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Implement LD on VisDrone dataset #68

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melika-sce opened this issue Jul 14, 2023 · 5 comments
Open

Implement LD on VisDrone dataset #68

melika-sce opened this issue Jul 14, 2023 · 5 comments

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@melika-sce
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Hi and thanks for this great work
I wanted to reimplement your LD on VisDrone dataset
here is the steps I followed:
1- Finetune 'faster-rcnn_r18_fpn_1x.py' config on VisDrone dataset
2- Finetune 'faster-rcnn_r101_fpn_1x.py' config on VisDrone dataset
3- train with 'ld_r18-gflv1-r101_fpn_1x_coco' config and modify the config to load the finetuned R101 as teacher and finetuned R18 as student and also change the dataset part to load VisDrone

but the result is NOT what I expected

bbox_mAP_50:

gfl_r101_fpn_1x_finetuned : 31.8 
gfl_r101_fpn_1x_finetuned : 28.5
ld_gfl_R18_R101_1x : 18

bbox_mAP:

gfl_r101_fpn_1x_finetuned : 19.7
gfl_r101_fpn_1x_finetuned : 17.6
ld_gfl_R18_R101_1x : 10.8

I wonder if you can help me figure which part may cause the problem
@HikariTJU
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Owner

Can you paste ld_gfl_R18_R101_1x training log here?
And btw what do you mean by "Finetune 'faster-rcnn_r18_fpn_1x.py' config"? We didn't provide code to train LD in Faster-RCNN

@melika-sce
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Author

Oh sorry, I made mistake pasting the name of configs, I finetuned gfl_r18_fpn_1x and gfl_r101_fpn_1x

  • training log of ld_gfl_R18_R101_1x:
2023/07/13 08:59:35 - mmengine - INFO - 
------------------------------------------------------------
System environment:
    sys.platform: linux
    Python: 3.8.16 (default, Jun 12 2023, 18:09:05) [GCC 11.2.0]
    CUDA available: True
    numpy_random_seed: 903740675
    GPU 0: NVIDIA GeForce RTX 3090
    CUDA_HOME: /usr/local/cuda
    NVCC: Cuda compilation tools, release 11.3, V11.3.109
    GCC: gcc (GCC) 4.4.7 20120313 (Red Hat 4.4.7-18)
    PyTorch: 2.0.1
    PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201703
  - Intel(R) oneAPI Math Kernel Library Version 2023.1-Product Build 20230303 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 11.7
  - 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_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37
  - CuDNN 8.5
  - Magma 2.6.1
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.7, CUDNN_VERSION=8.5.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -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 -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.1, 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, USE_ROCM=OFF, 

    TorchVision: 0.15.2
    OpenCV: 4.7.0
    MMEngine: 0.7.4

Runtime environment:
    cudnn_benchmark: False
    mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0}
    dist_cfg: {'backend': 'nccl'}
    seed: 903740675
    Distributed launcher: none
    Distributed training: False
    GPU number: 1
------------------------------------------------------------

2023/07/13 08:59:36 - mmengine - INFO - Config:
dataset_type = 'CocoDataset'
data_root = 'dataset/VisDrone/'
classes = ('pedestrian', 'people', 'bicycle', 'car', 'van', 'truck',
           'tricycle', 'awning-tricycle', 'bus', 'motor')
METAINFO = dict(
    classes=('pedestrian', 'people', 'bicycle', 'car', 'van', 'truck',
             'tricycle', 'awning-tricycle', 'bus', 'motor'))
backend_args = None
train_pipeline = [
    dict(type='LoadImageFromFile', backend_args=None),
    dict(type='LoadAnnotations', with_bbox=True),
    dict(type='Resize', scale=(640, 640), keep_ratio=True),
    dict(type='RandomFlip', prob=0.5),
    dict(type='PackDetInputs')
]
test_pipeline = [
    dict(type='LoadImageFromFile', backend_args=None),
    dict(type='Resize', scale=(640, 640), keep_ratio=True),
    dict(type='LoadAnnotations', with_bbox=True),
    dict(
        type='PackDetInputs',
        meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
                   'scale_factor'))
]
train_dataloader = dict(
    batch_size=2,
    num_workers=2,
    persistent_workers=True,
    sampler=dict(type='DefaultSampler', shuffle=True),
    batch_sampler=dict(type='AspectRatioBatchSampler'),
    dataset=dict(
        type='CocoDataset',
        data_root='dataset/VisDrone/',
        ann_file='VisDrone2019-DET-train/annotations_VisDrone_train.json',
        data_prefix=dict(img='VisDrone2019-DET-train/images/'),
        filter_cfg=dict(filter_empty_gt=True, min_size=32),
        pipeline=[
            dict(type='LoadImageFromFile', backend_args=None),
            dict(type='LoadAnnotations', with_bbox=True),
            dict(type='Resize', scale=(640, 640), keep_ratio=True),
            dict(type='RandomFlip', prob=0.5),
            dict(type='PackDetInputs')
        ],
        backend_args=None))
val_dataloader = dict(
    batch_size=1,
    num_workers=2,
    persistent_workers=True,
    drop_last=False,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type='CocoDataset',
        data_root=dataset/VisDrone/',
        ann_file='VisDrone2019-DET-val/annotations_VisDrone_val.json',
        data_prefix=dict(img='VisDrone2019-DET-val/images/'),
        test_mode=True,
        pipeline=[
            dict(type='LoadImageFromFile', backend_args=None),
            dict(type='Resize', scale=(640, 640), keep_ratio=True),
            dict(type='LoadAnnotations', with_bbox=True),
            dict(
                type='PackDetInputs',
                meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
                           'scale_factor'))
        ],
        backend_args=None))
test_dataloader = dict(
    batch_size=1,
    num_workers=2,
    persistent_workers=True,
    drop_last=False,
    sampler=dict(type='DefaultSampler', shuffle=False),
    dataset=dict(
        type='CocoDataset',
        data_root='dataset/VisDrone/',
        ann_file='VisDrone2019-DET-test-dev/annotations_VisDrone_dev.json',
        data_prefix=dict(img='VisDrone2019-DET-test-dev/images/'),
        test_mode=True,
        pipeline=[
            dict(type='LoadImageFromFile', backend_args=None),
            dict(type='Resize', scale=(640, 640), keep_ratio=True),
            dict(type='LoadAnnotations', with_bbox=True),
            dict(
                type='PackDetInputs',
                meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
                           'scale_factor'))
        ],
        backend_args=None))
val_evaluator = dict(
    type='CocoMetric',
    ann_file=
    'dataset/VisDrone/VisDrone2019-DET-val/annotations_VisDrone_val.json',
    metric='bbox',
    format_only=False,
    backend_args=None)
test_evaluator = dict(
    type='CocoMetric',
    ann_file=
    'dataset/VisDrone/VisDrone2019-DET-test-dev/annotations_VisDrone_dev.json',
    metric='bbox',
    format_only=True,
    backend_args=None,
    outfile_prefix='./work_dirs/visdrone_detection/test')
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=12, val_interval=1)
val_cfg = dict(type='ValLoop')
test_cfg = dict(type='TestLoop')
param_scheduler = [
    dict(
        type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
    dict(
        type='MultiStepLR',
        begin=0,
        end=12,
        by_epoch=True,
        milestones=[8, 11],
        gamma=0.1)
]
optim_wrapper = dict(
    type='OptimWrapper',
    optimizer=dict(type='SGD', lr=0.00125, momentum=0.9, weight_decay=0.0001))
auto_scale_lr = dict(enable=False, base_batch_size=16)
default_scope = 'mmdet'
default_hooks = dict(
    timer=dict(type='IterTimerHook'),
    logger=dict(type='LoggerHook', interval=50),
    param_scheduler=dict(type='ParamSchedulerHook'),
    checkpoint=dict(type='CheckpointHook', interval=1),
    sampler_seed=dict(type='DistSamplerSeedHook'),
    visualization=dict(type='DetVisualizationHook'))
env_cfg = dict(
    cudnn_benchmark=False,
    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
    dist_cfg=dict(backend='nccl'))
vis_backends = [dict(type='LocalVisBackend')]
visualizer = dict(
    type='DetLocalVisualizer',
    vis_backends=[dict(type='LocalVisBackend')],
    name='visualizer')
log_processor = dict(type='LogProcessor', window_size=50, by_epoch=True)
log_level = 'INFO'
load_from = None
resume = False
teacher_ckpt = 'mmdetection/work_dirs/gfl_r101_fpn_finetune_vis_1x/epoch_12.pth'
model = dict(
    type='KnowledgeDistillationSingleStageDetector',
    data_preprocessor=dict(
        type='DetDataPreprocessor',
        mean=[123.675, 116.28, 103.53],
        std=[58.395, 57.12, 57.375],
        bgr_to_rgb=True,
        pad_size_divisor=32),
    teacher_config='configs/ld/gfl_r101_fpn_finetune_vis_1x.py',
    teacher_ckpt=
    'mmdetection/work_dirs/gfl_r101_fpn_finetune_vis_1x/epoch_12.pth',
    backbone=dict(
        type='ResNet',
        depth=18,
        num_stages=4,
        out_indices=(0, 1, 2, 3),
        frozen_stages=1,
        norm_cfg=dict(type='BN', requires_grad=True),
        norm_eval=True,
        style='pytorch',
        init_cfg=dict(
            type='Pretrained',
            checkpoint=
            'mmdetection/work_dirs/gfl_r18_fpn_finetune_vis_1x/epoch_12.pth'
        )),
    neck=dict(
        type='FPN',
        in_channels=[64, 128, 256, 512],
        out_channels=256,
        start_level=1,
        add_extra_convs='on_output',
        num_outs=5),
    bbox_head=dict(
        type='LDHead',
        num_classes=10,
        in_channels=256,
        stacked_convs=4,
        feat_channels=256,
        anchor_generator=dict(
            type='AnchorGenerator',
            ratios=[1.0],
            octave_base_scale=8,
            scales_per_octave=1,
            strides=[8, 16, 32, 64, 128]),
        loss_cls=dict(
            type='QualityFocalLoss',
            use_sigmoid=True,
            beta=2.0,
            loss_weight=1.0),
        loss_dfl=dict(type='DistributionFocalLoss', loss_weight=0.25),
        loss_ld=dict(
            type='KnowledgeDistillationKLDivLoss', loss_weight=0.25, T=10),
        reg_max=16,
        loss_bbox=dict(type='GIoULoss', loss_weight=2.0)),
    train_cfg=dict(
        assigner=dict(type='ATSSAssigner', topk=9),
        allowed_border=-1,
        pos_weight=-1,
        debug=False),
    test_cfg=dict(
        nms_pre=1000,
        min_bbox_size=0,
        score_thr=0.05,
        nms=dict(type='nms', iou_threshold=0.6),
        max_per_img=100))
launcher = 'none'
work_dir = 'mmdetection/work_dir/ld_gfl_r18_r101_fpn_1x_vis'

2023/07/13 08:59:43 - mmengine - INFO - Distributed training is not used, all SyncBatchNorm (SyncBN) layers in the model will be automatically reverted to BatchNormXd layers if they are used.
2023/07/13 08:59:43 - mmengine - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH   ) RuntimeInfoHook                    
(BELOW_NORMAL) LoggerHook                         
 -------------------- 
before_train:
(VERY_HIGH   ) RuntimeInfoHook                    
(NORMAL      ) IterTimerHook                      
(VERY_LOW    ) CheckpointHook                     
 -------------------- 
before_train_epoch:
(VERY_HIGH   ) RuntimeInfoHook                    
(NORMAL      ) IterTimerHook                      
(NORMAL      ) DistSamplerSeedHook                
 -------------------- 
before_train_iter:
(VERY_HIGH   ) RuntimeInfoHook                    
(NORMAL      ) IterTimerHook                      
 -------------------- 
after_train_iter:
(VERY_HIGH   ) RuntimeInfoHook                    
(NORMAL      ) IterTimerHook                      
(BELOW_NORMAL) LoggerHook                         
(LOW         ) ParamSchedulerHook                 
(VERY_LOW    ) CheckpointHook                     
 -------------------- 
after_train_epoch:
(NORMAL      ) IterTimerHook                      
(LOW         ) ParamSchedulerHook                 
(VERY_LOW    ) CheckpointHook                     
 -------------------- 
before_val_epoch:
(NORMAL      ) IterTimerHook                      
 -------------------- 
before_val_iter:
(NORMAL      ) IterTimerHook                      
 -------------------- 
after_val_iter:
(NORMAL      ) IterTimerHook                      
(NORMAL      ) DetVisualizationHook               
(BELOW_NORMAL) LoggerHook                         
 -------------------- 
after_val_epoch:
(VERY_HIGH   ) RuntimeInfoHook                    
(NORMAL      ) IterTimerHook                      
(BELOW_NORMAL) LoggerHook                         
(LOW         ) ParamSchedulerHook                 
(VERY_LOW    ) CheckpointHook                     
 -------------------- 
after_train:
(VERY_LOW    ) CheckpointHook                     
 -------------------- 
before_test_epoch:
(NORMAL      ) IterTimerHook                      
 -------------------- 
before_test_iter:
(NORMAL      ) IterTimerHook                      
 -------------------- 
after_test_iter:
(NORMAL      ) IterTimerHook                      
(NORMAL      ) DetVisualizationHook               
(BELOW_NORMAL) LoggerHook                         
 -------------------- 
after_test_epoch:
(VERY_HIGH   ) RuntimeInfoHook                    
(NORMAL      ) IterTimerHook                      
(BELOW_NORMAL) LoggerHook                         
 -------------------- 
after_run:
(BELOW_NORMAL) LoggerHook                         
 -------------------- 
2023/07/13 08:59:48 - mmengine - INFO - load model from: 
mmdetection/work_dirs/gfl_r18_fpn_finetune_vis_1x/epoch_12.pth
2023/07/13 08:59:48 - mmengine - INFO - Loads checkpoint by local backend from path: mmdetection/work_dirs/gfl_r18_fpn_finetune_vis_1x/epoch_12.pth
2023/07/13 08:59:49 - mmengine - WARNING - The model and loaded state dict do not match exactly

unexpected key in source state_dict: backbone.conv1.weight, backbone.bn1.weight, backbone.bn1.bias, backbone.bn1.running_mean, backbone.bn1.running_var, backbone.bn1.num_batches_tracked, backbone.layer1.0.conv1.weight, backbone.layer1.0.bn1.weight, backbone.layer1.0.bn1.bias, backbone.layer1.0.bn1.running_mean, backbone.layer1.0.bn1.running_var, backbone.layer1.0.bn1.num_batches_tracked, backbone.layer1.0.conv2.weight, backbone.layer1.0.bn2.weight, backbone.layer1.0.bn2.bias, backbone.layer1.0.bn2.running_mean, backbone.layer1.0.bn2.running_var, backbone.layer1.0.bn2.num_batches_tracked, backbone.layer1.1.conv1.weight, backbone.layer1.1.bn1.weight, backbone.layer1.1.bn1.bias, backbone.layer1.1.bn1.running_mean, backbone.layer1.1.bn1.running_var, backbone.layer1.1.bn1.num_batches_tracked, backbone.layer1.1.conv2.weight, backbone.layer1.1.bn2.weight, backbone.layer1.1.bn2.bias, backbone.layer1.1.bn2.running_mean, backbone.layer1.1.bn2.running_var, backbone.layer1.1.bn2.num_batches_tracked, backbone.layer2.0.conv1.weight, backbone.layer2.0.bn1.weight, backbone.layer2.0.bn1.bias, backbone.layer2.0.bn1.running_mean, backbone.layer2.0.bn1.running_var, backbone.layer2.0.bn1.num_batches_tracked, backbone.layer2.0.conv2.weight, backbone.layer2.0.bn2.weight, backbone.layer2.0.bn2.bias, backbone.layer2.0.bn2.running_mean, backbone.layer2.0.bn2.running_var, backbone.layer2.0.bn2.num_batches_tracked, backbone.layer2.0.downsample.0.weight, backbone.layer2.0.downsample.1.weight, backbone.layer2.0.downsample.1.bias, backbone.layer2.0.downsample.1.running_mean, backbone.layer2.0.downsample.1.running_var, backbone.layer2.0.downsample.1.num_batches_tracked, backbone.layer2.1.conv1.weight, backbone.layer2.1.bn1.weight, backbone.layer2.1.bn1.bias, backbone.layer2.1.bn1.running_mean, backbone.layer2.1.bn1.running_var, backbone.layer2.1.bn1.num_batches_tracked, backbone.layer2.1.conv2.weight, backbone.layer2.1.bn2.weight, backbone.layer2.1.bn2.bias, backbone.layer2.1.bn2.running_mean, backbone.layer2.1.bn2.running_var, backbone.layer2.1.bn2.num_batches_tracked, backbone.layer3.0.conv1.weight, backbone.layer3.0.bn1.weight, backbone.layer3.0.bn1.bias, backbone.layer3.0.bn1.running_mean, backbone.layer3.0.bn1.running_var, backbone.layer3.0.bn1.num_batches_tracked, backbone.layer3.0.conv2.weight, backbone.layer3.0.bn2.weight, backbone.layer3.0.bn2.bias, backbone.layer3.0.bn2.running_mean, backbone.layer3.0.bn2.running_var, backbone.layer3.0.bn2.num_batches_tracked, backbone.layer3.0.downsample.0.weight, backbone.layer3.0.downsample.1.weight, backbone.layer3.0.downsample.1.bias, backbone.layer3.0.downsample.1.running_mean, backbone.layer3.0.downsample.1.running_var, backbone.layer3.0.downsample.1.num_batches_tracked, backbone.layer3.1.conv1.weight, backbone.layer3.1.bn1.weight, backbone.layer3.1.bn1.bias, backbone.layer3.1.bn1.running_mean, backbone.layer3.1.bn1.running_var, backbone.layer3.1.bn1.num_batches_tracked, backbone.layer3.1.conv2.weight, backbone.layer3.1.bn2.weight, backbone.layer3.1.bn2.bias, backbone.layer3.1.bn2.running_mean, backbone.layer3.1.bn2.running_var, backbone.layer3.1.bn2.num_batches_tracked, backbone.layer4.0.conv1.weight, backbone.layer4.0.bn1.weight, backbone.layer4.0.bn1.bias, backbone.layer4.0.bn1.running_mean, backbone.layer4.0.bn1.running_var, backbone.layer4.0.bn1.num_batches_tracked, backbone.layer4.0.conv2.weight, backbone.layer4.0.bn2.weight, backbone.layer4.0.bn2.bias, backbone.layer4.0.bn2.running_mean, backbone.layer4.0.bn2.running_var, backbone.layer4.0.bn2.num_batches_tracked, backbone.layer4.0.downsample.0.weight, backbone.layer4.0.downsample.1.weight, backbone.layer4.0.downsample.1.bias, backbone.layer4.0.downsample.1.running_mean, backbone.layer4.0.downsample.1.running_var, backbone.layer4.0.downsample.1.num_batches_tracked, backbone.layer4.1.conv1.weight, backbone.layer4.1.bn1.weight, backbone.layer4.1.bn1.bias, backbone.layer4.1.bn1.running_mean, backbone.layer4.1.bn1.running_var, backbone.layer4.1.bn1.num_batches_tracked, backbone.layer4.1.conv2.weight, backbone.layer4.1.bn2.weight, backbone.layer4.1.bn2.bias, backbone.layer4.1.bn2.running_mean, backbone.layer4.1.bn2.running_var, backbone.layer4.1.bn2.num_batches_tracked, neck.lateral_convs.0.conv.weight, neck.lateral_convs.0.conv.bias, neck.lateral_convs.1.conv.weight, neck.lateral_convs.1.conv.bias, neck.lateral_convs.2.conv.weight, neck.lateral_convs.2.conv.bias, neck.fpn_convs.0.conv.weight, neck.fpn_convs.0.conv.bias, neck.fpn_convs.1.conv.weight, neck.fpn_convs.1.conv.bias, neck.fpn_convs.2.conv.weight, neck.fpn_convs.2.conv.bias, neck.fpn_convs.3.conv.weight, neck.fpn_convs.3.conv.bias, neck.fpn_convs.4.conv.weight, neck.fpn_convs.4.conv.bias, bbox_head.cls_convs.0.conv.weight, bbox_head.cls_convs.0.gn.weight, bbox_head.cls_convs.0.gn.bias, bbox_head.cls_convs.1.conv.weight, bbox_head.cls_convs.1.gn.weight, bbox_head.cls_convs.1.gn.bias, bbox_head.cls_convs.2.conv.weight, bbox_head.cls_convs.2.gn.weight, bbox_head.cls_convs.2.gn.bias, bbox_head.cls_convs.3.conv.weight, bbox_head.cls_convs.3.gn.weight, bbox_head.cls_convs.3.gn.bias, bbox_head.reg_convs.0.conv.weight, bbox_head.reg_convs.0.gn.weight, bbox_head.reg_convs.0.gn.bias, bbox_head.reg_convs.1.conv.weight, bbox_head.reg_convs.1.gn.weight, bbox_head.reg_convs.1.gn.bias, bbox_head.reg_convs.2.conv.weight, bbox_head.reg_convs.2.gn.weight, bbox_head.reg_convs.2.gn.bias, bbox_head.reg_convs.3.conv.weight, bbox_head.reg_convs.3.gn.weight, bbox_head.reg_convs.3.gn.bias, bbox_head.gfl_cls.weight, bbox_head.gfl_cls.bias, bbox_head.gfl_reg.weight, bbox_head.gfl_reg.bias, bbox_head.scales.0.scale, bbox_head.scales.1.scale, bbox_head.scales.2.scale, bbox_head.scales.3.scale, bbox_head.scales.4.scale, bbox_head.integral.project

missing keys in source state_dict: conv1.weight, bn1.weight, bn1.bias, bn1.running_mean, bn1.running_var, layer1.0.conv1.weight, layer1.0.bn1.weight, layer1.0.bn1.bias, layer1.0.bn1.running_mean, layer1.0.bn1.running_var, layer1.0.conv2.weight, layer1.0.bn2.weight, layer1.0.bn2.bias, layer1.0.bn2.running_mean, layer1.0.bn2.running_var, layer1.1.conv1.weight, layer1.1.bn1.weight, layer1.1.bn1.bias, layer1.1.bn1.running_mean, layer1.1.bn1.running_var, layer1.1.conv2.weight, layer1.1.bn2.weight, layer1.1.bn2.bias, layer1.1.bn2.running_mean, layer1.1.bn2.running_var, layer2.0.conv1.weight, layer2.0.bn1.weight, layer2.0.bn1.bias, layer2.0.bn1.running_mean, layer2.0.bn1.running_var, layer2.0.conv2.weight, layer2.0.bn2.weight, layer2.0.bn2.bias, layer2.0.bn2.running_mean, layer2.0.bn2.running_var, layer2.0.downsample.0.weight, layer2.0.downsample.1.weight, layer2.0.downsample.1.bias, layer2.0.downsample.1.running_mean, layer2.0.downsample.1.running_var, layer2.1.conv1.weight, layer2.1.bn1.weight, layer2.1.bn1.bias, layer2.1.bn1.running_mean, layer2.1.bn1.running_var, layer2.1.conv2.weight, layer2.1.bn2.weight, layer2.1.bn2.bias, layer2.1.bn2.running_mean, layer2.1.bn2.running_var, layer3.0.conv1.weight, layer3.0.bn1.weight, layer3.0.bn1.bias, layer3.0.bn1.running_mean, layer3.0.bn1.running_var, layer3.0.conv2.weight, layer3.0.bn2.weight, layer3.0.bn2.bias, layer3.0.bn2.running_mean, layer3.0.bn2.running_var, layer3.0.downsample.0.weight, layer3.0.downsample.1.weight, layer3.0.downsample.1.bias, layer3.0.downsample.1.running_mean, layer3.0.downsample.1.running_var, layer3.1.conv1.weight, layer3.1.bn1.weight, layer3.1.bn1.bias, layer3.1.bn1.running_mean, layer3.1.bn1.running_var, layer3.1.conv2.weight, layer3.1.bn2.weight, layer3.1.bn2.bias, layer3.1.bn2.running_mean, layer3.1.bn2.running_var, layer4.0.conv1.weight, layer4.0.bn1.weight, layer4.0.bn1.bias, layer4.0.bn1.running_mean, layer4.0.bn1.running_var, layer4.0.conv2.weight, layer4.0.bn2.weight, layer4.0.bn2.bias, layer4.0.bn2.running_mean, layer4.0.bn2.running_var, layer4.0.downsample.0.weight, layer4.0.downsample.1.weight, layer4.0.downsample.1.bias, layer4.0.downsample.1.running_mean, layer4.0.downsample.1.running_var, layer4.1.conv1.weight, layer4.1.bn1.weight, layer4.1.bn1.bias, layer4.1.bn1.running_mean, layer4.1.bn1.running_var, layer4.1.conv2.weight, layer4.1.bn2.weight, layer4.1.bn2.bias, layer4.1.bn2.running_mean, layer4.1.bn2.running_var

Name of parameter - Initialization information

backbone.conv1.weight - torch.Size([64, 3, 7, 7]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.bn1.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.bn1.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.0.conv1.weight - torch.Size([64, 64, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.0.bn1.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.0.bn1.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.0.bn2.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.0.bn2.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.1.conv1.weight - torch.Size([64, 64, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.1.bn1.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.1.bn1.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.1.bn2.weight - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer1.1.bn2.bias - torch.Size([64]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.conv1.weight - torch.Size([128, 64, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.bn1.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.bn1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.bn2.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.bn2.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.downsample.0.weight - torch.Size([128, 64, 1, 1]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.downsample.1.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.0.downsample.1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.1.conv1.weight - torch.Size([128, 128, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.1.bn1.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.1.bn1.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.1.bn2.weight - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer2.1.bn2.bias - torch.Size([128]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.conv1.weight - torch.Size([256, 128, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.bn1.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.bn1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.bn2.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.bn2.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.downsample.0.weight - torch.Size([256, 128, 1, 1]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.downsample.1.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.0.downsample.1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.1.conv1.weight - torch.Size([256, 256, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.1.bn1.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.1.bn1.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.1.bn2.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer3.1.bn2.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.conv1.weight - torch.Size([512, 256, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.bn1.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.bn1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.bn2.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.bn2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.downsample.0.weight - torch.Size([512, 256, 1, 1]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.downsample.1.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.0.downsample.1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.1.conv1.weight - torch.Size([512, 512, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.1.bn1.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.1.bn1.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.1.bn2.weight - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

backbone.layer4.1.bn2.bias - torch.Size([512]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.lateral_convs.0.conv.weight - torch.Size([256, 128, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.0.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.lateral_convs.1.conv.weight - torch.Size([256, 256, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.1.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.lateral_convs.2.conv.weight - torch.Size([256, 512, 1, 1]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.lateral_convs.2.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.fpn_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.0.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.fpn_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.1.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.fpn_convs.2.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.2.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.fpn_convs.3.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.3.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

neck.fpn_convs.4.conv.weight - torch.Size([256, 256, 3, 3]): 
XavierInit: gain=1, distribution=uniform, bias=0 

neck.fpn_convs.4.conv.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.cls_convs.0.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.0.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.cls_convs.1.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.1.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.2.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.cls_convs.2.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.2.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.3.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.cls_convs.3.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.cls_convs.3.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.0.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.reg_convs.0.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.0.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.1.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.reg_convs.1.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.1.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.2.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.reg_convs.2.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.2.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.3.conv.weight - torch.Size([256, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.reg_convs.3.gn.weight - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.reg_convs.3.gn.bias - torch.Size([256]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.gfl_cls.weight - torch.Size([10, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=-4.59511985013459 

bbox_head.gfl_cls.bias - torch.Size([10]): 
NormalInit: mean=0, std=0.01, bias=-4.59511985013459 

bbox_head.gfl_reg.weight - torch.Size([68, 256, 3, 3]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.gfl_reg.bias - torch.Size([68]): 
NormalInit: mean=0, std=0.01, bias=0 

bbox_head.scales.0.scale - torch.Size([]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.scales.1.scale - torch.Size([]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.scales.2.scale - torch.Size([]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.scales.3.scale - torch.Size([]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  

bbox_head.scales.4.scale - torch.Size([]): 
The value is the same before and after calling `init_weights` of KnowledgeDistillationSingleStageDetector  
2023/07/13 08:59:49 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io
2023/07/13 08:59:49 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future.
2023/07/13 08:59:49 - mmengine - INFO - Checkpoints will be saved to mmdetection/work_dir/ld_gfl_r18_r101_fpn_1x_vis.
2023/07/13 09:00:12 - mmengine - INFO - Epoch(train)  [1][  50/3139]  lr: 1.2387e-04  eta: 4:51:04  time: 0.4643  data_time: 0.0102  memory: 726  loss: 2.8593  loss_cls: 0.0497  loss_bbox: 1.7562  loss_dfl: 0.6355  loss_ld: 0.4180
2023/07/13 09:00:28 - mmengine - INFO - Epoch(train)  [1][ 100/3139]  lr: 2.4900e-04  eta: 4:06:07  time: 0.3219  data_time: 0.0032  memory: 735  loss: 2.8364  loss_cls: 0.1487  loss_bbox: 1.4559  loss_dfl: 0.4698  loss_ld: 0.7620
2023/07/13 09:00:45 - mmengine - INFO - Epoch(train)  [1][ 150/3139]  lr: 3.7412e-04  eta: 3:51:05  time: 0.3225  data_time: 0.0032  memory: 728  loss: 2.8286  loss_cls: 0.1581  loss_bbox: 1.3511  loss_dfl: 0.4469  loss_ld: 0.8726
2023/07/13 09:01:01 - mmengine - INFO - Epoch(train)  [1][ 200/3139]  lr: 4.9925e-04  eta: 3:43:30  time: 0.3230  data_time: 0.0033  memory: 726  loss: 2.8752  loss_cls: 0.1716  loss_bbox: 1.3117  loss_dfl: 0.4379  loss_ld: 0.9539
2023/07/13 09:01:17 - mmengine - INFO - Epoch(train)  [1][ 250/3139]  lr: 6.2437e-04  eta: 3:38:54  time: 0.3234  data_time: 0.0034  memory: 734  loss: 2.7505  loss_cls: 0.2777  loss_bbox: 1.2401  loss_dfl: 0.4148  loss_ld: 0.8179
2023/07/13 09:01:33 - mmengine - INFO - Epoch(train)  [1][ 300/3139]  lr: 7.4950e-04  eta: 3:35:54  time: 0.3249  data_time: 0.0043  memory: 762  loss: 2.6779  loss_cls: 0.2078  loss_bbox: 1.2246  loss_dfl: 0.3988  loss_ld: 0.8467
2023/07/13 09:01:49 - mmengine - INFO - Epoch(train)  [1][ 350/3139]  lr: 8.7462e-04  eta: 3:33:27  time: 0.3224  data_time: 0.0035  memory: 727  loss: 2.7521  loss_cls: 0.2863  loss_bbox: 1.1349  loss_dfl: 0.4004  loss_ld: 0.9305
2023/07/13 09:02:05 - mmengine - INFO - Epoch(train)  [1][ 400/3139]  lr: 9.9975e-04  eta: 3:31:12  time: 0.3180  data_time: 0.0032  memory: 718  loss: 2.5842  loss_cls: 0.2757  loss_bbox: 1.1461  loss_dfl: 0.4002  loss_ld: 0.7622
2023/07/13 09:02:21 - mmengine - INFO - Epoch(train)  [1][ 450/3139]  lr: 1.1249e-03  eta: 3:29:55  time: 0.3255  data_time: 0.0044  memory: 715  loss: 2.7192  loss_cls: 0.2496  loss_bbox: 1.0995  loss_dfl: 0.3936  loss_ld: 0.9766
2023/07/13 09:02:37 - mmengine - INFO - Epoch(train)  [1][ 500/3139]  lr: 1.2500e-03  eta: 3:28:31  time: 0.3203  data_time: 0.0032  memory: 725  loss: 2.6099  loss_cls: 0.2229  loss_bbox: 1.1500  loss_dfl: 0.3945  loss_ld: 0.8425
2023/07/13 09:02:54 - mmengine - INFO - Epoch(train)  [1][ 550/3139]  lr: 1.2500e-03  eta: 3:27:30  time: 0.3237  data_time: 0.0036  memory: 731  loss: 2.4420  loss_cls: 0.4721  loss_bbox: 1.1231  loss_dfl: 0.3913  loss_ld: 0.4554
2023/07/13 09:03:10 - mmengine - INFO - Epoch(train)  [1][ 600/3139]  lr: 1.2500e-03  eta: 3:26:43  time: 0.3257  data_time: 0.0037  memory: 752  loss: 2.5645  loss_cls: 0.3175  loss_bbox: 1.1156  loss_dfl: 0.3883  loss_ld: 0.7430
2023/07/13 09:03:26 - mmengine - INFO - Epoch(train)  [1][ 650/3139]  lr: 1.2500e-03  eta: 3:25:55  time: 0.3236  data_time: 0.0040  memory: 717  loss: 2.4554  loss_cls: 0.3810  loss_bbox: 1.0707  loss_dfl: 0.3833  loss_ld: 0.6203
2023/07/13 09:03:42 - mmengine - INFO - Epoch(train)  [1][ 700/3139]  lr: 1.2500e-03  eta: 3:25:15  time: 0.3247  data_time: 0.0036  memory: 726  loss: 2.5690  loss_cls: 0.2448  loss_bbox: 1.0416  loss_dfl: 0.3644  loss_ld: 0.9182
2023/07/13 09:03:58 - mmengine - INFO - Epoch(train)  [1][ 750/3139]  lr: 1.2500e-03  eta: 3:24:32  time: 0.3224  data_time: 0.0038  memory: 725  loss: 2.3903  loss_cls: 0.2681  loss_bbox: 1.0477  loss_dfl: 0.3556  loss_ld: 0.7188
2023/07/13 09:04:15 - mmengine - INFO - Epoch(train)  [1][ 800/3139]  lr: 1.2500e-03  eta: 3:23:53  time: 0.3230  data_time: 0.0036  memory: 728  loss: 2.6587  loss_cls: 0.2732  loss_bbox: 1.0669  loss_dfl: 0.3701  loss_ld: 0.9483
2023/07/13 09:04:31 - mmengine - INFO - Epoch(train)  [1][ 850/3139]  lr: 1.2500e-03  eta: 3:23:25  time: 0.3265  data_time: 0.0047  memory: 746  loss: 2.5394  loss_cls: 0.2578  loss_bbox: 1.0237  loss_dfl: 0.3494  loss_ld: 0.9085
2023/07/13 09:04:47 - mmengine - INFO - Epoch(train)  [1][ 900/3139]  lr: 1.2500e-03  eta: 3:22:56  time: 0.3253  data_time: 0.0037  memory: 728  loss: 2.4551  loss_cls: 0.2998  loss_bbox: 1.0223  loss_dfl: 0.3577  loss_ld: 0.7753
2023/07/13 09:05:03 - mmengine - INFO - Epoch(train)  [1][ 950/3139]  lr: 1.2500e-03  eta: 3:22:27  time: 0.3247  data_time: 0.0037  memory: 721  loss: 2.5495  loss_cls: 0.2648  loss_bbox: 1.0234  loss_dfl: 0.3582  loss_ld: 0.9032
2023/07/13 09:05:19 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:05:19 - mmengine - INFO - Epoch(train)  [1][1000/3139]  lr: 1.2500e-03  eta: 3:21:47  time: 0.3180  data_time: 0.0035  memory: 736  loss: 2.4022  loss_cls: 0.2666  loss_bbox: 1.0429  loss_dfl: 0.3513  loss_ld: 0.7414
2023/07/13 09:05:35 - mmengine - INFO - Epoch(train)  [1][1050/3139]  lr: 1.2500e-03  eta: 3:21:16  time: 0.3220  data_time: 0.0043  memory: 723  loss: 2.2707  loss_cls: 0.5327  loss_bbox: 0.9849  loss_dfl: 0.3297  loss_ld: 0.4234
2023/07/13 09:05:52 - mmengine - INFO - Epoch(train)  [1][1100/3139]  lr: 1.2500e-03  eta: 3:20:49  time: 0.3235  data_time: 0.0038  memory: 716  loss: 2.3549  loss_cls: 0.2943  loss_bbox: 1.0201  loss_dfl: 0.3505  loss_ld: 0.6900
2023/07/13 09:06:08 - mmengine - INFO - Epoch(train)  [1][1150/3139]  lr: 1.2500e-03  eta: 3:20:22  time: 0.3228  data_time: 0.0039  memory: 718  loss: 2.2110  loss_cls: 0.3172  loss_bbox: 0.9607  loss_dfl: 0.3248  loss_ld: 0.6083
2023/07/13 09:06:24 - mmengine - INFO - Epoch(train)  [1][1200/3139]  lr: 1.2500e-03  eta: 3:19:52  time: 0.3199  data_time: 0.0033  memory: 719  loss: 2.5678  loss_cls: 0.2996  loss_bbox: 0.9581  loss_dfl: 0.3483  loss_ld: 0.9618
2023/07/13 09:06:40 - mmengine - INFO - Epoch(train)  [1][1250/3139]  lr: 1.2500e-03  eta: 3:19:27  time: 0.3232  data_time: 0.0036  memory: 726  loss: 2.2851  loss_cls: 0.2567  loss_bbox: 1.0031  loss_dfl: 0.3344  loss_ld: 0.6910
2023/07/13 09:06:56 - mmengine - INFO - Epoch(train)  [1][1300/3139]  lr: 1.2500e-03  eta: 3:19:02  time: 0.3226  data_time: 0.0035  memory: 714  loss: 2.4766  loss_cls: 0.2856  loss_bbox: 0.9674  loss_dfl: 0.3455  loss_ld: 0.8780
2023/07/13 09:07:12 - mmengine - INFO - Epoch(train)  [1][1350/3139]  lr: 1.2500e-03  eta: 3:18:40  time: 0.3239  data_time: 0.0039  memory: 728  loss: 2.5335  loss_cls: 0.3209  loss_bbox: 0.9661  loss_dfl: 0.3481  loss_ld: 0.8984
2023/07/13 09:07:28 - mmengine - INFO - Epoch(train)  [1][1400/3139]  lr: 1.2500e-03  eta: 3:18:16  time: 0.3224  data_time: 0.0035  memory: 734  loss: 2.3318  loss_cls: 0.3507  loss_bbox: 0.9512  loss_dfl: 0.3247  loss_ld: 0.7052
2023/07/13 09:07:44 - mmengine - INFO - Epoch(train)  [1][1450/3139]  lr: 1.2500e-03  eta: 3:17:53  time: 0.3227  data_time: 0.0041  memory: 740  loss: 2.4525  loss_cls: 0.2690  loss_bbox: 0.9553  loss_dfl: 0.3351  loss_ld: 0.8930
2023/07/13 09:08:01 - mmengine - INFO - Epoch(train)  [1][1500/3139]  lr: 1.2500e-03  eta: 3:17:30  time: 0.3224  data_time: 0.0043  memory: 731  loss: 2.3288  loss_cls: 0.2671  loss_bbox: 0.9753  loss_dfl: 0.3258  loss_ld: 0.7606
2023/07/13 09:08:17 - mmengine - INFO - Epoch(train)  [1][1550/3139]  lr: 1.2500e-03  eta: 3:17:12  time: 0.3267  data_time: 0.0040  memory: 730  loss: 2.3856  loss_cls: 0.2628  loss_bbox: 0.8593  loss_dfl: 0.3091  loss_ld: 0.9545
2023/07/13 09:08:33 - mmengine - INFO - Epoch(train)  [1][1600/3139]  lr: 1.2500e-03  eta: 3:16:53  time: 0.3248  data_time: 0.0042  memory: 731  loss: 2.2865  loss_cls: 0.3131  loss_bbox: 0.8571  loss_dfl: 0.3039  loss_ld: 0.8124
2023/07/13 09:08:49 - mmengine - INFO - Epoch(train)  [1][1650/3139]  lr: 1.2500e-03  eta: 3:16:32  time: 0.3233  data_time: 0.0039  memory: 727  loss: 2.2641  loss_cls: 0.3056  loss_bbox: 0.9180  loss_dfl: 0.3223  loss_ld: 0.7182
2023/07/13 09:09:05 - mmengine - INFO - Epoch(train)  [1][1700/3139]  lr: 1.2500e-03  eta: 3:16:10  time: 0.3223  data_time: 0.0035  memory: 721  loss: 2.3271  loss_cls: 0.2757  loss_bbox: 0.9004  loss_dfl: 0.3115  loss_ld: 0.8394
2023/07/13 09:09:22 - mmengine - INFO - Epoch(train)  [1][1750/3139]  lr: 1.2500e-03  eta: 3:15:49  time: 0.3225  data_time: 0.0037  memory: 722  loss: 2.1586  loss_cls: 0.3351  loss_bbox: 0.9035  loss_dfl: 0.3016  loss_ld: 0.6184
2023/07/13 09:09:38 - mmengine - INFO - Epoch(train)  [1][1800/3139]  lr: 1.2500e-03  eta: 3:15:32  time: 0.3271  data_time: 0.0040  memory: 730  loss: 2.2740  loss_cls: 0.2776  loss_bbox: 0.9105  loss_dfl: 0.3151  loss_ld: 0.7707
2023/07/13 09:09:54 - mmengine - INFO - Epoch(train)  [1][1850/3139]  lr: 1.2500e-03  eta: 3:15:11  time: 0.3215  data_time: 0.0037  memory: 749  loss: 2.2827  loss_cls: 0.2938  loss_bbox: 0.8489  loss_dfl: 0.3241  loss_ld: 0.8158
2023/07/13 09:10:10 - mmengine - INFO - Epoch(train)  [1][1900/3139]  lr: 1.2500e-03  eta: 3:14:51  time: 0.3233  data_time: 0.0040  memory: 721  loss: 2.2303  loss_cls: 0.2871  loss_bbox: 0.9360  loss_dfl: 0.3187  loss_ld: 0.6886
2023/07/13 09:10:26 - mmengine - INFO - Epoch(train)  [1][1950/3139]  lr: 1.2500e-03  eta: 3:14:28  time: 0.3201  data_time: 0.0035  memory: 722  loss: 2.1642  loss_cls: 0.2894  loss_bbox: 0.8575  loss_dfl: 0.2940  loss_ld: 0.7232
2023/07/13 09:10:42 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:10:42 - mmengine - INFO - Epoch(train)  [1][2000/3139]  lr: 1.2500e-03  eta: 3:14:11  time: 0.3252  data_time: 0.0033  memory: 723  loss: 2.2237  loss_cls: 0.3377  loss_bbox: 0.8221  loss_dfl: 0.3112  loss_ld: 0.7527
2023/07/13 09:10:59 - mmengine - INFO - Epoch(train)  [1][2050/3139]  lr: 1.2500e-03  eta: 3:13:52  time: 0.3242  data_time: 0.0040  memory: 716  loss: 2.1239  loss_cls: 0.2976  loss_bbox: 0.8956  loss_dfl: 0.3111  loss_ld: 0.6196
2023/07/13 09:11:15 - mmengine - INFO - Epoch(train)  [1][2100/3139]  lr: 1.2500e-03  eta: 3:13:33  time: 0.3232  data_time: 0.0038  memory: 713  loss: 2.2035  loss_cls: 0.2751  loss_bbox: 0.8657  loss_dfl: 0.3090  loss_ld: 0.7537
2023/07/13 09:11:31 - mmengine - INFO - Epoch(train)  [1][2150/3139]  lr: 1.2500e-03  eta: 3:13:14  time: 0.3235  data_time: 0.0035  memory: 732  loss: 2.3374  loss_cls: 0.2631  loss_bbox: 0.8443  loss_dfl: 0.3060  loss_ld: 0.9240
2023/07/13 09:11:47 - mmengine - INFO - Epoch(train)  [1][2200/3139]  lr: 1.2500e-03  eta: 3:12:55  time: 0.3224  data_time: 0.0036  memory: 722  loss: 2.1256  loss_cls: 0.2977  loss_bbox: 0.8422  loss_dfl: 0.2959  loss_ld: 0.6898
2023/07/13 09:12:03 - mmengine - INFO - Epoch(train)  [1][2250/3139]  lr: 1.2500e-03  eta: 3:12:34  time: 0.3216  data_time: 0.0037  memory: 718  loss: 2.1131  loss_cls: 0.2979  loss_bbox: 0.8392  loss_dfl: 0.2979  loss_ld: 0.6782
2023/07/13 09:12:19 - mmengine - INFO - Epoch(train)  [1][2300/3139]  lr: 1.2500e-03  eta: 3:12:15  time: 0.3218  data_time: 0.0037  memory: 723  loss: 2.2634  loss_cls: 0.2936  loss_bbox: 0.8086  loss_dfl: 0.3019  loss_ld: 0.8593
2023/07/13 09:12:35 - mmengine - INFO - Epoch(train)  [1][2350/3139]  lr: 1.2500e-03  eta: 3:11:55  time: 0.3214  data_time: 0.0037  memory: 720  loss: 2.1510  loss_cls: 0.3258  loss_bbox: 0.8311  loss_dfl: 0.2962  loss_ld: 0.6979
2023/07/13 09:12:51 - mmengine - INFO - Epoch(train)  [1][2400/3139]  lr: 1.2500e-03  eta: 3:11:35  time: 0.3206  data_time: 0.0042  memory: 730  loss: 2.3122  loss_cls: 0.7657  loss_bbox: 0.8856  loss_dfl: 0.3006  loss_ld: 0.3602
2023/07/13 09:13:08 - mmengine - INFO - Epoch(train)  [1][2450/3139]  lr: 1.2500e-03  eta: 3:11:16  time: 0.3226  data_time: 0.0038  memory: 735  loss: 2.1597  loss_cls: 0.3952  loss_bbox: 0.8340  loss_dfl: 0.3073  loss_ld: 0.6231
2023/07/13 09:13:24 - mmengine - INFO - Epoch(train)  [1][2500/3139]  lr: 1.2500e-03  eta: 3:10:56  time: 0.3206  data_time: 0.0035  memory: 722  loss: 2.1330  loss_cls: 0.3067  loss_bbox: 0.8367  loss_dfl: 0.2961  loss_ld: 0.6935
2023/07/13 09:13:40 - mmengine - INFO - Epoch(train)  [1][2550/3139]  lr: 1.2500e-03  eta: 3:10:36  time: 0.3202  data_time: 0.0037  memory: 723  loss: 2.0319  loss_cls: 0.4225  loss_bbox: 0.8425  loss_dfl: 0.2964  loss_ld: 0.4705
2023/07/13 09:13:56 - mmengine - INFO - Epoch(train)  [1][2600/3139]  lr: 1.2500e-03  eta: 3:10:17  time: 0.3223  data_time: 0.0045  memory: 738  loss: 2.1100  loss_cls: 0.3306  loss_bbox: 0.8441  loss_dfl: 0.2945  loss_ld: 0.6407
2023/07/13 09:14:12 - mmengine - INFO - Epoch(train)  [1][2650/3139]  lr: 1.2500e-03  eta: 3:09:59  time: 0.3222  data_time: 0.0033  memory: 728  loss: 2.0686  loss_cls: 0.3202  loss_bbox: 0.8319  loss_dfl: 0.2910  loss_ld: 0.6254
2023/07/13 09:14:28 - mmengine - INFO - Epoch(train)  [1][2700/3139]  lr: 1.2500e-03  eta: 3:09:41  time: 0.3241  data_time: 0.0034  memory: 737  loss: 2.1032  loss_cls: 0.4505  loss_bbox: 0.8201  loss_dfl: 0.2842  loss_ld: 0.5483
2023/07/13 09:14:44 - mmengine - INFO - Epoch(train)  [1][2750/3139]  lr: 1.2500e-03  eta: 3:09:24  time: 0.3232  data_time: 0.0039  memory: 719  loss: 2.0519  loss_cls: 0.3435  loss_bbox: 0.8369  loss_dfl: 0.2891  loss_ld: 0.5824
2023/07/13 09:15:00 - mmengine - INFO - Epoch(train)  [1][2800/3139]  lr: 1.2500e-03  eta: 3:09:06  time: 0.3233  data_time: 0.0042  memory: 738  loss: 1.9789  loss_cls: 0.3233  loss_bbox: 0.7799  loss_dfl: 0.2734  loss_ld: 0.6024
2023/07/13 09:15:17 - mmengine - INFO - Epoch(train)  [1][2850/3139]  lr: 1.2500e-03  eta: 3:08:49  time: 0.3249  data_time: 0.0038  memory: 731  loss: 2.0823  loss_cls: 0.3069  loss_bbox: 0.8366  loss_dfl: 0.2891  loss_ld: 0.6497
2023/07/13 09:15:33 - mmengine - INFO - Epoch(train)  [1][2900/3139]  lr: 1.2500e-03  eta: 3:08:32  time: 0.3230  data_time: 0.0033  memory: 716  loss: 2.1838  loss_cls: 0.3102  loss_bbox: 0.8087  loss_dfl: 0.2888  loss_ld: 0.7760
2023/07/13 09:15:49 - mmengine - INFO - Epoch(train)  [1][2950/3139]  lr: 1.2500e-03  eta: 3:08:15  time: 0.3251  data_time: 0.0038  memory: 737  loss: 2.1450  loss_cls: 0.3113  loss_bbox: 0.8374  loss_dfl: 0.2961  loss_ld: 0.7001
2023/07/13 09:16:05 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:16:05 - mmengine - INFO - Epoch(train)  [1][3000/3139]  lr: 1.2500e-03  eta: 3:07:58  time: 0.3233  data_time: 0.0040  memory: 729  loss: 2.0610  loss_cls: 0.3165  loss_bbox: 0.8524  loss_dfl: 0.2961  loss_ld: 0.5960
2023/07/13 09:16:21 - mmengine - INFO - Epoch(train)  [1][3050/3139]  lr: 1.2500e-03  eta: 3:07:41  time: 0.3246  data_time: 0.0038  memory: 718  loss: 2.0545  loss_cls: 0.3105  loss_bbox: 0.7869  loss_dfl: 0.2838  loss_ld: 0.6733
2023/07/13 09:16:38 - mmengine - INFO - Epoch(train)  [1][3100/3139]  lr: 1.2500e-03  eta: 3:07:24  time: 0.3236  data_time: 0.0035  memory: 719  loss: 2.1269  loss_cls: 0.3013  loss_bbox: 0.8114  loss_dfl: 0.2933  loss_ld: 0.7210
2023/07/13 09:16:50 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:16:50 - mmengine - INFO - Saving checkpoint at 1 epochs
2023/07/13 09:16:57 - mmengine - INFO - Epoch(val)  [1][ 50/548]    eta: 0:00:43  time: 0.0875  data_time: 0.0058  memory: 725  
2023/07/13 09:17:01 - mmengine - INFO - Epoch(val)  [1][100/548]    eta: 0:00:37  time: 0.0814  data_time: 0.0017  memory: 497  
2023/07/13 09:17:05 - mmengine - INFO - Epoch(val)  [1][150/548]    eta: 0:00:33  time: 0.0811  data_time: 0.0015  memory: 497  
2023/07/13 09:17:09 - mmengine - INFO - Epoch(val)  [1][200/548]    eta: 0:00:28  time: 0.0804  data_time: 0.0015  memory: 497  
2023/07/13 09:17:13 - mmengine - INFO - Epoch(val)  [1][250/548]    eta: 0:00:24  time: 0.0808  data_time: 0.0015  memory: 497  
2023/07/13 09:17:17 - mmengine - INFO - Epoch(val)  [1][300/548]    eta: 0:00:20  time: 0.0804  data_time: 0.0015  memory: 497  
2023/07/13 09:17:21 - mmengine - INFO - Epoch(val)  [1][350/548]    eta: 0:00:16  time: 0.0799  data_time: 0.0015  memory: 497  
2023/07/13 09:17:25 - mmengine - INFO - Epoch(val)  [1][400/548]    eta: 0:00:12  time: 0.0801  data_time: 0.0014  memory: 497  
2023/07/13 09:17:29 - mmengine - INFO - Epoch(val)  [1][450/548]    eta: 0:00:07  time: 0.0776  data_time: 0.0014  memory: 497  
2023/07/13 09:17:33 - mmengine - INFO - Epoch(val)  [1][500/548]    eta: 0:00:03  time: 0.0789  data_time: 0.0015  memory: 497  
2023/07/13 09:17:37 - mmengine - INFO - Evaluating bbox...
2023/07/13 09:17:54 - mmengine - INFO - bbox_mAP_copypaste: 0.031 0.067 0.024 0.007 0.048 0.097
2023/07/13 09:17:54 - mmengine - INFO - Epoch(val) [1][548/548]    coco/bbox_mAP: 0.0310  coco/bbox_mAP_50: 0.0670  coco/bbox_mAP_75: 0.0240  coco/bbox_mAP_s: 0.0070  coco/bbox_mAP_m: 0.0480  coco/bbox_mAP_l: 0.0970  data_time: 0.0019  time: 0.0802
2023/07/13 09:18:10 - mmengine - INFO - Epoch(train)  [2][  50/3139]  lr: 1.2500e-03  eta: 3:06:55  time: 0.3250  data_time: 0.0054  memory: 718  loss: 2.0558  loss_cls: 0.3033  loss_bbox: 0.8179  loss_dfl: 0.2912  loss_ld: 0.6434
2023/07/13 09:18:26 - mmengine - INFO - Epoch(train)  [2][ 100/3139]  lr: 1.2500e-03  eta: 3:06:38  time: 0.3239  data_time: 0.0039  memory: 726  loss: 2.0286  loss_cls: 0.3108  loss_bbox: 0.7554  loss_dfl: 0.2671  loss_ld: 0.6952
2023/07/13 09:18:42 - mmengine - INFO - Epoch(train)  [2][ 150/3139]  lr: 1.2500e-03  eta: 3:06:21  time: 0.3244  data_time: 0.0035  memory: 761  loss: 1.9695  loss_cls: 0.3787  loss_bbox: 0.8066  loss_dfl: 0.2699  loss_ld: 0.5144
2023/07/13 09:18:59 - mmengine - INFO - Epoch(train)  [2][ 200/3139]  lr: 1.2500e-03  eta: 3:06:04  time: 0.3236  data_time: 0.0033  memory: 725  loss: 2.0286  loss_cls: 0.3670  loss_bbox: 0.8487  loss_dfl: 0.2991  loss_ld: 0.5138
2023/07/13 09:19:15 - mmengine - INFO - Epoch(train)  [2][ 250/3139]  lr: 1.2500e-03  eta: 3:05:48  time: 0.3242  data_time: 0.0043  memory: 722  loss: 2.0063  loss_cls: 0.3011  loss_bbox: 0.7753  loss_dfl: 0.2722  loss_ld: 0.6577
2023/07/13 09:19:31 - mmengine - INFO - Epoch(train)  [2][ 300/3139]  lr: 1.2500e-03  eta: 3:05:29  time: 0.3202  data_time: 0.0034  memory: 729  loss: 2.0693  loss_cls: 0.3063  loss_bbox: 0.7949  loss_dfl: 0.2754  loss_ld: 0.6926
2023/07/13 09:19:47 - mmengine - INFO - Epoch(train)  [2][ 350/3139]  lr: 1.2500e-03  eta: 3:05:12  time: 0.3246  data_time: 0.0038  memory: 716  loss: 1.9857  loss_cls: 0.3404  loss_bbox: 0.7884  loss_dfl: 0.2801  loss_ld: 0.5768
2023/07/13 09:20:03 - mmengine - INFO - Epoch(train)  [2][ 400/3139]  lr: 1.2500e-03  eta: 3:04:54  time: 0.3203  data_time: 0.0036  memory: 748  loss: 1.9519  loss_cls: 0.3383  loss_bbox: 0.7646  loss_dfl: 0.2705  loss_ld: 0.5785
2023/07/13 09:20:19 - mmengine - INFO - Epoch(train)  [2][ 450/3139]  lr: 1.2500e-03  eta: 3:04:37  time: 0.3246  data_time: 0.0038  memory: 728  loss: 2.0275  loss_cls: 0.3325  loss_bbox: 0.7809  loss_dfl: 0.2818  loss_ld: 0.6323
2023/07/13 09:20:36 - mmengine - INFO - Epoch(train)  [2][ 500/3139]  lr: 1.2500e-03  eta: 3:04:22  time: 0.3274  data_time: 0.0040  memory: 722  loss: 2.1411  loss_cls: 0.3269  loss_bbox: 0.7443  loss_dfl: 0.2810  loss_ld: 0.7889
2023/07/13 09:20:52 - mmengine - INFO - Epoch(train)  [2][ 550/3139]  lr: 1.2500e-03  eta: 3:04:05  time: 0.3225  data_time: 0.0036  memory: 725  loss: 1.9630  loss_cls: 0.3111  loss_bbox: 0.7642  loss_dfl: 0.2778  loss_ld: 0.6100
2023/07/13 09:21:08 - mmengine - INFO - Epoch(train)  [2][ 600/3139]  lr: 1.2500e-03  eta: 3:03:47  time: 0.3225  data_time: 0.0034  memory: 730  loss: 2.0902  loss_cls: 0.3224  loss_bbox: 0.7505  loss_dfl: 0.2831  loss_ld: 0.7342
2023/07/13 09:21:24 - mmengine - INFO - Epoch(train)  [2][ 650/3139]  lr: 1.2500e-03  eta: 3:03:30  time: 0.3233  data_time: 0.0037  memory: 724  loss: 1.8091  loss_cls: 0.3269  loss_bbox: 0.7080  loss_dfl: 0.2486  loss_ld: 0.5256
2023/07/13 09:21:40 - mmengine - INFO - Epoch(train)  [2][ 700/3139]  lr: 1.2500e-03  eta: 3:03:13  time: 0.3225  data_time: 0.0040  memory: 716  loss: 1.9109  loss_cls: 0.3289  loss_bbox: 0.7713  loss_dfl: 0.2799  loss_ld: 0.5308
2023/07/13 09:21:56 - mmengine - INFO - Epoch(train)  [2][ 750/3139]  lr: 1.2500e-03  eta: 3:02:56  time: 0.3233  data_time: 0.0043  memory: 728  loss: 2.0026  loss_cls: 0.3085  loss_bbox: 0.7894  loss_dfl: 0.2758  loss_ld: 0.6289
2023/07/13 09:22:13 - mmengine - INFO - Epoch(train)  [2][ 800/3139]  lr: 1.2500e-03  eta: 3:02:40  time: 0.3251  data_time: 0.0045  memory: 731  loss: 1.8804  loss_cls: 0.3210  loss_bbox: 0.7396  loss_dfl: 0.2668  loss_ld: 0.5530
2023/07/13 09:22:29 - mmengine - INFO - Epoch(train)  [2][ 850/3139]  lr: 1.2500e-03  eta: 3:02:21  time: 0.3199  data_time: 0.0033  memory: 723  loss: 1.9802  loss_cls: 0.3337  loss_bbox: 0.7190  loss_dfl: 0.2613  loss_ld: 0.6663
2023/07/13 09:22:32 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:22:45 - mmengine - INFO - Epoch(train)  [2][ 900/3139]  lr: 1.2500e-03  eta: 3:02:05  time: 0.3248  data_time: 0.0038  memory: 731  loss: 2.0623  loss_cls: 0.2714  loss_bbox: 0.7810  loss_dfl: 0.2799  loss_ld: 0.7300
2023/07/13 09:23:01 - mmengine - INFO - Epoch(train)  [2][ 950/3139]  lr: 1.2500e-03  eta: 3:01:48  time: 0.3230  data_time: 0.0034  memory: 746  loss: 1.8590  loss_cls: 0.2915  loss_bbox: 0.7538  loss_dfl: 0.2669  loss_ld: 0.5467
2023/07/13 09:23:17 - mmengine - INFO - Epoch(train)  [2][1000/3139]  lr: 1.2500e-03  eta: 3:01:31  time: 0.3237  data_time: 0.0039  memory: 720  loss: 1.9172  loss_cls: 0.3102  loss_bbox: 0.7668  loss_dfl: 0.2671  loss_ld: 0.5733
2023/07/13 09:23:33 - mmengine - INFO - Epoch(train)  [2][1050/3139]  lr: 1.2500e-03  eta: 3:01:13  time: 0.3206  data_time: 0.0034  memory: 720  loss: 1.8737  loss_cls: 0.3256  loss_bbox: 0.7144  loss_dfl: 0.2580  loss_ld: 0.5756
2023/07/13 09:23:49 - mmengine - INFO - Epoch(train)  [2][1100/3139]  lr: 1.2500e-03  eta: 3:00:57  time: 0.3258  data_time: 0.0038  memory: 739  loss: 1.9443  loss_cls: 0.3277  loss_bbox: 0.7204  loss_dfl: 0.2713  loss_ld: 0.6248
2023/07/13 09:24:06 - mmengine - INFO - Epoch(train)  [2][1150/3139]  lr: 1.2500e-03  eta: 3:00:41  time: 0.3241  data_time: 0.0040  memory: 738  loss: 1.9872  loss_cls: 0.2868  loss_bbox: 0.7940  loss_dfl: 0.2785  loss_ld: 0.6280
2023/07/13 09:24:22 - mmengine - INFO - Epoch(train)  [2][1200/3139]  lr: 1.2500e-03  eta: 3:00:24  time: 0.3241  data_time: 0.0036  memory: 735  loss: 1.9264  loss_cls: 0.3261  loss_bbox: 0.7162  loss_dfl: 0.2589  loss_ld: 0.6251
2023/07/13 09:24:38 - mmengine - INFO - Epoch(train)  [2][1250/3139]  lr: 1.2500e-03  eta: 3:00:07  time: 0.3219  data_time: 0.0034  memory: 734  loss: 1.9784  loss_cls: 0.3095  loss_bbox: 0.7702  loss_dfl: 0.2738  loss_ld: 0.6249
2023/07/13 09:24:54 - mmengine - INFO - Epoch(train)  [2][1300/3139]  lr: 1.2500e-03  eta: 2:59:50  time: 0.3232  data_time: 0.0036  memory: 724  loss: 2.0347  loss_cls: 0.2970  loss_bbox: 0.7701  loss_dfl: 0.2739  loss_ld: 0.6937
2023/07/13 09:25:10 - mmengine - INFO - Epoch(train)  [2][1350/3139]  lr: 1.2500e-03  eta: 2:59:33  time: 0.3212  data_time: 0.0035  memory: 726  loss: 2.0080  loss_cls: 0.2750  loss_bbox: 0.7498  loss_dfl: 0.2679  loss_ld: 0.7153
2023/07/13 09:25:26 - mmengine - INFO - Epoch(train)  [2][1400/3139]  lr: 1.2500e-03  eta: 2:59:15  time: 0.3201  data_time: 0.0037  memory: 719  loss: 1.8600  loss_cls: 0.3123  loss_bbox: 0.7422  loss_dfl: 0.2567  loss_ld: 0.5488
2023/07/13 09:25:42 - mmengine - INFO - Epoch(train)  [2][1450/3139]  lr: 1.2500e-03  eta: 2:58:58  time: 0.3226  data_time: 0.0036  memory: 725  loss: 1.7912  loss_cls: 0.3119  loss_bbox: 0.7084  loss_dfl: 0.2505  loss_ld: 0.5204
2023/07/13 09:25:58 - mmengine - INFO - Epoch(train)  [2][1500/3139]  lr: 1.2500e-03  eta: 2:58:40  time: 0.3214  data_time: 0.0038  memory: 718  loss: 1.8293  loss_cls: 0.3279  loss_bbox: 0.7110  loss_dfl: 0.2525  loss_ld: 0.5379
2023/07/13 09:26:15 - mmengine - INFO - Epoch(train)  [2][1550/3139]  lr: 1.2500e-03  eta: 2:58:24  time: 0.3228  data_time: 0.0037  memory: 718  loss: 1.9348  loss_cls: 0.3098  loss_bbox: 0.7497  loss_dfl: 0.2682  loss_ld: 0.6071
2023/07/13 09:26:31 - mmengine - INFO - Epoch(train)  [2][1600/3139]  lr: 1.2500e-03  eta: 2:58:07  time: 0.3238  data_time: 0.0046  memory: 720  loss: 1.8630  loss_cls: 0.2764  loss_bbox: 0.7121  loss_dfl: 0.2573  loss_ld: 0.6173
2023/07/13 09:26:47 - mmengine - INFO - Epoch(train)  [2][1650/3139]  lr: 1.2500e-03  eta: 2:57:50  time: 0.3219  data_time: 0.0037  memory: 717  loss: 1.9354  loss_cls: 0.3247  loss_bbox: 0.7084  loss_dfl: 0.2811  loss_ld: 0.6211
2023/07/13 09:27:03 - mmengine - INFO - Epoch(train)  [2][1700/3139]  lr: 1.2500e-03  eta: 2:57:34  time: 0.3266  data_time: 0.0048  memory: 734  loss: 1.8319  loss_cls: 0.3123  loss_bbox: 0.7048  loss_dfl: 0.2617  loss_ld: 0.5531
2023/07/13 09:27:19 - mmengine - INFO - Epoch(train)  [2][1750/3139]  lr: 1.2500e-03  eta: 2:57:18  time: 0.3227  data_time: 0.0039  memory: 727  loss: 1.8714  loss_cls: 0.3081  loss_bbox: 0.6823  loss_dfl: 0.2552  loss_ld: 0.6258
2023/07/13 09:27:36 - mmengine - INFO - Epoch(train)  [2][1800/3139]  lr: 1.2500e-03  eta: 2:57:02  time: 0.3251  data_time: 0.0041  memory: 720  loss: 1.9765  loss_cls: 0.3413  loss_bbox: 0.6715  loss_dfl: 0.2611  loss_ld: 0.7026
2023/07/13 09:27:52 - mmengine - INFO - Epoch(train)  [2][1850/3139]  lr: 1.2500e-03  eta: 2:56:45  time: 0.3238  data_time: 0.0037  memory: 728  loss: 1.8822  loss_cls: 0.3238  loss_bbox: 0.7194  loss_dfl: 0.2648  loss_ld: 0.5742
2023/07/13 09:27:55 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:28:08 - mmengine - INFO - Epoch(train)  [2][1900/3139]  lr: 1.2500e-03  eta: 2:56:29  time: 0.3258  data_time: 0.0053  memory: 736  loss: 1.9576  loss_cls: 0.3062  loss_bbox: 0.7264  loss_dfl: 0.2701  loss_ld: 0.6549
2023/07/13 09:28:24 - mmengine - INFO - Epoch(train)  [2][1950/3139]  lr: 1.2500e-03  eta: 2:56:12  time: 0.3211  data_time: 0.0039  memory: 752  loss: 1.9770  loss_cls: 0.3051  loss_bbox: 0.7281  loss_dfl: 0.2630  loss_ld: 0.6809
2023/07/13 09:28:40 - mmengine - INFO - Epoch(train)  [2][2000/3139]  lr: 1.2500e-03  eta: 2:55:56  time: 0.3241  data_time: 0.0042  memory: 735  loss: 1.9473  loss_cls: 0.3038  loss_bbox: 0.7434  loss_dfl: 0.2653  loss_ld: 0.6347
2023/07/13 09:28:56 - mmengine - INFO - Epoch(train)  [2][2050/3139]  lr: 1.2500e-03  eta: 2:55:39  time: 0.3234  data_time: 0.0038  memory: 724  loss: 1.8560  loss_cls: 0.2922  loss_bbox: 0.7566  loss_dfl: 0.2661  loss_ld: 0.5411
2023/07/13 09:29:13 - mmengine - INFO - Epoch(train)  [2][2100/3139]  lr: 1.2500e-03  eta: 2:55:22  time: 0.3233  data_time: 0.0038  memory: 721  loss: 1.9887  loss_cls: 0.2847  loss_bbox: 0.7514  loss_dfl: 0.2719  loss_ld: 0.6808
2023/07/13 09:29:29 - mmengine - INFO - Epoch(train)  [2][2150/3139]  lr: 1.2500e-03  eta: 2:55:07  time: 0.3263  data_time: 0.0035  memory: 716  loss: 1.8883  loss_cls: 0.2965  loss_bbox: 0.7605  loss_dfl: 0.2633  loss_ld: 0.5680
2023/07/13 09:29:45 - mmengine - INFO - Epoch(train)  [2][2200/3139]  lr: 1.2500e-03  eta: 2:54:51  time: 0.3268  data_time: 0.0044  memory: 724  loss: 1.8254  loss_cls: 0.3345  loss_bbox: 0.7304  loss_dfl: 0.2607  loss_ld: 0.4997
2023/07/13 09:30:01 - mmengine - INFO - Epoch(train)  [2][2250/3139]  lr: 1.2500e-03  eta: 2:54:35  time: 0.3234  data_time: 0.0035  memory: 728  loss: 1.9334  loss_cls: 0.2764  loss_bbox: 0.7136  loss_dfl: 0.2621  loss_ld: 0.6813
2023/07/13 09:30:17 - mmengine - INFO - Epoch(train)  [2][2300/3139]  lr: 1.2500e-03  eta: 2:54:17  time: 0.3200  data_time: 0.0035  memory: 723  loss: 1.8456  loss_cls: 0.3174  loss_bbox: 0.6934  loss_dfl: 0.2487  loss_ld: 0.5861
2023/07/13 09:30:34 - mmengine - INFO - Epoch(train)  [2][2350/3139]  lr: 1.2500e-03  eta: 2:54:01  time: 0.3252  data_time: 0.0035  memory: 727  loss: 1.8935  loss_cls: 0.3127  loss_bbox: 0.7063  loss_dfl: 0.2561  loss_ld: 0.6184
2023/07/13 09:30:50 - mmengine - INFO - Epoch(train)  [2][2400/3139]  lr: 1.2500e-03  eta: 2:53:45  time: 0.3242  data_time: 0.0035  memory: 719  loss: 1.9534  loss_cls: 0.2927  loss_bbox: 0.7259  loss_dfl: 0.2734  loss_ld: 0.6614
2023/07/13 09:31:06 - mmengine - INFO - Epoch(train)  [2][2450/3139]  lr: 1.2500e-03  eta: 2:53:28  time: 0.3229  data_time: 0.0041  memory: 723  loss: 1.8156  loss_cls: 0.2992  loss_bbox: 0.7202  loss_dfl: 0.2554  loss_ld: 0.5408
2023/07/13 09:31:22 - mmengine - INFO - Epoch(train)  [2][2500/3139]  lr: 1.2500e-03  eta: 2:53:11  time: 0.3198  data_time: 0.0035  memory: 720  loss: 1.8135  loss_cls: 0.3204  loss_bbox: 0.7004  loss_dfl: 0.2479  loss_ld: 0.5448
2023/07/13 09:31:38 - mmengine - INFO - Epoch(train)  [2][2550/3139]  lr: 1.2500e-03  eta: 2:52:53  time: 0.3196  data_time: 0.0034  memory: 716  loss: 1.9388  loss_cls: 0.3347  loss_bbox: 0.6979  loss_dfl: 0.2593  loss_ld: 0.6469
2023/07/13 09:31:54 - mmengine - INFO - Epoch(train)  [2][2600/3139]  lr: 1.2500e-03  eta: 2:52:37  time: 0.3245  data_time: 0.0036  memory: 725  loss: 1.8589  loss_cls: 0.3147  loss_bbox: 0.6931  loss_dfl: 0.2517  loss_ld: 0.5994
2023/07/13 09:32:11 - mmengine - INFO - Epoch(train)  [2][2650/3139]  lr: 1.2500e-03  eta: 2:52:21  time: 0.3262  data_time: 0.0049  memory: 731  loss: 1.8815  loss_cls: 0.3208  loss_bbox: 0.7220  loss_dfl: 0.2599  loss_ld: 0.5789
2023/07/13 09:32:27 - mmengine - INFO - Epoch(train)  [2][2700/3139]  lr: 1.2500e-03  eta: 2:52:04  time: 0.3229  data_time: 0.0040  memory: 714  loss: 1.8437  loss_cls: 0.4384  loss_bbox: 0.7151  loss_dfl: 0.2542  loss_ld: 0.4361
2023/07/13 09:32:43 - mmengine - INFO - Epoch(train)  [2][2750/3139]  lr: 1.2500e-03  eta: 2:51:48  time: 0.3223  data_time: 0.0038  memory: 724  loss: 1.8273  loss_cls: 0.3126  loss_bbox: 0.6736  loss_dfl: 0.2441  loss_ld: 0.5970
2023/07/13 09:32:59 - mmengine - INFO - Epoch(train)  [2][2800/3139]  lr: 1.2500e-03  eta: 2:51:31  time: 0.3236  data_time: 0.0035  memory: 724  loss: 1.8726  loss_cls: 0.3061  loss_bbox: 0.7400  loss_dfl: 0.2535  loss_ld: 0.5730
2023/07/13 09:33:15 - mmengine - INFO - Epoch(train)  [2][2850/3139]  lr: 1.2500e-03  eta: 2:51:15  time: 0.3231  data_time: 0.0037  memory: 731  loss: 1.9095  loss_cls: 0.3015  loss_bbox: 0.6970  loss_dfl: 0.2557  loss_ld: 0.6552
2023/07/13 09:33:19 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:33:31 - mmengine - INFO - Epoch(train)  [2][2900/3139]  lr: 1.2500e-03  eta: 2:50:57  time: 0.3192  data_time: 0.0036  memory: 722  loss: 1.7870  loss_cls: 0.3112  loss_bbox: 0.6900  loss_dfl: 0.2493  loss_ld: 0.5364
2023/07/13 09:33:47 - mmengine - INFO - Epoch(train)  [2][2950/3139]  lr: 1.2500e-03  eta: 2:50:41  time: 0.3229  data_time: 0.0039  memory: 725  loss: 1.7961  loss_cls: 0.3078  loss_bbox: 0.6761  loss_dfl: 0.2541  loss_ld: 0.5582
2023/07/13 09:34:03 - mmengine - INFO - Epoch(train)  [2][3000/3139]  lr: 1.2500e-03  eta: 2:50:24  time: 0.3216  data_time: 0.0033  memory: 721  loss: 1.8967  loss_cls: 0.2707  loss_bbox: 0.7093  loss_dfl: 0.2490  loss_ld: 0.6677
2023/07/13 09:34:20 - mmengine - INFO - Epoch(train)  [2][3050/3139]  lr: 1.2500e-03  eta: 2:50:07  time: 0.3226  data_time: 0.0039  memory: 726  loss: 1.7837  loss_cls: 0.3187  loss_bbox: 0.6984  loss_dfl: 0.2479  loss_ld: 0.5185
2023/07/13 09:34:36 - mmengine - INFO - Epoch(train)  [2][3100/3139]  lr: 1.2500e-03  eta: 2:49:50  time: 0.3225  data_time: 0.0043  memory: 723  loss: 1.9092  loss_cls: 0.2882  loss_bbox: 0.7083  loss_dfl: 0.2708  loss_ld: 0.6420
2023/07/13 09:34:48 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:34:48 - mmengine - INFO - Saving checkpoint at 2 epochs
2023/07/13 09:34:56 - mmengine - INFO - Epoch(val)  [2][ 50/548]    eta: 0:00:38  time: 0.0765  data_time: 0.0022  memory: 723  
2023/07/13 09:35:00 - mmengine - INFO - Epoch(val)  [2][100/548]    eta: 0:00:33  time: 0.0744  data_time: 0.0015  memory: 497  
2023/07/13 09:35:03 - mmengine - INFO - Epoch(val)  [2][150/548]    eta: 0:00:29  time: 0.0746  data_time: 0.0014  memory: 497  
2023/07/13 09:35:07 - mmengine - INFO - Epoch(val)  [2][200/548]    eta: 0:00:26  time: 0.0746  data_time: 0.0014  memory: 497  
2023/07/13 09:35:11 - mmengine - INFO - Epoch(val)  [2][250/548]    eta: 0:00:22  time: 0.0748  data_time: 0.0014  memory: 497  
2023/07/13 09:35:14 - mmengine - INFO - Epoch(val)  [2][300/548]    eta: 0:00:18  time: 0.0742  data_time: 0.0014  memory: 497  
2023/07/13 09:35:18 - mmengine - INFO - Epoch(val)  [2][350/548]    eta: 0:00:14  time: 0.0743  data_time: 0.0014  memory: 497  
2023/07/13 09:35:22 - mmengine - INFO - Epoch(val)  [2][400/548]    eta: 0:00:11  time: 0.0742  data_time: 0.0014  memory: 497  
2023/07/13 09:35:26 - mmengine - INFO - Epoch(val)  [2][450/548]    eta: 0:00:07  time: 0.0747  data_time: 0.0014  memory: 497  
2023/07/13 09:35:29 - mmengine - INFO - Epoch(val)  [2][500/548]    eta: 0:00:03  time: 0.0738  data_time: 0.0014  memory: 497  
2023/07/13 09:35:34 - mmengine - INFO - Evaluating bbox...
2023/07/13 09:35:50 - mmengine - INFO - bbox_mAP_copypaste: 0.047 0.088 0.046 0.012 0.073 0.137
2023/07/13 09:35:50 - mmengine - INFO - Epoch(val) [2][548/548]    coco/bbox_mAP: 0.0470  coco/bbox_mAP_50: 0.0880  coco/bbox_mAP_75: 0.0460  coco/bbox_mAP_s: 0.0120  coco/bbox_mAP_m: 0.0730  coco/bbox_mAP_l: 0.1370  data_time: 0.0015  time: 0.0745
2023/07/13 09:36:06 - mmengine - INFO - Epoch(train)  [3][  50/3139]  lr: 1.2500e-03  eta: 2:49:21  time: 0.3253  data_time: 0.0053  memory: 736  loss: 1.8826  loss_cls: 0.3176  loss_bbox: 0.7338  loss_dfl: 0.2575  loss_ld: 0.5737
2023/07/13 09:36:22 - mmengine - INFO - Epoch(train)  [3][ 100/3139]  lr: 1.2500e-03  eta: 2:49:05  time: 0.3260  data_time: 0.0040  memory: 761  loss: 1.9164  loss_cls: 0.3083  loss_bbox: 0.6900  loss_dfl: 0.2560  loss_ld: 0.6622
2023/07/13 09:36:38 - mmengine - INFO - Epoch(train)  [3][ 150/3139]  lr: 1.2500e-03  eta: 2:48:49  time: 0.3230  data_time: 0.0039  memory: 725  loss: 1.7631  loss_cls: 0.3200  loss_bbox: 0.6550  loss_dfl: 0.2445  loss_ld: 0.5436
2023/07/13 09:36:55 - mmengine - INFO - Epoch(train)  [3][ 200/3139]  lr: 1.2500e-03  eta: 2:48:33  time: 0.3243  data_time: 0.0038  memory: 738  loss: 1.7691  loss_cls: 0.2909  loss_bbox: 0.6617  loss_dfl: 0.2443  loss_ld: 0.5722
2023/07/13 09:37:11 - mmengine - INFO - Epoch(train)  [3][ 250/3139]  lr: 1.2500e-03  eta: 2:48:16  time: 0.3234  data_time: 0.0043  memory: 731  loss: 1.8646  loss_cls: 0.3569  loss_bbox: 0.7482  loss_dfl: 0.2608  loss_ld: 0.4988
2023/07/13 09:37:27 - mmengine - INFO - Epoch(train)  [3][ 300/3139]  lr: 1.2500e-03  eta: 2:48:00  time: 0.3249  data_time: 0.0038  memory: 725  loss: 1.8495  loss_cls: 0.3542  loss_bbox: 0.6976  loss_dfl: 0.2578  loss_ld: 0.5399
2023/07/13 09:37:43 - mmengine - INFO - Epoch(train)  [3][ 350/3139]  lr: 1.2500e-03  eta: 2:47:44  time: 0.3249  data_time: 0.0038  memory: 719  loss: 1.6635  loss_cls: 0.3014  loss_bbox: 0.6512  loss_dfl: 0.2349  loss_ld: 0.4760
2023/07/13 09:37:59 - mmengine - INFO - Epoch(train)  [3][ 400/3139]  lr: 1.2500e-03  eta: 2:47:27  time: 0.3192  data_time: 0.0035  memory: 736  loss: 1.8188  loss_cls: 0.2809  loss_bbox: 0.6584  loss_dfl: 0.2473  loss_ld: 0.6323
2023/07/13 09:38:15 - mmengine - INFO - Epoch(train)  [3][ 450/3139]  lr: 1.2500e-03  eta: 2:47:10  time: 0.3213  data_time: 0.0037  memory: 727  loss: 1.7053  loss_cls: 0.2907  loss_bbox: 0.6477  loss_dfl: 0.2389  loss_ld: 0.5280
2023/07/13 09:38:32 - mmengine - INFO - Epoch(train)  [3][ 500/3139]  lr: 1.2500e-03  eta: 2:46:54  time: 0.3259  data_time: 0.0039  memory: 739  loss: 1.7975  loss_cls: 0.3063  loss_bbox: 0.6783  loss_dfl: 0.2532  loss_ld: 0.5597
2023/07/13 09:38:48 - mmengine - INFO - Epoch(train)  [3][ 550/3139]  lr: 1.2500e-03  eta: 2:46:37  time: 0.3224  data_time: 0.0037  memory: 724  loss: 1.6889  loss_cls: 0.3176  loss_bbox: 0.6765  loss_dfl: 0.2397  loss_ld: 0.4551
2023/07/13 09:39:04 - mmengine - INFO - Epoch(train)  [3][ 600/3139]  lr: 1.2500e-03  eta: 2:46:22  time: 0.3269  data_time: 0.0036  memory: 721  loss: 1.7503  loss_cls: 0.3217  loss_bbox: 0.6744  loss_dfl: 0.2418  loss_ld: 0.5124
2023/07/13 09:39:20 - mmengine - INFO - Epoch(train)  [3][ 650/3139]  lr: 1.2500e-03  eta: 2:46:05  time: 0.3213  data_time: 0.0038  memory: 728  loss: 1.6895  loss_cls: 0.3153  loss_bbox: 0.6657  loss_dfl: 0.2365  loss_ld: 0.4720
2023/07/13 09:39:36 - mmengine - INFO - Epoch(train)  [3][ 700/3139]  lr: 1.2500e-03  eta: 2:45:49  time: 0.3268  data_time: 0.0044  memory: 730  loss: 1.7855  loss_cls: 0.2912  loss_bbox: 0.6791  loss_dfl: 0.2483  loss_ld: 0.5669
2023/07/13 09:39:44 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:39:53 - mmengine - INFO - Epoch(train)  [3][ 750/3139]  lr: 1.2500e-03  eta: 2:45:34  time: 0.3275  data_time: 0.0047  memory: 728  loss: 1.8173  loss_cls: 0.3525  loss_bbox: 0.7012  loss_dfl: 0.2536  loss_ld: 0.5100
2023/07/13 09:40:09 - mmengine - INFO - Epoch(train)  [3][ 800/3139]  lr: 1.2500e-03  eta: 2:45:18  time: 0.3237  data_time: 0.0043  memory: 719  loss: 1.6604  loss_cls: 0.3124  loss_bbox: 0.6397  loss_dfl: 0.2305  loss_ld: 0.4778
2023/07/13 09:40:25 - mmengine - INFO - Epoch(train)  [3][ 850/3139]  lr: 1.2500e-03  eta: 2:45:01  time: 0.3250  data_time: 0.0048  memory: 720  loss: 1.9202  loss_cls: 0.4515  loss_bbox: 0.6893  loss_dfl: 0.2518  loss_ld: 0.5276
2023/07/13 09:40:42 - mmengine - INFO - Epoch(train)  [3][ 900/3139]  lr: 1.2500e-03  eta: 2:44:46  time: 0.3253  data_time: 0.0052  memory: 734  loss: 1.7818  loss_cls: 0.3226  loss_bbox: 0.6853  loss_dfl: 0.2532  loss_ld: 0.5208
2023/07/13 09:40:58 - mmengine - INFO - Epoch(train)  [3][ 950/3139]  lr: 1.2500e-03  eta: 2:44:29  time: 0.3225  data_time: 0.0035  memory: 722  loss: 1.7329  loss_cls: 0.2982  loss_bbox: 0.7071  loss_dfl: 0.2441  loss_ld: 0.4836
2023/07/13 09:41:14 - mmengine - INFO - Epoch(train)  [3][1000/3139]  lr: 1.2500e-03  eta: 2:44:12  time: 0.3203  data_time: 0.0034  memory: 720  loss: 1.7894  loss_cls: 0.3457  loss_bbox: 0.6593  loss_dfl: 0.2498  loss_ld: 0.5346
2023/07/13 09:41:30 - mmengine - INFO - Epoch(train)  [3][1050/3139]  lr: 1.2500e-03  eta: 2:43:54  time: 0.3179  data_time: 0.0036  memory: 730  loss: 1.8213  loss_cls: 0.2858  loss_bbox: 0.7340  loss_dfl: 0.2595  loss_ld: 0.5420
2023/07/13 09:41:46 - mmengine - INFO - Epoch(train)  [3][1100/3139]  lr: 1.2500e-03  eta: 2:43:38  time: 0.3255  data_time: 0.0034  memory: 721  loss: 1.7667  loss_cls: 0.2856  loss_bbox: 0.6852  loss_dfl: 0.2427  loss_ld: 0.5531
2023/07/13 09:42:02 - mmengine - INFO - Epoch(train)  [3][1150/3139]  lr: 1.2500e-03  eta: 2:43:22  time: 0.3229  data_time: 0.0040  memory: 743  loss: 1.7536  loss_cls: 0.2996  loss_bbox: 0.6769  loss_dfl: 0.2433  loss_ld: 0.5338
2023/07/13 09:42:18 - mmengine - INFO - Epoch(train)  [3][1200/3139]  lr: 1.2500e-03  eta: 2:43:06  time: 0.3229  data_time: 0.0036  memory: 722  loss: 1.8510  loss_cls: 0.2991  loss_bbox: 0.7014  loss_dfl: 0.2586  loss_ld: 0.5920
2023/07/13 09:42:34 - mmengine - INFO - Epoch(train)  [3][1250/3139]  lr: 1.2500e-03  eta: 2:42:49  time: 0.3247  data_time: 0.0049  memory: 727  loss: 1.7946  loss_cls: 0.3205  loss_bbox: 0.6787  loss_dfl: 0.2571  loss_ld: 0.5383
2023/07/13 09:42:50 - mmengine - INFO - Epoch(train)  [3][1300/3139]  lr: 1.2500e-03  eta: 2:42:33  time: 0.3212  data_time: 0.0042  memory: 728  loss: 1.7787  loss_cls: 0.3071  loss_bbox: 0.6426  loss_dfl: 0.2497  loss_ld: 0.5793
2023/07/13 09:43:06 - mmengine - INFO - Epoch(train)  [3][1350/3139]  lr: 1.2500e-03  eta: 2:42:15  time: 0.3182  data_time: 0.0035  memory: 721  loss: 1.6389  loss_cls: 0.3236  loss_bbox: 0.6563  loss_dfl: 0.2367  loss_ld: 0.4223
2023/07/13 09:43:22 - mmengine - INFO - Epoch(train)  [3][1400/3139]  lr: 1.2500e-03  eta: 2:41:58  time: 0.3204  data_time: 0.0035  memory: 719  loss: 1.6971  loss_cls: 0.3330  loss_bbox: 0.6628  loss_dfl: 0.2419  loss_ld: 0.4595
2023/07/13 09:43:39 - mmengine - INFO - Epoch(train)  [3][1450/3139]  lr: 1.2500e-03  eta: 2:41:42  time: 0.3257  data_time: 0.0057  memory: 723  loss: 1.7828  loss_cls: 0.2973  loss_bbox: 0.6071  loss_dfl: 0.2327  loss_ld: 0.6457
2023/07/13 09:43:55 - mmengine - INFO - Epoch(train)  [3][1500/3139]  lr: 1.2500e-03  eta: 2:41:27  time: 0.3257  data_time: 0.0040  memory: 722  loss: 1.7950  loss_cls: 0.3041  loss_bbox: 0.6637  loss_dfl: 0.2658  loss_ld: 0.5614
2023/07/13 09:44:11 - mmengine - INFO - Epoch(train)  [3][1550/3139]  lr: 1.2500e-03  eta: 2:41:11  time: 0.3259  data_time: 0.0044  memory: 735  loss: 1.8003  loss_cls: 0.2908  loss_bbox: 0.6566  loss_dfl: 0.2495  loss_ld: 0.6034
2023/07/13 09:44:27 - mmengine - INFO - Epoch(train)  [3][1600/3139]  lr: 1.2500e-03  eta: 2:40:54  time: 0.3230  data_time: 0.0034  memory: 729  loss: 1.7032  loss_cls: 0.2926  loss_bbox: 0.6789  loss_dfl: 0.2369  loss_ld: 0.4949
2023/07/13 09:44:44 - mmengine - INFO - Epoch(train)  [3][1650/3139]  lr: 1.2500e-03  eta: 2:40:38  time: 0.3247  data_time: 0.0045  memory: 726  loss: 1.5559  loss_cls: 0.2925  loss_bbox: 0.6437  loss_dfl: 0.2308  loss_ld: 0.3889
2023/07/13 09:45:00 - mmengine - INFO - Epoch(train)  [3][1700/3139]  lr: 1.2500e-03  eta: 2:40:21  time: 0.3177  data_time: 0.0037  memory: 720  loss: 1.7090  loss_cls: 0.3076  loss_bbox: 0.7041  loss_dfl: 0.2446  loss_ld: 0.4528
2023/07/13 09:45:07 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:45:16 - mmengine - INFO - Epoch(train)  [3][1750/3139]  lr: 1.2500e-03  eta: 2:40:04  time: 0.3229  data_time: 0.0043  memory: 724  loss: 1.7273  loss_cls: 0.3010  loss_bbox: 0.6569  loss_dfl: 0.2371  loss_ld: 0.5324
2023/07/13 09:45:32 - mmengine - INFO - Epoch(train)  [3][1800/3139]  lr: 1.2500e-03  eta: 2:39:48  time: 0.3235  data_time: 0.0040  memory: 726  loss: 1.7042  loss_cls: 0.2848  loss_bbox: 0.6160  loss_dfl: 0.2347  loss_ld: 0.5687
2023/07/13 09:45:48 - mmengine - INFO - Epoch(train)  [3][1850/3139]  lr: 1.2500e-03  eta: 2:39:32  time: 0.3259  data_time: 0.0049  memory: 749  loss: 1.6815  loss_cls: 0.2918  loss_bbox: 0.6143  loss_dfl: 0.2297  loss_ld: 0.5457
2023/07/13 09:46:04 - mmengine - INFO - Epoch(train)  [3][1900/3139]  lr: 1.2500e-03  eta: 2:39:16  time: 0.3240  data_time: 0.0040  memory: 735  loss: 1.7921  loss_cls: 0.3143  loss_bbox: 0.6799  loss_dfl: 0.2467  loss_ld: 0.5512
2023/07/13 09:46:20 - mmengine - INFO - Epoch(train)  [3][1950/3139]  lr: 1.2500e-03  eta: 2:38:59  time: 0.3219  data_time: 0.0043  memory: 723  loss: 1.6559  loss_cls: 0.3036  loss_bbox: 0.6732  loss_dfl: 0.2379  loss_ld: 0.4411
2023/07/13 09:46:37 - mmengine - INFO - Epoch(train)  [3][2000/3139]  lr: 1.2500e-03  eta: 2:38:43  time: 0.3247  data_time: 0.0045  memory: 724  loss: 1.7445  loss_cls: 0.2829  loss_bbox: 0.6628  loss_dfl: 0.2365  loss_ld: 0.5623
2023/07/13 09:46:53 - mmengine - INFO - Epoch(train)  [3][2050/3139]  lr: 1.2500e-03  eta: 2:38:27  time: 0.3260  data_time: 0.0042  memory: 721  loss: 1.7954  loss_cls: 0.3056  loss_bbox: 0.6592  loss_dfl: 0.2422  loss_ld: 0.5885
2023/07/13 09:47:09 - mmengine - INFO - Epoch(train)  [3][2100/3139]  lr: 1.2500e-03  eta: 2:38:11  time: 0.3204  data_time: 0.0037  memory: 731  loss: 1.6894  loss_cls: 0.2826  loss_bbox: 0.6194  loss_dfl: 0.2350  loss_ld: 0.5525
2023/07/13 09:47:25 - mmengine - INFO - Epoch(train)  [3][2150/3139]  lr: 1.2500e-03  eta: 2:37:54  time: 0.3196  data_time: 0.0040  memory: 724  loss: 1.7174  loss_cls: 0.3070  loss_bbox: 0.6485  loss_dfl: 0.2422  loss_ld: 0.5197
2023/07/13 09:47:41 - mmengine - INFO - Epoch(train)  [3][2200/3139]  lr: 1.2500e-03  eta: 2:37:38  time: 0.3261  data_time: 0.0042  memory: 731  loss: 1.6862  loss_cls: 0.2828  loss_bbox: 0.6432  loss_dfl: 0.2337  loss_ld: 0.5265
2023/07/13 09:47:57 - mmengine - INFO - Epoch(train)  [3][2250/3139]  lr: 1.2500e-03  eta: 2:37:21  time: 0.3229  data_time: 0.0042  memory: 717  loss: 1.7430  loss_cls: 0.4050  loss_bbox: 0.6291  loss_dfl: 0.2442  loss_ld: 0.4647
2023/07/13 09:48:14 - mmengine - INFO - Epoch(train)  [3][2300/3139]  lr: 1.2500e-03  eta: 2:37:05  time: 0.3229  data_time: 0.0044  memory: 718  loss: 1.7529  loss_cls: 0.3015  loss_bbox: 0.6391  loss_dfl: 0.2432  loss_ld: 0.5691
2023/07/13 09:48:30 - mmengine - INFO - Epoch(train)  [3][2350/3139]  lr: 1.2500e-03  eta: 2:36:49  time: 0.3237  data_time: 0.0036  memory: 740  loss: 1.7104  loss_cls: 0.3037  loss_bbox: 0.6394  loss_dfl: 0.2373  loss_ld: 0.5300
2023/07/13 09:48:46 - mmengine - INFO - Epoch(train)  [3][2400/3139]  lr: 1.2500e-03  eta: 2:36:33  time: 0.3240  data_time: 0.0036  memory: 721  loss: 1.6954  loss_cls: 0.2795  loss_bbox: 0.6491  loss_dfl: 0.2397  loss_ld: 0.5272
2023/07/13 09:49:02 - mmengine - INFO - Epoch(train)  [3][2450/3139]  lr: 1.2500e-03  eta: 2:36:17  time: 0.3261  data_time: 0.0047  memory: 720  loss: 1.7749  loss_cls: 0.2825  loss_bbox: 0.6929  loss_dfl: 0.2439  loss_ld: 0.5555
2023/07/13 09:49:18 - mmengine - INFO - Epoch(train)  [3][2500/3139]  lr: 1.2500e-03  eta: 2:36:00  time: 0.3222  data_time: 0.0037  memory: 721  loss: 1.7334  loss_cls: 0.2933  loss_bbox: 0.6363  loss_dfl: 0.2343  loss_ld: 0.5695
2023/07/13 09:49:34 - mmengine - INFO - Epoch(train)  [3][2550/3139]  lr: 1.2500e-03  eta: 2:35:44  time: 0.3222  data_time: 0.0045  memory: 721  loss: 1.6472  loss_cls: 0.3077  loss_bbox: 0.6057  loss_dfl: 0.2268  loss_ld: 0.5070
2023/07/13 09:49:51 - mmengine - INFO - Epoch(train)  [3][2600/3139]  lr: 1.2500e-03  eta: 2:35:27  time: 0.3212  data_time: 0.0038  memory: 717  loss: 1.7285  loss_cls: 0.3769  loss_bbox: 0.6477  loss_dfl: 0.2424  loss_ld: 0.4615
2023/07/13 09:50:07 - mmengine - INFO - Epoch(train)  [3][2650/3139]  lr: 1.2500e-03  eta: 2:35:10  time: 0.3204  data_time: 0.0043  memory: 733  loss: 1.7224  loss_cls: 0.3253  loss_bbox: 0.6217  loss_dfl: 0.2337  loss_ld: 0.5418
2023/07/13 09:50:23 - mmengine - INFO - Epoch(train)  [3][2700/3139]  lr: 1.2500e-03  eta: 2:34:54  time: 0.3213  data_time: 0.0038  memory: 730  loss: 1.7368  loss_cls: 0.3461  loss_bbox: 0.6826  loss_dfl: 0.2416  loss_ld: 0.4665
2023/07/13 09:50:30 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:50:39 - mmengine - INFO - Epoch(train)  [3][2750/3139]  lr: 1.2500e-03  eta: 2:34:38  time: 0.3244  data_time: 0.0048  memory: 728  loss: 1.7753  loss_cls: 0.3013  loss_bbox: 0.6344  loss_dfl: 0.2495  loss_ld: 0.5901
2023/07/13 09:50:55 - mmengine - INFO - Epoch(train)  [3][2800/3139]  lr: 1.2500e-03  eta: 2:34:22  time: 0.3251  data_time: 0.0045  memory: 717  loss: 1.6345  loss_cls: 0.3108  loss_bbox: 0.6211  loss_dfl: 0.2315  loss_ld: 0.4710
2023/07/13 09:51:11 - mmengine - INFO - Epoch(train)  [3][2850/3139]  lr: 1.2500e-03  eta: 2:34:05  time: 0.3250  data_time: 0.0038  memory: 729  loss: 1.6595  loss_cls: 0.3047  loss_bbox: 0.6489  loss_dfl: 0.2301  loss_ld: 0.4757
2023/07/13 09:51:28 - mmengine - INFO - Epoch(train)  [3][2900/3139]  lr: 1.2500e-03  eta: 2:33:49  time: 0.3242  data_time: 0.0048  memory: 722  loss: 1.6273  loss_cls: 0.3099  loss_bbox: 0.6613  loss_dfl: 0.2323  loss_ld: 0.4239
2023/07/13 09:51:44 - mmengine - INFO - Epoch(train)  [3][2950/3139]  lr: 1.2500e-03  eta: 2:33:33  time: 0.3221  data_time: 0.0036  memory: 727  loss: 1.5958  loss_cls: 0.2899  loss_bbox: 0.6558  loss_dfl: 0.2293  loss_ld: 0.4207
2023/07/13 09:52:00 - mmengine - INFO - Epoch(train)  [3][3000/3139]  lr: 1.2500e-03  eta: 2:33:17  time: 0.3234  data_time: 0.0051  memory: 752  loss: 1.6329  loss_cls: 0.3156  loss_bbox: 0.6314  loss_dfl: 0.2291  loss_ld: 0.4568
2023/07/13 09:52:16 - mmengine - INFO - Epoch(train)  [3][3050/3139]  lr: 1.2500e-03  eta: 2:33:01  time: 0.3254  data_time: 0.0046  memory: 723  loss: 1.7130  loss_cls: 0.3481  loss_bbox: 0.6830  loss_dfl: 0.2373  loss_ld: 0.4447
2023/07/13 09:52:32 - mmengine - INFO - Epoch(train)  [3][3100/3139]  lr: 1.2500e-03  eta: 2:32:45  time: 0.3257  data_time: 0.0041  memory: 723  loss: 1.7310  loss_cls: 0.3720  loss_bbox: 0.6343  loss_dfl: 0.2464  loss_ld: 0.4783
2023/07/13 09:52:45 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:52:45 - mmengine - INFO - Saving checkpoint at 3 epochs
2023/07/13 09:52:52 - mmengine - INFO - Epoch(val)  [3][ 50/548]    eta: 0:00:37  time: 0.0761  data_time: 0.0021  memory: 722  
2023/07/13 09:52:56 - mmengine - INFO - Epoch(val)  [3][100/548]    eta: 0:00:33  time: 0.0738  data_time: 0.0014  memory: 497  
2023/07/13 09:53:00 - mmengine - INFO - Epoch(val)  [3][150/548]    eta: 0:00:29  time: 0.0754  data_time: 0.0013  memory: 497  
2023/07/13 09:53:03 - mmengine - INFO - Epoch(val)  [3][200/548]    eta: 0:00:26  time: 0.0737  data_time: 0.0014  memory: 497  
2023/07/13 09:53:07 - mmengine - INFO - Epoch(val)  [3][250/548]    eta: 0:00:22  time: 0.0741  data_time: 0.0013  memory: 497  
2023/07/13 09:53:11 - mmengine - INFO - Epoch(val)  [3][300/548]    eta: 0:00:18  time: 0.0743  data_time: 0.0014  memory: 497  
2023/07/13 09:53:14 - mmengine - INFO - Epoch(val)  [3][350/548]    eta: 0:00:14  time: 0.0742  data_time: 0.0014  memory: 497  
2023/07/13 09:53:18 - mmengine - INFO - Epoch(val)  [3][400/548]    eta: 0:00:10  time: 0.0729  data_time: 0.0013  memory: 497  
2023/07/13 09:53:22 - mmengine - INFO - Epoch(val)  [3][450/548]    eta: 0:00:07  time: 0.0740  data_time: 0.0014  memory: 497  
2023/07/13 09:53:25 - mmengine - INFO - Epoch(val)  [3][500/548]    eta: 0:00:03  time: 0.0731  data_time: 0.0013  memory: 497  
2023/07/13 09:53:30 - mmengine - INFO - Evaluating bbox...
2023/07/13 09:53:46 - mmengine - INFO - bbox_mAP_copypaste: 0.053 0.096 0.053 0.015 0.082 0.154
2023/07/13 09:53:46 - mmengine - INFO - Epoch(val) [3][548/548]    coco/bbox_mAP: 0.0530  coco/bbox_mAP_50: 0.0960  coco/bbox_mAP_75: 0.0530  coco/bbox_mAP_s: 0.0150  coco/bbox_mAP_m: 0.0820  coco/bbox_mAP_l: 0.1540  data_time: 0.0014  time: 0.0740
2023/07/13 09:54:03 - mmengine - INFO - Epoch(train)  [4][  50/3139]  lr: 1.2500e-03  eta: 2:32:15  time: 0.3244  data_time: 0.0056  memory: 725  loss: 1.6609  loss_cls: 0.3170  loss_bbox: 0.6065  loss_dfl: 0.2251  loss_ld: 0.5123
2023/07/13 09:54:19 - mmengine - INFO - Epoch(train)  [4][ 100/3139]  lr: 1.2500e-03  eta: 2:31:59  time: 0.3242  data_time: 0.0038  memory: 724  loss: 1.6738  loss_cls: 0.3014  loss_bbox: 0.6159  loss_dfl: 0.2317  loss_ld: 0.5248
2023/07/13 09:54:35 - mmengine - INFO - Epoch(train)  [4][ 150/3139]  lr: 1.2500e-03  eta: 2:31:43  time: 0.3257  data_time: 0.0046  memory: 743  loss: 1.6492  loss_cls: 0.2921  loss_bbox: 0.6131  loss_dfl: 0.2400  loss_ld: 0.5041
2023/07/13 09:54:51 - mmengine - INFO - Epoch(train)  [4][ 200/3139]  lr: 1.2500e-03  eta: 2:31:27  time: 0.3225  data_time: 0.0038  memory: 728  loss: 1.6534  loss_cls: 0.3130  loss_bbox: 0.6324  loss_dfl: 0.2362  loss_ld: 0.4718
2023/07/13 09:55:07 - mmengine - INFO - Epoch(train)  [4][ 250/3139]  lr: 1.2500e-03  eta: 2:31:10  time: 0.3237  data_time: 0.0036  memory: 726  loss: 1.7223  loss_cls: 0.3333  loss_bbox: 0.6572  loss_dfl: 0.2403  loss_ld: 0.4915
2023/07/13 09:55:24 - mmengine - INFO - Epoch(train)  [4][ 300/3139]  lr: 1.2500e-03  eta: 2:30:54  time: 0.3236  data_time: 0.0038  memory: 718  loss: 1.7746  loss_cls: 0.2730  loss_bbox: 0.6352  loss_dfl: 0.2358  loss_ld: 0.6306
2023/07/13 09:55:40 - mmengine - INFO - Epoch(train)  [4][ 350/3139]  lr: 1.2500e-03  eta: 2:30:38  time: 0.3233  data_time: 0.0038  memory: 735  loss: 1.7653  loss_cls: 0.3134  loss_bbox: 0.6006  loss_dfl: 0.2379  loss_ld: 0.6134
2023/07/13 09:55:56 - mmengine - INFO - Epoch(train)  [4][ 400/3139]  lr: 1.2500e-03  eta: 2:30:22  time: 0.3225  data_time: 0.0043  memory: 721  loss: 1.5574  loss_cls: 0.3010  loss_bbox: 0.6111  loss_dfl: 0.2195  loss_ld: 0.4258
2023/07/13 09:56:12 - mmengine - INFO - Epoch(train)  [4][ 450/3139]  lr: 1.2500e-03  eta: 2:30:05  time: 0.3238  data_time: 0.0040  memory: 729  loss: 1.5666  loss_cls: 0.3066  loss_bbox: 0.5807  loss_dfl: 0.2224  loss_ld: 0.4570
2023/07/13 09:56:28 - mmengine - INFO - Epoch(train)  [4][ 500/3139]  lr: 1.2500e-03  eta: 2:29:49  time: 0.3226  data_time: 0.0041  memory: 717  loss: 1.6884  loss_cls: 0.3584  loss_bbox: 0.6401  loss_dfl: 0.2494  loss_ld: 0.4404
2023/07/13 09:56:44 - mmengine - INFO - Epoch(train)  [4][ 550/3139]  lr: 1.2500e-03  eta: 2:29:33  time: 0.3227  data_time: 0.0036  memory: 747  loss: 1.6006  loss_cls: 0.3157  loss_bbox: 0.6012  loss_dfl: 0.2243  loss_ld: 0.4594
2023/07/13 09:56:55 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 09:57:01 - mmengine - INFO - Epoch(train)  [4][ 600/3139]  lr: 1.2500e-03  eta: 2:29:17  time: 0.3266  data_time: 0.0045  memory: 748  loss: 1.6206  loss_cls: 0.3020  loss_bbox: 0.6347  loss_dfl: 0.2384  loss_ld: 0.4454
2023/07/13 09:57:17 - mmengine - INFO - Epoch(train)  [4][ 650/3139]  lr: 1.2500e-03  eta: 2:29:00  time: 0.3210  data_time: 0.0036  memory: 736  loss: 1.5812  loss_cls: 0.2834  loss_bbox: 0.5935  loss_dfl: 0.2254  loss_ld: 0.4789
2023/07/13 09:57:33 - mmengine - INFO - Epoch(train)  [4][ 700/3139]  lr: 1.2500e-03  eta: 2:28:44  time: 0.3233  data_time: 0.0047  memory: 716  loss: 1.5782  loss_cls: 0.3371  loss_bbox: 0.5906  loss_dfl: 0.2291  loss_ld: 0.4214
2023/07/13 09:57:49 - mmengine - INFO - Epoch(train)  [4][ 750/3139]  lr: 1.2500e-03  eta: 2:28:28  time: 0.3246  data_time: 0.0043  memory: 734  loss: 1.7681  loss_cls: 0.2940  loss_bbox: 0.6413  loss_dfl: 0.2435  loss_ld: 0.5893
2023/07/13 09:58:05 - mmengine - INFO - Epoch(train)  [4][ 800/3139]  lr: 1.2500e-03  eta: 2:28:11  time: 0.3224  data_time: 0.0044  memory: 731  loss: 1.6285  loss_cls: 0.2880  loss_bbox: 0.6338  loss_dfl: 0.2335  loss_ld: 0.4731
2023/07/13 09:58:21 - mmengine - INFO - Epoch(train)  [4][ 850/3139]  lr: 1.2500e-03  eta: 2:27:54  time: 0.3178  data_time: 0.0036  memory: 723  loss: 1.4931  loss_cls: 0.2853  loss_bbox: 0.6277  loss_dfl: 0.2149  loss_ld: 0.3651
2023/07/13 09:58:37 - mmengine - INFO - Epoch(train)  [4][ 900/3139]  lr: 1.2500e-03  eta: 2:27:38  time: 0.3226  data_time: 0.0034  memory: 724  loss: 1.6793  loss_cls: 0.2839  loss_bbox: 0.6440  loss_dfl: 0.2423  loss_ld: 0.5091
2023/07/13 09:58:54 - mmengine - INFO - Epoch(train)  [4][ 950/3139]  lr: 1.2500e-03  eta: 2:27:22  time: 0.3253  data_time: 0.0037  memory: 726  loss: 1.7256  loss_cls: 0.3178  loss_bbox: 0.6403  loss_dfl: 0.2459  loss_ld: 0.5216
2023/07/13 09:59:10 - mmengine - INFO - Epoch(train)  [4][1000/3139]  lr: 1.2500e-03  eta: 2:27:06  time: 0.3235  data_time: 0.0036  memory: 761  loss: 1.6828  loss_cls: 0.2971  loss_bbox: 0.6434  loss_dfl: 0.2328  loss_ld: 0.5095
2023/07/13 09:59:26 - mmengine - INFO - Epoch(train)  [4][1050/3139]  lr: 1.2500e-03  eta: 2:26:49  time: 0.3238  data_time: 0.0041  memory: 730  loss: 1.5927  loss_cls: 0.3012  loss_bbox: 0.5875  loss_dfl: 0.2294  loss_ld: 0.4746
2023/07/13 09:59:42 - mmengine - INFO - Epoch(train)  [4][1100/3139]  lr: 1.2500e-03  eta: 2:26:33  time: 0.3229  data_time: 0.0036  memory: 722  loss: 1.7036  loss_cls: 0.2863  loss_bbox: 0.6579  loss_dfl: 0.2439  loss_ld: 0.5155
2023/07/13 09:59:58 - mmengine - INFO - Epoch(train)  [4][1150/3139]  lr: 1.2500e-03  eta: 2:26:17  time: 0.3234  data_time: 0.0036  memory: 731  loss: 1.7146  loss_cls: 0.2923  loss_bbox: 0.6351  loss_dfl: 0.2355  loss_ld: 0.5517
2023/07/13 10:00:14 - mmengine - INFO - Epoch(train)  [4][1200/3139]  lr: 1.2500e-03  eta: 2:26:01  time: 0.3231  data_time: 0.0039  memory: 735  loss: 1.6105  loss_cls: 0.3002  loss_bbox: 0.6477  loss_dfl: 0.2305  loss_ld: 0.4322
2023/07/13 10:00:31 - mmengine - INFO - Epoch(train)  [4][1250/3139]  lr: 1.2500e-03  eta: 2:25:44  time: 0.3223  data_time: 0.0038  memory: 738  loss: 1.4955  loss_cls: 0.2861  loss_bbox: 0.5842  loss_dfl: 0.2179  loss_ld: 0.4073
2023/07/13 10:00:47 - mmengine - INFO - Epoch(train)  [4][1300/3139]  lr: 1.2500e-03  eta: 2:25:28  time: 0.3223  data_time: 0.0036  memory: 718  loss: 1.5994  loss_cls: 0.2946  loss_bbox: 0.6317  loss_dfl: 0.2308  loss_ld: 0.4423
2023/07/13 10:01:03 - mmengine - INFO - Epoch(train)  [4][1350/3139]  lr: 1.2500e-03  eta: 2:25:11  time: 0.3210  data_time: 0.0037  memory: 717  loss: 1.5460  loss_cls: 0.3087  loss_bbox: 0.6060  loss_dfl: 0.2235  loss_ld: 0.4077
2023/07/13 10:01:19 - mmengine - INFO - Epoch(train)  [4][1400/3139]  lr: 1.2500e-03  eta: 2:24:55  time: 0.3250  data_time: 0.0034  memory: 720  loss: 1.6103  loss_cls: 0.3110  loss_bbox: 0.6020  loss_dfl: 0.2288  loss_ld: 0.4685
2023/07/13 10:01:35 - mmengine - INFO - Epoch(train)  [4][1450/3139]  lr: 1.2500e-03  eta: 2:24:39  time: 0.3202  data_time: 0.0045  memory: 738  loss: 1.6203  loss_cls: 0.3007  loss_bbox: 0.6013  loss_dfl: 0.2261  loss_ld: 0.4921
2023/07/13 10:01:51 - mmengine - INFO - Epoch(train)  [4][1500/3139]  lr: 1.2500e-03  eta: 2:24:22  time: 0.3196  data_time: 0.0040  memory: 718  loss: 1.6609  loss_cls: 0.2998  loss_bbox: 0.6037  loss_dfl: 0.2358  loss_ld: 0.5216
2023/07/13 10:02:07 - mmengine - INFO - Epoch(train)  [4][1550/3139]  lr: 1.2500e-03  eta: 2:24:06  time: 0.3238  data_time: 0.0046  memory: 719  loss: 1.5864  loss_cls: 0.3355  loss_bbox: 0.6165  loss_dfl: 0.2303  loss_ld: 0.4042
2023/07/13 10:02:18 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:02:23 - mmengine - INFO - Epoch(train)  [4][1600/3139]  lr: 1.2500e-03  eta: 2:23:49  time: 0.3226  data_time: 0.0048  memory: 731  loss: 1.5555  loss_cls: 0.2792  loss_bbox: 0.5924  loss_dfl: 0.2212  loss_ld: 0.4627
2023/07/13 10:02:39 - mmengine - INFO - Epoch(train)  [4][1650/3139]  lr: 1.2500e-03  eta: 2:23:32  time: 0.3179  data_time: 0.0034  memory: 724  loss: 1.6156  loss_cls: 0.2967  loss_bbox: 0.6349  loss_dfl: 0.2286  loss_ld: 0.4554
2023/07/13 10:02:55 - mmengine - INFO - Epoch(train)  [4][1700/3139]  lr: 1.2500e-03  eta: 2:23:16  time: 0.3193  data_time: 0.0037  memory: 730  loss: 1.6876  loss_cls: 0.2813  loss_bbox: 0.6413  loss_dfl: 0.2319  loss_ld: 0.5331
2023/07/13 10:03:11 - mmengine - INFO - Epoch(train)  [4][1750/3139]  lr: 1.2500e-03  eta: 2:22:59  time: 0.3215  data_time: 0.0038  memory: 751  loss: 1.6275  loss_cls: 0.2825  loss_bbox: 0.6073  loss_dfl: 0.2294  loss_ld: 0.5083
2023/07/13 10:03:27 - mmengine - INFO - Epoch(train)  [4][1800/3139]  lr: 1.2500e-03  eta: 2:22:43  time: 0.3243  data_time: 0.0036  memory: 718  loss: 1.5517  loss_cls: 0.3020  loss_bbox: 0.5795  loss_dfl: 0.2226  loss_ld: 0.4476
2023/07/13 10:03:43 - mmengine - INFO - Epoch(train)  [4][1850/3139]  lr: 1.2500e-03  eta: 2:22:26  time: 0.3194  data_time: 0.0038  memory: 731  loss: 1.5816  loss_cls: 0.3103  loss_bbox: 0.5761  loss_dfl: 0.2221  loss_ld: 0.4731
2023/07/13 10:04:00 - mmengine - INFO - Epoch(train)  [4][1900/3139]  lr: 1.2500e-03  eta: 2:22:10  time: 0.3222  data_time: 0.0037  memory: 730  loss: 1.6354  loss_cls: 0.3879  loss_bbox: 0.6260  loss_dfl: 0.2301  loss_ld: 0.3915
2023/07/13 10:04:16 - mmengine - INFO - Epoch(train)  [4][1950/3139]  lr: 1.2500e-03  eta: 2:21:54  time: 0.3208  data_time: 0.0040  memory: 719  loss: 1.5983  loss_cls: 0.3429  loss_bbox: 0.6295  loss_dfl: 0.2315  loss_ld: 0.3944
2023/07/13 10:04:32 - mmengine - INFO - Epoch(train)  [4][2000/3139]  lr: 1.2500e-03  eta: 2:21:37  time: 0.3241  data_time: 0.0034  memory: 722  loss: 1.6137  loss_cls: 0.2994  loss_bbox: 0.6279  loss_dfl: 0.2289  loss_ld: 0.4574
2023/07/13 10:04:48 - mmengine - INFO - Epoch(train)  [4][2050/3139]  lr: 1.2500e-03  eta: 2:21:21  time: 0.3256  data_time: 0.0039  memory: 727  loss: 1.6690  loss_cls: 0.2868  loss_bbox: 0.6604  loss_dfl: 0.2371  loss_ld: 0.4849
2023/07/13 10:05:04 - mmengine - INFO - Epoch(train)  [4][2100/3139]  lr: 1.2500e-03  eta: 2:21:05  time: 0.3257  data_time: 0.0049  memory: 717  loss: 1.6261  loss_cls: 0.2825  loss_bbox: 0.5595  loss_dfl: 0.2195  loss_ld: 0.5647
2023/07/13 10:05:21 - mmengine - INFO - Epoch(train)  [4][2150/3139]  lr: 1.2500e-03  eta: 2:20:49  time: 0.3235  data_time: 0.0040  memory: 733  loss: 1.6317  loss_cls: 0.2766  loss_bbox: 0.6097  loss_dfl: 0.2286  loss_ld: 0.5168
2023/07/13 10:05:37 - mmengine - INFO - Epoch(train)  [4][2200/3139]  lr: 1.2500e-03  eta: 2:20:33  time: 0.3238  data_time: 0.0040  memory: 728  loss: 1.5919  loss_cls: 0.2982  loss_bbox: 0.6204  loss_dfl: 0.2288  loss_ld: 0.4445
2023/07/13 10:05:53 - mmengine - INFO - Epoch(train)  [4][2250/3139]  lr: 1.2500e-03  eta: 2:20:17  time: 0.3222  data_time: 0.0040  memory: 729  loss: 1.5749  loss_cls: 0.2837  loss_bbox: 0.5812  loss_dfl: 0.2219  loss_ld: 0.4881
2023/07/13 10:06:09 - mmengine - INFO - Epoch(train)  [4][2300/3139]  lr: 1.2500e-03  eta: 2:20:01  time: 0.3271  data_time: 0.0053  memory: 737  loss: 1.6759  loss_cls: 0.3027  loss_bbox: 0.6070  loss_dfl: 0.2292  loss_ld: 0.5370
2023/07/13 10:06:25 - mmengine - INFO - Epoch(train)  [4][2350/3139]  lr: 1.2500e-03  eta: 2:19:45  time: 0.3239  data_time: 0.0037  memory: 722  loss: 1.6808  loss_cls: 0.2827  loss_bbox: 0.6676  loss_dfl: 0.2342  loss_ld: 0.4962
2023/07/13 10:06:42 - mmengine - INFO - Epoch(train)  [4][2400/3139]  lr: 1.2500e-03  eta: 2:19:29  time: 0.3251  data_time: 0.0052  memory: 718  loss: 1.6569  loss_cls: 0.2924  loss_bbox: 0.6039  loss_dfl: 0.2288  loss_ld: 0.5318
2023/07/13 10:06:58 - mmengine - INFO - Epoch(train)  [4][2450/3139]  lr: 1.2500e-03  eta: 2:19:12  time: 0.3215  data_time: 0.0037  memory: 724  loss: 1.5428  loss_cls: 0.2850  loss_bbox: 0.5973  loss_dfl: 0.2204  loss_ld: 0.4402
2023/07/13 10:07:14 - mmengine - INFO - Epoch(train)  [4][2500/3139]  lr: 1.2500e-03  eta: 2:18:56  time: 0.3249  data_time: 0.0038  memory: 725  loss: 1.5301  loss_cls: 0.3251  loss_bbox: 0.5905  loss_dfl: 0.2228  loss_ld: 0.3918
2023/07/13 10:07:30 - mmengine - INFO - Epoch(train)  [4][2550/3139]  lr: 1.2500e-03  eta: 2:18:40  time: 0.3256  data_time: 0.0040  memory: 722  loss: 1.6683  loss_cls: 0.2749  loss_bbox: 0.6364  loss_dfl: 0.2343  loss_ld: 0.5227
2023/07/13 10:07:41 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:07:46 - mmengine - INFO - Epoch(train)  [4][2600/3139]  lr: 1.2500e-03  eta: 2:18:24  time: 0.3229  data_time: 0.0043  memory: 721  loss: 1.6208  loss_cls: 0.3127  loss_bbox: 0.6382  loss_dfl: 0.2283  loss_ld: 0.4416
2023/07/13 10:08:03 - mmengine - INFO - Epoch(train)  [4][2650/3139]  lr: 1.2500e-03  eta: 2:18:07  time: 0.3208  data_time: 0.0039  memory: 720  loss: 1.6255  loss_cls: 0.3084  loss_bbox: 0.6243  loss_dfl: 0.2277  loss_ld: 0.4651
2023/07/13 10:08:19 - mmengine - INFO - Epoch(train)  [4][2700/3139]  lr: 1.2500e-03  eta: 2:17:51  time: 0.3246  data_time: 0.0041  memory: 728  loss: 1.5179  loss_cls: 0.2919  loss_bbox: 0.5658  loss_dfl: 0.2168  loss_ld: 0.4433
2023/07/13 10:08:35 - mmengine - INFO - Epoch(train)  [4][2750/3139]  lr: 1.2500e-03  eta: 2:17:35  time: 0.3239  data_time: 0.0041  memory: 722  loss: 1.5299  loss_cls: 0.2885  loss_bbox: 0.6058  loss_dfl: 0.2237  loss_ld: 0.4120
2023/07/13 10:08:51 - mmengine - INFO - Epoch(train)  [4][2800/3139]  lr: 1.2500e-03  eta: 2:17:19  time: 0.3243  data_time: 0.0037  memory: 718  loss: 1.5205  loss_cls: 0.3011  loss_bbox: 0.6071  loss_dfl: 0.2221  loss_ld: 0.3902
2023/07/13 10:09:07 - mmengine - INFO - Epoch(train)  [4][2850/3139]  lr: 1.2500e-03  eta: 2:17:03  time: 0.3261  data_time: 0.0049  memory: 720  loss: 1.6026  loss_cls: 0.2897  loss_bbox: 0.6093  loss_dfl: 0.2257  loss_ld: 0.4779
2023/07/13 10:09:23 - mmengine - INFO - Epoch(train)  [4][2900/3139]  lr: 1.2500e-03  eta: 2:16:46  time: 0.3188  data_time: 0.0036  memory: 728  loss: 1.6273  loss_cls: 0.3026  loss_bbox: 0.5709  loss_dfl: 0.2252  loss_ld: 0.5285
2023/07/13 10:09:40 - mmengine - INFO - Epoch(train)  [4][2950/3139]  lr: 1.2500e-03  eta: 2:16:30  time: 0.3228  data_time: 0.0041  memory: 718  loss: 1.5321  loss_cls: 0.3416  loss_bbox: 0.5831  loss_dfl: 0.2139  loss_ld: 0.3935
2023/07/13 10:09:56 - mmengine - INFO - Epoch(train)  [4][3000/3139]  lr: 1.2500e-03  eta: 2:16:14  time: 0.3226  data_time: 0.0041  memory: 714  loss: 1.6321  loss_cls: 0.3229  loss_bbox: 0.6716  loss_dfl: 0.2356  loss_ld: 0.4019
2023/07/13 10:10:12 - mmengine - INFO - Epoch(train)  [4][3050/3139]  lr: 1.2500e-03  eta: 2:15:58  time: 0.3224  data_time: 0.0046  memory: 724  loss: 1.4739  loss_cls: 0.2961  loss_bbox: 0.5578  loss_dfl: 0.2148  loss_ld: 0.4053
2023/07/13 10:10:28 - mmengine - INFO - Epoch(train)  [4][3100/3139]  lr: 1.2500e-03  eta: 2:15:41  time: 0.3246  data_time: 0.0043  memory: 714  loss: 1.4723  loss_cls: 0.3252  loss_bbox: 0.5380  loss_dfl: 0.2103  loss_ld: 0.3989
2023/07/13 10:10:41 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:10:41 - mmengine - INFO - Saving checkpoint at 4 epochs
2023/07/13 10:10:47 - mmengine - INFO - Epoch(val)  [4][ 50/548]    eta: 0:00:37  time: 0.0755  data_time: 0.0022  memory: 717  
2023/07/13 10:10:51 - mmengine - INFO - Epoch(val)  [4][100/548]    eta: 0:00:33  time: 0.0739  data_time: 0.0014  memory: 497  
2023/07/13 10:10:54 - mmengine - INFO - Epoch(val)  [4][150/548]    eta: 0:00:29  time: 0.0740  data_time: 0.0013  memory: 497  
2023/07/13 10:10:58 - mmengine - INFO - Epoch(val)  [4][200/548]    eta: 0:00:25  time: 0.0734  data_time: 0.0013  memory: 497  
2023/07/13 10:11:02 - mmengine - INFO - Epoch(val)  [4][250/548]    eta: 0:00:22  time: 0.0746  data_time: 0.0014  memory: 497  
2023/07/13 10:11:06 - mmengine - INFO - Epoch(val)  [4][300/548]    eta: 0:00:18  time: 0.0797  data_time: 0.0015  memory: 497  
2023/07/13 10:11:10 - mmengine - INFO - Epoch(val)  [4][350/548]    eta: 0:00:15  time: 0.0802  data_time: 0.0015  memory: 497  
2023/07/13 10:11:14 - mmengine - INFO - Epoch(val)  [4][400/548]    eta: 0:00:11  time: 0.0801  data_time: 0.0017  memory: 497  
2023/07/13 10:11:18 - mmengine - INFO - Epoch(val)  [4][450/548]    eta: 0:00:07  time: 0.0816  data_time: 0.0016  memory: 497  
2023/07/13 10:11:22 - mmengine - INFO - Epoch(val)  [4][500/548]    eta: 0:00:03  time: 0.0801  data_time: 0.0015  memory: 497  
2023/07/13 10:11:27 - mmengine - INFO - Evaluating bbox...
2023/07/13 10:11:39 - mmengine - INFO - bbox_mAP_copypaste: 0.066 0.117 0.064 0.018 0.098 0.186
2023/07/13 10:11:39 - mmengine - INFO - Epoch(val) [4][548/548]    coco/bbox_mAP: 0.0660  coco/bbox_mAP_50: 0.1170  coco/bbox_mAP_75: 0.0640  coco/bbox_mAP_s: 0.0180  coco/bbox_mAP_m: 0.0980  coco/bbox_mAP_l: 0.1860  data_time: 0.0015  time: 0.0775
2023/07/13 10:11:55 - mmengine - INFO - Epoch(train)  [5][  50/3139]  lr: 1.2500e-03  eta: 2:15:13  time: 0.3233  data_time: 0.0052  memory: 719  loss: 1.5870  loss_cls: 0.3097  loss_bbox: 0.5917  loss_dfl: 0.2234  loss_ld: 0.4623
2023/07/13 10:12:11 - mmengine - INFO - Epoch(train)  [5][ 100/3139]  lr: 1.2500e-03  eta: 2:14:56  time: 0.3238  data_time: 0.0040  memory: 725  loss: 1.6450  loss_cls: 0.2861  loss_bbox: 0.6141  loss_dfl: 0.2267  loss_ld: 0.5181
2023/07/13 10:12:27 - mmengine - INFO - Epoch(train)  [5][ 150/3139]  lr: 1.2500e-03  eta: 2:14:40  time: 0.3259  data_time: 0.0045  memory: 725  loss: 1.5837  loss_cls: 0.2831  loss_bbox: 0.5994  loss_dfl: 0.2206  loss_ld: 0.4806
2023/07/13 10:12:44 - mmengine - INFO - Epoch(train)  [5][ 200/3139]  lr: 1.2500e-03  eta: 2:14:24  time: 0.3239  data_time: 0.0034  memory: 751  loss: 1.6039  loss_cls: 0.3022  loss_bbox: 0.6138  loss_dfl: 0.2296  loss_ld: 0.4583
2023/07/13 10:13:00 - mmengine - INFO - Epoch(train)  [5][ 250/3139]  lr: 1.2500e-03  eta: 2:14:08  time: 0.3196  data_time: 0.0037  memory: 721  loss: 1.5543  loss_cls: 0.3430  loss_bbox: 0.5877  loss_dfl: 0.2187  loss_ld: 0.4049
2023/07/13 10:13:16 - mmengine - INFO - Epoch(train)  [5][ 300/3139]  lr: 1.2500e-03  eta: 2:13:51  time: 0.3227  data_time: 0.0035  memory: 726  loss: 1.4466  loss_cls: 0.2904  loss_bbox: 0.5653  loss_dfl: 0.2076  loss_ld: 0.3833
2023/07/13 10:13:32 - mmengine - INFO - Epoch(train)  [5][ 350/3139]  lr: 1.2500e-03  eta: 2:13:35  time: 0.3240  data_time: 0.0037  memory: 720  loss: 1.5930  loss_cls: 0.3079  loss_bbox: 0.5842  loss_dfl: 0.2287  loss_ld: 0.4723
2023/07/13 10:13:48 - mmengine - INFO - Epoch(train)  [5][ 400/3139]  lr: 1.2500e-03  eta: 2:13:19  time: 0.3226  data_time: 0.0041  memory: 733  loss: 1.5866  loss_cls: 0.3077  loss_bbox: 0.5805  loss_dfl: 0.2263  loss_ld: 0.4721
2023/07/13 10:14:02 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:14:04 - mmengine - INFO - Epoch(train)  [5][ 450/3139]  lr: 1.2500e-03  eta: 2:13:03  time: 0.3223  data_time: 0.0041  memory: 726  loss: 1.5262  loss_cls: 0.3127  loss_bbox: 0.5712  loss_dfl: 0.2152  loss_ld: 0.4271
2023/07/13 10:14:20 - mmengine - INFO - Epoch(train)  [5][ 500/3139]  lr: 1.2500e-03  eta: 2:12:46  time: 0.3227  data_time: 0.0040  memory: 720  loss: 1.5950  loss_cls: 0.2993  loss_bbox: 0.5980  loss_dfl: 0.2258  loss_ld: 0.4719
2023/07/13 10:14:36 - mmengine - INFO - Epoch(train)  [5][ 550/3139]  lr: 1.2500e-03  eta: 2:12:30  time: 0.3222  data_time: 0.0036  memory: 720  loss: 1.5205  loss_cls: 0.2911  loss_bbox: 0.6022  loss_dfl: 0.2158  loss_ld: 0.4114
2023/07/13 10:14:53 - mmengine - INFO - Epoch(train)  [5][ 600/3139]  lr: 1.2500e-03  eta: 2:12:14  time: 0.3273  data_time: 0.0047  memory: 728  loss: 1.5082  loss_cls: 0.2707  loss_bbox: 0.5892  loss_dfl: 0.2108  loss_ld: 0.4375
2023/07/13 10:15:09 - mmengine - INFO - Epoch(train)  [5][ 650/3139]  lr: 1.2500e-03  eta: 2:11:58  time: 0.3219  data_time: 0.0042  memory: 716  loss: 1.5426  loss_cls: 0.3245  loss_bbox: 0.5844  loss_dfl: 0.2186  loss_ld: 0.4152
2023/07/13 10:15:25 - mmengine - INFO - Epoch(train)  [5][ 700/3139]  lr: 1.2500e-03  eta: 2:11:42  time: 0.3245  data_time: 0.0040  memory: 720  loss: 1.5275  loss_cls: 0.2948  loss_bbox: 0.5751  loss_dfl: 0.2207  loss_ld: 0.4370
2023/07/13 10:15:41 - mmengine - INFO - Epoch(train)  [5][ 750/3139]  lr: 1.2500e-03  eta: 2:11:25  time: 0.3230  data_time: 0.0039  memory: 718  loss: 1.5166  loss_cls: 0.2733  loss_bbox: 0.6071  loss_dfl: 0.2247  loss_ld: 0.4115
2023/07/13 10:15:57 - mmengine - INFO - Epoch(train)  [5][ 800/3139]  lr: 1.2500e-03  eta: 2:11:09  time: 0.3235  data_time: 0.0037  memory: 718  loss: 1.5252  loss_cls: 0.3147  loss_bbox: 0.5810  loss_dfl: 0.2234  loss_ld: 0.4061
2023/07/13 10:16:14 - mmengine - INFO - Epoch(train)  [5][ 850/3139]  lr: 1.2500e-03  eta: 2:10:53  time: 0.3227  data_time: 0.0042  memory: 733  loss: 1.6378  loss_cls: 0.2573  loss_bbox: 0.6580  loss_dfl: 0.2382  loss_ld: 0.4843
2023/07/13 10:16:30 - mmengine - INFO - Epoch(train)  [5][ 900/3139]  lr: 1.2500e-03  eta: 2:10:37  time: 0.3222  data_time: 0.0041  memory: 725  loss: 1.5498  loss_cls: 0.2875  loss_bbox: 0.5715  loss_dfl: 0.2130  loss_ld: 0.4778
2023/07/13 10:16:46 - mmengine - INFO - Epoch(train)  [5][ 950/3139]  lr: 1.2500e-03  eta: 2:10:21  time: 0.3240  data_time: 0.0042  memory: 725  loss: 1.5275  loss_cls: 0.2808  loss_bbox: 0.5979  loss_dfl: 0.2199  loss_ld: 0.4288
2023/07/13 10:17:02 - mmengine - INFO - Epoch(train)  [5][1000/3139]  lr: 1.2500e-03  eta: 2:10:04  time: 0.3238  data_time: 0.0039  memory: 716  loss: 1.6419  loss_cls: 0.2687  loss_bbox: 0.5576  loss_dfl: 0.2245  loss_ld: 0.5910
2023/07/13 10:17:18 - mmengine - INFO - Epoch(train)  [5][1050/3139]  lr: 1.2500e-03  eta: 2:09:48  time: 0.3235  data_time: 0.0040  memory: 722  loss: 1.5864  loss_cls: 0.2661  loss_bbox: 0.6137  loss_dfl: 0.2259  loss_ld: 0.4806
2023/07/13 10:17:34 - mmengine - INFO - Epoch(train)  [5][1100/3139]  lr: 1.2500e-03  eta: 2:09:32  time: 0.3229  data_time: 0.0044  memory: 738  loss: 1.5210  loss_cls: 0.2852  loss_bbox: 0.5749  loss_dfl: 0.2200  loss_ld: 0.4410
2023/07/13 10:17:51 - mmengine - INFO - Epoch(train)  [5][1150/3139]  lr: 1.2500e-03  eta: 2:09:16  time: 0.3260  data_time: 0.0046  memory: 719  loss: 1.4864  loss_cls: 0.3133  loss_bbox: 0.5542  loss_dfl: 0.2194  loss_ld: 0.3995
2023/07/13 10:18:07 - mmengine - INFO - Epoch(train)  [5][1200/3139]  lr: 1.2500e-03  eta: 2:09:00  time: 0.3232  data_time: 0.0036  memory: 726  loss: 1.5272  loss_cls: 0.2885  loss_bbox: 0.5814  loss_dfl: 0.2172  loss_ld: 0.4401
2023/07/13 10:18:23 - mmengine - INFO - Epoch(train)  [5][1250/3139]  lr: 1.2500e-03  eta: 2:08:43  time: 0.3220  data_time: 0.0040  memory: 730  loss: 1.4830  loss_cls: 0.3102  loss_bbox: 0.5841  loss_dfl: 0.2209  loss_ld: 0.3677
2023/07/13 10:18:39 - mmengine - INFO - Epoch(train)  [5][1300/3139]  lr: 1.2500e-03  eta: 2:08:27  time: 0.3257  data_time: 0.0046  memory: 719  loss: 1.6614  loss_cls: 0.2799  loss_bbox: 0.6400  loss_dfl: 0.2401  loss_ld: 0.5014
2023/07/13 10:18:56 - mmengine - INFO - Epoch(train)  [5][1350/3139]  lr: 1.2500e-03  eta: 2:08:11  time: 0.3263  data_time: 0.0045  memory: 731  loss: 1.6498  loss_cls: 0.3143  loss_bbox: 0.6270  loss_dfl: 0.2318  loss_ld: 0.4768
2023/07/13 10:19:12 - mmengine - INFO - Epoch(train)  [5][1400/3139]  lr: 1.2500e-03  eta: 2:07:55  time: 0.3257  data_time: 0.0040  memory: 734  loss: 1.5465  loss_cls: 0.2991  loss_bbox: 0.6105  loss_dfl: 0.2219  loss_ld: 0.4151
2023/07/13 10:19:26 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:19:28 - mmengine - INFO - Epoch(train)  [5][1450/3139]  lr: 1.2500e-03  eta: 2:07:39  time: 0.3246  data_time: 0.0049  memory: 749  loss: 1.5501  loss_cls: 0.3036  loss_bbox: 0.6085  loss_dfl: 0.2237  loss_ld: 0.4142
2023/07/13 10:19:44 - mmengine - INFO - Epoch(train)  [5][1500/3139]  lr: 1.2500e-03  eta: 2:07:23  time: 0.3245  data_time: 0.0034  memory: 725  loss: 1.6720  loss_cls: 0.2803  loss_bbox: 0.6502  loss_dfl: 0.2337  loss_ld: 0.5077
2023/07/13 10:20:01 - mmengine - INFO - Epoch(train)  [5][1550/3139]  lr: 1.2500e-03  eta: 2:07:07  time: 0.3231  data_time: 0.0036  memory: 761  loss: 1.6321  loss_cls: 0.2847  loss_bbox: 0.6272  loss_dfl: 0.2342  loss_ld: 0.4860
2023/07/13 10:20:17 - mmengine - INFO - Epoch(train)  [5][1600/3139]  lr: 1.2500e-03  eta: 2:06:51  time: 0.3229  data_time: 0.0039  memory: 727  loss: 1.5962  loss_cls: 0.2804  loss_bbox: 0.6020  loss_dfl: 0.2286  loss_ld: 0.4851
2023/07/13 10:20:33 - mmengine - INFO - Epoch(train)  [5][1650/3139]  lr: 1.2500e-03  eta: 2:06:35  time: 0.3244  data_time: 0.0038  memory: 734  loss: 1.5460  loss_cls: 0.3222  loss_bbox: 0.5528  loss_dfl: 0.2215  loss_ld: 0.4495
2023/07/13 10:20:49 - mmengine - INFO - Epoch(train)  [5][1700/3139]  lr: 1.2500e-03  eta: 2:06:19  time: 0.3283  data_time: 0.0059  memory: 731  loss: 1.5154  loss_cls: 0.3046  loss_bbox: 0.5546  loss_dfl: 0.2147  loss_ld: 0.4415
2023/07/13 10:21:06 - mmengine - INFO - Epoch(train)  [5][1750/3139]  lr: 1.2500e-03  eta: 2:06:03  time: 0.3254  data_time: 0.0040  memory: 731  loss: 1.5247  loss_cls: 0.2744  loss_bbox: 0.5852  loss_dfl: 0.2206  loss_ld: 0.4445
2023/07/13 10:21:22 - mmengine - INFO - Epoch(train)  [5][1800/3139]  lr: 1.2500e-03  eta: 2:05:46  time: 0.3225  data_time: 0.0041  memory: 715  loss: 1.4612  loss_cls: 0.2821  loss_bbox: 0.5300  loss_dfl: 0.2123  loss_ld: 0.4368
2023/07/13 10:21:38 - mmengine - INFO - Epoch(train)  [5][1850/3139]  lr: 1.2500e-03  eta: 2:05:30  time: 0.3241  data_time: 0.0041  memory: 721  loss: 1.5141  loss_cls: 0.3028  loss_bbox: 0.5729  loss_dfl: 0.2155  loss_ld: 0.4229
2023/07/13 10:21:54 - mmengine - INFO - Epoch(train)  [5][1900/3139]  lr: 1.2500e-03  eta: 2:05:14  time: 0.3237  data_time: 0.0040  memory: 730  loss: 1.6111  loss_cls: 0.2899  loss_bbox: 0.5888  loss_dfl: 0.2232  loss_ld: 0.5092
2023/07/13 10:22:10 - mmengine - INFO - Epoch(train)  [5][1950/3139]  lr: 1.2500e-03  eta: 2:04:58  time: 0.3228  data_time: 0.0040  memory: 723  loss: 1.4404  loss_cls: 0.3022  loss_bbox: 0.5509  loss_dfl: 0.2034  loss_ld: 0.3839
2023/07/13 10:22:26 - mmengine - INFO - Epoch(train)  [5][2000/3139]  lr: 1.2500e-03  eta: 2:04:42  time: 0.3238  data_time: 0.0044  memory: 728  loss: 1.5306  loss_cls: 0.2899  loss_bbox: 0.5833  loss_dfl: 0.2190  loss_ld: 0.4384
2023/07/13 10:22:43 - mmengine - INFO - Epoch(train)  [5][2050/3139]  lr: 1.2500e-03  eta: 2:04:25  time: 0.3246  data_time: 0.0036  memory: 724  loss: 1.5170  loss_cls: 0.3259  loss_bbox: 0.5574  loss_dfl: 0.2209  loss_ld: 0.4129
2023/07/13 10:22:59 - mmengine - INFO - Epoch(train)  [5][2100/3139]  lr: 1.2500e-03  eta: 2:04:10  time: 0.3265  data_time: 0.0042  memory: 723  loss: 1.5098  loss_cls: 0.2768  loss_bbox: 0.5936  loss_dfl: 0.2115  loss_ld: 0.4279
2023/07/13 10:23:15 - mmengine - INFO - Epoch(train)  [5][2150/3139]  lr: 1.2500e-03  eta: 2:03:53  time: 0.3202  data_time: 0.0037  memory: 723  loss: 1.4869  loss_cls: 0.2665  loss_bbox: 0.6001  loss_dfl: 0.2098  loss_ld: 0.4105
2023/07/13 10:23:31 - mmengine - INFO - Epoch(train)  [5][2200/3139]  lr: 1.2500e-03  eta: 2:03:37  time: 0.3221  data_time: 0.0034  memory: 722  loss: 1.4931  loss_cls: 0.2821  loss_bbox: 0.5613  loss_dfl: 0.2140  loss_ld: 0.4357
2023/07/13 10:23:47 - mmengine - INFO - Epoch(train)  [5][2250/3139]  lr: 1.2500e-03  eta: 2:03:20  time: 0.3208  data_time: 0.0041  memory: 723  loss: 1.4007  loss_cls: 0.2801  loss_bbox: 0.5559  loss_dfl: 0.2061  loss_ld: 0.3586
2023/07/13 10:24:03 - mmengine - INFO - Epoch(train)  [5][2300/3139]  lr: 1.2500e-03  eta: 2:03:04  time: 0.3251  data_time: 0.0047  memory: 735  loss: 1.5600  loss_cls: 0.2937  loss_bbox: 0.5785  loss_dfl: 0.2236  loss_ld: 0.4641
2023/07/13 10:24:20 - mmengine - INFO - Epoch(train)  [5][2350/3139]  lr: 1.2500e-03  eta: 2:02:48  time: 0.3214  data_time: 0.0045  memory: 736  loss: 1.4759  loss_cls: 0.2939  loss_bbox: 0.5487  loss_dfl: 0.2090  loss_ld: 0.4243
2023/07/13 10:24:36 - mmengine - INFO - Epoch(train)  [5][2400/3139]  lr: 1.2500e-03  eta: 2:02:32  time: 0.3224  data_time: 0.0034  memory: 743  loss: 1.5816  loss_cls: 0.2834  loss_bbox: 0.5899  loss_dfl: 0.2219  loss_ld: 0.4864
2023/07/13 10:24:50 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:24:52 - mmengine - INFO - Epoch(train)  [5][2450/3139]  lr: 1.2500e-03  eta: 2:02:16  time: 0.3258  data_time: 0.0046  memory: 739  loss: 1.3679  loss_cls: 0.2983  loss_bbox: 0.5262  loss_dfl: 0.2057  loss_ld: 0.3378
2023/07/13 10:25:08 - mmengine - INFO - Epoch(train)  [5][2500/3139]  lr: 1.2500e-03  eta: 2:01:59  time: 0.3237  data_time: 0.0035  memory: 724  loss: 1.5274  loss_cls: 0.2788  loss_bbox: 0.5908  loss_dfl: 0.2226  loss_ld: 0.4352
2023/07/13 10:25:24 - mmengine - INFO - Epoch(train)  [5][2550/3139]  lr: 1.2500e-03  eta: 2:01:43  time: 0.3241  data_time: 0.0040  memory: 722  loss: 1.5777  loss_cls: 0.2909  loss_bbox: 0.5880  loss_dfl: 0.2225  loss_ld: 0.4763
2023/07/13 10:25:41 - mmengine - INFO - Epoch(train)  [5][2600/3139]  lr: 1.2500e-03  eta: 2:01:27  time: 0.3277  data_time: 0.0057  memory: 718  loss: 1.4542  loss_cls: 0.3093  loss_bbox: 0.5311  loss_dfl: 0.2134  loss_ld: 0.4004
2023/07/13 10:25:57 - mmengine - INFO - Epoch(train)  [5][2650/3139]  lr: 1.2500e-03  eta: 2:01:11  time: 0.3229  data_time: 0.0040  memory: 729  loss: 1.4725  loss_cls: 0.2797  loss_bbox: 0.5662  loss_dfl: 0.2178  loss_ld: 0.4088
2023/07/13 10:26:13 - mmengine - INFO - Epoch(train)  [5][2700/3139]  lr: 1.2500e-03  eta: 2:00:55  time: 0.3229  data_time: 0.0047  memory: 728  loss: 1.4876  loss_cls: 0.2955  loss_bbox: 0.5564  loss_dfl: 0.2133  loss_ld: 0.4225
2023/07/13 10:26:29 - mmengine - INFO - Epoch(train)  [5][2750/3139]  lr: 1.2500e-03  eta: 2:00:38  time: 0.3203  data_time: 0.0041  memory: 720  loss: 1.5981  loss_cls: 0.2754  loss_bbox: 0.6745  loss_dfl: 0.2396  loss_ld: 0.4086
2023/07/13 10:26:45 - mmengine - INFO - Epoch(train)  [5][2800/3139]  lr: 1.2500e-03  eta: 2:00:22  time: 0.3224  data_time: 0.0042  memory: 739  loss: 1.5540  loss_cls: 0.2639  loss_bbox: 0.5992  loss_dfl: 0.2181  loss_ld: 0.4727
2023/07/13 10:27:01 - mmengine - INFO - Epoch(train)  [5][2850/3139]  lr: 1.2500e-03  eta: 2:00:06  time: 0.3263  data_time: 0.0040  memory: 723  loss: 1.5763  loss_cls: 0.2890  loss_bbox: 0.5501  loss_dfl: 0.2181  loss_ld: 0.5191
2023/07/13 10:27:18 - mmengine - INFO - Epoch(train)  [5][2900/3139]  lr: 1.2500e-03  eta: 1:59:50  time: 0.3209  data_time: 0.0035  memory: 717  loss: 1.4625  loss_cls: 0.2731  loss_bbox: 0.5449  loss_dfl: 0.2128  loss_ld: 0.4317
2023/07/13 10:27:34 - mmengine - INFO - Epoch(train)  [5][2950/3139]  lr: 1.2500e-03  eta: 1:59:34  time: 0.3244  data_time: 0.0036  memory: 746  loss: 1.4578  loss_cls: 0.2799  loss_bbox: 0.5559  loss_dfl: 0.2129  loss_ld: 0.4091
2023/07/13 10:27:50 - mmengine - INFO - Epoch(train)  [5][3000/3139]  lr: 1.2500e-03  eta: 1:59:17  time: 0.3208  data_time: 0.0042  memory: 724  loss: 1.4898  loss_cls: 0.3076  loss_bbox: 0.6186  loss_dfl: 0.2258  loss_ld: 0.3378
2023/07/13 10:28:06 - mmengine - INFO - Epoch(train)  [5][3050/3139]  lr: 1.2500e-03  eta: 1:59:01  time: 0.3250  data_time: 0.0045  memory: 722  loss: 1.4977  loss_cls: 0.2848  loss_bbox: 0.5942  loss_dfl: 0.2154  loss_ld: 0.4033
2023/07/13 10:28:22 - mmengine - INFO - Epoch(train)  [5][3100/3139]  lr: 1.2500e-03  eta: 1:58:45  time: 0.3218  data_time: 0.0040  memory: 717  loss: 1.4411  loss_cls: 0.2774  loss_bbox: 0.5660  loss_dfl: 0.2111  loss_ld: 0.3866
2023/07/13 10:28:35 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:28:35 - mmengine - INFO - Saving checkpoint at 5 epochs
2023/07/13 10:28:41 - mmengine - INFO - Epoch(val)  [5][ 50/548]    eta: 0:00:37  time: 0.0746  data_time: 0.0022  memory: 722  
2023/07/13 10:28:45 - mmengine - INFO - Epoch(val)  [5][100/548]    eta: 0:00:33  time: 0.0734  data_time: 0.0014  memory: 497  
2023/07/13 10:28:48 - mmengine - INFO - Epoch(val)  [5][150/548]    eta: 0:00:29  time: 0.0737  data_time: 0.0013  memory: 497  
2023/07/13 10:28:52 - mmengine - INFO - Epoch(val)  [5][200/548]    eta: 0:00:25  time: 0.0736  data_time: 0.0013  memory: 497  
2023/07/13 10:28:56 - mmengine - INFO - Epoch(val)  [5][250/548]    eta: 0:00:21  time: 0.0737  data_time: 0.0013  memory: 497  
2023/07/13 10:28:59 - mmengine - INFO - Epoch(val)  [5][300/548]    eta: 0:00:18  time: 0.0730  data_time: 0.0013  memory: 497  
2023/07/13 10:29:03 - mmengine - INFO - Epoch(val)  [5][350/548]    eta: 0:00:14  time: 0.0730  data_time: 0.0014  memory: 497  
2023/07/13 10:29:07 - mmengine - INFO - Epoch(val)  [5][400/548]    eta: 0:00:10  time: 0.0734  data_time: 0.0013  memory: 497  
2023/07/13 10:29:10 - mmengine - INFO - Epoch(val)  [5][450/548]    eta: 0:00:07  time: 0.0743  data_time: 0.0014  memory: 497  
2023/07/13 10:29:14 - mmengine - INFO - Epoch(val)  [5][500/548]    eta: 0:00:03  time: 0.0732  data_time: 0.0013  memory: 497  
2023/07/13 10:29:18 - mmengine - INFO - Evaluating bbox...
2023/07/13 10:29:32 - mmengine - INFO - bbox_mAP_copypaste: 0.076 0.134 0.077 0.020 0.112 0.212
2023/07/13 10:29:32 - mmengine - INFO - Epoch(val) [5][548/548]    coco/bbox_mAP: 0.0760  coco/bbox_mAP_50: 0.1340  coco/bbox_mAP_75: 0.0770  coco/bbox_mAP_s: 0.0200  coco/bbox_mAP_m: 0.1120  coco/bbox_mAP_l: 0.2120  data_time: 0.0014  time: 0.0735
2023/07/13 10:29:48 - mmengine - INFO - Epoch(train)  [6][  50/3139]  lr: 1.2500e-03  eta: 1:58:16  time: 0.3255  data_time: 0.0055  memory: 718  loss: 1.5618  loss_cls: 0.3030  loss_bbox: 0.5504  loss_dfl: 0.2272  loss_ld: 0.4812
2023/07/13 10:30:05 - mmengine - INFO - Epoch(train)  [6][ 100/3139]  lr: 1.2500e-03  eta: 1:58:00  time: 0.3363  data_time: 0.0163  memory: 715  loss: 1.4490  loss_cls: 0.2706  loss_bbox: 0.5386  loss_dfl: 0.2074  loss_ld: 0.4324
2023/07/13 10:30:21 - mmengine - INFO - Epoch(train)  [6][ 150/3139]  lr: 1.2500e-03  eta: 1:57:44  time: 0.3239  data_time: 0.0045  memory: 739  loss: 1.4762  loss_cls: 0.3092  loss_bbox: 0.5758  loss_dfl: 0.2145  loss_ld: 0.3768
2023/07/13 10:30:37 - mmengine - INFO - Epoch(train)  [6][ 200/3139]  lr: 1.2500e-03  eta: 1:57:28  time: 0.3215  data_time: 0.0046  memory: 735  loss: 1.4730  loss_cls: 0.2697  loss_bbox: 0.5599  loss_dfl: 0.2178  loss_ld: 0.4256
2023/07/13 10:30:54 - mmengine - INFO - Epoch(train)  [6][ 250/3139]  lr: 1.2500e-03  eta: 1:57:12  time: 0.3239  data_time: 0.0059  memory: 726  loss: 1.5377  loss_cls: 0.2833  loss_bbox: 0.5929  loss_dfl: 0.2173  loss_ld: 0.4441
2023/07/13 10:31:10 - mmengine - INFO - Epoch(train)  [6][ 300/3139]  lr: 1.2500e-03  eta: 1:56:56  time: 0.3244  data_time: 0.0049  memory: 718  loss: 1.4510  loss_cls: 0.2759  loss_bbox: 0.5443  loss_dfl: 0.2118  loss_ld: 0.4189
2023/07/13 10:31:11 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:31:26 - mmengine - INFO - Epoch(train)  [6][ 350/3139]  lr: 1.2500e-03  eta: 1:56:40  time: 0.3248  data_time: 0.0046  memory: 719  loss: 1.5020  loss_cls: 0.2964  loss_bbox: 0.5755  loss_dfl: 0.2176  loss_ld: 0.4125
2023/07/13 10:31:42 - mmengine - INFO - Epoch(train)  [6][ 400/3139]  lr: 1.2500e-03  eta: 1:56:23  time: 0.3258  data_time: 0.0054  memory: 719  loss: 1.5070  loss_cls: 0.3138  loss_bbox: 0.5358  loss_dfl: 0.2118  loss_ld: 0.4456
2023/07/13 10:31:59 - mmengine - INFO - Epoch(train)  [6][ 450/3139]  lr: 1.2500e-03  eta: 1:56:07  time: 0.3245  data_time: 0.0044  memory: 728  loss: 1.4172  loss_cls: 0.2548  loss_bbox: 0.5908  loss_dfl: 0.2084  loss_ld: 0.3631
2023/07/13 10:32:15 - mmengine - INFO - Epoch(train)  [6][ 500/3139]  lr: 1.2500e-03  eta: 1:55:51  time: 0.3260  data_time: 0.0056  memory: 723  loss: 1.5151  loss_cls: 0.2702  loss_bbox: 0.5687  loss_dfl: 0.2127  loss_ld: 0.4635
2023/07/13 10:32:31 - mmengine - INFO - Epoch(train)  [6][ 550/3139]  lr: 1.2500e-03  eta: 1:55:35  time: 0.3225  data_time: 0.0037  memory: 716  loss: 1.4598  loss_cls: 0.3019  loss_bbox: 0.5408  loss_dfl: 0.2196  loss_ld: 0.3975
2023/07/13 10:32:47 - mmengine - INFO - Epoch(train)  [6][ 600/3139]  lr: 1.2500e-03  eta: 1:55:19  time: 0.3244  data_time: 0.0041  memory: 752  loss: 1.3938  loss_cls: 0.2829  loss_bbox: 0.5321  loss_dfl: 0.1991  loss_ld: 0.3797
2023/07/13 10:33:03 - mmengine - INFO - Epoch(train)  [6][ 650/3139]  lr: 1.2500e-03  eta: 1:55:03  time: 0.3235  data_time: 0.0041  memory: 719  loss: 1.4508  loss_cls: 0.3349  loss_bbox: 0.5523  loss_dfl: 0.2130  loss_ld: 0.3506
2023/07/13 10:33:20 - mmengine - INFO - Epoch(train)  [6][ 700/3139]  lr: 1.2500e-03  eta: 1:54:47  time: 0.3254  data_time: 0.0049  memory: 720  loss: 1.5036  loss_cls: 0.2665  loss_bbox: 0.5783  loss_dfl: 0.2118  loss_ld: 0.4469
2023/07/13 10:33:36 - mmengine - INFO - Epoch(train)  [6][ 750/3139]  lr: 1.2500e-03  eta: 1:54:30  time: 0.3223  data_time: 0.0035  memory: 734  loss: 1.5234  loss_cls: 0.2776  loss_bbox: 0.6122  loss_dfl: 0.2248  loss_ld: 0.4088
2023/07/13 10:33:52 - mmengine - INFO - Epoch(train)  [6][ 800/3139]  lr: 1.2500e-03  eta: 1:54:14  time: 0.3269  data_time: 0.0046  memory: 735  loss: 1.4862  loss_cls: 0.3002  loss_bbox: 0.5691  loss_dfl: 0.2206  loss_ld: 0.3963
2023/07/13 10:34:08 - mmengine - INFO - Epoch(train)  [6][ 850/3139]  lr: 1.2500e-03  eta: 1:53:58  time: 0.3233  data_time: 0.0035  memory: 723  loss: 1.4806  loss_cls: 0.2956  loss_bbox: 0.5461  loss_dfl: 0.2146  loss_ld: 0.4244
2023/07/13 10:34:25 - mmengine - INFO - Epoch(train)  [6][ 900/3139]  lr: 1.2500e-03  eta: 1:53:42  time: 0.3234  data_time: 0.0039  memory: 727  loss: 1.4754  loss_cls: 0.2752  loss_bbox: 0.5859  loss_dfl: 0.2192  loss_ld: 0.3950
2023/07/13 10:34:41 - mmengine - INFO - Epoch(train)  [6][ 950/3139]  lr: 1.2500e-03  eta: 1:53:26  time: 0.3227  data_time: 0.0037  memory: 718  loss: 1.4499  loss_cls: 0.2701  loss_bbox: 0.6056  loss_dfl: 0.2184  loss_ld: 0.3558
2023/07/13 10:34:57 - mmengine - INFO - Epoch(train)  [6][1000/3139]  lr: 1.2500e-03  eta: 1:53:09  time: 0.3218  data_time: 0.0040  memory: 723  loss: 1.4863  loss_cls: 0.3108  loss_bbox: 0.5472  loss_dfl: 0.2163  loss_ld: 0.4120
2023/07/13 10:35:13 - mmengine - INFO - Epoch(train)  [6][1050/3139]  lr: 1.2500e-03  eta: 1:52:53  time: 0.3269  data_time: 0.0049  memory: 724  loss: 1.5582  loss_cls: 0.2787  loss_bbox: 0.6120  loss_dfl: 0.2298  loss_ld: 0.4377
2023/07/13 10:35:29 - mmengine - INFO - Epoch(train)  [6][1100/3139]  lr: 1.2500e-03  eta: 1:52:37  time: 0.3248  data_time: 0.0038  memory: 736  loss: 1.4991  loss_cls: 0.3142  loss_bbox: 0.5664  loss_dfl: 0.2184  loss_ld: 0.4001
2023/07/13 10:35:46 - mmengine - INFO - Epoch(train)  [6][1150/3139]  lr: 1.2500e-03  eta: 1:52:21  time: 0.3237  data_time: 0.0044  memory: 718  loss: 1.4970  loss_cls: 0.2965  loss_bbox: 0.5799  loss_dfl: 0.2221  loss_ld: 0.3985
2023/07/13 10:36:02 - mmengine - INFO - Epoch(train)  [6][1200/3139]  lr: 1.2500e-03  eta: 1:52:05  time: 0.3224  data_time: 0.0038  memory: 722  loss: 1.5052  loss_cls: 0.2926  loss_bbox: 0.5439  loss_dfl: 0.2098  loss_ld: 0.4588
2023/07/13 10:36:18 - mmengine - INFO - Epoch(train)  [6][1250/3139]  lr: 1.2500e-03  eta: 1:51:49  time: 0.3286  data_time: 0.0052  memory: 738  loss: 1.5513  loss_cls: 0.2676  loss_bbox: 0.5861  loss_dfl: 0.2146  loss_ld: 0.4830
2023/07/13 10:36:34 - mmengine - INFO - Epoch(train)  [6][1300/3139]  lr: 1.2500e-03  eta: 1:51:32  time: 0.3180  data_time: 0.0038  memory: 733  loss: 1.3892  loss_cls: 0.3083  loss_bbox: 0.5267  loss_dfl: 0.2073  loss_ld: 0.3470
2023/07/13 10:36:36 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:36:50 - mmengine - INFO - Epoch(train)  [6][1350/3139]  lr: 1.2500e-03  eta: 1:51:16  time: 0.3210  data_time: 0.0043  memory: 722  loss: 1.4809  loss_cls: 0.3612  loss_bbox: 0.5595  loss_dfl: 0.2209  loss_ld: 0.3392
2023/07/13 10:37:06 - mmengine - INFO - Epoch(train)  [6][1400/3139]  lr: 1.2500e-03  eta: 1:51:00  time: 0.3244  data_time: 0.0042  memory: 731  loss: 1.5203  loss_cls: 0.3002  loss_bbox: 0.5608  loss_dfl: 0.2176  loss_ld: 0.4417
2023/07/13 10:37:23 - mmengine - INFO - Epoch(train)  [6][1450/3139]  lr: 1.2500e-03  eta: 1:50:44  time: 0.3268  data_time: 0.0046  memory: 738  loss: 1.4336  loss_cls: 0.2933  loss_bbox: 0.5227  loss_dfl: 0.2069  loss_ld: 0.4108
2023/07/13 10:37:39 - mmengine - INFO - Epoch(train)  [6][1500/3139]  lr: 1.2500e-03  eta: 1:50:28  time: 0.3232  data_time: 0.0043  memory: 727  loss: 1.4834  loss_cls: 0.2647  loss_bbox: 0.5462  loss_dfl: 0.2126  loss_ld: 0.4599
2023/07/13 10:37:55 - mmengine - INFO - Epoch(train)  [6][1550/3139]  lr: 1.2500e-03  eta: 1:50:11  time: 0.3241  data_time: 0.0044  memory: 728  loss: 1.4552  loss_cls: 0.2768  loss_bbox: 0.5508  loss_dfl: 0.2214  loss_ld: 0.4061
2023/07/13 10:38:11 - mmengine - INFO - Epoch(train)  [6][1600/3139]  lr: 1.2500e-03  eta: 1:49:55  time: 0.3248  data_time: 0.0042  memory: 730  loss: 1.4521  loss_cls: 0.2779  loss_bbox: 0.5500  loss_dfl: 0.2080  loss_ld: 0.4163
2023/07/13 10:38:28 - mmengine - INFO - Epoch(train)  [6][1650/3139]  lr: 1.2500e-03  eta: 1:49:39  time: 0.3245  data_time: 0.0043  memory: 748  loss: 1.5542  loss_cls: 0.2811  loss_bbox: 0.6290  loss_dfl: 0.2221  loss_ld: 0.4220
2023/07/13 10:38:44 - mmengine - INFO - Epoch(train)  [6][1700/3139]  lr: 1.2500e-03  eta: 1:49:23  time: 0.3239  data_time: 0.0041  memory: 719  loss: 1.4406  loss_cls: 0.2942  loss_bbox: 0.5626  loss_dfl: 0.2077  loss_ld: 0.3760
2023/07/13 10:39:00 - mmengine - INFO - Epoch(train)  [6][1750/3139]  lr: 1.2500e-03  eta: 1:49:07  time: 0.3245  data_time: 0.0044  memory: 731  loss: 1.4180  loss_cls: 0.2688  loss_bbox: 0.5571  loss_dfl: 0.2052  loss_ld: 0.3868
2023/07/13 10:39:16 - mmengine - INFO - Epoch(train)  [6][1800/3139]  lr: 1.2500e-03  eta: 1:48:51  time: 0.3253  data_time: 0.0053  memory: 728  loss: 1.4703  loss_cls: 0.3352  loss_bbox: 0.5732  loss_dfl: 0.2187  loss_ld: 0.3433
2023/07/13 10:39:32 - mmengine - INFO - Epoch(train)  [6][1850/3139]  lr: 1.2500e-03  eta: 1:48:35  time: 0.3231  data_time: 0.0039  memory: 743  loss: 1.4461  loss_cls: 0.2791  loss_bbox: 0.5771  loss_dfl: 0.2146  loss_ld: 0.3754
2023/07/13 10:39:49 - mmengine - INFO - Epoch(train)  [6][1900/3139]  lr: 1.2500e-03  eta: 1:48:18  time: 0.3255  data_time: 0.0048  memory: 728  loss: 1.4641  loss_cls: 0.2846  loss_bbox: 0.5721  loss_dfl: 0.2111  loss_ld: 0.3963
2023/07/13 10:40:05 - mmengine - INFO - Epoch(train)  [6][1950/3139]  lr: 1.2500e-03  eta: 1:48:02  time: 0.3226  data_time: 0.0038  memory: 723  loss: 1.3658  loss_cls: 0.2993  loss_bbox: 0.5270  loss_dfl: 0.2028  loss_ld: 0.3366
2023/07/13 10:40:21 - mmengine - INFO - Epoch(train)  [6][2000/3139]  lr: 1.2500e-03  eta: 1:47:46  time: 0.3259  data_time: 0.0047  memory: 724  loss: 1.4734  loss_cls: 0.3104  loss_bbox: 0.5660  loss_dfl: 0.2117  loss_ld: 0.3853
2023/07/13 10:40:37 - mmengine - INFO - Epoch(train)  [6][2050/3139]  lr: 1.2500e-03  eta: 1:47:30  time: 0.3161  data_time: 0.0035  memory: 713  loss: 1.4723  loss_cls: 0.2883  loss_bbox: 0.5558  loss_dfl: 0.2117  loss_ld: 0.4165
2023/07/13 10:40:53 - mmengine - INFO - Epoch(train)  [6][2100/3139]  lr: 1.2500e-03  eta: 1:47:13  time: 0.3215  data_time: 0.0050  memory: 729  loss: 1.4494  loss_cls: 0.2626  loss_bbox: 0.5574  loss_dfl: 0.2081  loss_ld: 0.4213
2023/07/13 10:41:09 - mmengine - INFO - Epoch(train)  [6][2150/3139]  lr: 1.2500e-03  eta: 1:46:57  time: 0.3212  data_time: 0.0044  memory: 725  loss: 1.3984  loss_cls: 0.2915  loss_bbox: 0.5740  loss_dfl: 0.2049  loss_ld: 0.3281
2023/07/13 10:41:25 - mmengine - INFO - Epoch(train)  [6][2200/3139]  lr: 1.2500e-03  eta: 1:46:41  time: 0.3220  data_time: 0.0042  memory: 722  loss: 1.4249  loss_cls: 0.2788  loss_bbox: 0.5516  loss_dfl: 0.2099  loss_ld: 0.3846
2023/07/13 10:41:41 - mmengine - INFO - Epoch(train)  [6][2250/3139]  lr: 1.2500e-03  eta: 1:46:24  time: 0.3222  data_time: 0.0038  memory: 719  loss: 1.4156  loss_cls: 0.3045  loss_bbox: 0.4991  loss_dfl: 0.2054  loss_ld: 0.4065
2023/07/13 10:41:57 - mmengine - INFO - Epoch(train)  [6][2300/3139]  lr: 1.2500e-03  eta: 1:46:08  time: 0.3237  data_time: 0.0037  memory: 746  loss: 1.4969  loss_cls: 0.2672  loss_bbox: 0.5588  loss_dfl: 0.2126  loss_ld: 0.4583
2023/07/13 10:41:59 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:42:14 - mmengine - INFO - Epoch(train)  [6][2350/3139]  lr: 1.2500e-03  eta: 1:45:52  time: 0.3241  data_time: 0.0047  memory: 722  loss: 1.5010  loss_cls: 0.2939  loss_bbox: 0.5682  loss_dfl: 0.2199  loss_ld: 0.4189
2023/07/13 10:42:30 - mmengine - INFO - Epoch(train)  [6][2400/3139]  lr: 1.2500e-03  eta: 1:45:36  time: 0.3237  data_time: 0.0039  memory: 724  loss: 1.5057  loss_cls: 0.2798  loss_bbox: 0.5945  loss_dfl: 0.2141  loss_ld: 0.4174
2023/07/13 10:42:46 - mmengine - INFO - Epoch(train)  [6][2450/3139]  lr: 1.2500e-03  eta: 1:45:20  time: 0.3283  data_time: 0.0060  memory: 722  loss: 1.4331  loss_cls: 0.2923  loss_bbox: 0.5607  loss_dfl: 0.2111  loss_ld: 0.3690
2023/07/13 10:43:02 - mmengine - INFO - Epoch(train)  [6][2500/3139]  lr: 1.2500e-03  eta: 1:45:04  time: 0.3232  data_time: 0.0042  memory: 729  loss: 1.5680  loss_cls: 0.2843  loss_bbox: 0.5956  loss_dfl: 0.2162  loss_ld: 0.4719
2023/07/13 10:43:19 - mmengine - INFO - Epoch(train)  [6][2550/3139]  lr: 1.2500e-03  eta: 1:44:47  time: 0.3237  data_time: 0.0045  memory: 731  loss: 1.4080  loss_cls: 0.2632  loss_bbox: 0.5278  loss_dfl: 0.2045  loss_ld: 0.4124
2023/07/13 10:43:35 - mmengine - INFO - Epoch(train)  [6][2600/3139]  lr: 1.2500e-03  eta: 1:44:31  time: 0.3246  data_time: 0.0044  memory: 720  loss: 1.5215  loss_cls: 0.2894  loss_bbox: 0.5754  loss_dfl: 0.2162  loss_ld: 0.4405
2023/07/13 10:43:51 - mmengine - INFO - Epoch(train)  [6][2650/3139]  lr: 1.2500e-03  eta: 1:44:15  time: 0.3241  data_time: 0.0043  memory: 735  loss: 1.4660  loss_cls: 0.2775  loss_bbox: 0.5578  loss_dfl: 0.2146  loss_ld: 0.4161
2023/07/13 10:44:07 - mmengine - INFO - Epoch(train)  [6][2700/3139]  lr: 1.2500e-03  eta: 1:43:59  time: 0.3237  data_time: 0.0040  memory: 725  loss: 1.4928  loss_cls: 0.2724  loss_bbox: 0.5535  loss_dfl: 0.2104  loss_ld: 0.4565
2023/07/13 10:44:24 - mmengine - INFO - Epoch(train)  [6][2750/3139]  lr: 1.2500e-03  eta: 1:43:43  time: 0.3253  data_time: 0.0040  memory: 723  loss: 1.5198  loss_cls: 0.2872  loss_bbox: 0.5783  loss_dfl: 0.2212  loss_ld: 0.4330
2023/07/13 10:44:40 - mmengine - INFO - Epoch(train)  [6][2800/3139]  lr: 1.2500e-03  eta: 1:43:27  time: 0.3264  data_time: 0.0048  memory: 734  loss: 1.5031  loss_cls: 0.2930  loss_bbox: 0.5906  loss_dfl: 0.2175  loss_ld: 0.4020
2023/07/13 10:44:56 - mmengine - INFO - Epoch(train)  [6][2850/3139]  lr: 1.2500e-03  eta: 1:43:11  time: 0.3250  data_time: 0.0041  memory: 730  loss: 1.4463  loss_cls: 0.2796  loss_bbox: 0.5601  loss_dfl: 0.2109  loss_ld: 0.3957
2023/07/13 10:45:12 - mmengine - INFO - Epoch(train)  [6][2900/3139]  lr: 1.2500e-03  eta: 1:42:55  time: 0.3249  data_time: 0.0038  memory: 721  loss: 1.4619  loss_cls: 0.2732  loss_bbox: 0.5594  loss_dfl: 0.2152  loss_ld: 0.4141
2023/07/13 10:45:28 - mmengine - INFO - Epoch(train)  [6][2950/3139]  lr: 1.2500e-03  eta: 1:42:38  time: 0.3227  data_time: 0.0038  memory: 726  loss: 1.4056  loss_cls: 0.2890  loss_bbox: 0.5090  loss_dfl: 0.2046  loss_ld: 0.4030
2023/07/13 10:45:45 - mmengine - INFO - Epoch(train)  [6][3000/3139]  lr: 1.2500e-03  eta: 1:42:22  time: 0.3208  data_time: 0.0035  memory: 717  loss: 1.4688  loss_cls: 0.2788  loss_bbox: 0.5626  loss_dfl: 0.2112  loss_ld: 0.4162
2023/07/13 10:46:01 - mmengine - INFO - Epoch(train)  [6][3050/3139]  lr: 1.2500e-03  eta: 1:42:06  time: 0.3250  data_time: 0.0039  memory: 717  loss: 1.3784  loss_cls: 0.2680  loss_bbox: 0.5499  loss_dfl: 0.2060  loss_ld: 0.3545
2023/07/13 10:46:17 - mmengine - INFO - Epoch(train)  [6][3100/3139]  lr: 1.2500e-03  eta: 1:41:50  time: 0.3260  data_time: 0.0054  memory: 724  loss: 1.3641  loss_cls: 0.2749  loss_bbox: 0.5394  loss_dfl: 0.2040  loss_ld: 0.3458
2023/07/13 10:46:30 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:46:30 - mmengine - INFO - Saving checkpoint at 6 epochs
2023/07/13 10:46:36 - mmengine - INFO - Epoch(val)  [6][ 50/548]    eta: 0:00:40  time: 0.0817  data_time: 0.0023  memory: 728  
2023/07/13 10:46:40 - mmengine - INFO - Epoch(val)  [6][100/548]    eta: 0:00:36  time: 0.0810  data_time: 0.0016  memory: 497  
2023/07/13 10:46:44 - mmengine - INFO - Epoch(val)  [6][150/548]    eta: 0:00:32  time: 0.0815  data_time: 0.0015  memory: 497  
2023/07/13 10:46:48 - mmengine - INFO - Epoch(val)  [6][200/548]    eta: 0:00:28  time: 0.0807  data_time: 0.0015  memory: 497  
2023/07/13 10:46:52 - mmengine - INFO - Epoch(val)  [6][250/548]    eta: 0:00:24  time: 0.0810  data_time: 0.0015  memory: 497  
2023/07/13 10:46:56 - mmengine - INFO - Epoch(val)  [6][300/548]    eta: 0:00:20  time: 0.0806  data_time: 0.0016  memory: 497  
2023/07/13 10:47:01 - mmengine - INFO - Epoch(val)  [6][350/548]    eta: 0:00:16  time: 0.0803  data_time: 0.0015  memory: 497  
2023/07/13 10:47:05 - mmengine - INFO - Epoch(val)  [6][400/548]    eta: 0:00:11  time: 0.0801  data_time: 0.0015  memory: 497  
2023/07/13 10:47:09 - mmengine - INFO - Epoch(val)  [6][450/548]    eta: 0:00:07  time: 0.0821  data_time: 0.0016  memory: 497  
2023/07/13 10:47:13 - mmengine - INFO - Epoch(val)  [6][500/548]    eta: 0:00:03  time: 0.0804  data_time: 0.0015  memory: 497  
2023/07/13 10:47:17 - mmengine - INFO - Evaluating bbox...
2023/07/13 10:47:33 - mmengine - INFO - bbox_mAP_copypaste: 0.079 0.138 0.083 0.021 0.121 0.220
2023/07/13 10:47:33 - mmengine - INFO - Epoch(val) [6][548/548]    coco/bbox_mAP: 0.0790  coco/bbox_mAP_50: 0.1380  coco/bbox_mAP_75: 0.0830  coco/bbox_mAP_s: 0.0210  coco/bbox_mAP_m: 0.1210  coco/bbox_mAP_l: 0.2200  data_time: 0.0016  time: 0.0808
2023/07/13 10:47:49 - mmengine - INFO - Epoch(train)  [7][  50/3139]  lr: 1.2500e-03  eta: 1:41:21  time: 0.3265  data_time: 0.0065  memory: 724  loss: 1.4282  loss_cls: 0.3088  loss_bbox: 0.4985  loss_dfl: 0.2078  loss_ld: 0.4131
2023/07/13 10:48:05 - mmengine - INFO - Epoch(train)  [7][ 100/3139]  lr: 1.2500e-03  eta: 1:41:05  time: 0.3245  data_time: 0.0045  memory: 720  loss: 1.4331  loss_cls: 0.2812  loss_bbox: 0.5627  loss_dfl: 0.2104  loss_ld: 0.3788
2023/07/13 10:48:22 - mmengine - INFO - Epoch(train)  [7][ 150/3139]  lr: 1.2500e-03  eta: 1:40:49  time: 0.3252  data_time: 0.0056  memory: 726  loss: 1.3833  loss_cls: 0.2901  loss_bbox: 0.5681  loss_dfl: 0.2131  loss_ld: 0.3121
2023/07/13 10:48:27 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:48:38 - mmengine - INFO - Epoch(train)  [7][ 200/3139]  lr: 1.2500e-03  eta: 1:40:33  time: 0.3268  data_time: 0.0061  memory: 735  loss: 1.4552  loss_cls: 0.2859  loss_bbox: 0.5476  loss_dfl: 0.2133  loss_ld: 0.4083
2023/07/13 10:48:54 - mmengine - INFO - Epoch(train)  [7][ 250/3139]  lr: 1.2500e-03  eta: 1:40:16  time: 0.3198  data_time: 0.0047  memory: 728  loss: 1.4024  loss_cls: 0.2867  loss_bbox: 0.5826  loss_dfl: 0.2133  loss_ld: 0.3198
2023/07/13 10:49:10 - mmengine - INFO - Epoch(train)  [7][ 300/3139]  lr: 1.2500e-03  eta: 1:40:00  time: 0.3207  data_time: 0.0044  memory: 722  loss: 1.4317  loss_cls: 0.2868  loss_bbox: 0.5349  loss_dfl: 0.2092  loss_ld: 0.4008
2023/07/13 10:49:26 - mmengine - INFO - Epoch(train)  [7][ 350/3139]  lr: 1.2500e-03  eta: 1:39:43  time: 0.3187  data_time: 0.0039  memory: 732  loss: 1.4014  loss_cls: 0.3009  loss_bbox: 0.5011  loss_dfl: 0.2017  loss_ld: 0.3978
2023/07/13 10:49:42 - mmengine - INFO - Epoch(train)  [7][ 400/3139]  lr: 1.2500e-03  eta: 1:39:27  time: 0.3203  data_time: 0.0038  memory: 719  loss: 1.4316  loss_cls: 0.2699  loss_bbox: 0.5013  loss_dfl: 0.2052  loss_ld: 0.4551
2023/07/13 10:49:58 - mmengine - INFO - Epoch(train)  [7][ 450/3139]  lr: 1.2500e-03  eta: 1:39:11  time: 0.3214  data_time: 0.0039  memory: 734  loss: 1.4775  loss_cls: 0.3040  loss_bbox: 0.5289  loss_dfl: 0.2137  loss_ld: 0.4309
2023/07/13 10:50:14 - mmengine - INFO - Epoch(train)  [7][ 500/3139]  lr: 1.2500e-03  eta: 1:38:55  time: 0.3250  data_time: 0.0037  memory: 746  loss: 1.5016  loss_cls: 0.2934  loss_bbox: 0.5204  loss_dfl: 0.2091  loss_ld: 0.4788
2023/07/13 10:50:30 - mmengine - INFO - Epoch(train)  [7][ 550/3139]  lr: 1.2500e-03  eta: 1:38:39  time: 0.3232  data_time: 0.0049  memory: 727  loss: 1.4515  loss_cls: 0.3007  loss_bbox: 0.5379  loss_dfl: 0.2080  loss_ld: 0.4050
2023/07/13 10:50:47 - mmengine - INFO - Epoch(train)  [7][ 600/3139]  lr: 1.2500e-03  eta: 1:38:22  time: 0.3228  data_time: 0.0048  memory: 720  loss: 1.4159  loss_cls: 0.2875  loss_bbox: 0.5381  loss_dfl: 0.2040  loss_ld: 0.3862
2023/07/13 10:51:03 - mmengine - INFO - Epoch(train)  [7][ 650/3139]  lr: 1.2500e-03  eta: 1:38:06  time: 0.3247  data_time: 0.0042  memory: 739  loss: 1.4810  loss_cls: 0.2779  loss_bbox: 0.5765  loss_dfl: 0.2124  loss_ld: 0.4141
2023/07/13 10:51:19 - mmengine - INFO - Epoch(train)  [7][ 700/3139]  lr: 1.2500e-03  eta: 1:37:50  time: 0.3217  data_time: 0.0040  memory: 734  loss: 1.4030  loss_cls: 0.2868  loss_bbox: 0.5622  loss_dfl: 0.2083  loss_ld: 0.3457
2023/07/13 10:51:35 - mmengine - INFO - Epoch(train)  [7][ 750/3139]  lr: 1.2500e-03  eta: 1:37:34  time: 0.3262  data_time: 0.0041  memory: 761  loss: 1.4338  loss_cls: 0.2674  loss_bbox: 0.5626  loss_dfl: 0.2059  loss_ld: 0.3979
2023/07/13 10:51:51 - mmengine - INFO - Epoch(train)  [7][ 800/3139]  lr: 1.2500e-03  eta: 1:37:18  time: 0.3229  data_time: 0.0043  memory: 724  loss: 1.3891  loss_cls: 0.2639  loss_bbox: 0.5826  loss_dfl: 0.2100  loss_ld: 0.3325
2023/07/13 10:52:08 - mmengine - INFO - Epoch(train)  [7][ 850/3139]  lr: 1.2500e-03  eta: 1:37:02  time: 0.3276  data_time: 0.0048  memory: 726  loss: 1.4284  loss_cls: 0.2779  loss_bbox: 0.5264  loss_dfl: 0.2083  loss_ld: 0.4158
2023/07/13 10:52:24 - mmengine - INFO - Epoch(train)  [7][ 900/3139]  lr: 1.2500e-03  eta: 1:36:45  time: 0.3217  data_time: 0.0038  memory: 743  loss: 1.3843  loss_cls: 0.2664  loss_bbox: 0.5160  loss_dfl: 0.2044  loss_ld: 0.3975
2023/07/13 10:52:40 - mmengine - INFO - Epoch(train)  [7][ 950/3139]  lr: 1.2500e-03  eta: 1:36:29  time: 0.3223  data_time: 0.0037  memory: 730  loss: 1.3875  loss_cls: 0.2692  loss_bbox: 0.5216  loss_dfl: 0.2036  loss_ld: 0.3931
2023/07/13 10:52:56 - mmengine - INFO - Epoch(train)  [7][1000/3139]  lr: 1.2500e-03  eta: 1:36:13  time: 0.3258  data_time: 0.0058  memory: 737  loss: 1.3626  loss_cls: 0.2817  loss_bbox: 0.5184  loss_dfl: 0.2033  loss_ld: 0.3592
2023/07/13 10:53:13 - mmengine - INFO - Epoch(train)  [7][1050/3139]  lr: 1.2500e-03  eta: 1:35:57  time: 0.3250  data_time: 0.0049  memory: 720  loss: 1.3209  loss_cls: 0.2784  loss_bbox: 0.5009  loss_dfl: 0.2009  loss_ld: 0.3406
2023/07/13 10:53:29 - mmengine - INFO - Epoch(train)  [7][1100/3139]  lr: 1.2500e-03  eta: 1:35:41  time: 0.3246  data_time: 0.0037  memory: 721  loss: 1.4186  loss_cls: 0.2610  loss_bbox: 0.5822  loss_dfl: 0.2118  loss_ld: 0.3637
2023/07/13 10:53:45 - mmengine - INFO - Epoch(train)  [7][1150/3139]  lr: 1.2500e-03  eta: 1:35:24  time: 0.3211  data_time: 0.0045  memory: 729  loss: 1.4968  loss_cls: 0.2721  loss_bbox: 0.5888  loss_dfl: 0.2159  loss_ld: 0.4200
2023/07/13 10:53:50 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:54:01 - mmengine - INFO - Epoch(train)  [7][1200/3139]  lr: 1.2500e-03  eta: 1:35:08  time: 0.3225  data_time: 0.0037  memory: 720  loss: 1.4002  loss_cls: 0.2731  loss_bbox: 0.5268  loss_dfl: 0.2103  loss_ld: 0.3900
2023/07/13 10:54:17 - mmengine - INFO - Epoch(train)  [7][1250/3139]  lr: 1.2500e-03  eta: 1:34:52  time: 0.3254  data_time: 0.0039  memory: 748  loss: 1.3912  loss_cls: 0.3139  loss_bbox: 0.5369  loss_dfl: 0.2080  loss_ld: 0.3323
2023/07/13 10:54:33 - mmengine - INFO - Epoch(train)  [7][1300/3139]  lr: 1.2500e-03  eta: 1:34:36  time: 0.3229  data_time: 0.0040  memory: 730  loss: 1.3949  loss_cls: 0.2664  loss_bbox: 0.5187  loss_dfl: 0.2012  loss_ld: 0.4086
2023/07/13 10:54:50 - mmengine - INFO - Epoch(train)  [7][1350/3139]  lr: 1.2500e-03  eta: 1:34:20  time: 0.3245  data_time: 0.0052  memory: 718  loss: 1.3823  loss_cls: 0.3054  loss_bbox: 0.4844  loss_dfl: 0.2002  loss_ld: 0.3923
2023/07/13 10:55:06 - mmengine - INFO - Epoch(train)  [7][1400/3139]  lr: 1.2500e-03  eta: 1:34:03  time: 0.3220  data_time: 0.0047  memory: 726  loss: 1.3197  loss_cls: 0.2879  loss_bbox: 0.5139  loss_dfl: 0.1977  loss_ld: 0.3202
2023/07/13 10:55:22 - mmengine - INFO - Epoch(train)  [7][1450/3139]  lr: 1.2500e-03  eta: 1:33:47  time: 0.3237  data_time: 0.0044  memory: 725  loss: 1.5088  loss_cls: 0.2747  loss_bbox: 0.6048  loss_dfl: 0.2213  loss_ld: 0.4080
2023/07/13 10:55:38 - mmengine - INFO - Epoch(train)  [7][1500/3139]  lr: 1.2500e-03  eta: 1:33:31  time: 0.3250  data_time: 0.0051  memory: 725  loss: 1.4431  loss_cls: 0.2634  loss_bbox: 0.5638  loss_dfl: 0.2105  loss_ld: 0.4054
2023/07/13 10:55:54 - mmengine - INFO - Epoch(train)  [7][1550/3139]  lr: 1.2500e-03  eta: 1:33:15  time: 0.3245  data_time: 0.0049  memory: 724  loss: 1.3571  loss_cls: 0.2884  loss_bbox: 0.5246  loss_dfl: 0.2049  loss_ld: 0.3393
2023/07/13 10:56:11 - mmengine - INFO - Epoch(train)  [7][1600/3139]  lr: 1.2500e-03  eta: 1:32:59  time: 0.3229  data_time: 0.0036  memory: 716  loss: 1.4895  loss_cls: 0.2868  loss_bbox: 0.5969  loss_dfl: 0.2219  loss_ld: 0.3839
2023/07/13 10:56:27 - mmengine - INFO - Epoch(train)  [7][1650/3139]  lr: 1.2500e-03  eta: 1:32:42  time: 0.3235  data_time: 0.0043  memory: 739  loss: 1.4965  loss_cls: 0.3061  loss_bbox: 0.5693  loss_dfl: 0.2102  loss_ld: 0.4109
2023/07/13 10:56:43 - mmengine - INFO - Epoch(train)  [7][1700/3139]  lr: 1.2500e-03  eta: 1:32:26  time: 0.3229  data_time: 0.0041  memory: 736  loss: 1.4203  loss_cls: 0.2793  loss_bbox: 0.5563  loss_dfl: 0.2098  loss_ld: 0.3748
2023/07/13 10:56:59 - mmengine - INFO - Epoch(train)  [7][1750/3139]  lr: 1.2500e-03  eta: 1:32:10  time: 0.3223  data_time: 0.0049  memory: 752  loss: 1.3984  loss_cls: 0.2780  loss_bbox: 0.5484  loss_dfl: 0.2026  loss_ld: 0.3694
2023/07/13 10:57:15 - mmengine - INFO - Epoch(train)  [7][1800/3139]  lr: 1.2500e-03  eta: 1:31:54  time: 0.3237  data_time: 0.0044  memory: 722  loss: 1.4150  loss_cls: 0.2687  loss_bbox: 0.5425  loss_dfl: 0.2110  loss_ld: 0.3929
2023/07/13 10:57:31 - mmengine - INFO - Epoch(train)  [7][1850/3139]  lr: 1.2500e-03  eta: 1:31:38  time: 0.3242  data_time: 0.0046  memory: 720  loss: 1.3582  loss_cls: 0.2694  loss_bbox: 0.5212  loss_dfl: 0.2048  loss_ld: 0.3628
2023/07/13 10:57:48 - mmengine - INFO - Epoch(train)  [7][1900/3139]  lr: 1.2500e-03  eta: 1:31:21  time: 0.3222  data_time: 0.0039  memory: 715  loss: 1.4383  loss_cls: 0.3133  loss_bbox: 0.5498  loss_dfl: 0.2162  loss_ld: 0.3590
2023/07/13 10:58:04 - mmengine - INFO - Epoch(train)  [7][1950/3139]  lr: 1.2500e-03  eta: 1:31:05  time: 0.3250  data_time: 0.0040  memory: 715  loss: 1.3908  loss_cls: 0.3072  loss_bbox: 0.5531  loss_dfl: 0.2095  loss_ld: 0.3211
2023/07/13 10:58:20 - mmengine - INFO - Epoch(train)  [7][2000/3139]  lr: 1.2500e-03  eta: 1:30:49  time: 0.3248  data_time: 0.0043  memory: 731  loss: 1.3431  loss_cls: 0.2497  loss_bbox: 0.5300  loss_dfl: 0.1986  loss_ld: 0.3648
2023/07/13 10:58:36 - mmengine - INFO - Epoch(train)  [7][2050/3139]  lr: 1.2500e-03  eta: 1:30:33  time: 0.3244  data_time: 0.0041  memory: 722  loss: 1.5324  loss_cls: 0.2862  loss_bbox: 0.5753  loss_dfl: 0.2154  loss_ld: 0.4555
2023/07/13 10:58:53 - mmengine - INFO - Epoch(train)  [7][2100/3139]  lr: 1.2500e-03  eta: 1:30:17  time: 0.3270  data_time: 0.0054  memory: 725  loss: 1.4519  loss_cls: 0.2715  loss_bbox: 0.5522  loss_dfl: 0.2122  loss_ld: 0.4160
2023/07/13 10:59:09 - mmengine - INFO - Epoch(train)  [7][2150/3139]  lr: 1.2500e-03  eta: 1:30:01  time: 0.3244  data_time: 0.0046  memory: 728  loss: 1.2961  loss_cls: 0.2710  loss_bbox: 0.4890  loss_dfl: 0.1981  loss_ld: 0.3380
2023/07/13 10:59:14 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 10:59:25 - mmengine - INFO - Epoch(train)  [7][2200/3139]  lr: 1.2500e-03  eta: 1:29:45  time: 0.3239  data_time: 0.0045  memory: 727  loss: 1.4459  loss_cls: 0.2990  loss_bbox: 0.5610  loss_dfl: 0.2161  loss_ld: 0.3698
2023/07/13 10:59:41 - mmengine - INFO - Epoch(train)  [7][2250/3139]  lr: 1.2500e-03  eta: 1:29:28  time: 0.3237  data_time: 0.0062  memory: 721  loss: 1.3848  loss_cls: 0.2766  loss_bbox: 0.5441  loss_dfl: 0.2128  loss_ld: 0.3512
2023/07/13 10:59:57 - mmengine - INFO - Epoch(train)  [7][2300/3139]  lr: 1.2500e-03  eta: 1:29:12  time: 0.3244  data_time: 0.0047  memory: 738  loss: 1.2992  loss_cls: 0.2924  loss_bbox: 0.5005  loss_dfl: 0.1972  loss_ld: 0.3091
2023/07/13 11:00:14 - mmengine - INFO - Epoch(train)  [7][2350/3139]  lr: 1.2500e-03  eta: 1:28:56  time: 0.3244  data_time: 0.0050  memory: 723  loss: 1.4591  loss_cls: 0.3058  loss_bbox: 0.5811  loss_dfl: 0.2144  loss_ld: 0.3578
2023/07/13 11:00:30 - mmengine - INFO - Epoch(train)  [7][2400/3139]  lr: 1.2500e-03  eta: 1:28:40  time: 0.3259  data_time: 0.0042  memory: 723  loss: 1.4369  loss_cls: 0.2912  loss_bbox: 0.5689  loss_dfl: 0.2135  loss_ld: 0.3632
2023/07/13 11:00:46 - mmengine - INFO - Epoch(train)  [7][2450/3139]  lr: 1.2500e-03  eta: 1:28:24  time: 0.3231  data_time: 0.0045  memory: 716  loss: 1.4387  loss_cls: 0.2817  loss_bbox: 0.5644  loss_dfl: 0.2103  loss_ld: 0.3824
2023/07/13 11:01:02 - mmengine - INFO - Epoch(train)  [7][2500/3139]  lr: 1.2500e-03  eta: 1:28:08  time: 0.3237  data_time: 0.0043  memory: 725  loss: 1.3705  loss_cls: 0.2750  loss_bbox: 0.4959  loss_dfl: 0.2020  loss_ld: 0.3976
2023/07/13 11:01:19 - mmengine - INFO - Epoch(train)  [7][2550/3139]  lr: 1.2500e-03  eta: 1:27:51  time: 0.3258  data_time: 0.0046  memory: 726  loss: 1.4087  loss_cls: 0.2727  loss_bbox: 0.5476  loss_dfl: 0.2057  loss_ld: 0.3828
2023/07/13 11:01:35 - mmengine - INFO - Epoch(train)  [7][2600/3139]  lr: 1.2500e-03  eta: 1:27:35  time: 0.3241  data_time: 0.0035  memory: 734  loss: 1.3668  loss_cls: 0.2714  loss_bbox: 0.5075  loss_dfl: 0.2024  loss_ld: 0.3855
2023/07/13 11:01:51 - mmengine - INFO - Epoch(train)  [7][2650/3139]  lr: 1.2500e-03  eta: 1:27:19  time: 0.3262  data_time: 0.0046  memory: 725  loss: 1.3526  loss_cls: 0.2686  loss_bbox: 0.5445  loss_dfl: 0.2065  loss_ld: 0.3330
2023/07/13 11:02:07 - mmengine - INFO - Epoch(train)  [7][2700/3139]  lr: 1.2500e-03  eta: 1:27:03  time: 0.3237  data_time: 0.0041  memory: 722  loss: 1.4276  loss_cls: 0.2606  loss_bbox: 0.5481  loss_dfl: 0.2106  loss_ld: 0.4083
2023/07/13 11:02:24 - mmengine - INFO - Epoch(train)  [7][2750/3139]  lr: 1.2500e-03  eta: 1:26:47  time: 0.3241  data_time: 0.0038  memory: 722  loss: 1.4438  loss_cls: 0.2915  loss_bbox: 0.5741  loss_dfl: 0.2104  loss_ld: 0.3679
2023/07/13 11:02:40 - mmengine - INFO - Epoch(train)  [7][2800/3139]  lr: 1.2500e-03  eta: 1:26:31  time: 0.3226  data_time: 0.0046  memory: 730  loss: 1.3689  loss_cls: 0.2739  loss_bbox: 0.5262  loss_dfl: 0.2032  loss_ld: 0.3657
2023/07/13 11:02:56 - mmengine - INFO - Epoch(train)  [7][2850/3139]  lr: 1.2500e-03  eta: 1:26:14  time: 0.3230  data_time: 0.0040  memory: 722  loss: 1.4578  loss_cls: 0.2479  loss_bbox: 0.5723  loss_dfl: 0.2125  loss_ld: 0.4251
2023/07/13 11:03:12 - mmengine - INFO - Epoch(train)  [7][2900/3139]  lr: 1.2500e-03  eta: 1:25:58  time: 0.3219  data_time: 0.0040  memory: 735  loss: 1.3961  loss_cls: 0.3004  loss_bbox: 0.5684  loss_dfl: 0.2142  loss_ld: 0.3131
2023/07/13 11:03:28 - mmengine - INFO - Epoch(train)  [7][2950/3139]  lr: 1.2500e-03  eta: 1:25:42  time: 0.3255  data_time: 0.0048  memory: 728  loss: 1.4112  loss_cls: 0.2772  loss_bbox: 0.4983  loss_dfl: 0.2060  loss_ld: 0.4297
2023/07/13 11:03:44 - mmengine - INFO - Epoch(train)  [7][3000/3139]  lr: 1.2500e-03  eta: 1:25:26  time: 0.3248  data_time: 0.0045  memory: 722  loss: 1.4907  loss_cls: 0.2831  loss_bbox: 0.5595  loss_dfl: 0.2183  loss_ld: 0.4297
2023/07/13 11:04:01 - mmengine - INFO - Epoch(train)  [7][3050/3139]  lr: 1.2500e-03  eta: 1:25:10  time: 0.3251  data_time: 0.0040  memory: 730  loss: 1.5072  loss_cls: 0.2674  loss_bbox: 0.5219  loss_dfl: 0.2045  loss_ld: 0.5134
2023/07/13 11:04:17 - mmengine - INFO - Epoch(train)  [7][3100/3139]  lr: 1.2500e-03  eta: 1:24:53  time: 0.3198  data_time: 0.0042  memory: 730  loss: 1.4002  loss_cls: 0.3106  loss_bbox: 0.5149  loss_dfl: 0.2111  loss_ld: 0.3637
2023/07/13 11:04:29 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:04:29 - mmengine - INFO - Saving checkpoint at 7 epochs
2023/07/13 11:04:35 - mmengine - INFO - Epoch(val)  [7][ 50/548]    eta: 0:00:38  time: 0.0767  data_time: 0.0024  memory: 728  
2023/07/13 11:04:39 - mmengine - INFO - Epoch(val)  [7][100/548]    eta: 0:00:34  time: 0.0751  data_time: 0.0015  memory: 497  
2023/07/13 11:04:43 - mmengine - INFO - Epoch(val)  [7][150/548]    eta: 0:00:30  time: 0.0748  data_time: 0.0014  memory: 497  
2023/07/13 11:04:47 - mmengine - INFO - Epoch(val)  [7][200/548]    eta: 0:00:26  time: 0.0758  data_time: 0.0015  memory: 497  
2023/07/13 11:04:51 - mmengine - INFO - Epoch(val)  [7][250/548]    eta: 0:00:22  time: 0.0749  data_time: 0.0014  memory: 497  
2023/07/13 11:04:54 - mmengine - INFO - Epoch(val)  [7][300/548]    eta: 0:00:18  time: 0.0742  data_time: 0.0015  memory: 497  
2023/07/13 11:04:58 - mmengine - INFO - Epoch(val)  [7][350/548]    eta: 0:00:14  time: 0.0742  data_time: 0.0014  memory: 497  
2023/07/13 11:05:02 - mmengine - INFO - Epoch(val)  [7][400/548]    eta: 0:00:11  time: 0.0744  data_time: 0.0014  memory: 497  
2023/07/13 11:05:05 - mmengine - INFO - Epoch(val)  [7][450/548]    eta: 0:00:07  time: 0.0748  data_time: 0.0015  memory: 497  
2023/07/13 11:05:09 - mmengine - INFO - Epoch(val)  [7][500/548]    eta: 0:00:03  time: 0.0747  data_time: 0.0015  memory: 497  
2023/07/13 11:05:13 - mmengine - INFO - Evaluating bbox...
2023/07/13 11:05:26 - mmengine - INFO - bbox_mAP_copypaste: 0.092 0.159 0.096 0.023 0.131 0.262
2023/07/13 11:05:26 - mmengine - INFO - Epoch(val) [7][548/548]    coco/bbox_mAP: 0.0920  coco/bbox_mAP_50: 0.1590  coco/bbox_mAP_75: 0.0960  coco/bbox_mAP_s: 0.0230  coco/bbox_mAP_m: 0.1310  coco/bbox_mAP_l: 0.2620  data_time: 0.0015  time: 0.0749
2023/07/13 11:05:35 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:05:42 - mmengine - INFO - Epoch(train)  [8][  50/3139]  lr: 1.2500e-03  eta: 1:24:24  time: 0.3243  data_time: 0.0063  memory: 722  loss: 1.4144  loss_cls: 0.2700  loss_bbox: 0.5692  loss_dfl: 0.2053  loss_ld: 0.3699
2023/07/13 11:05:58 - mmengine - INFO - Epoch(train)  [8][ 100/3139]  lr: 1.2500e-03  eta: 1:24:08  time: 0.3245  data_time: 0.0041  memory: 726  loss: 1.3326  loss_cls: 0.2820  loss_bbox: 0.4831  loss_dfl: 0.2027  loss_ld: 0.3649
2023/07/13 11:06:15 - mmengine - INFO - Epoch(train)  [8][ 150/3139]  lr: 1.2500e-03  eta: 1:23:52  time: 0.3289  data_time: 0.0058  memory: 717  loss: 1.4507  loss_cls: 0.3069  loss_bbox: 0.5347  loss_dfl: 0.2109  loss_ld: 0.3981
2023/07/13 11:06:31 - mmengine - INFO - Epoch(train)  [8][ 200/3139]  lr: 1.2500e-03  eta: 1:23:36  time: 0.3249  data_time: 0.0039  memory: 747  loss: 1.3148  loss_cls: 0.2862  loss_bbox: 0.4894  loss_dfl: 0.1964  loss_ld: 0.3429
2023/07/13 11:06:47 - mmengine - INFO - Epoch(train)  [8][ 250/3139]  lr: 1.2500e-03  eta: 1:23:20  time: 0.3237  data_time: 0.0037  memory: 735  loss: 1.3929  loss_cls: 0.2776  loss_bbox: 0.5155  loss_dfl: 0.2068  loss_ld: 0.3929
2023/07/13 11:07:04 - mmengine - INFO - Epoch(train)  [8][ 300/3139]  lr: 1.2500e-03  eta: 1:23:04  time: 0.3241  data_time: 0.0038  memory: 738  loss: 1.3656  loss_cls: 0.2774  loss_bbox: 0.4885  loss_dfl: 0.2004  loss_ld: 0.3993
2023/07/13 11:07:20 - mmengine - INFO - Epoch(train)  [8][ 350/3139]  lr: 1.2500e-03  eta: 1:22:48  time: 0.3241  data_time: 0.0045  memory: 719  loss: 1.3877  loss_cls: 0.2745  loss_bbox: 0.5570  loss_dfl: 0.2094  loss_ld: 0.3467
2023/07/13 11:07:36 - mmengine - INFO - Epoch(train)  [8][ 400/3139]  lr: 1.2500e-03  eta: 1:22:31  time: 0.3230  data_time: 0.0037  memory: 740  loss: 1.4406  loss_cls: 0.2670  loss_bbox: 0.5085  loss_dfl: 0.2112  loss_ld: 0.4539
2023/07/13 11:07:52 - mmengine - INFO - Epoch(train)  [8][ 450/3139]  lr: 1.2500e-03  eta: 1:22:15  time: 0.3234  data_time: 0.0047  memory: 733  loss: 1.3083  loss_cls: 0.2674  loss_bbox: 0.5188  loss_dfl: 0.1974  loss_ld: 0.3248
2023/07/13 11:08:08 - mmengine - INFO - Epoch(train)  [8][ 500/3139]  lr: 1.2500e-03  eta: 1:21:59  time: 0.3227  data_time: 0.0037  memory: 718  loss: 1.4169  loss_cls: 0.2794  loss_bbox: 0.5329  loss_dfl: 0.2046  loss_ld: 0.4000
2023/07/13 11:08:24 - mmengine - INFO - Epoch(train)  [8][ 550/3139]  lr: 1.2500e-03  eta: 1:21:43  time: 0.3217  data_time: 0.0035  memory: 738  loss: 1.4341  loss_cls: 0.2641  loss_bbox: 0.5821  loss_dfl: 0.2235  loss_ld: 0.3644
2023/07/13 11:08:41 - mmengine - INFO - Epoch(train)  [8][ 600/3139]  lr: 1.2500e-03  eta: 1:21:27  time: 0.3265  data_time: 0.0056  memory: 752  loss: 1.4175  loss_cls: 0.2596  loss_bbox: 0.5902  loss_dfl: 0.2082  loss_ld: 0.3595
2023/07/13 11:08:57 - mmengine - INFO - Epoch(train)  [8][ 650/3139]  lr: 1.2500e-03  eta: 1:21:10  time: 0.3255  data_time: 0.0046  memory: 718  loss: 1.3580  loss_cls: 0.2814  loss_bbox: 0.4849  loss_dfl: 0.2004  loss_ld: 0.3914
2023/07/13 11:09:13 - mmengine - INFO - Epoch(train)  [8][ 700/3139]  lr: 1.2500e-03  eta: 1:20:54  time: 0.3243  data_time: 0.0047  memory: 723  loss: 1.4132  loss_cls: 0.3057  loss_bbox: 0.5336  loss_dfl: 0.2139  loss_ld: 0.3600
2023/07/13 11:09:29 - mmengine - INFO - Epoch(train)  [8][ 750/3139]  lr: 1.2500e-03  eta: 1:20:38  time: 0.3232  data_time: 0.0036  memory: 730  loss: 1.4185  loss_cls: 0.2710  loss_bbox: 0.5383  loss_dfl: 0.2114  loss_ld: 0.3978
2023/07/13 11:09:46 - mmengine - INFO - Epoch(train)  [8][ 800/3139]  lr: 1.2500e-03  eta: 1:20:22  time: 0.3237  data_time: 0.0044  memory: 714  loss: 1.3746  loss_cls: 0.2571  loss_bbox: 0.5551  loss_dfl: 0.2064  loss_ld: 0.3560
2023/07/13 11:10:02 - mmengine - INFO - Epoch(train)  [8][ 850/3139]  lr: 1.2500e-03  eta: 1:20:06  time: 0.3249  data_time: 0.0055  memory: 736  loss: 1.3410  loss_cls: 0.2528  loss_bbox: 0.5191  loss_dfl: 0.2005  loss_ld: 0.3686
2023/07/13 11:10:18 - mmengine - INFO - Epoch(train)  [8][ 900/3139]  lr: 1.2500e-03  eta: 1:19:49  time: 0.3209  data_time: 0.0042  memory: 722  loss: 1.3495  loss_cls: 0.2753  loss_bbox: 0.4938  loss_dfl: 0.2018  loss_ld: 0.3786
2023/07/13 11:10:34 - mmengine - INFO - Epoch(train)  [8][ 950/3139]  lr: 1.2500e-03  eta: 1:19:33  time: 0.3247  data_time: 0.0051  memory: 719  loss: 1.3778  loss_cls: 0.2832  loss_bbox: 0.5587  loss_dfl: 0.2147  loss_ld: 0.3212
2023/07/13 11:10:50 - mmengine - INFO - Epoch(train)  [8][1000/3139]  lr: 1.2500e-03  eta: 1:19:17  time: 0.3200  data_time: 0.0038  memory: 728  loss: 1.3727  loss_cls: 0.2730  loss_bbox: 0.5527  loss_dfl: 0.2019  loss_ld: 0.3451
2023/07/13 11:10:59 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:11:06 - mmengine - INFO - Epoch(train)  [8][1050/3139]  lr: 1.2500e-03  eta: 1:19:01  time: 0.3257  data_time: 0.0052  memory: 726  loss: 1.3827  loss_cls: 0.2702  loss_bbox: 0.5208  loss_dfl: 0.2040  loss_ld: 0.3877
2023/07/13 11:11:23 - mmengine - INFO - Epoch(train)  [8][1100/3139]  lr: 1.2500e-03  eta: 1:18:45  time: 0.3256  data_time: 0.0053  memory: 715  loss: 1.3165  loss_cls: 0.2704  loss_bbox: 0.5012  loss_dfl: 0.1997  loss_ld: 0.3451
2023/07/13 11:11:39 - mmengine - INFO - Epoch(train)  [8][1150/3139]  lr: 1.2500e-03  eta: 1:18:29  time: 0.3267  data_time: 0.0043  memory: 723  loss: 1.3811  loss_cls: 0.2478  loss_bbox: 0.5198  loss_dfl: 0.2011  loss_ld: 0.4123
2023/07/13 11:11:55 - mmengine - INFO - Epoch(train)  [8][1200/3139]  lr: 1.2500e-03  eta: 1:18:12  time: 0.3245  data_time: 0.0044  memory: 720  loss: 1.3759  loss_cls: 0.2545  loss_bbox: 0.5337  loss_dfl: 0.2062  loss_ld: 0.3815
2023/07/13 11:12:11 - mmengine - INFO - Epoch(train)  [8][1250/3139]  lr: 1.2500e-03  eta: 1:17:56  time: 0.3244  data_time: 0.0052  memory: 717  loss: 1.3390  loss_cls: 0.2655  loss_bbox: 0.5255  loss_dfl: 0.2002  loss_ld: 0.3478
2023/07/13 11:12:28 - mmengine - INFO - Epoch(train)  [8][1300/3139]  lr: 1.2500e-03  eta: 1:17:40  time: 0.3221  data_time: 0.0039  memory: 719  loss: 1.3301  loss_cls: 0.3015  loss_bbox: 0.5022  loss_dfl: 0.1966  loss_ld: 0.3297
2023/07/13 11:12:44 - mmengine - INFO - Epoch(train)  [8][1350/3139]  lr: 1.2500e-03  eta: 1:17:24  time: 0.3243  data_time: 0.0049  memory: 734  loss: 1.3398  loss_cls: 0.2825  loss_bbox: 0.4893  loss_dfl: 0.1985  loss_ld: 0.3695
2023/07/13 11:13:00 - mmengine - INFO - Epoch(train)  [8][1400/3139]  lr: 1.2500e-03  eta: 1:17:08  time: 0.3241  data_time: 0.0043  memory: 730  loss: 1.3648  loss_cls: 0.2504  loss_bbox: 0.5164  loss_dfl: 0.1996  loss_ld: 0.3984
2023/07/13 11:13:16 - mmengine - INFO - Epoch(train)  [8][1450/3139]  lr: 1.2500e-03  eta: 1:16:51  time: 0.3224  data_time: 0.0040  memory: 748  loss: 1.3701  loss_cls: 0.2711  loss_bbox: 0.5327  loss_dfl: 0.1992  loss_ld: 0.3671
2023/07/13 11:13:32 - mmengine - INFO - Epoch(train)  [8][1500/3139]  lr: 1.2500e-03  eta: 1:16:35  time: 0.3244  data_time: 0.0044  memory: 727  loss: 1.2810  loss_cls: 0.2888  loss_bbox: 0.4668  loss_dfl: 0.1905  loss_ld: 0.3349
2023/07/13 11:13:49 - mmengine - INFO - Epoch(train)  [8][1550/3139]  lr: 1.2500e-03  eta: 1:16:19  time: 0.3285  data_time: 0.0047  memory: 722  loss: 1.3855  loss_cls: 0.2875  loss_bbox: 0.5343  loss_dfl: 0.2070  loss_ld: 0.3567
2023/07/13 11:14:05 - mmengine - INFO - Epoch(train)  [8][1600/3139]  lr: 1.2500e-03  eta: 1:16:03  time: 0.3258  data_time: 0.0054  memory: 721  loss: 1.4322  loss_cls: 0.2907  loss_bbox: 0.5742  loss_dfl: 0.2149  loss_ld: 0.3523
2023/07/13 11:14:21 - mmengine - INFO - Epoch(train)  [8][1650/3139]  lr: 1.2500e-03  eta: 1:15:47  time: 0.3255  data_time: 0.0051  memory: 730  loss: 1.4318  loss_cls: 0.2818  loss_bbox: 0.5378  loss_dfl: 0.2076  loss_ld: 0.4046
2023/07/13 11:14:38 - mmengine - INFO - Epoch(train)  [8][1700/3139]  lr: 1.2500e-03  eta: 1:15:31  time: 0.3247  data_time: 0.0049  memory: 728  loss: 1.3974  loss_cls: 0.2656  loss_bbox: 0.5420  loss_dfl: 0.2075  loss_ld: 0.3822
2023/07/13 11:14:54 - mmengine - INFO - Epoch(train)  [8][1750/3139]  lr: 1.2500e-03  eta: 1:15:15  time: 0.3255  data_time: 0.0050  memory: 724  loss: 1.3416  loss_cls: 0.2662  loss_bbox: 0.4932  loss_dfl: 0.2040  loss_ld: 0.3782
2023/07/13 11:15:10 - mmengine - INFO - Epoch(train)  [8][1800/3139]  lr: 1.2500e-03  eta: 1:14:58  time: 0.3241  data_time: 0.0038  memory: 719  loss: 1.4180  loss_cls: 0.2552  loss_bbox: 0.5351  loss_dfl: 0.2022  loss_ld: 0.4255
2023/07/13 11:15:26 - mmengine - INFO - Epoch(train)  [8][1850/3139]  lr: 1.2500e-03  eta: 1:14:42  time: 0.3232  data_time: 0.0043  memory: 730  loss: 1.3413  loss_cls: 0.2811  loss_bbox: 0.5260  loss_dfl: 0.2016  loss_ld: 0.3325
2023/07/13 11:15:42 - mmengine - INFO - Epoch(train)  [8][1900/3139]  lr: 1.2500e-03  eta: 1:14:26  time: 0.3240  data_time: 0.0054  memory: 719  loss: 1.3654  loss_cls: 0.2669  loss_bbox: 0.4937  loss_dfl: 0.2038  loss_ld: 0.4010
2023/07/13 11:15:58 - mmengine - INFO - Epoch(train)  [8][1950/3139]  lr: 1.2500e-03  eta: 1:14:10  time: 0.3199  data_time: 0.0040  memory: 722  loss: 1.3743  loss_cls: 0.2891  loss_bbox: 0.5150  loss_dfl: 0.2049  loss_ld: 0.3653
2023/07/13 11:16:15 - mmengine - INFO - Epoch(train)  [8][2000/3139]  lr: 1.2500e-03  eta: 1:13:54  time: 0.3221  data_time: 0.0047  memory: 734  loss: 1.4129  loss_cls: 0.2837  loss_bbox: 0.5541  loss_dfl: 0.2100  loss_ld: 0.3651
2023/07/13 11:16:23 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:16:30 - mmengine - INFO - Epoch(train)  [8][2050/3139]  lr: 1.2500e-03  eta: 1:13:37  time: 0.3178  data_time: 0.0042  memory: 718  loss: 1.3423  loss_cls: 0.2764  loss_bbox: 0.5336  loss_dfl: 0.2013  loss_ld: 0.3310
2023/07/13 11:16:47 - mmengine - INFO - Epoch(train)  [8][2100/3139]  lr: 1.2500e-03  eta: 1:13:21  time: 0.3210  data_time: 0.0041  memory: 762  loss: 1.4917  loss_cls: 0.2771  loss_bbox: 0.5775  loss_dfl: 0.2191  loss_ld: 0.4180
2023/07/13 11:17:02 - mmengine - INFO - Epoch(train)  [8][2150/3139]  lr: 1.2500e-03  eta: 1:13:05  time: 0.3186  data_time: 0.0045  memory: 730  loss: 1.3312  loss_cls: 0.2777  loss_bbox: 0.5507  loss_dfl: 0.2011  loss_ld: 0.3017
2023/07/13 11:17:18 - mmengine - INFO - Epoch(train)  [8][2200/3139]  lr: 1.2500e-03  eta: 1:12:48  time: 0.3161  data_time: 0.0041  memory: 720  loss: 1.3960  loss_cls: 0.3026  loss_bbox: 0.5572  loss_dfl: 0.2091  loss_ld: 0.3271
2023/07/13 11:17:34 - mmengine - INFO - Epoch(train)  [8][2250/3139]  lr: 1.2500e-03  eta: 1:12:32  time: 0.3237  data_time: 0.0051  memory: 716  loss: 1.3309  loss_cls: 0.3018  loss_bbox: 0.5303  loss_dfl: 0.2044  loss_ld: 0.2943
2023/07/13 11:17:51 - mmengine - INFO - Epoch(train)  [8][2300/3139]  lr: 1.2500e-03  eta: 1:12:16  time: 0.3202  data_time: 0.0037  memory: 720  loss: 1.4057  loss_cls: 0.2922  loss_bbox: 0.5727  loss_dfl: 0.2128  loss_ld: 0.3279
2023/07/13 11:18:07 - mmengine - INFO - Epoch(train)  [8][2350/3139]  lr: 1.2500e-03  eta: 1:11:59  time: 0.3213  data_time: 0.0041  memory: 723  loss: 1.4028  loss_cls: 0.2575  loss_bbox: 0.5831  loss_dfl: 0.2113  loss_ld: 0.3508
2023/07/13 11:18:23 - mmengine - INFO - Epoch(train)  [8][2400/3139]  lr: 1.2500e-03  eta: 1:11:43  time: 0.3243  data_time: 0.0044  memory: 729  loss: 1.3738  loss_cls: 0.2666  loss_bbox: 0.5415  loss_dfl: 0.2030  loss_ld: 0.3627
2023/07/13 11:18:39 - mmengine - INFO - Epoch(train)  [8][2450/3139]  lr: 1.2500e-03  eta: 1:11:27  time: 0.3189  data_time: 0.0039  memory: 722  loss: 1.3515  loss_cls: 0.3076  loss_bbox: 0.5601  loss_dfl: 0.2089  loss_ld: 0.2748
2023/07/13 11:18:55 - mmengine - INFO - Epoch(train)  [8][2500/3139]  lr: 1.2500e-03  eta: 1:11:11  time: 0.3238  data_time: 0.0043  memory: 727  loss: 1.3708  loss_cls: 0.2667  loss_bbox: 0.5338  loss_dfl: 0.2030  loss_ld: 0.3673
2023/07/13 11:19:11 - mmengine - INFO - Epoch(train)  [8][2550/3139]  lr: 1.2500e-03  eta: 1:10:55  time: 0.3252  data_time: 0.0039  memory: 726  loss: 1.3650  loss_cls: 0.2647  loss_bbox: 0.5036  loss_dfl: 0.1960  loss_ld: 0.4007
2023/07/13 11:19:27 - mmengine - INFO - Epoch(train)  [8][2600/3139]  lr: 1.2500e-03  eta: 1:10:39  time: 0.3245  data_time: 0.0059  memory: 730  loss: 1.3290  loss_cls: 0.2922  loss_bbox: 0.5241  loss_dfl: 0.2020  loss_ld: 0.3106
2023/07/13 11:19:44 - mmengine - INFO - Epoch(train)  [8][2650/3139]  lr: 1.2500e-03  eta: 1:10:22  time: 0.3223  data_time: 0.0047  memory: 720  loss: 1.3354  loss_cls: 0.2671  loss_bbox: 0.5109  loss_dfl: 0.1995  loss_ld: 0.3580
2023/07/13 11:20:00 - mmengine - INFO - Epoch(train)  [8][2700/3139]  lr: 1.2500e-03  eta: 1:10:06  time: 0.3251  data_time: 0.0044  memory: 724  loss: 1.3890  loss_cls: 0.2873  loss_bbox: 0.5595  loss_dfl: 0.2112  loss_ld: 0.3310
2023/07/13 11:20:16 - mmengine - INFO - Epoch(train)  [8][2750/3139]  lr: 1.2500e-03  eta: 1:09:50  time: 0.3220  data_time: 0.0047  memory: 722  loss: 1.3080  loss_cls: 0.2667  loss_bbox: 0.4950  loss_dfl: 0.1954  loss_ld: 0.3510
2023/07/13 11:20:32 - mmengine - INFO - Epoch(train)  [8][2800/3139]  lr: 1.2500e-03  eta: 1:09:34  time: 0.3206  data_time: 0.0057  memory: 718  loss: 1.3306  loss_cls: 0.2765  loss_bbox: 0.5113  loss_dfl: 0.2044  loss_ld: 0.3384
2023/07/13 11:20:48 - mmengine - INFO - Epoch(train)  [8][2850/3139]  lr: 1.2500e-03  eta: 1:09:17  time: 0.3191  data_time: 0.0044  memory: 728  loss: 1.4454  loss_cls: 0.2693  loss_bbox: 0.5706  loss_dfl: 0.2111  loss_ld: 0.3943
2023/07/13 11:21:04 - mmengine - INFO - Epoch(train)  [8][2900/3139]  lr: 1.2500e-03  eta: 1:09:01  time: 0.3213  data_time: 0.0044  memory: 738  loss: 1.3739  loss_cls: 0.2836  loss_bbox: 0.5400  loss_dfl: 0.2051  loss_ld: 0.3452
2023/07/13 11:21:20 - mmengine - INFO - Epoch(train)  [8][2950/3139]  lr: 1.2500e-03  eta: 1:08:45  time: 0.3237  data_time: 0.0053  memory: 732  loss: 1.4174  loss_cls: 0.2586  loss_bbox: 0.5640  loss_dfl: 0.2085  loss_ld: 0.3863
2023/07/13 11:21:36 - mmengine - INFO - Epoch(train)  [8][3000/3139]  lr: 1.2500e-03  eta: 1:08:29  time: 0.3205  data_time: 0.0039  memory: 721  loss: 1.2969  loss_cls: 0.2494  loss_bbox: 0.5192  loss_dfl: 0.1978  loss_ld: 0.3307
2023/07/13 11:21:45 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:21:52 - mmengine - INFO - Epoch(train)  [8][3050/3139]  lr: 1.2500e-03  eta: 1:08:12  time: 0.3183  data_time: 0.0042  memory: 715  loss: 1.3892  loss_cls: 0.2794  loss_bbox: 0.5125  loss_dfl: 0.2067  loss_ld: 0.3906
2023/07/13 11:22:08 - mmengine - INFO - Epoch(train)  [8][3100/3139]  lr: 1.2500e-03  eta: 1:07:56  time: 0.3178  data_time: 0.0045  memory: 715  loss: 1.3082  loss_cls: 0.2581  loss_bbox: 0.4917  loss_dfl: 0.1964  loss_ld: 0.3620
2023/07/13 11:22:21 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:22:21 - mmengine - INFO - Saving checkpoint at 8 epochs
2023/07/13 11:22:27 - mmengine - INFO - Epoch(val)  [8][ 50/548]    eta: 0:00:37  time: 0.0759  data_time: 0.0024  memory: 729  
2023/07/13 11:22:31 - mmengine - INFO - Epoch(val)  [8][100/548]    eta: 0:00:33  time: 0.0743  data_time: 0.0014  memory: 497  
2023/07/13 11:22:34 - mmengine - INFO - Epoch(val)  [8][150/548]    eta: 0:00:29  time: 0.0742  data_time: 0.0013  memory: 497  
2023/07/13 11:22:38 - mmengine - INFO - Epoch(val)  [8][200/548]    eta: 0:00:25  time: 0.0743  data_time: 0.0014  memory: 497  
2023/07/13 11:22:42 - mmengine - INFO - Epoch(val)  [8][250/548]    eta: 0:00:22  time: 0.0743  data_time: 0.0013  memory: 497  
2023/07/13 11:22:46 - mmengine - INFO - Epoch(val)  [8][300/548]    eta: 0:00:18  time: 0.0738  data_time: 0.0013  memory: 497  
2023/07/13 11:22:49 - mmengine - INFO - Epoch(val)  [8][350/548]    eta: 0:00:14  time: 0.0737  data_time: 0.0014  memory: 497  
2023/07/13 11:22:53 - mmengine - INFO - Epoch(val)  [8][400/548]    eta: 0:00:11  time: 0.0742  data_time: 0.0014  memory: 497  
2023/07/13 11:22:57 - mmengine - INFO - Epoch(val)  [8][450/548]    eta: 0:00:07  time: 0.0752  data_time: 0.0015  memory: 497  
2023/07/13 11:23:00 - mmengine - INFO - Epoch(val)  [8][500/548]    eta: 0:00:03  time: 0.0740  data_time: 0.0014  memory: 497  
2023/07/13 11:23:05 - mmengine - INFO - Evaluating bbox...
2023/07/13 11:23:19 - mmengine - INFO - bbox_mAP_copypaste: 0.088 0.148 0.094 0.024 0.130 0.231
2023/07/13 11:23:19 - mmengine - INFO - Epoch(val) [8][548/548]    coco/bbox_mAP: 0.0880  coco/bbox_mAP_50: 0.1480  coco/bbox_mAP_75: 0.0940  coco/bbox_mAP_s: 0.0240  coco/bbox_mAP_m: 0.1300  coco/bbox_mAP_l: 0.2310  data_time: 0.0015  time: 0.0743
2023/07/13 11:23:35 - mmengine - INFO - Epoch(train)  [9][  50/3139]  lr: 1.2500e-04  eta: 1:07:27  time: 0.3269  data_time: 0.0071  memory: 735  loss: 1.3473  loss_cls: 0.2625  loss_bbox: 0.5659  loss_dfl: 0.2029  loss_ld: 0.3159
2023/07/13 11:23:51 - mmengine - INFO - Epoch(train)  [9][ 100/3139]  lr: 1.2500e-04  eta: 1:07:11  time: 0.3216  data_time: 0.0044  memory: 723  loss: 1.2487  loss_cls: 0.2574  loss_bbox: 0.4744  loss_dfl: 0.1943  loss_ld: 0.3227
2023/07/13 11:24:08 - mmengine - INFO - Epoch(train)  [9][ 150/3139]  lr: 1.2500e-04  eta: 1:06:55  time: 0.3230  data_time: 0.0042  memory: 736  loss: 1.2396  loss_cls: 0.2573  loss_bbox: 0.5001  loss_dfl: 0.1933  loss_ld: 0.2888
2023/07/13 11:24:24 - mmengine - INFO - Epoch(train)  [9][ 200/3139]  lr: 1.2500e-04  eta: 1:06:39  time: 0.3250  data_time: 0.0051  memory: 728  loss: 1.2888  loss_cls: 0.2662  loss_bbox: 0.5338  loss_dfl: 0.2013  loss_ld: 0.2875
2023/07/13 11:24:40 - mmengine - INFO - Epoch(train)  [9][ 250/3139]  lr: 1.2500e-04  eta: 1:06:23  time: 0.3248  data_time: 0.0046  memory: 720  loss: 1.2527  loss_cls: 0.2654  loss_bbox: 0.4967  loss_dfl: 0.1960  loss_ld: 0.2946
2023/07/13 11:24:56 - mmengine - INFO - Epoch(train)  [9][ 300/3139]  lr: 1.2500e-04  eta: 1:06:06  time: 0.3249  data_time: 0.0049  memory: 718  loss: 1.2549  loss_cls: 0.2618  loss_bbox: 0.4835  loss_dfl: 0.1943  loss_ld: 0.3153
2023/07/13 11:25:12 - mmengine - INFO - Epoch(train)  [9][ 350/3139]  lr: 1.2500e-04  eta: 1:05:50  time: 0.3231  data_time: 0.0038  memory: 716  loss: 1.2280  loss_cls: 0.2629  loss_bbox: 0.4922  loss_dfl: 0.1960  loss_ld: 0.2770
2023/07/13 11:25:29 - mmengine - INFO - Epoch(train)  [9][ 400/3139]  lr: 1.2500e-04  eta: 1:05:34  time: 0.3207  data_time: 0.0038  memory: 751  loss: 1.2605  loss_cls: 0.2549  loss_bbox: 0.4877  loss_dfl: 0.1951  loss_ld: 0.3229
2023/07/13 11:25:45 - mmengine - INFO - Epoch(train)  [9][ 450/3139]  lr: 1.2500e-04  eta: 1:05:18  time: 0.3258  data_time: 0.0047  memory: 725  loss: 1.1991  loss_cls: 0.2700  loss_bbox: 0.4538  loss_dfl: 0.1902  loss_ld: 0.2850
2023/07/13 11:26:01 - mmengine - INFO - Epoch(train)  [9][ 500/3139]  lr: 1.2500e-04  eta: 1:05:02  time: 0.3272  data_time: 0.0057  memory: 722  loss: 1.2144  loss_cls: 0.2339  loss_bbox: 0.4751  loss_dfl: 0.1889  loss_ld: 0.3165
2023/07/13 11:26:17 - mmengine - INFO - Epoch(train)  [9][ 550/3139]  lr: 1.2500e-04  eta: 1:04:45  time: 0.3213  data_time: 0.0035  memory: 739  loss: 1.2632  loss_cls: 0.2730  loss_bbox: 0.4912  loss_dfl: 0.1968  loss_ld: 0.3021
2023/07/13 11:26:34 - mmengine - INFO - Epoch(train)  [9][ 600/3139]  lr: 1.2500e-04  eta: 1:04:29  time: 0.3267  data_time: 0.0047  memory: 734  loss: 1.2557  loss_cls: 0.2600  loss_bbox: 0.4719  loss_dfl: 0.1947  loss_ld: 0.3290
2023/07/13 11:26:50 - mmengine - INFO - Epoch(train)  [9][ 650/3139]  lr: 1.2500e-04  eta: 1:04:13  time: 0.3242  data_time: 0.0043  memory: 725  loss: 1.1711  loss_cls: 0.2394  loss_bbox: 0.4700  loss_dfl: 0.1856  loss_ld: 0.2761
2023/07/13 11:27:06 - mmengine - INFO - Epoch(train)  [9][ 700/3139]  lr: 1.2500e-04  eta: 1:03:57  time: 0.3237  data_time: 0.0039  memory: 713  loss: 1.2435  loss_cls: 0.2698  loss_bbox: 0.4941  loss_dfl: 0.2036  loss_ld: 0.2760
2023/07/13 11:27:22 - mmengine - INFO - Epoch(train)  [9][ 750/3139]  lr: 1.2500e-04  eta: 1:03:41  time: 0.3246  data_time: 0.0043  memory: 729  loss: 1.2771  loss_cls: 0.2709  loss_bbox: 0.4946  loss_dfl: 0.1984  loss_ld: 0.3132
2023/07/13 11:27:39 - mmengine - INFO - Epoch(train)  [9][ 800/3139]  lr: 1.2500e-04  eta: 1:03:25  time: 0.3267  data_time: 0.0052  memory: 730  loss: 1.2391  loss_cls: 0.2492  loss_bbox: 0.4773  loss_dfl: 0.1947  loss_ld: 0.3179
2023/07/13 11:27:55 - mmengine - INFO - Epoch(train)  [9][ 850/3139]  lr: 1.2500e-04  eta: 1:03:08  time: 0.3223  data_time: 0.0042  memory: 713  loss: 1.2725  loss_cls: 0.2521  loss_bbox: 0.4711  loss_dfl: 0.1945  loss_ld: 0.3547
2023/07/13 11:28:07 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:28:11 - mmengine - INFO - Epoch(train)  [9][ 900/3139]  lr: 1.2500e-04  eta: 1:02:52  time: 0.3248  data_time: 0.0054  memory: 722  loss: 1.2348  loss_cls: 0.2442  loss_bbox: 0.5268  loss_dfl: 0.1962  loss_ld: 0.2676
2023/07/13 11:28:27 - mmengine - INFO - Epoch(train)  [9][ 950/3139]  lr: 1.2500e-04  eta: 1:02:36  time: 0.3233  data_time: 0.0052  memory: 739  loss: 1.2494  loss_cls: 0.2498  loss_bbox: 0.4975  loss_dfl: 0.1943  loss_ld: 0.3077
2023/07/13 11:28:43 - mmengine - INFO - Epoch(train)  [9][1000/3139]  lr: 1.2500e-04  eta: 1:02:20  time: 0.3259  data_time: 0.0050  memory: 743  loss: 1.2567  loss_cls: 0.2512  loss_bbox: 0.4794  loss_dfl: 0.1956  loss_ld: 0.3306
2023/07/13 11:29:00 - mmengine - INFO - Epoch(train)  [9][1050/3139]  lr: 1.2500e-04  eta: 1:02:04  time: 0.3224  data_time: 0.0039  memory: 728  loss: 1.1486  loss_cls: 0.2422  loss_bbox: 0.4500  loss_dfl: 0.1853  loss_ld: 0.2711
2023/07/13 11:29:16 - mmengine - INFO - Epoch(train)  [9][1100/3139]  lr: 1.2500e-04  eta: 1:01:48  time: 0.3255  data_time: 0.0051  memory: 730  loss: 1.2315  loss_cls: 0.2482  loss_bbox: 0.4918  loss_dfl: 0.1901  loss_ld: 0.3014
2023/07/13 11:29:32 - mmengine - INFO - Epoch(train)  [9][1150/3139]  lr: 1.2500e-04  eta: 1:01:32  time: 0.3274  data_time: 0.0056  memory: 731  loss: 1.2414  loss_cls: 0.2476  loss_bbox: 0.5017  loss_dfl: 0.1923  loss_ld: 0.2998
2023/07/13 11:29:49 - mmengine - INFO - Epoch(train)  [9][1200/3139]  lr: 1.2500e-04  eta: 1:01:15  time: 0.3273  data_time: 0.0066  memory: 726  loss: 1.2496  loss_cls: 0.2458  loss_bbox: 0.5141  loss_dfl: 0.1911  loss_ld: 0.2985
2023/07/13 11:30:05 - mmengine - INFO - Epoch(train)  [9][1250/3139]  lr: 1.2500e-04  eta: 1:00:59  time: 0.3244  data_time: 0.0039  memory: 721  loss: 1.2399  loss_cls: 0.2455  loss_bbox: 0.4791  loss_dfl: 0.1952  loss_ld: 0.3199
2023/07/13 11:30:21 - mmengine - INFO - Epoch(train)  [9][1300/3139]  lr: 1.2500e-04  eta: 1:00:43  time: 0.3236  data_time: 0.0039  memory: 718  loss: 1.1843  loss_cls: 0.2352  loss_bbox: 0.4721  loss_dfl: 0.1872  loss_ld: 0.2899
2023/07/13 11:30:37 - mmengine - INFO - Epoch(train)  [9][1350/3139]  lr: 1.2500e-04  eta: 1:00:27  time: 0.3225  data_time: 0.0041  memory: 728  loss: 1.1968  loss_cls: 0.2405  loss_bbox: 0.4717  loss_dfl: 0.1927  loss_ld: 0.2917
2023/07/13 11:30:53 - mmengine - INFO - Epoch(train)  [9][1400/3139]  lr: 1.2500e-04  eta: 1:00:11  time: 0.3226  data_time: 0.0038  memory: 717  loss: 1.2120  loss_cls: 0.2688  loss_bbox: 0.4497  loss_dfl: 0.1896  loss_ld: 0.3040
2023/07/13 11:31:10 - mmengine - INFO - Epoch(train)  [9][1450/3139]  lr: 1.2500e-04  eta: 0:59:54  time: 0.3248  data_time: 0.0050  memory: 731  loss: 1.2858  loss_cls: 0.2546  loss_bbox: 0.5295  loss_dfl: 0.1992  loss_ld: 0.3025
2023/07/13 11:31:26 - mmengine - INFO - Epoch(train)  [9][1500/3139]  lr: 1.2500e-04  eta: 0:59:38  time: 0.3228  data_time: 0.0046  memory: 725  loss: 1.1687  loss_cls: 0.2425  loss_bbox: 0.4535  loss_dfl: 0.1873  loss_ld: 0.2854
2023/07/13 11:31:42 - mmengine - INFO - Epoch(train)  [9][1550/3139]  lr: 1.2500e-04  eta: 0:59:22  time: 0.3218  data_time: 0.0041  memory: 725  loss: 1.1884  loss_cls: 0.2403  loss_bbox: 0.5029  loss_dfl: 0.1877  loss_ld: 0.2574
2023/07/13 11:31:58 - mmengine - INFO - Epoch(train)  [9][1600/3139]  lr: 1.2500e-04  eta: 0:59:06  time: 0.3201  data_time: 0.0039  memory: 735  loss: 1.2581  loss_cls: 0.2741  loss_bbox: 0.4919  loss_dfl: 0.1964  loss_ld: 0.2956
2023/07/13 11:32:14 - mmengine - INFO - Epoch(train)  [9][1650/3139]  lr: 1.2500e-04  eta: 0:58:50  time: 0.3236  data_time: 0.0041  memory: 730  loss: 1.2905  loss_cls: 0.2302  loss_bbox: 0.5238  loss_dfl: 0.2006  loss_ld: 0.3358
2023/07/13 11:32:30 - mmengine - INFO - Epoch(train)  [9][1700/3139]  lr: 1.2500e-04  eta: 0:58:33  time: 0.3207  data_time: 0.0042  memory: 717  loss: 1.1960  loss_cls: 0.2693  loss_bbox: 0.4549  loss_dfl: 0.1891  loss_ld: 0.2827
2023/07/13 11:32:46 - mmengine - INFO - Epoch(train)  [9][1750/3139]  lr: 1.2500e-04  eta: 0:58:17  time: 0.3273  data_time: 0.0059  memory: 722  loss: 1.1931  loss_cls: 0.2414  loss_bbox: 0.4688  loss_dfl: 0.1911  loss_ld: 0.2919
2023/07/13 11:33:03 - mmengine - INFO - Epoch(train)  [9][1800/3139]  lr: 1.2500e-04  eta: 0:58:01  time: 0.3268  data_time: 0.0062  memory: 718  loss: 1.2021  loss_cls: 0.2395  loss_bbox: 0.4841  loss_dfl: 0.1880  loss_ld: 0.2905
2023/07/13 11:33:19 - mmengine - INFO - Epoch(train)  [9][1850/3139]  lr: 1.2500e-04  eta: 0:57:45  time: 0.3259  data_time: 0.0039  memory: 728  loss: 1.2342  loss_cls: 0.2521  loss_bbox: 0.4896  loss_dfl: 0.1896  loss_ld: 0.3029
2023/07/13 11:33:31 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:33:35 - mmengine - INFO - Epoch(train)  [9][1900/3139]  lr: 1.2500e-04  eta: 0:57:29  time: 0.3246  data_time: 0.0045  memory: 733  loss: 1.1834  loss_cls: 0.2314  loss_bbox: 0.4605  loss_dfl: 0.1864  loss_ld: 0.3051
2023/07/13 11:33:51 - mmengine - INFO - Epoch(train)  [9][1950/3139]  lr: 1.2500e-04  eta: 0:57:13  time: 0.3227  data_time: 0.0037  memory: 723  loss: 1.2651  loss_cls: 0.2483  loss_bbox: 0.4855  loss_dfl: 0.1946  loss_ld: 0.3367
2023/07/13 11:34:08 - mmengine - INFO - Epoch(train)  [9][2000/3139]  lr: 1.2500e-04  eta: 0:56:56  time: 0.3248  data_time: 0.0047  memory: 722  loss: 1.2578  loss_cls: 0.2659  loss_bbox: 0.4594  loss_dfl: 0.1973  loss_ld: 0.3352
2023/07/13 11:34:24 - mmengine - INFO - Epoch(train)  [9][2050/3139]  lr: 1.2500e-04  eta: 0:56:40  time: 0.3258  data_time: 0.0057  memory: 723  loss: 1.2219  loss_cls: 0.2499  loss_bbox: 0.4759  loss_dfl: 0.1923  loss_ld: 0.3037
2023/07/13 11:34:40 - mmengine - INFO - Epoch(train)  [9][2100/3139]  lr: 1.2500e-04  eta: 0:56:24  time: 0.3255  data_time: 0.0045  memory: 719  loss: 1.2703  loss_cls: 0.2464  loss_bbox: 0.4557  loss_dfl: 0.1925  loss_ld: 0.3757
2023/07/13 11:34:56 - mmengine - INFO - Epoch(train)  [9][2150/3139]  lr: 1.2500e-04  eta: 0:56:08  time: 0.3193  data_time: 0.0052  memory: 731  loss: 1.2446  loss_cls: 0.2458  loss_bbox: 0.5070  loss_dfl: 0.1937  loss_ld: 0.2981
2023/07/13 11:35:12 - mmengine - INFO - Epoch(train)  [9][2200/3139]  lr: 1.2500e-04  eta: 0:55:52  time: 0.3182  data_time: 0.0041  memory: 728  loss: 1.1493  loss_cls: 0.2280  loss_bbox: 0.4627  loss_dfl: 0.1821  loss_ld: 0.2765
2023/07/13 11:35:28 - mmengine - INFO - Epoch(train)  [9][2250/3139]  lr: 1.2500e-04  eta: 0:55:35  time: 0.3223  data_time: 0.0039  memory: 722  loss: 1.2738  loss_cls: 0.2506  loss_bbox: 0.4808  loss_dfl: 0.1942  loss_ld: 0.3483
2023/07/13 11:35:44 - mmengine - INFO - Epoch(train)  [9][2300/3139]  lr: 1.2500e-04  eta: 0:55:19  time: 0.3249  data_time: 0.0051  memory: 730  loss: 1.1455  loss_cls: 0.2500  loss_bbox: 0.4384  loss_dfl: 0.1831  loss_ld: 0.2739
2023/07/13 11:36:01 - mmengine - INFO - Epoch(train)  [9][2350/3139]  lr: 1.2500e-04  eta: 0:55:03  time: 0.3263  data_time: 0.0048  memory: 724  loss: 1.2137  loss_cls: 0.2262  loss_bbox: 0.4623  loss_dfl: 0.1850  loss_ld: 0.3401
2023/07/13 11:36:17 - mmengine - INFO - Epoch(train)  [9][2400/3139]  lr: 1.2500e-04  eta: 0:54:47  time: 0.3261  data_time: 0.0044  memory: 722  loss: 1.2706  loss_cls: 0.2544  loss_bbox: 0.4802  loss_dfl: 0.1997  loss_ld: 0.3362
2023/07/13 11:36:33 - mmengine - INFO - Epoch(train)  [9][2450/3139]  lr: 1.2500e-04  eta: 0:54:31  time: 0.3270  data_time: 0.0054  memory: 722  loss: 1.1875  loss_cls: 0.2478  loss_bbox: 0.4662  loss_dfl: 0.1908  loss_ld: 0.2827
2023/07/13 11:36:50 - mmengine - INFO - Epoch(train)  [9][2500/3139]  lr: 1.2500e-04  eta: 0:54:15  time: 0.3283  data_time: 0.0049  memory: 721  loss: 1.2376  loss_cls: 0.2320  loss_bbox: 0.4545  loss_dfl: 0.1914  loss_ld: 0.3598
2023/07/13 11:37:06 - mmengine - INFO - Epoch(train)  [9][2550/3139]  lr: 1.2500e-04  eta: 0:53:59  time: 0.3261  data_time: 0.0057  memory: 722  loss: 1.2354  loss_cls: 0.2486  loss_bbox: 0.5193  loss_dfl: 0.1929  loss_ld: 0.2746
2023/07/13 11:37:22 - mmengine - INFO - Epoch(train)  [9][2600/3139]  lr: 1.2500e-04  eta: 0:53:42  time: 0.3236  data_time: 0.0046  memory: 721  loss: 1.2549  loss_cls: 0.2502  loss_bbox: 0.4912  loss_dfl: 0.1921  loss_ld: 0.3215
2023/07/13 11:37:39 - mmengine - INFO - Epoch(train)  [9][2650/3139]  lr: 1.2500e-04  eta: 0:53:26  time: 0.3236  data_time: 0.0040  memory: 718  loss: 1.2683  loss_cls: 0.2600  loss_bbox: 0.4970  loss_dfl: 0.2011  loss_ld: 0.3102
2023/07/13 11:37:55 - mmengine - INFO - Epoch(train)  [9][2700/3139]  lr: 1.2500e-04  eta: 0:53:10  time: 0.3245  data_time: 0.0044  memory: 717  loss: 1.2316  loss_cls: 0.2738  loss_bbox: 0.4917  loss_dfl: 0.1933  loss_ld: 0.2728
2023/07/13 11:38:11 - mmengine - INFO - Epoch(train)  [9][2750/3139]  lr: 1.2500e-04  eta: 0:52:54  time: 0.3245  data_time: 0.0041  memory: 739  loss: 1.1684  loss_cls: 0.2452  loss_bbox: 0.4285  loss_dfl: 0.1817  loss_ld: 0.3130
2023/07/13 11:38:27 - mmengine - INFO - Epoch(train)  [9][2800/3139]  lr: 1.2500e-04  eta: 0:52:38  time: 0.3269  data_time: 0.0056  memory: 734  loss: 1.2725  loss_cls: 0.2456  loss_bbox: 0.5170  loss_dfl: 0.1956  loss_ld: 0.3143
2023/07/13 11:38:44 - mmengine - INFO - Epoch(train)  [9][2850/3139]  lr: 1.2500e-04  eta: 0:52:22  time: 0.3247  data_time: 0.0043  memory: 723  loss: 1.2577  loss_cls: 0.2568  loss_bbox: 0.5124  loss_dfl: 0.2012  loss_ld: 0.2873
2023/07/13 11:38:56 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:39:00 - mmengine - INFO - Epoch(train)  [9][2900/3139]  lr: 1.2500e-04  eta: 0:52:05  time: 0.3238  data_time: 0.0047  memory: 721  loss: 1.2145  loss_cls: 0.2553  loss_bbox: 0.4855  loss_dfl: 0.1951  loss_ld: 0.2785
2023/07/13 11:39:16 - mmengine - INFO - Epoch(train)  [9][2950/3139]  lr: 1.2500e-04  eta: 0:51:49  time: 0.3219  data_time: 0.0040  memory: 727  loss: 1.2428  loss_cls: 0.2435  loss_bbox: 0.4885  loss_dfl: 0.1980  loss_ld: 0.3128
2023/07/13 11:39:32 - mmengine - INFO - Epoch(train)  [9][3000/3139]  lr: 1.2500e-04  eta: 0:51:33  time: 0.3230  data_time: 0.0042  memory: 749  loss: 1.2665  loss_cls: 0.2942  loss_bbox: 0.5096  loss_dfl: 0.1928  loss_ld: 0.2700
2023/07/13 11:39:48 - mmengine - INFO - Epoch(train)  [9][3050/3139]  lr: 1.2500e-04  eta: 0:51:17  time: 0.3248  data_time: 0.0055  memory: 719  loss: 1.2241  loss_cls: 0.2632  loss_bbox: 0.5003  loss_dfl: 0.1921  loss_ld: 0.2685
2023/07/13 11:40:05 - mmengine - INFO - Epoch(train)  [9][3100/3139]  lr: 1.2500e-04  eta: 0:51:01  time: 0.3269  data_time: 0.0059  memory: 714  loss: 1.1613  loss_cls: 0.2526  loss_bbox: 0.4429  loss_dfl: 0.1890  loss_ld: 0.2768
2023/07/13 11:40:17 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:40:17 - mmengine - INFO - Saving checkpoint at 9 epochs
2023/07/13 11:40:24 - mmengine - INFO - Epoch(val)  [9][ 50/548]    eta: 0:00:38  time: 0.0764  data_time: 0.0023  memory: 747  
2023/07/13 11:40:28 - mmengine - INFO - Epoch(val)  [9][100/548]    eta: 0:00:33  time: 0.0738  data_time: 0.0014  memory: 497  
2023/07/13 11:40:32 - mmengine - INFO - Epoch(val)  [9][150/548]    eta: 0:00:29  time: 0.0741  data_time: 0.0014  memory: 497  
2023/07/13 11:40:35 - mmengine - INFO - Epoch(val)  [9][200/548]    eta: 0:00:25  time: 0.0738  data_time: 0.0015  memory: 497  
2023/07/13 11:40:39 - mmengine - INFO - Epoch(val)  [9][250/548]    eta: 0:00:22  time: 0.0798  data_time: 0.0015  memory: 497  
2023/07/13 11:40:43 - mmengine - INFO - Epoch(val)  [9][300/548]    eta: 0:00:18  time: 0.0745  data_time: 0.0015  memory: 497  
2023/07/13 11:40:47 - mmengine - INFO - Epoch(val)  [9][350/548]    eta: 0:00:14  time: 0.0754  data_time: 0.0015  memory: 497  
2023/07/13 11:40:51 - mmengine - INFO - Epoch(val)  [9][400/548]    eta: 0:00:11  time: 0.0754  data_time: 0.0015  memory: 497  
2023/07/13 11:40:55 - mmengine - INFO - Epoch(val)  [9][450/548]    eta: 0:00:07  time: 0.0818  data_time: 0.0018  memory: 497  
2023/07/13 11:40:59 - mmengine - INFO - Epoch(val)  [9][500/548]    eta: 0:00:03  time: 0.0802  data_time: 0.0015  memory: 497  
2023/07/13 11:41:03 - mmengine - INFO - Evaluating bbox...
2023/07/13 11:41:18 - mmengine - INFO - bbox_mAP_copypaste: 0.104 0.173 0.111 0.029 0.150 0.287
2023/07/13 11:41:18 - mmengine - INFO - Epoch(val) [9][548/548]    coco/bbox_mAP: 0.1040  coco/bbox_mAP_50: 0.1730  coco/bbox_mAP_75: 0.1110  coco/bbox_mAP_s: 0.0290  coco/bbox_mAP_m: 0.1500  coco/bbox_mAP_l: 0.2870  data_time: 0.0016  time: 0.0768
2023/07/13 11:41:34 - mmengine - INFO - Epoch(train) [10][  50/3139]  lr: 1.2500e-04  eta: 0:50:32  time: 0.3265  data_time: 0.0054  memory: 749  loss: 1.2177  loss_cls: 0.2798  loss_bbox: 0.4894  loss_dfl: 0.1970  loss_ld: 0.2515
2023/07/13 11:41:51 - mmengine - INFO - Epoch(train) [10][ 100/3139]  lr: 1.2500e-04  eta: 0:50:16  time: 0.3259  data_time: 0.0059  memory: 720  loss: 1.2503  loss_cls: 0.2552  loss_bbox: 0.4884  loss_dfl: 0.1936  loss_ld: 0.3130
2023/07/13 11:42:07 - mmengine - INFO - Epoch(train) [10][ 150/3139]  lr: 1.2500e-04  eta: 0:50:00  time: 0.3240  data_time: 0.0040  memory: 728  loss: 1.2495  loss_cls: 0.2466  loss_bbox: 0.5115  loss_dfl: 0.1949  loss_ld: 0.2965
2023/07/13 11:42:23 - mmengine - INFO - Epoch(train) [10][ 200/3139]  lr: 1.2500e-04  eta: 0:49:43  time: 0.3221  data_time: 0.0043  memory: 726  loss: 1.2286  loss_cls: 0.2382  loss_bbox: 0.4799  loss_dfl: 0.1930  loss_ld: 0.3175
2023/07/13 11:42:39 - mmengine - INFO - Epoch(train) [10][ 250/3139]  lr: 1.2500e-04  eta: 0:49:27  time: 0.3245  data_time: 0.0050  memory: 752  loss: 1.2961  loss_cls: 0.2551  loss_bbox: 0.5053  loss_dfl: 0.2019  loss_ld: 0.3339
2023/07/13 11:42:56 - mmengine - INFO - Epoch(train) [10][ 300/3139]  lr: 1.2500e-04  eta: 0:49:11  time: 0.3265  data_time: 0.0048  memory: 727  loss: 1.2394  loss_cls: 0.2444  loss_bbox: 0.4874  loss_dfl: 0.1938  loss_ld: 0.3139
2023/07/13 11:43:12 - mmengine - INFO - Epoch(train) [10][ 350/3139]  lr: 1.2500e-04  eta: 0:48:55  time: 0.3227  data_time: 0.0042  memory: 731  loss: 1.2467  loss_cls: 0.2317  loss_bbox: 0.5031  loss_dfl: 0.1978  loss_ld: 0.3142
2023/07/13 11:43:28 - mmengine - INFO - Epoch(train) [10][ 400/3139]  lr: 1.2500e-04  eta: 0:48:39  time: 0.3238  data_time: 0.0040  memory: 719  loss: 1.2236  loss_cls: 0.2535  loss_bbox: 0.5045  loss_dfl: 0.1956  loss_ld: 0.2701
2023/07/13 11:43:44 - mmengine - INFO - Epoch(train) [10][ 450/3139]  lr: 1.2500e-04  eta: 0:48:22  time: 0.3247  data_time: 0.0041  memory: 726  loss: 1.2078  loss_cls: 0.2553  loss_bbox: 0.4639  loss_dfl: 0.1916  loss_ld: 0.2971
2023/07/13 11:44:00 - mmengine - INFO - Epoch(train) [10][ 500/3139]  lr: 1.2500e-04  eta: 0:48:06  time: 0.3234  data_time: 0.0043  memory: 721  loss: 1.2389  loss_cls: 0.2589  loss_bbox: 0.5026  loss_dfl: 0.1938  loss_ld: 0.2835
2023/07/13 11:44:16 - mmengine - INFO - Epoch(train) [10][ 550/3139]  lr: 1.2500e-04  eta: 0:47:50  time: 0.3177  data_time: 0.0042  memory: 733  loss: 1.1247  loss_cls: 0.2339  loss_bbox: 0.4444  loss_dfl: 0.1812  loss_ld: 0.2652
2023/07/13 11:44:32 - mmengine - INFO - Epoch(train) [10][ 600/3139]  lr: 1.2500e-04  eta: 0:47:34  time: 0.3230  data_time: 0.0042  memory: 730  loss: 1.2644  loss_cls: 0.2595  loss_bbox: 0.4865  loss_dfl: 0.1979  loss_ld: 0.3205
2023/07/13 11:44:49 - mmengine - INFO - Epoch(train) [10][ 650/3139]  lr: 1.2500e-04  eta: 0:47:18  time: 0.3237  data_time: 0.0041  memory: 731  loss: 1.1762  loss_cls: 0.2540  loss_bbox: 0.4496  loss_dfl: 0.1861  loss_ld: 0.2865
2023/07/13 11:45:05 - mmengine - INFO - Epoch(train) [10][ 700/3139]  lr: 1.2500e-04  eta: 0:47:01  time: 0.3223  data_time: 0.0050  memory: 738  loss: 1.1346  loss_cls: 0.2409  loss_bbox: 0.4590  loss_dfl: 0.1840  loss_ld: 0.2507
2023/07/13 11:45:21 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:45:21 - mmengine - INFO - Epoch(train) [10][ 750/3139]  lr: 1.2500e-04  eta: 0:46:45  time: 0.3254  data_time: 0.0049  memory: 716  loss: 1.1291  loss_cls: 0.2478  loss_bbox: 0.4283  loss_dfl: 0.1809  loss_ld: 0.2721
2023/07/13 11:45:37 - mmengine - INFO - Epoch(train) [10][ 800/3139]  lr: 1.2500e-04  eta: 0:46:29  time: 0.3169  data_time: 0.0044  memory: 735  loss: 1.2224  loss_cls: 0.2396  loss_bbox: 0.4718  loss_dfl: 0.1860  loss_ld: 0.3249
2023/07/13 11:45:53 - mmengine - INFO - Epoch(train) [10][ 850/3139]  lr: 1.2500e-04  eta: 0:46:13  time: 0.3186  data_time: 0.0051  memory: 721  loss: 1.2213  loss_cls: 0.2643  loss_bbox: 0.4687  loss_dfl: 0.1945  loss_ld: 0.2938
2023/07/13 11:46:09 - mmengine - INFO - Epoch(train) [10][ 900/3139]  lr: 1.2500e-04  eta: 0:45:56  time: 0.3238  data_time: 0.0060  memory: 747  loss: 1.2673  loss_cls: 0.2467  loss_bbox: 0.4713  loss_dfl: 0.1930  loss_ld: 0.3562
2023/07/13 11:46:25 - mmengine - INFO - Epoch(train) [10][ 950/3139]  lr: 1.2500e-04  eta: 0:45:40  time: 0.3268  data_time: 0.0055  memory: 724  loss: 1.2589  loss_cls: 0.2650  loss_bbox: 0.5004  loss_dfl: 0.1986  loss_ld: 0.2949
2023/07/13 11:46:42 - mmengine - INFO - Epoch(train) [10][1000/3139]  lr: 1.2500e-04  eta: 0:45:24  time: 0.3237  data_time: 0.0042  memory: 728  loss: 1.2755  loss_cls: 0.2458  loss_bbox: 0.5185  loss_dfl: 0.1982  loss_ld: 0.3130
2023/07/13 11:46:58 - mmengine - INFO - Epoch(train) [10][1050/3139]  lr: 1.2500e-04  eta: 0:45:08  time: 0.3273  data_time: 0.0045  memory: 727  loss: 1.2150  loss_cls: 0.2514  loss_bbox: 0.4788  loss_dfl: 0.1934  loss_ld: 0.2913
2023/07/13 11:47:14 - mmengine - INFO - Epoch(train) [10][1100/3139]  lr: 1.2500e-04  eta: 0:44:52  time: 0.3266  data_time: 0.0053  memory: 722  loss: 1.2518  loss_cls: 0.2733  loss_bbox: 0.4935  loss_dfl: 0.1951  loss_ld: 0.2898
2023/07/13 11:47:30 - mmengine - INFO - Epoch(train) [10][1150/3139]  lr: 1.2500e-04  eta: 0:44:36  time: 0.3236  data_time: 0.0043  memory: 717  loss: 1.2149  loss_cls: 0.2582  loss_bbox: 0.4822  loss_dfl: 0.1935  loss_ld: 0.2809
2023/07/13 11:47:47 - mmengine - INFO - Epoch(train) [10][1200/3139]  lr: 1.2500e-04  eta: 0:44:20  time: 0.3238  data_time: 0.0044  memory: 716  loss: 1.1944  loss_cls: 0.2540  loss_bbox: 0.4827  loss_dfl: 0.1962  loss_ld: 0.2614
2023/07/13 11:48:03 - mmengine - INFO - Epoch(train) [10][1250/3139]  lr: 1.2500e-04  eta: 0:44:03  time: 0.3261  data_time: 0.0050  memory: 717  loss: 1.1337  loss_cls: 0.2663  loss_bbox: 0.4173  loss_dfl: 0.1811  loss_ld: 0.2690
2023/07/13 11:48:19 - mmengine - INFO - Epoch(train) [10][1300/3139]  lr: 1.2500e-04  eta: 0:43:47  time: 0.3212  data_time: 0.0038  memory: 721  loss: 1.2079  loss_cls: 0.2347  loss_bbox: 0.4630  loss_dfl: 0.1886  loss_ld: 0.3216
2023/07/13 11:48:36 - mmengine - INFO - Epoch(train) [10][1350/3139]  lr: 1.2500e-04  eta: 0:43:31  time: 0.3293  data_time: 0.0064  memory: 729  loss: 1.2399  loss_cls: 0.2432  loss_bbox: 0.4776  loss_dfl: 0.1928  loss_ld: 0.3262
2023/07/13 11:48:52 - mmengine - INFO - Epoch(train) [10][1400/3139]  lr: 1.2500e-04  eta: 0:43:15  time: 0.3264  data_time: 0.0063  memory: 736  loss: 1.2599  loss_cls: 0.2348  loss_bbox: 0.4713  loss_dfl: 0.1933  loss_ld: 0.3605
2023/07/13 11:49:08 - mmengine - INFO - Epoch(train) [10][1450/3139]  lr: 1.2500e-04  eta: 0:42:59  time: 0.3252  data_time: 0.0043  memory: 724  loss: 1.2432  loss_cls: 0.2582  loss_bbox: 0.4671  loss_dfl: 0.1946  loss_ld: 0.3232
2023/07/13 11:49:24 - mmengine - INFO - Epoch(train) [10][1500/3139]  lr: 1.2500e-04  eta: 0:42:43  time: 0.3219  data_time: 0.0037  memory: 739  loss: 1.1955  loss_cls: 0.2486  loss_bbox: 0.4817  loss_dfl: 0.1901  loss_ld: 0.2751
2023/07/13 11:49:40 - mmengine - INFO - Epoch(train) [10][1550/3139]  lr: 1.2500e-04  eta: 0:42:26  time: 0.3238  data_time: 0.0051  memory: 725  loss: 1.1882  loss_cls: 0.2570  loss_bbox: 0.4774  loss_dfl: 0.1898  loss_ld: 0.2641
2023/07/13 11:49:57 - mmengine - INFO - Epoch(train) [10][1600/3139]  lr: 1.2500e-04  eta: 0:42:10  time: 0.3236  data_time: 0.0046  memory: 718  loss: 1.1636  loss_cls: 0.2474  loss_bbox: 0.4599  loss_dfl: 0.1869  loss_ld: 0.2693
2023/07/13 11:50:13 - mmengine - INFO - Epoch(train) [10][1650/3139]  lr: 1.2500e-04  eta: 0:41:54  time: 0.3239  data_time: 0.0040  memory: 718  loss: 1.2405  loss_cls: 0.2479  loss_bbox: 0.4701  loss_dfl: 0.1916  loss_ld: 0.3309
2023/07/13 11:50:29 - mmengine - INFO - Epoch(train) [10][1700/3139]  lr: 1.2500e-04  eta: 0:41:38  time: 0.3234  data_time: 0.0044  memory: 725  loss: 1.1332  loss_cls: 0.2422  loss_bbox: 0.4520  loss_dfl: 0.1813  loss_ld: 0.2577
2023/07/13 11:50:45 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:50:45 - mmengine - INFO - Epoch(train) [10][1750/3139]  lr: 1.2500e-04  eta: 0:41:22  time: 0.3260  data_time: 0.0047  memory: 719  loss: 1.1978  loss_cls: 0.2409  loss_bbox: 0.4930  loss_dfl: 0.1872  loss_ld: 0.2767
2023/07/13 11:51:01 - mmengine - INFO - Epoch(train) [10][1800/3139]  lr: 1.2500e-04  eta: 0:41:05  time: 0.3208  data_time: 0.0043  memory: 728  loss: 1.1760  loss_cls: 0.2386  loss_bbox: 0.5025  loss_dfl: 0.1911  loss_ld: 0.2438
2023/07/13 11:51:18 - mmengine - INFO - Epoch(train) [10][1850/3139]  lr: 1.2500e-04  eta: 0:40:49  time: 0.3259  data_time: 0.0053  memory: 731  loss: 1.2506  loss_cls: 0.2527  loss_bbox: 0.4925  loss_dfl: 0.1982  loss_ld: 0.3072
2023/07/13 11:51:34 - mmengine - INFO - Epoch(train) [10][1900/3139]  lr: 1.2500e-04  eta: 0:40:33  time: 0.3263  data_time: 0.0045  memory: 730  loss: 1.2023  loss_cls: 0.2507  loss_bbox: 0.4673  loss_dfl: 0.1889  loss_ld: 0.2953
2023/07/13 11:51:50 - mmengine - INFO - Epoch(train) [10][1950/3139]  lr: 1.2500e-04  eta: 0:40:17  time: 0.3298  data_time: 0.0060  memory: 738  loss: 1.1793  loss_cls: 0.2470  loss_bbox: 0.4623  loss_dfl: 0.1871  loss_ld: 0.2829
2023/07/13 11:52:07 - mmengine - INFO - Epoch(train) [10][2000/3139]  lr: 1.2500e-04  eta: 0:40:01  time: 0.3240  data_time: 0.0043  memory: 724  loss: 1.1872  loss_cls: 0.2568  loss_bbox: 0.4895  loss_dfl: 0.1919  loss_ld: 0.2490
2023/07/13 11:52:23 - mmengine - INFO - Epoch(train) [10][2050/3139]  lr: 1.2500e-04  eta: 0:39:45  time: 0.3240  data_time: 0.0039  memory: 720  loss: 1.1916  loss_cls: 0.2387  loss_bbox: 0.4883  loss_dfl: 0.1888  loss_ld: 0.2757
2023/07/13 11:52:39 - mmengine - INFO - Epoch(train) [10][2100/3139]  lr: 1.2500e-04  eta: 0:39:28  time: 0.3239  data_time: 0.0047  memory: 717  loss: 1.1983  loss_cls: 0.2375  loss_bbox: 0.4656  loss_dfl: 0.1903  loss_ld: 0.3049
2023/07/13 11:52:55 - mmengine - INFO - Epoch(train) [10][2150/3139]  lr: 1.2500e-04  eta: 0:39:12  time: 0.3249  data_time: 0.0048  memory: 726  loss: 1.2119  loss_cls: 0.2396  loss_bbox: 0.5048  loss_dfl: 0.1951  loss_ld: 0.2724
2023/07/13 11:53:12 - mmengine - INFO - Epoch(train) [10][2200/3139]  lr: 1.2500e-04  eta: 0:38:56  time: 0.3252  data_time: 0.0047  memory: 739  loss: 1.2090  loss_cls: 0.2469  loss_bbox: 0.4549  loss_dfl: 0.1907  loss_ld: 0.3164
2023/07/13 11:53:28 - mmengine - INFO - Epoch(train) [10][2250/3139]  lr: 1.2500e-04  eta: 0:38:40  time: 0.3252  data_time: 0.0050  memory: 761  loss: 1.2033  loss_cls: 0.2383  loss_bbox: 0.4725  loss_dfl: 0.1897  loss_ld: 0.3027
2023/07/13 11:53:44 - mmengine - INFO - Epoch(train) [10][2300/3139]  lr: 1.2500e-04  eta: 0:38:24  time: 0.3275  data_time: 0.0049  memory: 724  loss: 1.2538  loss_cls: 0.2691  loss_bbox: 0.4996  loss_dfl: 0.1958  loss_ld: 0.2894
2023/07/13 11:54:01 - mmengine - INFO - Epoch(train) [10][2350/3139]  lr: 1.2500e-04  eta: 0:38:08  time: 0.3254  data_time: 0.0049  memory: 722  loss: 1.1284  loss_cls: 0.2512  loss_bbox: 0.4458  loss_dfl: 0.1864  loss_ld: 0.2451
2023/07/13 11:54:17 - mmengine - INFO - Epoch(train) [10][2400/3139]  lr: 1.2500e-04  eta: 0:37:51  time: 0.3202  data_time: 0.0041  memory: 719  loss: 1.2091  loss_cls: 0.2443  loss_bbox: 0.4935  loss_dfl: 0.1875  loss_ld: 0.2837
2023/07/13 11:54:33 - mmengine - INFO - Epoch(train) [10][2450/3139]  lr: 1.2500e-04  eta: 0:37:35  time: 0.3249  data_time: 0.0046  memory: 722  loss: 1.2162  loss_cls: 0.2322  loss_bbox: 0.4611  loss_dfl: 0.1911  loss_ld: 0.3317
2023/07/13 11:54:49 - mmengine - INFO - Epoch(train) [10][2500/3139]  lr: 1.2500e-04  eta: 0:37:19  time: 0.3235  data_time: 0.0039  memory: 731  loss: 1.2185  loss_cls: 0.2553  loss_bbox: 0.4890  loss_dfl: 0.1977  loss_ld: 0.2764
2023/07/13 11:55:05 - mmengine - INFO - Epoch(train) [10][2550/3139]  lr: 1.2500e-04  eta: 0:37:03  time: 0.3227  data_time: 0.0045  memory: 719  loss: 1.2120  loss_cls: 0.2452  loss_bbox: 0.4683  loss_dfl: 0.1921  loss_ld: 0.3065
2023/07/13 11:55:21 - mmengine - INFO - Epoch(train) [10][2600/3139]  lr: 1.2500e-04  eta: 0:36:47  time: 0.3232  data_time: 0.0046  memory: 716  loss: 1.2094  loss_cls: 0.2558  loss_bbox: 0.4813  loss_dfl: 0.1893  loss_ld: 0.2830
2023/07/13 11:55:38 - mmengine - INFO - Epoch(train) [10][2650/3139]  lr: 1.2500e-04  eta: 0:36:30  time: 0.3238  data_time: 0.0064  memory: 722  loss: 1.1792  loss_cls: 0.2255  loss_bbox: 0.4487  loss_dfl: 0.1868  loss_ld: 0.3183
2023/07/13 11:55:54 - mmengine - INFO - Epoch(train) [10][2700/3139]  lr: 1.2500e-04  eta: 0:36:14  time: 0.3228  data_time: 0.0052  memory: 743  loss: 1.2271  loss_cls: 0.2394  loss_bbox: 0.4341  loss_dfl: 0.1881  loss_ld: 0.3655
2023/07/13 11:56:09 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:56:10 - mmengine - INFO - Epoch(train) [10][2750/3139]  lr: 1.2500e-04  eta: 0:35:58  time: 0.3187  data_time: 0.0039  memory: 725  loss: 1.2399  loss_cls: 0.2371  loss_bbox: 0.5109  loss_dfl: 0.1943  loss_ld: 0.2975
2023/07/13 11:56:26 - mmengine - INFO - Epoch(train) [10][2800/3139]  lr: 1.2500e-04  eta: 0:35:42  time: 0.3199  data_time: 0.0041  memory: 726  loss: 1.2392  loss_cls: 0.2554  loss_bbox: 0.4999  loss_dfl: 0.1938  loss_ld: 0.2902
2023/07/13 11:56:42 - mmengine - INFO - Epoch(train) [10][2850/3139]  lr: 1.2500e-04  eta: 0:35:26  time: 0.3256  data_time: 0.0058  memory: 728  loss: 1.2184  loss_cls: 0.2472  loss_bbox: 0.4856  loss_dfl: 0.1944  loss_ld: 0.2912
2023/07/13 11:56:58 - mmengine - INFO - Epoch(train) [10][2900/3139]  lr: 1.2500e-04  eta: 0:35:09  time: 0.3210  data_time: 0.0044  memory: 715  loss: 1.1950  loss_cls: 0.2396  loss_bbox: 0.4839  loss_dfl: 0.1940  loss_ld: 0.2774
2023/07/13 11:57:14 - mmengine - INFO - Epoch(train) [10][2950/3139]  lr: 1.2500e-04  eta: 0:34:53  time: 0.3232  data_time: 0.0038  memory: 728  loss: 1.2083  loss_cls: 0.2173  loss_bbox: 0.4828  loss_dfl: 0.1903  loss_ld: 0.3179
2023/07/13 11:57:30 - mmengine - INFO - Epoch(train) [10][3000/3139]  lr: 1.2500e-04  eta: 0:34:37  time: 0.3238  data_time: 0.0040  memory: 717  loss: 1.1855  loss_cls: 0.2478  loss_bbox: 0.4771  loss_dfl: 0.1898  loss_ld: 0.2708
2023/07/13 11:57:47 - mmengine - INFO - Epoch(train) [10][3050/3139]  lr: 1.2500e-04  eta: 0:34:21  time: 0.3271  data_time: 0.0046  memory: 717  loss: 1.1969  loss_cls: 0.2554  loss_bbox: 0.4589  loss_dfl: 0.1901  loss_ld: 0.2926
2023/07/13 11:58:03 - mmengine - INFO - Epoch(train) [10][3100/3139]  lr: 1.2500e-04  eta: 0:34:05  time: 0.3248  data_time: 0.0042  memory: 719  loss: 1.1892  loss_cls: 0.2525  loss_bbox: 0.4341  loss_dfl: 0.1891  loss_ld: 0.3134
2023/07/13 11:58:15 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 11:58:15 - mmengine - INFO - Saving checkpoint at 10 epochs
2023/07/13 11:58:23 - mmengine - INFO - Epoch(val) [10][ 50/548]    eta: 0:00:37  time: 0.0751  data_time: 0.0019  memory: 731  
2023/07/13 11:58:26 - mmengine - INFO - Epoch(val) [10][100/548]    eta: 0:00:33  time: 0.0737  data_time: 0.0014  memory: 497  
2023/07/13 11:58:30 - mmengine - INFO - Epoch(val) [10][150/548]    eta: 0:00:29  time: 0.0739  data_time: 0.0014  memory: 497  
2023/07/13 11:58:34 - mmengine - INFO - Epoch(val) [10][200/548]    eta: 0:00:25  time: 0.0736  data_time: 0.0014  memory: 497  
2023/07/13 11:58:37 - mmengine - INFO - Epoch(val) [10][250/548]    eta: 0:00:22  time: 0.0743  data_time: 0.0014  memory: 497  
2023/07/13 11:58:41 - mmengine - INFO - Epoch(val) [10][300/548]    eta: 0:00:18  time: 0.0733  data_time: 0.0014  memory: 497  
2023/07/13 11:58:45 - mmengine - INFO - Epoch(val) [10][350/548]    eta: 0:00:14  time: 0.0735  data_time: 0.0013  memory: 497  
2023/07/13 11:58:48 - mmengine - INFO - Epoch(val) [10][400/548]    eta: 0:00:10  time: 0.0740  data_time: 0.0014  memory: 497  
2023/07/13 11:58:52 - mmengine - INFO - Epoch(val) [10][450/548]    eta: 0:00:07  time: 0.0760  data_time: 0.0015  memory: 497  
2023/07/13 11:58:56 - mmengine - INFO - Epoch(val) [10][500/548]    eta: 0:00:03  time: 0.0783  data_time: 0.0015  memory: 497  
2023/07/13 11:59:01 - mmengine - INFO - Evaluating bbox...
2023/07/13 11:59:15 - mmengine - INFO - bbox_mAP_copypaste: 0.106 0.176 0.114 0.030 0.152 0.294
2023/07/13 11:59:16 - mmengine - INFO - Epoch(val) [10][548/548]    coco/bbox_mAP: 0.1060  coco/bbox_mAP_50: 0.1760  coco/bbox_mAP_75: 0.1140  coco/bbox_mAP_s: 0.0300  coco/bbox_mAP_m: 0.1520  coco/bbox_mAP_l: 0.2940  data_time: 0.0015  time: 0.0750
2023/07/13 11:59:33 - mmengine - INFO - Epoch(train) [11][  50/3139]  lr: 1.2500e-04  eta: 0:33:36  time: 0.3487  data_time: 0.0284  memory: 727  loss: 1.2236  loss_cls: 0.2321  loss_bbox: 0.5062  loss_dfl: 0.1933  loss_ld: 0.2921
2023/07/13 11:59:49 - mmengine - INFO - Epoch(train) [11][ 100/3139]  lr: 1.2500e-04  eta: 0:33:20  time: 0.3251  data_time: 0.0052  memory: 726  loss: 1.1504  loss_cls: 0.2462  loss_bbox: 0.4401  loss_dfl: 0.1880  loss_ld: 0.2761
2023/07/13 12:00:05 - mmengine - INFO - Epoch(train) [11][ 150/3139]  lr: 1.2500e-04  eta: 0:33:04  time: 0.3224  data_time: 0.0041  memory: 717  loss: 1.1470  loss_cls: 0.2413  loss_bbox: 0.4835  loss_dfl: 0.1846  loss_ld: 0.2375
2023/07/13 12:00:22 - mmengine - INFO - Epoch(train) [11][ 200/3139]  lr: 1.2500e-04  eta: 0:32:47  time: 0.3252  data_time: 0.0050  memory: 720  loss: 1.1683  loss_cls: 0.2531  loss_bbox: 0.4735  loss_dfl: 0.1865  loss_ld: 0.2552
2023/07/13 12:00:38 - mmengine - INFO - Epoch(train) [11][ 250/3139]  lr: 1.2500e-04  eta: 0:32:31  time: 0.3233  data_time: 0.0042  memory: 725  loss: 1.1745  loss_cls: 0.2475  loss_bbox: 0.4605  loss_dfl: 0.1897  loss_ld: 0.2767
2023/07/13 12:00:54 - mmengine - INFO - Epoch(train) [11][ 300/3139]  lr: 1.2500e-04  eta: 0:32:15  time: 0.3245  data_time: 0.0038  memory: 724  loss: 1.1941  loss_cls: 0.2468  loss_bbox: 0.4622  loss_dfl: 0.1886  loss_ld: 0.2966
2023/07/13 12:01:10 - mmengine - INFO - Epoch(train) [11][ 350/3139]  lr: 1.2500e-04  eta: 0:31:59  time: 0.3228  data_time: 0.0043  memory: 719  loss: 1.2189  loss_cls: 0.2594  loss_bbox: 0.4448  loss_dfl: 0.1897  loss_ld: 0.3250
2023/07/13 12:01:26 - mmengine - INFO - Epoch(train) [11][ 400/3139]  lr: 1.2500e-04  eta: 0:31:43  time: 0.3244  data_time: 0.0045  memory: 723  loss: 1.1743  loss_cls: 0.2434  loss_bbox: 0.4510  loss_dfl: 0.1887  loss_ld: 0.2913
2023/07/13 12:01:44 - mmengine - INFO - Epoch(train) [11][ 450/3139]  lr: 1.2500e-04  eta: 0:31:27  time: 0.3577  data_time: 0.0383  memory: 724  loss: 1.1679  loss_cls: 0.2518  loss_bbox: 0.4564  loss_dfl: 0.1895  loss_ld: 0.2702
2023/07/13 12:02:01 - mmengine - INFO - Epoch(train) [11][ 500/3139]  lr: 1.2500e-04  eta: 0:31:11  time: 0.3266  data_time: 0.0059  memory: 747  loss: 1.2163  loss_cls: 0.2450  loss_bbox: 0.4849  loss_dfl: 0.1891  loss_ld: 0.2974
2023/07/13 12:02:17 - mmengine - INFO - Epoch(train) [11][ 550/3139]  lr: 1.2500e-04  eta: 0:30:54  time: 0.3242  data_time: 0.0039  memory: 725  loss: 1.2020  loss_cls: 0.2539  loss_bbox: 0.4576  loss_dfl: 0.1925  loss_ld: 0.2980
2023/07/13 12:02:33 - mmengine - INFO - Epoch(train) [11][ 600/3139]  lr: 1.2500e-04  eta: 0:30:38  time: 0.3258  data_time: 0.0046  memory: 728  loss: 1.1803  loss_cls: 0.2555  loss_bbox: 0.4708  loss_dfl: 0.1861  loss_ld: 0.2680
2023/07/13 12:02:36 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:02:49 - mmengine - INFO - Epoch(train) [11][ 650/3139]  lr: 1.2500e-04  eta: 0:30:22  time: 0.3259  data_time: 0.0049  memory: 725  loss: 1.2111  loss_cls: 0.2388  loss_bbox: 0.5050  loss_dfl: 0.1942  loss_ld: 0.2731
2023/07/13 12:03:06 - mmengine - INFO - Epoch(train) [11][ 700/3139]  lr: 1.2500e-04  eta: 0:30:06  time: 0.3242  data_time: 0.0045  memory: 749  loss: 1.1850  loss_cls: 0.2377  loss_bbox: 0.4485  loss_dfl: 0.1850  loss_ld: 0.3139
2023/07/13 12:03:22 - mmengine - INFO - Epoch(train) [11][ 750/3139]  lr: 1.2500e-04  eta: 0:29:50  time: 0.3257  data_time: 0.0044  memory: 717  loss: 1.2151  loss_cls: 0.2623  loss_bbox: 0.4750  loss_dfl: 0.1907  loss_ld: 0.2872
2023/07/13 12:03:38 - mmengine - INFO - Epoch(train) [11][ 800/3139]  lr: 1.2500e-04  eta: 0:29:34  time: 0.3236  data_time: 0.0038  memory: 739  loss: 1.2042  loss_cls: 0.2293  loss_bbox: 0.4492  loss_dfl: 0.1837  loss_ld: 0.3420
2023/07/13 12:03:54 - mmengine - INFO - Epoch(train) [11][ 850/3139]  lr: 1.2500e-04  eta: 0:29:17  time: 0.3254  data_time: 0.0044  memory: 730  loss: 1.2148  loss_cls: 0.2354  loss_bbox: 0.4821  loss_dfl: 0.1902  loss_ld: 0.3072
2023/07/13 12:04:11 - mmengine - INFO - Epoch(train) [11][ 900/3139]  lr: 1.2500e-04  eta: 0:29:01  time: 0.3247  data_time: 0.0048  memory: 734  loss: 1.1883  loss_cls: 0.2449  loss_bbox: 0.4806  loss_dfl: 0.1944  loss_ld: 0.2684
2023/07/13 12:04:27 - mmengine - INFO - Epoch(train) [11][ 950/3139]  lr: 1.2500e-04  eta: 0:28:45  time: 0.3226  data_time: 0.0041  memory: 730  loss: 1.1513  loss_cls: 0.2370  loss_bbox: 0.4630  loss_dfl: 0.1874  loss_ld: 0.2639
2023/07/13 12:04:43 - mmengine - INFO - Epoch(train) [11][1000/3139]  lr: 1.2500e-04  eta: 0:28:29  time: 0.3265  data_time: 0.0057  memory: 728  loss: 1.1948  loss_cls: 0.2332  loss_bbox: 0.4887  loss_dfl: 0.1911  loss_ld: 0.2818
2023/07/13 12:04:59 - mmengine - INFO - Epoch(train) [11][1050/3139]  lr: 1.2500e-04  eta: 0:28:13  time: 0.3223  data_time: 0.0046  memory: 714  loss: 1.1708  loss_cls: 0.2593  loss_bbox: 0.4735  loss_dfl: 0.1828  loss_ld: 0.2552
2023/07/13 12:05:15 - mmengine - INFO - Epoch(train) [11][1100/3139]  lr: 1.2500e-04  eta: 0:27:56  time: 0.3218  data_time: 0.0038  memory: 731  loss: 1.1562  loss_cls: 0.2368  loss_bbox: 0.4708  loss_dfl: 0.1857  loss_ld: 0.2628
2023/07/13 12:05:32 - mmengine - INFO - Epoch(train) [11][1150/3139]  lr: 1.2500e-04  eta: 0:27:40  time: 0.3229  data_time: 0.0046  memory: 728  loss: 1.2290  loss_cls: 0.2674  loss_bbox: 0.4916  loss_dfl: 0.1941  loss_ld: 0.2760
2023/07/13 12:05:48 - mmengine - INFO - Epoch(train) [11][1200/3139]  lr: 1.2500e-04  eta: 0:27:24  time: 0.3248  data_time: 0.0043  memory: 722  loss: 1.2213  loss_cls: 0.2409  loss_bbox: 0.5026  loss_dfl: 0.1915  loss_ld: 0.2864
2023/07/13 12:06:04 - mmengine - INFO - Epoch(train) [11][1250/3139]  lr: 1.2500e-04  eta: 0:27:08  time: 0.3288  data_time: 0.0062  memory: 730  loss: 1.2993  loss_cls: 0.2443  loss_bbox: 0.5213  loss_dfl: 0.2067  loss_ld: 0.3271
2023/07/13 12:06:21 - mmengine - INFO - Epoch(train) [11][1300/3139]  lr: 1.2500e-04  eta: 0:26:52  time: 0.3253  data_time: 0.0058  memory: 714  loss: 1.2402  loss_cls: 0.2616  loss_bbox: 0.4825  loss_dfl: 0.1979  loss_ld: 0.2982
2023/07/13 12:06:37 - mmengine - INFO - Epoch(train) [11][1350/3139]  lr: 1.2500e-04  eta: 0:26:35  time: 0.3207  data_time: 0.0042  memory: 724  loss: 1.1523  loss_cls: 0.2527  loss_bbox: 0.4509  loss_dfl: 0.1827  loss_ld: 0.2659
2023/07/13 12:06:53 - mmengine - INFO - Epoch(train) [11][1400/3139]  lr: 1.2500e-04  eta: 0:26:19  time: 0.3224  data_time: 0.0045  memory: 752  loss: 1.2442  loss_cls: 0.2456  loss_bbox: 0.4988  loss_dfl: 0.1938  loss_ld: 0.3061
2023/07/13 12:07:09 - mmengine - INFO - Epoch(train) [11][1450/3139]  lr: 1.2500e-04  eta: 0:26:03  time: 0.3232  data_time: 0.0042  memory: 721  loss: 1.2260  loss_cls: 0.2471  loss_bbox: 0.5113  loss_dfl: 0.1932  loss_ld: 0.2743
2023/07/13 12:07:25 - mmengine - INFO - Epoch(train) [11][1500/3139]  lr: 1.2500e-04  eta: 0:25:47  time: 0.3248  data_time: 0.0042  memory: 743  loss: 1.2419  loss_cls: 0.2638  loss_bbox: 0.4905  loss_dfl: 0.1925  loss_ld: 0.2951
2023/07/13 12:07:41 - mmengine - INFO - Epoch(train) [11][1550/3139]  lr: 1.2500e-04  eta: 0:25:31  time: 0.3256  data_time: 0.0038  memory: 719  loss: 1.2683  loss_cls: 0.2752  loss_bbox: 0.4866  loss_dfl: 0.1918  loss_ld: 0.3146
2023/07/13 12:07:58 - mmengine - INFO - Epoch(train) [11][1600/3139]  lr: 1.2500e-04  eta: 0:25:15  time: 0.3274  data_time: 0.0056  memory: 725  loss: 1.2503  loss_cls: 0.2761  loss_bbox: 0.4910  loss_dfl: 0.1931  loss_ld: 0.2902
2023/07/13 12:08:01 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:08:14 - mmengine - INFO - Epoch(train) [11][1650/3139]  lr: 1.2500e-04  eta: 0:24:58  time: 0.3263  data_time: 0.0052  memory: 728  loss: 1.1922  loss_cls: 0.2304  loss_bbox: 0.4700  loss_dfl: 0.1903  loss_ld: 0.3015
2023/07/13 12:08:30 - mmengine - INFO - Epoch(train) [11][1700/3139]  lr: 1.2500e-04  eta: 0:24:42  time: 0.3236  data_time: 0.0035  memory: 762  loss: 1.1163  loss_cls: 0.2413  loss_bbox: 0.4113  loss_dfl: 0.1821  loss_ld: 0.2817
2023/07/13 12:08:46 - mmengine - INFO - Epoch(train) [11][1750/3139]  lr: 1.2500e-04  eta: 0:24:26  time: 0.3233  data_time: 0.0041  memory: 722  loss: 1.2238  loss_cls: 0.2456  loss_bbox: 0.4865  loss_dfl: 0.1917  loss_ld: 0.3001
2023/07/13 12:09:03 - mmengine - INFO - Epoch(train) [11][1800/3139]  lr: 1.2500e-04  eta: 0:24:10  time: 0.3250  data_time: 0.0042  memory: 733  loss: 1.2372  loss_cls: 0.2599  loss_bbox: 0.4670  loss_dfl: 0.1928  loss_ld: 0.3175
2023/07/13 12:09:19 - mmengine - INFO - Epoch(train) [11][1850/3139]  lr: 1.2500e-04  eta: 0:23:54  time: 0.3225  data_time: 0.0050  memory: 717  loss: 1.1934  loss_cls: 0.2624  loss_bbox: 0.4707  loss_dfl: 0.1969  loss_ld: 0.2635
2023/07/13 12:09:35 - mmengine - INFO - Epoch(train) [11][1900/3139]  lr: 1.2500e-04  eta: 0:23:37  time: 0.3252  data_time: 0.0041  memory: 726  loss: 1.1468  loss_cls: 0.2350  loss_bbox: 0.4407  loss_dfl: 0.1833  loss_ld: 0.2877
2023/07/13 12:09:51 - mmengine - INFO - Epoch(train) [11][1950/3139]  lr: 1.2500e-04  eta: 0:23:21  time: 0.3243  data_time: 0.0040  memory: 721  loss: 1.2369  loss_cls: 0.2493  loss_bbox: 0.4573  loss_dfl: 0.1944  loss_ld: 0.3359
2023/07/13 12:10:08 - mmengine - INFO - Epoch(train) [11][2000/3139]  lr: 1.2500e-04  eta: 0:23:05  time: 0.3256  data_time: 0.0049  memory: 722  loss: 1.2107  loss_cls: 0.2486  loss_bbox: 0.4535  loss_dfl: 0.1858  loss_ld: 0.3228
2023/07/13 12:10:24 - mmengine - INFO - Epoch(train) [11][2050/3139]  lr: 1.2500e-04  eta: 0:22:49  time: 0.3243  data_time: 0.0048  memory: 724  loss: 1.1932  loss_cls: 0.2423  loss_bbox: 0.4826  loss_dfl: 0.1900  loss_ld: 0.2782
2023/07/13 12:10:40 - mmengine - INFO - Epoch(train) [11][2100/3139]  lr: 1.2500e-04  eta: 0:22:33  time: 0.3235  data_time: 0.0046  memory: 720  loss: 1.1958  loss_cls: 0.2405  loss_bbox: 0.4563  loss_dfl: 0.1899  loss_ld: 0.3091
2023/07/13 12:10:56 - mmengine - INFO - Epoch(train) [11][2150/3139]  lr: 1.2500e-04  eta: 0:22:16  time: 0.3239  data_time: 0.0039  memory: 724  loss: 1.1824  loss_cls: 0.2463  loss_bbox: 0.4620  loss_dfl: 0.1882  loss_ld: 0.2860
2023/07/13 12:11:12 - mmengine - INFO - Epoch(train) [11][2200/3139]  lr: 1.2500e-04  eta: 0:22:00  time: 0.3225  data_time: 0.0053  memory: 728  loss: 1.1747  loss_cls: 0.2408  loss_bbox: 0.4678  loss_dfl: 0.1860  loss_ld: 0.2801
2023/07/13 12:11:28 - mmengine - INFO - Epoch(train) [11][2250/3139]  lr: 1.2500e-04  eta: 0:21:44  time: 0.3220  data_time: 0.0046  memory: 722  loss: 1.2942  loss_cls: 0.2577  loss_bbox: 0.5115  loss_dfl: 0.1989  loss_ld: 0.3262
2023/07/13 12:11:45 - mmengine - INFO - Epoch(train) [11][2300/3139]  lr: 1.2500e-04  eta: 0:21:28  time: 0.3216  data_time: 0.0043  memory: 718  loss: 1.2191  loss_cls: 0.2533  loss_bbox: 0.4808  loss_dfl: 0.1921  loss_ld: 0.2928
2023/07/13 12:12:01 - mmengine - INFO - Epoch(train) [11][2350/3139]  lr: 1.2500e-04  eta: 0:21:12  time: 0.3228  data_time: 0.0047  memory: 720  loss: 1.1961  loss_cls: 0.2387  loss_bbox: 0.4615  loss_dfl: 0.1874  loss_ld: 0.3085
2023/07/13 12:12:17 - mmengine - INFO - Epoch(train) [11][2400/3139]  lr: 1.2500e-04  eta: 0:20:55  time: 0.3216  data_time: 0.0036  memory: 721  loss: 1.2196  loss_cls: 0.2414  loss_bbox: 0.4733  loss_dfl: 0.1896  loss_ld: 0.3152
2023/07/13 12:12:33 - mmengine - INFO - Epoch(train) [11][2450/3139]  lr: 1.2500e-04  eta: 0:20:39  time: 0.3261  data_time: 0.0055  memory: 728  loss: 1.1946  loss_cls: 0.2423  loss_bbox: 0.4694  loss_dfl: 0.1892  loss_ld: 0.2937
2023/07/13 12:12:49 - mmengine - INFO - Epoch(train) [11][2500/3139]  lr: 1.2500e-04  eta: 0:20:23  time: 0.3230  data_time: 0.0040  memory: 738  loss: 1.1457  loss_cls: 0.2427  loss_bbox: 0.4468  loss_dfl: 0.1893  loss_ld: 0.2670
2023/07/13 12:13:06 - mmengine - INFO - Epoch(train) [11][2550/3139]  lr: 1.2500e-04  eta: 0:20:07  time: 0.3255  data_time: 0.0049  memory: 723  loss: 1.2458  loss_cls: 0.2291  loss_bbox: 0.4753  loss_dfl: 0.1883  loss_ld: 0.3531
2023/07/13 12:13:22 - mmengine - INFO - Epoch(train) [11][2600/3139]  lr: 1.2500e-04  eta: 0:19:51  time: 0.3198  data_time: 0.0040  memory: 727  loss: 1.2106  loss_cls: 0.2371  loss_bbox: 0.4990  loss_dfl: 0.1968  loss_ld: 0.2777
2023/07/13 12:13:25 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:13:38 - mmengine - INFO - Epoch(train) [11][2650/3139]  lr: 1.2500e-04  eta: 0:19:34  time: 0.3223  data_time: 0.0039  memory: 736  loss: 1.1502  loss_cls: 0.2485  loss_bbox: 0.4699  loss_dfl: 0.1888  loss_ld: 0.2430
2023/07/13 12:13:54 - mmengine - INFO - Epoch(train) [11][2700/3139]  lr: 1.2500e-04  eta: 0:19:18  time: 0.3238  data_time: 0.0044  memory: 736  loss: 1.2106  loss_cls: 0.2508  loss_bbox: 0.4743  loss_dfl: 0.1900  loss_ld: 0.2956
2023/07/13 12:14:10 - mmengine - INFO - Epoch(train) [11][2750/3139]  lr: 1.2500e-04  eta: 0:19:02  time: 0.3257  data_time: 0.0061  memory: 731  loss: 1.1862  loss_cls: 0.2468  loss_bbox: 0.4687  loss_dfl: 0.1928  loss_ld: 0.2779
2023/07/13 12:14:26 - mmengine - INFO - Epoch(train) [11][2800/3139]  lr: 1.2500e-04  eta: 0:18:46  time: 0.3235  data_time: 0.0047  memory: 724  loss: 1.1403  loss_cls: 0.2295  loss_bbox: 0.4768  loss_dfl: 0.1847  loss_ld: 0.2492
2023/07/13 12:14:43 - mmengine - INFO - Epoch(train) [11][2850/3139]  lr: 1.2500e-04  eta: 0:18:30  time: 0.3255  data_time: 0.0050  memory: 716  loss: 1.1358  loss_cls: 0.2390  loss_bbox: 0.4549  loss_dfl: 0.1825  loss_ld: 0.2594
2023/07/13 12:14:59 - mmengine - INFO - Epoch(train) [11][2900/3139]  lr: 1.2500e-04  eta: 0:18:13  time: 0.3206  data_time: 0.0043  memory: 729  loss: 1.2350  loss_cls: 0.2442  loss_bbox: 0.5052  loss_dfl: 0.1927  loss_ld: 0.2929
2023/07/13 12:15:15 - mmengine - INFO - Epoch(train) [11][2950/3139]  lr: 1.2500e-04  eta: 0:17:57  time: 0.3234  data_time: 0.0039  memory: 738  loss: 1.2387  loss_cls: 0.2609  loss_bbox: 0.5123  loss_dfl: 0.1933  loss_ld: 0.2722
2023/07/13 12:15:31 - mmengine - INFO - Epoch(train) [11][3000/3139]  lr: 1.2500e-04  eta: 0:17:41  time: 0.3195  data_time: 0.0043  memory: 719  loss: 1.1482  loss_cls: 0.2411  loss_bbox: 0.4766  loss_dfl: 0.1848  loss_ld: 0.2456
2023/07/13 12:15:47 - mmengine - INFO - Epoch(train) [11][3050/3139]  lr: 1.2500e-04  eta: 0:17:25  time: 0.3252  data_time: 0.0045  memory: 731  loss: 1.2554  loss_cls: 0.2565  loss_bbox: 0.4805  loss_dfl: 0.1909  loss_ld: 0.3275
2023/07/13 12:16:03 - mmengine - INFO - Epoch(train) [11][3100/3139]  lr: 1.2500e-04  eta: 0:17:09  time: 0.3220  data_time: 0.0038  memory: 720  loss: 1.1899  loss_cls: 0.2417  loss_bbox: 0.4601  loss_dfl: 0.1886  loss_ld: 0.2995
2023/07/13 12:16:16 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:16:16 - mmengine - INFO - Saving checkpoint at 11 epochs
2023/07/13 12:16:22 - mmengine - INFO - Epoch(val) [11][ 50/548]    eta: 0:00:37  time: 0.0750  data_time: 0.0019  memory: 717  
2023/07/13 12:16:26 - mmengine - INFO - Epoch(val) [11][100/548]    eta: 0:00:33  time: 0.0732  data_time: 0.0014  memory: 497  
2023/07/13 12:16:30 - mmengine - INFO - Epoch(val) [11][150/548]    eta: 0:00:30  time: 0.0783  data_time: 0.0015  memory: 497  
2023/07/13 12:16:34 - mmengine - INFO - Epoch(val) [11][200/548]    eta: 0:00:26  time: 0.0805  data_time: 0.0016  memory: 497  
2023/07/13 12:16:38 - mmengine - INFO - Epoch(val) [11][250/548]    eta: 0:00:23  time: 0.0808  data_time: 0.0015  memory: 497  
2023/07/13 12:16:42 - mmengine - INFO - Epoch(val) [11][300/548]    eta: 0:00:19  time: 0.0801  data_time: 0.0015  memory: 497  
2023/07/13 12:16:46 - mmengine - INFO - Epoch(val) [11][350/548]    eta: 0:00:15  time: 0.0770  data_time: 0.0015  memory: 497  
2023/07/13 12:16:49 - mmengine - INFO - Epoch(val) [11][400/548]    eta: 0:00:11  time: 0.0740  data_time: 0.0014  memory: 497  
2023/07/13 12:16:53 - mmengine - INFO - Epoch(val) [11][450/548]    eta: 0:00:07  time: 0.0752  data_time: 0.0015  memory: 497  
2023/07/13 12:16:57 - mmengine - INFO - Epoch(val) [11][500/548]    eta: 0:00:03  time: 0.0740  data_time: 0.0014  memory: 497  
2023/07/13 12:17:01 - mmengine - INFO - Evaluating bbox...
2023/07/13 12:17:16 - mmengine - INFO - bbox_mAP_copypaste: 0.106 0.178 0.114 0.029 0.150 0.301
2023/07/13 12:17:16 - mmengine - INFO - Epoch(val) [11][548/548]    coco/bbox_mAP: 0.1060  coco/bbox_mAP_50: 0.1780  coco/bbox_mAP_75: 0.1140  coco/bbox_mAP_s: 0.0290  coco/bbox_mAP_m: 0.1500  coco/bbox_mAP_l: 0.3010  data_time: 0.0015  time: 0.0765
2023/07/13 12:17:32 - mmengine - INFO - Epoch(train) [12][  50/3139]  lr: 1.2500e-05  eta: 0:16:40  time: 0.3243  data_time: 0.0063  memory: 736  loss: 1.1746  loss_cls: 0.2516  loss_bbox: 0.4843  loss_dfl: 0.1900  loss_ld: 0.2488
2023/07/13 12:17:48 - mmengine - INFO - Epoch(train) [12][ 100/3139]  lr: 1.2500e-05  eta: 0:16:24  time: 0.3245  data_time: 0.0042  memory: 720  loss: 1.2346  loss_cls: 0.2458  loss_bbox: 0.4900  loss_dfl: 0.1956  loss_ld: 0.3031
2023/07/13 12:18:04 - mmengine - INFO - Epoch(train) [12][ 150/3139]  lr: 1.2500e-05  eta: 0:16:07  time: 0.3205  data_time: 0.0041  memory: 720  loss: 1.2152  loss_cls: 0.2326  loss_bbox: 0.4936  loss_dfl: 0.1930  loss_ld: 0.2959
2023/07/13 12:18:20 - mmengine - INFO - Epoch(train) [12][ 200/3139]  lr: 1.2500e-05  eta: 0:15:51  time: 0.3218  data_time: 0.0041  memory: 720  loss: 1.2453  loss_cls: 0.2425  loss_bbox: 0.4880  loss_dfl: 0.1945  loss_ld: 0.3203
2023/07/13 12:18:37 - mmengine - INFO - Epoch(train) [12][ 250/3139]  lr: 1.2500e-05  eta: 0:15:35  time: 0.3244  data_time: 0.0043  memory: 715  loss: 1.1671  loss_cls: 0.2438  loss_bbox: 0.4768  loss_dfl: 0.1894  loss_ld: 0.2572
2023/07/13 12:18:53 - mmengine - INFO - Epoch(train) [12][ 300/3139]  lr: 1.2500e-05  eta: 0:15:19  time: 0.3231  data_time: 0.0054  memory: 718  loss: 1.0983  loss_cls: 0.2439  loss_bbox: 0.4141  loss_dfl: 0.1789  loss_ld: 0.2615
2023/07/13 12:19:09 - mmengine - INFO - Epoch(train) [12][ 350/3139]  lr: 1.2500e-05  eta: 0:15:03  time: 0.3246  data_time: 0.0046  memory: 749  loss: 1.2101  loss_cls: 0.2450  loss_bbox: 0.4672  loss_dfl: 0.1933  loss_ld: 0.3046
2023/07/13 12:19:25 - mmengine - INFO - Epoch(train) [12][ 400/3139]  lr: 1.2500e-05  eta: 0:14:46  time: 0.3250  data_time: 0.0053  memory: 733  loss: 1.1897  loss_cls: 0.2397  loss_bbox: 0.4704  loss_dfl: 0.1893  loss_ld: 0.2902
2023/07/13 12:19:42 - mmengine - INFO - Epoch(train) [12][ 450/3139]  lr: 1.2500e-05  eta: 0:14:30  time: 0.3249  data_time: 0.0051  memory: 719  loss: 1.1459  loss_cls: 0.2391  loss_bbox: 0.4423  loss_dfl: 0.1863  loss_ld: 0.2782
2023/07/13 12:19:48 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:19:58 - mmengine - INFO - Epoch(train) [12][ 500/3139]  lr: 1.2500e-05  eta: 0:14:14  time: 0.3247  data_time: 0.0052  memory: 717  loss: 1.1956  loss_cls: 0.2541  loss_bbox: 0.4512  loss_dfl: 0.1881  loss_ld: 0.3022
2023/07/13 12:20:14 - mmengine - INFO - Epoch(train) [12][ 550/3139]  lr: 1.2500e-05  eta: 0:13:58  time: 0.3229  data_time: 0.0044  memory: 727  loss: 1.1815  loss_cls: 0.2313  loss_bbox: 0.5024  loss_dfl: 0.1901  loss_ld: 0.2577
2023/07/13 12:20:30 - mmengine - INFO - Epoch(train) [12][ 600/3139]  lr: 1.2500e-05  eta: 0:13:42  time: 0.3253  data_time: 0.0048  memory: 743  loss: 1.1483  loss_cls: 0.2502  loss_bbox: 0.4687  loss_dfl: 0.1866  loss_ld: 0.2428
2023/07/13 12:20:46 - mmengine - INFO - Epoch(train) [12][ 650/3139]  lr: 1.2500e-05  eta: 0:13:26  time: 0.3191  data_time: 0.0047  memory: 731  loss: 1.1650  loss_cls: 0.2273  loss_bbox: 0.4644  loss_dfl: 0.1890  loss_ld: 0.2843
2023/07/13 12:21:03 - mmengine - INFO - Epoch(train) [12][ 700/3139]  lr: 1.2500e-05  eta: 0:13:09  time: 0.3256  data_time: 0.0038  memory: 734  loss: 1.2436  loss_cls: 0.2404  loss_bbox: 0.4757  loss_dfl: 0.1930  loss_ld: 0.3345
2023/07/13 12:21:19 - mmengine - INFO - Epoch(train) [12][ 750/3139]  lr: 1.2500e-05  eta: 0:12:53  time: 0.3197  data_time: 0.0038  memory: 730  loss: 1.1643  loss_cls: 0.2274  loss_bbox: 0.4844  loss_dfl: 0.1869  loss_ld: 0.2656
2023/07/13 12:21:35 - mmengine - INFO - Epoch(train) [12][ 800/3139]  lr: 1.2500e-05  eta: 0:12:37  time: 0.3232  data_time: 0.0039  memory: 721  loss: 1.1777  loss_cls: 0.2397  loss_bbox: 0.4815  loss_dfl: 0.1872  loss_ld: 0.2693
2023/07/13 12:21:51 - mmengine - INFO - Epoch(train) [12][ 850/3139]  lr: 1.2500e-05  eta: 0:12:21  time: 0.3244  data_time: 0.0039  memory: 725  loss: 1.2224  loss_cls: 0.2437  loss_bbox: 0.4905  loss_dfl: 0.1902  loss_ld: 0.2979
2023/07/13 12:22:07 - mmengine - INFO - Epoch(train) [12][ 900/3139]  lr: 1.2500e-05  eta: 0:12:05  time: 0.3237  data_time: 0.0044  memory: 737  loss: 1.1405  loss_cls: 0.2252  loss_bbox: 0.4562  loss_dfl: 0.1830  loss_ld: 0.2762
2023/07/13 12:22:23 - mmengine - INFO - Epoch(train) [12][ 950/3139]  lr: 1.2500e-05  eta: 0:11:48  time: 0.3265  data_time: 0.0042  memory: 729  loss: 1.2238  loss_cls: 0.2508  loss_bbox: 0.4770  loss_dfl: 0.1906  loss_ld: 0.3054
2023/07/13 12:22:40 - mmengine - INFO - Epoch(train) [12][1000/3139]  lr: 1.2500e-05  eta: 0:11:32  time: 0.3293  data_time: 0.0068  memory: 730  loss: 1.1691  loss_cls: 0.2491  loss_bbox: 0.4610  loss_dfl: 0.1877  loss_ld: 0.2713
2023/07/13 12:22:56 - mmengine - INFO - Epoch(train) [12][1050/3139]  lr: 1.2500e-05  eta: 0:11:16  time: 0.3220  data_time: 0.0038  memory: 723  loss: 1.1927  loss_cls: 0.2453  loss_bbox: 0.4768  loss_dfl: 0.1924  loss_ld: 0.2782
2023/07/13 12:23:12 - mmengine - INFO - Epoch(train) [12][1100/3139]  lr: 1.2500e-05  eta: 0:11:00  time: 0.3245  data_time: 0.0040  memory: 735  loss: 1.2186  loss_cls: 0.2332  loss_bbox: 0.5000  loss_dfl: 0.1936  loss_ld: 0.2917
2023/07/13 12:23:29 - mmengine - INFO - Epoch(train) [12][1150/3139]  lr: 1.2500e-05  eta: 0:10:44  time: 0.3240  data_time: 0.0041  memory: 723  loss: 1.2151  loss_cls: 0.2457  loss_bbox: 0.4632  loss_dfl: 0.1887  loss_ld: 0.3175
2023/07/13 12:23:45 - mmengine - INFO - Epoch(train) [12][1200/3139]  lr: 1.2500e-05  eta: 0:10:27  time: 0.3248  data_time: 0.0047  memory: 720  loss: 1.1923  loss_cls: 0.2637  loss_bbox: 0.4702  loss_dfl: 0.1887  loss_ld: 0.2697
2023/07/13 12:24:01 - mmengine - INFO - Epoch(train) [12][1250/3139]  lr: 1.2500e-05  eta: 0:10:11  time: 0.3254  data_time: 0.0051  memory: 731  loss: 1.2070  loss_cls: 0.2325  loss_bbox: 0.4787  loss_dfl: 0.1861  loss_ld: 0.3097
2023/07/13 12:24:17 - mmengine - INFO - Epoch(train) [12][1300/3139]  lr: 1.2500e-05  eta: 0:09:55  time: 0.3212  data_time: 0.0046  memory: 717  loss: 1.1637  loss_cls: 0.2503  loss_bbox: 0.4659  loss_dfl: 0.1869  loss_ld: 0.2607
2023/07/13 12:24:34 - mmengine - INFO - Epoch(train) [12][1350/3139]  lr: 1.2500e-05  eta: 0:09:39  time: 0.3296  data_time: 0.0055  memory: 751  loss: 1.1443  loss_cls: 0.2288  loss_bbox: 0.4377  loss_dfl: 0.1848  loss_ld: 0.2929
2023/07/13 12:24:50 - mmengine - INFO - Epoch(train) [12][1400/3139]  lr: 1.2500e-05  eta: 0:09:23  time: 0.3227  data_time: 0.0044  memory: 730  loss: 1.2217  loss_cls: 0.2403  loss_bbox: 0.4977  loss_dfl: 0.1911  loss_ld: 0.2927
2023/07/13 12:25:06 - mmengine - INFO - Epoch(train) [12][1450/3139]  lr: 1.2500e-05  eta: 0:09:06  time: 0.3231  data_time: 0.0049  memory: 716  loss: 1.2251  loss_cls: 0.2563  loss_bbox: 0.4879  loss_dfl: 0.1967  loss_ld: 0.2842
2023/07/13 12:25:13 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:25:22 - mmengine - INFO - Epoch(train) [12][1500/3139]  lr: 1.2500e-05  eta: 0:08:50  time: 0.3213  data_time: 0.0043  memory: 722  loss: 1.1678  loss_cls: 0.2552  loss_bbox: 0.4863  loss_dfl: 0.1895  loss_ld: 0.2368
2023/07/13 12:25:38 - mmengine - INFO - Epoch(train) [12][1550/3139]  lr: 1.2500e-05  eta: 0:08:34  time: 0.3221  data_time: 0.0041  memory: 735  loss: 1.1817  loss_cls: 0.2345  loss_bbox: 0.4659  loss_dfl: 0.1886  loss_ld: 0.2927
2023/07/13 12:25:54 - mmengine - INFO - Epoch(train) [12][1600/3139]  lr: 1.2500e-05  eta: 0:08:18  time: 0.3250  data_time: 0.0048  memory: 718  loss: 1.1470  loss_cls: 0.2468  loss_bbox: 0.4426  loss_dfl: 0.1905  loss_ld: 0.2670
2023/07/13 12:26:11 - mmengine - INFO - Epoch(train) [12][1650/3139]  lr: 1.2500e-05  eta: 0:08:02  time: 0.3258  data_time: 0.0051  memory: 761  loss: 1.1481  loss_cls: 0.2454  loss_bbox: 0.4509  loss_dfl: 0.1848  loss_ld: 0.2670
2023/07/13 12:26:27 - mmengine - INFO - Epoch(train) [12][1700/3139]  lr: 1.2500e-05  eta: 0:07:46  time: 0.3254  data_time: 0.0052  memory: 721  loss: 1.1865  loss_cls: 0.2358  loss_bbox: 0.4594  loss_dfl: 0.1842  loss_ld: 0.3070
2023/07/13 12:26:43 - mmengine - INFO - Epoch(train) [12][1750/3139]  lr: 1.2500e-05  eta: 0:07:29  time: 0.3237  data_time: 0.0038  memory: 717  loss: 1.2031  loss_cls: 0.2439  loss_bbox: 0.4490  loss_dfl: 0.1886  loss_ld: 0.3216
2023/07/13 12:26:59 - mmengine - INFO - Epoch(train) [12][1800/3139]  lr: 1.2500e-05  eta: 0:07:13  time: 0.3234  data_time: 0.0042  memory: 719  loss: 1.1345  loss_cls: 0.2508  loss_bbox: 0.4638  loss_dfl: 0.1836  loss_ld: 0.2362
2023/07/13 12:27:15 - mmengine - INFO - Epoch(train) [12][1850/3139]  lr: 1.2500e-05  eta: 0:06:57  time: 0.3224  data_time: 0.0047  memory: 728  loss: 1.1307  loss_cls: 0.2440  loss_bbox: 0.4368  loss_dfl: 0.1846  loss_ld: 0.2653
2023/07/13 12:27:32 - mmengine - INFO - Epoch(train) [12][1900/3139]  lr: 1.2500e-05  eta: 0:06:41  time: 0.3250  data_time: 0.0046  memory: 728  loss: 1.2123  loss_cls: 0.2338  loss_bbox: 0.4853  loss_dfl: 0.1940  loss_ld: 0.2991
2023/07/13 12:27:48 - mmengine - INFO - Epoch(train) [12][1950/3139]  lr: 1.2500e-05  eta: 0:06:25  time: 0.3304  data_time: 0.0055  memory: 731  loss: 1.2245  loss_cls: 0.2415  loss_bbox: 0.5063  loss_dfl: 0.1933  loss_ld: 0.2833
2023/07/13 12:28:04 - mmengine - INFO - Epoch(train) [12][2000/3139]  lr: 1.2500e-05  eta: 0:06:08  time: 0.3186  data_time: 0.0044  memory: 726  loss: 1.1360  loss_cls: 0.2305  loss_bbox: 0.4318  loss_dfl: 0.1832  loss_ld: 0.2905
2023/07/13 12:28:20 - mmengine - INFO - Epoch(train) [12][2050/3139]  lr: 1.2500e-05  eta: 0:05:52  time: 0.3179  data_time: 0.0042  memory: 719  loss: 1.2056  loss_cls: 0.2445  loss_bbox: 0.4739  loss_dfl: 0.1917  loss_ld: 0.2956
2023/07/13 12:28:36 - mmengine - INFO - Epoch(train) [12][2100/3139]  lr: 1.2500e-05  eta: 0:05:36  time: 0.3232  data_time: 0.0045  memory: 738  loss: 1.1473  loss_cls: 0.2394  loss_bbox: 0.4621  loss_dfl: 0.1838  loss_ld: 0.2620
2023/07/13 12:28:52 - mmengine - INFO - Epoch(train) [12][2150/3139]  lr: 1.2500e-05  eta: 0:05:20  time: 0.3232  data_time: 0.0039  memory: 728  loss: 1.2740  loss_cls: 0.2653  loss_bbox: 0.5257  loss_dfl: 0.2003  loss_ld: 0.2827
2023/07/13 12:29:09 - mmengine - INFO - Epoch(train) [12][2200/3139]  lr: 1.2500e-05  eta: 0:05:04  time: 0.3264  data_time: 0.0049  memory: 721  loss: 1.2042  loss_cls: 0.2441  loss_bbox: 0.4724  loss_dfl: 0.1887  loss_ld: 0.2989
2023/07/13 12:29:25 - mmengine - INFO - Epoch(train) [12][2250/3139]  lr: 1.2500e-05  eta: 0:04:47  time: 0.3279  data_time: 0.0055  memory: 721  loss: 1.1704  loss_cls: 0.2420  loss_bbox: 0.4602  loss_dfl: 0.1886  loss_ld: 0.2797
2023/07/13 12:29:41 - mmengine - INFO - Epoch(train) [12][2300/3139]  lr: 1.2500e-05  eta: 0:04:31  time: 0.3221  data_time: 0.0036  memory: 721  loss: 1.1490  loss_cls: 0.2497  loss_bbox: 0.4474  loss_dfl: 0.1925  loss_ld: 0.2595
2023/07/13 12:29:58 - mmengine - INFO - Epoch(train) [12][2350/3139]  lr: 1.2500e-05  eta: 0:04:15  time: 0.3262  data_time: 0.0044  memory: 739  loss: 1.1888  loss_cls: 0.2471  loss_bbox: 0.4549  loss_dfl: 0.1910  loss_ld: 0.2958
2023/07/13 12:30:14 - mmengine - INFO - Epoch(train) [12][2400/3139]  lr: 1.2500e-05  eta: 0:03:59  time: 0.3265  data_time: 0.0054  memory: 720  loss: 1.1587  loss_cls: 0.2422  loss_bbox: 0.4455  loss_dfl: 0.1905  loss_ld: 0.2804
2023/07/13 12:30:30 - mmengine - INFO - Epoch(train) [12][2450/3139]  lr: 1.2500e-05  eta: 0:03:43  time: 0.3243  data_time: 0.0047  memory: 722  loss: 1.1986  loss_cls: 0.2504  loss_bbox: 0.4841  loss_dfl: 0.1906  loss_ld: 0.2736
2023/07/13 12:30:37 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:30:46 - mmengine - INFO - Epoch(train) [12][2500/3139]  lr: 1.2500e-05  eta: 0:03:26  time: 0.3265  data_time: 0.0047  memory: 737  loss: 1.1908  loss_cls: 0.2368  loss_bbox: 0.4881  loss_dfl: 0.1916  loss_ld: 0.2744
2023/07/13 12:31:03 - mmengine - INFO - Epoch(train) [12][2550/3139]  lr: 1.2500e-05  eta: 0:03:10  time: 0.3277  data_time: 0.0058  memory: 725  loss: 1.1967  loss_cls: 0.2369  loss_bbox: 0.4267  loss_dfl: 0.1824  loss_ld: 0.3507
2023/07/13 12:31:19 - mmengine - INFO - Epoch(train) [12][2600/3139]  lr: 1.2500e-05  eta: 0:02:54  time: 0.3254  data_time: 0.0043  memory: 722  loss: 1.2200  loss_cls: 0.2550  loss_bbox: 0.4887  loss_dfl: 0.1984  loss_ld: 0.2779
2023/07/13 12:31:35 - mmengine - INFO - Epoch(train) [12][2650/3139]  lr: 1.2500e-05  eta: 0:02:38  time: 0.3233  data_time: 0.0040  memory: 718  loss: 1.1096  loss_cls: 0.2333  loss_bbox: 0.4453  loss_dfl: 0.1860  loss_ld: 0.2451
2023/07/13 12:31:52 - mmengine - INFO - Epoch(train) [12][2700/3139]  lr: 1.2500e-05  eta: 0:02:22  time: 0.3262  data_time: 0.0050  memory: 726  loss: 1.1450  loss_cls: 0.2383  loss_bbox: 0.4454  loss_dfl: 0.1886  loss_ld: 0.2728
2023/07/13 12:32:08 - mmengine - INFO - Epoch(train) [12][2750/3139]  lr: 1.2500e-05  eta: 0:02:05  time: 0.3236  data_time: 0.0041  memory: 723  loss: 1.1926  loss_cls: 0.2387  loss_bbox: 0.4584  loss_dfl: 0.1871  loss_ld: 0.3084
2023/07/13 12:32:24 - mmengine - INFO - Epoch(train) [12][2800/3139]  lr: 1.2500e-05  eta: 0:01:49  time: 0.3224  data_time: 0.0036  memory: 728  loss: 1.1488  loss_cls: 0.2320  loss_bbox: 0.4602  loss_dfl: 0.1892  loss_ld: 0.2674
2023/07/13 12:32:40 - mmengine - INFO - Epoch(train) [12][2850/3139]  lr: 1.2500e-05  eta: 0:01:33  time: 0.3180  data_time: 0.0040  memory: 730  loss: 1.1971  loss_cls: 0.2411  loss_bbox: 0.4715  loss_dfl: 0.1903  loss_ld: 0.2942
2023/07/13 12:32:56 - mmengine - INFO - Epoch(train) [12][2900/3139]  lr: 1.2500e-05  eta: 0:01:17  time: 0.3225  data_time: 0.0041  memory: 747  loss: 1.1561  loss_cls: 0.2527  loss_bbox: 0.4643  loss_dfl: 0.1871  loss_ld: 0.2521
2023/07/13 12:33:12 - mmengine - INFO - Epoch(train) [12][2950/3139]  lr: 1.2500e-05  eta: 0:01:01  time: 0.3262  data_time: 0.0055  memory: 724  loss: 1.1136  loss_cls: 0.2540  loss_bbox: 0.4172  loss_dfl: 0.1815  loss_ld: 0.2609
2023/07/13 12:33:29 - mmengine - INFO - Epoch(train) [12][3000/3139]  lr: 1.2500e-05  eta: 0:00:45  time: 0.3237  data_time: 0.0039  memory: 728  loss: 1.2584  loss_cls: 0.2383  loss_bbox: 0.5114  loss_dfl: 0.2004  loss_ld: 0.3083
2023/07/13 12:33:45 - mmengine - INFO - Epoch(train) [12][3050/3139]  lr: 1.2500e-05  eta: 0:00:28  time: 0.3262  data_time: 0.0049  memory: 724  loss: 1.1736  loss_cls: 0.2513  loss_bbox: 0.4469  loss_dfl: 0.1843  loss_ld: 0.2912
2023/07/13 12:34:01 - mmengine - INFO - Epoch(train) [12][3100/3139]  lr: 1.2500e-05  eta: 0:00:12  time: 0.3242  data_time: 0.0047  memory: 724  loss: 1.1423  loss_cls: 0.2349  loss_bbox: 0.4564  loss_dfl: 0.1831  loss_ld: 0.2679
2023/07/13 12:34:13 - mmengine - INFO - Exp name: ld_gfl_r18_r101_fpn_1x_vis_20230713_085933
2023/07/13 12:34:13 - mmengine - INFO - Saving checkpoint at 12 epochs
2023/07/13 12:34:21 - mmengine - INFO - Epoch(val) [12][ 50/548]    eta: 0:00:38  time: 0.0772  data_time: 0.0022  memory: 717  
2023/07/13 12:34:24 - mmengine - INFO - Epoch(val) [12][100/548]    eta: 0:00:33  time: 0.0742  data_time: 0.0013  memory: 497  
2023/07/13 12:34:28 - mmengine - INFO - Epoch(val) [12][150/548]    eta: 0:00:29  time: 0.0739  data_time: 0.0013  memory: 497  
2023/07/13 12:34:32 - mmengine - INFO - Epoch(val) [12][200/548]    eta: 0:00:26  time: 0.0738  data_time: 0.0013  memory: 497  
2023/07/13 12:34:35 - mmengine - INFO - Epoch(val) [12][250/548]    eta: 0:00:22  time: 0.0735  data_time: 0.0013  memory: 497  
2023/07/13 12:34:39 - mmengine - INFO - Epoch(val) [12][300/548]    eta: 0:00:18  time: 0.0738  data_time: 0.0013  memory: 497  
2023/07/13 12:34:43 - mmengine - INFO - Epoch(val) [12][350/548]    eta: 0:00:14  time: 0.0735  data_time: 0.0013  memory: 497  
2023/07/13 12:34:47 - mmengine - INFO - Epoch(val) [12][400/548]    eta: 0:00:10  time: 0.0733  data_time: 0.0013  memory: 497  
2023/07/13 12:34:50 - mmengine - INFO - Epoch(val) [12][450/548]    eta: 0:00:07  time: 0.0739  data_time: 0.0013  memory: 497  
2023/07/13 12:34:54 - mmengine - INFO - Epoch(val) [12][500/548]    eta: 0:00:03  time: 0.0742  data_time: 0.0013  memory: 497  
2023/07/13 12:34:58 - mmengine - INFO - Evaluating bbox...
2023/07/13 12:35:13 - mmengine - INFO - bbox_mAP_copypaste: 0.108 0.180 0.116 0.030 0.153 0.302
2023/07/13 12:35:13 - mmengine - INFO - Epoch(val) [12][548/548]    coco/bbox_mAP: 0.1080  coco/bbox_mAP_50: 0.1800  coco/bbox_mAP_75: 0.1160  coco/bbox_mAP_s: 0.0300  coco/bbox_mAP_m: 0.1530  coco/bbox_mAP_l: 0.3020  data_time: 0.0014  time: 0.0741

@HikariTJU
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I didn't find problems in this log, can you try setting loss_ld=0 in your config and retrain ld_r18-gflv1-r101_fpn_1x, theoritically it should have same accuracy as gfl_r18_fpn_1x

@melika-sce
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melika-sce commented Jul 14, 2023 •
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Thanks for the response, I will give it a try and tell the result
should I set loss_weight=0.0 and let the temperature be 10?

Screenshot 2023-07-14 185935

@HikariTJU
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Yes, loss_weight=0

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@HikariTJU @melika-sce