss_prob: 0.5436 loss_thr: 0.3775 loss_db: 0.0921 2022/10/26 06:41:52 - mmengine - INFO - Epoch(train) [908][60/63] lr: 9.9171e-04 eta: 3:32:51 time: 0.5093 data_time: 0.0138 memory: 16131 loss: 1.0843 loss_prob: 0.5812 loss_thr: 0.4051 loss_db: 0.0980 2022/10/26 06:41:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:41:58 - mmengine - INFO - Epoch(train) [909][5/63] lr: 9.8866e-04 eta: 3:32:51 time: 0.6702 data_time: 0.1571 memory: 16131 loss: 1.0109 loss_prob: 0.5266 loss_thr: 0.3930 loss_db: 0.0914 2022/10/26 06:42:01 - mmengine - INFO - Epoch(train) [909][10/63] lr: 9.8866e-04 eta: 3:32:41 time: 0.6898 data_time: 0.1662 memory: 16131 loss: 1.0342 loss_prob: 0.5438 loss_thr: 0.3971 loss_db: 0.0934 2022/10/26 06:42:03 - mmengine - INFO - Epoch(train) [909][15/63] lr: 9.8866e-04 eta: 3:32:41 time: 0.5370 data_time: 0.0184 memory: 16131 loss: 1.0273 loss_prob: 0.5397 loss_thr: 0.3971 loss_db: 0.0905 2022/10/26 06:42:06 - mmengine - INFO - Epoch(train) [909][20/63] lr: 9.8866e-04 eta: 3:32:34 time: 0.5046 data_time: 0.0092 memory: 16131 loss: 1.0757 loss_prob: 0.5731 loss_thr: 0.4056 loss_db: 0.0970 2022/10/26 06:42:08 - mmengine - INFO - Epoch(train) [909][25/63] lr: 9.8866e-04 eta: 3:32:34 time: 0.4997 data_time: 0.0199 memory: 16131 loss: 1.0649 loss_prob: 0.5583 loss_thr: 0.4090 loss_db: 0.0975 2022/10/26 06:42:11 - mmengine - INFO - Epoch(train) [909][30/63] lr: 9.8866e-04 eta: 3:32:26 time: 0.4991 data_time: 0.0216 memory: 16131 loss: 0.9871 loss_prob: 0.5026 loss_thr: 0.3971 loss_db: 0.0873 2022/10/26 06:42:13 - mmengine - INFO - Epoch(train) [909][35/63] lr: 9.8866e-04 eta: 3:32:26 time: 0.5142 data_time: 0.0162 memory: 16131 loss: 0.9992 loss_prob: 0.5238 loss_thr: 0.3855 loss_db: 0.0899 2022/10/26 06:42:16 - mmengine - INFO - Epoch(train) [909][40/63] lr: 9.8866e-04 eta: 3:32:19 time: 0.5146 data_time: 0.0166 memory: 16131 loss: 0.9655 loss_prob: 0.5132 loss_thr: 0.3635 loss_db: 0.0887 2022/10/26 06:42:18 - mmengine - INFO - Epoch(train) [909][45/63] lr: 9.8866e-04 eta: 3:32:19 time: 0.4873 data_time: 0.0100 memory: 16131 loss: 0.9694 loss_prob: 0.5180 loss_thr: 0.3632 loss_db: 0.0882 2022/10/26 06:42:21 - mmengine - INFO - Epoch(train) [909][50/63] lr: 9.8866e-04 eta: 3:32:11 time: 0.5217 data_time: 0.0222 memory: 16131 loss: 0.9994 loss_prob: 0.5338 loss_thr: 0.3744 loss_db: 0.0913 2022/10/26 06:42:24 - mmengine - INFO - Epoch(train) [909][55/63] lr: 9.8866e-04 eta: 3:32:11 time: 0.5501 data_time: 0.0286 memory: 16131 loss: 0.9961 loss_prob: 0.5236 loss_thr: 0.3799 loss_db: 0.0927 2022/10/26 06:42:27 - mmengine - INFO - Epoch(train) [909][60/63] lr: 9.8866e-04 eta: 3:32:04 time: 0.5757 data_time: 0.0133 memory: 16131 loss: 0.9756 loss_prob: 0.5126 loss_thr: 0.3738 loss_db: 0.0892 2022/10/26 06:42:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:42:33 - mmengine - INFO - Epoch(train) [910][5/63] lr: 9.8560e-04 eta: 3:32:04 time: 0.7418 data_time: 0.2136 memory: 16131 loss: 1.0564 loss_prob: 0.5514 loss_thr: 0.4113 loss_db: 0.0936 2022/10/26 06:42:36 - mmengine - INFO - Epoch(train) [910][10/63] lr: 9.8560e-04 eta: 3:31:54 time: 0.7654 data_time: 0.2146 memory: 16131 loss: 1.0722 loss_prob: 0.5681 loss_thr: 0.4057 loss_db: 0.0984 2022/10/26 06:42:38 - mmengine - INFO - Epoch(train) [910][15/63] lr: 9.8560e-04 eta: 3:31:54 time: 0.5338 data_time: 0.0110 memory: 16131 loss: 0.9786 loss_prob: 0.5236 loss_thr: 0.3627 loss_db: 0.0923 2022/10/26 06:42:41 - mmengine - INFO - Epoch(train) [910][20/63] lr: 9.8560e-04 eta: 3:31:47 time: 0.5193 data_time: 0.0077 memory: 16131 loss: 0.9450 loss_prob: 0.4952 loss_thr: 0.3624 loss_db: 0.0874 2022/10/26 06:42:44 - mmengine - INFO - Epoch(train) [910][25/63] lr: 9.8560e-04 eta: 3:31:47 time: 0.5881 data_time: 0.0453 memory: 16131 loss: 1.0116 loss_prob: 0.5265 loss_thr: 0.3933 loss_db: 0.0918 2022/10/26 06:42:47 - mmengine - INFO - Epoch(train) [910][30/63] lr: 9.8560e-04 eta: 3:31:40 time: 0.5574 data_time: 0.0454 memory: 16131 loss: 0.9977 loss_prob: 0.5163 loss_thr: 0.3908 loss_db: 0.0906 2022/10/26 06:42:49 - mmengine - INFO - Epoch(train) [910][35/63] lr: 9.8560e-04 eta: 3:31:40 time: 0.5051 data_time: 0.0121 memory: 16131 loss: 0.9259 loss_prob: 0.4802 loss_thr: 0.3606 loss_db: 0.0851 2022/10/26 06:42:52 - mmengine - INFO - Epoch(train) [910][40/63] lr: 9.8560e-04 eta: 3:31:32 time: 0.5287 data_time: 0.0133 memory: 16131 loss: 0.9947 loss_prob: 0.5285 loss_thr: 0.3749 loss_db: 0.0913 2022/10/26 06:42:54 - mmengine - INFO - Epoch(train) [910][45/63] lr: 9.8560e-04 eta: 3:31:32 time: 0.5053 data_time: 0.0087 memory: 16131 loss: 1.0269 loss_prob: 0.5467 loss_thr: 0.3860 loss_db: 0.0942 2022/10/26 06:42:57 - mmengine - INFO - Epoch(train) [910][50/63] lr: 9.8560e-04 eta: 3:31:25 time: 0.5166 data_time: 0.0262 memory: 16131 loss: 0.9940 loss_prob: 0.5254 loss_thr: 0.3780 loss_db: 0.0906 2022/10/26 06:43:00 - mmengine - INFO - Epoch(train) [910][55/63] lr: 9.8560e-04 eta: 3:31:25 time: 0.5403 data_time: 0.0256 memory: 16131 loss: 0.9960 loss_prob: 0.5260 loss_thr: 0.3805 loss_db: 0.0894 2022/10/26 06:43:02 - mmengine - INFO - Epoch(train) [910][60/63] lr: 9.8560e-04 eta: 3:31:17 time: 0.5303 data_time: 0.0053 memory: 16131 loss: 1.0009 loss_prob: 0.5295 loss_thr: 0.3805 loss_db: 0.0909 2022/10/26 06:43:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:43:09 - mmengine - INFO - Epoch(train) [911][5/63] lr: 9.8254e-04 eta: 3:31:17 time: 0.7728 data_time: 0.1846 memory: 16131 loss: 1.0263 loss_prob: 0.5492 loss_thr: 0.3831 loss_db: 0.0940 2022/10/26 06:43:12 - mmengine - INFO - Epoch(train) [911][10/63] lr: 9.8254e-04 eta: 3:31:08 time: 0.8300 data_time: 0.1854 memory: 16131 loss: 1.0053 loss_prob: 0.5315 loss_thr: 0.3843 loss_db: 0.0895 2022/10/26 06:43:14 - mmengine - INFO - Epoch(train) [911][15/63] lr: 9.8254e-04 eta: 3:31:08 time: 0.5162 data_time: 0.0056 memory: 16131 loss: 0.9415 loss_prob: 0.4777 loss_thr: 0.3812 loss_db: 0.0826 2022/10/26 06:43:17 - mmengine - INFO - Epoch(train) [911][20/63] lr: 9.8254e-04 eta: 3:31:00 time: 0.5278 data_time: 0.0047 memory: 16131 loss: 1.0433 loss_prob: 0.5423 loss_thr: 0.4055 loss_db: 0.0955 2022/10/26 06:43:20 - mmengine - INFO - Epoch(train) [911][25/63] lr: 9.8254e-04 eta: 3:31:00 time: 0.5712 data_time: 0.0431 memory: 16131 loss: 1.0512 loss_prob: 0.5561 loss_thr: 0.3995 loss_db: 0.0956 2022/10/26 06:43:23 - mmengine - INFO - Epoch(train) [911][30/63] lr: 9.8254e-04 eta: 3:30:53 time: 0.5429 data_time: 0.0443 memory: 16131 loss: 1.0136 loss_prob: 0.5340 loss_thr: 0.3874 loss_db: 0.0922 2022/10/26 06:43:25 - mmengine - INFO - Epoch(train) [911][35/63] lr: 9.8254e-04 eta: 3:30:53 time: 0.5165 data_time: 0.0071 memory: 16131 loss: 0.9888 loss_prob: 0.5240 loss_thr: 0.3728 loss_db: 0.0919 2022/10/26 06:43:28 - mmengine - INFO - Epoch(train) [911][40/63] lr: 9.8254e-04 eta: 3:30:45 time: 0.5052 data_time: 0.0091 memory: 16131 loss: 0.9949 loss_prob: 0.5311 loss_thr: 0.3731 loss_db: 0.0908 2022/10/26 06:43:30 - mmengine - INFO - Epoch(train) [911][45/63] lr: 9.8254e-04 eta: 3:30:45 time: 0.4927 data_time: 0.0076 memory: 16131 loss: 0.9700 loss_prob: 0.5128 loss_thr: 0.3692 loss_db: 0.0880 2022/10/26 06:43:33 - mmengine - INFO - Epoch(train) [911][50/63] lr: 9.8254e-04 eta: 3:30:38 time: 0.5320 data_time: 0.0219 memory: 16131 loss: 0.9675 loss_prob: 0.5063 loss_thr: 0.3718 loss_db: 0.0894 2022/10/26 06:43:36 - mmengine - INFO - Epoch(train) [911][55/63] lr: 9.8254e-04 eta: 3:30:38 time: 0.5393 data_time: 0.0224 memory: 16131 loss: 0.9791 loss_prob: 0.5135 loss_thr: 0.3759 loss_db: 0.0898 2022/10/26 06:43:38 - mmengine - INFO - Epoch(train) [911][60/63] lr: 9.8254e-04 eta: 3:30:31 time: 0.5275 data_time: 0.0063 memory: 16131 loss: 0.9705 loss_prob: 0.5092 loss_thr: 0.3734 loss_db: 0.0880 2022/10/26 06:43:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:43:44 - mmengine - INFO - Epoch(train) [912][5/63] lr: 9.7948e-04 eta: 3:30:31 time: 0.6625 data_time: 0.1670 memory: 16131 loss: 0.9755 loss_prob: 0.5267 loss_thr: 0.3640 loss_db: 0.0848 2022/10/26 06:43:47 - mmengine - INFO - Epoch(train) [912][10/63] lr: 9.7948e-04 eta: 3:30:21 time: 0.7103 data_time: 0.1692 memory: 16131 loss: 1.0596 loss_prob: 0.5824 loss_thr: 0.3863 loss_db: 0.0910 2022/10/26 06:43:49 - mmengine - INFO - Epoch(train) [912][15/63] lr: 9.7948e-04 eta: 3:30:21 time: 0.5262 data_time: 0.0111 memory: 16131 loss: 1.0020 loss_prob: 0.5300 loss_thr: 0.3815 loss_db: 0.0905 2022/10/26 06:43:52 - mmengine - INFO - Epoch(train) [912][20/63] lr: 9.7948e-04 eta: 3:30:13 time: 0.5035 data_time: 0.0075 memory: 16131 loss: 0.9639 loss_prob: 0.5072 loss_thr: 0.3673 loss_db: 0.0894 2022/10/26 06:43:54 - mmengine - INFO - Epoch(train) [912][25/63] lr: 9.7948e-04 eta: 3:30:13 time: 0.5246 data_time: 0.0236 memory: 16131 loss: 1.0539 loss_prob: 0.5660 loss_thr: 0.3890 loss_db: 0.0989 2022/10/26 06:43:57 - mmengine - INFO - Epoch(train) [912][30/63] lr: 9.7948e-04 eta: 3:30:06 time: 0.5433 data_time: 0.0298 memory: 16131 loss: 1.1059 loss_prob: 0.6032 loss_thr: 0.3982 loss_db: 0.1045 2022/10/26 06:44:00 - mmengine - INFO - Epoch(train) [912][35/63] lr: 9.7948e-04 eta: 3:30:06 time: 0.5045 data_time: 0.0112 memory: 16131 loss: 0.9665 loss_prob: 0.5199 loss_thr: 0.3577 loss_db: 0.0890 2022/10/26 06:44:02 - mmengine - INFO - Epoch(train) [912][40/63] lr: 9.7948e-04 eta: 3:29:58 time: 0.5048 data_time: 0.0073 memory: 16131 loss: 0.9493 loss_prob: 0.5061 loss_thr: 0.3567 loss_db: 0.0865 2022/10/26 06:44:05 - mmengine - INFO - Epoch(train) [912][45/63] lr: 9.7948e-04 eta: 3:29:58 time: 0.5205 data_time: 0.0081 memory: 16131 loss: 1.0070 loss_prob: 0.5410 loss_thr: 0.3727 loss_db: 0.0933 2022/10/26 06:44:07 - mmengine - INFO - Epoch(train) [912][50/63] lr: 9.7948e-04 eta: 3:29:51 time: 0.5167 data_time: 0.0205 memory: 16131 loss: 1.0546 loss_prob: 0.5619 loss_thr: 0.3958 loss_db: 0.0969 2022/10/26 06:44:10 - mmengine - INFO - Epoch(train) [912][55/63] lr: 9.7948e-04 eta: 3:29:51 time: 0.5174 data_time: 0.0223 memory: 16131 loss: 1.0937 loss_prob: 0.5784 loss_thr: 0.4159 loss_db: 0.0994 2022/10/26 06:44:13 - mmengine - INFO - Epoch(train) [912][60/63] lr: 9.7948e-04 eta: 3:29:43 time: 0.5263 data_time: 0.0076 memory: 16131 loss: 1.0164 loss_prob: 0.5262 loss_thr: 0.4008 loss_db: 0.0895 2022/10/26 06:44:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:44:18 - mmengine - INFO - Epoch(train) [913][5/63] lr: 9.7642e-04 eta: 3:29:43 time: 0.6885 data_time: 0.2096 memory: 16131 loss: 0.9600 loss_prob: 0.4993 loss_thr: 0.3732 loss_db: 0.0875 2022/10/26 06:44:21 - mmengine - INFO - Epoch(train) [913][10/63] lr: 9.7642e-04 eta: 3:29:34 time: 0.7167 data_time: 0.2053 memory: 16131 loss: 0.9646 loss_prob: 0.5053 loss_thr: 0.3720 loss_db: 0.0873 2022/10/26 06:44:24 - mmengine - INFO - Epoch(train) [913][15/63] lr: 9.7642e-04 eta: 3:29:34 time: 0.5661 data_time: 0.0081 memory: 16131 loss: 0.9366 loss_prob: 0.4934 loss_thr: 0.3580 loss_db: 0.0852 2022/10/26 06:44:27 - mmengine - INFO - Epoch(train) [913][20/63] lr: 9.7642e-04 eta: 3:29:27 time: 0.6084 data_time: 0.0080 memory: 16131 loss: 0.8951 loss_prob: 0.4696 loss_thr: 0.3432 loss_db: 0.0823 2022/10/26 06:44:30 - mmengine - INFO - Epoch(train) [913][25/63] lr: 9.7642e-04 eta: 3:29:27 time: 0.5941 data_time: 0.0299 memory: 16131 loss: 0.9542 loss_prob: 0.4979 loss_thr: 0.3686 loss_db: 0.0877 2022/10/26 06:44:33 - mmengine - INFO - Epoch(train) [913][30/63] lr: 9.7642e-04 eta: 3:29:19 time: 0.5407 data_time: 0.0374 memory: 16131 loss: 1.0725 loss_prob: 0.5775 loss_thr: 0.3965 loss_db: 0.0985 2022/10/26 06:44:35 - mmengine - INFO - Epoch(train) [913][35/63] lr: 9.7642e-04 eta: 3:29:19 time: 0.5014 data_time: 0.0147 memory: 16131 loss: 1.0780 loss_prob: 0.5792 loss_thr: 0.3994 loss_db: 0.0994 2022/10/26 06:44:38 - mmengine - INFO - Epoch(train) [913][40/63] lr: 9.7642e-04 eta: 3:29:12 time: 0.5001 data_time: 0.0051 memory: 16131 loss: 1.0193 loss_prob: 0.5342 loss_thr: 0.3914 loss_db: 0.0938 2022/10/26 06:44:40 - mmengine - INFO - Epoch(train) [913][45/63] lr: 9.7642e-04 eta: 3:29:12 time: 0.5301 data_time: 0.0066 memory: 16131 loss: 0.9838 loss_prob: 0.5151 loss_thr: 0.3795 loss_db: 0.0892 2022/10/26 06:44:43 - mmengine - INFO - Epoch(train) [913][50/63] lr: 9.7642e-04 eta: 3:29:04 time: 0.5303 data_time: 0.0191 memory: 16131 loss: 1.0242 loss_prob: 0.5343 loss_thr: 0.3983 loss_db: 0.0916 2022/10/26 06:44:45 - mmengine - INFO - Epoch(train) [913][55/63] lr: 9.7642e-04 eta: 3:29:04 time: 0.5191 data_time: 0.0278 memory: 16131 loss: 1.0797 loss_prob: 0.5716 loss_thr: 0.4099 loss_db: 0.0981 2022/10/26 06:44:48 - mmengine - INFO - Epoch(train) [913][60/63] lr: 9.7642e-04 eta: 3:28:57 time: 0.5252 data_time: 0.0154 memory: 16131 loss: 1.0735 loss_prob: 0.5728 loss_thr: 0.4004 loss_db: 0.1003 2022/10/26 06:44:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:44:55 - mmengine - INFO - Epoch(train) [914][5/63] lr: 9.7336e-04 eta: 3:28:57 time: 0.8379 data_time: 0.2580 memory: 16131 loss: 0.9711 loss_prob: 0.5140 loss_thr: 0.3681 loss_db: 0.0889 2022/10/26 06:44:58 - mmengine - INFO - Epoch(train) [914][10/63] lr: 9.7336e-04 eta: 3:28:48 time: 0.8258 data_time: 0.2516 memory: 16131 loss: 1.0419 loss_prob: 0.5565 loss_thr: 0.3878 loss_db: 0.0976 2022/10/26 06:45:00 - mmengine - INFO - Epoch(train) [914][15/63] lr: 9.7336e-04 eta: 3:28:48 time: 0.5031 data_time: 0.0070 memory: 16131 loss: 0.9876 loss_prob: 0.5194 loss_thr: 0.3767 loss_db: 0.0915 2022/10/26 06:45:03 - mmengine - INFO - Epoch(train) [914][20/63] lr: 9.7336e-04 eta: 3:28:40 time: 0.5197 data_time: 0.0082 memory: 16131 loss: 0.9328 loss_prob: 0.4913 loss_thr: 0.3559 loss_db: 0.0856 2022/10/26 06:45:06 - mmengine - INFO - Epoch(train) [914][25/63] lr: 9.7336e-04 eta: 3:28:40 time: 0.5564 data_time: 0.0381 memory: 16131 loss: 0.9496 loss_prob: 0.5022 loss_thr: 0.3591 loss_db: 0.0883 2022/10/26 06:45:08 - mmengine - INFO - Epoch(train) [914][30/63] lr: 9.7336e-04 eta: 3:28:33 time: 0.5272 data_time: 0.0355 memory: 16131 loss: 0.9589 loss_prob: 0.5038 loss_thr: 0.3659 loss_db: 0.0892 2022/10/26 06:45:11 - mmengine - INFO - Epoch(train) [914][35/63] lr: 9.7336e-04 eta: 3:28:33 time: 0.4819 data_time: 0.0053 memory: 16131 loss: 0.9572 loss_prob: 0.4974 loss_thr: 0.3723 loss_db: 0.0875 2022/10/26 06:45:14 - mmengine - INFO - Epoch(train) [914][40/63] lr: 9.7336e-04 eta: 3:28:25 time: 0.5099 data_time: 0.0085 memory: 16131 loss: 1.0091 loss_prob: 0.5374 loss_thr: 0.3809 loss_db: 0.0908 2022/10/26 06:45:16 - mmengine - INFO - Epoch(train) [914][45/63] lr: 9.7336e-04 eta: 3:28:25 time: 0.5404 data_time: 0.0109 memory: 16131 loss: 0.9684 loss_prob: 0.5190 loss_thr: 0.3614 loss_db: 0.0880 2022/10/26 06:45:19 - mmengine - INFO - Epoch(train) [914][50/63] lr: 9.7336e-04 eta: 3:28:18 time: 0.5704 data_time: 0.0256 memory: 16131 loss: 0.9084 loss_prob: 0.4747 loss_thr: 0.3495 loss_db: 0.0842 2022/10/26 06:45:22 - mmengine - INFO - Epoch(train) [914][55/63] lr: 9.7336e-04 eta: 3:28:18 time: 0.5392 data_time: 0.0228 memory: 16131 loss: 0.9837 loss_prob: 0.5165 loss_thr: 0.3762 loss_db: 0.0910 2022/10/26 06:45:24 - mmengine - INFO - Epoch(train) [914][60/63] lr: 9.7336e-04 eta: 3:28:10 time: 0.5227 data_time: 0.0056 memory: 16131 loss: 1.0354 loss_prob: 0.5428 loss_thr: 0.3983 loss_db: 0.0944 2022/10/26 06:45:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:45:31 - mmengine - INFO - Epoch(train) [915][5/63] lr: 9.7029e-04 eta: 3:28:10 time: 0.7872 data_time: 0.1895 memory: 16131 loss: 0.9859 loss_prob: 0.5153 loss_thr: 0.3808 loss_db: 0.0898 2022/10/26 06:45:34 - mmengine - INFO - Epoch(train) [915][10/63] lr: 9.7029e-04 eta: 3:28:01 time: 0.8196 data_time: 0.1928 memory: 16131 loss: 0.9500 loss_prob: 0.4956 loss_thr: 0.3684 loss_db: 0.0860 2022/10/26 06:45:36 - mmengine - INFO - Epoch(train) [915][15/63] lr: 9.7029e-04 eta: 3:28:01 time: 0.5301 data_time: 0.0089 memory: 16131 loss: 0.9922 loss_prob: 0.5234 loss_thr: 0.3778 loss_db: 0.0910 2022/10/26 06:45:39 - mmengine - INFO - Epoch(train) [915][20/63] lr: 9.7029e-04 eta: 3:27:54 time: 0.5205 data_time: 0.0111 memory: 16131 loss: 0.9763 loss_prob: 0.5165 loss_thr: 0.3689 loss_db: 0.0909 2022/10/26 06:45:42 - mmengine - INFO - Epoch(train) [915][25/63] lr: 9.7029e-04 eta: 3:27:54 time: 0.5353 data_time: 0.0179 memory: 16131 loss: 0.9705 loss_prob: 0.5138 loss_thr: 0.3666 loss_db: 0.0901 2022/10/26 06:45:44 - mmengine - INFO - Epoch(train) [915][30/63] lr: 9.7029e-04 eta: 3:27:46 time: 0.5253 data_time: 0.0333 memory: 16131 loss: 0.9442 loss_prob: 0.4881 loss_thr: 0.3710 loss_db: 0.0851 2022/10/26 06:45:47 - mmengine - INFO - Epoch(train) [915][35/63] lr: 9.7029e-04 eta: 3:27:46 time: 0.5175 data_time: 0.0281 memory: 16131 loss: 0.9638 loss_prob: 0.5036 loss_thr: 0.3729 loss_db: 0.0872 2022/10/26 06:45:50 - mmengine - INFO - Epoch(train) [915][40/63] lr: 9.7029e-04 eta: 3:27:39 time: 0.5461 data_time: 0.0063 memory: 16131 loss: 1.0382 loss_prob: 0.5553 loss_thr: 0.3874 loss_db: 0.0955 2022/10/26 06:45:52 - mmengine - INFO - Epoch(train) [915][45/63] lr: 9.7029e-04 eta: 3:27:39 time: 0.5418 data_time: 0.0065 memory: 16131 loss: 0.9631 loss_prob: 0.4995 loss_thr: 0.3772 loss_db: 0.0864 2022/10/26 06:45:55 - mmengine - INFO - Epoch(train) [915][50/63] lr: 9.7029e-04 eta: 3:27:31 time: 0.4969 data_time: 0.0126 memory: 16131 loss: 0.8684 loss_prob: 0.4477 loss_thr: 0.3414 loss_db: 0.0793 2022/10/26 06:45:57 - mmengine - INFO - Epoch(train) [915][55/63] lr: 9.7029e-04 eta: 3:27:31 time: 0.4958 data_time: 0.0230 memory: 16131 loss: 0.9431 loss_prob: 0.5020 loss_thr: 0.3523 loss_db: 0.0888 2022/10/26 06:46:00 - mmengine - INFO - Epoch(train) [915][60/63] lr: 9.7029e-04 eta: 3:27:24 time: 0.5224 data_time: 0.0186 memory: 16131 loss: 0.9212 loss_prob: 0.4840 loss_thr: 0.3517 loss_db: 0.0855 2022/10/26 06:46:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:46:07 - mmengine - INFO - Epoch(train) [916][5/63] lr: 9.6723e-04 eta: 3:27:24 time: 0.8370 data_time: 0.2769 memory: 16131 loss: 0.9970 loss_prob: 0.5281 loss_thr: 0.3766 loss_db: 0.0923 2022/10/26 06:46:10 - mmengine - INFO - Epoch(train) [916][10/63] lr: 9.6723e-04 eta: 3:27:15 time: 0.8577 data_time: 0.2760 memory: 16131 loss: 0.9738 loss_prob: 0.5160 loss_thr: 0.3721 loss_db: 0.0858 2022/10/26 06:46:13 - mmengine - INFO - Epoch(train) [916][15/63] lr: 9.6723e-04 eta: 3:27:15 time: 0.5320 data_time: 0.0091 memory: 16131 loss: 1.0477 loss_prob: 0.5593 loss_thr: 0.3940 loss_db: 0.0945 2022/10/26 06:46:15 - mmengine - INFO - Epoch(train) [916][20/63] lr: 9.6723e-04 eta: 3:27:07 time: 0.5313 data_time: 0.0064 memory: 16131 loss: 1.0852 loss_prob: 0.5854 loss_thr: 0.3990 loss_db: 0.1008 2022/10/26 06:46:18 - mmengine - INFO - Epoch(train) [916][25/63] lr: 9.6723e-04 eta: 3:27:07 time: 0.5276 data_time: 0.0357 memory: 16131 loss: 0.9643 loss_prob: 0.5089 loss_thr: 0.3658 loss_db: 0.0896 2022/10/26 06:46:20 - mmengine - INFO - Epoch(train) [916][30/63] lr: 9.6723e-04 eta: 3:27:00 time: 0.5237 data_time: 0.0357 memory: 16131 loss: 0.9772 loss_prob: 0.5255 loss_thr: 0.3595 loss_db: 0.0922 2022/10/26 06:46:23 - mmengine - INFO - Epoch(train) [916][35/63] lr: 9.6723e-04 eta: 3:27:00 time: 0.4871 data_time: 0.0063 memory: 16131 loss: 0.9898 loss_prob: 0.5486 loss_thr: 0.3489 loss_db: 0.0923 2022/10/26 06:46:25 - mmengine - INFO - Epoch(train) [916][40/63] lr: 9.6723e-04 eta: 3:26:52 time: 0.4982 data_time: 0.0081 memory: 16131 loss: 1.0084 loss_prob: 0.5436 loss_thr: 0.3747 loss_db: 0.0901 2022/10/26 06:46:28 - mmengine - INFO - Epoch(train) [916][45/63] lr: 9.6723e-04 eta: 3:26:52 time: 0.5366 data_time: 0.0115 memory: 16131 loss: 0.9378 loss_prob: 0.4851 loss_thr: 0.3685 loss_db: 0.0841 2022/10/26 06:46:31 - mmengine - INFO - Epoch(train) [916][50/63] lr: 9.6723e-04 eta: 3:26:45 time: 0.5384 data_time: 0.0273 memory: 16131 loss: 0.8821 loss_prob: 0.4537 loss_thr: 0.3470 loss_db: 0.0814 2022/10/26 06:46:33 - mmengine - INFO - Epoch(train) [916][55/63] lr: 9.6723e-04 eta: 3:26:45 time: 0.5140 data_time: 0.0245 memory: 16131 loss: 0.9682 loss_prob: 0.5144 loss_thr: 0.3642 loss_db: 0.0896 2022/10/26 06:46:36 - mmengine - INFO - Epoch(train) [916][60/63] lr: 9.6723e-04 eta: 3:26:37 time: 0.5242 data_time: 0.0062 memory: 16131 loss: 1.0242 loss_prob: 0.5524 loss_thr: 0.3777 loss_db: 0.0941 2022/10/26 06:46:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:46:42 - mmengine - INFO - Epoch(train) [917][5/63] lr: 9.6416e-04 eta: 3:26:37 time: 0.7138 data_time: 0.1972 memory: 16131 loss: 1.0805 loss_prob: 0.5806 loss_thr: 0.4014 loss_db: 0.0986 2022/10/26 06:46:45 - mmengine - INFO - Epoch(train) [917][10/63] lr: 9.6416e-04 eta: 3:26:28 time: 0.7396 data_time: 0.1986 memory: 16131 loss: 1.0432 loss_prob: 0.5606 loss_thr: 0.3868 loss_db: 0.0958 2022/10/26 06:46:48 - mmengine - INFO - Epoch(train) [917][15/63] lr: 9.6416e-04 eta: 3:26:28 time: 0.5808 data_time: 0.0110 memory: 16131 loss: 0.9107 loss_prob: 0.4733 loss_thr: 0.3564 loss_db: 0.0810 2022/10/26 06:46:50 - mmengine - INFO - Epoch(train) [917][20/63] lr: 9.6416e-04 eta: 3:26:20 time: 0.5518 data_time: 0.0058 memory: 16131 loss: 0.9639 loss_prob: 0.5014 loss_thr: 0.3758 loss_db: 0.0867 2022/10/26 06:46:53 - mmengine - INFO - Epoch(train) [917][25/63] lr: 9.6416e-04 eta: 3:26:20 time: 0.5196 data_time: 0.0290 memory: 16131 loss: 0.9530 loss_prob: 0.4990 loss_thr: 0.3670 loss_db: 0.0870 2022/10/26 06:46:56 - mmengine - INFO - Epoch(train) [917][30/63] lr: 9.6416e-04 eta: 3:26:13 time: 0.5273 data_time: 0.0379 memory: 16131 loss: 0.9443 loss_prob: 0.4922 loss_thr: 0.3656 loss_db: 0.0865 2022/10/26 06:46:58 - mmengine - INFO - Epoch(train) [917][35/63] lr: 9.6416e-04 eta: 3:26:13 time: 0.5219 data_time: 0.0151 memory: 16131 loss: 1.1197 loss_prob: 0.5865 loss_thr: 0.4314 loss_db: 0.1018 2022/10/26 06:47:01 - mmengine - INFO - Epoch(train) [917][40/63] lr: 9.6416e-04 eta: 3:26:06 time: 0.5167 data_time: 0.0114 memory: 16131 loss: 1.1210 loss_prob: 0.5839 loss_thr: 0.4355 loss_db: 0.1016 2022/10/26 06:47:03 - mmengine - INFO - Epoch(train) [917][45/63] lr: 9.6416e-04 eta: 3:26:06 time: 0.5020 data_time: 0.0124 memory: 16131 loss: 0.9833 loss_prob: 0.5119 loss_thr: 0.3810 loss_db: 0.0904 2022/10/26 06:47:06 - mmengine - INFO - Epoch(train) [917][50/63] lr: 9.6416e-04 eta: 3:25:58 time: 0.5090 data_time: 0.0181 memory: 16131 loss: 0.9883 loss_prob: 0.5201 loss_thr: 0.3784 loss_db: 0.0898 2022/10/26 06:47:08 - mmengine - INFO - Epoch(train) [917][55/63] lr: 9.6416e-04 eta: 3:25:58 time: 0.5143 data_time: 0.0205 memory: 16131 loss: 0.9979 loss_prob: 0.5232 loss_thr: 0.3840 loss_db: 0.0908 2022/10/26 06:47:11 - mmengine - INFO - Epoch(train) [917][60/63] lr: 9.6416e-04 eta: 3:25:51 time: 0.5101 data_time: 0.0105 memory: 16131 loss: 0.9972 loss_prob: 0.5325 loss_thr: 0.3723 loss_db: 0.0925 2022/10/26 06:47:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:47:17 - mmengine - INFO - Epoch(train) [918][5/63] lr: 9.6110e-04 eta: 3:25:51 time: 0.6972 data_time: 0.1869 memory: 16131 loss: 0.9933 loss_prob: 0.5285 loss_thr: 0.3742 loss_db: 0.0906 2022/10/26 06:47:20 - mmengine - INFO - Epoch(train) [918][10/63] lr: 9.6110e-04 eta: 3:25:41 time: 0.7393 data_time: 0.1952 memory: 16131 loss: 0.8984 loss_prob: 0.4591 loss_thr: 0.3593 loss_db: 0.0800 2022/10/26 06:47:22 - mmengine - INFO - Epoch(train) [918][15/63] lr: 9.6110e-04 eta: 3:25:41 time: 0.5666 data_time: 0.0186 memory: 16131 loss: 0.9478 loss_prob: 0.4923 loss_thr: 0.3720 loss_db: 0.0835 2022/10/26 06:47:25 - mmengine - INFO - Epoch(train) [918][20/63] lr: 9.6110e-04 eta: 3:25:34 time: 0.5310 data_time: 0.0092 memory: 16131 loss: 1.0044 loss_prob: 0.5240 loss_thr: 0.3899 loss_db: 0.0905 2022/10/26 06:47:28 - mmengine - INFO - Epoch(train) [918][25/63] lr: 9.6110e-04 eta: 3:25:34 time: 0.5342 data_time: 0.0252 memory: 16131 loss: 0.9653 loss_prob: 0.5047 loss_thr: 0.3708 loss_db: 0.0899 2022/10/26 06:47:30 - mmengine - INFO - Epoch(train) [918][30/63] lr: 9.6110e-04 eta: 3:25:26 time: 0.5271 data_time: 0.0294 memory: 16131 loss: 0.9622 loss_prob: 0.5109 loss_thr: 0.3592 loss_db: 0.0921 2022/10/26 06:47:33 - mmengine - INFO - Epoch(train) [918][35/63] lr: 9.6110e-04 eta: 3:25:26 time: 0.5081 data_time: 0.0198 memory: 16131 loss: 0.9960 loss_prob: 0.5293 loss_thr: 0.3742 loss_db: 0.0926 2022/10/26 06:47:36 - mmengine - INFO - Epoch(train) [918][40/63] lr: 9.6110e-04 eta: 3:25:19 time: 0.5354 data_time: 0.0215 memory: 16131 loss: 1.0332 loss_prob: 0.5403 loss_thr: 0.4003 loss_db: 0.0926 2022/10/26 06:47:38 - mmengine - INFO - Epoch(train) [918][45/63] lr: 9.6110e-04 eta: 3:25:19 time: 0.5261 data_time: 0.0115 memory: 16131 loss: 1.1089 loss_prob: 0.5848 loss_thr: 0.4227 loss_db: 0.1014 2022/10/26 06:47:41 - mmengine - INFO - Epoch(train) [918][50/63] lr: 9.6110e-04 eta: 3:25:11 time: 0.5094 data_time: 0.0211 memory: 16131 loss: 1.0738 loss_prob: 0.5668 loss_thr: 0.4087 loss_db: 0.0983 2022/10/26 06:47:43 - mmengine - INFO - Epoch(train) [918][55/63] lr: 9.6110e-04 eta: 3:25:11 time: 0.5085 data_time: 0.0211 memory: 16131 loss: 0.9817 loss_prob: 0.5140 loss_thr: 0.3775 loss_db: 0.0902 2022/10/26 06:47:46 - mmengine - INFO - Epoch(train) [918][60/63] lr: 9.6110e-04 eta: 3:25:04 time: 0.5497 data_time: 0.0116 memory: 16131 loss: 1.0051 loss_prob: 0.5275 loss_thr: 0.3851 loss_db: 0.0926 2022/10/26 06:47:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:47:52 - mmengine - INFO - Epoch(train) [919][5/63] lr: 9.5803e-04 eta: 3:25:04 time: 0.7329 data_time: 0.1671 memory: 16131 loss: 0.9475 loss_prob: 0.4944 loss_thr: 0.3663 loss_db: 0.0868 2022/10/26 06:47:55 - mmengine - INFO - Epoch(train) [919][10/63] lr: 9.5803e-04 eta: 3:24:54 time: 0.7143 data_time: 0.1709 memory: 16131 loss: 0.9676 loss_prob: 0.5042 loss_thr: 0.3748 loss_db: 0.0886 2022/10/26 06:47:57 - mmengine - INFO - Epoch(train) [919][15/63] lr: 9.5803e-04 eta: 3:24:54 time: 0.5260 data_time: 0.0126 memory: 16131 loss: 1.0195 loss_prob: 0.5308 loss_thr: 0.3952 loss_db: 0.0936 2022/10/26 06:48:00 - mmengine - INFO - Epoch(train) [919][20/63] lr: 9.5803e-04 eta: 3:24:47 time: 0.5099 data_time: 0.0085 memory: 16131 loss: 1.0271 loss_prob: 0.5427 loss_thr: 0.3903 loss_db: 0.0941 2022/10/26 06:48:02 - mmengine - INFO - Epoch(train) [919][25/63] lr: 9.5803e-04 eta: 3:24:47 time: 0.4897 data_time: 0.0128 memory: 16131 loss: 1.0468 loss_prob: 0.5519 loss_thr: 0.3994 loss_db: 0.0954 2022/10/26 06:48:05 - mmengine - INFO - Epoch(train) [919][30/63] lr: 9.5803e-04 eta: 3:24:39 time: 0.5009 data_time: 0.0286 memory: 16131 loss: 1.0324 loss_prob: 0.5438 loss_thr: 0.3936 loss_db: 0.0949 2022/10/26 06:48:08 - mmengine - INFO - Epoch(train) [919][35/63] lr: 9.5803e-04 eta: 3:24:39 time: 0.5283 data_time: 0.0297 memory: 16131 loss: 1.0053 loss_prob: 0.5391 loss_thr: 0.3741 loss_db: 0.0922 2022/10/26 06:48:10 - mmengine - INFO - Epoch(train) [919][40/63] lr: 9.5803e-04 eta: 3:24:32 time: 0.5308 data_time: 0.0113 memory: 16131 loss: 0.9736 loss_prob: 0.5122 loss_thr: 0.3739 loss_db: 0.0875 2022/10/26 06:48:13 - mmengine - INFO - Epoch(train) [919][45/63] lr: 9.5803e-04 eta: 3:24:32 time: 0.5119 data_time: 0.0066 memory: 16131 loss: 0.9556 loss_prob: 0.4932 loss_thr: 0.3776 loss_db: 0.0848 2022/10/26 06:48:15 - mmengine - INFO - Epoch(train) [919][50/63] lr: 9.5803e-04 eta: 3:24:24 time: 0.5091 data_time: 0.0147 memory: 16131 loss: 0.9668 loss_prob: 0.4989 loss_thr: 0.3814 loss_db: 0.0864 2022/10/26 06:48:18 - mmengine - INFO - Epoch(train) [919][55/63] lr: 9.5803e-04 eta: 3:24:24 time: 0.5031 data_time: 0.0207 memory: 16131 loss: 0.9781 loss_prob: 0.5087 loss_thr: 0.3801 loss_db: 0.0893 2022/10/26 06:48:20 - mmengine - INFO - Epoch(train) [919][60/63] lr: 9.5803e-04 eta: 3:24:17 time: 0.5109 data_time: 0.0150 memory: 16131 loss: 0.9648 loss_prob: 0.5029 loss_thr: 0.3734 loss_db: 0.0884 2022/10/26 06:48:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:48:26 - mmengine - INFO - Epoch(train) [920][5/63] lr: 9.5496e-04 eta: 3:24:17 time: 0.6918 data_time: 0.1948 memory: 16131 loss: 0.9762 loss_prob: 0.5114 loss_thr: 0.3773 loss_db: 0.0875 2022/10/26 06:48:29 - mmengine - INFO - Epoch(train) [920][10/63] lr: 9.5496e-04 eta: 3:24:07 time: 0.7047 data_time: 0.1993 memory: 16131 loss: 0.9987 loss_prob: 0.5273 loss_thr: 0.3801 loss_db: 0.0913 2022/10/26 06:48:31 - mmengine - INFO - Epoch(train) [920][15/63] lr: 9.5496e-04 eta: 3:24:07 time: 0.5082 data_time: 0.0121 memory: 16131 loss: 1.0132 loss_prob: 0.5372 loss_thr: 0.3820 loss_db: 0.0940 2022/10/26 06:48:34 - mmengine - INFO - Epoch(train) [920][20/63] lr: 9.5496e-04 eta: 3:24:00 time: 0.5324 data_time: 0.0127 memory: 16131 loss: 1.0540 loss_prob: 0.5611 loss_thr: 0.3950 loss_db: 0.0979 2022/10/26 06:48:37 - mmengine - INFO - Epoch(train) [920][25/63] lr: 9.5496e-04 eta: 3:24:00 time: 0.5374 data_time: 0.0185 memory: 16131 loss: 0.9945 loss_prob: 0.5251 loss_thr: 0.3786 loss_db: 0.0908 2022/10/26 06:48:40 - mmengine - INFO - Epoch(train) [920][30/63] lr: 9.5496e-04 eta: 3:23:53 time: 0.5537 data_time: 0.0307 memory: 16131 loss: 0.9182 loss_prob: 0.4723 loss_thr: 0.3636 loss_db: 0.0823 2022/10/26 06:48:42 - mmengine - INFO - Epoch(train) [920][35/63] lr: 9.5496e-04 eta: 3:23:53 time: 0.5347 data_time: 0.0241 memory: 16131 loss: 0.9525 loss_prob: 0.4890 loss_thr: 0.3783 loss_db: 0.0853 2022/10/26 06:48:45 - mmengine - INFO - Epoch(train) [920][40/63] lr: 9.5496e-04 eta: 3:23:45 time: 0.4835 data_time: 0.0077 memory: 16131 loss: 1.0348 loss_prob: 0.5514 loss_thr: 0.3920 loss_db: 0.0914 2022/10/26 06:48:47 - mmengine - INFO - Epoch(train) [920][45/63] lr: 9.5496e-04 eta: 3:23:45 time: 0.5016 data_time: 0.0093 memory: 16131 loss: 0.9987 loss_prob: 0.5348 loss_thr: 0.3752 loss_db: 0.0887 2022/10/26 06:48:50 - mmengine - INFO - Epoch(train) [920][50/63] lr: 9.5496e-04 eta: 3:23:38 time: 0.5098 data_time: 0.0188 memory: 16131 loss: 0.9738 loss_prob: 0.5194 loss_thr: 0.3658 loss_db: 0.0886 2022/10/26 06:48:52 - mmengine - INFO - Epoch(train) [920][55/63] lr: 9.5496e-04 eta: 3:23:38 time: 0.5017 data_time: 0.0232 memory: 16131 loss: 0.9765 loss_prob: 0.5178 loss_thr: 0.3703 loss_db: 0.0884 2022/10/26 06:48:55 - mmengine - INFO - Epoch(train) [920][60/63] lr: 9.5496e-04 eta: 3:23:30 time: 0.4918 data_time: 0.0124 memory: 16131 loss: 1.0579 loss_prob: 0.5707 loss_thr: 0.3912 loss_db: 0.0960 2022/10/26 06:48:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:48:56 - mmengine - INFO - Saving checkpoint at 920 epochs 2022/10/26 06:49:03 - mmengine - INFO - Epoch(val) [920][5/32] eta: 3:23:30 time: 0.5405 data_time: 0.0856 memory: 16131 2022/10/26 06:49:06 - mmengine - INFO - Epoch(val) [920][10/32] eta: 0:00:13 time: 0.5978 data_time: 0.1019 memory: 15724 2022/10/26 06:49:08 - mmengine - INFO - Epoch(val) [920][15/32] eta: 0:00:13 time: 0.5409 data_time: 0.0457 memory: 15724 2022/10/26 06:49:11 - mmengine - INFO - Epoch(val) [920][20/32] eta: 0:00:06 time: 0.5346 data_time: 0.0417 memory: 15724 2022/10/26 06:49:14 - mmengine - INFO - Epoch(val) [920][25/32] eta: 0:00:06 time: 0.5462 data_time: 0.0439 memory: 15724 2022/10/26 06:49:16 - mmengine - INFO - Epoch(val) [920][30/32] eta: 0:00:01 time: 0.5295 data_time: 0.0346 memory: 15724 2022/10/26 06:49:17 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8320, precision: 0.7823, hmean: 0.8063 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8320, precision: 0.8213, hmean: 0.8266 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8315, precision: 0.8486, hmean: 0.8400 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8272, precision: 0.8703, hmean: 0.8482 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8079, precision: 0.8945, hmean: 0.8490 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7193, precision: 0.9332, hmean: 0.8124 2022/10/26 06:49:17 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1180, precision: 0.9879, hmean: 0.2108 2022/10/26 06:49:17 - mmengine - INFO - Epoch(val) [920][32/32] icdar/precision: 0.8945 icdar/recall: 0.8079 icdar/hmean: 0.8490 2022/10/26 06:49:22 - mmengine - INFO - Epoch(train) [921][5/63] lr: 9.5189e-04 eta: 0:00:01 time: 0.7118 data_time: 0.1936 memory: 16131 loss: 1.0304 loss_prob: 0.5556 loss_thr: 0.3796 loss_db: 0.0952 2022/10/26 06:49:25 - mmengine - INFO - Epoch(train) [921][10/63] lr: 9.5189e-04 eta: 3:23:21 time: 0.8341 data_time: 0.1931 memory: 16131 loss: 1.1214 loss_prob: 0.6083 loss_thr: 0.4122 loss_db: 0.1010 2022/10/26 06:49:28 - mmengine - INFO - Epoch(train) [921][15/63] lr: 9.5189e-04 eta: 3:23:21 time: 0.6147 data_time: 0.0057 memory: 16131 loss: 1.0000 loss_prob: 0.5300 loss_thr: 0.3801 loss_db: 0.0899 2022/10/26 06:49:30 - mmengine - INFO - Epoch(train) [921][20/63] lr: 9.5189e-04 eta: 3:23:13 time: 0.5005 data_time: 0.0086 memory: 16131 loss: 0.9331 loss_prob: 0.4919 loss_thr: 0.3541 loss_db: 0.0872 2022/10/26 06:49:33 - mmengine - INFO - Epoch(train) [921][25/63] lr: 9.5189e-04 eta: 3:23:13 time: 0.5085 data_time: 0.0170 memory: 16131 loss: 1.0209 loss_prob: 0.5453 loss_thr: 0.3793 loss_db: 0.0963 2022/10/26 06:49:36 - mmengine - INFO - Epoch(train) [921][30/63] lr: 9.5189e-04 eta: 3:23:06 time: 0.5410 data_time: 0.0378 memory: 16131 loss: 0.9905 loss_prob: 0.5297 loss_thr: 0.3686 loss_db: 0.0922 2022/10/26 06:49:38 - mmengine - INFO - Epoch(train) [921][35/63] lr: 9.5189e-04 eta: 3:23:06 time: 0.5317 data_time: 0.0292 memory: 16131 loss: 0.9870 loss_prob: 0.5318 loss_thr: 0.3653 loss_db: 0.0899 2022/10/26 06:49:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:49:41 - mmengine - INFO - Epoch(train) [921][40/63] lr: 9.5189e-04 eta: 3:22:59 time: 0.5200 data_time: 0.0055 memory: 16131 loss: 1.0190 loss_prob: 0.5455 loss_thr: 0.3806 loss_db: 0.0929 2022/10/26 06:49:44 - mmengine - INFO - Epoch(train) [921][45/63] lr: 9.5189e-04 eta: 3:22:59 time: 0.5193 data_time: 0.0073 memory: 16131 loss: 1.0376 loss_prob: 0.5499 loss_thr: 0.3912 loss_db: 0.0966 2022/10/26 06:49:46 - mmengine - INFO - Epoch(train) [921][50/63] lr: 9.5189e-04 eta: 3:22:51 time: 0.5310 data_time: 0.0230 memory: 16131 loss: 1.0405 loss_prob: 0.5521 loss_thr: 0.3921 loss_db: 0.0963 2022/10/26 06:49:49 - mmengine - INFO - Epoch(train) [921][55/63] lr: 9.5189e-04 eta: 3:22:51 time: 0.5407 data_time: 0.0281 memory: 16131 loss: 0.9991 loss_prob: 0.5243 loss_thr: 0.3845 loss_db: 0.0903 2022/10/26 06:49:51 - mmengine - INFO - Epoch(train) [921][60/63] lr: 9.5189e-04 eta: 3:22:44 time: 0.5149 data_time: 0.0128 memory: 16131 loss: 1.0102 loss_prob: 0.5297 loss_thr: 0.3884 loss_db: 0.0922 2022/10/26 06:49:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:49:58 - mmengine - INFO - Epoch(train) [922][5/63] lr: 9.4882e-04 eta: 3:22:44 time: 0.7316 data_time: 0.1592 memory: 16131 loss: 0.9597 loss_prob: 0.4969 loss_thr: 0.3773 loss_db: 0.0855 2022/10/26 06:50:01 - mmengine - INFO - Epoch(train) [922][10/63] lr: 9.4882e-04 eta: 3:22:34 time: 0.7733 data_time: 0.1592 memory: 16131 loss: 0.8993 loss_prob: 0.4590 loss_thr: 0.3610 loss_db: 0.0794 2022/10/26 06:50:04 - mmengine - INFO - Epoch(train) [922][15/63] lr: 9.4882e-04 eta: 3:22:34 time: 0.5683 data_time: 0.0207 memory: 16131 loss: 0.9643 loss_prob: 0.5077 loss_thr: 0.3687 loss_db: 0.0879 2022/10/26 06:50:06 - mmengine - INFO - Epoch(train) [922][20/63] lr: 9.4882e-04 eta: 3:22:27 time: 0.5473 data_time: 0.0201 memory: 16131 loss: 0.9567 loss_prob: 0.5028 loss_thr: 0.3662 loss_db: 0.0878 2022/10/26 06:50:08 - mmengine - INFO - Epoch(train) [922][25/63] lr: 9.4882e-04 eta: 3:22:27 time: 0.4968 data_time: 0.0076 memory: 16131 loss: 1.0117 loss_prob: 0.5307 loss_thr: 0.3880 loss_db: 0.0930 2022/10/26 06:50:11 - mmengine - INFO - Epoch(train) [922][30/63] lr: 9.4882e-04 eta: 3:22:19 time: 0.5100 data_time: 0.0352 memory: 16131 loss: 1.0231 loss_prob: 0.5370 loss_thr: 0.3928 loss_db: 0.0933 2022/10/26 06:50:14 - mmengine - INFO - Epoch(train) [922][35/63] lr: 9.4882e-04 eta: 3:22:19 time: 0.5462 data_time: 0.0360 memory: 16131 loss: 0.9862 loss_prob: 0.5117 loss_thr: 0.3852 loss_db: 0.0893 2022/10/26 06:50:17 - mmengine - INFO - Epoch(train) [922][40/63] lr: 9.4882e-04 eta: 3:22:12 time: 0.5366 data_time: 0.0111 memory: 16131 loss: 1.0471 loss_prob: 0.5678 loss_thr: 0.3859 loss_db: 0.0934 2022/10/26 06:50:19 - mmengine - INFO - Epoch(train) [922][45/63] lr: 9.4882e-04 eta: 3:22:12 time: 0.5291 data_time: 0.0115 memory: 16131 loss: 1.1275 loss_prob: 0.6178 loss_thr: 0.4090 loss_db: 0.1007 2022/10/26 06:50:22 - mmengine - INFO - Epoch(train) [922][50/63] lr: 9.4882e-04 eta: 3:22:05 time: 0.5714 data_time: 0.0166 memory: 16131 loss: 1.0730 loss_prob: 0.5646 loss_thr: 0.4114 loss_db: 0.0970 2022/10/26 06:50:25 - mmengine - INFO - Epoch(train) [922][55/63] lr: 9.4882e-04 eta: 3:22:05 time: 0.5740 data_time: 0.0237 memory: 16131 loss: 0.9691 loss_prob: 0.5058 loss_thr: 0.3767 loss_db: 0.0866 2022/10/26 06:50:27 - mmengine - INFO - Epoch(train) [922][60/63] lr: 9.4882e-04 eta: 3:21:57 time: 0.5195 data_time: 0.0173 memory: 16131 loss: 0.9631 loss_prob: 0.5124 loss_thr: 0.3641 loss_db: 0.0866 2022/10/26 06:50:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:50:33 - mmengine - INFO - Epoch(train) [923][5/63] lr: 9.4575e-04 eta: 3:21:57 time: 0.6694 data_time: 0.1770 memory: 16131 loss: 1.0531 loss_prob: 0.5663 loss_thr: 0.3885 loss_db: 0.0984 2022/10/26 06:50:36 - mmengine - INFO - Epoch(train) [923][10/63] lr: 9.4575e-04 eta: 3:21:48 time: 0.7091 data_time: 0.1760 memory: 16131 loss: 1.0182 loss_prob: 0.5399 loss_thr: 0.3838 loss_db: 0.0946 2022/10/26 06:50:39 - mmengine - INFO - Epoch(train) [923][15/63] lr: 9.4575e-04 eta: 3:21:48 time: 0.5551 data_time: 0.0111 memory: 16131 loss: 0.9552 loss_prob: 0.4978 loss_thr: 0.3693 loss_db: 0.0881 2022/10/26 06:50:41 - mmengine - INFO - Epoch(train) [923][20/63] lr: 9.4575e-04 eta: 3:21:41 time: 0.5623 data_time: 0.0115 memory: 16131 loss: 1.0612 loss_prob: 0.5537 loss_thr: 0.4106 loss_db: 0.0969 2022/10/26 06:50:44 - mmengine - INFO - Epoch(train) [923][25/63] lr: 9.4575e-04 eta: 3:21:41 time: 0.5248 data_time: 0.0157 memory: 16131 loss: 1.0789 loss_prob: 0.5625 loss_thr: 0.4199 loss_db: 0.0964 2022/10/26 06:50:47 - mmengine - INFO - Epoch(train) [923][30/63] lr: 9.4575e-04 eta: 3:21:33 time: 0.5177 data_time: 0.0296 memory: 16131 loss: 0.9867 loss_prob: 0.5217 loss_thr: 0.3758 loss_db: 0.0892 2022/10/26 06:50:49 - mmengine - INFO - Epoch(train) [923][35/63] lr: 9.4575e-04 eta: 3:21:33 time: 0.4925 data_time: 0.0210 memory: 16131 loss: 0.9800 loss_prob: 0.5272 loss_thr: 0.3631 loss_db: 0.0897 2022/10/26 06:50:51 - mmengine - INFO - Epoch(train) [923][40/63] lr: 9.4575e-04 eta: 3:21:26 time: 0.4833 data_time: 0.0098 memory: 16131 loss: 0.8853 loss_prob: 0.4631 loss_thr: 0.3428 loss_db: 0.0794 2022/10/26 06:50:54 - mmengine - INFO - Epoch(train) [923][45/63] lr: 9.4575e-04 eta: 3:21:26 time: 0.4911 data_time: 0.0122 memory: 16131 loss: 0.8940 loss_prob: 0.4718 loss_thr: 0.3396 loss_db: 0.0826 2022/10/26 06:50:56 - mmengine - INFO - Epoch(train) [923][50/63] lr: 9.4575e-04 eta: 3:21:18 time: 0.5099 data_time: 0.0198 memory: 16131 loss: 1.0106 loss_prob: 0.5439 loss_thr: 0.3723 loss_db: 0.0944 2022/10/26 06:50:59 - mmengine - INFO - Epoch(train) [923][55/63] lr: 9.4575e-04 eta: 3:21:18 time: 0.5565 data_time: 0.0253 memory: 16131 loss: 0.9522 loss_prob: 0.5031 loss_thr: 0.3622 loss_db: 0.0870 2022/10/26 06:51:02 - mmengine - INFO - Epoch(train) [923][60/63] lr: 9.4575e-04 eta: 3:21:11 time: 0.5398 data_time: 0.0147 memory: 16131 loss: 0.9049 loss_prob: 0.4669 loss_thr: 0.3570 loss_db: 0.0810 2022/10/26 06:51:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:51:08 - mmengine - INFO - Epoch(train) [924][5/63] lr: 9.4268e-04 eta: 3:21:11 time: 0.7007 data_time: 0.2045 memory: 16131 loss: 0.9574 loss_prob: 0.5038 loss_thr: 0.3665 loss_db: 0.0872 2022/10/26 06:51:10 - mmengine - INFO - Epoch(train) [924][10/63] lr: 9.4268e-04 eta: 3:21:01 time: 0.7116 data_time: 0.2033 memory: 16131 loss: 0.9775 loss_prob: 0.5172 loss_thr: 0.3721 loss_db: 0.0881 2022/10/26 06:51:13 - mmengine - INFO - Epoch(train) [924][15/63] lr: 9.4268e-04 eta: 3:21:01 time: 0.4935 data_time: 0.0063 memory: 16131 loss: 0.9801 loss_prob: 0.5191 loss_thr: 0.3712 loss_db: 0.0899 2022/10/26 06:51:15 - mmengine - INFO - Epoch(train) [924][20/63] lr: 9.4268e-04 eta: 3:20:54 time: 0.4975 data_time: 0.0062 memory: 16131 loss: 1.0210 loss_prob: 0.5430 loss_thr: 0.3846 loss_db: 0.0934 2022/10/26 06:51:18 - mmengine - INFO - Epoch(train) [924][25/63] lr: 9.4268e-04 eta: 3:20:54 time: 0.5282 data_time: 0.0245 memory: 16131 loss: 1.0202 loss_prob: 0.5411 loss_thr: 0.3850 loss_db: 0.0941 2022/10/26 06:51:21 - mmengine - INFO - Epoch(train) [924][30/63] lr: 9.4268e-04 eta: 3:20:46 time: 0.5466 data_time: 0.0312 memory: 16131 loss: 0.9386 loss_prob: 0.4851 loss_thr: 0.3669 loss_db: 0.0867 2022/10/26 06:51:23 - mmengine - INFO - Epoch(train) [924][35/63] lr: 9.4268e-04 eta: 3:20:46 time: 0.5222 data_time: 0.0116 memory: 16131 loss: 0.9637 loss_prob: 0.4948 loss_thr: 0.3818 loss_db: 0.0871 2022/10/26 06:51:26 - mmengine - INFO - Epoch(train) [924][40/63] lr: 9.4268e-04 eta: 3:20:39 time: 0.5115 data_time: 0.0068 memory: 16131 loss: 0.9748 loss_prob: 0.5061 loss_thr: 0.3821 loss_db: 0.0866 2022/10/26 06:51:28 - mmengine - INFO - Epoch(train) [924][45/63] lr: 9.4268e-04 eta: 3:20:39 time: 0.5179 data_time: 0.0072 memory: 16131 loss: 0.9625 loss_prob: 0.5032 loss_thr: 0.3718 loss_db: 0.0875 2022/10/26 06:51:31 - mmengine - INFO - Epoch(train) [924][50/63] lr: 9.4268e-04 eta: 3:20:31 time: 0.5445 data_time: 0.0191 memory: 16131 loss: 1.0342 loss_prob: 0.5426 loss_thr: 0.3952 loss_db: 0.0963 2022/10/26 06:51:34 - mmengine - INFO - Epoch(train) [924][55/63] lr: 9.4268e-04 eta: 3:20:31 time: 0.5258 data_time: 0.0199 memory: 16131 loss: 0.9950 loss_prob: 0.5189 loss_thr: 0.3858 loss_db: 0.0903 2022/10/26 06:51:36 - mmengine - INFO - Epoch(train) [924][60/63] lr: 9.4268e-04 eta: 3:20:24 time: 0.4821 data_time: 0.0064 memory: 16131 loss: 0.9490 loss_prob: 0.4935 loss_thr: 0.3697 loss_db: 0.0858 2022/10/26 06:51:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:51:42 - mmengine - INFO - Epoch(train) [925][5/63] lr: 9.3960e-04 eta: 3:20:24 time: 0.6788 data_time: 0.1992 memory: 16131 loss: 0.9557 loss_prob: 0.5074 loss_thr: 0.3600 loss_db: 0.0883 2022/10/26 06:51:44 - mmengine - INFO - Epoch(train) [925][10/63] lr: 9.3960e-04 eta: 3:20:14 time: 0.7031 data_time: 0.1967 memory: 16131 loss: 0.9047 loss_prob: 0.4790 loss_thr: 0.3432 loss_db: 0.0825 2022/10/26 06:51:47 - mmengine - INFO - Epoch(train) [925][15/63] lr: 9.3960e-04 eta: 3:20:14 time: 0.4917 data_time: 0.0049 memory: 16131 loss: 0.9280 loss_prob: 0.4908 loss_thr: 0.3520 loss_db: 0.0852 2022/10/26 06:51:49 - mmengine - INFO - Epoch(train) [925][20/63] lr: 9.3960e-04 eta: 3:20:07 time: 0.4948 data_time: 0.0064 memory: 16131 loss: 1.0252 loss_prob: 0.5432 loss_thr: 0.3895 loss_db: 0.0925 2022/10/26 06:51:52 - mmengine - INFO - Epoch(train) [925][25/63] lr: 9.3960e-04 eta: 3:20:07 time: 0.5488 data_time: 0.0430 memory: 16131 loss: 0.9876 loss_prob: 0.5155 loss_thr: 0.3846 loss_db: 0.0876 2022/10/26 06:51:55 - mmengine - INFO - Epoch(train) [925][30/63] lr: 9.3960e-04 eta: 3:20:00 time: 0.5907 data_time: 0.0426 memory: 16131 loss: 0.9824 loss_prob: 0.5137 loss_thr: 0.3793 loss_db: 0.0894 2022/10/26 06:51:58 - mmengine - INFO - Epoch(train) [925][35/63] lr: 9.3960e-04 eta: 3:20:00 time: 0.5584 data_time: 0.0074 memory: 16131 loss: 1.0045 loss_prob: 0.5204 loss_thr: 0.3920 loss_db: 0.0921 2022/10/26 06:52:00 - mmengine - INFO - Epoch(train) [925][40/63] lr: 9.3960e-04 eta: 3:19:52 time: 0.5044 data_time: 0.0064 memory: 16131 loss: 1.0121 loss_prob: 0.5285 loss_thr: 0.3926 loss_db: 0.0910 2022/10/26 06:52:03 - mmengine - INFO - Epoch(train) [925][45/63] lr: 9.3960e-04 eta: 3:19:52 time: 0.5025 data_time: 0.0081 memory: 16131 loss: 1.0375 loss_prob: 0.5501 loss_thr: 0.3944 loss_db: 0.0930 2022/10/26 06:52:06 - mmengine - INFO - Epoch(train) [925][50/63] lr: 9.3960e-04 eta: 3:19:45 time: 0.5567 data_time: 0.0257 memory: 16131 loss: 0.9740 loss_prob: 0.5081 loss_thr: 0.3774 loss_db: 0.0885 2022/10/26 06:52:08 - mmengine - INFO - Epoch(train) [925][55/63] lr: 9.3960e-04 eta: 3:19:45 time: 0.5445 data_time: 0.0226 memory: 16131 loss: 0.9658 loss_prob: 0.5081 loss_thr: 0.3685 loss_db: 0.0891 2022/10/26 06:52:11 - mmengine - INFO - Epoch(train) [925][60/63] lr: 9.3960e-04 eta: 3:19:37 time: 0.5187 data_time: 0.0058 memory: 16131 loss: 0.9793 loss_prob: 0.5178 loss_thr: 0.3717 loss_db: 0.0898 2022/10/26 06:52:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:52:17 - mmengine - INFO - Epoch(train) [926][5/63] lr: 9.3653e-04 eta: 3:19:37 time: 0.6976 data_time: 0.2071 memory: 16131 loss: 0.9412 loss_prob: 0.4956 loss_thr: 0.3563 loss_db: 0.0894 2022/10/26 06:52:20 - mmengine - INFO - Epoch(train) [926][10/63] lr: 9.3653e-04 eta: 3:19:28 time: 0.7552 data_time: 0.2054 memory: 16131 loss: 0.9398 loss_prob: 0.4972 loss_thr: 0.3567 loss_db: 0.0859 2022/10/26 06:52:22 - mmengine - INFO - Epoch(train) [926][15/63] lr: 9.3653e-04 eta: 3:19:28 time: 0.5265 data_time: 0.0077 memory: 16131 loss: 0.9893 loss_prob: 0.5195 loss_thr: 0.3810 loss_db: 0.0888 2022/10/26 06:52:25 - mmengine - INFO - Epoch(train) [926][20/63] lr: 9.3653e-04 eta: 3:19:21 time: 0.4967 data_time: 0.0081 memory: 16131 loss: 0.9989 loss_prob: 0.5303 loss_thr: 0.3770 loss_db: 0.0916 2022/10/26 06:52:27 - mmengine - INFO - Epoch(train) [926][25/63] lr: 9.3653e-04 eta: 3:19:21 time: 0.5198 data_time: 0.0296 memory: 16131 loss: 0.9942 loss_prob: 0.5325 loss_thr: 0.3706 loss_db: 0.0911 2022/10/26 06:52:30 - mmengine - INFO - Epoch(train) [926][30/63] lr: 9.3653e-04 eta: 3:19:13 time: 0.5397 data_time: 0.0342 memory: 16131 loss: 1.0142 loss_prob: 0.5384 loss_thr: 0.3874 loss_db: 0.0884 2022/10/26 06:52:33 - mmengine - INFO - Epoch(train) [926][35/63] lr: 9.3653e-04 eta: 3:19:13 time: 0.5219 data_time: 0.0175 memory: 16131 loss: 0.9298 loss_prob: 0.4846 loss_thr: 0.3648 loss_db: 0.0804 2022/10/26 06:52:35 - mmengine - INFO - Epoch(train) [926][40/63] lr: 9.3653e-04 eta: 3:19:06 time: 0.5219 data_time: 0.0126 memory: 16131 loss: 0.9241 loss_prob: 0.4897 loss_thr: 0.3517 loss_db: 0.0828 2022/10/26 06:52:38 - mmengine - INFO - Epoch(train) [926][45/63] lr: 9.3653e-04 eta: 3:19:06 time: 0.5250 data_time: 0.0060 memory: 16131 loss: 0.9857 loss_prob: 0.5158 loss_thr: 0.3817 loss_db: 0.0882 2022/10/26 06:52:41 - mmengine - INFO - Epoch(train) [926][50/63] lr: 9.3653e-04 eta: 3:18:58 time: 0.5228 data_time: 0.0262 memory: 16131 loss: 1.0094 loss_prob: 0.5200 loss_thr: 0.3960 loss_db: 0.0934 2022/10/26 06:52:43 - mmengine - INFO - Epoch(train) [926][55/63] lr: 9.3653e-04 eta: 3:18:58 time: 0.5050 data_time: 0.0264 memory: 16131 loss: 1.0275 loss_prob: 0.5431 loss_thr: 0.3893 loss_db: 0.0951 2022/10/26 06:52:45 - mmengine - INFO - Epoch(train) [926][60/63] lr: 9.3653e-04 eta: 3:18:51 time: 0.4872 data_time: 0.0089 memory: 16131 loss: 1.0013 loss_prob: 0.5362 loss_thr: 0.3754 loss_db: 0.0897 2022/10/26 06:52:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:52:51 - mmengine - INFO - Epoch(train) [927][5/63] lr: 9.3345e-04 eta: 3:18:51 time: 0.6600 data_time: 0.1863 memory: 16131 loss: 1.0099 loss_prob: 0.5413 loss_thr: 0.3738 loss_db: 0.0948 2022/10/26 06:52:54 - mmengine - INFO - Epoch(train) [927][10/63] lr: 9.3345e-04 eta: 3:18:41 time: 0.7228 data_time: 0.1912 memory: 16131 loss: 1.0133 loss_prob: 0.5398 loss_thr: 0.3786 loss_db: 0.0949 2022/10/26 06:52:57 - mmengine - INFO - Epoch(train) [927][15/63] lr: 9.3345e-04 eta: 3:18:41 time: 0.5511 data_time: 0.0124 memory: 16131 loss: 1.0292 loss_prob: 0.5513 loss_thr: 0.3831 loss_db: 0.0947 2022/10/26 06:52:59 - mmengine - INFO - Epoch(train) [927][20/63] lr: 9.3345e-04 eta: 3:18:34 time: 0.5105 data_time: 0.0050 memory: 16131 loss: 0.9888 loss_prob: 0.5208 loss_thr: 0.3772 loss_db: 0.0908 2022/10/26 06:53:02 - mmengine - INFO - Epoch(train) [927][25/63] lr: 9.3345e-04 eta: 3:18:34 time: 0.5337 data_time: 0.0128 memory: 16131 loss: 1.0739 loss_prob: 0.5631 loss_thr: 0.4116 loss_db: 0.0992 2022/10/26 06:53:05 - mmengine - INFO - Epoch(train) [927][30/63] lr: 9.3345e-04 eta: 3:18:27 time: 0.5417 data_time: 0.0317 memory: 16131 loss: 1.0526 loss_prob: 0.5492 loss_thr: 0.4079 loss_db: 0.0955 2022/10/26 06:53:07 - mmengine - INFO - Epoch(train) [927][35/63] lr: 9.3345e-04 eta: 3:18:27 time: 0.5509 data_time: 0.0309 memory: 16131 loss: 0.9442 loss_prob: 0.4830 loss_thr: 0.3782 loss_db: 0.0830 2022/10/26 06:53:10 - mmengine - INFO - Epoch(train) [927][40/63] lr: 9.3345e-04 eta: 3:18:19 time: 0.5372 data_time: 0.0217 memory: 16131 loss: 1.0038 loss_prob: 0.5310 loss_thr: 0.3830 loss_db: 0.0898 2022/10/26 06:53:12 - mmengine - INFO - Epoch(train) [927][45/63] lr: 9.3345e-04 eta: 3:18:19 time: 0.4995 data_time: 0.0147 memory: 16131 loss: 1.0908 loss_prob: 0.5913 loss_thr: 0.3981 loss_db: 0.1014 2022/10/26 06:53:15 - mmengine - INFO - Epoch(train) [927][50/63] lr: 9.3345e-04 eta: 3:18:12 time: 0.5102 data_time: 0.0089 memory: 16131 loss: 1.0176 loss_prob: 0.5331 loss_thr: 0.3913 loss_db: 0.0932 2022/10/26 06:53:18 - mmengine - INFO - Epoch(train) [927][55/63] lr: 9.3345e-04 eta: 3:18:12 time: 0.5201 data_time: 0.0149 memory: 16131 loss: 0.9983 loss_prob: 0.5264 loss_thr: 0.3826 loss_db: 0.0893 2022/10/26 06:53:20 - mmengine - INFO - Epoch(train) [927][60/63] lr: 9.3345e-04 eta: 3:18:04 time: 0.5090 data_time: 0.0146 memory: 16131 loss: 0.9615 loss_prob: 0.5057 loss_thr: 0.3696 loss_db: 0.0862 2022/10/26 06:53:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:53:26 - mmengine - INFO - Epoch(train) [928][5/63] lr: 9.3037e-04 eta: 3:18:04 time: 0.6894 data_time: 0.2093 memory: 16131 loss: 0.9257 loss_prob: 0.4866 loss_thr: 0.3540 loss_db: 0.0852 2022/10/26 06:53:29 - mmengine - INFO - Epoch(train) [928][10/63] lr: 9.3037e-04 eta: 3:17:55 time: 0.7650 data_time: 0.2106 memory: 16131 loss: 0.9616 loss_prob: 0.5131 loss_thr: 0.3604 loss_db: 0.0881 2022/10/26 06:53:31 - mmengine - INFO - Epoch(train) [928][15/63] lr: 9.3037e-04 eta: 3:17:55 time: 0.5440 data_time: 0.0075 memory: 16131 loss: 0.9970 loss_prob: 0.5351 loss_thr: 0.3692 loss_db: 0.0927 2022/10/26 06:53:34 - mmengine - INFO - Epoch(train) [928][20/63] lr: 9.3037e-04 eta: 3:17:47 time: 0.4963 data_time: 0.0114 memory: 16131 loss: 0.9432 loss_prob: 0.4996 loss_thr: 0.3556 loss_db: 0.0879 2022/10/26 06:53:37 - mmengine - INFO - Epoch(train) [928][25/63] lr: 9.3037e-04 eta: 3:17:47 time: 0.5434 data_time: 0.0351 memory: 16131 loss: 0.9387 loss_prob: 0.4946 loss_thr: 0.3573 loss_db: 0.0868 2022/10/26 06:53:40 - mmengine - INFO - Epoch(train) [928][30/63] lr: 9.3037e-04 eta: 3:17:40 time: 0.5579 data_time: 0.0338 memory: 16131 loss: 0.9676 loss_prob: 0.5106 loss_thr: 0.3696 loss_db: 0.0874 2022/10/26 06:53:42 - mmengine - INFO - Epoch(train) [928][35/63] lr: 9.3037e-04 eta: 3:17:40 time: 0.5200 data_time: 0.0114 memory: 16131 loss: 0.9486 loss_prob: 0.4919 loss_thr: 0.3698 loss_db: 0.0868 2022/10/26 06:53:45 - mmengine - INFO - Epoch(train) [928][40/63] lr: 9.3037e-04 eta: 3:17:33 time: 0.5630 data_time: 0.0092 memory: 16131 loss: 0.8865 loss_prob: 0.4471 loss_thr: 0.3588 loss_db: 0.0806 2022/10/26 06:53:48 - mmengine - INFO - Epoch(train) [928][45/63] lr: 9.3037e-04 eta: 3:17:33 time: 0.5758 data_time: 0.0078 memory: 16131 loss: 0.9386 loss_prob: 0.4837 loss_thr: 0.3711 loss_db: 0.0838 2022/10/26 06:53:50 - mmengine - INFO - Epoch(train) [928][50/63] lr: 9.3037e-04 eta: 3:17:25 time: 0.5298 data_time: 0.0237 memory: 16131 loss: 1.0152 loss_prob: 0.5352 loss_thr: 0.3868 loss_db: 0.0933 2022/10/26 06:53:53 - mmengine - INFO - Epoch(train) [928][55/63] lr: 9.3037e-04 eta: 3:17:25 time: 0.5199 data_time: 0.0245 memory: 16131 loss: 1.0502 loss_prob: 0.5526 loss_thr: 0.4018 loss_db: 0.0958 2022/10/26 06:53:56 - mmengine - INFO - Epoch(train) [928][60/63] lr: 9.3037e-04 eta: 3:17:18 time: 0.5131 data_time: 0.0093 memory: 16131 loss: 0.9895 loss_prob: 0.5188 loss_thr: 0.3823 loss_db: 0.0885 2022/10/26 06:53:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:54:02 - mmengine - INFO - Epoch(train) [929][5/63] lr: 9.2729e-04 eta: 3:17:18 time: 0.7301 data_time: 0.1785 memory: 16131 loss: 0.9956 loss_prob: 0.5296 loss_thr: 0.3759 loss_db: 0.0901 2022/10/26 06:54:04 - mmengine - INFO - Epoch(train) [929][10/63] lr: 9.2729e-04 eta: 3:17:09 time: 0.7339 data_time: 0.1804 memory: 16131 loss: 1.0024 loss_prob: 0.5348 loss_thr: 0.3777 loss_db: 0.0899 2022/10/26 06:54:07 - mmengine - INFO - Epoch(train) [929][15/63] lr: 9.2729e-04 eta: 3:17:09 time: 0.5061 data_time: 0.0079 memory: 16131 loss: 0.9050 loss_prob: 0.4711 loss_thr: 0.3512 loss_db: 0.0826 2022/10/26 06:54:10 - mmengine - INFO - Epoch(train) [929][20/63] lr: 9.2729e-04 eta: 3:17:01 time: 0.5251 data_time: 0.0051 memory: 16131 loss: 0.9423 loss_prob: 0.4907 loss_thr: 0.3647 loss_db: 0.0869 2022/10/26 06:54:12 - mmengine - INFO - Epoch(train) [929][25/63] lr: 9.2729e-04 eta: 3:17:01 time: 0.5385 data_time: 0.0208 memory: 16131 loss: 1.1532 loss_prob: 0.6406 loss_thr: 0.4128 loss_db: 0.0998 2022/10/26 06:54:15 - mmengine - INFO - Epoch(train) [929][30/63] lr: 9.2729e-04 eta: 3:16:54 time: 0.5242 data_time: 0.0337 memory: 16131 loss: 1.0843 loss_prob: 0.5983 loss_thr: 0.3920 loss_db: 0.0940 2022/10/26 06:54:17 - mmengine - INFO - Epoch(train) [929][35/63] lr: 9.2729e-04 eta: 3:16:54 time: 0.5173 data_time: 0.0189 memory: 16131 loss: 0.9366 loss_prob: 0.4844 loss_thr: 0.3672 loss_db: 0.0850 2022/10/26 06:54:20 - mmengine - INFO - Epoch(train) [929][40/63] lr: 9.2729e-04 eta: 3:16:46 time: 0.5121 data_time: 0.0064 memory: 16131 loss: 1.0197 loss_prob: 0.5365 loss_thr: 0.3908 loss_db: 0.0923 2022/10/26 06:54:22 - mmengine - INFO - Epoch(train) [929][45/63] lr: 9.2729e-04 eta: 3:16:46 time: 0.5048 data_time: 0.0058 memory: 16131 loss: 1.0190 loss_prob: 0.5290 loss_thr: 0.3983 loss_db: 0.0918 2022/10/26 06:54:25 - mmengine - INFO - Epoch(train) [929][50/63] lr: 9.2729e-04 eta: 3:16:39 time: 0.5121 data_time: 0.0142 memory: 16131 loss: 0.9874 loss_prob: 0.5158 loss_thr: 0.3815 loss_db: 0.0902 2022/10/26 06:54:28 - mmengine - INFO - Epoch(train) [929][55/63] lr: 9.2729e-04 eta: 3:16:39 time: 0.5121 data_time: 0.0218 memory: 16131 loss: 0.9848 loss_prob: 0.5261 loss_thr: 0.3678 loss_db: 0.0909 2022/10/26 06:54:30 - mmengine - INFO - Epoch(train) [929][60/63] lr: 9.2729e-04 eta: 3:16:32 time: 0.5118 data_time: 0.0149 memory: 16131 loss: 1.0604 loss_prob: 0.5730 loss_thr: 0.3916 loss_db: 0.0957 2022/10/26 06:54:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:54:36 - mmengine - INFO - Epoch(train) [930][5/63] lr: 9.2421e-04 eta: 3:16:32 time: 0.7082 data_time: 0.1632 memory: 16131 loss: 1.0732 loss_prob: 0.5729 loss_thr: 0.4017 loss_db: 0.0986 2022/10/26 06:54:39 - mmengine - INFO - Epoch(train) [930][10/63] lr: 9.2421e-04 eta: 3:16:22 time: 0.7100 data_time: 0.1667 memory: 16131 loss: 0.9724 loss_prob: 0.5030 loss_thr: 0.3802 loss_db: 0.0892 2022/10/26 06:54:41 - mmengine - INFO - Epoch(train) [930][15/63] lr: 9.2421e-04 eta: 3:16:22 time: 0.5048 data_time: 0.0110 memory: 16131 loss: 0.9418 loss_prob: 0.4936 loss_thr: 0.3628 loss_db: 0.0854 2022/10/26 06:54:44 - mmengine - INFO - Epoch(train) [930][20/63] lr: 9.2421e-04 eta: 3:16:15 time: 0.4959 data_time: 0.0076 memory: 16131 loss: 0.9334 loss_prob: 0.4799 loss_thr: 0.3707 loss_db: 0.0828 2022/10/26 06:54:46 - mmengine - INFO - Epoch(train) [930][25/63] lr: 9.2421e-04 eta: 3:16:15 time: 0.5066 data_time: 0.0169 memory: 16131 loss: 0.9173 loss_prob: 0.4669 loss_thr: 0.3686 loss_db: 0.0819 2022/10/26 06:54:49 - mmengine - INFO - Epoch(train) [930][30/63] lr: 9.2421e-04 eta: 3:16:07 time: 0.5159 data_time: 0.0297 memory: 16131 loss: 0.9647 loss_prob: 0.5063 loss_thr: 0.3697 loss_db: 0.0888 2022/10/26 06:54:51 - mmengine - INFO - Epoch(train) [930][35/63] lr: 9.2421e-04 eta: 3:16:07 time: 0.5091 data_time: 0.0201 memory: 16131 loss: 1.0681 loss_prob: 0.5716 loss_thr: 0.3981 loss_db: 0.0983 2022/10/26 06:54:54 - mmengine - INFO - Epoch(train) [930][40/63] lr: 9.2421e-04 eta: 3:16:00 time: 0.5071 data_time: 0.0147 memory: 16131 loss: 1.0172 loss_prob: 0.5379 loss_thr: 0.3865 loss_db: 0.0929 2022/10/26 06:54:56 - mmengine - INFO - Epoch(train) [930][45/63] lr: 9.2421e-04 eta: 3:16:00 time: 0.5068 data_time: 0.0124 memory: 16131 loss: 0.9907 loss_prob: 0.5213 loss_thr: 0.3782 loss_db: 0.0913 2022/10/26 06:54:59 - mmengine - INFO - Epoch(train) [930][50/63] lr: 9.2421e-04 eta: 3:15:52 time: 0.5193 data_time: 0.0145 memory: 16131 loss: 1.0480 loss_prob: 0.5640 loss_thr: 0.3876 loss_db: 0.0964 2022/10/26 06:55:02 - mmengine - INFO - Epoch(train) [930][55/63] lr: 9.2421e-04 eta: 3:15:52 time: 0.5380 data_time: 0.0220 memory: 16131 loss: 1.1021 loss_prob: 0.6107 loss_thr: 0.3917 loss_db: 0.0997 2022/10/26 06:55:04 - mmengine - INFO - Epoch(train) [930][60/63] lr: 9.2421e-04 eta: 3:15:45 time: 0.5196 data_time: 0.0135 memory: 16131 loss: 1.1223 loss_prob: 0.6182 loss_thr: 0.4020 loss_db: 0.1021 2022/10/26 06:55:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:55:11 - mmengine - INFO - Epoch(train) [931][5/63] lr: 9.2113e-04 eta: 3:15:45 time: 0.7541 data_time: 0.2309 memory: 16131 loss: 0.9751 loss_prob: 0.5094 loss_thr: 0.3769 loss_db: 0.0888 2022/10/26 06:55:13 - mmengine - INFO - Epoch(train) [931][10/63] lr: 9.2113e-04 eta: 3:15:36 time: 0.7810 data_time: 0.2326 memory: 16131 loss: 0.9046 loss_prob: 0.4760 loss_thr: 0.3460 loss_db: 0.0826 2022/10/26 06:55:16 - mmengine - INFO - Epoch(train) [931][15/63] lr: 9.2113e-04 eta: 3:15:36 time: 0.5225 data_time: 0.0155 memory: 16131 loss: 0.8968 loss_prob: 0.4688 loss_thr: 0.3481 loss_db: 0.0799 2022/10/26 06:55:19 - mmengine - INFO - Epoch(train) [931][20/63] lr: 9.2113e-04 eta: 3:15:28 time: 0.5418 data_time: 0.0137 memory: 16131 loss: 0.9542 loss_prob: 0.4981 loss_thr: 0.3714 loss_db: 0.0847 2022/10/26 06:55:22 - mmengine - INFO - Epoch(train) [931][25/63] lr: 9.2113e-04 eta: 3:15:28 time: 0.5584 data_time: 0.0359 memory: 16131 loss: 0.9778 loss_prob: 0.5166 loss_thr: 0.3722 loss_db: 0.0890 2022/10/26 06:55:24 - mmengine - INFO - Epoch(train) [931][30/63] lr: 9.2113e-04 eta: 3:15:21 time: 0.5190 data_time: 0.0350 memory: 16131 loss: 0.9687 loss_prob: 0.5113 loss_thr: 0.3684 loss_db: 0.0889 2022/10/26 06:55:27 - mmengine - INFO - Epoch(train) [931][35/63] lr: 9.2113e-04 eta: 3:15:21 time: 0.5100 data_time: 0.0086 memory: 16131 loss: 0.9568 loss_prob: 0.5061 loss_thr: 0.3654 loss_db: 0.0852 2022/10/26 06:55:29 - mmengine - INFO - Epoch(train) [931][40/63] lr: 9.2113e-04 eta: 3:15:13 time: 0.5229 data_time: 0.0080 memory: 16131 loss: 1.0472 loss_prob: 0.5544 loss_thr: 0.3993 loss_db: 0.0936 2022/10/26 06:55:32 - mmengine - INFO - Epoch(train) [931][45/63] lr: 9.2113e-04 eta: 3:15:13 time: 0.5015 data_time: 0.0059 memory: 16131 loss: 1.0154 loss_prob: 0.5277 loss_thr: 0.3946 loss_db: 0.0931 2022/10/26 06:55:35 - mmengine - INFO - Epoch(train) [931][50/63] lr: 9.2113e-04 eta: 3:15:06 time: 0.5176 data_time: 0.0273 memory: 16131 loss: 0.9718 loss_prob: 0.5085 loss_thr: 0.3743 loss_db: 0.0890 2022/10/26 06:55:37 - mmengine - INFO - Epoch(train) [931][55/63] lr: 9.2113e-04 eta: 3:15:06 time: 0.5313 data_time: 0.0275 memory: 16131 loss: 0.9798 loss_prob: 0.5211 loss_thr: 0.3693 loss_db: 0.0894 2022/10/26 06:55:40 - mmengine - INFO - Epoch(train) [931][60/63] lr: 9.2113e-04 eta: 3:14:59 time: 0.5127 data_time: 0.0069 memory: 16131 loss: 0.9631 loss_prob: 0.5151 loss_thr: 0.3593 loss_db: 0.0887 2022/10/26 06:55:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:55:46 - mmengine - INFO - Epoch(train) [932][5/63] lr: 9.1805e-04 eta: 3:14:59 time: 0.6797 data_time: 0.2103 memory: 16131 loss: 0.9884 loss_prob: 0.5230 loss_thr: 0.3751 loss_db: 0.0902 2022/10/26 06:55:48 - mmengine - INFO - Epoch(train) [932][10/63] lr: 9.1805e-04 eta: 3:14:49 time: 0.7342 data_time: 0.2111 memory: 16131 loss: 0.9775 loss_prob: 0.5224 loss_thr: 0.3672 loss_db: 0.0879 2022/10/26 06:55:51 - mmengine - INFO - Epoch(train) [932][15/63] lr: 9.1805e-04 eta: 3:14:49 time: 0.5683 data_time: 0.0064 memory: 16131 loss: 1.0048 loss_prob: 0.5372 loss_thr: 0.3759 loss_db: 0.0918 2022/10/26 06:55:54 - mmengine - INFO - Epoch(train) [932][20/63] lr: 9.1805e-04 eta: 3:14:42 time: 0.5853 data_time: 0.0070 memory: 16131 loss: 1.0004 loss_prob: 0.5256 loss_thr: 0.3829 loss_db: 0.0920 2022/10/26 06:55:57 - mmengine - INFO - Epoch(train) [932][25/63] lr: 9.1805e-04 eta: 3:14:42 time: 0.5786 data_time: 0.0221 memory: 16131 loss: 0.9776 loss_prob: 0.5167 loss_thr: 0.3723 loss_db: 0.0886 2022/10/26 06:56:00 - mmengine - INFO - Epoch(train) [932][30/63] lr: 9.1805e-04 eta: 3:14:35 time: 0.5479 data_time: 0.0343 memory: 16131 loss: 0.9928 loss_prob: 0.5511 loss_thr: 0.3538 loss_db: 0.0879 2022/10/26 06:56:02 - mmengine - INFO - Epoch(train) [932][35/63] lr: 9.1805e-04 eta: 3:14:35 time: 0.5122 data_time: 0.0182 memory: 16131 loss: 1.0204 loss_prob: 0.5654 loss_thr: 0.3612 loss_db: 0.0938 2022/10/26 06:56:05 - mmengine - INFO - Epoch(train) [932][40/63] lr: 9.1805e-04 eta: 3:14:27 time: 0.4976 data_time: 0.0080 memory: 16131 loss: 0.9615 loss_prob: 0.5092 loss_thr: 0.3591 loss_db: 0.0932 2022/10/26 06:56:07 - mmengine - INFO - Epoch(train) [932][45/63] lr: 9.1805e-04 eta: 3:14:27 time: 0.5049 data_time: 0.0100 memory: 16131 loss: 0.9020 loss_prob: 0.4705 loss_thr: 0.3464 loss_db: 0.0851 2022/10/26 06:56:10 - mmengine - INFO - Epoch(train) [932][50/63] lr: 9.1805e-04 eta: 3:14:20 time: 0.5286 data_time: 0.0172 memory: 16131 loss: 0.9179 loss_prob: 0.4716 loss_thr: 0.3634 loss_db: 0.0829 2022/10/26 06:56:13 - mmengine - INFO - Epoch(train) [932][55/63] lr: 9.1805e-04 eta: 3:14:20 time: 0.5433 data_time: 0.0299 memory: 16131 loss: 0.9820 loss_prob: 0.5110 loss_thr: 0.3820 loss_db: 0.0890 2022/10/26 06:56:15 - mmengine - INFO - Epoch(train) [932][60/63] lr: 9.1805e-04 eta: 3:14:13 time: 0.5491 data_time: 0.0197 memory: 16131 loss: 0.9828 loss_prob: 0.5168 loss_thr: 0.3752 loss_db: 0.0908 2022/10/26 06:56:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:56:21 - mmengine - INFO - Epoch(train) [933][5/63] lr: 9.1497e-04 eta: 3:14:13 time: 0.7164 data_time: 0.1709 memory: 16131 loss: 0.9382 loss_prob: 0.4935 loss_thr: 0.3596 loss_db: 0.0851 2022/10/26 06:56:24 - mmengine - INFO - Epoch(train) [933][10/63] lr: 9.1497e-04 eta: 3:14:03 time: 0.7270 data_time: 0.1739 memory: 16131 loss: 1.0159 loss_prob: 0.5528 loss_thr: 0.3695 loss_db: 0.0936 2022/10/26 06:56:26 - mmengine - INFO - Epoch(train) [933][15/63] lr: 9.1497e-04 eta: 3:14:03 time: 0.5199 data_time: 0.0079 memory: 16131 loss: 1.0333 loss_prob: 0.5604 loss_thr: 0.3792 loss_db: 0.0937 2022/10/26 06:56:29 - mmengine - INFO - Epoch(train) [933][20/63] lr: 9.1497e-04 eta: 3:13:56 time: 0.5339 data_time: 0.0076 memory: 16131 loss: 0.9588 loss_prob: 0.5089 loss_thr: 0.3619 loss_db: 0.0879 2022/10/26 06:56:32 - mmengine - INFO - Epoch(train) [933][25/63] lr: 9.1497e-04 eta: 3:13:56 time: 0.5274 data_time: 0.0190 memory: 16131 loss: 0.9239 loss_prob: 0.4850 loss_thr: 0.3547 loss_db: 0.0842 2022/10/26 06:56:35 - mmengine - INFO - Epoch(train) [933][30/63] lr: 9.1497e-04 eta: 3:13:48 time: 0.5424 data_time: 0.0364 memory: 16131 loss: 0.9164 loss_prob: 0.4702 loss_thr: 0.3644 loss_db: 0.0818 2022/10/26 06:56:37 - mmengine - INFO - Epoch(train) [933][35/63] lr: 9.1497e-04 eta: 3:13:48 time: 0.5430 data_time: 0.0250 memory: 16131 loss: 0.9374 loss_prob: 0.4823 loss_thr: 0.3705 loss_db: 0.0846 2022/10/26 06:56:40 - mmengine - INFO - Epoch(train) [933][40/63] lr: 9.1497e-04 eta: 3:13:41 time: 0.5217 data_time: 0.0070 memory: 16131 loss: 0.9076 loss_prob: 0.4720 loss_thr: 0.3520 loss_db: 0.0836 2022/10/26 06:56:42 - mmengine - INFO - Epoch(train) [933][45/63] lr: 9.1497e-04 eta: 3:13:41 time: 0.5256 data_time: 0.0098 memory: 16131 loss: 1.0474 loss_prob: 0.5633 loss_thr: 0.3889 loss_db: 0.0952 2022/10/26 06:56:45 - mmengine - INFO - Epoch(train) [933][50/63] lr: 9.1497e-04 eta: 3:13:34 time: 0.5572 data_time: 0.0210 memory: 16131 loss: 1.0857 loss_prob: 0.5845 loss_thr: 0.4019 loss_db: 0.0993 2022/10/26 06:56:48 - mmengine - INFO - Epoch(train) [933][55/63] lr: 9.1497e-04 eta: 3:13:34 time: 0.5635 data_time: 0.0218 memory: 16131 loss: 0.9470 loss_prob: 0.4941 loss_thr: 0.3660 loss_db: 0.0870 2022/10/26 06:56:51 - mmengine - INFO - Epoch(train) [933][60/63] lr: 9.1497e-04 eta: 3:13:26 time: 0.5393 data_time: 0.0086 memory: 16131 loss: 1.0028 loss_prob: 0.5216 loss_thr: 0.3914 loss_db: 0.0898 2022/10/26 06:56:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:56:56 - mmengine - INFO - Epoch(train) [934][5/63] lr: 9.1188e-04 eta: 3:13:26 time: 0.6649 data_time: 0.1853 memory: 16131 loss: 1.0113 loss_prob: 0.5314 loss_thr: 0.3883 loss_db: 0.0916 2022/10/26 06:56:59 - mmengine - INFO - Epoch(train) [934][10/63] lr: 9.1188e-04 eta: 3:13:17 time: 0.6956 data_time: 0.1913 memory: 16131 loss: 0.9585 loss_prob: 0.5002 loss_thr: 0.3711 loss_db: 0.0873 2022/10/26 06:57:01 - mmengine - INFO - Epoch(train) [934][15/63] lr: 9.1188e-04 eta: 3:13:17 time: 0.5109 data_time: 0.0131 memory: 16131 loss: 0.9723 loss_prob: 0.5154 loss_thr: 0.3680 loss_db: 0.0890 2022/10/26 06:57:04 - mmengine - INFO - Epoch(train) [934][20/63] lr: 9.1188e-04 eta: 3:13:09 time: 0.5080 data_time: 0.0097 memory: 16131 loss: 1.0718 loss_prob: 0.5832 loss_thr: 0.3916 loss_db: 0.0970 2022/10/26 06:57:07 - mmengine - INFO - Epoch(train) [934][25/63] lr: 9.1188e-04 eta: 3:13:09 time: 0.5363 data_time: 0.0287 memory: 16131 loss: 1.0329 loss_prob: 0.5496 loss_thr: 0.3898 loss_db: 0.0935 2022/10/26 06:57:10 - mmengine - INFO - Epoch(train) [934][30/63] lr: 9.1188e-04 eta: 3:13:02 time: 0.5922 data_time: 0.0398 memory: 16131 loss: 0.9535 loss_prob: 0.5046 loss_thr: 0.3602 loss_db: 0.0888 2022/10/26 06:57:12 - mmengine - INFO - Epoch(train) [934][35/63] lr: 9.1188e-04 eta: 3:13:02 time: 0.5606 data_time: 0.0207 memory: 16131 loss: 0.9935 loss_prob: 0.5280 loss_thr: 0.3750 loss_db: 0.0905 2022/10/26 06:57:15 - mmengine - INFO - Epoch(train) [934][40/63] lr: 9.1188e-04 eta: 3:12:55 time: 0.4885 data_time: 0.0075 memory: 16131 loss: 1.0205 loss_prob: 0.5400 loss_thr: 0.3868 loss_db: 0.0937 2022/10/26 06:57:18 - mmengine - INFO - Epoch(train) [934][45/63] lr: 9.1188e-04 eta: 3:12:55 time: 0.5359 data_time: 0.0055 memory: 16131 loss: 1.0343 loss_prob: 0.5511 loss_thr: 0.3877 loss_db: 0.0955 2022/10/26 06:57:20 - mmengine - INFO - Epoch(train) [934][50/63] lr: 9.1188e-04 eta: 3:12:47 time: 0.5454 data_time: 0.0155 memory: 16131 loss: 1.0300 loss_prob: 0.5507 loss_thr: 0.3870 loss_db: 0.0923 2022/10/26 06:57:23 - mmengine - INFO - Epoch(train) [934][55/63] lr: 9.1188e-04 eta: 3:12:47 time: 0.4912 data_time: 0.0218 memory: 16131 loss: 1.0119 loss_prob: 0.5435 loss_thr: 0.3765 loss_db: 0.0919 2022/10/26 06:57:25 - mmengine - INFO - Epoch(train) [934][60/63] lr: 9.1188e-04 eta: 3:12:40 time: 0.5183 data_time: 0.0122 memory: 16131 loss: 1.0046 loss_prob: 0.5357 loss_thr: 0.3760 loss_db: 0.0928 2022/10/26 06:57:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:57:31 - mmengine - INFO - Epoch(train) [935][5/63] lr: 9.0880e-04 eta: 3:12:40 time: 0.6883 data_time: 0.1897 memory: 16131 loss: 0.9125 loss_prob: 0.4782 loss_thr: 0.3524 loss_db: 0.0819 2022/10/26 06:57:34 - mmengine - INFO - Epoch(train) [935][10/63] lr: 9.0880e-04 eta: 3:12:31 time: 0.6804 data_time: 0.1882 memory: 16131 loss: 0.9255 loss_prob: 0.4857 loss_thr: 0.3566 loss_db: 0.0833 2022/10/26 06:57:36 - mmengine - INFO - Epoch(train) [935][15/63] lr: 9.0880e-04 eta: 3:12:31 time: 0.5061 data_time: 0.0142 memory: 16131 loss: 1.0598 loss_prob: 0.5474 loss_thr: 0.4152 loss_db: 0.0972 2022/10/26 06:57:39 - mmengine - INFO - Epoch(train) [935][20/63] lr: 9.0880e-04 eta: 3:12:23 time: 0.5301 data_time: 0.0072 memory: 16131 loss: 1.0531 loss_prob: 0.5416 loss_thr: 0.4169 loss_db: 0.0945 2022/10/26 06:57:42 - mmengine - INFO - Epoch(train) [935][25/63] lr: 9.0880e-04 eta: 3:12:23 time: 0.5644 data_time: 0.0270 memory: 16131 loss: 0.9715 loss_prob: 0.5185 loss_thr: 0.3650 loss_db: 0.0880 2022/10/26 06:57:45 - mmengine - INFO - Epoch(train) [935][30/63] lr: 9.0880e-04 eta: 3:12:16 time: 0.5589 data_time: 0.0304 memory: 16131 loss: 0.9339 loss_prob: 0.4954 loss_thr: 0.3526 loss_db: 0.0859 2022/10/26 06:57:47 - mmengine - INFO - Epoch(train) [935][35/63] lr: 9.0880e-04 eta: 3:12:16 time: 0.5411 data_time: 0.0111 memory: 16131 loss: 0.9401 loss_prob: 0.4905 loss_thr: 0.3635 loss_db: 0.0861 2022/10/26 06:57:50 - mmengine - INFO - Epoch(train) [935][40/63] lr: 9.0880e-04 eta: 3:12:09 time: 0.5212 data_time: 0.0090 memory: 16131 loss: 0.9908 loss_prob: 0.5230 loss_thr: 0.3792 loss_db: 0.0886 2022/10/26 06:57:52 - mmengine - INFO - Epoch(train) [935][45/63] lr: 9.0880e-04 eta: 3:12:09 time: 0.4894 data_time: 0.0098 memory: 16131 loss: 1.0427 loss_prob: 0.5610 loss_thr: 0.3874 loss_db: 0.0942 2022/10/26 06:57:55 - mmengine - INFO - Epoch(train) [935][50/63] lr: 9.0880e-04 eta: 3:12:01 time: 0.5287 data_time: 0.0230 memory: 16131 loss: 1.0695 loss_prob: 0.5861 loss_thr: 0.3854 loss_db: 0.0981 2022/10/26 06:57:57 - mmengine - INFO - Epoch(train) [935][55/63] lr: 9.0880e-04 eta: 3:12:01 time: 0.5199 data_time: 0.0189 memory: 16131 loss: 1.0435 loss_prob: 0.5626 loss_thr: 0.3849 loss_db: 0.0959 2022/10/26 06:58:00 - mmengine - INFO - Epoch(train) [935][60/63] lr: 9.0880e-04 eta: 3:11:54 time: 0.4952 data_time: 0.0118 memory: 16131 loss: 1.0208 loss_prob: 0.5385 loss_thr: 0.3877 loss_db: 0.0945 2022/10/26 06:58:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:58:06 - mmengine - INFO - Epoch(train) [936][5/63] lr: 9.0571e-04 eta: 3:11:54 time: 0.7458 data_time: 0.2312 memory: 16131 loss: 1.0688 loss_prob: 0.5790 loss_thr: 0.3922 loss_db: 0.0976 2022/10/26 06:58:09 - mmengine - INFO - Epoch(train) [936][10/63] lr: 9.0571e-04 eta: 3:11:44 time: 0.7900 data_time: 0.2330 memory: 16131 loss: 0.9707 loss_prob: 0.5107 loss_thr: 0.3687 loss_db: 0.0913 2022/10/26 06:58:12 - mmengine - INFO - Epoch(train) [936][15/63] lr: 9.0571e-04 eta: 3:11:44 time: 0.5290 data_time: 0.0092 memory: 16131 loss: 0.9748 loss_prob: 0.5089 loss_thr: 0.3744 loss_db: 0.0916 2022/10/26 06:58:14 - mmengine - INFO - Epoch(train) [936][20/63] lr: 9.0571e-04 eta: 3:11:37 time: 0.4922 data_time: 0.0070 memory: 16131 loss: 0.9203 loss_prob: 0.4844 loss_thr: 0.3523 loss_db: 0.0835 2022/10/26 06:58:17 - mmengine - INFO - Epoch(train) [936][25/63] lr: 9.0571e-04 eta: 3:11:37 time: 0.5183 data_time: 0.0230 memory: 16131 loss: 0.9866 loss_prob: 0.5304 loss_thr: 0.3663 loss_db: 0.0898 2022/10/26 06:58:19 - mmengine - INFO - Epoch(train) [936][30/63] lr: 9.0571e-04 eta: 3:11:30 time: 0.5190 data_time: 0.0374 memory: 16131 loss: 1.0528 loss_prob: 0.5678 loss_thr: 0.3876 loss_db: 0.0975 2022/10/26 06:58:22 - mmengine - INFO - Epoch(train) [936][35/63] lr: 9.0571e-04 eta: 3:11:30 time: 0.5103 data_time: 0.0215 memory: 16131 loss: 1.0827 loss_prob: 0.5861 loss_thr: 0.3961 loss_db: 0.1005 2022/10/26 06:58:24 - mmengine - INFO - Epoch(train) [936][40/63] lr: 9.0571e-04 eta: 3:11:22 time: 0.4993 data_time: 0.0057 memory: 16131 loss: 1.1193 loss_prob: 0.5968 loss_thr: 0.4220 loss_db: 0.1005 2022/10/26 06:58:27 - mmengine - INFO - Epoch(train) [936][45/63] lr: 9.0571e-04 eta: 3:11:22 time: 0.5140 data_time: 0.0049 memory: 16131 loss: 1.1250 loss_prob: 0.5913 loss_thr: 0.4325 loss_db: 0.1012 2022/10/26 06:58:30 - mmengine - INFO - Epoch(train) [936][50/63] lr: 9.0571e-04 eta: 3:11:15 time: 0.5252 data_time: 0.0235 memory: 16131 loss: 1.0545 loss_prob: 0.5597 loss_thr: 0.3975 loss_db: 0.0973 2022/10/26 06:58:32 - mmengine - INFO - Epoch(train) [936][55/63] lr: 9.0571e-04 eta: 3:11:15 time: 0.5208 data_time: 0.0238 memory: 16131 loss: 0.9541 loss_prob: 0.4955 loss_thr: 0.3722 loss_db: 0.0864 2022/10/26 06:58:35 - mmengine - INFO - Epoch(train) [936][60/63] lr: 9.0571e-04 eta: 3:11:07 time: 0.5145 data_time: 0.0068 memory: 16131 loss: 1.0226 loss_prob: 0.5382 loss_thr: 0.3938 loss_db: 0.0907 2022/10/26 06:58:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:58:41 - mmengine - INFO - Epoch(train) [937][5/63] lr: 9.0262e-04 eta: 3:11:07 time: 0.7462 data_time: 0.2196 memory: 16131 loss: 0.9788 loss_prob: 0.5078 loss_thr: 0.3817 loss_db: 0.0893 2022/10/26 06:58:44 - mmengine - INFO - Epoch(train) [937][10/63] lr: 9.0262e-04 eta: 3:10:58 time: 0.7700 data_time: 0.2186 memory: 16131 loss: 0.9678 loss_prob: 0.5061 loss_thr: 0.3730 loss_db: 0.0887 2022/10/26 06:58:47 - mmengine - INFO - Epoch(train) [937][15/63] lr: 9.0262e-04 eta: 3:10:58 time: 0.5317 data_time: 0.0075 memory: 16131 loss: 1.0496 loss_prob: 0.5663 loss_thr: 0.3884 loss_db: 0.0948 2022/10/26 06:58:49 - mmengine - INFO - Epoch(train) [937][20/63] lr: 9.0262e-04 eta: 3:10:51 time: 0.5578 data_time: 0.0073 memory: 16131 loss: 1.0327 loss_prob: 0.5495 loss_thr: 0.3898 loss_db: 0.0934 2022/10/26 06:58:52 - mmengine - INFO - Epoch(train) [937][25/63] lr: 9.0262e-04 eta: 3:10:51 time: 0.5440 data_time: 0.0214 memory: 16131 loss: 0.9212 loss_prob: 0.4759 loss_thr: 0.3600 loss_db: 0.0852 2022/10/26 06:58:55 - mmengine - INFO - Epoch(train) [937][30/63] lr: 9.0262e-04 eta: 3:10:44 time: 0.5533 data_time: 0.0427 memory: 16131 loss: 0.9686 loss_prob: 0.5143 loss_thr: 0.3641 loss_db: 0.0901 2022/10/26 06:58:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:58:57 - mmengine - INFO - Epoch(train) [937][35/63] lr: 9.0262e-04 eta: 3:10:44 time: 0.5359 data_time: 0.0285 memory: 16131 loss: 0.9890 loss_prob: 0.5274 loss_thr: 0.3702 loss_db: 0.0913 2022/10/26 06:59:00 - mmengine - INFO - Epoch(train) [937][40/63] lr: 9.0262e-04 eta: 3:10:36 time: 0.5104 data_time: 0.0071 memory: 16131 loss: 0.9360 loss_prob: 0.4898 loss_thr: 0.3596 loss_db: 0.0865 2022/10/26 06:59:03 - mmengine - INFO - Epoch(train) [937][45/63] lr: 9.0262e-04 eta: 3:10:36 time: 0.5314 data_time: 0.0057 memory: 16131 loss: 0.9324 loss_prob: 0.4879 loss_thr: 0.3586 loss_db: 0.0858 2022/10/26 06:59:05 - mmengine - INFO - Epoch(train) [937][50/63] lr: 9.0262e-04 eta: 3:10:29 time: 0.5173 data_time: 0.0171 memory: 16131 loss: 0.9366 loss_prob: 0.4872 loss_thr: 0.3647 loss_db: 0.0847 2022/10/26 06:59:08 - mmengine - INFO - Epoch(train) [937][55/63] lr: 9.0262e-04 eta: 3:10:29 time: 0.5054 data_time: 0.0204 memory: 16131 loss: 0.9759 loss_prob: 0.5060 loss_thr: 0.3812 loss_db: 0.0887 2022/10/26 06:59:10 - mmengine - INFO - Epoch(train) [937][60/63] lr: 9.0262e-04 eta: 3:10:21 time: 0.5168 data_time: 0.0107 memory: 16131 loss: 1.0131 loss_prob: 0.5294 loss_thr: 0.3903 loss_db: 0.0934 2022/10/26 06:59:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:59:16 - mmengine - INFO - Epoch(train) [938][5/63] lr: 8.9953e-04 eta: 3:10:21 time: 0.6874 data_time: 0.1999 memory: 16131 loss: 1.0236 loss_prob: 0.5308 loss_thr: 0.4016 loss_db: 0.0913 2022/10/26 06:59:19 - mmengine - INFO - Epoch(train) [938][10/63] lr: 8.9953e-04 eta: 3:10:12 time: 0.7441 data_time: 0.1983 memory: 16131 loss: 1.0344 loss_prob: 0.5354 loss_thr: 0.4082 loss_db: 0.0909 2022/10/26 06:59:22 - mmengine - INFO - Epoch(train) [938][15/63] lr: 8.9953e-04 eta: 3:10:12 time: 0.5726 data_time: 0.0077 memory: 16131 loss: 0.9447 loss_prob: 0.4879 loss_thr: 0.3752 loss_db: 0.0816 2022/10/26 06:59:24 - mmengine - INFO - Epoch(train) [938][20/63] lr: 8.9953e-04 eta: 3:10:05 time: 0.5264 data_time: 0.0070 memory: 16131 loss: 0.9905 loss_prob: 0.5211 loss_thr: 0.3814 loss_db: 0.0879 2022/10/26 06:59:27 - mmengine - INFO - Epoch(train) [938][25/63] lr: 8.9953e-04 eta: 3:10:05 time: 0.5092 data_time: 0.0073 memory: 16131 loss: 1.0429 loss_prob: 0.5482 loss_thr: 0.3981 loss_db: 0.0966 2022/10/26 06:59:30 - mmengine - INFO - Epoch(train) [938][30/63] lr: 8.9953e-04 eta: 3:09:57 time: 0.5336 data_time: 0.0289 memory: 16131 loss: 0.9216 loss_prob: 0.4750 loss_thr: 0.3622 loss_db: 0.0844 2022/10/26 06:59:33 - mmengine - INFO - Epoch(train) [938][35/63] lr: 8.9953e-04 eta: 3:09:57 time: 0.5391 data_time: 0.0319 memory: 16131 loss: 0.8406 loss_prob: 0.4358 loss_thr: 0.3297 loss_db: 0.0752 2022/10/26 06:59:35 - mmengine - INFO - Epoch(train) [938][40/63] lr: 8.9953e-04 eta: 3:09:50 time: 0.5288 data_time: 0.0100 memory: 16131 loss: 0.9421 loss_prob: 0.4935 loss_thr: 0.3633 loss_db: 0.0853 2022/10/26 06:59:38 - mmengine - INFO - Epoch(train) [938][45/63] lr: 8.9953e-04 eta: 3:09:50 time: 0.5135 data_time: 0.0085 memory: 16131 loss: 1.0971 loss_prob: 0.5825 loss_thr: 0.4152 loss_db: 0.0994 2022/10/26 06:59:40 - mmengine - INFO - Epoch(train) [938][50/63] lr: 8.9953e-04 eta: 3:09:43 time: 0.5260 data_time: 0.0225 memory: 16131 loss: 1.0461 loss_prob: 0.5610 loss_thr: 0.3921 loss_db: 0.0930 2022/10/26 06:59:43 - mmengine - INFO - Epoch(train) [938][55/63] lr: 8.9953e-04 eta: 3:09:43 time: 0.5061 data_time: 0.0197 memory: 16131 loss: 1.0249 loss_prob: 0.5445 loss_thr: 0.3883 loss_db: 0.0921 2022/10/26 06:59:45 - mmengine - INFO - Epoch(train) [938][60/63] lr: 8.9953e-04 eta: 3:09:35 time: 0.4962 data_time: 0.0110 memory: 16131 loss: 1.0320 loss_prob: 0.5539 loss_thr: 0.3831 loss_db: 0.0950 2022/10/26 06:59:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 06:59:51 - mmengine - INFO - Epoch(train) [939][5/63] lr: 8.9644e-04 eta: 3:09:35 time: 0.7022 data_time: 0.1960 memory: 16131 loss: 0.9548 loss_prob: 0.5097 loss_thr: 0.3585 loss_db: 0.0866 2022/10/26 06:59:55 - mmengine - INFO - Epoch(train) [939][10/63] lr: 8.9644e-04 eta: 3:09:26 time: 0.8012 data_time: 0.1948 memory: 16131 loss: 0.9542 loss_prob: 0.5040 loss_thr: 0.3636 loss_db: 0.0866 2022/10/26 06:59:58 - mmengine - INFO - Epoch(train) [939][15/63] lr: 8.9644e-04 eta: 3:09:26 time: 0.6307 data_time: 0.0076 memory: 16131 loss: 0.9535 loss_prob: 0.5074 loss_thr: 0.3606 loss_db: 0.0856 2022/10/26 07:00:00 - mmengine - INFO - Epoch(train) [939][20/63] lr: 8.9644e-04 eta: 3:09:19 time: 0.5662 data_time: 0.0089 memory: 16131 loss: 0.9456 loss_prob: 0.4977 loss_thr: 0.3644 loss_db: 0.0835 2022/10/26 07:00:03 - mmengine - INFO - Epoch(train) [939][25/63] lr: 8.9644e-04 eta: 3:09:19 time: 0.5280 data_time: 0.0209 memory: 16131 loss: 0.9433 loss_prob: 0.4894 loss_thr: 0.3692 loss_db: 0.0847 2022/10/26 07:00:05 - mmengine - INFO - Epoch(train) [939][30/63] lr: 8.9644e-04 eta: 3:09:11 time: 0.5174 data_time: 0.0276 memory: 16131 loss: 0.9513 loss_prob: 0.4994 loss_thr: 0.3636 loss_db: 0.0883 2022/10/26 07:00:08 - mmengine - INFO - Epoch(train) [939][35/63] lr: 8.9644e-04 eta: 3:09:11 time: 0.5238 data_time: 0.0179 memory: 16131 loss: 1.0024 loss_prob: 0.5383 loss_thr: 0.3698 loss_db: 0.0943 2022/10/26 07:00:11 - mmengine - INFO - Epoch(train) [939][40/63] lr: 8.9644e-04 eta: 3:09:04 time: 0.5267 data_time: 0.0089 memory: 16131 loss: 1.0571 loss_prob: 0.5677 loss_thr: 0.3934 loss_db: 0.0960 2022/10/26 07:00:13 - mmengine - INFO - Epoch(train) [939][45/63] lr: 8.9644e-04 eta: 3:09:04 time: 0.5215 data_time: 0.0091 memory: 16131 loss: 1.0194 loss_prob: 0.5370 loss_thr: 0.3922 loss_db: 0.0903 2022/10/26 07:00:16 - mmengine - INFO - Epoch(train) [939][50/63] lr: 8.9644e-04 eta: 3:08:57 time: 0.5184 data_time: 0.0158 memory: 16131 loss: 0.9749 loss_prob: 0.5106 loss_thr: 0.3756 loss_db: 0.0887 2022/10/26 07:00:18 - mmengine - INFO - Epoch(train) [939][55/63] lr: 8.9644e-04 eta: 3:08:57 time: 0.5021 data_time: 0.0200 memory: 16131 loss: 1.0040 loss_prob: 0.5257 loss_thr: 0.3847 loss_db: 0.0937 2022/10/26 07:00:21 - mmengine - INFO - Epoch(train) [939][60/63] lr: 8.9644e-04 eta: 3:08:49 time: 0.5156 data_time: 0.0146 memory: 16131 loss: 1.0127 loss_prob: 0.5277 loss_thr: 0.3923 loss_db: 0.0926 2022/10/26 07:00:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:00:27 - mmengine - INFO - Epoch(train) [940][5/63] lr: 8.9335e-04 eta: 3:08:49 time: 0.6969 data_time: 0.2057 memory: 16131 loss: 0.9728 loss_prob: 0.5015 loss_thr: 0.3834 loss_db: 0.0879 2022/10/26 07:00:29 - mmengine - INFO - Epoch(train) [940][10/63] lr: 8.9335e-04 eta: 3:08:40 time: 0.7153 data_time: 0.2088 memory: 16131 loss: 0.9253 loss_prob: 0.4874 loss_thr: 0.3544 loss_db: 0.0835 2022/10/26 07:00:33 - mmengine - INFO - Epoch(train) [940][15/63] lr: 8.9335e-04 eta: 3:08:40 time: 0.6429 data_time: 0.0090 memory: 16131 loss: 0.8890 loss_prob: 0.4673 loss_thr: 0.3404 loss_db: 0.0813 2022/10/26 07:00:36 - mmengine - INFO - Epoch(train) [940][20/63] lr: 8.9335e-04 eta: 3:08:33 time: 0.6453 data_time: 0.0052 memory: 16131 loss: 0.8244 loss_prob: 0.4244 loss_thr: 0.3252 loss_db: 0.0747 2022/10/26 07:00:39 - mmengine - INFO - Epoch(train) [940][25/63] lr: 8.9335e-04 eta: 3:08:33 time: 0.5402 data_time: 0.0319 memory: 16131 loss: 0.8383 loss_prob: 0.4281 loss_thr: 0.3357 loss_db: 0.0745 2022/10/26 07:00:41 - mmengine - INFO - Epoch(train) [940][30/63] lr: 8.9335e-04 eta: 3:08:26 time: 0.5319 data_time: 0.0408 memory: 16131 loss: 0.8899 loss_prob: 0.4557 loss_thr: 0.3542 loss_db: 0.0800 2022/10/26 07:00:44 - mmengine - INFO - Epoch(train) [940][35/63] lr: 8.9335e-04 eta: 3:08:26 time: 0.5426 data_time: 0.0148 memory: 16131 loss: 0.9698 loss_prob: 0.5026 loss_thr: 0.3770 loss_db: 0.0903 2022/10/26 07:00:46 - mmengine - INFO - Epoch(train) [940][40/63] lr: 8.9335e-04 eta: 3:08:18 time: 0.5238 data_time: 0.0063 memory: 16131 loss: 1.0640 loss_prob: 0.5614 loss_thr: 0.4030 loss_db: 0.0996 2022/10/26 07:00:49 - mmengine - INFO - Epoch(train) [940][45/63] lr: 8.9335e-04 eta: 3:08:18 time: 0.4815 data_time: 0.0062 memory: 16131 loss: 0.9909 loss_prob: 0.5228 loss_thr: 0.3777 loss_db: 0.0904 2022/10/26 07:00:51 - mmengine - INFO - Epoch(train) [940][50/63] lr: 8.9335e-04 eta: 3:08:11 time: 0.4979 data_time: 0.0127 memory: 16131 loss: 0.8625 loss_prob: 0.4468 loss_thr: 0.3379 loss_db: 0.0778 2022/10/26 07:00:54 - mmengine - INFO - Epoch(train) [940][55/63] lr: 8.9335e-04 eta: 3:08:11 time: 0.5215 data_time: 0.0146 memory: 16131 loss: 0.9339 loss_prob: 0.4894 loss_thr: 0.3602 loss_db: 0.0843 2022/10/26 07:00:57 - mmengine - INFO - Epoch(train) [940][60/63] lr: 8.9335e-04 eta: 3:08:03 time: 0.5346 data_time: 0.0071 memory: 16131 loss: 1.0663 loss_prob: 0.5747 loss_thr: 0.3955 loss_db: 0.0961 2022/10/26 07:00:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:00:58 - mmengine - INFO - Saving checkpoint at 940 epochs 2022/10/26 07:01:05 - mmengine - INFO - Epoch(val) [940][5/32] eta: 3:08:03 time: 0.5294 data_time: 0.0839 memory: 16131 2022/10/26 07:01:08 - mmengine - INFO - Epoch(val) [940][10/32] eta: 0:00:13 time: 0.6137 data_time: 0.1214 memory: 15724 2022/10/26 07:01:11 - mmengine - INFO - Epoch(val) [940][15/32] eta: 0:00:13 time: 0.5577 data_time: 0.0536 memory: 15724 2022/10/26 07:01:13 - mmengine - INFO - Epoch(val) [940][20/32] eta: 0:00:06 time: 0.5458 data_time: 0.0501 memory: 15724 2022/10/26 07:01:16 - mmengine - INFO - Epoch(val) [940][25/32] eta: 0:00:06 time: 0.5498 data_time: 0.0523 memory: 15724 2022/10/26 07:01:18 - mmengine - INFO - Epoch(val) [940][30/32] eta: 0:00:01 time: 0.5042 data_time: 0.0199 memory: 15724 2022/10/26 07:01:19 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8353, precision: 0.7819, hmean: 0.8077 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8353, precision: 0.8250, hmean: 0.8301 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8344, precision: 0.8541, hmean: 0.8441 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8305, precision: 0.8815, hmean: 0.8552 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8209, precision: 0.9079, hmean: 0.8622 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7386, precision: 0.9463, hmean: 0.8296 2022/10/26 07:01:19 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1425, precision: 0.9834, hmean: 0.2489 2022/10/26 07:01:19 - mmengine - INFO - Epoch(val) [940][32/32] icdar/precision: 0.9079 icdar/recall: 0.8209 icdar/hmean: 0.8622 2022/10/26 07:01:24 - mmengine - INFO - Epoch(train) [941][5/63] lr: 8.9026e-04 eta: 0:00:01 time: 0.6871 data_time: 0.1922 memory: 16131 loss: 0.9841 loss_prob: 0.5137 loss_thr: 0.3786 loss_db: 0.0917 2022/10/26 07:01:26 - mmengine - INFO - Epoch(train) [941][10/63] lr: 8.9026e-04 eta: 3:07:54 time: 0.7266 data_time: 0.1926 memory: 16131 loss: 0.9728 loss_prob: 0.5091 loss_thr: 0.3743 loss_db: 0.0894 2022/10/26 07:01:29 - mmengine - INFO - Epoch(train) [941][15/63] lr: 8.9026e-04 eta: 3:07:54 time: 0.5275 data_time: 0.0060 memory: 16131 loss: 0.9961 loss_prob: 0.5325 loss_thr: 0.3698 loss_db: 0.0937 2022/10/26 07:01:32 - mmengine - INFO - Epoch(train) [941][20/63] lr: 8.9026e-04 eta: 3:07:47 time: 0.5135 data_time: 0.0061 memory: 16131 loss: 0.9859 loss_prob: 0.5277 loss_thr: 0.3655 loss_db: 0.0926 2022/10/26 07:01:34 - mmengine - INFO - Epoch(train) [941][25/63] lr: 8.9026e-04 eta: 3:07:47 time: 0.5404 data_time: 0.0306 memory: 16131 loss: 0.9910 loss_prob: 0.5257 loss_thr: 0.3755 loss_db: 0.0899 2022/10/26 07:01:37 - mmengine - INFO - Epoch(train) [941][30/63] lr: 8.9026e-04 eta: 3:07:39 time: 0.5428 data_time: 0.0315 memory: 16131 loss: 0.9979 loss_prob: 0.5272 loss_thr: 0.3809 loss_db: 0.0898 2022/10/26 07:01:39 - mmengine - INFO - Epoch(train) [941][35/63] lr: 8.9026e-04 eta: 3:07:39 time: 0.4930 data_time: 0.0057 memory: 16131 loss: 1.0198 loss_prob: 0.5370 loss_thr: 0.3881 loss_db: 0.0947 2022/10/26 07:01:42 - mmengine - INFO - Epoch(train) [941][40/63] lr: 8.9026e-04 eta: 3:07:32 time: 0.5077 data_time: 0.0135 memory: 16131 loss: 1.0087 loss_prob: 0.5258 loss_thr: 0.3893 loss_db: 0.0935 2022/10/26 07:01:45 - mmengine - INFO - Epoch(train) [941][45/63] lr: 8.9026e-04 eta: 3:07:32 time: 0.5623 data_time: 0.0139 memory: 16131 loss: 0.9936 loss_prob: 0.5228 loss_thr: 0.3814 loss_db: 0.0894 2022/10/26 07:01:48 - mmengine - INFO - Epoch(train) [941][50/63] lr: 8.9026e-04 eta: 3:07:25 time: 0.5958 data_time: 0.0251 memory: 16131 loss: 0.9071 loss_prob: 0.4718 loss_thr: 0.3531 loss_db: 0.0822 2022/10/26 07:01:51 - mmengine - INFO - Epoch(train) [941][55/63] lr: 8.9026e-04 eta: 3:07:25 time: 0.5513 data_time: 0.0251 memory: 16131 loss: 0.8987 loss_prob: 0.4651 loss_thr: 0.3511 loss_db: 0.0825 2022/10/26 07:01:53 - mmengine - INFO - Epoch(train) [941][60/63] lr: 8.9026e-04 eta: 3:07:17 time: 0.5001 data_time: 0.0059 memory: 16131 loss: 0.9588 loss_prob: 0.5001 loss_thr: 0.3740 loss_db: 0.0847 2022/10/26 07:01:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:01:59 - mmengine - INFO - Epoch(train) [942][5/63] lr: 8.8717e-04 eta: 3:07:17 time: 0.7232 data_time: 0.2080 memory: 16131 loss: 0.9249 loss_prob: 0.4781 loss_thr: 0.3617 loss_db: 0.0851 2022/10/26 07:02:02 - mmengine - INFO - Epoch(train) [942][10/63] lr: 8.8717e-04 eta: 3:07:08 time: 0.7378 data_time: 0.2067 memory: 16131 loss: 0.8644 loss_prob: 0.4432 loss_thr: 0.3410 loss_db: 0.0802 2022/10/26 07:02:05 - mmengine - INFO - Epoch(train) [942][15/63] lr: 8.8717e-04 eta: 3:07:08 time: 0.5366 data_time: 0.0048 memory: 16131 loss: 1.0467 loss_prob: 0.5691 loss_thr: 0.3802 loss_db: 0.0974 2022/10/26 07:02:07 - mmengine - INFO - Epoch(train) [942][20/63] lr: 8.8717e-04 eta: 3:07:01 time: 0.5525 data_time: 0.0058 memory: 16131 loss: 1.0519 loss_prob: 0.5741 loss_thr: 0.3797 loss_db: 0.0980 2022/10/26 07:02:10 - mmengine - INFO - Epoch(train) [942][25/63] lr: 8.8717e-04 eta: 3:07:01 time: 0.5438 data_time: 0.0366 memory: 16131 loss: 1.0213 loss_prob: 0.5342 loss_thr: 0.3965 loss_db: 0.0905 2022/10/26 07:02:13 - mmengine - INFO - Epoch(train) [942][30/63] lr: 8.8717e-04 eta: 3:06:54 time: 0.5411 data_time: 0.0357 memory: 16131 loss: 1.0465 loss_prob: 0.5380 loss_thr: 0.4147 loss_db: 0.0938 2022/10/26 07:02:15 - mmengine - INFO - Epoch(train) [942][35/63] lr: 8.8717e-04 eta: 3:06:54 time: 0.5087 data_time: 0.0051 memory: 16131 loss: 0.9652 loss_prob: 0.4931 loss_thr: 0.3846 loss_db: 0.0874 2022/10/26 07:02:18 - mmengine - INFO - Epoch(train) [942][40/63] lr: 8.8717e-04 eta: 3:06:46 time: 0.4955 data_time: 0.0104 memory: 16131 loss: 0.9983 loss_prob: 0.5328 loss_thr: 0.3737 loss_db: 0.0918 2022/10/26 07:02:20 - mmengine - INFO - Epoch(train) [942][45/63] lr: 8.8717e-04 eta: 3:06:46 time: 0.5025 data_time: 0.0101 memory: 16131 loss: 1.0939 loss_prob: 0.6099 loss_thr: 0.3853 loss_db: 0.0986 2022/10/26 07:02:23 - mmengine - INFO - Epoch(train) [942][50/63] lr: 8.8717e-04 eta: 3:06:39 time: 0.5614 data_time: 0.0266 memory: 16131 loss: 1.0623 loss_prob: 0.5888 loss_thr: 0.3783 loss_db: 0.0952 2022/10/26 07:02:26 - mmengine - INFO - Epoch(train) [942][55/63] lr: 8.8717e-04 eta: 3:06:39 time: 0.5530 data_time: 0.0274 memory: 16131 loss: 1.0000 loss_prob: 0.5348 loss_thr: 0.3734 loss_db: 0.0917 2022/10/26 07:02:28 - mmengine - INFO - Epoch(train) [942][60/63] lr: 8.8717e-04 eta: 3:06:31 time: 0.5007 data_time: 0.0058 memory: 16131 loss: 0.9867 loss_prob: 0.5162 loss_thr: 0.3826 loss_db: 0.0879 2022/10/26 07:02:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:02:34 - mmengine - INFO - Epoch(train) [943][5/63] lr: 8.8407e-04 eta: 3:06:31 time: 0.7100 data_time: 0.1764 memory: 16131 loss: 0.9355 loss_prob: 0.4867 loss_thr: 0.3635 loss_db: 0.0853 2022/10/26 07:02:37 - mmengine - INFO - Epoch(train) [943][10/63] lr: 8.8407e-04 eta: 3:06:22 time: 0.7087 data_time: 0.1826 memory: 16131 loss: 0.8809 loss_prob: 0.4575 loss_thr: 0.3428 loss_db: 0.0807 2022/10/26 07:02:39 - mmengine - INFO - Epoch(train) [943][15/63] lr: 8.8407e-04 eta: 3:06:22 time: 0.5170 data_time: 0.0124 memory: 16131 loss: 0.9435 loss_prob: 0.4890 loss_thr: 0.3688 loss_db: 0.0857 2022/10/26 07:02:43 - mmengine - INFO - Epoch(train) [943][20/63] lr: 8.8407e-04 eta: 3:06:15 time: 0.5664 data_time: 0.0075 memory: 16131 loss: 1.0357 loss_prob: 0.5462 loss_thr: 0.3937 loss_db: 0.0958 2022/10/26 07:02:46 - mmengine - INFO - Epoch(train) [943][25/63] lr: 8.8407e-04 eta: 3:06:15 time: 0.6139 data_time: 0.0440 memory: 16131 loss: 1.0619 loss_prob: 0.5683 loss_thr: 0.3964 loss_db: 0.0972 2022/10/26 07:02:48 - mmengine - INFO - Epoch(train) [943][30/63] lr: 8.8407e-04 eta: 3:06:08 time: 0.5707 data_time: 0.0441 memory: 16131 loss: 1.0212 loss_prob: 0.5458 loss_thr: 0.3830 loss_db: 0.0924 2022/10/26 07:02:51 - mmengine - INFO - Epoch(train) [943][35/63] lr: 8.8407e-04 eta: 3:06:08 time: 0.5074 data_time: 0.0078 memory: 16131 loss: 0.9933 loss_prob: 0.5242 loss_thr: 0.3773 loss_db: 0.0918 2022/10/26 07:02:53 - mmengine - INFO - Epoch(train) [943][40/63] lr: 8.8407e-04 eta: 3:06:00 time: 0.5073 data_time: 0.0096 memory: 16131 loss: 1.0383 loss_prob: 0.5555 loss_thr: 0.3873 loss_db: 0.0955 2022/10/26 07:02:56 - mmengine - INFO - Epoch(train) [943][45/63] lr: 8.8407e-04 eta: 3:06:00 time: 0.5102 data_time: 0.0112 memory: 16131 loss: 1.0095 loss_prob: 0.5377 loss_thr: 0.3810 loss_db: 0.0908 2022/10/26 07:02:59 - mmengine - INFO - Epoch(train) [943][50/63] lr: 8.8407e-04 eta: 3:05:53 time: 0.5367 data_time: 0.0237 memory: 16131 loss: 1.0040 loss_prob: 0.5315 loss_thr: 0.3813 loss_db: 0.0912 2022/10/26 07:03:02 - mmengine - INFO - Epoch(train) [943][55/63] lr: 8.8407e-04 eta: 3:05:53 time: 0.6031 data_time: 0.0257 memory: 16131 loss: 1.0566 loss_prob: 0.5648 loss_thr: 0.3936 loss_db: 0.0982 2022/10/26 07:03:04 - mmengine - INFO - Epoch(train) [943][60/63] lr: 8.8407e-04 eta: 3:05:46 time: 0.5490 data_time: 0.0090 memory: 16131 loss: 1.0431 loss_prob: 0.5567 loss_thr: 0.3903 loss_db: 0.0960 2022/10/26 07:03:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:03:10 - mmengine - INFO - Epoch(train) [944][5/63] lr: 8.8097e-04 eta: 3:05:46 time: 0.7198 data_time: 0.1897 memory: 16131 loss: 1.0713 loss_prob: 0.5788 loss_thr: 0.3943 loss_db: 0.0983 2022/10/26 07:03:13 - mmengine - INFO - Epoch(train) [944][10/63] lr: 8.8097e-04 eta: 3:05:36 time: 0.7325 data_time: 0.1942 memory: 16131 loss: 0.9483 loss_prob: 0.4924 loss_thr: 0.3714 loss_db: 0.0845 2022/10/26 07:03:16 - mmengine - INFO - Epoch(train) [944][15/63] lr: 8.8097e-04 eta: 3:05:36 time: 0.5304 data_time: 0.0108 memory: 16131 loss: 0.9602 loss_prob: 0.5003 loss_thr: 0.3713 loss_db: 0.0886 2022/10/26 07:03:18 - mmengine - INFO - Epoch(train) [944][20/63] lr: 8.8097e-04 eta: 3:05:29 time: 0.5387 data_time: 0.0063 memory: 16131 loss: 0.9933 loss_prob: 0.5202 loss_thr: 0.3771 loss_db: 0.0960 2022/10/26 07:03:21 - mmengine - INFO - Epoch(train) [944][25/63] lr: 8.8097e-04 eta: 3:05:29 time: 0.5202 data_time: 0.0295 memory: 16131 loss: 0.9272 loss_prob: 0.4823 loss_thr: 0.3574 loss_db: 0.0876 2022/10/26 07:03:24 - mmengine - INFO - Epoch(train) [944][30/63] lr: 8.8097e-04 eta: 3:05:22 time: 0.5331 data_time: 0.0326 memory: 16131 loss: 0.9848 loss_prob: 0.5292 loss_thr: 0.3689 loss_db: 0.0866 2022/10/26 07:03:26 - mmengine - INFO - Epoch(train) [944][35/63] lr: 8.8097e-04 eta: 3:05:22 time: 0.5115 data_time: 0.0132 memory: 16131 loss: 1.0158 loss_prob: 0.5452 loss_thr: 0.3804 loss_db: 0.0901 2022/10/26 07:03:29 - mmengine - INFO - Epoch(train) [944][40/63] lr: 8.8097e-04 eta: 3:05:14 time: 0.5200 data_time: 0.0113 memory: 16131 loss: 1.0339 loss_prob: 0.5494 loss_thr: 0.3881 loss_db: 0.0964 2022/10/26 07:03:32 - mmengine - INFO - Epoch(train) [944][45/63] lr: 8.8097e-04 eta: 3:05:14 time: 0.5690 data_time: 0.0079 memory: 16131 loss: 1.0325 loss_prob: 0.5528 loss_thr: 0.3818 loss_db: 0.0979 2022/10/26 07:03:34 - mmengine - INFO - Epoch(train) [944][50/63] lr: 8.8097e-04 eta: 3:05:07 time: 0.5461 data_time: 0.0177 memory: 16131 loss: 1.0029 loss_prob: 0.5281 loss_thr: 0.3830 loss_db: 0.0918 2022/10/26 07:03:37 - mmengine - INFO - Epoch(train) [944][55/63] lr: 8.8097e-04 eta: 3:05:07 time: 0.5213 data_time: 0.0227 memory: 16131 loss: 1.0151 loss_prob: 0.5345 loss_thr: 0.3894 loss_db: 0.0911 2022/10/26 07:03:40 - mmengine - INFO - Epoch(train) [944][60/63] lr: 8.8097e-04 eta: 3:05:00 time: 0.5740 data_time: 0.0129 memory: 16131 loss: 0.9651 loss_prob: 0.5145 loss_thr: 0.3635 loss_db: 0.0871 2022/10/26 07:03:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:03:46 - mmengine - INFO - Epoch(train) [945][5/63] lr: 8.7788e-04 eta: 3:05:00 time: 0.7096 data_time: 0.1631 memory: 16131 loss: 1.0048 loss_prob: 0.5356 loss_thr: 0.3755 loss_db: 0.0937 2022/10/26 07:03:49 - mmengine - INFO - Epoch(train) [945][10/63] lr: 8.7788e-04 eta: 3:04:50 time: 0.7113 data_time: 0.1618 memory: 16131 loss: 0.9819 loss_prob: 0.5151 loss_thr: 0.3777 loss_db: 0.0891 2022/10/26 07:03:51 - mmengine - INFO - Epoch(train) [945][15/63] lr: 8.7788e-04 eta: 3:04:50 time: 0.5068 data_time: 0.0069 memory: 16131 loss: 0.9542 loss_prob: 0.5013 loss_thr: 0.3666 loss_db: 0.0862 2022/10/26 07:03:53 - mmengine - INFO - Epoch(train) [945][20/63] lr: 8.7788e-04 eta: 3:04:43 time: 0.4861 data_time: 0.0072 memory: 16131 loss: 0.9202 loss_prob: 0.4816 loss_thr: 0.3543 loss_db: 0.0843 2022/10/26 07:03:56 - mmengine - INFO - Epoch(train) [945][25/63] lr: 8.7788e-04 eta: 3:04:43 time: 0.5020 data_time: 0.0168 memory: 16131 loss: 0.9815 loss_prob: 0.5139 loss_thr: 0.3771 loss_db: 0.0906 2022/10/26 07:03:59 - mmengine - INFO - Epoch(train) [945][30/63] lr: 8.7788e-04 eta: 3:04:36 time: 0.5301 data_time: 0.0385 memory: 16131 loss: 1.0398 loss_prob: 0.5551 loss_thr: 0.3884 loss_db: 0.0963 2022/10/26 07:04:01 - mmengine - INFO - Epoch(train) [945][35/63] lr: 8.7788e-04 eta: 3:04:36 time: 0.5324 data_time: 0.0306 memory: 16131 loss: 1.0507 loss_prob: 0.5647 loss_thr: 0.3880 loss_db: 0.0980 2022/10/26 07:04:04 - mmengine - INFO - Epoch(train) [945][40/63] lr: 8.7788e-04 eta: 3:04:28 time: 0.5159 data_time: 0.0086 memory: 16131 loss: 1.0909 loss_prob: 0.5936 loss_thr: 0.3990 loss_db: 0.0983 2022/10/26 07:04:07 - mmengine - INFO - Epoch(train) [945][45/63] lr: 8.7788e-04 eta: 3:04:28 time: 0.5141 data_time: 0.0048 memory: 16131 loss: 1.0423 loss_prob: 0.5691 loss_thr: 0.3820 loss_db: 0.0912 2022/10/26 07:04:09 - mmengine - INFO - Epoch(train) [945][50/63] lr: 8.7788e-04 eta: 3:04:21 time: 0.5048 data_time: 0.0112 memory: 16131 loss: 0.9901 loss_prob: 0.5270 loss_thr: 0.3737 loss_db: 0.0894 2022/10/26 07:04:11 - mmengine - INFO - Epoch(train) [945][55/63] lr: 8.7788e-04 eta: 3:04:21 time: 0.4960 data_time: 0.0195 memory: 16131 loss: 0.9907 loss_prob: 0.5225 loss_thr: 0.3771 loss_db: 0.0910 2022/10/26 07:04:14 - mmengine - INFO - Epoch(train) [945][60/63] lr: 8.7788e-04 eta: 3:04:14 time: 0.4935 data_time: 0.0157 memory: 16131 loss: 0.9695 loss_prob: 0.5012 loss_thr: 0.3797 loss_db: 0.0887 2022/10/26 07:04:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:04:19 - mmengine - INFO - Epoch(train) [946][5/63] lr: 8.7478e-04 eta: 3:04:14 time: 0.6404 data_time: 0.1773 memory: 16131 loss: 0.9170 loss_prob: 0.4829 loss_thr: 0.3493 loss_db: 0.0848 2022/10/26 07:04:22 - mmengine - INFO - Epoch(train) [946][10/63] lr: 8.7478e-04 eta: 3:04:04 time: 0.6827 data_time: 0.1819 memory: 16131 loss: 0.9478 loss_prob: 0.4937 loss_thr: 0.3687 loss_db: 0.0854 2022/10/26 07:04:25 - mmengine - INFO - Epoch(train) [946][15/63] lr: 8.7478e-04 eta: 3:04:04 time: 0.5166 data_time: 0.0213 memory: 16131 loss: 1.0153 loss_prob: 0.5419 loss_thr: 0.3802 loss_db: 0.0931 2022/10/26 07:04:27 - mmengine - INFO - Epoch(train) [946][20/63] lr: 8.7478e-04 eta: 3:03:57 time: 0.5050 data_time: 0.0152 memory: 16131 loss: 0.9612 loss_prob: 0.5127 loss_thr: 0.3608 loss_db: 0.0877 2022/10/26 07:04:29 - mmengine - INFO - Epoch(train) [946][25/63] lr: 8.7478e-04 eta: 3:03:57 time: 0.4962 data_time: 0.0174 memory: 16131 loss: 0.9977 loss_prob: 0.5240 loss_thr: 0.3836 loss_db: 0.0901 2022/10/26 07:04:32 - mmengine - INFO - Epoch(train) [946][30/63] lr: 8.7478e-04 eta: 3:03:49 time: 0.5301 data_time: 0.0321 memory: 16131 loss: 1.0232 loss_prob: 0.5396 loss_thr: 0.3893 loss_db: 0.0943 2022/10/26 07:04:35 - mmengine - INFO - Epoch(train) [946][35/63] lr: 8.7478e-04 eta: 3:03:49 time: 0.5629 data_time: 0.0238 memory: 16131 loss: 0.9473 loss_prob: 0.4990 loss_thr: 0.3618 loss_db: 0.0865 2022/10/26 07:04:38 - mmengine - INFO - Epoch(train) [946][40/63] lr: 8.7478e-04 eta: 3:03:42 time: 0.5332 data_time: 0.0084 memory: 16131 loss: 0.9597 loss_prob: 0.5115 loss_thr: 0.3601 loss_db: 0.0882 2022/10/26 07:04:40 - mmengine - INFO - Epoch(train) [946][45/63] lr: 8.7478e-04 eta: 3:03:42 time: 0.5015 data_time: 0.0068 memory: 16131 loss: 0.9579 loss_prob: 0.4993 loss_thr: 0.3715 loss_db: 0.0872 2022/10/26 07:04:43 - mmengine - INFO - Epoch(train) [946][50/63] lr: 8.7478e-04 eta: 3:03:35 time: 0.5565 data_time: 0.0226 memory: 16131 loss: 1.0256 loss_prob: 0.5584 loss_thr: 0.3775 loss_db: 0.0897 2022/10/26 07:04:46 - mmengine - INFO - Epoch(train) [946][55/63] lr: 8.7478e-04 eta: 3:03:35 time: 0.5837 data_time: 0.0235 memory: 16131 loss: 0.9740 loss_prob: 0.5294 loss_thr: 0.3574 loss_db: 0.0873 2022/10/26 07:04:48 - mmengine - INFO - Epoch(train) [946][60/63] lr: 8.7478e-04 eta: 3:03:28 time: 0.5277 data_time: 0.0101 memory: 16131 loss: 0.9405 loss_prob: 0.4922 loss_thr: 0.3620 loss_db: 0.0863 2022/10/26 07:04:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:04:55 - mmengine - INFO - Epoch(train) [947][5/63] lr: 8.7168e-04 eta: 3:03:28 time: 0.7053 data_time: 0.2049 memory: 16131 loss: 0.9080 loss_prob: 0.4793 loss_thr: 0.3465 loss_db: 0.0823 2022/10/26 07:04:57 - mmengine - INFO - Epoch(train) [947][10/63] lr: 8.7168e-04 eta: 3:03:18 time: 0.7179 data_time: 0.2036 memory: 16131 loss: 0.9383 loss_prob: 0.4967 loss_thr: 0.3550 loss_db: 0.0866 2022/10/26 07:05:00 - mmengine - INFO - Epoch(train) [947][15/63] lr: 8.7168e-04 eta: 3:03:18 time: 0.5031 data_time: 0.0091 memory: 16131 loss: 0.9290 loss_prob: 0.4893 loss_thr: 0.3535 loss_db: 0.0863 2022/10/26 07:05:02 - mmengine - INFO - Epoch(train) [947][20/63] lr: 8.7168e-04 eta: 3:03:11 time: 0.5529 data_time: 0.0081 memory: 16131 loss: 0.8991 loss_prob: 0.4765 loss_thr: 0.3388 loss_db: 0.0838 2022/10/26 07:05:05 - mmengine - INFO - Epoch(train) [947][25/63] lr: 8.7168e-04 eta: 3:03:11 time: 0.5378 data_time: 0.0089 memory: 16131 loss: 0.9455 loss_prob: 0.5007 loss_thr: 0.3583 loss_db: 0.0865 2022/10/26 07:05:08 - mmengine - INFO - Epoch(train) [947][30/63] lr: 8.7168e-04 eta: 3:03:04 time: 0.5733 data_time: 0.0375 memory: 16131 loss: 0.9497 loss_prob: 0.4935 loss_thr: 0.3705 loss_db: 0.0857 2022/10/26 07:05:11 - mmengine - INFO - Epoch(train) [947][35/63] lr: 8.7168e-04 eta: 3:03:04 time: 0.5947 data_time: 0.0339 memory: 16131 loss: 1.0429 loss_prob: 0.5821 loss_thr: 0.3662 loss_db: 0.0946 2022/10/26 07:05:14 - mmengine - INFO - Epoch(train) [947][40/63] lr: 8.7168e-04 eta: 3:02:56 time: 0.5392 data_time: 0.0058 memory: 16131 loss: 1.0244 loss_prob: 0.5745 loss_thr: 0.3551 loss_db: 0.0948 2022/10/26 07:05:16 - mmengine - INFO - Epoch(train) [947][45/63] lr: 8.7168e-04 eta: 3:02:56 time: 0.5520 data_time: 0.0099 memory: 16131 loss: 0.9339 loss_prob: 0.4956 loss_thr: 0.3507 loss_db: 0.0876 2022/10/26 07:05:19 - mmengine - INFO - Epoch(train) [947][50/63] lr: 8.7168e-04 eta: 3:02:49 time: 0.5424 data_time: 0.0278 memory: 16131 loss: 1.0099 loss_prob: 0.5403 loss_thr: 0.3773 loss_db: 0.0923 2022/10/26 07:05:22 - mmengine - INFO - Epoch(train) [947][55/63] lr: 8.7168e-04 eta: 3:02:49 time: 0.5113 data_time: 0.0237 memory: 16131 loss: 1.0019 loss_prob: 0.5276 loss_thr: 0.3832 loss_db: 0.0911 2022/10/26 07:05:24 - mmengine - INFO - Epoch(train) [947][60/63] lr: 8.7168e-04 eta: 3:02:42 time: 0.5018 data_time: 0.0053 memory: 16131 loss: 0.9759 loss_prob: 0.5061 loss_thr: 0.3817 loss_db: 0.0881 2022/10/26 07:05:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:05:30 - mmengine - INFO - Epoch(train) [948][5/63] lr: 8.6858e-04 eta: 3:02:42 time: 0.7039 data_time: 0.1866 memory: 16131 loss: 0.9282 loss_prob: 0.4828 loss_thr: 0.3587 loss_db: 0.0867 2022/10/26 07:05:33 - mmengine - INFO - Epoch(train) [948][10/63] lr: 8.6858e-04 eta: 3:02:32 time: 0.7282 data_time: 0.1924 memory: 16131 loss: 1.0263 loss_prob: 0.5352 loss_thr: 0.3977 loss_db: 0.0934 2022/10/26 07:05:35 - mmengine - INFO - Epoch(train) [948][15/63] lr: 8.6858e-04 eta: 3:02:32 time: 0.5031 data_time: 0.0178 memory: 16131 loss: 1.0070 loss_prob: 0.5300 loss_thr: 0.3859 loss_db: 0.0911 2022/10/26 07:05:38 - mmengine - INFO - Epoch(train) [948][20/63] lr: 8.6858e-04 eta: 3:02:25 time: 0.5169 data_time: 0.0108 memory: 16131 loss: 1.0009 loss_prob: 0.5333 loss_thr: 0.3752 loss_db: 0.0923 2022/10/26 07:05:41 - mmengine - INFO - Epoch(train) [948][25/63] lr: 8.6858e-04 eta: 3:02:25 time: 0.5528 data_time: 0.0257 memory: 16131 loss: 1.0286 loss_prob: 0.5490 loss_thr: 0.3841 loss_db: 0.0955 2022/10/26 07:05:43 - mmengine - INFO - Epoch(train) [948][30/63] lr: 8.6858e-04 eta: 3:02:18 time: 0.5537 data_time: 0.0275 memory: 16131 loss: 0.9551 loss_prob: 0.5073 loss_thr: 0.3609 loss_db: 0.0870 2022/10/26 07:05:46 - mmengine - INFO - Epoch(train) [948][35/63] lr: 8.6858e-04 eta: 3:02:18 time: 0.5108 data_time: 0.0115 memory: 16131 loss: 0.9415 loss_prob: 0.5042 loss_thr: 0.3525 loss_db: 0.0848 2022/10/26 07:05:49 - mmengine - INFO - Epoch(train) [948][40/63] lr: 8.6858e-04 eta: 3:02:11 time: 0.5434 data_time: 0.0110 memory: 16131 loss: 0.9204 loss_prob: 0.4890 loss_thr: 0.3476 loss_db: 0.0838 2022/10/26 07:05:51 - mmengine - INFO - Epoch(train) [948][45/63] lr: 8.6858e-04 eta: 3:02:11 time: 0.5589 data_time: 0.0067 memory: 16131 loss: 0.8731 loss_prob: 0.4550 loss_thr: 0.3382 loss_db: 0.0799 2022/10/26 07:05:54 - mmengine - INFO - Epoch(train) [948][50/63] lr: 8.6858e-04 eta: 3:02:03 time: 0.5216 data_time: 0.0169 memory: 16131 loss: 0.9113 loss_prob: 0.4675 loss_thr: 0.3604 loss_db: 0.0833 2022/10/26 07:05:57 - mmengine - INFO - Epoch(train) [948][55/63] lr: 8.6858e-04 eta: 3:02:03 time: 0.5425 data_time: 0.0475 memory: 16131 loss: 0.9818 loss_prob: 0.5183 loss_thr: 0.3720 loss_db: 0.0915 2022/10/26 07:05:59 - mmengine - INFO - Epoch(train) [948][60/63] lr: 8.6858e-04 eta: 3:01:56 time: 0.5548 data_time: 0.0374 memory: 16131 loss: 1.0234 loss_prob: 0.5506 loss_thr: 0.3797 loss_db: 0.0931 2022/10/26 07:06:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:06:05 - mmengine - INFO - Epoch(train) [949][5/63] lr: 8.6547e-04 eta: 3:01:56 time: 0.6603 data_time: 0.1654 memory: 16131 loss: 0.9407 loss_prob: 0.4999 loss_thr: 0.3540 loss_db: 0.0868 2022/10/26 07:06:07 - mmengine - INFO - Epoch(train) [949][10/63] lr: 8.6547e-04 eta: 3:01:47 time: 0.6694 data_time: 0.1649 memory: 16131 loss: 0.9069 loss_prob: 0.4822 loss_thr: 0.3401 loss_db: 0.0846 2022/10/26 07:06:10 - mmengine - INFO - Epoch(train) [949][15/63] lr: 8.6547e-04 eta: 3:01:47 time: 0.5193 data_time: 0.0062 memory: 16131 loss: 0.9474 loss_prob: 0.4961 loss_thr: 0.3657 loss_db: 0.0855 2022/10/26 07:06:13 - mmengine - INFO - Epoch(train) [949][20/63] lr: 8.6547e-04 eta: 3:01:39 time: 0.5241 data_time: 0.0049 memory: 16131 loss: 0.9183 loss_prob: 0.4731 loss_thr: 0.3627 loss_db: 0.0826 2022/10/26 07:06:15 - mmengine - INFO - Epoch(train) [949][25/63] lr: 8.6547e-04 eta: 3:01:39 time: 0.5260 data_time: 0.0123 memory: 16131 loss: 0.8566 loss_prob: 0.4385 loss_thr: 0.3411 loss_db: 0.0770 2022/10/26 07:06:18 - mmengine - INFO - Epoch(train) [949][30/63] lr: 8.6547e-04 eta: 3:01:32 time: 0.5524 data_time: 0.0336 memory: 16131 loss: 0.8795 loss_prob: 0.4574 loss_thr: 0.3425 loss_db: 0.0796 2022/10/26 07:06:21 - mmengine - INFO - Epoch(train) [949][35/63] lr: 8.6547e-04 eta: 3:01:32 time: 0.5285 data_time: 0.0265 memory: 16131 loss: 0.9360 loss_prob: 0.4906 loss_thr: 0.3599 loss_db: 0.0856 2022/10/26 07:06:23 - mmengine - INFO - Epoch(train) [949][40/63] lr: 8.6547e-04 eta: 3:01:25 time: 0.5188 data_time: 0.0103 memory: 16131 loss: 0.9816 loss_prob: 0.5053 loss_thr: 0.3871 loss_db: 0.0891 2022/10/26 07:06:26 - mmengine - INFO - Epoch(train) [949][45/63] lr: 8.6547e-04 eta: 3:01:25 time: 0.5575 data_time: 0.0120 memory: 16131 loss: 0.9357 loss_prob: 0.4786 loss_thr: 0.3728 loss_db: 0.0843 2022/10/26 07:06:29 - mmengine - INFO - Epoch(train) [949][50/63] lr: 8.6547e-04 eta: 3:01:17 time: 0.5398 data_time: 0.0134 memory: 16131 loss: 0.9461 loss_prob: 0.5005 loss_thr: 0.3587 loss_db: 0.0869 2022/10/26 07:06:31 - mmengine - INFO - Epoch(train) [949][55/63] lr: 8.6547e-04 eta: 3:01:17 time: 0.5151 data_time: 0.0227 memory: 16131 loss: 1.0568 loss_prob: 0.5633 loss_thr: 0.3948 loss_db: 0.0987 2022/10/26 07:06:34 - mmengine - INFO - Epoch(train) [949][60/63] lr: 8.6547e-04 eta: 3:01:10 time: 0.5089 data_time: 0.0163 memory: 16131 loss: 1.0134 loss_prob: 0.5289 loss_thr: 0.3918 loss_db: 0.0928 2022/10/26 07:06:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:06:40 - mmengine - INFO - Epoch(train) [950][5/63] lr: 8.6237e-04 eta: 3:01:10 time: 0.7429 data_time: 0.2012 memory: 16131 loss: 0.9606 loss_prob: 0.4887 loss_thr: 0.3875 loss_db: 0.0844 2022/10/26 07:06:43 - mmengine - INFO - Epoch(train) [950][10/63] lr: 8.6237e-04 eta: 3:01:01 time: 0.7986 data_time: 0.2078 memory: 16131 loss: 0.8768 loss_prob: 0.4402 loss_thr: 0.3601 loss_db: 0.0766 2022/10/26 07:06:46 - mmengine - INFO - Epoch(train) [950][15/63] lr: 8.6237e-04 eta: 3:01:01 time: 0.5243 data_time: 0.0120 memory: 16131 loss: 0.9021 loss_prob: 0.4658 loss_thr: 0.3544 loss_db: 0.0819 2022/10/26 07:06:49 - mmengine - INFO - Epoch(train) [950][20/63] lr: 8.6237e-04 eta: 3:00:54 time: 0.5415 data_time: 0.0082 memory: 16131 loss: 0.9656 loss_prob: 0.5103 loss_thr: 0.3663 loss_db: 0.0889 2022/10/26 07:06:52 - mmengine - INFO - Epoch(train) [950][25/63] lr: 8.6237e-04 eta: 3:00:54 time: 0.6082 data_time: 0.0210 memory: 16131 loss: 0.9689 loss_prob: 0.5250 loss_thr: 0.3575 loss_db: 0.0864 2022/10/26 07:06:54 - mmengine - INFO - Epoch(train) [950][30/63] lr: 8.6237e-04 eta: 3:00:46 time: 0.5701 data_time: 0.0343 memory: 16131 loss: 0.9286 loss_prob: 0.4987 loss_thr: 0.3484 loss_db: 0.0815 2022/10/26 07:06:57 - mmengine - INFO - Epoch(train) [950][35/63] lr: 8.6237e-04 eta: 3:00:46 time: 0.5103 data_time: 0.0221 memory: 16131 loss: 0.9115 loss_prob: 0.4764 loss_thr: 0.3535 loss_db: 0.0816 2022/10/26 07:06:59 - mmengine - INFO - Epoch(train) [950][40/63] lr: 8.6237e-04 eta: 3:00:39 time: 0.4815 data_time: 0.0080 memory: 16131 loss: 0.9668 loss_prob: 0.4972 loss_thr: 0.3835 loss_db: 0.0861 2022/10/26 07:07:02 - mmengine - INFO - Epoch(train) [950][45/63] lr: 8.6237e-04 eta: 3:00:39 time: 0.5108 data_time: 0.0074 memory: 16131 loss: 0.9508 loss_prob: 0.4886 loss_thr: 0.3781 loss_db: 0.0840 2022/10/26 07:07:05 - mmengine - INFO - Epoch(train) [950][50/63] lr: 8.6237e-04 eta: 3:00:32 time: 0.5794 data_time: 0.0244 memory: 16131 loss: 0.9751 loss_prob: 0.5096 loss_thr: 0.3768 loss_db: 0.0887 2022/10/26 07:07:08 - mmengine - INFO - Epoch(train) [950][55/63] lr: 8.6237e-04 eta: 3:00:32 time: 0.5851 data_time: 0.0273 memory: 16131 loss: 0.9727 loss_prob: 0.5105 loss_thr: 0.3730 loss_db: 0.0892 2022/10/26 07:07:10 - mmengine - INFO - Epoch(train) [950][60/63] lr: 8.6237e-04 eta: 3:00:25 time: 0.5205 data_time: 0.0087 memory: 16131 loss: 0.9673 loss_prob: 0.5141 loss_thr: 0.3637 loss_db: 0.0895 2022/10/26 07:07:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:07:16 - mmengine - INFO - Epoch(train) [951][5/63] lr: 8.5927e-04 eta: 3:00:25 time: 0.7104 data_time: 0.1930 memory: 16131 loss: 1.0051 loss_prob: 0.5338 loss_thr: 0.3807 loss_db: 0.0906 2022/10/26 07:07:19 - mmengine - INFO - Epoch(train) [951][10/63] lr: 8.5927e-04 eta: 3:00:15 time: 0.7520 data_time: 0.1949 memory: 16131 loss: 1.0093 loss_prob: 0.5342 loss_thr: 0.3830 loss_db: 0.0921 2022/10/26 07:07:22 - mmengine - INFO - Epoch(train) [951][15/63] lr: 8.5927e-04 eta: 3:00:15 time: 0.5977 data_time: 0.0080 memory: 16131 loss: 0.9908 loss_prob: 0.5243 loss_thr: 0.3750 loss_db: 0.0915 2022/10/26 07:07:25 - mmengine - INFO - Epoch(train) [951][20/63] lr: 8.5927e-04 eta: 3:00:08 time: 0.5688 data_time: 0.0065 memory: 16131 loss: 0.9419 loss_prob: 0.4925 loss_thr: 0.3608 loss_db: 0.0886 2022/10/26 07:07:27 - mmengine - INFO - Epoch(train) [951][25/63] lr: 8.5927e-04 eta: 3:00:08 time: 0.5038 data_time: 0.0246 memory: 16131 loss: 0.9864 loss_prob: 0.5110 loss_thr: 0.3840 loss_db: 0.0913 2022/10/26 07:07:30 - mmengine - INFO - Epoch(train) [951][30/63] lr: 8.5927e-04 eta: 3:00:01 time: 0.5200 data_time: 0.0362 memory: 16131 loss: 0.9502 loss_prob: 0.4942 loss_thr: 0.3715 loss_db: 0.0845 2022/10/26 07:07:33 - mmengine - INFO - Epoch(train) [951][35/63] lr: 8.5927e-04 eta: 3:00:01 time: 0.5171 data_time: 0.0172 memory: 16131 loss: 0.8962 loss_prob: 0.4632 loss_thr: 0.3521 loss_db: 0.0809 2022/10/26 07:07:35 - mmengine - INFO - Epoch(train) [951][40/63] lr: 8.5927e-04 eta: 2:59:53 time: 0.5010 data_time: 0.0053 memory: 16131 loss: 0.9516 loss_prob: 0.4995 loss_thr: 0.3618 loss_db: 0.0903 2022/10/26 07:07:37 - mmengine - INFO - Epoch(train) [951][45/63] lr: 8.5927e-04 eta: 2:59:53 time: 0.4965 data_time: 0.0052 memory: 16131 loss: 0.9623 loss_prob: 0.5155 loss_thr: 0.3557 loss_db: 0.0911 2022/10/26 07:07:41 - mmengine - INFO - Epoch(train) [951][50/63] lr: 8.5927e-04 eta: 2:59:46 time: 0.6133 data_time: 0.0218 memory: 16131 loss: 0.9270 loss_prob: 0.4859 loss_thr: 0.3569 loss_db: 0.0842 2022/10/26 07:07:44 - mmengine - INFO - Epoch(train) [951][55/63] lr: 8.5927e-04 eta: 2:59:46 time: 0.6435 data_time: 0.0262 memory: 16131 loss: 0.8968 loss_prob: 0.4585 loss_thr: 0.3581 loss_db: 0.0802 2022/10/26 07:07:47 - mmengine - INFO - Epoch(train) [951][60/63] lr: 8.5927e-04 eta: 2:59:39 time: 0.5590 data_time: 0.0093 memory: 16131 loss: 0.8742 loss_prob: 0.4507 loss_thr: 0.3441 loss_db: 0.0794 2022/10/26 07:07:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:07:53 - mmengine - INFO - Epoch(train) [952][5/63] lr: 8.5616e-04 eta: 2:59:39 time: 0.7069 data_time: 0.1863 memory: 16131 loss: 0.9135 loss_prob: 0.4781 loss_thr: 0.3516 loss_db: 0.0838 2022/10/26 07:07:55 - mmengine - INFO - Epoch(train) [952][10/63] lr: 8.5616e-04 eta: 2:59:30 time: 0.7095 data_time: 0.1864 memory: 16131 loss: 0.9060 loss_prob: 0.4711 loss_thr: 0.3529 loss_db: 0.0820 2022/10/26 07:07:58 - mmengine - INFO - Epoch(train) [952][15/63] lr: 8.5616e-04 eta: 2:59:30 time: 0.5387 data_time: 0.0061 memory: 16131 loss: 0.8742 loss_prob: 0.4470 loss_thr: 0.3490 loss_db: 0.0783 2022/10/26 07:08:01 - mmengine - INFO - Epoch(train) [952][20/63] lr: 8.5616e-04 eta: 2:59:22 time: 0.5260 data_time: 0.0055 memory: 16131 loss: 1.0056 loss_prob: 0.5258 loss_thr: 0.3881 loss_db: 0.0917 2022/10/26 07:08:03 - mmengine - INFO - Epoch(train) [952][25/63] lr: 8.5616e-04 eta: 2:59:22 time: 0.5109 data_time: 0.0316 memory: 16131 loss: 1.0300 loss_prob: 0.5441 loss_thr: 0.3924 loss_db: 0.0936 2022/10/26 07:08:06 - mmengine - INFO - Epoch(train) [952][30/63] lr: 8.5616e-04 eta: 2:59:15 time: 0.5305 data_time: 0.0422 memory: 16131 loss: 0.9424 loss_prob: 0.4935 loss_thr: 0.3630 loss_db: 0.0859 2022/10/26 07:08:08 - mmengine - INFO - Epoch(train) [952][35/63] lr: 8.5616e-04 eta: 2:59:15 time: 0.5151 data_time: 0.0184 memory: 16131 loss: 0.9911 loss_prob: 0.5257 loss_thr: 0.3737 loss_db: 0.0916 2022/10/26 07:08:11 - mmengine - INFO - Epoch(train) [952][40/63] lr: 8.5616e-04 eta: 2:59:08 time: 0.5000 data_time: 0.0117 memory: 16131 loss: 0.9608 loss_prob: 0.5074 loss_thr: 0.3646 loss_db: 0.0888 2022/10/26 07:08:13 - mmengine - INFO - Epoch(train) [952][45/63] lr: 8.5616e-04 eta: 2:59:08 time: 0.5024 data_time: 0.0115 memory: 16131 loss: 0.8900 loss_prob: 0.4614 loss_thr: 0.3474 loss_db: 0.0813 2022/10/26 07:08:16 - mmengine - INFO - Epoch(train) [952][50/63] lr: 8.5616e-04 eta: 2:59:01 time: 0.5301 data_time: 0.0212 memory: 16131 loss: 0.9436 loss_prob: 0.4922 loss_thr: 0.3665 loss_db: 0.0849 2022/10/26 07:08:19 - mmengine - INFO - Epoch(train) [952][55/63] lr: 8.5616e-04 eta: 2:59:01 time: 0.6053 data_time: 0.0443 memory: 16131 loss: 0.9902 loss_prob: 0.5213 loss_thr: 0.3796 loss_db: 0.0893 2022/10/26 07:08:22 - mmengine - INFO - Epoch(train) [952][60/63] lr: 8.5616e-04 eta: 2:58:53 time: 0.5872 data_time: 0.0307 memory: 16131 loss: 0.9982 loss_prob: 0.5250 loss_thr: 0.3828 loss_db: 0.0904 2022/10/26 07:08:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:08:28 - mmengine - INFO - Epoch(train) [953][5/63] lr: 8.5305e-04 eta: 2:58:53 time: 0.7163 data_time: 0.1692 memory: 16131 loss: 0.9898 loss_prob: 0.5194 loss_thr: 0.3813 loss_db: 0.0892 2022/10/26 07:08:31 - mmengine - INFO - Epoch(train) [953][10/63] lr: 8.5305e-04 eta: 2:58:44 time: 0.7808 data_time: 0.1871 memory: 16131 loss: 0.8955 loss_prob: 0.4657 loss_thr: 0.3485 loss_db: 0.0814 2022/10/26 07:08:34 - mmengine - INFO - Epoch(train) [953][15/63] lr: 8.5305e-04 eta: 2:58:44 time: 0.5545 data_time: 0.0250 memory: 16131 loss: 0.9555 loss_prob: 0.5041 loss_thr: 0.3627 loss_db: 0.0887 2022/10/26 07:08:36 - mmengine - INFO - Epoch(train) [953][20/63] lr: 8.5305e-04 eta: 2:58:37 time: 0.5320 data_time: 0.0064 memory: 16131 loss: 1.0354 loss_prob: 0.5589 loss_thr: 0.3800 loss_db: 0.0965 2022/10/26 07:08:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:08:39 - mmengine - INFO - Epoch(train) [953][25/63] lr: 8.5305e-04 eta: 2:58:37 time: 0.5189 data_time: 0.0152 memory: 16131 loss: 1.0733 loss_prob: 0.5875 loss_thr: 0.3896 loss_db: 0.0962 2022/10/26 07:08:42 - mmengine - INFO - Epoch(train) [953][30/63] lr: 8.5305e-04 eta: 2:58:30 time: 0.5332 data_time: 0.0354 memory: 16131 loss: 1.0688 loss_prob: 0.5785 loss_thr: 0.3948 loss_db: 0.0955 2022/10/26 07:08:44 - mmengine - INFO - Epoch(train) [953][35/63] lr: 8.5305e-04 eta: 2:58:30 time: 0.5215 data_time: 0.0265 memory: 16131 loss: 1.0477 loss_prob: 0.5649 loss_thr: 0.3891 loss_db: 0.0937 2022/10/26 07:08:47 - mmengine - INFO - Epoch(train) [953][40/63] lr: 8.5305e-04 eta: 2:58:22 time: 0.5173 data_time: 0.0047 memory: 16131 loss: 0.9879 loss_prob: 0.5299 loss_thr: 0.3698 loss_db: 0.0883 2022/10/26 07:08:49 - mmengine - INFO - Epoch(train) [953][45/63] lr: 8.5305e-04 eta: 2:58:22 time: 0.5137 data_time: 0.0046 memory: 16131 loss: 0.9918 loss_prob: 0.5215 loss_thr: 0.3776 loss_db: 0.0927 2022/10/26 07:08:52 - mmengine - INFO - Epoch(train) [953][50/63] lr: 8.5305e-04 eta: 2:58:15 time: 0.5143 data_time: 0.0155 memory: 16131 loss: 1.0415 loss_prob: 0.5526 loss_thr: 0.3932 loss_db: 0.0956 2022/10/26 07:08:55 - mmengine - INFO - Epoch(train) [953][55/63] lr: 8.5305e-04 eta: 2:58:15 time: 0.5342 data_time: 0.0259 memory: 16131 loss: 0.9242 loss_prob: 0.4849 loss_thr: 0.3569 loss_db: 0.0824 2022/10/26 07:08:57 - mmengine - INFO - Epoch(train) [953][60/63] lr: 8.5305e-04 eta: 2:58:08 time: 0.5298 data_time: 0.0158 memory: 16131 loss: 0.8830 loss_prob: 0.4629 loss_thr: 0.3399 loss_db: 0.0801 2022/10/26 07:08:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:09:04 - mmengine - INFO - Epoch(train) [954][5/63] lr: 8.4994e-04 eta: 2:58:08 time: 0.7579 data_time: 0.2133 memory: 16131 loss: 0.9999 loss_prob: 0.5254 loss_thr: 0.3812 loss_db: 0.0933 2022/10/26 07:09:06 - mmengine - INFO - Epoch(train) [954][10/63] lr: 8.4994e-04 eta: 2:57:58 time: 0.7519 data_time: 0.2080 memory: 16131 loss: 0.9797 loss_prob: 0.5204 loss_thr: 0.3680 loss_db: 0.0913 2022/10/26 07:09:09 - mmengine - INFO - Epoch(train) [954][15/63] lr: 8.4994e-04 eta: 2:57:58 time: 0.5354 data_time: 0.0055 memory: 16131 loss: 0.9559 loss_prob: 0.4980 loss_thr: 0.3717 loss_db: 0.0863 2022/10/26 07:09:12 - mmengine - INFO - Epoch(train) [954][20/63] lr: 8.4994e-04 eta: 2:57:51 time: 0.5663 data_time: 0.0060 memory: 16131 loss: 1.0112 loss_prob: 0.5267 loss_thr: 0.3921 loss_db: 0.0924 2022/10/26 07:09:15 - mmengine - INFO - Epoch(train) [954][25/63] lr: 8.4994e-04 eta: 2:57:51 time: 0.5911 data_time: 0.0310 memory: 16131 loss: 0.9793 loss_prob: 0.5116 loss_thr: 0.3770 loss_db: 0.0906 2022/10/26 07:09:18 - mmengine - INFO - Epoch(train) [954][30/63] lr: 8.4994e-04 eta: 2:57:44 time: 0.5494 data_time: 0.0368 memory: 16131 loss: 0.9103 loss_prob: 0.4722 loss_thr: 0.3558 loss_db: 0.0823 2022/10/26 07:09:20 - mmengine - INFO - Epoch(train) [954][35/63] lr: 8.4994e-04 eta: 2:57:44 time: 0.5285 data_time: 0.0121 memory: 16131 loss: 0.8978 loss_prob: 0.4642 loss_thr: 0.3531 loss_db: 0.0805 2022/10/26 07:09:23 - mmengine - INFO - Epoch(train) [954][40/63] lr: 8.4994e-04 eta: 2:57:37 time: 0.5187 data_time: 0.0096 memory: 16131 loss: 0.9125 loss_prob: 0.4803 loss_thr: 0.3517 loss_db: 0.0805 2022/10/26 07:09:25 - mmengine - INFO - Epoch(train) [954][45/63] lr: 8.4994e-04 eta: 2:57:37 time: 0.4970 data_time: 0.0127 memory: 16131 loss: 0.9739 loss_prob: 0.5203 loss_thr: 0.3670 loss_db: 0.0867 2022/10/26 07:09:28 - mmengine - INFO - Epoch(train) [954][50/63] lr: 8.4994e-04 eta: 2:57:29 time: 0.5180 data_time: 0.0244 memory: 16131 loss: 1.0009 loss_prob: 0.5248 loss_thr: 0.3854 loss_db: 0.0908 2022/10/26 07:09:31 - mmengine - INFO - Epoch(train) [954][55/63] lr: 8.4994e-04 eta: 2:57:29 time: 0.5231 data_time: 0.0251 memory: 16131 loss: 0.9916 loss_prob: 0.5160 loss_thr: 0.3875 loss_db: 0.0881 2022/10/26 07:09:33 - mmengine - INFO - Epoch(train) [954][60/63] lr: 8.4994e-04 eta: 2:57:22 time: 0.5036 data_time: 0.0108 memory: 16131 loss: 1.0103 loss_prob: 0.5288 loss_thr: 0.3921 loss_db: 0.0894 2022/10/26 07:09:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:09:39 - mmengine - INFO - Epoch(train) [955][5/63] lr: 8.4683e-04 eta: 2:57:22 time: 0.6937 data_time: 0.1872 memory: 16131 loss: 1.0598 loss_prob: 0.5635 loss_thr: 0.3994 loss_db: 0.0969 2022/10/26 07:09:42 - mmengine - INFO - Epoch(train) [955][10/63] lr: 8.4683e-04 eta: 2:57:13 time: 0.7195 data_time: 0.1850 memory: 16131 loss: 0.9844 loss_prob: 0.5189 loss_thr: 0.3753 loss_db: 0.0902 2022/10/26 07:09:44 - mmengine - INFO - Epoch(train) [955][15/63] lr: 8.4683e-04 eta: 2:57:13 time: 0.5003 data_time: 0.0051 memory: 16131 loss: 0.9350 loss_prob: 0.4853 loss_thr: 0.3661 loss_db: 0.0836 2022/10/26 07:09:47 - mmengine - INFO - Epoch(train) [955][20/63] lr: 8.4683e-04 eta: 2:57:05 time: 0.5070 data_time: 0.0062 memory: 16131 loss: 0.9709 loss_prob: 0.5123 loss_thr: 0.3713 loss_db: 0.0874 2022/10/26 07:09:49 - mmengine - INFO - Epoch(train) [955][25/63] lr: 8.4683e-04 eta: 2:57:05 time: 0.5509 data_time: 0.0337 memory: 16131 loss: 0.9620 loss_prob: 0.5080 loss_thr: 0.3653 loss_db: 0.0887 2022/10/26 07:09:52 - mmengine - INFO - Epoch(train) [955][30/63] lr: 8.4683e-04 eta: 2:56:58 time: 0.5168 data_time: 0.0325 memory: 16131 loss: 0.9613 loss_prob: 0.5064 loss_thr: 0.3658 loss_db: 0.0892 2022/10/26 07:09:55 - mmengine - INFO - Epoch(train) [955][35/63] lr: 8.4683e-04 eta: 2:56:58 time: 0.5131 data_time: 0.0049 memory: 16131 loss: 1.0553 loss_prob: 0.5679 loss_thr: 0.3887 loss_db: 0.0988 2022/10/26 07:09:57 - mmengine - INFO - Epoch(train) [955][40/63] lr: 8.4683e-04 eta: 2:56:51 time: 0.5278 data_time: 0.0082 memory: 16131 loss: 1.0988 loss_prob: 0.5936 loss_thr: 0.4047 loss_db: 0.1006 2022/10/26 07:10:00 - mmengine - INFO - Epoch(train) [955][45/63] lr: 8.4683e-04 eta: 2:56:51 time: 0.5039 data_time: 0.0081 memory: 16131 loss: 0.9533 loss_prob: 0.5034 loss_thr: 0.3641 loss_db: 0.0859 2022/10/26 07:10:02 - mmengine - INFO - Epoch(train) [955][50/63] lr: 8.4683e-04 eta: 2:56:43 time: 0.5081 data_time: 0.0236 memory: 16131 loss: 0.9628 loss_prob: 0.5166 loss_thr: 0.3535 loss_db: 0.0926 2022/10/26 07:10:05 - mmengine - INFO - Epoch(train) [955][55/63] lr: 8.4683e-04 eta: 2:56:43 time: 0.5441 data_time: 0.0242 memory: 16131 loss: 1.0306 loss_prob: 0.5538 loss_thr: 0.3788 loss_db: 0.0980 2022/10/26 07:10:08 - mmengine - INFO - Epoch(train) [955][60/63] lr: 8.4683e-04 eta: 2:56:36 time: 0.5919 data_time: 0.0062 memory: 16131 loss: 1.0003 loss_prob: 0.5240 loss_thr: 0.3867 loss_db: 0.0896 2022/10/26 07:10:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:10:15 - mmengine - INFO - Epoch(train) [956][5/63] lr: 8.4372e-04 eta: 2:56:36 time: 0.8109 data_time: 0.2677 memory: 16131 loss: 0.9723 loss_prob: 0.5121 loss_thr: 0.3721 loss_db: 0.0881 2022/10/26 07:10:17 - mmengine - INFO - Epoch(train) [956][10/63] lr: 8.4372e-04 eta: 2:56:27 time: 0.7921 data_time: 0.2669 memory: 16131 loss: 0.9990 loss_prob: 0.5196 loss_thr: 0.3887 loss_db: 0.0907 2022/10/26 07:10:20 - mmengine - INFO - Epoch(train) [956][15/63] lr: 8.4372e-04 eta: 2:56:27 time: 0.5165 data_time: 0.0066 memory: 16131 loss: 0.9476 loss_prob: 0.4910 loss_thr: 0.3704 loss_db: 0.0862 2022/10/26 07:10:23 - mmengine - INFO - Epoch(train) [956][20/63] lr: 8.4372e-04 eta: 2:56:20 time: 0.5048 data_time: 0.0062 memory: 16131 loss: 0.9583 loss_prob: 0.5065 loss_thr: 0.3632 loss_db: 0.0885 2022/10/26 07:10:25 - mmengine - INFO - Epoch(train) [956][25/63] lr: 8.4372e-04 eta: 2:56:20 time: 0.5388 data_time: 0.0215 memory: 16131 loss: 1.0594 loss_prob: 0.5676 loss_thr: 0.3961 loss_db: 0.0957 2022/10/26 07:10:28 - mmengine - INFO - Epoch(train) [956][30/63] lr: 8.4372e-04 eta: 2:56:13 time: 0.5557 data_time: 0.0361 memory: 16131 loss: 1.0529 loss_prob: 0.5631 loss_thr: 0.3935 loss_db: 0.0963 2022/10/26 07:10:31 - mmengine - INFO - Epoch(train) [956][35/63] lr: 8.4372e-04 eta: 2:56:13 time: 0.5083 data_time: 0.0266 memory: 16131 loss: 0.9711 loss_prob: 0.5139 loss_thr: 0.3665 loss_db: 0.0907 2022/10/26 07:10:34 - mmengine - INFO - Epoch(train) [956][40/63] lr: 8.4372e-04 eta: 2:56:05 time: 0.5569 data_time: 0.0114 memory: 16131 loss: 0.9698 loss_prob: 0.5116 loss_thr: 0.3705 loss_db: 0.0878 2022/10/26 07:10:36 - mmengine - INFO - Epoch(train) [956][45/63] lr: 8.4372e-04 eta: 2:56:05 time: 0.5593 data_time: 0.0059 memory: 16131 loss: 1.0091 loss_prob: 0.5415 loss_thr: 0.3760 loss_db: 0.0916 2022/10/26 07:10:39 - mmengine - INFO - Epoch(train) [956][50/63] lr: 8.4372e-04 eta: 2:55:58 time: 0.5572 data_time: 0.0144 memory: 16131 loss: 0.9535 loss_prob: 0.5081 loss_thr: 0.3581 loss_db: 0.0873 2022/10/26 07:10:42 - mmengine - INFO - Epoch(train) [956][55/63] lr: 8.4372e-04 eta: 2:55:58 time: 0.5651 data_time: 0.0242 memory: 16131 loss: 0.8817 loss_prob: 0.4630 loss_thr: 0.3390 loss_db: 0.0796 2022/10/26 07:10:44 - mmengine - INFO - Epoch(train) [956][60/63] lr: 8.4372e-04 eta: 2:55:51 time: 0.5137 data_time: 0.0170 memory: 16131 loss: 0.8937 loss_prob: 0.4698 loss_thr: 0.3433 loss_db: 0.0806 2022/10/26 07:10:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:10:51 - mmengine - INFO - Epoch(train) [957][5/63] lr: 8.4061e-04 eta: 2:55:51 time: 0.7201 data_time: 0.2204 memory: 16131 loss: 0.8842 loss_prob: 0.4571 loss_thr: 0.3483 loss_db: 0.0789 2022/10/26 07:10:53 - mmengine - INFO - Epoch(train) [957][10/63] lr: 8.4061e-04 eta: 2:55:42 time: 0.7500 data_time: 0.2250 memory: 16131 loss: 0.9134 loss_prob: 0.4776 loss_thr: 0.3532 loss_db: 0.0826 2022/10/26 07:10:56 - mmengine - INFO - Epoch(train) [957][15/63] lr: 8.4061e-04 eta: 2:55:42 time: 0.5129 data_time: 0.0245 memory: 16131 loss: 0.9080 loss_prob: 0.4787 loss_thr: 0.3467 loss_db: 0.0826 2022/10/26 07:10:58 - mmengine - INFO - Epoch(train) [957][20/63] lr: 8.4061e-04 eta: 2:55:34 time: 0.5066 data_time: 0.0209 memory: 16131 loss: 0.9350 loss_prob: 0.4937 loss_thr: 0.3558 loss_db: 0.0854 2022/10/26 07:11:01 - mmengine - INFO - Epoch(train) [957][25/63] lr: 8.4061e-04 eta: 2:55:34 time: 0.4998 data_time: 0.0150 memory: 16131 loss: 0.9643 loss_prob: 0.5039 loss_thr: 0.3715 loss_db: 0.0889 2022/10/26 07:11:03 - mmengine - INFO - Epoch(train) [957][30/63] lr: 8.4061e-04 eta: 2:55:27 time: 0.5334 data_time: 0.0374 memory: 16131 loss: 0.9962 loss_prob: 0.5179 loss_thr: 0.3887 loss_db: 0.0897 2022/10/26 07:11:06 - mmengine - INFO - Epoch(train) [957][35/63] lr: 8.4061e-04 eta: 2:55:27 time: 0.5670 data_time: 0.0306 memory: 16131 loss: 1.0107 loss_prob: 0.5325 loss_thr: 0.3859 loss_db: 0.0923 2022/10/26 07:11:09 - mmengine - INFO - Epoch(train) [957][40/63] lr: 8.4061e-04 eta: 2:55:20 time: 0.5467 data_time: 0.0062 memory: 16131 loss: 0.9715 loss_prob: 0.5138 loss_thr: 0.3670 loss_db: 0.0907 2022/10/26 07:11:11 - mmengine - INFO - Epoch(train) [957][45/63] lr: 8.4061e-04 eta: 2:55:20 time: 0.4934 data_time: 0.0055 memory: 16131 loss: 0.9100 loss_prob: 0.4774 loss_thr: 0.3485 loss_db: 0.0840 2022/10/26 07:11:14 - mmengine - INFO - Epoch(train) [957][50/63] lr: 8.4061e-04 eta: 2:55:13 time: 0.4981 data_time: 0.0242 memory: 16131 loss: 0.9090 loss_prob: 0.4715 loss_thr: 0.3551 loss_db: 0.0823 2022/10/26 07:11:17 - mmengine - INFO - Epoch(train) [957][55/63] lr: 8.4061e-04 eta: 2:55:13 time: 0.5164 data_time: 0.0243 memory: 16131 loss: 0.9562 loss_prob: 0.5091 loss_thr: 0.3637 loss_db: 0.0834 2022/10/26 07:11:19 - mmengine - INFO - Epoch(train) [957][60/63] lr: 8.4061e-04 eta: 2:55:05 time: 0.5165 data_time: 0.0054 memory: 16131 loss: 0.9666 loss_prob: 0.5166 loss_thr: 0.3647 loss_db: 0.0854 2022/10/26 07:11:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:11:25 - mmengine - INFO - Epoch(train) [958][5/63] lr: 8.3750e-04 eta: 2:55:05 time: 0.7195 data_time: 0.2093 memory: 16131 loss: 0.9548 loss_prob: 0.5013 loss_thr: 0.3664 loss_db: 0.0870 2022/10/26 07:11:28 - mmengine - INFO - Epoch(train) [958][10/63] lr: 8.3750e-04 eta: 2:54:56 time: 0.7507 data_time: 0.2108 memory: 16131 loss: 0.8979 loss_prob: 0.4662 loss_thr: 0.3510 loss_db: 0.0807 2022/10/26 07:11:30 - mmengine - INFO - Epoch(train) [958][15/63] lr: 8.3750e-04 eta: 2:54:56 time: 0.5241 data_time: 0.0110 memory: 16131 loss: 0.9073 loss_prob: 0.4717 loss_thr: 0.3536 loss_db: 0.0820 2022/10/26 07:11:33 - mmengine - INFO - Epoch(train) [958][20/63] lr: 8.3750e-04 eta: 2:54:49 time: 0.5129 data_time: 0.0128 memory: 16131 loss: 0.9439 loss_prob: 0.5017 loss_thr: 0.3582 loss_db: 0.0840 2022/10/26 07:11:36 - mmengine - INFO - Epoch(train) [958][25/63] lr: 8.3750e-04 eta: 2:54:49 time: 0.5455 data_time: 0.0395 memory: 16131 loss: 0.9041 loss_prob: 0.4742 loss_thr: 0.3516 loss_db: 0.0784 2022/10/26 07:11:38 - mmengine - INFO - Epoch(train) [958][30/63] lr: 8.3750e-04 eta: 2:54:41 time: 0.5364 data_time: 0.0363 memory: 16131 loss: 0.8571 loss_prob: 0.4433 loss_thr: 0.3368 loss_db: 0.0770 2022/10/26 07:11:42 - mmengine - INFO - Epoch(train) [958][35/63] lr: 8.3750e-04 eta: 2:54:41 time: 0.5747 data_time: 0.0074 memory: 16131 loss: 0.9162 loss_prob: 0.4867 loss_thr: 0.3443 loss_db: 0.0851 2022/10/26 07:11:45 - mmengine - INFO - Epoch(train) [958][40/63] lr: 8.3750e-04 eta: 2:54:34 time: 0.6201 data_time: 0.0074 memory: 16131 loss: 0.9666 loss_prob: 0.5027 loss_thr: 0.3769 loss_db: 0.0870 2022/10/26 07:11:47 - mmengine - INFO - Epoch(train) [958][45/63] lr: 8.3750e-04 eta: 2:54:34 time: 0.5334 data_time: 0.0073 memory: 16131 loss: 1.0382 loss_prob: 0.5468 loss_thr: 0.3988 loss_db: 0.0926 2022/10/26 07:11:50 - mmengine - INFO - Epoch(train) [958][50/63] lr: 8.3750e-04 eta: 2:54:27 time: 0.5131 data_time: 0.0240 memory: 16131 loss: 1.0767 loss_prob: 0.5862 loss_thr: 0.3908 loss_db: 0.0997 2022/10/26 07:11:52 - mmengine - INFO - Epoch(train) [958][55/63] lr: 8.3750e-04 eta: 2:54:27 time: 0.5402 data_time: 0.0220 memory: 16131 loss: 1.0697 loss_prob: 0.5727 loss_thr: 0.3990 loss_db: 0.0980 2022/10/26 07:11:55 - mmengine - INFO - Epoch(train) [958][60/63] lr: 8.3750e-04 eta: 2:54:20 time: 0.5454 data_time: 0.0060 memory: 16131 loss: 1.0099 loss_prob: 0.5336 loss_thr: 0.3848 loss_db: 0.0914 2022/10/26 07:11:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:12:01 - mmengine - INFO - Epoch(train) [959][5/63] lr: 8.3438e-04 eta: 2:54:20 time: 0.7025 data_time: 0.1733 memory: 16131 loss: 0.8330 loss_prob: 0.4344 loss_thr: 0.3229 loss_db: 0.0757 2022/10/26 07:12:04 - mmengine - INFO - Epoch(train) [959][10/63] lr: 8.3438e-04 eta: 2:54:11 time: 0.7383 data_time: 0.1744 memory: 16131 loss: 0.9233 loss_prob: 0.4832 loss_thr: 0.3557 loss_db: 0.0843 2022/10/26 07:12:07 - mmengine - INFO - Epoch(train) [959][15/63] lr: 8.3438e-04 eta: 2:54:11 time: 0.5460 data_time: 0.0108 memory: 16131 loss: 0.9860 loss_prob: 0.5218 loss_thr: 0.3749 loss_db: 0.0893 2022/10/26 07:12:09 - mmengine - INFO - Epoch(train) [959][20/63] lr: 8.3438e-04 eta: 2:54:03 time: 0.5097 data_time: 0.0103 memory: 16131 loss: 1.0131 loss_prob: 0.5496 loss_thr: 0.3708 loss_db: 0.0927 2022/10/26 07:12:12 - mmengine - INFO - Epoch(train) [959][25/63] lr: 8.3438e-04 eta: 2:54:03 time: 0.5182 data_time: 0.0205 memory: 16131 loss: 0.9994 loss_prob: 0.5325 loss_thr: 0.3763 loss_db: 0.0906 2022/10/26 07:12:15 - mmengine - INFO - Epoch(train) [959][30/63] lr: 8.3438e-04 eta: 2:53:56 time: 0.5439 data_time: 0.0325 memory: 16131 loss: 0.9718 loss_prob: 0.5045 loss_thr: 0.3800 loss_db: 0.0873 2022/10/26 07:12:17 - mmengine - INFO - Epoch(train) [959][35/63] lr: 8.3438e-04 eta: 2:53:56 time: 0.5225 data_time: 0.0193 memory: 16131 loss: 0.9242 loss_prob: 0.4793 loss_thr: 0.3617 loss_db: 0.0832 2022/10/26 07:12:19 - mmengine - INFO - Epoch(train) [959][40/63] lr: 8.3438e-04 eta: 2:53:49 time: 0.4971 data_time: 0.0070 memory: 16131 loss: 0.8841 loss_prob: 0.4566 loss_thr: 0.3475 loss_db: 0.0800 2022/10/26 07:12:22 - mmengine - INFO - Epoch(train) [959][45/63] lr: 8.3438e-04 eta: 2:53:49 time: 0.5171 data_time: 0.0075 memory: 16131 loss: 0.8928 loss_prob: 0.4623 loss_thr: 0.3492 loss_db: 0.0813 2022/10/26 07:12:25 - mmengine - INFO - Epoch(train) [959][50/63] lr: 8.3438e-04 eta: 2:53:42 time: 0.5489 data_time: 0.0201 memory: 16131 loss: 0.9115 loss_prob: 0.4726 loss_thr: 0.3566 loss_db: 0.0822 2022/10/26 07:12:28 - mmengine - INFO - Epoch(train) [959][55/63] lr: 8.3438e-04 eta: 2:53:42 time: 0.5702 data_time: 0.0227 memory: 16131 loss: 0.9769 loss_prob: 0.5116 loss_thr: 0.3754 loss_db: 0.0899 2022/10/26 07:12:30 - mmengine - INFO - Epoch(train) [959][60/63] lr: 8.3438e-04 eta: 2:53:34 time: 0.5380 data_time: 0.0165 memory: 16131 loss: 1.0363 loss_prob: 0.5541 loss_thr: 0.3858 loss_db: 0.0965 2022/10/26 07:12:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:12:36 - mmengine - INFO - Epoch(train) [960][5/63] lr: 8.3127e-04 eta: 2:53:34 time: 0.6511 data_time: 0.1833 memory: 16131 loss: 1.0033 loss_prob: 0.5329 loss_thr: 0.3788 loss_db: 0.0916 2022/10/26 07:12:39 - mmengine - INFO - Epoch(train) [960][10/63] lr: 8.3127e-04 eta: 2:53:25 time: 0.6932 data_time: 0.1822 memory: 16131 loss: 1.0025 loss_prob: 0.5320 loss_thr: 0.3816 loss_db: 0.0889 2022/10/26 07:12:41 - mmengine - INFO - Epoch(train) [960][15/63] lr: 8.3127e-04 eta: 2:53:25 time: 0.5334 data_time: 0.0108 memory: 16131 loss: 1.0013 loss_prob: 0.5421 loss_thr: 0.3672 loss_db: 0.0920 2022/10/26 07:12:44 - mmengine - INFO - Epoch(train) [960][20/63] lr: 8.3127e-04 eta: 2:53:18 time: 0.5132 data_time: 0.0104 memory: 16131 loss: 0.9122 loss_prob: 0.4910 loss_thr: 0.3374 loss_db: 0.0838 2022/10/26 07:12:46 - mmengine - INFO - Epoch(train) [960][25/63] lr: 8.3127e-04 eta: 2:53:18 time: 0.5029 data_time: 0.0146 memory: 16131 loss: 0.9646 loss_prob: 0.5164 loss_thr: 0.3624 loss_db: 0.0858 2022/10/26 07:12:49 - mmengine - INFO - Epoch(train) [960][30/63] lr: 8.3127e-04 eta: 2:53:10 time: 0.5329 data_time: 0.0332 memory: 16131 loss: 0.9428 loss_prob: 0.4939 loss_thr: 0.3632 loss_db: 0.0856 2022/10/26 07:12:52 - mmengine - INFO - Epoch(train) [960][35/63] lr: 8.3127e-04 eta: 2:53:10 time: 0.5254 data_time: 0.0255 memory: 16131 loss: 0.9564 loss_prob: 0.4869 loss_thr: 0.3846 loss_db: 0.0849 2022/10/26 07:12:54 - mmengine - INFO - Epoch(train) [960][40/63] lr: 8.3127e-04 eta: 2:53:03 time: 0.4972 data_time: 0.0090 memory: 16131 loss: 1.1529 loss_prob: 0.6042 loss_thr: 0.4461 loss_db: 0.1026 2022/10/26 07:12:56 - mmengine - INFO - Epoch(train) [960][45/63] lr: 8.3127e-04 eta: 2:53:03 time: 0.4919 data_time: 0.0092 memory: 16131 loss: 1.1159 loss_prob: 0.5995 loss_thr: 0.4163 loss_db: 0.1001 2022/10/26 07:12:59 - mmengine - INFO - Epoch(train) [960][50/63] lr: 8.3127e-04 eta: 2:52:56 time: 0.5032 data_time: 0.0137 memory: 16131 loss: 0.9728 loss_prob: 0.5096 loss_thr: 0.3771 loss_db: 0.0861 2022/10/26 07:13:02 - mmengine - INFO - Epoch(train) [960][55/63] lr: 8.3127e-04 eta: 2:52:56 time: 0.5161 data_time: 0.0210 memory: 16131 loss: 0.9755 loss_prob: 0.5096 loss_thr: 0.3763 loss_db: 0.0896 2022/10/26 07:13:04 - mmengine - INFO - Epoch(train) [960][60/63] lr: 8.3127e-04 eta: 2:52:48 time: 0.5091 data_time: 0.0159 memory: 16131 loss: 0.9267 loss_prob: 0.4884 loss_thr: 0.3520 loss_db: 0.0863 2022/10/26 07:13:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:13:05 - mmengine - INFO - Saving checkpoint at 960 epochs 2022/10/26 07:13:12 - mmengine - INFO - Epoch(val) [960][5/32] eta: 2:52:48 time: 0.5105 data_time: 0.0632 memory: 16131 2022/10/26 07:13:15 - mmengine - INFO - Epoch(val) [960][10/32] eta: 0:00:13 time: 0.6126 data_time: 0.1111 memory: 15724 2022/10/26 07:13:18 - mmengine - INFO - Epoch(val) [960][15/32] eta: 0:00:13 time: 0.5717 data_time: 0.0696 memory: 15724 2022/10/26 07:13:20 - mmengine - INFO - Epoch(val) [960][20/32] eta: 0:00:06 time: 0.5420 data_time: 0.0513 memory: 15724 2022/10/26 07:13:23 - mmengine - INFO - Epoch(val) [960][25/32] eta: 0:00:06 time: 0.5590 data_time: 0.0588 memory: 15724 2022/10/26 07:13:26 - mmengine - INFO - Epoch(val) [960][30/32] eta: 0:00:01 time: 0.5208 data_time: 0.0301 memory: 15724 2022/10/26 07:13:26 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8377, precision: 0.7526, hmean: 0.7929 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8377, precision: 0.8033, hmean: 0.8202 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8373, precision: 0.8305, hmean: 0.8339 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8353, precision: 0.8593, hmean: 0.8472 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8175, precision: 0.8835, hmean: 0.8492 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7386, precision: 0.9308, hmean: 0.8236 2022/10/26 07:13:26 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1570, precision: 0.9879, hmean: 0.2709 2022/10/26 07:13:26 - mmengine - INFO - Epoch(val) [960][32/32] icdar/precision: 0.8835 icdar/recall: 0.8175 icdar/hmean: 0.8492 2022/10/26 07:13:31 - mmengine - INFO - Epoch(train) [961][5/63] lr: 8.2815e-04 eta: 0:00:01 time: 0.6835 data_time: 0.2055 memory: 16131 loss: 0.9315 loss_prob: 0.4908 loss_thr: 0.3564 loss_db: 0.0844 2022/10/26 07:13:34 - mmengine - INFO - Epoch(train) [961][10/63] lr: 8.2815e-04 eta: 2:52:39 time: 0.7535 data_time: 0.2089 memory: 16131 loss: 0.9836 loss_prob: 0.5135 loss_thr: 0.3825 loss_db: 0.0876 2022/10/26 07:13:37 - mmengine - INFO - Epoch(train) [961][15/63] lr: 8.2815e-04 eta: 2:52:39 time: 0.6003 data_time: 0.0116 memory: 16131 loss: 0.9579 loss_prob: 0.4934 loss_thr: 0.3771 loss_db: 0.0873 2022/10/26 07:13:40 - mmengine - INFO - Epoch(train) [961][20/63] lr: 8.2815e-04 eta: 2:52:32 time: 0.5686 data_time: 0.0054 memory: 16131 loss: 0.9332 loss_prob: 0.4814 loss_thr: 0.3654 loss_db: 0.0865 2022/10/26 07:13:42 - mmengine - INFO - Epoch(train) [961][25/63] lr: 8.2815e-04 eta: 2:52:32 time: 0.5245 data_time: 0.0178 memory: 16131 loss: 0.9936 loss_prob: 0.5155 loss_thr: 0.3909 loss_db: 0.0871 2022/10/26 07:13:45 - mmengine - INFO - Epoch(train) [961][30/63] lr: 8.2815e-04 eta: 2:52:25 time: 0.5271 data_time: 0.0345 memory: 16131 loss: 1.0611 loss_prob: 0.5680 loss_thr: 0.3978 loss_db: 0.0954 2022/10/26 07:13:48 - mmengine - INFO - Epoch(train) [961][35/63] lr: 8.2815e-04 eta: 2:52:25 time: 0.5393 data_time: 0.0250 memory: 16131 loss: 0.9968 loss_prob: 0.5357 loss_thr: 0.3685 loss_db: 0.0925 2022/10/26 07:13:50 - mmengine - INFO - Epoch(train) [961][40/63] lr: 8.2815e-04 eta: 2:52:18 time: 0.5603 data_time: 0.0110 memory: 16131 loss: 0.9098 loss_prob: 0.4729 loss_thr: 0.3545 loss_db: 0.0825 2022/10/26 07:13:53 - mmengine - INFO - Epoch(train) [961][45/63] lr: 8.2815e-04 eta: 2:52:18 time: 0.5424 data_time: 0.0114 memory: 16131 loss: 0.9128 loss_prob: 0.4714 loss_thr: 0.3591 loss_db: 0.0823 2022/10/26 07:13:56 - mmengine - INFO - Epoch(train) [961][50/63] lr: 8.2815e-04 eta: 2:52:10 time: 0.5325 data_time: 0.0223 memory: 16131 loss: 0.8923 loss_prob: 0.4596 loss_thr: 0.3529 loss_db: 0.0798 2022/10/26 07:13:58 - mmengine - INFO - Epoch(train) [961][55/63] lr: 8.2815e-04 eta: 2:52:10 time: 0.5332 data_time: 0.0276 memory: 16131 loss: 0.9183 loss_prob: 0.4763 loss_thr: 0.3575 loss_db: 0.0845 2022/10/26 07:14:01 - mmengine - INFO - Epoch(train) [961][60/63] lr: 8.2815e-04 eta: 2:52:03 time: 0.5165 data_time: 0.0156 memory: 16131 loss: 0.9187 loss_prob: 0.4811 loss_thr: 0.3525 loss_db: 0.0851 2022/10/26 07:14:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:14:08 - mmengine - INFO - Epoch(train) [962][5/63] lr: 8.2503e-04 eta: 2:52:03 time: 0.7617 data_time: 0.1741 memory: 16131 loss: 1.0000 loss_prob: 0.5263 loss_thr: 0.3846 loss_db: 0.0891 2022/10/26 07:14:10 - mmengine - INFO - Epoch(train) [962][10/63] lr: 8.2503e-04 eta: 2:51:54 time: 0.7689 data_time: 0.1689 memory: 16131 loss: 0.9866 loss_prob: 0.5163 loss_thr: 0.3818 loss_db: 0.0885 2022/10/26 07:14:13 - mmengine - INFO - Epoch(train) [962][15/63] lr: 8.2503e-04 eta: 2:51:54 time: 0.5046 data_time: 0.0065 memory: 16131 loss: 0.9807 loss_prob: 0.5133 loss_thr: 0.3779 loss_db: 0.0895 2022/10/26 07:14:15 - mmengine - INFO - Epoch(train) [962][20/63] lr: 8.2503e-04 eta: 2:51:47 time: 0.5016 data_time: 0.0066 memory: 16131 loss: 0.9727 loss_prob: 0.5093 loss_thr: 0.3752 loss_db: 0.0881 2022/10/26 07:14:18 - mmengine - INFO - Epoch(train) [962][25/63] lr: 8.2503e-04 eta: 2:51:47 time: 0.5032 data_time: 0.0204 memory: 16131 loss: 0.9610 loss_prob: 0.5055 loss_thr: 0.3683 loss_db: 0.0872 2022/10/26 07:14:20 - mmengine - INFO - Epoch(train) [962][30/63] lr: 8.2503e-04 eta: 2:51:39 time: 0.5207 data_time: 0.0349 memory: 16131 loss: 0.9391 loss_prob: 0.4874 loss_thr: 0.3662 loss_db: 0.0855 2022/10/26 07:14:23 - mmengine - INFO - Epoch(train) [962][35/63] lr: 8.2503e-04 eta: 2:51:39 time: 0.5388 data_time: 0.0198 memory: 16131 loss: 0.9253 loss_prob: 0.4733 loss_thr: 0.3682 loss_db: 0.0837 2022/10/26 07:14:25 - mmengine - INFO - Epoch(train) [962][40/63] lr: 8.2503e-04 eta: 2:51:32 time: 0.5101 data_time: 0.0049 memory: 16131 loss: 0.9664 loss_prob: 0.4955 loss_thr: 0.3838 loss_db: 0.0871 2022/10/26 07:14:28 - mmengine - INFO - Epoch(train) [962][45/63] lr: 8.2503e-04 eta: 2:51:32 time: 0.4999 data_time: 0.0051 memory: 16131 loss: 0.9947 loss_prob: 0.5159 loss_thr: 0.3885 loss_db: 0.0903 2022/10/26 07:14:31 - mmengine - INFO - Epoch(train) [962][50/63] lr: 8.2503e-04 eta: 2:51:25 time: 0.5653 data_time: 0.0244 memory: 16131 loss: 0.9477 loss_prob: 0.4952 loss_thr: 0.3678 loss_db: 0.0847 2022/10/26 07:14:34 - mmengine - INFO - Epoch(train) [962][55/63] lr: 8.2503e-04 eta: 2:51:25 time: 0.5553 data_time: 0.0289 memory: 16131 loss: 0.9225 loss_prob: 0.4734 loss_thr: 0.3681 loss_db: 0.0810 2022/10/26 07:14:36 - mmengine - INFO - Epoch(train) [962][60/63] lr: 8.2503e-04 eta: 2:51:18 time: 0.5015 data_time: 0.0094 memory: 16131 loss: 0.9527 loss_prob: 0.4923 loss_thr: 0.3732 loss_db: 0.0872 2022/10/26 07:14:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:14:42 - mmengine - INFO - Epoch(train) [963][5/63] lr: 8.2191e-04 eta: 2:51:18 time: 0.6769 data_time: 0.1661 memory: 16131 loss: 1.0108 loss_prob: 0.5323 loss_thr: 0.3885 loss_db: 0.0901 2022/10/26 07:14:45 - mmengine - INFO - Epoch(train) [963][10/63] lr: 8.2191e-04 eta: 2:51:08 time: 0.7118 data_time: 0.1750 memory: 16131 loss: 1.0394 loss_prob: 0.5561 loss_thr: 0.3876 loss_db: 0.0958 2022/10/26 07:14:47 - mmengine - INFO - Epoch(train) [963][15/63] lr: 8.2191e-04 eta: 2:51:08 time: 0.5483 data_time: 0.0138 memory: 16131 loss: 0.9930 loss_prob: 0.5321 loss_thr: 0.3689 loss_db: 0.0920 2022/10/26 07:14:50 - mmengine - INFO - Epoch(train) [963][20/63] lr: 8.2191e-04 eta: 2:51:01 time: 0.5173 data_time: 0.0057 memory: 16131 loss: 0.9737 loss_prob: 0.5206 loss_thr: 0.3631 loss_db: 0.0900 2022/10/26 07:14:52 - mmengine - INFO - Epoch(train) [963][25/63] lr: 8.2191e-04 eta: 2:51:01 time: 0.4984 data_time: 0.0160 memory: 16131 loss: 1.2365 loss_prob: 0.7322 loss_thr: 0.3948 loss_db: 0.1095 2022/10/26 07:14:55 - mmengine - INFO - Epoch(train) [963][30/63] lr: 8.2191e-04 eta: 2:50:54 time: 0.5074 data_time: 0.0264 memory: 16131 loss: 1.2078 loss_prob: 0.7085 loss_thr: 0.3932 loss_db: 0.1061 2022/10/26 07:14:58 - mmengine - INFO - Epoch(train) [963][35/63] lr: 8.2191e-04 eta: 2:50:54 time: 0.5439 data_time: 0.0511 memory: 16131 loss: 0.9209 loss_prob: 0.4722 loss_thr: 0.3637 loss_db: 0.0850 2022/10/26 07:15:00 - mmengine - INFO - Epoch(train) [963][40/63] lr: 8.2191e-04 eta: 2:50:46 time: 0.5610 data_time: 0.0394 memory: 16131 loss: 0.9861 loss_prob: 0.5253 loss_thr: 0.3723 loss_db: 0.0885 2022/10/26 07:15:03 - mmengine - INFO - Epoch(train) [963][45/63] lr: 8.2191e-04 eta: 2:50:46 time: 0.5449 data_time: 0.0051 memory: 16131 loss: 1.0530 loss_prob: 0.5645 loss_thr: 0.3944 loss_db: 0.0941 2022/10/26 07:15:06 - mmengine - INFO - Epoch(train) [963][50/63] lr: 8.2191e-04 eta: 2:50:39 time: 0.5200 data_time: 0.0135 memory: 16131 loss: 1.0227 loss_prob: 0.5402 loss_thr: 0.3880 loss_db: 0.0946 2022/10/26 07:15:09 - mmengine - INFO - Epoch(train) [963][55/63] lr: 8.2191e-04 eta: 2:50:39 time: 0.5488 data_time: 0.0310 memory: 16131 loss: 0.9737 loss_prob: 0.5144 loss_thr: 0.3706 loss_db: 0.0888 2022/10/26 07:15:12 - mmengine - INFO - Epoch(train) [963][60/63] lr: 8.2191e-04 eta: 2:50:32 time: 0.6164 data_time: 0.0230 memory: 16131 loss: 0.9518 loss_prob: 0.4910 loss_thr: 0.3765 loss_db: 0.0843 2022/10/26 07:15:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:15:18 - mmengine - INFO - Epoch(train) [964][5/63] lr: 8.1879e-04 eta: 2:50:32 time: 0.7182 data_time: 0.1693 memory: 16131 loss: 0.9079 loss_prob: 0.4676 loss_thr: 0.3576 loss_db: 0.0827 2022/10/26 07:15:20 - mmengine - INFO - Epoch(train) [964][10/63] lr: 8.1879e-04 eta: 2:50:23 time: 0.6994 data_time: 0.1690 memory: 16131 loss: 0.9522 loss_prob: 0.4955 loss_thr: 0.3695 loss_db: 0.0872 2022/10/26 07:15:23 - mmengine - INFO - Epoch(train) [964][15/63] lr: 8.1879e-04 eta: 2:50:23 time: 0.4942 data_time: 0.0074 memory: 16131 loss: 1.0196 loss_prob: 0.5395 loss_thr: 0.3872 loss_db: 0.0929 2022/10/26 07:15:25 - mmengine - INFO - Epoch(train) [964][20/63] lr: 8.1879e-04 eta: 2:50:16 time: 0.5049 data_time: 0.0096 memory: 16131 loss: 1.0207 loss_prob: 0.5517 loss_thr: 0.3772 loss_db: 0.0917 2022/10/26 07:15:28 - mmengine - INFO - Epoch(train) [964][25/63] lr: 8.1879e-04 eta: 2:50:16 time: 0.5443 data_time: 0.0217 memory: 16131 loss: 1.0229 loss_prob: 0.5500 loss_thr: 0.3810 loss_db: 0.0918 2022/10/26 07:15:31 - mmengine - INFO - Epoch(train) [964][30/63] lr: 8.1879e-04 eta: 2:50:08 time: 0.5538 data_time: 0.0303 memory: 16131 loss: 1.0189 loss_prob: 0.5438 loss_thr: 0.3809 loss_db: 0.0942 2022/10/26 07:15:34 - mmengine - INFO - Epoch(train) [964][35/63] lr: 8.1879e-04 eta: 2:50:08 time: 0.5438 data_time: 0.0174 memory: 16131 loss: 0.9837 loss_prob: 0.5284 loss_thr: 0.3654 loss_db: 0.0899 2022/10/26 07:15:36 - mmengine - INFO - Epoch(train) [964][40/63] lr: 8.1879e-04 eta: 2:50:01 time: 0.5326 data_time: 0.0070 memory: 16131 loss: 0.9862 loss_prob: 0.5187 loss_thr: 0.3775 loss_db: 0.0900 2022/10/26 07:15:39 - mmengine - INFO - Epoch(train) [964][45/63] lr: 8.1879e-04 eta: 2:50:01 time: 0.5059 data_time: 0.0083 memory: 16131 loss: 0.9555 loss_prob: 0.4964 loss_thr: 0.3713 loss_db: 0.0878 2022/10/26 07:15:41 - mmengine - INFO - Epoch(train) [964][50/63] lr: 8.1879e-04 eta: 2:49:54 time: 0.5230 data_time: 0.0164 memory: 16131 loss: 0.8934 loss_prob: 0.4620 loss_thr: 0.3519 loss_db: 0.0795 2022/10/26 07:15:45 - mmengine - INFO - Epoch(train) [964][55/63] lr: 8.1879e-04 eta: 2:49:54 time: 0.6140 data_time: 0.0215 memory: 16131 loss: 0.9557 loss_prob: 0.5033 loss_thr: 0.3659 loss_db: 0.0865 2022/10/26 07:15:47 - mmengine - INFO - Epoch(train) [964][60/63] lr: 8.1879e-04 eta: 2:49:47 time: 0.5827 data_time: 0.0122 memory: 16131 loss: 0.9984 loss_prob: 0.5362 loss_thr: 0.3697 loss_db: 0.0925 2022/10/26 07:15:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:15:53 - mmengine - INFO - Epoch(train) [965][5/63] lr: 8.1567e-04 eta: 2:49:47 time: 0.6871 data_time: 0.2080 memory: 16131 loss: 0.9434 loss_prob: 0.4974 loss_thr: 0.3600 loss_db: 0.0860 2022/10/26 07:15:56 - mmengine - INFO - Epoch(train) [965][10/63] lr: 8.1567e-04 eta: 2:49:38 time: 0.7400 data_time: 0.2068 memory: 16131 loss: 0.9407 loss_prob: 0.5015 loss_thr: 0.3535 loss_db: 0.0857 2022/10/26 07:15:59 - mmengine - INFO - Epoch(train) [965][15/63] lr: 8.1567e-04 eta: 2:49:38 time: 0.5398 data_time: 0.0072 memory: 16131 loss: 0.9691 loss_prob: 0.5071 loss_thr: 0.3738 loss_db: 0.0882 2022/10/26 07:16:01 - mmengine - INFO - Epoch(train) [965][20/63] lr: 8.1567e-04 eta: 2:49:30 time: 0.5262 data_time: 0.0105 memory: 16131 loss: 1.0171 loss_prob: 0.5367 loss_thr: 0.3855 loss_db: 0.0948 2022/10/26 07:16:04 - mmengine - INFO - Epoch(train) [965][25/63] lr: 8.1567e-04 eta: 2:49:30 time: 0.5351 data_time: 0.0096 memory: 16131 loss: 0.9613 loss_prob: 0.5106 loss_thr: 0.3600 loss_db: 0.0908 2022/10/26 07:16:07 - mmengine - INFO - Epoch(train) [965][30/63] lr: 8.1567e-04 eta: 2:49:23 time: 0.5912 data_time: 0.0245 memory: 16131 loss: 0.9621 loss_prob: 0.5074 loss_thr: 0.3665 loss_db: 0.0882 2022/10/26 07:16:10 - mmengine - INFO - Epoch(train) [965][35/63] lr: 8.1567e-04 eta: 2:49:23 time: 0.5628 data_time: 0.0286 memory: 16131 loss: 0.9623 loss_prob: 0.5061 loss_thr: 0.3671 loss_db: 0.0891 2022/10/26 07:16:12 - mmengine - INFO - Epoch(train) [965][40/63] lr: 8.1567e-04 eta: 2:49:16 time: 0.4917 data_time: 0.0101 memory: 16131 loss: 0.9737 loss_prob: 0.5179 loss_thr: 0.3657 loss_db: 0.0901 2022/10/26 07:16:15 - mmengine - INFO - Epoch(train) [965][45/63] lr: 8.1567e-04 eta: 2:49:16 time: 0.5153 data_time: 0.0065 memory: 16131 loss: 1.0102 loss_prob: 0.5399 loss_thr: 0.3786 loss_db: 0.0917 2022/10/26 07:16:17 - mmengine - INFO - Epoch(train) [965][50/63] lr: 8.1567e-04 eta: 2:49:09 time: 0.5470 data_time: 0.0238 memory: 16131 loss: 0.9609 loss_prob: 0.4996 loss_thr: 0.3752 loss_db: 0.0860 2022/10/26 07:16:20 - mmengine - INFO - Epoch(train) [965][55/63] lr: 8.1567e-04 eta: 2:49:09 time: 0.5193 data_time: 0.0226 memory: 16131 loss: 0.9391 loss_prob: 0.4846 loss_thr: 0.3713 loss_db: 0.0831 2022/10/26 07:16:22 - mmengine - INFO - Epoch(train) [965][60/63] lr: 8.1567e-04 eta: 2:49:01 time: 0.5025 data_time: 0.0080 memory: 16131 loss: 0.9820 loss_prob: 0.5177 loss_thr: 0.3762 loss_db: 0.0881 2022/10/26 07:16:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:16:29 - mmengine - INFO - Epoch(train) [966][5/63] lr: 8.1254e-04 eta: 2:49:01 time: 0.7279 data_time: 0.1885 memory: 16131 loss: 0.9864 loss_prob: 0.5241 loss_thr: 0.3697 loss_db: 0.0926 2022/10/26 07:16:31 - mmengine - INFO - Epoch(train) [966][10/63] lr: 8.1254e-04 eta: 2:48:52 time: 0.7198 data_time: 0.1939 memory: 16131 loss: 0.9297 loss_prob: 0.4879 loss_thr: 0.3557 loss_db: 0.0861 2022/10/26 07:16:34 - mmengine - INFO - Epoch(train) [966][15/63] lr: 8.1254e-04 eta: 2:48:52 time: 0.5367 data_time: 0.0155 memory: 16131 loss: 0.8887 loss_prob: 0.4563 loss_thr: 0.3540 loss_db: 0.0784 2022/10/26 07:16:37 - mmengine - INFO - Epoch(train) [966][20/63] lr: 8.1254e-04 eta: 2:48:45 time: 0.5373 data_time: 0.0070 memory: 16131 loss: 0.9832 loss_prob: 0.5184 loss_thr: 0.3769 loss_db: 0.0879 2022/10/26 07:16:39 - mmengine - INFO - Epoch(train) [966][25/63] lr: 8.1254e-04 eta: 2:48:45 time: 0.5321 data_time: 0.0093 memory: 16131 loss: 0.9520 loss_prob: 0.5120 loss_thr: 0.3539 loss_db: 0.0861 2022/10/26 07:16:42 - mmengine - INFO - Epoch(train) [966][30/63] lr: 8.1254e-04 eta: 2:48:38 time: 0.5370 data_time: 0.0331 memory: 16131 loss: 0.9728 loss_prob: 0.5184 loss_thr: 0.3647 loss_db: 0.0897 2022/10/26 07:16:45 - mmengine - INFO - Epoch(train) [966][35/63] lr: 8.1254e-04 eta: 2:48:38 time: 0.5357 data_time: 0.0303 memory: 16131 loss: 0.9933 loss_prob: 0.5344 loss_thr: 0.3633 loss_db: 0.0956 2022/10/26 07:16:47 - mmengine - INFO - Epoch(train) [966][40/63] lr: 8.1254e-04 eta: 2:48:30 time: 0.5284 data_time: 0.0061 memory: 16131 loss: 0.9045 loss_prob: 0.4822 loss_thr: 0.3358 loss_db: 0.0864 2022/10/26 07:16:50 - mmengine - INFO - Epoch(train) [966][45/63] lr: 8.1254e-04 eta: 2:48:30 time: 0.5448 data_time: 0.0084 memory: 16131 loss: 0.8766 loss_prob: 0.4566 loss_thr: 0.3394 loss_db: 0.0806 2022/10/26 07:16:53 - mmengine - INFO - Epoch(train) [966][50/63] lr: 8.1254e-04 eta: 2:48:23 time: 0.5950 data_time: 0.0246 memory: 16131 loss: 0.8492 loss_prob: 0.4415 loss_thr: 0.3301 loss_db: 0.0775 2022/10/26 07:16:56 - mmengine - INFO - Epoch(train) [966][55/63] lr: 8.1254e-04 eta: 2:48:23 time: 0.6027 data_time: 0.0252 memory: 16131 loss: 0.9745 loss_prob: 0.5183 loss_thr: 0.3687 loss_db: 0.0875 2022/10/26 07:16:59 - mmengine - INFO - Epoch(train) [966][60/63] lr: 8.1254e-04 eta: 2:48:16 time: 0.5609 data_time: 0.0097 memory: 16131 loss: 1.0724 loss_prob: 0.5734 loss_thr: 0.4041 loss_db: 0.0949 2022/10/26 07:17:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:17:04 - mmengine - INFO - Epoch(train) [967][5/63] lr: 8.0942e-04 eta: 2:48:16 time: 0.6209 data_time: 0.1392 memory: 16131 loss: 1.0216 loss_prob: 0.5498 loss_thr: 0.3782 loss_db: 0.0937 2022/10/26 07:17:07 - mmengine - INFO - Epoch(train) [967][10/63] lr: 8.0942e-04 eta: 2:48:07 time: 0.6653 data_time: 0.1562 memory: 16131 loss: 0.9436 loss_prob: 0.4900 loss_thr: 0.3697 loss_db: 0.0839 2022/10/26 07:17:09 - mmengine - INFO - Epoch(train) [967][15/63] lr: 8.0942e-04 eta: 2:48:07 time: 0.5232 data_time: 0.0350 memory: 16131 loss: 0.9554 loss_prob: 0.4934 loss_thr: 0.3758 loss_db: 0.0861 2022/10/26 07:17:12 - mmengine - INFO - Epoch(train) [967][20/63] lr: 8.0942e-04 eta: 2:47:59 time: 0.4901 data_time: 0.0183 memory: 16131 loss: 0.9326 loss_prob: 0.4815 loss_thr: 0.3660 loss_db: 0.0851 2022/10/26 07:17:14 - mmengine - INFO - Epoch(train) [967][25/63] lr: 8.0942e-04 eta: 2:47:59 time: 0.4844 data_time: 0.0092 memory: 16131 loss: 0.9353 loss_prob: 0.4873 loss_thr: 0.3627 loss_db: 0.0853 2022/10/26 07:17:16 - mmengine - INFO - Epoch(train) [967][30/63] lr: 8.0942e-04 eta: 2:47:52 time: 0.4845 data_time: 0.0112 memory: 16131 loss: 0.8705 loss_prob: 0.4510 loss_thr: 0.3409 loss_db: 0.0787 2022/10/26 07:17:21 - mmengine - INFO - Epoch(train) [967][35/63] lr: 8.0942e-04 eta: 2:47:52 time: 0.6788 data_time: 0.0318 memory: 16131 loss: 0.8304 loss_prob: 0.4302 loss_thr: 0.3266 loss_db: 0.0736 2022/10/26 07:17:23 - mmengine - INFO - Epoch(train) [967][40/63] lr: 8.0942e-04 eta: 2:47:45 time: 0.6905 data_time: 0.0297 memory: 16131 loss: 0.8599 loss_prob: 0.4498 loss_thr: 0.3334 loss_db: 0.0766 2022/10/26 07:17:26 - mmengine - INFO - Epoch(train) [967][45/63] lr: 8.0942e-04 eta: 2:47:45 time: 0.5067 data_time: 0.0057 memory: 16131 loss: 0.8989 loss_prob: 0.4692 loss_thr: 0.3476 loss_db: 0.0822 2022/10/26 07:17:28 - mmengine - INFO - Epoch(train) [967][50/63] lr: 8.0942e-04 eta: 2:47:38 time: 0.5215 data_time: 0.0077 memory: 16131 loss: 0.9587 loss_prob: 0.5034 loss_thr: 0.3671 loss_db: 0.0881 2022/10/26 07:17:31 - mmengine - INFO - Epoch(train) [967][55/63] lr: 8.0942e-04 eta: 2:47:38 time: 0.5054 data_time: 0.0078 memory: 16131 loss: 0.9256 loss_prob: 0.4799 loss_thr: 0.3604 loss_db: 0.0853 2022/10/26 07:17:34 - mmengine - INFO - Epoch(train) [967][60/63] lr: 8.0942e-04 eta: 2:47:31 time: 0.5172 data_time: 0.0148 memory: 16131 loss: 0.8735 loss_prob: 0.4499 loss_thr: 0.3453 loss_db: 0.0783 2022/10/26 07:17:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:17:40 - mmengine - INFO - Epoch(train) [968][5/63] lr: 8.0629e-04 eta: 2:47:31 time: 0.7905 data_time: 0.1721 memory: 16131 loss: 1.0506 loss_prob: 0.5794 loss_thr: 0.3717 loss_db: 0.0995 2022/10/26 07:17:43 - mmengine - INFO - Epoch(train) [968][10/63] lr: 8.0629e-04 eta: 2:47:22 time: 0.7899 data_time: 0.1708 memory: 16131 loss: 1.0434 loss_prob: 0.5722 loss_thr: 0.3731 loss_db: 0.0980 2022/10/26 07:17:46 - mmengine - INFO - Epoch(train) [968][15/63] lr: 8.0629e-04 eta: 2:47:22 time: 0.5116 data_time: 0.0094 memory: 16131 loss: 0.8876 loss_prob: 0.4619 loss_thr: 0.3443 loss_db: 0.0814 2022/10/26 07:17:48 - mmengine - INFO - Epoch(train) [968][20/63] lr: 8.0629e-04 eta: 2:47:14 time: 0.5343 data_time: 0.0112 memory: 16131 loss: 0.9320 loss_prob: 0.4836 loss_thr: 0.3628 loss_db: 0.0856 2022/10/26 07:17:51 - mmengine - INFO - Epoch(train) [968][25/63] lr: 8.0629e-04 eta: 2:47:14 time: 0.5305 data_time: 0.0180 memory: 16131 loss: 0.9622 loss_prob: 0.4974 loss_thr: 0.3783 loss_db: 0.0866 2022/10/26 07:17:54 - mmengine - INFO - Epoch(train) [968][30/63] lr: 8.0629e-04 eta: 2:47:07 time: 0.5418 data_time: 0.0314 memory: 16131 loss: 0.9269 loss_prob: 0.4823 loss_thr: 0.3608 loss_db: 0.0839 2022/10/26 07:17:56 - mmengine - INFO - Epoch(train) [968][35/63] lr: 8.0629e-04 eta: 2:47:07 time: 0.5541 data_time: 0.0254 memory: 16131 loss: 0.9019 loss_prob: 0.4671 loss_thr: 0.3530 loss_db: 0.0818 2022/10/26 07:17:59 - mmengine - INFO - Epoch(train) [968][40/63] lr: 8.0629e-04 eta: 2:47:00 time: 0.5361 data_time: 0.0098 memory: 16131 loss: 0.9314 loss_prob: 0.4826 loss_thr: 0.3644 loss_db: 0.0844 2022/10/26 07:18:01 - mmengine - INFO - Epoch(train) [968][45/63] lr: 8.0629e-04 eta: 2:47:00 time: 0.5052 data_time: 0.0057 memory: 16131 loss: 0.9609 loss_prob: 0.5138 loss_thr: 0.3566 loss_db: 0.0905 2022/10/26 07:18:04 - mmengine - INFO - Epoch(train) [968][50/63] lr: 8.0629e-04 eta: 2:46:53 time: 0.5011 data_time: 0.0150 memory: 16131 loss: 0.9676 loss_prob: 0.5179 loss_thr: 0.3583 loss_db: 0.0914 2022/10/26 07:18:07 - mmengine - INFO - Epoch(train) [968][55/63] lr: 8.0629e-04 eta: 2:46:53 time: 0.5140 data_time: 0.0204 memory: 16131 loss: 0.9900 loss_prob: 0.5251 loss_thr: 0.3733 loss_db: 0.0916 2022/10/26 07:18:09 - mmengine - INFO - Epoch(train) [968][60/63] lr: 8.0629e-04 eta: 2:46:46 time: 0.5148 data_time: 0.0184 memory: 16131 loss: 1.0099 loss_prob: 0.5412 loss_thr: 0.3770 loss_db: 0.0917 2022/10/26 07:18:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:18:15 - mmengine - INFO - Epoch(train) [969][5/63] lr: 8.0316e-04 eta: 2:46:46 time: 0.7161 data_time: 0.1700 memory: 16131 loss: 0.9921 loss_prob: 0.5209 loss_thr: 0.3797 loss_db: 0.0915 2022/10/26 07:18:18 - mmengine - INFO - Epoch(train) [969][10/63] lr: 8.0316e-04 eta: 2:46:36 time: 0.7252 data_time: 0.1732 memory: 16131 loss: 0.9939 loss_prob: 0.5247 loss_thr: 0.3761 loss_db: 0.0931 2022/10/26 07:18:20 - mmengine - INFO - Epoch(train) [969][15/63] lr: 8.0316e-04 eta: 2:46:36 time: 0.5216 data_time: 0.0139 memory: 16131 loss: 0.8741 loss_prob: 0.4494 loss_thr: 0.3447 loss_db: 0.0800 2022/10/26 07:18:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:18:23 - mmengine - INFO - Epoch(train) [969][20/63] lr: 8.0316e-04 eta: 2:46:29 time: 0.5429 data_time: 0.0057 memory: 16131 loss: 0.8464 loss_prob: 0.4298 loss_thr: 0.3415 loss_db: 0.0751 2022/10/26 07:18:26 - mmengine - INFO - Epoch(train) [969][25/63] lr: 8.0316e-04 eta: 2:46:29 time: 0.5194 data_time: 0.0083 memory: 16131 loss: 0.9214 loss_prob: 0.4817 loss_thr: 0.3561 loss_db: 0.0836 2022/10/26 07:18:29 - mmengine - INFO - Epoch(train) [969][30/63] lr: 8.0316e-04 eta: 2:46:22 time: 0.5646 data_time: 0.0448 memory: 16131 loss: 0.9291 loss_prob: 0.4829 loss_thr: 0.3629 loss_db: 0.0832 2022/10/26 07:18:32 - mmengine - INFO - Epoch(train) [969][35/63] lr: 8.0316e-04 eta: 2:46:22 time: 0.6220 data_time: 0.0493 memory: 16131 loss: 0.8650 loss_prob: 0.4476 loss_thr: 0.3399 loss_db: 0.0776 2022/10/26 07:18:34 - mmengine - INFO - Epoch(train) [969][40/63] lr: 8.0316e-04 eta: 2:46:15 time: 0.5551 data_time: 0.0133 memory: 16131 loss: 0.8640 loss_prob: 0.4398 loss_thr: 0.3457 loss_db: 0.0785 2022/10/26 07:18:38 - mmengine - INFO - Epoch(train) [969][45/63] lr: 8.0316e-04 eta: 2:46:15 time: 0.5622 data_time: 0.0097 memory: 16131 loss: 0.9550 loss_prob: 0.4954 loss_thr: 0.3703 loss_db: 0.0893 2022/10/26 07:18:40 - mmengine - INFO - Epoch(train) [969][50/63] lr: 8.0316e-04 eta: 2:46:08 time: 0.5646 data_time: 0.0192 memory: 16131 loss: 1.0269 loss_prob: 0.5458 loss_thr: 0.3864 loss_db: 0.0947 2022/10/26 07:18:43 - mmengine - INFO - Epoch(train) [969][55/63] lr: 8.0316e-04 eta: 2:46:08 time: 0.5187 data_time: 0.0226 memory: 16131 loss: 0.9964 loss_prob: 0.5183 loss_thr: 0.3891 loss_db: 0.0890 2022/10/26 07:18:45 - mmengine - INFO - Epoch(train) [969][60/63] lr: 8.0316e-04 eta: 2:46:00 time: 0.5188 data_time: 0.0165 memory: 16131 loss: 0.9480 loss_prob: 0.4920 loss_thr: 0.3707 loss_db: 0.0853 2022/10/26 07:18:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:18:51 - mmengine - INFO - Epoch(train) [970][5/63] lr: 8.0003e-04 eta: 2:46:00 time: 0.6850 data_time: 0.1727 memory: 16131 loss: 0.9027 loss_prob: 0.4728 loss_thr: 0.3464 loss_db: 0.0834 2022/10/26 07:18:54 - mmengine - INFO - Epoch(train) [970][10/63] lr: 8.0003e-04 eta: 2:45:51 time: 0.6949 data_time: 0.1719 memory: 16131 loss: 0.9269 loss_prob: 0.4824 loss_thr: 0.3619 loss_db: 0.0826 2022/10/26 07:18:56 - mmengine - INFO - Epoch(train) [970][15/63] lr: 8.0003e-04 eta: 2:45:51 time: 0.5107 data_time: 0.0137 memory: 16131 loss: 0.9133 loss_prob: 0.4678 loss_thr: 0.3661 loss_db: 0.0794 2022/10/26 07:18:59 - mmengine - INFO - Epoch(train) [970][20/63] lr: 8.0003e-04 eta: 2:45:44 time: 0.5238 data_time: 0.0107 memory: 16131 loss: 0.9312 loss_prob: 0.4809 loss_thr: 0.3664 loss_db: 0.0840 2022/10/26 07:19:02 - mmengine - INFO - Epoch(train) [970][25/63] lr: 8.0003e-04 eta: 2:45:44 time: 0.5433 data_time: 0.0131 memory: 16131 loss: 0.9452 loss_prob: 0.4937 loss_thr: 0.3640 loss_db: 0.0875 2022/10/26 07:19:04 - mmengine - INFO - Epoch(train) [970][30/63] lr: 8.0003e-04 eta: 2:45:37 time: 0.5337 data_time: 0.0295 memory: 16131 loss: 0.8784 loss_prob: 0.4556 loss_thr: 0.3419 loss_db: 0.0809 2022/10/26 07:19:07 - mmengine - INFO - Epoch(train) [970][35/63] lr: 8.0003e-04 eta: 2:45:37 time: 0.5123 data_time: 0.0242 memory: 16131 loss: 1.0030 loss_prob: 0.5322 loss_thr: 0.3803 loss_db: 0.0905 2022/10/26 07:19:09 - mmengine - INFO - Epoch(train) [970][40/63] lr: 8.0003e-04 eta: 2:45:29 time: 0.5155 data_time: 0.0082 memory: 16131 loss: 1.0866 loss_prob: 0.5805 loss_thr: 0.4076 loss_db: 0.0985 2022/10/26 07:19:12 - mmengine - INFO - Epoch(train) [970][45/63] lr: 8.0003e-04 eta: 2:45:29 time: 0.5289 data_time: 0.0102 memory: 16131 loss: 1.0120 loss_prob: 0.5316 loss_thr: 0.3888 loss_db: 0.0915 2022/10/26 07:19:15 - mmengine - INFO - Epoch(train) [970][50/63] lr: 8.0003e-04 eta: 2:45:22 time: 0.5435 data_time: 0.0135 memory: 16131 loss: 1.0040 loss_prob: 0.5251 loss_thr: 0.3885 loss_db: 0.0904 2022/10/26 07:19:17 - mmengine - INFO - Epoch(train) [970][55/63] lr: 8.0003e-04 eta: 2:45:22 time: 0.5431 data_time: 0.0208 memory: 16131 loss: 1.0119 loss_prob: 0.5360 loss_thr: 0.3814 loss_db: 0.0946 2022/10/26 07:19:20 - mmengine - INFO - Epoch(train) [970][60/63] lr: 8.0003e-04 eta: 2:45:15 time: 0.5244 data_time: 0.0159 memory: 16131 loss: 1.0478 loss_prob: 0.5660 loss_thr: 0.3828 loss_db: 0.0989 2022/10/26 07:19:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:19:27 - mmengine - INFO - Epoch(train) [971][5/63] lr: 7.9690e-04 eta: 2:45:15 time: 0.7706 data_time: 0.1757 memory: 16131 loss: 1.0927 loss_prob: 0.5887 loss_thr: 0.4015 loss_db: 0.1025 2022/10/26 07:19:29 - mmengine - INFO - Epoch(train) [971][10/63] lr: 7.9690e-04 eta: 2:45:06 time: 0.8019 data_time: 0.1791 memory: 16131 loss: 1.0835 loss_prob: 0.5893 loss_thr: 0.3944 loss_db: 0.0998 2022/10/26 07:19:32 - mmengine - INFO - Epoch(train) [971][15/63] lr: 7.9690e-04 eta: 2:45:06 time: 0.5463 data_time: 0.0133 memory: 16131 loss: 1.0244 loss_prob: 0.5602 loss_thr: 0.3706 loss_db: 0.0936 2022/10/26 07:19:34 - mmengine - INFO - Epoch(train) [971][20/63] lr: 7.9690e-04 eta: 2:44:59 time: 0.5067 data_time: 0.0090 memory: 16131 loss: 0.9537 loss_prob: 0.4974 loss_thr: 0.3700 loss_db: 0.0863 2022/10/26 07:19:37 - mmengine - INFO - Epoch(train) [971][25/63] lr: 7.9690e-04 eta: 2:44:59 time: 0.5176 data_time: 0.0212 memory: 16131 loss: 0.9000 loss_prob: 0.4637 loss_thr: 0.3536 loss_db: 0.0827 2022/10/26 07:19:40 - mmengine - INFO - Epoch(train) [971][30/63] lr: 7.9690e-04 eta: 2:44:51 time: 0.5505 data_time: 0.0337 memory: 16131 loss: 0.9036 loss_prob: 0.4738 loss_thr: 0.3461 loss_db: 0.0837 2022/10/26 07:19:43 - mmengine - INFO - Epoch(train) [971][35/63] lr: 7.9690e-04 eta: 2:44:51 time: 0.5439 data_time: 0.0228 memory: 16131 loss: 0.9517 loss_prob: 0.5017 loss_thr: 0.3633 loss_db: 0.0867 2022/10/26 07:19:46 - mmengine - INFO - Epoch(train) [971][40/63] lr: 7.9690e-04 eta: 2:44:44 time: 0.5547 data_time: 0.0088 memory: 16131 loss: 0.9553 loss_prob: 0.4989 loss_thr: 0.3717 loss_db: 0.0847 2022/10/26 07:19:48 - mmengine - INFO - Epoch(train) [971][45/63] lr: 7.9690e-04 eta: 2:44:44 time: 0.5352 data_time: 0.0074 memory: 16131 loss: 0.9201 loss_prob: 0.4775 loss_thr: 0.3611 loss_db: 0.0816 2022/10/26 07:19:51 - mmengine - INFO - Epoch(train) [971][50/63] lr: 7.9690e-04 eta: 2:44:37 time: 0.5475 data_time: 0.0274 memory: 16131 loss: 0.9143 loss_prob: 0.4755 loss_thr: 0.3567 loss_db: 0.0821 2022/10/26 07:19:54 - mmengine - INFO - Epoch(train) [971][55/63] lr: 7.9690e-04 eta: 2:44:37 time: 0.5575 data_time: 0.0297 memory: 16131 loss: 0.9598 loss_prob: 0.5112 loss_thr: 0.3608 loss_db: 0.0878 2022/10/26 07:19:56 - mmengine - INFO - Epoch(train) [971][60/63] lr: 7.9690e-04 eta: 2:44:30 time: 0.5120 data_time: 0.0098 memory: 16131 loss: 1.0149 loss_prob: 0.5396 loss_thr: 0.3822 loss_db: 0.0930 2022/10/26 07:19:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:20:02 - mmengine - INFO - Epoch(train) [972][5/63] lr: 7.9377e-04 eta: 2:44:30 time: 0.6785 data_time: 0.1888 memory: 16131 loss: 0.9404 loss_prob: 0.4885 loss_thr: 0.3675 loss_db: 0.0843 2022/10/26 07:20:05 - mmengine - INFO - Epoch(train) [972][10/63] lr: 7.9377e-04 eta: 2:44:21 time: 0.6995 data_time: 0.1879 memory: 16131 loss: 0.8893 loss_prob: 0.4584 loss_thr: 0.3510 loss_db: 0.0799 2022/10/26 07:20:07 - mmengine - INFO - Epoch(train) [972][15/63] lr: 7.9377e-04 eta: 2:44:21 time: 0.5098 data_time: 0.0111 memory: 16131 loss: 0.9077 loss_prob: 0.4711 loss_thr: 0.3544 loss_db: 0.0822 2022/10/26 07:20:10 - mmengine - INFO - Epoch(train) [972][20/63] lr: 7.9377e-04 eta: 2:44:13 time: 0.4982 data_time: 0.0140 memory: 16131 loss: 0.9484 loss_prob: 0.4895 loss_thr: 0.3736 loss_db: 0.0852 2022/10/26 07:20:13 - mmengine - INFO - Epoch(train) [972][25/63] lr: 7.9377e-04 eta: 2:44:13 time: 0.5628 data_time: 0.0399 memory: 16131 loss: 0.9550 loss_prob: 0.4933 loss_thr: 0.3766 loss_db: 0.0851 2022/10/26 07:20:16 - mmengine - INFO - Epoch(train) [972][30/63] lr: 7.9377e-04 eta: 2:44:06 time: 0.6179 data_time: 0.0357 memory: 16131 loss: 0.9569 loss_prob: 0.4996 loss_thr: 0.3715 loss_db: 0.0858 2022/10/26 07:20:18 - mmengine - INFO - Epoch(train) [972][35/63] lr: 7.9377e-04 eta: 2:44:06 time: 0.5488 data_time: 0.0087 memory: 16131 loss: 0.9397 loss_prob: 0.4953 loss_thr: 0.3590 loss_db: 0.0855 2022/10/26 07:20:21 - mmengine - INFO - Epoch(train) [972][40/63] lr: 7.9377e-04 eta: 2:43:59 time: 0.5105 data_time: 0.0126 memory: 16131 loss: 0.8933 loss_prob: 0.4678 loss_thr: 0.3433 loss_db: 0.0822 2022/10/26 07:20:23 - mmengine - INFO - Epoch(train) [972][45/63] lr: 7.9377e-04 eta: 2:43:59 time: 0.5193 data_time: 0.0097 memory: 16131 loss: 0.8880 loss_prob: 0.4594 loss_thr: 0.3495 loss_db: 0.0791 2022/10/26 07:20:26 - mmengine - INFO - Epoch(train) [972][50/63] lr: 7.9377e-04 eta: 2:43:52 time: 0.5185 data_time: 0.0217 memory: 16131 loss: 0.9901 loss_prob: 0.5360 loss_thr: 0.3612 loss_db: 0.0930 2022/10/26 07:20:29 - mmengine - INFO - Epoch(train) [972][55/63] lr: 7.9377e-04 eta: 2:43:52 time: 0.5274 data_time: 0.0244 memory: 16131 loss: 1.0210 loss_prob: 0.5501 loss_thr: 0.3732 loss_db: 0.0977 2022/10/26 07:20:31 - mmengine - INFO - Epoch(train) [972][60/63] lr: 7.9377e-04 eta: 2:43:45 time: 0.5332 data_time: 0.0097 memory: 16131 loss: 0.9408 loss_prob: 0.4826 loss_thr: 0.3729 loss_db: 0.0852 2022/10/26 07:20:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:20:37 - mmengine - INFO - Epoch(train) [973][5/63] lr: 7.9064e-04 eta: 2:43:45 time: 0.7060 data_time: 0.1903 memory: 16131 loss: 0.9005 loss_prob: 0.4699 loss_thr: 0.3494 loss_db: 0.0812 2022/10/26 07:20:40 - mmengine - INFO - Epoch(train) [973][10/63] lr: 7.9064e-04 eta: 2:43:35 time: 0.7278 data_time: 0.1898 memory: 16131 loss: 0.8972 loss_prob: 0.4792 loss_thr: 0.3402 loss_db: 0.0777 2022/10/26 07:20:43 - mmengine - INFO - Epoch(train) [973][15/63] lr: 7.9064e-04 eta: 2:43:35 time: 0.5424 data_time: 0.0095 memory: 16131 loss: 0.9118 loss_prob: 0.4825 loss_thr: 0.3482 loss_db: 0.0812 2022/10/26 07:20:45 - mmengine - INFO - Epoch(train) [973][20/63] lr: 7.9064e-04 eta: 2:43:28 time: 0.5184 data_time: 0.0078 memory: 16131 loss: 0.9205 loss_prob: 0.4804 loss_thr: 0.3564 loss_db: 0.0837 2022/10/26 07:20:48 - mmengine - INFO - Epoch(train) [973][25/63] lr: 7.9064e-04 eta: 2:43:28 time: 0.5131 data_time: 0.0295 memory: 16131 loss: 0.9252 loss_prob: 0.4858 loss_thr: 0.3561 loss_db: 0.0834 2022/10/26 07:20:50 - mmengine - INFO - Epoch(train) [973][30/63] lr: 7.9064e-04 eta: 2:43:21 time: 0.5037 data_time: 0.0294 memory: 16131 loss: 0.9221 loss_prob: 0.4872 loss_thr: 0.3494 loss_db: 0.0855 2022/10/26 07:20:53 - mmengine - INFO - Epoch(train) [973][35/63] lr: 7.9064e-04 eta: 2:43:21 time: 0.5021 data_time: 0.0053 memory: 16131 loss: 0.9056 loss_prob: 0.4818 loss_thr: 0.3402 loss_db: 0.0837 2022/10/26 07:20:56 - mmengine - INFO - Epoch(train) [973][40/63] lr: 7.9064e-04 eta: 2:43:14 time: 0.5602 data_time: 0.0089 memory: 16131 loss: 0.9322 loss_prob: 0.4784 loss_thr: 0.3716 loss_db: 0.0823 2022/10/26 07:20:58 - mmengine - INFO - Epoch(train) [973][45/63] lr: 7.9064e-04 eta: 2:43:14 time: 0.5427 data_time: 0.0099 memory: 16131 loss: 1.0037 loss_prob: 0.5184 loss_thr: 0.3951 loss_db: 0.0901 2022/10/26 07:21:01 - mmengine - INFO - Epoch(train) [973][50/63] lr: 7.9064e-04 eta: 2:43:06 time: 0.4996 data_time: 0.0212 memory: 16131 loss: 0.9701 loss_prob: 0.5060 loss_thr: 0.3754 loss_db: 0.0887 2022/10/26 07:21:03 - mmengine - INFO - Epoch(train) [973][55/63] lr: 7.9064e-04 eta: 2:43:06 time: 0.5105 data_time: 0.0205 memory: 16131 loss: 0.9816 loss_prob: 0.5207 loss_thr: 0.3710 loss_db: 0.0899 2022/10/26 07:21:06 - mmengine - INFO - Epoch(train) [973][60/63] lr: 7.9064e-04 eta: 2:42:59 time: 0.5359 data_time: 0.0096 memory: 16131 loss: 0.9773 loss_prob: 0.5197 loss_thr: 0.3686 loss_db: 0.0890 2022/10/26 07:21:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:21:12 - mmengine - INFO - Epoch(train) [974][5/63] lr: 7.8750e-04 eta: 2:42:59 time: 0.6993 data_time: 0.1897 memory: 16131 loss: 0.8906 loss_prob: 0.4632 loss_thr: 0.3464 loss_db: 0.0810 2022/10/26 07:21:15 - mmengine - INFO - Epoch(train) [974][10/63] lr: 7.8750e-04 eta: 2:42:50 time: 0.7344 data_time: 0.1895 memory: 16131 loss: 0.8671 loss_prob: 0.4467 loss_thr: 0.3414 loss_db: 0.0790 2022/10/26 07:21:17 - mmengine - INFO - Epoch(train) [974][15/63] lr: 7.8750e-04 eta: 2:42:50 time: 0.5170 data_time: 0.0073 memory: 16131 loss: 0.9279 loss_prob: 0.4824 loss_thr: 0.3611 loss_db: 0.0845 2022/10/26 07:21:20 - mmengine - INFO - Epoch(train) [974][20/63] lr: 7.8750e-04 eta: 2:42:43 time: 0.5222 data_time: 0.0066 memory: 16131 loss: 1.0108 loss_prob: 0.5292 loss_thr: 0.3883 loss_db: 0.0932 2022/10/26 07:21:23 - mmengine - INFO - Epoch(train) [974][25/63] lr: 7.8750e-04 eta: 2:42:43 time: 0.5391 data_time: 0.0218 memory: 16131 loss: 1.0211 loss_prob: 0.5438 loss_thr: 0.3848 loss_db: 0.0924 2022/10/26 07:21:26 - mmengine - INFO - Epoch(train) [974][30/63] lr: 7.8750e-04 eta: 2:42:36 time: 0.5707 data_time: 0.0304 memory: 16131 loss: 0.9883 loss_prob: 0.5300 loss_thr: 0.3724 loss_db: 0.0859 2022/10/26 07:21:29 - mmengine - INFO - Epoch(train) [974][35/63] lr: 7.8750e-04 eta: 2:42:36 time: 0.5929 data_time: 0.0174 memory: 16131 loss: 0.9728 loss_prob: 0.5108 loss_thr: 0.3757 loss_db: 0.0863 2022/10/26 07:21:31 - mmengine - INFO - Epoch(train) [974][40/63] lr: 7.8750e-04 eta: 2:42:29 time: 0.5529 data_time: 0.0144 memory: 16131 loss: 0.9742 loss_prob: 0.5156 loss_thr: 0.3702 loss_db: 0.0884 2022/10/26 07:21:34 - mmengine - INFO - Epoch(train) [974][45/63] lr: 7.8750e-04 eta: 2:42:29 time: 0.5211 data_time: 0.0151 memory: 16131 loss: 0.9426 loss_prob: 0.4942 loss_thr: 0.3645 loss_db: 0.0839 2022/10/26 07:21:37 - mmengine - INFO - Epoch(train) [974][50/63] lr: 7.8750e-04 eta: 2:42:21 time: 0.5693 data_time: 0.0237 memory: 16131 loss: 0.8907 loss_prob: 0.4561 loss_thr: 0.3541 loss_db: 0.0805 2022/10/26 07:21:40 - mmengine - INFO - Epoch(train) [974][55/63] lr: 7.8750e-04 eta: 2:42:21 time: 0.5945 data_time: 0.0243 memory: 16131 loss: 0.9976 loss_prob: 0.5266 loss_thr: 0.3805 loss_db: 0.0906 2022/10/26 07:21:42 - mmengine - INFO - Epoch(train) [974][60/63] lr: 7.8750e-04 eta: 2:42:14 time: 0.5424 data_time: 0.0096 memory: 16131 loss: 0.9754 loss_prob: 0.5057 loss_thr: 0.3837 loss_db: 0.0860 2022/10/26 07:21:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:21:49 - mmengine - INFO - Epoch(train) [975][5/63] lr: 7.8436e-04 eta: 2:42:14 time: 0.7887 data_time: 0.1688 memory: 16131 loss: 0.9201 loss_prob: 0.4827 loss_thr: 0.3522 loss_db: 0.0852 2022/10/26 07:21:52 - mmengine - INFO - Epoch(train) [975][10/63] lr: 7.8436e-04 eta: 2:42:05 time: 0.7907 data_time: 0.1675 memory: 16131 loss: 0.9819 loss_prob: 0.5118 loss_thr: 0.3790 loss_db: 0.0911 2022/10/26 07:21:54 - mmengine - INFO - Epoch(train) [975][15/63] lr: 7.8436e-04 eta: 2:42:05 time: 0.5139 data_time: 0.0060 memory: 16131 loss: 0.9064 loss_prob: 0.4695 loss_thr: 0.3545 loss_db: 0.0825 2022/10/26 07:21:57 - mmengine - INFO - Epoch(train) [975][20/63] lr: 7.8436e-04 eta: 2:41:58 time: 0.5250 data_time: 0.0061 memory: 16131 loss: 0.9533 loss_prob: 0.5052 loss_thr: 0.3614 loss_db: 0.0866 2022/10/26 07:22:00 - mmengine - INFO - Epoch(train) [975][25/63] lr: 7.8436e-04 eta: 2:41:58 time: 0.5610 data_time: 0.0252 memory: 16131 loss: 1.0500 loss_prob: 0.5618 loss_thr: 0.3926 loss_db: 0.0955 2022/10/26 07:22:03 - mmengine - INFO - Epoch(train) [975][30/63] lr: 7.8436e-04 eta: 2:41:51 time: 0.6022 data_time: 0.0454 memory: 16131 loss: 1.0055 loss_prob: 0.5441 loss_thr: 0.3722 loss_db: 0.0893 2022/10/26 07:22:06 - mmengine - INFO - Epoch(train) [975][35/63] lr: 7.8436e-04 eta: 2:41:51 time: 0.5750 data_time: 0.0302 memory: 16131 loss: 0.9852 loss_prob: 0.5346 loss_thr: 0.3623 loss_db: 0.0882 2022/10/26 07:22:08 - mmengine - INFO - Epoch(train) [975][40/63] lr: 7.8436e-04 eta: 2:41:44 time: 0.5226 data_time: 0.0097 memory: 16131 loss: 1.0197 loss_prob: 0.5384 loss_thr: 0.3879 loss_db: 0.0933 2022/10/26 07:22:11 - mmengine - INFO - Epoch(train) [975][45/63] lr: 7.8436e-04 eta: 2:41:44 time: 0.5081 data_time: 0.0051 memory: 16131 loss: 1.0319 loss_prob: 0.5439 loss_thr: 0.3936 loss_db: 0.0944 2022/10/26 07:22:14 - mmengine - INFO - Epoch(train) [975][50/63] lr: 7.8436e-04 eta: 2:41:37 time: 0.5390 data_time: 0.0119 memory: 16131 loss: 0.9618 loss_prob: 0.5065 loss_thr: 0.3675 loss_db: 0.0878 2022/10/26 07:22:16 - mmengine - INFO - Epoch(train) [975][55/63] lr: 7.8436e-04 eta: 2:41:37 time: 0.5489 data_time: 0.0223 memory: 16131 loss: 0.9421 loss_prob: 0.4920 loss_thr: 0.3667 loss_db: 0.0834 2022/10/26 07:22:19 - mmengine - INFO - Epoch(train) [975][60/63] lr: 7.8436e-04 eta: 2:41:29 time: 0.5156 data_time: 0.0172 memory: 16131 loss: 0.9694 loss_prob: 0.5080 loss_thr: 0.3755 loss_db: 0.0859 2022/10/26 07:22:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:22:26 - mmengine - INFO - Epoch(train) [976][5/63] lr: 7.8123e-04 eta: 2:41:29 time: 0.7717 data_time: 0.2443 memory: 16131 loss: 0.9291 loss_prob: 0.4760 loss_thr: 0.3696 loss_db: 0.0835 2022/10/26 07:22:28 - mmengine - INFO - Epoch(train) [976][10/63] lr: 7.8123e-04 eta: 2:41:20 time: 0.7752 data_time: 0.2432 memory: 16131 loss: 0.9581 loss_prob: 0.5043 loss_thr: 0.3657 loss_db: 0.0881 2022/10/26 07:22:31 - mmengine - INFO - Epoch(train) [976][15/63] lr: 7.8123e-04 eta: 2:41:20 time: 0.5202 data_time: 0.0090 memory: 16131 loss: 0.9251 loss_prob: 0.4862 loss_thr: 0.3543 loss_db: 0.0846 2022/10/26 07:22:33 - mmengine - INFO - Epoch(train) [976][20/63] lr: 7.8123e-04 eta: 2:41:13 time: 0.5429 data_time: 0.0094 memory: 16131 loss: 0.9256 loss_prob: 0.4788 loss_thr: 0.3648 loss_db: 0.0820 2022/10/26 07:22:36 - mmengine - INFO - Epoch(train) [976][25/63] lr: 7.8123e-04 eta: 2:41:13 time: 0.5369 data_time: 0.0370 memory: 16131 loss: 0.9068 loss_prob: 0.4723 loss_thr: 0.3529 loss_db: 0.0815 2022/10/26 07:22:39 - mmengine - INFO - Epoch(train) [976][30/63] lr: 7.8123e-04 eta: 2:41:06 time: 0.5422 data_time: 0.0357 memory: 16131 loss: 0.8523 loss_prob: 0.4426 loss_thr: 0.3309 loss_db: 0.0788 2022/10/26 07:22:42 - mmengine - INFO - Epoch(train) [976][35/63] lr: 7.8123e-04 eta: 2:41:06 time: 0.5355 data_time: 0.0083 memory: 16131 loss: 0.9177 loss_prob: 0.4879 loss_thr: 0.3445 loss_db: 0.0854 2022/10/26 07:22:44 - mmengine - INFO - Epoch(train) [976][40/63] lr: 7.8123e-04 eta: 2:40:59 time: 0.5256 data_time: 0.0110 memory: 16131 loss: 0.9532 loss_prob: 0.5117 loss_thr: 0.3546 loss_db: 0.0869 2022/10/26 07:22:47 - mmengine - INFO - Epoch(train) [976][45/63] lr: 7.8123e-04 eta: 2:40:59 time: 0.5321 data_time: 0.0095 memory: 16131 loss: 0.9546 loss_prob: 0.5144 loss_thr: 0.3546 loss_db: 0.0857 2022/10/26 07:22:50 - mmengine - INFO - Epoch(train) [976][50/63] lr: 7.8123e-04 eta: 2:40:52 time: 0.5804 data_time: 0.0215 memory: 16131 loss: 0.9320 loss_prob: 0.4921 loss_thr: 0.3557 loss_db: 0.0842 2022/10/26 07:22:52 - mmengine - INFO - Epoch(train) [976][55/63] lr: 7.8123e-04 eta: 2:40:52 time: 0.5610 data_time: 0.0195 memory: 16131 loss: 0.9329 loss_prob: 0.4855 loss_thr: 0.3603 loss_db: 0.0870 2022/10/26 07:22:55 - mmengine - INFO - Epoch(train) [976][60/63] lr: 7.8123e-04 eta: 2:40:44 time: 0.5394 data_time: 0.0067 memory: 16131 loss: 0.9366 loss_prob: 0.4893 loss_thr: 0.3600 loss_db: 0.0873 2022/10/26 07:22:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:23:03 - mmengine - INFO - Epoch(train) [977][5/63] lr: 7.7809e-04 eta: 2:40:44 time: 0.8740 data_time: 0.2045 memory: 16131 loss: 0.9734 loss_prob: 0.5102 loss_thr: 0.3753 loss_db: 0.0880 2022/10/26 07:23:05 - mmengine - INFO - Epoch(train) [977][10/63] lr: 7.7809e-04 eta: 2:40:36 time: 0.8775 data_time: 0.2041 memory: 16131 loss: 0.9197 loss_prob: 0.4822 loss_thr: 0.3528 loss_db: 0.0847 2022/10/26 07:23:08 - mmengine - INFO - Epoch(train) [977][15/63] lr: 7.7809e-04 eta: 2:40:36 time: 0.5089 data_time: 0.0113 memory: 16131 loss: 0.8699 loss_prob: 0.4433 loss_thr: 0.3479 loss_db: 0.0787 2022/10/26 07:23:10 - mmengine - INFO - Epoch(train) [977][20/63] lr: 7.7809e-04 eta: 2:40:28 time: 0.5051 data_time: 0.0087 memory: 16131 loss: 0.9346 loss_prob: 0.4849 loss_thr: 0.3634 loss_db: 0.0862 2022/10/26 07:23:13 - mmengine - INFO - Epoch(train) [977][25/63] lr: 7.7809e-04 eta: 2:40:28 time: 0.5286 data_time: 0.0076 memory: 16131 loss: 0.9592 loss_prob: 0.5038 loss_thr: 0.3668 loss_db: 0.0886 2022/10/26 07:23:16 - mmengine - INFO - Epoch(train) [977][30/63] lr: 7.7809e-04 eta: 2:40:21 time: 0.5790 data_time: 0.0308 memory: 16131 loss: 0.9832 loss_prob: 0.5169 loss_thr: 0.3783 loss_db: 0.0880 2022/10/26 07:23:19 - mmengine - INFO - Epoch(train) [977][35/63] lr: 7.7809e-04 eta: 2:40:21 time: 0.5557 data_time: 0.0293 memory: 16131 loss: 1.0313 loss_prob: 0.5582 loss_thr: 0.3806 loss_db: 0.0925 2022/10/26 07:23:21 - mmengine - INFO - Epoch(train) [977][40/63] lr: 7.7809e-04 eta: 2:40:14 time: 0.5219 data_time: 0.0108 memory: 16131 loss: 0.9635 loss_prob: 0.5195 loss_thr: 0.3578 loss_db: 0.0862 2022/10/26 07:23:24 - mmengine - INFO - Epoch(train) [977][45/63] lr: 7.7809e-04 eta: 2:40:14 time: 0.5146 data_time: 0.0110 memory: 16131 loss: 0.9396 loss_prob: 0.4984 loss_thr: 0.3555 loss_db: 0.0857 2022/10/26 07:23:27 - mmengine - INFO - Epoch(train) [977][50/63] lr: 7.7809e-04 eta: 2:40:07 time: 0.5140 data_time: 0.0144 memory: 16131 loss: 0.9467 loss_prob: 0.5044 loss_thr: 0.3543 loss_db: 0.0880 2022/10/26 07:23:29 - mmengine - INFO - Epoch(train) [977][55/63] lr: 7.7809e-04 eta: 2:40:07 time: 0.5470 data_time: 0.0193 memory: 16131 loss: 0.9098 loss_prob: 0.4787 loss_thr: 0.3480 loss_db: 0.0832 2022/10/26 07:23:32 - mmengine - INFO - Epoch(train) [977][60/63] lr: 7.7809e-04 eta: 2:40:00 time: 0.5245 data_time: 0.0125 memory: 16131 loss: 0.9001 loss_prob: 0.4705 loss_thr: 0.3475 loss_db: 0.0822 2022/10/26 07:23:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:23:39 - mmengine - INFO - Epoch(train) [978][5/63] lr: 7.7495e-04 eta: 2:40:00 time: 0.7803 data_time: 0.2242 memory: 16131 loss: 0.9096 loss_prob: 0.4792 loss_thr: 0.3494 loss_db: 0.0811 2022/10/26 07:23:41 - mmengine - INFO - Epoch(train) [978][10/63] lr: 7.7495e-04 eta: 2:39:51 time: 0.8073 data_time: 0.2256 memory: 16131 loss: 0.9798 loss_prob: 0.5194 loss_thr: 0.3738 loss_db: 0.0865 2022/10/26 07:23:44 - mmengine - INFO - Epoch(train) [978][15/63] lr: 7.7495e-04 eta: 2:39:51 time: 0.5154 data_time: 0.0078 memory: 16131 loss: 0.9782 loss_prob: 0.5073 loss_thr: 0.3837 loss_db: 0.0873 2022/10/26 07:23:47 - mmengine - INFO - Epoch(train) [978][20/63] lr: 7.7495e-04 eta: 2:39:43 time: 0.5608 data_time: 0.0062 memory: 16131 loss: 0.9657 loss_prob: 0.4947 loss_thr: 0.3850 loss_db: 0.0860 2022/10/26 07:23:50 - mmengine - INFO - Epoch(train) [978][25/63] lr: 7.7495e-04 eta: 2:39:43 time: 0.5665 data_time: 0.0079 memory: 16131 loss: 0.9520 loss_prob: 0.4874 loss_thr: 0.3783 loss_db: 0.0863 2022/10/26 07:23:53 - mmengine - INFO - Epoch(train) [978][30/63] lr: 7.7495e-04 eta: 2:39:36 time: 0.5958 data_time: 0.0384 memory: 16131 loss: 0.9256 loss_prob: 0.4757 loss_thr: 0.3650 loss_db: 0.0849 2022/10/26 07:23:55 - mmengine - INFO - Epoch(train) [978][35/63] lr: 7.7495e-04 eta: 2:39:36 time: 0.5796 data_time: 0.0384 memory: 16131 loss: 1.0222 loss_prob: 0.5473 loss_thr: 0.3832 loss_db: 0.0917 2022/10/26 07:23:58 - mmengine - INFO - Epoch(train) [978][40/63] lr: 7.7495e-04 eta: 2:39:29 time: 0.5160 data_time: 0.0081 memory: 16131 loss: 1.0337 loss_prob: 0.5556 loss_thr: 0.3847 loss_db: 0.0934 2022/10/26 07:24:01 - mmengine - INFO - Epoch(train) [978][45/63] lr: 7.7495e-04 eta: 2:39:29 time: 0.5534 data_time: 0.0065 memory: 16131 loss: 0.9623 loss_prob: 0.5018 loss_thr: 0.3718 loss_db: 0.0887 2022/10/26 07:24:04 - mmengine - INFO - Epoch(train) [978][50/63] lr: 7.7495e-04 eta: 2:39:22 time: 0.5526 data_time: 0.0175 memory: 16131 loss: 0.9246 loss_prob: 0.4808 loss_thr: 0.3600 loss_db: 0.0838 2022/10/26 07:24:06 - mmengine - INFO - Epoch(train) [978][55/63] lr: 7.7495e-04 eta: 2:39:22 time: 0.5137 data_time: 0.0203 memory: 16131 loss: 0.9229 loss_prob: 0.4862 loss_thr: 0.3500 loss_db: 0.0867 2022/10/26 07:24:09 - mmengine - INFO - Epoch(train) [978][60/63] lr: 7.7495e-04 eta: 2:39:15 time: 0.5082 data_time: 0.0082 memory: 16131 loss: 0.9046 loss_prob: 0.4748 loss_thr: 0.3452 loss_db: 0.0846 2022/10/26 07:24:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:24:14 - mmengine - INFO - Epoch(train) [979][5/63] lr: 7.7180e-04 eta: 2:39:15 time: 0.6530 data_time: 0.1758 memory: 16131 loss: 0.8740 loss_prob: 0.4553 loss_thr: 0.3421 loss_db: 0.0766 2022/10/26 07:24:17 - mmengine - INFO - Epoch(train) [979][10/63] lr: 7.7180e-04 eta: 2:39:06 time: 0.7021 data_time: 0.1781 memory: 16131 loss: 0.9706 loss_prob: 0.5182 loss_thr: 0.3665 loss_db: 0.0860 2022/10/26 07:24:20 - mmengine - INFO - Epoch(train) [979][15/63] lr: 7.7180e-04 eta: 2:39:06 time: 0.5476 data_time: 0.0138 memory: 16131 loss: 1.1533 loss_prob: 0.6355 loss_thr: 0.4079 loss_db: 0.1098 2022/10/26 07:24:22 - mmengine - INFO - Epoch(train) [979][20/63] lr: 7.7180e-04 eta: 2:38:58 time: 0.5215 data_time: 0.0096 memory: 16131 loss: 1.0913 loss_prob: 0.5947 loss_thr: 0.3913 loss_db: 0.1053 2022/10/26 07:24:25 - mmengine - INFO - Epoch(train) [979][25/63] lr: 7.7180e-04 eta: 2:38:58 time: 0.5233 data_time: 0.0263 memory: 16131 loss: 0.9613 loss_prob: 0.5068 loss_thr: 0.3679 loss_db: 0.0867 2022/10/26 07:24:27 - mmengine - INFO - Epoch(train) [979][30/63] lr: 7.7180e-04 eta: 2:38:51 time: 0.5308 data_time: 0.0343 memory: 16131 loss: 0.9242 loss_prob: 0.4826 loss_thr: 0.3580 loss_db: 0.0836 2022/10/26 07:24:30 - mmengine - INFO - Epoch(train) [979][35/63] lr: 7.7180e-04 eta: 2:38:51 time: 0.4974 data_time: 0.0126 memory: 16131 loss: 0.8768 loss_prob: 0.4494 loss_thr: 0.3473 loss_db: 0.0801 2022/10/26 07:24:33 - mmengine - INFO - Epoch(train) [979][40/63] lr: 7.7180e-04 eta: 2:38:44 time: 0.5000 data_time: 0.0092 memory: 16131 loss: 0.9201 loss_prob: 0.4745 loss_thr: 0.3623 loss_db: 0.0833 2022/10/26 07:24:35 - mmengine - INFO - Epoch(train) [979][45/63] lr: 7.7180e-04 eta: 2:38:44 time: 0.5023 data_time: 0.0096 memory: 16131 loss: 0.9885 loss_prob: 0.5235 loss_thr: 0.3754 loss_db: 0.0896 2022/10/26 07:24:38 - mmengine - INFO - Epoch(train) [979][50/63] lr: 7.7180e-04 eta: 2:38:37 time: 0.5350 data_time: 0.0135 memory: 16131 loss: 0.9509 loss_prob: 0.4959 loss_thr: 0.3685 loss_db: 0.0865 2022/10/26 07:24:41 - mmengine - INFO - Epoch(train) [979][55/63] lr: 7.7180e-04 eta: 2:38:37 time: 0.5740 data_time: 0.0194 memory: 16131 loss: 0.9062 loss_prob: 0.4677 loss_thr: 0.3563 loss_db: 0.0823 2022/10/26 07:24:44 - mmengine - INFO - Epoch(train) [979][60/63] lr: 7.7180e-04 eta: 2:38:30 time: 0.5830 data_time: 0.0154 memory: 16131 loss: 1.0336 loss_prob: 0.5795 loss_thr: 0.3617 loss_db: 0.0924 2022/10/26 07:24:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:24:50 - mmengine - INFO - Epoch(train) [980][5/63] lr: 7.6866e-04 eta: 2:38:30 time: 0.7084 data_time: 0.1996 memory: 16131 loss: 0.9276 loss_prob: 0.4909 loss_thr: 0.3534 loss_db: 0.0834 2022/10/26 07:24:52 - mmengine - INFO - Epoch(train) [980][10/63] lr: 7.6866e-04 eta: 2:38:21 time: 0.7413 data_time: 0.2003 memory: 16131 loss: 1.0588 loss_prob: 0.5801 loss_thr: 0.3803 loss_db: 0.0984 2022/10/26 07:24:55 - mmengine - INFO - Epoch(train) [980][15/63] lr: 7.6866e-04 eta: 2:38:21 time: 0.5424 data_time: 0.0138 memory: 16131 loss: 1.0236 loss_prob: 0.5528 loss_thr: 0.3747 loss_db: 0.0961 2022/10/26 07:24:58 - mmengine - INFO - Epoch(train) [980][20/63] lr: 7.6866e-04 eta: 2:38:13 time: 0.5251 data_time: 0.0107 memory: 16131 loss: 0.9228 loss_prob: 0.4782 loss_thr: 0.3619 loss_db: 0.0828 2022/10/26 07:25:01 - mmengine - INFO - Epoch(train) [980][25/63] lr: 7.6866e-04 eta: 2:38:13 time: 0.5448 data_time: 0.0452 memory: 16131 loss: 0.9291 loss_prob: 0.4903 loss_thr: 0.3543 loss_db: 0.0844 2022/10/26 07:25:03 - mmengine - INFO - Epoch(train) [980][30/63] lr: 7.6866e-04 eta: 2:38:06 time: 0.5630 data_time: 0.0461 memory: 16131 loss: 0.9811 loss_prob: 0.5258 loss_thr: 0.3643 loss_db: 0.0910 2022/10/26 07:25:06 - mmengine - INFO - Epoch(train) [980][35/63] lr: 7.6866e-04 eta: 2:38:06 time: 0.5222 data_time: 0.0097 memory: 16131 loss: 0.9902 loss_prob: 0.5225 loss_thr: 0.3764 loss_db: 0.0913 2022/10/26 07:25:08 - mmengine - INFO - Epoch(train) [980][40/63] lr: 7.6866e-04 eta: 2:37:59 time: 0.5203 data_time: 0.0068 memory: 16131 loss: 0.9905 loss_prob: 0.5260 loss_thr: 0.3740 loss_db: 0.0905 2022/10/26 07:25:11 - mmengine - INFO - Epoch(train) [980][45/63] lr: 7.6866e-04 eta: 2:37:59 time: 0.5165 data_time: 0.0049 memory: 16131 loss: 0.9667 loss_prob: 0.5162 loss_thr: 0.3617 loss_db: 0.0888 2022/10/26 07:25:14 - mmengine - INFO - Epoch(train) [980][50/63] lr: 7.6866e-04 eta: 2:37:52 time: 0.5171 data_time: 0.0217 memory: 16131 loss: 0.9327 loss_prob: 0.4892 loss_thr: 0.3566 loss_db: 0.0870 2022/10/26 07:25:16 - mmengine - INFO - Epoch(train) [980][55/63] lr: 7.6866e-04 eta: 2:37:52 time: 0.5131 data_time: 0.0218 memory: 16131 loss: 0.9443 loss_prob: 0.4902 loss_thr: 0.3668 loss_db: 0.0874 2022/10/26 07:25:18 - mmengine - INFO - Epoch(train) [980][60/63] lr: 7.6866e-04 eta: 2:37:45 time: 0.4845 data_time: 0.0046 memory: 16131 loss: 0.9224 loss_prob: 0.4828 loss_thr: 0.3562 loss_db: 0.0834 2022/10/26 07:25:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:25:20 - mmengine - INFO - Saving checkpoint at 980 epochs 2022/10/26 07:25:26 - mmengine - INFO - Epoch(val) [980][5/32] eta: 2:37:45 time: 0.5068 data_time: 0.0561 memory: 16131 2022/10/26 07:25:29 - mmengine - INFO - Epoch(val) [980][10/32] eta: 0:00:12 time: 0.5802 data_time: 0.0758 memory: 15724 2022/10/26 07:25:32 - mmengine - INFO - Epoch(val) [980][15/32] eta: 0:00:12 time: 0.5511 data_time: 0.0480 memory: 15724 2022/10/26 07:25:34 - mmengine - INFO - Epoch(val) [980][20/32] eta: 0:00:06 time: 0.5557 data_time: 0.0623 memory: 15724 2022/10/26 07:25:37 - mmengine - INFO - Epoch(val) [980][25/32] eta: 0:00:06 time: 0.5631 data_time: 0.0516 memory: 15724 2022/10/26 07:25:40 - mmengine - INFO - Epoch(val) [980][30/32] eta: 0:00:01 time: 0.5354 data_time: 0.0214 memory: 15724 2022/10/26 07:25:40 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8406, precision: 0.7698, hmean: 0.8037 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8406, precision: 0.8113, hmean: 0.8257 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8392, precision: 0.8465, hmean: 0.8428 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8339, precision: 0.8743, hmean: 0.8536 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8243, precision: 0.8992, hmean: 0.8601 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7448, precision: 0.9381, hmean: 0.8304 2022/10/26 07:25:40 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1623, precision: 0.9825, hmean: 0.2785 2022/10/26 07:25:40 - mmengine - INFO - Epoch(val) [980][32/32] icdar/precision: 0.8992 icdar/recall: 0.8243 icdar/hmean: 0.8601 2022/10/26 07:25:45 - mmengine - INFO - Epoch(train) [981][5/63] lr: 7.6552e-04 eta: 0:00:01 time: 0.6482 data_time: 0.1820 memory: 16131 loss: 0.9328 loss_prob: 0.4757 loss_thr: 0.3740 loss_db: 0.0830 2022/10/26 07:25:47 - mmengine - INFO - Epoch(train) [981][10/63] lr: 7.6552e-04 eta: 2:37:35 time: 0.6887 data_time: 0.1869 memory: 16131 loss: 0.9466 loss_prob: 0.4890 loss_thr: 0.3734 loss_db: 0.0843 2022/10/26 07:25:50 - mmengine - INFO - Epoch(train) [981][15/63] lr: 7.6552e-04 eta: 2:37:35 time: 0.5157 data_time: 0.0100 memory: 16131 loss: 1.0954 loss_prob: 0.5907 loss_thr: 0.4069 loss_db: 0.0978 2022/10/26 07:25:53 - mmengine - INFO - Epoch(train) [981][20/63] lr: 7.6552e-04 eta: 2:37:28 time: 0.5137 data_time: 0.0066 memory: 16131 loss: 1.0665 loss_prob: 0.5697 loss_thr: 0.4014 loss_db: 0.0954 2022/10/26 07:25:55 - mmengine - INFO - Epoch(train) [981][25/63] lr: 7.6552e-04 eta: 2:37:28 time: 0.5410 data_time: 0.0320 memory: 16131 loss: 0.9151 loss_prob: 0.4726 loss_thr: 0.3613 loss_db: 0.0812 2022/10/26 07:25:58 - mmengine - INFO - Epoch(train) [981][30/63] lr: 7.6552e-04 eta: 2:37:21 time: 0.5404 data_time: 0.0385 memory: 16131 loss: 0.9797 loss_prob: 0.5155 loss_thr: 0.3742 loss_db: 0.0900 2022/10/26 07:26:01 - mmengine - INFO - Epoch(train) [981][35/63] lr: 7.6552e-04 eta: 2:37:21 time: 0.5403 data_time: 0.0129 memory: 16131 loss: 0.9654 loss_prob: 0.5011 loss_thr: 0.3763 loss_db: 0.0879 2022/10/26 07:26:04 - mmengine - INFO - Epoch(train) [981][40/63] lr: 7.6552e-04 eta: 2:37:14 time: 0.5686 data_time: 0.0075 memory: 16131 loss: 0.8475 loss_prob: 0.4358 loss_thr: 0.3348 loss_db: 0.0769 2022/10/26 07:26:06 - mmengine - INFO - Epoch(train) [981][45/63] lr: 7.6552e-04 eta: 2:37:14 time: 0.5582 data_time: 0.0078 memory: 16131 loss: 0.8996 loss_prob: 0.4699 loss_thr: 0.3471 loss_db: 0.0827 2022/10/26 07:26:09 - mmengine - INFO - Epoch(train) [981][50/63] lr: 7.6552e-04 eta: 2:37:07 time: 0.5394 data_time: 0.0186 memory: 16131 loss: 0.9494 loss_prob: 0.5011 loss_thr: 0.3613 loss_db: 0.0871 2022/10/26 07:26:12 - mmengine - INFO - Epoch(train) [981][55/63] lr: 7.6552e-04 eta: 2:37:07 time: 0.5350 data_time: 0.0237 memory: 16131 loss: 0.9743 loss_prob: 0.5261 loss_thr: 0.3578 loss_db: 0.0904 2022/10/26 07:26:14 - mmengine - INFO - Epoch(train) [981][60/63] lr: 7.6552e-04 eta: 2:37:00 time: 0.5430 data_time: 0.0101 memory: 16131 loss: 0.9573 loss_prob: 0.5093 loss_thr: 0.3608 loss_db: 0.0872 2022/10/26 07:26:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:26:20 - mmengine - INFO - Epoch(train) [982][5/63] lr: 7.6237e-04 eta: 2:37:00 time: 0.6554 data_time: 0.1865 memory: 16131 loss: 1.0496 loss_prob: 0.5462 loss_thr: 0.4099 loss_db: 0.0936 2022/10/26 07:26:23 - mmengine - INFO - Epoch(train) [982][10/63] lr: 7.6237e-04 eta: 2:36:50 time: 0.7175 data_time: 0.1865 memory: 16131 loss: 1.0099 loss_prob: 0.5270 loss_thr: 0.3930 loss_db: 0.0899 2022/10/26 07:26:25 - mmengine - INFO - Epoch(train) [982][15/63] lr: 7.6237e-04 eta: 2:36:50 time: 0.5331 data_time: 0.0089 memory: 16131 loss: 0.9211 loss_prob: 0.4771 loss_thr: 0.3623 loss_db: 0.0817 2022/10/26 07:26:28 - mmengine - INFO - Epoch(train) [982][20/63] lr: 7.6237e-04 eta: 2:36:43 time: 0.4875 data_time: 0.0083 memory: 16131 loss: 0.8971 loss_prob: 0.4630 loss_thr: 0.3546 loss_db: 0.0795 2022/10/26 07:26:30 - mmengine - INFO - Epoch(train) [982][25/63] lr: 7.6237e-04 eta: 2:36:43 time: 0.5106 data_time: 0.0228 memory: 16131 loss: 0.9291 loss_prob: 0.4878 loss_thr: 0.3566 loss_db: 0.0847 2022/10/26 07:26:33 - mmengine - INFO - Epoch(train) [982][30/63] lr: 7.6237e-04 eta: 2:36:36 time: 0.5304 data_time: 0.0354 memory: 16131 loss: 0.8999 loss_prob: 0.4739 loss_thr: 0.3430 loss_db: 0.0830 2022/10/26 07:26:36 - mmengine - INFO - Epoch(train) [982][35/63] lr: 7.6237e-04 eta: 2:36:36 time: 0.5078 data_time: 0.0198 memory: 16131 loss: 0.9030 loss_prob: 0.4716 loss_thr: 0.3481 loss_db: 0.0833 2022/10/26 07:26:39 - mmengine - INFO - Epoch(train) [982][40/63] lr: 7.6237e-04 eta: 2:36:29 time: 0.5532 data_time: 0.0131 memory: 16131 loss: 0.9282 loss_prob: 0.4804 loss_thr: 0.3631 loss_db: 0.0847 2022/10/26 07:26:41 - mmengine - INFO - Epoch(train) [982][45/63] lr: 7.6237e-04 eta: 2:36:29 time: 0.5427 data_time: 0.0114 memory: 16131 loss: 0.9041 loss_prob: 0.4666 loss_thr: 0.3565 loss_db: 0.0810 2022/10/26 07:26:44 - mmengine - INFO - Epoch(train) [982][50/63] lr: 7.6237e-04 eta: 2:36:22 time: 0.5251 data_time: 0.0161 memory: 16131 loss: 0.9511 loss_prob: 0.5061 loss_thr: 0.3596 loss_db: 0.0854 2022/10/26 07:26:46 - mmengine - INFO - Epoch(train) [982][55/63] lr: 7.6237e-04 eta: 2:36:22 time: 0.5318 data_time: 0.0226 memory: 16131 loss: 0.9775 loss_prob: 0.5251 loss_thr: 0.3614 loss_db: 0.0910 2022/10/26 07:26:49 - mmengine - INFO - Epoch(train) [982][60/63] lr: 7.6237e-04 eta: 2:36:14 time: 0.5277 data_time: 0.0124 memory: 16131 loss: 0.9443 loss_prob: 0.4949 loss_thr: 0.3612 loss_db: 0.0882 2022/10/26 07:26:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:26:55 - mmengine - INFO - Epoch(train) [983][5/63] lr: 7.5922e-04 eta: 2:36:14 time: 0.7435 data_time: 0.2080 memory: 16131 loss: 1.0007 loss_prob: 0.5361 loss_thr: 0.3732 loss_db: 0.0914 2022/10/26 07:26:58 - mmengine - INFO - Epoch(train) [983][10/63] lr: 7.5922e-04 eta: 2:36:05 time: 0.7411 data_time: 0.2100 memory: 16131 loss: 0.9320 loss_prob: 0.5010 loss_thr: 0.3462 loss_db: 0.0847 2022/10/26 07:27:00 - mmengine - INFO - Epoch(train) [983][15/63] lr: 7.5922e-04 eta: 2:36:05 time: 0.5045 data_time: 0.0097 memory: 16131 loss: 0.8997 loss_prob: 0.4701 loss_thr: 0.3473 loss_db: 0.0823 2022/10/26 07:27:03 - mmengine - INFO - Epoch(train) [983][20/63] lr: 7.5922e-04 eta: 2:35:58 time: 0.4944 data_time: 0.0062 memory: 16131 loss: 0.9198 loss_prob: 0.4732 loss_thr: 0.3628 loss_db: 0.0838 2022/10/26 07:27:05 - mmengine - INFO - Epoch(train) [983][25/63] lr: 7.5922e-04 eta: 2:35:58 time: 0.5027 data_time: 0.0089 memory: 16131 loss: 0.9093 loss_prob: 0.4682 loss_thr: 0.3573 loss_db: 0.0838 2022/10/26 07:27:08 - mmengine - INFO - Epoch(train) [983][30/63] lr: 7.5922e-04 eta: 2:35:51 time: 0.5343 data_time: 0.0307 memory: 16131 loss: 0.9873 loss_prob: 0.5246 loss_thr: 0.3711 loss_db: 0.0916 2022/10/26 07:27:11 - mmengine - INFO - Epoch(train) [983][35/63] lr: 7.5922e-04 eta: 2:35:51 time: 0.5592 data_time: 0.0299 memory: 16131 loss: 1.0335 loss_prob: 0.5507 loss_thr: 0.3887 loss_db: 0.0941 2022/10/26 07:27:14 - mmengine - INFO - Epoch(train) [983][40/63] lr: 7.5922e-04 eta: 2:35:44 time: 0.5487 data_time: 0.0078 memory: 16131 loss: 1.0049 loss_prob: 0.5305 loss_thr: 0.3840 loss_db: 0.0905 2022/10/26 07:27:16 - mmengine - INFO - Epoch(train) [983][45/63] lr: 7.5922e-04 eta: 2:35:44 time: 0.5361 data_time: 0.0076 memory: 16131 loss: 0.9193 loss_prob: 0.4810 loss_thr: 0.3548 loss_db: 0.0835 2022/10/26 07:27:19 - mmengine - INFO - Epoch(train) [983][50/63] lr: 7.5922e-04 eta: 2:35:37 time: 0.5685 data_time: 0.0257 memory: 16131 loss: 0.8517 loss_prob: 0.4404 loss_thr: 0.3340 loss_db: 0.0774 2022/10/26 07:27:22 - mmengine - INFO - Epoch(train) [983][55/63] lr: 7.5922e-04 eta: 2:35:37 time: 0.6163 data_time: 0.0265 memory: 16131 loss: 0.8715 loss_prob: 0.4520 loss_thr: 0.3398 loss_db: 0.0797 2022/10/26 07:27:26 - mmengine - INFO - Epoch(train) [983][60/63] lr: 7.5922e-04 eta: 2:35:30 time: 0.6278 data_time: 0.0091 memory: 16131 loss: 0.9732 loss_prob: 0.5146 loss_thr: 0.3680 loss_db: 0.0907 2022/10/26 07:27:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:27:32 - mmengine - INFO - Epoch(train) [984][5/63] lr: 7.5607e-04 eta: 2:35:30 time: 0.7958 data_time: 0.1898 memory: 16131 loss: 0.8847 loss_prob: 0.4691 loss_thr: 0.3346 loss_db: 0.0810 2022/10/26 07:27:35 - mmengine - INFO - Epoch(train) [984][10/63] lr: 7.5607e-04 eta: 2:35:21 time: 0.8090 data_time: 0.1849 memory: 16131 loss: 0.9085 loss_prob: 0.4804 loss_thr: 0.3470 loss_db: 0.0812 2022/10/26 07:27:38 - mmengine - INFO - Epoch(train) [984][15/63] lr: 7.5607e-04 eta: 2:35:21 time: 0.5299 data_time: 0.0122 memory: 16131 loss: 1.0034 loss_prob: 0.5362 loss_thr: 0.3747 loss_db: 0.0925 2022/10/26 07:27:40 - mmengine - INFO - Epoch(train) [984][20/63] lr: 7.5607e-04 eta: 2:35:13 time: 0.4935 data_time: 0.0103 memory: 16131 loss: 1.0002 loss_prob: 0.5226 loss_thr: 0.3853 loss_db: 0.0923 2022/10/26 07:27:43 - mmengine - INFO - Epoch(train) [984][25/63] lr: 7.5607e-04 eta: 2:35:13 time: 0.5377 data_time: 0.0354 memory: 16131 loss: 0.9290 loss_prob: 0.4862 loss_thr: 0.3581 loss_db: 0.0846 2022/10/26 07:27:46 - mmengine - INFO - Epoch(train) [984][30/63] lr: 7.5607e-04 eta: 2:35:06 time: 0.5845 data_time: 0.0421 memory: 16131 loss: 0.9309 loss_prob: 0.4950 loss_thr: 0.3512 loss_db: 0.0846 2022/10/26 07:27:48 - mmengine - INFO - Epoch(train) [984][35/63] lr: 7.5607e-04 eta: 2:35:06 time: 0.5362 data_time: 0.0119 memory: 16131 loss: 0.9563 loss_prob: 0.4961 loss_thr: 0.3740 loss_db: 0.0863 2022/10/26 07:27:51 - mmengine - INFO - Epoch(train) [984][40/63] lr: 7.5607e-04 eta: 2:34:59 time: 0.5358 data_time: 0.0050 memory: 16131 loss: 0.9652 loss_prob: 0.5093 loss_thr: 0.3699 loss_db: 0.0860 2022/10/26 07:27:54 - mmengine - INFO - Epoch(train) [984][45/63] lr: 7.5607e-04 eta: 2:34:59 time: 0.5374 data_time: 0.0064 memory: 16131 loss: 0.9519 loss_prob: 0.5027 loss_thr: 0.3650 loss_db: 0.0842 2022/10/26 07:27:56 - mmengine - INFO - Epoch(train) [984][50/63] lr: 7.5607e-04 eta: 2:34:52 time: 0.5100 data_time: 0.0234 memory: 16131 loss: 0.9158 loss_prob: 0.4775 loss_thr: 0.3545 loss_db: 0.0839 2022/10/26 07:27:59 - mmengine - INFO - Epoch(train) [984][55/63] lr: 7.5607e-04 eta: 2:34:52 time: 0.5162 data_time: 0.0234 memory: 16131 loss: 0.9205 loss_prob: 0.4832 loss_thr: 0.3520 loss_db: 0.0853 2022/10/26 07:28:02 - mmengine - INFO - Epoch(train) [984][60/63] lr: 7.5607e-04 eta: 2:34:45 time: 0.5277 data_time: 0.0064 memory: 16131 loss: 0.9842 loss_prob: 0.5162 loss_thr: 0.3776 loss_db: 0.0904 2022/10/26 07:28:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:28:07 - mmengine - INFO - Epoch(train) [985][5/63] lr: 7.5292e-04 eta: 2:34:45 time: 0.6806 data_time: 0.1558 memory: 16131 loss: 0.8918 loss_prob: 0.4704 loss_thr: 0.3403 loss_db: 0.0812 2022/10/26 07:28:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:28:10 - mmengine - INFO - Epoch(train) [985][10/63] lr: 7.5292e-04 eta: 2:34:36 time: 0.6924 data_time: 0.1670 memory: 16131 loss: 0.9033 loss_prob: 0.4723 loss_thr: 0.3493 loss_db: 0.0817 2022/10/26 07:28:12 - mmengine - INFO - Epoch(train) [985][15/63] lr: 7.5292e-04 eta: 2:34:36 time: 0.5270 data_time: 0.0254 memory: 16131 loss: 0.9093 loss_prob: 0.4649 loss_thr: 0.3647 loss_db: 0.0798 2022/10/26 07:28:15 - mmengine - INFO - Epoch(train) [985][20/63] lr: 7.5292e-04 eta: 2:34:28 time: 0.5065 data_time: 0.0115 memory: 16131 loss: 0.8550 loss_prob: 0.4320 loss_thr: 0.3473 loss_db: 0.0756 2022/10/26 07:28:18 - mmengine - INFO - Epoch(train) [985][25/63] lr: 7.5292e-04 eta: 2:34:28 time: 0.5303 data_time: 0.0171 memory: 16131 loss: 0.9195 loss_prob: 0.4834 loss_thr: 0.3513 loss_db: 0.0848 2022/10/26 07:28:21 - mmengine - INFO - Epoch(train) [985][30/63] lr: 7.5292e-04 eta: 2:34:21 time: 0.5636 data_time: 0.0180 memory: 16131 loss: 1.0209 loss_prob: 0.5466 loss_thr: 0.3827 loss_db: 0.0916 2022/10/26 07:28:23 - mmengine - INFO - Epoch(train) [985][35/63] lr: 7.5292e-04 eta: 2:34:21 time: 0.5403 data_time: 0.0218 memory: 16131 loss: 1.0241 loss_prob: 0.5394 loss_thr: 0.3928 loss_db: 0.0919 2022/10/26 07:28:26 - mmengine - INFO - Epoch(train) [985][40/63] lr: 7.5292e-04 eta: 2:34:14 time: 0.5255 data_time: 0.0239 memory: 16131 loss: 0.9718 loss_prob: 0.5038 loss_thr: 0.3789 loss_db: 0.0892 2022/10/26 07:28:28 - mmengine - INFO - Epoch(train) [985][45/63] lr: 7.5292e-04 eta: 2:34:14 time: 0.5392 data_time: 0.0125 memory: 16131 loss: 0.8652 loss_prob: 0.4438 loss_thr: 0.3438 loss_db: 0.0776 2022/10/26 07:28:31 - mmengine - INFO - Epoch(train) [985][50/63] lr: 7.5292e-04 eta: 2:34:07 time: 0.5131 data_time: 0.0157 memory: 16131 loss: 0.8627 loss_prob: 0.4434 loss_thr: 0.3419 loss_db: 0.0774 2022/10/26 07:28:34 - mmengine - INFO - Epoch(train) [985][55/63] lr: 7.5292e-04 eta: 2:34:07 time: 0.5052 data_time: 0.0194 memory: 16131 loss: 0.9150 loss_prob: 0.4743 loss_thr: 0.3583 loss_db: 0.0824 2022/10/26 07:28:36 - mmengine - INFO - Epoch(train) [985][60/63] lr: 7.5292e-04 eta: 2:34:00 time: 0.5184 data_time: 0.0134 memory: 16131 loss: 0.9055 loss_prob: 0.4754 loss_thr: 0.3481 loss_db: 0.0820 2022/10/26 07:28:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:28:42 - mmengine - INFO - Epoch(train) [986][5/63] lr: 7.4977e-04 eta: 2:34:00 time: 0.6692 data_time: 0.1739 memory: 16131 loss: 0.9004 loss_prob: 0.4641 loss_thr: 0.3539 loss_db: 0.0825 2022/10/26 07:28:44 - mmengine - INFO - Epoch(train) [986][10/63] lr: 7.4977e-04 eta: 2:33:50 time: 0.6991 data_time: 0.1823 memory: 16131 loss: 0.9017 loss_prob: 0.4567 loss_thr: 0.3630 loss_db: 0.0821 2022/10/26 07:28:47 - mmengine - INFO - Epoch(train) [986][15/63] lr: 7.4977e-04 eta: 2:33:50 time: 0.5095 data_time: 0.0175 memory: 16131 loss: 0.8823 loss_prob: 0.4510 loss_thr: 0.3523 loss_db: 0.0790 2022/10/26 07:28:50 - mmengine - INFO - Epoch(train) [986][20/63] lr: 7.4977e-04 eta: 2:33:43 time: 0.5180 data_time: 0.0067 memory: 16131 loss: 0.9082 loss_prob: 0.4721 loss_thr: 0.3549 loss_db: 0.0812 2022/10/26 07:28:52 - mmengine - INFO - Epoch(train) [986][25/63] lr: 7.4977e-04 eta: 2:33:43 time: 0.5195 data_time: 0.0131 memory: 16131 loss: 0.9697 loss_prob: 0.5092 loss_thr: 0.3716 loss_db: 0.0889 2022/10/26 07:28:55 - mmengine - INFO - Epoch(train) [986][30/63] lr: 7.4977e-04 eta: 2:33:36 time: 0.5054 data_time: 0.0353 memory: 16131 loss: 0.9927 loss_prob: 0.5274 loss_thr: 0.3722 loss_db: 0.0932 2022/10/26 07:28:57 - mmengine - INFO - Epoch(train) [986][35/63] lr: 7.4977e-04 eta: 2:33:36 time: 0.5272 data_time: 0.0419 memory: 16131 loss: 0.9998 loss_prob: 0.5336 loss_thr: 0.3724 loss_db: 0.0938 2022/10/26 07:29:00 - mmengine - INFO - Epoch(train) [986][40/63] lr: 7.4977e-04 eta: 2:33:29 time: 0.5278 data_time: 0.0187 memory: 16131 loss: 0.9929 loss_prob: 0.5283 loss_thr: 0.3725 loss_db: 0.0920 2022/10/26 07:29:03 - mmengine - INFO - Epoch(train) [986][45/63] lr: 7.4977e-04 eta: 2:33:29 time: 0.5373 data_time: 0.0087 memory: 16131 loss: 1.0449 loss_prob: 0.5612 loss_thr: 0.3899 loss_db: 0.0938 2022/10/26 07:29:05 - mmengine - INFO - Epoch(train) [986][50/63] lr: 7.4977e-04 eta: 2:33:22 time: 0.5202 data_time: 0.0163 memory: 16131 loss: 0.9901 loss_prob: 0.5269 loss_thr: 0.3755 loss_db: 0.0877 2022/10/26 07:29:08 - mmengine - INFO - Epoch(train) [986][55/63] lr: 7.4977e-04 eta: 2:33:22 time: 0.5020 data_time: 0.0237 memory: 16131 loss: 0.9280 loss_prob: 0.4914 loss_thr: 0.3500 loss_db: 0.0865 2022/10/26 07:29:10 - mmengine - INFO - Epoch(train) [986][60/63] lr: 7.4977e-04 eta: 2:33:15 time: 0.5229 data_time: 0.0187 memory: 16131 loss: 0.9787 loss_prob: 0.5262 loss_thr: 0.3620 loss_db: 0.0905 2022/10/26 07:29:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:29:17 - mmengine - INFO - Epoch(train) [987][5/63] lr: 7.4662e-04 eta: 2:33:15 time: 0.7781 data_time: 0.1940 memory: 16131 loss: 0.9012 loss_prob: 0.4798 loss_thr: 0.3408 loss_db: 0.0806 2022/10/26 07:29:19 - mmengine - INFO - Epoch(train) [987][10/63] lr: 7.4662e-04 eta: 2:33:06 time: 0.7857 data_time: 0.1938 memory: 16131 loss: 0.9270 loss_prob: 0.4895 loss_thr: 0.3515 loss_db: 0.0861 2022/10/26 07:29:22 - mmengine - INFO - Epoch(train) [987][15/63] lr: 7.4662e-04 eta: 2:33:06 time: 0.5160 data_time: 0.0047 memory: 16131 loss: 0.9981 loss_prob: 0.5243 loss_thr: 0.3831 loss_db: 0.0907 2022/10/26 07:29:25 - mmengine - INFO - Epoch(train) [987][20/63] lr: 7.4662e-04 eta: 2:32:58 time: 0.5096 data_time: 0.0053 memory: 16131 loss: 0.9952 loss_prob: 0.5222 loss_thr: 0.3815 loss_db: 0.0915 2022/10/26 07:29:27 - mmengine - INFO - Epoch(train) [987][25/63] lr: 7.4662e-04 eta: 2:32:58 time: 0.5437 data_time: 0.0133 memory: 16131 loss: 0.9025 loss_prob: 0.4713 loss_thr: 0.3467 loss_db: 0.0845 2022/10/26 07:29:30 - mmengine - INFO - Epoch(train) [987][30/63] lr: 7.4662e-04 eta: 2:32:51 time: 0.5652 data_time: 0.0332 memory: 16131 loss: 0.8165 loss_prob: 0.4215 loss_thr: 0.3223 loss_db: 0.0727 2022/10/26 07:29:33 - mmengine - INFO - Epoch(train) [987][35/63] lr: 7.4662e-04 eta: 2:32:51 time: 0.5197 data_time: 0.0252 memory: 16131 loss: 0.9198 loss_prob: 0.4848 loss_thr: 0.3508 loss_db: 0.0843 2022/10/26 07:29:35 - mmengine - INFO - Epoch(train) [987][40/63] lr: 7.4662e-04 eta: 2:32:44 time: 0.4983 data_time: 0.0063 memory: 16131 loss: 0.9958 loss_prob: 0.5295 loss_thr: 0.3756 loss_db: 0.0908 2022/10/26 07:29:38 - mmengine - INFO - Epoch(train) [987][45/63] lr: 7.4662e-04 eta: 2:32:44 time: 0.5389 data_time: 0.0061 memory: 16131 loss: 0.9758 loss_prob: 0.5149 loss_thr: 0.3729 loss_db: 0.0880 2022/10/26 07:29:41 - mmengine - INFO - Epoch(train) [987][50/63] lr: 7.4662e-04 eta: 2:32:37 time: 0.5358 data_time: 0.0107 memory: 16131 loss: 0.9505 loss_prob: 0.5054 loss_thr: 0.3582 loss_db: 0.0868 2022/10/26 07:29:43 - mmengine - INFO - Epoch(train) [987][55/63] lr: 7.4662e-04 eta: 2:32:37 time: 0.4984 data_time: 0.0212 memory: 16131 loss: 0.9262 loss_prob: 0.5001 loss_thr: 0.3427 loss_db: 0.0835 2022/10/26 07:29:46 - mmengine - INFO - Epoch(train) [987][60/63] lr: 7.4662e-04 eta: 2:32:30 time: 0.5049 data_time: 0.0148 memory: 16131 loss: 0.9154 loss_prob: 0.4845 loss_thr: 0.3483 loss_db: 0.0826 2022/10/26 07:29:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:29:51 - mmengine - INFO - Epoch(train) [988][5/63] lr: 7.4346e-04 eta: 2:32:30 time: 0.6285 data_time: 0.1616 memory: 16131 loss: 0.9155 loss_prob: 0.4765 loss_thr: 0.3535 loss_db: 0.0855 2022/10/26 07:29:53 - mmengine - INFO - Epoch(train) [988][10/63] lr: 7.4346e-04 eta: 2:32:20 time: 0.6484 data_time: 0.1624 memory: 16131 loss: 0.8874 loss_prob: 0.4568 loss_thr: 0.3496 loss_db: 0.0810 2022/10/26 07:29:56 - mmengine - INFO - Epoch(train) [988][15/63] lr: 7.4346e-04 eta: 2:32:20 time: 0.4694 data_time: 0.0065 memory: 16131 loss: 0.9728 loss_prob: 0.5145 loss_thr: 0.3728 loss_db: 0.0855 2022/10/26 07:29:58 - mmengine - INFO - Epoch(train) [988][20/63] lr: 7.4346e-04 eta: 2:32:13 time: 0.4802 data_time: 0.0065 memory: 16131 loss: 1.0544 loss_prob: 0.5721 loss_thr: 0.3900 loss_db: 0.0923 2022/10/26 07:30:00 - mmengine - INFO - Epoch(train) [988][25/63] lr: 7.4346e-04 eta: 2:32:13 time: 0.4782 data_time: 0.0071 memory: 16131 loss: 0.9976 loss_prob: 0.5369 loss_thr: 0.3687 loss_db: 0.0921 2022/10/26 07:30:03 - mmengine - INFO - Epoch(train) [988][30/63] lr: 7.4346e-04 eta: 2:32:06 time: 0.5061 data_time: 0.0313 memory: 16131 loss: 0.9121 loss_prob: 0.4725 loss_thr: 0.3545 loss_db: 0.0850 2022/10/26 07:30:05 - mmengine - INFO - Epoch(train) [988][35/63] lr: 7.4346e-04 eta: 2:32:06 time: 0.5043 data_time: 0.0297 memory: 16131 loss: 0.9105 loss_prob: 0.4677 loss_thr: 0.3619 loss_db: 0.0808 2022/10/26 07:30:08 - mmengine - INFO - Epoch(train) [988][40/63] lr: 7.4346e-04 eta: 2:31:59 time: 0.5183 data_time: 0.0053 memory: 16131 loss: 0.9742 loss_prob: 0.5072 loss_thr: 0.3797 loss_db: 0.0873 2022/10/26 07:30:11 - mmengine - INFO - Epoch(train) [988][45/63] lr: 7.4346e-04 eta: 2:31:59 time: 0.5739 data_time: 0.0076 memory: 16131 loss: 0.9873 loss_prob: 0.5155 loss_thr: 0.3811 loss_db: 0.0907 2022/10/26 07:30:14 - mmengine - INFO - Epoch(train) [988][50/63] lr: 7.4346e-04 eta: 2:31:52 time: 0.5453 data_time: 0.0148 memory: 16131 loss: 1.0038 loss_prob: 0.5272 loss_thr: 0.3841 loss_db: 0.0924 2022/10/26 07:30:16 - mmengine - INFO - Epoch(train) [988][55/63] lr: 7.4346e-04 eta: 2:31:52 time: 0.5008 data_time: 0.0224 memory: 16131 loss: 1.0333 loss_prob: 0.5482 loss_thr: 0.3912 loss_db: 0.0939 2022/10/26 07:30:19 - mmengine - INFO - Epoch(train) [988][60/63] lr: 7.4346e-04 eta: 2:31:44 time: 0.5283 data_time: 0.0145 memory: 16131 loss: 0.9453 loss_prob: 0.4965 loss_thr: 0.3617 loss_db: 0.0871 2022/10/26 07:30:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:30:25 - mmengine - INFO - Epoch(train) [989][5/63] lr: 7.4031e-04 eta: 2:31:44 time: 0.7157 data_time: 0.1722 memory: 16131 loss: 0.9102 loss_prob: 0.4740 loss_thr: 0.3525 loss_db: 0.0838 2022/10/26 07:30:27 - mmengine - INFO - Epoch(train) [989][10/63] lr: 7.4031e-04 eta: 2:31:35 time: 0.7094 data_time: 0.1725 memory: 16131 loss: 0.8766 loss_prob: 0.4573 loss_thr: 0.3401 loss_db: 0.0792 2022/10/26 07:30:30 - mmengine - INFO - Epoch(train) [989][15/63] lr: 7.4031e-04 eta: 2:31:35 time: 0.5106 data_time: 0.0100 memory: 16131 loss: 0.9092 loss_prob: 0.4717 loss_thr: 0.3541 loss_db: 0.0834 2022/10/26 07:30:33 - mmengine - INFO - Epoch(train) [989][20/63] lr: 7.4031e-04 eta: 2:31:28 time: 0.5130 data_time: 0.0114 memory: 16131 loss: 0.9493 loss_prob: 0.4942 loss_thr: 0.3682 loss_db: 0.0869 2022/10/26 07:30:35 - mmengine - INFO - Epoch(train) [989][25/63] lr: 7.4031e-04 eta: 2:31:28 time: 0.5264 data_time: 0.0274 memory: 16131 loss: 1.0014 loss_prob: 0.5286 loss_thr: 0.3829 loss_db: 0.0899 2022/10/26 07:30:38 - mmengine - INFO - Epoch(train) [989][30/63] lr: 7.4031e-04 eta: 2:31:21 time: 0.5463 data_time: 0.0296 memory: 16131 loss: 1.0062 loss_prob: 0.5344 loss_thr: 0.3796 loss_db: 0.0922 2022/10/26 07:30:41 - mmengine - INFO - Epoch(train) [989][35/63] lr: 7.4031e-04 eta: 2:31:21 time: 0.5233 data_time: 0.0081 memory: 16131 loss: 0.9299 loss_prob: 0.4825 loss_thr: 0.3613 loss_db: 0.0860 2022/10/26 07:30:43 - mmengine - INFO - Epoch(train) [989][40/63] lr: 7.4031e-04 eta: 2:31:14 time: 0.5089 data_time: 0.0055 memory: 16131 loss: 0.9511 loss_prob: 0.4875 loss_thr: 0.3772 loss_db: 0.0864 2022/10/26 07:30:46 - mmengine - INFO - Epoch(train) [989][45/63] lr: 7.4031e-04 eta: 2:31:14 time: 0.5464 data_time: 0.0090 memory: 16131 loss: 0.9254 loss_prob: 0.4765 loss_thr: 0.3656 loss_db: 0.0832 2022/10/26 07:30:49 - mmengine - INFO - Epoch(train) [989][50/63] lr: 7.4031e-04 eta: 2:31:07 time: 0.5839 data_time: 0.0202 memory: 16131 loss: 0.8708 loss_prob: 0.4460 loss_thr: 0.3474 loss_db: 0.0774 2022/10/26 07:30:51 - mmengine - INFO - Epoch(train) [989][55/63] lr: 7.4031e-04 eta: 2:31:07 time: 0.5361 data_time: 0.0195 memory: 16131 loss: 0.8615 loss_prob: 0.4454 loss_thr: 0.3361 loss_db: 0.0799 2022/10/26 07:30:54 - mmengine - INFO - Epoch(train) [989][60/63] lr: 7.4031e-04 eta: 2:31:00 time: 0.5315 data_time: 0.0087 memory: 16131 loss: 0.8951 loss_prob: 0.4682 loss_thr: 0.3436 loss_db: 0.0833 2022/10/26 07:30:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:31:01 - mmengine - INFO - Epoch(train) [990][5/63] lr: 7.3715e-04 eta: 2:31:00 time: 0.7630 data_time: 0.2041 memory: 16131 loss: 0.9271 loss_prob: 0.4816 loss_thr: 0.3617 loss_db: 0.0837 2022/10/26 07:31:04 - mmengine - INFO - Epoch(train) [990][10/63] lr: 7.3715e-04 eta: 2:30:51 time: 0.7984 data_time: 0.2095 memory: 16131 loss: 0.8953 loss_prob: 0.4590 loss_thr: 0.3553 loss_db: 0.0810 2022/10/26 07:31:06 - mmengine - INFO - Epoch(train) [990][15/63] lr: 7.3715e-04 eta: 2:30:51 time: 0.5458 data_time: 0.0148 memory: 16131 loss: 0.9062 loss_prob: 0.4642 loss_thr: 0.3609 loss_db: 0.0811 2022/10/26 07:31:09 - mmengine - INFO - Epoch(train) [990][20/63] lr: 7.3715e-04 eta: 2:30:43 time: 0.5593 data_time: 0.0070 memory: 16131 loss: 0.9516 loss_prob: 0.4932 loss_thr: 0.3716 loss_db: 0.0868 2022/10/26 07:31:12 - mmengine - INFO - Epoch(train) [990][25/63] lr: 7.3715e-04 eta: 2:30:43 time: 0.5373 data_time: 0.0301 memory: 16131 loss: 0.9915 loss_prob: 0.5265 loss_thr: 0.3736 loss_db: 0.0914 2022/10/26 07:31:14 - mmengine - INFO - Epoch(train) [990][30/63] lr: 7.3715e-04 eta: 2:30:36 time: 0.5090 data_time: 0.0316 memory: 16131 loss: 0.9607 loss_prob: 0.5080 loss_thr: 0.3640 loss_db: 0.0887 2022/10/26 07:31:17 - mmengine - INFO - Epoch(train) [990][35/63] lr: 7.3715e-04 eta: 2:30:36 time: 0.5089 data_time: 0.0159 memory: 16131 loss: 0.9048 loss_prob: 0.4756 loss_thr: 0.3452 loss_db: 0.0840 2022/10/26 07:31:19 - mmengine - INFO - Epoch(train) [990][40/63] lr: 7.3715e-04 eta: 2:30:29 time: 0.5288 data_time: 0.0159 memory: 16131 loss: 0.9674 loss_prob: 0.5166 loss_thr: 0.3621 loss_db: 0.0888 2022/10/26 07:31:22 - mmengine - INFO - Epoch(train) [990][45/63] lr: 7.3715e-04 eta: 2:30:29 time: 0.5122 data_time: 0.0063 memory: 16131 loss: 0.9607 loss_prob: 0.5122 loss_thr: 0.3618 loss_db: 0.0866 2022/10/26 07:31:26 - mmengine - INFO - Epoch(train) [990][50/63] lr: 7.3715e-04 eta: 2:30:22 time: 0.6660 data_time: 0.0181 memory: 16131 loss: 0.8854 loss_prob: 0.4589 loss_thr: 0.3478 loss_db: 0.0787 2022/10/26 07:31:29 - mmengine - INFO - Epoch(train) [990][55/63] lr: 7.3715e-04 eta: 2:30:22 time: 0.6750 data_time: 0.0216 memory: 16131 loss: 0.8806 loss_prob: 0.4551 loss_thr: 0.3451 loss_db: 0.0803 2022/10/26 07:31:31 - mmengine - INFO - Epoch(train) [990][60/63] lr: 7.3715e-04 eta: 2:30:15 time: 0.5092 data_time: 0.0096 memory: 16131 loss: 0.8827 loss_prob: 0.4601 loss_thr: 0.3417 loss_db: 0.0809 2022/10/26 07:31:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:31:37 - mmengine - INFO - Epoch(train) [991][5/63] lr: 7.3399e-04 eta: 2:30:15 time: 0.6665 data_time: 0.1667 memory: 16131 loss: 0.8900 loss_prob: 0.4508 loss_thr: 0.3623 loss_db: 0.0768 2022/10/26 07:31:40 - mmengine - INFO - Epoch(train) [991][10/63] lr: 7.3399e-04 eta: 2:30:06 time: 0.7122 data_time: 0.1670 memory: 16131 loss: 0.9707 loss_prob: 0.5072 loss_thr: 0.3760 loss_db: 0.0875 2022/10/26 07:31:42 - mmengine - INFO - Epoch(train) [991][15/63] lr: 7.3399e-04 eta: 2:30:06 time: 0.5162 data_time: 0.0055 memory: 16131 loss: 1.0471 loss_prob: 0.5623 loss_thr: 0.3901 loss_db: 0.0947 2022/10/26 07:31:45 - mmengine - INFO - Epoch(train) [991][20/63] lr: 7.3399e-04 eta: 2:29:59 time: 0.5213 data_time: 0.0052 memory: 16131 loss: 1.0261 loss_prob: 0.5510 loss_thr: 0.3827 loss_db: 0.0924 2022/10/26 07:31:48 - mmengine - INFO - Epoch(train) [991][25/63] lr: 7.3399e-04 eta: 2:29:59 time: 0.5434 data_time: 0.0090 memory: 16131 loss: 0.9200 loss_prob: 0.4830 loss_thr: 0.3504 loss_db: 0.0866 2022/10/26 07:31:50 - mmengine - INFO - Epoch(train) [991][30/63] lr: 7.3399e-04 eta: 2:29:52 time: 0.5472 data_time: 0.0359 memory: 16131 loss: 0.8851 loss_prob: 0.4551 loss_thr: 0.3485 loss_db: 0.0815 2022/10/26 07:31:53 - mmengine - INFO - Epoch(train) [991][35/63] lr: 7.3399e-04 eta: 2:29:52 time: 0.5403 data_time: 0.0327 memory: 16131 loss: 0.8907 loss_prob: 0.4643 loss_thr: 0.3471 loss_db: 0.0793 2022/10/26 07:31:55 - mmengine - INFO - Epoch(train) [991][40/63] lr: 7.3399e-04 eta: 2:29:45 time: 0.5156 data_time: 0.0053 memory: 16131 loss: 1.0172 loss_prob: 0.5645 loss_thr: 0.3592 loss_db: 0.0935 2022/10/26 07:31:58 - mmengine - INFO - Epoch(train) [991][45/63] lr: 7.3399e-04 eta: 2:29:45 time: 0.5124 data_time: 0.0046 memory: 16131 loss: 0.9256 loss_prob: 0.5046 loss_thr: 0.3365 loss_db: 0.0845 2022/10/26 07:32:01 - mmengine - INFO - Epoch(train) [991][50/63] lr: 7.3399e-04 eta: 2:29:37 time: 0.5582 data_time: 0.0107 memory: 16131 loss: 0.8105 loss_prob: 0.4156 loss_thr: 0.3220 loss_db: 0.0729 2022/10/26 07:32:04 - mmengine - INFO - Epoch(train) [991][55/63] lr: 7.3399e-04 eta: 2:29:37 time: 0.5799 data_time: 0.0260 memory: 16131 loss: 0.8636 loss_prob: 0.4482 loss_thr: 0.3382 loss_db: 0.0772 2022/10/26 07:32:06 - mmengine - INFO - Epoch(train) [991][60/63] lr: 7.3399e-04 eta: 2:29:30 time: 0.5268 data_time: 0.0220 memory: 16131 loss: 0.8530 loss_prob: 0.4378 loss_thr: 0.3389 loss_db: 0.0763 2022/10/26 07:32:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:32:13 - mmengine - INFO - Epoch(train) [992][5/63] lr: 7.3083e-04 eta: 2:29:30 time: 0.7396 data_time: 0.1830 memory: 16131 loss: 0.8732 loss_prob: 0.4515 loss_thr: 0.3415 loss_db: 0.0801 2022/10/26 07:32:15 - mmengine - INFO - Epoch(train) [992][10/63] lr: 7.3083e-04 eta: 2:29:21 time: 0.7663 data_time: 0.1858 memory: 16131 loss: 0.8881 loss_prob: 0.4581 loss_thr: 0.3493 loss_db: 0.0807 2022/10/26 07:32:18 - mmengine - INFO - Epoch(train) [992][15/63] lr: 7.3083e-04 eta: 2:29:21 time: 0.5157 data_time: 0.0084 memory: 16131 loss: 0.9075 loss_prob: 0.4691 loss_thr: 0.3588 loss_db: 0.0796 2022/10/26 07:32:20 - mmengine - INFO - Epoch(train) [992][20/63] lr: 7.3083e-04 eta: 2:29:14 time: 0.5108 data_time: 0.0070 memory: 16131 loss: 0.9443 loss_prob: 0.4928 loss_thr: 0.3668 loss_db: 0.0847 2022/10/26 07:32:23 - mmengine - INFO - Epoch(train) [992][25/63] lr: 7.3083e-04 eta: 2:29:14 time: 0.5397 data_time: 0.0395 memory: 16131 loss: 0.9841 loss_prob: 0.5144 loss_thr: 0.3789 loss_db: 0.0908 2022/10/26 07:32:26 - mmengine - INFO - Epoch(train) [992][30/63] lr: 7.3083e-04 eta: 2:29:07 time: 0.5331 data_time: 0.0485 memory: 16131 loss: 1.0373 loss_prob: 0.5490 loss_thr: 0.3941 loss_db: 0.0942 2022/10/26 07:32:28 - mmengine - INFO - Epoch(train) [992][35/63] lr: 7.3083e-04 eta: 2:29:07 time: 0.4992 data_time: 0.0166 memory: 16131 loss: 0.8901 loss_prob: 0.4611 loss_thr: 0.3493 loss_db: 0.0797 2022/10/26 07:32:31 - mmengine - INFO - Epoch(train) [992][40/63] lr: 7.3083e-04 eta: 2:29:00 time: 0.5149 data_time: 0.0061 memory: 16131 loss: 0.8459 loss_prob: 0.4306 loss_thr: 0.3372 loss_db: 0.0781 2022/10/26 07:32:33 - mmengine - INFO - Epoch(train) [992][45/63] lr: 7.3083e-04 eta: 2:29:00 time: 0.5134 data_time: 0.0054 memory: 16131 loss: 0.9612 loss_prob: 0.5009 loss_thr: 0.3710 loss_db: 0.0894 2022/10/26 07:32:36 - mmengine - INFO - Epoch(train) [992][50/63] lr: 7.3083e-04 eta: 2:28:53 time: 0.5084 data_time: 0.0166 memory: 16131 loss: 0.9945 loss_prob: 0.5308 loss_thr: 0.3721 loss_db: 0.0916 2022/10/26 07:32:39 - mmengine - INFO - Epoch(train) [992][55/63] lr: 7.3083e-04 eta: 2:28:53 time: 0.5263 data_time: 0.0239 memory: 16131 loss: 0.9730 loss_prob: 0.5276 loss_thr: 0.3560 loss_db: 0.0894 2022/10/26 07:32:41 - mmengine - INFO - Epoch(train) [992][60/63] lr: 7.3083e-04 eta: 2:28:45 time: 0.5284 data_time: 0.0132 memory: 16131 loss: 0.9596 loss_prob: 0.5146 loss_thr: 0.3559 loss_db: 0.0891 2022/10/26 07:32:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:32:48 - mmengine - INFO - Epoch(train) [993][5/63] lr: 7.2766e-04 eta: 2:28:45 time: 0.7483 data_time: 0.2020 memory: 16131 loss: 1.0399 loss_prob: 0.5667 loss_thr: 0.3766 loss_db: 0.0965 2022/10/26 07:32:50 - mmengine - INFO - Epoch(train) [993][10/63] lr: 7.2766e-04 eta: 2:28:36 time: 0.7752 data_time: 0.2031 memory: 16131 loss: 1.0434 loss_prob: 0.5657 loss_thr: 0.3804 loss_db: 0.0974 2022/10/26 07:32:53 - mmengine - INFO - Epoch(train) [993][15/63] lr: 7.2766e-04 eta: 2:28:36 time: 0.5038 data_time: 0.0060 memory: 16131 loss: 0.9568 loss_prob: 0.5014 loss_thr: 0.3677 loss_db: 0.0876 2022/10/26 07:32:55 - mmengine - INFO - Epoch(train) [993][20/63] lr: 7.2766e-04 eta: 2:28:29 time: 0.5137 data_time: 0.0078 memory: 16131 loss: 0.9645 loss_prob: 0.5030 loss_thr: 0.3716 loss_db: 0.0899 2022/10/26 07:32:58 - mmengine - INFO - Epoch(train) [993][25/63] lr: 7.2766e-04 eta: 2:28:29 time: 0.5295 data_time: 0.0378 memory: 16131 loss: 1.0013 loss_prob: 0.5234 loss_thr: 0.3855 loss_db: 0.0924 2022/10/26 07:33:01 - mmengine - INFO - Epoch(train) [993][30/63] lr: 7.2766e-04 eta: 2:28:22 time: 0.5226 data_time: 0.0350 memory: 16131 loss: 0.9309 loss_prob: 0.4811 loss_thr: 0.3671 loss_db: 0.0827 2022/10/26 07:33:03 - mmengine - INFO - Epoch(train) [993][35/63] lr: 7.2766e-04 eta: 2:28:22 time: 0.4939 data_time: 0.0060 memory: 16131 loss: 0.8810 loss_prob: 0.4617 loss_thr: 0.3391 loss_db: 0.0802 2022/10/26 07:33:06 - mmengine - INFO - Epoch(train) [993][40/63] lr: 7.2766e-04 eta: 2:28:15 time: 0.4887 data_time: 0.0064 memory: 16131 loss: 0.9599 loss_prob: 0.5140 loss_thr: 0.3565 loss_db: 0.0894 2022/10/26 07:33:09 - mmengine - INFO - Epoch(train) [993][45/63] lr: 7.2766e-04 eta: 2:28:15 time: 0.5703 data_time: 0.0069 memory: 16131 loss: 0.9553 loss_prob: 0.5031 loss_thr: 0.3656 loss_db: 0.0866 2022/10/26 07:33:12 - mmengine - INFO - Epoch(train) [993][50/63] lr: 7.2766e-04 eta: 2:28:08 time: 0.6196 data_time: 0.0283 memory: 16131 loss: 0.9124 loss_prob: 0.4825 loss_thr: 0.3472 loss_db: 0.0827 2022/10/26 07:33:14 - mmengine - INFO - Epoch(train) [993][55/63] lr: 7.2766e-04 eta: 2:28:08 time: 0.5301 data_time: 0.0264 memory: 16131 loss: 0.8824 loss_prob: 0.4652 loss_thr: 0.3385 loss_db: 0.0786 2022/10/26 07:33:17 - mmengine - INFO - Epoch(train) [993][60/63] lr: 7.2766e-04 eta: 2:28:01 time: 0.5369 data_time: 0.0049 memory: 16131 loss: 0.8814 loss_prob: 0.4536 loss_thr: 0.3501 loss_db: 0.0777 2022/10/26 07:33:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:33:23 - mmengine - INFO - Epoch(train) [994][5/63] lr: 7.2450e-04 eta: 2:28:01 time: 0.7578 data_time: 0.1870 memory: 16131 loss: 0.9733 loss_prob: 0.5163 loss_thr: 0.3682 loss_db: 0.0889 2022/10/26 07:33:26 - mmengine - INFO - Epoch(train) [994][10/63] lr: 7.2450e-04 eta: 2:27:52 time: 0.7569 data_time: 0.1864 memory: 16131 loss: 0.9951 loss_prob: 0.5288 loss_thr: 0.3755 loss_db: 0.0908 2022/10/26 07:33:28 - mmengine - INFO - Epoch(train) [994][15/63] lr: 7.2450e-04 eta: 2:27:52 time: 0.5127 data_time: 0.0047 memory: 16131 loss: 0.9324 loss_prob: 0.4873 loss_thr: 0.3617 loss_db: 0.0834 2022/10/26 07:33:31 - mmengine - INFO - Epoch(train) [994][20/63] lr: 7.2450e-04 eta: 2:27:44 time: 0.4880 data_time: 0.0078 memory: 16131 loss: 0.9584 loss_prob: 0.5052 loss_thr: 0.3663 loss_db: 0.0869 2022/10/26 07:33:34 - mmengine - INFO - Epoch(train) [994][25/63] lr: 7.2450e-04 eta: 2:27:44 time: 0.5164 data_time: 0.0333 memory: 16131 loss: 0.9064 loss_prob: 0.4748 loss_thr: 0.3473 loss_db: 0.0843 2022/10/26 07:33:36 - mmengine - INFO - Epoch(train) [994][30/63] lr: 7.2450e-04 eta: 2:27:37 time: 0.5440 data_time: 0.0338 memory: 16131 loss: 0.8558 loss_prob: 0.4420 loss_thr: 0.3348 loss_db: 0.0789 2022/10/26 07:33:39 - mmengine - INFO - Epoch(train) [994][35/63] lr: 7.2450e-04 eta: 2:27:37 time: 0.5296 data_time: 0.0084 memory: 16131 loss: 0.9293 loss_prob: 0.4967 loss_thr: 0.3507 loss_db: 0.0819 2022/10/26 07:33:42 - mmengine - INFO - Epoch(train) [994][40/63] lr: 7.2450e-04 eta: 2:27:30 time: 0.5333 data_time: 0.0065 memory: 16131 loss: 0.9179 loss_prob: 0.4851 loss_thr: 0.3538 loss_db: 0.0790 2022/10/26 07:33:44 - mmengine - INFO - Epoch(train) [994][45/63] lr: 7.2450e-04 eta: 2:27:30 time: 0.5221 data_time: 0.0078 memory: 16131 loss: 0.8823 loss_prob: 0.4531 loss_thr: 0.3511 loss_db: 0.0781 2022/10/26 07:33:47 - mmengine - INFO - Epoch(train) [994][50/63] lr: 7.2450e-04 eta: 2:27:23 time: 0.5324 data_time: 0.0242 memory: 16131 loss: 0.9461 loss_prob: 0.5014 loss_thr: 0.3568 loss_db: 0.0879 2022/10/26 07:33:50 - mmengine - INFO - Epoch(train) [994][55/63] lr: 7.2450e-04 eta: 2:27:23 time: 0.5468 data_time: 0.0243 memory: 16131 loss: 0.9388 loss_prob: 0.4955 loss_thr: 0.3551 loss_db: 0.0882 2022/10/26 07:33:52 - mmengine - INFO - Epoch(train) [994][60/63] lr: 7.2450e-04 eta: 2:27:16 time: 0.5090 data_time: 0.0061 memory: 16131 loss: 0.8792 loss_prob: 0.4588 loss_thr: 0.3396 loss_db: 0.0809 2022/10/26 07:33:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:33:59 - mmengine - INFO - Epoch(train) [995][5/63] lr: 7.2133e-04 eta: 2:27:16 time: 0.7590 data_time: 0.1836 memory: 16131 loss: 0.8619 loss_prob: 0.4461 loss_thr: 0.3387 loss_db: 0.0771 2022/10/26 07:34:01 - mmengine - INFO - Epoch(train) [995][10/63] lr: 7.2133e-04 eta: 2:27:07 time: 0.7461 data_time: 0.1836 memory: 16131 loss: 0.9438 loss_prob: 0.4879 loss_thr: 0.3702 loss_db: 0.0856 2022/10/26 07:34:04 - mmengine - INFO - Epoch(train) [995][15/63] lr: 7.2133e-04 eta: 2:27:07 time: 0.4922 data_time: 0.0099 memory: 16131 loss: 0.9840 loss_prob: 0.5180 loss_thr: 0.3756 loss_db: 0.0905 2022/10/26 07:34:06 - mmengine - INFO - Epoch(train) [995][20/63] lr: 7.2133e-04 eta: 2:27:00 time: 0.5106 data_time: 0.0095 memory: 16131 loss: 0.9934 loss_prob: 0.5377 loss_thr: 0.3657 loss_db: 0.0900 2022/10/26 07:34:09 - mmengine - INFO - Epoch(train) [995][25/63] lr: 7.2133e-04 eta: 2:27:00 time: 0.5242 data_time: 0.0150 memory: 16131 loss: 0.9758 loss_prob: 0.5244 loss_thr: 0.3643 loss_db: 0.0871 2022/10/26 07:34:12 - mmengine - INFO - Epoch(train) [995][30/63] lr: 7.2133e-04 eta: 2:26:53 time: 0.5407 data_time: 0.0386 memory: 16131 loss: 0.8827 loss_prob: 0.4550 loss_thr: 0.3487 loss_db: 0.0790 2022/10/26 07:34:14 - mmengine - INFO - Epoch(train) [995][35/63] lr: 7.2133e-04 eta: 2:26:53 time: 0.5313 data_time: 0.0295 memory: 16131 loss: 0.8652 loss_prob: 0.4366 loss_thr: 0.3519 loss_db: 0.0766 2022/10/26 07:34:17 - mmengine - INFO - Epoch(train) [995][40/63] lr: 7.2133e-04 eta: 2:26:45 time: 0.5033 data_time: 0.0101 memory: 16131 loss: 0.9516 loss_prob: 0.4951 loss_thr: 0.3693 loss_db: 0.0872 2022/10/26 07:34:19 - mmengine - INFO - Epoch(train) [995][45/63] lr: 7.2133e-04 eta: 2:26:45 time: 0.5139 data_time: 0.0087 memory: 16131 loss: 0.9555 loss_prob: 0.5055 loss_thr: 0.3608 loss_db: 0.0893 2022/10/26 07:34:22 - mmengine - INFO - Epoch(train) [995][50/63] lr: 7.2133e-04 eta: 2:26:38 time: 0.5189 data_time: 0.0154 memory: 16131 loss: 0.9187 loss_prob: 0.4842 loss_thr: 0.3494 loss_db: 0.0851 2022/10/26 07:34:25 - mmengine - INFO - Epoch(train) [995][55/63] lr: 7.2133e-04 eta: 2:26:38 time: 0.5246 data_time: 0.0230 memory: 16131 loss: 0.8263 loss_prob: 0.4279 loss_thr: 0.3221 loss_db: 0.0762 2022/10/26 07:34:27 - mmengine - INFO - Epoch(train) [995][60/63] lr: 7.2133e-04 eta: 2:26:31 time: 0.5140 data_time: 0.0143 memory: 16131 loss: 0.8293 loss_prob: 0.4260 loss_thr: 0.3296 loss_db: 0.0737 2022/10/26 07:34:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:34:33 - mmengine - INFO - Epoch(train) [996][5/63] lr: 7.1817e-04 eta: 2:26:31 time: 0.7342 data_time: 0.1885 memory: 16131 loss: 1.0037 loss_prob: 0.5334 loss_thr: 0.3795 loss_db: 0.0907 2022/10/26 07:34:36 - mmengine - INFO - Epoch(train) [996][10/63] lr: 7.1817e-04 eta: 2:26:22 time: 0.7789 data_time: 0.1954 memory: 16131 loss: 0.9689 loss_prob: 0.5125 loss_thr: 0.3677 loss_db: 0.0887 2022/10/26 07:34:39 - mmengine - INFO - Epoch(train) [996][15/63] lr: 7.1817e-04 eta: 2:26:22 time: 0.5305 data_time: 0.0154 memory: 16131 loss: 0.9386 loss_prob: 0.4897 loss_thr: 0.3637 loss_db: 0.0852 2022/10/26 07:34:41 - mmengine - INFO - Epoch(train) [996][20/63] lr: 7.1817e-04 eta: 2:26:15 time: 0.5319 data_time: 0.0049 memory: 16131 loss: 0.9619 loss_prob: 0.5027 loss_thr: 0.3726 loss_db: 0.0866 2022/10/26 07:34:44 - mmengine - INFO - Epoch(train) [996][25/63] lr: 7.1817e-04 eta: 2:26:15 time: 0.5574 data_time: 0.0121 memory: 16131 loss: 0.9887 loss_prob: 0.5298 loss_thr: 0.3690 loss_db: 0.0898 2022/10/26 07:34:47 - mmengine - INFO - Epoch(train) [996][30/63] lr: 7.1817e-04 eta: 2:26:08 time: 0.5488 data_time: 0.0324 memory: 16131 loss: 0.9479 loss_prob: 0.5035 loss_thr: 0.3567 loss_db: 0.0877 2022/10/26 07:34:50 - mmengine - INFO - Epoch(train) [996][35/63] lr: 7.1817e-04 eta: 2:26:08 time: 0.5282 data_time: 0.0247 memory: 16131 loss: 0.9171 loss_prob: 0.4729 loss_thr: 0.3597 loss_db: 0.0846 2022/10/26 07:34:52 - mmengine - INFO - Epoch(train) [996][40/63] lr: 7.1817e-04 eta: 2:26:01 time: 0.5083 data_time: 0.0042 memory: 16131 loss: 0.8760 loss_prob: 0.4481 loss_thr: 0.3475 loss_db: 0.0804 2022/10/26 07:34:55 - mmengine - INFO - Epoch(train) [996][45/63] lr: 7.1817e-04 eta: 2:26:01 time: 0.5046 data_time: 0.0045 memory: 16131 loss: 0.8423 loss_prob: 0.4352 loss_thr: 0.3313 loss_db: 0.0758 2022/10/26 07:34:57 - mmengine - INFO - Epoch(train) [996][50/63] lr: 7.1817e-04 eta: 2:25:54 time: 0.5077 data_time: 0.0095 memory: 16131 loss: 0.9054 loss_prob: 0.4774 loss_thr: 0.3463 loss_db: 0.0816 2022/10/26 07:35:00 - mmengine - INFO - Epoch(train) [996][55/63] lr: 7.1817e-04 eta: 2:25:54 time: 0.5119 data_time: 0.0208 memory: 16131 loss: 0.9550 loss_prob: 0.5098 loss_thr: 0.3562 loss_db: 0.0890 2022/10/26 07:35:02 - mmengine - INFO - Epoch(train) [996][60/63] lr: 7.1817e-04 eta: 2:25:46 time: 0.5189 data_time: 0.0158 memory: 16131 loss: 0.9482 loss_prob: 0.5000 loss_thr: 0.3597 loss_db: 0.0885 2022/10/26 07:35:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:35:08 - mmengine - INFO - Epoch(train) [997][5/63] lr: 7.1500e-04 eta: 2:25:46 time: 0.6988 data_time: 0.1972 memory: 16131 loss: 0.9666 loss_prob: 0.5223 loss_thr: 0.3556 loss_db: 0.0886 2022/10/26 07:35:11 - mmengine - INFO - Epoch(train) [997][10/63] lr: 7.1500e-04 eta: 2:25:37 time: 0.7713 data_time: 0.1994 memory: 16131 loss: 0.9542 loss_prob: 0.5097 loss_thr: 0.3561 loss_db: 0.0884 2022/10/26 07:35:14 - mmengine - INFO - Epoch(train) [997][15/63] lr: 7.1500e-04 eta: 2:25:37 time: 0.5479 data_time: 0.0081 memory: 16131 loss: 0.8900 loss_prob: 0.4588 loss_thr: 0.3495 loss_db: 0.0817 2022/10/26 07:35:16 - mmengine - INFO - Epoch(train) [997][20/63] lr: 7.1500e-04 eta: 2:25:30 time: 0.5153 data_time: 0.0091 memory: 16131 loss: 0.8682 loss_prob: 0.4486 loss_thr: 0.3414 loss_db: 0.0783 2022/10/26 07:35:19 - mmengine - INFO - Epoch(train) [997][25/63] lr: 7.1500e-04 eta: 2:25:30 time: 0.5334 data_time: 0.0248 memory: 16131 loss: 0.9123 loss_prob: 0.4780 loss_thr: 0.3545 loss_db: 0.0798 2022/10/26 07:35:22 - mmengine - INFO - Epoch(train) [997][30/63] lr: 7.1500e-04 eta: 2:25:23 time: 0.5543 data_time: 0.0380 memory: 16131 loss: 0.9856 loss_prob: 0.5194 loss_thr: 0.3790 loss_db: 0.0872 2022/10/26 07:35:24 - mmengine - INFO - Epoch(train) [997][35/63] lr: 7.1500e-04 eta: 2:25:23 time: 0.5219 data_time: 0.0210 memory: 16131 loss: 0.9301 loss_prob: 0.4749 loss_thr: 0.3722 loss_db: 0.0830 2022/10/26 07:35:27 - mmengine - INFO - Epoch(train) [997][40/63] lr: 7.1500e-04 eta: 2:25:16 time: 0.4914 data_time: 0.0100 memory: 16131 loss: 0.9571 loss_prob: 0.4944 loss_thr: 0.3768 loss_db: 0.0859 2022/10/26 07:35:29 - mmengine - INFO - Epoch(train) [997][45/63] lr: 7.1500e-04 eta: 2:25:16 time: 0.5123 data_time: 0.0106 memory: 16131 loss: 0.9968 loss_prob: 0.5307 loss_thr: 0.3776 loss_db: 0.0886 2022/10/26 07:35:32 - mmengine - INFO - Epoch(train) [997][50/63] lr: 7.1500e-04 eta: 2:25:09 time: 0.5536 data_time: 0.0222 memory: 16131 loss: 0.9757 loss_prob: 0.5202 loss_thr: 0.3696 loss_db: 0.0860 2022/10/26 07:35:35 - mmengine - INFO - Epoch(train) [997][55/63] lr: 7.1500e-04 eta: 2:25:09 time: 0.5741 data_time: 0.0214 memory: 16131 loss: 0.9688 loss_prob: 0.5119 loss_thr: 0.3685 loss_db: 0.0884 2022/10/26 07:35:38 - mmengine - INFO - Epoch(train) [997][60/63] lr: 7.1500e-04 eta: 2:25:02 time: 0.5369 data_time: 0.0050 memory: 16131 loss: 0.9766 loss_prob: 0.5149 loss_thr: 0.3738 loss_db: 0.0879 2022/10/26 07:35:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:35:44 - mmengine - INFO - Epoch(train) [998][5/63] lr: 7.1183e-04 eta: 2:25:02 time: 0.7239 data_time: 0.2245 memory: 16131 loss: 0.9412 loss_prob: 0.4969 loss_thr: 0.3605 loss_db: 0.0839 2022/10/26 07:35:47 - mmengine - INFO - Epoch(train) [998][10/63] lr: 7.1183e-04 eta: 2:24:53 time: 0.8190 data_time: 0.2261 memory: 16131 loss: 0.9513 loss_prob: 0.4992 loss_thr: 0.3650 loss_db: 0.0871 2022/10/26 07:35:50 - mmengine - INFO - Epoch(train) [998][15/63] lr: 7.1183e-04 eta: 2:24:53 time: 0.5680 data_time: 0.0088 memory: 16131 loss: 1.0262 loss_prob: 0.5447 loss_thr: 0.3860 loss_db: 0.0955 2022/10/26 07:35:52 - mmengine - INFO - Epoch(train) [998][20/63] lr: 7.1183e-04 eta: 2:24:46 time: 0.5008 data_time: 0.0080 memory: 16131 loss: 0.9692 loss_prob: 0.5168 loss_thr: 0.3628 loss_db: 0.0896 2022/10/26 07:35:55 - mmengine - INFO - Epoch(train) [998][25/63] lr: 7.1183e-04 eta: 2:24:46 time: 0.5263 data_time: 0.0347 memory: 16131 loss: 0.8659 loss_prob: 0.4511 loss_thr: 0.3353 loss_db: 0.0795 2022/10/26 07:35:57 - mmengine - INFO - Epoch(train) [998][30/63] lr: 7.1183e-04 eta: 2:24:39 time: 0.5212 data_time: 0.0335 memory: 16131 loss: 0.9008 loss_prob: 0.4742 loss_thr: 0.3437 loss_db: 0.0828 2022/10/26 07:36:00 - mmengine - INFO - Epoch(train) [998][35/63] lr: 7.1183e-04 eta: 2:24:39 time: 0.4978 data_time: 0.0090 memory: 16131 loss: 0.9441 loss_prob: 0.5005 loss_thr: 0.3582 loss_db: 0.0854 2022/10/26 07:36:03 - mmengine - INFO - Epoch(train) [998][40/63] lr: 7.1183e-04 eta: 2:24:31 time: 0.5486 data_time: 0.0095 memory: 16131 loss: 0.9634 loss_prob: 0.5063 loss_thr: 0.3698 loss_db: 0.0873 2022/10/26 07:36:06 - mmengine - INFO - Epoch(train) [998][45/63] lr: 7.1183e-04 eta: 2:24:31 time: 0.5803 data_time: 0.0064 memory: 16131 loss: 0.9122 loss_prob: 0.4773 loss_thr: 0.3507 loss_db: 0.0842 2022/10/26 07:36:09 - mmengine - INFO - Epoch(train) [998][50/63] lr: 7.1183e-04 eta: 2:24:24 time: 0.5797 data_time: 0.0235 memory: 16131 loss: 0.8506 loss_prob: 0.4425 loss_thr: 0.3301 loss_db: 0.0780 2022/10/26 07:36:11 - mmengine - INFO - Epoch(train) [998][55/63] lr: 7.1183e-04 eta: 2:24:24 time: 0.5590 data_time: 0.0226 memory: 16131 loss: 0.9029 loss_prob: 0.4681 loss_thr: 0.3528 loss_db: 0.0820 2022/10/26 07:36:14 - mmengine - INFO - Epoch(train) [998][60/63] lr: 7.1183e-04 eta: 2:24:17 time: 0.5221 data_time: 0.0070 memory: 16131 loss: 0.9587 loss_prob: 0.4993 loss_thr: 0.3718 loss_db: 0.0876 2022/10/26 07:36:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:36:20 - mmengine - INFO - Epoch(train) [999][5/63] lr: 7.0866e-04 eta: 2:24:17 time: 0.6768 data_time: 0.1694 memory: 16131 loss: 0.9212 loss_prob: 0.4868 loss_thr: 0.3495 loss_db: 0.0849 2022/10/26 07:36:22 - mmengine - INFO - Epoch(train) [999][10/63] lr: 7.0866e-04 eta: 2:24:08 time: 0.7154 data_time: 0.1734 memory: 16131 loss: 0.8753 loss_prob: 0.4577 loss_thr: 0.3359 loss_db: 0.0817 2022/10/26 07:36:25 - mmengine - INFO - Epoch(train) [999][15/63] lr: 7.0866e-04 eta: 2:24:08 time: 0.5283 data_time: 0.0121 memory: 16131 loss: 0.8550 loss_prob: 0.4374 loss_thr: 0.3401 loss_db: 0.0774 2022/10/26 07:36:28 - mmengine - INFO - Epoch(train) [999][20/63] lr: 7.0866e-04 eta: 2:24:01 time: 0.5560 data_time: 0.0115 memory: 16131 loss: 0.8790 loss_prob: 0.4540 loss_thr: 0.3466 loss_db: 0.0784 2022/10/26 07:36:31 - mmengine - INFO - Epoch(train) [999][25/63] lr: 7.0866e-04 eta: 2:24:01 time: 0.5954 data_time: 0.0209 memory: 16131 loss: 0.9009 loss_prob: 0.4734 loss_thr: 0.3457 loss_db: 0.0818 2022/10/26 07:36:33 - mmengine - INFO - Epoch(train) [999][30/63] lr: 7.0866e-04 eta: 2:23:54 time: 0.5654 data_time: 0.0291 memory: 16131 loss: 0.8770 loss_prob: 0.4630 loss_thr: 0.3342 loss_db: 0.0798 2022/10/26 07:36:36 - mmengine - INFO - Epoch(train) [999][35/63] lr: 7.0866e-04 eta: 2:23:54 time: 0.5154 data_time: 0.0217 memory: 16131 loss: 0.9048 loss_prob: 0.4726 loss_thr: 0.3490 loss_db: 0.0832 2022/10/26 07:36:38 - mmengine - INFO - Epoch(train) [999][40/63] lr: 7.0866e-04 eta: 2:23:47 time: 0.4973 data_time: 0.0095 memory: 16131 loss: 0.9232 loss_prob: 0.4758 loss_thr: 0.3638 loss_db: 0.0836 2022/10/26 07:36:41 - mmengine - INFO - Epoch(train) [999][45/63] lr: 7.0866e-04 eta: 2:23:47 time: 0.4988 data_time: 0.0086 memory: 16131 loss: 0.9536 loss_prob: 0.4875 loss_thr: 0.3833 loss_db: 0.0828 2022/10/26 07:36:44 - mmengine - INFO - Epoch(train) [999][50/63] lr: 7.0866e-04 eta: 2:23:40 time: 0.5153 data_time: 0.0143 memory: 16131 loss: 1.0065 loss_prob: 0.5209 loss_thr: 0.3964 loss_db: 0.0892 2022/10/26 07:36:46 - mmengine - INFO - Epoch(train) [999][55/63] lr: 7.0866e-04 eta: 2:23:40 time: 0.5098 data_time: 0.0195 memory: 16131 loss: 0.9162 loss_prob: 0.4801 loss_thr: 0.3533 loss_db: 0.0827 2022/10/26 07:36:49 - mmengine - INFO - Epoch(train) [999][60/63] lr: 7.0866e-04 eta: 2:23:33 time: 0.5069 data_time: 0.0209 memory: 16131 loss: 0.8683 loss_prob: 0.4507 loss_thr: 0.3386 loss_db: 0.0791 2022/10/26 07:36:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:36:55 - mmengine - INFO - Epoch(train) [1000][5/63] lr: 7.0548e-04 eta: 2:23:33 time: 0.7105 data_time: 0.1886 memory: 16131 loss: 0.9520 loss_prob: 0.4929 loss_thr: 0.3728 loss_db: 0.0862 2022/10/26 07:36:57 - mmengine - INFO - Epoch(train) [1000][10/63] lr: 7.0548e-04 eta: 2:23:23 time: 0.7258 data_time: 0.1880 memory: 16131 loss: 0.9181 loss_prob: 0.4747 loss_thr: 0.3592 loss_db: 0.0842 2022/10/26 07:37:00 - mmengine - INFO - Epoch(train) [1000][15/63] lr: 7.0548e-04 eta: 2:23:23 time: 0.5001 data_time: 0.0090 memory: 16131 loss: 0.8954 loss_prob: 0.4627 loss_thr: 0.3496 loss_db: 0.0831 2022/10/26 07:37:02 - mmengine - INFO - Epoch(train) [1000][20/63] lr: 7.0548e-04 eta: 2:23:16 time: 0.5019 data_time: 0.0085 memory: 16131 loss: 0.9899 loss_prob: 0.5203 loss_thr: 0.3780 loss_db: 0.0916 2022/10/26 07:37:05 - mmengine - INFO - Epoch(train) [1000][25/63] lr: 7.0548e-04 eta: 2:23:16 time: 0.5399 data_time: 0.0296 memory: 16131 loss: 0.9686 loss_prob: 0.5147 loss_thr: 0.3648 loss_db: 0.0890 2022/10/26 07:37:08 - mmengine - INFO - Epoch(train) [1000][30/63] lr: 7.0548e-04 eta: 2:23:09 time: 0.5726 data_time: 0.0353 memory: 16131 loss: 1.0182 loss_prob: 0.5443 loss_thr: 0.3803 loss_db: 0.0936 2022/10/26 07:37:10 - mmengine - INFO - Epoch(train) [1000][35/63] lr: 7.0548e-04 eta: 2:23:09 time: 0.5337 data_time: 0.0133 memory: 16131 loss: 0.9872 loss_prob: 0.5234 loss_thr: 0.3731 loss_db: 0.0907 2022/10/26 07:37:13 - mmengine - INFO - Epoch(train) [1000][40/63] lr: 7.0548e-04 eta: 2:23:02 time: 0.5099 data_time: 0.0069 memory: 16131 loss: 0.8340 loss_prob: 0.4323 loss_thr: 0.3274 loss_db: 0.0744 2022/10/26 07:37:16 - mmengine - INFO - Epoch(train) [1000][45/63] lr: 7.0548e-04 eta: 2:23:02 time: 0.5094 data_time: 0.0083 memory: 16131 loss: 0.8687 loss_prob: 0.4523 loss_thr: 0.3380 loss_db: 0.0784 2022/10/26 07:37:18 - mmengine - INFO - Epoch(train) [1000][50/63] lr: 7.0548e-04 eta: 2:22:55 time: 0.5312 data_time: 0.0285 memory: 16131 loss: 0.9042 loss_prob: 0.4729 loss_thr: 0.3488 loss_db: 0.0826 2022/10/26 07:37:21 - mmengine - INFO - Epoch(train) [1000][55/63] lr: 7.0548e-04 eta: 2:22:55 time: 0.5225 data_time: 0.0288 memory: 16131 loss: 0.9059 loss_prob: 0.4655 loss_thr: 0.3598 loss_db: 0.0805 2022/10/26 07:37:23 - mmengine - INFO - Epoch(train) [1000][60/63] lr: 7.0548e-04 eta: 2:22:48 time: 0.4982 data_time: 0.0103 memory: 16131 loss: 0.8752 loss_prob: 0.4518 loss_thr: 0.3468 loss_db: 0.0766 2022/10/26 07:37:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:37:25 - mmengine - INFO - Saving checkpoint at 1000 epochs 2022/10/26 07:37:33 - mmengine - INFO - Epoch(val) [1000][5/32] eta: 2:22:48 time: 0.5330 data_time: 0.0686 memory: 16131 2022/10/26 07:37:35 - mmengine - INFO - Epoch(val) [1000][10/32] eta: 0:00:12 time: 0.5694 data_time: 0.0718 memory: 15724 2022/10/26 07:37:38 - mmengine - INFO - Epoch(val) [1000][15/32] eta: 0:00:12 time: 0.5395 data_time: 0.0382 memory: 15724 2022/10/26 07:37:41 - mmengine - INFO - Epoch(val) [1000][20/32] eta: 0:00:06 time: 0.5504 data_time: 0.0476 memory: 15724 2022/10/26 07:37:44 - mmengine - INFO - Epoch(val) [1000][25/32] eta: 0:00:06 time: 0.5542 data_time: 0.0456 memory: 15724 2022/10/26 07:37:46 - mmengine - INFO - Epoch(val) [1000][30/32] eta: 0:00:01 time: 0.5320 data_time: 0.0409 memory: 15724 2022/10/26 07:37:47 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8440, precision: 0.7475, hmean: 0.7929 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8440, precision: 0.7968, hmean: 0.8197 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8440, precision: 0.8184, hmean: 0.8310 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8406, precision: 0.8468, hmean: 0.8437 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8320, precision: 0.8732, hmean: 0.8521 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7617, precision: 0.9230, hmean: 0.8346 2022/10/26 07:37:47 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1738, precision: 0.9783, hmean: 0.2952 2022/10/26 07:37:47 - mmengine - INFO - Epoch(val) [1000][32/32] icdar/precision: 0.8732 icdar/recall: 0.8320 icdar/hmean: 0.8521 2022/10/26 07:37:52 - mmengine - INFO - Epoch(train) [1001][5/63] lr: 7.0231e-04 eta: 0:00:01 time: 0.8128 data_time: 0.1820 memory: 16131 loss: 0.9092 loss_prob: 0.4842 loss_thr: 0.3437 loss_db: 0.0813 2022/10/26 07:37:55 - mmengine - INFO - Epoch(train) [1001][10/63] lr: 7.0231e-04 eta: 2:22:39 time: 0.8298 data_time: 0.1814 memory: 16131 loss: 0.9888 loss_prob: 0.5318 loss_thr: 0.3671 loss_db: 0.0899 2022/10/26 07:37:58 - mmengine - INFO - Epoch(train) [1001][15/63] lr: 7.0231e-04 eta: 2:22:39 time: 0.5210 data_time: 0.0079 memory: 16131 loss: 0.9820 loss_prob: 0.5253 loss_thr: 0.3683 loss_db: 0.0884 2022/10/26 07:38:00 - mmengine - INFO - Epoch(train) [1001][20/63] lr: 7.0231e-04 eta: 2:22:32 time: 0.5173 data_time: 0.0106 memory: 16131 loss: 0.9154 loss_prob: 0.4764 loss_thr: 0.3564 loss_db: 0.0826 2022/10/26 07:38:03 - mmengine - INFO - Epoch(train) [1001][25/63] lr: 7.0231e-04 eta: 2:22:32 time: 0.5224 data_time: 0.0115 memory: 16131 loss: 0.8924 loss_prob: 0.4545 loss_thr: 0.3565 loss_db: 0.0814 2022/10/26 07:38:06 - mmengine - INFO - Epoch(train) [1001][30/63] lr: 7.0231e-04 eta: 2:22:25 time: 0.5447 data_time: 0.0301 memory: 16131 loss: 0.8413 loss_prob: 0.4287 loss_thr: 0.3366 loss_db: 0.0759 2022/10/26 07:38:08 - mmengine - INFO - Epoch(train) [1001][35/63] lr: 7.0231e-04 eta: 2:22:25 time: 0.5658 data_time: 0.0270 memory: 16131 loss: 0.8357 loss_prob: 0.4332 loss_thr: 0.3278 loss_db: 0.0747 2022/10/26 07:38:11 - mmengine - INFO - Epoch(train) [1001][40/63] lr: 7.0231e-04 eta: 2:22:18 time: 0.5818 data_time: 0.0077 memory: 16131 loss: 0.8949 loss_prob: 0.4705 loss_thr: 0.3444 loss_db: 0.0799 2022/10/26 07:38:15 - mmengine - INFO - Epoch(train) [1001][45/63] lr: 7.0231e-04 eta: 2:22:18 time: 0.6003 data_time: 0.0072 memory: 16131 loss: 0.8622 loss_prob: 0.4509 loss_thr: 0.3336 loss_db: 0.0777 2022/10/26 07:38:18 - mmengine - INFO - Epoch(train) [1001][50/63] lr: 7.0231e-04 eta: 2:22:11 time: 0.6110 data_time: 0.0101 memory: 16131 loss: 0.8201 loss_prob: 0.4229 loss_thr: 0.3230 loss_db: 0.0741 2022/10/26 07:38:20 - mmengine - INFO - Epoch(train) [1001][55/63] lr: 7.0231e-04 eta: 2:22:11 time: 0.5620 data_time: 0.0202 memory: 16131 loss: 0.9029 loss_prob: 0.4734 loss_thr: 0.3488 loss_db: 0.0807 2022/10/26 07:38:23 - mmengine - INFO - Epoch(train) [1001][60/63] lr: 7.0231e-04 eta: 2:22:04 time: 0.5016 data_time: 0.0174 memory: 16131 loss: 0.9048 loss_prob: 0.4700 loss_thr: 0.3533 loss_db: 0.0815 2022/10/26 07:38:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:38:29 - mmengine - INFO - Epoch(train) [1002][5/63] lr: 6.9913e-04 eta: 2:22:04 time: 0.7134 data_time: 0.1868 memory: 16131 loss: 0.9489 loss_prob: 0.5120 loss_thr: 0.3508 loss_db: 0.0861 2022/10/26 07:38:31 - mmengine - INFO - Epoch(train) [1002][10/63] lr: 6.9913e-04 eta: 2:21:55 time: 0.7335 data_time: 0.1828 memory: 16131 loss: 1.2891 loss_prob: 0.7875 loss_thr: 0.3879 loss_db: 0.1137 2022/10/26 07:38:34 - mmengine - INFO - Epoch(train) [1002][15/63] lr: 6.9913e-04 eta: 2:21:55 time: 0.5086 data_time: 0.0119 memory: 16131 loss: 1.2555 loss_prob: 0.7554 loss_thr: 0.3898 loss_db: 0.1103 2022/10/26 07:38:36 - mmengine - INFO - Epoch(train) [1002][20/63] lr: 6.9913e-04 eta: 2:21:47 time: 0.5195 data_time: 0.0123 memory: 16131 loss: 0.9599 loss_prob: 0.4989 loss_thr: 0.3742 loss_db: 0.0868 2022/10/26 07:38:39 - mmengine - INFO - Epoch(train) [1002][25/63] lr: 6.9913e-04 eta: 2:21:47 time: 0.5401 data_time: 0.0325 memory: 16131 loss: 1.0565 loss_prob: 0.5632 loss_thr: 0.3944 loss_db: 0.0989 2022/10/26 07:38:42 - mmengine - INFO - Epoch(train) [1002][30/63] lr: 6.9913e-04 eta: 2:21:40 time: 0.5485 data_time: 0.0337 memory: 16131 loss: 0.9954 loss_prob: 0.5315 loss_thr: 0.3720 loss_db: 0.0918 2022/10/26 07:38:44 - mmengine - INFO - Epoch(train) [1002][35/63] lr: 6.9913e-04 eta: 2:21:40 time: 0.5188 data_time: 0.0143 memory: 16131 loss: 0.9151 loss_prob: 0.4714 loss_thr: 0.3620 loss_db: 0.0817 2022/10/26 07:38:47 - mmengine - INFO - Epoch(train) [1002][40/63] lr: 6.9913e-04 eta: 2:21:33 time: 0.5096 data_time: 0.0147 memory: 16131 loss: 0.9940 loss_prob: 0.5161 loss_thr: 0.3893 loss_db: 0.0886 2022/10/26 07:38:50 - mmengine - INFO - Epoch(train) [1002][45/63] lr: 6.9913e-04 eta: 2:21:33 time: 0.5168 data_time: 0.0115 memory: 16131 loss: 0.9986 loss_prob: 0.5271 loss_thr: 0.3802 loss_db: 0.0914 2022/10/26 07:38:53 - mmengine - INFO - Epoch(train) [1002][50/63] lr: 6.9913e-04 eta: 2:21:26 time: 0.5669 data_time: 0.0168 memory: 16131 loss: 0.9524 loss_prob: 0.4986 loss_thr: 0.3661 loss_db: 0.0877 2022/10/26 07:38:55 - mmengine - INFO - Epoch(train) [1002][55/63] lr: 6.9913e-04 eta: 2:21:26 time: 0.5634 data_time: 0.0214 memory: 16131 loss: 0.9694 loss_prob: 0.5015 loss_thr: 0.3809 loss_db: 0.0870 2022/10/26 07:38:58 - mmengine - INFO - Epoch(train) [1002][60/63] lr: 6.9913e-04 eta: 2:21:19 time: 0.5189 data_time: 0.0126 memory: 16131 loss: 0.9855 loss_prob: 0.5160 loss_thr: 0.3797 loss_db: 0.0898 2022/10/26 07:38:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:39:04 - mmengine - INFO - Epoch(train) [1003][5/63] lr: 6.9595e-04 eta: 2:21:19 time: 0.7177 data_time: 0.1840 memory: 16131 loss: 0.8537 loss_prob: 0.4393 loss_thr: 0.3371 loss_db: 0.0773 2022/10/26 07:39:07 - mmengine - INFO - Epoch(train) [1003][10/63] lr: 6.9595e-04 eta: 2:21:10 time: 0.7420 data_time: 0.1782 memory: 16131 loss: 0.9382 loss_prob: 0.4912 loss_thr: 0.3637 loss_db: 0.0834 2022/10/26 07:39:09 - mmengine - INFO - Epoch(train) [1003][15/63] lr: 6.9595e-04 eta: 2:21:10 time: 0.5096 data_time: 0.0054 memory: 16131 loss: 0.9260 loss_prob: 0.4876 loss_thr: 0.3562 loss_db: 0.0822 2022/10/26 07:39:12 - mmengine - INFO - Epoch(train) [1003][20/63] lr: 6.9595e-04 eta: 2:21:03 time: 0.5398 data_time: 0.0064 memory: 16131 loss: 0.9016 loss_prob: 0.4678 loss_thr: 0.3530 loss_db: 0.0808 2022/10/26 07:39:15 - mmengine - INFO - Epoch(train) [1003][25/63] lr: 6.9595e-04 eta: 2:21:03 time: 0.5570 data_time: 0.0326 memory: 16131 loss: 0.9633 loss_prob: 0.4974 loss_thr: 0.3801 loss_db: 0.0857 2022/10/26 07:39:17 - mmengine - INFO - Epoch(train) [1003][30/63] lr: 6.9595e-04 eta: 2:20:56 time: 0.5293 data_time: 0.0352 memory: 16131 loss: 0.8692 loss_prob: 0.4463 loss_thr: 0.3461 loss_db: 0.0768 2022/10/26 07:39:20 - mmengine - INFO - Epoch(train) [1003][35/63] lr: 6.9595e-04 eta: 2:20:56 time: 0.4967 data_time: 0.0081 memory: 16131 loss: 0.9205 loss_prob: 0.4776 loss_thr: 0.3591 loss_db: 0.0837 2022/10/26 07:39:22 - mmengine - INFO - Epoch(train) [1003][40/63] lr: 6.9595e-04 eta: 2:20:49 time: 0.4921 data_time: 0.0055 memory: 16131 loss: 0.9294 loss_prob: 0.4739 loss_thr: 0.3711 loss_db: 0.0845 2022/10/26 07:39:25 - mmengine - INFO - Epoch(train) [1003][45/63] lr: 6.9595e-04 eta: 2:20:49 time: 0.5047 data_time: 0.0057 memory: 16131 loss: 0.9359 loss_prob: 0.4982 loss_thr: 0.3514 loss_db: 0.0864 2022/10/26 07:39:28 - mmengine - INFO - Epoch(train) [1003][50/63] lr: 6.9595e-04 eta: 2:20:42 time: 0.5352 data_time: 0.0168 memory: 16131 loss: 0.9665 loss_prob: 0.5246 loss_thr: 0.3528 loss_db: 0.0891 2022/10/26 07:39:30 - mmengine - INFO - Epoch(train) [1003][55/63] lr: 6.9595e-04 eta: 2:20:42 time: 0.5527 data_time: 0.0225 memory: 16131 loss: 0.9235 loss_prob: 0.4842 loss_thr: 0.3566 loss_db: 0.0826 2022/10/26 07:39:34 - mmengine - INFO - Epoch(train) [1003][60/63] lr: 6.9595e-04 eta: 2:20:35 time: 0.6223 data_time: 0.0122 memory: 16131 loss: 0.9830 loss_prob: 0.5169 loss_thr: 0.3769 loss_db: 0.0891 2022/10/26 07:39:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:39:40 - mmengine - INFO - Epoch(train) [1004][5/63] lr: 6.9277e-04 eta: 2:20:35 time: 0.6805 data_time: 0.2133 memory: 16131 loss: 1.0040 loss_prob: 0.5245 loss_thr: 0.3865 loss_db: 0.0930 2022/10/26 07:39:42 - mmengine - INFO - Epoch(train) [1004][10/63] lr: 6.9277e-04 eta: 2:20:26 time: 0.7348 data_time: 0.2138 memory: 16131 loss: 0.9424 loss_prob: 0.4837 loss_thr: 0.3742 loss_db: 0.0846 2022/10/26 07:39:45 - mmengine - INFO - Epoch(train) [1004][15/63] lr: 6.9277e-04 eta: 2:20:26 time: 0.5280 data_time: 0.0079 memory: 16131 loss: 0.8972 loss_prob: 0.4614 loss_thr: 0.3538 loss_db: 0.0820 2022/10/26 07:39:47 - mmengine - INFO - Epoch(train) [1004][20/63] lr: 6.9277e-04 eta: 2:20:18 time: 0.5011 data_time: 0.0059 memory: 16131 loss: 0.9624 loss_prob: 0.5081 loss_thr: 0.3653 loss_db: 0.0890 2022/10/26 07:39:50 - mmengine - INFO - Epoch(train) [1004][25/63] lr: 6.9277e-04 eta: 2:20:18 time: 0.5278 data_time: 0.0289 memory: 16131 loss: 1.0455 loss_prob: 0.5620 loss_thr: 0.3874 loss_db: 0.0960 2022/10/26 07:39:53 - mmengine - INFO - Epoch(train) [1004][30/63] lr: 6.9277e-04 eta: 2:20:11 time: 0.5323 data_time: 0.0313 memory: 16131 loss: 0.9377 loss_prob: 0.4914 loss_thr: 0.3606 loss_db: 0.0856 2022/10/26 07:39:55 - mmengine - INFO - Epoch(train) [1004][35/63] lr: 6.9277e-04 eta: 2:20:11 time: 0.5188 data_time: 0.0115 memory: 16131 loss: 0.8755 loss_prob: 0.4484 loss_thr: 0.3497 loss_db: 0.0774 2022/10/26 07:39:58 - mmengine - INFO - Epoch(train) [1004][40/63] lr: 6.9277e-04 eta: 2:20:04 time: 0.5397 data_time: 0.0084 memory: 16131 loss: 0.9317 loss_prob: 0.4771 loss_thr: 0.3710 loss_db: 0.0835 2022/10/26 07:40:00 - mmengine - INFO - Epoch(train) [1004][45/63] lr: 6.9277e-04 eta: 2:20:04 time: 0.5104 data_time: 0.0061 memory: 16131 loss: 0.9496 loss_prob: 0.4901 loss_thr: 0.3716 loss_db: 0.0879 2022/10/26 07:40:03 - mmengine - INFO - Epoch(train) [1004][50/63] lr: 6.9277e-04 eta: 2:19:57 time: 0.5082 data_time: 0.0225 memory: 16131 loss: 0.8746 loss_prob: 0.4533 loss_thr: 0.3421 loss_db: 0.0791 2022/10/26 07:40:06 - mmengine - INFO - Epoch(train) [1004][55/63] lr: 6.9277e-04 eta: 2:19:57 time: 0.5395 data_time: 0.0212 memory: 16131 loss: 0.9475 loss_prob: 0.5102 loss_thr: 0.3488 loss_db: 0.0885 2022/10/26 07:40:08 - mmengine - INFO - Epoch(train) [1004][60/63] lr: 6.9277e-04 eta: 2:19:50 time: 0.5383 data_time: 0.0067 memory: 16131 loss: 0.9961 loss_prob: 0.5387 loss_thr: 0.3630 loss_db: 0.0943 2022/10/26 07:40:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:40:15 - mmengine - INFO - Epoch(train) [1005][5/63] lr: 6.8959e-04 eta: 2:19:50 time: 0.7622 data_time: 0.1930 memory: 16131 loss: 0.9766 loss_prob: 0.5040 loss_thr: 0.3846 loss_db: 0.0880 2022/10/26 07:40:18 - mmengine - INFO - Epoch(train) [1005][10/63] lr: 6.8959e-04 eta: 2:19:41 time: 0.8024 data_time: 0.1942 memory: 16131 loss: 0.9901 loss_prob: 0.5116 loss_thr: 0.3893 loss_db: 0.0892 2022/10/26 07:40:20 - mmengine - INFO - Epoch(train) [1005][15/63] lr: 6.8959e-04 eta: 2:19:41 time: 0.5123 data_time: 0.0070 memory: 16131 loss: 0.9747 loss_prob: 0.5124 loss_thr: 0.3727 loss_db: 0.0896 2022/10/26 07:40:23 - mmengine - INFO - Epoch(train) [1005][20/63] lr: 6.8959e-04 eta: 2:19:34 time: 0.5094 data_time: 0.0197 memory: 16131 loss: 0.9287 loss_prob: 0.4789 loss_thr: 0.3676 loss_db: 0.0822 2022/10/26 07:40:25 - mmengine - INFO - Epoch(train) [1005][25/63] lr: 6.8959e-04 eta: 2:19:34 time: 0.5038 data_time: 0.0197 memory: 16131 loss: 0.8900 loss_prob: 0.4577 loss_thr: 0.3541 loss_db: 0.0782 2022/10/26 07:40:28 - mmengine - INFO - Epoch(train) [1005][30/63] lr: 6.8959e-04 eta: 2:19:27 time: 0.4911 data_time: 0.0164 memory: 16131 loss: 0.9308 loss_prob: 0.4888 loss_thr: 0.3572 loss_db: 0.0848 2022/10/26 07:40:30 - mmengine - INFO - Epoch(train) [1005][35/63] lr: 6.8959e-04 eta: 2:19:27 time: 0.5235 data_time: 0.0203 memory: 16131 loss: 0.9679 loss_prob: 0.5161 loss_thr: 0.3622 loss_db: 0.0896 2022/10/26 07:40:33 - mmengine - INFO - Epoch(train) [1005][40/63] lr: 6.8959e-04 eta: 2:19:20 time: 0.5099 data_time: 0.0154 memory: 16131 loss: 0.9802 loss_prob: 0.5246 loss_thr: 0.3661 loss_db: 0.0895 2022/10/26 07:40:35 - mmengine - INFO - Epoch(train) [1005][45/63] lr: 6.8959e-04 eta: 2:19:20 time: 0.4885 data_time: 0.0107 memory: 16131 loss: 0.9214 loss_prob: 0.4813 loss_thr: 0.3573 loss_db: 0.0828 2022/10/26 07:40:38 - mmengine - INFO - Epoch(train) [1005][50/63] lr: 6.8959e-04 eta: 2:19:13 time: 0.4985 data_time: 0.0142 memory: 16131 loss: 0.8886 loss_prob: 0.4645 loss_thr: 0.3428 loss_db: 0.0813 2022/10/26 07:40:40 - mmengine - INFO - Epoch(train) [1005][55/63] lr: 6.8959e-04 eta: 2:19:13 time: 0.5114 data_time: 0.0169 memory: 16131 loss: 0.9009 loss_prob: 0.4745 loss_thr: 0.3434 loss_db: 0.0830 2022/10/26 07:40:43 - mmengine - INFO - Epoch(train) [1005][60/63] lr: 6.8959e-04 eta: 2:19:05 time: 0.5362 data_time: 0.0094 memory: 16131 loss: 0.9378 loss_prob: 0.4944 loss_thr: 0.3575 loss_db: 0.0858 2022/10/26 07:40:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:40:49 - mmengine - INFO - Epoch(train) [1006][5/63] lr: 6.8641e-04 eta: 2:19:05 time: 0.7063 data_time: 0.2045 memory: 16131 loss: 0.9110 loss_prob: 0.4782 loss_thr: 0.3516 loss_db: 0.0812 2022/10/26 07:40:52 - mmengine - INFO - Epoch(train) [1006][10/63] lr: 6.8641e-04 eta: 2:18:56 time: 0.7385 data_time: 0.2042 memory: 16131 loss: 0.8784 loss_prob: 0.4593 loss_thr: 0.3383 loss_db: 0.0808 2022/10/26 07:40:54 - mmengine - INFO - Epoch(train) [1006][15/63] lr: 6.8641e-04 eta: 2:18:56 time: 0.5317 data_time: 0.0084 memory: 16131 loss: 0.9549 loss_prob: 0.4993 loss_thr: 0.3674 loss_db: 0.0883 2022/10/26 07:40:57 - mmengine - INFO - Epoch(train) [1006][20/63] lr: 6.8641e-04 eta: 2:18:49 time: 0.5026 data_time: 0.0088 memory: 16131 loss: 0.9418 loss_prob: 0.4950 loss_thr: 0.3599 loss_db: 0.0870 2022/10/26 07:41:00 - mmengine - INFO - Epoch(train) [1006][25/63] lr: 6.8641e-04 eta: 2:18:49 time: 0.5208 data_time: 0.0307 memory: 16131 loss: 0.9003 loss_prob: 0.4662 loss_thr: 0.3523 loss_db: 0.0818 2022/10/26 07:41:02 - mmengine - INFO - Epoch(train) [1006][30/63] lr: 6.8641e-04 eta: 2:18:42 time: 0.5188 data_time: 0.0330 memory: 16131 loss: 0.9061 loss_prob: 0.4675 loss_thr: 0.3561 loss_db: 0.0825 2022/10/26 07:41:05 - mmengine - INFO - Epoch(train) [1006][35/63] lr: 6.8641e-04 eta: 2:18:42 time: 0.5171 data_time: 0.0083 memory: 16131 loss: 0.8989 loss_prob: 0.4670 loss_thr: 0.3484 loss_db: 0.0836 2022/10/26 07:41:07 - mmengine - INFO - Epoch(train) [1006][40/63] lr: 6.8641e-04 eta: 2:18:35 time: 0.5178 data_time: 0.0051 memory: 16131 loss: 0.9252 loss_prob: 0.4900 loss_thr: 0.3506 loss_db: 0.0846 2022/10/26 07:41:10 - mmengine - INFO - Epoch(train) [1006][45/63] lr: 6.8641e-04 eta: 2:18:35 time: 0.4986 data_time: 0.0054 memory: 16131 loss: 0.9700 loss_prob: 0.5106 loss_thr: 0.3734 loss_db: 0.0860 2022/10/26 07:41:13 - mmengine - INFO - Epoch(train) [1006][50/63] lr: 6.8641e-04 eta: 2:18:28 time: 0.5277 data_time: 0.0263 memory: 16131 loss: 1.0314 loss_prob: 0.5508 loss_thr: 0.3870 loss_db: 0.0936 2022/10/26 07:41:15 - mmengine - INFO - Epoch(train) [1006][55/63] lr: 6.8641e-04 eta: 2:18:28 time: 0.5330 data_time: 0.0293 memory: 16131 loss: 1.0351 loss_prob: 0.5660 loss_thr: 0.3735 loss_db: 0.0957 2022/10/26 07:41:18 - mmengine - INFO - Epoch(train) [1006][60/63] lr: 6.8641e-04 eta: 2:18:21 time: 0.5087 data_time: 0.0135 memory: 16131 loss: 0.9538 loss_prob: 0.5100 loss_thr: 0.3577 loss_db: 0.0861 2022/10/26 07:41:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:41:25 - mmengine - INFO - Epoch(train) [1007][5/63] lr: 6.8322e-04 eta: 2:18:21 time: 0.7820 data_time: 0.2170 memory: 16131 loss: 1.0067 loss_prob: 0.5374 loss_thr: 0.3760 loss_db: 0.0934 2022/10/26 07:41:27 - mmengine - INFO - Epoch(train) [1007][10/63] lr: 6.8322e-04 eta: 2:18:12 time: 0.8062 data_time: 0.2172 memory: 16131 loss: 0.9458 loss_prob: 0.4932 loss_thr: 0.3651 loss_db: 0.0875 2022/10/26 07:41:30 - mmengine - INFO - Epoch(train) [1007][15/63] lr: 6.8322e-04 eta: 2:18:12 time: 0.5334 data_time: 0.0052 memory: 16131 loss: 1.0045 loss_prob: 0.5487 loss_thr: 0.3649 loss_db: 0.0908 2022/10/26 07:41:32 - mmengine - INFO - Epoch(train) [1007][20/63] lr: 6.8322e-04 eta: 2:18:05 time: 0.5305 data_time: 0.0051 memory: 16131 loss: 1.1189 loss_prob: 0.6170 loss_thr: 0.3990 loss_db: 0.1029 2022/10/26 07:41:35 - mmengine - INFO - Epoch(train) [1007][25/63] lr: 6.8322e-04 eta: 2:18:05 time: 0.4915 data_time: 0.0124 memory: 16131 loss: 1.0616 loss_prob: 0.5718 loss_thr: 0.3914 loss_db: 0.0984 2022/10/26 07:41:38 - mmengine - INFO - Epoch(train) [1007][30/63] lr: 6.8322e-04 eta: 2:17:58 time: 0.5200 data_time: 0.0376 memory: 16131 loss: 1.0081 loss_prob: 0.5382 loss_thr: 0.3764 loss_db: 0.0935 2022/10/26 07:41:40 - mmengine - INFO - Epoch(train) [1007][35/63] lr: 6.8322e-04 eta: 2:17:58 time: 0.5052 data_time: 0.0309 memory: 16131 loss: 0.9411 loss_prob: 0.4964 loss_thr: 0.3576 loss_db: 0.0871 2022/10/26 07:41:43 - mmengine - INFO - Epoch(train) [1007][40/63] lr: 6.8322e-04 eta: 2:17:51 time: 0.5009 data_time: 0.0054 memory: 16131 loss: 0.9541 loss_prob: 0.5003 loss_thr: 0.3677 loss_db: 0.0861 2022/10/26 07:41:45 - mmengine - INFO - Epoch(train) [1007][45/63] lr: 6.8322e-04 eta: 2:17:51 time: 0.5100 data_time: 0.0044 memory: 16131 loss: 0.9507 loss_prob: 0.4968 loss_thr: 0.3685 loss_db: 0.0854 2022/10/26 07:41:47 - mmengine - INFO - Epoch(train) [1007][50/63] lr: 6.8322e-04 eta: 2:17:43 time: 0.4900 data_time: 0.0087 memory: 16131 loss: 0.9005 loss_prob: 0.4760 loss_thr: 0.3419 loss_db: 0.0826 2022/10/26 07:41:50 - mmengine - INFO - Epoch(train) [1007][55/63] lr: 6.8322e-04 eta: 2:17:43 time: 0.5027 data_time: 0.0198 memory: 16131 loss: 0.9328 loss_prob: 0.4993 loss_thr: 0.3465 loss_db: 0.0871 2022/10/26 07:41:52 - mmengine - INFO - Epoch(train) [1007][60/63] lr: 6.8322e-04 eta: 2:17:36 time: 0.5029 data_time: 0.0162 memory: 16131 loss: 0.9334 loss_prob: 0.4967 loss_thr: 0.3494 loss_db: 0.0873 2022/10/26 07:41:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:41:59 - mmengine - INFO - Epoch(train) [1008][5/63] lr: 6.8004e-04 eta: 2:17:36 time: 0.7139 data_time: 0.1920 memory: 16131 loss: 0.8657 loss_prob: 0.4501 loss_thr: 0.3357 loss_db: 0.0799 2022/10/26 07:42:02 - mmengine - INFO - Epoch(train) [1008][10/63] lr: 6.8004e-04 eta: 2:17:27 time: 0.7785 data_time: 0.1937 memory: 16131 loss: 0.8465 loss_prob: 0.4351 loss_thr: 0.3346 loss_db: 0.0768 2022/10/26 07:42:04 - mmengine - INFO - Epoch(train) [1008][15/63] lr: 6.8004e-04 eta: 2:17:27 time: 0.5776 data_time: 0.0087 memory: 16131 loss: 0.8866 loss_prob: 0.4535 loss_thr: 0.3537 loss_db: 0.0794 2022/10/26 07:42:07 - mmengine - INFO - Epoch(train) [1008][20/63] lr: 6.8004e-04 eta: 2:17:20 time: 0.5115 data_time: 0.0068 memory: 16131 loss: 0.8887 loss_prob: 0.4546 loss_thr: 0.3541 loss_db: 0.0801 2022/10/26 07:42:10 - mmengine - INFO - Epoch(train) [1008][25/63] lr: 6.8004e-04 eta: 2:17:20 time: 0.5251 data_time: 0.0395 memory: 16131 loss: 0.8928 loss_prob: 0.4585 loss_thr: 0.3534 loss_db: 0.0809 2022/10/26 07:42:12 - mmengine - INFO - Epoch(train) [1008][30/63] lr: 6.8004e-04 eta: 2:17:13 time: 0.5394 data_time: 0.0440 memory: 16131 loss: 0.9356 loss_prob: 0.4804 loss_thr: 0.3713 loss_db: 0.0840 2022/10/26 07:42:15 - mmengine - INFO - Epoch(train) [1008][35/63] lr: 6.8004e-04 eta: 2:17:13 time: 0.5230 data_time: 0.0100 memory: 16131 loss: 0.9929 loss_prob: 0.5194 loss_thr: 0.3833 loss_db: 0.0902 2022/10/26 07:42:17 - mmengine - INFO - Epoch(train) [1008][40/63] lr: 6.8004e-04 eta: 2:17:06 time: 0.5092 data_time: 0.0057 memory: 16131 loss: 0.9454 loss_prob: 0.4923 loss_thr: 0.3645 loss_db: 0.0887 2022/10/26 07:42:20 - mmengine - INFO - Epoch(train) [1008][45/63] lr: 6.8004e-04 eta: 2:17:06 time: 0.4973 data_time: 0.0055 memory: 16131 loss: 0.9154 loss_prob: 0.4731 loss_thr: 0.3567 loss_db: 0.0856 2022/10/26 07:42:23 - mmengine - INFO - Epoch(train) [1008][50/63] lr: 6.8004e-04 eta: 2:16:59 time: 0.5331 data_time: 0.0189 memory: 16131 loss: 0.9354 loss_prob: 0.4839 loss_thr: 0.3684 loss_db: 0.0831 2022/10/26 07:42:26 - mmengine - INFO - Epoch(train) [1008][55/63] lr: 6.8004e-04 eta: 2:16:59 time: 0.5802 data_time: 0.0206 memory: 16131 loss: 0.9402 loss_prob: 0.4882 loss_thr: 0.3680 loss_db: 0.0840 2022/10/26 07:42:28 - mmengine - INFO - Epoch(train) [1008][60/63] lr: 6.8004e-04 eta: 2:16:52 time: 0.5506 data_time: 0.0141 memory: 16131 loss: 0.9323 loss_prob: 0.4923 loss_thr: 0.3528 loss_db: 0.0871 2022/10/26 07:42:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:42:34 - mmengine - INFO - Epoch(train) [1009][5/63] lr: 6.7685e-04 eta: 2:16:52 time: 0.7083 data_time: 0.1953 memory: 16131 loss: 0.9941 loss_prob: 0.5364 loss_thr: 0.3685 loss_db: 0.0892 2022/10/26 07:42:37 - mmengine - INFO - Epoch(train) [1009][10/63] lr: 6.7685e-04 eta: 2:16:43 time: 0.7379 data_time: 0.1960 memory: 16131 loss: 0.9848 loss_prob: 0.5316 loss_thr: 0.3635 loss_db: 0.0897 2022/10/26 07:42:39 - mmengine - INFO - Epoch(train) [1009][15/63] lr: 6.7685e-04 eta: 2:16:43 time: 0.4880 data_time: 0.0077 memory: 16131 loss: 0.9043 loss_prob: 0.4802 loss_thr: 0.3393 loss_db: 0.0849 2022/10/26 07:42:41 - mmengine - INFO - Epoch(train) [1009][20/63] lr: 6.7685e-04 eta: 2:16:36 time: 0.4694 data_time: 0.0065 memory: 16131 loss: 0.9445 loss_prob: 0.5044 loss_thr: 0.3528 loss_db: 0.0873 2022/10/26 07:42:44 - mmengine - INFO - Epoch(train) [1009][25/63] lr: 6.7685e-04 eta: 2:16:36 time: 0.4839 data_time: 0.0160 memory: 16131 loss: 0.9830 loss_prob: 0.5193 loss_thr: 0.3758 loss_db: 0.0879 2022/10/26 07:42:47 - mmengine - INFO - Epoch(train) [1009][30/63] lr: 6.7685e-04 eta: 2:16:28 time: 0.5191 data_time: 0.0316 memory: 16131 loss: 0.9931 loss_prob: 0.5219 loss_thr: 0.3826 loss_db: 0.0886 2022/10/26 07:42:49 - mmengine - INFO - Epoch(train) [1009][35/63] lr: 6.7685e-04 eta: 2:16:28 time: 0.5057 data_time: 0.0217 memory: 16131 loss: 0.9144 loss_prob: 0.4760 loss_thr: 0.3562 loss_db: 0.0822 2022/10/26 07:42:52 - mmengine - INFO - Epoch(train) [1009][40/63] lr: 6.7685e-04 eta: 2:16:21 time: 0.5038 data_time: 0.0060 memory: 16131 loss: 0.8104 loss_prob: 0.4130 loss_thr: 0.3253 loss_db: 0.0721 2022/10/26 07:42:54 - mmengine - INFO - Epoch(train) [1009][45/63] lr: 6.7685e-04 eta: 2:16:21 time: 0.5349 data_time: 0.0065 memory: 16131 loss: 0.8783 loss_prob: 0.4634 loss_thr: 0.3349 loss_db: 0.0800 2022/10/26 07:42:57 - mmengine - INFO - Epoch(train) [1009][50/63] lr: 6.7685e-04 eta: 2:16:14 time: 0.5449 data_time: 0.0210 memory: 16131 loss: 0.9453 loss_prob: 0.5073 loss_thr: 0.3502 loss_db: 0.0878 2022/10/26 07:43:00 - mmengine - INFO - Epoch(train) [1009][55/63] lr: 6.7685e-04 eta: 2:16:14 time: 0.5610 data_time: 0.0221 memory: 16131 loss: 0.9183 loss_prob: 0.4877 loss_thr: 0.3447 loss_db: 0.0859 2022/10/26 07:43:03 - mmengine - INFO - Epoch(train) [1009][60/63] lr: 6.7685e-04 eta: 2:16:07 time: 0.5808 data_time: 0.0080 memory: 16131 loss: 0.9669 loss_prob: 0.5094 loss_thr: 0.3692 loss_db: 0.0883 2022/10/26 07:43:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:43:09 - mmengine - INFO - Epoch(train) [1010][5/63] lr: 6.7366e-04 eta: 2:16:07 time: 0.6805 data_time: 0.1687 memory: 16131 loss: 0.9590 loss_prob: 0.5070 loss_thr: 0.3655 loss_db: 0.0865 2022/10/26 07:43:11 - mmengine - INFO - Epoch(train) [1010][10/63] lr: 6.7366e-04 eta: 2:15:58 time: 0.7019 data_time: 0.1680 memory: 16131 loss: 0.8887 loss_prob: 0.4569 loss_thr: 0.3505 loss_db: 0.0813 2022/10/26 07:43:14 - mmengine - INFO - Epoch(train) [1010][15/63] lr: 6.7366e-04 eta: 2:15:58 time: 0.4986 data_time: 0.0108 memory: 16131 loss: 0.9710 loss_prob: 0.5092 loss_thr: 0.3702 loss_db: 0.0916 2022/10/26 07:43:17 - mmengine - INFO - Epoch(train) [1010][20/63] lr: 6.7366e-04 eta: 2:15:51 time: 0.5290 data_time: 0.0100 memory: 16131 loss: 1.0262 loss_prob: 0.5507 loss_thr: 0.3796 loss_db: 0.0959 2022/10/26 07:43:19 - mmengine - INFO - Epoch(train) [1010][25/63] lr: 6.7366e-04 eta: 2:15:51 time: 0.5697 data_time: 0.0150 memory: 16131 loss: 0.9249 loss_prob: 0.4856 loss_thr: 0.3559 loss_db: 0.0833 2022/10/26 07:43:22 - mmengine - INFO - Epoch(train) [1010][30/63] lr: 6.7366e-04 eta: 2:15:44 time: 0.5569 data_time: 0.0269 memory: 16131 loss: 0.8534 loss_prob: 0.4406 loss_thr: 0.3352 loss_db: 0.0776 2022/10/26 07:43:25 - mmengine - INFO - Epoch(train) [1010][35/63] lr: 6.7366e-04 eta: 2:15:44 time: 0.5237 data_time: 0.0214 memory: 16131 loss: 0.9071 loss_prob: 0.4746 loss_thr: 0.3490 loss_db: 0.0835 2022/10/26 07:43:27 - mmengine - INFO - Epoch(train) [1010][40/63] lr: 6.7366e-04 eta: 2:15:37 time: 0.5020 data_time: 0.0099 memory: 16131 loss: 0.9650 loss_prob: 0.5119 loss_thr: 0.3650 loss_db: 0.0881 2022/10/26 07:43:30 - mmengine - INFO - Epoch(train) [1010][45/63] lr: 6.7366e-04 eta: 2:15:37 time: 0.4919 data_time: 0.0064 memory: 16131 loss: 0.9248 loss_prob: 0.4862 loss_thr: 0.3549 loss_db: 0.0837 2022/10/26 07:43:32 - mmengine - INFO - Epoch(train) [1010][50/63] lr: 6.7366e-04 eta: 2:15:30 time: 0.5320 data_time: 0.0149 memory: 16131 loss: 0.8796 loss_prob: 0.4563 loss_thr: 0.3443 loss_db: 0.0789 2022/10/26 07:43:35 - mmengine - INFO - Epoch(train) [1010][55/63] lr: 6.7366e-04 eta: 2:15:30 time: 0.5740 data_time: 0.0241 memory: 16131 loss: 0.8730 loss_prob: 0.4562 loss_thr: 0.3380 loss_db: 0.0788 2022/10/26 07:43:38 - mmengine - INFO - Epoch(train) [1010][60/63] lr: 6.7366e-04 eta: 2:15:23 time: 0.5940 data_time: 0.0196 memory: 16131 loss: 0.9118 loss_prob: 0.4811 loss_thr: 0.3491 loss_db: 0.0815 2022/10/26 07:43:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:43:44 - mmengine - INFO - Epoch(train) [1011][5/63] lr: 6.7047e-04 eta: 2:15:23 time: 0.7413 data_time: 0.1995 memory: 16131 loss: 0.9080 loss_prob: 0.4780 loss_thr: 0.3466 loss_db: 0.0834 2022/10/26 07:43:47 - mmengine - INFO - Epoch(train) [1011][10/63] lr: 6.7047e-04 eta: 2:15:14 time: 0.7125 data_time: 0.1938 memory: 16131 loss: 0.8839 loss_prob: 0.4539 loss_thr: 0.3504 loss_db: 0.0796 2022/10/26 07:43:49 - mmengine - INFO - Epoch(train) [1011][15/63] lr: 6.7047e-04 eta: 2:15:14 time: 0.4875 data_time: 0.0070 memory: 16131 loss: 0.9021 loss_prob: 0.4662 loss_thr: 0.3535 loss_db: 0.0824 2022/10/26 07:43:52 - mmengine - INFO - Epoch(train) [1011][20/63] lr: 6.7047e-04 eta: 2:15:07 time: 0.4936 data_time: 0.0087 memory: 16131 loss: 0.9348 loss_prob: 0.4830 loss_thr: 0.3670 loss_db: 0.0848 2022/10/26 07:43:55 - mmengine - INFO - Epoch(train) [1011][25/63] lr: 6.7047e-04 eta: 2:15:07 time: 0.5237 data_time: 0.0122 memory: 16131 loss: 0.9161 loss_prob: 0.4718 loss_thr: 0.3615 loss_db: 0.0828 2022/10/26 07:43:58 - mmengine - INFO - Epoch(train) [1011][30/63] lr: 6.7047e-04 eta: 2:15:00 time: 0.5730 data_time: 0.0295 memory: 16131 loss: 0.8547 loss_prob: 0.4388 loss_thr: 0.3384 loss_db: 0.0775 2022/10/26 07:44:00 - mmengine - INFO - Epoch(train) [1011][35/63] lr: 6.7047e-04 eta: 2:15:00 time: 0.5698 data_time: 0.0240 memory: 16131 loss: 0.8937 loss_prob: 0.4562 loss_thr: 0.3583 loss_db: 0.0792 2022/10/26 07:44:03 - mmengine - INFO - Epoch(train) [1011][40/63] lr: 6.7047e-04 eta: 2:14:53 time: 0.5283 data_time: 0.0055 memory: 16131 loss: 0.9106 loss_prob: 0.4688 loss_thr: 0.3584 loss_db: 0.0834 2022/10/26 07:44:05 - mmengine - INFO - Epoch(train) [1011][45/63] lr: 6.7047e-04 eta: 2:14:53 time: 0.5101 data_time: 0.0047 memory: 16131 loss: 0.9640 loss_prob: 0.5093 loss_thr: 0.3653 loss_db: 0.0894 2022/10/26 07:44:08 - mmengine - INFO - Epoch(train) [1011][50/63] lr: 6.7047e-04 eta: 2:14:46 time: 0.5449 data_time: 0.0252 memory: 16131 loss: 0.9786 loss_prob: 0.5233 loss_thr: 0.3655 loss_db: 0.0897 2022/10/26 07:44:11 - mmengine - INFO - Epoch(train) [1011][55/63] lr: 6.7047e-04 eta: 2:14:46 time: 0.5731 data_time: 0.0258 memory: 16131 loss: 0.9333 loss_prob: 0.4913 loss_thr: 0.3565 loss_db: 0.0856 2022/10/26 07:44:14 - mmengine - INFO - Epoch(train) [1011][60/63] lr: 6.7047e-04 eta: 2:14:39 time: 0.5362 data_time: 0.0055 memory: 16131 loss: 0.8861 loss_prob: 0.4593 loss_thr: 0.3473 loss_db: 0.0795 2022/10/26 07:44:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:44:19 - mmengine - INFO - Epoch(train) [1012][5/63] lr: 6.6728e-04 eta: 2:14:39 time: 0.6742 data_time: 0.1900 memory: 16131 loss: 0.9024 loss_prob: 0.4707 loss_thr: 0.3504 loss_db: 0.0813 2022/10/26 07:44:22 - mmengine - INFO - Epoch(train) [1012][10/63] lr: 6.6728e-04 eta: 2:14:29 time: 0.6870 data_time: 0.1900 memory: 16131 loss: 0.9790 loss_prob: 0.5152 loss_thr: 0.3745 loss_db: 0.0893 2022/10/26 07:44:24 - mmengine - INFO - Epoch(train) [1012][15/63] lr: 6.6728e-04 eta: 2:14:29 time: 0.4926 data_time: 0.0050 memory: 16131 loss: 0.8720 loss_prob: 0.4647 loss_thr: 0.3282 loss_db: 0.0791 2022/10/26 07:44:27 - mmengine - INFO - Epoch(train) [1012][20/63] lr: 6.6728e-04 eta: 2:14:22 time: 0.5050 data_time: 0.0047 memory: 16131 loss: 0.8505 loss_prob: 0.4517 loss_thr: 0.3210 loss_db: 0.0777 2022/10/26 07:44:29 - mmengine - INFO - Epoch(train) [1012][25/63] lr: 6.6728e-04 eta: 2:14:22 time: 0.5125 data_time: 0.0144 memory: 16131 loss: 0.9327 loss_prob: 0.4932 loss_thr: 0.3524 loss_db: 0.0871 2022/10/26 07:44:33 - mmengine - INFO - Epoch(train) [1012][30/63] lr: 6.6728e-04 eta: 2:14:15 time: 0.6213 data_time: 0.0314 memory: 16131 loss: 0.8782 loss_prob: 0.4569 loss_thr: 0.3412 loss_db: 0.0801 2022/10/26 07:44:36 - mmengine - INFO - Epoch(train) [1012][35/63] lr: 6.6728e-04 eta: 2:14:15 time: 0.6170 data_time: 0.0218 memory: 16131 loss: 0.8661 loss_prob: 0.4521 loss_thr: 0.3354 loss_db: 0.0785 2022/10/26 07:44:38 - mmengine - INFO - Epoch(train) [1012][40/63] lr: 6.6728e-04 eta: 2:14:08 time: 0.5082 data_time: 0.0055 memory: 16131 loss: 0.8980 loss_prob: 0.4798 loss_thr: 0.3352 loss_db: 0.0829 2022/10/26 07:44:41 - mmengine - INFO - Epoch(train) [1012][45/63] lr: 6.6728e-04 eta: 2:14:08 time: 0.5351 data_time: 0.0053 memory: 16131 loss: 0.9271 loss_prob: 0.4925 loss_thr: 0.3505 loss_db: 0.0841 2022/10/26 07:44:44 - mmengine - INFO - Epoch(train) [1012][50/63] lr: 6.6728e-04 eta: 2:14:01 time: 0.5427 data_time: 0.0189 memory: 16131 loss: 1.0791 loss_prob: 0.5822 loss_thr: 0.3959 loss_db: 0.1010 2022/10/26 07:44:46 - mmengine - INFO - Epoch(train) [1012][55/63] lr: 6.6728e-04 eta: 2:14:01 time: 0.5345 data_time: 0.0266 memory: 16131 loss: 1.0217 loss_prob: 0.5453 loss_thr: 0.3794 loss_db: 0.0970 2022/10/26 07:44:49 - mmengine - INFO - Epoch(train) [1012][60/63] lr: 6.6728e-04 eta: 2:13:54 time: 0.5684 data_time: 0.0136 memory: 16131 loss: 0.9660 loss_prob: 0.5090 loss_thr: 0.3674 loss_db: 0.0895 2022/10/26 07:44:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:44:55 - mmengine - INFO - Epoch(train) [1013][5/63] lr: 6.6408e-04 eta: 2:13:54 time: 0.6970 data_time: 0.1814 memory: 16131 loss: 1.0309 loss_prob: 0.5496 loss_thr: 0.3863 loss_db: 0.0949 2022/10/26 07:44:57 - mmengine - INFO - Epoch(train) [1013][10/63] lr: 6.6408e-04 eta: 2:13:45 time: 0.6811 data_time: 0.1801 memory: 16131 loss: 1.0034 loss_prob: 0.5239 loss_thr: 0.3879 loss_db: 0.0916 2022/10/26 07:45:00 - mmengine - INFO - Epoch(train) [1013][15/63] lr: 6.6408e-04 eta: 2:13:45 time: 0.5123 data_time: 0.0247 memory: 16131 loss: 0.9439 loss_prob: 0.4858 loss_thr: 0.3729 loss_db: 0.0851 2022/10/26 07:45:03 - mmengine - INFO - Epoch(train) [1013][20/63] lr: 6.6408e-04 eta: 2:13:38 time: 0.5494 data_time: 0.0274 memory: 16131 loss: 0.9589 loss_prob: 0.4998 loss_thr: 0.3730 loss_db: 0.0861 2022/10/26 07:45:05 - mmengine - INFO - Epoch(train) [1013][25/63] lr: 6.6408e-04 eta: 2:13:38 time: 0.5306 data_time: 0.0198 memory: 16131 loss: 0.9969 loss_prob: 0.5248 loss_thr: 0.3817 loss_db: 0.0905 2022/10/26 07:45:08 - mmengine - INFO - Epoch(train) [1013][30/63] lr: 6.6408e-04 eta: 2:13:31 time: 0.5072 data_time: 0.0263 memory: 16131 loss: 0.9498 loss_prob: 0.4964 loss_thr: 0.3671 loss_db: 0.0863 2022/10/26 07:45:11 - mmengine - INFO - Epoch(train) [1013][35/63] lr: 6.6408e-04 eta: 2:13:31 time: 0.5099 data_time: 0.0161 memory: 16131 loss: 0.9775 loss_prob: 0.5155 loss_thr: 0.3732 loss_db: 0.0888 2022/10/26 07:45:13 - mmengine - INFO - Epoch(train) [1013][40/63] lr: 6.6408e-04 eta: 2:13:24 time: 0.5175 data_time: 0.0159 memory: 16131 loss: 0.9743 loss_prob: 0.5124 loss_thr: 0.3733 loss_db: 0.0887 2022/10/26 07:45:16 - mmengine - INFO - Epoch(train) [1013][45/63] lr: 6.6408e-04 eta: 2:13:24 time: 0.5161 data_time: 0.0162 memory: 16131 loss: 0.8877 loss_prob: 0.4603 loss_thr: 0.3486 loss_db: 0.0788 2022/10/26 07:45:18 - mmengine - INFO - Epoch(train) [1013][50/63] lr: 6.6408e-04 eta: 2:13:17 time: 0.5042 data_time: 0.0115 memory: 16131 loss: 0.8569 loss_prob: 0.4428 loss_thr: 0.3373 loss_db: 0.0768 2022/10/26 07:45:21 - mmengine - INFO - Epoch(train) [1013][55/63] lr: 6.6408e-04 eta: 2:13:17 time: 0.5257 data_time: 0.0195 memory: 16131 loss: 0.9088 loss_prob: 0.4717 loss_thr: 0.3528 loss_db: 0.0843 2022/10/26 07:45:24 - mmengine - INFO - Epoch(train) [1013][60/63] lr: 6.6408e-04 eta: 2:13:10 time: 0.5418 data_time: 0.0147 memory: 16131 loss: 0.9590 loss_prob: 0.5024 loss_thr: 0.3690 loss_db: 0.0876 2022/10/26 07:45:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:45:30 - mmengine - INFO - Epoch(train) [1014][5/63] lr: 6.6088e-04 eta: 2:13:10 time: 0.7124 data_time: 0.2009 memory: 16131 loss: 1.0042 loss_prob: 0.5284 loss_thr: 0.3841 loss_db: 0.0917 2022/10/26 07:45:32 - mmengine - INFO - Epoch(train) [1014][10/63] lr: 6.6088e-04 eta: 2:13:01 time: 0.7161 data_time: 0.1974 memory: 16131 loss: 0.9843 loss_prob: 0.5209 loss_thr: 0.3697 loss_db: 0.0938 2022/10/26 07:45:35 - mmengine - INFO - Epoch(train) [1014][15/63] lr: 6.6088e-04 eta: 2:13:01 time: 0.5025 data_time: 0.0053 memory: 16131 loss: 0.9347 loss_prob: 0.4954 loss_thr: 0.3504 loss_db: 0.0889 2022/10/26 07:45:37 - mmengine - INFO - Epoch(train) [1014][20/63] lr: 6.6088e-04 eta: 2:12:53 time: 0.4949 data_time: 0.0054 memory: 16131 loss: 0.9653 loss_prob: 0.5120 loss_thr: 0.3650 loss_db: 0.0883 2022/10/26 07:45:40 - mmengine - INFO - Epoch(train) [1014][25/63] lr: 6.6088e-04 eta: 2:12:53 time: 0.5408 data_time: 0.0320 memory: 16131 loss: 0.9594 loss_prob: 0.5067 loss_thr: 0.3668 loss_db: 0.0858 2022/10/26 07:45:43 - mmengine - INFO - Epoch(train) [1014][30/63] lr: 6.6088e-04 eta: 2:12:46 time: 0.5482 data_time: 0.0318 memory: 16131 loss: 0.9983 loss_prob: 0.5327 loss_thr: 0.3747 loss_db: 0.0908 2022/10/26 07:45:45 - mmengine - INFO - Epoch(train) [1014][35/63] lr: 6.6088e-04 eta: 2:12:46 time: 0.5051 data_time: 0.0041 memory: 16131 loss: 0.9865 loss_prob: 0.5267 loss_thr: 0.3699 loss_db: 0.0899 2022/10/26 07:45:48 - mmengine - INFO - Epoch(train) [1014][40/63] lr: 6.6088e-04 eta: 2:12:39 time: 0.5242 data_time: 0.0043 memory: 16131 loss: 0.9205 loss_prob: 0.4852 loss_thr: 0.3532 loss_db: 0.0821 2022/10/26 07:45:51 - mmengine - INFO - Epoch(train) [1014][45/63] lr: 6.6088e-04 eta: 2:12:39 time: 0.5426 data_time: 0.0042 memory: 16131 loss: 0.9014 loss_prob: 0.4760 loss_thr: 0.3433 loss_db: 0.0821 2022/10/26 07:45:53 - mmengine - INFO - Epoch(train) [1014][50/63] lr: 6.6088e-04 eta: 2:12:32 time: 0.5678 data_time: 0.0195 memory: 16131 loss: 0.8707 loss_prob: 0.4496 loss_thr: 0.3437 loss_db: 0.0775 2022/10/26 07:45:56 - mmengine - INFO - Epoch(train) [1014][55/63] lr: 6.6088e-04 eta: 2:12:32 time: 0.5504 data_time: 0.0208 memory: 16131 loss: 0.9324 loss_prob: 0.4776 loss_thr: 0.3716 loss_db: 0.0832 2022/10/26 07:45:58 - mmengine - INFO - Epoch(train) [1014][60/63] lr: 6.6088e-04 eta: 2:12:25 time: 0.5012 data_time: 0.0053 memory: 16131 loss: 0.9577 loss_prob: 0.4946 loss_thr: 0.3767 loss_db: 0.0863 2022/10/26 07:46:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:46:05 - mmengine - INFO - Epoch(train) [1015][5/63] lr: 6.5769e-04 eta: 2:12:25 time: 0.7321 data_time: 0.2472 memory: 16131 loss: 0.9002 loss_prob: 0.4629 loss_thr: 0.3553 loss_db: 0.0820 2022/10/26 07:46:08 - mmengine - INFO - Epoch(train) [1015][10/63] lr: 6.5769e-04 eta: 2:12:16 time: 0.8096 data_time: 0.2464 memory: 16131 loss: 0.9284 loss_prob: 0.4790 loss_thr: 0.3658 loss_db: 0.0836 2022/10/26 07:46:11 - mmengine - INFO - Epoch(train) [1015][15/63] lr: 6.5769e-04 eta: 2:12:16 time: 0.5792 data_time: 0.0072 memory: 16131 loss: 0.9711 loss_prob: 0.5119 loss_thr: 0.3709 loss_db: 0.0883 2022/10/26 07:46:14 - mmengine - INFO - Epoch(train) [1015][20/63] lr: 6.5769e-04 eta: 2:12:09 time: 0.5703 data_time: 0.0128 memory: 16131 loss: 0.9314 loss_prob: 0.4911 loss_thr: 0.3545 loss_db: 0.0858 2022/10/26 07:46:16 - mmengine - INFO - Epoch(train) [1015][25/63] lr: 6.5769e-04 eta: 2:12:09 time: 0.5436 data_time: 0.0182 memory: 16131 loss: 0.9377 loss_prob: 0.4904 loss_thr: 0.3622 loss_db: 0.0851 2022/10/26 07:46:19 - mmengine - INFO - Epoch(train) [1015][30/63] lr: 6.5769e-04 eta: 2:12:02 time: 0.5214 data_time: 0.0296 memory: 16131 loss: 0.9586 loss_prob: 0.5088 loss_thr: 0.3621 loss_db: 0.0877 2022/10/26 07:46:21 - mmengine - INFO - Epoch(train) [1015][35/63] lr: 6.5769e-04 eta: 2:12:02 time: 0.5369 data_time: 0.0267 memory: 16131 loss: 0.8878 loss_prob: 0.4707 loss_thr: 0.3346 loss_db: 0.0825 2022/10/26 07:46:24 - mmengine - INFO - Epoch(train) [1015][40/63] lr: 6.5769e-04 eta: 2:11:55 time: 0.5737 data_time: 0.0084 memory: 16131 loss: 0.9264 loss_prob: 0.4900 loss_thr: 0.3513 loss_db: 0.0851 2022/10/26 07:46:27 - mmengine - INFO - Epoch(train) [1015][45/63] lr: 6.5769e-04 eta: 2:11:55 time: 0.5730 data_time: 0.0053 memory: 16131 loss: 0.9474 loss_prob: 0.5092 loss_thr: 0.3532 loss_db: 0.0850 2022/10/26 07:46:30 - mmengine - INFO - Epoch(train) [1015][50/63] lr: 6.5769e-04 eta: 2:11:48 time: 0.5340 data_time: 0.0195 memory: 16131 loss: 0.8713 loss_prob: 0.4647 loss_thr: 0.3281 loss_db: 0.0785 2022/10/26 07:46:32 - mmengine - INFO - Epoch(train) [1015][55/63] lr: 6.5769e-04 eta: 2:11:48 time: 0.5123 data_time: 0.0196 memory: 16131 loss: 0.8641 loss_prob: 0.4512 loss_thr: 0.3333 loss_db: 0.0796 2022/10/26 07:46:35 - mmengine - INFO - Epoch(train) [1015][60/63] lr: 6.5769e-04 eta: 2:11:41 time: 0.5308 data_time: 0.0090 memory: 16131 loss: 0.8773 loss_prob: 0.4586 loss_thr: 0.3391 loss_db: 0.0796 2022/10/26 07:46:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:46:41 - mmengine - INFO - Epoch(train) [1016][5/63] lr: 6.5449e-04 eta: 2:11:41 time: 0.7206 data_time: 0.2094 memory: 16131 loss: 0.9337 loss_prob: 0.4898 loss_thr: 0.3591 loss_db: 0.0847 2022/10/26 07:46:44 - mmengine - INFO - Epoch(train) [1016][10/63] lr: 6.5449e-04 eta: 2:11:32 time: 0.7488 data_time: 0.2104 memory: 16131 loss: 0.9723 loss_prob: 0.5104 loss_thr: 0.3747 loss_db: 0.0872 2022/10/26 07:46:47 - mmengine - INFO - Epoch(train) [1016][15/63] lr: 6.5449e-04 eta: 2:11:32 time: 0.5622 data_time: 0.0106 memory: 16131 loss: 0.9500 loss_prob: 0.5017 loss_thr: 0.3607 loss_db: 0.0876 2022/10/26 07:46:49 - mmengine - INFO - Epoch(train) [1016][20/63] lr: 6.5449e-04 eta: 2:11:25 time: 0.5565 data_time: 0.0060 memory: 16131 loss: 0.8629 loss_prob: 0.4473 loss_thr: 0.3355 loss_db: 0.0801 2022/10/26 07:46:52 - mmengine - INFO - Epoch(train) [1016][25/63] lr: 6.5449e-04 eta: 2:11:25 time: 0.5190 data_time: 0.0290 memory: 16131 loss: 0.8120 loss_prob: 0.4128 loss_thr: 0.3267 loss_db: 0.0726 2022/10/26 07:46:54 - mmengine - INFO - Epoch(train) [1016][30/63] lr: 6.5449e-04 eta: 2:11:18 time: 0.5077 data_time: 0.0299 memory: 16131 loss: 0.8952 loss_prob: 0.4688 loss_thr: 0.3444 loss_db: 0.0820 2022/10/26 07:46:57 - mmengine - INFO - Epoch(train) [1016][35/63] lr: 6.5449e-04 eta: 2:11:18 time: 0.5018 data_time: 0.0079 memory: 16131 loss: 0.8935 loss_prob: 0.4705 loss_thr: 0.3397 loss_db: 0.0833 2022/10/26 07:46:59 - mmengine - INFO - Epoch(train) [1016][40/63] lr: 6.5449e-04 eta: 2:11:11 time: 0.4944 data_time: 0.0085 memory: 16131 loss: 0.8656 loss_prob: 0.4444 loss_thr: 0.3432 loss_db: 0.0779 2022/10/26 07:47:02 - mmengine - INFO - Epoch(train) [1016][45/63] lr: 6.5449e-04 eta: 2:11:11 time: 0.4949 data_time: 0.0068 memory: 16131 loss: 0.9173 loss_prob: 0.4775 loss_thr: 0.3576 loss_db: 0.0823 2022/10/26 07:47:05 - mmengine - INFO - Epoch(train) [1016][50/63] lr: 6.5449e-04 eta: 2:11:04 time: 0.5336 data_time: 0.0214 memory: 16131 loss: 0.9133 loss_prob: 0.4793 loss_thr: 0.3509 loss_db: 0.0831 2022/10/26 07:47:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:47:07 - mmengine - INFO - Epoch(train) [1016][55/63] lr: 6.5449e-04 eta: 2:11:04 time: 0.5343 data_time: 0.0212 memory: 16131 loss: 0.9971 loss_prob: 0.5249 loss_thr: 0.3828 loss_db: 0.0893 2022/10/26 07:47:10 - mmengine - INFO - Epoch(train) [1016][60/63] lr: 6.5449e-04 eta: 2:10:57 time: 0.5187 data_time: 0.0060 memory: 16131 loss: 1.0123 loss_prob: 0.5381 loss_thr: 0.3837 loss_db: 0.0905 2022/10/26 07:47:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:47:16 - mmengine - INFO - Epoch(train) [1017][5/63] lr: 6.5128e-04 eta: 2:10:57 time: 0.7051 data_time: 0.1967 memory: 16131 loss: 0.8904 loss_prob: 0.4531 loss_thr: 0.3590 loss_db: 0.0783 2022/10/26 07:47:19 - mmengine - INFO - Epoch(train) [1017][10/63] lr: 6.5128e-04 eta: 2:10:48 time: 0.7645 data_time: 0.1959 memory: 16131 loss: 0.9244 loss_prob: 0.4852 loss_thr: 0.3564 loss_db: 0.0829 2022/10/26 07:47:21 - mmengine - INFO - Epoch(train) [1017][15/63] lr: 6.5128e-04 eta: 2:10:48 time: 0.5453 data_time: 0.0053 memory: 16131 loss: 0.9471 loss_prob: 0.5017 loss_thr: 0.3579 loss_db: 0.0875 2022/10/26 07:47:24 - mmengine - INFO - Epoch(train) [1017][20/63] lr: 6.5128e-04 eta: 2:10:41 time: 0.4903 data_time: 0.0056 memory: 16131 loss: 0.9761 loss_prob: 0.5194 loss_thr: 0.3661 loss_db: 0.0906 2022/10/26 07:47:27 - mmengine - INFO - Epoch(train) [1017][25/63] lr: 6.5128e-04 eta: 2:10:41 time: 0.5061 data_time: 0.0255 memory: 16131 loss: 1.0040 loss_prob: 0.5346 loss_thr: 0.3771 loss_db: 0.0923 2022/10/26 07:47:29 - mmengine - INFO - Epoch(train) [1017][30/63] lr: 6.5128e-04 eta: 2:10:34 time: 0.5197 data_time: 0.0353 memory: 16131 loss: 0.9804 loss_prob: 0.5186 loss_thr: 0.3728 loss_db: 0.0890 2022/10/26 07:47:32 - mmengine - INFO - Epoch(train) [1017][35/63] lr: 6.5128e-04 eta: 2:10:34 time: 0.5168 data_time: 0.0153 memory: 16131 loss: 0.9078 loss_prob: 0.4804 loss_thr: 0.3447 loss_db: 0.0827 2022/10/26 07:47:34 - mmengine - INFO - Epoch(train) [1017][40/63] lr: 6.5128e-04 eta: 2:10:27 time: 0.5070 data_time: 0.0060 memory: 16131 loss: 0.9218 loss_prob: 0.4774 loss_thr: 0.3596 loss_db: 0.0848 2022/10/26 07:47:37 - mmengine - INFO - Epoch(train) [1017][45/63] lr: 6.5128e-04 eta: 2:10:27 time: 0.4901 data_time: 0.0066 memory: 16131 loss: 0.9523 loss_prob: 0.4913 loss_thr: 0.3730 loss_db: 0.0880 2022/10/26 07:47:39 - mmengine - INFO - Epoch(train) [1017][50/63] lr: 6.5128e-04 eta: 2:10:20 time: 0.5292 data_time: 0.0180 memory: 16131 loss: 0.9184 loss_prob: 0.4779 loss_thr: 0.3557 loss_db: 0.0848 2022/10/26 07:47:42 - mmengine - INFO - Epoch(train) [1017][55/63] lr: 6.5128e-04 eta: 2:10:20 time: 0.5506 data_time: 0.0306 memory: 16131 loss: 0.8979 loss_prob: 0.4641 loss_thr: 0.3532 loss_db: 0.0807 2022/10/26 07:47:45 - mmengine - INFO - Epoch(train) [1017][60/63] lr: 6.5128e-04 eta: 2:10:13 time: 0.5485 data_time: 0.0178 memory: 16131 loss: 0.9276 loss_prob: 0.4799 loss_thr: 0.3646 loss_db: 0.0832 2022/10/26 07:47:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:47:51 - mmengine - INFO - Epoch(train) [1018][5/63] lr: 6.4808e-04 eta: 2:10:13 time: 0.6750 data_time: 0.1820 memory: 16131 loss: 0.7938 loss_prob: 0.3970 loss_thr: 0.3263 loss_db: 0.0705 2022/10/26 07:47:54 - mmengine - INFO - Epoch(train) [1018][10/63] lr: 6.4808e-04 eta: 2:10:04 time: 0.7516 data_time: 0.1819 memory: 16131 loss: 0.8161 loss_prob: 0.4193 loss_thr: 0.3243 loss_db: 0.0725 2022/10/26 07:47:57 - mmengine - INFO - Epoch(train) [1018][15/63] lr: 6.4808e-04 eta: 2:10:04 time: 0.6507 data_time: 0.0112 memory: 16131 loss: 0.8229 loss_prob: 0.4300 loss_thr: 0.3195 loss_db: 0.0734 2022/10/26 07:48:00 - mmengine - INFO - Epoch(train) [1018][20/63] lr: 6.4808e-04 eta: 2:09:57 time: 0.6292 data_time: 0.0131 memory: 16131 loss: 0.8680 loss_prob: 0.4518 loss_thr: 0.3374 loss_db: 0.0788 2022/10/26 07:48:03 - mmengine - INFO - Epoch(train) [1018][25/63] lr: 6.4808e-04 eta: 2:09:57 time: 0.5443 data_time: 0.0219 memory: 16131 loss: 0.9539 loss_prob: 0.4998 loss_thr: 0.3659 loss_db: 0.0882 2022/10/26 07:48:05 - mmengine - INFO - Epoch(train) [1018][30/63] lr: 6.4808e-04 eta: 2:09:50 time: 0.5312 data_time: 0.0400 memory: 16131 loss: 0.9231 loss_prob: 0.4887 loss_thr: 0.3483 loss_db: 0.0861 2022/10/26 07:48:08 - mmengine - INFO - Epoch(train) [1018][35/63] lr: 6.4808e-04 eta: 2:09:50 time: 0.5224 data_time: 0.0248 memory: 16131 loss: 0.8805 loss_prob: 0.4599 loss_thr: 0.3396 loss_db: 0.0811 2022/10/26 07:48:11 - mmengine - INFO - Epoch(train) [1018][40/63] lr: 6.4808e-04 eta: 2:09:43 time: 0.5282 data_time: 0.0046 memory: 16131 loss: 0.9181 loss_prob: 0.4759 loss_thr: 0.3584 loss_db: 0.0838 2022/10/26 07:48:13 - mmengine - INFO - Epoch(train) [1018][45/63] lr: 6.4808e-04 eta: 2:09:43 time: 0.5588 data_time: 0.0087 memory: 16131 loss: 0.8951 loss_prob: 0.4623 loss_thr: 0.3515 loss_db: 0.0813 2022/10/26 07:48:16 - mmengine - INFO - Epoch(train) [1018][50/63] lr: 6.4808e-04 eta: 2:09:36 time: 0.5700 data_time: 0.0199 memory: 16131 loss: 0.9075 loss_prob: 0.4817 loss_thr: 0.3444 loss_db: 0.0814 2022/10/26 07:48:19 - mmengine - INFO - Epoch(train) [1018][55/63] lr: 6.4808e-04 eta: 2:09:36 time: 0.5559 data_time: 0.0208 memory: 16131 loss: 0.9165 loss_prob: 0.4925 loss_thr: 0.3415 loss_db: 0.0824 2022/10/26 07:48:22 - mmengine - INFO - Epoch(train) [1018][60/63] lr: 6.4808e-04 eta: 2:09:29 time: 0.5468 data_time: 0.0102 memory: 16131 loss: 0.9096 loss_prob: 0.4819 loss_thr: 0.3447 loss_db: 0.0830 2022/10/26 07:48:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:48:28 - mmengine - INFO - Epoch(train) [1019][5/63] lr: 6.4488e-04 eta: 2:09:29 time: 0.7076 data_time: 0.2019 memory: 16131 loss: 0.9788 loss_prob: 0.5231 loss_thr: 0.3671 loss_db: 0.0887 2022/10/26 07:48:30 - mmengine - INFO - Epoch(train) [1019][10/63] lr: 6.4488e-04 eta: 2:09:20 time: 0.7357 data_time: 0.2058 memory: 16131 loss: 0.8985 loss_prob: 0.4660 loss_thr: 0.3523 loss_db: 0.0802 2022/10/26 07:48:33 - mmengine - INFO - Epoch(train) [1019][15/63] lr: 6.4488e-04 eta: 2:09:20 time: 0.5401 data_time: 0.0105 memory: 16131 loss: 0.8153 loss_prob: 0.4153 loss_thr: 0.3266 loss_db: 0.0734 2022/10/26 07:48:36 - mmengine - INFO - Epoch(train) [1019][20/63] lr: 6.4488e-04 eta: 2:09:13 time: 0.5524 data_time: 0.0117 memory: 16131 loss: 0.8665 loss_prob: 0.4497 loss_thr: 0.3377 loss_db: 0.0791 2022/10/26 07:48:39 - mmengine - INFO - Epoch(train) [1019][25/63] lr: 6.4488e-04 eta: 2:09:13 time: 0.5455 data_time: 0.0341 memory: 16131 loss: 0.9256 loss_prob: 0.4875 loss_thr: 0.3532 loss_db: 0.0849 2022/10/26 07:48:41 - mmengine - INFO - Epoch(train) [1019][30/63] lr: 6.4488e-04 eta: 2:09:06 time: 0.5237 data_time: 0.0339 memory: 16131 loss: 0.8942 loss_prob: 0.4715 loss_thr: 0.3386 loss_db: 0.0840 2022/10/26 07:48:44 - mmengine - INFO - Epoch(train) [1019][35/63] lr: 6.4488e-04 eta: 2:09:06 time: 0.4940 data_time: 0.0099 memory: 16131 loss: 0.8892 loss_prob: 0.4670 loss_thr: 0.3398 loss_db: 0.0824 2022/10/26 07:48:46 - mmengine - INFO - Epoch(train) [1019][40/63] lr: 6.4488e-04 eta: 2:08:58 time: 0.4971 data_time: 0.0059 memory: 16131 loss: 0.8837 loss_prob: 0.4626 loss_thr: 0.3415 loss_db: 0.0795 2022/10/26 07:48:49 - mmengine - INFO - Epoch(train) [1019][45/63] lr: 6.4488e-04 eta: 2:08:58 time: 0.4909 data_time: 0.0073 memory: 16131 loss: 0.9311 loss_prob: 0.4850 loss_thr: 0.3632 loss_db: 0.0829 2022/10/26 07:48:51 - mmengine - INFO - Epoch(train) [1019][50/63] lr: 6.4488e-04 eta: 2:08:51 time: 0.4981 data_time: 0.0208 memory: 16131 loss: 1.0492 loss_prob: 0.5606 loss_thr: 0.3944 loss_db: 0.0942 2022/10/26 07:48:54 - mmengine - INFO - Epoch(train) [1019][55/63] lr: 6.4488e-04 eta: 2:08:51 time: 0.5022 data_time: 0.0225 memory: 16131 loss: 1.0041 loss_prob: 0.5346 loss_thr: 0.3768 loss_db: 0.0927 2022/10/26 07:48:56 - mmengine - INFO - Epoch(train) [1019][60/63] lr: 6.4488e-04 eta: 2:08:44 time: 0.5208 data_time: 0.0077 memory: 16131 loss: 0.9493 loss_prob: 0.4929 loss_thr: 0.3681 loss_db: 0.0884 2022/10/26 07:48:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:49:03 - mmengine - INFO - Epoch(train) [1020][5/63] lr: 6.4167e-04 eta: 2:08:44 time: 0.7450 data_time: 0.2100 memory: 16131 loss: 0.8694 loss_prob: 0.4481 loss_thr: 0.3423 loss_db: 0.0790 2022/10/26 07:49:05 - mmengine - INFO - Epoch(train) [1020][10/63] lr: 6.4167e-04 eta: 2:08:35 time: 0.7320 data_time: 0.2120 memory: 16131 loss: 0.9008 loss_prob: 0.4712 loss_thr: 0.3465 loss_db: 0.0831 2022/10/26 07:49:08 - mmengine - INFO - Epoch(train) [1020][15/63] lr: 6.4167e-04 eta: 2:08:35 time: 0.5170 data_time: 0.0124 memory: 16131 loss: 0.8632 loss_prob: 0.4543 loss_thr: 0.3301 loss_db: 0.0789 2022/10/26 07:49:10 - mmengine - INFO - Epoch(train) [1020][20/63] lr: 6.4167e-04 eta: 2:08:28 time: 0.5311 data_time: 0.0128 memory: 16131 loss: 0.9124 loss_prob: 0.4821 loss_thr: 0.3482 loss_db: 0.0822 2022/10/26 07:49:13 - mmengine - INFO - Epoch(train) [1020][25/63] lr: 6.4167e-04 eta: 2:08:28 time: 0.5265 data_time: 0.0277 memory: 16131 loss: 0.9606 loss_prob: 0.5062 loss_thr: 0.3667 loss_db: 0.0877 2022/10/26 07:49:16 - mmengine - INFO - Epoch(train) [1020][30/63] lr: 6.4167e-04 eta: 2:08:21 time: 0.5299 data_time: 0.0328 memory: 16131 loss: 0.9109 loss_prob: 0.4723 loss_thr: 0.3556 loss_db: 0.0830 2022/10/26 07:49:18 - mmengine - INFO - Epoch(train) [1020][35/63] lr: 6.4167e-04 eta: 2:08:21 time: 0.5128 data_time: 0.0124 memory: 16131 loss: 1.0295 loss_prob: 0.5574 loss_thr: 0.3804 loss_db: 0.0917 2022/10/26 07:49:21 - mmengine - INFO - Epoch(train) [1020][40/63] lr: 6.4167e-04 eta: 2:08:14 time: 0.4990 data_time: 0.0164 memory: 16131 loss: 1.0173 loss_prob: 0.5556 loss_thr: 0.3709 loss_db: 0.0908 2022/10/26 07:49:23 - mmengine - INFO - Epoch(train) [1020][45/63] lr: 6.4167e-04 eta: 2:08:14 time: 0.5140 data_time: 0.0211 memory: 16131 loss: 0.8756 loss_prob: 0.4591 loss_thr: 0.3362 loss_db: 0.0803 2022/10/26 07:49:26 - mmengine - INFO - Epoch(train) [1020][50/63] lr: 6.4167e-04 eta: 2:08:07 time: 0.5243 data_time: 0.0279 memory: 16131 loss: 0.8821 loss_prob: 0.4653 loss_thr: 0.3359 loss_db: 0.0810 2022/10/26 07:49:28 - mmengine - INFO - Epoch(train) [1020][55/63] lr: 6.4167e-04 eta: 2:08:07 time: 0.5171 data_time: 0.0257 memory: 16131 loss: 0.9477 loss_prob: 0.4994 loss_thr: 0.3633 loss_db: 0.0851 2022/10/26 07:49:31 - mmengine - INFO - Epoch(train) [1020][60/63] lr: 6.4167e-04 eta: 2:08:00 time: 0.5128 data_time: 0.0076 memory: 16131 loss: 0.9385 loss_prob: 0.4957 loss_thr: 0.3584 loss_db: 0.0843 2022/10/26 07:49:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:49:33 - mmengine - INFO - Saving checkpoint at 1020 epochs 2022/10/26 07:49:39 - mmengine - INFO - Epoch(val) [1020][5/32] eta: 2:08:00 time: 0.5052 data_time: 0.0658 memory: 16131 2022/10/26 07:49:42 - mmengine - INFO - Epoch(val) [1020][10/32] eta: 0:00:12 time: 0.5619 data_time: 0.0784 memory: 15724 2022/10/26 07:49:45 - mmengine - INFO - Epoch(val) [1020][15/32] eta: 0:00:12 time: 0.5400 data_time: 0.0434 memory: 15724 2022/10/26 07:49:47 - mmengine - INFO - Epoch(val) [1020][20/32] eta: 0:00:06 time: 0.5525 data_time: 0.0498 memory: 15724 2022/10/26 07:49:50 - mmengine - INFO - Epoch(val) [1020][25/32] eta: 0:00:06 time: 0.5595 data_time: 0.0516 memory: 15724 2022/10/26 07:49:53 - mmengine - INFO - Epoch(val) [1020][30/32] eta: 0:00:01 time: 0.5239 data_time: 0.0341 memory: 15724 2022/10/26 07:49:53 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8329, precision: 0.7720, hmean: 0.8013 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8329, precision: 0.8203, hmean: 0.8266 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8320, precision: 0.8479, hmean: 0.8399 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8291, precision: 0.8679, hmean: 0.8481 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8156, precision: 0.8996, hmean: 0.8556 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7439, precision: 0.9358, hmean: 0.8289 2022/10/26 07:49:53 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1526, precision: 0.9875, hmean: 0.2644 2022/10/26 07:49:53 - mmengine - INFO - Epoch(val) [1020][32/32] icdar/precision: 0.8996 icdar/recall: 0.8156 icdar/hmean: 0.8556 2022/10/26 07:49:58 - mmengine - INFO - Epoch(train) [1021][5/63] lr: 6.3846e-04 eta: 0:00:01 time: 0.7302 data_time: 0.1971 memory: 16131 loss: 0.8933 loss_prob: 0.4610 loss_thr: 0.3519 loss_db: 0.0804 2022/10/26 07:50:00 - mmengine - INFO - Epoch(train) [1021][10/63] lr: 6.3846e-04 eta: 2:07:51 time: 0.7236 data_time: 0.1961 memory: 16131 loss: 0.9226 loss_prob: 0.4816 loss_thr: 0.3560 loss_db: 0.0849 2022/10/26 07:50:03 - mmengine - INFO - Epoch(train) [1021][15/63] lr: 6.3846e-04 eta: 2:07:51 time: 0.5139 data_time: 0.0093 memory: 16131 loss: 0.9700 loss_prob: 0.5193 loss_thr: 0.3593 loss_db: 0.0914 2022/10/26 07:50:06 - mmengine - INFO - Epoch(train) [1021][20/63] lr: 6.3846e-04 eta: 2:07:44 time: 0.5329 data_time: 0.0069 memory: 16131 loss: 0.9392 loss_prob: 0.4934 loss_thr: 0.3596 loss_db: 0.0863 2022/10/26 07:50:09 - mmengine - INFO - Epoch(train) [1021][25/63] lr: 6.3846e-04 eta: 2:07:44 time: 0.5417 data_time: 0.0213 memory: 16131 loss: 0.9261 loss_prob: 0.4770 loss_thr: 0.3654 loss_db: 0.0837 2022/10/26 07:50:11 - mmengine - INFO - Epoch(train) [1021][30/63] lr: 6.3846e-04 eta: 2:07:37 time: 0.5445 data_time: 0.0324 memory: 16131 loss: 0.9251 loss_prob: 0.4720 loss_thr: 0.3688 loss_db: 0.0843 2022/10/26 07:50:14 - mmengine - INFO - Epoch(train) [1021][35/63] lr: 6.3846e-04 eta: 2:07:37 time: 0.5359 data_time: 0.0199 memory: 16131 loss: 0.9451 loss_prob: 0.4822 loss_thr: 0.3782 loss_db: 0.0847 2022/10/26 07:50:16 - mmengine - INFO - Epoch(train) [1021][40/63] lr: 6.3846e-04 eta: 2:07:30 time: 0.5176 data_time: 0.0090 memory: 16131 loss: 0.9695 loss_prob: 0.5082 loss_thr: 0.3740 loss_db: 0.0873 2022/10/26 07:50:19 - mmengine - INFO - Epoch(train) [1021][45/63] lr: 6.3846e-04 eta: 2:07:30 time: 0.5119 data_time: 0.0083 memory: 16131 loss: 0.9172 loss_prob: 0.4832 loss_thr: 0.3502 loss_db: 0.0838 2022/10/26 07:50:22 - mmengine - INFO - Epoch(train) [1021][50/63] lr: 6.3846e-04 eta: 2:07:23 time: 0.5321 data_time: 0.0253 memory: 16131 loss: 0.9010 loss_prob: 0.4726 loss_thr: 0.3459 loss_db: 0.0825 2022/10/26 07:50:24 - mmengine - INFO - Epoch(train) [1021][55/63] lr: 6.3846e-04 eta: 2:07:23 time: 0.5340 data_time: 0.0261 memory: 16131 loss: 0.8771 loss_prob: 0.4551 loss_thr: 0.3421 loss_db: 0.0799 2022/10/26 07:50:27 - mmengine - INFO - Epoch(train) [1021][60/63] lr: 6.3846e-04 eta: 2:07:16 time: 0.5212 data_time: 0.0094 memory: 16131 loss: 0.9155 loss_prob: 0.4797 loss_thr: 0.3520 loss_db: 0.0838 2022/10/26 07:50:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:50:33 - mmengine - INFO - Epoch(train) [1022][5/63] lr: 6.3525e-04 eta: 2:07:16 time: 0.6613 data_time: 0.1730 memory: 16131 loss: 0.9626 loss_prob: 0.5145 loss_thr: 0.3590 loss_db: 0.0892 2022/10/26 07:50:35 - mmengine - INFO - Epoch(train) [1022][10/63] lr: 6.3525e-04 eta: 2:07:07 time: 0.6915 data_time: 0.1795 memory: 16131 loss: 0.9783 loss_prob: 0.5159 loss_thr: 0.3709 loss_db: 0.0915 2022/10/26 07:50:38 - mmengine - INFO - Epoch(train) [1022][15/63] lr: 6.3525e-04 eta: 2:07:07 time: 0.5200 data_time: 0.0118 memory: 16131 loss: 0.9962 loss_prob: 0.5296 loss_thr: 0.3745 loss_db: 0.0920 2022/10/26 07:50:40 - mmengine - INFO - Epoch(train) [1022][20/63] lr: 6.3525e-04 eta: 2:07:00 time: 0.5085 data_time: 0.0058 memory: 16131 loss: 0.9709 loss_prob: 0.5185 loss_thr: 0.3620 loss_db: 0.0904 2022/10/26 07:50:43 - mmengine - INFO - Epoch(train) [1022][25/63] lr: 6.3525e-04 eta: 2:07:00 time: 0.5219 data_time: 0.0191 memory: 16131 loss: 0.9637 loss_prob: 0.5160 loss_thr: 0.3581 loss_db: 0.0895 2022/10/26 07:50:46 - mmengine - INFO - Epoch(train) [1022][30/63] lr: 6.3525e-04 eta: 2:06:53 time: 0.5475 data_time: 0.0292 memory: 16131 loss: 0.9798 loss_prob: 0.5257 loss_thr: 0.3654 loss_db: 0.0888 2022/10/26 07:50:48 - mmengine - INFO - Epoch(train) [1022][35/63] lr: 6.3525e-04 eta: 2:06:53 time: 0.5097 data_time: 0.0209 memory: 16131 loss: 0.9577 loss_prob: 0.5068 loss_thr: 0.3616 loss_db: 0.0894 2022/10/26 07:50:51 - mmengine - INFO - Epoch(train) [1022][40/63] lr: 6.3525e-04 eta: 2:06:46 time: 0.5213 data_time: 0.0102 memory: 16131 loss: 0.9149 loss_prob: 0.4798 loss_thr: 0.3469 loss_db: 0.0883 2022/10/26 07:50:53 - mmengine - INFO - Epoch(train) [1022][45/63] lr: 6.3525e-04 eta: 2:06:46 time: 0.5312 data_time: 0.0056 memory: 16131 loss: 0.9049 loss_prob: 0.4707 loss_thr: 0.3505 loss_db: 0.0837 2022/10/26 07:50:56 - mmengine - INFO - Epoch(train) [1022][50/63] lr: 6.3525e-04 eta: 2:06:38 time: 0.5196 data_time: 0.0143 memory: 16131 loss: 0.9176 loss_prob: 0.4879 loss_thr: 0.3470 loss_db: 0.0828 2022/10/26 07:50:59 - mmengine - INFO - Epoch(train) [1022][55/63] lr: 6.3525e-04 eta: 2:06:38 time: 0.5748 data_time: 0.0308 memory: 16131 loss: 0.9067 loss_prob: 0.4828 loss_thr: 0.3417 loss_db: 0.0822 2022/10/26 07:51:02 - mmengine - INFO - Epoch(train) [1022][60/63] lr: 6.3525e-04 eta: 2:06:32 time: 0.5659 data_time: 0.0227 memory: 16131 loss: 0.8889 loss_prob: 0.4631 loss_thr: 0.3448 loss_db: 0.0810 2022/10/26 07:51:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:51:08 - mmengine - INFO - Epoch(train) [1023][5/63] lr: 6.3204e-04 eta: 2:06:32 time: 0.6929 data_time: 0.1876 memory: 16131 loss: 0.9778 loss_prob: 0.5192 loss_thr: 0.3669 loss_db: 0.0917 2022/10/26 07:51:10 - mmengine - INFO - Epoch(train) [1023][10/63] lr: 6.3204e-04 eta: 2:06:22 time: 0.7261 data_time: 0.1887 memory: 16131 loss: 0.9800 loss_prob: 0.5100 loss_thr: 0.3788 loss_db: 0.0911 2022/10/26 07:51:13 - mmengine - INFO - Epoch(train) [1023][15/63] lr: 6.3204e-04 eta: 2:06:22 time: 0.5132 data_time: 0.0095 memory: 16131 loss: 0.9424 loss_prob: 0.4943 loss_thr: 0.3615 loss_db: 0.0867 2022/10/26 07:51:16 - mmengine - INFO - Epoch(train) [1023][20/63] lr: 6.3204e-04 eta: 2:06:15 time: 0.5196 data_time: 0.0097 memory: 16131 loss: 0.9076 loss_prob: 0.4795 loss_thr: 0.3458 loss_db: 0.0822 2022/10/26 07:51:18 - mmengine - INFO - Epoch(train) [1023][25/63] lr: 6.3204e-04 eta: 2:06:15 time: 0.5245 data_time: 0.0119 memory: 16131 loss: 0.9706 loss_prob: 0.5099 loss_thr: 0.3733 loss_db: 0.0874 2022/10/26 07:51:21 - mmengine - INFO - Epoch(train) [1023][30/63] lr: 6.3204e-04 eta: 2:06:08 time: 0.5146 data_time: 0.0333 memory: 16131 loss: 0.9387 loss_prob: 0.4862 loss_thr: 0.3671 loss_db: 0.0854 2022/10/26 07:51:23 - mmengine - INFO - Epoch(train) [1023][35/63] lr: 6.3204e-04 eta: 2:06:08 time: 0.5086 data_time: 0.0283 memory: 16131 loss: 0.8766 loss_prob: 0.4561 loss_thr: 0.3389 loss_db: 0.0817 2022/10/26 07:51:26 - mmengine - INFO - Epoch(train) [1023][40/63] lr: 6.3204e-04 eta: 2:06:01 time: 0.5232 data_time: 0.0098 memory: 16131 loss: 1.0258 loss_prob: 0.5429 loss_thr: 0.3887 loss_db: 0.0943 2022/10/26 07:51:29 - mmengine - INFO - Epoch(train) [1023][45/63] lr: 6.3204e-04 eta: 2:06:01 time: 0.5576 data_time: 0.0107 memory: 16131 loss: 1.0472 loss_prob: 0.5543 loss_thr: 0.3993 loss_db: 0.0936 2022/10/26 07:51:31 - mmengine - INFO - Epoch(train) [1023][50/63] lr: 6.3204e-04 eta: 2:05:54 time: 0.5414 data_time: 0.0175 memory: 16131 loss: 0.8883 loss_prob: 0.4627 loss_thr: 0.3449 loss_db: 0.0806 2022/10/26 07:51:34 - mmengine - INFO - Epoch(train) [1023][55/63] lr: 6.3204e-04 eta: 2:05:54 time: 0.5145 data_time: 0.0209 memory: 16131 loss: 0.8689 loss_prob: 0.4459 loss_thr: 0.3433 loss_db: 0.0796 2022/10/26 07:51:37 - mmengine - INFO - Epoch(train) [1023][60/63] lr: 6.3204e-04 eta: 2:05:47 time: 0.5500 data_time: 0.0100 memory: 16131 loss: 0.9081 loss_prob: 0.4707 loss_thr: 0.3568 loss_db: 0.0806 2022/10/26 07:51:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:51:43 - mmengine - INFO - Epoch(train) [1024][5/63] lr: 6.2882e-04 eta: 2:05:47 time: 0.6928 data_time: 0.1697 memory: 16131 loss: 0.8941 loss_prob: 0.4700 loss_thr: 0.3423 loss_db: 0.0818 2022/10/26 07:51:45 - mmengine - INFO - Epoch(train) [1024][10/63] lr: 6.2882e-04 eta: 2:05:38 time: 0.7275 data_time: 0.1644 memory: 16131 loss: 0.8871 loss_prob: 0.4572 loss_thr: 0.3478 loss_db: 0.0821 2022/10/26 07:51:48 - mmengine - INFO - Epoch(train) [1024][15/63] lr: 6.2882e-04 eta: 2:05:38 time: 0.5163 data_time: 0.0102 memory: 16131 loss: 0.8900 loss_prob: 0.4592 loss_thr: 0.3506 loss_db: 0.0801 2022/10/26 07:51:51 - mmengine - INFO - Epoch(train) [1024][20/63] lr: 6.2882e-04 eta: 2:05:31 time: 0.5278 data_time: 0.0111 memory: 16131 loss: 0.9356 loss_prob: 0.4850 loss_thr: 0.3678 loss_db: 0.0828 2022/10/26 07:51:53 - mmengine - INFO - Epoch(train) [1024][25/63] lr: 6.2882e-04 eta: 2:05:31 time: 0.5286 data_time: 0.0092 memory: 16131 loss: 0.9527 loss_prob: 0.4896 loss_thr: 0.3772 loss_db: 0.0859 2022/10/26 07:51:56 - mmengine - INFO - Epoch(train) [1024][30/63] lr: 6.2882e-04 eta: 2:05:24 time: 0.5364 data_time: 0.0291 memory: 16131 loss: 0.8760 loss_prob: 0.4491 loss_thr: 0.3453 loss_db: 0.0817 2022/10/26 07:51:59 - mmengine - INFO - Epoch(train) [1024][35/63] lr: 6.2882e-04 eta: 2:05:24 time: 0.5296 data_time: 0.0259 memory: 16131 loss: 0.8990 loss_prob: 0.4716 loss_thr: 0.3459 loss_db: 0.0815 2022/10/26 07:52:01 - mmengine - INFO - Epoch(train) [1024][40/63] lr: 6.2882e-04 eta: 2:05:17 time: 0.4959 data_time: 0.0098 memory: 16131 loss: 0.9279 loss_prob: 0.4865 loss_thr: 0.3609 loss_db: 0.0806 2022/10/26 07:52:04 - mmengine - INFO - Epoch(train) [1024][45/63] lr: 6.2882e-04 eta: 2:05:17 time: 0.5112 data_time: 0.0107 memory: 16131 loss: 0.9520 loss_prob: 0.4943 loss_thr: 0.3730 loss_db: 0.0847 2022/10/26 07:52:06 - mmengine - INFO - Epoch(train) [1024][50/63] lr: 6.2882e-04 eta: 2:05:10 time: 0.5209 data_time: 0.0187 memory: 16131 loss: 0.8978 loss_prob: 0.4665 loss_thr: 0.3492 loss_db: 0.0821 2022/10/26 07:52:09 - mmengine - INFO - Epoch(train) [1024][55/63] lr: 6.2882e-04 eta: 2:05:10 time: 0.5004 data_time: 0.0183 memory: 16131 loss: 0.8911 loss_prob: 0.4679 loss_thr: 0.3429 loss_db: 0.0804 2022/10/26 07:52:11 - mmengine - INFO - Epoch(train) [1024][60/63] lr: 6.2882e-04 eta: 2:05:03 time: 0.4940 data_time: 0.0065 memory: 16131 loss: 0.8693 loss_prob: 0.4502 loss_thr: 0.3421 loss_db: 0.0770 2022/10/26 07:52:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:52:17 - mmengine - INFO - Epoch(train) [1025][5/63] lr: 6.2561e-04 eta: 2:05:03 time: 0.6954 data_time: 0.1528 memory: 16131 loss: 0.8530 loss_prob: 0.4462 loss_thr: 0.3286 loss_db: 0.0782 2022/10/26 07:52:20 - mmengine - INFO - Epoch(train) [1025][10/63] lr: 6.2561e-04 eta: 2:04:54 time: 0.6804 data_time: 0.1535 memory: 16131 loss: 0.8667 loss_prob: 0.4508 loss_thr: 0.3358 loss_db: 0.0800 2022/10/26 07:52:22 - mmengine - INFO - Epoch(train) [1025][15/63] lr: 6.2561e-04 eta: 2:04:54 time: 0.5057 data_time: 0.0122 memory: 16131 loss: 0.9251 loss_prob: 0.4803 loss_thr: 0.3604 loss_db: 0.0843 2022/10/26 07:52:25 - mmengine - INFO - Epoch(train) [1025][20/63] lr: 6.2561e-04 eta: 2:04:47 time: 0.5289 data_time: 0.0088 memory: 16131 loss: 0.9740 loss_prob: 0.5069 loss_thr: 0.3791 loss_db: 0.0880 2022/10/26 07:52:28 - mmengine - INFO - Epoch(train) [1025][25/63] lr: 6.2561e-04 eta: 2:04:47 time: 0.5443 data_time: 0.0134 memory: 16131 loss: 1.0722 loss_prob: 0.5694 loss_thr: 0.4063 loss_db: 0.0964 2022/10/26 07:52:30 - mmengine - INFO - Epoch(train) [1025][30/63] lr: 6.2561e-04 eta: 2:04:40 time: 0.5348 data_time: 0.0356 memory: 16131 loss: 1.0027 loss_prob: 0.5290 loss_thr: 0.3822 loss_db: 0.0915 2022/10/26 07:52:33 - mmengine - INFO - Epoch(train) [1025][35/63] lr: 6.2561e-04 eta: 2:04:40 time: 0.5203 data_time: 0.0304 memory: 16131 loss: 0.9409 loss_prob: 0.4854 loss_thr: 0.3685 loss_db: 0.0870 2022/10/26 07:52:35 - mmengine - INFO - Epoch(train) [1025][40/63] lr: 6.2561e-04 eta: 2:04:33 time: 0.5113 data_time: 0.0102 memory: 16131 loss: 0.9945 loss_prob: 0.5138 loss_thr: 0.3909 loss_db: 0.0897 2022/10/26 07:52:38 - mmengine - INFO - Epoch(train) [1025][45/63] lr: 6.2561e-04 eta: 2:04:33 time: 0.4985 data_time: 0.0078 memory: 16131 loss: 0.9900 loss_prob: 0.5144 loss_thr: 0.3863 loss_db: 0.0893 2022/10/26 07:52:41 - mmengine - INFO - Epoch(train) [1025][50/63] lr: 6.2561e-04 eta: 2:04:26 time: 0.5323 data_time: 0.0118 memory: 16131 loss: 0.9250 loss_prob: 0.4829 loss_thr: 0.3564 loss_db: 0.0857 2022/10/26 07:52:44 - mmengine - INFO - Epoch(train) [1025][55/63] lr: 6.2561e-04 eta: 2:04:26 time: 0.5809 data_time: 0.0315 memory: 16131 loss: 0.8196 loss_prob: 0.4250 loss_thr: 0.3185 loss_db: 0.0761 2022/10/26 07:52:46 - mmengine - INFO - Epoch(train) [1025][60/63] lr: 6.2561e-04 eta: 2:04:19 time: 0.5662 data_time: 0.0247 memory: 16131 loss: 0.7870 loss_prob: 0.4096 loss_thr: 0.3080 loss_db: 0.0695 2022/10/26 07:52:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:52:53 - mmengine - INFO - Epoch(train) [1026][5/63] lr: 6.2239e-04 eta: 2:04:19 time: 0.7506 data_time: 0.1925 memory: 16131 loss: 0.9715 loss_prob: 0.5162 loss_thr: 0.3689 loss_db: 0.0864 2022/10/26 07:52:56 - mmengine - INFO - Epoch(train) [1026][10/63] lr: 6.2239e-04 eta: 2:04:10 time: 0.8310 data_time: 0.1973 memory: 16131 loss: 0.9032 loss_prob: 0.4675 loss_thr: 0.3534 loss_db: 0.0823 2022/10/26 07:52:58 - mmengine - INFO - Epoch(train) [1026][15/63] lr: 6.2239e-04 eta: 2:04:10 time: 0.5686 data_time: 0.0140 memory: 16131 loss: 0.9082 loss_prob: 0.4713 loss_thr: 0.3534 loss_db: 0.0834 2022/10/26 07:53:01 - mmengine - INFO - Epoch(train) [1026][20/63] lr: 6.2239e-04 eta: 2:04:03 time: 0.5016 data_time: 0.0095 memory: 16131 loss: 0.9665 loss_prob: 0.5216 loss_thr: 0.3562 loss_db: 0.0887 2022/10/26 07:53:04 - mmengine - INFO - Epoch(train) [1026][25/63] lr: 6.2239e-04 eta: 2:04:03 time: 0.5171 data_time: 0.0141 memory: 16131 loss: 0.9558 loss_prob: 0.5161 loss_thr: 0.3521 loss_db: 0.0875 2022/10/26 07:53:07 - mmengine - INFO - Epoch(train) [1026][30/63] lr: 6.2239e-04 eta: 2:03:56 time: 0.5747 data_time: 0.0284 memory: 16131 loss: 0.9189 loss_prob: 0.4771 loss_thr: 0.3564 loss_db: 0.0854 2022/10/26 07:53:09 - mmengine - INFO - Epoch(train) [1026][35/63] lr: 6.2239e-04 eta: 2:03:56 time: 0.5599 data_time: 0.0276 memory: 16131 loss: 0.8875 loss_prob: 0.4596 loss_thr: 0.3457 loss_db: 0.0822 2022/10/26 07:53:12 - mmengine - INFO - Epoch(train) [1026][40/63] lr: 6.2239e-04 eta: 2:03:49 time: 0.5049 data_time: 0.0116 memory: 16131 loss: 0.8885 loss_prob: 0.4675 loss_thr: 0.3401 loss_db: 0.0809 2022/10/26 07:53:15 - mmengine - INFO - Epoch(train) [1026][45/63] lr: 6.2239e-04 eta: 2:03:49 time: 0.5266 data_time: 0.0074 memory: 16131 loss: 0.9290 loss_prob: 0.4910 loss_thr: 0.3543 loss_db: 0.0837 2022/10/26 07:53:17 - mmengine - INFO - Epoch(train) [1026][50/63] lr: 6.2239e-04 eta: 2:03:42 time: 0.5542 data_time: 0.0140 memory: 16131 loss: 0.9251 loss_prob: 0.4852 loss_thr: 0.3547 loss_db: 0.0851 2022/10/26 07:53:20 - mmengine - INFO - Epoch(train) [1026][55/63] lr: 6.2239e-04 eta: 2:03:42 time: 0.5254 data_time: 0.0177 memory: 16131 loss: 0.9478 loss_prob: 0.5011 loss_thr: 0.3587 loss_db: 0.0879 2022/10/26 07:53:22 - mmengine - INFO - Epoch(train) [1026][60/63] lr: 6.2239e-04 eta: 2:03:35 time: 0.4973 data_time: 0.0138 memory: 16131 loss: 0.9331 loss_prob: 0.4977 loss_thr: 0.3482 loss_db: 0.0873 2022/10/26 07:53:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:53:29 - mmengine - INFO - Epoch(train) [1027][5/63] lr: 6.1917e-04 eta: 2:03:35 time: 0.7831 data_time: 0.2221 memory: 16131 loss: 0.8861 loss_prob: 0.4615 loss_thr: 0.3453 loss_db: 0.0793 2022/10/26 07:53:32 - mmengine - INFO - Epoch(train) [1027][10/63] lr: 6.1917e-04 eta: 2:03:26 time: 0.8128 data_time: 0.2211 memory: 16131 loss: 1.0036 loss_prob: 0.5434 loss_thr: 0.3712 loss_db: 0.0891 2022/10/26 07:53:34 - mmengine - INFO - Epoch(train) [1027][15/63] lr: 6.1917e-04 eta: 2:03:26 time: 0.5105 data_time: 0.0089 memory: 16131 loss: 0.9979 loss_prob: 0.5448 loss_thr: 0.3619 loss_db: 0.0912 2022/10/26 07:53:37 - mmengine - INFO - Epoch(train) [1027][20/63] lr: 6.1917e-04 eta: 2:03:19 time: 0.5041 data_time: 0.0107 memory: 16131 loss: 1.0012 loss_prob: 0.5328 loss_thr: 0.3748 loss_db: 0.0936 2022/10/26 07:53:39 - mmengine - INFO - Epoch(train) [1027][25/63] lr: 6.1917e-04 eta: 2:03:19 time: 0.5249 data_time: 0.0255 memory: 16131 loss: 0.9772 loss_prob: 0.5347 loss_thr: 0.3500 loss_db: 0.0924 2022/10/26 07:53:42 - mmengine - INFO - Epoch(train) [1027][30/63] lr: 6.1917e-04 eta: 2:03:12 time: 0.5238 data_time: 0.0312 memory: 16131 loss: 0.9429 loss_prob: 0.5078 loss_thr: 0.3495 loss_db: 0.0857 2022/10/26 07:53:44 - mmengine - INFO - Epoch(train) [1027][35/63] lr: 6.1917e-04 eta: 2:03:12 time: 0.4978 data_time: 0.0186 memory: 16131 loss: 0.9463 loss_prob: 0.4900 loss_thr: 0.3722 loss_db: 0.0841 2022/10/26 07:53:47 - mmengine - INFO - Epoch(train) [1027][40/63] lr: 6.1917e-04 eta: 2:03:05 time: 0.5006 data_time: 0.0096 memory: 16131 loss: 0.9589 loss_prob: 0.4968 loss_thr: 0.3742 loss_db: 0.0880 2022/10/26 07:53:50 - mmengine - INFO - Epoch(train) [1027][45/63] lr: 6.1917e-04 eta: 2:03:05 time: 0.5454 data_time: 0.0054 memory: 16131 loss: 0.9332 loss_prob: 0.4811 loss_thr: 0.3655 loss_db: 0.0866 2022/10/26 07:53:52 - mmengine - INFO - Epoch(train) [1027][50/63] lr: 6.1917e-04 eta: 2:02:58 time: 0.5415 data_time: 0.0203 memory: 16131 loss: 0.9273 loss_prob: 0.4758 loss_thr: 0.3686 loss_db: 0.0829 2022/10/26 07:53:55 - mmengine - INFO - Epoch(train) [1027][55/63] lr: 6.1917e-04 eta: 2:02:58 time: 0.5086 data_time: 0.0210 memory: 16131 loss: 0.9949 loss_prob: 0.5228 loss_thr: 0.3835 loss_db: 0.0886 2022/10/26 07:53:58 - mmengine - INFO - Epoch(train) [1027][60/63] lr: 6.1917e-04 eta: 2:02:51 time: 0.5235 data_time: 0.0074 memory: 16131 loss: 0.9641 loss_prob: 0.5134 loss_thr: 0.3610 loss_db: 0.0896 2022/10/26 07:53:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:54:05 - mmengine - INFO - Epoch(train) [1028][5/63] lr: 6.1595e-04 eta: 2:02:51 time: 0.7947 data_time: 0.1824 memory: 16131 loss: 1.0062 loss_prob: 0.5448 loss_thr: 0.3691 loss_db: 0.0923 2022/10/26 07:54:07 - mmengine - INFO - Epoch(train) [1028][10/63] lr: 6.1595e-04 eta: 2:02:42 time: 0.7941 data_time: 0.1783 memory: 16131 loss: 0.9021 loss_prob: 0.4707 loss_thr: 0.3491 loss_db: 0.0823 2022/10/26 07:54:10 - mmengine - INFO - Epoch(train) [1028][15/63] lr: 6.1595e-04 eta: 2:02:42 time: 0.4943 data_time: 0.0074 memory: 16131 loss: 0.9639 loss_prob: 0.5091 loss_thr: 0.3681 loss_db: 0.0867 2022/10/26 07:54:12 - mmengine - INFO - Epoch(train) [1028][20/63] lr: 6.1595e-04 eta: 2:02:35 time: 0.5295 data_time: 0.0110 memory: 16131 loss: 1.0034 loss_prob: 0.5439 loss_thr: 0.3695 loss_db: 0.0900 2022/10/26 07:54:15 - mmengine - INFO - Epoch(train) [1028][25/63] lr: 6.1595e-04 eta: 2:02:35 time: 0.5684 data_time: 0.0186 memory: 16131 loss: 0.9508 loss_prob: 0.5048 loss_thr: 0.3586 loss_db: 0.0874 2022/10/26 07:54:18 - mmengine - INFO - Epoch(train) [1028][30/63] lr: 6.1595e-04 eta: 2:02:28 time: 0.5844 data_time: 0.0422 memory: 16131 loss: 0.8957 loss_prob: 0.4662 loss_thr: 0.3479 loss_db: 0.0815 2022/10/26 07:54:21 - mmengine - INFO - Epoch(train) [1028][35/63] lr: 6.1595e-04 eta: 2:02:28 time: 0.5554 data_time: 0.0338 memory: 16131 loss: 0.9306 loss_prob: 0.4979 loss_thr: 0.3505 loss_db: 0.0822 2022/10/26 07:54:24 - mmengine - INFO - Epoch(train) [1028][40/63] lr: 6.1595e-04 eta: 2:02:21 time: 0.5450 data_time: 0.0119 memory: 16131 loss: 0.9029 loss_prob: 0.4798 loss_thr: 0.3429 loss_db: 0.0803 2022/10/26 07:54:27 - mmengine - INFO - Epoch(train) [1028][45/63] lr: 6.1595e-04 eta: 2:02:21 time: 0.5776 data_time: 0.0121 memory: 16131 loss: 0.8655 loss_prob: 0.4469 loss_thr: 0.3411 loss_db: 0.0775 2022/10/26 07:54:29 - mmengine - INFO - Epoch(train) [1028][50/63] lr: 6.1595e-04 eta: 2:02:14 time: 0.5517 data_time: 0.0122 memory: 16131 loss: 0.9307 loss_prob: 0.4881 loss_thr: 0.3580 loss_db: 0.0846 2022/10/26 07:54:32 - mmengine - INFO - Epoch(train) [1028][55/63] lr: 6.1595e-04 eta: 2:02:14 time: 0.5525 data_time: 0.0245 memory: 16131 loss: 0.9524 loss_prob: 0.5071 loss_thr: 0.3579 loss_db: 0.0873 2022/10/26 07:54:35 - mmengine - INFO - Epoch(train) [1028][60/63] lr: 6.1595e-04 eta: 2:02:07 time: 0.6173 data_time: 0.0202 memory: 16131 loss: 0.9028 loss_prob: 0.4744 loss_thr: 0.3485 loss_db: 0.0800 2022/10/26 07:54:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:54:41 - mmengine - INFO - Epoch(train) [1029][5/63] lr: 6.1272e-04 eta: 2:02:07 time: 0.6903 data_time: 0.1617 memory: 16131 loss: 0.8891 loss_prob: 0.4593 loss_thr: 0.3498 loss_db: 0.0800 2022/10/26 07:54:44 - mmengine - INFO - Epoch(train) [1029][10/63] lr: 6.1272e-04 eta: 2:01:58 time: 0.7443 data_time: 0.1630 memory: 16131 loss: 0.9781 loss_prob: 0.5174 loss_thr: 0.3720 loss_db: 0.0888 2022/10/26 07:54:47 - mmengine - INFO - Epoch(train) [1029][15/63] lr: 6.1272e-04 eta: 2:01:58 time: 0.5763 data_time: 0.0081 memory: 16131 loss: 0.9264 loss_prob: 0.4916 loss_thr: 0.3501 loss_db: 0.0847 2022/10/26 07:54:50 - mmengine - INFO - Epoch(train) [1029][20/63] lr: 6.1272e-04 eta: 2:01:51 time: 0.5213 data_time: 0.0059 memory: 16131 loss: 0.9544 loss_prob: 0.5135 loss_thr: 0.3525 loss_db: 0.0884 2022/10/26 07:54:52 - mmengine - INFO - Epoch(train) [1029][25/63] lr: 6.1272e-04 eta: 2:01:51 time: 0.5301 data_time: 0.0123 memory: 16131 loss: 0.9458 loss_prob: 0.5105 loss_thr: 0.3489 loss_db: 0.0864 2022/10/26 07:54:55 - mmengine - INFO - Epoch(train) [1029][30/63] lr: 6.1272e-04 eta: 2:01:44 time: 0.5723 data_time: 0.0329 memory: 16131 loss: 0.8380 loss_prob: 0.4335 loss_thr: 0.3293 loss_db: 0.0752 2022/10/26 07:54:58 - mmengine - INFO - Epoch(train) [1029][35/63] lr: 6.1272e-04 eta: 2:01:44 time: 0.5810 data_time: 0.0282 memory: 16131 loss: 0.8029 loss_prob: 0.4068 loss_thr: 0.3238 loss_db: 0.0723 2022/10/26 07:55:01 - mmengine - INFO - Epoch(train) [1029][40/63] lr: 6.1272e-04 eta: 2:01:37 time: 0.5552 data_time: 0.0068 memory: 16131 loss: 0.8270 loss_prob: 0.4166 loss_thr: 0.3370 loss_db: 0.0734 2022/10/26 07:55:04 - mmengine - INFO - Epoch(train) [1029][45/63] lr: 6.1272e-04 eta: 2:01:37 time: 0.5598 data_time: 0.0059 memory: 16131 loss: 0.9143 loss_prob: 0.4743 loss_thr: 0.3586 loss_db: 0.0814 2022/10/26 07:55:06 - mmengine - INFO - Epoch(train) [1029][50/63] lr: 6.1272e-04 eta: 2:01:30 time: 0.5271 data_time: 0.0111 memory: 16131 loss: 1.0065 loss_prob: 0.5358 loss_thr: 0.3788 loss_db: 0.0919 2022/10/26 07:55:09 - mmengine - INFO - Epoch(train) [1029][55/63] lr: 6.1272e-04 eta: 2:01:30 time: 0.5030 data_time: 0.0207 memory: 16131 loss: 0.9909 loss_prob: 0.5408 loss_thr: 0.3615 loss_db: 0.0886 2022/10/26 07:55:11 - mmengine - INFO - Epoch(train) [1029][60/63] lr: 6.1272e-04 eta: 2:01:23 time: 0.5143 data_time: 0.0175 memory: 16131 loss: 0.8765 loss_prob: 0.4656 loss_thr: 0.3360 loss_db: 0.0750 2022/10/26 07:55:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:55:17 - mmengine - INFO - Epoch(train) [1030][5/63] lr: 6.0950e-04 eta: 2:01:23 time: 0.6751 data_time: 0.1753 memory: 16131 loss: 0.9617 loss_prob: 0.5011 loss_thr: 0.3744 loss_db: 0.0863 2022/10/26 07:55:20 - mmengine - INFO - Epoch(train) [1030][10/63] lr: 6.0950e-04 eta: 2:01:14 time: 0.7428 data_time: 0.1801 memory: 16131 loss: 0.9866 loss_prob: 0.5221 loss_thr: 0.3739 loss_db: 0.0906 2022/10/26 07:55:22 - mmengine - INFO - Epoch(train) [1030][15/63] lr: 6.0950e-04 eta: 2:01:14 time: 0.5354 data_time: 0.0110 memory: 16131 loss: 0.8745 loss_prob: 0.4587 loss_thr: 0.3346 loss_db: 0.0813 2022/10/26 07:55:25 - mmengine - INFO - Epoch(train) [1030][20/63] lr: 6.0950e-04 eta: 2:01:07 time: 0.4964 data_time: 0.0074 memory: 16131 loss: 0.8973 loss_prob: 0.4694 loss_thr: 0.3460 loss_db: 0.0819 2022/10/26 07:55:27 - mmengine - INFO - Epoch(train) [1030][25/63] lr: 6.0950e-04 eta: 2:01:07 time: 0.5005 data_time: 0.0170 memory: 16131 loss: 0.9567 loss_prob: 0.5046 loss_thr: 0.3662 loss_db: 0.0859 2022/10/26 07:55:30 - mmengine - INFO - Epoch(train) [1030][30/63] lr: 6.0950e-04 eta: 2:01:00 time: 0.5153 data_time: 0.0364 memory: 16131 loss: 0.8930 loss_prob: 0.4675 loss_thr: 0.3443 loss_db: 0.0812 2022/10/26 07:55:32 - mmengine - INFO - Epoch(train) [1030][35/63] lr: 6.0950e-04 eta: 2:01:00 time: 0.5083 data_time: 0.0255 memory: 16131 loss: 0.8237 loss_prob: 0.4258 loss_thr: 0.3225 loss_db: 0.0754 2022/10/26 07:55:35 - mmengine - INFO - Epoch(train) [1030][40/63] lr: 6.0950e-04 eta: 2:00:53 time: 0.5061 data_time: 0.0100 memory: 16131 loss: 0.9532 loss_prob: 0.4992 loss_thr: 0.3673 loss_db: 0.0867 2022/10/26 07:55:38 - mmengine - INFO - Epoch(train) [1030][45/63] lr: 6.0950e-04 eta: 2:00:53 time: 0.5049 data_time: 0.0109 memory: 16131 loss: 0.9719 loss_prob: 0.5097 loss_thr: 0.3758 loss_db: 0.0864 2022/10/26 07:55:40 - mmengine - INFO - Epoch(train) [1030][50/63] lr: 6.0950e-04 eta: 2:00:46 time: 0.5122 data_time: 0.0178 memory: 16131 loss: 0.8618 loss_prob: 0.4487 loss_thr: 0.3366 loss_db: 0.0765 2022/10/26 07:55:43 - mmengine - INFO - Epoch(train) [1030][55/63] lr: 6.0950e-04 eta: 2:00:46 time: 0.5310 data_time: 0.0309 memory: 16131 loss: 0.9143 loss_prob: 0.4754 loss_thr: 0.3557 loss_db: 0.0833 2022/10/26 07:55:45 - mmengine - INFO - Epoch(train) [1030][60/63] lr: 6.0950e-04 eta: 2:00:39 time: 0.5145 data_time: 0.0191 memory: 16131 loss: 0.9095 loss_prob: 0.4678 loss_thr: 0.3579 loss_db: 0.0837 2022/10/26 07:55:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:55:51 - mmengine - INFO - Epoch(train) [1031][5/63] lr: 6.0627e-04 eta: 2:00:39 time: 0.6992 data_time: 0.1799 memory: 16131 loss: 0.9436 loss_prob: 0.4931 loss_thr: 0.3660 loss_db: 0.0844 2022/10/26 07:55:54 - mmengine - INFO - Epoch(train) [1031][10/63] lr: 6.0627e-04 eta: 2:00:30 time: 0.6963 data_time: 0.1789 memory: 16131 loss: 0.8947 loss_prob: 0.4669 loss_thr: 0.3477 loss_db: 0.0801 2022/10/26 07:55:57 - mmengine - INFO - Epoch(train) [1031][15/63] lr: 6.0627e-04 eta: 2:00:30 time: 0.5265 data_time: 0.0064 memory: 16131 loss: 0.9706 loss_prob: 0.5098 loss_thr: 0.3733 loss_db: 0.0875 2022/10/26 07:55:59 - mmengine - INFO - Epoch(train) [1031][20/63] lr: 6.0627e-04 eta: 2:00:23 time: 0.5136 data_time: 0.0070 memory: 16131 loss: 0.9975 loss_prob: 0.5296 loss_thr: 0.3764 loss_db: 0.0915 2022/10/26 07:56:02 - mmengine - INFO - Epoch(train) [1031][25/63] lr: 6.0627e-04 eta: 2:00:23 time: 0.5126 data_time: 0.0131 memory: 16131 loss: 0.9268 loss_prob: 0.4891 loss_thr: 0.3536 loss_db: 0.0841 2022/10/26 07:56:05 - mmengine - INFO - Epoch(train) [1031][30/63] lr: 6.0627e-04 eta: 2:00:16 time: 0.5453 data_time: 0.0359 memory: 16131 loss: 0.9062 loss_prob: 0.4741 loss_thr: 0.3496 loss_db: 0.0825 2022/10/26 07:56:07 - mmengine - INFO - Epoch(train) [1031][35/63] lr: 6.0627e-04 eta: 2:00:16 time: 0.5536 data_time: 0.0284 memory: 16131 loss: 0.9484 loss_prob: 0.5007 loss_thr: 0.3604 loss_db: 0.0874 2022/10/26 07:56:10 - mmengine - INFO - Epoch(train) [1031][40/63] lr: 6.0627e-04 eta: 2:00:09 time: 0.5211 data_time: 0.0064 memory: 16131 loss: 0.8595 loss_prob: 0.4511 loss_thr: 0.3290 loss_db: 0.0794 2022/10/26 07:56:12 - mmengine - INFO - Epoch(train) [1031][45/63] lr: 6.0627e-04 eta: 2:00:09 time: 0.4954 data_time: 0.0066 memory: 16131 loss: 0.8087 loss_prob: 0.4204 loss_thr: 0.3129 loss_db: 0.0753 2022/10/26 07:56:16 - mmengine - INFO - Epoch(train) [1031][50/63] lr: 6.0627e-04 eta: 2:00:02 time: 0.5735 data_time: 0.0175 memory: 16131 loss: 0.8538 loss_prob: 0.4452 loss_thr: 0.3300 loss_db: 0.0786 2022/10/26 07:56:18 - mmengine - INFO - Epoch(train) [1031][55/63] lr: 6.0627e-04 eta: 2:00:02 time: 0.6072 data_time: 0.0320 memory: 16131 loss: 0.9791 loss_prob: 0.5268 loss_thr: 0.3643 loss_db: 0.0880 2022/10/26 07:56:22 - mmengine - INFO - Epoch(train) [1031][60/63] lr: 6.0627e-04 eta: 1:59:55 time: 0.6106 data_time: 0.0209 memory: 16131 loss: 1.0439 loss_prob: 0.5570 loss_thr: 0.3908 loss_db: 0.0961 2022/10/26 07:56:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:56:28 - mmengine - INFO - Epoch(train) [1032][5/63] lr: 6.0304e-04 eta: 1:59:55 time: 0.7547 data_time: 0.1729 memory: 16131 loss: 0.8022 loss_prob: 0.4123 loss_thr: 0.3181 loss_db: 0.0718 2022/10/26 07:56:30 - mmengine - INFO - Epoch(train) [1032][10/63] lr: 6.0304e-04 eta: 1:59:46 time: 0.7264 data_time: 0.1731 memory: 16131 loss: 0.8424 loss_prob: 0.4402 loss_thr: 0.3268 loss_db: 0.0754 2022/10/26 07:56:33 - mmengine - INFO - Epoch(train) [1032][15/63] lr: 6.0304e-04 eta: 1:59:46 time: 0.5255 data_time: 0.0178 memory: 16131 loss: 0.8952 loss_prob: 0.4676 loss_thr: 0.3458 loss_db: 0.0817 2022/10/26 07:56:35 - mmengine - INFO - Epoch(train) [1032][20/63] lr: 6.0304e-04 eta: 1:59:39 time: 0.5318 data_time: 0.0190 memory: 16131 loss: 0.8512 loss_prob: 0.4418 loss_thr: 0.3322 loss_db: 0.0772 2022/10/26 07:56:38 - mmengine - INFO - Epoch(train) [1032][25/63] lr: 6.0304e-04 eta: 1:59:39 time: 0.5440 data_time: 0.0169 memory: 16131 loss: 0.8601 loss_prob: 0.4462 loss_thr: 0.3364 loss_db: 0.0774 2022/10/26 07:56:41 - mmengine - INFO - Epoch(train) [1032][30/63] lr: 6.0304e-04 eta: 1:59:32 time: 0.5550 data_time: 0.0268 memory: 16131 loss: 0.8754 loss_prob: 0.4539 loss_thr: 0.3413 loss_db: 0.0801 2022/10/26 07:56:44 - mmengine - INFO - Epoch(train) [1032][35/63] lr: 6.0304e-04 eta: 1:59:32 time: 0.5492 data_time: 0.0206 memory: 16131 loss: 0.8371 loss_prob: 0.4297 loss_thr: 0.3310 loss_db: 0.0763 2022/10/26 07:56:46 - mmengine - INFO - Epoch(train) [1032][40/63] lr: 6.0304e-04 eta: 1:59:25 time: 0.5483 data_time: 0.0128 memory: 16131 loss: 0.9093 loss_prob: 0.4729 loss_thr: 0.3536 loss_db: 0.0829 2022/10/26 07:56:49 - mmengine - INFO - Epoch(train) [1032][45/63] lr: 6.0304e-04 eta: 1:59:25 time: 0.5152 data_time: 0.0147 memory: 16131 loss: 0.9302 loss_prob: 0.4872 loss_thr: 0.3583 loss_db: 0.0848 2022/10/26 07:56:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:56:51 - mmengine - INFO - Epoch(train) [1032][50/63] lr: 6.0304e-04 eta: 1:59:18 time: 0.4920 data_time: 0.0150 memory: 16131 loss: 0.9092 loss_prob: 0.4773 loss_thr: 0.3486 loss_db: 0.0833 2022/10/26 07:56:54 - mmengine - INFO - Epoch(train) [1032][55/63] lr: 6.0304e-04 eta: 1:59:18 time: 0.5119 data_time: 0.0201 memory: 16131 loss: 0.9287 loss_prob: 0.4850 loss_thr: 0.3580 loss_db: 0.0857 2022/10/26 07:56:57 - mmengine - INFO - Epoch(train) [1032][60/63] lr: 6.0304e-04 eta: 1:59:11 time: 0.5503 data_time: 0.0208 memory: 16131 loss: 0.9386 loss_prob: 0.4905 loss_thr: 0.3616 loss_db: 0.0865 2022/10/26 07:56:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:57:03 - mmengine - INFO - Epoch(train) [1033][5/63] lr: 5.9981e-04 eta: 1:59:11 time: 0.7290 data_time: 0.1708 memory: 16131 loss: 0.9316 loss_prob: 0.4851 loss_thr: 0.3635 loss_db: 0.0830 2022/10/26 07:57:06 - mmengine - INFO - Epoch(train) [1033][10/63] lr: 5.9981e-04 eta: 1:59:02 time: 0.7810 data_time: 0.1713 memory: 16131 loss: 0.9205 loss_prob: 0.4763 loss_thr: 0.3623 loss_db: 0.0820 2022/10/26 07:57:09 - mmengine - INFO - Epoch(train) [1033][15/63] lr: 5.9981e-04 eta: 1:59:02 time: 0.5215 data_time: 0.0096 memory: 16131 loss: 0.8629 loss_prob: 0.4484 loss_thr: 0.3348 loss_db: 0.0797 2022/10/26 07:57:11 - mmengine - INFO - Epoch(train) [1033][20/63] lr: 5.9981e-04 eta: 1:58:55 time: 0.4901 data_time: 0.0078 memory: 16131 loss: 0.9071 loss_prob: 0.4776 loss_thr: 0.3446 loss_db: 0.0850 2022/10/26 07:57:14 - mmengine - INFO - Epoch(train) [1033][25/63] lr: 5.9981e-04 eta: 1:58:55 time: 0.5140 data_time: 0.0316 memory: 16131 loss: 0.9613 loss_prob: 0.5081 loss_thr: 0.3639 loss_db: 0.0894 2022/10/26 07:57:16 - mmengine - INFO - Epoch(train) [1033][30/63] lr: 5.9981e-04 eta: 1:58:48 time: 0.5151 data_time: 0.0332 memory: 16131 loss: 0.9700 loss_prob: 0.5224 loss_thr: 0.3608 loss_db: 0.0869 2022/10/26 07:57:19 - mmengine - INFO - Epoch(train) [1033][35/63] lr: 5.9981e-04 eta: 1:58:48 time: 0.5040 data_time: 0.0134 memory: 16131 loss: 0.9046 loss_prob: 0.4714 loss_thr: 0.3551 loss_db: 0.0781 2022/10/26 07:57:21 - mmengine - INFO - Epoch(train) [1033][40/63] lr: 5.9981e-04 eta: 1:58:41 time: 0.5097 data_time: 0.0093 memory: 16131 loss: 0.9003 loss_prob: 0.4589 loss_thr: 0.3623 loss_db: 0.0791 2022/10/26 07:57:24 - mmengine - INFO - Epoch(train) [1033][45/63] lr: 5.9981e-04 eta: 1:58:41 time: 0.5431 data_time: 0.0064 memory: 16131 loss: 0.9498 loss_prob: 0.4980 loss_thr: 0.3648 loss_db: 0.0870 2022/10/26 07:57:27 - mmengine - INFO - Epoch(train) [1033][50/63] lr: 5.9981e-04 eta: 1:58:34 time: 0.5528 data_time: 0.0221 memory: 16131 loss: 0.8782 loss_prob: 0.4539 loss_thr: 0.3443 loss_db: 0.0800 2022/10/26 07:57:29 - mmengine - INFO - Epoch(train) [1033][55/63] lr: 5.9981e-04 eta: 1:58:34 time: 0.5095 data_time: 0.0234 memory: 16131 loss: 0.9788 loss_prob: 0.5148 loss_thr: 0.3747 loss_db: 0.0894 2022/10/26 07:57:32 - mmengine - INFO - Epoch(train) [1033][60/63] lr: 5.9981e-04 eta: 1:58:27 time: 0.5316 data_time: 0.0107 memory: 16131 loss: 0.9967 loss_prob: 0.5267 loss_thr: 0.3778 loss_db: 0.0923 2022/10/26 07:57:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:57:38 - mmengine - INFO - Epoch(train) [1034][5/63] lr: 5.9658e-04 eta: 1:58:27 time: 0.6639 data_time: 0.1592 memory: 16131 loss: 0.8891 loss_prob: 0.4609 loss_thr: 0.3486 loss_db: 0.0797 2022/10/26 07:57:41 - mmengine - INFO - Epoch(train) [1034][10/63] lr: 5.9658e-04 eta: 1:58:18 time: 0.7226 data_time: 0.1666 memory: 16131 loss: 0.8590 loss_prob: 0.4419 loss_thr: 0.3402 loss_db: 0.0770 2022/10/26 07:57:43 - mmengine - INFO - Epoch(train) [1034][15/63] lr: 5.9658e-04 eta: 1:58:18 time: 0.5566 data_time: 0.0139 memory: 16131 loss: 0.8721 loss_prob: 0.4486 loss_thr: 0.3450 loss_db: 0.0785 2022/10/26 07:57:46 - mmengine - INFO - Epoch(train) [1034][20/63] lr: 5.9658e-04 eta: 1:58:11 time: 0.5131 data_time: 0.0064 memory: 16131 loss: 0.9394 loss_prob: 0.5003 loss_thr: 0.3533 loss_db: 0.0858 2022/10/26 07:57:49 - mmengine - INFO - Epoch(train) [1034][25/63] lr: 5.9658e-04 eta: 1:58:11 time: 0.5400 data_time: 0.0420 memory: 16131 loss: 0.9011 loss_prob: 0.4807 loss_thr: 0.3382 loss_db: 0.0822 2022/10/26 07:57:51 - mmengine - INFO - Epoch(train) [1034][30/63] lr: 5.9658e-04 eta: 1:58:04 time: 0.5557 data_time: 0.0629 memory: 16131 loss: 0.8802 loss_prob: 0.4568 loss_thr: 0.3430 loss_db: 0.0804 2022/10/26 07:57:54 - mmengine - INFO - Epoch(train) [1034][35/63] lr: 5.9658e-04 eta: 1:58:04 time: 0.5060 data_time: 0.0261 memory: 16131 loss: 0.8980 loss_prob: 0.4667 loss_thr: 0.3488 loss_db: 0.0825 2022/10/26 07:57:56 - mmengine - INFO - Epoch(train) [1034][40/63] lr: 5.9658e-04 eta: 1:57:57 time: 0.5194 data_time: 0.0082 memory: 16131 loss: 0.8855 loss_prob: 0.4575 loss_thr: 0.3468 loss_db: 0.0811 2022/10/26 07:57:59 - mmengine - INFO - Epoch(train) [1034][45/63] lr: 5.9658e-04 eta: 1:57:57 time: 0.5414 data_time: 0.0078 memory: 16131 loss: 0.8387 loss_prob: 0.4301 loss_thr: 0.3321 loss_db: 0.0765 2022/10/26 07:58:02 - mmengine - INFO - Epoch(train) [1034][50/63] lr: 5.9658e-04 eta: 1:57:50 time: 0.5107 data_time: 0.0094 memory: 16131 loss: 0.8581 loss_prob: 0.4442 loss_thr: 0.3351 loss_db: 0.0787 2022/10/26 07:58:04 - mmengine - INFO - Epoch(train) [1034][55/63] lr: 5.9658e-04 eta: 1:57:50 time: 0.5046 data_time: 0.0222 memory: 16131 loss: 0.8631 loss_prob: 0.4496 loss_thr: 0.3349 loss_db: 0.0785 2022/10/26 07:58:07 - mmengine - INFO - Epoch(train) [1034][60/63] lr: 5.9658e-04 eta: 1:57:43 time: 0.5217 data_time: 0.0175 memory: 16131 loss: 0.8844 loss_prob: 0.4625 loss_thr: 0.3418 loss_db: 0.0801 2022/10/26 07:58:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:58:13 - mmengine - INFO - Epoch(train) [1035][5/63] lr: 5.9334e-04 eta: 1:57:43 time: 0.7077 data_time: 0.2062 memory: 16131 loss: 0.9703 loss_prob: 0.5127 loss_thr: 0.3669 loss_db: 0.0908 2022/10/26 07:58:16 - mmengine - INFO - Epoch(train) [1035][10/63] lr: 5.9334e-04 eta: 1:57:34 time: 0.7465 data_time: 0.1997 memory: 16131 loss: 0.9471 loss_prob: 0.4939 loss_thr: 0.3648 loss_db: 0.0885 2022/10/26 07:58:19 - mmengine - INFO - Epoch(train) [1035][15/63] lr: 5.9334e-04 eta: 1:57:34 time: 0.5765 data_time: 0.0053 memory: 16131 loss: 0.9098 loss_prob: 0.4663 loss_thr: 0.3599 loss_db: 0.0836 2022/10/26 07:58:21 - mmengine - INFO - Epoch(train) [1035][20/63] lr: 5.9334e-04 eta: 1:57:27 time: 0.5641 data_time: 0.0059 memory: 16131 loss: 0.8709 loss_prob: 0.4514 loss_thr: 0.3402 loss_db: 0.0793 2022/10/26 07:58:25 - mmengine - INFO - Epoch(train) [1035][25/63] lr: 5.9334e-04 eta: 1:57:27 time: 0.6008 data_time: 0.0320 memory: 16131 loss: 0.8529 loss_prob: 0.4419 loss_thr: 0.3351 loss_db: 0.0758 2022/10/26 07:58:27 - mmengine - INFO - Epoch(train) [1035][30/63] lr: 5.9334e-04 eta: 1:57:20 time: 0.5737 data_time: 0.0320 memory: 16131 loss: 0.8806 loss_prob: 0.4600 loss_thr: 0.3438 loss_db: 0.0769 2022/10/26 07:58:30 - mmengine - INFO - Epoch(train) [1035][35/63] lr: 5.9334e-04 eta: 1:57:20 time: 0.5081 data_time: 0.0063 memory: 16131 loss: 0.9136 loss_prob: 0.4822 loss_thr: 0.3499 loss_db: 0.0816 2022/10/26 07:58:32 - mmengine - INFO - Epoch(train) [1035][40/63] lr: 5.9334e-04 eta: 1:57:13 time: 0.5040 data_time: 0.0089 memory: 16131 loss: 0.9402 loss_prob: 0.4972 loss_thr: 0.3561 loss_db: 0.0869 2022/10/26 07:58:35 - mmengine - INFO - Epoch(train) [1035][45/63] lr: 5.9334e-04 eta: 1:57:13 time: 0.5064 data_time: 0.0122 memory: 16131 loss: 0.9584 loss_prob: 0.5045 loss_thr: 0.3655 loss_db: 0.0883 2022/10/26 07:58:38 - mmengine - INFO - Epoch(train) [1035][50/63] lr: 5.9334e-04 eta: 1:57:06 time: 0.5401 data_time: 0.0249 memory: 16131 loss: 0.9261 loss_prob: 0.4827 loss_thr: 0.3588 loss_db: 0.0846 2022/10/26 07:58:40 - mmengine - INFO - Epoch(train) [1035][55/63] lr: 5.9334e-04 eta: 1:57:06 time: 0.5558 data_time: 0.0206 memory: 16131 loss: 0.8995 loss_prob: 0.4676 loss_thr: 0.3492 loss_db: 0.0827 2022/10/26 07:58:43 - mmengine - INFO - Epoch(train) [1035][60/63] lr: 5.9334e-04 eta: 1:56:59 time: 0.5392 data_time: 0.0109 memory: 16131 loss: 0.8645 loss_prob: 0.4477 loss_thr: 0.3379 loss_db: 0.0789 2022/10/26 07:58:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:58:49 - mmengine - INFO - Epoch(train) [1036][5/63] lr: 5.9011e-04 eta: 1:56:59 time: 0.7044 data_time: 0.1763 memory: 16131 loss: 0.9556 loss_prob: 0.5163 loss_thr: 0.3531 loss_db: 0.0861 2022/10/26 07:58:52 - mmengine - INFO - Epoch(train) [1036][10/63] lr: 5.9011e-04 eta: 1:56:50 time: 0.7348 data_time: 0.1752 memory: 16131 loss: 0.8679 loss_prob: 0.4518 loss_thr: 0.3376 loss_db: 0.0785 2022/10/26 07:58:54 - mmengine - INFO - Epoch(train) [1036][15/63] lr: 5.9011e-04 eta: 1:56:50 time: 0.5215 data_time: 0.0053 memory: 16131 loss: 0.8612 loss_prob: 0.4459 loss_thr: 0.3345 loss_db: 0.0808 2022/10/26 07:58:57 - mmengine - INFO - Epoch(train) [1036][20/63] lr: 5.9011e-04 eta: 1:56:43 time: 0.5118 data_time: 0.0045 memory: 16131 loss: 1.0007 loss_prob: 0.5320 loss_thr: 0.3784 loss_db: 0.0903 2022/10/26 07:58:59 - mmengine - INFO - Epoch(train) [1036][25/63] lr: 5.9011e-04 eta: 1:56:43 time: 0.4990 data_time: 0.0127 memory: 16131 loss: 0.9933 loss_prob: 0.5284 loss_thr: 0.3770 loss_db: 0.0879 2022/10/26 07:59:02 - mmengine - INFO - Epoch(train) [1036][30/63] lr: 5.9011e-04 eta: 1:56:36 time: 0.5421 data_time: 0.0381 memory: 16131 loss: 0.9404 loss_prob: 0.4981 loss_thr: 0.3550 loss_db: 0.0874 2022/10/26 07:59:05 - mmengine - INFO - Epoch(train) [1036][35/63] lr: 5.9011e-04 eta: 1:56:36 time: 0.5413 data_time: 0.0298 memory: 16131 loss: 0.9233 loss_prob: 0.4867 loss_thr: 0.3502 loss_db: 0.0864 2022/10/26 07:59:07 - mmengine - INFO - Epoch(train) [1036][40/63] lr: 5.9011e-04 eta: 1:56:29 time: 0.4976 data_time: 0.0046 memory: 16131 loss: 0.8820 loss_prob: 0.4587 loss_thr: 0.3427 loss_db: 0.0805 2022/10/26 07:59:10 - mmengine - INFO - Epoch(train) [1036][45/63] lr: 5.9011e-04 eta: 1:56:29 time: 0.4948 data_time: 0.0047 memory: 16131 loss: 0.9146 loss_prob: 0.4788 loss_thr: 0.3525 loss_db: 0.0832 2022/10/26 07:59:12 - mmengine - INFO - Epoch(train) [1036][50/63] lr: 5.9011e-04 eta: 1:56:22 time: 0.5075 data_time: 0.0112 memory: 16131 loss: 0.9022 loss_prob: 0.4756 loss_thr: 0.3432 loss_db: 0.0834 2022/10/26 07:59:15 - mmengine - INFO - Epoch(train) [1036][55/63] lr: 5.9011e-04 eta: 1:56:22 time: 0.5365 data_time: 0.0242 memory: 16131 loss: 0.9283 loss_prob: 0.4862 loss_thr: 0.3574 loss_db: 0.0847 2022/10/26 07:59:17 - mmengine - INFO - Epoch(train) [1036][60/63] lr: 5.9011e-04 eta: 1:56:15 time: 0.5072 data_time: 0.0210 memory: 16131 loss: 0.9832 loss_prob: 0.5180 loss_thr: 0.3735 loss_db: 0.0917 2022/10/26 07:59:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:59:25 - mmengine - INFO - Epoch(train) [1037][5/63] lr: 5.8687e-04 eta: 1:56:15 time: 0.8303 data_time: 0.2013 memory: 16131 loss: 0.9324 loss_prob: 0.4969 loss_thr: 0.3501 loss_db: 0.0854 2022/10/26 07:59:27 - mmengine - INFO - Epoch(train) [1037][10/63] lr: 5.8687e-04 eta: 1:56:07 time: 0.8404 data_time: 0.1991 memory: 16131 loss: 1.0493 loss_prob: 0.5634 loss_thr: 0.3925 loss_db: 0.0933 2022/10/26 07:59:30 - mmengine - INFO - Epoch(train) [1037][15/63] lr: 5.8687e-04 eta: 1:56:07 time: 0.5094 data_time: 0.0072 memory: 16131 loss: 1.0245 loss_prob: 0.5414 loss_thr: 0.3922 loss_db: 0.0910 2022/10/26 07:59:32 - mmengine - INFO - Epoch(train) [1037][20/63] lr: 5.8687e-04 eta: 1:56:00 time: 0.4991 data_time: 0.0057 memory: 16131 loss: 0.8477 loss_prob: 0.4390 loss_thr: 0.3312 loss_db: 0.0775 2022/10/26 07:59:35 - mmengine - INFO - Epoch(train) [1037][25/63] lr: 5.8687e-04 eta: 1:56:00 time: 0.5028 data_time: 0.0103 memory: 16131 loss: 0.8104 loss_prob: 0.4235 loss_thr: 0.3124 loss_db: 0.0746 2022/10/26 07:59:38 - mmengine - INFO - Epoch(train) [1037][30/63] lr: 5.8687e-04 eta: 1:55:53 time: 0.5191 data_time: 0.0333 memory: 16131 loss: 0.9126 loss_prob: 0.4805 loss_thr: 0.3489 loss_db: 0.0833 2022/10/26 07:59:40 - mmengine - INFO - Epoch(train) [1037][35/63] lr: 5.8687e-04 eta: 1:55:53 time: 0.5332 data_time: 0.0294 memory: 16131 loss: 0.9839 loss_prob: 0.5174 loss_thr: 0.3766 loss_db: 0.0899 2022/10/26 07:59:43 - mmengine - INFO - Epoch(train) [1037][40/63] lr: 5.8687e-04 eta: 1:55:46 time: 0.5181 data_time: 0.0074 memory: 16131 loss: 1.0557 loss_prob: 0.5725 loss_thr: 0.3881 loss_db: 0.0951 2022/10/26 07:59:45 - mmengine - INFO - Epoch(train) [1037][45/63] lr: 5.8687e-04 eta: 1:55:46 time: 0.5025 data_time: 0.0079 memory: 16131 loss: 0.9848 loss_prob: 0.5301 loss_thr: 0.3661 loss_db: 0.0887 2022/10/26 07:59:48 - mmengine - INFO - Epoch(train) [1037][50/63] lr: 5.8687e-04 eta: 1:55:39 time: 0.5200 data_time: 0.0148 memory: 16131 loss: 0.9313 loss_prob: 0.4829 loss_thr: 0.3631 loss_db: 0.0853 2022/10/26 07:59:51 - mmengine - INFO - Epoch(train) [1037][55/63] lr: 5.8687e-04 eta: 1:55:39 time: 0.5314 data_time: 0.0251 memory: 16131 loss: 0.9418 loss_prob: 0.4940 loss_thr: 0.3628 loss_db: 0.0851 2022/10/26 07:59:53 - mmengine - INFO - Epoch(train) [1037][60/63] lr: 5.8687e-04 eta: 1:55:32 time: 0.5133 data_time: 0.0215 memory: 16131 loss: 0.9505 loss_prob: 0.4969 loss_thr: 0.3671 loss_db: 0.0865 2022/10/26 07:59:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 07:59:59 - mmengine - INFO - Epoch(train) [1038][5/63] lr: 5.8363e-04 eta: 1:55:32 time: 0.7112 data_time: 0.1813 memory: 16131 loss: 0.9001 loss_prob: 0.4656 loss_thr: 0.3526 loss_db: 0.0819 2022/10/26 08:00:02 - mmengine - INFO - Epoch(train) [1038][10/63] lr: 5.8363e-04 eta: 1:55:23 time: 0.7368 data_time: 0.1815 memory: 16131 loss: 0.9004 loss_prob: 0.4736 loss_thr: 0.3447 loss_db: 0.0822 2022/10/26 08:00:04 - mmengine - INFO - Epoch(train) [1038][15/63] lr: 5.8363e-04 eta: 1:55:23 time: 0.5063 data_time: 0.0062 memory: 16131 loss: 0.9411 loss_prob: 0.5019 loss_thr: 0.3540 loss_db: 0.0852 2022/10/26 08:00:07 - mmengine - INFO - Epoch(train) [1038][20/63] lr: 5.8363e-04 eta: 1:55:16 time: 0.4943 data_time: 0.0086 memory: 16131 loss: 0.9232 loss_prob: 0.4781 loss_thr: 0.3642 loss_db: 0.0808 2022/10/26 08:00:10 - mmengine - INFO - Epoch(train) [1038][25/63] lr: 5.8363e-04 eta: 1:55:16 time: 0.5380 data_time: 0.0282 memory: 16131 loss: 0.8910 loss_prob: 0.4618 loss_thr: 0.3510 loss_db: 0.0782 2022/10/26 08:00:12 - mmengine - INFO - Epoch(train) [1038][30/63] lr: 5.8363e-04 eta: 1:55:09 time: 0.5519 data_time: 0.0363 memory: 16131 loss: 0.9629 loss_prob: 0.5055 loss_thr: 0.3711 loss_db: 0.0863 2022/10/26 08:00:15 - mmengine - INFO - Epoch(train) [1038][35/63] lr: 5.8363e-04 eta: 1:55:09 time: 0.5130 data_time: 0.0155 memory: 16131 loss: 0.9516 loss_prob: 0.4893 loss_thr: 0.3767 loss_db: 0.0857 2022/10/26 08:00:17 - mmengine - INFO - Epoch(train) [1038][40/63] lr: 5.8363e-04 eta: 1:55:02 time: 0.5102 data_time: 0.0048 memory: 16131 loss: 0.9443 loss_prob: 0.4977 loss_thr: 0.3606 loss_db: 0.0861 2022/10/26 08:00:20 - mmengine - INFO - Epoch(train) [1038][45/63] lr: 5.8363e-04 eta: 1:55:02 time: 0.5344 data_time: 0.0051 memory: 16131 loss: 0.9339 loss_prob: 0.4943 loss_thr: 0.3544 loss_db: 0.0852 2022/10/26 08:00:23 - mmengine - INFO - Epoch(train) [1038][50/63] lr: 5.8363e-04 eta: 1:54:55 time: 0.5772 data_time: 0.0273 memory: 16131 loss: 0.9378 loss_prob: 0.4840 loss_thr: 0.3696 loss_db: 0.0842 2022/10/26 08:00:26 - mmengine - INFO - Epoch(train) [1038][55/63] lr: 5.8363e-04 eta: 1:54:55 time: 0.5909 data_time: 0.0273 memory: 16131 loss: 0.8962 loss_prob: 0.4573 loss_thr: 0.3592 loss_db: 0.0797 2022/10/26 08:00:28 - mmengine - INFO - Epoch(train) [1038][60/63] lr: 5.8363e-04 eta: 1:54:48 time: 0.5326 data_time: 0.0048 memory: 16131 loss: 0.9125 loss_prob: 0.4800 loss_thr: 0.3482 loss_db: 0.0843 2022/10/26 08:00:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:00:34 - mmengine - INFO - Epoch(train) [1039][5/63] lr: 5.8038e-04 eta: 1:54:48 time: 0.6919 data_time: 0.1998 memory: 16131 loss: 0.9666 loss_prob: 0.5158 loss_thr: 0.3608 loss_db: 0.0900 2022/10/26 08:00:37 - mmengine - INFO - Epoch(train) [1039][10/63] lr: 5.8038e-04 eta: 1:54:39 time: 0.7513 data_time: 0.2003 memory: 16131 loss: 0.9013 loss_prob: 0.4730 loss_thr: 0.3459 loss_db: 0.0824 2022/10/26 08:00:40 - mmengine - INFO - Epoch(train) [1039][15/63] lr: 5.8038e-04 eta: 1:54:39 time: 0.5514 data_time: 0.0099 memory: 16131 loss: 0.9051 loss_prob: 0.4883 loss_thr: 0.3341 loss_db: 0.0828 2022/10/26 08:00:42 - mmengine - INFO - Epoch(train) [1039][20/63] lr: 5.8038e-04 eta: 1:54:32 time: 0.5184 data_time: 0.0092 memory: 16131 loss: 1.0394 loss_prob: 0.5874 loss_thr: 0.3608 loss_db: 0.0912 2022/10/26 08:00:45 - mmengine - INFO - Epoch(train) [1039][25/63] lr: 5.8038e-04 eta: 1:54:32 time: 0.5230 data_time: 0.0103 memory: 16131 loss: 1.0793 loss_prob: 0.6001 loss_thr: 0.3833 loss_db: 0.0959 2022/10/26 08:00:48 - mmengine - INFO - Epoch(train) [1039][30/63] lr: 5.8038e-04 eta: 1:54:25 time: 0.5681 data_time: 0.0330 memory: 16131 loss: 0.9781 loss_prob: 0.5154 loss_thr: 0.3733 loss_db: 0.0893 2022/10/26 08:00:51 - mmengine - INFO - Epoch(train) [1039][35/63] lr: 5.8038e-04 eta: 1:54:25 time: 0.5336 data_time: 0.0284 memory: 16131 loss: 0.9591 loss_prob: 0.4969 loss_thr: 0.3752 loss_db: 0.0871 2022/10/26 08:00:53 - mmengine - INFO - Epoch(train) [1039][40/63] lr: 5.8038e-04 eta: 1:54:18 time: 0.5086 data_time: 0.0087 memory: 16131 loss: 0.9351 loss_prob: 0.4867 loss_thr: 0.3636 loss_db: 0.0848 2022/10/26 08:00:56 - mmengine - INFO - Epoch(train) [1039][45/63] lr: 5.8038e-04 eta: 1:54:18 time: 0.5433 data_time: 0.0142 memory: 16131 loss: 0.9008 loss_prob: 0.4676 loss_thr: 0.3512 loss_db: 0.0819 2022/10/26 08:00:59 - mmengine - INFO - Epoch(train) [1039][50/63] lr: 5.8038e-04 eta: 1:54:11 time: 0.5552 data_time: 0.0363 memory: 16131 loss: 0.9599 loss_prob: 0.5159 loss_thr: 0.3555 loss_db: 0.0885 2022/10/26 08:01:01 - mmengine - INFO - Epoch(train) [1039][55/63] lr: 5.8038e-04 eta: 1:54:11 time: 0.5290 data_time: 0.0323 memory: 16131 loss: 0.9022 loss_prob: 0.4861 loss_thr: 0.3335 loss_db: 0.0826 2022/10/26 08:01:04 - mmengine - INFO - Epoch(train) [1039][60/63] lr: 5.8038e-04 eta: 1:54:04 time: 0.5003 data_time: 0.0081 memory: 16131 loss: 0.8677 loss_prob: 0.4624 loss_thr: 0.3273 loss_db: 0.0779 2022/10/26 08:01:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:01:10 - mmengine - INFO - Epoch(train) [1040][5/63] lr: 5.7714e-04 eta: 1:54:04 time: 0.7132 data_time: 0.2267 memory: 16131 loss: 0.9492 loss_prob: 0.5143 loss_thr: 0.3488 loss_db: 0.0862 2022/10/26 08:01:13 - mmengine - INFO - Epoch(train) [1040][10/63] lr: 5.7714e-04 eta: 1:53:55 time: 0.7863 data_time: 0.2274 memory: 16131 loss: 0.8924 loss_prob: 0.4636 loss_thr: 0.3489 loss_db: 0.0799 2022/10/26 08:01:16 - mmengine - INFO - Epoch(train) [1040][15/63] lr: 5.7714e-04 eta: 1:53:55 time: 0.5738 data_time: 0.0078 memory: 16131 loss: 0.9269 loss_prob: 0.4723 loss_thr: 0.3710 loss_db: 0.0836 2022/10/26 08:01:18 - mmengine - INFO - Epoch(train) [1040][20/63] lr: 5.7714e-04 eta: 1:53:48 time: 0.5420 data_time: 0.0068 memory: 16131 loss: 0.8758 loss_prob: 0.4504 loss_thr: 0.3464 loss_db: 0.0790 2022/10/26 08:01:21 - mmengine - INFO - Epoch(train) [1040][25/63] lr: 5.7714e-04 eta: 1:53:48 time: 0.5622 data_time: 0.0358 memory: 16131 loss: 0.9000 loss_prob: 0.4670 loss_thr: 0.3507 loss_db: 0.0822 2022/10/26 08:01:24 - mmengine - INFO - Epoch(train) [1040][30/63] lr: 5.7714e-04 eta: 1:53:41 time: 0.5711 data_time: 0.0358 memory: 16131 loss: 0.9520 loss_prob: 0.4973 loss_thr: 0.3678 loss_db: 0.0869 2022/10/26 08:01:26 - mmengine - INFO - Epoch(train) [1040][35/63] lr: 5.7714e-04 eta: 1:53:41 time: 0.5204 data_time: 0.0061 memory: 16131 loss: 0.8976 loss_prob: 0.4686 loss_thr: 0.3484 loss_db: 0.0806 2022/10/26 08:01:29 - mmengine - INFO - Epoch(train) [1040][40/63] lr: 5.7714e-04 eta: 1:53:34 time: 0.4838 data_time: 0.0050 memory: 16131 loss: 0.9262 loss_prob: 0.4944 loss_thr: 0.3439 loss_db: 0.0880 2022/10/26 08:01:32 - mmengine - INFO - Epoch(train) [1040][45/63] lr: 5.7714e-04 eta: 1:53:34 time: 0.5091 data_time: 0.0055 memory: 16131 loss: 0.8969 loss_prob: 0.4799 loss_thr: 0.3302 loss_db: 0.0868 2022/10/26 08:01:34 - mmengine - INFO - Epoch(train) [1040][50/63] lr: 5.7714e-04 eta: 1:53:27 time: 0.5554 data_time: 0.0253 memory: 16131 loss: 0.8921 loss_prob: 0.4735 loss_thr: 0.3371 loss_db: 0.0815 2022/10/26 08:01:37 - mmengine - INFO - Epoch(train) [1040][55/63] lr: 5.7714e-04 eta: 1:53:27 time: 0.5333 data_time: 0.0266 memory: 16131 loss: 0.9090 loss_prob: 0.4815 loss_thr: 0.3463 loss_db: 0.0812 2022/10/26 08:01:39 - mmengine - INFO - Epoch(train) [1040][60/63] lr: 5.7714e-04 eta: 1:53:20 time: 0.4885 data_time: 0.0069 memory: 16131 loss: 0.8854 loss_prob: 0.4562 loss_thr: 0.3509 loss_db: 0.0783 2022/10/26 08:01:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:01:41 - mmengine - INFO - Saving checkpoint at 1040 epochs 2022/10/26 08:01:48 - mmengine - INFO - Epoch(val) [1040][5/32] eta: 1:53:20 time: 0.5315 data_time: 0.0858 memory: 16131 2022/10/26 08:01:50 - mmengine - INFO - Epoch(val) [1040][10/32] eta: 0:00:12 time: 0.5902 data_time: 0.0946 memory: 15724 2022/10/26 08:01:53 - mmengine - INFO - Epoch(val) [1040][15/32] eta: 0:00:12 time: 0.5351 data_time: 0.0380 memory: 15724 2022/10/26 08:01:56 - mmengine - INFO - Epoch(val) [1040][20/32] eta: 0:00:06 time: 0.5444 data_time: 0.0528 memory: 15724 2022/10/26 08:01:58 - mmengine - INFO - Epoch(val) [1040][25/32] eta: 0:00:06 time: 0.5412 data_time: 0.0432 memory: 15724 2022/10/26 08:02:01 - mmengine - INFO - Epoch(val) [1040][30/32] eta: 0:00:01 time: 0.5114 data_time: 0.0240 memory: 15724 2022/10/26 08:02:01 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8281, precision: 0.7840, hmean: 0.8054 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8281, precision: 0.8265, hmean: 0.8273 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8272, precision: 0.8463, hmean: 0.8366 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8247, precision: 0.8673, hmean: 0.8455 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8132, precision: 0.8894, hmean: 0.8496 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7439, precision: 0.9296, hmean: 0.8264 2022/10/26 08:02:01 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1916, precision: 0.9803, hmean: 0.3206 2022/10/26 08:02:01 - mmengine - INFO - Epoch(val) [1040][32/32] icdar/precision: 0.8894 icdar/recall: 0.8132 icdar/hmean: 0.8496 2022/10/26 08:02:06 - mmengine - INFO - Epoch(train) [1041][5/63] lr: 5.7389e-04 eta: 0:00:01 time: 0.7082 data_time: 0.1800 memory: 16131 loss: 0.8861 loss_prob: 0.4593 loss_thr: 0.3471 loss_db: 0.0798 2022/10/26 08:02:09 - mmengine - INFO - Epoch(train) [1041][10/63] lr: 5.7389e-04 eta: 1:53:11 time: 0.7700 data_time: 0.1913 memory: 16131 loss: 0.9976 loss_prob: 0.5337 loss_thr: 0.3732 loss_db: 0.0908 2022/10/26 08:02:12 - mmengine - INFO - Epoch(train) [1041][15/63] lr: 5.7389e-04 eta: 1:53:11 time: 0.5869 data_time: 0.0186 memory: 16131 loss: 0.9810 loss_prob: 0.5307 loss_thr: 0.3590 loss_db: 0.0913 2022/10/26 08:02:15 - mmengine - INFO - Epoch(train) [1041][20/63] lr: 5.7389e-04 eta: 1:53:04 time: 0.5798 data_time: 0.0072 memory: 16131 loss: 0.8893 loss_prob: 0.4721 loss_thr: 0.3337 loss_db: 0.0835 2022/10/26 08:02:18 - mmengine - INFO - Epoch(train) [1041][25/63] lr: 5.7389e-04 eta: 1:53:04 time: 0.5838 data_time: 0.0231 memory: 16131 loss: 0.8404 loss_prob: 0.4371 loss_thr: 0.3274 loss_db: 0.0759 2022/10/26 08:02:20 - mmengine - INFO - Epoch(train) [1041][30/63] lr: 5.7389e-04 eta: 1:52:57 time: 0.5534 data_time: 0.0296 memory: 16131 loss: 0.7839 loss_prob: 0.4002 loss_thr: 0.3143 loss_db: 0.0694 2022/10/26 08:02:23 - mmengine - INFO - Epoch(train) [1041][35/63] lr: 5.7389e-04 eta: 1:52:57 time: 0.5039 data_time: 0.0137 memory: 16131 loss: 0.8659 loss_prob: 0.4529 loss_thr: 0.3334 loss_db: 0.0795 2022/10/26 08:02:25 - mmengine - INFO - Epoch(train) [1041][40/63] lr: 5.7389e-04 eta: 1:52:50 time: 0.4940 data_time: 0.0083 memory: 16131 loss: 0.9648 loss_prob: 0.5282 loss_thr: 0.3487 loss_db: 0.0879 2022/10/26 08:02:28 - mmengine - INFO - Epoch(train) [1041][45/63] lr: 5.7389e-04 eta: 1:52:50 time: 0.5038 data_time: 0.0109 memory: 16131 loss: 0.9902 loss_prob: 0.5380 loss_thr: 0.3636 loss_db: 0.0887 2022/10/26 08:02:30 - mmengine - INFO - Epoch(train) [1041][50/63] lr: 5.7389e-04 eta: 1:52:43 time: 0.5106 data_time: 0.0193 memory: 16131 loss: 0.9525 loss_prob: 0.5024 loss_thr: 0.3650 loss_db: 0.0850 2022/10/26 08:02:33 - mmengine - INFO - Epoch(train) [1041][55/63] lr: 5.7389e-04 eta: 1:52:43 time: 0.5063 data_time: 0.0218 memory: 16131 loss: 0.9138 loss_prob: 0.4832 loss_thr: 0.3486 loss_db: 0.0820 2022/10/26 08:02:36 - mmengine - INFO - Epoch(train) [1041][60/63] lr: 5.7389e-04 eta: 1:52:36 time: 0.5081 data_time: 0.0132 memory: 16131 loss: 0.8941 loss_prob: 0.4679 loss_thr: 0.3447 loss_db: 0.0815 2022/10/26 08:02:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:02:41 - mmengine - INFO - Epoch(train) [1042][5/63] lr: 5.7064e-04 eta: 1:52:36 time: 0.6761 data_time: 0.1694 memory: 16131 loss: 0.8673 loss_prob: 0.4471 loss_thr: 0.3415 loss_db: 0.0788 2022/10/26 08:02:44 - mmengine - INFO - Epoch(train) [1042][10/63] lr: 5.7064e-04 eta: 1:52:27 time: 0.6988 data_time: 0.1753 memory: 16131 loss: 0.9111 loss_prob: 0.4740 loss_thr: 0.3544 loss_db: 0.0826 2022/10/26 08:02:46 - mmengine - INFO - Epoch(train) [1042][15/63] lr: 5.7064e-04 eta: 1:52:27 time: 0.4961 data_time: 0.0118 memory: 16131 loss: 0.9012 loss_prob: 0.4707 loss_thr: 0.3505 loss_db: 0.0801 2022/10/26 08:02:49 - mmengine - INFO - Epoch(train) [1042][20/63] lr: 5.7064e-04 eta: 1:52:20 time: 0.5060 data_time: 0.0051 memory: 16131 loss: 0.9117 loss_prob: 0.4726 loss_thr: 0.3569 loss_db: 0.0822 2022/10/26 08:02:51 - mmengine - INFO - Epoch(train) [1042][25/63] lr: 5.7064e-04 eta: 1:52:20 time: 0.5054 data_time: 0.0067 memory: 16131 loss: 0.8762 loss_prob: 0.4518 loss_thr: 0.3441 loss_db: 0.0803 2022/10/26 08:02:54 - mmengine - INFO - Epoch(train) [1042][30/63] lr: 5.7064e-04 eta: 1:52:13 time: 0.5099 data_time: 0.0283 memory: 16131 loss: 0.8905 loss_prob: 0.4565 loss_thr: 0.3555 loss_db: 0.0785 2022/10/26 08:02:57 - mmengine - INFO - Epoch(train) [1042][35/63] lr: 5.7064e-04 eta: 1:52:13 time: 0.5242 data_time: 0.0345 memory: 16131 loss: 0.9825 loss_prob: 0.5069 loss_thr: 0.3893 loss_db: 0.0864 2022/10/26 08:02:59 - mmengine - INFO - Epoch(train) [1042][40/63] lr: 5.7064e-04 eta: 1:52:06 time: 0.5038 data_time: 0.0145 memory: 16131 loss: 0.9785 loss_prob: 0.5195 loss_thr: 0.3691 loss_db: 0.0899 2022/10/26 08:03:02 - mmengine - INFO - Epoch(train) [1042][45/63] lr: 5.7064e-04 eta: 1:52:06 time: 0.4993 data_time: 0.0092 memory: 16131 loss: 0.9868 loss_prob: 0.5292 loss_thr: 0.3641 loss_db: 0.0935 2022/10/26 08:03:04 - mmengine - INFO - Epoch(train) [1042][50/63] lr: 5.7064e-04 eta: 1:51:59 time: 0.5293 data_time: 0.0129 memory: 16131 loss: 0.9030 loss_prob: 0.4745 loss_thr: 0.3446 loss_db: 0.0839 2022/10/26 08:03:08 - mmengine - INFO - Epoch(train) [1042][55/63] lr: 5.7064e-04 eta: 1:51:59 time: 0.5954 data_time: 0.0267 memory: 16131 loss: 0.8407 loss_prob: 0.4408 loss_thr: 0.3244 loss_db: 0.0755 2022/10/26 08:03:10 - mmengine - INFO - Epoch(train) [1042][60/63] lr: 5.7064e-04 eta: 1:51:53 time: 0.6057 data_time: 0.0221 memory: 16131 loss: 0.8390 loss_prob: 0.4418 loss_thr: 0.3217 loss_db: 0.0754 2022/10/26 08:03:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:03:16 - mmengine - INFO - Epoch(train) [1043][5/63] lr: 5.6739e-04 eta: 1:51:53 time: 0.6965 data_time: 0.1925 memory: 16131 loss: 0.8748 loss_prob: 0.4560 loss_thr: 0.3406 loss_db: 0.0782 2022/10/26 08:03:19 - mmengine - INFO - Epoch(train) [1043][10/63] lr: 5.6739e-04 eta: 1:51:43 time: 0.6954 data_time: 0.1946 memory: 16131 loss: 0.8357 loss_prob: 0.4194 loss_thr: 0.3423 loss_db: 0.0740 2022/10/26 08:03:21 - mmengine - INFO - Epoch(train) [1043][15/63] lr: 5.6739e-04 eta: 1:51:43 time: 0.4981 data_time: 0.0078 memory: 16131 loss: 0.9549 loss_prob: 0.4918 loss_thr: 0.3783 loss_db: 0.0848 2022/10/26 08:03:24 - mmengine - INFO - Epoch(train) [1043][20/63] lr: 5.6739e-04 eta: 1:51:37 time: 0.5210 data_time: 0.0116 memory: 16131 loss: 0.9994 loss_prob: 0.5233 loss_thr: 0.3844 loss_db: 0.0917 2022/10/26 08:03:27 - mmengine - INFO - Epoch(train) [1043][25/63] lr: 5.6739e-04 eta: 1:51:37 time: 0.5452 data_time: 0.0301 memory: 16131 loss: 0.9007 loss_prob: 0.4717 loss_thr: 0.3443 loss_db: 0.0848 2022/10/26 08:03:30 - mmengine - INFO - Epoch(train) [1043][30/63] lr: 5.6739e-04 eta: 1:51:30 time: 0.5689 data_time: 0.0351 memory: 16131 loss: 0.9445 loss_prob: 0.4999 loss_thr: 0.3563 loss_db: 0.0883 2022/10/26 08:03:32 - mmengine - INFO - Epoch(train) [1043][35/63] lr: 5.6739e-04 eta: 1:51:30 time: 0.5497 data_time: 0.0171 memory: 16131 loss: 0.9813 loss_prob: 0.5217 loss_thr: 0.3712 loss_db: 0.0883 2022/10/26 08:03:35 - mmengine - INFO - Epoch(train) [1043][40/63] lr: 5.6739e-04 eta: 1:51:23 time: 0.5075 data_time: 0.0061 memory: 16131 loss: 0.9497 loss_prob: 0.5052 loss_thr: 0.3599 loss_db: 0.0846 2022/10/26 08:03:37 - mmengine - INFO - Epoch(train) [1043][45/63] lr: 5.6739e-04 eta: 1:51:23 time: 0.5000 data_time: 0.0057 memory: 16131 loss: 0.9429 loss_prob: 0.4963 loss_thr: 0.3608 loss_db: 0.0858 2022/10/26 08:03:40 - mmengine - INFO - Epoch(train) [1043][50/63] lr: 5.6739e-04 eta: 1:51:16 time: 0.5400 data_time: 0.0244 memory: 16131 loss: 0.8473 loss_prob: 0.4381 loss_thr: 0.3337 loss_db: 0.0756 2022/10/26 08:03:43 - mmengine - INFO - Epoch(train) [1043][55/63] lr: 5.6739e-04 eta: 1:51:16 time: 0.5656 data_time: 0.0315 memory: 16131 loss: 0.8896 loss_prob: 0.4664 loss_thr: 0.3440 loss_db: 0.0793 2022/10/26 08:03:45 - mmengine - INFO - Epoch(train) [1043][60/63] lr: 5.6739e-04 eta: 1:51:09 time: 0.5422 data_time: 0.0130 memory: 16131 loss: 0.9513 loss_prob: 0.5038 loss_thr: 0.3620 loss_db: 0.0856 2022/10/26 08:03:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:03:51 - mmengine - INFO - Epoch(train) [1044][5/63] lr: 5.6414e-04 eta: 1:51:09 time: 0.7122 data_time: 0.1904 memory: 16131 loss: 0.8594 loss_prob: 0.4481 loss_thr: 0.3323 loss_db: 0.0790 2022/10/26 08:03:54 - mmengine - INFO - Epoch(train) [1044][10/63] lr: 5.6414e-04 eta: 1:51:00 time: 0.7333 data_time: 0.1941 memory: 16131 loss: 0.8864 loss_prob: 0.4671 loss_thr: 0.3366 loss_db: 0.0826 2022/10/26 08:03:57 - mmengine - INFO - Epoch(train) [1044][15/63] lr: 5.6414e-04 eta: 1:51:00 time: 0.5343 data_time: 0.0088 memory: 16131 loss: 0.9140 loss_prob: 0.4879 loss_thr: 0.3418 loss_db: 0.0843 2022/10/26 08:03:59 - mmengine - INFO - Epoch(train) [1044][20/63] lr: 5.6414e-04 eta: 1:50:53 time: 0.5131 data_time: 0.0060 memory: 16131 loss: 0.8919 loss_prob: 0.4681 loss_thr: 0.3436 loss_db: 0.0802 2022/10/26 08:04:02 - mmengine - INFO - Epoch(train) [1044][25/63] lr: 5.6414e-04 eta: 1:50:53 time: 0.5218 data_time: 0.0212 memory: 16131 loss: 0.9215 loss_prob: 0.4811 loss_thr: 0.3567 loss_db: 0.0836 2022/10/26 08:04:05 - mmengine - INFO - Epoch(train) [1044][30/63] lr: 5.6414e-04 eta: 1:50:46 time: 0.5232 data_time: 0.0311 memory: 16131 loss: 0.8971 loss_prob: 0.4663 loss_thr: 0.3489 loss_db: 0.0820 2022/10/26 08:04:07 - mmengine - INFO - Epoch(train) [1044][35/63] lr: 5.6414e-04 eta: 1:50:46 time: 0.5127 data_time: 0.0182 memory: 16131 loss: 0.8600 loss_prob: 0.4429 loss_thr: 0.3396 loss_db: 0.0775 2022/10/26 08:04:10 - mmengine - INFO - Epoch(train) [1044][40/63] lr: 5.6414e-04 eta: 1:50:39 time: 0.5023 data_time: 0.0082 memory: 16131 loss: 0.8662 loss_prob: 0.4512 loss_thr: 0.3363 loss_db: 0.0787 2022/10/26 08:04:12 - mmengine - INFO - Epoch(train) [1044][45/63] lr: 5.6414e-04 eta: 1:50:39 time: 0.4935 data_time: 0.0065 memory: 16131 loss: 0.9172 loss_prob: 0.4862 loss_thr: 0.3475 loss_db: 0.0835 2022/10/26 08:04:15 - mmengine - INFO - Epoch(train) [1044][50/63] lr: 5.6414e-04 eta: 1:50:32 time: 0.5229 data_time: 0.0258 memory: 16131 loss: 0.8813 loss_prob: 0.4633 loss_thr: 0.3370 loss_db: 0.0809 2022/10/26 08:04:18 - mmengine - INFO - Epoch(train) [1044][55/63] lr: 5.6414e-04 eta: 1:50:32 time: 0.5517 data_time: 0.0264 memory: 16131 loss: 0.8834 loss_prob: 0.4631 loss_thr: 0.3415 loss_db: 0.0789 2022/10/26 08:04:20 - mmengine - INFO - Epoch(train) [1044][60/63] lr: 5.6414e-04 eta: 1:50:25 time: 0.5080 data_time: 0.0064 memory: 16131 loss: 0.9866 loss_prob: 0.5253 loss_thr: 0.3720 loss_db: 0.0892 2022/10/26 08:04:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:04:26 - mmengine - INFO - Epoch(train) [1045][5/63] lr: 5.6088e-04 eta: 1:50:25 time: 0.6910 data_time: 0.2059 memory: 16131 loss: 0.8739 loss_prob: 0.4447 loss_thr: 0.3489 loss_db: 0.0804 2022/10/26 08:04:29 - mmengine - INFO - Epoch(train) [1045][10/63] lr: 5.6088e-04 eta: 1:50:16 time: 0.7447 data_time: 0.2048 memory: 16131 loss: 0.8289 loss_prob: 0.4224 loss_thr: 0.3324 loss_db: 0.0740 2022/10/26 08:04:31 - mmengine - INFO - Epoch(train) [1045][15/63] lr: 5.6088e-04 eta: 1:50:16 time: 0.5482 data_time: 0.0098 memory: 16131 loss: 0.8586 loss_prob: 0.4414 loss_thr: 0.3420 loss_db: 0.0752 2022/10/26 08:04:34 - mmengine - INFO - Epoch(train) [1045][20/63] lr: 5.6088e-04 eta: 1:50:09 time: 0.5117 data_time: 0.0100 memory: 16131 loss: 0.8560 loss_prob: 0.4342 loss_thr: 0.3464 loss_db: 0.0754 2022/10/26 08:04:36 - mmengine - INFO - Epoch(train) [1045][25/63] lr: 5.6088e-04 eta: 1:50:09 time: 0.4973 data_time: 0.0180 memory: 16131 loss: 0.9160 loss_prob: 0.4706 loss_thr: 0.3616 loss_db: 0.0838 2022/10/26 08:04:39 - mmengine - INFO - Epoch(train) [1045][30/63] lr: 5.6088e-04 eta: 1:50:02 time: 0.5148 data_time: 0.0286 memory: 16131 loss: 0.9833 loss_prob: 0.5219 loss_thr: 0.3706 loss_db: 0.0908 2022/10/26 08:04:41 - mmengine - INFO - Epoch(train) [1045][35/63] lr: 5.6088e-04 eta: 1:50:02 time: 0.4972 data_time: 0.0196 memory: 16131 loss: 0.9269 loss_prob: 0.4959 loss_thr: 0.3459 loss_db: 0.0852 2022/10/26 08:04:44 - mmengine - INFO - Epoch(train) [1045][40/63] lr: 5.6088e-04 eta: 1:49:55 time: 0.5180 data_time: 0.0177 memory: 16131 loss: 0.8472 loss_prob: 0.4465 loss_thr: 0.3240 loss_db: 0.0767 2022/10/26 08:04:47 - mmengine - INFO - Epoch(train) [1045][45/63] lr: 5.6088e-04 eta: 1:49:55 time: 0.5451 data_time: 0.0139 memory: 16131 loss: 0.8498 loss_prob: 0.4390 loss_thr: 0.3342 loss_db: 0.0766 2022/10/26 08:04:49 - mmengine - INFO - Epoch(train) [1045][50/63] lr: 5.6088e-04 eta: 1:49:48 time: 0.5297 data_time: 0.0186 memory: 16131 loss: 0.8994 loss_prob: 0.4678 loss_thr: 0.3494 loss_db: 0.0822 2022/10/26 08:04:52 - mmengine - INFO - Epoch(train) [1045][55/63] lr: 5.6088e-04 eta: 1:49:48 time: 0.5458 data_time: 0.0189 memory: 16131 loss: 0.9619 loss_prob: 0.5110 loss_thr: 0.3617 loss_db: 0.0893 2022/10/26 08:04:55 - mmengine - INFO - Epoch(train) [1045][60/63] lr: 5.6088e-04 eta: 1:49:41 time: 0.5290 data_time: 0.0081 memory: 16131 loss: 0.9069 loss_prob: 0.4755 loss_thr: 0.3474 loss_db: 0.0839 2022/10/26 08:04:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:05:02 - mmengine - INFO - Epoch(train) [1046][5/63] lr: 5.5763e-04 eta: 1:49:41 time: 0.8189 data_time: 0.2179 memory: 16131 loss: 0.9097 loss_prob: 0.4714 loss_thr: 0.3569 loss_db: 0.0814 2022/10/26 08:05:05 - mmengine - INFO - Epoch(train) [1046][10/63] lr: 5.5763e-04 eta: 1:49:32 time: 0.8309 data_time: 0.2154 memory: 16131 loss: 0.9230 loss_prob: 0.4797 loss_thr: 0.3588 loss_db: 0.0845 2022/10/26 08:05:07 - mmengine - INFO - Epoch(train) [1046][15/63] lr: 5.5763e-04 eta: 1:49:32 time: 0.5132 data_time: 0.0060 memory: 16131 loss: 0.9337 loss_prob: 0.4880 loss_thr: 0.3599 loss_db: 0.0858 2022/10/26 08:05:10 - mmengine - INFO - Epoch(train) [1046][20/63] lr: 5.5763e-04 eta: 1:49:25 time: 0.5021 data_time: 0.0057 memory: 16131 loss: 0.9107 loss_prob: 0.4719 loss_thr: 0.3545 loss_db: 0.0843 2022/10/26 08:05:12 - mmengine - INFO - Epoch(train) [1046][25/63] lr: 5.5763e-04 eta: 1:49:25 time: 0.5349 data_time: 0.0315 memory: 16131 loss: 0.9150 loss_prob: 0.4686 loss_thr: 0.3626 loss_db: 0.0838 2022/10/26 08:05:15 - mmengine - INFO - Epoch(train) [1046][30/63] lr: 5.5763e-04 eta: 1:49:18 time: 0.5490 data_time: 0.0326 memory: 16131 loss: 0.9037 loss_prob: 0.4705 loss_thr: 0.3515 loss_db: 0.0816 2022/10/26 08:05:18 - mmengine - INFO - Epoch(train) [1046][35/63] lr: 5.5763e-04 eta: 1:49:18 time: 0.5156 data_time: 0.0075 memory: 16131 loss: 0.9722 loss_prob: 0.5205 loss_thr: 0.3621 loss_db: 0.0896 2022/10/26 08:05:20 - mmengine - INFO - Epoch(train) [1046][40/63] lr: 5.5763e-04 eta: 1:49:11 time: 0.5006 data_time: 0.0062 memory: 16131 loss: 0.9282 loss_prob: 0.4901 loss_thr: 0.3538 loss_db: 0.0842 2022/10/26 08:05:23 - mmengine - INFO - Epoch(train) [1046][45/63] lr: 5.5763e-04 eta: 1:49:11 time: 0.5656 data_time: 0.0053 memory: 16131 loss: 0.7953 loss_prob: 0.4037 loss_thr: 0.3209 loss_db: 0.0707 2022/10/26 08:05:26 - mmengine - INFO - Epoch(train) [1046][50/63] lr: 5.5763e-04 eta: 1:49:04 time: 0.5814 data_time: 0.0225 memory: 16131 loss: 0.8272 loss_prob: 0.4294 loss_thr: 0.3236 loss_db: 0.0742 2022/10/26 08:05:29 - mmengine - INFO - Epoch(train) [1046][55/63] lr: 5.5763e-04 eta: 1:49:04 time: 0.5323 data_time: 0.0240 memory: 16131 loss: 0.8668 loss_prob: 0.4564 loss_thr: 0.3320 loss_db: 0.0784 2022/10/26 08:05:31 - mmengine - INFO - Epoch(train) [1046][60/63] lr: 5.5763e-04 eta: 1:48:58 time: 0.5323 data_time: 0.0064 memory: 16131 loss: 0.9129 loss_prob: 0.4779 loss_thr: 0.3520 loss_db: 0.0830 2022/10/26 08:05:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:05:37 - mmengine - INFO - Epoch(train) [1047][5/63] lr: 5.5437e-04 eta: 1:48:58 time: 0.7060 data_time: 0.1829 memory: 16131 loss: 0.9850 loss_prob: 0.5238 loss_thr: 0.3719 loss_db: 0.0893 2022/10/26 08:05:40 - mmengine - INFO - Epoch(train) [1047][10/63] lr: 5.5437e-04 eta: 1:48:49 time: 0.7101 data_time: 0.1886 memory: 16131 loss: 0.8982 loss_prob: 0.4622 loss_thr: 0.3550 loss_db: 0.0810 2022/10/26 08:05:42 - mmengine - INFO - Epoch(train) [1047][15/63] lr: 5.5437e-04 eta: 1:48:49 time: 0.5096 data_time: 0.0109 memory: 16131 loss: 0.9486 loss_prob: 0.4993 loss_thr: 0.3634 loss_db: 0.0860 2022/10/26 08:05:45 - mmengine - INFO - Epoch(train) [1047][20/63] lr: 5.5437e-04 eta: 1:48:42 time: 0.5136 data_time: 0.0051 memory: 16131 loss: 0.9064 loss_prob: 0.4734 loss_thr: 0.3511 loss_db: 0.0820 2022/10/26 08:05:48 - mmengine - INFO - Epoch(train) [1047][25/63] lr: 5.5437e-04 eta: 1:48:42 time: 0.5163 data_time: 0.0156 memory: 16131 loss: 0.8880 loss_prob: 0.4492 loss_thr: 0.3599 loss_db: 0.0789 2022/10/26 08:05:50 - mmengine - INFO - Epoch(train) [1047][30/63] lr: 5.5437e-04 eta: 1:48:35 time: 0.5044 data_time: 0.0305 memory: 16131 loss: 0.9711 loss_prob: 0.5109 loss_thr: 0.3729 loss_db: 0.0873 2022/10/26 08:05:53 - mmengine - INFO - Epoch(train) [1047][35/63] lr: 5.5437e-04 eta: 1:48:35 time: 0.5324 data_time: 0.0233 memory: 16131 loss: 0.8843 loss_prob: 0.4668 loss_thr: 0.3377 loss_db: 0.0798 2022/10/26 08:05:56 - mmengine - INFO - Epoch(train) [1047][40/63] lr: 5.5437e-04 eta: 1:48:28 time: 0.5721 data_time: 0.0090 memory: 16131 loss: 0.8158 loss_prob: 0.4181 loss_thr: 0.3239 loss_db: 0.0738 2022/10/26 08:05:58 - mmengine - INFO - Epoch(train) [1047][45/63] lr: 5.5437e-04 eta: 1:48:28 time: 0.5441 data_time: 0.0066 memory: 16131 loss: 0.8409 loss_prob: 0.4305 loss_thr: 0.3345 loss_db: 0.0759 2022/10/26 08:06:01 - mmengine - INFO - Epoch(train) [1047][50/63] lr: 5.5437e-04 eta: 1:48:21 time: 0.5022 data_time: 0.0135 memory: 16131 loss: 0.8657 loss_prob: 0.4520 loss_thr: 0.3374 loss_db: 0.0763 2022/10/26 08:06:03 - mmengine - INFO - Epoch(train) [1047][55/63] lr: 5.5437e-04 eta: 1:48:21 time: 0.5136 data_time: 0.0239 memory: 16131 loss: 0.8676 loss_prob: 0.4546 loss_thr: 0.3354 loss_db: 0.0776 2022/10/26 08:06:06 - mmengine - INFO - Epoch(train) [1047][60/63] lr: 5.5437e-04 eta: 1:48:14 time: 0.5292 data_time: 0.0165 memory: 16131 loss: 0.8270 loss_prob: 0.4182 loss_thr: 0.3344 loss_db: 0.0744 2022/10/26 08:06:07 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:06:12 - mmengine - INFO - Epoch(train) [1048][5/63] lr: 5.5111e-04 eta: 1:48:14 time: 0.6977 data_time: 0.1854 memory: 16131 loss: 0.8797 loss_prob: 0.4549 loss_thr: 0.3445 loss_db: 0.0803 2022/10/26 08:06:15 - mmengine - INFO - Epoch(train) [1048][10/63] lr: 5.5111e-04 eta: 1:48:05 time: 0.7219 data_time: 0.1852 memory: 16131 loss: 0.8580 loss_prob: 0.4468 loss_thr: 0.3327 loss_db: 0.0784 2022/10/26 08:06:17 - mmengine - INFO - Epoch(train) [1048][15/63] lr: 5.5111e-04 eta: 1:48:05 time: 0.5223 data_time: 0.0055 memory: 16131 loss: 0.8613 loss_prob: 0.4528 loss_thr: 0.3303 loss_db: 0.0782 2022/10/26 08:06:20 - mmengine - INFO - Epoch(train) [1048][20/63] lr: 5.5111e-04 eta: 1:47:58 time: 0.5233 data_time: 0.0077 memory: 16131 loss: 0.8933 loss_prob: 0.4757 loss_thr: 0.3342 loss_db: 0.0833 2022/10/26 08:06:23 - mmengine - INFO - Epoch(train) [1048][25/63] lr: 5.5111e-04 eta: 1:47:58 time: 0.5819 data_time: 0.0220 memory: 16131 loss: 0.9049 loss_prob: 0.4856 loss_thr: 0.3353 loss_db: 0.0840 2022/10/26 08:06:26 - mmengine - INFO - Epoch(train) [1048][30/63] lr: 5.5111e-04 eta: 1:47:51 time: 0.5936 data_time: 0.0329 memory: 16131 loss: 0.8961 loss_prob: 0.4739 loss_thr: 0.3411 loss_db: 0.0811 2022/10/26 08:06:28 - mmengine - INFO - Epoch(train) [1048][35/63] lr: 5.5111e-04 eta: 1:47:51 time: 0.5259 data_time: 0.0195 memory: 16131 loss: 0.9026 loss_prob: 0.4731 loss_thr: 0.3492 loss_db: 0.0802 2022/10/26 08:06:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:06:31 - mmengine - INFO - Epoch(train) [1048][40/63] lr: 5.5111e-04 eta: 1:47:44 time: 0.5364 data_time: 0.0065 memory: 16131 loss: 0.9636 loss_prob: 0.5105 loss_thr: 0.3655 loss_db: 0.0875 2022/10/26 08:06:34 - mmengine - INFO - Epoch(train) [1048][45/63] lr: 5.5111e-04 eta: 1:47:44 time: 0.5265 data_time: 0.0097 memory: 16131 loss: 0.9363 loss_prob: 0.4865 loss_thr: 0.3645 loss_db: 0.0852 2022/10/26 08:06:36 - mmengine - INFO - Epoch(train) [1048][50/63] lr: 5.5111e-04 eta: 1:47:37 time: 0.4951 data_time: 0.0172 memory: 16131 loss: 0.8997 loss_prob: 0.4709 loss_thr: 0.3468 loss_db: 0.0820 2022/10/26 08:06:39 - mmengine - INFO - Epoch(train) [1048][55/63] lr: 5.5111e-04 eta: 1:47:37 time: 0.5100 data_time: 0.0214 memory: 16131 loss: 0.9567 loss_prob: 0.5181 loss_thr: 0.3499 loss_db: 0.0888 2022/10/26 08:06:41 - mmengine - INFO - Epoch(train) [1048][60/63] lr: 5.5111e-04 eta: 1:47:30 time: 0.5121 data_time: 0.0133 memory: 16131 loss: 0.9324 loss_prob: 0.4996 loss_thr: 0.3484 loss_db: 0.0844 2022/10/26 08:06:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:06:48 - mmengine - INFO - Epoch(train) [1049][5/63] lr: 5.4784e-04 eta: 1:47:30 time: 0.8022 data_time: 0.1734 memory: 16131 loss: 0.9328 loss_prob: 0.4881 loss_thr: 0.3596 loss_db: 0.0851 2022/10/26 08:06:51 - mmengine - INFO - Epoch(train) [1049][10/63] lr: 5.4784e-04 eta: 1:47:21 time: 0.8110 data_time: 0.1743 memory: 16131 loss: 0.9108 loss_prob: 0.4792 loss_thr: 0.3496 loss_db: 0.0821 2022/10/26 08:06:54 - mmengine - INFO - Epoch(train) [1049][15/63] lr: 5.4784e-04 eta: 1:47:21 time: 0.5699 data_time: 0.0082 memory: 16131 loss: 0.8928 loss_prob: 0.4625 loss_thr: 0.3498 loss_db: 0.0806 2022/10/26 08:06:56 - mmengine - INFO - Epoch(train) [1049][20/63] lr: 5.4784e-04 eta: 1:47:14 time: 0.5172 data_time: 0.0084 memory: 16131 loss: 0.8819 loss_prob: 0.4546 loss_thr: 0.3466 loss_db: 0.0806 2022/10/26 08:06:59 - mmengine - INFO - Epoch(train) [1049][25/63] lr: 5.4784e-04 eta: 1:47:14 time: 0.5216 data_time: 0.0177 memory: 16131 loss: 0.9220 loss_prob: 0.4838 loss_thr: 0.3518 loss_db: 0.0865 2022/10/26 08:07:02 - mmengine - INFO - Epoch(train) [1049][30/63] lr: 5.4784e-04 eta: 1:47:07 time: 0.5539 data_time: 0.0337 memory: 16131 loss: 0.9259 loss_prob: 0.4933 loss_thr: 0.3456 loss_db: 0.0870 2022/10/26 08:07:04 - mmengine - INFO - Epoch(train) [1049][35/63] lr: 5.4784e-04 eta: 1:47:07 time: 0.5291 data_time: 0.0240 memory: 16131 loss: 0.9139 loss_prob: 0.4859 loss_thr: 0.3454 loss_db: 0.0827 2022/10/26 08:07:07 - mmengine - INFO - Epoch(train) [1049][40/63] lr: 5.4784e-04 eta: 1:47:00 time: 0.5153 data_time: 0.0067 memory: 16131 loss: 0.9215 loss_prob: 0.4809 loss_thr: 0.3593 loss_db: 0.0813 2022/10/26 08:07:10 - mmengine - INFO - Epoch(train) [1049][45/63] lr: 5.4784e-04 eta: 1:47:00 time: 0.5403 data_time: 0.0049 memory: 16131 loss: 0.8706 loss_prob: 0.4483 loss_thr: 0.3435 loss_db: 0.0788 2022/10/26 08:07:12 - mmengine - INFO - Epoch(train) [1049][50/63] lr: 5.4784e-04 eta: 1:46:53 time: 0.5444 data_time: 0.0086 memory: 16131 loss: 0.8476 loss_prob: 0.4338 loss_thr: 0.3363 loss_db: 0.0775 2022/10/26 08:07:15 - mmengine - INFO - Epoch(train) [1049][55/63] lr: 5.4784e-04 eta: 1:46:53 time: 0.5389 data_time: 0.0201 memory: 16131 loss: 0.8525 loss_prob: 0.4367 loss_thr: 0.3390 loss_db: 0.0768 2022/10/26 08:07:18 - mmengine - INFO - Epoch(train) [1049][60/63] lr: 5.4784e-04 eta: 1:46:47 time: 0.5344 data_time: 0.0183 memory: 16131 loss: 0.8857 loss_prob: 0.4674 loss_thr: 0.3369 loss_db: 0.0814 2022/10/26 08:07:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:07:24 - mmengine - INFO - Epoch(train) [1050][5/63] lr: 5.4458e-04 eta: 1:46:47 time: 0.7528 data_time: 0.2222 memory: 16131 loss: 0.9120 loss_prob: 0.4752 loss_thr: 0.3560 loss_db: 0.0808 2022/10/26 08:07:27 - mmengine - INFO - Epoch(train) [1050][10/63] lr: 5.4458e-04 eta: 1:46:38 time: 0.7687 data_time: 0.2202 memory: 16131 loss: 0.9967 loss_prob: 0.5304 loss_thr: 0.3767 loss_db: 0.0896 2022/10/26 08:07:30 - mmengine - INFO - Epoch(train) [1050][15/63] lr: 5.4458e-04 eta: 1:46:38 time: 0.5160 data_time: 0.0119 memory: 16131 loss: 0.9817 loss_prob: 0.5268 loss_thr: 0.3628 loss_db: 0.0920 2022/10/26 08:07:32 - mmengine - INFO - Epoch(train) [1050][20/63] lr: 5.4458e-04 eta: 1:46:31 time: 0.5599 data_time: 0.0131 memory: 16131 loss: 0.8784 loss_prob: 0.4682 loss_thr: 0.3291 loss_db: 0.0811 2022/10/26 08:07:35 - mmengine - INFO - Epoch(train) [1050][25/63] lr: 5.4458e-04 eta: 1:46:31 time: 0.5846 data_time: 0.0275 memory: 16131 loss: 0.8730 loss_prob: 0.4618 loss_thr: 0.3337 loss_db: 0.0776 2022/10/26 08:07:38 - mmengine - INFO - Epoch(train) [1050][30/63] lr: 5.4458e-04 eta: 1:46:24 time: 0.5559 data_time: 0.0291 memory: 16131 loss: 0.8613 loss_prob: 0.4404 loss_thr: 0.3450 loss_db: 0.0760 2022/10/26 08:07:40 - mmengine - INFO - Epoch(train) [1050][35/63] lr: 5.4458e-04 eta: 1:46:24 time: 0.5090 data_time: 0.0151 memory: 16131 loss: 0.8975 loss_prob: 0.4686 loss_thr: 0.3464 loss_db: 0.0824 2022/10/26 08:07:43 - mmengine - INFO - Epoch(train) [1050][40/63] lr: 5.4458e-04 eta: 1:46:17 time: 0.5010 data_time: 0.0151 memory: 16131 loss: 0.9525 loss_prob: 0.4994 loss_thr: 0.3650 loss_db: 0.0881 2022/10/26 08:07:46 - mmengine - INFO - Epoch(train) [1050][45/63] lr: 5.4458e-04 eta: 1:46:17 time: 0.5038 data_time: 0.0115 memory: 16131 loss: 0.9463 loss_prob: 0.4918 loss_thr: 0.3684 loss_db: 0.0860 2022/10/26 08:07:49 - mmengine - INFO - Epoch(train) [1050][50/63] lr: 5.4458e-04 eta: 1:46:10 time: 0.5628 data_time: 0.0487 memory: 16131 loss: 0.9404 loss_prob: 0.4993 loss_thr: 0.3538 loss_db: 0.0873 2022/10/26 08:07:51 - mmengine - INFO - Epoch(train) [1050][55/63] lr: 5.4458e-04 eta: 1:46:10 time: 0.5972 data_time: 0.0488 memory: 16131 loss: 0.8893 loss_prob: 0.4655 loss_thr: 0.3425 loss_db: 0.0813 2022/10/26 08:07:54 - mmengine - INFO - Epoch(train) [1050][60/63] lr: 5.4458e-04 eta: 1:46:03 time: 0.5289 data_time: 0.0100 memory: 16131 loss: 0.8702 loss_prob: 0.4516 loss_thr: 0.3415 loss_db: 0.0771 2022/10/26 08:07:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:08:00 - mmengine - INFO - Epoch(train) [1051][5/63] lr: 5.4131e-04 eta: 1:46:03 time: 0.6666 data_time: 0.1762 memory: 16131 loss: 0.8699 loss_prob: 0.4554 loss_thr: 0.3354 loss_db: 0.0792 2022/10/26 08:08:02 - mmengine - INFO - Epoch(train) [1051][10/63] lr: 5.4131e-04 eta: 1:45:54 time: 0.6821 data_time: 0.1782 memory: 16131 loss: 0.9179 loss_prob: 0.4819 loss_thr: 0.3517 loss_db: 0.0843 2022/10/26 08:08:05 - mmengine - INFO - Epoch(train) [1051][15/63] lr: 5.4131e-04 eta: 1:45:54 time: 0.4989 data_time: 0.0101 memory: 16131 loss: 0.9445 loss_prob: 0.4977 loss_thr: 0.3601 loss_db: 0.0867 2022/10/26 08:08:07 - mmengine - INFO - Epoch(train) [1051][20/63] lr: 5.4131e-04 eta: 1:45:47 time: 0.4944 data_time: 0.0055 memory: 16131 loss: 0.9108 loss_prob: 0.4794 loss_thr: 0.3478 loss_db: 0.0836 2022/10/26 08:08:10 - mmengine - INFO - Epoch(train) [1051][25/63] lr: 5.4131e-04 eta: 1:45:47 time: 0.5064 data_time: 0.0133 memory: 16131 loss: 0.9060 loss_prob: 0.4676 loss_thr: 0.3573 loss_db: 0.0811 2022/10/26 08:08:12 - mmengine - INFO - Epoch(train) [1051][30/63] lr: 5.4131e-04 eta: 1:45:40 time: 0.5205 data_time: 0.0265 memory: 16131 loss: 0.9361 loss_prob: 0.4919 loss_thr: 0.3584 loss_db: 0.0858 2022/10/26 08:08:15 - mmengine - INFO - Epoch(train) [1051][35/63] lr: 5.4131e-04 eta: 1:45:40 time: 0.5119 data_time: 0.0241 memory: 16131 loss: 0.9718 loss_prob: 0.5332 loss_thr: 0.3469 loss_db: 0.0916 2022/10/26 08:08:17 - mmengine - INFO - Epoch(train) [1051][40/63] lr: 5.4131e-04 eta: 1:45:33 time: 0.5222 data_time: 0.0104 memory: 16131 loss: 0.9827 loss_prob: 0.5474 loss_thr: 0.3459 loss_db: 0.0894 2022/10/26 08:08:20 - mmengine - INFO - Epoch(train) [1051][45/63] lr: 5.4131e-04 eta: 1:45:33 time: 0.5328 data_time: 0.0093 memory: 16131 loss: 0.9733 loss_prob: 0.5248 loss_thr: 0.3621 loss_db: 0.0864 2022/10/26 08:08:23 - mmengine - INFO - Epoch(train) [1051][50/63] lr: 5.4131e-04 eta: 1:45:26 time: 0.5276 data_time: 0.0189 memory: 16131 loss: 0.9445 loss_prob: 0.4918 loss_thr: 0.3667 loss_db: 0.0860 2022/10/26 08:08:25 - mmengine - INFO - Epoch(train) [1051][55/63] lr: 5.4131e-04 eta: 1:45:26 time: 0.5331 data_time: 0.0247 memory: 16131 loss: 0.9126 loss_prob: 0.4793 loss_thr: 0.3489 loss_db: 0.0844 2022/10/26 08:08:28 - mmengine - INFO - Epoch(train) [1051][60/63] lr: 5.4131e-04 eta: 1:45:19 time: 0.5316 data_time: 0.0155 memory: 16131 loss: 0.8953 loss_prob: 0.4707 loss_thr: 0.3419 loss_db: 0.0827 2022/10/26 08:08:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:08:34 - mmengine - INFO - Epoch(train) [1052][5/63] lr: 5.3804e-04 eta: 1:45:19 time: 0.7437 data_time: 0.1936 memory: 16131 loss: 0.8423 loss_prob: 0.4380 loss_thr: 0.3290 loss_db: 0.0753 2022/10/26 08:08:37 - mmengine - INFO - Epoch(train) [1052][10/63] lr: 5.3804e-04 eta: 1:45:10 time: 0.7362 data_time: 0.1930 memory: 16131 loss: 0.8356 loss_prob: 0.4350 loss_thr: 0.3268 loss_db: 0.0738 2022/10/26 08:08:39 - mmengine - INFO - Epoch(train) [1052][15/63] lr: 5.3804e-04 eta: 1:45:10 time: 0.5031 data_time: 0.0046 memory: 16131 loss: 0.8602 loss_prob: 0.4553 loss_thr: 0.3272 loss_db: 0.0777 2022/10/26 08:08:42 - mmengine - INFO - Epoch(train) [1052][20/63] lr: 5.3804e-04 eta: 1:45:03 time: 0.4871 data_time: 0.0051 memory: 16131 loss: 0.8935 loss_prob: 0.4733 loss_thr: 0.3376 loss_db: 0.0826 2022/10/26 08:08:45 - mmengine - INFO - Epoch(train) [1052][25/63] lr: 5.3804e-04 eta: 1:45:03 time: 0.5488 data_time: 0.0184 memory: 16131 loss: 0.9064 loss_prob: 0.4731 loss_thr: 0.3497 loss_db: 0.0836 2022/10/26 08:08:48 - mmengine - INFO - Epoch(train) [1052][30/63] lr: 5.3804e-04 eta: 1:44:56 time: 0.5794 data_time: 0.0326 memory: 16131 loss: 0.9690 loss_prob: 0.5096 loss_thr: 0.3711 loss_db: 0.0883 2022/10/26 08:08:50 - mmengine - INFO - Epoch(train) [1052][35/63] lr: 5.3804e-04 eta: 1:44:56 time: 0.5240 data_time: 0.0246 memory: 16131 loss: 0.9067 loss_prob: 0.4771 loss_thr: 0.3462 loss_db: 0.0834 2022/10/26 08:08:53 - mmengine - INFO - Epoch(train) [1052][40/63] lr: 5.3804e-04 eta: 1:44:49 time: 0.4958 data_time: 0.0137 memory: 16131 loss: 0.8700 loss_prob: 0.4534 loss_thr: 0.3369 loss_db: 0.0797 2022/10/26 08:08:55 - mmengine - INFO - Epoch(train) [1052][45/63] lr: 5.3804e-04 eta: 1:44:49 time: 0.5212 data_time: 0.0089 memory: 16131 loss: 0.8781 loss_prob: 0.4527 loss_thr: 0.3456 loss_db: 0.0797 2022/10/26 08:08:58 - mmengine - INFO - Epoch(train) [1052][50/63] lr: 5.3804e-04 eta: 1:44:43 time: 0.5388 data_time: 0.0329 memory: 16131 loss: 0.9153 loss_prob: 0.4745 loss_thr: 0.3579 loss_db: 0.0829 2022/10/26 08:09:01 - mmengine - INFO - Epoch(train) [1052][55/63] lr: 5.3804e-04 eta: 1:44:43 time: 0.5121 data_time: 0.0330 memory: 16131 loss: 0.9607 loss_prob: 0.5051 loss_thr: 0.3688 loss_db: 0.0867 2022/10/26 08:09:03 - mmengine - INFO - Epoch(train) [1052][60/63] lr: 5.3804e-04 eta: 1:44:36 time: 0.5236 data_time: 0.0081 memory: 16131 loss: 0.9219 loss_prob: 0.4887 loss_thr: 0.3485 loss_db: 0.0847 2022/10/26 08:09:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:09:09 - mmengine - INFO - Epoch(train) [1053][5/63] lr: 5.3477e-04 eta: 1:44:36 time: 0.7197 data_time: 0.1988 memory: 16131 loss: 0.9841 loss_prob: 0.5164 loss_thr: 0.3766 loss_db: 0.0911 2022/10/26 08:09:12 - mmengine - INFO - Epoch(train) [1053][10/63] lr: 5.3477e-04 eta: 1:44:27 time: 0.7613 data_time: 0.1990 memory: 16131 loss: 1.0388 loss_prob: 0.5368 loss_thr: 0.4077 loss_db: 0.0943 2022/10/26 08:09:15 - mmengine - INFO - Epoch(train) [1053][15/63] lr: 5.3477e-04 eta: 1:44:27 time: 0.5438 data_time: 0.0066 memory: 16131 loss: 1.0413 loss_prob: 0.5351 loss_thr: 0.4116 loss_db: 0.0946 2022/10/26 08:09:18 - mmengine - INFO - Epoch(train) [1053][20/63] lr: 5.3477e-04 eta: 1:44:20 time: 0.5601 data_time: 0.0051 memory: 16131 loss: 0.9390 loss_prob: 0.4747 loss_thr: 0.3791 loss_db: 0.0852 2022/10/26 08:09:21 - mmengine - INFO - Epoch(train) [1053][25/63] lr: 5.3477e-04 eta: 1:44:20 time: 0.5856 data_time: 0.0287 memory: 16131 loss: 0.8582 loss_prob: 0.4352 loss_thr: 0.3453 loss_db: 0.0778 2022/10/26 08:09:23 - mmengine - INFO - Epoch(train) [1053][30/63] lr: 5.3477e-04 eta: 1:44:13 time: 0.5560 data_time: 0.0311 memory: 16131 loss: 0.8603 loss_prob: 0.4503 loss_thr: 0.3330 loss_db: 0.0770 2022/10/26 08:09:26 - mmengine - INFO - Epoch(train) [1053][35/63] lr: 5.3477e-04 eta: 1:44:13 time: 0.4983 data_time: 0.0104 memory: 16131 loss: 0.8456 loss_prob: 0.4433 loss_thr: 0.3274 loss_db: 0.0749 2022/10/26 08:09:28 - mmengine - INFO - Epoch(train) [1053][40/63] lr: 5.3477e-04 eta: 1:44:06 time: 0.4968 data_time: 0.0092 memory: 16131 loss: 0.8608 loss_prob: 0.4419 loss_thr: 0.3419 loss_db: 0.0770 2022/10/26 08:09:31 - mmengine - INFO - Epoch(train) [1053][45/63] lr: 5.3477e-04 eta: 1:44:06 time: 0.5036 data_time: 0.0062 memory: 16131 loss: 0.9009 loss_prob: 0.4701 loss_thr: 0.3469 loss_db: 0.0839 2022/10/26 08:09:34 - mmengine - INFO - Epoch(train) [1053][50/63] lr: 5.3477e-04 eta: 1:43:59 time: 0.5321 data_time: 0.0221 memory: 16131 loss: 0.8358 loss_prob: 0.4345 loss_thr: 0.3231 loss_db: 0.0782 2022/10/26 08:09:36 - mmengine - INFO - Epoch(train) [1053][55/63] lr: 5.3477e-04 eta: 1:43:59 time: 0.5215 data_time: 0.0241 memory: 16131 loss: 0.8554 loss_prob: 0.4393 loss_thr: 0.3399 loss_db: 0.0761 2022/10/26 08:09:39 - mmengine - INFO - Epoch(train) [1053][60/63] lr: 5.3477e-04 eta: 1:43:52 time: 0.4998 data_time: 0.0076 memory: 16131 loss: 0.8724 loss_prob: 0.4473 loss_thr: 0.3477 loss_db: 0.0773 2022/10/26 08:09:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:09:44 - mmengine - INFO - Epoch(train) [1054][5/63] lr: 5.3149e-04 eta: 1:43:52 time: 0.6751 data_time: 0.1595 memory: 16131 loss: 0.8989 loss_prob: 0.4691 loss_thr: 0.3489 loss_db: 0.0810 2022/10/26 08:09:47 - mmengine - INFO - Epoch(train) [1054][10/63] lr: 5.3149e-04 eta: 1:43:43 time: 0.6898 data_time: 0.1697 memory: 16131 loss: 0.8135 loss_prob: 0.4239 loss_thr: 0.3169 loss_db: 0.0727 2022/10/26 08:09:49 - mmengine - INFO - Epoch(train) [1054][15/63] lr: 5.3149e-04 eta: 1:43:43 time: 0.5154 data_time: 0.0171 memory: 16131 loss: 0.7976 loss_prob: 0.4140 loss_thr: 0.3112 loss_db: 0.0725 2022/10/26 08:09:52 - mmengine - INFO - Epoch(train) [1054][20/63] lr: 5.3149e-04 eta: 1:43:36 time: 0.4947 data_time: 0.0062 memory: 16131 loss: 0.9164 loss_prob: 0.4794 loss_thr: 0.3539 loss_db: 0.0831 2022/10/26 08:09:54 - mmengine - INFO - Epoch(train) [1054][25/63] lr: 5.3149e-04 eta: 1:43:36 time: 0.5071 data_time: 0.0075 memory: 16131 loss: 0.9340 loss_prob: 0.4937 loss_thr: 0.3541 loss_db: 0.0862 2022/10/26 08:09:57 - mmengine - INFO - Epoch(train) [1054][30/63] lr: 5.3149e-04 eta: 1:43:29 time: 0.5289 data_time: 0.0212 memory: 16131 loss: 0.8687 loss_prob: 0.4574 loss_thr: 0.3311 loss_db: 0.0802 2022/10/26 08:10:00 - mmengine - INFO - Epoch(train) [1054][35/63] lr: 5.3149e-04 eta: 1:43:29 time: 0.5211 data_time: 0.0280 memory: 16131 loss: 0.9082 loss_prob: 0.4737 loss_thr: 0.3525 loss_db: 0.0820 2022/10/26 08:10:02 - mmengine - INFO - Epoch(train) [1054][40/63] lr: 5.3149e-04 eta: 1:43:22 time: 0.5104 data_time: 0.0166 memory: 16131 loss: 0.8914 loss_prob: 0.4561 loss_thr: 0.3557 loss_db: 0.0796 2022/10/26 08:10:05 - mmengine - INFO - Epoch(train) [1054][45/63] lr: 5.3149e-04 eta: 1:43:22 time: 0.5199 data_time: 0.0078 memory: 16131 loss: 0.9320 loss_prob: 0.4898 loss_thr: 0.3582 loss_db: 0.0840 2022/10/26 08:10:08 - mmengine - INFO - Epoch(train) [1054][50/63] lr: 5.3149e-04 eta: 1:43:15 time: 0.5318 data_time: 0.0181 memory: 16131 loss: 1.0086 loss_prob: 0.5321 loss_thr: 0.3851 loss_db: 0.0914 2022/10/26 08:10:10 - mmengine - INFO - Epoch(train) [1054][55/63] lr: 5.3149e-04 eta: 1:43:15 time: 0.5359 data_time: 0.0216 memory: 16131 loss: 0.9310 loss_prob: 0.4824 loss_thr: 0.3649 loss_db: 0.0838 2022/10/26 08:10:13 - mmengine - INFO - Epoch(train) [1054][60/63] lr: 5.3149e-04 eta: 1:43:08 time: 0.5271 data_time: 0.0147 memory: 16131 loss: 0.8948 loss_prob: 0.4689 loss_thr: 0.3448 loss_db: 0.0811 2022/10/26 08:10:14 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:10:18 - mmengine - INFO - Epoch(train) [1055][5/63] lr: 5.2822e-04 eta: 1:43:08 time: 0.6569 data_time: 0.1703 memory: 16131 loss: 0.8240 loss_prob: 0.4254 loss_thr: 0.3232 loss_db: 0.0754 2022/10/26 08:10:21 - mmengine - INFO - Epoch(train) [1055][10/63] lr: 5.2822e-04 eta: 1:42:59 time: 0.6972 data_time: 0.1742 memory: 16131 loss: 0.9200 loss_prob: 0.4873 loss_thr: 0.3500 loss_db: 0.0828 2022/10/26 08:10:24 - mmengine - INFO - Epoch(train) [1055][15/63] lr: 5.2822e-04 eta: 1:42:59 time: 0.5499 data_time: 0.0119 memory: 16131 loss: 0.9523 loss_prob: 0.5059 loss_thr: 0.3610 loss_db: 0.0854 2022/10/26 08:10:26 - mmengine - INFO - Epoch(train) [1055][20/63] lr: 5.2822e-04 eta: 1:42:52 time: 0.5211 data_time: 0.0061 memory: 16131 loss: 0.9293 loss_prob: 0.4871 loss_thr: 0.3581 loss_db: 0.0841 2022/10/26 08:10:29 - mmengine - INFO - Epoch(train) [1055][25/63] lr: 5.2822e-04 eta: 1:42:52 time: 0.5167 data_time: 0.0208 memory: 16131 loss: 0.8769 loss_prob: 0.4557 loss_thr: 0.3427 loss_db: 0.0784 2022/10/26 08:10:32 - mmengine - INFO - Epoch(train) [1055][30/63] lr: 5.2822e-04 eta: 1:42:45 time: 0.5350 data_time: 0.0338 memory: 16131 loss: 0.8041 loss_prob: 0.4108 loss_thr: 0.3211 loss_db: 0.0722 2022/10/26 08:10:34 - mmengine - INFO - Epoch(train) [1055][35/63] lr: 5.2822e-04 eta: 1:42:45 time: 0.5275 data_time: 0.0239 memory: 16131 loss: 0.8676 loss_prob: 0.4516 loss_thr: 0.3379 loss_db: 0.0781 2022/10/26 08:10:37 - mmengine - INFO - Epoch(train) [1055][40/63] lr: 5.2822e-04 eta: 1:42:39 time: 0.5069 data_time: 0.0104 memory: 16131 loss: 0.9337 loss_prob: 0.4960 loss_thr: 0.3539 loss_db: 0.0839 2022/10/26 08:10:39 - mmengine - INFO - Epoch(train) [1055][45/63] lr: 5.2822e-04 eta: 1:42:39 time: 0.5068 data_time: 0.0061 memory: 16131 loss: 0.9211 loss_prob: 0.4929 loss_thr: 0.3451 loss_db: 0.0831 2022/10/26 08:10:42 - mmengine - INFO - Epoch(train) [1055][50/63] lr: 5.2822e-04 eta: 1:42:32 time: 0.5133 data_time: 0.0151 memory: 16131 loss: 0.8862 loss_prob: 0.4632 loss_thr: 0.3430 loss_db: 0.0800 2022/10/26 08:10:45 - mmengine - INFO - Epoch(train) [1055][55/63] lr: 5.2822e-04 eta: 1:42:32 time: 0.5152 data_time: 0.0196 memory: 16131 loss: 0.9618 loss_prob: 0.5037 loss_thr: 0.3703 loss_db: 0.0878 2022/10/26 08:10:47 - mmengine - INFO - Epoch(train) [1055][60/63] lr: 5.2822e-04 eta: 1:42:25 time: 0.5533 data_time: 0.0137 memory: 16131 loss: 0.9391 loss_prob: 0.4973 loss_thr: 0.3555 loss_db: 0.0863 2022/10/26 08:10:49 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:10:54 - mmengine - INFO - Epoch(train) [1056][5/63] lr: 5.2494e-04 eta: 1:42:25 time: 0.7499 data_time: 0.1957 memory: 16131 loss: 0.9101 loss_prob: 0.4775 loss_thr: 0.3490 loss_db: 0.0836 2022/10/26 08:10:56 - mmengine - INFO - Epoch(train) [1056][10/63] lr: 5.2494e-04 eta: 1:42:16 time: 0.7525 data_time: 0.1990 memory: 16131 loss: 0.8718 loss_prob: 0.4558 loss_thr: 0.3375 loss_db: 0.0785 2022/10/26 08:10:59 - mmengine - INFO - Epoch(train) [1056][15/63] lr: 5.2494e-04 eta: 1:42:16 time: 0.5265 data_time: 0.0083 memory: 16131 loss: 0.8750 loss_prob: 0.4587 loss_thr: 0.3369 loss_db: 0.0794 2022/10/26 08:11:02 - mmengine - INFO - Epoch(train) [1056][20/63] lr: 5.2494e-04 eta: 1:42:09 time: 0.5448 data_time: 0.0049 memory: 16131 loss: 0.8962 loss_prob: 0.4680 loss_thr: 0.3464 loss_db: 0.0818 2022/10/26 08:11:05 - mmengine - INFO - Epoch(train) [1056][25/63] lr: 5.2494e-04 eta: 1:42:09 time: 0.5635 data_time: 0.0223 memory: 16131 loss: 0.8512 loss_prob: 0.4341 loss_thr: 0.3406 loss_db: 0.0765 2022/10/26 08:11:07 - mmengine - INFO - Epoch(train) [1056][30/63] lr: 5.2494e-04 eta: 1:42:02 time: 0.5792 data_time: 0.0332 memory: 16131 loss: 0.8802 loss_prob: 0.4590 loss_thr: 0.3426 loss_db: 0.0787 2022/10/26 08:11:10 - mmengine - INFO - Epoch(train) [1056][35/63] lr: 5.2494e-04 eta: 1:42:02 time: 0.5904 data_time: 0.0171 memory: 16131 loss: 0.8824 loss_prob: 0.4657 loss_thr: 0.3388 loss_db: 0.0779 2022/10/26 08:11:13 - mmengine - INFO - Epoch(train) [1056][40/63] lr: 5.2494e-04 eta: 1:41:55 time: 0.5469 data_time: 0.0090 memory: 16131 loss: 0.8975 loss_prob: 0.4685 loss_thr: 0.3484 loss_db: 0.0806 2022/10/26 08:11:16 - mmengine - INFO - Epoch(train) [1056][45/63] lr: 5.2494e-04 eta: 1:41:55 time: 0.5100 data_time: 0.0076 memory: 16131 loss: 0.8581 loss_prob: 0.4405 loss_thr: 0.3409 loss_db: 0.0767 2022/10/26 08:11:18 - mmengine - INFO - Epoch(train) [1056][50/63] lr: 5.2494e-04 eta: 1:41:48 time: 0.5506 data_time: 0.0325 memory: 16131 loss: 0.8104 loss_prob: 0.4195 loss_thr: 0.3204 loss_db: 0.0705 2022/10/26 08:11:21 - mmengine - INFO - Epoch(train) [1056][55/63] lr: 5.2494e-04 eta: 1:41:48 time: 0.5256 data_time: 0.0358 memory: 16131 loss: 0.9682 loss_prob: 0.5147 loss_thr: 0.3656 loss_db: 0.0879 2022/10/26 08:11:24 - mmengine - INFO - Epoch(train) [1056][60/63] lr: 5.2494e-04 eta: 1:41:41 time: 0.5338 data_time: 0.0090 memory: 16131 loss: 0.9599 loss_prob: 0.4984 loss_thr: 0.3754 loss_db: 0.0861 2022/10/26 08:11:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:11:30 - mmengine - INFO - Epoch(train) [1057][5/63] lr: 5.2166e-04 eta: 1:41:41 time: 0.6750 data_time: 0.1858 memory: 16131 loss: 0.8282 loss_prob: 0.4305 loss_thr: 0.3218 loss_db: 0.0759 2022/10/26 08:11:32 - mmengine - INFO - Epoch(train) [1057][10/63] lr: 5.2166e-04 eta: 1:41:32 time: 0.7275 data_time: 0.1831 memory: 16131 loss: 0.9471 loss_prob: 0.4995 loss_thr: 0.3604 loss_db: 0.0871 2022/10/26 08:11:35 - mmengine - INFO - Epoch(train) [1057][15/63] lr: 5.2166e-04 eta: 1:41:32 time: 0.5197 data_time: 0.0050 memory: 16131 loss: 0.9565 loss_prob: 0.4989 loss_thr: 0.3719 loss_db: 0.0857 2022/10/26 08:11:38 - mmengine - INFO - Epoch(train) [1057][20/63] lr: 5.2166e-04 eta: 1:41:25 time: 0.5215 data_time: 0.0058 memory: 16131 loss: 0.8559 loss_prob: 0.4377 loss_thr: 0.3414 loss_db: 0.0768 2022/10/26 08:11:40 - mmengine - INFO - Epoch(train) [1057][25/63] lr: 5.2166e-04 eta: 1:41:25 time: 0.5558 data_time: 0.0261 memory: 16131 loss: 0.8624 loss_prob: 0.4436 loss_thr: 0.3396 loss_db: 0.0792 2022/10/26 08:11:43 - mmengine - INFO - Epoch(train) [1057][30/63] lr: 5.2166e-04 eta: 1:41:19 time: 0.5514 data_time: 0.0284 memory: 16131 loss: 0.8472 loss_prob: 0.4372 loss_thr: 0.3333 loss_db: 0.0767 2022/10/26 08:11:46 - mmengine - INFO - Epoch(train) [1057][35/63] lr: 5.2166e-04 eta: 1:41:19 time: 0.5210 data_time: 0.0084 memory: 16131 loss: 0.8303 loss_prob: 0.4277 loss_thr: 0.3279 loss_db: 0.0746 2022/10/26 08:11:48 - mmengine - INFO - Epoch(train) [1057][40/63] lr: 5.2166e-04 eta: 1:41:12 time: 0.5196 data_time: 0.0094 memory: 16131 loss: 0.9203 loss_prob: 0.4861 loss_thr: 0.3493 loss_db: 0.0849 2022/10/26 08:11:51 - mmengine - INFO - Epoch(train) [1057][45/63] lr: 5.2166e-04 eta: 1:41:12 time: 0.5114 data_time: 0.0099 memory: 16131 loss: 0.9578 loss_prob: 0.5134 loss_thr: 0.3532 loss_db: 0.0913 2022/10/26 08:11:53 - mmengine - INFO - Epoch(train) [1057][50/63] lr: 5.2166e-04 eta: 1:41:05 time: 0.5107 data_time: 0.0202 memory: 16131 loss: 0.9107 loss_prob: 0.4823 loss_thr: 0.3441 loss_db: 0.0842 2022/10/26 08:11:56 - mmengine - INFO - Epoch(train) [1057][55/63] lr: 5.2166e-04 eta: 1:41:05 time: 0.5330 data_time: 0.0220 memory: 16131 loss: 0.9142 loss_prob: 0.4810 loss_thr: 0.3526 loss_db: 0.0806 2022/10/26 08:11:59 - mmengine - INFO - Epoch(train) [1057][60/63] lr: 5.2166e-04 eta: 1:40:58 time: 0.5235 data_time: 0.0105 memory: 16131 loss: 0.8812 loss_prob: 0.4591 loss_thr: 0.3434 loss_db: 0.0787 2022/10/26 08:12:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:12:05 - mmengine - INFO - Epoch(train) [1058][5/63] lr: 5.1837e-04 eta: 1:40:58 time: 0.7144 data_time: 0.2149 memory: 16131 loss: 0.9043 loss_prob: 0.4815 loss_thr: 0.3420 loss_db: 0.0809 2022/10/26 08:12:08 - mmengine - INFO - Epoch(train) [1058][10/63] lr: 5.1837e-04 eta: 1:40:49 time: 0.7597 data_time: 0.2133 memory: 16131 loss: 0.9404 loss_prob: 0.4940 loss_thr: 0.3603 loss_db: 0.0862 2022/10/26 08:12:10 - mmengine - INFO - Epoch(train) [1058][15/63] lr: 5.1837e-04 eta: 1:40:49 time: 0.5733 data_time: 0.0087 memory: 16131 loss: 0.9649 loss_prob: 0.5216 loss_thr: 0.3551 loss_db: 0.0883 2022/10/26 08:12:13 - mmengine - INFO - Epoch(train) [1058][20/63] lr: 5.1837e-04 eta: 1:40:42 time: 0.5508 data_time: 0.0081 memory: 16131 loss: 0.8836 loss_prob: 0.4710 loss_thr: 0.3333 loss_db: 0.0792 2022/10/26 08:12:16 - mmengine - INFO - Epoch(train) [1058][25/63] lr: 5.1837e-04 eta: 1:40:42 time: 0.5320 data_time: 0.0284 memory: 16131 loss: 0.9311 loss_prob: 0.4957 loss_thr: 0.3495 loss_db: 0.0860 2022/10/26 08:12:19 - mmengine - INFO - Epoch(train) [1058][30/63] lr: 5.1837e-04 eta: 1:40:35 time: 0.5678 data_time: 0.0342 memory: 16131 loss: 0.9997 loss_prob: 0.5387 loss_thr: 0.3670 loss_db: 0.0940 2022/10/26 08:12:22 - mmengine - INFO - Epoch(train) [1058][35/63] lr: 5.1837e-04 eta: 1:40:35 time: 0.5761 data_time: 0.0129 memory: 16131 loss: 0.9411 loss_prob: 0.4955 loss_thr: 0.3591 loss_db: 0.0865 2022/10/26 08:12:24 - mmengine - INFO - Epoch(train) [1058][40/63] lr: 5.1837e-04 eta: 1:40:28 time: 0.5577 data_time: 0.0079 memory: 16131 loss: 0.8659 loss_prob: 0.4411 loss_thr: 0.3479 loss_db: 0.0768 2022/10/26 08:12:27 - mmengine - INFO - Epoch(train) [1058][45/63] lr: 5.1837e-04 eta: 1:40:28 time: 0.5524 data_time: 0.0068 memory: 16131 loss: 0.7964 loss_prob: 0.4061 loss_thr: 0.3178 loss_db: 0.0725 2022/10/26 08:12:30 - mmengine - INFO - Epoch(train) [1058][50/63] lr: 5.1837e-04 eta: 1:40:21 time: 0.5479 data_time: 0.0156 memory: 16131 loss: 0.9252 loss_prob: 0.4896 loss_thr: 0.3490 loss_db: 0.0866 2022/10/26 08:12:32 - mmengine - INFO - Epoch(train) [1058][55/63] lr: 5.1837e-04 eta: 1:40:21 time: 0.5334 data_time: 0.0228 memory: 16131 loss: 0.9330 loss_prob: 0.4921 loss_thr: 0.3549 loss_db: 0.0860 2022/10/26 08:12:35 - mmengine - INFO - Epoch(train) [1058][60/63] lr: 5.1837e-04 eta: 1:40:14 time: 0.5408 data_time: 0.0131 memory: 16131 loss: 0.8838 loss_prob: 0.4623 loss_thr: 0.3421 loss_db: 0.0793 2022/10/26 08:12:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:12:42 - mmengine - INFO - Epoch(train) [1059][5/63] lr: 5.1509e-04 eta: 1:40:14 time: 0.7700 data_time: 0.1836 memory: 16131 loss: 0.9109 loss_prob: 0.4762 loss_thr: 0.3512 loss_db: 0.0836 2022/10/26 08:12:45 - mmengine - INFO - Epoch(train) [1059][10/63] lr: 5.1509e-04 eta: 1:40:06 time: 0.8172 data_time: 0.1824 memory: 16131 loss: 0.9414 loss_prob: 0.4945 loss_thr: 0.3604 loss_db: 0.0866 2022/10/26 08:12:48 - mmengine - INFO - Epoch(train) [1059][15/63] lr: 5.1509e-04 eta: 1:40:06 time: 0.5788 data_time: 0.0102 memory: 16131 loss: 0.8819 loss_prob: 0.4613 loss_thr: 0.3411 loss_db: 0.0795 2022/10/26 08:12:50 - mmengine - INFO - Epoch(train) [1059][20/63] lr: 5.1509e-04 eta: 1:39:59 time: 0.5418 data_time: 0.0102 memory: 16131 loss: 0.8810 loss_prob: 0.4589 loss_thr: 0.3415 loss_db: 0.0805 2022/10/26 08:12:53 - mmengine - INFO - Epoch(train) [1059][25/63] lr: 5.1509e-04 eta: 1:39:59 time: 0.4882 data_time: 0.0181 memory: 16131 loss: 0.9280 loss_prob: 0.4836 loss_thr: 0.3597 loss_db: 0.0848 2022/10/26 08:12:56 - mmengine - INFO - Epoch(train) [1059][30/63] lr: 5.1509e-04 eta: 1:39:52 time: 0.5467 data_time: 0.0339 memory: 16131 loss: 0.8964 loss_prob: 0.4638 loss_thr: 0.3527 loss_db: 0.0799 2022/10/26 08:12:58 - mmengine - INFO - Epoch(train) [1059][35/63] lr: 5.1509e-04 eta: 1:39:52 time: 0.5560 data_time: 0.0220 memory: 16131 loss: 0.9247 loss_prob: 0.4950 loss_thr: 0.3475 loss_db: 0.0821 2022/10/26 08:13:01 - mmengine - INFO - Epoch(train) [1059][40/63] lr: 5.1509e-04 eta: 1:39:45 time: 0.5172 data_time: 0.0094 memory: 16131 loss: 0.9846 loss_prob: 0.5495 loss_thr: 0.3418 loss_db: 0.0933 2022/10/26 08:13:03 - mmengine - INFO - Epoch(train) [1059][45/63] lr: 5.1509e-04 eta: 1:39:45 time: 0.5251 data_time: 0.0084 memory: 16131 loss: 0.9397 loss_prob: 0.5116 loss_thr: 0.3375 loss_db: 0.0906 2022/10/26 08:13:06 - mmengine - INFO - Epoch(train) [1059][50/63] lr: 5.1509e-04 eta: 1:39:38 time: 0.5143 data_time: 0.0134 memory: 16131 loss: 0.9194 loss_prob: 0.4890 loss_thr: 0.3456 loss_db: 0.0848 2022/10/26 08:13:08 - mmengine - INFO - Epoch(train) [1059][55/63] lr: 5.1509e-04 eta: 1:39:38 time: 0.5004 data_time: 0.0219 memory: 16131 loss: 1.0337 loss_prob: 0.5559 loss_thr: 0.3817 loss_db: 0.0961 2022/10/26 08:13:11 - mmengine - INFO - Epoch(train) [1059][60/63] lr: 5.1509e-04 eta: 1:39:31 time: 0.5480 data_time: 0.0149 memory: 16131 loss: 1.0584 loss_prob: 0.5643 loss_thr: 0.3964 loss_db: 0.0977 2022/10/26 08:13:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:13:17 - mmengine - INFO - Epoch(train) [1060][5/63] lr: 5.1180e-04 eta: 1:39:31 time: 0.7145 data_time: 0.1816 memory: 16131 loss: 0.9648 loss_prob: 0.5158 loss_thr: 0.3599 loss_db: 0.0892 2022/10/26 08:13:20 - mmengine - INFO - Epoch(train) [1060][10/63] lr: 5.1180e-04 eta: 1:39:22 time: 0.7454 data_time: 0.1801 memory: 16131 loss: 0.9093 loss_prob: 0.4762 loss_thr: 0.3513 loss_db: 0.0817 2022/10/26 08:13:23 - mmengine - INFO - Epoch(train) [1060][15/63] lr: 5.1180e-04 eta: 1:39:22 time: 0.5400 data_time: 0.0061 memory: 16131 loss: 0.9559 loss_prob: 0.5056 loss_thr: 0.3631 loss_db: 0.0872 2022/10/26 08:13:25 - mmengine - INFO - Epoch(train) [1060][20/63] lr: 5.1180e-04 eta: 1:39:15 time: 0.5279 data_time: 0.0060 memory: 16131 loss: 0.9569 loss_prob: 0.5023 loss_thr: 0.3645 loss_db: 0.0901 2022/10/26 08:13:28 - mmengine - INFO - Epoch(train) [1060][25/63] lr: 5.1180e-04 eta: 1:39:15 time: 0.5605 data_time: 0.0243 memory: 16131 loss: 0.9019 loss_prob: 0.4689 loss_thr: 0.3504 loss_db: 0.0826 2022/10/26 08:13:31 - mmengine - INFO - Epoch(train) [1060][30/63] lr: 5.1180e-04 eta: 1:39:08 time: 0.5607 data_time: 0.0373 memory: 16131 loss: 0.9030 loss_prob: 0.4716 loss_thr: 0.3513 loss_db: 0.0801 2022/10/26 08:13:34 - mmengine - INFO - Epoch(train) [1060][35/63] lr: 5.1180e-04 eta: 1:39:08 time: 0.5239 data_time: 0.0185 memory: 16131 loss: 0.9393 loss_prob: 0.4930 loss_thr: 0.3614 loss_db: 0.0848 2022/10/26 08:13:36 - mmengine - INFO - Epoch(train) [1060][40/63] lr: 5.1180e-04 eta: 1:39:02 time: 0.5147 data_time: 0.0079 memory: 16131 loss: 0.8683 loss_prob: 0.4515 loss_thr: 0.3382 loss_db: 0.0786 2022/10/26 08:13:39 - mmengine - INFO - Epoch(train) [1060][45/63] lr: 5.1180e-04 eta: 1:39:02 time: 0.5054 data_time: 0.0156 memory: 16131 loss: 0.8523 loss_prob: 0.4336 loss_thr: 0.3422 loss_db: 0.0765 2022/10/26 08:13:41 - mmengine - INFO - Epoch(train) [1060][50/63] lr: 5.1180e-04 eta: 1:38:55 time: 0.4959 data_time: 0.0235 memory: 16131 loss: 0.9680 loss_prob: 0.5026 loss_thr: 0.3771 loss_db: 0.0883 2022/10/26 08:13:44 - mmengine - INFO - Epoch(train) [1060][55/63] lr: 5.1180e-04 eta: 1:38:55 time: 0.5079 data_time: 0.0241 memory: 16131 loss: 0.9648 loss_prob: 0.5017 loss_thr: 0.3749 loss_db: 0.0882 2022/10/26 08:13:47 - mmengine - INFO - Epoch(train) [1060][60/63] lr: 5.1180e-04 eta: 1:38:48 time: 0.5452 data_time: 0.0147 memory: 16131 loss: 0.9634 loss_prob: 0.5120 loss_thr: 0.3631 loss_db: 0.0882 2022/10/26 08:13:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:13:48 - mmengine - INFO - Saving checkpoint at 1060 epochs 2022/10/26 08:13:55 - mmengine - INFO - Epoch(val) [1060][5/32] eta: 1:38:48 time: 0.5366 data_time: 0.0727 memory: 16131 2022/10/26 08:13:57 - mmengine - INFO - Epoch(val) [1060][10/32] eta: 0:00:13 time: 0.6066 data_time: 0.1012 memory: 15724 2022/10/26 08:14:00 - mmengine - INFO - Epoch(val) [1060][15/32] eta: 0:00:13 time: 0.5371 data_time: 0.0443 memory: 15724 2022/10/26 08:14:03 - mmengine - INFO - Epoch(val) [1060][20/32] eta: 0:00:06 time: 0.5444 data_time: 0.0468 memory: 15724 2022/10/26 08:14:06 - mmengine - INFO - Epoch(val) [1060][25/32] eta: 0:00:06 time: 0.5633 data_time: 0.0487 memory: 15724 2022/10/26 08:14:08 - mmengine - INFO - Epoch(val) [1060][30/32] eta: 0:00:01 time: 0.5287 data_time: 0.0215 memory: 15724 2022/10/26 08:14:09 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8493, precision: 0.7494, hmean: 0.7962 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8493, precision: 0.7946, hmean: 0.8210 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8493, precision: 0.8286, hmean: 0.8388 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8469, precision: 0.8568, hmean: 0.8518 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8305, precision: 0.8887, hmean: 0.8586 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7554, precision: 0.9295, hmean: 0.8335 2022/10/26 08:14:09 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.1988, precision: 0.9787, hmean: 0.3305 2022/10/26 08:14:09 - mmengine - INFO - Epoch(val) [1060][32/32] icdar/precision: 0.8887 icdar/recall: 0.8305 icdar/hmean: 0.8586 2022/10/26 08:14:13 - mmengine - INFO - Epoch(train) [1061][5/63] lr: 5.0851e-04 eta: 0:00:01 time: 0.6845 data_time: 0.1676 memory: 16131 loss: 0.9016 loss_prob: 0.4722 loss_thr: 0.3465 loss_db: 0.0829 2022/10/26 08:14:16 - mmengine - INFO - Epoch(train) [1061][10/63] lr: 5.0851e-04 eta: 1:38:39 time: 0.7367 data_time: 0.1800 memory: 16131 loss: 0.9465 loss_prob: 0.5047 loss_thr: 0.3533 loss_db: 0.0885 2022/10/26 08:14:19 - mmengine - INFO - Epoch(train) [1061][15/63] lr: 5.0851e-04 eta: 1:38:39 time: 0.5453 data_time: 0.0181 memory: 16131 loss: 0.9983 loss_prob: 0.5348 loss_thr: 0.3724 loss_db: 0.0912 2022/10/26 08:14:21 - mmengine - INFO - Epoch(train) [1061][20/63] lr: 5.0851e-04 eta: 1:38:32 time: 0.5175 data_time: 0.0051 memory: 16131 loss: 0.9622 loss_prob: 0.5033 loss_thr: 0.3735 loss_db: 0.0854 2022/10/26 08:14:24 - mmengine - INFO - Epoch(train) [1061][25/63] lr: 5.0851e-04 eta: 1:38:32 time: 0.5217 data_time: 0.0223 memory: 16131 loss: 0.9652 loss_prob: 0.5088 loss_thr: 0.3674 loss_db: 0.0890 2022/10/26 08:14:27 - mmengine - INFO - Epoch(train) [1061][30/63] lr: 5.0851e-04 eta: 1:38:25 time: 0.5286 data_time: 0.0225 memory: 16131 loss: 0.9235 loss_prob: 0.4828 loss_thr: 0.3549 loss_db: 0.0857 2022/10/26 08:14:30 - mmengine - INFO - Epoch(train) [1061][35/63] lr: 5.0851e-04 eta: 1:38:25 time: 0.5394 data_time: 0.0179 memory: 16131 loss: 0.9233 loss_prob: 0.4832 loss_thr: 0.3563 loss_db: 0.0838 2022/10/26 08:14:32 - mmengine - INFO - Epoch(train) [1061][40/63] lr: 5.0851e-04 eta: 1:38:18 time: 0.5472 data_time: 0.0196 memory: 16131 loss: 0.9485 loss_prob: 0.5065 loss_thr: 0.3551 loss_db: 0.0869 2022/10/26 08:14:35 - mmengine - INFO - Epoch(train) [1061][45/63] lr: 5.0851e-04 eta: 1:38:18 time: 0.5272 data_time: 0.0078 memory: 16131 loss: 0.9374 loss_prob: 0.4988 loss_thr: 0.3533 loss_db: 0.0853 2022/10/26 08:14:37 - mmengine - INFO - Epoch(train) [1061][50/63] lr: 5.0851e-04 eta: 1:38:11 time: 0.5330 data_time: 0.0195 memory: 16131 loss: 0.8728 loss_prob: 0.4481 loss_thr: 0.3461 loss_db: 0.0786 2022/10/26 08:14:40 - mmengine - INFO - Epoch(train) [1061][55/63] lr: 5.0851e-04 eta: 1:38:11 time: 0.5311 data_time: 0.0248 memory: 16131 loss: 0.8579 loss_prob: 0.4393 loss_thr: 0.3406 loss_db: 0.0780 2022/10/26 08:14:43 - mmengine - INFO - Epoch(train) [1061][60/63] lr: 5.0851e-04 eta: 1:38:04 time: 0.5089 data_time: 0.0133 memory: 16131 loss: 0.9592 loss_prob: 0.5204 loss_thr: 0.3513 loss_db: 0.0875 2022/10/26 08:14:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:14:49 - mmengine - INFO - Epoch(train) [1062][5/63] lr: 5.0521e-04 eta: 1:38:04 time: 0.7772 data_time: 0.2020 memory: 16131 loss: 0.9338 loss_prob: 0.4912 loss_thr: 0.3585 loss_db: 0.0841 2022/10/26 08:14:52 - mmengine - INFO - Epoch(train) [1062][10/63] lr: 5.0521e-04 eta: 1:37:55 time: 0.7929 data_time: 0.2027 memory: 16131 loss: 0.8956 loss_prob: 0.4682 loss_thr: 0.3487 loss_db: 0.0788 2022/10/26 08:14:54 - mmengine - INFO - Epoch(train) [1062][15/63] lr: 5.0521e-04 eta: 1:37:55 time: 0.5027 data_time: 0.0100 memory: 16131 loss: 0.9127 loss_prob: 0.4844 loss_thr: 0.3451 loss_db: 0.0832 2022/10/26 08:14:57 - mmengine - INFO - Epoch(train) [1062][20/63] lr: 5.0521e-04 eta: 1:37:48 time: 0.5068 data_time: 0.0081 memory: 16131 loss: 0.9018 loss_prob: 0.4722 loss_thr: 0.3447 loss_db: 0.0850 2022/10/26 08:15:00 - mmengine - INFO - Epoch(train) [1062][25/63] lr: 5.0521e-04 eta: 1:37:48 time: 0.5388 data_time: 0.0114 memory: 16131 loss: 0.9615 loss_prob: 0.5107 loss_thr: 0.3643 loss_db: 0.0865 2022/10/26 08:15:03 - mmengine - INFO - Epoch(train) [1062][30/63] lr: 5.0521e-04 eta: 1:37:42 time: 0.5829 data_time: 0.0344 memory: 16131 loss: 0.9960 loss_prob: 0.5256 loss_thr: 0.3825 loss_db: 0.0879 2022/10/26 08:15:05 - mmengine - INFO - Epoch(train) [1062][35/63] lr: 5.0521e-04 eta: 1:37:42 time: 0.5545 data_time: 0.0298 memory: 16131 loss: 0.9361 loss_prob: 0.4919 loss_thr: 0.3609 loss_db: 0.0833 2022/10/26 08:15:08 - mmengine - INFO - Epoch(train) [1062][40/63] lr: 5.0521e-04 eta: 1:37:35 time: 0.5422 data_time: 0.0090 memory: 16131 loss: 0.9073 loss_prob: 0.4838 loss_thr: 0.3411 loss_db: 0.0824 2022/10/26 08:15:11 - mmengine - INFO - Epoch(train) [1062][45/63] lr: 5.0521e-04 eta: 1:37:35 time: 0.5373 data_time: 0.0092 memory: 16131 loss: 0.8846 loss_prob: 0.4670 loss_thr: 0.3354 loss_db: 0.0821 2022/10/26 08:15:13 - mmengine - INFO - Epoch(train) [1062][50/63] lr: 5.0521e-04 eta: 1:37:28 time: 0.5144 data_time: 0.0177 memory: 16131 loss: 0.8929 loss_prob: 0.4694 loss_thr: 0.3412 loss_db: 0.0822 2022/10/26 08:15:16 - mmengine - INFO - Epoch(train) [1062][55/63] lr: 5.0521e-04 eta: 1:37:28 time: 0.5315 data_time: 0.0238 memory: 16131 loss: 0.8662 loss_prob: 0.4494 loss_thr: 0.3377 loss_db: 0.0790 2022/10/26 08:15:18 - mmengine - INFO - Epoch(train) [1062][60/63] lr: 5.0521e-04 eta: 1:37:21 time: 0.5036 data_time: 0.0123 memory: 16131 loss: 0.8519 loss_prob: 0.4442 loss_thr: 0.3308 loss_db: 0.0769 2022/10/26 08:15:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:15:26 - mmengine - INFO - Epoch(train) [1063][5/63] lr: 5.0192e-04 eta: 1:37:21 time: 0.8564 data_time: 0.1900 memory: 16131 loss: 0.8827 loss_prob: 0.4613 loss_thr: 0.3422 loss_db: 0.0792 2022/10/26 08:15:29 - mmengine - INFO - Epoch(train) [1063][10/63] lr: 5.0192e-04 eta: 1:37:12 time: 0.9044 data_time: 0.1929 memory: 16131 loss: 0.9038 loss_prob: 0.4720 loss_thr: 0.3499 loss_db: 0.0819 2022/10/26 08:15:31 - mmengine - INFO - Epoch(train) [1063][15/63] lr: 5.0192e-04 eta: 1:37:12 time: 0.5272 data_time: 0.0098 memory: 16131 loss: 0.8469 loss_prob: 0.4416 loss_thr: 0.3297 loss_db: 0.0757 2022/10/26 08:15:34 - mmengine - INFO - Epoch(train) [1063][20/63] lr: 5.0192e-04 eta: 1:37:05 time: 0.5105 data_time: 0.0074 memory: 16131 loss: 0.7692 loss_prob: 0.3933 loss_thr: 0.3070 loss_db: 0.0689 2022/10/26 08:15:37 - mmengine - INFO - Epoch(train) [1063][25/63] lr: 5.0192e-04 eta: 1:37:05 time: 0.5217 data_time: 0.0206 memory: 16131 loss: 0.8192 loss_prob: 0.4149 loss_thr: 0.3305 loss_db: 0.0738 2022/10/26 08:15:39 - mmengine - INFO - Epoch(train) [1063][30/63] lr: 5.0192e-04 eta: 1:36:58 time: 0.5461 data_time: 0.0304 memory: 16131 loss: 0.8582 loss_prob: 0.4380 loss_thr: 0.3427 loss_db: 0.0775 2022/10/26 08:15:42 - mmengine - INFO - Epoch(train) [1063][35/63] lr: 5.0192e-04 eta: 1:36:58 time: 0.5232 data_time: 0.0202 memory: 16131 loss: 0.8511 loss_prob: 0.4407 loss_thr: 0.3330 loss_db: 0.0774 2022/10/26 08:15:44 - mmengine - INFO - Epoch(train) [1063][40/63] lr: 5.0192e-04 eta: 1:36:51 time: 0.5099 data_time: 0.0119 memory: 16131 loss: 0.8614 loss_prob: 0.4463 loss_thr: 0.3371 loss_db: 0.0781 2022/10/26 08:15:47 - mmengine - INFO - Epoch(train) [1063][45/63] lr: 5.0192e-04 eta: 1:36:51 time: 0.5261 data_time: 0.0097 memory: 16131 loss: 0.9104 loss_prob: 0.4739 loss_thr: 0.3542 loss_db: 0.0823 2022/10/26 08:15:50 - mmengine - INFO - Epoch(train) [1063][50/63] lr: 5.0192e-04 eta: 1:36:45 time: 0.5430 data_time: 0.0083 memory: 16131 loss: 0.9398 loss_prob: 0.5060 loss_thr: 0.3453 loss_db: 0.0885 2022/10/26 08:15:53 - mmengine - INFO - Epoch(train) [1063][55/63] lr: 5.0192e-04 eta: 1:36:45 time: 0.5862 data_time: 0.0277 memory: 16131 loss: 0.9210 loss_prob: 0.4935 loss_thr: 0.3401 loss_db: 0.0873 2022/10/26 08:15:55 - mmengine - INFO - Epoch(train) [1063][60/63] lr: 5.0192e-04 eta: 1:36:38 time: 0.5545 data_time: 0.0295 memory: 16131 loss: 0.8961 loss_prob: 0.4660 loss_thr: 0.3488 loss_db: 0.0814 2022/10/26 08:15:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:16:02 - mmengine - INFO - Epoch(train) [1064][5/63] lr: 4.9862e-04 eta: 1:36:38 time: 0.7385 data_time: 0.2235 memory: 16131 loss: 0.8849 loss_prob: 0.4793 loss_thr: 0.3260 loss_db: 0.0795 2022/10/26 08:16:05 - mmengine - INFO - Epoch(train) [1064][10/63] lr: 4.9862e-04 eta: 1:36:29 time: 0.8029 data_time: 0.2145 memory: 16131 loss: 0.9020 loss_prob: 0.4828 loss_thr: 0.3381 loss_db: 0.0811 2022/10/26 08:16:07 - mmengine - INFO - Epoch(train) [1064][15/63] lr: 4.9862e-04 eta: 1:36:29 time: 0.5551 data_time: 0.0077 memory: 16131 loss: 0.9113 loss_prob: 0.4790 loss_thr: 0.3465 loss_db: 0.0858 2022/10/26 08:16:10 - mmengine - INFO - Epoch(train) [1064][20/63] lr: 4.9862e-04 eta: 1:36:22 time: 0.5142 data_time: 0.0087 memory: 16131 loss: 0.9792 loss_prob: 0.5239 loss_thr: 0.3629 loss_db: 0.0923 2022/10/26 08:16:13 - mmengine - INFO - Epoch(train) [1064][25/63] lr: 4.9862e-04 eta: 1:36:22 time: 0.5331 data_time: 0.0348 memory: 16131 loss: 1.0714 loss_prob: 0.5920 loss_thr: 0.3857 loss_db: 0.0936 2022/10/26 08:16:15 - mmengine - INFO - Epoch(train) [1064][30/63] lr: 4.9862e-04 eta: 1:36:15 time: 0.5301 data_time: 0.0334 memory: 16131 loss: 0.9915 loss_prob: 0.5417 loss_thr: 0.3627 loss_db: 0.0871 2022/10/26 08:16:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:16:18 - mmengine - INFO - Epoch(train) [1064][35/63] lr: 4.9862e-04 eta: 1:36:15 time: 0.4970 data_time: 0.0058 memory: 16131 loss: 0.8847 loss_prob: 0.4630 loss_thr: 0.3407 loss_db: 0.0810 2022/10/26 08:16:20 - mmengine - INFO - Epoch(train) [1064][40/63] lr: 4.9862e-04 eta: 1:36:08 time: 0.4934 data_time: 0.0060 memory: 16131 loss: 0.9183 loss_prob: 0.4904 loss_thr: 0.3459 loss_db: 0.0820 2022/10/26 08:16:23 - mmengine - INFO - Epoch(train) [1064][45/63] lr: 4.9862e-04 eta: 1:36:08 time: 0.5448 data_time: 0.0084 memory: 16131 loss: 0.9300 loss_prob: 0.4891 loss_thr: 0.3574 loss_db: 0.0836 2022/10/26 08:16:26 - mmengine - INFO - Epoch(train) [1064][50/63] lr: 4.9862e-04 eta: 1:36:01 time: 0.5867 data_time: 0.0248 memory: 16131 loss: 0.9160 loss_prob: 0.4745 loss_thr: 0.3576 loss_db: 0.0839 2022/10/26 08:16:29 - mmengine - INFO - Epoch(train) [1064][55/63] lr: 4.9862e-04 eta: 1:36:01 time: 0.5570 data_time: 0.0218 memory: 16131 loss: 0.9638 loss_prob: 0.5089 loss_thr: 0.3665 loss_db: 0.0885 2022/10/26 08:16:31 - mmengine - INFO - Epoch(train) [1064][60/63] lr: 4.9862e-04 eta: 1:35:54 time: 0.5251 data_time: 0.0055 memory: 16131 loss: 0.9577 loss_prob: 0.5021 loss_thr: 0.3691 loss_db: 0.0864 2022/10/26 08:16:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:16:37 - mmengine - INFO - Epoch(train) [1065][5/63] lr: 4.9532e-04 eta: 1:35:54 time: 0.6921 data_time: 0.1794 memory: 16131 loss: 0.8775 loss_prob: 0.4554 loss_thr: 0.3423 loss_db: 0.0798 2022/10/26 08:16:40 - mmengine - INFO - Epoch(train) [1065][10/63] lr: 4.9532e-04 eta: 1:35:45 time: 0.7141 data_time: 0.1824 memory: 16131 loss: 0.9154 loss_prob: 0.4776 loss_thr: 0.3537 loss_db: 0.0841 2022/10/26 08:16:42 - mmengine - INFO - Epoch(train) [1065][15/63] lr: 4.9532e-04 eta: 1:35:45 time: 0.5302 data_time: 0.0135 memory: 16131 loss: 0.8850 loss_prob: 0.4571 loss_thr: 0.3469 loss_db: 0.0811 2022/10/26 08:16:45 - mmengine - INFO - Epoch(train) [1065][20/63] lr: 4.9532e-04 eta: 1:35:39 time: 0.5031 data_time: 0.0090 memory: 16131 loss: 0.8712 loss_prob: 0.4474 loss_thr: 0.3456 loss_db: 0.0782 2022/10/26 08:16:48 - mmengine - INFO - Epoch(train) [1065][25/63] lr: 4.9532e-04 eta: 1:35:39 time: 0.5088 data_time: 0.0153 memory: 16131 loss: 0.9537 loss_prob: 0.5040 loss_thr: 0.3622 loss_db: 0.0874 2022/10/26 08:16:51 - mmengine - INFO - Epoch(train) [1065][30/63] lr: 4.9532e-04 eta: 1:35:32 time: 0.5687 data_time: 0.0377 memory: 16131 loss: 1.0051 loss_prob: 0.5430 loss_thr: 0.3701 loss_db: 0.0920 2022/10/26 08:16:54 - mmengine - INFO - Epoch(train) [1065][35/63] lr: 4.9532e-04 eta: 1:35:32 time: 0.5945 data_time: 0.0276 memory: 16131 loss: 0.9517 loss_prob: 0.5085 loss_thr: 0.3568 loss_db: 0.0864 2022/10/26 08:16:56 - mmengine - INFO - Epoch(train) [1065][40/63] lr: 4.9532e-04 eta: 1:35:25 time: 0.5574 data_time: 0.0051 memory: 16131 loss: 0.9324 loss_prob: 0.4912 loss_thr: 0.3550 loss_db: 0.0862 2022/10/26 08:16:59 - mmengine - INFO - Epoch(train) [1065][45/63] lr: 4.9532e-04 eta: 1:35:25 time: 0.5250 data_time: 0.0051 memory: 16131 loss: 0.9320 loss_prob: 0.4886 loss_thr: 0.3585 loss_db: 0.0849 2022/10/26 08:17:02 - mmengine - INFO - Epoch(train) [1065][50/63] lr: 4.9532e-04 eta: 1:35:18 time: 0.5445 data_time: 0.0142 memory: 16131 loss: 0.9469 loss_prob: 0.4969 loss_thr: 0.3637 loss_db: 0.0864 2022/10/26 08:17:05 - mmengine - INFO - Epoch(train) [1065][55/63] lr: 4.9532e-04 eta: 1:35:18 time: 0.6391 data_time: 0.0242 memory: 16131 loss: 0.9271 loss_prob: 0.4839 loss_thr: 0.3602 loss_db: 0.0831 2022/10/26 08:17:08 - mmengine - INFO - Epoch(train) [1065][60/63] lr: 4.9532e-04 eta: 1:35:11 time: 0.6364 data_time: 0.0152 memory: 16131 loss: 0.8989 loss_prob: 0.4681 loss_thr: 0.3510 loss_db: 0.0799 2022/10/26 08:17:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:17:13 - mmengine - INFO - Epoch(train) [1066][5/63] lr: 4.9202e-04 eta: 1:35:11 time: 0.6434 data_time: 0.1506 memory: 16131 loss: 0.8683 loss_prob: 0.4545 loss_thr: 0.3337 loss_db: 0.0801 2022/10/26 08:17:16 - mmengine - INFO - Epoch(train) [1066][10/63] lr: 4.9202e-04 eta: 1:35:02 time: 0.6768 data_time: 0.1571 memory: 16131 loss: 0.8940 loss_prob: 0.4691 loss_thr: 0.3431 loss_db: 0.0819 2022/10/26 08:17:19 - mmengine - INFO - Epoch(train) [1066][15/63] lr: 4.9202e-04 eta: 1:35:02 time: 0.5143 data_time: 0.0123 memory: 16131 loss: 0.8853 loss_prob: 0.4690 loss_thr: 0.3363 loss_db: 0.0801 2022/10/26 08:17:21 - mmengine - INFO - Epoch(train) [1066][20/63] lr: 4.9202e-04 eta: 1:34:55 time: 0.5157 data_time: 0.0055 memory: 16131 loss: 0.8446 loss_prob: 0.4431 loss_thr: 0.3247 loss_db: 0.0768 2022/10/26 08:17:24 - mmengine - INFO - Epoch(train) [1066][25/63] lr: 4.9202e-04 eta: 1:34:55 time: 0.5141 data_time: 0.0140 memory: 16131 loss: 0.8552 loss_prob: 0.4404 loss_thr: 0.3370 loss_db: 0.0777 2022/10/26 08:17:27 - mmengine - INFO - Epoch(train) [1066][30/63] lr: 4.9202e-04 eta: 1:34:48 time: 0.5496 data_time: 0.0305 memory: 16131 loss: 0.8902 loss_prob: 0.4711 loss_thr: 0.3382 loss_db: 0.0808 2022/10/26 08:17:29 - mmengine - INFO - Epoch(train) [1066][35/63] lr: 4.9202e-04 eta: 1:34:48 time: 0.5597 data_time: 0.0278 memory: 16131 loss: 1.0225 loss_prob: 0.5742 loss_thr: 0.3574 loss_db: 0.0910 2022/10/26 08:17:32 - mmengine - INFO - Epoch(train) [1066][40/63] lr: 4.9202e-04 eta: 1:34:42 time: 0.5216 data_time: 0.0149 memory: 16131 loss: 1.0190 loss_prob: 0.5620 loss_thr: 0.3660 loss_db: 0.0910 2022/10/26 08:17:34 - mmengine - INFO - Epoch(train) [1066][45/63] lr: 4.9202e-04 eta: 1:34:42 time: 0.4934 data_time: 0.0092 memory: 16131 loss: 0.9317 loss_prob: 0.4907 loss_thr: 0.3555 loss_db: 0.0855 2022/10/26 08:17:37 - mmengine - INFO - Epoch(train) [1066][50/63] lr: 4.9202e-04 eta: 1:34:35 time: 0.5491 data_time: 0.0125 memory: 16131 loss: 0.9484 loss_prob: 0.5026 loss_thr: 0.3574 loss_db: 0.0883 2022/10/26 08:17:40 - mmengine - INFO - Epoch(train) [1066][55/63] lr: 4.9202e-04 eta: 1:34:35 time: 0.5694 data_time: 0.0258 memory: 16131 loss: 0.9039 loss_prob: 0.4784 loss_thr: 0.3420 loss_db: 0.0836 2022/10/26 08:17:43 - mmengine - INFO - Epoch(train) [1066][60/63] lr: 4.9202e-04 eta: 1:34:28 time: 0.5177 data_time: 0.0189 memory: 16131 loss: 0.8798 loss_prob: 0.4653 loss_thr: 0.3343 loss_db: 0.0802 2022/10/26 08:17:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:17:48 - mmengine - INFO - Epoch(train) [1067][5/63] lr: 4.8871e-04 eta: 1:34:28 time: 0.7020 data_time: 0.1838 memory: 16131 loss: 0.9090 loss_prob: 0.4759 loss_thr: 0.3512 loss_db: 0.0820 2022/10/26 08:17:51 - mmengine - INFO - Epoch(train) [1067][10/63] lr: 4.8871e-04 eta: 1:34:19 time: 0.7031 data_time: 0.1829 memory: 16131 loss: 0.9279 loss_prob: 0.4773 loss_thr: 0.3679 loss_db: 0.0827 2022/10/26 08:17:53 - mmengine - INFO - Epoch(train) [1067][15/63] lr: 4.8871e-04 eta: 1:34:19 time: 0.5006 data_time: 0.0051 memory: 16131 loss: 0.8726 loss_prob: 0.4423 loss_thr: 0.3517 loss_db: 0.0786 2022/10/26 08:17:56 - mmengine - INFO - Epoch(train) [1067][20/63] lr: 4.8871e-04 eta: 1:34:12 time: 0.5019 data_time: 0.0081 memory: 16131 loss: 0.8646 loss_prob: 0.4435 loss_thr: 0.3431 loss_db: 0.0780 2022/10/26 08:17:58 - mmengine - INFO - Epoch(train) [1067][25/63] lr: 4.8871e-04 eta: 1:34:12 time: 0.5043 data_time: 0.0114 memory: 16131 loss: 0.8799 loss_prob: 0.4542 loss_thr: 0.3456 loss_db: 0.0801 2022/10/26 08:18:01 - mmengine - INFO - Epoch(train) [1067][30/63] lr: 4.8871e-04 eta: 1:34:05 time: 0.5137 data_time: 0.0357 memory: 16131 loss: 0.8454 loss_prob: 0.4369 loss_thr: 0.3322 loss_db: 0.0762 2022/10/26 08:18:04 - mmengine - INFO - Epoch(train) [1067][35/63] lr: 4.8871e-04 eta: 1:34:05 time: 0.5398 data_time: 0.0329 memory: 16131 loss: 0.8213 loss_prob: 0.4261 loss_thr: 0.3212 loss_db: 0.0741 2022/10/26 08:18:06 - mmengine - INFO - Epoch(train) [1067][40/63] lr: 4.8871e-04 eta: 1:33:58 time: 0.5348 data_time: 0.0117 memory: 16131 loss: 0.8617 loss_prob: 0.4437 loss_thr: 0.3390 loss_db: 0.0790 2022/10/26 08:18:09 - mmengine - INFO - Epoch(train) [1067][45/63] lr: 4.8871e-04 eta: 1:33:58 time: 0.5072 data_time: 0.0140 memory: 16131 loss: 0.8595 loss_prob: 0.4441 loss_thr: 0.3368 loss_db: 0.0786 2022/10/26 08:18:12 - mmengine - INFO - Epoch(train) [1067][50/63] lr: 4.8871e-04 eta: 1:33:51 time: 0.5127 data_time: 0.0229 memory: 16131 loss: 0.8491 loss_prob: 0.4418 loss_thr: 0.3310 loss_db: 0.0763 2022/10/26 08:18:14 - mmengine - INFO - Epoch(train) [1067][55/63] lr: 4.8871e-04 eta: 1:33:51 time: 0.5463 data_time: 0.0244 memory: 16131 loss: 0.9760 loss_prob: 0.5231 loss_thr: 0.3674 loss_db: 0.0856 2022/10/26 08:18:17 - mmengine - INFO - Epoch(train) [1067][60/63] lr: 4.8871e-04 eta: 1:33:44 time: 0.5504 data_time: 0.0116 memory: 16131 loss: 1.0164 loss_prob: 0.5491 loss_thr: 0.3755 loss_db: 0.0918 2022/10/26 08:18:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:18:23 - mmengine - INFO - Epoch(train) [1068][5/63] lr: 4.8540e-04 eta: 1:33:44 time: 0.7250 data_time: 0.1865 memory: 16131 loss: 0.8951 loss_prob: 0.4756 loss_thr: 0.3361 loss_db: 0.0834 2022/10/26 08:18:26 - mmengine - INFO - Epoch(train) [1068][10/63] lr: 4.8540e-04 eta: 1:33:36 time: 0.7742 data_time: 0.2024 memory: 16131 loss: 0.8315 loss_prob: 0.4348 loss_thr: 0.3215 loss_db: 0.0752 2022/10/26 08:18:29 - mmengine - INFO - Epoch(train) [1068][15/63] lr: 4.8540e-04 eta: 1:33:36 time: 0.5129 data_time: 0.0211 memory: 16131 loss: 0.8242 loss_prob: 0.4216 loss_thr: 0.3289 loss_db: 0.0736 2022/10/26 08:18:31 - mmengine - INFO - Epoch(train) [1068][20/63] lr: 4.8540e-04 eta: 1:33:29 time: 0.4948 data_time: 0.0064 memory: 16131 loss: 0.9051 loss_prob: 0.4642 loss_thr: 0.3589 loss_db: 0.0819 2022/10/26 08:18:34 - mmengine - INFO - Epoch(train) [1068][25/63] lr: 4.8540e-04 eta: 1:33:29 time: 0.5188 data_time: 0.0324 memory: 16131 loss: 0.9566 loss_prob: 0.4966 loss_thr: 0.3731 loss_db: 0.0869 2022/10/26 08:18:36 - mmengine - INFO - Epoch(train) [1068][30/63] lr: 4.8540e-04 eta: 1:33:22 time: 0.5008 data_time: 0.0310 memory: 16131 loss: 1.0273 loss_prob: 0.5569 loss_thr: 0.3765 loss_db: 0.0939 2022/10/26 08:18:39 - mmengine - INFO - Epoch(train) [1068][35/63] lr: 4.8540e-04 eta: 1:33:22 time: 0.5000 data_time: 0.0091 memory: 16131 loss: 1.0098 loss_prob: 0.5449 loss_thr: 0.3738 loss_db: 0.0912 2022/10/26 08:18:41 - mmengine - INFO - Epoch(train) [1068][40/63] lr: 4.8540e-04 eta: 1:33:15 time: 0.5239 data_time: 0.0091 memory: 16131 loss: 0.8766 loss_prob: 0.4528 loss_thr: 0.3467 loss_db: 0.0772 2022/10/26 08:18:44 - mmengine - INFO - Epoch(train) [1068][45/63] lr: 4.8540e-04 eta: 1:33:15 time: 0.5025 data_time: 0.0054 memory: 16131 loss: 0.8203 loss_prob: 0.4242 loss_thr: 0.3226 loss_db: 0.0736 2022/10/26 08:18:47 - mmengine - INFO - Epoch(train) [1068][50/63] lr: 4.8540e-04 eta: 1:33:08 time: 0.5319 data_time: 0.0238 memory: 16131 loss: 0.8494 loss_prob: 0.4415 loss_thr: 0.3294 loss_db: 0.0785 2022/10/26 08:18:49 - mmengine - INFO - Epoch(train) [1068][55/63] lr: 4.8540e-04 eta: 1:33:08 time: 0.5537 data_time: 0.0249 memory: 16131 loss: 0.8249 loss_prob: 0.4266 loss_thr: 0.3229 loss_db: 0.0753 2022/10/26 08:18:52 - mmengine - INFO - Epoch(train) [1068][60/63] lr: 4.8540e-04 eta: 1:33:01 time: 0.5305 data_time: 0.0151 memory: 16131 loss: 0.8228 loss_prob: 0.4316 loss_thr: 0.3156 loss_db: 0.0755 2022/10/26 08:18:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:18:59 - mmengine - INFO - Epoch(train) [1069][5/63] lr: 4.8209e-04 eta: 1:33:01 time: 0.7710 data_time: 0.2003 memory: 16131 loss: 0.8237 loss_prob: 0.4277 loss_thr: 0.3207 loss_db: 0.0753 2022/10/26 08:19:01 - mmengine - INFO - Epoch(train) [1069][10/63] lr: 4.8209e-04 eta: 1:32:52 time: 0.7721 data_time: 0.1992 memory: 16131 loss: 0.9191 loss_prob: 0.4798 loss_thr: 0.3541 loss_db: 0.0852 2022/10/26 08:19:04 - mmengine - INFO - Epoch(train) [1069][15/63] lr: 4.8209e-04 eta: 1:32:52 time: 0.5116 data_time: 0.0071 memory: 16131 loss: 0.9443 loss_prob: 0.4939 loss_thr: 0.3637 loss_db: 0.0867 2022/10/26 08:19:06 - mmengine - INFO - Epoch(train) [1069][20/63] lr: 4.8209e-04 eta: 1:32:45 time: 0.5088 data_time: 0.0070 memory: 16131 loss: 0.9060 loss_prob: 0.4739 loss_thr: 0.3488 loss_db: 0.0833 2022/10/26 08:19:09 - mmengine - INFO - Epoch(train) [1069][25/63] lr: 4.8209e-04 eta: 1:32:45 time: 0.5502 data_time: 0.0339 memory: 16131 loss: 0.8965 loss_prob: 0.4692 loss_thr: 0.3453 loss_db: 0.0820 2022/10/26 08:19:12 - mmengine - INFO - Epoch(train) [1069][30/63] lr: 4.8209e-04 eta: 1:32:38 time: 0.5402 data_time: 0.0367 memory: 16131 loss: 0.8762 loss_prob: 0.4581 loss_thr: 0.3388 loss_db: 0.0793 2022/10/26 08:19:14 - mmengine - INFO - Epoch(train) [1069][35/63] lr: 4.8209e-04 eta: 1:32:38 time: 0.4934 data_time: 0.0085 memory: 16131 loss: 0.8254 loss_prob: 0.4255 loss_thr: 0.3250 loss_db: 0.0749 2022/10/26 08:19:17 - mmengine - INFO - Epoch(train) [1069][40/63] lr: 4.8209e-04 eta: 1:32:31 time: 0.4857 data_time: 0.0069 memory: 16131 loss: 0.8391 loss_prob: 0.4298 loss_thr: 0.3328 loss_db: 0.0764 2022/10/26 08:19:19 - mmengine - INFO - Epoch(train) [1069][45/63] lr: 4.8209e-04 eta: 1:32:31 time: 0.5156 data_time: 0.0092 memory: 16131 loss: 0.8573 loss_prob: 0.4412 loss_thr: 0.3382 loss_db: 0.0778 2022/10/26 08:19:22 - mmengine - INFO - Epoch(train) [1069][50/63] lr: 4.8209e-04 eta: 1:32:25 time: 0.5377 data_time: 0.0272 memory: 16131 loss: 0.9054 loss_prob: 0.4707 loss_thr: 0.3522 loss_db: 0.0826 2022/10/26 08:19:24 - mmengine - INFO - Epoch(train) [1069][55/63] lr: 4.8209e-04 eta: 1:32:25 time: 0.5105 data_time: 0.0244 memory: 16131 loss: 0.8892 loss_prob: 0.4631 loss_thr: 0.3449 loss_db: 0.0813 2022/10/26 08:19:27 - mmengine - INFO - Epoch(train) [1069][60/63] lr: 4.8209e-04 eta: 1:32:18 time: 0.5114 data_time: 0.0066 memory: 16131 loss: 0.8423 loss_prob: 0.4287 loss_thr: 0.3382 loss_db: 0.0753 2022/10/26 08:19:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:19:34 - mmengine - INFO - Epoch(train) [1070][5/63] lr: 4.7878e-04 eta: 1:32:18 time: 0.7677 data_time: 0.1957 memory: 16131 loss: 0.9478 loss_prob: 0.5004 loss_thr: 0.3610 loss_db: 0.0865 2022/10/26 08:19:36 - mmengine - INFO - Epoch(train) [1070][10/63] lr: 4.7878e-04 eta: 1:32:09 time: 0.7409 data_time: 0.1970 memory: 16131 loss: 0.9277 loss_prob: 0.4872 loss_thr: 0.3562 loss_db: 0.0844 2022/10/26 08:19:39 - mmengine - INFO - Epoch(train) [1070][15/63] lr: 4.7878e-04 eta: 1:32:09 time: 0.5053 data_time: 0.0097 memory: 16131 loss: 0.8502 loss_prob: 0.4381 loss_thr: 0.3357 loss_db: 0.0765 2022/10/26 08:19:41 - mmengine - INFO - Epoch(train) [1070][20/63] lr: 4.7878e-04 eta: 1:32:02 time: 0.5152 data_time: 0.0072 memory: 16131 loss: 0.8053 loss_prob: 0.4146 loss_thr: 0.3192 loss_db: 0.0714 2022/10/26 08:19:44 - mmengine - INFO - Epoch(train) [1070][25/63] lr: 4.7878e-04 eta: 1:32:02 time: 0.5398 data_time: 0.0300 memory: 16131 loss: 0.9047 loss_prob: 0.4687 loss_thr: 0.3549 loss_db: 0.0811 2022/10/26 08:19:47 - mmengine - INFO - Epoch(train) [1070][30/63] lr: 4.7878e-04 eta: 1:31:55 time: 0.5375 data_time: 0.0305 memory: 16131 loss: 0.9255 loss_prob: 0.4870 loss_thr: 0.3540 loss_db: 0.0845 2022/10/26 08:19:49 - mmengine - INFO - Epoch(train) [1070][35/63] lr: 4.7878e-04 eta: 1:31:55 time: 0.4986 data_time: 0.0066 memory: 16131 loss: 0.8743 loss_prob: 0.4673 loss_thr: 0.3275 loss_db: 0.0794 2022/10/26 08:19:52 - mmengine - INFO - Epoch(train) [1070][40/63] lr: 4.7878e-04 eta: 1:31:48 time: 0.4952 data_time: 0.0114 memory: 16131 loss: 0.8492 loss_prob: 0.4460 loss_thr: 0.3267 loss_db: 0.0765 2022/10/26 08:19:54 - mmengine - INFO - Epoch(train) [1070][45/63] lr: 4.7878e-04 eta: 1:31:48 time: 0.5160 data_time: 0.0163 memory: 16131 loss: 0.8701 loss_prob: 0.4476 loss_thr: 0.3445 loss_db: 0.0779 2022/10/26 08:19:57 - mmengine - INFO - Epoch(train) [1070][50/63] lr: 4.7878e-04 eta: 1:31:41 time: 0.5420 data_time: 0.0269 memory: 16131 loss: 0.8797 loss_prob: 0.4506 loss_thr: 0.3498 loss_db: 0.0793 2022/10/26 08:20:00 - mmengine - INFO - Epoch(train) [1070][55/63] lr: 4.7878e-04 eta: 1:31:41 time: 0.5180 data_time: 0.0206 memory: 16131 loss: 0.8185 loss_prob: 0.4213 loss_thr: 0.3224 loss_db: 0.0748 2022/10/26 08:20:02 - mmengine - INFO - Epoch(train) [1070][60/63] lr: 4.7878e-04 eta: 1:31:34 time: 0.5090 data_time: 0.0074 memory: 16131 loss: 0.8645 loss_prob: 0.4446 loss_thr: 0.3422 loss_db: 0.0777 2022/10/26 08:20:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:20:08 - mmengine - INFO - Epoch(train) [1071][5/63] lr: 4.7547e-04 eta: 1:31:34 time: 0.6948 data_time: 0.1972 memory: 16131 loss: 0.9568 loss_prob: 0.5078 loss_thr: 0.3616 loss_db: 0.0874 2022/10/26 08:20:11 - mmengine - INFO - Epoch(train) [1071][10/63] lr: 4.7547e-04 eta: 1:31:25 time: 0.7323 data_time: 0.1965 memory: 16131 loss: 0.9640 loss_prob: 0.5169 loss_thr: 0.3594 loss_db: 0.0877 2022/10/26 08:20:14 - mmengine - INFO - Epoch(train) [1071][15/63] lr: 4.7547e-04 eta: 1:31:25 time: 0.5548 data_time: 0.0057 memory: 16131 loss: 0.9028 loss_prob: 0.4735 loss_thr: 0.3456 loss_db: 0.0838 2022/10/26 08:20:16 - mmengine - INFO - Epoch(train) [1071][20/63] lr: 4.7547e-04 eta: 1:31:19 time: 0.5530 data_time: 0.0060 memory: 16131 loss: 0.8915 loss_prob: 0.4717 loss_thr: 0.3366 loss_db: 0.0832 2022/10/26 08:20:19 - mmengine - INFO - Epoch(train) [1071][25/63] lr: 4.7547e-04 eta: 1:31:19 time: 0.5416 data_time: 0.0209 memory: 16131 loss: 0.8472 loss_prob: 0.4464 loss_thr: 0.3234 loss_db: 0.0774 2022/10/26 08:20:22 - mmengine - INFO - Epoch(train) [1071][30/63] lr: 4.7547e-04 eta: 1:31:12 time: 0.5353 data_time: 0.0383 memory: 16131 loss: 0.8323 loss_prob: 0.4356 loss_thr: 0.3220 loss_db: 0.0747 2022/10/26 08:20:24 - mmengine - INFO - Epoch(train) [1071][35/63] lr: 4.7547e-04 eta: 1:31:12 time: 0.5292 data_time: 0.0230 memory: 16131 loss: 0.8568 loss_prob: 0.4501 loss_thr: 0.3299 loss_db: 0.0768 2022/10/26 08:20:29 - mmengine - INFO - Epoch(train) [1071][40/63] lr: 4.7547e-04 eta: 1:31:05 time: 0.6752 data_time: 0.0047 memory: 16131 loss: 0.9301 loss_prob: 0.4893 loss_thr: 0.3550 loss_db: 0.0858 2022/10/26 08:20:31 - mmengine - INFO - Epoch(train) [1071][45/63] lr: 4.7547e-04 eta: 1:31:05 time: 0.6885 data_time: 0.0051 memory: 16131 loss: 0.8932 loss_prob: 0.4661 loss_thr: 0.3442 loss_db: 0.0828 2022/10/26 08:20:34 - mmengine - INFO - Epoch(train) [1071][50/63] lr: 4.7547e-04 eta: 1:30:58 time: 0.5419 data_time: 0.0254 memory: 16131 loss: 0.8691 loss_prob: 0.4605 loss_thr: 0.3266 loss_db: 0.0819 2022/10/26 08:20:37 - mmengine - INFO - Epoch(train) [1071][55/63] lr: 4.7547e-04 eta: 1:30:58 time: 0.5222 data_time: 0.0267 memory: 16131 loss: 0.8922 loss_prob: 0.4708 loss_thr: 0.3385 loss_db: 0.0829 2022/10/26 08:20:39 - mmengine - INFO - Epoch(train) [1071][60/63] lr: 4.7547e-04 eta: 1:30:51 time: 0.5126 data_time: 0.0061 memory: 16131 loss: 0.8682 loss_prob: 0.4487 loss_thr: 0.3409 loss_db: 0.0786 2022/10/26 08:20:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:20:45 - mmengine - INFO - Epoch(train) [1072][5/63] lr: 4.7215e-04 eta: 1:30:51 time: 0.7112 data_time: 0.2090 memory: 16131 loss: 0.8142 loss_prob: 0.4153 loss_thr: 0.3273 loss_db: 0.0716 2022/10/26 08:20:48 - mmengine - INFO - Epoch(train) [1072][10/63] lr: 4.7215e-04 eta: 1:30:42 time: 0.7464 data_time: 0.2083 memory: 16131 loss: 0.8240 loss_prob: 0.4247 loss_thr: 0.3265 loss_db: 0.0728 2022/10/26 08:20:50 - mmengine - INFO - Epoch(train) [1072][15/63] lr: 4.7215e-04 eta: 1:30:42 time: 0.5015 data_time: 0.0050 memory: 16131 loss: 0.8486 loss_prob: 0.4436 loss_thr: 0.3267 loss_db: 0.0783 2022/10/26 08:20:53 - mmengine - INFO - Epoch(train) [1072][20/63] lr: 4.7215e-04 eta: 1:30:35 time: 0.4820 data_time: 0.0052 memory: 16131 loss: 0.8990 loss_prob: 0.4705 loss_thr: 0.3455 loss_db: 0.0830 2022/10/26 08:20:55 - mmengine - INFO - Epoch(train) [1072][25/63] lr: 4.7215e-04 eta: 1:30:35 time: 0.5126 data_time: 0.0315 memory: 16131 loss: 0.9147 loss_prob: 0.4757 loss_thr: 0.3557 loss_db: 0.0833 2022/10/26 08:20:58 - mmengine - INFO - Epoch(train) [1072][30/63] lr: 4.7215e-04 eta: 1:30:29 time: 0.5317 data_time: 0.0354 memory: 16131 loss: 0.8357 loss_prob: 0.4367 loss_thr: 0.3231 loss_db: 0.0759 2022/10/26 08:21:00 - mmengine - INFO - Epoch(train) [1072][35/63] lr: 4.7215e-04 eta: 1:30:29 time: 0.4990 data_time: 0.0093 memory: 16131 loss: 0.7986 loss_prob: 0.4186 loss_thr: 0.3077 loss_db: 0.0722 2022/10/26 08:21:03 - mmengine - INFO - Epoch(train) [1072][40/63] lr: 4.7215e-04 eta: 1:30:22 time: 0.5446 data_time: 0.0090 memory: 16131 loss: 0.9367 loss_prob: 0.5020 loss_thr: 0.3502 loss_db: 0.0845 2022/10/26 08:21:06 - mmengine - INFO - Epoch(train) [1072][45/63] lr: 4.7215e-04 eta: 1:30:22 time: 0.5401 data_time: 0.0085 memory: 16131 loss: 0.9598 loss_prob: 0.5108 loss_thr: 0.3626 loss_db: 0.0865 2022/10/26 08:21:09 - mmengine - INFO - Epoch(train) [1072][50/63] lr: 4.7215e-04 eta: 1:30:15 time: 0.5262 data_time: 0.0218 memory: 16131 loss: 0.8207 loss_prob: 0.4231 loss_thr: 0.3221 loss_db: 0.0755 2022/10/26 08:21:12 - mmengine - INFO - Epoch(train) [1072][55/63] lr: 4.7215e-04 eta: 1:30:15 time: 0.5753 data_time: 0.0216 memory: 16131 loss: 0.8059 loss_prob: 0.4181 loss_thr: 0.3131 loss_db: 0.0746 2022/10/26 08:21:14 - mmengine - INFO - Epoch(train) [1072][60/63] lr: 4.7215e-04 eta: 1:30:08 time: 0.5502 data_time: 0.0053 memory: 16131 loss: 0.8721 loss_prob: 0.4624 loss_thr: 0.3307 loss_db: 0.0791 2022/10/26 08:21:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:21:20 - mmengine - INFO - Epoch(train) [1073][5/63] lr: 4.6883e-04 eta: 1:30:08 time: 0.7198 data_time: 0.1630 memory: 16131 loss: 0.9074 loss_prob: 0.4768 loss_thr: 0.3498 loss_db: 0.0809 2022/10/26 08:21:23 - mmengine - INFO - Epoch(train) [1073][10/63] lr: 4.6883e-04 eta: 1:29:59 time: 0.7673 data_time: 0.1634 memory: 16131 loss: 0.8961 loss_prob: 0.4694 loss_thr: 0.3450 loss_db: 0.0817 2022/10/26 08:21:25 - mmengine - INFO - Epoch(train) [1073][15/63] lr: 4.6883e-04 eta: 1:29:59 time: 0.5071 data_time: 0.0051 memory: 16131 loss: 0.8590 loss_prob: 0.4532 loss_thr: 0.3276 loss_db: 0.0782 2022/10/26 08:21:28 - mmengine - INFO - Epoch(train) [1073][20/63] lr: 4.6883e-04 eta: 1:29:52 time: 0.5077 data_time: 0.0045 memory: 16131 loss: 0.8408 loss_prob: 0.4400 loss_thr: 0.3240 loss_db: 0.0768 2022/10/26 08:21:31 - mmengine - INFO - Epoch(train) [1073][25/63] lr: 4.6883e-04 eta: 1:29:52 time: 0.5255 data_time: 0.0104 memory: 16131 loss: 0.8555 loss_prob: 0.4440 loss_thr: 0.3345 loss_db: 0.0771 2022/10/26 08:21:34 - mmengine - INFO - Epoch(train) [1073][30/63] lr: 4.6883e-04 eta: 1:29:45 time: 0.5351 data_time: 0.0428 memory: 16131 loss: 0.8978 loss_prob: 0.4666 loss_thr: 0.3516 loss_db: 0.0796 2022/10/26 08:21:36 - mmengine - INFO - Epoch(train) [1073][35/63] lr: 4.6883e-04 eta: 1:29:45 time: 0.5246 data_time: 0.0383 memory: 16131 loss: 0.8906 loss_prob: 0.4605 loss_thr: 0.3502 loss_db: 0.0798 2022/10/26 08:21:39 - mmengine - INFO - Epoch(train) [1073][40/63] lr: 4.6883e-04 eta: 1:29:39 time: 0.5095 data_time: 0.0062 memory: 16131 loss: 0.8902 loss_prob: 0.4605 loss_thr: 0.3496 loss_db: 0.0801 2022/10/26 08:21:41 - mmengine - INFO - Epoch(train) [1073][45/63] lr: 4.6883e-04 eta: 1:29:39 time: 0.5189 data_time: 0.0058 memory: 16131 loss: 0.9165 loss_prob: 0.4784 loss_thr: 0.3554 loss_db: 0.0828 2022/10/26 08:21:44 - mmengine - INFO - Epoch(train) [1073][50/63] lr: 4.6883e-04 eta: 1:29:32 time: 0.5186 data_time: 0.0215 memory: 16131 loss: 0.8756 loss_prob: 0.4580 loss_thr: 0.3370 loss_db: 0.0806 2022/10/26 08:21:46 - mmengine - INFO - Epoch(train) [1073][55/63] lr: 4.6883e-04 eta: 1:29:32 time: 0.5245 data_time: 0.0221 memory: 16131 loss: 0.8497 loss_prob: 0.4425 loss_thr: 0.3303 loss_db: 0.0769 2022/10/26 08:21:49 - mmengine - INFO - Epoch(train) [1073][60/63] lr: 4.6883e-04 eta: 1:29:25 time: 0.5147 data_time: 0.0084 memory: 16131 loss: 0.9577 loss_prob: 0.5120 loss_thr: 0.3593 loss_db: 0.0864 2022/10/26 08:21:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:21:55 - mmengine - INFO - Epoch(train) [1074][5/63] lr: 4.6551e-04 eta: 1:29:25 time: 0.7082 data_time: 0.1837 memory: 16131 loss: 0.8845 loss_prob: 0.4603 loss_thr: 0.3438 loss_db: 0.0804 2022/10/26 08:21:58 - mmengine - INFO - Epoch(train) [1074][10/63] lr: 4.6551e-04 eta: 1:29:16 time: 0.7626 data_time: 0.1932 memory: 16131 loss: 0.8470 loss_prob: 0.4384 loss_thr: 0.3327 loss_db: 0.0759 2022/10/26 08:22:01 - mmengine - INFO - Epoch(train) [1074][15/63] lr: 4.6551e-04 eta: 1:29:16 time: 0.5541 data_time: 0.0188 memory: 16131 loss: 0.8531 loss_prob: 0.4383 loss_thr: 0.3386 loss_db: 0.0763 2022/10/26 08:22:03 - mmengine - INFO - Epoch(train) [1074][20/63] lr: 4.6551e-04 eta: 1:29:09 time: 0.5088 data_time: 0.0081 memory: 16131 loss: 0.8203 loss_prob: 0.4154 loss_thr: 0.3308 loss_db: 0.0740 2022/10/26 08:22:06 - mmengine - INFO - Epoch(train) [1074][25/63] lr: 4.6551e-04 eta: 1:29:09 time: 0.4946 data_time: 0.0074 memory: 16131 loss: 0.9245 loss_prob: 0.4744 loss_thr: 0.3671 loss_db: 0.0829 2022/10/26 08:22:08 - mmengine - INFO - Epoch(train) [1074][30/63] lr: 4.6551e-04 eta: 1:29:02 time: 0.5269 data_time: 0.0229 memory: 16131 loss: 1.0090 loss_prob: 0.5327 loss_thr: 0.3838 loss_db: 0.0925 2022/10/26 08:22:11 - mmengine - INFO - Epoch(train) [1074][35/63] lr: 4.6551e-04 eta: 1:29:02 time: 0.5519 data_time: 0.0300 memory: 16131 loss: 0.9328 loss_prob: 0.4869 loss_thr: 0.3609 loss_db: 0.0850 2022/10/26 08:22:14 - mmengine - INFO - Epoch(train) [1074][40/63] lr: 4.6551e-04 eta: 1:28:55 time: 0.5256 data_time: 0.0183 memory: 16131 loss: 0.8528 loss_prob: 0.4386 loss_thr: 0.3378 loss_db: 0.0765 2022/10/26 08:22:16 - mmengine - INFO - Epoch(train) [1074][45/63] lr: 4.6551e-04 eta: 1:28:55 time: 0.5066 data_time: 0.0097 memory: 16131 loss: 0.8679 loss_prob: 0.4494 loss_thr: 0.3396 loss_db: 0.0789 2022/10/26 08:22:19 - mmengine - INFO - Epoch(train) [1074][50/63] lr: 4.6551e-04 eta: 1:28:48 time: 0.5568 data_time: 0.0178 memory: 16131 loss: 0.8603 loss_prob: 0.4490 loss_thr: 0.3327 loss_db: 0.0786 2022/10/26 08:22:22 - mmengine - INFO - Epoch(train) [1074][55/63] lr: 4.6551e-04 eta: 1:28:48 time: 0.5926 data_time: 0.0182 memory: 16131 loss: 0.8720 loss_prob: 0.4548 loss_thr: 0.3377 loss_db: 0.0795 2022/10/26 08:22:25 - mmengine - INFO - Epoch(train) [1074][60/63] lr: 4.6551e-04 eta: 1:28:42 time: 0.5514 data_time: 0.0123 memory: 16131 loss: 0.9154 loss_prob: 0.4792 loss_thr: 0.3528 loss_db: 0.0834 2022/10/26 08:22:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:22:31 - mmengine - INFO - Epoch(train) [1075][5/63] lr: 4.6218e-04 eta: 1:28:42 time: 0.7088 data_time: 0.1838 memory: 16131 loss: 0.9099 loss_prob: 0.4724 loss_thr: 0.3555 loss_db: 0.0820 2022/10/26 08:22:33 - mmengine - INFO - Epoch(train) [1075][10/63] lr: 4.6218e-04 eta: 1:28:33 time: 0.7425 data_time: 0.1851 memory: 16131 loss: 0.8500 loss_prob: 0.4382 loss_thr: 0.3357 loss_db: 0.0761 2022/10/26 08:22:36 - mmengine - INFO - Epoch(train) [1075][15/63] lr: 4.6218e-04 eta: 1:28:33 time: 0.5470 data_time: 0.0130 memory: 16131 loss: 0.8638 loss_prob: 0.4476 loss_thr: 0.3374 loss_db: 0.0788 2022/10/26 08:22:39 - mmengine - INFO - Epoch(train) [1075][20/63] lr: 4.6218e-04 eta: 1:28:26 time: 0.5420 data_time: 0.0089 memory: 16131 loss: 0.8653 loss_prob: 0.4483 loss_thr: 0.3383 loss_db: 0.0787 2022/10/26 08:22:42 - mmengine - INFO - Epoch(train) [1075][25/63] lr: 4.6218e-04 eta: 1:28:26 time: 0.5420 data_time: 0.0242 memory: 16131 loss: 0.8169 loss_prob: 0.4267 loss_thr: 0.3164 loss_db: 0.0737 2022/10/26 08:22:44 - mmengine - INFO - Epoch(train) [1075][30/63] lr: 4.6218e-04 eta: 1:28:19 time: 0.5259 data_time: 0.0233 memory: 16131 loss: 0.8222 loss_prob: 0.4318 loss_thr: 0.3171 loss_db: 0.0733 2022/10/26 08:22:47 - mmengine - INFO - Epoch(train) [1075][35/63] lr: 4.6218e-04 eta: 1:28:19 time: 0.5032 data_time: 0.0117 memory: 16131 loss: 0.8057 loss_prob: 0.4146 loss_thr: 0.3197 loss_db: 0.0714 2022/10/26 08:22:49 - mmengine - INFO - Epoch(train) [1075][40/63] lr: 4.6218e-04 eta: 1:28:12 time: 0.4939 data_time: 0.0131 memory: 16131 loss: 0.8311 loss_prob: 0.4353 loss_thr: 0.3206 loss_db: 0.0752 2022/10/26 08:22:52 - mmengine - INFO - Epoch(train) [1075][45/63] lr: 4.6218e-04 eta: 1:28:12 time: 0.5015 data_time: 0.0099 memory: 16131 loss: 0.9103 loss_prob: 0.4891 loss_thr: 0.3372 loss_db: 0.0840 2022/10/26 08:22:55 - mmengine - INFO - Epoch(train) [1075][50/63] lr: 4.6218e-04 eta: 1:28:05 time: 0.6253 data_time: 0.0258 memory: 16131 loss: 0.9013 loss_prob: 0.4752 loss_thr: 0.3435 loss_db: 0.0826 2022/10/26 08:22:58 - mmengine - INFO - Epoch(train) [1075][55/63] lr: 4.6218e-04 eta: 1:28:05 time: 0.6088 data_time: 0.0270 memory: 16131 loss: 0.8959 loss_prob: 0.4655 loss_thr: 0.3503 loss_db: 0.0801 2022/10/26 08:23:00 - mmengine - INFO - Epoch(train) [1075][60/63] lr: 4.6218e-04 eta: 1:27:58 time: 0.5112 data_time: 0.0106 memory: 16131 loss: 0.8903 loss_prob: 0.4628 loss_thr: 0.3473 loss_db: 0.0802 2022/10/26 08:23:02 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:23:06 - mmengine - INFO - Epoch(train) [1076][5/63] lr: 4.5885e-04 eta: 1:27:58 time: 0.6319 data_time: 0.1383 memory: 16131 loss: 0.8385 loss_prob: 0.4331 loss_thr: 0.3288 loss_db: 0.0766 2022/10/26 08:23:08 - mmengine - INFO - Epoch(train) [1076][10/63] lr: 4.5885e-04 eta: 1:27:49 time: 0.6476 data_time: 0.1438 memory: 16131 loss: 0.8936 loss_prob: 0.4639 loss_thr: 0.3475 loss_db: 0.0822 2022/10/26 08:23:11 - mmengine - INFO - Epoch(train) [1076][15/63] lr: 4.5885e-04 eta: 1:27:49 time: 0.5149 data_time: 0.0151 memory: 16131 loss: 0.9173 loss_prob: 0.4693 loss_thr: 0.3670 loss_db: 0.0810 2022/10/26 08:23:13 - mmengine - INFO - Epoch(train) [1076][20/63] lr: 4.5885e-04 eta: 1:27:43 time: 0.5049 data_time: 0.0119 memory: 16131 loss: 0.9030 loss_prob: 0.4637 loss_thr: 0.3597 loss_db: 0.0796 2022/10/26 08:23:16 - mmengine - INFO - Epoch(train) [1076][25/63] lr: 4.5885e-04 eta: 1:27:43 time: 0.5273 data_time: 0.0168 memory: 16131 loss: 0.8954 loss_prob: 0.4611 loss_thr: 0.3533 loss_db: 0.0810 2022/10/26 08:23:19 - mmengine - INFO - Epoch(train) [1076][30/63] lr: 4.5885e-04 eta: 1:27:36 time: 0.5657 data_time: 0.0248 memory: 16131 loss: 0.9026 loss_prob: 0.4685 loss_thr: 0.3508 loss_db: 0.0833 2022/10/26 08:23:22 - mmengine - INFO - Epoch(train) [1076][35/63] lr: 4.5885e-04 eta: 1:27:36 time: 0.5602 data_time: 0.0246 memory: 16131 loss: 0.8913 loss_prob: 0.4700 loss_thr: 0.3388 loss_db: 0.0825 2022/10/26 08:23:24 - mmengine - INFO - Epoch(train) [1076][40/63] lr: 4.5885e-04 eta: 1:27:29 time: 0.5181 data_time: 0.0146 memory: 16131 loss: 0.8736 loss_prob: 0.4606 loss_thr: 0.3328 loss_db: 0.0801 2022/10/26 08:23:27 - mmengine - INFO - Epoch(train) [1076][45/63] lr: 4.5885e-04 eta: 1:27:29 time: 0.4961 data_time: 0.0115 memory: 16131 loss: 0.9638 loss_prob: 0.5269 loss_thr: 0.3481 loss_db: 0.0888 2022/10/26 08:23:29 - mmengine - INFO - Epoch(train) [1076][50/63] lr: 4.5885e-04 eta: 1:27:22 time: 0.5077 data_time: 0.0158 memory: 16131 loss: 0.9414 loss_prob: 0.5084 loss_thr: 0.3470 loss_db: 0.0860 2022/10/26 08:23:32 - mmengine - INFO - Epoch(train) [1076][55/63] lr: 4.5885e-04 eta: 1:27:22 time: 0.5358 data_time: 0.0218 memory: 16131 loss: 0.8772 loss_prob: 0.4572 loss_thr: 0.3386 loss_db: 0.0814 2022/10/26 08:23:35 - mmengine - INFO - Epoch(train) [1076][60/63] lr: 4.5885e-04 eta: 1:27:15 time: 0.5480 data_time: 0.0184 memory: 16131 loss: 0.8719 loss_prob: 0.4611 loss_thr: 0.3314 loss_db: 0.0793 2022/10/26 08:23:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:23:40 - mmengine - INFO - Epoch(train) [1077][5/63] lr: 4.5552e-04 eta: 1:27:15 time: 0.6776 data_time: 0.1798 memory: 16131 loss: 0.8884 loss_prob: 0.4680 loss_thr: 0.3386 loss_db: 0.0818 2022/10/26 08:23:43 - mmengine - INFO - Epoch(train) [1077][10/63] lr: 4.5552e-04 eta: 1:27:06 time: 0.7401 data_time: 0.1790 memory: 16131 loss: 0.8368 loss_prob: 0.4365 loss_thr: 0.3236 loss_db: 0.0766 2022/10/26 08:23:46 - mmengine - INFO - Epoch(train) [1077][15/63] lr: 4.5552e-04 eta: 1:27:06 time: 0.5313 data_time: 0.0074 memory: 16131 loss: 0.8816 loss_prob: 0.4615 loss_thr: 0.3408 loss_db: 0.0793 2022/10/26 08:23:49 - mmengine - INFO - Epoch(train) [1077][20/63] lr: 4.5552e-04 eta: 1:26:59 time: 0.5327 data_time: 0.0084 memory: 16131 loss: 0.8862 loss_prob: 0.4685 loss_thr: 0.3366 loss_db: 0.0811 2022/10/26 08:23:51 - mmengine - INFO - Epoch(train) [1077][25/63] lr: 4.5552e-04 eta: 1:26:59 time: 0.5499 data_time: 0.0240 memory: 16131 loss: 0.8332 loss_prob: 0.4417 loss_thr: 0.3144 loss_db: 0.0772 2022/10/26 08:23:54 - mmengine - INFO - Epoch(train) [1077][30/63] lr: 4.5552e-04 eta: 1:26:53 time: 0.5340 data_time: 0.0377 memory: 16131 loss: 0.8534 loss_prob: 0.4486 loss_thr: 0.3276 loss_db: 0.0772 2022/10/26 08:23:56 - mmengine - INFO - Epoch(train) [1077][35/63] lr: 4.5552e-04 eta: 1:26:53 time: 0.5112 data_time: 0.0250 memory: 16131 loss: 0.8755 loss_prob: 0.4524 loss_thr: 0.3444 loss_db: 0.0786 2022/10/26 08:23:59 - mmengine - INFO - Epoch(train) [1077][40/63] lr: 4.5552e-04 eta: 1:26:46 time: 0.5301 data_time: 0.0119 memory: 16131 loss: 0.9580 loss_prob: 0.4950 loss_thr: 0.3769 loss_db: 0.0861 2022/10/26 08:24:02 - mmengine - INFO - Epoch(train) [1077][45/63] lr: 4.5552e-04 eta: 1:26:46 time: 0.5403 data_time: 0.0067 memory: 16131 loss: 0.9203 loss_prob: 0.4752 loss_thr: 0.3610 loss_db: 0.0842 2022/10/26 08:24:05 - mmengine - INFO - Epoch(train) [1077][50/63] lr: 4.5552e-04 eta: 1:26:39 time: 0.5320 data_time: 0.0131 memory: 16131 loss: 0.8296 loss_prob: 0.4266 loss_thr: 0.3284 loss_db: 0.0747 2022/10/26 08:24:07 - mmengine - INFO - Epoch(train) [1077][55/63] lr: 4.5552e-04 eta: 1:26:39 time: 0.5615 data_time: 0.0221 memory: 16131 loss: 0.8345 loss_prob: 0.4222 loss_thr: 0.3396 loss_db: 0.0727 2022/10/26 08:24:10 - mmengine - INFO - Epoch(train) [1077][60/63] lr: 4.5552e-04 eta: 1:26:32 time: 0.5597 data_time: 0.0145 memory: 16131 loss: 0.8465 loss_prob: 0.4251 loss_thr: 0.3465 loss_db: 0.0748 2022/10/26 08:24:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:24:15 - mmengine - INFO - Epoch(train) [1078][5/63] lr: 4.5219e-04 eta: 1:26:32 time: 0.6372 data_time: 0.1780 memory: 16131 loss: 0.9506 loss_prob: 0.4967 loss_thr: 0.3676 loss_db: 0.0863 2022/10/26 08:24:18 - mmengine - INFO - Epoch(train) [1078][10/63] lr: 4.5219e-04 eta: 1:26:23 time: 0.6801 data_time: 0.1727 memory: 16131 loss: 0.9552 loss_prob: 0.5101 loss_thr: 0.3571 loss_db: 0.0880 2022/10/26 08:24:21 - mmengine - INFO - Epoch(train) [1078][15/63] lr: 4.5219e-04 eta: 1:26:23 time: 0.5214 data_time: 0.0054 memory: 16131 loss: 0.9319 loss_prob: 0.4946 loss_thr: 0.3502 loss_db: 0.0871 2022/10/26 08:24:23 - mmengine - INFO - Epoch(train) [1078][20/63] lr: 4.5219e-04 eta: 1:26:16 time: 0.5025 data_time: 0.0053 memory: 16131 loss: 0.9081 loss_prob: 0.4739 loss_thr: 0.3517 loss_db: 0.0825 2022/10/26 08:24:26 - mmengine - INFO - Epoch(train) [1078][25/63] lr: 4.5219e-04 eta: 1:26:16 time: 0.5106 data_time: 0.0130 memory: 16131 loss: 0.8715 loss_prob: 0.4471 loss_thr: 0.3466 loss_db: 0.0779 2022/10/26 08:24:29 - mmengine - INFO - Epoch(train) [1078][30/63] lr: 4.5219e-04 eta: 1:26:09 time: 0.5275 data_time: 0.0357 memory: 16131 loss: 0.8857 loss_prob: 0.4511 loss_thr: 0.3539 loss_db: 0.0807 2022/10/26 08:24:31 - mmengine - INFO - Epoch(train) [1078][35/63] lr: 4.5219e-04 eta: 1:26:09 time: 0.5356 data_time: 0.0276 memory: 16131 loss: 0.9311 loss_prob: 0.4860 loss_thr: 0.3607 loss_db: 0.0844 2022/10/26 08:24:34 - mmengine - INFO - Epoch(train) [1078][40/63] lr: 4.5219e-04 eta: 1:26:03 time: 0.5396 data_time: 0.0047 memory: 16131 loss: 0.9250 loss_prob: 0.4873 loss_thr: 0.3539 loss_db: 0.0838 2022/10/26 08:24:37 - mmengine - INFO - Epoch(train) [1078][45/63] lr: 4.5219e-04 eta: 1:26:03 time: 0.5367 data_time: 0.0060 memory: 16131 loss: 0.8611 loss_prob: 0.4463 loss_thr: 0.3363 loss_db: 0.0785 2022/10/26 08:24:39 - mmengine - INFO - Epoch(train) [1078][50/63] lr: 4.5219e-04 eta: 1:25:56 time: 0.5219 data_time: 0.0138 memory: 16131 loss: 0.8270 loss_prob: 0.4215 loss_thr: 0.3313 loss_db: 0.0743 2022/10/26 08:24:42 - mmengine - INFO - Epoch(train) [1078][55/63] lr: 4.5219e-04 eta: 1:25:56 time: 0.5076 data_time: 0.0230 memory: 16131 loss: 0.8915 loss_prob: 0.4644 loss_thr: 0.3477 loss_db: 0.0795 2022/10/26 08:24:44 - mmengine - INFO - Epoch(train) [1078][60/63] lr: 4.5219e-04 eta: 1:25:49 time: 0.5019 data_time: 0.0166 memory: 16131 loss: 0.9646 loss_prob: 0.5184 loss_thr: 0.3589 loss_db: 0.0873 2022/10/26 08:24:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:24:51 - mmengine - INFO - Epoch(train) [1079][5/63] lr: 4.4885e-04 eta: 1:25:49 time: 0.7500 data_time: 0.1750 memory: 16131 loss: 0.9032 loss_prob: 0.4767 loss_thr: 0.3461 loss_db: 0.0803 2022/10/26 08:24:53 - mmengine - INFO - Epoch(train) [1079][10/63] lr: 4.4885e-04 eta: 1:25:40 time: 0.7310 data_time: 0.1764 memory: 16131 loss: 0.8755 loss_prob: 0.4508 loss_thr: 0.3468 loss_db: 0.0778 2022/10/26 08:24:56 - mmengine - INFO - Epoch(train) [1079][15/63] lr: 4.4885e-04 eta: 1:25:40 time: 0.5089 data_time: 0.0073 memory: 16131 loss: 0.8547 loss_prob: 0.4436 loss_thr: 0.3335 loss_db: 0.0776 2022/10/26 08:24:58 - mmengine - INFO - Epoch(train) [1079][20/63] lr: 4.4885e-04 eta: 1:25:33 time: 0.5075 data_time: 0.0063 memory: 16131 loss: 0.9098 loss_prob: 0.4812 loss_thr: 0.3457 loss_db: 0.0829 2022/10/26 08:25:01 - mmengine - INFO - Epoch(train) [1079][25/63] lr: 4.4885e-04 eta: 1:25:33 time: 0.5099 data_time: 0.0132 memory: 16131 loss: 0.9227 loss_prob: 0.4832 loss_thr: 0.3557 loss_db: 0.0838 2022/10/26 08:25:04 - mmengine - INFO - Epoch(train) [1079][30/63] lr: 4.4885e-04 eta: 1:25:26 time: 0.5262 data_time: 0.0333 memory: 16131 loss: 0.9091 loss_prob: 0.4795 loss_thr: 0.3477 loss_db: 0.0818 2022/10/26 08:25:06 - mmengine - INFO - Epoch(train) [1079][35/63] lr: 4.4885e-04 eta: 1:25:26 time: 0.5328 data_time: 0.0288 memory: 16131 loss: 0.9624 loss_prob: 0.5099 loss_thr: 0.3644 loss_db: 0.0881 2022/10/26 08:25:09 - mmengine - INFO - Epoch(train) [1079][40/63] lr: 4.4885e-04 eta: 1:25:19 time: 0.5104 data_time: 0.0082 memory: 16131 loss: 0.9186 loss_prob: 0.4754 loss_thr: 0.3589 loss_db: 0.0843 2022/10/26 08:25:11 - mmengine - INFO - Epoch(train) [1079][45/63] lr: 4.4885e-04 eta: 1:25:19 time: 0.5049 data_time: 0.0096 memory: 16131 loss: 0.9073 loss_prob: 0.4716 loss_thr: 0.3543 loss_db: 0.0814 2022/10/26 08:25:14 - mmengine - INFO - Epoch(train) [1079][50/63] lr: 4.4885e-04 eta: 1:25:12 time: 0.5221 data_time: 0.0246 memory: 16131 loss: 0.8711 loss_prob: 0.4533 loss_thr: 0.3393 loss_db: 0.0786 2022/10/26 08:25:17 - mmengine - INFO - Epoch(train) [1079][55/63] lr: 4.4885e-04 eta: 1:25:12 time: 0.5308 data_time: 0.0284 memory: 16131 loss: 0.8316 loss_prob: 0.4300 loss_thr: 0.3258 loss_db: 0.0758 2022/10/26 08:25:19 - mmengine - INFO - Epoch(train) [1079][60/63] lr: 4.4885e-04 eta: 1:25:06 time: 0.5080 data_time: 0.0140 memory: 16131 loss: 0.9434 loss_prob: 0.5019 loss_thr: 0.3526 loss_db: 0.0888 2022/10/26 08:25:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:25:26 - mmengine - INFO - Epoch(train) [1080][5/63] lr: 4.4551e-04 eta: 1:25:06 time: 0.7962 data_time: 0.2185 memory: 16131 loss: 0.9114 loss_prob: 0.4683 loss_thr: 0.3608 loss_db: 0.0823 2022/10/26 08:25:29 - mmengine - INFO - Epoch(train) [1080][10/63] lr: 4.4551e-04 eta: 1:24:57 time: 0.8795 data_time: 0.2167 memory: 16131 loss: 0.8418 loss_prob: 0.4275 loss_thr: 0.3395 loss_db: 0.0748 2022/10/26 08:25:32 - mmengine - INFO - Epoch(train) [1080][15/63] lr: 4.4551e-04 eta: 1:24:57 time: 0.6410 data_time: 0.0068 memory: 16131 loss: 0.8542 loss_prob: 0.4434 loss_thr: 0.3341 loss_db: 0.0768 2022/10/26 08:25:35 - mmengine - INFO - Epoch(train) [1080][20/63] lr: 4.4551e-04 eta: 1:24:50 time: 0.5613 data_time: 0.0079 memory: 16131 loss: 0.9593 loss_prob: 0.5066 loss_thr: 0.3651 loss_db: 0.0876 2022/10/26 08:25:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:25:38 - mmengine - INFO - Epoch(train) [1080][25/63] lr: 4.4551e-04 eta: 1:24:50 time: 0.5280 data_time: 0.0226 memory: 16131 loss: 0.9288 loss_prob: 0.4896 loss_thr: 0.3541 loss_db: 0.0851 2022/10/26 08:25:40 - mmengine - INFO - Epoch(train) [1080][30/63] lr: 4.4551e-04 eta: 1:24:43 time: 0.5580 data_time: 0.0308 memory: 16131 loss: 0.8485 loss_prob: 0.4383 loss_thr: 0.3338 loss_db: 0.0764 2022/10/26 08:25:43 - mmengine - INFO - Epoch(train) [1080][35/63] lr: 4.4551e-04 eta: 1:24:43 time: 0.5343 data_time: 0.0162 memory: 16131 loss: 0.8279 loss_prob: 0.4193 loss_thr: 0.3356 loss_db: 0.0730 2022/10/26 08:25:46 - mmengine - INFO - Epoch(train) [1080][40/63] lr: 4.4551e-04 eta: 1:24:36 time: 0.5228 data_time: 0.0065 memory: 16131 loss: 0.8424 loss_prob: 0.4320 loss_thr: 0.3365 loss_db: 0.0739 2022/10/26 08:25:48 - mmengine - INFO - Epoch(train) [1080][45/63] lr: 4.4551e-04 eta: 1:24:36 time: 0.5233 data_time: 0.0057 memory: 16131 loss: 0.8531 loss_prob: 0.4379 loss_thr: 0.3394 loss_db: 0.0758 2022/10/26 08:25:51 - mmengine - INFO - Epoch(train) [1080][50/63] lr: 4.4551e-04 eta: 1:24:30 time: 0.5136 data_time: 0.0197 memory: 16131 loss: 0.8363 loss_prob: 0.4322 loss_thr: 0.3268 loss_db: 0.0773 2022/10/26 08:25:53 - mmengine - INFO - Epoch(train) [1080][55/63] lr: 4.4551e-04 eta: 1:24:30 time: 0.5053 data_time: 0.0274 memory: 16131 loss: 0.9145 loss_prob: 0.4820 loss_thr: 0.3481 loss_db: 0.0844 2022/10/26 08:25:56 - mmengine - INFO - Epoch(train) [1080][60/63] lr: 4.4551e-04 eta: 1:24:23 time: 0.5131 data_time: 0.0135 memory: 16131 loss: 0.8751 loss_prob: 0.4582 loss_thr: 0.3383 loss_db: 0.0785 2022/10/26 08:25:57 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:25:57 - mmengine - INFO - Saving checkpoint at 1080 epochs 2022/10/26 08:26:04 - mmengine - INFO - Epoch(val) [1080][5/32] eta: 1:24:23 time: 0.5084 data_time: 0.0660 memory: 16131 2022/10/26 08:26:07 - mmengine - INFO - Epoch(val) [1080][10/32] eta: 0:00:12 time: 0.5783 data_time: 0.1027 memory: 15724 2022/10/26 08:26:09 - mmengine - INFO - Epoch(val) [1080][15/32] eta: 0:00:12 time: 0.5255 data_time: 0.0503 memory: 15724 2022/10/26 08:26:12 - mmengine - INFO - Epoch(val) [1080][20/32] eta: 0:00:06 time: 0.5234 data_time: 0.0513 memory: 15724 2022/10/26 08:26:15 - mmengine - INFO - Epoch(val) [1080][25/32] eta: 0:00:06 time: 0.5425 data_time: 0.0552 memory: 15724 2022/10/26 08:26:17 - mmengine - INFO - Epoch(val) [1080][30/32] eta: 0:00:01 time: 0.5062 data_time: 0.0190 memory: 15724 2022/10/26 08:26:18 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8315, precision: 0.7797, hmean: 0.8048 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8315, precision: 0.8283, hmean: 0.8299 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8310, precision: 0.8553, hmean: 0.8430 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8281, precision: 0.8735, hmean: 0.8502 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8166, precision: 0.8950, hmean: 0.8540 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7496, precision: 0.9229, hmean: 0.8273 2022/10/26 08:26:18 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2133, precision: 0.9779, hmean: 0.3502 2022/10/26 08:26:18 - mmengine - INFO - Epoch(val) [1080][32/32] icdar/precision: 0.8950 icdar/recall: 0.8166 icdar/hmean: 0.8540 2022/10/26 08:26:22 - mmengine - INFO - Epoch(train) [1081][5/63] lr: 4.4217e-04 eta: 0:00:01 time: 0.7191 data_time: 0.2071 memory: 16131 loss: 0.7745 loss_prob: 0.4015 loss_thr: 0.3030 loss_db: 0.0700 2022/10/26 08:26:25 - mmengine - INFO - Epoch(train) [1081][10/63] lr: 4.4217e-04 eta: 1:24:14 time: 0.7152 data_time: 0.2076 memory: 16131 loss: 0.9868 loss_prob: 0.5460 loss_thr: 0.3532 loss_db: 0.0876 2022/10/26 08:26:28 - mmengine - INFO - Epoch(train) [1081][15/63] lr: 4.4217e-04 eta: 1:24:14 time: 0.5122 data_time: 0.0076 memory: 16131 loss: 0.9561 loss_prob: 0.5182 loss_thr: 0.3555 loss_db: 0.0824 2022/10/26 08:26:30 - mmengine - INFO - Epoch(train) [1081][20/63] lr: 4.4217e-04 eta: 1:24:07 time: 0.5315 data_time: 0.0083 memory: 16131 loss: 0.8075 loss_prob: 0.4109 loss_thr: 0.3259 loss_db: 0.0707 2022/10/26 08:26:33 - mmengine - INFO - Epoch(train) [1081][25/63] lr: 4.4217e-04 eta: 1:24:07 time: 0.5323 data_time: 0.0325 memory: 16131 loss: 0.9503 loss_prob: 0.5114 loss_thr: 0.3531 loss_db: 0.0859 2022/10/26 08:26:36 - mmengine - INFO - Epoch(train) [1081][30/63] lr: 4.4217e-04 eta: 1:24:00 time: 0.5344 data_time: 0.0320 memory: 16131 loss: 0.9493 loss_prob: 0.5091 loss_thr: 0.3533 loss_db: 0.0870 2022/10/26 08:26:38 - mmengine - INFO - Epoch(train) [1081][35/63] lr: 4.4217e-04 eta: 1:24:00 time: 0.5344 data_time: 0.0067 memory: 16131 loss: 0.8888 loss_prob: 0.4610 loss_thr: 0.3454 loss_db: 0.0824 2022/10/26 08:26:41 - mmengine - INFO - Epoch(train) [1081][40/63] lr: 4.4217e-04 eta: 1:23:53 time: 0.5639 data_time: 0.0086 memory: 16131 loss: 0.9285 loss_prob: 0.4787 loss_thr: 0.3656 loss_db: 0.0842 2022/10/26 08:26:44 - mmengine - INFO - Epoch(train) [1081][45/63] lr: 4.4217e-04 eta: 1:23:53 time: 0.5416 data_time: 0.0098 memory: 16131 loss: 0.9638 loss_prob: 0.5053 loss_thr: 0.3710 loss_db: 0.0875 2022/10/26 08:26:46 - mmengine - INFO - Epoch(train) [1081][50/63] lr: 4.4217e-04 eta: 1:23:46 time: 0.5159 data_time: 0.0250 memory: 16131 loss: 0.9028 loss_prob: 0.4718 loss_thr: 0.3486 loss_db: 0.0823 2022/10/26 08:26:49 - mmengine - INFO - Epoch(train) [1081][55/63] lr: 4.4217e-04 eta: 1:23:46 time: 0.5210 data_time: 0.0267 memory: 16131 loss: 0.8759 loss_prob: 0.4613 loss_thr: 0.3334 loss_db: 0.0813 2022/10/26 08:26:51 - mmengine - INFO - Epoch(train) [1081][60/63] lr: 4.4217e-04 eta: 1:23:40 time: 0.5068 data_time: 0.0089 memory: 16131 loss: 0.8818 loss_prob: 0.4640 loss_thr: 0.3343 loss_db: 0.0835 2022/10/26 08:26:53 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:26:58 - mmengine - INFO - Epoch(train) [1082][5/63] lr: 4.3882e-04 eta: 1:23:40 time: 0.7075 data_time: 0.1745 memory: 16131 loss: 0.9463 loss_prob: 0.5324 loss_thr: 0.3335 loss_db: 0.0803 2022/10/26 08:27:00 - mmengine - INFO - Epoch(train) [1082][10/63] lr: 4.3882e-04 eta: 1:23:31 time: 0.7516 data_time: 0.1859 memory: 16131 loss: 0.9213 loss_prob: 0.5162 loss_thr: 0.3250 loss_db: 0.0800 2022/10/26 08:27:03 - mmengine - INFO - Epoch(train) [1082][15/63] lr: 4.3882e-04 eta: 1:23:31 time: 0.5095 data_time: 0.0228 memory: 16131 loss: 0.7902 loss_prob: 0.4044 loss_thr: 0.3137 loss_db: 0.0721 2022/10/26 08:27:05 - mmengine - INFO - Epoch(train) [1082][20/63] lr: 4.3882e-04 eta: 1:23:24 time: 0.5288 data_time: 0.0114 memory: 16131 loss: 0.7886 loss_prob: 0.4104 loss_thr: 0.3070 loss_db: 0.0712 2022/10/26 08:27:09 - mmengine - INFO - Epoch(train) [1082][25/63] lr: 4.3882e-04 eta: 1:23:24 time: 0.6148 data_time: 0.0211 memory: 16131 loss: 0.7675 loss_prob: 0.3956 loss_thr: 0.3011 loss_db: 0.0708 2022/10/26 08:27:11 - mmengine - INFO - Epoch(train) [1082][30/63] lr: 4.3882e-04 eta: 1:23:17 time: 0.5932 data_time: 0.0358 memory: 16131 loss: 0.9735 loss_prob: 0.5437 loss_thr: 0.3428 loss_db: 0.0870 2022/10/26 08:27:14 - mmengine - INFO - Epoch(train) [1082][35/63] lr: 4.3882e-04 eta: 1:23:17 time: 0.5564 data_time: 0.0212 memory: 16131 loss: 1.0295 loss_prob: 0.5833 loss_thr: 0.3536 loss_db: 0.0926 2022/10/26 08:27:17 - mmengine - INFO - Epoch(train) [1082][40/63] lr: 4.3882e-04 eta: 1:23:10 time: 0.5368 data_time: 0.0070 memory: 16131 loss: 0.8841 loss_prob: 0.4662 loss_thr: 0.3364 loss_db: 0.0815 2022/10/26 08:27:19 - mmengine - INFO - Epoch(train) [1082][45/63] lr: 4.3882e-04 eta: 1:23:10 time: 0.5168 data_time: 0.0053 memory: 16131 loss: 0.9183 loss_prob: 0.4784 loss_thr: 0.3558 loss_db: 0.0841 2022/10/26 08:27:22 - mmengine - INFO - Epoch(train) [1082][50/63] lr: 4.3882e-04 eta: 1:23:03 time: 0.5666 data_time: 0.0164 memory: 16131 loss: 0.9533 loss_prob: 0.5069 loss_thr: 0.3584 loss_db: 0.0881 2022/10/26 08:27:25 - mmengine - INFO - Epoch(train) [1082][55/63] lr: 4.3882e-04 eta: 1:23:03 time: 0.5438 data_time: 0.0207 memory: 16131 loss: 0.9561 loss_prob: 0.5108 loss_thr: 0.3568 loss_db: 0.0885 2022/10/26 08:27:27 - mmengine - INFO - Epoch(train) [1082][60/63] lr: 4.3882e-04 eta: 1:22:57 time: 0.4965 data_time: 0.0090 memory: 16131 loss: 0.9211 loss_prob: 0.4864 loss_thr: 0.3502 loss_db: 0.0845 2022/10/26 08:27:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:27:33 - mmengine - INFO - Epoch(train) [1083][5/63] lr: 4.3548e-04 eta: 1:22:57 time: 0.6647 data_time: 0.2070 memory: 16131 loss: 0.8401 loss_prob: 0.4383 loss_thr: 0.3257 loss_db: 0.0761 2022/10/26 08:27:36 - mmengine - INFO - Epoch(train) [1083][10/63] lr: 4.3548e-04 eta: 1:22:48 time: 0.7153 data_time: 0.2072 memory: 16131 loss: 0.8737 loss_prob: 0.4569 loss_thr: 0.3396 loss_db: 0.0772 2022/10/26 08:27:39 - mmengine - INFO - Epoch(train) [1083][15/63] lr: 4.3548e-04 eta: 1:22:48 time: 0.5551 data_time: 0.0101 memory: 16131 loss: 0.8782 loss_prob: 0.4553 loss_thr: 0.3454 loss_db: 0.0776 2022/10/26 08:27:41 - mmengine - INFO - Epoch(train) [1083][20/63] lr: 4.3548e-04 eta: 1:22:41 time: 0.5427 data_time: 0.0149 memory: 16131 loss: 0.8306 loss_prob: 0.4296 loss_thr: 0.3262 loss_db: 0.0748 2022/10/26 08:27:44 - mmengine - INFO - Epoch(train) [1083][25/63] lr: 4.3548e-04 eta: 1:22:41 time: 0.5285 data_time: 0.0299 memory: 16131 loss: 0.7964 loss_prob: 0.4101 loss_thr: 0.3142 loss_db: 0.0720 2022/10/26 08:27:47 - mmengine - INFO - Epoch(train) [1083][30/63] lr: 4.3548e-04 eta: 1:22:34 time: 0.5983 data_time: 0.0278 memory: 16131 loss: 0.8218 loss_prob: 0.4245 loss_thr: 0.3241 loss_db: 0.0732 2022/10/26 08:27:50 - mmengine - INFO - Epoch(train) [1083][35/63] lr: 4.3548e-04 eta: 1:22:34 time: 0.5645 data_time: 0.0117 memory: 16131 loss: 0.8271 loss_prob: 0.4252 loss_thr: 0.3291 loss_db: 0.0728 2022/10/26 08:27:52 - mmengine - INFO - Epoch(train) [1083][40/63] lr: 4.3548e-04 eta: 1:22:27 time: 0.5205 data_time: 0.0134 memory: 16131 loss: 0.8294 loss_prob: 0.4215 loss_thr: 0.3346 loss_db: 0.0733 2022/10/26 08:27:55 - mmengine - INFO - Epoch(train) [1083][45/63] lr: 4.3548e-04 eta: 1:22:27 time: 0.5617 data_time: 0.0113 memory: 16131 loss: 0.8692 loss_prob: 0.4460 loss_thr: 0.3439 loss_db: 0.0794 2022/10/26 08:27:58 - mmengine - INFO - Epoch(train) [1083][50/63] lr: 4.3548e-04 eta: 1:22:20 time: 0.5727 data_time: 0.0201 memory: 16131 loss: 0.9493 loss_prob: 0.4948 loss_thr: 0.3654 loss_db: 0.0891 2022/10/26 08:28:01 - mmengine - INFO - Epoch(train) [1083][55/63] lr: 4.3548e-04 eta: 1:22:20 time: 0.5673 data_time: 0.0200 memory: 16131 loss: 1.0062 loss_prob: 0.5365 loss_thr: 0.3801 loss_db: 0.0895 2022/10/26 08:28:04 - mmengine - INFO - Epoch(train) [1083][60/63] lr: 4.3548e-04 eta: 1:22:14 time: 0.5621 data_time: 0.0108 memory: 16131 loss: 0.9654 loss_prob: 0.5177 loss_thr: 0.3646 loss_db: 0.0831 2022/10/26 08:28:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:28:10 - mmengine - INFO - Epoch(train) [1084][5/63] lr: 4.3213e-04 eta: 1:22:14 time: 0.7350 data_time: 0.1882 memory: 16131 loss: 0.9393 loss_prob: 0.4985 loss_thr: 0.3562 loss_db: 0.0846 2022/10/26 08:28:13 - mmengine - INFO - Epoch(train) [1084][10/63] lr: 4.3213e-04 eta: 1:22:05 time: 0.7488 data_time: 0.1935 memory: 16131 loss: 0.9404 loss_prob: 0.4984 loss_thr: 0.3565 loss_db: 0.0855 2022/10/26 08:28:15 - mmengine - INFO - Epoch(train) [1084][15/63] lr: 4.3213e-04 eta: 1:22:05 time: 0.5188 data_time: 0.0159 memory: 16131 loss: 0.9285 loss_prob: 0.4872 loss_thr: 0.3577 loss_db: 0.0836 2022/10/26 08:28:18 - mmengine - INFO - Epoch(train) [1084][20/63] lr: 4.3213e-04 eta: 1:21:58 time: 0.5114 data_time: 0.0115 memory: 16131 loss: 0.9418 loss_prob: 0.4906 loss_thr: 0.3664 loss_db: 0.0848 2022/10/26 08:28:20 - mmengine - INFO - Epoch(train) [1084][25/63] lr: 4.3213e-04 eta: 1:21:58 time: 0.5307 data_time: 0.0264 memory: 16131 loss: 0.9548 loss_prob: 0.4933 loss_thr: 0.3749 loss_db: 0.0866 2022/10/26 08:28:23 - mmengine - INFO - Epoch(train) [1084][30/63] lr: 4.3213e-04 eta: 1:21:51 time: 0.5302 data_time: 0.0353 memory: 16131 loss: 0.8917 loss_prob: 0.4572 loss_thr: 0.3541 loss_db: 0.0805 2022/10/26 08:28:26 - mmengine - INFO - Epoch(train) [1084][35/63] lr: 4.3213e-04 eta: 1:21:51 time: 0.5242 data_time: 0.0172 memory: 16131 loss: 0.8921 loss_prob: 0.4628 loss_thr: 0.3476 loss_db: 0.0817 2022/10/26 08:28:29 - mmengine - INFO - Epoch(train) [1084][40/63] lr: 4.3213e-04 eta: 1:21:44 time: 0.5584 data_time: 0.0081 memory: 16131 loss: 0.9334 loss_prob: 0.4894 loss_thr: 0.3583 loss_db: 0.0857 2022/10/26 08:28:32 - mmengine - INFO - Epoch(train) [1084][45/63] lr: 4.3213e-04 eta: 1:21:44 time: 0.5891 data_time: 0.0087 memory: 16131 loss: 0.9415 loss_prob: 0.5055 loss_thr: 0.3494 loss_db: 0.0866 2022/10/26 08:28:34 - mmengine - INFO - Epoch(train) [1084][50/63] lr: 4.3213e-04 eta: 1:21:37 time: 0.5476 data_time: 0.0188 memory: 16131 loss: 0.8823 loss_prob: 0.4645 loss_thr: 0.3374 loss_db: 0.0803 2022/10/26 08:28:37 - mmengine - INFO - Epoch(train) [1084][55/63] lr: 4.3213e-04 eta: 1:21:37 time: 0.5116 data_time: 0.0229 memory: 16131 loss: 0.8715 loss_prob: 0.4539 loss_thr: 0.3380 loss_db: 0.0797 2022/10/26 08:28:39 - mmengine - INFO - Epoch(train) [1084][60/63] lr: 4.3213e-04 eta: 1:21:31 time: 0.5195 data_time: 0.0123 memory: 16131 loss: 0.8759 loss_prob: 0.4627 loss_thr: 0.3329 loss_db: 0.0803 2022/10/26 08:28:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:28:46 - mmengine - INFO - Epoch(train) [1085][5/63] lr: 4.2877e-04 eta: 1:21:31 time: 0.7355 data_time: 0.1816 memory: 16131 loss: 0.8669 loss_prob: 0.4603 loss_thr: 0.3276 loss_db: 0.0790 2022/10/26 08:28:48 - mmengine - INFO - Epoch(train) [1085][10/63] lr: 4.2877e-04 eta: 1:21:22 time: 0.7533 data_time: 0.1786 memory: 16131 loss: 0.8705 loss_prob: 0.4550 loss_thr: 0.3374 loss_db: 0.0781 2022/10/26 08:28:51 - mmengine - INFO - Epoch(train) [1085][15/63] lr: 4.2877e-04 eta: 1:21:22 time: 0.5073 data_time: 0.0054 memory: 16131 loss: 0.8136 loss_prob: 0.4156 loss_thr: 0.3249 loss_db: 0.0731 2022/10/26 08:28:53 - mmengine - INFO - Epoch(train) [1085][20/63] lr: 4.2877e-04 eta: 1:21:15 time: 0.5133 data_time: 0.0069 memory: 16131 loss: 0.8870 loss_prob: 0.4571 loss_thr: 0.3488 loss_db: 0.0811 2022/10/26 08:28:56 - mmengine - INFO - Epoch(train) [1085][25/63] lr: 4.2877e-04 eta: 1:21:15 time: 0.5262 data_time: 0.0139 memory: 16131 loss: 0.9697 loss_prob: 0.5092 loss_thr: 0.3717 loss_db: 0.0888 2022/10/26 08:28:58 - mmengine - INFO - Epoch(train) [1085][30/63] lr: 4.2877e-04 eta: 1:21:08 time: 0.5185 data_time: 0.0328 memory: 16131 loss: 0.9423 loss_prob: 0.4892 loss_thr: 0.3687 loss_db: 0.0844 2022/10/26 08:29:01 - mmengine - INFO - Epoch(train) [1085][35/63] lr: 4.2877e-04 eta: 1:21:08 time: 0.5293 data_time: 0.0258 memory: 16131 loss: 0.9135 loss_prob: 0.4585 loss_thr: 0.3744 loss_db: 0.0806 2022/10/26 08:29:04 - mmengine - INFO - Epoch(train) [1085][40/63] lr: 4.2877e-04 eta: 1:21:01 time: 0.5123 data_time: 0.0053 memory: 16131 loss: 0.8866 loss_prob: 0.4472 loss_thr: 0.3602 loss_db: 0.0792 2022/10/26 08:29:06 - mmengine - INFO - Epoch(train) [1085][45/63] lr: 4.2877e-04 eta: 1:21:01 time: 0.4966 data_time: 0.0058 memory: 16131 loss: 0.8441 loss_prob: 0.4407 loss_thr: 0.3264 loss_db: 0.0770 2022/10/26 08:29:09 - mmengine - INFO - Epoch(train) [1085][50/63] lr: 4.2877e-04 eta: 1:20:54 time: 0.5333 data_time: 0.0185 memory: 16131 loss: 0.7752 loss_prob: 0.4039 loss_thr: 0.3015 loss_db: 0.0698 2022/10/26 08:29:12 - mmengine - INFO - Epoch(train) [1085][55/63] lr: 4.2877e-04 eta: 1:20:54 time: 0.5499 data_time: 0.0273 memory: 16131 loss: 0.7778 loss_prob: 0.3980 loss_thr: 0.3106 loss_db: 0.0692 2022/10/26 08:29:15 - mmengine - INFO - Epoch(train) [1085][60/63] lr: 4.2877e-04 eta: 1:20:48 time: 0.5625 data_time: 0.0144 memory: 16131 loss: 0.8710 loss_prob: 0.4535 loss_thr: 0.3388 loss_db: 0.0787 2022/10/26 08:29:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:29:20 - mmengine - INFO - Epoch(train) [1086][5/63] lr: 4.2542e-04 eta: 1:20:48 time: 0.7010 data_time: 0.1838 memory: 16131 loss: 0.9527 loss_prob: 0.5039 loss_thr: 0.3586 loss_db: 0.0901 2022/10/26 08:29:23 - mmengine - INFO - Epoch(train) [1086][10/63] lr: 4.2542e-04 eta: 1:20:39 time: 0.7116 data_time: 0.1859 memory: 16131 loss: 0.8396 loss_prob: 0.4226 loss_thr: 0.3436 loss_db: 0.0734 2022/10/26 08:29:25 - mmengine - INFO - Epoch(train) [1086][15/63] lr: 4.2542e-04 eta: 1:20:39 time: 0.4934 data_time: 0.0078 memory: 16131 loss: 0.8877 loss_prob: 0.4640 loss_thr: 0.3430 loss_db: 0.0807 2022/10/26 08:29:28 - mmengine - INFO - Epoch(train) [1086][20/63] lr: 4.2542e-04 eta: 1:20:32 time: 0.4940 data_time: 0.0098 memory: 16131 loss: 0.8491 loss_prob: 0.4418 loss_thr: 0.3307 loss_db: 0.0766 2022/10/26 08:29:31 - mmengine - INFO - Epoch(train) [1086][25/63] lr: 4.2542e-04 eta: 1:20:32 time: 0.5168 data_time: 0.0217 memory: 16131 loss: 0.8485 loss_prob: 0.4414 loss_thr: 0.3317 loss_db: 0.0753 2022/10/26 08:29:33 - mmengine - INFO - Epoch(train) [1086][30/63] lr: 4.2542e-04 eta: 1:20:25 time: 0.5281 data_time: 0.0293 memory: 16131 loss: 0.8684 loss_prob: 0.4555 loss_thr: 0.3331 loss_db: 0.0798 2022/10/26 08:29:36 - mmengine - INFO - Epoch(train) [1086][35/63] lr: 4.2542e-04 eta: 1:20:25 time: 0.5302 data_time: 0.0164 memory: 16131 loss: 0.8470 loss_prob: 0.4415 loss_thr: 0.3273 loss_db: 0.0782 2022/10/26 08:29:39 - mmengine - INFO - Epoch(train) [1086][40/63] lr: 4.2542e-04 eta: 1:20:18 time: 0.5671 data_time: 0.0046 memory: 16131 loss: 0.8515 loss_prob: 0.4325 loss_thr: 0.3436 loss_db: 0.0754 2022/10/26 08:29:42 - mmengine - INFO - Epoch(train) [1086][45/63] lr: 4.2542e-04 eta: 1:20:18 time: 0.5863 data_time: 0.0075 memory: 16131 loss: 0.8637 loss_prob: 0.4434 loss_thr: 0.3432 loss_db: 0.0770 2022/10/26 08:29:45 - mmengine - INFO - Epoch(train) [1086][50/63] lr: 4.2542e-04 eta: 1:20:11 time: 0.6045 data_time: 0.0217 memory: 16131 loss: 0.9386 loss_prob: 0.4922 loss_thr: 0.3601 loss_db: 0.0863 2022/10/26 08:29:47 - mmengine - INFO - Epoch(train) [1086][55/63] lr: 4.2542e-04 eta: 1:20:11 time: 0.5757 data_time: 0.0266 memory: 16131 loss: 0.9420 loss_prob: 0.4874 loss_thr: 0.3674 loss_db: 0.0872 2022/10/26 08:29:50 - mmengine - INFO - Epoch(train) [1086][60/63] lr: 4.2542e-04 eta: 1:20:05 time: 0.5083 data_time: 0.0125 memory: 16131 loss: 0.9016 loss_prob: 0.4690 loss_thr: 0.3501 loss_db: 0.0826 2022/10/26 08:29:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:29:56 - mmengine - INFO - Epoch(train) [1087][5/63] lr: 4.2206e-04 eta: 1:20:05 time: 0.6658 data_time: 0.1778 memory: 16131 loss: 0.9741 loss_prob: 0.5217 loss_thr: 0.3614 loss_db: 0.0910 2022/10/26 08:29:58 - mmengine - INFO - Epoch(train) [1087][10/63] lr: 4.2206e-04 eta: 1:19:56 time: 0.6940 data_time: 0.1778 memory: 16131 loss: 0.8868 loss_prob: 0.4659 loss_thr: 0.3406 loss_db: 0.0803 2022/10/26 08:30:01 - mmengine - INFO - Epoch(train) [1087][15/63] lr: 4.2206e-04 eta: 1:19:56 time: 0.5036 data_time: 0.0047 memory: 16131 loss: 0.9889 loss_prob: 0.5224 loss_thr: 0.3776 loss_db: 0.0889 2022/10/26 08:30:03 - mmengine - INFO - Epoch(train) [1087][20/63] lr: 4.2206e-04 eta: 1:19:49 time: 0.4989 data_time: 0.0055 memory: 16131 loss: 1.0027 loss_prob: 0.5241 loss_thr: 0.3878 loss_db: 0.0907 2022/10/26 08:30:06 - mmengine - INFO - Epoch(train) [1087][25/63] lr: 4.2206e-04 eta: 1:19:49 time: 0.5514 data_time: 0.0216 memory: 16131 loss: 0.9498 loss_prob: 0.4938 loss_thr: 0.3692 loss_db: 0.0868 2022/10/26 08:30:09 - mmengine - INFO - Epoch(train) [1087][30/63] lr: 4.2206e-04 eta: 1:19:42 time: 0.5526 data_time: 0.0325 memory: 16131 loss: 0.8891 loss_prob: 0.4543 loss_thr: 0.3548 loss_db: 0.0800 2022/10/26 08:30:11 - mmengine - INFO - Epoch(train) [1087][35/63] lr: 4.2206e-04 eta: 1:19:42 time: 0.5291 data_time: 0.0179 memory: 16131 loss: 0.8277 loss_prob: 0.4139 loss_thr: 0.3397 loss_db: 0.0741 2022/10/26 08:30:14 - mmengine - INFO - Epoch(train) [1087][40/63] lr: 4.2206e-04 eta: 1:19:35 time: 0.5239 data_time: 0.0083 memory: 16131 loss: 0.8768 loss_prob: 0.4494 loss_thr: 0.3472 loss_db: 0.0802 2022/10/26 08:30:17 - mmengine - INFO - Epoch(train) [1087][45/63] lr: 4.2206e-04 eta: 1:19:35 time: 0.5165 data_time: 0.0071 memory: 16131 loss: 0.8857 loss_prob: 0.4578 loss_thr: 0.3461 loss_db: 0.0818 2022/10/26 08:30:19 - mmengine - INFO - Epoch(train) [1087][50/63] lr: 4.2206e-04 eta: 1:19:28 time: 0.5464 data_time: 0.0162 memory: 16131 loss: 0.9191 loss_prob: 0.4816 loss_thr: 0.3530 loss_db: 0.0846 2022/10/26 08:30:23 - mmengine - INFO - Epoch(train) [1087][55/63] lr: 4.2206e-04 eta: 1:19:28 time: 0.5978 data_time: 0.0240 memory: 16131 loss: 0.9291 loss_prob: 0.4912 loss_thr: 0.3525 loss_db: 0.0855 2022/10/26 08:30:25 - mmengine - INFO - Epoch(train) [1087][60/63] lr: 4.2206e-04 eta: 1:19:22 time: 0.5938 data_time: 0.0130 memory: 16131 loss: 0.9725 loss_prob: 0.5122 loss_thr: 0.3740 loss_db: 0.0863 2022/10/26 08:30:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:30:33 - mmengine - INFO - Epoch(train) [1088][5/63] lr: 4.1870e-04 eta: 1:19:22 time: 0.8510 data_time: 0.1964 memory: 16131 loss: 0.8963 loss_prob: 0.4623 loss_thr: 0.3522 loss_db: 0.0818 2022/10/26 08:30:36 - mmengine - INFO - Epoch(train) [1088][10/63] lr: 4.1870e-04 eta: 1:19:13 time: 0.8637 data_time: 0.1952 memory: 16131 loss: 0.9217 loss_prob: 0.4767 loss_thr: 0.3618 loss_db: 0.0833 2022/10/26 08:30:38 - mmengine - INFO - Epoch(train) [1088][15/63] lr: 4.1870e-04 eta: 1:19:13 time: 0.5447 data_time: 0.0072 memory: 16131 loss: 0.9419 loss_prob: 0.4887 loss_thr: 0.3674 loss_db: 0.0858 2022/10/26 08:30:41 - mmengine - INFO - Epoch(train) [1088][20/63] lr: 4.1870e-04 eta: 1:19:06 time: 0.5245 data_time: 0.0119 memory: 16131 loss: 0.9446 loss_prob: 0.4922 loss_thr: 0.3656 loss_db: 0.0868 2022/10/26 08:30:43 - mmengine - INFO - Epoch(train) [1088][25/63] lr: 4.1870e-04 eta: 1:19:06 time: 0.5148 data_time: 0.0197 memory: 16131 loss: 0.8730 loss_prob: 0.4504 loss_thr: 0.3440 loss_db: 0.0786 2022/10/26 08:30:46 - mmengine - INFO - Epoch(train) [1088][30/63] lr: 4.1870e-04 eta: 1:18:59 time: 0.5133 data_time: 0.0330 memory: 16131 loss: 0.8489 loss_prob: 0.4348 loss_thr: 0.3379 loss_db: 0.0762 2022/10/26 08:30:48 - mmengine - INFO - Epoch(train) [1088][35/63] lr: 4.1870e-04 eta: 1:18:59 time: 0.5118 data_time: 0.0247 memory: 16131 loss: 0.8172 loss_prob: 0.4171 loss_thr: 0.3269 loss_db: 0.0733 2022/10/26 08:30:51 - mmengine - INFO - Epoch(train) [1088][40/63] lr: 4.1870e-04 eta: 1:18:52 time: 0.5083 data_time: 0.0076 memory: 16131 loss: 0.9057 loss_prob: 0.4749 loss_thr: 0.3483 loss_db: 0.0825 2022/10/26 08:30:54 - mmengine - INFO - Epoch(train) [1088][45/63] lr: 4.1870e-04 eta: 1:18:52 time: 0.5173 data_time: 0.0101 memory: 16131 loss: 0.9397 loss_prob: 0.4966 loss_thr: 0.3559 loss_db: 0.0873 2022/10/26 08:30:56 - mmengine - INFO - Epoch(train) [1088][50/63] lr: 4.1870e-04 eta: 1:18:46 time: 0.5043 data_time: 0.0164 memory: 16131 loss: 0.8717 loss_prob: 0.4467 loss_thr: 0.3464 loss_db: 0.0786 2022/10/26 08:31:00 - mmengine - INFO - Epoch(train) [1088][55/63] lr: 4.1870e-04 eta: 1:18:46 time: 0.6309 data_time: 0.0255 memory: 16131 loss: 0.8443 loss_prob: 0.4291 loss_thr: 0.3403 loss_db: 0.0749 2022/10/26 08:31:02 - mmengine - INFO - Epoch(train) [1088][60/63] lr: 4.1870e-04 eta: 1:18:39 time: 0.6364 data_time: 0.0199 memory: 16131 loss: 0.8030 loss_prob: 0.4156 loss_thr: 0.3140 loss_db: 0.0734 2022/10/26 08:31:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:31:08 - mmengine - INFO - Epoch(train) [1089][5/63] lr: 4.1533e-04 eta: 1:18:39 time: 0.7057 data_time: 0.1628 memory: 16131 loss: 0.8425 loss_prob: 0.4352 loss_thr: 0.3290 loss_db: 0.0782 2022/10/26 08:31:11 - mmengine - INFO - Epoch(train) [1089][10/63] lr: 4.1533e-04 eta: 1:18:30 time: 0.7147 data_time: 0.1625 memory: 16131 loss: 0.8522 loss_prob: 0.4480 loss_thr: 0.3248 loss_db: 0.0793 2022/10/26 08:31:14 - mmengine - INFO - Epoch(train) [1089][15/63] lr: 4.1533e-04 eta: 1:18:30 time: 0.5136 data_time: 0.0084 memory: 16131 loss: 0.8712 loss_prob: 0.4506 loss_thr: 0.3428 loss_db: 0.0778 2022/10/26 08:31:16 - mmengine - INFO - Epoch(train) [1089][20/63] lr: 4.1533e-04 eta: 1:18:23 time: 0.5122 data_time: 0.0067 memory: 16131 loss: 0.9050 loss_prob: 0.4575 loss_thr: 0.3683 loss_db: 0.0792 2022/10/26 08:31:19 - mmengine - INFO - Epoch(train) [1089][25/63] lr: 4.1533e-04 eta: 1:18:23 time: 0.5171 data_time: 0.0127 memory: 16131 loss: 0.8889 loss_prob: 0.4490 loss_thr: 0.3607 loss_db: 0.0792 2022/10/26 08:31:21 - mmengine - INFO - Epoch(train) [1089][30/63] lr: 4.1533e-04 eta: 1:18:16 time: 0.5211 data_time: 0.0324 memory: 16131 loss: 0.8402 loss_prob: 0.4340 loss_thr: 0.3284 loss_db: 0.0779 2022/10/26 08:31:24 - mmengine - INFO - Epoch(train) [1089][35/63] lr: 4.1533e-04 eta: 1:18:16 time: 0.5113 data_time: 0.0277 memory: 16131 loss: 0.8499 loss_prob: 0.4463 loss_thr: 0.3242 loss_db: 0.0794 2022/10/26 08:31:27 - mmengine - INFO - Epoch(train) [1089][40/63] lr: 4.1533e-04 eta: 1:18:09 time: 0.5256 data_time: 0.0090 memory: 16131 loss: 0.8591 loss_prob: 0.4480 loss_thr: 0.3317 loss_db: 0.0795 2022/10/26 08:31:29 - mmengine - INFO - Epoch(train) [1089][45/63] lr: 4.1533e-04 eta: 1:18:09 time: 0.5262 data_time: 0.0068 memory: 16131 loss: 0.8301 loss_prob: 0.4303 loss_thr: 0.3244 loss_db: 0.0755 2022/10/26 08:31:32 - mmengine - INFO - Epoch(train) [1089][50/63] lr: 4.1533e-04 eta: 1:18:03 time: 0.5138 data_time: 0.0143 memory: 16131 loss: 0.8557 loss_prob: 0.4434 loss_thr: 0.3350 loss_db: 0.0773 2022/10/26 08:31:35 - mmengine - INFO - Epoch(train) [1089][55/63] lr: 4.1533e-04 eta: 1:18:03 time: 0.5470 data_time: 0.0194 memory: 16131 loss: 0.8852 loss_prob: 0.4610 loss_thr: 0.3432 loss_db: 0.0810 2022/10/26 08:31:37 - mmengine - INFO - Epoch(train) [1089][60/63] lr: 4.1533e-04 eta: 1:17:56 time: 0.5475 data_time: 0.0130 memory: 16131 loss: 0.8110 loss_prob: 0.4166 loss_thr: 0.3206 loss_db: 0.0739 2022/10/26 08:31:39 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:31:43 - mmengine - INFO - Epoch(train) [1090][5/63] lr: 4.1196e-04 eta: 1:17:56 time: 0.7282 data_time: 0.1863 memory: 16131 loss: 0.8814 loss_prob: 0.4611 loss_thr: 0.3404 loss_db: 0.0799 2022/10/26 08:31:46 - mmengine - INFO - Epoch(train) [1090][10/63] lr: 4.1196e-04 eta: 1:17:47 time: 0.7578 data_time: 0.1851 memory: 16131 loss: 0.8042 loss_prob: 0.4160 loss_thr: 0.3171 loss_db: 0.0710 2022/10/26 08:31:49 - mmengine - INFO - Epoch(train) [1090][15/63] lr: 4.1196e-04 eta: 1:17:47 time: 0.5110 data_time: 0.0082 memory: 16131 loss: 0.8258 loss_prob: 0.4294 loss_thr: 0.3225 loss_db: 0.0740 2022/10/26 08:31:52 - mmengine - INFO - Epoch(train) [1090][20/63] lr: 4.1196e-04 eta: 1:17:40 time: 0.5436 data_time: 0.0177 memory: 16131 loss: 0.8912 loss_prob: 0.4658 loss_thr: 0.3440 loss_db: 0.0813 2022/10/26 08:31:54 - mmengine - INFO - Epoch(train) [1090][25/63] lr: 4.1196e-04 eta: 1:17:40 time: 0.5780 data_time: 0.0388 memory: 16131 loss: 0.9249 loss_prob: 0.4887 loss_thr: 0.3508 loss_db: 0.0855 2022/10/26 08:31:57 - mmengine - INFO - Epoch(train) [1090][30/63] lr: 4.1196e-04 eta: 1:17:33 time: 0.5496 data_time: 0.0306 memory: 16131 loss: 0.9514 loss_prob: 0.5065 loss_thr: 0.3556 loss_db: 0.0893 2022/10/26 08:31:59 - mmengine - INFO - Epoch(train) [1090][35/63] lr: 4.1196e-04 eta: 1:17:33 time: 0.5106 data_time: 0.0069 memory: 16131 loss: 0.9157 loss_prob: 0.4828 loss_thr: 0.3470 loss_db: 0.0860 2022/10/26 08:32:02 - mmengine - INFO - Epoch(train) [1090][40/63] lr: 4.1196e-04 eta: 1:17:27 time: 0.5079 data_time: 0.0063 memory: 16131 loss: 0.8866 loss_prob: 0.4628 loss_thr: 0.3422 loss_db: 0.0816 2022/10/26 08:32:05 - mmengine - INFO - Epoch(train) [1090][45/63] lr: 4.1196e-04 eta: 1:17:27 time: 0.5268 data_time: 0.0101 memory: 16131 loss: 0.9118 loss_prob: 0.4805 loss_thr: 0.3465 loss_db: 0.0848 2022/10/26 08:32:08 - mmengine - INFO - Epoch(train) [1090][50/63] lr: 4.1196e-04 eta: 1:17:20 time: 0.5943 data_time: 0.0246 memory: 16131 loss: 0.9134 loss_prob: 0.4758 loss_thr: 0.3544 loss_db: 0.0832 2022/10/26 08:32:11 - mmengine - INFO - Epoch(train) [1090][55/63] lr: 4.1196e-04 eta: 1:17:20 time: 0.6498 data_time: 0.0204 memory: 16131 loss: 0.8786 loss_prob: 0.4456 loss_thr: 0.3568 loss_db: 0.0762 2022/10/26 08:32:14 - mmengine - INFO - Epoch(train) [1090][60/63] lr: 4.1196e-04 eta: 1:17:13 time: 0.5757 data_time: 0.0059 memory: 16131 loss: 0.8561 loss_prob: 0.4468 loss_thr: 0.3334 loss_db: 0.0759 2022/10/26 08:32:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:32:20 - mmengine - INFO - Epoch(train) [1091][5/63] lr: 4.0859e-04 eta: 1:17:13 time: 0.7396 data_time: 0.1799 memory: 16131 loss: 0.7798 loss_prob: 0.3986 loss_thr: 0.3091 loss_db: 0.0721 2022/10/26 08:32:23 - mmengine - INFO - Epoch(train) [1091][10/63] lr: 4.0859e-04 eta: 1:17:04 time: 0.7595 data_time: 0.1794 memory: 16131 loss: 0.8274 loss_prob: 0.4223 loss_thr: 0.3298 loss_db: 0.0753 2022/10/26 08:32:26 - mmengine - INFO - Epoch(train) [1091][15/63] lr: 4.0859e-04 eta: 1:17:04 time: 0.5496 data_time: 0.0117 memory: 16131 loss: 0.8231 loss_prob: 0.4198 loss_thr: 0.3297 loss_db: 0.0736 2022/10/26 08:32:28 - mmengine - INFO - Epoch(train) [1091][20/63] lr: 4.0859e-04 eta: 1:16:57 time: 0.5041 data_time: 0.0120 memory: 16131 loss: 0.8292 loss_prob: 0.4308 loss_thr: 0.3239 loss_db: 0.0745 2022/10/26 08:32:31 - mmengine - INFO - Epoch(train) [1091][25/63] lr: 4.0859e-04 eta: 1:16:57 time: 0.5172 data_time: 0.0115 memory: 16131 loss: 0.8354 loss_prob: 0.4303 loss_thr: 0.3312 loss_db: 0.0738 2022/10/26 08:32:34 - mmengine - INFO - Epoch(train) [1091][30/63] lr: 4.0859e-04 eta: 1:16:51 time: 0.5532 data_time: 0.0328 memory: 16131 loss: 0.8177 loss_prob: 0.4156 loss_thr: 0.3299 loss_db: 0.0722 2022/10/26 08:32:36 - mmengine - INFO - Epoch(train) [1091][35/63] lr: 4.0859e-04 eta: 1:16:51 time: 0.5241 data_time: 0.0266 memory: 16131 loss: 0.8034 loss_prob: 0.4144 loss_thr: 0.3167 loss_db: 0.0723 2022/10/26 08:32:39 - mmengine - INFO - Epoch(train) [1091][40/63] lr: 4.0859e-04 eta: 1:16:44 time: 0.4877 data_time: 0.0057 memory: 16131 loss: 0.8242 loss_prob: 0.4333 loss_thr: 0.3169 loss_db: 0.0741 2022/10/26 08:32:41 - mmengine - INFO - Epoch(train) [1091][45/63] lr: 4.0859e-04 eta: 1:16:44 time: 0.5247 data_time: 0.0064 memory: 16131 loss: 0.8946 loss_prob: 0.4751 loss_thr: 0.3379 loss_db: 0.0816 2022/10/26 08:32:44 - mmengine - INFO - Epoch(train) [1091][50/63] lr: 4.0859e-04 eta: 1:16:37 time: 0.5366 data_time: 0.0202 memory: 16131 loss: 0.9321 loss_prob: 0.4899 loss_thr: 0.3559 loss_db: 0.0863 2022/10/26 08:32:47 - mmengine - INFO - Epoch(train) [1091][55/63] lr: 4.0859e-04 eta: 1:16:37 time: 0.5258 data_time: 0.0317 memory: 16131 loss: 0.9142 loss_prob: 0.4779 loss_thr: 0.3531 loss_db: 0.0832 2022/10/26 08:32:49 - mmengine - INFO - Epoch(train) [1091][60/63] lr: 4.0859e-04 eta: 1:16:30 time: 0.5086 data_time: 0.0182 memory: 16131 loss: 0.9195 loss_prob: 0.4828 loss_thr: 0.3554 loss_db: 0.0813 2022/10/26 08:32:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:32:56 - mmengine - INFO - Epoch(train) [1092][5/63] lr: 4.0522e-04 eta: 1:16:30 time: 0.7713 data_time: 0.1987 memory: 16131 loss: 0.8515 loss_prob: 0.4445 loss_thr: 0.3284 loss_db: 0.0786 2022/10/26 08:32:58 - mmengine - INFO - Epoch(train) [1092][10/63] lr: 4.0522e-04 eta: 1:16:21 time: 0.7866 data_time: 0.1943 memory: 16131 loss: 0.7823 loss_prob: 0.3944 loss_thr: 0.3167 loss_db: 0.0711 2022/10/26 08:33:01 - mmengine - INFO - Epoch(train) [1092][15/63] lr: 4.0522e-04 eta: 1:16:21 time: 0.5043 data_time: 0.0056 memory: 16131 loss: 0.8238 loss_prob: 0.4195 loss_thr: 0.3301 loss_db: 0.0742 2022/10/26 08:33:04 - mmengine - INFO - Epoch(train) [1092][20/63] lr: 4.0522e-04 eta: 1:16:15 time: 0.5577 data_time: 0.0079 memory: 16131 loss: 0.9075 loss_prob: 0.4697 loss_thr: 0.3565 loss_db: 0.0813 2022/10/26 08:33:07 - mmengine - INFO - Epoch(train) [1092][25/63] lr: 4.0522e-04 eta: 1:16:15 time: 0.5912 data_time: 0.0288 memory: 16131 loss: 0.8462 loss_prob: 0.4362 loss_thr: 0.3352 loss_db: 0.0749 2022/10/26 08:33:09 - mmengine - INFO - Epoch(train) [1092][30/63] lr: 4.0522e-04 eta: 1:16:08 time: 0.5606 data_time: 0.0341 memory: 16131 loss: 0.8048 loss_prob: 0.4172 loss_thr: 0.3142 loss_db: 0.0734 2022/10/26 08:33:12 - mmengine - INFO - Epoch(train) [1092][35/63] lr: 4.0522e-04 eta: 1:16:08 time: 0.5140 data_time: 0.0128 memory: 16131 loss: 0.8594 loss_prob: 0.4567 loss_thr: 0.3261 loss_db: 0.0766 2022/10/26 08:33:14 - mmengine - INFO - Epoch(train) [1092][40/63] lr: 4.0522e-04 eta: 1:16:01 time: 0.4896 data_time: 0.0059 memory: 16131 loss: 0.8652 loss_prob: 0.4599 loss_thr: 0.3291 loss_db: 0.0761 2022/10/26 08:33:17 - mmengine - INFO - Epoch(train) [1092][45/63] lr: 4.0522e-04 eta: 1:16:01 time: 0.5131 data_time: 0.0087 memory: 16131 loss: 0.8484 loss_prob: 0.4424 loss_thr: 0.3291 loss_db: 0.0769 2022/10/26 08:33:20 - mmengine - INFO - Epoch(train) [1092][50/63] lr: 4.0522e-04 eta: 1:15:54 time: 0.5583 data_time: 0.0212 memory: 16131 loss: 0.8521 loss_prob: 0.4439 loss_thr: 0.3308 loss_db: 0.0774 2022/10/26 08:33:22 - mmengine - INFO - Epoch(train) [1092][55/63] lr: 4.0522e-04 eta: 1:15:54 time: 0.5408 data_time: 0.0223 memory: 16131 loss: 0.9523 loss_prob: 0.5077 loss_thr: 0.3574 loss_db: 0.0871 2022/10/26 08:33:25 - mmengine - INFO - Epoch(train) [1092][60/63] lr: 4.0522e-04 eta: 1:15:47 time: 0.4951 data_time: 0.0103 memory: 16131 loss: 0.9439 loss_prob: 0.4980 loss_thr: 0.3600 loss_db: 0.0859 2022/10/26 08:33:26 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:33:30 - mmengine - INFO - Epoch(train) [1093][5/63] lr: 4.0184e-04 eta: 1:15:47 time: 0.6536 data_time: 0.1945 memory: 16131 loss: 1.0812 loss_prob: 0.5913 loss_thr: 0.3911 loss_db: 0.0988 2022/10/26 08:33:33 - mmengine - INFO - Epoch(train) [1093][10/63] lr: 4.0184e-04 eta: 1:15:38 time: 0.6772 data_time: 0.1935 memory: 16131 loss: 1.0365 loss_prob: 0.5593 loss_thr: 0.3835 loss_db: 0.0937 2022/10/26 08:33:35 - mmengine - INFO - Epoch(train) [1093][15/63] lr: 4.0184e-04 eta: 1:15:38 time: 0.4824 data_time: 0.0048 memory: 16131 loss: 0.9198 loss_prob: 0.4901 loss_thr: 0.3467 loss_db: 0.0830 2022/10/26 08:33:38 - mmengine - INFO - Epoch(train) [1093][20/63] lr: 4.0184e-04 eta: 1:15:31 time: 0.4864 data_time: 0.0086 memory: 16131 loss: 0.8226 loss_prob: 0.4288 loss_thr: 0.3204 loss_db: 0.0734 2022/10/26 08:33:40 - mmengine - INFO - Epoch(train) [1093][25/63] lr: 4.0184e-04 eta: 1:15:31 time: 0.5063 data_time: 0.0293 memory: 16131 loss: 0.7957 loss_prob: 0.4132 loss_thr: 0.3102 loss_db: 0.0723 2022/10/26 08:33:43 - mmengine - INFO - Epoch(train) [1093][30/63] lr: 4.0184e-04 eta: 1:15:25 time: 0.5015 data_time: 0.0323 memory: 16131 loss: 0.8909 loss_prob: 0.4639 loss_thr: 0.3451 loss_db: 0.0819 2022/10/26 08:33:45 - mmengine - INFO - Epoch(train) [1093][35/63] lr: 4.0184e-04 eta: 1:15:25 time: 0.4907 data_time: 0.0190 memory: 16131 loss: 0.9360 loss_prob: 0.4889 loss_thr: 0.3615 loss_db: 0.0857 2022/10/26 08:33:48 - mmengine - INFO - Epoch(train) [1093][40/63] lr: 4.0184e-04 eta: 1:15:18 time: 0.5018 data_time: 0.0131 memory: 16131 loss: 0.9118 loss_prob: 0.4827 loss_thr: 0.3446 loss_db: 0.0845 2022/10/26 08:33:50 - mmengine - INFO - Epoch(train) [1093][45/63] lr: 4.0184e-04 eta: 1:15:18 time: 0.5139 data_time: 0.0060 memory: 16131 loss: 0.9193 loss_prob: 0.4844 loss_thr: 0.3502 loss_db: 0.0847 2022/10/26 08:33:53 - mmengine - INFO - Epoch(train) [1093][50/63] lr: 4.0184e-04 eta: 1:15:11 time: 0.5255 data_time: 0.0225 memory: 16131 loss: 0.9062 loss_prob: 0.4705 loss_thr: 0.3534 loss_db: 0.0824 2022/10/26 08:33:56 - mmengine - INFO - Epoch(train) [1093][55/63] lr: 4.0184e-04 eta: 1:15:11 time: 0.5191 data_time: 0.0223 memory: 16131 loss: 0.8797 loss_prob: 0.4564 loss_thr: 0.3434 loss_db: 0.0799 2022/10/26 08:33:58 - mmengine - INFO - Epoch(train) [1093][60/63] lr: 4.0184e-04 eta: 1:15:04 time: 0.5226 data_time: 0.0062 memory: 16131 loss: 0.8571 loss_prob: 0.4412 loss_thr: 0.3392 loss_db: 0.0766 2022/10/26 08:33:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:34:04 - mmengine - INFO - Epoch(train) [1094][5/63] lr: 3.9846e-04 eta: 1:15:04 time: 0.6949 data_time: 0.2209 memory: 16131 loss: 0.8358 loss_prob: 0.4302 loss_thr: 0.3322 loss_db: 0.0734 2022/10/26 08:34:07 - mmengine - INFO - Epoch(train) [1094][10/63] lr: 3.9846e-04 eta: 1:14:55 time: 0.7355 data_time: 0.2216 memory: 16131 loss: 0.8266 loss_prob: 0.4316 loss_thr: 0.3225 loss_db: 0.0725 2022/10/26 08:34:09 - mmengine - INFO - Epoch(train) [1094][15/63] lr: 3.9846e-04 eta: 1:14:55 time: 0.5088 data_time: 0.0105 memory: 16131 loss: 0.9162 loss_prob: 0.4755 loss_thr: 0.3592 loss_db: 0.0814 2022/10/26 08:34:12 - mmengine - INFO - Epoch(train) [1094][20/63] lr: 3.9846e-04 eta: 1:14:48 time: 0.4974 data_time: 0.0051 memory: 16131 loss: 0.9243 loss_prob: 0.4846 loss_thr: 0.3557 loss_db: 0.0840 2022/10/26 08:34:15 - mmengine - INFO - Epoch(train) [1094][25/63] lr: 3.9846e-04 eta: 1:14:48 time: 0.5343 data_time: 0.0334 memory: 16131 loss: 0.8196 loss_prob: 0.4309 loss_thr: 0.3133 loss_db: 0.0754 2022/10/26 08:34:17 - mmengine - INFO - Epoch(train) [1094][30/63] lr: 3.9846e-04 eta: 1:14:42 time: 0.5356 data_time: 0.0359 memory: 16131 loss: 0.8345 loss_prob: 0.4357 loss_thr: 0.3224 loss_db: 0.0764 2022/10/26 08:34:20 - mmengine - INFO - Epoch(train) [1094][35/63] lr: 3.9846e-04 eta: 1:14:42 time: 0.5113 data_time: 0.0078 memory: 16131 loss: 0.8930 loss_prob: 0.4648 loss_thr: 0.3468 loss_db: 0.0815 2022/10/26 08:34:22 - mmengine - INFO - Epoch(train) [1094][40/63] lr: 3.9846e-04 eta: 1:14:35 time: 0.5169 data_time: 0.0064 memory: 16131 loss: 0.8420 loss_prob: 0.4321 loss_thr: 0.3339 loss_db: 0.0760 2022/10/26 08:34:25 - mmengine - INFO - Epoch(train) [1094][45/63] lr: 3.9846e-04 eta: 1:14:35 time: 0.5239 data_time: 0.0066 memory: 16131 loss: 0.8494 loss_prob: 0.4378 loss_thr: 0.3339 loss_db: 0.0777 2022/10/26 08:34:28 - mmengine - INFO - Epoch(train) [1094][50/63] lr: 3.9846e-04 eta: 1:14:28 time: 0.5438 data_time: 0.0219 memory: 16131 loss: 0.8308 loss_prob: 0.4239 loss_thr: 0.3313 loss_db: 0.0756 2022/10/26 08:34:30 - mmengine - INFO - Epoch(train) [1094][55/63] lr: 3.9846e-04 eta: 1:14:28 time: 0.5305 data_time: 0.0289 memory: 16131 loss: 0.8616 loss_prob: 0.4436 loss_thr: 0.3399 loss_db: 0.0781 2022/10/26 08:34:33 - mmengine - INFO - Epoch(train) [1094][60/63] lr: 3.9846e-04 eta: 1:14:21 time: 0.5033 data_time: 0.0155 memory: 16131 loss: 0.8873 loss_prob: 0.4651 loss_thr: 0.3406 loss_db: 0.0816 2022/10/26 08:34:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:34:39 - mmengine - INFO - Epoch(train) [1095][5/63] lr: 3.9507e-04 eta: 1:14:21 time: 0.7108 data_time: 0.1988 memory: 16131 loss: 0.9443 loss_prob: 0.4965 loss_thr: 0.3628 loss_db: 0.0850 2022/10/26 08:34:41 - mmengine - INFO - Epoch(train) [1095][10/63] lr: 3.9507e-04 eta: 1:14:12 time: 0.7160 data_time: 0.1981 memory: 16131 loss: 0.9983 loss_prob: 0.5303 loss_thr: 0.3771 loss_db: 0.0908 2022/10/26 08:34:44 - mmengine - INFO - Epoch(train) [1095][15/63] lr: 3.9507e-04 eta: 1:14:12 time: 0.5138 data_time: 0.0058 memory: 16131 loss: 0.9070 loss_prob: 0.4741 loss_thr: 0.3502 loss_db: 0.0826 2022/10/26 08:34:47 - mmengine - INFO - Epoch(train) [1095][20/63] lr: 3.9507e-04 eta: 1:14:06 time: 0.5192 data_time: 0.0070 memory: 16131 loss: 0.9003 loss_prob: 0.4750 loss_thr: 0.3441 loss_db: 0.0812 2022/10/26 08:34:49 - mmengine - INFO - Epoch(train) [1095][25/63] lr: 3.9507e-04 eta: 1:14:06 time: 0.5112 data_time: 0.0135 memory: 16131 loss: 0.9382 loss_prob: 0.5033 loss_thr: 0.3500 loss_db: 0.0850 2022/10/26 08:34:52 - mmengine - INFO - Epoch(train) [1095][30/63] lr: 3.9507e-04 eta: 1:13:59 time: 0.5272 data_time: 0.0341 memory: 16131 loss: 0.8947 loss_prob: 0.4715 loss_thr: 0.3423 loss_db: 0.0810 2022/10/26 08:34:54 - mmengine - INFO - Epoch(train) [1095][35/63] lr: 3.9507e-04 eta: 1:13:59 time: 0.5339 data_time: 0.0312 memory: 16131 loss: 0.8959 loss_prob: 0.4822 loss_thr: 0.3348 loss_db: 0.0789 2022/10/26 08:34:57 - mmengine - INFO - Epoch(train) [1095][40/63] lr: 3.9507e-04 eta: 1:13:52 time: 0.5337 data_time: 0.0096 memory: 16131 loss: 0.9271 loss_prob: 0.5037 loss_thr: 0.3406 loss_db: 0.0828 2022/10/26 08:35:00 - mmengine - INFO - Epoch(train) [1095][45/63] lr: 3.9507e-04 eta: 1:13:52 time: 0.5406 data_time: 0.0061 memory: 16131 loss: 0.9100 loss_prob: 0.4733 loss_thr: 0.3523 loss_db: 0.0843 2022/10/26 08:35:02 - mmengine - INFO - Epoch(train) [1095][50/63] lr: 3.9507e-04 eta: 1:13:45 time: 0.5209 data_time: 0.0143 memory: 16131 loss: 0.9063 loss_prob: 0.4679 loss_thr: 0.3550 loss_db: 0.0834 2022/10/26 08:35:05 - mmengine - INFO - Epoch(train) [1095][55/63] lr: 3.9507e-04 eta: 1:13:45 time: 0.5379 data_time: 0.0274 memory: 16131 loss: 0.8564 loss_prob: 0.4417 loss_thr: 0.3359 loss_db: 0.0787 2022/10/26 08:35:08 - mmengine - INFO - Epoch(train) [1095][60/63] lr: 3.9507e-04 eta: 1:13:38 time: 0.5695 data_time: 0.0200 memory: 16131 loss: 0.8335 loss_prob: 0.4287 loss_thr: 0.3283 loss_db: 0.0764 2022/10/26 08:35:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:35:14 - mmengine - INFO - Epoch(train) [1096][5/63] lr: 3.9169e-04 eta: 1:13:38 time: 0.7108 data_time: 0.2136 memory: 16131 loss: 0.8514 loss_prob: 0.4439 loss_thr: 0.3313 loss_db: 0.0762 2022/10/26 08:35:17 - mmengine - INFO - Epoch(train) [1096][10/63] lr: 3.9169e-04 eta: 1:13:30 time: 0.7209 data_time: 0.2085 memory: 16131 loss: 0.8060 loss_prob: 0.4196 loss_thr: 0.3137 loss_db: 0.0727 2022/10/26 08:35:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:35:19 - mmengine - INFO - Epoch(train) [1096][15/63] lr: 3.9169e-04 eta: 1:13:30 time: 0.5208 data_time: 0.0096 memory: 16131 loss: 0.7666 loss_prob: 0.3874 loss_thr: 0.3107 loss_db: 0.0685 2022/10/26 08:35:22 - mmengine - INFO - Epoch(train) [1096][20/63] lr: 3.9169e-04 eta: 1:13:23 time: 0.5292 data_time: 0.0103 memory: 16131 loss: 0.8505 loss_prob: 0.4288 loss_thr: 0.3465 loss_db: 0.0753 2022/10/26 08:35:25 - mmengine - INFO - Epoch(train) [1096][25/63] lr: 3.9169e-04 eta: 1:13:23 time: 0.5608 data_time: 0.0279 memory: 16131 loss: 0.8873 loss_prob: 0.4614 loss_thr: 0.3454 loss_db: 0.0804 2022/10/26 08:35:28 - mmengine - INFO - Epoch(train) [1096][30/63] lr: 3.9169e-04 eta: 1:13:16 time: 0.5665 data_time: 0.0330 memory: 16131 loss: 0.8743 loss_prob: 0.4613 loss_thr: 0.3313 loss_db: 0.0818 2022/10/26 08:35:30 - mmengine - INFO - Epoch(train) [1096][35/63] lr: 3.9169e-04 eta: 1:13:16 time: 0.5461 data_time: 0.0133 memory: 16131 loss: 0.8730 loss_prob: 0.4561 loss_thr: 0.3363 loss_db: 0.0806 2022/10/26 08:35:33 - mmengine - INFO - Epoch(train) [1096][40/63] lr: 3.9169e-04 eta: 1:13:09 time: 0.5147 data_time: 0.0051 memory: 16131 loss: 0.8513 loss_prob: 0.4392 loss_thr: 0.3358 loss_db: 0.0764 2022/10/26 08:35:35 - mmengine - INFO - Epoch(train) [1096][45/63] lr: 3.9169e-04 eta: 1:13:09 time: 0.5037 data_time: 0.0051 memory: 16131 loss: 0.8667 loss_prob: 0.4547 loss_thr: 0.3324 loss_db: 0.0795 2022/10/26 08:35:38 - mmengine - INFO - Epoch(train) [1096][50/63] lr: 3.9169e-04 eta: 1:13:02 time: 0.5115 data_time: 0.0196 memory: 16131 loss: 0.9021 loss_prob: 0.4792 loss_thr: 0.3395 loss_db: 0.0835 2022/10/26 08:35:41 - mmengine - INFO - Epoch(train) [1096][55/63] lr: 3.9169e-04 eta: 1:13:02 time: 0.5337 data_time: 0.0247 memory: 16131 loss: 0.9691 loss_prob: 0.5103 loss_thr: 0.3704 loss_db: 0.0883 2022/10/26 08:35:44 - mmengine - INFO - Epoch(train) [1096][60/63] lr: 3.9169e-04 eta: 1:12:56 time: 0.5597 data_time: 0.0115 memory: 16131 loss: 0.9488 loss_prob: 0.4966 loss_thr: 0.3670 loss_db: 0.0852 2022/10/26 08:35:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:35:49 - mmengine - INFO - Epoch(train) [1097][5/63] lr: 3.8830e-04 eta: 1:12:56 time: 0.6663 data_time: 0.1997 memory: 16131 loss: 0.8376 loss_prob: 0.4390 loss_thr: 0.3237 loss_db: 0.0749 2022/10/26 08:35:52 - mmengine - INFO - Epoch(train) [1097][10/63] lr: 3.8830e-04 eta: 1:12:47 time: 0.7087 data_time: 0.2030 memory: 16131 loss: 0.9205 loss_prob: 0.4869 loss_thr: 0.3503 loss_db: 0.0833 2022/10/26 08:35:54 - mmengine - INFO - Epoch(train) [1097][15/63] lr: 3.8830e-04 eta: 1:12:47 time: 0.5158 data_time: 0.0137 memory: 16131 loss: 0.8806 loss_prob: 0.4490 loss_thr: 0.3527 loss_db: 0.0789 2022/10/26 08:35:57 - mmengine - INFO - Epoch(train) [1097][20/63] lr: 3.8830e-04 eta: 1:12:40 time: 0.5083 data_time: 0.0110 memory: 16131 loss: 0.9042 loss_prob: 0.4659 loss_thr: 0.3571 loss_db: 0.0813 2022/10/26 08:36:00 - mmengine - INFO - Epoch(train) [1097][25/63] lr: 3.8830e-04 eta: 1:12:40 time: 0.5265 data_time: 0.0205 memory: 16131 loss: 0.8832 loss_prob: 0.4628 loss_thr: 0.3392 loss_db: 0.0812 2022/10/26 08:36:02 - mmengine - INFO - Epoch(train) [1097][30/63] lr: 3.8830e-04 eta: 1:12:33 time: 0.5474 data_time: 0.0283 memory: 16131 loss: 0.8520 loss_prob: 0.4434 loss_thr: 0.3308 loss_db: 0.0778 2022/10/26 08:36:05 - mmengine - INFO - Epoch(train) [1097][35/63] lr: 3.8830e-04 eta: 1:12:33 time: 0.5437 data_time: 0.0220 memory: 16131 loss: 0.8286 loss_prob: 0.4317 loss_thr: 0.3221 loss_db: 0.0748 2022/10/26 08:36:08 - mmengine - INFO - Epoch(train) [1097][40/63] lr: 3.8830e-04 eta: 1:12:26 time: 0.5280 data_time: 0.0172 memory: 16131 loss: 0.8536 loss_prob: 0.4502 loss_thr: 0.3260 loss_db: 0.0774 2022/10/26 08:36:10 - mmengine - INFO - Epoch(train) [1097][45/63] lr: 3.8830e-04 eta: 1:12:26 time: 0.5111 data_time: 0.0105 memory: 16131 loss: 0.9223 loss_prob: 0.4866 loss_thr: 0.3502 loss_db: 0.0855 2022/10/26 08:36:13 - mmengine - INFO - Epoch(train) [1097][50/63] lr: 3.8830e-04 eta: 1:12:19 time: 0.5152 data_time: 0.0174 memory: 16131 loss: 0.9364 loss_prob: 0.4880 loss_thr: 0.3620 loss_db: 0.0863 2022/10/26 08:36:16 - mmengine - INFO - Epoch(train) [1097][55/63] lr: 3.8830e-04 eta: 1:12:19 time: 0.5486 data_time: 0.0218 memory: 16131 loss: 1.0054 loss_prob: 0.5424 loss_thr: 0.3691 loss_db: 0.0939 2022/10/26 08:36:19 - mmengine - INFO - Epoch(train) [1097][60/63] lr: 3.8830e-04 eta: 1:12:13 time: 0.5788 data_time: 0.0209 memory: 16131 loss: 0.9994 loss_prob: 0.5515 loss_thr: 0.3520 loss_db: 0.0960 2022/10/26 08:36:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:36:25 - mmengine - INFO - Epoch(train) [1098][5/63] lr: 3.8490e-04 eta: 1:12:13 time: 0.7224 data_time: 0.1899 memory: 16131 loss: 0.9354 loss_prob: 0.5004 loss_thr: 0.3464 loss_db: 0.0886 2022/10/26 08:36:27 - mmengine - INFO - Epoch(train) [1098][10/63] lr: 3.8490e-04 eta: 1:12:04 time: 0.7238 data_time: 0.1873 memory: 16131 loss: 0.9166 loss_prob: 0.4856 loss_thr: 0.3464 loss_db: 0.0846 2022/10/26 08:36:30 - mmengine - INFO - Epoch(train) [1098][15/63] lr: 3.8490e-04 eta: 1:12:04 time: 0.4975 data_time: 0.0047 memory: 16131 loss: 0.8981 loss_prob: 0.4809 loss_thr: 0.3357 loss_db: 0.0815 2022/10/26 08:36:33 - mmengine - INFO - Epoch(train) [1098][20/63] lr: 3.8490e-04 eta: 1:11:57 time: 0.5558 data_time: 0.0053 memory: 16131 loss: 0.8591 loss_prob: 0.4548 loss_thr: 0.3257 loss_db: 0.0786 2022/10/26 08:36:35 - mmengine - INFO - Epoch(train) [1098][25/63] lr: 3.8490e-04 eta: 1:11:57 time: 0.5706 data_time: 0.0092 memory: 16131 loss: 0.8683 loss_prob: 0.4589 loss_thr: 0.3291 loss_db: 0.0803 2022/10/26 08:36:38 - mmengine - INFO - Epoch(train) [1098][30/63] lr: 3.8490e-04 eta: 1:11:50 time: 0.5711 data_time: 0.0354 memory: 16131 loss: 0.9013 loss_prob: 0.4786 loss_thr: 0.3385 loss_db: 0.0842 2022/10/26 08:36:41 - mmengine - INFO - Epoch(train) [1098][35/63] lr: 3.8490e-04 eta: 1:11:50 time: 0.5537 data_time: 0.0312 memory: 16131 loss: 0.8632 loss_prob: 0.4470 loss_thr: 0.3375 loss_db: 0.0788 2022/10/26 08:36:43 - mmengine - INFO - Epoch(train) [1098][40/63] lr: 3.8490e-04 eta: 1:11:44 time: 0.4872 data_time: 0.0045 memory: 16131 loss: 0.8686 loss_prob: 0.4527 loss_thr: 0.3366 loss_db: 0.0793 2022/10/26 08:36:46 - mmengine - INFO - Epoch(train) [1098][45/63] lr: 3.8490e-04 eta: 1:11:44 time: 0.5162 data_time: 0.0051 memory: 16131 loss: 0.8391 loss_prob: 0.4374 loss_thr: 0.3243 loss_db: 0.0775 2022/10/26 08:36:49 - mmengine - INFO - Epoch(train) [1098][50/63] lr: 3.8490e-04 eta: 1:11:37 time: 0.5192 data_time: 0.0132 memory: 16131 loss: 0.7671 loss_prob: 0.3856 loss_thr: 0.3119 loss_db: 0.0696 2022/10/26 08:36:51 - mmengine - INFO - Epoch(train) [1098][55/63] lr: 3.8490e-04 eta: 1:11:37 time: 0.4977 data_time: 0.0242 memory: 16131 loss: 0.8161 loss_prob: 0.4181 loss_thr: 0.3248 loss_db: 0.0732 2022/10/26 08:36:54 - mmengine - INFO - Epoch(train) [1098][60/63] lr: 3.8490e-04 eta: 1:11:30 time: 0.5144 data_time: 0.0161 memory: 16131 loss: 0.9081 loss_prob: 0.4800 loss_thr: 0.3455 loss_db: 0.0826 2022/10/26 08:36:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:37:01 - mmengine - INFO - Epoch(train) [1099][5/63] lr: 3.8151e-04 eta: 1:11:30 time: 0.8191 data_time: 0.2129 memory: 16131 loss: 0.9549 loss_prob: 0.5092 loss_thr: 0.3570 loss_db: 0.0886 2022/10/26 08:37:04 - mmengine - INFO - Epoch(train) [1099][10/63] lr: 3.8151e-04 eta: 1:11:21 time: 0.8561 data_time: 0.2101 memory: 16131 loss: 0.9323 loss_prob: 0.4887 loss_thr: 0.3581 loss_db: 0.0854 2022/10/26 08:37:06 - mmengine - INFO - Epoch(train) [1099][15/63] lr: 3.8151e-04 eta: 1:11:21 time: 0.5115 data_time: 0.0105 memory: 16131 loss: 0.9479 loss_prob: 0.4983 loss_thr: 0.3619 loss_db: 0.0876 2022/10/26 08:37:08 - mmengine - INFO - Epoch(train) [1099][20/63] lr: 3.8151e-04 eta: 1:11:14 time: 0.4943 data_time: 0.0064 memory: 16131 loss: 0.9530 loss_prob: 0.5148 loss_thr: 0.3488 loss_db: 0.0895 2022/10/26 08:37:11 - mmengine - INFO - Epoch(train) [1099][25/63] lr: 3.8151e-04 eta: 1:11:14 time: 0.5375 data_time: 0.0245 memory: 16131 loss: 0.9381 loss_prob: 0.4988 loss_thr: 0.3536 loss_db: 0.0857 2022/10/26 08:37:14 - mmengine - INFO - Epoch(train) [1099][30/63] lr: 3.8151e-04 eta: 1:11:08 time: 0.5318 data_time: 0.0350 memory: 16131 loss: 0.9149 loss_prob: 0.4756 loss_thr: 0.3567 loss_db: 0.0825 2022/10/26 08:37:16 - mmengine - INFO - Epoch(train) [1099][35/63] lr: 3.8151e-04 eta: 1:11:08 time: 0.5127 data_time: 0.0153 memory: 16131 loss: 0.8528 loss_prob: 0.4473 loss_thr: 0.3275 loss_db: 0.0779 2022/10/26 08:37:19 - mmengine - INFO - Epoch(train) [1099][40/63] lr: 3.8151e-04 eta: 1:11:01 time: 0.5172 data_time: 0.0061 memory: 16131 loss: 0.8145 loss_prob: 0.4248 loss_thr: 0.3159 loss_db: 0.0738 2022/10/26 08:37:21 - mmengine - INFO - Epoch(train) [1099][45/63] lr: 3.8151e-04 eta: 1:11:01 time: 0.5045 data_time: 0.0071 memory: 16131 loss: 0.8212 loss_prob: 0.4227 loss_thr: 0.3239 loss_db: 0.0746 2022/10/26 08:37:24 - mmengine - INFO - Epoch(train) [1099][50/63] lr: 3.8151e-04 eta: 1:10:54 time: 0.5225 data_time: 0.0182 memory: 16131 loss: 0.8170 loss_prob: 0.4132 loss_thr: 0.3296 loss_db: 0.0742 2022/10/26 08:37:27 - mmengine - INFO - Epoch(train) [1099][55/63] lr: 3.8151e-04 eta: 1:10:54 time: 0.5716 data_time: 0.0228 memory: 16131 loss: 0.8124 loss_prob: 0.4123 loss_thr: 0.3273 loss_db: 0.0728 2022/10/26 08:37:30 - mmengine - INFO - Epoch(train) [1099][60/63] lr: 3.8151e-04 eta: 1:10:47 time: 0.5694 data_time: 0.0118 memory: 16131 loss: 0.8640 loss_prob: 0.4474 loss_thr: 0.3389 loss_db: 0.0777 2022/10/26 08:37:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:37:37 - mmengine - INFO - Epoch(train) [1100][5/63] lr: 3.7811e-04 eta: 1:10:47 time: 0.7907 data_time: 0.1829 memory: 16131 loss: 0.8365 loss_prob: 0.4285 loss_thr: 0.3340 loss_db: 0.0740 2022/10/26 08:37:39 - mmengine - INFO - Epoch(train) [1100][10/63] lr: 3.7811e-04 eta: 1:10:38 time: 0.8162 data_time: 0.1882 memory: 16131 loss: 0.8291 loss_prob: 0.4298 loss_thr: 0.3233 loss_db: 0.0760 2022/10/26 08:37:42 - mmengine - INFO - Epoch(train) [1100][15/63] lr: 3.7811e-04 eta: 1:10:38 time: 0.5642 data_time: 0.0185 memory: 16131 loss: 0.8008 loss_prob: 0.4195 loss_thr: 0.3066 loss_db: 0.0746 2022/10/26 08:37:45 - mmengine - INFO - Epoch(train) [1100][20/63] lr: 3.7811e-04 eta: 1:10:32 time: 0.5302 data_time: 0.0128 memory: 16131 loss: 0.7928 loss_prob: 0.4096 loss_thr: 0.3105 loss_db: 0.0727 2022/10/26 08:37:47 - mmengine - INFO - Epoch(train) [1100][25/63] lr: 3.7811e-04 eta: 1:10:32 time: 0.5124 data_time: 0.0182 memory: 16131 loss: 0.8997 loss_prob: 0.4717 loss_thr: 0.3444 loss_db: 0.0836 2022/10/26 08:37:50 - mmengine - INFO - Epoch(train) [1100][30/63] lr: 3.7811e-04 eta: 1:10:25 time: 0.5354 data_time: 0.0309 memory: 16131 loss: 0.9257 loss_prob: 0.4858 loss_thr: 0.3550 loss_db: 0.0849 2022/10/26 08:37:53 - mmengine - INFO - Epoch(train) [1100][35/63] lr: 3.7811e-04 eta: 1:10:25 time: 0.5715 data_time: 0.0198 memory: 16131 loss: 0.8927 loss_prob: 0.4668 loss_thr: 0.3451 loss_db: 0.0807 2022/10/26 08:37:56 - mmengine - INFO - Epoch(train) [1100][40/63] lr: 3.7811e-04 eta: 1:10:18 time: 0.5659 data_time: 0.0195 memory: 16131 loss: 0.9184 loss_prob: 0.4836 loss_thr: 0.3500 loss_db: 0.0848 2022/10/26 08:37:59 - mmengine - INFO - Epoch(train) [1100][45/63] lr: 3.7811e-04 eta: 1:10:18 time: 0.5414 data_time: 0.0178 memory: 16131 loss: 0.8662 loss_prob: 0.4562 loss_thr: 0.3295 loss_db: 0.0805 2022/10/26 08:38:01 - mmengine - INFO - Epoch(train) [1100][50/63] lr: 3.7811e-04 eta: 1:10:11 time: 0.5239 data_time: 0.0148 memory: 16131 loss: 0.8300 loss_prob: 0.4362 loss_thr: 0.3178 loss_db: 0.0760 2022/10/26 08:38:04 - mmengine - INFO - Epoch(train) [1100][55/63] lr: 3.7811e-04 eta: 1:10:11 time: 0.5048 data_time: 0.0196 memory: 16131 loss: 0.8319 loss_prob: 0.4364 loss_thr: 0.3206 loss_db: 0.0749 2022/10/26 08:38:07 - mmengine - INFO - Epoch(train) [1100][60/63] lr: 3.7811e-04 eta: 1:10:05 time: 0.5466 data_time: 0.0136 memory: 16131 loss: 0.8530 loss_prob: 0.4394 loss_thr: 0.3373 loss_db: 0.0764 2022/10/26 08:38:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:38:08 - mmengine - INFO - Saving checkpoint at 1100 epochs 2022/10/26 08:38:15 - mmengine - INFO - Epoch(val) [1100][5/32] eta: 1:10:05 time: 0.5476 data_time: 0.0959 memory: 16131 2022/10/26 08:38:17 - mmengine - INFO - Epoch(val) [1100][10/32] eta: 0:00:13 time: 0.6020 data_time: 0.1146 memory: 15724 2022/10/26 08:38:20 - mmengine - INFO - Epoch(val) [1100][15/32] eta: 0:00:13 time: 0.5344 data_time: 0.0511 memory: 15724 2022/10/26 08:38:23 - mmengine - INFO - Epoch(val) [1100][20/32] eta: 0:00:06 time: 0.5384 data_time: 0.0586 memory: 15724 2022/10/26 08:38:26 - mmengine - INFO - Epoch(val) [1100][25/32] eta: 0:00:06 time: 0.5436 data_time: 0.0507 memory: 15724 2022/10/26 08:38:28 - mmengine - INFO - Epoch(val) [1100][30/32] eta: 0:00:01 time: 0.5195 data_time: 0.0312 memory: 15724 2022/10/26 08:38:29 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8382, precision: 0.7670, hmean: 0.8010 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8382, precision: 0.8143, hmean: 0.8261 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8382, precision: 0.8398, hmean: 0.8390 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8349, precision: 0.8631, hmean: 0.8488 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8276, precision: 0.8879, hmean: 0.8567 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7670, precision: 0.9213, hmean: 0.8371 2022/10/26 08:38:29 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2484, precision: 0.9718, hmean: 0.3957 2022/10/26 08:38:29 - mmengine - INFO - Epoch(val) [1100][32/32] icdar/precision: 0.8879 icdar/recall: 0.8276 icdar/hmean: 0.8567 2022/10/26 08:38:34 - mmengine - INFO - Epoch(train) [1101][5/63] lr: 3.7470e-04 eta: 0:00:01 time: 0.7368 data_time: 0.2089 memory: 16131 loss: 0.9061 loss_prob: 0.4615 loss_thr: 0.3637 loss_db: 0.0808 2022/10/26 08:38:36 - mmengine - INFO - Epoch(train) [1101][10/63] lr: 3.7470e-04 eta: 1:09:56 time: 0.7419 data_time: 0.2089 memory: 16131 loss: 0.8912 loss_prob: 0.4651 loss_thr: 0.3465 loss_db: 0.0796 2022/10/26 08:38:39 - mmengine - INFO - Epoch(train) [1101][15/63] lr: 3.7470e-04 eta: 1:09:56 time: 0.5018 data_time: 0.0098 memory: 16131 loss: 0.9289 loss_prob: 0.4843 loss_thr: 0.3613 loss_db: 0.0832 2022/10/26 08:38:41 - mmengine - INFO - Epoch(train) [1101][20/63] lr: 3.7470e-04 eta: 1:09:49 time: 0.5180 data_time: 0.0063 memory: 16131 loss: 1.0630 loss_prob: 0.5723 loss_thr: 0.3907 loss_db: 0.1000 2022/10/26 08:38:44 - mmengine - INFO - Epoch(train) [1101][25/63] lr: 3.7470e-04 eta: 1:09:49 time: 0.5369 data_time: 0.0224 memory: 16131 loss: 1.0574 loss_prob: 0.5819 loss_thr: 0.3763 loss_db: 0.0991 2022/10/26 08:38:47 - mmengine - INFO - Epoch(train) [1101][30/63] lr: 3.7470e-04 eta: 1:09:42 time: 0.5447 data_time: 0.0320 memory: 16131 loss: 0.9685 loss_prob: 0.5164 loss_thr: 0.3638 loss_db: 0.0884 2022/10/26 08:38:50 - mmengine - INFO - Epoch(train) [1101][35/63] lr: 3.7470e-04 eta: 1:09:42 time: 0.5861 data_time: 0.0146 memory: 16131 loss: 0.8840 loss_prob: 0.4635 loss_thr: 0.3393 loss_db: 0.0812 2022/10/26 08:38:53 - mmengine - INFO - Epoch(train) [1101][40/63] lr: 3.7470e-04 eta: 1:09:35 time: 0.5814 data_time: 0.0068 memory: 16131 loss: 0.8214 loss_prob: 0.4179 loss_thr: 0.3285 loss_db: 0.0750 2022/10/26 08:38:55 - mmengine - INFO - Epoch(train) [1101][45/63] lr: 3.7470e-04 eta: 1:09:35 time: 0.5154 data_time: 0.0076 memory: 16131 loss: 0.8337 loss_prob: 0.4266 loss_thr: 0.3319 loss_db: 0.0752 2022/10/26 08:38:58 - mmengine - INFO - Epoch(train) [1101][50/63] lr: 3.7470e-04 eta: 1:09:29 time: 0.5023 data_time: 0.0190 memory: 16131 loss: 0.8194 loss_prob: 0.4246 loss_thr: 0.3224 loss_db: 0.0724 2022/10/26 08:39:00 - mmengine - INFO - Epoch(train) [1101][55/63] lr: 3.7470e-04 eta: 1:09:29 time: 0.5306 data_time: 0.0212 memory: 16131 loss: 0.8429 loss_prob: 0.4286 loss_thr: 0.3396 loss_db: 0.0747 2022/10/26 08:39:03 - mmengine - INFO - Epoch(train) [1101][60/63] lr: 3.7470e-04 eta: 1:09:22 time: 0.5317 data_time: 0.0085 memory: 16131 loss: 0.8333 loss_prob: 0.4215 loss_thr: 0.3373 loss_db: 0.0745 2022/10/26 08:39:04 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:39:09 - mmengine - INFO - Epoch(train) [1102][5/63] lr: 3.7129e-04 eta: 1:09:22 time: 0.7439 data_time: 0.2086 memory: 16131 loss: 0.8802 loss_prob: 0.4562 loss_thr: 0.3449 loss_db: 0.0790 2022/10/26 08:39:12 - mmengine - INFO - Epoch(train) [1102][10/63] lr: 3.7129e-04 eta: 1:09:13 time: 0.7683 data_time: 0.2114 memory: 16131 loss: 0.9299 loss_prob: 0.4896 loss_thr: 0.3553 loss_db: 0.0849 2022/10/26 08:39:14 - mmengine - INFO - Epoch(train) [1102][15/63] lr: 3.7129e-04 eta: 1:09:13 time: 0.4994 data_time: 0.0123 memory: 16131 loss: 0.9204 loss_prob: 0.4791 loss_thr: 0.3565 loss_db: 0.0848 2022/10/26 08:39:17 - mmengine - INFO - Epoch(train) [1102][20/63] lr: 3.7129e-04 eta: 1:09:06 time: 0.5188 data_time: 0.0078 memory: 16131 loss: 0.9417 loss_prob: 0.4944 loss_thr: 0.3594 loss_db: 0.0880 2022/10/26 08:39:20 - mmengine - INFO - Epoch(train) [1102][25/63] lr: 3.7129e-04 eta: 1:09:06 time: 0.5330 data_time: 0.0180 memory: 16131 loss: 0.9336 loss_prob: 0.4983 loss_thr: 0.3488 loss_db: 0.0865 2022/10/26 08:39:23 - mmengine - INFO - Epoch(train) [1102][30/63] lr: 3.7129e-04 eta: 1:08:59 time: 0.5511 data_time: 0.0339 memory: 16131 loss: 0.8845 loss_prob: 0.4656 loss_thr: 0.3379 loss_db: 0.0810 2022/10/26 08:39:25 - mmengine - INFO - Epoch(train) [1102][35/63] lr: 3.7129e-04 eta: 1:08:59 time: 0.5562 data_time: 0.0216 memory: 16131 loss: 0.9227 loss_prob: 0.4728 loss_thr: 0.3670 loss_db: 0.0828 2022/10/26 08:39:28 - mmengine - INFO - Epoch(train) [1102][40/63] lr: 3.7129e-04 eta: 1:08:53 time: 0.5493 data_time: 0.0064 memory: 16131 loss: 0.9658 loss_prob: 0.5052 loss_thr: 0.3748 loss_db: 0.0859 2022/10/26 08:39:31 - mmengine - INFO - Epoch(train) [1102][45/63] lr: 3.7129e-04 eta: 1:08:53 time: 0.5726 data_time: 0.0083 memory: 16131 loss: 0.8530 loss_prob: 0.4446 loss_thr: 0.3315 loss_db: 0.0769 2022/10/26 08:39:34 - mmengine - INFO - Epoch(train) [1102][50/63] lr: 3.7129e-04 eta: 1:08:46 time: 0.5757 data_time: 0.0243 memory: 16131 loss: 0.8547 loss_prob: 0.4432 loss_thr: 0.3337 loss_db: 0.0778 2022/10/26 08:39:36 - mmengine - INFO - Epoch(train) [1102][55/63] lr: 3.7129e-04 eta: 1:08:46 time: 0.5449 data_time: 0.0214 memory: 16131 loss: 1.0255 loss_prob: 0.5519 loss_thr: 0.3782 loss_db: 0.0954 2022/10/26 08:39:39 - mmengine - INFO - Epoch(train) [1102][60/63] lr: 3.7129e-04 eta: 1:08:39 time: 0.5315 data_time: 0.0084 memory: 16131 loss: 1.0608 loss_prob: 0.5753 loss_thr: 0.3870 loss_db: 0.0985 2022/10/26 08:39:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:39:45 - mmengine - INFO - Epoch(train) [1103][5/63] lr: 3.6788e-04 eta: 1:08:39 time: 0.7131 data_time: 0.2088 memory: 16131 loss: 0.8528 loss_prob: 0.4463 loss_thr: 0.3315 loss_db: 0.0750 2022/10/26 08:39:48 - mmengine - INFO - Epoch(train) [1103][10/63] lr: 3.6788e-04 eta: 1:08:30 time: 0.7467 data_time: 0.2116 memory: 16131 loss: 0.8176 loss_prob: 0.4214 loss_thr: 0.3242 loss_db: 0.0720 2022/10/26 08:39:51 - mmengine - INFO - Epoch(train) [1103][15/63] lr: 3.6788e-04 eta: 1:08:30 time: 0.5679 data_time: 0.0096 memory: 16131 loss: 0.8660 loss_prob: 0.4397 loss_thr: 0.3489 loss_db: 0.0774 2022/10/26 08:39:53 - mmengine - INFO - Epoch(train) [1103][20/63] lr: 3.6788e-04 eta: 1:08:24 time: 0.5368 data_time: 0.0047 memory: 16131 loss: 0.9009 loss_prob: 0.4665 loss_thr: 0.3516 loss_db: 0.0827 2022/10/26 08:39:56 - mmengine - INFO - Epoch(train) [1103][25/63] lr: 3.6788e-04 eta: 1:08:24 time: 0.5211 data_time: 0.0193 memory: 16131 loss: 0.8703 loss_prob: 0.4597 loss_thr: 0.3299 loss_db: 0.0807 2022/10/26 08:39:59 - mmengine - INFO - Epoch(train) [1103][30/63] lr: 3.6788e-04 eta: 1:08:17 time: 0.5521 data_time: 0.0413 memory: 16131 loss: 0.9137 loss_prob: 0.4814 loss_thr: 0.3500 loss_db: 0.0823 2022/10/26 08:40:01 - mmengine - INFO - Epoch(train) [1103][35/63] lr: 3.6788e-04 eta: 1:08:17 time: 0.5304 data_time: 0.0283 memory: 16131 loss: 0.9212 loss_prob: 0.4799 loss_thr: 0.3589 loss_db: 0.0823 2022/10/26 08:40:04 - mmengine - INFO - Epoch(train) [1103][40/63] lr: 3.6788e-04 eta: 1:08:10 time: 0.5417 data_time: 0.0075 memory: 16131 loss: 0.9415 loss_prob: 0.4943 loss_thr: 0.3615 loss_db: 0.0856 2022/10/26 08:40:07 - mmengine - INFO - Epoch(train) [1103][45/63] lr: 3.6788e-04 eta: 1:08:10 time: 0.5624 data_time: 0.0082 memory: 16131 loss: 0.9400 loss_prob: 0.4904 loss_thr: 0.3646 loss_db: 0.0850 2022/10/26 08:40:10 - mmengine - INFO - Epoch(train) [1103][50/63] lr: 3.6788e-04 eta: 1:08:03 time: 0.5733 data_time: 0.0189 memory: 16131 loss: 0.7938 loss_prob: 0.3989 loss_thr: 0.3246 loss_db: 0.0702 2022/10/26 08:40:13 - mmengine - INFO - Epoch(train) [1103][55/63] lr: 3.6788e-04 eta: 1:08:03 time: 0.5672 data_time: 0.0303 memory: 16131 loss: 0.7857 loss_prob: 0.3937 loss_thr: 0.3218 loss_db: 0.0701 2022/10/26 08:40:16 - mmengine - INFO - Epoch(train) [1103][60/63] lr: 3.6788e-04 eta: 1:07:57 time: 0.5639 data_time: 0.0196 memory: 16131 loss: 0.8232 loss_prob: 0.4189 loss_thr: 0.3300 loss_db: 0.0743 2022/10/26 08:40:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:40:22 - mmengine - INFO - Epoch(train) [1104][5/63] lr: 3.6447e-04 eta: 1:07:57 time: 0.7392 data_time: 0.1672 memory: 16131 loss: 0.8351 loss_prob: 0.4346 loss_thr: 0.3251 loss_db: 0.0754 2022/10/26 08:40:25 - mmengine - INFO - Epoch(train) [1104][10/63] lr: 3.6447e-04 eta: 1:07:48 time: 0.7382 data_time: 0.1712 memory: 16131 loss: 0.9187 loss_prob: 0.4796 loss_thr: 0.3532 loss_db: 0.0859 2022/10/26 08:40:27 - mmengine - INFO - Epoch(train) [1104][15/63] lr: 3.6447e-04 eta: 1:07:48 time: 0.5158 data_time: 0.0086 memory: 16131 loss: 0.9524 loss_prob: 0.5012 loss_thr: 0.3629 loss_db: 0.0883 2022/10/26 08:40:30 - mmengine - INFO - Epoch(train) [1104][20/63] lr: 3.6447e-04 eta: 1:07:41 time: 0.4995 data_time: 0.0047 memory: 16131 loss: 0.8729 loss_prob: 0.4537 loss_thr: 0.3405 loss_db: 0.0787 2022/10/26 08:40:33 - mmengine - INFO - Epoch(train) [1104][25/63] lr: 3.6447e-04 eta: 1:07:41 time: 0.5488 data_time: 0.0240 memory: 16131 loss: 0.8661 loss_prob: 0.4480 loss_thr: 0.3392 loss_db: 0.0788 2022/10/26 08:40:35 - mmengine - INFO - Epoch(train) [1104][30/63] lr: 3.6447e-04 eta: 1:07:34 time: 0.5676 data_time: 0.0244 memory: 16131 loss: 0.8873 loss_prob: 0.4644 loss_thr: 0.3421 loss_db: 0.0807 2022/10/26 08:40:38 - mmengine - INFO - Epoch(train) [1104][35/63] lr: 3.6447e-04 eta: 1:07:34 time: 0.5325 data_time: 0.0134 memory: 16131 loss: 0.8710 loss_prob: 0.4598 loss_thr: 0.3305 loss_db: 0.0807 2022/10/26 08:40:41 - mmengine - INFO - Epoch(train) [1104][40/63] lr: 3.6447e-04 eta: 1:07:27 time: 0.5244 data_time: 0.0137 memory: 16131 loss: 0.9372 loss_prob: 0.5288 loss_thr: 0.3257 loss_db: 0.0827 2022/10/26 08:40:44 - mmengine - INFO - Epoch(train) [1104][45/63] lr: 3.6447e-04 eta: 1:07:27 time: 0.5914 data_time: 0.0055 memory: 16131 loss: 1.0007 loss_prob: 0.5619 loss_thr: 0.3516 loss_db: 0.0872 2022/10/26 08:40:47 - mmengine - INFO - Epoch(train) [1104][50/63] lr: 3.6447e-04 eta: 1:07:21 time: 0.6311 data_time: 0.0165 memory: 16131 loss: 1.0108 loss_prob: 0.5262 loss_thr: 0.3933 loss_db: 0.0913 2022/10/26 08:40:50 - mmengine - INFO - Epoch(train) [1104][55/63] lr: 3.6447e-04 eta: 1:07:21 time: 0.5766 data_time: 0.0228 memory: 16131 loss: 1.0011 loss_prob: 0.5207 loss_thr: 0.3898 loss_db: 0.0906 2022/10/26 08:40:52 - mmengine - INFO - Epoch(train) [1104][60/63] lr: 3.6447e-04 eta: 1:07:14 time: 0.5405 data_time: 0.0117 memory: 16131 loss: 0.9116 loss_prob: 0.4815 loss_thr: 0.3457 loss_db: 0.0844 2022/10/26 08:40:54 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:40:58 - mmengine - INFO - Epoch(train) [1105][5/63] lr: 3.6105e-04 eta: 1:07:14 time: 0.6613 data_time: 0.1837 memory: 16131 loss: 0.8921 loss_prob: 0.4711 loss_thr: 0.3387 loss_db: 0.0823 2022/10/26 08:41:00 - mmengine - INFO - Epoch(train) [1105][10/63] lr: 3.6105e-04 eta: 1:07:05 time: 0.6864 data_time: 0.1859 memory: 16131 loss: 0.8820 loss_prob: 0.4610 loss_thr: 0.3422 loss_db: 0.0788 2022/10/26 08:41:03 - mmengine - INFO - Epoch(train) [1105][15/63] lr: 3.6105e-04 eta: 1:07:05 time: 0.5043 data_time: 0.0102 memory: 16131 loss: 0.8465 loss_prob: 0.4388 loss_thr: 0.3314 loss_db: 0.0764 2022/10/26 08:41:05 - mmengine - INFO - Epoch(train) [1105][20/63] lr: 3.6105e-04 eta: 1:06:58 time: 0.5032 data_time: 0.0076 memory: 16131 loss: 0.8912 loss_prob: 0.4709 loss_thr: 0.3369 loss_db: 0.0835 2022/10/26 08:41:08 - mmengine - INFO - Epoch(train) [1105][25/63] lr: 3.6105e-04 eta: 1:06:58 time: 0.5119 data_time: 0.0234 memory: 16131 loss: 0.9504 loss_prob: 0.4961 loss_thr: 0.3670 loss_db: 0.0872 2022/10/26 08:41:11 - mmengine - INFO - Epoch(train) [1105][30/63] lr: 3.6105e-04 eta: 1:06:51 time: 0.5262 data_time: 0.0259 memory: 16131 loss: 0.8965 loss_prob: 0.4584 loss_thr: 0.3587 loss_db: 0.0794 2022/10/26 08:41:13 - mmengine - INFO - Epoch(train) [1105][35/63] lr: 3.6105e-04 eta: 1:06:51 time: 0.5085 data_time: 0.0092 memory: 16131 loss: 0.8183 loss_prob: 0.4129 loss_thr: 0.3337 loss_db: 0.0716 2022/10/26 08:41:16 - mmengine - INFO - Epoch(train) [1105][40/63] lr: 3.6105e-04 eta: 1:06:45 time: 0.4962 data_time: 0.0133 memory: 16131 loss: 0.8712 loss_prob: 0.4492 loss_thr: 0.3445 loss_db: 0.0774 2022/10/26 08:41:18 - mmengine - INFO - Epoch(train) [1105][45/63] lr: 3.6105e-04 eta: 1:06:45 time: 0.5307 data_time: 0.0112 memory: 16131 loss: 0.8788 loss_prob: 0.4565 loss_thr: 0.3431 loss_db: 0.0793 2022/10/26 08:41:22 - mmengine - INFO - Epoch(train) [1105][50/63] lr: 3.6105e-04 eta: 1:06:38 time: 0.6589 data_time: 0.0254 memory: 16131 loss: 0.8484 loss_prob: 0.4464 loss_thr: 0.3243 loss_db: 0.0776 2022/10/26 08:41:25 - mmengine - INFO - Epoch(train) [1105][55/63] lr: 3.6105e-04 eta: 1:06:38 time: 0.6304 data_time: 0.0291 memory: 16131 loss: 0.9275 loss_prob: 0.4969 loss_thr: 0.3434 loss_db: 0.0873 2022/10/26 08:41:28 - mmengine - INFO - Epoch(train) [1105][60/63] lr: 3.6105e-04 eta: 1:06:31 time: 0.5462 data_time: 0.0104 memory: 16131 loss: 0.9318 loss_prob: 0.4874 loss_thr: 0.3598 loss_db: 0.0846 2022/10/26 08:41:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:41:34 - mmengine - INFO - Epoch(train) [1106][5/63] lr: 3.5763e-04 eta: 1:06:31 time: 0.7292 data_time: 0.2026 memory: 16131 loss: 0.8529 loss_prob: 0.4452 loss_thr: 0.3308 loss_db: 0.0769 2022/10/26 08:41:36 - mmengine - INFO - Epoch(train) [1106][10/63] lr: 3.5763e-04 eta: 1:06:22 time: 0.7441 data_time: 0.2012 memory: 16131 loss: 0.8909 loss_prob: 0.4718 loss_thr: 0.3387 loss_db: 0.0805 2022/10/26 08:41:39 - mmengine - INFO - Epoch(train) [1106][15/63] lr: 3.5763e-04 eta: 1:06:22 time: 0.5223 data_time: 0.0098 memory: 16131 loss: 0.8989 loss_prob: 0.4742 loss_thr: 0.3442 loss_db: 0.0806 2022/10/26 08:41:42 - mmengine - INFO - Epoch(train) [1106][20/63] lr: 3.5763e-04 eta: 1:06:16 time: 0.5390 data_time: 0.0087 memory: 16131 loss: 0.9103 loss_prob: 0.4757 loss_thr: 0.3528 loss_db: 0.0818 2022/10/26 08:41:45 - mmengine - INFO - Epoch(train) [1106][25/63] lr: 3.5763e-04 eta: 1:06:16 time: 0.5558 data_time: 0.0113 memory: 16131 loss: 0.8508 loss_prob: 0.4407 loss_thr: 0.3335 loss_db: 0.0766 2022/10/26 08:41:48 - mmengine - INFO - Epoch(train) [1106][30/63] lr: 3.5763e-04 eta: 1:06:09 time: 0.5913 data_time: 0.0263 memory: 16131 loss: 0.8512 loss_prob: 0.4393 loss_thr: 0.3354 loss_db: 0.0765 2022/10/26 08:41:50 - mmengine - INFO - Epoch(train) [1106][35/63] lr: 3.5763e-04 eta: 1:06:09 time: 0.5660 data_time: 0.0274 memory: 16131 loss: 0.9600 loss_prob: 0.5027 loss_thr: 0.3712 loss_db: 0.0861 2022/10/26 08:41:53 - mmengine - INFO - Epoch(train) [1106][40/63] lr: 3.5763e-04 eta: 1:06:02 time: 0.5071 data_time: 0.0130 memory: 16131 loss: 0.9873 loss_prob: 0.5148 loss_thr: 0.3826 loss_db: 0.0898 2022/10/26 08:41:55 - mmengine - INFO - Epoch(train) [1106][45/63] lr: 3.5763e-04 eta: 1:06:02 time: 0.4961 data_time: 0.0075 memory: 16131 loss: 0.8506 loss_prob: 0.4366 loss_thr: 0.3362 loss_db: 0.0778 2022/10/26 08:41:58 - mmengine - INFO - Epoch(train) [1106][50/63] lr: 3.5763e-04 eta: 1:05:55 time: 0.5204 data_time: 0.0197 memory: 16131 loss: 0.7526 loss_prob: 0.3783 loss_thr: 0.3079 loss_db: 0.0663 2022/10/26 08:42:01 - mmengine - INFO - Epoch(train) [1106][55/63] lr: 3.5763e-04 eta: 1:05:55 time: 0.5719 data_time: 0.0211 memory: 16131 loss: 0.8094 loss_prob: 0.4088 loss_thr: 0.3290 loss_db: 0.0716 2022/10/26 08:42:03 - mmengine - INFO - Epoch(train) [1106][60/63] lr: 3.5763e-04 eta: 1:05:49 time: 0.5409 data_time: 0.0117 memory: 16131 loss: 0.8163 loss_prob: 0.4205 loss_thr: 0.3218 loss_db: 0.0741 2022/10/26 08:42:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:42:09 - mmengine - INFO - Epoch(train) [1107][5/63] lr: 3.5421e-04 eta: 1:05:49 time: 0.6692 data_time: 0.1573 memory: 16131 loss: 0.8655 loss_prob: 0.4537 loss_thr: 0.3343 loss_db: 0.0775 2022/10/26 08:42:12 - mmengine - INFO - Epoch(train) [1107][10/63] lr: 3.5421e-04 eta: 1:05:40 time: 0.7246 data_time: 0.1584 memory: 16131 loss: 0.9596 loss_prob: 0.5266 loss_thr: 0.3446 loss_db: 0.0884 2022/10/26 08:42:15 - mmengine - INFO - Epoch(train) [1107][15/63] lr: 3.5421e-04 eta: 1:05:40 time: 0.5425 data_time: 0.0097 memory: 16131 loss: 0.9864 loss_prob: 0.5393 loss_thr: 0.3533 loss_db: 0.0938 2022/10/26 08:42:17 - mmengine - INFO - Epoch(train) [1107][20/63] lr: 3.5421e-04 eta: 1:05:33 time: 0.5286 data_time: 0.0069 memory: 16131 loss: 0.9028 loss_prob: 0.4636 loss_thr: 0.3573 loss_db: 0.0819 2022/10/26 08:42:20 - mmengine - INFO - Epoch(train) [1107][25/63] lr: 3.5421e-04 eta: 1:05:33 time: 0.5504 data_time: 0.0094 memory: 16131 loss: 0.8615 loss_prob: 0.4444 loss_thr: 0.3409 loss_db: 0.0762 2022/10/26 08:42:23 - mmengine - INFO - Epoch(train) [1107][30/63] lr: 3.5421e-04 eta: 1:05:26 time: 0.5821 data_time: 0.0294 memory: 16131 loss: 0.8068 loss_prob: 0.4230 loss_thr: 0.3109 loss_db: 0.0729 2022/10/26 08:42:26 - mmengine - INFO - Epoch(train) [1107][35/63] lr: 3.5421e-04 eta: 1:05:26 time: 0.5634 data_time: 0.0275 memory: 16131 loss: 0.8010 loss_prob: 0.4172 loss_thr: 0.3120 loss_db: 0.0718 2022/10/26 08:42:28 - mmengine - INFO - Epoch(train) [1107][40/63] lr: 3.5421e-04 eta: 1:05:19 time: 0.5046 data_time: 0.0067 memory: 16131 loss: 0.8550 loss_prob: 0.4437 loss_thr: 0.3354 loss_db: 0.0759 2022/10/26 08:42:31 - mmengine - INFO - Epoch(train) [1107][45/63] lr: 3.5421e-04 eta: 1:05:19 time: 0.5108 data_time: 0.0089 memory: 16131 loss: 0.8231 loss_prob: 0.4239 loss_thr: 0.3255 loss_db: 0.0737 2022/10/26 08:42:33 - mmengine - INFO - Epoch(train) [1107][50/63] lr: 3.5421e-04 eta: 1:05:13 time: 0.5384 data_time: 0.0113 memory: 16131 loss: 0.7947 loss_prob: 0.4111 loss_thr: 0.3115 loss_db: 0.0721 2022/10/26 08:42:36 - mmengine - INFO - Epoch(train) [1107][55/63] lr: 3.5421e-04 eta: 1:05:13 time: 0.5539 data_time: 0.0214 memory: 16131 loss: 0.8336 loss_prob: 0.4295 loss_thr: 0.3294 loss_db: 0.0747 2022/10/26 08:42:39 - mmengine - INFO - Epoch(train) [1107][60/63] lr: 3.5421e-04 eta: 1:05:06 time: 0.5687 data_time: 0.0213 memory: 16131 loss: 0.9102 loss_prob: 0.4755 loss_thr: 0.3530 loss_db: 0.0817 2022/10/26 08:42:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:42:45 - mmengine - INFO - Epoch(train) [1108][5/63] lr: 3.5078e-04 eta: 1:05:06 time: 0.6979 data_time: 0.1840 memory: 16131 loss: 0.9520 loss_prob: 0.5108 loss_thr: 0.3480 loss_db: 0.0932 2022/10/26 08:42:48 - mmengine - INFO - Epoch(train) [1108][10/63] lr: 3.5078e-04 eta: 1:04:57 time: 0.7369 data_time: 0.1889 memory: 16131 loss: 0.8478 loss_prob: 0.4488 loss_thr: 0.3155 loss_db: 0.0835 2022/10/26 08:42:50 - mmengine - INFO - Epoch(train) [1108][15/63] lr: 3.5078e-04 eta: 1:04:57 time: 0.5304 data_time: 0.0108 memory: 16131 loss: 0.8160 loss_prob: 0.4274 loss_thr: 0.3159 loss_db: 0.0726 2022/10/26 08:42:53 - mmengine - INFO - Epoch(train) [1108][20/63] lr: 3.5078e-04 eta: 1:04:50 time: 0.5284 data_time: 0.0084 memory: 16131 loss: 0.8660 loss_prob: 0.4543 loss_thr: 0.3343 loss_db: 0.0775 2022/10/26 08:42:56 - mmengine - INFO - Epoch(train) [1108][25/63] lr: 3.5078e-04 eta: 1:04:50 time: 0.5570 data_time: 0.0300 memory: 16131 loss: 0.8553 loss_prob: 0.4387 loss_thr: 0.3406 loss_db: 0.0759 2022/10/26 08:42:59 - mmengine - INFO - Epoch(train) [1108][30/63] lr: 3.5078e-04 eta: 1:04:44 time: 0.5612 data_time: 0.0279 memory: 16131 loss: 0.8946 loss_prob: 0.4673 loss_thr: 0.3469 loss_db: 0.0804 2022/10/26 08:43:01 - mmengine - INFO - Epoch(train) [1108][35/63] lr: 3.5078e-04 eta: 1:04:44 time: 0.5234 data_time: 0.0106 memory: 16131 loss: 0.9351 loss_prob: 0.4895 loss_thr: 0.3587 loss_db: 0.0869 2022/10/26 08:43:04 - mmengine - INFO - Epoch(train) [1108][40/63] lr: 3.5078e-04 eta: 1:04:37 time: 0.5139 data_time: 0.0141 memory: 16131 loss: 0.9003 loss_prob: 0.4659 loss_thr: 0.3523 loss_db: 0.0820 2022/10/26 08:43:07 - mmengine - INFO - Epoch(train) [1108][45/63] lr: 3.5078e-04 eta: 1:04:37 time: 0.5354 data_time: 0.0088 memory: 16131 loss: 0.8627 loss_prob: 0.4509 loss_thr: 0.3343 loss_db: 0.0775 2022/10/26 08:43:09 - mmengine - INFO - Epoch(train) [1108][50/63] lr: 3.5078e-04 eta: 1:04:30 time: 0.5443 data_time: 0.0182 memory: 16131 loss: 0.8825 loss_prob: 0.4604 loss_thr: 0.3422 loss_db: 0.0799 2022/10/26 08:43:12 - mmengine - INFO - Epoch(train) [1108][55/63] lr: 3.5078e-04 eta: 1:04:30 time: 0.5249 data_time: 0.0215 memory: 16131 loss: 0.8683 loss_prob: 0.4474 loss_thr: 0.3424 loss_db: 0.0784 2022/10/26 08:43:15 - mmengine - INFO - Epoch(train) [1108][60/63] lr: 3.5078e-04 eta: 1:04:23 time: 0.5418 data_time: 0.0088 memory: 16131 loss: 0.8373 loss_prob: 0.4256 loss_thr: 0.3374 loss_db: 0.0743 2022/10/26 08:43:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:43:21 - mmengine - INFO - Epoch(train) [1109][5/63] lr: 3.4734e-04 eta: 1:04:23 time: 0.7512 data_time: 0.2122 memory: 16131 loss: 0.8610 loss_prob: 0.4420 loss_thr: 0.3437 loss_db: 0.0754 2022/10/26 08:43:24 - mmengine - INFO - Epoch(train) [1109][10/63] lr: 3.4734e-04 eta: 1:04:15 time: 0.8079 data_time: 0.2186 memory: 16131 loss: 0.8825 loss_prob: 0.4590 loss_thr: 0.3446 loss_db: 0.0789 2022/10/26 08:43:27 - mmengine - INFO - Epoch(train) [1109][15/63] lr: 3.4734e-04 eta: 1:04:15 time: 0.5382 data_time: 0.0129 memory: 16131 loss: 0.8529 loss_prob: 0.4318 loss_thr: 0.3431 loss_db: 0.0780 2022/10/26 08:43:29 - mmengine - INFO - Epoch(train) [1109][20/63] lr: 3.4734e-04 eta: 1:04:08 time: 0.4991 data_time: 0.0076 memory: 16131 loss: 0.8342 loss_prob: 0.4253 loss_thr: 0.3325 loss_db: 0.0764 2022/10/26 08:43:32 - mmengine - INFO - Epoch(train) [1109][25/63] lr: 3.4734e-04 eta: 1:04:08 time: 0.5306 data_time: 0.0309 memory: 16131 loss: 0.8380 loss_prob: 0.4301 loss_thr: 0.3313 loss_db: 0.0766 2022/10/26 08:43:34 - mmengine - INFO - Epoch(train) [1109][30/63] lr: 3.4734e-04 eta: 1:04:01 time: 0.5418 data_time: 0.0316 memory: 16131 loss: 0.8901 loss_prob: 0.4614 loss_thr: 0.3476 loss_db: 0.0811 2022/10/26 08:43:37 - mmengine - INFO - Epoch(train) [1109][35/63] lr: 3.4734e-04 eta: 1:04:01 time: 0.5148 data_time: 0.0086 memory: 16131 loss: 0.8730 loss_prob: 0.4595 loss_thr: 0.3353 loss_db: 0.0782 2022/10/26 08:43:40 - mmengine - INFO - Epoch(train) [1109][40/63] lr: 3.4734e-04 eta: 1:03:54 time: 0.5210 data_time: 0.0093 memory: 16131 loss: 0.8373 loss_prob: 0.4371 loss_thr: 0.3259 loss_db: 0.0743 2022/10/26 08:43:42 - mmengine - INFO - Epoch(train) [1109][45/63] lr: 3.4734e-04 eta: 1:03:54 time: 0.5099 data_time: 0.0082 memory: 16131 loss: 0.8915 loss_prob: 0.4708 loss_thr: 0.3405 loss_db: 0.0803 2022/10/26 08:43:45 - mmengine - INFO - Epoch(train) [1109][50/63] lr: 3.4734e-04 eta: 1:03:48 time: 0.5456 data_time: 0.0203 memory: 16131 loss: 0.8537 loss_prob: 0.4537 loss_thr: 0.3234 loss_db: 0.0765 2022/10/26 08:43:48 - mmengine - INFO - Epoch(train) [1109][55/63] lr: 3.4734e-04 eta: 1:03:48 time: 0.5532 data_time: 0.0202 memory: 16131 loss: 0.8576 loss_prob: 0.4520 loss_thr: 0.3264 loss_db: 0.0792 2022/10/26 08:43:50 - mmengine - INFO - Epoch(train) [1109][60/63] lr: 3.4734e-04 eta: 1:03:41 time: 0.5078 data_time: 0.0075 memory: 16131 loss: 0.8953 loss_prob: 0.4746 loss_thr: 0.3370 loss_db: 0.0837 2022/10/26 08:43:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:43:57 - mmengine - INFO - Epoch(train) [1110][5/63] lr: 3.4391e-04 eta: 1:03:41 time: 0.7444 data_time: 0.2226 memory: 16131 loss: 0.9240 loss_prob: 0.4858 loss_thr: 0.3540 loss_db: 0.0841 2022/10/26 08:43:59 - mmengine - INFO - Epoch(train) [1110][10/63] lr: 3.4391e-04 eta: 1:03:32 time: 0.7473 data_time: 0.2191 memory: 16131 loss: 0.9478 loss_prob: 0.5027 loss_thr: 0.3582 loss_db: 0.0869 2022/10/26 08:44:02 - mmengine - INFO - Epoch(train) [1110][15/63] lr: 3.4391e-04 eta: 1:03:32 time: 0.5413 data_time: 0.0055 memory: 16131 loss: 0.8612 loss_prob: 0.4523 loss_thr: 0.3305 loss_db: 0.0785 2022/10/26 08:44:04 - mmengine - INFO - Epoch(train) [1110][20/63] lr: 3.4391e-04 eta: 1:03:25 time: 0.5385 data_time: 0.0077 memory: 16131 loss: 0.7585 loss_prob: 0.3923 loss_thr: 0.2970 loss_db: 0.0691 2022/10/26 08:44:07 - mmengine - INFO - Epoch(train) [1110][25/63] lr: 3.4391e-04 eta: 1:03:25 time: 0.5266 data_time: 0.0311 memory: 16131 loss: 0.8000 loss_prob: 0.4155 loss_thr: 0.3119 loss_db: 0.0726 2022/10/26 08:44:10 - mmengine - INFO - Epoch(train) [1110][30/63] lr: 3.4391e-04 eta: 1:03:18 time: 0.5489 data_time: 0.0294 memory: 16131 loss: 0.8900 loss_prob: 0.4604 loss_thr: 0.3494 loss_db: 0.0802 2022/10/26 08:44:13 - mmengine - INFO - Epoch(train) [1110][35/63] lr: 3.4391e-04 eta: 1:03:18 time: 0.5306 data_time: 0.0084 memory: 16131 loss: 0.8623 loss_prob: 0.4444 loss_thr: 0.3405 loss_db: 0.0774 2022/10/26 08:44:15 - mmengine - INFO - Epoch(train) [1110][40/63] lr: 3.4391e-04 eta: 1:03:12 time: 0.5073 data_time: 0.0106 memory: 16131 loss: 0.8919 loss_prob: 0.4682 loss_thr: 0.3423 loss_db: 0.0814 2022/10/26 08:44:18 - mmengine - INFO - Epoch(train) [1110][45/63] lr: 3.4391e-04 eta: 1:03:12 time: 0.5109 data_time: 0.0154 memory: 16131 loss: 0.8711 loss_prob: 0.4559 loss_thr: 0.3346 loss_db: 0.0806 2022/10/26 08:44:20 - mmengine - INFO - Epoch(train) [1110][50/63] lr: 3.4391e-04 eta: 1:03:05 time: 0.5407 data_time: 0.0258 memory: 16131 loss: 0.8375 loss_prob: 0.4336 loss_thr: 0.3276 loss_db: 0.0764 2022/10/26 08:44:23 - mmengine - INFO - Epoch(train) [1110][55/63] lr: 3.4391e-04 eta: 1:03:05 time: 0.5295 data_time: 0.0199 memory: 16131 loss: 0.8548 loss_prob: 0.4392 loss_thr: 0.3396 loss_db: 0.0760 2022/10/26 08:44:25 - mmengine - INFO - Epoch(train) [1110][60/63] lr: 3.4391e-04 eta: 1:02:58 time: 0.5024 data_time: 0.0079 memory: 16131 loss: 0.9464 loss_prob: 0.4926 loss_thr: 0.3678 loss_db: 0.0860 2022/10/26 08:44:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:44:31 - mmengine - INFO - Epoch(train) [1111][5/63] lr: 3.4047e-04 eta: 1:02:58 time: 0.6927 data_time: 0.1886 memory: 16131 loss: 0.8811 loss_prob: 0.4614 loss_thr: 0.3385 loss_db: 0.0811 2022/10/26 08:44:34 - mmengine - INFO - Epoch(train) [1111][10/63] lr: 3.4047e-04 eta: 1:02:49 time: 0.7550 data_time: 0.2001 memory: 16131 loss: 0.8214 loss_prob: 0.4226 loss_thr: 0.3246 loss_db: 0.0742 2022/10/26 08:44:37 - mmengine - INFO - Epoch(train) [1111][15/63] lr: 3.4047e-04 eta: 1:02:49 time: 0.5445 data_time: 0.0191 memory: 16131 loss: 0.8185 loss_prob: 0.4225 loss_thr: 0.3212 loss_db: 0.0748 2022/10/26 08:44:40 - mmengine - INFO - Epoch(train) [1111][20/63] lr: 3.4047e-04 eta: 1:02:43 time: 0.6093 data_time: 0.0082 memory: 16131 loss: 0.9368 loss_prob: 0.5042 loss_thr: 0.3473 loss_db: 0.0853 2022/10/26 08:44:43 - mmengine - INFO - Epoch(train) [1111][25/63] lr: 3.4047e-04 eta: 1:02:43 time: 0.6196 data_time: 0.0228 memory: 16131 loss: 0.9539 loss_prob: 0.5115 loss_thr: 0.3568 loss_db: 0.0856 2022/10/26 08:44:46 - mmengine - INFO - Epoch(train) [1111][30/63] lr: 3.4047e-04 eta: 1:02:36 time: 0.5337 data_time: 0.0362 memory: 16131 loss: 0.8331 loss_prob: 0.4307 loss_thr: 0.3275 loss_db: 0.0749 2022/10/26 08:44:48 - mmengine - INFO - Epoch(train) [1111][35/63] lr: 3.4047e-04 eta: 1:02:36 time: 0.5368 data_time: 0.0320 memory: 16131 loss: 0.8921 loss_prob: 0.4645 loss_thr: 0.3456 loss_db: 0.0820 2022/10/26 08:44:51 - mmengine - INFO - Epoch(train) [1111][40/63] lr: 3.4047e-04 eta: 1:02:29 time: 0.5190 data_time: 0.0160 memory: 16131 loss: 0.8792 loss_prob: 0.4545 loss_thr: 0.3441 loss_db: 0.0806 2022/10/26 08:44:54 - mmengine - INFO - Epoch(train) [1111][45/63] lr: 3.4047e-04 eta: 1:02:29 time: 0.5290 data_time: 0.0077 memory: 16131 loss: 0.7930 loss_prob: 0.4051 loss_thr: 0.3168 loss_db: 0.0710 2022/10/26 08:44:56 - mmengine - INFO - Epoch(train) [1111][50/63] lr: 3.4047e-04 eta: 1:02:22 time: 0.5335 data_time: 0.0136 memory: 16131 loss: 0.8182 loss_prob: 0.4181 loss_thr: 0.3273 loss_db: 0.0728 2022/10/26 08:44:59 - mmengine - INFO - Epoch(train) [1111][55/63] lr: 3.4047e-04 eta: 1:02:22 time: 0.5130 data_time: 0.0202 memory: 16131 loss: 0.8558 loss_prob: 0.4457 loss_thr: 0.3321 loss_db: 0.0780 2022/10/26 08:45:02 - mmengine - INFO - Epoch(train) [1111][60/63] lr: 3.4047e-04 eta: 1:02:16 time: 0.5274 data_time: 0.0165 memory: 16131 loss: 0.8892 loss_prob: 0.4747 loss_thr: 0.3306 loss_db: 0.0839 2022/10/26 08:45:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:45:08 - mmengine - INFO - Epoch(train) [1112][5/63] lr: 3.3702e-04 eta: 1:02:16 time: 0.7453 data_time: 0.1965 memory: 16131 loss: 0.8291 loss_prob: 0.4361 loss_thr: 0.3178 loss_db: 0.0752 2022/10/26 08:45:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:45:11 - mmengine - INFO - Epoch(train) [1112][10/63] lr: 3.3702e-04 eta: 1:02:07 time: 0.7653 data_time: 0.2046 memory: 16131 loss: 0.8586 loss_prob: 0.4491 loss_thr: 0.3329 loss_db: 0.0765 2022/10/26 08:45:13 - mmengine - INFO - Epoch(train) [1112][15/63] lr: 3.3702e-04 eta: 1:02:07 time: 0.5173 data_time: 0.0133 memory: 16131 loss: 0.9180 loss_prob: 0.4962 loss_thr: 0.3396 loss_db: 0.0822 2022/10/26 08:45:16 - mmengine - INFO - Epoch(train) [1112][20/63] lr: 3.3702e-04 eta: 1:02:00 time: 0.5204 data_time: 0.0062 memory: 16131 loss: 0.9672 loss_prob: 0.5274 loss_thr: 0.3533 loss_db: 0.0865 2022/10/26 08:45:18 - mmengine - INFO - Epoch(train) [1112][25/63] lr: 3.3702e-04 eta: 1:02:00 time: 0.5250 data_time: 0.0291 memory: 16131 loss: 0.9007 loss_prob: 0.4789 loss_thr: 0.3405 loss_db: 0.0813 2022/10/26 08:45:21 - mmengine - INFO - Epoch(train) [1112][30/63] lr: 3.3702e-04 eta: 1:01:53 time: 0.5301 data_time: 0.0302 memory: 16131 loss: 0.8243 loss_prob: 0.4331 loss_thr: 0.3142 loss_db: 0.0770 2022/10/26 08:45:24 - mmengine - INFO - Epoch(train) [1112][35/63] lr: 3.3702e-04 eta: 1:01:53 time: 0.5290 data_time: 0.0105 memory: 16131 loss: 0.8202 loss_prob: 0.4203 loss_thr: 0.3254 loss_db: 0.0745 2022/10/26 08:45:26 - mmengine - INFO - Epoch(train) [1112][40/63] lr: 3.3702e-04 eta: 1:01:47 time: 0.5224 data_time: 0.0087 memory: 16131 loss: 0.8585 loss_prob: 0.4481 loss_thr: 0.3320 loss_db: 0.0784 2022/10/26 08:45:29 - mmengine - INFO - Epoch(train) [1112][45/63] lr: 3.3702e-04 eta: 1:01:47 time: 0.5193 data_time: 0.0110 memory: 16131 loss: 0.8834 loss_prob: 0.4666 loss_thr: 0.3355 loss_db: 0.0814 2022/10/26 08:45:32 - mmengine - INFO - Epoch(train) [1112][50/63] lr: 3.3702e-04 eta: 1:01:40 time: 0.5520 data_time: 0.0237 memory: 16131 loss: 0.8721 loss_prob: 0.4609 loss_thr: 0.3329 loss_db: 0.0783 2022/10/26 08:45:34 - mmengine - INFO - Epoch(train) [1112][55/63] lr: 3.3702e-04 eta: 1:01:40 time: 0.5478 data_time: 0.0214 memory: 16131 loss: 0.8541 loss_prob: 0.4500 loss_thr: 0.3265 loss_db: 0.0776 2022/10/26 08:45:37 - mmengine - INFO - Epoch(train) [1112][60/63] lr: 3.3702e-04 eta: 1:01:33 time: 0.5113 data_time: 0.0085 memory: 16131 loss: 0.8049 loss_prob: 0.4142 loss_thr: 0.3180 loss_db: 0.0727 2022/10/26 08:45:38 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:45:43 - mmengine - INFO - Epoch(train) [1113][5/63] lr: 3.3358e-04 eta: 1:01:33 time: 0.6852 data_time: 0.1852 memory: 16131 loss: 0.8472 loss_prob: 0.4374 loss_thr: 0.3329 loss_db: 0.0769 2022/10/26 08:45:46 - mmengine - INFO - Epoch(train) [1113][10/63] lr: 3.3358e-04 eta: 1:01:24 time: 0.7261 data_time: 0.1944 memory: 16131 loss: 0.8873 loss_prob: 0.4599 loss_thr: 0.3457 loss_db: 0.0817 2022/10/26 08:45:48 - mmengine - INFO - Epoch(train) [1113][15/63] lr: 3.3358e-04 eta: 1:01:24 time: 0.5308 data_time: 0.0167 memory: 16131 loss: 0.8527 loss_prob: 0.4451 loss_thr: 0.3290 loss_db: 0.0785 2022/10/26 08:45:51 - mmengine - INFO - Epoch(train) [1113][20/63] lr: 3.3358e-04 eta: 1:01:17 time: 0.5016 data_time: 0.0064 memory: 16131 loss: 0.8347 loss_prob: 0.4348 loss_thr: 0.3233 loss_db: 0.0766 2022/10/26 08:45:53 - mmengine - INFO - Epoch(train) [1113][25/63] lr: 3.3358e-04 eta: 1:01:17 time: 0.5278 data_time: 0.0307 memory: 16131 loss: 0.8979 loss_prob: 0.4698 loss_thr: 0.3475 loss_db: 0.0806 2022/10/26 08:45:56 - mmengine - INFO - Epoch(train) [1113][30/63] lr: 3.3358e-04 eta: 1:01:11 time: 0.5382 data_time: 0.0362 memory: 16131 loss: 0.8981 loss_prob: 0.4686 loss_thr: 0.3515 loss_db: 0.0780 2022/10/26 08:45:59 - mmengine - INFO - Epoch(train) [1113][35/63] lr: 3.3358e-04 eta: 1:01:11 time: 0.5271 data_time: 0.0121 memory: 16131 loss: 0.8070 loss_prob: 0.4152 loss_thr: 0.3209 loss_db: 0.0709 2022/10/26 08:46:01 - mmengine - INFO - Epoch(train) [1113][40/63] lr: 3.3358e-04 eta: 1:01:04 time: 0.5166 data_time: 0.0111 memory: 16131 loss: 0.8150 loss_prob: 0.4189 loss_thr: 0.3225 loss_db: 0.0736 2022/10/26 08:46:04 - mmengine - INFO - Epoch(train) [1113][45/63] lr: 3.3358e-04 eta: 1:01:04 time: 0.5260 data_time: 0.0112 memory: 16131 loss: 0.8177 loss_prob: 0.4269 loss_thr: 0.3161 loss_db: 0.0747 2022/10/26 08:46:07 - mmengine - INFO - Epoch(train) [1113][50/63] lr: 3.3358e-04 eta: 1:00:57 time: 0.5518 data_time: 0.0191 memory: 16131 loss: 0.7983 loss_prob: 0.4154 loss_thr: 0.3113 loss_db: 0.0716 2022/10/26 08:46:09 - mmengine - INFO - Epoch(train) [1113][55/63] lr: 3.3358e-04 eta: 1:00:57 time: 0.5404 data_time: 0.0228 memory: 16131 loss: 0.8966 loss_prob: 0.4622 loss_thr: 0.3561 loss_db: 0.0784 2022/10/26 08:46:12 - mmengine - INFO - Epoch(train) [1113][60/63] lr: 3.3358e-04 eta: 1:00:50 time: 0.5172 data_time: 0.0101 memory: 16131 loss: 0.8944 loss_prob: 0.4643 loss_thr: 0.3499 loss_db: 0.0801 2022/10/26 08:46:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:46:18 - mmengine - INFO - Epoch(train) [1114][5/63] lr: 3.3012e-04 eta: 1:00:50 time: 0.6716 data_time: 0.1667 memory: 16131 loss: 0.8823 loss_prob: 0.4606 loss_thr: 0.3437 loss_db: 0.0780 2022/10/26 08:46:20 - mmengine - INFO - Epoch(train) [1114][10/63] lr: 3.3012e-04 eta: 1:00:42 time: 0.6997 data_time: 0.1745 memory: 16131 loss: 0.8767 loss_prob: 0.4545 loss_thr: 0.3422 loss_db: 0.0801 2022/10/26 08:46:23 - mmengine - INFO - Epoch(train) [1114][15/63] lr: 3.3012e-04 eta: 1:00:42 time: 0.5384 data_time: 0.0287 memory: 16131 loss: 0.8811 loss_prob: 0.4556 loss_thr: 0.3435 loss_db: 0.0820 2022/10/26 08:46:25 - mmengine - INFO - Epoch(train) [1114][20/63] lr: 3.3012e-04 eta: 1:00:35 time: 0.5101 data_time: 0.0209 memory: 16131 loss: 0.8830 loss_prob: 0.4617 loss_thr: 0.3403 loss_db: 0.0809 2022/10/26 08:46:28 - mmengine - INFO - Epoch(train) [1114][25/63] lr: 3.3012e-04 eta: 1:00:35 time: 0.4834 data_time: 0.0048 memory: 16131 loss: 0.8415 loss_prob: 0.4442 loss_thr: 0.3203 loss_db: 0.0769 2022/10/26 08:46:30 - mmengine - INFO - Epoch(train) [1114][30/63] lr: 3.3012e-04 eta: 1:00:28 time: 0.4881 data_time: 0.0129 memory: 16131 loss: 0.8411 loss_prob: 0.4410 loss_thr: 0.3247 loss_db: 0.0754 2022/10/26 08:46:33 - mmengine - INFO - Epoch(train) [1114][35/63] lr: 3.3012e-04 eta: 1:00:28 time: 0.4995 data_time: 0.0173 memory: 16131 loss: 0.8492 loss_prob: 0.4351 loss_thr: 0.3385 loss_db: 0.0756 2022/10/26 08:46:35 - mmengine - INFO - Epoch(train) [1114][40/63] lr: 3.3012e-04 eta: 1:00:21 time: 0.5014 data_time: 0.0183 memory: 16131 loss: 0.8159 loss_prob: 0.4129 loss_thr: 0.3297 loss_db: 0.0733 2022/10/26 08:46:38 - mmengine - INFO - Epoch(train) [1114][45/63] lr: 3.3012e-04 eta: 1:00:21 time: 0.5002 data_time: 0.0147 memory: 16131 loss: 0.7681 loss_prob: 0.3908 loss_thr: 0.3075 loss_db: 0.0698 2022/10/26 08:46:41 - mmengine - INFO - Epoch(train) [1114][50/63] lr: 3.3012e-04 eta: 1:00:14 time: 0.5407 data_time: 0.0062 memory: 16131 loss: 0.7909 loss_prob: 0.4092 loss_thr: 0.3097 loss_db: 0.0720 2022/10/26 08:46:43 - mmengine - INFO - Epoch(train) [1114][55/63] lr: 3.3012e-04 eta: 1:00:14 time: 0.5395 data_time: 0.0146 memory: 16131 loss: 0.9109 loss_prob: 0.4850 loss_thr: 0.3427 loss_db: 0.0831 2022/10/26 08:46:46 - mmengine - INFO - Epoch(train) [1114][60/63] lr: 3.3012e-04 eta: 1:00:08 time: 0.5028 data_time: 0.0196 memory: 16131 loss: 0.9154 loss_prob: 0.4873 loss_thr: 0.3439 loss_db: 0.0842 2022/10/26 08:46:47 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:46:51 - mmengine - INFO - Epoch(train) [1115][5/63] lr: 3.2667e-04 eta: 1:00:08 time: 0.6598 data_time: 0.1687 memory: 16131 loss: 0.9490 loss_prob: 0.5073 loss_thr: 0.3543 loss_db: 0.0874 2022/10/26 08:46:54 - mmengine - INFO - Epoch(train) [1115][10/63] lr: 3.2667e-04 eta: 0:59:59 time: 0.7076 data_time: 0.1799 memory: 16131 loss: 0.9633 loss_prob: 0.5166 loss_thr: 0.3590 loss_db: 0.0877 2022/10/26 08:46:57 - mmengine - INFO - Epoch(train) [1115][15/63] lr: 3.2667e-04 eta: 0:59:59 time: 0.5428 data_time: 0.0257 memory: 16131 loss: 0.9063 loss_prob: 0.4776 loss_thr: 0.3457 loss_db: 0.0830 2022/10/26 08:46:59 - mmengine - INFO - Epoch(train) [1115][20/63] lr: 3.2667e-04 eta: 0:59:52 time: 0.5135 data_time: 0.0075 memory: 16131 loss: 0.8584 loss_prob: 0.4410 loss_thr: 0.3382 loss_db: 0.0792 2022/10/26 08:47:02 - mmengine - INFO - Epoch(train) [1115][25/63] lr: 3.2667e-04 eta: 0:59:52 time: 0.5367 data_time: 0.0240 memory: 16131 loss: 0.8017 loss_prob: 0.4131 loss_thr: 0.3150 loss_db: 0.0736 2022/10/26 08:47:05 - mmengine - INFO - Epoch(train) [1115][30/63] lr: 3.2667e-04 eta: 0:59:45 time: 0.5205 data_time: 0.0288 memory: 16131 loss: 0.8114 loss_prob: 0.4253 loss_thr: 0.3143 loss_db: 0.0717 2022/10/26 08:47:07 - mmengine - INFO - Epoch(train) [1115][35/63] lr: 3.2667e-04 eta: 0:59:45 time: 0.5144 data_time: 0.0140 memory: 16131 loss: 0.8334 loss_prob: 0.4348 loss_thr: 0.3248 loss_db: 0.0738 2022/10/26 08:47:10 - mmengine - INFO - Epoch(train) [1115][40/63] lr: 3.2667e-04 eta: 0:59:39 time: 0.5144 data_time: 0.0065 memory: 16131 loss: 0.7963 loss_prob: 0.4070 loss_thr: 0.3175 loss_db: 0.0718 2022/10/26 08:47:12 - mmengine - INFO - Epoch(train) [1115][45/63] lr: 3.2667e-04 eta: 0:59:39 time: 0.5047 data_time: 0.0071 memory: 16131 loss: 0.8474 loss_prob: 0.4367 loss_thr: 0.3350 loss_db: 0.0756 2022/10/26 08:47:15 - mmengine - INFO - Epoch(train) [1115][50/63] lr: 3.2667e-04 eta: 0:59:32 time: 0.5221 data_time: 0.0204 memory: 16131 loss: 0.9006 loss_prob: 0.4733 loss_thr: 0.3454 loss_db: 0.0819 2022/10/26 08:47:18 - mmengine - INFO - Epoch(train) [1115][55/63] lr: 3.2667e-04 eta: 0:59:32 time: 0.5382 data_time: 0.0222 memory: 16131 loss: 0.9116 loss_prob: 0.4801 loss_thr: 0.3482 loss_db: 0.0834 2022/10/26 08:47:20 - mmengine - INFO - Epoch(train) [1115][60/63] lr: 3.2667e-04 eta: 0:59:25 time: 0.5426 data_time: 0.0106 memory: 16131 loss: 0.9785 loss_prob: 0.5243 loss_thr: 0.3629 loss_db: 0.0913 2022/10/26 08:47:22 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:47:27 - mmengine - INFO - Epoch(train) [1116][5/63] lr: 3.2321e-04 eta: 0:59:25 time: 0.7319 data_time: 0.1917 memory: 16131 loss: 0.7698 loss_prob: 0.4030 loss_thr: 0.2970 loss_db: 0.0699 2022/10/26 08:47:29 - mmengine - INFO - Epoch(train) [1116][10/63] lr: 3.2321e-04 eta: 0:59:16 time: 0.7335 data_time: 0.1905 memory: 16131 loss: 0.8033 loss_prob: 0.4183 loss_thr: 0.3135 loss_db: 0.0714 2022/10/26 08:47:32 - mmengine - INFO - Epoch(train) [1116][15/63] lr: 3.2321e-04 eta: 0:59:16 time: 0.4930 data_time: 0.0051 memory: 16131 loss: 0.8213 loss_prob: 0.4271 loss_thr: 0.3193 loss_db: 0.0749 2022/10/26 08:47:34 - mmengine - INFO - Epoch(train) [1116][20/63] lr: 3.2321e-04 eta: 0:59:10 time: 0.4913 data_time: 0.0053 memory: 16131 loss: 0.8384 loss_prob: 0.4420 loss_thr: 0.3203 loss_db: 0.0761 2022/10/26 08:47:37 - mmengine - INFO - Epoch(train) [1116][25/63] lr: 3.2321e-04 eta: 0:59:10 time: 0.5373 data_time: 0.0366 memory: 16131 loss: 0.9515 loss_prob: 0.5000 loss_thr: 0.3647 loss_db: 0.0868 2022/10/26 08:47:40 - mmengine - INFO - Epoch(train) [1116][30/63] lr: 3.2321e-04 eta: 0:59:03 time: 0.5486 data_time: 0.0373 memory: 16131 loss: 0.9143 loss_prob: 0.4718 loss_thr: 0.3597 loss_db: 0.0828 2022/10/26 08:47:42 - mmengine - INFO - Epoch(train) [1116][35/63] lr: 3.2321e-04 eta: 0:59:03 time: 0.5212 data_time: 0.0055 memory: 16131 loss: 0.8212 loss_prob: 0.4232 loss_thr: 0.3228 loss_db: 0.0751 2022/10/26 08:47:45 - mmengine - INFO - Epoch(train) [1116][40/63] lr: 3.2321e-04 eta: 0:58:56 time: 0.5130 data_time: 0.0057 memory: 16131 loss: 0.8317 loss_prob: 0.4404 loss_thr: 0.3133 loss_db: 0.0780 2022/10/26 08:47:47 - mmengine - INFO - Epoch(train) [1116][45/63] lr: 3.2321e-04 eta: 0:58:56 time: 0.5164 data_time: 0.0066 memory: 16131 loss: 0.8766 loss_prob: 0.4667 loss_thr: 0.3289 loss_db: 0.0810 2022/10/26 08:47:50 - mmengine - INFO - Epoch(train) [1116][50/63] lr: 3.2321e-04 eta: 0:58:49 time: 0.5629 data_time: 0.0207 memory: 16131 loss: 0.8897 loss_prob: 0.4597 loss_thr: 0.3493 loss_db: 0.0807 2022/10/26 08:47:53 - mmengine - INFO - Epoch(train) [1116][55/63] lr: 3.2321e-04 eta: 0:58:49 time: 0.6104 data_time: 0.0204 memory: 16131 loss: 0.8486 loss_prob: 0.4253 loss_thr: 0.3465 loss_db: 0.0768 2022/10/26 08:47:56 - mmengine - INFO - Epoch(train) [1116][60/63] lr: 3.2321e-04 eta: 0:58:43 time: 0.5856 data_time: 0.0065 memory: 16131 loss: 0.8601 loss_prob: 0.4413 loss_thr: 0.3408 loss_db: 0.0780 2022/10/26 08:47:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:48:03 - mmengine - INFO - Epoch(train) [1117][5/63] lr: 3.1975e-04 eta: 0:58:43 time: 0.7749 data_time: 0.2125 memory: 16131 loss: 0.8882 loss_prob: 0.4689 loss_thr: 0.3382 loss_db: 0.0810 2022/10/26 08:48:05 - mmengine - INFO - Epoch(train) [1117][10/63] lr: 3.1975e-04 eta: 0:58:34 time: 0.7756 data_time: 0.2127 memory: 16131 loss: 0.8546 loss_prob: 0.4385 loss_thr: 0.3384 loss_db: 0.0777 2022/10/26 08:48:08 - mmengine - INFO - Epoch(train) [1117][15/63] lr: 3.1975e-04 eta: 0:58:34 time: 0.5076 data_time: 0.0090 memory: 16131 loss: 0.7725 loss_prob: 0.3912 loss_thr: 0.3122 loss_db: 0.0691 2022/10/26 08:48:11 - mmengine - INFO - Epoch(train) [1117][20/63] lr: 3.1975e-04 eta: 0:58:27 time: 0.5123 data_time: 0.0091 memory: 16131 loss: 0.8012 loss_prob: 0.4113 loss_thr: 0.3190 loss_db: 0.0709 2022/10/26 08:48:13 - mmengine - INFO - Epoch(train) [1117][25/63] lr: 3.1975e-04 eta: 0:58:27 time: 0.5223 data_time: 0.0251 memory: 16131 loss: 0.8957 loss_prob: 0.4746 loss_thr: 0.3413 loss_db: 0.0798 2022/10/26 08:48:16 - mmengine - INFO - Epoch(train) [1117][30/63] lr: 3.1975e-04 eta: 0:58:20 time: 0.5301 data_time: 0.0355 memory: 16131 loss: 0.8585 loss_prob: 0.4526 loss_thr: 0.3284 loss_db: 0.0775 2022/10/26 08:48:18 - mmengine - INFO - Epoch(train) [1117][35/63] lr: 3.1975e-04 eta: 0:58:20 time: 0.5088 data_time: 0.0172 memory: 16131 loss: 0.7818 loss_prob: 0.4058 loss_thr: 0.3047 loss_db: 0.0713 2022/10/26 08:48:21 - mmengine - INFO - Epoch(train) [1117][40/63] lr: 3.1975e-04 eta: 0:58:14 time: 0.5197 data_time: 0.0069 memory: 16131 loss: 0.8477 loss_prob: 0.4437 loss_thr: 0.3282 loss_db: 0.0758 2022/10/26 08:48:24 - mmengine - INFO - Epoch(train) [1117][45/63] lr: 3.1975e-04 eta: 0:58:14 time: 0.5188 data_time: 0.0075 memory: 16131 loss: 0.8984 loss_prob: 0.4684 loss_thr: 0.3495 loss_db: 0.0805 2022/10/26 08:48:26 - mmengine - INFO - Epoch(train) [1117][50/63] lr: 3.1975e-04 eta: 0:58:07 time: 0.5133 data_time: 0.0280 memory: 16131 loss: 0.8904 loss_prob: 0.4657 loss_thr: 0.3433 loss_db: 0.0813 2022/10/26 08:48:29 - mmengine - INFO - Epoch(train) [1117][55/63] lr: 3.1975e-04 eta: 0:58:07 time: 0.5122 data_time: 0.0271 memory: 16131 loss: 0.8500 loss_prob: 0.4466 loss_thr: 0.3246 loss_db: 0.0787 2022/10/26 08:48:31 - mmengine - INFO - Epoch(train) [1117][60/63] lr: 3.1975e-04 eta: 0:58:00 time: 0.5125 data_time: 0.0051 memory: 16131 loss: 0.8541 loss_prob: 0.4556 loss_thr: 0.3189 loss_db: 0.0797 2022/10/26 08:48:33 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:48:37 - mmengine - INFO - Epoch(train) [1118][5/63] lr: 3.1628e-04 eta: 0:58:00 time: 0.7012 data_time: 0.1993 memory: 16131 loss: 0.8349 loss_prob: 0.4309 loss_thr: 0.3291 loss_db: 0.0748 2022/10/26 08:48:40 - mmengine - INFO - Epoch(train) [1118][10/63] lr: 3.1628e-04 eta: 0:57:51 time: 0.7494 data_time: 0.2023 memory: 16131 loss: 0.8445 loss_prob: 0.4432 loss_thr: 0.3246 loss_db: 0.0767 2022/10/26 08:48:43 - mmengine - INFO - Epoch(train) [1118][15/63] lr: 3.1628e-04 eta: 0:57:51 time: 0.5356 data_time: 0.0093 memory: 16131 loss: 0.8644 loss_prob: 0.4543 loss_thr: 0.3317 loss_db: 0.0784 2022/10/26 08:48:45 - mmengine - INFO - Epoch(train) [1118][20/63] lr: 3.1628e-04 eta: 0:57:45 time: 0.5367 data_time: 0.0050 memory: 16131 loss: 0.8004 loss_prob: 0.4041 loss_thr: 0.3269 loss_db: 0.0694 2022/10/26 08:48:48 - mmengine - INFO - Epoch(train) [1118][25/63] lr: 3.1628e-04 eta: 0:57:45 time: 0.5690 data_time: 0.0271 memory: 16131 loss: 0.7816 loss_prob: 0.3916 loss_thr: 0.3216 loss_db: 0.0684 2022/10/26 08:48:51 - mmengine - INFO - Epoch(train) [1118][30/63] lr: 3.1628e-04 eta: 0:57:38 time: 0.5691 data_time: 0.0332 memory: 16131 loss: 0.8433 loss_prob: 0.4392 loss_thr: 0.3269 loss_db: 0.0773 2022/10/26 08:48:54 - mmengine - INFO - Epoch(train) [1118][35/63] lr: 3.1628e-04 eta: 0:57:38 time: 0.5246 data_time: 0.0107 memory: 16131 loss: 0.9124 loss_prob: 0.4808 loss_thr: 0.3481 loss_db: 0.0835 2022/10/26 08:48:56 - mmengine - INFO - Epoch(train) [1118][40/63] lr: 3.1628e-04 eta: 0:57:31 time: 0.4935 data_time: 0.0043 memory: 16131 loss: 0.8730 loss_prob: 0.4509 loss_thr: 0.3428 loss_db: 0.0792 2022/10/26 08:48:59 - mmengine - INFO - Epoch(train) [1118][45/63] lr: 3.1628e-04 eta: 0:57:31 time: 0.4934 data_time: 0.0050 memory: 16131 loss: 0.8437 loss_prob: 0.4405 loss_thr: 0.3272 loss_db: 0.0760 2022/10/26 08:49:01 - mmengine - INFO - Epoch(train) [1118][50/63] lr: 3.1628e-04 eta: 0:57:24 time: 0.5089 data_time: 0.0202 memory: 16131 loss: 0.9129 loss_prob: 0.4827 loss_thr: 0.3485 loss_db: 0.0818 2022/10/26 08:49:04 - mmengine - INFO - Epoch(train) [1118][55/63] lr: 3.1628e-04 eta: 0:57:24 time: 0.5185 data_time: 0.0250 memory: 16131 loss: 0.9370 loss_prob: 0.4900 loss_thr: 0.3602 loss_db: 0.0867 2022/10/26 08:49:06 - mmengine - INFO - Epoch(train) [1118][60/63] lr: 3.1628e-04 eta: 0:57:18 time: 0.5274 data_time: 0.0113 memory: 16131 loss: 0.8575 loss_prob: 0.4371 loss_thr: 0.3411 loss_db: 0.0793 2022/10/26 08:49:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:49:13 - mmengine - INFO - Epoch(train) [1119][5/63] lr: 3.1280e-04 eta: 0:57:18 time: 0.7581 data_time: 0.1479 memory: 16131 loss: 0.8072 loss_prob: 0.4094 loss_thr: 0.3271 loss_db: 0.0707 2022/10/26 08:49:16 - mmengine - INFO - Epoch(train) [1119][10/63] lr: 3.1280e-04 eta: 0:57:09 time: 0.7850 data_time: 0.1575 memory: 16131 loss: 0.7784 loss_prob: 0.4051 loss_thr: 0.3031 loss_db: 0.0703 2022/10/26 08:49:18 - mmengine - INFO - Epoch(train) [1119][15/63] lr: 3.1280e-04 eta: 0:57:09 time: 0.5570 data_time: 0.0153 memory: 16131 loss: 0.8366 loss_prob: 0.4382 loss_thr: 0.3213 loss_db: 0.0771 2022/10/26 08:49:21 - mmengine - INFO - Epoch(train) [1119][20/63] lr: 3.1280e-04 eta: 0:57:02 time: 0.5348 data_time: 0.0127 memory: 16131 loss: 0.8831 loss_prob: 0.4620 loss_thr: 0.3387 loss_db: 0.0823 2022/10/26 08:49:24 - mmengine - INFO - Epoch(train) [1119][25/63] lr: 3.1280e-04 eta: 0:57:02 time: 0.5564 data_time: 0.0160 memory: 16131 loss: 0.9001 loss_prob: 0.4686 loss_thr: 0.3513 loss_db: 0.0802 2022/10/26 08:49:27 - mmengine - INFO - Epoch(train) [1119][30/63] lr: 3.1280e-04 eta: 0:56:55 time: 0.5791 data_time: 0.0224 memory: 16131 loss: 0.8917 loss_prob: 0.4665 loss_thr: 0.3469 loss_db: 0.0783 2022/10/26 08:49:29 - mmengine - INFO - Epoch(train) [1119][35/63] lr: 3.1280e-04 eta: 0:56:55 time: 0.5346 data_time: 0.0295 memory: 16131 loss: 0.8603 loss_prob: 0.4550 loss_thr: 0.3259 loss_db: 0.0794 2022/10/26 08:49:32 - mmengine - INFO - Epoch(train) [1119][40/63] lr: 3.1280e-04 eta: 0:56:49 time: 0.4968 data_time: 0.0149 memory: 16131 loss: 0.8403 loss_prob: 0.4360 loss_thr: 0.3264 loss_db: 0.0779 2022/10/26 08:49:34 - mmengine - INFO - Epoch(train) [1119][45/63] lr: 3.1280e-04 eta: 0:56:49 time: 0.5050 data_time: 0.0059 memory: 16131 loss: 0.8088 loss_prob: 0.4202 loss_thr: 0.3139 loss_db: 0.0748 2022/10/26 08:49:37 - mmengine - INFO - Epoch(train) [1119][50/63] lr: 3.1280e-04 eta: 0:56:42 time: 0.5061 data_time: 0.0121 memory: 16131 loss: 0.8342 loss_prob: 0.4341 loss_thr: 0.3245 loss_db: 0.0756 2022/10/26 08:49:40 - mmengine - INFO - Epoch(train) [1119][55/63] lr: 3.1280e-04 eta: 0:56:42 time: 0.5202 data_time: 0.0199 memory: 16131 loss: 0.8595 loss_prob: 0.4407 loss_thr: 0.3420 loss_db: 0.0769 2022/10/26 08:49:42 - mmengine - INFO - Epoch(train) [1119][60/63] lr: 3.1280e-04 eta: 0:56:35 time: 0.5375 data_time: 0.0238 memory: 16131 loss: 0.8089 loss_prob: 0.4145 loss_thr: 0.3210 loss_db: 0.0734 2022/10/26 08:49:44 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:49:48 - mmengine - INFO - Epoch(train) [1120][5/63] lr: 3.0933e-04 eta: 0:56:35 time: 0.7124 data_time: 0.1905 memory: 16131 loss: 0.8033 loss_prob: 0.4072 loss_thr: 0.3251 loss_db: 0.0710 2022/10/26 08:49:51 - mmengine - INFO - Epoch(train) [1120][10/63] lr: 3.0933e-04 eta: 0:56:26 time: 0.7511 data_time: 0.1902 memory: 16131 loss: 0.7702 loss_prob: 0.3961 loss_thr: 0.3058 loss_db: 0.0683 2022/10/26 08:49:54 - mmengine - INFO - Epoch(train) [1120][15/63] lr: 3.0933e-04 eta: 0:56:26 time: 0.5509 data_time: 0.0168 memory: 16131 loss: 0.8717 loss_prob: 0.4586 loss_thr: 0.3345 loss_db: 0.0786 2022/10/26 08:49:57 - mmengine - INFO - Epoch(train) [1120][20/63] lr: 3.0933e-04 eta: 0:56:20 time: 0.5429 data_time: 0.0167 memory: 16131 loss: 0.9186 loss_prob: 0.4861 loss_thr: 0.3481 loss_db: 0.0845 2022/10/26 08:49:59 - mmengine - INFO - Epoch(train) [1120][25/63] lr: 3.0933e-04 eta: 0:56:20 time: 0.5295 data_time: 0.0158 memory: 16131 loss: 0.8980 loss_prob: 0.4679 loss_thr: 0.3479 loss_db: 0.0822 2022/10/26 08:50:02 - mmengine - INFO - Epoch(train) [1120][30/63] lr: 3.0933e-04 eta: 0:56:13 time: 0.5299 data_time: 0.0344 memory: 16131 loss: 0.9083 loss_prob: 0.4718 loss_thr: 0.3532 loss_db: 0.0833 2022/10/26 08:50:04 - mmengine - INFO - Epoch(train) [1120][35/63] lr: 3.0933e-04 eta: 0:56:13 time: 0.4973 data_time: 0.0248 memory: 16131 loss: 0.9724 loss_prob: 0.5205 loss_thr: 0.3625 loss_db: 0.0895 2022/10/26 08:50:07 - mmengine - INFO - Epoch(train) [1120][40/63] lr: 3.0933e-04 eta: 0:56:06 time: 0.5026 data_time: 0.0104 memory: 16131 loss: 0.9439 loss_prob: 0.5052 loss_thr: 0.3524 loss_db: 0.0863 2022/10/26 08:50:10 - mmengine - INFO - Epoch(train) [1120][45/63] lr: 3.0933e-04 eta: 0:56:06 time: 0.5638 data_time: 0.0088 memory: 16131 loss: 0.8328 loss_prob: 0.4311 loss_thr: 0.3263 loss_db: 0.0754 2022/10/26 08:50:13 - mmengine - INFO - Epoch(train) [1120][50/63] lr: 3.0933e-04 eta: 0:55:59 time: 0.5666 data_time: 0.0148 memory: 16131 loss: 0.7965 loss_prob: 0.4149 loss_thr: 0.3098 loss_db: 0.0719 2022/10/26 08:50:15 - mmengine - INFO - Epoch(train) [1120][55/63] lr: 3.0933e-04 eta: 0:55:59 time: 0.5290 data_time: 0.0210 memory: 16131 loss: 0.8296 loss_prob: 0.4364 loss_thr: 0.3166 loss_db: 0.0767 2022/10/26 08:50:18 - mmengine - INFO - Epoch(train) [1120][60/63] lr: 3.0933e-04 eta: 0:55:53 time: 0.5001 data_time: 0.0133 memory: 16131 loss: 0.8665 loss_prob: 0.4549 loss_thr: 0.3323 loss_db: 0.0793 2022/10/26 08:50:19 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:50:19 - mmengine - INFO - Saving checkpoint at 1120 epochs 2022/10/26 08:50:26 - mmengine - INFO - Epoch(val) [1120][5/32] eta: 0:55:53 time: 0.5228 data_time: 0.0747 memory: 16131 2022/10/26 08:50:28 - mmengine - INFO - Epoch(val) [1120][10/32] eta: 0:00:12 time: 0.5886 data_time: 0.0894 memory: 15724 2022/10/26 08:50:31 - mmengine - INFO - Epoch(val) [1120][15/32] eta: 0:00:12 time: 0.5391 data_time: 0.0448 memory: 15724 2022/10/26 08:50:34 - mmengine - INFO - Epoch(val) [1120][20/32] eta: 0:00:06 time: 0.5453 data_time: 0.0547 memory: 15724 2022/10/26 08:50:36 - mmengine - INFO - Epoch(val) [1120][25/32] eta: 0:00:06 time: 0.5504 data_time: 0.0465 memory: 15724 2022/10/26 08:50:39 - mmengine - INFO - Epoch(val) [1120][30/32] eta: 0:00:01 time: 0.5121 data_time: 0.0221 memory: 15724 2022/10/26 08:50:40 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8464, precision: 0.7704, hmean: 0.8066 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8464, precision: 0.8143, hmean: 0.8300 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8459, precision: 0.8415, hmean: 0.8437 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8440, precision: 0.8627, hmean: 0.8532 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8329, precision: 0.8881, hmean: 0.8596 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7703, precision: 0.9243, hmean: 0.8403 2022/10/26 08:50:40 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2460, precision: 0.9789, hmean: 0.3932 2022/10/26 08:50:40 - mmengine - INFO - Epoch(val) [1120][32/32] icdar/precision: 0.8881 icdar/recall: 0.8329 icdar/hmean: 0.8596 2022/10/26 08:50:45 - mmengine - INFO - Epoch(train) [1121][5/63] lr: 3.0585e-04 eta: 0:00:01 time: 0.7692 data_time: 0.1706 memory: 16131 loss: 0.8328 loss_prob: 0.4335 loss_thr: 0.3244 loss_db: 0.0749 2022/10/26 08:50:48 - mmengine - INFO - Epoch(train) [1121][10/63] lr: 3.0585e-04 eta: 0:55:44 time: 0.8074 data_time: 0.1694 memory: 16131 loss: 0.8606 loss_prob: 0.4477 loss_thr: 0.3348 loss_db: 0.0781 2022/10/26 08:50:50 - mmengine - INFO - Epoch(train) [1121][15/63] lr: 3.0585e-04 eta: 0:55:44 time: 0.5190 data_time: 0.0124 memory: 16131 loss: 0.8867 loss_prob: 0.4619 loss_thr: 0.3457 loss_db: 0.0791 2022/10/26 08:50:53 - mmengine - INFO - Epoch(train) [1121][20/63] lr: 3.0585e-04 eta: 0:55:37 time: 0.5016 data_time: 0.0148 memory: 16131 loss: 0.8784 loss_prob: 0.4605 loss_thr: 0.3395 loss_db: 0.0784 2022/10/26 08:50:55 - mmengine - INFO - Epoch(train) [1121][25/63] lr: 3.0585e-04 eta: 0:55:37 time: 0.5198 data_time: 0.0227 memory: 16131 loss: 0.8620 loss_prob: 0.4454 loss_thr: 0.3386 loss_db: 0.0780 2022/10/26 08:50:58 - mmengine - INFO - Epoch(train) [1121][30/63] lr: 3.0585e-04 eta: 0:55:30 time: 0.5335 data_time: 0.0350 memory: 16131 loss: 0.8615 loss_prob: 0.4424 loss_thr: 0.3409 loss_db: 0.0781 2022/10/26 08:51:01 - mmengine - INFO - Epoch(train) [1121][35/63] lr: 3.0585e-04 eta: 0:55:30 time: 0.5166 data_time: 0.0202 memory: 16131 loss: 0.8578 loss_prob: 0.4432 loss_thr: 0.3367 loss_db: 0.0779 2022/10/26 08:51:03 - mmengine - INFO - Epoch(train) [1121][40/63] lr: 3.0585e-04 eta: 0:55:24 time: 0.5138 data_time: 0.0113 memory: 16131 loss: 0.8196 loss_prob: 0.4245 loss_thr: 0.3199 loss_db: 0.0751 2022/10/26 08:51:06 - mmengine - INFO - Epoch(train) [1121][45/63] lr: 3.0585e-04 eta: 0:55:24 time: 0.5132 data_time: 0.0107 memory: 16131 loss: 0.8070 loss_prob: 0.4126 loss_thr: 0.3188 loss_db: 0.0756 2022/10/26 08:51:08 - mmengine - INFO - Epoch(train) [1121][50/63] lr: 3.0585e-04 eta: 0:55:17 time: 0.5274 data_time: 0.0196 memory: 16131 loss: 0.8356 loss_prob: 0.4290 loss_thr: 0.3299 loss_db: 0.0767 2022/10/26 08:51:11 - mmengine - INFO - Epoch(train) [1121][55/63] lr: 3.0585e-04 eta: 0:55:17 time: 0.5309 data_time: 0.0192 memory: 16131 loss: 0.8771 loss_prob: 0.4546 loss_thr: 0.3459 loss_db: 0.0767 2022/10/26 08:51:13 - mmengine - INFO - Epoch(train) [1121][60/63] lr: 3.0585e-04 eta: 0:55:10 time: 0.5056 data_time: 0.0078 memory: 16131 loss: 0.9088 loss_prob: 0.4800 loss_thr: 0.3460 loss_db: 0.0828 2022/10/26 08:51:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:51:20 - mmengine - INFO - Epoch(train) [1122][5/63] lr: 3.0236e-04 eta: 0:55:10 time: 0.7207 data_time: 0.1892 memory: 16131 loss: 0.8136 loss_prob: 0.4179 loss_thr: 0.3227 loss_db: 0.0730 2022/10/26 08:51:22 - mmengine - INFO - Epoch(train) [1122][10/63] lr: 3.0236e-04 eta: 0:55:01 time: 0.7418 data_time: 0.1876 memory: 16131 loss: 0.8487 loss_prob: 0.4419 loss_thr: 0.3303 loss_db: 0.0765 2022/10/26 08:51:25 - mmengine - INFO - Epoch(train) [1122][15/63] lr: 3.0236e-04 eta: 0:55:01 time: 0.5110 data_time: 0.0126 memory: 16131 loss: 0.9940 loss_prob: 0.5399 loss_thr: 0.3632 loss_db: 0.0909 2022/10/26 08:51:28 - mmengine - INFO - Epoch(train) [1122][20/63] lr: 3.0236e-04 eta: 0:54:55 time: 0.5293 data_time: 0.0110 memory: 16131 loss: 0.9564 loss_prob: 0.5113 loss_thr: 0.3571 loss_db: 0.0880 2022/10/26 08:51:30 - mmengine - INFO - Epoch(train) [1122][25/63] lr: 3.0236e-04 eta: 0:54:55 time: 0.5414 data_time: 0.0124 memory: 16131 loss: 0.8986 loss_prob: 0.4676 loss_thr: 0.3481 loss_db: 0.0830 2022/10/26 08:51:33 - mmengine - INFO - Epoch(train) [1122][30/63] lr: 3.0236e-04 eta: 0:54:48 time: 0.5534 data_time: 0.0309 memory: 16131 loss: 0.9087 loss_prob: 0.4761 loss_thr: 0.3504 loss_db: 0.0822 2022/10/26 08:51:37 - mmengine - INFO - Epoch(train) [1122][35/63] lr: 3.0236e-04 eta: 0:54:48 time: 0.6471 data_time: 0.0232 memory: 16131 loss: 0.8585 loss_prob: 0.4489 loss_thr: 0.3331 loss_db: 0.0765 2022/10/26 08:51:39 - mmengine - INFO - Epoch(train) [1122][40/63] lr: 3.0236e-04 eta: 0:54:41 time: 0.6234 data_time: 0.0102 memory: 16131 loss: 0.8432 loss_prob: 0.4385 loss_thr: 0.3284 loss_db: 0.0764 2022/10/26 08:51:42 - mmengine - INFO - Epoch(train) [1122][45/63] lr: 3.0236e-04 eta: 0:54:41 time: 0.5103 data_time: 0.0106 memory: 16131 loss: 0.8773 loss_prob: 0.4573 loss_thr: 0.3392 loss_db: 0.0809 2022/10/26 08:51:44 - mmengine - INFO - Epoch(train) [1122][50/63] lr: 3.0236e-04 eta: 0:54:35 time: 0.5035 data_time: 0.0146 memory: 16131 loss: 0.9193 loss_prob: 0.4824 loss_thr: 0.3516 loss_db: 0.0853 2022/10/26 08:51:47 - mmengine - INFO - Epoch(train) [1122][55/63] lr: 3.0236e-04 eta: 0:54:35 time: 0.5040 data_time: 0.0248 memory: 16131 loss: 0.9345 loss_prob: 0.4974 loss_thr: 0.3505 loss_db: 0.0866 2022/10/26 08:51:49 - mmengine - INFO - Epoch(train) [1122][60/63] lr: 3.0236e-04 eta: 0:54:28 time: 0.5001 data_time: 0.0192 memory: 16131 loss: 0.8777 loss_prob: 0.4655 loss_thr: 0.3319 loss_db: 0.0803 2022/10/26 08:51:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:51:55 - mmengine - INFO - Epoch(train) [1123][5/63] lr: 2.9887e-04 eta: 0:54:28 time: 0.6578 data_time: 0.1600 memory: 16131 loss: 0.8116 loss_prob: 0.4272 loss_thr: 0.3097 loss_db: 0.0746 2022/10/26 08:51:57 - mmengine - INFO - Epoch(train) [1123][10/63] lr: 2.9887e-04 eta: 0:54:19 time: 0.6887 data_time: 0.1590 memory: 16131 loss: 0.8433 loss_prob: 0.4406 loss_thr: 0.3256 loss_db: 0.0772 2022/10/26 08:52:00 - mmengine - INFO - Epoch(train) [1123][15/63] lr: 2.9887e-04 eta: 0:54:19 time: 0.5033 data_time: 0.0085 memory: 16131 loss: 0.8804 loss_prob: 0.4578 loss_thr: 0.3420 loss_db: 0.0807 2022/10/26 08:52:03 - mmengine - INFO - Epoch(train) [1123][20/63] lr: 2.9887e-04 eta: 0:54:12 time: 0.5156 data_time: 0.0076 memory: 16131 loss: 0.8619 loss_prob: 0.4457 loss_thr: 0.3379 loss_db: 0.0783 2022/10/26 08:52:05 - mmengine - INFO - Epoch(train) [1123][25/63] lr: 2.9887e-04 eta: 0:54:12 time: 0.5163 data_time: 0.0104 memory: 16131 loss: 0.8381 loss_prob: 0.4404 loss_thr: 0.3212 loss_db: 0.0765 2022/10/26 08:52:08 - mmengine - INFO - Epoch(train) [1123][30/63] lr: 2.9887e-04 eta: 0:54:06 time: 0.5124 data_time: 0.0308 memory: 16131 loss: 0.9147 loss_prob: 0.4882 loss_thr: 0.3404 loss_db: 0.0860 2022/10/26 08:52:10 - mmengine - INFO - Epoch(train) [1123][35/63] lr: 2.9887e-04 eta: 0:54:06 time: 0.5329 data_time: 0.0354 memory: 16131 loss: 0.9087 loss_prob: 0.4771 loss_thr: 0.3484 loss_db: 0.0833 2022/10/26 08:52:13 - mmengine - INFO - Epoch(train) [1123][40/63] lr: 2.9887e-04 eta: 0:53:59 time: 0.5445 data_time: 0.0125 memory: 16131 loss: 0.8438 loss_prob: 0.4400 loss_thr: 0.3278 loss_db: 0.0760 2022/10/26 08:52:16 - mmengine - INFO - Epoch(train) [1123][45/63] lr: 2.9887e-04 eta: 0:53:59 time: 0.5211 data_time: 0.0047 memory: 16131 loss: 0.8885 loss_prob: 0.4672 loss_thr: 0.3394 loss_db: 0.0818 2022/10/26 08:52:18 - mmengine - INFO - Epoch(train) [1123][50/63] lr: 2.9887e-04 eta: 0:53:52 time: 0.4923 data_time: 0.0082 memory: 16131 loss: 0.8289 loss_prob: 0.4278 loss_thr: 0.3249 loss_db: 0.0762 2022/10/26 08:52:21 - mmengine - INFO - Epoch(train) [1123][55/63] lr: 2.9887e-04 eta: 0:53:52 time: 0.5065 data_time: 0.0217 memory: 16131 loss: 0.8028 loss_prob: 0.4149 loss_thr: 0.3144 loss_db: 0.0736 2022/10/26 08:52:23 - mmengine - INFO - Epoch(train) [1123][60/63] lr: 2.9887e-04 eta: 0:53:45 time: 0.5101 data_time: 0.0236 memory: 16131 loss: 0.8081 loss_prob: 0.4197 loss_thr: 0.3161 loss_db: 0.0723 2022/10/26 08:52:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:52:29 - mmengine - INFO - Epoch(train) [1124][5/63] lr: 2.9538e-04 eta: 0:53:45 time: 0.6792 data_time: 0.1774 memory: 16131 loss: 0.8239 loss_prob: 0.4213 loss_thr: 0.3291 loss_db: 0.0735 2022/10/26 08:52:32 - mmengine - INFO - Epoch(train) [1124][10/63] lr: 2.9538e-04 eta: 0:53:37 time: 0.6812 data_time: 0.1765 memory: 16131 loss: 0.8059 loss_prob: 0.4161 loss_thr: 0.3167 loss_db: 0.0730 2022/10/26 08:52:34 - mmengine - INFO - Epoch(train) [1124][15/63] lr: 2.9538e-04 eta: 0:53:37 time: 0.5171 data_time: 0.0092 memory: 16131 loss: 0.7772 loss_prob: 0.3980 loss_thr: 0.3100 loss_db: 0.0692 2022/10/26 08:52:37 - mmengine - INFO - Epoch(train) [1124][20/63] lr: 2.9538e-04 eta: 0:53:30 time: 0.5535 data_time: 0.0092 memory: 16131 loss: 0.8133 loss_prob: 0.4213 loss_thr: 0.3189 loss_db: 0.0730 2022/10/26 08:52:40 - mmengine - INFO - Epoch(train) [1124][25/63] lr: 2.9538e-04 eta: 0:53:30 time: 0.5628 data_time: 0.0196 memory: 16131 loss: 0.8816 loss_prob: 0.4622 loss_thr: 0.3388 loss_db: 0.0806 2022/10/26 08:52:43 - mmengine - INFO - Epoch(train) [1124][30/63] lr: 2.9538e-04 eta: 0:53:23 time: 0.5824 data_time: 0.0316 memory: 16131 loss: 0.8171 loss_prob: 0.4155 loss_thr: 0.3275 loss_db: 0.0740 2022/10/26 08:52:45 - mmengine - INFO - Epoch(train) [1124][35/63] lr: 2.9538e-04 eta: 0:53:23 time: 0.5607 data_time: 0.0176 memory: 16131 loss: 0.8564 loss_prob: 0.4397 loss_thr: 0.3380 loss_db: 0.0787 2022/10/26 08:52:48 - mmengine - INFO - Epoch(train) [1124][40/63] lr: 2.9538e-04 eta: 0:53:16 time: 0.5386 data_time: 0.0122 memory: 16131 loss: 0.8871 loss_prob: 0.4565 loss_thr: 0.3512 loss_db: 0.0795 2022/10/26 08:52:51 - mmengine - INFO - Epoch(train) [1124][45/63] lr: 2.9538e-04 eta: 0:53:16 time: 0.5293 data_time: 0.0119 memory: 16131 loss: 0.8518 loss_prob: 0.4361 loss_thr: 0.3427 loss_db: 0.0730 2022/10/26 08:52:53 - mmengine - INFO - Epoch(train) [1124][50/63] lr: 2.9538e-04 eta: 0:53:10 time: 0.5186 data_time: 0.0202 memory: 16131 loss: 0.9032 loss_prob: 0.4692 loss_thr: 0.3535 loss_db: 0.0804 2022/10/26 08:52:56 - mmengine - INFO - Epoch(train) [1124][55/63] lr: 2.9538e-04 eta: 0:53:10 time: 0.5476 data_time: 0.0253 memory: 16131 loss: 0.9082 loss_prob: 0.4780 loss_thr: 0.3455 loss_db: 0.0846 2022/10/26 08:52:59 - mmengine - INFO - Epoch(train) [1124][60/63] lr: 2.9538e-04 eta: 0:53:03 time: 0.5514 data_time: 0.0115 memory: 16131 loss: 0.9332 loss_prob: 0.4967 loss_thr: 0.3487 loss_db: 0.0878 2022/10/26 08:53:01 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:53:05 - mmengine - INFO - Epoch(train) [1125][5/63] lr: 2.9188e-04 eta: 0:53:03 time: 0.7724 data_time: 0.1607 memory: 16131 loss: 0.8489 loss_prob: 0.4370 loss_thr: 0.3355 loss_db: 0.0765 2022/10/26 08:53:08 - mmengine - INFO - Epoch(train) [1125][10/63] lr: 2.9188e-04 eta: 0:52:54 time: 0.7322 data_time: 0.1612 memory: 16131 loss: 0.8036 loss_prob: 0.4109 loss_thr: 0.3216 loss_db: 0.0711 2022/10/26 08:53:11 - mmengine - INFO - Epoch(train) [1125][15/63] lr: 2.9188e-04 eta: 0:52:54 time: 0.5873 data_time: 0.0129 memory: 16131 loss: 0.8459 loss_prob: 0.4422 loss_thr: 0.3261 loss_db: 0.0777 2022/10/26 08:53:14 - mmengine - INFO - Epoch(train) [1125][20/63] lr: 2.9188e-04 eta: 0:52:47 time: 0.5708 data_time: 0.0077 memory: 16131 loss: 0.8470 loss_prob: 0.4469 loss_thr: 0.3210 loss_db: 0.0790 2022/10/26 08:53:16 - mmengine - INFO - Epoch(train) [1125][25/63] lr: 2.9188e-04 eta: 0:52:47 time: 0.5113 data_time: 0.0071 memory: 16131 loss: 0.8363 loss_prob: 0.4371 loss_thr: 0.3228 loss_db: 0.0763 2022/10/26 08:53:19 - mmengine - INFO - Epoch(train) [1125][30/63] lr: 2.9188e-04 eta: 0:52:41 time: 0.5180 data_time: 0.0322 memory: 16131 loss: 0.8402 loss_prob: 0.4394 loss_thr: 0.3237 loss_db: 0.0771 2022/10/26 08:53:22 - mmengine - INFO - Epoch(train) [1125][35/63] lr: 2.9188e-04 eta: 0:52:41 time: 0.5178 data_time: 0.0319 memory: 16131 loss: 0.8752 loss_prob: 0.4591 loss_thr: 0.3350 loss_db: 0.0810 2022/10/26 08:53:24 - mmengine - INFO - Epoch(train) [1125][40/63] lr: 2.9188e-04 eta: 0:52:34 time: 0.4941 data_time: 0.0070 memory: 16131 loss: 0.8380 loss_prob: 0.4316 loss_thr: 0.3314 loss_db: 0.0750 2022/10/26 08:53:27 - mmengine - INFO - Epoch(train) [1125][45/63] lr: 2.9188e-04 eta: 0:52:34 time: 0.5014 data_time: 0.0049 memory: 16131 loss: 0.8260 loss_prob: 0.4225 loss_thr: 0.3292 loss_db: 0.0743 2022/10/26 08:53:29 - mmengine - INFO - Epoch(train) [1125][50/63] lr: 2.9188e-04 eta: 0:52:27 time: 0.5141 data_time: 0.0178 memory: 16131 loss: 0.9236 loss_prob: 0.4892 loss_thr: 0.3503 loss_db: 0.0841 2022/10/26 08:53:32 - mmengine - INFO - Epoch(train) [1125][55/63] lr: 2.9188e-04 eta: 0:52:27 time: 0.5122 data_time: 0.0291 memory: 16131 loss: 0.9842 loss_prob: 0.5311 loss_thr: 0.3619 loss_db: 0.0912 2022/10/26 08:53:34 - mmengine - INFO - Epoch(train) [1125][60/63] lr: 2.9188e-04 eta: 0:52:20 time: 0.5032 data_time: 0.0174 memory: 16131 loss: 0.8408 loss_prob: 0.4436 loss_thr: 0.3183 loss_db: 0.0789 2022/10/26 08:53:36 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:53:40 - mmengine - INFO - Epoch(train) [1126][5/63] lr: 2.8837e-04 eta: 0:52:20 time: 0.6448 data_time: 0.1589 memory: 16131 loss: 0.8263 loss_prob: 0.4302 loss_thr: 0.3232 loss_db: 0.0729 2022/10/26 08:53:42 - mmengine - INFO - Epoch(train) [1126][10/63] lr: 2.8837e-04 eta: 0:52:12 time: 0.6762 data_time: 0.1645 memory: 16131 loss: 0.8898 loss_prob: 0.4705 loss_thr: 0.3380 loss_db: 0.0814 2022/10/26 08:53:45 - mmengine - INFO - Epoch(train) [1126][15/63] lr: 2.8837e-04 eta: 0:52:12 time: 0.5233 data_time: 0.0183 memory: 16131 loss: 0.8717 loss_prob: 0.4551 loss_thr: 0.3354 loss_db: 0.0813 2022/10/26 08:53:47 - mmengine - INFO - Epoch(train) [1126][20/63] lr: 2.8837e-04 eta: 0:52:05 time: 0.5078 data_time: 0.0128 memory: 16131 loss: 0.8270 loss_prob: 0.4255 loss_thr: 0.3251 loss_db: 0.0764 2022/10/26 08:53:50 - mmengine - INFO - Epoch(train) [1126][25/63] lr: 2.8837e-04 eta: 0:52:05 time: 0.5098 data_time: 0.0179 memory: 16131 loss: 0.8460 loss_prob: 0.4394 loss_thr: 0.3288 loss_db: 0.0779 2022/10/26 08:53:53 - mmengine - INFO - Epoch(train) [1126][30/63] lr: 2.8837e-04 eta: 0:51:58 time: 0.5330 data_time: 0.0397 memory: 16131 loss: 0.8753 loss_prob: 0.4560 loss_thr: 0.3384 loss_db: 0.0809 2022/10/26 08:53:55 - mmengine - INFO - Epoch(train) [1126][35/63] lr: 2.8837e-04 eta: 0:51:58 time: 0.5335 data_time: 0.0286 memory: 16131 loss: 0.8851 loss_prob: 0.4578 loss_thr: 0.3477 loss_db: 0.0795 2022/10/26 08:53:58 - mmengine - INFO - Epoch(train) [1126][40/63] lr: 2.8837e-04 eta: 0:51:52 time: 0.5698 data_time: 0.0063 memory: 16131 loss: 0.9525 loss_prob: 0.5008 loss_thr: 0.3655 loss_db: 0.0862 2022/10/26 08:54:01 - mmengine - INFO - Epoch(train) [1126][45/63] lr: 2.8837e-04 eta: 0:51:52 time: 0.5713 data_time: 0.0055 memory: 16131 loss: 0.9502 loss_prob: 0.5055 loss_thr: 0.3561 loss_db: 0.0885 2022/10/26 08:54:04 - mmengine - INFO - Epoch(train) [1126][50/63] lr: 2.8837e-04 eta: 0:51:45 time: 0.5691 data_time: 0.0188 memory: 16131 loss: 0.8735 loss_prob: 0.4499 loss_thr: 0.3445 loss_db: 0.0791 2022/10/26 08:54:07 - mmengine - INFO - Epoch(train) [1126][55/63] lr: 2.8837e-04 eta: 0:51:45 time: 0.5775 data_time: 0.0202 memory: 16131 loss: 0.9347 loss_prob: 0.4876 loss_thr: 0.3649 loss_db: 0.0822 2022/10/26 08:54:10 - mmengine - INFO - Epoch(train) [1126][60/63] lr: 2.8837e-04 eta: 0:51:38 time: 0.5687 data_time: 0.0082 memory: 16131 loss: 0.8999 loss_prob: 0.4760 loss_thr: 0.3423 loss_db: 0.0815 2022/10/26 08:54:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:54:16 - mmengine - INFO - Epoch(train) [1127][5/63] lr: 2.8487e-04 eta: 0:51:38 time: 0.7031 data_time: 0.2110 memory: 16131 loss: 0.9112 loss_prob: 0.4741 loss_thr: 0.3546 loss_db: 0.0825 2022/10/26 08:54:18 - mmengine - INFO - Epoch(train) [1127][10/63] lr: 2.8487e-04 eta: 0:51:29 time: 0.7251 data_time: 0.2065 memory: 16131 loss: 0.8732 loss_prob: 0.4628 loss_thr: 0.3325 loss_db: 0.0779 2022/10/26 08:54:21 - mmengine - INFO - Epoch(train) [1127][15/63] lr: 2.8487e-04 eta: 0:51:29 time: 0.5501 data_time: 0.0052 memory: 16131 loss: 0.8389 loss_prob: 0.4496 loss_thr: 0.3134 loss_db: 0.0758 2022/10/26 08:54:24 - mmengine - INFO - Epoch(train) [1127][20/63] lr: 2.8487e-04 eta: 0:51:23 time: 0.5491 data_time: 0.0080 memory: 16131 loss: 0.8774 loss_prob: 0.4512 loss_thr: 0.3478 loss_db: 0.0784 2022/10/26 08:54:27 - mmengine - INFO - Epoch(train) [1127][25/63] lr: 2.8487e-04 eta: 0:51:23 time: 0.5366 data_time: 0.0289 memory: 16131 loss: 0.8772 loss_prob: 0.4481 loss_thr: 0.3514 loss_db: 0.0777 2022/10/26 08:54:30 - mmengine - INFO - Epoch(train) [1127][30/63] lr: 2.8487e-04 eta: 0:51:16 time: 0.6059 data_time: 0.0306 memory: 16131 loss: 0.7642 loss_prob: 0.3883 loss_thr: 0.3087 loss_db: 0.0672 2022/10/26 08:54:32 - mmengine - INFO - Epoch(train) [1127][35/63] lr: 2.8487e-04 eta: 0:51:16 time: 0.5706 data_time: 0.0092 memory: 16131 loss: 0.7527 loss_prob: 0.3786 loss_thr: 0.3079 loss_db: 0.0662 2022/10/26 08:54:35 - mmengine - INFO - Epoch(train) [1127][40/63] lr: 2.8487e-04 eta: 0:51:09 time: 0.5013 data_time: 0.0049 memory: 16131 loss: 0.9589 loss_prob: 0.5018 loss_thr: 0.3696 loss_db: 0.0875 2022/10/26 08:54:38 - mmengine - INFO - Epoch(train) [1127][45/63] lr: 2.8487e-04 eta: 0:51:09 time: 0.5045 data_time: 0.0087 memory: 16131 loss: 1.0012 loss_prob: 0.5362 loss_thr: 0.3715 loss_db: 0.0935 2022/10/26 08:54:41 - mmengine - INFO - Epoch(train) [1127][50/63] lr: 2.8487e-04 eta: 0:51:03 time: 0.6156 data_time: 0.0274 memory: 16131 loss: 0.8988 loss_prob: 0.4804 loss_thr: 0.3362 loss_db: 0.0822 2022/10/26 08:54:44 - mmengine - INFO - Epoch(train) [1127][55/63] lr: 2.8487e-04 eta: 0:51:03 time: 0.6523 data_time: 0.0270 memory: 16131 loss: 0.9104 loss_prob: 0.4822 loss_thr: 0.3467 loss_db: 0.0816 2022/10/26 08:54:47 - mmengine - INFO - Epoch(train) [1127][60/63] lr: 2.8487e-04 eta: 0:50:56 time: 0.5333 data_time: 0.0094 memory: 16131 loss: 0.8825 loss_prob: 0.4641 loss_thr: 0.3371 loss_db: 0.0813 2022/10/26 08:54:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:54:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:54:52 - mmengine - INFO - Epoch(train) [1128][5/63] lr: 2.8135e-04 eta: 0:50:56 time: 0.6670 data_time: 0.1795 memory: 16131 loss: 0.8845 loss_prob: 0.4624 loss_thr: 0.3416 loss_db: 0.0806 2022/10/26 08:54:55 - mmengine - INFO - Epoch(train) [1128][10/63] lr: 2.8135e-04 eta: 0:50:47 time: 0.7019 data_time: 0.1786 memory: 16131 loss: 0.9333 loss_prob: 0.4953 loss_thr: 0.3530 loss_db: 0.0850 2022/10/26 08:54:58 - mmengine - INFO - Epoch(train) [1128][15/63] lr: 2.8135e-04 eta: 0:50:47 time: 0.5295 data_time: 0.0062 memory: 16131 loss: 0.8678 loss_prob: 0.4576 loss_thr: 0.3313 loss_db: 0.0788 2022/10/26 08:55:00 - mmengine - INFO - Epoch(train) [1128][20/63] lr: 2.8135e-04 eta: 0:50:40 time: 0.5209 data_time: 0.0072 memory: 16131 loss: 0.8204 loss_prob: 0.4303 loss_thr: 0.3164 loss_db: 0.0738 2022/10/26 08:55:03 - mmengine - INFO - Epoch(train) [1128][25/63] lr: 2.8135e-04 eta: 0:50:40 time: 0.5606 data_time: 0.0143 memory: 16131 loss: 0.7908 loss_prob: 0.4101 loss_thr: 0.3086 loss_db: 0.0721 2022/10/26 08:55:06 - mmengine - INFO - Epoch(train) [1128][30/63] lr: 2.8135e-04 eta: 0:50:34 time: 0.6084 data_time: 0.0334 memory: 16131 loss: 0.7966 loss_prob: 0.4140 loss_thr: 0.3066 loss_db: 0.0759 2022/10/26 08:55:09 - mmengine - INFO - Epoch(train) [1128][35/63] lr: 2.8135e-04 eta: 0:50:34 time: 0.5679 data_time: 0.0254 memory: 16131 loss: 0.8228 loss_prob: 0.4259 loss_thr: 0.3203 loss_db: 0.0767 2022/10/26 08:55:11 - mmengine - INFO - Epoch(train) [1128][40/63] lr: 2.8135e-04 eta: 0:50:27 time: 0.5088 data_time: 0.0055 memory: 16131 loss: 0.8888 loss_prob: 0.4558 loss_thr: 0.3550 loss_db: 0.0780 2022/10/26 08:55:14 - mmengine - INFO - Epoch(train) [1128][45/63] lr: 2.8135e-04 eta: 0:50:27 time: 0.5000 data_time: 0.0057 memory: 16131 loss: 0.8851 loss_prob: 0.4598 loss_thr: 0.3477 loss_db: 0.0775 2022/10/26 08:55:17 - mmengine - INFO - Epoch(train) [1128][50/63] lr: 2.8135e-04 eta: 0:50:20 time: 0.5365 data_time: 0.0161 memory: 16131 loss: 0.8706 loss_prob: 0.4561 loss_thr: 0.3356 loss_db: 0.0789 2022/10/26 08:55:19 - mmengine - INFO - Epoch(train) [1128][55/63] lr: 2.8135e-04 eta: 0:50:20 time: 0.5680 data_time: 0.0237 memory: 16131 loss: 0.9003 loss_prob: 0.4676 loss_thr: 0.3503 loss_db: 0.0824 2022/10/26 08:55:22 - mmengine - INFO - Epoch(train) [1128][60/63] lr: 2.8135e-04 eta: 0:50:14 time: 0.5406 data_time: 0.0133 memory: 16131 loss: 0.8747 loss_prob: 0.4532 loss_thr: 0.3422 loss_db: 0.0793 2022/10/26 08:55:23 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:55:28 - mmengine - INFO - Epoch(train) [1129][5/63] lr: 2.7783e-04 eta: 0:50:14 time: 0.6908 data_time: 0.1933 memory: 16131 loss: 0.8383 loss_prob: 0.4389 loss_thr: 0.3229 loss_db: 0.0765 2022/10/26 08:55:31 - mmengine - INFO - Epoch(train) [1129][10/63] lr: 2.7783e-04 eta: 0:50:05 time: 0.7311 data_time: 0.1931 memory: 16131 loss: 0.8790 loss_prob: 0.4697 loss_thr: 0.3286 loss_db: 0.0807 2022/10/26 08:55:33 - mmengine - INFO - Epoch(train) [1129][15/63] lr: 2.7783e-04 eta: 0:50:05 time: 0.5072 data_time: 0.0052 memory: 16131 loss: 0.9528 loss_prob: 0.5120 loss_thr: 0.3533 loss_db: 0.0875 2022/10/26 08:55:36 - mmengine - INFO - Epoch(train) [1129][20/63] lr: 2.7783e-04 eta: 0:49:58 time: 0.4899 data_time: 0.0067 memory: 16131 loss: 0.8984 loss_prob: 0.4692 loss_thr: 0.3476 loss_db: 0.0816 2022/10/26 08:55:38 - mmengine - INFO - Epoch(train) [1129][25/63] lr: 2.7783e-04 eta: 0:49:58 time: 0.5278 data_time: 0.0222 memory: 16131 loss: 0.8879 loss_prob: 0.4640 loss_thr: 0.3415 loss_db: 0.0825 2022/10/26 08:55:41 - mmengine - INFO - Epoch(train) [1129][30/63] lr: 2.7783e-04 eta: 0:49:51 time: 0.5893 data_time: 0.0330 memory: 16131 loss: 0.9356 loss_prob: 0.4972 loss_thr: 0.3521 loss_db: 0.0864 2022/10/26 08:55:44 - mmengine - INFO - Epoch(train) [1129][35/63] lr: 2.7783e-04 eta: 0:49:51 time: 0.5734 data_time: 0.0174 memory: 16131 loss: 0.9426 loss_prob: 0.5028 loss_thr: 0.3537 loss_db: 0.0861 2022/10/26 08:55:47 - mmengine - INFO - Epoch(train) [1129][40/63] lr: 2.7783e-04 eta: 0:49:45 time: 0.5234 data_time: 0.0047 memory: 16131 loss: 0.8884 loss_prob: 0.4724 loss_thr: 0.3345 loss_db: 0.0814 2022/10/26 08:55:49 - mmengine - INFO - Epoch(train) [1129][45/63] lr: 2.7783e-04 eta: 0:49:45 time: 0.4977 data_time: 0.0072 memory: 16131 loss: 0.8661 loss_prob: 0.4478 loss_thr: 0.3406 loss_db: 0.0777 2022/10/26 08:55:52 - mmengine - INFO - Epoch(train) [1129][50/63] lr: 2.7783e-04 eta: 0:49:38 time: 0.5132 data_time: 0.0215 memory: 16131 loss: 0.8435 loss_prob: 0.4307 loss_thr: 0.3364 loss_db: 0.0764 2022/10/26 08:55:55 - mmengine - INFO - Epoch(train) [1129][55/63] lr: 2.7783e-04 eta: 0:49:38 time: 0.5806 data_time: 0.0265 memory: 16131 loss: 0.8461 loss_prob: 0.4351 loss_thr: 0.3344 loss_db: 0.0765 2022/10/26 08:55:57 - mmengine - INFO - Epoch(train) [1129][60/63] lr: 2.7783e-04 eta: 0:49:31 time: 0.5655 data_time: 0.0132 memory: 16131 loss: 0.8738 loss_prob: 0.4533 loss_thr: 0.3425 loss_db: 0.0779 2022/10/26 08:55:59 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:56:03 - mmengine - INFO - Epoch(train) [1130][5/63] lr: 2.7431e-04 eta: 0:49:31 time: 0.6659 data_time: 0.1844 memory: 16131 loss: 0.9313 loss_prob: 0.4963 loss_thr: 0.3502 loss_db: 0.0848 2022/10/26 08:56:06 - mmengine - INFO - Epoch(train) [1130][10/63] lr: 2.7431e-04 eta: 0:49:22 time: 0.6748 data_time: 0.1836 memory: 16131 loss: 0.9469 loss_prob: 0.5101 loss_thr: 0.3509 loss_db: 0.0859 2022/10/26 08:56:08 - mmengine - INFO - Epoch(train) [1130][15/63] lr: 2.7431e-04 eta: 0:49:22 time: 0.5046 data_time: 0.0074 memory: 16131 loss: 0.9117 loss_prob: 0.4847 loss_thr: 0.3439 loss_db: 0.0832 2022/10/26 08:56:11 - mmengine - INFO - Epoch(train) [1130][20/63] lr: 2.7431e-04 eta: 0:49:16 time: 0.5264 data_time: 0.0076 memory: 16131 loss: 0.9158 loss_prob: 0.4828 loss_thr: 0.3481 loss_db: 0.0848 2022/10/26 08:56:13 - mmengine - INFO - Epoch(train) [1130][25/63] lr: 2.7431e-04 eta: 0:49:16 time: 0.5362 data_time: 0.0134 memory: 16131 loss: 0.8712 loss_prob: 0.4582 loss_thr: 0.3331 loss_db: 0.0798 2022/10/26 08:56:17 - mmengine - INFO - Epoch(train) [1130][30/63] lr: 2.7431e-04 eta: 0:49:09 time: 0.5681 data_time: 0.0325 memory: 16131 loss: 0.8197 loss_prob: 0.4319 loss_thr: 0.3146 loss_db: 0.0731 2022/10/26 08:56:19 - mmengine - INFO - Epoch(train) [1130][35/63] lr: 2.7431e-04 eta: 0:49:09 time: 0.5773 data_time: 0.0269 memory: 16131 loss: 0.7734 loss_prob: 0.3921 loss_thr: 0.3139 loss_db: 0.0674 2022/10/26 08:56:22 - mmengine - INFO - Epoch(train) [1130][40/63] lr: 2.7431e-04 eta: 0:49:02 time: 0.5220 data_time: 0.0081 memory: 16131 loss: 0.8174 loss_prob: 0.4145 loss_thr: 0.3302 loss_db: 0.0727 2022/10/26 08:56:24 - mmengine - INFO - Epoch(train) [1130][45/63] lr: 2.7431e-04 eta: 0:49:02 time: 0.5229 data_time: 0.0070 memory: 16131 loss: 0.8822 loss_prob: 0.4613 loss_thr: 0.3412 loss_db: 0.0798 2022/10/26 08:56:27 - mmengine - INFO - Epoch(train) [1130][50/63] lr: 2.7431e-04 eta: 0:48:56 time: 0.5267 data_time: 0.0151 memory: 16131 loss: 0.9127 loss_prob: 0.4798 loss_thr: 0.3496 loss_db: 0.0832 2022/10/26 08:56:29 - mmengine - INFO - Epoch(train) [1130][55/63] lr: 2.7431e-04 eta: 0:48:56 time: 0.4992 data_time: 0.0235 memory: 16131 loss: 0.8538 loss_prob: 0.4414 loss_thr: 0.3343 loss_db: 0.0781 2022/10/26 08:56:32 - mmengine - INFO - Epoch(train) [1130][60/63] lr: 2.7431e-04 eta: 0:48:49 time: 0.5183 data_time: 0.0150 memory: 16131 loss: 0.8514 loss_prob: 0.4435 loss_thr: 0.3305 loss_db: 0.0775 2022/10/26 08:56:34 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:56:39 - mmengine - INFO - Epoch(train) [1131][5/63] lr: 2.7078e-04 eta: 0:48:49 time: 0.7417 data_time: 0.1837 memory: 16131 loss: 0.8615 loss_prob: 0.4524 loss_thr: 0.3304 loss_db: 0.0788 2022/10/26 08:56:41 - mmengine - INFO - Epoch(train) [1131][10/63] lr: 2.7078e-04 eta: 0:48:40 time: 0.7716 data_time: 0.1914 memory: 16131 loss: 0.8683 loss_prob: 0.4507 loss_thr: 0.3395 loss_db: 0.0782 2022/10/26 08:56:44 - mmengine - INFO - Epoch(train) [1131][15/63] lr: 2.7078e-04 eta: 0:48:40 time: 0.5102 data_time: 0.0129 memory: 16131 loss: 0.8591 loss_prob: 0.4472 loss_thr: 0.3338 loss_db: 0.0782 2022/10/26 08:56:46 - mmengine - INFO - Epoch(train) [1131][20/63] lr: 2.7078e-04 eta: 0:48:33 time: 0.5235 data_time: 0.0059 memory: 16131 loss: 0.9324 loss_prob: 0.4905 loss_thr: 0.3564 loss_db: 0.0856 2022/10/26 08:56:49 - mmengine - INFO - Epoch(train) [1131][25/63] lr: 2.7078e-04 eta: 0:48:33 time: 0.5521 data_time: 0.0303 memory: 16131 loss: 0.9442 loss_prob: 0.4941 loss_thr: 0.3641 loss_db: 0.0860 2022/10/26 08:56:52 - mmengine - INFO - Epoch(train) [1131][30/63] lr: 2.7078e-04 eta: 0:48:27 time: 0.5424 data_time: 0.0314 memory: 16131 loss: 0.8649 loss_prob: 0.4560 loss_thr: 0.3316 loss_db: 0.0773 2022/10/26 08:56:55 - mmengine - INFO - Epoch(train) [1131][35/63] lr: 2.7078e-04 eta: 0:48:27 time: 0.5388 data_time: 0.0155 memory: 16131 loss: 0.8345 loss_prob: 0.4369 loss_thr: 0.3224 loss_db: 0.0752 2022/10/26 08:56:57 - mmengine - INFO - Epoch(train) [1131][40/63] lr: 2.7078e-04 eta: 0:48:20 time: 0.5243 data_time: 0.0139 memory: 16131 loss: 0.7832 loss_prob: 0.3987 loss_thr: 0.3135 loss_db: 0.0710 2022/10/26 08:57:00 - mmengine - INFO - Epoch(train) [1131][45/63] lr: 2.7078e-04 eta: 0:48:20 time: 0.5225 data_time: 0.0065 memory: 16131 loss: 0.8173 loss_prob: 0.4179 loss_thr: 0.3254 loss_db: 0.0739 2022/10/26 08:57:03 - mmengine - INFO - Epoch(train) [1131][50/63] lr: 2.7078e-04 eta: 0:48:13 time: 0.5504 data_time: 0.0195 memory: 16131 loss: 0.8661 loss_prob: 0.4492 loss_thr: 0.3371 loss_db: 0.0798 2022/10/26 08:57:05 - mmengine - INFO - Epoch(train) [1131][55/63] lr: 2.7078e-04 eta: 0:48:13 time: 0.5232 data_time: 0.0195 memory: 16131 loss: 0.8798 loss_prob: 0.4613 loss_thr: 0.3403 loss_db: 0.0783 2022/10/26 08:57:08 - mmengine - INFO - Epoch(train) [1131][60/63] lr: 2.7078e-04 eta: 0:48:07 time: 0.5133 data_time: 0.0112 memory: 16131 loss: 0.8542 loss_prob: 0.4501 loss_thr: 0.3295 loss_db: 0.0746 2022/10/26 08:57:09 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:57:14 - mmengine - INFO - Epoch(train) [1132][5/63] lr: 2.6725e-04 eta: 0:48:07 time: 0.6779 data_time: 0.1943 memory: 16131 loss: 0.8354 loss_prob: 0.4409 loss_thr: 0.3177 loss_db: 0.0768 2022/10/26 08:57:17 - mmengine - INFO - Epoch(train) [1132][10/63] lr: 2.6725e-04 eta: 0:47:58 time: 0.7809 data_time: 0.1999 memory: 16131 loss: 0.8998 loss_prob: 0.4773 loss_thr: 0.3398 loss_db: 0.0828 2022/10/26 08:57:19 - mmengine - INFO - Epoch(train) [1132][15/63] lr: 2.6725e-04 eta: 0:47:58 time: 0.5955 data_time: 0.0154 memory: 16131 loss: 0.8987 loss_prob: 0.4646 loss_thr: 0.3538 loss_db: 0.0803 2022/10/26 08:57:22 - mmengine - INFO - Epoch(train) [1132][20/63] lr: 2.6725e-04 eta: 0:47:51 time: 0.5075 data_time: 0.0067 memory: 16131 loss: 0.8581 loss_prob: 0.4385 loss_thr: 0.3424 loss_db: 0.0772 2022/10/26 08:57:25 - mmengine - INFO - Epoch(train) [1132][25/63] lr: 2.6725e-04 eta: 0:47:51 time: 0.5378 data_time: 0.0193 memory: 16131 loss: 0.8744 loss_prob: 0.4604 loss_thr: 0.3336 loss_db: 0.0804 2022/10/26 08:57:28 - mmengine - INFO - Epoch(train) [1132][30/63] lr: 2.6725e-04 eta: 0:47:44 time: 0.5674 data_time: 0.0231 memory: 16131 loss: 0.8592 loss_prob: 0.4526 loss_thr: 0.3279 loss_db: 0.0787 2022/10/26 08:57:30 - mmengine - INFO - Epoch(train) [1132][35/63] lr: 2.6725e-04 eta: 0:47:44 time: 0.5343 data_time: 0.0179 memory: 16131 loss: 0.8576 loss_prob: 0.4448 loss_thr: 0.3342 loss_db: 0.0785 2022/10/26 08:57:33 - mmengine - INFO - Epoch(train) [1132][40/63] lr: 2.6725e-04 eta: 0:47:38 time: 0.5057 data_time: 0.0136 memory: 16131 loss: 0.8473 loss_prob: 0.4344 loss_thr: 0.3353 loss_db: 0.0775 2022/10/26 08:57:36 - mmengine - INFO - Epoch(train) [1132][45/63] lr: 2.6725e-04 eta: 0:47:38 time: 0.5492 data_time: 0.0067 memory: 16131 loss: 0.8026 loss_prob: 0.4099 loss_thr: 0.3216 loss_db: 0.0711 2022/10/26 08:57:38 - mmengine - INFO - Epoch(train) [1132][50/63] lr: 2.6725e-04 eta: 0:47:31 time: 0.5649 data_time: 0.0187 memory: 16131 loss: 0.8191 loss_prob: 0.4200 loss_thr: 0.3261 loss_db: 0.0730 2022/10/26 08:57:41 - mmengine - INFO - Epoch(train) [1132][55/63] lr: 2.6725e-04 eta: 0:47:31 time: 0.5161 data_time: 0.0167 memory: 16131 loss: 0.8011 loss_prob: 0.4070 loss_thr: 0.3211 loss_db: 0.0731 2022/10/26 08:57:44 - mmengine - INFO - Epoch(train) [1132][60/63] lr: 2.6725e-04 eta: 0:47:24 time: 0.5141 data_time: 0.0089 memory: 16131 loss: 0.8194 loss_prob: 0.4184 loss_thr: 0.3261 loss_db: 0.0749 2022/10/26 08:57:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:57:50 - mmengine - INFO - Epoch(train) [1133][5/63] lr: 2.6371e-04 eta: 0:47:24 time: 0.7490 data_time: 0.1895 memory: 16131 loss: 0.8230 loss_prob: 0.4229 loss_thr: 0.3267 loss_db: 0.0733 2022/10/26 08:57:53 - mmengine - INFO - Epoch(train) [1133][10/63] lr: 2.6371e-04 eta: 0:47:16 time: 0.8005 data_time: 0.2061 memory: 16131 loss: 0.8018 loss_prob: 0.4129 loss_thr: 0.3178 loss_db: 0.0711 2022/10/26 08:57:56 - mmengine - INFO - Epoch(train) [1133][15/63] lr: 2.6371e-04 eta: 0:47:16 time: 0.5660 data_time: 0.0226 memory: 16131 loss: 0.8327 loss_prob: 0.4316 loss_thr: 0.3248 loss_db: 0.0763 2022/10/26 08:57:58 - mmengine - INFO - Epoch(train) [1133][20/63] lr: 2.6371e-04 eta: 0:47:09 time: 0.5133 data_time: 0.0047 memory: 16131 loss: 0.8581 loss_prob: 0.4586 loss_thr: 0.3215 loss_db: 0.0781 2022/10/26 08:58:01 - mmengine - INFO - Epoch(train) [1133][25/63] lr: 2.6371e-04 eta: 0:47:09 time: 0.5043 data_time: 0.0105 memory: 16131 loss: 0.9145 loss_prob: 0.4977 loss_thr: 0.3338 loss_db: 0.0830 2022/10/26 08:58:03 - mmengine - INFO - Epoch(train) [1133][30/63] lr: 2.6371e-04 eta: 0:47:02 time: 0.5302 data_time: 0.0339 memory: 16131 loss: 0.9958 loss_prob: 0.5381 loss_thr: 0.3675 loss_db: 0.0903 2022/10/26 08:58:06 - mmengine - INFO - Epoch(train) [1133][35/63] lr: 2.6371e-04 eta: 0:47:02 time: 0.5364 data_time: 0.0310 memory: 16131 loss: 0.9195 loss_prob: 0.4827 loss_thr: 0.3556 loss_db: 0.0813 2022/10/26 08:58:09 - mmengine - INFO - Epoch(train) [1133][40/63] lr: 2.6371e-04 eta: 0:46:55 time: 0.5134 data_time: 0.0076 memory: 16131 loss: 0.8237 loss_prob: 0.4269 loss_thr: 0.3219 loss_db: 0.0748 2022/10/26 08:58:11 - mmengine - INFO - Epoch(train) [1133][45/63] lr: 2.6371e-04 eta: 0:46:55 time: 0.4971 data_time: 0.0051 memory: 16131 loss: 0.7925 loss_prob: 0.4117 loss_thr: 0.3064 loss_db: 0.0743 2022/10/26 08:58:14 - mmengine - INFO - Epoch(train) [1133][50/63] lr: 2.6371e-04 eta: 0:46:49 time: 0.5186 data_time: 0.0102 memory: 16131 loss: 0.8250 loss_prob: 0.4266 loss_thr: 0.3242 loss_db: 0.0742 2022/10/26 08:58:16 - mmengine - INFO - Epoch(train) [1133][55/63] lr: 2.6371e-04 eta: 0:46:49 time: 0.5349 data_time: 0.0204 memory: 16131 loss: 0.8913 loss_prob: 0.4691 loss_thr: 0.3440 loss_db: 0.0782 2022/10/26 08:58:19 - mmengine - INFO - Epoch(train) [1133][60/63] lr: 2.6371e-04 eta: 0:46:42 time: 0.5146 data_time: 0.0184 memory: 16131 loss: 0.8743 loss_prob: 0.4629 loss_thr: 0.3308 loss_db: 0.0806 2022/10/26 08:58:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:58:26 - mmengine - INFO - Epoch(train) [1134][5/63] lr: 2.6017e-04 eta: 0:46:42 time: 0.7657 data_time: 0.2299 memory: 16131 loss: 0.8272 loss_prob: 0.4287 loss_thr: 0.3228 loss_db: 0.0757 2022/10/26 08:58:28 - mmengine - INFO - Epoch(train) [1134][10/63] lr: 2.6017e-04 eta: 0:46:33 time: 0.7844 data_time: 0.2290 memory: 16131 loss: 0.9798 loss_prob: 0.5250 loss_thr: 0.3638 loss_db: 0.0909 2022/10/26 08:58:31 - mmengine - INFO - Epoch(train) [1134][15/63] lr: 2.6017e-04 eta: 0:46:33 time: 0.5146 data_time: 0.0066 memory: 16131 loss: 0.9610 loss_prob: 0.5120 loss_thr: 0.3621 loss_db: 0.0869 2022/10/26 08:58:33 - mmengine - INFO - Epoch(train) [1134][20/63] lr: 2.6017e-04 eta: 0:46:27 time: 0.5109 data_time: 0.0130 memory: 16131 loss: 0.9064 loss_prob: 0.4796 loss_thr: 0.3473 loss_db: 0.0795 2022/10/26 08:58:36 - mmengine - INFO - Epoch(train) [1134][25/63] lr: 2.6017e-04 eta: 0:46:27 time: 0.5145 data_time: 0.0340 memory: 16131 loss: 0.9143 loss_prob: 0.4824 loss_thr: 0.3504 loss_db: 0.0816 2022/10/26 08:58:38 - mmengine - INFO - Epoch(train) [1134][30/63] lr: 2.6017e-04 eta: 0:46:20 time: 0.5225 data_time: 0.0272 memory: 16131 loss: 0.8327 loss_prob: 0.4219 loss_thr: 0.3364 loss_db: 0.0744 2022/10/26 08:58:41 - mmengine - INFO - Epoch(train) [1134][35/63] lr: 2.6017e-04 eta: 0:46:20 time: 0.5159 data_time: 0.0095 memory: 16131 loss: 0.8733 loss_prob: 0.4462 loss_thr: 0.3481 loss_db: 0.0790 2022/10/26 08:58:44 - mmengine - INFO - Epoch(train) [1134][40/63] lr: 2.6017e-04 eta: 0:46:13 time: 0.5118 data_time: 0.0150 memory: 16131 loss: 0.8815 loss_prob: 0.4640 loss_thr: 0.3341 loss_db: 0.0834 2022/10/26 08:58:46 - mmengine - INFO - Epoch(train) [1134][45/63] lr: 2.6017e-04 eta: 0:46:13 time: 0.4988 data_time: 0.0103 memory: 16131 loss: 0.8801 loss_prob: 0.4661 loss_thr: 0.3307 loss_db: 0.0832 2022/10/26 08:58:49 - mmengine - INFO - Epoch(train) [1134][50/63] lr: 2.6017e-04 eta: 0:46:06 time: 0.5194 data_time: 0.0199 memory: 16131 loss: 0.8609 loss_prob: 0.4427 loss_thr: 0.3403 loss_db: 0.0778 2022/10/26 08:58:52 - mmengine - INFO - Epoch(train) [1134][55/63] lr: 2.6017e-04 eta: 0:46:06 time: 0.5511 data_time: 0.0201 memory: 16131 loss: 0.8320 loss_prob: 0.4195 loss_thr: 0.3401 loss_db: 0.0724 2022/10/26 08:58:54 - mmengine - INFO - Epoch(train) [1134][60/63] lr: 2.6017e-04 eta: 0:46:00 time: 0.5416 data_time: 0.0084 memory: 16131 loss: 0.8666 loss_prob: 0.4441 loss_thr: 0.3448 loss_db: 0.0777 2022/10/26 08:58:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:59:00 - mmengine - INFO - Epoch(train) [1135][5/63] lr: 2.5662e-04 eta: 0:46:00 time: 0.6857 data_time: 0.2100 memory: 16131 loss: 0.9036 loss_prob: 0.4672 loss_thr: 0.3559 loss_db: 0.0806 2022/10/26 08:59:02 - mmengine - INFO - Epoch(train) [1135][10/63] lr: 2.5662e-04 eta: 0:45:51 time: 0.7058 data_time: 0.2080 memory: 16131 loss: 0.9328 loss_prob: 0.4870 loss_thr: 0.3612 loss_db: 0.0845 2022/10/26 08:59:05 - mmengine - INFO - Epoch(train) [1135][15/63] lr: 2.5662e-04 eta: 0:45:51 time: 0.4885 data_time: 0.0053 memory: 16131 loss: 0.9737 loss_prob: 0.5294 loss_thr: 0.3554 loss_db: 0.0889 2022/10/26 08:59:07 - mmengine - INFO - Epoch(train) [1135][20/63] lr: 2.5662e-04 eta: 0:45:44 time: 0.4913 data_time: 0.0090 memory: 16131 loss: 0.9757 loss_prob: 0.5200 loss_thr: 0.3663 loss_db: 0.0894 2022/10/26 08:59:10 - mmengine - INFO - Epoch(train) [1135][25/63] lr: 2.5662e-04 eta: 0:45:44 time: 0.5235 data_time: 0.0341 memory: 16131 loss: 0.8813 loss_prob: 0.4505 loss_thr: 0.3512 loss_db: 0.0795 2022/10/26 08:59:13 - mmengine - INFO - Epoch(train) [1135][30/63] lr: 2.5662e-04 eta: 0:45:38 time: 0.5210 data_time: 0.0312 memory: 16131 loss: 0.8205 loss_prob: 0.4176 loss_thr: 0.3308 loss_db: 0.0721 2022/10/26 08:59:15 - mmengine - INFO - Epoch(train) [1135][35/63] lr: 2.5662e-04 eta: 0:45:38 time: 0.4861 data_time: 0.0055 memory: 16131 loss: 0.8115 loss_prob: 0.4140 loss_thr: 0.3249 loss_db: 0.0725 2022/10/26 08:59:18 - mmengine - INFO - Epoch(train) [1135][40/63] lr: 2.5662e-04 eta: 0:45:31 time: 0.5136 data_time: 0.0047 memory: 16131 loss: 0.8203 loss_prob: 0.4243 loss_thr: 0.3215 loss_db: 0.0745 2022/10/26 08:59:20 - mmengine - INFO - Epoch(train) [1135][45/63] lr: 2.5662e-04 eta: 0:45:31 time: 0.5184 data_time: 0.0065 memory: 16131 loss: 0.8249 loss_prob: 0.4278 loss_thr: 0.3227 loss_db: 0.0744 2022/10/26 08:59:23 - mmengine - INFO - Epoch(train) [1135][50/63] lr: 2.5662e-04 eta: 0:45:24 time: 0.5469 data_time: 0.0225 memory: 16131 loss: 0.8800 loss_prob: 0.4506 loss_thr: 0.3512 loss_db: 0.0782 2022/10/26 08:59:26 - mmengine - INFO - Epoch(train) [1135][55/63] lr: 2.5662e-04 eta: 0:45:24 time: 0.5687 data_time: 0.0209 memory: 16131 loss: 0.8795 loss_prob: 0.4546 loss_thr: 0.3465 loss_db: 0.0784 2022/10/26 08:59:29 - mmengine - INFO - Epoch(train) [1135][60/63] lr: 2.5662e-04 eta: 0:45:17 time: 0.5406 data_time: 0.0053 memory: 16131 loss: 0.7960 loss_prob: 0.4117 loss_thr: 0.3130 loss_db: 0.0713 2022/10/26 08:59:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 08:59:35 - mmengine - INFO - Epoch(train) [1136][5/63] lr: 2.5306e-04 eta: 0:45:17 time: 0.7170 data_time: 0.1684 memory: 16131 loss: 0.8791 loss_prob: 0.4594 loss_thr: 0.3406 loss_db: 0.0792 2022/10/26 08:59:37 - mmengine - INFO - Epoch(train) [1136][10/63] lr: 2.5306e-04 eta: 0:45:09 time: 0.7324 data_time: 0.1666 memory: 16131 loss: 0.9315 loss_prob: 0.4968 loss_thr: 0.3497 loss_db: 0.0850 2022/10/26 08:59:40 - mmengine - INFO - Epoch(train) [1136][15/63] lr: 2.5306e-04 eta: 0:45:09 time: 0.5178 data_time: 0.0072 memory: 16131 loss: 0.8163 loss_prob: 0.4267 loss_thr: 0.3165 loss_db: 0.0731 2022/10/26 08:59:42 - mmengine - INFO - Epoch(train) [1136][20/63] lr: 2.5306e-04 eta: 0:45:02 time: 0.5151 data_time: 0.0076 memory: 16131 loss: 0.7629 loss_prob: 0.3929 loss_thr: 0.3019 loss_db: 0.0682 2022/10/26 08:59:45 - mmengine - INFO - Epoch(train) [1136][25/63] lr: 2.5306e-04 eta: 0:45:02 time: 0.5140 data_time: 0.0137 memory: 16131 loss: 0.7902 loss_prob: 0.4048 loss_thr: 0.3153 loss_db: 0.0702 2022/10/26 08:59:48 - mmengine - INFO - Epoch(train) [1136][30/63] lr: 2.5306e-04 eta: 0:44:55 time: 0.5381 data_time: 0.0379 memory: 16131 loss: 0.8411 loss_prob: 0.4308 loss_thr: 0.3360 loss_db: 0.0743 2022/10/26 08:59:51 - mmengine - INFO - Epoch(train) [1136][35/63] lr: 2.5306e-04 eta: 0:44:55 time: 0.5519 data_time: 0.0293 memory: 16131 loss: 0.8670 loss_prob: 0.4512 loss_thr: 0.3373 loss_db: 0.0784 2022/10/26 08:59:53 - mmengine - INFO - Epoch(train) [1136][40/63] lr: 2.5306e-04 eta: 0:44:49 time: 0.5453 data_time: 0.0044 memory: 16131 loss: 0.9032 loss_prob: 0.4823 loss_thr: 0.3373 loss_db: 0.0835 2022/10/26 08:59:56 - mmengine - INFO - Epoch(train) [1136][45/63] lr: 2.5306e-04 eta: 0:44:49 time: 0.5458 data_time: 0.0061 memory: 16131 loss: 0.8943 loss_prob: 0.4670 loss_thr: 0.3460 loss_db: 0.0814 2022/10/26 08:59:59 - mmengine - INFO - Epoch(train) [1136][50/63] lr: 2.5306e-04 eta: 0:44:42 time: 0.5399 data_time: 0.0139 memory: 16131 loss: 0.8579 loss_prob: 0.4263 loss_thr: 0.3565 loss_db: 0.0750 2022/10/26 09:00:01 - mmengine - INFO - Epoch(train) [1136][55/63] lr: 2.5306e-04 eta: 0:44:42 time: 0.5405 data_time: 0.0257 memory: 16131 loss: 0.8582 loss_prob: 0.4278 loss_thr: 0.3555 loss_db: 0.0749 2022/10/26 09:00:04 - mmengine - INFO - Epoch(train) [1136][60/63] lr: 2.5306e-04 eta: 0:44:35 time: 0.5457 data_time: 0.0213 memory: 16131 loss: 0.8391 loss_prob: 0.4318 loss_thr: 0.3317 loss_db: 0.0756 2022/10/26 09:00:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:00:10 - mmengine - INFO - Epoch(train) [1137][5/63] lr: 2.4950e-04 eta: 0:44:35 time: 0.6663 data_time: 0.1739 memory: 16131 loss: 0.7907 loss_prob: 0.4123 loss_thr: 0.3060 loss_db: 0.0724 2022/10/26 09:00:12 - mmengine - INFO - Epoch(train) [1137][10/63] lr: 2.4950e-04 eta: 0:44:27 time: 0.6990 data_time: 0.1734 memory: 16131 loss: 0.7712 loss_prob: 0.3929 loss_thr: 0.3083 loss_db: 0.0701 2022/10/26 09:00:15 - mmengine - INFO - Epoch(train) [1137][15/63] lr: 2.4950e-04 eta: 0:44:27 time: 0.5356 data_time: 0.0075 memory: 16131 loss: 0.8311 loss_prob: 0.4273 loss_thr: 0.3281 loss_db: 0.0757 2022/10/26 09:00:18 - mmengine - INFO - Epoch(train) [1137][20/63] lr: 2.4950e-04 eta: 0:44:20 time: 0.5547 data_time: 0.0099 memory: 16131 loss: 0.8919 loss_prob: 0.4689 loss_thr: 0.3414 loss_db: 0.0817 2022/10/26 09:00:21 - mmengine - INFO - Epoch(train) [1137][25/63] lr: 2.4950e-04 eta: 0:44:20 time: 0.5364 data_time: 0.0352 memory: 16131 loss: 0.9490 loss_prob: 0.4962 loss_thr: 0.3665 loss_db: 0.0863 2022/10/26 09:00:23 - mmengine - INFO - Epoch(train) [1137][30/63] lr: 2.4950e-04 eta: 0:44:13 time: 0.5164 data_time: 0.0318 memory: 16131 loss: 0.9352 loss_prob: 0.4832 loss_thr: 0.3684 loss_db: 0.0836 2022/10/26 09:00:26 - mmengine - INFO - Epoch(train) [1137][35/63] lr: 2.4950e-04 eta: 0:44:13 time: 0.5215 data_time: 0.0043 memory: 16131 loss: 0.8404 loss_prob: 0.4355 loss_thr: 0.3306 loss_db: 0.0743 2022/10/26 09:00:28 - mmengine - INFO - Epoch(train) [1137][40/63] lr: 2.4950e-04 eta: 0:44:06 time: 0.5174 data_time: 0.0051 memory: 16131 loss: 0.8633 loss_prob: 0.4489 loss_thr: 0.3359 loss_db: 0.0785 2022/10/26 09:00:31 - mmengine - INFO - Epoch(train) [1137][45/63] lr: 2.4950e-04 eta: 0:44:06 time: 0.5098 data_time: 0.0076 memory: 16131 loss: 0.8740 loss_prob: 0.4550 loss_thr: 0.3381 loss_db: 0.0809 2022/10/26 09:00:34 - mmengine - INFO - Epoch(train) [1137][50/63] lr: 2.4950e-04 eta: 0:44:00 time: 0.5993 data_time: 0.0250 memory: 16131 loss: 0.8563 loss_prob: 0.4456 loss_thr: 0.3312 loss_db: 0.0795 2022/10/26 09:00:37 - mmengine - INFO - Epoch(train) [1137][55/63] lr: 2.4950e-04 eta: 0:44:00 time: 0.5818 data_time: 0.0227 memory: 16131 loss: 0.8548 loss_prob: 0.4432 loss_thr: 0.3322 loss_db: 0.0794 2022/10/26 09:00:39 - mmengine - INFO - Epoch(train) [1137][60/63] lr: 2.4950e-04 eta: 0:43:53 time: 0.5017 data_time: 0.0049 memory: 16131 loss: 0.9254 loss_prob: 0.4983 loss_thr: 0.3434 loss_db: 0.0837 2022/10/26 09:00:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:00:46 - mmengine - INFO - Epoch(train) [1138][5/63] lr: 2.4594e-04 eta: 0:43:53 time: 0.7316 data_time: 0.1788 memory: 16131 loss: 0.9622 loss_prob: 0.5024 loss_thr: 0.3730 loss_db: 0.0867 2022/10/26 09:00:48 - mmengine - INFO - Epoch(train) [1138][10/63] lr: 2.4594e-04 eta: 0:43:44 time: 0.7249 data_time: 0.1788 memory: 16131 loss: 1.0102 loss_prob: 0.5382 loss_thr: 0.3811 loss_db: 0.0909 2022/10/26 09:00:51 - mmengine - INFO - Epoch(train) [1138][15/63] lr: 2.4594e-04 eta: 0:43:44 time: 0.5241 data_time: 0.0048 memory: 16131 loss: 0.8384 loss_prob: 0.4381 loss_thr: 0.3240 loss_db: 0.0763 2022/10/26 09:00:54 - mmengine - INFO - Epoch(train) [1138][20/63] lr: 2.4594e-04 eta: 0:43:38 time: 0.5708 data_time: 0.0068 memory: 16131 loss: 0.7676 loss_prob: 0.3934 loss_thr: 0.3042 loss_db: 0.0700 2022/10/26 09:00:56 - mmengine - INFO - Epoch(train) [1138][25/63] lr: 2.4594e-04 eta: 0:43:38 time: 0.5702 data_time: 0.0136 memory: 16131 loss: 0.8066 loss_prob: 0.4146 loss_thr: 0.3172 loss_db: 0.0748 2022/10/26 09:00:59 - mmengine - INFO - Epoch(train) [1138][30/63] lr: 2.4594e-04 eta: 0:43:31 time: 0.5647 data_time: 0.0430 memory: 16131 loss: 0.8182 loss_prob: 0.4177 loss_thr: 0.3255 loss_db: 0.0750 2022/10/26 09:01:02 - mmengine - INFO - Epoch(train) [1138][35/63] lr: 2.4594e-04 eta: 0:43:31 time: 0.5268 data_time: 0.0367 memory: 16131 loss: 0.7899 loss_prob: 0.4023 loss_thr: 0.3175 loss_db: 0.0701 2022/10/26 09:01:05 - mmengine - INFO - Epoch(train) [1138][40/63] lr: 2.4594e-04 eta: 0:43:24 time: 0.5256 data_time: 0.0050 memory: 16131 loss: 0.8010 loss_prob: 0.4151 loss_thr: 0.3140 loss_db: 0.0718 2022/10/26 09:01:07 - mmengine - INFO - Epoch(train) [1138][45/63] lr: 2.4594e-04 eta: 0:43:24 time: 0.5474 data_time: 0.0052 memory: 16131 loss: 0.8049 loss_prob: 0.4180 loss_thr: 0.3137 loss_db: 0.0732 2022/10/26 09:01:10 - mmengine - INFO - Epoch(train) [1138][50/63] lr: 2.4594e-04 eta: 0:43:18 time: 0.5500 data_time: 0.0155 memory: 16131 loss: 0.8994 loss_prob: 0.4716 loss_thr: 0.3447 loss_db: 0.0832 2022/10/26 09:01:13 - mmengine - INFO - Epoch(train) [1138][55/63] lr: 2.4594e-04 eta: 0:43:18 time: 0.5889 data_time: 0.0276 memory: 16131 loss: 0.9494 loss_prob: 0.5026 loss_thr: 0.3575 loss_db: 0.0892 2022/10/26 09:01:16 - mmengine - INFO - Epoch(train) [1138][60/63] lr: 2.4594e-04 eta: 0:43:11 time: 0.5505 data_time: 0.0176 memory: 16131 loss: 0.9188 loss_prob: 0.4845 loss_thr: 0.3497 loss_db: 0.0846 2022/10/26 09:01:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:01:21 - mmengine - INFO - Epoch(train) [1139][5/63] lr: 2.4237e-04 eta: 0:43:11 time: 0.6334 data_time: 0.1722 memory: 16131 loss: 0.8968 loss_prob: 0.4766 loss_thr: 0.3417 loss_db: 0.0784 2022/10/26 09:01:24 - mmengine - INFO - Epoch(train) [1139][10/63] lr: 2.4237e-04 eta: 0:43:02 time: 0.6773 data_time: 0.1714 memory: 16131 loss: 0.8290 loss_prob: 0.4284 loss_thr: 0.3255 loss_db: 0.0751 2022/10/26 09:01:26 - mmengine - INFO - Epoch(train) [1139][15/63] lr: 2.4237e-04 eta: 0:43:02 time: 0.5283 data_time: 0.0107 memory: 16131 loss: 0.8592 loss_prob: 0.4386 loss_thr: 0.3427 loss_db: 0.0780 2022/10/26 09:01:29 - mmengine - INFO - Epoch(train) [1139][20/63] lr: 2.4237e-04 eta: 0:42:56 time: 0.5662 data_time: 0.0127 memory: 16131 loss: 0.8595 loss_prob: 0.4398 loss_thr: 0.3421 loss_db: 0.0776 2022/10/26 09:01:32 - mmengine - INFO - Epoch(train) [1139][25/63] lr: 2.4237e-04 eta: 0:42:56 time: 0.5815 data_time: 0.0222 memory: 16131 loss: 0.9091 loss_prob: 0.4840 loss_thr: 0.3435 loss_db: 0.0816 2022/10/26 09:01:35 - mmengine - INFO - Epoch(train) [1139][30/63] lr: 2.4237e-04 eta: 0:42:49 time: 0.5469 data_time: 0.0311 memory: 16131 loss: 0.9218 loss_prob: 0.4939 loss_thr: 0.3453 loss_db: 0.0827 2022/10/26 09:01:38 - mmengine - INFO - Epoch(train) [1139][35/63] lr: 2.4237e-04 eta: 0:42:49 time: 0.5534 data_time: 0.0157 memory: 16131 loss: 0.8357 loss_prob: 0.4320 loss_thr: 0.3280 loss_db: 0.0756 2022/10/26 09:01:40 - mmengine - INFO - Epoch(train) [1139][40/63] lr: 2.4237e-04 eta: 0:42:42 time: 0.5579 data_time: 0.0119 memory: 16131 loss: 0.8340 loss_prob: 0.4317 loss_thr: 0.3258 loss_db: 0.0766 2022/10/26 09:01:43 - mmengine - INFO - Epoch(train) [1139][45/63] lr: 2.4237e-04 eta: 0:42:42 time: 0.5225 data_time: 0.0138 memory: 16131 loss: 0.8621 loss_prob: 0.4496 loss_thr: 0.3328 loss_db: 0.0797 2022/10/26 09:01:46 - mmengine - INFO - Epoch(train) [1139][50/63] lr: 2.4237e-04 eta: 0:42:35 time: 0.5173 data_time: 0.0184 memory: 16131 loss: 0.8073 loss_prob: 0.4086 loss_thr: 0.3271 loss_db: 0.0717 2022/10/26 09:01:48 - mmengine - INFO - Epoch(train) [1139][55/63] lr: 2.4237e-04 eta: 0:42:35 time: 0.5348 data_time: 0.0204 memory: 16131 loss: 0.8195 loss_prob: 0.4170 loss_thr: 0.3296 loss_db: 0.0729 2022/10/26 09:01:51 - mmengine - INFO - Epoch(train) [1139][60/63] lr: 2.4237e-04 eta: 0:42:29 time: 0.5533 data_time: 0.0122 memory: 16131 loss: 0.8442 loss_prob: 0.4473 loss_thr: 0.3214 loss_db: 0.0755 2022/10/26 09:01:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:01:57 - mmengine - INFO - Epoch(train) [1140][5/63] lr: 2.3879e-04 eta: 0:42:29 time: 0.7416 data_time: 0.1932 memory: 16131 loss: 0.8525 loss_prob: 0.4483 loss_thr: 0.3296 loss_db: 0.0746 2022/10/26 09:02:00 - mmengine - INFO - Epoch(train) [1140][10/63] lr: 2.3879e-04 eta: 0:42:20 time: 0.7291 data_time: 0.2032 memory: 16131 loss: 0.8333 loss_prob: 0.4313 loss_thr: 0.3282 loss_db: 0.0738 2022/10/26 09:02:02 - mmengine - INFO - Epoch(train) [1140][15/63] lr: 2.3879e-04 eta: 0:42:20 time: 0.5218 data_time: 0.0190 memory: 16131 loss: 0.8973 loss_prob: 0.4638 loss_thr: 0.3522 loss_db: 0.0813 2022/10/26 09:02:05 - mmengine - INFO - Epoch(train) [1140][20/63] lr: 2.3879e-04 eta: 0:42:13 time: 0.5036 data_time: 0.0060 memory: 16131 loss: 0.8933 loss_prob: 0.4658 loss_thr: 0.3439 loss_db: 0.0836 2022/10/26 09:02:08 - mmengine - INFO - Epoch(train) [1140][25/63] lr: 2.3879e-04 eta: 0:42:13 time: 0.5108 data_time: 0.0303 memory: 16131 loss: 0.8433 loss_prob: 0.4430 loss_thr: 0.3213 loss_db: 0.0790 2022/10/26 09:02:10 - mmengine - INFO - Epoch(train) [1140][30/63] lr: 2.3879e-04 eta: 0:42:07 time: 0.5331 data_time: 0.0307 memory: 16131 loss: 0.8670 loss_prob: 0.4540 loss_thr: 0.3340 loss_db: 0.0790 2022/10/26 09:02:13 - mmengine - INFO - Epoch(train) [1140][35/63] lr: 2.3879e-04 eta: 0:42:07 time: 0.5556 data_time: 0.0111 memory: 16131 loss: 0.8377 loss_prob: 0.4350 loss_thr: 0.3263 loss_db: 0.0764 2022/10/26 09:02:16 - mmengine - INFO - Epoch(train) [1140][40/63] lr: 2.3879e-04 eta: 0:42:00 time: 0.5406 data_time: 0.0113 memory: 16131 loss: 0.8626 loss_prob: 0.4565 loss_thr: 0.3260 loss_db: 0.0801 2022/10/26 09:02:18 - mmengine - INFO - Epoch(train) [1140][45/63] lr: 2.3879e-04 eta: 0:42:00 time: 0.5204 data_time: 0.0055 memory: 16131 loss: 0.9215 loss_prob: 0.4844 loss_thr: 0.3519 loss_db: 0.0852 2022/10/26 09:02:21 - mmengine - INFO - Epoch(train) [1140][50/63] lr: 2.3879e-04 eta: 0:41:53 time: 0.5566 data_time: 0.0171 memory: 16131 loss: 0.9497 loss_prob: 0.5210 loss_thr: 0.3454 loss_db: 0.0832 2022/10/26 09:02:24 - mmengine - INFO - Epoch(train) [1140][55/63] lr: 2.3879e-04 eta: 0:41:53 time: 0.5340 data_time: 0.0174 memory: 16131 loss: 0.9828 loss_prob: 0.5491 loss_thr: 0.3475 loss_db: 0.0862 2022/10/26 09:02:26 - mmengine - INFO - Epoch(train) [1140][60/63] lr: 2.3879e-04 eta: 0:41:47 time: 0.5166 data_time: 0.0100 memory: 16131 loss: 0.9009 loss_prob: 0.4751 loss_thr: 0.3446 loss_db: 0.0812 2022/10/26 09:02:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:02:28 - mmengine - INFO - Saving checkpoint at 1140 epochs 2022/10/26 09:02:34 - mmengine - INFO - Epoch(val) [1140][5/32] eta: 0:41:47 time: 0.5208 data_time: 0.0698 memory: 16131 2022/10/26 09:02:37 - mmengine - INFO - Epoch(val) [1140][10/32] eta: 0:00:12 time: 0.5682 data_time: 0.0859 memory: 15724 2022/10/26 09:02:39 - mmengine - INFO - Epoch(val) [1140][15/32] eta: 0:00:12 time: 0.5290 data_time: 0.0494 memory: 15724 2022/10/26 09:02:42 - mmengine - INFO - Epoch(val) [1140][20/32] eta: 0:00:06 time: 0.5478 data_time: 0.0702 memory: 15724 2022/10/26 09:02:45 - mmengine - INFO - Epoch(val) [1140][25/32] eta: 0:00:06 time: 0.5404 data_time: 0.0529 memory: 15724 2022/10/26 09:02:47 - mmengine - INFO - Epoch(val) [1140][30/32] eta: 0:00:00 time: 0.4972 data_time: 0.0198 memory: 15724 2022/10/26 09:02:48 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8243, precision: 0.7821, hmean: 0.8026 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8243, precision: 0.8215, hmean: 0.8229 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8238, precision: 0.8445, hmean: 0.8340 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8209, precision: 0.8695, hmean: 0.8445 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8132, precision: 0.8974, hmean: 0.8532 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7496, precision: 0.9312, hmean: 0.8306 2022/10/26 09:02:48 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2234, precision: 0.9831, hmean: 0.3641 2022/10/26 09:02:48 - mmengine - INFO - Epoch(val) [1140][32/32] icdar/precision: 0.8974 icdar/recall: 0.8132 icdar/hmean: 0.8532 2022/10/26 09:02:53 - mmengine - INFO - Epoch(train) [1141][5/63] lr: 2.3521e-04 eta: 0:00:00 time: 0.7275 data_time: 0.1868 memory: 16131 loss: 0.8090 loss_prob: 0.4225 loss_thr: 0.3105 loss_db: 0.0760 2022/10/26 09:02:56 - mmengine - INFO - Epoch(train) [1141][10/63] lr: 2.3521e-04 eta: 0:41:38 time: 0.7859 data_time: 0.1869 memory: 16131 loss: 0.8088 loss_prob: 0.4189 loss_thr: 0.3151 loss_db: 0.0748 2022/10/26 09:02:59 - mmengine - INFO - Epoch(train) [1141][15/63] lr: 2.3521e-04 eta: 0:41:38 time: 0.5622 data_time: 0.0052 memory: 16131 loss: 1.0797 loss_prob: 0.6061 loss_thr: 0.3742 loss_db: 0.0994 2022/10/26 09:03:01 - mmengine - INFO - Epoch(train) [1141][20/63] lr: 2.3521e-04 eta: 0:41:31 time: 0.5687 data_time: 0.0067 memory: 16131 loss: 1.1528 loss_prob: 0.6511 loss_thr: 0.3956 loss_db: 0.1060 2022/10/26 09:03:05 - mmengine - INFO - Epoch(train) [1141][25/63] lr: 2.3521e-04 eta: 0:41:31 time: 0.6151 data_time: 0.0131 memory: 16131 loss: 0.9492 loss_prob: 0.4968 loss_thr: 0.3659 loss_db: 0.0865 2022/10/26 09:03:07 - mmengine - INFO - Epoch(train) [1141][30/63] lr: 2.3521e-04 eta: 0:41:25 time: 0.6002 data_time: 0.0338 memory: 16131 loss: 0.8836 loss_prob: 0.4554 loss_thr: 0.3479 loss_db: 0.0804 2022/10/26 09:03:10 - mmengine - INFO - Epoch(train) [1141][35/63] lr: 2.3521e-04 eta: 0:41:25 time: 0.5503 data_time: 0.0272 memory: 16131 loss: 0.8391 loss_prob: 0.4412 loss_thr: 0.3222 loss_db: 0.0757 2022/10/26 09:03:13 - mmengine - INFO - Epoch(train) [1141][40/63] lr: 2.3521e-04 eta: 0:41:18 time: 0.5333 data_time: 0.0049 memory: 16131 loss: 0.8515 loss_prob: 0.4490 loss_thr: 0.3245 loss_db: 0.0780 2022/10/26 09:03:15 - mmengine - INFO - Epoch(train) [1141][45/63] lr: 2.3521e-04 eta: 0:41:18 time: 0.5170 data_time: 0.0082 memory: 16131 loss: 0.8607 loss_prob: 0.4517 loss_thr: 0.3307 loss_db: 0.0783 2022/10/26 09:03:18 - mmengine - INFO - Epoch(train) [1141][50/63] lr: 2.3521e-04 eta: 0:41:11 time: 0.5603 data_time: 0.0242 memory: 16131 loss: 0.8280 loss_prob: 0.4289 loss_thr: 0.3249 loss_db: 0.0743 2022/10/26 09:03:21 - mmengine - INFO - Epoch(train) [1141][55/63] lr: 2.3521e-04 eta: 0:41:11 time: 0.5425 data_time: 0.0223 memory: 16131 loss: 0.8471 loss_prob: 0.4370 loss_thr: 0.3330 loss_db: 0.0771 2022/10/26 09:03:23 - mmengine - INFO - Epoch(train) [1141][60/63] lr: 2.3521e-04 eta: 0:41:04 time: 0.4891 data_time: 0.0074 memory: 16131 loss: 0.7887 loss_prob: 0.4042 loss_thr: 0.3141 loss_db: 0.0704 2022/10/26 09:03:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:03:29 - mmengine - INFO - Epoch(train) [1142][5/63] lr: 2.3162e-04 eta: 0:41:04 time: 0.6766 data_time: 0.1756 memory: 16131 loss: 0.7641 loss_prob: 0.3953 loss_thr: 0.2991 loss_db: 0.0697 2022/10/26 09:03:32 - mmengine - INFO - Epoch(train) [1142][10/63] lr: 2.3162e-04 eta: 0:40:56 time: 0.7184 data_time: 0.1742 memory: 16131 loss: 0.8365 loss_prob: 0.4428 loss_thr: 0.3163 loss_db: 0.0773 2022/10/26 09:03:35 - mmengine - INFO - Epoch(train) [1142][15/63] lr: 2.3162e-04 eta: 0:40:56 time: 0.5661 data_time: 0.0070 memory: 16131 loss: 0.9874 loss_prob: 0.5144 loss_thr: 0.3815 loss_db: 0.0915 2022/10/26 09:03:37 - mmengine - INFO - Epoch(train) [1142][20/63] lr: 2.3162e-04 eta: 0:40:49 time: 0.5613 data_time: 0.0081 memory: 16131 loss: 0.9898 loss_prob: 0.5115 loss_thr: 0.3874 loss_db: 0.0909 2022/10/26 09:03:40 - mmengine - INFO - Epoch(train) [1142][25/63] lr: 2.3162e-04 eta: 0:40:49 time: 0.5758 data_time: 0.0187 memory: 16131 loss: 0.7918 loss_prob: 0.4126 loss_thr: 0.3080 loss_db: 0.0712 2022/10/26 09:03:43 - mmengine - INFO - Epoch(train) [1142][30/63] lr: 2.3162e-04 eta: 0:40:42 time: 0.5866 data_time: 0.0279 memory: 16131 loss: 0.7711 loss_prob: 0.3957 loss_thr: 0.3061 loss_db: 0.0692 2022/10/26 09:03:46 - mmengine - INFO - Epoch(train) [1142][35/63] lr: 2.3162e-04 eta: 0:40:42 time: 0.5262 data_time: 0.0194 memory: 16131 loss: 0.8561 loss_prob: 0.4448 loss_thr: 0.3334 loss_db: 0.0779 2022/10/26 09:03:48 - mmengine - INFO - Epoch(train) [1142][40/63] lr: 2.3162e-04 eta: 0:40:36 time: 0.5023 data_time: 0.0149 memory: 16131 loss: 0.9805 loss_prob: 0.5306 loss_thr: 0.3605 loss_db: 0.0893 2022/10/26 09:03:51 - mmengine - INFO - Epoch(train) [1142][45/63] lr: 2.3162e-04 eta: 0:40:36 time: 0.4945 data_time: 0.0111 memory: 16131 loss: 0.9018 loss_prob: 0.4765 loss_thr: 0.3433 loss_db: 0.0820 2022/10/26 09:03:53 - mmengine - INFO - Epoch(train) [1142][50/63] lr: 2.3162e-04 eta: 0:40:29 time: 0.5159 data_time: 0.0168 memory: 16131 loss: 0.8139 loss_prob: 0.4206 loss_thr: 0.3198 loss_db: 0.0735 2022/10/26 09:03:56 - mmengine - INFO - Epoch(train) [1142][55/63] lr: 2.3162e-04 eta: 0:40:29 time: 0.5196 data_time: 0.0161 memory: 16131 loss: 0.8365 loss_prob: 0.4356 loss_thr: 0.3260 loss_db: 0.0750 2022/10/26 09:03:58 - mmengine - INFO - Epoch(train) [1142][60/63] lr: 2.3162e-04 eta: 0:40:22 time: 0.4965 data_time: 0.0110 memory: 16131 loss: 0.7998 loss_prob: 0.4094 loss_thr: 0.3178 loss_db: 0.0725 2022/10/26 09:04:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:04:04 - mmengine - INFO - Epoch(train) [1143][5/63] lr: 2.2802e-04 eta: 0:40:22 time: 0.6904 data_time: 0.1991 memory: 16131 loss: 0.8348 loss_prob: 0.4305 loss_thr: 0.3303 loss_db: 0.0739 2022/10/26 09:04:07 - mmengine - INFO - Epoch(train) [1143][10/63] lr: 2.2802e-04 eta: 0:40:14 time: 0.7166 data_time: 0.1984 memory: 16131 loss: 0.8629 loss_prob: 0.4472 loss_thr: 0.3379 loss_db: 0.0778 2022/10/26 09:04:10 - mmengine - INFO - Epoch(train) [1143][15/63] lr: 2.2802e-04 eta: 0:40:14 time: 0.5427 data_time: 0.0088 memory: 16131 loss: 0.9541 loss_prob: 0.5102 loss_thr: 0.3584 loss_db: 0.0855 2022/10/26 09:04:12 - mmengine - INFO - Epoch(train) [1143][20/63] lr: 2.2802e-04 eta: 0:40:07 time: 0.5301 data_time: 0.0086 memory: 16131 loss: 0.8609 loss_prob: 0.4481 loss_thr: 0.3365 loss_db: 0.0763 2022/10/26 09:04:15 - mmengine - INFO - Epoch(train) [1143][25/63] lr: 2.2802e-04 eta: 0:40:07 time: 0.5595 data_time: 0.0205 memory: 16131 loss: 0.8045 loss_prob: 0.4200 loss_thr: 0.3134 loss_db: 0.0712 2022/10/26 09:04:18 - mmengine - INFO - Epoch(train) [1143][30/63] lr: 2.2802e-04 eta: 0:40:00 time: 0.5838 data_time: 0.0399 memory: 16131 loss: 0.8220 loss_prob: 0.4324 loss_thr: 0.3171 loss_db: 0.0725 2022/10/26 09:04:21 - mmengine - INFO - Epoch(train) [1143][35/63] lr: 2.2802e-04 eta: 0:40:00 time: 0.5212 data_time: 0.0274 memory: 16131 loss: 0.8583 loss_prob: 0.4377 loss_thr: 0.3441 loss_db: 0.0764 2022/10/26 09:04:23 - mmengine - INFO - Epoch(train) [1143][40/63] lr: 2.2802e-04 eta: 0:39:54 time: 0.5177 data_time: 0.0081 memory: 16131 loss: 0.9058 loss_prob: 0.4755 loss_thr: 0.3477 loss_db: 0.0827 2022/10/26 09:04:26 - mmengine - INFO - Epoch(train) [1143][45/63] lr: 2.2802e-04 eta: 0:39:54 time: 0.5268 data_time: 0.0057 memory: 16131 loss: 0.8802 loss_prob: 0.4640 loss_thr: 0.3350 loss_db: 0.0812 2022/10/26 09:04:28 - mmengine - INFO - Epoch(train) [1143][50/63] lr: 2.2802e-04 eta: 0:39:47 time: 0.5016 data_time: 0.0147 memory: 16131 loss: 0.8633 loss_prob: 0.4527 loss_thr: 0.3332 loss_db: 0.0775 2022/10/26 09:04:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:04:31 - mmengine - INFO - Epoch(train) [1143][55/63] lr: 2.2802e-04 eta: 0:39:47 time: 0.5108 data_time: 0.0250 memory: 16131 loss: 0.8561 loss_prob: 0.4483 loss_thr: 0.3311 loss_db: 0.0767 2022/10/26 09:04:33 - mmengine - INFO - Epoch(train) [1143][60/63] lr: 2.2802e-04 eta: 0:39:40 time: 0.5033 data_time: 0.0153 memory: 16131 loss: 0.9059 loss_prob: 0.4743 loss_thr: 0.3474 loss_db: 0.0842 2022/10/26 09:04:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:04:39 - mmengine - INFO - Epoch(train) [1144][5/63] lr: 2.2442e-04 eta: 0:39:40 time: 0.6930 data_time: 0.1948 memory: 16131 loss: 0.9285 loss_prob: 0.4961 loss_thr: 0.3453 loss_db: 0.0870 2022/10/26 09:04:42 - mmengine - INFO - Epoch(train) [1144][10/63] lr: 2.2442e-04 eta: 0:39:32 time: 0.7271 data_time: 0.1980 memory: 16131 loss: 0.9108 loss_prob: 0.4876 loss_thr: 0.3413 loss_db: 0.0819 2022/10/26 09:04:45 - mmengine - INFO - Epoch(train) [1144][15/63] lr: 2.2442e-04 eta: 0:39:32 time: 0.5358 data_time: 0.0158 memory: 16131 loss: 0.8327 loss_prob: 0.4365 loss_thr: 0.3229 loss_db: 0.0733 2022/10/26 09:04:47 - mmengine - INFO - Epoch(train) [1144][20/63] lr: 2.2442e-04 eta: 0:39:25 time: 0.5412 data_time: 0.0138 memory: 16131 loss: 0.8423 loss_prob: 0.4358 loss_thr: 0.3313 loss_db: 0.0752 2022/10/26 09:04:50 - mmengine - INFO - Epoch(train) [1144][25/63] lr: 2.2442e-04 eta: 0:39:25 time: 0.5119 data_time: 0.0117 memory: 16131 loss: 0.9002 loss_prob: 0.4698 loss_thr: 0.3473 loss_db: 0.0831 2022/10/26 09:04:53 - mmengine - INFO - Epoch(train) [1144][30/63] lr: 2.2442e-04 eta: 0:39:18 time: 0.5523 data_time: 0.0364 memory: 16131 loss: 0.8723 loss_prob: 0.4558 loss_thr: 0.3352 loss_db: 0.0812 2022/10/26 09:04:55 - mmengine - INFO - Epoch(train) [1144][35/63] lr: 2.2442e-04 eta: 0:39:18 time: 0.5601 data_time: 0.0399 memory: 16131 loss: 0.8888 loss_prob: 0.4660 loss_thr: 0.3419 loss_db: 0.0808 2022/10/26 09:04:58 - mmengine - INFO - Epoch(train) [1144][40/63] lr: 2.2442e-04 eta: 0:39:11 time: 0.5158 data_time: 0.0201 memory: 16131 loss: 0.9574 loss_prob: 0.5016 loss_thr: 0.3691 loss_db: 0.0867 2022/10/26 09:05:01 - mmengine - INFO - Epoch(train) [1144][45/63] lr: 2.2442e-04 eta: 0:39:11 time: 0.5243 data_time: 0.0118 memory: 16131 loss: 0.8548 loss_prob: 0.4440 loss_thr: 0.3316 loss_db: 0.0793 2022/10/26 09:05:04 - mmengine - INFO - Epoch(train) [1144][50/63] lr: 2.2442e-04 eta: 0:39:05 time: 0.5645 data_time: 0.0225 memory: 16131 loss: 0.8010 loss_prob: 0.4159 loss_thr: 0.3103 loss_db: 0.0748 2022/10/26 09:05:06 - mmengine - INFO - Epoch(train) [1144][55/63] lr: 2.2442e-04 eta: 0:39:05 time: 0.5709 data_time: 0.0240 memory: 16131 loss: 0.8099 loss_prob: 0.4204 loss_thr: 0.3153 loss_db: 0.0742 2022/10/26 09:05:09 - mmengine - INFO - Epoch(train) [1144][60/63] lr: 2.2442e-04 eta: 0:38:58 time: 0.5177 data_time: 0.0070 memory: 16131 loss: 0.7842 loss_prob: 0.4076 loss_thr: 0.3046 loss_db: 0.0721 2022/10/26 09:05:10 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:05:15 - mmengine - INFO - Epoch(train) [1145][5/63] lr: 2.2081e-04 eta: 0:38:58 time: 0.7179 data_time: 0.1881 memory: 16131 loss: 0.8693 loss_prob: 0.4537 loss_thr: 0.3367 loss_db: 0.0789 2022/10/26 09:05:18 - mmengine - INFO - Epoch(train) [1145][10/63] lr: 2.2081e-04 eta: 0:38:49 time: 0.7681 data_time: 0.1885 memory: 16131 loss: 0.8412 loss_prob: 0.4401 loss_thr: 0.3248 loss_db: 0.0763 2022/10/26 09:05:20 - mmengine - INFO - Epoch(train) [1145][15/63] lr: 2.2081e-04 eta: 0:38:49 time: 0.5491 data_time: 0.0066 memory: 16131 loss: 0.9218 loss_prob: 0.4840 loss_thr: 0.3535 loss_db: 0.0843 2022/10/26 09:05:23 - mmengine - INFO - Epoch(train) [1145][20/63] lr: 2.2081e-04 eta: 0:38:43 time: 0.5267 data_time: 0.0095 memory: 16131 loss: 0.8780 loss_prob: 0.4519 loss_thr: 0.3477 loss_db: 0.0784 2022/10/26 09:05:26 - mmengine - INFO - Epoch(train) [1145][25/63] lr: 2.2081e-04 eta: 0:38:43 time: 0.5121 data_time: 0.0165 memory: 16131 loss: 0.7710 loss_prob: 0.3918 loss_thr: 0.3101 loss_db: 0.0692 2022/10/26 09:05:28 - mmengine - INFO - Epoch(train) [1145][30/63] lr: 2.2081e-04 eta: 0:38:36 time: 0.5503 data_time: 0.0331 memory: 16131 loss: 0.7979 loss_prob: 0.4133 loss_thr: 0.3100 loss_db: 0.0746 2022/10/26 09:05:31 - mmengine - INFO - Epoch(train) [1145][35/63] lr: 2.2081e-04 eta: 0:38:36 time: 0.5840 data_time: 0.0314 memory: 16131 loss: 0.8558 loss_prob: 0.4503 loss_thr: 0.3268 loss_db: 0.0787 2022/10/26 09:05:34 - mmengine - INFO - Epoch(train) [1145][40/63] lr: 2.2081e-04 eta: 0:38:29 time: 0.5639 data_time: 0.0131 memory: 16131 loss: 0.9268 loss_prob: 0.4957 loss_thr: 0.3456 loss_db: 0.0855 2022/10/26 09:05:36 - mmengine - INFO - Epoch(train) [1145][45/63] lr: 2.2081e-04 eta: 0:38:29 time: 0.5074 data_time: 0.0075 memory: 16131 loss: 0.9023 loss_prob: 0.4821 loss_thr: 0.3379 loss_db: 0.0823 2022/10/26 09:05:39 - mmengine - INFO - Epoch(train) [1145][50/63] lr: 2.2081e-04 eta: 0:38:23 time: 0.5190 data_time: 0.0188 memory: 16131 loss: 0.9983 loss_prob: 0.5787 loss_thr: 0.3386 loss_db: 0.0809 2022/10/26 09:05:42 - mmengine - INFO - Epoch(train) [1145][55/63] lr: 2.2081e-04 eta: 0:38:23 time: 0.5358 data_time: 0.0215 memory: 16131 loss: 0.9730 loss_prob: 0.5562 loss_thr: 0.3374 loss_db: 0.0794 2022/10/26 09:05:45 - mmengine - INFO - Epoch(train) [1145][60/63] lr: 2.2081e-04 eta: 0:38:16 time: 0.5259 data_time: 0.0086 memory: 16131 loss: 0.8857 loss_prob: 0.4649 loss_thr: 0.3391 loss_db: 0.0817 2022/10/26 09:05:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:05:51 - mmengine - INFO - Epoch(train) [1146][5/63] lr: 2.1720e-04 eta: 0:38:16 time: 0.7335 data_time: 0.1825 memory: 16131 loss: 0.8584 loss_prob: 0.4477 loss_thr: 0.3329 loss_db: 0.0778 2022/10/26 09:05:53 - mmengine - INFO - Epoch(train) [1146][10/63] lr: 2.1720e-04 eta: 0:38:07 time: 0.7339 data_time: 0.1844 memory: 16131 loss: 0.8128 loss_prob: 0.4182 loss_thr: 0.3202 loss_db: 0.0745 2022/10/26 09:05:56 - mmengine - INFO - Epoch(train) [1146][15/63] lr: 2.1720e-04 eta: 0:38:07 time: 0.4873 data_time: 0.0069 memory: 16131 loss: 0.8308 loss_prob: 0.4253 loss_thr: 0.3289 loss_db: 0.0766 2022/10/26 09:05:58 - mmengine - INFO - Epoch(train) [1146][20/63] lr: 2.1720e-04 eta: 0:38:01 time: 0.4989 data_time: 0.0087 memory: 16131 loss: 0.8650 loss_prob: 0.4514 loss_thr: 0.3348 loss_db: 0.0788 2022/10/26 09:06:01 - mmengine - INFO - Epoch(train) [1146][25/63] lr: 2.1720e-04 eta: 0:38:01 time: 0.5155 data_time: 0.0157 memory: 16131 loss: 0.8535 loss_prob: 0.4581 loss_thr: 0.3177 loss_db: 0.0777 2022/10/26 09:06:04 - mmengine - INFO - Epoch(train) [1146][30/63] lr: 2.1720e-04 eta: 0:37:54 time: 0.5573 data_time: 0.0326 memory: 16131 loss: 0.8524 loss_prob: 0.4550 loss_thr: 0.3199 loss_db: 0.0775 2022/10/26 09:06:07 - mmengine - INFO - Epoch(train) [1146][35/63] lr: 2.1720e-04 eta: 0:37:54 time: 0.5770 data_time: 0.0274 memory: 16131 loss: 0.8153 loss_prob: 0.4266 loss_thr: 0.3151 loss_db: 0.0736 2022/10/26 09:06:09 - mmengine - INFO - Epoch(train) [1146][40/63] lr: 2.1720e-04 eta: 0:37:47 time: 0.5251 data_time: 0.0066 memory: 16131 loss: 0.8059 loss_prob: 0.4234 loss_thr: 0.3087 loss_db: 0.0738 2022/10/26 09:06:12 - mmengine - INFO - Epoch(train) [1146][45/63] lr: 2.1720e-04 eta: 0:37:47 time: 0.5065 data_time: 0.0059 memory: 16131 loss: 0.8459 loss_prob: 0.4386 loss_thr: 0.3293 loss_db: 0.0779 2022/10/26 09:06:14 - mmengine - INFO - Epoch(train) [1146][50/63] lr: 2.1720e-04 eta: 0:37:41 time: 0.5101 data_time: 0.0133 memory: 16131 loss: 0.8299 loss_prob: 0.4244 loss_thr: 0.3302 loss_db: 0.0752 2022/10/26 09:06:17 - mmengine - INFO - Epoch(train) [1146][55/63] lr: 2.1720e-04 eta: 0:37:41 time: 0.5103 data_time: 0.0207 memory: 16131 loss: 0.8013 loss_prob: 0.4113 loss_thr: 0.3182 loss_db: 0.0718 2022/10/26 09:06:19 - mmengine - INFO - Epoch(train) [1146][60/63] lr: 2.1720e-04 eta: 0:37:34 time: 0.5025 data_time: 0.0139 memory: 16131 loss: 0.8651 loss_prob: 0.4518 loss_thr: 0.3359 loss_db: 0.0773 2022/10/26 09:06:20 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:06:26 - mmengine - INFO - Epoch(train) [1147][5/63] lr: 2.1357e-04 eta: 0:37:34 time: 0.8025 data_time: 0.1894 memory: 16131 loss: 0.8877 loss_prob: 0.4658 loss_thr: 0.3398 loss_db: 0.0820 2022/10/26 09:06:29 - mmengine - INFO - Epoch(train) [1147][10/63] lr: 2.1357e-04 eta: 0:37:25 time: 0.8280 data_time: 0.1897 memory: 16131 loss: 0.8108 loss_prob: 0.4162 loss_thr: 0.3199 loss_db: 0.0748 2022/10/26 09:06:31 - mmengine - INFO - Epoch(train) [1147][15/63] lr: 2.1357e-04 eta: 0:37:25 time: 0.5002 data_time: 0.0134 memory: 16131 loss: 0.8142 loss_prob: 0.4196 loss_thr: 0.3192 loss_db: 0.0753 2022/10/26 09:06:34 - mmengine - INFO - Epoch(train) [1147][20/63] lr: 2.1357e-04 eta: 0:37:19 time: 0.5123 data_time: 0.0134 memory: 16131 loss: 0.8655 loss_prob: 0.4517 loss_thr: 0.3343 loss_db: 0.0795 2022/10/26 09:06:36 - mmengine - INFO - Epoch(train) [1147][25/63] lr: 2.1357e-04 eta: 0:37:19 time: 0.5240 data_time: 0.0294 memory: 16131 loss: 0.8955 loss_prob: 0.4694 loss_thr: 0.3439 loss_db: 0.0821 2022/10/26 09:06:39 - mmengine - INFO - Epoch(train) [1147][30/63] lr: 2.1357e-04 eta: 0:37:12 time: 0.5214 data_time: 0.0301 memory: 16131 loss: 0.7982 loss_prob: 0.4153 loss_thr: 0.3108 loss_db: 0.0721 2022/10/26 09:06:41 - mmengine - INFO - Epoch(train) [1147][35/63] lr: 2.1357e-04 eta: 0:37:12 time: 0.4987 data_time: 0.0065 memory: 16131 loss: 0.8009 loss_prob: 0.4073 loss_thr: 0.3240 loss_db: 0.0696 2022/10/26 09:06:44 - mmengine - INFO - Epoch(train) [1147][40/63] lr: 2.1357e-04 eta: 0:37:05 time: 0.5222 data_time: 0.0130 memory: 16131 loss: 0.8530 loss_prob: 0.4408 loss_thr: 0.3361 loss_db: 0.0761 2022/10/26 09:06:47 - mmengine - INFO - Epoch(train) [1147][45/63] lr: 2.1357e-04 eta: 0:37:05 time: 0.5400 data_time: 0.0128 memory: 16131 loss: 0.8774 loss_prob: 0.4705 loss_thr: 0.3225 loss_db: 0.0844 2022/10/26 09:06:49 - mmengine - INFO - Epoch(train) [1147][50/63] lr: 2.1357e-04 eta: 0:36:59 time: 0.5139 data_time: 0.0198 memory: 16131 loss: 0.9123 loss_prob: 0.4828 loss_thr: 0.3427 loss_db: 0.0868 2022/10/26 09:06:52 - mmengine - INFO - Epoch(train) [1147][55/63] lr: 2.1357e-04 eta: 0:36:59 time: 0.5053 data_time: 0.0195 memory: 16131 loss: 0.8514 loss_prob: 0.4370 loss_thr: 0.3376 loss_db: 0.0767 2022/10/26 09:06:54 - mmengine - INFO - Epoch(train) [1147][60/63] lr: 2.1357e-04 eta: 0:36:52 time: 0.5106 data_time: 0.0048 memory: 16131 loss: 0.8382 loss_prob: 0.4294 loss_thr: 0.3339 loss_db: 0.0749 2022/10/26 09:06:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:07:01 - mmengine - INFO - Epoch(train) [1148][5/63] lr: 2.0995e-04 eta: 0:36:52 time: 0.7554 data_time: 0.1648 memory: 16131 loss: 0.9229 loss_prob: 0.4864 loss_thr: 0.3516 loss_db: 0.0849 2022/10/26 09:07:04 - mmengine - INFO - Epoch(train) [1148][10/63] lr: 2.0995e-04 eta: 0:36:43 time: 0.8147 data_time: 0.1663 memory: 16131 loss: 0.9073 loss_prob: 0.4858 loss_thr: 0.3391 loss_db: 0.0823 2022/10/26 09:07:07 - mmengine - INFO - Epoch(train) [1148][15/63] lr: 2.0995e-04 eta: 0:36:43 time: 0.5663 data_time: 0.0099 memory: 16131 loss: 0.8914 loss_prob: 0.4765 loss_thr: 0.3341 loss_db: 0.0809 2022/10/26 09:07:09 - mmengine - INFO - Epoch(train) [1148][20/63] lr: 2.0995e-04 eta: 0:36:37 time: 0.5298 data_time: 0.0057 memory: 16131 loss: 0.8036 loss_prob: 0.4196 loss_thr: 0.3112 loss_db: 0.0728 2022/10/26 09:07:12 - mmengine - INFO - Epoch(train) [1148][25/63] lr: 2.0995e-04 eta: 0:36:37 time: 0.5105 data_time: 0.0119 memory: 16131 loss: 0.8148 loss_prob: 0.4255 loss_thr: 0.3160 loss_db: 0.0733 2022/10/26 09:07:15 - mmengine - INFO - Epoch(train) [1148][30/63] lr: 2.0995e-04 eta: 0:36:30 time: 0.5582 data_time: 0.0314 memory: 16131 loss: 0.8539 loss_prob: 0.4424 loss_thr: 0.3351 loss_db: 0.0764 2022/10/26 09:07:17 - mmengine - INFO - Epoch(train) [1148][35/63] lr: 2.0995e-04 eta: 0:36:30 time: 0.5604 data_time: 0.0250 memory: 16131 loss: 0.8692 loss_prob: 0.4589 loss_thr: 0.3277 loss_db: 0.0827 2022/10/26 09:07:20 - mmengine - INFO - Epoch(train) [1148][40/63] lr: 2.0995e-04 eta: 0:36:23 time: 0.5051 data_time: 0.0104 memory: 16131 loss: 0.8537 loss_prob: 0.4516 loss_thr: 0.3180 loss_db: 0.0841 2022/10/26 09:07:22 - mmengine - INFO - Epoch(train) [1148][45/63] lr: 2.0995e-04 eta: 0:36:23 time: 0.5042 data_time: 0.0136 memory: 16131 loss: 0.8167 loss_prob: 0.4235 loss_thr: 0.3174 loss_db: 0.0758 2022/10/26 09:07:25 - mmengine - INFO - Epoch(train) [1148][50/63] lr: 2.0995e-04 eta: 0:36:16 time: 0.5136 data_time: 0.0230 memory: 16131 loss: 0.8159 loss_prob: 0.4208 loss_thr: 0.3213 loss_db: 0.0739 2022/10/26 09:07:28 - mmengine - INFO - Epoch(train) [1148][55/63] lr: 2.0995e-04 eta: 0:36:16 time: 0.5185 data_time: 0.0252 memory: 16131 loss: 0.8100 loss_prob: 0.4148 loss_thr: 0.3225 loss_db: 0.0728 2022/10/26 09:07:30 - mmengine - INFO - Epoch(train) [1148][60/63] lr: 2.0995e-04 eta: 0:36:10 time: 0.5522 data_time: 0.0141 memory: 16131 loss: 0.8113 loss_prob: 0.4161 loss_thr: 0.3215 loss_db: 0.0737 2022/10/26 09:07:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:07:36 - mmengine - INFO - Epoch(train) [1149][5/63] lr: 2.0631e-04 eta: 0:36:10 time: 0.7059 data_time: 0.2031 memory: 16131 loss: 0.8786 loss_prob: 0.4584 loss_thr: 0.3422 loss_db: 0.0780 2022/10/26 09:07:39 - mmengine - INFO - Epoch(train) [1149][10/63] lr: 2.0631e-04 eta: 0:36:01 time: 0.7011 data_time: 0.1989 memory: 16131 loss: 0.8492 loss_prob: 0.4482 loss_thr: 0.3257 loss_db: 0.0753 2022/10/26 09:07:41 - mmengine - INFO - Epoch(train) [1149][15/63] lr: 2.0631e-04 eta: 0:36:01 time: 0.5082 data_time: 0.0085 memory: 16131 loss: 0.7536 loss_prob: 0.3881 loss_thr: 0.2976 loss_db: 0.0679 2022/10/26 09:07:44 - mmengine - INFO - Epoch(train) [1149][20/63] lr: 2.0631e-04 eta: 0:35:54 time: 0.5105 data_time: 0.0083 memory: 16131 loss: 0.8108 loss_prob: 0.4231 loss_thr: 0.3147 loss_db: 0.0729 2022/10/26 09:07:47 - mmengine - INFO - Epoch(train) [1149][25/63] lr: 2.0631e-04 eta: 0:35:54 time: 0.5574 data_time: 0.0255 memory: 16131 loss: 0.8322 loss_prob: 0.4392 loss_thr: 0.3159 loss_db: 0.0770 2022/10/26 09:07:49 - mmengine - INFO - Epoch(train) [1149][30/63] lr: 2.0631e-04 eta: 0:35:48 time: 0.5471 data_time: 0.0265 memory: 16131 loss: 0.8852 loss_prob: 0.4713 loss_thr: 0.3310 loss_db: 0.0830 2022/10/26 09:07:52 - mmengine - INFO - Epoch(train) [1149][35/63] lr: 2.0631e-04 eta: 0:35:48 time: 0.4916 data_time: 0.0109 memory: 16131 loss: 0.9350 loss_prob: 0.4981 loss_thr: 0.3497 loss_db: 0.0872 2022/10/26 09:07:54 - mmengine - INFO - Epoch(train) [1149][40/63] lr: 2.0631e-04 eta: 0:35:41 time: 0.4932 data_time: 0.0109 memory: 16131 loss: 0.9089 loss_prob: 0.4773 loss_thr: 0.3477 loss_db: 0.0838 2022/10/26 09:07:57 - mmengine - INFO - Epoch(train) [1149][45/63] lr: 2.0631e-04 eta: 0:35:41 time: 0.5455 data_time: 0.0105 memory: 16131 loss: 0.8242 loss_prob: 0.4223 loss_thr: 0.3288 loss_db: 0.0731 2022/10/26 09:08:00 - mmengine - INFO - Epoch(train) [1149][50/63] lr: 2.0631e-04 eta: 0:35:34 time: 0.5583 data_time: 0.0252 memory: 16131 loss: 0.7948 loss_prob: 0.4048 loss_thr: 0.3190 loss_db: 0.0710 2022/10/26 09:08:02 - mmengine - INFO - Epoch(train) [1149][55/63] lr: 2.0631e-04 eta: 0:35:34 time: 0.5149 data_time: 0.0233 memory: 16131 loss: 0.8762 loss_prob: 0.4561 loss_thr: 0.3409 loss_db: 0.0793 2022/10/26 09:08:05 - mmengine - INFO - Epoch(train) [1149][60/63] lr: 2.0631e-04 eta: 0:35:28 time: 0.5142 data_time: 0.0086 memory: 16131 loss: 0.8439 loss_prob: 0.4361 loss_thr: 0.3326 loss_db: 0.0752 2022/10/26 09:08:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:08:11 - mmengine - INFO - Epoch(train) [1150][5/63] lr: 2.0267e-04 eta: 0:35:28 time: 0.6759 data_time: 0.1772 memory: 16131 loss: 0.8625 loss_prob: 0.4521 loss_thr: 0.3307 loss_db: 0.0796 2022/10/26 09:08:14 - mmengine - INFO - Epoch(train) [1150][10/63] lr: 2.0267e-04 eta: 0:35:19 time: 0.7194 data_time: 0.1803 memory: 16131 loss: 0.9104 loss_prob: 0.4849 loss_thr: 0.3421 loss_db: 0.0834 2022/10/26 09:08:16 - mmengine - INFO - Epoch(train) [1150][15/63] lr: 2.0267e-04 eta: 0:35:19 time: 0.5137 data_time: 0.0083 memory: 16131 loss: 0.8119 loss_prob: 0.4181 loss_thr: 0.3211 loss_db: 0.0727 2022/10/26 09:08:18 - mmengine - INFO - Epoch(train) [1150][20/63] lr: 2.0267e-04 eta: 0:35:12 time: 0.4875 data_time: 0.0063 memory: 16131 loss: 0.8075 loss_prob: 0.4127 loss_thr: 0.3235 loss_db: 0.0713 2022/10/26 09:08:21 - mmengine - INFO - Epoch(train) [1150][25/63] lr: 2.0267e-04 eta: 0:35:12 time: 0.5347 data_time: 0.0303 memory: 16131 loss: 0.8664 loss_prob: 0.4546 loss_thr: 0.3344 loss_db: 0.0774 2022/10/26 09:08:24 - mmengine - INFO - Epoch(train) [1150][30/63] lr: 2.0267e-04 eta: 0:35:06 time: 0.5455 data_time: 0.0287 memory: 16131 loss: 0.8550 loss_prob: 0.4445 loss_thr: 0.3337 loss_db: 0.0768 2022/10/26 09:08:27 - mmengine - INFO - Epoch(train) [1150][35/63] lr: 2.0267e-04 eta: 0:35:06 time: 0.5325 data_time: 0.0065 memory: 16131 loss: 0.8420 loss_prob: 0.4349 loss_thr: 0.3306 loss_db: 0.0766 2022/10/26 09:08:29 - mmengine - INFO - Epoch(train) [1150][40/63] lr: 2.0267e-04 eta: 0:34:59 time: 0.5191 data_time: 0.0064 memory: 16131 loss: 0.8300 loss_prob: 0.4362 loss_thr: 0.3174 loss_db: 0.0763 2022/10/26 09:08:32 - mmengine - INFO - Epoch(train) [1150][45/63] lr: 2.0267e-04 eta: 0:34:59 time: 0.4924 data_time: 0.0062 memory: 16131 loss: 0.8306 loss_prob: 0.4309 loss_thr: 0.3238 loss_db: 0.0759 2022/10/26 09:08:34 - mmengine - INFO - Epoch(train) [1150][50/63] lr: 2.0267e-04 eta: 0:34:52 time: 0.5369 data_time: 0.0241 memory: 16131 loss: 0.8154 loss_prob: 0.4178 loss_thr: 0.3246 loss_db: 0.0730 2022/10/26 09:08:37 - mmengine - INFO - Epoch(train) [1150][55/63] lr: 2.0267e-04 eta: 0:34:52 time: 0.5432 data_time: 0.0225 memory: 16131 loss: 0.7636 loss_prob: 0.3939 loss_thr: 0.3017 loss_db: 0.0680 2022/10/26 09:08:40 - mmengine - INFO - Epoch(train) [1150][60/63] lr: 2.0267e-04 eta: 0:34:46 time: 0.5480 data_time: 0.0092 memory: 16131 loss: 0.8063 loss_prob: 0.4183 loss_thr: 0.3140 loss_db: 0.0739 2022/10/26 09:08:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:08:46 - mmengine - INFO - Epoch(train) [1151][5/63] lr: 1.9902e-04 eta: 0:34:46 time: 0.7018 data_time: 0.2136 memory: 16131 loss: 0.8286 loss_prob: 0.4323 loss_thr: 0.3212 loss_db: 0.0751 2022/10/26 09:08:49 - mmengine - INFO - Epoch(train) [1151][10/63] lr: 1.9902e-04 eta: 0:34:37 time: 0.7661 data_time: 0.2141 memory: 16131 loss: 0.8162 loss_prob: 0.4240 loss_thr: 0.3192 loss_db: 0.0729 2022/10/26 09:08:52 - mmengine - INFO - Epoch(train) [1151][15/63] lr: 1.9902e-04 eta: 0:34:37 time: 0.5681 data_time: 0.0061 memory: 16131 loss: 0.9116 loss_prob: 0.4847 loss_thr: 0.3451 loss_db: 0.0817 2022/10/26 09:08:54 - mmengine - INFO - Epoch(train) [1151][20/63] lr: 1.9902e-04 eta: 0:34:30 time: 0.5108 data_time: 0.0053 memory: 16131 loss: 0.8922 loss_prob: 0.4646 loss_thr: 0.3481 loss_db: 0.0794 2022/10/26 09:08:57 - mmengine - INFO - Epoch(train) [1151][25/63] lr: 1.9902e-04 eta: 0:34:30 time: 0.5113 data_time: 0.0280 memory: 16131 loss: 0.7940 loss_prob: 0.3971 loss_thr: 0.3266 loss_db: 0.0702 2022/10/26 09:08:59 - mmengine - INFO - Epoch(train) [1151][30/63] lr: 1.9902e-04 eta: 0:34:24 time: 0.5346 data_time: 0.0364 memory: 16131 loss: 0.7963 loss_prob: 0.4098 loss_thr: 0.3144 loss_db: 0.0721 2022/10/26 09:09:02 - mmengine - INFO - Epoch(train) [1151][35/63] lr: 1.9902e-04 eta: 0:34:24 time: 0.5222 data_time: 0.0132 memory: 16131 loss: 0.8337 loss_prob: 0.4357 loss_thr: 0.3237 loss_db: 0.0744 2022/10/26 09:09:04 - mmengine - INFO - Epoch(train) [1151][40/63] lr: 1.9902e-04 eta: 0:34:17 time: 0.5174 data_time: 0.0051 memory: 16131 loss: 0.8758 loss_prob: 0.4592 loss_thr: 0.3390 loss_db: 0.0776 2022/10/26 09:09:07 - mmengine - INFO - Epoch(train) [1151][45/63] lr: 1.9902e-04 eta: 0:34:17 time: 0.5112 data_time: 0.0057 memory: 16131 loss: 0.8583 loss_prob: 0.4489 loss_thr: 0.3321 loss_db: 0.0773 2022/10/26 09:09:10 - mmengine - INFO - Epoch(train) [1151][50/63] lr: 1.9902e-04 eta: 0:34:10 time: 0.5546 data_time: 0.0211 memory: 16131 loss: 0.7998 loss_prob: 0.4143 loss_thr: 0.3123 loss_db: 0.0733 2022/10/26 09:09:13 - mmengine - INFO - Epoch(train) [1151][55/63] lr: 1.9902e-04 eta: 0:34:10 time: 0.5799 data_time: 0.0305 memory: 16131 loss: 0.9095 loss_prob: 0.4916 loss_thr: 0.3337 loss_db: 0.0842 2022/10/26 09:09:15 - mmengine - INFO - Epoch(train) [1151][60/63] lr: 1.9902e-04 eta: 0:34:04 time: 0.5276 data_time: 0.0169 memory: 16131 loss: 0.9655 loss_prob: 0.5275 loss_thr: 0.3494 loss_db: 0.0886 2022/10/26 09:09:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:09:21 - mmengine - INFO - Epoch(train) [1152][5/63] lr: 1.9536e-04 eta: 0:34:04 time: 0.6722 data_time: 0.1793 memory: 16131 loss: 0.7911 loss_prob: 0.4053 loss_thr: 0.3130 loss_db: 0.0728 2022/10/26 09:09:23 - mmengine - INFO - Epoch(train) [1152][10/63] lr: 1.9536e-04 eta: 0:33:55 time: 0.6756 data_time: 0.1788 memory: 16131 loss: 0.8407 loss_prob: 0.4321 loss_thr: 0.3310 loss_db: 0.0776 2022/10/26 09:09:26 - mmengine - INFO - Epoch(train) [1152][15/63] lr: 1.9536e-04 eta: 0:33:55 time: 0.5255 data_time: 0.0134 memory: 16131 loss: 0.8754 loss_prob: 0.4556 loss_thr: 0.3392 loss_db: 0.0806 2022/10/26 09:09:29 - mmengine - INFO - Epoch(train) [1152][20/63] lr: 1.9536e-04 eta: 0:33:48 time: 0.5339 data_time: 0.0157 memory: 16131 loss: 0.8305 loss_prob: 0.4297 loss_thr: 0.3256 loss_db: 0.0751 2022/10/26 09:09:31 - mmengine - INFO - Epoch(train) [1152][25/63] lr: 1.9536e-04 eta: 0:33:48 time: 0.5248 data_time: 0.0272 memory: 16131 loss: 0.8058 loss_prob: 0.4218 loss_thr: 0.3106 loss_db: 0.0734 2022/10/26 09:09:34 - mmengine - INFO - Epoch(train) [1152][30/63] lr: 1.9536e-04 eta: 0:33:42 time: 0.5124 data_time: 0.0249 memory: 16131 loss: 0.7898 loss_prob: 0.4064 loss_thr: 0.3115 loss_db: 0.0719 2022/10/26 09:09:36 - mmengine - INFO - Epoch(train) [1152][35/63] lr: 1.9536e-04 eta: 0:33:42 time: 0.5039 data_time: 0.0109 memory: 16131 loss: 0.8202 loss_prob: 0.4197 loss_thr: 0.3268 loss_db: 0.0737 2022/10/26 09:09:39 - mmengine - INFO - Epoch(train) [1152][40/63] lr: 1.9536e-04 eta: 0:33:35 time: 0.5291 data_time: 0.0101 memory: 16131 loss: 0.8230 loss_prob: 0.4205 loss_thr: 0.3284 loss_db: 0.0741 2022/10/26 09:09:42 - mmengine - INFO - Epoch(train) [1152][45/63] lr: 1.9536e-04 eta: 0:33:35 time: 0.5681 data_time: 0.0054 memory: 16131 loss: 0.8200 loss_prob: 0.4212 loss_thr: 0.3242 loss_db: 0.0747 2022/10/26 09:09:45 - mmengine - INFO - Epoch(train) [1152][50/63] lr: 1.9536e-04 eta: 0:33:28 time: 0.6044 data_time: 0.0224 memory: 16131 loss: 0.8654 loss_prob: 0.4561 loss_thr: 0.3294 loss_db: 0.0798 2022/10/26 09:09:48 - mmengine - INFO - Epoch(train) [1152][55/63] lr: 1.9536e-04 eta: 0:33:28 time: 0.5709 data_time: 0.0275 memory: 16131 loss: 0.9108 loss_prob: 0.4844 loss_thr: 0.3442 loss_db: 0.0822 2022/10/26 09:09:50 - mmengine - INFO - Epoch(train) [1152][60/63] lr: 1.9536e-04 eta: 0:33:22 time: 0.5140 data_time: 0.0157 memory: 16131 loss: 0.9381 loss_prob: 0.5005 loss_thr: 0.3536 loss_db: 0.0840 2022/10/26 09:09:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:09:57 - mmengine - INFO - Epoch(train) [1153][5/63] lr: 1.9170e-04 eta: 0:33:22 time: 0.7148 data_time: 0.1924 memory: 16131 loss: 0.9093 loss_prob: 0.4759 loss_thr: 0.3505 loss_db: 0.0829 2022/10/26 09:09:59 - mmengine - INFO - Epoch(train) [1153][10/63] lr: 1.9170e-04 eta: 0:33:13 time: 0.7167 data_time: 0.1839 memory: 16131 loss: 0.8955 loss_prob: 0.4673 loss_thr: 0.3471 loss_db: 0.0810 2022/10/26 09:10:02 - mmengine - INFO - Epoch(train) [1153][15/63] lr: 1.9170e-04 eta: 0:33:13 time: 0.5104 data_time: 0.0069 memory: 16131 loss: 0.8693 loss_prob: 0.4556 loss_thr: 0.3342 loss_db: 0.0795 2022/10/26 09:10:04 - mmengine - INFO - Epoch(train) [1153][20/63] lr: 1.9170e-04 eta: 0:33:06 time: 0.5252 data_time: 0.0068 memory: 16131 loss: 0.8738 loss_prob: 0.4688 loss_thr: 0.3269 loss_db: 0.0781 2022/10/26 09:10:07 - mmengine - INFO - Epoch(train) [1153][25/63] lr: 1.9170e-04 eta: 0:33:06 time: 0.5621 data_time: 0.0104 memory: 16131 loss: 0.8709 loss_prob: 0.4657 loss_thr: 0.3270 loss_db: 0.0782 2022/10/26 09:10:10 - mmengine - INFO - Epoch(train) [1153][30/63] lr: 1.9170e-04 eta: 0:33:00 time: 0.5684 data_time: 0.0341 memory: 16131 loss: 0.8232 loss_prob: 0.4251 loss_thr: 0.3224 loss_db: 0.0756 2022/10/26 09:10:13 - mmengine - INFO - Epoch(train) [1153][35/63] lr: 1.9170e-04 eta: 0:33:00 time: 0.5575 data_time: 0.0289 memory: 16131 loss: 0.7768 loss_prob: 0.3961 loss_thr: 0.3100 loss_db: 0.0708 2022/10/26 09:10:15 - mmengine - INFO - Epoch(train) [1153][40/63] lr: 1.9170e-04 eta: 0:32:53 time: 0.5505 data_time: 0.0055 memory: 16131 loss: 0.8261 loss_prob: 0.4258 loss_thr: 0.3257 loss_db: 0.0746 2022/10/26 09:10:18 - mmengine - INFO - Epoch(train) [1153][45/63] lr: 1.9170e-04 eta: 0:32:53 time: 0.5118 data_time: 0.0086 memory: 16131 loss: 0.8321 loss_prob: 0.4329 loss_thr: 0.3251 loss_db: 0.0741 2022/10/26 09:10:21 - mmengine - INFO - Epoch(train) [1153][50/63] lr: 1.9170e-04 eta: 0:32:46 time: 0.5066 data_time: 0.0164 memory: 16131 loss: 0.7929 loss_prob: 0.4157 loss_thr: 0.3070 loss_db: 0.0702 2022/10/26 09:10:24 - mmengine - INFO - Epoch(train) [1153][55/63] lr: 1.9170e-04 eta: 0:32:46 time: 0.5784 data_time: 0.0234 memory: 16131 loss: 0.8262 loss_prob: 0.4386 loss_thr: 0.3149 loss_db: 0.0727 2022/10/26 09:10:26 - mmengine - INFO - Epoch(train) [1153][60/63] lr: 1.9170e-04 eta: 0:32:40 time: 0.5701 data_time: 0.0150 memory: 16131 loss: 0.8410 loss_prob: 0.4422 loss_thr: 0.3226 loss_db: 0.0762 2022/10/26 09:10:27 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:10:33 - mmengine - INFO - Epoch(train) [1154][5/63] lr: 1.8802e-04 eta: 0:32:40 time: 0.7620 data_time: 0.2028 memory: 16131 loss: 0.8735 loss_prob: 0.4443 loss_thr: 0.3521 loss_db: 0.0771 2022/10/26 09:10:35 - mmengine - INFO - Epoch(train) [1154][10/63] lr: 1.8802e-04 eta: 0:32:31 time: 0.8052 data_time: 0.2136 memory: 16131 loss: 0.9634 loss_prob: 0.5150 loss_thr: 0.3614 loss_db: 0.0870 2022/10/26 09:10:38 - mmengine - INFO - Epoch(train) [1154][15/63] lr: 1.8802e-04 eta: 0:32:31 time: 0.5330 data_time: 0.0185 memory: 16131 loss: 0.9104 loss_prob: 0.4860 loss_thr: 0.3415 loss_db: 0.0829 2022/10/26 09:10:41 - mmengine - INFO - Epoch(train) [1154][20/63] lr: 1.8802e-04 eta: 0:32:24 time: 0.5125 data_time: 0.0094 memory: 16131 loss: 0.8379 loss_prob: 0.4392 loss_thr: 0.3214 loss_db: 0.0773 2022/10/26 09:10:43 - mmengine - INFO - Epoch(train) [1154][25/63] lr: 1.8802e-04 eta: 0:32:24 time: 0.4997 data_time: 0.0113 memory: 16131 loss: 0.8074 loss_prob: 0.4184 loss_thr: 0.3159 loss_db: 0.0731 2022/10/26 09:10:46 - mmengine - INFO - Epoch(train) [1154][30/63] lr: 1.8802e-04 eta: 0:32:18 time: 0.5311 data_time: 0.0326 memory: 16131 loss: 0.8078 loss_prob: 0.4214 loss_thr: 0.3140 loss_db: 0.0724 2022/10/26 09:10:48 - mmengine - INFO - Epoch(train) [1154][35/63] lr: 1.8802e-04 eta: 0:32:18 time: 0.5186 data_time: 0.0342 memory: 16131 loss: 0.8460 loss_prob: 0.4441 loss_thr: 0.3251 loss_db: 0.0768 2022/10/26 09:10:51 - mmengine - INFO - Epoch(train) [1154][40/63] lr: 1.8802e-04 eta: 0:32:11 time: 0.5078 data_time: 0.0115 memory: 16131 loss: 0.8635 loss_prob: 0.4501 loss_thr: 0.3353 loss_db: 0.0781 2022/10/26 09:10:54 - mmengine - INFO - Epoch(train) [1154][45/63] lr: 1.8802e-04 eta: 0:32:11 time: 0.5156 data_time: 0.0051 memory: 16131 loss: 0.8223 loss_prob: 0.4218 loss_thr: 0.3272 loss_db: 0.0733 2022/10/26 09:10:56 - mmengine - INFO - Epoch(train) [1154][50/63] lr: 1.8802e-04 eta: 0:32:04 time: 0.5118 data_time: 0.0167 memory: 16131 loss: 0.8179 loss_prob: 0.4224 loss_thr: 0.3220 loss_db: 0.0736 2022/10/26 09:10:59 - mmengine - INFO - Epoch(train) [1154][55/63] lr: 1.8802e-04 eta: 0:32:04 time: 0.5049 data_time: 0.0220 memory: 16131 loss: 0.8246 loss_prob: 0.4293 loss_thr: 0.3206 loss_db: 0.0746 2022/10/26 09:11:01 - mmengine - INFO - Epoch(train) [1154][60/63] lr: 1.8802e-04 eta: 0:31:58 time: 0.5341 data_time: 0.0125 memory: 16131 loss: 0.8371 loss_prob: 0.4299 loss_thr: 0.3326 loss_db: 0.0746 2022/10/26 09:11:03 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:11:08 - mmengine - INFO - Epoch(train) [1155][5/63] lr: 1.8434e-04 eta: 0:31:58 time: 0.7054 data_time: 0.1801 memory: 16131 loss: 0.9256 loss_prob: 0.4820 loss_thr: 0.3602 loss_db: 0.0834 2022/10/26 09:11:10 - mmengine - INFO - Epoch(train) [1155][10/63] lr: 1.8434e-04 eta: 0:31:49 time: 0.7451 data_time: 0.1850 memory: 16131 loss: 0.8737 loss_prob: 0.4596 loss_thr: 0.3341 loss_db: 0.0800 2022/10/26 09:11:13 - mmengine - INFO - Epoch(train) [1155][15/63] lr: 1.8434e-04 eta: 0:31:49 time: 0.5066 data_time: 0.0099 memory: 16131 loss: 0.8164 loss_prob: 0.4188 loss_thr: 0.3235 loss_db: 0.0742 2022/10/26 09:11:15 - mmengine - INFO - Epoch(train) [1155][20/63] lr: 1.8434e-04 eta: 0:31:42 time: 0.5010 data_time: 0.0061 memory: 16131 loss: 0.8815 loss_prob: 0.4594 loss_thr: 0.3425 loss_db: 0.0796 2022/10/26 09:11:18 - mmengine - INFO - Epoch(train) [1155][25/63] lr: 1.8434e-04 eta: 0:31:42 time: 0.5343 data_time: 0.0349 memory: 16131 loss: 0.9001 loss_prob: 0.4713 loss_thr: 0.3476 loss_db: 0.0812 2022/10/26 09:11:21 - mmengine - INFO - Epoch(train) [1155][30/63] lr: 1.8434e-04 eta: 0:31:36 time: 0.5346 data_time: 0.0391 memory: 16131 loss: 0.8822 loss_prob: 0.4617 loss_thr: 0.3403 loss_db: 0.0802 2022/10/26 09:11:23 - mmengine - INFO - Epoch(train) [1155][35/63] lr: 1.8434e-04 eta: 0:31:36 time: 0.5138 data_time: 0.0143 memory: 16131 loss: 0.8641 loss_prob: 0.4512 loss_thr: 0.3337 loss_db: 0.0792 2022/10/26 09:11:26 - mmengine - INFO - Epoch(train) [1155][40/63] lr: 1.8434e-04 eta: 0:31:29 time: 0.4990 data_time: 0.0090 memory: 16131 loss: 0.8374 loss_prob: 0.4383 loss_thr: 0.3223 loss_db: 0.0768 2022/10/26 09:11:28 - mmengine - INFO - Epoch(train) [1155][45/63] lr: 1.8434e-04 eta: 0:31:29 time: 0.5132 data_time: 0.0059 memory: 16131 loss: 0.8285 loss_prob: 0.4366 loss_thr: 0.3168 loss_db: 0.0751 2022/10/26 09:11:31 - mmengine - INFO - Epoch(train) [1155][50/63] lr: 1.8434e-04 eta: 0:31:22 time: 0.5392 data_time: 0.0199 memory: 16131 loss: 0.8724 loss_prob: 0.4724 loss_thr: 0.3200 loss_db: 0.0800 2022/10/26 09:11:33 - mmengine - INFO - Epoch(train) [1155][55/63] lr: 1.8434e-04 eta: 0:31:22 time: 0.5245 data_time: 0.0223 memory: 16131 loss: 1.0744 loss_prob: 0.6341 loss_thr: 0.3475 loss_db: 0.0928 2022/10/26 09:11:36 - mmengine - INFO - Epoch(train) [1155][60/63] lr: 1.8434e-04 eta: 0:31:16 time: 0.4980 data_time: 0.0087 memory: 16131 loss: 1.0088 loss_prob: 0.5820 loss_thr: 0.3399 loss_db: 0.0869 2022/10/26 09:11:37 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:11:41 - mmengine - INFO - Epoch(train) [1156][5/63] lr: 1.8065e-04 eta: 0:31:16 time: 0.6261 data_time: 0.1563 memory: 16131 loss: 0.8921 loss_prob: 0.4630 loss_thr: 0.3461 loss_db: 0.0830 2022/10/26 09:11:44 - mmengine - INFO - Epoch(train) [1156][10/63] lr: 1.8065e-04 eta: 0:31:07 time: 0.6658 data_time: 0.1651 memory: 16131 loss: 0.9103 loss_prob: 0.4771 loss_thr: 0.3512 loss_db: 0.0820 2022/10/26 09:11:46 - mmengine - INFO - Epoch(train) [1156][15/63] lr: 1.8065e-04 eta: 0:31:07 time: 0.5065 data_time: 0.0148 memory: 16131 loss: 0.8694 loss_prob: 0.4517 loss_thr: 0.3400 loss_db: 0.0776 2022/10/26 09:11:49 - mmengine - INFO - Epoch(train) [1156][20/63] lr: 1.8065e-04 eta: 0:31:00 time: 0.5033 data_time: 0.0110 memory: 16131 loss: 0.8683 loss_prob: 0.4455 loss_thr: 0.3446 loss_db: 0.0782 2022/10/26 09:11:51 - mmengine - INFO - Epoch(train) [1156][25/63] lr: 1.8065e-04 eta: 0:31:00 time: 0.5115 data_time: 0.0206 memory: 16131 loss: 0.9793 loss_prob: 0.5097 loss_thr: 0.3814 loss_db: 0.0882 2022/10/26 09:11:55 - mmengine - INFO - Epoch(train) [1156][30/63] lr: 1.8065e-04 eta: 0:30:54 time: 0.5896 data_time: 0.0354 memory: 16131 loss: 0.9169 loss_prob: 0.4763 loss_thr: 0.3575 loss_db: 0.0831 2022/10/26 09:11:58 - mmengine - INFO - Epoch(train) [1156][35/63] lr: 1.8065e-04 eta: 0:30:54 time: 0.6184 data_time: 0.0244 memory: 16131 loss: 0.8087 loss_prob: 0.4166 loss_thr: 0.3178 loss_db: 0.0743 2022/10/26 09:12:00 - mmengine - INFO - Epoch(train) [1156][40/63] lr: 1.8065e-04 eta: 0:30:47 time: 0.5289 data_time: 0.0098 memory: 16131 loss: 0.8405 loss_prob: 0.4342 loss_thr: 0.3295 loss_db: 0.0768 2022/10/26 09:12:03 - mmengine - INFO - Epoch(train) [1156][45/63] lr: 1.8065e-04 eta: 0:30:47 time: 0.5192 data_time: 0.0124 memory: 16131 loss: 0.8238 loss_prob: 0.4295 loss_thr: 0.3195 loss_db: 0.0749 2022/10/26 09:12:06 - mmengine - INFO - Epoch(train) [1156][50/63] lr: 1.8065e-04 eta: 0:30:40 time: 0.5799 data_time: 0.0201 memory: 16131 loss: 0.7980 loss_prob: 0.4225 loss_thr: 0.3036 loss_db: 0.0720 2022/10/26 09:12:09 - mmengine - INFO - Epoch(train) [1156][55/63] lr: 1.8065e-04 eta: 0:30:40 time: 0.5988 data_time: 0.0226 memory: 16131 loss: 0.8484 loss_prob: 0.4571 loss_thr: 0.3142 loss_db: 0.0772 2022/10/26 09:12:11 - mmengine - INFO - Epoch(train) [1156][60/63] lr: 1.8065e-04 eta: 0:30:34 time: 0.5678 data_time: 0.0112 memory: 16131 loss: 0.9281 loss_prob: 0.4956 loss_thr: 0.3484 loss_db: 0.0841 2022/10/26 09:12:13 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:12:17 - mmengine - INFO - Epoch(train) [1157][5/63] lr: 1.7696e-04 eta: 0:30:34 time: 0.6725 data_time: 0.1825 memory: 16131 loss: 0.9075 loss_prob: 0.4723 loss_thr: 0.3532 loss_db: 0.0820 2022/10/26 09:12:20 - mmengine - INFO - Epoch(train) [1157][10/63] lr: 1.7696e-04 eta: 0:30:25 time: 0.7097 data_time: 0.1881 memory: 16131 loss: 0.8910 loss_prob: 0.4720 loss_thr: 0.3379 loss_db: 0.0810 2022/10/26 09:12:23 - mmengine - INFO - Epoch(train) [1157][15/63] lr: 1.7696e-04 eta: 0:30:25 time: 0.5464 data_time: 0.0134 memory: 16131 loss: 0.9345 loss_prob: 0.4972 loss_thr: 0.3516 loss_db: 0.0857 2022/10/26 09:12:25 - mmengine - INFO - Epoch(train) [1157][20/63] lr: 1.7696e-04 eta: 0:30:19 time: 0.5250 data_time: 0.0075 memory: 16131 loss: 0.8868 loss_prob: 0.4638 loss_thr: 0.3432 loss_db: 0.0798 2022/10/26 09:12:28 - mmengine - INFO - Epoch(train) [1157][25/63] lr: 1.7696e-04 eta: 0:30:19 time: 0.5222 data_time: 0.0142 memory: 16131 loss: 0.8489 loss_prob: 0.4432 loss_thr: 0.3293 loss_db: 0.0764 2022/10/26 09:12:31 - mmengine - INFO - Epoch(train) [1157][30/63] lr: 1.7696e-04 eta: 0:30:12 time: 0.5435 data_time: 0.0353 memory: 16131 loss: 0.8959 loss_prob: 0.4721 loss_thr: 0.3419 loss_db: 0.0818 2022/10/26 09:12:33 - mmengine - INFO - Epoch(train) [1157][35/63] lr: 1.7696e-04 eta: 0:30:12 time: 0.5432 data_time: 0.0291 memory: 16131 loss: 0.9181 loss_prob: 0.4827 loss_thr: 0.3519 loss_db: 0.0835 2022/10/26 09:12:36 - mmengine - INFO - Epoch(train) [1157][40/63] lr: 1.7696e-04 eta: 0:30:05 time: 0.5219 data_time: 0.0073 memory: 16131 loss: 0.9182 loss_prob: 0.4844 loss_thr: 0.3483 loss_db: 0.0854 2022/10/26 09:12:38 - mmengine - INFO - Epoch(train) [1157][45/63] lr: 1.7696e-04 eta: 0:30:05 time: 0.5126 data_time: 0.0049 memory: 16131 loss: 0.8597 loss_prob: 0.4519 loss_thr: 0.3285 loss_db: 0.0793 2022/10/26 09:12:41 - mmengine - INFO - Epoch(train) [1157][50/63] lr: 1.7696e-04 eta: 0:29:59 time: 0.5660 data_time: 0.0198 memory: 16131 loss: 0.8424 loss_prob: 0.4417 loss_thr: 0.3230 loss_db: 0.0777 2022/10/26 09:12:44 - mmengine - INFO - Epoch(train) [1157][55/63] lr: 1.7696e-04 eta: 0:29:59 time: 0.5712 data_time: 0.0217 memory: 16131 loss: 0.8562 loss_prob: 0.4522 loss_thr: 0.3234 loss_db: 0.0806 2022/10/26 09:12:47 - mmengine - INFO - Epoch(train) [1157][60/63] lr: 1.7696e-04 eta: 0:29:52 time: 0.5311 data_time: 0.0065 memory: 16131 loss: 0.8906 loss_prob: 0.4705 loss_thr: 0.3383 loss_db: 0.0818 2022/10/26 09:12:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:12:53 - mmengine - INFO - Epoch(train) [1158][5/63] lr: 1.7325e-04 eta: 0:29:52 time: 0.7473 data_time: 0.2060 memory: 16131 loss: 0.9608 loss_prob: 0.5257 loss_thr: 0.3495 loss_db: 0.0856 2022/10/26 09:12:56 - mmengine - INFO - Epoch(train) [1158][10/63] lr: 1.7325e-04 eta: 0:29:43 time: 0.7689 data_time: 0.2062 memory: 16131 loss: 0.9267 loss_prob: 0.4953 loss_thr: 0.3515 loss_db: 0.0800 2022/10/26 09:12:59 - mmengine - INFO - Epoch(train) [1158][15/63] lr: 1.7325e-04 eta: 0:29:43 time: 0.5439 data_time: 0.0047 memory: 16131 loss: 0.9248 loss_prob: 0.4776 loss_thr: 0.3654 loss_db: 0.0819 2022/10/26 09:13:01 - mmengine - INFO - Epoch(train) [1158][20/63] lr: 1.7325e-04 eta: 0:29:37 time: 0.5315 data_time: 0.0048 memory: 16131 loss: 0.8638 loss_prob: 0.4463 loss_thr: 0.3387 loss_db: 0.0787 2022/10/26 09:13:04 - mmengine - INFO - Epoch(train) [1158][25/63] lr: 1.7325e-04 eta: 0:29:37 time: 0.5441 data_time: 0.0233 memory: 16131 loss: 0.8656 loss_prob: 0.4520 loss_thr: 0.3334 loss_db: 0.0801 2022/10/26 09:13:07 - mmengine - INFO - Epoch(train) [1158][30/63] lr: 1.7325e-04 eta: 0:29:30 time: 0.5360 data_time: 0.0323 memory: 16131 loss: 0.8429 loss_prob: 0.4372 loss_thr: 0.3294 loss_db: 0.0763 2022/10/26 09:13:09 - mmengine - INFO - Epoch(train) [1158][35/63] lr: 1.7325e-04 eta: 0:29:30 time: 0.4993 data_time: 0.0142 memory: 16131 loss: 0.8409 loss_prob: 0.4351 loss_thr: 0.3295 loss_db: 0.0762 2022/10/26 09:13:12 - mmengine - INFO - Epoch(train) [1158][40/63] lr: 1.7325e-04 eta: 0:29:23 time: 0.5372 data_time: 0.0068 memory: 16131 loss: 0.9054 loss_prob: 0.4727 loss_thr: 0.3524 loss_db: 0.0803 2022/10/26 09:13:15 - mmengine - INFO - Epoch(train) [1158][45/63] lr: 1.7325e-04 eta: 0:29:23 time: 0.5682 data_time: 0.0225 memory: 16131 loss: 0.8960 loss_prob: 0.4688 loss_thr: 0.3482 loss_db: 0.0791 2022/10/26 09:13:17 - mmengine - INFO - Epoch(train) [1158][50/63] lr: 1.7325e-04 eta: 0:29:17 time: 0.5413 data_time: 0.0226 memory: 16131 loss: 0.8238 loss_prob: 0.4280 loss_thr: 0.3195 loss_db: 0.0762 2022/10/26 09:13:20 - mmengine - INFO - Epoch(train) [1158][55/63] lr: 1.7325e-04 eta: 0:29:17 time: 0.5113 data_time: 0.0082 memory: 16131 loss: 0.8073 loss_prob: 0.4184 loss_thr: 0.3134 loss_db: 0.0755 2022/10/26 09:13:22 - mmengine - INFO - Epoch(train) [1158][60/63] lr: 1.7325e-04 eta: 0:29:10 time: 0.4976 data_time: 0.0069 memory: 16131 loss: 0.8436 loss_prob: 0.4361 loss_thr: 0.3287 loss_db: 0.0788 2022/10/26 09:13:24 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:13:28 - mmengine - INFO - Epoch(train) [1159][5/63] lr: 1.6954e-04 eta: 0:29:10 time: 0.7048 data_time: 0.1966 memory: 16131 loss: 0.8306 loss_prob: 0.4349 loss_thr: 0.3195 loss_db: 0.0762 2022/10/26 09:13:31 - mmengine - INFO - Epoch(train) [1159][10/63] lr: 1.6954e-04 eta: 0:29:01 time: 0.7142 data_time: 0.1964 memory: 16131 loss: 0.8893 loss_prob: 0.4672 loss_thr: 0.3422 loss_db: 0.0799 2022/10/26 09:13:33 - mmengine - INFO - Epoch(train) [1159][15/63] lr: 1.6954e-04 eta: 0:29:01 time: 0.4986 data_time: 0.0055 memory: 16131 loss: 0.8977 loss_prob: 0.4726 loss_thr: 0.3445 loss_db: 0.0807 2022/10/26 09:13:36 - mmengine - INFO - Epoch(train) [1159][20/63] lr: 1.6954e-04 eta: 0:28:55 time: 0.5295 data_time: 0.0079 memory: 16131 loss: 0.8665 loss_prob: 0.4557 loss_thr: 0.3323 loss_db: 0.0785 2022/10/26 09:13:39 - mmengine - INFO - Epoch(train) [1159][25/63] lr: 1.6954e-04 eta: 0:28:55 time: 0.5530 data_time: 0.0326 memory: 16131 loss: 0.8379 loss_prob: 0.4295 loss_thr: 0.3324 loss_db: 0.0759 2022/10/26 09:13:42 - mmengine - INFO - Epoch(train) [1159][30/63] lr: 1.6954e-04 eta: 0:28:48 time: 0.5450 data_time: 0.0376 memory: 16131 loss: 0.8006 loss_prob: 0.4035 loss_thr: 0.3251 loss_db: 0.0721 2022/10/26 09:13:44 - mmengine - INFO - Epoch(train) [1159][35/63] lr: 1.6954e-04 eta: 0:28:48 time: 0.5190 data_time: 0.0119 memory: 16131 loss: 0.8021 loss_prob: 0.4065 loss_thr: 0.3244 loss_db: 0.0712 2022/10/26 09:13:47 - mmengine - INFO - Epoch(train) [1159][40/63] lr: 1.6954e-04 eta: 0:28:41 time: 0.5196 data_time: 0.0048 memory: 16131 loss: 0.8773 loss_prob: 0.4560 loss_thr: 0.3408 loss_db: 0.0806 2022/10/26 09:13:50 - mmengine - INFO - Epoch(train) [1159][45/63] lr: 1.6954e-04 eta: 0:28:41 time: 0.6159 data_time: 0.0089 memory: 16131 loss: 0.9073 loss_prob: 0.4778 loss_thr: 0.3449 loss_db: 0.0846 2022/10/26 09:13:51 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:13:53 - mmengine - INFO - Epoch(train) [1159][50/63] lr: 1.6954e-04 eta: 0:28:35 time: 0.6452 data_time: 0.0299 memory: 16131 loss: 0.8712 loss_prob: 0.4690 loss_thr: 0.3243 loss_db: 0.0779 2022/10/26 09:13:56 - mmengine - INFO - Epoch(train) [1159][55/63] lr: 1.6954e-04 eta: 0:28:35 time: 0.5395 data_time: 0.0265 memory: 16131 loss: 0.8902 loss_prob: 0.4759 loss_thr: 0.3358 loss_db: 0.0785 2022/10/26 09:13:59 - mmengine - INFO - Epoch(train) [1159][60/63] lr: 1.6954e-04 eta: 0:28:28 time: 0.5326 data_time: 0.0052 memory: 16131 loss: 0.8830 loss_prob: 0.4608 loss_thr: 0.3424 loss_db: 0.0798 2022/10/26 09:14:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:14:04 - mmengine - INFO - Epoch(train) [1160][5/63] lr: 1.6581e-04 eta: 0:28:28 time: 0.6923 data_time: 0.1779 memory: 16131 loss: 0.8647 loss_prob: 0.4565 loss_thr: 0.3284 loss_db: 0.0798 2022/10/26 09:14:07 - mmengine - INFO - Epoch(train) [1160][10/63] lr: 1.6581e-04 eta: 0:28:19 time: 0.6914 data_time: 0.1793 memory: 16131 loss: 0.8579 loss_prob: 0.4544 loss_thr: 0.3269 loss_db: 0.0766 2022/10/26 09:14:09 - mmengine - INFO - Epoch(train) [1160][15/63] lr: 1.6581e-04 eta: 0:28:19 time: 0.5119 data_time: 0.0065 memory: 16131 loss: 0.8431 loss_prob: 0.4458 loss_thr: 0.3204 loss_db: 0.0769 2022/10/26 09:14:12 - mmengine - INFO - Epoch(train) [1160][20/63] lr: 1.6581e-04 eta: 0:28:13 time: 0.5089 data_time: 0.0075 memory: 16131 loss: 0.8356 loss_prob: 0.4466 loss_thr: 0.3125 loss_db: 0.0765 2022/10/26 09:14:14 - mmengine - INFO - Epoch(train) [1160][25/63] lr: 1.6581e-04 eta: 0:28:13 time: 0.5069 data_time: 0.0187 memory: 16131 loss: 0.8574 loss_prob: 0.4541 loss_thr: 0.3260 loss_db: 0.0773 2022/10/26 09:14:17 - mmengine - INFO - Epoch(train) [1160][30/63] lr: 1.6581e-04 eta: 0:28:06 time: 0.5243 data_time: 0.0311 memory: 16131 loss: 0.8840 loss_prob: 0.4679 loss_thr: 0.3354 loss_db: 0.0807 2022/10/26 09:14:20 - mmengine - INFO - Epoch(train) [1160][35/63] lr: 1.6581e-04 eta: 0:28:06 time: 0.5440 data_time: 0.0200 memory: 16131 loss: 0.8401 loss_prob: 0.4385 loss_thr: 0.3253 loss_db: 0.0763 2022/10/26 09:14:23 - mmengine - INFO - Epoch(train) [1160][40/63] lr: 1.6581e-04 eta: 0:28:00 time: 0.5580 data_time: 0.0052 memory: 16131 loss: 0.8147 loss_prob: 0.4189 loss_thr: 0.3216 loss_db: 0.0742 2022/10/26 09:14:25 - mmengine - INFO - Epoch(train) [1160][45/63] lr: 1.6581e-04 eta: 0:28:00 time: 0.5576 data_time: 0.0097 memory: 16131 loss: 0.8631 loss_prob: 0.4467 loss_thr: 0.3368 loss_db: 0.0796 2022/10/26 09:14:28 - mmengine - INFO - Epoch(train) [1160][50/63] lr: 1.6581e-04 eta: 0:27:53 time: 0.5542 data_time: 0.0214 memory: 16131 loss: 0.9059 loss_prob: 0.4695 loss_thr: 0.3532 loss_db: 0.0832 2022/10/26 09:14:31 - mmengine - INFO - Epoch(train) [1160][55/63] lr: 1.6581e-04 eta: 0:27:53 time: 0.5736 data_time: 0.0245 memory: 16131 loss: 0.8720 loss_prob: 0.4550 loss_thr: 0.3358 loss_db: 0.0812 2022/10/26 09:14:34 - mmengine - INFO - Epoch(train) [1160][60/63] lr: 1.6581e-04 eta: 0:27:46 time: 0.5759 data_time: 0.0131 memory: 16131 loss: 0.7883 loss_prob: 0.4095 loss_thr: 0.3071 loss_db: 0.0717 2022/10/26 09:14:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:14:35 - mmengine - INFO - Saving checkpoint at 1160 epochs 2022/10/26 09:14:42 - mmengine - INFO - Epoch(val) [1160][5/32] eta: 0:27:46 time: 0.5027 data_time: 0.0694 memory: 16131 2022/10/26 09:14:45 - mmengine - INFO - Epoch(val) [1160][10/32] eta: 0:00:12 time: 0.5633 data_time: 0.0880 memory: 15724 2022/10/26 09:14:47 - mmengine - INFO - Epoch(val) [1160][15/32] eta: 0:00:12 time: 0.5145 data_time: 0.0369 memory: 15724 2022/10/26 09:14:50 - mmengine - INFO - Epoch(val) [1160][20/32] eta: 0:00:06 time: 0.5129 data_time: 0.0344 memory: 15724 2022/10/26 09:14:53 - mmengine - INFO - Epoch(val) [1160][25/32] eta: 0:00:06 time: 0.5404 data_time: 0.0420 memory: 15724 2022/10/26 09:14:55 - mmengine - INFO - Epoch(val) [1160][30/32] eta: 0:00:01 time: 0.5199 data_time: 0.0278 memory: 15724 2022/10/26 09:14:56 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8377, precision: 0.7806, hmean: 0.8082 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8377, precision: 0.8227, hmean: 0.8302 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8363, precision: 0.8440, hmean: 0.8401 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8325, precision: 0.8658, hmean: 0.8488 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8228, precision: 0.8896, hmean: 0.8549 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7588, precision: 0.9282, hmean: 0.8350 2022/10/26 09:14:56 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2508, precision: 0.9775, hmean: 0.3992 2022/10/26 09:14:56 - mmengine - INFO - Epoch(val) [1160][32/32] icdar/precision: 0.8896 icdar/recall: 0.8228 icdar/hmean: 0.8549 2022/10/26 09:15:01 - mmengine - INFO - Epoch(train) [1161][5/63] lr: 1.6208e-04 eta: 0:00:01 time: 0.7409 data_time: 0.1711 memory: 16131 loss: 0.7915 loss_prob: 0.4091 loss_thr: 0.3111 loss_db: 0.0713 2022/10/26 09:15:04 - mmengine - INFO - Epoch(train) [1161][10/63] lr: 1.6208e-04 eta: 0:27:38 time: 0.8261 data_time: 0.1704 memory: 16131 loss: 0.8443 loss_prob: 0.4359 loss_thr: 0.3318 loss_db: 0.0766 2022/10/26 09:15:07 - mmengine - INFO - Epoch(train) [1161][15/63] lr: 1.6208e-04 eta: 0:27:38 time: 0.5920 data_time: 0.0058 memory: 16131 loss: 0.8166 loss_prob: 0.4209 loss_thr: 0.3216 loss_db: 0.0741 2022/10/26 09:15:09 - mmengine - INFO - Epoch(train) [1161][20/63] lr: 1.6208e-04 eta: 0:27:31 time: 0.5362 data_time: 0.0064 memory: 16131 loss: 0.8620 loss_prob: 0.4546 loss_thr: 0.3263 loss_db: 0.0811 2022/10/26 09:15:12 - mmengine - INFO - Epoch(train) [1161][25/63] lr: 1.6208e-04 eta: 0:27:31 time: 0.5283 data_time: 0.0152 memory: 16131 loss: 0.8666 loss_prob: 0.4540 loss_thr: 0.3317 loss_db: 0.0808 2022/10/26 09:15:15 - mmengine - INFO - Epoch(train) [1161][30/63] lr: 1.6208e-04 eta: 0:27:24 time: 0.5155 data_time: 0.0316 memory: 16131 loss: 0.7853 loss_prob: 0.4049 loss_thr: 0.3094 loss_db: 0.0711 2022/10/26 09:15:17 - mmengine - INFO - Epoch(train) [1161][35/63] lr: 1.6208e-04 eta: 0:27:24 time: 0.5451 data_time: 0.0222 memory: 16131 loss: 0.7604 loss_prob: 0.3976 loss_thr: 0.2940 loss_db: 0.0689 2022/10/26 09:15:20 - mmengine - INFO - Epoch(train) [1161][40/63] lr: 1.6208e-04 eta: 0:27:18 time: 0.5525 data_time: 0.0068 memory: 16131 loss: 0.8090 loss_prob: 0.4248 loss_thr: 0.3109 loss_db: 0.0733 2022/10/26 09:15:23 - mmengine - INFO - Epoch(train) [1161][45/63] lr: 1.6208e-04 eta: 0:27:18 time: 0.5153 data_time: 0.0099 memory: 16131 loss: 0.8170 loss_prob: 0.4246 loss_thr: 0.3192 loss_db: 0.0732 2022/10/26 09:15:25 - mmengine - INFO - Epoch(train) [1161][50/63] lr: 1.6208e-04 eta: 0:27:11 time: 0.4883 data_time: 0.0178 memory: 16131 loss: 0.8616 loss_prob: 0.4534 loss_thr: 0.3296 loss_db: 0.0786 2022/10/26 09:15:28 - mmengine - INFO - Epoch(train) [1161][55/63] lr: 1.6208e-04 eta: 0:27:11 time: 0.5533 data_time: 0.0240 memory: 16131 loss: 0.8727 loss_prob: 0.4595 loss_thr: 0.3330 loss_db: 0.0801 2022/10/26 09:15:31 - mmengine - INFO - Epoch(train) [1161][60/63] lr: 1.6208e-04 eta: 0:27:04 time: 0.5878 data_time: 0.0151 memory: 16131 loss: 0.8444 loss_prob: 0.4399 loss_thr: 0.3270 loss_db: 0.0775 2022/10/26 09:15:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:15:37 - mmengine - INFO - Epoch(train) [1162][5/63] lr: 1.5834e-04 eta: 0:27:04 time: 0.6975 data_time: 0.2058 memory: 16131 loss: 0.8841 loss_prob: 0.4617 loss_thr: 0.3419 loss_db: 0.0804 2022/10/26 09:15:40 - mmengine - INFO - Epoch(train) [1162][10/63] lr: 1.5834e-04 eta: 0:26:56 time: 0.8222 data_time: 0.2054 memory: 16131 loss: 0.8666 loss_prob: 0.4479 loss_thr: 0.3409 loss_db: 0.0777 2022/10/26 09:15:43 - mmengine - INFO - Epoch(train) [1162][15/63] lr: 1.5834e-04 eta: 0:26:56 time: 0.6180 data_time: 0.0055 memory: 16131 loss: 0.8295 loss_prob: 0.4215 loss_thr: 0.3344 loss_db: 0.0736 2022/10/26 09:15:46 - mmengine - INFO - Epoch(train) [1162][20/63] lr: 1.5834e-04 eta: 0:26:49 time: 0.5188 data_time: 0.0058 memory: 16131 loss: 0.9324 loss_prob: 0.4942 loss_thr: 0.3525 loss_db: 0.0857 2022/10/26 09:15:49 - mmengine - INFO - Epoch(train) [1162][25/63] lr: 1.5834e-04 eta: 0:26:49 time: 0.5443 data_time: 0.0254 memory: 16131 loss: 0.8915 loss_prob: 0.4726 loss_thr: 0.3365 loss_db: 0.0824 2022/10/26 09:15:51 - mmengine - INFO - Epoch(train) [1162][30/63] lr: 1.5834e-04 eta: 0:26:42 time: 0.5519 data_time: 0.0347 memory: 16131 loss: 0.7358 loss_prob: 0.3738 loss_thr: 0.2954 loss_db: 0.0666 2022/10/26 09:15:54 - mmengine - INFO - Epoch(train) [1162][35/63] lr: 1.5834e-04 eta: 0:26:42 time: 0.5209 data_time: 0.0148 memory: 16131 loss: 0.7556 loss_prob: 0.3881 loss_thr: 0.2994 loss_db: 0.0680 2022/10/26 09:15:56 - mmengine - INFO - Epoch(train) [1162][40/63] lr: 1.5834e-04 eta: 0:26:36 time: 0.5171 data_time: 0.0044 memory: 16131 loss: 0.8448 loss_prob: 0.4444 loss_thr: 0.3242 loss_db: 0.0762 2022/10/26 09:15:59 - mmengine - INFO - Epoch(train) [1162][45/63] lr: 1.5834e-04 eta: 0:26:36 time: 0.5394 data_time: 0.0044 memory: 16131 loss: 0.9408 loss_prob: 0.4982 loss_thr: 0.3557 loss_db: 0.0869 2022/10/26 09:16:02 - mmengine - INFO - Epoch(train) [1162][50/63] lr: 1.5834e-04 eta: 0:26:29 time: 0.5420 data_time: 0.0174 memory: 16131 loss: 0.8979 loss_prob: 0.4653 loss_thr: 0.3510 loss_db: 0.0816 2022/10/26 09:16:04 - mmengine - INFO - Epoch(train) [1162][55/63] lr: 1.5834e-04 eta: 0:26:29 time: 0.5272 data_time: 0.0205 memory: 16131 loss: 0.8180 loss_prob: 0.4204 loss_thr: 0.3250 loss_db: 0.0726 2022/10/26 09:16:07 - mmengine - INFO - Epoch(train) [1162][60/63] lr: 1.5834e-04 eta: 0:26:23 time: 0.5070 data_time: 0.0074 memory: 16131 loss: 0.8593 loss_prob: 0.4521 loss_thr: 0.3276 loss_db: 0.0797 2022/10/26 09:16:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:16:13 - mmengine - INFO - Epoch(train) [1163][5/63] lr: 1.5458e-04 eta: 0:26:23 time: 0.7282 data_time: 0.1880 memory: 16131 loss: 0.8645 loss_prob: 0.4508 loss_thr: 0.3340 loss_db: 0.0797 2022/10/26 09:16:16 - mmengine - INFO - Epoch(train) [1163][10/63] lr: 1.5458e-04 eta: 0:26:14 time: 0.7473 data_time: 0.1890 memory: 16131 loss: 0.8483 loss_prob: 0.4436 loss_thr: 0.3261 loss_db: 0.0786 2022/10/26 09:16:19 - mmengine - INFO - Epoch(train) [1163][15/63] lr: 1.5458e-04 eta: 0:26:14 time: 0.5631 data_time: 0.0122 memory: 16131 loss: 0.9519 loss_prob: 0.5018 loss_thr: 0.3605 loss_db: 0.0896 2022/10/26 09:16:21 - mmengine - INFO - Epoch(train) [1163][20/63] lr: 1.5458e-04 eta: 0:26:07 time: 0.5510 data_time: 0.0113 memory: 16131 loss: 0.9124 loss_prob: 0.4753 loss_thr: 0.3526 loss_db: 0.0844 2022/10/26 09:16:24 - mmengine - INFO - Epoch(train) [1163][25/63] lr: 1.5458e-04 eta: 0:26:07 time: 0.5182 data_time: 0.0210 memory: 16131 loss: 0.8588 loss_prob: 0.4493 loss_thr: 0.3316 loss_db: 0.0780 2022/10/26 09:16:27 - mmengine - INFO - Epoch(train) [1163][30/63] lr: 1.5458e-04 eta: 0:26:01 time: 0.5471 data_time: 0.0257 memory: 16131 loss: 0.8489 loss_prob: 0.4468 loss_thr: 0.3253 loss_db: 0.0769 2022/10/26 09:16:30 - mmengine - INFO - Epoch(train) [1163][35/63] lr: 1.5458e-04 eta: 0:26:01 time: 0.6057 data_time: 0.0128 memory: 16131 loss: 0.7917 loss_prob: 0.4085 loss_thr: 0.3128 loss_db: 0.0704 2022/10/26 09:16:33 - mmengine - INFO - Epoch(train) [1163][40/63] lr: 1.5458e-04 eta: 0:25:54 time: 0.5911 data_time: 0.0114 memory: 16131 loss: 0.7881 loss_prob: 0.4063 loss_thr: 0.3124 loss_db: 0.0694 2022/10/26 09:16:36 - mmengine - INFO - Epoch(train) [1163][45/63] lr: 1.5458e-04 eta: 0:25:54 time: 0.5498 data_time: 0.0078 memory: 16131 loss: 0.7891 loss_prob: 0.4076 loss_thr: 0.3119 loss_db: 0.0695 2022/10/26 09:16:38 - mmengine - INFO - Epoch(train) [1163][50/63] lr: 1.5458e-04 eta: 0:25:47 time: 0.5719 data_time: 0.0164 memory: 16131 loss: 0.8540 loss_prob: 0.4307 loss_thr: 0.3481 loss_db: 0.0752 2022/10/26 09:16:41 - mmengine - INFO - Epoch(train) [1163][55/63] lr: 1.5458e-04 eta: 0:25:47 time: 0.5372 data_time: 0.0166 memory: 16131 loss: 0.8008 loss_prob: 0.3959 loss_thr: 0.3355 loss_db: 0.0694 2022/10/26 09:16:43 - mmengine - INFO - Epoch(train) [1163][60/63] lr: 1.5458e-04 eta: 0:25:41 time: 0.5012 data_time: 0.0058 memory: 16131 loss: 0.7317 loss_prob: 0.3666 loss_thr: 0.3008 loss_db: 0.0643 2022/10/26 09:16:45 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:16:49 - mmengine - INFO - Epoch(train) [1164][5/63] lr: 1.5082e-04 eta: 0:25:41 time: 0.7014 data_time: 0.2038 memory: 16131 loss: 0.8621 loss_prob: 0.4533 loss_thr: 0.3281 loss_db: 0.0807 2022/10/26 09:16:52 - mmengine - INFO - Epoch(train) [1164][10/63] lr: 1.5082e-04 eta: 0:25:32 time: 0.7258 data_time: 0.2068 memory: 16131 loss: 0.8580 loss_prob: 0.4536 loss_thr: 0.3261 loss_db: 0.0784 2022/10/26 09:16:55 - mmengine - INFO - Epoch(train) [1164][15/63] lr: 1.5082e-04 eta: 0:25:32 time: 0.5539 data_time: 0.0128 memory: 16131 loss: 0.8314 loss_prob: 0.4311 loss_thr: 0.3272 loss_db: 0.0732 2022/10/26 09:16:58 - mmengine - INFO - Epoch(train) [1164][20/63] lr: 1.5082e-04 eta: 0:25:25 time: 0.5708 data_time: 0.0121 memory: 16131 loss: 0.8855 loss_prob: 0.4629 loss_thr: 0.3423 loss_db: 0.0803 2022/10/26 09:17:01 - mmengine - INFO - Epoch(train) [1164][25/63] lr: 1.5082e-04 eta: 0:25:25 time: 0.5801 data_time: 0.0393 memory: 16131 loss: 0.9136 loss_prob: 0.4767 loss_thr: 0.3503 loss_db: 0.0866 2022/10/26 09:17:03 - mmengine - INFO - Epoch(train) [1164][30/63] lr: 1.5082e-04 eta: 0:25:19 time: 0.5565 data_time: 0.0330 memory: 16131 loss: 0.8058 loss_prob: 0.4067 loss_thr: 0.3242 loss_db: 0.0750 2022/10/26 09:17:06 - mmengine - INFO - Epoch(train) [1164][35/63] lr: 1.5082e-04 eta: 0:25:19 time: 0.5314 data_time: 0.0073 memory: 16131 loss: 0.7964 loss_prob: 0.4101 loss_thr: 0.3140 loss_db: 0.0723 2022/10/26 09:17:09 - mmengine - INFO - Epoch(train) [1164][40/63] lr: 1.5082e-04 eta: 0:25:12 time: 0.5284 data_time: 0.0067 memory: 16131 loss: 0.8449 loss_prob: 0.4422 loss_thr: 0.3260 loss_db: 0.0766 2022/10/26 09:17:12 - mmengine - INFO - Epoch(train) [1164][45/63] lr: 1.5082e-04 eta: 0:25:12 time: 0.5513 data_time: 0.0047 memory: 16131 loss: 0.8647 loss_prob: 0.4560 loss_thr: 0.3323 loss_db: 0.0764 2022/10/26 09:17:14 - mmengine - INFO - Epoch(train) [1164][50/63] lr: 1.5082e-04 eta: 0:25:06 time: 0.5637 data_time: 0.0203 memory: 16131 loss: 0.8845 loss_prob: 0.4663 loss_thr: 0.3401 loss_db: 0.0782 2022/10/26 09:17:17 - mmengine - INFO - Epoch(train) [1164][55/63] lr: 1.5082e-04 eta: 0:25:06 time: 0.5278 data_time: 0.0259 memory: 16131 loss: 0.8896 loss_prob: 0.4663 loss_thr: 0.3439 loss_db: 0.0793 2022/10/26 09:17:19 - mmengine - INFO - Epoch(train) [1164][60/63] lr: 1.5082e-04 eta: 0:24:59 time: 0.5071 data_time: 0.0103 memory: 16131 loss: 0.8277 loss_prob: 0.4342 loss_thr: 0.3181 loss_db: 0.0754 2022/10/26 09:17:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:17:25 - mmengine - INFO - Epoch(train) [1165][5/63] lr: 1.4705e-04 eta: 0:24:59 time: 0.6824 data_time: 0.1703 memory: 16131 loss: 0.8054 loss_prob: 0.4133 loss_thr: 0.3197 loss_db: 0.0725 2022/10/26 09:17:28 - mmengine - INFO - Epoch(train) [1165][10/63] lr: 1.4705e-04 eta: 0:24:50 time: 0.7196 data_time: 0.1766 memory: 16131 loss: 0.7957 loss_prob: 0.4111 loss_thr: 0.3147 loss_db: 0.0700 2022/10/26 09:17:30 - mmengine - INFO - Epoch(train) [1165][15/63] lr: 1.4705e-04 eta: 0:24:50 time: 0.5371 data_time: 0.0141 memory: 16131 loss: 0.8419 loss_prob: 0.4406 loss_thr: 0.3257 loss_db: 0.0755 2022/10/26 09:17:33 - mmengine - INFO - Epoch(train) [1165][20/63] lr: 1.4705e-04 eta: 0:24:44 time: 0.5347 data_time: 0.0086 memory: 16131 loss: 0.7917 loss_prob: 0.4095 loss_thr: 0.3107 loss_db: 0.0715 2022/10/26 09:17:36 - mmengine - INFO - Epoch(train) [1165][25/63] lr: 1.4705e-04 eta: 0:24:44 time: 0.5412 data_time: 0.0186 memory: 16131 loss: 0.8080 loss_prob: 0.4108 loss_thr: 0.3240 loss_db: 0.0731 2022/10/26 09:17:39 - mmengine - INFO - Epoch(train) [1165][30/63] lr: 1.4705e-04 eta: 0:24:37 time: 0.5513 data_time: 0.0296 memory: 16131 loss: 0.8292 loss_prob: 0.4229 loss_thr: 0.3303 loss_db: 0.0760 2022/10/26 09:17:41 - mmengine - INFO - Epoch(train) [1165][35/63] lr: 1.4705e-04 eta: 0:24:37 time: 0.5245 data_time: 0.0220 memory: 16131 loss: 0.8095 loss_prob: 0.4195 loss_thr: 0.3158 loss_db: 0.0742 2022/10/26 09:17:44 - mmengine - INFO - Epoch(train) [1165][40/63] lr: 1.4705e-04 eta: 0:24:30 time: 0.4937 data_time: 0.0092 memory: 16131 loss: 0.8497 loss_prob: 0.4377 loss_thr: 0.3360 loss_db: 0.0760 2022/10/26 09:17:46 - mmengine - INFO - Epoch(train) [1165][45/63] lr: 1.4705e-04 eta: 0:24:30 time: 0.5247 data_time: 0.0047 memory: 16131 loss: 0.8540 loss_prob: 0.4402 loss_thr: 0.3375 loss_db: 0.0763 2022/10/26 09:17:49 - mmengine - INFO - Epoch(train) [1165][50/63] lr: 1.4705e-04 eta: 0:24:24 time: 0.5469 data_time: 0.0183 memory: 16131 loss: 0.8499 loss_prob: 0.4435 loss_thr: 0.3278 loss_db: 0.0785 2022/10/26 09:17:52 - mmengine - INFO - Epoch(train) [1165][55/63] lr: 1.4705e-04 eta: 0:24:24 time: 0.5125 data_time: 0.0215 memory: 16131 loss: 0.8222 loss_prob: 0.4270 loss_thr: 0.3195 loss_db: 0.0757 2022/10/26 09:17:54 - mmengine - INFO - Epoch(train) [1165][60/63] lr: 1.4705e-04 eta: 0:24:17 time: 0.5104 data_time: 0.0095 memory: 16131 loss: 0.8315 loss_prob: 0.4356 loss_thr: 0.3204 loss_db: 0.0755 2022/10/26 09:17:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:18:00 - mmengine - INFO - Epoch(train) [1166][5/63] lr: 1.4326e-04 eta: 0:24:17 time: 0.7409 data_time: 0.1681 memory: 16131 loss: 0.8957 loss_prob: 0.4693 loss_thr: 0.3459 loss_db: 0.0806 2022/10/26 09:18:03 - mmengine - INFO - Epoch(train) [1166][10/63] lr: 1.4326e-04 eta: 0:24:08 time: 0.7729 data_time: 0.1836 memory: 16131 loss: 0.9081 loss_prob: 0.4768 loss_thr: 0.3487 loss_db: 0.0825 2022/10/26 09:18:06 - mmengine - INFO - Epoch(train) [1166][15/63] lr: 1.4326e-04 eta: 0:24:08 time: 0.5374 data_time: 0.0206 memory: 16131 loss: 0.8981 loss_prob: 0.4648 loss_thr: 0.3519 loss_db: 0.0815 2022/10/26 09:18:09 - mmengine - INFO - Epoch(train) [1166][20/63] lr: 1.4326e-04 eta: 0:24:02 time: 0.5500 data_time: 0.0077 memory: 16131 loss: 0.8921 loss_prob: 0.4662 loss_thr: 0.3467 loss_db: 0.0792 2022/10/26 09:18:11 - mmengine - INFO - Epoch(train) [1166][25/63] lr: 1.4326e-04 eta: 0:24:02 time: 0.5423 data_time: 0.0200 memory: 16131 loss: 1.0134 loss_prob: 0.5684 loss_thr: 0.3559 loss_db: 0.0891 2022/10/26 09:18:14 - mmengine - INFO - Epoch(train) [1166][30/63] lr: 1.4326e-04 eta: 0:23:55 time: 0.5152 data_time: 0.0218 memory: 16131 loss: 0.9164 loss_prob: 0.5061 loss_thr: 0.3287 loss_db: 0.0816 2022/10/26 09:18:17 - mmengine - INFO - Epoch(train) [1166][35/63] lr: 1.4326e-04 eta: 0:23:55 time: 0.5265 data_time: 0.0188 memory: 16131 loss: 0.9118 loss_prob: 0.4811 loss_thr: 0.3465 loss_db: 0.0842 2022/10/26 09:18:19 - mmengine - INFO - Epoch(train) [1166][40/63] lr: 1.4326e-04 eta: 0:23:49 time: 0.5181 data_time: 0.0139 memory: 16131 loss: 0.9190 loss_prob: 0.4896 loss_thr: 0.3450 loss_db: 0.0844 2022/10/26 09:18:22 - mmengine - INFO - Epoch(train) [1166][45/63] lr: 1.4326e-04 eta: 0:23:49 time: 0.5023 data_time: 0.0067 memory: 16131 loss: 0.8716 loss_prob: 0.4612 loss_thr: 0.3312 loss_db: 0.0792 2022/10/26 09:18:24 - mmengine - INFO - Epoch(train) [1166][50/63] lr: 1.4326e-04 eta: 0:23:42 time: 0.5003 data_time: 0.0142 memory: 16131 loss: 0.9119 loss_prob: 0.4832 loss_thr: 0.3449 loss_db: 0.0837 2022/10/26 09:18:27 - mmengine - INFO - Epoch(train) [1166][55/63] lr: 1.4326e-04 eta: 0:23:42 time: 0.5020 data_time: 0.0161 memory: 16131 loss: 0.9396 loss_prob: 0.5064 loss_thr: 0.3487 loss_db: 0.0845 2022/10/26 09:18:29 - mmengine - INFO - Epoch(train) [1166][60/63] lr: 1.4326e-04 eta: 0:23:35 time: 0.5161 data_time: 0.0141 memory: 16131 loss: 0.8995 loss_prob: 0.4845 loss_thr: 0.3341 loss_db: 0.0809 2022/10/26 09:18:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:18:35 - mmengine - INFO - Epoch(train) [1167][5/63] lr: 1.3947e-04 eta: 0:23:35 time: 0.7207 data_time: 0.1946 memory: 16131 loss: 0.8256 loss_prob: 0.4283 loss_thr: 0.3223 loss_db: 0.0749 2022/10/26 09:18:38 - mmengine - INFO - Epoch(train) [1167][10/63] lr: 1.3947e-04 eta: 0:23:27 time: 0.7274 data_time: 0.1948 memory: 16131 loss: 0.8247 loss_prob: 0.4239 loss_thr: 0.3270 loss_db: 0.0738 2022/10/26 09:18:40 - mmengine - INFO - Epoch(train) [1167][15/63] lr: 1.3947e-04 eta: 0:23:27 time: 0.5160 data_time: 0.0105 memory: 16131 loss: 0.7794 loss_prob: 0.4030 loss_thr: 0.3059 loss_db: 0.0704 2022/10/26 09:18:43 - mmengine - INFO - Epoch(train) [1167][20/63] lr: 1.3947e-04 eta: 0:23:20 time: 0.4954 data_time: 0.0180 memory: 16131 loss: 0.8633 loss_prob: 0.4538 loss_thr: 0.3308 loss_db: 0.0787 2022/10/26 09:18:46 - mmengine - INFO - Epoch(train) [1167][25/63] lr: 1.3947e-04 eta: 0:23:20 time: 0.5113 data_time: 0.0264 memory: 16131 loss: 0.8671 loss_prob: 0.4578 loss_thr: 0.3297 loss_db: 0.0797 2022/10/26 09:18:48 - mmengine - INFO - Epoch(train) [1167][30/63] lr: 1.3947e-04 eta: 0:23:13 time: 0.5218 data_time: 0.0338 memory: 16131 loss: 0.8184 loss_prob: 0.4341 loss_thr: 0.3078 loss_db: 0.0764 2022/10/26 09:18:51 - mmengine - INFO - Epoch(train) [1167][35/63] lr: 1.3947e-04 eta: 0:23:13 time: 0.5831 data_time: 0.0202 memory: 16131 loss: 0.8302 loss_prob: 0.4371 loss_thr: 0.3151 loss_db: 0.0779 2022/10/26 09:18:54 - mmengine - INFO - Epoch(train) [1167][40/63] lr: 1.3947e-04 eta: 0:23:07 time: 0.6286 data_time: 0.0140 memory: 16131 loss: 0.8212 loss_prob: 0.4251 loss_thr: 0.3199 loss_db: 0.0762 2022/10/26 09:18:57 - mmengine - INFO - Epoch(train) [1167][45/63] lr: 1.3947e-04 eta: 0:23:07 time: 0.5433 data_time: 0.0134 memory: 16131 loss: 0.8913 loss_prob: 0.4628 loss_thr: 0.3476 loss_db: 0.0809 2022/10/26 09:18:59 - mmengine - INFO - Epoch(train) [1167][50/63] lr: 1.3947e-04 eta: 0:23:00 time: 0.5001 data_time: 0.0137 memory: 16131 loss: 0.8654 loss_prob: 0.4461 loss_thr: 0.3420 loss_db: 0.0773 2022/10/26 09:19:02 - mmengine - INFO - Epoch(train) [1167][55/63] lr: 1.3947e-04 eta: 0:23:00 time: 0.5254 data_time: 0.0283 memory: 16131 loss: 0.7858 loss_prob: 0.4112 loss_thr: 0.3028 loss_db: 0.0718 2022/10/26 09:19:05 - mmengine - INFO - Epoch(train) [1167][60/63] lr: 1.3947e-04 eta: 0:22:53 time: 0.5228 data_time: 0.0215 memory: 16131 loss: 0.8533 loss_prob: 0.4493 loss_thr: 0.3264 loss_db: 0.0776 2022/10/26 09:19:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:19:10 - mmengine - INFO - Epoch(train) [1168][5/63] lr: 1.3566e-04 eta: 0:22:53 time: 0.6579 data_time: 0.1876 memory: 16131 loss: 0.8567 loss_prob: 0.4403 loss_thr: 0.3391 loss_db: 0.0773 2022/10/26 09:19:13 - mmengine - INFO - Epoch(train) [1168][10/63] lr: 1.3566e-04 eta: 0:22:45 time: 0.6932 data_time: 0.1879 memory: 16131 loss: 0.9020 loss_prob: 0.4655 loss_thr: 0.3539 loss_db: 0.0826 2022/10/26 09:19:15 - mmengine - INFO - Epoch(train) [1168][15/63] lr: 1.3566e-04 eta: 0:22:45 time: 0.5056 data_time: 0.0093 memory: 16131 loss: 0.8481 loss_prob: 0.4369 loss_thr: 0.3354 loss_db: 0.0759 2022/10/26 09:19:18 - mmengine - INFO - Epoch(train) [1168][20/63] lr: 1.3566e-04 eta: 0:22:38 time: 0.5160 data_time: 0.0064 memory: 16131 loss: 0.8358 loss_prob: 0.4348 loss_thr: 0.3236 loss_db: 0.0774 2022/10/26 09:19:21 - mmengine - INFO - Epoch(train) [1168][25/63] lr: 1.3566e-04 eta: 0:22:38 time: 0.5545 data_time: 0.0323 memory: 16131 loss: 0.8288 loss_prob: 0.4375 loss_thr: 0.3130 loss_db: 0.0783 2022/10/26 09:19:23 - mmengine - INFO - Epoch(train) [1168][30/63] lr: 1.3566e-04 eta: 0:22:32 time: 0.5500 data_time: 0.0356 memory: 16131 loss: 0.8303 loss_prob: 0.4281 loss_thr: 0.3273 loss_db: 0.0750 2022/10/26 09:19:26 - mmengine - INFO - Epoch(train) [1168][35/63] lr: 1.3566e-04 eta: 0:22:32 time: 0.5262 data_time: 0.0161 memory: 16131 loss: 0.8048 loss_prob: 0.4117 loss_thr: 0.3225 loss_db: 0.0706 2022/10/26 09:19:29 - mmengine - INFO - Epoch(train) [1168][40/63] lr: 1.3566e-04 eta: 0:22:25 time: 0.5293 data_time: 0.0124 memory: 16131 loss: 0.8296 loss_prob: 0.4353 loss_thr: 0.3194 loss_db: 0.0749 2022/10/26 09:19:31 - mmengine - INFO - Epoch(train) [1168][45/63] lr: 1.3566e-04 eta: 0:22:25 time: 0.5091 data_time: 0.0063 memory: 16131 loss: 0.9543 loss_prob: 0.5051 loss_thr: 0.3604 loss_db: 0.0888 2022/10/26 09:19:34 - mmengine - INFO - Epoch(train) [1168][50/63] lr: 1.3566e-04 eta: 0:22:18 time: 0.5050 data_time: 0.0189 memory: 16131 loss: 0.8747 loss_prob: 0.4593 loss_thr: 0.3339 loss_db: 0.0815 2022/10/26 09:19:37 - mmengine - INFO - Epoch(train) [1168][55/63] lr: 1.3566e-04 eta: 0:22:18 time: 0.5343 data_time: 0.0197 memory: 16131 loss: 0.8339 loss_prob: 0.4359 loss_thr: 0.3206 loss_db: 0.0774 2022/10/26 09:19:39 - mmengine - INFO - Epoch(train) [1168][60/63] lr: 1.3566e-04 eta: 0:22:12 time: 0.5271 data_time: 0.0130 memory: 16131 loss: 0.8253 loss_prob: 0.4300 loss_thr: 0.3194 loss_db: 0.0758 2022/10/26 09:19:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:19:45 - mmengine - INFO - Epoch(train) [1169][5/63] lr: 1.3184e-04 eta: 0:22:12 time: 0.6964 data_time: 0.2250 memory: 16131 loss: 0.8368 loss_prob: 0.4398 loss_thr: 0.3220 loss_db: 0.0750 2022/10/26 09:19:48 - mmengine - INFO - Epoch(train) [1169][10/63] lr: 1.3184e-04 eta: 0:22:03 time: 0.7438 data_time: 0.2246 memory: 16131 loss: 0.8114 loss_prob: 0.4157 loss_thr: 0.3230 loss_db: 0.0727 2022/10/26 09:19:50 - mmengine - INFO - Epoch(train) [1169][15/63] lr: 1.3184e-04 eta: 0:22:03 time: 0.5153 data_time: 0.0058 memory: 16131 loss: 1.0297 loss_prob: 0.5895 loss_thr: 0.3523 loss_db: 0.0879 2022/10/26 09:19:53 - mmengine - INFO - Epoch(train) [1169][20/63] lr: 1.3184e-04 eta: 0:21:56 time: 0.4778 data_time: 0.0052 memory: 16131 loss: 1.0347 loss_prob: 0.5961 loss_thr: 0.3506 loss_db: 0.0879 2022/10/26 09:19:55 - mmengine - INFO - Epoch(train) [1169][25/63] lr: 1.3184e-04 eta: 0:21:56 time: 0.4851 data_time: 0.0089 memory: 16131 loss: 0.8124 loss_prob: 0.4133 loss_thr: 0.3277 loss_db: 0.0713 2022/10/26 09:19:58 - mmengine - INFO - Epoch(train) [1169][30/63] lr: 1.3184e-04 eta: 0:21:50 time: 0.5257 data_time: 0.0305 memory: 16131 loss: 0.8634 loss_prob: 0.4518 loss_thr: 0.3355 loss_db: 0.0761 2022/10/26 09:20:01 - mmengine - INFO - Epoch(train) [1169][35/63] lr: 1.3184e-04 eta: 0:21:50 time: 0.5630 data_time: 0.0284 memory: 16131 loss: 0.8119 loss_prob: 0.4274 loss_thr: 0.3112 loss_db: 0.0732 2022/10/26 09:20:03 - mmengine - INFO - Epoch(train) [1169][40/63] lr: 1.3184e-04 eta: 0:21:43 time: 0.5641 data_time: 0.0109 memory: 16131 loss: 0.8623 loss_prob: 0.4449 loss_thr: 0.3382 loss_db: 0.0792 2022/10/26 09:20:06 - mmengine - INFO - Epoch(train) [1169][45/63] lr: 1.3184e-04 eta: 0:21:43 time: 0.5280 data_time: 0.0108 memory: 16131 loss: 0.9273 loss_prob: 0.4940 loss_thr: 0.3498 loss_db: 0.0835 2022/10/26 09:20:08 - mmengine - INFO - Epoch(train) [1169][50/63] lr: 1.3184e-04 eta: 0:21:37 time: 0.5010 data_time: 0.0199 memory: 16131 loss: 0.8886 loss_prob: 0.4769 loss_thr: 0.3310 loss_db: 0.0807 2022/10/26 09:20:11 - mmengine - INFO - Epoch(train) [1169][55/63] lr: 1.3184e-04 eta: 0:21:37 time: 0.5091 data_time: 0.0183 memory: 16131 loss: 0.8525 loss_prob: 0.4497 loss_thr: 0.3235 loss_db: 0.0793 2022/10/26 09:20:14 - mmengine - INFO - Epoch(train) [1169][60/63] lr: 1.3184e-04 eta: 0:21:30 time: 0.5032 data_time: 0.0094 memory: 16131 loss: 0.8421 loss_prob: 0.4456 loss_thr: 0.3178 loss_db: 0.0787 2022/10/26 09:20:15 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:20:20 - mmengine - INFO - Epoch(train) [1170][5/63] lr: 1.2801e-04 eta: 0:21:30 time: 0.7069 data_time: 0.2031 memory: 16131 loss: 0.9399 loss_prob: 0.4849 loss_thr: 0.3710 loss_db: 0.0839 2022/10/26 09:20:22 - mmengine - INFO - Epoch(train) [1170][10/63] lr: 1.2801e-04 eta: 0:21:21 time: 0.7482 data_time: 0.1999 memory: 16131 loss: 0.9734 loss_prob: 0.5031 loss_thr: 0.3838 loss_db: 0.0866 2022/10/26 09:20:25 - mmengine - INFO - Epoch(train) [1170][15/63] lr: 1.2801e-04 eta: 0:21:21 time: 0.5430 data_time: 0.0078 memory: 16131 loss: 0.9112 loss_prob: 0.4716 loss_thr: 0.3567 loss_db: 0.0829 2022/10/26 09:20:27 - mmengine - INFO - Epoch(train) [1170][20/63] lr: 1.2801e-04 eta: 0:21:15 time: 0.5067 data_time: 0.0070 memory: 16131 loss: 0.8654 loss_prob: 0.4472 loss_thr: 0.3386 loss_db: 0.0795 2022/10/26 09:20:30 - mmengine - INFO - Epoch(train) [1170][25/63] lr: 1.2801e-04 eta: 0:21:15 time: 0.5340 data_time: 0.0275 memory: 16131 loss: 0.7819 loss_prob: 0.4007 loss_thr: 0.3107 loss_db: 0.0705 2022/10/26 09:20:33 - mmengine - INFO - Epoch(train) [1170][30/63] lr: 1.2801e-04 eta: 0:21:08 time: 0.5577 data_time: 0.0355 memory: 16131 loss: 0.7275 loss_prob: 0.3684 loss_thr: 0.2945 loss_db: 0.0646 2022/10/26 09:20:36 - mmengine - INFO - Epoch(train) [1170][35/63] lr: 1.2801e-04 eta: 0:21:08 time: 0.5240 data_time: 0.0164 memory: 16131 loss: 0.8039 loss_prob: 0.4118 loss_thr: 0.3204 loss_db: 0.0717 2022/10/26 09:20:39 - mmengine - INFO - Epoch(train) [1170][40/63] lr: 1.2801e-04 eta: 0:21:01 time: 0.5554 data_time: 0.0077 memory: 16131 loss: 0.8172 loss_prob: 0.4213 loss_thr: 0.3209 loss_db: 0.0750 2022/10/26 09:20:41 - mmengine - INFO - Epoch(train) [1170][45/63] lr: 1.2801e-04 eta: 0:21:01 time: 0.5306 data_time: 0.0051 memory: 16131 loss: 0.8024 loss_prob: 0.4153 loss_thr: 0.3132 loss_db: 0.0739 2022/10/26 09:20:44 - mmengine - INFO - Epoch(train) [1170][50/63] lr: 1.2801e-04 eta: 0:20:55 time: 0.5053 data_time: 0.0127 memory: 16131 loss: 0.8267 loss_prob: 0.4272 loss_thr: 0.3244 loss_db: 0.0751 2022/10/26 09:20:46 - mmengine - INFO - Epoch(train) [1170][55/63] lr: 1.2801e-04 eta: 0:20:55 time: 0.5435 data_time: 0.0188 memory: 16131 loss: 0.8658 loss_prob: 0.4438 loss_thr: 0.3435 loss_db: 0.0785 2022/10/26 09:20:49 - mmengine - INFO - Epoch(train) [1170][60/63] lr: 1.2801e-04 eta: 0:20:48 time: 0.5417 data_time: 0.0136 memory: 16131 loss: 0.8615 loss_prob: 0.4472 loss_thr: 0.3354 loss_db: 0.0789 2022/10/26 09:20:50 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:20:55 - mmengine - INFO - Epoch(train) [1171][5/63] lr: 1.2417e-04 eta: 0:20:48 time: 0.6660 data_time: 0.1570 memory: 16131 loss: 0.8806 loss_prob: 0.4730 loss_thr: 0.3242 loss_db: 0.0833 2022/10/26 09:20:57 - mmengine - INFO - Epoch(train) [1171][10/63] lr: 1.2417e-04 eta: 0:20:39 time: 0.6821 data_time: 0.1659 memory: 16131 loss: 0.8909 loss_prob: 0.4756 loss_thr: 0.3317 loss_db: 0.0836 2022/10/26 09:21:00 - mmengine - INFO - Epoch(train) [1171][15/63] lr: 1.2417e-04 eta: 0:20:39 time: 0.5083 data_time: 0.0175 memory: 16131 loss: 0.8951 loss_prob: 0.4703 loss_thr: 0.3434 loss_db: 0.0813 2022/10/26 09:21:02 - mmengine - INFO - Epoch(train) [1171][20/63] lr: 1.2417e-04 eta: 0:20:33 time: 0.5127 data_time: 0.0058 memory: 16131 loss: 0.8674 loss_prob: 0.4538 loss_thr: 0.3360 loss_db: 0.0776 2022/10/26 09:21:05 - mmengine - INFO - Epoch(train) [1171][25/63] lr: 1.2417e-04 eta: 0:20:33 time: 0.5235 data_time: 0.0056 memory: 16131 loss: 0.8645 loss_prob: 0.4534 loss_thr: 0.3330 loss_db: 0.0781 2022/10/26 09:21:08 - mmengine - INFO - Epoch(train) [1171][30/63] lr: 1.2417e-04 eta: 0:20:26 time: 0.5416 data_time: 0.0363 memory: 16131 loss: 0.8746 loss_prob: 0.4524 loss_thr: 0.3437 loss_db: 0.0785 2022/10/26 09:21:10 - mmengine - INFO - Epoch(train) [1171][35/63] lr: 1.2417e-04 eta: 0:20:26 time: 0.5382 data_time: 0.0395 memory: 16131 loss: 0.9166 loss_prob: 0.4786 loss_thr: 0.3546 loss_db: 0.0833 2022/10/26 09:21:13 - mmengine - INFO - Epoch(train) [1171][40/63] lr: 1.2417e-04 eta: 0:20:20 time: 0.5286 data_time: 0.0097 memory: 16131 loss: 0.8349 loss_prob: 0.4336 loss_thr: 0.3265 loss_db: 0.0749 2022/10/26 09:21:15 - mmengine - INFO - Epoch(train) [1171][45/63] lr: 1.2417e-04 eta: 0:20:20 time: 0.5172 data_time: 0.0057 memory: 16131 loss: 0.7851 loss_prob: 0.4080 loss_thr: 0.3060 loss_db: 0.0711 2022/10/26 09:21:18 - mmengine - INFO - Epoch(train) [1171][50/63] lr: 1.2417e-04 eta: 0:20:13 time: 0.5093 data_time: 0.0104 memory: 16131 loss: 0.8614 loss_prob: 0.4598 loss_thr: 0.3196 loss_db: 0.0820 2022/10/26 09:21:21 - mmengine - INFO - Epoch(train) [1171][55/63] lr: 1.2417e-04 eta: 0:20:13 time: 0.5436 data_time: 0.0207 memory: 16131 loss: 0.8226 loss_prob: 0.4357 loss_thr: 0.3102 loss_db: 0.0767 2022/10/26 09:21:24 - mmengine - INFO - Epoch(train) [1171][60/63] lr: 1.2417e-04 eta: 0:20:06 time: 0.5458 data_time: 0.0173 memory: 16131 loss: 0.8253 loss_prob: 0.4283 loss_thr: 0.3244 loss_db: 0.0726 2022/10/26 09:21:25 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:21:29 - mmengine - INFO - Epoch(train) [1172][5/63] lr: 1.2031e-04 eta: 0:20:06 time: 0.6459 data_time: 0.1732 memory: 16131 loss: 0.8623 loss_prob: 0.4477 loss_thr: 0.3360 loss_db: 0.0786 2022/10/26 09:21:32 - mmengine - INFO - Epoch(train) [1172][10/63] lr: 1.2031e-04 eta: 0:19:58 time: 0.6972 data_time: 0.1739 memory: 16131 loss: 0.8453 loss_prob: 0.4385 loss_thr: 0.3287 loss_db: 0.0781 2022/10/26 09:21:34 - mmengine - INFO - Epoch(train) [1172][15/63] lr: 1.2031e-04 eta: 0:19:58 time: 0.5123 data_time: 0.0086 memory: 16131 loss: 0.9061 loss_prob: 0.4766 loss_thr: 0.3452 loss_db: 0.0843 2022/10/26 09:21:37 - mmengine - INFO - Epoch(train) [1172][20/63] lr: 1.2031e-04 eta: 0:19:51 time: 0.4914 data_time: 0.0113 memory: 16131 loss: 0.8928 loss_prob: 0.4683 loss_thr: 0.3417 loss_db: 0.0828 2022/10/26 09:21:39 - mmengine - INFO - Epoch(train) [1172][25/63] lr: 1.2031e-04 eta: 0:19:51 time: 0.4945 data_time: 0.0112 memory: 16131 loss: 0.8893 loss_prob: 0.4682 loss_thr: 0.3400 loss_db: 0.0812 2022/10/26 09:21:42 - mmengine - INFO - Epoch(train) [1172][30/63] lr: 1.2031e-04 eta: 0:19:44 time: 0.5443 data_time: 0.0318 memory: 16131 loss: 0.8805 loss_prob: 0.4616 loss_thr: 0.3405 loss_db: 0.0784 2022/10/26 09:21:45 - mmengine - INFO - Epoch(train) [1172][35/63] lr: 1.2031e-04 eta: 0:19:44 time: 0.5591 data_time: 0.0329 memory: 16131 loss: 0.8201 loss_prob: 0.4252 loss_thr: 0.3214 loss_db: 0.0735 2022/10/26 09:21:47 - mmengine - INFO - Epoch(train) [1172][40/63] lr: 1.2031e-04 eta: 0:19:38 time: 0.5128 data_time: 0.0112 memory: 16131 loss: 0.8244 loss_prob: 0.4241 loss_thr: 0.3254 loss_db: 0.0749 2022/10/26 09:21:51 - mmengine - INFO - Epoch(train) [1172][45/63] lr: 1.2031e-04 eta: 0:19:38 time: 0.5932 data_time: 0.0112 memory: 16131 loss: 0.8791 loss_prob: 0.4564 loss_thr: 0.3419 loss_db: 0.0807 2022/10/26 09:21:53 - mmengine - INFO - Epoch(train) [1172][50/63] lr: 1.2031e-04 eta: 0:19:31 time: 0.6030 data_time: 0.0159 memory: 16131 loss: 0.8479 loss_prob: 0.4434 loss_thr: 0.3254 loss_db: 0.0791 2022/10/26 09:21:56 - mmengine - INFO - Epoch(train) [1172][55/63] lr: 1.2031e-04 eta: 0:19:31 time: 0.5300 data_time: 0.0222 memory: 16131 loss: 0.8803 loss_prob: 0.4653 loss_thr: 0.3341 loss_db: 0.0810 2022/10/26 09:21:58 - mmengine - INFO - Epoch(train) [1172][60/63] lr: 1.2031e-04 eta: 0:19:25 time: 0.5250 data_time: 0.0152 memory: 16131 loss: 0.9169 loss_prob: 0.4909 loss_thr: 0.3427 loss_db: 0.0832 2022/10/26 09:22:00 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:22:04 - mmengine - INFO - Epoch(train) [1173][5/63] lr: 1.1644e-04 eta: 0:19:25 time: 0.6484 data_time: 0.1752 memory: 16131 loss: 1.0174 loss_prob: 0.5573 loss_thr: 0.3663 loss_db: 0.0938 2022/10/26 09:22:07 - mmengine - INFO - Epoch(train) [1173][10/63] lr: 1.1644e-04 eta: 0:19:16 time: 0.6879 data_time: 0.1906 memory: 16131 loss: 1.0118 loss_prob: 0.5573 loss_thr: 0.3595 loss_db: 0.0950 2022/10/26 09:22:10 - mmengine - INFO - Epoch(train) [1173][15/63] lr: 1.1644e-04 eta: 0:19:16 time: 0.5839 data_time: 0.0212 memory: 16131 loss: 0.9144 loss_prob: 0.4890 loss_thr: 0.3409 loss_db: 0.0846 2022/10/26 09:22:12 - mmengine - INFO - Epoch(train) [1173][20/63] lr: 1.1644e-04 eta: 0:19:09 time: 0.5822 data_time: 0.0074 memory: 16131 loss: 0.8331 loss_prob: 0.4345 loss_thr: 0.3220 loss_db: 0.0767 2022/10/26 09:22:15 - mmengine - INFO - Epoch(train) [1173][25/63] lr: 1.1644e-04 eta: 0:19:09 time: 0.5033 data_time: 0.0112 memory: 16131 loss: 0.8358 loss_prob: 0.4327 loss_thr: 0.3269 loss_db: 0.0762 2022/10/26 09:22:18 - mmengine - INFO - Epoch(train) [1173][30/63] lr: 1.1644e-04 eta: 0:19:03 time: 0.5664 data_time: 0.0494 memory: 16131 loss: 0.8686 loss_prob: 0.4537 loss_thr: 0.3365 loss_db: 0.0784 2022/10/26 09:22:21 - mmengine - INFO - Epoch(train) [1173][35/63] lr: 1.1644e-04 eta: 0:19:03 time: 0.5755 data_time: 0.0465 memory: 16131 loss: 0.8479 loss_prob: 0.4465 loss_thr: 0.3243 loss_db: 0.0771 2022/10/26 09:22:23 - mmengine - INFO - Epoch(train) [1173][40/63] lr: 1.1644e-04 eta: 0:18:56 time: 0.5106 data_time: 0.0066 memory: 16131 loss: 0.8381 loss_prob: 0.4410 loss_thr: 0.3204 loss_db: 0.0767 2022/10/26 09:22:26 - mmengine - INFO - Epoch(train) [1173][45/63] lr: 1.1644e-04 eta: 0:18:56 time: 0.5584 data_time: 0.0059 memory: 16131 loss: 0.8203 loss_prob: 0.4279 loss_thr: 0.3167 loss_db: 0.0757 2022/10/26 09:22:29 - mmengine - INFO - Epoch(train) [1173][50/63] lr: 1.1644e-04 eta: 0:18:50 time: 0.5753 data_time: 0.0124 memory: 16131 loss: 0.8320 loss_prob: 0.4294 loss_thr: 0.3258 loss_db: 0.0768 2022/10/26 09:22:31 - mmengine - INFO - Epoch(train) [1173][55/63] lr: 1.1644e-04 eta: 0:18:50 time: 0.5206 data_time: 0.0236 memory: 16131 loss: 0.9302 loss_prob: 0.4877 loss_thr: 0.3562 loss_db: 0.0863 2022/10/26 09:22:34 - mmengine - INFO - Epoch(train) [1173][60/63] lr: 1.1644e-04 eta: 0:18:43 time: 0.5023 data_time: 0.0201 memory: 16131 loss: 0.9226 loss_prob: 0.4837 loss_thr: 0.3530 loss_db: 0.0860 2022/10/26 09:22:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:22:40 - mmengine - INFO - Epoch(train) [1174][5/63] lr: 1.1255e-04 eta: 0:18:43 time: 0.7377 data_time: 0.1971 memory: 16131 loss: 0.7959 loss_prob: 0.4054 loss_thr: 0.3180 loss_db: 0.0725 2022/10/26 09:22:43 - mmengine - INFO - Epoch(train) [1174][10/63] lr: 1.1255e-04 eta: 0:18:34 time: 0.7503 data_time: 0.1958 memory: 16131 loss: 0.7859 loss_prob: 0.3996 loss_thr: 0.3167 loss_db: 0.0696 2022/10/26 09:22:46 - mmengine - INFO - Epoch(train) [1174][15/63] lr: 1.1255e-04 eta: 0:18:34 time: 0.5232 data_time: 0.0095 memory: 16131 loss: 0.8689 loss_prob: 0.4586 loss_thr: 0.3304 loss_db: 0.0798 2022/10/26 09:22:48 - mmengine - INFO - Epoch(train) [1174][20/63] lr: 1.1255e-04 eta: 0:18:28 time: 0.5300 data_time: 0.0092 memory: 16131 loss: 0.8923 loss_prob: 0.4726 loss_thr: 0.3364 loss_db: 0.0833 2022/10/26 09:22:51 - mmengine - INFO - Epoch(train) [1174][25/63] lr: 1.1255e-04 eta: 0:18:28 time: 0.5240 data_time: 0.0228 memory: 16131 loss: 0.9110 loss_prob: 0.4778 loss_thr: 0.3503 loss_db: 0.0829 2022/10/26 09:22:53 - mmengine - INFO - Epoch(train) [1174][30/63] lr: 1.1255e-04 eta: 0:18:21 time: 0.5278 data_time: 0.0301 memory: 16131 loss: 0.8938 loss_prob: 0.4686 loss_thr: 0.3443 loss_db: 0.0809 2022/10/26 09:22:56 - mmengine - INFO - Epoch(train) [1174][35/63] lr: 1.1255e-04 eta: 0:18:21 time: 0.5115 data_time: 0.0152 memory: 16131 loss: 0.7897 loss_prob: 0.4142 loss_thr: 0.3042 loss_db: 0.0714 2022/10/26 09:22:59 - mmengine - INFO - Epoch(train) [1174][40/63] lr: 1.1255e-04 eta: 0:18:14 time: 0.5295 data_time: 0.0080 memory: 16131 loss: 0.7868 loss_prob: 0.4087 loss_thr: 0.3079 loss_db: 0.0702 2022/10/26 09:23:01 - mmengine - INFO - Epoch(train) [1174][45/63] lr: 1.1255e-04 eta: 0:18:14 time: 0.5304 data_time: 0.0045 memory: 16131 loss: 0.8018 loss_prob: 0.4078 loss_thr: 0.3229 loss_db: 0.0710 2022/10/26 09:23:04 - mmengine - INFO - Epoch(train) [1174][50/63] lr: 1.1255e-04 eta: 0:18:08 time: 0.5250 data_time: 0.0165 memory: 16131 loss: 0.8007 loss_prob: 0.4115 loss_thr: 0.3171 loss_db: 0.0721 2022/10/26 09:23:07 - mmengine - INFO - Epoch(train) [1174][55/63] lr: 1.1255e-04 eta: 0:18:08 time: 0.5346 data_time: 0.0257 memory: 16131 loss: 0.7632 loss_prob: 0.3915 loss_thr: 0.3018 loss_db: 0.0699 2022/10/26 09:23:10 - mmengine - INFO - Epoch(train) [1174][60/63] lr: 1.1255e-04 eta: 0:18:01 time: 0.5653 data_time: 0.0154 memory: 16131 loss: 0.7571 loss_prob: 0.3884 loss_thr: 0.2998 loss_db: 0.0690 2022/10/26 09:23:11 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:23:15 - mmengine - INFO - Epoch(train) [1175][5/63] lr: 1.0865e-04 eta: 0:18:01 time: 0.6922 data_time: 0.1819 memory: 16131 loss: 0.8535 loss_prob: 0.4442 loss_thr: 0.3313 loss_db: 0.0781 2022/10/26 09:23:18 - mmengine - INFO - Epoch(train) [1175][10/63] lr: 1.0865e-04 eta: 0:17:53 time: 0.6929 data_time: 0.1751 memory: 16131 loss: 0.8928 loss_prob: 0.4675 loss_thr: 0.3430 loss_db: 0.0822 2022/10/26 09:23:21 - mmengine - INFO - Epoch(train) [1175][15/63] lr: 1.0865e-04 eta: 0:17:53 time: 0.5182 data_time: 0.0124 memory: 16131 loss: 0.8934 loss_prob: 0.4646 loss_thr: 0.3474 loss_db: 0.0813 2022/10/26 09:23:23 - mmengine - INFO - Epoch(train) [1175][20/63] lr: 1.0865e-04 eta: 0:17:46 time: 0.5254 data_time: 0.0114 memory: 16131 loss: 0.8219 loss_prob: 0.4157 loss_thr: 0.3330 loss_db: 0.0733 2022/10/26 09:23:26 - mmengine - INFO - Epoch(train) [1175][25/63] lr: 1.0865e-04 eta: 0:17:46 time: 0.5173 data_time: 0.0206 memory: 16131 loss: 0.7635 loss_prob: 0.3837 loss_thr: 0.3118 loss_db: 0.0680 2022/10/26 09:23:28 - mmengine - INFO - Epoch(train) [1175][30/63] lr: 1.0865e-04 eta: 0:17:39 time: 0.5139 data_time: 0.0277 memory: 16131 loss: 0.7647 loss_prob: 0.3920 loss_thr: 0.3043 loss_db: 0.0685 2022/10/26 09:23:31 - mmengine - INFO - Epoch(train) [1175][35/63] lr: 1.0865e-04 eta: 0:17:39 time: 0.5118 data_time: 0.0138 memory: 16131 loss: 0.7798 loss_prob: 0.3980 loss_thr: 0.3123 loss_db: 0.0695 2022/10/26 09:23:32 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:23:33 - mmengine - INFO - Epoch(train) [1175][40/63] lr: 1.0865e-04 eta: 0:17:33 time: 0.4937 data_time: 0.0131 memory: 16131 loss: 0.8396 loss_prob: 0.4237 loss_thr: 0.3414 loss_db: 0.0745 2022/10/26 09:23:36 - mmengine - INFO - Epoch(train) [1175][45/63] lr: 1.0865e-04 eta: 0:17:33 time: 0.5242 data_time: 0.0119 memory: 16131 loss: 0.8041 loss_prob: 0.4084 loss_thr: 0.3240 loss_db: 0.0717 2022/10/26 09:23:39 - mmengine - INFO - Epoch(train) [1175][50/63] lr: 1.0865e-04 eta: 0:17:26 time: 0.5532 data_time: 0.0185 memory: 16131 loss: 0.7914 loss_prob: 0.4107 loss_thr: 0.3079 loss_db: 0.0728 2022/10/26 09:23:42 - mmengine - INFO - Epoch(train) [1175][55/63] lr: 1.0865e-04 eta: 0:17:26 time: 0.5610 data_time: 0.0222 memory: 16131 loss: 0.8500 loss_prob: 0.4443 loss_thr: 0.3271 loss_db: 0.0786 2022/10/26 09:23:44 - mmengine - INFO - Epoch(train) [1175][60/63] lr: 1.0865e-04 eta: 0:17:20 time: 0.5478 data_time: 0.0138 memory: 16131 loss: 0.8170 loss_prob: 0.4296 loss_thr: 0.3134 loss_db: 0.0741 2022/10/26 09:23:46 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:23:50 - mmengine - INFO - Epoch(train) [1176][5/63] lr: 1.0474e-04 eta: 0:17:20 time: 0.6966 data_time: 0.1915 memory: 16131 loss: 0.7659 loss_prob: 0.3977 loss_thr: 0.2999 loss_db: 0.0683 2022/10/26 09:23:53 - mmengine - INFO - Epoch(train) [1176][10/63] lr: 1.0474e-04 eta: 0:17:11 time: 0.7948 data_time: 0.1906 memory: 16131 loss: 0.8322 loss_prob: 0.4380 loss_thr: 0.3179 loss_db: 0.0763 2022/10/26 09:23:56 - mmengine - INFO - Epoch(train) [1176][15/63] lr: 1.0474e-04 eta: 0:17:11 time: 0.5897 data_time: 0.0174 memory: 16131 loss: 0.7902 loss_prob: 0.4067 loss_thr: 0.3125 loss_db: 0.0711 2022/10/26 09:23:59 - mmengine - INFO - Epoch(train) [1176][20/63] lr: 1.0474e-04 eta: 0:17:04 time: 0.5082 data_time: 0.0165 memory: 16131 loss: 0.8346 loss_prob: 0.4307 loss_thr: 0.3281 loss_db: 0.0757 2022/10/26 09:24:01 - mmengine - INFO - Epoch(train) [1176][25/63] lr: 1.0474e-04 eta: 0:17:04 time: 0.5279 data_time: 0.0258 memory: 16131 loss: 0.9186 loss_prob: 0.4854 loss_thr: 0.3488 loss_db: 0.0845 2022/10/26 09:24:04 - mmengine - INFO - Epoch(train) [1176][30/63] lr: 1.0474e-04 eta: 0:16:58 time: 0.5702 data_time: 0.0408 memory: 16131 loss: 0.8508 loss_prob: 0.4389 loss_thr: 0.3350 loss_db: 0.0769 2022/10/26 09:24:07 - mmengine - INFO - Epoch(train) [1176][35/63] lr: 1.0474e-04 eta: 0:16:58 time: 0.5359 data_time: 0.0211 memory: 16131 loss: 0.7807 loss_prob: 0.4026 loss_thr: 0.3076 loss_db: 0.0704 2022/10/26 09:24:10 - mmengine - INFO - Epoch(train) [1176][40/63] lr: 1.0474e-04 eta: 0:16:51 time: 0.5333 data_time: 0.0060 memory: 16131 loss: 0.7704 loss_prob: 0.4020 loss_thr: 0.2986 loss_db: 0.0698 2022/10/26 09:24:12 - mmengine - INFO - Epoch(train) [1176][45/63] lr: 1.0474e-04 eta: 0:16:51 time: 0.5620 data_time: 0.0055 memory: 16131 loss: 0.8389 loss_prob: 0.4481 loss_thr: 0.3161 loss_db: 0.0747 2022/10/26 09:24:15 - mmengine - INFO - Epoch(train) [1176][50/63] lr: 1.0474e-04 eta: 0:16:44 time: 0.5555 data_time: 0.0186 memory: 16131 loss: 0.9283 loss_prob: 0.5012 loss_thr: 0.3421 loss_db: 0.0850 2022/10/26 09:24:18 - mmengine - INFO - Epoch(train) [1176][55/63] lr: 1.0474e-04 eta: 0:16:44 time: 0.5126 data_time: 0.0183 memory: 16131 loss: 0.8646 loss_prob: 0.4574 loss_thr: 0.3262 loss_db: 0.0810 2022/10/26 09:24:20 - mmengine - INFO - Epoch(train) [1176][60/63] lr: 1.0474e-04 eta: 0:16:38 time: 0.4868 data_time: 0.0061 memory: 16131 loss: 0.8303 loss_prob: 0.4321 loss_thr: 0.3218 loss_db: 0.0764 2022/10/26 09:24:21 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:24:26 - mmengine - INFO - Epoch(train) [1177][5/63] lr: 1.0081e-04 eta: 0:16:38 time: 0.6597 data_time: 0.1808 memory: 16131 loss: 0.8189 loss_prob: 0.4218 loss_thr: 0.3234 loss_db: 0.0737 2022/10/26 09:24:28 - mmengine - INFO - Epoch(train) [1177][10/63] lr: 1.0081e-04 eta: 0:16:29 time: 0.6816 data_time: 0.1842 memory: 16131 loss: 0.8001 loss_prob: 0.4120 loss_thr: 0.3151 loss_db: 0.0731 2022/10/26 09:24:30 - mmengine - INFO - Epoch(train) [1177][15/63] lr: 1.0081e-04 eta: 0:16:29 time: 0.4885 data_time: 0.0105 memory: 16131 loss: 0.8290 loss_prob: 0.4334 loss_thr: 0.3184 loss_db: 0.0772 2022/10/26 09:24:33 - mmengine - INFO - Epoch(train) [1177][20/63] lr: 1.0081e-04 eta: 0:16:23 time: 0.4800 data_time: 0.0111 memory: 16131 loss: 0.7879 loss_prob: 0.4095 loss_thr: 0.3060 loss_db: 0.0724 2022/10/26 09:24:36 - mmengine - INFO - Epoch(train) [1177][25/63] lr: 1.0081e-04 eta: 0:16:23 time: 0.5274 data_time: 0.0454 memory: 16131 loss: 0.8013 loss_prob: 0.4106 loss_thr: 0.3194 loss_db: 0.0713 2022/10/26 09:24:39 - mmengine - INFO - Epoch(train) [1177][30/63] lr: 1.0081e-04 eta: 0:16:16 time: 0.5733 data_time: 0.0406 memory: 16131 loss: 0.8592 loss_prob: 0.4460 loss_thr: 0.3377 loss_db: 0.0755 2022/10/26 09:24:41 - mmengine - INFO - Epoch(train) [1177][35/63] lr: 1.0081e-04 eta: 0:16:16 time: 0.5356 data_time: 0.0060 memory: 16131 loss: 0.8930 loss_prob: 0.4687 loss_thr: 0.3439 loss_db: 0.0803 2022/10/26 09:24:44 - mmengine - INFO - Epoch(train) [1177][40/63] lr: 1.0081e-04 eta: 0:16:09 time: 0.5267 data_time: 0.0083 memory: 16131 loss: 0.8826 loss_prob: 0.4630 loss_thr: 0.3385 loss_db: 0.0810 2022/10/26 09:24:46 - mmengine - INFO - Epoch(train) [1177][45/63] lr: 1.0081e-04 eta: 0:16:09 time: 0.5224 data_time: 0.0079 memory: 16131 loss: 0.7817 loss_prob: 0.4106 loss_thr: 0.2981 loss_db: 0.0730 2022/10/26 09:24:49 - mmengine - INFO - Epoch(train) [1177][50/63] lr: 1.0081e-04 eta: 0:16:03 time: 0.5324 data_time: 0.0292 memory: 16131 loss: 0.7923 loss_prob: 0.4122 loss_thr: 0.3073 loss_db: 0.0727 2022/10/26 09:24:52 - mmengine - INFO - Epoch(train) [1177][55/63] lr: 1.0081e-04 eta: 0:16:03 time: 0.5305 data_time: 0.0290 memory: 16131 loss: 0.8414 loss_prob: 0.4335 loss_thr: 0.3326 loss_db: 0.0753 2022/10/26 09:24:54 - mmengine - INFO - Epoch(train) [1177][60/63] lr: 1.0081e-04 eta: 0:15:56 time: 0.5002 data_time: 0.0075 memory: 16131 loss: 0.8574 loss_prob: 0.4540 loss_thr: 0.3248 loss_db: 0.0786 2022/10/26 09:24:56 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:25:01 - mmengine - INFO - Epoch(train) [1178][5/63] lr: 9.6856e-05 eta: 0:15:56 time: 0.7409 data_time: 0.1890 memory: 16131 loss: 0.8686 loss_prob: 0.4657 loss_thr: 0.3228 loss_db: 0.0801 2022/10/26 09:25:03 - mmengine - INFO - Epoch(train) [1178][10/63] lr: 9.6856e-05 eta: 0:15:48 time: 0.7677 data_time: 0.1873 memory: 16131 loss: 0.8007 loss_prob: 0.4183 loss_thr: 0.3104 loss_db: 0.0719 2022/10/26 09:25:06 - mmengine - INFO - Epoch(train) [1178][15/63] lr: 9.6856e-05 eta: 0:15:48 time: 0.5149 data_time: 0.0063 memory: 16131 loss: 0.8611 loss_prob: 0.4439 loss_thr: 0.3407 loss_db: 0.0765 2022/10/26 09:25:08 - mmengine - INFO - Epoch(train) [1178][20/63] lr: 9.6856e-05 eta: 0:15:41 time: 0.5126 data_time: 0.0067 memory: 16131 loss: 0.9018 loss_prob: 0.4664 loss_thr: 0.3545 loss_db: 0.0809 2022/10/26 09:25:11 - mmengine - INFO - Epoch(train) [1178][25/63] lr: 9.6856e-05 eta: 0:15:41 time: 0.5495 data_time: 0.0190 memory: 16131 loss: 0.8265 loss_prob: 0.4331 loss_thr: 0.3187 loss_db: 0.0747 2022/10/26 09:25:14 - mmengine - INFO - Epoch(train) [1178][30/63] lr: 9.6856e-05 eta: 0:15:34 time: 0.5788 data_time: 0.0374 memory: 16131 loss: 0.8600 loss_prob: 0.4557 loss_thr: 0.3271 loss_db: 0.0773 2022/10/26 09:25:17 - mmengine - INFO - Epoch(train) [1178][35/63] lr: 9.6856e-05 eta: 0:15:34 time: 0.5517 data_time: 0.0277 memory: 16131 loss: 0.8643 loss_prob: 0.4640 loss_thr: 0.3214 loss_db: 0.0788 2022/10/26 09:25:19 - mmengine - INFO - Epoch(train) [1178][40/63] lr: 9.6856e-05 eta: 0:15:28 time: 0.5303 data_time: 0.0089 memory: 16131 loss: 0.8386 loss_prob: 0.4477 loss_thr: 0.3154 loss_db: 0.0754 2022/10/26 09:25:22 - mmengine - INFO - Epoch(train) [1178][45/63] lr: 9.6856e-05 eta: 0:15:28 time: 0.5292 data_time: 0.0067 memory: 16131 loss: 0.8858 loss_prob: 0.4616 loss_thr: 0.3453 loss_db: 0.0788 2022/10/26 09:25:25 - mmengine - INFO - Epoch(train) [1178][50/63] lr: 9.6856e-05 eta: 0:15:21 time: 0.5131 data_time: 0.0207 memory: 16131 loss: 0.8878 loss_prob: 0.4652 loss_thr: 0.3432 loss_db: 0.0795 2022/10/26 09:25:27 - mmengine - INFO - Epoch(train) [1178][55/63] lr: 9.6856e-05 eta: 0:15:21 time: 0.5042 data_time: 0.0249 memory: 16131 loss: 0.8214 loss_prob: 0.4332 loss_thr: 0.3137 loss_db: 0.0745 2022/10/26 09:25:30 - mmengine - INFO - Epoch(train) [1178][60/63] lr: 9.6856e-05 eta: 0:15:15 time: 0.4939 data_time: 0.0125 memory: 16131 loss: 0.8085 loss_prob: 0.4172 loss_thr: 0.3158 loss_db: 0.0755 2022/10/26 09:25:31 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:25:36 - mmengine - INFO - Epoch(train) [1179][5/63] lr: 9.2889e-05 eta: 0:15:15 time: 0.7824 data_time: 0.2468 memory: 16131 loss: 0.8202 loss_prob: 0.4257 loss_thr: 0.3188 loss_db: 0.0756 2022/10/26 09:25:39 - mmengine - INFO - Epoch(train) [1179][10/63] lr: 9.2889e-05 eta: 0:15:06 time: 0.8005 data_time: 0.2473 memory: 16131 loss: 0.8540 loss_prob: 0.4461 loss_thr: 0.3295 loss_db: 0.0784 2022/10/26 09:25:41 - mmengine - INFO - Epoch(train) [1179][15/63] lr: 9.2889e-05 eta: 0:15:06 time: 0.5028 data_time: 0.0085 memory: 16131 loss: 0.8361 loss_prob: 0.4322 loss_thr: 0.3285 loss_db: 0.0753 2022/10/26 09:25:44 - mmengine - INFO - Epoch(train) [1179][20/63] lr: 9.2889e-05 eta: 0:14:59 time: 0.5255 data_time: 0.0080 memory: 16131 loss: 0.7806 loss_prob: 0.4045 loss_thr: 0.3050 loss_db: 0.0711 2022/10/26 09:25:47 - mmengine - INFO - Epoch(train) [1179][25/63] lr: 9.2889e-05 eta: 0:14:59 time: 0.5420 data_time: 0.0148 memory: 16131 loss: 0.7796 loss_prob: 0.4059 loss_thr: 0.3006 loss_db: 0.0731 2022/10/26 09:25:50 - mmengine - INFO - Epoch(train) [1179][30/63] lr: 9.2889e-05 eta: 0:14:53 time: 0.5345 data_time: 0.0309 memory: 16131 loss: 0.8502 loss_prob: 0.4413 loss_thr: 0.3311 loss_db: 0.0777 2022/10/26 09:25:53 - mmengine - INFO - Epoch(train) [1179][35/63] lr: 9.2889e-05 eta: 0:14:53 time: 0.6309 data_time: 0.0270 memory: 16131 loss: 0.8299 loss_prob: 0.4306 loss_thr: 0.3252 loss_db: 0.0741 2022/10/26 09:25:56 - mmengine - INFO - Epoch(train) [1179][40/63] lr: 9.2889e-05 eta: 0:14:46 time: 0.6116 data_time: 0.0088 memory: 16131 loss: 0.8515 loss_prob: 0.4490 loss_thr: 0.3263 loss_db: 0.0761 2022/10/26 09:25:58 - mmengine - INFO - Epoch(train) [1179][45/63] lr: 9.2889e-05 eta: 0:14:46 time: 0.4959 data_time: 0.0069 memory: 16131 loss: 0.9155 loss_prob: 0.4781 loss_thr: 0.3554 loss_db: 0.0821 2022/10/26 09:26:01 - mmengine - INFO - Epoch(train) [1179][50/63] lr: 9.2889e-05 eta: 0:14:40 time: 0.5345 data_time: 0.0232 memory: 16131 loss: 0.8801 loss_prob: 0.4570 loss_thr: 0.3434 loss_db: 0.0797 2022/10/26 09:26:04 - mmengine - INFO - Epoch(train) [1179][55/63] lr: 9.2889e-05 eta: 0:14:40 time: 0.5669 data_time: 0.0242 memory: 16131 loss: 0.8396 loss_prob: 0.4488 loss_thr: 0.3133 loss_db: 0.0776 2022/10/26 09:26:06 - mmengine - INFO - Epoch(train) [1179][60/63] lr: 9.2889e-05 eta: 0:14:33 time: 0.5305 data_time: 0.0108 memory: 16131 loss: 0.8581 loss_prob: 0.4609 loss_thr: 0.3169 loss_db: 0.0803 2022/10/26 09:26:08 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:26:13 - mmengine - INFO - Epoch(train) [1180][5/63] lr: 8.8902e-05 eta: 0:14:33 time: 0.7796 data_time: 0.2020 memory: 16131 loss: 0.8710 loss_prob: 0.4519 loss_thr: 0.3420 loss_db: 0.0771 2022/10/26 09:26:16 - mmengine - INFO - Epoch(train) [1180][10/63] lr: 8.8902e-05 eta: 0:14:24 time: 0.8057 data_time: 0.2005 memory: 16131 loss: 0.9035 loss_prob: 0.4720 loss_thr: 0.3502 loss_db: 0.0813 2022/10/26 09:26:18 - mmengine - INFO - Epoch(train) [1180][15/63] lr: 8.8902e-05 eta: 0:14:24 time: 0.5093 data_time: 0.0050 memory: 16131 loss: 0.8199 loss_prob: 0.4292 loss_thr: 0.3164 loss_db: 0.0742 2022/10/26 09:26:21 - mmengine - INFO - Epoch(train) [1180][20/63] lr: 8.8902e-05 eta: 0:14:18 time: 0.5085 data_time: 0.0054 memory: 16131 loss: 0.8738 loss_prob: 0.4738 loss_thr: 0.3209 loss_db: 0.0791 2022/10/26 09:26:24 - mmengine - INFO - Epoch(train) [1180][25/63] lr: 8.8902e-05 eta: 0:14:18 time: 0.5538 data_time: 0.0268 memory: 16131 loss: 0.9119 loss_prob: 0.4892 loss_thr: 0.3404 loss_db: 0.0823 2022/10/26 09:26:26 - mmengine - INFO - Epoch(train) [1180][30/63] lr: 8.8902e-05 eta: 0:14:11 time: 0.5647 data_time: 0.0372 memory: 16131 loss: 0.9056 loss_prob: 0.4685 loss_thr: 0.3554 loss_db: 0.0818 2022/10/26 09:26:29 - mmengine - INFO - Epoch(train) [1180][35/63] lr: 8.8902e-05 eta: 0:14:11 time: 0.5191 data_time: 0.0170 memory: 16131 loss: 0.9247 loss_prob: 0.4777 loss_thr: 0.3635 loss_db: 0.0834 2022/10/26 09:26:32 - mmengine - INFO - Epoch(train) [1180][40/63] lr: 8.8902e-05 eta: 0:14:05 time: 0.5162 data_time: 0.0080 memory: 16131 loss: 0.9251 loss_prob: 0.4811 loss_thr: 0.3607 loss_db: 0.0833 2022/10/26 09:26:34 - mmengine - INFO - Epoch(train) [1180][45/63] lr: 8.8902e-05 eta: 0:14:05 time: 0.5162 data_time: 0.0085 memory: 16131 loss: 0.8561 loss_prob: 0.4497 loss_thr: 0.3283 loss_db: 0.0781 2022/10/26 09:26:37 - mmengine - INFO - Epoch(train) [1180][50/63] lr: 8.8902e-05 eta: 0:13:58 time: 0.5073 data_time: 0.0188 memory: 16131 loss: 0.7525 loss_prob: 0.3887 loss_thr: 0.2975 loss_db: 0.0663 2022/10/26 09:26:39 - mmengine - INFO - Epoch(train) [1180][55/63] lr: 8.8902e-05 eta: 0:13:58 time: 0.5357 data_time: 0.0228 memory: 16131 loss: 0.7795 loss_prob: 0.3978 loss_thr: 0.3133 loss_db: 0.0684 2022/10/26 09:26:42 - mmengine - INFO - Epoch(train) [1180][60/63] lr: 8.8902e-05 eta: 0:13:51 time: 0.5233 data_time: 0.0124 memory: 16131 loss: 0.8356 loss_prob: 0.4323 loss_thr: 0.3260 loss_db: 0.0773 2022/10/26 09:26:43 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:26:43 - mmengine - INFO - Saving checkpoint at 1180 epochs 2022/10/26 09:26:50 - mmengine - INFO - Epoch(val) [1180][5/32] eta: 0:13:51 time: 0.5063 data_time: 0.0616 memory: 16131 2022/10/26 09:26:53 - mmengine - INFO - Epoch(val) [1180][10/32] eta: 0:00:12 time: 0.5799 data_time: 0.0920 memory: 15724 2022/10/26 09:26:56 - mmengine - INFO - Epoch(val) [1180][15/32] eta: 0:00:12 time: 0.5291 data_time: 0.0440 memory: 15724 2022/10/26 09:26:59 - mmengine - INFO - Epoch(val) [1180][20/32] eta: 0:00:06 time: 0.5390 data_time: 0.0533 memory: 15724 2022/10/26 09:27:01 - mmengine - INFO - Epoch(val) [1180][25/32] eta: 0:00:06 time: 0.5578 data_time: 0.0556 memory: 15724 2022/10/26 09:27:04 - mmengine - INFO - Epoch(val) [1180][30/32] eta: 0:00:01 time: 0.5198 data_time: 0.0218 memory: 15724 2022/10/26 09:27:05 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8349, precision: 0.7857, hmean: 0.8095 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8349, precision: 0.8269, hmean: 0.8309 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8344, precision: 0.8483, hmean: 0.8413 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8300, precision: 0.8716, hmean: 0.8503 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8204, precision: 0.8950, hmean: 0.8561 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7535, precision: 0.9310, hmean: 0.8329 2022/10/26 09:27:05 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2513, precision: 0.9757, hmean: 0.3997 2022/10/26 09:27:05 - mmengine - INFO - Epoch(val) [1180][32/32] icdar/precision: 0.8950 icdar/recall: 0.8204 icdar/hmean: 0.8561 2022/10/26 09:27:09 - mmengine - INFO - Epoch(train) [1181][5/63] lr: 8.4896e-05 eta: 0:00:01 time: 0.6634 data_time: 0.1927 memory: 16131 loss: 0.7968 loss_prob: 0.4149 loss_thr: 0.3086 loss_db: 0.0733 2022/10/26 09:27:12 - mmengine - INFO - Epoch(train) [1181][10/63] lr: 8.4896e-05 eta: 0:13:43 time: 0.7161 data_time: 0.1976 memory: 16131 loss: 0.8282 loss_prob: 0.4343 loss_thr: 0.3180 loss_db: 0.0759 2022/10/26 09:27:15 - mmengine - INFO - Epoch(train) [1181][15/63] lr: 8.4896e-05 eta: 0:13:43 time: 0.6219 data_time: 0.0139 memory: 16131 loss: 0.8249 loss_prob: 0.4263 loss_thr: 0.3239 loss_db: 0.0747 2022/10/26 09:27:18 - mmengine - INFO - Epoch(train) [1181][20/63] lr: 8.4896e-05 eta: 0:13:36 time: 0.6015 data_time: 0.0153 memory: 16131 loss: 0.8167 loss_prob: 0.4207 loss_thr: 0.3240 loss_db: 0.0720 2022/10/26 09:27:21 - mmengine - INFO - Epoch(train) [1181][25/63] lr: 8.4896e-05 eta: 0:13:36 time: 0.5435 data_time: 0.0440 memory: 16131 loss: 0.8509 loss_prob: 0.4478 loss_thr: 0.3271 loss_db: 0.0760 2022/10/26 09:27:23 - mmengine - INFO - Epoch(train) [1181][30/63] lr: 8.4896e-05 eta: 0:13:29 time: 0.5354 data_time: 0.0357 memory: 16131 loss: 0.8744 loss_prob: 0.4742 loss_thr: 0.3227 loss_db: 0.0775 2022/10/26 09:27:26 - mmengine - INFO - Epoch(train) [1181][35/63] lr: 8.4896e-05 eta: 0:13:29 time: 0.4971 data_time: 0.0101 memory: 16131 loss: 0.9132 loss_prob: 0.4947 loss_thr: 0.3363 loss_db: 0.0822 2022/10/26 09:27:28 - mmengine - INFO - Epoch(train) [1181][40/63] lr: 8.4896e-05 eta: 0:13:23 time: 0.5151 data_time: 0.0106 memory: 16131 loss: 0.9132 loss_prob: 0.4780 loss_thr: 0.3506 loss_db: 0.0846 2022/10/26 09:27:31 - mmengine - INFO - Epoch(train) [1181][45/63] lr: 8.4896e-05 eta: 0:13:23 time: 0.5302 data_time: 0.0052 memory: 16131 loss: 0.8962 loss_prob: 0.4634 loss_thr: 0.3507 loss_db: 0.0821 2022/10/26 09:27:34 - mmengine - INFO - Epoch(train) [1181][50/63] lr: 8.4896e-05 eta: 0:13:16 time: 0.5339 data_time: 0.0197 memory: 16131 loss: 0.8150 loss_prob: 0.4162 loss_thr: 0.3247 loss_db: 0.0741 2022/10/26 09:27:36 - mmengine - INFO - Epoch(train) [1181][55/63] lr: 8.4896e-05 eta: 0:13:16 time: 0.5212 data_time: 0.0226 memory: 16131 loss: 0.8100 loss_prob: 0.4186 loss_thr: 0.3179 loss_db: 0.0735 2022/10/26 09:27:39 - mmengine - INFO - Epoch(train) [1181][60/63] lr: 8.4896e-05 eta: 0:13:10 time: 0.4987 data_time: 0.0090 memory: 16131 loss: 0.8932 loss_prob: 0.4642 loss_thr: 0.3485 loss_db: 0.0806 2022/10/26 09:27:40 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:27:45 - mmengine - INFO - Epoch(train) [1182][5/63] lr: 8.0869e-05 eta: 0:13:10 time: 0.7380 data_time: 0.2183 memory: 16131 loss: 0.8557 loss_prob: 0.4407 loss_thr: 0.3375 loss_db: 0.0775 2022/10/26 09:27:48 - mmengine - INFO - Epoch(train) [1182][10/63] lr: 8.0869e-05 eta: 0:13:01 time: 0.7743 data_time: 0.2198 memory: 16131 loss: 0.8591 loss_prob: 0.4429 loss_thr: 0.3377 loss_db: 0.0785 2022/10/26 09:27:50 - mmengine - INFO - Epoch(train) [1182][15/63] lr: 8.0869e-05 eta: 0:13:01 time: 0.5047 data_time: 0.0076 memory: 16131 loss: 0.8634 loss_prob: 0.4489 loss_thr: 0.3354 loss_db: 0.0791 2022/10/26 09:27:53 - mmengine - INFO - Epoch(train) [1182][20/63] lr: 8.0869e-05 eta: 0:12:54 time: 0.5001 data_time: 0.0058 memory: 16131 loss: 0.8673 loss_prob: 0.4542 loss_thr: 0.3362 loss_db: 0.0769 2022/10/26 09:27:56 - mmengine - INFO - Epoch(train) [1182][25/63] lr: 8.0869e-05 eta: 0:12:54 time: 0.5448 data_time: 0.0262 memory: 16131 loss: 0.8479 loss_prob: 0.4440 loss_thr: 0.3300 loss_db: 0.0739 2022/10/26 09:27:58 - mmengine - INFO - Epoch(train) [1182][30/63] lr: 8.0869e-05 eta: 0:12:48 time: 0.5683 data_time: 0.0343 memory: 16131 loss: 0.7898 loss_prob: 0.4150 loss_thr: 0.3040 loss_db: 0.0708 2022/10/26 09:28:01 - mmengine - INFO - Epoch(train) [1182][35/63] lr: 8.0869e-05 eta: 0:12:48 time: 0.5640 data_time: 0.0157 memory: 16131 loss: 0.8236 loss_prob: 0.4320 loss_thr: 0.3162 loss_db: 0.0754 2022/10/26 09:28:04 - mmengine - INFO - Epoch(train) [1182][40/63] lr: 8.0869e-05 eta: 0:12:41 time: 0.5353 data_time: 0.0080 memory: 16131 loss: 0.8957 loss_prob: 0.4726 loss_thr: 0.3407 loss_db: 0.0824 2022/10/26 09:28:06 - mmengine - INFO - Epoch(train) [1182][45/63] lr: 8.0869e-05 eta: 0:12:41 time: 0.5141 data_time: 0.0074 memory: 16131 loss: 0.8903 loss_prob: 0.4746 loss_thr: 0.3318 loss_db: 0.0839 2022/10/26 09:28:09 - mmengine - INFO - Epoch(train) [1182][50/63] lr: 8.0869e-05 eta: 0:12:35 time: 0.5360 data_time: 0.0189 memory: 16131 loss: 0.8002 loss_prob: 0.4153 loss_thr: 0.3105 loss_db: 0.0744 2022/10/26 09:28:12 - mmengine - INFO - Epoch(train) [1182][55/63] lr: 8.0869e-05 eta: 0:12:35 time: 0.5454 data_time: 0.0229 memory: 16131 loss: 0.8139 loss_prob: 0.4171 loss_thr: 0.3235 loss_db: 0.0733 2022/10/26 09:28:14 - mmengine - INFO - Epoch(train) [1182][60/63] lr: 8.0869e-05 eta: 0:12:28 time: 0.5369 data_time: 0.0102 memory: 16131 loss: 0.8218 loss_prob: 0.4221 loss_thr: 0.3262 loss_db: 0.0734 2022/10/26 09:28:16 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:28:21 - mmengine - INFO - Epoch(train) [1183][5/63] lr: 7.6819e-05 eta: 0:12:28 time: 0.7803 data_time: 0.1719 memory: 16131 loss: 0.8033 loss_prob: 0.4172 loss_thr: 0.3133 loss_db: 0.0728 2022/10/26 09:28:24 - mmengine - INFO - Epoch(train) [1183][10/63] lr: 7.6819e-05 eta: 0:12:20 time: 0.8117 data_time: 0.1810 memory: 16131 loss: 0.7908 loss_prob: 0.4063 loss_thr: 0.3130 loss_db: 0.0715 2022/10/26 09:28:27 - mmengine - INFO - Epoch(train) [1183][15/63] lr: 7.6819e-05 eta: 0:12:20 time: 0.5326 data_time: 0.0143 memory: 16131 loss: 0.8055 loss_prob: 0.4138 loss_thr: 0.3184 loss_db: 0.0732 2022/10/26 09:28:29 - mmengine - INFO - Epoch(train) [1183][20/63] lr: 7.6819e-05 eta: 0:12:13 time: 0.5108 data_time: 0.0065 memory: 16131 loss: 0.7838 loss_prob: 0.3963 loss_thr: 0.3168 loss_db: 0.0707 2022/10/26 09:28:32 - mmengine - INFO - Epoch(train) [1183][25/63] lr: 7.6819e-05 eta: 0:12:13 time: 0.5356 data_time: 0.0198 memory: 16131 loss: 0.8346 loss_prob: 0.4269 loss_thr: 0.3344 loss_db: 0.0733 2022/10/26 09:28:34 - mmengine - INFO - Epoch(train) [1183][30/63] lr: 7.6819e-05 eta: 0:12:06 time: 0.5307 data_time: 0.0264 memory: 16131 loss: 0.8607 loss_prob: 0.4458 loss_thr: 0.3379 loss_db: 0.0769 2022/10/26 09:28:37 - mmengine - INFO - Epoch(train) [1183][35/63] lr: 7.6819e-05 eta: 0:12:06 time: 0.5109 data_time: 0.0262 memory: 16131 loss: 0.7951 loss_prob: 0.4105 loss_thr: 0.3113 loss_db: 0.0733 2022/10/26 09:28:39 - mmengine - INFO - Epoch(train) [1183][40/63] lr: 7.6819e-05 eta: 0:12:00 time: 0.5018 data_time: 0.0185 memory: 16131 loss: 0.8155 loss_prob: 0.4285 loss_thr: 0.3121 loss_db: 0.0749 2022/10/26 09:28:42 - mmengine - INFO - Epoch(train) [1183][45/63] lr: 7.6819e-05 eta: 0:12:00 time: 0.5227 data_time: 0.0060 memory: 16131 loss: 0.8324 loss_prob: 0.4322 loss_thr: 0.3256 loss_db: 0.0746 2022/10/26 09:28:45 - mmengine - INFO - Epoch(train) [1183][50/63] lr: 7.6819e-05 eta: 0:11:53 time: 0.5465 data_time: 0.0143 memory: 16131 loss: 0.8460 loss_prob: 0.4279 loss_thr: 0.3443 loss_db: 0.0738 2022/10/26 09:28:48 - mmengine - INFO - Epoch(train) [1183][55/63] lr: 7.6819e-05 eta: 0:11:53 time: 0.5715 data_time: 0.0178 memory: 16131 loss: 0.8324 loss_prob: 0.4233 loss_thr: 0.3365 loss_db: 0.0726 2022/10/26 09:28:51 - mmengine - INFO - Epoch(train) [1183][60/63] lr: 7.6819e-05 eta: 0:11:47 time: 0.5714 data_time: 0.0147 memory: 16131 loss: 0.7583 loss_prob: 0.3921 loss_thr: 0.2992 loss_db: 0.0670 2022/10/26 09:28:52 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:28:58 - mmengine - INFO - Epoch(train) [1184][5/63] lr: 7.2745e-05 eta: 0:11:47 time: 0.8036 data_time: 0.1658 memory: 16131 loss: 0.8460 loss_prob: 0.4446 loss_thr: 0.3244 loss_db: 0.0769 2022/10/26 09:29:01 - mmengine - INFO - Epoch(train) [1184][10/63] lr: 7.2745e-05 eta: 0:11:38 time: 0.8691 data_time: 0.1847 memory: 16131 loss: 0.8740 loss_prob: 0.4532 loss_thr: 0.3424 loss_db: 0.0785 2022/10/26 09:29:03 - mmengine - INFO - Epoch(train) [1184][15/63] lr: 7.2745e-05 eta: 0:11:38 time: 0.5407 data_time: 0.0251 memory: 16131 loss: 0.8123 loss_prob: 0.4170 loss_thr: 0.3216 loss_db: 0.0737 2022/10/26 09:29:06 - mmengine - INFO - Epoch(train) [1184][20/63] lr: 7.2745e-05 eta: 0:11:31 time: 0.5186 data_time: 0.0071 memory: 16131 loss: 0.8526 loss_prob: 0.4500 loss_thr: 0.3229 loss_db: 0.0798 2022/10/26 09:29:09 - mmengine - INFO - Epoch(train) [1184][25/63] lr: 7.2745e-05 eta: 0:11:31 time: 0.5426 data_time: 0.0123 memory: 16131 loss: 0.8435 loss_prob: 0.4427 loss_thr: 0.3234 loss_db: 0.0774 2022/10/26 09:29:11 - mmengine - INFO - Epoch(train) [1184][30/63] lr: 7.2745e-05 eta: 0:11:25 time: 0.5599 data_time: 0.0163 memory: 16131 loss: 0.8577 loss_prob: 0.4484 loss_thr: 0.3312 loss_db: 0.0781 2022/10/26 09:29:14 - mmengine - INFO - Epoch(train) [1184][35/63] lr: 7.2745e-05 eta: 0:11:25 time: 0.5564 data_time: 0.0295 memory: 16131 loss: 0.9655 loss_prob: 0.5155 loss_thr: 0.3596 loss_db: 0.0904 2022/10/26 09:29:16 - mmengine - INFO - Epoch(train) [1184][40/63] lr: 7.2745e-05 eta: 0:11:18 time: 0.5128 data_time: 0.0237 memory: 16131 loss: 0.8874 loss_prob: 0.4645 loss_thr: 0.3414 loss_db: 0.0815 2022/10/26 09:29:19 - mmengine - INFO - Epoch(train) [1184][45/63] lr: 7.2745e-05 eta: 0:11:18 time: 0.5260 data_time: 0.0059 memory: 16131 loss: 0.7910 loss_prob: 0.4041 loss_thr: 0.3163 loss_db: 0.0706 2022/10/26 09:29:22 - mmengine - INFO - Epoch(train) [1184][50/63] lr: 7.2745e-05 eta: 0:11:12 time: 0.5902 data_time: 0.0243 memory: 16131 loss: 0.7875 loss_prob: 0.4041 loss_thr: 0.3130 loss_db: 0.0704 2022/10/26 09:29:25 - mmengine - INFO - Epoch(train) [1184][55/63] lr: 7.2745e-05 eta: 0:11:12 time: 0.5584 data_time: 0.0299 memory: 16131 loss: 0.7774 loss_prob: 0.4022 loss_thr: 0.3046 loss_db: 0.0706 2022/10/26 09:29:27 - mmengine - INFO - Epoch(train) [1184][60/63] lr: 7.2745e-05 eta: 0:11:05 time: 0.5075 data_time: 0.0137 memory: 16131 loss: 0.8319 loss_prob: 0.4412 loss_thr: 0.3138 loss_db: 0.0769 2022/10/26 09:29:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:29:34 - mmengine - INFO - Epoch(train) [1185][5/63] lr: 6.8646e-05 eta: 0:11:05 time: 0.7224 data_time: 0.1876 memory: 16131 loss: 0.9187 loss_prob: 0.4779 loss_thr: 0.3601 loss_db: 0.0807 2022/10/26 09:29:36 - mmengine - INFO - Epoch(train) [1185][10/63] lr: 6.8646e-05 eta: 0:10:56 time: 0.7499 data_time: 0.1876 memory: 16131 loss: 0.9395 loss_prob: 0.4823 loss_thr: 0.3757 loss_db: 0.0815 2022/10/26 09:29:39 - mmengine - INFO - Epoch(train) [1185][15/63] lr: 6.8646e-05 eta: 0:10:56 time: 0.5700 data_time: 0.0115 memory: 16131 loss: 0.8144 loss_prob: 0.4139 loss_thr: 0.3290 loss_db: 0.0714 2022/10/26 09:29:42 - mmengine - INFO - Epoch(train) [1185][20/63] lr: 6.8646e-05 eta: 0:10:50 time: 0.5963 data_time: 0.0107 memory: 16131 loss: 0.8984 loss_prob: 0.4726 loss_thr: 0.3469 loss_db: 0.0788 2022/10/26 09:29:45 - mmengine - INFO - Epoch(train) [1185][25/63] lr: 6.8646e-05 eta: 0:10:50 time: 0.5867 data_time: 0.0315 memory: 16131 loss: 1.0118 loss_prob: 0.5466 loss_thr: 0.3744 loss_db: 0.0908 2022/10/26 09:29:48 - mmengine - INFO - Epoch(train) [1185][30/63] lr: 6.8646e-05 eta: 0:10:43 time: 0.5622 data_time: 0.0419 memory: 16131 loss: 0.8783 loss_prob: 0.4672 loss_thr: 0.3304 loss_db: 0.0807 2022/10/26 09:29:51 - mmengine - INFO - Epoch(train) [1185][35/63] lr: 6.8646e-05 eta: 0:10:43 time: 0.5442 data_time: 0.0163 memory: 16131 loss: 0.8134 loss_prob: 0.4269 loss_thr: 0.3121 loss_db: 0.0744 2022/10/26 09:29:53 - mmengine - INFO - Epoch(train) [1185][40/63] lr: 6.8646e-05 eta: 0:10:37 time: 0.5404 data_time: 0.0058 memory: 16131 loss: 0.8147 loss_prob: 0.4260 loss_thr: 0.3139 loss_db: 0.0748 2022/10/26 09:29:56 - mmengine - INFO - Epoch(train) [1185][45/63] lr: 6.8646e-05 eta: 0:10:37 time: 0.5465 data_time: 0.0103 memory: 16131 loss: 0.8227 loss_prob: 0.4342 loss_thr: 0.3138 loss_db: 0.0746 2022/10/26 09:29:59 - mmengine - INFO - Epoch(train) [1185][50/63] lr: 6.8646e-05 eta: 0:10:30 time: 0.5708 data_time: 0.0248 memory: 16131 loss: 0.8437 loss_prob: 0.4458 loss_thr: 0.3216 loss_db: 0.0764 2022/10/26 09:30:02 - mmengine - INFO - Epoch(train) [1185][55/63] lr: 6.8646e-05 eta: 0:10:30 time: 0.6020 data_time: 0.0219 memory: 16131 loss: 0.8978 loss_prob: 0.4756 loss_thr: 0.3391 loss_db: 0.0831 2022/10/26 09:30:05 - mmengine - INFO - Epoch(train) [1185][60/63] lr: 6.8646e-05 eta: 0:10:23 time: 0.5587 data_time: 0.0074 memory: 16131 loss: 0.9118 loss_prob: 0.4895 loss_thr: 0.3389 loss_db: 0.0835 2022/10/26 09:30:06 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:30:11 - mmengine - INFO - Epoch(train) [1186][5/63] lr: 6.4519e-05 eta: 0:10:23 time: 0.6912 data_time: 0.1996 memory: 16131 loss: 0.8447 loss_prob: 0.4324 loss_thr: 0.3367 loss_db: 0.0756 2022/10/26 09:30:14 - mmengine - INFO - Epoch(train) [1186][10/63] lr: 6.4519e-05 eta: 0:10:15 time: 0.7653 data_time: 0.2031 memory: 16131 loss: 0.8505 loss_prob: 0.4380 loss_thr: 0.3358 loss_db: 0.0768 2022/10/26 09:30:16 - mmengine - INFO - Epoch(train) [1186][15/63] lr: 6.4519e-05 eta: 0:10:15 time: 0.5534 data_time: 0.0086 memory: 16131 loss: 0.8382 loss_prob: 0.4285 loss_thr: 0.3354 loss_db: 0.0744 2022/10/26 09:30:19 - mmengine - INFO - Epoch(train) [1186][20/63] lr: 6.4519e-05 eta: 0:10:08 time: 0.5106 data_time: 0.0060 memory: 16131 loss: 0.8827 loss_prob: 0.4613 loss_thr: 0.3433 loss_db: 0.0781 2022/10/26 09:30:21 - mmengine - INFO - Epoch(train) [1186][25/63] lr: 6.4519e-05 eta: 0:10:08 time: 0.5266 data_time: 0.0088 memory: 16131 loss: 0.8933 loss_prob: 0.4753 loss_thr: 0.3358 loss_db: 0.0822 2022/10/26 09:30:24 - mmengine - INFO - Epoch(train) [1186][30/63] lr: 6.4519e-05 eta: 0:10:02 time: 0.5567 data_time: 0.0412 memory: 16131 loss: 0.8359 loss_prob: 0.4375 loss_thr: 0.3201 loss_db: 0.0782 2022/10/26 09:30:27 - mmengine - INFO - Epoch(train) [1186][35/63] lr: 6.4519e-05 eta: 0:10:02 time: 0.5692 data_time: 0.0443 memory: 16131 loss: 0.8480 loss_prob: 0.4470 loss_thr: 0.3225 loss_db: 0.0784 2022/10/26 09:30:30 - mmengine - INFO - Epoch(train) [1186][40/63] lr: 6.4519e-05 eta: 0:09:55 time: 0.5643 data_time: 0.0126 memory: 16131 loss: 0.8558 loss_prob: 0.4472 loss_thr: 0.3304 loss_db: 0.0782 2022/10/26 09:30:33 - mmengine - INFO - Epoch(train) [1186][45/63] lr: 6.4519e-05 eta: 0:09:55 time: 0.5584 data_time: 0.0089 memory: 16131 loss: 0.8386 loss_prob: 0.4385 loss_thr: 0.3222 loss_db: 0.0779 2022/10/26 09:30:35 - mmengine - INFO - Epoch(train) [1186][50/63] lr: 6.4519e-05 eta: 0:09:48 time: 0.5247 data_time: 0.0143 memory: 16131 loss: 0.7926 loss_prob: 0.4077 loss_thr: 0.3120 loss_db: 0.0729 2022/10/26 09:30:38 - mmengine - INFO - Epoch(train) [1186][55/63] lr: 6.4519e-05 eta: 0:09:48 time: 0.5263 data_time: 0.0248 memory: 16131 loss: 0.8156 loss_prob: 0.4177 loss_thr: 0.3246 loss_db: 0.0733 2022/10/26 09:30:41 - mmengine - INFO - Epoch(train) [1186][60/63] lr: 6.4519e-05 eta: 0:09:42 time: 0.5417 data_time: 0.0176 memory: 16131 loss: 0.8158 loss_prob: 0.4179 loss_thr: 0.3253 loss_db: 0.0727 2022/10/26 09:30:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:30:47 - mmengine - INFO - Epoch(train) [1187][5/63] lr: 6.0362e-05 eta: 0:09:42 time: 0.7659 data_time: 0.1907 memory: 16131 loss: 0.7795 loss_prob: 0.3978 loss_thr: 0.3117 loss_db: 0.0700 2022/10/26 09:30:50 - mmengine - INFO - Epoch(train) [1187][10/63] lr: 6.0362e-05 eta: 0:09:33 time: 0.7449 data_time: 0.1907 memory: 16131 loss: 0.8249 loss_prob: 0.4328 loss_thr: 0.3173 loss_db: 0.0748 2022/10/26 09:30:53 - mmengine - INFO - Epoch(train) [1187][15/63] lr: 6.0362e-05 eta: 0:09:33 time: 0.5476 data_time: 0.0054 memory: 16131 loss: 0.8325 loss_prob: 0.4360 loss_thr: 0.3216 loss_db: 0.0749 2022/10/26 09:30:55 - mmengine - INFO - Epoch(train) [1187][20/63] lr: 6.0362e-05 eta: 0:09:27 time: 0.5521 data_time: 0.0058 memory: 16131 loss: 0.8293 loss_prob: 0.4293 loss_thr: 0.3250 loss_db: 0.0750 2022/10/26 09:30:58 - mmengine - INFO - Epoch(train) [1187][25/63] lr: 6.0362e-05 eta: 0:09:27 time: 0.5273 data_time: 0.0270 memory: 16131 loss: 0.7905 loss_prob: 0.4108 loss_thr: 0.3066 loss_db: 0.0731 2022/10/26 09:31:01 - mmengine - INFO - Epoch(train) [1187][30/63] lr: 6.0362e-05 eta: 0:09:20 time: 0.5767 data_time: 0.0397 memory: 16131 loss: 0.7345 loss_prob: 0.3789 loss_thr: 0.2877 loss_db: 0.0679 2022/10/26 09:31:04 - mmengine - INFO - Epoch(train) [1187][35/63] lr: 6.0362e-05 eta: 0:09:20 time: 0.6010 data_time: 0.0201 memory: 16131 loss: 0.7753 loss_prob: 0.4007 loss_thr: 0.3032 loss_db: 0.0714 2022/10/26 09:31:06 - mmengine - INFO - Epoch(train) [1187][40/63] lr: 6.0362e-05 eta: 0:09:14 time: 0.5412 data_time: 0.0077 memory: 16131 loss: 0.8447 loss_prob: 0.4401 loss_thr: 0.3273 loss_db: 0.0773 2022/10/26 09:31:09 - mmengine - INFO - Epoch(train) [1187][45/63] lr: 6.0362e-05 eta: 0:09:14 time: 0.5006 data_time: 0.0086 memory: 16131 loss: 0.8327 loss_prob: 0.4348 loss_thr: 0.3227 loss_db: 0.0752 2022/10/26 09:31:12 - mmengine - INFO - Epoch(train) [1187][50/63] lr: 6.0362e-05 eta: 0:09:07 time: 0.5376 data_time: 0.0193 memory: 16131 loss: 0.8287 loss_prob: 0.4349 loss_thr: 0.3194 loss_db: 0.0744 2022/10/26 09:31:14 - mmengine - INFO - Epoch(train) [1187][55/63] lr: 6.0362e-05 eta: 0:09:07 time: 0.5557 data_time: 0.0254 memory: 16131 loss: 0.9806 loss_prob: 0.5351 loss_thr: 0.3577 loss_db: 0.0878 2022/10/26 09:31:17 - mmengine - INFO - Epoch(train) [1187][60/63] lr: 6.0362e-05 eta: 0:09:00 time: 0.5292 data_time: 0.0148 memory: 16131 loss: 0.9165 loss_prob: 0.4949 loss_thr: 0.3390 loss_db: 0.0826 2022/10/26 09:31:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:31:24 - mmengine - INFO - Epoch(train) [1188][5/63] lr: 5.6174e-05 eta: 0:09:00 time: 0.7768 data_time: 0.2020 memory: 16131 loss: 0.8350 loss_prob: 0.4294 loss_thr: 0.3294 loss_db: 0.0762 2022/10/26 09:31:29 - mmengine - INFO - Epoch(train) [1188][10/63] lr: 5.6174e-05 eta: 0:08:52 time: 1.0232 data_time: 0.2047 memory: 16131 loss: 0.8616 loss_prob: 0.4507 loss_thr: 0.3329 loss_db: 0.0780 2022/10/26 09:31:32 - mmengine - INFO - Epoch(train) [1188][15/63] lr: 5.6174e-05 eta: 0:08:52 time: 0.7853 data_time: 0.0112 memory: 16131 loss: 0.8654 loss_prob: 0.4566 loss_thr: 0.3282 loss_db: 0.0807 2022/10/26 09:31:34 - mmengine - INFO - Epoch(train) [1188][20/63] lr: 5.6174e-05 eta: 0:08:45 time: 0.5796 data_time: 0.0088 memory: 16131 loss: 0.9049 loss_prob: 0.4639 loss_thr: 0.3575 loss_db: 0.0835 2022/10/26 09:31:37 - mmengine - INFO - Epoch(train) [1188][25/63] lr: 5.6174e-05 eta: 0:08:45 time: 0.5484 data_time: 0.0099 memory: 16131 loss: 0.8174 loss_prob: 0.4113 loss_thr: 0.3332 loss_db: 0.0730 2022/10/26 09:31:40 - mmengine - INFO - Epoch(train) [1188][30/63] lr: 5.6174e-05 eta: 0:08:39 time: 0.5987 data_time: 0.0316 memory: 16131 loss: 0.8002 loss_prob: 0.4137 loss_thr: 0.3134 loss_db: 0.0731 2022/10/26 09:31:43 - mmengine - INFO - Epoch(train) [1188][35/63] lr: 5.6174e-05 eta: 0:08:39 time: 0.6039 data_time: 0.0268 memory: 16131 loss: 0.8340 loss_prob: 0.4335 loss_thr: 0.3233 loss_db: 0.0772 2022/10/26 09:31:46 - mmengine - INFO - Epoch(train) [1188][40/63] lr: 5.6174e-05 eta: 0:08:32 time: 0.5432 data_time: 0.0081 memory: 16131 loss: 0.8077 loss_prob: 0.4163 loss_thr: 0.3171 loss_db: 0.0744 2022/10/26 09:31:49 - mmengine - INFO - Epoch(train) [1188][45/63] lr: 5.6174e-05 eta: 0:08:32 time: 0.5554 data_time: 0.0086 memory: 16131 loss: 0.8421 loss_prob: 0.4376 loss_thr: 0.3273 loss_db: 0.0771 2022/10/26 09:31:52 - mmengine - INFO - Epoch(train) [1188][50/63] lr: 5.6174e-05 eta: 0:08:25 time: 0.6118 data_time: 0.0241 memory: 16131 loss: 0.8486 loss_prob: 0.4501 loss_thr: 0.3203 loss_db: 0.0782 2022/10/26 09:31:55 - mmengine - INFO - Epoch(train) [1188][55/63] lr: 5.6174e-05 eta: 0:08:25 time: 0.5958 data_time: 0.0242 memory: 16131 loss: 0.8508 loss_prob: 0.4512 loss_thr: 0.3208 loss_db: 0.0788 2022/10/26 09:31:57 - mmengine - INFO - Epoch(train) [1188][60/63] lr: 5.6174e-05 eta: 0:08:19 time: 0.5143 data_time: 0.0076 memory: 16131 loss: 0.8745 loss_prob: 0.4563 loss_thr: 0.3375 loss_db: 0.0807 2022/10/26 09:31:58 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:32:04 - mmengine - INFO - Epoch(train) [1189][5/63] lr: 5.1950e-05 eta: 0:08:19 time: 0.7516 data_time: 0.2241 memory: 16131 loss: 0.8213 loss_prob: 0.4248 loss_thr: 0.3206 loss_db: 0.0759 2022/10/26 09:32:07 - mmengine - INFO - Epoch(train) [1189][10/63] lr: 5.1950e-05 eta: 0:08:10 time: 0.8215 data_time: 0.2218 memory: 16131 loss: 0.7472 loss_prob: 0.3839 loss_thr: 0.2947 loss_db: 0.0685 2022/10/26 09:32:10 - mmengine - INFO - Epoch(train) [1189][15/63] lr: 5.1950e-05 eta: 0:08:10 time: 0.5921 data_time: 0.0096 memory: 16131 loss: 0.8056 loss_prob: 0.4235 loss_thr: 0.3092 loss_db: 0.0729 2022/10/26 09:32:12 - mmengine - INFO - Epoch(train) [1189][20/63] lr: 5.1950e-05 eta: 0:08:04 time: 0.5696 data_time: 0.0119 memory: 16131 loss: 0.9625 loss_prob: 0.5047 loss_thr: 0.3722 loss_db: 0.0856 2022/10/26 09:32:15 - mmengine - INFO - Epoch(train) [1189][25/63] lr: 5.1950e-05 eta: 0:08:04 time: 0.5564 data_time: 0.0275 memory: 16131 loss: 0.8904 loss_prob: 0.4541 loss_thr: 0.3573 loss_db: 0.0790 2022/10/26 09:32:18 - mmengine - INFO - Epoch(train) [1189][30/63] lr: 5.1950e-05 eta: 0:07:57 time: 0.5489 data_time: 0.0320 memory: 16131 loss: 0.8005 loss_prob: 0.4098 loss_thr: 0.3183 loss_db: 0.0724 2022/10/26 09:32:20 - mmengine - INFO - Epoch(train) [1189][35/63] lr: 5.1950e-05 eta: 0:07:57 time: 0.5171 data_time: 0.0166 memory: 16131 loss: 0.8201 loss_prob: 0.4244 loss_thr: 0.3206 loss_db: 0.0751 2022/10/26 09:32:23 - mmengine - INFO - Epoch(train) [1189][40/63] lr: 5.1950e-05 eta: 0:07:51 time: 0.5064 data_time: 0.0127 memory: 16131 loss: 0.8188 loss_prob: 0.4238 loss_thr: 0.3194 loss_db: 0.0757 2022/10/26 09:32:25 - mmengine - INFO - Epoch(train) [1189][45/63] lr: 5.1950e-05 eta: 0:07:51 time: 0.5208 data_time: 0.0082 memory: 16131 loss: 0.8370 loss_prob: 0.4360 loss_thr: 0.3245 loss_db: 0.0766 2022/10/26 09:32:28 - mmengine - INFO - Epoch(train) [1189][50/63] lr: 5.1950e-05 eta: 0:07:44 time: 0.5425 data_time: 0.0255 memory: 16131 loss: 0.8950 loss_prob: 0.4721 loss_thr: 0.3424 loss_db: 0.0804 2022/10/26 09:32:31 - mmengine - INFO - Epoch(train) [1189][55/63] lr: 5.1950e-05 eta: 0:07:44 time: 0.5331 data_time: 0.0253 memory: 16131 loss: 0.8998 loss_prob: 0.4733 loss_thr: 0.3447 loss_db: 0.0817 2022/10/26 09:32:33 - mmengine - INFO - Epoch(train) [1189][60/63] lr: 5.1950e-05 eta: 0:07:37 time: 0.5073 data_time: 0.0074 memory: 16131 loss: 0.8226 loss_prob: 0.4272 loss_thr: 0.3185 loss_db: 0.0769 2022/10/26 09:32:35 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:32:39 - mmengine - INFO - Epoch(train) [1190][5/63] lr: 4.7688e-05 eta: 0:07:37 time: 0.7059 data_time: 0.1695 memory: 16131 loss: 0.7549 loss_prob: 0.3768 loss_thr: 0.3110 loss_db: 0.0671 2022/10/26 09:32:42 - mmengine - INFO - Epoch(train) [1190][10/63] lr: 4.7688e-05 eta: 0:07:29 time: 0.7222 data_time: 0.1832 memory: 16131 loss: 0.8200 loss_prob: 0.4232 loss_thr: 0.3225 loss_db: 0.0743 2022/10/26 09:32:45 - mmengine - INFO - Epoch(train) [1190][15/63] lr: 4.7688e-05 eta: 0:07:29 time: 0.5347 data_time: 0.0225 memory: 16131 loss: 0.8591 loss_prob: 0.4497 loss_thr: 0.3309 loss_db: 0.0785 2022/10/26 09:32:48 - mmengine - INFO - Epoch(train) [1190][20/63] lr: 4.7688e-05 eta: 0:07:22 time: 0.5905 data_time: 0.0088 memory: 16131 loss: 0.8389 loss_prob: 0.4289 loss_thr: 0.3350 loss_db: 0.0750 2022/10/26 09:32:51 - mmengine - INFO - Epoch(train) [1190][25/63] lr: 4.7688e-05 eta: 0:07:22 time: 0.6089 data_time: 0.0203 memory: 16131 loss: 0.7698 loss_prob: 0.3885 loss_thr: 0.3129 loss_db: 0.0683 2022/10/26 09:32:53 - mmengine - INFO - Epoch(train) [1190][30/63] lr: 4.7688e-05 eta: 0:07:16 time: 0.5566 data_time: 0.0199 memory: 16131 loss: 0.7435 loss_prob: 0.3744 loss_thr: 0.3028 loss_db: 0.0663 2022/10/26 09:32:57 - mmengine - INFO - Epoch(train) [1190][35/63] lr: 4.7688e-05 eta: 0:07:16 time: 0.5829 data_time: 0.0344 memory: 16131 loss: 0.8093 loss_prob: 0.4155 loss_thr: 0.3204 loss_db: 0.0733 2022/10/26 09:32:59 - mmengine - INFO - Epoch(train) [1190][40/63] lr: 4.7688e-05 eta: 0:07:09 time: 0.6091 data_time: 0.0351 memory: 16131 loss: 0.8888 loss_prob: 0.4634 loss_thr: 0.3439 loss_db: 0.0815 2022/10/26 09:33:02 - mmengine - INFO - Epoch(train) [1190][45/63] lr: 4.7688e-05 eta: 0:07:09 time: 0.5684 data_time: 0.0094 memory: 16131 loss: 0.9210 loss_prob: 0.4881 loss_thr: 0.3485 loss_db: 0.0845 2022/10/26 09:33:05 - mmengine - INFO - Epoch(train) [1190][50/63] lr: 4.7688e-05 eta: 0:07:02 time: 0.5825 data_time: 0.0199 memory: 16131 loss: 0.8732 loss_prob: 0.4617 loss_thr: 0.3323 loss_db: 0.0792 2022/10/26 09:33:08 - mmengine - INFO - Epoch(train) [1190][55/63] lr: 4.7688e-05 eta: 0:07:02 time: 0.5542 data_time: 0.0213 memory: 16131 loss: 0.9042 loss_prob: 0.4712 loss_thr: 0.3503 loss_db: 0.0826 2022/10/26 09:33:10 - mmengine - INFO - Epoch(train) [1190][60/63] lr: 4.7688e-05 eta: 0:06:56 time: 0.5079 data_time: 0.0158 memory: 16131 loss: 0.9198 loss_prob: 0.4838 loss_thr: 0.3501 loss_db: 0.0859 2022/10/26 09:33:12 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:33:16 - mmengine - INFO - Epoch(train) [1191][5/63] lr: 4.3383e-05 eta: 0:06:56 time: 0.6897 data_time: 0.1844 memory: 16131 loss: 0.9018 loss_prob: 0.4758 loss_thr: 0.3430 loss_db: 0.0830 2022/10/26 09:33:19 - mmengine - INFO - Epoch(train) [1191][10/63] lr: 4.3383e-05 eta: 0:06:47 time: 0.7415 data_time: 0.1966 memory: 16131 loss: 0.8452 loss_prob: 0.4482 loss_thr: 0.3192 loss_db: 0.0778 2022/10/26 09:33:22 - mmengine - INFO - Epoch(train) [1191][15/63] lr: 4.3383e-05 eta: 0:06:47 time: 0.5893 data_time: 0.0256 memory: 16131 loss: 0.8479 loss_prob: 0.4425 loss_thr: 0.3283 loss_db: 0.0770 2022/10/26 09:33:25 - mmengine - INFO - Epoch(train) [1191][20/63] lr: 4.3383e-05 eta: 0:06:41 time: 0.5899 data_time: 0.0109 memory: 16131 loss: 0.8796 loss_prob: 0.4571 loss_thr: 0.3442 loss_db: 0.0783 2022/10/26 09:33:27 - mmengine - INFO - Epoch(train) [1191][25/63] lr: 4.3383e-05 eta: 0:06:41 time: 0.5326 data_time: 0.0078 memory: 16131 loss: 0.8246 loss_prob: 0.4256 loss_thr: 0.3256 loss_db: 0.0733 2022/10/26 09:33:30 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:33:30 - mmengine - INFO - Epoch(train) [1191][30/63] lr: 4.3383e-05 eta: 0:06:34 time: 0.5129 data_time: 0.0291 memory: 16131 loss: 0.8516 loss_prob: 0.4374 loss_thr: 0.3388 loss_db: 0.0754 2022/10/26 09:33:33 - mmengine - INFO - Epoch(train) [1191][35/63] lr: 4.3383e-05 eta: 0:06:34 time: 0.5323 data_time: 0.0348 memory: 16131 loss: 0.9244 loss_prob: 0.4813 loss_thr: 0.3597 loss_db: 0.0833 2022/10/26 09:33:35 - mmengine - INFO - Epoch(train) [1191][40/63] lr: 4.3383e-05 eta: 0:06:28 time: 0.5196 data_time: 0.0202 memory: 16131 loss: 0.9175 loss_prob: 0.4814 loss_thr: 0.3513 loss_db: 0.0848 2022/10/26 09:33:38 - mmengine - INFO - Epoch(train) [1191][45/63] lr: 4.3383e-05 eta: 0:06:28 time: 0.5114 data_time: 0.0143 memory: 16131 loss: 0.8578 loss_prob: 0.4528 loss_thr: 0.3250 loss_db: 0.0800 2022/10/26 09:33:41 - mmengine - INFO - Epoch(train) [1191][50/63] lr: 4.3383e-05 eta: 0:06:21 time: 0.5200 data_time: 0.0158 memory: 16131 loss: 0.8261 loss_prob: 0.4334 loss_thr: 0.3162 loss_db: 0.0764 2022/10/26 09:33:43 - mmengine - INFO - Epoch(train) [1191][55/63] lr: 4.3383e-05 eta: 0:06:21 time: 0.5447 data_time: 0.0241 memory: 16131 loss: 0.8468 loss_prob: 0.4400 loss_thr: 0.3296 loss_db: 0.0772 2022/10/26 09:33:46 - mmengine - INFO - Epoch(train) [1191][60/63] lr: 4.3383e-05 eta: 0:06:14 time: 0.5892 data_time: 0.0180 memory: 16131 loss: 0.8681 loss_prob: 0.4544 loss_thr: 0.3337 loss_db: 0.0799 2022/10/26 09:33:48 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:33:53 - mmengine - INFO - Epoch(train) [1192][5/63] lr: 3.9030e-05 eta: 0:06:14 time: 0.7711 data_time: 0.1946 memory: 16131 loss: 0.8370 loss_prob: 0.4294 loss_thr: 0.3324 loss_db: 0.0752 2022/10/26 09:33:56 - mmengine - INFO - Epoch(train) [1192][10/63] lr: 3.9030e-05 eta: 0:06:06 time: 0.8018 data_time: 0.1894 memory: 16131 loss: 0.8636 loss_prob: 0.4434 loss_thr: 0.3419 loss_db: 0.0784 2022/10/26 09:33:58 - mmengine - INFO - Epoch(train) [1192][15/63] lr: 3.9030e-05 eta: 0:06:06 time: 0.5359 data_time: 0.0068 memory: 16131 loss: 0.8582 loss_prob: 0.4429 loss_thr: 0.3365 loss_db: 0.0787 2022/10/26 09:34:02 - mmengine - INFO - Epoch(train) [1192][20/63] lr: 3.9030e-05 eta: 0:05:59 time: 0.5801 data_time: 0.0078 memory: 16131 loss: 0.8527 loss_prob: 0.4393 loss_thr: 0.3351 loss_db: 0.0783 2022/10/26 09:34:05 - mmengine - INFO - Epoch(train) [1192][25/63] lr: 3.9030e-05 eta: 0:05:59 time: 0.6283 data_time: 0.0270 memory: 16131 loss: 0.8790 loss_prob: 0.4637 loss_thr: 0.3343 loss_db: 0.0810 2022/10/26 09:34:08 - mmengine - INFO - Epoch(train) [1192][30/63] lr: 3.9030e-05 eta: 0:05:53 time: 0.6500 data_time: 0.0445 memory: 16131 loss: 0.8904 loss_prob: 0.4730 loss_thr: 0.3364 loss_db: 0.0810 2022/10/26 09:34:11 - mmengine - INFO - Epoch(train) [1192][35/63] lr: 3.9030e-05 eta: 0:05:53 time: 0.6305 data_time: 0.0240 memory: 16131 loss: 0.7994 loss_prob: 0.4150 loss_thr: 0.3121 loss_db: 0.0723 2022/10/26 09:34:14 - mmengine - INFO - Epoch(train) [1192][40/63] lr: 3.9030e-05 eta: 0:05:46 time: 0.6278 data_time: 0.0088 memory: 16131 loss: 0.7925 loss_prob: 0.4039 loss_thr: 0.3179 loss_db: 0.0707 2022/10/26 09:34:17 - mmengine - INFO - Epoch(train) [1192][45/63] lr: 3.9030e-05 eta: 0:05:46 time: 0.5719 data_time: 0.0089 memory: 16131 loss: 0.8749 loss_prob: 0.4540 loss_thr: 0.3404 loss_db: 0.0804 2022/10/26 09:34:20 - mmengine - INFO - Epoch(train) [1192][50/63] lr: 3.9030e-05 eta: 0:05:39 time: 0.5642 data_time: 0.0166 memory: 16131 loss: 0.8933 loss_prob: 0.4698 loss_thr: 0.3399 loss_db: 0.0836 2022/10/26 09:34:24 - mmengine - INFO - Epoch(train) [1192][55/63] lr: 3.9030e-05 eta: 0:05:39 time: 0.6796 data_time: 0.0239 memory: 16131 loss: 0.8923 loss_prob: 0.4749 loss_thr: 0.3361 loss_db: 0.0813 2022/10/26 09:34:27 - mmengine - INFO - Epoch(train) [1192][60/63] lr: 3.9030e-05 eta: 0:05:33 time: 0.6618 data_time: 0.0140 memory: 16131 loss: 0.8532 loss_prob: 0.4574 loss_thr: 0.3175 loss_db: 0.0783 2022/10/26 09:34:28 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:34:32 - mmengine - INFO - Epoch(train) [1193][5/63] lr: 3.4621e-05 eta: 0:05:33 time: 0.6763 data_time: 0.1717 memory: 16131 loss: 0.9344 loss_prob: 0.4934 loss_thr: 0.3553 loss_db: 0.0856 2022/10/26 09:34:35 - mmengine - INFO - Epoch(train) [1193][10/63] lr: 3.4621e-05 eta: 0:05:24 time: 0.7075 data_time: 0.1806 memory: 16131 loss: 0.8325 loss_prob: 0.4325 loss_thr: 0.3253 loss_db: 0.0748 2022/10/26 09:34:38 - mmengine - INFO - Epoch(train) [1193][15/63] lr: 3.4621e-05 eta: 0:05:24 time: 0.5440 data_time: 0.0170 memory: 16131 loss: 0.8464 loss_prob: 0.4424 loss_thr: 0.3272 loss_db: 0.0768 2022/10/26 09:34:40 - mmengine - INFO - Epoch(train) [1193][20/63] lr: 3.4621e-05 eta: 0:05:18 time: 0.5377 data_time: 0.0069 memory: 16131 loss: 0.8522 loss_prob: 0.4444 loss_thr: 0.3301 loss_db: 0.0777 2022/10/26 09:34:43 - mmengine - INFO - Epoch(train) [1193][25/63] lr: 3.4621e-05 eta: 0:05:18 time: 0.5505 data_time: 0.0202 memory: 16131 loss: 0.8236 loss_prob: 0.4340 loss_thr: 0.3158 loss_db: 0.0738 2022/10/26 09:34:46 - mmengine - INFO - Epoch(train) [1193][30/63] lr: 3.4621e-05 eta: 0:05:11 time: 0.5710 data_time: 0.0363 memory: 16131 loss: 0.8790 loss_prob: 0.4664 loss_thr: 0.3318 loss_db: 0.0808 2022/10/26 09:34:49 - mmengine - INFO - Epoch(train) [1193][35/63] lr: 3.4621e-05 eta: 0:05:11 time: 0.5506 data_time: 0.0278 memory: 16131 loss: 0.8475 loss_prob: 0.4419 loss_thr: 0.3253 loss_db: 0.0804 2022/10/26 09:34:52 - mmengine - INFO - Epoch(train) [1193][40/63] lr: 3.4621e-05 eta: 0:05:05 time: 0.5889 data_time: 0.0107 memory: 16131 loss: 0.7748 loss_prob: 0.3961 loss_thr: 0.3075 loss_db: 0.0712 2022/10/26 09:34:55 - mmengine - INFO - Epoch(train) [1193][45/63] lr: 3.4621e-05 eta: 0:05:05 time: 0.6629 data_time: 0.0072 memory: 16131 loss: 0.8043 loss_prob: 0.4072 loss_thr: 0.3257 loss_db: 0.0714 2022/10/26 09:34:58 - mmengine - INFO - Epoch(train) [1193][50/63] lr: 3.4621e-05 eta: 0:04:58 time: 0.6359 data_time: 0.0135 memory: 16131 loss: 0.8425 loss_prob: 0.4338 loss_thr: 0.3334 loss_db: 0.0752 2022/10/26 09:35:01 - mmengine - INFO - Epoch(train) [1193][55/63] lr: 3.4621e-05 eta: 0:04:58 time: 0.5833 data_time: 0.0223 memory: 16131 loss: 0.8047 loss_prob: 0.4216 loss_thr: 0.3104 loss_db: 0.0726 2022/10/26 09:35:04 - mmengine - INFO - Epoch(train) [1193][60/63] lr: 3.4621e-05 eta: 0:04:51 time: 0.5409 data_time: 0.0166 memory: 16131 loss: 0.7989 loss_prob: 0.4127 loss_thr: 0.3143 loss_db: 0.0719 2022/10/26 09:35:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:35:10 - mmengine - INFO - Epoch(train) [1194][5/63] lr: 3.0149e-05 eta: 0:04:51 time: 0.7084 data_time: 0.2114 memory: 16131 loss: 0.8139 loss_prob: 0.4216 loss_thr: 0.3198 loss_db: 0.0725 2022/10/26 09:35:13 - mmengine - INFO - Epoch(train) [1194][10/63] lr: 3.0149e-05 eta: 0:04:43 time: 0.7680 data_time: 0.2158 memory: 16131 loss: 0.8005 loss_prob: 0.4164 loss_thr: 0.3132 loss_db: 0.0709 2022/10/26 09:35:16 - mmengine - INFO - Epoch(train) [1194][15/63] lr: 3.0149e-05 eta: 0:04:43 time: 0.6088 data_time: 0.0097 memory: 16131 loss: 0.8448 loss_prob: 0.4457 loss_thr: 0.3219 loss_db: 0.0772 2022/10/26 09:35:19 - mmengine - INFO - Epoch(train) [1194][20/63] lr: 3.0149e-05 eta: 0:04:36 time: 0.5962 data_time: 0.0067 memory: 16131 loss: 0.8251 loss_prob: 0.4325 loss_thr: 0.3164 loss_db: 0.0762 2022/10/26 09:35:21 - mmengine - INFO - Epoch(train) [1194][25/63] lr: 3.0149e-05 eta: 0:04:36 time: 0.5195 data_time: 0.0141 memory: 16131 loss: 0.8586 loss_prob: 0.4637 loss_thr: 0.3140 loss_db: 0.0809 2022/10/26 09:35:24 - mmengine - INFO - Epoch(train) [1194][30/63] lr: 3.0149e-05 eta: 0:04:30 time: 0.5321 data_time: 0.0369 memory: 16131 loss: 0.9826 loss_prob: 0.5415 loss_thr: 0.3482 loss_db: 0.0930 2022/10/26 09:35:27 - mmengine - INFO - Epoch(train) [1194][35/63] lr: 3.0149e-05 eta: 0:04:30 time: 0.5701 data_time: 0.0299 memory: 16131 loss: 0.9029 loss_prob: 0.4796 loss_thr: 0.3406 loss_db: 0.0827 2022/10/26 09:35:29 - mmengine - INFO - Epoch(train) [1194][40/63] lr: 3.0149e-05 eta: 0:04:23 time: 0.5483 data_time: 0.0062 memory: 16131 loss: 0.8246 loss_prob: 0.4276 loss_thr: 0.3218 loss_db: 0.0752 2022/10/26 09:35:32 - mmengine - INFO - Epoch(train) [1194][45/63] lr: 3.0149e-05 eta: 0:04:23 time: 0.5147 data_time: 0.0063 memory: 16131 loss: 0.8028 loss_prob: 0.4142 loss_thr: 0.3162 loss_db: 0.0724 2022/10/26 09:35:35 - mmengine - INFO - Epoch(train) [1194][50/63] lr: 3.0149e-05 eta: 0:04:17 time: 0.5299 data_time: 0.0226 memory: 16131 loss: 0.8193 loss_prob: 0.4200 loss_thr: 0.3264 loss_db: 0.0730 2022/10/26 09:35:37 - mmengine - INFO - Epoch(train) [1194][55/63] lr: 3.0149e-05 eta: 0:04:17 time: 0.5278 data_time: 0.0292 memory: 16131 loss: 0.9341 loss_prob: 0.4876 loss_thr: 0.3623 loss_db: 0.0842 2022/10/26 09:35:41 - mmengine - INFO - Epoch(train) [1194][60/63] lr: 3.0149e-05 eta: 0:04:10 time: 0.5865 data_time: 0.0141 memory: 16131 loss: 0.8950 loss_prob: 0.4734 loss_thr: 0.3401 loss_db: 0.0815 2022/10/26 09:35:42 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:35:46 - mmengine - INFO - Epoch(train) [1195][5/63] lr: 2.5602e-05 eta: 0:04:10 time: 0.7011 data_time: 0.2136 memory: 16131 loss: 0.8095 loss_prob: 0.4156 loss_thr: 0.3213 loss_db: 0.0726 2022/10/26 09:35:50 - mmengine - INFO - Epoch(train) [1195][10/63] lr: 2.5602e-05 eta: 0:04:01 time: 0.7876 data_time: 0.2125 memory: 16131 loss: 0.9043 loss_prob: 0.4695 loss_thr: 0.3525 loss_db: 0.0823 2022/10/26 09:35:53 - mmengine - INFO - Epoch(train) [1195][15/63] lr: 2.5602e-05 eta: 0:04:01 time: 0.6357 data_time: 0.0067 memory: 16131 loss: 0.9102 loss_prob: 0.4733 loss_thr: 0.3534 loss_db: 0.0835 2022/10/26 09:35:55 - mmengine - INFO - Epoch(train) [1195][20/63] lr: 2.5602e-05 eta: 0:03:55 time: 0.5730 data_time: 0.0098 memory: 16131 loss: 0.8395 loss_prob: 0.4329 loss_thr: 0.3303 loss_db: 0.0763 2022/10/26 09:35:58 - mmengine - INFO - Epoch(train) [1195][25/63] lr: 2.5602e-05 eta: 0:03:55 time: 0.5075 data_time: 0.0166 memory: 16131 loss: 0.7772 loss_prob: 0.4033 loss_thr: 0.3029 loss_db: 0.0710 2022/10/26 09:36:01 - mmengine - INFO - Epoch(train) [1195][30/63] lr: 2.5602e-05 eta: 0:03:48 time: 0.5220 data_time: 0.0371 memory: 16131 loss: 0.7606 loss_prob: 0.3968 loss_thr: 0.2945 loss_db: 0.0692 2022/10/26 09:36:03 - mmengine - INFO - Epoch(train) [1195][35/63] lr: 2.5602e-05 eta: 0:03:48 time: 0.5528 data_time: 0.0293 memory: 16131 loss: 0.7609 loss_prob: 0.3939 loss_thr: 0.2984 loss_db: 0.0686 2022/10/26 09:36:06 - mmengine - INFO - Epoch(train) [1195][40/63] lr: 2.5602e-05 eta: 0:03:42 time: 0.5531 data_time: 0.0093 memory: 16131 loss: 0.7922 loss_prob: 0.4115 loss_thr: 0.3087 loss_db: 0.0720 2022/10/26 09:36:09 - mmengine - INFO - Epoch(train) [1195][45/63] lr: 2.5602e-05 eta: 0:03:42 time: 0.5229 data_time: 0.0105 memory: 16131 loss: 0.8332 loss_prob: 0.4402 loss_thr: 0.3186 loss_db: 0.0743 2022/10/26 09:36:11 - mmengine - INFO - Epoch(train) [1195][50/63] lr: 2.5602e-05 eta: 0:03:35 time: 0.5245 data_time: 0.0227 memory: 16131 loss: 0.8444 loss_prob: 0.4409 loss_thr: 0.3273 loss_db: 0.0762 2022/10/26 09:36:14 - mmengine - INFO - Epoch(train) [1195][55/63] lr: 2.5602e-05 eta: 0:03:35 time: 0.5279 data_time: 0.0238 memory: 16131 loss: 0.8625 loss_prob: 0.4450 loss_thr: 0.3383 loss_db: 0.0791 2022/10/26 09:36:17 - mmengine - INFO - Epoch(train) [1195][60/63] lr: 2.5602e-05 eta: 0:03:29 time: 0.5247 data_time: 0.0078 memory: 16131 loss: 0.9125 loss_prob: 0.4803 loss_thr: 0.3486 loss_db: 0.0836 2022/10/26 09:36:18 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:36:22 - mmengine - INFO - Epoch(train) [1196][5/63] lr: 2.0962e-05 eta: 0:03:29 time: 0.6670 data_time: 0.1839 memory: 16131 loss: 0.9139 loss_prob: 0.4828 loss_thr: 0.3461 loss_db: 0.0850 2022/10/26 09:36:25 - mmengine - INFO - Epoch(train) [1196][10/63] lr: 2.0962e-05 eta: 0:03:20 time: 0.6972 data_time: 0.1840 memory: 16131 loss: 0.8360 loss_prob: 0.4319 loss_thr: 0.3275 loss_db: 0.0767 2022/10/26 09:36:28 - mmengine - INFO - Epoch(train) [1196][15/63] lr: 2.0962e-05 eta: 0:03:20 time: 0.5331 data_time: 0.0116 memory: 16131 loss: 0.8193 loss_prob: 0.4234 loss_thr: 0.3230 loss_db: 0.0729 2022/10/26 09:36:30 - mmengine - INFO - Epoch(train) [1196][20/63] lr: 2.0962e-05 eta: 0:03:13 time: 0.5357 data_time: 0.0112 memory: 16131 loss: 0.8143 loss_prob: 0.4217 loss_thr: 0.3200 loss_db: 0.0726 2022/10/26 09:36:33 - mmengine - INFO - Epoch(train) [1196][25/63] lr: 2.0962e-05 eta: 0:03:13 time: 0.5614 data_time: 0.0202 memory: 16131 loss: 0.8152 loss_prob: 0.4283 loss_thr: 0.3101 loss_db: 0.0768 2022/10/26 09:36:36 - mmengine - INFO - Epoch(train) [1196][30/63] lr: 2.0962e-05 eta: 0:03:07 time: 0.5968 data_time: 0.0301 memory: 16131 loss: 0.8079 loss_prob: 0.4273 loss_thr: 0.3048 loss_db: 0.0758 2022/10/26 09:36:40 - mmengine - INFO - Epoch(train) [1196][35/63] lr: 2.0962e-05 eta: 0:03:07 time: 0.6332 data_time: 0.0216 memory: 16131 loss: 0.7992 loss_prob: 0.4166 loss_thr: 0.3105 loss_db: 0.0720 2022/10/26 09:36:43 - mmengine - INFO - Epoch(train) [1196][40/63] lr: 2.0962e-05 eta: 0:03:00 time: 0.6736 data_time: 0.0120 memory: 16131 loss: 0.8212 loss_prob: 0.4368 loss_thr: 0.3106 loss_db: 0.0738 2022/10/26 09:36:45 - mmengine - INFO - Epoch(train) [1196][45/63] lr: 2.0962e-05 eta: 0:03:00 time: 0.5804 data_time: 0.0055 memory: 16131 loss: 0.8718 loss_prob: 0.4622 loss_thr: 0.3326 loss_db: 0.0770 2022/10/26 09:36:48 - mmengine - INFO - Epoch(train) [1196][50/63] lr: 2.0962e-05 eta: 0:02:54 time: 0.5371 data_time: 0.0235 memory: 16131 loss: 0.8263 loss_prob: 0.4218 loss_thr: 0.3318 loss_db: 0.0728 2022/10/26 09:36:51 - mmengine - INFO - Epoch(train) [1196][55/63] lr: 2.0962e-05 eta: 0:02:54 time: 0.5847 data_time: 0.0320 memory: 16131 loss: 0.8296 loss_prob: 0.4250 loss_thr: 0.3301 loss_db: 0.0745 2022/10/26 09:36:54 - mmengine - INFO - Epoch(train) [1196][60/63] lr: 2.0962e-05 eta: 0:02:47 time: 0.5431 data_time: 0.0180 memory: 16131 loss: 0.8786 loss_prob: 0.4564 loss_thr: 0.3430 loss_db: 0.0792 2022/10/26 09:36:55 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:37:00 - mmengine - INFO - Epoch(train) [1197][5/63] lr: 1.6203e-05 eta: 0:02:47 time: 0.7028 data_time: 0.1805 memory: 16131 loss: 0.7980 loss_prob: 0.4105 loss_thr: 0.3158 loss_db: 0.0717 2022/10/26 09:37:03 - mmengine - INFO - Epoch(train) [1197][10/63] lr: 1.6203e-05 eta: 0:02:39 time: 0.7455 data_time: 0.1808 memory: 16131 loss: 0.8363 loss_prob: 0.4320 loss_thr: 0.3293 loss_db: 0.0751 2022/10/26 09:37:05 - mmengine - INFO - Epoch(train) [1197][15/63] lr: 1.6203e-05 eta: 0:02:39 time: 0.5557 data_time: 0.0118 memory: 16131 loss: 0.8799 loss_prob: 0.4591 loss_thr: 0.3398 loss_db: 0.0809 2022/10/26 09:37:08 - mmengine - INFO - Epoch(train) [1197][20/63] lr: 1.6203e-05 eta: 0:02:32 time: 0.5330 data_time: 0.0122 memory: 16131 loss: 0.8403 loss_prob: 0.4349 loss_thr: 0.3278 loss_db: 0.0776 2022/10/26 09:37:10 - mmengine - INFO - Epoch(train) [1197][25/63] lr: 1.6203e-05 eta: 0:02:32 time: 0.5104 data_time: 0.0168 memory: 16131 loss: 0.8955 loss_prob: 0.4771 loss_thr: 0.3361 loss_db: 0.0823 2022/10/26 09:37:13 - mmengine - INFO - Epoch(train) [1197][30/63] lr: 1.6203e-05 eta: 0:02:25 time: 0.5239 data_time: 0.0314 memory: 16131 loss: 0.9038 loss_prob: 0.4850 loss_thr: 0.3367 loss_db: 0.0821 2022/10/26 09:37:16 - mmengine - INFO - Epoch(train) [1197][35/63] lr: 1.6203e-05 eta: 0:02:25 time: 0.5313 data_time: 0.0278 memory: 16131 loss: 0.8841 loss_prob: 0.4684 loss_thr: 0.3351 loss_db: 0.0807 2022/10/26 09:37:18 - mmengine - INFO - Epoch(train) [1197][40/63] lr: 1.6203e-05 eta: 0:02:19 time: 0.5032 data_time: 0.0093 memory: 16131 loss: 0.9492 loss_prob: 0.5078 loss_thr: 0.3547 loss_db: 0.0867 2022/10/26 09:37:21 - mmengine - INFO - Epoch(train) [1197][45/63] lr: 1.6203e-05 eta: 0:02:19 time: 0.4874 data_time: 0.0073 memory: 16131 loss: 0.9012 loss_prob: 0.4750 loss_thr: 0.3446 loss_db: 0.0817 2022/10/26 09:37:23 - mmengine - INFO - Epoch(train) [1197][50/63] lr: 1.6203e-05 eta: 0:02:12 time: 0.4954 data_time: 0.0155 memory: 16131 loss: 0.8286 loss_prob: 0.4334 loss_thr: 0.3190 loss_db: 0.0762 2022/10/26 09:37:25 - mmengine - INFO - Epoch(train) [1197][55/63] lr: 1.6203e-05 eta: 0:02:12 time: 0.4927 data_time: 0.0222 memory: 16131 loss: 0.8483 loss_prob: 0.4476 loss_thr: 0.3223 loss_db: 0.0785 2022/10/26 09:37:28 - mmengine - INFO - Epoch(train) [1197][60/63] lr: 1.6203e-05 eta: 0:02:06 time: 0.5083 data_time: 0.0160 memory: 16131 loss: 0.8090 loss_prob: 0.4198 loss_thr: 0.3147 loss_db: 0.0745 2022/10/26 09:37:29 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:37:34 - mmengine - INFO - Epoch(train) [1198][5/63] lr: 1.1280e-05 eta: 0:02:06 time: 0.6858 data_time: 0.1953 memory: 16131 loss: 0.7898 loss_prob: 0.4071 loss_thr: 0.3129 loss_db: 0.0698 2022/10/26 09:37:37 - mmengine - INFO - Epoch(train) [1198][10/63] lr: 1.1280e-05 eta: 0:01:57 time: 0.7497 data_time: 0.1944 memory: 16131 loss: 0.8785 loss_prob: 0.4578 loss_thr: 0.3438 loss_db: 0.0769 2022/10/26 09:37:40 - mmengine - INFO - Epoch(train) [1198][15/63] lr: 1.1280e-05 eta: 0:01:57 time: 0.5633 data_time: 0.0065 memory: 16131 loss: 0.9112 loss_prob: 0.4809 loss_thr: 0.3483 loss_db: 0.0820 2022/10/26 09:37:43 - mmengine - INFO - Epoch(train) [1198][20/63] lr: 1.1280e-05 eta: 0:01:51 time: 0.5620 data_time: 0.0068 memory: 16131 loss: 0.8848 loss_prob: 0.4589 loss_thr: 0.3452 loss_db: 0.0807 2022/10/26 09:37:46 - mmengine - INFO - Epoch(train) [1198][25/63] lr: 1.1280e-05 eta: 0:01:51 time: 0.6235 data_time: 0.0351 memory: 16131 loss: 0.8714 loss_prob: 0.4430 loss_thr: 0.3493 loss_db: 0.0790 2022/10/26 09:37:49 - mmengine - INFO - Epoch(train) [1198][30/63] lr: 1.1280e-05 eta: 0:01:44 time: 0.6004 data_time: 0.0346 memory: 16131 loss: 0.8515 loss_prob: 0.4338 loss_thr: 0.3411 loss_db: 0.0765 2022/10/26 09:37:51 - mmengine - INFO - Epoch(train) [1198][35/63] lr: 1.1280e-05 eta: 0:01:44 time: 0.5082 data_time: 0.0055 memory: 16131 loss: 0.8439 loss_prob: 0.4319 loss_thr: 0.3355 loss_db: 0.0765 2022/10/26 09:37:53 - mmengine - INFO - Epoch(train) [1198][40/63] lr: 1.1280e-05 eta: 0:01:37 time: 0.4902 data_time: 0.0092 memory: 16131 loss: 0.8840 loss_prob: 0.4622 loss_thr: 0.3386 loss_db: 0.0832 2022/10/26 09:37:56 - mmengine - INFO - Epoch(train) [1198][45/63] lr: 1.1280e-05 eta: 0:01:37 time: 0.4957 data_time: 0.0123 memory: 16131 loss: 0.8403 loss_prob: 0.4392 loss_thr: 0.3232 loss_db: 0.0779 2022/10/26 09:37:59 - mmengine - INFO - Epoch(train) [1198][50/63] lr: 1.1280e-05 eta: 0:01:31 time: 0.5230 data_time: 0.0266 memory: 16131 loss: 0.8079 loss_prob: 0.4150 loss_thr: 0.3207 loss_db: 0.0722 2022/10/26 09:38:01 - mmengine - INFO - Epoch(train) [1198][55/63] lr: 1.1280e-05 eta: 0:01:31 time: 0.5381 data_time: 0.0283 memory: 16131 loss: 0.8389 loss_prob: 0.4345 loss_thr: 0.3284 loss_db: 0.0760 2022/10/26 09:38:04 - mmengine - INFO - Epoch(train) [1198][60/63] lr: 1.1280e-05 eta: 0:01:24 time: 0.5277 data_time: 0.0098 memory: 16131 loss: 0.7833 loss_prob: 0.4070 loss_thr: 0.3043 loss_db: 0.0721 2022/10/26 09:38:05 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:38:10 - mmengine - INFO - Epoch(train) [1199][5/63] lr: 6.0910e-06 eta: 0:01:24 time: 0.7531 data_time: 0.1919 memory: 16131 loss: 0.7834 loss_prob: 0.4100 loss_thr: 0.3005 loss_db: 0.0728 2022/10/26 09:38:13 - mmengine - INFO - Epoch(train) [1199][10/63] lr: 6.0910e-06 eta: 0:01:16 time: 0.7537 data_time: 0.1965 memory: 16131 loss: 0.7886 loss_prob: 0.4020 loss_thr: 0.3160 loss_db: 0.0706 2022/10/26 09:38:16 - mmengine - INFO - Epoch(train) [1199][15/63] lr: 6.0910e-06 eta: 0:01:16 time: 0.5283 data_time: 0.0188 memory: 16131 loss: 0.8361 loss_prob: 0.4291 loss_thr: 0.3311 loss_db: 0.0759 2022/10/26 09:38:18 - mmengine - INFO - Epoch(train) [1199][20/63] lr: 6.0910e-06 eta: 0:01:09 time: 0.5553 data_time: 0.0137 memory: 16131 loss: 0.8175 loss_prob: 0.4243 loss_thr: 0.3187 loss_db: 0.0745 2022/10/26 09:38:21 - mmengine - INFO - Epoch(train) [1199][25/63] lr: 6.0910e-06 eta: 0:01:09 time: 0.5347 data_time: 0.0245 memory: 16131 loss: 0.8131 loss_prob: 0.4183 loss_thr: 0.3223 loss_db: 0.0726 2022/10/26 09:38:24 - mmengine - INFO - Epoch(train) [1199][30/63] lr: 6.0910e-06 eta: 0:01:03 time: 0.5210 data_time: 0.0302 memory: 16131 loss: 0.9016 loss_prob: 0.4697 loss_thr: 0.3493 loss_db: 0.0827 2022/10/26 09:38:26 - mmengine - INFO - Epoch(train) [1199][35/63] lr: 6.0910e-06 eta: 0:01:03 time: 0.5027 data_time: 0.0169 memory: 16131 loss: 0.9445 loss_prob: 0.4971 loss_thr: 0.3611 loss_db: 0.0863 2022/10/26 09:38:29 - mmengine - INFO - Epoch(train) [1199][40/63] lr: 6.0910e-06 eta: 0:00:56 time: 0.5063 data_time: 0.0127 memory: 16131 loss: 0.8969 loss_prob: 0.4671 loss_thr: 0.3487 loss_db: 0.0811 2022/10/26 09:38:31 - mmengine - INFO - Epoch(train) [1199][45/63] lr: 6.0910e-06 eta: 0:00:56 time: 0.5349 data_time: 0.0103 memory: 16131 loss: 0.8421 loss_prob: 0.4364 loss_thr: 0.3279 loss_db: 0.0778 2022/10/26 09:38:34 - mmengine - INFO - Epoch(train) [1199][50/63] lr: 6.0910e-06 eta: 0:00:49 time: 0.5402 data_time: 0.0198 memory: 16131 loss: 0.8054 loss_prob: 0.4115 loss_thr: 0.3207 loss_db: 0.0733 2022/10/26 09:38:37 - mmengine - INFO - Epoch(train) [1199][55/63] lr: 6.0910e-06 eta: 0:00:49 time: 0.5024 data_time: 0.0199 memory: 16131 loss: 0.8191 loss_prob: 0.4139 loss_thr: 0.3314 loss_db: 0.0738 2022/10/26 09:38:40 - mmengine - INFO - Epoch(train) [1199][60/63] lr: 6.0910e-06 eta: 0:00:43 time: 0.5656 data_time: 0.0144 memory: 16131 loss: 0.7977 loss_prob: 0.4112 loss_thr: 0.3132 loss_db: 0.0734 2022/10/26 09:38:41 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:38:46 - mmengine - INFO - Epoch(train) [1200][5/63] lr: 1.0000e-07 eta: 0:00:43 time: 0.7552 data_time: 0.2164 memory: 16131 loss: 0.8506 loss_prob: 0.4370 loss_thr: 0.3368 loss_db: 0.0769 2022/10/26 09:38:48 - mmengine - INFO - Epoch(train) [1200][10/63] lr: 1.0000e-07 eta: 0:00:34 time: 0.7090 data_time: 0.2110 memory: 16131 loss: 0.8838 loss_prob: 0.4537 loss_thr: 0.3510 loss_db: 0.0790 2022/10/26 09:38:51 - mmengine - INFO - Epoch(train) [1200][15/63] lr: 1.0000e-07 eta: 0:00:34 time: 0.5518 data_time: 0.0052 memory: 16131 loss: 0.9122 loss_prob: 0.4761 loss_thr: 0.3521 loss_db: 0.0840 2022/10/26 09:38:54 - mmengine - INFO - Epoch(train) [1200][20/63] lr: 1.0000e-07 eta: 0:00:28 time: 0.5986 data_time: 0.0077 memory: 16131 loss: 0.8843 loss_prob: 0.4641 loss_thr: 0.3373 loss_db: 0.0828 2022/10/26 09:38:57 - mmengine - INFO - Epoch(train) [1200][25/63] lr: 1.0000e-07 eta: 0:00:28 time: 0.5902 data_time: 0.0295 memory: 16131 loss: 0.8215 loss_prob: 0.4290 loss_thr: 0.3164 loss_db: 0.0762 2022/10/26 09:39:00 - mmengine - INFO - Epoch(train) [1200][30/63] lr: 1.0000e-07 eta: 0:00:21 time: 0.5715 data_time: 0.0376 memory: 16131 loss: 0.8760 loss_prob: 0.4584 loss_thr: 0.3377 loss_db: 0.0798 2022/10/26 09:39:03 - mmengine - INFO - Epoch(train) [1200][35/63] lr: 1.0000e-07 eta: 0:00:21 time: 0.5170 data_time: 0.0167 memory: 16131 loss: 0.8277 loss_prob: 0.4227 loss_thr: 0.3318 loss_db: 0.0732 2022/10/26 09:39:05 - mmengine - INFO - Epoch(train) [1200][40/63] lr: 1.0000e-07 eta: 0:00:15 time: 0.5154 data_time: 0.0077 memory: 16131 loss: 0.8025 loss_prob: 0.4083 loss_thr: 0.3225 loss_db: 0.0717 2022/10/26 09:39:08 - mmengine - INFO - Epoch(train) [1200][45/63] lr: 1.0000e-07 eta: 0:00:15 time: 0.5278 data_time: 0.0142 memory: 16131 loss: 0.7960 loss_prob: 0.4120 loss_thr: 0.3112 loss_db: 0.0728 2022/10/26 09:39:10 - mmengine - INFO - Epoch(train) [1200][50/63] lr: 1.0000e-07 eta: 0:00:08 time: 0.5248 data_time: 0.0261 memory: 16131 loss: 0.7703 loss_prob: 0.3963 loss_thr: 0.3036 loss_db: 0.0704 2022/10/26 09:39:13 - mmengine - INFO - Epoch(train) [1200][55/63] lr: 1.0000e-07 eta: 0:00:08 time: 0.5346 data_time: 0.0280 memory: 16131 loss: 0.8272 loss_prob: 0.4383 loss_thr: 0.3116 loss_db: 0.0774 2022/10/26 09:39:16 - mmengine - INFO - Epoch(train) [1200][60/63] lr: 1.0000e-07 eta: 0:00:01 time: 0.5318 data_time: 0.0154 memory: 16131 loss: 0.9072 loss_prob: 0.4838 loss_thr: 0.3394 loss_db: 0.0841 2022/10/26 09:39:17 - mmengine - INFO - Exp name: dbnetpp_resnet50_fpnc_1200e_icdar2015_20221025_185550 2022/10/26 09:39:17 - mmengine - INFO - Saving checkpoint at 1200 epochs 2022/10/26 09:39:24 - mmengine - INFO - Epoch(val) [1200][5/32] eta: 0:00:01 time: 0.5229 data_time: 0.0615 memory: 16131 2022/10/26 09:39:27 - mmengine - INFO - Epoch(val) [1200][10/32] eta: 0:00:12 time: 0.5861 data_time: 0.0842 memory: 15724 2022/10/26 09:39:29 - mmengine - INFO - Epoch(val) [1200][15/32] eta: 0:00:12 time: 0.5418 data_time: 0.0394 memory: 15724 2022/10/26 09:39:32 - mmengine - INFO - Epoch(val) [1200][20/32] eta: 0:00:06 time: 0.5399 data_time: 0.0442 memory: 15724 2022/10/26 09:39:35 - mmengine - INFO - Epoch(val) [1200][25/32] eta: 0:00:06 time: 0.5618 data_time: 0.0529 memory: 15724 2022/10/26 09:39:37 - mmengine - INFO - Epoch(val) [1200][30/32] eta: 0:00:01 time: 0.5301 data_time: 0.0325 memory: 15724 2022/10/26 09:39:38 - mmengine - INFO - Evaluating hmean-iou... 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8392, precision: 0.7887, hmean: 0.8132 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8392, precision: 0.8229, hmean: 0.8310 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8387, precision: 0.8440, hmean: 0.8413 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8353, precision: 0.8666, hmean: 0.8507 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8281, precision: 0.8940, hmean: 0.8598 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.7646, precision: 0.9259, hmean: 0.8376 2022/10/26 09:39:38 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.2735, precision: 0.9693, hmean: 0.4266 2022/10/26 09:39:38 - mmengine - INFO - Epoch(val) [1200][32/32] icdar/precision: 0.8940 icdar/recall: 0.8281 icdar/hmean: 0.8598