2022/11/01 12:41:39 - 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: 960292547 GPU 0: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.10.0+cu111 OpenCV: 4.6.0 MMEngine: 0.2.0 Runtime environment: cudnn_benchmark: True mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 1 ------------------------------------------------------------ 2022/11/01 12:41:39 - mmengine - INFO - Config: model = dict( type='DBNet', backbone=dict( type='CLIPResNet', init_cfg=dict( type='Pretrained', checkpoint= 'r50_oclip.pth')), 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 = True 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=0.002, momentum=0.9, weight_decay=0.0001)) train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=1200, val_interval=20) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict(type='LinearLR', end=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-oclip_fpnc_1200e_icdar2015' Name of parameter - Initialization information backbone.stem.0.weight - torch.Size([32, 3, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.stem.1.weight - torch.Size([32]): PretrainedInit: load from r50_oclip.pth backbone.stem.1.bias - torch.Size([32]): PretrainedInit: load from r50_oclip.pth backbone.stem.3.weight - torch.Size([32, 32, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.stem.4.weight - torch.Size([32]): PretrainedInit: load from r50_oclip.pth backbone.stem.4.bias - torch.Size([32]): PretrainedInit: load from r50_oclip.pth backbone.stem.6.weight - torch.Size([64, 32, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.stem.7.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.stem.7.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.bn1.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.bn1.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.bn2.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.bn2.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.bn3.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.bn3.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.downsample.1.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.downsample.2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.0.downsample.2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.bn1.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.bn1.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.bn2.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.bn2.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.bn3.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.1.bn3.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.bn1.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.bn1.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.bn2.weight - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.bn2.bias - torch.Size([64]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.bn3.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer1.2.bn3.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.conv1.weight - torch.Size([128, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.bn1.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.bn1.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.bn2.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.bn2.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.bn3.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.bn3.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.downsample.1.weight - torch.Size([512, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.downsample.2.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.0.downsample.2.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.bn1.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.bn1.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.bn2.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.bn2.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.bn3.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.1.bn3.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.bn1.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.bn1.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.bn2.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.bn2.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.bn3.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.2.bn3.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.bn1.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.bn1.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.bn2.weight - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.bn2.bias - torch.Size([128]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.bn3.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer2.3.bn3.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.conv1.weight - torch.Size([256, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.bn1.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.bn1.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.bn2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.bn2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.bn3.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.bn3.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.downsample.1.weight - torch.Size([1024, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.downsample.2.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.0.downsample.2.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.bn1.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.bn1.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.bn2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.bn2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.bn3.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.1.bn3.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.bn1.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.bn1.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.bn2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.bn2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.bn3.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.2.bn3.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.bn1.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.bn1.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.bn2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.bn2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.bn3.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.3.bn3.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.bn1.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.bn1.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.bn2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.bn2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.bn3.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.4.bn3.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.bn1.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.bn1.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.bn2.weight - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.bn2.bias - torch.Size([256]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.bn3.weight - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer3.5.bn3.bias - torch.Size([1024]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.conv1.weight - torch.Size([512, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.bn1.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.bn1.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.bn2.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.bn2.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.bn3.weight - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.bn3.bias - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.downsample.1.weight - torch.Size([2048, 1024, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.downsample.2.weight - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.0.downsample.2.bias - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.bn1.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.bn1.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.bn2.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.bn2.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.bn3.weight - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.1.bn3.bias - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.bn1.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.bn1.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.bn2.weight - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.bn2.bias - torch.Size([512]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.bn3.weight - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth backbone.layer4.2.bn3.bias - torch.Size([2048]): PretrainedInit: load from r50_oclip.pth 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 2022/11/01 12:42:24 - mmengine - INFO - Auto resumed from the latest checkpoint None. 2022/11/01 12:42:24 - mmengine - INFO - Checkpoints will be saved to sproject:s3://oclip/dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015. 2022/11/01 12:48:33 - mmengine - INFO - Epoch(train) [1][5/63] lr: 2.0000e-06 memory: 49612 data_time: 70.8109 loss: 22.4251 loss_prob: 18.3992 loss_thr: 3.0378 loss_db: 0.9881 time: 73.9852 2022/11/01 12:48:40 - mmengine - INFO - Epoch(train) [1][10/63] lr: 2.0000e-06 eta: 32 days, 22:01:12 time: 37.6250 data_time: 35.4080 memory: 17619 loss: 22.8798 loss_prob: 18.8409 loss_thr: 3.0488 loss_db: 0.9901 2022/11/01 12:48:44 - mmengine - INFO - Epoch(train) [1][15/63] lr: 2.0000e-06 eta: 32 days, 22:01:12 time: 1.0646 data_time: 0.0101 memory: 17619 loss: 22.3264 loss_prob: 18.3841 loss_thr: 2.9510 loss_db: 0.9914 2022/11/01 12:48:49 - mmengine - INFO - Epoch(train) [1][20/63] lr: 2.0000e-06 eta: 16 days, 20:38:51 time: 0.9231 data_time: 0.0107 memory: 17619 loss: 20.7236 loss_prob: 16.9118 loss_thr: 2.8205 loss_db: 0.9913 2022/11/01 12:48:54 - mmengine - INFO - Epoch(train) [1][25/63] lr: 2.0000e-06 eta: 16 days, 20:38:51 time: 0.9841 data_time: 0.0284 memory: 17619 loss: 19.2752 loss_prob: 15.5350 loss_thr: 2.7485 loss_db: 0.9917 2022/11/01 12:49:00 - mmengine - INFO - Epoch(train) [1][30/63] lr: 2.0000e-06 eta: 11 days, 13:26:31 time: 1.1022 data_time: 0.0341 memory: 17619 loss: 17.8729 loss_prob: 14.2097 loss_thr: 2.6723 loss_db: 0.9908 2022/11/01 12:49:05 - mmengine - INFO - Epoch(train) [1][35/63] lr: 2.0000e-06 eta: 11 days, 13:26:31 time: 1.0685 data_time: 0.0254 memory: 17619 loss: 17.2549 loss_prob: 13.5770 loss_thr: 2.6867 loss_db: 0.9911 2022/11/01 12:49:09 - mmengine - INFO - Epoch(train) [1][40/63] lr: 2.0000e-06 eta: 8 days, 20:39:43 time: 0.8782 data_time: 0.0204 memory: 17619 loss: 16.9158 loss_prob: 13.1950 loss_thr: 2.7283 loss_db: 0.9926 2022/11/01 12:49:13 - mmengine - INFO - Epoch(train) [1][45/63] lr: 2.0000e-06 eta: 8 days, 20:39:43 time: 0.8522 data_time: 0.0059 memory: 17619 loss: 16.6540 loss_prob: 12.9827 loss_thr: 2.6788 loss_db: 0.9925 2022/11/01 12:49:17 - mmengine - INFO - Epoch(train) [1][50/63] lr: 2.0000e-06 eta: 7 days, 5:37:39 time: 0.8388 data_time: 0.0155 memory: 17619 loss: 16.3252 loss_prob: 12.7058 loss_thr: 2.6281 loss_db: 0.9914 2022/11/01 12:49:21 - mmengine - INFO - Epoch(train) [1][55/63] lr: 2.0000e-06 eta: 7 days, 5:37:39 time: 0.7986 data_time: 0.0350 memory: 17619 loss: 15.7243 loss_prob: 12.1090 loss_thr: 2.6244 loss_db: 0.9910 2022/11/01 12:49:24 - mmengine - INFO - Epoch(train) [1][60/63] lr: 2.0000e-06 eta: 6 days, 3:09:33 time: 0.7116 data_time: 0.0247 memory: 17619 loss: 15.2996 loss_prob: 11.7159 loss_thr: 2.5929 loss_db: 0.9908 2022/11/01 12:49:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:49:43 - mmengine - INFO - Epoch(train) [2][5/63] lr: 1.2040e-05 eta: 6 days, 3:09:33 time: 1.9789 data_time: 0.1906 memory: 41624 loss: 14.7851 loss_prob: 11.2024 loss_thr: 2.5921 loss_db: 0.9906 2022/11/01 12:49:49 - mmengine - INFO - Epoch(train) [2][10/63] lr: 1.2040e-05 eta: 5 days, 4:23:36 time: 1.2045 data_time: 0.1977 memory: 17620 loss: 17.4836 loss_prob: 13.9419 loss_thr: 2.5509 loss_db: 0.9908 2022/11/01 12:49:55 - mmengine - INFO - Epoch(train) [2][15/63] lr: 1.2040e-05 eta: 5 days, 4:23:36 time: 1.2263 data_time: 0.0209 memory: 17620 loss: 18.4986 loss_prob: 15.0510 loss_thr: 2.4592 loss_db: 0.9885 2022/11/01 12:50:00 - mmengine - INFO - Epoch(train) [2][20/63] lr: 1.2040e-05 eta: 4 days, 16:10:47 time: 1.1032 data_time: 0.0127 memory: 17620 loss: 15.9380 loss_prob: 12.5663 loss_thr: 2.3817 loss_db: 0.9899 2022/11/01 12:50:05 - mmengine - INFO - Epoch(train) [2][25/63] lr: 1.2040e-05 eta: 4 days, 16:10:47 time: 1.0028 data_time: 0.0226 memory: 17620 loss: 14.0364 loss_prob: 10.7628 loss_thr: 2.2836 loss_db: 0.9900 2022/11/01 12:50:09 - mmengine - INFO - Epoch(train) [2][30/63] lr: 1.2040e-05 eta: 4 days, 6:08:48 time: 0.9056 data_time: 0.0229 memory: 17620 loss: 12.8178 loss_prob: 9.6289 loss_thr: 2.1984 loss_db: 0.9905 2022/11/01 12:50:14 - mmengine - INFO - Epoch(train) [2][35/63] lr: 1.2040e-05 eta: 4 days, 6:08:48 time: 0.9045 data_time: 0.0179 memory: 17620 loss: 12.1563 loss_prob: 9.0084 loss_thr: 2.1550 loss_db: 0.9929 2022/11/01 12:50:20 - mmengine - INFO - Epoch(train) [2][40/63] lr: 1.2040e-05 eta: 3 days, 22:31:46 time: 1.1357 data_time: 0.0177 memory: 17620 loss: 11.5292 loss_prob: 8.3960 loss_thr: 2.1396 loss_db: 0.9936 2022/11/01 12:50:25 - mmengine - INFO - Epoch(train) [2][45/63] lr: 1.2040e-05 eta: 3 days, 22:31:46 time: 1.0738 data_time: 0.0043 memory: 17620 loss: 10.9022 loss_prob: 7.8267 loss_thr: 2.0845 loss_db: 0.9910 2022/11/01 12:50:29 - mmengine - INFO - Epoch(train) [2][50/63] lr: 1.2040e-05 eta: 3 days, 15:50:11 time: 0.9074 data_time: 0.0136 memory: 17620 loss: 10.2828 loss_prob: 7.2975 loss_thr: 1.9991 loss_db: 0.9862 2022/11/01 12:50:32 - mmengine - INFO - Epoch(train) [2][55/63] lr: 1.2040e-05 eta: 3 days, 15:50:11 time: 0.7452 data_time: 0.0166 memory: 17620 loss: 9.8702 loss_prob: 6.9678 loss_thr: 1.9153 loss_db: 0.9870 2022/11/01 12:50:36 - mmengine - INFO - Epoch(train) [2][60/63] lr: 1.2040e-05 eta: 3 days, 9:44:38 time: 0.6214 data_time: 0.0151 memory: 17620 loss: 9.6768 loss_prob: 6.8337 loss_thr: 1.8537 loss_db: 0.9894 2022/11/01 12:50:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:50:43 - mmengine - INFO - Epoch(train) [3][5/63] lr: 2.2080e-05 eta: 3 days, 9:44:38 time: 0.9340 data_time: 0.2306 memory: 17620 loss: 9.3476 loss_prob: 6.5490 loss_thr: 1.8097 loss_db: 0.9889 2022/11/01 12:50:49 - mmengine - INFO - Epoch(train) [3][10/63] lr: 2.2080e-05 eta: 3 days, 3:32:23 time: 1.0526 data_time: 0.2223 memory: 17620 loss: 8.7431 loss_prob: 6.0520 loss_thr: 1.7037 loss_db: 0.9875 2022/11/01 12:50:52 - mmengine - INFO - Epoch(train) [3][15/63] lr: 2.2080e-05 eta: 3 days, 3:32:23 time: 0.8358 data_time: 0.0084 memory: 17620 loss: 8.4046 loss_prob: 5.7911 loss_thr: 1.6275 loss_db: 0.9859 2022/11/01 12:50:55 - mmengine - INFO - Epoch(train) [3][20/63] lr: 2.2080e-05 eta: 2 days, 23:16:50 time: 0.6437 data_time: 0.0072 memory: 17620 loss: 8.3042 loss_prob: 5.6914 loss_thr: 1.6250 loss_db: 0.9877 2022/11/01 12:50:59 - mmengine - INFO - Epoch(train) [3][25/63] lr: 2.2080e-05 eta: 2 days, 23:16:50 time: 0.6733 data_time: 0.0408 memory: 17620 loss: 8.0153 loss_prob: 5.4404 loss_thr: 1.5870 loss_db: 0.9879 2022/11/01 12:51:03 - mmengine - INFO - Epoch(train) [3][30/63] lr: 2.2080e-05 eta: 2 days, 19:45:51 time: 0.7904 data_time: 0.0453 memory: 17620 loss: 7.7659 loss_prob: 5.2498 loss_thr: 1.5290 loss_db: 0.9870 2022/11/01 12:51:09 - mmengine - INFO - Epoch(train) [3][35/63] lr: 2.2080e-05 eta: 2 days, 19:45:51 time: 1.0511 data_time: 0.0101 memory: 17620 loss: 7.6285 loss_prob: 5.1559 loss_thr: 1.4850 loss_db: 0.9875 2022/11/01 12:51:13 - mmengine - INFO - Epoch(train) [3][40/63] lr: 2.2080e-05 eta: 2 days, 16:58:03 time: 1.0251 data_time: 0.0065 memory: 17620 loss: 7.5101 loss_prob: 5.0440 loss_thr: 1.4771 loss_db: 0.9890 2022/11/01 12:51:18 - mmengine - INFO - Epoch(train) [3][45/63] lr: 2.2080e-05 eta: 2 days, 16:58:03 time: 0.9011 data_time: 0.0058 memory: 17620 loss: 7.4373 loss_prob: 4.9476 loss_thr: 1.4997 loss_db: 0.9900 2022/11/01 12:51:23 - mmengine - INFO - Epoch(train) [3][50/63] lr: 2.2080e-05 eta: 2 days, 14:28:03 time: 1.0076 data_time: 0.0186 memory: 17620 loss: 7.3751 loss_prob: 4.8948 loss_thr: 1.4906 loss_db: 0.9897 2022/11/01 12:51:26 - mmengine - INFO - Epoch(train) [3][55/63] lr: 2.2080e-05 eta: 2 days, 14:28:03 time: 0.8372 data_time: 0.0225 memory: 17620 loss: 7.1572 loss_prob: 4.7460 loss_thr: 1.4225 loss_db: 0.9886 2022/11/01 12:51:31 - mmengine - INFO - Epoch(train) [3][60/63] lr: 2.2080e-05 eta: 2 days, 11:55:16 time: 0.7280 data_time: 0.0109 memory: 17620 loss: 6.9679 loss_prob: 4.5813 loss_thr: 1.3994 loss_db: 0.9872 2022/11/01 12:51:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:51:40 - mmengine - INFO - Epoch(train) [4][5/63] lr: 3.2121e-05 eta: 2 days, 11:55:16 time: 1.0688 data_time: 0.2358 memory: 17620 loss: 6.9152 loss_prob: 4.5174 loss_thr: 1.4109 loss_db: 0.9869 2022/11/01 12:51:45 - mmengine - INFO - Epoch(train) [4][10/63] lr: 3.2121e-05 eta: 2 days, 9:17:50 time: 1.2353 data_time: 0.2366 memory: 17620 loss: 6.8813 loss_prob: 4.5112 loss_thr: 1.3818 loss_db: 0.9883 2022/11/01 12:51:49 - mmengine - INFO - Epoch(train) [4][15/63] lr: 3.2121e-05 eta: 2 days, 9:17:50 time: 0.9456 data_time: 0.0075 memory: 17620 loss: 6.7828 loss_prob: 4.3863 loss_thr: 1.4093 loss_db: 0.9873 2022/11/01 12:51:53 - mmengine - INFO - Epoch(train) [4][20/63] lr: 3.2121e-05 eta: 2 days, 7:19:24 time: 0.7734 data_time: 0.0047 memory: 17620 loss: 6.7494 loss_prob: 4.3486 loss_thr: 1.4130 loss_db: 0.9878 2022/11/01 12:51:59 - mmengine - INFO - Epoch(train) [4][25/63] lr: 3.2121e-05 eta: 2 days, 7:19:24 time: 1.0018 data_time: 0.0086 memory: 17620 loss: 6.6244 loss_prob: 4.2801 loss_thr: 1.3553 loss_db: 0.9889 2022/11/01 12:52:04 - mmengine - INFO - Epoch(train) [4][30/63] lr: 3.2121e-05 eta: 2 days, 5:47:47 time: 1.0524 data_time: 0.0323 memory: 17620 loss: 6.8289 loss_prob: 4.4072 loss_thr: 1.4331 loss_db: 0.9887 2022/11/01 12:52:07 - mmengine - INFO - Epoch(train) [4][35/63] lr: 3.2121e-05 eta: 2 days, 5:47:47 time: 0.7989 data_time: 0.0291 memory: 17620 loss: 7.0095 loss_prob: 4.4890 loss_thr: 1.5329 loss_db: 0.9875 2022/11/01 12:52:11 - mmengine - INFO - Epoch(train) [4][40/63] lr: 3.2121e-05 eta: 2 days, 4:05:55 time: 0.7200 data_time: 0.0056 memory: 17620 loss: 6.7435 loss_prob: 4.2854 loss_thr: 1.4714 loss_db: 0.9867 2022/11/01 12:52:17 - mmengine - INFO - Epoch(train) [4][45/63] lr: 3.2121e-05 eta: 2 days, 4:05:55 time: 0.9642 data_time: 0.0069 memory: 17620 loss: 6.5772 loss_prob: 4.1910 loss_thr: 1.3988 loss_db: 0.9874 2022/11/01 12:52:21 - mmengine - INFO - Epoch(train) [4][50/63] lr: 3.2121e-05 eta: 2 days, 2:49:19 time: 1.0387 data_time: 0.0165 memory: 17620 loss: 6.5011 loss_prob: 4.1450 loss_thr: 1.3686 loss_db: 0.9875 2022/11/01 12:52:25 - mmengine - INFO - Epoch(train) [4][55/63] lr: 3.2121e-05 eta: 2 days, 2:49:19 time: 0.8077 data_time: 0.0314 memory: 17620 loss: 6.5066 loss_prob: 4.1348 loss_thr: 1.3833 loss_db: 0.9885 2022/11/01 12:52:29 - mmengine - INFO - Epoch(train) [4][60/63] lr: 3.2121e-05 eta: 2 days, 1:25:20 time: 0.7706 data_time: 0.0222 memory: 17620 loss: 6.5155 loss_prob: 4.1248 loss_thr: 1.4008 loss_db: 0.9899 2022/11/01 12:52:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:52:37 - mmengine - INFO - Epoch(train) [5][5/63] lr: 4.2161e-05 eta: 2 days, 1:25:20 time: 1.0323 data_time: 0.2056 memory: 17620 loss: 6.3534 loss_prob: 4.0199 loss_thr: 1.3412 loss_db: 0.9922 2022/11/01 12:52:43 - mmengine - INFO - Epoch(train) [5][10/63] lr: 4.2161e-05 eta: 1 day, 23:51:54 time: 1.1309 data_time: 0.2056 memory: 17620 loss: 6.2103 loss_prob: 3.9122 loss_thr: 1.3075 loss_db: 0.9906 2022/11/01 12:52:46 - mmengine - INFO - Epoch(train) [5][15/63] lr: 4.2161e-05 eta: 1 day, 23:51:54 time: 0.8598 data_time: 0.0048 memory: 17620 loss: 6.0975 loss_prob: 3.8157 loss_thr: 1.2933 loss_db: 0.9885 2022/11/01 12:52:51 - mmengine - INFO - Epoch(train) [5][20/63] lr: 4.2161e-05 eta: 1 day, 22:44:33 time: 0.8361 data_time: 0.0092 memory: 17620 loss: 6.0612 loss_prob: 3.7740 loss_thr: 1.2975 loss_db: 0.9897 2022/11/01 12:52:57 - mmengine - INFO - Epoch(train) [5][25/63] lr: 4.2161e-05 eta: 1 day, 22:44:33 time: 1.0676 data_time: 0.0295 memory: 17620 loss: 6.0425 loss_prob: 3.7629 loss_thr: 1.2879 loss_db: 0.9917 2022/11/01 12:53:01 - mmengine - INFO - Epoch(train) [5][30/63] lr: 4.2161e-05 eta: 1 day, 21:50:21 time: 1.0247 data_time: 0.0329 memory: 17620 loss: 6.0188 loss_prob: 3.7350 loss_thr: 1.2911 loss_db: 0.9927 2022/11/01 12:53:05 - mmengine - INFO - Epoch(train) [5][35/63] lr: 4.2161e-05 eta: 1 day, 21:50:21 time: 0.8505 data_time: 0.0132 memory: 17620 loss: 5.9857 loss_prob: 3.7147 loss_thr: 1.2774 loss_db: 0.9936 2022/11/01 12:53:08 - mmengine - INFO - Epoch(train) [5][40/63] lr: 4.2161e-05 eta: 1 day, 20:45:30 time: 0.6909 data_time: 0.0070 memory: 17620 loss: 5.9860 loss_prob: 3.7096 loss_thr: 1.2837 loss_db: 0.9927 2022/11/01 12:53:13 - mmengine - INFO - Epoch(train) [5][45/63] lr: 4.2161e-05 eta: 1 day, 20:45:30 time: 0.7833 data_time: 0.0061 memory: 17620 loss: 5.9737 loss_prob: 3.6867 loss_thr: 1.2945 loss_db: 0.9925 2022/11/01 12:53:18 - mmengine - INFO - Epoch(train) [5][50/63] lr: 4.2161e-05 eta: 1 day, 19:57:03 time: 0.9823 data_time: 0.0151 memory: 17620 loss: 5.8888 loss_prob: 3.6364 loss_thr: 1.2615 loss_db: 0.9908 2022/11/01 12:53:22 - mmengine - INFO - Epoch(train) [5][55/63] lr: 4.2161e-05 eta: 1 day, 19:57:03 time: 0.8902 data_time: 0.0213 memory: 17620 loss: 5.8292 loss_prob: 3.5911 loss_thr: 1.2486 loss_db: 0.9895 2022/11/01 12:53:25 - mmengine - INFO - Epoch(train) [5][60/63] lr: 4.2161e-05 eta: 1 day, 19:00:29 time: 0.7036 data_time: 0.0111 memory: 17620 loss: 5.7963 loss_prob: 3.5644 loss_thr: 1.2398 loss_db: 0.9921 2022/11/01 12:53:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:53:34 - mmengine - INFO - Epoch(train) [6][5/63] lr: 5.2201e-05 eta: 1 day, 19:00:29 time: 0.9557 data_time: 0.1975 memory: 17620 loss: 5.8289 loss_prob: 3.5765 loss_thr: 1.2625 loss_db: 0.9900 2022/11/01 12:53:39 - mmengine - INFO - Epoch(train) [6][10/63] lr: 5.2201e-05 eta: 1 day, 18:01:01 time: 1.1445 data_time: 0.2088 memory: 17620 loss: 5.7810 loss_prob: 3.5211 loss_thr: 1.2696 loss_db: 0.9902 2022/11/01 12:53:43 - mmengine - INFO - Epoch(train) [6][15/63] lr: 5.2201e-05 eta: 1 day, 18:01:01 time: 0.9136 data_time: 0.0159 memory: 17620 loss: 5.7586 loss_prob: 3.4978 loss_thr: 1.2681 loss_db: 0.9927 2022/11/01 12:53:49 - mmengine - INFO - Epoch(train) [6][20/63] lr: 5.2201e-05 eta: 1 day, 17:20:59 time: 0.9492 data_time: 0.0042 memory: 17620 loss: 5.7496 loss_prob: 3.4966 loss_thr: 1.2590 loss_db: 0.9939 2022/11/01 12:53:54 - mmengine - INFO - Epoch(train) [6][25/63] lr: 5.2201e-05 eta: 1 day, 17:20:59 time: 1.1277 data_time: 0.0251 memory: 17620 loss: 5.6936 loss_prob: 3.4595 loss_thr: 1.2407 loss_db: 0.9933 2022/11/01 12:53:59 - mmengine - INFO - Epoch(train) [6][30/63] lr: 5.2201e-05 eta: 1 day, 16:46:44 time: 1.0449 data_time: 0.0343 memory: 17620 loss: 5.6419 loss_prob: 3.4089 loss_thr: 1.2404 loss_db: 0.9926 2022/11/01 12:54:03 - mmengine - INFO - Epoch(train) [6][35/63] lr: 5.2201e-05 eta: 1 day, 16:46:44 time: 0.8743 data_time: 0.0136 memory: 17620 loss: 5.6088 loss_prob: 3.3754 loss_thr: 1.2420 loss_db: 0.9914 2022/11/01 12:54:09 - mmengine - INFO - Epoch(train) [6][40/63] lr: 5.2201e-05 eta: 1 day, 16:12:24 time: 0.9882 data_time: 0.0051 memory: 17620 loss: 5.5949 loss_prob: 3.3788 loss_thr: 1.2231 loss_db: 0.9930 2022/11/01 12:54:14 - mmengine - INFO - Epoch(train) [6][45/63] lr: 5.2201e-05 eta: 1 day, 16:12:24 time: 1.1527 data_time: 0.0052 memory: 17620 loss: 5.5937 loss_prob: 3.3745 loss_thr: 1.2250 loss_db: 0.9942 2022/11/01 12:54:18 - mmengine - INFO - Epoch(train) [6][50/63] lr: 5.2201e-05 eta: 1 day, 15:38:26 time: 0.9442 data_time: 0.0185 memory: 17620 loss: 5.5971 loss_prob: 3.3724 loss_thr: 1.2297 loss_db: 0.9950 2022/11/01 12:54:24 - mmengine - INFO - Epoch(train) [6][55/63] lr: 5.2201e-05 eta: 1 day, 15:38:26 time: 0.9286 data_time: 0.0254 memory: 17620 loss: 5.5583 loss_prob: 3.3467 loss_thr: 1.2164 loss_db: 0.9952 2022/11/01 12:54:27 - mmengine - INFO - Epoch(train) [6][60/63] lr: 5.2201e-05 eta: 1 day, 15:02:24 time: 0.8284 data_time: 0.0124 memory: 17620 loss: 5.5408 loss_prob: 3.3112 loss_thr: 1.2351 loss_db: 0.9945 2022/11/01 12:54:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:54:37 - mmengine - INFO - Epoch(train) [7][5/63] lr: 6.2241e-05 eta: 1 day, 15:02:24 time: 1.1267 data_time: 0.2227 memory: 17620 loss: 5.5130 loss_prob: 3.2863 loss_thr: 1.2317 loss_db: 0.9950 2022/11/01 12:54:40 - mmengine - INFO - Epoch(train) [7][10/63] lr: 6.2241e-05 eta: 1 day, 14:19:34 time: 1.1154 data_time: 0.2229 memory: 17620 loss: 5.4656 loss_prob: 3.2669 loss_thr: 1.2032 loss_db: 0.9956 2022/11/01 12:54:46 - mmengine - INFO - Epoch(train) [7][15/63] lr: 6.2241e-05 eta: 1 day, 14:19:34 time: 0.9149 data_time: 0.0053 memory: 17620 loss: 5.4877 loss_prob: 3.2876 loss_thr: 1.2060 loss_db: 0.9941 2022/11/01 12:54:50 - mmengine - INFO - Epoch(train) [7][20/63] lr: 6.2241e-05 eta: 1 day, 13:51:31 time: 0.9537 data_time: 0.0064 memory: 17620 loss: 5.4699 loss_prob: 3.2676 loss_thr: 1.2079 loss_db: 0.9943 2022/11/01 12:54:54 - mmengine - INFO - Epoch(train) [7][25/63] lr: 6.2241e-05 eta: 1 day, 13:51:31 time: 0.7936 data_time: 0.0283 memory: 17620 loss: 5.4494 loss_prob: 3.2548 loss_thr: 1.1982 loss_db: 0.9964 2022/11/01 12:54:59 - mmengine - INFO - Epoch(train) [7][30/63] lr: 6.2241e-05 eta: 1 day, 13:25:07 time: 0.9626 data_time: 0.0372 memory: 17620 loss: 5.4371 loss_prob: 3.2445 loss_thr: 1.1964 loss_db: 0.9962 2022/11/01 12:55:05 - mmengine - INFO - Epoch(train) [7][35/63] lr: 6.2241e-05 eta: 1 day, 13:25:07 time: 1.1098 data_time: 0.0148 memory: 17620 loss: 5.4235 loss_prob: 3.2187 loss_thr: 1.2090 loss_db: 0.9959 2022/11/01 12:55:09 - mmengine - INFO - Epoch(train) [7][40/63] lr: 6.2241e-05 eta: 1 day, 12:59:34 time: 0.9492 data_time: 0.0049 memory: 17620 loss: 5.4343 loss_prob: 3.2125 loss_thr: 1.2264 loss_db: 0.9954 2022/11/01 12:55:13 - mmengine - INFO - Epoch(train) [7][45/63] lr: 6.2241e-05 eta: 1 day, 12:59:34 time: 0.7780 data_time: 0.0049 memory: 17620 loss: 5.4012 loss_prob: 3.1814 loss_thr: 1.2243 loss_db: 0.9955 2022/11/01 12:55:18 - mmengine - INFO - Epoch(train) [7][50/63] lr: 6.2241e-05 eta: 1 day, 12:33:37 time: 0.8947 data_time: 0.0164 memory: 17620 loss: 5.3738 loss_prob: 3.1576 loss_thr: 1.2193 loss_db: 0.9970 2022/11/01 12:55:21 - mmengine - INFO - Epoch(train) [7][55/63] lr: 6.2241e-05 eta: 1 day, 12:33:37 time: 0.8588 data_time: 0.0232 memory: 17620 loss: 5.4125 loss_prob: 3.1872 loss_thr: 1.2291 loss_db: 0.9963 2022/11/01 12:55:26 - mmengine - INFO - Epoch(train) [7][60/63] lr: 6.2241e-05 eta: 1 day, 12:05:14 time: 0.7690 data_time: 0.0118 memory: 17620 loss: 5.4562 loss_prob: 3.2329 loss_thr: 1.2270 loss_db: 0.9964 2022/11/01 12:55:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:55:33 - mmengine - INFO - Epoch(train) [8][5/63] lr: 7.2281e-05 eta: 1 day, 12:05:14 time: 0.9964 data_time: 0.2228 memory: 17620 loss: 5.4355 loss_prob: 3.2213 loss_thr: 1.2178 loss_db: 0.9964 2022/11/01 12:55:37 - mmengine - INFO - Epoch(train) [8][10/63] lr: 7.2281e-05 eta: 1 day, 11:30:20 time: 1.0035 data_time: 0.2226 memory: 17620 loss: 5.4126 loss_prob: 3.2125 loss_thr: 1.2033 loss_db: 0.9968 2022/11/01 12:55:41 - mmengine - INFO - Epoch(train) [8][15/63] lr: 7.2281e-05 eta: 1 day, 11:30:20 time: 0.8031 data_time: 0.0055 memory: 17620 loss: 5.4395 loss_prob: 3.1937 loss_thr: 1.2501 loss_db: 0.9957 2022/11/01 12:55:45 - mmengine - INFO - Epoch(train) [8][20/63] lr: 7.2281e-05 eta: 1 day, 11:04:36 time: 0.7640 data_time: 0.0056 memory: 17620 loss: 5.3766 loss_prob: 3.1464 loss_thr: 1.2352 loss_db: 0.9951 2022/11/01 12:55:48 - mmengine - INFO - Epoch(train) [8][25/63] lr: 7.2281e-05 eta: 1 day, 11:04:36 time: 0.6492 data_time: 0.0063 memory: 17620 loss: 5.3196 loss_prob: 3.1363 loss_thr: 1.1859 loss_db: 0.9974 2022/11/01 12:55:52 - mmengine - INFO - Epoch(train) [8][30/63] lr: 7.2281e-05 eta: 1 day, 10:38:47 time: 0.7202 data_time: 0.0369 memory: 17620 loss: 5.3568 loss_prob: 3.1568 loss_thr: 1.2031 loss_db: 0.9969 2022/11/01 12:55:56 - mmengine - INFO - Epoch(train) [8][35/63] lr: 7.2281e-05 eta: 1 day, 10:38:47 time: 0.7883 data_time: 0.0354 memory: 17620 loss: 5.3911 loss_prob: 3.1829 loss_thr: 1.2122 loss_db: 0.9960 2022/11/01 12:55:59 - mmengine - INFO - Epoch(train) [8][40/63] lr: 7.2281e-05 eta: 1 day, 10:13:03 time: 0.6825 data_time: 0.0053 memory: 17620 loss: 5.4176 loss_prob: 3.2158 loss_thr: 1.2040 loss_db: 0.9978 2022/11/01 12:56:03 - mmengine - INFO - Epoch(train) [8][45/63] lr: 7.2281e-05 eta: 1 day, 10:13:03 time: 0.6900 data_time: 0.0054 memory: 17620 loss: 5.4281 loss_prob: 3.2301 loss_thr: 1.1996 loss_db: 0.9984 2022/11/01 12:56:06 - mmengine - INFO - Epoch(train) [8][50/63] lr: 7.2281e-05 eta: 1 day, 9:50:11 time: 0.7533 data_time: 0.0273 memory: 17620 loss: 5.4380 loss_prob: 3.2407 loss_thr: 1.1991 loss_db: 0.9982 2022/11/01 12:56:09 - mmengine - INFO - Epoch(train) [8][55/63] lr: 7.2281e-05 eta: 1 day, 9:50:11 time: 0.6742 data_time: 0.0289 memory: 17620 loss: 5.4551 loss_prob: 3.2496 loss_thr: 1.2074 loss_db: 0.9981 2022/11/01 12:56:15 - mmengine - INFO - Epoch(train) [8][60/63] lr: 7.2281e-05 eta: 1 day, 9:30:29 time: 0.8443 data_time: 0.0068 memory: 17620 loss: 5.4432 loss_prob: 3.2309 loss_thr: 1.2148 loss_db: 0.9976 2022/11/01 12:56:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:56:24 - mmengine - INFO - Epoch(train) [9][5/63] lr: 8.2322e-05 eta: 1 day, 9:30:29 time: 1.1760 data_time: 0.2303 memory: 17620 loss: 5.4358 loss_prob: 3.2213 loss_thr: 1.2169 loss_db: 0.9977 2022/11/01 12:56:29 - mmengine - INFO - Epoch(train) [9][10/63] lr: 8.2322e-05 eta: 1 day, 9:08:57 time: 1.2175 data_time: 0.2300 memory: 17620 loss: 5.3987 loss_prob: 3.1950 loss_thr: 1.2064 loss_db: 0.9973 2022/11/01 12:56:32 - mmengine - INFO - Epoch(train) [9][15/63] lr: 8.2322e-05 eta: 1 day, 9:08:57 time: 0.8130 data_time: 0.0073 memory: 17620 loss: 5.3722 loss_prob: 3.1677 loss_thr: 1.2066 loss_db: 0.9979 2022/11/01 12:56:39 - mmengine - INFO - Epoch(train) [9][20/63] lr: 8.2322e-05 eta: 1 day, 8:53:50 time: 0.9676 data_time: 0.0074 memory: 17620 loss: 5.4044 loss_prob: 3.2047 loss_thr: 1.2011 loss_db: 0.9986 2022/11/01 12:56:44 - mmengine - INFO - Epoch(train) [9][25/63] lr: 8.2322e-05 eta: 1 day, 8:53:50 time: 1.1954 data_time: 0.0323 memory: 17620 loss: 5.3894 loss_prob: 3.1974 loss_thr: 1.1932 loss_db: 0.9988 2022/11/01 12:56:48 - mmengine - INFO - Epoch(train) [9][30/63] lr: 8.2322e-05 eta: 1 day, 8:39:35 time: 0.9805 data_time: 0.0323 memory: 17620 loss: 5.3354 loss_prob: 3.1495 loss_thr: 1.1868 loss_db: 0.9990 2022/11/01 12:56:53 - mmengine - INFO - Epoch(train) [9][35/63] lr: 8.2322e-05 eta: 1 day, 8:39:35 time: 0.9391 data_time: 0.0083 memory: 17620 loss: 5.3276 loss_prob: 3.1359 loss_thr: 1.1923 loss_db: 0.9994 2022/11/01 12:56:57 - mmengine - INFO - Epoch(train) [9][40/63] lr: 8.2322e-05 eta: 1 day, 8:24:04 time: 0.9032 data_time: 0.0150 memory: 17620 loss: 5.3075 loss_prob: 3.1187 loss_thr: 1.1893 loss_db: 0.9995 2022/11/01 12:57:01 - mmengine - INFO - Epoch(train) [9][45/63] lr: 8.2322e-05 eta: 1 day, 8:24:04 time: 0.7911 data_time: 0.0114 memory: 17620 loss: 5.3283 loss_prob: 3.1326 loss_thr: 1.1964 loss_db: 0.9993 2022/11/01 12:57:05 - mmengine - INFO - Epoch(train) [9][50/63] lr: 8.2322e-05 eta: 1 day, 8:07:06 time: 0.8135 data_time: 0.0457 memory: 17620 loss: 5.2894 loss_prob: 3.0948 loss_thr: 1.1955 loss_db: 0.9991 2022/11/01 12:57:11 - mmengine - INFO - Epoch(train) [9][55/63] lr: 8.2322e-05 eta: 1 day, 8:07:06 time: 1.0052 data_time: 0.0465 memory: 17620 loss: 5.2398 loss_prob: 3.0559 loss_thr: 1.1846 loss_db: 0.9993 2022/11/01 12:57:17 - mmengine - INFO - Epoch(train) [9][60/63] lr: 8.2322e-05 eta: 1 day, 7:58:57 time: 1.1848 data_time: 0.0084 memory: 17620 loss: 5.2694 loss_prob: 3.0794 loss_thr: 1.1905 loss_db: 0.9995 2022/11/01 12:57:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:57:27 - mmengine - INFO - Epoch(train) [10][5/63] lr: 9.2362e-05 eta: 1 day, 7:58:57 time: 1.2490 data_time: 0.2243 memory: 17620 loss: 5.2545 loss_prob: 3.0714 loss_thr: 1.1837 loss_db: 0.9995 2022/11/01 12:57:34 - mmengine - INFO - Epoch(train) [10][10/63] lr: 9.2362e-05 eta: 1 day, 7:45:47 time: 1.4025 data_time: 0.2292 memory: 17620 loss: 5.2281 loss_prob: 3.0422 loss_thr: 1.1865 loss_db: 0.9994 2022/11/01 12:57:38 - mmengine - INFO - Epoch(train) [10][15/63] lr: 9.2362e-05 eta: 1 day, 7:45:47 time: 1.0414 data_time: 0.0096 memory: 17620 loss: 5.2462 loss_prob: 3.0601 loss_thr: 1.1866 loss_db: 0.9995 2022/11/01 12:57:44 - mmengine - INFO - Epoch(train) [10][20/63] lr: 9.2362e-05 eta: 1 day, 7:34:58 time: 1.0286 data_time: 0.0058 memory: 17620 loss: 5.2049 loss_prob: 3.0290 loss_thr: 1.1761 loss_db: 0.9997 2022/11/01 12:57:50 - mmengine - INFO - Epoch(train) [10][25/63] lr: 9.2362e-05 eta: 1 day, 7:34:58 time: 1.1803 data_time: 0.0153 memory: 17620 loss: 5.1752 loss_prob: 3.0006 loss_thr: 1.1751 loss_db: 0.9995 2022/11/01 12:57:55 - mmengine - INFO - Epoch(train) [10][30/63] lr: 9.2362e-05 eta: 1 day, 7:26:20 time: 1.1152 data_time: 0.0277 memory: 17620 loss: 5.2139 loss_prob: 3.0249 loss_thr: 1.1900 loss_db: 0.9990 2022/11/01 12:57:58 - mmengine - INFO - Epoch(train) [10][35/63] lr: 9.2362e-05 eta: 1 day, 7:26:20 time: 0.8783 data_time: 0.0300 memory: 17620 loss: 5.1999 loss_prob: 3.0142 loss_thr: 1.1866 loss_db: 0.9991 2022/11/01 12:58:02 - mmengine - INFO - Epoch(train) [10][40/63] lr: 9.2362e-05 eta: 1 day, 7:08:47 time: 0.6687 data_time: 0.0166 memory: 17620 loss: 5.1686 loss_prob: 2.9951 loss_thr: 1.1740 loss_db: 0.9995 2022/11/01 12:58:07 - mmengine - INFO - Epoch(train) [10][45/63] lr: 9.2362e-05 eta: 1 day, 7:08:47 time: 0.8235 data_time: 0.0072 memory: 17620 loss: 5.2110 loss_prob: 3.0321 loss_thr: 1.1794 loss_db: 0.9995 2022/11/01 12:58:12 - mmengine - INFO - Epoch(train) [10][50/63] lr: 9.2362e-05 eta: 1 day, 6:58:36 time: 1.0053 data_time: 0.0212 memory: 17620 loss: 5.2302 loss_prob: 3.0529 loss_thr: 1.1777 loss_db: 0.9996 2022/11/01 12:58:15 - mmengine - INFO - Epoch(train) [10][55/63] lr: 9.2362e-05 eta: 1 day, 6:58:36 time: 0.8579 data_time: 0.0225 memory: 17620 loss: 5.1937 loss_prob: 3.0206 loss_thr: 1.1733 loss_db: 0.9998 2022/11/01 12:58:19 - mmengine - INFO - Epoch(train) [10][60/63] lr: 9.2362e-05 eta: 1 day, 6:43:47 time: 0.7555 data_time: 0.0114 memory: 17620 loss: 5.1840 loss_prob: 3.0065 loss_thr: 1.1778 loss_db: 0.9997 2022/11/01 12:58:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:58:28 - mmengine - INFO - Epoch(train) [11][5/63] lr: 1.0240e-04 eta: 1 day, 6:43:47 time: 0.9925 data_time: 0.1914 memory: 17620 loss: 5.2433 loss_prob: 3.0591 loss_thr: 1.1846 loss_db: 0.9996 2022/11/01 12:58:34 - mmengine - INFO - Epoch(train) [11][10/63] lr: 1.0240e-04 eta: 1 day, 6:30:53 time: 1.2740 data_time: 0.1955 memory: 17620 loss: 5.1839 loss_prob: 3.0087 loss_thr: 1.1756 loss_db: 0.9995 2022/11/01 12:58:39 - mmengine - INFO - Epoch(train) [11][15/63] lr: 1.0240e-04 eta: 1 day, 6:30:53 time: 1.1238 data_time: 0.0085 memory: 17620 loss: 5.2221 loss_prob: 3.0413 loss_thr: 1.1812 loss_db: 0.9996 2022/11/01 12:58:42 - mmengine - INFO - Epoch(train) [11][20/63] lr: 1.0240e-04 eta: 1 day, 6:18:37 time: 0.8401 data_time: 0.0048 memory: 17620 loss: 5.2838 loss_prob: 3.0932 loss_thr: 1.1911 loss_db: 0.9995 2022/11/01 12:58:46 - mmengine - INFO - Epoch(train) [11][25/63] lr: 1.0240e-04 eta: 1 day, 6:18:37 time: 0.6855 data_time: 0.0164 memory: 17620 loss: 5.2481 loss_prob: 3.0599 loss_thr: 1.1888 loss_db: 0.9994 2022/11/01 12:58:49 - mmengine - INFO - Epoch(train) [11][30/63] lr: 1.0240e-04 eta: 1 day, 6:04:22 time: 0.7154 data_time: 0.0369 memory: 17620 loss: 5.2204 loss_prob: 3.0375 loss_thr: 1.1832 loss_db: 0.9997 2022/11/01 12:58:55 - mmengine - INFO - Epoch(train) [11][35/63] lr: 1.0240e-04 eta: 1 day, 6:04:22 time: 0.8892 data_time: 0.0301 memory: 17620 loss: 5.2062 loss_prob: 3.0261 loss_thr: 1.1803 loss_db: 0.9998 2022/11/01 12:58:59 - mmengine - INFO - Epoch(train) [11][40/63] lr: 1.0240e-04 eta: 1 day, 5:54:51 time: 0.9473 data_time: 0.0091 memory: 17620 loss: 5.1873 loss_prob: 3.0063 loss_thr: 1.1812 loss_db: 0.9997 2022/11/01 12:59:03 - mmengine - INFO - Epoch(train) [11][45/63] lr: 1.0240e-04 eta: 1 day, 5:54:51 time: 0.8003 data_time: 0.0048 memory: 17620 loss: 5.1920 loss_prob: 3.0165 loss_thr: 1.1762 loss_db: 0.9994 2022/11/01 12:59:09 - mmengine - INFO - Epoch(train) [11][50/63] lr: 1.0240e-04 eta: 1 day, 5:46:49 time: 1.0125 data_time: 0.0146 memory: 17620 loss: 5.2023 loss_prob: 3.0271 loss_thr: 1.1760 loss_db: 0.9993 2022/11/01 12:59:12 - mmengine - INFO - Epoch(train) [11][55/63] lr: 1.0240e-04 eta: 1 day, 5:46:49 time: 0.9568 data_time: 0.0196 memory: 17620 loss: 5.1949 loss_prob: 3.0147 loss_thr: 1.1806 loss_db: 0.9996 2022/11/01 12:59:16 - mmengine - INFO - Epoch(train) [11][60/63] lr: 1.0240e-04 eta: 1 day, 5:33:03 time: 0.6841 data_time: 0.0125 memory: 17620 loss: 5.1676 loss_prob: 2.9876 loss_thr: 1.1803 loss_db: 0.9997 2022/11/01 12:59:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 12:59:25 - mmengine - INFO - Epoch(train) [12][5/63] lr: 1.1244e-04 eta: 1 day, 5:33:03 time: 1.0836 data_time: 0.2207 memory: 17620 loss: 5.1679 loss_prob: 2.9838 loss_thr: 1.1845 loss_db: 0.9996 2022/11/01 12:59:29 - mmengine - INFO - Epoch(train) [12][10/63] lr: 1.1244e-04 eta: 1 day, 5:20:19 time: 1.1458 data_time: 0.2197 memory: 17620 loss: 5.1558 loss_prob: 2.9773 loss_thr: 1.1789 loss_db: 0.9997 2022/11/01 12:59:33 - mmengine - INFO - Epoch(train) [12][15/63] lr: 1.1244e-04 eta: 1 day, 5:20:19 time: 0.7758 data_time: 0.0048 memory: 17620 loss: 5.1565 loss_prob: 2.9769 loss_thr: 1.1799 loss_db: 0.9998 2022/11/01 12:59:37 - mmengine - INFO - Epoch(train) [12][20/63] lr: 1.1244e-04 eta: 1 day, 5:09:43 time: 0.8179 data_time: 0.0050 memory: 17620 loss: 5.1503 loss_prob: 2.9703 loss_thr: 1.1801 loss_db: 0.9998 2022/11/01 12:59:40 - mmengine - INFO - Epoch(train) [12][25/63] lr: 1.1244e-04 eta: 1 day, 5:09:43 time: 0.7512 data_time: 0.0087 memory: 17620 loss: 5.1281 loss_prob: 2.9527 loss_thr: 1.1756 loss_db: 0.9998 2022/11/01 12:59:47 - mmengine - INFO - Epoch(train) [12][30/63] lr: 1.1244e-04 eta: 1 day, 5:02:05 time: 0.9737 data_time: 0.0490 memory: 17620 loss: 5.1488 loss_prob: 2.9739 loss_thr: 1.1750 loss_db: 0.9998 2022/11/01 12:59:50 - mmengine - INFO - Epoch(train) [12][35/63] lr: 1.1244e-04 eta: 1 day, 5:02:05 time: 0.9480 data_time: 0.0453 memory: 17620 loss: 5.1747 loss_prob: 3.0058 loss_thr: 1.1691 loss_db: 0.9998 2022/11/01 12:59:53 - mmengine - INFO - Epoch(train) [12][40/63] lr: 1.1244e-04 eta: 1 day, 4:48:35 time: 0.6170 data_time: 0.0054 memory: 17620 loss: 5.1504 loss_prob: 2.9835 loss_thr: 1.1670 loss_db: 0.9999 2022/11/01 12:59:57 - mmengine - INFO - Epoch(train) [12][45/63] lr: 1.1244e-04 eta: 1 day, 4:48:35 time: 0.6696 data_time: 0.0059 memory: 17620 loss: 5.1179 loss_prob: 2.9496 loss_thr: 1.1684 loss_db: 0.9999 2022/11/01 13:00:00 - mmengine - INFO - Epoch(train) [12][50/63] lr: 1.1244e-04 eta: 1 day, 4:36:26 time: 0.6746 data_time: 0.0218 memory: 17620 loss: 5.1481 loss_prob: 2.9573 loss_thr: 1.1911 loss_db: 0.9998 2022/11/01 13:00:05 - mmengine - INFO - Epoch(train) [12][55/63] lr: 1.1244e-04 eta: 1 day, 4:36:26 time: 0.8658 data_time: 0.0293 memory: 17620 loss: 5.1846 loss_prob: 2.9952 loss_thr: 1.1896 loss_db: 0.9998 2022/11/01 13:00:10 - mmengine - INFO - Epoch(train) [12][60/63] lr: 1.1244e-04 eta: 1 day, 4:30:37 time: 1.0385 data_time: 0.0129 memory: 17620 loss: 5.1795 loss_prob: 3.0092 loss_thr: 1.1704 loss_db: 0.9999 2022/11/01 13:00:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:00:19 - mmengine - INFO - Epoch(train) [13][5/63] lr: 1.2248e-04 eta: 1 day, 4:30:37 time: 1.0694 data_time: 0.2312 memory: 17620 loss: 5.1720 loss_prob: 2.9943 loss_thr: 1.1778 loss_db: 0.9998 2022/11/01 13:00:23 - mmengine - INFO - Epoch(train) [13][10/63] lr: 1.2248e-04 eta: 1 day, 4:18:43 time: 1.0705 data_time: 0.2404 memory: 17620 loss: 5.1400 loss_prob: 2.9653 loss_thr: 1.1749 loss_db: 0.9998 2022/11/01 13:00:27 - mmengine - INFO - Epoch(train) [13][15/63] lr: 1.2248e-04 eta: 1 day, 4:18:43 time: 0.8773 data_time: 0.0171 memory: 17620 loss: 5.1153 loss_prob: 2.9467 loss_thr: 1.1687 loss_db: 0.9999 2022/11/01 13:00:31 - mmengine - INFO - Epoch(train) [13][20/63] lr: 1.2248e-04 eta: 1 day, 4:09:15 time: 0.7867 data_time: 0.0104 memory: 17620 loss: 5.1580 loss_prob: 2.9861 loss_thr: 1.1720 loss_db: 0.9999 2022/11/01 13:00:35 - mmengine - INFO - Epoch(train) [13][25/63] lr: 1.2248e-04 eta: 1 day, 4:09:15 time: 0.7545 data_time: 0.0248 memory: 17620 loss: 5.1898 loss_prob: 3.0068 loss_thr: 1.1833 loss_db: 0.9996 2022/11/01 13:00:39 - mmengine - INFO - Epoch(train) [13][30/63] lr: 1.2248e-04 eta: 1 day, 3:59:28 time: 0.7530 data_time: 0.0503 memory: 17620 loss: 5.1462 loss_prob: 2.9602 loss_thr: 1.1864 loss_db: 0.9995 2022/11/01 13:00:41 - mmengine - INFO - Epoch(train) [13][35/63] lr: 1.2248e-04 eta: 1 day, 3:59:28 time: 0.6505 data_time: 0.0328 memory: 17620 loss: 5.1350 loss_prob: 2.9598 loss_thr: 1.1754 loss_db: 0.9997 2022/11/01 13:00:45 - mmengine - INFO - Epoch(train) [13][40/63] lr: 1.2248e-04 eta: 1 day, 3:48:27 time: 0.6574 data_time: 0.0064 memory: 17620 loss: 5.1316 loss_prob: 2.9649 loss_thr: 1.1669 loss_db: 0.9998 2022/11/01 13:00:49 - mmengine - INFO - Epoch(train) [13][45/63] lr: 1.2248e-04 eta: 1 day, 3:48:27 time: 0.7312 data_time: 0.0104 memory: 17620 loss: 5.1273 loss_prob: 2.9572 loss_thr: 1.1704 loss_db: 0.9998 2022/11/01 13:00:53 - mmengine - INFO - Epoch(train) [13][50/63] lr: 1.2248e-04 eta: 1 day, 3:38:45 time: 0.7259 data_time: 0.0176 memory: 17620 loss: 5.1224 loss_prob: 2.9584 loss_thr: 1.1644 loss_db: 0.9996 2022/11/01 13:00:57 - mmengine - INFO - Epoch(train) [13][55/63] lr: 1.2248e-04 eta: 1 day, 3:38:45 time: 0.7957 data_time: 0.0229 memory: 17620 loss: 5.1100 loss_prob: 2.9452 loss_thr: 1.1650 loss_db: 0.9998 2022/11/01 13:01:03 - mmengine - INFO - Epoch(train) [13][60/63] lr: 1.2248e-04 eta: 1 day, 3:33:29 time: 1.0003 data_time: 0.0159 memory: 17620 loss: 5.1006 loss_prob: 2.9386 loss_thr: 1.1624 loss_db: 0.9995 2022/11/01 13:01:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:01:12 - mmengine - INFO - Epoch(train) [14][5/63] lr: 1.3252e-04 eta: 1 day, 3:33:29 time: 1.2216 data_time: 0.1840 memory: 17620 loss: 5.2053 loss_prob: 3.0312 loss_thr: 1.1746 loss_db: 0.9995 2022/11/01 13:01:15 - mmengine - INFO - Epoch(train) [14][10/63] lr: 1.3252e-04 eta: 1 day, 3:22:44 time: 1.0278 data_time: 0.1874 memory: 17620 loss: 5.2071 loss_prob: 3.0267 loss_thr: 1.1806 loss_db: 0.9998 2022/11/01 13:01:20 - mmengine - INFO - Epoch(train) [14][15/63] lr: 1.3252e-04 eta: 1 day, 3:22:44 time: 0.7721 data_time: 0.0092 memory: 17620 loss: 5.1894 loss_prob: 2.9991 loss_thr: 1.1909 loss_db: 0.9994 2022/11/01 13:01:23 - mmengine - INFO - Epoch(train) [14][20/63] lr: 1.3252e-04 eta: 1 day, 3:14:28 time: 0.7766 data_time: 0.0053 memory: 17620 loss: 5.1972 loss_prob: 3.0116 loss_thr: 1.1862 loss_db: 0.9994 2022/11/01 13:01:27 - mmengine - INFO - Epoch(train) [14][25/63] lr: 1.3252e-04 eta: 1 day, 3:14:28 time: 0.6471 data_time: 0.0239 memory: 17620 loss: 5.1568 loss_prob: 2.9892 loss_thr: 1.1680 loss_db: 0.9996 2022/11/01 13:01:32 - mmengine - INFO - Epoch(train) [14][30/63] lr: 1.3252e-04 eta: 1 day, 3:07:43 time: 0.8674 data_time: 0.0404 memory: 17620 loss: 5.1364 loss_prob: 2.9683 loss_thr: 1.1684 loss_db: 0.9997 2022/11/01 13:01:38 - mmengine - INFO - Epoch(train) [14][35/63] lr: 1.3252e-04 eta: 1 day, 3:07:43 time: 1.1687 data_time: 0.0230 memory: 17620 loss: 5.1222 loss_prob: 2.9595 loss_thr: 1.1628 loss_db: 0.9999 2022/11/01 13:01:43 - mmengine - INFO - Epoch(train) [14][40/63] lr: 1.3252e-04 eta: 1 day, 3:04:29 time: 1.0985 data_time: 0.0060 memory: 17620 loss: 5.1056 loss_prob: 2.9461 loss_thr: 1.1597 loss_db: 0.9998 2022/11/01 13:01:46 - mmengine - INFO - Epoch(train) [14][45/63] lr: 1.3252e-04 eta: 1 day, 3:04:29 time: 0.8023 data_time: 0.0048 memory: 17620 loss: 5.1399 loss_prob: 2.9734 loss_thr: 1.1669 loss_db: 0.9996 2022/11/01 13:01:50 - mmengine - INFO - Epoch(train) [14][50/63] lr: 1.3252e-04 eta: 1 day, 2:56:24 time: 0.7553 data_time: 0.0125 memory: 17620 loss: 5.1377 loss_prob: 2.9699 loss_thr: 1.1682 loss_db: 0.9996 2022/11/01 13:01:54 - mmengine - INFO - Epoch(train) [14][55/63] lr: 1.3252e-04 eta: 1 day, 2:56:24 time: 0.7524 data_time: 0.0237 memory: 17620 loss: 5.1550 loss_prob: 2.9845 loss_thr: 1.1710 loss_db: 0.9995 2022/11/01 13:01:59 - mmengine - INFO - Epoch(train) [14][60/63] lr: 1.3252e-04 eta: 1 day, 2:50:03 time: 0.8639 data_time: 0.0177 memory: 17620 loss: 5.2534 loss_prob: 3.0674 loss_thr: 1.1865 loss_db: 0.9996 2022/11/01 13:02:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:02:08 - mmengine - INFO - Epoch(train) [15][5/63] lr: 1.4256e-04 eta: 1 day, 2:50:03 time: 1.1006 data_time: 0.2174 memory: 17620 loss: 5.2818 loss_prob: 3.0834 loss_thr: 1.1989 loss_db: 0.9995 2022/11/01 13:02:14 - mmengine - INFO - Epoch(train) [15][10/63] lr: 1.4256e-04 eta: 1 day, 2:44:32 time: 1.3057 data_time: 0.2179 memory: 17620 loss: 5.2494 loss_prob: 3.0583 loss_thr: 1.1913 loss_db: 0.9997 2022/11/01 13:02:17 - mmengine - INFO - Epoch(train) [15][15/63] lr: 1.4256e-04 eta: 1 day, 2:44:32 time: 0.9918 data_time: 0.0101 memory: 17620 loss: 5.2082 loss_prob: 3.0279 loss_thr: 1.1804 loss_db: 0.9999 2022/11/01 13:02:23 - mmengine - INFO - Epoch(train) [15][20/63] lr: 1.4256e-04 eta: 1 day, 2:39:35 time: 0.9458 data_time: 0.0087 memory: 17620 loss: 5.2152 loss_prob: 3.0366 loss_thr: 1.1786 loss_db: 0.9999 2022/11/01 13:02:27 - mmengine - INFO - Epoch(train) [15][25/63] lr: 1.4256e-04 eta: 1 day, 2:39:35 time: 0.9419 data_time: 0.0249 memory: 17620 loss: 5.2009 loss_prob: 3.0284 loss_thr: 1.1727 loss_db: 0.9998 2022/11/01 13:02:30 - mmengine - INFO - Epoch(train) [15][30/63] lr: 1.4256e-04 eta: 1 day, 2:31:28 time: 0.7055 data_time: 0.0519 memory: 17620 loss: 5.1826 loss_prob: 3.0139 loss_thr: 1.1689 loss_db: 0.9998 2022/11/01 13:02:36 - mmengine - INFO - Epoch(train) [15][35/63] lr: 1.4256e-04 eta: 1 day, 2:31:28 time: 0.8726 data_time: 0.0367 memory: 17620 loss: 5.1781 loss_prob: 3.0080 loss_thr: 1.1704 loss_db: 0.9996 2022/11/01 13:02:40 - mmengine - INFO - Epoch(train) [15][40/63] lr: 1.4256e-04 eta: 1 day, 2:26:32 time: 0.9287 data_time: 0.0099 memory: 17620 loss: 5.1809 loss_prob: 3.0090 loss_thr: 1.1723 loss_db: 0.9996 2022/11/01 13:02:43 - mmengine - INFO - Epoch(train) [15][45/63] lr: 1.4256e-04 eta: 1 day, 2:26:32 time: 0.7457 data_time: 0.0051 memory: 17620 loss: 5.1506 loss_prob: 2.9844 loss_thr: 1.1663 loss_db: 0.9998 2022/11/01 13:02:46 - mmengine - INFO - Epoch(train) [15][50/63] lr: 1.4256e-04 eta: 1 day, 2:18:19 time: 0.6764 data_time: 0.0169 memory: 17620 loss: 5.0860 loss_prob: 2.9276 loss_thr: 1.1585 loss_db: 0.9999 2022/11/01 13:02:52 - mmengine - INFO - Epoch(train) [15][55/63] lr: 1.4256e-04 eta: 1 day, 2:18:19 time: 0.8735 data_time: 0.0283 memory: 17620 loss: 5.0923 loss_prob: 2.9333 loss_thr: 1.1590 loss_db: 0.9999 2022/11/01 13:02:57 - mmengine - INFO - Epoch(train) [15][60/63] lr: 1.4256e-04 eta: 1 day, 2:15:30 time: 1.0708 data_time: 0.0187 memory: 17620 loss: 5.2798 loss_prob: 3.0980 loss_thr: 1.1838 loss_db: 0.9979 2022/11/01 13:02:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:03:06 - mmengine - INFO - Epoch(train) [16][5/63] lr: 1.5260e-04 eta: 1 day, 2:15:30 time: 1.1397 data_time: 0.2271 memory: 17620 loss: 5.3496 loss_prob: 3.1482 loss_thr: 1.2020 loss_db: 0.9993 2022/11/01 13:03:12 - mmengine - INFO - Epoch(train) [16][10/63] lr: 1.5260e-04 eta: 1 day, 2:10:54 time: 1.3138 data_time: 0.2299 memory: 17620 loss: 5.3285 loss_prob: 3.1331 loss_thr: 1.1961 loss_db: 0.9993 2022/11/01 13:03:16 - mmengine - INFO - Epoch(train) [16][15/63] lr: 1.5260e-04 eta: 1 day, 2:10:54 time: 0.9997 data_time: 0.0109 memory: 17620 loss: 5.2859 loss_prob: 3.0956 loss_thr: 1.1911 loss_db: 0.9993 2022/11/01 13:03:21 - mmengine - INFO - Epoch(train) [16][20/63] lr: 1.5260e-04 eta: 1 day, 2:04:50 time: 0.8089 data_time: 0.0104 memory: 17620 loss: 5.2953 loss_prob: 3.1021 loss_thr: 1.1938 loss_db: 0.9994 2022/11/01 13:03:25 - mmengine - INFO - Epoch(train) [16][25/63] lr: 1.5260e-04 eta: 1 day, 2:04:50 time: 0.8889 data_time: 0.0138 memory: 17620 loss: 5.2716 loss_prob: 3.0788 loss_thr: 1.1935 loss_db: 0.9992 2022/11/01 13:03:31 - mmengine - INFO - Epoch(train) [16][30/63] lr: 1.5260e-04 eta: 1 day, 2:01:45 time: 1.0322 data_time: 0.0239 memory: 17620 loss: 5.2681 loss_prob: 3.0727 loss_thr: 1.1959 loss_db: 0.9994 2022/11/01 13:03:34 - mmengine - INFO - Epoch(train) [16][35/63] lr: 1.5260e-04 eta: 1 day, 2:01:45 time: 0.9213 data_time: 0.0247 memory: 17620 loss: 5.2560 loss_prob: 3.0768 loss_thr: 1.1795 loss_db: 0.9998 2022/11/01 13:03:38 - mmengine - INFO - Epoch(train) [16][40/63] lr: 1.5260e-04 eta: 1 day, 1:54:39 time: 0.7098 data_time: 0.0104 memory: 17620 loss: 5.2375 loss_prob: 3.0713 loss_thr: 1.1665 loss_db: 0.9998 2022/11/01 13:03:44 - mmengine - INFO - Epoch(train) [16][45/63] lr: 1.5260e-04 eta: 1 day, 1:54:39 time: 0.9017 data_time: 0.0084 memory: 17620 loss: 5.2099 loss_prob: 3.0425 loss_thr: 1.1678 loss_db: 0.9996 2022/11/01 13:03:47 - mmengine - INFO - Epoch(train) [16][50/63] lr: 1.5260e-04 eta: 1 day, 1:49:56 time: 0.8894 data_time: 0.0235 memory: 17620 loss: 5.2005 loss_prob: 3.0280 loss_thr: 1.1730 loss_db: 0.9995 2022/11/01 13:03:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:03:51 - mmengine - INFO - Epoch(train) [16][55/63] lr: 1.5260e-04 eta: 1 day, 1:49:56 time: 0.7483 data_time: 0.0275 memory: 17620 loss: 5.2115 loss_prob: 3.0374 loss_thr: 1.1744 loss_db: 0.9996 2022/11/01 13:03:55 - mmengine - INFO - Epoch(train) [16][60/63] lr: 1.5260e-04 eta: 1 day, 1:44:04 time: 0.7890 data_time: 0.0163 memory: 17620 loss: 5.2069 loss_prob: 3.0434 loss_thr: 1.1639 loss_db: 0.9997 2022/11/01 13:03:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:04:03 - mmengine - INFO - Epoch(train) [17][5/63] lr: 1.6264e-04 eta: 1 day, 1:44:04 time: 0.9506 data_time: 0.1908 memory: 17620 loss: 5.1791 loss_prob: 3.0155 loss_thr: 1.1640 loss_db: 0.9996 2022/11/01 13:04:06 - mmengine - INFO - Epoch(train) [17][10/63] lr: 1.6264e-04 eta: 1 day, 1:36:02 time: 0.9786 data_time: 0.1956 memory: 17620 loss: 5.1975 loss_prob: 3.0298 loss_thr: 1.1684 loss_db: 0.9992 2022/11/01 13:04:12 - mmengine - INFO - Epoch(train) [17][15/63] lr: 1.6264e-04 eta: 1 day, 1:36:02 time: 0.9551 data_time: 0.0094 memory: 17620 loss: 5.2101 loss_prob: 3.0485 loss_thr: 1.1622 loss_db: 0.9994 2022/11/01 13:04:18 - mmengine - INFO - Epoch(train) [17][20/63] lr: 1.6264e-04 eta: 1 day, 1:35:10 time: 1.1820 data_time: 0.0047 memory: 17620 loss: 5.2136 loss_prob: 3.0468 loss_thr: 1.1675 loss_db: 0.9993 2022/11/01 13:04:22 - mmengine - INFO - Epoch(train) [17][25/63] lr: 1.6264e-04 eta: 1 day, 1:35:10 time: 0.9537 data_time: 0.0161 memory: 17620 loss: 5.2364 loss_prob: 3.0677 loss_thr: 1.1696 loss_db: 0.9991 2022/11/01 13:04:26 - mmengine - INFO - Epoch(train) [17][30/63] lr: 1.6264e-04 eta: 1 day, 1:29:12 time: 0.7540 data_time: 0.0402 memory: 17620 loss: 5.2282 loss_prob: 3.0654 loss_thr: 1.1633 loss_db: 0.9996 2022/11/01 13:04:30 - mmengine - INFO - Epoch(train) [17][35/63] lr: 1.6264e-04 eta: 1 day, 1:29:12 time: 0.8131 data_time: 0.0302 memory: 17620 loss: 5.2171 loss_prob: 3.0513 loss_thr: 1.1661 loss_db: 0.9997 2022/11/01 13:04:36 - mmengine - INFO - Epoch(train) [17][40/63] lr: 1.6264e-04 eta: 1 day, 1:26:22 time: 1.0078 data_time: 0.0061 memory: 17620 loss: 5.2045 loss_prob: 3.0308 loss_thr: 1.1741 loss_db: 0.9997 2022/11/01 13:04:40 - mmengine - INFO - Epoch(train) [17][45/63] lr: 1.6264e-04 eta: 1 day, 1:26:22 time: 0.9906 data_time: 0.0056 memory: 17620 loss: 5.1630 loss_prob: 2.9927 loss_thr: 1.1706 loss_db: 0.9997 2022/11/01 13:04:44 - mmengine - INFO - Epoch(train) [17][50/63] lr: 1.6264e-04 eta: 1 day, 1:21:22 time: 0.8212 data_time: 0.0154 memory: 17620 loss: 5.1374 loss_prob: 2.9706 loss_thr: 1.1674 loss_db: 0.9994 2022/11/01 13:04:48 - mmengine - INFO - Epoch(train) [17][55/63] lr: 1.6264e-04 eta: 1 day, 1:21:22 time: 0.8642 data_time: 0.0261 memory: 17620 loss: 5.1303 loss_prob: 2.9632 loss_thr: 1.1676 loss_db: 0.9994 2022/11/01 13:04:55 - mmengine - INFO - Epoch(train) [17][60/63] lr: 1.6264e-04 eta: 1 day, 1:19:18 time: 1.0632 data_time: 0.0187 memory: 17620 loss: 5.1104 loss_prob: 2.9548 loss_thr: 1.1562 loss_db: 0.9994 2022/11/01 13:04:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:05:03 - mmengine - INFO - Epoch(train) [18][5/63] lr: 1.7268e-04 eta: 1 day, 1:19:18 time: 1.1117 data_time: 0.2169 memory: 17620 loss: 5.0970 loss_prob: 2.9432 loss_thr: 1.1545 loss_db: 0.9992 2022/11/01 13:05:07 - mmengine - INFO - Epoch(train) [18][10/63] lr: 1.7268e-04 eta: 1 day, 1:12:04 time: 0.9841 data_time: 0.2237 memory: 17620 loss: 5.1319 loss_prob: 2.9642 loss_thr: 1.1684 loss_db: 0.9993 2022/11/01 13:05:12 - mmengine - INFO - Epoch(train) [18][15/63] lr: 1.7268e-04 eta: 1 day, 1:12:04 time: 0.8544 data_time: 0.0131 memory: 17620 loss: 5.0997 loss_prob: 2.9403 loss_thr: 1.1603 loss_db: 0.9991 2022/11/01 13:05:16 - mmengine - INFO - Epoch(train) [18][20/63] lr: 1.7268e-04 eta: 1 day, 1:07:48 time: 0.8604 data_time: 0.0066 memory: 17620 loss: 5.0856 loss_prob: 2.9173 loss_thr: 1.1689 loss_db: 0.9994 2022/11/01 13:05:21 - mmengine - INFO - Epoch(train) [18][25/63] lr: 1.7268e-04 eta: 1 day, 1:07:48 time: 0.8821 data_time: 0.0268 memory: 17620 loss: 5.0814 loss_prob: 2.9233 loss_thr: 1.1591 loss_db: 0.9989 2022/11/01 13:05:24 - mmengine - INFO - Epoch(train) [18][30/63] lr: 1.7268e-04 eta: 1 day, 1:03:27 time: 0.8464 data_time: 0.0518 memory: 17620 loss: 5.0725 loss_prob: 2.9216 loss_thr: 1.1521 loss_db: 0.9988 2022/11/01 13:05:29 - mmengine - INFO - Epoch(train) [18][35/63] lr: 1.7268e-04 eta: 1 day, 1:03:27 time: 0.8253 data_time: 0.0333 memory: 17620 loss: 5.0855 loss_prob: 2.9228 loss_thr: 1.1631 loss_db: 0.9995 2022/11/01 13:05:33 - mmengine - INFO - Epoch(train) [18][40/63] lr: 1.7268e-04 eta: 1 day, 0:59:45 time: 0.8982 data_time: 0.0085 memory: 17620 loss: 5.0937 loss_prob: 2.9396 loss_thr: 1.1545 loss_db: 0.9996 2022/11/01 13:05:37 - mmengine - INFO - Epoch(train) [18][45/63] lr: 1.7268e-04 eta: 1 day, 0:59:45 time: 0.8044 data_time: 0.0052 memory: 17620 loss: 5.0849 loss_prob: 2.9333 loss_thr: 1.1534 loss_db: 0.9982 2022/11/01 13:05:42 - mmengine - INFO - Epoch(train) [18][50/63] lr: 1.7268e-04 eta: 1 day, 0:56:13 time: 0.9073 data_time: 0.0183 memory: 17620 loss: 5.0873 loss_prob: 2.9320 loss_thr: 1.1580 loss_db: 0.9973 2022/11/01 13:05:46 - mmengine - INFO - Epoch(train) [18][55/63] lr: 1.7268e-04 eta: 1 day, 0:56:13 time: 0.8855 data_time: 0.0220 memory: 17620 loss: 5.0733 loss_prob: 2.9206 loss_thr: 1.1552 loss_db: 0.9975 2022/11/01 13:05:50 - mmengine - INFO - Epoch(train) [18][60/63] lr: 1.7268e-04 eta: 1 day, 0:51:09 time: 0.7619 data_time: 0.0113 memory: 17620 loss: 5.0593 loss_prob: 2.9174 loss_thr: 1.1454 loss_db: 0.9965 2022/11/01 13:05:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:05:58 - mmengine - INFO - Epoch(train) [19][5/63] lr: 1.8272e-04 eta: 1 day, 0:51:09 time: 0.9122 data_time: 0.2050 memory: 17620 loss: 5.0582 loss_prob: 2.9142 loss_thr: 1.1495 loss_db: 0.9944 2022/11/01 13:06:01 - mmengine - INFO - Epoch(train) [19][10/63] lr: 1.8272e-04 eta: 1 day, 0:42:54 time: 0.8257 data_time: 0.2062 memory: 17620 loss: 5.0731 loss_prob: 2.9218 loss_thr: 1.1597 loss_db: 0.9916 2022/11/01 13:06:03 - mmengine - INFO - Epoch(train) [19][15/63] lr: 1.8272e-04 eta: 1 day, 0:42:54 time: 0.5131 data_time: 0.0086 memory: 17620 loss: 5.0565 loss_prob: 2.9097 loss_thr: 1.1539 loss_db: 0.9929 2022/11/01 13:06:06 - mmengine - INFO - Epoch(train) [19][20/63] lr: 1.8272e-04 eta: 1 day, 0:35:22 time: 0.5121 data_time: 0.0042 memory: 17620 loss: 5.0446 loss_prob: 2.9035 loss_thr: 1.1450 loss_db: 0.9962 2022/11/01 13:06:09 - mmengine - INFO - Epoch(train) [19][25/63] lr: 1.8272e-04 eta: 1 day, 0:35:22 time: 0.5392 data_time: 0.0188 memory: 17620 loss: 5.0980 loss_prob: 2.9591 loss_thr: 1.1509 loss_db: 0.9881 2022/11/01 13:06:11 - mmengine - INFO - Epoch(train) [19][30/63] lr: 1.8272e-04 eta: 1 day, 0:28:20 time: 0.5471 data_time: 0.0271 memory: 17620 loss: 5.1063 loss_prob: 2.9707 loss_thr: 1.1510 loss_db: 0.9846 2022/11/01 13:06:14 - mmengine - INFO - Epoch(train) [19][35/63] lr: 1.8272e-04 eta: 1 day, 0:28:20 time: 0.5548 data_time: 0.0176 memory: 17620 loss: 5.0881 loss_prob: 2.9416 loss_thr: 1.1555 loss_db: 0.9910 2022/11/01 13:06:17 - mmengine - INFO - Epoch(train) [19][40/63] lr: 1.8272e-04 eta: 1 day, 0:21:28 time: 0.5538 data_time: 0.0104 memory: 17620 loss: 5.0843 loss_prob: 2.9312 loss_thr: 1.1699 loss_db: 0.9832 2022/11/01 13:06:19 - mmengine - INFO - Epoch(train) [19][45/63] lr: 1.8272e-04 eta: 1 day, 0:21:28 time: 0.5251 data_time: 0.0053 memory: 17620 loss: 5.0502 loss_prob: 2.9158 loss_thr: 1.1670 loss_db: 0.9674 2022/11/01 13:06:22 - mmengine - INFO - Epoch(train) [19][50/63] lr: 1.8272e-04 eta: 1 day, 0:14:33 time: 0.5359 data_time: 0.0131 memory: 17620 loss: 5.0340 loss_prob: 2.9069 loss_thr: 1.1614 loss_db: 0.9656 2022/11/01 13:06:25 - mmengine - INFO - Epoch(train) [19][55/63] lr: 1.8272e-04 eta: 1 day, 0:14:33 time: 0.5473 data_time: 0.0191 memory: 17620 loss: 5.0237 loss_prob: 2.8947 loss_thr: 1.1652 loss_db: 0.9637 2022/11/01 13:06:27 - mmengine - INFO - Epoch(train) [19][60/63] lr: 1.8272e-04 eta: 1 day, 0:07:40 time: 0.5282 data_time: 0.0146 memory: 17620 loss: 5.0376 loss_prob: 2.9123 loss_thr: 1.1681 loss_db: 0.9572 2022/11/01 13:06:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:06:33 - mmengine - INFO - Epoch(train) [20][5/63] lr: 1.9276e-04 eta: 1 day, 0:07:40 time: 0.6750 data_time: 0.1704 memory: 17620 loss: 5.0749 loss_prob: 2.9437 loss_thr: 1.1918 loss_db: 0.9394 2022/11/01 13:06:36 - mmengine - INFO - Epoch(train) [20][10/63] lr: 1.9276e-04 eta: 23:59:10 time: 0.7150 data_time: 0.1727 memory: 17620 loss: 5.0701 loss_prob: 2.9533 loss_thr: 1.1756 loss_db: 0.9412 2022/11/01 13:06:39 - mmengine - INFO - Epoch(train) [20][15/63] lr: 1.9276e-04 eta: 23:59:10 time: 0.5392 data_time: 0.0094 memory: 17620 loss: 5.0496 loss_prob: 2.9448 loss_thr: 1.1733 loss_db: 0.9314 2022/11/01 13:06:41 - mmengine - INFO - Epoch(train) [20][20/63] lr: 1.9276e-04 eta: 23:52:24 time: 0.5161 data_time: 0.0075 memory: 17620 loss: 5.0169 loss_prob: 2.9222 loss_thr: 1.1564 loss_db: 0.9383 2022/11/01 13:06:44 - mmengine - INFO - Epoch(train) [20][25/63] lr: 1.9276e-04 eta: 23:52:24 time: 0.5135 data_time: 0.0180 memory: 17620 loss: 5.0056 loss_prob: 2.9129 loss_thr: 1.1424 loss_db: 0.9503 2022/11/01 13:06:46 - mmengine - INFO - Epoch(train) [20][30/63] lr: 1.9276e-04 eta: 23:45:58 time: 0.5371 data_time: 0.0283 memory: 17620 loss: 5.0146 loss_prob: 2.9109 loss_thr: 1.1797 loss_db: 0.9240 2022/11/01 13:06:49 - mmengine - INFO - Epoch(train) [20][35/63] lr: 1.9276e-04 eta: 23:45:58 time: 0.5215 data_time: 0.0164 memory: 17620 loss: 5.0534 loss_prob: 2.9305 loss_thr: 1.1908 loss_db: 0.9321 2022/11/01 13:06:51 - mmengine - INFO - Epoch(train) [20][40/63] lr: 1.9276e-04 eta: 23:39:14 time: 0.4983 data_time: 0.0066 memory: 17620 loss: 5.1374 loss_prob: 2.9874 loss_thr: 1.2047 loss_db: 0.9452 2022/11/01 13:06:54 - mmengine - INFO - Epoch(train) [20][45/63] lr: 1.9276e-04 eta: 23:39:14 time: 0.4944 data_time: 0.0078 memory: 17620 loss: 5.1778 loss_prob: 3.0137 loss_thr: 1.2049 loss_db: 0.9592 2022/11/01 13:06:56 - mmengine - INFO - Epoch(train) [20][50/63] lr: 1.9276e-04 eta: 23:32:40 time: 0.5024 data_time: 0.0160 memory: 17620 loss: 5.1461 loss_prob: 2.9952 loss_thr: 1.1612 loss_db: 0.9897 2022/11/01 13:06:59 - mmengine - INFO - Epoch(train) [20][55/63] lr: 1.9276e-04 eta: 23:32:40 time: 0.5226 data_time: 0.0195 memory: 17620 loss: 5.1077 loss_prob: 2.9709 loss_thr: 1.1542 loss_db: 0.9826 2022/11/01 13:07:02 - mmengine - INFO - Epoch(train) [20][60/63] lr: 1.9276e-04 eta: 23:26:24 time: 0.5237 data_time: 0.0118 memory: 17620 loss: 5.1304 loss_prob: 2.9814 loss_thr: 1.1725 loss_db: 0.9765 2022/11/01 13:07:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:07:03 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/11/01 13:09:00 - mmengine - INFO - Epoch(val) [20][5/32] eta: 23:26:24 time: 22.8057 data_time: 20.4801 memory: 40864 2022/11/01 13:09:03 - mmengine - INFO - Epoch(val) [20][10/32] eta: 0:04:16 time: 11.6552 data_time: 10.2838 memory: 15725 2022/11/01 13:09:05 - mmengine - INFO - Epoch(val) [20][15/32] eta: 0:04:16 time: 0.4698 data_time: 0.0499 memory: 15725 2022/11/01 13:09:08 - mmengine - INFO - Epoch(val) [20][20/32] eta: 0:00:05 time: 0.4739 data_time: 0.0550 memory: 15725 2022/11/01 13:09:10 - mmengine - INFO - Epoch(val) [20][25/32] eta: 0:00:05 time: 0.4809 data_time: 0.0635 memory: 15725 2022/11/01 13:09:12 - mmengine - INFO - Epoch(val) [20][30/32] eta: 0:00:00 time: 0.4404 data_time: 0.0203 memory: 15725 2022/11/01 13:09:20 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:09:20 - mmengine - INFO - Epoch(val) [20][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/11/01 13:09:25 - mmengine - INFO - Epoch(train) [21][5/63] lr: 2.0280e-04 eta: 0:00:00 time: 0.6670 data_time: 0.1848 memory: 35421 loss: 5.1377 loss_prob: 3.0002 loss_thr: 1.1801 loss_db: 0.9574 2022/11/01 13:09:27 - mmengine - INFO - Epoch(train) [21][10/63] lr: 2.0280e-04 eta: 23:18:30 time: 0.6916 data_time: 0.1814 memory: 17620 loss: 5.0957 loss_prob: 2.9721 loss_thr: 1.1760 loss_db: 0.9477 2022/11/01 13:09:30 - mmengine - INFO - Epoch(train) [21][15/63] lr: 2.0280e-04 eta: 23:18:30 time: 0.5279 data_time: 0.0053 memory: 17620 loss: 5.0526 loss_prob: 2.9399 loss_thr: 1.1671 loss_db: 0.9457 2022/11/01 13:09:33 - mmengine - INFO - Epoch(train) [21][20/63] lr: 2.0280e-04 eta: 23:12:43 time: 0.5510 data_time: 0.0068 memory: 17620 loss: 5.0133 loss_prob: 2.9235 loss_thr: 1.1677 loss_db: 0.9221 2022/11/01 13:09:35 - mmengine - INFO - Epoch(train) [21][25/63] lr: 2.0280e-04 eta: 23:12:43 time: 0.5455 data_time: 0.0143 memory: 17620 loss: 5.0088 loss_prob: 2.9220 loss_thr: 1.1766 loss_db: 0.9102 2022/11/01 13:09:38 - mmengine - INFO - Epoch(train) [21][30/63] lr: 2.0280e-04 eta: 23:07:01 time: 0.5499 data_time: 0.0336 memory: 17620 loss: 5.0271 loss_prob: 2.9213 loss_thr: 1.1846 loss_db: 0.9212 2022/11/01 13:09:41 - mmengine - INFO - Epoch(train) [21][35/63] lr: 2.0280e-04 eta: 23:07:01 time: 0.5395 data_time: 0.0253 memory: 17620 loss: 5.0252 loss_prob: 2.9218 loss_thr: 1.1728 loss_db: 0.9307 2022/11/01 13:09:43 - mmengine - INFO - Epoch(train) [21][40/63] lr: 2.0280e-04 eta: 23:01:00 time: 0.5074 data_time: 0.0044 memory: 17620 loss: 5.0153 loss_prob: 2.9260 loss_thr: 1.1809 loss_db: 0.9085 2022/11/01 13:09:46 - mmengine - INFO - Epoch(train) [21][45/63] lr: 2.0280e-04 eta: 23:01:00 time: 0.5084 data_time: 0.0059 memory: 17620 loss: 5.0001 loss_prob: 2.9215 loss_thr: 1.1937 loss_db: 0.8849 2022/11/01 13:09:48 - mmengine - INFO - Epoch(train) [21][50/63] lr: 2.0280e-04 eta: 22:55:06 time: 0.5113 data_time: 0.0126 memory: 17620 loss: 4.9510 loss_prob: 2.8983 loss_thr: 1.1757 loss_db: 0.8770 2022/11/01 13:09:51 - mmengine - INFO - Epoch(train) [21][55/63] lr: 2.0280e-04 eta: 22:55:06 time: 0.5306 data_time: 0.0223 memory: 17620 loss: 4.8725 loss_prob: 2.8809 loss_thr: 1.1431 loss_db: 0.8486 2022/11/01 13:09:54 - mmengine - INFO - Epoch(train) [21][60/63] lr: 2.0280e-04 eta: 22:49:28 time: 0.5293 data_time: 0.0159 memory: 17620 loss: 4.9097 loss_prob: 2.8976 loss_thr: 1.1670 loss_db: 0.8450 2022/11/01 13:09:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:10:00 - mmengine - INFO - Epoch(train) [22][5/63] lr: 2.1284e-04 eta: 22:49:28 time: 0.7061 data_time: 0.1849 memory: 17620 loss: 4.9025 loss_prob: 2.8931 loss_thr: 1.1304 loss_db: 0.8789 2022/11/01 13:10:02 - mmengine - INFO - Epoch(train) [22][10/63] lr: 2.1284e-04 eta: 22:42:39 time: 0.7302 data_time: 0.1940 memory: 17620 loss: 4.9505 loss_prob: 2.9062 loss_thr: 1.1485 loss_db: 0.8958 2022/11/01 13:10:05 - mmengine - INFO - Epoch(train) [22][15/63] lr: 2.1284e-04 eta: 22:42:39 time: 0.5529 data_time: 0.0145 memory: 17620 loss: 4.9507 loss_prob: 2.8983 loss_thr: 1.1721 loss_db: 0.8803 2022/11/01 13:10:08 - mmengine - INFO - Epoch(train) [22][20/63] lr: 2.1284e-04 eta: 22:37:22 time: 0.5469 data_time: 0.0053 memory: 17620 loss: 4.9441 loss_prob: 2.9067 loss_thr: 1.1723 loss_db: 0.8651 2022/11/01 13:10:10 - mmengine - INFO - Epoch(train) [22][25/63] lr: 2.1284e-04 eta: 22:37:22 time: 0.5128 data_time: 0.0137 memory: 17620 loss: 4.9473 loss_prob: 2.9132 loss_thr: 1.1660 loss_db: 0.8680 2022/11/01 13:10:13 - mmengine - INFO - Epoch(train) [22][30/63] lr: 2.1284e-04 eta: 22:31:58 time: 0.5265 data_time: 0.0273 memory: 17620 loss: 4.8918 loss_prob: 2.9004 loss_thr: 1.1651 loss_db: 0.8263 2022/11/01 13:10:16 - mmengine - INFO - Epoch(train) [22][35/63] lr: 2.1284e-04 eta: 22:31:58 time: 0.5419 data_time: 0.0262 memory: 17620 loss: 4.8809 loss_prob: 2.8998 loss_thr: 1.1458 loss_db: 0.8353 2022/11/01 13:10:18 - mmengine - INFO - Epoch(train) [22][40/63] lr: 2.1284e-04 eta: 22:26:48 time: 0.5428 data_time: 0.0124 memory: 17620 loss: 4.8946 loss_prob: 2.9082 loss_thr: 1.1326 loss_db: 0.8538 2022/11/01 13:10:21 - mmengine - INFO - Epoch(train) [22][45/63] lr: 2.1284e-04 eta: 22:26:48 time: 0.5364 data_time: 0.0048 memory: 17620 loss: 4.8474 loss_prob: 2.9052 loss_thr: 1.1494 loss_db: 0.7928 2022/11/01 13:10:24 - mmengine - INFO - Epoch(train) [22][50/63] lr: 2.1284e-04 eta: 22:21:39 time: 0.5373 data_time: 0.0137 memory: 17620 loss: 4.8203 loss_prob: 2.8949 loss_thr: 1.1582 loss_db: 0.7672 2022/11/01 13:10:26 - mmengine - INFO - Epoch(train) [22][55/63] lr: 2.1284e-04 eta: 22:21:39 time: 0.5251 data_time: 0.0157 memory: 17620 loss: 4.8708 loss_prob: 2.8947 loss_thr: 1.1430 loss_db: 0.8331 2022/11/01 13:10:29 - mmengine - INFO - Epoch(train) [22][60/63] lr: 2.1284e-04 eta: 22:16:28 time: 0.5260 data_time: 0.0116 memory: 17620 loss: 4.9274 loss_prob: 2.9169 loss_thr: 1.1431 loss_db: 0.8674 2022/11/01 13:10:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:10:35 - mmengine - INFO - Epoch(train) [23][5/63] lr: 2.2288e-04 eta: 22:16:28 time: 0.7286 data_time: 0.2012 memory: 17620 loss: 4.9225 loss_prob: 2.9365 loss_thr: 1.1447 loss_db: 0.8414 2022/11/01 13:10:38 - mmengine - INFO - Epoch(train) [23][10/63] lr: 2.2288e-04 eta: 22:10:37 time: 0.7701 data_time: 0.2048 memory: 17620 loss: 4.8885 loss_prob: 2.9265 loss_thr: 1.1492 loss_db: 0.8128 2022/11/01 13:10:41 - mmengine - INFO - Epoch(train) [23][15/63] lr: 2.2288e-04 eta: 22:10:37 time: 0.5326 data_time: 0.0111 memory: 17620 loss: 4.7838 loss_prob: 2.9206 loss_thr: 1.1234 loss_db: 0.7398 2022/11/01 13:10:43 - mmengine - INFO - Epoch(train) [23][20/63] lr: 2.2288e-04 eta: 22:05:32 time: 0.5180 data_time: 0.0079 memory: 17620 loss: 4.8174 loss_prob: 2.9280 loss_thr: 1.1215 loss_db: 0.7679 2022/11/01 13:10:46 - mmengine - INFO - Epoch(train) [23][25/63] lr: 2.2288e-04 eta: 22:05:32 time: 0.5484 data_time: 0.0296 memory: 17620 loss: 4.8570 loss_prob: 2.9114 loss_thr: 1.1446 loss_db: 0.8010 2022/11/01 13:10:49 - mmengine - INFO - Epoch(train) [23][30/63] lr: 2.2288e-04 eta: 22:00:46 time: 0.5467 data_time: 0.0295 memory: 17620 loss: 4.8279 loss_prob: 2.8967 loss_thr: 1.1211 loss_db: 0.8102 2022/11/01 13:10:51 - mmengine - INFO - Epoch(train) [23][35/63] lr: 2.2288e-04 eta: 22:00:46 time: 0.4986 data_time: 0.0048 memory: 17620 loss: 4.7796 loss_prob: 2.8872 loss_thr: 1.1164 loss_db: 0.7761 2022/11/01 13:10:54 - mmengine - INFO - Epoch(train) [23][40/63] lr: 2.2288e-04 eta: 21:55:44 time: 0.5080 data_time: 0.0071 memory: 17620 loss: 4.7315 loss_prob: 2.8648 loss_thr: 1.1241 loss_db: 0.7426 2022/11/01 13:10:56 - mmengine - INFO - Epoch(train) [23][45/63] lr: 2.2288e-04 eta: 21:55:44 time: 0.5276 data_time: 0.0074 memory: 17620 loss: 4.7344 loss_prob: 2.8629 loss_thr: 1.1173 loss_db: 0.7542 2022/11/01 13:10:59 - mmengine - INFO - Epoch(train) [23][50/63] lr: 2.2288e-04 eta: 21:51:04 time: 0.5426 data_time: 0.0225 memory: 17620 loss: 4.7869 loss_prob: 2.9129 loss_thr: 1.1166 loss_db: 0.7575 2022/11/01 13:11:02 - mmengine - INFO - Epoch(train) [23][55/63] lr: 2.2288e-04 eta: 21:51:04 time: 0.5468 data_time: 0.0241 memory: 17620 loss: 4.7555 loss_prob: 2.9192 loss_thr: 1.1143 loss_db: 0.7220 2022/11/01 13:11:05 - mmengine - INFO - Epoch(train) [23][60/63] lr: 2.2288e-04 eta: 21:46:20 time: 0.5275 data_time: 0.0071 memory: 17620 loss: 4.6257 loss_prob: 2.8631 loss_thr: 1.1003 loss_db: 0.6623 2022/11/01 13:11:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:11:10 - mmengine - INFO - Epoch(train) [24][5/63] lr: 2.3292e-04 eta: 21:46:20 time: 0.6640 data_time: 0.1515 memory: 17620 loss: 4.7290 loss_prob: 2.8810 loss_thr: 1.0956 loss_db: 0.7524 2022/11/01 13:11:13 - mmengine - INFO - Epoch(train) [24][10/63] lr: 2.3292e-04 eta: 21:40:30 time: 0.7129 data_time: 0.1628 memory: 17620 loss: 4.7689 loss_prob: 2.9025 loss_thr: 1.1059 loss_db: 0.7604 2022/11/01 13:11:15 - mmengine - INFO - Epoch(train) [24][15/63] lr: 2.3292e-04 eta: 21:40:30 time: 0.5352 data_time: 0.0176 memory: 17620 loss: 4.8165 loss_prob: 2.9169 loss_thr: 1.1408 loss_db: 0.7588 2022/11/01 13:11:18 - mmengine - INFO - Epoch(train) [24][20/63] lr: 2.3292e-04 eta: 21:35:51 time: 0.5208 data_time: 0.0084 memory: 17620 loss: 4.9043 loss_prob: 2.9314 loss_thr: 1.1350 loss_db: 0.8378 2022/11/01 13:11:21 - mmengine - INFO - Epoch(train) [24][25/63] lr: 2.3292e-04 eta: 21:35:51 time: 0.5431 data_time: 0.0095 memory: 17620 loss: 4.7522 loss_prob: 2.8873 loss_thr: 1.0982 loss_db: 0.7667 2022/11/01 13:11:24 - mmengine - INFO - Epoch(train) [24][30/63] lr: 2.3292e-04 eta: 21:31:29 time: 0.5462 data_time: 0.0178 memory: 17620 loss: 4.6138 loss_prob: 2.8644 loss_thr: 1.1034 loss_db: 0.6461 2022/11/01 13:11:26 - mmengine - INFO - Epoch(train) [24][35/63] lr: 2.3292e-04 eta: 21:31:29 time: 0.5294 data_time: 0.0266 memory: 17620 loss: 4.6968 loss_prob: 2.8971 loss_thr: 1.1035 loss_db: 0.6962 2022/11/01 13:11:29 - mmengine - INFO - Epoch(train) [24][40/63] lr: 2.3292e-04 eta: 21:27:01 time: 0.5292 data_time: 0.0146 memory: 17620 loss: 4.7082 loss_prob: 2.8900 loss_thr: 1.0917 loss_db: 0.7265 2022/11/01 13:11:32 - mmengine - INFO - Epoch(train) [24][45/63] lr: 2.3292e-04 eta: 21:27:01 time: 0.5368 data_time: 0.0084 memory: 17620 loss: 4.6419 loss_prob: 2.8686 loss_thr: 1.0901 loss_db: 0.6832 2022/11/01 13:11:34 - mmengine - INFO - Epoch(train) [24][50/63] lr: 2.3292e-04 eta: 21:22:43 time: 0.5398 data_time: 0.0119 memory: 17620 loss: 4.6069 loss_prob: 2.8467 loss_thr: 1.1124 loss_db: 0.6478 2022/11/01 13:11:37 - mmengine - INFO - Epoch(train) [24][55/63] lr: 2.3292e-04 eta: 21:22:43 time: 0.5445 data_time: 0.0195 memory: 17620 loss: 4.5508 loss_prob: 2.8266 loss_thr: 1.1051 loss_db: 0.6191 2022/11/01 13:11:40 - mmengine - INFO - Epoch(train) [24][60/63] lr: 2.3292e-04 eta: 21:18:32 time: 0.5505 data_time: 0.0203 memory: 17620 loss: 4.5177 loss_prob: 2.8238 loss_thr: 1.0682 loss_db: 0.6256 2022/11/01 13:11:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:11:46 - mmengine - INFO - Epoch(train) [25][5/63] lr: 2.4296e-04 eta: 21:18:32 time: 0.7510 data_time: 0.2116 memory: 17620 loss: 4.4326 loss_prob: 2.7885 loss_thr: 1.0517 loss_db: 0.5924 2022/11/01 13:11:49 - mmengine - INFO - Epoch(train) [25][10/63] lr: 2.4296e-04 eta: 21:13:34 time: 0.7600 data_time: 0.2119 memory: 17620 loss: 4.4599 loss_prob: 2.8049 loss_thr: 1.0540 loss_db: 0.6011 2022/11/01 13:11:51 - mmengine - INFO - Epoch(train) [25][15/63] lr: 2.4296e-04 eta: 21:13:34 time: 0.5078 data_time: 0.0050 memory: 17620 loss: 4.5622 loss_prob: 2.8633 loss_thr: 1.0703 loss_db: 0.6286 2022/11/01 13:11:54 - mmengine - INFO - Epoch(train) [25][20/63] lr: 2.4296e-04 eta: 21:09:12 time: 0.5124 data_time: 0.0047 memory: 17620 loss: 4.6234 loss_prob: 2.8949 loss_thr: 1.0974 loss_db: 0.6311 2022/11/01 13:11:57 - mmengine - INFO - Epoch(train) [25][25/63] lr: 2.4296e-04 eta: 21:09:12 time: 0.5351 data_time: 0.0221 memory: 17620 loss: 4.5638 loss_prob: 2.8691 loss_thr: 1.0783 loss_db: 0.6164 2022/11/01 13:11:59 - mmengine - INFO - Epoch(train) [25][30/63] lr: 2.4296e-04 eta: 21:05:15 time: 0.5561 data_time: 0.0449 memory: 17620 loss: 4.5216 loss_prob: 2.8636 loss_thr: 1.0434 loss_db: 0.6146 2022/11/01 13:12:02 - mmengine - INFO - Epoch(train) [25][35/63] lr: 2.4296e-04 eta: 21:05:15 time: 0.5318 data_time: 0.0274 memory: 17620 loss: 4.5687 loss_prob: 2.8727 loss_thr: 1.0577 loss_db: 0.6383 2022/11/01 13:12:05 - mmengine - INFO - Epoch(train) [25][40/63] lr: 2.4296e-04 eta: 21:01:06 time: 0.5247 data_time: 0.0048 memory: 17620 loss: 4.5635 loss_prob: 2.8490 loss_thr: 1.0722 loss_db: 0.6424 2022/11/01 13:12:07 - mmengine - INFO - Epoch(train) [25][45/63] lr: 2.4296e-04 eta: 21:01:06 time: 0.5193 data_time: 0.0050 memory: 17620 loss: 4.5492 loss_prob: 2.8541 loss_thr: 1.0643 loss_db: 0.6307 2022/11/01 13:12:10 - mmengine - INFO - Epoch(train) [25][50/63] lr: 2.4296e-04 eta: 20:57:00 time: 0.5242 data_time: 0.0162 memory: 17620 loss: 4.6169 loss_prob: 2.8943 loss_thr: 1.0634 loss_db: 0.6593 2022/11/01 13:12:12 - mmengine - INFO - Epoch(train) [25][55/63] lr: 2.4296e-04 eta: 20:57:00 time: 0.5360 data_time: 0.0225 memory: 17620 loss: 4.6447 loss_prob: 2.8979 loss_thr: 1.0790 loss_db: 0.6677 2022/11/01 13:12:15 - mmengine - INFO - Epoch(train) [25][60/63] lr: 2.4296e-04 eta: 20:52:58 time: 0.5247 data_time: 0.0109 memory: 17620 loss: 4.5937 loss_prob: 2.8881 loss_thr: 1.0649 loss_db: 0.6407 2022/11/01 13:12:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:12:21 - mmengine - INFO - Epoch(train) [26][5/63] lr: 2.5301e-04 eta: 20:52:58 time: 0.7384 data_time: 0.2213 memory: 17620 loss: 4.5788 loss_prob: 2.8762 loss_thr: 1.0407 loss_db: 0.6619 2022/11/01 13:12:24 - mmengine - INFO - Epoch(train) [26][10/63] lr: 2.5301e-04 eta: 20:48:11 time: 0.7356 data_time: 0.2210 memory: 17620 loss: 4.8186 loss_prob: 2.9230 loss_thr: 1.1009 loss_db: 0.7947 2022/11/01 13:12:26 - mmengine - INFO - Epoch(train) [26][15/63] lr: 2.5301e-04 eta: 20:48:11 time: 0.5034 data_time: 0.0076 memory: 17620 loss: 5.2870 loss_prob: 3.1548 loss_thr: 1.1988 loss_db: 0.9333 2022/11/01 13:12:29 - mmengine - INFO - Epoch(train) [26][20/63] lr: 2.5301e-04 eta: 20:44:10 time: 0.5143 data_time: 0.0060 memory: 17620 loss: 5.3431 loss_prob: 3.1836 loss_thr: 1.1918 loss_db: 0.9678 2022/11/01 13:12:32 - mmengine - INFO - Epoch(train) [26][25/63] lr: 2.5301e-04 eta: 20:44:10 time: 0.5273 data_time: 0.0165 memory: 17620 loss: 5.1831 loss_prob: 3.0594 loss_thr: 1.1734 loss_db: 0.9504 2022/11/01 13:12:34 - mmengine - INFO - Epoch(train) [26][30/63] lr: 2.5301e-04 eta: 20:40:22 time: 0.5353 data_time: 0.0319 memory: 17620 loss: 5.1544 loss_prob: 3.0678 loss_thr: 1.1764 loss_db: 0.9103 2022/11/01 13:12:37 - mmengine - INFO - Epoch(train) [26][35/63] lr: 2.5301e-04 eta: 20:40:22 time: 0.5184 data_time: 0.0238 memory: 17620 loss: 5.1221 loss_prob: 3.0519 loss_thr: 1.1589 loss_db: 0.9113 2022/11/01 13:12:39 - mmengine - INFO - Epoch(train) [26][40/63] lr: 2.5301e-04 eta: 20:36:23 time: 0.5050 data_time: 0.0106 memory: 17620 loss: 5.0342 loss_prob: 3.0050 loss_thr: 1.1442 loss_db: 0.8850 2022/11/01 13:12:42 - mmengine - INFO - Epoch(train) [26][45/63] lr: 2.5301e-04 eta: 20:36:23 time: 0.5038 data_time: 0.0067 memory: 17620 loss: 4.9637 loss_prob: 2.9818 loss_thr: 1.1501 loss_db: 0.8319 2022/11/01 13:12:45 - mmengine - INFO - Epoch(train) [26][50/63] lr: 2.5301e-04 eta: 20:32:38 time: 0.5308 data_time: 0.0104 memory: 17620 loss: 4.9383 loss_prob: 2.9687 loss_thr: 1.1550 loss_db: 0.8147 2022/11/01 13:12:47 - mmengine - INFO - Epoch(train) [26][55/63] lr: 2.5301e-04 eta: 20:32:38 time: 0.5488 data_time: 0.0219 memory: 17620 loss: 4.8375 loss_prob: 2.9236 loss_thr: 1.1441 loss_db: 0.7698 2022/11/01 13:12:50 - mmengine - INFO - Epoch(train) [26][60/63] lr: 2.5301e-04 eta: 20:28:54 time: 0.5261 data_time: 0.0185 memory: 17620 loss: 4.7933 loss_prob: 2.9055 loss_thr: 1.1258 loss_db: 0.7621 2022/11/01 13:12:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:12:56 - mmengine - INFO - Epoch(train) [27][5/63] lr: 2.6305e-04 eta: 20:28:54 time: 0.7012 data_time: 0.2115 memory: 17620 loss: 4.7799 loss_prob: 2.9041 loss_thr: 1.1152 loss_db: 0.7606 2022/11/01 13:12:59 - mmengine - INFO - Epoch(train) [27][10/63] lr: 2.6305e-04 eta: 20:24:27 time: 0.7313 data_time: 0.2127 memory: 17620 loss: 4.9265 loss_prob: 2.9739 loss_thr: 1.1227 loss_db: 0.8300 2022/11/01 13:13:01 - mmengine - INFO - Epoch(train) [27][15/63] lr: 2.6305e-04 eta: 20:24:27 time: 0.5290 data_time: 0.0074 memory: 17620 loss: 4.9667 loss_prob: 3.0086 loss_thr: 1.1233 loss_db: 0.8348 2022/11/01 13:13:04 - mmengine - INFO - Epoch(train) [27][20/63] lr: 2.6305e-04 eta: 20:20:47 time: 0.5228 data_time: 0.0069 memory: 17620 loss: 4.8147 loss_prob: 2.9569 loss_thr: 1.0993 loss_db: 0.7585 2022/11/01 13:13:07 - mmengine - INFO - Epoch(train) [27][25/63] lr: 2.6305e-04 eta: 20:20:47 time: 0.5574 data_time: 0.0427 memory: 17620 loss: 4.7006 loss_prob: 2.8938 loss_thr: 1.0984 loss_db: 0.7084 2022/11/01 13:13:09 - mmengine - INFO - Epoch(train) [27][30/63] lr: 2.6305e-04 eta: 20:17:24 time: 0.5536 data_time: 0.0408 memory: 17620 loss: 4.7819 loss_prob: 2.9112 loss_thr: 1.1142 loss_db: 0.7565 2022/11/01 13:13:12 - mmengine - INFO - Epoch(train) [27][35/63] lr: 2.6305e-04 eta: 20:17:24 time: 0.5020 data_time: 0.0046 memory: 17620 loss: 4.7498 loss_prob: 2.9020 loss_thr: 1.1077 loss_db: 0.7402 2022/11/01 13:13:14 - mmengine - INFO - Epoch(train) [27][40/63] lr: 2.6305e-04 eta: 20:13:37 time: 0.4950 data_time: 0.0046 memory: 17620 loss: 4.6484 loss_prob: 2.8589 loss_thr: 1.0834 loss_db: 0.7061 2022/11/01 13:13:17 - mmengine - INFO - Epoch(train) [27][45/63] lr: 2.6305e-04 eta: 20:13:37 time: 0.5292 data_time: 0.0047 memory: 17620 loss: 4.7453 loss_prob: 2.9054 loss_thr: 1.0893 loss_db: 0.7506 2022/11/01 13:13:20 - mmengine - INFO - Epoch(train) [27][50/63] lr: 2.6305e-04 eta: 20:10:18 time: 0.5536 data_time: 0.0126 memory: 17620 loss: 4.7479 loss_prob: 2.9078 loss_thr: 1.0955 loss_db: 0.7446 2022/11/01 13:13:22 - mmengine - INFO - Epoch(train) [27][55/63] lr: 2.6305e-04 eta: 20:10:18 time: 0.5218 data_time: 0.0130 memory: 17620 loss: 4.7064 loss_prob: 2.9031 loss_thr: 1.0749 loss_db: 0.7284 2022/11/01 13:13:25 - mmengine - INFO - Epoch(train) [27][60/63] lr: 2.6305e-04 eta: 20:06:43 time: 0.5123 data_time: 0.0055 memory: 17620 loss: 4.6874 loss_prob: 2.8891 loss_thr: 1.0590 loss_db: 0.7394 2022/11/01 13:13:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:13:32 - mmengine - INFO - Epoch(train) [28][5/63] lr: 2.7309e-04 eta: 20:06:43 time: 0.7512 data_time: 0.2173 memory: 17620 loss: 4.5994 loss_prob: 2.8427 loss_thr: 1.0716 loss_db: 0.6850 2022/11/01 13:13:34 - mmengine - INFO - Epoch(train) [28][10/63] lr: 2.7309e-04 eta: 20:02:45 time: 0.7505 data_time: 0.2163 memory: 17620 loss: 4.5813 loss_prob: 2.8294 loss_thr: 1.0708 loss_db: 0.6812 2022/11/01 13:13:37 - mmengine - INFO - Epoch(train) [28][15/63] lr: 2.7309e-04 eta: 20:02:45 time: 0.4992 data_time: 0.0048 memory: 17620 loss: 4.6414 loss_prob: 2.8619 loss_thr: 1.0668 loss_db: 0.7128 2022/11/01 13:13:39 - mmengine - INFO - Epoch(train) [28][20/63] lr: 2.7309e-04 eta: 19:59:10 time: 0.5001 data_time: 0.0048 memory: 17620 loss: 4.6957 loss_prob: 2.8828 loss_thr: 1.0855 loss_db: 0.7275 2022/11/01 13:13:42 - mmengine - INFO - Epoch(train) [28][25/63] lr: 2.7309e-04 eta: 19:59:10 time: 0.5095 data_time: 0.0042 memory: 17620 loss: 4.6184 loss_prob: 2.8447 loss_thr: 1.0801 loss_db: 0.6936 2022/11/01 13:13:44 - mmengine - INFO - Epoch(train) [28][30/63] lr: 2.7309e-04 eta: 19:55:52 time: 0.5313 data_time: 0.0120 memory: 17620 loss: 4.5894 loss_prob: 2.8428 loss_thr: 1.0673 loss_db: 0.6793 2022/11/01 13:13:47 - mmengine - INFO - Epoch(train) [28][35/63] lr: 2.7309e-04 eta: 19:55:52 time: 0.5530 data_time: 0.0121 memory: 17620 loss: 4.5499 loss_prob: 2.8343 loss_thr: 1.0579 loss_db: 0.6577 2022/11/01 13:13:50 - mmengine - INFO - Epoch(train) [28][40/63] lr: 2.7309e-04 eta: 19:52:40 time: 0.5416 data_time: 0.0044 memory: 17620 loss: 4.5199 loss_prob: 2.8044 loss_thr: 1.0544 loss_db: 0.6610 2022/11/01 13:13:52 - mmengine - INFO - Epoch(train) [28][45/63] lr: 2.7309e-04 eta: 19:52:40 time: 0.5287 data_time: 0.0044 memory: 17620 loss: 4.5313 loss_prob: 2.8028 loss_thr: 1.0678 loss_db: 0.6607 2022/11/01 13:13:55 - mmengine - INFO - Epoch(train) [28][50/63] lr: 2.7309e-04 eta: 19:49:18 time: 0.5143 data_time: 0.0059 memory: 17620 loss: 4.5022 loss_prob: 2.8379 loss_thr: 1.0521 loss_db: 0.6121 2022/11/01 13:13:58 - mmengine - INFO - Epoch(train) [28][55/63] lr: 2.7309e-04 eta: 19:49:18 time: 0.5193 data_time: 0.0203 memory: 17620 loss: 4.5671 loss_prob: 2.8734 loss_thr: 1.0482 loss_db: 0.6456 2022/11/01 13:14:00 - mmengine - INFO - Epoch(train) [28][60/63] lr: 2.7309e-04 eta: 19:46:16 time: 0.5553 data_time: 0.0194 memory: 17620 loss: 4.4493 loss_prob: 2.7955 loss_thr: 1.0335 loss_db: 0.6204 2022/11/01 13:14:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:14:06 - mmengine - INFO - Epoch(train) [29][5/63] lr: 2.8313e-04 eta: 19:46:16 time: 0.6835 data_time: 0.1811 memory: 17620 loss: 4.4683 loss_prob: 2.8263 loss_thr: 1.0292 loss_db: 0.6128 2022/11/01 13:14:09 - mmengine - INFO - Epoch(train) [29][10/63] lr: 2.8313e-04 eta: 19:42:12 time: 0.6954 data_time: 0.1808 memory: 17620 loss: 4.5947 loss_prob: 2.8576 loss_thr: 1.0437 loss_db: 0.6934 2022/11/01 13:14:12 - mmengine - INFO - Epoch(train) [29][15/63] lr: 2.8313e-04 eta: 19:42:12 time: 0.5280 data_time: 0.0075 memory: 17620 loss: 4.6403 loss_prob: 2.8550 loss_thr: 1.0589 loss_db: 0.7264 2022/11/01 13:14:14 - mmengine - INFO - Epoch(train) [29][20/63] lr: 2.8313e-04 eta: 19:39:04 time: 0.5299 data_time: 0.0074 memory: 17620 loss: 4.6131 loss_prob: 2.8394 loss_thr: 1.0779 loss_db: 0.6958 2022/11/01 13:14:17 - mmengine - INFO - Epoch(train) [29][25/63] lr: 2.8313e-04 eta: 19:39:04 time: 0.5229 data_time: 0.0206 memory: 17620 loss: 4.5607 loss_prob: 2.8301 loss_thr: 1.0558 loss_db: 0.6748 2022/11/01 13:14:19 - mmengine - INFO - Epoch(train) [29][30/63] lr: 2.8313e-04 eta: 19:36:00 time: 0.5354 data_time: 0.0322 memory: 17620 loss: 4.4812 loss_prob: 2.8253 loss_thr: 1.0360 loss_db: 0.6199 2022/11/01 13:14:22 - mmengine - INFO - Epoch(train) [29][35/63] lr: 2.8313e-04 eta: 19:36:00 time: 0.5242 data_time: 0.0175 memory: 17620 loss: 4.5344 loss_prob: 2.8256 loss_thr: 1.0416 loss_db: 0.6673 2022/11/01 13:14:25 - mmengine - INFO - Epoch(train) [29][40/63] lr: 2.8313e-04 eta: 19:32:51 time: 0.5178 data_time: 0.0062 memory: 17620 loss: 4.5047 loss_prob: 2.8125 loss_thr: 1.0313 loss_db: 0.6609 2022/11/01 13:14:27 - mmengine - INFO - Epoch(train) [29][45/63] lr: 2.8313e-04 eta: 19:32:51 time: 0.5434 data_time: 0.0072 memory: 17620 loss: 4.3099 loss_prob: 2.7240 loss_thr: 1.0206 loss_db: 0.5653 2022/11/01 13:14:30 - mmengine - INFO - Epoch(train) [29][50/63] lr: 2.8313e-04 eta: 19:29:55 time: 0.5438 data_time: 0.0155 memory: 17620 loss: 4.3216 loss_prob: 2.7323 loss_thr: 1.0251 loss_db: 0.5643 2022/11/01 13:14:33 - mmengine - INFO - Epoch(train) [29][55/63] lr: 2.8313e-04 eta: 19:29:55 time: 0.5339 data_time: 0.0199 memory: 17620 loss: 4.4122 loss_prob: 2.7936 loss_thr: 1.0165 loss_db: 0.6021 2022/11/01 13:14:35 - mmengine - INFO - Epoch(train) [29][60/63] lr: 2.8313e-04 eta: 19:26:58 time: 0.5376 data_time: 0.0117 memory: 17620 loss: 4.5955 loss_prob: 2.9065 loss_thr: 1.0441 loss_db: 0.6449 2022/11/01 13:14:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:14:41 - mmengine - INFO - Epoch(train) [30][5/63] lr: 2.9317e-04 eta: 19:26:58 time: 0.6609 data_time: 0.1615 memory: 17620 loss: 4.8677 loss_prob: 2.9983 loss_thr: 1.1108 loss_db: 0.7585 2022/11/01 13:14:44 - mmengine - INFO - Epoch(train) [30][10/63] lr: 2.9317e-04 eta: 19:23:12 time: 0.7007 data_time: 0.1675 memory: 17620 loss: 4.7392 loss_prob: 2.9631 loss_thr: 1.0860 loss_db: 0.6901 2022/11/01 13:14:46 - mmengine - INFO - Epoch(train) [30][15/63] lr: 2.9317e-04 eta: 19:23:12 time: 0.5439 data_time: 0.0113 memory: 17620 loss: 4.7621 loss_prob: 2.9975 loss_thr: 1.0884 loss_db: 0.6762 2022/11/01 13:14:49 - mmengine - INFO - Epoch(train) [30][20/63] lr: 2.9317e-04 eta: 19:20:16 time: 0.5285 data_time: 0.0048 memory: 17620 loss: 5.0915 loss_prob: 3.1082 loss_thr: 1.1505 loss_db: 0.8328 2022/11/01 13:14:52 - mmengine - INFO - Epoch(train) [30][25/63] lr: 2.9317e-04 eta: 19:20:16 time: 0.5214 data_time: 0.0081 memory: 17620 loss: 5.2321 loss_prob: 3.0892 loss_thr: 1.1778 loss_db: 0.9651 2022/11/01 13:14:54 - mmengine - INFO - Epoch(train) [30][30/63] lr: 2.9317e-04 eta: 19:17:25 time: 0.5371 data_time: 0.0348 memory: 17620 loss: 5.1368 loss_prob: 3.0192 loss_thr: 1.1658 loss_db: 0.9518 2022/11/01 13:14:57 - mmengine - INFO - Epoch(train) [30][35/63] lr: 2.9317e-04 eta: 19:17:25 time: 0.5444 data_time: 0.0413 memory: 17620 loss: 5.0809 loss_prob: 2.9853 loss_thr: 1.1521 loss_db: 0.9435 2022/11/01 13:15:00 - mmengine - INFO - Epoch(train) [30][40/63] lr: 2.9317e-04 eta: 19:14:33 time: 0.5320 data_time: 0.0144 memory: 17620 loss: 4.9861 loss_prob: 2.9351 loss_thr: 1.1369 loss_db: 0.9141 2022/11/01 13:15:02 - mmengine - INFO - Epoch(train) [30][45/63] lr: 2.9317e-04 eta: 19:14:33 time: 0.5174 data_time: 0.0042 memory: 17620 loss: 4.8853 loss_prob: 2.9275 loss_thr: 1.1177 loss_db: 0.8401 2022/11/01 13:15:05 - mmengine - INFO - Epoch(train) [30][50/63] lr: 2.9317e-04 eta: 19:11:43 time: 0.5291 data_time: 0.0137 memory: 17620 loss: 4.7945 loss_prob: 2.9144 loss_thr: 1.1094 loss_db: 0.7707 2022/11/01 13:15:08 - mmengine - INFO - Epoch(train) [30][55/63] lr: 2.9317e-04 eta: 19:11:43 time: 0.5434 data_time: 0.0230 memory: 17620 loss: 4.8574 loss_prob: 2.9404 loss_thr: 1.1357 loss_db: 0.7813 2022/11/01 13:15:10 - mmengine - INFO - Epoch(train) [30][60/63] lr: 2.9317e-04 eta: 19:08:53 time: 0.5273 data_time: 0.0182 memory: 17620 loss: 4.9480 loss_prob: 2.9918 loss_thr: 1.1480 loss_db: 0.8082 2022/11/01 13:15:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:15:16 - mmengine - INFO - Epoch(train) [31][5/63] lr: 3.0321e-04 eta: 19:08:53 time: 0.6985 data_time: 0.1840 memory: 17620 loss: 4.8436 loss_prob: 2.9599 loss_thr: 1.1065 loss_db: 0.7772 2022/11/01 13:15:19 - mmengine - INFO - Epoch(train) [31][10/63] lr: 3.0321e-04 eta: 19:05:30 time: 0.7237 data_time: 0.1838 memory: 17620 loss: 4.7725 loss_prob: 2.9235 loss_thr: 1.1014 loss_db: 0.7476 2022/11/01 13:15:22 - mmengine - INFO - Epoch(train) [31][15/63] lr: 3.0321e-04 eta: 19:05:30 time: 0.5389 data_time: 0.0091 memory: 17620 loss: 4.6505 loss_prob: 2.8877 loss_thr: 1.0643 loss_db: 0.6985 2022/11/01 13:15:24 - mmengine - INFO - Epoch(train) [31][20/63] lr: 3.0321e-04 eta: 19:02:46 time: 0.5310 data_time: 0.0116 memory: 17620 loss: 4.6356 loss_prob: 2.8744 loss_thr: 1.0619 loss_db: 0.6994 2022/11/01 13:15:27 - mmengine - INFO - Epoch(train) [31][25/63] lr: 3.0321e-04 eta: 19:02:46 time: 0.5357 data_time: 0.0215 memory: 17620 loss: 4.6435 loss_prob: 2.8631 loss_thr: 1.0793 loss_db: 0.7011 2022/11/01 13:15:30 - mmengine - INFO - Epoch(train) [31][30/63] lr: 3.0321e-04 eta: 19:00:08 time: 0.5432 data_time: 0.0281 memory: 17620 loss: 4.6091 loss_prob: 2.8554 loss_thr: 1.0705 loss_db: 0.6832 2022/11/01 13:15:32 - mmengine - INFO - Epoch(train) [31][35/63] lr: 3.0321e-04 eta: 19:00:08 time: 0.5251 data_time: 0.0148 memory: 17620 loss: 4.6118 loss_prob: 2.8879 loss_thr: 1.0592 loss_db: 0.6647 2022/11/01 13:15:35 - mmengine - INFO - Epoch(train) [31][40/63] lr: 3.0321e-04 eta: 18:57:29 time: 0.5360 data_time: 0.0104 memory: 17620 loss: 4.6089 loss_prob: 2.8760 loss_thr: 1.0584 loss_db: 0.6745 2022/11/01 13:15:38 - mmengine - INFO - Epoch(train) [31][45/63] lr: 3.0321e-04 eta: 18:57:29 time: 0.5334 data_time: 0.0095 memory: 17620 loss: 4.5111 loss_prob: 2.8127 loss_thr: 1.0354 loss_db: 0.6631 2022/11/01 13:15:41 - mmengine - INFO - Epoch(train) [31][50/63] lr: 3.0321e-04 eta: 18:54:58 time: 0.5523 data_time: 0.0179 memory: 17620 loss: 4.4596 loss_prob: 2.8026 loss_thr: 1.0293 loss_db: 0.6278 2022/11/01 13:15:43 - mmengine - INFO - Epoch(train) [31][55/63] lr: 3.0321e-04 eta: 18:54:58 time: 0.5615 data_time: 0.0191 memory: 17620 loss: 4.4230 loss_prob: 2.7900 loss_thr: 1.0226 loss_db: 0.6103 2022/11/01 13:15:46 - mmengine - INFO - Epoch(train) [31][60/63] lr: 3.0321e-04 eta: 18:52:19 time: 0.5296 data_time: 0.0073 memory: 17620 loss: 4.4856 loss_prob: 2.8219 loss_thr: 1.0267 loss_db: 0.6371 2022/11/01 13:15:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:15:52 - mmengine - INFO - Epoch(train) [32][5/63] lr: 3.1325e-04 eta: 18:52:19 time: 0.7032 data_time: 0.1851 memory: 17620 loss: 4.4530 loss_prob: 2.8043 loss_thr: 1.0127 loss_db: 0.6360 2022/11/01 13:15:54 - mmengine - INFO - Epoch(train) [32][10/63] lr: 3.1325e-04 eta: 18:49:06 time: 0.7156 data_time: 0.1830 memory: 17620 loss: 4.4986 loss_prob: 2.8272 loss_thr: 1.0118 loss_db: 0.6596 2022/11/01 13:15:57 - mmengine - INFO - Epoch(train) [32][15/63] lr: 3.1325e-04 eta: 18:49:06 time: 0.5278 data_time: 0.0058 memory: 17620 loss: 4.5762 loss_prob: 2.8472 loss_thr: 1.0287 loss_db: 0.7002 2022/11/01 13:16:00 - mmengine - INFO - Epoch(train) [32][20/63] lr: 3.1325e-04 eta: 18:46:30 time: 0.5262 data_time: 0.0060 memory: 17620 loss: 4.6196 loss_prob: 2.8457 loss_thr: 1.0445 loss_db: 0.7295 2022/11/01 13:16:02 - mmengine - INFO - Epoch(train) [32][25/63] lr: 3.1325e-04 eta: 18:46:30 time: 0.5121 data_time: 0.0090 memory: 17620 loss: 4.5298 loss_prob: 2.8048 loss_thr: 1.0422 loss_db: 0.6829 2022/11/01 13:16:05 - mmengine - INFO - Epoch(train) [32][30/63] lr: 3.1325e-04 eta: 18:43:55 time: 0.5246 data_time: 0.0308 memory: 17620 loss: 4.3969 loss_prob: 2.7543 loss_thr: 1.0286 loss_db: 0.6140 2022/11/01 13:16:07 - mmengine - INFO - Epoch(train) [32][35/63] lr: 3.1325e-04 eta: 18:43:55 time: 0.5193 data_time: 0.0275 memory: 17620 loss: 4.3354 loss_prob: 2.7373 loss_thr: 1.0089 loss_db: 0.5892 2022/11/01 13:16:10 - mmengine - INFO - Epoch(train) [32][40/63] lr: 3.1325e-04 eta: 18:41:13 time: 0.5024 data_time: 0.0064 memory: 17620 loss: 4.4659 loss_prob: 2.8184 loss_thr: 1.0080 loss_db: 0.6395 2022/11/01 13:16:12 - mmengine - INFO - Epoch(train) [32][45/63] lr: 3.1325e-04 eta: 18:41:13 time: 0.5029 data_time: 0.0057 memory: 17620 loss: 4.6413 loss_prob: 2.8995 loss_thr: 1.0154 loss_db: 0.7265 2022/11/01 13:16:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:16:15 - mmengine - INFO - Epoch(train) [32][50/63] lr: 3.1325e-04 eta: 18:38:49 time: 0.5474 data_time: 0.0156 memory: 17620 loss: 4.6635 loss_prob: 2.9058 loss_thr: 1.0333 loss_db: 0.7244 2022/11/01 13:16:18 - mmengine - INFO - Epoch(train) [32][55/63] lr: 3.1325e-04 eta: 18:38:49 time: 0.5780 data_time: 0.0214 memory: 17620 loss: 4.4953 loss_prob: 2.8306 loss_thr: 1.0264 loss_db: 0.6384 2022/11/01 13:16:21 - mmengine - INFO - Epoch(train) [32][60/63] lr: 3.1325e-04 eta: 18:36:20 time: 0.5297 data_time: 0.0101 memory: 17620 loss: 4.3802 loss_prob: 2.7806 loss_thr: 1.0044 loss_db: 0.5953 2022/11/01 13:16:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:16:26 - mmengine - INFO - Epoch(train) [33][5/63] lr: 3.2329e-04 eta: 18:36:20 time: 0.6746 data_time: 0.1808 memory: 17620 loss: 4.3103 loss_prob: 2.7271 loss_thr: 0.9983 loss_db: 0.5849 2022/11/01 13:16:29 - mmengine - INFO - Epoch(train) [33][10/63] lr: 3.2329e-04 eta: 18:33:17 time: 0.7124 data_time: 0.1948 memory: 17620 loss: 4.3577 loss_prob: 2.7507 loss_thr: 1.0033 loss_db: 0.6037 2022/11/01 13:16:32 - mmengine - INFO - Epoch(train) [33][15/63] lr: 3.2329e-04 eta: 18:33:17 time: 0.5280 data_time: 0.0204 memory: 17620 loss: 4.3846 loss_prob: 2.7698 loss_thr: 1.0005 loss_db: 0.6143 2022/11/01 13:16:34 - mmengine - INFO - Epoch(train) [33][20/63] lr: 3.2329e-04 eta: 18:30:45 time: 0.5117 data_time: 0.0052 memory: 17620 loss: 4.2787 loss_prob: 2.7280 loss_thr: 0.9781 loss_db: 0.5725 2022/11/01 13:16:37 - mmengine - INFO - Epoch(train) [33][25/63] lr: 3.2329e-04 eta: 18:30:45 time: 0.5137 data_time: 0.0068 memory: 17620 loss: 4.1705 loss_prob: 2.6694 loss_thr: 0.9728 loss_db: 0.5283 2022/11/01 13:16:40 - mmengine - INFO - Epoch(train) [33][30/63] lr: 3.2329e-04 eta: 18:28:21 time: 0.5325 data_time: 0.0195 memory: 17620 loss: 4.1665 loss_prob: 2.6520 loss_thr: 0.9867 loss_db: 0.5278 2022/11/01 13:16:42 - mmengine - INFO - Epoch(train) [33][35/63] lr: 3.2329e-04 eta: 18:28:21 time: 0.5432 data_time: 0.0324 memory: 17620 loss: 4.3097 loss_prob: 2.7294 loss_thr: 0.9931 loss_db: 0.5872 2022/11/01 13:16:45 - mmengine - INFO - Epoch(train) [33][40/63] lr: 3.2329e-04 eta: 18:25:54 time: 0.5181 data_time: 0.0201 memory: 17620 loss: 4.4016 loss_prob: 2.7624 loss_thr: 0.9990 loss_db: 0.6402 2022/11/01 13:16:48 - mmengine - INFO - Epoch(train) [33][45/63] lr: 3.2329e-04 eta: 18:25:54 time: 0.5387 data_time: 0.0050 memory: 17620 loss: 4.3970 loss_prob: 2.7439 loss_thr: 1.0092 loss_db: 0.6438 2022/11/01 13:16:50 - mmengine - INFO - Epoch(train) [33][50/63] lr: 3.2329e-04 eta: 18:23:47 time: 0.5707 data_time: 0.0083 memory: 17620 loss: 4.3470 loss_prob: 2.7263 loss_thr: 1.0048 loss_db: 0.6160 2022/11/01 13:16:54 - mmengine - INFO - Epoch(train) [33][55/63] lr: 3.2329e-04 eta: 18:23:47 time: 0.6134 data_time: 0.0229 memory: 17620 loss: 4.1161 loss_prob: 2.6130 loss_thr: 0.9789 loss_db: 0.5242 2022/11/01 13:16:57 - mmengine - INFO - Epoch(train) [33][60/63] lr: 3.2329e-04 eta: 18:21:57 time: 0.6159 data_time: 0.0193 memory: 17620 loss: 4.1490 loss_prob: 2.6345 loss_thr: 0.9770 loss_db: 0.5375 2022/11/01 13:16:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:17:03 - mmengine - INFO - Epoch(train) [34][5/63] lr: 3.3333e-04 eta: 18:21:57 time: 0.7861 data_time: 0.1921 memory: 17620 loss: 4.2026 loss_prob: 2.6565 loss_thr: 0.9910 loss_db: 0.5551 2022/11/01 13:17:06 - mmengine - INFO - Epoch(train) [34][10/63] lr: 3.3333e-04 eta: 18:19:50 time: 0.8404 data_time: 0.2004 memory: 17620 loss: 4.1722 loss_prob: 2.6431 loss_thr: 0.9699 loss_db: 0.5591 2022/11/01 13:17:10 - mmengine - INFO - Epoch(train) [34][15/63] lr: 3.3333e-04 eta: 18:19:50 time: 0.6444 data_time: 0.0170 memory: 17620 loss: 4.2371 loss_prob: 2.6826 loss_thr: 0.9843 loss_db: 0.5703 2022/11/01 13:17:12 - mmengine - INFO - Epoch(train) [34][20/63] lr: 3.3333e-04 eta: 18:17:59 time: 0.6049 data_time: 0.0093 memory: 17620 loss: 4.2242 loss_prob: 2.6819 loss_thr: 0.9866 loss_db: 0.5557 2022/11/01 13:17:15 - mmengine - INFO - Epoch(train) [34][25/63] lr: 3.3333e-04 eta: 18:17:59 time: 0.5514 data_time: 0.0264 memory: 17620 loss: 4.0790 loss_prob: 2.5962 loss_thr: 0.9666 loss_db: 0.5162 2022/11/01 13:17:18 - mmengine - INFO - Epoch(train) [34][30/63] lr: 3.3333e-04 eta: 18:16:02 time: 0.5866 data_time: 0.0286 memory: 17620 loss: 4.0755 loss_prob: 2.6006 loss_thr: 0.9589 loss_db: 0.5160 2022/11/01 13:17:21 - mmengine - INFO - Epoch(train) [34][35/63] lr: 3.3333e-04 eta: 18:16:02 time: 0.6055 data_time: 0.0105 memory: 17620 loss: 3.9955 loss_prob: 2.5512 loss_thr: 0.9510 loss_db: 0.4933 2022/11/01 13:17:24 - mmengine - INFO - Epoch(train) [34][40/63] lr: 3.3333e-04 eta: 18:14:04 time: 0.5816 data_time: 0.0058 memory: 17620 loss: 4.0370 loss_prob: 2.5597 loss_thr: 0.9645 loss_db: 0.5127 2022/11/01 13:17:27 - mmengine - INFO - Epoch(train) [34][45/63] lr: 3.3333e-04 eta: 18:14:04 time: 0.5970 data_time: 0.0086 memory: 17620 loss: 4.1234 loss_prob: 2.6105 loss_thr: 0.9694 loss_db: 0.5436 2022/11/01 13:17:30 - mmengine - INFO - Epoch(train) [34][50/63] lr: 3.3333e-04 eta: 18:12:21 time: 0.6213 data_time: 0.0205 memory: 17620 loss: 4.0029 loss_prob: 2.5575 loss_thr: 0.9510 loss_db: 0.4944 2022/11/01 13:17:33 - mmengine - INFO - Epoch(train) [34][55/63] lr: 3.3333e-04 eta: 18:12:21 time: 0.5917 data_time: 0.0218 memory: 17620 loss: 4.0872 loss_prob: 2.5908 loss_thr: 0.9635 loss_db: 0.5329 2022/11/01 13:17:37 - mmengine - INFO - Epoch(train) [34][60/63] lr: 3.3333e-04 eta: 18:10:42 time: 0.6299 data_time: 0.0095 memory: 17620 loss: 4.2496 loss_prob: 2.6530 loss_thr: 1.0074 loss_db: 0.5892 2022/11/01 13:17:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:17:44 - mmengine - INFO - Epoch(train) [35][5/63] lr: 3.4337e-04 eta: 18:10:42 time: 0.8494 data_time: 0.2229 memory: 17620 loss: 4.2113 loss_prob: 2.6651 loss_thr: 0.9907 loss_db: 0.5555 2022/11/01 13:17:46 - mmengine - INFO - Epoch(train) [35][10/63] lr: 3.4337e-04 eta: 18:08:42 time: 0.8392 data_time: 0.2222 memory: 17620 loss: 4.2291 loss_prob: 2.6774 loss_thr: 0.9720 loss_db: 0.5796 2022/11/01 13:17:49 - mmengine - INFO - Epoch(train) [35][15/63] lr: 3.4337e-04 eta: 18:08:42 time: 0.5393 data_time: 0.0054 memory: 17620 loss: 4.3364 loss_prob: 2.7085 loss_thr: 1.0121 loss_db: 0.6158 2022/11/01 13:17:52 - mmengine - INFO - Epoch(train) [35][20/63] lr: 3.4337e-04 eta: 18:06:37 time: 0.5491 data_time: 0.0079 memory: 17620 loss: 4.4389 loss_prob: 2.7673 loss_thr: 1.0236 loss_db: 0.6480 2022/11/01 13:17:55 - mmengine - INFO - Epoch(train) [35][25/63] lr: 3.4337e-04 eta: 18:06:37 time: 0.5566 data_time: 0.0313 memory: 17620 loss: 4.2140 loss_prob: 2.6581 loss_thr: 0.9884 loss_db: 0.5676 2022/11/01 13:17:58 - mmengine - INFO - Epoch(train) [35][30/63] lr: 3.4337e-04 eta: 18:04:40 time: 0.5663 data_time: 0.0352 memory: 17620 loss: 4.0230 loss_prob: 2.5502 loss_thr: 0.9652 loss_db: 0.5076 2022/11/01 13:18:00 - mmengine - INFO - Epoch(train) [35][35/63] lr: 3.4337e-04 eta: 18:04:40 time: 0.5616 data_time: 0.0112 memory: 17620 loss: 4.0320 loss_prob: 2.5462 loss_thr: 0.9725 loss_db: 0.5133 2022/11/01 13:18:03 - mmengine - INFO - Epoch(train) [35][40/63] lr: 3.4337e-04 eta: 18:02:47 time: 0.5771 data_time: 0.0087 memory: 17620 loss: 4.1111 loss_prob: 2.6059 loss_thr: 0.9843 loss_db: 0.5209 2022/11/01 13:18:06 - mmengine - INFO - Epoch(train) [35][45/63] lr: 3.4337e-04 eta: 18:02:47 time: 0.5693 data_time: 0.0087 memory: 17620 loss: 4.0605 loss_prob: 2.5766 loss_thr: 0.9722 loss_db: 0.5117 2022/11/01 13:18:09 - mmengine - INFO - Epoch(train) [35][50/63] lr: 3.4337e-04 eta: 18:00:55 time: 0.5781 data_time: 0.0154 memory: 17620 loss: 3.9498 loss_prob: 2.5119 loss_thr: 0.9525 loss_db: 0.4853 2022/11/01 13:18:12 - mmengine - INFO - Epoch(train) [35][55/63] lr: 3.4337e-04 eta: 18:00:55 time: 0.5634 data_time: 0.0199 memory: 17620 loss: 3.9421 loss_prob: 2.5082 loss_thr: 0.9507 loss_db: 0.4832 2022/11/01 13:18:14 - mmengine - INFO - Epoch(train) [35][60/63] lr: 3.4337e-04 eta: 17:58:43 time: 0.5125 data_time: 0.0094 memory: 17620 loss: 3.8617 loss_prob: 2.4717 loss_thr: 0.9264 loss_db: 0.4637 2022/11/01 13:18:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:18:20 - mmengine - INFO - Epoch(train) [36][5/63] lr: 3.5341e-04 eta: 17:58:43 time: 0.6943 data_time: 0.1862 memory: 17620 loss: 4.0402 loss_prob: 2.5701 loss_thr: 0.9514 loss_db: 0.5187 2022/11/01 13:18:23 - mmengine - INFO - Epoch(train) [36][10/63] lr: 3.5341e-04 eta: 17:56:21 time: 0.7535 data_time: 0.2030 memory: 17620 loss: 4.0628 loss_prob: 2.5672 loss_thr: 0.9737 loss_db: 0.5219 2022/11/01 13:18:26 - mmengine - INFO - Epoch(train) [36][15/63] lr: 3.5341e-04 eta: 17:56:21 time: 0.5522 data_time: 0.0243 memory: 17620 loss: 3.9979 loss_prob: 2.5205 loss_thr: 0.9686 loss_db: 0.5087 2022/11/01 13:18:29 - mmengine - INFO - Epoch(train) [36][20/63] lr: 3.5341e-04 eta: 17:54:28 time: 0.5624 data_time: 0.0063 memory: 17620 loss: 3.8845 loss_prob: 2.4594 loss_thr: 0.9450 loss_db: 0.4800 2022/11/01 13:18:31 - mmengine - INFO - Epoch(train) [36][25/63] lr: 3.5341e-04 eta: 17:54:28 time: 0.5718 data_time: 0.0109 memory: 17620 loss: 3.8812 loss_prob: 2.4616 loss_thr: 0.9473 loss_db: 0.4723 2022/11/01 13:18:34 - mmengine - INFO - Epoch(train) [36][30/63] lr: 3.5341e-04 eta: 17:52:29 time: 0.5430 data_time: 0.0244 memory: 17620 loss: 3.8962 loss_prob: 2.4756 loss_thr: 0.9377 loss_db: 0.4829 2022/11/01 13:18:37 - mmengine - INFO - Epoch(train) [36][35/63] lr: 3.5341e-04 eta: 17:52:29 time: 0.5382 data_time: 0.0272 memory: 17620 loss: 3.9460 loss_prob: 2.5169 loss_thr: 0.9260 loss_db: 0.5031 2022/11/01 13:18:40 - mmengine - INFO - Epoch(train) [36][40/63] lr: 3.5341e-04 eta: 17:50:39 time: 0.5669 data_time: 0.0121 memory: 17620 loss: 3.9343 loss_prob: 2.5051 loss_thr: 0.9378 loss_db: 0.4915 2022/11/01 13:18:43 - mmengine - INFO - Epoch(train) [36][45/63] lr: 3.5341e-04 eta: 17:50:39 time: 0.5953 data_time: 0.0071 memory: 17620 loss: 3.7549 loss_prob: 2.3946 loss_thr: 0.9207 loss_db: 0.4397 2022/11/01 13:18:46 - mmengine - INFO - Epoch(train) [36][50/63] lr: 3.5341e-04 eta: 17:48:58 time: 0.5931 data_time: 0.0157 memory: 17620 loss: 3.6921 loss_prob: 2.3589 loss_thr: 0.9075 loss_db: 0.4258 2022/11/01 13:18:49 - mmengine - INFO - Epoch(train) [36][55/63] lr: 3.5341e-04 eta: 17:48:58 time: 0.5983 data_time: 0.0213 memory: 17620 loss: 3.7179 loss_prob: 2.3724 loss_thr: 0.9113 loss_db: 0.4342 2022/11/01 13:18:51 - mmengine - INFO - Epoch(train) [36][60/63] lr: 3.5341e-04 eta: 17:47:11 time: 0.5709 data_time: 0.0144 memory: 17620 loss: 3.7736 loss_prob: 2.3933 loss_thr: 0.9308 loss_db: 0.4495 2022/11/01 13:18:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:18:57 - mmengine - INFO - Epoch(train) [37][5/63] lr: 3.6345e-04 eta: 17:47:11 time: 0.7058 data_time: 0.2046 memory: 17620 loss: 3.9073 loss_prob: 2.4721 loss_thr: 0.9466 loss_db: 0.4885 2022/11/01 13:19:00 - mmengine - INFO - Epoch(train) [37][10/63] lr: 3.6345e-04 eta: 17:44:46 time: 0.7209 data_time: 0.2047 memory: 17620 loss: 4.0991 loss_prob: 2.6156 loss_thr: 0.9540 loss_db: 0.5294 2022/11/01 13:19:03 - mmengine - INFO - Epoch(train) [37][15/63] lr: 3.6345e-04 eta: 17:44:46 time: 0.5159 data_time: 0.0057 memory: 17620 loss: 4.3055 loss_prob: 2.7259 loss_thr: 0.9745 loss_db: 0.6051 2022/11/01 13:19:05 - mmengine - INFO - Epoch(train) [37][20/63] lr: 3.6345e-04 eta: 17:42:49 time: 0.5319 data_time: 0.0055 memory: 17620 loss: 4.3613 loss_prob: 2.7446 loss_thr: 0.9972 loss_db: 0.6195 2022/11/01 13:19:08 - mmengine - INFO - Epoch(train) [37][25/63] lr: 3.6345e-04 eta: 17:42:49 time: 0.5713 data_time: 0.0231 memory: 17620 loss: 4.3225 loss_prob: 2.7205 loss_thr: 1.0158 loss_db: 0.5862 2022/11/01 13:19:11 - mmengine - INFO - Epoch(train) [37][30/63] lr: 3.6345e-04 eta: 17:41:00 time: 0.5557 data_time: 0.0257 memory: 17620 loss: 4.2153 loss_prob: 2.6570 loss_thr: 0.9931 loss_db: 0.5653 2022/11/01 13:19:14 - mmengine - INFO - Epoch(train) [37][35/63] lr: 3.6345e-04 eta: 17:41:00 time: 0.5530 data_time: 0.0080 memory: 17620 loss: 4.2204 loss_prob: 2.6830 loss_thr: 0.9706 loss_db: 0.5667 2022/11/01 13:19:16 - mmengine - INFO - Epoch(train) [37][40/63] lr: 3.6345e-04 eta: 17:39:08 time: 0.5447 data_time: 0.0109 memory: 17620 loss: 4.0874 loss_prob: 2.6058 loss_thr: 0.9465 loss_db: 0.5351 2022/11/01 13:19:19 - mmengine - INFO - Epoch(train) [37][45/63] lr: 3.6345e-04 eta: 17:39:08 time: 0.5196 data_time: 0.0114 memory: 17620 loss: 4.0583 loss_prob: 2.5863 loss_thr: 0.9544 loss_db: 0.5176 2022/11/01 13:19:22 - mmengine - INFO - Epoch(train) [37][50/63] lr: 3.6345e-04 eta: 17:37:15 time: 0.5364 data_time: 0.0171 memory: 17620 loss: 4.1091 loss_prob: 2.6023 loss_thr: 0.9602 loss_db: 0.5466 2022/11/01 13:19:24 - mmengine - INFO - Epoch(train) [37][55/63] lr: 3.6345e-04 eta: 17:37:15 time: 0.5413 data_time: 0.0194 memory: 17620 loss: 4.0756 loss_prob: 2.5753 loss_thr: 0.9579 loss_db: 0.5424 2022/11/01 13:19:27 - mmengine - INFO - Epoch(train) [37][60/63] lr: 3.6345e-04 eta: 17:35:32 time: 0.5669 data_time: 0.0083 memory: 17620 loss: 4.0230 loss_prob: 2.5519 loss_thr: 0.9567 loss_db: 0.5144 2022/11/01 13:19:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:19:35 - mmengine - INFO - Epoch(train) [38][5/63] lr: 3.7349e-04 eta: 17:35:32 time: 0.8110 data_time: 0.2271 memory: 17620 loss: 4.0563 loss_prob: 2.5468 loss_thr: 0.9770 loss_db: 0.5324 2022/11/01 13:19:37 - mmengine - INFO - Epoch(train) [38][10/63] lr: 3.7349e-04 eta: 17:33:46 time: 0.8196 data_time: 0.2241 memory: 17620 loss: 4.0478 loss_prob: 2.5308 loss_thr: 0.9800 loss_db: 0.5369 2022/11/01 13:19:40 - mmengine - INFO - Epoch(train) [38][15/63] lr: 3.7349e-04 eta: 17:33:46 time: 0.5527 data_time: 0.0049 memory: 17620 loss: 4.7225 loss_prob: 2.9083 loss_thr: 1.0724 loss_db: 0.7417 2022/11/01 13:19:43 - mmengine - INFO - Epoch(train) [38][20/63] lr: 3.7349e-04 eta: 17:31:59 time: 0.5474 data_time: 0.0046 memory: 17620 loss: 5.3870 loss_prob: 3.2389 loss_thr: 1.1808 loss_db: 0.9672 2022/11/01 13:19:46 - mmengine - INFO - Epoch(train) [38][25/63] lr: 3.7349e-04 eta: 17:31:59 time: 0.5613 data_time: 0.0205 memory: 17620 loss: 5.3790 loss_prob: 3.1941 loss_thr: 1.1849 loss_db: 1.0000 2022/11/01 13:19:49 - mmengine - INFO - Epoch(train) [38][30/63] lr: 3.7349e-04 eta: 17:30:40 time: 0.6343 data_time: 0.0385 memory: 17620 loss: 5.3855 loss_prob: 3.2152 loss_thr: 1.1703 loss_db: 1.0000 2022/11/01 13:19:52 - mmengine - INFO - Epoch(train) [38][35/63] lr: 3.7349e-04 eta: 17:30:40 time: 0.6292 data_time: 0.0230 memory: 17620 loss: 5.3891 loss_prob: 3.2262 loss_thr: 1.1630 loss_db: 1.0000 2022/11/01 13:19:55 - mmengine - INFO - Epoch(train) [38][40/63] lr: 3.7349e-04 eta: 17:28:53 time: 0.5432 data_time: 0.0052 memory: 17620 loss: 5.3458 loss_prob: 3.1921 loss_thr: 1.1538 loss_db: 1.0000 2022/11/01 13:19:57 - mmengine - INFO - Epoch(train) [38][45/63] lr: 3.7349e-04 eta: 17:28:53 time: 0.5296 data_time: 0.0065 memory: 17620 loss: 5.3814 loss_prob: 3.2243 loss_thr: 1.1571 loss_db: 1.0000 2022/11/01 13:20:00 - mmengine - INFO - Epoch(train) [38][50/63] lr: 3.7349e-04 eta: 17:27:20 time: 0.5845 data_time: 0.0225 memory: 17620 loss: 5.4260 loss_prob: 3.2659 loss_thr: 1.1602 loss_db: 0.9999 2022/11/01 13:20:03 - mmengine - INFO - Epoch(train) [38][55/63] lr: 3.7349e-04 eta: 17:27:20 time: 0.6110 data_time: 0.0264 memory: 17620 loss: 5.4102 loss_prob: 3.2544 loss_thr: 1.1559 loss_db: 1.0000 2022/11/01 13:20:06 - mmengine - INFO - Epoch(train) [38][60/63] lr: 3.7349e-04 eta: 17:25:56 time: 0.6105 data_time: 0.0109 memory: 17620 loss: 5.4266 loss_prob: 3.2741 loss_thr: 1.1525 loss_db: 1.0000 2022/11/01 13:20:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:20:13 - mmengine - INFO - Epoch(train) [39][5/63] lr: 3.8353e-04 eta: 17:25:56 time: 0.7822 data_time: 0.1975 memory: 17620 loss: 5.3219 loss_prob: 3.1754 loss_thr: 1.1465 loss_db: 1.0000 2022/11/01 13:20:16 - mmengine - INFO - Epoch(train) [39][10/63] lr: 3.8353e-04 eta: 17:24:09 time: 0.8014 data_time: 0.1974 memory: 17620 loss: 5.2406 loss_prob: 3.0973 loss_thr: 1.1433 loss_db: 1.0000 2022/11/01 13:20:19 - mmengine - INFO - Epoch(train) [39][15/63] lr: 3.8353e-04 eta: 17:24:09 time: 0.5449 data_time: 0.0058 memory: 17620 loss: 5.2422 loss_prob: 3.0958 loss_thr: 1.1465 loss_db: 1.0000 2022/11/01 13:20:21 - mmengine - INFO - Epoch(train) [39][20/63] lr: 3.8353e-04 eta: 17:22:29 time: 0.5537 data_time: 0.0057 memory: 17620 loss: 5.2505 loss_prob: 3.1000 loss_thr: 1.1506 loss_db: 0.9999 2022/11/01 13:20:24 - mmengine - INFO - Epoch(train) [39][25/63] lr: 3.8353e-04 eta: 17:22:29 time: 0.5797 data_time: 0.0175 memory: 17620 loss: 5.2391 loss_prob: 3.0926 loss_thr: 1.1465 loss_db: 0.9999 2022/11/01 13:20:27 - mmengine - INFO - Epoch(train) [39][30/63] lr: 3.8353e-04 eta: 17:20:57 time: 0.5776 data_time: 0.0303 memory: 17620 loss: 5.2111 loss_prob: 3.0637 loss_thr: 1.1474 loss_db: 1.0000 2022/11/01 13:20:30 - mmengine - INFO - Epoch(train) [39][35/63] lr: 3.8353e-04 eta: 17:20:57 time: 0.5509 data_time: 0.0174 memory: 17620 loss: 5.2407 loss_prob: 3.0866 loss_thr: 1.1541 loss_db: 1.0000 2022/11/01 13:20:33 - mmengine - INFO - Epoch(train) [39][40/63] lr: 3.8353e-04 eta: 17:19:11 time: 0.5309 data_time: 0.0061 memory: 17620 loss: 5.2296 loss_prob: 3.0806 loss_thr: 1.1491 loss_db: 1.0000 2022/11/01 13:20:35 - mmengine - INFO - Epoch(train) [39][45/63] lr: 3.8353e-04 eta: 17:19:11 time: 0.5226 data_time: 0.0064 memory: 17620 loss: 5.1651 loss_prob: 3.0264 loss_thr: 1.1388 loss_db: 0.9999 2022/11/01 13:20:38 - mmengine - INFO - Epoch(train) [39][50/63] lr: 3.8353e-04 eta: 17:17:27 time: 0.5323 data_time: 0.0155 memory: 17620 loss: 5.1630 loss_prob: 3.0155 loss_thr: 1.1475 loss_db: 0.9999 2022/11/01 13:20:40 - mmengine - INFO - Epoch(train) [39][55/63] lr: 3.8353e-04 eta: 17:17:27 time: 0.5332 data_time: 0.0193 memory: 17620 loss: 5.1984 loss_prob: 3.0531 loss_thr: 1.1454 loss_db: 0.9999 2022/11/01 13:20:43 - mmengine - INFO - Epoch(train) [39][60/63] lr: 3.8353e-04 eta: 17:15:36 time: 0.5067 data_time: 0.0088 memory: 17620 loss: 5.2581 loss_prob: 3.1225 loss_thr: 1.1360 loss_db: 0.9997 2022/11/01 13:20:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:20:49 - mmengine - INFO - Epoch(train) [40][5/63] lr: 3.9357e-04 eta: 17:15:36 time: 0.6938 data_time: 0.1919 memory: 17620 loss: 5.2388 loss_prob: 3.0953 loss_thr: 1.1446 loss_db: 0.9989 2022/11/01 13:20:52 - mmengine - INFO - Epoch(train) [40][10/63] lr: 3.9357e-04 eta: 17:13:36 time: 0.7357 data_time: 0.1975 memory: 17620 loss: 5.1959 loss_prob: 3.0576 loss_thr: 1.1406 loss_db: 0.9978 2022/11/01 13:20:55 - mmengine - INFO - Epoch(train) [40][15/63] lr: 3.9357e-04 eta: 17:13:36 time: 0.5814 data_time: 0.0122 memory: 17620 loss: 5.1799 loss_prob: 3.0379 loss_thr: 1.1446 loss_db: 0.9975 2022/11/01 13:20:58 - mmengine - INFO - Epoch(train) [40][20/63] lr: 3.9357e-04 eta: 17:12:11 time: 0.5910 data_time: 0.0056 memory: 17620 loss: 5.2235 loss_prob: 3.0752 loss_thr: 1.1498 loss_db: 0.9986 2022/11/01 13:21:00 - mmengine - INFO - Epoch(train) [40][25/63] lr: 3.9357e-04 eta: 17:12:11 time: 0.5596 data_time: 0.0231 memory: 17620 loss: 5.2048 loss_prob: 3.0618 loss_thr: 1.1436 loss_db: 0.9994 2022/11/01 13:21:03 - mmengine - INFO - Epoch(train) [40][30/63] lr: 3.9357e-04 eta: 17:10:35 time: 0.5478 data_time: 0.0341 memory: 17620 loss: 5.1503 loss_prob: 3.0091 loss_thr: 1.1416 loss_db: 0.9997 2022/11/01 13:21:06 - mmengine - INFO - Epoch(train) [40][35/63] lr: 3.9357e-04 eta: 17:10:35 time: 0.5279 data_time: 0.0181 memory: 17620 loss: 5.2028 loss_prob: 3.0626 loss_thr: 1.1405 loss_db: 0.9998 2022/11/01 13:21:08 - mmengine - INFO - Epoch(train) [40][40/63] lr: 3.9357e-04 eta: 17:08:49 time: 0.5137 data_time: 0.0071 memory: 17620 loss: 5.2161 loss_prob: 3.0900 loss_thr: 1.1263 loss_db: 0.9999 2022/11/01 13:21:11 - mmengine - INFO - Epoch(train) [40][45/63] lr: 3.9357e-04 eta: 17:08:49 time: 0.5230 data_time: 0.0050 memory: 17620 loss: 5.2225 loss_prob: 3.0923 loss_thr: 1.1304 loss_db: 0.9998 2022/11/01 13:21:14 - mmengine - INFO - Epoch(train) [40][50/63] lr: 3.9357e-04 eta: 17:07:13 time: 0.5450 data_time: 0.0130 memory: 17620 loss: 5.2870 loss_prob: 3.1491 loss_thr: 1.1385 loss_db: 0.9994 2022/11/01 13:21:16 - mmengine - INFO - Epoch(train) [40][55/63] lr: 3.9357e-04 eta: 17:07:13 time: 0.5515 data_time: 0.0181 memory: 17620 loss: 5.2929 loss_prob: 3.1562 loss_thr: 1.1376 loss_db: 0.9992 2022/11/01 13:21:19 - mmengine - INFO - Epoch(train) [40][60/63] lr: 3.9357e-04 eta: 17:05:40 time: 0.5496 data_time: 0.0133 memory: 17620 loss: 5.2829 loss_prob: 3.1449 loss_thr: 1.1385 loss_db: 0.9995 2022/11/01 13:21:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:21:20 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/11/01 13:21:27 - mmengine - INFO - Epoch(val) [40][5/32] eta: 17:05:40 time: 1.2304 data_time: 0.0726 memory: 17620 2022/11/01 13:21:29 - mmengine - INFO - Epoch(val) [40][10/32] eta: 0:00:11 time: 0.5188 data_time: 0.0974 memory: 15725 2022/11/01 13:21:31 - mmengine - INFO - Epoch(val) [40][15/32] eta: 0:00:11 time: 0.4680 data_time: 0.0473 memory: 15725 2022/11/01 13:21:34 - mmengine - INFO - Epoch(val) [40][20/32] eta: 0:00:05 time: 0.4846 data_time: 0.0674 memory: 15725 2022/11/01 13:21:36 - mmengine - INFO - Epoch(val) [40][25/32] eta: 0:00:05 time: 0.4752 data_time: 0.0604 memory: 15725 2022/11/01 13:21:38 - mmengine - INFO - Epoch(val) [40][30/32] eta: 0:00:00 time: 0.4307 data_time: 0.0195 memory: 15725 2022/11/01 13:21:39 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:21:39 - mmengine - INFO - Epoch(val) [40][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/11/01 13:21:44 - mmengine - INFO - Epoch(train) [41][5/63] lr: 4.0361e-04 eta: 0:00:00 time: 0.7164 data_time: 0.2080 memory: 17620 loss: 5.1753 loss_prob: 3.0468 loss_thr: 1.1287 loss_db: 0.9998 2022/11/01 13:21:46 - mmengine - INFO - Epoch(train) [41][10/63] lr: 4.0361e-04 eta: 17:03:45 time: 0.7348 data_time: 0.2086 memory: 17620 loss: 5.0924 loss_prob: 2.9747 loss_thr: 1.1186 loss_db: 0.9991 2022/11/01 13:21:49 - mmengine - INFO - Epoch(train) [41][15/63] lr: 4.0361e-04 eta: 17:03:45 time: 0.5222 data_time: 0.0058 memory: 17620 loss: 5.1152 loss_prob: 2.9942 loss_thr: 1.1225 loss_db: 0.9985 2022/11/01 13:21:51 - mmengine - INFO - Epoch(train) [41][20/63] lr: 4.0361e-04 eta: 17:02:07 time: 0.5305 data_time: 0.0054 memory: 17620 loss: 5.1698 loss_prob: 3.0499 loss_thr: 1.1217 loss_db: 0.9981 2022/11/01 13:21:54 - mmengine - INFO - Epoch(train) [41][25/63] lr: 4.0361e-04 eta: 17:02:07 time: 0.5275 data_time: 0.0068 memory: 17620 loss: 5.1609 loss_prob: 3.0690 loss_thr: 1.1014 loss_db: 0.9906 2022/11/01 13:21:57 - mmengine - INFO - Epoch(train) [41][30/63] lr: 4.0361e-04 eta: 17:00:40 time: 0.5652 data_time: 0.0347 memory: 17620 loss: 5.1586 loss_prob: 3.0589 loss_thr: 1.1147 loss_db: 0.9850 2022/11/01 13:22:00 - mmengine - INFO - Epoch(train) [41][35/63] lr: 4.0361e-04 eta: 17:00:40 time: 0.5724 data_time: 0.0326 memory: 17620 loss: 5.1603 loss_prob: 3.0502 loss_thr: 1.1289 loss_db: 0.9811 2022/11/01 13:22:03 - mmengine - INFO - Epoch(train) [41][40/63] lr: 4.0361e-04 eta: 16:59:12 time: 0.5588 data_time: 0.0046 memory: 17620 loss: 5.1370 loss_prob: 3.0204 loss_thr: 1.1354 loss_db: 0.9812 2022/11/01 13:22:06 - mmengine - INFO - Epoch(train) [41][45/63] lr: 4.0361e-04 eta: 16:59:12 time: 0.6577 data_time: 0.0048 memory: 17620 loss: 5.1203 loss_prob: 2.9852 loss_thr: 1.1552 loss_db: 0.9799 2022/11/01 13:22:10 - mmengine - INFO - Epoch(train) [41][50/63] lr: 4.0361e-04 eta: 16:58:20 time: 0.6814 data_time: 0.0156 memory: 17620 loss: 5.1369 loss_prob: 3.0042 loss_thr: 1.1577 loss_db: 0.9750 2022/11/01 13:22:13 - mmengine - INFO - Epoch(train) [41][55/63] lr: 4.0361e-04 eta: 16:58:20 time: 0.6057 data_time: 0.0220 memory: 17620 loss: 5.1638 loss_prob: 3.0234 loss_thr: 1.1539 loss_db: 0.9865 2022/11/01 13:22:15 - mmengine - INFO - Epoch(train) [41][60/63] lr: 4.0361e-04 eta: 16:57:00 time: 0.5838 data_time: 0.0123 memory: 17620 loss: 5.1409 loss_prob: 2.9944 loss_thr: 1.1487 loss_db: 0.9979 2022/11/01 13:22:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:22:22 - mmengine - INFO - Epoch(train) [42][5/63] lr: 4.1365e-04 eta: 16:57:00 time: 0.7879 data_time: 0.1832 memory: 17620 loss: 5.0837 loss_prob: 2.9573 loss_thr: 1.1293 loss_db: 0.9971 2022/11/01 13:22:25 - mmengine - INFO - Epoch(train) [42][10/63] lr: 4.1365e-04 eta: 16:55:17 time: 0.7602 data_time: 0.1850 memory: 17620 loss: 5.0669 loss_prob: 2.9452 loss_thr: 1.1305 loss_db: 0.9912 2022/11/01 13:22:28 - mmengine - INFO - Epoch(train) [42][15/63] lr: 4.1365e-04 eta: 16:55:17 time: 0.5666 data_time: 0.0085 memory: 17620 loss: 5.0561 loss_prob: 2.9378 loss_thr: 1.1436 loss_db: 0.9747 2022/11/01 13:22:31 - mmengine - INFO - Epoch(train) [42][20/63] lr: 4.1365e-04 eta: 16:54:00 time: 0.5908 data_time: 0.0059 memory: 17620 loss: 5.0571 loss_prob: 2.9338 loss_thr: 1.1429 loss_db: 0.9805 2022/11/01 13:22:34 - mmengine - INFO - Epoch(train) [42][25/63] lr: 4.1365e-04 eta: 16:54:00 time: 0.6232 data_time: 0.0180 memory: 17620 loss: 5.1062 loss_prob: 2.9738 loss_thr: 1.1332 loss_db: 0.9992 2022/11/01 13:22:37 - mmengine - INFO - Epoch(train) [42][30/63] lr: 4.1365e-04 eta: 16:53:04 time: 0.6622 data_time: 0.0459 memory: 17620 loss: 5.1282 loss_prob: 3.0101 loss_thr: 1.1288 loss_db: 0.9893 2022/11/01 13:22:40 - mmengine - INFO - Epoch(train) [42][35/63] lr: 4.1365e-04 eta: 16:53:04 time: 0.6035 data_time: 0.0328 memory: 17620 loss: 5.0994 loss_prob: 2.9922 loss_thr: 1.1380 loss_db: 0.9691 2022/11/01 13:22:43 - mmengine - INFO - Epoch(train) [42][40/63] lr: 4.1365e-04 eta: 16:51:46 time: 0.5826 data_time: 0.0068 memory: 17620 loss: 5.0604 loss_prob: 2.9627 loss_thr: 1.1368 loss_db: 0.9609 2022/11/01 13:22:46 - mmengine - INFO - Epoch(train) [42][45/63] lr: 4.1365e-04 eta: 16:51:46 time: 0.5761 data_time: 0.0083 memory: 17620 loss: 4.9971 loss_prob: 2.9442 loss_thr: 1.1190 loss_db: 0.9339 2022/11/01 13:22:49 - mmengine - INFO - Epoch(train) [42][50/63] lr: 4.1365e-04 eta: 16:50:19 time: 0.5465 data_time: 0.0128 memory: 17620 loss: 4.9726 loss_prob: 2.9391 loss_thr: 1.1206 loss_db: 0.9129 2022/11/01 13:22:51 - mmengine - INFO - Epoch(train) [42][55/63] lr: 4.1365e-04 eta: 16:50:19 time: 0.5690 data_time: 0.0207 memory: 17620 loss: 4.9980 loss_prob: 2.9450 loss_thr: 1.1278 loss_db: 0.9252 2022/11/01 13:22:54 - mmengine - INFO - Epoch(train) [42][60/63] lr: 4.1365e-04 eta: 16:48:56 time: 0.5622 data_time: 0.0170 memory: 17620 loss: 4.9732 loss_prob: 2.9501 loss_thr: 1.1236 loss_db: 0.8994 2022/11/01 13:22:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:23:00 - mmengine - INFO - Epoch(train) [43][5/63] lr: 4.2369e-04 eta: 16:48:56 time: 0.7362 data_time: 0.1865 memory: 17620 loss: 5.1069 loss_prob: 2.9891 loss_thr: 1.1427 loss_db: 0.9751 2022/11/01 13:23:03 - mmengine - INFO - Epoch(train) [43][10/63] lr: 4.2369e-04 eta: 16:47:18 time: 0.7620 data_time: 0.1977 memory: 17620 loss: 5.0453 loss_prob: 2.9647 loss_thr: 1.1581 loss_db: 0.9225 2022/11/01 13:23:06 - mmengine - INFO - Epoch(train) [43][15/63] lr: 4.2369e-04 eta: 16:47:18 time: 0.5296 data_time: 0.0159 memory: 17620 loss: 5.0212 loss_prob: 2.9569 loss_thr: 1.1618 loss_db: 0.9026 2022/11/01 13:23:09 - mmengine - INFO - Epoch(train) [43][20/63] lr: 4.2369e-04 eta: 16:45:54 time: 0.5489 data_time: 0.0050 memory: 17620 loss: 5.0124 loss_prob: 2.9407 loss_thr: 1.1544 loss_db: 0.9173 2022/11/01 13:23:11 - mmengine - INFO - Epoch(train) [43][25/63] lr: 4.2369e-04 eta: 16:45:54 time: 0.5754 data_time: 0.0174 memory: 17620 loss: 4.9919 loss_prob: 2.9283 loss_thr: 1.1553 loss_db: 0.9083 2022/11/01 13:23:14 - mmengine - INFO - Epoch(train) [43][30/63] lr: 4.2369e-04 eta: 16:44:27 time: 0.5384 data_time: 0.0176 memory: 17620 loss: 4.9454 loss_prob: 2.9259 loss_thr: 1.1457 loss_db: 0.8738 2022/11/01 13:23:17 - mmengine - INFO - Epoch(train) [43][35/63] lr: 4.2369e-04 eta: 16:44:27 time: 0.5279 data_time: 0.0243 memory: 17620 loss: 4.8820 loss_prob: 2.9281 loss_thr: 1.1209 loss_db: 0.8331 2022/11/01 13:23:19 - mmengine - INFO - Epoch(train) [43][40/63] lr: 4.2369e-04 eta: 16:43:04 time: 0.5518 data_time: 0.0241 memory: 17620 loss: 4.8783 loss_prob: 2.9371 loss_thr: 1.1194 loss_db: 0.8218 2022/11/01 13:23:22 - mmengine - INFO - Epoch(train) [43][45/63] lr: 4.2369e-04 eta: 16:43:04 time: 0.5508 data_time: 0.0048 memory: 17620 loss: 4.8775 loss_prob: 2.9235 loss_thr: 1.1344 loss_db: 0.8197 2022/11/01 13:23:25 - mmengine - INFO - Epoch(train) [43][50/63] lr: 4.2369e-04 eta: 16:41:39 time: 0.5440 data_time: 0.0130 memory: 17620 loss: 4.7783 loss_prob: 2.8823 loss_thr: 1.1137 loss_db: 0.7823 2022/11/01 13:23:28 - mmengine - INFO - Epoch(train) [43][55/63] lr: 4.2369e-04 eta: 16:41:39 time: 0.5371 data_time: 0.0181 memory: 17620 loss: 4.8191 loss_prob: 2.9032 loss_thr: 1.1169 loss_db: 0.7991 2022/11/01 13:23:31 - mmengine - INFO - Epoch(train) [43][60/63] lr: 4.2369e-04 eta: 16:40:23 time: 0.5701 data_time: 0.0126 memory: 17620 loss: 4.8528 loss_prob: 2.9298 loss_thr: 1.1220 loss_db: 0.8010 2022/11/01 13:23:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:23:37 - mmengine - INFO - Epoch(train) [44][5/63] lr: 4.3373e-04 eta: 16:40:23 time: 0.7262 data_time: 0.1949 memory: 17620 loss: 4.7174 loss_prob: 2.8895 loss_thr: 1.0838 loss_db: 0.7442 2022/11/01 13:23:39 - mmengine - INFO - Epoch(train) [44][10/63] lr: 4.3373e-04 eta: 16:38:45 time: 0.7454 data_time: 0.1963 memory: 17620 loss: 4.7109 loss_prob: 2.8604 loss_thr: 1.0827 loss_db: 0.7678 2022/11/01 13:23:42 - mmengine - INFO - Epoch(train) [44][15/63] lr: 4.3373e-04 eta: 16:38:45 time: 0.5370 data_time: 0.0109 memory: 17620 loss: 4.7473 loss_prob: 2.8734 loss_thr: 1.0846 loss_db: 0.7892 2022/11/01 13:23:45 - mmengine - INFO - Epoch(train) [44][20/63] lr: 4.3373e-04 eta: 16:37:20 time: 0.5332 data_time: 0.0097 memory: 17620 loss: 4.7878 loss_prob: 2.8981 loss_thr: 1.1072 loss_db: 0.7825 2022/11/01 13:23:48 - mmengine - INFO - Epoch(train) [44][25/63] lr: 4.3373e-04 eta: 16:37:20 time: 0.5591 data_time: 0.0297 memory: 17620 loss: 4.7430 loss_prob: 2.8857 loss_thr: 1.0878 loss_db: 0.7695 2022/11/01 13:23:50 - mmengine - INFO - Epoch(train) [44][30/63] lr: 4.3373e-04 eta: 16:36:04 time: 0.5667 data_time: 0.0298 memory: 17620 loss: 4.7072 loss_prob: 2.8738 loss_thr: 1.0910 loss_db: 0.7424 2022/11/01 13:23:53 - mmengine - INFO - Epoch(train) [44][35/63] lr: 4.3373e-04 eta: 16:36:04 time: 0.5419 data_time: 0.0126 memory: 17620 loss: 4.6389 loss_prob: 2.8329 loss_thr: 1.0876 loss_db: 0.7185 2022/11/01 13:23:56 - mmengine - INFO - Epoch(train) [44][40/63] lr: 4.3373e-04 eta: 16:34:40 time: 0.5347 data_time: 0.0132 memory: 17620 loss: 4.6210 loss_prob: 2.8418 loss_thr: 1.0564 loss_db: 0.7228 2022/11/01 13:23:58 - mmengine - INFO - Epoch(train) [44][45/63] lr: 4.3373e-04 eta: 16:34:40 time: 0.5103 data_time: 0.0056 memory: 17620 loss: 4.7041 loss_prob: 2.8914 loss_thr: 1.0678 loss_db: 0.7450 2022/11/01 13:24:01 - mmengine - INFO - Epoch(train) [44][50/63] lr: 4.3373e-04 eta: 16:33:22 time: 0.5557 data_time: 0.0195 memory: 17620 loss: 4.7262 loss_prob: 2.8871 loss_thr: 1.0733 loss_db: 0.7658 2022/11/01 13:24:04 - mmengine - INFO - Epoch(train) [44][55/63] lr: 4.3373e-04 eta: 16:33:22 time: 0.5649 data_time: 0.0195 memory: 17620 loss: 4.6071 loss_prob: 2.8404 loss_thr: 1.0659 loss_db: 0.7008 2022/11/01 13:24:07 - mmengine - INFO - Epoch(train) [44][60/63] lr: 4.3373e-04 eta: 16:32:00 time: 0.5370 data_time: 0.0088 memory: 17620 loss: 4.5666 loss_prob: 2.8268 loss_thr: 1.0668 loss_db: 0.6730 2022/11/01 13:24:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:24:13 - mmengine - INFO - Epoch(train) [45][5/63] lr: 4.4377e-04 eta: 16:32:00 time: 0.7444 data_time: 0.2263 memory: 17620 loss: 4.6535 loss_prob: 2.8650 loss_thr: 1.0695 loss_db: 0.7190 2022/11/01 13:24:16 - mmengine - INFO - Epoch(train) [45][10/63] lr: 4.4377e-04 eta: 16:30:42 time: 0.8053 data_time: 0.2249 memory: 17620 loss: 4.6803 loss_prob: 2.8644 loss_thr: 1.0752 loss_db: 0.7407 2022/11/01 13:24:19 - mmengine - INFO - Epoch(train) [45][15/63] lr: 4.4377e-04 eta: 16:30:42 time: 0.6289 data_time: 0.0063 memory: 17620 loss: 4.6628 loss_prob: 2.8566 loss_thr: 1.0716 loss_db: 0.7345 2022/11/01 13:24:22 - mmengine - INFO - Epoch(train) [45][20/63] lr: 4.4377e-04 eta: 16:29:42 time: 0.6173 data_time: 0.0046 memory: 17620 loss: 4.6854 loss_prob: 2.8612 loss_thr: 1.0622 loss_db: 0.7620 2022/11/01 13:24:26 - mmengine - INFO - Epoch(train) [45][25/63] lr: 4.4377e-04 eta: 16:29:42 time: 0.6453 data_time: 0.0356 memory: 17620 loss: 4.5590 loss_prob: 2.8176 loss_thr: 1.0431 loss_db: 0.6983 2022/11/01 13:24:30 - mmengine - INFO - Epoch(train) [45][30/63] lr: 4.4377e-04 eta: 16:29:10 time: 0.7246 data_time: 0.0360 memory: 17620 loss: 4.5468 loss_prob: 2.7918 loss_thr: 1.0566 loss_db: 0.6985 2022/11/01 13:24:33 - mmengine - INFO - Epoch(train) [45][35/63] lr: 4.4377e-04 eta: 16:29:10 time: 0.7122 data_time: 0.0052 memory: 17620 loss: 4.5602 loss_prob: 2.8017 loss_thr: 1.0440 loss_db: 0.7145 2022/11/01 13:24:36 - mmengine - INFO - Epoch(train) [45][40/63] lr: 4.4377e-04 eta: 16:28:15 time: 0.6355 data_time: 0.0061 memory: 17620 loss: 4.5071 loss_prob: 2.8106 loss_thr: 1.0318 loss_db: 0.6647 2022/11/01 13:24:39 - mmengine - INFO - Epoch(train) [45][45/63] lr: 4.4377e-04 eta: 16:28:15 time: 0.5967 data_time: 0.0060 memory: 17620 loss: 4.4351 loss_prob: 2.7855 loss_thr: 1.0051 loss_db: 0.6445 2022/11/01 13:24:42 - mmengine - INFO - Epoch(train) [45][50/63] lr: 4.4377e-04 eta: 16:27:14 time: 0.6103 data_time: 0.0197 memory: 17620 loss: 4.4255 loss_prob: 2.7875 loss_thr: 1.0059 loss_db: 0.6320 2022/11/01 13:24:45 - mmengine - INFO - Epoch(train) [45][55/63] lr: 4.4377e-04 eta: 16:27:14 time: 0.5967 data_time: 0.0242 memory: 17620 loss: 4.4271 loss_prob: 2.7732 loss_thr: 1.0255 loss_db: 0.6284 2022/11/01 13:24:48 - mmengine - INFO - Epoch(train) [45][60/63] lr: 4.4377e-04 eta: 16:26:01 time: 0.5578 data_time: 0.0095 memory: 17620 loss: 4.4064 loss_prob: 2.7596 loss_thr: 1.0139 loss_db: 0.6329 2022/11/01 13:24:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:24:55 - mmengine - INFO - Epoch(train) [46][5/63] lr: 4.5381e-04 eta: 16:26:01 time: 0.8986 data_time: 0.2123 memory: 17620 loss: 4.2580 loss_prob: 2.6954 loss_thr: 0.9907 loss_db: 0.5719 2022/11/01 13:24:58 - mmengine - INFO - Epoch(train) [46][10/63] lr: 4.5381e-04 eta: 16:25:03 time: 0.8745 data_time: 0.2115 memory: 17620 loss: 4.1951 loss_prob: 2.6723 loss_thr: 0.9709 loss_db: 0.5519 2022/11/01 13:25:01 - mmengine - INFO - Epoch(train) [46][15/63] lr: 4.5381e-04 eta: 16:25:03 time: 0.5367 data_time: 0.0075 memory: 17620 loss: 4.3957 loss_prob: 2.7596 loss_thr: 0.9946 loss_db: 0.6415 2022/11/01 13:25:04 - mmengine - INFO - Epoch(train) [46][20/63] lr: 4.5381e-04 eta: 16:23:53 time: 0.5702 data_time: 0.0052 memory: 17620 loss: 4.4677 loss_prob: 2.7978 loss_thr: 0.9971 loss_db: 0.6727 2022/11/01 13:25:07 - mmengine - INFO - Epoch(train) [46][25/63] lr: 4.5381e-04 eta: 16:23:53 time: 0.6097 data_time: 0.0355 memory: 17620 loss: 4.3820 loss_prob: 2.7706 loss_thr: 0.9739 loss_db: 0.6375 2022/11/01 13:25:10 - mmengine - INFO - Epoch(train) [46][30/63] lr: 4.5381e-04 eta: 16:23:01 time: 0.6375 data_time: 0.0420 memory: 17620 loss: 4.3641 loss_prob: 2.7451 loss_thr: 0.9797 loss_db: 0.6393 2022/11/01 13:25:13 - mmengine - INFO - Epoch(train) [46][35/63] lr: 4.5381e-04 eta: 16:23:01 time: 0.6025 data_time: 0.0114 memory: 17620 loss: 4.3500 loss_prob: 2.7323 loss_thr: 0.9886 loss_db: 0.6292 2022/11/01 13:25:16 - mmengine - INFO - Epoch(train) [46][40/63] lr: 4.5381e-04 eta: 16:21:43 time: 0.5323 data_time: 0.0051 memory: 17620 loss: 4.2693 loss_prob: 2.6965 loss_thr: 0.9817 loss_db: 0.5911 2022/11/01 13:25:18 - mmengine - INFO - Epoch(train) [46][45/63] lr: 4.5381e-04 eta: 16:21:43 time: 0.5174 data_time: 0.0049 memory: 17620 loss: 4.2849 loss_prob: 2.7203 loss_thr: 0.9809 loss_db: 0.5838 2022/11/01 13:25:21 - mmengine - INFO - Epoch(train) [46][50/63] lr: 4.5381e-04 eta: 16:20:32 time: 0.5626 data_time: 0.0183 memory: 17620 loss: 4.2615 loss_prob: 2.7100 loss_thr: 0.9737 loss_db: 0.5777 2022/11/01 13:25:24 - mmengine - INFO - Epoch(train) [46][55/63] lr: 4.5381e-04 eta: 16:20:32 time: 0.5699 data_time: 0.0205 memory: 17620 loss: 4.2793 loss_prob: 2.7240 loss_thr: 0.9636 loss_db: 0.5917 2022/11/01 13:25:26 - mmengine - INFO - Epoch(train) [46][60/63] lr: 4.5381e-04 eta: 16:19:15 time: 0.5329 data_time: 0.0073 memory: 17620 loss: 4.2952 loss_prob: 2.7597 loss_thr: 0.9568 loss_db: 0.5787 2022/11/01 13:25:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:25:33 - mmengine - INFO - Epoch(train) [47][5/63] lr: 4.6385e-04 eta: 16:19:15 time: 0.7068 data_time: 0.1803 memory: 17620 loss: 4.2665 loss_prob: 2.7078 loss_thr: 0.9733 loss_db: 0.5854 2022/11/01 13:25:35 - mmengine - INFO - Epoch(train) [47][10/63] lr: 4.6385e-04 eta: 16:17:45 time: 0.7346 data_time: 0.1870 memory: 17620 loss: 4.4516 loss_prob: 2.7995 loss_thr: 1.0134 loss_db: 0.6387 2022/11/01 13:25:38 - mmengine - INFO - Epoch(train) [47][15/63] lr: 4.6385e-04 eta: 16:17:45 time: 0.5133 data_time: 0.0119 memory: 17620 loss: 4.5926 loss_prob: 2.8341 loss_thr: 1.0244 loss_db: 0.7342 2022/11/01 13:25:40 - mmengine - INFO - Epoch(train) [47][20/63] lr: 4.6385e-04 eta: 16:16:23 time: 0.5112 data_time: 0.0051 memory: 17620 loss: 4.6172 loss_prob: 2.8362 loss_thr: 1.0384 loss_db: 0.7425 2022/11/01 13:25:43 - mmengine - INFO - Epoch(train) [47][25/63] lr: 4.6385e-04 eta: 16:16:23 time: 0.5432 data_time: 0.0238 memory: 17620 loss: 4.4789 loss_prob: 2.7994 loss_thr: 1.0227 loss_db: 0.6569 2022/11/01 13:25:46 - mmengine - INFO - Epoch(train) [47][30/63] lr: 4.6385e-04 eta: 16:15:23 time: 0.5960 data_time: 0.0272 memory: 17620 loss: 4.4763 loss_prob: 2.8011 loss_thr: 1.0161 loss_db: 0.6591 2022/11/01 13:25:49 - mmengine - INFO - Epoch(train) [47][35/63] lr: 4.6385e-04 eta: 16:15:23 time: 0.5795 data_time: 0.0176 memory: 17620 loss: 4.3997 loss_prob: 2.7559 loss_thr: 1.0146 loss_db: 0.6292 2022/11/01 13:25:52 - mmengine - INFO - Epoch(train) [47][40/63] lr: 4.6385e-04 eta: 16:14:19 time: 0.5769 data_time: 0.0168 memory: 17620 loss: 4.2544 loss_prob: 2.6814 loss_thr: 0.9893 loss_db: 0.5837 2022/11/01 13:25:55 - mmengine - INFO - Epoch(train) [47][45/63] lr: 4.6385e-04 eta: 16:14:19 time: 0.5765 data_time: 0.0105 memory: 17620 loss: 4.4089 loss_prob: 2.7706 loss_thr: 0.9859 loss_db: 0.6523 2022/11/01 13:25:57 - mmengine - INFO - Epoch(train) [47][50/63] lr: 4.6385e-04 eta: 16:13:03 time: 0.5313 data_time: 0.0183 memory: 17620 loss: 4.5491 loss_prob: 2.8271 loss_thr: 1.0134 loss_db: 0.7086 2022/11/01 13:26:00 - mmengine - INFO - Epoch(train) [47][55/63] lr: 4.6385e-04 eta: 16:13:03 time: 0.5403 data_time: 0.0175 memory: 17620 loss: 4.4415 loss_prob: 2.7443 loss_thr: 1.0118 loss_db: 0.6853 2022/11/01 13:26:03 - mmengine - INFO - Epoch(train) [47][60/63] lr: 4.6385e-04 eta: 16:11:56 time: 0.5603 data_time: 0.0109 memory: 17620 loss: 4.2456 loss_prob: 2.6607 loss_thr: 0.9834 loss_db: 0.6016 2022/11/01 13:26:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:26:09 - mmengine - INFO - Epoch(train) [48][5/63] lr: 4.7389e-04 eta: 16:11:56 time: 0.7248 data_time: 0.2217 memory: 17620 loss: 4.2042 loss_prob: 2.6556 loss_thr: 0.9714 loss_db: 0.5772 2022/11/01 13:26:12 - mmengine - INFO - Epoch(train) [48][10/63] lr: 4.7389e-04 eta: 16:10:32 time: 0.7440 data_time: 0.2218 memory: 17620 loss: 4.2195 loss_prob: 2.6868 loss_thr: 0.9575 loss_db: 0.5753 2022/11/01 13:26:14 - mmengine - INFO - Epoch(train) [48][15/63] lr: 4.7389e-04 eta: 16:10:32 time: 0.5222 data_time: 0.0051 memory: 17620 loss: 4.3676 loss_prob: 2.7504 loss_thr: 0.9856 loss_db: 0.6317 2022/11/01 13:26:17 - mmengine - INFO - Epoch(train) [48][20/63] lr: 4.7389e-04 eta: 16:09:14 time: 0.5136 data_time: 0.0049 memory: 17620 loss: 4.4396 loss_prob: 2.7640 loss_thr: 0.9935 loss_db: 0.6821 2022/11/01 13:26:20 - mmengine - INFO - Epoch(train) [48][25/63] lr: 4.7389e-04 eta: 16:09:14 time: 0.5764 data_time: 0.0439 memory: 17620 loss: 4.3874 loss_prob: 2.7397 loss_thr: 0.9870 loss_db: 0.6607 2022/11/01 13:26:23 - mmengine - INFO - Epoch(train) [48][30/63] lr: 4.7389e-04 eta: 16:08:15 time: 0.5924 data_time: 0.0477 memory: 17620 loss: 4.3606 loss_prob: 2.7252 loss_thr: 0.9894 loss_db: 0.6460 2022/11/01 13:26:26 - mmengine - INFO - Epoch(train) [48][35/63] lr: 4.7389e-04 eta: 16:08:15 time: 0.5841 data_time: 0.0086 memory: 17620 loss: 4.2263 loss_prob: 2.6611 loss_thr: 0.9821 loss_db: 0.5831 2022/11/01 13:26:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:26:29 - mmengine - INFO - Epoch(train) [48][40/63] lr: 4.7389e-04 eta: 16:07:25 time: 0.6271 data_time: 0.0049 memory: 17620 loss: 4.1844 loss_prob: 2.6314 loss_thr: 0.9767 loss_db: 0.5764 2022/11/01 13:26:32 - mmengine - INFO - Epoch(train) [48][45/63] lr: 4.7389e-04 eta: 16:07:25 time: 0.6213 data_time: 0.0048 memory: 17620 loss: 4.2828 loss_prob: 2.6786 loss_thr: 1.0003 loss_db: 0.6039 2022/11/01 13:26:35 - mmengine - INFO - Epoch(train) [48][50/63] lr: 4.7389e-04 eta: 16:06:30 time: 0.6037 data_time: 0.0227 memory: 17620 loss: 4.2051 loss_prob: 2.6464 loss_thr: 0.9921 loss_db: 0.5666 2022/11/01 13:26:38 - mmengine - INFO - Epoch(train) [48][55/63] lr: 4.7389e-04 eta: 16:06:30 time: 0.5651 data_time: 0.0235 memory: 17620 loss: 4.2074 loss_prob: 2.6695 loss_thr: 0.9648 loss_db: 0.5732 2022/11/01 13:26:41 - mmengine - INFO - Epoch(train) [48][60/63] lr: 4.7389e-04 eta: 16:05:20 time: 0.5394 data_time: 0.0067 memory: 17620 loss: 4.2515 loss_prob: 2.6772 loss_thr: 0.9770 loss_db: 0.5973 2022/11/01 13:26:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:26:47 - mmengine - INFO - Epoch(train) [49][5/63] lr: 4.8393e-04 eta: 16:05:20 time: 0.7454 data_time: 0.1832 memory: 17620 loss: 4.1574 loss_prob: 2.6156 loss_thr: 0.9931 loss_db: 0.5486 2022/11/01 13:26:49 - mmengine - INFO - Epoch(train) [49][10/63] lr: 4.8393e-04 eta: 16:04:04 time: 0.7633 data_time: 0.1843 memory: 17620 loss: 4.1586 loss_prob: 2.6101 loss_thr: 0.9772 loss_db: 0.5713 2022/11/01 13:26:52 - mmengine - INFO - Epoch(train) [49][15/63] lr: 4.8393e-04 eta: 16:04:04 time: 0.5390 data_time: 0.0060 memory: 17620 loss: 4.1033 loss_prob: 2.6028 loss_thr: 0.9579 loss_db: 0.5425 2022/11/01 13:26:56 - mmengine - INFO - Epoch(train) [49][20/63] lr: 4.8393e-04 eta: 16:03:20 time: 0.6463 data_time: 0.0092 memory: 17620 loss: 4.1541 loss_prob: 2.6293 loss_thr: 0.9636 loss_db: 0.5612 2022/11/01 13:26:59 - mmengine - INFO - Epoch(train) [49][25/63] lr: 4.8393e-04 eta: 16:03:20 time: 0.6875 data_time: 0.0324 memory: 17620 loss: 4.1429 loss_prob: 2.6130 loss_thr: 0.9639 loss_db: 0.5660 2022/11/01 13:27:03 - mmengine - INFO - Epoch(train) [49][30/63] lr: 4.8393e-04 eta: 16:02:46 time: 0.6874 data_time: 0.0311 memory: 17620 loss: 4.1348 loss_prob: 2.6078 loss_thr: 0.9569 loss_db: 0.5700 2022/11/01 13:27:06 - mmengine - INFO - Epoch(train) [49][35/63] lr: 4.8393e-04 eta: 16:02:46 time: 0.6710 data_time: 0.0081 memory: 17620 loss: 4.1606 loss_prob: 2.6218 loss_thr: 0.9603 loss_db: 0.5784 2022/11/01 13:27:08 - mmengine - INFO - Epoch(train) [49][40/63] lr: 4.8393e-04 eta: 16:01:43 time: 0.5659 data_time: 0.0052 memory: 17620 loss: 4.1150 loss_prob: 2.6110 loss_thr: 0.9640 loss_db: 0.5400 2022/11/01 13:27:11 - mmengine - INFO - Epoch(train) [49][45/63] lr: 4.8393e-04 eta: 16:01:43 time: 0.5595 data_time: 0.0077 memory: 17620 loss: 4.1411 loss_prob: 2.6052 loss_thr: 0.9859 loss_db: 0.5500 2022/11/01 13:27:15 - mmengine - INFO - Epoch(train) [49][50/63] lr: 4.8393e-04 eta: 16:00:56 time: 0.6278 data_time: 0.0211 memory: 17620 loss: 4.0407 loss_prob: 2.5385 loss_thr: 0.9697 loss_db: 0.5325 2022/11/01 13:27:18 - mmengine - INFO - Epoch(train) [49][55/63] lr: 4.8393e-04 eta: 16:00:56 time: 0.6127 data_time: 0.0219 memory: 17620 loss: 3.7867 loss_prob: 2.4021 loss_thr: 0.9324 loss_db: 0.4521 2022/11/01 13:27:20 - mmengine - INFO - Epoch(train) [49][60/63] lr: 4.8393e-04 eta: 15:59:47 time: 0.5351 data_time: 0.0089 memory: 17620 loss: 3.8265 loss_prob: 2.4467 loss_thr: 0.9126 loss_db: 0.4672 2022/11/01 13:27:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:27:26 - mmengine - INFO - Epoch(train) [50][5/63] lr: 4.9397e-04 eta: 15:59:47 time: 0.7355 data_time: 0.2197 memory: 17620 loss: 3.9477 loss_prob: 2.5267 loss_thr: 0.9305 loss_db: 0.4905 2022/11/01 13:27:29 - mmengine - INFO - Epoch(train) [50][10/63] lr: 4.9397e-04 eta: 15:58:37 time: 0.7767 data_time: 0.2184 memory: 17620 loss: 3.9295 loss_prob: 2.4904 loss_thr: 0.9495 loss_db: 0.4896 2022/11/01 13:27:32 - mmengine - INFO - Epoch(train) [50][15/63] lr: 4.9397e-04 eta: 15:58:37 time: 0.5906 data_time: 0.0051 memory: 17620 loss: 3.7995 loss_prob: 2.4172 loss_thr: 0.9193 loss_db: 0.4630 2022/11/01 13:27:35 - mmengine - INFO - Epoch(train) [50][20/63] lr: 4.9397e-04 eta: 15:57:38 time: 0.5761 data_time: 0.0067 memory: 17620 loss: 3.8519 loss_prob: 2.4768 loss_thr: 0.9073 loss_db: 0.4678 2022/11/01 13:27:38 - mmengine - INFO - Epoch(train) [50][25/63] lr: 4.9397e-04 eta: 15:57:38 time: 0.5552 data_time: 0.0299 memory: 17620 loss: 3.8391 loss_prob: 2.4617 loss_thr: 0.9009 loss_db: 0.4765 2022/11/01 13:27:41 - mmengine - INFO - Epoch(train) [50][30/63] lr: 4.9397e-04 eta: 15:56:35 time: 0.5544 data_time: 0.0319 memory: 17620 loss: 3.7295 loss_prob: 2.3612 loss_thr: 0.9211 loss_db: 0.4471 2022/11/01 13:27:43 - mmengine - INFO - Epoch(train) [50][35/63] lr: 4.9397e-04 eta: 15:56:35 time: 0.5286 data_time: 0.0089 memory: 17620 loss: 3.8780 loss_prob: 2.4316 loss_thr: 0.9610 loss_db: 0.4854 2022/11/01 13:27:46 - mmengine - INFO - Epoch(train) [50][40/63] lr: 4.9397e-04 eta: 15:55:25 time: 0.5255 data_time: 0.0059 memory: 17620 loss: 3.8795 loss_prob: 2.4467 loss_thr: 0.9418 loss_db: 0.4910 2022/11/01 13:27:48 - mmengine - INFO - Epoch(train) [50][45/63] lr: 4.9397e-04 eta: 15:55:25 time: 0.5295 data_time: 0.0059 memory: 17620 loss: 3.8148 loss_prob: 2.4150 loss_thr: 0.9214 loss_db: 0.4783 2022/11/01 13:27:51 - mmengine - INFO - Epoch(train) [50][50/63] lr: 4.9397e-04 eta: 15:54:22 time: 0.5544 data_time: 0.0190 memory: 17620 loss: 3.9398 loss_prob: 2.5028 loss_thr: 0.9318 loss_db: 0.5052 2022/11/01 13:27:54 - mmengine - INFO - Epoch(train) [50][55/63] lr: 4.9397e-04 eta: 15:54:22 time: 0.5682 data_time: 0.0217 memory: 17620 loss: 4.1119 loss_prob: 2.6131 loss_thr: 0.9614 loss_db: 0.5374 2022/11/01 13:27:57 - mmengine - INFO - Epoch(train) [50][60/63] lr: 4.9397e-04 eta: 15:53:20 time: 0.5518 data_time: 0.0097 memory: 17620 loss: 4.4279 loss_prob: 2.7822 loss_thr: 0.9967 loss_db: 0.6490 2022/11/01 13:27:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:28:03 - mmengine - INFO - Epoch(train) [51][5/63] lr: 5.0401e-04 eta: 15:53:20 time: 0.7238 data_time: 0.2107 memory: 17620 loss: 4.0808 loss_prob: 2.5585 loss_thr: 0.9731 loss_db: 0.5492 2022/11/01 13:28:06 - mmengine - INFO - Epoch(train) [51][10/63] lr: 5.0401e-04 eta: 15:52:08 time: 0.7579 data_time: 0.2084 memory: 17620 loss: 3.9926 loss_prob: 2.5192 loss_thr: 0.9585 loss_db: 0.5149 2022/11/01 13:28:09 - mmengine - INFO - Epoch(train) [51][15/63] lr: 5.0401e-04 eta: 15:52:08 time: 0.5596 data_time: 0.0047 memory: 17620 loss: 3.9557 loss_prob: 2.4906 loss_thr: 0.9647 loss_db: 0.5005 2022/11/01 13:28:11 - mmengine - INFO - Epoch(train) [51][20/63] lr: 5.0401e-04 eta: 15:51:07 time: 0.5572 data_time: 0.0052 memory: 17620 loss: 3.9475 loss_prob: 2.4942 loss_thr: 0.9582 loss_db: 0.4951 2022/11/01 13:28:14 - mmengine - INFO - Epoch(train) [51][25/63] lr: 5.0401e-04 eta: 15:51:07 time: 0.5516 data_time: 0.0181 memory: 17620 loss: 3.8905 loss_prob: 2.4715 loss_thr: 0.9426 loss_db: 0.4764 2022/11/01 13:28:17 - mmengine - INFO - Epoch(train) [51][30/63] lr: 5.0401e-04 eta: 15:50:06 time: 0.5539 data_time: 0.0371 memory: 17620 loss: 3.8133 loss_prob: 2.4242 loss_thr: 0.9190 loss_db: 0.4701 2022/11/01 13:28:20 - mmengine - INFO - Epoch(train) [51][35/63] lr: 5.0401e-04 eta: 15:50:06 time: 0.5423 data_time: 0.0240 memory: 17620 loss: 3.7034 loss_prob: 2.3520 loss_thr: 0.9100 loss_db: 0.4414 2022/11/01 13:28:22 - mmengine - INFO - Epoch(train) [51][40/63] lr: 5.0401e-04 eta: 15:49:01 time: 0.5373 data_time: 0.0046 memory: 17620 loss: 3.6525 loss_prob: 2.3108 loss_thr: 0.9209 loss_db: 0.4208 2022/11/01 13:28:25 - mmengine - INFO - Epoch(train) [51][45/63] lr: 5.0401e-04 eta: 15:49:01 time: 0.5263 data_time: 0.0052 memory: 17620 loss: 3.5760 loss_prob: 2.2623 loss_thr: 0.9110 loss_db: 0.4028 2022/11/01 13:28:28 - mmengine - INFO - Epoch(train) [51][50/63] lr: 5.0401e-04 eta: 15:48:00 time: 0.5494 data_time: 0.0205 memory: 17620 loss: 3.6971 loss_prob: 2.3323 loss_thr: 0.9167 loss_db: 0.4481 2022/11/01 13:28:30 - mmengine - INFO - Epoch(train) [51][55/63] lr: 5.0401e-04 eta: 15:48:00 time: 0.5490 data_time: 0.0200 memory: 17620 loss: 3.8714 loss_prob: 2.4637 loss_thr: 0.9179 loss_db: 0.4897 2022/11/01 13:28:33 - mmengine - INFO - Epoch(train) [51][60/63] lr: 5.0401e-04 eta: 15:46:52 time: 0.5211 data_time: 0.0048 memory: 17620 loss: 3.7854 loss_prob: 2.4113 loss_thr: 0.9259 loss_db: 0.4483 2022/11/01 13:28:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:28:39 - mmengine - INFO - Epoch(train) [52][5/63] lr: 5.1405e-04 eta: 15:46:52 time: 0.7335 data_time: 0.2102 memory: 17620 loss: 3.6697 loss_prob: 2.3146 loss_thr: 0.9206 loss_db: 0.4344 2022/11/01 13:28:42 - mmengine - INFO - Epoch(train) [52][10/63] lr: 5.1405e-04 eta: 15:45:49 time: 0.7856 data_time: 0.2135 memory: 17620 loss: 3.6635 loss_prob: 2.3133 loss_thr: 0.9091 loss_db: 0.4411 2022/11/01 13:28:45 - mmengine - INFO - Epoch(train) [52][15/63] lr: 5.1405e-04 eta: 15:45:49 time: 0.5632 data_time: 0.0085 memory: 17620 loss: 3.7248 loss_prob: 2.3618 loss_thr: 0.9151 loss_db: 0.4479 2022/11/01 13:28:48 - mmengine - INFO - Epoch(train) [52][20/63] lr: 5.1405e-04 eta: 15:44:47 time: 0.5414 data_time: 0.0065 memory: 17620 loss: 3.8064 loss_prob: 2.4184 loss_thr: 0.9212 loss_db: 0.4668 2022/11/01 13:28:51 - mmengine - INFO - Epoch(train) [52][25/63] lr: 5.1405e-04 eta: 15:44:47 time: 0.5643 data_time: 0.0280 memory: 17620 loss: 3.6052 loss_prob: 2.2914 loss_thr: 0.8899 loss_db: 0.4239 2022/11/01 13:28:54 - mmengine - INFO - Epoch(train) [52][30/63] lr: 5.1405e-04 eta: 15:43:58 time: 0.5961 data_time: 0.0372 memory: 17620 loss: 3.4681 loss_prob: 2.1812 loss_thr: 0.8918 loss_db: 0.3951 2022/11/01 13:28:56 - mmengine - INFO - Epoch(train) [52][35/63] lr: 5.1405e-04 eta: 15:43:58 time: 0.5538 data_time: 0.0177 memory: 17620 loss: 3.7178 loss_prob: 2.3287 loss_thr: 0.9356 loss_db: 0.4535 2022/11/01 13:28:59 - mmengine - INFO - Epoch(train) [52][40/63] lr: 5.1405e-04 eta: 15:42:58 time: 0.5483 data_time: 0.0088 memory: 17620 loss: 3.7854 loss_prob: 2.3771 loss_thr: 0.9447 loss_db: 0.4637 2022/11/01 13:29:02 - mmengine - INFO - Epoch(train) [52][45/63] lr: 5.1405e-04 eta: 15:42:58 time: 0.5915 data_time: 0.0065 memory: 17620 loss: 3.5794 loss_prob: 2.2432 loss_thr: 0.9183 loss_db: 0.4179 2022/11/01 13:29:05 - mmengine - INFO - Epoch(train) [52][50/63] lr: 5.1405e-04 eta: 15:42:14 time: 0.6182 data_time: 0.0175 memory: 17620 loss: 3.4089 loss_prob: 2.1463 loss_thr: 0.8830 loss_db: 0.3796 2022/11/01 13:29:08 - mmengine - INFO - Epoch(train) [52][55/63] lr: 5.1405e-04 eta: 15:42:14 time: 0.6360 data_time: 0.0217 memory: 17620 loss: 3.4801 loss_prob: 2.1874 loss_thr: 0.8892 loss_db: 0.4035 2022/11/01 13:29:11 - mmengine - INFO - Epoch(train) [52][60/63] lr: 5.1405e-04 eta: 15:41:28 time: 0.6098 data_time: 0.0094 memory: 17620 loss: 3.4966 loss_prob: 2.1937 loss_thr: 0.8941 loss_db: 0.4088 2022/11/01 13:29:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:29:18 - mmengine - INFO - Epoch(train) [53][5/63] lr: 5.2409e-04 eta: 15:41:28 time: 0.7992 data_time: 0.2274 memory: 17620 loss: 3.5459 loss_prob: 2.2392 loss_thr: 0.8906 loss_db: 0.4161 2022/11/01 13:29:21 - mmengine - INFO - Epoch(train) [53][10/63] lr: 5.2409e-04 eta: 15:40:32 time: 0.8093 data_time: 0.2256 memory: 17620 loss: 3.6675 loss_prob: 2.3302 loss_thr: 0.8929 loss_db: 0.4445 2022/11/01 13:29:24 - mmengine - INFO - Epoch(train) [53][15/63] lr: 5.2409e-04 eta: 15:40:32 time: 0.5677 data_time: 0.0080 memory: 17620 loss: 3.6202 loss_prob: 2.2942 loss_thr: 0.8865 loss_db: 0.4395 2022/11/01 13:29:27 - mmengine - INFO - Epoch(train) [53][20/63] lr: 5.2409e-04 eta: 15:39:41 time: 0.5818 data_time: 0.0080 memory: 17620 loss: 3.4992 loss_prob: 2.1981 loss_thr: 0.9073 loss_db: 0.3937 2022/11/01 13:29:30 - mmengine - INFO - Epoch(train) [53][25/63] lr: 5.2409e-04 eta: 15:39:41 time: 0.5853 data_time: 0.0381 memory: 17620 loss: 3.4726 loss_prob: 2.1769 loss_thr: 0.9110 loss_db: 0.3847 2022/11/01 13:29:32 - mmengine - INFO - Epoch(train) [53][30/63] lr: 5.2409e-04 eta: 15:38:47 time: 0.5674 data_time: 0.0379 memory: 17620 loss: 3.4440 loss_prob: 2.1680 loss_thr: 0.8889 loss_db: 0.3871 2022/11/01 13:29:35 - mmengine - INFO - Epoch(train) [53][35/63] lr: 5.2409e-04 eta: 15:38:47 time: 0.5420 data_time: 0.0048 memory: 17620 loss: 3.4749 loss_prob: 2.1991 loss_thr: 0.8849 loss_db: 0.3909 2022/11/01 13:29:38 - mmengine - INFO - Epoch(train) [53][40/63] lr: 5.2409e-04 eta: 15:37:55 time: 0.5794 data_time: 0.0045 memory: 17620 loss: 3.5479 loss_prob: 2.2461 loss_thr: 0.8952 loss_db: 0.4066 2022/11/01 13:29:41 - mmengine - INFO - Epoch(train) [53][45/63] lr: 5.2409e-04 eta: 15:37:55 time: 0.6109 data_time: 0.0055 memory: 17620 loss: 3.6035 loss_prob: 2.2641 loss_thr: 0.9157 loss_db: 0.4237 2022/11/01 13:29:44 - mmengine - INFO - Epoch(train) [53][50/63] lr: 5.2409e-04 eta: 15:37:11 time: 0.6125 data_time: 0.0218 memory: 17620 loss: 3.6836 loss_prob: 2.3043 loss_thr: 0.9342 loss_db: 0.4452 2022/11/01 13:29:47 - mmengine - INFO - Epoch(train) [53][55/63] lr: 5.2409e-04 eta: 15:37:11 time: 0.5755 data_time: 0.0214 memory: 17620 loss: 3.7213 loss_prob: 2.3472 loss_thr: 0.9259 loss_db: 0.4482 2022/11/01 13:29:50 - mmengine - INFO - Epoch(train) [53][60/63] lr: 5.2409e-04 eta: 15:36:14 time: 0.5463 data_time: 0.0053 memory: 17620 loss: 3.7911 loss_prob: 2.3991 loss_thr: 0.9297 loss_db: 0.4622 2022/11/01 13:29:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:29:56 - mmengine - INFO - Epoch(train) [54][5/63] lr: 5.3413e-04 eta: 15:36:14 time: 0.7295 data_time: 0.2036 memory: 17620 loss: 3.7211 loss_prob: 2.3521 loss_thr: 0.9148 loss_db: 0.4542 2022/11/01 13:29:59 - mmengine - INFO - Epoch(train) [54][10/63] lr: 5.3413e-04 eta: 15:35:23 time: 0.8217 data_time: 0.2184 memory: 17620 loss: 3.7529 loss_prob: 2.3625 loss_thr: 0.9264 loss_db: 0.4640 2022/11/01 13:30:02 - mmengine - INFO - Epoch(train) [54][15/63] lr: 5.3413e-04 eta: 15:35:23 time: 0.6006 data_time: 0.0212 memory: 17620 loss: 3.9532 loss_prob: 2.5019 loss_thr: 0.9415 loss_db: 0.5097 2022/11/01 13:30:04 - mmengine - INFO - Epoch(train) [54][20/63] lr: 5.3413e-04 eta: 15:34:19 time: 0.5149 data_time: 0.0069 memory: 17620 loss: 3.8945 loss_prob: 2.4960 loss_thr: 0.9084 loss_db: 0.4902 2022/11/01 13:30:07 - mmengine - INFO - Epoch(train) [54][25/63] lr: 5.3413e-04 eta: 15:34:19 time: 0.5312 data_time: 0.0065 memory: 17620 loss: 3.6672 loss_prob: 2.3387 loss_thr: 0.8824 loss_db: 0.4461 2022/11/01 13:30:10 - mmengine - INFO - Epoch(train) [54][30/63] lr: 5.3413e-04 eta: 15:33:26 time: 0.5690 data_time: 0.0329 memory: 17620 loss: 3.4974 loss_prob: 2.1889 loss_thr: 0.9040 loss_db: 0.4045 2022/11/01 13:30:13 - mmengine - INFO - Epoch(train) [54][35/63] lr: 5.3413e-04 eta: 15:33:26 time: 0.5570 data_time: 0.0341 memory: 17620 loss: 3.4072 loss_prob: 2.1454 loss_thr: 0.8907 loss_db: 0.3710 2022/11/01 13:30:15 - mmengine - INFO - Epoch(train) [54][40/63] lr: 5.3413e-04 eta: 15:32:22 time: 0.5109 data_time: 0.0070 memory: 17620 loss: 3.4907 loss_prob: 2.2064 loss_thr: 0.8836 loss_db: 0.4006 2022/11/01 13:30:18 - mmengine - INFO - Epoch(train) [54][45/63] lr: 5.3413e-04 eta: 15:32:22 time: 0.5287 data_time: 0.0046 memory: 17620 loss: 3.4785 loss_prob: 2.1854 loss_thr: 0.8911 loss_db: 0.4020 2022/11/01 13:30:21 - mmengine - INFO - Epoch(train) [54][50/63] lr: 5.3413e-04 eta: 15:31:30 time: 0.5649 data_time: 0.0179 memory: 17620 loss: 3.4016 loss_prob: 2.1507 loss_thr: 0.8755 loss_db: 0.3754 2022/11/01 13:30:24 - mmengine - INFO - Epoch(train) [54][55/63] lr: 5.3413e-04 eta: 15:31:30 time: 0.5656 data_time: 0.0249 memory: 17620 loss: 3.4525 loss_prob: 2.1798 loss_thr: 0.8788 loss_db: 0.3939 2022/11/01 13:30:26 - mmengine - INFO - Epoch(train) [54][60/63] lr: 5.3413e-04 eta: 15:30:31 time: 0.5358 data_time: 0.0129 memory: 17620 loss: 3.4297 loss_prob: 2.1673 loss_thr: 0.8807 loss_db: 0.3818 2022/11/01 13:30:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:30:32 - mmengine - INFO - Epoch(train) [55][5/63] lr: 5.4417e-04 eta: 15:30:31 time: 0.7218 data_time: 0.2058 memory: 17620 loss: 3.5707 loss_prob: 2.2502 loss_thr: 0.8922 loss_db: 0.4284 2022/11/01 13:30:36 - mmengine - INFO - Epoch(train) [55][10/63] lr: 5.4417e-04 eta: 15:29:41 time: 0.8156 data_time: 0.2093 memory: 17620 loss: 3.5849 loss_prob: 2.2633 loss_thr: 0.8935 loss_db: 0.4281 2022/11/01 13:30:39 - mmengine - INFO - Epoch(train) [55][15/63] lr: 5.4417e-04 eta: 15:29:41 time: 0.6315 data_time: 0.0104 memory: 17620 loss: 3.7055 loss_prob: 2.3478 loss_thr: 0.9056 loss_db: 0.4520 2022/11/01 13:30:41 - mmengine - INFO - Epoch(train) [55][20/63] lr: 5.4417e-04 eta: 15:28:49 time: 0.5634 data_time: 0.0067 memory: 17620 loss: 3.6589 loss_prob: 2.3205 loss_thr: 0.9047 loss_db: 0.4336 2022/11/01 13:30:44 - mmengine - INFO - Epoch(train) [55][25/63] lr: 5.4417e-04 eta: 15:28:49 time: 0.5498 data_time: 0.0256 memory: 17620 loss: 3.5199 loss_prob: 2.2172 loss_thr: 0.9007 loss_db: 0.4020 2022/11/01 13:30:47 - mmengine - INFO - Epoch(train) [55][30/63] lr: 5.4417e-04 eta: 15:28:01 time: 0.5812 data_time: 0.0294 memory: 17620 loss: 3.5267 loss_prob: 2.2310 loss_thr: 0.8935 loss_db: 0.4022 2022/11/01 13:30:50 - mmengine - INFO - Epoch(train) [55][35/63] lr: 5.4417e-04 eta: 15:28:01 time: 0.5885 data_time: 0.0099 memory: 17620 loss: 3.8444 loss_prob: 2.4307 loss_thr: 0.9284 loss_db: 0.4853 2022/11/01 13:30:53 - mmengine - INFO - Epoch(train) [55][40/63] lr: 5.4417e-04 eta: 15:27:15 time: 0.5874 data_time: 0.0069 memory: 17620 loss: 3.7580 loss_prob: 2.3467 loss_thr: 0.9496 loss_db: 0.4617 2022/11/01 13:30:56 - mmengine - INFO - Epoch(train) [55][45/63] lr: 5.4417e-04 eta: 15:27:15 time: 0.5697 data_time: 0.0059 memory: 17620 loss: 3.4883 loss_prob: 2.1875 loss_thr: 0.9062 loss_db: 0.3947 2022/11/01 13:30:59 - mmengine - INFO - Epoch(train) [55][50/63] lr: 5.4417e-04 eta: 15:26:21 time: 0.5501 data_time: 0.0183 memory: 17620 loss: 3.5788 loss_prob: 2.2540 loss_thr: 0.8999 loss_db: 0.4249 2022/11/01 13:31:01 - mmengine - INFO - Epoch(train) [55][55/63] lr: 5.4417e-04 eta: 15:26:21 time: 0.5401 data_time: 0.0192 memory: 17620 loss: 3.5243 loss_prob: 2.2219 loss_thr: 0.8899 loss_db: 0.4124 2022/11/01 13:31:04 - mmengine - INFO - Epoch(train) [55][60/63] lr: 5.4417e-04 eta: 15:25:24 time: 0.5331 data_time: 0.0078 memory: 17620 loss: 3.4362 loss_prob: 2.1541 loss_thr: 0.8979 loss_db: 0.3843 2022/11/01 13:31:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:31:11 - mmengine - INFO - Epoch(train) [56][5/63] lr: 5.5421e-04 eta: 15:25:24 time: 0.8349 data_time: 0.2206 memory: 17620 loss: 3.2941 loss_prob: 2.0548 loss_thr: 0.8897 loss_db: 0.3496 2022/11/01 13:31:14 - mmengine - INFO - Epoch(train) [56][10/63] lr: 5.5421e-04 eta: 15:24:57 time: 0.9180 data_time: 0.2197 memory: 17620 loss: 3.2985 loss_prob: 2.0696 loss_thr: 0.8731 loss_db: 0.3558 2022/11/01 13:31:17 - mmengine - INFO - Epoch(train) [56][15/63] lr: 5.5421e-04 eta: 15:24:57 time: 0.5989 data_time: 0.0080 memory: 17620 loss: 3.5211 loss_prob: 2.2060 loss_thr: 0.9010 loss_db: 0.4141 2022/11/01 13:31:20 - mmengine - INFO - Epoch(train) [56][20/63] lr: 5.5421e-04 eta: 15:24:07 time: 0.5627 data_time: 0.0108 memory: 17620 loss: 3.6982 loss_prob: 2.3153 loss_thr: 0.9252 loss_db: 0.4577 2022/11/01 13:31:24 - mmengine - INFO - Epoch(train) [56][25/63] lr: 5.5421e-04 eta: 15:24:07 time: 0.6365 data_time: 0.0281 memory: 17620 loss: 3.4830 loss_prob: 2.1890 loss_thr: 0.8955 loss_db: 0.3986 2022/11/01 13:31:27 - mmengine - INFO - Epoch(train) [56][30/63] lr: 5.5421e-04 eta: 15:23:33 time: 0.6416 data_time: 0.0338 memory: 17620 loss: 3.3012 loss_prob: 2.0731 loss_thr: 0.8739 loss_db: 0.3543 2022/11/01 13:31:29 - mmengine - INFO - Epoch(train) [56][35/63] lr: 5.5421e-04 eta: 15:23:33 time: 0.5971 data_time: 0.0146 memory: 17620 loss: 3.3846 loss_prob: 2.1171 loss_thr: 0.8868 loss_db: 0.3807 2022/11/01 13:31:33 - mmengine - INFO - Epoch(train) [56][40/63] lr: 5.5421e-04 eta: 15:22:56 time: 0.6270 data_time: 0.0046 memory: 17620 loss: 3.5127 loss_prob: 2.2097 loss_thr: 0.8956 loss_db: 0.4074 2022/11/01 13:31:36 - mmengine - INFO - Epoch(train) [56][45/63] lr: 5.5421e-04 eta: 15:22:56 time: 0.6045 data_time: 0.0059 memory: 17620 loss: 3.5210 loss_prob: 2.2208 loss_thr: 0.8821 loss_db: 0.4182 2022/11/01 13:31:38 - mmengine - INFO - Epoch(train) [56][50/63] lr: 5.5421e-04 eta: 15:22:07 time: 0.5686 data_time: 0.0164 memory: 17620 loss: 3.5644 loss_prob: 2.2426 loss_thr: 0.8838 loss_db: 0.4380 2022/11/01 13:31:41 - mmengine - INFO - Epoch(train) [56][55/63] lr: 5.5421e-04 eta: 15:22:07 time: 0.5699 data_time: 0.0272 memory: 17620 loss: 3.5261 loss_prob: 2.2278 loss_thr: 0.8869 loss_db: 0.4114 2022/11/01 13:31:44 - mmengine - INFO - Epoch(train) [56][60/63] lr: 5.5421e-04 eta: 15:21:14 time: 0.5469 data_time: 0.0168 memory: 17620 loss: 3.6027 loss_prob: 2.2936 loss_thr: 0.9041 loss_db: 0.4049 2022/11/01 13:31:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:31:52 - mmengine - INFO - Epoch(train) [57][5/63] lr: 5.6425e-04 eta: 15:21:14 time: 0.8668 data_time: 0.2055 memory: 17620 loss: 5.2105 loss_prob: 3.3734 loss_thr: 1.0620 loss_db: 0.7750 2022/11/01 13:31:54 - mmengine - INFO - Epoch(train) [57][10/63] lr: 5.6425e-04 eta: 15:20:47 time: 0.9123 data_time: 0.2067 memory: 17620 loss: 5.4489 loss_prob: 3.3014 loss_thr: 1.1475 loss_db: 1.0000 2022/11/01 13:31:58 - mmengine - INFO - Epoch(train) [57][15/63] lr: 5.6425e-04 eta: 15:20:47 time: 0.6392 data_time: 0.0149 memory: 17620 loss: 5.4042 loss_prob: 3.2424 loss_thr: 1.1618 loss_db: 1.0000 2022/11/01 13:32:01 - mmengine - INFO - Epoch(train) [57][20/63] lr: 5.6425e-04 eta: 15:20:10 time: 0.6200 data_time: 0.0124 memory: 17620 loss: 5.3291 loss_prob: 3.1765 loss_thr: 1.1526 loss_db: 1.0000 2022/11/01 13:32:03 - mmengine - INFO - Epoch(train) [57][25/63] lr: 5.6425e-04 eta: 15:20:10 time: 0.5501 data_time: 0.0177 memory: 17620 loss: 5.3158 loss_prob: 3.1679 loss_thr: 1.1479 loss_db: 1.0000 2022/11/01 13:32:06 - mmengine - INFO - Epoch(train) [57][30/63] lr: 5.6425e-04 eta: 15:19:24 time: 0.5775 data_time: 0.0253 memory: 17620 loss: 5.2870 loss_prob: 3.1378 loss_thr: 1.1493 loss_db: 1.0000 2022/11/01 13:32:09 - mmengine - INFO - Epoch(train) [57][35/63] lr: 5.6425e-04 eta: 15:19:24 time: 0.5714 data_time: 0.0212 memory: 17620 loss: 5.2391 loss_prob: 3.0886 loss_thr: 1.1505 loss_db: 1.0000 2022/11/01 13:32:12 - mmengine - INFO - Epoch(train) [57][40/63] lr: 5.6425e-04 eta: 15:18:43 time: 0.5993 data_time: 0.0161 memory: 17620 loss: 5.2225 loss_prob: 3.0727 loss_thr: 1.1499 loss_db: 1.0000 2022/11/01 13:32:15 - mmengine - INFO - Epoch(train) [57][45/63] lr: 5.6425e-04 eta: 15:18:43 time: 0.5929 data_time: 0.0083 memory: 17620 loss: 5.2179 loss_prob: 3.0638 loss_thr: 1.1541 loss_db: 1.0000 2022/11/01 13:32:18 - mmengine - INFO - Epoch(train) [57][50/63] lr: 5.6425e-04 eta: 15:17:51 time: 0.5487 data_time: 0.0144 memory: 17620 loss: 5.2200 loss_prob: 3.0722 loss_thr: 1.1478 loss_db: 1.0000 2022/11/01 13:32:21 - mmengine - INFO - Epoch(train) [57][55/63] lr: 5.6425e-04 eta: 15:17:51 time: 0.5634 data_time: 0.0171 memory: 17620 loss: 5.2303 loss_prob: 3.0862 loss_thr: 1.1441 loss_db: 1.0000 2022/11/01 13:32:24 - mmengine - INFO - Epoch(train) [57][60/63] lr: 5.6425e-04 eta: 15:17:06 time: 0.5777 data_time: 0.0153 memory: 17620 loss: 5.2173 loss_prob: 3.0722 loss_thr: 1.1450 loss_db: 1.0000 2022/11/01 13:32:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:32:30 - mmengine - INFO - Epoch(train) [58][5/63] lr: 5.7429e-04 eta: 15:17:06 time: 0.7804 data_time: 0.1991 memory: 17620 loss: 5.1798 loss_prob: 3.0318 loss_thr: 1.1480 loss_db: 1.0000 2022/11/01 13:32:33 - mmengine - INFO - Epoch(train) [58][10/63] lr: 5.7429e-04 eta: 15:16:16 time: 0.7910 data_time: 0.1963 memory: 17620 loss: 5.1680 loss_prob: 3.0208 loss_thr: 1.1473 loss_db: 1.0000 2022/11/01 13:32:36 - mmengine - INFO - Epoch(train) [58][15/63] lr: 5.7429e-04 eta: 15:16:16 time: 0.5585 data_time: 0.0049 memory: 17620 loss: 5.2895 loss_prob: 3.1359 loss_thr: 1.1537 loss_db: 1.0000 2022/11/01 13:32:39 - mmengine - INFO - Epoch(train) [58][20/63] lr: 5.7429e-04 eta: 15:15:34 time: 0.5914 data_time: 0.0069 memory: 17620 loss: 5.4299 loss_prob: 3.2748 loss_thr: 1.1551 loss_db: 1.0000 2022/11/01 13:32:42 - mmengine - INFO - Epoch(train) [58][25/63] lr: 5.7429e-04 eta: 15:15:34 time: 0.6194 data_time: 0.0123 memory: 17620 loss: 5.4238 loss_prob: 3.2751 loss_thr: 1.1488 loss_db: 1.0000 2022/11/01 13:32:45 - mmengine - INFO - Epoch(train) [58][30/63] lr: 5.7429e-04 eta: 15:14:56 time: 0.6092 data_time: 0.0335 memory: 17620 loss: 5.3897 loss_prob: 3.2360 loss_thr: 1.1537 loss_db: 1.0000 2022/11/01 13:32:48 - mmengine - INFO - Epoch(train) [58][35/63] lr: 5.7429e-04 eta: 15:14:56 time: 0.5872 data_time: 0.0284 memory: 17620 loss: 5.3414 loss_prob: 3.1912 loss_thr: 1.1502 loss_db: 1.0000 2022/11/01 13:32:51 - mmengine - INFO - Epoch(train) [58][40/63] lr: 5.7429e-04 eta: 15:14:12 time: 0.5822 data_time: 0.0052 memory: 17620 loss: 5.2446 loss_prob: 3.1062 loss_thr: 1.1384 loss_db: 1.0000 2022/11/01 13:32:54 - mmengine - INFO - Epoch(train) [58][45/63] lr: 5.7429e-04 eta: 15:14:12 time: 0.5607 data_time: 0.0074 memory: 17620 loss: 5.2094 loss_prob: 3.0684 loss_thr: 1.1410 loss_db: 1.0000 2022/11/01 13:32:56 - mmengine - INFO - Epoch(train) [58][50/63] lr: 5.7429e-04 eta: 15:13:23 time: 0.5532 data_time: 0.0124 memory: 17620 loss: 5.2450 loss_prob: 3.1026 loss_thr: 1.1425 loss_db: 0.9999 2022/11/01 13:32:59 - mmengine - INFO - Epoch(train) [58][55/63] lr: 5.7429e-04 eta: 15:13:23 time: 0.5325 data_time: 0.0202 memory: 17620 loss: 5.2524 loss_prob: 3.1136 loss_thr: 1.1389 loss_db: 0.9999 2022/11/01 13:33:02 - mmengine - INFO - Epoch(train) [58][60/63] lr: 5.7429e-04 eta: 15:12:33 time: 0.5442 data_time: 0.0151 memory: 17620 loss: 5.2570 loss_prob: 3.1124 loss_thr: 1.1447 loss_db: 1.0000 2022/11/01 13:33:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:33:08 - mmengine - INFO - Epoch(train) [59][5/63] lr: 5.8433e-04 eta: 15:12:33 time: 0.6993 data_time: 0.1771 memory: 17620 loss: 5.1887 loss_prob: 3.0545 loss_thr: 1.1343 loss_db: 1.0000 2022/11/01 13:33:10 - mmengine - INFO - Epoch(train) [59][10/63] lr: 5.8433e-04 eta: 15:11:30 time: 0.7214 data_time: 0.1840 memory: 17620 loss: 5.1433 loss_prob: 3.0110 loss_thr: 1.1323 loss_db: 0.9999 2022/11/01 13:33:13 - mmengine - INFO - Epoch(train) [59][15/63] lr: 5.8433e-04 eta: 15:11:30 time: 0.5329 data_time: 0.0145 memory: 17620 loss: 5.1641 loss_prob: 3.0261 loss_thr: 1.1381 loss_db: 0.9999 2022/11/01 13:33:16 - mmengine - INFO - Epoch(train) [59][20/63] lr: 5.8433e-04 eta: 15:10:38 time: 0.5343 data_time: 0.0059 memory: 17620 loss: 5.1571 loss_prob: 3.0177 loss_thr: 1.1395 loss_db: 0.9999 2022/11/01 13:33:18 - mmengine - INFO - Epoch(train) [59][25/63] lr: 5.8433e-04 eta: 15:10:38 time: 0.5490 data_time: 0.0169 memory: 17620 loss: 5.1960 loss_prob: 3.0537 loss_thr: 1.1424 loss_db: 0.9999 2022/11/01 13:33:21 - mmengine - INFO - Epoch(train) [59][30/63] lr: 5.8433e-04 eta: 15:09:51 time: 0.5567 data_time: 0.0316 memory: 17620 loss: 5.2056 loss_prob: 3.0677 loss_thr: 1.1379 loss_db: 0.9999 2022/11/01 13:33:24 - mmengine - INFO - Epoch(train) [59][35/63] lr: 5.8433e-04 eta: 15:09:51 time: 0.5485 data_time: 0.0220 memory: 17620 loss: 5.1613 loss_prob: 3.0358 loss_thr: 1.1255 loss_db: 0.9999 2022/11/01 13:33:27 - mmengine - INFO - Epoch(train) [59][40/63] lr: 5.8433e-04 eta: 15:09:00 time: 0.5341 data_time: 0.0061 memory: 17620 loss: 5.1536 loss_prob: 3.0209 loss_thr: 1.1329 loss_db: 0.9999 2022/11/01 13:33:29 - mmengine - INFO - Epoch(train) [59][45/63] lr: 5.8433e-04 eta: 15:09:00 time: 0.5435 data_time: 0.0059 memory: 17620 loss: 5.2005 loss_prob: 3.0545 loss_thr: 1.1462 loss_db: 0.9999 2022/11/01 13:33:32 - mmengine - INFO - Epoch(train) [59][50/63] lr: 5.8433e-04 eta: 15:08:18 time: 0.5829 data_time: 0.0185 memory: 17620 loss: 5.2128 loss_prob: 3.0695 loss_thr: 1.1434 loss_db: 0.9999 2022/11/01 13:33:35 - mmengine - INFO - Epoch(train) [59][55/63] lr: 5.8433e-04 eta: 15:08:18 time: 0.6198 data_time: 0.0229 memory: 17620 loss: 5.1634 loss_prob: 3.0268 loss_thr: 1.1366 loss_db: 0.9999 2022/11/01 13:33:39 - mmengine - INFO - Epoch(train) [59][60/63] lr: 5.8433e-04 eta: 15:07:49 time: 0.6460 data_time: 0.0114 memory: 17620 loss: 5.1624 loss_prob: 3.0265 loss_thr: 1.1359 loss_db: 0.9999 2022/11/01 13:33:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:33:46 - mmengine - INFO - Epoch(train) [60][5/63] lr: 5.9437e-04 eta: 15:07:49 time: 0.8751 data_time: 0.2231 memory: 17620 loss: 5.1432 loss_prob: 3.0280 loss_thr: 1.1159 loss_db: 0.9993 2022/11/01 13:33:49 - mmengine - INFO - Epoch(train) [60][10/63] lr: 5.9437e-04 eta: 15:07:19 time: 0.8829 data_time: 0.2248 memory: 17620 loss: 5.2107 loss_prob: 3.0859 loss_thr: 1.1254 loss_db: 0.9993 2022/11/01 13:33:52 - mmengine - INFO - Epoch(train) [60][15/63] lr: 5.9437e-04 eta: 15:07:19 time: 0.6021 data_time: 0.0076 memory: 17620 loss: 5.2293 loss_prob: 3.0855 loss_thr: 1.1440 loss_db: 0.9997 2022/11/01 13:33:55 - mmengine - INFO - Epoch(train) [60][20/63] lr: 5.9437e-04 eta: 15:06:40 time: 0.5899 data_time: 0.0059 memory: 17620 loss: 5.1718 loss_prob: 3.0478 loss_thr: 1.1255 loss_db: 0.9985 2022/11/01 13:33:58 - mmengine - INFO - Epoch(train) [60][25/63] lr: 5.9437e-04 eta: 15:06:40 time: 0.5700 data_time: 0.0234 memory: 17620 loss: 5.1409 loss_prob: 3.0302 loss_thr: 1.1123 loss_db: 0.9984 2022/11/01 13:34:01 - mmengine - INFO - Epoch(train) [60][30/63] lr: 5.9437e-04 eta: 15:05:57 time: 0.5750 data_time: 0.0312 memory: 17620 loss: 5.0863 loss_prob: 2.9790 loss_thr: 1.1082 loss_db: 0.9990 2022/11/01 13:34:03 - mmengine - INFO - Epoch(train) [60][35/63] lr: 5.9437e-04 eta: 15:05:57 time: 0.5586 data_time: 0.0139 memory: 17620 loss: 5.0985 loss_prob: 2.9823 loss_thr: 1.1172 loss_db: 0.9991 2022/11/01 13:34:07 - mmengine - INFO - Epoch(train) [60][40/63] lr: 5.9437e-04 eta: 15:05:31 time: 0.6570 data_time: 0.0091 memory: 17620 loss: 5.1265 loss_prob: 3.0093 loss_thr: 1.1177 loss_db: 0.9995 2022/11/01 13:34:10 - mmengine - INFO - Epoch(train) [60][45/63] lr: 5.9437e-04 eta: 15:05:31 time: 0.6909 data_time: 0.0078 memory: 17620 loss: 5.0952 loss_prob: 2.9938 loss_thr: 1.1023 loss_db: 0.9991 2022/11/01 13:34:13 - mmengine - INFO - Epoch(train) [60][50/63] lr: 5.9437e-04 eta: 15:04:56 time: 0.6130 data_time: 0.0256 memory: 17620 loss: 5.0734 loss_prob: 2.9844 loss_thr: 1.0908 loss_db: 0.9982 2022/11/01 13:34:16 - mmengine - INFO - Epoch(train) [60][55/63] lr: 5.9437e-04 eta: 15:04:56 time: 0.5662 data_time: 0.0267 memory: 17620 loss: 5.0682 loss_prob: 2.9814 loss_thr: 1.0887 loss_db: 0.9982 2022/11/01 13:34:19 - mmengine - INFO - Epoch(train) [60][60/63] lr: 5.9437e-04 eta: 15:04:13 time: 0.5713 data_time: 0.0071 memory: 17620 loss: 5.0502 loss_prob: 2.9551 loss_thr: 1.0986 loss_db: 0.9965 2022/11/01 13:34:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:34:20 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/11/01 13:34:27 - mmengine - INFO - Epoch(val) [60][5/32] eta: 15:04:13 time: 0.4667 data_time: 0.0816 memory: 17620 2022/11/01 13:34:29 - mmengine - INFO - Epoch(val) [60][10/32] eta: 0:00:11 time: 0.5148 data_time: 0.0950 memory: 15725 2022/11/01 13:34:32 - mmengine - INFO - Epoch(val) [60][15/32] eta: 0:00:11 time: 0.4611 data_time: 0.0453 memory: 15725 2022/11/01 13:34:34 - mmengine - INFO - Epoch(val) [60][20/32] eta: 0:00:05 time: 0.4776 data_time: 0.0646 memory: 15725 2022/11/01 13:34:36 - mmengine - INFO - Epoch(val) [60][25/32] eta: 0:00:05 time: 0.4608 data_time: 0.0478 memory: 15725 2022/11/01 13:34:38 - mmengine - INFO - Epoch(val) [60][30/32] eta: 0:00:00 time: 0.4363 data_time: 0.0206 memory: 15725 2022/11/01 13:34:39 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:34:39 - mmengine - INFO - Epoch(val) [60][32/32] icdar/precision: 0.0000 icdar/recall: 0.0000 icdar/hmean: 0.0000 2022/11/01 13:34:45 - mmengine - INFO - Epoch(train) [61][5/63] lr: 6.0441e-04 eta: 0:00:00 time: 0.8219 data_time: 0.1989 memory: 17620 loss: 4.9744 loss_prob: 2.9163 loss_thr: 1.1031 loss_db: 0.9550 2022/11/01 13:34:47 - mmengine - INFO - Epoch(train) [61][10/63] lr: 6.0441e-04 eta: 15:03:31 time: 0.8146 data_time: 0.1995 memory: 17620 loss: 5.0011 loss_prob: 2.9203 loss_thr: 1.1294 loss_db: 0.9515 2022/11/01 13:34:50 - mmengine - INFO - Epoch(train) [61][15/63] lr: 6.0441e-04 eta: 15:03:31 time: 0.5347 data_time: 0.0121 memory: 17620 loss: 4.9514 loss_prob: 2.9153 loss_thr: 1.1203 loss_db: 0.9158 2022/11/01 13:34:52 - mmengine - INFO - Epoch(train) [61][20/63] lr: 6.0441e-04 eta: 15:02:42 time: 0.5325 data_time: 0.0100 memory: 17620 loss: 4.8926 loss_prob: 2.9072 loss_thr: 1.0966 loss_db: 0.8887 2022/11/01 13:34:55 - mmengine - INFO - Epoch(train) [61][25/63] lr: 6.0441e-04 eta: 15:02:42 time: 0.5210 data_time: 0.0108 memory: 17620 loss: 4.9349 loss_prob: 2.9189 loss_thr: 1.0998 loss_db: 0.9162 2022/11/01 13:34:58 - mmengine - INFO - Epoch(train) [61][30/63] lr: 6.0441e-04 eta: 15:01:55 time: 0.5476 data_time: 0.0316 memory: 17620 loss: 4.9222 loss_prob: 2.9025 loss_thr: 1.0987 loss_db: 0.9210 2022/11/01 13:35:01 - mmengine - INFO - Epoch(train) [61][35/63] lr: 6.0441e-04 eta: 15:01:55 time: 0.5601 data_time: 0.0250 memory: 17620 loss: 4.8661 loss_prob: 2.8921 loss_thr: 1.0797 loss_db: 0.8943 2022/11/01 13:35:03 - mmengine - INFO - Epoch(train) [61][40/63] lr: 6.0441e-04 eta: 15:01:11 time: 0.5562 data_time: 0.0154 memory: 17620 loss: 4.8450 loss_prob: 2.8873 loss_thr: 1.0814 loss_db: 0.8764 2022/11/01 13:35:06 - mmengine - INFO - Epoch(train) [61][45/63] lr: 6.0441e-04 eta: 15:01:11 time: 0.5433 data_time: 0.0160 memory: 17620 loss: 4.7779 loss_prob: 2.8720 loss_thr: 1.0782 loss_db: 0.8277 2022/11/01 13:35:09 - mmengine - INFO - Epoch(train) [61][50/63] lr: 6.0441e-04 eta: 15:00:21 time: 0.5275 data_time: 0.0177 memory: 17620 loss: 4.6806 loss_prob: 2.8607 loss_thr: 1.0504 loss_db: 0.7696 2022/11/01 13:35:11 - mmengine - INFO - Epoch(train) [61][55/63] lr: 6.0441e-04 eta: 15:00:21 time: 0.5235 data_time: 0.0213 memory: 17620 loss: 4.6933 loss_prob: 2.8710 loss_thr: 1.0565 loss_db: 0.7658 2022/11/01 13:35:14 - mmengine - INFO - Epoch(train) [61][60/63] lr: 6.0441e-04 eta: 14:59:30 time: 0.5206 data_time: 0.0113 memory: 17620 loss: 4.7242 loss_prob: 2.8723 loss_thr: 1.0459 loss_db: 0.8060 2022/11/01 13:35:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:35:20 - mmengine - INFO - Epoch(train) [62][5/63] lr: 6.1445e-04 eta: 14:59:30 time: 0.6682 data_time: 0.1712 memory: 17620 loss: 4.6664 loss_prob: 2.8592 loss_thr: 1.0378 loss_db: 0.7695 2022/11/01 13:35:22 - mmengine - INFO - Epoch(train) [62][10/63] lr: 6.1445e-04 eta: 14:58:30 time: 0.7075 data_time: 0.1767 memory: 17620 loss: 4.6310 loss_prob: 2.8588 loss_thr: 1.0348 loss_db: 0.7375 2022/11/01 13:35:25 - mmengine - INFO - Epoch(train) [62][15/63] lr: 6.1445e-04 eta: 14:58:30 time: 0.5354 data_time: 0.0140 memory: 17620 loss: 4.6342 loss_prob: 2.8701 loss_thr: 1.0210 loss_db: 0.7431 2022/11/01 13:35:28 - mmengine - INFO - Epoch(train) [62][20/63] lr: 6.1445e-04 eta: 14:57:39 time: 0.5175 data_time: 0.0106 memory: 17620 loss: 4.6787 loss_prob: 2.8735 loss_thr: 1.0299 loss_db: 0.7753 2022/11/01 13:35:30 - mmengine - INFO - Epoch(train) [62][25/63] lr: 6.1445e-04 eta: 14:57:39 time: 0.5294 data_time: 0.0187 memory: 17620 loss: 4.6272 loss_prob: 2.8590 loss_thr: 1.0378 loss_db: 0.7304 2022/11/01 13:35:33 - mmengine - INFO - Epoch(train) [62][30/63] lr: 6.1445e-04 eta: 14:56:50 time: 0.5283 data_time: 0.0210 memory: 17620 loss: 4.7094 loss_prob: 2.8552 loss_thr: 1.0481 loss_db: 0.8061 2022/11/01 13:35:36 - mmengine - INFO - Epoch(train) [62][35/63] lr: 6.1445e-04 eta: 14:56:50 time: 0.5437 data_time: 0.0208 memory: 17620 loss: 4.7024 loss_prob: 2.8525 loss_thr: 1.0454 loss_db: 0.8046 2022/11/01 13:35:38 - mmengine - INFO - Epoch(train) [62][40/63] lr: 6.1445e-04 eta: 14:56:05 time: 0.5478 data_time: 0.0151 memory: 17620 loss: 4.5931 loss_prob: 2.8538 loss_thr: 1.0480 loss_db: 0.6914 2022/11/01 13:35:41 - mmengine - INFO - Epoch(train) [62][45/63] lr: 6.1445e-04 eta: 14:56:05 time: 0.5336 data_time: 0.0085 memory: 17620 loss: 4.5339 loss_prob: 2.8443 loss_thr: 1.0169 loss_db: 0.6727 2022/11/01 13:35:44 - mmengine - INFO - Epoch(train) [62][50/63] lr: 6.1445e-04 eta: 14:55:20 time: 0.5435 data_time: 0.0183 memory: 17620 loss: 4.5350 loss_prob: 2.8356 loss_thr: 1.0423 loss_db: 0.6571 2022/11/01 13:35:46 - mmengine - INFO - Epoch(train) [62][55/63] lr: 6.1445e-04 eta: 14:55:20 time: 0.5309 data_time: 0.0195 memory: 17620 loss: 4.5678 loss_prob: 2.8331 loss_thr: 1.0466 loss_db: 0.6881 2022/11/01 13:35:49 - mmengine - INFO - Epoch(train) [62][60/63] lr: 6.1445e-04 eta: 14:54:31 time: 0.5239 data_time: 0.0169 memory: 17620 loss: 4.5191 loss_prob: 2.8291 loss_thr: 1.0106 loss_db: 0.6794 2022/11/01 13:35:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:35:55 - mmengine - INFO - Epoch(train) [63][5/63] lr: 6.2449e-04 eta: 14:54:31 time: 0.7190 data_time: 0.1949 memory: 17620 loss: 4.4849 loss_prob: 2.8238 loss_thr: 1.0064 loss_db: 0.6547 2022/11/01 13:35:58 - mmengine - INFO - Epoch(train) [63][10/63] lr: 6.2449e-04 eta: 14:53:34 time: 0.7130 data_time: 0.1947 memory: 17620 loss: 4.5825 loss_prob: 2.8513 loss_thr: 1.0325 loss_db: 0.6987 2022/11/01 13:36:00 - mmengine - INFO - Epoch(train) [63][15/63] lr: 6.2449e-04 eta: 14:53:34 time: 0.5215 data_time: 0.0049 memory: 17620 loss: 4.5684 loss_prob: 2.8363 loss_thr: 1.0153 loss_db: 0.7167 2022/11/01 13:36:03 - mmengine - INFO - Epoch(train) [63][20/63] lr: 6.2449e-04 eta: 14:52:45 time: 0.5237 data_time: 0.0070 memory: 17620 loss: 4.4679 loss_prob: 2.8119 loss_thr: 0.9954 loss_db: 0.6606 2022/11/01 13:36:06 - mmengine - INFO - Epoch(train) [63][25/63] lr: 6.2449e-04 eta: 14:52:45 time: 0.5402 data_time: 0.0342 memory: 17620 loss: 4.4875 loss_prob: 2.8163 loss_thr: 0.9971 loss_db: 0.6741 2022/11/01 13:36:08 - mmengine - INFO - Epoch(train) [63][30/63] lr: 6.2449e-04 eta: 14:52:00 time: 0.5389 data_time: 0.0319 memory: 17620 loss: 4.3846 loss_prob: 2.7876 loss_thr: 0.9776 loss_db: 0.6195 2022/11/01 13:36:11 - mmengine - INFO - Epoch(train) [63][35/63] lr: 6.2449e-04 eta: 14:52:00 time: 0.5217 data_time: 0.0046 memory: 17620 loss: 4.3798 loss_prob: 2.7901 loss_thr: 0.9691 loss_db: 0.6206 2022/11/01 13:36:14 - mmengine - INFO - Epoch(train) [63][40/63] lr: 6.2449e-04 eta: 14:51:16 time: 0.5441 data_time: 0.0069 memory: 17620 loss: 4.3837 loss_prob: 2.7737 loss_thr: 0.9726 loss_db: 0.6374 2022/11/01 13:36:17 - mmengine - INFO - Epoch(train) [63][45/63] lr: 6.2449e-04 eta: 14:51:16 time: 0.5476 data_time: 0.0070 memory: 17620 loss: 4.4155 loss_prob: 2.7865 loss_thr: 0.9940 loss_db: 0.6349 2022/11/01 13:36:19 - mmengine - INFO - Epoch(train) [63][50/63] lr: 6.2449e-04 eta: 14:50:36 time: 0.5680 data_time: 0.0213 memory: 17620 loss: 4.4386 loss_prob: 2.7922 loss_thr: 0.9917 loss_db: 0.6546 2022/11/01 13:36:22 - mmengine - INFO - Epoch(train) [63][55/63] lr: 6.2449e-04 eta: 14:50:36 time: 0.5995 data_time: 0.0216 memory: 17620 loss: 4.3768 loss_prob: 2.7624 loss_thr: 0.9867 loss_db: 0.6277 2022/11/01 13:36:25 - mmengine - INFO - Epoch(train) [63][60/63] lr: 6.2449e-04 eta: 14:49:58 time: 0.5764 data_time: 0.0053 memory: 17620 loss: 4.2290 loss_prob: 2.6926 loss_thr: 0.9641 loss_db: 0.5723 2022/11/01 13:36:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:36:32 - mmengine - INFO - Epoch(train) [64][5/63] lr: 6.3453e-04 eta: 14:49:58 time: 0.7640 data_time: 0.2276 memory: 17620 loss: 4.2101 loss_prob: 2.6914 loss_thr: 0.9564 loss_db: 0.5622 2022/11/01 13:36:35 - mmengine - INFO - Epoch(train) [64][10/63] lr: 6.3453e-04 eta: 14:49:21 time: 0.8216 data_time: 0.2278 memory: 17620 loss: 4.3517 loss_prob: 2.7484 loss_thr: 0.9654 loss_db: 0.6379 2022/11/01 13:36:38 - mmengine - INFO - Epoch(train) [64][15/63] lr: 6.3453e-04 eta: 14:49:21 time: 0.6055 data_time: 0.0049 memory: 17620 loss: 4.3593 loss_prob: 2.7528 loss_thr: 0.9703 loss_db: 0.6362 2022/11/01 13:36:41 - mmengine - INFO - Epoch(train) [64][20/63] lr: 6.3453e-04 eta: 14:48:43 time: 0.5719 data_time: 0.0049 memory: 17620 loss: 4.2054 loss_prob: 2.6756 loss_thr: 0.9534 loss_db: 0.5764 2022/11/01 13:36:44 - mmengine - INFO - Epoch(train) [64][25/63] lr: 6.3453e-04 eta: 14:48:43 time: 0.5896 data_time: 0.0266 memory: 17620 loss: 4.1731 loss_prob: 2.6756 loss_thr: 0.9424 loss_db: 0.5551 2022/11/01 13:36:46 - mmengine - INFO - Epoch(train) [64][30/63] lr: 6.3453e-04 eta: 14:48:06 time: 0.5786 data_time: 0.0352 memory: 17620 loss: 4.2538 loss_prob: 2.7165 loss_thr: 0.9359 loss_db: 0.6014 2022/11/01 13:36:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:36:50 - mmengine - INFO - Epoch(train) [64][35/63] lr: 6.3453e-04 eta: 14:48:06 time: 0.5760 data_time: 0.0148 memory: 17620 loss: 4.2517 loss_prob: 2.6982 loss_thr: 0.9332 loss_db: 0.6203 2022/11/01 13:36:52 - mmengine - INFO - Epoch(train) [64][40/63] lr: 6.3453e-04 eta: 14:47:33 time: 0.6013 data_time: 0.0057 memory: 17620 loss: 4.2231 loss_prob: 2.7071 loss_thr: 0.9442 loss_db: 0.5718 2022/11/01 13:36:55 - mmengine - INFO - Epoch(train) [64][45/63] lr: 6.3453e-04 eta: 14:47:33 time: 0.5561 data_time: 0.0045 memory: 17620 loss: 4.2035 loss_prob: 2.6921 loss_thr: 0.9421 loss_db: 0.5694 2022/11/01 13:36:58 - mmengine - INFO - Epoch(train) [64][50/63] lr: 6.3453e-04 eta: 14:46:55 time: 0.5739 data_time: 0.0156 memory: 17620 loss: 4.2817 loss_prob: 2.7201 loss_thr: 0.9706 loss_db: 0.5910 2022/11/01 13:37:01 - mmengine - INFO - Epoch(train) [64][55/63] lr: 6.3453e-04 eta: 14:46:55 time: 0.5900 data_time: 0.0226 memory: 17620 loss: 4.2493 loss_prob: 2.7037 loss_thr: 0.9580 loss_db: 0.5875 2022/11/01 13:37:04 - mmengine - INFO - Epoch(train) [64][60/63] lr: 6.3453e-04 eta: 14:46:10 time: 0.5311 data_time: 0.0129 memory: 17620 loss: 4.2062 loss_prob: 2.6965 loss_thr: 0.9320 loss_db: 0.5777 2022/11/01 13:37:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:37:10 - mmengine - INFO - Epoch(train) [65][5/63] lr: 6.4457e-04 eta: 14:46:10 time: 0.7562 data_time: 0.2245 memory: 17620 loss: 4.2905 loss_prob: 2.7370 loss_thr: 0.9331 loss_db: 0.6204 2022/11/01 13:37:13 - mmengine - INFO - Epoch(train) [65][10/63] lr: 6.4457e-04 eta: 14:45:30 time: 0.7925 data_time: 0.2245 memory: 17620 loss: 4.1383 loss_prob: 2.6500 loss_thr: 0.9394 loss_db: 0.5489 2022/11/01 13:37:16 - mmengine - INFO - Epoch(train) [65][15/63] lr: 6.4457e-04 eta: 14:45:30 time: 0.5621 data_time: 0.0071 memory: 17620 loss: 4.0164 loss_prob: 2.5792 loss_thr: 0.9327 loss_db: 0.5044 2022/11/01 13:37:18 - mmengine - INFO - Epoch(train) [65][20/63] lr: 6.4457e-04 eta: 14:44:51 time: 0.5654 data_time: 0.0112 memory: 17620 loss: 3.9619 loss_prob: 2.5345 loss_thr: 0.9285 loss_db: 0.4990 2022/11/01 13:37:21 - mmengine - INFO - Epoch(train) [65][25/63] lr: 6.4457e-04 eta: 14:44:51 time: 0.5449 data_time: 0.0231 memory: 17620 loss: 3.8179 loss_prob: 2.4635 loss_thr: 0.8940 loss_db: 0.4603 2022/11/01 13:37:24 - mmengine - INFO - Epoch(train) [65][30/63] lr: 6.4457e-04 eta: 14:44:10 time: 0.5493 data_time: 0.0278 memory: 17620 loss: 3.9575 loss_prob: 2.5548 loss_thr: 0.9093 loss_db: 0.4933 2022/11/01 13:37:27 - mmengine - INFO - Epoch(train) [65][35/63] lr: 6.4457e-04 eta: 14:44:10 time: 0.5682 data_time: 0.0176 memory: 17620 loss: 4.1400 loss_prob: 2.6413 loss_thr: 0.9409 loss_db: 0.5578 2022/11/01 13:37:29 - mmengine - INFO - Epoch(train) [65][40/63] lr: 6.4457e-04 eta: 14:43:29 time: 0.5520 data_time: 0.0117 memory: 17620 loss: 4.1021 loss_prob: 2.5959 loss_thr: 0.9476 loss_db: 0.5586 2022/11/01 13:37:32 - mmengine - INFO - Epoch(train) [65][45/63] lr: 6.4457e-04 eta: 14:43:29 time: 0.5505 data_time: 0.0075 memory: 17620 loss: 4.0224 loss_prob: 2.5558 loss_thr: 0.9329 loss_db: 0.5338 2022/11/01 13:37:36 - mmengine - INFO - Epoch(train) [65][50/63] lr: 6.4457e-04 eta: 14:42:57 time: 0.6029 data_time: 0.0136 memory: 17620 loss: 3.9012 loss_prob: 2.4928 loss_thr: 0.9092 loss_db: 0.4992 2022/11/01 13:37:38 - mmengine - INFO - Epoch(train) [65][55/63] lr: 6.4457e-04 eta: 14:42:57 time: 0.5926 data_time: 0.0192 memory: 17620 loss: 3.8463 loss_prob: 2.4734 loss_thr: 0.8891 loss_db: 0.4837 2022/11/01 13:37:41 - mmengine - INFO - Epoch(train) [65][60/63] lr: 6.4457e-04 eta: 14:42:17 time: 0.5544 data_time: 0.0136 memory: 17620 loss: 3.8693 loss_prob: 2.4834 loss_thr: 0.8927 loss_db: 0.4932 2022/11/01 13:37:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:37:47 - mmengine - INFO - Epoch(train) [66][5/63] lr: 6.5461e-04 eta: 14:42:17 time: 0.7144 data_time: 0.2148 memory: 17620 loss: 3.8454 loss_prob: 2.4779 loss_thr: 0.8870 loss_db: 0.4805 2022/11/01 13:37:50 - mmengine - INFO - Epoch(train) [66][10/63] lr: 6.5461e-04 eta: 14:41:29 time: 0.7422 data_time: 0.2155 memory: 17620 loss: 3.8444 loss_prob: 2.4903 loss_thr: 0.8815 loss_db: 0.4727 2022/11/01 13:37:53 - mmengine - INFO - Epoch(train) [66][15/63] lr: 6.5461e-04 eta: 14:41:29 time: 0.5475 data_time: 0.0077 memory: 17620 loss: 3.8120 loss_prob: 2.4493 loss_thr: 0.8991 loss_db: 0.4636 2022/11/01 13:37:55 - mmengine - INFO - Epoch(train) [66][20/63] lr: 6.5461e-04 eta: 14:40:48 time: 0.5448 data_time: 0.0065 memory: 17620 loss: 3.8314 loss_prob: 2.4584 loss_thr: 0.8984 loss_db: 0.4746 2022/11/01 13:37:58 - mmengine - INFO - Epoch(train) [66][25/63] lr: 6.5461e-04 eta: 14:40:48 time: 0.5711 data_time: 0.0186 memory: 17620 loss: 3.9453 loss_prob: 2.5238 loss_thr: 0.9207 loss_db: 0.5008 2022/11/01 13:38:01 - mmengine - INFO - Epoch(train) [66][30/63] lr: 6.5461e-04 eta: 14:40:16 time: 0.5982 data_time: 0.0297 memory: 17620 loss: 3.9038 loss_prob: 2.4883 loss_thr: 0.9214 loss_db: 0.4941 2022/11/01 13:38:04 - mmengine - INFO - Epoch(train) [66][35/63] lr: 6.5461e-04 eta: 14:40:16 time: 0.5606 data_time: 0.0171 memory: 17620 loss: 3.8496 loss_prob: 2.4519 loss_thr: 0.9038 loss_db: 0.4939 2022/11/01 13:38:06 - mmengine - INFO - Epoch(train) [66][40/63] lr: 6.5461e-04 eta: 14:39:32 time: 0.5247 data_time: 0.0067 memory: 17620 loss: 4.0104 loss_prob: 2.5520 loss_thr: 0.9200 loss_db: 0.5384 2022/11/01 13:38:09 - mmengine - INFO - Epoch(train) [66][45/63] lr: 6.5461e-04 eta: 14:39:32 time: 0.5362 data_time: 0.0075 memory: 17620 loss: 4.0528 loss_prob: 2.5749 loss_thr: 0.9256 loss_db: 0.5522 2022/11/01 13:38:12 - mmengine - INFO - Epoch(train) [66][50/63] lr: 6.5461e-04 eta: 14:38:58 time: 0.5835 data_time: 0.0132 memory: 17620 loss: 3.9279 loss_prob: 2.5121 loss_thr: 0.9145 loss_db: 0.5013 2022/11/01 13:38:15 - mmengine - INFO - Epoch(train) [66][55/63] lr: 6.5461e-04 eta: 14:38:58 time: 0.6207 data_time: 0.0200 memory: 17620 loss: 3.9817 loss_prob: 2.5529 loss_thr: 0.9224 loss_db: 0.5064 2022/11/01 13:38:18 - mmengine - INFO - Epoch(train) [66][60/63] lr: 6.5461e-04 eta: 14:38:23 time: 0.5796 data_time: 0.0138 memory: 17620 loss: 3.9286 loss_prob: 2.5145 loss_thr: 0.9133 loss_db: 0.5008 2022/11/01 13:38:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:38:25 - mmengine - INFO - Epoch(train) [67][5/63] lr: 6.6465e-04 eta: 14:38:23 time: 0.7522 data_time: 0.2105 memory: 17620 loss: 4.0748 loss_prob: 2.5860 loss_thr: 0.9337 loss_db: 0.5552 2022/11/01 13:38:27 - mmengine - INFO - Epoch(train) [67][10/63] lr: 6.6465e-04 eta: 14:37:44 time: 0.7862 data_time: 0.2091 memory: 17620 loss: 3.8930 loss_prob: 2.4955 loss_thr: 0.9145 loss_db: 0.4830 2022/11/01 13:38:31 - mmengine - INFO - Epoch(train) [67][15/63] lr: 6.6465e-04 eta: 14:37:44 time: 0.6489 data_time: 0.0054 memory: 17620 loss: 3.6950 loss_prob: 2.3560 loss_thr: 0.9087 loss_db: 0.4303 2022/11/01 13:38:34 - mmengine - INFO - Epoch(train) [67][20/63] lr: 6.6465e-04 eta: 14:37:26 time: 0.6774 data_time: 0.0057 memory: 17620 loss: 3.5851 loss_prob: 2.2762 loss_thr: 0.9044 loss_db: 0.4044 2022/11/01 13:38:37 - mmengine - INFO - Epoch(train) [67][25/63] lr: 6.6465e-04 eta: 14:37:26 time: 0.6165 data_time: 0.0320 memory: 17620 loss: 3.6748 loss_prob: 2.3229 loss_thr: 0.9164 loss_db: 0.4355 2022/11/01 13:38:40 - mmengine - INFO - Epoch(train) [67][30/63] lr: 6.6465e-04 eta: 14:36:58 time: 0.6133 data_time: 0.0425 memory: 17620 loss: 3.7227 loss_prob: 2.3578 loss_thr: 0.9092 loss_db: 0.4557 2022/11/01 13:38:43 - mmengine - INFO - Epoch(train) [67][35/63] lr: 6.6465e-04 eta: 14:36:58 time: 0.5870 data_time: 0.0157 memory: 17620 loss: 3.8560 loss_prob: 2.4371 loss_thr: 0.9236 loss_db: 0.4954 2022/11/01 13:38:46 - mmengine - INFO - Epoch(train) [67][40/63] lr: 6.6465e-04 eta: 14:36:24 time: 0.5839 data_time: 0.0054 memory: 17620 loss: 4.1519 loss_prob: 2.5950 loss_thr: 0.9905 loss_db: 0.5664 2022/11/01 13:38:49 - mmengine - INFO - Epoch(train) [67][45/63] lr: 6.6465e-04 eta: 14:36:24 time: 0.5886 data_time: 0.0061 memory: 17620 loss: 4.1657 loss_prob: 2.6267 loss_thr: 0.9821 loss_db: 0.5568 2022/11/01 13:38:52 - mmengine - INFO - Epoch(train) [67][50/63] lr: 6.6465e-04 eta: 14:35:52 time: 0.5867 data_time: 0.0162 memory: 17620 loss: 4.1855 loss_prob: 2.6441 loss_thr: 0.9563 loss_db: 0.5851 2022/11/01 13:38:55 - mmengine - INFO - Epoch(train) [67][55/63] lr: 6.6465e-04 eta: 14:35:52 time: 0.6211 data_time: 0.0222 memory: 17620 loss: 4.0594 loss_prob: 2.5630 loss_thr: 0.9506 loss_db: 0.5458 2022/11/01 13:38:58 - mmengine - INFO - Epoch(train) [67][60/63] lr: 6.6465e-04 eta: 14:35:29 time: 0.6435 data_time: 0.0112 memory: 17620 loss: 3.8189 loss_prob: 2.4273 loss_thr: 0.9293 loss_db: 0.4623 2022/11/01 13:39:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:39:05 - mmengine - INFO - Epoch(train) [68][5/63] lr: 6.7469e-04 eta: 14:35:29 time: 0.8396 data_time: 0.2014 memory: 17620 loss: 3.5672 loss_prob: 2.2649 loss_thr: 0.8988 loss_db: 0.4034 2022/11/01 13:39:08 - mmengine - INFO - Epoch(train) [68][10/63] lr: 6.7469e-04 eta: 14:34:59 time: 0.8400 data_time: 0.2054 memory: 17620 loss: 3.6555 loss_prob: 2.3334 loss_thr: 0.8977 loss_db: 0.4244 2022/11/01 13:39:11 - mmengine - INFO - Epoch(train) [68][15/63] lr: 6.7469e-04 eta: 14:34:59 time: 0.5414 data_time: 0.0088 memory: 17620 loss: 3.8047 loss_prob: 2.4325 loss_thr: 0.8895 loss_db: 0.4826 2022/11/01 13:39:14 - mmengine - INFO - Epoch(train) [68][20/63] lr: 6.7469e-04 eta: 14:34:22 time: 0.5605 data_time: 0.0062 memory: 17620 loss: 3.8274 loss_prob: 2.4323 loss_thr: 0.8982 loss_db: 0.4968 2022/11/01 13:39:17 - mmengine - INFO - Epoch(train) [68][25/63] lr: 6.7469e-04 eta: 14:34:22 time: 0.6002 data_time: 0.0285 memory: 17620 loss: 3.7121 loss_prob: 2.3616 loss_thr: 0.8963 loss_db: 0.4542 2022/11/01 13:39:19 - mmengine - INFO - Epoch(train) [68][30/63] lr: 6.7469e-04 eta: 14:33:48 time: 0.5724 data_time: 0.0295 memory: 17620 loss: 3.5281 loss_prob: 2.2592 loss_thr: 0.8605 loss_db: 0.4083 2022/11/01 13:39:22 - mmengine - INFO - Epoch(train) [68][35/63] lr: 6.7469e-04 eta: 14:33:48 time: 0.5527 data_time: 0.0126 memory: 17620 loss: 3.4820 loss_prob: 2.2133 loss_thr: 0.8735 loss_db: 0.3952 2022/11/01 13:39:26 - mmengine - INFO - Epoch(train) [68][40/63] lr: 6.7469e-04 eta: 14:33:21 time: 0.6203 data_time: 0.0105 memory: 17620 loss: 3.7124 loss_prob: 2.3550 loss_thr: 0.9099 loss_db: 0.4475 2022/11/01 13:39:29 - mmengine - INFO - Epoch(train) [68][45/63] lr: 6.7469e-04 eta: 14:33:21 time: 0.6616 data_time: 0.0081 memory: 17620 loss: 3.9685 loss_prob: 2.5416 loss_thr: 0.9138 loss_db: 0.5131 2022/11/01 13:39:32 - mmengine - INFO - Epoch(train) [68][50/63] lr: 6.7469e-04 eta: 14:32:54 time: 0.6159 data_time: 0.0250 memory: 17620 loss: 3.7849 loss_prob: 2.4138 loss_thr: 0.9008 loss_db: 0.4702 2022/11/01 13:39:35 - mmengine - INFO - Epoch(train) [68][55/63] lr: 6.7469e-04 eta: 14:32:54 time: 0.5823 data_time: 0.0242 memory: 17620 loss: 3.5403 loss_prob: 2.2479 loss_thr: 0.8891 loss_db: 0.4033 2022/11/01 13:39:37 - mmengine - INFO - Epoch(train) [68][60/63] lr: 6.7469e-04 eta: 14:32:19 time: 0.5654 data_time: 0.0101 memory: 17620 loss: 3.4803 loss_prob: 2.2028 loss_thr: 0.8801 loss_db: 0.3974 2022/11/01 13:39:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:39:44 - mmengine - INFO - Epoch(train) [69][5/63] lr: 6.8473e-04 eta: 14:32:19 time: 0.7173 data_time: 0.2189 memory: 17620 loss: 3.8083 loss_prob: 2.4111 loss_thr: 0.9181 loss_db: 0.4790 2022/11/01 13:39:46 - mmengine - INFO - Epoch(train) [69][10/63] lr: 6.8473e-04 eta: 14:31:36 time: 0.7539 data_time: 0.2185 memory: 17620 loss: 3.8196 loss_prob: 2.4268 loss_thr: 0.9140 loss_db: 0.4788 2022/11/01 13:39:49 - mmengine - INFO - Epoch(train) [69][15/63] lr: 6.8473e-04 eta: 14:31:36 time: 0.5746 data_time: 0.0055 memory: 17620 loss: 3.5630 loss_prob: 2.2593 loss_thr: 0.8882 loss_db: 0.4154 2022/11/01 13:39:52 - mmengine - INFO - Epoch(train) [69][20/63] lr: 6.8473e-04 eta: 14:31:03 time: 0.5767 data_time: 0.0071 memory: 17620 loss: 3.3299 loss_prob: 2.1025 loss_thr: 0.8691 loss_db: 0.3584 2022/11/01 13:39:55 - mmengine - INFO - Epoch(train) [69][25/63] lr: 6.8473e-04 eta: 14:31:03 time: 0.5741 data_time: 0.0242 memory: 17620 loss: 3.2235 loss_prob: 2.0343 loss_thr: 0.8522 loss_db: 0.3370 2022/11/01 13:39:58 - mmengine - INFO - Epoch(train) [69][30/63] lr: 6.8473e-04 eta: 14:30:28 time: 0.5698 data_time: 0.0351 memory: 17620 loss: 3.1329 loss_prob: 1.9803 loss_thr: 0.8323 loss_db: 0.3203 2022/11/01 13:40:00 - mmengine - INFO - Epoch(train) [69][35/63] lr: 6.8473e-04 eta: 14:30:28 time: 0.5475 data_time: 0.0180 memory: 17620 loss: 3.2297 loss_prob: 2.0487 loss_thr: 0.8335 loss_db: 0.3475 2022/11/01 13:40:03 - mmengine - INFO - Epoch(train) [69][40/63] lr: 6.8473e-04 eta: 14:29:50 time: 0.5465 data_time: 0.0049 memory: 17620 loss: 3.5536 loss_prob: 2.2587 loss_thr: 0.8666 loss_db: 0.4283 2022/11/01 13:40:06 - mmengine - INFO - Epoch(train) [69][45/63] lr: 6.8473e-04 eta: 14:29:50 time: 0.5464 data_time: 0.0046 memory: 17620 loss: 3.6913 loss_prob: 2.3368 loss_thr: 0.8916 loss_db: 0.4630 2022/11/01 13:40:09 - mmengine - INFO - Epoch(train) [69][50/63] lr: 6.8473e-04 eta: 14:29:17 time: 0.5742 data_time: 0.0205 memory: 17620 loss: 3.3909 loss_prob: 2.1487 loss_thr: 0.8515 loss_db: 0.3906 2022/11/01 13:40:12 - mmengine - INFO - Epoch(train) [69][55/63] lr: 6.8473e-04 eta: 14:29:17 time: 0.5669 data_time: 0.0237 memory: 17620 loss: 3.2796 loss_prob: 2.0848 loss_thr: 0.8308 loss_db: 0.3640 2022/11/01 13:40:14 - mmengine - INFO - Epoch(train) [69][60/63] lr: 6.8473e-04 eta: 14:28:39 time: 0.5425 data_time: 0.0088 memory: 17620 loss: 3.3801 loss_prob: 2.1482 loss_thr: 0.8525 loss_db: 0.3793 2022/11/01 13:40:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:40:21 - mmengine - INFO - Epoch(train) [70][5/63] lr: 6.9477e-04 eta: 14:28:39 time: 0.7343 data_time: 0.1933 memory: 17620 loss: 3.2673 loss_prob: 2.0639 loss_thr: 0.8422 loss_db: 0.3612 2022/11/01 13:40:23 - mmengine - INFO - Epoch(train) [70][10/63] lr: 6.9477e-04 eta: 14:27:56 time: 0.7481 data_time: 0.1933 memory: 17620 loss: 3.4204 loss_prob: 2.1690 loss_thr: 0.8639 loss_db: 0.3875 2022/11/01 13:40:26 - mmengine - INFO - Epoch(train) [70][15/63] lr: 6.9477e-04 eta: 14:27:56 time: 0.5513 data_time: 0.0055 memory: 17620 loss: 3.4252 loss_prob: 2.1532 loss_thr: 0.8899 loss_db: 0.3821 2022/11/01 13:40:29 - mmengine - INFO - Epoch(train) [70][20/63] lr: 6.9477e-04 eta: 14:27:20 time: 0.5587 data_time: 0.0067 memory: 17620 loss: 3.3477 loss_prob: 2.1133 loss_thr: 0.8655 loss_db: 0.3689 2022/11/01 13:40:32 - mmengine - INFO - Epoch(train) [70][25/63] lr: 6.9477e-04 eta: 14:27:20 time: 0.5784 data_time: 0.0274 memory: 17620 loss: 3.3273 loss_prob: 2.1067 loss_thr: 0.8509 loss_db: 0.3698 2022/11/01 13:40:35 - mmengine - INFO - Epoch(train) [70][30/63] lr: 6.9477e-04 eta: 14:26:54 time: 0.6105 data_time: 0.0315 memory: 17620 loss: 3.5165 loss_prob: 2.2280 loss_thr: 0.8757 loss_db: 0.4127 2022/11/01 13:40:38 - mmengine - INFO - Epoch(train) [70][35/63] lr: 6.9477e-04 eta: 14:26:54 time: 0.5900 data_time: 0.0099 memory: 17620 loss: 3.6914 loss_prob: 2.3433 loss_thr: 0.8881 loss_db: 0.4600 2022/11/01 13:40:40 - mmengine - INFO - Epoch(train) [70][40/63] lr: 6.9477e-04 eta: 14:26:16 time: 0.5413 data_time: 0.0048 memory: 17620 loss: 3.6810 loss_prob: 2.3522 loss_thr: 0.8811 loss_db: 0.4477 2022/11/01 13:40:43 - mmengine - INFO - Epoch(train) [70][45/63] lr: 6.9477e-04 eta: 14:26:16 time: 0.5194 data_time: 0.0065 memory: 17620 loss: 3.5023 loss_prob: 2.2450 loss_thr: 0.8494 loss_db: 0.4079 2022/11/01 13:40:46 - mmengine - INFO - Epoch(train) [70][50/63] lr: 6.9477e-04 eta: 14:25:39 time: 0.5469 data_time: 0.0217 memory: 17620 loss: 3.4486 loss_prob: 2.1844 loss_thr: 0.8611 loss_db: 0.4030 2022/11/01 13:40:49 - mmengine - INFO - Epoch(train) [70][55/63] lr: 6.9477e-04 eta: 14:25:39 time: 0.5592 data_time: 0.0202 memory: 17620 loss: 3.4653 loss_prob: 2.1886 loss_thr: 0.8811 loss_db: 0.3956 2022/11/01 13:40:51 - mmengine - INFO - Epoch(train) [70][60/63] lr: 6.9477e-04 eta: 14:25:00 time: 0.5374 data_time: 0.0048 memory: 17620 loss: 3.4214 loss_prob: 2.1641 loss_thr: 0.8604 loss_db: 0.3969 2022/11/01 13:40:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:40:57 - mmengine - INFO - Epoch(train) [71][5/63] lr: 7.0481e-04 eta: 14:25:00 time: 0.7288 data_time: 0.1893 memory: 17620 loss: 3.3527 loss_prob: 2.1270 loss_thr: 0.8307 loss_db: 0.3951 2022/11/01 13:41:00 - mmengine - INFO - Epoch(train) [71][10/63] lr: 7.0481e-04 eta: 14:24:23 time: 0.7769 data_time: 0.1879 memory: 17620 loss: 3.5524 loss_prob: 2.2494 loss_thr: 0.8826 loss_db: 0.4204 2022/11/01 13:41:03 - mmengine - INFO - Epoch(train) [71][15/63] lr: 7.0481e-04 eta: 14:24:23 time: 0.5581 data_time: 0.0044 memory: 17620 loss: 3.6259 loss_prob: 2.2978 loss_thr: 0.9017 loss_db: 0.4264 2022/11/01 13:41:06 - mmengine - INFO - Epoch(train) [71][20/63] lr: 7.0481e-04 eta: 14:23:50 time: 0.5679 data_time: 0.0049 memory: 17620 loss: 3.4096 loss_prob: 2.1652 loss_thr: 0.8493 loss_db: 0.3951 2022/11/01 13:41:09 - mmengine - INFO - Epoch(train) [71][25/63] lr: 7.0481e-04 eta: 14:23:50 time: 0.5785 data_time: 0.0120 memory: 17620 loss: 3.3320 loss_prob: 2.1140 loss_thr: 0.8297 loss_db: 0.3883 2022/11/01 13:41:13 - mmengine - INFO - Epoch(train) [71][30/63] lr: 7.0481e-04 eta: 14:23:37 time: 0.6928 data_time: 0.0403 memory: 17620 loss: 3.3184 loss_prob: 2.0964 loss_thr: 0.8366 loss_db: 0.3854 2022/11/01 13:41:16 - mmengine - INFO - Epoch(train) [71][35/63] lr: 7.0481e-04 eta: 14:23:37 time: 0.7098 data_time: 0.0332 memory: 17620 loss: 3.3125 loss_prob: 2.0889 loss_thr: 0.8501 loss_db: 0.3736 2022/11/01 13:41:19 - mmengine - INFO - Epoch(train) [71][40/63] lr: 7.0481e-04 eta: 14:23:04 time: 0.5664 data_time: 0.0054 memory: 17620 loss: 3.5090 loss_prob: 2.2302 loss_thr: 0.8681 loss_db: 0.4107 2022/11/01 13:41:21 - mmengine - INFO - Epoch(train) [71][45/63] lr: 7.0481e-04 eta: 14:23:04 time: 0.5348 data_time: 0.0053 memory: 17620 loss: 3.6958 loss_prob: 2.3456 loss_thr: 0.8906 loss_db: 0.4596 2022/11/01 13:41:24 - mmengine - INFO - Epoch(train) [71][50/63] lr: 7.0481e-04 eta: 14:22:29 time: 0.5532 data_time: 0.0146 memory: 17620 loss: 3.7010 loss_prob: 2.3406 loss_thr: 0.9039 loss_db: 0.4565 2022/11/01 13:41:27 - mmengine - INFO - Epoch(train) [71][55/63] lr: 7.0481e-04 eta: 14:22:29 time: 0.5701 data_time: 0.0238 memory: 17620 loss: 3.2962 loss_prob: 2.0885 loss_thr: 0.8486 loss_db: 0.3592 2022/11/01 13:41:30 - mmengine - INFO - Epoch(train) [71][60/63] lr: 7.0481e-04 eta: 14:21:59 time: 0.5815 data_time: 0.0164 memory: 17620 loss: 3.1423 loss_prob: 1.9859 loss_thr: 0.8253 loss_db: 0.3310 2022/11/01 13:41:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:41:36 - mmengine - INFO - Epoch(train) [72][5/63] lr: 7.1485e-04 eta: 14:21:59 time: 0.7514 data_time: 0.1943 memory: 17620 loss: 3.2279 loss_prob: 2.0428 loss_thr: 0.8354 loss_db: 0.3497 2022/11/01 13:41:39 - mmengine - INFO - Epoch(train) [72][10/63] lr: 7.1485e-04 eta: 14:21:26 time: 0.7996 data_time: 0.2029 memory: 17620 loss: 3.0747 loss_prob: 1.9362 loss_thr: 0.8154 loss_db: 0.3230 2022/11/01 13:41:43 - mmengine - INFO - Epoch(train) [72][15/63] lr: 7.1485e-04 eta: 14:21:26 time: 0.6604 data_time: 0.0151 memory: 17620 loss: 3.1787 loss_prob: 2.0128 loss_thr: 0.8141 loss_db: 0.3518 2022/11/01 13:41:46 - mmengine - INFO - Epoch(train) [72][20/63] lr: 7.1485e-04 eta: 14:21:12 time: 0.6850 data_time: 0.0049 memory: 17620 loss: 3.3186 loss_prob: 2.0889 loss_thr: 0.8512 loss_db: 0.3785 2022/11/01 13:41:49 - mmengine - INFO - Epoch(train) [72][25/63] lr: 7.1485e-04 eta: 14:21:12 time: 0.6409 data_time: 0.0112 memory: 17620 loss: 3.2655 loss_prob: 2.0535 loss_thr: 0.8523 loss_db: 0.3597 2022/11/01 13:41:52 - mmengine - INFO - Epoch(train) [72][30/63] lr: 7.1485e-04 eta: 14:20:47 time: 0.6115 data_time: 0.0322 memory: 17620 loss: 3.3017 loss_prob: 2.0905 loss_thr: 0.8446 loss_db: 0.3665 2022/11/01 13:41:55 - mmengine - INFO - Epoch(train) [72][35/63] lr: 7.1485e-04 eta: 14:20:47 time: 0.6019 data_time: 0.0320 memory: 17620 loss: 3.2471 loss_prob: 2.0381 loss_thr: 0.8521 loss_db: 0.3568 2022/11/01 13:41:58 - mmengine - INFO - Epoch(train) [72][40/63] lr: 7.1485e-04 eta: 14:20:11 time: 0.5487 data_time: 0.0107 memory: 17620 loss: 3.2712 loss_prob: 2.0547 loss_thr: 0.8465 loss_db: 0.3700 2022/11/01 13:42:01 - mmengine - INFO - Epoch(train) [72][45/63] lr: 7.1485e-04 eta: 14:20:11 time: 0.5357 data_time: 0.0048 memory: 17620 loss: 3.3035 loss_prob: 2.0808 loss_thr: 0.8376 loss_db: 0.3851 2022/11/01 13:42:03 - mmengine - INFO - Epoch(train) [72][50/63] lr: 7.1485e-04 eta: 14:19:38 time: 0.5589 data_time: 0.0290 memory: 17620 loss: 3.3726 loss_prob: 2.1357 loss_thr: 0.8377 loss_db: 0.3993 2022/11/01 13:42:06 - mmengine - INFO - Epoch(train) [72][55/63] lr: 7.1485e-04 eta: 14:19:38 time: 0.5667 data_time: 0.0342 memory: 17620 loss: 3.4078 loss_prob: 2.1701 loss_thr: 0.8423 loss_db: 0.3954 2022/11/01 13:42:09 - mmengine - INFO - Epoch(train) [72][60/63] lr: 7.1485e-04 eta: 14:19:05 time: 0.5618 data_time: 0.0126 memory: 17620 loss: 3.3264 loss_prob: 2.1100 loss_thr: 0.8349 loss_db: 0.3816 2022/11/01 13:42:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:42:15 - mmengine - INFO - Epoch(train) [73][5/63] lr: 7.2489e-04 eta: 14:19:05 time: 0.7237 data_time: 0.1737 memory: 17620 loss: 3.2731 loss_prob: 2.0674 loss_thr: 0.8382 loss_db: 0.3674 2022/11/01 13:42:18 - mmengine - INFO - Epoch(train) [73][10/63] lr: 7.2489e-04 eta: 14:18:25 time: 0.7509 data_time: 0.1773 memory: 17620 loss: 3.0715 loss_prob: 1.9289 loss_thr: 0.8191 loss_db: 0.3236 2022/11/01 13:42:20 - mmengine - INFO - Epoch(train) [73][15/63] lr: 7.2489e-04 eta: 14:18:25 time: 0.5242 data_time: 0.0094 memory: 17620 loss: 3.3124 loss_prob: 2.0948 loss_thr: 0.8456 loss_db: 0.3720 2022/11/01 13:42:23 - mmengine - INFO - Epoch(train) [73][20/63] lr: 7.2489e-04 eta: 14:17:48 time: 0.5318 data_time: 0.0098 memory: 17620 loss: 3.3385 loss_prob: 2.1112 loss_thr: 0.8503 loss_db: 0.3771 2022/11/01 13:42:26 - mmengine - INFO - Epoch(train) [73][25/63] lr: 7.2489e-04 eta: 14:17:48 time: 0.5977 data_time: 0.0207 memory: 17620 loss: 3.2261 loss_prob: 2.0405 loss_thr: 0.8277 loss_db: 0.3579 2022/11/01 13:42:29 - mmengine - INFO - Epoch(train) [73][30/63] lr: 7.2489e-04 eta: 14:17:20 time: 0.5927 data_time: 0.0304 memory: 17620 loss: 3.4412 loss_prob: 2.1764 loss_thr: 0.8293 loss_db: 0.4356 2022/11/01 13:42:32 - mmengine - INFO - Epoch(train) [73][35/63] lr: 7.2489e-04 eta: 14:17:20 time: 0.5663 data_time: 0.0258 memory: 17620 loss: 3.8489 loss_prob: 2.4486 loss_thr: 0.8691 loss_db: 0.5312 2022/11/01 13:42:35 - mmengine - INFO - Epoch(train) [73][40/63] lr: 7.2489e-04 eta: 14:16:51 time: 0.5792 data_time: 0.0137 memory: 17620 loss: 3.7160 loss_prob: 2.3785 loss_thr: 0.8646 loss_db: 0.4728 2022/11/01 13:42:38 - mmengine - INFO - Epoch(train) [73][45/63] lr: 7.2489e-04 eta: 14:16:51 time: 0.5666 data_time: 0.0060 memory: 17620 loss: 3.3763 loss_prob: 2.1552 loss_thr: 0.8327 loss_db: 0.3884 2022/11/01 13:42:41 - mmengine - INFO - Epoch(train) [73][50/63] lr: 7.2489e-04 eta: 14:16:19 time: 0.5640 data_time: 0.0139 memory: 17620 loss: 3.3068 loss_prob: 2.0981 loss_thr: 0.8348 loss_db: 0.3739 2022/11/01 13:42:43 - mmengine - INFO - Epoch(train) [73][55/63] lr: 7.2489e-04 eta: 14:16:19 time: 0.5708 data_time: 0.0211 memory: 17620 loss: 3.3175 loss_prob: 2.0954 loss_thr: 0.8505 loss_db: 0.3717 2022/11/01 13:42:46 - mmengine - INFO - Epoch(train) [73][60/63] lr: 7.2489e-04 eta: 14:15:44 time: 0.5437 data_time: 0.0117 memory: 17620 loss: 3.2349 loss_prob: 2.0413 loss_thr: 0.8336 loss_db: 0.3600 2022/11/01 13:42:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:42:52 - mmengine - INFO - Epoch(train) [74][5/63] lr: 7.3493e-04 eta: 14:15:44 time: 0.6798 data_time: 0.1558 memory: 17620 loss: 3.1536 loss_prob: 1.9996 loss_thr: 0.8033 loss_db: 0.3507 2022/11/01 13:42:55 - mmengine - INFO - Epoch(train) [74][10/63] lr: 7.3493e-04 eta: 14:15:00 time: 0.7177 data_time: 0.1663 memory: 17620 loss: 2.9661 loss_prob: 1.8701 loss_thr: 0.7894 loss_db: 0.3066 2022/11/01 13:42:57 - mmengine - INFO - Epoch(train) [74][15/63] lr: 7.3493e-04 eta: 14:15:00 time: 0.5597 data_time: 0.0190 memory: 17620 loss: 3.0332 loss_prob: 1.9027 loss_thr: 0.8083 loss_db: 0.3222 2022/11/01 13:43:00 - mmengine - INFO - Epoch(train) [74][20/63] lr: 7.3493e-04 eta: 14:14:30 time: 0.5734 data_time: 0.0100 memory: 17620 loss: 3.0594 loss_prob: 1.9193 loss_thr: 0.8061 loss_db: 0.3340 2022/11/01 13:43:03 - mmengine - INFO - Epoch(train) [74][25/63] lr: 7.3493e-04 eta: 14:14:30 time: 0.6091 data_time: 0.0149 memory: 17620 loss: 3.1213 loss_prob: 1.9590 loss_thr: 0.8151 loss_db: 0.3472 2022/11/01 13:43:06 - mmengine - INFO - Epoch(train) [74][30/63] lr: 7.3493e-04 eta: 14:14:06 time: 0.6120 data_time: 0.0281 memory: 17620 loss: 3.2405 loss_prob: 2.0223 loss_thr: 0.8512 loss_db: 0.3670 2022/11/01 13:43:09 - mmengine - INFO - Epoch(train) [74][35/63] lr: 7.3493e-04 eta: 14:14:06 time: 0.5653 data_time: 0.0249 memory: 17620 loss: 3.0902 loss_prob: 1.9039 loss_thr: 0.8583 loss_db: 0.3280 2022/11/01 13:43:12 - mmengine - INFO - Epoch(train) [74][40/63] lr: 7.3493e-04 eta: 14:13:28 time: 0.5257 data_time: 0.0111 memory: 17620 loss: 2.9875 loss_prob: 1.8503 loss_thr: 0.8316 loss_db: 0.3056 2022/11/01 13:43:14 - mmengine - INFO - Epoch(train) [74][45/63] lr: 7.3493e-04 eta: 14:13:28 time: 0.5405 data_time: 0.0085 memory: 17620 loss: 3.0509 loss_prob: 1.9070 loss_thr: 0.8237 loss_db: 0.3202 2022/11/01 13:43:18 - mmengine - INFO - Epoch(train) [74][50/63] lr: 7.3493e-04 eta: 14:13:04 time: 0.6107 data_time: 0.0120 memory: 17620 loss: 2.9509 loss_prob: 1.8374 loss_thr: 0.8055 loss_db: 0.3079 2022/11/01 13:43:21 - mmengine - INFO - Epoch(train) [74][55/63] lr: 7.3493e-04 eta: 14:13:04 time: 0.6288 data_time: 0.0201 memory: 17620 loss: 3.0046 loss_prob: 1.8903 loss_thr: 0.7877 loss_db: 0.3265 2022/11/01 13:43:23 - mmengine - INFO - Epoch(train) [74][60/63] lr: 7.3493e-04 eta: 14:12:34 time: 0.5708 data_time: 0.0197 memory: 17620 loss: 3.2652 loss_prob: 2.0701 loss_thr: 0.8124 loss_db: 0.3827 2022/11/01 13:43:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:43:30 - mmengine - INFO - Epoch(train) [75][5/63] lr: 7.4497e-04 eta: 14:12:34 time: 0.7888 data_time: 0.2093 memory: 17620 loss: 3.2185 loss_prob: 2.0558 loss_thr: 0.7940 loss_db: 0.3686 2022/11/01 13:43:34 - mmengine - INFO - Epoch(train) [75][10/63] lr: 7.4497e-04 eta: 14:12:15 time: 0.8757 data_time: 0.2076 memory: 17620 loss: 3.3708 loss_prob: 2.1429 loss_thr: 0.8396 loss_db: 0.3884 2022/11/01 13:43:37 - mmengine - INFO - Epoch(train) [75][15/63] lr: 7.4497e-04 eta: 14:12:15 time: 0.6400 data_time: 0.0052 memory: 17620 loss: 3.5638 loss_prob: 2.2692 loss_thr: 0.8805 loss_db: 0.4141 2022/11/01 13:43:40 - mmengine - INFO - Epoch(train) [75][20/63] lr: 7.4497e-04 eta: 14:11:57 time: 0.6448 data_time: 0.0066 memory: 17620 loss: 3.7467 loss_prob: 2.4038 loss_thr: 0.8878 loss_db: 0.4552 2022/11/01 13:43:43 - mmengine - INFO - Epoch(train) [75][25/63] lr: 7.4497e-04 eta: 14:11:57 time: 0.6397 data_time: 0.0213 memory: 17620 loss: 3.4988 loss_prob: 2.2276 loss_thr: 0.8732 loss_db: 0.3980 2022/11/01 13:43:47 - mmengine - INFO - Epoch(train) [75][30/63] lr: 7.4497e-04 eta: 14:11:42 time: 0.6734 data_time: 0.0353 memory: 17620 loss: 3.3542 loss_prob: 2.1267 loss_thr: 0.8591 loss_db: 0.3685 2022/11/01 13:43:50 - mmengine - INFO - Epoch(train) [75][35/63] lr: 7.4497e-04 eta: 14:11:42 time: 0.6525 data_time: 0.0212 memory: 17620 loss: 3.3290 loss_prob: 2.1047 loss_thr: 0.8595 loss_db: 0.3649 2022/11/01 13:43:52 - mmengine - INFO - Epoch(train) [75][40/63] lr: 7.4497e-04 eta: 14:11:10 time: 0.5542 data_time: 0.0060 memory: 17620 loss: 3.0660 loss_prob: 1.9230 loss_thr: 0.8219 loss_db: 0.3211 2022/11/01 13:43:55 - mmengine - INFO - Epoch(train) [75][45/63] lr: 7.4497e-04 eta: 14:11:10 time: 0.5707 data_time: 0.0055 memory: 17620 loss: 2.9505 loss_prob: 1.8515 loss_thr: 0.7942 loss_db: 0.3049 2022/11/01 13:43:58 - mmengine - INFO - Epoch(train) [75][50/63] lr: 7.4497e-04 eta: 14:10:47 time: 0.6176 data_time: 0.0142 memory: 17620 loss: 3.1543 loss_prob: 1.9886 loss_thr: 0.8304 loss_db: 0.3352 2022/11/01 13:44:01 - mmengine - INFO - Epoch(train) [75][55/63] lr: 7.4497e-04 eta: 14:10:47 time: 0.5861 data_time: 0.0241 memory: 17620 loss: 3.2671 loss_prob: 2.0503 loss_thr: 0.8575 loss_db: 0.3593 2022/11/01 13:44:05 - mmengine - INFO - Epoch(train) [75][60/63] lr: 7.4497e-04 eta: 14:10:26 time: 0.6233 data_time: 0.0175 memory: 17620 loss: 3.2235 loss_prob: 2.0248 loss_thr: 0.8318 loss_db: 0.3670 2022/11/01 13:44:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:44:12 - mmengine - INFO - Epoch(train) [76][5/63] lr: 7.5502e-04 eta: 14:10:26 time: 0.8556 data_time: 0.2312 memory: 17620 loss: 2.9682 loss_prob: 1.8511 loss_thr: 0.8057 loss_db: 0.3114 2022/11/01 13:44:14 - mmengine - INFO - Epoch(train) [76][10/63] lr: 7.5502e-04 eta: 14:09:58 time: 0.8112 data_time: 0.2319 memory: 17620 loss: 2.9722 loss_prob: 1.8472 loss_thr: 0.8127 loss_db: 0.3123 2022/11/01 13:44:17 - mmengine - INFO - Epoch(train) [76][15/63] lr: 7.5502e-04 eta: 14:09:58 time: 0.5564 data_time: 0.0087 memory: 17620 loss: 3.0660 loss_prob: 1.9116 loss_thr: 0.8245 loss_db: 0.3299 2022/11/01 13:44:20 - mmengine - INFO - Epoch(train) [76][20/63] lr: 7.5502e-04 eta: 14:09:29 time: 0.5756 data_time: 0.0085 memory: 17620 loss: 3.0287 loss_prob: 1.8903 loss_thr: 0.8204 loss_db: 0.3179 2022/11/01 13:44:23 - mmengine - INFO - Epoch(train) [76][25/63] lr: 7.5502e-04 eta: 14:09:29 time: 0.5991 data_time: 0.0367 memory: 17620 loss: 3.1396 loss_prob: 1.9745 loss_thr: 0.8237 loss_db: 0.3414 2022/11/01 13:44:26 - mmengine - INFO - Epoch(train) [76][30/63] lr: 7.5502e-04 eta: 14:09:03 time: 0.5937 data_time: 0.0365 memory: 17620 loss: 3.5456 loss_prob: 2.2444 loss_thr: 0.8860 loss_db: 0.4152 2022/11/01 13:44:29 - mmengine - INFO - Epoch(train) [76][35/63] lr: 7.5502e-04 eta: 14:09:03 time: 0.5493 data_time: 0.0046 memory: 17620 loss: 3.3797 loss_prob: 2.1262 loss_thr: 0.8723 loss_db: 0.3812 2022/11/01 13:44:31 - mmengine - INFO - Epoch(train) [76][40/63] lr: 7.5502e-04 eta: 14:08:30 time: 0.5454 data_time: 0.0050 memory: 17620 loss: 2.8696 loss_prob: 1.7842 loss_thr: 0.7930 loss_db: 0.2923 2022/11/01 13:44:34 - mmengine - INFO - Epoch(train) [76][45/63] lr: 7.5502e-04 eta: 14:08:30 time: 0.5402 data_time: 0.0065 memory: 17620 loss: 2.8534 loss_prob: 1.7662 loss_thr: 0.7993 loss_db: 0.2879 2022/11/01 13:44:37 - mmengine - INFO - Epoch(train) [76][50/63] lr: 7.5502e-04 eta: 14:07:59 time: 0.5583 data_time: 0.0233 memory: 17620 loss: 3.0704 loss_prob: 1.9111 loss_thr: 0.8308 loss_db: 0.3285 2022/11/01 13:44:40 - mmengine - INFO - Epoch(train) [76][55/63] lr: 7.5502e-04 eta: 14:07:59 time: 0.5748 data_time: 0.0227 memory: 17620 loss: 3.0290 loss_prob: 1.8906 loss_thr: 0.8123 loss_db: 0.3261 2022/11/01 13:44:43 - mmengine - INFO - Epoch(train) [76][60/63] lr: 7.5502e-04 eta: 14:07:30 time: 0.5735 data_time: 0.0071 memory: 17620 loss: 3.0450 loss_prob: 1.8932 loss_thr: 0.8223 loss_db: 0.3294 2022/11/01 13:44:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:44:49 - mmengine - INFO - Epoch(train) [77][5/63] lr: 7.6506e-04 eta: 14:07:30 time: 0.7185 data_time: 0.1827 memory: 17620 loss: 3.3687 loss_prob: 2.1837 loss_thr: 0.8009 loss_db: 0.3841 2022/11/01 13:44:52 - mmengine - INFO - Epoch(train) [77][10/63] lr: 7.6506e-04 eta: 14:06:53 time: 0.7447 data_time: 0.1851 memory: 17620 loss: 3.2549 loss_prob: 2.0805 loss_thr: 0.8060 loss_db: 0.3685 2022/11/01 13:44:55 - mmengine - INFO - Epoch(train) [77][15/63] lr: 7.6506e-04 eta: 14:06:53 time: 0.5847 data_time: 0.0129 memory: 17620 loss: 3.0716 loss_prob: 1.9283 loss_thr: 0.8180 loss_db: 0.3253 2022/11/01 13:44:58 - mmengine - INFO - Epoch(train) [77][20/63] lr: 7.6506e-04 eta: 14:06:29 time: 0.6035 data_time: 0.0135 memory: 17620 loss: 3.0034 loss_prob: 1.8788 loss_thr: 0.8008 loss_db: 0.3237 2022/11/01 13:45:01 - mmengine - INFO - Epoch(train) [77][25/63] lr: 7.6506e-04 eta: 14:06:29 time: 0.5872 data_time: 0.0269 memory: 17620 loss: 3.2436 loss_prob: 2.0508 loss_thr: 0.8275 loss_db: 0.3653 2022/11/01 13:45:03 - mmengine - INFO - Epoch(train) [77][30/63] lr: 7.6506e-04 eta: 14:06:02 time: 0.5789 data_time: 0.0274 memory: 17620 loss: 3.1517 loss_prob: 1.9798 loss_thr: 0.8345 loss_db: 0.3375 2022/11/01 13:45:06 - mmengine - INFO - Epoch(train) [77][35/63] lr: 7.6506e-04 eta: 14:06:02 time: 0.5836 data_time: 0.0105 memory: 17620 loss: 3.0041 loss_prob: 1.8699 loss_thr: 0.8209 loss_db: 0.3134 2022/11/01 13:45:09 - mmengine - INFO - Epoch(train) [77][40/63] lr: 7.6506e-04 eta: 14:05:32 time: 0.5660 data_time: 0.0105 memory: 17620 loss: 3.0483 loss_prob: 1.9047 loss_thr: 0.8189 loss_db: 0.3247 2022/11/01 13:45:12 - mmengine - INFO - Epoch(train) [77][45/63] lr: 7.6506e-04 eta: 14:05:32 time: 0.5643 data_time: 0.0120 memory: 17620 loss: 3.0241 loss_prob: 1.9043 loss_thr: 0.7916 loss_db: 0.3282 2022/11/01 13:45:15 - mmengine - INFO - Epoch(train) [77][50/63] lr: 7.6506e-04 eta: 14:05:05 time: 0.5823 data_time: 0.0247 memory: 17620 loss: 3.0912 loss_prob: 1.9447 loss_thr: 0.8007 loss_db: 0.3458 2022/11/01 13:45:18 - mmengine - INFO - Epoch(train) [77][55/63] lr: 7.6506e-04 eta: 14:05:05 time: 0.5649 data_time: 0.0208 memory: 17620 loss: 3.1853 loss_prob: 2.0130 loss_thr: 0.8107 loss_db: 0.3616 2022/11/01 13:45:20 - mmengine - INFO - Epoch(train) [77][60/63] lr: 7.6506e-04 eta: 14:04:33 time: 0.5457 data_time: 0.0070 memory: 17620 loss: 3.0289 loss_prob: 1.9109 loss_thr: 0.7896 loss_db: 0.3284 2022/11/01 13:45:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:45:26 - mmengine - INFO - Epoch(train) [78][5/63] lr: 7.7510e-04 eta: 14:04:33 time: 0.6997 data_time: 0.1861 memory: 17620 loss: 2.9564 loss_prob: 1.8356 loss_thr: 0.7984 loss_db: 0.3225 2022/11/01 13:45:29 - mmengine - INFO - Epoch(train) [78][10/63] lr: 7.7510e-04 eta: 14:03:55 time: 0.7326 data_time: 0.1864 memory: 17620 loss: 2.8895 loss_prob: 1.7937 loss_thr: 0.7969 loss_db: 0.2990 2022/11/01 13:45:32 - mmengine - INFO - Epoch(train) [78][15/63] lr: 7.7510e-04 eta: 14:03:55 time: 0.5553 data_time: 0.0093 memory: 17620 loss: 2.9194 loss_prob: 1.8277 loss_thr: 0.7895 loss_db: 0.3023 2022/11/01 13:45:35 - mmengine - INFO - Epoch(train) [78][20/63] lr: 7.7510e-04 eta: 14:03:27 time: 0.5719 data_time: 0.0082 memory: 17620 loss: 2.8899 loss_prob: 1.8105 loss_thr: 0.7809 loss_db: 0.2985 2022/11/01 13:45:38 - mmengine - INFO - Epoch(train) [78][25/63] lr: 7.7510e-04 eta: 14:03:27 time: 0.5899 data_time: 0.0288 memory: 17620 loss: 3.0924 loss_prob: 1.9441 loss_thr: 0.8192 loss_db: 0.3290 2022/11/01 13:45:41 - mmengine - INFO - Epoch(train) [78][30/63] lr: 7.7510e-04 eta: 14:03:05 time: 0.6150 data_time: 0.0461 memory: 17620 loss: 3.3439 loss_prob: 2.1135 loss_thr: 0.8585 loss_db: 0.3719 2022/11/01 13:45:44 - mmengine - INFO - Epoch(train) [78][35/63] lr: 7.7510e-04 eta: 14:03:05 time: 0.5876 data_time: 0.0257 memory: 17620 loss: 3.1517 loss_prob: 1.9858 loss_thr: 0.8203 loss_db: 0.3456 2022/11/01 13:45:46 - mmengine - INFO - Epoch(train) [78][40/63] lr: 7.7510e-04 eta: 14:02:35 time: 0.5549 data_time: 0.0094 memory: 17620 loss: 2.8526 loss_prob: 1.7788 loss_thr: 0.7839 loss_db: 0.2899 2022/11/01 13:45:49 - mmengine - INFO - Epoch(train) [78][45/63] lr: 7.7510e-04 eta: 14:02:35 time: 0.5711 data_time: 0.0074 memory: 17620 loss: 2.9285 loss_prob: 1.8363 loss_thr: 0.7889 loss_db: 0.3033 2022/11/01 13:45:52 - mmengine - INFO - Epoch(train) [78][50/63] lr: 7.7510e-04 eta: 14:02:11 time: 0.5947 data_time: 0.0095 memory: 17620 loss: 2.9321 loss_prob: 1.8429 loss_thr: 0.7806 loss_db: 0.3086 2022/11/01 13:45:55 - mmengine - INFO - Epoch(train) [78][55/63] lr: 7.7510e-04 eta: 14:02:11 time: 0.6013 data_time: 0.0212 memory: 17620 loss: 3.1051 loss_prob: 1.9506 loss_thr: 0.8167 loss_db: 0.3377 2022/11/01 13:45:59 - mmengine - INFO - Epoch(train) [78][60/63] lr: 7.7510e-04 eta: 14:01:50 time: 0.6241 data_time: 0.0197 memory: 17620 loss: 3.2489 loss_prob: 2.0466 loss_thr: 0.8331 loss_db: 0.3691 2022/11/01 13:46:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:46:06 - mmengine - INFO - Epoch(train) [79][5/63] lr: 7.8514e-04 eta: 14:01:50 time: 0.8574 data_time: 0.1712 memory: 17620 loss: 3.2756 loss_prob: 2.0883 loss_thr: 0.8054 loss_db: 0.3819 2022/11/01 13:46:09 - mmengine - INFO - Epoch(train) [79][10/63] lr: 7.8514e-04 eta: 14:01:27 time: 0.8303 data_time: 0.1772 memory: 17620 loss: 3.0154 loss_prob: 1.8844 loss_thr: 0.8011 loss_db: 0.3299 2022/11/01 13:46:12 - mmengine - INFO - Epoch(train) [79][15/63] lr: 7.8514e-04 eta: 14:01:27 time: 0.5874 data_time: 0.0121 memory: 17620 loss: 2.9536 loss_prob: 1.8312 loss_thr: 0.8082 loss_db: 0.3141 2022/11/01 13:46:15 - mmengine - INFO - Epoch(train) [79][20/63] lr: 7.8514e-04 eta: 14:01:06 time: 0.6190 data_time: 0.0053 memory: 17620 loss: 2.9823 loss_prob: 1.8603 loss_thr: 0.8035 loss_db: 0.3185 2022/11/01 13:46:18 - mmengine - INFO - Epoch(train) [79][25/63] lr: 7.8514e-04 eta: 14:01:06 time: 0.5948 data_time: 0.0125 memory: 17620 loss: 2.9598 loss_prob: 1.8494 loss_thr: 0.7978 loss_db: 0.3126 2022/11/01 13:46:20 - mmengine - INFO - Epoch(train) [79][30/63] lr: 7.8514e-04 eta: 14:00:39 time: 0.5761 data_time: 0.0310 memory: 17620 loss: 3.0934 loss_prob: 1.9328 loss_thr: 0.8218 loss_db: 0.3388 2022/11/01 13:46:23 - mmengine - INFO - Epoch(train) [79][35/63] lr: 7.8514e-04 eta: 14:00:39 time: 0.5802 data_time: 0.0262 memory: 17620 loss: 3.1379 loss_prob: 1.9629 loss_thr: 0.8345 loss_db: 0.3405 2022/11/01 13:46:26 - mmengine - INFO - Epoch(train) [79][40/63] lr: 7.8514e-04 eta: 14:00:12 time: 0.5747 data_time: 0.0084 memory: 17620 loss: 3.1091 loss_prob: 1.9540 loss_thr: 0.8242 loss_db: 0.3308 2022/11/01 13:46:29 - mmengine - INFO - Epoch(train) [79][45/63] lr: 7.8514e-04 eta: 14:00:12 time: 0.5837 data_time: 0.0054 memory: 17620 loss: 3.1871 loss_prob: 2.0160 loss_thr: 0.8197 loss_db: 0.3514 2022/11/01 13:46:32 - mmengine - INFO - Epoch(train) [79][50/63] lr: 7.8514e-04 eta: 13:59:47 time: 0.5889 data_time: 0.0147 memory: 17620 loss: 3.0131 loss_prob: 1.8949 loss_thr: 0.7985 loss_db: 0.3198 2022/11/01 13:46:35 - mmengine - INFO - Epoch(train) [79][55/63] lr: 7.8514e-04 eta: 13:59:47 time: 0.5756 data_time: 0.0233 memory: 17620 loss: 3.1014 loss_prob: 1.9357 loss_thr: 0.8385 loss_db: 0.3273 2022/11/01 13:46:38 - mmengine - INFO - Epoch(train) [79][60/63] lr: 7.8514e-04 eta: 13:59:17 time: 0.5509 data_time: 0.0134 memory: 17620 loss: 3.1060 loss_prob: 1.9391 loss_thr: 0.8315 loss_db: 0.3355 2022/11/01 13:46:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:46:44 - mmengine - INFO - Epoch(train) [80][5/63] lr: 7.9518e-04 eta: 13:59:17 time: 0.7292 data_time: 0.1800 memory: 17620 loss: 2.8543 loss_prob: 1.7777 loss_thr: 0.7801 loss_db: 0.2965 2022/11/01 13:46:47 - mmengine - INFO - Epoch(train) [80][10/63] lr: 7.9518e-04 eta: 13:58:46 time: 0.7706 data_time: 0.1807 memory: 17620 loss: 2.9902 loss_prob: 1.8697 loss_thr: 0.8018 loss_db: 0.3187 2022/11/01 13:46:49 - mmengine - INFO - Epoch(train) [80][15/63] lr: 7.9518e-04 eta: 13:58:46 time: 0.5510 data_time: 0.0056 memory: 17620 loss: 2.9871 loss_prob: 1.8725 loss_thr: 0.7934 loss_db: 0.3211 2022/11/01 13:46:52 - mmengine - INFO - Epoch(train) [80][20/63] lr: 7.9518e-04 eta: 13:58:16 time: 0.5545 data_time: 0.0080 memory: 17620 loss: 2.8314 loss_prob: 1.7546 loss_thr: 0.7846 loss_db: 0.2922 2022/11/01 13:46:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:46:55 - mmengine - INFO - Epoch(train) [80][25/63] lr: 7.9518e-04 eta: 13:58:16 time: 0.5440 data_time: 0.0228 memory: 17620 loss: 2.8412 loss_prob: 1.7507 loss_thr: 0.7980 loss_db: 0.2925 2022/11/01 13:46:58 - mmengine - INFO - Epoch(train) [80][30/63] lr: 7.9518e-04 eta: 13:57:49 time: 0.5687 data_time: 0.0339 memory: 17620 loss: 2.7663 loss_prob: 1.7069 loss_thr: 0.7781 loss_db: 0.2814 2022/11/01 13:47:01 - mmengine - INFO - Epoch(train) [80][35/63] lr: 7.9518e-04 eta: 13:57:49 time: 0.5662 data_time: 0.0193 memory: 17620 loss: 2.7655 loss_prob: 1.7047 loss_thr: 0.7814 loss_db: 0.2794 2022/11/01 13:47:03 - mmengine - INFO - Epoch(train) [80][40/63] lr: 7.9518e-04 eta: 13:57:20 time: 0.5550 data_time: 0.0056 memory: 17620 loss: 2.9201 loss_prob: 1.8153 loss_thr: 0.7864 loss_db: 0.3184 2022/11/01 13:47:07 - mmengine - INFO - Epoch(train) [80][45/63] lr: 7.9518e-04 eta: 13:57:20 time: 0.5991 data_time: 0.0068 memory: 17620 loss: 3.0795 loss_prob: 1.9360 loss_thr: 0.7940 loss_db: 0.3494 2022/11/01 13:47:09 - mmengine - INFO - Epoch(train) [80][50/63] lr: 7.9518e-04 eta: 13:56:54 time: 0.5829 data_time: 0.0164 memory: 17620 loss: 2.9079 loss_prob: 1.8095 loss_thr: 0.7916 loss_db: 0.3068 2022/11/01 13:47:12 - mmengine - INFO - Epoch(train) [80][55/63] lr: 7.9518e-04 eta: 13:56:54 time: 0.5336 data_time: 0.0226 memory: 17620 loss: 2.8493 loss_prob: 1.7664 loss_thr: 0.7919 loss_db: 0.2910 2022/11/01 13:47:14 - mmengine - INFO - Epoch(train) [80][60/63] lr: 7.9518e-04 eta: 13:56:20 time: 0.5168 data_time: 0.0133 memory: 17620 loss: 3.2505 loss_prob: 2.0513 loss_thr: 0.8455 loss_db: 0.3538 2022/11/01 13:47:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:47:16 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/11/01 13:47:22 - mmengine - INFO - Epoch(val) [80][5/32] eta: 13:56:20 time: 0.5100 data_time: 0.0552 memory: 17620 2022/11/01 13:47:26 - mmengine - INFO - Epoch(val) [80][10/32] eta: 0:00:14 time: 0.6410 data_time: 0.0868 memory: 15725 2022/11/01 13:47:29 - mmengine - INFO - Epoch(val) [80][15/32] eta: 0:00:14 time: 0.6047 data_time: 0.0469 memory: 15725 2022/11/01 13:47:32 - mmengine - INFO - Epoch(val) [80][20/32] eta: 0:00:07 time: 0.6110 data_time: 0.0543 memory: 15725 2022/11/01 13:47:35 - mmengine - INFO - Epoch(val) [80][25/32] eta: 0:00:07 time: 0.6272 data_time: 0.0596 memory: 15725 2022/11/01 13:47:37 - mmengine - INFO - Epoch(val) [80][30/32] eta: 0:00:01 time: 0.5768 data_time: 0.0217 memory: 15725 2022/11/01 13:47:38 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.5835, precision: 0.4441, hmean: 0.5044 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.5835, precision: 0.6042, hmean: 0.5937 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.5739, precision: 0.7207, hmean: 0.6390 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.5262, precision: 0.8274, hmean: 0.6433 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.3274, precision: 0.9103, hmean: 0.4816 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0120, precision: 0.9259, hmean: 0.0238 2022/11/01 13:47:38 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 13:47:38 - mmengine - INFO - Epoch(val) [80][32/32] icdar/precision: 0.8274 icdar/recall: 0.5262 icdar/hmean: 0.6433 2022/11/01 13:47:43 - mmengine - INFO - Epoch(train) [81][5/63] lr: 8.0522e-04 eta: 0:00:01 time: 0.7191 data_time: 0.2204 memory: 17620 loss: 3.1527 loss_prob: 1.9803 loss_thr: 0.8308 loss_db: 0.3416 2022/11/01 13:47:46 - mmengine - INFO - Epoch(train) [81][10/63] lr: 8.0522e-04 eta: 13:55:46 time: 0.7463 data_time: 0.2204 memory: 17620 loss: 3.1437 loss_prob: 1.9659 loss_thr: 0.8395 loss_db: 0.3384 2022/11/01 13:47:48 - mmengine - INFO - Epoch(train) [81][15/63] lr: 8.0522e-04 eta: 13:55:46 time: 0.5308 data_time: 0.0098 memory: 17620 loss: 3.5835 loss_prob: 2.2862 loss_thr: 0.8848 loss_db: 0.4124 2022/11/01 13:47:51 - mmengine - INFO - Epoch(train) [81][20/63] lr: 8.0522e-04 eta: 13:55:20 time: 0.5776 data_time: 0.0109 memory: 17620 loss: 3.9247 loss_prob: 2.5376 loss_thr: 0.8985 loss_db: 0.4885 2022/11/01 13:47:55 - mmengine - INFO - Epoch(train) [81][25/63] lr: 8.0522e-04 eta: 13:55:20 time: 0.6197 data_time: 0.0257 memory: 17620 loss: 3.4682 loss_prob: 2.2104 loss_thr: 0.8463 loss_db: 0.4115 2022/11/01 13:47:58 - mmengine - INFO - Epoch(train) [81][30/63] lr: 8.0522e-04 eta: 13:55:04 time: 0.6457 data_time: 0.0303 memory: 17620 loss: 3.2269 loss_prob: 2.0263 loss_thr: 0.8389 loss_db: 0.3617 2022/11/01 13:48:01 - mmengine - INFO - Epoch(train) [81][35/63] lr: 8.0522e-04 eta: 13:55:04 time: 0.6056 data_time: 0.0113 memory: 17620 loss: 3.4737 loss_prob: 2.1975 loss_thr: 0.8585 loss_db: 0.4177 2022/11/01 13:48:04 - mmengine - INFO - Epoch(train) [81][40/63] lr: 8.0522e-04 eta: 13:54:39 time: 0.5800 data_time: 0.0098 memory: 17620 loss: 3.1862 loss_prob: 2.0051 loss_thr: 0.8204 loss_db: 0.3607 2022/11/01 13:48:07 - mmengine - INFO - Epoch(train) [81][45/63] lr: 8.0522e-04 eta: 13:54:39 time: 0.5891 data_time: 0.0113 memory: 17620 loss: 2.9626 loss_prob: 1.8514 loss_thr: 0.8064 loss_db: 0.3049 2022/11/01 13:48:10 - mmengine - INFO - Epoch(train) [81][50/63] lr: 8.0522e-04 eta: 13:54:15 time: 0.5898 data_time: 0.0200 memory: 17620 loss: 2.9645 loss_prob: 1.8594 loss_thr: 0.7934 loss_db: 0.3117 2022/11/01 13:48:12 - mmengine - INFO - Epoch(train) [81][55/63] lr: 8.0522e-04 eta: 13:54:15 time: 0.5828 data_time: 0.0220 memory: 17620 loss: 3.0625 loss_prob: 1.9299 loss_thr: 0.8021 loss_db: 0.3306 2022/11/01 13:48:16 - mmengine - INFO - Epoch(train) [81][60/63] lr: 8.0522e-04 eta: 13:53:58 time: 0.6370 data_time: 0.0093 memory: 17620 loss: 3.1067 loss_prob: 1.9490 loss_thr: 0.8251 loss_db: 0.3327 2022/11/01 13:48:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:48:23 - mmengine - INFO - Epoch(train) [82][5/63] lr: 8.1526e-04 eta: 13:53:58 time: 0.9031 data_time: 0.2112 memory: 17620 loss: 3.2322 loss_prob: 2.0400 loss_thr: 0.8277 loss_db: 0.3645 2022/11/01 13:48:26 - mmengine - INFO - Epoch(train) [82][10/63] lr: 8.1526e-04 eta: 13:53:42 time: 0.8734 data_time: 0.2100 memory: 17620 loss: 3.2037 loss_prob: 2.0304 loss_thr: 0.8073 loss_db: 0.3660 2022/11/01 13:48:30 - mmengine - INFO - Epoch(train) [82][15/63] lr: 8.1526e-04 eta: 13:53:42 time: 0.6389 data_time: 0.0075 memory: 17620 loss: 3.0054 loss_prob: 1.8798 loss_thr: 0.8130 loss_db: 0.3126 2022/11/01 13:48:33 - mmengine - INFO - Epoch(train) [82][20/63] lr: 8.1526e-04 eta: 13:53:26 time: 0.6426 data_time: 0.0086 memory: 17620 loss: 3.0797 loss_prob: 1.9239 loss_thr: 0.8275 loss_db: 0.3283 2022/11/01 13:48:36 - mmengine - INFO - Epoch(train) [82][25/63] lr: 8.1526e-04 eta: 13:53:26 time: 0.6038 data_time: 0.0180 memory: 17620 loss: 2.9751 loss_prob: 1.8637 loss_thr: 0.7901 loss_db: 0.3212 2022/11/01 13:48:39 - mmengine - INFO - Epoch(train) [82][30/63] lr: 8.1526e-04 eta: 13:53:02 time: 0.5882 data_time: 0.0373 memory: 17620 loss: 3.0149 loss_prob: 1.8898 loss_thr: 0.8013 loss_db: 0.3238 2022/11/01 13:48:42 - mmengine - INFO - Epoch(train) [82][35/63] lr: 8.1526e-04 eta: 13:53:02 time: 0.6031 data_time: 0.0252 memory: 17620 loss: 3.1887 loss_prob: 2.0009 loss_thr: 0.8376 loss_db: 0.3502 2022/11/01 13:48:45 - mmengine - INFO - Epoch(train) [82][40/63] lr: 8.1526e-04 eta: 13:52:43 time: 0.6237 data_time: 0.0048 memory: 17620 loss: 3.1434 loss_prob: 1.9735 loss_thr: 0.8263 loss_db: 0.3435 2022/11/01 13:48:48 - mmengine - INFO - Epoch(train) [82][45/63] lr: 8.1526e-04 eta: 13:52:43 time: 0.6464 data_time: 0.0075 memory: 17620 loss: 3.0762 loss_prob: 1.9503 loss_thr: 0.7838 loss_db: 0.3421 2022/11/01 13:48:51 - mmengine - INFO - Epoch(train) [82][50/63] lr: 8.1526e-04 eta: 13:52:26 time: 0.6395 data_time: 0.0181 memory: 17620 loss: 2.8922 loss_prob: 1.8172 loss_thr: 0.7637 loss_db: 0.3112 2022/11/01 13:48:54 - mmengine - INFO - Epoch(train) [82][55/63] lr: 8.1526e-04 eta: 13:52:26 time: 0.6097 data_time: 0.0248 memory: 17620 loss: 2.7697 loss_prob: 1.7185 loss_thr: 0.7706 loss_db: 0.2806 2022/11/01 13:48:57 - mmengine - INFO - Epoch(train) [82][60/63] lr: 8.1526e-04 eta: 13:52:07 time: 0.6207 data_time: 0.0159 memory: 17620 loss: 2.8309 loss_prob: 1.7487 loss_thr: 0.7958 loss_db: 0.2865 2022/11/01 13:48:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:49:03 - mmengine - INFO - Epoch(train) [83][5/63] lr: 8.2530e-04 eta: 13:52:07 time: 0.7426 data_time: 0.1778 memory: 17620 loss: 2.8729 loss_prob: 1.7932 loss_thr: 0.7745 loss_db: 0.3052 2022/11/01 13:49:07 - mmengine - INFO - Epoch(train) [83][10/63] lr: 8.2530e-04 eta: 13:51:37 time: 0.7646 data_time: 0.1915 memory: 17620 loss: 2.6923 loss_prob: 1.6829 loss_thr: 0.7357 loss_db: 0.2737 2022/11/01 13:49:09 - mmengine - INFO - Epoch(train) [83][15/63] lr: 8.2530e-04 eta: 13:51:37 time: 0.5914 data_time: 0.0199 memory: 17620 loss: 2.7496 loss_prob: 1.7116 loss_thr: 0.7606 loss_db: 0.2774 2022/11/01 13:49:12 - mmengine - INFO - Epoch(train) [83][20/63] lr: 8.2530e-04 eta: 13:51:11 time: 0.5699 data_time: 0.0061 memory: 17620 loss: 2.9297 loss_prob: 1.8170 loss_thr: 0.8109 loss_db: 0.3018 2022/11/01 13:49:15 - mmengine - INFO - Epoch(train) [83][25/63] lr: 8.2530e-04 eta: 13:51:11 time: 0.5720 data_time: 0.0177 memory: 17620 loss: 2.9816 loss_prob: 1.8653 loss_thr: 0.7988 loss_db: 0.3175 2022/11/01 13:49:18 - mmengine - INFO - Epoch(train) [83][30/63] lr: 8.2530e-04 eta: 13:50:47 time: 0.5832 data_time: 0.0309 memory: 17620 loss: 2.9830 loss_prob: 1.8791 loss_thr: 0.7846 loss_db: 0.3192 2022/11/01 13:49:21 - mmengine - INFO - Epoch(train) [83][35/63] lr: 8.2530e-04 eta: 13:50:47 time: 0.5908 data_time: 0.0227 memory: 17620 loss: 2.9796 loss_prob: 1.8715 loss_thr: 0.7896 loss_db: 0.3185 2022/11/01 13:49:24 - mmengine - INFO - Epoch(train) [83][40/63] lr: 8.2530e-04 eta: 13:50:21 time: 0.5698 data_time: 0.0082 memory: 17620 loss: 3.1366 loss_prob: 1.9953 loss_thr: 0.7962 loss_db: 0.3450 2022/11/01 13:49:26 - mmengine - INFO - Epoch(train) [83][45/63] lr: 8.2530e-04 eta: 13:50:21 time: 0.5441 data_time: 0.0043 memory: 17620 loss: 3.4108 loss_prob: 2.1800 loss_thr: 0.8296 loss_db: 0.4012 2022/11/01 13:49:29 - mmengine - INFO - Epoch(train) [83][50/63] lr: 8.2530e-04 eta: 13:49:52 time: 0.5448 data_time: 0.0130 memory: 17620 loss: 3.3310 loss_prob: 2.1130 loss_thr: 0.8285 loss_db: 0.3895 2022/11/01 13:49:32 - mmengine - INFO - Epoch(train) [83][55/63] lr: 8.2530e-04 eta: 13:49:52 time: 0.5704 data_time: 0.0238 memory: 17620 loss: 3.0989 loss_prob: 1.9542 loss_thr: 0.8016 loss_db: 0.3430 2022/11/01 13:49:35 - mmengine - INFO - Epoch(train) [83][60/63] lr: 8.2530e-04 eta: 13:49:26 time: 0.5648 data_time: 0.0155 memory: 17620 loss: 3.0814 loss_prob: 1.9259 loss_thr: 0.8149 loss_db: 0.3406 2022/11/01 13:49:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:49:41 - mmengine - INFO - Epoch(train) [84][5/63] lr: 8.3534e-04 eta: 13:49:26 time: 0.7567 data_time: 0.1692 memory: 17620 loss: 2.8519 loss_prob: 1.7649 loss_thr: 0.7956 loss_db: 0.2913 2022/11/01 13:49:44 - mmengine - INFO - Epoch(train) [84][10/63] lr: 8.3534e-04 eta: 13:48:57 time: 0.7731 data_time: 0.1696 memory: 17620 loss: 2.8954 loss_prob: 1.7898 loss_thr: 0.8120 loss_db: 0.2935 2022/11/01 13:49:47 - mmengine - INFO - Epoch(train) [84][15/63] lr: 8.3534e-04 eta: 13:48:57 time: 0.5531 data_time: 0.0058 memory: 17620 loss: 2.9930 loss_prob: 1.8613 loss_thr: 0.8103 loss_db: 0.3214 2022/11/01 13:49:50 - mmengine - INFO - Epoch(train) [84][20/63] lr: 8.3534e-04 eta: 13:48:28 time: 0.5471 data_time: 0.0067 memory: 17620 loss: 2.8074 loss_prob: 1.7474 loss_thr: 0.7584 loss_db: 0.3017 2022/11/01 13:49:53 - mmengine - INFO - Epoch(train) [84][25/63] lr: 8.3534e-04 eta: 13:48:28 time: 0.5533 data_time: 0.0186 memory: 17620 loss: 2.7261 loss_prob: 1.6813 loss_thr: 0.7652 loss_db: 0.2796 2022/11/01 13:49:56 - mmengine - INFO - Epoch(train) [84][30/63] lr: 8.3534e-04 eta: 13:48:05 time: 0.5819 data_time: 0.0443 memory: 17620 loss: 3.0696 loss_prob: 1.9095 loss_thr: 0.8308 loss_db: 0.3293 2022/11/01 13:49:58 - mmengine - INFO - Epoch(train) [84][35/63] lr: 8.3534e-04 eta: 13:48:05 time: 0.5818 data_time: 0.0316 memory: 17620 loss: 3.1592 loss_prob: 1.9785 loss_thr: 0.8333 loss_db: 0.3475 2022/11/01 13:50:01 - mmengine - INFO - Epoch(train) [84][40/63] lr: 8.3534e-04 eta: 13:47:35 time: 0.5404 data_time: 0.0060 memory: 17620 loss: 2.9201 loss_prob: 1.8224 loss_thr: 0.7926 loss_db: 0.3051 2022/11/01 13:50:04 - mmengine - INFO - Epoch(train) [84][45/63] lr: 8.3534e-04 eta: 13:47:35 time: 0.5337 data_time: 0.0070 memory: 17620 loss: 2.7827 loss_prob: 1.7236 loss_thr: 0.7773 loss_db: 0.2818 2022/11/01 13:50:07 - mmengine - INFO - Epoch(train) [84][50/63] lr: 8.3534e-04 eta: 13:47:09 time: 0.5619 data_time: 0.0129 memory: 17620 loss: 2.7884 loss_prob: 1.7255 loss_thr: 0.7774 loss_db: 0.2855 2022/11/01 13:50:09 - mmengine - INFO - Epoch(train) [84][55/63] lr: 8.3534e-04 eta: 13:47:09 time: 0.5673 data_time: 0.0229 memory: 17620 loss: 2.7077 loss_prob: 1.6864 loss_thr: 0.7484 loss_db: 0.2729 2022/11/01 13:50:12 - mmengine - INFO - Epoch(train) [84][60/63] lr: 8.3534e-04 eta: 13:46:43 time: 0.5634 data_time: 0.0156 memory: 17620 loss: 2.5655 loss_prob: 1.5793 loss_thr: 0.7368 loss_db: 0.2494 2022/11/01 13:50:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:50:19 - mmengine - INFO - Epoch(train) [85][5/63] lr: 8.4538e-04 eta: 13:46:43 time: 0.8231 data_time: 0.1818 memory: 17620 loss: 2.8382 loss_prob: 1.7628 loss_thr: 0.7819 loss_db: 0.2935 2022/11/01 13:50:23 - mmengine - INFO - Epoch(train) [85][10/63] lr: 8.4538e-04 eta: 13:46:32 time: 0.9008 data_time: 0.1850 memory: 17620 loss: 3.0971 loss_prob: 1.9766 loss_thr: 0.7798 loss_db: 0.3407 2022/11/01 13:50:26 - mmengine - INFO - Epoch(train) [85][15/63] lr: 8.4538e-04 eta: 13:46:32 time: 0.6530 data_time: 0.0078 memory: 17620 loss: 3.1091 loss_prob: 1.9902 loss_thr: 0.7750 loss_db: 0.3439 2022/11/01 13:50:29 - mmengine - INFO - Epoch(train) [85][20/63] lr: 8.4538e-04 eta: 13:46:13 time: 0.6158 data_time: 0.0076 memory: 17620 loss: 3.0702 loss_prob: 1.9592 loss_thr: 0.7762 loss_db: 0.3348 2022/11/01 13:50:32 - mmengine - INFO - Epoch(train) [85][25/63] lr: 8.4538e-04 eta: 13:46:13 time: 0.6035 data_time: 0.0221 memory: 17620 loss: 3.0210 loss_prob: 1.9128 loss_thr: 0.7853 loss_db: 0.3229 2022/11/01 13:50:35 - mmengine - INFO - Epoch(train) [85][30/63] lr: 8.4538e-04 eta: 13:45:50 time: 0.5889 data_time: 0.0344 memory: 17620 loss: 2.9400 loss_prob: 1.8333 loss_thr: 0.7999 loss_db: 0.3068 2022/11/01 13:50:38 - mmengine - INFO - Epoch(train) [85][35/63] lr: 8.4538e-04 eta: 13:45:50 time: 0.5729 data_time: 0.0220 memory: 17620 loss: 2.8102 loss_prob: 1.7405 loss_thr: 0.7797 loss_db: 0.2899 2022/11/01 13:50:41 - mmengine - INFO - Epoch(train) [85][40/63] lr: 8.4538e-04 eta: 13:45:31 time: 0.6139 data_time: 0.0069 memory: 17620 loss: 2.9699 loss_prob: 1.8467 loss_thr: 0.8007 loss_db: 0.3225 2022/11/01 13:50:44 - mmengine - INFO - Epoch(train) [85][45/63] lr: 8.4538e-04 eta: 13:45:31 time: 0.6789 data_time: 0.0063 memory: 17620 loss: 3.1385 loss_prob: 1.9577 loss_thr: 0.8326 loss_db: 0.3482 2022/11/01 13:50:47 - mmengine - INFO - Epoch(train) [85][50/63] lr: 8.4538e-04 eta: 13:45:17 time: 0.6471 data_time: 0.0182 memory: 17620 loss: 3.3369 loss_prob: 2.1500 loss_thr: 0.8179 loss_db: 0.3689 2022/11/01 13:50:51 - mmengine - INFO - Epoch(train) [85][55/63] lr: 8.4538e-04 eta: 13:45:17 time: 0.6277 data_time: 0.0242 memory: 17620 loss: 3.2806 loss_prob: 2.1265 loss_thr: 0.7997 loss_db: 0.3544 2022/11/01 13:50:54 - mmengine - INFO - Epoch(train) [85][60/63] lr: 8.4538e-04 eta: 13:45:04 time: 0.6612 data_time: 0.0126 memory: 17620 loss: 2.8659 loss_prob: 1.7808 loss_thr: 0.7985 loss_db: 0.2867 2022/11/01 13:50:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:51:01 - mmengine - INFO - Epoch(train) [86][5/63] lr: 8.5542e-04 eta: 13:45:04 time: 0.7897 data_time: 0.1935 memory: 17620 loss: 2.8649 loss_prob: 1.7794 loss_thr: 0.7897 loss_db: 0.2959 2022/11/01 13:51:03 - mmengine - INFO - Epoch(train) [86][10/63] lr: 8.5542e-04 eta: 13:44:37 time: 0.7801 data_time: 0.1958 memory: 17620 loss: 2.8771 loss_prob: 1.7891 loss_thr: 0.7883 loss_db: 0.2997 2022/11/01 13:51:07 - mmengine - INFO - Epoch(train) [86][15/63] lr: 8.5542e-04 eta: 13:44:37 time: 0.5994 data_time: 0.0171 memory: 17620 loss: 2.8315 loss_prob: 1.7661 loss_thr: 0.7650 loss_db: 0.3004 2022/11/01 13:51:09 - mmengine - INFO - Epoch(train) [86][20/63] lr: 8.5542e-04 eta: 13:44:19 time: 0.6202 data_time: 0.0145 memory: 17620 loss: 2.9778 loss_prob: 1.8631 loss_thr: 0.7912 loss_db: 0.3234 2022/11/01 13:51:13 - mmengine - INFO - Epoch(train) [86][25/63] lr: 8.5542e-04 eta: 13:44:19 time: 0.6108 data_time: 0.0228 memory: 17620 loss: 2.9126 loss_prob: 1.8209 loss_thr: 0.7853 loss_db: 0.3064 2022/11/01 13:51:15 - mmengine - INFO - Epoch(train) [86][30/63] lr: 8.5542e-04 eta: 13:43:58 time: 0.5974 data_time: 0.0238 memory: 17620 loss: 2.9211 loss_prob: 1.8301 loss_thr: 0.7851 loss_db: 0.3059 2022/11/01 13:51:18 - mmengine - INFO - Epoch(train) [86][35/63] lr: 8.5542e-04 eta: 13:43:58 time: 0.5524 data_time: 0.0143 memory: 17620 loss: 2.9011 loss_prob: 1.8143 loss_thr: 0.7865 loss_db: 0.3003 2022/11/01 13:51:21 - mmengine - INFO - Epoch(train) [86][40/63] lr: 8.5542e-04 eta: 13:43:30 time: 0.5394 data_time: 0.0131 memory: 17620 loss: 2.9825 loss_prob: 1.8871 loss_thr: 0.7727 loss_db: 0.3227 2022/11/01 13:51:24 - mmengine - INFO - Epoch(train) [86][45/63] lr: 8.5542e-04 eta: 13:43:30 time: 0.5610 data_time: 0.0059 memory: 17620 loss: 2.9952 loss_prob: 1.8965 loss_thr: 0.7701 loss_db: 0.3287 2022/11/01 13:51:27 - mmengine - INFO - Epoch(train) [86][50/63] lr: 8.5542e-04 eta: 13:43:08 time: 0.5959 data_time: 0.0212 memory: 17620 loss: 2.7952 loss_prob: 1.7415 loss_thr: 0.7655 loss_db: 0.2881 2022/11/01 13:51:30 - mmengine - INFO - Epoch(train) [86][55/63] lr: 8.5542e-04 eta: 13:43:08 time: 0.5805 data_time: 0.0216 memory: 17620 loss: 2.7691 loss_prob: 1.7101 loss_thr: 0.7756 loss_db: 0.2833 2022/11/01 13:51:33 - mmengine - INFO - Epoch(train) [86][60/63] lr: 8.5542e-04 eta: 13:42:45 time: 0.5790 data_time: 0.0093 memory: 17620 loss: 2.8663 loss_prob: 1.7678 loss_thr: 0.8016 loss_db: 0.2970 2022/11/01 13:51:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:51:39 - mmengine - INFO - Epoch(train) [87][5/63] lr: 8.6546e-04 eta: 13:42:45 time: 0.7182 data_time: 0.1773 memory: 17620 loss: 2.8872 loss_prob: 1.7911 loss_thr: 0.7961 loss_db: 0.3000 2022/11/01 13:51:41 - mmengine - INFO - Epoch(train) [87][10/63] lr: 8.6546e-04 eta: 13:42:14 time: 0.7466 data_time: 0.1847 memory: 17620 loss: 2.9130 loss_prob: 1.8108 loss_thr: 0.7990 loss_db: 0.3032 2022/11/01 13:51:44 - mmengine - INFO - Epoch(train) [87][15/63] lr: 8.6546e-04 eta: 13:42:14 time: 0.5727 data_time: 0.0152 memory: 17620 loss: 2.8043 loss_prob: 1.7260 loss_thr: 0.7914 loss_db: 0.2868 2022/11/01 13:51:47 - mmengine - INFO - Epoch(train) [87][20/63] lr: 8.6546e-04 eta: 13:41:48 time: 0.5557 data_time: 0.0074 memory: 17620 loss: 2.8113 loss_prob: 1.7411 loss_thr: 0.7780 loss_db: 0.2921 2022/11/01 13:51:50 - mmengine - INFO - Epoch(train) [87][25/63] lr: 8.6546e-04 eta: 13:41:48 time: 0.5367 data_time: 0.0173 memory: 17620 loss: 2.9178 loss_prob: 1.8192 loss_thr: 0.7919 loss_db: 0.3067 2022/11/01 13:51:53 - mmengine - INFO - Epoch(train) [87][30/63] lr: 8.6546e-04 eta: 13:41:23 time: 0.5629 data_time: 0.0235 memory: 17620 loss: 3.0494 loss_prob: 1.9239 loss_thr: 0.7846 loss_db: 0.3408 2022/11/01 13:51:56 - mmengine - INFO - Epoch(train) [87][35/63] lr: 8.6546e-04 eta: 13:41:23 time: 0.6024 data_time: 0.0213 memory: 17620 loss: 3.0601 loss_prob: 1.9219 loss_thr: 0.7956 loss_db: 0.3425 2022/11/01 13:51:59 - mmengine - INFO - Epoch(train) [87][40/63] lr: 8.6546e-04 eta: 13:41:03 time: 0.6005 data_time: 0.0127 memory: 17620 loss: 2.9735 loss_prob: 1.8529 loss_thr: 0.8041 loss_db: 0.3165 2022/11/01 13:52:02 - mmengine - INFO - Epoch(train) [87][45/63] lr: 8.6546e-04 eta: 13:41:03 time: 0.5912 data_time: 0.0062 memory: 17620 loss: 3.0850 loss_prob: 1.9504 loss_thr: 0.7934 loss_db: 0.3412 2022/11/01 13:52:04 - mmengine - INFO - Epoch(train) [87][50/63] lr: 8.6546e-04 eta: 13:40:42 time: 0.5903 data_time: 0.0198 memory: 17620 loss: 2.9881 loss_prob: 1.8677 loss_thr: 0.8001 loss_db: 0.3203 2022/11/01 13:52:07 - mmengine - INFO - Epoch(train) [87][55/63] lr: 8.6546e-04 eta: 13:40:42 time: 0.5523 data_time: 0.0183 memory: 17620 loss: 2.9873 loss_prob: 1.8610 loss_thr: 0.8113 loss_db: 0.3150 2022/11/01 13:52:10 - mmengine - INFO - Epoch(train) [87][60/63] lr: 8.6546e-04 eta: 13:40:16 time: 0.5530 data_time: 0.0077 memory: 17620 loss: 2.9228 loss_prob: 1.8244 loss_thr: 0.7904 loss_db: 0.3080 2022/11/01 13:52:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:52:16 - mmengine - INFO - Epoch(train) [88][5/63] lr: 8.7550e-04 eta: 13:40:16 time: 0.6701 data_time: 0.1573 memory: 17620 loss: 2.9113 loss_prob: 1.8266 loss_thr: 0.7693 loss_db: 0.3154 2022/11/01 13:52:19 - mmengine - INFO - Epoch(train) [88][10/63] lr: 8.7550e-04 eta: 13:39:42 time: 0.7180 data_time: 0.1645 memory: 17620 loss: 2.8809 loss_prob: 1.8095 loss_thr: 0.7586 loss_db: 0.3128 2022/11/01 13:52:21 - mmengine - INFO - Epoch(train) [88][15/63] lr: 8.7550e-04 eta: 13:39:42 time: 0.5758 data_time: 0.0154 memory: 17620 loss: 2.9171 loss_prob: 1.8147 loss_thr: 0.7915 loss_db: 0.3109 2022/11/01 13:52:24 - mmengine - INFO - Epoch(train) [88][20/63] lr: 8.7550e-04 eta: 13:39:18 time: 0.5701 data_time: 0.0093 memory: 17620 loss: 2.8801 loss_prob: 1.7776 loss_thr: 0.8029 loss_db: 0.2996 2022/11/01 13:52:27 - mmengine - INFO - Epoch(train) [88][25/63] lr: 8.7550e-04 eta: 13:39:18 time: 0.5696 data_time: 0.0083 memory: 17620 loss: 2.9920 loss_prob: 1.8557 loss_thr: 0.8101 loss_db: 0.3261 2022/11/01 13:52:30 - mmengine - INFO - Epoch(train) [88][30/63] lr: 8.7550e-04 eta: 13:38:58 time: 0.5983 data_time: 0.0260 memory: 17620 loss: 3.0204 loss_prob: 1.8752 loss_thr: 0.8192 loss_db: 0.3261 2022/11/01 13:52:33 - mmengine - INFO - Epoch(train) [88][35/63] lr: 8.7550e-04 eta: 13:38:58 time: 0.5869 data_time: 0.0292 memory: 17620 loss: 2.7810 loss_prob: 1.7279 loss_thr: 0.7697 loss_db: 0.2834 2022/11/01 13:52:36 - mmengine - INFO - Epoch(train) [88][40/63] lr: 8.7550e-04 eta: 13:38:31 time: 0.5446 data_time: 0.0160 memory: 17620 loss: 2.6279 loss_prob: 1.6154 loss_thr: 0.7530 loss_db: 0.2595 2022/11/01 13:52:39 - mmengine - INFO - Epoch(train) [88][45/63] lr: 8.7550e-04 eta: 13:38:31 time: 0.6477 data_time: 0.0120 memory: 17620 loss: 2.5853 loss_prob: 1.5806 loss_thr: 0.7524 loss_db: 0.2523 2022/11/01 13:52:43 - mmengine - INFO - Epoch(train) [88][50/63] lr: 8.7550e-04 eta: 13:38:24 time: 0.7015 data_time: 0.0164 memory: 17620 loss: 2.6455 loss_prob: 1.6206 loss_thr: 0.7595 loss_db: 0.2654 2022/11/01 13:52:45 - mmengine - INFO - Epoch(train) [88][55/63] lr: 8.7550e-04 eta: 13:38:24 time: 0.5992 data_time: 0.0206 memory: 17620 loss: 2.7118 loss_prob: 1.6727 loss_thr: 0.7638 loss_db: 0.2753 2022/11/01 13:52:49 - mmengine - INFO - Epoch(train) [88][60/63] lr: 8.7550e-04 eta: 13:38:06 time: 0.6106 data_time: 0.0119 memory: 17620 loss: 2.5961 loss_prob: 1.5966 loss_thr: 0.7406 loss_db: 0.2589 2022/11/01 13:52:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:52:55 - mmengine - INFO - Epoch(train) [89][5/63] lr: 8.8554e-04 eta: 13:38:06 time: 0.7853 data_time: 0.1960 memory: 17620 loss: 2.6849 loss_prob: 1.6565 loss_thr: 0.7581 loss_db: 0.2703 2022/11/01 13:52:59 - mmengine - INFO - Epoch(train) [89][10/63] lr: 8.8554e-04 eta: 13:37:49 time: 0.8495 data_time: 0.2019 memory: 17620 loss: 2.9141 loss_prob: 1.8136 loss_thr: 0.7918 loss_db: 0.3086 2022/11/01 13:53:01 - mmengine - INFO - Epoch(train) [89][15/63] lr: 8.8554e-04 eta: 13:37:49 time: 0.6058 data_time: 0.0138 memory: 17620 loss: 2.7855 loss_prob: 1.7189 loss_thr: 0.7774 loss_db: 0.2891 2022/11/01 13:53:04 - mmengine - INFO - Epoch(train) [89][20/63] lr: 8.8554e-04 eta: 13:37:24 time: 0.5588 data_time: 0.0050 memory: 17620 loss: 2.6791 loss_prob: 1.6517 loss_thr: 0.7573 loss_db: 0.2701 2022/11/01 13:53:08 - mmengine - INFO - Epoch(train) [89][25/63] lr: 8.8554e-04 eta: 13:37:24 time: 0.6309 data_time: 0.0307 memory: 17620 loss: 2.6689 loss_prob: 1.6415 loss_thr: 0.7588 loss_db: 0.2685 2022/11/01 13:53:11 - mmengine - INFO - Epoch(train) [89][30/63] lr: 8.8554e-04 eta: 13:37:09 time: 0.6356 data_time: 0.0341 memory: 17620 loss: 2.5771 loss_prob: 1.5667 loss_thr: 0.7584 loss_db: 0.2521 2022/11/01 13:53:15 - mmengine - INFO - Epoch(train) [89][35/63] lr: 8.8554e-04 eta: 13:37:09 time: 0.6748 data_time: 0.0149 memory: 17620 loss: 2.7389 loss_prob: 1.6754 loss_thr: 0.7833 loss_db: 0.2802 2022/11/01 13:53:18 - mmengine - INFO - Epoch(train) [89][40/63] lr: 8.8554e-04 eta: 13:37:03 time: 0.7105 data_time: 0.0115 memory: 17620 loss: 2.9123 loss_prob: 1.8140 loss_thr: 0.7870 loss_db: 0.3112 2022/11/01 13:53:21 - mmengine - INFO - Epoch(train) [89][45/63] lr: 8.8554e-04 eta: 13:37:03 time: 0.6276 data_time: 0.0049 memory: 17620 loss: 2.8188 loss_prob: 1.7641 loss_thr: 0.7596 loss_db: 0.2951 2022/11/01 13:53:24 - mmengine - INFO - Epoch(train) [89][50/63] lr: 8.8554e-04 eta: 13:36:42 time: 0.5833 data_time: 0.0167 memory: 17620 loss: 2.7235 loss_prob: 1.6941 loss_thr: 0.7495 loss_db: 0.2799 2022/11/01 13:53:26 - mmengine - INFO - Epoch(train) [89][55/63] lr: 8.8554e-04 eta: 13:36:42 time: 0.5672 data_time: 0.0207 memory: 17620 loss: 2.7717 loss_prob: 1.7275 loss_thr: 0.7569 loss_db: 0.2873 2022/11/01 13:53:30 - mmengine - INFO - Epoch(train) [89][60/63] lr: 8.8554e-04 eta: 13:36:20 time: 0.5808 data_time: 0.0107 memory: 17620 loss: 2.9179 loss_prob: 1.8278 loss_thr: 0.7774 loss_db: 0.3127 2022/11/01 13:53:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:53:36 - mmengine - INFO - Epoch(train) [90][5/63] lr: 8.9558e-04 eta: 13:36:20 time: 0.8118 data_time: 0.2378 memory: 17620 loss: 2.7622 loss_prob: 1.6978 loss_thr: 0.7779 loss_db: 0.2866 2022/11/01 13:53:40 - mmengine - INFO - Epoch(train) [90][10/63] lr: 8.9558e-04 eta: 13:36:08 time: 0.8897 data_time: 0.2330 memory: 17620 loss: 2.8005 loss_prob: 1.7322 loss_thr: 0.7778 loss_db: 0.2905 2022/11/01 13:53:43 - mmengine - INFO - Epoch(train) [90][15/63] lr: 8.9558e-04 eta: 13:36:08 time: 0.6265 data_time: 0.0049 memory: 17620 loss: 2.7016 loss_prob: 1.6552 loss_thr: 0.7751 loss_db: 0.2714 2022/11/01 13:53:46 - mmengine - INFO - Epoch(train) [90][20/63] lr: 8.9558e-04 eta: 13:35:45 time: 0.5745 data_time: 0.0071 memory: 17620 loss: 2.5044 loss_prob: 1.5235 loss_thr: 0.7360 loss_db: 0.2449 2022/11/01 13:53:48 - mmengine - INFO - Epoch(train) [90][25/63] lr: 8.9558e-04 eta: 13:35:45 time: 0.5697 data_time: 0.0202 memory: 17620 loss: 2.6035 loss_prob: 1.6226 loss_thr: 0.7161 loss_db: 0.2649 2022/11/01 13:53:51 - mmengine - INFO - Epoch(train) [90][30/63] lr: 8.9558e-04 eta: 13:35:23 time: 0.5784 data_time: 0.0461 memory: 17620 loss: 2.9069 loss_prob: 1.8330 loss_thr: 0.7678 loss_db: 0.3061 2022/11/01 13:53:54 - mmengine - INFO - Epoch(train) [90][35/63] lr: 8.9558e-04 eta: 13:35:23 time: 0.5650 data_time: 0.0330 memory: 17620 loss: 2.9149 loss_prob: 1.8177 loss_thr: 0.7902 loss_db: 0.3070 2022/11/01 13:53:57 - mmengine - INFO - Epoch(train) [90][40/63] lr: 8.9558e-04 eta: 13:34:54 time: 0.5169 data_time: 0.0048 memory: 17620 loss: 2.8503 loss_prob: 1.7769 loss_thr: 0.7713 loss_db: 0.3020 2022/11/01 13:53:59 - mmengine - INFO - Epoch(train) [90][45/63] lr: 8.9558e-04 eta: 13:34:54 time: 0.5230 data_time: 0.0049 memory: 17620 loss: 2.8503 loss_prob: 1.7846 loss_thr: 0.7639 loss_db: 0.3017 2022/11/01 13:54:02 - mmengine - INFO - Epoch(train) [90][50/63] lr: 8.9558e-04 eta: 13:34:28 time: 0.5500 data_time: 0.0216 memory: 17620 loss: 2.8416 loss_prob: 1.7607 loss_thr: 0.7842 loss_db: 0.2968 2022/11/01 13:54:05 - mmengine - INFO - Epoch(train) [90][55/63] lr: 8.9558e-04 eta: 13:34:28 time: 0.5784 data_time: 0.0226 memory: 17620 loss: 3.0446 loss_prob: 1.8956 loss_thr: 0.8226 loss_db: 0.3264 2022/11/01 13:54:08 - mmengine - INFO - Epoch(train) [90][60/63] lr: 8.9558e-04 eta: 13:34:03 time: 0.5524 data_time: 0.0062 memory: 17620 loss: 3.1407 loss_prob: 1.9747 loss_thr: 0.8216 loss_db: 0.3445 2022/11/01 13:54:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:54:14 - mmengine - INFO - Epoch(train) [91][5/63] lr: 9.0562e-04 eta: 13:34:03 time: 0.7236 data_time: 0.2037 memory: 17620 loss: 3.0047 loss_prob: 1.8882 loss_thr: 0.7932 loss_db: 0.3232 2022/11/01 13:54:17 - mmengine - INFO - Epoch(train) [91][10/63] lr: 9.0562e-04 eta: 13:33:35 time: 0.7485 data_time: 0.2058 memory: 17620 loss: 3.1590 loss_prob: 1.9968 loss_thr: 0.8136 loss_db: 0.3486 2022/11/01 13:54:19 - mmengine - INFO - Epoch(train) [91][15/63] lr: 9.0562e-04 eta: 13:33:35 time: 0.5297 data_time: 0.0076 memory: 17620 loss: 3.2517 loss_prob: 2.0701 loss_thr: 0.8127 loss_db: 0.3688 2022/11/01 13:54:22 - mmengine - INFO - Epoch(train) [91][20/63] lr: 9.0562e-04 eta: 13:33:06 time: 0.5220 data_time: 0.0054 memory: 17620 loss: 3.2315 loss_prob: 2.0632 loss_thr: 0.8016 loss_db: 0.3667 2022/11/01 13:54:25 - mmengine - INFO - Epoch(train) [91][25/63] lr: 9.0562e-04 eta: 13:33:06 time: 0.5542 data_time: 0.0331 memory: 17620 loss: 3.1306 loss_prob: 1.9805 loss_thr: 0.8069 loss_db: 0.3433 2022/11/01 13:54:28 - mmengine - INFO - Epoch(train) [91][30/63] lr: 9.0562e-04 eta: 13:32:45 time: 0.5847 data_time: 0.0335 memory: 17620 loss: 3.0296 loss_prob: 1.9084 loss_thr: 0.7941 loss_db: 0.3271 2022/11/01 13:54:30 - mmengine - INFO - Epoch(train) [91][35/63] lr: 9.0562e-04 eta: 13:32:45 time: 0.5694 data_time: 0.0080 memory: 17620 loss: 2.8183 loss_prob: 1.7684 loss_thr: 0.7594 loss_db: 0.2905 2022/11/01 13:54:33 - mmengine - INFO - Epoch(train) [91][40/63] lr: 9.0562e-04 eta: 13:32:19 time: 0.5381 data_time: 0.0114 memory: 17620 loss: 2.7033 loss_prob: 1.6884 loss_thr: 0.7431 loss_db: 0.2718 2022/11/01 13:54:36 - mmengine - INFO - Epoch(train) [91][45/63] lr: 9.0562e-04 eta: 13:32:19 time: 0.5232 data_time: 0.0083 memory: 17620 loss: 2.9511 loss_prob: 1.8657 loss_thr: 0.7697 loss_db: 0.3157 2022/11/01 13:54:39 - mmengine - INFO - Epoch(train) [91][50/63] lr: 9.0562e-04 eta: 13:31:55 time: 0.5610 data_time: 0.0183 memory: 17620 loss: 3.1391 loss_prob: 1.9877 loss_thr: 0.8017 loss_db: 0.3497 2022/11/01 13:54:41 - mmengine - INFO - Epoch(train) [91][55/63] lr: 9.0562e-04 eta: 13:31:55 time: 0.5727 data_time: 0.0189 memory: 17620 loss: 3.0661 loss_prob: 1.9092 loss_thr: 0.8191 loss_db: 0.3378 2022/11/01 13:54:44 - mmengine - INFO - Epoch(train) [91][60/63] lr: 9.0562e-04 eta: 13:31:30 time: 0.5496 data_time: 0.0082 memory: 17620 loss: 2.9184 loss_prob: 1.7950 loss_thr: 0.8152 loss_db: 0.3082 2022/11/01 13:54:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:54:50 - mmengine - INFO - Epoch(train) [92][5/63] lr: 9.1566e-04 eta: 13:31:30 time: 0.7307 data_time: 0.2194 memory: 17620 loss: 2.7189 loss_prob: 1.6645 loss_thr: 0.7763 loss_db: 0.2781 2022/11/01 13:54:53 - mmengine - INFO - Epoch(train) [92][10/63] lr: 9.1566e-04 eta: 13:31:04 time: 0.7652 data_time: 0.2161 memory: 17620 loss: 2.6477 loss_prob: 1.6056 loss_thr: 0.7757 loss_db: 0.2665 2022/11/01 13:54:56 - mmengine - INFO - Epoch(train) [92][15/63] lr: 9.1566e-04 eta: 13:31:04 time: 0.5481 data_time: 0.0060 memory: 17620 loss: 2.6031 loss_prob: 1.5814 loss_thr: 0.7633 loss_db: 0.2584 2022/11/01 13:54:58 - mmengine - INFO - Epoch(train) [92][20/63] lr: 9.1566e-04 eta: 13:30:37 time: 0.5281 data_time: 0.0062 memory: 17620 loss: 2.7336 loss_prob: 1.6927 loss_thr: 0.7639 loss_db: 0.2770 2022/11/01 13:55:02 - mmengine - INFO - Epoch(train) [92][25/63] lr: 9.1566e-04 eta: 13:30:37 time: 0.6492 data_time: 0.0281 memory: 17620 loss: 2.9588 loss_prob: 1.8541 loss_thr: 0.7903 loss_db: 0.3145 2022/11/01 13:55:06 - mmengine - INFO - Epoch(train) [92][30/63] lr: 9.1566e-04 eta: 13:30:33 time: 0.7208 data_time: 0.0376 memory: 17620 loss: 2.9175 loss_prob: 1.8181 loss_thr: 0.7877 loss_db: 0.3116 2022/11/01 13:55:09 - mmengine - INFO - Epoch(train) [92][35/63] lr: 9.1566e-04 eta: 13:30:33 time: 0.6482 data_time: 0.0145 memory: 17620 loss: 2.6656 loss_prob: 1.6445 loss_thr: 0.7508 loss_db: 0.2702 2022/11/01 13:55:12 - mmengine - INFO - Epoch(train) [92][40/63] lr: 9.1566e-04 eta: 13:30:19 time: 0.6411 data_time: 0.0075 memory: 17620 loss: 2.8610 loss_prob: 1.7866 loss_thr: 0.7733 loss_db: 0.3011 2022/11/01 13:55:15 - mmengine - INFO - Epoch(train) [92][45/63] lr: 9.1566e-04 eta: 13:30:19 time: 0.6337 data_time: 0.0094 memory: 17620 loss: 2.9392 loss_prob: 1.8545 loss_thr: 0.7663 loss_db: 0.3183 2022/11/01 13:55:18 - mmengine - INFO - Epoch(train) [92][50/63] lr: 9.1566e-04 eta: 13:30:02 time: 0.6159 data_time: 0.0234 memory: 17620 loss: 3.2249 loss_prob: 2.0573 loss_thr: 0.7778 loss_db: 0.3898 2022/11/01 13:55:21 - mmengine - INFO - Epoch(train) [92][55/63] lr: 9.1566e-04 eta: 13:30:02 time: 0.5956 data_time: 0.0220 memory: 17620 loss: 3.3893 loss_prob: 2.1746 loss_thr: 0.7918 loss_db: 0.4230 2022/11/01 13:55:24 - mmengine - INFO - Epoch(train) [92][60/63] lr: 9.1566e-04 eta: 13:29:46 time: 0.6180 data_time: 0.0051 memory: 17620 loss: 2.8938 loss_prob: 1.8449 loss_thr: 0.7266 loss_db: 0.3223 2022/11/01 13:55:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:55:31 - mmengine - INFO - Epoch(train) [93][5/63] lr: 9.2570e-04 eta: 13:29:46 time: 0.7424 data_time: 0.2169 memory: 17620 loss: 2.7647 loss_prob: 1.7256 loss_thr: 0.7490 loss_db: 0.2901 2022/11/01 13:55:34 - mmengine - INFO - Epoch(train) [93][10/63] lr: 9.2570e-04 eta: 13:29:31 time: 0.8533 data_time: 0.2211 memory: 17620 loss: 2.6787 loss_prob: 1.6555 loss_thr: 0.7494 loss_db: 0.2739 2022/11/01 13:55:37 - mmengine - INFO - Epoch(train) [93][15/63] lr: 9.2570e-04 eta: 13:29:31 time: 0.6583 data_time: 0.0115 memory: 17620 loss: 2.8278 loss_prob: 1.7515 loss_thr: 0.7875 loss_db: 0.2888 2022/11/01 13:55:40 - mmengine - INFO - Epoch(train) [93][20/63] lr: 9.2570e-04 eta: 13:29:12 time: 0.5950 data_time: 0.0089 memory: 17620 loss: 2.7815 loss_prob: 1.7276 loss_thr: 0.7699 loss_db: 0.2840 2022/11/01 13:55:43 - mmengine - INFO - Epoch(train) [93][25/63] lr: 9.2570e-04 eta: 13:29:12 time: 0.6156 data_time: 0.0318 memory: 17620 loss: 2.6412 loss_prob: 1.6310 loss_thr: 0.7451 loss_db: 0.2650 2022/11/01 13:55:47 - mmengine - INFO - Epoch(train) [93][30/63] lr: 9.2570e-04 eta: 13:28:58 time: 0.6414 data_time: 0.0307 memory: 17620 loss: 2.7603 loss_prob: 1.7194 loss_thr: 0.7620 loss_db: 0.2789 2022/11/01 13:55:50 - mmengine - INFO - Epoch(train) [93][35/63] lr: 9.2570e-04 eta: 13:28:58 time: 0.6074 data_time: 0.0053 memory: 17620 loss: 3.0534 loss_prob: 1.9481 loss_thr: 0.7757 loss_db: 0.3297 2022/11/01 13:55:52 - mmengine - INFO - Epoch(train) [93][40/63] lr: 9.2570e-04 eta: 13:28:34 time: 0.5510 data_time: 0.0070 memory: 17620 loss: 3.0081 loss_prob: 1.9217 loss_thr: 0.7614 loss_db: 0.3250 2022/11/01 13:55:55 - mmengine - INFO - Epoch(train) [93][45/63] lr: 9.2570e-04 eta: 13:28:34 time: 0.5578 data_time: 0.0100 memory: 17620 loss: 2.8604 loss_prob: 1.8065 loss_thr: 0.7578 loss_db: 0.2960 2022/11/01 13:55:58 - mmengine - INFO - Epoch(train) [93][50/63] lr: 9.2570e-04 eta: 13:28:14 time: 0.5882 data_time: 0.0236 memory: 17620 loss: 3.0876 loss_prob: 1.9448 loss_thr: 0.8136 loss_db: 0.3292 2022/11/01 13:56:01 - mmengine - INFO - Epoch(train) [93][55/63] lr: 9.2570e-04 eta: 13:28:14 time: 0.6217 data_time: 0.0204 memory: 17620 loss: 3.0322 loss_prob: 1.9000 loss_thr: 0.8035 loss_db: 0.3287 2022/11/01 13:56:04 - mmengine - INFO - Epoch(train) [93][60/63] lr: 9.2570e-04 eta: 13:27:57 time: 0.6080 data_time: 0.0075 memory: 17620 loss: 2.8092 loss_prob: 1.7553 loss_thr: 0.7537 loss_db: 0.3003 2022/11/01 13:56:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:56:11 - mmengine - INFO - Epoch(train) [94][5/63] lr: 9.3574e-04 eta: 13:27:57 time: 0.7490 data_time: 0.1809 memory: 17620 loss: 2.9180 loss_prob: 1.8342 loss_thr: 0.7696 loss_db: 0.3143 2022/11/01 13:56:13 - mmengine - INFO - Epoch(train) [94][10/63] lr: 9.3574e-04 eta: 13:27:33 time: 0.7772 data_time: 0.1834 memory: 17620 loss: 2.8922 loss_prob: 1.8112 loss_thr: 0.7742 loss_db: 0.3068 2022/11/01 13:56:17 - mmengine - INFO - Epoch(train) [94][15/63] lr: 9.3574e-04 eta: 13:27:33 time: 0.6207 data_time: 0.0093 memory: 17620 loss: 2.9738 loss_prob: 1.8602 loss_thr: 0.8000 loss_db: 0.3136 2022/11/01 13:56:19 - mmengine - INFO - Epoch(train) [94][20/63] lr: 9.3574e-04 eta: 13:27:15 time: 0.6041 data_time: 0.0055 memory: 17620 loss: 2.8018 loss_prob: 1.7451 loss_thr: 0.7698 loss_db: 0.2870 2022/11/01 13:56:22 - mmengine - INFO - Epoch(train) [94][25/63] lr: 9.3574e-04 eta: 13:27:15 time: 0.5271 data_time: 0.0068 memory: 17620 loss: 2.7302 loss_prob: 1.6967 loss_thr: 0.7515 loss_db: 0.2819 2022/11/01 13:56:25 - mmengine - INFO - Epoch(train) [94][30/63] lr: 9.3574e-04 eta: 13:26:51 time: 0.5516 data_time: 0.0306 memory: 17620 loss: 2.8800 loss_prob: 1.8047 loss_thr: 0.7681 loss_db: 0.3072 2022/11/01 13:56:28 - mmengine - INFO - Epoch(train) [94][35/63] lr: 9.3574e-04 eta: 13:26:51 time: 0.5735 data_time: 0.0320 memory: 17620 loss: 2.9914 loss_prob: 1.8870 loss_thr: 0.7777 loss_db: 0.3267 2022/11/01 13:56:30 - mmengine - INFO - Epoch(train) [94][40/63] lr: 9.3574e-04 eta: 13:26:27 time: 0.5513 data_time: 0.0082 memory: 17620 loss: 2.9597 loss_prob: 1.8642 loss_thr: 0.7793 loss_db: 0.3161 2022/11/01 13:56:33 - mmengine - INFO - Epoch(train) [94][45/63] lr: 9.3574e-04 eta: 13:26:27 time: 0.5407 data_time: 0.0047 memory: 17620 loss: 2.8188 loss_prob: 1.7581 loss_thr: 0.7713 loss_db: 0.2894 2022/11/01 13:56:36 - mmengine - INFO - Epoch(train) [94][50/63] lr: 9.3574e-04 eta: 13:26:04 time: 0.5565 data_time: 0.0132 memory: 17620 loss: 2.8785 loss_prob: 1.7715 loss_thr: 0.8046 loss_db: 0.3024 2022/11/01 13:56:39 - mmengine - INFO - Epoch(train) [94][55/63] lr: 9.3574e-04 eta: 13:26:04 time: 0.5833 data_time: 0.0242 memory: 17620 loss: 2.9499 loss_prob: 1.8154 loss_thr: 0.8170 loss_db: 0.3175 2022/11/01 13:56:42 - mmengine - INFO - Epoch(train) [94][60/63] lr: 9.3574e-04 eta: 13:25:43 time: 0.5726 data_time: 0.0161 memory: 17620 loss: 2.8195 loss_prob: 1.7614 loss_thr: 0.7658 loss_db: 0.2923 2022/11/01 13:56:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:56:48 - mmengine - INFO - Epoch(train) [95][5/63] lr: 9.4578e-04 eta: 13:25:43 time: 0.7298 data_time: 0.2008 memory: 17620 loss: 2.7606 loss_prob: 1.7110 loss_thr: 0.7696 loss_db: 0.2799 2022/11/01 13:56:51 - mmengine - INFO - Epoch(train) [95][10/63] lr: 9.4578e-04 eta: 13:25:16 time: 0.7480 data_time: 0.2008 memory: 17620 loss: 2.7089 loss_prob: 1.6821 loss_thr: 0.7464 loss_db: 0.2804 2022/11/01 13:56:54 - mmengine - INFO - Epoch(train) [95][15/63] lr: 9.4578e-04 eta: 13:25:16 time: 0.5879 data_time: 0.0057 memory: 17620 loss: 2.7797 loss_prob: 1.7278 loss_thr: 0.7608 loss_db: 0.2911 2022/11/01 13:56:56 - mmengine - INFO - Epoch(train) [95][20/63] lr: 9.4578e-04 eta: 13:24:56 time: 0.5880 data_time: 0.0055 memory: 17620 loss: 3.0551 loss_prob: 1.9118 loss_thr: 0.8115 loss_db: 0.3318 2022/11/01 13:57:00 - mmengine - INFO - Epoch(train) [95][25/63] lr: 9.4578e-04 eta: 13:24:56 time: 0.5793 data_time: 0.0412 memory: 17620 loss: 3.1108 loss_prob: 1.9540 loss_thr: 0.8166 loss_db: 0.3402 2022/11/01 13:57:02 - mmengine - INFO - Epoch(train) [95][30/63] lr: 9.4578e-04 eta: 13:24:39 time: 0.6010 data_time: 0.0437 memory: 17620 loss: 2.8372 loss_prob: 1.7598 loss_thr: 0.7823 loss_db: 0.2951 2022/11/01 13:57:05 - mmengine - INFO - Epoch(train) [95][35/63] lr: 9.4578e-04 eta: 13:24:39 time: 0.5520 data_time: 0.0070 memory: 17620 loss: 2.7693 loss_prob: 1.7051 loss_thr: 0.7822 loss_db: 0.2820 2022/11/01 13:57:08 - mmengine - INFO - Epoch(train) [95][40/63] lr: 9.4578e-04 eta: 13:24:15 time: 0.5528 data_time: 0.0046 memory: 17620 loss: 2.8064 loss_prob: 1.7338 loss_thr: 0.7840 loss_db: 0.2887 2022/11/01 13:57:11 - mmengine - INFO - Epoch(train) [95][45/63] lr: 9.4578e-04 eta: 13:24:15 time: 0.5625 data_time: 0.0049 memory: 17620 loss: 2.9400 loss_prob: 1.8371 loss_thr: 0.7866 loss_db: 0.3163 2022/11/01 13:57:13 - mmengine - INFO - Epoch(train) [95][50/63] lr: 9.4578e-04 eta: 13:23:51 time: 0.5429 data_time: 0.0217 memory: 17620 loss: 2.8189 loss_prob: 1.7599 loss_thr: 0.7609 loss_db: 0.2982 2022/11/01 13:57:16 - mmengine - INFO - Epoch(train) [95][55/63] lr: 9.4578e-04 eta: 13:23:51 time: 0.5611 data_time: 0.0228 memory: 17620 loss: 2.6625 loss_prob: 1.6510 loss_thr: 0.7406 loss_db: 0.2709 2022/11/01 13:57:19 - mmengine - INFO - Epoch(train) [95][60/63] lr: 9.4578e-04 eta: 13:23:30 time: 0.5711 data_time: 0.0060 memory: 17620 loss: 2.6291 loss_prob: 1.6129 loss_thr: 0.7518 loss_db: 0.2644 2022/11/01 13:57:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:57:26 - mmengine - INFO - Epoch(train) [96][5/63] lr: 9.5582e-04 eta: 13:23:30 time: 0.8199 data_time: 0.2404 memory: 17620 loss: 2.5482 loss_prob: 1.5464 loss_thr: 0.7565 loss_db: 0.2453 2022/11/01 13:57:30 - mmengine - INFO - Epoch(train) [96][10/63] lr: 9.5582e-04 eta: 13:23:27 time: 0.9518 data_time: 0.2412 memory: 17620 loss: 2.7781 loss_prob: 1.6988 loss_thr: 0.7913 loss_db: 0.2880 2022/11/01 13:57:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:57:33 - mmengine - INFO - Epoch(train) [96][15/63] lr: 9.5582e-04 eta: 13:23:27 time: 0.7202 data_time: 0.0068 memory: 17620 loss: 2.9335 loss_prob: 1.8151 loss_thr: 0.8059 loss_db: 0.3125 2022/11/01 13:57:36 - mmengine - INFO - Epoch(train) [96][20/63] lr: 9.5582e-04 eta: 13:23:10 time: 0.6115 data_time: 0.0054 memory: 17620 loss: 2.8060 loss_prob: 1.7393 loss_thr: 0.7758 loss_db: 0.2909 2022/11/01 13:57:39 - mmengine - INFO - Epoch(train) [96][25/63] lr: 9.5582e-04 eta: 13:23:10 time: 0.5737 data_time: 0.0258 memory: 17620 loss: 2.8728 loss_prob: 1.7960 loss_thr: 0.7695 loss_db: 0.3073 2022/11/01 13:57:42 - mmengine - INFO - Epoch(train) [96][30/63] lr: 9.5582e-04 eta: 13:22:53 time: 0.6000 data_time: 0.0345 memory: 17620 loss: 2.8414 loss_prob: 1.7711 loss_thr: 0.7671 loss_db: 0.3032 2022/11/01 13:57:45 - mmengine - INFO - Epoch(train) [96][35/63] lr: 9.5582e-04 eta: 13:22:53 time: 0.5803 data_time: 0.0158 memory: 17620 loss: 2.9672 loss_prob: 1.8705 loss_thr: 0.7717 loss_db: 0.3251 2022/11/01 13:57:48 - mmengine - INFO - Epoch(train) [96][40/63] lr: 9.5582e-04 eta: 13:22:28 time: 0.5372 data_time: 0.0076 memory: 17620 loss: 3.1010 loss_prob: 1.9851 loss_thr: 0.7676 loss_db: 0.3482 2022/11/01 13:57:50 - mmengine - INFO - Epoch(train) [96][45/63] lr: 9.5582e-04 eta: 13:22:28 time: 0.5488 data_time: 0.0055 memory: 17620 loss: 3.2025 loss_prob: 2.0603 loss_thr: 0.7782 loss_db: 0.3639 2022/11/01 13:57:54 - mmengine - INFO - Epoch(train) [96][50/63] lr: 9.5582e-04 eta: 13:22:12 time: 0.6098 data_time: 0.0209 memory: 17620 loss: 3.0500 loss_prob: 1.9457 loss_thr: 0.7701 loss_db: 0.3341 2022/11/01 13:57:56 - mmengine - INFO - Epoch(train) [96][55/63] lr: 9.5582e-04 eta: 13:22:12 time: 0.5919 data_time: 0.0240 memory: 17620 loss: 2.7561 loss_prob: 1.7279 loss_thr: 0.7461 loss_db: 0.2821 2022/11/01 13:57:59 - mmengine - INFO - Epoch(train) [96][60/63] lr: 9.5582e-04 eta: 13:21:48 time: 0.5441 data_time: 0.0078 memory: 17620 loss: 2.6455 loss_prob: 1.6390 loss_thr: 0.7433 loss_db: 0.2632 2022/11/01 13:58:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:58:06 - mmengine - INFO - Epoch(train) [97][5/63] lr: 9.6586e-04 eta: 13:21:48 time: 0.7948 data_time: 0.1811 memory: 17620 loss: 2.7031 loss_prob: 1.6810 loss_thr: 0.7455 loss_db: 0.2766 2022/11/01 13:58:09 - mmengine - INFO - Epoch(train) [97][10/63] lr: 9.6586e-04 eta: 13:21:27 time: 0.8010 data_time: 0.1955 memory: 17620 loss: 2.7971 loss_prob: 1.7458 loss_thr: 0.7540 loss_db: 0.2973 2022/11/01 13:58:12 - mmengine - INFO - Epoch(train) [97][15/63] lr: 9.6586e-04 eta: 13:21:27 time: 0.5837 data_time: 0.0202 memory: 17620 loss: 2.7865 loss_prob: 1.7193 loss_thr: 0.7731 loss_db: 0.2941 2022/11/01 13:58:15 - mmengine - INFO - Epoch(train) [97][20/63] lr: 9.6586e-04 eta: 13:21:05 time: 0.5582 data_time: 0.0072 memory: 17620 loss: 2.6942 loss_prob: 1.6706 loss_thr: 0.7447 loss_db: 0.2789 2022/11/01 13:58:18 - mmengine - INFO - Epoch(train) [97][25/63] lr: 9.6586e-04 eta: 13:21:05 time: 0.5870 data_time: 0.0204 memory: 17620 loss: 2.8721 loss_prob: 1.8207 loss_thr: 0.7435 loss_db: 0.3079 2022/11/01 13:58:21 - mmengine - INFO - Epoch(train) [97][30/63] lr: 9.6586e-04 eta: 13:20:48 time: 0.6016 data_time: 0.0347 memory: 17620 loss: 2.8927 loss_prob: 1.8210 loss_thr: 0.7669 loss_db: 0.3047 2022/11/01 13:58:23 - mmengine - INFO - Epoch(train) [97][35/63] lr: 9.6586e-04 eta: 13:20:48 time: 0.5845 data_time: 0.0212 memory: 17620 loss: 2.8126 loss_prob: 1.7403 loss_thr: 0.7797 loss_db: 0.2926 2022/11/01 13:58:26 - mmengine - INFO - Epoch(train) [97][40/63] lr: 9.6586e-04 eta: 13:20:25 time: 0.5518 data_time: 0.0044 memory: 17620 loss: 2.8016 loss_prob: 1.7330 loss_thr: 0.7751 loss_db: 0.2936 2022/11/01 13:58:29 - mmengine - INFO - Epoch(train) [97][45/63] lr: 9.6586e-04 eta: 13:20:25 time: 0.5424 data_time: 0.0052 memory: 17620 loss: 2.9890 loss_prob: 1.8909 loss_thr: 0.7702 loss_db: 0.3280 2022/11/01 13:58:32 - mmengine - INFO - Epoch(train) [97][50/63] lr: 9.6586e-04 eta: 13:20:05 time: 0.5775 data_time: 0.0164 memory: 17620 loss: 3.2064 loss_prob: 2.0487 loss_thr: 0.7962 loss_db: 0.3614 2022/11/01 13:58:35 - mmengine - INFO - Epoch(train) [97][55/63] lr: 9.6586e-04 eta: 13:20:05 time: 0.5869 data_time: 0.0248 memory: 17620 loss: 2.8717 loss_prob: 1.8060 loss_thr: 0.7630 loss_db: 0.3027 2022/11/01 13:58:38 - mmengine - INFO - Epoch(train) [97][60/63] lr: 9.6586e-04 eta: 13:19:47 time: 0.5865 data_time: 0.0139 memory: 17620 loss: 2.7323 loss_prob: 1.7136 loss_thr: 0.7409 loss_db: 0.2778 2022/11/01 13:58:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:58:44 - mmengine - INFO - Epoch(train) [98][5/63] lr: 9.7590e-04 eta: 13:19:47 time: 0.7787 data_time: 0.1963 memory: 17620 loss: 2.7501 loss_prob: 1.7119 loss_thr: 0.7574 loss_db: 0.2809 2022/11/01 13:58:47 - mmengine - INFO - Epoch(train) [98][10/63] lr: 9.7590e-04 eta: 13:19:24 time: 0.7800 data_time: 0.1961 memory: 17620 loss: 2.8733 loss_prob: 1.8174 loss_thr: 0.7520 loss_db: 0.3039 2022/11/01 13:58:50 - mmengine - INFO - Epoch(train) [98][15/63] lr: 9.7590e-04 eta: 13:19:24 time: 0.5614 data_time: 0.0059 memory: 17620 loss: 2.7914 loss_prob: 1.7439 loss_thr: 0.7592 loss_db: 0.2882 2022/11/01 13:58:52 - mmengine - INFO - Epoch(train) [98][20/63] lr: 9.7590e-04 eta: 13:19:00 time: 0.5335 data_time: 0.0093 memory: 17620 loss: 2.7391 loss_prob: 1.6848 loss_thr: 0.7760 loss_db: 0.2783 2022/11/01 13:58:55 - mmengine - INFO - Epoch(train) [98][25/63] lr: 9.7590e-04 eta: 13:19:00 time: 0.5520 data_time: 0.0369 memory: 17620 loss: 2.6509 loss_prob: 1.6393 loss_thr: 0.7404 loss_db: 0.2713 2022/11/01 13:58:58 - mmengine - INFO - Epoch(train) [98][30/63] lr: 9.7590e-04 eta: 13:18:39 time: 0.5707 data_time: 0.0338 memory: 17620 loss: 2.5846 loss_prob: 1.5945 loss_thr: 0.7313 loss_db: 0.2588 2022/11/01 13:59:01 - mmengine - INFO - Epoch(train) [98][35/63] lr: 9.7590e-04 eta: 13:18:39 time: 0.5592 data_time: 0.0051 memory: 17620 loss: 2.5208 loss_prob: 1.5377 loss_thr: 0.7375 loss_db: 0.2457 2022/11/01 13:59:04 - mmengine - INFO - Epoch(train) [98][40/63] lr: 9.7590e-04 eta: 13:18:17 time: 0.5575 data_time: 0.0117 memory: 17620 loss: 2.7537 loss_prob: 1.7175 loss_thr: 0.7521 loss_db: 0.2841 2022/11/01 13:59:07 - mmengine - INFO - Epoch(train) [98][45/63] lr: 9.7590e-04 eta: 13:18:17 time: 0.6097 data_time: 0.0134 memory: 17620 loss: 2.9866 loss_prob: 1.8917 loss_thr: 0.7686 loss_db: 0.3263 2022/11/01 13:59:10 - mmengine - INFO - Epoch(train) [98][50/63] lr: 9.7590e-04 eta: 13:18:01 time: 0.6095 data_time: 0.0204 memory: 17620 loss: 2.8474 loss_prob: 1.7906 loss_thr: 0.7494 loss_db: 0.3073 2022/11/01 13:59:13 - mmengine - INFO - Epoch(train) [98][55/63] lr: 9.7590e-04 eta: 13:18:01 time: 0.5687 data_time: 0.0187 memory: 17620 loss: 2.7979 loss_prob: 1.7393 loss_thr: 0.7691 loss_db: 0.2894 2022/11/01 13:59:15 - mmengine - INFO - Epoch(train) [98][60/63] lr: 9.7590e-04 eta: 13:17:39 time: 0.5483 data_time: 0.0088 memory: 17620 loss: 2.7378 loss_prob: 1.6975 loss_thr: 0.7612 loss_db: 0.2791 2022/11/01 13:59:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 13:59:22 - mmengine - INFO - Epoch(train) [99][5/63] lr: 9.8594e-04 eta: 13:17:39 time: 0.7468 data_time: 0.1903 memory: 17620 loss: 2.8547 loss_prob: 1.8000 loss_thr: 0.7541 loss_db: 0.3006 2022/11/01 13:59:24 - mmengine - INFO - Epoch(train) [99][10/63] lr: 9.8594e-04 eta: 13:17:18 time: 0.7875 data_time: 0.1990 memory: 17620 loss: 2.7735 loss_prob: 1.7356 loss_thr: 0.7509 loss_db: 0.2869 2022/11/01 13:59:27 - mmengine - INFO - Epoch(train) [99][15/63] lr: 9.8594e-04 eta: 13:17:18 time: 0.5810 data_time: 0.0170 memory: 17620 loss: 2.7642 loss_prob: 1.7031 loss_thr: 0.7812 loss_db: 0.2799 2022/11/01 13:59:30 - mmengine - INFO - Epoch(train) [99][20/63] lr: 9.8594e-04 eta: 13:16:56 time: 0.5614 data_time: 0.0074 memory: 17620 loss: 2.9589 loss_prob: 1.8493 loss_thr: 0.7964 loss_db: 0.3132 2022/11/01 13:59:33 - mmengine - INFO - Epoch(train) [99][25/63] lr: 9.8594e-04 eta: 13:16:56 time: 0.5659 data_time: 0.0246 memory: 17620 loss: 2.9866 loss_prob: 1.8723 loss_thr: 0.7875 loss_db: 0.3268 2022/11/01 13:59:36 - mmengine - INFO - Epoch(train) [99][30/63] lr: 9.8594e-04 eta: 13:16:40 time: 0.6035 data_time: 0.0314 memory: 17620 loss: 2.7633 loss_prob: 1.7039 loss_thr: 0.7675 loss_db: 0.2920 2022/11/01 13:59:39 - mmengine - INFO - Epoch(train) [99][35/63] lr: 9.8594e-04 eta: 13:16:40 time: 0.5644 data_time: 0.0170 memory: 17620 loss: 2.6568 loss_prob: 1.6321 loss_thr: 0.7572 loss_db: 0.2675 2022/11/01 13:59:42 - mmengine - INFO - Epoch(train) [99][40/63] lr: 9.8594e-04 eta: 13:16:21 time: 0.5803 data_time: 0.0085 memory: 17620 loss: 2.8182 loss_prob: 1.7596 loss_thr: 0.7630 loss_db: 0.2957 2022/11/01 13:59:46 - mmengine - INFO - Epoch(train) [99][45/63] lr: 9.8594e-04 eta: 13:16:21 time: 0.7063 data_time: 0.0067 memory: 17620 loss: 2.6863 loss_prob: 1.6652 loss_thr: 0.7389 loss_db: 0.2823 2022/11/01 13:59:49 - mmengine - INFO - Epoch(train) [99][50/63] lr: 9.8594e-04 eta: 13:16:18 time: 0.7220 data_time: 0.0207 memory: 17620 loss: 2.7009 loss_prob: 1.6561 loss_thr: 0.7643 loss_db: 0.2805 2022/11/01 13:59:52 - mmengine - INFO - Epoch(train) [99][55/63] lr: 9.8594e-04 eta: 13:16:18 time: 0.6428 data_time: 0.0230 memory: 17620 loss: 2.8047 loss_prob: 1.7282 loss_thr: 0.7851 loss_db: 0.2913 2022/11/01 13:59:55 - mmengine - INFO - Epoch(train) [99][60/63] lr: 9.8594e-04 eta: 13:16:01 time: 0.5964 data_time: 0.0124 memory: 17620 loss: 2.7471 loss_prob: 1.7064 loss_thr: 0.7598 loss_db: 0.2809 2022/11/01 13:59:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:00:02 - mmengine - INFO - Epoch(train) [100][5/63] lr: 9.9598e-04 eta: 13:16:01 time: 0.8496 data_time: 0.2075 memory: 17620 loss: 2.5783 loss_prob: 1.5935 loss_thr: 0.7259 loss_db: 0.2589 2022/11/01 14:00:06 - mmengine - INFO - Epoch(train) [100][10/63] lr: 9.9598e-04 eta: 13:15:50 time: 0.8804 data_time: 0.2071 memory: 17620 loss: 2.5592 loss_prob: 1.5682 loss_thr: 0.7394 loss_db: 0.2516 2022/11/01 14:00:08 - mmengine - INFO - Epoch(train) [100][15/63] lr: 9.9598e-04 eta: 13:15:50 time: 0.6031 data_time: 0.0066 memory: 17620 loss: 2.4602 loss_prob: 1.5060 loss_thr: 0.7129 loss_db: 0.2412 2022/11/01 14:00:11 - mmengine - INFO - Epoch(train) [100][20/63] lr: 9.9598e-04 eta: 13:15:28 time: 0.5544 data_time: 0.0083 memory: 17620 loss: 2.6618 loss_prob: 1.6603 loss_thr: 0.7303 loss_db: 0.2712 2022/11/01 14:00:15 - mmengine - INFO - Epoch(train) [100][25/63] lr: 9.9598e-04 eta: 13:15:28 time: 0.6508 data_time: 0.0278 memory: 17620 loss: 2.8614 loss_prob: 1.7793 loss_thr: 0.7882 loss_db: 0.2940 2022/11/01 14:00:18 - mmengine - INFO - Epoch(train) [100][30/63] lr: 9.9598e-04 eta: 13:15:20 time: 0.6750 data_time: 0.0315 memory: 17620 loss: 2.5373 loss_prob: 1.5366 loss_thr: 0.7550 loss_db: 0.2457 2022/11/01 14:00:21 - mmengine - INFO - Epoch(train) [100][35/63] lr: 9.9598e-04 eta: 13:15:20 time: 0.5859 data_time: 0.0131 memory: 17620 loss: 2.4619 loss_prob: 1.4945 loss_thr: 0.7256 loss_db: 0.2419 2022/11/01 14:00:24 - mmengine - INFO - Epoch(train) [100][40/63] lr: 9.9598e-04 eta: 13:14:59 time: 0.5648 data_time: 0.0074 memory: 17620 loss: 2.6176 loss_prob: 1.6094 loss_thr: 0.7432 loss_db: 0.2650 2022/11/01 14:00:26 - mmengine - INFO - Epoch(train) [100][45/63] lr: 9.9598e-04 eta: 13:14:59 time: 0.5757 data_time: 0.0091 memory: 17620 loss: 2.7304 loss_prob: 1.6953 loss_thr: 0.7555 loss_db: 0.2797 2022/11/01 14:00:30 - mmengine - INFO - Epoch(train) [100][50/63] lr: 9.9598e-04 eta: 13:14:43 time: 0.5985 data_time: 0.0325 memory: 17620 loss: 2.9124 loss_prob: 1.8411 loss_thr: 0.7537 loss_db: 0.3176 2022/11/01 14:00:33 - mmengine - INFO - Epoch(train) [100][55/63] lr: 9.9598e-04 eta: 13:14:43 time: 0.6358 data_time: 0.0363 memory: 17620 loss: 3.0644 loss_prob: 1.9589 loss_thr: 0.7602 loss_db: 0.3452 2022/11/01 14:00:36 - mmengine - INFO - Epoch(train) [100][60/63] lr: 9.9598e-04 eta: 13:14:29 time: 0.6300 data_time: 0.0122 memory: 17620 loss: 2.9197 loss_prob: 1.8410 loss_thr: 0.7661 loss_db: 0.3126 2022/11/01 14:00:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:00:37 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/11/01 14:00:44 - mmengine - INFO - Epoch(val) [100][5/32] eta: 13:14:29 time: 0.5756 data_time: 0.0752 memory: 17620 2022/11/01 14:00:47 - mmengine - INFO - Epoch(val) [100][10/32] eta: 0:00:14 time: 0.6461 data_time: 0.1101 memory: 15725 2022/11/01 14:00:50 - mmengine - INFO - Epoch(val) [100][15/32] eta: 0:00:14 time: 0.5756 data_time: 0.0488 memory: 15725 2022/11/01 14:00:53 - mmengine - INFO - Epoch(val) [100][20/32] eta: 0:00:06 time: 0.5713 data_time: 0.0523 memory: 15725 2022/11/01 14:00:56 - mmengine - INFO - Epoch(val) [100][25/32] eta: 0:00:06 time: 0.5867 data_time: 0.0556 memory: 15725 2022/11/01 14:00:59 - mmengine - INFO - Epoch(val) [100][30/32] eta: 0:00:01 time: 0.5986 data_time: 0.0534 memory: 15725 2022/11/01 14:01:00 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7087, precision: 0.6425, hmean: 0.6740 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7082, precision: 0.7854, hmean: 0.7448 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.6981, precision: 0.8519, hmean: 0.7674 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.6403, precision: 0.8950, hmean: 0.7466 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.4396, precision: 0.9501, hmean: 0.6011 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0130, precision: 1.0000, hmean: 0.0257 2022/11/01 14:01:00 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 14:01:00 - mmengine - INFO - Epoch(val) [100][32/32] icdar/precision: 0.8519 icdar/recall: 0.6981 icdar/hmean: 0.7674 2022/11/01 14:01:05 - mmengine - INFO - Epoch(train) [101][5/63] lr: 1.0060e-03 eta: 0:00:01 time: 0.7806 data_time: 0.2140 memory: 17620 loss: 2.7294 loss_prob: 1.7007 loss_thr: 0.7505 loss_db: 0.2782 2022/11/01 14:01:08 - mmengine - INFO - Epoch(train) [101][10/63] lr: 1.0060e-03 eta: 13:14:12 time: 0.8208 data_time: 0.2129 memory: 17620 loss: 2.5488 loss_prob: 1.5666 loss_thr: 0.7252 loss_db: 0.2571 2022/11/01 14:01:10 - mmengine - INFO - Epoch(train) [101][15/63] lr: 1.0060e-03 eta: 13:14:12 time: 0.5389 data_time: 0.0048 memory: 17620 loss: 2.6871 loss_prob: 1.6694 loss_thr: 0.7417 loss_db: 0.2759 2022/11/01 14:01:13 - mmengine - INFO - Epoch(train) [101][20/63] lr: 1.0060e-03 eta: 13:13:46 time: 0.5132 data_time: 0.0058 memory: 17620 loss: 2.9865 loss_prob: 1.8945 loss_thr: 0.7690 loss_db: 0.3230 2022/11/01 14:01:16 - mmengine - INFO - Epoch(train) [101][25/63] lr: 1.0060e-03 eta: 13:13:46 time: 0.5454 data_time: 0.0110 memory: 17620 loss: 2.9454 loss_prob: 1.8586 loss_thr: 0.7664 loss_db: 0.3204 2022/11/01 14:01:19 - mmengine - INFO - Epoch(train) [101][30/63] lr: 1.0060e-03 eta: 13:13:26 time: 0.5622 data_time: 0.0330 memory: 17620 loss: 2.6819 loss_prob: 1.6521 loss_thr: 0.7560 loss_db: 0.2738 2022/11/01 14:01:21 - mmengine - INFO - Epoch(train) [101][35/63] lr: 1.0060e-03 eta: 13:13:26 time: 0.5341 data_time: 0.0279 memory: 17620 loss: 2.7447 loss_prob: 1.7026 loss_thr: 0.7573 loss_db: 0.2848 2022/11/01 14:01:24 - mmengine - INFO - Epoch(train) [101][40/63] lr: 1.0060e-03 eta: 13:13:03 time: 0.5446 data_time: 0.0047 memory: 17620 loss: 2.7572 loss_prob: 1.7211 loss_thr: 0.7455 loss_db: 0.2906 2022/11/01 14:01:27 - mmengine - INFO - Epoch(train) [101][45/63] lr: 1.0060e-03 eta: 13:13:03 time: 0.5808 data_time: 0.0045 memory: 17620 loss: 2.6715 loss_prob: 1.6591 loss_thr: 0.7385 loss_db: 0.2739 2022/11/01 14:01:30 - mmengine - INFO - Epoch(train) [101][50/63] lr: 1.0060e-03 eta: 13:12:45 time: 0.5829 data_time: 0.0251 memory: 17620 loss: 2.6590 loss_prob: 1.6395 loss_thr: 0.7520 loss_db: 0.2675 2022/11/01 14:01:33 - mmengine - INFO - Epoch(train) [101][55/63] lr: 1.0060e-03 eta: 13:12:45 time: 0.5930 data_time: 0.0257 memory: 17620 loss: 2.4849 loss_prob: 1.5103 loss_thr: 0.7326 loss_db: 0.2420 2022/11/01 14:01:36 - mmengine - INFO - Epoch(train) [101][60/63] lr: 1.0060e-03 eta: 13:12:30 time: 0.6125 data_time: 0.0056 memory: 17620 loss: 2.5798 loss_prob: 1.6049 loss_thr: 0.7130 loss_db: 0.2620 2022/11/01 14:01:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:01:42 - mmengine - INFO - Epoch(train) [102][5/63] lr: 1.0161e-03 eta: 13:12:30 time: 0.7188 data_time: 0.1807 memory: 17620 loss: 2.6979 loss_prob: 1.6843 loss_thr: 0.7282 loss_db: 0.2854 2022/11/01 14:01:45 - mmengine - INFO - Epoch(train) [102][10/63] lr: 1.0161e-03 eta: 13:12:03 time: 0.7214 data_time: 0.1839 memory: 17620 loss: 2.7071 loss_prob: 1.6528 loss_thr: 0.7810 loss_db: 0.2733 2022/11/01 14:01:47 - mmengine - INFO - Epoch(train) [102][15/63] lr: 1.0161e-03 eta: 13:12:03 time: 0.5357 data_time: 0.0109 memory: 17620 loss: 2.7694 loss_prob: 1.6950 loss_thr: 0.7937 loss_db: 0.2806 2022/11/01 14:01:50 - mmengine - INFO - Epoch(train) [102][20/63] lr: 1.0161e-03 eta: 13:11:39 time: 0.5348 data_time: 0.0077 memory: 17620 loss: 2.6515 loss_prob: 1.6502 loss_thr: 0.7277 loss_db: 0.2736 2022/11/01 14:01:53 - mmengine - INFO - Epoch(train) [102][25/63] lr: 1.0161e-03 eta: 13:11:39 time: 0.5726 data_time: 0.0211 memory: 17620 loss: 2.7995 loss_prob: 1.7751 loss_thr: 0.7221 loss_db: 0.3024 2022/11/01 14:01:56 - mmengine - INFO - Epoch(train) [102][30/63] lr: 1.0161e-03 eta: 13:11:23 time: 0.6017 data_time: 0.0324 memory: 17620 loss: 2.8031 loss_prob: 1.7660 loss_thr: 0.7412 loss_db: 0.2958 2022/11/01 14:01:59 - mmengine - INFO - Epoch(train) [102][35/63] lr: 1.0161e-03 eta: 13:11:23 time: 0.5671 data_time: 0.0174 memory: 17620 loss: 2.5321 loss_prob: 1.5579 loss_thr: 0.7262 loss_db: 0.2481 2022/11/01 14:02:02 - mmengine - INFO - Epoch(train) [102][40/63] lr: 1.0161e-03 eta: 13:11:00 time: 0.5385 data_time: 0.0062 memory: 17620 loss: 2.5902 loss_prob: 1.6060 loss_thr: 0.7209 loss_db: 0.2633 2022/11/01 14:02:04 - mmengine - INFO - Epoch(train) [102][45/63] lr: 1.0161e-03 eta: 13:11:00 time: 0.5246 data_time: 0.0065 memory: 17620 loss: 2.6763 loss_prob: 1.6551 loss_thr: 0.7460 loss_db: 0.2752 2022/11/01 14:02:07 - mmengine - INFO - Epoch(train) [102][50/63] lr: 1.0161e-03 eta: 13:10:37 time: 0.5314 data_time: 0.0200 memory: 17620 loss: 2.7174 loss_prob: 1.6863 loss_thr: 0.7524 loss_db: 0.2788 2022/11/01 14:02:11 - mmengine - INFO - Epoch(train) [102][55/63] lr: 1.0161e-03 eta: 13:10:37 time: 0.6441 data_time: 0.0250 memory: 17620 loss: 2.8020 loss_prob: 1.7602 loss_thr: 0.7468 loss_db: 0.2950 2022/11/01 14:02:14 - mmengine - INFO - Epoch(train) [102][60/63] lr: 1.0161e-03 eta: 13:10:30 time: 0.6811 data_time: 0.0125 memory: 17620 loss: 2.8276 loss_prob: 1.7759 loss_thr: 0.7547 loss_db: 0.2970 2022/11/01 14:02:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:02:21 - mmengine - INFO - Epoch(train) [103][5/63] lr: 1.0261e-03 eta: 13:10:30 time: 0.8077 data_time: 0.2143 memory: 17620 loss: 2.9437 loss_prob: 1.8777 loss_thr: 0.7472 loss_db: 0.3189 2022/11/01 14:02:24 - mmengine - INFO - Epoch(train) [103][10/63] lr: 1.0261e-03 eta: 13:10:17 time: 0.8598 data_time: 0.2147 memory: 17620 loss: 2.7829 loss_prob: 1.7352 loss_thr: 0.7563 loss_db: 0.2914 2022/11/01 14:02:27 - mmengine - INFO - Epoch(train) [103][15/63] lr: 1.0261e-03 eta: 13:10:17 time: 0.6110 data_time: 0.0051 memory: 17620 loss: 2.6514 loss_prob: 1.6313 loss_thr: 0.7502 loss_db: 0.2699 2022/11/01 14:02:30 - mmengine - INFO - Epoch(train) [103][20/63] lr: 1.0261e-03 eta: 13:10:00 time: 0.5904 data_time: 0.0049 memory: 17620 loss: 2.6570 loss_prob: 1.6392 loss_thr: 0.7462 loss_db: 0.2717 2022/11/01 14:02:33 - mmengine - INFO - Epoch(train) [103][25/63] lr: 1.0261e-03 eta: 13:10:00 time: 0.6497 data_time: 0.0152 memory: 17620 loss: 2.4772 loss_prob: 1.5224 loss_thr: 0.7122 loss_db: 0.2427 2022/11/01 14:02:37 - mmengine - INFO - Epoch(train) [103][30/63] lr: 1.0261e-03 eta: 13:09:54 time: 0.6940 data_time: 0.0370 memory: 17620 loss: 2.5826 loss_prob: 1.6016 loss_thr: 0.7216 loss_db: 0.2594 2022/11/01 14:02:40 - mmengine - INFO - Epoch(train) [103][35/63] lr: 1.0261e-03 eta: 13:09:54 time: 0.6942 data_time: 0.0262 memory: 17620 loss: 2.5877 loss_prob: 1.6034 loss_thr: 0.7191 loss_db: 0.2652 2022/11/01 14:02:43 - mmengine - INFO - Epoch(train) [103][40/63] lr: 1.0261e-03 eta: 13:09:46 time: 0.6754 data_time: 0.0045 memory: 17620 loss: 2.5820 loss_prob: 1.5857 loss_thr: 0.7346 loss_db: 0.2616 2022/11/01 14:02:46 - mmengine - INFO - Epoch(train) [103][45/63] lr: 1.0261e-03 eta: 13:09:46 time: 0.5951 data_time: 0.0055 memory: 17620 loss: 2.6956 loss_prob: 1.6625 loss_thr: 0.7590 loss_db: 0.2742 2022/11/01 14:02:50 - mmengine - INFO - Epoch(train) [103][50/63] lr: 1.0261e-03 eta: 13:09:32 time: 0.6155 data_time: 0.0159 memory: 17620 loss: 2.6496 loss_prob: 1.6395 loss_thr: 0.7367 loss_db: 0.2734 2022/11/01 14:02:53 - mmengine - INFO - Epoch(train) [103][55/63] lr: 1.0261e-03 eta: 13:09:32 time: 0.6884 data_time: 0.0289 memory: 17620 loss: 2.6976 loss_prob: 1.6728 loss_thr: 0.7465 loss_db: 0.2782 2022/11/01 14:02:56 - mmengine - INFO - Epoch(train) [103][60/63] lr: 1.0261e-03 eta: 13:09:20 time: 0.6416 data_time: 0.0183 memory: 17620 loss: 2.7916 loss_prob: 1.7440 loss_thr: 0.7546 loss_db: 0.2931 2022/11/01 14:02:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:03:03 - mmengine - INFO - Epoch(train) [104][5/63] lr: 1.0361e-03 eta: 13:09:20 time: 0.7707 data_time: 0.2190 memory: 17620 loss: 2.7058 loss_prob: 1.6970 loss_thr: 0.7289 loss_db: 0.2799 2022/11/01 14:03:05 - mmengine - INFO - Epoch(train) [104][10/63] lr: 1.0361e-03 eta: 13:09:00 time: 0.7834 data_time: 0.2203 memory: 17620 loss: 2.7605 loss_prob: 1.7253 loss_thr: 0.7476 loss_db: 0.2877 2022/11/01 14:03:08 - mmengine - INFO - Epoch(train) [104][15/63] lr: 1.0361e-03 eta: 13:09:00 time: 0.5401 data_time: 0.0067 memory: 17620 loss: 2.5327 loss_prob: 1.5610 loss_thr: 0.7154 loss_db: 0.2564 2022/11/01 14:03:11 - mmengine - INFO - Epoch(train) [104][20/63] lr: 1.0361e-03 eta: 13:08:39 time: 0.5461 data_time: 0.0073 memory: 17620 loss: 2.5967 loss_prob: 1.6058 loss_thr: 0.7261 loss_db: 0.2648 2022/11/01 14:03:14 - mmengine - INFO - Epoch(train) [104][25/63] lr: 1.0361e-03 eta: 13:08:39 time: 0.5734 data_time: 0.0346 memory: 17620 loss: 2.5925 loss_prob: 1.5998 loss_thr: 0.7302 loss_db: 0.2625 2022/11/01 14:03:16 - mmengine - INFO - Epoch(train) [104][30/63] lr: 1.0361e-03 eta: 13:08:18 time: 0.5553 data_time: 0.0320 memory: 17620 loss: 2.5914 loss_prob: 1.5988 loss_thr: 0.7291 loss_db: 0.2636 2022/11/01 14:03:19 - mmengine - INFO - Epoch(train) [104][35/63] lr: 1.0361e-03 eta: 13:08:18 time: 0.5242 data_time: 0.0070 memory: 17620 loss: 2.9923 loss_prob: 1.9036 loss_thr: 0.7673 loss_db: 0.3214 2022/11/01 14:03:21 - mmengine - INFO - Epoch(train) [104][40/63] lr: 1.0361e-03 eta: 13:07:54 time: 0.5207 data_time: 0.0094 memory: 17620 loss: 3.3671 loss_prob: 2.1714 loss_thr: 0.8177 loss_db: 0.3780 2022/11/01 14:03:24 - mmengine - INFO - Epoch(train) [104][45/63] lr: 1.0361e-03 eta: 13:07:54 time: 0.5324 data_time: 0.0070 memory: 17620 loss: 3.5090 loss_prob: 2.2596 loss_thr: 0.8514 loss_db: 0.3980 2022/11/01 14:03:27 - mmengine - INFO - Epoch(train) [104][50/63] lr: 1.0361e-03 eta: 13:07:38 time: 0.5984 data_time: 0.0237 memory: 17620 loss: 3.2345 loss_prob: 2.0709 loss_thr: 0.8075 loss_db: 0.3561 2022/11/01 14:03:30 - mmengine - INFO - Epoch(train) [104][55/63] lr: 1.0361e-03 eta: 13:07:38 time: 0.6072 data_time: 0.0237 memory: 17620 loss: 2.9449 loss_prob: 1.8455 loss_thr: 0.7904 loss_db: 0.3090 2022/11/01 14:03:33 - mmengine - INFO - Epoch(train) [104][60/63] lr: 1.0361e-03 eta: 13:07:20 time: 0.5757 data_time: 0.0058 memory: 17620 loss: 3.0003 loss_prob: 1.8916 loss_thr: 0.7890 loss_db: 0.3197 2022/11/01 14:03:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:03:39 - mmengine - INFO - Epoch(train) [105][5/63] lr: 1.0462e-03 eta: 13:07:20 time: 0.7456 data_time: 0.1899 memory: 17620 loss: 3.2996 loss_prob: 2.1075 loss_thr: 0.8269 loss_db: 0.3651 2022/11/01 14:03:42 - mmengine - INFO - Epoch(train) [105][10/63] lr: 1.0462e-03 eta: 13:06:56 time: 0.7525 data_time: 0.1896 memory: 17620 loss: 3.4027 loss_prob: 2.2016 loss_thr: 0.8247 loss_db: 0.3765 2022/11/01 14:03:45 - mmengine - INFO - Epoch(train) [105][15/63] lr: 1.0462e-03 eta: 13:06:56 time: 0.5316 data_time: 0.0054 memory: 17620 loss: 3.0645 loss_prob: 1.9507 loss_thr: 0.7846 loss_db: 0.3293 2022/11/01 14:03:47 - mmengine - INFO - Epoch(train) [105][20/63] lr: 1.0462e-03 eta: 13:06:33 time: 0.5310 data_time: 0.0072 memory: 17620 loss: 2.8742 loss_prob: 1.8074 loss_thr: 0.7641 loss_db: 0.3027 2022/11/01 14:03:50 - mmengine - INFO - Epoch(train) [105][25/63] lr: 1.0462e-03 eta: 13:06:33 time: 0.5559 data_time: 0.0229 memory: 17620 loss: 2.8718 loss_prob: 1.7975 loss_thr: 0.7744 loss_db: 0.3000 2022/11/01 14:03:54 - mmengine - INFO - Epoch(train) [105][30/63] lr: 1.0462e-03 eta: 13:06:18 time: 0.6036 data_time: 0.0498 memory: 17620 loss: 2.7061 loss_prob: 1.6691 loss_thr: 0.7633 loss_db: 0.2738 2022/11/01 14:03:56 - mmengine - INFO - Epoch(train) [105][35/63] lr: 1.0462e-03 eta: 13:06:18 time: 0.5843 data_time: 0.0338 memory: 17620 loss: 2.8590 loss_prob: 1.7800 loss_thr: 0.7813 loss_db: 0.2977 2022/11/01 14:03:59 - mmengine - INFO - Epoch(train) [105][40/63] lr: 1.0462e-03 eta: 13:05:56 time: 0.5370 data_time: 0.0045 memory: 17620 loss: 2.8362 loss_prob: 1.7713 loss_thr: 0.7685 loss_db: 0.2964 2022/11/01 14:04:02 - mmengine - INFO - Epoch(train) [105][45/63] lr: 1.0462e-03 eta: 13:05:56 time: 0.5461 data_time: 0.0066 memory: 17620 loss: 2.7835 loss_prob: 1.7571 loss_thr: 0.7387 loss_db: 0.2877 2022/11/01 14:04:05 - mmengine - INFO - Epoch(train) [105][50/63] lr: 1.0462e-03 eta: 13:05:39 time: 0.5913 data_time: 0.0208 memory: 17620 loss: 2.7989 loss_prob: 1.7686 loss_thr: 0.7383 loss_db: 0.2920 2022/11/01 14:04:08 - mmengine - INFO - Epoch(train) [105][55/63] lr: 1.0462e-03 eta: 13:05:39 time: 0.5879 data_time: 0.0230 memory: 17620 loss: 2.7813 loss_prob: 1.7375 loss_thr: 0.7521 loss_db: 0.2917 2022/11/01 14:04:10 - mmengine - INFO - Epoch(train) [105][60/63] lr: 1.0462e-03 eta: 13:05:18 time: 0.5451 data_time: 0.0089 memory: 17620 loss: 3.0032 loss_prob: 1.8857 loss_thr: 0.7919 loss_db: 0.3256 2022/11/01 14:04:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:04:16 - mmengine - INFO - Epoch(train) [106][5/63] lr: 1.0562e-03 eta: 13:05:18 time: 0.7141 data_time: 0.1874 memory: 17620 loss: 2.9670 loss_prob: 1.8722 loss_thr: 0.7690 loss_db: 0.3257 2022/11/01 14:04:19 - mmengine - INFO - Epoch(train) [106][10/63] lr: 1.0562e-03 eta: 13:04:52 time: 0.7250 data_time: 0.1926 memory: 17620 loss: 2.9576 loss_prob: 1.8703 loss_thr: 0.7608 loss_db: 0.3265 2022/11/01 14:04:22 - mmengine - INFO - Epoch(train) [106][15/63] lr: 1.0562e-03 eta: 13:04:52 time: 0.5527 data_time: 0.0134 memory: 17620 loss: 2.8331 loss_prob: 1.7572 loss_thr: 0.7749 loss_db: 0.3011 2022/11/01 14:04:25 - mmengine - INFO - Epoch(train) [106][20/63] lr: 1.0562e-03 eta: 13:04:34 time: 0.5683 data_time: 0.0082 memory: 17620 loss: 2.8107 loss_prob: 1.7163 loss_thr: 0.8045 loss_db: 0.2899 2022/11/01 14:04:28 - mmengine - INFO - Epoch(train) [106][25/63] lr: 1.0562e-03 eta: 13:04:34 time: 0.5999 data_time: 0.0277 memory: 17620 loss: 2.6883 loss_prob: 1.6359 loss_thr: 0.7883 loss_db: 0.2641 2022/11/01 14:04:31 - mmengine - INFO - Epoch(train) [106][30/63] lr: 1.0562e-03 eta: 13:04:25 time: 0.6695 data_time: 0.0279 memory: 17620 loss: 2.5915 loss_prob: 1.5872 loss_thr: 0.7476 loss_db: 0.2567 2022/11/01 14:04:34 - mmengine - INFO - Epoch(train) [106][35/63] lr: 1.0562e-03 eta: 13:04:25 time: 0.6427 data_time: 0.0104 memory: 17620 loss: 2.5574 loss_prob: 1.5870 loss_thr: 0.7074 loss_db: 0.2630 2022/11/01 14:04:38 - mmengine - INFO - Epoch(train) [106][40/63] lr: 1.0562e-03 eta: 13:04:11 time: 0.6083 data_time: 0.0148 memory: 17620 loss: 2.5192 loss_prob: 1.5714 loss_thr: 0.6928 loss_db: 0.2550 2022/11/01 14:04:40 - mmengine - INFO - Epoch(train) [106][45/63] lr: 1.0562e-03 eta: 13:04:11 time: 0.6202 data_time: 0.0101 memory: 17620 loss: 2.6959 loss_prob: 1.6806 loss_thr: 0.7386 loss_db: 0.2766 2022/11/01 14:04:44 - mmengine - INFO - Epoch(train) [106][50/63] lr: 1.0562e-03 eta: 13:04:00 time: 0.6406 data_time: 0.0207 memory: 17620 loss: 3.0196 loss_prob: 1.8994 loss_thr: 0.7959 loss_db: 0.3242 2022/11/01 14:04:47 - mmengine - INFO - Epoch(train) [106][55/63] lr: 1.0562e-03 eta: 13:04:00 time: 0.6118 data_time: 0.0215 memory: 17620 loss: 2.8503 loss_prob: 1.7861 loss_thr: 0.7636 loss_db: 0.3007 2022/11/01 14:04:49 - mmengine - INFO - Epoch(train) [106][60/63] lr: 1.0562e-03 eta: 13:03:38 time: 0.5378 data_time: 0.0091 memory: 17620 loss: 2.6832 loss_prob: 1.6598 loss_thr: 0.7463 loss_db: 0.2772 2022/11/01 14:04:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:04:56 - mmengine - INFO - Epoch(train) [107][5/63] lr: 1.0663e-03 eta: 13:03:38 time: 0.7506 data_time: 0.2349 memory: 17620 loss: 3.0884 loss_prob: 1.9554 loss_thr: 0.7919 loss_db: 0.3411 2022/11/01 14:04:58 - mmengine - INFO - Epoch(train) [107][10/63] lr: 1.0663e-03 eta: 13:03:17 time: 0.7719 data_time: 0.2334 memory: 17620 loss: 2.9909 loss_prob: 1.8665 loss_thr: 0.8026 loss_db: 0.3218 2022/11/01 14:05:01 - mmengine - INFO - Epoch(train) [107][15/63] lr: 1.0663e-03 eta: 13:03:17 time: 0.5480 data_time: 0.0065 memory: 17620 loss: 3.1515 loss_prob: 1.9842 loss_thr: 0.8200 loss_db: 0.3473 2022/11/01 14:05:04 - mmengine - INFO - Epoch(train) [107][20/63] lr: 1.0663e-03 eta: 13:02:57 time: 0.5481 data_time: 0.0107 memory: 17620 loss: 3.2469 loss_prob: 2.0706 loss_thr: 0.8048 loss_db: 0.3714 2022/11/01 14:05:07 - mmengine - INFO - Epoch(train) [107][25/63] lr: 1.0663e-03 eta: 13:02:57 time: 0.5821 data_time: 0.0393 memory: 17620 loss: 3.0776 loss_prob: 1.9507 loss_thr: 0.7851 loss_db: 0.3418 2022/11/01 14:05:10 - mmengine - INFO - Epoch(train) [107][30/63] lr: 1.0663e-03 eta: 13:02:43 time: 0.6150 data_time: 0.0397 memory: 17620 loss: 2.7888 loss_prob: 1.7386 loss_thr: 0.7575 loss_db: 0.2927 2022/11/01 14:05:13 - mmengine - INFO - Epoch(train) [107][35/63] lr: 1.0663e-03 eta: 13:02:43 time: 0.6261 data_time: 0.0092 memory: 17620 loss: 2.7424 loss_prob: 1.6890 loss_thr: 0.7720 loss_db: 0.2813 2022/11/01 14:05:16 - mmengine - INFO - Epoch(train) [107][40/63] lr: 1.0663e-03 eta: 13:02:30 time: 0.6244 data_time: 0.0060 memory: 17620 loss: 2.9177 loss_prob: 1.8159 loss_thr: 0.7961 loss_db: 0.3057 2022/11/01 14:05:20 - mmengine - INFO - Epoch(train) [107][45/63] lr: 1.0663e-03 eta: 13:02:30 time: 0.6463 data_time: 0.0066 memory: 17620 loss: 2.8299 loss_prob: 1.7743 loss_thr: 0.7580 loss_db: 0.2976 2022/11/01 14:05:23 - mmengine - INFO - Epoch(train) [107][50/63] lr: 1.0663e-03 eta: 13:02:20 time: 0.6510 data_time: 0.0268 memory: 17620 loss: 2.6678 loss_prob: 1.6564 loss_thr: 0.7384 loss_db: 0.2730 2022/11/01 14:05:26 - mmengine - INFO - Epoch(train) [107][55/63] lr: 1.0663e-03 eta: 13:02:20 time: 0.5821 data_time: 0.0270 memory: 17620 loss: 2.6558 loss_prob: 1.6384 loss_thr: 0.7478 loss_db: 0.2697 2022/11/01 14:05:29 - mmengine - INFO - Epoch(train) [107][60/63] lr: 1.0663e-03 eta: 13:02:03 time: 0.5825 data_time: 0.0053 memory: 17620 loss: 2.6977 loss_prob: 1.6743 loss_thr: 0.7488 loss_db: 0.2746 2022/11/01 14:05:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:05:35 - mmengine - INFO - Epoch(train) [108][5/63] lr: 1.0763e-03 eta: 13:02:03 time: 0.7851 data_time: 0.1919 memory: 17620 loss: 3.0393 loss_prob: 1.9078 loss_thr: 0.8031 loss_db: 0.3284 2022/11/01 14:05:38 - mmengine - INFO - Epoch(train) [108][10/63] lr: 1.0763e-03 eta: 13:01:44 time: 0.7778 data_time: 0.1968 memory: 17620 loss: 3.1786 loss_prob: 2.0227 loss_thr: 0.8006 loss_db: 0.3554 2022/11/01 14:05:41 - mmengine - INFO - Epoch(train) [108][15/63] lr: 1.0763e-03 eta: 13:01:44 time: 0.5512 data_time: 0.0128 memory: 17620 loss: 2.9044 loss_prob: 1.8495 loss_thr: 0.7397 loss_db: 0.3152 2022/11/01 14:05:43 - mmengine - INFO - Epoch(train) [108][20/63] lr: 1.0763e-03 eta: 13:01:22 time: 0.5386 data_time: 0.0068 memory: 17620 loss: 2.7688 loss_prob: 1.7365 loss_thr: 0.7466 loss_db: 0.2856 2022/11/01 14:05:46 - mmengine - INFO - Epoch(train) [108][25/63] lr: 1.0763e-03 eta: 13:01:22 time: 0.5701 data_time: 0.0220 memory: 17620 loss: 2.8024 loss_prob: 1.7363 loss_thr: 0.7755 loss_db: 0.2906 2022/11/01 14:05:49 - mmengine - INFO - Epoch(train) [108][30/63] lr: 1.0763e-03 eta: 13:01:03 time: 0.5627 data_time: 0.0219 memory: 17620 loss: 2.8305 loss_prob: 1.7615 loss_thr: 0.7748 loss_db: 0.2942 2022/11/01 14:05:52 - mmengine - INFO - Epoch(train) [108][35/63] lr: 1.0763e-03 eta: 13:01:03 time: 0.5460 data_time: 0.0165 memory: 17620 loss: 2.9474 loss_prob: 1.8659 loss_thr: 0.7643 loss_db: 0.3171 2022/11/01 14:05:55 - mmengine - INFO - Epoch(train) [108][40/63] lr: 1.0763e-03 eta: 13:00:45 time: 0.5672 data_time: 0.0165 memory: 17620 loss: 2.7974 loss_prob: 1.7748 loss_thr: 0.7243 loss_db: 0.2983 2022/11/01 14:05:58 - mmengine - INFO - Epoch(train) [108][45/63] lr: 1.0763e-03 eta: 13:00:45 time: 0.5679 data_time: 0.0061 memory: 17620 loss: 2.4874 loss_prob: 1.5399 loss_thr: 0.7025 loss_db: 0.2450 2022/11/01 14:06:00 - mmengine - INFO - Epoch(train) [108][50/63] lr: 1.0763e-03 eta: 13:00:26 time: 0.5550 data_time: 0.0144 memory: 17620 loss: 2.4763 loss_prob: 1.4981 loss_thr: 0.7400 loss_db: 0.2382 2022/11/01 14:06:03 - mmengine - INFO - Epoch(train) [108][55/63] lr: 1.0763e-03 eta: 13:00:26 time: 0.5573 data_time: 0.0213 memory: 17620 loss: 2.6181 loss_prob: 1.6089 loss_thr: 0.7476 loss_db: 0.2616 2022/11/01 14:06:06 - mmengine - INFO - Epoch(train) [108][60/63] lr: 1.0763e-03 eta: 13:00:05 time: 0.5489 data_time: 0.0139 memory: 17620 loss: 2.6744 loss_prob: 1.6586 loss_thr: 0.7434 loss_db: 0.2724 2022/11/01 14:06:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:06:12 - mmengine - INFO - Epoch(train) [109][5/63] lr: 1.0863e-03 eta: 13:00:05 time: 0.7728 data_time: 0.2253 memory: 17620 loss: 2.7858 loss_prob: 1.7365 loss_thr: 0.7576 loss_db: 0.2917 2022/11/01 14:06:15 - mmengine - INFO - Epoch(train) [109][10/63] lr: 1.0863e-03 eta: 12:59:48 time: 0.7966 data_time: 0.2262 memory: 17620 loss: 2.7057 loss_prob: 1.6801 loss_thr: 0.7432 loss_db: 0.2824 2022/11/01 14:06:18 - mmengine - INFO - Epoch(train) [109][15/63] lr: 1.0863e-03 eta: 12:59:48 time: 0.5382 data_time: 0.0101 memory: 17620 loss: 2.5233 loss_prob: 1.5523 loss_thr: 0.7122 loss_db: 0.2588 2022/11/01 14:06:20 - mmengine - INFO - Epoch(train) [109][20/63] lr: 1.0863e-03 eta: 12:59:25 time: 0.5257 data_time: 0.0051 memory: 17620 loss: 2.6179 loss_prob: 1.6132 loss_thr: 0.7329 loss_db: 0.2718 2022/11/01 14:06:23 - mmengine - INFO - Epoch(train) [109][25/63] lr: 1.0863e-03 eta: 12:59:25 time: 0.5300 data_time: 0.0134 memory: 17620 loss: 2.7429 loss_prob: 1.7138 loss_thr: 0.7409 loss_db: 0.2881 2022/11/01 14:06:26 - mmengine - INFO - Epoch(train) [109][30/63] lr: 1.0863e-03 eta: 12:59:07 time: 0.5678 data_time: 0.0335 memory: 17620 loss: 2.8282 loss_prob: 1.7824 loss_thr: 0.7489 loss_db: 0.2969 2022/11/01 14:06:29 - mmengine - INFO - Epoch(train) [109][35/63] lr: 1.0863e-03 eta: 12:59:07 time: 0.5755 data_time: 0.0250 memory: 17620 loss: 2.9403 loss_prob: 1.8543 loss_thr: 0.7686 loss_db: 0.3174 2022/11/01 14:06:32 - mmengine - INFO - Epoch(train) [109][40/63] lr: 1.0863e-03 eta: 12:58:48 time: 0.5549 data_time: 0.0067 memory: 17620 loss: 2.8438 loss_prob: 1.7812 loss_thr: 0.7542 loss_db: 0.3084 2022/11/01 14:06:34 - mmengine - INFO - Epoch(train) [109][45/63] lr: 1.0863e-03 eta: 12:58:48 time: 0.5311 data_time: 0.0074 memory: 17620 loss: 2.8533 loss_prob: 1.7959 loss_thr: 0.7491 loss_db: 0.3082 2022/11/01 14:06:37 - mmengine - INFO - Epoch(train) [109][50/63] lr: 1.0863e-03 eta: 12:58:28 time: 0.5451 data_time: 0.0139 memory: 17620 loss: 3.2912 loss_prob: 2.0984 loss_thr: 0.8018 loss_db: 0.3909 2022/11/01 14:06:40 - mmengine - INFO - Epoch(train) [109][55/63] lr: 1.0863e-03 eta: 12:58:28 time: 0.5649 data_time: 0.0203 memory: 17620 loss: 3.1765 loss_prob: 2.0065 loss_thr: 0.8024 loss_db: 0.3676 2022/11/01 14:06:43 - mmengine - INFO - Epoch(train) [109][60/63] lr: 1.0863e-03 eta: 12:58:09 time: 0.5610 data_time: 0.0121 memory: 17620 loss: 2.6087 loss_prob: 1.6146 loss_thr: 0.7357 loss_db: 0.2585 2022/11/01 14:06:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:06:49 - mmengine - INFO - Epoch(train) [110][5/63] lr: 1.0964e-03 eta: 12:58:09 time: 0.7458 data_time: 0.2101 memory: 17620 loss: 2.6063 loss_prob: 1.6155 loss_thr: 0.7258 loss_db: 0.2650 2022/11/01 14:06:52 - mmengine - INFO - Epoch(train) [110][10/63] lr: 1.0964e-03 eta: 12:57:50 time: 0.7853 data_time: 0.2088 memory: 17620 loss: 2.5981 loss_prob: 1.6193 loss_thr: 0.7140 loss_db: 0.2648 2022/11/01 14:06:55 - mmengine - INFO - Epoch(train) [110][15/63] lr: 1.0964e-03 eta: 12:57:50 time: 0.5607 data_time: 0.0051 memory: 17620 loss: 2.8247 loss_prob: 1.7947 loss_thr: 0.7199 loss_db: 0.3101 2022/11/01 14:06:58 - mmengine - INFO - Epoch(train) [110][20/63] lr: 1.0964e-03 eta: 12:57:36 time: 0.6067 data_time: 0.0071 memory: 17620 loss: 2.6664 loss_prob: 1.6796 loss_thr: 0.7034 loss_db: 0.2834 2022/11/01 14:07:01 - mmengine - INFO - Epoch(train) [110][25/63] lr: 1.0964e-03 eta: 12:57:36 time: 0.6210 data_time: 0.0244 memory: 17620 loss: 2.4621 loss_prob: 1.5180 loss_thr: 0.7018 loss_db: 0.2424 2022/11/01 14:07:04 - mmengine - INFO - Epoch(train) [110][30/63] lr: 1.0964e-03 eta: 12:57:25 time: 0.6286 data_time: 0.0486 memory: 17620 loss: 2.4291 loss_prob: 1.4947 loss_thr: 0.6957 loss_db: 0.2387 2022/11/01 14:07:08 - mmengine - INFO - Epoch(train) [110][35/63] lr: 1.0964e-03 eta: 12:57:25 time: 0.6828 data_time: 0.0312 memory: 17620 loss: 2.6879 loss_prob: 1.6712 loss_thr: 0.7450 loss_db: 0.2717 2022/11/01 14:07:11 - mmengine - INFO - Epoch(train) [110][40/63] lr: 1.0964e-03 eta: 12:57:13 time: 0.6342 data_time: 0.0054 memory: 17620 loss: 2.7006 loss_prob: 1.6761 loss_thr: 0.7496 loss_db: 0.2748 2022/11/01 14:07:14 - mmengine - INFO - Epoch(train) [110][45/63] lr: 1.0964e-03 eta: 12:57:13 time: 0.6369 data_time: 0.0082 memory: 17620 loss: 2.6571 loss_prob: 1.6387 loss_thr: 0.7439 loss_db: 0.2745 2022/11/01 14:07:17 - mmengine - INFO - Epoch(train) [110][50/63] lr: 1.0964e-03 eta: 12:57:04 time: 0.6538 data_time: 0.0187 memory: 17620 loss: 2.7671 loss_prob: 1.6998 loss_thr: 0.7796 loss_db: 0.2876 2022/11/01 14:07:20 - mmengine - INFO - Epoch(train) [110][55/63] lr: 1.0964e-03 eta: 12:57:04 time: 0.5908 data_time: 0.0232 memory: 17620 loss: 2.9175 loss_prob: 1.8303 loss_thr: 0.7794 loss_db: 0.3078 2022/11/01 14:07:23 - mmengine - INFO - Epoch(train) [110][60/63] lr: 1.0964e-03 eta: 12:56:48 time: 0.5869 data_time: 0.0128 memory: 17620 loss: 3.1813 loss_prob: 2.0360 loss_thr: 0.7823 loss_db: 0.3630 2022/11/01 14:07:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:07:29 - mmengine - INFO - Epoch(train) [111][5/63] lr: 1.1064e-03 eta: 12:56:48 time: 0.7650 data_time: 0.1832 memory: 17620 loss: 2.7324 loss_prob: 1.7184 loss_thr: 0.7218 loss_db: 0.2922 2022/11/01 14:07:32 - mmengine - INFO - Epoch(train) [111][10/63] lr: 1.1064e-03 eta: 12:56:24 time: 0.7290 data_time: 0.1898 memory: 17620 loss: 2.7690 loss_prob: 1.7344 loss_thr: 0.7520 loss_db: 0.2827 2022/11/01 14:07:35 - mmengine - INFO - Epoch(train) [111][15/63] lr: 1.1064e-03 eta: 12:56:24 time: 0.5519 data_time: 0.0141 memory: 17620 loss: 2.9567 loss_prob: 1.8633 loss_thr: 0.7832 loss_db: 0.3103 2022/11/01 14:07:38 - mmengine - INFO - Epoch(train) [111][20/63] lr: 1.1064e-03 eta: 12:56:08 time: 0.5886 data_time: 0.0107 memory: 17620 loss: 2.9221 loss_prob: 1.8479 loss_thr: 0.7638 loss_db: 0.3103 2022/11/01 14:07:41 - mmengine - INFO - Epoch(train) [111][25/63] lr: 1.1064e-03 eta: 12:56:08 time: 0.6066 data_time: 0.0235 memory: 17620 loss: 3.0093 loss_prob: 1.8940 loss_thr: 0.7889 loss_db: 0.3264 2022/11/01 14:07:45 - mmengine - INFO - Epoch(train) [111][30/63] lr: 1.1064e-03 eta: 12:56:02 time: 0.6855 data_time: 0.0359 memory: 17620 loss: 2.8426 loss_prob: 1.7778 loss_thr: 0.7617 loss_db: 0.3031 2022/11/01 14:07:48 - mmengine - INFO - Epoch(train) [111][35/63] lr: 1.1064e-03 eta: 12:56:02 time: 0.6796 data_time: 0.0282 memory: 17620 loss: 2.9300 loss_prob: 1.8544 loss_thr: 0.7645 loss_db: 0.3111 2022/11/01 14:07:51 - mmengine - INFO - Epoch(train) [111][40/63] lr: 1.1064e-03 eta: 12:55:49 time: 0.6125 data_time: 0.0147 memory: 17620 loss: 3.1839 loss_prob: 2.0341 loss_thr: 0.8004 loss_db: 0.3494 2022/11/01 14:07:54 - mmengine - INFO - Epoch(train) [111][45/63] lr: 1.1064e-03 eta: 12:55:49 time: 0.5990 data_time: 0.0083 memory: 17620 loss: 2.9086 loss_prob: 1.8204 loss_thr: 0.7749 loss_db: 0.3133 2022/11/01 14:07:57 - mmengine - INFO - Epoch(train) [111][50/63] lr: 1.1064e-03 eta: 12:55:31 time: 0.5611 data_time: 0.0143 memory: 17620 loss: 2.9797 loss_prob: 1.8760 loss_thr: 0.7768 loss_db: 0.3269 2022/11/01 14:07:59 - mmengine - INFO - Epoch(train) [111][55/63] lr: 1.1064e-03 eta: 12:55:31 time: 0.5453 data_time: 0.0161 memory: 17620 loss: 2.8832 loss_prob: 1.8143 loss_thr: 0.7623 loss_db: 0.3065 2022/11/01 14:08:02 - mmengine - INFO - Epoch(train) [111][60/63] lr: 1.1064e-03 eta: 12:55:12 time: 0.5592 data_time: 0.0122 memory: 17620 loss: 2.5418 loss_prob: 1.5558 loss_thr: 0.7340 loss_db: 0.2520 2022/11/01 14:08:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:08:08 - mmengine - INFO - Epoch(train) [112][5/63] lr: 1.1165e-03 eta: 12:55:12 time: 0.7432 data_time: 0.1940 memory: 17620 loss: 2.5311 loss_prob: 1.5583 loss_thr: 0.7190 loss_db: 0.2539 2022/11/01 14:08:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:08:11 - mmengine - INFO - Epoch(train) [112][10/63] lr: 1.1165e-03 eta: 12:54:53 time: 0.7709 data_time: 0.1980 memory: 17620 loss: 2.5272 loss_prob: 1.5545 loss_thr: 0.7220 loss_db: 0.2507 2022/11/01 14:08:14 - mmengine - INFO - Epoch(train) [112][15/63] lr: 1.1165e-03 eta: 12:54:53 time: 0.5746 data_time: 0.0112 memory: 17620 loss: 2.5440 loss_prob: 1.5614 loss_thr: 0.7327 loss_db: 0.2500 2022/11/01 14:08:17 - mmengine - INFO - Epoch(train) [112][20/63] lr: 1.1165e-03 eta: 12:54:34 time: 0.5606 data_time: 0.0066 memory: 17620 loss: 2.5713 loss_prob: 1.5707 loss_thr: 0.7454 loss_db: 0.2552 2022/11/01 14:08:20 - mmengine - INFO - Epoch(train) [112][25/63] lr: 1.1165e-03 eta: 12:54:34 time: 0.5874 data_time: 0.0285 memory: 17620 loss: 2.4949 loss_prob: 1.5299 loss_thr: 0.7152 loss_db: 0.2498 2022/11/01 14:08:23 - mmengine - INFO - Epoch(train) [112][30/63] lr: 1.1165e-03 eta: 12:54:20 time: 0.5974 data_time: 0.0319 memory: 17620 loss: 2.5789 loss_prob: 1.6015 loss_thr: 0.7171 loss_db: 0.2603 2022/11/01 14:08:26 - mmengine - INFO - Epoch(train) [112][35/63] lr: 1.1165e-03 eta: 12:54:20 time: 0.5691 data_time: 0.0143 memory: 17620 loss: 2.6266 loss_prob: 1.6190 loss_thr: 0.7440 loss_db: 0.2636 2022/11/01 14:08:29 - mmengine - INFO - Epoch(train) [112][40/63] lr: 1.1165e-03 eta: 12:54:03 time: 0.5742 data_time: 0.0119 memory: 17620 loss: 2.5206 loss_prob: 1.5379 loss_thr: 0.7304 loss_db: 0.2523 2022/11/01 14:08:31 - mmengine - INFO - Epoch(train) [112][45/63] lr: 1.1165e-03 eta: 12:54:03 time: 0.5430 data_time: 0.0075 memory: 17620 loss: 2.4473 loss_prob: 1.4880 loss_thr: 0.7187 loss_db: 0.2406 2022/11/01 14:08:34 - mmengine - INFO - Epoch(train) [112][50/63] lr: 1.1165e-03 eta: 12:53:43 time: 0.5398 data_time: 0.0176 memory: 17620 loss: 2.5990 loss_prob: 1.6133 loss_thr: 0.7256 loss_db: 0.2600 2022/11/01 14:08:37 - mmengine - INFO - Epoch(train) [112][55/63] lr: 1.1165e-03 eta: 12:53:43 time: 0.5497 data_time: 0.0196 memory: 17620 loss: 2.7259 loss_prob: 1.7114 loss_thr: 0.7319 loss_db: 0.2827 2022/11/01 14:08:39 - mmengine - INFO - Epoch(train) [112][60/63] lr: 1.1165e-03 eta: 12:53:23 time: 0.5388 data_time: 0.0089 memory: 17620 loss: 2.6963 loss_prob: 1.6588 loss_thr: 0.7619 loss_db: 0.2756 2022/11/01 14:08:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:08:46 - mmengine - INFO - Epoch(train) [113][5/63] lr: 1.1265e-03 eta: 12:53:23 time: 0.7532 data_time: 0.1945 memory: 17620 loss: 2.4736 loss_prob: 1.5320 loss_thr: 0.6966 loss_db: 0.2450 2022/11/01 14:08:49 - mmengine - INFO - Epoch(train) [113][10/63] lr: 1.1265e-03 eta: 12:53:06 time: 0.8026 data_time: 0.1969 memory: 17620 loss: 2.6033 loss_prob: 1.6082 loss_thr: 0.7292 loss_db: 0.2659 2022/11/01 14:08:51 - mmengine - INFO - Epoch(train) [113][15/63] lr: 1.1265e-03 eta: 12:53:06 time: 0.5580 data_time: 0.0092 memory: 17620 loss: 2.7248 loss_prob: 1.6987 loss_thr: 0.7456 loss_db: 0.2805 2022/11/01 14:08:54 - mmengine - INFO - Epoch(train) [113][20/63] lr: 1.1265e-03 eta: 12:52:46 time: 0.5332 data_time: 0.0088 memory: 17620 loss: 2.8809 loss_prob: 1.8120 loss_thr: 0.7666 loss_db: 0.3023 2022/11/01 14:08:57 - mmengine - INFO - Epoch(train) [113][25/63] lr: 1.1265e-03 eta: 12:52:46 time: 0.5684 data_time: 0.0121 memory: 17620 loss: 2.8269 loss_prob: 1.7605 loss_thr: 0.7682 loss_db: 0.2983 2022/11/01 14:09:00 - mmengine - INFO - Epoch(train) [113][30/63] lr: 1.1265e-03 eta: 12:52:34 time: 0.6241 data_time: 0.0361 memory: 17620 loss: 2.5760 loss_prob: 1.5869 loss_thr: 0.7264 loss_db: 0.2627 2022/11/01 14:09:03 - mmengine - INFO - Epoch(train) [113][35/63] lr: 1.1265e-03 eta: 12:52:34 time: 0.6069 data_time: 0.0319 memory: 17620 loss: 2.7575 loss_prob: 1.7084 loss_thr: 0.7588 loss_db: 0.2903 2022/11/01 14:09:06 - mmengine - INFO - Epoch(train) [113][40/63] lr: 1.1265e-03 eta: 12:52:15 time: 0.5543 data_time: 0.0074 memory: 17620 loss: 3.0962 loss_prob: 1.9483 loss_thr: 0.8056 loss_db: 0.3423 2022/11/01 14:09:09 - mmengine - INFO - Epoch(train) [113][45/63] lr: 1.1265e-03 eta: 12:52:15 time: 0.5393 data_time: 0.0086 memory: 17620 loss: 3.0466 loss_prob: 1.9240 loss_thr: 0.7910 loss_db: 0.3316 2022/11/01 14:09:12 - mmengine - INFO - Epoch(train) [113][50/63] lr: 1.1265e-03 eta: 12:52:03 time: 0.6178 data_time: 0.0140 memory: 17620 loss: 2.7813 loss_prob: 1.7438 loss_thr: 0.7497 loss_db: 0.2879 2022/11/01 14:09:15 - mmengine - INFO - Epoch(train) [113][55/63] lr: 1.1265e-03 eta: 12:52:03 time: 0.6454 data_time: 0.0240 memory: 17620 loss: 2.7183 loss_prob: 1.7085 loss_thr: 0.7295 loss_db: 0.2802 2022/11/01 14:09:19 - mmengine - INFO - Epoch(train) [113][60/63] lr: 1.1265e-03 eta: 12:51:53 time: 0.6434 data_time: 0.0182 memory: 17620 loss: 2.8840 loss_prob: 1.8087 loss_thr: 0.7716 loss_db: 0.3037 2022/11/01 14:09:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:09:27 - mmengine - INFO - Epoch(train) [114][5/63] lr: 1.1365e-03 eta: 12:51:53 time: 0.9303 data_time: 0.2199 memory: 17620 loss: 2.9071 loss_prob: 1.8537 loss_thr: 0.7441 loss_db: 0.3093 2022/11/01 14:09:30 - mmengine - INFO - Epoch(train) [114][10/63] lr: 1.1365e-03 eta: 12:51:52 time: 0.9648 data_time: 0.2179 memory: 17620 loss: 2.7052 loss_prob: 1.7288 loss_thr: 0.7023 loss_db: 0.2741 2022/11/01 14:09:33 - mmengine - INFO - Epoch(train) [114][15/63] lr: 1.1365e-03 eta: 12:51:52 time: 0.6197 data_time: 0.0081 memory: 17620 loss: 2.6337 loss_prob: 1.6498 loss_thr: 0.7187 loss_db: 0.2652 2022/11/01 14:09:36 - mmengine - INFO - Epoch(train) [114][20/63] lr: 1.1365e-03 eta: 12:51:40 time: 0.6210 data_time: 0.0155 memory: 17620 loss: 2.7844 loss_prob: 1.7307 loss_thr: 0.7610 loss_db: 0.2928 2022/11/01 14:09:39 - mmengine - INFO - Epoch(train) [114][25/63] lr: 1.1365e-03 eta: 12:51:40 time: 0.6427 data_time: 0.0320 memory: 17620 loss: 2.7811 loss_prob: 1.7527 loss_thr: 0.7339 loss_db: 0.2945 2022/11/01 14:09:42 - mmengine - INFO - Epoch(train) [114][30/63] lr: 1.1365e-03 eta: 12:51:30 time: 0.6430 data_time: 0.0281 memory: 17620 loss: 2.6542 loss_prob: 1.6674 loss_thr: 0.7156 loss_db: 0.2712 2022/11/01 14:09:46 - mmengine - INFO - Epoch(train) [114][35/63] lr: 1.1365e-03 eta: 12:51:30 time: 0.6612 data_time: 0.0079 memory: 17620 loss: 2.6175 loss_prob: 1.6142 loss_thr: 0.7400 loss_db: 0.2632 2022/11/01 14:09:49 - mmengine - INFO - Epoch(train) [114][40/63] lr: 1.1365e-03 eta: 12:51:18 time: 0.6144 data_time: 0.0091 memory: 17620 loss: 2.6054 loss_prob: 1.6048 loss_thr: 0.7344 loss_db: 0.2662 2022/11/01 14:09:52 - mmengine - INFO - Epoch(train) [114][45/63] lr: 1.1365e-03 eta: 12:51:18 time: 0.6091 data_time: 0.0108 memory: 17620 loss: 2.5178 loss_prob: 1.5502 loss_thr: 0.7146 loss_db: 0.2530 2022/11/01 14:09:55 - mmengine - INFO - Epoch(train) [114][50/63] lr: 1.1365e-03 eta: 12:51:05 time: 0.6130 data_time: 0.0194 memory: 17620 loss: 2.6336 loss_prob: 1.6411 loss_thr: 0.7251 loss_db: 0.2675 2022/11/01 14:09:57 - mmengine - INFO - Epoch(train) [114][55/63] lr: 1.1365e-03 eta: 12:51:05 time: 0.5648 data_time: 0.0191 memory: 17620 loss: 2.5708 loss_prob: 1.5852 loss_thr: 0.7278 loss_db: 0.2578 2022/11/01 14:10:01 - mmengine - INFO - Epoch(train) [114][60/63] lr: 1.1365e-03 eta: 12:50:52 time: 0.6155 data_time: 0.0072 memory: 17620 loss: 2.3719 loss_prob: 1.4419 loss_thr: 0.6995 loss_db: 0.2305 2022/11/01 14:10:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:10:08 - mmengine - INFO - Epoch(train) [115][5/63] lr: 1.1466e-03 eta: 12:50:52 time: 0.7844 data_time: 0.1921 memory: 17620 loss: 2.4203 loss_prob: 1.4706 loss_thr: 0.7140 loss_db: 0.2358 2022/11/01 14:10:10 - mmengine - INFO - Epoch(train) [115][10/63] lr: 1.1466e-03 eta: 12:50:33 time: 0.7682 data_time: 0.1889 memory: 17620 loss: 2.4995 loss_prob: 1.5112 loss_thr: 0.7393 loss_db: 0.2490 2022/11/01 14:10:13 - mmengine - INFO - Epoch(train) [115][15/63] lr: 1.1466e-03 eta: 12:50:33 time: 0.5731 data_time: 0.0079 memory: 17620 loss: 2.5968 loss_prob: 1.5969 loss_thr: 0.7364 loss_db: 0.2635 2022/11/01 14:10:16 - mmengine - INFO - Epoch(train) [115][20/63] lr: 1.1466e-03 eta: 12:50:17 time: 0.5793 data_time: 0.0080 memory: 17620 loss: 2.5384 loss_prob: 1.5658 loss_thr: 0.7139 loss_db: 0.2588 2022/11/01 14:10:19 - mmengine - INFO - Epoch(train) [115][25/63] lr: 1.1466e-03 eta: 12:50:17 time: 0.5393 data_time: 0.0113 memory: 17620 loss: 2.5324 loss_prob: 1.5585 loss_thr: 0.7141 loss_db: 0.2598 2022/11/01 14:10:22 - mmengine - INFO - Epoch(train) [115][30/63] lr: 1.1466e-03 eta: 12:49:59 time: 0.5604 data_time: 0.0367 memory: 17620 loss: 2.7009 loss_prob: 1.6833 loss_thr: 0.7338 loss_db: 0.2838 2022/11/01 14:10:24 - mmengine - INFO - Epoch(train) [115][35/63] lr: 1.1466e-03 eta: 12:49:59 time: 0.5654 data_time: 0.0303 memory: 17620 loss: 2.8129 loss_prob: 1.7781 loss_thr: 0.7330 loss_db: 0.3018 2022/11/01 14:10:27 - mmengine - INFO - Epoch(train) [115][40/63] lr: 1.1466e-03 eta: 12:49:39 time: 0.5331 data_time: 0.0070 memory: 17620 loss: 2.9871 loss_prob: 1.9019 loss_thr: 0.7610 loss_db: 0.3242 2022/11/01 14:10:30 - mmengine - INFO - Epoch(train) [115][45/63] lr: 1.1466e-03 eta: 12:49:39 time: 0.5290 data_time: 0.0074 memory: 17620 loss: 3.0242 loss_prob: 1.9243 loss_thr: 0.7666 loss_db: 0.3333 2022/11/01 14:10:32 - mmengine - INFO - Epoch(train) [115][50/63] lr: 1.1466e-03 eta: 12:49:20 time: 0.5487 data_time: 0.0082 memory: 17620 loss: 2.7231 loss_prob: 1.7018 loss_thr: 0.7348 loss_db: 0.2865 2022/11/01 14:10:35 - mmengine - INFO - Epoch(train) [115][55/63] lr: 1.1466e-03 eta: 12:49:20 time: 0.5797 data_time: 0.0221 memory: 17620 loss: 2.5643 loss_prob: 1.5819 loss_thr: 0.7311 loss_db: 0.2514 2022/11/01 14:10:38 - mmengine - INFO - Epoch(train) [115][60/63] lr: 1.1466e-03 eta: 12:49:03 time: 0.5643 data_time: 0.0237 memory: 17620 loss: 2.7673 loss_prob: 1.7211 loss_thr: 0.7670 loss_db: 0.2792 2022/11/01 14:10:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:10:44 - mmengine - INFO - Epoch(train) [116][5/63] lr: 1.1566e-03 eta: 12:49:03 time: 0.7555 data_time: 0.2004 memory: 17620 loss: 2.6168 loss_prob: 1.6093 loss_thr: 0.7502 loss_db: 0.2573 2022/11/01 14:10:47 - mmengine - INFO - Epoch(train) [116][10/63] lr: 1.1566e-03 eta: 12:48:46 time: 0.7874 data_time: 0.2126 memory: 17620 loss: 2.5016 loss_prob: 1.5144 loss_thr: 0.7381 loss_db: 0.2491 2022/11/01 14:10:50 - mmengine - INFO - Epoch(train) [116][15/63] lr: 1.1566e-03 eta: 12:48:46 time: 0.5369 data_time: 0.0183 memory: 17620 loss: 2.5370 loss_prob: 1.5566 loss_thr: 0.7206 loss_db: 0.2598 2022/11/01 14:10:53 - mmengine - INFO - Epoch(train) [116][20/63] lr: 1.1566e-03 eta: 12:48:27 time: 0.5405 data_time: 0.0047 memory: 17620 loss: 2.6990 loss_prob: 1.6672 loss_thr: 0.7509 loss_db: 0.2809 2022/11/01 14:10:56 - mmengine - INFO - Epoch(train) [116][25/63] lr: 1.1566e-03 eta: 12:48:27 time: 0.5671 data_time: 0.0250 memory: 17620 loss: 2.6951 loss_prob: 1.6675 loss_thr: 0.7499 loss_db: 0.2777 2022/11/01 14:10:58 - mmengine - INFO - Epoch(train) [116][30/63] lr: 1.1566e-03 eta: 12:48:08 time: 0.5517 data_time: 0.0247 memory: 17620 loss: 2.6232 loss_prob: 1.6351 loss_thr: 0.7232 loss_db: 0.2649 2022/11/01 14:11:01 - mmengine - INFO - Epoch(train) [116][35/63] lr: 1.1566e-03 eta: 12:48:08 time: 0.5405 data_time: 0.0142 memory: 17620 loss: 2.6325 loss_prob: 1.6355 loss_thr: 0.7321 loss_db: 0.2649 2022/11/01 14:11:04 - mmengine - INFO - Epoch(train) [116][40/63] lr: 1.1566e-03 eta: 12:47:51 time: 0.5611 data_time: 0.0145 memory: 17620 loss: 2.5847 loss_prob: 1.5947 loss_thr: 0.7288 loss_db: 0.2611 2022/11/01 14:11:06 - mmengine - INFO - Epoch(train) [116][45/63] lr: 1.1566e-03 eta: 12:47:51 time: 0.5538 data_time: 0.0046 memory: 17620 loss: 2.7976 loss_prob: 1.7553 loss_thr: 0.7506 loss_db: 0.2918 2022/11/01 14:11:09 - mmengine - INFO - Epoch(train) [116][50/63] lr: 1.1566e-03 eta: 12:47:35 time: 0.5723 data_time: 0.0341 memory: 17620 loss: 2.7010 loss_prob: 1.6905 loss_thr: 0.7300 loss_db: 0.2805 2022/11/01 14:11:12 - mmengine - INFO - Epoch(train) [116][55/63] lr: 1.1566e-03 eta: 12:47:35 time: 0.5773 data_time: 0.0345 memory: 17620 loss: 2.7708 loss_prob: 1.7448 loss_thr: 0.7361 loss_db: 0.2899 2022/11/01 14:11:15 - mmengine - INFO - Epoch(train) [116][60/63] lr: 1.1566e-03 eta: 12:47:18 time: 0.5730 data_time: 0.0083 memory: 17620 loss: 2.9301 loss_prob: 1.8605 loss_thr: 0.7592 loss_db: 0.3104 2022/11/01 14:11:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:11:22 - mmengine - INFO - Epoch(train) [117][5/63] lr: 1.1667e-03 eta: 12:47:18 time: 0.7840 data_time: 0.2097 memory: 17620 loss: 2.6632 loss_prob: 1.6537 loss_thr: 0.7381 loss_db: 0.2715 2022/11/01 14:11:24 - mmengine - INFO - Epoch(train) [117][10/63] lr: 1.1667e-03 eta: 12:47:00 time: 0.7781 data_time: 0.2078 memory: 17620 loss: 2.8683 loss_prob: 1.8096 loss_thr: 0.7499 loss_db: 0.3088 2022/11/01 14:11:27 - mmengine - INFO - Epoch(train) [117][15/63] lr: 1.1667e-03 eta: 12:47:00 time: 0.5389 data_time: 0.0057 memory: 17620 loss: 2.8029 loss_prob: 1.7679 loss_thr: 0.7338 loss_db: 0.3012 2022/11/01 14:11:30 - mmengine - INFO - Epoch(train) [117][20/63] lr: 1.1667e-03 eta: 12:46:41 time: 0.5431 data_time: 0.0055 memory: 17620 loss: 2.5234 loss_prob: 1.5648 loss_thr: 0.7067 loss_db: 0.2519 2022/11/01 14:11:33 - mmengine - INFO - Epoch(train) [117][25/63] lr: 1.1667e-03 eta: 12:46:41 time: 0.5576 data_time: 0.0119 memory: 17620 loss: 2.5663 loss_prob: 1.5966 loss_thr: 0.7088 loss_db: 0.2609 2022/11/01 14:11:36 - mmengine - INFO - Epoch(train) [117][30/63] lr: 1.1667e-03 eta: 12:46:27 time: 0.5948 data_time: 0.0438 memory: 17620 loss: 2.5247 loss_prob: 1.5598 loss_thr: 0.7087 loss_db: 0.2562 2022/11/01 14:11:39 - mmengine - INFO - Epoch(train) [117][35/63] lr: 1.1667e-03 eta: 12:46:27 time: 0.6043 data_time: 0.0368 memory: 17620 loss: 2.5414 loss_prob: 1.5469 loss_thr: 0.7413 loss_db: 0.2532 2022/11/01 14:11:42 - mmengine - INFO - Epoch(train) [117][40/63] lr: 1.1667e-03 eta: 12:46:15 time: 0.6127 data_time: 0.0060 memory: 17620 loss: 2.5232 loss_prob: 1.5321 loss_thr: 0.7430 loss_db: 0.2481 2022/11/01 14:11:45 - mmengine - INFO - Epoch(train) [117][45/63] lr: 1.1667e-03 eta: 12:46:15 time: 0.5909 data_time: 0.0070 memory: 17620 loss: 2.4014 loss_prob: 1.4506 loss_thr: 0.7177 loss_db: 0.2330 2022/11/01 14:11:48 - mmengine - INFO - Epoch(train) [117][50/63] lr: 1.1667e-03 eta: 12:46:01 time: 0.6004 data_time: 0.0217 memory: 17620 loss: 2.5490 loss_prob: 1.5537 loss_thr: 0.7396 loss_db: 0.2557 2022/11/01 14:11:51 - mmengine - INFO - Epoch(train) [117][55/63] lr: 1.1667e-03 eta: 12:46:01 time: 0.6396 data_time: 0.0236 memory: 17620 loss: 2.7871 loss_prob: 1.7527 loss_thr: 0.7384 loss_db: 0.2960 2022/11/01 14:11:55 - mmengine - INFO - Epoch(train) [117][60/63] lr: 1.1667e-03 eta: 12:46:02 time: 0.7489 data_time: 0.0096 memory: 17620 loss: 2.8530 loss_prob: 1.8151 loss_thr: 0.7273 loss_db: 0.3106 2022/11/01 14:11:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:12:02 - mmengine - INFO - Epoch(train) [118][5/63] lr: 1.1767e-03 eta: 12:46:02 time: 0.8244 data_time: 0.2074 memory: 17620 loss: 2.7417 loss_prob: 1.7235 loss_thr: 0.7327 loss_db: 0.2855 2022/11/01 14:12:05 - mmengine - INFO - Epoch(train) [118][10/63] lr: 1.1767e-03 eta: 12:45:46 time: 0.7977 data_time: 0.2058 memory: 17620 loss: 2.8495 loss_prob: 1.8085 loss_thr: 0.7419 loss_db: 0.2991 2022/11/01 14:12:08 - mmengine - INFO - Epoch(train) [118][15/63] lr: 1.1767e-03 eta: 12:45:46 time: 0.5413 data_time: 0.0063 memory: 17620 loss: 2.8613 loss_prob: 1.8133 loss_thr: 0.7391 loss_db: 0.3090 2022/11/01 14:12:11 - mmengine - INFO - Epoch(train) [118][20/63] lr: 1.1767e-03 eta: 12:45:31 time: 0.5866 data_time: 0.0059 memory: 17620 loss: 2.7532 loss_prob: 1.7258 loss_thr: 0.7376 loss_db: 0.2898 2022/11/01 14:12:14 - mmengine - INFO - Epoch(train) [118][25/63] lr: 1.1767e-03 eta: 12:45:31 time: 0.6327 data_time: 0.0132 memory: 17620 loss: 2.4696 loss_prob: 1.5199 loss_thr: 0.7108 loss_db: 0.2389 2022/11/01 14:12:17 - mmengine - INFO - Epoch(train) [118][30/63] lr: 1.1767e-03 eta: 12:45:20 time: 0.6317 data_time: 0.0324 memory: 17620 loss: 2.4893 loss_prob: 1.5452 loss_thr: 0.6979 loss_db: 0.2463 2022/11/01 14:12:20 - mmengine - INFO - Epoch(train) [118][35/63] lr: 1.1767e-03 eta: 12:45:20 time: 0.6020 data_time: 0.0259 memory: 17620 loss: 2.6464 loss_prob: 1.6499 loss_thr: 0.7244 loss_db: 0.2721 2022/11/01 14:12:23 - mmengine - INFO - Epoch(train) [118][40/63] lr: 1.1767e-03 eta: 12:45:04 time: 0.5704 data_time: 0.0056 memory: 17620 loss: 2.5489 loss_prob: 1.5861 loss_thr: 0.7053 loss_db: 0.2575 2022/11/01 14:12:26 - mmengine - INFO - Epoch(train) [118][45/63] lr: 1.1767e-03 eta: 12:45:04 time: 0.5507 data_time: 0.0077 memory: 17620 loss: 2.3391 loss_prob: 1.4490 loss_thr: 0.6626 loss_db: 0.2276 2022/11/01 14:12:29 - mmengine - INFO - Epoch(train) [118][50/63] lr: 1.1767e-03 eta: 12:44:49 time: 0.5784 data_time: 0.0162 memory: 17620 loss: 2.4815 loss_prob: 1.5292 loss_thr: 0.7017 loss_db: 0.2506 2022/11/01 14:12:32 - mmengine - INFO - Epoch(train) [118][55/63] lr: 1.1767e-03 eta: 12:44:49 time: 0.6269 data_time: 0.0222 memory: 17620 loss: 2.5967 loss_prob: 1.5873 loss_thr: 0.7439 loss_db: 0.2656 2022/11/01 14:12:35 - mmengine - INFO - Epoch(train) [118][60/63] lr: 1.1767e-03 eta: 12:44:37 time: 0.6164 data_time: 0.0140 memory: 17620 loss: 2.5419 loss_prob: 1.5543 loss_thr: 0.7329 loss_db: 0.2546 2022/11/01 14:12:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:12:41 - mmengine - INFO - Epoch(train) [119][5/63] lr: 1.1867e-03 eta: 12:44:37 time: 0.7332 data_time: 0.2016 memory: 17620 loss: 2.5078 loss_prob: 1.5589 loss_thr: 0.6938 loss_db: 0.2551 2022/11/01 14:12:44 - mmengine - INFO - Epoch(train) [119][10/63] lr: 1.1867e-03 eta: 12:44:15 time: 0.7305 data_time: 0.2000 memory: 17620 loss: 2.5751 loss_prob: 1.5981 loss_thr: 0.7141 loss_db: 0.2629 2022/11/01 14:12:46 - mmengine - INFO - Epoch(train) [119][15/63] lr: 1.1867e-03 eta: 12:44:15 time: 0.5349 data_time: 0.0108 memory: 17620 loss: 2.4166 loss_prob: 1.4641 loss_thr: 0.7155 loss_db: 0.2370 2022/11/01 14:12:49 - mmengine - INFO - Epoch(train) [119][20/63] lr: 1.1867e-03 eta: 12:43:56 time: 0.5405 data_time: 0.0121 memory: 17620 loss: 2.5186 loss_prob: 1.5396 loss_thr: 0.7299 loss_db: 0.2492 2022/11/01 14:12:52 - mmengine - INFO - Epoch(train) [119][25/63] lr: 1.1867e-03 eta: 12:43:56 time: 0.5387 data_time: 0.0145 memory: 17620 loss: 2.6514 loss_prob: 1.6513 loss_thr: 0.7353 loss_db: 0.2648 2022/11/01 14:12:55 - mmengine - INFO - Epoch(train) [119][30/63] lr: 1.1867e-03 eta: 12:43:42 time: 0.5886 data_time: 0.0320 memory: 17620 loss: 2.3968 loss_prob: 1.4613 loss_thr: 0.7029 loss_db: 0.2327 2022/11/01 14:12:58 - mmengine - INFO - Epoch(train) [119][35/63] lr: 1.1867e-03 eta: 12:43:42 time: 0.5884 data_time: 0.0252 memory: 17620 loss: 2.3770 loss_prob: 1.4360 loss_thr: 0.7056 loss_db: 0.2354 2022/11/01 14:13:00 - mmengine - INFO - Epoch(train) [119][40/63] lr: 1.1867e-03 eta: 12:43:23 time: 0.5419 data_time: 0.0079 memory: 17620 loss: 2.4317 loss_prob: 1.4866 loss_thr: 0.7000 loss_db: 0.2452 2022/11/01 14:13:03 - mmengine - INFO - Epoch(train) [119][45/63] lr: 1.1867e-03 eta: 12:43:23 time: 0.5264 data_time: 0.0074 memory: 17620 loss: 2.5262 loss_prob: 1.5776 loss_thr: 0.6839 loss_db: 0.2647 2022/11/01 14:13:06 - mmengine - INFO - Epoch(train) [119][50/63] lr: 1.1867e-03 eta: 12:43:05 time: 0.5511 data_time: 0.0249 memory: 17620 loss: 3.0012 loss_prob: 1.9456 loss_thr: 0.7177 loss_db: 0.3379 2022/11/01 14:13:09 - mmengine - INFO - Epoch(train) [119][55/63] lr: 1.1867e-03 eta: 12:43:05 time: 0.5727 data_time: 0.0260 memory: 17620 loss: 3.1881 loss_prob: 2.0558 loss_thr: 0.7832 loss_db: 0.3491 2022/11/01 14:13:12 - mmengine - INFO - Epoch(train) [119][60/63] lr: 1.1867e-03 eta: 12:42:50 time: 0.5751 data_time: 0.0082 memory: 17620 loss: 3.1670 loss_prob: 2.0015 loss_thr: 0.8143 loss_db: 0.3512 2022/11/01 14:13:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:13:18 - mmengine - INFO - Epoch(train) [120][5/63] lr: 1.1968e-03 eta: 12:42:50 time: 0.7319 data_time: 0.1783 memory: 17620 loss: 2.8246 loss_prob: 1.7739 loss_thr: 0.7539 loss_db: 0.2968 2022/11/01 14:13:21 - mmengine - INFO - Epoch(train) [120][10/63] lr: 1.1968e-03 eta: 12:42:29 time: 0.7423 data_time: 0.1878 memory: 17620 loss: 2.7824 loss_prob: 1.7354 loss_thr: 0.7506 loss_db: 0.2964 2022/11/01 14:13:23 - mmengine - INFO - Epoch(train) [120][15/63] lr: 1.1968e-03 eta: 12:42:29 time: 0.5598 data_time: 0.0158 memory: 17620 loss: 2.9710 loss_prob: 1.8854 loss_thr: 0.7558 loss_db: 0.3298 2022/11/01 14:13:26 - mmengine - INFO - Epoch(train) [120][20/63] lr: 1.1968e-03 eta: 12:42:11 time: 0.5440 data_time: 0.0052 memory: 17620 loss: 3.0823 loss_prob: 1.9601 loss_thr: 0.7744 loss_db: 0.3477 2022/11/01 14:13:29 - mmengine - INFO - Epoch(train) [120][25/63] lr: 1.1968e-03 eta: 12:42:11 time: 0.5589 data_time: 0.0220 memory: 17620 loss: 3.1233 loss_prob: 1.9797 loss_thr: 0.7914 loss_db: 0.3522 2022/11/01 14:13:32 - mmengine - INFO - Epoch(train) [120][30/63] lr: 1.1968e-03 eta: 12:41:54 time: 0.5569 data_time: 0.0271 memory: 17620 loss: 2.8543 loss_prob: 1.8057 loss_thr: 0.7399 loss_db: 0.3087 2022/11/01 14:13:34 - mmengine - INFO - Epoch(train) [120][35/63] lr: 1.1968e-03 eta: 12:41:54 time: 0.5437 data_time: 0.0163 memory: 17620 loss: 2.6927 loss_prob: 1.6767 loss_thr: 0.7404 loss_db: 0.2756 2022/11/01 14:13:37 - mmengine - INFO - Epoch(train) [120][40/63] lr: 1.1968e-03 eta: 12:41:34 time: 0.5332 data_time: 0.0105 memory: 17620 loss: 2.7450 loss_prob: 1.7036 loss_thr: 0.7623 loss_db: 0.2791 2022/11/01 14:13:40 - mmengine - INFO - Epoch(train) [120][45/63] lr: 1.1968e-03 eta: 12:41:34 time: 0.5291 data_time: 0.0057 memory: 17620 loss: 2.8186 loss_prob: 1.7807 loss_thr: 0.7401 loss_db: 0.2978 2022/11/01 14:13:43 - mmengine - INFO - Epoch(train) [120][50/63] lr: 1.1968e-03 eta: 12:41:21 time: 0.5930 data_time: 0.0158 memory: 17620 loss: 2.7917 loss_prob: 1.7587 loss_thr: 0.7411 loss_db: 0.2920 2022/11/01 14:13:45 - mmengine - INFO - Epoch(train) [120][55/63] lr: 1.1968e-03 eta: 12:41:21 time: 0.5880 data_time: 0.0190 memory: 17620 loss: 2.6954 loss_prob: 1.6708 loss_thr: 0.7519 loss_db: 0.2727 2022/11/01 14:13:48 - mmengine - INFO - Epoch(train) [120][60/63] lr: 1.1968e-03 eta: 12:41:02 time: 0.5390 data_time: 0.0137 memory: 17620 loss: 2.6516 loss_prob: 1.6445 loss_thr: 0.7406 loss_db: 0.2665 2022/11/01 14:13:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:13:50 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/11/01 14:13:58 - mmengine - INFO - Epoch(val) [120][5/32] eta: 12:41:02 time: 0.6241 data_time: 0.0801 memory: 17620 2022/11/01 14:14:01 - mmengine - INFO - Epoch(val) [120][10/32] eta: 0:00:15 time: 0.7179 data_time: 0.1051 memory: 15725 2022/11/01 14:14:05 - mmengine - INFO - Epoch(val) [120][15/32] eta: 0:00:15 time: 0.6545 data_time: 0.0504 memory: 15725 2022/11/01 14:14:08 - mmengine - INFO - Epoch(val) [120][20/32] eta: 0:00:07 time: 0.6539 data_time: 0.0514 memory: 15725 2022/11/01 14:14:12 - mmengine - INFO - Epoch(val) [120][25/32] eta: 0:00:07 time: 0.6932 data_time: 0.0593 memory: 15725 2022/11/01 14:14:15 - mmengine - INFO - Epoch(val) [120][30/32] eta: 0:00:01 time: 0.6760 data_time: 0.0355 memory: 15725 2022/11/01 14:14:15 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.6914, precision: 0.3556, hmean: 0.4697 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.6909, precision: 0.5270, hmean: 0.5979 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.6846, precision: 0.6382, hmean: 0.6606 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.6596, precision: 0.7401, hmean: 0.6976 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.5272, precision: 0.8649, hmean: 0.6551 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0645, precision: 0.9853, hmean: 0.1211 2022/11/01 14:14:16 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 14:14:16 - mmengine - INFO - Epoch(val) [120][32/32] icdar/precision: 0.7401 icdar/recall: 0.6596 icdar/hmean: 0.6976 2022/11/01 14:14:21 - mmengine - INFO - Epoch(train) [121][5/63] lr: 1.2068e-03 eta: 0:00:01 time: 0.8138 data_time: 0.2014 memory: 17620 loss: 2.7198 loss_prob: 1.7210 loss_thr: 0.7136 loss_db: 0.2851 2022/11/01 14:14:24 - mmengine - INFO - Epoch(train) [121][10/63] lr: 1.2068e-03 eta: 12:40:51 time: 0.8429 data_time: 0.2035 memory: 17620 loss: 2.8768 loss_prob: 1.8469 loss_thr: 0.7228 loss_db: 0.3072 2022/11/01 14:14:27 - mmengine - INFO - Epoch(train) [121][15/63] lr: 1.2068e-03 eta: 12:40:51 time: 0.5851 data_time: 0.0078 memory: 17620 loss: 2.6984 loss_prob: 1.6885 loss_thr: 0.7264 loss_db: 0.2834 2022/11/01 14:14:30 - mmengine - INFO - Epoch(train) [121][20/63] lr: 1.2068e-03 eta: 12:40:38 time: 0.6043 data_time: 0.0064 memory: 17620 loss: 2.5380 loss_prob: 1.5534 loss_thr: 0.7264 loss_db: 0.2582 2022/11/01 14:14:34 - mmengine - INFO - Epoch(train) [121][25/63] lr: 1.2068e-03 eta: 12:40:38 time: 0.6665 data_time: 0.0147 memory: 17620 loss: 2.5606 loss_prob: 1.5875 loss_thr: 0.7122 loss_db: 0.2608 2022/11/01 14:14:37 - mmengine - INFO - Epoch(train) [121][30/63] lr: 1.2068e-03 eta: 12:40:33 time: 0.6912 data_time: 0.0307 memory: 17620 loss: 2.6541 loss_prob: 1.6671 loss_thr: 0.7081 loss_db: 0.2790 2022/11/01 14:14:40 - mmengine - INFO - Epoch(train) [121][35/63] lr: 1.2068e-03 eta: 12:40:33 time: 0.5949 data_time: 0.0235 memory: 17620 loss: 2.7405 loss_prob: 1.7246 loss_thr: 0.7300 loss_db: 0.2858 2022/11/01 14:14:43 - mmengine - INFO - Epoch(train) [121][40/63] lr: 1.2068e-03 eta: 12:40:21 time: 0.6093 data_time: 0.0063 memory: 17620 loss: 3.0633 loss_prob: 1.9541 loss_thr: 0.7789 loss_db: 0.3304 2022/11/01 14:14:46 - mmengine - INFO - Epoch(train) [121][45/63] lr: 1.2068e-03 eta: 12:40:21 time: 0.6234 data_time: 0.0050 memory: 17620 loss: 3.0062 loss_prob: 1.9142 loss_thr: 0.7619 loss_db: 0.3301 2022/11/01 14:14:49 - mmengine - INFO - Epoch(train) [121][50/63] lr: 1.2068e-03 eta: 12:40:09 time: 0.6185 data_time: 0.0097 memory: 17620 loss: 2.8539 loss_prob: 1.8130 loss_thr: 0.7305 loss_db: 0.3104 2022/11/01 14:14:52 - mmengine - INFO - Epoch(train) [121][55/63] lr: 1.2068e-03 eta: 12:40:09 time: 0.5935 data_time: 0.0205 memory: 17620 loss: 2.9699 loss_prob: 1.8907 loss_thr: 0.7472 loss_db: 0.3320 2022/11/01 14:14:55 - mmengine - INFO - Epoch(train) [121][60/63] lr: 1.2068e-03 eta: 12:39:53 time: 0.5638 data_time: 0.0171 memory: 17620 loss: 2.8400 loss_prob: 1.7905 loss_thr: 0.7376 loss_db: 0.3119 2022/11/01 14:14:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:15:01 - mmengine - INFO - Epoch(train) [122][5/63] lr: 1.2169e-03 eta: 12:39:53 time: 0.7749 data_time: 0.1890 memory: 17620 loss: 2.7392 loss_prob: 1.7262 loss_thr: 0.7183 loss_db: 0.2948 2022/11/01 14:15:04 - mmengine - INFO - Epoch(train) [122][10/63] lr: 1.2169e-03 eta: 12:39:38 time: 0.7937 data_time: 0.2001 memory: 17620 loss: 2.8664 loss_prob: 1.8247 loss_thr: 0.7330 loss_db: 0.3087 2022/11/01 14:15:07 - mmengine - INFO - Epoch(train) [122][15/63] lr: 1.2169e-03 eta: 12:39:38 time: 0.5657 data_time: 0.0190 memory: 17620 loss: 2.8427 loss_prob: 1.7966 loss_thr: 0.7463 loss_db: 0.2998 2022/11/01 14:15:10 - mmengine - INFO - Epoch(train) [122][20/63] lr: 1.2169e-03 eta: 12:39:21 time: 0.5562 data_time: 0.0050 memory: 17620 loss: 2.7234 loss_prob: 1.7016 loss_thr: 0.7396 loss_db: 0.2821 2022/11/01 14:15:13 - mmengine - INFO - Epoch(train) [122][25/63] lr: 1.2169e-03 eta: 12:39:21 time: 0.5576 data_time: 0.0091 memory: 17620 loss: 2.6680 loss_prob: 1.6757 loss_thr: 0.7194 loss_db: 0.2729 2022/11/01 14:15:16 - mmengine - INFO - Epoch(train) [122][30/63] lr: 1.2169e-03 eta: 12:39:06 time: 0.5781 data_time: 0.0348 memory: 17620 loss: 2.5022 loss_prob: 1.5475 loss_thr: 0.7032 loss_db: 0.2515 2022/11/01 14:15:18 - mmengine - INFO - Epoch(train) [122][35/63] lr: 1.2169e-03 eta: 12:39:06 time: 0.5741 data_time: 0.0316 memory: 17620 loss: 2.4397 loss_prob: 1.4963 loss_thr: 0.6963 loss_db: 0.2470 2022/11/01 14:15:21 - mmengine - INFO - Epoch(train) [122][40/63] lr: 1.2169e-03 eta: 12:38:48 time: 0.5428 data_time: 0.0055 memory: 17620 loss: 2.5271 loss_prob: 1.5662 loss_thr: 0.7028 loss_db: 0.2581 2022/11/01 14:15:24 - mmengine - INFO - Epoch(train) [122][45/63] lr: 1.2169e-03 eta: 12:38:48 time: 0.5331 data_time: 0.0043 memory: 17620 loss: 2.5317 loss_prob: 1.5676 loss_thr: 0.7122 loss_db: 0.2519 2022/11/01 14:15:27 - mmengine - INFO - Epoch(train) [122][50/63] lr: 1.2169e-03 eta: 12:38:29 time: 0.5387 data_time: 0.0136 memory: 17620 loss: 2.6508 loss_prob: 1.6514 loss_thr: 0.7324 loss_db: 0.2669 2022/11/01 14:15:29 - mmengine - INFO - Epoch(train) [122][55/63] lr: 1.2169e-03 eta: 12:38:29 time: 0.5603 data_time: 0.0217 memory: 17620 loss: 2.5416 loss_prob: 1.5664 loss_thr: 0.7242 loss_db: 0.2510 2022/11/01 14:15:32 - mmengine - INFO - Epoch(train) [122][60/63] lr: 1.2169e-03 eta: 12:38:14 time: 0.5758 data_time: 0.0130 memory: 17620 loss: 2.3615 loss_prob: 1.4305 loss_thr: 0.7048 loss_db: 0.2262 2022/11/01 14:15:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:15:38 - mmengine - INFO - Epoch(train) [123][5/63] lr: 1.2269e-03 eta: 12:38:14 time: 0.6955 data_time: 0.1590 memory: 17620 loss: 2.5065 loss_prob: 1.5447 loss_thr: 0.7144 loss_db: 0.2474 2022/11/01 14:15:41 - mmengine - INFO - Epoch(train) [123][10/63] lr: 1.2269e-03 eta: 12:37:54 time: 0.7377 data_time: 0.1716 memory: 17620 loss: 2.4685 loss_prob: 1.5077 loss_thr: 0.7175 loss_db: 0.2432 2022/11/01 14:15:44 - mmengine - INFO - Epoch(train) [123][15/63] lr: 1.2269e-03 eta: 12:37:54 time: 0.5850 data_time: 0.0439 memory: 17620 loss: 2.5764 loss_prob: 1.5852 loss_thr: 0.7311 loss_db: 0.2601 2022/11/01 14:15:47 - mmengine - INFO - Epoch(train) [123][20/63] lr: 1.2269e-03 eta: 12:37:38 time: 0.5632 data_time: 0.0314 memory: 17620 loss: 2.6386 loss_prob: 1.6470 loss_thr: 0.7211 loss_db: 0.2705 2022/11/01 14:15:50 - mmengine - INFO - Epoch(train) [123][25/63] lr: 1.2269e-03 eta: 12:37:38 time: 0.5655 data_time: 0.0141 memory: 17620 loss: 2.6675 loss_prob: 1.6621 loss_thr: 0.7348 loss_db: 0.2706 2022/11/01 14:15:53 - mmengine - INFO - Epoch(train) [123][30/63] lr: 1.2269e-03 eta: 12:37:26 time: 0.6059 data_time: 0.0248 memory: 17620 loss: 2.6612 loss_prob: 1.6559 loss_thr: 0.7341 loss_db: 0.2712 2022/11/01 14:15:55 - mmengine - INFO - Epoch(train) [123][35/63] lr: 1.2269e-03 eta: 12:37:26 time: 0.5693 data_time: 0.0175 memory: 17620 loss: 2.6479 loss_prob: 1.6560 loss_thr: 0.7175 loss_db: 0.2744 2022/11/01 14:15:58 - mmengine - INFO - Epoch(train) [123][40/63] lr: 1.2269e-03 eta: 12:37:09 time: 0.5517 data_time: 0.0116 memory: 17620 loss: 2.6031 loss_prob: 1.6081 loss_thr: 0.7289 loss_db: 0.2660 2022/11/01 14:16:01 - mmengine - INFO - Epoch(train) [123][45/63] lr: 1.2269e-03 eta: 12:37:09 time: 0.5601 data_time: 0.0094 memory: 17620 loss: 2.4219 loss_prob: 1.4677 loss_thr: 0.7185 loss_db: 0.2358 2022/11/01 14:16:04 - mmengine - INFO - Epoch(train) [123][50/63] lr: 1.2269e-03 eta: 12:36:54 time: 0.5807 data_time: 0.0136 memory: 17620 loss: 2.4266 loss_prob: 1.4662 loss_thr: 0.7230 loss_db: 0.2375 2022/11/01 14:16:07 - mmengine - INFO - Epoch(train) [123][55/63] lr: 1.2269e-03 eta: 12:36:54 time: 0.5903 data_time: 0.0211 memory: 17620 loss: 2.4899 loss_prob: 1.5195 loss_thr: 0.7197 loss_db: 0.2508 2022/11/01 14:16:09 - mmengine - INFO - Epoch(train) [123][60/63] lr: 1.2269e-03 eta: 12:36:37 time: 0.5494 data_time: 0.0146 memory: 17620 loss: 2.4668 loss_prob: 1.5184 loss_thr: 0.7036 loss_db: 0.2448 2022/11/01 14:16:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:16:16 - mmengine - INFO - Epoch(train) [124][5/63] lr: 1.2369e-03 eta: 12:36:37 time: 0.7645 data_time: 0.1959 memory: 17620 loss: 2.2910 loss_prob: 1.3855 loss_thr: 0.6833 loss_db: 0.2222 2022/11/01 14:16:19 - mmengine - INFO - Epoch(train) [124][10/63] lr: 1.2369e-03 eta: 12:36:24 time: 0.8251 data_time: 0.1957 memory: 17620 loss: 2.4656 loss_prob: 1.5180 loss_thr: 0.6996 loss_db: 0.2480 2022/11/01 14:16:22 - mmengine - INFO - Epoch(train) [124][15/63] lr: 1.2369e-03 eta: 12:36:24 time: 0.6154 data_time: 0.0079 memory: 17620 loss: 2.4885 loss_prob: 1.5330 loss_thr: 0.7015 loss_db: 0.2540 2022/11/01 14:16:26 - mmengine - INFO - Epoch(train) [124][20/63] lr: 1.2369e-03 eta: 12:36:16 time: 0.6537 data_time: 0.0100 memory: 17620 loss: 2.5028 loss_prob: 1.5463 loss_thr: 0.7036 loss_db: 0.2529 2022/11/01 14:16:29 - mmengine - INFO - Epoch(train) [124][25/63] lr: 1.2369e-03 eta: 12:36:16 time: 0.6801 data_time: 0.0281 memory: 17620 loss: 2.6722 loss_prob: 1.6732 loss_thr: 0.7259 loss_db: 0.2731 2022/11/01 14:16:32 - mmengine - INFO - Epoch(train) [124][30/63] lr: 1.2369e-03 eta: 12:36:10 time: 0.6761 data_time: 0.0314 memory: 17620 loss: 2.7642 loss_prob: 1.7486 loss_thr: 0.7288 loss_db: 0.2867 2022/11/01 14:16:35 - mmengine - INFO - Epoch(train) [124][35/63] lr: 1.2369e-03 eta: 12:36:10 time: 0.6277 data_time: 0.0165 memory: 17620 loss: 2.5981 loss_prob: 1.6218 loss_thr: 0.7123 loss_db: 0.2640 2022/11/01 14:16:38 - mmengine - INFO - Epoch(train) [124][40/63] lr: 1.2369e-03 eta: 12:35:54 time: 0.5615 data_time: 0.0096 memory: 17620 loss: 2.5990 loss_prob: 1.6086 loss_thr: 0.7203 loss_db: 0.2701 2022/11/01 14:16:41 - mmengine - INFO - Epoch(train) [124][45/63] lr: 1.2369e-03 eta: 12:35:54 time: 0.5379 data_time: 0.0072 memory: 17620 loss: 2.5714 loss_prob: 1.5934 loss_thr: 0.7147 loss_db: 0.2633 2022/11/01 14:16:44 - mmengine - INFO - Epoch(train) [124][50/63] lr: 1.2369e-03 eta: 12:35:42 time: 0.6111 data_time: 0.0175 memory: 17620 loss: 2.5287 loss_prob: 1.5808 loss_thr: 0.6986 loss_db: 0.2492 2022/11/01 14:16:47 - mmengine - INFO - Epoch(train) [124][55/63] lr: 1.2369e-03 eta: 12:35:42 time: 0.6378 data_time: 0.0227 memory: 17620 loss: 2.8007 loss_prob: 1.7836 loss_thr: 0.7297 loss_db: 0.2875 2022/11/01 14:16:50 - mmengine - INFO - Epoch(train) [124][60/63] lr: 1.2369e-03 eta: 12:35:27 time: 0.5736 data_time: 0.0123 memory: 17620 loss: 2.8564 loss_prob: 1.8127 loss_thr: 0.7461 loss_db: 0.2976 2022/11/01 14:16:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:16:57 - mmengine - INFO - Epoch(train) [125][5/63] lr: 1.2470e-03 eta: 12:35:27 time: 0.8192 data_time: 0.2236 memory: 17620 loss: 2.6193 loss_prob: 1.6266 loss_thr: 0.7178 loss_db: 0.2749 2022/11/01 14:17:00 - mmengine - INFO - Epoch(train) [125][10/63] lr: 1.2470e-03 eta: 12:35:21 time: 0.8916 data_time: 0.2211 memory: 17620 loss: 2.5768 loss_prob: 1.5913 loss_thr: 0.7218 loss_db: 0.2638 2022/11/01 14:17:03 - mmengine - INFO - Epoch(train) [125][15/63] lr: 1.2470e-03 eta: 12:35:21 time: 0.6033 data_time: 0.0068 memory: 17620 loss: 2.4600 loss_prob: 1.5032 loss_thr: 0.7149 loss_db: 0.2419 2022/11/01 14:17:06 - mmengine - INFO - Epoch(train) [125][20/63] lr: 1.2470e-03 eta: 12:35:04 time: 0.5561 data_time: 0.0078 memory: 17620 loss: 2.4542 loss_prob: 1.5133 loss_thr: 0.6929 loss_db: 0.2480 2022/11/01 14:17:08 - mmengine - INFO - Epoch(train) [125][25/63] lr: 1.2470e-03 eta: 12:35:04 time: 0.5522 data_time: 0.0097 memory: 17620 loss: 2.6855 loss_prob: 1.6984 loss_thr: 0.7006 loss_db: 0.2865 2022/11/01 14:17:12 - mmengine - INFO - Epoch(train) [125][30/63] lr: 1.2470e-03 eta: 12:34:51 time: 0.5869 data_time: 0.0408 memory: 17620 loss: 3.0778 loss_prob: 1.9687 loss_thr: 0.7732 loss_db: 0.3359 2022/11/01 14:17:14 - mmengine - INFO - Epoch(train) [125][35/63] lr: 1.2470e-03 eta: 12:34:51 time: 0.5872 data_time: 0.0366 memory: 17620 loss: 2.9423 loss_prob: 1.8481 loss_thr: 0.7807 loss_db: 0.3135 2022/11/01 14:17:17 - mmengine - INFO - Epoch(train) [125][40/63] lr: 1.2470e-03 eta: 12:34:32 time: 0.5358 data_time: 0.0045 memory: 17620 loss: 2.5495 loss_prob: 1.5717 loss_thr: 0.7217 loss_db: 0.2562 2022/11/01 14:17:20 - mmengine - INFO - Epoch(train) [125][45/63] lr: 1.2470e-03 eta: 12:34:32 time: 0.5392 data_time: 0.0047 memory: 17620 loss: 2.4402 loss_prob: 1.4901 loss_thr: 0.7129 loss_db: 0.2373 2022/11/01 14:17:23 - mmengine - INFO - Epoch(train) [125][50/63] lr: 1.2470e-03 eta: 12:34:21 time: 0.6168 data_time: 0.0249 memory: 17620 loss: 2.4526 loss_prob: 1.5004 loss_thr: 0.7120 loss_db: 0.2402 2022/11/01 14:17:26 - mmengine - INFO - Epoch(train) [125][55/63] lr: 1.2470e-03 eta: 12:34:21 time: 0.6485 data_time: 0.0265 memory: 17620 loss: 2.5290 loss_prob: 1.5541 loss_thr: 0.7242 loss_db: 0.2507 2022/11/01 14:17:29 - mmengine - INFO - Epoch(train) [125][60/63] lr: 1.2470e-03 eta: 12:34:08 time: 0.5970 data_time: 0.0063 memory: 17620 loss: 2.6248 loss_prob: 1.6298 loss_thr: 0.7276 loss_db: 0.2674 2022/11/01 14:17:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:17:36 - mmengine - INFO - Epoch(train) [126][5/63] lr: 1.2570e-03 eta: 12:34:08 time: 0.8016 data_time: 0.2210 memory: 17620 loss: 2.6777 loss_prob: 1.6647 loss_thr: 0.7247 loss_db: 0.2883 2022/11/01 14:17:39 - mmengine - INFO - Epoch(train) [126][10/63] lr: 1.2570e-03 eta: 12:33:55 time: 0.8121 data_time: 0.2197 memory: 17620 loss: 2.6464 loss_prob: 1.6292 loss_thr: 0.7384 loss_db: 0.2788 2022/11/01 14:17:41 - mmengine - INFO - Epoch(train) [126][15/63] lr: 1.2570e-03 eta: 12:33:55 time: 0.5446 data_time: 0.0050 memory: 17620 loss: 2.5238 loss_prob: 1.5558 loss_thr: 0.7066 loss_db: 0.2614 2022/11/01 14:17:44 - mmengine - INFO - Epoch(train) [126][20/63] lr: 1.2570e-03 eta: 12:33:38 time: 0.5441 data_time: 0.0055 memory: 17620 loss: 2.3528 loss_prob: 1.4363 loss_thr: 0.6812 loss_db: 0.2353 2022/11/01 14:17:47 - mmengine - INFO - Epoch(train) [126][25/63] lr: 1.2570e-03 eta: 12:33:38 time: 0.5714 data_time: 0.0221 memory: 17620 loss: 2.5586 loss_prob: 1.5770 loss_thr: 0.7236 loss_db: 0.2580 2022/11/01 14:17:50 - mmengine - INFO - Epoch(train) [126][30/63] lr: 1.2570e-03 eta: 12:33:23 time: 0.5719 data_time: 0.0334 memory: 17620 loss: 2.7828 loss_prob: 1.7162 loss_thr: 0.7795 loss_db: 0.2870 2022/11/01 14:17:52 - mmengine - INFO - Epoch(train) [126][35/63] lr: 1.2570e-03 eta: 12:33:23 time: 0.5279 data_time: 0.0180 memory: 17620 loss: 2.5948 loss_prob: 1.6006 loss_thr: 0.7313 loss_db: 0.2629 2022/11/01 14:17:55 - mmengine - INFO - Epoch(train) [126][40/63] lr: 1.2570e-03 eta: 12:33:04 time: 0.5234 data_time: 0.0059 memory: 17620 loss: 2.6848 loss_prob: 1.7033 loss_thr: 0.6954 loss_db: 0.2861 2022/11/01 14:17:58 - mmengine - INFO - Epoch(train) [126][45/63] lr: 1.2570e-03 eta: 12:33:04 time: 0.5438 data_time: 0.0067 memory: 17620 loss: 2.8147 loss_prob: 1.8038 loss_thr: 0.7061 loss_db: 0.3047 2022/11/01 14:18:01 - mmengine - INFO - Epoch(train) [126][50/63] lr: 1.2570e-03 eta: 12:32:52 time: 0.6107 data_time: 0.0219 memory: 17620 loss: 2.6159 loss_prob: 1.6343 loss_thr: 0.7139 loss_db: 0.2677 2022/11/01 14:18:04 - mmengine - INFO - Epoch(train) [126][55/63] lr: 1.2570e-03 eta: 12:32:52 time: 0.6093 data_time: 0.0232 memory: 17620 loss: 2.6485 loss_prob: 1.6322 loss_thr: 0.7431 loss_db: 0.2732 2022/11/01 14:18:07 - mmengine - INFO - Epoch(train) [126][60/63] lr: 1.2570e-03 eta: 12:32:36 time: 0.5598 data_time: 0.0090 memory: 17620 loss: 2.5358 loss_prob: 1.5593 loss_thr: 0.7174 loss_db: 0.2591 2022/11/01 14:18:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:18:13 - mmengine - INFO - Epoch(train) [127][5/63] lr: 1.2671e-03 eta: 12:32:36 time: 0.7891 data_time: 0.2280 memory: 17620 loss: 2.4280 loss_prob: 1.4934 loss_thr: 0.6891 loss_db: 0.2456 2022/11/01 14:18:16 - mmengine - INFO - Epoch(train) [127][10/63] lr: 1.2671e-03 eta: 12:32:21 time: 0.7929 data_time: 0.2287 memory: 17620 loss: 2.4873 loss_prob: 1.5220 loss_thr: 0.7179 loss_db: 0.2473 2022/11/01 14:18:19 - mmengine - INFO - Epoch(train) [127][15/63] lr: 1.2671e-03 eta: 12:32:21 time: 0.5143 data_time: 0.0057 memory: 17620 loss: 2.4758 loss_prob: 1.5163 loss_thr: 0.7107 loss_db: 0.2488 2022/11/01 14:18:21 - mmengine - INFO - Epoch(train) [127][20/63] lr: 1.2671e-03 eta: 12:32:02 time: 0.5235 data_time: 0.0044 memory: 17620 loss: 2.4046 loss_prob: 1.4754 loss_thr: 0.6890 loss_db: 0.2402 2022/11/01 14:18:24 - mmengine - INFO - Epoch(train) [127][25/63] lr: 1.2671e-03 eta: 12:32:02 time: 0.5786 data_time: 0.0358 memory: 17620 loss: 2.5653 loss_prob: 1.6033 loss_thr: 0.7062 loss_db: 0.2558 2022/11/01 14:18:27 - mmengine - INFO - Epoch(train) [127][30/63] lr: 1.2671e-03 eta: 12:31:47 time: 0.5685 data_time: 0.0363 memory: 17620 loss: 2.6676 loss_prob: 1.6834 loss_thr: 0.7087 loss_db: 0.2756 2022/11/01 14:18:30 - mmengine - INFO - Epoch(train) [127][35/63] lr: 1.2671e-03 eta: 12:31:47 time: 0.5193 data_time: 0.0046 memory: 17620 loss: 2.6027 loss_prob: 1.6113 loss_thr: 0.7217 loss_db: 0.2697 2022/11/01 14:18:32 - mmengine - INFO - Epoch(train) [127][40/63] lr: 1.2671e-03 eta: 12:31:30 time: 0.5376 data_time: 0.0042 memory: 17620 loss: 2.3976 loss_prob: 1.4486 loss_thr: 0.7138 loss_db: 0.2352 2022/11/01 14:18:35 - mmengine - INFO - Epoch(train) [127][45/63] lr: 1.2671e-03 eta: 12:31:30 time: 0.5690 data_time: 0.0079 memory: 17620 loss: 2.2033 loss_prob: 1.3072 loss_thr: 0.6860 loss_db: 0.2100 2022/11/01 14:18:39 - mmengine - INFO - Epoch(train) [127][50/63] lr: 1.2671e-03 eta: 12:31:19 time: 0.6190 data_time: 0.0259 memory: 17620 loss: 2.3161 loss_prob: 1.3947 loss_thr: 0.6969 loss_db: 0.2245 2022/11/01 14:18:42 - mmengine - INFO - Epoch(train) [127][55/63] lr: 1.2671e-03 eta: 12:31:19 time: 0.6318 data_time: 0.0223 memory: 17620 loss: 2.4637 loss_prob: 1.5056 loss_thr: 0.7147 loss_db: 0.2434 2022/11/01 14:18:44 - mmengine - INFO - Epoch(train) [127][60/63] lr: 1.2671e-03 eta: 12:31:04 time: 0.5712 data_time: 0.0047 memory: 17620 loss: 2.4324 loss_prob: 1.4746 loss_thr: 0.7146 loss_db: 0.2432 2022/11/01 14:18:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:18:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:18:51 - mmengine - INFO - Epoch(train) [128][5/63] lr: 1.2771e-03 eta: 12:31:04 time: 0.7525 data_time: 0.2049 memory: 17620 loss: 2.2919 loss_prob: 1.3881 loss_thr: 0.6771 loss_db: 0.2267 2022/11/01 14:18:54 - mmengine - INFO - Epoch(train) [128][10/63] lr: 1.2771e-03 eta: 12:30:51 time: 0.8173 data_time: 0.2051 memory: 17620 loss: 2.3924 loss_prob: 1.4635 loss_thr: 0.6946 loss_db: 0.2343 2022/11/01 14:18:57 - mmengine - INFO - Epoch(train) [128][15/63] lr: 1.2771e-03 eta: 12:30:51 time: 0.6046 data_time: 0.0075 memory: 17620 loss: 2.6657 loss_prob: 1.6660 loss_thr: 0.7255 loss_db: 0.2742 2022/11/01 14:19:00 - mmengine - INFO - Epoch(train) [128][20/63] lr: 1.2771e-03 eta: 12:30:37 time: 0.5736 data_time: 0.0090 memory: 17620 loss: 2.7107 loss_prob: 1.7054 loss_thr: 0.7066 loss_db: 0.2987 2022/11/01 14:19:03 - mmengine - INFO - Epoch(train) [128][25/63] lr: 1.2771e-03 eta: 12:30:37 time: 0.5822 data_time: 0.0291 memory: 17620 loss: 2.4106 loss_prob: 1.4813 loss_thr: 0.6771 loss_db: 0.2522 2022/11/01 14:19:05 - mmengine - INFO - Epoch(train) [128][30/63] lr: 1.2771e-03 eta: 12:30:24 time: 0.5857 data_time: 0.0300 memory: 17620 loss: 2.4103 loss_prob: 1.4761 loss_thr: 0.6944 loss_db: 0.2398 2022/11/01 14:19:08 - mmengine - INFO - Epoch(train) [128][35/63] lr: 1.2771e-03 eta: 12:30:24 time: 0.5490 data_time: 0.0094 memory: 17620 loss: 2.5393 loss_prob: 1.5650 loss_thr: 0.7176 loss_db: 0.2567 2022/11/01 14:19:11 - mmengine - INFO - Epoch(train) [128][40/63] lr: 1.2771e-03 eta: 12:30:09 time: 0.5757 data_time: 0.0210 memory: 17620 loss: 2.5159 loss_prob: 1.5493 loss_thr: 0.7160 loss_db: 0.2506 2022/11/01 14:19:14 - mmengine - INFO - Epoch(train) [128][45/63] lr: 1.2771e-03 eta: 12:30:09 time: 0.6301 data_time: 0.0196 memory: 17620 loss: 2.4987 loss_prob: 1.5470 loss_thr: 0.7039 loss_db: 0.2478 2022/11/01 14:19:18 - mmengine - INFO - Epoch(train) [128][50/63] lr: 1.2771e-03 eta: 12:30:00 time: 0.6409 data_time: 0.0272 memory: 17620 loss: 2.3308 loss_prob: 1.4263 loss_thr: 0.6727 loss_db: 0.2319 2022/11/01 14:19:21 - mmengine - INFO - Epoch(train) [128][55/63] lr: 1.2771e-03 eta: 12:30:00 time: 0.6214 data_time: 0.0265 memory: 17620 loss: 2.2530 loss_prob: 1.3562 loss_thr: 0.6746 loss_db: 0.2222 2022/11/01 14:19:23 - mmengine - INFO - Epoch(train) [128][60/63] lr: 1.2771e-03 eta: 12:29:46 time: 0.5716 data_time: 0.0057 memory: 17620 loss: 2.5468 loss_prob: 1.5722 loss_thr: 0.7175 loss_db: 0.2571 2022/11/01 14:19:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:19:30 - mmengine - INFO - Epoch(train) [129][5/63] lr: 1.2871e-03 eta: 12:29:46 time: 0.7762 data_time: 0.2253 memory: 17620 loss: 2.5803 loss_prob: 1.6074 loss_thr: 0.7051 loss_db: 0.2679 2022/11/01 14:19:33 - mmengine - INFO - Epoch(train) [129][10/63] lr: 1.2871e-03 eta: 12:29:38 time: 0.8740 data_time: 0.2243 memory: 17620 loss: 2.6070 loss_prob: 1.6273 loss_thr: 0.7089 loss_db: 0.2708 2022/11/01 14:19:37 - mmengine - INFO - Epoch(train) [129][15/63] lr: 1.2871e-03 eta: 12:29:38 time: 0.6689 data_time: 0.0071 memory: 17620 loss: 2.6007 loss_prob: 1.6195 loss_thr: 0.7124 loss_db: 0.2688 2022/11/01 14:19:40 - mmengine - INFO - Epoch(train) [129][20/63] lr: 1.2871e-03 eta: 12:29:27 time: 0.6152 data_time: 0.0069 memory: 17620 loss: 2.4962 loss_prob: 1.5304 loss_thr: 0.7137 loss_db: 0.2521 2022/11/01 14:19:43 - mmengine - INFO - Epoch(train) [129][25/63] lr: 1.2871e-03 eta: 12:29:27 time: 0.5957 data_time: 0.0137 memory: 17620 loss: 2.4987 loss_prob: 1.5283 loss_thr: 0.7264 loss_db: 0.2440 2022/11/01 14:19:45 - mmengine - INFO - Epoch(train) [129][30/63] lr: 1.2871e-03 eta: 12:29:13 time: 0.5808 data_time: 0.0338 memory: 17620 loss: 2.5491 loss_prob: 1.5667 loss_thr: 0.7280 loss_db: 0.2543 2022/11/01 14:19:48 - mmengine - INFO - Epoch(train) [129][35/63] lr: 1.2871e-03 eta: 12:29:13 time: 0.5827 data_time: 0.0248 memory: 17620 loss: 2.5722 loss_prob: 1.5752 loss_thr: 0.7356 loss_db: 0.2613 2022/11/01 14:19:51 - mmengine - INFO - Epoch(train) [129][40/63] lr: 1.2871e-03 eta: 12:29:01 time: 0.6043 data_time: 0.0066 memory: 17620 loss: 2.5065 loss_prob: 1.5392 loss_thr: 0.7145 loss_db: 0.2529 2022/11/01 14:19:54 - mmengine - INFO - Epoch(train) [129][45/63] lr: 1.2871e-03 eta: 12:29:01 time: 0.5763 data_time: 0.0068 memory: 17620 loss: 2.4632 loss_prob: 1.5284 loss_thr: 0.6917 loss_db: 0.2430 2022/11/01 14:19:57 - mmengine - INFO - Epoch(train) [129][50/63] lr: 1.2871e-03 eta: 12:28:47 time: 0.5669 data_time: 0.0150 memory: 17620 loss: 2.5956 loss_prob: 1.6258 loss_thr: 0.7110 loss_db: 0.2588 2022/11/01 14:20:00 - mmengine - INFO - Epoch(train) [129][55/63] lr: 1.2871e-03 eta: 12:28:47 time: 0.5766 data_time: 0.0234 memory: 17620 loss: 2.6925 loss_prob: 1.6813 loss_thr: 0.7374 loss_db: 0.2738 2022/11/01 14:20:03 - mmengine - INFO - Epoch(train) [129][60/63] lr: 1.2871e-03 eta: 12:28:30 time: 0.5472 data_time: 0.0131 memory: 17620 loss: 2.5564 loss_prob: 1.5766 loss_thr: 0.7249 loss_db: 0.2549 2022/11/01 14:20:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:20:09 - mmengine - INFO - Epoch(train) [130][5/63] lr: 1.2972e-03 eta: 12:28:30 time: 0.7324 data_time: 0.2069 memory: 17620 loss: 2.8521 loss_prob: 1.7801 loss_thr: 0.7619 loss_db: 0.3100 2022/11/01 14:20:12 - mmengine - INFO - Epoch(train) [130][10/63] lr: 1.2972e-03 eta: 12:28:15 time: 0.7905 data_time: 0.2072 memory: 17620 loss: 2.9635 loss_prob: 1.8862 loss_thr: 0.7547 loss_db: 0.3227 2022/11/01 14:20:15 - mmengine - INFO - Epoch(train) [130][15/63] lr: 1.2972e-03 eta: 12:28:15 time: 0.5652 data_time: 0.0065 memory: 17620 loss: 2.5916 loss_prob: 1.6076 loss_thr: 0.7212 loss_db: 0.2629 2022/11/01 14:20:17 - mmengine - INFO - Epoch(train) [130][20/63] lr: 1.2972e-03 eta: 12:27:58 time: 0.5398 data_time: 0.0069 memory: 17620 loss: 2.6240 loss_prob: 1.6306 loss_thr: 0.7206 loss_db: 0.2729 2022/11/01 14:20:20 - mmengine - INFO - Epoch(train) [130][25/63] lr: 1.2972e-03 eta: 12:27:58 time: 0.5318 data_time: 0.0106 memory: 17620 loss: 2.7927 loss_prob: 1.7567 loss_thr: 0.7387 loss_db: 0.2973 2022/11/01 14:20:23 - mmengine - INFO - Epoch(train) [130][30/63] lr: 1.2972e-03 eta: 12:27:44 time: 0.5792 data_time: 0.0338 memory: 17620 loss: 2.7751 loss_prob: 1.7500 loss_thr: 0.7329 loss_db: 0.2922 2022/11/01 14:20:26 - mmengine - INFO - Epoch(train) [130][35/63] lr: 1.2972e-03 eta: 12:27:44 time: 0.6054 data_time: 0.0289 memory: 17620 loss: 2.5032 loss_prob: 1.5549 loss_thr: 0.6988 loss_db: 0.2495 2022/11/01 14:20:29 - mmengine - INFO - Epoch(train) [130][40/63] lr: 1.2972e-03 eta: 12:27:31 time: 0.5823 data_time: 0.0053 memory: 17620 loss: 2.4649 loss_prob: 1.5314 loss_thr: 0.6880 loss_db: 0.2455 2022/11/01 14:20:31 - mmengine - INFO - Epoch(train) [130][45/63] lr: 1.2972e-03 eta: 12:27:31 time: 0.5514 data_time: 0.0049 memory: 17620 loss: 2.5592 loss_prob: 1.5948 loss_thr: 0.7042 loss_db: 0.2602 2022/11/01 14:20:34 - mmengine - INFO - Epoch(train) [130][50/63] lr: 1.2972e-03 eta: 12:27:14 time: 0.5466 data_time: 0.0148 memory: 17620 loss: 2.5854 loss_prob: 1.5595 loss_thr: 0.7676 loss_db: 0.2583 2022/11/01 14:20:37 - mmengine - INFO - Epoch(train) [130][55/63] lr: 1.2972e-03 eta: 12:27:14 time: 0.5677 data_time: 0.0235 memory: 17620 loss: 2.6425 loss_prob: 1.6079 loss_thr: 0.7657 loss_db: 0.2689 2022/11/01 14:20:40 - mmengine - INFO - Epoch(train) [130][60/63] lr: 1.2972e-03 eta: 12:26:58 time: 0.5462 data_time: 0.0140 memory: 17620 loss: 2.5288 loss_prob: 1.5668 loss_thr: 0.7055 loss_db: 0.2564 2022/11/01 14:20:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:20:46 - mmengine - INFO - Epoch(train) [131][5/63] lr: 1.3072e-03 eta: 12:26:58 time: 0.6993 data_time: 0.2051 memory: 17620 loss: 2.3156 loss_prob: 1.4053 loss_thr: 0.6838 loss_db: 0.2265 2022/11/01 14:20:48 - mmengine - INFO - Epoch(train) [131][10/63] lr: 1.3072e-03 eta: 12:26:38 time: 0.7278 data_time: 0.2068 memory: 17620 loss: 2.3433 loss_prob: 1.4246 loss_thr: 0.6858 loss_db: 0.2329 2022/11/01 14:20:51 - mmengine - INFO - Epoch(train) [131][15/63] lr: 1.3072e-03 eta: 12:26:38 time: 0.5234 data_time: 0.0085 memory: 17620 loss: 2.7636 loss_prob: 1.7537 loss_thr: 0.7171 loss_db: 0.2927 2022/11/01 14:20:54 - mmengine - INFO - Epoch(train) [131][20/63] lr: 1.3072e-03 eta: 12:26:21 time: 0.5397 data_time: 0.0061 memory: 17620 loss: 2.8875 loss_prob: 1.8614 loss_thr: 0.7176 loss_db: 0.3085 2022/11/01 14:20:57 - mmengine - INFO - Epoch(train) [131][25/63] lr: 1.3072e-03 eta: 12:26:21 time: 0.5848 data_time: 0.0329 memory: 17620 loss: 2.7444 loss_prob: 1.7423 loss_thr: 0.7160 loss_db: 0.2862 2022/11/01 14:21:00 - mmengine - INFO - Epoch(train) [131][30/63] lr: 1.3072e-03 eta: 12:26:11 time: 0.6253 data_time: 0.0350 memory: 17620 loss: 2.9917 loss_prob: 1.9222 loss_thr: 0.7541 loss_db: 0.3154 2022/11/01 14:21:04 - mmengine - INFO - Epoch(train) [131][35/63] lr: 1.3072e-03 eta: 12:26:11 time: 0.7325 data_time: 0.0071 memory: 17620 loss: 2.9469 loss_prob: 1.8818 loss_thr: 0.7588 loss_db: 0.3063 2022/11/01 14:21:07 - mmengine - INFO - Epoch(train) [131][40/63] lr: 1.3072e-03 eta: 12:26:10 time: 0.7247 data_time: 0.0050 memory: 17620 loss: 2.5540 loss_prob: 1.5942 loss_thr: 0.7012 loss_db: 0.2586 2022/11/01 14:21:10 - mmengine - INFO - Epoch(train) [131][45/63] lr: 1.3072e-03 eta: 12:26:10 time: 0.5763 data_time: 0.0054 memory: 17620 loss: 2.3050 loss_prob: 1.4135 loss_thr: 0.6662 loss_db: 0.2253 2022/11/01 14:21:13 - mmengine - INFO - Epoch(train) [131][50/63] lr: 1.3072e-03 eta: 12:25:54 time: 0.5577 data_time: 0.0256 memory: 17620 loss: 2.2617 loss_prob: 1.3689 loss_thr: 0.6749 loss_db: 0.2179 2022/11/01 14:21:16 - mmengine - INFO - Epoch(train) [131][55/63] lr: 1.3072e-03 eta: 12:25:54 time: 0.5744 data_time: 0.0248 memory: 17620 loss: 2.4077 loss_prob: 1.4792 loss_thr: 0.6890 loss_db: 0.2396 2022/11/01 14:21:18 - mmengine - INFO - Epoch(train) [131][60/63] lr: 1.3072e-03 eta: 12:25:38 time: 0.5490 data_time: 0.0049 memory: 17620 loss: 2.6173 loss_prob: 1.6417 loss_thr: 0.7019 loss_db: 0.2737 2022/11/01 14:21:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:21:25 - mmengine - INFO - Epoch(train) [132][5/63] lr: 1.3173e-03 eta: 12:25:38 time: 0.7608 data_time: 0.1956 memory: 17620 loss: 2.6992 loss_prob: 1.6829 loss_thr: 0.7350 loss_db: 0.2814 2022/11/01 14:21:29 - mmengine - INFO - Epoch(train) [132][10/63] lr: 1.3173e-03 eta: 12:25:31 time: 0.8824 data_time: 0.1976 memory: 17620 loss: 2.7180 loss_prob: 1.6744 loss_thr: 0.7665 loss_db: 0.2771 2022/11/01 14:21:31 - mmengine - INFO - Epoch(train) [132][15/63] lr: 1.3173e-03 eta: 12:25:31 time: 0.6607 data_time: 0.0092 memory: 17620 loss: 2.6210 loss_prob: 1.6017 loss_thr: 0.7527 loss_db: 0.2666 2022/11/01 14:21:34 - mmengine - INFO - Epoch(train) [132][20/63] lr: 1.3173e-03 eta: 12:25:17 time: 0.5710 data_time: 0.0070 memory: 17620 loss: 2.4203 loss_prob: 1.4841 loss_thr: 0.6958 loss_db: 0.2404 2022/11/01 14:21:37 - mmengine - INFO - Epoch(train) [132][25/63] lr: 1.3173e-03 eta: 12:25:17 time: 0.5736 data_time: 0.0254 memory: 17620 loss: 2.3912 loss_prob: 1.4755 loss_thr: 0.6845 loss_db: 0.2312 2022/11/01 14:21:40 - mmengine - INFO - Epoch(train) [132][30/63] lr: 1.3173e-03 eta: 12:25:07 time: 0.6218 data_time: 0.0390 memory: 17620 loss: 2.5567 loss_prob: 1.5944 loss_thr: 0.7019 loss_db: 0.2604 2022/11/01 14:21:43 - mmengine - INFO - Epoch(train) [132][35/63] lr: 1.3173e-03 eta: 12:25:07 time: 0.6222 data_time: 0.0226 memory: 17620 loss: 2.5050 loss_prob: 1.5530 loss_thr: 0.6970 loss_db: 0.2551 2022/11/01 14:21:47 - mmengine - INFO - Epoch(train) [132][40/63] lr: 1.3173e-03 eta: 12:24:57 time: 0.6273 data_time: 0.0082 memory: 17620 loss: 2.3891 loss_prob: 1.4583 loss_thr: 0.6954 loss_db: 0.2354 2022/11/01 14:21:50 - mmengine - INFO - Epoch(train) [132][45/63] lr: 1.3173e-03 eta: 12:24:57 time: 0.6331 data_time: 0.0055 memory: 17620 loss: 2.4200 loss_prob: 1.4695 loss_thr: 0.7131 loss_db: 0.2373 2022/11/01 14:21:53 - mmengine - INFO - Epoch(train) [132][50/63] lr: 1.3173e-03 eta: 12:24:44 time: 0.5806 data_time: 0.0157 memory: 17620 loss: 2.4568 loss_prob: 1.4994 loss_thr: 0.7116 loss_db: 0.2457 2022/11/01 14:21:56 - mmengine - INFO - Epoch(train) [132][55/63] lr: 1.3173e-03 eta: 12:24:44 time: 0.5833 data_time: 0.0217 memory: 17620 loss: 2.3792 loss_prob: 1.4449 loss_thr: 0.6953 loss_db: 0.2390 2022/11/01 14:21:58 - mmengine - INFO - Epoch(train) [132][60/63] lr: 1.3173e-03 eta: 12:24:30 time: 0.5786 data_time: 0.0127 memory: 17620 loss: 2.2828 loss_prob: 1.3862 loss_thr: 0.6727 loss_db: 0.2240 2022/11/01 14:22:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:22:05 - mmengine - INFO - Epoch(train) [133][5/63] lr: 1.3273e-03 eta: 12:24:30 time: 0.7554 data_time: 0.2342 memory: 17620 loss: 2.5898 loss_prob: 1.6028 loss_thr: 0.7291 loss_db: 0.2579 2022/11/01 14:22:08 - mmengine - INFO - Epoch(train) [133][10/63] lr: 1.3273e-03 eta: 12:24:14 time: 0.7720 data_time: 0.2344 memory: 17620 loss: 2.4760 loss_prob: 1.5199 loss_thr: 0.7113 loss_db: 0.2449 2022/11/01 14:22:11 - mmengine - INFO - Epoch(train) [133][15/63] lr: 1.3273e-03 eta: 12:24:14 time: 0.5608 data_time: 0.0050 memory: 17620 loss: 2.2280 loss_prob: 1.3570 loss_thr: 0.6534 loss_db: 0.2176 2022/11/01 14:22:13 - mmengine - INFO - Epoch(train) [133][20/63] lr: 1.3273e-03 eta: 12:24:00 time: 0.5723 data_time: 0.0048 memory: 17620 loss: 2.1499 loss_prob: 1.2846 loss_thr: 0.6606 loss_db: 0.2047 2022/11/01 14:22:16 - mmengine - INFO - Epoch(train) [133][25/63] lr: 1.3273e-03 eta: 12:24:00 time: 0.5828 data_time: 0.0280 memory: 17620 loss: 2.3869 loss_prob: 1.4441 loss_thr: 0.7089 loss_db: 0.2339 2022/11/01 14:22:20 - mmengine - INFO - Epoch(train) [133][30/63] lr: 1.3273e-03 eta: 12:23:51 time: 0.6271 data_time: 0.0375 memory: 17620 loss: 2.4600 loss_prob: 1.5024 loss_thr: 0.7087 loss_db: 0.2490 2022/11/01 14:22:22 - mmengine - INFO - Epoch(train) [133][35/63] lr: 1.3273e-03 eta: 12:23:51 time: 0.5907 data_time: 0.0143 memory: 17620 loss: 2.4165 loss_prob: 1.4771 loss_thr: 0.6968 loss_db: 0.2427 2022/11/01 14:22:25 - mmengine - INFO - Epoch(train) [133][40/63] lr: 1.3273e-03 eta: 12:23:34 time: 0.5402 data_time: 0.0047 memory: 17620 loss: 2.5395 loss_prob: 1.5697 loss_thr: 0.7120 loss_db: 0.2578 2022/11/01 14:22:28 - mmengine - INFO - Epoch(train) [133][45/63] lr: 1.3273e-03 eta: 12:23:34 time: 0.5392 data_time: 0.0047 memory: 17620 loss: 2.4864 loss_prob: 1.5152 loss_thr: 0.7265 loss_db: 0.2447 2022/11/01 14:22:31 - mmengine - INFO - Epoch(train) [133][50/63] lr: 1.3273e-03 eta: 12:23:20 time: 0.5727 data_time: 0.0220 memory: 17620 loss: 2.4586 loss_prob: 1.5015 loss_thr: 0.7199 loss_db: 0.2371 2022/11/01 14:22:33 - mmengine - INFO - Epoch(train) [133][55/63] lr: 1.3273e-03 eta: 12:23:20 time: 0.5638 data_time: 0.0222 memory: 17620 loss: 2.6464 loss_prob: 1.6532 loss_thr: 0.7288 loss_db: 0.2643 2022/11/01 14:22:36 - mmengine - INFO - Epoch(train) [133][60/63] lr: 1.3273e-03 eta: 12:23:02 time: 0.5209 data_time: 0.0051 memory: 17620 loss: 2.4948 loss_prob: 1.5365 loss_thr: 0.7113 loss_db: 0.2471 2022/11/01 14:22:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:22:42 - mmengine - INFO - Epoch(train) [134][5/63] lr: 1.3373e-03 eta: 12:23:02 time: 0.7443 data_time: 0.2143 memory: 17620 loss: 2.2198 loss_prob: 1.3462 loss_thr: 0.6552 loss_db: 0.2183 2022/11/01 14:22:45 - mmengine - INFO - Epoch(train) [134][10/63] lr: 1.3373e-03 eta: 12:22:46 time: 0.7664 data_time: 0.2155 memory: 17620 loss: 2.2708 loss_prob: 1.3707 loss_thr: 0.6767 loss_db: 0.2234 2022/11/01 14:22:47 - mmengine - INFO - Epoch(train) [134][15/63] lr: 1.3373e-03 eta: 12:22:46 time: 0.5183 data_time: 0.0058 memory: 17620 loss: 2.3496 loss_prob: 1.4163 loss_thr: 0.7028 loss_db: 0.2305 2022/11/01 14:22:50 - mmengine - INFO - Epoch(train) [134][20/63] lr: 1.3373e-03 eta: 12:22:28 time: 0.5254 data_time: 0.0062 memory: 17620 loss: 2.3650 loss_prob: 1.4402 loss_thr: 0.6919 loss_db: 0.2329 2022/11/01 14:22:53 - mmengine - INFO - Epoch(train) [134][25/63] lr: 1.3373e-03 eta: 12:22:28 time: 0.6021 data_time: 0.0352 memory: 17620 loss: 2.3510 loss_prob: 1.4262 loss_thr: 0.6930 loss_db: 0.2318 2022/11/01 14:22:56 - mmengine - INFO - Epoch(train) [134][30/63] lr: 1.3373e-03 eta: 12:22:17 time: 0.6059 data_time: 0.0354 memory: 17620 loss: 2.4130 loss_prob: 1.4552 loss_thr: 0.7150 loss_db: 0.2427 2022/11/01 14:22:59 - mmengine - INFO - Epoch(train) [134][35/63] lr: 1.3373e-03 eta: 12:22:17 time: 0.5637 data_time: 0.0063 memory: 17620 loss: 2.4979 loss_prob: 1.5260 loss_thr: 0.7213 loss_db: 0.2506 2022/11/01 14:23:02 - mmengine - INFO - Epoch(train) [134][40/63] lr: 1.3373e-03 eta: 12:22:03 time: 0.5708 data_time: 0.0046 memory: 17620 loss: 2.5537 loss_prob: 1.5841 loss_thr: 0.7096 loss_db: 0.2600 2022/11/01 14:23:05 - mmengine - INFO - Epoch(train) [134][45/63] lr: 1.3373e-03 eta: 12:22:03 time: 0.5481 data_time: 0.0051 memory: 17620 loss: 2.4622 loss_prob: 1.5289 loss_thr: 0.6827 loss_db: 0.2506 2022/11/01 14:23:08 - mmengine - INFO - Epoch(train) [134][50/63] lr: 1.3373e-03 eta: 12:21:49 time: 0.5684 data_time: 0.0222 memory: 17620 loss: 2.5865 loss_prob: 1.6150 loss_thr: 0.7105 loss_db: 0.2610 2022/11/01 14:23:10 - mmengine - INFO - Epoch(train) [134][55/63] lr: 1.3373e-03 eta: 12:21:49 time: 0.5560 data_time: 0.0231 memory: 17620 loss: 2.5387 loss_prob: 1.5728 loss_thr: 0.7117 loss_db: 0.2543 2022/11/01 14:23:13 - mmengine - INFO - Epoch(train) [134][60/63] lr: 1.3373e-03 eta: 12:21:30 time: 0.5135 data_time: 0.0058 memory: 17620 loss: 2.3064 loss_prob: 1.4000 loss_thr: 0.6792 loss_db: 0.2273 2022/11/01 14:23:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:23:19 - mmengine - INFO - Epoch(train) [135][5/63] lr: 1.3474e-03 eta: 12:21:30 time: 0.7452 data_time: 0.1860 memory: 17620 loss: 2.8533 loss_prob: 1.7978 loss_thr: 0.7406 loss_db: 0.3149 2022/11/01 14:23:22 - mmengine - INFO - Epoch(train) [135][10/63] lr: 1.3474e-03 eta: 12:21:18 time: 0.8166 data_time: 0.1889 memory: 17620 loss: 2.8772 loss_prob: 1.8234 loss_thr: 0.7448 loss_db: 0.3090 2022/11/01 14:23:25 - mmengine - INFO - Epoch(train) [135][15/63] lr: 1.3474e-03 eta: 12:21:18 time: 0.6123 data_time: 0.0136 memory: 17620 loss: 2.6361 loss_prob: 1.6301 loss_thr: 0.7365 loss_db: 0.2695 2022/11/01 14:23:28 - mmengine - INFO - Epoch(train) [135][20/63] lr: 1.3474e-03 eta: 12:21:04 time: 0.5628 data_time: 0.0111 memory: 17620 loss: 2.4871 loss_prob: 1.5102 loss_thr: 0.7285 loss_db: 0.2484 2022/11/01 14:23:31 - mmengine - INFO - Epoch(train) [135][25/63] lr: 1.3474e-03 eta: 12:21:04 time: 0.5541 data_time: 0.0264 memory: 17620 loss: 2.5222 loss_prob: 1.5456 loss_thr: 0.7237 loss_db: 0.2528 2022/11/01 14:23:34 - mmengine - INFO - Epoch(train) [135][30/63] lr: 1.3474e-03 eta: 12:20:50 time: 0.5677 data_time: 0.0259 memory: 17620 loss: 2.5944 loss_prob: 1.6054 loss_thr: 0.7258 loss_db: 0.2632 2022/11/01 14:23:36 - mmengine - INFO - Epoch(train) [135][35/63] lr: 1.3474e-03 eta: 12:20:50 time: 0.5587 data_time: 0.0126 memory: 17620 loss: 2.6361 loss_prob: 1.6590 loss_thr: 0.7078 loss_db: 0.2693 2022/11/01 14:23:39 - mmengine - INFO - Epoch(train) [135][40/63] lr: 1.3474e-03 eta: 12:20:35 time: 0.5640 data_time: 0.0136 memory: 17620 loss: 2.6897 loss_prob: 1.7110 loss_thr: 0.6988 loss_db: 0.2800 2022/11/01 14:23:42 - mmengine - INFO - Epoch(train) [135][45/63] lr: 1.3474e-03 eta: 12:20:35 time: 0.5721 data_time: 0.0098 memory: 17620 loss: 2.7032 loss_prob: 1.7159 loss_thr: 0.7044 loss_db: 0.2829 2022/11/01 14:23:45 - mmengine - INFO - Epoch(train) [135][50/63] lr: 1.3474e-03 eta: 12:20:22 time: 0.5766 data_time: 0.0245 memory: 17620 loss: 2.6389 loss_prob: 1.6367 loss_thr: 0.7332 loss_db: 0.2691 2022/11/01 14:23:48 - mmengine - INFO - Epoch(train) [135][55/63] lr: 1.3474e-03 eta: 12:20:22 time: 0.5615 data_time: 0.0209 memory: 17620 loss: 2.5597 loss_prob: 1.5680 loss_thr: 0.7313 loss_db: 0.2605 2022/11/01 14:23:51 - mmengine - INFO - Epoch(train) [135][60/63] lr: 1.3474e-03 eta: 12:20:06 time: 0.5510 data_time: 0.0079 memory: 17620 loss: 2.7455 loss_prob: 1.7325 loss_thr: 0.7253 loss_db: 0.2876 2022/11/01 14:23:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:23:58 - mmengine - INFO - Epoch(train) [136][5/63] lr: 1.3574e-03 eta: 12:20:06 time: 0.8806 data_time: 0.2334 memory: 17620 loss: 3.0240 loss_prob: 1.9317 loss_thr: 0.7487 loss_db: 0.3435 2022/11/01 14:24:01 - mmengine - INFO - Epoch(train) [136][10/63] lr: 1.3574e-03 eta: 12:20:05 time: 0.9460 data_time: 0.2360 memory: 17620 loss: 2.7654 loss_prob: 1.7217 loss_thr: 0.7492 loss_db: 0.2945 2022/11/01 14:24:05 - mmengine - INFO - Epoch(train) [136][15/63] lr: 1.3574e-03 eta: 12:20:05 time: 0.6440 data_time: 0.0109 memory: 17620 loss: 2.6501 loss_prob: 1.6613 loss_thr: 0.7135 loss_db: 0.2753 2022/11/01 14:24:07 - mmengine - INFO - Epoch(train) [136][20/63] lr: 1.3574e-03 eta: 12:19:53 time: 0.6005 data_time: 0.0052 memory: 17620 loss: 2.6351 loss_prob: 1.6463 loss_thr: 0.7122 loss_db: 0.2765 2022/11/01 14:24:10 - mmengine - INFO - Epoch(train) [136][25/63] lr: 1.3574e-03 eta: 12:19:53 time: 0.5672 data_time: 0.0265 memory: 17620 loss: 2.6878 loss_prob: 1.6709 loss_thr: 0.7386 loss_db: 0.2783 2022/11/01 14:24:13 - mmengine - INFO - Epoch(train) [136][30/63] lr: 1.3574e-03 eta: 12:19:39 time: 0.5634 data_time: 0.0318 memory: 17620 loss: 2.6173 loss_prob: 1.6332 loss_thr: 0.7193 loss_db: 0.2648 2022/11/01 14:24:16 - mmengine - INFO - Epoch(train) [136][35/63] lr: 1.3574e-03 eta: 12:19:39 time: 0.5500 data_time: 0.0135 memory: 17620 loss: 2.4692 loss_prob: 1.5053 loss_thr: 0.7225 loss_db: 0.2414 2022/11/01 14:24:19 - mmengine - INFO - Epoch(train) [136][40/63] lr: 1.3574e-03 eta: 12:19:26 time: 0.5798 data_time: 0.0117 memory: 17620 loss: 2.3858 loss_prob: 1.4345 loss_thr: 0.7206 loss_db: 0.2307 2022/11/01 14:24:21 - mmengine - INFO - Epoch(train) [136][45/63] lr: 1.3574e-03 eta: 12:19:26 time: 0.5658 data_time: 0.0101 memory: 17620 loss: 2.2928 loss_prob: 1.3760 loss_thr: 0.6931 loss_db: 0.2237 2022/11/01 14:24:24 - mmengine - INFO - Epoch(train) [136][50/63] lr: 1.3574e-03 eta: 12:19:09 time: 0.5273 data_time: 0.0186 memory: 17620 loss: 2.2700 loss_prob: 1.3624 loss_thr: 0.6864 loss_db: 0.2213 2022/11/01 14:24:27 - mmengine - INFO - Epoch(train) [136][55/63] lr: 1.3574e-03 eta: 12:19:09 time: 0.5416 data_time: 0.0227 memory: 17620 loss: 2.4674 loss_prob: 1.5201 loss_thr: 0.7011 loss_db: 0.2461 2022/11/01 14:24:30 - mmengine - INFO - Epoch(train) [136][60/63] lr: 1.3574e-03 eta: 12:18:54 time: 0.5593 data_time: 0.0101 memory: 17620 loss: 2.5771 loss_prob: 1.5791 loss_thr: 0.7413 loss_db: 0.2566 2022/11/01 14:24:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:24:37 - mmengine - INFO - Epoch(train) [137][5/63] lr: 1.3675e-03 eta: 12:18:54 time: 0.8714 data_time: 0.2478 memory: 17620 loss: 2.4276 loss_prob: 1.4913 loss_thr: 0.6962 loss_db: 0.2401 2022/11/01 14:24:40 - mmengine - INFO - Epoch(train) [137][10/63] lr: 1.3675e-03 eta: 12:18:48 time: 0.8885 data_time: 0.2454 memory: 17620 loss: 2.4628 loss_prob: 1.5317 loss_thr: 0.6827 loss_db: 0.2485 2022/11/01 14:24:43 - mmengine - INFO - Epoch(train) [137][15/63] lr: 1.3675e-03 eta: 12:18:48 time: 0.5604 data_time: 0.0078 memory: 17620 loss: 2.5832 loss_prob: 1.6163 loss_thr: 0.7003 loss_db: 0.2666 2022/11/01 14:24:46 - mmengine - INFO - Epoch(train) [137][20/63] lr: 1.3675e-03 eta: 12:18:34 time: 0.5755 data_time: 0.0103 memory: 17620 loss: 2.4604 loss_prob: 1.5125 loss_thr: 0.6977 loss_db: 0.2503 2022/11/01 14:24:49 - mmengine - INFO - Epoch(train) [137][25/63] lr: 1.3675e-03 eta: 12:18:34 time: 0.5873 data_time: 0.0406 memory: 17620 loss: 2.3999 loss_prob: 1.4624 loss_thr: 0.6965 loss_db: 0.2410 2022/11/01 14:24:52 - mmengine - INFO - Epoch(train) [137][30/63] lr: 1.3675e-03 eta: 12:18:22 time: 0.5879 data_time: 0.0378 memory: 17620 loss: 2.5038 loss_prob: 1.5301 loss_thr: 0.7230 loss_db: 0.2506 2022/11/01 14:24:55 - mmengine - INFO - Epoch(train) [137][35/63] lr: 1.3675e-03 eta: 12:18:22 time: 0.5761 data_time: 0.0049 memory: 17620 loss: 2.3746 loss_prob: 1.4329 loss_thr: 0.7087 loss_db: 0.2330 2022/11/01 14:24:57 - mmengine - INFO - Epoch(train) [137][40/63] lr: 1.3675e-03 eta: 12:18:06 time: 0.5440 data_time: 0.0066 memory: 17620 loss: 2.3232 loss_prob: 1.4084 loss_thr: 0.6864 loss_db: 0.2283 2022/11/01 14:25:00 - mmengine - INFO - Epoch(train) [137][45/63] lr: 1.3675e-03 eta: 12:18:06 time: 0.5292 data_time: 0.0069 memory: 17620 loss: 2.4583 loss_prob: 1.5146 loss_thr: 0.6991 loss_db: 0.2446 2022/11/01 14:25:03 - mmengine - INFO - Epoch(train) [137][50/63] lr: 1.3675e-03 eta: 12:17:51 time: 0.5496 data_time: 0.0226 memory: 17620 loss: 2.4708 loss_prob: 1.5031 loss_thr: 0.7215 loss_db: 0.2462 2022/11/01 14:25:06 - mmengine - INFO - Epoch(train) [137][55/63] lr: 1.3675e-03 eta: 12:17:51 time: 0.5751 data_time: 0.0235 memory: 17620 loss: 2.4255 loss_prob: 1.4693 loss_thr: 0.7129 loss_db: 0.2433 2022/11/01 14:25:08 - mmengine - INFO - Epoch(train) [137][60/63] lr: 1.3675e-03 eta: 12:17:38 time: 0.5741 data_time: 0.0060 memory: 17620 loss: 2.5378 loss_prob: 1.5686 loss_thr: 0.7143 loss_db: 0.2549 2022/11/01 14:25:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:25:15 - mmengine - INFO - Epoch(train) [138][5/63] lr: 1.3775e-03 eta: 12:17:38 time: 0.7382 data_time: 0.2234 memory: 17620 loss: 2.5523 loss_prob: 1.5700 loss_thr: 0.7302 loss_db: 0.2522 2022/11/01 14:25:17 - mmengine - INFO - Epoch(train) [138][10/63] lr: 1.3775e-03 eta: 12:17:20 time: 0.7476 data_time: 0.2234 memory: 17620 loss: 2.4842 loss_prob: 1.5340 loss_thr: 0.7035 loss_db: 0.2466 2022/11/01 14:25:20 - mmengine - INFO - Epoch(train) [138][15/63] lr: 1.3775e-03 eta: 12:17:20 time: 0.5212 data_time: 0.0055 memory: 17620 loss: 2.5949 loss_prob: 1.6262 loss_thr: 0.7051 loss_db: 0.2635 2022/11/01 14:25:23 - mmengine - INFO - Epoch(train) [138][20/63] lr: 1.3775e-03 eta: 12:17:04 time: 0.5299 data_time: 0.0050 memory: 17620 loss: 2.4848 loss_prob: 1.5332 loss_thr: 0.7074 loss_db: 0.2442 2022/11/01 14:25:26 - mmengine - INFO - Epoch(train) [138][25/63] lr: 1.3775e-03 eta: 12:17:04 time: 0.5780 data_time: 0.0370 memory: 17620 loss: 2.3249 loss_prob: 1.4123 loss_thr: 0.6819 loss_db: 0.2307 2022/11/01 14:25:29 - mmengine - INFO - Epoch(train) [138][30/63] lr: 1.3775e-03 eta: 12:16:52 time: 0.5911 data_time: 0.0472 memory: 17620 loss: 2.4514 loss_prob: 1.5360 loss_thr: 0.6565 loss_db: 0.2589 2022/11/01 14:25:32 - mmengine - INFO - Epoch(train) [138][35/63] lr: 1.3775e-03 eta: 12:16:52 time: 0.5787 data_time: 0.0149 memory: 17620 loss: 2.6515 loss_prob: 1.6747 loss_thr: 0.6933 loss_db: 0.2836 2022/11/01 14:25:34 - mmengine - INFO - Epoch(train) [138][40/63] lr: 1.3775e-03 eta: 12:16:37 time: 0.5615 data_time: 0.0048 memory: 17620 loss: 2.9070 loss_prob: 1.8537 loss_thr: 0.7373 loss_db: 0.3160 2022/11/01 14:25:37 - mmengine - INFO - Epoch(train) [138][45/63] lr: 1.3775e-03 eta: 12:16:37 time: 0.5503 data_time: 0.0047 memory: 17620 loss: 3.1208 loss_prob: 2.0011 loss_thr: 0.7805 loss_db: 0.3393 2022/11/01 14:25:40 - mmengine - INFO - Epoch(train) [138][50/63] lr: 1.3775e-03 eta: 12:16:27 time: 0.6178 data_time: 0.0188 memory: 17620 loss: 2.9971 loss_prob: 1.8851 loss_thr: 0.7982 loss_db: 0.3139 2022/11/01 14:25:44 - mmengine - INFO - Epoch(train) [138][55/63] lr: 1.3775e-03 eta: 12:16:27 time: 0.6406 data_time: 0.0247 memory: 17620 loss: 2.6505 loss_prob: 1.6388 loss_thr: 0.7457 loss_db: 0.2660 2022/11/01 14:25:47 - mmengine - INFO - Epoch(train) [138][60/63] lr: 1.3775e-03 eta: 12:16:18 time: 0.6272 data_time: 0.0119 memory: 17620 loss: 2.7465 loss_prob: 1.7170 loss_thr: 0.7437 loss_db: 0.2858 2022/11/01 14:25:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:25:54 - mmengine - INFO - Epoch(train) [139][5/63] lr: 1.3875e-03 eta: 12:16:18 time: 0.8574 data_time: 0.2003 memory: 17620 loss: 2.5024 loss_prob: 1.5593 loss_thr: 0.6925 loss_db: 0.2506 2022/11/01 14:25:57 - mmengine - INFO - Epoch(train) [139][10/63] lr: 1.3875e-03 eta: 12:16:11 time: 0.8750 data_time: 0.1996 memory: 17620 loss: 2.9076 loss_prob: 1.8603 loss_thr: 0.7318 loss_db: 0.3155 2022/11/01 14:26:00 - mmengine - INFO - Epoch(train) [139][15/63] lr: 1.3875e-03 eta: 12:16:11 time: 0.6496 data_time: 0.0058 memory: 17620 loss: 3.2642 loss_prob: 2.1200 loss_thr: 0.7663 loss_db: 0.3778 2022/11/01 14:26:03 - mmengine - INFO - Epoch(train) [139][20/63] lr: 1.3875e-03 eta: 12:16:02 time: 0.6284 data_time: 0.0099 memory: 17620 loss: 3.0331 loss_prob: 1.9529 loss_thr: 0.7430 loss_db: 0.3372 2022/11/01 14:26:06 - mmengine - INFO - Epoch(train) [139][25/63] lr: 1.3875e-03 eta: 12:16:02 time: 0.5916 data_time: 0.0138 memory: 17620 loss: 2.7762 loss_prob: 1.7533 loss_thr: 0.7367 loss_db: 0.2862 2022/11/01 14:26:10 - mmengine - INFO - Epoch(train) [139][30/63] lr: 1.3875e-03 eta: 12:15:53 time: 0.6332 data_time: 0.0337 memory: 17620 loss: 2.8579 loss_prob: 1.7960 loss_thr: 0.7584 loss_db: 0.3036 2022/11/01 14:26:13 - mmengine - INFO - Epoch(train) [139][35/63] lr: 1.3875e-03 eta: 12:15:53 time: 0.6442 data_time: 0.0296 memory: 17620 loss: 2.8130 loss_prob: 1.7664 loss_thr: 0.7429 loss_db: 0.3037 2022/11/01 14:26:16 - mmengine - INFO - Epoch(train) [139][40/63] lr: 1.3875e-03 eta: 12:15:43 time: 0.6076 data_time: 0.0051 memory: 17620 loss: 2.6259 loss_prob: 1.6378 loss_thr: 0.7165 loss_db: 0.2716 2022/11/01 14:26:19 - mmengine - INFO - Epoch(train) [139][45/63] lr: 1.3875e-03 eta: 12:15:43 time: 0.6080 data_time: 0.0059 memory: 17620 loss: 2.7702 loss_prob: 1.7501 loss_thr: 0.7325 loss_db: 0.2877 2022/11/01 14:26:22 - mmengine - INFO - Epoch(train) [139][50/63] lr: 1.3875e-03 eta: 12:15:34 time: 0.6275 data_time: 0.0211 memory: 17620 loss: 3.0040 loss_prob: 1.9359 loss_thr: 0.7469 loss_db: 0.3211 2022/11/01 14:26:25 - mmengine - INFO - Epoch(train) [139][55/63] lr: 1.3875e-03 eta: 12:15:34 time: 0.5894 data_time: 0.0231 memory: 17620 loss: 2.9563 loss_prob: 1.8911 loss_thr: 0.7399 loss_db: 0.3254 2022/11/01 14:26:28 - mmengine - INFO - Epoch(train) [139][60/63] lr: 1.3875e-03 eta: 12:15:25 time: 0.6361 data_time: 0.0114 memory: 17620 loss: 2.8795 loss_prob: 1.8186 loss_thr: 0.7414 loss_db: 0.3195 2022/11/01 14:26:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:26:36 - mmengine - INFO - Epoch(train) [140][5/63] lr: 1.3976e-03 eta: 12:15:25 time: 0.8745 data_time: 0.2325 memory: 17620 loss: 2.7794 loss_prob: 1.7564 loss_thr: 0.7331 loss_db: 0.2899 2022/11/01 14:26:39 - mmengine - INFO - Epoch(train) [140][10/63] lr: 1.3976e-03 eta: 12:15:19 time: 0.8880 data_time: 0.2314 memory: 17620 loss: 2.6144 loss_prob: 1.6323 loss_thr: 0.7168 loss_db: 0.2653 2022/11/01 14:26:42 - mmengine - INFO - Epoch(train) [140][15/63] lr: 1.3976e-03 eta: 12:15:19 time: 0.5801 data_time: 0.0045 memory: 17620 loss: 2.5197 loss_prob: 1.5622 loss_thr: 0.7086 loss_db: 0.2489 2022/11/01 14:26:44 - mmengine - INFO - Epoch(train) [140][20/63] lr: 1.3976e-03 eta: 12:15:04 time: 0.5543 data_time: 0.0050 memory: 17620 loss: 2.4019 loss_prob: 1.4702 loss_thr: 0.7031 loss_db: 0.2286 2022/11/01 14:26:47 - mmengine - INFO - Epoch(train) [140][25/63] lr: 1.3976e-03 eta: 12:15:04 time: 0.5638 data_time: 0.0326 memory: 17620 loss: 2.5993 loss_prob: 1.6232 loss_thr: 0.7091 loss_db: 0.2670 2022/11/01 14:26:50 - mmengine - INFO - Epoch(train) [140][30/63] lr: 1.3976e-03 eta: 12:14:51 time: 0.5758 data_time: 0.0331 memory: 17620 loss: 2.8993 loss_prob: 1.8471 loss_thr: 0.7390 loss_db: 0.3132 2022/11/01 14:26:53 - mmengine - INFO - Epoch(train) [140][35/63] lr: 1.3976e-03 eta: 12:14:51 time: 0.5650 data_time: 0.0058 memory: 17620 loss: 2.6706 loss_prob: 1.6663 loss_thr: 0.7326 loss_db: 0.2717 2022/11/01 14:26:56 - mmengine - INFO - Epoch(train) [140][40/63] lr: 1.3976e-03 eta: 12:14:36 time: 0.5458 data_time: 0.0056 memory: 17620 loss: 2.5493 loss_prob: 1.5693 loss_thr: 0.7167 loss_db: 0.2633 2022/11/01 14:26:58 - mmengine - INFO - Epoch(train) [140][45/63] lr: 1.3976e-03 eta: 12:14:36 time: 0.5511 data_time: 0.0060 memory: 17620 loss: 2.5236 loss_prob: 1.5614 loss_thr: 0.6949 loss_db: 0.2672 2022/11/01 14:27:01 - mmengine - INFO - Epoch(train) [140][50/63] lr: 1.3976e-03 eta: 12:14:23 time: 0.5774 data_time: 0.0202 memory: 17620 loss: 2.3380 loss_prob: 1.4288 loss_thr: 0.6812 loss_db: 0.2280 2022/11/01 14:27:04 - mmengine - INFO - Epoch(train) [140][55/63] lr: 1.3976e-03 eta: 12:14:23 time: 0.6041 data_time: 0.0209 memory: 17620 loss: 2.6909 loss_prob: 1.6715 loss_thr: 0.7327 loss_db: 0.2867 2022/11/01 14:27:07 - mmengine - INFO - Epoch(train) [140][60/63] lr: 1.3976e-03 eta: 12:14:10 time: 0.5769 data_time: 0.0057 memory: 17620 loss: 2.7464 loss_prob: 1.7048 loss_thr: 0.7454 loss_db: 0.2961 2022/11/01 14:27:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:27:08 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/11/01 14:27:16 - mmengine - INFO - Epoch(val) [140][5/32] eta: 12:14:10 time: 0.6055 data_time: 0.0697 memory: 17620 2022/11/01 14:27:18 - mmengine - INFO - Epoch(val) [140][10/32] eta: 0:00:13 time: 0.6359 data_time: 0.0795 memory: 15725 2022/11/01 14:27:21 - mmengine - INFO - Epoch(val) [140][15/32] eta: 0:00:13 time: 0.5973 data_time: 0.0398 memory: 15725 2022/11/01 14:27:24 - mmengine - INFO - Epoch(val) [140][20/32] eta: 0:00:07 time: 0.5950 data_time: 0.0494 memory: 15725 2022/11/01 14:27:28 - mmengine - INFO - Epoch(val) [140][25/32] eta: 0:00:07 time: 0.6033 data_time: 0.0471 memory: 15725 2022/11/01 14:27:30 - mmengine - INFO - Epoch(val) [140][30/32] eta: 0:00:01 time: 0.5840 data_time: 0.0303 memory: 15725 2022/11/01 14:27:31 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8204, precision: 0.6129, hmean: 0.7017 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8204, precision: 0.7085, hmean: 0.7604 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8122, precision: 0.7883, hmean: 0.8001 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7862, precision: 0.8668, hmean: 0.8245 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6654, precision: 0.9395, hmean: 0.7790 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1367, precision: 0.9930, hmean: 0.2404 2022/11/01 14:27:31 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 14:27:31 - mmengine - INFO - Epoch(val) [140][32/32] icdar/precision: 0.8668 icdar/recall: 0.7862 icdar/hmean: 0.8245 2022/11/01 14:27:36 - mmengine - INFO - Epoch(train) [141][5/63] lr: 1.4076e-03 eta: 0:00:01 time: 0.7274 data_time: 0.2094 memory: 17620 loss: 2.3490 loss_prob: 1.4307 loss_thr: 0.6872 loss_db: 0.2311 2022/11/01 14:27:39 - mmengine - INFO - Epoch(train) [141][10/63] lr: 1.4076e-03 eta: 12:13:56 time: 0.7851 data_time: 0.2123 memory: 17620 loss: 2.5448 loss_prob: 1.5569 loss_thr: 0.7333 loss_db: 0.2546 2022/11/01 14:27:42 - mmengine - INFO - Epoch(train) [141][15/63] lr: 1.4076e-03 eta: 12:13:56 time: 0.5697 data_time: 0.0093 memory: 17620 loss: 2.6182 loss_prob: 1.6121 loss_thr: 0.7361 loss_db: 0.2699 2022/11/01 14:27:45 - mmengine - INFO - Epoch(train) [141][20/63] lr: 1.4076e-03 eta: 12:13:44 time: 0.5830 data_time: 0.0063 memory: 17620 loss: 2.5022 loss_prob: 1.5262 loss_thr: 0.7252 loss_db: 0.2508 2022/11/01 14:27:47 - mmengine - INFO - Epoch(train) [141][25/63] lr: 1.4076e-03 eta: 12:13:44 time: 0.5873 data_time: 0.0170 memory: 17620 loss: 2.4704 loss_prob: 1.4954 loss_thr: 0.7334 loss_db: 0.2415 2022/11/01 14:27:50 - mmengine - INFO - Epoch(train) [141][30/63] lr: 1.4076e-03 eta: 12:13:30 time: 0.5656 data_time: 0.0277 memory: 17620 loss: 2.5549 loss_prob: 1.5644 loss_thr: 0.7389 loss_db: 0.2516 2022/11/01 14:27:53 - mmengine - INFO - Epoch(train) [141][35/63] lr: 1.4076e-03 eta: 12:13:30 time: 0.5475 data_time: 0.0154 memory: 17620 loss: 2.6014 loss_prob: 1.6059 loss_thr: 0.7382 loss_db: 0.2573 2022/11/01 14:27:56 - mmengine - INFO - Epoch(train) [141][40/63] lr: 1.4076e-03 eta: 12:13:13 time: 0.5245 data_time: 0.0122 memory: 17620 loss: 2.5051 loss_prob: 1.5403 loss_thr: 0.7147 loss_db: 0.2500 2022/11/01 14:27:58 - mmengine - INFO - Epoch(train) [141][45/63] lr: 1.4076e-03 eta: 12:13:13 time: 0.5398 data_time: 0.0131 memory: 17620 loss: 2.4885 loss_prob: 1.5396 loss_thr: 0.6966 loss_db: 0.2523 2022/11/01 14:28:02 - mmengine - INFO - Epoch(train) [141][50/63] lr: 1.4076e-03 eta: 12:13:02 time: 0.5952 data_time: 0.0146 memory: 17620 loss: 2.5991 loss_prob: 1.6339 loss_thr: 0.6985 loss_db: 0.2667 2022/11/01 14:28:05 - mmengine - INFO - Epoch(train) [141][55/63] lr: 1.4076e-03 eta: 12:13:02 time: 0.6272 data_time: 0.0218 memory: 17620 loss: 2.5407 loss_prob: 1.5781 loss_thr: 0.7105 loss_db: 0.2520 2022/11/01 14:28:07 - mmengine - INFO - Epoch(train) [141][60/63] lr: 1.4076e-03 eta: 12:12:49 time: 0.5725 data_time: 0.0136 memory: 17620 loss: 2.4095 loss_prob: 1.4763 loss_thr: 0.6976 loss_db: 0.2355 2022/11/01 14:28:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:28:14 - mmengine - INFO - Epoch(train) [142][5/63] lr: 1.4177e-03 eta: 12:12:49 time: 0.7640 data_time: 0.1988 memory: 17620 loss: 2.5313 loss_prob: 1.5828 loss_thr: 0.6784 loss_db: 0.2702 2022/11/01 14:28:18 - mmengine - INFO - Epoch(train) [142][10/63] lr: 1.4177e-03 eta: 12:12:43 time: 0.8957 data_time: 0.2021 memory: 17620 loss: 2.6835 loss_prob: 1.6989 loss_thr: 0.6974 loss_db: 0.2873 2022/11/01 14:28:21 - mmengine - INFO - Epoch(train) [142][15/63] lr: 1.4177e-03 eta: 12:12:43 time: 0.7278 data_time: 0.0143 memory: 17620 loss: 2.4802 loss_prob: 1.5334 loss_thr: 0.6965 loss_db: 0.2503 2022/11/01 14:28:24 - mmengine - INFO - Epoch(train) [142][20/63] lr: 1.4177e-03 eta: 12:12:38 time: 0.6812 data_time: 0.0089 memory: 17620 loss: 2.4938 loss_prob: 1.5515 loss_thr: 0.6865 loss_db: 0.2558 2022/11/01 14:28:28 - mmengine - INFO - Epoch(train) [142][25/63] lr: 1.4177e-03 eta: 12:12:38 time: 0.6595 data_time: 0.0154 memory: 17620 loss: 2.6954 loss_prob: 1.6991 loss_thr: 0.7114 loss_db: 0.2849 2022/11/01 14:28:31 - mmengine - INFO - Epoch(train) [142][30/63] lr: 1.4177e-03 eta: 12:12:29 time: 0.6198 data_time: 0.0254 memory: 17620 loss: 2.8171 loss_prob: 1.7721 loss_thr: 0.7451 loss_db: 0.2999 2022/11/01 14:28:33 - mmengine - INFO - Epoch(train) [142][35/63] lr: 1.4177e-03 eta: 12:12:29 time: 0.5682 data_time: 0.0251 memory: 17620 loss: 2.6841 loss_prob: 1.6737 loss_thr: 0.7337 loss_db: 0.2766 2022/11/01 14:28:37 - mmengine - INFO - Epoch(train) [142][40/63] lr: 1.4177e-03 eta: 12:12:18 time: 0.6103 data_time: 0.0184 memory: 17620 loss: 2.6897 loss_prob: 1.6732 loss_thr: 0.7370 loss_db: 0.2794 2022/11/01 14:28:39 - mmengine - INFO - Epoch(train) [142][45/63] lr: 1.4177e-03 eta: 12:12:18 time: 0.5912 data_time: 0.0089 memory: 17620 loss: 2.6885 loss_prob: 1.6738 loss_thr: 0.7354 loss_db: 0.2792 2022/11/01 14:28:42 - mmengine - INFO - Epoch(train) [142][50/63] lr: 1.4177e-03 eta: 12:12:04 time: 0.5548 data_time: 0.0227 memory: 17620 loss: 2.5069 loss_prob: 1.5439 loss_thr: 0.7119 loss_db: 0.2512 2022/11/01 14:28:45 - mmengine - INFO - Epoch(train) [142][55/63] lr: 1.4177e-03 eta: 12:12:04 time: 0.5734 data_time: 0.0252 memory: 17620 loss: 2.3741 loss_prob: 1.4559 loss_thr: 0.6785 loss_db: 0.2397 2022/11/01 14:28:48 - mmengine - INFO - Epoch(train) [142][60/63] lr: 1.4177e-03 eta: 12:11:51 time: 0.5774 data_time: 0.0103 memory: 17620 loss: 2.2261 loss_prob: 1.3518 loss_thr: 0.6561 loss_db: 0.2182 2022/11/01 14:28:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:28:55 - mmengine - INFO - Epoch(train) [143][5/63] lr: 1.4277e-03 eta: 12:11:51 time: 0.8661 data_time: 0.2225 memory: 17620 loss: 2.4058 loss_prob: 1.4744 loss_thr: 0.6926 loss_db: 0.2388 2022/11/01 14:28:59 - mmengine - INFO - Epoch(train) [143][10/63] lr: 1.4277e-03 eta: 12:11:47 time: 0.9132 data_time: 0.2217 memory: 17620 loss: 2.4665 loss_prob: 1.5032 loss_thr: 0.7206 loss_db: 0.2427 2022/11/01 14:29:02 - mmengine - INFO - Epoch(train) [143][15/63] lr: 1.4277e-03 eta: 12:11:47 time: 0.6806 data_time: 0.0066 memory: 17620 loss: 2.5158 loss_prob: 1.5382 loss_thr: 0.7332 loss_db: 0.2444 2022/11/01 14:29:05 - mmengine - INFO - Epoch(train) [143][20/63] lr: 1.4277e-03 eta: 12:11:37 time: 0.6172 data_time: 0.0107 memory: 17620 loss: 2.3562 loss_prob: 1.4447 loss_thr: 0.6840 loss_db: 0.2275 2022/11/01 14:29:08 - mmengine - INFO - Epoch(train) [143][25/63] lr: 1.4277e-03 eta: 12:11:37 time: 0.5550 data_time: 0.0277 memory: 17620 loss: 2.4134 loss_prob: 1.4973 loss_thr: 0.6729 loss_db: 0.2431 2022/11/01 14:29:11 - mmengine - INFO - Epoch(train) [143][30/63] lr: 1.4277e-03 eta: 12:11:23 time: 0.5527 data_time: 0.0257 memory: 17620 loss: 2.3934 loss_prob: 1.4817 loss_thr: 0.6711 loss_db: 0.2406 2022/11/01 14:29:14 - mmengine - INFO - Epoch(train) [143][35/63] lr: 1.4277e-03 eta: 12:11:23 time: 0.5728 data_time: 0.0122 memory: 17620 loss: 2.5132 loss_prob: 1.5548 loss_thr: 0.7023 loss_db: 0.2561 2022/11/01 14:29:16 - mmengine - INFO - Epoch(train) [143][40/63] lr: 1.4277e-03 eta: 12:11:09 time: 0.5581 data_time: 0.0141 memory: 17620 loss: 3.0859 loss_prob: 2.0262 loss_thr: 0.7329 loss_db: 0.3267 2022/11/01 14:29:19 - mmengine - INFO - Epoch(train) [143][45/63] lr: 1.4277e-03 eta: 12:11:09 time: 0.5304 data_time: 0.0116 memory: 17620 loss: 3.2475 loss_prob: 2.1675 loss_thr: 0.7238 loss_db: 0.3563 2022/11/01 14:29:22 - mmengine - INFO - Epoch(train) [143][50/63] lr: 1.4277e-03 eta: 12:10:56 time: 0.5667 data_time: 0.0200 memory: 17620 loss: 3.3112 loss_prob: 2.1482 loss_thr: 0.7742 loss_db: 0.3888 2022/11/01 14:29:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:29:25 - mmengine - INFO - Epoch(train) [143][55/63] lr: 1.4277e-03 eta: 12:10:56 time: 0.5687 data_time: 0.0211 memory: 17620 loss: 3.2437 loss_prob: 2.1014 loss_thr: 0.7611 loss_db: 0.3813 2022/11/01 14:29:27 - mmengine - INFO - Epoch(train) [143][60/63] lr: 1.4277e-03 eta: 12:10:42 time: 0.5604 data_time: 0.0096 memory: 17620 loss: 2.9202 loss_prob: 1.8745 loss_thr: 0.7316 loss_db: 0.3141 2022/11/01 14:29:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:29:35 - mmengine - INFO - Epoch(train) [144][5/63] lr: 1.4377e-03 eta: 12:10:42 time: 0.8625 data_time: 0.2347 memory: 17620 loss: 2.7789 loss_prob: 1.7533 loss_thr: 0.7415 loss_db: 0.2840 2022/11/01 14:29:38 - mmengine - INFO - Epoch(train) [144][10/63] lr: 1.4377e-03 eta: 12:10:37 time: 0.9063 data_time: 0.2345 memory: 17620 loss: 2.6807 loss_prob: 1.6894 loss_thr: 0.7084 loss_db: 0.2828 2022/11/01 14:29:41 - mmengine - INFO - Epoch(train) [144][15/63] lr: 1.4377e-03 eta: 12:10:37 time: 0.5733 data_time: 0.0059 memory: 17620 loss: 2.7701 loss_prob: 1.7708 loss_thr: 0.7005 loss_db: 0.2989 2022/11/01 14:29:44 - mmengine - INFO - Epoch(train) [144][20/63] lr: 1.4377e-03 eta: 12:10:24 time: 0.5676 data_time: 0.0075 memory: 17620 loss: 2.7734 loss_prob: 1.7725 loss_thr: 0.7098 loss_db: 0.2911 2022/11/01 14:29:47 - mmengine - INFO - Epoch(train) [144][25/63] lr: 1.4377e-03 eta: 12:10:24 time: 0.5925 data_time: 0.0354 memory: 17620 loss: 2.6439 loss_prob: 1.6592 loss_thr: 0.7150 loss_db: 0.2697 2022/11/01 14:29:49 - mmengine - INFO - Epoch(train) [144][30/63] lr: 1.4377e-03 eta: 12:10:12 time: 0.5859 data_time: 0.0324 memory: 17620 loss: 2.5851 loss_prob: 1.6168 loss_thr: 0.7012 loss_db: 0.2672 2022/11/01 14:29:52 - mmengine - INFO - Epoch(train) [144][35/63] lr: 1.4377e-03 eta: 12:10:12 time: 0.5480 data_time: 0.0071 memory: 17620 loss: 2.3854 loss_prob: 1.4757 loss_thr: 0.6691 loss_db: 0.2406 2022/11/01 14:29:55 - mmengine - INFO - Epoch(train) [144][40/63] lr: 1.4377e-03 eta: 12:09:56 time: 0.5362 data_time: 0.0101 memory: 17620 loss: 2.3620 loss_prob: 1.4433 loss_thr: 0.6834 loss_db: 0.2353 2022/11/01 14:29:58 - mmengine - INFO - Epoch(train) [144][45/63] lr: 1.4377e-03 eta: 12:09:56 time: 0.5645 data_time: 0.0116 memory: 17620 loss: 2.7128 loss_prob: 1.6715 loss_thr: 0.7576 loss_db: 0.2837 2022/11/01 14:30:01 - mmengine - INFO - Epoch(train) [144][50/63] lr: 1.4377e-03 eta: 12:09:44 time: 0.5804 data_time: 0.0265 memory: 17620 loss: 2.6777 loss_prob: 1.6612 loss_thr: 0.7420 loss_db: 0.2745 2022/11/01 14:30:03 - mmengine - INFO - Epoch(train) [144][55/63] lr: 1.4377e-03 eta: 12:09:44 time: 0.5413 data_time: 0.0226 memory: 17620 loss: 2.4659 loss_prob: 1.5212 loss_thr: 0.6975 loss_db: 0.2472 2022/11/01 14:30:06 - mmengine - INFO - Epoch(train) [144][60/63] lr: 1.4377e-03 eta: 12:09:27 time: 0.5143 data_time: 0.0056 memory: 17620 loss: 2.6598 loss_prob: 1.6635 loss_thr: 0.7127 loss_db: 0.2835 2022/11/01 14:30:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:30:13 - mmengine - INFO - Epoch(train) [145][5/63] lr: 1.4478e-03 eta: 12:09:27 time: 0.8282 data_time: 0.2363 memory: 17620 loss: 2.8902 loss_prob: 1.8449 loss_thr: 0.7333 loss_db: 0.3120 2022/11/01 14:30:16 - mmengine - INFO - Epoch(train) [145][10/63] lr: 1.4478e-03 eta: 12:09:19 time: 0.8692 data_time: 0.2417 memory: 17620 loss: 3.0468 loss_prob: 1.9572 loss_thr: 0.7523 loss_db: 0.3373 2022/11/01 14:30:18 - mmengine - INFO - Epoch(train) [145][15/63] lr: 1.4478e-03 eta: 12:09:19 time: 0.5325 data_time: 0.0105 memory: 17620 loss: 3.1742 loss_prob: 2.0359 loss_thr: 0.7787 loss_db: 0.3595 2022/11/01 14:30:21 - mmengine - INFO - Epoch(train) [145][20/63] lr: 1.4478e-03 eta: 12:09:02 time: 0.5071 data_time: 0.0051 memory: 17620 loss: 2.9970 loss_prob: 1.9001 loss_thr: 0.7688 loss_db: 0.3281 2022/11/01 14:30:24 - mmengine - INFO - Epoch(train) [145][25/63] lr: 1.4478e-03 eta: 12:09:02 time: 0.5356 data_time: 0.0158 memory: 17620 loss: 2.9379 loss_prob: 1.8588 loss_thr: 0.7635 loss_db: 0.3155 2022/11/01 14:30:27 - mmengine - INFO - Epoch(train) [145][30/63] lr: 1.4478e-03 eta: 12:08:52 time: 0.6177 data_time: 0.0329 memory: 17620 loss: 2.8829 loss_prob: 1.8132 loss_thr: 0.7639 loss_db: 0.3058 2022/11/01 14:30:30 - mmengine - INFO - Epoch(train) [145][35/63] lr: 1.4478e-03 eta: 12:08:52 time: 0.6579 data_time: 0.0248 memory: 17620 loss: 2.8496 loss_prob: 1.8119 loss_thr: 0.7374 loss_db: 0.3004 2022/11/01 14:30:33 - mmengine - INFO - Epoch(train) [145][40/63] lr: 1.4478e-03 eta: 12:08:42 time: 0.6047 data_time: 0.0092 memory: 17620 loss: 2.9197 loss_prob: 1.8606 loss_thr: 0.7373 loss_db: 0.3218 2022/11/01 14:30:36 - mmengine - INFO - Epoch(train) [145][45/63] lr: 1.4478e-03 eta: 12:08:42 time: 0.5634 data_time: 0.0081 memory: 17620 loss: 2.8243 loss_prob: 1.7899 loss_thr: 0.7233 loss_db: 0.3111 2022/11/01 14:30:39 - mmengine - INFO - Epoch(train) [145][50/63] lr: 1.4478e-03 eta: 12:08:32 time: 0.6193 data_time: 0.0339 memory: 17620 loss: 2.6054 loss_prob: 1.6269 loss_thr: 0.7104 loss_db: 0.2681 2022/11/01 14:30:42 - mmengine - INFO - Epoch(train) [145][55/63] lr: 1.4478e-03 eta: 12:08:32 time: 0.6027 data_time: 0.0323 memory: 17620 loss: 2.4800 loss_prob: 1.5273 loss_thr: 0.7075 loss_db: 0.2452 2022/11/01 14:30:45 - mmengine - INFO - Epoch(train) [145][60/63] lr: 1.4478e-03 eta: 12:08:19 time: 0.5592 data_time: 0.0065 memory: 17620 loss: 2.4891 loss_prob: 1.5328 loss_thr: 0.7088 loss_db: 0.2475 2022/11/01 14:30:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:30:53 - mmengine - INFO - Epoch(train) [146][5/63] lr: 1.4578e-03 eta: 12:08:19 time: 0.8996 data_time: 0.2128 memory: 17620 loss: 2.7438 loss_prob: 1.7016 loss_thr: 0.7556 loss_db: 0.2866 2022/11/01 14:30:55 - mmengine - INFO - Epoch(train) [146][10/63] lr: 1.4578e-03 eta: 12:08:08 time: 0.8338 data_time: 0.2113 memory: 17620 loss: 2.8474 loss_prob: 1.7727 loss_thr: 0.7648 loss_db: 0.3099 2022/11/01 14:30:58 - mmengine - INFO - Epoch(train) [146][15/63] lr: 1.4578e-03 eta: 12:08:08 time: 0.5413 data_time: 0.0063 memory: 17620 loss: 2.9309 loss_prob: 1.8796 loss_thr: 0.7294 loss_db: 0.3219 2022/11/01 14:31:01 - mmengine - INFO - Epoch(train) [146][20/63] lr: 1.4578e-03 eta: 12:07:53 time: 0.5327 data_time: 0.0058 memory: 17620 loss: 2.7998 loss_prob: 1.8065 loss_thr: 0.6988 loss_db: 0.2945 2022/11/01 14:31:04 - mmengine - INFO - Epoch(train) [146][25/63] lr: 1.4578e-03 eta: 12:07:53 time: 0.6112 data_time: 0.0391 memory: 17620 loss: 2.8875 loss_prob: 1.8456 loss_thr: 0.7404 loss_db: 0.3015 2022/11/01 14:31:07 - mmengine - INFO - Epoch(train) [146][30/63] lr: 1.4578e-03 eta: 12:07:45 time: 0.6342 data_time: 0.0393 memory: 17620 loss: 3.0953 loss_prob: 1.9779 loss_thr: 0.7833 loss_db: 0.3340 2022/11/01 14:31:10 - mmengine - INFO - Epoch(train) [146][35/63] lr: 1.4578e-03 eta: 12:07:45 time: 0.5751 data_time: 0.0082 memory: 17620 loss: 3.1154 loss_prob: 1.9823 loss_thr: 0.7847 loss_db: 0.3485 2022/11/01 14:31:13 - mmengine - INFO - Epoch(train) [146][40/63] lr: 1.4578e-03 eta: 12:07:32 time: 0.5701 data_time: 0.0069 memory: 17620 loss: 2.8412 loss_prob: 1.7750 loss_thr: 0.7602 loss_db: 0.3060 2022/11/01 14:31:16 - mmengine - INFO - Epoch(train) [146][45/63] lr: 1.4578e-03 eta: 12:07:32 time: 0.5887 data_time: 0.0054 memory: 17620 loss: 2.6898 loss_prob: 1.6784 loss_thr: 0.7390 loss_db: 0.2725 2022/11/01 14:31:19 - mmengine - INFO - Epoch(train) [146][50/63] lr: 1.4578e-03 eta: 12:07:22 time: 0.6101 data_time: 0.0225 memory: 17620 loss: 2.4725 loss_prob: 1.5230 loss_thr: 0.7093 loss_db: 0.2402 2022/11/01 14:31:22 - mmengine - INFO - Epoch(train) [146][55/63] lr: 1.4578e-03 eta: 12:07:22 time: 0.6038 data_time: 0.0221 memory: 17620 loss: 2.2632 loss_prob: 1.3688 loss_thr: 0.6782 loss_db: 0.2162 2022/11/01 14:31:25 - mmengine - INFO - Epoch(train) [146][60/63] lr: 1.4578e-03 eta: 12:07:11 time: 0.5946 data_time: 0.0060 memory: 17620 loss: 2.4962 loss_prob: 1.5364 loss_thr: 0.7109 loss_db: 0.2488 2022/11/01 14:31:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:31:31 - mmengine - INFO - Epoch(train) [147][5/63] lr: 1.4679e-03 eta: 12:07:11 time: 0.7291 data_time: 0.1987 memory: 17620 loss: 2.3756 loss_prob: 1.4542 loss_thr: 0.6833 loss_db: 0.2380 2022/11/01 14:31:34 - mmengine - INFO - Epoch(train) [147][10/63] lr: 1.4679e-03 eta: 12:06:57 time: 0.7830 data_time: 0.2053 memory: 17620 loss: 2.2708 loss_prob: 1.3670 loss_thr: 0.6839 loss_db: 0.2199 2022/11/01 14:31:37 - mmengine - INFO - Epoch(train) [147][15/63] lr: 1.4679e-03 eta: 12:06:57 time: 0.5605 data_time: 0.0125 memory: 17620 loss: 2.3740 loss_prob: 1.4452 loss_thr: 0.7000 loss_db: 0.2287 2022/11/01 14:31:39 - mmengine - INFO - Epoch(train) [147][20/63] lr: 1.4679e-03 eta: 12:06:41 time: 0.5309 data_time: 0.0048 memory: 17620 loss: 2.4239 loss_prob: 1.4885 loss_thr: 0.7004 loss_db: 0.2351 2022/11/01 14:31:42 - mmengine - INFO - Epoch(train) [147][25/63] lr: 1.4679e-03 eta: 12:06:41 time: 0.5601 data_time: 0.0217 memory: 17620 loss: 2.4538 loss_prob: 1.5031 loss_thr: 0.7067 loss_db: 0.2440 2022/11/01 14:31:45 - mmengine - INFO - Epoch(train) [147][30/63] lr: 1.4679e-03 eta: 12:06:29 time: 0.5744 data_time: 0.0289 memory: 17620 loss: 2.5118 loss_prob: 1.5401 loss_thr: 0.7168 loss_db: 0.2549 2022/11/01 14:31:48 - mmengine - INFO - Epoch(train) [147][35/63] lr: 1.4679e-03 eta: 12:06:29 time: 0.5643 data_time: 0.0178 memory: 17620 loss: 2.4740 loss_prob: 1.5227 loss_thr: 0.7008 loss_db: 0.2505 2022/11/01 14:31:51 - mmengine - INFO - Epoch(train) [147][40/63] lr: 1.4679e-03 eta: 12:06:15 time: 0.5555 data_time: 0.0102 memory: 17620 loss: 2.7650 loss_prob: 1.7448 loss_thr: 0.7221 loss_db: 0.2981 2022/11/01 14:31:53 - mmengine - INFO - Epoch(train) [147][45/63] lr: 1.4679e-03 eta: 12:06:15 time: 0.5558 data_time: 0.0056 memory: 17620 loss: 2.8135 loss_prob: 1.7660 loss_thr: 0.7443 loss_db: 0.3032 2022/11/01 14:31:56 - mmengine - INFO - Epoch(train) [147][50/63] lr: 1.4679e-03 eta: 12:06:04 time: 0.5882 data_time: 0.0139 memory: 17620 loss: 2.5634 loss_prob: 1.5650 loss_thr: 0.7384 loss_db: 0.2601 2022/11/01 14:32:00 - mmengine - INFO - Epoch(train) [147][55/63] lr: 1.4679e-03 eta: 12:06:04 time: 0.6287 data_time: 0.0193 memory: 17620 loss: 2.4733 loss_prob: 1.4998 loss_thr: 0.7272 loss_db: 0.2463 2022/11/01 14:32:02 - mmengine - INFO - Epoch(train) [147][60/63] lr: 1.4679e-03 eta: 12:05:53 time: 0.5948 data_time: 0.0137 memory: 17620 loss: 2.3480 loss_prob: 1.4227 loss_thr: 0.6945 loss_db: 0.2307 2022/11/01 14:32:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:32:08 - mmengine - INFO - Epoch(train) [148][5/63] lr: 1.4779e-03 eta: 12:05:53 time: 0.6876 data_time: 0.1608 memory: 17620 loss: 2.3332 loss_prob: 1.4273 loss_thr: 0.6740 loss_db: 0.2319 2022/11/01 14:32:11 - mmengine - INFO - Epoch(train) [148][10/63] lr: 1.4779e-03 eta: 12:05:35 time: 0.7225 data_time: 0.1705 memory: 17620 loss: 2.4545 loss_prob: 1.5135 loss_thr: 0.6931 loss_db: 0.2479 2022/11/01 14:32:14 - mmengine - INFO - Epoch(train) [148][15/63] lr: 1.4779e-03 eta: 12:05:35 time: 0.5599 data_time: 0.0155 memory: 17620 loss: 2.4878 loss_prob: 1.5478 loss_thr: 0.6822 loss_db: 0.2577 2022/11/01 14:32:17 - mmengine - INFO - Epoch(train) [148][20/63] lr: 1.4779e-03 eta: 12:05:21 time: 0.5606 data_time: 0.0059 memory: 17620 loss: 2.3754 loss_prob: 1.4609 loss_thr: 0.6761 loss_db: 0.2384 2022/11/01 14:32:20 - mmengine - INFO - Epoch(train) [148][25/63] lr: 1.4779e-03 eta: 12:05:21 time: 0.5722 data_time: 0.0202 memory: 17620 loss: 2.3195 loss_prob: 1.4054 loss_thr: 0.6874 loss_db: 0.2267 2022/11/01 14:32:22 - mmengine - INFO - Epoch(train) [148][30/63] lr: 1.4779e-03 eta: 12:05:09 time: 0.5712 data_time: 0.0263 memory: 17620 loss: 2.2745 loss_prob: 1.3792 loss_thr: 0.6730 loss_db: 0.2222 2022/11/01 14:32:25 - mmengine - INFO - Epoch(train) [148][35/63] lr: 1.4779e-03 eta: 12:05:09 time: 0.5671 data_time: 0.0219 memory: 17620 loss: 2.3495 loss_prob: 1.4390 loss_thr: 0.6744 loss_db: 0.2361 2022/11/01 14:32:28 - mmengine - INFO - Epoch(train) [148][40/63] lr: 1.4779e-03 eta: 12:04:56 time: 0.5646 data_time: 0.0165 memory: 17620 loss: 2.5295 loss_prob: 1.5644 loss_thr: 0.7037 loss_db: 0.2613 2022/11/01 14:32:31 - mmengine - INFO - Epoch(train) [148][45/63] lr: 1.4779e-03 eta: 12:04:56 time: 0.5741 data_time: 0.0053 memory: 17620 loss: 2.4605 loss_prob: 1.5175 loss_thr: 0.6976 loss_db: 0.2454 2022/11/01 14:32:34 - mmengine - INFO - Epoch(train) [148][50/63] lr: 1.4779e-03 eta: 12:04:43 time: 0.5673 data_time: 0.0136 memory: 17620 loss: 2.5505 loss_prob: 1.5704 loss_thr: 0.7211 loss_db: 0.2590 2022/11/01 14:32:37 - mmengine - INFO - Epoch(train) [148][55/63] lr: 1.4779e-03 eta: 12:04:43 time: 0.5628 data_time: 0.0174 memory: 17620 loss: 2.6415 loss_prob: 1.6202 loss_thr: 0.7525 loss_db: 0.2689 2022/11/01 14:32:39 - mmengine - INFO - Epoch(train) [148][60/63] lr: 1.4779e-03 eta: 12:04:29 time: 0.5509 data_time: 0.0173 memory: 17620 loss: 2.3843 loss_prob: 1.4639 loss_thr: 0.6849 loss_db: 0.2356 2022/11/01 14:32:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:32:47 - mmengine - INFO - Epoch(train) [149][5/63] lr: 1.4879e-03 eta: 12:04:29 time: 0.8563 data_time: 0.1882 memory: 17620 loss: 2.7393 loss_prob: 1.7341 loss_thr: 0.7185 loss_db: 0.2867 2022/11/01 14:32:50 - mmengine - INFO - Epoch(train) [149][10/63] lr: 1.4879e-03 eta: 12:04:27 time: 0.9519 data_time: 0.1995 memory: 17620 loss: 2.6567 loss_prob: 1.6710 loss_thr: 0.7158 loss_db: 0.2699 2022/11/01 14:32:53 - mmengine - INFO - Epoch(train) [149][15/63] lr: 1.4879e-03 eta: 12:04:27 time: 0.6436 data_time: 0.0172 memory: 17620 loss: 2.8385 loss_prob: 1.8021 loss_thr: 0.7404 loss_db: 0.2959 2022/11/01 14:32:56 - mmengine - INFO - Epoch(train) [149][20/63] lr: 1.4879e-03 eta: 12:04:16 time: 0.5956 data_time: 0.0055 memory: 17620 loss: 2.6532 loss_prob: 1.6486 loss_thr: 0.7368 loss_db: 0.2679 2022/11/01 14:32:59 - mmengine - INFO - Epoch(train) [149][25/63] lr: 1.4879e-03 eta: 12:04:16 time: 0.5610 data_time: 0.0180 memory: 17620 loss: 2.3472 loss_prob: 1.4317 loss_thr: 0.6854 loss_db: 0.2301 2022/11/01 14:33:02 - mmengine - INFO - Epoch(train) [149][30/63] lr: 1.4879e-03 eta: 12:04:04 time: 0.5800 data_time: 0.0277 memory: 17620 loss: 2.4770 loss_prob: 1.5231 loss_thr: 0.6983 loss_db: 0.2557 2022/11/01 14:33:05 - mmengine - INFO - Epoch(train) [149][35/63] lr: 1.4879e-03 eta: 12:04:04 time: 0.6199 data_time: 0.0300 memory: 17620 loss: 2.6309 loss_prob: 1.6253 loss_thr: 0.7317 loss_db: 0.2740 2022/11/01 14:33:08 - mmengine - INFO - Epoch(train) [149][40/63] lr: 1.4879e-03 eta: 12:03:54 time: 0.6092 data_time: 0.0197 memory: 17620 loss: 2.6429 loss_prob: 1.6499 loss_thr: 0.7232 loss_db: 0.2698 2022/11/01 14:33:12 - mmengine - INFO - Epoch(train) [149][45/63] lr: 1.4879e-03 eta: 12:03:54 time: 0.6500 data_time: 0.0046 memory: 17620 loss: 2.5425 loss_prob: 1.5759 loss_thr: 0.7126 loss_db: 0.2540 2022/11/01 14:33:14 - mmengine - INFO - Epoch(train) [149][50/63] lr: 1.4879e-03 eta: 12:03:48 time: 0.6563 data_time: 0.0143 memory: 17620 loss: 2.5296 loss_prob: 1.5458 loss_thr: 0.7300 loss_db: 0.2538 2022/11/01 14:33:18 - mmengine - INFO - Epoch(train) [149][55/63] lr: 1.4879e-03 eta: 12:03:48 time: 0.6032 data_time: 0.0164 memory: 17620 loss: 2.3038 loss_prob: 1.3875 loss_thr: 0.6895 loss_db: 0.2269 2022/11/01 14:33:20 - mmengine - INFO - Epoch(train) [149][60/63] lr: 1.4879e-03 eta: 12:03:37 time: 0.5948 data_time: 0.0176 memory: 17620 loss: 2.2984 loss_prob: 1.4005 loss_thr: 0.6739 loss_db: 0.2239 2022/11/01 14:33:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:33:28 - mmengine - INFO - Epoch(train) [150][5/63] lr: 1.4980e-03 eta: 12:03:37 time: 0.8362 data_time: 0.2079 memory: 17620 loss: 2.3776 loss_prob: 1.4567 loss_thr: 0.6816 loss_db: 0.2393 2022/11/01 14:33:31 - mmengine - INFO - Epoch(train) [150][10/63] lr: 1.4980e-03 eta: 12:03:32 time: 0.8944 data_time: 0.2079 memory: 17620 loss: 2.4076 loss_prob: 1.4655 loss_thr: 0.6946 loss_db: 0.2475 2022/11/01 14:33:34 - mmengine - INFO - Epoch(train) [150][15/63] lr: 1.4980e-03 eta: 12:03:32 time: 0.6571 data_time: 0.0048 memory: 17620 loss: 2.4668 loss_prob: 1.5125 loss_thr: 0.7045 loss_db: 0.2499 2022/11/01 14:33:37 - mmengine - INFO - Epoch(train) [150][20/63] lr: 1.4980e-03 eta: 12:03:22 time: 0.6175 data_time: 0.0052 memory: 17620 loss: 2.4574 loss_prob: 1.5149 loss_thr: 0.7015 loss_db: 0.2410 2022/11/01 14:33:40 - mmengine - INFO - Epoch(train) [150][25/63] lr: 1.4980e-03 eta: 12:03:22 time: 0.5865 data_time: 0.0159 memory: 17620 loss: 2.2437 loss_prob: 1.3534 loss_thr: 0.6749 loss_db: 0.2154 2022/11/01 14:33:43 - mmengine - INFO - Epoch(train) [150][30/63] lr: 1.4980e-03 eta: 12:03:15 time: 0.6433 data_time: 0.0367 memory: 17620 loss: 2.1273 loss_prob: 1.2534 loss_thr: 0.6736 loss_db: 0.2003 2022/11/01 14:33:46 - mmengine - INFO - Epoch(train) [150][35/63] lr: 1.4980e-03 eta: 12:03:15 time: 0.6179 data_time: 0.0260 memory: 17620 loss: 2.3383 loss_prob: 1.4071 loss_thr: 0.7022 loss_db: 0.2290 2022/11/01 14:33:49 - mmengine - INFO - Epoch(train) [150][40/63] lr: 1.4980e-03 eta: 12:03:01 time: 0.5508 data_time: 0.0059 memory: 17620 loss: 2.3952 loss_prob: 1.4498 loss_thr: 0.7061 loss_db: 0.2394 2022/11/01 14:33:51 - mmengine - INFO - Epoch(train) [150][45/63] lr: 1.4980e-03 eta: 12:03:01 time: 0.5178 data_time: 0.0058 memory: 17620 loss: 2.4798 loss_prob: 1.5148 loss_thr: 0.7190 loss_db: 0.2459 2022/11/01 14:33:54 - mmengine - INFO - Epoch(train) [150][50/63] lr: 1.4980e-03 eta: 12:02:48 time: 0.5620 data_time: 0.0112 memory: 17620 loss: 2.4946 loss_prob: 1.5358 loss_thr: 0.7108 loss_db: 0.2480 2022/11/01 14:33:57 - mmengine - INFO - Epoch(train) [150][55/63] lr: 1.4980e-03 eta: 12:02:48 time: 0.5879 data_time: 0.0221 memory: 17620 loss: 2.5040 loss_prob: 1.5442 loss_thr: 0.7045 loss_db: 0.2554 2022/11/01 14:34:00 - mmengine - INFO - Epoch(train) [150][60/63] lr: 1.4980e-03 eta: 12:02:37 time: 0.5882 data_time: 0.0158 memory: 17620 loss: 2.6064 loss_prob: 1.6331 loss_thr: 0.7038 loss_db: 0.2694 2022/11/01 14:34:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:34:07 - mmengine - INFO - Epoch(train) [151][5/63] lr: 1.5080e-03 eta: 12:02:37 time: 0.7817 data_time: 0.2480 memory: 17620 loss: 2.6550 loss_prob: 1.6292 loss_thr: 0.7440 loss_db: 0.2817 2022/11/01 14:34:10 - mmengine - INFO - Epoch(train) [151][10/63] lr: 1.5080e-03 eta: 12:02:24 time: 0.7975 data_time: 0.2472 memory: 17620 loss: 2.6142 loss_prob: 1.6081 loss_thr: 0.7464 loss_db: 0.2597 2022/11/01 14:34:13 - mmengine - INFO - Epoch(train) [151][15/63] lr: 1.5080e-03 eta: 12:02:24 time: 0.5634 data_time: 0.0045 memory: 17620 loss: 2.6154 loss_prob: 1.6294 loss_thr: 0.7201 loss_db: 0.2659 2022/11/01 14:34:15 - mmengine - INFO - Epoch(train) [151][20/63] lr: 1.5080e-03 eta: 12:02:11 time: 0.5583 data_time: 0.0046 memory: 17620 loss: 2.4609 loss_prob: 1.5106 loss_thr: 0.7061 loss_db: 0.2442 2022/11/01 14:34:18 - mmengine - INFO - Epoch(train) [151][25/63] lr: 1.5080e-03 eta: 12:02:11 time: 0.5774 data_time: 0.0206 memory: 17620 loss: 2.5080 loss_prob: 1.5366 loss_thr: 0.7242 loss_db: 0.2472 2022/11/01 14:34:22 - mmengine - INFO - Epoch(train) [151][30/63] lr: 1.5080e-03 eta: 12:02:02 time: 0.6207 data_time: 0.0399 memory: 17620 loss: 2.5195 loss_prob: 1.5481 loss_thr: 0.7194 loss_db: 0.2520 2022/11/01 14:34:25 - mmengine - INFO - Epoch(train) [151][35/63] lr: 1.5080e-03 eta: 12:02:02 time: 0.6151 data_time: 0.0269 memory: 17620 loss: 2.6030 loss_prob: 1.6193 loss_thr: 0.7135 loss_db: 0.2702 2022/11/01 14:34:27 - mmengine - INFO - Epoch(train) [151][40/63] lr: 1.5080e-03 eta: 12:01:50 time: 0.5797 data_time: 0.0076 memory: 17620 loss: 2.5621 loss_prob: 1.6036 loss_thr: 0.6945 loss_db: 0.2640 2022/11/01 14:34:30 - mmengine - INFO - Epoch(train) [151][45/63] lr: 1.5080e-03 eta: 12:01:50 time: 0.5421 data_time: 0.0046 memory: 17620 loss: 2.4261 loss_prob: 1.5205 loss_thr: 0.6598 loss_db: 0.2457 2022/11/01 14:34:33 - mmengine - INFO - Epoch(train) [151][50/63] lr: 1.5080e-03 eta: 12:01:37 time: 0.5594 data_time: 0.0194 memory: 17620 loss: 2.5047 loss_prob: 1.5655 loss_thr: 0.6797 loss_db: 0.2595 2022/11/01 14:34:36 - mmengine - INFO - Epoch(train) [151][55/63] lr: 1.5080e-03 eta: 12:01:37 time: 0.6019 data_time: 0.0209 memory: 17620 loss: 2.5685 loss_prob: 1.5769 loss_thr: 0.7256 loss_db: 0.2660 2022/11/01 14:34:39 - mmengine - INFO - Epoch(train) [151][60/63] lr: 1.5080e-03 eta: 12:01:25 time: 0.5750 data_time: 0.0097 memory: 17620 loss: 2.3606 loss_prob: 1.4350 loss_thr: 0.6911 loss_db: 0.2345 2022/11/01 14:34:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:34:45 - mmengine - INFO - Epoch(train) [152][5/63] lr: 1.5181e-03 eta: 12:01:25 time: 0.7040 data_time: 0.1932 memory: 17620 loss: 2.2360 loss_prob: 1.3578 loss_thr: 0.6596 loss_db: 0.2186 2022/11/01 14:34:48 - mmengine - INFO - Epoch(train) [152][10/63] lr: 1.5181e-03 eta: 12:01:09 time: 0.7523 data_time: 0.1938 memory: 17620 loss: 2.2129 loss_prob: 1.3289 loss_thr: 0.6736 loss_db: 0.2104 2022/11/01 14:34:50 - mmengine - INFO - Epoch(train) [152][15/63] lr: 1.5181e-03 eta: 12:01:09 time: 0.5430 data_time: 0.0066 memory: 17620 loss: 2.1707 loss_prob: 1.2889 loss_thr: 0.6795 loss_db: 0.2023 2022/11/01 14:34:53 - mmengine - INFO - Epoch(train) [152][20/63] lr: 1.5181e-03 eta: 12:00:54 time: 0.5300 data_time: 0.0075 memory: 17620 loss: 2.1757 loss_prob: 1.2882 loss_thr: 0.6827 loss_db: 0.2048 2022/11/01 14:34:56 - mmengine - INFO - Epoch(train) [152][25/63] lr: 1.5181e-03 eta: 12:00:54 time: 0.5675 data_time: 0.0280 memory: 17620 loss: 2.3849 loss_prob: 1.4596 loss_thr: 0.6911 loss_db: 0.2342 2022/11/01 14:34:59 - mmengine - INFO - Epoch(train) [152][30/63] lr: 1.5181e-03 eta: 12:00:42 time: 0.5691 data_time: 0.0325 memory: 17620 loss: 2.3493 loss_prob: 1.4312 loss_thr: 0.6839 loss_db: 0.2342 2022/11/01 14:35:01 - mmengine - INFO - Epoch(train) [152][35/63] lr: 1.5181e-03 eta: 12:00:42 time: 0.5547 data_time: 0.0107 memory: 17620 loss: 2.3452 loss_prob: 1.4387 loss_thr: 0.6767 loss_db: 0.2298 2022/11/01 14:35:04 - mmengine - INFO - Epoch(train) [152][40/63] lr: 1.5181e-03 eta: 12:00:29 time: 0.5665 data_time: 0.0079 memory: 17620 loss: 2.4247 loss_prob: 1.5029 loss_thr: 0.6851 loss_db: 0.2367 2022/11/01 14:35:08 - mmengine - INFO - Epoch(train) [152][45/63] lr: 1.5181e-03 eta: 12:00:29 time: 0.6875 data_time: 0.0092 memory: 17620 loss: 2.5048 loss_prob: 1.5414 loss_thr: 0.7042 loss_db: 0.2592 2022/11/01 14:35:11 - mmengine - INFO - Epoch(train) [152][50/63] lr: 1.5181e-03 eta: 12:00:27 time: 0.7150 data_time: 0.0203 memory: 17620 loss: 2.7889 loss_prob: 1.7516 loss_thr: 0.7306 loss_db: 0.3067 2022/11/01 14:35:15 - mmengine - INFO - Epoch(train) [152][55/63] lr: 1.5181e-03 eta: 12:00:27 time: 0.6455 data_time: 0.0228 memory: 17620 loss: 2.6841 loss_prob: 1.6810 loss_thr: 0.7177 loss_db: 0.2855 2022/11/01 14:35:17 - mmengine - INFO - Epoch(train) [152][60/63] lr: 1.5181e-03 eta: 12:00:17 time: 0.6080 data_time: 0.0108 memory: 17620 loss: 2.5014 loss_prob: 1.5349 loss_thr: 0.7104 loss_db: 0.2561 2022/11/01 14:35:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:35:24 - mmengine - INFO - Epoch(train) [153][5/63] lr: 1.5281e-03 eta: 12:00:17 time: 0.7713 data_time: 0.2131 memory: 17620 loss: 2.5018 loss_prob: 1.5178 loss_thr: 0.7314 loss_db: 0.2525 2022/11/01 14:35:27 - mmengine - INFO - Epoch(train) [153][10/63] lr: 1.5281e-03 eta: 12:00:06 time: 0.8223 data_time: 0.2152 memory: 17620 loss: 2.5013 loss_prob: 1.5396 loss_thr: 0.7087 loss_db: 0.2531 2022/11/01 14:35:30 - mmengine - INFO - Epoch(train) [153][15/63] lr: 1.5281e-03 eta: 12:00:06 time: 0.6048 data_time: 0.0093 memory: 17620 loss: 2.3878 loss_prob: 1.4500 loss_thr: 0.7038 loss_db: 0.2340 2022/11/01 14:35:33 - mmengine - INFO - Epoch(train) [153][20/63] lr: 1.5281e-03 eta: 11:59:56 time: 0.6021 data_time: 0.0069 memory: 17620 loss: 2.4141 loss_prob: 1.4568 loss_thr: 0.7195 loss_db: 0.2378 2022/11/01 14:35:36 - mmengine - INFO - Epoch(train) [153][25/63] lr: 1.5281e-03 eta: 11:59:56 time: 0.6075 data_time: 0.0208 memory: 17620 loss: 2.3467 loss_prob: 1.4192 loss_thr: 0.6975 loss_db: 0.2299 2022/11/01 14:35:39 - mmengine - INFO - Epoch(train) [153][30/63] lr: 1.5281e-03 eta: 11:59:46 time: 0.6063 data_time: 0.0361 memory: 17620 loss: 2.4056 loss_prob: 1.4806 loss_thr: 0.6870 loss_db: 0.2380 2022/11/01 14:35:42 - mmengine - INFO - Epoch(train) [153][35/63] lr: 1.5281e-03 eta: 11:59:46 time: 0.6052 data_time: 0.0268 memory: 17620 loss: 2.4274 loss_prob: 1.5148 loss_thr: 0.6652 loss_db: 0.2473 2022/11/01 14:35:46 - mmengine - INFO - Epoch(train) [153][40/63] lr: 1.5281e-03 eta: 11:59:41 time: 0.6735 data_time: 0.0097 memory: 17620 loss: 2.4941 loss_prob: 1.5685 loss_thr: 0.6702 loss_db: 0.2553 2022/11/01 14:35:49 - mmengine - INFO - Epoch(train) [153][45/63] lr: 1.5281e-03 eta: 11:59:41 time: 0.6275 data_time: 0.0052 memory: 17620 loss: 2.5541 loss_prob: 1.5971 loss_thr: 0.7044 loss_db: 0.2525 2022/11/01 14:35:51 - mmengine - INFO - Epoch(train) [153][50/63] lr: 1.5281e-03 eta: 11:59:29 time: 0.5692 data_time: 0.0214 memory: 17620 loss: 2.3384 loss_prob: 1.4274 loss_thr: 0.6869 loss_db: 0.2240 2022/11/01 14:35:55 - mmengine - INFO - Epoch(train) [153][55/63] lr: 1.5281e-03 eta: 11:59:29 time: 0.5940 data_time: 0.0278 memory: 17620 loss: 2.6268 loss_prob: 1.6539 loss_thr: 0.6994 loss_db: 0.2736 2022/11/01 14:35:58 - mmengine - INFO - Epoch(train) [153][60/63] lr: 1.5281e-03 eta: 11:59:22 time: 0.6453 data_time: 0.0117 memory: 17620 loss: 2.9167 loss_prob: 1.8470 loss_thr: 0.7585 loss_db: 0.3112 2022/11/01 14:36:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:36:05 - mmengine - INFO - Epoch(train) [154][5/63] lr: 1.5382e-03 eta: 11:59:22 time: 0.8177 data_time: 0.1707 memory: 17620 loss: 2.5991 loss_prob: 1.6109 loss_thr: 0.7255 loss_db: 0.2627 2022/11/01 14:36:08 - mmengine - INFO - Epoch(train) [154][10/63] lr: 1.5382e-03 eta: 11:59:11 time: 0.8183 data_time: 0.1707 memory: 17620 loss: 2.5450 loss_prob: 1.5802 loss_thr: 0.7085 loss_db: 0.2564 2022/11/01 14:36:11 - mmengine - INFO - Epoch(train) [154][15/63] lr: 1.5382e-03 eta: 11:59:11 time: 0.6168 data_time: 0.0048 memory: 17620 loss: 2.5581 loss_prob: 1.5932 loss_thr: 0.7079 loss_db: 0.2570 2022/11/01 14:36:14 - mmengine - INFO - Epoch(train) [154][20/63] lr: 1.5382e-03 eta: 11:58:59 time: 0.5777 data_time: 0.0068 memory: 17620 loss: 2.7411 loss_prob: 1.7244 loss_thr: 0.7248 loss_db: 0.2920 2022/11/01 14:36:16 - mmengine - INFO - Epoch(train) [154][25/63] lr: 1.5382e-03 eta: 11:58:59 time: 0.5297 data_time: 0.0082 memory: 17620 loss: 2.9148 loss_prob: 1.8518 loss_thr: 0.7463 loss_db: 0.3168 2022/11/01 14:36:19 - mmengine - INFO - Epoch(train) [154][30/63] lr: 1.5382e-03 eta: 11:58:47 time: 0.5750 data_time: 0.0346 memory: 17620 loss: 2.7156 loss_prob: 1.7021 loss_thr: 0.7291 loss_db: 0.2843 2022/11/01 14:36:22 - mmengine - INFO - Epoch(train) [154][35/63] lr: 1.5382e-03 eta: 11:58:47 time: 0.5675 data_time: 0.0329 memory: 17620 loss: 2.6003 loss_prob: 1.6160 loss_thr: 0.7152 loss_db: 0.2691 2022/11/01 14:36:25 - mmengine - INFO - Epoch(train) [154][40/63] lr: 1.5382e-03 eta: 11:58:32 time: 0.5314 data_time: 0.0058 memory: 17620 loss: 2.8166 loss_prob: 1.7592 loss_thr: 0.7608 loss_db: 0.2965 2022/11/01 14:36:27 - mmengine - INFO - Epoch(train) [154][45/63] lr: 1.5382e-03 eta: 11:58:32 time: 0.5481 data_time: 0.0059 memory: 17620 loss: 2.9549 loss_prob: 1.8751 loss_thr: 0.7679 loss_db: 0.3119 2022/11/01 14:36:30 - mmengine - INFO - Epoch(train) [154][50/63] lr: 1.5382e-03 eta: 11:58:18 time: 0.5423 data_time: 0.0075 memory: 17620 loss: 2.7481 loss_prob: 1.7439 loss_thr: 0.7225 loss_db: 0.2817 2022/11/01 14:36:33 - mmengine - INFO - Epoch(train) [154][55/63] lr: 1.5382e-03 eta: 11:58:18 time: 0.5461 data_time: 0.0225 memory: 17620 loss: 2.4841 loss_prob: 1.5515 loss_thr: 0.6859 loss_db: 0.2467 2022/11/01 14:36:35 - mmengine - INFO - Epoch(train) [154][60/63] lr: 1.5382e-03 eta: 11:58:05 time: 0.5488 data_time: 0.0198 memory: 17620 loss: 2.5828 loss_prob: 1.6273 loss_thr: 0.6925 loss_db: 0.2630 2022/11/01 14:36:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:36:42 - mmengine - INFO - Epoch(train) [155][5/63] lr: 1.5482e-03 eta: 11:58:05 time: 0.7186 data_time: 0.2080 memory: 17620 loss: 2.5731 loss_prob: 1.5973 loss_thr: 0.7113 loss_db: 0.2645 2022/11/01 14:36:45 - mmengine - INFO - Epoch(train) [155][10/63] lr: 1.5482e-03 eta: 11:57:51 time: 0.7748 data_time: 0.2141 memory: 17620 loss: 2.5472 loss_prob: 1.5635 loss_thr: 0.7312 loss_db: 0.2526 2022/11/01 14:36:48 - mmengine - INFO - Epoch(train) [155][15/63] lr: 1.5482e-03 eta: 11:57:51 time: 0.5896 data_time: 0.0122 memory: 17620 loss: 2.3752 loss_prob: 1.4569 loss_thr: 0.6822 loss_db: 0.2361 2022/11/01 14:36:50 - mmengine - INFO - Epoch(train) [155][20/63] lr: 1.5482e-03 eta: 11:57:40 time: 0.5817 data_time: 0.0093 memory: 17620 loss: 2.6542 loss_prob: 1.6780 loss_thr: 0.6937 loss_db: 0.2825 2022/11/01 14:36:53 - mmengine - INFO - Epoch(train) [155][25/63] lr: 1.5482e-03 eta: 11:57:40 time: 0.5500 data_time: 0.0110 memory: 17620 loss: 2.9163 loss_prob: 1.8570 loss_thr: 0.7408 loss_db: 0.3185 2022/11/01 14:36:56 - mmengine - INFO - Epoch(train) [155][30/63] lr: 1.5482e-03 eta: 11:57:27 time: 0.5713 data_time: 0.0317 memory: 17620 loss: 2.8269 loss_prob: 1.7912 loss_thr: 0.7343 loss_db: 0.3013 2022/11/01 14:36:59 - mmengine - INFO - Epoch(train) [155][35/63] lr: 1.5482e-03 eta: 11:57:27 time: 0.5730 data_time: 0.0299 memory: 17620 loss: 2.6691 loss_prob: 1.6755 loss_thr: 0.7167 loss_db: 0.2769 2022/11/01 14:37:01 - mmengine - INFO - Epoch(train) [155][40/63] lr: 1.5482e-03 eta: 11:57:12 time: 0.5194 data_time: 0.0054 memory: 17620 loss: 2.7316 loss_prob: 1.7128 loss_thr: 0.7300 loss_db: 0.2888 2022/11/01 14:37:04 - mmengine - INFO - Epoch(train) [155][45/63] lr: 1.5482e-03 eta: 11:57:12 time: 0.5494 data_time: 0.0112 memory: 17620 loss: 2.6805 loss_prob: 1.6781 loss_thr: 0.7189 loss_db: 0.2835 2022/11/01 14:37:07 - mmengine - INFO - Epoch(train) [155][50/63] lr: 1.5482e-03 eta: 11:57:00 time: 0.5680 data_time: 0.0241 memory: 17620 loss: 2.5285 loss_prob: 1.5695 loss_thr: 0.6979 loss_db: 0.2611 2022/11/01 14:37:10 - mmengine - INFO - Epoch(train) [155][55/63] lr: 1.5482e-03 eta: 11:57:00 time: 0.5579 data_time: 0.0248 memory: 17620 loss: 2.4562 loss_prob: 1.5141 loss_thr: 0.6911 loss_db: 0.2510 2022/11/01 14:37:13 - mmengine - INFO - Epoch(train) [155][60/63] lr: 1.5482e-03 eta: 11:56:46 time: 0.5529 data_time: 0.0139 memory: 17620 loss: 2.3352 loss_prob: 1.4263 loss_thr: 0.6800 loss_db: 0.2289 2022/11/01 14:37:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:37:19 - mmengine - INFO - Epoch(train) [156][5/63] lr: 1.5582e-03 eta: 11:56:46 time: 0.7306 data_time: 0.1965 memory: 17620 loss: 2.4470 loss_prob: 1.5192 loss_thr: 0.6812 loss_db: 0.2466 2022/11/01 14:37:22 - mmengine - INFO - Epoch(train) [156][10/63] lr: 1.5582e-03 eta: 11:56:31 time: 0.7513 data_time: 0.1970 memory: 17620 loss: 2.5389 loss_prob: 1.5836 loss_thr: 0.6975 loss_db: 0.2578 2022/11/01 14:37:25 - mmengine - INFO - Epoch(train) [156][15/63] lr: 1.5582e-03 eta: 11:56:31 time: 0.5864 data_time: 0.0085 memory: 17620 loss: 2.4419 loss_prob: 1.5022 loss_thr: 0.6969 loss_db: 0.2427 2022/11/01 14:37:28 - mmengine - INFO - Epoch(train) [156][20/63] lr: 1.5582e-03 eta: 11:56:22 time: 0.6160 data_time: 0.0074 memory: 17620 loss: 2.4594 loss_prob: 1.5058 loss_thr: 0.7109 loss_db: 0.2427 2022/11/01 14:37:31 - mmengine - INFO - Epoch(train) [156][25/63] lr: 1.5582e-03 eta: 11:56:22 time: 0.6285 data_time: 0.0324 memory: 17620 loss: 2.4976 loss_prob: 1.5392 loss_thr: 0.7133 loss_db: 0.2452 2022/11/01 14:37:34 - mmengine - INFO - Epoch(train) [156][30/63] lr: 1.5582e-03 eta: 11:56:15 time: 0.6392 data_time: 0.0315 memory: 17620 loss: 2.3419 loss_prob: 1.4370 loss_thr: 0.6790 loss_db: 0.2259 2022/11/01 14:37:37 - mmengine - INFO - Epoch(train) [156][35/63] lr: 1.5582e-03 eta: 11:56:15 time: 0.6357 data_time: 0.0123 memory: 17620 loss: 2.3114 loss_prob: 1.4018 loss_thr: 0.6850 loss_db: 0.2246 2022/11/01 14:37:41 - mmengine - INFO - Epoch(train) [156][40/63] lr: 1.5582e-03 eta: 11:56:11 time: 0.6910 data_time: 0.0114 memory: 17620 loss: 2.3733 loss_prob: 1.4474 loss_thr: 0.6915 loss_db: 0.2343 2022/11/01 14:37:44 - mmengine - INFO - Epoch(train) [156][45/63] lr: 1.5582e-03 eta: 11:56:11 time: 0.6599 data_time: 0.0083 memory: 17620 loss: 2.6454 loss_prob: 1.6552 loss_thr: 0.7190 loss_db: 0.2712 2022/11/01 14:37:47 - mmengine - INFO - Epoch(train) [156][50/63] lr: 1.5582e-03 eta: 11:56:00 time: 0.5944 data_time: 0.0238 memory: 17620 loss: 2.9254 loss_prob: 1.8571 loss_thr: 0.7548 loss_db: 0.3135 2022/11/01 14:37:50 - mmengine - INFO - Epoch(train) [156][55/63] lr: 1.5582e-03 eta: 11:56:00 time: 0.6341 data_time: 0.0205 memory: 17620 loss: 2.6900 loss_prob: 1.6664 loss_thr: 0.7464 loss_db: 0.2773 2022/11/01 14:37:53 - mmengine - INFO - Epoch(train) [156][60/63] lr: 1.5582e-03 eta: 11:55:52 time: 0.6207 data_time: 0.0258 memory: 17620 loss: 2.4830 loss_prob: 1.5279 loss_thr: 0.7079 loss_db: 0.2471 2022/11/01 14:37:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:38:00 - mmengine - INFO - Epoch(train) [157][5/63] lr: 1.5683e-03 eta: 11:55:52 time: 0.7892 data_time: 0.2153 memory: 17620 loss: 2.5811 loss_prob: 1.6214 loss_thr: 0.6865 loss_db: 0.2733 2022/11/01 14:38:03 - mmengine - INFO - Epoch(train) [157][10/63] lr: 1.5683e-03 eta: 11:55:45 time: 0.8795 data_time: 0.2132 memory: 17620 loss: 2.6505 loss_prob: 1.6766 loss_thr: 0.6923 loss_db: 0.2815 2022/11/01 14:38:07 - mmengine - INFO - Epoch(train) [157][15/63] lr: 1.5683e-03 eta: 11:55:45 time: 0.6799 data_time: 0.0068 memory: 17620 loss: 2.5965 loss_prob: 1.6022 loss_thr: 0.7322 loss_db: 0.2621 2022/11/01 14:38:10 - mmengine - INFO - Epoch(train) [157][20/63] lr: 1.5683e-03 eta: 11:55:38 time: 0.6393 data_time: 0.0101 memory: 17620 loss: 2.4162 loss_prob: 1.4506 loss_thr: 0.7264 loss_db: 0.2392 2022/11/01 14:38:12 - mmengine - INFO - Epoch(train) [157][25/63] lr: 1.5683e-03 eta: 11:55:38 time: 0.5661 data_time: 0.0190 memory: 17620 loss: 2.2385 loss_prob: 1.3382 loss_thr: 0.6806 loss_db: 0.2196 2022/11/01 14:38:15 - mmengine - INFO - Epoch(train) [157][30/63] lr: 1.5683e-03 eta: 11:55:25 time: 0.5686 data_time: 0.0331 memory: 17620 loss: 2.2464 loss_prob: 1.3590 loss_thr: 0.6669 loss_db: 0.2206 2022/11/01 14:38:18 - mmengine - INFO - Epoch(train) [157][35/63] lr: 1.5683e-03 eta: 11:55:25 time: 0.5615 data_time: 0.0260 memory: 17620 loss: 2.4994 loss_prob: 1.5475 loss_thr: 0.7012 loss_db: 0.2507 2022/11/01 14:38:21 - mmengine - INFO - Epoch(train) [157][40/63] lr: 1.5683e-03 eta: 11:55:13 time: 0.5671 data_time: 0.0080 memory: 17620 loss: 2.3695 loss_prob: 1.4578 loss_thr: 0.6783 loss_db: 0.2334 2022/11/01 14:38:24 - mmengine - INFO - Epoch(train) [157][45/63] lr: 1.5683e-03 eta: 11:55:13 time: 0.5580 data_time: 0.0061 memory: 17620 loss: 2.2160 loss_prob: 1.3477 loss_thr: 0.6504 loss_db: 0.2179 2022/11/01 14:38:27 - mmengine - INFO - Epoch(train) [157][50/63] lr: 1.5683e-03 eta: 11:55:01 time: 0.5734 data_time: 0.0202 memory: 17620 loss: 2.5643 loss_prob: 1.5971 loss_thr: 0.6986 loss_db: 0.2686 2022/11/01 14:38:30 - mmengine - INFO - Epoch(train) [157][55/63] lr: 1.5683e-03 eta: 11:55:01 time: 0.6083 data_time: 0.0202 memory: 17620 loss: 2.9128 loss_prob: 1.8456 loss_thr: 0.7452 loss_db: 0.3220 2022/11/01 14:38:32 - mmengine - INFO - Epoch(train) [157][60/63] lr: 1.5683e-03 eta: 11:54:49 time: 0.5649 data_time: 0.0082 memory: 17620 loss: 2.8667 loss_prob: 1.8185 loss_thr: 0.7347 loss_db: 0.3135 2022/11/01 14:38:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:38:39 - mmengine - INFO - Epoch(train) [158][5/63] lr: 1.5783e-03 eta: 11:54:49 time: 0.7450 data_time: 0.1854 memory: 17620 loss: 2.4095 loss_prob: 1.4771 loss_thr: 0.6974 loss_db: 0.2350 2022/11/01 14:38:42 - mmengine - INFO - Epoch(train) [158][10/63] lr: 1.5783e-03 eta: 11:54:36 time: 0.7839 data_time: 0.1856 memory: 17620 loss: 2.3558 loss_prob: 1.4454 loss_thr: 0.6760 loss_db: 0.2344 2022/11/01 14:38:44 - mmengine - INFO - Epoch(train) [158][15/63] lr: 1.5783e-03 eta: 11:54:36 time: 0.5630 data_time: 0.0084 memory: 17620 loss: 2.3312 loss_prob: 1.4220 loss_thr: 0.6780 loss_db: 0.2311 2022/11/01 14:38:47 - mmengine - INFO - Epoch(train) [158][20/63] lr: 1.5783e-03 eta: 11:54:24 time: 0.5639 data_time: 0.0080 memory: 17620 loss: 2.1965 loss_prob: 1.3153 loss_thr: 0.6728 loss_db: 0.2083 2022/11/01 14:38:50 - mmengine - INFO - Epoch(train) [158][25/63] lr: 1.5783e-03 eta: 11:54:24 time: 0.5794 data_time: 0.0154 memory: 17620 loss: 2.2643 loss_prob: 1.3640 loss_thr: 0.6783 loss_db: 0.2220 2022/11/01 14:38:53 - mmengine - INFO - Epoch(train) [158][30/63] lr: 1.5783e-03 eta: 11:54:13 time: 0.5819 data_time: 0.0356 memory: 17620 loss: 2.4652 loss_prob: 1.4988 loss_thr: 0.7166 loss_db: 0.2498 2022/11/01 14:38:56 - mmengine - INFO - Epoch(train) [158][35/63] lr: 1.5783e-03 eta: 11:54:13 time: 0.5387 data_time: 0.0255 memory: 17620 loss: 2.4789 loss_prob: 1.5181 loss_thr: 0.7061 loss_db: 0.2547 2022/11/01 14:38:58 - mmengine - INFO - Epoch(train) [158][40/63] lr: 1.5783e-03 eta: 11:53:57 time: 0.5118 data_time: 0.0061 memory: 17620 loss: 2.4064 loss_prob: 1.4761 loss_thr: 0.6861 loss_db: 0.2441 2022/11/01 14:39:01 - mmengine - INFO - Epoch(train) [158][45/63] lr: 1.5783e-03 eta: 11:53:57 time: 0.5267 data_time: 0.0074 memory: 17620 loss: 2.4325 loss_prob: 1.4849 loss_thr: 0.7097 loss_db: 0.2380 2022/11/01 14:39:04 - mmengine - INFO - Epoch(train) [158][50/63] lr: 1.5783e-03 eta: 11:53:43 time: 0.5484 data_time: 0.0140 memory: 17620 loss: 2.3577 loss_prob: 1.4196 loss_thr: 0.7099 loss_db: 0.2281 2022/11/01 14:39:07 - mmengine - INFO - Epoch(train) [158][55/63] lr: 1.5783e-03 eta: 11:53:43 time: 0.5748 data_time: 0.0202 memory: 17620 loss: 2.3822 loss_prob: 1.4520 loss_thr: 0.6946 loss_db: 0.2356 2022/11/01 14:39:09 - mmengine - INFO - Epoch(train) [158][60/63] lr: 1.5783e-03 eta: 11:53:31 time: 0.5680 data_time: 0.0125 memory: 17620 loss: 2.3272 loss_prob: 1.4200 loss_thr: 0.6801 loss_db: 0.2271 2022/11/01 14:39:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:39:16 - mmengine - INFO - Epoch(train) [159][5/63] lr: 1.5884e-03 eta: 11:53:31 time: 0.7752 data_time: 0.2284 memory: 17620 loss: 2.3614 loss_prob: 1.4387 loss_thr: 0.6903 loss_db: 0.2323 2022/11/01 14:39:19 - mmengine - INFO - Epoch(train) [159][10/63] lr: 1.5884e-03 eta: 11:53:22 time: 0.8310 data_time: 0.2327 memory: 17620 loss: 2.2018 loss_prob: 1.3300 loss_thr: 0.6571 loss_db: 0.2147 2022/11/01 14:39:22 - mmengine - INFO - Epoch(train) [159][15/63] lr: 1.5884e-03 eta: 11:53:22 time: 0.5997 data_time: 0.0113 memory: 17620 loss: 2.2887 loss_prob: 1.3997 loss_thr: 0.6610 loss_db: 0.2280 2022/11/01 14:39:25 - mmengine - INFO - Epoch(train) [159][20/63] lr: 1.5884e-03 eta: 11:53:11 time: 0.5946 data_time: 0.0066 memory: 17620 loss: 2.4197 loss_prob: 1.4979 loss_thr: 0.6743 loss_db: 0.2476 2022/11/01 14:39:28 - mmengine - INFO - Epoch(train) [159][25/63] lr: 1.5884e-03 eta: 11:53:11 time: 0.5907 data_time: 0.0324 memory: 17620 loss: 2.5183 loss_prob: 1.5552 loss_thr: 0.7078 loss_db: 0.2553 2022/11/01 14:39:31 - mmengine - INFO - Epoch(train) [159][30/63] lr: 1.5884e-03 eta: 11:52:59 time: 0.5667 data_time: 0.0317 memory: 17620 loss: 2.3191 loss_prob: 1.4129 loss_thr: 0.6785 loss_db: 0.2277 2022/11/01 14:39:33 - mmengine - INFO - Epoch(train) [159][35/63] lr: 1.5884e-03 eta: 11:52:59 time: 0.5417 data_time: 0.0071 memory: 17620 loss: 2.4346 loss_prob: 1.4981 loss_thr: 0.6877 loss_db: 0.2489 2022/11/01 14:39:36 - mmengine - INFO - Epoch(train) [159][40/63] lr: 1.5884e-03 eta: 11:52:46 time: 0.5457 data_time: 0.0066 memory: 17620 loss: 2.6674 loss_prob: 1.6700 loss_thr: 0.7134 loss_db: 0.2840 2022/11/01 14:39:39 - mmengine - INFO - Epoch(train) [159][45/63] lr: 1.5884e-03 eta: 11:52:46 time: 0.5397 data_time: 0.0058 memory: 17620 loss: 2.7194 loss_prob: 1.7254 loss_thr: 0.7028 loss_db: 0.2911 2022/11/01 14:39:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:39:42 - mmengine - INFO - Epoch(train) [159][50/63] lr: 1.5884e-03 eta: 11:52:34 time: 0.5741 data_time: 0.0229 memory: 17620 loss: 2.6760 loss_prob: 1.6734 loss_thr: 0.7235 loss_db: 0.2791 2022/11/01 14:39:44 - mmengine - INFO - Epoch(train) [159][55/63] lr: 1.5884e-03 eta: 11:52:34 time: 0.5650 data_time: 0.0234 memory: 17620 loss: 2.8752 loss_prob: 1.7849 loss_thr: 0.7841 loss_db: 0.3063 2022/11/01 14:39:47 - mmengine - INFO - Epoch(train) [159][60/63] lr: 1.5884e-03 eta: 11:52:19 time: 0.5176 data_time: 0.0069 memory: 17620 loss: 2.8823 loss_prob: 1.8098 loss_thr: 0.7658 loss_db: 0.3067 2022/11/01 14:39:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:39:56 - mmengine - INFO - Epoch(train) [160][5/63] lr: 1.5984e-03 eta: 11:52:19 time: 0.9672 data_time: 0.2667 memory: 17620 loss: 2.6242 loss_prob: 1.6097 loss_thr: 0.7456 loss_db: 0.2688 2022/11/01 14:39:58 - mmengine - INFO - Epoch(train) [160][10/63] lr: 1.5984e-03 eta: 11:52:19 time: 0.9786 data_time: 0.2662 memory: 17620 loss: 2.7020 loss_prob: 1.6796 loss_thr: 0.7387 loss_db: 0.2837 2022/11/01 14:40:01 - mmengine - INFO - Epoch(train) [160][15/63] lr: 1.5984e-03 eta: 11:52:19 time: 0.5623 data_time: 0.0057 memory: 17620 loss: 2.6733 loss_prob: 1.6646 loss_thr: 0.7325 loss_db: 0.2762 2022/11/01 14:40:04 - mmengine - INFO - Epoch(train) [160][20/63] lr: 1.5984e-03 eta: 11:52:08 time: 0.5895 data_time: 0.0063 memory: 17620 loss: 2.4199 loss_prob: 1.4809 loss_thr: 0.7004 loss_db: 0.2387 2022/11/01 14:40:08 - mmengine - INFO - Epoch(train) [160][25/63] lr: 1.5984e-03 eta: 11:52:08 time: 0.6740 data_time: 0.0414 memory: 17620 loss: 2.5958 loss_prob: 1.6313 loss_thr: 0.6977 loss_db: 0.2669 2022/11/01 14:40:11 - mmengine - INFO - Epoch(train) [160][30/63] lr: 1.5984e-03 eta: 11:52:02 time: 0.6456 data_time: 0.0418 memory: 17620 loss: 2.6510 loss_prob: 1.6738 loss_thr: 0.7011 loss_db: 0.2762 2022/11/01 14:40:14 - mmengine - INFO - Epoch(train) [160][35/63] lr: 1.5984e-03 eta: 11:52:02 time: 0.6249 data_time: 0.0067 memory: 17620 loss: 2.4879 loss_prob: 1.5446 loss_thr: 0.6919 loss_db: 0.2514 2022/11/01 14:40:17 - mmengine - INFO - Epoch(train) [160][40/63] lr: 1.5984e-03 eta: 11:51:53 time: 0.6136 data_time: 0.0048 memory: 17620 loss: 2.4652 loss_prob: 1.5247 loss_thr: 0.6915 loss_db: 0.2489 2022/11/01 14:40:20 - mmengine - INFO - Epoch(train) [160][45/63] lr: 1.5984e-03 eta: 11:51:53 time: 0.5743 data_time: 0.0058 memory: 17620 loss: 2.4695 loss_prob: 1.5289 loss_thr: 0.6918 loss_db: 0.2488 2022/11/01 14:40:23 - mmengine - INFO - Epoch(train) [160][50/63] lr: 1.5984e-03 eta: 11:51:41 time: 0.5814 data_time: 0.0274 memory: 17620 loss: 2.4664 loss_prob: 1.5255 loss_thr: 0.6992 loss_db: 0.2417 2022/11/01 14:40:26 - mmengine - INFO - Epoch(train) [160][55/63] lr: 1.5984e-03 eta: 11:51:41 time: 0.6294 data_time: 0.0273 memory: 17620 loss: 2.4684 loss_prob: 1.5299 loss_thr: 0.6930 loss_db: 0.2455 2022/11/01 14:40:29 - mmengine - INFO - Epoch(train) [160][60/63] lr: 1.5984e-03 eta: 11:51:36 time: 0.6700 data_time: 0.0060 memory: 17620 loss: 2.6054 loss_prob: 1.6466 loss_thr: 0.6926 loss_db: 0.2662 2022/11/01 14:40:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:40:32 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/11/01 14:40:39 - mmengine - INFO - Epoch(val) [160][5/32] eta: 11:51:36 time: 0.5754 data_time: 0.0845 memory: 17620 2022/11/01 14:40:42 - mmengine - INFO - Epoch(val) [160][10/32] eta: 0:00:13 time: 0.6274 data_time: 0.0953 memory: 15725 2022/11/01 14:40:45 - mmengine - INFO - Epoch(val) [160][15/32] eta: 0:00:13 time: 0.5944 data_time: 0.0497 memory: 15725 2022/11/01 14:40:48 - mmengine - INFO - Epoch(val) [160][20/32] eta: 0:00:07 time: 0.6040 data_time: 0.0693 memory: 15725 2022/11/01 14:40:50 - mmengine - INFO - Epoch(val) [160][25/32] eta: 0:00:07 time: 0.5752 data_time: 0.0493 memory: 15725 2022/11/01 14:40:53 - mmengine - INFO - Epoch(val) [160][30/32] eta: 0:00:01 time: 0.5450 data_time: 0.0222 memory: 15725 2022/11/01 14:40:54 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7737, precision: 0.6812, hmean: 0.7245 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7737, precision: 0.7940, hmean: 0.7837 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7641, precision: 0.8644, hmean: 0.8111 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7169, precision: 0.9113, hmean: 0.8025 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.5402, precision: 0.9508, hmean: 0.6890 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.0515, precision: 0.9907, hmean: 0.0979 2022/11/01 14:40:54 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 14:40:54 - mmengine - INFO - Epoch(val) [160][32/32] icdar/precision: 0.8644 icdar/recall: 0.7641 icdar/hmean: 0.8111 2022/11/01 14:40:59 - mmengine - INFO - Epoch(train) [161][5/63] lr: 1.6084e-03 eta: 0:00:01 time: 0.8310 data_time: 0.2056 memory: 17620 loss: 2.4930 loss_prob: 1.5445 loss_thr: 0.7035 loss_db: 0.2449 2022/11/01 14:41:01 - mmengine - INFO - Epoch(train) [161][10/63] lr: 1.6084e-03 eta: 11:51:22 time: 0.7555 data_time: 0.2045 memory: 17620 loss: 2.3435 loss_prob: 1.4189 loss_thr: 0.6956 loss_db: 0.2290 2022/11/01 14:41:04 - mmengine - INFO - Epoch(train) [161][15/63] lr: 1.6084e-03 eta: 11:51:22 time: 0.5365 data_time: 0.0082 memory: 17620 loss: 2.3951 loss_prob: 1.4496 loss_thr: 0.7086 loss_db: 0.2368 2022/11/01 14:41:07 - mmengine - INFO - Epoch(train) [161][20/63] lr: 1.6084e-03 eta: 11:51:09 time: 0.5530 data_time: 0.0086 memory: 17620 loss: 2.6306 loss_prob: 1.6351 loss_thr: 0.7222 loss_db: 0.2733 2022/11/01 14:41:10 - mmengine - INFO - Epoch(train) [161][25/63] lr: 1.6084e-03 eta: 11:51:09 time: 0.5785 data_time: 0.0298 memory: 17620 loss: 2.5261 loss_prob: 1.5745 loss_thr: 0.6928 loss_db: 0.2589 2022/11/01 14:41:13 - mmengine - INFO - Epoch(train) [161][30/63] lr: 1.6084e-03 eta: 11:50:56 time: 0.5570 data_time: 0.0318 memory: 17620 loss: 2.2538 loss_prob: 1.3738 loss_thr: 0.6625 loss_db: 0.2174 2022/11/01 14:41:15 - mmengine - INFO - Epoch(train) [161][35/63] lr: 1.6084e-03 eta: 11:50:56 time: 0.5240 data_time: 0.0108 memory: 17620 loss: 2.2491 loss_prob: 1.3698 loss_thr: 0.6599 loss_db: 0.2194 2022/11/01 14:41:18 - mmengine - INFO - Epoch(train) [161][40/63] lr: 1.6084e-03 eta: 11:50:41 time: 0.5224 data_time: 0.0091 memory: 17620 loss: 2.1956 loss_prob: 1.3392 loss_thr: 0.6404 loss_db: 0.2161 2022/11/01 14:41:20 - mmengine - INFO - Epoch(train) [161][45/63] lr: 1.6084e-03 eta: 11:50:41 time: 0.5343 data_time: 0.0100 memory: 17620 loss: 2.3651 loss_prob: 1.4651 loss_thr: 0.6643 loss_db: 0.2357 2022/11/01 14:41:23 - mmengine - INFO - Epoch(train) [161][50/63] lr: 1.6084e-03 eta: 11:50:28 time: 0.5526 data_time: 0.0214 memory: 17620 loss: 2.7065 loss_prob: 1.7114 loss_thr: 0.7109 loss_db: 0.2842 2022/11/01 14:41:26 - mmengine - INFO - Epoch(train) [161][55/63] lr: 1.6084e-03 eta: 11:50:28 time: 0.5580 data_time: 0.0179 memory: 17620 loss: 2.5873 loss_prob: 1.6137 loss_thr: 0.7051 loss_db: 0.2685 2022/11/01 14:41:29 - mmengine - INFO - Epoch(train) [161][60/63] lr: 1.6084e-03 eta: 11:50:15 time: 0.5404 data_time: 0.0054 memory: 17620 loss: 2.4812 loss_prob: 1.5228 loss_thr: 0.7134 loss_db: 0.2450 2022/11/01 14:41:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:41:35 - mmengine - INFO - Epoch(train) [162][5/63] lr: 1.6185e-03 eta: 11:50:15 time: 0.7417 data_time: 0.2062 memory: 17620 loss: 2.4428 loss_prob: 1.4887 loss_thr: 0.7144 loss_db: 0.2397 2022/11/01 14:41:38 - mmengine - INFO - Epoch(train) [162][10/63] lr: 1.6185e-03 eta: 11:50:02 time: 0.7731 data_time: 0.2290 memory: 17620 loss: 2.1790 loss_prob: 1.2893 loss_thr: 0.6832 loss_db: 0.2065 2022/11/01 14:41:41 - mmengine - INFO - Epoch(train) [162][15/63] lr: 1.6185e-03 eta: 11:50:02 time: 0.5827 data_time: 0.0296 memory: 17620 loss: 2.2590 loss_prob: 1.3664 loss_thr: 0.6729 loss_db: 0.2197 2022/11/01 14:41:44 - mmengine - INFO - Epoch(train) [162][20/63] lr: 1.6185e-03 eta: 11:49:51 time: 0.5860 data_time: 0.0059 memory: 17620 loss: 2.5571 loss_prob: 1.6062 loss_thr: 0.6899 loss_db: 0.2610 2022/11/01 14:41:47 - mmengine - INFO - Epoch(train) [162][25/63] lr: 1.6185e-03 eta: 11:49:51 time: 0.5849 data_time: 0.0146 memory: 17620 loss: 2.6988 loss_prob: 1.6999 loss_thr: 0.7204 loss_db: 0.2785 2022/11/01 14:41:50 - mmengine - INFO - Epoch(train) [162][30/63] lr: 1.6185e-03 eta: 11:49:41 time: 0.6025 data_time: 0.0358 memory: 17620 loss: 2.6069 loss_prob: 1.6363 loss_thr: 0.7009 loss_db: 0.2697 2022/11/01 14:41:52 - mmengine - INFO - Epoch(train) [162][35/63] lr: 1.6185e-03 eta: 11:49:41 time: 0.5707 data_time: 0.0271 memory: 17620 loss: 2.3270 loss_prob: 1.4487 loss_thr: 0.6444 loss_db: 0.2338 2022/11/01 14:41:55 - mmengine - INFO - Epoch(train) [162][40/63] lr: 1.6185e-03 eta: 11:49:27 time: 0.5355 data_time: 0.0050 memory: 17620 loss: 2.2505 loss_prob: 1.3840 loss_thr: 0.6447 loss_db: 0.2217 2022/11/01 14:41:58 - mmengine - INFO - Epoch(train) [162][45/63] lr: 1.6185e-03 eta: 11:49:27 time: 0.5341 data_time: 0.0049 memory: 17620 loss: 2.3836 loss_prob: 1.4639 loss_thr: 0.6779 loss_db: 0.2419 2022/11/01 14:42:01 - mmengine - INFO - Epoch(train) [162][50/63] lr: 1.6185e-03 eta: 11:49:13 time: 0.5287 data_time: 0.0185 memory: 17620 loss: 2.4634 loss_prob: 1.5037 loss_thr: 0.7129 loss_db: 0.2468 2022/11/01 14:42:03 - mmengine - INFO - Epoch(train) [162][55/63] lr: 1.6185e-03 eta: 11:49:13 time: 0.5618 data_time: 0.0235 memory: 17620 loss: 2.5090 loss_prob: 1.5443 loss_thr: 0.7165 loss_db: 0.2481 2022/11/01 14:42:06 - mmengine - INFO - Epoch(train) [162][60/63] lr: 1.6185e-03 eta: 11:49:02 time: 0.5734 data_time: 0.0109 memory: 17620 loss: 2.3845 loss_prob: 1.4659 loss_thr: 0.6856 loss_db: 0.2330 2022/11/01 14:42:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:42:13 - mmengine - INFO - Epoch(train) [163][5/63] lr: 1.6285e-03 eta: 11:49:02 time: 0.7924 data_time: 0.1881 memory: 17620 loss: 2.1104 loss_prob: 1.2722 loss_thr: 0.6408 loss_db: 0.1974 2022/11/01 14:42:17 - mmengine - INFO - Epoch(train) [163][10/63] lr: 1.6285e-03 eta: 11:48:57 time: 0.9109 data_time: 0.1918 memory: 17620 loss: 2.1708 loss_prob: 1.3195 loss_thr: 0.6403 loss_db: 0.2110 2022/11/01 14:42:20 - mmengine - INFO - Epoch(train) [163][15/63] lr: 1.6285e-03 eta: 11:48:57 time: 0.6425 data_time: 0.0103 memory: 17620 loss: 2.2692 loss_prob: 1.3835 loss_thr: 0.6615 loss_db: 0.2242 2022/11/01 14:42:22 - mmengine - INFO - Epoch(train) [163][20/63] lr: 1.6285e-03 eta: 11:48:44 time: 0.5374 data_time: 0.0054 memory: 17620 loss: 2.4047 loss_prob: 1.4883 loss_thr: 0.6756 loss_db: 0.2408 2022/11/01 14:42:25 - mmengine - INFO - Epoch(train) [163][25/63] lr: 1.6285e-03 eta: 11:48:44 time: 0.5431 data_time: 0.0119 memory: 17620 loss: 2.3983 loss_prob: 1.4845 loss_thr: 0.6705 loss_db: 0.2433 2022/11/01 14:42:28 - mmengine - INFO - Epoch(train) [163][30/63] lr: 1.6285e-03 eta: 11:48:32 time: 0.5717 data_time: 0.0306 memory: 17620 loss: 2.4600 loss_prob: 1.5087 loss_thr: 0.7064 loss_db: 0.2449 2022/11/01 14:42:31 - mmengine - INFO - Epoch(train) [163][35/63] lr: 1.6285e-03 eta: 11:48:32 time: 0.5762 data_time: 0.0276 memory: 17620 loss: 2.3491 loss_prob: 1.4292 loss_thr: 0.6888 loss_db: 0.2311 2022/11/01 14:42:33 - mmengine - INFO - Epoch(train) [163][40/63] lr: 1.6285e-03 eta: 11:48:20 time: 0.5668 data_time: 0.0088 memory: 17620 loss: 2.3582 loss_prob: 1.4294 loss_thr: 0.6916 loss_db: 0.2372 2022/11/01 14:42:37 - mmengine - INFO - Epoch(train) [163][45/63] lr: 1.6285e-03 eta: 11:48:20 time: 0.5818 data_time: 0.0050 memory: 17620 loss: 2.5498 loss_prob: 1.5745 loss_thr: 0.7127 loss_db: 0.2626 2022/11/01 14:42:40 - mmengine - INFO - Epoch(train) [163][50/63] lr: 1.6285e-03 eta: 11:48:13 time: 0.6378 data_time: 0.0194 memory: 17620 loss: 2.5568 loss_prob: 1.5901 loss_thr: 0.7079 loss_db: 0.2589 2022/11/01 14:42:43 - mmengine - INFO - Epoch(train) [163][55/63] lr: 1.6285e-03 eta: 11:48:13 time: 0.6133 data_time: 0.0224 memory: 17620 loss: 2.3899 loss_prob: 1.4696 loss_thr: 0.6855 loss_db: 0.2348 2022/11/01 14:42:45 - mmengine - INFO - Epoch(train) [163][60/63] lr: 1.6285e-03 eta: 11:48:00 time: 0.5501 data_time: 0.0091 memory: 17620 loss: 2.2162 loss_prob: 1.3330 loss_thr: 0.6684 loss_db: 0.2148 2022/11/01 14:42:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:42:53 - mmengine - INFO - Epoch(train) [164][5/63] lr: 1.6386e-03 eta: 11:48:00 time: 0.8159 data_time: 0.2081 memory: 17620 loss: 2.2640 loss_prob: 1.3750 loss_thr: 0.6672 loss_db: 0.2217 2022/11/01 14:42:56 - mmengine - INFO - Epoch(train) [164][10/63] lr: 1.6386e-03 eta: 11:47:56 time: 0.9144 data_time: 0.2117 memory: 17620 loss: 2.2724 loss_prob: 1.3674 loss_thr: 0.6819 loss_db: 0.2231 2022/11/01 14:42:59 - mmengine - INFO - Epoch(train) [164][15/63] lr: 1.6386e-03 eta: 11:47:56 time: 0.6924 data_time: 0.0096 memory: 17620 loss: 2.2760 loss_prob: 1.3678 loss_thr: 0.6863 loss_db: 0.2220 2022/11/01 14:43:02 - mmengine - INFO - Epoch(train) [164][20/63] lr: 1.6386e-03 eta: 11:47:49 time: 0.6435 data_time: 0.0059 memory: 17620 loss: 2.4913 loss_prob: 1.5321 loss_thr: 0.7080 loss_db: 0.2511 2022/11/01 14:43:06 - mmengine - INFO - Epoch(train) [164][25/63] lr: 1.6386e-03 eta: 11:47:49 time: 0.6296 data_time: 0.0198 memory: 17620 loss: 2.7823 loss_prob: 1.7519 loss_thr: 0.7416 loss_db: 0.2888 2022/11/01 14:43:09 - mmengine - INFO - Epoch(train) [164][30/63] lr: 1.6386e-03 eta: 11:47:41 time: 0.6266 data_time: 0.0296 memory: 17620 loss: 2.8697 loss_prob: 1.8320 loss_thr: 0.7295 loss_db: 0.3082 2022/11/01 14:43:11 - mmengine - INFO - Epoch(train) [164][35/63] lr: 1.6386e-03 eta: 11:47:41 time: 0.5485 data_time: 0.0152 memory: 17620 loss: 2.8779 loss_prob: 1.8221 loss_thr: 0.7454 loss_db: 0.3103 2022/11/01 14:43:14 - mmengine - INFO - Epoch(train) [164][40/63] lr: 1.6386e-03 eta: 11:47:26 time: 0.5204 data_time: 0.0048 memory: 17620 loss: 2.6340 loss_prob: 1.6404 loss_thr: 0.7227 loss_db: 0.2709 2022/11/01 14:43:16 - mmengine - INFO - Epoch(train) [164][45/63] lr: 1.6386e-03 eta: 11:47:26 time: 0.5248 data_time: 0.0083 memory: 17620 loss: 2.4663 loss_prob: 1.5203 loss_thr: 0.7032 loss_db: 0.2428 2022/11/01 14:43:19 - mmengine - INFO - Epoch(train) [164][50/63] lr: 1.6386e-03 eta: 11:47:14 time: 0.5588 data_time: 0.0231 memory: 17620 loss: 2.5981 loss_prob: 1.6186 loss_thr: 0.7154 loss_db: 0.2642 2022/11/01 14:43:22 - mmengine - INFO - Epoch(train) [164][55/63] lr: 1.6386e-03 eta: 11:47:14 time: 0.5762 data_time: 0.0193 memory: 17620 loss: 2.6551 loss_prob: 1.6619 loss_thr: 0.7187 loss_db: 0.2745 2022/11/01 14:43:25 - mmengine - INFO - Epoch(train) [164][60/63] lr: 1.6386e-03 eta: 11:47:04 time: 0.5877 data_time: 0.0084 memory: 17620 loss: 2.5933 loss_prob: 1.6061 loss_thr: 0.7236 loss_db: 0.2636 2022/11/01 14:43:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:43:32 - mmengine - INFO - Epoch(train) [165][5/63] lr: 1.6486e-03 eta: 11:47:04 time: 0.7678 data_time: 0.1982 memory: 17620 loss: 2.3964 loss_prob: 1.4617 loss_thr: 0.6998 loss_db: 0.2349 2022/11/01 14:43:35 - mmengine - INFO - Epoch(train) [165][10/63] lr: 1.6486e-03 eta: 11:46:52 time: 0.8005 data_time: 0.1998 memory: 17620 loss: 2.4855 loss_prob: 1.5339 loss_thr: 0.7060 loss_db: 0.2456 2022/11/01 14:43:37 - mmengine - INFO - Epoch(train) [165][15/63] lr: 1.6486e-03 eta: 11:46:52 time: 0.5479 data_time: 0.0078 memory: 17620 loss: 2.7275 loss_prob: 1.7304 loss_thr: 0.7170 loss_db: 0.2801 2022/11/01 14:43:40 - mmengine - INFO - Epoch(train) [165][20/63] lr: 1.6486e-03 eta: 11:46:39 time: 0.5382 data_time: 0.0061 memory: 17620 loss: 2.7445 loss_prob: 1.7368 loss_thr: 0.7224 loss_db: 0.2853 2022/11/01 14:43:43 - mmengine - INFO - Epoch(train) [165][25/63] lr: 1.6486e-03 eta: 11:46:39 time: 0.5778 data_time: 0.0243 memory: 17620 loss: 2.5019 loss_prob: 1.5318 loss_thr: 0.7185 loss_db: 0.2517 2022/11/01 14:43:46 - mmengine - INFO - Epoch(train) [165][30/63] lr: 1.6486e-03 eta: 11:46:28 time: 0.5791 data_time: 0.0326 memory: 17620 loss: 2.3576 loss_prob: 1.4306 loss_thr: 0.6967 loss_db: 0.2304 2022/11/01 14:43:48 - mmengine - INFO - Epoch(train) [165][35/63] lr: 1.6486e-03 eta: 11:46:28 time: 0.5356 data_time: 0.0138 memory: 17620 loss: 2.3079 loss_prob: 1.4009 loss_thr: 0.6815 loss_db: 0.2255 2022/11/01 14:43:51 - mmengine - INFO - Epoch(train) [165][40/63] lr: 1.6486e-03 eta: 11:46:14 time: 0.5281 data_time: 0.0079 memory: 17620 loss: 2.4769 loss_prob: 1.5302 loss_thr: 0.6944 loss_db: 0.2524 2022/11/01 14:43:54 - mmengine - INFO - Epoch(train) [165][45/63] lr: 1.6486e-03 eta: 11:46:14 time: 0.5339 data_time: 0.0079 memory: 17620 loss: 2.5790 loss_prob: 1.6204 loss_thr: 0.6937 loss_db: 0.2650 2022/11/01 14:43:57 - mmengine - INFO - Epoch(train) [165][50/63] lr: 1.6486e-03 eta: 11:46:02 time: 0.5675 data_time: 0.0147 memory: 17620 loss: 2.4503 loss_prob: 1.4968 loss_thr: 0.7131 loss_db: 0.2404 2022/11/01 14:43:59 - mmengine - INFO - Epoch(train) [165][55/63] lr: 1.6486e-03 eta: 11:46:02 time: 0.5685 data_time: 0.0213 memory: 17620 loss: 2.4698 loss_prob: 1.4962 loss_thr: 0.7285 loss_db: 0.2450 2022/11/01 14:44:02 - mmengine - INFO - Epoch(train) [165][60/63] lr: 1.6486e-03 eta: 11:45:50 time: 0.5546 data_time: 0.0115 memory: 17620 loss: 2.5695 loss_prob: 1.6074 loss_thr: 0.7063 loss_db: 0.2559 2022/11/01 14:44:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:44:09 - mmengine - INFO - Epoch(train) [166][5/63] lr: 1.6586e-03 eta: 11:45:50 time: 0.8189 data_time: 0.2145 memory: 17620 loss: 2.5936 loss_prob: 1.6305 loss_thr: 0.7067 loss_db: 0.2564 2022/11/01 14:44:12 - mmengine - INFO - Epoch(train) [166][10/63] lr: 1.6586e-03 eta: 11:45:40 time: 0.8259 data_time: 0.2166 memory: 17620 loss: 2.4692 loss_prob: 1.5289 loss_thr: 0.6971 loss_db: 0.2432 2022/11/01 14:44:15 - mmengine - INFO - Epoch(train) [166][15/63] lr: 1.6586e-03 eta: 11:45:40 time: 0.5416 data_time: 0.0089 memory: 17620 loss: 2.3394 loss_prob: 1.4309 loss_thr: 0.6822 loss_db: 0.2263 2022/11/01 14:44:17 - mmengine - INFO - Epoch(train) [166][20/63] lr: 1.6586e-03 eta: 11:45:26 time: 0.5336 data_time: 0.0069 memory: 17620 loss: 2.3439 loss_prob: 1.3984 loss_thr: 0.7231 loss_db: 0.2224 2022/11/01 14:44:20 - mmengine - INFO - Epoch(train) [166][25/63] lr: 1.6586e-03 eta: 11:45:26 time: 0.5268 data_time: 0.0156 memory: 17620 loss: 2.6645 loss_prob: 1.6537 loss_thr: 0.7356 loss_db: 0.2751 2022/11/01 14:44:23 - mmengine - INFO - Epoch(train) [166][30/63] lr: 1.6586e-03 eta: 11:45:15 time: 0.5779 data_time: 0.0306 memory: 17620 loss: 2.9019 loss_prob: 1.8541 loss_thr: 0.7386 loss_db: 0.3091 2022/11/01 14:44:26 - mmengine - INFO - Epoch(train) [166][35/63] lr: 1.6586e-03 eta: 11:45:15 time: 0.5799 data_time: 0.0230 memory: 17620 loss: 2.7954 loss_prob: 1.7613 loss_thr: 0.7441 loss_db: 0.2900 2022/11/01 14:44:28 - mmengine - INFO - Epoch(train) [166][40/63] lr: 1.6586e-03 eta: 11:45:02 time: 0.5343 data_time: 0.0084 memory: 17620 loss: 2.7742 loss_prob: 1.7326 loss_thr: 0.7469 loss_db: 0.2947 2022/11/01 14:44:32 - mmengine - INFO - Epoch(train) [166][45/63] lr: 1.6586e-03 eta: 11:45:02 time: 0.5957 data_time: 0.0064 memory: 17620 loss: 2.6106 loss_prob: 1.5934 loss_thr: 0.7489 loss_db: 0.2683 2022/11/01 14:44:35 - mmengine - INFO - Epoch(train) [166][50/63] lr: 1.6586e-03 eta: 11:44:58 time: 0.6917 data_time: 0.0182 memory: 17620 loss: 2.3884 loss_prob: 1.4316 loss_thr: 0.7204 loss_db: 0.2364 2022/11/01 14:44:38 - mmengine - INFO - Epoch(train) [166][55/63] lr: 1.6586e-03 eta: 11:44:58 time: 0.6392 data_time: 0.0220 memory: 17620 loss: 2.6180 loss_prob: 1.6022 loss_thr: 0.7389 loss_db: 0.2770 2022/11/01 14:44:41 - mmengine - INFO - Epoch(train) [166][60/63] lr: 1.6586e-03 eta: 11:44:48 time: 0.6024 data_time: 0.0106 memory: 17620 loss: 2.5753 loss_prob: 1.5733 loss_thr: 0.7308 loss_db: 0.2712 2022/11/01 14:44:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:44:48 - mmengine - INFO - Epoch(train) [167][5/63] lr: 1.6687e-03 eta: 11:44:48 time: 0.7709 data_time: 0.2258 memory: 17620 loss: 2.3212 loss_prob: 1.4034 loss_thr: 0.6854 loss_db: 0.2324 2022/11/01 14:44:51 - mmengine - INFO - Epoch(train) [167][10/63] lr: 1.6687e-03 eta: 11:44:36 time: 0.7892 data_time: 0.2239 memory: 17620 loss: 2.3500 loss_prob: 1.4343 loss_thr: 0.6851 loss_db: 0.2306 2022/11/01 14:44:54 - mmengine - INFO - Epoch(train) [167][15/63] lr: 1.6687e-03 eta: 11:44:36 time: 0.6478 data_time: 0.0073 memory: 17620 loss: 2.2917 loss_prob: 1.4039 loss_thr: 0.6676 loss_db: 0.2202 2022/11/01 14:44:58 - mmengine - INFO - Epoch(train) [167][20/63] lr: 1.6687e-03 eta: 11:44:35 time: 0.7244 data_time: 0.0082 memory: 17620 loss: 2.3468 loss_prob: 1.4305 loss_thr: 0.6855 loss_db: 0.2308 2022/11/01 14:45:01 - mmengine - INFO - Epoch(train) [167][25/63] lr: 1.6687e-03 eta: 11:44:35 time: 0.6894 data_time: 0.0266 memory: 17620 loss: 2.2287 loss_prob: 1.3296 loss_thr: 0.6830 loss_db: 0.2161 2022/11/01 14:45:04 - mmengine - INFO - Epoch(train) [167][30/63] lr: 1.6687e-03 eta: 11:44:28 time: 0.6503 data_time: 0.0433 memory: 17620 loss: 2.2366 loss_prob: 1.3268 loss_thr: 0.6914 loss_db: 0.2184 2022/11/01 14:45:07 - mmengine - INFO - Epoch(train) [167][35/63] lr: 1.6687e-03 eta: 11:44:28 time: 0.6277 data_time: 0.0257 memory: 17620 loss: 2.4461 loss_prob: 1.5048 loss_thr: 0.6922 loss_db: 0.2491 2022/11/01 14:45:11 - mmengine - INFO - Epoch(train) [167][40/63] lr: 1.6687e-03 eta: 11:44:21 time: 0.6312 data_time: 0.0087 memory: 17620 loss: 2.3983 loss_prob: 1.4859 loss_thr: 0.6725 loss_db: 0.2399 2022/11/01 14:45:13 - mmengine - INFO - Epoch(train) [167][45/63] lr: 1.6687e-03 eta: 11:44:21 time: 0.6038 data_time: 0.0061 memory: 17620 loss: 2.2540 loss_prob: 1.3821 loss_thr: 0.6529 loss_db: 0.2190 2022/11/01 14:45:16 - mmengine - INFO - Epoch(train) [167][50/63] lr: 1.6687e-03 eta: 11:44:10 time: 0.5818 data_time: 0.0162 memory: 17620 loss: 2.3253 loss_prob: 1.4362 loss_thr: 0.6597 loss_db: 0.2294 2022/11/01 14:45:19 - mmengine - INFO - Epoch(train) [167][55/63] lr: 1.6687e-03 eta: 11:44:10 time: 0.5805 data_time: 0.0238 memory: 17620 loss: 2.6440 loss_prob: 1.6600 loss_thr: 0.7115 loss_db: 0.2725 2022/11/01 14:45:23 - mmengine - INFO - Epoch(train) [167][60/63] lr: 1.6687e-03 eta: 11:44:02 time: 0.6247 data_time: 0.0172 memory: 17620 loss: 2.5758 loss_prob: 1.6095 loss_thr: 0.7006 loss_db: 0.2658 2022/11/01 14:45:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:45:30 - mmengine - INFO - Epoch(train) [168][5/63] lr: 1.6787e-03 eta: 11:44:02 time: 0.9172 data_time: 0.2218 memory: 17620 loss: 2.5219 loss_prob: 1.5539 loss_thr: 0.7170 loss_db: 0.2510 2022/11/01 14:45:33 - mmengine - INFO - Epoch(train) [168][10/63] lr: 1.6787e-03 eta: 11:43:56 time: 0.8817 data_time: 0.2219 memory: 17620 loss: 2.4896 loss_prob: 1.5327 loss_thr: 0.7117 loss_db: 0.2451 2022/11/01 14:45:36 - mmengine - INFO - Epoch(train) [168][15/63] lr: 1.6787e-03 eta: 11:43:56 time: 0.5297 data_time: 0.0048 memory: 17620 loss: 2.3974 loss_prob: 1.4882 loss_thr: 0.6632 loss_db: 0.2460 2022/11/01 14:45:38 - mmengine - INFO - Epoch(train) [168][20/63] lr: 1.6787e-03 eta: 11:43:42 time: 0.5215 data_time: 0.0047 memory: 17620 loss: 2.3308 loss_prob: 1.4250 loss_thr: 0.6739 loss_db: 0.2318 2022/11/01 14:45:41 - mmengine - INFO - Epoch(train) [168][25/63] lr: 1.6787e-03 eta: 11:43:42 time: 0.5567 data_time: 0.0237 memory: 17620 loss: 2.3303 loss_prob: 1.4100 loss_thr: 0.6933 loss_db: 0.2270 2022/11/01 14:45:44 - mmengine - INFO - Epoch(train) [168][30/63] lr: 1.6787e-03 eta: 11:43:30 time: 0.5646 data_time: 0.0362 memory: 17620 loss: 2.3583 loss_prob: 1.4432 loss_thr: 0.6769 loss_db: 0.2382 2022/11/01 14:45:47 - mmengine - INFO - Epoch(train) [168][35/63] lr: 1.6787e-03 eta: 11:43:30 time: 0.5616 data_time: 0.0174 memory: 17620 loss: 2.3948 loss_prob: 1.4808 loss_thr: 0.6644 loss_db: 0.2497 2022/11/01 14:45:50 - mmengine - INFO - Epoch(train) [168][40/63] lr: 1.6787e-03 eta: 11:43:19 time: 0.5715 data_time: 0.0061 memory: 17620 loss: 2.4290 loss_prob: 1.4859 loss_thr: 0.6970 loss_db: 0.2460 2022/11/01 14:45:52 - mmengine - INFO - Epoch(train) [168][45/63] lr: 1.6787e-03 eta: 11:43:19 time: 0.5479 data_time: 0.0057 memory: 17620 loss: 2.3975 loss_prob: 1.4571 loss_thr: 0.7108 loss_db: 0.2296 2022/11/01 14:45:55 - mmengine - INFO - Epoch(train) [168][50/63] lr: 1.6787e-03 eta: 11:43:07 time: 0.5662 data_time: 0.0188 memory: 17620 loss: 2.3784 loss_prob: 1.4618 loss_thr: 0.6866 loss_db: 0.2299 2022/11/01 14:45:58 - mmengine - INFO - Epoch(train) [168][55/63] lr: 1.6787e-03 eta: 11:43:07 time: 0.5767 data_time: 0.0208 memory: 17620 loss: 2.3958 loss_prob: 1.4640 loss_thr: 0.6967 loss_db: 0.2350 2022/11/01 14:46:01 - mmengine - INFO - Epoch(train) [168][60/63] lr: 1.6787e-03 eta: 11:42:55 time: 0.5622 data_time: 0.0084 memory: 17620 loss: 2.3404 loss_prob: 1.4083 loss_thr: 0.6995 loss_db: 0.2327 2022/11/01 14:46:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:46:07 - mmengine - INFO - Epoch(train) [169][5/63] lr: 1.6888e-03 eta: 11:42:55 time: 0.7487 data_time: 0.2004 memory: 17620 loss: 2.3248 loss_prob: 1.4267 loss_thr: 0.6622 loss_db: 0.2359 2022/11/01 14:46:10 - mmengine - INFO - Epoch(train) [169][10/63] lr: 1.6888e-03 eta: 11:42:44 time: 0.8012 data_time: 0.1992 memory: 17620 loss: 2.3494 loss_prob: 1.4398 loss_thr: 0.6675 loss_db: 0.2421 2022/11/01 14:46:13 - mmengine - INFO - Epoch(train) [169][15/63] lr: 1.6888e-03 eta: 11:42:44 time: 0.5544 data_time: 0.0067 memory: 17620 loss: 2.4107 loss_prob: 1.4784 loss_thr: 0.6905 loss_db: 0.2418 2022/11/01 14:46:16 - mmengine - INFO - Epoch(train) [169][20/63] lr: 1.6888e-03 eta: 11:42:31 time: 0.5337 data_time: 0.0062 memory: 17620 loss: 2.5542 loss_prob: 1.5922 loss_thr: 0.7023 loss_db: 0.2597 2022/11/01 14:46:18 - mmengine - INFO - Epoch(train) [169][25/63] lr: 1.6888e-03 eta: 11:42:31 time: 0.5512 data_time: 0.0208 memory: 17620 loss: 2.4616 loss_prob: 1.5461 loss_thr: 0.6620 loss_db: 0.2535 2022/11/01 14:46:21 - mmengine - INFO - Epoch(train) [169][30/63] lr: 1.6888e-03 eta: 11:42:21 time: 0.5935 data_time: 0.0341 memory: 17620 loss: 2.6734 loss_prob: 1.7065 loss_thr: 0.6858 loss_db: 0.2811 2022/11/01 14:46:24 - mmengine - INFO - Epoch(train) [169][35/63] lr: 1.6888e-03 eta: 11:42:21 time: 0.5676 data_time: 0.0181 memory: 17620 loss: 2.6747 loss_prob: 1.6880 loss_thr: 0.7100 loss_db: 0.2768 2022/11/01 14:46:27 - mmengine - INFO - Epoch(train) [169][40/63] lr: 1.6888e-03 eta: 11:42:07 time: 0.5331 data_time: 0.0047 memory: 17620 loss: 2.4478 loss_prob: 1.4961 loss_thr: 0.7087 loss_db: 0.2430 2022/11/01 14:46:30 - mmengine - INFO - Epoch(train) [169][45/63] lr: 1.6888e-03 eta: 11:42:07 time: 0.5540 data_time: 0.0057 memory: 17620 loss: 2.5531 loss_prob: 1.5781 loss_thr: 0.7168 loss_db: 0.2582 2022/11/01 14:46:32 - mmengine - INFO - Epoch(train) [169][50/63] lr: 1.6888e-03 eta: 11:41:54 time: 0.5441 data_time: 0.0190 memory: 17620 loss: 2.5313 loss_prob: 1.5820 loss_thr: 0.6960 loss_db: 0.2533 2022/11/01 14:46:36 - mmengine - INFO - Epoch(train) [169][55/63] lr: 1.6888e-03 eta: 11:41:54 time: 0.5869 data_time: 0.0234 memory: 17620 loss: 2.5088 loss_prob: 1.5647 loss_thr: 0.6899 loss_db: 0.2542 2022/11/01 14:46:38 - mmengine - INFO - Epoch(train) [169][60/63] lr: 1.6888e-03 eta: 11:41:46 time: 0.6087 data_time: 0.0103 memory: 17620 loss: 2.5410 loss_prob: 1.5805 loss_thr: 0.6924 loss_db: 0.2681 2022/11/01 14:46:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:46:45 - mmengine - INFO - Epoch(train) [170][5/63] lr: 1.6988e-03 eta: 11:41:46 time: 0.7655 data_time: 0.2292 memory: 17620 loss: 2.3120 loss_prob: 1.4343 loss_thr: 0.6478 loss_db: 0.2299 2022/11/01 14:46:48 - mmengine - INFO - Epoch(train) [170][10/63] lr: 1.6988e-03 eta: 11:41:34 time: 0.7980 data_time: 0.2275 memory: 17620 loss: 2.4145 loss_prob: 1.5033 loss_thr: 0.6700 loss_db: 0.2412 2022/11/01 14:46:51 - mmengine - INFO - Epoch(train) [170][15/63] lr: 1.6988e-03 eta: 11:41:34 time: 0.5579 data_time: 0.0055 memory: 17620 loss: 2.5662 loss_prob: 1.6021 loss_thr: 0.7028 loss_db: 0.2613 2022/11/01 14:46:54 - mmengine - INFO - Epoch(train) [170][20/63] lr: 1.6988e-03 eta: 11:41:25 time: 0.6051 data_time: 0.0059 memory: 17620 loss: 2.5218 loss_prob: 1.5742 loss_thr: 0.6925 loss_db: 0.2551 2022/11/01 14:46:57 - mmengine - INFO - Epoch(train) [170][25/63] lr: 1.6988e-03 eta: 11:41:25 time: 0.6279 data_time: 0.0261 memory: 17620 loss: 2.5007 loss_prob: 1.5350 loss_thr: 0.7152 loss_db: 0.2505 2022/11/01 14:47:00 - mmengine - INFO - Epoch(train) [170][30/63] lr: 1.6988e-03 eta: 11:41:17 time: 0.6135 data_time: 0.0321 memory: 17620 loss: 2.3417 loss_prob: 1.4150 loss_thr: 0.6971 loss_db: 0.2297 2022/11/01 14:47:03 - mmengine - INFO - Epoch(train) [170][35/63] lr: 1.6988e-03 eta: 11:41:17 time: 0.5869 data_time: 0.0128 memory: 17620 loss: 2.4270 loss_prob: 1.4996 loss_thr: 0.6872 loss_db: 0.2402 2022/11/01 14:47:05 - mmengine - INFO - Epoch(train) [170][40/63] lr: 1.6988e-03 eta: 11:41:04 time: 0.5467 data_time: 0.0068 memory: 17620 loss: 2.3353 loss_prob: 1.4222 loss_thr: 0.6844 loss_db: 0.2287 2022/11/01 14:47:08 - mmengine - INFO - Epoch(train) [170][45/63] lr: 1.6988e-03 eta: 11:41:04 time: 0.5268 data_time: 0.0046 memory: 17620 loss: 2.2758 loss_prob: 1.3649 loss_thr: 0.6916 loss_db: 0.2193 2022/11/01 14:47:11 - mmengine - INFO - Epoch(train) [170][50/63] lr: 1.6988e-03 eta: 11:40:54 time: 0.5820 data_time: 0.0257 memory: 17620 loss: 2.4198 loss_prob: 1.4810 loss_thr: 0.7019 loss_db: 0.2369 2022/11/01 14:47:14 - mmengine - INFO - Epoch(train) [170][55/63] lr: 1.6988e-03 eta: 11:40:54 time: 0.6448 data_time: 0.0297 memory: 17620 loss: 2.3730 loss_prob: 1.4570 loss_thr: 0.6806 loss_db: 0.2355 2022/11/01 14:47:18 - mmengine - INFO - Epoch(train) [170][60/63] lr: 1.6988e-03 eta: 11:40:47 time: 0.6543 data_time: 0.0094 memory: 17620 loss: 2.2907 loss_prob: 1.3938 loss_thr: 0.6692 loss_db: 0.2276 2022/11/01 14:47:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:47:25 - mmengine - INFO - Epoch(train) [171][5/63] lr: 1.7088e-03 eta: 11:40:47 time: 0.8121 data_time: 0.2217 memory: 17620 loss: 2.4787 loss_prob: 1.5226 loss_thr: 0.7088 loss_db: 0.2473 2022/11/01 14:47:27 - mmengine - INFO - Epoch(train) [171][10/63] lr: 1.7088e-03 eta: 11:40:38 time: 0.8320 data_time: 0.2225 memory: 17620 loss: 2.4663 loss_prob: 1.5157 loss_thr: 0.7062 loss_db: 0.2444 2022/11/01 14:47:30 - mmengine - INFO - Epoch(train) [171][15/63] lr: 1.7088e-03 eta: 11:40:38 time: 0.5885 data_time: 0.0070 memory: 17620 loss: 2.3538 loss_prob: 1.4337 loss_thr: 0.6859 loss_db: 0.2342 2022/11/01 14:47:33 - mmengine - INFO - Epoch(train) [171][20/63] lr: 1.7088e-03 eta: 11:40:27 time: 0.5716 data_time: 0.0082 memory: 17620 loss: 2.3185 loss_prob: 1.4173 loss_thr: 0.6750 loss_db: 0.2261 2022/11/01 14:47:36 - mmengine - INFO - Epoch(train) [171][25/63] lr: 1.7088e-03 eta: 11:40:27 time: 0.5988 data_time: 0.0202 memory: 17620 loss: 2.5223 loss_prob: 1.5739 loss_thr: 0.7007 loss_db: 0.2477 2022/11/01 14:47:39 - mmengine - INFO - Epoch(train) [171][30/63] lr: 1.7088e-03 eta: 11:40:20 time: 0.6294 data_time: 0.0312 memory: 17620 loss: 2.4060 loss_prob: 1.4843 loss_thr: 0.6821 loss_db: 0.2395 2022/11/01 14:47:42 - mmengine - INFO - Epoch(train) [171][35/63] lr: 1.7088e-03 eta: 11:40:20 time: 0.5753 data_time: 0.0210 memory: 17620 loss: 2.4104 loss_prob: 1.4877 loss_thr: 0.6821 loss_db: 0.2406 2022/11/01 14:47:45 - mmengine - INFO - Epoch(train) [171][40/63] lr: 1.7088e-03 eta: 11:40:10 time: 0.5908 data_time: 0.0064 memory: 17620 loss: 2.4617 loss_prob: 1.5293 loss_thr: 0.6880 loss_db: 0.2444 2022/11/01 14:47:48 - mmengine - INFO - Epoch(train) [171][45/63] lr: 1.7088e-03 eta: 11:40:10 time: 0.5854 data_time: 0.0052 memory: 17620 loss: 2.2308 loss_prob: 1.3347 loss_thr: 0.6803 loss_db: 0.2158 2022/11/01 14:47:52 - mmengine - INFO - Epoch(train) [171][50/63] lr: 1.7088e-03 eta: 11:40:06 time: 0.6919 data_time: 0.0207 memory: 17620 loss: 2.4398 loss_prob: 1.4743 loss_thr: 0.7205 loss_db: 0.2450 2022/11/01 14:47:55 - mmengine - INFO - Epoch(train) [171][55/63] lr: 1.7088e-03 eta: 11:40:06 time: 0.6899 data_time: 0.0211 memory: 17620 loss: 2.4538 loss_prob: 1.4931 loss_thr: 0.7148 loss_db: 0.2459 2022/11/01 14:47:58 - mmengine - INFO - Epoch(train) [171][60/63] lr: 1.7088e-03 eta: 11:39:53 time: 0.5396 data_time: 0.0069 memory: 17620 loss: 2.2606 loss_prob: 1.3370 loss_thr: 0.7088 loss_db: 0.2148 2022/11/01 14:47:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:48:04 - mmengine - INFO - Epoch(train) [172][5/63] lr: 1.7189e-03 eta: 11:39:53 time: 0.7141 data_time: 0.1873 memory: 17620 loss: 2.3613 loss_prob: 1.4068 loss_thr: 0.7206 loss_db: 0.2340 2022/11/01 14:48:06 - mmengine - INFO - Epoch(train) [172][10/63] lr: 1.7189e-03 eta: 11:39:38 time: 0.7346 data_time: 0.1884 memory: 17620 loss: 2.5628 loss_prob: 1.5974 loss_thr: 0.7000 loss_db: 0.2654 2022/11/01 14:48:09 - mmengine - INFO - Epoch(train) [172][15/63] lr: 1.7189e-03 eta: 11:39:38 time: 0.5640 data_time: 0.0061 memory: 17620 loss: 2.6801 loss_prob: 1.6961 loss_thr: 0.7047 loss_db: 0.2793 2022/11/01 14:48:12 - mmengine - INFO - Epoch(train) [172][20/63] lr: 1.7189e-03 eta: 11:39:26 time: 0.5586 data_time: 0.0052 memory: 17620 loss: 2.6411 loss_prob: 1.6718 loss_thr: 0.6991 loss_db: 0.2701 2022/11/01 14:48:15 - mmengine - INFO - Epoch(train) [172][25/63] lr: 1.7189e-03 eta: 11:39:26 time: 0.5369 data_time: 0.0163 memory: 17620 loss: 2.4428 loss_prob: 1.5334 loss_thr: 0.6691 loss_db: 0.2403 2022/11/01 14:48:18 - mmengine - INFO - Epoch(train) [172][30/63] lr: 1.7189e-03 eta: 11:39:15 time: 0.5645 data_time: 0.0271 memory: 17620 loss: 2.2273 loss_prob: 1.3760 loss_thr: 0.6398 loss_db: 0.2114 2022/11/01 14:48:20 - mmengine - INFO - Epoch(train) [172][35/63] lr: 1.7189e-03 eta: 11:39:15 time: 0.5453 data_time: 0.0200 memory: 17620 loss: 2.2608 loss_prob: 1.3865 loss_thr: 0.6558 loss_db: 0.2185 2022/11/01 14:48:23 - mmengine - INFO - Epoch(train) [172][40/63] lr: 1.7189e-03 eta: 11:39:01 time: 0.5219 data_time: 0.0127 memory: 17620 loss: 2.6015 loss_prob: 1.6250 loss_thr: 0.7067 loss_db: 0.2699 2022/11/01 14:48:25 - mmengine - INFO - Epoch(train) [172][45/63] lr: 1.7189e-03 eta: 11:39:01 time: 0.5339 data_time: 0.0087 memory: 17620 loss: 2.4850 loss_prob: 1.5394 loss_thr: 0.6891 loss_db: 0.2565 2022/11/01 14:48:28 - mmengine - INFO - Epoch(train) [172][50/63] lr: 1.7189e-03 eta: 11:38:49 time: 0.5591 data_time: 0.0199 memory: 17620 loss: 2.2325 loss_prob: 1.3504 loss_thr: 0.6650 loss_db: 0.2171 2022/11/01 14:48:31 - mmengine - INFO - Epoch(train) [172][55/63] lr: 1.7189e-03 eta: 11:38:49 time: 0.5745 data_time: 0.0193 memory: 17620 loss: 2.2725 loss_prob: 1.3705 loss_thr: 0.6818 loss_db: 0.2203 2022/11/01 14:48:34 - mmengine - INFO - Epoch(train) [172][60/63] lr: 1.7189e-03 eta: 11:38:37 time: 0.5510 data_time: 0.0065 memory: 17620 loss: 2.4197 loss_prob: 1.4727 loss_thr: 0.7088 loss_db: 0.2382 2022/11/01 14:48:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:48:40 - mmengine - INFO - Epoch(train) [173][5/63] lr: 1.7289e-03 eta: 11:38:37 time: 0.7391 data_time: 0.2225 memory: 17620 loss: 2.1955 loss_prob: 1.3306 loss_thr: 0.6543 loss_db: 0.2106 2022/11/01 14:48:43 - mmengine - INFO - Epoch(train) [173][10/63] lr: 1.7289e-03 eta: 11:38:24 time: 0.7646 data_time: 0.2256 memory: 17620 loss: 2.3015 loss_prob: 1.4129 loss_thr: 0.6572 loss_db: 0.2314 2022/11/01 14:48:46 - mmengine - INFO - Epoch(train) [173][15/63] lr: 1.7289e-03 eta: 11:38:24 time: 0.5406 data_time: 0.0090 memory: 17620 loss: 2.4671 loss_prob: 1.5125 loss_thr: 0.7020 loss_db: 0.2526 2022/11/01 14:48:48 - mmengine - INFO - Epoch(train) [173][20/63] lr: 1.7289e-03 eta: 11:38:10 time: 0.5220 data_time: 0.0049 memory: 17620 loss: 2.5601 loss_prob: 1.5711 loss_thr: 0.7275 loss_db: 0.2614 2022/11/01 14:48:51 - mmengine - INFO - Epoch(train) [173][25/63] lr: 1.7289e-03 eta: 11:38:10 time: 0.5311 data_time: 0.0281 memory: 17620 loss: 2.5918 loss_prob: 1.6063 loss_thr: 0.7195 loss_db: 0.2660 2022/11/01 14:48:54 - mmengine - INFO - Epoch(train) [173][30/63] lr: 1.7289e-03 eta: 11:37:59 time: 0.5797 data_time: 0.0331 memory: 17620 loss: 2.3855 loss_prob: 1.4662 loss_thr: 0.6832 loss_db: 0.2362 2022/11/01 14:48:57 - mmengine - INFO - Epoch(train) [173][35/63] lr: 1.7289e-03 eta: 11:37:59 time: 0.5792 data_time: 0.0134 memory: 17620 loss: 2.2875 loss_prob: 1.3896 loss_thr: 0.6762 loss_db: 0.2218 2022/11/01 14:48:59 - mmengine - INFO - Epoch(train) [173][40/63] lr: 1.7289e-03 eta: 11:37:47 time: 0.5435 data_time: 0.0095 memory: 17620 loss: 2.1722 loss_prob: 1.3026 loss_thr: 0.6579 loss_db: 0.2116 2022/11/01 14:49:02 - mmengine - INFO - Epoch(train) [173][45/63] lr: 1.7289e-03 eta: 11:37:47 time: 0.5455 data_time: 0.0061 memory: 17620 loss: 2.1935 loss_prob: 1.3236 loss_thr: 0.6555 loss_db: 0.2144 2022/11/01 14:49:05 - mmengine - INFO - Epoch(train) [173][50/63] lr: 1.7289e-03 eta: 11:37:36 time: 0.5672 data_time: 0.0235 memory: 17620 loss: 2.3081 loss_prob: 1.4048 loss_thr: 0.6783 loss_db: 0.2251 2022/11/01 14:49:08 - mmengine - INFO - Epoch(train) [173][55/63] lr: 1.7289e-03 eta: 11:37:36 time: 0.5523 data_time: 0.0232 memory: 17620 loss: 2.4500 loss_prob: 1.5102 loss_thr: 0.6912 loss_db: 0.2486 2022/11/01 14:49:10 - mmengine - INFO - Epoch(train) [173][60/63] lr: 1.7289e-03 eta: 11:37:23 time: 0.5457 data_time: 0.0047 memory: 17620 loss: 2.4153 loss_prob: 1.4759 loss_thr: 0.6902 loss_db: 0.2492 2022/11/01 14:49:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:49:17 - mmengine - INFO - Epoch(train) [174][5/63] lr: 1.7390e-03 eta: 11:37:23 time: 0.7874 data_time: 0.2021 memory: 17620 loss: 2.4365 loss_prob: 1.4860 loss_thr: 0.7046 loss_db: 0.2459 2022/11/01 14:49:20 - mmengine - INFO - Epoch(train) [174][10/63] lr: 1.7390e-03 eta: 11:37:13 time: 0.8192 data_time: 0.2021 memory: 17620 loss: 2.2024 loss_prob: 1.3245 loss_thr: 0.6600 loss_db: 0.2179 2022/11/01 14:49:23 - mmengine - INFO - Epoch(train) [174][15/63] lr: 1.7390e-03 eta: 11:37:13 time: 0.6070 data_time: 0.0050 memory: 17620 loss: 2.2161 loss_prob: 1.3320 loss_thr: 0.6690 loss_db: 0.2151 2022/11/01 14:49:27 - mmengine - INFO - Epoch(train) [174][20/63] lr: 1.7390e-03 eta: 11:37:10 time: 0.7002 data_time: 0.0067 memory: 17620 loss: 2.5590 loss_prob: 1.5817 loss_thr: 0.7159 loss_db: 0.2615 2022/11/01 14:49:31 - mmengine - INFO - Epoch(train) [174][25/63] lr: 1.7390e-03 eta: 11:37:10 time: 0.7475 data_time: 0.0252 memory: 17620 loss: 2.6488 loss_prob: 1.6438 loss_thr: 0.7308 loss_db: 0.2742 2022/11/01 14:49:34 - mmengine - INFO - Epoch(train) [174][30/63] lr: 1.7390e-03 eta: 11:37:04 time: 0.6588 data_time: 0.0335 memory: 17620 loss: 2.2423 loss_prob: 1.3449 loss_thr: 0.6802 loss_db: 0.2172 2022/11/01 14:49:37 - mmengine - INFO - Epoch(train) [174][35/63] lr: 1.7390e-03 eta: 11:37:04 time: 0.5972 data_time: 0.0147 memory: 17620 loss: 2.1972 loss_prob: 1.3247 loss_thr: 0.6585 loss_db: 0.2141 2022/11/01 14:49:40 - mmengine - INFO - Epoch(train) [174][40/63] lr: 1.7390e-03 eta: 11:36:56 time: 0.6086 data_time: 0.0044 memory: 17620 loss: 2.1735 loss_prob: 1.3009 loss_thr: 0.6647 loss_db: 0.2079 2022/11/01 14:49:43 - mmengine - INFO - Epoch(train) [174][45/63] lr: 1.7390e-03 eta: 11:36:56 time: 0.5796 data_time: 0.0058 memory: 17620 loss: 2.3259 loss_prob: 1.4102 loss_thr: 0.6893 loss_db: 0.2263 2022/11/01 14:49:46 - mmengine - INFO - Epoch(train) [174][50/63] lr: 1.7390e-03 eta: 11:36:46 time: 0.5977 data_time: 0.0202 memory: 17620 loss: 2.4630 loss_prob: 1.5319 loss_thr: 0.6845 loss_db: 0.2466 2022/11/01 14:49:49 - mmengine - INFO - Epoch(train) [174][55/63] lr: 1.7390e-03 eta: 11:36:46 time: 0.6320 data_time: 0.0230 memory: 17620 loss: 2.4048 loss_prob: 1.4916 loss_thr: 0.6754 loss_db: 0.2377 2022/11/01 14:49:52 - mmengine - INFO - Epoch(train) [174][60/63] lr: 1.7390e-03 eta: 11:36:36 time: 0.5866 data_time: 0.0092 memory: 17620 loss: 2.4068 loss_prob: 1.4813 loss_thr: 0.6846 loss_db: 0.2409 2022/11/01 14:49:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:49:59 - mmengine - INFO - Epoch(train) [175][5/63] lr: 1.7490e-03 eta: 11:36:36 time: 0.8162 data_time: 0.2475 memory: 17620 loss: 2.6942 loss_prob: 1.6819 loss_thr: 0.7316 loss_db: 0.2807 2022/11/01 14:50:02 - mmengine - INFO - Epoch(train) [175][10/63] lr: 1.7490e-03 eta: 11:36:29 time: 0.8619 data_time: 0.2473 memory: 17620 loss: 3.2136 loss_prob: 2.0843 loss_thr: 0.7718 loss_db: 0.3575 2022/11/01 14:50:05 - mmengine - INFO - Epoch(train) [175][15/63] lr: 1.7490e-03 eta: 11:36:29 time: 0.6041 data_time: 0.0071 memory: 17620 loss: 3.3220 loss_prob: 2.1763 loss_thr: 0.7662 loss_db: 0.3795 2022/11/01 14:50:08 - mmengine - INFO - Epoch(train) [175][20/63] lr: 1.7490e-03 eta: 11:36:24 time: 0.6628 data_time: 0.0068 memory: 17620 loss: 2.8787 loss_prob: 1.8465 loss_thr: 0.7248 loss_db: 0.3074 2022/11/01 14:50:11 - mmengine - INFO - Epoch(train) [175][25/63] lr: 1.7490e-03 eta: 11:36:24 time: 0.6551 data_time: 0.0288 memory: 17620 loss: 2.6770 loss_prob: 1.6699 loss_thr: 0.7407 loss_db: 0.2663 2022/11/01 14:50:14 - mmengine - INFO - Epoch(train) [175][30/63] lr: 1.7490e-03 eta: 11:36:14 time: 0.5903 data_time: 0.0365 memory: 17620 loss: 2.8694 loss_prob: 1.8077 loss_thr: 0.7636 loss_db: 0.2981 2022/11/01 14:50:17 - mmengine - INFO - Epoch(train) [175][35/63] lr: 1.7490e-03 eta: 11:36:14 time: 0.5461 data_time: 0.0121 memory: 17620 loss: 3.0846 loss_prob: 1.9761 loss_thr: 0.7693 loss_db: 0.3391 2022/11/01 14:50:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:50:19 - mmengine - INFO - Epoch(train) [175][40/63] lr: 1.7490e-03 eta: 11:36:00 time: 0.5253 data_time: 0.0048 memory: 17620 loss: 2.9148 loss_prob: 1.8531 loss_thr: 0.7461 loss_db: 0.3156 2022/11/01 14:50:22 - mmengine - INFO - Epoch(train) [175][45/63] lr: 1.7490e-03 eta: 11:36:00 time: 0.5287 data_time: 0.0050 memory: 17620 loss: 2.8271 loss_prob: 1.7874 loss_thr: 0.7300 loss_db: 0.3097 2022/11/01 14:50:25 - mmengine - INFO - Epoch(train) [175][50/63] lr: 1.7490e-03 eta: 11:35:49 time: 0.5600 data_time: 0.0169 memory: 17620 loss: 2.7147 loss_prob: 1.7035 loss_thr: 0.7202 loss_db: 0.2910 2022/11/01 14:50:28 - mmengine - INFO - Epoch(train) [175][55/63] lr: 1.7490e-03 eta: 11:35:49 time: 0.5685 data_time: 0.0212 memory: 17620 loss: 2.5273 loss_prob: 1.5634 loss_thr: 0.7145 loss_db: 0.2494 2022/11/01 14:50:30 - mmengine - INFO - Epoch(train) [175][60/63] lr: 1.7490e-03 eta: 11:35:36 time: 0.5353 data_time: 0.0088 memory: 17620 loss: 2.5975 loss_prob: 1.6091 loss_thr: 0.7226 loss_db: 0.2659 2022/11/01 14:50:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:50:37 - mmengine - INFO - Epoch(train) [176][5/63] lr: 1.7590e-03 eta: 11:35:36 time: 0.7515 data_time: 0.2096 memory: 17620 loss: 2.3589 loss_prob: 1.4364 loss_thr: 0.6870 loss_db: 0.2355 2022/11/01 14:50:40 - mmengine - INFO - Epoch(train) [176][10/63] lr: 1.7590e-03 eta: 11:35:25 time: 0.7992 data_time: 0.2046 memory: 17620 loss: 2.6316 loss_prob: 1.6250 loss_thr: 0.7369 loss_db: 0.2697 2022/11/01 14:50:43 - mmengine - INFO - Epoch(train) [176][15/63] lr: 1.7590e-03 eta: 11:35:25 time: 0.5757 data_time: 0.0067 memory: 17620 loss: 2.6335 loss_prob: 1.6411 loss_thr: 0.7184 loss_db: 0.2740 2022/11/01 14:50:45 - mmengine - INFO - Epoch(train) [176][20/63] lr: 1.7590e-03 eta: 11:35:14 time: 0.5640 data_time: 0.0087 memory: 17620 loss: 2.3985 loss_prob: 1.4664 loss_thr: 0.6957 loss_db: 0.2364 2022/11/01 14:50:49 - mmengine - INFO - Epoch(train) [176][25/63] lr: 1.7590e-03 eta: 11:35:14 time: 0.5916 data_time: 0.0192 memory: 17620 loss: 2.3781 loss_prob: 1.4444 loss_thr: 0.7051 loss_db: 0.2286 2022/11/01 14:50:51 - mmengine - INFO - Epoch(train) [176][30/63] lr: 1.7590e-03 eta: 11:35:05 time: 0.6027 data_time: 0.0355 memory: 17620 loss: 2.3053 loss_prob: 1.4029 loss_thr: 0.6808 loss_db: 0.2216 2022/11/01 14:50:54 - mmengine - INFO - Epoch(train) [176][35/63] lr: 1.7590e-03 eta: 11:35:05 time: 0.5904 data_time: 0.0253 memory: 17620 loss: 2.4418 loss_prob: 1.5215 loss_thr: 0.6801 loss_db: 0.2402 2022/11/01 14:50:58 - mmengine - INFO - Epoch(train) [176][40/63] lr: 1.7590e-03 eta: 11:34:56 time: 0.6042 data_time: 0.0064 memory: 17620 loss: 2.5789 loss_prob: 1.6213 loss_thr: 0.6980 loss_db: 0.2596 2022/11/01 14:51:00 - mmengine - INFO - Epoch(train) [176][45/63] lr: 1.7590e-03 eta: 11:34:56 time: 0.5913 data_time: 0.0047 memory: 17620 loss: 2.3733 loss_prob: 1.4716 loss_thr: 0.6672 loss_db: 0.2345 2022/11/01 14:51:03 - mmengine - INFO - Epoch(train) [176][50/63] lr: 1.7590e-03 eta: 11:34:45 time: 0.5696 data_time: 0.0165 memory: 17620 loss: 2.4586 loss_prob: 1.5277 loss_thr: 0.6938 loss_db: 0.2372 2022/11/01 14:51:06 - mmengine - INFO - Epoch(train) [176][55/63] lr: 1.7590e-03 eta: 11:34:45 time: 0.5817 data_time: 0.0222 memory: 17620 loss: 2.4546 loss_prob: 1.5131 loss_thr: 0.7091 loss_db: 0.2324 2022/11/01 14:51:09 - mmengine - INFO - Epoch(train) [176][60/63] lr: 1.7590e-03 eta: 11:34:37 time: 0.6138 data_time: 0.0121 memory: 17620 loss: 2.4709 loss_prob: 1.5274 loss_thr: 0.6981 loss_db: 0.2455 2022/11/01 14:51:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:51:16 - mmengine - INFO - Epoch(train) [177][5/63] lr: 1.7691e-03 eta: 11:34:37 time: 0.7789 data_time: 0.1880 memory: 17620 loss: 2.8121 loss_prob: 1.8127 loss_thr: 0.7122 loss_db: 0.2872 2022/11/01 14:51:19 - mmengine - INFO - Epoch(train) [177][10/63] lr: 1.7691e-03 eta: 11:34:27 time: 0.8273 data_time: 0.1981 memory: 17620 loss: 3.2959 loss_prob: 2.1592 loss_thr: 0.7878 loss_db: 0.3489 2022/11/01 14:51:22 - mmengine - INFO - Epoch(train) [177][15/63] lr: 1.7691e-03 eta: 11:34:27 time: 0.5865 data_time: 0.0150 memory: 17620 loss: 3.4168 loss_prob: 2.2536 loss_thr: 0.7882 loss_db: 0.3751 2022/11/01 14:51:24 - mmengine - INFO - Epoch(train) [177][20/63] lr: 1.7691e-03 eta: 11:34:15 time: 0.5441 data_time: 0.0051 memory: 17620 loss: 2.8745 loss_prob: 1.8448 loss_thr: 0.7303 loss_db: 0.2995 2022/11/01 14:51:27 - mmengine - INFO - Epoch(train) [177][25/63] lr: 1.7691e-03 eta: 11:34:15 time: 0.5575 data_time: 0.0148 memory: 17620 loss: 2.3885 loss_prob: 1.4445 loss_thr: 0.7113 loss_db: 0.2327 2022/11/01 14:51:30 - mmengine - INFO - Epoch(train) [177][30/63] lr: 1.7691e-03 eta: 11:34:04 time: 0.5734 data_time: 0.0321 memory: 17620 loss: 2.3995 loss_prob: 1.4386 loss_thr: 0.7227 loss_db: 0.2382 2022/11/01 14:51:33 - mmengine - INFO - Epoch(train) [177][35/63] lr: 1.7691e-03 eta: 11:34:04 time: 0.5546 data_time: 0.0220 memory: 17620 loss: 2.5071 loss_prob: 1.5335 loss_thr: 0.7146 loss_db: 0.2590 2022/11/01 14:51:36 - mmengine - INFO - Epoch(train) [177][40/63] lr: 1.7691e-03 eta: 11:33:53 time: 0.5546 data_time: 0.0045 memory: 17620 loss: 2.5165 loss_prob: 1.5619 loss_thr: 0.6951 loss_db: 0.2595 2022/11/01 14:51:39 - mmengine - INFO - Epoch(train) [177][45/63] lr: 1.7691e-03 eta: 11:33:53 time: 0.5821 data_time: 0.0070 memory: 17620 loss: 2.4243 loss_prob: 1.5114 loss_thr: 0.6684 loss_db: 0.2445 2022/11/01 14:51:41 - mmengine - INFO - Epoch(train) [177][50/63] lr: 1.7691e-03 eta: 11:33:42 time: 0.5667 data_time: 0.0132 memory: 17620 loss: 2.3272 loss_prob: 1.4232 loss_thr: 0.6797 loss_db: 0.2242 2022/11/01 14:51:44 - mmengine - INFO - Epoch(train) [177][55/63] lr: 1.7691e-03 eta: 11:33:42 time: 0.5723 data_time: 0.0199 memory: 17620 loss: 2.5111 loss_prob: 1.5410 loss_thr: 0.7242 loss_db: 0.2459 2022/11/01 14:51:47 - mmengine - INFO - Epoch(train) [177][60/63] lr: 1.7691e-03 eta: 11:33:32 time: 0.5950 data_time: 0.0151 memory: 17620 loss: 2.6778 loss_prob: 1.6722 loss_thr: 0.7305 loss_db: 0.2750 2022/11/01 14:51:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:51:54 - mmengine - INFO - Epoch(train) [178][5/63] lr: 1.7791e-03 eta: 11:33:32 time: 0.7502 data_time: 0.1994 memory: 17620 loss: 2.6083 loss_prob: 1.6285 loss_thr: 0.7117 loss_db: 0.2681 2022/11/01 14:51:57 - mmengine - INFO - Epoch(train) [178][10/63] lr: 1.7791e-03 eta: 11:33:23 time: 0.8277 data_time: 0.2016 memory: 17620 loss: 2.4720 loss_prob: 1.5454 loss_thr: 0.6747 loss_db: 0.2518 2022/11/01 14:52:00 - mmengine - INFO - Epoch(train) [178][15/63] lr: 1.7791e-03 eta: 11:33:23 time: 0.5969 data_time: 0.0146 memory: 17620 loss: 2.4910 loss_prob: 1.5204 loss_thr: 0.7218 loss_db: 0.2488 2022/11/01 14:52:02 - mmengine - INFO - Epoch(train) [178][20/63] lr: 1.7791e-03 eta: 11:33:11 time: 0.5519 data_time: 0.0145 memory: 17620 loss: 2.4030 loss_prob: 1.4353 loss_thr: 0.7347 loss_db: 0.2330 2022/11/01 14:52:06 - mmengine - INFO - Epoch(train) [178][25/63] lr: 1.7791e-03 eta: 11:33:11 time: 0.5949 data_time: 0.0283 memory: 17620 loss: 2.3249 loss_prob: 1.4100 loss_thr: 0.6884 loss_db: 0.2265 2022/11/01 14:52:08 - mmengine - INFO - Epoch(train) [178][30/63] lr: 1.7791e-03 eta: 11:33:02 time: 0.5990 data_time: 0.0251 memory: 17620 loss: 2.3650 loss_prob: 1.4476 loss_thr: 0.6814 loss_db: 0.2359 2022/11/01 14:52:11 - mmengine - INFO - Epoch(train) [178][35/63] lr: 1.7791e-03 eta: 11:33:02 time: 0.5624 data_time: 0.0049 memory: 17620 loss: 2.5345 loss_prob: 1.5662 loss_thr: 0.7065 loss_db: 0.2619 2022/11/01 14:52:14 - mmengine - INFO - Epoch(train) [178][40/63] lr: 1.7791e-03 eta: 11:32:52 time: 0.5766 data_time: 0.0076 memory: 17620 loss: 2.5830 loss_prob: 1.6141 loss_thr: 0.7061 loss_db: 0.2627 2022/11/01 14:52:17 - mmengine - INFO - Epoch(train) [178][45/63] lr: 1.7791e-03 eta: 11:32:52 time: 0.5461 data_time: 0.0100 memory: 17620 loss: 2.4699 loss_prob: 1.5289 loss_thr: 0.6943 loss_db: 0.2468 2022/11/01 14:52:20 - mmengine - INFO - Epoch(train) [178][50/63] lr: 1.7791e-03 eta: 11:32:39 time: 0.5412 data_time: 0.0234 memory: 17620 loss: 2.5095 loss_prob: 1.5441 loss_thr: 0.7129 loss_db: 0.2526 2022/11/01 14:52:22 - mmengine - INFO - Epoch(train) [178][55/63] lr: 1.7791e-03 eta: 11:32:39 time: 0.5753 data_time: 0.0212 memory: 17620 loss: 2.4402 loss_prob: 1.4895 loss_thr: 0.7093 loss_db: 0.2414 2022/11/01 14:52:25 - mmengine - INFO - Epoch(train) [178][60/63] lr: 1.7791e-03 eta: 11:32:28 time: 0.5558 data_time: 0.0068 memory: 17620 loss: 2.2927 loss_prob: 1.3819 loss_thr: 0.6869 loss_db: 0.2239 2022/11/01 14:52:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:52:33 - mmengine - INFO - Epoch(train) [179][5/63] lr: 1.7892e-03 eta: 11:32:28 time: 0.8885 data_time: 0.2635 memory: 17620 loss: 2.2133 loss_prob: 1.3155 loss_thr: 0.6854 loss_db: 0.2124 2022/11/01 14:52:36 - mmengine - INFO - Epoch(train) [179][10/63] lr: 1.7892e-03 eta: 11:32:26 time: 0.9483 data_time: 0.2621 memory: 17620 loss: 2.4760 loss_prob: 1.5271 loss_thr: 0.7035 loss_db: 0.2455 2022/11/01 14:52:39 - mmengine - INFO - Epoch(train) [179][15/63] lr: 1.7892e-03 eta: 11:32:26 time: 0.5921 data_time: 0.0069 memory: 17620 loss: 2.4238 loss_prob: 1.4922 loss_thr: 0.6963 loss_db: 0.2353 2022/11/01 14:52:42 - mmengine - INFO - Epoch(train) [179][20/63] lr: 1.7892e-03 eta: 11:32:15 time: 0.5704 data_time: 0.0067 memory: 17620 loss: 2.3453 loss_prob: 1.4366 loss_thr: 0.6775 loss_db: 0.2313 2022/11/01 14:52:45 - mmengine - INFO - Epoch(train) [179][25/63] lr: 1.7892e-03 eta: 11:32:15 time: 0.5782 data_time: 0.0285 memory: 17620 loss: 2.4188 loss_prob: 1.4997 loss_thr: 0.6760 loss_db: 0.2431 2022/11/01 14:52:48 - mmengine - INFO - Epoch(train) [179][30/63] lr: 1.7892e-03 eta: 11:32:07 time: 0.6163 data_time: 0.0362 memory: 17620 loss: 2.3626 loss_prob: 1.4549 loss_thr: 0.6748 loss_db: 0.2329 2022/11/01 14:52:50 - mmengine - INFO - Epoch(train) [179][35/63] lr: 1.7892e-03 eta: 11:32:07 time: 0.5708 data_time: 0.0128 memory: 17620 loss: 2.2655 loss_prob: 1.3695 loss_thr: 0.6784 loss_db: 0.2175 2022/11/01 14:52:53 - mmengine - INFO - Epoch(train) [179][40/63] lr: 1.7892e-03 eta: 11:31:53 time: 0.5245 data_time: 0.0048 memory: 17620 loss: 2.2884 loss_prob: 1.3839 loss_thr: 0.6835 loss_db: 0.2210 2022/11/01 14:52:56 - mmengine - INFO - Epoch(train) [179][45/63] lr: 1.7892e-03 eta: 11:31:53 time: 0.5190 data_time: 0.0048 memory: 17620 loss: 2.5528 loss_prob: 1.6025 loss_thr: 0.6914 loss_db: 0.2589 2022/11/01 14:52:59 - mmengine - INFO - Epoch(train) [179][50/63] lr: 1.7892e-03 eta: 11:31:41 time: 0.5501 data_time: 0.0260 memory: 17620 loss: 2.5107 loss_prob: 1.5774 loss_thr: 0.6796 loss_db: 0.2536 2022/11/01 14:53:02 - mmengine - INFO - Epoch(train) [179][55/63] lr: 1.7892e-03 eta: 11:31:41 time: 0.6111 data_time: 0.0274 memory: 17620 loss: 2.2895 loss_prob: 1.3943 loss_thr: 0.6705 loss_db: 0.2246 2022/11/01 14:53:05 - mmengine - INFO - Epoch(train) [179][60/63] lr: 1.7892e-03 eta: 11:31:33 time: 0.6051 data_time: 0.0066 memory: 17620 loss: 2.2648 loss_prob: 1.3644 loss_thr: 0.6788 loss_db: 0.2217 2022/11/01 14:53:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:53:12 - mmengine - INFO - Epoch(train) [180][5/63] lr: 1.7992e-03 eta: 11:31:33 time: 0.8613 data_time: 0.2048 memory: 17620 loss: 2.5024 loss_prob: 1.5357 loss_thr: 0.7093 loss_db: 0.2574 2022/11/01 14:53:15 - mmengine - INFO - Epoch(train) [180][10/63] lr: 1.7992e-03 eta: 11:31:26 time: 0.8626 data_time: 0.2044 memory: 17620 loss: 2.3887 loss_prob: 1.4755 loss_thr: 0.6669 loss_db: 0.2463 2022/11/01 14:53:18 - mmengine - INFO - Epoch(train) [180][15/63] lr: 1.7992e-03 eta: 11:31:26 time: 0.6019 data_time: 0.0054 memory: 17620 loss: 2.4656 loss_prob: 1.5246 loss_thr: 0.6850 loss_db: 0.2560 2022/11/01 14:53:21 - mmengine - INFO - Epoch(train) [180][20/63] lr: 1.7992e-03 eta: 11:31:19 time: 0.6363 data_time: 0.0068 memory: 17620 loss: 2.4349 loss_prob: 1.4995 loss_thr: 0.6845 loss_db: 0.2509 2022/11/01 14:53:25 - mmengine - INFO - Epoch(train) [180][25/63] lr: 1.7992e-03 eta: 11:31:19 time: 0.6595 data_time: 0.0107 memory: 17620 loss: 2.7813 loss_prob: 1.7567 loss_thr: 0.7183 loss_db: 0.3062 2022/11/01 14:53:28 - mmengine - INFO - Epoch(train) [180][30/63] lr: 1.7992e-03 eta: 11:31:15 time: 0.6942 data_time: 0.0358 memory: 17620 loss: 2.8951 loss_prob: 1.8291 loss_thr: 0.7532 loss_db: 0.3127 2022/11/01 14:53:31 - mmengine - INFO - Epoch(train) [180][35/63] lr: 1.7992e-03 eta: 11:31:15 time: 0.6573 data_time: 0.0311 memory: 17620 loss: 2.4871 loss_prob: 1.5318 loss_thr: 0.7109 loss_db: 0.2443 2022/11/01 14:53:34 - mmengine - INFO - Epoch(train) [180][40/63] lr: 1.7992e-03 eta: 11:31:07 time: 0.6229 data_time: 0.0054 memory: 17620 loss: 2.3727 loss_prob: 1.4730 loss_thr: 0.6634 loss_db: 0.2363 2022/11/01 14:53:37 - mmengine - INFO - Epoch(train) [180][45/63] lr: 1.7992e-03 eta: 11:31:07 time: 0.6132 data_time: 0.0082 memory: 17620 loss: 2.3156 loss_prob: 1.4192 loss_thr: 0.6687 loss_db: 0.2277 2022/11/01 14:53:41 - mmengine - INFO - Epoch(train) [180][50/63] lr: 1.7992e-03 eta: 11:30:59 time: 0.6098 data_time: 0.0147 memory: 17620 loss: 2.5070 loss_prob: 1.5439 loss_thr: 0.7122 loss_db: 0.2509 2022/11/01 14:53:44 - mmengine - INFO - Epoch(train) [180][55/63] lr: 1.7992e-03 eta: 11:30:59 time: 0.6585 data_time: 0.0246 memory: 17620 loss: 2.6167 loss_prob: 1.6295 loss_thr: 0.7165 loss_db: 0.2707 2022/11/01 14:53:47 - mmengine - INFO - Epoch(train) [180][60/63] lr: 1.7992e-03 eta: 11:30:52 time: 0.6315 data_time: 0.0181 memory: 17620 loss: 2.3480 loss_prob: 1.4430 loss_thr: 0.6708 loss_db: 0.2342 2022/11/01 14:53:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:53:48 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/11/01 14:53:55 - mmengine - INFO - Epoch(val) [180][5/32] eta: 11:30:52 time: 0.5389 data_time: 0.0584 memory: 17620 2022/11/01 14:53:58 - mmengine - INFO - Epoch(val) [180][10/32] eta: 0:00:13 time: 0.6088 data_time: 0.0908 memory: 15725 2022/11/01 14:54:01 - mmengine - INFO - Epoch(val) [180][15/32] eta: 0:00:13 time: 0.5688 data_time: 0.0464 memory: 15725 2022/11/01 14:54:04 - mmengine - INFO - Epoch(val) [180][20/32] eta: 0:00:06 time: 0.5669 data_time: 0.0507 memory: 15725 2022/11/01 14:54:07 - mmengine - INFO - Epoch(val) [180][25/32] eta: 0:00:06 time: 0.5800 data_time: 0.0583 memory: 15725 2022/11/01 14:54:09 - mmengine - INFO - Epoch(val) [180][30/32] eta: 0:00:01 time: 0.5380 data_time: 0.0233 memory: 15725 2022/11/01 14:54:10 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7540, precision: 0.7227, hmean: 0.7380 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7535, precision: 0.8063, hmean: 0.7790 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7496, precision: 0.8655, hmean: 0.8034 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7193, precision: 0.9066, hmean: 0.8021 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6105, precision: 0.9498, hmean: 0.7433 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1478, precision: 0.9840, hmean: 0.2570 2022/11/01 14:54:10 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 14:54:10 - mmengine - INFO - Epoch(val) [180][32/32] icdar/precision: 0.8655 icdar/recall: 0.7496 icdar/hmean: 0.8034 2022/11/01 14:54:15 - mmengine - INFO - Epoch(train) [181][5/63] lr: 1.8092e-03 eta: 0:00:01 time: 0.7765 data_time: 0.2116 memory: 17620 loss: 2.2766 loss_prob: 1.3719 loss_thr: 0.6797 loss_db: 0.2249 2022/11/01 14:54:18 - mmengine - INFO - Epoch(train) [181][10/63] lr: 1.8092e-03 eta: 11:30:41 time: 0.7977 data_time: 0.2092 memory: 17620 loss: 2.4140 loss_prob: 1.4824 loss_thr: 0.6884 loss_db: 0.2433 2022/11/01 14:54:21 - mmengine - INFO - Epoch(train) [181][15/63] lr: 1.8092e-03 eta: 11:30:41 time: 0.5606 data_time: 0.0093 memory: 17620 loss: 2.7336 loss_prob: 1.7260 loss_thr: 0.7144 loss_db: 0.2932 2022/11/01 14:54:23 - mmengine - INFO - Epoch(train) [181][20/63] lr: 1.8092e-03 eta: 11:30:30 time: 0.5660 data_time: 0.0080 memory: 17620 loss: 2.8797 loss_prob: 1.8253 loss_thr: 0.7374 loss_db: 0.3170 2022/11/01 14:54:26 - mmengine - INFO - Epoch(train) [181][25/63] lr: 1.8092e-03 eta: 11:30:30 time: 0.5654 data_time: 0.0240 memory: 17620 loss: 2.7699 loss_prob: 1.7380 loss_thr: 0.7329 loss_db: 0.2991 2022/11/01 14:54:29 - mmengine - INFO - Epoch(train) [181][30/63] lr: 1.8092e-03 eta: 11:30:19 time: 0.5629 data_time: 0.0311 memory: 17620 loss: 2.6759 loss_prob: 1.6659 loss_thr: 0.7353 loss_db: 0.2747 2022/11/01 14:54:32 - mmengine - INFO - Epoch(train) [181][35/63] lr: 1.8092e-03 eta: 11:30:19 time: 0.5328 data_time: 0.0146 memory: 17620 loss: 2.5124 loss_prob: 1.5553 loss_thr: 0.7103 loss_db: 0.2469 2022/11/01 14:54:35 - mmengine - INFO - Epoch(train) [181][40/63] lr: 1.8092e-03 eta: 11:30:07 time: 0.5542 data_time: 0.0089 memory: 17620 loss: 2.5905 loss_prob: 1.6305 loss_thr: 0.6994 loss_db: 0.2606 2022/11/01 14:54:37 - mmengine - INFO - Epoch(train) [181][45/63] lr: 1.8092e-03 eta: 11:30:07 time: 0.5588 data_time: 0.0071 memory: 17620 loss: 2.4968 loss_prob: 1.5436 loss_thr: 0.7037 loss_db: 0.2495 2022/11/01 14:54:40 - mmengine - INFO - Epoch(train) [181][50/63] lr: 1.8092e-03 eta: 11:29:56 time: 0.5550 data_time: 0.0169 memory: 17620 loss: 2.2541 loss_prob: 1.3485 loss_thr: 0.6868 loss_db: 0.2188 2022/11/01 14:54:43 - mmengine - INFO - Epoch(train) [181][55/63] lr: 1.8092e-03 eta: 11:29:56 time: 0.5431 data_time: 0.0192 memory: 17620 loss: 2.2691 loss_prob: 1.3608 loss_thr: 0.6856 loss_db: 0.2227 2022/11/01 14:54:45 - mmengine - INFO - Epoch(train) [181][60/63] lr: 1.8092e-03 eta: 11:29:42 time: 0.5187 data_time: 0.0097 memory: 17620 loss: 2.4382 loss_prob: 1.5041 loss_thr: 0.6947 loss_db: 0.2394 2022/11/01 14:54:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:54:51 - mmengine - INFO - Epoch(train) [182][5/63] lr: 1.8193e-03 eta: 11:29:42 time: 0.7129 data_time: 0.1861 memory: 17620 loss: 2.2032 loss_prob: 1.3433 loss_thr: 0.6442 loss_db: 0.2158 2022/11/01 14:54:54 - mmengine - INFO - Epoch(train) [182][10/63] lr: 1.8193e-03 eta: 11:29:28 time: 0.7311 data_time: 0.1843 memory: 17620 loss: 2.1758 loss_prob: 1.3007 loss_thr: 0.6651 loss_db: 0.2099 2022/11/01 14:54:57 - mmengine - INFO - Epoch(train) [182][15/63] lr: 1.8193e-03 eta: 11:29:28 time: 0.5365 data_time: 0.0074 memory: 17620 loss: 2.1477 loss_prob: 1.2723 loss_thr: 0.6741 loss_db: 0.2013 2022/11/01 14:54:59 - mmengine - INFO - Epoch(train) [182][20/63] lr: 1.8193e-03 eta: 11:29:16 time: 0.5462 data_time: 0.0115 memory: 17620 loss: 2.2328 loss_prob: 1.3458 loss_thr: 0.6712 loss_db: 0.2159 2022/11/01 14:55:03 - mmengine - INFO - Epoch(train) [182][25/63] lr: 1.8193e-03 eta: 11:29:16 time: 0.5989 data_time: 0.0484 memory: 17620 loss: 2.2992 loss_prob: 1.3963 loss_thr: 0.6784 loss_db: 0.2245 2022/11/01 14:55:06 - mmengine - INFO - Epoch(train) [182][30/63] lr: 1.8193e-03 eta: 11:29:11 time: 0.6609 data_time: 0.0443 memory: 17620 loss: 2.1264 loss_prob: 1.2808 loss_thr: 0.6452 loss_db: 0.2005 2022/11/01 14:55:09 - mmengine - INFO - Epoch(train) [182][35/63] lr: 1.8193e-03 eta: 11:29:11 time: 0.6153 data_time: 0.0118 memory: 17620 loss: 2.1499 loss_prob: 1.3067 loss_thr: 0.6346 loss_db: 0.2085 2022/11/01 14:55:12 - mmengine - INFO - Epoch(train) [182][40/63] lr: 1.8193e-03 eta: 11:29:00 time: 0.5648 data_time: 0.0131 memory: 17620 loss: 2.6212 loss_prob: 1.6524 loss_thr: 0.6924 loss_db: 0.2763 2022/11/01 14:55:15 - mmengine - INFO - Epoch(train) [182][45/63] lr: 1.8193e-03 eta: 11:29:00 time: 0.5911 data_time: 0.0115 memory: 17620 loss: 2.6540 loss_prob: 1.6650 loss_thr: 0.7098 loss_db: 0.2792 2022/11/01 14:55:18 - mmengine - INFO - Epoch(train) [182][50/63] lr: 1.8193e-03 eta: 11:28:52 time: 0.6215 data_time: 0.0263 memory: 17620 loss: 2.2913 loss_prob: 1.3893 loss_thr: 0.6765 loss_db: 0.2255 2022/11/01 14:55:21 - mmengine - INFO - Epoch(train) [182][55/63] lr: 1.8193e-03 eta: 11:28:52 time: 0.6147 data_time: 0.0209 memory: 17620 loss: 2.5986 loss_prob: 1.6207 loss_thr: 0.7165 loss_db: 0.2613 2022/11/01 14:55:24 - mmengine - INFO - Epoch(train) [182][60/63] lr: 1.8193e-03 eta: 11:28:42 time: 0.5815 data_time: 0.0071 memory: 17620 loss: 2.6311 loss_prob: 1.6438 loss_thr: 0.7201 loss_db: 0.2673 2022/11/01 14:55:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:55:31 - mmengine - INFO - Epoch(train) [183][5/63] lr: 1.8293e-03 eta: 11:28:42 time: 0.8052 data_time: 0.2343 memory: 17620 loss: 2.0961 loss_prob: 1.2884 loss_thr: 0.6033 loss_db: 0.2045 2022/11/01 14:55:34 - mmengine - INFO - Epoch(train) [183][10/63] lr: 1.8293e-03 eta: 11:28:36 time: 0.8867 data_time: 0.2339 memory: 17620 loss: 2.2620 loss_prob: 1.3955 loss_thr: 0.6447 loss_db: 0.2217 2022/11/01 14:55:37 - mmengine - INFO - Epoch(train) [183][15/63] lr: 1.8293e-03 eta: 11:28:36 time: 0.6726 data_time: 0.0060 memory: 17620 loss: 2.4867 loss_prob: 1.5386 loss_thr: 0.6994 loss_db: 0.2488 2022/11/01 14:55:40 - mmengine - INFO - Epoch(train) [183][20/63] lr: 1.8293e-03 eta: 11:28:29 time: 0.6205 data_time: 0.0059 memory: 17620 loss: 2.4573 loss_prob: 1.5197 loss_thr: 0.6942 loss_db: 0.2435 2022/11/01 14:55:43 - mmengine - INFO - Epoch(train) [183][25/63] lr: 1.8293e-03 eta: 11:28:29 time: 0.5914 data_time: 0.0345 memory: 17620 loss: 2.3283 loss_prob: 1.4240 loss_thr: 0.6778 loss_db: 0.2264 2022/11/01 14:55:46 - mmengine - INFO - Epoch(train) [183][30/63] lr: 1.8293e-03 eta: 11:28:19 time: 0.5853 data_time: 0.0338 memory: 17620 loss: 2.3622 loss_prob: 1.4514 loss_thr: 0.6722 loss_db: 0.2386 2022/11/01 14:55:49 - mmengine - INFO - Epoch(train) [183][35/63] lr: 1.8293e-03 eta: 11:28:19 time: 0.5652 data_time: 0.0069 memory: 17620 loss: 2.2559 loss_prob: 1.3736 loss_thr: 0.6556 loss_db: 0.2267 2022/11/01 14:55:52 - mmengine - INFO - Epoch(train) [183][40/63] lr: 1.8293e-03 eta: 11:28:08 time: 0.5713 data_time: 0.0076 memory: 17620 loss: 2.6098 loss_prob: 1.6349 loss_thr: 0.7024 loss_db: 0.2725 2022/11/01 14:55:54 - mmengine - INFO - Epoch(train) [183][45/63] lr: 1.8293e-03 eta: 11:28:08 time: 0.5396 data_time: 0.0077 memory: 17620 loss: 2.8752 loss_prob: 1.8241 loss_thr: 0.7382 loss_db: 0.3128 2022/11/01 14:55:57 - mmengine - INFO - Epoch(train) [183][50/63] lr: 1.8293e-03 eta: 11:27:58 time: 0.5675 data_time: 0.0212 memory: 17620 loss: 2.5436 loss_prob: 1.5729 loss_thr: 0.7061 loss_db: 0.2646 2022/11/01 14:56:00 - mmengine - INFO - Epoch(train) [183][55/63] lr: 1.8293e-03 eta: 11:27:58 time: 0.5790 data_time: 0.0190 memory: 17620 loss: 2.3308 loss_prob: 1.4252 loss_thr: 0.6784 loss_db: 0.2271 2022/11/01 14:56:03 - mmengine - INFO - Epoch(train) [183][60/63] lr: 1.8293e-03 eta: 11:27:46 time: 0.5429 data_time: 0.0064 memory: 17620 loss: 2.1752 loss_prob: 1.3195 loss_thr: 0.6514 loss_db: 0.2043 2022/11/01 14:56:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:56:10 - mmengine - INFO - Epoch(train) [184][5/63] lr: 1.8394e-03 eta: 11:27:46 time: 0.7843 data_time: 0.2465 memory: 17620 loss: 2.3936 loss_prob: 1.4524 loss_thr: 0.7044 loss_db: 0.2368 2022/11/01 14:56:13 - mmengine - INFO - Epoch(train) [184][10/63] lr: 1.8394e-03 eta: 11:27:37 time: 0.8263 data_time: 0.2453 memory: 17620 loss: 2.4181 loss_prob: 1.4748 loss_thr: 0.7007 loss_db: 0.2426 2022/11/01 14:56:15 - mmengine - INFO - Epoch(train) [184][15/63] lr: 1.8394e-03 eta: 11:27:37 time: 0.5660 data_time: 0.0058 memory: 17620 loss: 2.3031 loss_prob: 1.3980 loss_thr: 0.6771 loss_db: 0.2280 2022/11/01 14:56:18 - mmengine - INFO - Epoch(train) [184][20/63] lr: 1.8394e-03 eta: 11:27:24 time: 0.5333 data_time: 0.0081 memory: 17620 loss: 2.3430 loss_prob: 1.4329 loss_thr: 0.6774 loss_db: 0.2327 2022/11/01 14:56:21 - mmengine - INFO - Epoch(train) [184][25/63] lr: 1.8394e-03 eta: 11:27:24 time: 0.5598 data_time: 0.0229 memory: 17620 loss: 2.3335 loss_prob: 1.4385 loss_thr: 0.6627 loss_db: 0.2323 2022/11/01 14:56:24 - mmengine - INFO - Epoch(train) [184][30/63] lr: 1.8394e-03 eta: 11:27:14 time: 0.5789 data_time: 0.0307 memory: 17620 loss: 2.4382 loss_prob: 1.5134 loss_thr: 0.6809 loss_db: 0.2439 2022/11/01 14:56:26 - mmengine - INFO - Epoch(train) [184][35/63] lr: 1.8394e-03 eta: 11:27:14 time: 0.5615 data_time: 0.0179 memory: 17620 loss: 2.3805 loss_prob: 1.4506 loss_thr: 0.6940 loss_db: 0.2358 2022/11/01 14:56:29 - mmengine - INFO - Epoch(train) [184][40/63] lr: 1.8394e-03 eta: 11:27:02 time: 0.5480 data_time: 0.0070 memory: 17620 loss: 2.2377 loss_prob: 1.3472 loss_thr: 0.6735 loss_db: 0.2169 2022/11/01 14:56:32 - mmengine - INFO - Epoch(train) [184][45/63] lr: 1.8394e-03 eta: 11:27:02 time: 0.5598 data_time: 0.0046 memory: 17620 loss: 2.2269 loss_prob: 1.3463 loss_thr: 0.6634 loss_db: 0.2173 2022/11/01 14:56:35 - mmengine - INFO - Epoch(train) [184][50/63] lr: 1.8394e-03 eta: 11:26:51 time: 0.5520 data_time: 0.0163 memory: 17620 loss: 2.1410 loss_prob: 1.2754 loss_thr: 0.6609 loss_db: 0.2046 2022/11/01 14:56:38 - mmengine - INFO - Epoch(train) [184][55/63] lr: 1.8394e-03 eta: 11:26:51 time: 0.5667 data_time: 0.0225 memory: 17620 loss: 2.2227 loss_prob: 1.3391 loss_thr: 0.6711 loss_db: 0.2125 2022/11/01 14:56:40 - mmengine - INFO - Epoch(train) [184][60/63] lr: 1.8394e-03 eta: 11:26:40 time: 0.5651 data_time: 0.0133 memory: 17620 loss: 2.3262 loss_prob: 1.4116 loss_thr: 0.6832 loss_db: 0.2315 2022/11/01 14:56:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:56:47 - mmengine - INFO - Epoch(train) [185][5/63] lr: 1.8494e-03 eta: 11:26:40 time: 0.7691 data_time: 0.2011 memory: 17620 loss: 2.4141 loss_prob: 1.4847 loss_thr: 0.6711 loss_db: 0.2584 2022/11/01 14:56:50 - mmengine - INFO - Epoch(train) [185][10/63] lr: 1.8494e-03 eta: 11:26:32 time: 0.8415 data_time: 0.2077 memory: 17620 loss: 2.4421 loss_prob: 1.5195 loss_thr: 0.6602 loss_db: 0.2624 2022/11/01 14:56:53 - mmengine - INFO - Epoch(train) [185][15/63] lr: 1.8494e-03 eta: 11:26:32 time: 0.5991 data_time: 0.0121 memory: 17620 loss: 2.2955 loss_prob: 1.4082 loss_thr: 0.6605 loss_db: 0.2269 2022/11/01 14:56:56 - mmengine - INFO - Epoch(train) [185][20/63] lr: 1.8494e-03 eta: 11:26:21 time: 0.5571 data_time: 0.0053 memory: 17620 loss: 2.3264 loss_prob: 1.4093 loss_thr: 0.6903 loss_db: 0.2267 2022/11/01 14:56:58 - mmengine - INFO - Epoch(train) [185][25/63] lr: 1.8494e-03 eta: 11:26:21 time: 0.5263 data_time: 0.0066 memory: 17620 loss: 2.5130 loss_prob: 1.5521 loss_thr: 0.7075 loss_db: 0.2534 2022/11/01 14:57:01 - mmengine - INFO - Epoch(train) [185][30/63] lr: 1.8494e-03 eta: 11:26:10 time: 0.5602 data_time: 0.0319 memory: 17620 loss: 2.5294 loss_prob: 1.5743 loss_thr: 0.6936 loss_db: 0.2616 2022/11/01 14:57:04 - mmengine - INFO - Epoch(train) [185][35/63] lr: 1.8494e-03 eta: 11:26:10 time: 0.5773 data_time: 0.0333 memory: 17620 loss: 2.5745 loss_prob: 1.6212 loss_thr: 0.6849 loss_db: 0.2685 2022/11/01 14:57:07 - mmengine - INFO - Epoch(train) [185][40/63] lr: 1.8494e-03 eta: 11:25:58 time: 0.5530 data_time: 0.0076 memory: 17620 loss: 2.6888 loss_prob: 1.7118 loss_thr: 0.6911 loss_db: 0.2859 2022/11/01 14:57:10 - mmengine - INFO - Epoch(train) [185][45/63] lr: 1.8494e-03 eta: 11:25:58 time: 0.5764 data_time: 0.0066 memory: 17620 loss: 2.8044 loss_prob: 1.7720 loss_thr: 0.7310 loss_db: 0.3014 2022/11/01 14:57:13 - mmengine - INFO - Epoch(train) [185][50/63] lr: 1.8494e-03 eta: 11:25:48 time: 0.5682 data_time: 0.0187 memory: 17620 loss: 2.7466 loss_prob: 1.6974 loss_thr: 0.7645 loss_db: 0.2847 2022/11/01 14:57:15 - mmengine - INFO - Epoch(train) [185][55/63] lr: 1.8494e-03 eta: 11:25:48 time: 0.5292 data_time: 0.0192 memory: 17620 loss: 2.4382 loss_prob: 1.4824 loss_thr: 0.7114 loss_db: 0.2444 2022/11/01 14:57:18 - mmengine - INFO - Epoch(train) [185][60/63] lr: 1.8494e-03 eta: 11:25:35 time: 0.5273 data_time: 0.0100 memory: 17620 loss: 2.4178 loss_prob: 1.4950 loss_thr: 0.6808 loss_db: 0.2419 2022/11/01 14:57:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:57:25 - mmengine - INFO - Epoch(train) [186][5/63] lr: 1.8594e-03 eta: 11:25:35 time: 0.8312 data_time: 0.2412 memory: 17620 loss: 2.6018 loss_prob: 1.5852 loss_thr: 0.7531 loss_db: 0.2635 2022/11/01 14:57:29 - mmengine - INFO - Epoch(train) [186][10/63] lr: 1.8594e-03 eta: 11:25:33 time: 0.9539 data_time: 0.2418 memory: 17620 loss: 2.4061 loss_prob: 1.4488 loss_thr: 0.7218 loss_db: 0.2356 2022/11/01 14:57:32 - mmengine - INFO - Epoch(train) [186][15/63] lr: 1.8594e-03 eta: 11:25:33 time: 0.6566 data_time: 0.0074 memory: 17620 loss: 2.4584 loss_prob: 1.5022 loss_thr: 0.7149 loss_db: 0.2412 2022/11/01 14:57:35 - mmengine - INFO - Epoch(train) [186][20/63] lr: 1.8594e-03 eta: 11:25:24 time: 0.5966 data_time: 0.0065 memory: 17620 loss: 2.3906 loss_prob: 1.4647 loss_thr: 0.6893 loss_db: 0.2367 2022/11/01 14:57:38 - mmengine - INFO - Epoch(train) [186][25/63] lr: 1.8594e-03 eta: 11:25:24 time: 0.6195 data_time: 0.0224 memory: 17620 loss: 2.2446 loss_prob: 1.3526 loss_thr: 0.6710 loss_db: 0.2209 2022/11/01 14:57:41 - mmengine - INFO - Epoch(train) [186][30/63] lr: 1.8594e-03 eta: 11:25:17 time: 0.6427 data_time: 0.0495 memory: 17620 loss: 2.3065 loss_prob: 1.3909 loss_thr: 0.6859 loss_db: 0.2297 2022/11/01 14:57:44 - mmengine - INFO - Epoch(train) [186][35/63] lr: 1.8594e-03 eta: 11:25:17 time: 0.6663 data_time: 0.0331 memory: 17620 loss: 2.3431 loss_prob: 1.4287 loss_thr: 0.6807 loss_db: 0.2337 2022/11/01 14:57:48 - mmengine - INFO - Epoch(train) [186][40/63] lr: 1.8594e-03 eta: 11:25:11 time: 0.6414 data_time: 0.0062 memory: 17620 loss: 2.4567 loss_prob: 1.5269 loss_thr: 0.6807 loss_db: 0.2491 2022/11/01 14:57:51 - mmengine - INFO - Epoch(train) [186][45/63] lr: 1.8594e-03 eta: 11:25:11 time: 0.6053 data_time: 0.0046 memory: 17620 loss: 2.4885 loss_prob: 1.5363 loss_thr: 0.7031 loss_db: 0.2491 2022/11/01 14:57:53 - mmengine - INFO - Epoch(train) [186][50/63] lr: 1.8594e-03 eta: 11:25:00 time: 0.5689 data_time: 0.0221 memory: 17620 loss: 2.3099 loss_prob: 1.4055 loss_thr: 0.6772 loss_db: 0.2273 2022/11/01 14:57:56 - mmengine - INFO - Epoch(train) [186][55/63] lr: 1.8594e-03 eta: 11:25:00 time: 0.5602 data_time: 0.0233 memory: 17620 loss: 2.1441 loss_prob: 1.2932 loss_thr: 0.6447 loss_db: 0.2062 2022/11/01 14:57:59 - mmengine - INFO - Epoch(train) [186][60/63] lr: 1.8594e-03 eta: 11:24:52 time: 0.6048 data_time: 0.0059 memory: 17620 loss: 2.0559 loss_prob: 1.2265 loss_thr: 0.6361 loss_db: 0.1933 2022/11/01 14:58:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:58:07 - mmengine - INFO - Epoch(train) [187][5/63] lr: 1.8695e-03 eta: 11:24:52 time: 0.8430 data_time: 0.2274 memory: 17620 loss: 2.2261 loss_prob: 1.3514 loss_thr: 0.6608 loss_db: 0.2139 2022/11/01 14:58:10 - mmengine - INFO - Epoch(train) [187][10/63] lr: 1.8695e-03 eta: 11:24:46 time: 0.8773 data_time: 0.2329 memory: 17620 loss: 2.3132 loss_prob: 1.4122 loss_thr: 0.6749 loss_db: 0.2262 2022/11/01 14:58:12 - mmengine - INFO - Epoch(train) [187][15/63] lr: 1.8695e-03 eta: 11:24:46 time: 0.5799 data_time: 0.0135 memory: 17620 loss: 2.3802 loss_prob: 1.4618 loss_thr: 0.6778 loss_db: 0.2406 2022/11/01 14:58:15 - mmengine - INFO - Epoch(train) [187][20/63] lr: 1.8695e-03 eta: 11:24:36 time: 0.5918 data_time: 0.0074 memory: 17620 loss: 2.3422 loss_prob: 1.4404 loss_thr: 0.6618 loss_db: 0.2399 2022/11/01 14:58:18 - mmengine - INFO - Epoch(train) [187][25/63] lr: 1.8695e-03 eta: 11:24:36 time: 0.5830 data_time: 0.0164 memory: 17620 loss: 2.4419 loss_prob: 1.5183 loss_thr: 0.6707 loss_db: 0.2529 2022/11/01 14:58:21 - mmengine - INFO - Epoch(train) [187][30/63] lr: 1.8695e-03 eta: 11:24:27 time: 0.5836 data_time: 0.0254 memory: 17620 loss: 2.5238 loss_prob: 1.5638 loss_thr: 0.7045 loss_db: 0.2555 2022/11/01 14:58:24 - mmengine - INFO - Epoch(train) [187][35/63] lr: 1.8695e-03 eta: 11:24:27 time: 0.5971 data_time: 0.0209 memory: 17620 loss: 2.5768 loss_prob: 1.6160 loss_thr: 0.7033 loss_db: 0.2574 2022/11/01 14:58:27 - mmengine - INFO - Epoch(train) [187][40/63] lr: 1.8695e-03 eta: 11:24:15 time: 0.5527 data_time: 0.0128 memory: 17620 loss: 2.6121 loss_prob: 1.6880 loss_thr: 0.6554 loss_db: 0.2688 2022/11/01 14:58:29 - mmengine - INFO - Epoch(train) [187][45/63] lr: 1.8695e-03 eta: 11:24:15 time: 0.5268 data_time: 0.0061 memory: 17620 loss: 2.6452 loss_prob: 1.7062 loss_thr: 0.6580 loss_db: 0.2809 2022/11/01 14:58:32 - mmengine - INFO - Epoch(train) [187][50/63] lr: 1.8695e-03 eta: 11:24:04 time: 0.5472 data_time: 0.0213 memory: 17620 loss: 2.6138 loss_prob: 1.6357 loss_thr: 0.7018 loss_db: 0.2763 2022/11/01 14:58:35 - mmengine - INFO - Epoch(train) [187][55/63] lr: 1.8695e-03 eta: 11:24:04 time: 0.5686 data_time: 0.0225 memory: 17620 loss: 2.4178 loss_prob: 1.4871 loss_thr: 0.6869 loss_db: 0.2438 2022/11/01 14:58:38 - mmengine - INFO - Epoch(train) [187][60/63] lr: 1.8695e-03 eta: 11:23:54 time: 0.5830 data_time: 0.0075 memory: 17620 loss: 2.3983 loss_prob: 1.4634 loss_thr: 0.7018 loss_db: 0.2331 2022/11/01 14:58:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:58:45 - mmengine - INFO - Epoch(train) [188][5/63] lr: 1.8795e-03 eta: 11:23:54 time: 0.7763 data_time: 0.1852 memory: 17620 loss: 2.2898 loss_prob: 1.3889 loss_thr: 0.6812 loss_db: 0.2197 2022/11/01 14:58:47 - mmengine - INFO - Epoch(train) [188][10/63] lr: 1.8795e-03 eta: 11:23:43 time: 0.7807 data_time: 0.1883 memory: 17620 loss: 2.3879 loss_prob: 1.4496 loss_thr: 0.7001 loss_db: 0.2382 2022/11/01 14:58:50 - mmengine - INFO - Epoch(train) [188][15/63] lr: 1.8795e-03 eta: 11:23:43 time: 0.5611 data_time: 0.0108 memory: 17620 loss: 2.3349 loss_prob: 1.4231 loss_thr: 0.6799 loss_db: 0.2319 2022/11/01 14:58:53 - mmengine - INFO - Epoch(train) [188][20/63] lr: 1.8795e-03 eta: 11:23:32 time: 0.5529 data_time: 0.0061 memory: 17620 loss: 2.2064 loss_prob: 1.3462 loss_thr: 0.6433 loss_db: 0.2168 2022/11/01 14:58:56 - mmengine - INFO - Epoch(train) [188][25/63] lr: 1.8795e-03 eta: 11:23:32 time: 0.5757 data_time: 0.0220 memory: 17620 loss: 2.2873 loss_prob: 1.4118 loss_thr: 0.6473 loss_db: 0.2282 2022/11/01 14:58:59 - mmengine - INFO - Epoch(train) [188][30/63] lr: 1.8795e-03 eta: 11:23:21 time: 0.5676 data_time: 0.0295 memory: 17620 loss: 2.3761 loss_prob: 1.4674 loss_thr: 0.6720 loss_db: 0.2367 2022/11/01 14:59:02 - mmengine - INFO - Epoch(train) [188][35/63] lr: 1.8795e-03 eta: 11:23:21 time: 0.5629 data_time: 0.0165 memory: 17620 loss: 2.2956 loss_prob: 1.4046 loss_thr: 0.6665 loss_db: 0.2246 2022/11/01 14:59:04 - mmengine - INFO - Epoch(train) [188][40/63] lr: 1.8795e-03 eta: 11:23:11 time: 0.5825 data_time: 0.0100 memory: 17620 loss: 2.2010 loss_prob: 1.3335 loss_thr: 0.6534 loss_db: 0.2141 2022/11/01 14:59:07 - mmengine - INFO - Epoch(train) [188][45/63] lr: 1.8795e-03 eta: 11:23:11 time: 0.5601 data_time: 0.0063 memory: 17620 loss: 2.1894 loss_prob: 1.3197 loss_thr: 0.6534 loss_db: 0.2163 2022/11/01 14:59:10 - mmengine - INFO - Epoch(train) [188][50/63] lr: 1.8795e-03 eta: 11:23:00 time: 0.5492 data_time: 0.0172 memory: 17620 loss: 2.1833 loss_prob: 1.3051 loss_thr: 0.6638 loss_db: 0.2144 2022/11/01 14:59:13 - mmengine - INFO - Epoch(train) [188][55/63] lr: 1.8795e-03 eta: 11:23:00 time: 0.5498 data_time: 0.0192 memory: 17620 loss: 2.0845 loss_prob: 1.2375 loss_thr: 0.6461 loss_db: 0.2009 2022/11/01 14:59:16 - mmengine - INFO - Epoch(train) [188][60/63] lr: 1.8795e-03 eta: 11:22:52 time: 0.6226 data_time: 0.0102 memory: 17620 loss: 2.3097 loss_prob: 1.4167 loss_thr: 0.6644 loss_db: 0.2285 2022/11/01 14:59:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 14:59:23 - mmengine - INFO - Epoch(train) [189][5/63] lr: 1.8896e-03 eta: 11:22:52 time: 0.7661 data_time: 0.1717 memory: 17620 loss: 2.3102 loss_prob: 1.3955 loss_thr: 0.6900 loss_db: 0.2246 2022/11/01 14:59:25 - mmengine - INFO - Epoch(train) [189][10/63] lr: 1.8896e-03 eta: 11:22:41 time: 0.7745 data_time: 0.1744 memory: 17620 loss: 2.2709 loss_prob: 1.3609 loss_thr: 0.6877 loss_db: 0.2223 2022/11/01 14:59:29 - mmengine - INFO - Epoch(train) [189][15/63] lr: 1.8896e-03 eta: 11:22:41 time: 0.5956 data_time: 0.0093 memory: 17620 loss: 2.4487 loss_prob: 1.5023 loss_thr: 0.6956 loss_db: 0.2508 2022/11/01 14:59:31 - mmengine - INFO - Epoch(train) [189][20/63] lr: 1.8896e-03 eta: 11:22:33 time: 0.6108 data_time: 0.0068 memory: 17620 loss: 2.3693 loss_prob: 1.4697 loss_thr: 0.6596 loss_db: 0.2400 2022/11/01 14:59:34 - mmengine - INFO - Epoch(train) [189][25/63] lr: 1.8896e-03 eta: 11:22:33 time: 0.5503 data_time: 0.0154 memory: 17620 loss: 2.1621 loss_prob: 1.3063 loss_thr: 0.6443 loss_db: 0.2115 2022/11/01 14:59:37 - mmengine - INFO - Epoch(train) [189][30/63] lr: 1.8896e-03 eta: 11:22:22 time: 0.5622 data_time: 0.0273 memory: 17620 loss: 2.1245 loss_prob: 1.2838 loss_thr: 0.6300 loss_db: 0.2106 2022/11/01 14:59:40 - mmengine - INFO - Epoch(train) [189][35/63] lr: 1.8896e-03 eta: 11:22:22 time: 0.5671 data_time: 0.0215 memory: 17620 loss: 2.1613 loss_prob: 1.3102 loss_thr: 0.6324 loss_db: 0.2186 2022/11/01 14:59:42 - mmengine - INFO - Epoch(train) [189][40/63] lr: 1.8896e-03 eta: 11:22:10 time: 0.5499 data_time: 0.0085 memory: 17620 loss: 2.1847 loss_prob: 1.3240 loss_thr: 0.6417 loss_db: 0.2189 2022/11/01 14:59:46 - mmengine - INFO - Epoch(train) [189][45/63] lr: 1.8896e-03 eta: 11:22:10 time: 0.5848 data_time: 0.0100 memory: 17620 loss: 2.1833 loss_prob: 1.3251 loss_thr: 0.6437 loss_db: 0.2145 2022/11/01 14:59:49 - mmengine - INFO - Epoch(train) [189][50/63] lr: 1.8896e-03 eta: 11:22:03 time: 0.6262 data_time: 0.0196 memory: 17620 loss: 2.2170 loss_prob: 1.3425 loss_thr: 0.6536 loss_db: 0.2209 2022/11/01 14:59:53 - mmengine - INFO - Epoch(train) [189][55/63] lr: 1.8896e-03 eta: 11:22:03 time: 0.7155 data_time: 0.0204 memory: 17620 loss: 2.3140 loss_prob: 1.4070 loss_thr: 0.6727 loss_db: 0.2343 2022/11/01 14:59:56 - mmengine - INFO - Epoch(train) [189][60/63] lr: 1.8896e-03 eta: 11:22:01 time: 0.7161 data_time: 0.0182 memory: 17620 loss: 2.3362 loss_prob: 1.4199 loss_thr: 0.6868 loss_db: 0.2296 2022/11/01 14:59:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:00:03 - mmengine - INFO - Epoch(train) [190][5/63] lr: 1.8996e-03 eta: 11:22:01 time: 0.8460 data_time: 0.1990 memory: 17620 loss: 2.4494 loss_prob: 1.5161 loss_thr: 0.6862 loss_db: 0.2470 2022/11/01 15:00:06 - mmengine - INFO - Epoch(train) [190][10/63] lr: 1.8996e-03 eta: 11:21:53 time: 0.8536 data_time: 0.1953 memory: 17620 loss: 2.2681 loss_prob: 1.3783 loss_thr: 0.6647 loss_db: 0.2251 2022/11/01 15:00:09 - mmengine - INFO - Epoch(train) [190][15/63] lr: 1.8996e-03 eta: 11:21:53 time: 0.5728 data_time: 0.0055 memory: 17620 loss: 2.4573 loss_prob: 1.5272 loss_thr: 0.6706 loss_db: 0.2595 2022/11/01 15:00:12 - mmengine - INFO - Epoch(train) [190][20/63] lr: 1.8996e-03 eta: 11:21:44 time: 0.5856 data_time: 0.0063 memory: 17620 loss: 2.4344 loss_prob: 1.5074 loss_thr: 0.6744 loss_db: 0.2526 2022/11/01 15:00:15 - mmengine - INFO - Epoch(train) [190][25/63] lr: 1.8996e-03 eta: 11:21:44 time: 0.5921 data_time: 0.0131 memory: 17620 loss: 2.3596 loss_prob: 1.4457 loss_thr: 0.6811 loss_db: 0.2328 2022/11/01 15:00:18 - mmengine - INFO - Epoch(train) [190][30/63] lr: 1.8996e-03 eta: 11:21:36 time: 0.6177 data_time: 0.0372 memory: 17620 loss: 2.4635 loss_prob: 1.5195 loss_thr: 0.6889 loss_db: 0.2551 2022/11/01 15:00:21 - mmengine - INFO - Epoch(train) [190][35/63] lr: 1.8996e-03 eta: 11:21:36 time: 0.6183 data_time: 0.0298 memory: 17620 loss: 2.4276 loss_prob: 1.5007 loss_thr: 0.6743 loss_db: 0.2526 2022/11/01 15:00:24 - mmengine - INFO - Epoch(train) [190][40/63] lr: 1.8996e-03 eta: 11:21:28 time: 0.6145 data_time: 0.0048 memory: 17620 loss: 2.2527 loss_prob: 1.3814 loss_thr: 0.6437 loss_db: 0.2276 2022/11/01 15:00:27 - mmengine - INFO - Epoch(train) [190][45/63] lr: 1.8996e-03 eta: 11:21:28 time: 0.6167 data_time: 0.0050 memory: 17620 loss: 2.0925 loss_prob: 1.2518 loss_thr: 0.6357 loss_db: 0.2050 2022/11/01 15:00:31 - mmengine - INFO - Epoch(train) [190][50/63] lr: 1.8996e-03 eta: 11:21:25 time: 0.7053 data_time: 0.0207 memory: 17620 loss: 2.2704 loss_prob: 1.3765 loss_thr: 0.6713 loss_db: 0.2225 2022/11/01 15:00:34 - mmengine - INFO - Epoch(train) [190][55/63] lr: 1.8996e-03 eta: 11:21:25 time: 0.6803 data_time: 0.0274 memory: 17620 loss: 2.2111 loss_prob: 1.3285 loss_thr: 0.6721 loss_db: 0.2105 2022/11/01 15:00:37 - mmengine - INFO - Epoch(train) [190][60/63] lr: 1.8996e-03 eta: 11:21:16 time: 0.5927 data_time: 0.0116 memory: 17620 loss: 2.0050 loss_prob: 1.1800 loss_thr: 0.6363 loss_db: 0.1887 2022/11/01 15:00:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:00:44 - mmengine - INFO - Epoch(train) [191][5/63] lr: 1.9096e-03 eta: 11:21:16 time: 0.7812 data_time: 0.2025 memory: 17620 loss: 2.2522 loss_prob: 1.3627 loss_thr: 0.6663 loss_db: 0.2232 2022/11/01 15:00:47 - mmengine - INFO - Epoch(train) [191][10/63] lr: 1.9096e-03 eta: 11:21:06 time: 0.7942 data_time: 0.2021 memory: 17620 loss: 2.2365 loss_prob: 1.3588 loss_thr: 0.6563 loss_db: 0.2213 2022/11/01 15:00:49 - mmengine - INFO - Epoch(train) [191][15/63] lr: 1.9096e-03 eta: 11:21:06 time: 0.5546 data_time: 0.0056 memory: 17620 loss: 2.2181 loss_prob: 1.3323 loss_thr: 0.6709 loss_db: 0.2149 2022/11/01 15:00:52 - mmengine - INFO - Epoch(train) [191][20/63] lr: 1.9096e-03 eta: 11:20:55 time: 0.5599 data_time: 0.0055 memory: 17620 loss: 2.3021 loss_prob: 1.3955 loss_thr: 0.6853 loss_db: 0.2213 2022/11/01 15:00:55 - mmengine - INFO - Epoch(train) [191][25/63] lr: 1.9096e-03 eta: 11:20:55 time: 0.5899 data_time: 0.0261 memory: 17620 loss: 2.2126 loss_prob: 1.3298 loss_thr: 0.6719 loss_db: 0.2110 2022/11/01 15:00:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:00:58 - mmengine - INFO - Epoch(train) [191][30/63] lr: 1.9096e-03 eta: 11:20:46 time: 0.6016 data_time: 0.0366 memory: 17620 loss: 1.9697 loss_prob: 1.1622 loss_thr: 0.6225 loss_db: 0.1851 2022/11/01 15:01:01 - mmengine - INFO - Epoch(train) [191][35/63] lr: 1.9096e-03 eta: 11:20:46 time: 0.5564 data_time: 0.0149 memory: 17620 loss: 2.0477 loss_prob: 1.2252 loss_thr: 0.6291 loss_db: 0.1934 2022/11/01 15:01:03 - mmengine - INFO - Epoch(train) [191][40/63] lr: 1.9096e-03 eta: 11:20:34 time: 0.5324 data_time: 0.0059 memory: 17620 loss: 2.2264 loss_prob: 1.3507 loss_thr: 0.6606 loss_db: 0.2151 2022/11/01 15:01:06 - mmengine - INFO - Epoch(train) [191][45/63] lr: 1.9096e-03 eta: 11:20:34 time: 0.5601 data_time: 0.0061 memory: 17620 loss: 2.2894 loss_prob: 1.3907 loss_thr: 0.6743 loss_db: 0.2244 2022/11/01 15:01:10 - mmengine - INFO - Epoch(train) [191][50/63] lr: 1.9096e-03 eta: 11:20:26 time: 0.6117 data_time: 0.0184 memory: 17620 loss: 2.2175 loss_prob: 1.3356 loss_thr: 0.6677 loss_db: 0.2142 2022/11/01 15:01:13 - mmengine - INFO - Epoch(train) [191][55/63] lr: 1.9096e-03 eta: 11:20:26 time: 0.6194 data_time: 0.0228 memory: 17620 loss: 2.2671 loss_prob: 1.3687 loss_thr: 0.6747 loss_db: 0.2238 2022/11/01 15:01:15 - mmengine - INFO - Epoch(train) [191][60/63] lr: 1.9096e-03 eta: 11:20:15 time: 0.5653 data_time: 0.0094 memory: 17620 loss: 2.3712 loss_prob: 1.4435 loss_thr: 0.6881 loss_db: 0.2396 2022/11/01 15:01:16 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:01:21 - mmengine - INFO - Epoch(train) [192][5/63] lr: 1.9197e-03 eta: 11:20:15 time: 0.6782 data_time: 0.1862 memory: 17620 loss: 2.4404 loss_prob: 1.4879 loss_thr: 0.7077 loss_db: 0.2448 2022/11/01 15:01:24 - mmengine - INFO - Epoch(train) [192][10/63] lr: 1.9197e-03 eta: 11:20:01 time: 0.7238 data_time: 0.1936 memory: 17620 loss: 2.4270 loss_prob: 1.4853 loss_thr: 0.7018 loss_db: 0.2400 2022/11/01 15:01:27 - mmengine - INFO - Epoch(train) [192][15/63] lr: 1.9197e-03 eta: 11:20:01 time: 0.5709 data_time: 0.0129 memory: 17620 loss: 2.4826 loss_prob: 1.5428 loss_thr: 0.6846 loss_db: 0.2552 2022/11/01 15:01:30 - mmengine - INFO - Epoch(train) [192][20/63] lr: 1.9197e-03 eta: 11:19:53 time: 0.6022 data_time: 0.0062 memory: 17620 loss: 2.5723 loss_prob: 1.6048 loss_thr: 0.6987 loss_db: 0.2688 2022/11/01 15:01:33 - mmengine - INFO - Epoch(train) [192][25/63] lr: 1.9197e-03 eta: 11:19:53 time: 0.6006 data_time: 0.0120 memory: 17620 loss: 2.5355 loss_prob: 1.5675 loss_thr: 0.7065 loss_db: 0.2616 2022/11/01 15:01:35 - mmengine - INFO - Epoch(train) [192][30/63] lr: 1.9197e-03 eta: 11:19:42 time: 0.5652 data_time: 0.0273 memory: 17620 loss: 2.5291 loss_prob: 1.5409 loss_thr: 0.7375 loss_db: 0.2507 2022/11/01 15:01:38 - mmengine - INFO - Epoch(train) [192][35/63] lr: 1.9197e-03 eta: 11:19:42 time: 0.5550 data_time: 0.0283 memory: 17620 loss: 2.6182 loss_prob: 1.6036 loss_thr: 0.7568 loss_db: 0.2577 2022/11/01 15:01:41 - mmengine - INFO - Epoch(train) [192][40/63] lr: 1.9197e-03 eta: 11:19:32 time: 0.5615 data_time: 0.0133 memory: 17620 loss: 2.6178 loss_prob: 1.6314 loss_thr: 0.7211 loss_db: 0.2653 2022/11/01 15:01:44 - mmengine - INFO - Epoch(train) [192][45/63] lr: 1.9197e-03 eta: 11:19:32 time: 0.5535 data_time: 0.0100 memory: 17620 loss: 2.5203 loss_prob: 1.5654 loss_thr: 0.7028 loss_db: 0.2522 2022/11/01 15:01:47 - mmengine - INFO - Epoch(train) [192][50/63] lr: 1.9197e-03 eta: 11:19:21 time: 0.5679 data_time: 0.0344 memory: 17620 loss: 2.5600 loss_prob: 1.6057 loss_thr: 0.6988 loss_db: 0.2556 2022/11/01 15:01:49 - mmengine - INFO - Epoch(train) [192][55/63] lr: 1.9197e-03 eta: 11:19:21 time: 0.5614 data_time: 0.0359 memory: 17620 loss: 2.5736 loss_prob: 1.6108 loss_thr: 0.7015 loss_db: 0.2614 2022/11/01 15:01:52 - mmengine - INFO - Epoch(train) [192][60/63] lr: 1.9197e-03 eta: 11:19:10 time: 0.5496 data_time: 0.0107 memory: 17620 loss: 2.4553 loss_prob: 1.5088 loss_thr: 0.7034 loss_db: 0.2431 2022/11/01 15:01:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:01:58 - mmengine - INFO - Epoch(train) [193][5/63] lr: 1.9297e-03 eta: 11:19:10 time: 0.7197 data_time: 0.1733 memory: 17620 loss: 2.4658 loss_prob: 1.5160 loss_thr: 0.7094 loss_db: 0.2404 2022/11/01 15:02:01 - mmengine - INFO - Epoch(train) [193][10/63] lr: 1.9297e-03 eta: 11:18:56 time: 0.7313 data_time: 0.1747 memory: 17620 loss: 2.7466 loss_prob: 1.7531 loss_thr: 0.7019 loss_db: 0.2916 2022/11/01 15:02:04 - mmengine - INFO - Epoch(train) [193][15/63] lr: 1.9297e-03 eta: 11:18:56 time: 0.5392 data_time: 0.0063 memory: 17620 loss: 2.8305 loss_prob: 1.7984 loss_thr: 0.7261 loss_db: 0.3061 2022/11/01 15:02:06 - mmengine - INFO - Epoch(train) [193][20/63] lr: 1.9297e-03 eta: 11:18:45 time: 0.5480 data_time: 0.0062 memory: 17620 loss: 2.6907 loss_prob: 1.6768 loss_thr: 0.7271 loss_db: 0.2867 2022/11/01 15:02:10 - mmengine - INFO - Epoch(train) [193][25/63] lr: 1.9297e-03 eta: 11:18:45 time: 0.6020 data_time: 0.0128 memory: 17620 loss: 2.6526 loss_prob: 1.6624 loss_thr: 0.7110 loss_db: 0.2792 2022/11/01 15:02:13 - mmengine - INFO - Epoch(train) [193][30/63] lr: 1.9297e-03 eta: 11:18:39 time: 0.6552 data_time: 0.0375 memory: 17620 loss: 2.7132 loss_prob: 1.7148 loss_thr: 0.7168 loss_db: 0.2816 2022/11/01 15:02:16 - mmengine - INFO - Epoch(train) [193][35/63] lr: 1.9297e-03 eta: 11:18:39 time: 0.5992 data_time: 0.0325 memory: 17620 loss: 2.6301 loss_prob: 1.6766 loss_thr: 0.6763 loss_db: 0.2772 2022/11/01 15:02:19 - mmengine - INFO - Epoch(train) [193][40/63] lr: 1.9297e-03 eta: 11:18:30 time: 0.5781 data_time: 0.0066 memory: 17620 loss: 2.3459 loss_prob: 1.4536 loss_thr: 0.6546 loss_db: 0.2377 2022/11/01 15:02:22 - mmengine - INFO - Epoch(train) [193][45/63] lr: 1.9297e-03 eta: 11:18:30 time: 0.6457 data_time: 0.0053 memory: 17620 loss: 2.2215 loss_prob: 1.3465 loss_thr: 0.6600 loss_db: 0.2150 2022/11/01 15:02:25 - mmengine - INFO - Epoch(train) [193][50/63] lr: 1.9297e-03 eta: 11:18:22 time: 0.6289 data_time: 0.0102 memory: 17620 loss: 2.3776 loss_prob: 1.4740 loss_thr: 0.6725 loss_db: 0.2310 2022/11/01 15:02:28 - mmengine - INFO - Epoch(train) [193][55/63] lr: 1.9297e-03 eta: 11:18:22 time: 0.5994 data_time: 0.0238 memory: 17620 loss: 2.4441 loss_prob: 1.5119 loss_thr: 0.6873 loss_db: 0.2449 2022/11/01 15:02:31 - mmengine - INFO - Epoch(train) [193][60/63] lr: 1.9297e-03 eta: 11:18:13 time: 0.5838 data_time: 0.0198 memory: 17620 loss: 2.4542 loss_prob: 1.5133 loss_thr: 0.6828 loss_db: 0.2581 2022/11/01 15:02:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:02:38 - mmengine - INFO - Epoch(train) [194][5/63] lr: 1.9398e-03 eta: 11:18:13 time: 0.7904 data_time: 0.2328 memory: 17620 loss: 2.2769 loss_prob: 1.3632 loss_thr: 0.6924 loss_db: 0.2212 2022/11/01 15:02:41 - mmengine - INFO - Epoch(train) [194][10/63] lr: 1.9398e-03 eta: 11:18:05 time: 0.8296 data_time: 0.2332 memory: 17620 loss: 2.3276 loss_prob: 1.3968 loss_thr: 0.7040 loss_db: 0.2268 2022/11/01 15:02:43 - mmengine - INFO - Epoch(train) [194][15/63] lr: 1.9398e-03 eta: 11:18:05 time: 0.5663 data_time: 0.0070 memory: 17620 loss: 2.3601 loss_prob: 1.4360 loss_thr: 0.6864 loss_db: 0.2377 2022/11/01 15:02:46 - mmengine - INFO - Epoch(train) [194][20/63] lr: 1.9398e-03 eta: 11:17:56 time: 0.5920 data_time: 0.0069 memory: 17620 loss: 2.3664 loss_prob: 1.4516 loss_thr: 0.6780 loss_db: 0.2368 2022/11/01 15:02:50 - mmengine - INFO - Epoch(train) [194][25/63] lr: 1.9398e-03 eta: 11:17:56 time: 0.6185 data_time: 0.0073 memory: 17620 loss: 2.2806 loss_prob: 1.3794 loss_thr: 0.6782 loss_db: 0.2229 2022/11/01 15:02:52 - mmengine - INFO - Epoch(train) [194][30/63] lr: 1.9398e-03 eta: 11:17:47 time: 0.5986 data_time: 0.0370 memory: 17620 loss: 2.4023 loss_prob: 1.4379 loss_thr: 0.7278 loss_db: 0.2366 2022/11/01 15:02:55 - mmengine - INFO - Epoch(train) [194][35/63] lr: 1.9398e-03 eta: 11:17:47 time: 0.5741 data_time: 0.0344 memory: 17620 loss: 2.4182 loss_prob: 1.4629 loss_thr: 0.7198 loss_db: 0.2355 2022/11/01 15:02:59 - mmengine - INFO - Epoch(train) [194][40/63] lr: 1.9398e-03 eta: 11:17:39 time: 0.6106 data_time: 0.0066 memory: 17620 loss: 2.4091 loss_prob: 1.4998 loss_thr: 0.6706 loss_db: 0.2388 2022/11/01 15:03:02 - mmengine - INFO - Epoch(train) [194][45/63] lr: 1.9398e-03 eta: 11:17:39 time: 0.6463 data_time: 0.0071 memory: 17620 loss: 2.4074 loss_prob: 1.4899 loss_thr: 0.6775 loss_db: 0.2399 2022/11/01 15:03:05 - mmengine - INFO - Epoch(train) [194][50/63] lr: 1.9398e-03 eta: 11:17:31 time: 0.6201 data_time: 0.0186 memory: 17620 loss: 2.4932 loss_prob: 1.5381 loss_thr: 0.7018 loss_db: 0.2532 2022/11/01 15:03:08 - mmengine - INFO - Epoch(train) [194][55/63] lr: 1.9398e-03 eta: 11:17:31 time: 0.6236 data_time: 0.0225 memory: 17620 loss: 2.7626 loss_prob: 1.7544 loss_thr: 0.7141 loss_db: 0.2941 2022/11/01 15:03:11 - mmengine - INFO - Epoch(train) [194][60/63] lr: 1.9398e-03 eta: 11:17:23 time: 0.6114 data_time: 0.0089 memory: 17620 loss: 2.5551 loss_prob: 1.6026 loss_thr: 0.6867 loss_db: 0.2659 2022/11/01 15:03:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:03:17 - mmengine - INFO - Epoch(train) [195][5/63] lr: 1.9498e-03 eta: 11:17:23 time: 0.7710 data_time: 0.2178 memory: 17620 loss: 2.5637 loss_prob: 1.5752 loss_thr: 0.7304 loss_db: 0.2581 2022/11/01 15:03:20 - mmengine - INFO - Epoch(train) [195][10/63] lr: 1.9498e-03 eta: 11:17:12 time: 0.7757 data_time: 0.2162 memory: 17620 loss: 2.2698 loss_prob: 1.3580 loss_thr: 0.6973 loss_db: 0.2146 2022/11/01 15:03:23 - mmengine - INFO - Epoch(train) [195][15/63] lr: 1.9498e-03 eta: 11:17:12 time: 0.5267 data_time: 0.0059 memory: 17620 loss: 2.2533 loss_prob: 1.3720 loss_thr: 0.6600 loss_db: 0.2212 2022/11/01 15:03:26 - mmengine - INFO - Epoch(train) [195][20/63] lr: 1.9498e-03 eta: 11:17:01 time: 0.5503 data_time: 0.0065 memory: 17620 loss: 2.6817 loss_prob: 1.6878 loss_thr: 0.7131 loss_db: 0.2809 2022/11/01 15:03:29 - mmengine - INFO - Epoch(train) [195][25/63] lr: 1.9498e-03 eta: 11:17:01 time: 0.5869 data_time: 0.0330 memory: 17620 loss: 2.5802 loss_prob: 1.6228 loss_thr: 0.6960 loss_db: 0.2614 2022/11/01 15:03:31 - mmengine - INFO - Epoch(train) [195][30/63] lr: 1.9498e-03 eta: 11:16:51 time: 0.5765 data_time: 0.0345 memory: 17620 loss: 2.4132 loss_prob: 1.4932 loss_thr: 0.6778 loss_db: 0.2422 2022/11/01 15:03:34 - mmengine - INFO - Epoch(train) [195][35/63] lr: 1.9498e-03 eta: 11:16:51 time: 0.5548 data_time: 0.0091 memory: 17620 loss: 2.4042 loss_prob: 1.4718 loss_thr: 0.6869 loss_db: 0.2455 2022/11/01 15:03:37 - mmengine - INFO - Epoch(train) [195][40/63] lr: 1.9498e-03 eta: 11:16:41 time: 0.5634 data_time: 0.0064 memory: 17620 loss: 2.5066 loss_prob: 1.5594 loss_thr: 0.6872 loss_db: 0.2599 2022/11/01 15:03:40 - mmengine - INFO - Epoch(train) [195][45/63] lr: 1.9498e-03 eta: 11:16:41 time: 0.5835 data_time: 0.0045 memory: 17620 loss: 3.1372 loss_prob: 2.0495 loss_thr: 0.7292 loss_db: 0.3585 2022/11/01 15:03:43 - mmengine - INFO - Epoch(train) [195][50/63] lr: 1.9498e-03 eta: 11:16:32 time: 0.5895 data_time: 0.0214 memory: 17620 loss: 3.2976 loss_prob: 2.1656 loss_thr: 0.7491 loss_db: 0.3829 2022/11/01 15:03:46 - mmengine - INFO - Epoch(train) [195][55/63] lr: 1.9498e-03 eta: 11:16:32 time: 0.5777 data_time: 0.0225 memory: 17620 loss: 2.8365 loss_prob: 1.8065 loss_thr: 0.7264 loss_db: 0.3035 2022/11/01 15:03:48 - mmengine - INFO - Epoch(train) [195][60/63] lr: 1.9498e-03 eta: 11:16:21 time: 0.5560 data_time: 0.0076 memory: 17620 loss: 2.6532 loss_prob: 1.6570 loss_thr: 0.7260 loss_db: 0.2702 2022/11/01 15:03:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:03:54 - mmengine - INFO - Epoch(train) [196][5/63] lr: 1.9598e-03 eta: 11:16:21 time: 0.6968 data_time: 0.1799 memory: 17620 loss: 2.5472 loss_prob: 1.5908 loss_thr: 0.6940 loss_db: 0.2625 2022/11/01 15:03:57 - mmengine - INFO - Epoch(train) [196][10/63] lr: 1.9598e-03 eta: 11:16:08 time: 0.7358 data_time: 0.1828 memory: 17620 loss: 2.3989 loss_prob: 1.4738 loss_thr: 0.6889 loss_db: 0.2362 2022/11/01 15:04:00 - mmengine - INFO - Epoch(train) [196][15/63] lr: 1.9598e-03 eta: 11:16:08 time: 0.5611 data_time: 0.0118 memory: 17620 loss: 2.1886 loss_prob: 1.3195 loss_thr: 0.6613 loss_db: 0.2078 2022/11/01 15:04:03 - mmengine - INFO - Epoch(train) [196][20/63] lr: 1.9598e-03 eta: 11:15:57 time: 0.5510 data_time: 0.0084 memory: 17620 loss: 2.2218 loss_prob: 1.3487 loss_thr: 0.6598 loss_db: 0.2134 2022/11/01 15:04:05 - mmengine - INFO - Epoch(train) [196][25/63] lr: 1.9598e-03 eta: 11:15:57 time: 0.5434 data_time: 0.0131 memory: 17620 loss: 2.3251 loss_prob: 1.4267 loss_thr: 0.6734 loss_db: 0.2250 2022/11/01 15:04:08 - mmengine - INFO - Epoch(train) [196][30/63] lr: 1.9598e-03 eta: 11:15:47 time: 0.5773 data_time: 0.0333 memory: 17620 loss: 2.3243 loss_prob: 1.4243 loss_thr: 0.6728 loss_db: 0.2273 2022/11/01 15:04:11 - mmengine - INFO - Epoch(train) [196][35/63] lr: 1.9598e-03 eta: 11:15:47 time: 0.5775 data_time: 0.0270 memory: 17620 loss: 2.1980 loss_prob: 1.3428 loss_thr: 0.6404 loss_db: 0.2148 2022/11/01 15:04:14 - mmengine - INFO - Epoch(train) [196][40/63] lr: 1.9598e-03 eta: 11:15:37 time: 0.5716 data_time: 0.0084 memory: 17620 loss: 2.1424 loss_prob: 1.2883 loss_thr: 0.6478 loss_db: 0.2062 2022/11/01 15:04:17 - mmengine - INFO - Epoch(train) [196][45/63] lr: 1.9598e-03 eta: 11:15:37 time: 0.5585 data_time: 0.0088 memory: 17620 loss: 2.2004 loss_prob: 1.3208 loss_thr: 0.6679 loss_db: 0.2117 2022/11/01 15:04:20 - mmengine - INFO - Epoch(train) [196][50/63] lr: 1.9598e-03 eta: 11:15:26 time: 0.5541 data_time: 0.0140 memory: 17620 loss: 2.1236 loss_prob: 1.2668 loss_thr: 0.6577 loss_db: 0.1991 2022/11/01 15:04:23 - mmengine - INFO - Epoch(train) [196][55/63] lr: 1.9598e-03 eta: 11:15:26 time: 0.5771 data_time: 0.0228 memory: 17620 loss: 2.0842 loss_prob: 1.2287 loss_thr: 0.6638 loss_db: 0.1916 2022/11/01 15:04:25 - mmengine - INFO - Epoch(train) [196][60/63] lr: 1.9598e-03 eta: 11:15:16 time: 0.5780 data_time: 0.0190 memory: 17620 loss: 2.2910 loss_prob: 1.4040 loss_thr: 0.6583 loss_db: 0.2287 2022/11/01 15:04:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:04:32 - mmengine - INFO - Epoch(train) [197][5/63] lr: 1.9699e-03 eta: 11:15:16 time: 0.8287 data_time: 0.2115 memory: 17620 loss: 2.8428 loss_prob: 1.8092 loss_thr: 0.7397 loss_db: 0.2939 2022/11/01 15:04:36 - mmengine - INFO - Epoch(train) [197][10/63] lr: 1.9699e-03 eta: 11:15:13 time: 0.9292 data_time: 0.2105 memory: 17620 loss: 2.9619 loss_prob: 1.9056 loss_thr: 0.7447 loss_db: 0.3117 2022/11/01 15:04:39 - mmengine - INFO - Epoch(train) [197][15/63] lr: 1.9699e-03 eta: 11:15:13 time: 0.6632 data_time: 0.0070 memory: 17620 loss: 2.6981 loss_prob: 1.6999 loss_thr: 0.7193 loss_db: 0.2789 2022/11/01 15:04:42 - mmengine - INFO - Epoch(train) [197][20/63] lr: 1.9699e-03 eta: 11:15:04 time: 0.5928 data_time: 0.0073 memory: 17620 loss: 2.8693 loss_prob: 1.8251 loss_thr: 0.7360 loss_db: 0.3083 2022/11/01 15:04:45 - mmengine - INFO - Epoch(train) [197][25/63] lr: 1.9699e-03 eta: 11:15:04 time: 0.5725 data_time: 0.0175 memory: 17620 loss: 2.7273 loss_prob: 1.7417 loss_thr: 0.6944 loss_db: 0.2912 2022/11/01 15:04:48 - mmengine - INFO - Epoch(train) [197][30/63] lr: 1.9699e-03 eta: 11:14:57 time: 0.6170 data_time: 0.0362 memory: 17620 loss: 2.4420 loss_prob: 1.5258 loss_thr: 0.6699 loss_db: 0.2463 2022/11/01 15:04:51 - mmengine - INFO - Epoch(train) [197][35/63] lr: 1.9699e-03 eta: 11:14:57 time: 0.6169 data_time: 0.0257 memory: 17620 loss: 2.5564 loss_prob: 1.5916 loss_thr: 0.7024 loss_db: 0.2625 2022/11/01 15:04:54 - mmengine - INFO - Epoch(train) [197][40/63] lr: 1.9699e-03 eta: 11:14:47 time: 0.5776 data_time: 0.0088 memory: 17620 loss: 2.4763 loss_prob: 1.5234 loss_thr: 0.7021 loss_db: 0.2508 2022/11/01 15:04:57 - mmengine - INFO - Epoch(train) [197][45/63] lr: 1.9699e-03 eta: 11:14:47 time: 0.5879 data_time: 0.0106 memory: 17620 loss: 2.3809 loss_prob: 1.4650 loss_thr: 0.6784 loss_db: 0.2375 2022/11/01 15:05:00 - mmengine - INFO - Epoch(train) [197][50/63] lr: 1.9699e-03 eta: 11:14:39 time: 0.6038 data_time: 0.0152 memory: 17620 loss: 2.2934 loss_prob: 1.4112 loss_thr: 0.6562 loss_db: 0.2259 2022/11/01 15:05:03 - mmengine - INFO - Epoch(train) [197][55/63] lr: 1.9699e-03 eta: 11:14:39 time: 0.6523 data_time: 0.0238 memory: 17620 loss: 2.2509 loss_prob: 1.3817 loss_thr: 0.6517 loss_db: 0.2175 2022/11/01 15:05:06 - mmengine - INFO - Epoch(train) [197][60/63] lr: 1.9699e-03 eta: 11:14:33 time: 0.6554 data_time: 0.0170 memory: 17620 loss: 2.3158 loss_prob: 1.4322 loss_thr: 0.6549 loss_db: 0.2287 2022/11/01 15:05:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:05:13 - mmengine - INFO - Epoch(train) [198][5/63] lr: 1.9799e-03 eta: 11:14:33 time: 0.8059 data_time: 0.1867 memory: 17620 loss: 2.3725 loss_prob: 1.4489 loss_thr: 0.6901 loss_db: 0.2335 2022/11/01 15:05:17 - mmengine - INFO - Epoch(train) [198][10/63] lr: 1.9799e-03 eta: 11:14:28 time: 0.9047 data_time: 0.1855 memory: 17620 loss: 2.3609 loss_prob: 1.4369 loss_thr: 0.6935 loss_db: 0.2305 2022/11/01 15:05:20 - mmengine - INFO - Epoch(train) [198][15/63] lr: 1.9799e-03 eta: 11:14:28 time: 0.6913 data_time: 0.0096 memory: 17620 loss: 2.4418 loss_prob: 1.5109 loss_thr: 0.6862 loss_db: 0.2448 2022/11/01 15:05:23 - mmengine - INFO - Epoch(train) [198][20/63] lr: 1.9799e-03 eta: 11:14:20 time: 0.6019 data_time: 0.0143 memory: 17620 loss: 2.4755 loss_prob: 1.5254 loss_thr: 0.7001 loss_db: 0.2500 2022/11/01 15:05:27 - mmengine - INFO - Epoch(train) [198][25/63] lr: 1.9799e-03 eta: 11:14:20 time: 0.6492 data_time: 0.0191 memory: 17620 loss: 2.2881 loss_prob: 1.3662 loss_thr: 0.7040 loss_db: 0.2178 2022/11/01 15:05:30 - mmengine - INFO - Epoch(train) [198][30/63] lr: 1.9799e-03 eta: 11:14:16 time: 0.6937 data_time: 0.0285 memory: 17620 loss: 2.2548 loss_prob: 1.3566 loss_thr: 0.6836 loss_db: 0.2146 2022/11/01 15:05:33 - mmengine - INFO - Epoch(train) [198][35/63] lr: 1.9799e-03 eta: 11:14:16 time: 0.5984 data_time: 0.0193 memory: 17620 loss: 2.3344 loss_prob: 1.4150 loss_thr: 0.6892 loss_db: 0.2303 2022/11/01 15:05:35 - mmengine - INFO - Epoch(train) [198][40/63] lr: 1.9799e-03 eta: 11:14:04 time: 0.5311 data_time: 0.0086 memory: 17620 loss: 2.2880 loss_prob: 1.3840 loss_thr: 0.6797 loss_db: 0.2243 2022/11/01 15:05:38 - mmengine - INFO - Epoch(train) [198][45/63] lr: 1.9799e-03 eta: 11:14:04 time: 0.5511 data_time: 0.0146 memory: 17620 loss: 2.1760 loss_prob: 1.3284 loss_thr: 0.6361 loss_db: 0.2115 2022/11/01 15:05:41 - mmengine - INFO - Epoch(train) [198][50/63] lr: 1.9799e-03 eta: 11:13:56 time: 0.6063 data_time: 0.0513 memory: 17620 loss: 2.3063 loss_prob: 1.4050 loss_thr: 0.6726 loss_db: 0.2287 2022/11/01 15:05:44 - mmengine - INFO - Epoch(train) [198][55/63] lr: 1.9799e-03 eta: 11:13:56 time: 0.5760 data_time: 0.0473 memory: 17620 loss: 2.3487 loss_prob: 1.4244 loss_thr: 0.6939 loss_db: 0.2304 2022/11/01 15:05:47 - mmengine - INFO - Epoch(train) [198][60/63] lr: 1.9799e-03 eta: 11:13:44 time: 0.5239 data_time: 0.0070 memory: 17620 loss: 2.1584 loss_prob: 1.2858 loss_thr: 0.6697 loss_db: 0.2028 2022/11/01 15:05:48 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:05:53 - mmengine - INFO - Epoch(train) [199][5/63] lr: 1.9900e-03 eta: 11:13:44 time: 0.7339 data_time: 0.1901 memory: 17620 loss: 2.1372 loss_prob: 1.2791 loss_thr: 0.6548 loss_db: 0.2034 2022/11/01 15:05:56 - mmengine - INFO - Epoch(train) [199][10/63] lr: 1.9900e-03 eta: 11:13:32 time: 0.7604 data_time: 0.1931 memory: 17620 loss: 2.0715 loss_prob: 1.2551 loss_thr: 0.6153 loss_db: 0.2012 2022/11/01 15:05:58 - mmengine - INFO - Epoch(train) [199][15/63] lr: 1.9900e-03 eta: 11:13:32 time: 0.5643 data_time: 0.0117 memory: 17620 loss: 2.1786 loss_prob: 1.3219 loss_thr: 0.6436 loss_db: 0.2131 2022/11/01 15:06:01 - mmengine - INFO - Epoch(train) [199][20/63] lr: 1.9900e-03 eta: 11:13:23 time: 0.5824 data_time: 0.0053 memory: 17620 loss: 2.3654 loss_prob: 1.4583 loss_thr: 0.6726 loss_db: 0.2345 2022/11/01 15:06:04 - mmengine - INFO - Epoch(train) [199][25/63] lr: 1.9900e-03 eta: 11:13:23 time: 0.5673 data_time: 0.0155 memory: 17620 loss: 2.2004 loss_prob: 1.3312 loss_thr: 0.6565 loss_db: 0.2126 2022/11/01 15:06:07 - mmengine - INFO - Epoch(train) [199][30/63] lr: 1.9900e-03 eta: 11:13:12 time: 0.5494 data_time: 0.0323 memory: 17620 loss: 2.0915 loss_prob: 1.2512 loss_thr: 0.6400 loss_db: 0.2002 2022/11/01 15:06:10 - mmengine - INFO - Epoch(train) [199][35/63] lr: 1.9900e-03 eta: 11:13:12 time: 0.5604 data_time: 0.0258 memory: 17620 loss: 2.2992 loss_prob: 1.4102 loss_thr: 0.6587 loss_db: 0.2303 2022/11/01 15:06:13 - mmengine - INFO - Epoch(train) [199][40/63] lr: 1.9900e-03 eta: 11:13:01 time: 0.5603 data_time: 0.0090 memory: 17620 loss: 2.4726 loss_prob: 1.5292 loss_thr: 0.6916 loss_db: 0.2519 2022/11/01 15:06:15 - mmengine - INFO - Epoch(train) [199][45/63] lr: 1.9900e-03 eta: 11:13:01 time: 0.5324 data_time: 0.0066 memory: 17620 loss: 2.3828 loss_prob: 1.4722 loss_thr: 0.6725 loss_db: 0.2381 2022/11/01 15:06:18 - mmengine - INFO - Epoch(train) [199][50/63] lr: 1.9900e-03 eta: 11:12:49 time: 0.5199 data_time: 0.0114 memory: 17620 loss: 2.1725 loss_prob: 1.3125 loss_thr: 0.6502 loss_db: 0.2098 2022/11/01 15:06:21 - mmengine - INFO - Epoch(train) [199][55/63] lr: 1.9900e-03 eta: 11:12:49 time: 0.5558 data_time: 0.0211 memory: 17620 loss: 2.1085 loss_prob: 1.2461 loss_thr: 0.6595 loss_db: 0.2029 2022/11/01 15:06:23 - mmengine - INFO - Epoch(train) [199][60/63] lr: 1.9900e-03 eta: 11:12:38 time: 0.5587 data_time: 0.0163 memory: 17620 loss: 2.2015 loss_prob: 1.3023 loss_thr: 0.6865 loss_db: 0.2127 2022/11/01 15:06:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:06:30 - mmengine - INFO - Epoch(train) [200][5/63] lr: 2.0000e-03 eta: 11:12:38 time: 0.7623 data_time: 0.2362 memory: 17620 loss: 2.1032 loss_prob: 1.2617 loss_thr: 0.6431 loss_db: 0.1983 2022/11/01 15:06:33 - mmengine - INFO - Epoch(train) [200][10/63] lr: 2.0000e-03 eta: 11:12:29 time: 0.8103 data_time: 0.2405 memory: 17620 loss: 2.1401 loss_prob: 1.2892 loss_thr: 0.6466 loss_db: 0.2044 2022/11/01 15:06:36 - mmengine - INFO - Epoch(train) [200][15/63] lr: 2.0000e-03 eta: 11:12:29 time: 0.5810 data_time: 0.0092 memory: 17620 loss: 2.3042 loss_prob: 1.4230 loss_thr: 0.6524 loss_db: 0.2288 2022/11/01 15:06:38 - mmengine - INFO - Epoch(train) [200][20/63] lr: 2.0000e-03 eta: 11:12:19 time: 0.5674 data_time: 0.0090 memory: 17620 loss: 2.3730 loss_prob: 1.4789 loss_thr: 0.6569 loss_db: 0.2372 2022/11/01 15:06:41 - mmengine - INFO - Epoch(train) [200][25/63] lr: 2.0000e-03 eta: 11:12:19 time: 0.5494 data_time: 0.0267 memory: 17620 loss: 2.3670 loss_prob: 1.4697 loss_thr: 0.6572 loss_db: 0.2400 2022/11/01 15:06:44 - mmengine - INFO - Epoch(train) [200][30/63] lr: 2.0000e-03 eta: 11:12:09 time: 0.5647 data_time: 0.0239 memory: 17620 loss: 2.3780 loss_prob: 1.4643 loss_thr: 0.6666 loss_db: 0.2471 2022/11/01 15:06:47 - mmengine - INFO - Epoch(train) [200][35/63] lr: 2.0000e-03 eta: 11:12:09 time: 0.5522 data_time: 0.0122 memory: 17620 loss: 2.8017 loss_prob: 1.7815 loss_thr: 0.7159 loss_db: 0.3043 2022/11/01 15:06:49 - mmengine - INFO - Epoch(train) [200][40/63] lr: 2.0000e-03 eta: 11:11:56 time: 0.5203 data_time: 0.0143 memory: 17620 loss: 3.1535 loss_prob: 2.0250 loss_thr: 0.7747 loss_db: 0.3537 2022/11/01 15:06:52 - mmengine - INFO - Epoch(train) [200][45/63] lr: 2.0000e-03 eta: 11:11:56 time: 0.5308 data_time: 0.0087 memory: 17620 loss: 2.8640 loss_prob: 1.8232 loss_thr: 0.7322 loss_db: 0.3086 2022/11/01 15:06:55 - mmengine - INFO - Epoch(train) [200][50/63] lr: 2.0000e-03 eta: 11:11:48 time: 0.5990 data_time: 0.0153 memory: 17620 loss: 2.5742 loss_prob: 1.6207 loss_thr: 0.6913 loss_db: 0.2622 2022/11/01 15:06:58 - mmengine - INFO - Epoch(train) [200][55/63] lr: 2.0000e-03 eta: 11:11:48 time: 0.6244 data_time: 0.0166 memory: 17620 loss: 2.5328 loss_prob: 1.5464 loss_thr: 0.7346 loss_db: 0.2518 2022/11/01 15:07:01 - mmengine - INFO - Epoch(train) [200][60/63] lr: 2.0000e-03 eta: 11:11:40 time: 0.6119 data_time: 0.0113 memory: 17620 loss: 2.4725 loss_prob: 1.5039 loss_thr: 0.7254 loss_db: 0.2433 2022/11/01 15:07:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:07:03 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/11/01 15:07:10 - mmengine - INFO - Epoch(val) [200][5/32] eta: 11:11:40 time: 0.5318 data_time: 0.0566 memory: 17620 2022/11/01 15:07:13 - mmengine - INFO - Epoch(val) [200][10/32] eta: 0:00:13 time: 0.6256 data_time: 0.0969 memory: 15725 2022/11/01 15:07:16 - mmengine - INFO - Epoch(val) [200][15/32] eta: 0:00:13 time: 0.5824 data_time: 0.0537 memory: 15725 2022/11/01 15:07:19 - mmengine - INFO - Epoch(val) [200][20/32] eta: 0:00:06 time: 0.5641 data_time: 0.0417 memory: 15725 2022/11/01 15:07:22 - mmengine - INFO - Epoch(val) [200][25/32] eta: 0:00:06 time: 0.5880 data_time: 0.0544 memory: 15725 2022/11/01 15:07:24 - mmengine - INFO - Epoch(val) [200][30/32] eta: 0:00:01 time: 0.5544 data_time: 0.0292 memory: 15725 2022/11/01 15:07:25 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7439, precision: 0.6941, hmean: 0.7181 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7429, precision: 0.7995, hmean: 0.7702 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7328, precision: 0.8613, hmean: 0.7919 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7068, precision: 0.8929, hmean: 0.7890 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6071, precision: 0.9279, hmean: 0.7340 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.1960, precision: 0.9760, hmean: 0.3264 2022/11/01 15:07:25 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 15:07:25 - mmengine - INFO - Epoch(val) [200][32/32] icdar/precision: 0.8613 icdar/recall: 0.7328 icdar/hmean: 0.7919 2022/11/01 15:07:30 - mmengine - INFO - Epoch(train) [201][5/63] lr: 2.0000e-03 eta: 0:00:01 time: 0.7796 data_time: 0.1841 memory: 17620 loss: 2.5442 loss_prob: 1.6009 loss_thr: 0.6846 loss_db: 0.2587 2022/11/01 15:07:33 - mmengine - INFO - Epoch(train) [201][10/63] lr: 2.0000e-03 eta: 11:11:31 time: 0.8267 data_time: 0.1843 memory: 17620 loss: 2.5785 loss_prob: 1.5887 loss_thr: 0.7274 loss_db: 0.2625 2022/11/01 15:07:36 - mmengine - INFO - Epoch(train) [201][15/63] lr: 2.0000e-03 eta: 11:11:31 time: 0.6341 data_time: 0.0096 memory: 17620 loss: 2.6494 loss_prob: 1.6438 loss_thr: 0.7376 loss_db: 0.2680 2022/11/01 15:07:39 - mmengine - INFO - Epoch(train) [201][20/63] lr: 2.0000e-03 eta: 11:11:23 time: 0.6034 data_time: 0.0092 memory: 17620 loss: 2.6741 loss_prob: 1.6933 loss_thr: 0.7041 loss_db: 0.2768 2022/11/01 15:07:42 - mmengine - INFO - Epoch(train) [201][25/63] lr: 2.0000e-03 eta: 11:11:23 time: 0.6017 data_time: 0.0230 memory: 17620 loss: 2.6060 loss_prob: 1.6337 loss_thr: 0.6947 loss_db: 0.2776 2022/11/01 15:07:45 - mmengine - INFO - Epoch(train) [201][30/63] lr: 2.0000e-03 eta: 11:11:15 time: 0.5980 data_time: 0.0342 memory: 17620 loss: 2.4005 loss_prob: 1.4931 loss_thr: 0.6614 loss_db: 0.2460 2022/11/01 15:07:48 - mmengine - INFO - Epoch(train) [201][35/63] lr: 2.0000e-03 eta: 11:11:15 time: 0.5825 data_time: 0.0166 memory: 17620 loss: 2.1580 loss_prob: 1.3166 loss_thr: 0.6336 loss_db: 0.2078 2022/11/01 15:07:51 - mmengine - INFO - Epoch(train) [201][40/63] lr: 2.0000e-03 eta: 11:11:05 time: 0.5709 data_time: 0.0083 memory: 17620 loss: 2.0675 loss_prob: 1.2456 loss_thr: 0.6273 loss_db: 0.1945 2022/11/01 15:07:54 - mmengine - INFO - Epoch(train) [201][45/63] lr: 2.0000e-03 eta: 11:11:05 time: 0.5529 data_time: 0.0093 memory: 17620 loss: 2.2246 loss_prob: 1.3417 loss_thr: 0.6686 loss_db: 0.2143 2022/11/01 15:07:56 - mmengine - INFO - Epoch(train) [201][50/63] lr: 2.0000e-03 eta: 11:10:54 time: 0.5467 data_time: 0.0161 memory: 17620 loss: 2.2452 loss_prob: 1.3502 loss_thr: 0.6764 loss_db: 0.2186 2022/11/01 15:07:59 - mmengine - INFO - Epoch(train) [201][55/63] lr: 2.0000e-03 eta: 11:10:54 time: 0.5495 data_time: 0.0214 memory: 17620 loss: 2.1297 loss_prob: 1.2793 loss_thr: 0.6413 loss_db: 0.2091 2022/11/01 15:08:02 - mmengine - INFO - Epoch(train) [201][60/63] lr: 2.0000e-03 eta: 11:10:44 time: 0.5733 data_time: 0.0138 memory: 17620 loss: 2.0826 loss_prob: 1.2444 loss_thr: 0.6342 loss_db: 0.2040 2022/11/01 15:08:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:08:09 - mmengine - INFO - Epoch(train) [202][5/63] lr: 1.9982e-03 eta: 11:10:44 time: 0.7960 data_time: 0.2305 memory: 17620 loss: 2.2645 loss_prob: 1.3827 loss_thr: 0.6578 loss_db: 0.2241 2022/11/01 15:08:11 - mmengine - INFO - Epoch(train) [202][10/63] lr: 1.9982e-03 eta: 11:10:34 time: 0.7988 data_time: 0.2301 memory: 17620 loss: 2.2741 loss_prob: 1.3902 loss_thr: 0.6573 loss_db: 0.2266 2022/11/01 15:08:14 - mmengine - INFO - Epoch(train) [202][15/63] lr: 1.9982e-03 eta: 11:10:34 time: 0.5396 data_time: 0.0060 memory: 17620 loss: 2.3866 loss_prob: 1.4685 loss_thr: 0.6777 loss_db: 0.2404 2022/11/01 15:08:17 - mmengine - INFO - Epoch(train) [202][20/63] lr: 1.9982e-03 eta: 11:10:25 time: 0.5718 data_time: 0.0060 memory: 17620 loss: 2.4411 loss_prob: 1.5043 loss_thr: 0.6907 loss_db: 0.2460 2022/11/01 15:08:20 - mmengine - INFO - Epoch(train) [202][25/63] lr: 1.9982e-03 eta: 11:10:25 time: 0.5925 data_time: 0.0153 memory: 17620 loss: 2.3952 loss_prob: 1.4636 loss_thr: 0.6994 loss_db: 0.2323 2022/11/01 15:08:23 - mmengine - INFO - Epoch(train) [202][30/63] lr: 1.9982e-03 eta: 11:10:16 time: 0.5971 data_time: 0.0367 memory: 17620 loss: 2.6636 loss_prob: 1.6546 loss_thr: 0.7440 loss_db: 0.2650 2022/11/01 15:08:26 - mmengine - INFO - Epoch(train) [202][35/63] lr: 1.9982e-03 eta: 11:10:16 time: 0.5682 data_time: 0.0267 memory: 17620 loss: 2.4614 loss_prob: 1.5145 loss_thr: 0.7007 loss_db: 0.2462 2022/11/01 15:08:28 - mmengine - INFO - Epoch(train) [202][40/63] lr: 1.9982e-03 eta: 11:10:04 time: 0.5263 data_time: 0.0071 memory: 17620 loss: 2.2185 loss_prob: 1.3451 loss_thr: 0.6547 loss_db: 0.2187 2022/11/01 15:08:31 - mmengine - INFO - Epoch(train) [202][45/63] lr: 1.9982e-03 eta: 11:10:04 time: 0.5337 data_time: 0.0068 memory: 17620 loss: 2.2484 loss_prob: 1.3658 loss_thr: 0.6605 loss_db: 0.2221 2022/11/01 15:08:34 - mmengine - INFO - Epoch(train) [202][50/63] lr: 1.9982e-03 eta: 11:09:53 time: 0.5505 data_time: 0.0207 memory: 17620 loss: 2.1443 loss_prob: 1.2827 loss_thr: 0.6573 loss_db: 0.2044 2022/11/01 15:08:37 - mmengine - INFO - Epoch(train) [202][55/63] lr: 1.9982e-03 eta: 11:09:53 time: 0.5419 data_time: 0.0211 memory: 17620 loss: 2.3241 loss_prob: 1.4172 loss_thr: 0.6823 loss_db: 0.2247 2022/11/01 15:08:39 - mmengine - INFO - Epoch(train) [202][60/63] lr: 1.9982e-03 eta: 11:09:41 time: 0.5245 data_time: 0.0064 memory: 17620 loss: 2.6060 loss_prob: 1.6209 loss_thr: 0.7167 loss_db: 0.2684 2022/11/01 15:08:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:08:45 - mmengine - INFO - Epoch(train) [203][5/63] lr: 1.9964e-03 eta: 11:09:41 time: 0.6946 data_time: 0.1780 memory: 17620 loss: 2.6056 loss_prob: 1.6101 loss_thr: 0.7348 loss_db: 0.2607 2022/11/01 15:08:48 - mmengine - INFO - Epoch(train) [203][10/63] lr: 1.9964e-03 eta: 11:09:28 time: 0.7342 data_time: 0.1806 memory: 17620 loss: 2.2862 loss_prob: 1.3822 loss_thr: 0.6770 loss_db: 0.2270 2022/11/01 15:08:51 - mmengine - INFO - Epoch(train) [203][15/63] lr: 1.9964e-03 eta: 11:09:28 time: 0.5540 data_time: 0.0107 memory: 17620 loss: 2.1539 loss_prob: 1.2831 loss_thr: 0.6621 loss_db: 0.2087 2022/11/01 15:08:54 - mmengine - INFO - Epoch(train) [203][20/63] lr: 1.9964e-03 eta: 11:09:19 time: 0.5733 data_time: 0.0090 memory: 17620 loss: 2.2283 loss_prob: 1.3163 loss_thr: 0.7016 loss_db: 0.2104 2022/11/01 15:08:57 - mmengine - INFO - Epoch(train) [203][25/63] lr: 1.9964e-03 eta: 11:09:19 time: 0.6049 data_time: 0.0374 memory: 17620 loss: 2.2865 loss_prob: 1.3752 loss_thr: 0.6958 loss_db: 0.2155 2022/11/01 15:08:59 - mmengine - INFO - Epoch(train) [203][30/63] lr: 1.9964e-03 eta: 11:09:08 time: 0.5576 data_time: 0.0362 memory: 17620 loss: 2.1417 loss_prob: 1.3019 loss_thr: 0.6365 loss_db: 0.2033 2022/11/01 15:09:02 - mmengine - INFO - Epoch(train) [203][35/63] lr: 1.9964e-03 eta: 11:09:08 time: 0.5248 data_time: 0.0042 memory: 17620 loss: 2.2118 loss_prob: 1.3420 loss_thr: 0.6562 loss_db: 0.2136 2022/11/01 15:09:05 - mmengine - INFO - Epoch(train) [203][40/63] lr: 1.9964e-03 eta: 11:08:59 time: 0.5759 data_time: 0.0077 memory: 17620 loss: 2.2721 loss_prob: 1.3687 loss_thr: 0.6870 loss_db: 0.2164 2022/11/01 15:09:08 - mmengine - INFO - Epoch(train) [203][45/63] lr: 1.9964e-03 eta: 11:08:59 time: 0.5693 data_time: 0.0078 memory: 17620 loss: 2.1552 loss_prob: 1.2744 loss_thr: 0.6821 loss_db: 0.1987 2022/11/01 15:09:11 - mmengine - INFO - Epoch(train) [203][50/63] lr: 1.9964e-03 eta: 11:08:52 time: 0.6304 data_time: 0.0233 memory: 17620 loss: 2.2548 loss_prob: 1.3505 loss_thr: 0.6869 loss_db: 0.2173 2022/11/01 15:09:14 - mmengine - INFO - Epoch(train) [203][55/63] lr: 1.9964e-03 eta: 11:08:52 time: 0.6675 data_time: 0.0237 memory: 17620 loss: 2.3075 loss_prob: 1.4102 loss_thr: 0.6673 loss_db: 0.2299 2022/11/01 15:09:17 - mmengine - INFO - Epoch(train) [203][60/63] lr: 1.9964e-03 eta: 11:08:42 time: 0.5760 data_time: 0.0052 memory: 17620 loss: 2.3609 loss_prob: 1.4582 loss_thr: 0.6648 loss_db: 0.2379 2022/11/01 15:09:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:09:23 - mmengine - INFO - Epoch(train) [204][5/63] lr: 1.9946e-03 eta: 11:08:42 time: 0.7222 data_time: 0.1825 memory: 17620 loss: 2.3987 loss_prob: 1.4689 loss_thr: 0.6883 loss_db: 0.2416 2022/11/01 15:09:26 - mmengine - INFO - Epoch(train) [204][10/63] lr: 1.9946e-03 eta: 11:08:32 time: 0.7902 data_time: 0.1871 memory: 17620 loss: 2.4435 loss_prob: 1.4824 loss_thr: 0.7140 loss_db: 0.2471 2022/11/01 15:09:30 - mmengine - INFO - Epoch(train) [204][15/63] lr: 1.9946e-03 eta: 11:08:32 time: 0.6857 data_time: 0.0141 memory: 17620 loss: 2.3441 loss_prob: 1.4309 loss_thr: 0.6798 loss_db: 0.2334 2022/11/01 15:09:33 - mmengine - INFO - Epoch(train) [204][20/63] lr: 1.9946e-03 eta: 11:08:28 time: 0.6842 data_time: 0.0093 memory: 17620 loss: 2.4260 loss_prob: 1.5016 loss_thr: 0.6865 loss_db: 0.2380 2022/11/01 15:09:36 - mmengine - INFO - Epoch(train) [204][25/63] lr: 1.9946e-03 eta: 11:08:28 time: 0.6087 data_time: 0.0132 memory: 17620 loss: 2.3158 loss_prob: 1.4211 loss_thr: 0.6710 loss_db: 0.2237 2022/11/01 15:09:39 - mmengine - INFO - Epoch(train) [204][30/63] lr: 1.9946e-03 eta: 11:08:20 time: 0.6029 data_time: 0.0414 memory: 17620 loss: 2.0195 loss_prob: 1.2103 loss_thr: 0.6135 loss_db: 0.1956 2022/11/01 15:09:42 - mmengine - INFO - Epoch(train) [204][35/63] lr: 1.9946e-03 eta: 11:08:20 time: 0.6364 data_time: 0.0363 memory: 17620 loss: 2.3304 loss_prob: 1.4418 loss_thr: 0.6594 loss_db: 0.2292 2022/11/01 15:09:46 - mmengine - INFO - Epoch(train) [204][40/63] lr: 1.9946e-03 eta: 11:08:13 time: 0.6285 data_time: 0.0080 memory: 17620 loss: 2.6270 loss_prob: 1.6355 loss_thr: 0.7318 loss_db: 0.2597 2022/11/01 15:09:49 - mmengine - INFO - Epoch(train) [204][45/63] lr: 1.9946e-03 eta: 11:08:13 time: 0.6090 data_time: 0.0071 memory: 17620 loss: 2.4626 loss_prob: 1.4874 loss_thr: 0.7278 loss_db: 0.2474 2022/11/01 15:09:52 - mmengine - INFO - Epoch(train) [204][50/63] lr: 1.9946e-03 eta: 11:08:06 time: 0.6331 data_time: 0.0128 memory: 17620 loss: 2.3732 loss_prob: 1.4458 loss_thr: 0.6909 loss_db: 0.2366 2022/11/01 15:09:55 - mmengine - INFO - Epoch(train) [204][55/63] lr: 1.9946e-03 eta: 11:08:06 time: 0.6090 data_time: 0.0205 memory: 17620 loss: 2.3739 loss_prob: 1.4531 loss_thr: 0.6851 loss_db: 0.2356 2022/11/01 15:09:58 - mmengine - INFO - Epoch(train) [204][60/63] lr: 1.9946e-03 eta: 11:07:59 time: 0.6245 data_time: 0.0176 memory: 17620 loss: 2.4066 loss_prob: 1.4687 loss_thr: 0.6951 loss_db: 0.2428 2022/11/01 15:10:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:10:06 - mmengine - INFO - Epoch(train) [205][5/63] lr: 1.9928e-03 eta: 11:07:59 time: 0.8695 data_time: 0.2167 memory: 17620 loss: 2.3535 loss_prob: 1.4295 loss_thr: 0.6853 loss_db: 0.2387 2022/11/01 15:10:09 - mmengine - INFO - Epoch(train) [205][10/63] lr: 1.9928e-03 eta: 11:07:55 time: 0.9104 data_time: 0.2111 memory: 17620 loss: 2.3926 loss_prob: 1.4509 loss_thr: 0.6995 loss_db: 0.2422 2022/11/01 15:10:13 - mmengine - INFO - Epoch(train) [205][15/63] lr: 1.9928e-03 eta: 11:07:55 time: 0.7183 data_time: 0.0050 memory: 17620 loss: 2.3361 loss_prob: 1.4214 loss_thr: 0.6828 loss_db: 0.2319 2022/11/01 15:10:15 - mmengine - INFO - Epoch(train) [205][20/63] lr: 1.9928e-03 eta: 11:07:50 time: 0.6763 data_time: 0.0060 memory: 17620 loss: 2.5037 loss_prob: 1.5526 loss_thr: 0.6973 loss_db: 0.2537 2022/11/01 15:10:18 - mmengine - INFO - Epoch(train) [205][25/63] lr: 1.9928e-03 eta: 11:07:50 time: 0.5585 data_time: 0.0193 memory: 17620 loss: 2.6080 loss_prob: 1.6211 loss_thr: 0.7187 loss_db: 0.2682 2022/11/01 15:10:21 - mmengine - INFO - Epoch(train) [205][30/63] lr: 1.9928e-03 eta: 11:07:41 time: 0.5822 data_time: 0.0359 memory: 17620 loss: 2.2884 loss_prob: 1.3816 loss_thr: 0.6798 loss_db: 0.2269 2022/11/01 15:10:24 - mmengine - INFO - Epoch(train) [205][35/63] lr: 1.9928e-03 eta: 11:07:41 time: 0.5861 data_time: 0.0222 memory: 17620 loss: 2.2870 loss_prob: 1.3754 loss_thr: 0.6891 loss_db: 0.2226 2022/11/01 15:10:27 - mmengine - INFO - Epoch(train) [205][40/63] lr: 1.9928e-03 eta: 11:07:31 time: 0.5665 data_time: 0.0046 memory: 17620 loss: 2.6551 loss_prob: 1.6684 loss_thr: 0.7142 loss_db: 0.2725 2022/11/01 15:10:30 - mmengine - INFO - Epoch(train) [205][45/63] lr: 1.9928e-03 eta: 11:07:31 time: 0.5516 data_time: 0.0068 memory: 17620 loss: 2.8756 loss_prob: 1.8272 loss_thr: 0.7408 loss_db: 0.3076 2022/11/01 15:10:33 - mmengine - INFO - Epoch(train) [205][50/63] lr: 1.9928e-03 eta: 11:07:22 time: 0.5731 data_time: 0.0146 memory: 17620 loss: 3.1064 loss_prob: 1.9777 loss_thr: 0.7889 loss_db: 0.3398 2022/11/01 15:10:35 - mmengine - INFO - Epoch(train) [205][55/63] lr: 1.9928e-03 eta: 11:07:22 time: 0.5664 data_time: 0.0221 memory: 17620 loss: 3.2554 loss_prob: 2.1096 loss_thr: 0.7788 loss_db: 0.3670 2022/11/01 15:10:38 - mmengine - INFO - Epoch(train) [205][60/63] lr: 1.9928e-03 eta: 11:07:10 time: 0.5317 data_time: 0.0148 memory: 17620 loss: 3.3638 loss_prob: 2.1849 loss_thr: 0.7884 loss_db: 0.3904 2022/11/01 15:10:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:10:44 - mmengine - INFO - Epoch(train) [206][5/63] lr: 1.9910e-03 eta: 11:07:10 time: 0.7413 data_time: 0.1950 memory: 17620 loss: 3.3269 loss_prob: 2.1509 loss_thr: 0.8089 loss_db: 0.3671 2022/11/01 15:10:47 - mmengine - INFO - Epoch(train) [206][10/63] lr: 1.9910e-03 eta: 11:07:01 time: 0.8178 data_time: 0.1990 memory: 17620 loss: 3.1447 loss_prob: 2.0448 loss_thr: 0.7620 loss_db: 0.3379 2022/11/01 15:10:50 - mmengine - INFO - Epoch(train) [206][15/63] lr: 1.9910e-03 eta: 11:07:01 time: 0.6071 data_time: 0.0186 memory: 17620 loss: 3.0474 loss_prob: 1.9744 loss_thr: 0.7387 loss_db: 0.3343 2022/11/01 15:10:53 - mmengine - INFO - Epoch(train) [206][20/63] lr: 1.9910e-03 eta: 11:06:51 time: 0.5594 data_time: 0.0135 memory: 17620 loss: 2.8759 loss_prob: 1.8370 loss_thr: 0.7389 loss_db: 0.3001 2022/11/01 15:10:56 - mmengine - INFO - Epoch(train) [206][25/63] lr: 1.9910e-03 eta: 11:06:51 time: 0.5620 data_time: 0.0073 memory: 17620 loss: 2.8630 loss_prob: 1.8273 loss_thr: 0.7433 loss_db: 0.2924 2022/11/01 15:10:59 - mmengine - INFO - Epoch(train) [206][30/63] lr: 1.9910e-03 eta: 11:06:41 time: 0.5711 data_time: 0.0245 memory: 17620 loss: 2.9673 loss_prob: 1.8999 loss_thr: 0.7563 loss_db: 0.3110 2022/11/01 15:11:01 - mmengine - INFO - Epoch(train) [206][35/63] lr: 1.9910e-03 eta: 11:06:41 time: 0.5449 data_time: 0.0277 memory: 17620 loss: 2.8822 loss_prob: 1.8186 loss_thr: 0.7629 loss_db: 0.3008 2022/11/01 15:11:04 - mmengine - INFO - Epoch(train) [206][40/63] lr: 1.9910e-03 eta: 11:06:31 time: 0.5571 data_time: 0.0185 memory: 17620 loss: 3.0477 loss_prob: 1.9425 loss_thr: 0.7625 loss_db: 0.3428 2022/11/01 15:11:07 - mmengine - INFO - Epoch(train) [206][45/63] lr: 1.9910e-03 eta: 11:06:31 time: 0.5804 data_time: 0.0125 memory: 17620 loss: 2.8091 loss_prob: 1.7818 loss_thr: 0.7193 loss_db: 0.3081 2022/11/01 15:11:10 - mmengine - INFO - Epoch(train) [206][50/63] lr: 1.9910e-03 eta: 11:06:21 time: 0.5680 data_time: 0.0162 memory: 17620 loss: 2.3613 loss_prob: 1.4491 loss_thr: 0.6835 loss_db: 0.2288 2022/11/01 15:11:13 - mmengine - INFO - Epoch(train) [206][55/63] lr: 1.9910e-03 eta: 11:06:21 time: 0.5458 data_time: 0.0183 memory: 17620 loss: 2.4959 loss_prob: 1.5441 loss_thr: 0.7022 loss_db: 0.2496 2022/11/01 15:11:15 - mmengine - INFO - Epoch(train) [206][60/63] lr: 1.9910e-03 eta: 11:06:10 time: 0.5402 data_time: 0.0090 memory: 17620 loss: 2.5799 loss_prob: 1.6165 loss_thr: 0.7006 loss_db: 0.2629 2022/11/01 15:11:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:11:22 - mmengine - INFO - Epoch(train) [207][5/63] lr: 1.9892e-03 eta: 11:06:10 time: 0.7390 data_time: 0.1935 memory: 17620 loss: 2.2424 loss_prob: 1.3683 loss_thr: 0.6519 loss_db: 0.2222 2022/11/01 15:11:25 - mmengine - INFO - Epoch(train) [207][10/63] lr: 1.9892e-03 eta: 11:05:59 time: 0.7810 data_time: 0.1918 memory: 17620 loss: 2.3352 loss_prob: 1.4345 loss_thr: 0.6644 loss_db: 0.2362 2022/11/01 15:11:27 - mmengine - INFO - Epoch(train) [207][15/63] lr: 1.9892e-03 eta: 11:05:59 time: 0.5596 data_time: 0.0094 memory: 17620 loss: 2.4060 loss_prob: 1.4785 loss_thr: 0.6821 loss_db: 0.2454 2022/11/01 15:11:30 - mmengine - INFO - Epoch(train) [207][20/63] lr: 1.9892e-03 eta: 11:05:47 time: 0.5203 data_time: 0.0064 memory: 17620 loss: 2.1708 loss_prob: 1.3059 loss_thr: 0.6540 loss_db: 0.2109 2022/11/01 15:11:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:11:33 - mmengine - INFO - Epoch(train) [207][25/63] lr: 1.9892e-03 eta: 11:05:47 time: 0.5934 data_time: 0.0384 memory: 17620 loss: 2.2724 loss_prob: 1.4030 loss_thr: 0.6486 loss_db: 0.2209 2022/11/01 15:11:36 - mmengine - INFO - Epoch(train) [207][30/63] lr: 1.9892e-03 eta: 11:05:40 time: 0.6251 data_time: 0.0382 memory: 17620 loss: 2.3223 loss_prob: 1.4406 loss_thr: 0.6538 loss_db: 0.2279 2022/11/01 15:11:40 - mmengine - INFO - Epoch(train) [207][35/63] lr: 1.9892e-03 eta: 11:05:40 time: 0.6308 data_time: 0.0058 memory: 17620 loss: 2.2855 loss_prob: 1.3894 loss_thr: 0.6741 loss_db: 0.2220 2022/11/01 15:11:42 - mmengine - INFO - Epoch(train) [207][40/63] lr: 1.9892e-03 eta: 11:05:33 time: 0.6111 data_time: 0.0090 memory: 17620 loss: 2.2582 loss_prob: 1.3623 loss_thr: 0.6776 loss_db: 0.2183 2022/11/01 15:11:45 - mmengine - INFO - Epoch(train) [207][45/63] lr: 1.9892e-03 eta: 11:05:33 time: 0.5397 data_time: 0.0093 memory: 17620 loss: 2.2492 loss_prob: 1.3544 loss_thr: 0.6792 loss_db: 0.2156 2022/11/01 15:11:48 - mmengine - INFO - Epoch(train) [207][50/63] lr: 1.9892e-03 eta: 11:05:23 time: 0.5762 data_time: 0.0223 memory: 17620 loss: 2.3704 loss_prob: 1.4565 loss_thr: 0.6851 loss_db: 0.2288 2022/11/01 15:11:51 - mmengine - INFO - Epoch(train) [207][55/63] lr: 1.9892e-03 eta: 11:05:23 time: 0.6407 data_time: 0.0220 memory: 17620 loss: 2.4102 loss_prob: 1.4832 loss_thr: 0.6901 loss_db: 0.2369 2022/11/01 15:11:54 - mmengine - INFO - Epoch(train) [207][60/63] lr: 1.9892e-03 eta: 11:05:15 time: 0.5960 data_time: 0.0074 memory: 17620 loss: 2.3872 loss_prob: 1.4682 loss_thr: 0.6760 loss_db: 0.2430 2022/11/01 15:11:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:12:02 - mmengine - INFO - Epoch(train) [208][5/63] lr: 1.9874e-03 eta: 11:05:15 time: 0.8972 data_time: 0.2189 memory: 17620 loss: 2.1588 loss_prob: 1.3127 loss_thr: 0.6378 loss_db: 0.2084 2022/11/01 15:12:05 - mmengine - INFO - Epoch(train) [208][10/63] lr: 1.9874e-03 eta: 11:05:14 time: 0.9828 data_time: 0.2166 memory: 17620 loss: 2.2269 loss_prob: 1.3635 loss_thr: 0.6448 loss_db: 0.2185 2022/11/01 15:12:08 - mmengine - INFO - Epoch(train) [208][15/63] lr: 1.9874e-03 eta: 11:05:14 time: 0.6140 data_time: 0.0073 memory: 17620 loss: 2.2229 loss_prob: 1.3587 loss_thr: 0.6431 loss_db: 0.2210 2022/11/01 15:12:11 - mmengine - INFO - Epoch(train) [208][20/63] lr: 1.9874e-03 eta: 11:05:04 time: 0.5544 data_time: 0.0086 memory: 17620 loss: 2.2342 loss_prob: 1.3537 loss_thr: 0.6560 loss_db: 0.2245 2022/11/01 15:12:14 - mmengine - INFO - Epoch(train) [208][25/63] lr: 1.9874e-03 eta: 11:05:04 time: 0.5497 data_time: 0.0266 memory: 17620 loss: 2.2650 loss_prob: 1.3784 loss_thr: 0.6562 loss_db: 0.2303 2022/11/01 15:12:17 - mmengine - INFO - Epoch(train) [208][30/63] lr: 1.9874e-03 eta: 11:04:58 time: 0.6571 data_time: 0.0369 memory: 17620 loss: 2.4276 loss_prob: 1.5007 loss_thr: 0.6790 loss_db: 0.2480 2022/11/01 15:12:21 - mmengine - INFO - Epoch(train) [208][35/63] lr: 1.9874e-03 eta: 11:04:58 time: 0.7093 data_time: 0.0181 memory: 17620 loss: 2.4256 loss_prob: 1.5139 loss_thr: 0.6657 loss_db: 0.2460 2022/11/01 15:12:23 - mmengine - INFO - Epoch(train) [208][40/63] lr: 1.9874e-03 eta: 11:04:51 time: 0.6151 data_time: 0.0076 memory: 17620 loss: 2.4530 loss_prob: 1.5459 loss_thr: 0.6590 loss_db: 0.2481 2022/11/01 15:12:26 - mmengine - INFO - Epoch(train) [208][45/63] lr: 1.9874e-03 eta: 11:04:51 time: 0.5405 data_time: 0.0083 memory: 17620 loss: 2.6228 loss_prob: 1.6444 loss_thr: 0.7109 loss_db: 0.2675 2022/11/01 15:12:29 - mmengine - INFO - Epoch(train) [208][50/63] lr: 1.9874e-03 eta: 11:04:40 time: 0.5456 data_time: 0.0218 memory: 17620 loss: 2.4420 loss_prob: 1.4924 loss_thr: 0.7082 loss_db: 0.2414 2022/11/01 15:12:32 - mmengine - INFO - Epoch(train) [208][55/63] lr: 1.9874e-03 eta: 11:04:40 time: 0.5490 data_time: 0.0225 memory: 17620 loss: 2.2496 loss_prob: 1.3753 loss_thr: 0.6615 loss_db: 0.2128 2022/11/01 15:12:35 - mmengine - INFO - Epoch(train) [208][60/63] lr: 1.9874e-03 eta: 11:04:30 time: 0.5675 data_time: 0.0090 memory: 17620 loss: 2.1407 loss_prob: 1.3028 loss_thr: 0.6376 loss_db: 0.2003 2022/11/01 15:12:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:12:41 - mmengine - INFO - Epoch(train) [209][5/63] lr: 1.9856e-03 eta: 11:04:30 time: 0.8076 data_time: 0.2537 memory: 17620 loss: 2.3480 loss_prob: 1.4468 loss_thr: 0.6623 loss_db: 0.2389 2022/11/01 15:12:44 - mmengine - INFO - Epoch(train) [209][10/63] lr: 1.9856e-03 eta: 11:04:22 time: 0.8284 data_time: 0.2535 memory: 17620 loss: 2.3792 loss_prob: 1.4651 loss_thr: 0.6767 loss_db: 0.2375 2022/11/01 15:12:47 - mmengine - INFO - Epoch(train) [209][15/63] lr: 1.9856e-03 eta: 11:04:22 time: 0.5724 data_time: 0.0083 memory: 17620 loss: 2.2987 loss_prob: 1.3951 loss_thr: 0.6823 loss_db: 0.2214 2022/11/01 15:12:50 - mmengine - INFO - Epoch(train) [209][20/63] lr: 1.9856e-03 eta: 11:04:10 time: 0.5300 data_time: 0.0089 memory: 17620 loss: 2.6017 loss_prob: 1.6338 loss_thr: 0.6991 loss_db: 0.2688 2022/11/01 15:12:53 - mmengine - INFO - Epoch(train) [209][25/63] lr: 1.9856e-03 eta: 11:04:10 time: 0.5503 data_time: 0.0365 memory: 17620 loss: 2.6853 loss_prob: 1.7116 loss_thr: 0.6958 loss_db: 0.2779 2022/11/01 15:12:55 - mmengine - INFO - Epoch(train) [209][30/63] lr: 1.9856e-03 eta: 11:04:00 time: 0.5456 data_time: 0.0347 memory: 17620 loss: 2.5231 loss_prob: 1.5793 loss_thr: 0.6924 loss_db: 0.2515 2022/11/01 15:12:58 - mmengine - INFO - Epoch(train) [209][35/63] lr: 1.9856e-03 eta: 11:04:00 time: 0.5186 data_time: 0.0043 memory: 17620 loss: 2.3672 loss_prob: 1.4384 loss_thr: 0.6942 loss_db: 0.2346 2022/11/01 15:13:00 - mmengine - INFO - Epoch(train) [209][40/63] lr: 1.9856e-03 eta: 11:03:48 time: 0.5232 data_time: 0.0046 memory: 17620 loss: 2.5401 loss_prob: 1.5881 loss_thr: 0.6827 loss_db: 0.2693 2022/11/01 15:13:03 - mmengine - INFO - Epoch(train) [209][45/63] lr: 1.9856e-03 eta: 11:03:48 time: 0.5448 data_time: 0.0047 memory: 17620 loss: 2.5029 loss_prob: 1.5864 loss_thr: 0.6547 loss_db: 0.2618 2022/11/01 15:13:06 - mmengine - INFO - Epoch(train) [209][50/63] lr: 1.9856e-03 eta: 11:03:40 time: 0.6016 data_time: 0.0217 memory: 17620 loss: 2.3555 loss_prob: 1.4540 loss_thr: 0.6686 loss_db: 0.2330 2022/11/01 15:13:09 - mmengine - INFO - Epoch(train) [209][55/63] lr: 1.9856e-03 eta: 11:03:40 time: 0.5884 data_time: 0.0232 memory: 17620 loss: 2.5753 loss_prob: 1.6032 loss_thr: 0.7032 loss_db: 0.2689 2022/11/01 15:13:12 - mmengine - INFO - Epoch(train) [209][60/63] lr: 1.9856e-03 eta: 11:03:29 time: 0.5504 data_time: 0.0067 memory: 17620 loss: 2.4425 loss_prob: 1.5177 loss_thr: 0.6738 loss_db: 0.2509 2022/11/01 15:13:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:13:19 - mmengine - INFO - Epoch(train) [210][5/63] lr: 1.9838e-03 eta: 11:03:29 time: 0.8052 data_time: 0.2091 memory: 17620 loss: 2.7481 loss_prob: 1.7116 loss_thr: 0.7506 loss_db: 0.2859 2022/11/01 15:13:22 - mmengine - INFO - Epoch(train) [210][10/63] lr: 1.9838e-03 eta: 11:03:20 time: 0.8122 data_time: 0.2086 memory: 17620 loss: 2.8127 loss_prob: 1.7624 loss_thr: 0.7576 loss_db: 0.2927 2022/11/01 15:13:25 - mmengine - INFO - Epoch(train) [210][15/63] lr: 1.9838e-03 eta: 11:03:20 time: 0.5921 data_time: 0.0092 memory: 17620 loss: 2.8856 loss_prob: 1.8540 loss_thr: 0.7238 loss_db: 0.3078 2022/11/01 15:13:28 - mmengine - INFO - Epoch(train) [210][20/63] lr: 1.9838e-03 eta: 11:03:12 time: 0.6096 data_time: 0.0112 memory: 17620 loss: 2.8565 loss_prob: 1.8357 loss_thr: 0.7154 loss_db: 0.3054 2022/11/01 15:13:30 - mmengine - INFO - Epoch(train) [210][25/63] lr: 1.9838e-03 eta: 11:03:12 time: 0.5653 data_time: 0.0196 memory: 17620 loss: 2.6103 loss_prob: 1.6507 loss_thr: 0.6961 loss_db: 0.2636 2022/11/01 15:13:33 - mmengine - INFO - Epoch(train) [210][30/63] lr: 1.9838e-03 eta: 11:03:03 time: 0.5709 data_time: 0.0493 memory: 17620 loss: 2.4097 loss_prob: 1.4945 loss_thr: 0.6840 loss_db: 0.2313 2022/11/01 15:13:36 - mmengine - INFO - Epoch(train) [210][35/63] lr: 1.9838e-03 eta: 11:03:03 time: 0.5736 data_time: 0.0364 memory: 17620 loss: 2.2507 loss_prob: 1.3731 loss_thr: 0.6624 loss_db: 0.2152 2022/11/01 15:13:39 - mmengine - INFO - Epoch(train) [210][40/63] lr: 1.9838e-03 eta: 11:02:53 time: 0.5587 data_time: 0.0072 memory: 17620 loss: 2.6203 loss_prob: 1.6589 loss_thr: 0.6889 loss_db: 0.2725 2022/11/01 15:13:42 - mmengine - INFO - Epoch(train) [210][45/63] lr: 1.9838e-03 eta: 11:02:53 time: 0.5552 data_time: 0.0105 memory: 17620 loss: 2.6693 loss_prob: 1.6779 loss_thr: 0.7146 loss_db: 0.2769 2022/11/01 15:13:45 - mmengine - INFO - Epoch(train) [210][50/63] lr: 1.9838e-03 eta: 11:02:42 time: 0.5461 data_time: 0.0213 memory: 17620 loss: 2.2022 loss_prob: 1.3317 loss_thr: 0.6559 loss_db: 0.2146 2022/11/01 15:13:47 - mmengine - INFO - Epoch(train) [210][55/63] lr: 1.9838e-03 eta: 11:02:42 time: 0.5680 data_time: 0.0254 memory: 17620 loss: 2.0333 loss_prob: 1.2223 loss_thr: 0.6166 loss_db: 0.1944 2022/11/01 15:13:50 - mmengine - INFO - Epoch(train) [210][60/63] lr: 1.9838e-03 eta: 11:02:31 time: 0.5443 data_time: 0.0133 memory: 17620 loss: 2.0242 loss_prob: 1.2025 loss_thr: 0.6327 loss_db: 0.1890 2022/11/01 15:13:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:13:58 - mmengine - INFO - Epoch(train) [211][5/63] lr: 1.9820e-03 eta: 11:02:31 time: 0.8941 data_time: 0.2225 memory: 17620 loss: 2.2033 loss_prob: 1.3125 loss_thr: 0.6767 loss_db: 0.2141 2022/11/01 15:14:01 - mmengine - INFO - Epoch(train) [211][10/63] lr: 1.9820e-03 eta: 11:02:30 time: 0.9767 data_time: 0.2216 memory: 17620 loss: 2.5263 loss_prob: 1.5662 loss_thr: 0.7061 loss_db: 0.2539 2022/11/01 15:14:04 - mmengine - INFO - Epoch(train) [211][15/63] lr: 1.9820e-03 eta: 11:02:30 time: 0.6294 data_time: 0.0057 memory: 17620 loss: 2.4776 loss_prob: 1.5302 loss_thr: 0.7007 loss_db: 0.2467 2022/11/01 15:14:07 - mmengine - INFO - Epoch(train) [211][20/63] lr: 1.9820e-03 eta: 11:02:21 time: 0.5779 data_time: 0.0097 memory: 17620 loss: 2.2828 loss_prob: 1.3925 loss_thr: 0.6671 loss_db: 0.2233 2022/11/01 15:14:10 - mmengine - INFO - Epoch(train) [211][25/63] lr: 1.9820e-03 eta: 11:02:21 time: 0.5876 data_time: 0.0283 memory: 17620 loss: 2.2676 loss_prob: 1.3905 loss_thr: 0.6573 loss_db: 0.2199 2022/11/01 15:14:13 - mmengine - INFO - Epoch(train) [211][30/63] lr: 1.9820e-03 eta: 11:02:14 time: 0.6240 data_time: 0.0315 memory: 17620 loss: 2.2305 loss_prob: 1.3556 loss_thr: 0.6611 loss_db: 0.2139 2022/11/01 15:14:16 - mmengine - INFO - Epoch(train) [211][35/63] lr: 1.9820e-03 eta: 11:02:14 time: 0.5868 data_time: 0.0118 memory: 17620 loss: 2.2638 loss_prob: 1.3894 loss_thr: 0.6508 loss_db: 0.2236 2022/11/01 15:14:19 - mmengine - INFO - Epoch(train) [211][40/63] lr: 1.9820e-03 eta: 11:02:05 time: 0.5906 data_time: 0.0090 memory: 17620 loss: 2.2063 loss_prob: 1.3408 loss_thr: 0.6486 loss_db: 0.2169 2022/11/01 15:14:22 - mmengine - INFO - Epoch(train) [211][45/63] lr: 1.9820e-03 eta: 11:02:05 time: 0.6181 data_time: 0.0142 memory: 17620 loss: 2.2514 loss_prob: 1.3500 loss_thr: 0.6792 loss_db: 0.2223 2022/11/01 15:14:25 - mmengine - INFO - Epoch(train) [211][50/63] lr: 1.9820e-03 eta: 11:01:56 time: 0.5844 data_time: 0.0243 memory: 17620 loss: 2.2466 loss_prob: 1.3482 loss_thr: 0.6791 loss_db: 0.2192 2022/11/01 15:14:28 - mmengine - INFO - Epoch(train) [211][55/63] lr: 1.9820e-03 eta: 11:01:56 time: 0.5719 data_time: 0.0239 memory: 17620 loss: 2.2171 loss_prob: 1.3130 loss_thr: 0.6918 loss_db: 0.2124 2022/11/01 15:14:31 - mmengine - INFO - Epoch(train) [211][60/63] lr: 1.9820e-03 eta: 11:01:46 time: 0.5544 data_time: 0.0098 memory: 17620 loss: 2.2184 loss_prob: 1.3199 loss_thr: 0.6826 loss_db: 0.2159 2022/11/01 15:14:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:14:37 - mmengine - INFO - Epoch(train) [212][5/63] lr: 1.9802e-03 eta: 11:01:46 time: 0.7341 data_time: 0.1964 memory: 17620 loss: 2.2414 loss_prob: 1.3441 loss_thr: 0.6871 loss_db: 0.2101 2022/11/01 15:14:40 - mmengine - INFO - Epoch(train) [212][10/63] lr: 1.9802e-03 eta: 11:01:35 time: 0.7745 data_time: 0.1968 memory: 17620 loss: 2.2151 loss_prob: 1.3343 loss_thr: 0.6735 loss_db: 0.2073 2022/11/01 15:14:43 - mmengine - INFO - Epoch(train) [212][15/63] lr: 1.9802e-03 eta: 11:01:35 time: 0.5815 data_time: 0.0051 memory: 17620 loss: 2.1887 loss_prob: 1.3218 loss_thr: 0.6595 loss_db: 0.2074 2022/11/01 15:14:46 - mmengine - INFO - Epoch(train) [212][20/63] lr: 1.9802e-03 eta: 11:01:27 time: 0.5888 data_time: 0.0063 memory: 17620 loss: 2.1474 loss_prob: 1.2952 loss_thr: 0.6515 loss_db: 0.2006 2022/11/01 15:14:48 - mmengine - INFO - Epoch(train) [212][25/63] lr: 1.9802e-03 eta: 11:01:27 time: 0.5818 data_time: 0.0253 memory: 17620 loss: 2.2840 loss_prob: 1.4158 loss_thr: 0.6468 loss_db: 0.2213 2022/11/01 15:14:51 - mmengine - INFO - Epoch(train) [212][30/63] lr: 1.9802e-03 eta: 11:01:18 time: 0.5867 data_time: 0.0385 memory: 17620 loss: 2.2860 loss_prob: 1.4198 loss_thr: 0.6367 loss_db: 0.2295 2022/11/01 15:14:54 - mmengine - INFO - Epoch(train) [212][35/63] lr: 1.9802e-03 eta: 11:01:18 time: 0.5724 data_time: 0.0195 memory: 17620 loss: 2.3435 loss_prob: 1.4501 loss_thr: 0.6516 loss_db: 0.2418 2022/11/01 15:14:57 - mmengine - INFO - Epoch(train) [212][40/63] lr: 1.9802e-03 eta: 11:01:08 time: 0.5569 data_time: 0.0075 memory: 17620 loss: 2.2971 loss_prob: 1.4009 loss_thr: 0.6691 loss_db: 0.2272 2022/11/01 15:15:00 - mmengine - INFO - Epoch(train) [212][45/63] lr: 1.9802e-03 eta: 11:01:08 time: 0.5379 data_time: 0.0087 memory: 17620 loss: 2.1841 loss_prob: 1.3010 loss_thr: 0.6763 loss_db: 0.2067 2022/11/01 15:15:03 - mmengine - INFO - Epoch(train) [212][50/63] lr: 1.9802e-03 eta: 11:00:57 time: 0.5512 data_time: 0.0172 memory: 17620 loss: 2.4511 loss_prob: 1.5133 loss_thr: 0.6872 loss_db: 0.2505 2022/11/01 15:15:05 - mmengine - INFO - Epoch(train) [212][55/63] lr: 1.9802e-03 eta: 11:00:57 time: 0.5747 data_time: 0.0242 memory: 17620 loss: 2.5387 loss_prob: 1.5920 loss_thr: 0.6841 loss_db: 0.2625 2022/11/01 15:15:08 - mmengine - INFO - Epoch(train) [212][60/63] lr: 1.9802e-03 eta: 11:00:47 time: 0.5606 data_time: 0.0147 memory: 17620 loss: 2.5146 loss_prob: 1.5610 loss_thr: 0.6946 loss_db: 0.2591 2022/11/01 15:15:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:15:14 - mmengine - INFO - Epoch(train) [213][5/63] lr: 1.9784e-03 eta: 11:00:47 time: 0.7029 data_time: 0.2061 memory: 17620 loss: 2.4225 loss_prob: 1.4938 loss_thr: 0.6845 loss_db: 0.2442 2022/11/01 15:15:17 - mmengine - INFO - Epoch(train) [213][10/63] lr: 1.9784e-03 eta: 11:00:37 time: 0.7784 data_time: 0.2047 memory: 17620 loss: 2.4859 loss_prob: 1.5261 loss_thr: 0.7133 loss_db: 0.2465 2022/11/01 15:15:20 - mmengine - INFO - Epoch(train) [213][15/63] lr: 1.9784e-03 eta: 11:00:37 time: 0.5748 data_time: 0.0055 memory: 17620 loss: 2.4229 loss_prob: 1.4919 loss_thr: 0.6929 loss_db: 0.2381 2022/11/01 15:15:23 - mmengine - INFO - Epoch(train) [213][20/63] lr: 1.9784e-03 eta: 11:00:27 time: 0.5592 data_time: 0.0058 memory: 17620 loss: 2.1755 loss_prob: 1.3151 loss_thr: 0.6474 loss_db: 0.2131 2022/11/01 15:15:26 - mmengine - INFO - Epoch(train) [213][25/63] lr: 1.9784e-03 eta: 11:00:27 time: 0.5909 data_time: 0.0311 memory: 17620 loss: 2.2495 loss_prob: 1.3743 loss_thr: 0.6508 loss_db: 0.2244 2022/11/01 15:15:29 - mmengine - INFO - Epoch(train) [213][30/63] lr: 1.9784e-03 eta: 11:00:18 time: 0.5788 data_time: 0.0333 memory: 17620 loss: 2.3018 loss_prob: 1.4244 loss_thr: 0.6503 loss_db: 0.2271 2022/11/01 15:15:32 - mmengine - INFO - Epoch(train) [213][35/63] lr: 1.9784e-03 eta: 11:00:18 time: 0.6138 data_time: 0.0114 memory: 17620 loss: 2.5175 loss_prob: 1.5791 loss_thr: 0.6850 loss_db: 0.2534 2022/11/01 15:15:35 - mmengine - INFO - Epoch(train) [213][40/63] lr: 1.9784e-03 eta: 11:00:10 time: 0.6152 data_time: 0.0114 memory: 17620 loss: 2.3912 loss_prob: 1.4880 loss_thr: 0.6636 loss_db: 0.2396 2022/11/01 15:15:38 - mmengine - INFO - Epoch(train) [213][45/63] lr: 1.9784e-03 eta: 11:00:10 time: 0.5513 data_time: 0.0095 memory: 17620 loss: 2.2135 loss_prob: 1.3524 loss_thr: 0.6481 loss_db: 0.2130 2022/11/01 15:15:40 - mmengine - INFO - Epoch(train) [213][50/63] lr: 1.9784e-03 eta: 11:00:01 time: 0.5640 data_time: 0.0234 memory: 17620 loss: 2.2377 loss_prob: 1.3602 loss_thr: 0.6619 loss_db: 0.2156 2022/11/01 15:15:43 - mmengine - INFO - Epoch(train) [213][55/63] lr: 1.9784e-03 eta: 11:00:01 time: 0.5799 data_time: 0.0245 memory: 17620 loss: 2.1232 loss_prob: 1.2720 loss_thr: 0.6474 loss_db: 0.2037 2022/11/01 15:15:46 - mmengine - INFO - Epoch(train) [213][60/63] lr: 1.9784e-03 eta: 10:59:50 time: 0.5478 data_time: 0.0080 memory: 17620 loss: 2.0263 loss_prob: 1.1981 loss_thr: 0.6367 loss_db: 0.1915 2022/11/01 15:15:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:15:52 - mmengine - INFO - Epoch(train) [214][5/63] lr: 1.9766e-03 eta: 10:59:50 time: 0.7014 data_time: 0.1985 memory: 17620 loss: 1.9888 loss_prob: 1.1656 loss_thr: 0.6392 loss_db: 0.1840 2022/11/01 15:15:55 - mmengine - INFO - Epoch(train) [214][10/63] lr: 1.9766e-03 eta: 10:59:39 time: 0.7553 data_time: 0.2053 memory: 17620 loss: 2.0693 loss_prob: 1.2440 loss_thr: 0.6286 loss_db: 0.1967 2022/11/01 15:15:57 - mmengine - INFO - Epoch(train) [214][15/63] lr: 1.9766e-03 eta: 10:59:39 time: 0.5532 data_time: 0.0116 memory: 17620 loss: 2.1063 loss_prob: 1.2804 loss_thr: 0.6207 loss_db: 0.2052 2022/11/01 15:16:00 - mmengine - INFO - Epoch(train) [214][20/63] lr: 1.9766e-03 eta: 10:59:27 time: 0.5270 data_time: 0.0076 memory: 17620 loss: 2.1941 loss_prob: 1.3315 loss_thr: 0.6469 loss_db: 0.2157 2022/11/01 15:16:03 - mmengine - INFO - Epoch(train) [214][25/63] lr: 1.9766e-03 eta: 10:59:27 time: 0.5724 data_time: 0.0231 memory: 17620 loss: 2.3002 loss_prob: 1.3997 loss_thr: 0.6742 loss_db: 0.2263 2022/11/01 15:16:06 - mmengine - INFO - Epoch(train) [214][30/63] lr: 1.9766e-03 eta: 10:59:20 time: 0.6204 data_time: 0.0327 memory: 17620 loss: 2.1655 loss_prob: 1.2979 loss_thr: 0.6602 loss_db: 0.2074 2022/11/01 15:16:09 - mmengine - INFO - Epoch(train) [214][35/63] lr: 1.9766e-03 eta: 10:59:20 time: 0.6018 data_time: 0.0207 memory: 17620 loss: 2.2410 loss_prob: 1.3457 loss_thr: 0.6786 loss_db: 0.2167 2022/11/01 15:16:12 - mmengine - INFO - Epoch(train) [214][40/63] lr: 1.9766e-03 eta: 10:59:11 time: 0.5852 data_time: 0.0084 memory: 17620 loss: 2.3375 loss_prob: 1.4326 loss_thr: 0.6719 loss_db: 0.2330 2022/11/01 15:16:16 - mmengine - INFO - Epoch(train) [214][45/63] lr: 1.9766e-03 eta: 10:59:11 time: 0.6417 data_time: 0.0060 memory: 17620 loss: 2.6254 loss_prob: 1.6599 loss_thr: 0.6912 loss_db: 0.2743 2022/11/01 15:16:19 - mmengine - INFO - Epoch(train) [214][50/63] lr: 1.9766e-03 eta: 10:59:07 time: 0.6759 data_time: 0.0242 memory: 17620 loss: 2.6308 loss_prob: 1.6630 loss_thr: 0.6916 loss_db: 0.2762 2022/11/01 15:16:22 - mmengine - INFO - Epoch(train) [214][55/63] lr: 1.9766e-03 eta: 10:59:07 time: 0.6053 data_time: 0.0246 memory: 17620 loss: 2.3311 loss_prob: 1.4119 loss_thr: 0.6856 loss_db: 0.2337 2022/11/01 15:16:24 - mmengine - INFO - Epoch(train) [214][60/63] lr: 1.9766e-03 eta: 10:58:57 time: 0.5597 data_time: 0.0078 memory: 17620 loss: 2.2504 loss_prob: 1.3484 loss_thr: 0.6815 loss_db: 0.2204 2022/11/01 15:16:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:16:32 - mmengine - INFO - Epoch(train) [215][5/63] lr: 1.9748e-03 eta: 10:58:57 time: 0.9115 data_time: 0.2355 memory: 17620 loss: 2.2768 loss_prob: 1.3808 loss_thr: 0.6780 loss_db: 0.2180 2022/11/01 15:16:35 - mmengine - INFO - Epoch(train) [215][10/63] lr: 1.9748e-03 eta: 10:58:53 time: 0.9237 data_time: 0.2368 memory: 17620 loss: 2.0647 loss_prob: 1.2448 loss_thr: 0.6208 loss_db: 0.1990 2022/11/01 15:16:38 - mmengine - INFO - Epoch(train) [215][15/63] lr: 1.9748e-03 eta: 10:58:53 time: 0.5802 data_time: 0.0078 memory: 17620 loss: 2.0283 loss_prob: 1.2108 loss_thr: 0.6220 loss_db: 0.1955 2022/11/01 15:16:41 - mmengine - INFO - Epoch(train) [215][20/63] lr: 1.9748e-03 eta: 10:58:43 time: 0.5664 data_time: 0.0061 memory: 17620 loss: 2.0857 loss_prob: 1.2341 loss_thr: 0.6569 loss_db: 0.1948 2022/11/01 15:16:44 - mmengine - INFO - Epoch(train) [215][25/63] lr: 1.9748e-03 eta: 10:58:43 time: 0.6008 data_time: 0.0429 memory: 17620 loss: 2.0468 loss_prob: 1.1968 loss_thr: 0.6613 loss_db: 0.1887 2022/11/01 15:16:47 - mmengine - INFO - Epoch(train) [215][30/63] lr: 1.9748e-03 eta: 10:58:37 time: 0.6259 data_time: 0.0426 memory: 17620 loss: 2.1312 loss_prob: 1.2515 loss_thr: 0.6771 loss_db: 0.2026 2022/11/01 15:16:50 - mmengine - INFO - Epoch(train) [215][35/63] lr: 1.9748e-03 eta: 10:58:37 time: 0.5818 data_time: 0.0048 memory: 17620 loss: 2.2726 loss_prob: 1.3654 loss_thr: 0.6868 loss_db: 0.2204 2022/11/01 15:16:53 - mmengine - INFO - Epoch(train) [215][40/63] lr: 1.9748e-03 eta: 10:58:27 time: 0.5756 data_time: 0.0066 memory: 17620 loss: 2.2998 loss_prob: 1.3912 loss_thr: 0.6832 loss_db: 0.2254 2022/11/01 15:16:56 - mmengine - INFO - Epoch(train) [215][45/63] lr: 1.9748e-03 eta: 10:58:27 time: 0.5984 data_time: 0.0067 memory: 17620 loss: 2.2371 loss_prob: 1.3507 loss_thr: 0.6658 loss_db: 0.2206 2022/11/01 15:16:59 - mmengine - INFO - Epoch(train) [215][50/63] lr: 1.9748e-03 eta: 10:58:21 time: 0.6357 data_time: 0.0250 memory: 17620 loss: 2.1534 loss_prob: 1.2877 loss_thr: 0.6589 loss_db: 0.2068 2022/11/01 15:17:03 - mmengine - INFO - Epoch(train) [215][55/63] lr: 1.9748e-03 eta: 10:58:21 time: 0.6528 data_time: 0.0265 memory: 17620 loss: 2.4351 loss_prob: 1.4984 loss_thr: 0.6972 loss_db: 0.2395 2022/11/01 15:17:05 - mmengine - INFO - Epoch(train) [215][60/63] lr: 1.9748e-03 eta: 10:58:13 time: 0.6018 data_time: 0.0075 memory: 17620 loss: 2.4990 loss_prob: 1.5675 loss_thr: 0.6835 loss_db: 0.2480 2022/11/01 15:17:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:17:13 - mmengine - INFO - Epoch(train) [216][5/63] lr: 1.9730e-03 eta: 10:58:13 time: 0.8194 data_time: 0.1785 memory: 17620 loss: 2.3162 loss_prob: 1.4363 loss_thr: 0.6528 loss_db: 0.2270 2022/11/01 15:17:16 - mmengine - INFO - Epoch(train) [216][10/63] lr: 1.9730e-03 eta: 10:58:08 time: 0.8956 data_time: 0.1812 memory: 17620 loss: 2.2245 loss_prob: 1.3607 loss_thr: 0.6480 loss_db: 0.2158 2022/11/01 15:17:19 - mmengine - INFO - Epoch(train) [216][15/63] lr: 1.9730e-03 eta: 10:58:08 time: 0.6319 data_time: 0.0094 memory: 17620 loss: 2.0517 loss_prob: 1.2249 loss_thr: 0.6299 loss_db: 0.1969 2022/11/01 15:17:22 - mmengine - INFO - Epoch(train) [216][20/63] lr: 1.9730e-03 eta: 10:57:59 time: 0.5798 data_time: 0.0046 memory: 17620 loss: 2.0353 loss_prob: 1.2217 loss_thr: 0.6183 loss_db: 0.1952 2022/11/01 15:17:25 - mmengine - INFO - Epoch(train) [216][25/63] lr: 1.9730e-03 eta: 10:57:59 time: 0.5818 data_time: 0.0147 memory: 17620 loss: 2.0678 loss_prob: 1.2247 loss_thr: 0.6494 loss_db: 0.1937 2022/11/01 15:17:28 - mmengine - INFO - Epoch(train) [216][30/63] lr: 1.9730e-03 eta: 10:57:51 time: 0.6081 data_time: 0.0360 memory: 17620 loss: 2.0757 loss_prob: 1.2202 loss_thr: 0.6625 loss_db: 0.1930 2022/11/01 15:17:30 - mmengine - INFO - Epoch(train) [216][35/63] lr: 1.9730e-03 eta: 10:57:51 time: 0.5803 data_time: 0.0262 memory: 17620 loss: 2.0932 loss_prob: 1.2501 loss_thr: 0.6452 loss_db: 0.1979 2022/11/01 15:17:33 - mmengine - INFO - Epoch(train) [216][40/63] lr: 1.9730e-03 eta: 10:57:41 time: 0.5452 data_time: 0.0049 memory: 17620 loss: 2.0781 loss_prob: 1.2427 loss_thr: 0.6376 loss_db: 0.1978 2022/11/01 15:17:36 - mmengine - INFO - Epoch(train) [216][45/63] lr: 1.9730e-03 eta: 10:57:41 time: 0.5474 data_time: 0.0059 memory: 17620 loss: 2.1715 loss_prob: 1.3171 loss_thr: 0.6376 loss_db: 0.2168 2022/11/01 15:17:39 - mmengine - INFO - Epoch(train) [216][50/63] lr: 1.9730e-03 eta: 10:57:32 time: 0.5748 data_time: 0.0154 memory: 17620 loss: 2.2587 loss_prob: 1.3942 loss_thr: 0.6376 loss_db: 0.2270 2022/11/01 15:17:42 - mmengine - INFO - Epoch(train) [216][55/63] lr: 1.9730e-03 eta: 10:57:32 time: 0.5760 data_time: 0.0225 memory: 17620 loss: 2.3320 loss_prob: 1.4296 loss_thr: 0.6743 loss_db: 0.2281 2022/11/01 15:17:45 - mmengine - INFO - Epoch(train) [216][60/63] lr: 1.9730e-03 eta: 10:57:24 time: 0.6000 data_time: 0.0131 memory: 17620 loss: 2.3399 loss_prob: 1.4171 loss_thr: 0.6914 loss_db: 0.2314 2022/11/01 15:17:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:17:51 - mmengine - INFO - Epoch(train) [217][5/63] lr: 1.9711e-03 eta: 10:57:24 time: 0.7294 data_time: 0.1870 memory: 17620 loss: 2.3139 loss_prob: 1.4018 loss_thr: 0.6876 loss_db: 0.2245 2022/11/01 15:17:54 - mmengine - INFO - Epoch(train) [217][10/63] lr: 1.9711e-03 eta: 10:57:11 time: 0.7380 data_time: 0.1930 memory: 17620 loss: 2.3377 loss_prob: 1.4169 loss_thr: 0.6922 loss_db: 0.2286 2022/11/01 15:17:57 - mmengine - INFO - Epoch(train) [217][15/63] lr: 1.9711e-03 eta: 10:57:11 time: 0.5639 data_time: 0.0144 memory: 17620 loss: 2.3541 loss_prob: 1.4450 loss_thr: 0.6739 loss_db: 0.2352 2022/11/01 15:18:00 - mmengine - INFO - Epoch(train) [217][20/63] lr: 1.9711e-03 eta: 10:57:04 time: 0.6089 data_time: 0.0087 memory: 17620 loss: 2.5577 loss_prob: 1.5965 loss_thr: 0.7005 loss_db: 0.2607 2022/11/01 15:18:03 - mmengine - INFO - Epoch(train) [217][25/63] lr: 1.9711e-03 eta: 10:57:04 time: 0.6078 data_time: 0.0093 memory: 17620 loss: 2.2023 loss_prob: 1.3453 loss_thr: 0.6416 loss_db: 0.2154 2022/11/01 15:18:06 - mmengine - INFO - Epoch(train) [217][30/63] lr: 1.9711e-03 eta: 10:56:55 time: 0.5912 data_time: 0.0270 memory: 17620 loss: 2.0328 loss_prob: 1.2113 loss_thr: 0.6285 loss_db: 0.1930 2022/11/01 15:18:09 - mmengine - INFO - Epoch(train) [217][35/63] lr: 1.9711e-03 eta: 10:56:55 time: 0.5974 data_time: 0.0323 memory: 17620 loss: 2.3017 loss_prob: 1.3976 loss_thr: 0.6786 loss_db: 0.2255 2022/11/01 15:18:11 - mmengine - INFO - Epoch(train) [217][40/63] lr: 1.9711e-03 eta: 10:56:46 time: 0.5786 data_time: 0.0142 memory: 17620 loss: 2.3085 loss_prob: 1.4157 loss_thr: 0.6620 loss_db: 0.2308 2022/11/01 15:18:14 - mmengine - INFO - Epoch(train) [217][45/63] lr: 1.9711e-03 eta: 10:56:46 time: 0.5423 data_time: 0.0069 memory: 17620 loss: 2.2412 loss_prob: 1.3543 loss_thr: 0.6664 loss_db: 0.2204 2022/11/01 15:18:17 - mmengine - INFO - Epoch(train) [217][50/63] lr: 1.9711e-03 eta: 10:56:34 time: 0.5145 data_time: 0.0120 memory: 17620 loss: 2.1774 loss_prob: 1.2959 loss_thr: 0.6745 loss_db: 0.2069 2022/11/01 15:18:20 - mmengine - INFO - Epoch(train) [217][55/63] lr: 1.9711e-03 eta: 10:56:34 time: 0.5496 data_time: 0.0185 memory: 17620 loss: 2.0684 loss_prob: 1.2315 loss_thr: 0.6403 loss_db: 0.1967 2022/11/01 15:18:22 - mmengine - INFO - Epoch(train) [217][60/63] lr: 1.9711e-03 eta: 10:56:25 time: 0.5682 data_time: 0.0150 memory: 17620 loss: 2.0932 loss_prob: 1.2571 loss_thr: 0.6335 loss_db: 0.2026 2022/11/01 15:18:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:18:28 - mmengine - INFO - Epoch(train) [218][5/63] lr: 1.9693e-03 eta: 10:56:25 time: 0.6936 data_time: 0.1687 memory: 17620 loss: 2.2634 loss_prob: 1.3848 loss_thr: 0.6583 loss_db: 0.2203 2022/11/01 15:18:31 - mmengine - INFO - Epoch(train) [218][10/63] lr: 1.9693e-03 eta: 10:56:13 time: 0.7495 data_time: 0.1810 memory: 17620 loss: 2.1761 loss_prob: 1.3103 loss_thr: 0.6560 loss_db: 0.2099 2022/11/01 15:18:34 - mmengine - INFO - Epoch(train) [218][15/63] lr: 1.9693e-03 eta: 10:56:13 time: 0.5755 data_time: 0.0210 memory: 17620 loss: 2.1891 loss_prob: 1.3196 loss_thr: 0.6509 loss_db: 0.2186 2022/11/01 15:18:37 - mmengine - INFO - Epoch(train) [218][20/63] lr: 1.9693e-03 eta: 10:56:04 time: 0.5661 data_time: 0.0068 memory: 17620 loss: 2.2659 loss_prob: 1.3662 loss_thr: 0.6751 loss_db: 0.2246 2022/11/01 15:18:40 - mmengine - INFO - Epoch(train) [218][25/63] lr: 1.9693e-03 eta: 10:56:04 time: 0.5904 data_time: 0.0078 memory: 17620 loss: 2.2444 loss_prob: 1.3429 loss_thr: 0.6829 loss_db: 0.2185 2022/11/01 15:18:43 - mmengine - INFO - Epoch(train) [218][30/63] lr: 1.9693e-03 eta: 10:55:57 time: 0.6183 data_time: 0.0205 memory: 17620 loss: 2.1108 loss_prob: 1.2565 loss_thr: 0.6468 loss_db: 0.2076 2022/11/01 15:18:46 - mmengine - INFO - Epoch(train) [218][35/63] lr: 1.9693e-03 eta: 10:55:57 time: 0.6385 data_time: 0.0333 memory: 17620 loss: 2.0285 loss_prob: 1.2019 loss_thr: 0.6309 loss_db: 0.1957 2022/11/01 15:18:49 - mmengine - INFO - Epoch(train) [218][40/63] lr: 1.9693e-03 eta: 10:55:50 time: 0.6245 data_time: 0.0204 memory: 17620 loss: 2.2023 loss_prob: 1.3240 loss_thr: 0.6632 loss_db: 0.2151 2022/11/01 15:18:52 - mmengine - INFO - Epoch(train) [218][45/63] lr: 1.9693e-03 eta: 10:55:50 time: 0.5948 data_time: 0.0071 memory: 17620 loss: 2.5052 loss_prob: 1.5417 loss_thr: 0.7080 loss_db: 0.2555 2022/11/01 15:18:55 - mmengine - INFO - Epoch(train) [218][50/63] lr: 1.9693e-03 eta: 10:55:41 time: 0.5926 data_time: 0.0139 memory: 17620 loss: 2.3948 loss_prob: 1.4590 loss_thr: 0.6920 loss_db: 0.2439 2022/11/01 15:18:58 - mmengine - INFO - Epoch(train) [218][55/63] lr: 1.9693e-03 eta: 10:55:41 time: 0.6369 data_time: 0.0213 memory: 17620 loss: 2.0984 loss_prob: 1.2524 loss_thr: 0.6389 loss_db: 0.2071 2022/11/01 15:19:02 - mmengine - INFO - Epoch(train) [218][60/63] lr: 1.9693e-03 eta: 10:55:35 time: 0.6330 data_time: 0.0166 memory: 17620 loss: 2.1136 loss_prob: 1.2747 loss_thr: 0.6312 loss_db: 0.2077 2022/11/01 15:19:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:19:09 - mmengine - INFO - Epoch(train) [219][5/63] lr: 1.9675e-03 eta: 10:55:35 time: 0.8625 data_time: 0.2051 memory: 17620 loss: 2.2643 loss_prob: 1.3745 loss_thr: 0.6708 loss_db: 0.2190 2022/11/01 15:19:12 - mmengine - INFO - Epoch(train) [219][10/63] lr: 1.9675e-03 eta: 10:55:27 time: 0.8464 data_time: 0.2013 memory: 17620 loss: 2.1645 loss_prob: 1.2979 loss_thr: 0.6605 loss_db: 0.2061 2022/11/01 15:19:15 - mmengine - INFO - Epoch(train) [219][15/63] lr: 1.9675e-03 eta: 10:55:27 time: 0.6464 data_time: 0.0174 memory: 17620 loss: 2.1675 loss_prob: 1.3106 loss_thr: 0.6504 loss_db: 0.2064 2022/11/01 15:19:19 - mmengine - INFO - Epoch(train) [219][20/63] lr: 1.9675e-03 eta: 10:55:26 time: 0.7431 data_time: 0.0174 memory: 17620 loss: 2.3369 loss_prob: 1.4411 loss_thr: 0.6619 loss_db: 0.2340 2022/11/01 15:19:22 - mmengine - INFO - Epoch(train) [219][25/63] lr: 1.9675e-03 eta: 10:55:26 time: 0.6918 data_time: 0.0227 memory: 17620 loss: 2.2437 loss_prob: 1.3501 loss_thr: 0.6705 loss_db: 0.2232 2022/11/01 15:19:25 - mmengine - INFO - Epoch(train) [219][30/63] lr: 1.9675e-03 eta: 10:55:19 time: 0.6301 data_time: 0.0314 memory: 17620 loss: 2.0650 loss_prob: 1.2200 loss_thr: 0.6484 loss_db: 0.1966 2022/11/01 15:19:29 - mmengine - INFO - Epoch(train) [219][35/63] lr: 1.9675e-03 eta: 10:55:19 time: 0.6125 data_time: 0.0141 memory: 17620 loss: 2.0242 loss_prob: 1.2096 loss_thr: 0.6207 loss_db: 0.1939 2022/11/01 15:19:32 - mmengine - INFO - Epoch(train) [219][40/63] lr: 1.9675e-03 eta: 10:55:12 time: 0.6183 data_time: 0.0118 memory: 17620 loss: 1.9975 loss_prob: 1.1817 loss_thr: 0.6277 loss_db: 0.1881 2022/11/01 15:19:34 - mmengine - INFO - Epoch(train) [219][45/63] lr: 1.9675e-03 eta: 10:55:12 time: 0.5870 data_time: 0.0113 memory: 17620 loss: 2.1029 loss_prob: 1.2668 loss_thr: 0.6327 loss_db: 0.2034 2022/11/01 15:19:38 - mmengine - INFO - Epoch(train) [219][50/63] lr: 1.9675e-03 eta: 10:55:04 time: 0.6046 data_time: 0.0170 memory: 17620 loss: 2.1545 loss_prob: 1.3106 loss_thr: 0.6303 loss_db: 0.2136 2022/11/01 15:19:40 - mmengine - INFO - Epoch(train) [219][55/63] lr: 1.9675e-03 eta: 10:55:04 time: 0.5926 data_time: 0.0233 memory: 17620 loss: 2.1237 loss_prob: 1.2692 loss_thr: 0.6467 loss_db: 0.2077 2022/11/01 15:19:43 - mmengine - INFO - Epoch(train) [219][60/63] lr: 1.9675e-03 eta: 10:54:53 time: 0.5288 data_time: 0.0133 memory: 17620 loss: 2.2797 loss_prob: 1.3806 loss_thr: 0.6722 loss_db: 0.2269 2022/11/01 15:19:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:19:49 - mmengine - INFO - Epoch(train) [220][5/63] lr: 1.9657e-03 eta: 10:54:53 time: 0.7494 data_time: 0.2084 memory: 17620 loss: 2.3567 loss_prob: 1.4142 loss_thr: 0.7150 loss_db: 0.2275 2022/11/01 15:19:52 - mmengine - INFO - Epoch(train) [220][10/63] lr: 1.9657e-03 eta: 10:54:44 time: 0.7968 data_time: 0.2063 memory: 17620 loss: 2.2854 loss_prob: 1.3930 loss_thr: 0.6719 loss_db: 0.2205 2022/11/01 15:19:55 - mmengine - INFO - Epoch(train) [220][15/63] lr: 1.9657e-03 eta: 10:54:44 time: 0.5482 data_time: 0.0063 memory: 17620 loss: 2.2836 loss_prob: 1.4023 loss_thr: 0.6581 loss_db: 0.2232 2022/11/01 15:19:57 - mmengine - INFO - Epoch(train) [220][20/63] lr: 1.9657e-03 eta: 10:54:32 time: 0.5151 data_time: 0.0062 memory: 17620 loss: 2.0978 loss_prob: 1.2516 loss_thr: 0.6404 loss_db: 0.2058 2022/11/01 15:20:00 - mmengine - INFO - Epoch(train) [220][25/63] lr: 1.9657e-03 eta: 10:54:32 time: 0.5511 data_time: 0.0260 memory: 17620 loss: 2.2507 loss_prob: 1.3752 loss_thr: 0.6504 loss_db: 0.2250 2022/11/01 15:20:03 - mmengine - INFO - Epoch(train) [220][30/63] lr: 1.9657e-03 eta: 10:54:23 time: 0.5722 data_time: 0.0369 memory: 17620 loss: 2.2494 loss_prob: 1.3847 loss_thr: 0.6392 loss_db: 0.2255 2022/11/01 15:20:06 - mmengine - INFO - Epoch(train) [220][35/63] lr: 1.9657e-03 eta: 10:54:23 time: 0.5518 data_time: 0.0164 memory: 17620 loss: 2.0860 loss_prob: 1.2384 loss_thr: 0.6493 loss_db: 0.1982 2022/11/01 15:20:09 - mmengine - INFO - Epoch(train) [220][40/63] lr: 1.9657e-03 eta: 10:54:12 time: 0.5390 data_time: 0.0067 memory: 17620 loss: 2.0735 loss_prob: 1.2163 loss_thr: 0.6649 loss_db: 0.1923 2022/11/01 15:20:11 - mmengine - INFO - Epoch(train) [220][45/63] lr: 1.9657e-03 eta: 10:54:12 time: 0.5363 data_time: 0.0082 memory: 17620 loss: 2.0756 loss_prob: 1.2297 loss_thr: 0.6479 loss_db: 0.1979 2022/11/01 15:20:14 - mmengine - INFO - Epoch(train) [220][50/63] lr: 1.9657e-03 eta: 10:54:03 time: 0.5694 data_time: 0.0253 memory: 17620 loss: 2.0244 loss_prob: 1.1917 loss_thr: 0.6408 loss_db: 0.1918 2022/11/01 15:20:17 - mmengine - INFO - Epoch(train) [220][55/63] lr: 1.9657e-03 eta: 10:54:03 time: 0.5676 data_time: 0.0245 memory: 17620 loss: 2.1029 loss_prob: 1.2695 loss_thr: 0.6339 loss_db: 0.1995 2022/11/01 15:20:20 - mmengine - INFO - Epoch(train) [220][60/63] lr: 1.9657e-03 eta: 10:53:53 time: 0.5484 data_time: 0.0062 memory: 17620 loss: 2.0973 loss_prob: 1.2685 loss_thr: 0.6291 loss_db: 0.1997 2022/11/01 15:20:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:20:21 - mmengine - INFO - Saving checkpoint at 220 epochs 2022/11/01 15:20:28 - mmengine - INFO - Epoch(val) [220][5/32] eta: 10:53:53 time: 0.5762 data_time: 0.0835 memory: 17620 2022/11/01 15:20:31 - mmengine - INFO - Epoch(val) [220][10/32] eta: 0:00:14 time: 0.6569 data_time: 0.1179 memory: 15725 2022/11/01 15:20:34 - mmengine - INFO - Epoch(val) [220][15/32] eta: 0:00:14 time: 0.5689 data_time: 0.0496 memory: 15725 2022/11/01 15:20:37 - mmengine - INFO - Epoch(val) [220][20/32] eta: 0:00:06 time: 0.5702 data_time: 0.0566 memory: 15725 2022/11/01 15:20:40 - mmengine - INFO - Epoch(val) [220][25/32] eta: 0:00:06 time: 0.5775 data_time: 0.0559 memory: 15725 2022/11/01 15:20:42 - mmengine - INFO - Epoch(val) [220][30/32] eta: 0:00:01 time: 0.5437 data_time: 0.0203 memory: 15725 2022/11/01 15:20:43 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8161, precision: 0.7517, hmean: 0.7825 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8151, precision: 0.8336, hmean: 0.8242 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8108, precision: 0.8757, hmean: 0.8420 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7857, precision: 0.9092, hmean: 0.8430 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7130, precision: 0.9439, hmean: 0.8124 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2191, precision: 0.9785, hmean: 0.3580 2022/11/01 15:20:43 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 15:20:43 - mmengine - INFO - Epoch(val) [220][32/32] icdar/precision: 0.9092 icdar/recall: 0.7857 icdar/hmean: 0.8430 2022/11/01 15:20:48 - mmengine - INFO - Epoch(train) [221][5/63] lr: 1.9639e-03 eta: 0:00:01 time: 0.7371 data_time: 0.2017 memory: 17620 loss: 1.9512 loss_prob: 1.1564 loss_thr: 0.6099 loss_db: 0.1849 2022/11/01 15:20:51 - mmengine - INFO - Epoch(train) [221][10/63] lr: 1.9639e-03 eta: 10:53:42 time: 0.7657 data_time: 0.2017 memory: 17620 loss: 1.8971 loss_prob: 1.1060 loss_thr: 0.6099 loss_db: 0.1812 2022/11/01 15:20:54 - mmengine - INFO - Epoch(train) [221][15/63] lr: 1.9639e-03 eta: 10:53:42 time: 0.5679 data_time: 0.0061 memory: 17620 loss: 1.9775 loss_prob: 1.1455 loss_thr: 0.6449 loss_db: 0.1870 2022/11/01 15:20:56 - mmengine - INFO - Epoch(train) [221][20/63] lr: 1.9639e-03 eta: 10:53:31 time: 0.5471 data_time: 0.0050 memory: 17620 loss: 1.9614 loss_prob: 1.1333 loss_thr: 0.6478 loss_db: 0.1802 2022/11/01 15:21:00 - mmengine - INFO - Epoch(train) [221][25/63] lr: 1.9639e-03 eta: 10:53:31 time: 0.5928 data_time: 0.0340 memory: 17620 loss: 2.0453 loss_prob: 1.2194 loss_thr: 0.6352 loss_db: 0.1907 2022/11/01 15:21:03 - mmengine - INFO - Epoch(train) [221][30/63] lr: 1.9639e-03 eta: 10:53:28 time: 0.7125 data_time: 0.0351 memory: 17620 loss: 2.1720 loss_prob: 1.3252 loss_thr: 0.6373 loss_db: 0.2095 2022/11/01 15:21:06 - mmengine - INFO - Epoch(train) [221][35/63] lr: 1.9639e-03 eta: 10:53:28 time: 0.6759 data_time: 0.0058 memory: 17620 loss: 2.2303 loss_prob: 1.3692 loss_thr: 0.6442 loss_db: 0.2169 2022/11/01 15:21:09 - mmengine - INFO - Epoch(train) [221][40/63] lr: 1.9639e-03 eta: 10:53:20 time: 0.5954 data_time: 0.0051 memory: 17620 loss: 2.2729 loss_prob: 1.4116 loss_thr: 0.6420 loss_db: 0.2193 2022/11/01 15:21:13 - mmengine - INFO - Epoch(train) [221][45/63] lr: 1.9639e-03 eta: 10:53:20 time: 0.6416 data_time: 0.0054 memory: 17620 loss: 2.1570 loss_prob: 1.3172 loss_thr: 0.6320 loss_db: 0.2078 2022/11/01 15:21:16 - mmengine - INFO - Epoch(train) [221][50/63] lr: 1.9639e-03 eta: 10:53:15 time: 0.6583 data_time: 0.0240 memory: 17620 loss: 2.1773 loss_prob: 1.3201 loss_thr: 0.6427 loss_db: 0.2145 2022/11/01 15:21:19 - mmengine - INFO - Epoch(train) [221][55/63] lr: 1.9639e-03 eta: 10:53:15 time: 0.5971 data_time: 0.0245 memory: 17620 loss: 2.2984 loss_prob: 1.4181 loss_thr: 0.6525 loss_db: 0.2278 2022/11/01 15:21:22 - mmengine - INFO - Epoch(train) [221][60/63] lr: 1.9639e-03 eta: 10:53:05 time: 0.5569 data_time: 0.0063 memory: 17620 loss: 2.2402 loss_prob: 1.3781 loss_thr: 0.6407 loss_db: 0.2214 2022/11/01 15:21:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:21:29 - mmengine - INFO - Epoch(train) [222][5/63] lr: 1.9621e-03 eta: 10:53:05 time: 0.8586 data_time: 0.2444 memory: 17620 loss: 2.0454 loss_prob: 1.2083 loss_thr: 0.6400 loss_db: 0.1971 2022/11/01 15:21:32 - mmengine - INFO - Epoch(train) [222][10/63] lr: 1.9621e-03 eta: 10:53:01 time: 0.9151 data_time: 0.2429 memory: 17620 loss: 2.1137 loss_prob: 1.2581 loss_thr: 0.6517 loss_db: 0.2039 2022/11/01 15:21:35 - mmengine - INFO - Epoch(train) [222][15/63] lr: 1.9621e-03 eta: 10:53:01 time: 0.5927 data_time: 0.0075 memory: 17620 loss: 2.2223 loss_prob: 1.3408 loss_thr: 0.6574 loss_db: 0.2241 2022/11/01 15:21:38 - mmengine - INFO - Epoch(train) [222][20/63] lr: 1.9621e-03 eta: 10:52:52 time: 0.5907 data_time: 0.0069 memory: 17620 loss: 2.3917 loss_prob: 1.4829 loss_thr: 0.6646 loss_db: 0.2442 2022/11/01 15:21:41 - mmengine - INFO - Epoch(train) [222][25/63] lr: 1.9621e-03 eta: 10:52:52 time: 0.6121 data_time: 0.0302 memory: 17620 loss: 2.4774 loss_prob: 1.5375 loss_thr: 0.6916 loss_db: 0.2484 2022/11/01 15:21:44 - mmengine - INFO - Epoch(train) [222][30/63] lr: 1.9621e-03 eta: 10:52:46 time: 0.6274 data_time: 0.0461 memory: 17620 loss: 2.4420 loss_prob: 1.5017 loss_thr: 0.6897 loss_db: 0.2506 2022/11/01 15:21:47 - mmengine - INFO - Epoch(train) [222][35/63] lr: 1.9621e-03 eta: 10:52:46 time: 0.6122 data_time: 0.0208 memory: 17620 loss: 2.3171 loss_prob: 1.4288 loss_thr: 0.6531 loss_db: 0.2352 2022/11/01 15:21:51 - mmengine - INFO - Epoch(train) [222][40/63] lr: 1.9621e-03 eta: 10:52:40 time: 0.6501 data_time: 0.0063 memory: 17620 loss: 2.1889 loss_prob: 1.3402 loss_thr: 0.6329 loss_db: 0.2158 2022/11/01 15:21:54 - mmengine - INFO - Epoch(train) [222][45/63] lr: 1.9621e-03 eta: 10:52:40 time: 0.6483 data_time: 0.0066 memory: 17620 loss: 2.2868 loss_prob: 1.4035 loss_thr: 0.6592 loss_db: 0.2240 2022/11/01 15:21:57 - mmengine - INFO - Epoch(train) [222][50/63] lr: 1.9621e-03 eta: 10:52:32 time: 0.5867 data_time: 0.0173 memory: 17620 loss: 2.4086 loss_prob: 1.4842 loss_thr: 0.6900 loss_db: 0.2345 2022/11/01 15:21:59 - mmengine - INFO - Epoch(train) [222][55/63] lr: 1.9621e-03 eta: 10:52:32 time: 0.5830 data_time: 0.0255 memory: 17620 loss: 2.4855 loss_prob: 1.5433 loss_thr: 0.6983 loss_db: 0.2440 2022/11/01 15:22:02 - mmengine - INFO - Epoch(train) [222][60/63] lr: 1.9621e-03 eta: 10:52:21 time: 0.5509 data_time: 0.0130 memory: 17620 loss: 2.2970 loss_prob: 1.3990 loss_thr: 0.6739 loss_db: 0.2241 2022/11/01 15:22:03 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:22:09 - mmengine - INFO - Epoch(train) [223][5/63] lr: 1.9603e-03 eta: 10:52:21 time: 0.7519 data_time: 0.1902 memory: 17620 loss: 2.2017 loss_prob: 1.3033 loss_thr: 0.6822 loss_db: 0.2162 2022/11/01 15:22:11 - mmengine - INFO - Epoch(train) [223][10/63] lr: 1.9603e-03 eta: 10:52:11 time: 0.7727 data_time: 0.1927 memory: 17620 loss: 2.2488 loss_prob: 1.3417 loss_thr: 0.6845 loss_db: 0.2226 2022/11/01 15:22:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:22:14 - mmengine - INFO - Epoch(train) [223][15/63] lr: 1.9603e-03 eta: 10:52:11 time: 0.5380 data_time: 0.0132 memory: 17620 loss: 2.1185 loss_prob: 1.2677 loss_thr: 0.6474 loss_db: 0.2034 2022/11/01 15:22:17 - mmengine - INFO - Epoch(train) [223][20/63] lr: 1.9603e-03 eta: 10:52:02 time: 0.5689 data_time: 0.0142 memory: 17620 loss: 2.1160 loss_prob: 1.2765 loss_thr: 0.6395 loss_db: 0.2000 2022/11/01 15:22:20 - mmengine - INFO - Epoch(train) [223][25/63] lr: 1.9603e-03 eta: 10:52:02 time: 0.5930 data_time: 0.0254 memory: 17620 loss: 2.2234 loss_prob: 1.3487 loss_thr: 0.6594 loss_db: 0.2153 2022/11/01 15:22:23 - mmengine - INFO - Epoch(train) [223][30/63] lr: 1.9603e-03 eta: 10:51:53 time: 0.5890 data_time: 0.0258 memory: 17620 loss: 2.3133 loss_prob: 1.4174 loss_thr: 0.6715 loss_db: 0.2245 2022/11/01 15:22:26 - mmengine - INFO - Epoch(train) [223][35/63] lr: 1.9603e-03 eta: 10:51:53 time: 0.5664 data_time: 0.0103 memory: 17620 loss: 2.2283 loss_prob: 1.3640 loss_thr: 0.6513 loss_db: 0.2130 2022/11/01 15:22:28 - mmengine - INFO - Epoch(train) [223][40/63] lr: 1.9603e-03 eta: 10:51:43 time: 0.5553 data_time: 0.0116 memory: 17620 loss: 2.0791 loss_prob: 1.2448 loss_thr: 0.6343 loss_db: 0.1999 2022/11/01 15:22:31 - mmengine - INFO - Epoch(train) [223][45/63] lr: 1.9603e-03 eta: 10:51:43 time: 0.5455 data_time: 0.0121 memory: 17620 loss: 2.1604 loss_prob: 1.3142 loss_thr: 0.6364 loss_db: 0.2099 2022/11/01 15:22:34 - mmengine - INFO - Epoch(train) [223][50/63] lr: 1.9603e-03 eta: 10:51:33 time: 0.5529 data_time: 0.0198 memory: 17620 loss: 2.2739 loss_prob: 1.3862 loss_thr: 0.6653 loss_db: 0.2224 2022/11/01 15:22:37 - mmengine - INFO - Epoch(train) [223][55/63] lr: 1.9603e-03 eta: 10:51:33 time: 0.5600 data_time: 0.0199 memory: 17620 loss: 2.0957 loss_prob: 1.2427 loss_thr: 0.6503 loss_db: 0.2027 2022/11/01 15:22:39 - mmengine - INFO - Epoch(train) [223][60/63] lr: 1.9603e-03 eta: 10:51:23 time: 0.5466 data_time: 0.0085 memory: 17620 loss: 2.0947 loss_prob: 1.2581 loss_thr: 0.6331 loss_db: 0.2036 2022/11/01 15:22:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:22:45 - mmengine - INFO - Epoch(train) [224][5/63] lr: 1.9585e-03 eta: 10:51:23 time: 0.6471 data_time: 0.1597 memory: 17620 loss: 1.9557 loss_prob: 1.1532 loss_thr: 0.6155 loss_db: 0.1870 2022/11/01 15:22:48 - mmengine - INFO - Epoch(train) [224][10/63] lr: 1.9585e-03 eta: 10:51:09 time: 0.6903 data_time: 0.1660 memory: 17620 loss: 1.9100 loss_prob: 1.1186 loss_thr: 0.6072 loss_db: 0.1841 2022/11/01 15:22:50 - mmengine - INFO - Epoch(train) [224][15/63] lr: 1.9585e-03 eta: 10:51:09 time: 0.5574 data_time: 0.0148 memory: 17620 loss: 2.1948 loss_prob: 1.3329 loss_thr: 0.6458 loss_db: 0.2161 2022/11/01 15:22:53 - mmengine - INFO - Epoch(train) [224][20/63] lr: 1.9585e-03 eta: 10:51:01 time: 0.5923 data_time: 0.0058 memory: 17620 loss: 2.3265 loss_prob: 1.4302 loss_thr: 0.6679 loss_db: 0.2284 2022/11/01 15:22:56 - mmengine - INFO - Epoch(train) [224][25/63] lr: 1.9585e-03 eta: 10:51:01 time: 0.5827 data_time: 0.0127 memory: 17620 loss: 2.1684 loss_prob: 1.3060 loss_thr: 0.6472 loss_db: 0.2152 2022/11/01 15:22:59 - mmengine - INFO - Epoch(train) [224][30/63] lr: 1.9585e-03 eta: 10:50:52 time: 0.5754 data_time: 0.0265 memory: 17620 loss: 2.0922 loss_prob: 1.2401 loss_thr: 0.6535 loss_db: 0.1987 2022/11/01 15:23:02 - mmengine - INFO - Epoch(train) [224][35/63] lr: 1.9585e-03 eta: 10:50:52 time: 0.5953 data_time: 0.0278 memory: 17620 loss: 2.0584 loss_prob: 1.2056 loss_thr: 0.6608 loss_db: 0.1920 2022/11/01 15:23:05 - mmengine - INFO - Epoch(train) [224][40/63] lr: 1.9585e-03 eta: 10:50:43 time: 0.5699 data_time: 0.0129 memory: 17620 loss: 2.0623 loss_prob: 1.2068 loss_thr: 0.6568 loss_db: 0.1988 2022/11/01 15:23:08 - mmengine - INFO - Epoch(train) [224][45/63] lr: 1.9585e-03 eta: 10:50:43 time: 0.5462 data_time: 0.0052 memory: 17620 loss: 2.0597 loss_prob: 1.2118 loss_thr: 0.6486 loss_db: 0.1993 2022/11/01 15:23:10 - mmengine - INFO - Epoch(train) [224][50/63] lr: 1.9585e-03 eta: 10:50:32 time: 0.5354 data_time: 0.0131 memory: 17620 loss: 2.0904 loss_prob: 1.2413 loss_thr: 0.6497 loss_db: 0.1993 2022/11/01 15:23:13 - mmengine - INFO - Epoch(train) [224][55/63] lr: 1.9585e-03 eta: 10:50:32 time: 0.5572 data_time: 0.0210 memory: 17620 loss: 2.0411 loss_prob: 1.2140 loss_thr: 0.6342 loss_db: 0.1928 2022/11/01 15:23:16 - mmengine - INFO - Epoch(train) [224][60/63] lr: 1.9585e-03 eta: 10:50:23 time: 0.5785 data_time: 0.0157 memory: 17620 loss: 1.9779 loss_prob: 1.1698 loss_thr: 0.6168 loss_db: 0.1914 2022/11/01 15:23:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:23:23 - mmengine - INFO - Epoch(train) [225][5/63] lr: 1.9567e-03 eta: 10:50:23 time: 0.8251 data_time: 0.2378 memory: 17620 loss: 2.3242 loss_prob: 1.4312 loss_thr: 0.6514 loss_db: 0.2416 2022/11/01 15:23:27 - mmengine - INFO - Epoch(train) [225][10/63] lr: 1.9567e-03 eta: 10:50:20 time: 0.9335 data_time: 0.2368 memory: 17620 loss: 2.1402 loss_prob: 1.2879 loss_thr: 0.6306 loss_db: 0.2218 2022/11/01 15:23:31 - mmengine - INFO - Epoch(train) [225][15/63] lr: 1.9567e-03 eta: 10:50:20 time: 0.7603 data_time: 0.0079 memory: 17620 loss: 2.3026 loss_prob: 1.3904 loss_thr: 0.6835 loss_db: 0.2287 2022/11/01 15:23:34 - mmengine - INFO - Epoch(train) [225][20/63] lr: 1.9567e-03 eta: 10:50:18 time: 0.7473 data_time: 0.0074 memory: 17620 loss: 2.3665 loss_prob: 1.4322 loss_thr: 0.7085 loss_db: 0.2258 2022/11/01 15:23:37 - mmengine - INFO - Epoch(train) [225][25/63] lr: 1.9567e-03 eta: 10:50:18 time: 0.6493 data_time: 0.0260 memory: 17620 loss: 2.2510 loss_prob: 1.3541 loss_thr: 0.6797 loss_db: 0.2172 2022/11/01 15:23:41 - mmengine - INFO - Epoch(train) [225][30/63] lr: 1.9567e-03 eta: 10:50:13 time: 0.6603 data_time: 0.0335 memory: 17620 loss: 2.2399 loss_prob: 1.3588 loss_thr: 0.6588 loss_db: 0.2223 2022/11/01 15:23:44 - mmengine - INFO - Epoch(train) [225][35/63] lr: 1.9567e-03 eta: 10:50:13 time: 0.6409 data_time: 0.0125 memory: 17620 loss: 2.2828 loss_prob: 1.3969 loss_thr: 0.6618 loss_db: 0.2241 2022/11/01 15:23:46 - mmengine - INFO - Epoch(train) [225][40/63] lr: 1.9567e-03 eta: 10:50:03 time: 0.5584 data_time: 0.0072 memory: 17620 loss: 2.3106 loss_prob: 1.4135 loss_thr: 0.6630 loss_db: 0.2340 2022/11/01 15:23:49 - mmengine - INFO - Epoch(train) [225][45/63] lr: 1.9567e-03 eta: 10:50:03 time: 0.5338 data_time: 0.0072 memory: 17620 loss: 2.1964 loss_prob: 1.3303 loss_thr: 0.6441 loss_db: 0.2220 2022/11/01 15:23:52 - mmengine - INFO - Epoch(train) [225][50/63] lr: 1.9567e-03 eta: 10:49:55 time: 0.5846 data_time: 0.0189 memory: 17620 loss: 2.2579 loss_prob: 1.3782 loss_thr: 0.6552 loss_db: 0.2245 2022/11/01 15:23:55 - mmengine - INFO - Epoch(train) [225][55/63] lr: 1.9567e-03 eta: 10:49:55 time: 0.5889 data_time: 0.0221 memory: 17620 loss: 2.2818 loss_prob: 1.3895 loss_thr: 0.6625 loss_db: 0.2297 2022/11/01 15:23:58 - mmengine - INFO - Epoch(train) [225][60/63] lr: 1.9567e-03 eta: 10:49:44 time: 0.5396 data_time: 0.0080 memory: 17620 loss: 2.2399 loss_prob: 1.3586 loss_thr: 0.6543 loss_db: 0.2271 2022/11/01 15:23:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:24:04 - mmengine - INFO - Epoch(train) [226][5/63] lr: 1.9549e-03 eta: 10:49:44 time: 0.7859 data_time: 0.1765 memory: 17620 loss: 2.5590 loss_prob: 1.6054 loss_thr: 0.6925 loss_db: 0.2611 2022/11/01 15:24:08 - mmengine - INFO - Epoch(train) [226][10/63] lr: 1.9549e-03 eta: 10:49:38 time: 0.8704 data_time: 0.1872 memory: 17620 loss: 2.2385 loss_prob: 1.3576 loss_thr: 0.6606 loss_db: 0.2204 2022/11/01 15:24:11 - mmengine - INFO - Epoch(train) [226][15/63] lr: 1.9549e-03 eta: 10:49:38 time: 0.6492 data_time: 0.0223 memory: 17620 loss: 2.1997 loss_prob: 1.3333 loss_thr: 0.6507 loss_db: 0.2157 2022/11/01 15:24:14 - mmengine - INFO - Epoch(train) [226][20/63] lr: 1.9549e-03 eta: 10:49:29 time: 0.5829 data_time: 0.0133 memory: 17620 loss: 2.2581 loss_prob: 1.3631 loss_thr: 0.6719 loss_db: 0.2231 2022/11/01 15:24:17 - mmengine - INFO - Epoch(train) [226][25/63] lr: 1.9549e-03 eta: 10:49:29 time: 0.5908 data_time: 0.0202 memory: 17620 loss: 2.2657 loss_prob: 1.3513 loss_thr: 0.6917 loss_db: 0.2227 2022/11/01 15:24:20 - mmengine - INFO - Epoch(train) [226][30/63] lr: 1.9549e-03 eta: 10:49:22 time: 0.5984 data_time: 0.0187 memory: 17620 loss: 2.0584 loss_prob: 1.2202 loss_thr: 0.6404 loss_db: 0.1978 2022/11/01 15:24:22 - mmengine - INFO - Epoch(train) [226][35/63] lr: 1.9549e-03 eta: 10:49:22 time: 0.5359 data_time: 0.0170 memory: 17620 loss: 2.0386 loss_prob: 1.2477 loss_thr: 0.5962 loss_db: 0.1946 2022/11/01 15:24:25 - mmengine - INFO - Epoch(train) [226][40/63] lr: 1.9549e-03 eta: 10:49:11 time: 0.5314 data_time: 0.0201 memory: 17620 loss: 2.0765 loss_prob: 1.2682 loss_thr: 0.6135 loss_db: 0.1948 2022/11/01 15:24:28 - mmengine - INFO - Epoch(train) [226][45/63] lr: 1.9549e-03 eta: 10:49:11 time: 0.5293 data_time: 0.0090 memory: 17620 loss: 2.1889 loss_prob: 1.2959 loss_thr: 0.6860 loss_db: 0.2070 2022/11/01 15:24:31 - mmengine - INFO - Epoch(train) [226][50/63] lr: 1.9549e-03 eta: 10:49:01 time: 0.5575 data_time: 0.0178 memory: 17620 loss: 2.3238 loss_prob: 1.3992 loss_thr: 0.7012 loss_db: 0.2234 2022/11/01 15:24:33 - mmengine - INFO - Epoch(train) [226][55/63] lr: 1.9549e-03 eta: 10:49:01 time: 0.5896 data_time: 0.0166 memory: 17620 loss: 2.1748 loss_prob: 1.3131 loss_thr: 0.6552 loss_db: 0.2065 2022/11/01 15:24:36 - mmengine - INFO - Epoch(train) [226][60/63] lr: 1.9549e-03 eta: 10:48:52 time: 0.5716 data_time: 0.0108 memory: 17620 loss: 2.0777 loss_prob: 1.2392 loss_thr: 0.6450 loss_db: 0.1935 2022/11/01 15:24:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:24:42 - mmengine - INFO - Epoch(train) [227][5/63] lr: 1.9531e-03 eta: 10:48:52 time: 0.6946 data_time: 0.1924 memory: 17620 loss: 2.0939 loss_prob: 1.2422 loss_thr: 0.6501 loss_db: 0.2016 2022/11/01 15:24:45 - mmengine - INFO - Epoch(train) [227][10/63] lr: 1.9531e-03 eta: 10:48:41 time: 0.7578 data_time: 0.1919 memory: 17620 loss: 2.0748 loss_prob: 1.2508 loss_thr: 0.6290 loss_db: 0.1951 2022/11/01 15:24:48 - mmengine - INFO - Epoch(train) [227][15/63] lr: 1.9531e-03 eta: 10:48:41 time: 0.6023 data_time: 0.0057 memory: 17620 loss: 2.2951 loss_prob: 1.4300 loss_thr: 0.6504 loss_db: 0.2147 2022/11/01 15:24:51 - mmengine - INFO - Epoch(train) [227][20/63] lr: 1.9531e-03 eta: 10:48:31 time: 0.5584 data_time: 0.0088 memory: 17620 loss: 2.2016 loss_prob: 1.3392 loss_thr: 0.6554 loss_db: 0.2070 2022/11/01 15:24:54 - mmengine - INFO - Epoch(train) [227][25/63] lr: 1.9531e-03 eta: 10:48:31 time: 0.5461 data_time: 0.0323 memory: 17620 loss: 2.1262 loss_prob: 1.2642 loss_thr: 0.6588 loss_db: 0.2032 2022/11/01 15:24:56 - mmengine - INFO - Epoch(train) [227][30/63] lr: 1.9531e-03 eta: 10:48:21 time: 0.5541 data_time: 0.0328 memory: 17620 loss: 2.1783 loss_prob: 1.2959 loss_thr: 0.6734 loss_db: 0.2090 2022/11/01 15:24:59 - mmengine - INFO - Epoch(train) [227][35/63] lr: 1.9531e-03 eta: 10:48:21 time: 0.5296 data_time: 0.0088 memory: 17620 loss: 2.2212 loss_prob: 1.3184 loss_thr: 0.6875 loss_db: 0.2153 2022/11/01 15:25:01 - mmengine - INFO - Epoch(train) [227][40/63] lr: 1.9531e-03 eta: 10:48:10 time: 0.5248 data_time: 0.0046 memory: 17620 loss: 2.3960 loss_prob: 1.4609 loss_thr: 0.6894 loss_db: 0.2457 2022/11/01 15:25:04 - mmengine - INFO - Epoch(train) [227][45/63] lr: 1.9531e-03 eta: 10:48:10 time: 0.5236 data_time: 0.0079 memory: 17620 loss: 2.5755 loss_prob: 1.5958 loss_thr: 0.7118 loss_db: 0.2678 2022/11/01 15:25:07 - mmengine - INFO - Epoch(train) [227][50/63] lr: 1.9531e-03 eta: 10:48:00 time: 0.5444 data_time: 0.0242 memory: 17620 loss: 2.4304 loss_prob: 1.4910 loss_thr: 0.7028 loss_db: 0.2366 2022/11/01 15:25:09 - mmengine - INFO - Epoch(train) [227][55/63] lr: 1.9531e-03 eta: 10:48:00 time: 0.5372 data_time: 0.0238 memory: 17620 loss: 2.5584 loss_prob: 1.6028 loss_thr: 0.7054 loss_db: 0.2502 2022/11/01 15:25:12 - mmengine - INFO - Epoch(train) [227][60/63] lr: 1.9531e-03 eta: 10:47:49 time: 0.5095 data_time: 0.0075 memory: 17620 loss: 2.6603 loss_prob: 1.6946 loss_thr: 0.6969 loss_db: 0.2688 2022/11/01 15:25:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:25:18 - mmengine - INFO - Epoch(train) [228][5/63] lr: 1.9513e-03 eta: 10:47:49 time: 0.6736 data_time: 0.1683 memory: 17620 loss: 2.2101 loss_prob: 1.3573 loss_thr: 0.6351 loss_db: 0.2178 2022/11/01 15:25:21 - mmengine - INFO - Epoch(train) [228][10/63] lr: 1.9513e-03 eta: 10:47:37 time: 0.7472 data_time: 0.1715 memory: 17620 loss: 2.2568 loss_prob: 1.3654 loss_thr: 0.6705 loss_db: 0.2208 2022/11/01 15:25:24 - mmengine - INFO - Epoch(train) [228][15/63] lr: 1.9513e-03 eta: 10:47:37 time: 0.5862 data_time: 0.0081 memory: 17620 loss: 2.1886 loss_prob: 1.3198 loss_thr: 0.6616 loss_db: 0.2072 2022/11/01 15:25:26 - mmengine - INFO - Epoch(train) [228][20/63] lr: 1.9513e-03 eta: 10:47:27 time: 0.5371 data_time: 0.0066 memory: 17620 loss: 2.3108 loss_prob: 1.4109 loss_thr: 0.6751 loss_db: 0.2247 2022/11/01 15:25:29 - mmengine - INFO - Epoch(train) [228][25/63] lr: 1.9513e-03 eta: 10:47:27 time: 0.5334 data_time: 0.0259 memory: 17620 loss: 2.2608 loss_prob: 1.3454 loss_thr: 0.6989 loss_db: 0.2164 2022/11/01 15:25:32 - mmengine - INFO - Epoch(train) [228][30/63] lr: 1.9513e-03 eta: 10:47:18 time: 0.5793 data_time: 0.0453 memory: 17620 loss: 1.8788 loss_prob: 1.0693 loss_thr: 0.6411 loss_db: 0.1684 2022/11/01 15:25:35 - mmengine - INFO - Epoch(train) [228][35/63] lr: 1.9513e-03 eta: 10:47:18 time: 0.5642 data_time: 0.0273 memory: 17620 loss: 2.0308 loss_prob: 1.2143 loss_thr: 0.6212 loss_db: 0.1953 2022/11/01 15:25:37 - mmengine - INFO - Epoch(train) [228][40/63] lr: 1.9513e-03 eta: 10:47:07 time: 0.5258 data_time: 0.0062 memory: 17620 loss: 2.2004 loss_prob: 1.3344 loss_thr: 0.6497 loss_db: 0.2163 2022/11/01 15:25:40 - mmengine - INFO - Epoch(train) [228][45/63] lr: 1.9513e-03 eta: 10:47:07 time: 0.5276 data_time: 0.0041 memory: 17620 loss: 2.2800 loss_prob: 1.3798 loss_thr: 0.6805 loss_db: 0.2197 2022/11/01 15:25:43 - mmengine - INFO - Epoch(train) [228][50/63] lr: 1.9513e-03 eta: 10:46:57 time: 0.5500 data_time: 0.0134 memory: 17620 loss: 2.4474 loss_prob: 1.5228 loss_thr: 0.6847 loss_db: 0.2400 2022/11/01 15:25:45 - mmengine - INFO - Epoch(train) [228][55/63] lr: 1.9513e-03 eta: 10:46:57 time: 0.5488 data_time: 0.0194 memory: 17620 loss: 2.3669 loss_prob: 1.4735 loss_thr: 0.6594 loss_db: 0.2340 2022/11/01 15:25:48 - mmengine - INFO - Epoch(train) [228][60/63] lr: 1.9513e-03 eta: 10:46:47 time: 0.5381 data_time: 0.0139 memory: 17620 loss: 2.2947 loss_prob: 1.4085 loss_thr: 0.6601 loss_db: 0.2260 2022/11/01 15:25:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:25:55 - mmengine - INFO - Epoch(train) [229][5/63] lr: 1.9495e-03 eta: 10:46:47 time: 0.7536 data_time: 0.2111 memory: 17620 loss: 2.5206 loss_prob: 1.5652 loss_thr: 0.6990 loss_db: 0.2564 2022/11/01 15:25:57 - mmengine - INFO - Epoch(train) [229][10/63] lr: 1.9495e-03 eta: 10:46:37 time: 0.7878 data_time: 0.2109 memory: 17620 loss: 2.2919 loss_prob: 1.3876 loss_thr: 0.6797 loss_db: 0.2247 2022/11/01 15:26:00 - mmengine - INFO - Epoch(train) [229][15/63] lr: 1.9495e-03 eta: 10:46:37 time: 0.5388 data_time: 0.0048 memory: 17620 loss: 2.2087 loss_prob: 1.3294 loss_thr: 0.6692 loss_db: 0.2100 2022/11/01 15:26:03 - mmengine - INFO - Epoch(train) [229][20/63] lr: 1.9495e-03 eta: 10:46:29 time: 0.5922 data_time: 0.0046 memory: 17620 loss: 2.1696 loss_prob: 1.3114 loss_thr: 0.6527 loss_db: 0.2056 2022/11/01 15:26:06 - mmengine - INFO - Epoch(train) [229][25/63] lr: 1.9495e-03 eta: 10:46:29 time: 0.6015 data_time: 0.0217 memory: 17620 loss: 2.0219 loss_prob: 1.2131 loss_thr: 0.6164 loss_db: 0.1924 2022/11/01 15:26:09 - mmengine - INFO - Epoch(train) [229][30/63] lr: 1.9495e-03 eta: 10:46:19 time: 0.5529 data_time: 0.0275 memory: 17620 loss: 2.3026 loss_prob: 1.4327 loss_thr: 0.6464 loss_db: 0.2235 2022/11/01 15:26:11 - mmengine - INFO - Epoch(train) [229][35/63] lr: 1.9495e-03 eta: 10:46:19 time: 0.5482 data_time: 0.0159 memory: 17620 loss: 2.3492 loss_prob: 1.4427 loss_thr: 0.6794 loss_db: 0.2271 2022/11/01 15:26:14 - mmengine - INFO - Epoch(train) [229][40/63] lr: 1.9495e-03 eta: 10:46:09 time: 0.5595 data_time: 0.0104 memory: 17620 loss: 2.0663 loss_prob: 1.2218 loss_thr: 0.6526 loss_db: 0.1919 2022/11/01 15:26:17 - mmengine - INFO - Epoch(train) [229][45/63] lr: 1.9495e-03 eta: 10:46:09 time: 0.5730 data_time: 0.0077 memory: 17620 loss: 2.3369 loss_prob: 1.4423 loss_thr: 0.6668 loss_db: 0.2278 2022/11/01 15:26:20 - mmengine - INFO - Epoch(train) [229][50/63] lr: 1.9495e-03 eta: 10:46:00 time: 0.5613 data_time: 0.0198 memory: 17620 loss: 2.2685 loss_prob: 1.3905 loss_thr: 0.6581 loss_db: 0.2199 2022/11/01 15:26:23 - mmengine - INFO - Epoch(train) [229][55/63] lr: 1.9495e-03 eta: 10:46:00 time: 0.5478 data_time: 0.0207 memory: 17620 loss: 2.1001 loss_prob: 1.2629 loss_thr: 0.6340 loss_db: 0.2033 2022/11/01 15:26:25 - mmengine - INFO - Epoch(train) [229][60/63] lr: 1.9495e-03 eta: 10:45:49 time: 0.5334 data_time: 0.0112 memory: 17620 loss: 2.3122 loss_prob: 1.4219 loss_thr: 0.6552 loss_db: 0.2350 2022/11/01 15:26:27 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:26:33 - mmengine - INFO - Epoch(train) [230][5/63] lr: 1.9477e-03 eta: 10:45:49 time: 0.8399 data_time: 0.2855 memory: 17620 loss: 2.1271 loss_prob: 1.2792 loss_thr: 0.6416 loss_db: 0.2062 2022/11/01 15:26:35 - mmengine - INFO - Epoch(train) [230][10/63] lr: 1.9477e-03 eta: 10:45:43 time: 0.8617 data_time: 0.2859 memory: 17620 loss: 2.0829 loss_prob: 1.2367 loss_thr: 0.6475 loss_db: 0.1986 2022/11/01 15:26:38 - mmengine - INFO - Epoch(train) [230][15/63] lr: 1.9477e-03 eta: 10:45:43 time: 0.5297 data_time: 0.0046 memory: 17620 loss: 2.1761 loss_prob: 1.3039 loss_thr: 0.6635 loss_db: 0.2087 2022/11/01 15:26:41 - mmengine - INFO - Epoch(train) [230][20/63] lr: 1.9477e-03 eta: 10:45:33 time: 0.5466 data_time: 0.0050 memory: 17620 loss: 2.0912 loss_prob: 1.2522 loss_thr: 0.6391 loss_db: 0.1999 2022/11/01 15:26:43 - mmengine - INFO - Epoch(train) [230][25/63] lr: 1.9477e-03 eta: 10:45:33 time: 0.5596 data_time: 0.0274 memory: 17620 loss: 2.1622 loss_prob: 1.3196 loss_thr: 0.6311 loss_db: 0.2116 2022/11/01 15:26:46 - mmengine - INFO - Epoch(train) [230][30/63] lr: 1.9477e-03 eta: 10:45:23 time: 0.5442 data_time: 0.0326 memory: 17620 loss: 2.2759 loss_prob: 1.3904 loss_thr: 0.6595 loss_db: 0.2261 2022/11/01 15:26:49 - mmengine - INFO - Epoch(train) [230][35/63] lr: 1.9477e-03 eta: 10:45:23 time: 0.5370 data_time: 0.0100 memory: 17620 loss: 2.1384 loss_prob: 1.2777 loss_thr: 0.6555 loss_db: 0.2052 2022/11/01 15:26:52 - mmengine - INFO - Epoch(train) [230][40/63] lr: 1.9477e-03 eta: 10:45:13 time: 0.5417 data_time: 0.0045 memory: 17620 loss: 1.9975 loss_prob: 1.1906 loss_thr: 0.6198 loss_db: 0.1871 2022/11/01 15:26:54 - mmengine - INFO - Epoch(train) [230][45/63] lr: 1.9477e-03 eta: 10:45:13 time: 0.5436 data_time: 0.0054 memory: 17620 loss: 1.9326 loss_prob: 1.1369 loss_thr: 0.6149 loss_db: 0.1809 2022/11/01 15:26:57 - mmengine - INFO - Epoch(train) [230][50/63] lr: 1.9477e-03 eta: 10:45:03 time: 0.5559 data_time: 0.0226 memory: 17620 loss: 2.1281 loss_prob: 1.2709 loss_thr: 0.6511 loss_db: 0.2061 2022/11/01 15:27:00 - mmengine - INFO - Epoch(train) [230][55/63] lr: 1.9477e-03 eta: 10:45:03 time: 0.5421 data_time: 0.0245 memory: 17620 loss: 2.1718 loss_prob: 1.3039 loss_thr: 0.6551 loss_db: 0.2127 2022/11/01 15:27:02 - mmengine - INFO - Epoch(train) [230][60/63] lr: 1.9477e-03 eta: 10:44:51 time: 0.5101 data_time: 0.0068 memory: 17620 loss: 2.0774 loss_prob: 1.2350 loss_thr: 0.6435 loss_db: 0.1989 2022/11/01 15:27:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:27:08 - mmengine - INFO - Epoch(train) [231][5/63] lr: 1.9459e-03 eta: 10:44:51 time: 0.6885 data_time: 0.1869 memory: 17620 loss: 2.0804 loss_prob: 1.2410 loss_thr: 0.6362 loss_db: 0.2032 2022/11/01 15:27:11 - mmengine - INFO - Epoch(train) [231][10/63] lr: 1.9459e-03 eta: 10:44:39 time: 0.7231 data_time: 0.1932 memory: 17620 loss: 2.0415 loss_prob: 1.2127 loss_thr: 0.6314 loss_db: 0.1974 2022/11/01 15:27:13 - mmengine - INFO - Epoch(train) [231][15/63] lr: 1.9459e-03 eta: 10:44:39 time: 0.5297 data_time: 0.0107 memory: 17620 loss: 2.0739 loss_prob: 1.2304 loss_thr: 0.6428 loss_db: 0.2007 2022/11/01 15:27:16 - mmengine - INFO - Epoch(train) [231][20/63] lr: 1.9459e-03 eta: 10:44:28 time: 0.5211 data_time: 0.0046 memory: 17620 loss: 2.0544 loss_prob: 1.2050 loss_thr: 0.6535 loss_db: 0.1959 2022/11/01 15:27:19 - mmengine - INFO - Epoch(train) [231][25/63] lr: 1.9459e-03 eta: 10:44:28 time: 0.5263 data_time: 0.0180 memory: 17620 loss: 1.9625 loss_prob: 1.1397 loss_thr: 0.6400 loss_db: 0.1828 2022/11/01 15:27:21 - mmengine - INFO - Epoch(train) [231][30/63] lr: 1.9459e-03 eta: 10:44:18 time: 0.5448 data_time: 0.0313 memory: 17620 loss: 1.8968 loss_prob: 1.1007 loss_thr: 0.6212 loss_db: 0.1749 2022/11/01 15:27:24 - mmengine - INFO - Epoch(train) [231][35/63] lr: 1.9459e-03 eta: 10:44:18 time: 0.5525 data_time: 0.0189 memory: 17620 loss: 1.9322 loss_prob: 1.1401 loss_thr: 0.6109 loss_db: 0.1811 2022/11/01 15:27:27 - mmengine - INFO - Epoch(train) [231][40/63] lr: 1.9459e-03 eta: 10:44:07 time: 0.5345 data_time: 0.0061 memory: 17620 loss: 1.9445 loss_prob: 1.1459 loss_thr: 0.6140 loss_db: 0.1846 2022/11/01 15:27:30 - mmengine - INFO - Epoch(train) [231][45/63] lr: 1.9459e-03 eta: 10:44:07 time: 0.5458 data_time: 0.0082 memory: 17620 loss: 1.9579 loss_prob: 1.1423 loss_thr: 0.6310 loss_db: 0.1846 2022/11/01 15:27:33 - mmengine - INFO - Epoch(train) [231][50/63] lr: 1.9459e-03 eta: 10:43:59 time: 0.5758 data_time: 0.0252 memory: 17620 loss: 2.1304 loss_prob: 1.2697 loss_thr: 0.6604 loss_db: 0.2003 2022/11/01 15:27:35 - mmengine - INFO - Epoch(train) [231][55/63] lr: 1.9459e-03 eta: 10:43:59 time: 0.5598 data_time: 0.0242 memory: 17620 loss: 2.2336 loss_prob: 1.3632 loss_thr: 0.6602 loss_db: 0.2102 2022/11/01 15:27:38 - mmengine - INFO - Epoch(train) [231][60/63] lr: 1.9459e-03 eta: 10:43:48 time: 0.5223 data_time: 0.0069 memory: 17620 loss: 2.1897 loss_prob: 1.3323 loss_thr: 0.6447 loss_db: 0.2127 2022/11/01 15:27:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:27:43 - mmengine - INFO - Epoch(train) [232][5/63] lr: 1.9441e-03 eta: 10:43:48 time: 0.6675 data_time: 0.1609 memory: 17620 loss: 2.0724 loss_prob: 1.2183 loss_thr: 0.6539 loss_db: 0.2001 2022/11/01 15:27:46 - mmengine - INFO - Epoch(train) [232][10/63] lr: 1.9441e-03 eta: 10:43:34 time: 0.6856 data_time: 0.1638 memory: 17620 loss: 2.2432 loss_prob: 1.3461 loss_thr: 0.6747 loss_db: 0.2224 2022/11/01 15:27:49 - mmengine - INFO - Epoch(train) [232][15/63] lr: 1.9441e-03 eta: 10:43:34 time: 0.5309 data_time: 0.0085 memory: 17620 loss: 2.3358 loss_prob: 1.4210 loss_thr: 0.6804 loss_db: 0.2344 2022/11/01 15:27:51 - mmengine - INFO - Epoch(train) [232][20/63] lr: 1.9441e-03 eta: 10:43:23 time: 0.5333 data_time: 0.0068 memory: 17620 loss: 2.1857 loss_prob: 1.3121 loss_thr: 0.6558 loss_db: 0.2178 2022/11/01 15:27:54 - mmengine - INFO - Epoch(train) [232][25/63] lr: 1.9441e-03 eta: 10:43:23 time: 0.5417 data_time: 0.0211 memory: 17620 loss: 2.0705 loss_prob: 1.2273 loss_thr: 0.6448 loss_db: 0.1984 2022/11/01 15:27:57 - mmengine - INFO - Epoch(train) [232][30/63] lr: 1.9441e-03 eta: 10:43:13 time: 0.5447 data_time: 0.0271 memory: 17620 loss: 1.9958 loss_prob: 1.1700 loss_thr: 0.6394 loss_db: 0.1864 2022/11/01 15:27:59 - mmengine - INFO - Epoch(train) [232][35/63] lr: 1.9441e-03 eta: 10:43:13 time: 0.5264 data_time: 0.0113 memory: 17620 loss: 2.0672 loss_prob: 1.2236 loss_thr: 0.6444 loss_db: 0.1992 2022/11/01 15:28:02 - mmengine - INFO - Epoch(train) [232][40/63] lr: 1.9441e-03 eta: 10:43:04 time: 0.5532 data_time: 0.0088 memory: 17620 loss: 2.1336 loss_prob: 1.2800 loss_thr: 0.6491 loss_db: 0.2046 2022/11/01 15:28:05 - mmengine - INFO - Epoch(train) [232][45/63] lr: 1.9441e-03 eta: 10:43:04 time: 0.5715 data_time: 0.0094 memory: 17620 loss: 2.1999 loss_prob: 1.3391 loss_thr: 0.6538 loss_db: 0.2070 2022/11/01 15:28:08 - mmengine - INFO - Epoch(train) [232][50/63] lr: 1.9441e-03 eta: 10:42:54 time: 0.5428 data_time: 0.0125 memory: 17620 loss: 2.0898 loss_prob: 1.2491 loss_thr: 0.6447 loss_db: 0.1960 2022/11/01 15:28:10 - mmengine - INFO - Epoch(train) [232][55/63] lr: 1.9441e-03 eta: 10:42:54 time: 0.5269 data_time: 0.0178 memory: 17620 loss: 1.9433 loss_prob: 1.1313 loss_thr: 0.6279 loss_db: 0.1841 2022/11/01 15:28:13 - mmengine - INFO - Epoch(train) [232][60/63] lr: 1.9441e-03 eta: 10:42:43 time: 0.5229 data_time: 0.0121 memory: 17620 loss: 2.0620 loss_prob: 1.2201 loss_thr: 0.6461 loss_db: 0.1959 2022/11/01 15:28:14 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:28:19 - mmengine - INFO - Epoch(train) [233][5/63] lr: 1.9423e-03 eta: 10:42:43 time: 0.7150 data_time: 0.2053 memory: 17620 loss: 1.9911 loss_prob: 1.1624 loss_thr: 0.6418 loss_db: 0.1868 2022/11/01 15:28:22 - mmengine - INFO - Epoch(train) [233][10/63] lr: 1.9423e-03 eta: 10:42:33 time: 0.7917 data_time: 0.2047 memory: 17620 loss: 1.9507 loss_prob: 1.1321 loss_thr: 0.6380 loss_db: 0.1806 2022/11/01 15:28:25 - mmengine - INFO - Epoch(train) [233][15/63] lr: 1.9423e-03 eta: 10:42:33 time: 0.5804 data_time: 0.0142 memory: 17620 loss: 2.0482 loss_prob: 1.2095 loss_thr: 0.6455 loss_db: 0.1932 2022/11/01 15:28:28 - mmengine - INFO - Epoch(train) [233][20/63] lr: 1.9423e-03 eta: 10:42:23 time: 0.5296 data_time: 0.0158 memory: 17620 loss: 2.0210 loss_prob: 1.2017 loss_thr: 0.6228 loss_db: 0.1965 2022/11/01 15:28:31 - mmengine - INFO - Epoch(train) [233][25/63] lr: 1.9423e-03 eta: 10:42:23 time: 0.5648 data_time: 0.0402 memory: 17620 loss: 1.9345 loss_prob: 1.1355 loss_thr: 0.6123 loss_db: 0.1866 2022/11/01 15:28:34 - mmengine - INFO - Epoch(train) [233][30/63] lr: 1.9423e-03 eta: 10:42:15 time: 0.5952 data_time: 0.0371 memory: 17620 loss: 2.0651 loss_prob: 1.2374 loss_thr: 0.6296 loss_db: 0.1981 2022/11/01 15:28:36 - mmengine - INFO - Epoch(train) [233][35/63] lr: 1.9423e-03 eta: 10:42:15 time: 0.5760 data_time: 0.0049 memory: 17620 loss: 2.1473 loss_prob: 1.2942 loss_thr: 0.6433 loss_db: 0.2098 2022/11/01 15:28:39 - mmengine - INFO - Epoch(train) [233][40/63] lr: 1.9423e-03 eta: 10:42:06 time: 0.5818 data_time: 0.0102 memory: 17620 loss: 2.3382 loss_prob: 1.4267 loss_thr: 0.6681 loss_db: 0.2434 2022/11/01 15:28:42 - mmengine - INFO - Epoch(train) [233][45/63] lr: 1.9423e-03 eta: 10:42:06 time: 0.5740 data_time: 0.0109 memory: 17620 loss: 2.3677 loss_prob: 1.4519 loss_thr: 0.6746 loss_db: 0.2413 2022/11/01 15:28:45 - mmengine - INFO - Epoch(train) [233][50/63] lr: 1.9423e-03 eta: 10:41:56 time: 0.5450 data_time: 0.0202 memory: 17620 loss: 2.2501 loss_prob: 1.3649 loss_thr: 0.6691 loss_db: 0.2161 2022/11/01 15:28:48 - mmengine - INFO - Epoch(train) [233][55/63] lr: 1.9423e-03 eta: 10:41:56 time: 0.5475 data_time: 0.0201 memory: 17620 loss: 2.4733 loss_prob: 1.5294 loss_thr: 0.6869 loss_db: 0.2570 2022/11/01 15:28:51 - mmengine - INFO - Epoch(train) [233][60/63] lr: 1.9423e-03 eta: 10:41:48 time: 0.5848 data_time: 0.0103 memory: 17620 loss: 2.5323 loss_prob: 1.5845 loss_thr: 0.6792 loss_db: 0.2686 2022/11/01 15:28:52 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:28:57 - mmengine - INFO - Epoch(train) [234][5/63] lr: 1.9404e-03 eta: 10:41:48 time: 0.7585 data_time: 0.2125 memory: 17620 loss: 2.6744 loss_prob: 1.6960 loss_thr: 0.7036 loss_db: 0.2748 2022/11/01 15:29:00 - mmengine - INFO - Epoch(train) [234][10/63] lr: 1.9404e-03 eta: 10:41:38 time: 0.7757 data_time: 0.2147 memory: 17620 loss: 2.3014 loss_prob: 1.4009 loss_thr: 0.6754 loss_db: 0.2251 2022/11/01 15:29:03 - mmengine - INFO - Epoch(train) [234][15/63] lr: 1.9404e-03 eta: 10:41:38 time: 0.5589 data_time: 0.0088 memory: 17620 loss: 2.2308 loss_prob: 1.3446 loss_thr: 0.6746 loss_db: 0.2116 2022/11/01 15:29:05 - mmengine - INFO - Epoch(train) [234][20/63] lr: 1.9404e-03 eta: 10:41:28 time: 0.5548 data_time: 0.0046 memory: 17620 loss: 2.2213 loss_prob: 1.3407 loss_thr: 0.6665 loss_db: 0.2140 2022/11/01 15:29:08 - mmengine - INFO - Epoch(train) [234][25/63] lr: 1.9404e-03 eta: 10:41:28 time: 0.5618 data_time: 0.0156 memory: 17620 loss: 2.3985 loss_prob: 1.4834 loss_thr: 0.6786 loss_db: 0.2365 2022/11/01 15:29:11 - mmengine - INFO - Epoch(train) [234][30/63] lr: 1.9404e-03 eta: 10:41:19 time: 0.5593 data_time: 0.0267 memory: 17620 loss: 2.4077 loss_prob: 1.4902 loss_thr: 0.6781 loss_db: 0.2394 2022/11/01 15:29:14 - mmengine - INFO - Epoch(train) [234][35/63] lr: 1.9404e-03 eta: 10:41:19 time: 0.5771 data_time: 0.0217 memory: 17620 loss: 2.0061 loss_prob: 1.1935 loss_thr: 0.6223 loss_db: 0.1903 2022/11/01 15:29:17 - mmengine - INFO - Epoch(train) [234][40/63] lr: 1.9404e-03 eta: 10:41:10 time: 0.5580 data_time: 0.0102 memory: 17620 loss: 2.0498 loss_prob: 1.2134 loss_thr: 0.6377 loss_db: 0.1986 2022/11/01 15:29:19 - mmengine - INFO - Epoch(train) [234][45/63] lr: 1.9404e-03 eta: 10:41:10 time: 0.5427 data_time: 0.0057 memory: 17620 loss: 2.1720 loss_prob: 1.3056 loss_thr: 0.6492 loss_db: 0.2172 2022/11/01 15:29:22 - mmengine - INFO - Epoch(train) [234][50/63] lr: 1.9404e-03 eta: 10:41:00 time: 0.5502 data_time: 0.0107 memory: 17620 loss: 2.1731 loss_prob: 1.3132 loss_thr: 0.6491 loss_db: 0.2108 2022/11/01 15:29:25 - mmengine - INFO - Epoch(train) [234][55/63] lr: 1.9404e-03 eta: 10:41:00 time: 0.5392 data_time: 0.0174 memory: 17620 loss: 2.2538 loss_prob: 1.3627 loss_thr: 0.6741 loss_db: 0.2169 2022/11/01 15:29:27 - mmengine - INFO - Epoch(train) [234][60/63] lr: 1.9404e-03 eta: 10:40:49 time: 0.5288 data_time: 0.0145 memory: 17620 loss: 2.2431 loss_prob: 1.3378 loss_thr: 0.6910 loss_db: 0.2143 2022/11/01 15:29:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:29:33 - mmengine - INFO - Epoch(train) [235][5/63] lr: 1.9386e-03 eta: 10:40:49 time: 0.6995 data_time: 0.1831 memory: 17620 loss: 1.9668 loss_prob: 1.1695 loss_thr: 0.6090 loss_db: 0.1883 2022/11/01 15:29:36 - mmengine - INFO - Epoch(train) [235][10/63] lr: 1.9386e-03 eta: 10:40:38 time: 0.7493 data_time: 0.1877 memory: 17620 loss: 2.0114 loss_prob: 1.1870 loss_thr: 0.6360 loss_db: 0.1884 2022/11/01 15:29:39 - mmengine - INFO - Epoch(train) [235][15/63] lr: 1.9386e-03 eta: 10:40:38 time: 0.5276 data_time: 0.0116 memory: 17620 loss: 2.3194 loss_prob: 1.4241 loss_thr: 0.6705 loss_db: 0.2248 2022/11/01 15:29:41 - mmengine - INFO - Epoch(train) [235][20/63] lr: 1.9386e-03 eta: 10:40:27 time: 0.5006 data_time: 0.0072 memory: 17620 loss: 2.3432 loss_prob: 1.4558 loss_thr: 0.6576 loss_db: 0.2298 2022/11/01 15:29:44 - mmengine - INFO - Epoch(train) [235][25/63] lr: 1.9386e-03 eta: 10:40:27 time: 0.4979 data_time: 0.0074 memory: 17620 loss: 2.2035 loss_prob: 1.3475 loss_thr: 0.6407 loss_db: 0.2153 2022/11/01 15:29:47 - mmengine - INFO - Epoch(train) [235][30/63] lr: 1.9386e-03 eta: 10:40:18 time: 0.5665 data_time: 0.0361 memory: 17620 loss: 2.2269 loss_prob: 1.3558 loss_thr: 0.6482 loss_db: 0.2229 2022/11/01 15:29:49 - mmengine - INFO - Epoch(train) [235][35/63] lr: 1.9386e-03 eta: 10:40:18 time: 0.5734 data_time: 0.0338 memory: 17620 loss: 2.3682 loss_prob: 1.4594 loss_thr: 0.6722 loss_db: 0.2366 2022/11/01 15:29:52 - mmengine - INFO - Epoch(train) [235][40/63] lr: 1.9386e-03 eta: 10:40:08 time: 0.5443 data_time: 0.0051 memory: 17620 loss: 2.2108 loss_prob: 1.3564 loss_thr: 0.6377 loss_db: 0.2167 2022/11/01 15:29:55 - mmengine - INFO - Epoch(train) [235][45/63] lr: 1.9386e-03 eta: 10:40:08 time: 0.5582 data_time: 0.0057 memory: 17620 loss: 1.9921 loss_prob: 1.1779 loss_thr: 0.6274 loss_db: 0.1867 2022/11/01 15:29:58 - mmengine - INFO - Epoch(train) [235][50/63] lr: 1.9386e-03 eta: 10:39:57 time: 0.5367 data_time: 0.0140 memory: 17620 loss: 2.0218 loss_prob: 1.1850 loss_thr: 0.6500 loss_db: 0.1868 2022/11/01 15:30:01 - mmengine - INFO - Epoch(train) [235][55/63] lr: 1.9386e-03 eta: 10:39:57 time: 0.5498 data_time: 0.0202 memory: 17620 loss: 1.8908 loss_prob: 1.1040 loss_thr: 0.6121 loss_db: 0.1746 2022/11/01 15:30:03 - mmengine - INFO - Epoch(train) [235][60/63] lr: 1.9386e-03 eta: 10:39:47 time: 0.5394 data_time: 0.0122 memory: 17620 loss: 1.8726 loss_prob: 1.0951 loss_thr: 0.6001 loss_db: 0.1774 2022/11/01 15:30:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:30:09 - mmengine - INFO - Epoch(train) [236][5/63] lr: 1.9368e-03 eta: 10:39:47 time: 0.6791 data_time: 0.1501 memory: 17620 loss: 2.0009 loss_prob: 1.1910 loss_thr: 0.6167 loss_db: 0.1932 2022/11/01 15:30:12 - mmengine - INFO - Epoch(train) [236][10/63] lr: 1.9368e-03 eta: 10:39:36 time: 0.7405 data_time: 0.1672 memory: 17620 loss: 1.9415 loss_prob: 1.1481 loss_thr: 0.6075 loss_db: 0.1859 2022/11/01 15:30:14 - mmengine - INFO - Epoch(train) [236][15/63] lr: 1.9368e-03 eta: 10:39:36 time: 0.5581 data_time: 0.0278 memory: 17620 loss: 1.8854 loss_prob: 1.1041 loss_thr: 0.6045 loss_db: 0.1768 2022/11/01 15:30:17 - mmengine - INFO - Epoch(train) [236][20/63] lr: 1.9368e-03 eta: 10:39:25 time: 0.5278 data_time: 0.0095 memory: 17620 loss: 1.8680 loss_prob: 1.1003 loss_thr: 0.5975 loss_db: 0.1702 2022/11/01 15:30:20 - mmengine - INFO - Epoch(train) [236][25/63] lr: 1.9368e-03 eta: 10:39:25 time: 0.5493 data_time: 0.0152 memory: 17620 loss: 1.9874 loss_prob: 1.1743 loss_thr: 0.6326 loss_db: 0.1805 2022/11/01 15:30:23 - mmengine - INFO - Epoch(train) [236][30/63] lr: 1.9368e-03 eta: 10:39:17 time: 0.5798 data_time: 0.0297 memory: 17620 loss: 2.1818 loss_prob: 1.3234 loss_thr: 0.6472 loss_db: 0.2113 2022/11/01 15:30:25 - mmengine - INFO - Epoch(train) [236][35/63] lr: 1.9368e-03 eta: 10:39:17 time: 0.5537 data_time: 0.0227 memory: 17620 loss: 2.2235 loss_prob: 1.3730 loss_thr: 0.6281 loss_db: 0.2223 2022/11/01 15:30:28 - mmengine - INFO - Epoch(train) [236][40/63] lr: 1.9368e-03 eta: 10:39:07 time: 0.5337 data_time: 0.0149 memory: 17620 loss: 2.0891 loss_prob: 1.2648 loss_thr: 0.6250 loss_db: 0.1993 2022/11/01 15:30:31 - mmengine - INFO - Epoch(train) [236][45/63] lr: 1.9368e-03 eta: 10:39:07 time: 0.5244 data_time: 0.0109 memory: 17620 loss: 2.0419 loss_prob: 1.2142 loss_thr: 0.6346 loss_db: 0.1932 2022/11/01 15:30:33 - mmengine - INFO - Epoch(train) [236][50/63] lr: 1.9368e-03 eta: 10:38:55 time: 0.5080 data_time: 0.0101 memory: 17620 loss: 2.1728 loss_prob: 1.2980 loss_thr: 0.6605 loss_db: 0.2144 2022/11/01 15:30:36 - mmengine - INFO - Epoch(train) [236][55/63] lr: 1.9368e-03 eta: 10:38:55 time: 0.5101 data_time: 0.0172 memory: 17620 loss: 2.1369 loss_prob: 1.2739 loss_thr: 0.6537 loss_db: 0.2094 2022/11/01 15:30:38 - mmengine - INFO - Epoch(train) [236][60/63] lr: 1.9368e-03 eta: 10:38:44 time: 0.5047 data_time: 0.0134 memory: 17620 loss: 2.2359 loss_prob: 1.3644 loss_thr: 0.6514 loss_db: 0.2201 2022/11/01 15:30:40 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:30:44 - mmengine - INFO - Epoch(train) [237][5/63] lr: 1.9350e-03 eta: 10:38:44 time: 0.7001 data_time: 0.2044 memory: 17620 loss: 2.1870 loss_prob: 1.3049 loss_thr: 0.6752 loss_db: 0.2070 2022/11/01 15:30:47 - mmengine - INFO - Epoch(train) [237][10/63] lr: 1.9350e-03 eta: 10:38:32 time: 0.7242 data_time: 0.2032 memory: 17620 loss: 2.0465 loss_prob: 1.2113 loss_thr: 0.6367 loss_db: 0.1985 2022/11/01 15:30:50 - mmengine - INFO - Epoch(train) [237][15/63] lr: 1.9350e-03 eta: 10:38:32 time: 0.5425 data_time: 0.0059 memory: 17620 loss: 2.0762 loss_prob: 1.2455 loss_thr: 0.6325 loss_db: 0.1982 2022/11/01 15:30:53 - mmengine - INFO - Epoch(train) [237][20/63] lr: 1.9350e-03 eta: 10:38:22 time: 0.5542 data_time: 0.0055 memory: 17620 loss: 2.1952 loss_prob: 1.3611 loss_thr: 0.6224 loss_db: 0.2117 2022/11/01 15:30:55 - mmengine - INFO - Epoch(train) [237][25/63] lr: 1.9350e-03 eta: 10:38:22 time: 0.5653 data_time: 0.0095 memory: 17620 loss: 2.4225 loss_prob: 1.5174 loss_thr: 0.6670 loss_db: 0.2381 2022/11/01 15:30:59 - mmengine - INFO - Epoch(train) [237][30/63] lr: 1.9350e-03 eta: 10:38:16 time: 0.6265 data_time: 0.0381 memory: 17620 loss: 2.3483 loss_prob: 1.4331 loss_thr: 0.6838 loss_db: 0.2314 2022/11/01 15:31:02 - mmengine - INFO - Epoch(train) [237][35/63] lr: 1.9350e-03 eta: 10:38:16 time: 0.6428 data_time: 0.0338 memory: 17620 loss: 2.1425 loss_prob: 1.2581 loss_thr: 0.6776 loss_db: 0.2068 2022/11/01 15:31:05 - mmengine - INFO - Epoch(train) [237][40/63] lr: 1.9350e-03 eta: 10:38:07 time: 0.5712 data_time: 0.0050 memory: 17620 loss: 2.1764 loss_prob: 1.2932 loss_thr: 0.6703 loss_db: 0.2130 2022/11/01 15:31:07 - mmengine - INFO - Epoch(train) [237][45/63] lr: 1.9350e-03 eta: 10:38:07 time: 0.5272 data_time: 0.0049 memory: 17620 loss: 2.1403 loss_prob: 1.2951 loss_thr: 0.6245 loss_db: 0.2207 2022/11/01 15:31:10 - mmengine - INFO - Epoch(train) [237][50/63] lr: 1.9350e-03 eta: 10:37:57 time: 0.5420 data_time: 0.0148 memory: 17620 loss: 2.0582 loss_prob: 1.2256 loss_thr: 0.6278 loss_db: 0.2048 2022/11/01 15:31:13 - mmengine - INFO - Epoch(train) [237][55/63] lr: 1.9350e-03 eta: 10:37:57 time: 0.5591 data_time: 0.0221 memory: 17620 loss: 2.1919 loss_prob: 1.3131 loss_thr: 0.6665 loss_db: 0.2123 2022/11/01 15:31:16 - mmengine - INFO - Epoch(train) [237][60/63] lr: 1.9350e-03 eta: 10:37:48 time: 0.5627 data_time: 0.0123 memory: 17620 loss: 2.2579 loss_prob: 1.3679 loss_thr: 0.6693 loss_db: 0.2207 2022/11/01 15:31:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:31:22 - mmengine - INFO - Epoch(train) [238][5/63] lr: 1.9332e-03 eta: 10:37:48 time: 0.8113 data_time: 0.2100 memory: 17620 loss: 1.9679 loss_prob: 1.1648 loss_thr: 0.6196 loss_db: 0.1834 2022/11/01 15:31:25 - mmengine - INFO - Epoch(train) [238][10/63] lr: 1.9332e-03 eta: 10:37:40 time: 0.8259 data_time: 0.2089 memory: 17620 loss: 1.9767 loss_prob: 1.1519 loss_thr: 0.6391 loss_db: 0.1857 2022/11/01 15:31:28 - mmengine - INFO - Epoch(train) [238][15/63] lr: 1.9332e-03 eta: 10:37:40 time: 0.5876 data_time: 0.0074 memory: 17620 loss: 2.0995 loss_prob: 1.2437 loss_thr: 0.6542 loss_db: 0.2016 2022/11/01 15:31:31 - mmengine - INFO - Epoch(train) [238][20/63] lr: 1.9332e-03 eta: 10:37:33 time: 0.6161 data_time: 0.0075 memory: 17620 loss: 2.1138 loss_prob: 1.2596 loss_thr: 0.6492 loss_db: 0.2050 2022/11/01 15:31:35 - mmengine - INFO - Epoch(train) [238][25/63] lr: 1.9332e-03 eta: 10:37:33 time: 0.6215 data_time: 0.0263 memory: 17620 loss: 2.1587 loss_prob: 1.2801 loss_thr: 0.6719 loss_db: 0.2068 2022/11/01 15:31:37 - mmengine - INFO - Epoch(train) [238][30/63] lr: 1.9332e-03 eta: 10:37:25 time: 0.5853 data_time: 0.0350 memory: 17620 loss: 2.2916 loss_prob: 1.3972 loss_thr: 0.6763 loss_db: 0.2180 2022/11/01 15:31:40 - mmengine - INFO - Epoch(train) [238][35/63] lr: 1.9332e-03 eta: 10:37:25 time: 0.5353 data_time: 0.0166 memory: 17620 loss: 2.2250 loss_prob: 1.3503 loss_thr: 0.6612 loss_db: 0.2135 2022/11/01 15:31:43 - mmengine - INFO - Epoch(train) [238][40/63] lr: 1.9332e-03 eta: 10:37:16 time: 0.5594 data_time: 0.0087 memory: 17620 loss: 2.1139 loss_prob: 1.2492 loss_thr: 0.6640 loss_db: 0.2006 2022/11/01 15:31:46 - mmengine - INFO - Epoch(train) [238][45/63] lr: 1.9332e-03 eta: 10:37:16 time: 0.5866 data_time: 0.0073 memory: 17620 loss: 2.2641 loss_prob: 1.3671 loss_thr: 0.6757 loss_db: 0.2214 2022/11/01 15:31:48 - mmengine - INFO - Epoch(train) [238][50/63] lr: 1.9332e-03 eta: 10:37:07 time: 0.5620 data_time: 0.0186 memory: 17620 loss: 2.2355 loss_prob: 1.3622 loss_thr: 0.6509 loss_db: 0.2225 2022/11/01 15:31:51 - mmengine - INFO - Epoch(train) [238][55/63] lr: 1.9332e-03 eta: 10:37:07 time: 0.5305 data_time: 0.0209 memory: 17620 loss: 1.9719 loss_prob: 1.1747 loss_thr: 0.6079 loss_db: 0.1892 2022/11/01 15:31:54 - mmengine - INFO - Epoch(train) [238][60/63] lr: 1.9332e-03 eta: 10:36:56 time: 0.5202 data_time: 0.0082 memory: 17620 loss: 2.0393 loss_prob: 1.2268 loss_thr: 0.6172 loss_db: 0.1954 2022/11/01 15:31:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:32:00 - mmengine - INFO - Epoch(train) [239][5/63] lr: 1.9314e-03 eta: 10:36:56 time: 0.6997 data_time: 0.2000 memory: 17620 loss: 2.1609 loss_prob: 1.2849 loss_thr: 0.6665 loss_db: 0.2095 2022/11/01 15:32:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:32:02 - mmengine - INFO - Epoch(train) [239][10/63] lr: 1.9314e-03 eta: 10:36:44 time: 0.7172 data_time: 0.2004 memory: 17620 loss: 2.1462 loss_prob: 1.2905 loss_thr: 0.6399 loss_db: 0.2159 2022/11/01 15:32:05 - mmengine - INFO - Epoch(train) [239][15/63] lr: 1.9314e-03 eta: 10:36:44 time: 0.5180 data_time: 0.0053 memory: 17620 loss: 2.1385 loss_prob: 1.3087 loss_thr: 0.6200 loss_db: 0.2098 2022/11/01 15:32:07 - mmengine - INFO - Epoch(train) [239][20/63] lr: 1.9314e-03 eta: 10:36:33 time: 0.5332 data_time: 0.0052 memory: 17620 loss: 2.0458 loss_prob: 1.2281 loss_thr: 0.6211 loss_db: 0.1965 2022/11/01 15:32:10 - mmengine - INFO - Epoch(train) [239][25/63] lr: 1.9314e-03 eta: 10:36:33 time: 0.5279 data_time: 0.0156 memory: 17620 loss: 2.0880 loss_prob: 1.2345 loss_thr: 0.6514 loss_db: 0.2020 2022/11/01 15:32:13 - mmengine - INFO - Epoch(train) [239][30/63] lr: 1.9314e-03 eta: 10:36:24 time: 0.5505 data_time: 0.0387 memory: 17620 loss: 2.0474 loss_prob: 1.2013 loss_thr: 0.6490 loss_db: 0.1971 2022/11/01 15:32:16 - mmengine - INFO - Epoch(train) [239][35/63] lr: 1.9314e-03 eta: 10:36:24 time: 0.5457 data_time: 0.0278 memory: 17620 loss: 2.0522 loss_prob: 1.2156 loss_thr: 0.6405 loss_db: 0.1961 2022/11/01 15:32:18 - mmengine - INFO - Epoch(train) [239][40/63] lr: 1.9314e-03 eta: 10:36:13 time: 0.5115 data_time: 0.0040 memory: 17620 loss: 2.0762 loss_prob: 1.2463 loss_thr: 0.6325 loss_db: 0.1975 2022/11/01 15:32:21 - mmengine - INFO - Epoch(train) [239][45/63] lr: 1.9314e-03 eta: 10:36:13 time: 0.5050 data_time: 0.0047 memory: 17620 loss: 2.0764 loss_prob: 1.2438 loss_thr: 0.6331 loss_db: 0.1995 2022/11/01 15:32:23 - mmengine - INFO - Epoch(train) [239][50/63] lr: 1.9314e-03 eta: 10:36:02 time: 0.5160 data_time: 0.0058 memory: 17620 loss: 2.2047 loss_prob: 1.3377 loss_thr: 0.6450 loss_db: 0.2220 2022/11/01 15:32:26 - mmengine - INFO - Epoch(train) [239][55/63] lr: 1.9314e-03 eta: 10:36:02 time: 0.5299 data_time: 0.0120 memory: 17620 loss: 2.1555 loss_prob: 1.3094 loss_thr: 0.6308 loss_db: 0.2153 2022/11/01 15:32:28 - mmengine - INFO - Epoch(train) [239][60/63] lr: 1.9314e-03 eta: 10:35:51 time: 0.5115 data_time: 0.0141 memory: 17620 loss: 2.2216 loss_prob: 1.3509 loss_thr: 0.6558 loss_db: 0.2149 2022/11/01 15:32:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:32:34 - mmengine - INFO - Epoch(train) [240][5/63] lr: 1.9296e-03 eta: 10:35:51 time: 0.7012 data_time: 0.1895 memory: 17620 loss: 2.6565 loss_prob: 1.6676 loss_thr: 0.7228 loss_db: 0.2660 2022/11/01 15:32:37 - mmengine - INFO - Epoch(train) [240][10/63] lr: 1.9296e-03 eta: 10:35:40 time: 0.7560 data_time: 0.1879 memory: 17620 loss: 2.2302 loss_prob: 1.3455 loss_thr: 0.6688 loss_db: 0.2160 2022/11/01 15:32:40 - mmengine - INFO - Epoch(train) [240][15/63] lr: 1.9296e-03 eta: 10:35:40 time: 0.5594 data_time: 0.0078 memory: 17620 loss: 2.1923 loss_prob: 1.3227 loss_thr: 0.6539 loss_db: 0.2156 2022/11/01 15:32:43 - mmengine - INFO - Epoch(train) [240][20/63] lr: 1.9296e-03 eta: 10:35:30 time: 0.5501 data_time: 0.0078 memory: 17620 loss: 2.1795 loss_prob: 1.3042 loss_thr: 0.6634 loss_db: 0.2119 2022/11/01 15:32:46 - mmengine - INFO - Epoch(train) [240][25/63] lr: 1.9296e-03 eta: 10:35:30 time: 0.5693 data_time: 0.0191 memory: 17620 loss: 2.2188 loss_prob: 1.3421 loss_thr: 0.6559 loss_db: 0.2208 2022/11/01 15:32:48 - mmengine - INFO - Epoch(train) [240][30/63] lr: 1.9296e-03 eta: 10:35:22 time: 0.5675 data_time: 0.0328 memory: 17620 loss: 2.1461 loss_prob: 1.2948 loss_thr: 0.6383 loss_db: 0.2131 2022/11/01 15:32:51 - mmengine - INFO - Epoch(train) [240][35/63] lr: 1.9296e-03 eta: 10:35:22 time: 0.5307 data_time: 0.0181 memory: 17620 loss: 2.2526 loss_prob: 1.3781 loss_thr: 0.6526 loss_db: 0.2219 2022/11/01 15:32:54 - mmengine - INFO - Epoch(train) [240][40/63] lr: 1.9296e-03 eta: 10:35:11 time: 0.5278 data_time: 0.0047 memory: 17620 loss: 2.3929 loss_prob: 1.4947 loss_thr: 0.6603 loss_db: 0.2379 2022/11/01 15:32:56 - mmengine - INFO - Epoch(train) [240][45/63] lr: 1.9296e-03 eta: 10:35:11 time: 0.5261 data_time: 0.0068 memory: 17620 loss: 2.1044 loss_prob: 1.2609 loss_thr: 0.6432 loss_db: 0.2003 2022/11/01 15:32:59 - mmengine - INFO - Epoch(train) [240][50/63] lr: 1.9296e-03 eta: 10:35:01 time: 0.5204 data_time: 0.0130 memory: 17620 loss: 1.9990 loss_prob: 1.1757 loss_thr: 0.6370 loss_db: 0.1863 2022/11/01 15:33:02 - mmengine - INFO - Epoch(train) [240][55/63] lr: 1.9296e-03 eta: 10:35:01 time: 0.5407 data_time: 0.0197 memory: 17620 loss: 2.0388 loss_prob: 1.2175 loss_thr: 0.6273 loss_db: 0.1941 2022/11/01 15:33:04 - mmengine - INFO - Epoch(train) [240][60/63] lr: 1.9296e-03 eta: 10:34:50 time: 0.5295 data_time: 0.0145 memory: 17620 loss: 2.1001 loss_prob: 1.2679 loss_thr: 0.6270 loss_db: 0.2052 2022/11/01 15:33:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:33:06 - mmengine - INFO - Saving checkpoint at 240 epochs 2022/11/01 15:33:13 - mmengine - INFO - Epoch(val) [240][5/32] eta: 10:34:50 time: 0.5668 data_time: 0.0760 memory: 17620 2022/11/01 15:33:16 - mmengine - INFO - Epoch(val) [240][10/32] eta: 0:00:14 time: 0.6448 data_time: 0.1075 memory: 15725 2022/11/01 15:33:18 - mmengine - INFO - Epoch(val) [240][15/32] eta: 0:00:14 time: 0.5665 data_time: 0.0463 memory: 15725 2022/11/01 15:33:21 - mmengine - INFO - Epoch(val) [240][20/32] eta: 0:00:06 time: 0.5712 data_time: 0.0547 memory: 15725 2022/11/01 15:33:24 - mmengine - INFO - Epoch(val) [240][25/32] eta: 0:00:06 time: 0.5889 data_time: 0.0607 memory: 15725 2022/11/01 15:33:27 - mmengine - INFO - Epoch(val) [240][30/32] eta: 0:00:01 time: 0.5438 data_time: 0.0230 memory: 15725 2022/11/01 15:33:27 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.7684, precision: 0.7406, hmean: 0.7543 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.7684, precision: 0.8147, hmean: 0.7909 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.7607, precision: 0.8686, hmean: 0.8111 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.7381, precision: 0.9007, hmean: 0.8113 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.6716, precision: 0.9331, hmean: 0.7811 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.2990, precision: 0.9826, hmean: 0.4585 2022/11/01 15:33:28 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 15:33:28 - mmengine - INFO - Epoch(val) [240][32/32] icdar/precision: 0.9007 icdar/recall: 0.7381 icdar/hmean: 0.8113 2022/11/01 15:33:33 - mmengine - INFO - Epoch(train) [241][5/63] lr: 1.9278e-03 eta: 0:00:01 time: 0.7386 data_time: 0.2011 memory: 17620 loss: 1.9606 loss_prob: 1.1882 loss_thr: 0.5857 loss_db: 0.1867 2022/11/01 15:33:35 - mmengine - INFO - Epoch(train) [241][10/63] lr: 1.9278e-03 eta: 10:34:40 time: 0.7700 data_time: 0.1999 memory: 17620 loss: 2.0443 loss_prob: 1.2357 loss_thr: 0.6151 loss_db: 0.1935 2022/11/01 15:33:38 - mmengine - INFO - Epoch(train) [241][15/63] lr: 1.9278e-03 eta: 10:34:40 time: 0.5631 data_time: 0.0090 memory: 17620 loss: 1.9920 loss_prob: 1.1637 loss_thr: 0.6483 loss_db: 0.1799 2022/11/01 15:33:41 - mmengine - INFO - Epoch(train) [241][20/63] lr: 1.9278e-03 eta: 10:34:32 time: 0.5728 data_time: 0.0093 memory: 17620 loss: 1.9692 loss_prob: 1.1380 loss_thr: 0.6516 loss_db: 0.1796 2022/11/01 15:33:44 - mmengine - INFO - Epoch(train) [241][25/63] lr: 1.9278e-03 eta: 10:34:32 time: 0.5751 data_time: 0.0107 memory: 17620 loss: 2.1330 loss_prob: 1.2748 loss_thr: 0.6478 loss_db: 0.2104 2022/11/01 15:33:47 - mmengine - INFO - Epoch(train) [241][30/63] lr: 1.9278e-03 eta: 10:34:25 time: 0.6289 data_time: 0.0346 memory: 17620 loss: 2.1105 loss_prob: 1.2717 loss_thr: 0.6317 loss_db: 0.2071 2022/11/01 15:33:50 - mmengine - INFO - Epoch(train) [241][35/63] lr: 1.9278e-03 eta: 10:34:25 time: 0.6128 data_time: 0.0288 memory: 17620 loss: 1.9727 loss_prob: 1.1553 loss_thr: 0.6265 loss_db: 0.1909 2022/11/01 15:33:53 - mmengine - INFO - Epoch(train) [241][40/63] lr: 1.9278e-03 eta: 10:34:17 time: 0.5717 data_time: 0.0093 memory: 17620 loss: 1.9538 loss_prob: 1.1356 loss_thr: 0.6290 loss_db: 0.1892 2022/11/01 15:33:56 - mmengine - INFO - Epoch(train) [241][45/63] lr: 1.9278e-03 eta: 10:34:17 time: 0.5747 data_time: 0.0092 memory: 17620 loss: 2.0293 loss_prob: 1.2022 loss_thr: 0.6315 loss_db: 0.1956 2022/11/01 15:33:59 - mmengine - INFO - Epoch(train) [241][50/63] lr: 1.9278e-03 eta: 10:34:08 time: 0.5602 data_time: 0.0154 memory: 17620 loss: 2.0544 loss_prob: 1.2319 loss_thr: 0.6239 loss_db: 0.1985 2022/11/01 15:34:02 - mmengine - INFO - Epoch(train) [241][55/63] lr: 1.9278e-03 eta: 10:34:08 time: 0.5800 data_time: 0.0202 memory: 17620 loss: 2.1719 loss_prob: 1.3148 loss_thr: 0.6457 loss_db: 0.2114 2022/11/01 15:34:04 - mmengine - INFO - Epoch(train) [241][60/63] lr: 1.9278e-03 eta: 10:33:59 time: 0.5624 data_time: 0.0106 memory: 17620 loss: 2.2357 loss_prob: 1.3449 loss_thr: 0.6767 loss_db: 0.2140 2022/11/01 15:34:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:34:10 - mmengine - INFO - Epoch(train) [242][5/63] lr: 1.9260e-03 eta: 10:33:59 time: 0.7239 data_time: 0.2147 memory: 17620 loss: 2.0537 loss_prob: 1.2048 loss_thr: 0.6491 loss_db: 0.1998 2022/11/01 15:34:14 - mmengine - INFO - Epoch(train) [242][10/63] lr: 1.9260e-03 eta: 10:33:50 time: 0.8001 data_time: 0.2153 memory: 17620 loss: 2.1159 loss_prob: 1.2553 loss_thr: 0.6611 loss_db: 0.1994 2022/11/01 15:34:17 - mmengine - INFO - Epoch(train) [242][15/63] lr: 1.9260e-03 eta: 10:33:50 time: 0.6106 data_time: 0.0081 memory: 17620 loss: 2.2627 loss_prob: 1.3901 loss_thr: 0.6535 loss_db: 0.2190 2022/11/01 15:34:19 - mmengine - INFO - Epoch(train) [242][20/63] lr: 1.9260e-03 eta: 10:33:41 time: 0.5612 data_time: 0.0059 memory: 17620 loss: 2.2626 loss_prob: 1.3836 loss_thr: 0.6571 loss_db: 0.2219 2022/11/01 15:34:22 - mmengine - INFO - Epoch(train) [242][25/63] lr: 1.9260e-03 eta: 10:33:41 time: 0.5336 data_time: 0.0183 memory: 17620 loss: 2.0966 loss_prob: 1.2366 loss_thr: 0.6597 loss_db: 0.2004 2022/11/01 15:34:25 - mmengine - INFO - Epoch(train) [242][30/63] lr: 1.9260e-03 eta: 10:33:32 time: 0.5666 data_time: 0.0393 memory: 17620 loss: 1.9402 loss_prob: 1.1270 loss_thr: 0.6315 loss_db: 0.1817 2022/11/01 15:34:28 - mmengine - INFO - Epoch(train) [242][35/63] lr: 1.9260e-03 eta: 10:33:32 time: 0.5805 data_time: 0.0278 memory: 17620 loss: 1.9921 loss_prob: 1.1654 loss_thr: 0.6383 loss_db: 0.1884 2022/11/01 15:34:30 - mmengine - INFO - Epoch(train) [242][40/63] lr: 1.9260e-03 eta: 10:33:22 time: 0.5384 data_time: 0.0057 memory: 17620 loss: 1.9740 loss_prob: 1.1357 loss_thr: 0.6526 loss_db: 0.1857 2022/11/01 15:34:33 - mmengine - INFO - Epoch(train) [242][45/63] lr: 1.9260e-03 eta: 10:33:22 time: 0.5133 data_time: 0.0043 memory: 17620 loss: 2.3476 loss_prob: 1.4432 loss_thr: 0.6766 loss_db: 0.2278 2022/11/01 15:34:36 - mmengine - INFO - Epoch(train) [242][50/63] lr: 1.9260e-03 eta: 10:33:12 time: 0.5381 data_time: 0.0187 memory: 17620 loss: 2.4243 loss_prob: 1.5107 loss_thr: 0.6776 loss_db: 0.2360 2022/11/01 15:34:39 - mmengine - INFO - Epoch(train) [242][55/63] lr: 1.9260e-03 eta: 10:33:12 time: 0.5724 data_time: 0.0226 memory: 17620 loss: 2.1507 loss_prob: 1.2962 loss_thr: 0.6511 loss_db: 0.2034 2022/11/01 15:34:41 - mmengine - INFO - Epoch(train) [242][60/63] lr: 1.9260e-03 eta: 10:33:02 time: 0.5417 data_time: 0.0084 memory: 17620 loss: 2.3472 loss_prob: 1.4777 loss_thr: 0.6437 loss_db: 0.2258 2022/11/01 15:34:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:34:47 - mmengine - INFO - Epoch(train) [243][5/63] lr: 1.9242e-03 eta: 10:33:02 time: 0.7026 data_time: 0.2230 memory: 17620 loss: 2.2210 loss_prob: 1.3538 loss_thr: 0.6558 loss_db: 0.2114 2022/11/01 15:34:50 - mmengine - INFO - Epoch(train) [243][10/63] lr: 1.9242e-03 eta: 10:32:51 time: 0.7375 data_time: 0.2228 memory: 17620 loss: 2.2429 loss_prob: 1.3567 loss_thr: 0.6712 loss_db: 0.2150 2022/11/01 15:34:52 - mmengine - INFO - Epoch(train) [243][15/63] lr: 1.9242e-03 eta: 10:32:51 time: 0.5318 data_time: 0.0063 memory: 17620 loss: 2.1963 loss_prob: 1.3209 loss_thr: 0.6557 loss_db: 0.2197 2022/11/01 15:34:55 - mmengine - INFO - Epoch(train) [243][20/63] lr: 1.9242e-03 eta: 10:32:41 time: 0.5356 data_time: 0.0087 memory: 17620 loss: 2.1589 loss_prob: 1.3036 loss_thr: 0.6435 loss_db: 0.2118 2022/11/01 15:34:58 - mmengine - INFO - Epoch(train) [243][25/63] lr: 1.9242e-03 eta: 10:32:41 time: 0.5687 data_time: 0.0374 memory: 17620 loss: 1.9874 loss_prob: 1.1966 loss_thr: 0.6006 loss_db: 0.1902 2022/11/01 15:35:01 - mmengine - INFO - Epoch(train) [243][30/63] lr: 1.9242e-03 eta: 10:32:33 time: 0.5804 data_time: 0.0351 memory: 17620 loss: 2.1902 loss_prob: 1.3371 loss_thr: 0.6400 loss_db: 0.2131 2022/11/01 15:35:04 - mmengine - INFO - Epoch(train) [243][35/63] lr: 1.9242e-03 eta: 10:32:33 time: 0.5427 data_time: 0.0047 memory: 17620 loss: 2.2974 loss_prob: 1.4085 loss_thr: 0.6680 loss_db: 0.2209 2022/11/01 15:35:06 - mmengine - INFO - Epoch(train) [243][40/63] lr: 1.9242e-03 eta: 10:32:22 time: 0.5277 data_time: 0.0058 memory: 17620 loss: 2.1865 loss_prob: 1.3142 loss_thr: 0.6628 loss_db: 0.2096 2022/11/01 15:35:09 - mmengine - INFO - Epoch(train) [243][45/63] lr: 1.9242e-03 eta: 10:32:22 time: 0.5213 data_time: 0.0076 memory: 17620 loss: 2.0598 loss_prob: 1.2168 loss_thr: 0.6475 loss_db: 0.1955 2022/11/01 15:35:11 - mmengine - INFO - Epoch(train) [243][50/63] lr: 1.9242e-03 eta: 10:32:12 time: 0.5294 data_time: 0.0243 memory: 17620 loss: 2.1253 loss_prob: 1.2645 loss_thr: 0.6536 loss_db: 0.2073 2022/11/01 15:35:14 - mmengine - INFO - Epoch(train) [243][55/63] lr: 1.9242e-03 eta: 10:32:12 time: 0.5244 data_time: 0.0225 memory: 17620 loss: 2.2400 loss_prob: 1.3541 loss_thr: 0.6644 loss_db: 0.2215 2022/11/01 15:35:17 - mmengine - INFO - Epoch(train) [243][60/63] lr: 1.9242e-03 eta: 10:32:02 time: 0.5318 data_time: 0.0049 memory: 17620 loss: 2.0452 loss_prob: 1.2208 loss_thr: 0.6281 loss_db: 0.1962 2022/11/01 15:35:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:35:23 - mmengine - INFO - Epoch(train) [244][5/63] lr: 1.9224e-03 eta: 10:32:02 time: 0.7397 data_time: 0.2150 memory: 17620 loss: 1.9656 loss_prob: 1.1278 loss_thr: 0.6537 loss_db: 0.1841 2022/11/01 15:35:26 - mmengine - INFO - Epoch(train) [244][10/63] lr: 1.9224e-03 eta: 10:31:52 time: 0.7732 data_time: 0.2144 memory: 17620 loss: 1.9785 loss_prob: 1.1650 loss_thr: 0.6238 loss_db: 0.1897 2022/11/01 15:35:29 - mmengine - INFO - Epoch(train) [244][15/63] lr: 1.9224e-03 eta: 10:31:52 time: 0.5477 data_time: 0.0052 memory: 17620 loss: 2.1419 loss_prob: 1.3026 loss_thr: 0.6333 loss_db: 0.2060 2022/11/01 15:35:32 - mmengine - INFO - Epoch(train) [244][20/63] lr: 1.9224e-03 eta: 10:31:44 time: 0.5706 data_time: 0.0104 memory: 17620 loss: 2.1659 loss_prob: 1.2995 loss_thr: 0.6604 loss_db: 0.2060 2022/11/01 15:35:34 - mmengine - INFO - Epoch(train) [244][25/63] lr: 1.9224e-03 eta: 10:31:44 time: 0.5905 data_time: 0.0177 memory: 17620 loss: 2.1403 loss_prob: 1.2754 loss_thr: 0.6572 loss_db: 0.2077 2022/11/01 15:35:37 - mmengine - INFO - Epoch(train) [244][30/63] lr: 1.9224e-03 eta: 10:31:35 time: 0.5622 data_time: 0.0283 memory: 17620 loss: 2.2119 loss_prob: 1.3468 loss_thr: 0.6520 loss_db: 0.2132 2022/11/01 15:35:40 - mmengine - INFO - Epoch(train) [244][35/63] lr: 1.9224e-03 eta: 10:31:35 time: 0.5414 data_time: 0.0205 memory: 17620 loss: 2.1145 loss_prob: 1.2665 loss_thr: 0.6500 loss_db: 0.1980 2022/11/01 15:35:42 - mmengine - INFO - Epoch(train) [244][40/63] lr: 1.9224e-03 eta: 10:31:24 time: 0.5227 data_time: 0.0061 memory: 17620 loss: 2.0703 loss_prob: 1.2173 loss_thr: 0.6557 loss_db: 0.1972 2022/11/01 15:35:45 - mmengine - INFO - Epoch(train) [244][45/63] lr: 1.9224e-03 eta: 10:31:24 time: 0.5136 data_time: 0.0112 memory: 17620 loss: 2.0011 loss_prob: 1.1816 loss_thr: 0.6272 loss_db: 0.1923 2022/11/01 15:35:48 - mmengine - INFO - Epoch(train) [244][50/63] lr: 1.9224e-03 eta: 10:31:14 time: 0.5266 data_time: 0.0158 memory: 17620 loss: 2.1309 loss_prob: 1.2953 loss_thr: 0.6278 loss_db: 0.2077 2022/11/01 15:35:50 - mmengine - INFO - Epoch(train) [244][55/63] lr: 1.9224e-03 eta: 10:31:14 time: 0.5350 data_time: 0.0187 memory: 17620 loss: 2.2325 loss_prob: 1.3645 loss_thr: 0.6480 loss_db: 0.2199 2022/11/01 15:35:53 - mmengine - INFO - Epoch(train) [244][60/63] lr: 1.9224e-03 eta: 10:31:04 time: 0.5308 data_time: 0.0124 memory: 17620 loss: 1.9882 loss_prob: 1.1755 loss_thr: 0.6196 loss_db: 0.1931 2022/11/01 15:35:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:36:00 - mmengine - INFO - Epoch(train) [245][5/63] lr: 1.9205e-03 eta: 10:31:04 time: 0.7929 data_time: 0.1837 memory: 17620 loss: 2.0645 loss_prob: 1.2306 loss_thr: 0.6319 loss_db: 0.2019 2022/11/01 15:36:02 - mmengine - INFO - Epoch(train) [245][10/63] lr: 1.9205e-03 eta: 10:30:56 time: 0.8142 data_time: 0.1832 memory: 17620 loss: 2.0258 loss_prob: 1.2004 loss_thr: 0.6334 loss_db: 0.1920 2022/11/01 15:36:05 - mmengine - INFO - Epoch(train) [245][15/63] lr: 1.9205e-03 eta: 10:30:56 time: 0.5499 data_time: 0.0049 memory: 17620 loss: 1.9976 loss_prob: 1.1783 loss_thr: 0.6276 loss_db: 0.1917 2022/11/01 15:36:08 - mmengine - INFO - Epoch(train) [245][20/63] lr: 1.9205e-03 eta: 10:30:46 time: 0.5555 data_time: 0.0059 memory: 17620 loss: 2.1440 loss_prob: 1.3017 loss_thr: 0.6278 loss_db: 0.2145 2022/11/01 15:36:11 - mmengine - INFO - Epoch(train) [245][25/63] lr: 1.9205e-03 eta: 10:30:46 time: 0.5531 data_time: 0.0100 memory: 17620 loss: 2.3268 loss_prob: 1.4436 loss_thr: 0.6459 loss_db: 0.2373 2022/11/01 15:36:14 - mmengine - INFO - Epoch(train) [245][30/63] lr: 1.9205e-03 eta: 10:30:38 time: 0.5796 data_time: 0.0368 memory: 17620 loss: 2.1601 loss_prob: 1.3088 loss_thr: 0.6416 loss_db: 0.2098 2022/11/01 15:36:17 - mmengine - INFO - Epoch(train) [245][35/63] lr: 1.9205e-03 eta: 10:30:38 time: 0.5650 data_time: 0.0344 memory: 17620 loss: 1.9968 loss_prob: 1.1746 loss_thr: 0.6316 loss_db: 0.1907 2022/11/01 15:36:19 - mmengine - INFO - Epoch(train) [245][40/63] lr: 1.9205e-03 eta: 10:30:29 time: 0.5427 data_time: 0.0066 memory: 17620 loss: 2.0255 loss_prob: 1.1939 loss_thr: 0.6374 loss_db: 0.1942 2022/11/01 15:36:22 - mmengine - INFO - Epoch(train) [245][45/63] lr: 1.9205e-03 eta: 10:30:29 time: 0.5294 data_time: 0.0041 memory: 17620 loss: 2.0153 loss_prob: 1.1934 loss_thr: 0.6345 loss_db: 0.1875 2022/11/01 15:36:25 - mmengine - INFO - Epoch(train) [245][50/63] lr: 1.9205e-03 eta: 10:30:20 time: 0.5596 data_time: 0.0095 memory: 17620 loss: 2.0511 loss_prob: 1.2330 loss_thr: 0.6274 loss_db: 0.1906 2022/11/01 15:36:28 - mmengine - INFO - Epoch(train) [245][55/63] lr: 1.9205e-03 eta: 10:30:20 time: 0.5883 data_time: 0.0236 memory: 17620 loss: 2.1516 loss_prob: 1.3060 loss_thr: 0.6419 loss_db: 0.2037 2022/11/01 15:36:30 - mmengine - INFO - Epoch(train) [245][60/63] lr: 1.9205e-03 eta: 10:30:10 time: 0.5494 data_time: 0.0184 memory: 17620 loss: 2.1512 loss_prob: 1.3096 loss_thr: 0.6349 loss_db: 0.2068 2022/11/01 15:36:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:36:37 - mmengine - INFO - Epoch(train) [246][5/63] lr: 1.9187e-03 eta: 10:30:10 time: 0.7238 data_time: 0.1876 memory: 17620 loss: 2.1766 loss_prob: 1.3172 loss_thr: 0.6526 loss_db: 0.2067 2022/11/01 15:36:39 - mmengine - INFO - Epoch(train) [246][10/63] lr: 1.9187e-03 eta: 10:30:00 time: 0.7736 data_time: 0.1913 memory: 17620 loss: 2.1567 loss_prob: 1.2922 loss_thr: 0.6618 loss_db: 0.2027 2022/11/01 15:36:43 - mmengine - INFO - Epoch(train) [246][15/63] lr: 1.9187e-03 eta: 10:30:00 time: 0.6638 data_time: 0.0131 memory: 17620 loss: 2.0073 loss_prob: 1.1865 loss_thr: 0.6376 loss_db: 0.1832 2022/11/01 15:36:46 - mmengine - INFO - Epoch(train) [246][20/63] lr: 1.9187e-03 eta: 10:29:55 time: 0.6563 data_time: 0.0095 memory: 17620 loss: 1.9768 loss_prob: 1.1701 loss_thr: 0.6213 loss_db: 0.1854 2022/11/01 15:36:49 - mmengine - INFO - Epoch(train) [246][25/63] lr: 1.9187e-03 eta: 10:29:55 time: 0.5793 data_time: 0.0075 memory: 17620 loss: 1.9063 loss_prob: 1.1182 loss_thr: 0.6101 loss_db: 0.1780 2022/11/01 15:36:52 - mmengine - INFO - Epoch(train) [246][30/63] lr: 1.9187e-03 eta: 10:29:47 time: 0.5897 data_time: 0.0263 memory: 17620 loss: 2.0669 loss_prob: 1.2305 loss_thr: 0.6436 loss_db: 0.1928 2022/11/01 15:36:54 - mmengine - INFO - Epoch(train) [246][35/63] lr: 1.9187e-03 eta: 10:29:47 time: 0.5546 data_time: 0.0273 memory: 17620 loss: 2.0917 loss_prob: 1.2391 loss_thr: 0.6545 loss_db: 0.1982 2022/11/01 15:36:57 - mmengine - INFO - Epoch(train) [246][40/63] lr: 1.9187e-03 eta: 10:29:37 time: 0.5252 data_time: 0.0115 memory: 17620 loss: 2.0467 loss_prob: 1.2088 loss_thr: 0.6448 loss_db: 0.1932 2022/11/01 15:37:00 - mmengine - INFO - Epoch(train) [246][45/63] lr: 1.9187e-03 eta: 10:29:37 time: 0.5139 data_time: 0.0090 memory: 17620 loss: 2.1351 loss_prob: 1.2830 loss_thr: 0.6510 loss_db: 0.2011 2022/11/01 15:37:02 - mmengine - INFO - Epoch(train) [246][50/63] lr: 1.9187e-03 eta: 10:29:26 time: 0.5133 data_time: 0.0125 memory: 17620 loss: 2.2074 loss_prob: 1.3505 loss_thr: 0.6389 loss_db: 0.2180 2022/11/01 15:37:05 - mmengine - INFO - Epoch(train) [246][55/63] lr: 1.9187e-03 eta: 10:29:26 time: 0.5263 data_time: 0.0174 memory: 17620 loss: 2.2209 loss_prob: 1.3631 loss_thr: 0.6350 loss_db: 0.2227 2022/11/01 15:37:08 - mmengine - INFO - Epoch(train) [246][60/63] lr: 1.9187e-03 eta: 10:29:17 time: 0.5393 data_time: 0.0135 memory: 17620 loss: 2.0477 loss_prob: 1.2269 loss_thr: 0.6293 loss_db: 0.1915 2022/11/01 15:37:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:37:14 - mmengine - INFO - Epoch(train) [247][5/63] lr: 1.9169e-03 eta: 10:29:17 time: 0.7075 data_time: 0.1751 memory: 17620 loss: 2.0379 loss_prob: 1.1860 loss_thr: 0.6625 loss_db: 0.1895 2022/11/01 15:37:16 - mmengine - INFO - Epoch(train) [247][10/63] lr: 1.9169e-03 eta: 10:29:06 time: 0.7568 data_time: 0.1879 memory: 17620 loss: 2.1459 loss_prob: 1.2828 loss_thr: 0.6591 loss_db: 0.2039 2022/11/01 15:37:19 - mmengine - INFO - Epoch(train) [247][15/63] lr: 1.9169e-03 eta: 10:29:06 time: 0.5354 data_time: 0.0185 memory: 17620 loss: 2.0632 loss_prob: 1.2354 loss_thr: 0.6294 loss_db: 0.1984 2022/11/01 15:37:22 - mmengine - INFO - Epoch(train) [247][20/63] lr: 1.9169e-03 eta: 10:28:55 time: 0.5105 data_time: 0.0049 memory: 17620 loss: 1.9720 loss_prob: 1.1678 loss_thr: 0.6131 loss_db: 0.1911 2022/11/01 15:37:24 - mmengine - INFO - Epoch(train) [247][25/63] lr: 1.9169e-03 eta: 10:28:55 time: 0.5385 data_time: 0.0171 memory: 17620 loss: 2.1379 loss_prob: 1.3080 loss_thr: 0.6214 loss_db: 0.2085 2022/11/01 15:37:27 - mmengine - INFO - Epoch(train) [247][30/63] lr: 1.9169e-03 eta: 10:28:46 time: 0.5458 data_time: 0.0297 memory: 17620 loss: 2.2329 loss_prob: 1.3713 loss_thr: 0.6442 loss_db: 0.2174 2022/11/01 15:37:30 - mmengine - INFO - Epoch(train) [247][35/63] lr: 1.9169e-03 eta: 10:28:46 time: 0.5131 data_time: 0.0200 memory: 17620 loss: 2.1788 loss_prob: 1.3025 loss_thr: 0.6661 loss_db: 0.2102 2022/11/01 15:37:32 - mmengine - INFO - Epoch(train) [247][40/63] lr: 1.9169e-03 eta: 10:28:35 time: 0.5095 data_time: 0.0076 memory: 17620 loss: 2.2999 loss_prob: 1.3936 loss_thr: 0.6782 loss_db: 0.2281 2022/11/01 15:37:35 - mmengine - INFO - Epoch(train) [247][45/63] lr: 1.9169e-03 eta: 10:28:35 time: 0.5281 data_time: 0.0047 memory: 17620 loss: 2.2598 loss_prob: 1.3751 loss_thr: 0.6645 loss_db: 0.2202 2022/11/01 15:37:38 - mmengine - INFO - Epoch(train) [247][50/63] lr: 1.9169e-03 eta: 10:28:26 time: 0.5504 data_time: 0.0180 memory: 17620 loss: 2.0577 loss_prob: 1.2308 loss_thr: 0.6313 loss_db: 0.1956 2022/11/01 15:37:40 - mmengine - INFO - Epoch(train) [247][55/63] lr: 1.9169e-03 eta: 10:28:26 time: 0.5431 data_time: 0.0241 memory: 17620 loss: 2.0470 loss_prob: 1.2245 loss_thr: 0.6244 loss_db: 0.1980 2022/11/01 15:37:43 - mmengine - INFO - Epoch(train) [247][60/63] lr: 1.9169e-03 eta: 10:28:15 time: 0.5212 data_time: 0.0140 memory: 17620 loss: 2.1061 loss_prob: 1.2676 loss_thr: 0.6299 loss_db: 0.2086 2022/11/01 15:37:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:37:49 - mmengine - INFO - Epoch(train) [248][5/63] lr: 1.9151e-03 eta: 10:28:15 time: 0.7092 data_time: 0.2165 memory: 17620 loss: 2.1414 loss_prob: 1.2699 loss_thr: 0.6676 loss_db: 0.2039 2022/11/01 15:37:52 - mmengine - INFO - Epoch(train) [248][10/63] lr: 1.9151e-03 eta: 10:28:05 time: 0.7653 data_time: 0.2200 memory: 17620 loss: 2.3195 loss_prob: 1.4130 loss_thr: 0.6789 loss_db: 0.2277 2022/11/01 15:37:54 - mmengine - INFO - Epoch(train) [248][15/63] lr: 1.9151e-03 eta: 10:28:05 time: 0.5402 data_time: 0.0086 memory: 17620 loss: 2.1021 loss_prob: 1.2635 loss_thr: 0.6344 loss_db: 0.2041 2022/11/01 15:37:57 - mmengine - INFO - Epoch(train) [248][20/63] lr: 1.9151e-03 eta: 10:27:54 time: 0.5106 data_time: 0.0053 memory: 17620 loss: 1.9281 loss_prob: 1.1402 loss_thr: 0.6049 loss_db: 0.1829 2022/11/01 15:38:00 - mmengine - INFO - Epoch(train) [248][25/63] lr: 1.9151e-03 eta: 10:27:54 time: 0.5393 data_time: 0.0133 memory: 17620 loss: 2.1800 loss_prob: 1.3159 loss_thr: 0.6552 loss_db: 0.2089 2022/11/01 15:38:03 - mmengine - INFO - Epoch(train) [248][30/63] lr: 1.9151e-03 eta: 10:27:45 time: 0.5606 data_time: 0.0350 memory: 17620 loss: 2.1731 loss_prob: 1.2944 loss_thr: 0.6715 loss_db: 0.2072 2022/11/01 15:38:05 - mmengine - INFO - Epoch(train) [248][35/63] lr: 1.9151e-03 eta: 10:27:45 time: 0.5272 data_time: 0.0264 memory: 17620 loss: 2.1214 loss_prob: 1.2725 loss_thr: 0.6476 loss_db: 0.2014 2022/11/01 15:38:08 - mmengine - INFO - Epoch(train) [248][40/63] lr: 1.9151e-03 eta: 10:27:34 time: 0.5035 data_time: 0.0058 memory: 17620 loss: 2.1076 loss_prob: 1.2673 loss_thr: 0.6387 loss_db: 0.2016 2022/11/01 15:38:10 - mmengine - INFO - Epoch(train) [248][45/63] lr: 1.9151e-03 eta: 10:27:34 time: 0.5083 data_time: 0.0065 memory: 17620 loss: 1.9691 loss_prob: 1.1611 loss_thr: 0.6200 loss_db: 0.1880 2022/11/01 15:38:13 - mmengine - INFO - Epoch(train) [248][50/63] lr: 1.9151e-03 eta: 10:27:25 time: 0.5415 data_time: 0.0219 memory: 17620 loss: 2.0261 loss_prob: 1.2171 loss_thr: 0.6145 loss_db: 0.1945 2022/11/01 15:38:16 - mmengine - INFO - Epoch(train) [248][55/63] lr: 1.9151e-03 eta: 10:27:25 time: 0.5424 data_time: 0.0212 memory: 17620 loss: 2.0592 loss_prob: 1.2360 loss_thr: 0.6252 loss_db: 0.1980 2022/11/01 15:38:18 - mmengine - INFO - Epoch(train) [248][60/63] lr: 1.9151e-03 eta: 10:27:14 time: 0.5136 data_time: 0.0043 memory: 17620 loss: 2.0073 loss_prob: 1.1878 loss_thr: 0.6276 loss_db: 0.1918 2022/11/01 15:38:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:38:25 - mmengine - INFO - Epoch(train) [249][5/63] lr: 1.9133e-03 eta: 10:27:14 time: 0.7561 data_time: 0.2411 memory: 17620 loss: 2.0790 loss_prob: 1.2334 loss_thr: 0.6469 loss_db: 0.1987 2022/11/01 15:38:27 - mmengine - INFO - Epoch(train) [249][10/63] lr: 1.9133e-03 eta: 10:27:05 time: 0.7935 data_time: 0.2419 memory: 17620 loss: 2.3374 loss_prob: 1.4207 loss_thr: 0.6883 loss_db: 0.2284 2022/11/01 15:38:31 - mmengine - INFO - Epoch(train) [249][15/63] lr: 1.9133e-03 eta: 10:27:05 time: 0.5855 data_time: 0.0072 memory: 17620 loss: 2.2267 loss_prob: 1.3459 loss_thr: 0.6619 loss_db: 0.2190 2022/11/01 15:38:33 - mmengine - INFO - Epoch(train) [249][20/63] lr: 1.9133e-03 eta: 10:26:58 time: 0.6071 data_time: 0.0075 memory: 17620 loss: 2.0263 loss_prob: 1.2060 loss_thr: 0.6220 loss_db: 0.1983 2022/11/01 15:38:36 - mmengine - INFO - Epoch(train) [249][25/63] lr: 1.9133e-03 eta: 10:26:58 time: 0.5817 data_time: 0.0161 memory: 17620 loss: 2.0087 loss_prob: 1.1881 loss_thr: 0.6289 loss_db: 0.1917 2022/11/01 15:38:39 - mmengine - INFO - Epoch(train) [249][30/63] lr: 1.9133e-03 eta: 10:26:50 time: 0.5921 data_time: 0.0284 memory: 17620 loss: 1.9069 loss_prob: 1.1104 loss_thr: 0.6203 loss_db: 0.1762 2022/11/01 15:38:42 - mmengine - INFO - Epoch(train) [249][35/63] lr: 1.9133e-03 eta: 10:26:50 time: 0.5557 data_time: 0.0221 memory: 17620 loss: 1.9237 loss_prob: 1.1191 loss_thr: 0.6231 loss_db: 0.1815 2022/11/01 15:38:45 - mmengine - INFO - Epoch(train) [249][40/63] lr: 1.9133e-03 eta: 10:26:41 time: 0.5329 data_time: 0.0131 memory: 17620 loss: 2.0381 loss_prob: 1.2220 loss_thr: 0.6199 loss_db: 0.1962 2022/11/01 15:38:48 - mmengine - INFO - Epoch(train) [249][45/63] lr: 1.9133e-03 eta: 10:26:41 time: 0.5869 data_time: 0.0109 memory: 17620 loss: 2.0691 loss_prob: 1.2613 loss_thr: 0.6070 loss_db: 0.2008 2022/11/01 15:38:51 - mmengine - INFO - Epoch(train) [249][50/63] lr: 1.9133e-03 eta: 10:26:34 time: 0.6237 data_time: 0.0202 memory: 17620 loss: 2.0998 loss_prob: 1.2848 loss_thr: 0.6154 loss_db: 0.1996 2022/11/01 15:38:54 - mmengine - INFO - Epoch(train) [249][55/63] lr: 1.9133e-03 eta: 10:26:34 time: 0.6332 data_time: 0.0196 memory: 17620 loss: 2.0736 loss_prob: 1.2566 loss_thr: 0.6237 loss_db: 0.1932 2022/11/01 15:38:57 - mmengine - INFO - Epoch(train) [249][60/63] lr: 1.9133e-03 eta: 10:26:26 time: 0.5878 data_time: 0.0064 memory: 17620 loss: 1.8964 loss_prob: 1.0934 loss_thr: 0.6278 loss_db: 0.1752 2022/11/01 15:38:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:39:03 - mmengine - INFO - Epoch(train) [250][5/63] lr: 1.9115e-03 eta: 10:26:26 time: 0.7001 data_time: 0.2004 memory: 17620 loss: 2.1626 loss_prob: 1.2964 loss_thr: 0.6593 loss_db: 0.2069 2022/11/01 15:39:05 - mmengine - INFO - Epoch(train) [250][10/63] lr: 1.9115e-03 eta: 10:26:15 time: 0.7280 data_time: 0.1969 memory: 17620 loss: 2.1252 loss_prob: 1.2716 loss_thr: 0.6530 loss_db: 0.2006 2022/11/01 15:39:08 - mmengine - INFO - Epoch(train) [250][15/63] lr: 1.9115e-03 eta: 10:26:15 time: 0.5475 data_time: 0.0090 memory: 17620 loss: 1.9064 loss_prob: 1.1184 loss_thr: 0.6081 loss_db: 0.1798 2022/11/01 15:39:11 - mmengine - INFO - Epoch(train) [250][20/63] lr: 1.9115e-03 eta: 10:26:06 time: 0.5473 data_time: 0.0100 memory: 17620 loss: 1.9343 loss_prob: 1.1143 loss_thr: 0.6392 loss_db: 0.1808 2022/11/01 15:39:14 - mmengine - INFO - Epoch(train) [250][25/63] lr: 1.9115e-03 eta: 10:26:06 time: 0.5477 data_time: 0.0225 memory: 17620 loss: 1.9426 loss_prob: 1.1115 loss_thr: 0.6502 loss_db: 0.1808 2022/11/01 15:39:17 - mmengine - INFO - Epoch(train) [250][30/63] lr: 1.9115e-03 eta: 10:25:57 time: 0.5705 data_time: 0.0321 memory: 17620 loss: 1.9170 loss_prob: 1.1192 loss_thr: 0.6150 loss_db: 0.1829 2022/11/01 15:39:19 - mmengine - INFO - Epoch(train) [250][35/63] lr: 1.9115e-03 eta: 10:25:57 time: 0.5729 data_time: 0.0197 memory: 17620 loss: 2.1189 loss_prob: 1.2787 loss_thr: 0.6269 loss_db: 0.2133 2022/11/01 15:39:22 - mmengine - INFO - Epoch(train) [250][40/63] lr: 1.9115e-03 eta: 10:25:48 time: 0.5645 data_time: 0.0103 memory: 17620 loss: 2.2536 loss_prob: 1.3571 loss_thr: 0.6692 loss_db: 0.2274 2022/11/01 15:39:25 - mmengine - INFO - Epoch(train) [250][45/63] lr: 1.9115e-03 eta: 10:25:48 time: 0.5598 data_time: 0.0074 memory: 17620 loss: 2.1624 loss_prob: 1.2880 loss_thr: 0.6648 loss_db: 0.2096 2022/11/01 15:39:28 - mmengine - INFO - Epoch(train) [250][50/63] lr: 1.9115e-03 eta: 10:25:40 time: 0.5684 data_time: 0.0230 memory: 17620 loss: 2.2240 loss_prob: 1.3607 loss_thr: 0.6488 loss_db: 0.2144 2022/11/01 15:39:30 - mmengine - INFO - Epoch(train) [250][55/63] lr: 1.9115e-03 eta: 10:25:40 time: 0.5434 data_time: 0.0236 memory: 17620 loss: 2.1983 loss_prob: 1.3319 loss_thr: 0.6551 loss_db: 0.2113 2022/11/01 15:39:33 - mmengine - INFO - Epoch(train) [250][60/63] lr: 1.9115e-03 eta: 10:25:29 time: 0.4982 data_time: 0.0067 memory: 17620 loss: 2.3397 loss_prob: 1.4449 loss_thr: 0.6606 loss_db: 0.2342 2022/11/01 15:39:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:39:39 - mmengine - INFO - Epoch(train) [251][5/63] lr: 1.9097e-03 eta: 10:25:29 time: 0.6772 data_time: 0.1742 memory: 17620 loss: 2.3737 loss_prob: 1.4768 loss_thr: 0.6619 loss_db: 0.2350 2022/11/01 15:39:41 - mmengine - INFO - Epoch(train) [251][10/63] lr: 1.9097e-03 eta: 10:25:17 time: 0.7081 data_time: 0.1755 memory: 17620 loss: 2.4335 loss_prob: 1.4938 loss_thr: 0.6995 loss_db: 0.2402 2022/11/01 15:39:44 - mmengine - INFO - Epoch(train) [251][15/63] lr: 1.9097e-03 eta: 10:25:17 time: 0.5182 data_time: 0.0107 memory: 17620 loss: 2.2843 loss_prob: 1.3788 loss_thr: 0.6857 loss_db: 0.2198 2022/11/01 15:39:47 - mmengine - INFO - Epoch(train) [251][20/63] lr: 1.9097e-03 eta: 10:25:06 time: 0.5227 data_time: 0.0104 memory: 17620 loss: 2.0312 loss_prob: 1.2116 loss_thr: 0.6309 loss_db: 0.1887 2022/11/01 15:39:49 - mmengine - INFO - Epoch(train) [251][25/63] lr: 1.9097e-03 eta: 10:25:06 time: 0.5612 data_time: 0.0261 memory: 17620 loss: 2.1461 loss_prob: 1.2911 loss_thr: 0.6528 loss_db: 0.2022 2022/11/01 15:39:52 - mmengine - INFO - Epoch(train) [251][30/63] lr: 1.9097e-03 eta: 10:24:57 time: 0.5524 data_time: 0.0263 memory: 17620 loss: 2.1166 loss_prob: 1.2705 loss_thr: 0.6389 loss_db: 0.2071 2022/11/01 15:39:55 - mmengine - INFO - Epoch(train) [251][35/63] lr: 1.9097e-03 eta: 10:24:57 time: 0.5270 data_time: 0.0067 memory: 17620 loss: 2.2569 loss_prob: 1.3802 loss_thr: 0.6550 loss_db: 0.2217 2022/11/01 15:39:57 - mmengine - INFO - Epoch(train) [251][40/63] lr: 1.9097e-03 eta: 10:24:48 time: 0.5364 data_time: 0.0087 memory: 17620 loss: 2.4257 loss_prob: 1.5380 loss_thr: 0.6510 loss_db: 0.2367 2022/11/01 15:40:00 - mmengine - INFO - Epoch(train) [251][45/63] lr: 1.9097e-03 eta: 10:24:48 time: 0.5464 data_time: 0.0096 memory: 17620 loss: 2.3168 loss_prob: 1.4650 loss_thr: 0.6237 loss_db: 0.2281 2022/11/01 15:40:03 - mmengine - INFO - Epoch(train) [251][50/63] lr: 1.9097e-03 eta: 10:24:39 time: 0.5593 data_time: 0.0196 memory: 17620 loss: 2.2941 loss_prob: 1.4102 loss_thr: 0.6465 loss_db: 0.2374 2022/11/01 15:40:06 - mmengine - INFO - Epoch(train) [251][55/63] lr: 1.9097e-03 eta: 10:24:39 time: 0.5454 data_time: 0.0198 memory: 17620 loss: 2.3117 loss_prob: 1.4139 loss_thr: 0.6602 loss_db: 0.2376 2022/11/01 15:40:08 - mmengine - INFO - Epoch(train) [251][60/63] lr: 1.9097e-03 eta: 10:24:29 time: 0.5231 data_time: 0.0074 memory: 17620 loss: 2.3435 loss_prob: 1.4570 loss_thr: 0.6489 loss_db: 0.2376 2022/11/01 15:40:10 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:40:15 - mmengine - INFO - Epoch(train) [252][5/63] lr: 1.9079e-03 eta: 10:24:29 time: 0.7310 data_time: 0.1689 memory: 17620 loss: 2.1893 loss_prob: 1.3448 loss_thr: 0.6236 loss_db: 0.2209 2022/11/01 15:40:17 - mmengine - INFO - Epoch(train) [252][10/63] lr: 1.9079e-03 eta: 10:24:18 time: 0.7521 data_time: 0.1720 memory: 17620 loss: 2.2299 loss_prob: 1.3486 loss_thr: 0.6631 loss_db: 0.2182 2022/11/01 15:40:20 - mmengine - INFO - Epoch(train) [252][15/63] lr: 1.9079e-03 eta: 10:24:18 time: 0.5422 data_time: 0.0146 memory: 17620 loss: 2.1923 loss_prob: 1.3059 loss_thr: 0.6852 loss_db: 0.2012 2022/11/01 15:40:23 - mmengine - INFO - Epoch(train) [252][20/63] lr: 1.9079e-03 eta: 10:24:09 time: 0.5463 data_time: 0.0088 memory: 17620 loss: 2.2748 loss_prob: 1.3898 loss_thr: 0.6692 loss_db: 0.2158 2022/11/01 15:40:25 - mmengine - INFO - Epoch(train) [252][25/63] lr: 1.9079e-03 eta: 10:24:09 time: 0.5370 data_time: 0.0061 memory: 17620 loss: 2.3746 loss_prob: 1.4899 loss_thr: 0.6485 loss_db: 0.2362 2022/11/01 15:40:28 - mmengine - INFO - Epoch(train) [252][30/63] lr: 1.9079e-03 eta: 10:24:00 time: 0.5483 data_time: 0.0249 memory: 17620 loss: 2.2671 loss_prob: 1.4018 loss_thr: 0.6420 loss_db: 0.2233 2022/11/01 15:40:31 - mmengine - INFO - Epoch(train) [252][35/63] lr: 1.9079e-03 eta: 10:24:00 time: 0.5487 data_time: 0.0279 memory: 17620 loss: 2.1038 loss_prob: 1.2618 loss_thr: 0.6367 loss_db: 0.2052 2022/11/01 15:40:34 - mmengine - INFO - Epoch(train) [252][40/63] lr: 1.9079e-03 eta: 10:23:50 time: 0.5429 data_time: 0.0114 memory: 17620 loss: 2.2616 loss_prob: 1.4027 loss_thr: 0.6326 loss_db: 0.2263 2022/11/01 15:40:36 - mmengine - INFO - Epoch(train) [252][45/63] lr: 1.9079e-03 eta: 10:23:50 time: 0.5263 data_time: 0.0067 memory: 17620 loss: 2.2375 loss_prob: 1.3934 loss_thr: 0.6237 loss_db: 0.2204 2022/11/01 15:40:39 - mmengine - INFO - Epoch(train) [252][50/63] lr: 1.9079e-03 eta: 10:23:40 time: 0.5285 data_time: 0.0094 memory: 17620 loss: 2.0522 loss_prob: 1.2266 loss_thr: 0.6322 loss_db: 0.1933 2022/11/01 15:40:41 - mmengine - INFO - Epoch(train) [252][55/63] lr: 1.9079e-03 eta: 10:23:40 time: 0.5341 data_time: 0.0191 memory: 17620 loss: 2.0596 loss_prob: 1.2286 loss_thr: 0.6322 loss_db: 0.1988 2022/11/01 15:40:44 - mmengine - INFO - Epoch(train) [252][60/63] lr: 1.9079e-03 eta: 10:23:30 time: 0.5124 data_time: 0.0178 memory: 17620 loss: 2.2862 loss_prob: 1.4203 loss_thr: 0.6342 loss_db: 0.2317 2022/11/01 15:40:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:40:50 - mmengine - INFO - Epoch(train) [253][5/63] lr: 1.9061e-03 eta: 10:23:30 time: 0.7417 data_time: 0.2167 memory: 17620 loss: 2.5056 loss_prob: 1.5876 loss_thr: 0.6623 loss_db: 0.2556 2022/11/01 15:40:53 - mmengine - INFO - Epoch(train) [253][10/63] lr: 1.9061e-03 eta: 10:23:19 time: 0.7540 data_time: 0.2137 memory: 17620 loss: 2.3199 loss_prob: 1.4332 loss_thr: 0.6518 loss_db: 0.2349 2022/11/01 15:40:55 - mmengine - INFO - Epoch(train) [253][15/63] lr: 1.9061e-03 eta: 10:23:19 time: 0.5129 data_time: 0.0058 memory: 17620 loss: 2.1958 loss_prob: 1.3369 loss_thr: 0.6389 loss_db: 0.2200 2022/11/01 15:40:58 - mmengine - INFO - Epoch(train) [253][20/63] lr: 1.9061e-03 eta: 10:23:09 time: 0.5108 data_time: 0.0046 memory: 17620 loss: 2.2503 loss_prob: 1.3765 loss_thr: 0.6478 loss_db: 0.2260 2022/11/01 15:41:01 - mmengine - INFO - Epoch(train) [253][25/63] lr: 1.9061e-03 eta: 10:23:09 time: 0.5155 data_time: 0.0124 memory: 17620 loss: 2.0908 loss_prob: 1.2587 loss_thr: 0.6271 loss_db: 0.2050 2022/11/01 15:41:03 - mmengine - INFO - Epoch(train) [253][30/63] lr: 1.9061e-03 eta: 10:22:59 time: 0.5413 data_time: 0.0277 memory: 17620 loss: 2.1036 loss_prob: 1.2590 loss_thr: 0.6434 loss_db: 0.2011 2022/11/01 15:41:06 - mmengine - INFO - Epoch(train) [253][35/63] lr: 1.9061e-03 eta: 10:22:59 time: 0.5734 data_time: 0.0227 memory: 17620 loss: 2.1395 loss_prob: 1.2904 loss_thr: 0.6405 loss_db: 0.2086 2022/11/01 15:41:09 - mmengine - INFO - Epoch(train) [253][40/63] lr: 1.9061e-03 eta: 10:22:52 time: 0.5985 data_time: 0.0076 memory: 17620 loss: 1.9907 loss_prob: 1.1760 loss_thr: 0.6232 loss_db: 0.1915 2022/11/01 15:41:12 - mmengine - INFO - Epoch(train) [253][45/63] lr: 1.9061e-03 eta: 10:22:52 time: 0.5813 data_time: 0.0050 memory: 17620 loss: 2.0133 loss_prob: 1.1935 loss_thr: 0.6254 loss_db: 0.1944 2022/11/01 15:41:15 - mmengine - INFO - Epoch(train) [253][50/63] lr: 1.9061e-03 eta: 10:22:44 time: 0.5729 data_time: 0.0176 memory: 17620 loss: 2.2322 loss_prob: 1.3807 loss_thr: 0.6385 loss_db: 0.2129 2022/11/01 15:41:18 - mmengine - INFO - Epoch(train) [253][55/63] lr: 1.9061e-03 eta: 10:22:44 time: 0.5738 data_time: 0.0219 memory: 17620 loss: 2.1021 loss_prob: 1.2811 loss_thr: 0.6237 loss_db: 0.1973 2022/11/01 15:41:21 - mmengine - INFO - Epoch(train) [253][60/63] lr: 1.9061e-03 eta: 10:22:35 time: 0.5523 data_time: 0.0089 memory: 17620 loss: 2.0559 loss_prob: 1.2324 loss_thr: 0.6238 loss_db: 0.1997 2022/11/01 15:41:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:41:27 - mmengine - INFO - Epoch(train) [254][5/63] lr: 1.9043e-03 eta: 10:22:35 time: 0.7440 data_time: 0.1867 memory: 17620 loss: 2.2395 loss_prob: 1.3533 loss_thr: 0.6644 loss_db: 0.2217 2022/11/01 15:41:30 - mmengine - INFO - Epoch(train) [254][10/63] lr: 1.9043e-03 eta: 10:22:26 time: 0.7949 data_time: 0.2070 memory: 17620 loss: 2.1190 loss_prob: 1.2597 loss_thr: 0.6608 loss_db: 0.1984 2022/11/01 15:41:33 - mmengine - INFO - Epoch(train) [254][15/63] lr: 1.9043e-03 eta: 10:22:26 time: 0.5633 data_time: 0.0283 memory: 17620 loss: 2.0717 loss_prob: 1.2324 loss_thr: 0.6429 loss_db: 0.1964 2022/11/01 15:41:35 - mmengine - INFO - Epoch(train) [254][20/63] lr: 1.9043e-03 eta: 10:22:16 time: 0.5396 data_time: 0.0067 memory: 17620 loss: 2.0166 loss_prob: 1.1864 loss_thr: 0.6418 loss_db: 0.1883 2022/11/01 15:41:38 - mmengine - INFO - Epoch(train) [254][25/63] lr: 1.9043e-03 eta: 10:22:16 time: 0.5794 data_time: 0.0155 memory: 17620 loss: 2.1010 loss_prob: 1.2619 loss_thr: 0.6393 loss_db: 0.1999 2022/11/01 15:41:41 - mmengine - INFO - Epoch(train) [254][30/63] lr: 1.9043e-03 eta: 10:22:08 time: 0.5811 data_time: 0.0211 memory: 17620 loss: 2.0609 loss_prob: 1.2411 loss_thr: 0.6203 loss_db: 0.1995 2022/11/01 15:41:44 - mmengine - INFO - Epoch(train) [254][35/63] lr: 1.9043e-03 eta: 10:22:08 time: 0.5812 data_time: 0.0233 memory: 17620 loss: 2.0449 loss_prob: 1.2226 loss_thr: 0.6284 loss_db: 0.1939 2022/11/01 15:41:47 - mmengine - INFO - Epoch(train) [254][40/63] lr: 1.9043e-03 eta: 10:22:00 time: 0.5826 data_time: 0.0203 memory: 17620 loss: 2.0409 loss_prob: 1.2139 loss_thr: 0.6369 loss_db: 0.1901 2022/11/01 15:41:50 - mmengine - INFO - Epoch(train) [254][45/63] lr: 1.9043e-03 eta: 10:22:00 time: 0.5327 data_time: 0.0081 memory: 17620 loss: 1.9011 loss_prob: 1.1051 loss_thr: 0.6220 loss_db: 0.1740 2022/11/01 15:41:52 - mmengine - INFO - Epoch(train) [254][50/63] lr: 1.9043e-03 eta: 10:21:51 time: 0.5394 data_time: 0.0169 memory: 17620 loss: 1.8650 loss_prob: 1.0942 loss_thr: 0.5989 loss_db: 0.1720 2022/11/01 15:41:55 - mmengine - INFO - Epoch(train) [254][55/63] lr: 1.9043e-03 eta: 10:21:51 time: 0.5571 data_time: 0.0159 memory: 17620 loss: 1.9764 loss_prob: 1.1712 loss_thr: 0.6184 loss_db: 0.1868 2022/11/01 15:41:58 - mmengine - INFO - Epoch(train) [254][60/63] lr: 1.9043e-03 eta: 10:21:42 time: 0.5469 data_time: 0.0092 memory: 17620 loss: 2.1658 loss_prob: 1.3118 loss_thr: 0.6455 loss_db: 0.2085 2022/11/01 15:41:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:41:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:42:04 - mmengine - INFO - Epoch(train) [255][5/63] lr: 1.9024e-03 eta: 10:21:42 time: 0.7343 data_time: 0.2216 memory: 17620 loss: 1.9498 loss_prob: 1.1283 loss_thr: 0.6434 loss_db: 0.1781 2022/11/01 15:42:07 - mmengine - INFO - Epoch(train) [255][10/63] lr: 1.9024e-03 eta: 10:21:31 time: 0.7453 data_time: 0.2211 memory: 17620 loss: 2.0244 loss_prob: 1.1999 loss_thr: 0.6383 loss_db: 0.1861 2022/11/01 15:42:09 - mmengine - INFO - Epoch(train) [255][15/63] lr: 1.9024e-03 eta: 10:21:31 time: 0.5139 data_time: 0.0110 memory: 17620 loss: 2.0409 loss_prob: 1.2228 loss_thr: 0.6320 loss_db: 0.1861 2022/11/01 15:42:12 - mmengine - INFO - Epoch(train) [255][20/63] lr: 1.9024e-03 eta: 10:21:21 time: 0.5234 data_time: 0.0104 memory: 17620 loss: 2.0057 loss_prob: 1.2022 loss_thr: 0.6166 loss_db: 0.1870 2022/11/01 15:42:15 - mmengine - INFO - Epoch(train) [255][25/63] lr: 1.9024e-03 eta: 10:21:21 time: 0.5390 data_time: 0.0182 memory: 17620 loss: 1.9587 loss_prob: 1.1635 loss_thr: 0.6110 loss_db: 0.1841 2022/11/01 15:42:18 - mmengine - INFO - Epoch(train) [255][30/63] lr: 1.9024e-03 eta: 10:21:13 time: 0.5821 data_time: 0.0285 memory: 17620 loss: 2.0045 loss_prob: 1.2026 loss_thr: 0.6135 loss_db: 0.1884 2022/11/01 15:42:21 - mmengine - INFO - Epoch(train) [255][35/63] lr: 1.9024e-03 eta: 10:21:13 time: 0.5852 data_time: 0.0159 memory: 17620 loss: 2.0279 loss_prob: 1.2218 loss_thr: 0.6151 loss_db: 0.1910 2022/11/01 15:42:23 - mmengine - INFO - Epoch(train) [255][40/63] lr: 1.9024e-03 eta: 10:21:04 time: 0.5556 data_time: 0.0105 memory: 17620 loss: 1.9378 loss_prob: 1.1433 loss_thr: 0.6137 loss_db: 0.1808 2022/11/01 15:42:26 - mmengine - INFO - Epoch(train) [255][45/63] lr: 1.9024e-03 eta: 10:21:04 time: 0.5394 data_time: 0.0115 memory: 17620 loss: 1.9977 loss_prob: 1.1856 loss_thr: 0.6213 loss_db: 0.1908 2022/11/01 15:42:29 - mmengine - INFO - Epoch(train) [255][50/63] lr: 1.9024e-03 eta: 10:20:55 time: 0.5363 data_time: 0.0150 memory: 17620 loss: 2.0754 loss_prob: 1.2398 loss_thr: 0.6372 loss_db: 0.1984 2022/11/01 15:42:31 - mmengine - INFO - Epoch(train) [255][55/63] lr: 1.9024e-03 eta: 10:20:55 time: 0.5361 data_time: 0.0182 memory: 17620 loss: 2.0815 loss_prob: 1.2441 loss_thr: 0.6406 loss_db: 0.1968 2022/11/01 15:42:34 - mmengine - INFO - Epoch(train) [255][60/63] lr: 1.9024e-03 eta: 10:20:45 time: 0.5246 data_time: 0.0110 memory: 17620 loss: 2.0169 loss_prob: 1.1958 loss_thr: 0.6300 loss_db: 0.1912 2022/11/01 15:42:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:42:40 - mmengine - INFO - Epoch(train) [256][5/63] lr: 1.9006e-03 eta: 10:20:45 time: 0.6774 data_time: 0.1675 memory: 17620 loss: 2.0085 loss_prob: 1.1910 loss_thr: 0.6295 loss_db: 0.1880 2022/11/01 15:42:42 - mmengine - INFO - Epoch(train) [256][10/63] lr: 1.9006e-03 eta: 10:20:33 time: 0.7189 data_time: 0.1655 memory: 17620 loss: 1.9341 loss_prob: 1.1351 loss_thr: 0.6162 loss_db: 0.1828 2022/11/01 15:42:45 - mmengine - INFO - Epoch(train) [256][15/63] lr: 1.9006e-03 eta: 10:20:33 time: 0.5389 data_time: 0.0070 memory: 17620 loss: 1.9536 loss_prob: 1.1523 loss_thr: 0.6115 loss_db: 0.1897 2022/11/01 15:42:48 - mmengine - INFO - Epoch(train) [256][20/63] lr: 1.9006e-03 eta: 10:20:23 time: 0.5357 data_time: 0.0069 memory: 17620 loss: 2.0370 loss_prob: 1.2033 loss_thr: 0.6342 loss_db: 0.1996 2022/11/01 15:42:50 - mmengine - INFO - Epoch(train) [256][25/63] lr: 1.9006e-03 eta: 10:20:23 time: 0.5313 data_time: 0.0143 memory: 17620 loss: 2.0143 loss_prob: 1.1823 loss_thr: 0.6380 loss_db: 0.1941 2022/11/01 15:42:53 - mmengine - INFO - Epoch(train) [256][30/63] lr: 1.9006e-03 eta: 10:20:14 time: 0.5409 data_time: 0.0368 memory: 17620 loss: 2.0358 loss_prob: 1.2148 loss_thr: 0.6233 loss_db: 0.1977 2022/11/01 15:42:56 - mmengine - INFO - Epoch(train) [256][35/63] lr: 1.9006e-03 eta: 10:20:14 time: 0.5484 data_time: 0.0270 memory: 17620 loss: 1.9538 loss_prob: 1.1504 loss_thr: 0.6157 loss_db: 0.1877 2022/11/01 15:42:59 - mmengine - INFO - Epoch(train) [256][40/63] lr: 1.9006e-03 eta: 10:20:05 time: 0.5445 data_time: 0.0072 memory: 17620 loss: 1.9613 loss_prob: 1.1526 loss_thr: 0.6226 loss_db: 0.1861 2022/11/01 15:43:01 - mmengine - INFO - Epoch(train) [256][45/63] lr: 1.9006e-03 eta: 10:20:05 time: 0.5388 data_time: 0.0072 memory: 17620 loss: 2.0285 loss_prob: 1.2084 loss_thr: 0.6290 loss_db: 0.1911 2022/11/01 15:43:04 - mmengine - INFO - Epoch(train) [256][50/63] lr: 1.9006e-03 eta: 10:19:55 time: 0.5214 data_time: 0.0110 memory: 17620 loss: 2.0132 loss_prob: 1.1940 loss_thr: 0.6273 loss_db: 0.1919 2022/11/01 15:43:07 - mmengine - INFO - Epoch(train) [256][55/63] lr: 1.9006e-03 eta: 10:19:55 time: 0.5327 data_time: 0.0204 memory: 17620 loss: 1.9166 loss_prob: 1.1254 loss_thr: 0.6100 loss_db: 0.1811 2022/11/01 15:43:09 - mmengine - INFO - Epoch(train) [256][60/63] lr: 1.9006e-03 eta: 10:19:45 time: 0.5404 data_time: 0.0173 memory: 17620 loss: 1.9353 loss_prob: 1.1367 loss_thr: 0.6162 loss_db: 0.1823 2022/11/01 15:43:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:43:15 - mmengine - INFO - Epoch(train) [257][5/63] lr: 1.8988e-03 eta: 10:19:45 time: 0.6848 data_time: 0.1838 memory: 17620 loss: 1.8733 loss_prob: 1.0910 loss_thr: 0.6014 loss_db: 0.1809 2022/11/01 15:43:18 - mmengine - INFO - Epoch(train) [257][10/63] lr: 1.8988e-03 eta: 10:19:34 time: 0.7138 data_time: 0.1861 memory: 17620 loss: 1.9063 loss_prob: 1.1231 loss_thr: 0.5986 loss_db: 0.1846 2022/11/01 15:43:20 - mmengine - INFO - Epoch(train) [257][15/63] lr: 1.8988e-03 eta: 10:19:34 time: 0.5239 data_time: 0.0113 memory: 17620 loss: 1.9043 loss_prob: 1.1148 loss_thr: 0.6095 loss_db: 0.1800 2022/11/01 15:43:23 - mmengine - INFO - Epoch(train) [257][20/63] lr: 1.8988e-03 eta: 10:19:23 time: 0.5098 data_time: 0.0051 memory: 17620 loss: 1.9113 loss_prob: 1.1044 loss_thr: 0.6266 loss_db: 0.1804 2022/11/01 15:43:26 - mmengine - INFO - Epoch(train) [257][25/63] lr: 1.8988e-03 eta: 10:19:23 time: 0.5470 data_time: 0.0268 memory: 17620 loss: 1.8538 loss_prob: 1.0490 loss_thr: 0.6303 loss_db: 0.1746 2022/11/01 15:43:28 - mmengine - INFO - Epoch(train) [257][30/63] lr: 1.8988e-03 eta: 10:19:14 time: 0.5606 data_time: 0.0346 memory: 17620 loss: 2.0654 loss_prob: 1.2423 loss_thr: 0.6301 loss_db: 0.1930 2022/11/01 15:43:31 - mmengine - INFO - Epoch(train) [257][35/63] lr: 1.8988e-03 eta: 10:19:14 time: 0.5379 data_time: 0.0142 memory: 17620 loss: 2.0844 loss_prob: 1.2727 loss_thr: 0.6164 loss_db: 0.1953 2022/11/01 15:43:34 - mmengine - INFO - Epoch(train) [257][40/63] lr: 1.8988e-03 eta: 10:19:05 time: 0.5503 data_time: 0.0077 memory: 17620 loss: 1.8863 loss_prob: 1.1042 loss_thr: 0.6031 loss_db: 0.1790 2022/11/01 15:43:36 - mmengine - INFO - Epoch(train) [257][45/63] lr: 1.8988e-03 eta: 10:19:05 time: 0.5360 data_time: 0.0073 memory: 17620 loss: 2.0804 loss_prob: 1.2496 loss_thr: 0.6308 loss_db: 0.2001 2022/11/01 15:43:39 - mmengine - INFO - Epoch(train) [257][50/63] lr: 1.8988e-03 eta: 10:18:56 time: 0.5336 data_time: 0.0142 memory: 17620 loss: 2.0341 loss_prob: 1.2076 loss_thr: 0.6309 loss_db: 0.1956 2022/11/01 15:43:42 - mmengine - INFO - Epoch(train) [257][55/63] lr: 1.8988e-03 eta: 10:18:56 time: 0.5695 data_time: 0.0183 memory: 17620 loss: 2.0233 loss_prob: 1.2040 loss_thr: 0.6253 loss_db: 0.1940 2022/11/01 15:43:45 - mmengine - INFO - Epoch(train) [257][60/63] lr: 1.8988e-03 eta: 10:18:48 time: 0.5774 data_time: 0.0135 memory: 17620 loss: 2.1853 loss_prob: 1.3277 loss_thr: 0.6465 loss_db: 0.2110 2022/11/01 15:43:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:43:52 - mmengine - INFO - Epoch(train) [258][5/63] lr: 1.8970e-03 eta: 10:18:48 time: 0.7767 data_time: 0.1913 memory: 17620 loss: 2.0469 loss_prob: 1.2115 loss_thr: 0.6464 loss_db: 0.1891 2022/11/01 15:43:55 - mmengine - INFO - Epoch(train) [258][10/63] lr: 1.8970e-03 eta: 10:18:40 time: 0.8251 data_time: 0.1907 memory: 17620 loss: 2.0380 loss_prob: 1.2019 loss_thr: 0.6445 loss_db: 0.1915 2022/11/01 15:43:57 - mmengine - INFO - Epoch(train) [258][15/63] lr: 1.8970e-03 eta: 10:18:40 time: 0.5467 data_time: 0.0083 memory: 17620 loss: 2.1478 loss_prob: 1.2984 loss_thr: 0.6291 loss_db: 0.2204 2022/11/01 15:44:00 - mmengine - INFO - Epoch(train) [258][20/63] lr: 1.8970e-03 eta: 10:18:32 time: 0.5817 data_time: 0.0080 memory: 17620 loss: 2.0832 loss_prob: 1.2548 loss_thr: 0.6204 loss_db: 0.2080 2022/11/01 15:44:03 - mmengine - INFO - Epoch(train) [258][25/63] lr: 1.8970e-03 eta: 10:18:32 time: 0.6147 data_time: 0.0310 memory: 17620 loss: 2.1136 loss_prob: 1.2640 loss_thr: 0.6485 loss_db: 0.2011 2022/11/01 15:44:06 - mmengine - INFO - Epoch(train) [258][30/63] lr: 1.8970e-03 eta: 10:18:24 time: 0.5558 data_time: 0.0326 memory: 17620 loss: 2.1984 loss_prob: 1.3232 loss_thr: 0.6556 loss_db: 0.2195 2022/11/01 15:44:09 - mmengine - INFO - Epoch(train) [258][35/63] lr: 1.8970e-03 eta: 10:18:24 time: 0.5374 data_time: 0.0087 memory: 17620 loss: 2.2006 loss_prob: 1.3197 loss_thr: 0.6652 loss_db: 0.2156 2022/11/01 15:44:12 - mmengine - INFO - Epoch(train) [258][40/63] lr: 1.8970e-03 eta: 10:18:15 time: 0.5551 data_time: 0.0080 memory: 17620 loss: 2.2707 loss_prob: 1.3797 loss_thr: 0.6737 loss_db: 0.2173 2022/11/01 15:44:14 - mmengine - INFO - Epoch(train) [258][45/63] lr: 1.8970e-03 eta: 10:18:15 time: 0.5514 data_time: 0.0088 memory: 17620 loss: 2.2316 loss_prob: 1.3528 loss_thr: 0.6622 loss_db: 0.2166 2022/11/01 15:44:17 - mmengine - INFO - Epoch(train) [258][50/63] lr: 1.8970e-03 eta: 10:18:07 time: 0.5746 data_time: 0.0235 memory: 17620 loss: 2.2269 loss_prob: 1.3553 loss_thr: 0.6502 loss_db: 0.2215 2022/11/01 15:44:20 - mmengine - INFO - Epoch(train) [258][55/63] lr: 1.8970e-03 eta: 10:18:07 time: 0.5706 data_time: 0.0214 memory: 17620 loss: 2.2065 loss_prob: 1.3468 loss_thr: 0.6452 loss_db: 0.2145 2022/11/01 15:44:23 - mmengine - INFO - Epoch(train) [258][60/63] lr: 1.8970e-03 eta: 10:17:59 time: 0.5738 data_time: 0.0077 memory: 17620 loss: 2.1059 loss_prob: 1.2642 loss_thr: 0.6409 loss_db: 0.2007 2022/11/01 15:44:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:44:29 - mmengine - INFO - Epoch(train) [259][5/63] lr: 1.8952e-03 eta: 10:17:59 time: 0.7475 data_time: 0.1691 memory: 17620 loss: 2.0378 loss_prob: 1.2225 loss_thr: 0.6127 loss_db: 0.2026 2022/11/01 15:44:32 - mmengine - INFO - Epoch(train) [259][10/63] lr: 1.8952e-03 eta: 10:17:48 time: 0.7512 data_time: 0.1721 memory: 17620 loss: 2.0330 loss_prob: 1.2135 loss_thr: 0.6231 loss_db: 0.1964 2022/11/01 15:44:35 - mmengine - INFO - Epoch(train) [259][15/63] lr: 1.8952e-03 eta: 10:17:48 time: 0.5662 data_time: 0.0147 memory: 17620 loss: 2.1091 loss_prob: 1.2591 loss_thr: 0.6525 loss_db: 0.1976 2022/11/01 15:44:38 - mmengine - INFO - Epoch(train) [259][20/63] lr: 1.8952e-03 eta: 10:17:40 time: 0.5622 data_time: 0.0105 memory: 17620 loss: 2.0456 loss_prob: 1.2227 loss_thr: 0.6286 loss_db: 0.1943 2022/11/01 15:44:40 - mmengine - INFO - Epoch(train) [259][25/63] lr: 1.8952e-03 eta: 10:17:40 time: 0.5467 data_time: 0.0195 memory: 17620 loss: 2.2999 loss_prob: 1.4207 loss_thr: 0.6420 loss_db: 0.2373 2022/11/01 15:44:43 - mmengine - INFO - Epoch(train) [259][30/63] lr: 1.8952e-03 eta: 10:17:31 time: 0.5535 data_time: 0.0235 memory: 17620 loss: 2.7392 loss_prob: 1.7568 loss_thr: 0.6915 loss_db: 0.2909 2022/11/01 15:44:46 - mmengine - INFO - Epoch(train) [259][35/63] lr: 1.8952e-03 eta: 10:17:31 time: 0.5578 data_time: 0.0132 memory: 17620 loss: 2.3846 loss_prob: 1.4884 loss_thr: 0.6551 loss_db: 0.2411 2022/11/01 15:44:49 - mmengine - INFO - Epoch(train) [259][40/63] lr: 1.8952e-03 eta: 10:17:21 time: 0.5367 data_time: 0.0144 memory: 17620 loss: 2.0662 loss_prob: 1.2517 loss_thr: 0.6168 loss_db: 0.1977 2022/11/01 15:44:51 - mmengine - INFO - Epoch(train) [259][45/63] lr: 1.8952e-03 eta: 10:17:21 time: 0.5182 data_time: 0.0103 memory: 17620 loss: 2.3211 loss_prob: 1.4669 loss_thr: 0.6237 loss_db: 0.2305 2022/11/01 15:44:54 - mmengine - INFO - Epoch(train) [259][50/63] lr: 1.8952e-03 eta: 10:17:11 time: 0.5157 data_time: 0.0121 memory: 17620 loss: 2.5265 loss_prob: 1.6224 loss_thr: 0.6453 loss_db: 0.2588 2022/11/01 15:44:56 - mmengine - INFO - Epoch(train) [259][55/63] lr: 1.8952e-03 eta: 10:17:11 time: 0.5215 data_time: 0.0160 memory: 17620 loss: 2.3666 loss_prob: 1.4662 loss_thr: 0.6648 loss_db: 0.2356 2022/11/01 15:44:59 - mmengine - INFO - Epoch(train) [259][60/63] lr: 1.8952e-03 eta: 10:17:01 time: 0.5098 data_time: 0.0103 memory: 17620 loss: 2.1462 loss_prob: 1.2869 loss_thr: 0.6507 loss_db: 0.2086 2022/11/01 15:45:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:45:06 - mmengine - INFO - Epoch(train) [260][5/63] lr: 1.8934e-03 eta: 10:17:01 time: 0.7653 data_time: 0.2416 memory: 17620 loss: 2.0669 loss_prob: 1.2293 loss_thr: 0.6337 loss_db: 0.2040 2022/11/01 15:45:08 - mmengine - INFO - Epoch(train) [260][10/63] lr: 1.8934e-03 eta: 10:16:52 time: 0.7927 data_time: 0.2404 memory: 17620 loss: 2.0866 loss_prob: 1.2404 loss_thr: 0.6389 loss_db: 0.2073 2022/11/01 15:45:11 - mmengine - INFO - Epoch(train) [260][15/63] lr: 1.8934e-03 eta: 10:16:52 time: 0.5613 data_time: 0.0066 memory: 17620 loss: 1.9835 loss_prob: 1.1653 loss_thr: 0.6291 loss_db: 0.1891 2022/11/01 15:45:14 - mmengine - INFO - Epoch(train) [260][20/63] lr: 1.8934e-03 eta: 10:16:44 time: 0.5778 data_time: 0.0061 memory: 17620 loss: 1.9465 loss_prob: 1.1238 loss_thr: 0.6420 loss_db: 0.1807 2022/11/01 15:45:17 - mmengine - INFO - Epoch(train) [260][25/63] lr: 1.8934e-03 eta: 10:16:44 time: 0.5762 data_time: 0.0487 memory: 17620 loss: 2.0268 loss_prob: 1.1735 loss_thr: 0.6609 loss_db: 0.1924 2022/11/01 15:45:20 - mmengine - INFO - Epoch(train) [260][30/63] lr: 1.8934e-03 eta: 10:16:35 time: 0.5600 data_time: 0.0506 memory: 17620 loss: 2.0295 loss_prob: 1.2028 loss_thr: 0.6272 loss_db: 0.1995 2022/11/01 15:45:22 - mmengine - INFO - Epoch(train) [260][35/63] lr: 1.8934e-03 eta: 10:16:35 time: 0.5157 data_time: 0.0067 memory: 17620 loss: 2.0461 loss_prob: 1.2228 loss_thr: 0.6225 loss_db: 0.2007 2022/11/01 15:45:25 - mmengine - INFO - Epoch(train) [260][40/63] lr: 1.8934e-03 eta: 10:16:25 time: 0.5015 data_time: 0.0057 memory: 17620 loss: 2.2491 loss_prob: 1.3693 loss_thr: 0.6569 loss_db: 0.2230 2022/11/01 15:45:27 - mmengine - INFO - Epoch(train) [260][45/63] lr: 1.8934e-03 eta: 10:16:25 time: 0.5033 data_time: 0.0067 memory: 17620 loss: 2.2952 loss_prob: 1.4007 loss_thr: 0.6671 loss_db: 0.2274 2022/11/01 15:45:30 - mmengine - INFO - Epoch(train) [260][50/63] lr: 1.8934e-03 eta: 10:16:15 time: 0.5198 data_time: 0.0186 memory: 17620 loss: 2.1358 loss_prob: 1.2767 loss_thr: 0.6528 loss_db: 0.2063 2022/11/01 15:45:32 - mmengine - INFO - Epoch(train) [260][55/63] lr: 1.8934e-03 eta: 10:16:15 time: 0.5349 data_time: 0.0198 memory: 17620 loss: 1.8638 loss_prob: 1.0883 loss_thr: 0.6030 loss_db: 0.1725 2022/11/01 15:45:35 - mmengine - INFO - Epoch(train) [260][60/63] lr: 1.8934e-03 eta: 10:16:05 time: 0.5229 data_time: 0.0082 memory: 17620 loss: 1.9265 loss_prob: 1.1187 loss_thr: 0.6302 loss_db: 0.1776 2022/11/01 15:45:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:45:36 - mmengine - INFO - Saving checkpoint at 260 epochs 2022/11/01 15:45:43 - mmengine - INFO - Epoch(val) [260][5/32] eta: 10:16:05 time: 0.5881 data_time: 0.0933 memory: 17620 2022/11/01 15:45:46 - mmengine - INFO - Epoch(val) [260][10/32] eta: 0:00:14 time: 0.6439 data_time: 0.0978 memory: 15725 2022/11/01 15:45:49 - mmengine - INFO - Epoch(val) [260][15/32] eta: 0:00:14 time: 0.5826 data_time: 0.0426 memory: 15725 2022/11/01 15:45:52 - mmengine - INFO - Epoch(val) [260][20/32] eta: 0:00:07 time: 0.6008 data_time: 0.0647 memory: 15725 2022/11/01 15:45:55 - mmengine - INFO - Epoch(val) [260][25/32] eta: 0:00:07 time: 0.6068 data_time: 0.0684 memory: 15725 2022/11/01 15:45:58 - mmengine - INFO - Epoch(val) [260][30/32] eta: 0:00:01 time: 0.5766 data_time: 0.0488 memory: 15725 2022/11/01 15:45:59 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8262, precision: 0.6956, hmean: 0.7553 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8262, precision: 0.7836, hmean: 0.8043 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8228, precision: 0.8224, hmean: 0.8226 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8093, precision: 0.8621, hmean: 0.8349 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7655, precision: 0.9029, hmean: 0.8286 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.5344, precision: 0.9635, hmean: 0.6875 2022/11/01 15:45:59 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0005, precision: 1.0000, hmean: 0.0010 2022/11/01 15:45:59 - mmengine - INFO - Epoch(val) [260][32/32] icdar/precision: 0.8621 icdar/recall: 0.8093 icdar/hmean: 0.8349 2022/11/01 15:46:03 - mmengine - INFO - Epoch(train) [261][5/63] lr: 1.8916e-03 eta: 0:00:01 time: 0.6843 data_time: 0.1858 memory: 17620 loss: 2.0322 loss_prob: 1.1910 loss_thr: 0.6482 loss_db: 0.1930 2022/11/01 15:46:06 - mmengine - INFO - Epoch(train) [261][10/63] lr: 1.8916e-03 eta: 10:15:53 time: 0.7100 data_time: 0.1873 memory: 17620 loss: 2.2192 loss_prob: 1.3562 loss_thr: 0.6455 loss_db: 0.2175 2022/11/01 15:46:08 - mmengine - INFO - Epoch(train) [261][15/63] lr: 1.8916e-03 eta: 10:15:53 time: 0.5179 data_time: 0.0070 memory: 17620 loss: 2.1068 loss_prob: 1.2773 loss_thr: 0.6254 loss_db: 0.2042 2022/11/01 15:46:11 - mmengine - INFO - Epoch(train) [261][20/63] lr: 1.8916e-03 eta: 10:15:43 time: 0.5142 data_time: 0.0066 memory: 17620 loss: 2.0133 loss_prob: 1.1893 loss_thr: 0.6331 loss_db: 0.1910 2022/11/01 15:46:14 - mmengine - INFO - Epoch(train) [261][25/63] lr: 1.8916e-03 eta: 10:15:43 time: 0.5153 data_time: 0.0171 memory: 17620 loss: 2.2122 loss_prob: 1.3539 loss_thr: 0.6371 loss_db: 0.2212 2022/11/01 15:46:16 - mmengine - INFO - Epoch(train) [261][30/63] lr: 1.8916e-03 eta: 10:15:34 time: 0.5514 data_time: 0.0302 memory: 17620 loss: 2.1623 loss_prob: 1.3306 loss_thr: 0.6139 loss_db: 0.2178 2022/11/01 15:46:19 - mmengine - INFO - Epoch(train) [261][35/63] lr: 1.8916e-03 eta: 10:15:34 time: 0.5505 data_time: 0.0214 memory: 17620 loss: 2.2667 loss_prob: 1.3949 loss_thr: 0.6461 loss_db: 0.2257 2022/11/01 15:46:22 - mmengine - INFO - Epoch(train) [261][40/63] lr: 1.8916e-03 eta: 10:15:24 time: 0.5201 data_time: 0.0070 memory: 17620 loss: 2.4487 loss_prob: 1.5235 loss_thr: 0.6770 loss_db: 0.2482 2022/11/01 15:46:25 - mmengine - INFO - Epoch(train) [261][45/63] lr: 1.8916e-03 eta: 10:15:24 time: 0.5505 data_time: 0.0040 memory: 17620 loss: 2.2569 loss_prob: 1.3743 loss_thr: 0.6611 loss_db: 0.2215 2022/11/01 15:46:28 - mmengine - INFO - Epoch(train) [261][50/63] lr: 1.8916e-03 eta: 10:15:17 time: 0.5973 data_time: 0.0111 memory: 17620 loss: 2.2787 loss_prob: 1.3929 loss_thr: 0.6594 loss_db: 0.2265 2022/11/01 15:46:31 - mmengine - INFO - Epoch(train) [261][55/63] lr: 1.8916e-03 eta: 10:15:17 time: 0.6103 data_time: 0.0199 memory: 17620 loss: 2.4469 loss_prob: 1.5317 loss_thr: 0.6598 loss_db: 0.2554 2022/11/01 15:46:33 - mmengine - INFO - Epoch(train) [261][60/63] lr: 1.8916e-03 eta: 10:15:09 time: 0.5790 data_time: 0.0144 memory: 17620 loss: 2.3935 loss_prob: 1.4863 loss_thr: 0.6598 loss_db: 0.2474 2022/11/01 15:46:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:46:39 - mmengine - INFO - Epoch(train) [262][5/63] lr: 1.8898e-03 eta: 10:15:09 time: 0.6898 data_time: 0.1721 memory: 17620 loss: 2.1036 loss_prob: 1.2738 loss_thr: 0.6245 loss_db: 0.2053 2022/11/01 15:46:42 - mmengine - INFO - Epoch(train) [262][10/63] lr: 1.8898e-03 eta: 10:14:57 time: 0.7034 data_time: 0.1700 memory: 17620 loss: 2.2046 loss_prob: 1.3326 loss_thr: 0.6573 loss_db: 0.2147 2022/11/01 15:46:45 - mmengine - INFO - Epoch(train) [262][15/63] lr: 1.8898e-03 eta: 10:14:57 time: 0.5844 data_time: 0.0143 memory: 17620 loss: 2.2136 loss_prob: 1.3218 loss_thr: 0.6809 loss_db: 0.2110 2022/11/01 15:46:48 - mmengine - INFO - Epoch(train) [262][20/63] lr: 1.8898e-03 eta: 10:14:51 time: 0.6323 data_time: 0.0167 memory: 17620 loss: 2.0632 loss_prob: 1.2141 loss_thr: 0.6584 loss_db: 0.1908 2022/11/01 15:46:51 - mmengine - INFO - Epoch(train) [262][25/63] lr: 1.8898e-03 eta: 10:14:51 time: 0.6032 data_time: 0.0219 memory: 17620 loss: 1.9040 loss_prob: 1.1019 loss_thr: 0.6254 loss_db: 0.1767 2022/11/01 15:46:54 - mmengine - INFO - Epoch(train) [262][30/63] lr: 1.8898e-03 eta: 10:14:43 time: 0.5733 data_time: 0.0298 memory: 17620 loss: 1.9026 loss_prob: 1.1117 loss_thr: 0.6108 loss_db: 0.1801 2022/11/01 15:46:57 - mmengine - INFO - Epoch(train) [262][35/63] lr: 1.8898e-03 eta: 10:14:43 time: 0.5533 data_time: 0.0163 memory: 17620 loss: 2.1190 loss_prob: 1.2811 loss_thr: 0.6318 loss_db: 0.2061 2022/11/01 15:47:00 - mmengine - INFO - Epoch(train) [262][40/63] lr: 1.8898e-03 eta: 10:14:35 time: 0.5702 data_time: 0.0127 memory: 17620 loss: 2.0696 loss_prob: 1.2361 loss_thr: 0.6355 loss_db: 0.1980 2022/11/01 15:47:02 - mmengine - INFO - Epoch(train) [262][45/63] lr: 1.8898e-03 eta: 10:14:35 time: 0.5771 data_time: 0.0120 memory: 17620 loss: 1.8881 loss_prob: 1.0944 loss_thr: 0.6161 loss_db: 0.1776 2022/11/01 15:47:05 - mmengine - INFO - Epoch(train) [262][50/63] lr: 1.8898e-03 eta: 10:14:26 time: 0.5599 data_time: 0.0177 memory: 17620 loss: 1.9438 loss_prob: 1.1228 loss_thr: 0.6394 loss_db: 0.1816 2022/11/01 15:47:08 - mmengine - INFO - Epoch(train) [262][55/63] lr: 1.8898e-03 eta: 10:14:26 time: 0.5797 data_time: 0.0198 memory: 17620 loss: 2.1141 loss_prob: 1.2568 loss_thr: 0.6462 loss_db: 0.2112 2022/11/01 15:47:11 - mmengine - INFO - Epoch(train) [262][60/63] lr: 1.8898e-03 eta: 10:14:17 time: 0.5473 data_time: 0.0089 memory: 17620 loss: 2.2019 loss_prob: 1.3515 loss_thr: 0.6235 loss_db: 0.2268 2022/11/01 15:47:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:47:18 - mmengine - INFO - Epoch(train) [263][5/63] lr: 1.8879e-03 eta: 10:14:17 time: 0.7777 data_time: 0.2033 memory: 17620 loss: 2.2404 loss_prob: 1.3832 loss_thr: 0.6304 loss_db: 0.2267 2022/11/01 15:47:20 - mmengine - INFO - Epoch(train) [263][10/63] lr: 1.8879e-03 eta: 10:14:10 time: 0.8267 data_time: 0.2018 memory: 17620 loss: 2.1376 loss_prob: 1.3033 loss_thr: 0.6233 loss_db: 0.2109 2022/11/01 15:47:23 - mmengine - INFO - Epoch(train) [263][15/63] lr: 1.8879e-03 eta: 10:14:10 time: 0.5506 data_time: 0.0076 memory: 17620 loss: 2.0800 loss_prob: 1.2308 loss_thr: 0.6449 loss_db: 0.2043 2022/11/01 15:47:26 - mmengine - INFO - Epoch(train) [263][20/63] lr: 1.8879e-03 eta: 10:14:00 time: 0.5203 data_time: 0.0085 memory: 17620 loss: 2.0786 loss_prob: 1.2108 loss_thr: 0.6690 loss_db: 0.1989 2022/11/01 15:47:29 - mmengine - INFO - Epoch(train) [263][25/63] lr: 1.8879e-03 eta: 10:14:00 time: 0.5558 data_time: 0.0337 memory: 17620 loss: 1.9855 loss_prob: 1.1579 loss_thr: 0.6434 loss_db: 0.1842 2022/11/01 15:47:31 - mmengine - INFO - Epoch(train) [263][30/63] lr: 1.8879e-03 eta: 10:13:52 time: 0.5690 data_time: 0.0349 memory: 17620 loss: 1.9836 loss_prob: 1.1849 loss_thr: 0.6151 loss_db: 0.1836 2022/11/01 15:47:34 - mmengine - INFO - Epoch(train) [263][35/63] lr: 1.8879e-03 eta: 10:13:52 time: 0.5459 data_time: 0.0086 memory: 17620 loss: 2.0262 loss_prob: 1.1971 loss_thr: 0.6420 loss_db: 0.1871 2022/11/01 15:47:37 - mmengine - INFO - Epoch(train) [263][40/63] lr: 1.8879e-03 eta: 10:13:42 time: 0.5394 data_time: 0.0062 memory: 17620 loss: 2.1663 loss_prob: 1.2846 loss_thr: 0.6697 loss_db: 0.2121 2022/11/01 15:47:39 - mmengine - INFO - Epoch(train) [263][45/63] lr: 1.8879e-03 eta: 10:13:42 time: 0.5288 data_time: 0.0063 memory: 17620 loss: 2.1506 loss_prob: 1.2876 loss_thr: 0.6529 loss_db: 0.2101 2022/11/01 15:47:42 - mmengine - INFO - Epoch(train) [263][50/63] lr: 1.8879e-03 eta: 10:13:34 time: 0.5517 data_time: 0.0189 memory: 17620 loss: 1.9669 loss_prob: 1.1552 loss_thr: 0.6282 loss_db: 0.1836 2022/11/01 15:47:45 - mmengine - INFO - Epoch(train) [263][55/63] lr: 1.8879e-03 eta: 10:13:34 time: 0.5550 data_time: 0.0197 memory: 17620 loss: 1.9448 loss_prob: 1.1350 loss_thr: 0.6260 loss_db: 0.1839 2022/11/01 15:47:48 - mmengine - INFO - Epoch(train) [263][60/63] lr: 1.8879e-03 eta: 10:13:24 time: 0.5245 data_time: 0.0060 memory: 17620 loss: 1.9755 loss_prob: 1.1546 loss_thr: 0.6329 loss_db: 0.1880 2022/11/01 15:47:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:47:53 - mmengine - INFO - Epoch(train) [264][5/63] lr: 1.8861e-03 eta: 10:13:24 time: 0.6868 data_time: 0.1996 memory: 17620 loss: 1.9625 loss_prob: 1.1383 loss_thr: 0.6396 loss_db: 0.1847 2022/11/01 15:47:56 - mmengine - INFO - Epoch(train) [264][10/63] lr: 1.8861e-03 eta: 10:13:13 time: 0.7200 data_time: 0.2009 memory: 17620 loss: 1.9711 loss_prob: 1.1636 loss_thr: 0.6242 loss_db: 0.1833 2022/11/01 15:47:59 - mmengine - INFO - Epoch(train) [264][15/63] lr: 1.8861e-03 eta: 10:13:13 time: 0.5165 data_time: 0.0095 memory: 17620 loss: 2.1079 loss_prob: 1.2796 loss_thr: 0.6314 loss_db: 0.1969 2022/11/01 15:48:01 - mmengine - INFO - Epoch(train) [264][20/63] lr: 1.8861e-03 eta: 10:13:03 time: 0.5271 data_time: 0.0086 memory: 17620 loss: 2.0560 loss_prob: 1.2348 loss_thr: 0.6254 loss_db: 0.1958 2022/11/01 15:48:04 - mmengine - INFO - Epoch(train) [264][25/63] lr: 1.8861e-03 eta: 10:13:03 time: 0.5811 data_time: 0.0124 memory: 17620 loss: 1.9472 loss_prob: 1.1457 loss_thr: 0.6146 loss_db: 0.1870 2022/11/01 15:48:07 - mmengine - INFO - Epoch(train) [264][30/63] lr: 1.8861e-03 eta: 10:12:55 time: 0.5895 data_time: 0.0315 memory: 17620 loss: 1.9245 loss_prob: 1.1290 loss_thr: 0.6125 loss_db: 0.1830 2022/11/01 15:48:10 - mmengine - INFO - Epoch(train) [264][35/63] lr: 1.8861e-03 eta: 10:12:55 time: 0.5402 data_time: 0.0236 memory: 17620 loss: 1.8943 loss_prob: 1.1018 loss_thr: 0.6093 loss_db: 0.1831 2022/11/01 15:48:13 - mmengine - INFO - Epoch(train) [264][40/63] lr: 1.8861e-03 eta: 10:12:47 time: 0.5496 data_time: 0.0072 memory: 17620 loss: 1.9928 loss_prob: 1.1762 loss_thr: 0.6221 loss_db: 0.1945 2022/11/01 15:48:15 - mmengine - INFO - Epoch(train) [264][45/63] lr: 1.8861e-03 eta: 10:12:47 time: 0.5517 data_time: 0.0069 memory: 17620 loss: 1.9557 loss_prob: 1.1577 loss_thr: 0.6126 loss_db: 0.1854 2022/11/01 15:48:18 - mmengine - INFO - Epoch(train) [264][50/63] lr: 1.8861e-03 eta: 10:12:37 time: 0.5250 data_time: 0.0091 memory: 17620 loss: 2.0458 loss_prob: 1.2164 loss_thr: 0.6315 loss_db: 0.1979 2022/11/01 15:48:21 - mmengine - INFO - Epoch(train) [264][55/63] lr: 1.8861e-03 eta: 10:12:37 time: 0.5300 data_time: 0.0211 memory: 17620 loss: 2.0816 loss_prob: 1.2342 loss_thr: 0.6452 loss_db: 0.2022 2022/11/01 15:48:23 - mmengine - INFO - Epoch(train) [264][60/63] lr: 1.8861e-03 eta: 10:12:28 time: 0.5368 data_time: 0.0160 memory: 17620 loss: 2.0331 loss_prob: 1.2000 loss_thr: 0.6358 loss_db: 0.1972 2022/11/01 15:48:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:48:30 - mmengine - INFO - Epoch(train) [265][5/63] lr: 1.8843e-03 eta: 10:12:28 time: 0.7312 data_time: 0.2098 memory: 17620 loss: 2.0585 loss_prob: 1.2300 loss_thr: 0.6213 loss_db: 0.2071 2022/11/01 15:48:32 - mmengine - INFO - Epoch(train) [265][10/63] lr: 1.8843e-03 eta: 10:12:17 time: 0.7412 data_time: 0.2068 memory: 17620 loss: 2.1228 loss_prob: 1.2868 loss_thr: 0.6295 loss_db: 0.2065 2022/11/01 15:48:35 - mmengine - INFO - Epoch(train) [265][15/63] lr: 1.8843e-03 eta: 10:12:17 time: 0.5307 data_time: 0.0047 memory: 17620 loss: 2.2710 loss_prob: 1.3983 loss_thr: 0.6503 loss_db: 0.2225 2022/11/01 15:48:38 - mmengine - INFO - Epoch(train) [265][20/63] lr: 1.8843e-03 eta: 10:12:08 time: 0.5308 data_time: 0.0083 memory: 17620 loss: 2.2958 loss_prob: 1.4035 loss_thr: 0.6650 loss_db: 0.2273 2022/11/01 15:48:40 - mmengine - INFO - Epoch(train) [265][25/63] lr: 1.8843e-03 eta: 10:12:08 time: 0.5458 data_time: 0.0155 memory: 17620 loss: 2.3617 loss_prob: 1.4466 loss_thr: 0.6825 loss_db: 0.2326 2022/11/01 15:48:43 - mmengine - INFO - Epoch(train) [265][30/63] lr: 1.8843e-03 eta: 10:11:59 time: 0.5681 data_time: 0.0385 memory: 17620 loss: 2.2268 loss_prob: 1.3449 loss_thr: 0.6632 loss_db: 0.2187 2022/11/01 15:48:46 - mmengine - INFO - Epoch(train) [265][35/63] lr: 1.8843e-03 eta: 10:11:59 time: 0.5650 data_time: 0.0314 memory: 17620 loss: 1.9130 loss_prob: 1.1213 loss_thr: 0.6094 loss_db: 0.1823 2022/11/01 15:48:49 - mmengine - INFO - Epoch(train) [265][40/63] lr: 1.8843e-03 eta: 10:11:51 time: 0.5613 data_time: 0.0045 memory: 17620 loss: 1.8778 loss_prob: 1.0978 loss_thr: 0.6034 loss_db: 0.1765 2022/11/01 15:48:52 - mmengine - INFO - Epoch(train) [265][45/63] lr: 1.8843e-03 eta: 10:11:51 time: 0.5681 data_time: 0.0048 memory: 17620 loss: 1.9304 loss_prob: 1.1367 loss_thr: 0.6114 loss_db: 0.1823 2022/11/01 15:48:55 - mmengine - INFO - Epoch(train) [265][50/63] lr: 1.8843e-03 eta: 10:11:43 time: 0.5813 data_time: 0.0097 memory: 17620 loss: 1.9078 loss_prob: 1.1124 loss_thr: 0.6175 loss_db: 0.1779 2022/11/01 15:48:58 - mmengine - INFO - Epoch(train) [265][55/63] lr: 1.8843e-03 eta: 10:11:43 time: 0.6038 data_time: 0.0217 memory: 17620 loss: 2.0485 loss_prob: 1.1995 loss_thr: 0.6534 loss_db: 0.1956 2022/11/01 15:49:00 - mmengine - INFO - Epoch(train) [265][60/63] lr: 1.8843e-03 eta: 10:11:36 time: 0.5804 data_time: 0.0167 memory: 17620 loss: 2.3827 loss_prob: 1.4729 loss_thr: 0.6746 loss_db: 0.2352 2022/11/01 15:49:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:49:07 - mmengine - INFO - Epoch(train) [266][5/63] lr: 1.8825e-03 eta: 10:11:36 time: 0.8120 data_time: 0.2155 memory: 17620 loss: 2.1303 loss_prob: 1.2798 loss_thr: 0.6483 loss_db: 0.2022 2022/11/01 15:49:11 - mmengine - INFO - Epoch(train) [266][10/63] lr: 1.8825e-03 eta: 10:11:32 time: 0.9263 data_time: 0.2178 memory: 17620 loss: 2.0003 loss_prob: 1.1849 loss_thr: 0.6278 loss_db: 0.1877 2022/11/01 15:49:14 - mmengine - INFO - Epoch(train) [266][15/63] lr: 1.8825e-03 eta: 10:11:32 time: 0.6712 data_time: 0.0076 memory: 17620 loss: 1.7970 loss_prob: 1.0496 loss_thr: 0.5785 loss_db: 0.1688 2022/11/01 15:49:17 - mmengine - INFO - Epoch(train) [266][20/63] lr: 1.8825e-03 eta: 10:11:25 time: 0.6225 data_time: 0.0064 memory: 17620 loss: 1.9388 loss_prob: 1.1436 loss_thr: 0.6127 loss_db: 0.1824 2022/11/01 15:49:21 - mmengine - INFO - Epoch(train) [266][25/63] lr: 1.8825e-03 eta: 10:11:25 time: 0.6649 data_time: 0.0499 memory: 17620 loss: 1.8988 loss_prob: 1.0983 loss_thr: 0.6268 loss_db: 0.1737 2022/11/01 15:49:24 - mmengine - INFO - Epoch(train) [266][30/63] lr: 1.8825e-03 eta: 10:11:21 time: 0.6887 data_time: 0.0487 memory: 17620 loss: 1.9708 loss_prob: 1.1550 loss_thr: 0.6315 loss_db: 0.1843 2022/11/01 15:49:27 - mmengine - INFO - Epoch(train) [266][35/63] lr: 1.8825e-03 eta: 10:11:21 time: 0.6145 data_time: 0.0063 memory: 17620 loss: 1.9780 loss_prob: 1.1828 loss_thr: 0.6053 loss_db: 0.1899 2022/11/01 15:49:30 - mmengine - INFO - Epoch(train) [266][40/63] lr: 1.8825e-03 eta: 10:11:13 time: 0.5625 data_time: 0.0065 memory: 17620 loss: 2.0581 loss_prob: 1.2354 loss_thr: 0.6271 loss_db: 0.1956 2022/11/01 15:49:33 - mmengine - INFO - Epoch(train) [266][45/63] lr: 1.8825e-03 eta: 10:11:13 time: 0.6287 data_time: 0.0048 memory: 17620 loss: 2.2257 loss_prob: 1.3442 loss_thr: 0.6641 loss_db: 0.2173 2022/11/01 15:49:36 - mmengine - INFO - Epoch(train) [266][50/63] lr: 1.8825e-03 eta: 10:11:07 time: 0.6340 data_time: 0.0212 memory: 17620 loss: 2.0114 loss_prob: 1.2132 loss_thr: 0.5982 loss_db: 0.2000 2022/11/01 15:49:39 - mmengine - INFO - Epoch(train) [266][55/63] lr: 1.8825e-03 eta: 10:11:07 time: 0.5677 data_time: 0.0210 memory: 17620 loss: 1.8789 loss_prob: 1.1002 loss_thr: 0.6011 loss_db: 0.1777 2022/11/01 15:49:42 - mmengine - INFO - Epoch(train) [266][60/63] lr: 1.8825e-03 eta: 10:10:59 time: 0.5737 data_time: 0.0042 memory: 17620 loss: 1.9817 loss_prob: 1.1562 loss_thr: 0.6378 loss_db: 0.1878 2022/11/01 15:49:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:49:48 - mmengine - INFO - Epoch(train) [267][5/63] lr: 1.8807e-03 eta: 10:10:59 time: 0.7495 data_time: 0.2158 memory: 17620 loss: 1.8946 loss_prob: 1.1116 loss_thr: 0.5984 loss_db: 0.1847 2022/11/01 15:49:51 - mmengine - INFO - Epoch(train) [267][10/63] lr: 1.8807e-03 eta: 10:10:50 time: 0.7783 data_time: 0.2174 memory: 17620 loss: 2.0474 loss_prob: 1.2248 loss_thr: 0.6212 loss_db: 0.2014 2022/11/01 15:49:54 - mmengine - INFO - Epoch(train) [267][15/63] lr: 1.8807e-03 eta: 10:10:50 time: 0.5614 data_time: 0.0068 memory: 17620 loss: 2.0832 loss_prob: 1.2220 loss_thr: 0.6598 loss_db: 0.2014 2022/11/01 15:49:58 - mmengine - INFO - Epoch(train) [267][20/63] lr: 1.8807e-03 eta: 10:10:45 time: 0.6572 data_time: 0.0061 memory: 17620 loss: 1.9379 loss_prob: 1.1034 loss_thr: 0.6518 loss_db: 0.1827 2022/11/01 15:50:01 - mmengine - INFO - Epoch(train) [267][25/63] lr: 1.8807e-03 eta: 10:10:45 time: 0.6917 data_time: 0.0204 memory: 17620 loss: 1.9898 loss_prob: 1.1775 loss_thr: 0.6229 loss_db: 0.1893 2022/11/01 15:50:04 - mmengine - INFO - Epoch(train) [267][30/63] lr: 1.8807e-03 eta: 10:10:38 time: 0.6025 data_time: 0.0321 memory: 17620 loss: 2.1326 loss_prob: 1.3070 loss_thr: 0.6224 loss_db: 0.2033 2022/11/01 15:50:07 - mmengine - INFO - Epoch(train) [267][35/63] lr: 1.8807e-03 eta: 10:10:38 time: 0.5956 data_time: 0.0223 memory: 17620 loss: 2.0591 loss_prob: 1.2214 loss_thr: 0.6460 loss_db: 0.1917 2022/11/01 15:50:10 - mmengine - INFO - Epoch(train) [267][40/63] lr: 1.8807e-03 eta: 10:10:31 time: 0.6125 data_time: 0.0123 memory: 17620 loss: 1.9365 loss_prob: 1.1336 loss_thr: 0.6253 loss_db: 0.1775 2022/11/01 15:50:12 - mmengine - INFO - Epoch(train) [267][45/63] lr: 1.8807e-03 eta: 10:10:31 time: 0.5688 data_time: 0.0067 memory: 17620 loss: 1.8966 loss_prob: 1.1241 loss_thr: 0.5917 loss_db: 0.1808 2022/11/01 15:50:15 - mmengine - INFO - Epoch(train) [267][50/63] lr: 1.8807e-03 eta: 10:10:23 time: 0.5690 data_time: 0.0194 memory: 17620 loss: 1.8819 loss_prob: 1.1122 loss_thr: 0.5848 loss_db: 0.1849 2022/11/01 15:50:18 - mmengine - INFO - Epoch(train) [267][55/63] lr: 1.8807e-03 eta: 10:10:23 time: 0.5630 data_time: 0.0194 memory: 17620 loss: 1.7845 loss_prob: 1.0541 loss_thr: 0.5608 loss_db: 0.1697 2022/11/01 15:50:21 - mmengine - INFO - Epoch(train) [267][60/63] lr: 1.8807e-03 eta: 10:10:14 time: 0.5290 data_time: 0.0075 memory: 17620 loss: 1.8037 loss_prob: 1.0500 loss_thr: 0.5868 loss_db: 0.1669 2022/11/01 15:50:22 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:50:27 - mmengine - INFO - Epoch(train) [268][5/63] lr: 1.8789e-03 eta: 10:10:14 time: 0.7506 data_time: 0.1969 memory: 17620 loss: 2.2378 loss_prob: 1.3569 loss_thr: 0.6627 loss_db: 0.2183 2022/11/01 15:50:30 - mmengine - INFO - Epoch(train) [268][10/63] lr: 1.8789e-03 eta: 10:10:05 time: 0.7879 data_time: 0.1971 memory: 17620 loss: 2.2630 loss_prob: 1.3628 loss_thr: 0.6822 loss_db: 0.2180 2022/11/01 15:50:33 - mmengine - INFO - Epoch(train) [268][15/63] lr: 1.8789e-03 eta: 10:10:05 time: 0.5587 data_time: 0.0065 memory: 17620 loss: 2.0264 loss_prob: 1.1880 loss_thr: 0.6426 loss_db: 0.1958 2022/11/01 15:50:35 - mmengine - INFO - Epoch(train) [268][20/63] lr: 1.8789e-03 eta: 10:09:57 time: 0.5645 data_time: 0.0060 memory: 17620 loss: 1.9686 loss_prob: 1.1573 loss_thr: 0.6245 loss_db: 0.1868 2022/11/01 15:50:38 - mmengine - INFO - Epoch(train) [268][25/63] lr: 1.8789e-03 eta: 10:09:57 time: 0.5701 data_time: 0.0309 memory: 17620 loss: 2.0969 loss_prob: 1.2545 loss_thr: 0.6376 loss_db: 0.2047 2022/11/01 15:50:41 - mmengine - INFO - Epoch(train) [268][30/63] lr: 1.8789e-03 eta: 10:09:49 time: 0.5712 data_time: 0.0315 memory: 17620 loss: 2.2128 loss_prob: 1.3451 loss_thr: 0.6498 loss_db: 0.2180 2022/11/01 15:50:44 - mmengine - INFO - Epoch(train) [268][35/63] lr: 1.8789e-03 eta: 10:09:49 time: 0.5677 data_time: 0.0056 memory: 17620 loss: 2.0710 loss_prob: 1.2442 loss_thr: 0.6295 loss_db: 0.1972 2022/11/01 15:50:47 - mmengine - INFO - Epoch(train) [268][40/63] lr: 1.8789e-03 eta: 10:09:40 time: 0.5643 data_time: 0.0053 memory: 17620 loss: 1.9144 loss_prob: 1.1193 loss_thr: 0.6159 loss_db: 0.1792 2022/11/01 15:50:50 - mmengine - INFO - Epoch(train) [268][45/63] lr: 1.8789e-03 eta: 10:09:40 time: 0.5368 data_time: 0.0065 memory: 17620 loss: 2.0613 loss_prob: 1.2080 loss_thr: 0.6571 loss_db: 0.1962 2022/11/01 15:50:52 - mmengine - INFO - Epoch(train) [268][50/63] lr: 1.8789e-03 eta: 10:09:32 time: 0.5576 data_time: 0.0223 memory: 17620 loss: 2.0230 loss_prob: 1.1719 loss_thr: 0.6600 loss_db: 0.1911 2022/11/01 15:50:55 - mmengine - INFO - Epoch(train) [268][55/63] lr: 1.8789e-03 eta: 10:09:32 time: 0.5711 data_time: 0.0237 memory: 17620 loss: 1.9209 loss_prob: 1.0975 loss_thr: 0.6455 loss_db: 0.1779 2022/11/01 15:50:58 - mmengine - INFO - Epoch(train) [268][60/63] lr: 1.8789e-03 eta: 10:09:23 time: 0.5501 data_time: 0.0071 memory: 17620 loss: 2.1937 loss_prob: 1.3162 loss_thr: 0.6700 loss_db: 0.2076 2022/11/01 15:50:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:51:04 - mmengine - INFO - Epoch(train) [269][5/63] lr: 1.8771e-03 eta: 10:09:23 time: 0.6885 data_time: 0.1838 memory: 17620 loss: 2.1779 loss_prob: 1.3375 loss_thr: 0.6249 loss_db: 0.2155 2022/11/01 15:51:06 - mmengine - INFO - Epoch(train) [269][10/63] lr: 1.8771e-03 eta: 10:09:12 time: 0.7225 data_time: 0.1903 memory: 17620 loss: 2.0007 loss_prob: 1.1864 loss_thr: 0.6205 loss_db: 0.1938 2022/11/01 15:51:09 - mmengine - INFO - Epoch(train) [269][15/63] lr: 1.8771e-03 eta: 10:09:12 time: 0.5289 data_time: 0.0113 memory: 17620 loss: 1.9540 loss_prob: 1.1553 loss_thr: 0.6119 loss_db: 0.1868 2022/11/01 15:51:12 - mmengine - INFO - Epoch(train) [269][20/63] lr: 1.8771e-03 eta: 10:09:03 time: 0.5334 data_time: 0.0060 memory: 17620 loss: 1.8636 loss_prob: 1.0894 loss_thr: 0.5977 loss_db: 0.1765 2022/11/01 15:51:15 - mmengine - INFO - Epoch(train) [269][25/63] lr: 1.8771e-03 eta: 10:09:03 time: 0.5598 data_time: 0.0203 memory: 17620 loss: 1.8112 loss_prob: 1.0495 loss_thr: 0.5911 loss_db: 0.1706 2022/11/01 15:51:17 - mmengine - INFO - Epoch(train) [269][30/63] lr: 1.8771e-03 eta: 10:08:55 time: 0.5666 data_time: 0.0273 memory: 17620 loss: 1.7924 loss_prob: 1.0422 loss_thr: 0.5809 loss_db: 0.1693 2022/11/01 15:51:20 - mmengine - INFO - Epoch(train) [269][35/63] lr: 1.8771e-03 eta: 10:08:55 time: 0.5553 data_time: 0.0201 memory: 17620 loss: 1.8866 loss_prob: 1.0961 loss_thr: 0.6117 loss_db: 0.1788 2022/11/01 15:51:23 - mmengine - INFO - Epoch(train) [269][40/63] lr: 1.8771e-03 eta: 10:08:46 time: 0.5476 data_time: 0.0120 memory: 17620 loss: 1.9950 loss_prob: 1.1694 loss_thr: 0.6333 loss_db: 0.1923 2022/11/01 15:51:26 - mmengine - INFO - Epoch(train) [269][45/63] lr: 1.8771e-03 eta: 10:08:46 time: 0.5356 data_time: 0.0058 memory: 17620 loss: 1.9866 loss_prob: 1.1823 loss_thr: 0.6135 loss_db: 0.1908 2022/11/01 15:51:28 - mmengine - INFO - Epoch(train) [269][50/63] lr: 1.8771e-03 eta: 10:08:37 time: 0.5507 data_time: 0.0161 memory: 17620 loss: 2.3049 loss_prob: 1.4386 loss_thr: 0.6418 loss_db: 0.2245 2022/11/01 15:51:31 - mmengine - INFO - Epoch(train) [269][55/63] lr: 1.8771e-03 eta: 10:08:37 time: 0.5807 data_time: 0.0238 memory: 17620 loss: 2.2760 loss_prob: 1.4143 loss_thr: 0.6369 loss_db: 0.2247 2022/11/01 15:51:34 - mmengine - INFO - Epoch(train) [269][60/63] lr: 1.8771e-03 eta: 10:08:29 time: 0.5675 data_time: 0.0143 memory: 17620 loss: 1.8697 loss_prob: 1.0908 loss_thr: 0.6025 loss_db: 0.1764 2022/11/01 15:51:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:51:41 - mmengine - INFO - Epoch(train) [270][5/63] lr: 1.8752e-03 eta: 10:08:29 time: 0.7493 data_time: 0.2051 memory: 17620 loss: 1.9342 loss_prob: 1.1366 loss_thr: 0.6117 loss_db: 0.1859 2022/11/01 15:51:45 - mmengine - INFO - Epoch(train) [270][10/63] lr: 1.8752e-03 eta: 10:08:25 time: 0.9193 data_time: 0.2052 memory: 17620 loss: 1.9443 loss_prob: 1.1702 loss_thr: 0.5845 loss_db: 0.1897 2022/11/01 15:51:48 - mmengine - INFO - Epoch(train) [270][15/63] lr: 1.8752e-03 eta: 10:08:25 time: 0.7004 data_time: 0.0050 memory: 17620 loss: 1.9993 loss_prob: 1.1947 loss_thr: 0.6102 loss_db: 0.1944 2022/11/01 15:51:50 - mmengine - INFO - Epoch(train) [270][20/63] lr: 1.8752e-03 eta: 10:08:16 time: 0.5555 data_time: 0.0053 memory: 17620 loss: 1.9879 loss_prob: 1.1759 loss_thr: 0.6215 loss_db: 0.1905 2022/11/01 15:51:53 - mmengine - INFO - Epoch(train) [270][25/63] lr: 1.8752e-03 eta: 10:08:16 time: 0.5844 data_time: 0.0084 memory: 17620 loss: 1.9665 loss_prob: 1.1531 loss_thr: 0.6289 loss_db: 0.1846 2022/11/01 15:51:57 - mmengine - INFO - Epoch(train) [270][30/63] lr: 1.8752e-03 eta: 10:08:11 time: 0.6551 data_time: 0.0345 memory: 17620 loss: 1.9374 loss_prob: 1.1299 loss_thr: 0.6263 loss_db: 0.1812 2022/11/01 15:52:01 - mmengine - INFO - Epoch(train) [270][35/63] lr: 1.8752e-03 eta: 10:08:11 time: 0.7326 data_time: 0.0312 memory: 17620 loss: 2.0913 loss_prob: 1.2434 loss_thr: 0.6480 loss_db: 0.1999 2022/11/01 15:52:04 - mmengine - INFO - Epoch(train) [270][40/63] lr: 1.8752e-03 eta: 10:08:08 time: 0.7246 data_time: 0.0053 memory: 17620 loss: 2.0727 loss_prob: 1.2273 loss_thr: 0.6463 loss_db: 0.1991 2022/11/01 15:52:07 - mmengine - INFO - Epoch(train) [270][45/63] lr: 1.8752e-03 eta: 10:08:08 time: 0.6021 data_time: 0.0054 memory: 17620 loss: 1.9891 loss_prob: 1.1834 loss_thr: 0.6051 loss_db: 0.2007 2022/11/01 15:52:10 - mmengine - INFO - Epoch(train) [270][50/63] lr: 1.8752e-03 eta: 10:08:00 time: 0.5503 data_time: 0.0114 memory: 17620 loss: 2.0766 loss_prob: 1.2663 loss_thr: 0.5948 loss_db: 0.2155 2022/11/01 15:52:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:52:12 - mmengine - INFO - Epoch(train) [270][55/63] lr: 1.8752e-03 eta: 10:08:00 time: 0.5741 data_time: 0.0281 memory: 17620 loss: 2.0768 loss_prob: 1.2799 loss_thr: 0.5899 loss_db: 0.2071 2022/11/01 15:52:15 - mmengine - INFO - Epoch(train) [270][60/63] lr: 1.8752e-03 eta: 10:07:52 time: 0.5831 data_time: 0.0237 memory: 17620 loss: 2.0023 loss_prob: 1.2111 loss_thr: 0.5967 loss_db: 0.1945 2022/11/01 15:52:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:52:22 - mmengine - INFO - Epoch(train) [271][5/63] lr: 1.8734e-03 eta: 10:07:52 time: 0.8190 data_time: 0.2192 memory: 17620 loss: 1.8548 loss_prob: 1.0702 loss_thr: 0.6100 loss_db: 0.1745 2022/11/01 15:52:26 - mmengine - INFO - Epoch(train) [271][10/63] lr: 1.8734e-03 eta: 10:07:47 time: 0.8909 data_time: 0.2234 memory: 17620 loss: 1.9952 loss_prob: 1.1698 loss_thr: 0.6379 loss_db: 0.1875 2022/11/01 15:52:29 - mmengine - INFO - Epoch(train) [271][15/63] lr: 1.8734e-03 eta: 10:07:47 time: 0.6386 data_time: 0.0128 memory: 17620 loss: 1.9544 loss_prob: 1.1413 loss_thr: 0.6339 loss_db: 0.1792 2022/11/01 15:52:33 - mmengine - INFO - Epoch(train) [271][20/63] lr: 1.8734e-03 eta: 10:07:42 time: 0.6768 data_time: 0.0065 memory: 17620 loss: 2.2050 loss_prob: 1.3580 loss_thr: 0.6349 loss_db: 0.2121 2022/11/01 15:52:36 - mmengine - INFO - Epoch(train) [271][25/63] lr: 1.8734e-03 eta: 10:07:42 time: 0.6788 data_time: 0.0226 memory: 17620 loss: 2.3185 loss_prob: 1.4394 loss_thr: 0.6523 loss_db: 0.2269 2022/11/01 15:52:38 - mmengine - INFO - Epoch(train) [271][30/63] lr: 1.8734e-03 eta: 10:07:35 time: 0.5951 data_time: 0.0304 memory: 17620 loss: 2.0336 loss_prob: 1.2019 loss_thr: 0.6372 loss_db: 0.1945 2022/11/01 15:52:41 - mmengine - INFO - Epoch(train) [271][35/63] lr: 1.8734e-03 eta: 10:07:35 time: 0.5677 data_time: 0.0172 memory: 17620 loss: 1.9704 loss_prob: 1.1685 loss_thr: 0.6178 loss_db: 0.1841 2022/11/01 15:52:44 - mmengine - INFO - Epoch(train) [271][40/63] lr: 1.8734e-03 eta: 10:07:27 time: 0.5606 data_time: 0.0113 memory: 17620 loss: 2.1112 loss_prob: 1.2800 loss_thr: 0.6322 loss_db: 0.1990 2022/11/01 15:52:47 - mmengine - INFO - Epoch(train) [271][45/63] lr: 1.8734e-03 eta: 10:07:27 time: 0.5497 data_time: 0.0106 memory: 17620 loss: 2.1686 loss_prob: 1.3239 loss_thr: 0.6331 loss_db: 0.2116 2022/11/01 15:52:50 - mmengine - INFO - Epoch(train) [271][50/63] lr: 1.8734e-03 eta: 10:07:20 time: 0.6118 data_time: 0.0359 memory: 17620 loss: 2.0469 loss_prob: 1.2225 loss_thr: 0.6268 loss_db: 0.1976 2022/11/01 15:52:53 - mmengine - INFO - Epoch(train) [271][55/63] lr: 1.8734e-03 eta: 10:07:20 time: 0.6246 data_time: 0.0323 memory: 17620 loss: 2.0706 loss_prob: 1.2332 loss_thr: 0.6392 loss_db: 0.1983 2022/11/01 15:52:56 - mmengine - INFO - Epoch(train) [271][60/63] lr: 1.8734e-03 eta: 10:07:11 time: 0.5448 data_time: 0.0076 memory: 17620 loss: 1.9531 loss_prob: 1.1462 loss_thr: 0.6213 loss_db: 0.1856 2022/11/01 15:52:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:53:02 - mmengine - INFO - Epoch(train) [272][5/63] lr: 1.8716e-03 eta: 10:07:11 time: 0.7177 data_time: 0.2129 memory: 17620 loss: 1.9955 loss_prob: 1.1873 loss_thr: 0.6144 loss_db: 0.1939 2022/11/01 15:53:04 - mmengine - INFO - Epoch(train) [272][10/63] lr: 1.8716e-03 eta: 10:07:01 time: 0.7564 data_time: 0.2143 memory: 17620 loss: 1.8760 loss_prob: 1.1012 loss_thr: 0.5947 loss_db: 0.1801 2022/11/01 15:53:07 - mmengine - INFO - Epoch(train) [272][15/63] lr: 1.8716e-03 eta: 10:07:01 time: 0.5323 data_time: 0.0123 memory: 17620 loss: 1.8706 loss_prob: 1.0977 loss_thr: 0.5949 loss_db: 0.1780 2022/11/01 15:53:10 - mmengine - INFO - Epoch(train) [272][20/63] lr: 1.8716e-03 eta: 10:06:53 time: 0.5545 data_time: 0.0091 memory: 17620 loss: 1.7986 loss_prob: 1.0376 loss_thr: 0.5947 loss_db: 0.1662 2022/11/01 15:53:13 - mmengine - INFO - Epoch(train) [272][25/63] lr: 1.8716e-03 eta: 10:06:53 time: 0.5795 data_time: 0.0142 memory: 17620 loss: 1.8921 loss_prob: 1.0978 loss_thr: 0.6153 loss_db: 0.1790 2022/11/01 15:53:16 - mmengine - INFO - Epoch(train) [272][30/63] lr: 1.8716e-03 eta: 10:06:45 time: 0.5684 data_time: 0.0290 memory: 17620 loss: 2.0366 loss_prob: 1.2008 loss_thr: 0.6413 loss_db: 0.1945 2022/11/01 15:53:19 - mmengine - INFO - Epoch(train) [272][35/63] lr: 1.8716e-03 eta: 10:06:45 time: 0.5745 data_time: 0.0228 memory: 17620 loss: 2.0257 loss_prob: 1.1913 loss_thr: 0.6418 loss_db: 0.1926 2022/11/01 15:53:22 - mmengine - INFO - Epoch(train) [272][40/63] lr: 1.8716e-03 eta: 10:06:38 time: 0.5928 data_time: 0.0115 memory: 17620 loss: 1.9609 loss_prob: 1.1305 loss_thr: 0.6484 loss_db: 0.1821 2022/11/01 15:53:24 - mmengine - INFO - Epoch(train) [272][45/63] lr: 1.8716e-03 eta: 10:06:38 time: 0.5804 data_time: 0.0106 memory: 17620 loss: 1.8884 loss_prob: 1.0823 loss_thr: 0.6333 loss_db: 0.1727 2022/11/01 15:53:27 - mmengine - INFO - Epoch(train) [272][50/63] lr: 1.8716e-03 eta: 10:06:29 time: 0.5599 data_time: 0.0198 memory: 17620 loss: 1.7870 loss_prob: 1.0129 loss_thr: 0.6130 loss_db: 0.1610 2022/11/01 15:53:30 - mmengine - INFO - Epoch(train) [272][55/63] lr: 1.8716e-03 eta: 10:06:29 time: 0.5775 data_time: 0.0219 memory: 17620 loss: 1.7590 loss_prob: 0.9791 loss_thr: 0.6210 loss_db: 0.1589 2022/11/01 15:53:33 - mmengine - INFO - Epoch(train) [272][60/63] lr: 1.8716e-03 eta: 10:06:22 time: 0.5916 data_time: 0.0116 memory: 17620 loss: 1.7931 loss_prob: 1.0242 loss_thr: 0.6023 loss_db: 0.1665 2022/11/01 15:53:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:53:40 - mmengine - INFO - Epoch(train) [273][5/63] lr: 1.8698e-03 eta: 10:06:22 time: 0.7559 data_time: 0.1962 memory: 17620 loss: 2.0666 loss_prob: 1.2669 loss_thr: 0.6049 loss_db: 0.1947 2022/11/01 15:53:42 - mmengine - INFO - Epoch(train) [273][10/63] lr: 1.8698e-03 eta: 10:06:13 time: 0.7907 data_time: 0.1967 memory: 17620 loss: 2.0389 loss_prob: 1.2434 loss_thr: 0.5998 loss_db: 0.1957 2022/11/01 15:53:45 - mmengine - INFO - Epoch(train) [273][15/63] lr: 1.8698e-03 eta: 10:06:13 time: 0.5703 data_time: 0.0116 memory: 17620 loss: 1.8493 loss_prob: 1.0980 loss_thr: 0.5770 loss_db: 0.1743 2022/11/01 15:53:48 - mmengine - INFO - Epoch(train) [273][20/63] lr: 1.8698e-03 eta: 10:06:05 time: 0.5755 data_time: 0.0098 memory: 17620 loss: 1.8758 loss_prob: 1.1051 loss_thr: 0.5960 loss_db: 0.1747 2022/11/01 15:53:51 - mmengine - INFO - Epoch(train) [273][25/63] lr: 1.8698e-03 eta: 10:06:05 time: 0.5994 data_time: 0.0243 memory: 17620 loss: 1.7116 loss_prob: 0.9713 loss_thr: 0.5836 loss_db: 0.1567 2022/11/01 15:53:54 - mmengine - INFO - Epoch(train) [273][30/63] lr: 1.8698e-03 eta: 10:05:57 time: 0.5653 data_time: 0.0308 memory: 17620 loss: 1.6937 loss_prob: 0.9622 loss_thr: 0.5763 loss_db: 0.1552 2022/11/01 15:53:57 - mmengine - INFO - Epoch(train) [273][35/63] lr: 1.8698e-03 eta: 10:05:57 time: 0.5412 data_time: 0.0136 memory: 17620 loss: 1.8097 loss_prob: 1.0364 loss_thr: 0.6092 loss_db: 0.1641 2022/11/01 15:53:59 - mmengine - INFO - Epoch(train) [273][40/63] lr: 1.8698e-03 eta: 10:05:49 time: 0.5550 data_time: 0.0089 memory: 17620 loss: 1.8141 loss_prob: 1.0394 loss_thr: 0.6071 loss_db: 0.1676 2022/11/01 15:54:03 - mmengine - INFO - Epoch(train) [273][45/63] lr: 1.8698e-03 eta: 10:05:49 time: 0.5910 data_time: 0.0096 memory: 17620 loss: 1.8407 loss_prob: 1.0510 loss_thr: 0.6176 loss_db: 0.1721 2022/11/01 15:54:05 - mmengine - INFO - Epoch(train) [273][50/63] lr: 1.8698e-03 eta: 10:05:41 time: 0.5807 data_time: 0.0180 memory: 17620 loss: 1.9843 loss_prob: 1.1598 loss_thr: 0.6386 loss_db: 0.1858 2022/11/01 15:54:08 - mmengine - INFO - Epoch(train) [273][55/63] lr: 1.8698e-03 eta: 10:05:41 time: 0.5652 data_time: 0.0231 memory: 17620 loss: 2.0119 loss_prob: 1.2024 loss_thr: 0.6231 loss_db: 0.1865 2022/11/01 15:54:11 - mmengine - INFO - Epoch(train) [273][60/63] lr: 1.8698e-03 eta: 10:05:33 time: 0.5748 data_time: 0.0109 memory: 17620 loss: 1.9682 loss_prob: 1.1637 loss_thr: 0.6225 loss_db: 0.1820 2022/11/01 15:54:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:54:17 - mmengine - INFO - Epoch(train) [274][5/63] lr: 1.8680e-03 eta: 10:05:33 time: 0.7232 data_time: 0.1776 memory: 17620 loss: 1.8670 loss_prob: 1.0844 loss_thr: 0.6036 loss_db: 0.1790 2022/11/01 15:54:20 - mmengine - INFO - Epoch(train) [274][10/63] lr: 1.8680e-03 eta: 10:05:24 time: 0.7783 data_time: 0.1738 memory: 17620 loss: 1.7643 loss_prob: 1.0036 loss_thr: 0.5968 loss_db: 0.1639 2022/11/01 15:54:24 - mmengine - INFO - Epoch(train) [274][15/63] lr: 1.8680e-03 eta: 10:05:24 time: 0.6472 data_time: 0.0173 memory: 17620 loss: 1.8869 loss_prob: 1.0958 loss_thr: 0.6162 loss_db: 0.1748 2022/11/01 15:54:27 - mmengine - INFO - Epoch(train) [274][20/63] lr: 1.8680e-03 eta: 10:05:19 time: 0.6493 data_time: 0.0172 memory: 17620 loss: 2.1104 loss_prob: 1.2690 loss_thr: 0.6401 loss_db: 0.2013 2022/11/01 15:54:30 - mmengine - INFO - Epoch(train) [274][25/63] lr: 1.8680e-03 eta: 10:05:19 time: 0.6576 data_time: 0.0111 memory: 17620 loss: 2.0368 loss_prob: 1.1964 loss_thr: 0.6487 loss_db: 0.1917 2022/11/01 15:54:33 - mmengine - INFO - Epoch(train) [274][30/63] lr: 1.8680e-03 eta: 10:05:14 time: 0.6512 data_time: 0.0285 memory: 17620 loss: 2.0066 loss_prob: 1.1723 loss_thr: 0.6416 loss_db: 0.1927 2022/11/01 15:54:36 - mmengine - INFO - Epoch(train) [274][35/63] lr: 1.8680e-03 eta: 10:05:14 time: 0.5972 data_time: 0.0228 memory: 17620 loss: 1.9862 loss_prob: 1.1732 loss_thr: 0.6190 loss_db: 0.1940 2022/11/01 15:54:40 - mmengine - INFO - Epoch(train) [274][40/63] lr: 1.8680e-03 eta: 10:05:09 time: 0.6825 data_time: 0.0182 memory: 17620 loss: 2.0418 loss_prob: 1.2323 loss_thr: 0.6116 loss_db: 0.1978 2022/11/01 15:54:43 - mmengine - INFO - Epoch(train) [274][45/63] lr: 1.8680e-03 eta: 10:05:09 time: 0.6822 data_time: 0.0196 memory: 17620 loss: 2.3972 loss_prob: 1.5103 loss_thr: 0.6461 loss_db: 0.2407 2022/11/01 15:54:46 - mmengine - INFO - Epoch(train) [274][50/63] lr: 1.8680e-03 eta: 10:05:02 time: 0.5991 data_time: 0.0111 memory: 17620 loss: 2.4881 loss_prob: 1.5729 loss_thr: 0.6633 loss_db: 0.2519 2022/11/01 15:54:49 - mmengine - INFO - Epoch(train) [274][55/63] lr: 1.8680e-03 eta: 10:05:02 time: 0.6235 data_time: 0.0201 memory: 17620 loss: 2.3817 loss_prob: 1.4759 loss_thr: 0.6675 loss_db: 0.2383 2022/11/01 15:54:52 - mmengine - INFO - Epoch(train) [274][60/63] lr: 1.8680e-03 eta: 10:04:55 time: 0.5954 data_time: 0.0156 memory: 17620 loss: 2.1156 loss_prob: 1.2748 loss_thr: 0.6385 loss_db: 0.2023 2022/11/01 15:54:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:54:59 - mmengine - INFO - Epoch(train) [275][5/63] lr: 1.8662e-03 eta: 10:04:55 time: 0.8096 data_time: 0.2161 memory: 17620 loss: 2.1202 loss_prob: 1.2786 loss_thr: 0.6332 loss_db: 0.2084 2022/11/01 15:55:02 - mmengine - INFO - Epoch(train) [275][10/63] lr: 1.8662e-03 eta: 10:04:49 time: 0.8508 data_time: 0.2174 memory: 17620 loss: 2.3024 loss_prob: 1.4206 loss_thr: 0.6572 loss_db: 0.2247 2022/11/01 15:55:04 - mmengine - INFO - Epoch(train) [275][15/63] lr: 1.8662e-03 eta: 10:04:49 time: 0.5527 data_time: 0.0095 memory: 17620 loss: 2.1226 loss_prob: 1.2964 loss_thr: 0.6202 loss_db: 0.2060 2022/11/01 15:55:07 - mmengine - INFO - Epoch(train) [275][20/63] lr: 1.8662e-03 eta: 10:04:40 time: 0.5404 data_time: 0.0052 memory: 17620 loss: 1.8515 loss_prob: 1.0851 loss_thr: 0.5869 loss_db: 0.1795 2022/11/01 15:55:11 - mmengine - INFO - Epoch(train) [275][25/63] lr: 1.8662e-03 eta: 10:04:40 time: 0.6080 data_time: 0.0352 memory: 17620 loss: 1.8762 loss_prob: 1.0926 loss_thr: 0.6037 loss_db: 0.1799 2022/11/01 15:55:14 - mmengine - INFO - Epoch(train) [275][30/63] lr: 1.8662e-03 eta: 10:04:34 time: 0.6408 data_time: 0.0388 memory: 17620 loss: 2.0255 loss_prob: 1.2174 loss_thr: 0.6118 loss_db: 0.1962 2022/11/01 15:55:17 - mmengine - INFO - Epoch(train) [275][35/63] lr: 1.8662e-03 eta: 10:04:34 time: 0.6085 data_time: 0.0085 memory: 17620 loss: 2.1441 loss_prob: 1.3031 loss_thr: 0.6330 loss_db: 0.2079 2022/11/01 15:55:21 - mmengine - INFO - Epoch(train) [275][40/63] lr: 1.8662e-03 eta: 10:04:30 time: 0.6922 data_time: 0.0052 memory: 17620 loss: 2.0960 loss_prob: 1.2521 loss_thr: 0.6340 loss_db: 0.2099 2022/11/01 15:55:23 - mmengine - INFO - Epoch(train) [275][45/63] lr: 1.8662e-03 eta: 10:04:30 time: 0.6871 data_time: 0.0050 memory: 17620 loss: 2.0337 loss_prob: 1.2149 loss_thr: 0.6134 loss_db: 0.2054 2022/11/01 15:55:26 - mmengine - INFO - Epoch(train) [275][50/63] lr: 1.8662e-03 eta: 10:04:23 time: 0.5906 data_time: 0.0211 memory: 17620 loss: 2.1012 loss_prob: 1.2496 loss_thr: 0.6506 loss_db: 0.2010 2022/11/01 15:55:29 - mmengine - INFO - Epoch(train) [275][55/63] lr: 1.8662e-03 eta: 10:04:23 time: 0.5718 data_time: 0.0231 memory: 17620 loss: 2.1351 loss_prob: 1.2721 loss_thr: 0.6577 loss_db: 0.2053 2022/11/01 15:55:32 - mmengine - INFO - Epoch(train) [275][60/63] lr: 1.8662e-03 eta: 10:04:14 time: 0.5467 data_time: 0.0075 memory: 17620 loss: 2.0731 loss_prob: 1.2503 loss_thr: 0.6238 loss_db: 0.1991 2022/11/01 15:55:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:55:38 - mmengine - INFO - Epoch(train) [276][5/63] lr: 1.8643e-03 eta: 10:04:14 time: 0.7136 data_time: 0.1860 memory: 17620 loss: 1.9895 loss_prob: 1.1710 loss_thr: 0.6296 loss_db: 0.1890 2022/11/01 15:55:41 - mmengine - INFO - Epoch(train) [276][10/63] lr: 1.8643e-03 eta: 10:04:04 time: 0.7512 data_time: 0.1937 memory: 17620 loss: 1.9758 loss_prob: 1.1504 loss_thr: 0.6342 loss_db: 0.1912 2022/11/01 15:55:44 - mmengine - INFO - Epoch(train) [276][15/63] lr: 1.8643e-03 eta: 10:04:04 time: 0.5615 data_time: 0.0138 memory: 17620 loss: 1.9698 loss_prob: 1.1766 loss_thr: 0.6018 loss_db: 0.1914 2022/11/01 15:55:46 - mmengine - INFO - Epoch(train) [276][20/63] lr: 1.8643e-03 eta: 10:03:55 time: 0.5308 data_time: 0.0070 memory: 17620 loss: 1.9980 loss_prob: 1.2118 loss_thr: 0.5995 loss_db: 0.1867 2022/11/01 15:55:49 - mmengine - INFO - Epoch(train) [276][25/63] lr: 1.8643e-03 eta: 10:03:55 time: 0.5348 data_time: 0.0139 memory: 17620 loss: 2.0648 loss_prob: 1.2363 loss_thr: 0.6374 loss_db: 0.1911 2022/11/01 15:55:52 - mmengine - INFO - Epoch(train) [276][30/63] lr: 1.8643e-03 eta: 10:03:46 time: 0.5481 data_time: 0.0208 memory: 17620 loss: 1.9251 loss_prob: 1.1274 loss_thr: 0.6169 loss_db: 0.1807 2022/11/01 15:55:55 - mmengine - INFO - Epoch(train) [276][35/63] lr: 1.8643e-03 eta: 10:03:46 time: 0.5851 data_time: 0.0281 memory: 17620 loss: 1.7809 loss_prob: 1.0274 loss_thr: 0.5872 loss_db: 0.1664 2022/11/01 15:55:58 - mmengine - INFO - Epoch(train) [276][40/63] lr: 1.8643e-03 eta: 10:03:39 time: 0.6019 data_time: 0.0230 memory: 17620 loss: 1.8655 loss_prob: 1.0830 loss_thr: 0.6109 loss_db: 0.1715 2022/11/01 15:56:01 - mmengine - INFO - Epoch(train) [276][45/63] lr: 1.8643e-03 eta: 10:03:39 time: 0.5731 data_time: 0.0087 memory: 17620 loss: 1.9085 loss_prob: 1.1102 loss_thr: 0.6178 loss_db: 0.1806 2022/11/01 15:56:03 - mmengine - INFO - Epoch(train) [276][50/63] lr: 1.8643e-03 eta: 10:03:31 time: 0.5588 data_time: 0.0158 memory: 17620 loss: 1.9866 loss_prob: 1.1803 loss_thr: 0.6166 loss_db: 0.1897 2022/11/01 15:56:06 - mmengine - INFO - Epoch(train) [276][55/63] lr: 1.8643e-03 eta: 10:03:31 time: 0.5852 data_time: 0.0168 memory: 17620 loss: 1.9465 loss_prob: 1.1551 loss_thr: 0.6122 loss_db: 0.1791 2022/11/01 15:56:09 - mmengine - INFO - Epoch(train) [276][60/63] lr: 1.8643e-03 eta: 10:03:24 time: 0.5944 data_time: 0.0115 memory: 17620 loss: 1.7682 loss_prob: 1.0125 loss_thr: 0.5964 loss_db: 0.1594 2022/11/01 15:56:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:56:16 - mmengine - INFO - Epoch(train) [277][5/63] lr: 1.8625e-03 eta: 10:03:24 time: 0.7559 data_time: 0.2003 memory: 17620 loss: 2.0231 loss_prob: 1.2010 loss_thr: 0.6281 loss_db: 0.1940 2022/11/01 15:56:18 - mmengine - INFO - Epoch(train) [277][10/63] lr: 1.8625e-03 eta: 10:03:14 time: 0.7689 data_time: 0.1978 memory: 17620 loss: 1.9667 loss_prob: 1.1510 loss_thr: 0.6281 loss_db: 0.1876 2022/11/01 15:56:21 - mmengine - INFO - Epoch(train) [277][15/63] lr: 1.8625e-03 eta: 10:03:14 time: 0.5520 data_time: 0.0073 memory: 17620 loss: 1.8475 loss_prob: 1.0787 loss_thr: 0.5976 loss_db: 0.1712 2022/11/01 15:56:24 - mmengine - INFO - Epoch(train) [277][20/63] lr: 1.8625e-03 eta: 10:03:06 time: 0.5524 data_time: 0.0087 memory: 17620 loss: 1.8554 loss_prob: 1.0932 loss_thr: 0.5877 loss_db: 0.1744 2022/11/01 15:56:27 - mmengine - INFO - Epoch(train) [277][25/63] lr: 1.8625e-03 eta: 10:03:06 time: 0.5679 data_time: 0.0114 memory: 17620 loss: 1.8719 loss_prob: 1.0931 loss_thr: 0.6003 loss_db: 0.1785 2022/11/01 15:56:30 - mmengine - INFO - Epoch(train) [277][30/63] lr: 1.8625e-03 eta: 10:02:59 time: 0.5911 data_time: 0.0410 memory: 17620 loss: 1.8837 loss_prob: 1.0984 loss_thr: 0.6106 loss_db: 0.1746 2022/11/01 15:56:33 - mmengine - INFO - Epoch(train) [277][35/63] lr: 1.8625e-03 eta: 10:02:59 time: 0.6165 data_time: 0.0366 memory: 17620 loss: 1.8554 loss_prob: 1.0819 loss_thr: 0.6047 loss_db: 0.1687 2022/11/01 15:56:36 - mmengine - INFO - Epoch(train) [277][40/63] lr: 1.8625e-03 eta: 10:02:51 time: 0.5920 data_time: 0.0050 memory: 17620 loss: 1.9939 loss_prob: 1.1892 loss_thr: 0.6144 loss_db: 0.1903 2022/11/01 15:56:39 - mmengine - INFO - Epoch(train) [277][45/63] lr: 1.8625e-03 eta: 10:02:51 time: 0.5766 data_time: 0.0045 memory: 17620 loss: 2.0087 loss_prob: 1.1906 loss_thr: 0.6273 loss_db: 0.1907 2022/11/01 15:56:42 - mmengine - INFO - Epoch(train) [277][50/63] lr: 1.8625e-03 eta: 10:02:43 time: 0.5690 data_time: 0.0199 memory: 17620 loss: 1.8889 loss_prob: 1.0870 loss_thr: 0.6263 loss_db: 0.1756 2022/11/01 15:56:44 - mmengine - INFO - Epoch(train) [277][55/63] lr: 1.8625e-03 eta: 10:02:43 time: 0.5506 data_time: 0.0276 memory: 17620 loss: 2.0124 loss_prob: 1.1901 loss_thr: 0.6273 loss_db: 0.1950 2022/11/01 15:56:47 - mmengine - INFO - Epoch(train) [277][60/63] lr: 1.8625e-03 eta: 10:02:35 time: 0.5626 data_time: 0.0137 memory: 17620 loss: 2.0429 loss_prob: 1.2133 loss_thr: 0.6333 loss_db: 0.1963 2022/11/01 15:56:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:56:53 - mmengine - INFO - Epoch(train) [278][5/63] lr: 1.8607e-03 eta: 10:02:35 time: 0.7007 data_time: 0.1520 memory: 17620 loss: 1.8997 loss_prob: 1.1080 loss_thr: 0.6090 loss_db: 0.1827 2022/11/01 15:56:56 - mmengine - INFO - Epoch(train) [278][10/63] lr: 1.8607e-03 eta: 10:02:26 time: 0.7783 data_time: 0.1886 memory: 17620 loss: 1.7607 loss_prob: 1.0085 loss_thr: 0.5852 loss_db: 0.1670 2022/11/01 15:57:00 - mmengine - INFO - Epoch(train) [278][15/63] lr: 1.8607e-03 eta: 10:02:26 time: 0.6496 data_time: 0.0488 memory: 17620 loss: 2.0374 loss_prob: 1.2219 loss_thr: 0.6240 loss_db: 0.1915 2022/11/01 15:57:02 - mmengine - INFO - Epoch(train) [278][20/63] lr: 1.8607e-03 eta: 10:02:19 time: 0.5989 data_time: 0.0139 memory: 17620 loss: 2.1003 loss_prob: 1.2621 loss_thr: 0.6394 loss_db: 0.1988 2022/11/01 15:57:05 - mmengine - INFO - Epoch(train) [278][25/63] lr: 1.8607e-03 eta: 10:02:19 time: 0.5645 data_time: 0.0143 memory: 17620 loss: 1.8327 loss_prob: 1.0508 loss_thr: 0.6089 loss_db: 0.1730 2022/11/01 15:57:09 - mmengine - INFO - Epoch(train) [278][30/63] lr: 1.8607e-03 eta: 10:02:13 time: 0.6261 data_time: 0.0269 memory: 17620 loss: 1.8451 loss_prob: 1.0609 loss_thr: 0.6138 loss_db: 0.1703 2022/11/01 15:57:12 - mmengine - INFO - Epoch(train) [278][35/63] lr: 1.8607e-03 eta: 10:02:13 time: 0.6489 data_time: 0.0277 memory: 17620 loss: 1.7962 loss_prob: 1.0376 loss_thr: 0.5920 loss_db: 0.1666 2022/11/01 15:57:15 - mmengine - INFO - Epoch(train) [278][40/63] lr: 1.8607e-03 eta: 10:02:07 time: 0.6386 data_time: 0.0200 memory: 17620 loss: 2.0440 loss_prob: 1.2257 loss_thr: 0.6215 loss_db: 0.1968 2022/11/01 15:57:18 - mmengine - INFO - Epoch(train) [278][45/63] lr: 1.8607e-03 eta: 10:02:07 time: 0.6785 data_time: 0.0148 memory: 17620 loss: 2.0733 loss_prob: 1.2327 loss_thr: 0.6440 loss_db: 0.1966 2022/11/01 15:57:22 - mmengine - INFO - Epoch(train) [278][50/63] lr: 1.8607e-03 eta: 10:02:03 time: 0.6895 data_time: 0.0115 memory: 17620 loss: 1.7563 loss_prob: 1.0057 loss_thr: 0.5912 loss_db: 0.1594 2022/11/01 15:57:25 - mmengine - INFO - Epoch(train) [278][55/63] lr: 1.8607e-03 eta: 10:02:03 time: 0.6479 data_time: 0.0173 memory: 17620 loss: 1.9950 loss_prob: 1.1931 loss_thr: 0.6129 loss_db: 0.1890 2022/11/01 15:57:28 - mmengine - INFO - Epoch(train) [278][60/63] lr: 1.8607e-03 eta: 10:01:57 time: 0.6160 data_time: 0.0167 memory: 17620 loss: 2.0204 loss_prob: 1.2085 loss_thr: 0.6164 loss_db: 0.1955 2022/11/01 15:57:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:57:36 - mmengine - INFO - Epoch(train) [279][5/63] lr: 1.8589e-03 eta: 10:01:57 time: 0.8828 data_time: 0.2126 memory: 17620 loss: 1.8142 loss_prob: 1.0672 loss_thr: 0.5840 loss_db: 0.1631 2022/11/01 15:57:38 - mmengine - INFO - Epoch(train) [279][10/63] lr: 1.8589e-03 eta: 10:01:51 time: 0.8579 data_time: 0.2114 memory: 17620 loss: 2.0911 loss_prob: 1.2402 loss_thr: 0.6599 loss_db: 0.1910 2022/11/01 15:57:42 - mmengine - INFO - Epoch(train) [279][15/63] lr: 1.8589e-03 eta: 10:01:51 time: 0.6208 data_time: 0.0070 memory: 17620 loss: 2.0040 loss_prob: 1.1518 loss_thr: 0.6650 loss_db: 0.1872 2022/11/01 15:57:45 - mmengine - INFO - Epoch(train) [279][20/63] lr: 1.8589e-03 eta: 10:01:45 time: 0.6346 data_time: 0.0057 memory: 17620 loss: 1.6307 loss_prob: 0.9190 loss_thr: 0.5580 loss_db: 0.1536 2022/11/01 15:57:49 - mmengine - INFO - Epoch(train) [279][25/63] lr: 1.8589e-03 eta: 10:01:45 time: 0.7023 data_time: 0.0336 memory: 17620 loss: 1.7487 loss_prob: 1.0092 loss_thr: 0.5746 loss_db: 0.1649 2022/11/01 15:57:52 - mmengine - INFO - Epoch(train) [279][30/63] lr: 1.8589e-03 eta: 10:01:43 time: 0.7542 data_time: 0.0462 memory: 17620 loss: 1.9130 loss_prob: 1.1361 loss_thr: 0.5936 loss_db: 0.1834 2022/11/01 15:57:56 - mmengine - INFO - Epoch(train) [279][35/63] lr: 1.8589e-03 eta: 10:01:43 time: 0.7157 data_time: 0.0183 memory: 17620 loss: 1.8548 loss_prob: 1.0966 loss_thr: 0.5856 loss_db: 0.1726 2022/11/01 15:57:59 - mmengine - INFO - Epoch(train) [279][40/63] lr: 1.8589e-03 eta: 10:01:38 time: 0.6575 data_time: 0.0071 memory: 17620 loss: 1.9217 loss_prob: 1.1290 loss_thr: 0.6129 loss_db: 0.1798 2022/11/01 15:58:02 - mmengine - INFO - Epoch(train) [279][45/63] lr: 1.8589e-03 eta: 10:01:38 time: 0.5737 data_time: 0.0070 memory: 17620 loss: 1.9045 loss_prob: 1.1032 loss_thr: 0.6189 loss_db: 0.1823 2022/11/01 15:58:05 - mmengine - INFO - Epoch(train) [279][50/63] lr: 1.8589e-03 eta: 10:01:30 time: 0.5736 data_time: 0.0167 memory: 17620 loss: 1.9346 loss_prob: 1.1269 loss_thr: 0.6208 loss_db: 0.1870 2022/11/01 15:58:07 - mmengine - INFO - Epoch(train) [279][55/63] lr: 1.8589e-03 eta: 10:01:30 time: 0.5631 data_time: 0.0230 memory: 17620 loss: 1.9390 loss_prob: 1.1427 loss_thr: 0.6070 loss_db: 0.1893 2022/11/01 15:58:10 - mmengine - INFO - Epoch(train) [279][60/63] lr: 1.8589e-03 eta: 10:01:22 time: 0.5647 data_time: 0.0127 memory: 17620 loss: 1.9050 loss_prob: 1.1379 loss_thr: 0.5851 loss_db: 0.1821 2022/11/01 15:58:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:58:17 - mmengine - INFO - Epoch(train) [280][5/63] lr: 1.8571e-03 eta: 10:01:22 time: 0.7414 data_time: 0.2030 memory: 17620 loss: 2.4357 loss_prob: 1.5558 loss_thr: 0.6430 loss_db: 0.2368 2022/11/01 15:58:20 - mmengine - INFO - Epoch(train) [280][10/63] lr: 1.8571e-03 eta: 10:01:13 time: 0.7704 data_time: 0.2009 memory: 17620 loss: 2.4563 loss_prob: 1.5504 loss_thr: 0.6591 loss_db: 0.2468 2022/11/01 15:58:22 - mmengine - INFO - Epoch(train) [280][15/63] lr: 1.8571e-03 eta: 10:01:13 time: 0.5878 data_time: 0.0065 memory: 17620 loss: 2.2049 loss_prob: 1.3415 loss_thr: 0.6399 loss_db: 0.2235 2022/11/01 15:58:25 - mmengine - INFO - Epoch(train) [280][20/63] lr: 1.8571e-03 eta: 10:01:05 time: 0.5762 data_time: 0.0057 memory: 17620 loss: 2.0971 loss_prob: 1.2543 loss_thr: 0.6392 loss_db: 0.2036 2022/11/01 15:58:28 - mmengine - INFO - Epoch(train) [280][25/63] lr: 1.8571e-03 eta: 10:01:05 time: 0.6024 data_time: 0.0123 memory: 17620 loss: 1.9359 loss_prob: 1.1459 loss_thr: 0.6053 loss_db: 0.1846 2022/11/01 15:58:31 - mmengine - INFO - Epoch(train) [280][30/63] lr: 1.8571e-03 eta: 10:00:58 time: 0.6059 data_time: 0.0338 memory: 17620 loss: 2.0142 loss_prob: 1.2143 loss_thr: 0.6055 loss_db: 0.1943 2022/11/01 15:58:34 - mmengine - INFO - Epoch(train) [280][35/63] lr: 1.8571e-03 eta: 10:00:58 time: 0.5548 data_time: 0.0269 memory: 17620 loss: 2.1592 loss_prob: 1.3212 loss_thr: 0.6297 loss_db: 0.2082 2022/11/01 15:58:37 - mmengine - INFO - Epoch(train) [280][40/63] lr: 1.8571e-03 eta: 10:00:49 time: 0.5274 data_time: 0.0048 memory: 17620 loss: 2.0675 loss_prob: 1.2438 loss_thr: 0.6231 loss_db: 0.2006 2022/11/01 15:58:40 - mmengine - INFO - Epoch(train) [280][45/63] lr: 1.8571e-03 eta: 10:00:49 time: 0.5574 data_time: 0.0052 memory: 17620 loss: 1.8678 loss_prob: 1.1095 loss_thr: 0.5773 loss_db: 0.1811 2022/11/01 15:58:42 - mmengine - INFO - Epoch(train) [280][50/63] lr: 1.8571e-03 eta: 10:00:41 time: 0.5716 data_time: 0.0108 memory: 17620 loss: 1.9699 loss_prob: 1.1803 loss_thr: 0.6006 loss_db: 0.1890 2022/11/01 15:58:45 - mmengine - INFO - Epoch(train) [280][55/63] lr: 1.8571e-03 eta: 10:00:41 time: 0.5702 data_time: 0.0213 memory: 17620 loss: 2.0891 loss_prob: 1.2554 loss_thr: 0.6346 loss_db: 0.1991 2022/11/01 15:58:48 - mmengine - INFO - Epoch(train) [280][60/63] lr: 1.8571e-03 eta: 10:00:34 time: 0.5994 data_time: 0.0157 memory: 17620 loss: 1.8898 loss_prob: 1.1074 loss_thr: 0.6015 loss_db: 0.1809 2022/11/01 15:58:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:58:50 - mmengine - INFO - Saving checkpoint at 280 epochs 2022/11/01 15:58:57 - mmengine - INFO - Epoch(val) [280][5/32] eta: 10:00:34 time: 0.5749 data_time: 0.0907 memory: 17620 2022/11/01 15:59:00 - mmengine - INFO - Epoch(val) [280][10/32] eta: 0:00:14 time: 0.6659 data_time: 0.1270 memory: 15725 2022/11/01 15:59:03 - mmengine - INFO - Epoch(val) [280][15/32] eta: 0:00:14 time: 0.5932 data_time: 0.0502 memory: 15725 2022/11/01 15:59:06 - mmengine - INFO - Epoch(val) [280][20/32] eta: 0:00:07 time: 0.5874 data_time: 0.0482 memory: 15725 2022/11/01 15:59:09 - mmengine - INFO - Epoch(val) [280][25/32] eta: 0:00:07 time: 0.5999 data_time: 0.0502 memory: 15725 2022/11/01 15:59:11 - mmengine - INFO - Epoch(val) [280][30/32] eta: 0:00:01 time: 0.5663 data_time: 0.0210 memory: 15725 2022/11/01 15:59:12 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8267, precision: 0.6887, hmean: 0.7514 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8267, precision: 0.7909, hmean: 0.8084 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8233, precision: 0.8424, hmean: 0.8327 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8074, precision: 0.8954, hmean: 0.8491 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7376, precision: 0.9422, hmean: 0.8274 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.3216, precision: 0.9752, hmean: 0.4837 2022/11/01 15:59:12 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 15:59:12 - mmengine - INFO - Epoch(val) [280][32/32] icdar/precision: 0.8954 icdar/recall: 0.8074 icdar/hmean: 0.8491 2022/11/01 15:59:17 - mmengine - INFO - Epoch(train) [281][5/63] lr: 1.8553e-03 eta: 0:00:01 time: 0.7541 data_time: 0.1948 memory: 17620 loss: 1.8417 loss_prob: 1.0565 loss_thr: 0.6149 loss_db: 0.1703 2022/11/01 15:59:20 - mmengine - INFO - Epoch(train) [281][10/63] lr: 1.8553e-03 eta: 10:00:25 time: 0.7655 data_time: 0.1983 memory: 17620 loss: 1.8667 loss_prob: 1.0652 loss_thr: 0.6288 loss_db: 0.1726 2022/11/01 15:59:22 - mmengine - INFO - Epoch(train) [281][15/63] lr: 1.8553e-03 eta: 10:00:25 time: 0.5302 data_time: 0.0096 memory: 17620 loss: 1.8186 loss_prob: 1.0355 loss_thr: 0.6131 loss_db: 0.1700 2022/11/01 15:59:25 - mmengine - INFO - Epoch(train) [281][20/63] lr: 1.8553e-03 eta: 10:00:16 time: 0.5347 data_time: 0.0065 memory: 17620 loss: 2.0226 loss_prob: 1.2321 loss_thr: 0.5979 loss_db: 0.1926 2022/11/01 15:59:28 - mmengine - INFO - Epoch(train) [281][25/63] lr: 1.8553e-03 eta: 10:00:16 time: 0.5652 data_time: 0.0235 memory: 17620 loss: 2.1219 loss_prob: 1.3066 loss_thr: 0.6137 loss_db: 0.2016 2022/11/01 15:59:31 - mmengine - INFO - Epoch(train) [281][30/63] lr: 1.8553e-03 eta: 10:00:07 time: 0.5592 data_time: 0.0328 memory: 17620 loss: 2.1274 loss_prob: 1.2887 loss_thr: 0.6380 loss_db: 0.2007 2022/11/01 15:59:33 - mmengine - INFO - Epoch(train) [281][35/63] lr: 1.8553e-03 eta: 10:00:07 time: 0.5331 data_time: 0.0146 memory: 17620 loss: 2.0740 loss_prob: 1.2667 loss_thr: 0.6098 loss_db: 0.1975 2022/11/01 15:59:36 - mmengine - INFO - Epoch(train) [281][40/63] lr: 1.8553e-03 eta: 9:59:59 time: 0.5552 data_time: 0.0050 memory: 17620 loss: 1.9116 loss_prob: 1.1464 loss_thr: 0.5881 loss_db: 0.1772 2022/11/01 15:59:40 - mmengine - INFO - Epoch(train) [281][45/63] lr: 1.8553e-03 eta: 9:59:59 time: 0.6675 data_time: 0.0055 memory: 17620 loss: 1.9157 loss_prob: 1.1388 loss_thr: 0.5966 loss_db: 0.1803 2022/11/01 15:59:43 - mmengine - INFO - Epoch(train) [281][50/63] lr: 1.8553e-03 eta: 9:59:55 time: 0.7061 data_time: 0.0161 memory: 17620 loss: 1.8832 loss_prob: 1.0978 loss_thr: 0.6070 loss_db: 0.1784 2022/11/01 15:59:46 - mmengine - INFO - Epoch(train) [281][55/63] lr: 1.8553e-03 eta: 9:59:55 time: 0.6101 data_time: 0.0250 memory: 17620 loss: 1.8771 loss_prob: 1.0807 loss_thr: 0.6210 loss_db: 0.1755 2022/11/01 15:59:49 - mmengine - INFO - Epoch(train) [281][60/63] lr: 1.8553e-03 eta: 9:59:48 time: 0.5799 data_time: 0.0147 memory: 17620 loss: 1.8550 loss_prob: 1.0677 loss_thr: 0.6125 loss_db: 0.1749 2022/11/01 15:59:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 15:59:57 - mmengine - INFO - Epoch(train) [282][5/63] lr: 1.8535e-03 eta: 9:59:48 time: 0.8800 data_time: 0.2135 memory: 17620 loss: 1.9235 loss_prob: 1.1162 loss_thr: 0.6268 loss_db: 0.1805 2022/11/01 16:00:00 - mmengine - INFO - Epoch(train) [282][10/63] lr: 1.8535e-03 eta: 9:59:43 time: 0.9051 data_time: 0.2135 memory: 17620 loss: 1.8907 loss_prob: 1.1045 loss_thr: 0.6098 loss_db: 0.1764 2022/11/01 16:00:03 - mmengine - INFO - Epoch(train) [282][15/63] lr: 1.8535e-03 eta: 9:59:43 time: 0.6302 data_time: 0.0051 memory: 17620 loss: 1.7754 loss_prob: 1.0199 loss_thr: 0.5884 loss_db: 0.1670 2022/11/01 16:00:06 - mmengine - INFO - Epoch(train) [282][20/63] lr: 1.8535e-03 eta: 9:59:36 time: 0.6022 data_time: 0.0051 memory: 17620 loss: 1.8034 loss_prob: 1.0387 loss_thr: 0.5932 loss_db: 0.1715 2022/11/01 16:00:10 - mmengine - INFO - Epoch(train) [282][25/63] lr: 1.8535e-03 eta: 9:59:36 time: 0.6457 data_time: 0.0332 memory: 17620 loss: 1.7725 loss_prob: 1.0160 loss_thr: 0.5909 loss_db: 0.1657 2022/11/01 16:00:13 - mmengine - INFO - Epoch(train) [282][30/63] lr: 1.8535e-03 eta: 9:59:32 time: 0.6733 data_time: 0.0369 memory: 17620 loss: 1.8201 loss_prob: 1.0658 loss_thr: 0.5849 loss_db: 0.1694 2022/11/01 16:00:16 - mmengine - INFO - Epoch(train) [282][35/63] lr: 1.8535e-03 eta: 9:59:32 time: 0.6616 data_time: 0.0100 memory: 17620 loss: 1.7994 loss_prob: 1.0453 loss_thr: 0.5873 loss_db: 0.1667 2022/11/01 16:00:20 - mmengine - INFO - Epoch(train) [282][40/63] lr: 1.8535e-03 eta: 9:59:29 time: 0.7344 data_time: 0.0062 memory: 17620 loss: 1.8095 loss_prob: 1.0402 loss_thr: 0.6012 loss_db: 0.1681 2022/11/01 16:00:23 - mmengine - INFO - Epoch(train) [282][45/63] lr: 1.8535e-03 eta: 9:59:29 time: 0.6777 data_time: 0.0053 memory: 17620 loss: 1.8219 loss_prob: 1.0682 loss_thr: 0.5826 loss_db: 0.1710 2022/11/01 16:00:27 - mmengine - INFO - Epoch(train) [282][50/63] lr: 1.8535e-03 eta: 9:59:25 time: 0.6928 data_time: 0.0223 memory: 17620 loss: 1.7402 loss_prob: 1.0050 loss_thr: 0.5714 loss_db: 0.1637 2022/11/01 16:00:30 - mmengine - INFO - Epoch(train) [282][55/63] lr: 1.8535e-03 eta: 9:59:25 time: 0.6662 data_time: 0.0234 memory: 17620 loss: 1.7310 loss_prob: 0.9899 loss_thr: 0.5799 loss_db: 0.1612 2022/11/01 16:00:32 - mmengine - INFO - Epoch(train) [282][60/63] lr: 1.8535e-03 eta: 9:59:17 time: 0.5529 data_time: 0.0064 memory: 17620 loss: 1.7531 loss_prob: 1.0068 loss_thr: 0.5821 loss_db: 0.1641 2022/11/01 16:00:34 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:00:39 - mmengine - INFO - Epoch(train) [283][5/63] lr: 1.8516e-03 eta: 9:59:17 time: 0.7931 data_time: 0.1837 memory: 17620 loss: 1.9706 loss_prob: 1.1502 loss_thr: 0.6315 loss_db: 0.1888 2022/11/01 16:00:42 - mmengine - INFO - Epoch(train) [283][10/63] lr: 1.8516e-03 eta: 9:59:09 time: 0.8110 data_time: 0.1959 memory: 17620 loss: 1.8030 loss_prob: 1.0470 loss_thr: 0.5885 loss_db: 0.1675 2022/11/01 16:00:45 - mmengine - INFO - Epoch(train) [283][15/63] lr: 1.8516e-03 eta: 9:59:09 time: 0.5457 data_time: 0.0186 memory: 17620 loss: 1.7155 loss_prob: 0.9895 loss_thr: 0.5675 loss_db: 0.1585 2022/11/01 16:00:47 - mmengine - INFO - Epoch(train) [283][20/63] lr: 1.8516e-03 eta: 9:58:59 time: 0.5296 data_time: 0.0097 memory: 17620 loss: 1.8881 loss_prob: 1.0997 loss_thr: 0.6101 loss_db: 0.1783 2022/11/01 16:00:50 - mmengine - INFO - Epoch(train) [283][25/63] lr: 1.8516e-03 eta: 9:58:59 time: 0.5524 data_time: 0.0279 memory: 17620 loss: 1.9611 loss_prob: 1.1529 loss_thr: 0.6223 loss_db: 0.1859 2022/11/01 16:00:53 - mmengine - INFO - Epoch(train) [283][30/63] lr: 1.8516e-03 eta: 9:58:52 time: 0.5959 data_time: 0.0319 memory: 17620 loss: 1.9355 loss_prob: 1.1206 loss_thr: 0.6310 loss_db: 0.1838 2022/11/01 16:00:56 - mmengine - INFO - Epoch(train) [283][35/63] lr: 1.8516e-03 eta: 9:58:52 time: 0.6205 data_time: 0.0138 memory: 17620 loss: 1.9351 loss_prob: 1.1080 loss_thr: 0.6431 loss_db: 0.1841 2022/11/01 16:00:59 - mmengine - INFO - Epoch(train) [283][40/63] lr: 1.8516e-03 eta: 9:58:46 time: 0.6010 data_time: 0.0091 memory: 17620 loss: 1.7877 loss_prob: 1.0149 loss_thr: 0.6058 loss_db: 0.1670 2022/11/01 16:01:02 - mmengine - INFO - Epoch(train) [283][45/63] lr: 1.8516e-03 eta: 9:58:46 time: 0.5706 data_time: 0.0085 memory: 17620 loss: 1.7918 loss_prob: 1.0253 loss_thr: 0.5986 loss_db: 0.1680 2022/11/01 16:01:05 - mmengine - INFO - Epoch(train) [283][50/63] lr: 1.8516e-03 eta: 9:58:38 time: 0.5751 data_time: 0.0203 memory: 17620 loss: 1.7795 loss_prob: 1.0226 loss_thr: 0.5907 loss_db: 0.1661 2022/11/01 16:01:08 - mmengine - INFO - Epoch(train) [283][55/63] lr: 1.8516e-03 eta: 9:58:38 time: 0.5996 data_time: 0.0235 memory: 17620 loss: 1.7143 loss_prob: 0.9779 loss_thr: 0.5789 loss_db: 0.1574 2022/11/01 16:01:11 - mmengine - INFO - Epoch(train) [283][60/63] lr: 1.8516e-03 eta: 9:58:31 time: 0.6043 data_time: 0.0090 memory: 17620 loss: 1.7217 loss_prob: 0.9890 loss_thr: 0.5722 loss_db: 0.1605 2022/11/01 16:01:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:01:17 - mmengine - INFO - Epoch(train) [284][5/63] lr: 1.8498e-03 eta: 9:58:31 time: 0.7534 data_time: 0.2192 memory: 17620 loss: 1.8718 loss_prob: 1.1031 loss_thr: 0.5971 loss_db: 0.1716 2022/11/01 16:01:20 - mmengine - INFO - Epoch(train) [284][10/63] lr: 1.8498e-03 eta: 9:58:22 time: 0.7717 data_time: 0.2233 memory: 17620 loss: 1.8346 loss_prob: 1.0534 loss_thr: 0.6130 loss_db: 0.1683 2022/11/01 16:01:23 - mmengine - INFO - Epoch(train) [284][15/63] lr: 1.8498e-03 eta: 9:58:22 time: 0.5855 data_time: 0.0115 memory: 17620 loss: 1.8285 loss_prob: 1.0522 loss_thr: 0.6053 loss_db: 0.1710 2022/11/01 16:01:26 - mmengine - INFO - Epoch(train) [284][20/63] lr: 1.8498e-03 eta: 9:58:14 time: 0.5880 data_time: 0.0065 memory: 17620 loss: 1.7930 loss_prob: 1.0268 loss_thr: 0.6014 loss_db: 0.1648 2022/11/01 16:01:29 - mmengine - INFO - Epoch(train) [284][25/63] lr: 1.8498e-03 eta: 9:58:14 time: 0.5904 data_time: 0.0397 memory: 17620 loss: 1.7968 loss_prob: 1.0415 loss_thr: 0.5911 loss_db: 0.1643 2022/11/01 16:01:32 - mmengine - INFO - Epoch(train) [284][30/63] lr: 1.8498e-03 eta: 9:58:07 time: 0.5706 data_time: 0.0419 memory: 17620 loss: 1.7747 loss_prob: 1.0424 loss_thr: 0.5644 loss_db: 0.1680 2022/11/01 16:01:35 - mmengine - INFO - Epoch(train) [284][35/63] lr: 1.8498e-03 eta: 9:58:07 time: 0.5656 data_time: 0.0166 memory: 17620 loss: 1.9766 loss_prob: 1.1869 loss_thr: 0.5965 loss_db: 0.1933 2022/11/01 16:01:38 - mmengine - INFO - Epoch(train) [284][40/63] lr: 1.8498e-03 eta: 9:58:00 time: 0.6081 data_time: 0.0187 memory: 17620 loss: 2.2167 loss_prob: 1.3615 loss_thr: 0.6354 loss_db: 0.2198 2022/11/01 16:01:41 - mmengine - INFO - Epoch(train) [284][45/63] lr: 1.8498e-03 eta: 9:58:00 time: 0.5777 data_time: 0.0100 memory: 17620 loss: 2.0120 loss_prob: 1.2062 loss_thr: 0.6117 loss_db: 0.1941 2022/11/01 16:01:44 - mmengine - INFO - Epoch(train) [284][50/63] lr: 1.8498e-03 eta: 9:57:52 time: 0.5720 data_time: 0.0187 memory: 17620 loss: 1.8740 loss_prob: 1.0860 loss_thr: 0.6139 loss_db: 0.1740 2022/11/01 16:01:46 - mmengine - INFO - Epoch(train) [284][55/63] lr: 1.8498e-03 eta: 9:57:52 time: 0.5805 data_time: 0.0191 memory: 17620 loss: 1.9744 loss_prob: 1.1611 loss_thr: 0.6263 loss_db: 0.1870 2022/11/01 16:01:49 - mmengine - INFO - Epoch(train) [284][60/63] lr: 1.8498e-03 eta: 9:57:43 time: 0.5430 data_time: 0.0084 memory: 17620 loss: 1.9612 loss_prob: 1.1804 loss_thr: 0.5900 loss_db: 0.1909 2022/11/01 16:01:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:01:55 - mmengine - INFO - Epoch(train) [285][5/63] lr: 1.8480e-03 eta: 9:57:43 time: 0.7184 data_time: 0.2107 memory: 17620 loss: 2.1005 loss_prob: 1.2932 loss_thr: 0.6059 loss_db: 0.2014 2022/11/01 16:01:58 - mmengine - INFO - Epoch(train) [285][10/63] lr: 1.8480e-03 eta: 9:57:33 time: 0.7489 data_time: 0.2103 memory: 17620 loss: 2.1358 loss_prob: 1.3137 loss_thr: 0.6179 loss_db: 0.2041 2022/11/01 16:02:01 - mmengine - INFO - Epoch(train) [285][15/63] lr: 1.8480e-03 eta: 9:57:33 time: 0.5598 data_time: 0.0056 memory: 17620 loss: 1.9749 loss_prob: 1.1809 loss_thr: 0.6074 loss_db: 0.1866 2022/11/01 16:02:04 - mmengine - INFO - Epoch(train) [285][20/63] lr: 1.8480e-03 eta: 9:57:26 time: 0.5753 data_time: 0.0068 memory: 17620 loss: 1.8553 loss_prob: 1.0853 loss_thr: 0.5955 loss_db: 0.1745 2022/11/01 16:02:07 - mmengine - INFO - Epoch(train) [285][25/63] lr: 1.8480e-03 eta: 9:57:26 time: 0.5756 data_time: 0.0225 memory: 17620 loss: 1.9318 loss_prob: 1.1512 loss_thr: 0.6011 loss_db: 0.1795 2022/11/01 16:02:10 - mmengine - INFO - Epoch(train) [285][30/63] lr: 1.8480e-03 eta: 9:57:20 time: 0.6234 data_time: 0.0427 memory: 17620 loss: 2.1921 loss_prob: 1.3350 loss_thr: 0.6457 loss_db: 0.2114 2022/11/01 16:02:13 - mmengine - INFO - Epoch(train) [285][35/63] lr: 1.8480e-03 eta: 9:57:20 time: 0.5963 data_time: 0.0266 memory: 17620 loss: 2.1648 loss_prob: 1.3068 loss_thr: 0.6461 loss_db: 0.2119 2022/11/01 16:02:16 - mmengine - INFO - Epoch(train) [285][40/63] lr: 1.8480e-03 eta: 9:57:13 time: 0.6142 data_time: 0.0049 memory: 17620 loss: 1.9626 loss_prob: 1.1640 loss_thr: 0.6121 loss_db: 0.1865 2022/11/01 16:02:19 - mmengine - INFO - Epoch(train) [285][45/63] lr: 1.8480e-03 eta: 9:57:13 time: 0.6127 data_time: 0.0064 memory: 17620 loss: 2.0173 loss_prob: 1.1903 loss_thr: 0.6335 loss_db: 0.1934 2022/11/01 16:02:22 - mmengine - INFO - Epoch(train) [285][50/63] lr: 1.8480e-03 eta: 9:57:05 time: 0.5561 data_time: 0.0145 memory: 17620 loss: 2.0643 loss_prob: 1.2199 loss_thr: 0.6462 loss_db: 0.1982 2022/11/01 16:02:24 - mmengine - INFO - Epoch(train) [285][55/63] lr: 1.8480e-03 eta: 9:57:05 time: 0.5661 data_time: 0.0234 memory: 17620 loss: 2.1132 loss_prob: 1.2805 loss_thr: 0.6314 loss_db: 0.2013 2022/11/01 16:02:28 - mmengine - INFO - Epoch(train) [285][60/63] lr: 1.8480e-03 eta: 9:56:59 time: 0.6490 data_time: 0.0155 memory: 17620 loss: 2.1375 loss_prob: 1.2941 loss_thr: 0.6413 loss_db: 0.2022 2022/11/01 16:02:29 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:02:35 - mmengine - INFO - Epoch(train) [286][5/63] lr: 1.8462e-03 eta: 9:56:59 time: 0.8156 data_time: 0.2339 memory: 17620 loss: 1.9042 loss_prob: 1.1237 loss_thr: 0.5972 loss_db: 0.1833 2022/11/01 16:02:38 - mmengine - INFO - Epoch(train) [286][10/63] lr: 1.8462e-03 eta: 9:56:53 time: 0.8681 data_time: 0.2359 memory: 17620 loss: 1.8232 loss_prob: 1.0608 loss_thr: 0.5907 loss_db: 0.1717 2022/11/01 16:02:41 - mmengine - INFO - Epoch(train) [286][15/63] lr: 1.8462e-03 eta: 9:56:53 time: 0.5993 data_time: 0.0130 memory: 17620 loss: 1.9102 loss_prob: 1.1166 loss_thr: 0.6124 loss_db: 0.1813 2022/11/01 16:02:44 - mmengine - INFO - Epoch(train) [286][20/63] lr: 1.8462e-03 eta: 9:56:47 time: 0.6050 data_time: 0.0136 memory: 17620 loss: 1.8795 loss_prob: 1.1090 loss_thr: 0.5915 loss_db: 0.1789 2022/11/01 16:02:48 - mmengine - INFO - Epoch(train) [286][25/63] lr: 1.8462e-03 eta: 9:56:47 time: 0.6831 data_time: 0.0482 memory: 17620 loss: 2.0040 loss_prob: 1.2194 loss_thr: 0.5931 loss_db: 0.1914 2022/11/01 16:02:51 - mmengine - INFO - Epoch(train) [286][30/63] lr: 1.8462e-03 eta: 9:56:42 time: 0.6773 data_time: 0.0505 memory: 17620 loss: 1.9889 loss_prob: 1.2084 loss_thr: 0.5847 loss_db: 0.1958 2022/11/01 16:02:54 - mmengine - INFO - Epoch(train) [286][35/63] lr: 1.8462e-03 eta: 9:56:42 time: 0.6370 data_time: 0.0151 memory: 17620 loss: 1.9319 loss_prob: 1.1573 loss_thr: 0.5787 loss_db: 0.1960 2022/11/01 16:02:57 - mmengine - INFO - Epoch(train) [286][40/63] lr: 1.8462e-03 eta: 9:56:35 time: 0.5867 data_time: 0.0087 memory: 17620 loss: 1.9185 loss_prob: 1.1439 loss_thr: 0.5879 loss_db: 0.1867 2022/11/01 16:03:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:03:00 - mmengine - INFO - Epoch(train) [286][45/63] lr: 1.8462e-03 eta: 9:56:35 time: 0.5523 data_time: 0.0068 memory: 17620 loss: 2.0489 loss_prob: 1.2252 loss_thr: 0.6313 loss_db: 0.1924 2022/11/01 16:03:02 - mmengine - INFO - Epoch(train) [286][50/63] lr: 1.8462e-03 eta: 9:56:27 time: 0.5670 data_time: 0.0227 memory: 17620 loss: 2.1353 loss_prob: 1.2714 loss_thr: 0.6633 loss_db: 0.2006 2022/11/01 16:03:06 - mmengine - INFO - Epoch(train) [286][55/63] lr: 1.8462e-03 eta: 9:56:27 time: 0.6047 data_time: 0.0260 memory: 17620 loss: 1.8658 loss_prob: 1.0806 loss_thr: 0.6138 loss_db: 0.1714 2022/11/01 16:03:09 - mmengine - INFO - Epoch(train) [286][60/63] lr: 1.8462e-03 eta: 9:56:21 time: 0.6366 data_time: 0.0087 memory: 17620 loss: 1.8719 loss_prob: 1.1026 loss_thr: 0.5919 loss_db: 0.1773 2022/11/01 16:03:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:03:16 - mmengine - INFO - Epoch(train) [287][5/63] lr: 1.8444e-03 eta: 9:56:21 time: 0.8573 data_time: 0.1933 memory: 17620 loss: 2.0330 loss_prob: 1.2084 loss_thr: 0.6292 loss_db: 0.1954 2022/11/01 16:03:19 - mmengine - INFO - Epoch(train) [287][10/63] lr: 1.8444e-03 eta: 9:56:14 time: 0.8208 data_time: 0.1985 memory: 17620 loss: 1.8601 loss_prob: 1.0876 loss_thr: 0.5968 loss_db: 0.1757 2022/11/01 16:03:22 - mmengine - INFO - Epoch(train) [287][15/63] lr: 1.8444e-03 eta: 9:56:14 time: 0.5921 data_time: 0.0102 memory: 17620 loss: 1.9547 loss_prob: 1.1475 loss_thr: 0.6236 loss_db: 0.1836 2022/11/01 16:03:25 - mmengine - INFO - Epoch(train) [287][20/63] lr: 1.8444e-03 eta: 9:56:06 time: 0.5774 data_time: 0.0049 memory: 17620 loss: 1.9469 loss_prob: 1.1320 loss_thr: 0.6327 loss_db: 0.1822 2022/11/01 16:03:28 - mmengine - INFO - Epoch(train) [287][25/63] lr: 1.8444e-03 eta: 9:56:06 time: 0.5709 data_time: 0.0180 memory: 17620 loss: 1.8976 loss_prob: 1.1068 loss_thr: 0.6103 loss_db: 0.1805 2022/11/01 16:03:31 - mmengine - INFO - Epoch(train) [287][30/63] lr: 1.8444e-03 eta: 9:55:59 time: 0.6105 data_time: 0.0317 memory: 17620 loss: 1.8908 loss_prob: 1.1030 loss_thr: 0.6110 loss_db: 0.1768 2022/11/01 16:03:34 - mmengine - INFO - Epoch(train) [287][35/63] lr: 1.8444e-03 eta: 9:55:59 time: 0.6041 data_time: 0.0231 memory: 17620 loss: 1.7926 loss_prob: 1.0460 loss_thr: 0.5817 loss_db: 0.1648 2022/11/01 16:03:37 - mmengine - INFO - Epoch(train) [287][40/63] lr: 1.8444e-03 eta: 9:55:52 time: 0.5881 data_time: 0.0102 memory: 17620 loss: 1.8477 loss_prob: 1.0883 loss_thr: 0.5859 loss_db: 0.1735 2022/11/01 16:03:40 - mmengine - INFO - Epoch(train) [287][45/63] lr: 1.8444e-03 eta: 9:55:52 time: 0.5842 data_time: 0.0054 memory: 17620 loss: 1.8942 loss_prob: 1.1038 loss_thr: 0.6130 loss_db: 0.1774 2022/11/01 16:03:43 - mmengine - INFO - Epoch(train) [287][50/63] lr: 1.8444e-03 eta: 9:55:45 time: 0.6021 data_time: 0.0148 memory: 17620 loss: 1.7826 loss_prob: 1.0208 loss_thr: 0.5961 loss_db: 0.1658 2022/11/01 16:03:46 - mmengine - INFO - Epoch(train) [287][55/63] lr: 1.8444e-03 eta: 9:55:45 time: 0.5835 data_time: 0.0220 memory: 17620 loss: 1.8399 loss_prob: 1.0637 loss_thr: 0.6064 loss_db: 0.1698 2022/11/01 16:03:48 - mmengine - INFO - Epoch(train) [287][60/63] lr: 1.8444e-03 eta: 9:55:37 time: 0.5529 data_time: 0.0139 memory: 17620 loss: 1.9977 loss_prob: 1.1852 loss_thr: 0.6238 loss_db: 0.1887 2022/11/01 16:03:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:03:54 - mmengine - INFO - Epoch(train) [288][5/63] lr: 1.8425e-03 eta: 9:55:37 time: 0.7189 data_time: 0.1971 memory: 17620 loss: 1.8689 loss_prob: 1.0907 loss_thr: 0.6044 loss_db: 0.1737 2022/11/01 16:03:57 - mmengine - INFO - Epoch(train) [288][10/63] lr: 1.8425e-03 eta: 9:55:27 time: 0.7589 data_time: 0.2082 memory: 17620 loss: 1.8545 loss_prob: 1.0917 loss_thr: 0.5898 loss_db: 0.1730 2022/11/01 16:04:00 - mmengine - INFO - Epoch(train) [288][15/63] lr: 1.8425e-03 eta: 9:55:27 time: 0.5617 data_time: 0.0178 memory: 17620 loss: 1.9461 loss_prob: 1.1525 loss_thr: 0.6098 loss_db: 0.1838 2022/11/01 16:04:03 - mmengine - INFO - Epoch(train) [288][20/63] lr: 1.8425e-03 eta: 9:55:18 time: 0.5203 data_time: 0.0071 memory: 17620 loss: 1.9572 loss_prob: 1.1557 loss_thr: 0.6143 loss_db: 0.1872 2022/11/01 16:04:05 - mmengine - INFO - Epoch(train) [288][25/63] lr: 1.8425e-03 eta: 9:55:18 time: 0.5475 data_time: 0.0195 memory: 17620 loss: 1.9512 loss_prob: 1.1602 loss_thr: 0.6018 loss_db: 0.1892 2022/11/01 16:04:08 - mmengine - INFO - Epoch(train) [288][30/63] lr: 1.8425e-03 eta: 9:55:10 time: 0.5710 data_time: 0.0244 memory: 17620 loss: 1.9586 loss_prob: 1.1658 loss_thr: 0.6047 loss_db: 0.1882 2022/11/01 16:04:11 - mmengine - INFO - Epoch(train) [288][35/63] lr: 1.8425e-03 eta: 9:55:10 time: 0.5638 data_time: 0.0208 memory: 17620 loss: 1.9649 loss_prob: 1.1472 loss_thr: 0.6294 loss_db: 0.1883 2022/11/01 16:04:14 - mmengine - INFO - Epoch(train) [288][40/63] lr: 1.8425e-03 eta: 9:55:02 time: 0.5522 data_time: 0.0159 memory: 17620 loss: 1.9759 loss_prob: 1.1413 loss_thr: 0.6466 loss_db: 0.1880 2022/11/01 16:04:17 - mmengine - INFO - Epoch(train) [288][45/63] lr: 1.8425e-03 eta: 9:55:02 time: 0.5463 data_time: 0.0088 memory: 17620 loss: 1.9473 loss_prob: 1.1429 loss_thr: 0.6207 loss_db: 0.1837 2022/11/01 16:04:19 - mmengine - INFO - Epoch(train) [288][50/63] lr: 1.8425e-03 eta: 9:54:54 time: 0.5622 data_time: 0.0198 memory: 17620 loss: 2.0026 loss_prob: 1.1966 loss_thr: 0.6161 loss_db: 0.1900 2022/11/01 16:04:22 - mmengine - INFO - Epoch(train) [288][55/63] lr: 1.8425e-03 eta: 9:54:54 time: 0.5710 data_time: 0.0238 memory: 17620 loss: 2.0499 loss_prob: 1.2257 loss_thr: 0.6254 loss_db: 0.1988 2022/11/01 16:04:25 - mmengine - INFO - Epoch(train) [288][60/63] lr: 1.8425e-03 eta: 9:54:45 time: 0.5621 data_time: 0.0152 memory: 17620 loss: 2.0016 loss_prob: 1.1814 loss_thr: 0.6270 loss_db: 0.1932 2022/11/01 16:04:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:04:32 - mmengine - INFO - Epoch(train) [289][5/63] lr: 1.8407e-03 eta: 9:54:45 time: 0.8215 data_time: 0.2250 memory: 17620 loss: 2.1110 loss_prob: 1.2913 loss_thr: 0.6177 loss_db: 0.2019 2022/11/01 16:04:35 - mmengine - INFO - Epoch(train) [289][10/63] lr: 1.8407e-03 eta: 9:54:39 time: 0.8730 data_time: 0.2251 memory: 17620 loss: 2.0229 loss_prob: 1.2343 loss_thr: 0.5954 loss_db: 0.1932 2022/11/01 16:04:38 - mmengine - INFO - Epoch(train) [289][15/63] lr: 1.8407e-03 eta: 9:54:39 time: 0.6105 data_time: 0.0058 memory: 17620 loss: 1.8008 loss_prob: 1.0539 loss_thr: 0.5762 loss_db: 0.1707 2022/11/01 16:04:41 - mmengine - INFO - Epoch(train) [289][20/63] lr: 1.8407e-03 eta: 9:54:32 time: 0.5808 data_time: 0.0056 memory: 17620 loss: 1.8851 loss_prob: 1.0931 loss_thr: 0.6130 loss_db: 0.1790 2022/11/01 16:04:44 - mmengine - INFO - Epoch(train) [289][25/63] lr: 1.8407e-03 eta: 9:54:32 time: 0.5796 data_time: 0.0375 memory: 17620 loss: 1.8726 loss_prob: 1.0878 loss_thr: 0.6095 loss_db: 0.1752 2022/11/01 16:04:47 - mmengine - INFO - Epoch(train) [289][30/63] lr: 1.8407e-03 eta: 9:54:26 time: 0.6185 data_time: 0.0498 memory: 17620 loss: 1.7863 loss_prob: 1.0304 loss_thr: 0.5864 loss_db: 0.1695 2022/11/01 16:04:50 - mmengine - INFO - Epoch(train) [289][35/63] lr: 1.8407e-03 eta: 9:54:26 time: 0.6186 data_time: 0.0175 memory: 17620 loss: 1.7712 loss_prob: 1.0281 loss_thr: 0.5741 loss_db: 0.1690 2022/11/01 16:04:53 - mmengine - INFO - Epoch(train) [289][40/63] lr: 1.8407e-03 eta: 9:54:19 time: 0.6080 data_time: 0.0061 memory: 17620 loss: 1.8122 loss_prob: 1.0371 loss_thr: 0.6096 loss_db: 0.1656 2022/11/01 16:04:56 - mmengine - INFO - Epoch(train) [289][45/63] lr: 1.8407e-03 eta: 9:54:19 time: 0.6054 data_time: 0.0058 memory: 17620 loss: 1.8007 loss_prob: 1.0264 loss_thr: 0.6094 loss_db: 0.1649 2022/11/01 16:05:00 - mmengine - INFO - Epoch(train) [289][50/63] lr: 1.8407e-03 eta: 9:54:14 time: 0.6590 data_time: 0.0161 memory: 17620 loss: 1.7610 loss_prob: 1.0224 loss_thr: 0.5748 loss_db: 0.1638 2022/11/01 16:05:03 - mmengine - INFO - Epoch(train) [289][55/63] lr: 1.8407e-03 eta: 9:54:14 time: 0.6460 data_time: 0.0279 memory: 17620 loss: 1.7664 loss_prob: 1.0193 loss_thr: 0.5826 loss_db: 0.1646 2022/11/01 16:05:05 - mmengine - INFO - Epoch(train) [289][60/63] lr: 1.8407e-03 eta: 9:54:06 time: 0.5696 data_time: 0.0177 memory: 17620 loss: 1.8048 loss_prob: 1.0499 loss_thr: 0.5831 loss_db: 0.1717 2022/11/01 16:05:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:05:14 - mmengine - INFO - Epoch(train) [290][5/63] lr: 1.8389e-03 eta: 9:54:06 time: 0.9245 data_time: 0.2846 memory: 17620 loss: 1.8628 loss_prob: 1.0783 loss_thr: 0.6072 loss_db: 0.1773 2022/11/01 16:05:17 - mmengine - INFO - Epoch(train) [290][10/63] lr: 1.8389e-03 eta: 9:54:03 time: 0.9709 data_time: 0.2846 memory: 17620 loss: 1.6714 loss_prob: 0.9474 loss_thr: 0.5660 loss_db: 0.1579 2022/11/01 16:05:21 - mmengine - INFO - Epoch(train) [290][15/63] lr: 1.8389e-03 eta: 9:54:03 time: 0.6999 data_time: 0.0124 memory: 17620 loss: 1.5832 loss_prob: 0.8970 loss_thr: 0.5401 loss_db: 0.1461 2022/11/01 16:05:24 - mmengine - INFO - Epoch(train) [290][20/63] lr: 1.8389e-03 eta: 9:53:59 time: 0.6897 data_time: 0.0061 memory: 17620 loss: 1.7765 loss_prob: 1.0270 loss_thr: 0.5827 loss_db: 0.1668 2022/11/01 16:05:27 - mmengine - INFO - Epoch(train) [290][25/63] lr: 1.8389e-03 eta: 9:53:59 time: 0.6329 data_time: 0.0231 memory: 17620 loss: 1.9848 loss_prob: 1.1657 loss_thr: 0.6268 loss_db: 0.1923 2022/11/01 16:05:31 - mmengine - INFO - Epoch(train) [290][30/63] lr: 1.8389e-03 eta: 9:53:55 time: 0.6998 data_time: 0.0317 memory: 17620 loss: 1.9344 loss_prob: 1.1433 loss_thr: 0.6085 loss_db: 0.1826 2022/11/01 16:05:34 - mmengine - INFO - Epoch(train) [290][35/63] lr: 1.8389e-03 eta: 9:53:55 time: 0.7025 data_time: 0.0174 memory: 17620 loss: 1.7950 loss_prob: 1.0499 loss_thr: 0.5798 loss_db: 0.1654 2022/11/01 16:05:37 - mmengine - INFO - Epoch(train) [290][40/63] lr: 1.8389e-03 eta: 9:53:49 time: 0.6111 data_time: 0.0088 memory: 17620 loss: 1.8514 loss_prob: 1.0739 loss_thr: 0.6007 loss_db: 0.1767 2022/11/01 16:05:40 - mmengine - INFO - Epoch(train) [290][45/63] lr: 1.8389e-03 eta: 9:53:49 time: 0.6022 data_time: 0.0064 memory: 17620 loss: 1.8294 loss_prob: 1.0576 loss_thr: 0.5992 loss_db: 0.1725 2022/11/01 16:05:44 - mmengine - INFO - Epoch(train) [290][50/63] lr: 1.8389e-03 eta: 9:53:45 time: 0.6864 data_time: 0.0214 memory: 17620 loss: 1.8370 loss_prob: 1.0769 loss_thr: 0.5847 loss_db: 0.1754 2022/11/01 16:05:46 - mmengine - INFO - Epoch(train) [290][55/63] lr: 1.8389e-03 eta: 9:53:45 time: 0.6505 data_time: 0.0199 memory: 17620 loss: 1.8712 loss_prob: 1.1043 loss_thr: 0.5835 loss_db: 0.1834 2022/11/01 16:05:49 - mmengine - INFO - Epoch(train) [290][60/63] lr: 1.8389e-03 eta: 9:53:38 time: 0.5980 data_time: 0.0086 memory: 17620 loss: 1.8554 loss_prob: 1.0765 loss_thr: 0.6036 loss_db: 0.1752 2022/11/01 16:05:51 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:05:56 - mmengine - INFO - Epoch(train) [291][5/63] lr: 1.8371e-03 eta: 9:53:38 time: 0.7978 data_time: 0.2061 memory: 17620 loss: 1.9945 loss_prob: 1.1797 loss_thr: 0.6239 loss_db: 0.1908 2022/11/01 16:05:59 - mmengine - INFO - Epoch(train) [291][10/63] lr: 1.8371e-03 eta: 9:53:29 time: 0.7753 data_time: 0.2142 memory: 17620 loss: 1.9905 loss_prob: 1.1659 loss_thr: 0.6369 loss_db: 0.1876 2022/11/01 16:06:02 - mmengine - INFO - Epoch(train) [291][15/63] lr: 1.8371e-03 eta: 9:53:29 time: 0.5473 data_time: 0.0137 memory: 17620 loss: 2.0145 loss_prob: 1.1930 loss_thr: 0.6266 loss_db: 0.1949 2022/11/01 16:06:05 - mmengine - INFO - Epoch(train) [291][20/63] lr: 1.8371e-03 eta: 9:53:21 time: 0.5676 data_time: 0.0054 memory: 17620 loss: 1.9232 loss_prob: 1.1379 loss_thr: 0.5961 loss_db: 0.1893 2022/11/01 16:06:08 - mmengine - INFO - Epoch(train) [291][25/63] lr: 1.8371e-03 eta: 9:53:21 time: 0.6001 data_time: 0.0149 memory: 17620 loss: 1.8195 loss_prob: 1.0502 loss_thr: 0.5975 loss_db: 0.1719 2022/11/01 16:06:11 - mmengine - INFO - Epoch(train) [291][30/63] lr: 1.8371e-03 eta: 9:53:14 time: 0.5919 data_time: 0.0273 memory: 17620 loss: 1.9179 loss_prob: 1.1256 loss_thr: 0.6097 loss_db: 0.1826 2022/11/01 16:06:14 - mmengine - INFO - Epoch(train) [291][35/63] lr: 1.8371e-03 eta: 9:53:14 time: 0.5958 data_time: 0.0248 memory: 17620 loss: 2.2102 loss_prob: 1.3818 loss_thr: 0.6060 loss_db: 0.2224 2022/11/01 16:06:16 - mmengine - INFO - Epoch(train) [291][40/63] lr: 1.8371e-03 eta: 9:53:07 time: 0.5967 data_time: 0.0118 memory: 17620 loss: 2.3224 loss_prob: 1.4526 loss_thr: 0.6407 loss_db: 0.2291 2022/11/01 16:06:19 - mmengine - INFO - Epoch(train) [291][45/63] lr: 1.8371e-03 eta: 9:53:07 time: 0.5895 data_time: 0.0044 memory: 17620 loss: 2.7350 loss_prob: 1.7491 loss_thr: 0.7148 loss_db: 0.2711 2022/11/01 16:06:22 - mmengine - INFO - Epoch(train) [291][50/63] lr: 1.8371e-03 eta: 9:52:59 time: 0.5762 data_time: 0.0170 memory: 17620 loss: 2.7601 loss_prob: 1.7388 loss_thr: 0.7434 loss_db: 0.2780 2022/11/01 16:06:25 - mmengine - INFO - Epoch(train) [291][55/63] lr: 1.8371e-03 eta: 9:52:59 time: 0.5580 data_time: 0.0216 memory: 17620 loss: 2.3669 loss_prob: 1.4400 loss_thr: 0.6889 loss_db: 0.2381 2022/11/01 16:06:28 - mmengine - INFO - Epoch(train) [291][60/63] lr: 1.8371e-03 eta: 9:52:52 time: 0.5926 data_time: 0.0129 memory: 17620 loss: 2.3649 loss_prob: 1.4757 loss_thr: 0.6460 loss_db: 0.2432 2022/11/01 16:06:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:06:34 - mmengine - INFO - Epoch(train) [292][5/63] lr: 1.8353e-03 eta: 9:52:52 time: 0.7329 data_time: 0.2046 memory: 17620 loss: 2.3450 loss_prob: 1.4496 loss_thr: 0.6700 loss_db: 0.2255 2022/11/01 16:06:37 - mmengine - INFO - Epoch(train) [292][10/63] lr: 1.8353e-03 eta: 9:52:42 time: 0.7457 data_time: 0.2069 memory: 17620 loss: 2.1523 loss_prob: 1.2972 loss_thr: 0.6486 loss_db: 0.2065 2022/11/01 16:06:40 - mmengine - INFO - Epoch(train) [292][15/63] lr: 1.8353e-03 eta: 9:52:42 time: 0.5549 data_time: 0.0096 memory: 17620 loss: 2.0609 loss_prob: 1.2304 loss_thr: 0.6292 loss_db: 0.2013 2022/11/01 16:06:43 - mmengine - INFO - Epoch(train) [292][20/63] lr: 1.8353e-03 eta: 9:52:34 time: 0.5485 data_time: 0.0073 memory: 17620 loss: 2.2198 loss_prob: 1.3399 loss_thr: 0.6595 loss_db: 0.2203 2022/11/01 16:06:45 - mmengine - INFO - Epoch(train) [292][25/63] lr: 1.8353e-03 eta: 9:52:34 time: 0.5355 data_time: 0.0241 memory: 17620 loss: 2.2416 loss_prob: 1.3632 loss_thr: 0.6551 loss_db: 0.2233 2022/11/01 16:06:48 - mmengine - INFO - Epoch(train) [292][30/63] lr: 1.8353e-03 eta: 9:52:25 time: 0.5493 data_time: 0.0324 memory: 17620 loss: 2.0179 loss_prob: 1.2057 loss_thr: 0.6193 loss_db: 0.1929 2022/11/01 16:06:51 - mmengine - INFO - Epoch(train) [292][35/63] lr: 1.8353e-03 eta: 9:52:25 time: 0.5364 data_time: 0.0155 memory: 17620 loss: 2.0855 loss_prob: 1.2321 loss_thr: 0.6566 loss_db: 0.1968 2022/11/01 16:06:53 - mmengine - INFO - Epoch(train) [292][40/63] lr: 1.8353e-03 eta: 9:52:15 time: 0.5088 data_time: 0.0071 memory: 17620 loss: 2.0784 loss_prob: 1.2256 loss_thr: 0.6551 loss_db: 0.1977 2022/11/01 16:06:56 - mmengine - INFO - Epoch(train) [292][45/63] lr: 1.8353e-03 eta: 9:52:15 time: 0.5040 data_time: 0.0058 memory: 17620 loss: 1.8926 loss_prob: 1.1241 loss_thr: 0.5904 loss_db: 0.1780 2022/11/01 16:06:58 - mmengine - INFO - Epoch(train) [292][50/63] lr: 1.8353e-03 eta: 9:52:06 time: 0.5255 data_time: 0.0155 memory: 17620 loss: 1.9976 loss_prob: 1.2221 loss_thr: 0.5876 loss_db: 0.1879 2022/11/01 16:07:01 - mmengine - INFO - Epoch(train) [292][55/63] lr: 1.8353e-03 eta: 9:52:06 time: 0.5507 data_time: 0.0193 memory: 17620 loss: 1.9623 loss_prob: 1.1875 loss_thr: 0.5915 loss_db: 0.1832 2022/11/01 16:07:04 - mmengine - INFO - Epoch(train) [292][60/63] lr: 1.8353e-03 eta: 9:51:58 time: 0.5468 data_time: 0.0098 memory: 17620 loss: 1.9081 loss_prob: 1.1298 loss_thr: 0.5962 loss_db: 0.1821 2022/11/01 16:07:05 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:07:10 - mmengine - INFO - Epoch(train) [293][5/63] lr: 1.8335e-03 eta: 9:51:58 time: 0.6925 data_time: 0.1711 memory: 17620 loss: 1.9977 loss_prob: 1.1612 loss_thr: 0.6480 loss_db: 0.1885 2022/11/01 16:07:13 - mmengine - INFO - Epoch(train) [293][10/63] lr: 1.8335e-03 eta: 9:51:47 time: 0.7309 data_time: 0.1778 memory: 17620 loss: 1.8611 loss_prob: 1.0655 loss_thr: 0.6261 loss_db: 0.1696 2022/11/01 16:07:15 - mmengine - INFO - Epoch(train) [293][15/63] lr: 1.8335e-03 eta: 9:51:47 time: 0.5476 data_time: 0.0160 memory: 17620 loss: 1.8270 loss_prob: 1.0475 loss_thr: 0.6036 loss_db: 0.1759 2022/11/01 16:07:18 - mmengine - INFO - Epoch(train) [293][20/63] lr: 1.8335e-03 eta: 9:51:38 time: 0.5214 data_time: 0.0114 memory: 17620 loss: 1.9825 loss_prob: 1.1735 loss_thr: 0.6175 loss_db: 0.1915 2022/11/01 16:07:21 - mmengine - INFO - Epoch(train) [293][25/63] lr: 1.8335e-03 eta: 9:51:38 time: 0.5275 data_time: 0.0225 memory: 17620 loss: 2.0948 loss_prob: 1.2676 loss_thr: 0.6275 loss_db: 0.1997 2022/11/01 16:07:23 - mmengine - INFO - Epoch(train) [293][30/63] lr: 1.8335e-03 eta: 9:51:29 time: 0.5357 data_time: 0.0204 memory: 17620 loss: 1.9901 loss_prob: 1.1802 loss_thr: 0.6222 loss_db: 0.1878 2022/11/01 16:07:26 - mmengine - INFO - Epoch(train) [293][35/63] lr: 1.8335e-03 eta: 9:51:29 time: 0.5358 data_time: 0.0148 memory: 17620 loss: 1.9996 loss_prob: 1.1801 loss_thr: 0.6298 loss_db: 0.1898 2022/11/01 16:07:29 - mmengine - INFO - Epoch(train) [293][40/63] lr: 1.8335e-03 eta: 9:51:22 time: 0.5803 data_time: 0.0141 memory: 17620 loss: 2.1305 loss_prob: 1.2949 loss_thr: 0.6323 loss_db: 0.2033 2022/11/01 16:07:32 - mmengine - INFO - Epoch(train) [293][45/63] lr: 1.8335e-03 eta: 9:51:22 time: 0.5798 data_time: 0.0089 memory: 17620 loss: 2.0611 loss_prob: 1.2302 loss_thr: 0.6363 loss_db: 0.1946 2022/11/01 16:07:34 - mmengine - INFO - Epoch(train) [293][50/63] lr: 1.8335e-03 eta: 9:51:13 time: 0.5500 data_time: 0.0181 memory: 17620 loss: 1.9094 loss_prob: 1.1098 loss_thr: 0.6179 loss_db: 0.1816 2022/11/01 16:07:38 - mmengine - INFO - Epoch(train) [293][55/63] lr: 1.8335e-03 eta: 9:51:13 time: 0.6093 data_time: 0.0225 memory: 17620 loss: 1.9317 loss_prob: 1.1402 loss_thr: 0.6064 loss_db: 0.1851 2022/11/01 16:07:40 - mmengine - INFO - Epoch(train) [293][60/63] lr: 1.8335e-03 eta: 9:51:07 time: 0.6056 data_time: 0.0133 memory: 17620 loss: 1.8344 loss_prob: 1.0646 loss_thr: 0.5965 loss_db: 0.1732 2022/11/01 16:07:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:07:47 - mmengine - INFO - Epoch(train) [294][5/63] lr: 1.8316e-03 eta: 9:51:07 time: 0.7571 data_time: 0.2211 memory: 17620 loss: 2.0718 loss_prob: 1.2474 loss_thr: 0.6235 loss_db: 0.2009 2022/11/01 16:07:50 - mmengine - INFO - Epoch(train) [294][10/63] lr: 1.8316e-03 eta: 9:50:57 time: 0.7471 data_time: 0.2231 memory: 17620 loss: 1.8584 loss_prob: 1.0980 loss_thr: 0.5805 loss_db: 0.1800 2022/11/01 16:07:52 - mmengine - INFO - Epoch(train) [294][15/63] lr: 1.8316e-03 eta: 9:50:57 time: 0.5267 data_time: 0.0094 memory: 17620 loss: 1.9086 loss_prob: 1.1198 loss_thr: 0.6064 loss_db: 0.1824 2022/11/01 16:07:55 - mmengine - INFO - Epoch(train) [294][20/63] lr: 1.8316e-03 eta: 9:50:48 time: 0.5297 data_time: 0.0060 memory: 17620 loss: 1.8556 loss_prob: 1.0803 loss_thr: 0.6039 loss_db: 0.1713 2022/11/01 16:07:58 - mmengine - INFO - Epoch(train) [294][25/63] lr: 1.8316e-03 eta: 9:50:48 time: 0.5604 data_time: 0.0331 memory: 17620 loss: 1.7729 loss_prob: 1.0328 loss_thr: 0.5758 loss_db: 0.1643 2022/11/01 16:08:01 - mmengine - INFO - Epoch(train) [294][30/63] lr: 1.8316e-03 eta: 9:50:40 time: 0.5702 data_time: 0.0327 memory: 17620 loss: 1.7857 loss_prob: 1.0352 loss_thr: 0.5825 loss_db: 0.1680 2022/11/01 16:08:03 - mmengine - INFO - Epoch(train) [294][35/63] lr: 1.8316e-03 eta: 9:50:40 time: 0.5480 data_time: 0.0111 memory: 17620 loss: 1.8834 loss_prob: 1.0892 loss_thr: 0.6169 loss_db: 0.1772 2022/11/01 16:08:06 - mmengine - INFO - Epoch(train) [294][40/63] lr: 1.8316e-03 eta: 9:50:31 time: 0.5312 data_time: 0.0101 memory: 17620 loss: 2.0311 loss_prob: 1.1977 loss_thr: 0.6467 loss_db: 0.1866 2022/11/01 16:08:09 - mmengine - INFO - Epoch(train) [294][45/63] lr: 1.8316e-03 eta: 9:50:31 time: 0.5353 data_time: 0.0103 memory: 17620 loss: 1.9541 loss_prob: 1.1550 loss_thr: 0.6179 loss_db: 0.1812 2022/11/01 16:08:12 - mmengine - INFO - Epoch(train) [294][50/63] lr: 1.8316e-03 eta: 9:50:24 time: 0.5925 data_time: 0.0276 memory: 17620 loss: 1.8405 loss_prob: 1.0663 loss_thr: 0.6008 loss_db: 0.1734 2022/11/01 16:08:15 - mmengine - INFO - Epoch(train) [294][55/63] lr: 1.8316e-03 eta: 9:50:24 time: 0.6175 data_time: 0.0247 memory: 17620 loss: 1.8921 loss_prob: 1.0996 loss_thr: 0.6169 loss_db: 0.1755 2022/11/01 16:08:18 - mmengine - INFO - Epoch(train) [294][60/63] lr: 1.8316e-03 eta: 9:50:17 time: 0.5836 data_time: 0.0089 memory: 17620 loss: 1.9334 loss_prob: 1.1244 loss_thr: 0.6281 loss_db: 0.1809 2022/11/01 16:08:19 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:08:24 - mmengine - INFO - Epoch(train) [295][5/63] lr: 1.8298e-03 eta: 9:50:17 time: 0.7066 data_time: 0.1750 memory: 17620 loss: 1.8932 loss_prob: 1.0980 loss_thr: 0.6143 loss_db: 0.1809 2022/11/01 16:08:26 - mmengine - INFO - Epoch(train) [295][10/63] lr: 1.8298e-03 eta: 9:50:06 time: 0.7393 data_time: 0.1846 memory: 17620 loss: 1.8051 loss_prob: 1.0474 loss_thr: 0.5854 loss_db: 0.1723 2022/11/01 16:08:29 - mmengine - INFO - Epoch(train) [295][15/63] lr: 1.8298e-03 eta: 9:50:06 time: 0.5484 data_time: 0.0154 memory: 17620 loss: 1.9123 loss_prob: 1.1440 loss_thr: 0.5874 loss_db: 0.1809 2022/11/01 16:08:32 - mmengine - INFO - Epoch(train) [295][20/63] lr: 1.8298e-03 eta: 9:49:58 time: 0.5347 data_time: 0.0048 memory: 17620 loss: 1.9989 loss_prob: 1.2059 loss_thr: 0.6017 loss_db: 0.1913 2022/11/01 16:08:35 - mmengine - INFO - Epoch(train) [295][25/63] lr: 1.8298e-03 eta: 9:49:58 time: 0.5481 data_time: 0.0320 memory: 17620 loss: 1.7895 loss_prob: 1.0392 loss_thr: 0.5828 loss_db: 0.1675 2022/11/01 16:08:37 - mmengine - INFO - Epoch(train) [295][30/63] lr: 1.8298e-03 eta: 9:49:49 time: 0.5389 data_time: 0.0319 memory: 17620 loss: 1.7252 loss_prob: 0.9775 loss_thr: 0.5885 loss_db: 0.1591 2022/11/01 16:08:40 - mmengine - INFO - Epoch(train) [295][35/63] lr: 1.8298e-03 eta: 9:49:49 time: 0.5101 data_time: 0.0111 memory: 17620 loss: 1.7754 loss_prob: 1.0147 loss_thr: 0.5947 loss_db: 0.1659 2022/11/01 16:08:42 - mmengine - INFO - Epoch(train) [295][40/63] lr: 1.8298e-03 eta: 9:49:40 time: 0.5263 data_time: 0.0108 memory: 17620 loss: 1.8365 loss_prob: 1.0620 loss_thr: 0.6041 loss_db: 0.1704 2022/11/01 16:08:45 - mmengine - INFO - Epoch(train) [295][45/63] lr: 1.8298e-03 eta: 9:49:40 time: 0.5331 data_time: 0.0050 memory: 17620 loss: 1.9569 loss_prob: 1.1524 loss_thr: 0.6207 loss_db: 0.1838 2022/11/01 16:08:48 - mmengine - INFO - Epoch(train) [295][50/63] lr: 1.8298e-03 eta: 9:49:31 time: 0.5474 data_time: 0.0194 memory: 17620 loss: 1.9944 loss_prob: 1.1828 loss_thr: 0.6217 loss_db: 0.1899 2022/11/01 16:08:50 - mmengine - INFO - Epoch(train) [295][55/63] lr: 1.8298e-03 eta: 9:49:31 time: 0.5349 data_time: 0.0190 memory: 17620 loss: 1.9028 loss_prob: 1.1064 loss_thr: 0.6159 loss_db: 0.1806 2022/11/01 16:08:53 - mmengine - INFO - Epoch(train) [295][60/63] lr: 1.8298e-03 eta: 9:49:22 time: 0.5123 data_time: 0.0109 memory: 17620 loss: 1.9261 loss_prob: 1.1476 loss_thr: 0.5967 loss_db: 0.1818 2022/11/01 16:08:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:08:59 - mmengine - INFO - Epoch(train) [296][5/63] lr: 1.8280e-03 eta: 9:49:22 time: 0.6695 data_time: 0.1848 memory: 17620 loss: 1.8878 loss_prob: 1.1189 loss_thr: 0.5875 loss_db: 0.1813 2022/11/01 16:09:01 - mmengine - INFO - Epoch(train) [296][10/63] lr: 1.8280e-03 eta: 9:49:11 time: 0.7065 data_time: 0.1847 memory: 17620 loss: 1.8142 loss_prob: 1.0485 loss_thr: 0.5964 loss_db: 0.1693 2022/11/01 16:09:04 - mmengine - INFO - Epoch(train) [296][15/63] lr: 1.8280e-03 eta: 9:49:11 time: 0.5254 data_time: 0.0062 memory: 17620 loss: 1.8322 loss_prob: 1.0451 loss_thr: 0.6176 loss_db: 0.1696 2022/11/01 16:09:06 - mmengine - INFO - Epoch(train) [296][20/63] lr: 1.8280e-03 eta: 9:49:01 time: 0.5119 data_time: 0.0093 memory: 17620 loss: 1.8314 loss_prob: 1.0510 loss_thr: 0.6073 loss_db: 0.1731 2022/11/01 16:09:09 - mmengine - INFO - Epoch(train) [296][25/63] lr: 1.8280e-03 eta: 9:49:01 time: 0.5345 data_time: 0.0266 memory: 17620 loss: 1.7913 loss_prob: 1.0412 loss_thr: 0.5824 loss_db: 0.1678 2022/11/01 16:09:12 - mmengine - INFO - Epoch(train) [296][30/63] lr: 1.8280e-03 eta: 9:48:53 time: 0.5596 data_time: 0.0365 memory: 17620 loss: 1.8628 loss_prob: 1.0794 loss_thr: 0.6094 loss_db: 0.1740 2022/11/01 16:09:15 - mmengine - INFO - Epoch(train) [296][35/63] lr: 1.8280e-03 eta: 9:48:53 time: 0.5253 data_time: 0.0184 memory: 17620 loss: 1.9313 loss_prob: 1.1225 loss_thr: 0.6220 loss_db: 0.1868 2022/11/01 16:09:17 - mmengine - INFO - Epoch(train) [296][40/63] lr: 1.8280e-03 eta: 9:48:44 time: 0.5285 data_time: 0.0053 memory: 17620 loss: 2.1605 loss_prob: 1.3181 loss_thr: 0.6383 loss_db: 0.2041 2022/11/01 16:09:20 - mmengine - INFO - Epoch(train) [296][45/63] lr: 1.8280e-03 eta: 9:48:44 time: 0.5739 data_time: 0.0070 memory: 17620 loss: 2.1517 loss_prob: 1.3171 loss_thr: 0.6359 loss_db: 0.1986 2022/11/01 16:09:23 - mmengine - INFO - Epoch(train) [296][50/63] lr: 1.8280e-03 eta: 9:48:37 time: 0.5769 data_time: 0.0211 memory: 17620 loss: 1.8863 loss_prob: 1.1059 loss_thr: 0.6036 loss_db: 0.1768 2022/11/01 16:09:26 - mmengine - INFO - Epoch(train) [296][55/63] lr: 1.8280e-03 eta: 9:48:37 time: 0.5391 data_time: 0.0243 memory: 17620 loss: 1.7468 loss_prob: 1.0022 loss_thr: 0.5829 loss_db: 0.1617 2022/11/01 16:09:28 - mmengine - INFO - Epoch(train) [296][60/63] lr: 1.8280e-03 eta: 9:48:27 time: 0.5189 data_time: 0.0103 memory: 17620 loss: 1.9287 loss_prob: 1.1555 loss_thr: 0.5955 loss_db: 0.1777 2022/11/01 16:09:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:09:34 - mmengine - INFO - Epoch(train) [297][5/63] lr: 1.8262e-03 eta: 9:48:27 time: 0.7024 data_time: 0.1876 memory: 17620 loss: 1.7792 loss_prob: 1.0275 loss_thr: 0.5881 loss_db: 0.1636 2022/11/01 16:09:37 - mmengine - INFO - Epoch(train) [297][10/63] lr: 1.8262e-03 eta: 9:48:17 time: 0.7292 data_time: 0.1898 memory: 17620 loss: 1.8396 loss_prob: 1.0721 loss_thr: 0.5899 loss_db: 0.1777 2022/11/01 16:09:40 - mmengine - INFO - Epoch(train) [297][15/63] lr: 1.8262e-03 eta: 9:48:17 time: 0.5422 data_time: 0.0068 memory: 17620 loss: 1.9000 loss_prob: 1.0983 loss_thr: 0.6230 loss_db: 0.1787 2022/11/01 16:09:42 - mmengine - INFO - Epoch(train) [297][20/63] lr: 1.8262e-03 eta: 9:48:08 time: 0.5327 data_time: 0.0049 memory: 17620 loss: 1.9755 loss_prob: 1.1528 loss_thr: 0.6385 loss_db: 0.1841 2022/11/01 16:09:45 - mmengine - INFO - Epoch(train) [297][25/63] lr: 1.8262e-03 eta: 9:48:08 time: 0.5245 data_time: 0.0115 memory: 17620 loss: 2.0306 loss_prob: 1.1822 loss_thr: 0.6582 loss_db: 0.1903 2022/11/01 16:09:48 - mmengine - INFO - Epoch(train) [297][30/63] lr: 1.8262e-03 eta: 9:48:00 time: 0.5661 data_time: 0.0369 memory: 17620 loss: 1.9511 loss_prob: 1.1503 loss_thr: 0.6194 loss_db: 0.1814 2022/11/01 16:09:51 - mmengine - INFO - Epoch(train) [297][35/63] lr: 1.8262e-03 eta: 9:48:00 time: 0.5690 data_time: 0.0314 memory: 17620 loss: 1.7595 loss_prob: 1.0174 loss_thr: 0.5809 loss_db: 0.1611 2022/11/01 16:09:53 - mmengine - INFO - Epoch(train) [297][40/63] lr: 1.8262e-03 eta: 9:47:51 time: 0.5383 data_time: 0.0057 memory: 17620 loss: 1.7985 loss_prob: 1.0192 loss_thr: 0.6115 loss_db: 0.1679 2022/11/01 16:09:56 - mmengine - INFO - Epoch(train) [297][45/63] lr: 1.8262e-03 eta: 9:47:51 time: 0.5310 data_time: 0.0050 memory: 17620 loss: 1.7353 loss_prob: 0.9787 loss_thr: 0.5958 loss_db: 0.1608 2022/11/01 16:09:59 - mmengine - INFO - Epoch(train) [297][50/63] lr: 1.8262e-03 eta: 9:47:43 time: 0.5543 data_time: 0.0159 memory: 17620 loss: 1.5691 loss_prob: 0.8734 loss_thr: 0.5531 loss_db: 0.1426 2022/11/01 16:10:02 - mmengine - INFO - Epoch(train) [297][55/63] lr: 1.8262e-03 eta: 9:47:43 time: 0.5731 data_time: 0.0239 memory: 17620 loss: 1.6521 loss_prob: 0.9551 loss_thr: 0.5394 loss_db: 0.1576 2022/11/01 16:10:05 - mmengine - INFO - Epoch(train) [297][60/63] lr: 1.8262e-03 eta: 9:47:36 time: 0.5711 data_time: 0.0163 memory: 17620 loss: 1.7898 loss_prob: 1.0508 loss_thr: 0.5745 loss_db: 0.1645 2022/11/01 16:10:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:10:11 - mmengine - INFO - Epoch(train) [298][5/63] lr: 1.8244e-03 eta: 9:47:36 time: 0.7513 data_time: 0.2065 memory: 17620 loss: 1.9645 loss_prob: 1.1523 loss_thr: 0.6260 loss_db: 0.1862 2022/11/01 16:10:14 - mmengine - INFO - Epoch(train) [298][10/63] lr: 1.8244e-03 eta: 9:47:27 time: 0.8011 data_time: 0.2058 memory: 17620 loss: 2.0559 loss_prob: 1.2368 loss_thr: 0.6240 loss_db: 0.1951 2022/11/01 16:10:17 - mmengine - INFO - Epoch(train) [298][15/63] lr: 1.8244e-03 eta: 9:47:27 time: 0.5917 data_time: 0.0090 memory: 17620 loss: 1.9288 loss_prob: 1.1620 loss_thr: 0.5866 loss_db: 0.1802 2022/11/01 16:10:19 - mmengine - INFO - Epoch(train) [298][20/63] lr: 1.8244e-03 eta: 9:47:19 time: 0.5439 data_time: 0.0091 memory: 17620 loss: 1.9046 loss_prob: 1.1192 loss_thr: 0.6089 loss_db: 0.1765 2022/11/01 16:10:22 - mmengine - INFO - Epoch(train) [298][25/63] lr: 1.8244e-03 eta: 9:47:19 time: 0.5573 data_time: 0.0321 memory: 17620 loss: 2.0781 loss_prob: 1.2479 loss_thr: 0.6316 loss_db: 0.1986 2022/11/01 16:10:25 - mmengine - INFO - Epoch(train) [298][30/63] lr: 1.8244e-03 eta: 9:47:11 time: 0.5767 data_time: 0.0308 memory: 17620 loss: 1.9125 loss_prob: 1.1250 loss_thr: 0.6040 loss_db: 0.1835 2022/11/01 16:10:28 - mmengine - INFO - Epoch(train) [298][35/63] lr: 1.8244e-03 eta: 9:47:11 time: 0.5581 data_time: 0.0087 memory: 17620 loss: 1.7490 loss_prob: 0.9934 loss_thr: 0.5918 loss_db: 0.1638 2022/11/01 16:10:31 - mmengine - INFO - Epoch(train) [298][40/63] lr: 1.8244e-03 eta: 9:47:05 time: 0.6012 data_time: 0.0185 memory: 17620 loss: 1.8746 loss_prob: 1.0903 loss_thr: 0.6086 loss_db: 0.1756 2022/11/01 16:10:34 - mmengine - INFO - Epoch(train) [298][45/63] lr: 1.8244e-03 eta: 9:47:05 time: 0.5996 data_time: 0.0175 memory: 17620 loss: 1.9419 loss_prob: 1.1391 loss_thr: 0.6218 loss_db: 0.1810 2022/11/01 16:10:37 - mmengine - INFO - Epoch(train) [298][50/63] lr: 1.8244e-03 eta: 9:46:57 time: 0.5762 data_time: 0.0210 memory: 17620 loss: 1.9690 loss_prob: 1.1563 loss_thr: 0.6273 loss_db: 0.1854 2022/11/01 16:10:40 - mmengine - INFO - Epoch(train) [298][55/63] lr: 1.8244e-03 eta: 9:46:57 time: 0.6020 data_time: 0.0192 memory: 17620 loss: 2.0374 loss_prob: 1.2270 loss_thr: 0.6101 loss_db: 0.2003 2022/11/01 16:10:43 - mmengine - INFO - Epoch(train) [298][60/63] lr: 1.8244e-03 eta: 9:46:50 time: 0.5784 data_time: 0.0052 memory: 17620 loss: 2.2792 loss_prob: 1.4297 loss_thr: 0.6215 loss_db: 0.2280 2022/11/01 16:10:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:10:49 - mmengine - INFO - Epoch(train) [299][5/63] lr: 1.8225e-03 eta: 9:46:50 time: 0.6993 data_time: 0.1838 memory: 17620 loss: 2.2225 loss_prob: 1.3758 loss_thr: 0.6266 loss_db: 0.2201 2022/11/01 16:10:52 - mmengine - INFO - Epoch(train) [299][10/63] lr: 1.8225e-03 eta: 9:46:40 time: 0.7591 data_time: 0.1852 memory: 17620 loss: 1.8067 loss_prob: 1.0519 loss_thr: 0.5831 loss_db: 0.1718 2022/11/01 16:10:54 - mmengine - INFO - Epoch(train) [299][15/63] lr: 1.8225e-03 eta: 9:46:40 time: 0.5681 data_time: 0.0095 memory: 17620 loss: 1.6855 loss_prob: 0.9558 loss_thr: 0.5748 loss_db: 0.1548 2022/11/01 16:10:57 - mmengine - INFO - Epoch(train) [299][20/63] lr: 1.8225e-03 eta: 9:46:33 time: 0.5794 data_time: 0.0072 memory: 17620 loss: 1.8110 loss_prob: 1.0402 loss_thr: 0.6010 loss_db: 0.1698 2022/11/01 16:11:00 - mmengine - INFO - Epoch(train) [299][25/63] lr: 1.8225e-03 eta: 9:46:33 time: 0.5956 data_time: 0.0180 memory: 17620 loss: 2.2152 loss_prob: 1.3612 loss_thr: 0.6412 loss_db: 0.2128 2022/11/01 16:11:03 - mmengine - INFO - Epoch(train) [299][30/63] lr: 1.8225e-03 eta: 9:46:25 time: 0.5696 data_time: 0.0510 memory: 17620 loss: 2.2418 loss_prob: 1.3831 loss_thr: 0.6403 loss_db: 0.2184 2022/11/01 16:11:06 - mmengine - INFO - Epoch(train) [299][35/63] lr: 1.8225e-03 eta: 9:46:25 time: 0.5436 data_time: 0.0387 memory: 17620 loss: 1.8965 loss_prob: 1.0991 loss_thr: 0.6161 loss_db: 0.1813 2022/11/01 16:11:08 - mmengine - INFO - Epoch(train) [299][40/63] lr: 1.8225e-03 eta: 9:46:16 time: 0.5310 data_time: 0.0051 memory: 17620 loss: 1.9572 loss_prob: 1.1411 loss_thr: 0.6321 loss_db: 0.1840 2022/11/01 16:11:11 - mmengine - INFO - Epoch(train) [299][45/63] lr: 1.8225e-03 eta: 9:46:16 time: 0.5332 data_time: 0.0053 memory: 17620 loss: 1.9559 loss_prob: 1.1491 loss_thr: 0.6200 loss_db: 0.1868 2022/11/01 16:11:14 - mmengine - INFO - Epoch(train) [299][50/63] lr: 1.8225e-03 eta: 9:46:07 time: 0.5173 data_time: 0.0059 memory: 17620 loss: 1.7890 loss_prob: 1.0287 loss_thr: 0.5926 loss_db: 0.1677 2022/11/01 16:11:16 - mmengine - INFO - Epoch(train) [299][55/63] lr: 1.8225e-03 eta: 9:46:07 time: 0.5318 data_time: 0.0093 memory: 17620 loss: 2.0653 loss_prob: 1.2505 loss_thr: 0.6118 loss_db: 0.2030 2022/11/01 16:11:19 - mmengine - INFO - Epoch(train) [299][60/63] lr: 1.8225e-03 eta: 9:45:58 time: 0.5350 data_time: 0.0097 memory: 17620 loss: 2.2594 loss_prob: 1.3904 loss_thr: 0.6441 loss_db: 0.2249 2022/11/01 16:11:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:11:25 - mmengine - INFO - Epoch(train) [300][5/63] lr: 1.8207e-03 eta: 9:45:58 time: 0.6846 data_time: 0.1813 memory: 17620 loss: 1.8830 loss_prob: 1.0962 loss_thr: 0.6106 loss_db: 0.1762 2022/11/01 16:11:28 - mmengine - INFO - Epoch(train) [300][10/63] lr: 1.8207e-03 eta: 9:45:48 time: 0.7167 data_time: 0.1925 memory: 17620 loss: 1.7172 loss_prob: 0.9849 loss_thr: 0.5750 loss_db: 0.1573 2022/11/01 16:11:30 - mmengine - INFO - Epoch(train) [300][15/63] lr: 1.8207e-03 eta: 9:45:48 time: 0.5290 data_time: 0.0163 memory: 17620 loss: 1.8492 loss_prob: 1.1065 loss_thr: 0.5693 loss_db: 0.1734 2022/11/01 16:11:33 - mmengine - INFO - Epoch(train) [300][20/63] lr: 1.8207e-03 eta: 9:45:39 time: 0.5273 data_time: 0.0082 memory: 17620 loss: 2.3045 loss_prob: 1.4447 loss_thr: 0.6383 loss_db: 0.2215 2022/11/01 16:11:35 - mmengine - INFO - Epoch(train) [300][25/63] lr: 1.8207e-03 eta: 9:45:39 time: 0.5290 data_time: 0.0196 memory: 17620 loss: 2.3975 loss_prob: 1.4965 loss_thr: 0.6692 loss_db: 0.2318 2022/11/01 16:11:38 - mmengine - INFO - Epoch(train) [300][30/63] lr: 1.8207e-03 eta: 9:45:30 time: 0.5418 data_time: 0.0230 memory: 17620 loss: 2.1189 loss_prob: 1.2825 loss_thr: 0.6339 loss_db: 0.2025 2022/11/01 16:11:41 - mmengine - INFO - Epoch(train) [300][35/63] lr: 1.8207e-03 eta: 9:45:30 time: 0.5648 data_time: 0.0216 memory: 17620 loss: 2.3836 loss_prob: 1.4898 loss_thr: 0.6620 loss_db: 0.2319 2022/11/01 16:11:44 - mmengine - INFO - Epoch(train) [300][40/63] lr: 1.8207e-03 eta: 9:45:22 time: 0.5542 data_time: 0.0150 memory: 17620 loss: 2.3369 loss_prob: 1.4622 loss_thr: 0.6471 loss_db: 0.2275 2022/11/01 16:11:46 - mmengine - INFO - Epoch(train) [300][45/63] lr: 1.8207e-03 eta: 9:45:22 time: 0.5326 data_time: 0.0073 memory: 17620 loss: 1.9456 loss_prob: 1.1545 loss_thr: 0.6094 loss_db: 0.1816 2022/11/01 16:11:49 - mmengine - INFO - Epoch(train) [300][50/63] lr: 1.8207e-03 eta: 9:45:13 time: 0.5340 data_time: 0.0150 memory: 17620 loss: 1.9313 loss_prob: 1.1264 loss_thr: 0.6261 loss_db: 0.1787 2022/11/01 16:11:52 - mmengine - INFO - Epoch(train) [300][55/63] lr: 1.8207e-03 eta: 9:45:13 time: 0.5393 data_time: 0.0204 memory: 17620 loss: 1.8612 loss_prob: 1.0751 loss_thr: 0.6152 loss_db: 0.1709 2022/11/01 16:11:55 - mmengine - INFO - Epoch(train) [300][60/63] lr: 1.8207e-03 eta: 9:45:05 time: 0.5452 data_time: 0.0138 memory: 17620 loss: 2.0300 loss_prob: 1.2231 loss_thr: 0.6186 loss_db: 0.1883 2022/11/01 16:11:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:11:56 - mmengine - INFO - Saving checkpoint at 300 epochs 2022/11/01 16:12:03 - mmengine - INFO - Epoch(val) [300][5/32] eta: 9:45:05 time: 0.5472 data_time: 0.0637 memory: 17620 2022/11/01 16:12:06 - mmengine - INFO - Epoch(val) [300][10/32] eta: 0:00:13 time: 0.6149 data_time: 0.0870 memory: 15725 2022/11/01 16:12:08 - mmengine - INFO - Epoch(val) [300][15/32] eta: 0:00:13 time: 0.5732 data_time: 0.0408 memory: 15725 2022/11/01 16:12:11 - mmengine - INFO - Epoch(val) [300][20/32] eta: 0:00:06 time: 0.5739 data_time: 0.0401 memory: 15725 2022/11/01 16:12:14 - mmengine - INFO - Epoch(val) [300][25/32] eta: 0:00:06 time: 0.5959 data_time: 0.0505 memory: 15725 2022/11/01 16:12:17 - mmengine - INFO - Epoch(val) [300][30/32] eta: 0:00:01 time: 0.5680 data_time: 0.0316 memory: 15725 2022/11/01 16:12:18 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8479, precision: 0.7144, hmean: 0.7754 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8479, precision: 0.7897, hmean: 0.8177 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8430, precision: 0.8358, hmean: 0.8394 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8305, precision: 0.8788, hmean: 0.8540 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7906, precision: 0.9209, hmean: 0.8508 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4689, precision: 0.9634, hmean: 0.6308 2022/11/01 16:12:18 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 16:12:18 - mmengine - INFO - Epoch(val) [300][32/32] icdar/precision: 0.8788 icdar/recall: 0.8305 icdar/hmean: 0.8540 2022/11/01 16:12:23 - mmengine - INFO - Epoch(train) [301][5/63] lr: 1.8189e-03 eta: 0:00:01 time: 0.7599 data_time: 0.2082 memory: 17620 loss: 1.7993 loss_prob: 1.0462 loss_thr: 0.5882 loss_db: 0.1649 2022/11/01 16:12:26 - mmengine - INFO - Epoch(train) [301][10/63] lr: 1.8189e-03 eta: 9:44:56 time: 0.7939 data_time: 0.2083 memory: 17620 loss: 1.7345 loss_prob: 1.0003 loss_thr: 0.5760 loss_db: 0.1582 2022/11/01 16:12:28 - mmengine - INFO - Epoch(train) [301][15/63] lr: 1.8189e-03 eta: 9:44:56 time: 0.5573 data_time: 0.0047 memory: 17620 loss: 1.8669 loss_prob: 1.0832 loss_thr: 0.6130 loss_db: 0.1707 2022/11/01 16:12:31 - mmengine - INFO - Epoch(train) [301][20/63] lr: 1.8189e-03 eta: 9:44:48 time: 0.5535 data_time: 0.0049 memory: 17620 loss: 1.8599 loss_prob: 1.0750 loss_thr: 0.6112 loss_db: 0.1737 2022/11/01 16:12:34 - mmengine - INFO - Epoch(train) [301][25/63] lr: 1.8189e-03 eta: 9:44:48 time: 0.5613 data_time: 0.0268 memory: 17620 loss: 1.7618 loss_prob: 1.0061 loss_thr: 0.5928 loss_db: 0.1629 2022/11/01 16:12:37 - mmengine - INFO - Epoch(train) [301][30/63] lr: 1.8189e-03 eta: 9:44:40 time: 0.5621 data_time: 0.0353 memory: 17620 loss: 1.9954 loss_prob: 1.1935 loss_thr: 0.6148 loss_db: 0.1870 2022/11/01 16:12:40 - mmengine - INFO - Epoch(train) [301][35/63] lr: 1.8189e-03 eta: 9:44:40 time: 0.5604 data_time: 0.0171 memory: 17620 loss: 2.1175 loss_prob: 1.2796 loss_thr: 0.6349 loss_db: 0.2030 2022/11/01 16:12:42 - mmengine - INFO - Epoch(train) [301][40/63] lr: 1.8189e-03 eta: 9:44:32 time: 0.5582 data_time: 0.0084 memory: 17620 loss: 1.9553 loss_prob: 1.1449 loss_thr: 0.6269 loss_db: 0.1834 2022/11/01 16:12:45 - mmengine - INFO - Epoch(train) [301][45/63] lr: 1.8189e-03 eta: 9:44:32 time: 0.5547 data_time: 0.0045 memory: 17620 loss: 1.9152 loss_prob: 1.1348 loss_thr: 0.6025 loss_db: 0.1779 2022/11/01 16:12:48 - mmengine - INFO - Epoch(train) [301][50/63] lr: 1.8189e-03 eta: 9:44:25 time: 0.5852 data_time: 0.0177 memory: 17620 loss: 1.9450 loss_prob: 1.1437 loss_thr: 0.6194 loss_db: 0.1819 2022/11/01 16:12:51 - mmengine - INFO - Epoch(train) [301][55/63] lr: 1.8189e-03 eta: 9:44:25 time: 0.5845 data_time: 0.0235 memory: 17620 loss: 1.8760 loss_prob: 1.0809 loss_thr: 0.6202 loss_db: 0.1750 2022/11/01 16:12:54 - mmengine - INFO - Epoch(train) [301][60/63] lr: 1.8189e-03 eta: 9:44:17 time: 0.5462 data_time: 0.0148 memory: 17620 loss: 1.8740 loss_prob: 1.0861 loss_thr: 0.6132 loss_db: 0.1747 2022/11/01 16:12:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:13:00 - mmengine - INFO - Epoch(train) [302][5/63] lr: 1.8171e-03 eta: 9:44:17 time: 0.7110 data_time: 0.1995 memory: 17620 loss: 1.6745 loss_prob: 0.9560 loss_thr: 0.5643 loss_db: 0.1543 2022/11/01 16:13:03 - mmengine - INFO - Epoch(train) [302][10/63] lr: 1.8171e-03 eta: 9:44:08 time: 0.7729 data_time: 0.2032 memory: 17620 loss: 1.7100 loss_prob: 0.9846 loss_thr: 0.5685 loss_db: 0.1570 2022/11/01 16:13:05 - mmengine - INFO - Epoch(train) [302][15/63] lr: 1.8171e-03 eta: 9:44:08 time: 0.5716 data_time: 0.0100 memory: 17620 loss: 1.8107 loss_prob: 1.0555 loss_thr: 0.5835 loss_db: 0.1716 2022/11/01 16:13:08 - mmengine - INFO - Epoch(train) [302][20/63] lr: 1.8171e-03 eta: 9:44:00 time: 0.5788 data_time: 0.0092 memory: 17620 loss: 1.9269 loss_prob: 1.1403 loss_thr: 0.6071 loss_db: 0.1795 2022/11/01 16:13:12 - mmengine - INFO - Epoch(train) [302][25/63] lr: 1.8171e-03 eta: 9:44:00 time: 0.6038 data_time: 0.0131 memory: 17620 loss: 1.9137 loss_prob: 1.1471 loss_thr: 0.5864 loss_db: 0.1803 2022/11/01 16:13:14 - mmengine - INFO - Epoch(train) [302][30/63] lr: 1.8171e-03 eta: 9:43:53 time: 0.5755 data_time: 0.0264 memory: 17620 loss: 1.7599 loss_prob: 1.0308 loss_thr: 0.5633 loss_db: 0.1658 2022/11/01 16:13:17 - mmengine - INFO - Epoch(train) [302][35/63] lr: 1.8171e-03 eta: 9:43:53 time: 0.5532 data_time: 0.0283 memory: 17620 loss: 1.7221 loss_prob: 0.9826 loss_thr: 0.5851 loss_db: 0.1544 2022/11/01 16:13:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:13:20 - mmengine - INFO - Epoch(train) [302][40/63] lr: 1.8171e-03 eta: 9:43:44 time: 0.5415 data_time: 0.0112 memory: 17620 loss: 1.9505 loss_prob: 1.1574 loss_thr: 0.6121 loss_db: 0.1810 2022/11/01 16:13:23 - mmengine - INFO - Epoch(train) [302][45/63] lr: 1.8171e-03 eta: 9:43:44 time: 0.5790 data_time: 0.0206 memory: 17620 loss: 1.9344 loss_prob: 1.1571 loss_thr: 0.5948 loss_db: 0.1825 2022/11/01 16:13:26 - mmengine - INFO - Epoch(train) [302][50/63] lr: 1.8171e-03 eta: 9:43:38 time: 0.6064 data_time: 0.0257 memory: 17620 loss: 1.7871 loss_prob: 1.0261 loss_thr: 0.5965 loss_db: 0.1646 2022/11/01 16:13:29 - mmengine - INFO - Epoch(train) [302][55/63] lr: 1.8171e-03 eta: 9:43:38 time: 0.5942 data_time: 0.0173 memory: 17620 loss: 1.8231 loss_prob: 1.0490 loss_thr: 0.6050 loss_db: 0.1691 2022/11/01 16:13:31 - mmengine - INFO - Epoch(train) [302][60/63] lr: 1.8171e-03 eta: 9:43:30 time: 0.5762 data_time: 0.0176 memory: 17620 loss: 1.8220 loss_prob: 1.0667 loss_thr: 0.5833 loss_db: 0.1720 2022/11/01 16:13:33 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:13:37 - mmengine - INFO - Epoch(train) [303][5/63] lr: 1.8153e-03 eta: 9:43:30 time: 0.6903 data_time: 0.1945 memory: 17620 loss: 1.6822 loss_prob: 0.9617 loss_thr: 0.5640 loss_db: 0.1564 2022/11/01 16:13:40 - mmengine - INFO - Epoch(train) [303][10/63] lr: 1.8153e-03 eta: 9:43:20 time: 0.7230 data_time: 0.1932 memory: 17620 loss: 1.7004 loss_prob: 0.9613 loss_thr: 0.5838 loss_db: 0.1553 2022/11/01 16:13:43 - mmengine - INFO - Epoch(train) [303][15/63] lr: 1.8153e-03 eta: 9:43:20 time: 0.5368 data_time: 0.0096 memory: 17620 loss: 1.9110 loss_prob: 1.1135 loss_thr: 0.6142 loss_db: 0.1833 2022/11/01 16:13:46 - mmengine - INFO - Epoch(train) [303][20/63] lr: 1.8153e-03 eta: 9:43:12 time: 0.5559 data_time: 0.0118 memory: 17620 loss: 2.0454 loss_prob: 1.2277 loss_thr: 0.6189 loss_db: 0.1989 2022/11/01 16:13:48 - mmengine - INFO - Epoch(train) [303][25/63] lr: 1.8153e-03 eta: 9:43:12 time: 0.5641 data_time: 0.0200 memory: 17620 loss: 2.0702 loss_prob: 1.2396 loss_thr: 0.6280 loss_db: 0.2027 2022/11/01 16:13:51 - mmengine - INFO - Epoch(train) [303][30/63] lr: 1.8153e-03 eta: 9:43:04 time: 0.5482 data_time: 0.0277 memory: 17620 loss: 2.0857 loss_prob: 1.2649 loss_thr: 0.6205 loss_db: 0.2003 2022/11/01 16:13:54 - mmengine - INFO - Epoch(train) [303][35/63] lr: 1.8153e-03 eta: 9:43:04 time: 0.5494 data_time: 0.0190 memory: 17620 loss: 1.8997 loss_prob: 1.1381 loss_thr: 0.5874 loss_db: 0.1743 2022/11/01 16:13:57 - mmengine - INFO - Epoch(train) [303][40/63] lr: 1.8153e-03 eta: 9:42:55 time: 0.5427 data_time: 0.0104 memory: 17620 loss: 1.9798 loss_prob: 1.1983 loss_thr: 0.5971 loss_db: 0.1845 2022/11/01 16:13:59 - mmengine - INFO - Epoch(train) [303][45/63] lr: 1.8153e-03 eta: 9:42:55 time: 0.5326 data_time: 0.0067 memory: 17620 loss: 2.2448 loss_prob: 1.3974 loss_thr: 0.6351 loss_db: 0.2124 2022/11/01 16:14:02 - mmengine - INFO - Epoch(train) [303][50/63] lr: 1.8153e-03 eta: 9:42:47 time: 0.5437 data_time: 0.0166 memory: 17620 loss: 2.0096 loss_prob: 1.2100 loss_thr: 0.6098 loss_db: 0.1898 2022/11/01 16:14:05 - mmengine - INFO - Epoch(train) [303][55/63] lr: 1.8153e-03 eta: 9:42:47 time: 0.5342 data_time: 0.0184 memory: 17620 loss: 1.9480 loss_prob: 1.1482 loss_thr: 0.6149 loss_db: 0.1848 2022/11/01 16:14:07 - mmengine - INFO - Epoch(train) [303][60/63] lr: 1.8153e-03 eta: 9:42:38 time: 0.5286 data_time: 0.0113 memory: 17620 loss: 2.0088 loss_prob: 1.1830 loss_thr: 0.6306 loss_db: 0.1952 2022/11/01 16:14:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:14:13 - mmengine - INFO - Epoch(train) [304][5/63] lr: 1.8134e-03 eta: 9:42:38 time: 0.6981 data_time: 0.1907 memory: 17620 loss: 1.8665 loss_prob: 1.0975 loss_thr: 0.5896 loss_db: 0.1794 2022/11/01 16:14:16 - mmengine - INFO - Epoch(train) [304][10/63] lr: 1.8134e-03 eta: 9:42:28 time: 0.7332 data_time: 0.1904 memory: 17620 loss: 2.0570 loss_prob: 1.2298 loss_thr: 0.6273 loss_db: 0.2000 2022/11/01 16:14:18 - mmengine - INFO - Epoch(train) [304][15/63] lr: 1.8134e-03 eta: 9:42:28 time: 0.5250 data_time: 0.0048 memory: 17620 loss: 1.9127 loss_prob: 1.1218 loss_thr: 0.6077 loss_db: 0.1833 2022/11/01 16:14:21 - mmengine - INFO - Epoch(train) [304][20/63] lr: 1.8134e-03 eta: 9:42:19 time: 0.5378 data_time: 0.0053 memory: 17620 loss: 1.6796 loss_prob: 0.9543 loss_thr: 0.5650 loss_db: 0.1603 2022/11/01 16:14:24 - mmengine - INFO - Epoch(train) [304][25/63] lr: 1.8134e-03 eta: 9:42:19 time: 0.5611 data_time: 0.0325 memory: 17620 loss: 1.7747 loss_prob: 1.0356 loss_thr: 0.5681 loss_db: 0.1709 2022/11/01 16:14:27 - mmengine - INFO - Epoch(train) [304][30/63] lr: 1.8134e-03 eta: 9:42:11 time: 0.5582 data_time: 0.0355 memory: 17620 loss: 1.7109 loss_prob: 1.0013 loss_thr: 0.5503 loss_db: 0.1594 2022/11/01 16:14:29 - mmengine - INFO - Epoch(train) [304][35/63] lr: 1.8134e-03 eta: 9:42:11 time: 0.5357 data_time: 0.0082 memory: 17620 loss: 1.7292 loss_prob: 0.9997 loss_thr: 0.5672 loss_db: 0.1623 2022/11/01 16:14:32 - mmengine - INFO - Epoch(train) [304][40/63] lr: 1.8134e-03 eta: 9:42:03 time: 0.5343 data_time: 0.0046 memory: 17620 loss: 1.7743 loss_prob: 1.0167 loss_thr: 0.5934 loss_db: 0.1642 2022/11/01 16:14:35 - mmengine - INFO - Epoch(train) [304][45/63] lr: 1.8134e-03 eta: 9:42:03 time: 0.5367 data_time: 0.0054 memory: 17620 loss: 1.8029 loss_prob: 1.0410 loss_thr: 0.5935 loss_db: 0.1683 2022/11/01 16:14:38 - mmengine - INFO - Epoch(train) [304][50/63] lr: 1.8134e-03 eta: 9:41:54 time: 0.5517 data_time: 0.0204 memory: 17620 loss: 1.9830 loss_prob: 1.1766 loss_thr: 0.6205 loss_db: 0.1859 2022/11/01 16:14:40 - mmengine - INFO - Epoch(train) [304][55/63] lr: 1.8134e-03 eta: 9:41:54 time: 0.5587 data_time: 0.0220 memory: 17620 loss: 2.3114 loss_prob: 1.4346 loss_thr: 0.6487 loss_db: 0.2281 2022/11/01 16:14:43 - mmengine - INFO - Epoch(train) [304][60/63] lr: 1.8134e-03 eta: 9:41:46 time: 0.5290 data_time: 0.0075 memory: 17620 loss: 2.3112 loss_prob: 1.4453 loss_thr: 0.6294 loss_db: 0.2365 2022/11/01 16:14:44 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:14:49 - mmengine - INFO - Epoch(train) [305][5/63] lr: 1.8116e-03 eta: 9:41:46 time: 0.7194 data_time: 0.1775 memory: 17620 loss: 2.0376 loss_prob: 1.2183 loss_thr: 0.6251 loss_db: 0.1942 2022/11/01 16:14:52 - mmengine - INFO - Epoch(train) [305][10/63] lr: 1.8116e-03 eta: 9:41:36 time: 0.7530 data_time: 0.1779 memory: 17620 loss: 1.9875 loss_prob: 1.1691 loss_thr: 0.6271 loss_db: 0.1913 2022/11/01 16:14:54 - mmengine - INFO - Epoch(train) [305][15/63] lr: 1.8116e-03 eta: 9:41:36 time: 0.5327 data_time: 0.0082 memory: 17620 loss: 2.1445 loss_prob: 1.3119 loss_thr: 0.6202 loss_db: 0.2124 2022/11/01 16:14:57 - mmengine - INFO - Epoch(train) [305][20/63] lr: 1.8116e-03 eta: 9:41:27 time: 0.5374 data_time: 0.0082 memory: 17620 loss: 2.0703 loss_prob: 1.2541 loss_thr: 0.6158 loss_db: 0.2003 2022/11/01 16:15:00 - mmengine - INFO - Epoch(train) [305][25/63] lr: 1.8116e-03 eta: 9:41:27 time: 0.5541 data_time: 0.0132 memory: 17620 loss: 2.0010 loss_prob: 1.1789 loss_thr: 0.6316 loss_db: 0.1905 2022/11/01 16:15:03 - mmengine - INFO - Epoch(train) [305][30/63] lr: 1.8116e-03 eta: 9:41:20 time: 0.5685 data_time: 0.0325 memory: 17620 loss: 2.0255 loss_prob: 1.2161 loss_thr: 0.6109 loss_db: 0.1985 2022/11/01 16:15:06 - mmengine - INFO - Epoch(train) [305][35/63] lr: 1.8116e-03 eta: 9:41:20 time: 0.5629 data_time: 0.0266 memory: 17620 loss: 2.2047 loss_prob: 1.3527 loss_thr: 0.6353 loss_db: 0.2166 2022/11/01 16:15:08 - mmengine - INFO - Epoch(train) [305][40/63] lr: 1.8116e-03 eta: 9:41:12 time: 0.5557 data_time: 0.0096 memory: 17620 loss: 2.2139 loss_prob: 1.3369 loss_thr: 0.6687 loss_db: 0.2083 2022/11/01 16:15:11 - mmengine - INFO - Epoch(train) [305][45/63] lr: 1.8116e-03 eta: 9:41:12 time: 0.5542 data_time: 0.0093 memory: 17620 loss: 1.9504 loss_prob: 1.1467 loss_thr: 0.6187 loss_db: 0.1850 2022/11/01 16:15:14 - mmengine - INFO - Epoch(train) [305][50/63] lr: 1.8116e-03 eta: 9:41:04 time: 0.5573 data_time: 0.0152 memory: 17620 loss: 2.1194 loss_prob: 1.3066 loss_thr: 0.6033 loss_db: 0.2095 2022/11/01 16:15:17 - mmengine - INFO - Epoch(train) [305][55/63] lr: 1.8116e-03 eta: 9:41:04 time: 0.6099 data_time: 0.0227 memory: 17620 loss: 2.1408 loss_prob: 1.3239 loss_thr: 0.6077 loss_db: 0.2092 2022/11/01 16:15:20 - mmengine - INFO - Epoch(train) [305][60/63] lr: 1.8116e-03 eta: 9:40:57 time: 0.6038 data_time: 0.0142 memory: 17620 loss: 1.9608 loss_prob: 1.1710 loss_thr: 0.6020 loss_db: 0.1878 2022/11/01 16:15:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:15:26 - mmengine - INFO - Epoch(train) [306][5/63] lr: 1.8098e-03 eta: 9:40:57 time: 0.7430 data_time: 0.2278 memory: 17620 loss: 1.9752 loss_prob: 1.1877 loss_thr: 0.6022 loss_db: 0.1852 2022/11/01 16:15:29 - mmengine - INFO - Epoch(train) [306][10/63] lr: 1.8098e-03 eta: 9:40:49 time: 0.8018 data_time: 0.2286 memory: 17620 loss: 2.0447 loss_prob: 1.2262 loss_thr: 0.6241 loss_db: 0.1943 2022/11/01 16:15:32 - mmengine - INFO - Epoch(train) [306][15/63] lr: 1.8098e-03 eta: 9:40:49 time: 0.5947 data_time: 0.0110 memory: 17620 loss: 2.0142 loss_prob: 1.1902 loss_thr: 0.6328 loss_db: 0.1912 2022/11/01 16:15:35 - mmengine - INFO - Epoch(train) [306][20/63] lr: 1.8098e-03 eta: 9:40:42 time: 0.5976 data_time: 0.0085 memory: 17620 loss: 1.9347 loss_prob: 1.1314 loss_thr: 0.6204 loss_db: 0.1829 2022/11/01 16:15:38 - mmengine - INFO - Epoch(train) [306][25/63] lr: 1.8098e-03 eta: 9:40:42 time: 0.6156 data_time: 0.0207 memory: 17620 loss: 1.8489 loss_prob: 1.0736 loss_thr: 0.5996 loss_db: 0.1757 2022/11/01 16:15:41 - mmengine - INFO - Epoch(train) [306][30/63] lr: 1.8098e-03 eta: 9:40:36 time: 0.5961 data_time: 0.0365 memory: 17620 loss: 1.7884 loss_prob: 1.0340 loss_thr: 0.5875 loss_db: 0.1670 2022/11/01 16:15:44 - mmengine - INFO - Epoch(train) [306][35/63] lr: 1.8098e-03 eta: 9:40:36 time: 0.5724 data_time: 0.0215 memory: 17620 loss: 1.9889 loss_prob: 1.1760 loss_thr: 0.6282 loss_db: 0.1847 2022/11/01 16:15:48 - mmengine - INFO - Epoch(train) [306][40/63] lr: 1.8098e-03 eta: 9:40:31 time: 0.6867 data_time: 0.0060 memory: 17620 loss: 2.0664 loss_prob: 1.2214 loss_thr: 0.6527 loss_db: 0.1924 2022/11/01 16:15:51 - mmengine - INFO - Epoch(train) [306][45/63] lr: 1.8098e-03 eta: 9:40:31 time: 0.6739 data_time: 0.0063 memory: 17620 loss: 2.2432 loss_prob: 1.3550 loss_thr: 0.6721 loss_db: 0.2161 2022/11/01 16:15:54 - mmengine - INFO - Epoch(train) [306][50/63] lr: 1.8098e-03 eta: 9:40:24 time: 0.5898 data_time: 0.0202 memory: 17620 loss: 2.2571 loss_prob: 1.3636 loss_thr: 0.6768 loss_db: 0.2168 2022/11/01 16:15:57 - mmengine - INFO - Epoch(train) [306][55/63] lr: 1.8098e-03 eta: 9:40:24 time: 0.5891 data_time: 0.0256 memory: 17620 loss: 1.9451 loss_prob: 1.1409 loss_thr: 0.6211 loss_db: 0.1831 2022/11/01 16:16:00 - mmengine - INFO - Epoch(train) [306][60/63] lr: 1.8098e-03 eta: 9:40:16 time: 0.5577 data_time: 0.0113 memory: 17620 loss: 1.9478 loss_prob: 1.1469 loss_thr: 0.6152 loss_db: 0.1857 2022/11/01 16:16:01 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:16:06 - mmengine - INFO - Epoch(train) [307][5/63] lr: 1.8080e-03 eta: 9:40:16 time: 0.7990 data_time: 0.2111 memory: 17620 loss: 1.8510 loss_prob: 1.0715 loss_thr: 0.6086 loss_db: 0.1710 2022/11/01 16:16:09 - mmengine - INFO - Epoch(train) [307][10/63] lr: 1.8080e-03 eta: 9:40:09 time: 0.8106 data_time: 0.2117 memory: 17620 loss: 1.8087 loss_prob: 1.0326 loss_thr: 0.6072 loss_db: 0.1690 2022/11/01 16:16:12 - mmengine - INFO - Epoch(train) [307][15/63] lr: 1.8080e-03 eta: 9:40:09 time: 0.5256 data_time: 0.0053 memory: 17620 loss: 1.7841 loss_prob: 1.0219 loss_thr: 0.5989 loss_db: 0.1633 2022/11/01 16:16:14 - mmengine - INFO - Epoch(train) [307][20/63] lr: 1.8080e-03 eta: 9:39:59 time: 0.5048 data_time: 0.0047 memory: 17620 loss: 1.7210 loss_prob: 0.9832 loss_thr: 0.5794 loss_db: 0.1584 2022/11/01 16:16:17 - mmengine - INFO - Epoch(train) [307][25/63] lr: 1.8080e-03 eta: 9:39:59 time: 0.5279 data_time: 0.0077 memory: 17620 loss: 1.7545 loss_prob: 1.0124 loss_thr: 0.5770 loss_db: 0.1652 2022/11/01 16:16:20 - mmengine - INFO - Epoch(train) [307][30/63] lr: 1.8080e-03 eta: 9:39:51 time: 0.5697 data_time: 0.0366 memory: 17620 loss: 1.9758 loss_prob: 1.1620 loss_thr: 0.6283 loss_db: 0.1854 2022/11/01 16:16:23 - mmengine - INFO - Epoch(train) [307][35/63] lr: 1.8080e-03 eta: 9:39:51 time: 0.5570 data_time: 0.0336 memory: 17620 loss: 1.9623 loss_prob: 1.1470 loss_thr: 0.6295 loss_db: 0.1858 2022/11/01 16:16:25 - mmengine - INFO - Epoch(train) [307][40/63] lr: 1.8080e-03 eta: 9:39:42 time: 0.5210 data_time: 0.0048 memory: 17620 loss: 1.7592 loss_prob: 1.0076 loss_thr: 0.5862 loss_db: 0.1654 2022/11/01 16:16:28 - mmengine - INFO - Epoch(train) [307][45/63] lr: 1.8080e-03 eta: 9:39:42 time: 0.5361 data_time: 0.0056 memory: 17620 loss: 1.6957 loss_prob: 0.9670 loss_thr: 0.5731 loss_db: 0.1557 2022/11/01 16:16:31 - mmengine - INFO - Epoch(train) [307][50/63] lr: 1.8080e-03 eta: 9:39:35 time: 0.5607 data_time: 0.0244 memory: 17620 loss: 1.7528 loss_prob: 1.0237 loss_thr: 0.5677 loss_db: 0.1614 2022/11/01 16:16:33 - mmengine - INFO - Epoch(train) [307][55/63] lr: 1.8080e-03 eta: 9:39:35 time: 0.5532 data_time: 0.0278 memory: 17620 loss: 1.8422 loss_prob: 1.0829 loss_thr: 0.5883 loss_db: 0.1710 2022/11/01 16:16:36 - mmengine - INFO - Epoch(train) [307][60/63] lr: 1.8080e-03 eta: 9:39:26 time: 0.5403 data_time: 0.0095 memory: 17620 loss: 1.8853 loss_prob: 1.0939 loss_thr: 0.6180 loss_db: 0.1735 2022/11/01 16:16:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:16:43 - mmengine - INFO - Epoch(train) [308][5/63] lr: 1.8061e-03 eta: 9:39:26 time: 0.7459 data_time: 0.2334 memory: 17620 loss: 1.8741 loss_prob: 1.0639 loss_thr: 0.6413 loss_db: 0.1690 2022/11/01 16:16:46 - mmengine - INFO - Epoch(train) [308][10/63] lr: 1.8061e-03 eta: 9:39:18 time: 0.8033 data_time: 0.2369 memory: 17620 loss: 1.8478 loss_prob: 1.0730 loss_thr: 0.6025 loss_db: 0.1723 2022/11/01 16:16:49 - mmengine - INFO - Epoch(train) [308][15/63] lr: 1.8061e-03 eta: 9:39:18 time: 0.5942 data_time: 0.0088 memory: 17620 loss: 1.8107 loss_prob: 1.0590 loss_thr: 0.5805 loss_db: 0.1712 2022/11/01 16:16:51 - mmengine - INFO - Epoch(train) [308][20/63] lr: 1.8061e-03 eta: 9:39:11 time: 0.5795 data_time: 0.0058 memory: 17620 loss: 1.7966 loss_prob: 1.0403 loss_thr: 0.5900 loss_db: 0.1664 2022/11/01 16:16:54 - mmengine - INFO - Epoch(train) [308][25/63] lr: 1.8061e-03 eta: 9:39:11 time: 0.5757 data_time: 0.0367 memory: 17620 loss: 1.7981 loss_prob: 1.0382 loss_thr: 0.5918 loss_db: 0.1680 2022/11/01 16:16:57 - mmengine - INFO - Epoch(train) [308][30/63] lr: 1.8061e-03 eta: 9:39:03 time: 0.5595 data_time: 0.0359 memory: 17620 loss: 1.8743 loss_prob: 1.0879 loss_thr: 0.6110 loss_db: 0.1754 2022/11/01 16:17:00 - mmengine - INFO - Epoch(train) [308][35/63] lr: 1.8061e-03 eta: 9:39:03 time: 0.5343 data_time: 0.0047 memory: 17620 loss: 1.8418 loss_prob: 1.0661 loss_thr: 0.6065 loss_db: 0.1692 2022/11/01 16:17:02 - mmengine - INFO - Epoch(train) [308][40/63] lr: 1.8061e-03 eta: 9:38:54 time: 0.5371 data_time: 0.0059 memory: 17620 loss: 1.7982 loss_prob: 1.0438 loss_thr: 0.5900 loss_db: 0.1644 2022/11/01 16:17:05 - mmengine - INFO - Epoch(train) [308][45/63] lr: 1.8061e-03 eta: 9:38:54 time: 0.5538 data_time: 0.0059 memory: 17620 loss: 1.8865 loss_prob: 1.1015 loss_thr: 0.6106 loss_db: 0.1744 2022/11/01 16:17:08 - mmengine - INFO - Epoch(train) [308][50/63] lr: 1.8061e-03 eta: 9:38:47 time: 0.5790 data_time: 0.0241 memory: 17620 loss: 2.0389 loss_prob: 1.1938 loss_thr: 0.6515 loss_db: 0.1937 2022/11/01 16:17:11 - mmengine - INFO - Epoch(train) [308][55/63] lr: 1.8061e-03 eta: 9:38:47 time: 0.5699 data_time: 0.0259 memory: 17620 loss: 1.9876 loss_prob: 1.1604 loss_thr: 0.6392 loss_db: 0.1881 2022/11/01 16:17:14 - mmengine - INFO - Epoch(train) [308][60/63] lr: 1.8061e-03 eta: 9:38:39 time: 0.5638 data_time: 0.0067 memory: 17620 loss: 1.8403 loss_prob: 1.0720 loss_thr: 0.5959 loss_db: 0.1724 2022/11/01 16:17:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:17:20 - mmengine - INFO - Epoch(train) [309][5/63] lr: 1.8043e-03 eta: 9:38:39 time: 0.7802 data_time: 0.2265 memory: 17620 loss: 1.8167 loss_prob: 1.0612 loss_thr: 0.5892 loss_db: 0.1664 2022/11/01 16:17:23 - mmengine - INFO - Epoch(train) [309][10/63] lr: 1.8043e-03 eta: 9:38:32 time: 0.8326 data_time: 0.2263 memory: 17620 loss: 1.9907 loss_prob: 1.1687 loss_thr: 0.6411 loss_db: 0.1808 2022/11/01 16:17:26 - mmengine - INFO - Epoch(train) [309][15/63] lr: 1.8043e-03 eta: 9:38:32 time: 0.5614 data_time: 0.0060 memory: 17620 loss: 1.8553 loss_prob: 1.0774 loss_thr: 0.6101 loss_db: 0.1678 2022/11/01 16:17:29 - mmengine - INFO - Epoch(train) [309][20/63] lr: 1.8043e-03 eta: 9:38:23 time: 0.5121 data_time: 0.0053 memory: 17620 loss: 1.8145 loss_prob: 1.0518 loss_thr: 0.5907 loss_db: 0.1719 2022/11/01 16:17:31 - mmengine - INFO - Epoch(train) [309][25/63] lr: 1.8043e-03 eta: 9:38:23 time: 0.5275 data_time: 0.0167 memory: 17620 loss: 1.7221 loss_prob: 0.9910 loss_thr: 0.5654 loss_db: 0.1657 2022/11/01 16:17:34 - mmengine - INFO - Epoch(train) [309][30/63] lr: 1.8043e-03 eta: 9:38:15 time: 0.5492 data_time: 0.0347 memory: 17620 loss: 1.6936 loss_prob: 0.9770 loss_thr: 0.5589 loss_db: 0.1577 2022/11/01 16:17:37 - mmengine - INFO - Epoch(train) [309][35/63] lr: 1.8043e-03 eta: 9:38:15 time: 0.5504 data_time: 0.0236 memory: 17620 loss: 1.8636 loss_prob: 1.1010 loss_thr: 0.5895 loss_db: 0.1730 2022/11/01 16:17:39 - mmengine - INFO - Epoch(train) [309][40/63] lr: 1.8043e-03 eta: 9:38:06 time: 0.5368 data_time: 0.0055 memory: 17620 loss: 1.7803 loss_prob: 1.0431 loss_thr: 0.5733 loss_db: 0.1639 2022/11/01 16:17:42 - mmengine - INFO - Epoch(train) [309][45/63] lr: 1.8043e-03 eta: 9:38:06 time: 0.5394 data_time: 0.0047 memory: 17620 loss: 1.6691 loss_prob: 0.9492 loss_thr: 0.5626 loss_db: 0.1573 2022/11/01 16:17:46 - mmengine - INFO - Epoch(train) [309][50/63] lr: 1.8043e-03 eta: 9:38:01 time: 0.6363 data_time: 0.0204 memory: 17620 loss: 1.7052 loss_prob: 0.9640 loss_thr: 0.5822 loss_db: 0.1590 2022/11/01 16:17:49 - mmengine - INFO - Epoch(train) [309][55/63] lr: 1.8043e-03 eta: 9:38:01 time: 0.6595 data_time: 0.0247 memory: 17620 loss: 1.6532 loss_prob: 0.9312 loss_thr: 0.5702 loss_db: 0.1518 2022/11/01 16:17:52 - mmengine - INFO - Epoch(train) [309][60/63] lr: 1.8043e-03 eta: 9:37:54 time: 0.6044 data_time: 0.0112 memory: 17620 loss: 1.9857 loss_prob: 1.2134 loss_thr: 0.5852 loss_db: 0.1871 2022/11/01 16:17:53 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:18:00 - mmengine - INFO - Epoch(train) [310][5/63] lr: 1.8025e-03 eta: 9:37:54 time: 0.9105 data_time: 0.2460 memory: 17620 loss: 1.8837 loss_prob: 1.1203 loss_thr: 0.5874 loss_db: 0.1761 2022/11/01 16:18:04 - mmengine - INFO - Epoch(train) [310][10/63] lr: 1.8025e-03 eta: 9:37:53 time: 1.0288 data_time: 0.2452 memory: 17620 loss: 1.8164 loss_prob: 1.0511 loss_thr: 0.5922 loss_db: 0.1730 2022/11/01 16:18:07 - mmengine - INFO - Epoch(train) [310][15/63] lr: 1.8025e-03 eta: 9:37:53 time: 0.7304 data_time: 0.0065 memory: 17620 loss: 1.9299 loss_prob: 1.1277 loss_thr: 0.6195 loss_db: 0.1827 2022/11/01 16:18:10 - mmengine - INFO - Epoch(train) [310][20/63] lr: 1.8025e-03 eta: 9:37:48 time: 0.6720 data_time: 0.0068 memory: 17620 loss: 1.9762 loss_prob: 1.1728 loss_thr: 0.6161 loss_db: 0.1873 2022/11/01 16:18:13 - mmengine - INFO - Epoch(train) [310][25/63] lr: 1.8025e-03 eta: 9:37:48 time: 0.6126 data_time: 0.0224 memory: 17620 loss: 1.9795 loss_prob: 1.1743 loss_thr: 0.6183 loss_db: 0.1869 2022/11/01 16:18:16 - mmengine - INFO - Epoch(train) [310][30/63] lr: 1.8025e-03 eta: 9:37:41 time: 0.5904 data_time: 0.0355 memory: 17620 loss: 1.8769 loss_prob: 1.0927 loss_thr: 0.6125 loss_db: 0.1716 2022/11/01 16:18:19 - mmengine - INFO - Epoch(train) [310][35/63] lr: 1.8025e-03 eta: 9:37:41 time: 0.5866 data_time: 0.0260 memory: 17620 loss: 1.7448 loss_prob: 0.9953 loss_thr: 0.5924 loss_db: 0.1571 2022/11/01 16:18:22 - mmengine - INFO - Epoch(train) [310][40/63] lr: 1.8025e-03 eta: 9:37:35 time: 0.6089 data_time: 0.0111 memory: 17620 loss: 1.6978 loss_prob: 0.9600 loss_thr: 0.5824 loss_db: 0.1554 2022/11/01 16:18:25 - mmengine - INFO - Epoch(train) [310][45/63] lr: 1.8025e-03 eta: 9:37:35 time: 0.5796 data_time: 0.0052 memory: 17620 loss: 1.7235 loss_prob: 0.9927 loss_thr: 0.5657 loss_db: 0.1651 2022/11/01 16:18:28 - mmengine - INFO - Epoch(train) [310][50/63] lr: 1.8025e-03 eta: 9:37:26 time: 0.5344 data_time: 0.0103 memory: 17620 loss: 1.7274 loss_prob: 1.0017 loss_thr: 0.5616 loss_db: 0.1641 2022/11/01 16:18:30 - mmengine - INFO - Epoch(train) [310][55/63] lr: 1.8025e-03 eta: 9:37:26 time: 0.5428 data_time: 0.0158 memory: 17620 loss: 1.8964 loss_prob: 1.1137 loss_thr: 0.6069 loss_db: 0.1757 2022/11/01 16:18:33 - mmengine - INFO - Epoch(train) [310][60/63] lr: 1.8025e-03 eta: 9:37:18 time: 0.5450 data_time: 0.0120 memory: 17620 loss: 2.0700 loss_prob: 1.2245 loss_thr: 0.6520 loss_db: 0.1935 2022/11/01 16:18:35 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:18:41 - mmengine - INFO - Epoch(train) [311][5/63] lr: 1.8007e-03 eta: 9:37:18 time: 0.9127 data_time: 0.1907 memory: 17620 loss: 1.8398 loss_prob: 1.0738 loss_thr: 0.5920 loss_db: 0.1740 2022/11/01 16:18:44 - mmengine - INFO - Epoch(train) [311][10/63] lr: 1.8007e-03 eta: 9:37:14 time: 0.9560 data_time: 0.1906 memory: 17620 loss: 1.7915 loss_prob: 1.0359 loss_thr: 0.5887 loss_db: 0.1669 2022/11/01 16:18:47 - mmengine - INFO - Epoch(train) [311][15/63] lr: 1.8007e-03 eta: 9:37:14 time: 0.5741 data_time: 0.0054 memory: 17620 loss: 1.8529 loss_prob: 1.0753 loss_thr: 0.6064 loss_db: 0.1713 2022/11/01 16:18:49 - mmengine - INFO - Epoch(train) [311][20/63] lr: 1.8007e-03 eta: 9:37:05 time: 0.5159 data_time: 0.0051 memory: 17620 loss: 1.9373 loss_prob: 1.1672 loss_thr: 0.5870 loss_db: 0.1830 2022/11/01 16:18:52 - mmengine - INFO - Epoch(train) [311][25/63] lr: 1.8007e-03 eta: 9:37:05 time: 0.5065 data_time: 0.0078 memory: 17620 loss: 1.9231 loss_prob: 1.1567 loss_thr: 0.5825 loss_db: 0.1840 2022/11/01 16:18:55 - mmengine - INFO - Epoch(train) [311][30/63] lr: 1.8007e-03 eta: 9:36:57 time: 0.5631 data_time: 0.0309 memory: 17620 loss: 1.8853 loss_prob: 1.1222 loss_thr: 0.5872 loss_db: 0.1759 2022/11/01 16:18:58 - mmengine - INFO - Epoch(train) [311][35/63] lr: 1.8007e-03 eta: 9:36:57 time: 0.5694 data_time: 0.0278 memory: 17620 loss: 1.9299 loss_prob: 1.1660 loss_thr: 0.5794 loss_db: 0.1845 2022/11/01 16:19:00 - mmengine - INFO - Epoch(train) [311][40/63] lr: 1.8007e-03 eta: 9:36:49 time: 0.5365 data_time: 0.0071 memory: 17620 loss: 2.0589 loss_prob: 1.2260 loss_thr: 0.6348 loss_db: 0.1981 2022/11/01 16:19:03 - mmengine - INFO - Epoch(train) [311][45/63] lr: 1.8007e-03 eta: 9:36:49 time: 0.5413 data_time: 0.0073 memory: 17620 loss: 2.2219 loss_prob: 1.3547 loss_thr: 0.6509 loss_db: 0.2163 2022/11/01 16:19:06 - mmengine - INFO - Epoch(train) [311][50/63] lr: 1.8007e-03 eta: 9:36:41 time: 0.5578 data_time: 0.0127 memory: 17620 loss: 2.1294 loss_prob: 1.3010 loss_thr: 0.6216 loss_db: 0.2067 2022/11/01 16:19:09 - mmengine - INFO - Epoch(train) [311][55/63] lr: 1.8007e-03 eta: 9:36:41 time: 0.5664 data_time: 0.0212 memory: 17620 loss: 1.9445 loss_prob: 1.1424 loss_thr: 0.6225 loss_db: 0.1796 2022/11/01 16:19:11 - mmengine - INFO - Epoch(train) [311][60/63] lr: 1.8007e-03 eta: 9:36:33 time: 0.5470 data_time: 0.0136 memory: 17620 loss: 1.8829 loss_prob: 1.1044 loss_thr: 0.5991 loss_db: 0.1794 2022/11/01 16:19:13 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:19:18 - mmengine - INFO - Epoch(train) [312][5/63] lr: 1.7989e-03 eta: 9:36:33 time: 0.7798 data_time: 0.2277 memory: 17620 loss: 1.8442 loss_prob: 1.0643 loss_thr: 0.6059 loss_db: 0.1741 2022/11/01 16:19:21 - mmengine - INFO - Epoch(train) [312][10/63] lr: 1.7989e-03 eta: 9:36:24 time: 0.7687 data_time: 0.2258 memory: 17620 loss: 1.9760 loss_prob: 1.1535 loss_thr: 0.6385 loss_db: 0.1841 2022/11/01 16:19:23 - mmengine - INFO - Epoch(train) [312][15/63] lr: 1.7989e-03 eta: 9:36:24 time: 0.5167 data_time: 0.0056 memory: 17620 loss: 2.1274 loss_prob: 1.2654 loss_thr: 0.6636 loss_db: 0.1985 2022/11/01 16:19:26 - mmengine - INFO - Epoch(train) [312][20/63] lr: 1.7989e-03 eta: 9:36:15 time: 0.5435 data_time: 0.0066 memory: 17620 loss: 2.0593 loss_prob: 1.2100 loss_thr: 0.6541 loss_db: 0.1951 2022/11/01 16:19:29 - mmengine - INFO - Epoch(train) [312][25/63] lr: 1.7989e-03 eta: 9:36:15 time: 0.5588 data_time: 0.0156 memory: 17620 loss: 1.7707 loss_prob: 1.0149 loss_thr: 0.5906 loss_db: 0.1652 2022/11/01 16:19:32 - mmengine - INFO - Epoch(train) [312][30/63] lr: 1.7989e-03 eta: 9:36:08 time: 0.5587 data_time: 0.0327 memory: 17620 loss: 1.9067 loss_prob: 1.1146 loss_thr: 0.6146 loss_db: 0.1775 2022/11/01 16:19:35 - mmengine - INFO - Epoch(train) [312][35/63] lr: 1.7989e-03 eta: 9:36:08 time: 0.5735 data_time: 0.0241 memory: 17620 loss: 1.9264 loss_prob: 1.1211 loss_thr: 0.6298 loss_db: 0.1754 2022/11/01 16:19:37 - mmengine - INFO - Epoch(train) [312][40/63] lr: 1.7989e-03 eta: 9:36:00 time: 0.5684 data_time: 0.0101 memory: 17620 loss: 1.8432 loss_prob: 1.0694 loss_thr: 0.6043 loss_db: 0.1695 2022/11/01 16:19:40 - mmengine - INFO - Epoch(train) [312][45/63] lr: 1.7989e-03 eta: 9:36:00 time: 0.5412 data_time: 0.0093 memory: 17620 loss: 1.9423 loss_prob: 1.1484 loss_thr: 0.6082 loss_db: 0.1857 2022/11/01 16:19:43 - mmengine - INFO - Epoch(train) [312][50/63] lr: 1.7989e-03 eta: 9:35:52 time: 0.5454 data_time: 0.0166 memory: 17620 loss: 1.8766 loss_prob: 1.0996 loss_thr: 0.6007 loss_db: 0.1763 2022/11/01 16:19:46 - mmengine - INFO - Epoch(train) [312][55/63] lr: 1.7989e-03 eta: 9:35:52 time: 0.5531 data_time: 0.0177 memory: 17620 loss: 1.8269 loss_prob: 1.0618 loss_thr: 0.5921 loss_db: 0.1730 2022/11/01 16:19:48 - mmengine - INFO - Epoch(train) [312][60/63] lr: 1.7989e-03 eta: 9:35:44 time: 0.5651 data_time: 0.0091 memory: 17620 loss: 1.8125 loss_prob: 1.0441 loss_thr: 0.5958 loss_db: 0.1726 2022/11/01 16:19:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:19:55 - mmengine - INFO - Epoch(train) [313][5/63] lr: 1.7970e-03 eta: 9:35:44 time: 0.7468 data_time: 0.2006 memory: 17620 loss: 1.9094 loss_prob: 1.1378 loss_thr: 0.5916 loss_db: 0.1799 2022/11/01 16:19:58 - mmengine - INFO - Epoch(train) [313][10/63] lr: 1.7970e-03 eta: 9:35:35 time: 0.7643 data_time: 0.2019 memory: 17620 loss: 2.0246 loss_prob: 1.2255 loss_thr: 0.6074 loss_db: 0.1918 2022/11/01 16:20:00 - mmengine - INFO - Epoch(train) [313][15/63] lr: 1.7970e-03 eta: 9:35:35 time: 0.5490 data_time: 0.0102 memory: 17620 loss: 2.0109 loss_prob: 1.1994 loss_thr: 0.6201 loss_db: 0.1913 2022/11/01 16:20:03 - mmengine - INFO - Epoch(train) [313][20/63] lr: 1.7970e-03 eta: 9:35:27 time: 0.5460 data_time: 0.0099 memory: 17620 loss: 1.8439 loss_prob: 1.0661 loss_thr: 0.6055 loss_db: 0.1723 2022/11/01 16:20:06 - mmengine - INFO - Epoch(train) [313][25/63] lr: 1.7970e-03 eta: 9:35:27 time: 0.5830 data_time: 0.0168 memory: 17620 loss: 1.7943 loss_prob: 1.0508 loss_thr: 0.5783 loss_db: 0.1652 2022/11/01 16:20:09 - mmengine - INFO - Epoch(train) [313][30/63] lr: 1.7970e-03 eta: 9:35:20 time: 0.5993 data_time: 0.0305 memory: 17620 loss: 1.8715 loss_prob: 1.0905 loss_thr: 0.6100 loss_db: 0.1709 2022/11/01 16:20:12 - mmengine - INFO - Epoch(train) [313][35/63] lr: 1.7970e-03 eta: 9:35:20 time: 0.5597 data_time: 0.0206 memory: 17620 loss: 1.8658 loss_prob: 1.0808 loss_thr: 0.6128 loss_db: 0.1722 2022/11/01 16:20:14 - mmengine - INFO - Epoch(train) [313][40/63] lr: 1.7970e-03 eta: 9:35:11 time: 0.5306 data_time: 0.0081 memory: 17620 loss: 1.8155 loss_prob: 1.0562 loss_thr: 0.5879 loss_db: 0.1715 2022/11/01 16:20:17 - mmengine - INFO - Epoch(train) [313][45/63] lr: 1.7970e-03 eta: 9:35:11 time: 0.5251 data_time: 0.0103 memory: 17620 loss: 1.7569 loss_prob: 1.0109 loss_thr: 0.5843 loss_db: 0.1617 2022/11/01 16:20:20 - mmengine - INFO - Epoch(train) [313][50/63] lr: 1.7970e-03 eta: 9:35:03 time: 0.5458 data_time: 0.0194 memory: 17620 loss: 1.7091 loss_prob: 0.9896 loss_thr: 0.5632 loss_db: 0.1563 2022/11/01 16:20:23 - mmengine - INFO - Epoch(train) [313][55/63] lr: 1.7970e-03 eta: 9:35:03 time: 0.5809 data_time: 0.0208 memory: 17620 loss: 1.9415 loss_prob: 1.1647 loss_thr: 0.5900 loss_db: 0.1868 2022/11/01 16:20:27 - mmengine - INFO - Epoch(train) [313][60/63] lr: 1.7970e-03 eta: 9:34:59 time: 0.6789 data_time: 0.0096 memory: 17620 loss: 2.1173 loss_prob: 1.2918 loss_thr: 0.6213 loss_db: 0.2042 2022/11/01 16:20:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:20:34 - mmengine - INFO - Epoch(train) [314][5/63] lr: 1.7952e-03 eta: 9:34:59 time: 0.8393 data_time: 0.2632 memory: 17620 loss: 1.6340 loss_prob: 0.9346 loss_thr: 0.5475 loss_db: 0.1519 2022/11/01 16:20:36 - mmengine - INFO - Epoch(train) [314][10/63] lr: 1.7952e-03 eta: 9:34:51 time: 0.8199 data_time: 0.2571 memory: 17620 loss: 1.7358 loss_prob: 1.0101 loss_thr: 0.5591 loss_db: 0.1666 2022/11/01 16:20:39 - mmengine - INFO - Epoch(train) [314][15/63] lr: 1.7952e-03 eta: 9:34:51 time: 0.5417 data_time: 0.0073 memory: 17620 loss: 1.9176 loss_prob: 1.1379 loss_thr: 0.5948 loss_db: 0.1850 2022/11/01 16:20:42 - mmengine - INFO - Epoch(train) [314][20/63] lr: 1.7952e-03 eta: 9:34:44 time: 0.5679 data_time: 0.0077 memory: 17620 loss: 1.9260 loss_prob: 1.1452 loss_thr: 0.5947 loss_db: 0.1861 2022/11/01 16:20:46 - mmengine - INFO - Epoch(train) [314][25/63] lr: 1.7952e-03 eta: 9:34:44 time: 0.6564 data_time: 0.0413 memory: 17620 loss: 2.1565 loss_prob: 1.3267 loss_thr: 0.6261 loss_db: 0.2038 2022/11/01 16:20:49 - mmengine - INFO - Epoch(train) [314][30/63] lr: 1.7952e-03 eta: 9:34:39 time: 0.6833 data_time: 0.0398 memory: 17620 loss: 2.0518 loss_prob: 1.2520 loss_thr: 0.6103 loss_db: 0.1895 2022/11/01 16:20:51 - mmengine - INFO - Epoch(train) [314][35/63] lr: 1.7952e-03 eta: 9:34:39 time: 0.5955 data_time: 0.0065 memory: 17620 loss: 1.8285 loss_prob: 1.0696 loss_thr: 0.5832 loss_db: 0.1757 2022/11/01 16:20:54 - mmengine - INFO - Epoch(train) [314][40/63] lr: 1.7952e-03 eta: 9:34:31 time: 0.5434 data_time: 0.0066 memory: 17620 loss: 1.9458 loss_prob: 1.1495 loss_thr: 0.6073 loss_db: 0.1889 2022/11/01 16:20:57 - mmengine - INFO - Epoch(train) [314][45/63] lr: 1.7952e-03 eta: 9:34:31 time: 0.5257 data_time: 0.0056 memory: 17620 loss: 2.0893 loss_prob: 1.2756 loss_thr: 0.6129 loss_db: 0.2008 2022/11/01 16:21:00 - mmengine - INFO - Epoch(train) [314][50/63] lr: 1.7952e-03 eta: 9:34:25 time: 0.6047 data_time: 0.0277 memory: 17620 loss: 2.3944 loss_prob: 1.5141 loss_thr: 0.6470 loss_db: 0.2334 2022/11/01 16:21:03 - mmengine - INFO - Epoch(train) [314][55/63] lr: 1.7952e-03 eta: 9:34:25 time: 0.6265 data_time: 0.0289 memory: 17620 loss: 2.2247 loss_prob: 1.3585 loss_thr: 0.6533 loss_db: 0.2129 2022/11/01 16:21:06 - mmengine - INFO - Epoch(train) [314][60/63] lr: 1.7952e-03 eta: 9:34:17 time: 0.5580 data_time: 0.0087 memory: 17620 loss: 2.0177 loss_prob: 1.2008 loss_thr: 0.6236 loss_db: 0.1933 2022/11/01 16:21:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:21:12 - mmengine - INFO - Epoch(train) [315][5/63] lr: 1.7934e-03 eta: 9:34:17 time: 0.7864 data_time: 0.2140 memory: 17620 loss: 2.0119 loss_prob: 1.2031 loss_thr: 0.6221 loss_db: 0.1868 2022/11/01 16:21:16 - mmengine - INFO - Epoch(train) [315][10/63] lr: 1.7934e-03 eta: 9:34:11 time: 0.8713 data_time: 0.2131 memory: 17620 loss: 1.9596 loss_prob: 1.1591 loss_thr: 0.6167 loss_db: 0.1838 2022/11/01 16:21:19 - mmengine - INFO - Epoch(train) [315][15/63] lr: 1.7934e-03 eta: 9:34:11 time: 0.6305 data_time: 0.0062 memory: 17620 loss: 1.8594 loss_prob: 1.0940 loss_thr: 0.5917 loss_db: 0.1737 2022/11/01 16:21:22 - mmengine - INFO - Epoch(train) [315][20/63] lr: 1.7934e-03 eta: 9:34:04 time: 0.5911 data_time: 0.0056 memory: 17620 loss: 1.8099 loss_prob: 1.0464 loss_thr: 0.5961 loss_db: 0.1675 2022/11/01 16:21:24 - mmengine - INFO - Epoch(train) [315][25/63] lr: 1.7934e-03 eta: 9:34:04 time: 0.5631 data_time: 0.0169 memory: 17620 loss: 1.8128 loss_prob: 1.0339 loss_thr: 0.6061 loss_db: 0.1727 2022/11/01 16:21:27 - mmengine - INFO - Epoch(train) [315][30/63] lr: 1.7934e-03 eta: 9:33:56 time: 0.5487 data_time: 0.0354 memory: 17620 loss: 1.8271 loss_prob: 1.0484 loss_thr: 0.6065 loss_db: 0.1723 2022/11/01 16:21:30 - mmengine - INFO - Epoch(train) [315][35/63] lr: 1.7934e-03 eta: 9:33:56 time: 0.5476 data_time: 0.0237 memory: 17620 loss: 1.9150 loss_prob: 1.1129 loss_thr: 0.6273 loss_db: 0.1748 2022/11/01 16:21:33 - mmengine - INFO - Epoch(train) [315][40/63] lr: 1.7934e-03 eta: 9:33:47 time: 0.5266 data_time: 0.0050 memory: 17620 loss: 1.8538 loss_prob: 1.0642 loss_thr: 0.6205 loss_db: 0.1692 2022/11/01 16:21:35 - mmengine - INFO - Epoch(train) [315][45/63] lr: 1.7934e-03 eta: 9:33:47 time: 0.5316 data_time: 0.0046 memory: 17620 loss: 1.8099 loss_prob: 1.0437 loss_thr: 0.5941 loss_db: 0.1721 2022/11/01 16:21:38 - mmengine - INFO - Epoch(train) [315][50/63] lr: 1.7934e-03 eta: 9:33:39 time: 0.5644 data_time: 0.0175 memory: 17620 loss: 1.8509 loss_prob: 1.0787 loss_thr: 0.5959 loss_db: 0.1763 2022/11/01 16:21:41 - mmengine - INFO - Epoch(train) [315][55/63] lr: 1.7934e-03 eta: 9:33:39 time: 0.5774 data_time: 0.0265 memory: 17620 loss: 1.9148 loss_prob: 1.1009 loss_thr: 0.6324 loss_db: 0.1815 2022/11/01 16:21:44 - mmengine - INFO - Epoch(train) [315][60/63] lr: 1.7934e-03 eta: 9:33:31 time: 0.5536 data_time: 0.0138 memory: 17620 loss: 1.8596 loss_prob: 1.0599 loss_thr: 0.6257 loss_db: 0.1741 2022/11/01 16:21:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:21:50 - mmengine - INFO - Epoch(train) [316][5/63] lr: 1.7916e-03 eta: 9:33:31 time: 0.7246 data_time: 0.2003 memory: 17620 loss: 1.9536 loss_prob: 1.1559 loss_thr: 0.6158 loss_db: 0.1819 2022/11/01 16:21:53 - mmengine - INFO - Epoch(train) [316][10/63] lr: 1.7916e-03 eta: 9:33:22 time: 0.7648 data_time: 0.1990 memory: 17620 loss: 1.8858 loss_prob: 1.0908 loss_thr: 0.6171 loss_db: 0.1780 2022/11/01 16:21:55 - mmengine - INFO - Epoch(train) [316][15/63] lr: 1.7916e-03 eta: 9:33:22 time: 0.5443 data_time: 0.0051 memory: 17620 loss: 1.8266 loss_prob: 1.0474 loss_thr: 0.6102 loss_db: 0.1690 2022/11/01 16:21:58 - mmengine - INFO - Epoch(train) [316][20/63] lr: 1.7916e-03 eta: 9:33:13 time: 0.5152 data_time: 0.0053 memory: 17620 loss: 1.8264 loss_prob: 1.0714 loss_thr: 0.5832 loss_db: 0.1718 2022/11/01 16:22:01 - mmengine - INFO - Epoch(train) [316][25/63] lr: 1.7916e-03 eta: 9:33:13 time: 0.5518 data_time: 0.0345 memory: 17620 loss: 1.6662 loss_prob: 0.9606 loss_thr: 0.5549 loss_db: 0.1507 2022/11/01 16:22:04 - mmengine - INFO - Epoch(train) [316][30/63] lr: 1.7916e-03 eta: 9:33:06 time: 0.5672 data_time: 0.0339 memory: 17620 loss: 1.6827 loss_prob: 0.9602 loss_thr: 0.5707 loss_db: 0.1518 2022/11/01 16:22:06 - mmengine - INFO - Epoch(train) [316][35/63] lr: 1.7916e-03 eta: 9:33:06 time: 0.5290 data_time: 0.0046 memory: 17620 loss: 1.7289 loss_prob: 0.9931 loss_thr: 0.5745 loss_db: 0.1614 2022/11/01 16:22:09 - mmengine - INFO - Epoch(train) [316][40/63] lr: 1.7916e-03 eta: 9:32:57 time: 0.5248 data_time: 0.0047 memory: 17620 loss: 1.6910 loss_prob: 0.9726 loss_thr: 0.5592 loss_db: 0.1593 2022/11/01 16:22:11 - mmengine - INFO - Epoch(train) [316][45/63] lr: 1.7916e-03 eta: 9:32:57 time: 0.5371 data_time: 0.0051 memory: 17620 loss: 1.7116 loss_prob: 0.9847 loss_thr: 0.5698 loss_db: 0.1572 2022/11/01 16:22:14 - mmengine - INFO - Epoch(train) [316][50/63] lr: 1.7916e-03 eta: 9:32:49 time: 0.5580 data_time: 0.0242 memory: 17620 loss: 1.7516 loss_prob: 1.0098 loss_thr: 0.5825 loss_db: 0.1594 2022/11/01 16:22:17 - mmengine - INFO - Epoch(train) [316][55/63] lr: 1.7916e-03 eta: 9:32:49 time: 0.5700 data_time: 0.0236 memory: 17620 loss: 1.7351 loss_prob: 0.9937 loss_thr: 0.5780 loss_db: 0.1634 2022/11/01 16:22:20 - mmengine - INFO - Epoch(train) [316][60/63] lr: 1.7916e-03 eta: 9:32:41 time: 0.5432 data_time: 0.0058 memory: 17620 loss: 1.7470 loss_prob: 0.9963 loss_thr: 0.5875 loss_db: 0.1632 2022/11/01 16:22:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:22:26 - mmengine - INFO - Epoch(train) [317][5/63] lr: 1.7897e-03 eta: 9:32:41 time: 0.7309 data_time: 0.2037 memory: 17620 loss: 1.8199 loss_prob: 1.0410 loss_thr: 0.6071 loss_db: 0.1718 2022/11/01 16:22:29 - mmengine - INFO - Epoch(train) [317][10/63] lr: 1.7897e-03 eta: 9:32:31 time: 0.7514 data_time: 0.2074 memory: 17620 loss: 1.8530 loss_prob: 1.0760 loss_thr: 0.6000 loss_db: 0.1770 2022/11/01 16:22:31 - mmengine - INFO - Epoch(train) [317][15/63] lr: 1.7897e-03 eta: 9:32:31 time: 0.5315 data_time: 0.0091 memory: 17620 loss: 1.8792 loss_prob: 1.0999 loss_thr: 0.6050 loss_db: 0.1743 2022/11/01 16:22:34 - mmengine - INFO - Epoch(train) [317][20/63] lr: 1.7897e-03 eta: 9:32:23 time: 0.5533 data_time: 0.0052 memory: 17620 loss: 1.9692 loss_prob: 1.1821 loss_thr: 0.6033 loss_db: 0.1838 2022/11/01 16:22:37 - mmengine - INFO - Epoch(train) [317][25/63] lr: 1.7897e-03 eta: 9:32:23 time: 0.5588 data_time: 0.0204 memory: 17620 loss: 1.8645 loss_prob: 1.1165 loss_thr: 0.5717 loss_db: 0.1763 2022/11/01 16:22:40 - mmengine - INFO - Epoch(train) [317][30/63] lr: 1.7897e-03 eta: 9:32:15 time: 0.5544 data_time: 0.0209 memory: 17620 loss: 1.7025 loss_prob: 0.9704 loss_thr: 0.5729 loss_db: 0.1591 2022/11/01 16:22:43 - mmengine - INFO - Epoch(train) [317][35/63] lr: 1.7897e-03 eta: 9:32:15 time: 0.5553 data_time: 0.0176 memory: 17620 loss: 1.7764 loss_prob: 1.0211 loss_thr: 0.5895 loss_db: 0.1658 2022/11/01 16:22:45 - mmengine - INFO - Epoch(train) [317][40/63] lr: 1.7897e-03 eta: 9:32:07 time: 0.5409 data_time: 0.0193 memory: 17620 loss: 1.8716 loss_prob: 1.0915 loss_thr: 0.6074 loss_db: 0.1727 2022/11/01 16:22:48 - mmengine - INFO - Epoch(train) [317][45/63] lr: 1.7897e-03 eta: 9:32:07 time: 0.5752 data_time: 0.0105 memory: 17620 loss: 1.8373 loss_prob: 1.0569 loss_thr: 0.6121 loss_db: 0.1683 2022/11/01 16:22:51 - mmengine - INFO - Epoch(train) [317][50/63] lr: 1.7897e-03 eta: 9:32:00 time: 0.5945 data_time: 0.0217 memory: 17620 loss: 1.7115 loss_prob: 0.9760 loss_thr: 0.5750 loss_db: 0.1605 2022/11/01 16:22:54 - mmengine - INFO - Epoch(train) [317][55/63] lr: 1.7897e-03 eta: 9:32:00 time: 0.5508 data_time: 0.0227 memory: 17620 loss: 1.8609 loss_prob: 1.0880 loss_thr: 0.5989 loss_db: 0.1740 2022/11/01 16:22:57 - mmengine - INFO - Epoch(train) [317][60/63] lr: 1.7897e-03 eta: 9:31:53 time: 0.5775 data_time: 0.0099 memory: 17620 loss: 1.8766 loss_prob: 1.0934 loss_thr: 0.6098 loss_db: 0.1733 2022/11/01 16:22:58 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:23:04 - mmengine - INFO - Epoch(train) [318][5/63] lr: 1.7879e-03 eta: 9:31:53 time: 0.7819 data_time: 0.2202 memory: 17620 loss: 1.8922 loss_prob: 1.1236 loss_thr: 0.5900 loss_db: 0.1786 2022/11/01 16:23:06 - mmengine - INFO - Epoch(train) [318][10/63] lr: 1.7879e-03 eta: 9:31:44 time: 0.7735 data_time: 0.2205 memory: 17620 loss: 1.9161 loss_prob: 1.1680 loss_thr: 0.5678 loss_db: 0.1803 2022/11/01 16:23:09 - mmengine - INFO - Epoch(train) [318][15/63] lr: 1.7879e-03 eta: 9:31:44 time: 0.5591 data_time: 0.0056 memory: 17620 loss: 1.7881 loss_prob: 1.0534 loss_thr: 0.5682 loss_db: 0.1665 2022/11/01 16:23:12 - mmengine - INFO - Epoch(train) [318][20/63] lr: 1.7879e-03 eta: 9:31:38 time: 0.6043 data_time: 0.0060 memory: 17620 loss: 1.9331 loss_prob: 1.1341 loss_thr: 0.6131 loss_db: 0.1860 2022/11/01 16:23:15 - mmengine - INFO - Epoch(train) [318][25/63] lr: 1.7879e-03 eta: 9:31:38 time: 0.6270 data_time: 0.0265 memory: 17620 loss: 1.8754 loss_prob: 1.0826 loss_thr: 0.6163 loss_db: 0.1765 2022/11/01 16:23:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:23:18 - mmengine - INFO - Epoch(train) [318][30/63] lr: 1.7879e-03 eta: 9:31:32 time: 0.6209 data_time: 0.0324 memory: 17620 loss: 1.8791 loss_prob: 1.1191 loss_thr: 0.5762 loss_db: 0.1838 2022/11/01 16:23:22 - mmengine - INFO - Epoch(train) [318][35/63] lr: 1.7879e-03 eta: 9:31:32 time: 0.6140 data_time: 0.0158 memory: 17620 loss: 1.8914 loss_prob: 1.1421 loss_thr: 0.5635 loss_db: 0.1857 2022/11/01 16:23:25 - mmengine - INFO - Epoch(train) [318][40/63] lr: 1.7879e-03 eta: 9:31:26 time: 0.6239 data_time: 0.0100 memory: 17620 loss: 1.8321 loss_prob: 1.0765 loss_thr: 0.5881 loss_db: 0.1675 2022/11/01 16:23:28 - mmengine - INFO - Epoch(train) [318][45/63] lr: 1.7879e-03 eta: 9:31:26 time: 0.6246 data_time: 0.0092 memory: 17620 loss: 1.8407 loss_prob: 1.0655 loss_thr: 0.6075 loss_db: 0.1678 2022/11/01 16:23:31 - mmengine - INFO - Epoch(train) [318][50/63] lr: 1.7879e-03 eta: 9:31:20 time: 0.6216 data_time: 0.0253 memory: 17620 loss: 1.9347 loss_prob: 1.1334 loss_thr: 0.6120 loss_db: 0.1893 2022/11/01 16:23:34 - mmengine - INFO - Epoch(train) [318][55/63] lr: 1.7879e-03 eta: 9:31:20 time: 0.5851 data_time: 0.0250 memory: 17620 loss: 1.9438 loss_prob: 1.1592 loss_thr: 0.5904 loss_db: 0.1943 2022/11/01 16:23:37 - mmengine - INFO - Epoch(train) [318][60/63] lr: 1.7879e-03 eta: 9:31:12 time: 0.5716 data_time: 0.0099 memory: 17620 loss: 1.9562 loss_prob: 1.1778 loss_thr: 0.5864 loss_db: 0.1920 2022/11/01 16:23:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:23:44 - mmengine - INFO - Epoch(train) [319][5/63] lr: 1.7861e-03 eta: 9:31:12 time: 0.8197 data_time: 0.1904 memory: 17620 loss: 2.3529 loss_prob: 1.4842 loss_thr: 0.6398 loss_db: 0.2289 2022/11/01 16:23:47 - mmengine - INFO - Epoch(train) [319][10/63] lr: 1.7861e-03 eta: 9:31:06 time: 0.8560 data_time: 0.1881 memory: 17620 loss: 2.3280 loss_prob: 1.4628 loss_thr: 0.6412 loss_db: 0.2240 2022/11/01 16:23:50 - mmengine - INFO - Epoch(train) [319][15/63] lr: 1.7861e-03 eta: 9:31:06 time: 0.6477 data_time: 0.0078 memory: 17620 loss: 2.4822 loss_prob: 1.5806 loss_thr: 0.6531 loss_db: 0.2486 2022/11/01 16:23:53 - mmengine - INFO - Epoch(train) [319][20/63] lr: 1.7861e-03 eta: 9:31:00 time: 0.6400 data_time: 0.0122 memory: 17620 loss: 2.1420 loss_prob: 1.3124 loss_thr: 0.6183 loss_db: 0.2114 2022/11/01 16:23:56 - mmengine - INFO - Epoch(train) [319][25/63] lr: 1.7861e-03 eta: 9:31:00 time: 0.5730 data_time: 0.0199 memory: 17620 loss: 1.9694 loss_prob: 1.1701 loss_thr: 0.6129 loss_db: 0.1864 2022/11/01 16:23:59 - mmengine - INFO - Epoch(train) [319][30/63] lr: 1.7861e-03 eta: 9:30:52 time: 0.5557 data_time: 0.0293 memory: 17620 loss: 1.9948 loss_prob: 1.1783 loss_thr: 0.6325 loss_db: 0.1840 2022/11/01 16:24:01 - mmengine - INFO - Epoch(train) [319][35/63] lr: 1.7861e-03 eta: 9:30:52 time: 0.5351 data_time: 0.0231 memory: 17620 loss: 1.9381 loss_prob: 1.1376 loss_thr: 0.6181 loss_db: 0.1823 2022/11/01 16:24:04 - mmengine - INFO - Epoch(train) [319][40/63] lr: 1.7861e-03 eta: 9:30:45 time: 0.5783 data_time: 0.0090 memory: 17620 loss: 1.9026 loss_prob: 1.1087 loss_thr: 0.6143 loss_db: 0.1796 2022/11/01 16:24:07 - mmengine - INFO - Epoch(train) [319][45/63] lr: 1.7861e-03 eta: 9:30:45 time: 0.5938 data_time: 0.0113 memory: 17620 loss: 1.9039 loss_prob: 1.0981 loss_thr: 0.6337 loss_db: 0.1721 2022/11/01 16:24:10 - mmengine - INFO - Epoch(train) [319][50/63] lr: 1.7861e-03 eta: 9:30:38 time: 0.5727 data_time: 0.0206 memory: 17620 loss: 1.8724 loss_prob: 1.0809 loss_thr: 0.6193 loss_db: 0.1721 2022/11/01 16:24:13 - mmengine - INFO - Epoch(train) [319][55/63] lr: 1.7861e-03 eta: 9:30:38 time: 0.5679 data_time: 0.0219 memory: 17620 loss: 1.8653 loss_prob: 1.0905 loss_thr: 0.5986 loss_db: 0.1762 2022/11/01 16:24:15 - mmengine - INFO - Epoch(train) [319][60/63] lr: 1.7861e-03 eta: 9:30:30 time: 0.5401 data_time: 0.0157 memory: 17620 loss: 1.9603 loss_prob: 1.1799 loss_thr: 0.5935 loss_db: 0.1869 2022/11/01 16:24:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:24:22 - mmengine - INFO - Epoch(train) [320][5/63] lr: 1.7843e-03 eta: 9:30:30 time: 0.7169 data_time: 0.2242 memory: 17620 loss: 1.7762 loss_prob: 1.0360 loss_thr: 0.5734 loss_db: 0.1668 2022/11/01 16:24:24 - mmengine - INFO - Epoch(train) [320][10/63] lr: 1.7843e-03 eta: 9:30:20 time: 0.7511 data_time: 0.2286 memory: 17620 loss: 1.7649 loss_prob: 1.0149 loss_thr: 0.5848 loss_db: 0.1652 2022/11/01 16:24:27 - mmengine - INFO - Epoch(train) [320][15/63] lr: 1.7843e-03 eta: 9:30:20 time: 0.5368 data_time: 0.0119 memory: 17620 loss: 1.7813 loss_prob: 1.0375 loss_thr: 0.5803 loss_db: 0.1634 2022/11/01 16:24:30 - mmengine - INFO - Epoch(train) [320][20/63] lr: 1.7843e-03 eta: 9:30:12 time: 0.5309 data_time: 0.0050 memory: 17620 loss: 1.8798 loss_prob: 1.0988 loss_thr: 0.6052 loss_db: 0.1758 2022/11/01 16:24:33 - mmengine - INFO - Epoch(train) [320][25/63] lr: 1.7843e-03 eta: 9:30:12 time: 0.5812 data_time: 0.0224 memory: 17620 loss: 1.9212 loss_prob: 1.1315 loss_thr: 0.6125 loss_db: 0.1771 2022/11/01 16:24:36 - mmengine - INFO - Epoch(train) [320][30/63] lr: 1.7843e-03 eta: 9:30:05 time: 0.6019 data_time: 0.0320 memory: 17620 loss: 1.8472 loss_prob: 1.0837 loss_thr: 0.5959 loss_db: 0.1676 2022/11/01 16:24:38 - mmengine - INFO - Epoch(train) [320][35/63] lr: 1.7843e-03 eta: 9:30:05 time: 0.5671 data_time: 0.0225 memory: 17620 loss: 1.8250 loss_prob: 1.0530 loss_thr: 0.6050 loss_db: 0.1670 2022/11/01 16:24:41 - mmengine - INFO - Epoch(train) [320][40/63] lr: 1.7843e-03 eta: 9:29:58 time: 0.5749 data_time: 0.0128 memory: 17620 loss: 1.6631 loss_prob: 0.9550 loss_thr: 0.5554 loss_db: 0.1527 2022/11/01 16:24:44 - mmengine - INFO - Epoch(train) [320][45/63] lr: 1.7843e-03 eta: 9:29:58 time: 0.5732 data_time: 0.0054 memory: 17620 loss: 1.6734 loss_prob: 0.9559 loss_thr: 0.5638 loss_db: 0.1537 2022/11/01 16:24:47 - mmengine - INFO - Epoch(train) [320][50/63] lr: 1.7843e-03 eta: 9:29:50 time: 0.5748 data_time: 0.0209 memory: 17620 loss: 1.8016 loss_prob: 1.0248 loss_thr: 0.6102 loss_db: 0.1666 2022/11/01 16:24:50 - mmengine - INFO - Epoch(train) [320][55/63] lr: 1.7843e-03 eta: 9:29:50 time: 0.5535 data_time: 0.0209 memory: 17620 loss: 1.9908 loss_prob: 1.1883 loss_thr: 0.6081 loss_db: 0.1944 2022/11/01 16:24:52 - mmengine - INFO - Epoch(train) [320][60/63] lr: 1.7843e-03 eta: 9:29:42 time: 0.5332 data_time: 0.0083 memory: 17620 loss: 1.9274 loss_prob: 1.1519 loss_thr: 0.5893 loss_db: 0.1862 2022/11/01 16:24:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:24:54 - mmengine - INFO - Saving checkpoint at 320 epochs 2022/11/01 16:25:01 - mmengine - INFO - Epoch(val) [320][5/32] eta: 9:29:42 time: 0.5666 data_time: 0.0788 memory: 17620 2022/11/01 16:25:04 - mmengine - INFO - Epoch(val) [320][10/32] eta: 0:00:14 time: 0.6605 data_time: 0.1266 memory: 15725 2022/11/01 16:25:07 - mmengine - INFO - Epoch(val) [320][15/32] eta: 0:00:14 time: 0.6047 data_time: 0.0725 memory: 15725 2022/11/01 16:25:10 - mmengine - INFO - Epoch(val) [320][20/32] eta: 0:00:07 time: 0.5994 data_time: 0.0563 memory: 15725 2022/11/01 16:25:13 - mmengine - INFO - Epoch(val) [320][25/32] eta: 0:00:07 time: 0.6147 data_time: 0.0513 memory: 15725 2022/11/01 16:25:16 - mmengine - INFO - Epoch(val) [320][30/32] eta: 0:00:01 time: 0.5674 data_time: 0.0212 memory: 15725 2022/11/01 16:25:16 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8474, precision: 0.6814, hmean: 0.7554 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8474, precision: 0.7805, hmean: 0.8126 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8440, precision: 0.8392, hmean: 0.8416 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8296, precision: 0.8804, hmean: 0.8542 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7901, precision: 0.9193, hmean: 0.8498 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4834, precision: 0.9608, hmean: 0.6432 2022/11/01 16:25:16 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0005, precision: 1.0000, hmean: 0.0010 2022/11/01 16:25:16 - mmengine - INFO - Epoch(val) [320][32/32] icdar/precision: 0.8804 icdar/recall: 0.8296 icdar/hmean: 0.8542 2022/11/01 16:25:22 - mmengine - INFO - Epoch(train) [321][5/63] lr: 1.7824e-03 eta: 0:00:01 time: 0.7862 data_time: 0.2052 memory: 17620 loss: 1.7171 loss_prob: 0.9837 loss_thr: 0.5770 loss_db: 0.1565 2022/11/01 16:25:25 - mmengine - INFO - Epoch(train) [321][10/63] lr: 1.7824e-03 eta: 9:29:35 time: 0.8349 data_time: 0.2072 memory: 17620 loss: 1.7956 loss_prob: 1.0474 loss_thr: 0.5820 loss_db: 0.1662 2022/11/01 16:25:28 - mmengine - INFO - Epoch(train) [321][15/63] lr: 1.7824e-03 eta: 9:29:35 time: 0.5809 data_time: 0.0097 memory: 17620 loss: 1.6514 loss_prob: 0.9489 loss_thr: 0.5508 loss_db: 0.1517 2022/11/01 16:25:30 - mmengine - INFO - Epoch(train) [321][20/63] lr: 1.7824e-03 eta: 9:29:27 time: 0.5660 data_time: 0.0074 memory: 17620 loss: 1.7623 loss_prob: 1.0276 loss_thr: 0.5656 loss_db: 0.1691 2022/11/01 16:25:33 - mmengine - INFO - Epoch(train) [321][25/63] lr: 1.7824e-03 eta: 9:29:27 time: 0.5920 data_time: 0.0189 memory: 17620 loss: 1.8993 loss_prob: 1.1194 loss_thr: 0.5986 loss_db: 0.1813 2022/11/01 16:25:36 - mmengine - INFO - Epoch(train) [321][30/63] lr: 1.7824e-03 eta: 9:29:21 time: 0.6017 data_time: 0.0301 memory: 17620 loss: 1.7312 loss_prob: 0.9961 loss_thr: 0.5766 loss_db: 0.1585 2022/11/01 16:25:39 - mmengine - INFO - Epoch(train) [321][35/63] lr: 1.7824e-03 eta: 9:29:21 time: 0.6008 data_time: 0.0231 memory: 17620 loss: 1.8369 loss_prob: 1.0798 loss_thr: 0.5866 loss_db: 0.1704 2022/11/01 16:25:43 - mmengine - INFO - Epoch(train) [321][40/63] lr: 1.7824e-03 eta: 9:29:15 time: 0.6381 data_time: 0.0110 memory: 17620 loss: 1.7928 loss_prob: 1.0551 loss_thr: 0.5678 loss_db: 0.1699 2022/11/01 16:25:46 - mmengine - INFO - Epoch(train) [321][45/63] lr: 1.7824e-03 eta: 9:29:15 time: 0.6135 data_time: 0.0051 memory: 17620 loss: 1.7361 loss_prob: 1.0004 loss_thr: 0.5752 loss_db: 0.1606 2022/11/01 16:25:49 - mmengine - INFO - Epoch(train) [321][50/63] lr: 1.7824e-03 eta: 9:29:11 time: 0.6735 data_time: 0.0167 memory: 17620 loss: 1.7822 loss_prob: 1.0165 loss_thr: 0.6042 loss_db: 0.1614 2022/11/01 16:25:52 - mmengine - INFO - Epoch(train) [321][55/63] lr: 1.7824e-03 eta: 9:29:11 time: 0.6882 data_time: 0.0219 memory: 17620 loss: 1.8048 loss_prob: 1.0262 loss_thr: 0.6142 loss_db: 0.1645 2022/11/01 16:25:55 - mmengine - INFO - Epoch(train) [321][60/63] lr: 1.7824e-03 eta: 9:29:03 time: 0.5700 data_time: 0.0155 memory: 17620 loss: 1.9610 loss_prob: 1.1556 loss_thr: 0.6223 loss_db: 0.1832 2022/11/01 16:25:57 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:26:02 - mmengine - INFO - Epoch(train) [322][5/63] lr: 1.7806e-03 eta: 9:29:03 time: 0.7707 data_time: 0.2245 memory: 17620 loss: 1.8752 loss_prob: 1.1141 loss_thr: 0.5865 loss_db: 0.1746 2022/11/01 16:26:05 - mmengine - INFO - Epoch(train) [322][10/63] lr: 1.7806e-03 eta: 9:28:56 time: 0.8343 data_time: 0.2228 memory: 17620 loss: 1.7953 loss_prob: 1.0449 loss_thr: 0.5856 loss_db: 0.1648 2022/11/01 16:26:08 - mmengine - INFO - Epoch(train) [322][15/63] lr: 1.7806e-03 eta: 9:28:56 time: 0.6148 data_time: 0.0076 memory: 17620 loss: 1.8759 loss_prob: 1.1014 loss_thr: 0.5951 loss_db: 0.1795 2022/11/01 16:26:11 - mmengine - INFO - Epoch(train) [322][20/63] lr: 1.7806e-03 eta: 9:28:50 time: 0.6301 data_time: 0.0065 memory: 17620 loss: 1.7549 loss_prob: 0.9982 loss_thr: 0.5913 loss_db: 0.1654 2022/11/01 16:26:14 - mmengine - INFO - Epoch(train) [322][25/63] lr: 1.7806e-03 eta: 9:28:50 time: 0.6292 data_time: 0.0268 memory: 17620 loss: 1.6244 loss_prob: 0.9058 loss_thr: 0.5690 loss_db: 0.1495 2022/11/01 16:26:17 - mmengine - INFO - Epoch(train) [322][30/63] lr: 1.7806e-03 eta: 9:28:43 time: 0.5804 data_time: 0.0342 memory: 17620 loss: 1.7978 loss_prob: 1.0591 loss_thr: 0.5674 loss_db: 0.1714 2022/11/01 16:26:20 - mmengine - INFO - Epoch(train) [322][35/63] lr: 1.7806e-03 eta: 9:28:43 time: 0.5435 data_time: 0.0159 memory: 17620 loss: 1.8846 loss_prob: 1.1061 loss_thr: 0.6002 loss_db: 0.1784 2022/11/01 16:26:22 - mmengine - INFO - Epoch(train) [322][40/63] lr: 1.7806e-03 eta: 9:28:35 time: 0.5447 data_time: 0.0091 memory: 17620 loss: 2.0821 loss_prob: 1.2671 loss_thr: 0.6181 loss_db: 0.1969 2022/11/01 16:26:26 - mmengine - INFO - Epoch(train) [322][45/63] lr: 1.7806e-03 eta: 9:28:35 time: 0.5887 data_time: 0.0066 memory: 17620 loss: 2.0347 loss_prob: 1.2354 loss_thr: 0.6096 loss_db: 0.1897 2022/11/01 16:26:29 - mmengine - INFO - Epoch(train) [322][50/63] lr: 1.7806e-03 eta: 9:28:30 time: 0.6751 data_time: 0.0180 memory: 17620 loss: 1.9214 loss_prob: 1.1282 loss_thr: 0.6097 loss_db: 0.1835 2022/11/01 16:26:32 - mmengine - INFO - Epoch(train) [322][55/63] lr: 1.7806e-03 eta: 9:28:30 time: 0.6272 data_time: 0.0237 memory: 17620 loss: 1.9143 loss_prob: 1.1286 loss_thr: 0.6002 loss_db: 0.1855 2022/11/01 16:26:35 - mmengine - INFO - Epoch(train) [322][60/63] lr: 1.7806e-03 eta: 9:28:22 time: 0.5356 data_time: 0.0146 memory: 17620 loss: 1.7362 loss_prob: 0.9913 loss_thr: 0.5831 loss_db: 0.1618 2022/11/01 16:26:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:26:41 - mmengine - INFO - Epoch(train) [323][5/63] lr: 1.7788e-03 eta: 9:28:22 time: 0.7313 data_time: 0.2096 memory: 17620 loss: 1.7498 loss_prob: 1.0085 loss_thr: 0.5714 loss_db: 0.1699 2022/11/01 16:26:44 - mmengine - INFO - Epoch(train) [323][10/63] lr: 1.7788e-03 eta: 9:28:13 time: 0.7761 data_time: 0.2108 memory: 17620 loss: 1.9387 loss_prob: 1.1460 loss_thr: 0.6030 loss_db: 0.1897 2022/11/01 16:26:46 - mmengine - INFO - Epoch(train) [323][15/63] lr: 1.7788e-03 eta: 9:28:13 time: 0.5542 data_time: 0.0073 memory: 17620 loss: 1.9403 loss_prob: 1.1470 loss_thr: 0.6064 loss_db: 0.1868 2022/11/01 16:26:49 - mmengine - INFO - Epoch(train) [323][20/63] lr: 1.7788e-03 eta: 9:28:05 time: 0.5467 data_time: 0.0062 memory: 17620 loss: 1.8137 loss_prob: 1.0488 loss_thr: 0.5925 loss_db: 0.1724 2022/11/01 16:26:52 - mmengine - INFO - Epoch(train) [323][25/63] lr: 1.7788e-03 eta: 9:28:05 time: 0.5782 data_time: 0.0334 memory: 17620 loss: 1.7986 loss_prob: 1.0375 loss_thr: 0.5925 loss_db: 0.1686 2022/11/01 16:26:55 - mmengine - INFO - Epoch(train) [323][30/63] lr: 1.7788e-03 eta: 9:27:58 time: 0.5634 data_time: 0.0345 memory: 17620 loss: 1.8725 loss_prob: 1.0926 loss_thr: 0.6024 loss_db: 0.1775 2022/11/01 16:26:57 - mmengine - INFO - Epoch(train) [323][35/63] lr: 1.7788e-03 eta: 9:27:58 time: 0.5342 data_time: 0.0112 memory: 17620 loss: 1.8983 loss_prob: 1.0996 loss_thr: 0.6217 loss_db: 0.1771 2022/11/01 16:27:00 - mmengine - INFO - Epoch(train) [323][40/63] lr: 1.7788e-03 eta: 9:27:49 time: 0.5310 data_time: 0.0106 memory: 17620 loss: 1.8056 loss_prob: 1.0332 loss_thr: 0.6097 loss_db: 0.1628 2022/11/01 16:27:03 - mmengine - INFO - Epoch(train) [323][45/63] lr: 1.7788e-03 eta: 9:27:49 time: 0.5631 data_time: 0.0073 memory: 17620 loss: 1.7637 loss_prob: 1.0202 loss_thr: 0.5842 loss_db: 0.1592 2022/11/01 16:27:06 - mmengine - INFO - Epoch(train) [323][50/63] lr: 1.7788e-03 eta: 9:27:42 time: 0.5799 data_time: 0.0237 memory: 17620 loss: 1.7507 loss_prob: 1.0111 loss_thr: 0.5751 loss_db: 0.1645 2022/11/01 16:27:09 - mmengine - INFO - Epoch(train) [323][55/63] lr: 1.7788e-03 eta: 9:27:42 time: 0.5492 data_time: 0.0243 memory: 17620 loss: 1.7432 loss_prob: 1.0140 loss_thr: 0.5666 loss_db: 0.1626 2022/11/01 16:27:11 - mmengine - INFO - Epoch(train) [323][60/63] lr: 1.7788e-03 eta: 9:27:33 time: 0.5189 data_time: 0.0071 memory: 17620 loss: 1.7979 loss_prob: 1.0507 loss_thr: 0.5805 loss_db: 0.1667 2022/11/01 16:27:12 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:27:17 - mmengine - INFO - Epoch(train) [324][5/63] lr: 1.7770e-03 eta: 9:27:33 time: 0.7059 data_time: 0.1811 memory: 17620 loss: 1.8999 loss_prob: 1.1024 loss_thr: 0.6194 loss_db: 0.1781 2022/11/01 16:27:20 - mmengine - INFO - Epoch(train) [324][10/63] lr: 1.7770e-03 eta: 9:27:24 time: 0.7553 data_time: 0.1869 memory: 17620 loss: 1.7276 loss_prob: 0.9791 loss_thr: 0.5905 loss_db: 0.1580 2022/11/01 16:27:23 - mmengine - INFO - Epoch(train) [324][15/63] lr: 1.7770e-03 eta: 9:27:24 time: 0.5802 data_time: 0.0132 memory: 17620 loss: 1.7666 loss_prob: 1.0078 loss_thr: 0.5968 loss_db: 0.1619 2022/11/01 16:27:26 - mmengine - INFO - Epoch(train) [324][20/63] lr: 1.7770e-03 eta: 9:27:17 time: 0.5859 data_time: 0.0229 memory: 17620 loss: 1.7937 loss_prob: 1.0305 loss_thr: 0.5969 loss_db: 0.1663 2022/11/01 16:27:29 - mmengine - INFO - Epoch(train) [324][25/63] lr: 1.7770e-03 eta: 9:27:17 time: 0.5923 data_time: 0.0335 memory: 17620 loss: 1.8473 loss_prob: 1.0501 loss_thr: 0.6212 loss_db: 0.1760 2022/11/01 16:27:32 - mmengine - INFO - Epoch(train) [324][30/63] lr: 1.7770e-03 eta: 9:27:10 time: 0.5976 data_time: 0.0319 memory: 17620 loss: 1.8632 loss_prob: 1.0635 loss_thr: 0.6244 loss_db: 0.1754 2022/11/01 16:27:35 - mmengine - INFO - Epoch(train) [324][35/63] lr: 1.7770e-03 eta: 9:27:10 time: 0.5737 data_time: 0.0217 memory: 17620 loss: 1.9049 loss_prob: 1.1218 loss_thr: 0.6005 loss_db: 0.1827 2022/11/01 16:27:38 - mmengine - INFO - Epoch(train) [324][40/63] lr: 1.7770e-03 eta: 9:27:03 time: 0.5683 data_time: 0.0094 memory: 17620 loss: 1.8110 loss_prob: 1.0529 loss_thr: 0.5829 loss_db: 0.1752 2022/11/01 16:27:40 - mmengine - INFO - Epoch(train) [324][45/63] lr: 1.7770e-03 eta: 9:27:03 time: 0.5703 data_time: 0.0086 memory: 17620 loss: 1.7843 loss_prob: 1.0269 loss_thr: 0.5869 loss_db: 0.1705 2022/11/01 16:27:43 - mmengine - INFO - Epoch(train) [324][50/63] lr: 1.7770e-03 eta: 9:26:55 time: 0.5690 data_time: 0.0131 memory: 17620 loss: 1.9200 loss_prob: 1.1304 loss_thr: 0.6063 loss_db: 0.1833 2022/11/01 16:27:46 - mmengine - INFO - Epoch(train) [324][55/63] lr: 1.7770e-03 eta: 9:26:55 time: 0.5834 data_time: 0.0204 memory: 17620 loss: 1.8665 loss_prob: 1.0969 loss_thr: 0.5913 loss_db: 0.1783 2022/11/01 16:27:49 - mmengine - INFO - Epoch(train) [324][60/63] lr: 1.7770e-03 eta: 9:26:48 time: 0.5651 data_time: 0.0161 memory: 17620 loss: 1.8673 loss_prob: 1.0904 loss_thr: 0.5997 loss_db: 0.1772 2022/11/01 16:27:50 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:27:55 - mmengine - INFO - Epoch(train) [325][5/63] lr: 1.7751e-03 eta: 9:26:48 time: 0.7258 data_time: 0.1938 memory: 17620 loss: 1.8126 loss_prob: 1.0398 loss_thr: 0.6007 loss_db: 0.1722 2022/11/01 16:27:58 - mmengine - INFO - Epoch(train) [325][10/63] lr: 1.7751e-03 eta: 9:26:39 time: 0.7591 data_time: 0.1988 memory: 17620 loss: 1.7918 loss_prob: 1.0496 loss_thr: 0.5702 loss_db: 0.1720 2022/11/01 16:28:01 - mmengine - INFO - Epoch(train) [325][15/63] lr: 1.7751e-03 eta: 9:26:39 time: 0.5660 data_time: 0.0147 memory: 17620 loss: 1.9938 loss_prob: 1.2005 loss_thr: 0.5947 loss_db: 0.1986 2022/11/01 16:28:03 - mmengine - INFO - Epoch(train) [325][20/63] lr: 1.7751e-03 eta: 9:26:31 time: 0.5586 data_time: 0.0073 memory: 17620 loss: 2.0141 loss_prob: 1.2000 loss_thr: 0.6122 loss_db: 0.2020 2022/11/01 16:28:06 - mmengine - INFO - Epoch(train) [325][25/63] lr: 1.7751e-03 eta: 9:26:31 time: 0.5690 data_time: 0.0243 memory: 17620 loss: 2.0955 loss_prob: 1.2642 loss_thr: 0.6279 loss_db: 0.2034 2022/11/01 16:28:09 - mmengine - INFO - Epoch(train) [325][30/63] lr: 1.7751e-03 eta: 9:26:24 time: 0.5881 data_time: 0.0350 memory: 17620 loss: 2.0914 loss_prob: 1.2639 loss_thr: 0.6249 loss_db: 0.2025 2022/11/01 16:28:12 - mmengine - INFO - Epoch(train) [325][35/63] lr: 1.7751e-03 eta: 9:26:24 time: 0.5901 data_time: 0.0179 memory: 17620 loss: 1.9876 loss_prob: 1.1747 loss_thr: 0.6265 loss_db: 0.1863 2022/11/01 16:28:15 - mmengine - INFO - Epoch(train) [325][40/63] lr: 1.7751e-03 eta: 9:26:16 time: 0.5583 data_time: 0.0073 memory: 17620 loss: 1.9199 loss_prob: 1.1298 loss_thr: 0.6114 loss_db: 0.1787 2022/11/01 16:28:18 - mmengine - INFO - Epoch(train) [325][45/63] lr: 1.7751e-03 eta: 9:26:16 time: 0.5764 data_time: 0.0058 memory: 17620 loss: 1.7926 loss_prob: 1.0364 loss_thr: 0.5892 loss_db: 0.1669 2022/11/01 16:28:21 - mmengine - INFO - Epoch(train) [325][50/63] lr: 1.7751e-03 eta: 9:26:10 time: 0.6304 data_time: 0.0172 memory: 17620 loss: 1.8466 loss_prob: 1.0688 loss_thr: 0.6027 loss_db: 0.1751 2022/11/01 16:28:24 - mmengine - INFO - Epoch(train) [325][55/63] lr: 1.7751e-03 eta: 9:26:10 time: 0.5894 data_time: 0.0241 memory: 17620 loss: 1.8482 loss_prob: 1.0761 loss_thr: 0.5968 loss_db: 0.1753 2022/11/01 16:28:27 - mmengine - INFO - Epoch(train) [325][60/63] lr: 1.7751e-03 eta: 9:26:03 time: 0.5514 data_time: 0.0120 memory: 17620 loss: 1.9790 loss_prob: 1.1754 loss_thr: 0.6142 loss_db: 0.1894 2022/11/01 16:28:28 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:28:33 - mmengine - INFO - Epoch(train) [326][5/63] lr: 1.7733e-03 eta: 9:26:03 time: 0.7648 data_time: 0.2567 memory: 17620 loss: 2.0828 loss_prob: 1.2416 loss_thr: 0.6330 loss_db: 0.2082 2022/11/01 16:28:37 - mmengine - INFO - Epoch(train) [326][10/63] lr: 1.7733e-03 eta: 9:25:56 time: 0.8463 data_time: 0.2565 memory: 17620 loss: 2.0077 loss_prob: 1.1974 loss_thr: 0.6164 loss_db: 0.1939 2022/11/01 16:28:39 - mmengine - INFO - Epoch(train) [326][15/63] lr: 1.7733e-03 eta: 9:25:56 time: 0.5982 data_time: 0.0083 memory: 17620 loss: 2.0399 loss_prob: 1.2209 loss_thr: 0.6227 loss_db: 0.1963 2022/11/01 16:28:42 - mmengine - INFO - Epoch(train) [326][20/63] lr: 1.7733e-03 eta: 9:25:48 time: 0.5694 data_time: 0.0100 memory: 17620 loss: 1.9725 loss_prob: 1.1580 loss_thr: 0.6254 loss_db: 0.1890 2022/11/01 16:28:46 - mmengine - INFO - Epoch(train) [326][25/63] lr: 1.7733e-03 eta: 9:25:48 time: 0.6188 data_time: 0.0213 memory: 17620 loss: 1.8870 loss_prob: 1.0944 loss_thr: 0.6158 loss_db: 0.1767 2022/11/01 16:28:48 - mmengine - INFO - Epoch(train) [326][30/63] lr: 1.7733e-03 eta: 9:25:42 time: 0.5965 data_time: 0.0322 memory: 17620 loss: 1.8981 loss_prob: 1.1181 loss_thr: 0.5994 loss_db: 0.1806 2022/11/01 16:28:51 - mmengine - INFO - Epoch(train) [326][35/63] lr: 1.7733e-03 eta: 9:25:42 time: 0.5483 data_time: 0.0181 memory: 17620 loss: 1.9656 loss_prob: 1.1700 loss_thr: 0.6081 loss_db: 0.1874 2022/11/01 16:28:54 - mmengine - INFO - Epoch(train) [326][40/63] lr: 1.7733e-03 eta: 9:25:34 time: 0.5514 data_time: 0.0052 memory: 17620 loss: 1.8616 loss_prob: 1.0934 loss_thr: 0.5961 loss_db: 0.1720 2022/11/01 16:28:57 - mmengine - INFO - Epoch(train) [326][45/63] lr: 1.7733e-03 eta: 9:25:34 time: 0.5520 data_time: 0.0065 memory: 17620 loss: 1.7108 loss_prob: 0.9914 loss_thr: 0.5620 loss_db: 0.1574 2022/11/01 16:28:59 - mmengine - INFO - Epoch(train) [326][50/63] lr: 1.7733e-03 eta: 9:25:26 time: 0.5555 data_time: 0.0255 memory: 17620 loss: 1.8049 loss_prob: 1.0634 loss_thr: 0.5716 loss_db: 0.1699 2022/11/01 16:29:02 - mmengine - INFO - Epoch(train) [326][55/63] lr: 1.7733e-03 eta: 9:25:26 time: 0.5611 data_time: 0.0254 memory: 17620 loss: 1.9445 loss_prob: 1.1592 loss_thr: 0.5993 loss_db: 0.1859 2022/11/01 16:29:05 - mmengine - INFO - Epoch(train) [326][60/63] lr: 1.7733e-03 eta: 9:25:19 time: 0.5685 data_time: 0.0064 memory: 17620 loss: 2.0337 loss_prob: 1.2017 loss_thr: 0.6327 loss_db: 0.1992 2022/11/01 16:29:06 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:29:11 - mmengine - INFO - Epoch(train) [327][5/63] lr: 1.7715e-03 eta: 9:25:19 time: 0.7406 data_time: 0.2216 memory: 17620 loss: 1.9442 loss_prob: 1.1521 loss_thr: 0.5942 loss_db: 0.1980 2022/11/01 16:29:14 - mmengine - INFO - Epoch(train) [327][10/63] lr: 1.7715e-03 eta: 9:25:10 time: 0.7869 data_time: 0.2237 memory: 17620 loss: 2.3260 loss_prob: 1.4250 loss_thr: 0.6734 loss_db: 0.2275 2022/11/01 16:29:17 - mmengine - INFO - Epoch(train) [327][15/63] lr: 1.7715e-03 eta: 9:25:10 time: 0.5501 data_time: 0.0075 memory: 17620 loss: 2.4817 loss_prob: 1.5244 loss_thr: 0.7136 loss_db: 0.2437 2022/11/01 16:29:20 - mmengine - INFO - Epoch(train) [327][20/63] lr: 1.7715e-03 eta: 9:25:02 time: 0.5459 data_time: 0.0061 memory: 17620 loss: 1.9288 loss_prob: 1.1120 loss_thr: 0.6394 loss_db: 0.1774 2022/11/01 16:29:22 - mmengine - INFO - Epoch(train) [327][25/63] lr: 1.7715e-03 eta: 9:25:02 time: 0.5602 data_time: 0.0222 memory: 17620 loss: 1.8017 loss_prob: 1.0478 loss_thr: 0.5905 loss_db: 0.1633 2022/11/01 16:29:25 - mmengine - INFO - Epoch(train) [327][30/63] lr: 1.7715e-03 eta: 9:24:55 time: 0.5691 data_time: 0.0335 memory: 17620 loss: 1.8476 loss_prob: 1.0753 loss_thr: 0.6007 loss_db: 0.1715 2022/11/01 16:29:28 - mmengine - INFO - Epoch(train) [327][35/63] lr: 1.7715e-03 eta: 9:24:55 time: 0.5596 data_time: 0.0170 memory: 17620 loss: 2.1118 loss_prob: 1.2651 loss_thr: 0.6457 loss_db: 0.2009 2022/11/01 16:29:31 - mmengine - INFO - Epoch(train) [327][40/63] lr: 1.7715e-03 eta: 9:24:46 time: 0.5319 data_time: 0.0085 memory: 17620 loss: 2.0748 loss_prob: 1.2522 loss_thr: 0.6238 loss_db: 0.1988 2022/11/01 16:29:33 - mmengine - INFO - Epoch(train) [327][45/63] lr: 1.7715e-03 eta: 9:24:46 time: 0.5425 data_time: 0.0091 memory: 17620 loss: 1.7564 loss_prob: 0.9971 loss_thr: 0.6001 loss_db: 0.1592 2022/11/01 16:29:36 - mmengine - INFO - Epoch(train) [327][50/63] lr: 1.7715e-03 eta: 9:24:39 time: 0.5710 data_time: 0.0226 memory: 17620 loss: 1.8311 loss_prob: 1.0520 loss_thr: 0.6101 loss_db: 0.1689 2022/11/01 16:29:39 - mmengine - INFO - Epoch(train) [327][55/63] lr: 1.7715e-03 eta: 9:24:39 time: 0.5631 data_time: 0.0221 memory: 17620 loss: 1.9186 loss_prob: 1.1194 loss_thr: 0.6094 loss_db: 0.1899 2022/11/01 16:29:42 - mmengine - INFO - Epoch(train) [327][60/63] lr: 1.7715e-03 eta: 9:24:31 time: 0.5375 data_time: 0.0049 memory: 17620 loss: 1.9025 loss_prob: 1.1154 loss_thr: 0.6018 loss_db: 0.1854 2022/11/01 16:29:43 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:29:48 - mmengine - INFO - Epoch(train) [328][5/63] lr: 1.7697e-03 eta: 9:24:31 time: 0.7420 data_time: 0.1834 memory: 17620 loss: 1.8143 loss_prob: 1.0629 loss_thr: 0.5790 loss_db: 0.1724 2022/11/01 16:29:51 - mmengine - INFO - Epoch(train) [328][10/63] lr: 1.7697e-03 eta: 9:24:22 time: 0.7887 data_time: 0.1889 memory: 17620 loss: 1.7933 loss_prob: 1.0498 loss_thr: 0.5762 loss_db: 0.1673 2022/11/01 16:29:54 - mmengine - INFO - Epoch(train) [328][15/63] lr: 1.7697e-03 eta: 9:24:22 time: 0.5898 data_time: 0.0133 memory: 17620 loss: 2.0041 loss_prob: 1.2035 loss_thr: 0.6125 loss_db: 0.1881 2022/11/01 16:29:57 - mmengine - INFO - Epoch(train) [328][20/63] lr: 1.7697e-03 eta: 9:24:14 time: 0.5455 data_time: 0.0086 memory: 17620 loss: 1.9941 loss_prob: 1.1809 loss_thr: 0.6234 loss_db: 0.1897 2022/11/01 16:29:59 - mmengine - INFO - Epoch(train) [328][25/63] lr: 1.7697e-03 eta: 9:24:14 time: 0.5585 data_time: 0.0287 memory: 17620 loss: 1.8597 loss_prob: 1.0787 loss_thr: 0.6032 loss_db: 0.1777 2022/11/01 16:30:02 - mmengine - INFO - Epoch(train) [328][30/63] lr: 1.7697e-03 eta: 9:24:07 time: 0.5621 data_time: 0.0315 memory: 17620 loss: 1.8572 loss_prob: 1.0846 loss_thr: 0.5983 loss_db: 0.1743 2022/11/01 16:30:05 - mmengine - INFO - Epoch(train) [328][35/63] lr: 1.7697e-03 eta: 9:24:07 time: 0.5361 data_time: 0.0169 memory: 17620 loss: 1.8101 loss_prob: 1.0519 loss_thr: 0.5901 loss_db: 0.1681 2022/11/01 16:30:08 - mmengine - INFO - Epoch(train) [328][40/63] lr: 1.7697e-03 eta: 9:23:59 time: 0.5366 data_time: 0.0129 memory: 17620 loss: 1.8082 loss_prob: 1.0454 loss_thr: 0.5957 loss_db: 0.1671 2022/11/01 16:30:10 - mmengine - INFO - Epoch(train) [328][45/63] lr: 1.7697e-03 eta: 9:23:59 time: 0.5340 data_time: 0.0070 memory: 17620 loss: 1.8695 loss_prob: 1.0839 loss_thr: 0.6138 loss_db: 0.1718 2022/11/01 16:30:13 - mmengine - INFO - Epoch(train) [328][50/63] lr: 1.7697e-03 eta: 9:23:51 time: 0.5522 data_time: 0.0150 memory: 17620 loss: 1.7837 loss_prob: 1.0283 loss_thr: 0.5914 loss_db: 0.1640 2022/11/01 16:30:16 - mmengine - INFO - Epoch(train) [328][55/63] lr: 1.7697e-03 eta: 9:23:51 time: 0.5853 data_time: 0.0233 memory: 17620 loss: 1.8238 loss_prob: 1.0550 loss_thr: 0.5997 loss_db: 0.1692 2022/11/01 16:30:19 - mmengine - INFO - Epoch(train) [328][60/63] lr: 1.7697e-03 eta: 9:23:44 time: 0.5825 data_time: 0.0147 memory: 17620 loss: 1.8477 loss_prob: 1.0684 loss_thr: 0.6070 loss_db: 0.1723 2022/11/01 16:30:20 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:30:26 - mmengine - INFO - Epoch(train) [329][5/63] lr: 1.7678e-03 eta: 9:23:44 time: 0.7839 data_time: 0.2146 memory: 17620 loss: 1.7325 loss_prob: 0.9856 loss_thr: 0.5859 loss_db: 0.1610 2022/11/01 16:30:29 - mmengine - INFO - Epoch(train) [329][10/63] lr: 1.7678e-03 eta: 9:23:36 time: 0.8140 data_time: 0.2145 memory: 17620 loss: 1.8281 loss_prob: 1.0631 loss_thr: 0.5910 loss_db: 0.1740 2022/11/01 16:30:31 - mmengine - INFO - Epoch(train) [329][15/63] lr: 1.7678e-03 eta: 9:23:36 time: 0.5704 data_time: 0.0077 memory: 17620 loss: 1.7972 loss_prob: 1.0396 loss_thr: 0.5934 loss_db: 0.1642 2022/11/01 16:30:34 - mmengine - INFO - Epoch(train) [329][20/63] lr: 1.7678e-03 eta: 9:23:28 time: 0.5438 data_time: 0.0077 memory: 17620 loss: 1.7476 loss_prob: 1.0075 loss_thr: 0.5791 loss_db: 0.1610 2022/11/01 16:30:37 - mmengine - INFO - Epoch(train) [329][25/63] lr: 1.7678e-03 eta: 9:23:28 time: 0.5590 data_time: 0.0193 memory: 17620 loss: 2.2069 loss_prob: 1.3868 loss_thr: 0.6125 loss_db: 0.2076 2022/11/01 16:30:40 - mmengine - INFO - Epoch(train) [329][30/63] lr: 1.7678e-03 eta: 9:23:22 time: 0.6289 data_time: 0.0582 memory: 17620 loss: 2.3275 loss_prob: 1.4676 loss_thr: 0.6396 loss_db: 0.2203 2022/11/01 16:30:43 - mmengine - INFO - Epoch(train) [329][35/63] lr: 1.7678e-03 eta: 9:23:22 time: 0.6444 data_time: 0.0445 memory: 17620 loss: 1.8702 loss_prob: 1.0838 loss_thr: 0.6099 loss_db: 0.1765 2022/11/01 16:30:46 - mmengine - INFO - Epoch(train) [329][40/63] lr: 1.7678e-03 eta: 9:23:16 time: 0.6150 data_time: 0.0053 memory: 17620 loss: 1.6294 loss_prob: 0.9076 loss_thr: 0.5736 loss_db: 0.1482 2022/11/01 16:30:49 - mmengine - INFO - Epoch(train) [329][45/63] lr: 1.7678e-03 eta: 9:23:16 time: 0.5832 data_time: 0.0049 memory: 17620 loss: 1.7141 loss_prob: 0.9589 loss_thr: 0.5991 loss_db: 0.1561 2022/11/01 16:30:52 - mmengine - INFO - Epoch(train) [329][50/63] lr: 1.7678e-03 eta: 9:23:09 time: 0.5682 data_time: 0.0115 memory: 17620 loss: 2.0948 loss_prob: 1.2630 loss_thr: 0.6229 loss_db: 0.2089 2022/11/01 16:30:55 - mmengine - INFO - Epoch(train) [329][55/63] lr: 1.7678e-03 eta: 9:23:09 time: 0.5958 data_time: 0.0212 memory: 17620 loss: 2.1540 loss_prob: 1.3273 loss_thr: 0.6030 loss_db: 0.2237 2022/11/01 16:30:58 - mmengine - INFO - Epoch(train) [329][60/63] lr: 1.7678e-03 eta: 9:23:02 time: 0.5877 data_time: 0.0159 memory: 17620 loss: 1.9076 loss_prob: 1.1290 loss_thr: 0.5937 loss_db: 0.1849 2022/11/01 16:31:00 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:31:05 - mmengine - INFO - Epoch(train) [330][5/63] lr: 1.7660e-03 eta: 9:23:02 time: 0.8436 data_time: 0.2755 memory: 17620 loss: 1.8234 loss_prob: 1.0690 loss_thr: 0.5835 loss_db: 0.1710 2022/11/01 16:31:08 - mmengine - INFO - Epoch(train) [330][10/63] lr: 1.7660e-03 eta: 9:22:55 time: 0.8403 data_time: 0.2746 memory: 17620 loss: 1.9207 loss_prob: 1.1424 loss_thr: 0.5973 loss_db: 0.1810 2022/11/01 16:31:11 - mmengine - INFO - Epoch(train) [330][15/63] lr: 1.7660e-03 eta: 9:22:55 time: 0.5861 data_time: 0.0073 memory: 17620 loss: 1.9782 loss_prob: 1.1706 loss_thr: 0.6170 loss_db: 0.1907 2022/11/01 16:31:14 - mmengine - INFO - Epoch(train) [330][20/63] lr: 1.7660e-03 eta: 9:22:49 time: 0.6328 data_time: 0.0073 memory: 17620 loss: 1.8576 loss_prob: 1.0697 loss_thr: 0.6089 loss_db: 0.1790 2022/11/01 16:31:18 - mmengine - INFO - Epoch(train) [330][25/63] lr: 1.7660e-03 eta: 9:22:49 time: 0.6324 data_time: 0.0332 memory: 17620 loss: 1.7708 loss_prob: 1.0164 loss_thr: 0.5902 loss_db: 0.1641 2022/11/01 16:31:20 - mmengine - INFO - Epoch(train) [330][30/63] lr: 1.7660e-03 eta: 9:22:42 time: 0.6020 data_time: 0.0334 memory: 17620 loss: 1.8077 loss_prob: 1.0593 loss_thr: 0.5813 loss_db: 0.1671 2022/11/01 16:31:24 - mmengine - INFO - Epoch(train) [330][35/63] lr: 1.7660e-03 eta: 9:22:42 time: 0.6048 data_time: 0.0067 memory: 17620 loss: 1.8521 loss_prob: 1.0919 loss_thr: 0.5871 loss_db: 0.1730 2022/11/01 16:31:26 - mmengine - INFO - Epoch(train) [330][40/63] lr: 1.7660e-03 eta: 9:22:36 time: 0.5944 data_time: 0.0077 memory: 17620 loss: 1.8925 loss_prob: 1.1287 loss_thr: 0.5780 loss_db: 0.1858 2022/11/01 16:31:29 - mmengine - INFO - Epoch(train) [330][45/63] lr: 1.7660e-03 eta: 9:22:36 time: 0.5591 data_time: 0.0083 memory: 17620 loss: 1.8854 loss_prob: 1.1209 loss_thr: 0.5800 loss_db: 0.1846 2022/11/01 16:31:32 - mmengine - INFO - Epoch(train) [330][50/63] lr: 1.7660e-03 eta: 9:22:29 time: 0.5814 data_time: 0.0227 memory: 17620 loss: 1.8573 loss_prob: 1.0883 loss_thr: 0.5977 loss_db: 0.1713 2022/11/01 16:31:35 - mmengine - INFO - Epoch(train) [330][55/63] lr: 1.7660e-03 eta: 9:22:29 time: 0.6069 data_time: 0.0240 memory: 17620 loss: 1.9018 loss_prob: 1.1162 loss_thr: 0.6070 loss_db: 0.1785 2022/11/01 16:31:38 - mmengine - INFO - Epoch(train) [330][60/63] lr: 1.7660e-03 eta: 9:22:22 time: 0.5848 data_time: 0.0115 memory: 17620 loss: 2.1271 loss_prob: 1.2985 loss_thr: 0.6188 loss_db: 0.2097 2022/11/01 16:31:39 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:31:44 - mmengine - INFO - Epoch(train) [331][5/63] lr: 1.7642e-03 eta: 9:22:22 time: 0.7513 data_time: 0.2270 memory: 17620 loss: 2.2016 loss_prob: 1.3520 loss_thr: 0.6424 loss_db: 0.2072 2022/11/01 16:31:47 - mmengine - INFO - Epoch(train) [331][10/63] lr: 1.7642e-03 eta: 9:22:13 time: 0.7543 data_time: 0.2269 memory: 17620 loss: 2.1970 loss_prob: 1.3281 loss_thr: 0.6565 loss_db: 0.2123 2022/11/01 16:31:50 - mmengine - INFO - Epoch(train) [331][15/63] lr: 1.7642e-03 eta: 9:22:13 time: 0.5431 data_time: 0.0105 memory: 17620 loss: 1.9678 loss_prob: 1.1584 loss_thr: 0.6192 loss_db: 0.1901 2022/11/01 16:31:53 - mmengine - INFO - Epoch(train) [331][20/63] lr: 1.7642e-03 eta: 9:22:05 time: 0.5517 data_time: 0.0089 memory: 17620 loss: 1.9630 loss_prob: 1.1676 loss_thr: 0.6041 loss_db: 0.1912 2022/11/01 16:31:56 - mmengine - INFO - Epoch(train) [331][25/63] lr: 1.7642e-03 eta: 9:22:05 time: 0.5762 data_time: 0.0236 memory: 17620 loss: 1.9532 loss_prob: 1.1538 loss_thr: 0.6130 loss_db: 0.1863 2022/11/01 16:31:58 - mmengine - INFO - Epoch(train) [331][30/63] lr: 1.7642e-03 eta: 9:21:58 time: 0.5819 data_time: 0.0290 memory: 17620 loss: 1.8540 loss_prob: 1.0735 loss_thr: 0.6070 loss_db: 0.1734 2022/11/01 16:32:01 - mmengine - INFO - Epoch(train) [331][35/63] lr: 1.7642e-03 eta: 9:21:58 time: 0.5371 data_time: 0.0101 memory: 17620 loss: 1.6819 loss_prob: 0.9604 loss_thr: 0.5660 loss_db: 0.1555 2022/11/01 16:32:04 - mmengine - INFO - Epoch(train) [331][40/63] lr: 1.7642e-03 eta: 9:21:50 time: 0.5446 data_time: 0.0088 memory: 17620 loss: 1.5940 loss_prob: 0.9054 loss_thr: 0.5461 loss_db: 0.1425 2022/11/01 16:32:06 - mmengine - INFO - Epoch(train) [331][45/63] lr: 1.7642e-03 eta: 9:21:50 time: 0.5440 data_time: 0.0092 memory: 17620 loss: 1.8966 loss_prob: 1.1151 loss_thr: 0.6049 loss_db: 0.1766 2022/11/01 16:32:09 - mmengine - INFO - Epoch(train) [331][50/63] lr: 1.7642e-03 eta: 9:21:42 time: 0.5544 data_time: 0.0200 memory: 17620 loss: 1.9135 loss_prob: 1.1383 loss_thr: 0.5826 loss_db: 0.1926 2022/11/01 16:32:12 - mmengine - INFO - Epoch(train) [331][55/63] lr: 1.7642e-03 eta: 9:21:42 time: 0.5656 data_time: 0.0256 memory: 17620 loss: 1.8020 loss_prob: 1.0549 loss_thr: 0.5675 loss_db: 0.1797 2022/11/01 16:32:15 - mmengine - INFO - Epoch(train) [331][60/63] lr: 1.7642e-03 eta: 9:21:35 time: 0.5733 data_time: 0.0117 memory: 17620 loss: 1.8970 loss_prob: 1.1169 loss_thr: 0.6012 loss_db: 0.1790 2022/11/01 16:32:17 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:32:21 - mmengine - INFO - Epoch(train) [332][5/63] lr: 1.7623e-03 eta: 9:21:35 time: 0.7362 data_time: 0.1825 memory: 17620 loss: 1.9819 loss_prob: 1.1819 loss_thr: 0.6124 loss_db: 0.1875 2022/11/01 16:32:24 - mmengine - INFO - Epoch(train) [332][10/63] lr: 1.7623e-03 eta: 9:21:25 time: 0.7355 data_time: 0.1871 memory: 17620 loss: 1.9212 loss_prob: 1.1388 loss_thr: 0.5976 loss_db: 0.1848 2022/11/01 16:32:27 - mmengine - INFO - Epoch(train) [332][15/63] lr: 1.7623e-03 eta: 9:21:25 time: 0.5589 data_time: 0.0122 memory: 17620 loss: 1.6760 loss_prob: 0.9527 loss_thr: 0.5675 loss_db: 0.1558 2022/11/01 16:32:30 - mmengine - INFO - Epoch(train) [332][20/63] lr: 1.7623e-03 eta: 9:21:17 time: 0.5642 data_time: 0.0067 memory: 17620 loss: 1.7958 loss_prob: 1.0359 loss_thr: 0.5938 loss_db: 0.1660 2022/11/01 16:32:33 - mmengine - INFO - Epoch(train) [332][25/63] lr: 1.7623e-03 eta: 9:21:17 time: 0.6071 data_time: 0.0174 memory: 17620 loss: 1.8774 loss_prob: 1.0826 loss_thr: 0.6191 loss_db: 0.1757 2022/11/01 16:32:36 - mmengine - INFO - Epoch(train) [332][30/63] lr: 1.7623e-03 eta: 9:21:12 time: 0.6306 data_time: 0.0349 memory: 17620 loss: 1.8362 loss_prob: 1.0368 loss_thr: 0.6315 loss_db: 0.1680 2022/11/01 16:32:39 - mmengine - INFO - Epoch(train) [332][35/63] lr: 1.7623e-03 eta: 9:21:12 time: 0.5755 data_time: 0.0234 memory: 17620 loss: 1.8222 loss_prob: 1.0364 loss_thr: 0.6214 loss_db: 0.1644 2022/11/01 16:32:41 - mmengine - INFO - Epoch(train) [332][40/63] lr: 1.7623e-03 eta: 9:21:04 time: 0.5488 data_time: 0.0080 memory: 17620 loss: 1.8263 loss_prob: 1.0500 loss_thr: 0.6115 loss_db: 0.1648 2022/11/01 16:32:44 - mmengine - INFO - Epoch(train) [332][45/63] lr: 1.7623e-03 eta: 9:21:04 time: 0.5481 data_time: 0.0079 memory: 17620 loss: 1.9822 loss_prob: 1.1967 loss_thr: 0.6024 loss_db: 0.1831 2022/11/01 16:32:47 - mmengine - INFO - Epoch(train) [332][50/63] lr: 1.7623e-03 eta: 9:20:57 time: 0.5861 data_time: 0.0118 memory: 17620 loss: 1.9712 loss_prob: 1.1951 loss_thr: 0.5920 loss_db: 0.1840 2022/11/01 16:32:50 - mmengine - INFO - Epoch(train) [332][55/63] lr: 1.7623e-03 eta: 9:20:57 time: 0.6267 data_time: 0.0215 memory: 17620 loss: 1.7893 loss_prob: 1.0355 loss_thr: 0.5881 loss_db: 0.1656 2022/11/01 16:32:53 - mmengine - INFO - Epoch(train) [332][60/63] lr: 1.7623e-03 eta: 9:20:51 time: 0.6277 data_time: 0.0184 memory: 17620 loss: 1.7782 loss_prob: 1.0267 loss_thr: 0.5837 loss_db: 0.1678 2022/11/01 16:32:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:33:00 - mmengine - INFO - Epoch(train) [333][5/63] lr: 1.7605e-03 eta: 9:20:51 time: 0.7682 data_time: 0.2148 memory: 17620 loss: 1.9196 loss_prob: 1.1230 loss_thr: 0.6160 loss_db: 0.1806 2022/11/01 16:33:03 - mmengine - INFO - Epoch(train) [333][10/63] lr: 1.7605e-03 eta: 9:20:43 time: 0.7906 data_time: 0.2172 memory: 17620 loss: 1.8128 loss_prob: 1.0393 loss_thr: 0.6009 loss_db: 0.1725 2022/11/01 16:33:05 - mmengine - INFO - Epoch(train) [333][15/63] lr: 1.7605e-03 eta: 9:20:43 time: 0.5357 data_time: 0.0109 memory: 17620 loss: 1.6768 loss_prob: 0.9527 loss_thr: 0.5689 loss_db: 0.1552 2022/11/01 16:33:08 - mmengine - INFO - Epoch(train) [333][20/63] lr: 1.7605e-03 eta: 9:20:34 time: 0.5262 data_time: 0.0069 memory: 17620 loss: 1.7423 loss_prob: 0.9872 loss_thr: 0.5963 loss_db: 0.1588 2022/11/01 16:33:11 - mmengine - INFO - Epoch(train) [333][25/63] lr: 1.7605e-03 eta: 9:20:34 time: 0.5478 data_time: 0.0236 memory: 17620 loss: 1.8110 loss_prob: 1.0214 loss_thr: 0.6215 loss_db: 0.1681 2022/11/01 16:33:14 - mmengine - INFO - Epoch(train) [333][30/63] lr: 1.7605e-03 eta: 9:20:27 time: 0.5598 data_time: 0.0323 memory: 17620 loss: 1.7128 loss_prob: 0.9654 loss_thr: 0.5888 loss_db: 0.1586 2022/11/01 16:33:16 - mmengine - INFO - Epoch(train) [333][35/63] lr: 1.7605e-03 eta: 9:20:27 time: 0.5405 data_time: 0.0178 memory: 17620 loss: 1.7660 loss_prob: 1.0209 loss_thr: 0.5820 loss_db: 0.1631 2022/11/01 16:33:19 - mmengine - INFO - Epoch(train) [333][40/63] lr: 1.7605e-03 eta: 9:20:18 time: 0.5225 data_time: 0.0093 memory: 17620 loss: 2.1165 loss_prob: 1.2898 loss_thr: 0.6255 loss_db: 0.2012 2022/11/01 16:33:21 - mmengine - INFO - Epoch(train) [333][45/63] lr: 1.7605e-03 eta: 9:20:18 time: 0.5130 data_time: 0.0055 memory: 17620 loss: 2.0672 loss_prob: 1.2520 loss_thr: 0.6223 loss_db: 0.1930 2022/11/01 16:33:24 - mmengine - INFO - Epoch(train) [333][50/63] lr: 1.7605e-03 eta: 9:20:10 time: 0.5419 data_time: 0.0139 memory: 17620 loss: 1.9912 loss_prob: 1.1844 loss_thr: 0.6245 loss_db: 0.1823 2022/11/01 16:33:27 - mmengine - INFO - Epoch(train) [333][55/63] lr: 1.7605e-03 eta: 9:20:10 time: 0.5690 data_time: 0.0249 memory: 17620 loss: 2.0366 loss_prob: 1.2143 loss_thr: 0.6308 loss_db: 0.1915 2022/11/01 16:33:30 - mmengine - INFO - Epoch(train) [333][60/63] lr: 1.7605e-03 eta: 9:20:02 time: 0.5607 data_time: 0.0186 memory: 17620 loss: 2.0801 loss_prob: 1.2554 loss_thr: 0.6257 loss_db: 0.1990 2022/11/01 16:33:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:33:36 - mmengine - INFO - Epoch(train) [334][5/63] lr: 1.7587e-03 eta: 9:20:02 time: 0.7336 data_time: 0.1869 memory: 17620 loss: 2.0688 loss_prob: 1.2269 loss_thr: 0.6430 loss_db: 0.1990 2022/11/01 16:33:39 - mmengine - INFO - Epoch(train) [334][10/63] lr: 1.7587e-03 eta: 9:19:54 time: 0.7692 data_time: 0.1950 memory: 17620 loss: 1.9674 loss_prob: 1.1689 loss_thr: 0.6133 loss_db: 0.1852 2022/11/01 16:33:42 - mmengine - INFO - Epoch(train) [334][15/63] lr: 1.7587e-03 eta: 9:19:54 time: 0.5670 data_time: 0.0149 memory: 17620 loss: 1.7808 loss_prob: 1.0315 loss_thr: 0.5790 loss_db: 0.1703 2022/11/01 16:33:44 - mmengine - INFO - Epoch(train) [334][20/63] lr: 1.7587e-03 eta: 9:19:46 time: 0.5399 data_time: 0.0069 memory: 17620 loss: 1.7730 loss_prob: 1.0134 loss_thr: 0.5894 loss_db: 0.1702 2022/11/01 16:33:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:33:47 - mmengine - INFO - Epoch(train) [334][25/63] lr: 1.7587e-03 eta: 9:19:46 time: 0.5456 data_time: 0.0184 memory: 17620 loss: 1.8713 loss_prob: 1.0928 loss_thr: 0.6054 loss_db: 0.1732 2022/11/01 16:33:50 - mmengine - INFO - Epoch(train) [334][30/63] lr: 1.7587e-03 eta: 9:19:38 time: 0.5628 data_time: 0.0299 memory: 17620 loss: 1.9982 loss_prob: 1.1984 loss_thr: 0.6082 loss_db: 0.1916 2022/11/01 16:33:53 - mmengine - INFO - Epoch(train) [334][35/63] lr: 1.7587e-03 eta: 9:19:38 time: 0.5405 data_time: 0.0230 memory: 17620 loss: 1.8975 loss_prob: 1.1131 loss_thr: 0.6030 loss_db: 0.1813 2022/11/01 16:33:55 - mmengine - INFO - Epoch(train) [334][40/63] lr: 1.7587e-03 eta: 9:19:29 time: 0.5206 data_time: 0.0096 memory: 17620 loss: 1.8247 loss_prob: 1.0615 loss_thr: 0.5928 loss_db: 0.1705 2022/11/01 16:33:58 - mmengine - INFO - Epoch(train) [334][45/63] lr: 1.7587e-03 eta: 9:19:29 time: 0.5299 data_time: 0.0062 memory: 17620 loss: 1.8877 loss_prob: 1.1115 loss_thr: 0.5959 loss_db: 0.1803 2022/11/01 16:34:01 - mmengine - INFO - Epoch(train) [334][50/63] lr: 1.7587e-03 eta: 9:19:22 time: 0.5585 data_time: 0.0223 memory: 17620 loss: 1.9221 loss_prob: 1.1294 loss_thr: 0.6050 loss_db: 0.1877 2022/11/01 16:34:03 - mmengine - INFO - Epoch(train) [334][55/63] lr: 1.7587e-03 eta: 9:19:22 time: 0.5514 data_time: 0.0241 memory: 17620 loss: 1.9295 loss_prob: 1.1374 loss_thr: 0.6022 loss_db: 0.1899 2022/11/01 16:34:06 - mmengine - INFO - Epoch(train) [334][60/63] lr: 1.7587e-03 eta: 9:19:14 time: 0.5597 data_time: 0.0117 memory: 17620 loss: 1.9006 loss_prob: 1.1228 loss_thr: 0.5949 loss_db: 0.1829 2022/11/01 16:34:08 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:34:13 - mmengine - INFO - Epoch(train) [335][5/63] lr: 1.7569e-03 eta: 9:19:14 time: 0.7929 data_time: 0.2608 memory: 17620 loss: 1.7407 loss_prob: 1.0049 loss_thr: 0.5721 loss_db: 0.1637 2022/11/01 16:34:16 - mmengine - INFO - Epoch(train) [335][10/63] lr: 1.7569e-03 eta: 9:19:06 time: 0.8080 data_time: 0.2613 memory: 17620 loss: 1.7837 loss_prob: 1.0362 loss_thr: 0.5777 loss_db: 0.1698 2022/11/01 16:34:19 - mmengine - INFO - Epoch(train) [335][15/63] lr: 1.7569e-03 eta: 9:19:06 time: 0.5684 data_time: 0.0055 memory: 17620 loss: 1.8026 loss_prob: 1.0532 loss_thr: 0.5801 loss_db: 0.1693 2022/11/01 16:34:22 - mmengine - INFO - Epoch(train) [335][20/63] lr: 1.7569e-03 eta: 9:18:59 time: 0.5711 data_time: 0.0064 memory: 17620 loss: 1.8298 loss_prob: 1.0786 loss_thr: 0.5849 loss_db: 0.1662 2022/11/01 16:34:25 - mmengine - INFO - Epoch(train) [335][25/63] lr: 1.7569e-03 eta: 9:18:59 time: 0.5879 data_time: 0.0329 memory: 17620 loss: 1.8948 loss_prob: 1.1213 loss_thr: 0.5891 loss_db: 0.1844 2022/11/01 16:34:27 - mmengine - INFO - Epoch(train) [335][30/63] lr: 1.7569e-03 eta: 9:18:52 time: 0.5807 data_time: 0.0315 memory: 17620 loss: 1.9991 loss_prob: 1.1827 loss_thr: 0.6088 loss_db: 0.2076 2022/11/01 16:34:30 - mmengine - INFO - Epoch(train) [335][35/63] lr: 1.7569e-03 eta: 9:18:52 time: 0.5362 data_time: 0.0100 memory: 17620 loss: 1.9248 loss_prob: 1.1388 loss_thr: 0.5908 loss_db: 0.1952 2022/11/01 16:34:33 - mmengine - INFO - Epoch(train) [335][40/63] lr: 1.7569e-03 eta: 9:18:45 time: 0.5697 data_time: 0.0102 memory: 17620 loss: 1.8882 loss_prob: 1.1225 loss_thr: 0.5859 loss_db: 0.1798 2022/11/01 16:34:36 - mmengine - INFO - Epoch(train) [335][45/63] lr: 1.7569e-03 eta: 9:18:45 time: 0.6208 data_time: 0.0067 memory: 17620 loss: 1.8584 loss_prob: 1.0866 loss_thr: 0.5998 loss_db: 0.1720 2022/11/01 16:34:39 - mmengine - INFO - Epoch(train) [335][50/63] lr: 1.7569e-03 eta: 9:18:39 time: 0.6428 data_time: 0.0241 memory: 17620 loss: 1.7774 loss_prob: 1.0155 loss_thr: 0.5949 loss_db: 0.1670 2022/11/01 16:34:42 - mmengine - INFO - Epoch(train) [335][55/63] lr: 1.7569e-03 eta: 9:18:39 time: 0.6112 data_time: 0.0234 memory: 17620 loss: 1.7318 loss_prob: 0.9904 loss_thr: 0.5818 loss_db: 0.1596 2022/11/01 16:34:45 - mmengine - INFO - Epoch(train) [335][60/63] lr: 1.7569e-03 eta: 9:18:33 time: 0.5999 data_time: 0.0080 memory: 17620 loss: 1.7358 loss_prob: 0.9861 loss_thr: 0.5909 loss_db: 0.1588 2022/11/01 16:34:47 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:34:52 - mmengine - INFO - Epoch(train) [336][5/63] lr: 1.7550e-03 eta: 9:18:33 time: 0.7423 data_time: 0.1668 memory: 17620 loss: 1.8829 loss_prob: 1.1035 loss_thr: 0.6007 loss_db: 0.1787 2022/11/01 16:34:55 - mmengine - INFO - Epoch(train) [336][10/63] lr: 1.7550e-03 eta: 9:18:24 time: 0.7631 data_time: 0.1746 memory: 17620 loss: 1.8446 loss_prob: 1.0985 loss_thr: 0.5767 loss_db: 0.1693 2022/11/01 16:34:57 - mmengine - INFO - Epoch(train) [336][15/63] lr: 1.7550e-03 eta: 9:18:24 time: 0.5754 data_time: 0.0162 memory: 17620 loss: 1.7967 loss_prob: 1.0618 loss_thr: 0.5703 loss_db: 0.1646 2022/11/01 16:35:00 - mmengine - INFO - Epoch(train) [336][20/63] lr: 1.7550e-03 eta: 9:18:17 time: 0.5823 data_time: 0.0052 memory: 17620 loss: 1.8188 loss_prob: 1.0666 loss_thr: 0.5797 loss_db: 0.1725 2022/11/01 16:35:03 - mmengine - INFO - Epoch(train) [336][25/63] lr: 1.7550e-03 eta: 9:18:17 time: 0.5737 data_time: 0.0140 memory: 17620 loss: 1.7967 loss_prob: 1.0391 loss_thr: 0.5916 loss_db: 0.1661 2022/11/01 16:35:06 - mmengine - INFO - Epoch(train) [336][30/63] lr: 1.7550e-03 eta: 9:18:10 time: 0.5804 data_time: 0.0364 memory: 17620 loss: 1.7913 loss_prob: 1.0214 loss_thr: 0.6064 loss_db: 0.1634 2022/11/01 16:35:09 - mmengine - INFO - Epoch(train) [336][35/63] lr: 1.7550e-03 eta: 9:18:10 time: 0.6248 data_time: 0.0318 memory: 17620 loss: 1.8524 loss_prob: 1.0773 loss_thr: 0.6011 loss_db: 0.1740 2022/11/01 16:35:12 - mmengine - INFO - Epoch(train) [336][40/63] lr: 1.7550e-03 eta: 9:18:03 time: 0.6032 data_time: 0.0097 memory: 17620 loss: 1.8309 loss_prob: 1.0752 loss_thr: 0.5853 loss_db: 0.1704 2022/11/01 16:35:15 - mmengine - INFO - Epoch(train) [336][45/63] lr: 1.7550e-03 eta: 9:18:03 time: 0.5721 data_time: 0.0075 memory: 17620 loss: 1.9270 loss_prob: 1.1377 loss_thr: 0.6107 loss_db: 0.1785 2022/11/01 16:35:18 - mmengine - INFO - Epoch(train) [336][50/63] lr: 1.7550e-03 eta: 9:17:57 time: 0.6196 data_time: 0.0134 memory: 17620 loss: 1.8740 loss_prob: 1.0815 loss_thr: 0.6187 loss_db: 0.1738 2022/11/01 16:35:21 - mmengine - INFO - Epoch(train) [336][55/63] lr: 1.7550e-03 eta: 9:17:57 time: 0.6128 data_time: 0.0209 memory: 17620 loss: 1.7727 loss_prob: 1.0129 loss_thr: 0.5940 loss_db: 0.1658 2022/11/01 16:35:25 - mmengine - INFO - Epoch(train) [336][60/63] lr: 1.7550e-03 eta: 9:17:51 time: 0.6131 data_time: 0.0169 memory: 17620 loss: 1.8243 loss_prob: 1.0714 loss_thr: 0.5855 loss_db: 0.1674 2022/11/01 16:35:26 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:35:31 - mmengine - INFO - Epoch(train) [337][5/63] lr: 1.7532e-03 eta: 9:17:51 time: 0.8412 data_time: 0.2047 memory: 17620 loss: 1.7942 loss_prob: 1.0412 loss_thr: 0.5904 loss_db: 0.1626 2022/11/01 16:35:34 - mmengine - INFO - Epoch(train) [337][10/63] lr: 1.7532e-03 eta: 9:17:43 time: 0.7963 data_time: 0.2053 memory: 17620 loss: 1.8199 loss_prob: 1.0580 loss_thr: 0.5951 loss_db: 0.1668 2022/11/01 16:35:37 - mmengine - INFO - Epoch(train) [337][15/63] lr: 1.7532e-03 eta: 9:17:43 time: 0.5314 data_time: 0.0082 memory: 17620 loss: 1.8029 loss_prob: 1.0501 loss_thr: 0.5865 loss_db: 0.1663 2022/11/01 16:35:40 - mmengine - INFO - Epoch(train) [337][20/63] lr: 1.7532e-03 eta: 9:17:36 time: 0.5682 data_time: 0.0077 memory: 17620 loss: 1.6568 loss_prob: 0.9447 loss_thr: 0.5581 loss_db: 0.1539 2022/11/01 16:35:43 - mmengine - INFO - Epoch(train) [337][25/63] lr: 1.7532e-03 eta: 9:17:36 time: 0.5760 data_time: 0.0076 memory: 17620 loss: 1.7613 loss_prob: 1.0107 loss_thr: 0.5843 loss_db: 0.1664 2022/11/01 16:35:46 - mmengine - INFO - Epoch(train) [337][30/63] lr: 1.7532e-03 eta: 9:17:29 time: 0.5888 data_time: 0.0314 memory: 17620 loss: 1.8348 loss_prob: 1.0613 loss_thr: 0.6000 loss_db: 0.1735 2022/11/01 16:35:48 - mmengine - INFO - Epoch(train) [337][35/63] lr: 1.7532e-03 eta: 9:17:29 time: 0.5799 data_time: 0.0292 memory: 17620 loss: 1.7997 loss_prob: 1.0500 loss_thr: 0.5853 loss_db: 0.1644 2022/11/01 16:35:51 - mmengine - INFO - Epoch(train) [337][40/63] lr: 1.7532e-03 eta: 9:17:21 time: 0.5421 data_time: 0.0076 memory: 17620 loss: 1.7985 loss_prob: 1.0507 loss_thr: 0.5835 loss_db: 0.1644 2022/11/01 16:35:54 - mmengine - INFO - Epoch(train) [337][45/63] lr: 1.7532e-03 eta: 9:17:21 time: 0.5336 data_time: 0.0073 memory: 17620 loss: 1.8136 loss_prob: 1.0344 loss_thr: 0.6115 loss_db: 0.1677 2022/11/01 16:35:56 - mmengine - INFO - Epoch(train) [337][50/63] lr: 1.7532e-03 eta: 9:17:13 time: 0.5374 data_time: 0.0130 memory: 17620 loss: 1.9210 loss_prob: 1.1114 loss_thr: 0.6306 loss_db: 0.1791 2022/11/01 16:35:59 - mmengine - INFO - Epoch(train) [337][55/63] lr: 1.7532e-03 eta: 9:17:13 time: 0.5769 data_time: 0.0251 memory: 17620 loss: 1.9743 loss_prob: 1.1708 loss_thr: 0.6157 loss_db: 0.1877 2022/11/01 16:36:02 - mmengine - INFO - Epoch(train) [337][60/63] lr: 1.7532e-03 eta: 9:17:06 time: 0.5870 data_time: 0.0171 memory: 17620 loss: 1.9577 loss_prob: 1.1598 loss_thr: 0.6110 loss_db: 0.1869 2022/11/01 16:36:04 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:36:08 - mmengine - INFO - Epoch(train) [338][5/63] lr: 1.7514e-03 eta: 9:17:06 time: 0.7137 data_time: 0.1817 memory: 17620 loss: 1.8109 loss_prob: 1.0594 loss_thr: 0.5847 loss_db: 0.1669 2022/11/01 16:36:11 - mmengine - INFO - Epoch(train) [338][10/63] lr: 1.7514e-03 eta: 9:16:57 time: 0.7470 data_time: 0.1872 memory: 17620 loss: 1.6513 loss_prob: 0.9330 loss_thr: 0.5683 loss_db: 0.1501 2022/11/01 16:36:14 - mmengine - INFO - Epoch(train) [338][15/63] lr: 1.7514e-03 eta: 9:16:57 time: 0.5449 data_time: 0.0119 memory: 17620 loss: 1.7300 loss_prob: 1.0066 loss_thr: 0.5636 loss_db: 0.1598 2022/11/01 16:36:16 - mmengine - INFO - Epoch(train) [338][20/63] lr: 1.7514e-03 eta: 9:16:48 time: 0.5207 data_time: 0.0046 memory: 17620 loss: 1.7716 loss_prob: 1.0298 loss_thr: 0.5782 loss_db: 0.1636 2022/11/01 16:36:19 - mmengine - INFO - Epoch(train) [338][25/63] lr: 1.7514e-03 eta: 9:16:48 time: 0.5341 data_time: 0.0116 memory: 17620 loss: 1.9706 loss_prob: 1.1886 loss_thr: 0.5952 loss_db: 0.1868 2022/11/01 16:36:22 - mmengine - INFO - Epoch(train) [338][30/63] lr: 1.7514e-03 eta: 9:16:41 time: 0.5592 data_time: 0.0315 memory: 17620 loss: 2.2891 loss_prob: 1.4267 loss_thr: 0.6444 loss_db: 0.2180 2022/11/01 16:36:25 - mmengine - INFO - Epoch(train) [338][35/63] lr: 1.7514e-03 eta: 9:16:41 time: 0.5975 data_time: 0.0249 memory: 17620 loss: 2.0243 loss_prob: 1.2036 loss_thr: 0.6341 loss_db: 0.1866 2022/11/01 16:36:28 - mmengine - INFO - Epoch(train) [338][40/63] lr: 1.7514e-03 eta: 9:16:34 time: 0.5949 data_time: 0.0062 memory: 17620 loss: 1.7260 loss_prob: 0.9814 loss_thr: 0.5853 loss_db: 0.1593 2022/11/01 16:36:31 - mmengine - INFO - Epoch(train) [338][45/63] lr: 1.7514e-03 eta: 9:16:34 time: 0.5757 data_time: 0.0063 memory: 17620 loss: 1.6191 loss_prob: 0.9173 loss_thr: 0.5531 loss_db: 0.1487 2022/11/01 16:36:34 - mmengine - INFO - Epoch(train) [338][50/63] lr: 1.7514e-03 eta: 9:16:27 time: 0.5738 data_time: 0.0122 memory: 17620 loss: 1.6383 loss_prob: 0.9342 loss_thr: 0.5533 loss_db: 0.1509 2022/11/01 16:36:37 - mmengine - INFO - Epoch(train) [338][55/63] lr: 1.7514e-03 eta: 9:16:27 time: 0.5695 data_time: 0.0228 memory: 17620 loss: 1.6512 loss_prob: 0.9301 loss_thr: 0.5688 loss_db: 0.1523 2022/11/01 16:36:39 - mmengine - INFO - Epoch(train) [338][60/63] lr: 1.7514e-03 eta: 9:16:19 time: 0.5700 data_time: 0.0196 memory: 17620 loss: 1.7198 loss_prob: 0.9906 loss_thr: 0.5728 loss_db: 0.1565 2022/11/01 16:36:41 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:36:46 - mmengine - INFO - Epoch(train) [339][5/63] lr: 1.7496e-03 eta: 9:16:19 time: 0.7589 data_time: 0.2234 memory: 17620 loss: 1.6283 loss_prob: 0.9283 loss_thr: 0.5534 loss_db: 0.1466 2022/11/01 16:36:49 - mmengine - INFO - Epoch(train) [339][10/63] lr: 1.7496e-03 eta: 9:16:11 time: 0.7712 data_time: 0.2211 memory: 17620 loss: 1.7322 loss_prob: 1.0033 loss_thr: 0.5678 loss_db: 0.1611 2022/11/01 16:36:51 - mmengine - INFO - Epoch(train) [339][15/63] lr: 1.7496e-03 eta: 9:16:11 time: 0.5533 data_time: 0.0062 memory: 17620 loss: 1.8936 loss_prob: 1.1115 loss_thr: 0.6046 loss_db: 0.1775 2022/11/01 16:36:54 - mmengine - INFO - Epoch(train) [339][20/63] lr: 1.7496e-03 eta: 9:16:03 time: 0.5683 data_time: 0.0073 memory: 17620 loss: 1.8059 loss_prob: 1.0439 loss_thr: 0.5952 loss_db: 0.1667 2022/11/01 16:36:57 - mmengine - INFO - Epoch(train) [339][25/63] lr: 1.7496e-03 eta: 9:16:03 time: 0.5781 data_time: 0.0206 memory: 17620 loss: 1.7096 loss_prob: 0.9781 loss_thr: 0.5753 loss_db: 0.1562 2022/11/01 16:37:00 - mmengine - INFO - Epoch(train) [339][30/63] lr: 1.7496e-03 eta: 9:15:56 time: 0.5772 data_time: 0.0350 memory: 17620 loss: 1.8407 loss_prob: 1.0684 loss_thr: 0.6033 loss_db: 0.1690 2022/11/01 16:37:04 - mmengine - INFO - Epoch(train) [339][35/63] lr: 1.7496e-03 eta: 9:15:56 time: 0.6586 data_time: 0.0214 memory: 17620 loss: 1.8726 loss_prob: 1.0982 loss_thr: 0.5995 loss_db: 0.1749 2022/11/01 16:37:07 - mmengine - INFO - Epoch(train) [339][40/63] lr: 1.7496e-03 eta: 9:15:53 time: 0.7169 data_time: 0.0058 memory: 17620 loss: 1.6923 loss_prob: 0.9627 loss_thr: 0.5755 loss_db: 0.1541 2022/11/01 16:37:10 - mmengine - INFO - Epoch(train) [339][45/63] lr: 1.7496e-03 eta: 9:15:53 time: 0.6428 data_time: 0.0055 memory: 17620 loss: 1.7233 loss_prob: 0.9862 loss_thr: 0.5837 loss_db: 0.1534 2022/11/01 16:37:13 - mmengine - INFO - Epoch(train) [339][50/63] lr: 1.7496e-03 eta: 9:15:46 time: 0.6019 data_time: 0.0179 memory: 17620 loss: 1.9293 loss_prob: 1.1116 loss_thr: 0.6419 loss_db: 0.1758 2022/11/01 16:37:16 - mmengine - INFO - Epoch(train) [339][55/63] lr: 1.7496e-03 eta: 9:15:46 time: 0.6176 data_time: 0.0209 memory: 17620 loss: 1.8565 loss_prob: 1.0566 loss_thr: 0.6282 loss_db: 0.1717 2022/11/01 16:37:19 - mmengine - INFO - Epoch(train) [339][60/63] lr: 1.7496e-03 eta: 9:15:40 time: 0.6030 data_time: 0.0083 memory: 17620 loss: 1.7863 loss_prob: 1.0457 loss_thr: 0.5721 loss_db: 0.1686 2022/11/01 16:37:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:37:25 - mmengine - INFO - Epoch(train) [340][5/63] lr: 1.7477e-03 eta: 9:15:40 time: 0.7174 data_time: 0.2030 memory: 17620 loss: 1.7717 loss_prob: 1.0334 loss_thr: 0.5735 loss_db: 0.1649 2022/11/01 16:37:28 - mmengine - INFO - Epoch(train) [340][10/63] lr: 1.7477e-03 eta: 9:15:31 time: 0.7608 data_time: 0.2066 memory: 17620 loss: 1.8723 loss_prob: 1.0861 loss_thr: 0.6039 loss_db: 0.1823 2022/11/01 16:37:31 - mmengine - INFO - Epoch(train) [340][15/63] lr: 1.7477e-03 eta: 9:15:31 time: 0.5647 data_time: 0.0098 memory: 17620 loss: 1.9194 loss_prob: 1.1140 loss_thr: 0.6167 loss_db: 0.1887 2022/11/01 16:37:34 - mmengine - INFO - Epoch(train) [340][20/63] lr: 1.7477e-03 eta: 9:15:23 time: 0.5587 data_time: 0.0076 memory: 17620 loss: 1.9242 loss_prob: 1.1411 loss_thr: 0.6000 loss_db: 0.1832 2022/11/01 16:37:37 - mmengine - INFO - Epoch(train) [340][25/63] lr: 1.7477e-03 eta: 9:15:23 time: 0.5657 data_time: 0.0290 memory: 17620 loss: 1.9815 loss_prob: 1.2015 loss_thr: 0.5959 loss_db: 0.1840 2022/11/01 16:37:40 - mmengine - INFO - Epoch(train) [340][30/63] lr: 1.7477e-03 eta: 9:15:17 time: 0.6068 data_time: 0.0510 memory: 17620 loss: 1.8676 loss_prob: 1.1029 loss_thr: 0.5861 loss_db: 0.1787 2022/11/01 16:37:43 - mmengine - INFO - Epoch(train) [340][35/63] lr: 1.7477e-03 eta: 9:15:17 time: 0.6350 data_time: 0.0347 memory: 17620 loss: 2.0038 loss_prob: 1.1911 loss_thr: 0.6100 loss_db: 0.2027 2022/11/01 16:37:46 - mmengine - INFO - Epoch(train) [340][40/63] lr: 1.7477e-03 eta: 9:15:12 time: 0.6603 data_time: 0.0104 memory: 17620 loss: 2.0600 loss_prob: 1.2354 loss_thr: 0.6253 loss_db: 0.1993 2022/11/01 16:37:49 - mmengine - INFO - Epoch(train) [340][45/63] lr: 1.7477e-03 eta: 9:15:12 time: 0.6252 data_time: 0.0074 memory: 17620 loss: 1.8752 loss_prob: 1.0932 loss_thr: 0.6098 loss_db: 0.1722 2022/11/01 16:37:52 - mmengine - INFO - Epoch(train) [340][50/63] lr: 1.7477e-03 eta: 9:15:05 time: 0.5864 data_time: 0.0223 memory: 17620 loss: 1.8354 loss_prob: 1.0601 loss_thr: 0.6014 loss_db: 0.1739 2022/11/01 16:37:55 - mmengine - INFO - Epoch(train) [340][55/63] lr: 1.7477e-03 eta: 9:15:05 time: 0.6051 data_time: 0.0239 memory: 17620 loss: 1.9257 loss_prob: 1.1260 loss_thr: 0.6166 loss_db: 0.1831 2022/11/01 16:37:58 - mmengine - INFO - Epoch(train) [340][60/63] lr: 1.7477e-03 eta: 9:14:58 time: 0.5892 data_time: 0.0123 memory: 17620 loss: 1.9139 loss_prob: 1.1277 loss_thr: 0.6032 loss_db: 0.1830 2022/11/01 16:37:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:37:59 - mmengine - INFO - Saving checkpoint at 340 epochs 2022/11/01 16:38:06 - mmengine - INFO - Epoch(val) [340][5/32] eta: 9:14:58 time: 0.5640 data_time: 0.0793 memory: 17620 2022/11/01 16:38:09 - mmengine - INFO - Epoch(val) [340][10/32] eta: 0:00:13 time: 0.6223 data_time: 0.0973 memory: 15725 2022/11/01 16:38:12 - mmengine - INFO - Epoch(val) [340][15/32] eta: 0:00:13 time: 0.5738 data_time: 0.0462 memory: 15725 2022/11/01 16:38:15 - mmengine - INFO - Epoch(val) [340][20/32] eta: 0:00:07 time: 0.5961 data_time: 0.0614 memory: 15725 2022/11/01 16:38:18 - mmengine - INFO - Epoch(val) [340][25/32] eta: 0:00:07 time: 0.6114 data_time: 0.0552 memory: 15725 2022/11/01 16:38:21 - mmengine - INFO - Epoch(val) [340][30/32] eta: 0:00:01 time: 0.5627 data_time: 0.0234 memory: 15725 2022/11/01 16:38:22 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8300, precision: 0.7710, hmean: 0.7994 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8296, precision: 0.8459, hmean: 0.8376 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8257, precision: 0.8781, hmean: 0.8511 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8098, precision: 0.9097, hmean: 0.8569 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.7660, precision: 0.9370, hmean: 0.8429 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.4940, precision: 0.9707, hmean: 0.6548 2022/11/01 16:38:22 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0000, precision: 0.0000, hmean: 0.0000 2022/11/01 16:38:22 - mmengine - INFO - Epoch(val) [340][32/32] icdar/precision: 0.9097 icdar/recall: 0.8098 icdar/hmean: 0.8569 2022/11/01 16:38:27 - mmengine - INFO - Epoch(train) [341][5/63] lr: 1.7459e-03 eta: 0:00:01 time: 0.7704 data_time: 0.2113 memory: 17620 loss: 1.8218 loss_prob: 1.0401 loss_thr: 0.6106 loss_db: 0.1711 2022/11/01 16:38:30 - mmengine - INFO - Epoch(train) [341][10/63] lr: 1.7459e-03 eta: 9:14:51 time: 0.8180 data_time: 0.2099 memory: 17620 loss: 1.7323 loss_prob: 0.9784 loss_thr: 0.5926 loss_db: 0.1614 2022/11/01 16:38:32 - mmengine - INFO - Epoch(train) [341][15/63] lr: 1.7459e-03 eta: 9:14:51 time: 0.5472 data_time: 0.0054 memory: 17620 loss: 1.7605 loss_prob: 1.0203 loss_thr: 0.5780 loss_db: 0.1622 2022/11/01 16:38:35 - mmengine - INFO - Epoch(train) [341][20/63] lr: 1.7459e-03 eta: 9:14:42 time: 0.5259 data_time: 0.0058 memory: 17620 loss: 1.7537 loss_prob: 1.0192 loss_thr: 0.5734 loss_db: 0.1612 2022/11/01 16:38:38 - mmengine - INFO - Epoch(train) [341][25/63] lr: 1.7459e-03 eta: 9:14:42 time: 0.5525 data_time: 0.0208 memory: 17620 loss: 1.6871 loss_prob: 0.9623 loss_thr: 0.5679 loss_db: 0.1569 2022/11/01 16:38:41 - mmengine - INFO - Epoch(train) [341][30/63] lr: 1.7459e-03 eta: 9:14:35 time: 0.5652 data_time: 0.0324 memory: 17620 loss: 1.7490 loss_prob: 1.0148 loss_thr: 0.5702 loss_db: 0.1640 2022/11/01 16:38:43 - mmengine - INFO - Epoch(train) [341][35/63] lr: 1.7459e-03 eta: 9:14:35 time: 0.5385 data_time: 0.0172 memory: 17620 loss: 1.7543 loss_prob: 1.0065 loss_thr: 0.5842 loss_db: 0.1637 2022/11/01 16:38:46 - mmengine - INFO - Epoch(train) [341][40/63] lr: 1.7459e-03 eta: 9:14:27 time: 0.5429 data_time: 0.0048 memory: 17620 loss: 1.7042 loss_prob: 0.9513 loss_thr: 0.5962 loss_db: 0.1568 2022/11/01 16:38:49 - mmengine - INFO - Epoch(train) [341][45/63] lr: 1.7459e-03 eta: 9:14:27 time: 0.5577 data_time: 0.0054 memory: 17620 loss: 1.7214 loss_prob: 0.9741 loss_thr: 0.5923 loss_db: 0.1549 2022/11/01 16:38:52 - mmengine - INFO - Epoch(train) [341][50/63] lr: 1.7459e-03 eta: 9:14:20 time: 0.5932 data_time: 0.0160 memory: 17620 loss: 1.6910 loss_prob: 0.9600 loss_thr: 0.5809 loss_db: 0.1501 2022/11/01 16:38:55 - mmengine - INFO - Epoch(train) [341][55/63] lr: 1.7459e-03 eta: 9:14:20 time: 0.5890 data_time: 0.0228 memory: 17620 loss: 1.8332 loss_prob: 1.0716 loss_thr: 0.5932 loss_db: 0.1685 2022/11/01 16:38:58 - mmengine - INFO - Epoch(train) [341][60/63] lr: 1.7459e-03 eta: 9:14:13 time: 0.5524 data_time: 0.0121 memory: 17620 loss: 1.9746 loss_prob: 1.1848 loss_thr: 0.6025 loss_db: 0.1872 2022/11/01 16:38:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:39:04 - mmengine - INFO - Epoch(train) [342][5/63] lr: 1.7441e-03 eta: 9:14:13 time: 0.7053 data_time: 0.1727 memory: 17620 loss: 1.7392 loss_prob: 1.0056 loss_thr: 0.5747 loss_db: 0.1589 2022/11/01 16:39:06 - mmengine - INFO - Epoch(train) [342][10/63] lr: 1.7441e-03 eta: 9:14:03 time: 0.7250 data_time: 0.1821 memory: 17620 loss: 1.6494 loss_prob: 0.9342 loss_thr: 0.5661 loss_db: 0.1491 2022/11/01 16:39:09 - mmengine - INFO - Epoch(train) [342][15/63] lr: 1.7441e-03 eta: 9:14:03 time: 0.5360 data_time: 0.0146 memory: 17620 loss: 1.6969 loss_prob: 0.9738 loss_thr: 0.5702 loss_db: 0.1529 2022/11/01 16:39:12 - mmengine - INFO - Epoch(train) [342][20/63] lr: 1.7441e-03 eta: 9:13:55 time: 0.5421 data_time: 0.0056 memory: 17620 loss: 1.7831 loss_prob: 1.0316 loss_thr: 0.5909 loss_db: 0.1605 2022/11/01 16:39:14 - mmengine - INFO - Epoch(train) [342][25/63] lr: 1.7441e-03 eta: 9:13:55 time: 0.5460 data_time: 0.0183 memory: 17620 loss: 1.8187 loss_prob: 1.0630 loss_thr: 0.5844 loss_db: 0.1712 2022/11/01 16:39:17 - mmengine - INFO - Epoch(train) [342][30/63] lr: 1.7441e-03 eta: 9:13:48 time: 0.5643 data_time: 0.0237 memory: 17620 loss: 1.8084 loss_prob: 1.0698 loss_thr: 0.5648 loss_db: 0.1738 2022/11/01 16:39:20 - mmengine - INFO - Epoch(train) [342][35/63] lr: 1.7441e-03 eta: 9:13:48 time: 0.5851 data_time: 0.0217 memory: 17620 loss: 1.7489 loss_prob: 1.0248 loss_thr: 0.5586 loss_db: 0.1655 2022/11/01 16:39:23 - mmengine - INFO - Epoch(train) [342][40/63] lr: 1.7441e-03 eta: 9:13:40 time: 0.5758 data_time: 0.0165 memory: 17620 loss: 1.7327 loss_prob: 1.0026 loss_thr: 0.5642 loss_db: 0.1660 2022/11/01 16:39:26 - mmengine - INFO - Epoch(train) [342][45/63] lr: 1.7441e-03 eta: 9:13:40 time: 0.5797 data_time: 0.0081 memory: 17620 loss: 1.8652 loss_prob: 1.0733 loss_thr: 0.6178 loss_db: 0.1740 2022/11/01 16:39:29 - mmengine - INFO - Epoch(train) [342][50/63] lr: 1.7441e-03 eta: 9:13:33 time: 0.5787 data_time: 0.0205 memory: 17620 loss: 1.8923 loss_prob: 1.0884 loss_thr: 0.6306 loss_db: 0.1734 2022/11/01 16:39:32 - mmengine - INFO - Epoch(train) [342][55/63] lr: 1.7441e-03 eta: 9:13:33 time: 0.5742 data_time: 0.0249 memory: 17620 loss: 1.7638 loss_prob: 1.0260 loss_thr: 0.5740 loss_db: 0.1638 2022/11/01 16:39:35 - mmengine - INFO - Epoch(train) [342][60/63] lr: 1.7441e-03 eta: 9:13:26 time: 0.5686 data_time: 0.0145 memory: 17620 loss: 1.7289 loss_prob: 1.0003 loss_thr: 0.5695 loss_db: 0.1590 2022/11/01 16:39:36 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:39:42 - mmengine - INFO - Epoch(train) [343][5/63] lr: 1.7422e-03 eta: 9:13:26 time: 0.8481 data_time: 0.2509 memory: 17620 loss: 1.6752 loss_prob: 0.9517 loss_thr: 0.5716 loss_db: 0.1519 2022/11/01 16:39:45 - mmengine - INFO - Epoch(train) [343][10/63] lr: 1.7422e-03 eta: 9:13:20 time: 0.8833 data_time: 0.2520 memory: 17620 loss: 1.7664 loss_prob: 1.0126 loss_thr: 0.5871 loss_db: 0.1666 2022/11/01 16:39:47 - mmengine - INFO - Epoch(train) [343][15/63] lr: 1.7422e-03 eta: 9:13:20 time: 0.5492 data_time: 0.0072 memory: 17620 loss: 1.7620 loss_prob: 1.0141 loss_thr: 0.5809 loss_db: 0.1670 2022/11/01 16:39:50 - mmengine - INFO - Epoch(train) [343][20/63] lr: 1.7422e-03 eta: 9:13:13 time: 0.5572 data_time: 0.0051 memory: 17620 loss: 1.7428 loss_prob: 1.0061 loss_thr: 0.5758 loss_db: 0.1610 2022/11/01 16:39:53 - mmengine - INFO - Epoch(train) [343][25/63] lr: 1.7422e-03 eta: 9:13:13 time: 0.5883 data_time: 0.0171 memory: 17620 loss: 1.8057 loss_prob: 1.0609 loss_thr: 0.5760 loss_db: 0.1688 2022/11/01 16:39:57 - mmengine - INFO - Epoch(train) [343][30/63] lr: 1.7422e-03 eta: 9:13:07 time: 0.6299 data_time: 0.0346 memory: 17620 loss: 1.8074 loss_prob: 1.0578 loss_thr: 0.5809 loss_db: 0.1687 2022/11/01 16:39:59 - mmengine - INFO - Epoch(train) [343][35/63] lr: 1.7422e-03 eta: 9:13:07 time: 0.6131 data_time: 0.0255 memory: 17620 loss: 1.7738 loss_prob: 1.0268 loss_thr: 0.5846 loss_db: 0.1624 2022/11/01 16:40:02 - mmengine - INFO - Epoch(train) [343][40/63] lr: 1.7422e-03 eta: 9:13:00 time: 0.5783 data_time: 0.0085 memory: 17620 loss: 1.8870 loss_prob: 1.1065 loss_thr: 0.6042 loss_db: 0.1763 2022/11/01 16:40:05 - mmengine - INFO - Epoch(train) [343][45/63] lr: 1.7422e-03 eta: 9:13:00 time: 0.5708 data_time: 0.0061 memory: 17620 loss: 1.8669 loss_prob: 1.0496 loss_thr: 0.6466 loss_db: 0.1708 2022/11/01 16:40:08 - mmengine - INFO - Epoch(train) [343][50/63] lr: 1.7422e-03 eta: 9:12:53 time: 0.5888 data_time: 0.0120 memory: 17620 loss: 1.7427 loss_prob: 0.9646 loss_thr: 0.6208 loss_db: 0.1573 2022/11/01 16:40:11 - mmengine - INFO - Epoch(train) [343][55/63] lr: 1.7422e-03 eta: 9:12:53 time: 0.5870 data_time: 0.0214 memory: 17620 loss: 1.7072 loss_prob: 0.9687 loss_thr: 0.5831 loss_db: 0.1554 2022/11/01 16:40:14 - mmengine - INFO - Epoch(train) [343][60/63] lr: 1.7422e-03 eta: 9:12:46 time: 0.5871 data_time: 0.0148 memory: 17620 loss: 1.6768 loss_prob: 0.9474 loss_thr: 0.5782 loss_db: 0.1513 2022/11/01 16:40:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:40:21 - mmengine - INFO - Epoch(train) [344][5/63] lr: 1.7404e-03 eta: 9:12:46 time: 0.8169 data_time: 0.1997 memory: 17620 loss: 1.8038 loss_prob: 1.0360 loss_thr: 0.5983 loss_db: 0.1695 2022/11/01 16:40:24 - mmengine - INFO - Epoch(train) [344][10/63] lr: 1.7404e-03 eta: 9:12:39 time: 0.8402 data_time: 0.2008 memory: 17620 loss: 1.7645 loss_prob: 1.0088 loss_thr: 0.5913 loss_db: 0.1645 2022/11/01 16:40:27 - mmengine - INFO - Epoch(train) [344][15/63] lr: 1.7404e-03 eta: 9:12:39 time: 0.5611 data_time: 0.0066 memory: 17620 loss: 1.6905 loss_prob: 0.9640 loss_thr: 0.5685 loss_db: 0.1580 2022/11/01 16:40:29 - mmengine - INFO - Epoch(train) [344][20/63] lr: 1.7404e-03 eta: 9:12:31 time: 0.5466 data_time: 0.0057 memory: 17620 loss: 1.8166 loss_prob: 1.0655 loss_thr: 0.5811 loss_db: 0.1700 2022/11/01 16:40:32 - mmengine - INFO - Epoch(train) [344][25/63] lr: 1.7404e-03 eta: 9:12:31 time: 0.5677 data_time: 0.0113 memory: 17620 loss: 1.8847 loss_prob: 1.1110 loss_thr: 0.5988 loss_db: 0.1749 2022/11/01 16:40:35 - mmengine - INFO - Epoch(train) [344][30/63] lr: 1.7404e-03 eta: 9:12:25 time: 0.5966 data_time: 0.0353 memory: 17620 loss: 1.8747 loss_prob: 1.1021 loss_thr: 0.5927 loss_db: 0.1799 2022/11/01 16:40:38 - mmengine - INFO - Epoch(train) [344][35/63] lr: 1.7404e-03 eta: 9:12:25 time: 0.5783 data_time: 0.0294 memory: 17620 loss: 1.8123 loss_prob: 1.0642 loss_thr: 0.5738 loss_db: 0.1743 2022/11/01 16:40:41 - mmengine - INFO - Epoch(train) [344][40/63] lr: 1.7404e-03 eta: 9:12:18 time: 0.5688 data_time: 0.0074 memory: 17620 loss: 1.7265 loss_prob: 0.9852 loss_thr: 0.5799 loss_db: 0.1613 2022/11/01 16:40:44 - mmengine - INFO - Epoch(train) [344][45/63] lr: 1.7404e-03 eta: 9:12:18 time: 0.5620 data_time: 0.0129 memory: 17620 loss: 1.9155 loss_prob: 1.1254 loss_thr: 0.6138 loss_db: 0.1763 2022/11/01 16:40:47 - mmengine - INFO - Epoch(train) [344][50/63] lr: 1.7404e-03 eta: 9:12:10 time: 0.5702 data_time: 0.0204 memory: 17620 loss: 1.8082 loss_prob: 1.0669 loss_thr: 0.5786 loss_db: 0.1627 2022/11/01 16:40:50 - mmengine - INFO - Epoch(train) [344][55/63] lr: 1.7404e-03 eta: 9:12:10 time: 0.5809 data_time: 0.0222 memory: 17620 loss: 1.5940 loss_prob: 0.8911 loss_thr: 0.5594 loss_db: 0.1435 2022/11/01 16:40:52 - mmengine - INFO - Epoch(train) [344][60/63] lr: 1.7404e-03 eta: 9:12:03 time: 0.5537 data_time: 0.0125 memory: 17620 loss: 1.6865 loss_prob: 0.9385 loss_thr: 0.5938 loss_db: 0.1542 2022/11/01 16:40:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:40:59 - mmengine - INFO - Epoch(train) [345][5/63] lr: 1.7386e-03 eta: 9:12:03 time: 0.7643 data_time: 0.2229 memory: 17620 loss: 1.9532 loss_prob: 1.1508 loss_thr: 0.6204 loss_db: 0.1821 2022/11/01 16:41:01 - mmengine - INFO - Epoch(train) [345][10/63] lr: 1.7386e-03 eta: 9:11:55 time: 0.7906 data_time: 0.2256 memory: 17620 loss: 1.9587 loss_prob: 1.1616 loss_thr: 0.6084 loss_db: 0.1886 2022/11/01 16:41:04 - mmengine - INFO - Epoch(train) [345][15/63] lr: 1.7386e-03 eta: 9:11:55 time: 0.5321 data_time: 0.0085 memory: 17620 loss: 1.7860 loss_prob: 1.0367 loss_thr: 0.5730 loss_db: 0.1764 2022/11/01 16:41:07 - mmengine - INFO - Epoch(train) [345][20/63] lr: 1.7386e-03 eta: 9:11:47 time: 0.5466 data_time: 0.0057 memory: 17620 loss: 1.8050 loss_prob: 1.0463 loss_thr: 0.5864 loss_db: 0.1723 2022/11/01 16:41:10 - mmengine - INFO - Epoch(train) [345][25/63] lr: 1.7386e-03 eta: 9:11:47 time: 0.5647 data_time: 0.0192 memory: 17620 loss: 1.8052 loss_prob: 1.0546 loss_thr: 0.5816 loss_db: 0.1690 2022/11/01 16:41:13 - mmengine - INFO - Epoch(train) [345][30/63] lr: 1.7386e-03 eta: 9:11:39 time: 0.5634 data_time: 0.0348 memory: 17620 loss: 1.7156 loss_prob: 0.9728 loss_thr: 0.5869 loss_db: 0.1559 2022/11/01 16:41:15 - mmengine - INFO - Epoch(train) [345][35/63] lr: 1.7386e-03 eta: 9:11:39 time: 0.5345 data_time: 0.0215 memory: 17620 loss: 1.7198 loss_prob: 0.9714 loss_thr: 0.5925 loss_db: 0.1559 2022/11/01 16:41:18 - mmengine - INFO - Epoch(train) [345][40/63] lr: 1.7386e-03 eta: 9:11:31 time: 0.5259 data_time: 0.0078 memory: 17620 loss: 1.6753 loss_prob: 0.9371 loss_thr: 0.5857 loss_db: 0.1525 2022/11/01 16:41:21 - mmengine - INFO - Epoch(train) [345][45/63] lr: 1.7386e-03 eta: 9:11:31 time: 0.5411 data_time: 0.0079 memory: 17620 loss: 1.7129 loss_prob: 0.9651 loss_thr: 0.5944 loss_db: 0.1534 2022/11/01 16:41:23 - mmengine - INFO - Epoch(train) [345][50/63] lr: 1.7386e-03 eta: 9:11:23 time: 0.5501 data_time: 0.0198 memory: 17620 loss: 1.8983 loss_prob: 1.1364 loss_thr: 0.5860 loss_db: 0.1759 2022/11/01 16:41:26 - mmengine - INFO - Epoch(train) [345][55/63] lr: 1.7386e-03 eta: 9:11:23 time: 0.5460 data_time: 0.0225 memory: 17620 loss: 1.8460 loss_prob: 1.1098 loss_thr: 0.5621 loss_db: 0.1741 2022/11/01 16:41:29 - mmengine - INFO - Epoch(train) [345][60/63] lr: 1.7386e-03 eta: 9:11:15 time: 0.5385 data_time: 0.0137 memory: 17620 loss: 1.7486 loss_prob: 1.0155 loss_thr: 0.5663 loss_db: 0.1668 2022/11/01 16:41:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:41:35 - mmengine - INFO - Epoch(train) [346][5/63] lr: 1.7367e-03 eta: 9:11:15 time: 0.7381 data_time: 0.2319 memory: 17620 loss: 1.7384 loss_prob: 0.9854 loss_thr: 0.5955 loss_db: 0.1575 2022/11/01 16:41:38 - mmengine - INFO - Epoch(train) [346][10/63] lr: 1.7367e-03 eta: 9:11:07 time: 0.7828 data_time: 0.2311 memory: 17620 loss: 1.8095 loss_prob: 1.0441 loss_thr: 0.5953 loss_db: 0.1701 2022/11/01 16:41:41 - mmengine - INFO - Epoch(train) [346][15/63] lr: 1.7367e-03 eta: 9:11:07 time: 0.5675 data_time: 0.0067 memory: 17620 loss: 1.8234 loss_prob: 1.0528 loss_thr: 0.5954 loss_db: 0.1751 2022/11/01 16:41:43 - mmengine - INFO - Epoch(train) [346][20/63] lr: 1.7367e-03 eta: 9:10:59 time: 0.5436 data_time: 0.0070 memory: 17620 loss: 1.6936 loss_prob: 0.9746 loss_thr: 0.5638 loss_db: 0.1553 2022/11/01 16:41:46 - mmengine - INFO - Epoch(train) [346][25/63] lr: 1.7367e-03 eta: 9:10:59 time: 0.5435 data_time: 0.0202 memory: 17620 loss: 1.7471 loss_prob: 1.0000 loss_thr: 0.5875 loss_db: 0.1596 2022/11/01 16:41:49 - mmengine - INFO - Epoch(train) [346][30/63] lr: 1.7367e-03 eta: 9:10:52 time: 0.5667 data_time: 0.0355 memory: 17620 loss: 1.8258 loss_prob: 1.0498 loss_thr: 0.6041 loss_db: 0.1719 2022/11/01 16:41:52 - mmengine - INFO - Epoch(train) [346][35/63] lr: 1.7367e-03 eta: 9:10:52 time: 0.5539 data_time: 0.0216 memory: 17620 loss: 1.7884 loss_prob: 1.0485 loss_thr: 0.5715 loss_db: 0.1683 2022/11/01 16:41:54 - mmengine - INFO - Epoch(train) [346][40/63] lr: 1.7367e-03 eta: 9:10:43 time: 0.5250 data_time: 0.0050 memory: 17620 loss: 1.7795 loss_prob: 1.0421 loss_thr: 0.5722 loss_db: 0.1652 2022/11/01 16:41:57 - mmengine - INFO - Epoch(train) [346][45/63] lr: 1.7367e-03 eta: 9:10:43 time: 0.5238 data_time: 0.0055 memory: 17620 loss: 1.8172 loss_prob: 1.0483 loss_thr: 0.5971 loss_db: 0.1719 2022/11/01 16:42:00 - mmengine - INFO - Epoch(train) [346][50/63] lr: 1.7367e-03 eta: 9:10:36 time: 0.5621 data_time: 0.0170 memory: 17620 loss: 1.7563 loss_prob: 1.0073 loss_thr: 0.5819 loss_db: 0.1671 2022/11/01 16:42:03 - mmengine - INFO - Epoch(train) [346][55/63] lr: 1.7367e-03 eta: 9:10:36 time: 0.5740 data_time: 0.0230 memory: 17620 loss: 1.6702 loss_prob: 0.9549 loss_thr: 0.5584 loss_db: 0.1569 2022/11/01 16:42:06 - mmengine - INFO - Epoch(train) [346][60/63] lr: 1.7367e-03 eta: 9:10:29 time: 0.5614 data_time: 0.0118 memory: 17620 loss: 1.7364 loss_prob: 1.0094 loss_thr: 0.5597 loss_db: 0.1673 2022/11/01 16:42:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:42:12 - mmengine - INFO - Epoch(train) [347][5/63] lr: 1.7349e-03 eta: 9:10:29 time: 0.7261 data_time: 0.1887 memory: 17620 loss: 1.6273 loss_prob: 0.9229 loss_thr: 0.5483 loss_db: 0.1561 2022/11/01 16:42:15 - mmengine - INFO - Epoch(train) [347][10/63] lr: 1.7349e-03 eta: 9:10:20 time: 0.7836 data_time: 0.1998 memory: 17620 loss: 1.6554 loss_prob: 0.9404 loss_thr: 0.5610 loss_db: 0.1540 2022/11/01 16:42:18 - mmengine - INFO - Epoch(train) [347][15/63] lr: 1.7349e-03 eta: 9:10:20 time: 0.5857 data_time: 0.0176 memory: 17620 loss: 1.9022 loss_prob: 1.1223 loss_thr: 0.5989 loss_db: 0.1810 2022/11/01 16:42:20 - mmengine - INFO - Epoch(train) [347][20/63] lr: 1.7349e-03 eta: 9:10:13 time: 0.5589 data_time: 0.0072 memory: 17620 loss: 1.8488 loss_prob: 1.0867 loss_thr: 0.5893 loss_db: 0.1729 2022/11/01 16:42:23 - mmengine - INFO - Epoch(train) [347][25/63] lr: 1.7349e-03 eta: 9:10:13 time: 0.5808 data_time: 0.0151 memory: 17620 loss: 1.8525 loss_prob: 1.0860 loss_thr: 0.5922 loss_db: 0.1743 2022/11/01 16:42:27 - mmengine - INFO - Epoch(train) [347][30/63] lr: 1.7349e-03 eta: 9:10:07 time: 0.6280 data_time: 0.0293 memory: 17620 loss: 1.9073 loss_prob: 1.1187 loss_thr: 0.6050 loss_db: 0.1836 2022/11/01 16:42:29 - mmengine - INFO - Epoch(train) [347][35/63] lr: 1.7349e-03 eta: 9:10:07 time: 0.6006 data_time: 0.0293 memory: 17620 loss: 1.9268 loss_prob: 1.1194 loss_thr: 0.6216 loss_db: 0.1858 2022/11/01 16:42:33 - mmengine - INFO - Epoch(train) [347][40/63] lr: 1.7349e-03 eta: 9:10:01 time: 0.6069 data_time: 0.0137 memory: 17620 loss: 1.9597 loss_prob: 1.1494 loss_thr: 0.6205 loss_db: 0.1898 2022/11/01 16:42:36 - mmengine - INFO - Epoch(train) [347][45/63] lr: 1.7349e-03 eta: 9:10:01 time: 0.6295 data_time: 0.0074 memory: 17620 loss: 1.8279 loss_prob: 1.0631 loss_thr: 0.5897 loss_db: 0.1751 2022/11/01 16:42:38 - mmengine - INFO - Epoch(train) [347][50/63] lr: 1.7349e-03 eta: 9:09:54 time: 0.5764 data_time: 0.0129 memory: 17620 loss: 1.9028 loss_prob: 1.1291 loss_thr: 0.5939 loss_db: 0.1797 2022/11/01 16:42:41 - mmengine - INFO - Epoch(train) [347][55/63] lr: 1.7349e-03 eta: 9:09:54 time: 0.5604 data_time: 0.0187 memory: 17620 loss: 1.7812 loss_prob: 1.0391 loss_thr: 0.5776 loss_db: 0.1645 2022/11/01 16:42:44 - mmengine - INFO - Epoch(train) [347][60/63] lr: 1.7349e-03 eta: 9:09:46 time: 0.5511 data_time: 0.0197 memory: 17620 loss: 1.7496 loss_prob: 1.0087 loss_thr: 0.5819 loss_db: 0.1589 2022/11/01 16:42:45 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:42:50 - mmengine - INFO - Epoch(train) [348][5/63] lr: 1.7331e-03 eta: 9:09:46 time: 0.7285 data_time: 0.1918 memory: 17620 loss: 1.8985 loss_prob: 1.1292 loss_thr: 0.5953 loss_db: 0.1741 2022/11/01 16:42:53 - mmengine - INFO - Epoch(train) [348][10/63] lr: 1.7331e-03 eta: 9:09:38 time: 0.8021 data_time: 0.2023 memory: 17620 loss: 1.6546 loss_prob: 0.9368 loss_thr: 0.5677 loss_db: 0.1502 2022/11/01 16:42:56 - mmengine - INFO - Epoch(train) [348][15/63] lr: 1.7331e-03 eta: 9:09:38 time: 0.5855 data_time: 0.0162 memory: 17620 loss: 1.8061 loss_prob: 1.0351 loss_thr: 0.6066 loss_db: 0.1644 2022/11/01 16:42:59 - mmengine - INFO - Epoch(train) [348][20/63] lr: 1.7331e-03 eta: 9:09:30 time: 0.5570 data_time: 0.0089 memory: 17620 loss: 1.8524 loss_prob: 1.0730 loss_thr: 0.6109 loss_db: 0.1686 2022/11/01 16:43:02 - mmengine - INFO - Epoch(train) [348][25/63] lr: 1.7331e-03 eta: 9:09:30 time: 0.6060 data_time: 0.0356 memory: 17620 loss: 1.6647 loss_prob: 0.9533 loss_thr: 0.5575 loss_db: 0.1540 2022/11/01 16:43:05 - mmengine - INFO - Epoch(train) [348][30/63] lr: 1.7331e-03 eta: 9:09:24 time: 0.6009 data_time: 0.0347 memory: 17620 loss: 1.6469 loss_prob: 0.9467 loss_thr: 0.5446 loss_db: 0.1556 2022/11/01 16:43:08 - mmengine - INFO - Epoch(train) [348][35/63] lr: 1.7331e-03 eta: 9:09:24 time: 0.5622 data_time: 0.0140 memory: 17620 loss: 1.9451 loss_prob: 1.1784 loss_thr: 0.5817 loss_db: 0.1850 2022/11/01 16:43:11 - mmengine - INFO - Epoch(train) [348][40/63] lr: 1.7331e-03 eta: 9:09:17 time: 0.5651 data_time: 0.0117 memory: 17620 loss: 2.0078 loss_prob: 1.2106 loss_thr: 0.6092 loss_db: 0.1881 2022/11/01 16:43:14 - mmengine - INFO - Epoch(train) [348][45/63] lr: 1.7331e-03 eta: 9:09:17 time: 0.5821 data_time: 0.0056 memory: 17620 loss: 1.8445 loss_prob: 1.0793 loss_thr: 0.5906 loss_db: 0.1746 2022/11/01 16:43:16 - mmengine - INFO - Epoch(train) [348][50/63] lr: 1.7331e-03 eta: 9:09:10 time: 0.5920 data_time: 0.0258 memory: 17620 loss: 1.8604 loss_prob: 1.0997 loss_thr: 0.5830 loss_db: 0.1778 2022/11/01 16:43:19 - mmengine - INFO - Epoch(train) [348][55/63] lr: 1.7331e-03 eta: 9:09:10 time: 0.5452 data_time: 0.0252 memory: 17620 loss: 1.7611 loss_prob: 1.0121 loss_thr: 0.5820 loss_db: 0.1669 2022/11/01 16:43:22 - mmengine - INFO - Epoch(train) [348][60/63] lr: 1.7331e-03 eta: 9:09:01 time: 0.5157 data_time: 0.0086 memory: 17620 loss: 1.7562 loss_prob: 1.0055 loss_thr: 0.5823 loss_db: 0.1684 2022/11/01 16:43:23 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:43:28 - mmengine - INFO - Epoch(train) [349][5/63] lr: 1.7313e-03 eta: 9:09:01 time: 0.7391 data_time: 0.1807 memory: 17620 loss: 1.8633 loss_prob: 1.0978 loss_thr: 0.5879 loss_db: 0.1776 2022/11/01 16:43:31 - mmengine - INFO - Epoch(train) [349][10/63] lr: 1.7313e-03 eta: 9:08:53 time: 0.7930 data_time: 0.1917 memory: 17620 loss: 1.8213 loss_prob: 1.0617 loss_thr: 0.5898 loss_db: 0.1699 2022/11/01 16:43:33 - mmengine - INFO - Epoch(train) [349][15/63] lr: 1.7313e-03 eta: 9:08:53 time: 0.5509 data_time: 0.0170 memory: 17620 loss: 1.6590 loss_prob: 0.9366 loss_thr: 0.5678 loss_db: 0.1547 2022/11/01 16:43:36 - mmengine - INFO - Epoch(train) [349][20/63] lr: 1.7313e-03 eta: 9:08:45 time: 0.5187 data_time: 0.0054 memory: 17620 loss: 1.7020 loss_prob: 0.9658 loss_thr: 0.5757 loss_db: 0.1605 2022/11/01 16:43:39 - mmengine - INFO - Epoch(train) [349][25/63] lr: 1.7313e-03 eta: 9:08:45 time: 0.5503 data_time: 0.0213 memory: 17620 loss: 1.7510 loss_prob: 0.9956 loss_thr: 0.5925 loss_db: 0.1629 2022/11/01 16:43:42 - mmengine - INFO - Epoch(train) [349][30/63] lr: 1.7313e-03 eta: 9:08:38 time: 0.5665 data_time: 0.0402 memory: 17620 loss: 1.7791 loss_prob: 1.0395 loss_thr: 0.5767 loss_db: 0.1630 2022/11/01 16:43:44 - mmengine - INFO - Epoch(train) [349][35/63] lr: 1.7313e-03 eta: 9:08:38 time: 0.5360 data_time: 0.0249 memory: 17620 loss: 1.8261 loss_prob: 1.0769 loss_thr: 0.5793 loss_db: 0.1698 2022/11/01 16:43:47 - mmengine - INFO - Epoch(train) [349][40/63] lr: 1.7313e-03 eta: 9:08:29 time: 0.5127 data_time: 0.0066 memory: 17620 loss: 1.6994 loss_prob: 0.9698 loss_thr: 0.5703 loss_db: 0.1593 2022/11/01 16:43:49 - mmengine - INFO - Epoch(train) [349][45/63] lr: 1.7313e-03 eta: 9:08:29 time: 0.5108 data_time: 0.0087 memory: 17620 loss: 1.6294 loss_prob: 0.9310 loss_thr: 0.5478 loss_db: 0.1505 2022/11/01 16:43:52 - mmengine - INFO - Epoch(train) [349][50/63] lr: 1.7313e-03 eta: 9:08:21 time: 0.5309 data_time: 0.0178 memory: 17620 loss: 1.6717 loss_prob: 0.9655 loss_thr: 0.5576 loss_db: 0.1486 2022/11/01 16:43:55 - mmengine - INFO - Epoch(train) [349][55/63] lr: 1.7313e-03 eta: 9:08:21 time: 0.5477 data_time: 0.0218 memory: 17620 loss: 1.6732 loss_prob: 0.9531 loss_thr: 0.5680 loss_db: 0.1521 2022/11/01 16:43:58 - mmengine - INFO - Epoch(train) [349][60/63] lr: 1.7313e-03 eta: 9:08:14 time: 0.5653 data_time: 0.0124 memory: 17620 loss: 1.7585 loss_prob: 0.9998 loss_thr: 0.5948 loss_db: 0.1639 2022/11/01 16:43:59 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:44:05 - mmengine - INFO - Epoch(train) [350][5/63] lr: 1.7294e-03 eta: 9:08:14 time: 0.7833 data_time: 0.2340 memory: 17620 loss: 1.7137 loss_prob: 0.9759 loss_thr: 0.5816 loss_db: 0.1561 2022/11/01 16:44:07 - mmengine - INFO - Epoch(train) [350][10/63] lr: 1.7294e-03 eta: 9:08:06 time: 0.8181 data_time: 0.2337 memory: 17620 loss: 1.7102 loss_prob: 0.9675 loss_thr: 0.5906 loss_db: 0.1521 2022/11/01 16:44:09 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:44:11 - mmengine - INFO - Epoch(train) [350][15/63] lr: 1.7294e-03 eta: 9:08:06 time: 0.5963 data_time: 0.0058 memory: 17620 loss: 1.6404 loss_prob: 0.9202 loss_thr: 0.5708 loss_db: 0.1494 2022/11/01 16:44:13 - mmengine - INFO - Epoch(train) [350][20/63] lr: 1.7294e-03 eta: 9:07:59 time: 0.5822 data_time: 0.0056 memory: 17620 loss: 1.7405 loss_prob: 1.0001 loss_thr: 0.5769 loss_db: 0.1635 2022/11/01 16:44:16 - mmengine - INFO - Epoch(train) [350][25/63] lr: 1.7294e-03 eta: 9:07:59 time: 0.5477 data_time: 0.0183 memory: 17620 loss: 1.7087 loss_prob: 0.9798 loss_thr: 0.5689 loss_db: 0.1601 2022/11/01 16:44:19 - mmengine - INFO - Epoch(train) [350][30/63] lr: 1.7294e-03 eta: 9:07:52 time: 0.5803 data_time: 0.0353 memory: 17620 loss: 1.6080 loss_prob: 0.9087 loss_thr: 0.5522 loss_db: 0.1472 2022/11/01 16:44:22 - mmengine - INFO - Epoch(train) [350][35/63] lr: 1.7294e-03 eta: 9:07:52 time: 0.5544 data_time: 0.0258 memory: 17620 loss: 1.5683 loss_prob: 0.8801 loss_thr: 0.5451 loss_db: 0.1432 2022/11/01 16:44:24 - mmengine - INFO - Epoch(train) [350][40/63] lr: 1.7294e-03 eta: 9:07:44 time: 0.5373 data_time: 0.0220 memory: 17620 loss: 1.6300 loss_prob: 0.9325 loss_thr: 0.5461 loss_db: 0.1514 2022/11/01 16:44:27 - mmengine - INFO - Epoch(train) [350][45/63] lr: 1.7294e-03 eta: 9:07:44 time: 0.5486 data_time: 0.0206 memory: 17620 loss: 1.7533 loss_prob: 1.0037 loss_thr: 0.5879 loss_db: 0.1617 2022/11/01 16:44:30 - mmengine - INFO - Epoch(train) [350][50/63] lr: 1.7294e-03 eta: 9:07:37 time: 0.5489 data_time: 0.0073 memory: 17620 loss: 1.7591 loss_prob: 1.0024 loss_thr: 0.5946 loss_db: 0.1621 2022/11/01 16:44:32 - mmengine - INFO - Epoch(train) [350][55/63] lr: 1.7294e-03 eta: 9:07:37 time: 0.5424 data_time: 0.0095 memory: 17620 loss: 1.8052 loss_prob: 1.0504 loss_thr: 0.5887 loss_db: 0.1661 2022/11/01 16:44:36 - mmengine - INFO - Epoch(train) [350][60/63] lr: 1.7294e-03 eta: 9:07:30 time: 0.5802 data_time: 0.0111 memory: 17620 loss: 1.8560 loss_prob: 1.0883 loss_thr: 0.5938 loss_db: 0.1738 2022/11/01 16:44:37 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:44:43 - mmengine - INFO - Epoch(train) [351][5/63] lr: 1.7276e-03 eta: 9:07:30 time: 0.8512 data_time: 0.2364 memory: 17620 loss: 1.7213 loss_prob: 0.9861 loss_thr: 0.5732 loss_db: 0.1620 2022/11/01 16:44:45 - mmengine - INFO - Epoch(train) [351][10/63] lr: 1.7276e-03 eta: 9:07:22 time: 0.8302 data_time: 0.2366 memory: 17620 loss: 1.5971 loss_prob: 0.9031 loss_thr: 0.5481 loss_db: 0.1458 2022/11/01 16:44:48 - mmengine - INFO - Epoch(train) [351][15/63] lr: 1.7276e-03 eta: 9:07:22 time: 0.5296 data_time: 0.0072 memory: 17620 loss: 1.7116 loss_prob: 0.9817 loss_thr: 0.5734 loss_db: 0.1565 2022/11/01 16:44:51 - mmengine - INFO - Epoch(train) [351][20/63] lr: 1.7276e-03 eta: 9:07:14 time: 0.5285 data_time: 0.0058 memory: 17620 loss: 1.8330 loss_prob: 1.0666 loss_thr: 0.5938 loss_db: 0.1726 2022/11/01 16:44:53 - mmengine - INFO - Epoch(train) [351][25/63] lr: 1.7276e-03 eta: 9:07:14 time: 0.5465 data_time: 0.0165 memory: 17620 loss: 1.9383 loss_prob: 1.1642 loss_thr: 0.5872 loss_db: 0.1869 2022/11/01 16:44:57 - mmengine - INFO - Epoch(train) [351][30/63] lr: 1.7276e-03 eta: 9:07:08 time: 0.6015 data_time: 0.0358 memory: 17620 loss: 1.7595 loss_prob: 1.0199 loss_thr: 0.5751 loss_db: 0.1645 2022/11/01 16:44:59 - mmengine - INFO - Epoch(train) [351][35/63] lr: 1.7276e-03 eta: 9:07:08 time: 0.5877 data_time: 0.0249 memory: 17620 loss: 1.6412 loss_prob: 0.9196 loss_thr: 0.5710 loss_db: 0.1507 2022/11/01 16:45:02 - mmengine - INFO - Epoch(train) [351][40/63] lr: 1.7276e-03 eta: 9:07:00 time: 0.5331 data_time: 0.0057 memory: 17620 loss: 1.6730 loss_prob: 0.9548 loss_thr: 0.5586 loss_db: 0.1595 2022/11/01 16:45:05 - mmengine - INFO - Epoch(train) [351][45/63] lr: 1.7276e-03 eta: 9:07:00 time: 0.5395 data_time: 0.0063 memory: 17620 loss: 1.6120 loss_prob: 0.8979 loss_thr: 0.5646 loss_db: 0.1495 2022/11/01 16:45:08 - mmengine - INFO - Epoch(train) [351][50/63] lr: 1.7276e-03 eta: 9:06:52 time: 0.5574 data_time: 0.0236 memory: 17620 loss: 1.6658 loss_prob: 0.9464 loss_thr: 0.5676 loss_db: 0.1519 2022/11/01 16:45:11 - mmengine - INFO - Epoch(train) [351][55/63] lr: 1.7276e-03 eta: 9:06:52 time: 0.5851 data_time: 0.0251 memory: 17620 loss: 1.6714 loss_prob: 0.9572 loss_thr: 0.5603 loss_db: 0.1539 2022/11/01 16:45:13 - mmengine - INFO - Epoch(train) [351][60/63] lr: 1.7276e-03 eta: 9:06:45 time: 0.5757 data_time: 0.0079 memory: 17620 loss: 1.6481 loss_prob: 0.9376 loss_thr: 0.5597 loss_db: 0.1508 2022/11/01 16:45:15 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:45:21 - mmengine - INFO - Epoch(train) [352][5/63] lr: 1.7258e-03 eta: 9:06:45 time: 0.8494 data_time: 0.2559 memory: 17620 loss: 1.7402 loss_prob: 1.0117 loss_thr: 0.5635 loss_db: 0.1650 2022/11/01 16:45:23 - mmengine - INFO - Epoch(train) [352][10/63] lr: 1.7258e-03 eta: 9:06:39 time: 0.8613 data_time: 0.2557 memory: 17620 loss: 1.7291 loss_prob: 0.9966 loss_thr: 0.5688 loss_db: 0.1637 2022/11/01 16:45:26 - mmengine - INFO - Epoch(train) [352][15/63] lr: 1.7258e-03 eta: 9:06:39 time: 0.5410 data_time: 0.0064 memory: 17620 loss: 1.9137 loss_prob: 1.1281 loss_thr: 0.6055 loss_db: 0.1800 2022/11/01 16:45:29 - mmengine - INFO - Epoch(train) [352][20/63] lr: 1.7258e-03 eta: 9:06:32 time: 0.5938 data_time: 0.0075 memory: 17620 loss: 1.9106 loss_prob: 1.1199 loss_thr: 0.6096 loss_db: 0.1812 2022/11/01 16:45:32 - mmengine - INFO - Epoch(train) [352][25/63] lr: 1.7258e-03 eta: 9:06:32 time: 0.6196 data_time: 0.0232 memory: 17620 loss: 1.7585 loss_prob: 1.0203 loss_thr: 0.5695 loss_db: 0.1687 2022/11/01 16:45:35 - mmengine - INFO - Epoch(train) [352][30/63] lr: 1.7258e-03 eta: 9:06:26 time: 0.6078 data_time: 0.0342 memory: 17620 loss: 1.9655 loss_prob: 1.1759 loss_thr: 0.5921 loss_db: 0.1975 2022/11/01 16:45:38 - mmengine - INFO - Epoch(train) [352][35/63] lr: 1.7258e-03 eta: 9:06:26 time: 0.5903 data_time: 0.0177 memory: 17620 loss: 2.0314 loss_prob: 1.2208 loss_thr: 0.6051 loss_db: 0.2054 2022/11/01 16:45:41 - mmengine - INFO - Epoch(train) [352][40/63] lr: 1.7258e-03 eta: 9:06:19 time: 0.5664 data_time: 0.0055 memory: 17620 loss: 1.8651 loss_prob: 1.1203 loss_thr: 0.5596 loss_db: 0.1851 2022/11/01 16:45:44 - mmengine - INFO - Epoch(train) [352][45/63] lr: 1.7258e-03 eta: 9:06:19 time: 0.5708 data_time: 0.0059 memory: 17620 loss: 1.9835 loss_prob: 1.2280 loss_thr: 0.5615 loss_db: 0.1941 2022/11/01 16:45:47 - mmengine - INFO - Epoch(train) [352][50/63] lr: 1.7258e-03 eta: 9:06:12 time: 0.6101 data_time: 0.0245 memory: 17620 loss: 1.9382 loss_prob: 1.1788 loss_thr: 0.5776 loss_db: 0.1818 2022/11/01 16:45:50 - mmengine - INFO - Epoch(train) [352][55/63] lr: 1.7258e-03 eta: 9:06:12 time: 0.5913 data_time: 0.0240 memory: 17620 loss: 1.7151 loss_prob: 0.9919 loss_thr: 0.5655 loss_db: 0.1577 2022/11/01 16:45:53 - mmengine - INFO - Epoch(train) [352][60/63] lr: 1.7258e-03 eta: 9:06:04 time: 0.5350 data_time: 0.0057 memory: 17620 loss: 1.6514 loss_prob: 0.9450 loss_thr: 0.5528 loss_db: 0.1536 2022/11/01 16:45:54 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:45:59 - mmengine - INFO - Epoch(train) [353][5/63] lr: 1.7239e-03 eta: 9:06:04 time: 0.7040 data_time: 0.1830 memory: 17620 loss: 1.8184 loss_prob: 1.0428 loss_thr: 0.6051 loss_db: 0.1704 2022/11/01 16:46:02 - mmengine - INFO - Epoch(train) [353][10/63] lr: 1.7239e-03 eta: 9:05:56 time: 0.7630 data_time: 0.1907 memory: 17620 loss: 1.8672 loss_prob: 1.0823 loss_thr: 0.6100 loss_db: 0.1750 2022/11/01 16:46:04 - mmengine - INFO - Epoch(train) [353][15/63] lr: 1.7239e-03 eta: 9:05:56 time: 0.5747 data_time: 0.0166 memory: 17620 loss: 1.7549 loss_prob: 1.0145 loss_thr: 0.5780 loss_db: 0.1623 2022/11/01 16:46:07 - mmengine - INFO - Epoch(train) [353][20/63] lr: 1.7239e-03 eta: 9:05:48 time: 0.5572 data_time: 0.0090 memory: 17620 loss: 1.6736 loss_prob: 0.9491 loss_thr: 0.5708 loss_db: 0.1536 2022/11/01 16:46:10 - mmengine - INFO - Epoch(train) [353][25/63] lr: 1.7239e-03 eta: 9:05:48 time: 0.5663 data_time: 0.0201 memory: 17620 loss: 1.6542 loss_prob: 0.9438 loss_thr: 0.5574 loss_db: 0.1529 2022/11/01 16:46:13 - mmengine - INFO - Epoch(train) [353][30/63] lr: 1.7239e-03 eta: 9:05:41 time: 0.5630 data_time: 0.0284 memory: 17620 loss: 1.7003 loss_prob: 0.9857 loss_thr: 0.5583 loss_db: 0.1563 2022/11/01 16:46:16 - mmengine - INFO - Epoch(train) [353][35/63] lr: 1.7239e-03 eta: 9:05:41 time: 0.5730 data_time: 0.0235 memory: 17620 loss: 1.6272 loss_prob: 0.9381 loss_thr: 0.5409 loss_db: 0.1482 2022/11/01 16:46:18 - mmengine - INFO - Epoch(train) [353][40/63] lr: 1.7239e-03 eta: 9:05:33 time: 0.5628 data_time: 0.0166 memory: 17620 loss: 1.6225 loss_prob: 0.9242 loss_thr: 0.5517 loss_db: 0.1466 2022/11/01 16:46:21 - mmengine - INFO - Epoch(train) [353][45/63] lr: 1.7239e-03 eta: 9:05:33 time: 0.5439 data_time: 0.0088 memory: 17620 loss: 1.6092 loss_prob: 0.9030 loss_thr: 0.5601 loss_db: 0.1461 2022/11/01 16:46:24 - mmengine - INFO - Epoch(train) [353][50/63] lr: 1.7239e-03 eta: 9:05:26 time: 0.5552 data_time: 0.0157 memory: 17620 loss: 1.8473 loss_prob: 1.1049 loss_thr: 0.5631 loss_db: 0.1792 2022/11/01 16:46:27 - mmengine - INFO - Epoch(train) [353][55/63] lr: 1.7239e-03 eta: 9:05:26 time: 0.5493 data_time: 0.0212 memory: 17620 loss: 2.0765 loss_prob: 1.2703 loss_thr: 0.6023 loss_db: 0.2038 2022/11/01 16:46:29 - mmengine - INFO - Epoch(train) [353][60/63] lr: 1.7239e-03 eta: 9:05:18 time: 0.5374 data_time: 0.0162 memory: 17620 loss: 1.9118 loss_prob: 1.1235 loss_thr: 0.6065 loss_db: 0.1819 2022/11/01 16:46:31 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:46:36 - mmengine - INFO - Epoch(train) [354][5/63] lr: 1.7221e-03 eta: 9:05:18 time: 0.7282 data_time: 0.2084 memory: 17620 loss: 1.9538 loss_prob: 1.1680 loss_thr: 0.6062 loss_db: 0.1796 2022/11/01 16:46:38 - mmengine - INFO - Epoch(train) [354][10/63] lr: 1.7221e-03 eta: 9:05:08 time: 0.7336 data_time: 0.2102 memory: 17620 loss: 1.8669 loss_prob: 1.1099 loss_thr: 0.5877 loss_db: 0.1693 2022/11/01 16:46:41 - mmengine - INFO - Epoch(train) [354][15/63] lr: 1.7221e-03 eta: 9:05:08 time: 0.5372 data_time: 0.0107 memory: 17620 loss: 1.8099 loss_prob: 1.0631 loss_thr: 0.5800 loss_db: 0.1668 2022/11/01 16:46:44 - mmengine - INFO - Epoch(train) [354][20/63] lr: 1.7221e-03 eta: 9:05:00 time: 0.5306 data_time: 0.0071 memory: 17620 loss: 1.6673 loss_prob: 0.9327 loss_thr: 0.5810 loss_db: 0.1536 2022/11/01 16:46:46 - mmengine - INFO - Epoch(train) [354][25/63] lr: 1.7221e-03 eta: 9:05:00 time: 0.5439 data_time: 0.0314 memory: 17620 loss: 1.6807 loss_prob: 0.9498 loss_thr: 0.5747 loss_db: 0.1562 2022/11/01 16:46:49 - mmengine - INFO - Epoch(train) [354][30/63] lr: 1.7221e-03 eta: 9:04:53 time: 0.5458 data_time: 0.0309 memory: 17620 loss: 1.7641 loss_prob: 1.0300 loss_thr: 0.5670 loss_db: 0.1671 2022/11/01 16:46:52 - mmengine - INFO - Epoch(train) [354][35/63] lr: 1.7221e-03 eta: 9:04:53 time: 0.5339 data_time: 0.0095 memory: 17620 loss: 1.8103 loss_prob: 1.0628 loss_thr: 0.5768 loss_db: 0.1707 2022/11/01 16:46:55 - mmengine - INFO - Epoch(train) [354][40/63] lr: 1.7221e-03 eta: 9:04:45 time: 0.5509 data_time: 0.0111 memory: 17620 loss: 1.7564 loss_prob: 1.0175 loss_thr: 0.5735 loss_db: 0.1654 2022/11/01 16:46:57 - mmengine - INFO - Epoch(train) [354][45/63] lr: 1.7221e-03 eta: 9:04:45 time: 0.5507 data_time: 0.0066 memory: 17620 loss: 1.7218 loss_prob: 0.9964 loss_thr: 0.5657 loss_db: 0.1597 2022/11/01 16:47:00 - mmengine - INFO - Epoch(train) [354][50/63] lr: 1.7221e-03 eta: 9:04:37 time: 0.5519 data_time: 0.0201 memory: 17620 loss: 1.6840 loss_prob: 0.9652 loss_thr: 0.5640 loss_db: 0.1548 2022/11/01 16:47:03 - mmengine - INFO - Epoch(train) [354][55/63] lr: 1.7221e-03 eta: 9:04:37 time: 0.5408 data_time: 0.0208 memory: 17620 loss: 1.6149 loss_prob: 0.9078 loss_thr: 0.5581 loss_db: 0.1490 2022/11/01 16:47:06 - mmengine - INFO - Epoch(train) [354][60/63] lr: 1.7221e-03 eta: 9:04:30 time: 0.5484 data_time: 0.0083 memory: 17620 loss: 1.6309 loss_prob: 0.9185 loss_thr: 0.5632 loss_db: 0.1492 2022/11/01 16:47:07 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:47:12 - mmengine - INFO - Epoch(train) [355][5/63] lr: 1.7203e-03 eta: 9:04:30 time: 0.7793 data_time: 0.2083 memory: 17620 loss: 1.7164 loss_prob: 0.9852 loss_thr: 0.5747 loss_db: 0.1565 2022/11/01 16:47:15 - mmengine - INFO - Epoch(train) [355][10/63] lr: 1.7203e-03 eta: 9:04:21 time: 0.7816 data_time: 0.2125 memory: 17620 loss: 1.6747 loss_prob: 0.9625 loss_thr: 0.5575 loss_db: 0.1547 2022/11/01 16:47:17 - mmengine - INFO - Epoch(train) [355][15/63] lr: 1.7203e-03 eta: 9:04:21 time: 0.5332 data_time: 0.0132 memory: 17620 loss: 1.6535 loss_prob: 0.9362 loss_thr: 0.5656 loss_db: 0.1517 2022/11/01 16:47:20 - mmengine - INFO - Epoch(train) [355][20/63] lr: 1.7203e-03 eta: 9:04:13 time: 0.5285 data_time: 0.0068 memory: 17620 loss: 1.5842 loss_prob: 0.8862 loss_thr: 0.5536 loss_db: 0.1444 2022/11/01 16:47:23 - mmengine - INFO - Epoch(train) [355][25/63] lr: 1.7203e-03 eta: 9:04:13 time: 0.5430 data_time: 0.0123 memory: 17620 loss: 1.5191 loss_prob: 0.8429 loss_thr: 0.5389 loss_db: 0.1373 2022/11/01 16:47:26 - mmengine - INFO - Epoch(train) [355][30/63] lr: 1.7203e-03 eta: 9:04:06 time: 0.5797 data_time: 0.0308 memory: 17620 loss: 1.6522 loss_prob: 0.9359 loss_thr: 0.5671 loss_db: 0.1492 2022/11/01 16:47:29 - mmengine - INFO - Epoch(train) [355][35/63] lr: 1.7203e-03 eta: 9:04:06 time: 0.5909 data_time: 0.0317 memory: 17620 loss: 1.7630 loss_prob: 0.9904 loss_thr: 0.6120 loss_db: 0.1607 2022/11/01 16:47:32 - mmengine - INFO - Epoch(train) [355][40/63] lr: 1.7203e-03 eta: 9:04:00 time: 0.6000 data_time: 0.0132 memory: 17620 loss: 1.7123 loss_prob: 0.9553 loss_thr: 0.5989 loss_db: 0.1581 2022/11/01 16:47:35 - mmengine - INFO - Epoch(train) [355][45/63] lr: 1.7203e-03 eta: 9:04:00 time: 0.6609 data_time: 0.0060 memory: 17620 loss: 1.5314 loss_prob: 0.8532 loss_thr: 0.5400 loss_db: 0.1382 2022/11/01 16:47:38 - mmengine - INFO - Epoch(train) [355][50/63] lr: 1.7203e-03 eta: 9:03:54 time: 0.6339 data_time: 0.0111 memory: 17620 loss: 1.4610 loss_prob: 0.8058 loss_thr: 0.5253 loss_db: 0.1299 2022/11/01 16:47:41 - mmengine - INFO - Epoch(train) [355][55/63] lr: 1.7203e-03 eta: 9:03:54 time: 0.5774 data_time: 0.0248 memory: 17620 loss: 1.4691 loss_prob: 0.8152 loss_thr: 0.5206 loss_db: 0.1333 2022/11/01 16:47:44 - mmengine - INFO - Epoch(train) [355][60/63] lr: 1.7203e-03 eta: 9:03:48 time: 0.6094 data_time: 0.0215 memory: 17620 loss: 1.7104 loss_prob: 0.9985 loss_thr: 0.5488 loss_db: 0.1631 2022/11/01 16:47:46 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:47:51 - mmengine - INFO - Epoch(train) [356][5/63] lr: 1.7184e-03 eta: 9:03:48 time: 0.8428 data_time: 0.1742 memory: 17620 loss: 2.0003 loss_prob: 1.1971 loss_thr: 0.6093 loss_db: 0.1939 2022/11/01 16:47:54 - mmengine - INFO - Epoch(train) [356][10/63] lr: 1.7184e-03 eta: 9:03:40 time: 0.8037 data_time: 0.1765 memory: 17620 loss: 1.8286 loss_prob: 1.0695 loss_thr: 0.5842 loss_db: 0.1749 2022/11/01 16:47:57 - mmengine - INFO - Epoch(train) [356][15/63] lr: 1.7184e-03 eta: 9:03:40 time: 0.5662 data_time: 0.0093 memory: 17620 loss: 1.7093 loss_prob: 0.9783 loss_thr: 0.5715 loss_db: 0.1596 2022/11/01 16:48:00 - mmengine - INFO - Epoch(train) [356][20/63] lr: 1.7184e-03 eta: 9:03:33 time: 0.5568 data_time: 0.0140 memory: 17620 loss: 1.7428 loss_prob: 0.9995 loss_thr: 0.5786 loss_db: 0.1647 2022/11/01 16:48:03 - mmengine - INFO - Epoch(train) [356][25/63] lr: 1.7184e-03 eta: 9:03:33 time: 0.5887 data_time: 0.0226 memory: 17620 loss: 1.7648 loss_prob: 1.0201 loss_thr: 0.5777 loss_db: 0.1670 2022/11/01 16:48:06 - mmengine - INFO - Epoch(train) [356][30/63] lr: 1.7184e-03 eta: 9:03:27 time: 0.6261 data_time: 0.0273 memory: 17620 loss: 1.7303 loss_prob: 0.9964 loss_thr: 0.5749 loss_db: 0.1590 2022/11/01 16:48:09 - mmengine - INFO - Epoch(train) [356][35/63] lr: 1.7184e-03 eta: 9:03:27 time: 0.5833 data_time: 0.0217 memory: 17620 loss: 1.6735 loss_prob: 0.9571 loss_thr: 0.5599 loss_db: 0.1565 2022/11/01 16:48:12 - mmengine - INFO - Epoch(train) [356][40/63] lr: 1.7184e-03 eta: 9:03:20 time: 0.5592 data_time: 0.0152 memory: 17620 loss: 1.9705 loss_prob: 1.1944 loss_thr: 0.5798 loss_db: 0.1963 2022/11/01 16:48:14 - mmengine - INFO - Epoch(train) [356][45/63] lr: 1.7184e-03 eta: 9:03:20 time: 0.5552 data_time: 0.0120 memory: 17620 loss: 2.0501 loss_prob: 1.2545 loss_thr: 0.5986 loss_db: 0.1969 2022/11/01 16:48:17 - mmengine - INFO - Epoch(train) [356][50/63] lr: 1.7184e-03 eta: 9:03:12 time: 0.5646 data_time: 0.0164 memory: 17620 loss: 1.7914 loss_prob: 1.0458 loss_thr: 0.5824 loss_db: 0.1632 2022/11/01 16:48:20 - mmengine - INFO - Epoch(train) [356][55/63] lr: 1.7184e-03 eta: 9:03:12 time: 0.5856 data_time: 0.0255 memory: 17620 loss: 1.7120 loss_prob: 0.9776 loss_thr: 0.5738 loss_db: 0.1606 2022/11/01 16:48:23 - mmengine - INFO - Epoch(train) [356][60/63] lr: 1.7184e-03 eta: 9:03:05 time: 0.5608 data_time: 0.0156 memory: 17620 loss: 1.7297 loss_prob: 0.9860 loss_thr: 0.5831 loss_db: 0.1606 2022/11/01 16:48:24 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:48:29 - mmengine - INFO - Epoch(train) [357][5/63] lr: 1.7166e-03 eta: 9:03:05 time: 0.7505 data_time: 0.2110 memory: 17620 loss: 1.6934 loss_prob: 0.9655 loss_thr: 0.5778 loss_db: 0.1501 2022/11/01 16:48:32 - mmengine - INFO - Epoch(train) [357][10/63] lr: 1.7166e-03 eta: 9:02:57 time: 0.7777 data_time: 0.2182 memory: 17620 loss: 1.7111 loss_prob: 0.9782 loss_thr: 0.5742 loss_db: 0.1587 2022/11/01 16:48:35 - mmengine - INFO - Epoch(train) [357][15/63] lr: 1.7166e-03 eta: 9:02:57 time: 0.5303 data_time: 0.0124 memory: 17620 loss: 1.7610 loss_prob: 1.0297 loss_thr: 0.5652 loss_db: 0.1661 2022/11/01 16:48:37 - mmengine - INFO - Epoch(train) [357][20/63] lr: 1.7166e-03 eta: 9:02:49 time: 0.5367 data_time: 0.0056 memory: 17620 loss: 1.7401 loss_prob: 1.0245 loss_thr: 0.5533 loss_db: 0.1622 2022/11/01 16:48:41 - mmengine - INFO - Epoch(train) [357][25/63] lr: 1.7166e-03 eta: 9:02:49 time: 0.5915 data_time: 0.0328 memory: 17620 loss: 1.7574 loss_prob: 1.0274 loss_thr: 0.5689 loss_db: 0.1611 2022/11/01 16:48:44 - mmengine - INFO - Epoch(train) [357][30/63] lr: 1.7166e-03 eta: 9:02:42 time: 0.6069 data_time: 0.0546 memory: 17620 loss: 1.6785 loss_prob: 0.9663 loss_thr: 0.5591 loss_db: 0.1530 2022/11/01 16:48:46 - mmengine - INFO - Epoch(train) [357][35/63] lr: 1.7166e-03 eta: 9:02:42 time: 0.5486 data_time: 0.0270 memory: 17620 loss: 1.6531 loss_prob: 0.9219 loss_thr: 0.5796 loss_db: 0.1516 2022/11/01 16:48:49 - mmengine - INFO - Epoch(train) [357][40/63] lr: 1.7166e-03 eta: 9:02:34 time: 0.5337 data_time: 0.0051 memory: 17620 loss: 1.7895 loss_prob: 1.0156 loss_thr: 0.6059 loss_db: 0.1679 2022/11/01 16:48:52 - mmengine - INFO - Epoch(train) [357][45/63] lr: 1.7166e-03 eta: 9:02:34 time: 0.5508 data_time: 0.0066 memory: 17620 loss: 1.7212 loss_prob: 0.9964 loss_thr: 0.5612 loss_db: 0.1635 2022/11/01 16:48:55 - mmengine - INFO - Epoch(train) [357][50/63] lr: 1.7166e-03 eta: 9:02:27 time: 0.5654 data_time: 0.0177 memory: 17620 loss: 1.6940 loss_prob: 0.9569 loss_thr: 0.5820 loss_db: 0.1551 2022/11/01 16:48:57 - mmengine - INFO - Epoch(train) [357][55/63] lr: 1.7166e-03 eta: 9:02:27 time: 0.5583 data_time: 0.0262 memory: 17620 loss: 1.6341 loss_prob: 0.9011 loss_thr: 0.5844 loss_db: 0.1487 2022/11/01 16:49:00 - mmengine - INFO - Epoch(train) [357][60/63] lr: 1.7166e-03 eta: 9:02:20 time: 0.5707 data_time: 0.0158 memory: 17620 loss: 1.7153 loss_prob: 0.9878 loss_thr: 0.5692 loss_db: 0.1582 2022/11/01 16:49:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:49:06 - mmengine - INFO - Epoch(train) [358][5/63] lr: 1.7148e-03 eta: 9:02:20 time: 0.7456 data_time: 0.2056 memory: 17620 loss: 1.8943 loss_prob: 1.1032 loss_thr: 0.6171 loss_db: 0.1741 2022/11/01 16:49:09 - mmengine - INFO - Epoch(train) [358][10/63] lr: 1.7148e-03 eta: 9:02:11 time: 0.7525 data_time: 0.2050 memory: 17620 loss: 1.7031 loss_prob: 0.9515 loss_thr: 0.6017 loss_db: 0.1499 2022/11/01 16:49:12 - mmengine - INFO - Epoch(train) [358][15/63] lr: 1.7148e-03 eta: 9:02:11 time: 0.5404 data_time: 0.0065 memory: 17620 loss: 1.7382 loss_prob: 0.9876 loss_thr: 0.5937 loss_db: 0.1569 2022/11/01 16:49:15 - mmengine - INFO - Epoch(train) [358][20/63] lr: 1.7148e-03 eta: 9:02:03 time: 0.5559 data_time: 0.0077 memory: 17620 loss: 1.8146 loss_prob: 1.0451 loss_thr: 0.5992 loss_db: 0.1704 2022/11/01 16:49:18 - mmengine - INFO - Epoch(train) [358][25/63] lr: 1.7148e-03 eta: 9:02:03 time: 0.5930 data_time: 0.0332 memory: 17620 loss: 1.6841 loss_prob: 0.9443 loss_thr: 0.5869 loss_db: 0.1528 2022/11/01 16:49:21 - mmengine - INFO - Epoch(train) [358][30/63] lr: 1.7148e-03 eta: 9:01:57 time: 0.5862 data_time: 0.0382 memory: 17620 loss: 1.8419 loss_prob: 1.0789 loss_thr: 0.5886 loss_db: 0.1744 2022/11/01 16:49:23 - mmengine - INFO - Epoch(train) [358][35/63] lr: 1.7148e-03 eta: 9:01:57 time: 0.5397 data_time: 0.0127 memory: 17620 loss: 1.9419 loss_prob: 1.1871 loss_thr: 0.5687 loss_db: 0.1861 2022/11/01 16:49:26 - mmengine - INFO - Epoch(train) [358][40/63] lr: 1.7148e-03 eta: 9:01:48 time: 0.5200 data_time: 0.0069 memory: 17620 loss: 1.8139 loss_prob: 1.0996 loss_thr: 0.5496 loss_db: 0.1647 2022/11/01 16:49:28 - mmengine - INFO - Epoch(train) [358][45/63] lr: 1.7148e-03 eta: 9:01:48 time: 0.5178 data_time: 0.0079 memory: 17620 loss: 1.7386 loss_prob: 1.0217 loss_thr: 0.5573 loss_db: 0.1596 2022/11/01 16:49:31 - mmengine - INFO - Epoch(train) [358][50/63] lr: 1.7148e-03 eta: 9:01:41 time: 0.5541 data_time: 0.0266 memory: 17620 loss: 1.7396 loss_prob: 1.0082 loss_thr: 0.5666 loss_db: 0.1648 2022/11/01 16:49:34 - mmengine - INFO - Epoch(train) [358][55/63] lr: 1.7148e-03 eta: 9:01:41 time: 0.5922 data_time: 0.0250 memory: 17620 loss: 1.8823 loss_prob: 1.1289 loss_thr: 0.5726 loss_db: 0.1807 2022/11/01 16:49:37 - mmengine - INFO - Epoch(train) [358][60/63] lr: 1.7148e-03 eta: 9:01:34 time: 0.5848 data_time: 0.0059 memory: 17620 loss: 1.8952 loss_prob: 1.1451 loss_thr: 0.5716 loss_db: 0.1785 2022/11/01 16:49:38 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:49:43 - mmengine - INFO - Epoch(train) [359][5/63] lr: 1.7129e-03 eta: 9:01:34 time: 0.7342 data_time: 0.1935 memory: 17620 loss: 1.6867 loss_prob: 0.9775 loss_thr: 0.5542 loss_db: 0.1551 2022/11/01 16:49:46 - mmengine - INFO - Epoch(train) [359][10/63] lr: 1.7129e-03 eta: 9:01:25 time: 0.7565 data_time: 0.1936 memory: 17620 loss: 1.8940 loss_prob: 1.1173 loss_thr: 0.5954 loss_db: 0.1813 2022/11/01 16:49:49 - mmengine - INFO - Epoch(train) [359][15/63] lr: 1.7129e-03 eta: 9:01:25 time: 0.5293 data_time: 0.0103 memory: 17620 loss: 1.8708 loss_prob: 1.0871 loss_thr: 0.6034 loss_db: 0.1804 2022/11/01 16:49:52 - mmengine - INFO - Epoch(train) [359][20/63] lr: 1.7129e-03 eta: 9:01:18 time: 0.5476 data_time: 0.0096 memory: 17620 loss: 1.6855 loss_prob: 0.9660 loss_thr: 0.5628 loss_db: 0.1568 2022/11/01 16:49:54 - mmengine - INFO - Epoch(train) [359][25/63] lr: 1.7129e-03 eta: 9:01:18 time: 0.5789 data_time: 0.0208 memory: 17620 loss: 1.6221 loss_prob: 0.9210 loss_thr: 0.5535 loss_db: 0.1476 2022/11/01 16:49:57 - mmengine - INFO - Epoch(train) [359][30/63] lr: 1.7129e-03 eta: 9:01:11 time: 0.5886 data_time: 0.0348 memory: 17620 loss: 1.8480 loss_prob: 1.0972 loss_thr: 0.5715 loss_db: 0.1793 2022/11/01 16:50:00 - mmengine - INFO - Epoch(train) [359][35/63] lr: 1.7129e-03 eta: 9:01:11 time: 0.5636 data_time: 0.0192 memory: 17620 loss: 2.0249 loss_prob: 1.2354 loss_thr: 0.5833 loss_db: 0.2061 2022/11/01 16:50:03 - mmengine - INFO - Epoch(train) [359][40/63] lr: 1.7129e-03 eta: 9:01:04 time: 0.5881 data_time: 0.0062 memory: 17620 loss: 1.9874 loss_prob: 1.1951 loss_thr: 0.6011 loss_db: 0.1912 2022/11/01 16:50:07 - mmengine - INFO - Epoch(train) [359][45/63] lr: 1.7129e-03 eta: 9:01:04 time: 0.6647 data_time: 0.0076 memory: 17620 loss: 1.8527 loss_prob: 1.0726 loss_thr: 0.6104 loss_db: 0.1697 2022/11/01 16:50:10 - mmengine - INFO - Epoch(train) [359][50/63] lr: 1.7129e-03 eta: 9:00:59 time: 0.6500 data_time: 0.0177 memory: 17620 loss: 2.1372 loss_prob: 1.3003 loss_thr: 0.6276 loss_db: 0.2094 2022/11/01 16:50:13 - mmengine - INFO - Epoch(train) [359][55/63] lr: 1.7129e-03 eta: 9:00:59 time: 0.6432 data_time: 0.0241 memory: 17620 loss: 2.2363 loss_prob: 1.3817 loss_thr: 0.6331 loss_db: 0.2215 2022/11/01 16:50:16 - mmengine - INFO - Epoch(train) [359][60/63] lr: 1.7129e-03 eta: 9:00:54 time: 0.6419 data_time: 0.0142 memory: 17620 loss: 2.0732 loss_prob: 1.2432 loss_thr: 0.6274 loss_db: 0.2026 2022/11/01 16:50:18 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:50:22 - mmengine - INFO - Epoch(train) [360][5/63] lr: 1.7111e-03 eta: 9:00:54 time: 0.7315 data_time: 0.2136 memory: 17620 loss: 1.9791 loss_prob: 1.1860 loss_thr: 0.6001 loss_db: 0.1930 2022/11/01 16:50:25 - mmengine - INFO - Epoch(train) [360][10/63] lr: 1.7111e-03 eta: 9:00:45 time: 0.7626 data_time: 0.2132 memory: 17620 loss: 1.9043 loss_prob: 1.1169 loss_thr: 0.6070 loss_db: 0.1804 2022/11/01 16:50:28 - mmengine - INFO - Epoch(train) [360][15/63] lr: 1.7111e-03 eta: 9:00:45 time: 0.5452 data_time: 0.0064 memory: 17620 loss: 1.9288 loss_prob: 1.1350 loss_thr: 0.6056 loss_db: 0.1882 2022/11/01 16:50:31 - mmengine - INFO - Epoch(train) [360][20/63] lr: 1.7111e-03 eta: 9:00:38 time: 0.5748 data_time: 0.0065 memory: 17620 loss: 1.8661 loss_prob: 1.1086 loss_thr: 0.5833 loss_db: 0.1742 2022/11/01 16:50:34 - mmengine - INFO - Epoch(train) [360][25/63] lr: 1.7111e-03 eta: 9:00:38 time: 0.5761 data_time: 0.0085 memory: 17620 loss: 1.9231 loss_prob: 1.1536 loss_thr: 0.5900 loss_db: 0.1795 2022/11/01 16:50:37 - mmengine - INFO - Epoch(train) [360][30/63] lr: 1.7111e-03 eta: 9:00:31 time: 0.5891 data_time: 0.0406 memory: 17620 loss: 1.8772 loss_prob: 1.1080 loss_thr: 0.5870 loss_db: 0.1822 2022/11/01 16:50:40 - mmengine - INFO - Epoch(train) [360][35/63] lr: 1.7111e-03 eta: 9:00:31 time: 0.5868 data_time: 0.0397 memory: 17620 loss: 1.9800 loss_prob: 1.1535 loss_thr: 0.6362 loss_db: 0.1903 2022/11/01 16:50:43 - mmengine - INFO - Epoch(train) [360][40/63] lr: 1.7111e-03 eta: 9:00:24 time: 0.5808 data_time: 0.0098 memory: 17620 loss: 1.9398 loss_prob: 1.1283 loss_thr: 0.6314 loss_db: 0.1800 2022/11/01 16:50:45 - mmengine - INFO - Epoch(train) [360][45/63] lr: 1.7111e-03 eta: 9:00:24 time: 0.5759 data_time: 0.0091 memory: 17620 loss: 1.6211 loss_prob: 0.9221 loss_thr: 0.5513 loss_db: 0.1477 2022/11/01 16:50:48 - mmengine - INFO - Epoch(train) [360][50/63] lr: 1.7111e-03 eta: 9:00:17 time: 0.5461 data_time: 0.0193 memory: 17620 loss: 1.5535 loss_prob: 0.8626 loss_thr: 0.5498 loss_db: 0.1411 2022/11/01 16:50:51 - mmengine - INFO - Epoch(train) [360][55/63] lr: 1.7111e-03 eta: 9:00:17 time: 0.5949 data_time: 0.0236 memory: 17620 loss: 1.6454 loss_prob: 0.9169 loss_thr: 0.5795 loss_db: 0.1490 2022/11/01 16:50:54 - mmengine - INFO - Epoch(train) [360][60/63] lr: 1.7111e-03 eta: 9:00:11 time: 0.6343 data_time: 0.0109 memory: 17620 loss: 1.7169 loss_prob: 0.9944 loss_thr: 0.5654 loss_db: 0.1570 2022/11/01 16:50:56 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:50:56 - mmengine - INFO - Saving checkpoint at 360 epochs 2022/11/01 16:51:03 - mmengine - INFO - Epoch(val) [360][5/32] eta: 9:00:11 time: 0.5755 data_time: 0.0716 memory: 17620 2022/11/01 16:51:06 - mmengine - INFO - Epoch(val) [360][10/32] eta: 0:00:13 time: 0.6349 data_time: 0.1031 memory: 15725 2022/11/01 16:51:08 - mmengine - INFO - Epoch(val) [360][15/32] eta: 0:00:13 time: 0.5771 data_time: 0.0451 memory: 15725 2022/11/01 16:51:12 - mmengine - INFO - Epoch(val) [360][20/32] eta: 0:00:07 time: 0.5872 data_time: 0.0498 memory: 15725 2022/11/01 16:51:15 - mmengine - INFO - Epoch(val) [360][25/32] eta: 0:00:07 time: 0.6142 data_time: 0.0558 memory: 15725 2022/11/01 16:51:17 - mmengine - INFO - Epoch(val) [360][30/32] eta: 0:00:01 time: 0.5734 data_time: 0.0241 memory: 15725 2022/11/01 16:51:18 - mmengine - INFO - Evaluating hmean-iou... 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.30, recall: 0.8440, precision: 0.6992, hmean: 0.7648 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.40, recall: 0.8440, precision: 0.7850, hmean: 0.8135 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.50, recall: 0.8402, precision: 0.8306, hmean: 0.8353 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.60, recall: 0.8325, precision: 0.8710, hmean: 0.8513 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.70, recall: 0.8007, precision: 0.9147, hmean: 0.8539 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.80, recall: 0.6095, precision: 0.9591, hmean: 0.7454 2022/11/01 16:51:18 - mmengine - INFO - prediction score threshold: 0.90, recall: 0.0014, precision: 1.0000, hmean: 0.0029 2022/11/01 16:51:18 - mmengine - INFO - Epoch(val) [360][32/32] icdar/precision: 0.9147 icdar/recall: 0.8007 icdar/hmean: 0.8539 2022/11/01 16:51:23 - mmengine - INFO - Epoch(train) [361][5/63] lr: 1.7093e-03 eta: 0:00:01 time: 0.7651 data_time: 0.2237 memory: 17620 loss: 1.8915 loss_prob: 1.1255 loss_thr: 0.5861 loss_db: 0.1799 2022/11/01 16:51:26 - mmengine - INFO - Epoch(train) [361][10/63] lr: 1.7093e-03 eta: 9:00:02 time: 0.7667 data_time: 0.2232 memory: 17620 loss: 1.7687 loss_prob: 1.0338 loss_thr: 0.5686 loss_db: 0.1663 2022/11/01 16:51:29 - mmengine - INFO - Epoch(train) [361][15/63] lr: 1.7093e-03 eta: 9:00:02 time: 0.5429 data_time: 0.0094 memory: 17620 loss: 1.7149 loss_prob: 0.9936 loss_thr: 0.5663 loss_db: 0.1551 2022/11/01 16:51:31 - mmengine - INFO - Epoch(train) [361][20/63] lr: 1.7093e-03 eta: 8:59:55 time: 0.5435 data_time: 0.0102 memory: 17620 loss: 1.7831 loss_prob: 1.0319 loss_thr: 0.5889 loss_db: 0.1623 2022/11/01 16:51:34 - mmengine - INFO - Epoch(train) [361][25/63] lr: 1.7093e-03 eta: 8:59:55 time: 0.5579 data_time: 0.0283 memory: 17620 loss: 1.7959 loss_prob: 1.0318 loss_thr: 0.5959 loss_db: 0.1683 2022/11/01 16:51:37 - mmengine - INFO - Epoch(train) [361][30/63] lr: 1.7093e-03 eta: 8:59:47 time: 0.5548 data_time: 0.0299 memory: 17620 loss: 1.7981 loss_prob: 1.0338 loss_thr: 0.5968 loss_db: 0.1675 2022/11/01 16:51:40 - mmengine - INFO - Epoch(train) [361][35/63] lr: 1.7093e-03 eta: 8:59:47 time: 0.5406 data_time: 0.0129 memory: 17620 loss: 1.6362 loss_prob: 0.9296 loss_thr: 0.5563 loss_db: 0.1503 2022/11/01 16:51:42 - mmengine - INFO - Epoch(train) [361][40/63] lr: 1.7093e-03 eta: 8:59:39 time: 0.5471 data_time: 0.0122 memory: 17620 loss: 1.6509 loss_prob: 0.9487 loss_thr: 0.5504 loss_db: 0.1518 2022/11/01 16:51:45 - mmengine - INFO - Epoch(train) [361][45/63] lr: 1.7093e-03 eta: 8:59:39 time: 0.5301 data_time: 0.0083 memory: 17620 loss: 1.7445 loss_prob: 0.9997 loss_thr: 0.5836 loss_db: 0.1612 2022/11/01 16:51:48 - mmengine - INFO - Epoch(train) [361][50/63] lr: 1.7093e-03 eta: 8:59:32 time: 0.5487 data_time: 0.0229 memory: 17620 loss: 1.7439 loss_prob: 1.0094 loss_thr: 0.5732 loss_db: 0.1613 2022/11/01 16:51:50 - mmengine - INFO - Epoch(train) [361][55/63] lr: 1.7093e-03 eta: 8:59:32 time: 0.5585 data_time: 0.0250 memory: 17620 loss: 1.6535 loss_prob: 0.9553 loss_thr: 0.5448 loss_db: 0.1534 2022/11/01 16:51:53 - mmengine - INFO - Epoch(train) [361][60/63] lr: 1.7093e-03 eta: 8:59:25 time: 0.5601 data_time: 0.0124 memory: 17620 loss: 1.6511 loss_prob: 0.9459 loss_thr: 0.5525 loss_db: 0.1527 2022/11/01 16:51:55 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:52:00 - mmengine - INFO - Epoch(train) [362][5/63] lr: 1.7074e-03 eta: 8:59:25 time: 0.8332 data_time: 0.2787 memory: 17620 loss: 1.6720 loss_prob: 0.9461 loss_thr: 0.5699 loss_db: 0.1560 2022/11/01 16:52:03 - mmengine - INFO - Epoch(train) [362][10/63] lr: 1.7074e-03 eta: 8:59:18 time: 0.8596 data_time: 0.2749 memory: 17620 loss: 1.6546 loss_prob: 0.9380 loss_thr: 0.5653 loss_db: 0.1513 2022/11/01 16:52:06 - mmengine - INFO - Epoch(train) [362][15/63] lr: 1.7074e-03 eta: 8:59:18 time: 0.5570 data_time: 0.0053 memory: 17620 loss: 1.6508 loss_prob: 0.9422 loss_thr: 0.5584 loss_db: 0.1502 2022/11/01 16:52:09 - mmengine - INFO - Epoch(train) [362][20/63] lr: 1.7074e-03 eta: 8:59:10 time: 0.5300 data_time: 0.0053 memory: 17620 loss: 1.7585 loss_prob: 1.0160 loss_thr: 0.5816 loss_db: 0.1609 2022/11/01 16:52:11 - mmengine - INFO - Epoch(train) [362][25/63] lr: 1.7074e-03 eta: 8:59:10 time: 0.5406 data_time: 0.0170 memory: 17620 loss: 1.6719 loss_prob: 0.9359 loss_thr: 0.5851 loss_db: 0.1509 2022/11/01 16:52:14 - mmengine - INFO - Epoch(train) [362][30/63] lr: 1.7074e-03 eta: 8:59:03 time: 0.5645 data_time: 0.0350 memory: 17620 loss: 1.6223 loss_prob: 0.9004 loss_thr: 0.5708 loss_db: 0.1511 2022/11/01 16:52:17 - mmengine - INFO - Epoch(train) [362][35/63] lr: 1.7074e-03 eta: 8:59:03 time: 0.5444 data_time: 0.0229 memory: 17620 loss: 1.5662 loss_prob: 0.8850 loss_thr: 0.5341 loss_db: 0.1471 2022/11/01 16:52:19 - mmengine - INFO - Epoch(train) [362][40/63] lr: 1.7074e-03 eta: 8:58:55 time: 0.5286 data_time: 0.0056 memory: 17620 loss: 2.3294 loss_prob: 1.4743 loss_thr: 0.6132 loss_db: 0.2420 2022/11/01 16:52:22 - mmengine - INFO - Epoch(train) [362][45/63] lr: 1.7074e-03 eta: 8:58:55 time: 0.5544 data_time: 0.0070 memory: 17620 loss: 2.5024 loss_prob: 1.5954 loss_thr: 0.6471 loss_db: 0.2600 2022/11/01 16:52:25 - mmengine - INFO - Epoch(train) [362][50/63] lr: 1.7074e-03 eta: 8:58:48 time: 0.5717 data_time: 0.0241 memory: 17620 loss: 1.8961 loss_prob: 1.1323 loss_thr: 0.5820 loss_db: 0.1817 2022/11/01 16:52:28 - mmengine - INFO - Epoch(train) [362][55/63] lr: 1.7074e-03 eta: 8:58:48 time: 0.5516 data_time: 0.0234 memory: 17620 loss: 2.2380 loss_prob: 1.3922 loss_thr: 0.6250 loss_db: 0.2207 2022/11/01 16:52:31 - mmengine - INFO - Epoch(train) [362][60/63] lr: 1.7074e-03 eta: 8:58:40 time: 0.5395 data_time: 0.0094 memory: 17620 loss: 2.2984 loss_prob: 1.4321 loss_thr: 0.6403 loss_db: 0.2260 2022/11/01 16:52:32 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:52:37 - mmengine - INFO - Epoch(train) [363][5/63] lr: 1.7056e-03 eta: 8:58:40 time: 0.7714 data_time: 0.2059 memory: 17620 loss: 2.0644 loss_prob: 1.2605 loss_thr: 0.6001 loss_db: 0.2038 2022/11/01 16:52:41 - mmengine - INFO - Epoch(train) [363][10/63] lr: 1.7056e-03 eta: 8:58:33 time: 0.8485 data_time: 0.2076 memory: 17620 loss: 1.9932 loss_prob: 1.1967 loss_thr: 0.6054 loss_db: 0.1911 2022/11/01 16:52:43 - mmengine - INFO - Epoch(train) [363][15/63] lr: 1.7056e-03 eta: 8:58:33 time: 0.6202 data_time: 0.0124 memory: 17620 loss: 1.9938 loss_prob: 1.1957 loss_thr: 0.6104 loss_db: 0.1877 2022/11/01 16:52:46 - mmengine - INFO - Epoch(train) [363][20/63] lr: 1.7056e-03 eta: 8:58:25 time: 0.5400 data_time: 0.0076 memory: 17620 loss: 1.9726 loss_prob: 1.1817 loss_thr: 0.5995 loss_db: 0.1915 2022/11/01 16:52:49 - mmengine - INFO - Epoch(train) [363][25/63] lr: 1.7056e-03 eta: 8:58:25 time: 0.5584 data_time: 0.0302 memory: 17620 loss: 1.9362 loss_prob: 1.1347 loss_thr: 0.6111 loss_db: 0.1904 2022/11/01 16:52:52 - mmengine - INFO - Epoch(train) [363][30/63] lr: 1.7056e-03 eta: 8:58:19 time: 0.6105 data_time: 0.0426 memory: 17620 loss: 1.9048 loss_prob: 1.1222 loss_thr: 0.5981 loss_db: 0.1845 2022/11/01 16:52:55 - mmengine - INFO - Epoch(train) [363][35/63] lr: 1.7056e-03 eta: 8:58:19 time: 0.6012 data_time: 0.0181 memory: 17620 loss: 1.7780 loss_prob: 1.0349 loss_thr: 0.5684 loss_db: 0.1748 2022/11/01 16:52:58 - mmengine - INFO - Epoch(train) [363][40/63] lr: 1.7056e-03 eta: 8:58:12 time: 0.5581 data_time: 0.0069 memory: 17620 loss: 1.8889 loss_prob: 1.0935 loss_thr: 0.6113 loss_db: 0.1842 2022/11/01 16:53:00 - mmengine - INFO - Epoch(train) [363][45/63] lr: 1.7056e-03 eta: 8:58:12 time: 0.5439 data_time: 0.0108 memory: 17620 loss: 1.9862 loss_prob: 1.1668 loss_thr: 0.6292 loss_db: 0.1901 2022/11/01 16:53:03 - mmengine - INFO - Epoch(train) [363][50/63] lr: 1.7056e-03 eta: 8:58:04 time: 0.5595 data_time: 0.0199 memory: 17620 loss: 1.8008 loss_prob: 1.0418 loss_thr: 0.5915 loss_db: 0.1676 2022/11/01 16:53:06 - mmengine - INFO - Epoch(train) [363][55/63] lr: 1.7056e-03 eta: 8:58:04 time: 0.5558 data_time: 0.0237 memory: 17620 loss: 1.7744 loss_prob: 1.0372 loss_thr: 0.5712 loss_db: 0.1660 2022/11/01 16:53:09 - mmengine - INFO - Epoch(train) [363][60/63] lr: 1.7056e-03 eta: 8:57:58 time: 0.5857 data_time: 0.0134 memory: 17620 loss: 1.7766 loss_prob: 1.0475 loss_thr: 0.5580 loss_db: 0.1711 2022/11/01 16:53:11 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:53:16 - mmengine - INFO - Epoch(train) [364][5/63] lr: 1.7038e-03 eta: 8:57:58 time: 0.8156 data_time: 0.2267 memory: 17620 loss: 1.7676 loss_prob: 1.0274 loss_thr: 0.5759 loss_db: 0.1643 2022/11/01 16:53:19 - mmengine - INFO - Epoch(train) [364][10/63] lr: 1.7038e-03 eta: 8:57:51 time: 0.8274 data_time: 0.2267 memory: 17620 loss: 1.7497 loss_prob: 1.0225 loss_thr: 0.5641 loss_db: 0.1632 2022/11/01 16:53:22 - mmengine - INFO - Epoch(train) [364][15/63] lr: 1.7038e-03 eta: 8:57:51 time: 0.5862 data_time: 0.0107 memory: 17620 loss: 1.7103 loss_prob: 0.9756 loss_thr: 0.5763 loss_db: 0.1583 2022/11/01 16:53:25 - mmengine - INFO - Epoch(train) [364][20/63] lr: 1.7038e-03 eta: 8:57:43 time: 0.5548 data_time: 0.0063 memory: 17620 loss: 1.8842 loss_prob: 1.1025 loss_thr: 0.6071 loss_db: 0.1747 2022/11/01 16:53:28 - mmengine - INFO - Epoch(train) [364][25/63] lr: 1.7038e-03 eta: 8:57:43 time: 0.5778 data_time: 0.0304 memory: 17620 loss: 1.9544 loss_prob: 1.1607 loss_thr: 0.6082 loss_db: 0.1856 2022/11/01 16:53:30 - mmengine - INFO - Epoch(train) [364][30/63] lr: 1.7038e-03 eta: 8:57:36 time: 0.5782 data_time: 0.0346 memory: 17620 loss: 1.8568 loss_prob: 1.0835 loss_thr: 0.5988 loss_db: 0.1745 2022/11/01 16:53:33 - mmengine - INFO - Epoch(train) [364][35/63] lr: 1.7038e-03 eta: 8:57:36 time: 0.5687 data_time: 0.0124 memory: 17620 loss: 1.8224 loss_prob: 1.0655 loss_thr: 0.5905 loss_db: 0.1664 2022/11/01 16:53:36 - mmengine - INFO - Epoch(train) [364][40/63] lr: 1.7038e-03 eta: 8:57:29 time: 0.5794 data_time: 0.0075 memory: 17620 loss: 1.7446 loss_prob: 0.9956 loss_thr: 0.5898 loss_db: 0.1592 2022/11/01 16:53:39 - mmengine - INFO - Epoch(train) [364][45/63] lr: 1.7038e-03 eta: 8:57:29 time: 0.5563 data_time: 0.0066 memory: 17620 loss: 1.7690 loss_prob: 0.9981 loss_thr: 0.6078 loss_db: 0.1631 2022/11/01 16:53:42 - mmengine - INFO - Epoch(train) [364][50/63] lr: 1.7038e-03 eta: 8:57:22 time: 0.5512 data_time: 0.0202 memory: 17620 loss: 1.8523 loss_prob: 1.0665 loss_thr: 0.6150 loss_db: 0.1708 2022/11/01 16:53:45 - mmengine - INFO - Epoch(train) [364][55/63] lr: 1.7038e-03 eta: 8:57:22 time: 0.5554 data_time: 0.0210 memory: 17620 loss: 1.8250 loss_prob: 1.0485 loss_thr: 0.6075 loss_db: 0.1690 2022/11/01 16:53:47 - mmengine - INFO - Epoch(train) [364][60/63] lr: 1.7038e-03 eta: 8:57:14 time: 0.5379 data_time: 0.0104 memory: 17620 loss: 1.7844 loss_prob: 1.0114 loss_thr: 0.6097 loss_db: 0.1634 2022/11/01 16:53:49 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:53:53 - mmengine - INFO - Epoch(train) [365][5/63] lr: 1.7019e-03 eta: 8:57:14 time: 0.7151 data_time: 0.1796 memory: 17620 loss: 2.0200 loss_prob: 1.1882 loss_thr: 0.6348 loss_db: 0.1970 2022/11/01 16:53:56 - mmengine - INFO - Epoch(train) [365][10/63] lr: 1.7019e-03 eta: 8:57:05 time: 0.7410 data_time: 0.1877 memory: 17620 loss: 1.8086 loss_prob: 1.0394 loss_thr: 0.5946 loss_db: 0.1746 2022/11/01 16:53:59 - mmengine - INFO - Epoch(train) [365][15/63] lr: 1.7019e-03 eta: 8:57:05 time: 0.5509 data_time: 0.0162 memory: 17620 loss: 2.0689 loss_prob: 1.2592 loss_thr: 0.6110 loss_db: 0.1986 2022/11/01 16:54:01 - mmengine - INFO - Epoch(train) [365][20/63] lr: 1.7019e-03 eta: 8:56:57 time: 0.5367 data_time: 0.0094 memory: 17620 loss: 2.2652 loss_prob: 1.3946 loss_thr: 0.6502 loss_db: 0.2203 2022/11/01 16:54:04 - mmengine - INFO - Epoch(train) [365][25/63] lr: 1.7019e-03 eta: 8:56:57 time: 0.5452 data_time: 0.0243 memory: 17620 loss: 2.2259 loss_prob: 1.3655 loss_thr: 0.6347 loss_db: 0.2257 2022/11/01 16:54:07 - mmengine - INFO - Epoch(train) [365][30/63] lr: 1.7019e-03 eta: 8:56:50 time: 0.5675 data_time: 0.0342 memory: 17620 loss: 2.2794 loss_prob: 1.3952 loss_thr: 0.6610 loss_db: 0.2232 2022/11/01 16:54:10 - mmengine - INFO - Epoch(train) [365][35/63] lr: 1.7019e-03 eta: 8:56:50 time: 0.5725 data_time: 0.0171 memory: 17620 loss: 2.3221 loss_prob: 1.4217 loss_thr: 0.6779 loss_db: 0.2225 2022/11/01 16:54:13 - mmengine - INFO - Epoch(train) [365][40/63] lr: 1.7019e-03 eta: 8:56:43 time: 0.5897 data_time: 0.0068 memory: 17620 loss: 2.6331 loss_prob: 1.6955 loss_thr: 0.6673 loss_db: 0.2703 2022/11/01 16:54:16 - mmengine - INFO - Epoch(train) [365][45/63] lr: 1.7019e-03 eta: 8:56:43 time: 0.5681 data_time: 0.0090 memory: 17620 loss: 2.5534 loss_prob: 1.6347 loss_thr: 0.6578 loss_db: 0.2609 2022/11/01 16:54:18 - mmengine - INFO - Epoch(train) [365][50/63] lr: 1.7019e-03 eta: 8:56:35 time: 0.5321 data_time: 0.0202 memory: 17620 loss: 2.2805 loss_prob: 1.4057 loss_thr: 0.6460 loss_db: 0.2288 2022/11/01 16:54:21 - mmengine - INFO - Epoch(train) [365][55/63] lr: 1.7019e-03 eta: 8:56:35 time: 0.5485 data_time: 0.0242 memory: 17620 loss: 2.1748 loss_prob: 1.3108 loss_thr: 0.6496 loss_db: 0.2143 2022/11/01 16:54:24 - mmengine - INFO - Epoch(train) [365][60/63] lr: 1.7019e-03 eta: 8:56:28 time: 0.5501 data_time: 0.0122 memory: 17620 loss: 1.9410 loss_prob: 1.1421 loss_thr: 0.6190 loss_db: 0.1800 2022/11/01 16:54:25 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:54:30 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:54:30 - mmengine - INFO - Epoch(train) [366][5/63] lr: 1.7001e-03 eta: 8:56:28 time: 0.7378 data_time: 0.2324 memory: 17620 loss: 1.9427 loss_prob: 1.1592 loss_thr: 0.5945 loss_db: 0.1890 2022/11/01 16:54:33 - mmengine - INFO - Epoch(train) [366][10/63] lr: 1.7001e-03 eta: 8:56:19 time: 0.7632 data_time: 0.2286 memory: 17620 loss: 1.8625 loss_prob: 1.1028 loss_thr: 0.5796 loss_db: 0.1801 2022/11/01 16:54:35 - mmengine - INFO - Epoch(train) [366][15/63] lr: 1.7001e-03 eta: 8:56:19 time: 0.5211 data_time: 0.0051 memory: 17620 loss: 1.9200 loss_prob: 1.1372 loss_thr: 0.6031 loss_db: 0.1797 2022/11/01 16:54:38 - mmengine - INFO - Epoch(train) [366][20/63] lr: 1.7001e-03 eta: 8:56:11 time: 0.5358 data_time: 0.0051 memory: 17620 loss: 2.1149 loss_prob: 1.2792 loss_thr: 0.6365 loss_db: 0.1992 2022/11/01 16:54:41 - mmengine - INFO - Epoch(train) [366][25/63] lr: 1.7001e-03 eta: 8:56:11 time: 0.5714 data_time: 0.0312 memory: 17620 loss: 2.0828 loss_prob: 1.2531 loss_thr: 0.6318 loss_db: 0.1979 2022/11/01 16:54:44 - mmengine - INFO - Epoch(train) [366][30/63] lr: 1.7001e-03 eta: 8:56:04 time: 0.5620 data_time: 0.0342 memory: 17620 loss: 2.0849 loss_prob: 1.2615 loss_thr: 0.6200 loss_db: 0.2034 2022/11/01 16:54:47 - mmengine - INFO - Epoch(train) [366][35/63] lr: 1.7001e-03 eta: 8:56:04 time: 0.5461 data_time: 0.0091 memory: 17620 loss: 2.1414 loss_prob: 1.3137 loss_thr: 0.6176 loss_db: 0.2101 2022/11/01 16:54:49 - mmengine - INFO - Epoch(train) [366][40/63] lr: 1.7001e-03 eta: 8:55:57 time: 0.5657 data_time: 0.0150 memory: 17620 loss: 1.9770 loss_prob: 1.1951 loss_thr: 0.5918 loss_db: 0.1901 2022/11/01 16:54:52 - mmengine - INFO - Epoch(train) [366][45/63] lr: 1.7001e-03 eta: 8:55:57 time: 0.5510 data_time: 0.0141 memory: 17620 loss: 1.9457 loss_prob: 1.1524 loss_thr: 0.6073 loss_db: 0.1860 2022/11/01 16:54:55 - mmengine - INFO - Epoch(train) [366][50/63] lr: 1.7001e-03 eta: 8:55:49 time: 0.5426 data_time: 0.0131 memory: 17620 loss: 1.9742 loss_prob: 1.1630 loss_thr: 0.6234 loss_db: 0.1879 2022/11/01 16:54:58 - mmengine - INFO - Epoch(train) [366][55/63] lr: 1.7001e-03 eta: 8:55:49 time: 0.5495 data_time: 0.0155 memory: 17620 loss: 1.9543 loss_prob: 1.1481 loss_thr: 0.6148 loss_db: 0.1914 2022/11/01 16:55:00 - mmengine - INFO - Epoch(train) [366][60/63] lr: 1.7001e-03 eta: 8:55:42 time: 0.5549 data_time: 0.0076 memory: 17620 loss: 1.9164 loss_prob: 1.1173 loss_thr: 0.6162 loss_db: 0.1828 2022/11/01 16:55:02 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:55:07 - mmengine - INFO - Epoch(train) [367][5/63] lr: 1.6983e-03 eta: 8:55:42 time: 0.7465 data_time: 0.1953 memory: 17620 loss: 2.0369 loss_prob: 1.2170 loss_thr: 0.6346 loss_db: 0.1853 2022/11/01 16:55:10 - mmengine - INFO - Epoch(train) [367][10/63] lr: 1.6983e-03 eta: 8:55:33 time: 0.7877 data_time: 0.2006 memory: 17620 loss: 1.9712 loss_prob: 1.1557 loss_thr: 0.6398 loss_db: 0.1757 2022/11/01 16:55:13 - mmengine - INFO - Epoch(train) [367][15/63] lr: 1.6983e-03 eta: 8:55:33 time: 0.5987 data_time: 0.0120 memory: 17620 loss: 1.8136 loss_prob: 1.0243 loss_thr: 0.6236 loss_db: 0.1658 2022/11/01 16:55:16 - mmengine - INFO - Epoch(train) [367][20/63] lr: 1.6983e-03 eta: 8:55:27 time: 0.5974 data_time: 0.0094 memory: 17620 loss: 1.7735 loss_prob: 1.0272 loss_thr: 0.5765 loss_db: 0.1698 2022/11/01 16:55:18 - mmengine - INFO - Epoch(train) [367][25/63] lr: 1.6983e-03 eta: 8:55:27 time: 0.5628 data_time: 0.0119 memory: 17620 loss: 1.8196 loss_prob: 1.0680 loss_thr: 0.5820 loss_db: 0.1696 2022/11/01 16:55:22 - mmengine - INFO - Epoch(train) [367][30/63] lr: 1.6983e-03 eta: 8:55:20 time: 0.5896 data_time: 0.0345 memory: 17620 loss: 1.7444 loss_prob: 1.0061 loss_thr: 0.5809 loss_db: 0.1573 2022/11/01 16:55:25 - mmengine - INFO - Epoch(train) [367][35/63] lr: 1.6983e-03 eta: 8:55:20 time: 0.6239 data_time: 0.0319 memory: 17620 loss: 1.7450 loss_prob: 1.0099 loss_thr: 0.5710 loss_db: 0.1641 2022/11/01 16:55:28 - mmengine - INFO - Epoch(train) [367][40/63] lr: 1.6983e-03 eta: 8:55:15 time: 0.6403 data_time: 0.0059 memory: 17620 loss: 1.7850 loss_prob: 1.0388 loss_thr: 0.5768 loss_db: 0.1694 2022/11/01 16:55:31 - mmengine - INFO - Epoch(train) [367][45/63] lr: 1.6983e-03 eta: 8:55:15 time: 0.6456 data_time: 0.0077 memory: 17620 loss: 1.7502 loss_prob: 1.0127 loss_thr: 0.5731 loss_db: 0.1644 2022/11/01 16:55:34 - mmengine - INFO - Epoch(train) [367][50/63] lr: 1.6983e-03 eta: 8:55:09 time: 0.6199 data_time: 0.0202 memory: 17620 loss: 1.8051 loss_prob: 1.0508 loss_thr: 0.5826 loss_db: 0.1717 2022/11/01 16:55:37 - mmengine - INFO - Epoch(train) [367][55/63] lr: 1.6983e-03 eta: 8:55:09 time: 0.5934 data_time: 0.0246 memory: 17620 loss: 1.9401 loss_prob: 1.1600 loss_thr: 0.5991 loss_db: 0.1810 2022/11/01 16:55:40 - mmengine - INFO - Epoch(train) [367][60/63] lr: 1.6983e-03 eta: 8:55:02 time: 0.5720 data_time: 0.0118 memory: 17620 loss: 1.9491 loss_prob: 1.1561 loss_thr: 0.6128 loss_db: 0.1802 2022/11/01 16:55:42 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_1200e_icdar2015_20221101_124139 2022/11/01 16:55:47 - mmengine - INFO - Epoch(train) [368][5/63] lr: 1.6964e-03 eta: 8:55:02 time: 0.8621 data_time: 0.2014 memory: 17620 loss: 1.7087 loss_prob: 0.9865 loss_thr: 0.5626 loss_db: 0.1596 2022/11/01 16:55:50 - mmengine - INFO - Epoch(train) [368][10/63] lr: 1.6964e-03 eta: 8:54:55 time: 0.8494 data_time: 0.2034 memory: 17620 loss: 1.7449 loss_prob: 1.0052 loss_thr: 0.5766 loss_db: 0.1631 2022/11/01 16:55:53 - mmengine - INFO - Epoch(train) [368][15/63] lr: 1.6964e-03 eta: 8:54:55 time: 0.5472 data_time: 0.0110 memory: 17620 loss: 1.8031 loss_prob: 1.0437 loss_thr: 0.5896 loss_db: 0.1698 2022/11/01 16:55:56 - mmengine - INFO - Epoch(train) [368][20/63] lr: 1.6964e-03 eta: 8:54:49 time: 0.5924 data_time: 0.0051 memory: 17620 loss: 1.8320 loss_prob: 1.0660 loss_thr: 0.5933 loss_db: 0.1728 2022/11/01 16:55:59 - mmengine - INFO - Epoch(train) [368][25/63] lr: 1.6964e-03 eta: 8:54:49 time: 0.6194 data_time: 0.0137 memory: 17620 loss: 1.9363 loss_prob: 1.1255 loss_thr: 0.6311 loss_db: 0.1797 2022/11/01 16:56:03 - mmengine - INFO - Epoch(train) [368][30/63] lr: 1.6964e-03 eta: 8:54:44 time: 0.6539 data_time: 0.0452 memory: 17620 loss: 1.8852 loss_prob: 1.0790 loss_thr: 0.6305 loss_db: 0.1757 2022/11/01 16:56:05 - mmengine - INFO - Epoch(train) [368][35/63] lr: 1.6964e-03 eta: 8:54:44 time: 0.6162 data_time: 0.0377 memory: 17620 loss: 1.7732 loss_prob: 1.0255 loss_thr: 0.5819 loss_db: 0.1658 2022/11/01 16:56:08 - mmengine - INFO - Epoch(train) [368][40/63] lr: 1.6964e-03 eta: 8:54:36 time: 0.5537 data_time: 0.0085 memory: 17620 loss: 1.8506 loss_prob: 1.0813 loss_thr: 0.5984 loss_db: 0.1709 2022/11/01 16:56:11 - mmengine - INFO - Epoch(train) [368][45/63] lr: 1.6964e-03 eta: 8:54:36 time: 0.6020 data_time: 0.0085 memory: 17620 loss: 1.9589 loss_prob: 1.1540 loss_thr: 0.6193 loss_db: 0.1856 2022/11/01 16:56:14 - mmengine - INFO - Epoch(train) [368][50/63] lr: 1.6964e-03 eta: 8:54:29 time: 0.5867 data_time: 0.0156 memory: 17620 loss: 1.9404 loss_prob: 1.1553 loss_thr: 0.5972 loss_db: 0.1879 2022/11/01 16:56:17 - mmengine - INFO - Epoch(train) [368][55/63] lr: 1.6964e-03 eta: 8:54:29 time: 0.5561 data_time: 0.0234 memory: 17620 loss: 1.8945 loss_prob: 1.1070 loss_thr: 0.6070 loss_db: 0.1804 2022/11/01 16:56:19 - mmengine - INFO - Epoch(train) [368][60/63] lr: 1.6964e-03 eta: 8:54:22 time: 0.5482 data_time: 0.0142 memory: 17620 loss: 1.9818 loss_prob: 1.1811 loss_thr: 0.6149 loss_db: 0.1858 2022/11/01 16:56:21 - mmengine - INFO - Exp name: dbnetpp_resnet50-oclip_fpnc_