Open melika-sce opened 1 year ago
HikariTJU
commented
1 year ago 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
commented
1 year ago Oh sorry, I made mistake pasting the name of configs, I finetuned gfl_r18_fpn_1x and gfl_r101_fpn_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, 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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
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
commented
1 year ago 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?
HikariTJU
commented
1 year ago Yes, loss_weight=0
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:
bbox_mAP:
I wonder if you can help me figure which part may cause the problem