diff --git "a/yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957.log" "b/yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957.log" new file mode 100644--- /dev/null +++ "b/yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957.log" @@ -0,0 +1,4617 @@ +2024/03/20 20:50:07 - mmengine - INFO - +------------------------------------------------------------ +System environment: + sys.platform: linux + Python: 3.8.5 (default, Sep 4 2020, 07:30:14) [GCC 7.3.0] + CUDA available: True + numpy_random_seed: 1651571566 + GPU 0,1,2,3,4,5,6,7: NVIDIA A10 + CUDA_HOME: /usr/local/cuda + NVCC: Cuda compilation tools, release 11.3, V11.3.109 + GCC: gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5) + PyTorch: 1.11.0+cu113 + PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.3 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 + - CuDNN 8.2 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + + TorchVision: 0.12.0+cu113 + OpenCV: 4.9.0 + MMEngine: 0.7.2 + +Runtime environment: + cudnn_benchmark: True + mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} + dist_cfg: {'backend': 'nccl'} + seed: None + Distributed launcher: pytorch + Distributed training: True + GPU number: 8 +------------------------------------------------------------ + +2024/03/20 20:50:09 - mmengine - INFO - Config: +default_scope = 'mmyolo' +default_hooks = dict( + timer=dict(type='IterTimerHook'), + logger=dict(type='LoggerHook', interval=50), + param_scheduler=dict( + type='YOLOv5ParamSchedulerHook', + scheduler_type='linear', + lr_factor=0.01, + max_epochs=80), + checkpoint=dict( + type='CheckpointHook', interval=5, save_best=None, max_keep_ckpts=-1), + sampler_seed=dict(type='DistSamplerSeedHook'), + visualization=dict(type='mmdet.DetVisualizationHook')) +env_cfg = dict( + cudnn_benchmark=True, + mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), + dist_cfg=dict(backend='nccl')) +vis_backends = [dict(type='LocalVisBackend')] +visualizer = dict( + type='mmdet.DetLocalVisualizer', + vis_backends=[dict(type='LocalVisBackend')], + name='visualizer') +log_processor = dict(type='LogProcessor', window_size=50, by_epoch=True) +log_level = 'INFO' +load_from = 'pretrained_models/yolo_world_m_clip_t2i_bn_2e-3adamw_32xb16-100e_obj365v1_goldg_train-c6237d5b.pth' +resume = False +backend_args = None +_backend_args = None +tta_model = dict( + type='mmdet.DetTTAModel', + tta_cfg=dict(nms=dict(type='nms', iou_threshold=0.65), max_per_img=300)) +img_scales = [(640, 640), (320, 320), (960, 960)] +_multiscale_resize_transforms = [ + dict( + type='Compose', + transforms=[ + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=False, + pad_val=dict(img=114)) + ]), + dict( + type='Compose', + transforms=[ + dict(type='YOLOv5KeepRatioResize', scale=(320, 320)), + dict( + type='LetterResize', + scale=(320, 320), + allow_scale_up=False, + pad_val=dict(img=114)) + ]), + dict( + type='Compose', + transforms=[ + dict(type='YOLOv5KeepRatioResize', scale=(960, 960)), + dict( + type='LetterResize', + scale=(960, 960), + allow_scale_up=False, + pad_val=dict(img=114)) + ]) +] +tta_pipeline = [ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='TestTimeAug', + transforms=[[{ + 'type': + 'Compose', + 'transforms': [{ + 'type': 'YOLOv5KeepRatioResize', + 'scale': (640, 640) + }, { + 'type': 'LetterResize', + 'scale': (640, 640), + 'allow_scale_up': False, + 'pad_val': { + 'img': 114 + } + }] + }, { + 'type': + 'Compose', + 'transforms': [{ + 'type': 'YOLOv5KeepRatioResize', + 'scale': (320, 320) + }, { + 'type': 'LetterResize', + 'scale': (320, 320), + 'allow_scale_up': False, + 'pad_val': { + 'img': 114 + } + }] + }, { + 'type': + 'Compose', + 'transforms': [{ + 'type': 'YOLOv5KeepRatioResize', + 'scale': (960, 960) + }, { + 'type': 'LetterResize', + 'scale': (960, 960), + 'allow_scale_up': False, + 'pad_val': { + 'img': 114 + } + }] + }], + [{ + 'type': 'mmdet.RandomFlip', + 'prob': 1.0 + }, { + 'type': 'mmdet.RandomFlip', + 'prob': 0.0 + }], [{ + 'type': 'mmdet.LoadAnnotations', + 'with_bbox': True + }], + [{ + 'type': + 'mmdet.PackDetInputs', + 'meta_keys': + ('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'pad_param', 'flip', 'flip_direction') + }]]) +] +data_root = 'data/coco/' +train_ann_file = 'annotations/instances_train2017.json' +train_data_prefix = 'train2017/' +val_ann_file = 'annotations/instances_val2017.json' +val_data_prefix = 'val2017/' +num_classes = 80 +train_batch_size_per_gpu = 16 +train_num_workers = 8 +persistent_workers = False +base_lr = 0.0002 +max_epochs = 80 +close_mosaic_epochs = 10 +model_test_cfg = dict( + multi_label=True, + nms_pre=30000, + score_thr=0.001, + nms=dict(type='nms', iou_threshold=0.7), + max_per_img=300) +img_scale = (640, 640) +dataset_type = 'YOLOv5CocoDataset' +val_batch_size_per_gpu = 1 +val_num_workers = 2 +batch_shapes_cfg = None +deepen_factor = 0.67 +widen_factor = 0.75 +strides = [8, 16, 32] +last_stage_out_channels = 768 +num_det_layers = 3 +norm_cfg = dict(type='BN', momentum=0.03, eps=0.001) +affine_scale = 0.9 +max_aspect_ratio = 100 +tal_topk = 10 +tal_alpha = 0.5 +tal_beta = 6.0 +loss_cls_weight = 0.5 +loss_bbox_weight = 7.5 +loss_dfl_weight = 0.375 +lr_factor = 0.01 +weight_decay = 0.05 +save_epoch_intervals = 5 +val_interval_stage2 = 1 +max_keep_ckpts = 2 +model = dict( + type='YOLOWorldDetector', + data_preprocessor=dict( + type='YOLOWDetDataPreprocessor', + mean=[0.0, 0.0, 0.0], + std=[255.0, 255.0, 255.0], + bgr_to_rgb=True), + backbone=dict( + type='MultiModalYOLOBackbone', + image_model=dict( + type='YOLOv8CSPDarknet', + arch='P5', + last_stage_out_channels=768, + deepen_factor=0.67, + widen_factor=0.75, + norm_cfg=dict(type='BN', momentum=0.03, eps=0.001), + act_cfg=dict(type='SiLU', inplace=True)), + text_model=dict( + type='HuggingCLIPLanguageBackbone', + model_name='../pretrained_models/clip-vit-base-patch32-projection', + frozen_modules=['all'])), + neck=dict( + type='YOLOWorldPAFPN', + deepen_factor=0.67, + widen_factor=0.75, + in_channels=[256, 512, 768], + out_channels=[256, 512, 768], + num_csp_blocks=3, + norm_cfg=dict(type='BN', momentum=0.03, eps=0.001), + act_cfg=dict(type='SiLU', inplace=True), + guide_channels=512, + embed_channels=[128, 256, 384], + num_heads=[4, 8, 12], + block_cfg=dict(type='MaxSigmoidCSPLayerWithTwoConv')), + bbox_head=dict( + type='YOLOWorldHead', + head_module=dict( + type='YOLOWorldHeadModule', + num_classes=80, + in_channels=[256, 512, 768], + widen_factor=0.75, + reg_max=16, + norm_cfg=dict(type='BN', momentum=0.03, eps=0.001), + act_cfg=dict(type='SiLU', inplace=True), + featmap_strides=[8, 16, 32], + use_bn_head=True, + embed_dims=512), + prior_generator=dict( + type='mmdet.MlvlPointGenerator', offset=0.5, strides=[8, 16, 32]), + bbox_coder=dict(type='DistancePointBBoxCoder'), + loss_cls=dict( + type='mmdet.CrossEntropyLoss', + use_sigmoid=True, + reduction='none', + loss_weight=0.5), + loss_bbox=dict( + type='IoULoss', + iou_mode='ciou', + bbox_format='xyxy', + reduction='sum', + loss_weight=7.5, + return_iou=False), + loss_dfl=dict( + type='mmdet.DistributionFocalLoss', + reduction='mean', + loss_weight=0.375)), + train_cfg=dict( + assigner=dict( + type='BatchTaskAlignedAssigner', + num_classes=80, + use_ciou=True, + topk=10, + alpha=0.5, + beta=6.0, + eps=1e-09)), + test_cfg=dict( + multi_label=True, + nms_pre=30000, + score_thr=0.001, + nms=dict(type='nms', iou_threshold=0.7), + max_per_img=300), + mm_neck=True, + num_train_classes=80, + num_test_classes=80) +albu_train_transforms = [ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) +] +pre_transform = [ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', with_bbox=True, with_mask=True, mask2bbox=True) +] +last_transform = [ + dict(type='RemoveDataElement', keys=['gt_masks']), + dict( + type='mmdet.Albu', + transforms=[ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) + ], + bbox_params=dict( + type='BboxParams', + format='pascal_voc', + label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), + keymap=dict(img='image', gt_bboxes='bboxes')), + dict(type='YOLOv5HSVRandomAug'), + dict(type='mmdet.RandomFlip', prob=0.5), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', + 'flip_direction')) +] +train_pipeline = [ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', with_bbox=True, with_mask=True, + mask2bbox=True), + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True), + dict( + type='YOLOv5MultiModalMixUp', + prob=0.1, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True), + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True) + ]), + dict(type='RemoveDataElement', keys=['gt_masks']), + dict( + type='mmdet.Albu', + transforms=[ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) + ], + bbox_params=dict( + type='BboxParams', + format='pascal_voc', + label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), + keymap=dict(img='image', gt_bboxes='bboxes')), + dict(type='YOLOv5HSVRandomAug'), + dict(type='mmdet.RandomFlip', prob=0.5), + dict( + type='RandomLoadText', + num_neg_samples=(80, 80), + max_num_samples=80, + padding_to_max=True, + padding_value=''), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', + 'flip_direction', 'texts')) +] +train_pipeline_stage2 = [ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', with_bbox=True, with_mask=True, + mask2bbox=True), + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=True, + pad_val=dict(img=114.0)), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + max_aspect_ratio=100, + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True), + dict(type='RemoveDataElement', keys=['gt_masks']), + dict( + type='mmdet.Albu', + transforms=[ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) + ], + bbox_params=dict( + type='BboxParams', + format='pascal_voc', + label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), + keymap=dict(img='image', gt_bboxes='bboxes')), + dict(type='YOLOv5HSVRandomAug'), + dict(type='mmdet.RandomFlip', prob=0.5), + dict( + type='RandomLoadText', + num_neg_samples=(80, 80), + max_num_samples=80, + padding_to_max=True, + padding_value=''), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', + 'flip_direction', 'texts')) +] +train_dataloader = dict( + batch_size=16, + num_workers=8, + persistent_workers=False, + pin_memory=True, + sampler=dict(type='DefaultSampler', shuffle=True), + collate_fn=dict(type='yolow_collate'), + dataset=dict( + type='MultiModalDataset', + dataset=dict( + type='YOLOv5CocoDataset', + data_root='data/coco', + ann_file='annotations/instances_train2017.json', + data_prefix=dict(img='train2017/'), + filter_cfg=dict(filter_empty_gt=False, min_size=32)), + class_text_path='data/texts/coco_class_texts.json', + pipeline=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True), + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True), + dict( + type='YOLOv5MultiModalMixUp', + prob=0.1, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True), + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True) + ]), + dict(type='RemoveDataElement', keys=['gt_masks']), + dict( + type='mmdet.Albu', + transforms=[ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) + ], + bbox_params=dict( + type='BboxParams', + format='pascal_voc', + label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), + keymap=dict(img='image', gt_bboxes='bboxes')), + dict(type='YOLOv5HSVRandomAug'), + dict(type='mmdet.RandomFlip', prob=0.5), + dict( + type='RandomLoadText', + num_neg_samples=(80, 80), + max_num_samples=80, + padding_to_max=True, + padding_value=''), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'flip', 'flip_direction', 'texts')) + ])) +test_pipeline = [ + dict(type='LoadImageFromFile', backend_args=None), + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=False, + pad_val=dict(img=114)), + dict(type='LoadAnnotations', with_bbox=True, _scope_='mmdet'), + dict(type='LoadText'), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'pad_param', 'texts')) +] +val_dataloader = dict( + batch_size=1, + num_workers=2, + persistent_workers=True, + pin_memory=True, + drop_last=False, + sampler=dict(type='DefaultSampler', shuffle=False), + dataset=dict( + type='MultiModalDataset', + dataset=dict( + type='YOLOv5CocoDataset', + data_root='data/coco', + ann_file='annotations/instances_val2017.json', + data_prefix=dict(img='val2017/'), + filter_cfg=dict(filter_empty_gt=False, min_size=32)), + class_text_path='data/texts/coco_class_texts.json', + pipeline=[ + dict(type='LoadImageFromFile', backend_args=None), + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=False, + pad_val=dict(img=114)), + dict(type='LoadAnnotations', with_bbox=True, _scope_='mmdet'), + dict(type='LoadText'), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'pad_param', 'texts')) + ])) +test_dataloader = dict( + batch_size=1, + num_workers=2, + persistent_workers=True, + pin_memory=True, + drop_last=False, + sampler=dict(type='DefaultSampler', shuffle=False), + dataset=dict( + type='MultiModalDataset', + dataset=dict( + type='YOLOv5CocoDataset', + data_root='data/coco', + ann_file='annotations/instances_val2017.json', + data_prefix=dict(img='val2017/'), + filter_cfg=dict(filter_empty_gt=False, min_size=32)), + class_text_path='data/texts/coco_class_texts.json', + pipeline=[ + dict(type='LoadImageFromFile', backend_args=None), + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=False, + pad_val=dict(img=114)), + dict(type='LoadAnnotations', with_bbox=True, _scope_='mmdet'), + dict(type='LoadText'), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'pad_param', 'texts')) + ])) +param_scheduler = None +optim_wrapper = dict( + type='AmpOptimWrapper', + clip_grad=dict(max_norm=10.0), + optimizer=dict( + type='AdamW', lr=0.0002, weight_decay=0.05, batch_size_per_gpu=16), + constructor='YOLOWv5OptimizerConstructor', + paramwise_cfg=dict( + bias_decay_mult=0.0, + norm_decay_mult=0.0, + custom_keys=dict({ + 'backbone.text_model': dict(lr_mult=0.01), + 'logit_scale': dict(weight_decay=0.0) + })), + loss_scale='dynamic') +custom_hooks = [ + dict( + type='EMAHook', + ema_type='ExpMomentumEMA', + momentum=0.0001, + update_buffers=True, + strict_load=False, + priority=49), + dict( + type='mmdet.PipelineSwitchHook', + switch_epoch=70, + switch_pipeline=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True), + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=True, + pad_val=dict(img=114.0)), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + max_aspect_ratio=100, + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True), + dict(type='RemoveDataElement', keys=['gt_masks']), + dict( + type='mmdet.Albu', + transforms=[ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) + ], + bbox_params=dict( + type='BboxParams', + format='pascal_voc', + label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), + keymap=dict(img='image', gt_bboxes='bboxes')), + dict(type='YOLOv5HSVRandomAug'), + dict(type='mmdet.RandomFlip', prob=0.5), + dict( + type='RandomLoadText', + num_neg_samples=(80, 80), + max_num_samples=80, + padding_to_max=True, + padding_value=''), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'flip', 'flip_direction', 'texts')) + ]) +] +val_evaluator = dict( + type='mmdet.CocoMetric', + proposal_nums=(100, 1, 10), + ann_file='data/coco/annotations/instances_val2017.json', + metric='bbox') +test_evaluator = dict( + type='mmdet.CocoMetric', + proposal_nums=(100, 1, 10), + ann_file='data/coco/annotations/instances_val2017.json', + metric='bbox') +train_cfg = dict( + type='EpochBasedTrainLoop', + max_epochs=80, + val_interval=5, + dynamic_intervals=[(70, 1)]) +val_cfg = dict(type='ValLoop') +test_cfg = dict(type='TestLoop') +use_mask2refine = True +min_area_ratio = 0.01 +mixup_prob = 0.1 +copypaste_prob = 0.1 +mosaic_affine_transform = [ + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True) +] +custom_imports = dict(imports=['yolo_world'], allow_failed_imports=False) +num_training_classes = 80 +text_channels = 512 +neck_embed_channels = [128, 256, 384] +neck_num_heads = [4, 8, 12] +text_model_name = '../pretrained_models/clip-vit-base-patch32-projection' +text_transform = [ + dict( + type='RandomLoadText', + num_neg_samples=(80, 80), + max_num_samples=80, + padding_to_max=True, + padding_value=''), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', + 'flip_direction', 'texts')) +] +coco_train_dataset = dict( + _delete_=True, + type='MultiModalDataset', + dataset=dict( + type='YOLOv5CocoDataset', + data_root='data/coco', + ann_file='annotations/instances_train2017.json', + data_prefix=dict(img='train2017/'), + filter_cfg=dict(filter_empty_gt=False, min_size=32)), + class_text_path='data/texts/coco_class_texts.json', + pipeline=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True), + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True), + dict( + type='YOLOv5MultiModalMixUp', + prob=0.1, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True), + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict(type='LoadImageFromFile', backend_args=None), + dict( + type='LoadAnnotations', + with_bbox=True, + with_mask=True, + mask2bbox=True) + ]), + dict(type='YOLOv5CopyPaste', prob=0.1), + dict( + type='YOLOv5RandomAffine', + max_rotate_degree=0.0, + max_shear_degree=0.0, + max_aspect_ratio=100.0, + scaling_ratio_range=(0.09999999999999998, 1.9), + border=(-320, -320), + border_val=(114, 114, 114), + min_area_ratio=0.01, + use_mask_refine=True) + ]), + dict(type='RemoveDataElement', keys=['gt_masks']), + dict( + type='mmdet.Albu', + transforms=[ + dict(type='Blur', p=0.01), + dict(type='MedianBlur', p=0.01), + dict(type='ToGray', p=0.01), + dict(type='CLAHE', p=0.01) + ], + bbox_params=dict( + type='BboxParams', + format='pascal_voc', + label_fields=['gt_bboxes_labels', 'gt_ignore_flags']), + keymap=dict(img='image', gt_bboxes='bboxes')), + dict(type='YOLOv5HSVRandomAug'), + dict(type='mmdet.RandomFlip', prob=0.5), + dict( + type='RandomLoadText', + num_neg_samples=(80, 80), + max_num_samples=80, + padding_to_max=True, + padding_value=''), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'flip', + 'flip_direction', 'texts')) + ]) +coco_val_dataset = dict( + _delete_=True, + type='MultiModalDataset', + dataset=dict( + type='YOLOv5CocoDataset', + data_root='data/coco', + ann_file='annotations/instances_val2017.json', + data_prefix=dict(img='val2017/'), + filter_cfg=dict(filter_empty_gt=False, min_size=32)), + class_text_path='data/texts/coco_class_texts.json', + pipeline=[ + dict(type='LoadImageFromFile', backend_args=None), + dict(type='YOLOv5KeepRatioResize', scale=(640, 640)), + dict( + type='LetterResize', + scale=(640, 640), + allow_scale_up=False, + pad_val=dict(img=114)), + dict(type='LoadAnnotations', with_bbox=True, _scope_='mmdet'), + dict(type='LoadText'), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'pad_param', 'texts')) + ]) +launcher = 'pytorch' +work_dir = './work_dirs/yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco' + +2024/03/20 20:50:12 - mmengine - INFO - Using SyncBatchNorm() +2024/03/20 20:50:12 - mmengine - INFO - Hooks will be executed in the following order: +before_run: +(VERY_HIGH ) RuntimeInfoHook +(49 ) EMAHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_load_checkpoint: +(49 ) EMAHook + -------------------- +before_train: +(9 ) YOLOv5ParamSchedulerHook +(VERY_HIGH ) RuntimeInfoHook +(49 ) EMAHook +(NORMAL ) IterTimerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_train_epoch: +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook +(NORMAL ) DistSamplerSeedHook +(NORMAL ) PipelineSwitchHook + -------------------- +before_train_iter: +(9 ) YOLOv5ParamSchedulerHook +(VERY_HIGH ) RuntimeInfoHook +(NORMAL ) IterTimerHook + -------------------- +after_train_iter: +(9 ) YOLOv5ParamSchedulerHook +(VERY_HIGH ) RuntimeInfoHook +(49 ) EMAHook +(NORMAL ) IterTimerHook +(BELOW_NORMAL) LoggerHook +(VERY_LOW ) CheckpointHook + -------------------- +after_train_epoch: +(9 ) YOLOv5ParamSchedulerHook +(NORMAL ) IterTimerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_val_epoch: +(49 ) EMAHook +(NORMAL ) IterTimerHook + -------------------- +before_val_iter: +(NORMAL ) IterTimerHook + -------------------- +after_val_iter: +(NORMAL ) IterTimerHook +(NORMAL ) DetVisualizationHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_val_epoch: +(9 ) YOLOv5ParamSchedulerHook +(VERY_HIGH ) RuntimeInfoHook +(49 ) EMAHook +(NORMAL ) IterTimerHook +(BELOW_NORMAL) LoggerHook +(VERY_LOW ) CheckpointHook + -------------------- +before_save_checkpoint: +(49 ) EMAHook + -------------------- +after_train: +(VERY_LOW ) CheckpointHook + -------------------- +before_test_epoch: +(49 ) EMAHook +(NORMAL ) IterTimerHook + -------------------- +before_test_iter: +(NORMAL ) IterTimerHook + -------------------- +after_test_iter: +(NORMAL ) IterTimerHook +(NORMAL ) DetVisualizationHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_test_epoch: +(VERY_HIGH ) RuntimeInfoHook +(49 ) EMAHook +(NORMAL ) IterTimerHook +(BELOW_NORMAL) LoggerHook + -------------------- +after_run: +(BELOW_NORMAL) LoggerHook + -------------------- +2024/03/20 20:50:43 - mmengine - INFO - Scaled weight_decay to 0.1 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stem.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stem.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- 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- paramwise_options -- backbone.image_model.stage4.1.final_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.final_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.1.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.1.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.1.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.1.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.main_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.main_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.final_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.final_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.1.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.1.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.1.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.1.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.attn_block.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.attn_block.guide_fc.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.main_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.main_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.final_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.final_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.1.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.1.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.1.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.1.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.guide_fc.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.downsample_layers.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.downsample_layers.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.downsample_layers.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.downsample_layers.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.main_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.main_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.final_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.final_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.1.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.1.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.1.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.1.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.guide_fc.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.main_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.main_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.final_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.final_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.1.conv1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.1.conv1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.1.conv2.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.1.conv2.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.guide_fc.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.0.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.0.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.1.bn.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.1.bn.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.logit_scale:lr=0.0002 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.logit_scale:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.norm.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.norm.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.logit_scale:lr=0.0002 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.logit_scale:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.norm.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.norm.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.bias:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.logit_scale:lr=0.0002 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.logit_scale:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.norm.weight:weight_decay=0.0 +2024/03/20 20:50:43 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.norm.bias:weight_decay=0.0 +Name of parameter - Initialization information + +backbone.image_model.stem.conv.weight - torch.Size([48, 3, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stem.bn.weight - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stem.bn.bias - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.0.conv.weight - torch.Size([96, 48, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.0.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.0.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.main_conv.conv.weight - torch.Size([96, 96, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.1.main_conv.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.main_conv.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.final_conv.conv.weight - torch.Size([96, 192, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.1.final_conv.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.final_conv.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.0.conv1.conv.weight - torch.Size([48, 48, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.1.blocks.0.conv1.bn.weight - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.0.conv1.bn.bias - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.0.conv2.conv.weight - torch.Size([48, 48, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.1.blocks.0.conv2.bn.weight - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.0.conv2.bn.bias - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.1.conv1.conv.weight - torch.Size([48, 48, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.1.blocks.1.conv1.bn.weight - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.1.conv1.bn.bias - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.1.conv2.conv.weight - torch.Size([48, 48, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage1.1.blocks.1.conv2.bn.weight - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage1.1.blocks.1.conv2.bn.bias - torch.Size([48]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.0.conv.weight - torch.Size([192, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.0.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.0.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.main_conv.conv.weight - torch.Size([192, 192, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.main_conv.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.main_conv.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.final_conv.conv.weight - torch.Size([192, 576, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.final_conv.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.final_conv.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.0.conv1.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.0.conv1.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.0.conv1.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.0.conv2.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.0.conv2.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.0.conv2.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.1.conv1.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.1.conv1.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.1.conv1.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.1.conv2.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.1.conv2.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.1.conv2.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.2.conv1.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.2.conv1.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.2.conv1.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.2.conv2.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.2.conv2.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.2.conv2.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.3.conv1.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.3.conv1.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.3.conv1.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.3.conv2.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage2.1.blocks.3.conv2.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage2.1.blocks.3.conv2.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.0.conv.weight - torch.Size([384, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.0.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.0.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.main_conv.conv.weight - torch.Size([384, 384, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.main_conv.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.main_conv.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.final_conv.conv.weight - torch.Size([384, 1152, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.final_conv.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.final_conv.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.0.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.0.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.0.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.0.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.0.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.0.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.1.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.1.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.1.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.1.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.1.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.1.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.2.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.2.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.2.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.2.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.2.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.2.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.3.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.3.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.3.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.3.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage3.1.blocks.3.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage3.1.blocks.3.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.0.conv.weight - torch.Size([576, 384, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.0.bn.weight - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.0.bn.bias - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.main_conv.conv.weight - torch.Size([576, 576, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.1.main_conv.bn.weight - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.main_conv.bn.bias - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.final_conv.conv.weight - torch.Size([576, 1152, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.1.final_conv.bn.weight - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.final_conv.bn.bias - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.0.conv1.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.1.blocks.0.conv1.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.0.conv1.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.0.conv2.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.1.blocks.0.conv2.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.0.conv2.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.1.conv1.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.1.blocks.1.conv1.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.1.conv1.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.1.conv2.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.1.blocks.1.conv2.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.1.blocks.1.conv2.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.2.conv1.conv.weight - torch.Size([288, 576, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.2.conv1.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.2.conv1.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.2.conv2.conv.weight - torch.Size([576, 1152, 1, 1]): +Initialized by user-defined `init_weights` in YOLOv8CSPDarknet + +backbone.image_model.stage4.2.conv2.bn.weight - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.image_model.stage4.2.conv2.bn.bias - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.embeddings.token_embedding.weight - torch.Size([49408, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.embeddings.position_embedding.weight - torch.Size([77, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.0.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.1.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.2.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.3.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.4.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.5.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.6.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.7.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.8.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.9.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.10.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.k_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.k_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.v_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.v_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.q_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.q_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.out_proj.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.self_attn.out_proj.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.layer_norm1.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.layer_norm1.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.mlp.fc1.weight - torch.Size([2048, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.mlp.fc1.bias - torch.Size([2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.mlp.fc2.weight - torch.Size([512, 2048]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.mlp.fc2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.layer_norm2.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.encoder.layers.11.layer_norm2.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.final_layer_norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_model.final_layer_norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +backbone.text_model.model.text_projection.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.main_conv.conv.weight - torch.Size([384, 960, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.main_conv.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.main_conv.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.final_conv.conv.weight - torch.Size([384, 960, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.final_conv.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.final_conv.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.0.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.blocks.0.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.0.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.0.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.blocks.0.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.0.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.1.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.blocks.1.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.1.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.1.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.blocks.1.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.blocks.1.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.attn_block.bias - torch.Size([6]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.attn_block.guide_fc.weight - torch.Size([192, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.attn_block.guide_fc.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.attn_block.project_conv.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.0.attn_block.project_conv.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.0.attn_block.project_conv.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.main_conv.conv.weight - torch.Size([192, 576, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.main_conv.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.main_conv.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.final_conv.conv.weight - torch.Size([192, 480, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.final_conv.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.final_conv.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.0.conv1.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.blocks.0.conv1.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.0.conv1.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.0.conv2.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.blocks.0.conv2.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.0.conv2.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.1.conv1.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.blocks.1.conv1.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.1.conv1.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.1.conv2.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.blocks.1.conv2.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.blocks.1.conv2.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.attn_block.bias - torch.Size([3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.attn_block.guide_fc.weight - torch.Size([96, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.attn_block.guide_fc.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.attn_block.project_conv.conv.weight - torch.Size([96, 96, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.top_down_layers.1.attn_block.project_conv.bn.weight - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.top_down_layers.1.attn_block.project_conv.bn.bias - torch.Size([96]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.downsample_layers.0.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.downsample_layers.0.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.downsample_layers.0.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.downsample_layers.1.conv.weight - torch.Size([384, 384, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.downsample_layers.1.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.downsample_layers.1.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.main_conv.conv.weight - torch.Size([384, 576, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.main_conv.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.main_conv.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.final_conv.conv.weight - torch.Size([384, 960, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.final_conv.bn.weight - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.final_conv.bn.bias - torch.Size([384]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.0.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.blocks.0.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.0.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.0.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.blocks.0.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.0.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.1.conv1.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.blocks.1.conv1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.1.conv1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.1.conv2.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.blocks.1.conv2.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.blocks.1.conv2.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.attn_block.bias - torch.Size([6]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.attn_block.guide_fc.weight - torch.Size([192, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.attn_block.guide_fc.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.attn_block.project_conv.conv.weight - torch.Size([192, 192, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.0.attn_block.project_conv.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.0.attn_block.project_conv.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.main_conv.conv.weight - torch.Size([576, 960, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.main_conv.bn.weight - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.main_conv.bn.bias - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.final_conv.conv.weight - torch.Size([576, 1440, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.final_conv.bn.weight - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.final_conv.bn.bias - torch.Size([576]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.0.conv1.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.blocks.0.conv1.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.0.conv1.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.0.conv2.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.blocks.0.conv2.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.0.conv2.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.1.conv1.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.blocks.1.conv1.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.1.conv1.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.1.conv2.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.blocks.1.conv2.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.blocks.1.conv2.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.attn_block.bias - torch.Size([9]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.attn_block.guide_fc.weight - torch.Size([288, 512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.attn_block.guide_fc.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.attn_block.project_conv.conv.weight - torch.Size([288, 288, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWorldPAFPN + +neck.bottom_up_layers.1.attn_block.project_conv.bn.weight - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +neck.bottom_up_layers.1.attn_block.project_conv.bn.bias - torch.Size([288]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.0.conv.weight - torch.Size([192, 192, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.0.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.0.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.1.conv.weight - torch.Size([192, 192, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.2.weight - torch.Size([512, 192, 1, 1]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.0.2.bias - torch.Size([512]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.cls_preds.1.0.conv.weight - torch.Size([192, 384, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.0.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.0.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.1.conv.weight - torch.Size([192, 192, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.2.weight - torch.Size([512, 192, 1, 1]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.1.2.bias - torch.Size([512]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.cls_preds.2.0.conv.weight - torch.Size([192, 576, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.0.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.0.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.1.conv.weight - torch.Size([192, 192, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.1.bn.weight - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.1.bn.bias - torch.Size([192]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.2.weight - torch.Size([512, 192, 1, 1]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_preds.2.2.bias - torch.Size([512]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.reg_preds.0.0.conv.weight - torch.Size([64, 192, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.0.bn.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.0.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.1.conv.weight - torch.Size([64, 64, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.1.bn.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.1.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.2.weight - torch.Size([64, 64, 1, 1]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.0.2.bias - torch.Size([64]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.reg_preds.1.0.conv.weight - torch.Size([64, 384, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.0.bn.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.0.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.1.conv.weight - torch.Size([64, 64, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.1.bn.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.1.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.2.weight - torch.Size([64, 64, 1, 1]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.1.2.bias - torch.Size([64]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.reg_preds.2.0.conv.weight - torch.Size([64, 576, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.0.bn.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.0.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.1.conv.weight - torch.Size([64, 64, 3, 3]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.1.bn.weight - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.1.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.2.weight - torch.Size([64, 64, 1, 1]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.reg_preds.2.2.bias - torch.Size([64]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.cls_contrasts.0.bias - torch.Size([]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.cls_contrasts.0.logit_scale - torch.Size([]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.0.norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.0.norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.1.bias - torch.Size([]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.cls_contrasts.1.logit_scale - torch.Size([]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.1.norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.1.norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.2.bias - torch.Size([]): +Initialized by user-defined `init_weights` in YOLOWorldHeadModule + +bbox_head.head_module.cls_contrasts.2.logit_scale - torch.Size([]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.2.norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector + +bbox_head.head_module.cls_contrasts.2.norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWorldDetector +2024/03/20 20:50:54 - mmengine - INFO - Load checkpoint from pretrained_models/yolo_world_m_clip_t2i_bn_2e-3adamw_32xb16-100e_obj365v1_goldg_train-c6237d5b.pth +2024/03/20 20:50:54 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io +2024/03/20 20:50:54 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. +2024/03/20 20:50:54 - mmengine - INFO - Checkpoints will be saved to /group/40034/adriancheng/YOLOWorld_Master/work_dirs/yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco. +2024/03/20 20:51:35 - mmengine - INFO - Epoch(train) [1][ 50/925] lr: 3.5315e-06 eta: 16:45:32 time: 0.8159 data_time: 0.1875 memory: 18805 grad_norm: nan loss: 501.8702 loss_cls: 199.8475 loss_bbox: 146.6303 loss_dfl: 155.3924 +2024/03/20 20:51:56 - mmengine - INFO - Epoch(train) [1][100/925] lr: 7.1351e-06 eta: 12:51:00 time: 0.4361 data_time: 0.0046 memory: 7936 grad_norm: 800.6302 loss: 475.8790 loss_cls: 182.2178 loss_bbox: 140.9971 loss_dfl: 152.6641 +2024/03/20 20:52:18 - mmengine - INFO - Epoch(train) [1][150/925] lr: 1.0739e-05 eta: 11:31:42 time: 0.4340 data_time: 0.0042 memory: 7789 grad_norm: 844.2977 loss: 450.1228 loss_cls: 167.9453 loss_bbox: 134.3896 loss_dfl: 147.7879 +2024/03/20 20:52:40 - mmengine - INFO - Epoch(train) [1][200/925] lr: 1.4342e-05 eta: 10:50:03 time: 0.4281 data_time: 0.0043 memory: 7789 grad_norm: 784.5267 loss: 445.6619 loss_cls: 165.3284 loss_bbox: 132.7871 loss_dfl: 147.5465 +2024/03/20 20:53:02 - mmengine - INFO - Epoch(train) [1][250/925] lr: 1.7946e-05 eta: 10:27:39 time: 0.4392 data_time: 0.0042 memory: 8109 grad_norm: 773.3413 loss: 441.7382 loss_cls: 164.5073 loss_bbox: 131.6748 loss_dfl: 145.5562 +2024/03/20 20:53:23 - mmengine - INFO - Epoch(train) [1][300/925] lr: 2.1550e-05 eta: 10:12:18 time: 0.4377 data_time: 0.0040 memory: 8029 grad_norm: 787.8988 loss: 437.3898 loss_cls: 161.4965 loss_bbox: 131.0148 loss_dfl: 144.8785 +2024/03/20 20:53:45 - mmengine - INFO - Epoch(train) [1][350/925] lr: 2.5153e-05 eta: 9:59:50 time: 0.4297 data_time: 0.0039 memory: 8043 grad_norm: 829.7043 loss: 434.3308 loss_cls: 159.3923 loss_bbox: 130.5002 loss_dfl: 144.4383 +2024/03/20 20:54:07 - mmengine - INFO - Epoch(train) [1][400/925] lr: 2.8757e-05 eta: 9:51:19 time: 0.4358 data_time: 0.0040 memory: 7829 grad_norm: 787.8407 loss: 427.6263 loss_cls: 155.2541 loss_bbox: 129.0642 loss_dfl: 143.3080 +2024/03/20 20:54:28 - mmengine - INFO - Epoch(train) [1][450/925] lr: 3.2360e-05 eta: 9:43:45 time: 0.4294 data_time: 0.0041 memory: 8029 grad_norm: 826.6081 loss: 429.7007 loss_cls: 159.3264 loss_bbox: 127.1861 loss_dfl: 143.1882 +2024/03/20 20:54:50 - mmengine - INFO - Epoch(train) [1][500/925] lr: 3.5964e-05 eta: 9:38:55 time: 0.4400 data_time: 0.0039 memory: 8096 grad_norm: 791.6157 loss: 430.0222 loss_cls: 155.8496 loss_bbox: 130.2243 loss_dfl: 143.9483 +2024/03/20 20:55:12 - mmengine - INFO - Epoch(train) [1][550/925] lr: 3.9568e-05 eta: 9:34:26 time: 0.4359 data_time: 0.0039 memory: 7763 grad_norm: 824.2323 loss: 419.1735 loss_cls: 152.4890 loss_bbox: 125.0960 loss_dfl: 141.5884 +2024/03/20 20:55:33 - mmengine - INFO - Epoch(train) [1][600/925] lr: 4.3171e-05 eta: 9:29:49 time: 0.4277 data_time: 0.0037 memory: 8189 grad_norm: 781.7336 loss: 423.0241 loss_cls: 151.7623 loss_bbox: 127.8511 loss_dfl: 143.4108 +2024/03/20 20:55:56 - mmengine - INFO - Epoch(train) [1][650/925] lr: 4.6775e-05 eta: 9:27:15 time: 0.4427 data_time: 0.0039 memory: 7909 grad_norm: 794.9721 loss: 415.8966 loss_cls: 149.0016 loss_bbox: 125.3278 loss_dfl: 141.5673 +2024/03/20 20:56:18 - mmengine - INFO - Epoch(train) [1][700/925] lr: 5.0378e-05 eta: 9:25:31 time: 0.4487 data_time: 0.0039 memory: 8229 grad_norm: 807.9727 loss: 422.8439 loss_cls: 153.9013 loss_bbox: 126.8150 loss_dfl: 142.1276 +2024/03/20 20:56:39 - mmengine - INFO - Epoch(train) [1][750/925] lr: 5.3982e-05 eta: 9:22:13 time: 0.4270 data_time: 0.0039 memory: 7829 grad_norm: 866.4852 loss: 423.7261 loss_cls: 153.2649 loss_bbox: 128.2897 loss_dfl: 142.1715 +2024/03/20 20:57:02 - mmengine - INFO - Epoch(train) [1][800/925] lr: 5.7586e-05 eta: 9:20:30 time: 0.4430 data_time: 0.0038 memory: 7976 grad_norm: 849.2955 loss: 421.4757 loss_cls: 152.0709 loss_bbox: 127.6114 loss_dfl: 141.7934 +2024/03/20 20:57:24 - mmengine - INFO - Epoch(train) [1][850/925] lr: 6.1189e-05 eta: 9:19:42 time: 0.4537 data_time: 0.0041 memory: 8083 grad_norm: 792.8765 loss: 425.3207 loss_cls: 153.8830 loss_bbox: 127.6345 loss_dfl: 143.8032 +2024/03/20 20:57:46 - mmengine - INFO - Epoch(train) [1][900/925] lr: 6.4793e-05 eta: 9:17:14 time: 0.4282 data_time: 0.0040 memory: 7816 grad_norm: 843.4263 loss: 417.4351 loss_cls: 148.9669 loss_bbox: 127.9353 loss_dfl: 140.5329 +2024/03/20 20:58:07 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 20:58:32 - mmengine - INFO - Epoch(train) [2][ 50/925] lr: 6.9329e-05 eta: 9:31:41 time: 0.5023 data_time: 0.0532 memory: 15769 grad_norm: 829.4115 loss: 420.3978 loss_cls: 149.6454 loss_bbox: 127.0770 loss_dfl: 143.6754 +2024/03/20 20:58:43 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 20:58:54 - mmengine - INFO - Epoch(train) [2][100/925] lr: 7.2889e-05 eta: 9:29:05 time: 0.4324 data_time: 0.0039 memory: 7813 grad_norm: 835.3708 loss: 430.2554 loss_cls: 157.2712 loss_bbox: 128.3865 loss_dfl: 144.5977 +2024/03/20 20:59:16 - mmengine - INFO - Epoch(train) [2][150/925] lr: 7.6448e-05 eta: 9:27:19 time: 0.4435 data_time: 0.0039 memory: 8253 grad_norm: 887.4663 loss: 423.7614 loss_cls: 155.1471 loss_bbox: 126.0309 loss_dfl: 142.5833 +2024/03/20 20:59:39 - mmengine - INFO - Epoch(train) [2][200/925] lr: 8.0007e-05 eta: 9:25:56 time: 0.4485 data_time: 0.0038 memory: 7760 grad_norm: 888.5566 loss: 419.8062 loss_cls: 153.2863 loss_bbox: 124.8777 loss_dfl: 141.6422 +2024/03/20 21:00:00 - mmengine - INFO - Epoch(train) [2][250/925] lr: 8.3566e-05 eta: 9:23:57 time: 0.4349 data_time: 0.0038 memory: 8373 grad_norm: 877.6843 loss: 421.1259 loss_cls: 151.2033 loss_bbox: 127.6998 loss_dfl: 142.2229 +2024/03/20 21:00:23 - mmengine - INFO - Epoch(train) [2][300/925] lr: 8.7125e-05 eta: 9:22:31 time: 0.4436 data_time: 0.0041 memory: 7893 grad_norm: 840.2642 loss: 423.3397 loss_cls: 153.5152 loss_bbox: 127.4573 loss_dfl: 142.3672 +2024/03/20 21:00:45 - mmengine - INFO - Epoch(train) [2][350/925] lr: 9.0684e-05 eta: 9:21:13 time: 0.4445 data_time: 0.0040 memory: 7813 grad_norm: 875.2494 loss: 430.9691 loss_cls: 158.0489 loss_bbox: 128.6658 loss_dfl: 144.2544 +2024/03/20 21:01:07 - mmengine - INFO - Epoch(train) [2][400/925] lr: 9.4243e-05 eta: 9:19:51 time: 0.4417 data_time: 0.0039 memory: 7933 grad_norm: 849.4007 loss: 424.7913 loss_cls: 153.6197 loss_bbox: 128.6402 loss_dfl: 142.5314 +2024/03/20 21:01:29 - mmengine - INFO - Epoch(train) [2][450/925] lr: 9.7802e-05 eta: 9:18:35 time: 0.4422 data_time: 0.0040 memory: 7866 grad_norm: 815.0299 loss: 419.5680 loss_cls: 149.7066 loss_bbox: 127.7435 loss_dfl: 142.1179 +2024/03/20 21:01:51 - mmengine - INFO - Epoch(train) [2][500/925] lr: 1.0136e-04 eta: 9:17:05 time: 0.4352 data_time: 0.0040 memory: 7960 grad_norm: 884.7623 loss: 427.9139 loss_cls: 153.7572 loss_bbox: 130.0996 loss_dfl: 144.0571 +2024/03/20 21:02:13 - mmengine - INFO - Epoch(train) [2][550/925] lr: 1.0492e-04 eta: 9:16:15 time: 0.4496 data_time: 0.0040 memory: 8053 grad_norm: 884.6676 loss: 421.9289 loss_cls: 153.2178 loss_bbox: 126.8675 loss_dfl: 141.8436 +2024/03/20 21:02:35 - mmengine - INFO - Epoch(train) [2][600/925] lr: 1.0848e-04 eta: 9:15:15 time: 0.4444 data_time: 0.0040 memory: 8053 grad_norm: 893.0868 loss: 423.5972 loss_cls: 152.9189 loss_bbox: 128.4352 loss_dfl: 142.2431 +2024/03/20 21:02:57 - mmengine - INFO - Epoch(train) [2][650/925] lr: 1.1204e-04 eta: 9:13:52 time: 0.4337 data_time: 0.0038 memory: 7853 grad_norm: 841.9185 loss: 420.1507 loss_cls: 152.8053 loss_bbox: 125.5069 loss_dfl: 141.8386 +2024/03/20 21:03:20 - mmengine - INFO - Epoch(train) [2][700/925] lr: 1.1560e-04 eta: 9:13:07 time: 0.4490 data_time: 0.0037 memory: 8013 grad_norm: 899.1198 loss: 425.1643 loss_cls: 154.1670 loss_bbox: 128.6471 loss_dfl: 142.3502 +2024/03/20 21:03:42 - mmengine - INFO - Epoch(train) [2][750/925] lr: 1.1916e-04 eta: 9:12:16 time: 0.4455 data_time: 0.0039 memory: 7746 grad_norm: inf loss: 420.5562 loss_cls: 151.8858 loss_bbox: 126.8379 loss_dfl: 141.8325 +2024/03/20 21:04:04 - mmengine - INFO - Epoch(train) [2][800/925] lr: 1.2271e-04 eta: 9:11:07 time: 0.4365 data_time: 0.0040 memory: 7960 grad_norm: 838.7506 loss: 428.0564 loss_cls: 155.5094 loss_bbox: 128.9405 loss_dfl: 143.6065 +2024/03/20 21:04:27 - mmengine - INFO - Epoch(train) [2][850/925] lr: 1.2627e-04 eta: 9:11:01 time: 0.4654 data_time: 0.0040 memory: 7813 grad_norm: 822.5347 loss: 422.3654 loss_cls: 152.9748 loss_bbox: 127.2609 loss_dfl: 142.1297 +2024/03/20 21:04:50 - mmengine - INFO - Epoch(train) [2][900/925] lr: 1.2983e-04 eta: 9:10:35 time: 0.4566 data_time: 0.0039 memory: 7946 grad_norm: 878.2579 loss: 426.9843 loss_cls: 153.6825 loss_bbox: 129.5392 loss_dfl: 143.7625 +2024/03/20 21:05:00 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:05:29 - mmengine - INFO - Epoch(train) [3][ 50/925] lr: 1.3348e-04 eta: 9:12:32 time: 0.5641 data_time: 0.0932 memory: 8013 grad_norm: 884.3041 loss: 423.8375 loss_cls: 152.0835 loss_bbox: 128.6085 loss_dfl: 143.1454 +2024/03/20 21:05:53 - mmengine - INFO - Epoch(train) [3][100/925] lr: 1.3699e-04 eta: 9:12:50 time: 0.4821 data_time: 0.0039 memory: 7720 grad_norm: 906.1211 loss: 418.5885 loss_cls: 151.2133 loss_bbox: 125.0194 loss_dfl: 142.3558 +2024/03/20 21:06:15 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:06:15 - mmengine - INFO - Epoch(train) [3][150/925] lr: 1.4051e-04 eta: 9:12:02 time: 0.4463 data_time: 0.0040 memory: 7986 grad_norm: 821.7829 loss: 427.2925 loss_cls: 156.7472 loss_bbox: 127.8345 loss_dfl: 142.7108 +2024/03/20 21:06:39 - mmengine - INFO - Epoch(train) [3][200/925] lr: 1.4402e-04 eta: 9:11:58 time: 0.4707 data_time: 0.0040 memory: 7840 grad_norm: 914.6975 loss: 430.8954 loss_cls: 156.6820 loss_bbox: 130.0918 loss_dfl: 144.1215 +2024/03/20 21:07:02 - mmengine - INFO - Epoch(train) [3][250/925] lr: 1.4754e-04 eta: 9:11:58 time: 0.4738 data_time: 0.0040 memory: 7826 grad_norm: 825.2209 loss: 420.2259 loss_cls: 151.7370 loss_bbox: 126.8894 loss_dfl: 141.5994 +2024/03/20 21:07:25 - mmengine - INFO - Epoch(train) [3][300/925] lr: 1.5105e-04 eta: 9:11:31 time: 0.4586 data_time: 0.0041 memory: 7786 grad_norm: 965.3357 loss: 422.9386 loss_cls: 151.4740 loss_bbox: 128.7843 loss_dfl: 142.6803 +2024/03/20 21:07:49 - mmengine - INFO - Epoch(train) [3][350/925] lr: 1.5456e-04 eta: 9:11:25 time: 0.4709 data_time: 0.0041 memory: 8173 grad_norm: 897.3738 loss: 425.9043 loss_cls: 152.8261 loss_bbox: 130.5157 loss_dfl: 142.5625 +2024/03/20 21:08:12 - mmengine - INFO - Epoch(train) [3][400/925] lr: 1.5808e-04 eta: 9:10:59 time: 0.4587 data_time: 0.0038 memory: 7826 grad_norm: 967.4504 loss: 427.9357 loss_cls: 154.1621 loss_bbox: 130.7468 loss_dfl: 143.0268 +2024/03/20 21:08:35 - mmengine - INFO - Epoch(train) [3][450/925] lr: 1.6159e-04 eta: 9:10:55 time: 0.4733 data_time: 0.0039 memory: 7920 grad_norm: 909.2179 loss: 432.3152 loss_cls: 156.4145 loss_bbox: 131.0488 loss_dfl: 144.8518 +2024/03/20 21:08:59 - mmengine - INFO - Epoch(train) [3][500/925] lr: 1.6511e-04 eta: 9:10:48 time: 0.4712 data_time: 0.0039 memory: 7893 grad_norm: 948.2758 loss: 437.6301 loss_cls: 159.6070 loss_bbox: 132.1746 loss_dfl: 145.8484 +2024/03/20 21:09:22 - mmengine - INFO - Epoch(train) [3][550/925] lr: 1.6862e-04 eta: 9:10:09 time: 0.4510 data_time: 0.0041 memory: 7986 grad_norm: 879.1452 loss: 430.4038 loss_cls: 156.5525 loss_bbox: 130.1862 loss_dfl: 143.6652 +2024/03/20 21:09:45 - mmengine - INFO - Epoch(train) [3][600/925] lr: 1.7214e-04 eta: 9:10:13 time: 0.4793 data_time: 0.0040 memory: 8160 grad_norm: 845.4908 loss: 434.9024 loss_cls: 158.6454 loss_bbox: 131.7509 loss_dfl: 144.5061 +2024/03/20 21:10:09 - mmengine - INFO - Epoch(train) [3][650/925] lr: 1.7565e-04 eta: 9:10:09 time: 0.4746 data_time: 0.0040 memory: 7986 grad_norm: 914.0511 loss: 434.0599 loss_cls: 158.9591 loss_bbox: 132.0635 loss_dfl: 143.0373 +2024/03/20 21:10:32 - mmengine - INFO - Epoch(train) [3][700/925] lr: 1.7916e-04 eta: 9:09:30 time: 0.4504 data_time: 0.0041 memory: 7840 grad_norm: 981.2858 loss: 434.6246 loss_cls: 159.8537 loss_bbox: 129.7649 loss_dfl: 145.0060 +2024/03/20 21:10:56 - mmengine - INFO - Epoch(train) [3][750/925] lr: 1.8268e-04 eta: 9:09:32 time: 0.4801 data_time: 0.0041 memory: 8080 grad_norm: 967.9867 loss: 434.8432 loss_cls: 159.4902 loss_bbox: 130.8056 loss_dfl: 144.5473 +2024/03/20 21:11:19 - mmengine - INFO - Epoch(train) [3][800/925] lr: 1.8619e-04 eta: 9:09:18 time: 0.4685 data_time: 0.0040 memory: 8213 grad_norm: 914.7772 loss: 438.1215 loss_cls: 159.2787 loss_bbox: 134.2483 loss_dfl: 144.5944 +2024/03/20 21:11:42 - mmengine - INFO - Epoch(train) [3][850/925] lr: 1.8971e-04 eta: 9:08:50 time: 0.4576 data_time: 0.0065 memory: 8080 grad_norm: 1031.1413 loss: 429.5674 loss_cls: 155.6101 loss_bbox: 130.1235 loss_dfl: 143.8337 +2024/03/20 21:12:06 - mmengine - INFO - Epoch(train) [3][900/925] lr: 1.9322e-04 eta: 9:08:47 time: 0.4777 data_time: 0.0040 memory: 8253 grad_norm: 911.7123 loss: 430.7632 loss_cls: 156.1570 loss_bbox: 131.5912 loss_dfl: 143.0150 +2024/03/20 21:12:17 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:12:43 - mmengine - INFO - Epoch(train) [4][ 50/925] lr: 1.9258e-04 eta: 9:09:08 time: 0.5147 data_time: 0.0608 memory: 8213 grad_norm: 959.8098 loss: 434.6615 loss_cls: 155.9942 loss_bbox: 133.4571 loss_dfl: 145.2102 +2024/03/20 21:13:07 - mmengine - INFO - Epoch(train) [4][100/925] lr: 1.9258e-04 eta: 9:09:01 time: 0.4754 data_time: 0.0020 memory: 7986 grad_norm: 902.6697 loss: 435.7271 loss_cls: 162.7448 loss_bbox: 128.8433 loss_dfl: 144.1389 +2024/03/20 21:13:30 - mmengine - INFO - Epoch(train) [4][150/925] lr: 1.9258e-04 eta: 9:08:38 time: 0.4638 data_time: 0.0020 memory: 8013 grad_norm: 831.7972 loss: 437.5135 loss_cls: 159.5862 loss_bbox: 132.7697 loss_dfl: 145.1577 +2024/03/20 21:13:53 - mmengine - INFO - Epoch(train) [4][200/925] lr: 1.9258e-04 eta: 9:08:08 time: 0.4577 data_time: 0.0021 memory: 8000 grad_norm: 893.6875 loss: 439.2047 loss_cls: 162.5741 loss_bbox: 131.5529 loss_dfl: 145.0777 +2024/03/20 21:14:05 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:14:17 - mmengine - INFO - Epoch(train) [4][250/925] lr: 1.9258e-04 eta: 9:08:04 time: 0.4793 data_time: 0.0019 memory: 8066 grad_norm: 902.8568 loss: 434.3407 loss_cls: 157.7164 loss_bbox: 132.2393 loss_dfl: 144.3850 +2024/03/20 21:14:40 - mmengine - INFO - Epoch(train) [4][300/925] lr: 1.9258e-04 eta: 9:07:32 time: 0.4556 data_time: 0.0020 memory: 7840 grad_norm: 831.1708 loss: 441.0195 loss_cls: 160.1189 loss_bbox: 134.8353 loss_dfl: 146.0654 +2024/03/20 21:15:03 - mmengine - INFO - Epoch(train) [4][350/925] lr: 1.9258e-04 eta: 9:07:11 time: 0.4645 data_time: 0.0019 memory: 8080 grad_norm: 913.1645 loss: 440.4986 loss_cls: 161.6389 loss_bbox: 133.2920 loss_dfl: 145.5677 +2024/03/20 21:15:27 - mmengine - INFO - Epoch(train) [4][400/925] lr: 1.9258e-04 eta: 9:07:07 time: 0.4808 data_time: 0.0020 memory: 8053 grad_norm: 838.3191 loss: 438.5773 loss_cls: 160.7883 loss_bbox: 132.8874 loss_dfl: 144.9015 +2024/03/20 21:15:50 - mmengine - INFO - Epoch(train) [4][450/925] lr: 1.9258e-04 eta: 9:06:28 time: 0.4493 data_time: 0.0019 memory: 7853 grad_norm: 969.2389 loss: 435.5603 loss_cls: 158.1931 loss_bbox: 131.9907 loss_dfl: 145.3765 +2024/03/20 21:16:13 - mmengine - INFO - Epoch(train) [4][500/925] lr: 1.9258e-04 eta: 9:06:16 time: 0.4732 data_time: 0.0020 memory: 7946 grad_norm: 820.5611 loss: 439.8263 loss_cls: 161.3514 loss_bbox: 133.2730 loss_dfl: 145.2019 +2024/03/20 21:16:37 - mmengine - INFO - Epoch(train) [4][550/925] lr: 1.9258e-04 eta: 9:06:07 time: 0.4768 data_time: 0.0018 memory: 7920 grad_norm: 936.2350 loss: 430.7879 loss_cls: 156.8049 loss_bbox: 129.8278 loss_dfl: 144.1552 +2024/03/20 21:17:00 - mmengine - INFO - Epoch(train) [4][600/925] lr: 1.9258e-04 eta: 9:05:35 time: 0.4550 data_time: 0.0020 memory: 7826 grad_norm: 825.8501 loss: 427.1405 loss_cls: 153.0418 loss_bbox: 130.3490 loss_dfl: 143.7497 +2024/03/20 21:17:24 - mmengine - INFO - Epoch(train) [4][650/925] lr: 1.9258e-04 eta: 9:05:33 time: 0.4844 data_time: 0.0019 memory: 7920 grad_norm: 952.1582 loss: 434.6667 loss_cls: 157.9703 loss_bbox: 131.6332 loss_dfl: 145.0632 +2024/03/20 21:17:47 - mmengine - INFO - Epoch(train) [4][700/925] lr: 1.9258e-04 eta: 9:05:02 time: 0.4563 data_time: 0.0020 memory: 8026 grad_norm: 849.0119 loss: 430.0097 loss_cls: 155.7532 loss_bbox: 130.8801 loss_dfl: 143.3764 +2024/03/20 21:18:11 - mmengine - INFO - Epoch(train) [4][750/925] lr: 1.9258e-04 eta: 9:04:59 time: 0.4836 data_time: 0.0020 memory: 8013 grad_norm: 798.7992 loss: 441.0521 loss_cls: 161.4291 loss_bbox: 133.8204 loss_dfl: 145.8026 +2024/03/20 21:18:35 - mmengine - INFO - Epoch(train) [4][800/925] lr: 1.9258e-04 eta: 9:04:53 time: 0.4811 data_time: 0.0018 memory: 8013 grad_norm: 850.4128 loss: 437.8876 loss_cls: 160.8682 loss_bbox: 132.0947 loss_dfl: 144.9246 +2024/03/20 21:18:58 - mmengine - INFO - Epoch(train) [4][850/925] lr: 1.9258e-04 eta: 9:04:21 time: 0.4555 data_time: 0.0019 memory: 7813 grad_norm: 896.9630 loss: 430.0046 loss_cls: 155.2119 loss_bbox: 131.5653 loss_dfl: 143.2274 +2024/03/20 21:19:22 - mmengine - INFO - Epoch(train) [4][900/925] lr: 1.9258e-04 eta: 9:04:05 time: 0.4723 data_time: 0.0020 memory: 8026 grad_norm: 796.4128 loss: 436.6540 loss_cls: 158.9632 loss_bbox: 132.7400 loss_dfl: 144.9508 +2024/03/20 21:19:33 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:19:59 - mmengine - INFO - Epoch(train) [5][ 50/925] lr: 1.9258e-04 eta: 9:04:21 time: 0.5125 data_time: 0.0521 memory: 8013 grad_norm: 883.7635 loss: 434.5514 loss_cls: 156.2888 loss_bbox: 133.5474 loss_dfl: 144.7152 +2024/03/20 21:20:23 - mmengine - INFO - Epoch(train) [5][100/925] lr: 1.9258e-04 eta: 9:04:02 time: 0.4702 data_time: 0.0020 memory: 7946 grad_norm: 875.9199 loss: 425.4073 loss_cls: 152.2980 loss_bbox: 130.3280 loss_dfl: 142.7813 +2024/03/20 21:20:47 - mmengine - INFO - Epoch(train) [5][150/925] lr: 1.9258e-04 eta: 9:03:53 time: 0.4808 data_time: 0.0019 memory: 7933 grad_norm: 805.8139 loss: 431.7180 loss_cls: 158.1814 loss_bbox: 130.5896 loss_dfl: 142.9470 +2024/03/20 21:21:10 - mmengine - INFO - Epoch(train) [5][200/925] lr: 1.9258e-04 eta: 9:03:21 time: 0.4545 data_time: 0.0019 memory: 8200 grad_norm: 838.5001 loss: 439.1588 loss_cls: 161.7088 loss_bbox: 132.3508 loss_dfl: 145.0992 +2024/03/20 21:21:33 - mmengine - INFO - Epoch(train) [5][250/925] lr: 1.9258e-04 eta: 9:02:54 time: 0.4611 data_time: 0.0021 memory: 8186 grad_norm: 860.8798 loss: 439.5836 loss_cls: 160.0814 loss_bbox: 134.1341 loss_dfl: 145.3682 +2024/03/20 21:21:57 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:21:57 - mmengine - INFO - Epoch(train) [5][300/925] lr: 1.9258e-04 eta: 9:02:43 time: 0.4795 data_time: 0.0021 memory: 7893 grad_norm: 866.6932 loss: 434.1708 loss_cls: 157.1395 loss_bbox: 132.8712 loss_dfl: 144.1600 +2024/03/20 21:22:19 - mmengine - INFO - Epoch(train) [5][350/925] lr: 1.9258e-04 eta: 9:02:05 time: 0.4481 data_time: 0.0021 memory: 7813 grad_norm: 942.6718 loss: 426.6618 loss_cls: 153.6430 loss_bbox: 129.8080 loss_dfl: 143.2109 +2024/03/20 21:22:43 - mmengine - INFO - Epoch(train) [5][400/925] lr: 1.9258e-04 eta: 9:01:48 time: 0.4727 data_time: 0.0020 memory: 7880 grad_norm: 794.4326 loss: 425.6224 loss_cls: 152.6537 loss_bbox: 130.0066 loss_dfl: 142.9621 +2024/03/20 21:23:06 - mmengine - INFO - Epoch(train) [5][450/925] lr: 1.9258e-04 eta: 9:01:24 time: 0.4637 data_time: 0.0020 memory: 8013 grad_norm: 806.8219 loss: 428.6405 loss_cls: 156.2983 loss_bbox: 129.3893 loss_dfl: 142.9529 +2024/03/20 21:23:29 - mmengine - INFO - Epoch(train) [5][500/925] lr: 1.9258e-04 eta: 9:00:53 time: 0.4551 data_time: 0.0018 memory: 7880 grad_norm: 807.4263 loss: 432.3225 loss_cls: 156.9218 loss_bbox: 131.5129 loss_dfl: 143.8879 +2024/03/20 21:23:53 - mmengine - INFO - Epoch(train) [5][550/925] lr: 1.9258e-04 eta: 9:00:40 time: 0.4775 data_time: 0.0029 memory: 7866 grad_norm: 809.2820 loss: 438.0641 loss_cls: 158.2867 loss_bbox: 134.2374 loss_dfl: 145.5400 +2024/03/20 21:24:15 - mmengine - INFO - Epoch(train) [5][600/925] lr: 1.9258e-04 eta: 9:00:06 time: 0.4524 data_time: 0.0021 memory: 8066 grad_norm: 843.6644 loss: 425.3548 loss_cls: 152.8570 loss_bbox: 129.3704 loss_dfl: 143.1274 +2024/03/20 21:24:38 - mmengine - INFO - Epoch(train) [5][650/925] lr: 1.9258e-04 eta: 8:59:41 time: 0.4626 data_time: 0.0019 memory: 8093 grad_norm: 824.1933 loss: 430.8828 loss_cls: 154.6332 loss_bbox: 131.3761 loss_dfl: 144.8735 +2024/03/20 21:25:03 - mmengine - INFO - Epoch(train) [5][700/925] lr: 1.9258e-04 eta: 8:59:32 time: 0.4831 data_time: 0.0019 memory: 8026 grad_norm: 883.8371 loss: 427.9949 loss_cls: 153.1385 loss_bbox: 130.4489 loss_dfl: 144.4075 +2024/03/20 21:25:25 - mmengine - INFO - Epoch(train) [5][750/925] lr: 1.9258e-04 eta: 8:59:00 time: 0.4534 data_time: 0.0020 memory: 7866 grad_norm: 880.4772 loss: 432.9782 loss_cls: 158.3243 loss_bbox: 130.2862 loss_dfl: 144.3677 +2024/03/20 21:25:48 - mmengine - INFO - Epoch(train) [5][800/925] lr: 1.9258e-04 eta: 8:58:34 time: 0.4626 data_time: 0.0019 memory: 7866 grad_norm: 837.7834 loss: 431.7184 loss_cls: 156.4006 loss_bbox: 131.4700 loss_dfl: 143.8478 +2024/03/20 21:26:12 - mmengine - INFO - Epoch(train) [5][850/925] lr: 1.9258e-04 eta: 8:58:17 time: 0.4721 data_time: 0.0018 memory: 7826 grad_norm: 875.1758 loss: 439.8026 loss_cls: 159.6549 loss_bbox: 133.8582 loss_dfl: 146.2896 +2024/03/20 21:26:35 - mmengine - INFO - Epoch(train) [5][900/925] lr: 1.9258e-04 eta: 8:57:44 time: 0.4533 data_time: 0.0018 memory: 8040 grad_norm: 810.5870 loss: 436.3153 loss_cls: 158.0823 loss_bbox: 132.8468 loss_dfl: 145.3862 +2024/03/20 21:26:46 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:26:46 - mmengine - INFO - Saving checkpoint at 5 epochs +2024/03/20 21:26:49 - mmengine - WARNING - `save_param_scheduler` is True but `self.param_schedulers` is None, so skip saving parameter schedulers +2024/03/20 21:26:59 - mmengine - INFO - Epoch(val) [5][ 50/625] eta: 0:01:15 time: 0.1312 data_time: 0.0121 memory: 15322 +2024/03/20 21:27:01 - mmengine - INFO - Epoch(val) [5][100/625] eta: 0:00:44 time: 0.0371 data_time: 0.0015 memory: 1245 +2024/03/20 21:27:05 - mmengine - INFO - Epoch(val) [5][150/625] eta: 0:00:38 time: 0.0775 data_time: 0.0439 memory: 1245 +2024/03/20 21:27:07 - mmengine - INFO - Epoch(val) [5][200/625] eta: 0:00:30 time: 0.0374 data_time: 0.0023 memory: 1245 +2024/03/20 21:27:08 - mmengine - INFO - Epoch(val) [5][250/625] eta: 0:00:23 time: 0.0363 data_time: 0.0024 memory: 1245 +2024/03/20 21:27:10 - mmengine - INFO - Epoch(val) [5][300/625] eta: 0:00:19 time: 0.0366 data_time: 0.0016 memory: 1245 +2024/03/20 21:27:12 - mmengine - INFO - Epoch(val) [5][350/625] eta: 0:00:15 time: 0.0374 data_time: 0.0017 memory: 1245 +2024/03/20 21:27:14 - mmengine - INFO - Epoch(val) [5][400/625] eta: 0:00:12 time: 0.0361 data_time: 0.0015 memory: 1245 +2024/03/20 21:27:16 - mmengine - INFO - Epoch(val) [5][450/625] eta: 0:00:09 time: 0.0353 data_time: 0.0006 memory: 1245 +2024/03/20 21:27:18 - mmengine - INFO - Epoch(val) [5][500/625] eta: 0:00:06 time: 0.0352 data_time: 0.0003 memory: 1245 +2024/03/20 21:27:19 - mmengine - INFO - Epoch(val) [5][550/625] eta: 0:00:03 time: 0.0349 data_time: 0.0003 memory: 1245 +2024/03/20 21:27:21 - mmengine - INFO - Epoch(val) [5][600/625] eta: 0:00:01 time: 0.0312 data_time: 0.0003 memory: 1245 +2024/03/20 21:27:35 - mmengine - INFO - Evaluating bbox... +2024/03/20 21:28:52 - mmengine - INFO - bbox_mAP_copypaste: 0.424 0.582 0.463 0.258 0.472 0.548 +2024/03/20 21:28:53 - mmengine - INFO - Epoch(val) [5][625/625] coco/bbox_mAP: 0.4240 coco/bbox_mAP_50: 0.5820 coco/bbox_mAP_75: 0.4630 coco/bbox_mAP_s: 0.2580 coco/bbox_mAP_m: 0.4720 coco/bbox_mAP_l: 0.5480 data_time: 0.0002 time: 0.0294 +2024/03/20 21:29:22 - mmengine - INFO - Epoch(train) [6][ 50/925] lr: 1.9010e-04 eta: 8:58:26 time: 0.5768 data_time: 0.0630 memory: 7759 grad_norm: 867.7514 loss: 435.3087 loss_cls: 156.2419 loss_bbox: 133.6838 loss_dfl: 145.3831 +2024/03/20 21:29:46 - mmengine - INFO - Epoch(train) [6][100/925] lr: 1.9010e-04 eta: 8:58:07 time: 0.4717 data_time: 0.0021 memory: 7746 grad_norm: 907.0871 loss: 437.4886 loss_cls: 158.3468 loss_bbox: 133.8602 loss_dfl: 145.2815 +2024/03/20 21:30:10 - mmengine - INFO - Epoch(train) [6][150/925] lr: 1.9010e-04 eta: 8:58:00 time: 0.4890 data_time: 0.0021 memory: 7839 grad_norm: 826.9219 loss: 432.2030 loss_cls: 155.9742 loss_bbox: 132.1447 loss_dfl: 144.0841 +2024/03/20 21:30:36 - mmengine - INFO - Epoch(train) [6][200/925] lr: 1.9010e-04 eta: 8:58:07 time: 0.5081 data_time: 0.0021 memory: 7906 grad_norm: 953.3314 loss: 431.2746 loss_cls: 155.8872 loss_bbox: 131.9328 loss_dfl: 143.4545 +2024/03/20 21:31:00 - mmengine - INFO - Epoch(train) [6][250/925] lr: 1.9010e-04 eta: 8:57:51 time: 0.4768 data_time: 0.0020 memory: 7813 grad_norm: 769.1359 loss: 426.4392 loss_cls: 152.5369 loss_bbox: 130.4176 loss_dfl: 143.4847 +2024/03/20 21:31:25 - mmengine - INFO - Epoch(train) [6][300/925] lr: 1.9010e-04 eta: 8:57:55 time: 0.5068 data_time: 0.0020 memory: 8027 grad_norm: 801.9472 loss: 436.2454 loss_cls: 160.2583 loss_bbox: 130.4503 loss_dfl: 145.5368 +2024/03/20 21:31:50 - mmengine - INFO - Epoch(train) [6][350/925] lr: 1.9010e-04 eta: 8:57:51 time: 0.4939 data_time: 0.0021 memory: 8175 grad_norm: 813.5911 loss: 429.0589 loss_cls: 156.1725 loss_bbox: 129.7877 loss_dfl: 143.0988 +2024/03/20 21:32:02 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:32:14 - mmengine - INFO - Epoch(train) [6][400/925] lr: 1.9010e-04 eta: 8:57:36 time: 0.4802 data_time: 0.0021 memory: 8029 grad_norm: 879.0969 loss: 431.9327 loss_cls: 155.7499 loss_bbox: 132.5021 loss_dfl: 143.6807 +2024/03/20 21:32:39 - mmengine - INFO - Epoch(train) [6][450/925] lr: 1.9010e-04 eta: 8:57:39 time: 0.5061 data_time: 0.0021 memory: 7975 grad_norm: 794.0019 loss: 426.7828 loss_cls: 152.4473 loss_bbox: 130.5784 loss_dfl: 143.7570 +2024/03/20 21:33:03 - mmengine - INFO - Epoch(train) [6][500/925] lr: 1.9010e-04 eta: 8:57:21 time: 0.4762 data_time: 0.0020 memory: 7989 grad_norm: 862.2431 loss: 433.6121 loss_cls: 155.2423 loss_bbox: 133.9079 loss_dfl: 144.4619 +2024/03/20 21:33:28 - mmengine - INFO - Epoch(train) [6][550/925] lr: 1.9010e-04 eta: 8:57:20 time: 0.5016 data_time: 0.0028 memory: 8002 grad_norm: 888.4679 loss: 432.9056 loss_cls: 157.4197 loss_bbox: 131.0423 loss_dfl: 144.4436 +2024/03/20 21:33:53 - mmengine - INFO - Epoch(train) [6][600/925] lr: 1.9010e-04 eta: 8:57:21 time: 0.5060 data_time: 0.0021 memory: 8002 grad_norm: 813.8952 loss: 432.9586 loss_cls: 157.1242 loss_bbox: 132.2811 loss_dfl: 143.5534 +2024/03/20 21:34:16 - mmengine - INFO - Epoch(train) [6][650/925] lr: 1.9010e-04 eta: 8:56:54 time: 0.4629 data_time: 0.0020 memory: 7815 grad_norm: 788.7226 loss: 433.6625 loss_cls: 158.3936 loss_bbox: 130.6007 loss_dfl: 144.6681 +2024/03/20 21:34:42 - mmengine - INFO - Epoch(train) [6][700/925] lr: 1.9010e-04 eta: 8:56:55 time: 0.5070 data_time: 0.0020 memory: 8042 grad_norm: 783.3481 loss: 430.8157 loss_cls: 155.6290 loss_bbox: 130.6554 loss_dfl: 144.5314 +2024/03/20 21:35:07 - mmengine - INFO - Epoch(train) [6][750/925] lr: 1.9010e-04 eta: 8:56:54 time: 0.5053 data_time: 0.0021 memory: 7975 grad_norm: 783.5112 loss: 434.8208 loss_cls: 157.5284 loss_bbox: 132.9397 loss_dfl: 144.3527 +2024/03/20 21:35:30 - mmengine - INFO - Epoch(train) [6][800/925] lr: 1.9010e-04 eta: 8:56:31 time: 0.4695 data_time: 0.0021 memory: 8149 grad_norm: 794.3737 loss: 426.8602 loss_cls: 152.9132 loss_bbox: 130.2294 loss_dfl: 143.7176 +2024/03/20 21:35:56 - mmengine - INFO - Epoch(train) [6][850/925] lr: 1.9010e-04 eta: 8:56:31 time: 0.5063 data_time: 0.0020 memory: 7815 grad_norm: 820.4510 loss: 428.6906 loss_cls: 153.8847 loss_bbox: 130.6963 loss_dfl: 144.1096 +2024/03/20 21:36:21 - mmengine - INFO - Epoch(train) [6][900/925] lr: 1.9010e-04 eta: 8:56:29 time: 0.5043 data_time: 0.0021 memory: 7869 grad_norm: 792.2456 loss: 425.1112 loss_cls: 153.5052 loss_bbox: 128.4892 loss_dfl: 143.1168 +2024/03/20 21:36:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:37:01 - mmengine - INFO - Epoch(train) [7][ 50/925] lr: 1.8762e-04 eta: 8:56:50 time: 0.5789 data_time: 0.0649 memory: 8642 grad_norm: 823.1998 loss: 426.4222 loss_cls: 153.0645 loss_bbox: 129.4621 loss_dfl: 143.8956 +2024/03/20 21:37:26 - mmengine - INFO - Epoch(train) [7][100/925] lr: 1.8762e-04 eta: 8:56:41 time: 0.4960 data_time: 0.0020 memory: 7922 grad_norm: 800.0539 loss: 431.1483 loss_cls: 155.5528 loss_bbox: 130.7534 loss_dfl: 144.8421 +2024/03/20 21:37:50 - mmengine - INFO - Epoch(train) [7][150/925] lr: 1.8762e-04 eta: 8:56:20 time: 0.4750 data_time: 0.0021 memory: 8295 grad_norm: 774.4526 loss: 435.2581 loss_cls: 157.8717 loss_bbox: 132.7838 loss_dfl: 144.6026 +2024/03/20 21:38:16 - mmengine - INFO - Epoch(train) [7][200/925] lr: 1.8762e-04 eta: 8:56:28 time: 0.5236 data_time: 0.0020 memory: 7695 grad_norm: 829.9716 loss: 435.2059 loss_cls: 156.7483 loss_bbox: 132.8384 loss_dfl: 145.6192 +2024/03/20 21:38:40 - mmengine - INFO - Epoch(train) [7][250/925] lr: 1.8762e-04 eta: 8:56:13 time: 0.4863 data_time: 0.0020 memory: 7775 grad_norm: 866.9591 loss: 423.0683 loss_cls: 151.5735 loss_bbox: 128.4395 loss_dfl: 143.0552 +2024/03/20 21:39:05 - mmengine - INFO - Epoch(train) [7][300/925] lr: 1.8762e-04 eta: 8:55:56 time: 0.4831 data_time: 0.0020 memory: 7962 grad_norm: 781.6523 loss: 429.6220 loss_cls: 155.1097 loss_bbox: 131.0776 loss_dfl: 143.4347 +2024/03/20 21:39:31 - mmengine - INFO - Epoch(train) [7][350/925] lr: 1.8762e-04 eta: 8:56:01 time: 0.5218 data_time: 0.0020 memory: 7962 grad_norm: 840.5325 loss: 430.8954 loss_cls: 154.4615 loss_bbox: 131.7365 loss_dfl: 144.6975 +2024/03/20 21:39:54 - mmengine - INFO - Epoch(train) [7][400/925] lr: 1.8762e-04 eta: 8:55:39 time: 0.4743 data_time: 0.0021 memory: 7909 grad_norm: 857.3640 loss: 427.5174 loss_cls: 153.5239 loss_bbox: 130.8263 loss_dfl: 143.1671 +2024/03/20 21:40:19 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:40:19 - mmengine - INFO - Epoch(train) [7][450/925] lr: 1.8762e-04 eta: 8:55:28 time: 0.4959 data_time: 0.0021 memory: 7949 grad_norm: 820.0171 loss: 423.0290 loss_cls: 151.8369 loss_bbox: 127.9124 loss_dfl: 143.2798 +2024/03/20 21:40:45 - mmengine - INFO - Epoch(train) [7][500/925] lr: 1.8762e-04 eta: 8:55:29 time: 0.5164 data_time: 0.0020 memory: 7975 grad_norm: 905.6163 loss: 431.7688 loss_cls: 154.5910 loss_bbox: 132.1212 loss_dfl: 145.0567 +2024/03/20 21:41:09 - mmengine - INFO - Epoch(train) [7][550/925] lr: 1.8762e-04 eta: 8:55:05 time: 0.4706 data_time: 0.0020 memory: 7855 grad_norm: 870.0536 loss: 430.1079 loss_cls: 154.2668 loss_bbox: 131.9109 loss_dfl: 143.9301 +2024/03/20 21:41:34 - mmengine - INFO - Epoch(train) [7][600/925] lr: 1.8762e-04 eta: 8:55:01 time: 0.5102 data_time: 0.0020 memory: 8269 grad_norm: 800.3474 loss: 431.6847 loss_cls: 156.2794 loss_bbox: 130.9115 loss_dfl: 144.4938 +2024/03/20 21:42:00 - mmengine - INFO - Epoch(train) [7][650/925] lr: 1.8762e-04 eta: 8:55:01 time: 0.5151 data_time: 0.0020 memory: 7962 grad_norm: 812.7028 loss: 429.5148 loss_cls: 153.7711 loss_bbox: 131.6759 loss_dfl: 144.0678 +2024/03/20 21:42:24 - mmengine - INFO - Epoch(train) [7][700/925] lr: 1.8762e-04 eta: 8:54:38 time: 0.4748 data_time: 0.0020 memory: 7762 grad_norm: 824.2414 loss: 427.7771 loss_cls: 153.7466 loss_bbox: 129.9365 loss_dfl: 144.0940 +2024/03/20 21:42:49 - mmengine - INFO - Epoch(train) [7][750/925] lr: 1.8762e-04 eta: 8:54:32 time: 0.5076 data_time: 0.0021 memory: 7949 grad_norm: 827.3994 loss: 426.2433 loss_cls: 154.2525 loss_bbox: 127.5671 loss_dfl: 144.4237 +2024/03/20 21:43:14 - mmengine - INFO - Epoch(train) [7][800/925] lr: 1.8762e-04 eta: 8:54:25 time: 0.5046 data_time: 0.0021 memory: 8055 grad_norm: 809.6317 loss: 424.1543 loss_cls: 149.9027 loss_bbox: 130.7274 loss_dfl: 143.5241 +2024/03/20 21:43:38 - mmengine - INFO - Epoch(train) [7][850/925] lr: 1.8762e-04 eta: 8:54:07 time: 0.4838 data_time: 0.0021 memory: 7802 grad_norm: 775.8959 loss: 438.5983 loss_cls: 159.8945 loss_bbox: 132.4276 loss_dfl: 146.2762 +2024/03/20 21:44:04 - mmengine - INFO - Epoch(train) [7][900/925] lr: 1.8762e-04 eta: 8:54:01 time: 0.5082 data_time: 0.0021 memory: 8309 grad_norm: 826.9371 loss: 425.4008 loss_cls: 151.2801 loss_bbox: 130.5462 loss_dfl: 143.5745 +2024/03/20 21:44:16 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:44:43 - mmengine - INFO - Epoch(train) [8][ 50/925] lr: 1.8515e-04 eta: 8:54:01 time: 0.5443 data_time: 0.0639 memory: 7935 grad_norm: 751.5582 loss: 432.7493 loss_cls: 157.2293 loss_bbox: 131.0719 loss_dfl: 144.4480 +2024/03/20 21:45:09 - mmengine - INFO - Epoch(train) [8][100/925] lr: 1.8515e-04 eta: 8:54:01 time: 0.5209 data_time: 0.0020 memory: 7909 grad_norm: 804.4478 loss: 433.3041 loss_cls: 157.1236 loss_bbox: 130.1845 loss_dfl: 145.9960 +2024/03/20 21:45:34 - mmengine - INFO - Epoch(train) [8][150/925] lr: 1.8515e-04 eta: 8:53:46 time: 0.4938 data_time: 0.0021 memory: 8295 grad_norm: 884.8724 loss: 432.6251 loss_cls: 154.3877 loss_bbox: 132.7579 loss_dfl: 145.4795 +2024/03/20 21:45:59 - mmengine - INFO - Epoch(train) [8][200/925] lr: 1.8515e-04 eta: 8:53:29 time: 0.4886 data_time: 0.0020 memory: 7882 grad_norm: 782.9984 loss: 426.3913 loss_cls: 151.7941 loss_bbox: 130.2505 loss_dfl: 144.3467 +2024/03/20 21:46:24 - mmengine - INFO - Epoch(train) [8][250/925] lr: 1.8515e-04 eta: 8:53:19 time: 0.5024 data_time: 0.0020 memory: 8363 grad_norm: 837.4978 loss: 430.5446 loss_cls: 154.5967 loss_bbox: 132.2478 loss_dfl: 143.7000 +2024/03/20 21:46:48 - mmengine - INFO - Epoch(train) [8][300/925] lr: 1.8515e-04 eta: 8:52:59 time: 0.4833 data_time: 0.0021 memory: 7869 grad_norm: 808.7757 loss: 431.2355 loss_cls: 154.7622 loss_bbox: 132.2853 loss_dfl: 144.1880 +2024/03/20 21:47:13 - mmengine - INFO - Epoch(train) [8][350/925] lr: 1.8515e-04 eta: 8:52:50 time: 0.5062 data_time: 0.0020 memory: 7669 grad_norm: 769.1369 loss: 426.0541 loss_cls: 152.4940 loss_bbox: 129.7820 loss_dfl: 143.7781 +2024/03/20 21:47:38 - mmengine - INFO - Epoch(train) [8][400/925] lr: 1.8515e-04 eta: 8:52:38 time: 0.5003 data_time: 0.0021 memory: 7855 grad_norm: 764.5871 loss: 429.5658 loss_cls: 155.1920 loss_bbox: 131.2232 loss_dfl: 143.1506 +2024/03/20 21:48:02 - mmengine - INFO - Epoch(train) [8][450/925] lr: 1.8515e-04 eta: 8:52:14 time: 0.4755 data_time: 0.0020 memory: 7909 grad_norm: 779.9371 loss: 420.3645 loss_cls: 149.0496 loss_bbox: 128.9344 loss_dfl: 142.3804 +2024/03/20 21:48:28 - mmengine - INFO - Epoch(train) [8][500/925] lr: 1.8515e-04 eta: 8:52:09 time: 0.5155 data_time: 0.0019 memory: 7762 grad_norm: 830.6531 loss: 430.6099 loss_cls: 155.1745 loss_bbox: 131.6280 loss_dfl: 143.8073 +2024/03/20 21:48:40 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:48:53 - mmengine - INFO - Epoch(train) [8][550/925] lr: 1.8515e-04 eta: 8:51:58 time: 0.5034 data_time: 0.0021 memory: 7922 grad_norm: 741.9954 loss: 426.3363 loss_cls: 152.1076 loss_bbox: 130.1271 loss_dfl: 144.1017 +2024/03/20 21:49:16 - mmengine - INFO - Epoch(train) [8][600/925] lr: 1.8515e-04 eta: 8:51:29 time: 0.4652 data_time: 0.0019 memory: 7962 grad_norm: 772.3566 loss: 423.8980 loss_cls: 150.0143 loss_bbox: 131.3051 loss_dfl: 142.5786 +2024/03/20 21:49:43 - mmengine - INFO - Epoch(train) [8][650/925] lr: 1.8515e-04 eta: 8:51:28 time: 0.5254 data_time: 0.0021 memory: 7882 grad_norm: 819.7197 loss: 420.4780 loss_cls: 148.4692 loss_bbox: 129.7735 loss_dfl: 142.2353 +2024/03/20 21:50:07 - mmengine - INFO - Epoch(train) [8][700/925] lr: 1.8515e-04 eta: 8:51:09 time: 0.4873 data_time: 0.0021 memory: 8215 grad_norm: 827.3073 loss: 424.7349 loss_cls: 152.1258 loss_bbox: 129.1862 loss_dfl: 143.4229 +2024/03/20 21:50:32 - mmengine - INFO - Epoch(train) [8][750/925] lr: 1.8515e-04 eta: 8:50:52 time: 0.4914 data_time: 0.0022 memory: 7815 grad_norm: 828.8699 loss: 423.5133 loss_cls: 152.6091 loss_bbox: 128.2902 loss_dfl: 142.6141 +2024/03/20 21:50:58 - mmengine - INFO - Epoch(train) [8][800/925] lr: 1.8515e-04 eta: 8:50:49 time: 0.5234 data_time: 0.0022 memory: 8122 grad_norm: 817.5565 loss: 431.4904 loss_cls: 153.6276 loss_bbox: 132.8943 loss_dfl: 144.9685 +2024/03/20 21:51:21 - mmengine - INFO - Epoch(train) [8][850/925] lr: 1.8515e-04 eta: 8:50:24 time: 0.4743 data_time: 0.0022 memory: 7935 grad_norm: 746.7880 loss: 427.4042 loss_cls: 154.0704 loss_bbox: 129.4177 loss_dfl: 143.9161 +2024/03/20 21:51:47 - mmengine - INFO - Epoch(train) [8][900/925] lr: 1.8515e-04 eta: 8:50:13 time: 0.5061 data_time: 0.0020 memory: 7802 grad_norm: 801.5321 loss: 431.0698 loss_cls: 154.4668 loss_bbox: 132.0554 loss_dfl: 144.5476 +2024/03/20 21:51:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:52:27 - mmengine - INFO - Epoch(train) [9][ 50/925] lr: 1.8268e-04 eta: 8:50:13 time: 0.5408 data_time: 0.0634 memory: 8042 grad_norm: 884.9614 loss: 425.1113 loss_cls: 148.6232 loss_bbox: 132.1320 loss_dfl: 144.3561 +2024/03/20 21:52:51 - mmengine - INFO - Epoch(train) [9][100/925] lr: 1.8268e-04 eta: 8:49:50 time: 0.4799 data_time: 0.0020 memory: 7869 grad_norm: 787.8012 loss: 426.3384 loss_cls: 151.5721 loss_bbox: 130.6022 loss_dfl: 144.1642 +2024/03/20 21:53:17 - mmengine - INFO - Epoch(train) [9][150/925] lr: 1.8268e-04 eta: 8:49:42 time: 0.5140 data_time: 0.0020 memory: 7922 grad_norm: inf loss: 428.2503 loss_cls: 152.3256 loss_bbox: 130.7073 loss_dfl: 145.2175 +2024/03/20 21:53:41 - mmengine - INFO - Epoch(train) [9][200/925] lr: 1.8268e-04 eta: 8:49:17 time: 0.4779 data_time: 0.0020 memory: 7695 grad_norm: 777.1252 loss: 430.9505 loss_cls: 154.8221 loss_bbox: 132.2728 loss_dfl: 143.8556 +2024/03/20 21:54:05 - mmengine - INFO - Epoch(train) [9][250/925] lr: 1.8268e-04 eta: 8:48:55 time: 0.4826 data_time: 0.0020 memory: 8242 grad_norm: 745.0352 loss: 423.3605 loss_cls: 151.4993 loss_bbox: 129.3460 loss_dfl: 142.5152 +2024/03/20 21:54:30 - mmengine - INFO - Epoch(train) [9][300/925] lr: 1.8268e-04 eta: 8:48:44 time: 0.5067 data_time: 0.0021 memory: 7962 grad_norm: 736.5203 loss: 434.2154 loss_cls: 157.0554 loss_bbox: 132.2454 loss_dfl: 144.9146 +2024/03/20 21:54:54 - mmengine - INFO - Epoch(train) [9][350/925] lr: 1.8268e-04 eta: 8:48:16 time: 0.4702 data_time: 0.0021 memory: 8029 grad_norm: 820.1601 loss: 428.0210 loss_cls: 151.2166 loss_bbox: 132.3979 loss_dfl: 144.4066 +2024/03/20 21:55:18 - mmengine - INFO - Epoch(train) [9][400/925] lr: 1.8268e-04 eta: 8:47:59 time: 0.4933 data_time: 0.0021 memory: 7869 grad_norm: 785.7801 loss: 424.7428 loss_cls: 150.7924 loss_bbox: 130.7057 loss_dfl: 143.2447 +2024/03/20 21:55:43 - mmengine - INFO - Epoch(train) [9][450/925] lr: 1.8268e-04 eta: 8:47:42 time: 0.4952 data_time: 0.0021 memory: 7669 grad_norm: 790.4560 loss: 426.7815 loss_cls: 153.3383 loss_bbox: 129.3963 loss_dfl: 144.0469 +2024/03/20 21:56:07 - mmengine - INFO - Epoch(train) [9][500/925] lr: 1.8268e-04 eta: 8:47:18 time: 0.4797 data_time: 0.0021 memory: 7815 grad_norm: 780.7997 loss: 423.7396 loss_cls: 149.4759 loss_bbox: 130.4845 loss_dfl: 143.7792 +2024/03/20 21:56:32 - mmengine - INFO - Epoch(train) [9][550/925] lr: 1.8268e-04 eta: 8:47:03 time: 0.5006 data_time: 0.0021 memory: 7789 grad_norm: 792.3567 loss: 426.1075 loss_cls: 152.5324 loss_bbox: 130.0349 loss_dfl: 143.5402 +2024/03/20 21:56:56 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 21:56:56 - mmengine - INFO - Epoch(train) [9][600/925] lr: 1.8268e-04 eta: 8:46:38 time: 0.4751 data_time: 0.0020 memory: 7935 grad_norm: 835.6760 loss: 422.0148 loss_cls: 149.2821 loss_bbox: 129.5689 loss_dfl: 143.1638 +2024/03/20 21:57:21 - mmengine - INFO - Epoch(train) [9][650/925] lr: 1.8268e-04 eta: 8:46:22 time: 0.4977 data_time: 0.0020 memory: 8349 grad_norm: 799.5808 loss: 416.8993 loss_cls: 147.6008 loss_bbox: 127.7386 loss_dfl: 141.5599 +2024/03/20 21:57:46 - mmengine - INFO - Epoch(train) [9][700/925] lr: 1.8268e-04 eta: 8:46:05 time: 0.4957 data_time: 0.0021 memory: 8015 grad_norm: 849.8771 loss: 426.2880 loss_cls: 150.5329 loss_bbox: 131.5685 loss_dfl: 144.1866 +2024/03/20 21:58:09 - mmengine - INFO - Epoch(train) [9][750/925] lr: 1.8268e-04 eta: 8:45:36 time: 0.4675 data_time: 0.0021 memory: 7722 grad_norm: 740.1291 loss: 421.5167 loss_cls: 149.2097 loss_bbox: 129.3974 loss_dfl: 142.9096 +2024/03/20 21:58:34 - mmengine - INFO - Epoch(train) [9][800/925] lr: 1.8268e-04 eta: 8:45:20 time: 0.4994 data_time: 0.0020 memory: 7842 grad_norm: 766.4077 loss: 415.3044 loss_cls: 146.3536 loss_bbox: 126.9999 loss_dfl: 141.9509 +2024/03/20 21:58:58 - mmengine - INFO - Epoch(train) [9][850/925] lr: 1.8268e-04 eta: 8:45:00 time: 0.4882 data_time: 0.0021 memory: 7815 grad_norm: 765.1394 loss: 423.8322 loss_cls: 150.2986 loss_bbox: 130.6535 loss_dfl: 142.8801 +2024/03/20 21:59:22 - mmengine - INFO - Epoch(train) [9][900/925] lr: 1.8268e-04 eta: 8:44:35 time: 0.4774 data_time: 0.0022 memory: 7935 grad_norm: 749.8022 loss: 420.2553 loss_cls: 149.7391 loss_bbox: 128.1133 loss_dfl: 142.4029 +2024/03/20 21:59:34 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:00:03 - mmengine - INFO - Epoch(train) [10][ 50/925] lr: 1.8020e-04 eta: 8:44:38 time: 0.5726 data_time: 0.0633 memory: 7922 grad_norm: 783.0197 loss: 429.0450 loss_cls: 152.6273 loss_bbox: 132.6430 loss_dfl: 143.7748 +2024/03/20 22:00:28 - mmengine - INFO - Epoch(train) [10][100/925] lr: 1.8020e-04 eta: 8:44:17 time: 0.4881 data_time: 0.0020 memory: 8095 grad_norm: 779.2450 loss: 424.6004 loss_cls: 151.0222 loss_bbox: 129.0811 loss_dfl: 144.4972 +2024/03/20 22:00:53 - mmengine - INFO - Epoch(train) [10][150/925] lr: 1.8020e-04 eta: 8:44:04 time: 0.5063 data_time: 0.0021 memory: 8015 grad_norm: 778.5392 loss: 424.6219 loss_cls: 151.6157 loss_bbox: 129.3622 loss_dfl: 143.6440 +2024/03/20 22:01:19 - mmengine - INFO - Epoch(train) [10][200/925] lr: 1.8020e-04 eta: 8:43:52 time: 0.5130 data_time: 0.0021 memory: 8002 grad_norm: 754.1367 loss: 426.2423 loss_cls: 152.3128 loss_bbox: 130.7967 loss_dfl: 143.1328 +2024/03/20 22:01:43 - mmengine - INFO - Epoch(train) [10][250/925] lr: 1.8020e-04 eta: 8:43:31 time: 0.4874 data_time: 0.0021 memory: 8069 grad_norm: 813.4723 loss: 426.6895 loss_cls: 152.6375 loss_bbox: 131.1441 loss_dfl: 142.9079 +2024/03/20 22:02:09 - mmengine - INFO - Epoch(train) [10][300/925] lr: 1.8020e-04 eta: 8:43:19 time: 0.5118 data_time: 0.0021 memory: 8002 grad_norm: 808.5231 loss: 420.9468 loss_cls: 147.3392 loss_bbox: 130.5451 loss_dfl: 143.0625 +2024/03/20 22:02:34 - mmengine - INFO - Epoch(train) [10][350/925] lr: 1.8020e-04 eta: 8:43:05 time: 0.5056 data_time: 0.0020 memory: 8055 grad_norm: 777.6124 loss: 429.6669 loss_cls: 151.9450 loss_bbox: 132.9847 loss_dfl: 144.7373 +2024/03/20 22:02:59 - mmengine - INFO - Epoch(train) [10][400/925] lr: 1.8020e-04 eta: 8:42:45 time: 0.4914 data_time: 0.0020 memory: 8109 grad_norm: 776.8531 loss: 425.4402 loss_cls: 150.3412 loss_bbox: 131.2134 loss_dfl: 143.8856 +2024/03/20 22:03:25 - mmengine - INFO - Epoch(train) [10][450/925] lr: 1.8020e-04 eta: 8:42:36 time: 0.5220 data_time: 0.0021 memory: 8082 grad_norm: 776.2481 loss: 432.1670 loss_cls: 153.0453 loss_bbox: 133.5437 loss_dfl: 145.5779 +2024/03/20 22:03:50 - mmengine - INFO - Epoch(train) [10][500/925] lr: 1.8020e-04 eta: 8:42:21 time: 0.5040 data_time: 0.0021 memory: 8069 grad_norm: 700.7446 loss: 423.5820 loss_cls: 150.9037 loss_bbox: 129.5228 loss_dfl: 143.1556 +2024/03/20 22:04:15 - mmengine - INFO - Epoch(train) [10][550/925] lr: 1.8020e-04 eta: 8:42:03 time: 0.4970 data_time: 0.0022 memory: 7749 grad_norm: 758.4239 loss: 422.4946 loss_cls: 149.4304 loss_bbox: 129.5796 loss_dfl: 143.4846 +2024/03/20 22:04:42 - mmengine - INFO - Epoch(train) [10][600/925] lr: 1.8020e-04 eta: 8:41:57 time: 0.5315 data_time: 0.0022 memory: 8002 grad_norm: 739.8757 loss: 423.1955 loss_cls: 149.1022 loss_bbox: 130.9914 loss_dfl: 143.1019 +2024/03/20 22:05:06 - mmengine - INFO - Epoch(train) [10][650/925] lr: 1.8020e-04 eta: 8:41:37 time: 0.4918 data_time: 0.0022 memory: 7922 grad_norm: 794.3322 loss: 422.8943 loss_cls: 149.9193 loss_bbox: 129.9476 loss_dfl: 143.0274 +2024/03/20 22:05:19 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:05:32 - mmengine - INFO - Epoch(train) [10][700/925] lr: 1.8020e-04 eta: 8:41:24 time: 0.5139 data_time: 0.0021 memory: 8042 grad_norm: 775.4446 loss: 422.8617 loss_cls: 150.4306 loss_bbox: 130.3809 loss_dfl: 142.0503 +2024/03/20 22:05:58 - mmengine - INFO - Epoch(train) [10][750/925] lr: 1.8020e-04 eta: 8:41:12 time: 0.5139 data_time: 0.0021 memory: 7869 grad_norm: 766.4328 loss: 425.4958 loss_cls: 151.4906 loss_bbox: 130.4291 loss_dfl: 143.5762 +2024/03/20 22:06:22 - mmengine - INFO - Epoch(train) [10][800/925] lr: 1.8020e-04 eta: 8:40:48 time: 0.4819 data_time: 0.0021 memory: 8015 grad_norm: 776.3269 loss: 420.7628 loss_cls: 149.2048 loss_bbox: 129.5043 loss_dfl: 142.0537 +2024/03/20 22:06:48 - mmengine - INFO - Epoch(train) [10][850/925] lr: 1.8020e-04 eta: 8:40:39 time: 0.5232 data_time: 0.0021 memory: 7855 grad_norm: 776.3244 loss: 427.0805 loss_cls: 152.7118 loss_bbox: 130.5426 loss_dfl: 143.8262 +2024/03/20 22:07:13 - mmengine - INFO - Epoch(train) [10][900/925] lr: 1.8020e-04 eta: 8:40:23 time: 0.5063 data_time: 0.0021 memory: 7935 grad_norm: 755.7021 loss: 424.9155 loss_cls: 149.1797 loss_bbox: 130.9575 loss_dfl: 144.7784 +2024/03/20 22:07:24 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:07:25 - mmengine - INFO - Saving checkpoint at 10 epochs +2024/03/20 22:07:34 - mmengine - INFO - Epoch(val) [10][ 50/625] eta: 0:00:21 time: 0.0380 data_time: 0.0009 memory: 7615 +2024/03/20 22:07:36 - mmengine - INFO - Epoch(val) [10][100/625] eta: 0:00:19 time: 0.0378 data_time: 0.0004 memory: 1244 +2024/03/20 22:07:38 - mmengine - INFO - Epoch(val) [10][150/625] eta: 0:00:18 time: 0.0393 data_time: 0.0004 memory: 1244 +2024/03/20 22:07:40 - mmengine - INFO - Epoch(val) [10][200/625] eta: 0:00:16 time: 0.0375 data_time: 0.0004 memory: 1244 +2024/03/20 22:07:41 - mmengine - INFO - Epoch(val) [10][250/625] eta: 0:00:14 time: 0.0366 data_time: 0.0003 memory: 1244 +2024/03/20 22:07:43 - mmengine - INFO - Epoch(val) [10][300/625] eta: 0:00:12 time: 0.0380 data_time: 0.0003 memory: 1244 +2024/03/20 22:07:45 - mmengine - INFO - Epoch(val) [10][350/625] eta: 0:00:10 time: 0.0368 data_time: 0.0003 memory: 1244 +2024/03/20 22:07:47 - mmengine - INFO - Epoch(val) [10][400/625] eta: 0:00:08 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/20 22:07:49 - mmengine - INFO - Epoch(val) [10][450/625] eta: 0:00:06 time: 0.0345 data_time: 0.0003 memory: 1244 +2024/03/20 22:07:50 - mmengine - INFO - Epoch(val) [10][500/625] eta: 0:00:04 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/20 22:07:52 - mmengine - INFO - Epoch(val) [10][550/625] eta: 0:00:02 time: 0.0281 data_time: 0.0002 memory: 1244 +2024/03/20 22:07:53 - mmengine - INFO - Epoch(val) [10][600/625] eta: 0:00:00 time: 0.0291 data_time: 0.0002 memory: 1244 +2024/03/20 22:08:06 - mmengine - INFO - Evaluating bbox... +2024/03/20 22:09:19 - mmengine - INFO - bbox_mAP_copypaste: 0.468 0.632 0.509 0.294 0.518 0.603 +2024/03/20 22:09:21 - mmengine - INFO - Epoch(val) [10][625/625] coco/bbox_mAP: 0.4680 coco/bbox_mAP_50: 0.6320 coco/bbox_mAP_75: 0.5090 coco/bbox_mAP_s: 0.2940 coco/bbox_mAP_m: 0.5180 coco/bbox_mAP_l: 0.6030 data_time: 0.0003 time: 0.0298 +2024/03/20 22:09:50 - mmengine - INFO - Epoch(train) [11][ 50/925] lr: 1.7772e-04 eta: 8:40:19 time: 0.5917 data_time: 0.0619 memory: 8122 grad_norm: 779.2485 loss: 422.7430 loss_cls: 148.8517 loss_bbox: 130.1345 loss_dfl: 143.7568 +2024/03/20 22:10:16 - mmengine - INFO - Epoch(train) [11][100/925] lr: 1.7772e-04 eta: 8:40:05 time: 0.5123 data_time: 0.0021 memory: 8029 grad_norm: 739.6489 loss: 423.4565 loss_cls: 149.7856 loss_bbox: 129.2814 loss_dfl: 144.3895 +2024/03/20 22:10:41 - mmengine - INFO - Epoch(train) [11][150/925] lr: 1.7772e-04 eta: 8:39:49 time: 0.5044 data_time: 0.0021 memory: 7935 grad_norm: 769.0180 loss: 424.8578 loss_cls: 151.0201 loss_bbox: 130.4499 loss_dfl: 143.3878 +2024/03/20 22:11:07 - mmengine - INFO - Epoch(train) [11][200/925] lr: 1.7772e-04 eta: 8:39:33 time: 0.5086 data_time: 0.0020 memory: 7802 grad_norm: 740.9317 loss: 424.7316 loss_cls: 153.1492 loss_bbox: 127.9351 loss_dfl: 143.6474 +2024/03/20 22:11:32 - mmengine - INFO - Epoch(train) [11][250/925] lr: 1.7772e-04 eta: 8:39:18 time: 0.5075 data_time: 0.0021 memory: 8162 grad_norm: 781.9946 loss: 418.8479 loss_cls: 147.7836 loss_bbox: 128.7804 loss_dfl: 142.2838 +2024/03/20 22:11:58 - mmengine - INFO - Epoch(train) [11][300/925] lr: 1.7772e-04 eta: 8:39:03 time: 0.5121 data_time: 0.0022 memory: 8095 grad_norm: 777.4046 loss: 422.3280 loss_cls: 148.4643 loss_bbox: 130.1029 loss_dfl: 143.7608 +2024/03/20 22:12:24 - mmengine - INFO - Epoch(train) [11][350/925] lr: 1.7772e-04 eta: 8:38:52 time: 0.5208 data_time: 0.0019 memory: 7949 grad_norm: 753.9006 loss: 424.5230 loss_cls: 150.4775 loss_bbox: 131.3167 loss_dfl: 142.7288 +2024/03/20 22:12:48 - mmengine - INFO - Epoch(train) [11][400/925] lr: 1.7772e-04 eta: 8:38:31 time: 0.4956 data_time: 0.0019 memory: 7802 grad_norm: 736.7294 loss: 422.5992 loss_cls: 149.9506 loss_bbox: 129.4111 loss_dfl: 143.2375 +2024/03/20 22:13:14 - mmengine - INFO - Epoch(train) [11][450/925] lr: 1.7772e-04 eta: 8:38:16 time: 0.5101 data_time: 0.0019 memory: 7802 grad_norm: inf loss: 426.7359 loss_cls: 153.5506 loss_bbox: 129.0936 loss_dfl: 144.0916 +2024/03/20 22:13:40 - mmengine - INFO - Epoch(train) [11][500/925] lr: 1.7772e-04 eta: 8:38:06 time: 0.5255 data_time: 0.0021 memory: 7895 grad_norm: 776.8818 loss: 427.8473 loss_cls: 152.5863 loss_bbox: 131.2204 loss_dfl: 144.0406 +2024/03/20 22:14:05 - mmengine - INFO - Epoch(train) [11][550/925] lr: 1.7772e-04 eta: 8:37:45 time: 0.4933 data_time: 0.0022 memory: 7789 grad_norm: 855.3907 loss: 421.8850 loss_cls: 149.3550 loss_bbox: 129.1014 loss_dfl: 143.4286 +2024/03/20 22:14:31 - mmengine - INFO - Epoch(train) [11][600/925] lr: 1.7772e-04 eta: 8:37:30 time: 0.5131 data_time: 0.0022 memory: 7855 grad_norm: 748.6579 loss: 416.7662 loss_cls: 146.1248 loss_bbox: 128.7744 loss_dfl: 141.8669 +2024/03/20 22:14:56 - mmengine - INFO - Epoch(train) [11][650/925] lr: 1.7772e-04 eta: 8:37:16 time: 0.5146 data_time: 0.0020 memory: 8082 grad_norm: 718.4925 loss: 421.2004 loss_cls: 149.2098 loss_bbox: 129.0350 loss_dfl: 142.9556 +2024/03/20 22:15:21 - mmengine - INFO - Epoch(train) [11][700/925] lr: 1.7772e-04 eta: 8:36:53 time: 0.4885 data_time: 0.0022 memory: 8015 grad_norm: 709.4478 loss: 418.6867 loss_cls: 146.8654 loss_bbox: 129.6391 loss_dfl: 142.1822 +2024/03/20 22:15:47 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:15:47 - mmengine - INFO - Epoch(train) [11][750/925] lr: 1.7772e-04 eta: 8:36:39 time: 0.5180 data_time: 0.0021 memory: 8069 grad_norm: 733.4316 loss: 424.4676 loss_cls: 151.3747 loss_bbox: 129.4844 loss_dfl: 143.6085 +2024/03/20 22:16:11 - mmengine - INFO - Epoch(train) [11][800/925] lr: 1.7772e-04 eta: 8:36:19 time: 0.4949 data_time: 0.0021 memory: 8135 grad_norm: 743.3596 loss: 424.3211 loss_cls: 151.0699 loss_bbox: 130.0659 loss_dfl: 143.1853 +2024/03/20 22:16:36 - mmengine - INFO - Epoch(train) [11][850/925] lr: 1.7772e-04 eta: 8:35:58 time: 0.4974 data_time: 0.0021 memory: 7855 grad_norm: 813.1619 loss: 428.1027 loss_cls: 152.3314 loss_bbox: 131.3670 loss_dfl: 144.4042 +2024/03/20 22:17:03 - mmengine - INFO - Epoch(train) [11][900/925] lr: 1.7772e-04 eta: 8:35:50 time: 0.5337 data_time: 0.0021 memory: 8029 grad_norm: 715.4780 loss: 422.1939 loss_cls: 147.2867 loss_bbox: 131.6611 loss_dfl: 143.2460 +2024/03/20 22:17:15 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:17:45 - mmengine - INFO - Epoch(train) [12][ 50/925] lr: 1.7525e-04 eta: 8:35:43 time: 0.5800 data_time: 0.0729 memory: 8149 grad_norm: 801.9725 loss: 423.9730 loss_cls: 150.1976 loss_bbox: 129.3997 loss_dfl: 144.3758 +2024/03/20 22:18:10 - mmengine - INFO - Epoch(train) [12][100/925] lr: 1.7525e-04 eta: 8:35:28 time: 0.5176 data_time: 0.0021 memory: 8335 grad_norm: 739.9765 loss: 427.7263 loss_cls: 152.5206 loss_bbox: 130.6522 loss_dfl: 144.5535 +2024/03/20 22:18:35 - mmengine - INFO - Epoch(train) [12][150/925] lr: 1.7525e-04 eta: 8:35:06 time: 0.4922 data_time: 0.0020 memory: 7882 grad_norm: 790.4856 loss: 429.7666 loss_cls: 155.1267 loss_bbox: 131.2519 loss_dfl: 143.3881 +2024/03/20 22:19:00 - mmengine - INFO - Epoch(train) [12][200/925] lr: 1.7525e-04 eta: 8:34:44 time: 0.4910 data_time: 0.0022 memory: 7949 grad_norm: 792.4367 loss: 420.7557 loss_cls: 148.5300 loss_bbox: 128.9440 loss_dfl: 143.2818 +2024/03/20 22:19:26 - mmengine - INFO - Epoch(train) [12][250/925] lr: 1.7525e-04 eta: 8:34:31 time: 0.5252 data_time: 0.0018 memory: 7829 grad_norm: 763.4450 loss: 415.9906 loss_cls: 145.0200 loss_bbox: 129.1882 loss_dfl: 141.7824 +2024/03/20 22:19:50 - mmengine - INFO - Epoch(train) [12][300/925] lr: 1.7525e-04 eta: 8:34:09 time: 0.4909 data_time: 0.0017 memory: 7695 grad_norm: 845.8955 loss: 417.5744 loss_cls: 145.8940 loss_bbox: 129.1236 loss_dfl: 142.5569 +2024/03/20 22:20:15 - mmengine - INFO - Epoch(train) [12][350/925] lr: 1.7525e-04 eta: 8:33:46 time: 0.4907 data_time: 0.0021 memory: 7855 grad_norm: 720.8303 loss: 428.3064 loss_cls: 151.4604 loss_bbox: 133.3661 loss_dfl: 143.4800 +2024/03/20 22:20:41 - mmengine - INFO - Epoch(train) [12][400/925] lr: 1.7525e-04 eta: 8:33:33 time: 0.5228 data_time: 0.0021 memory: 8229 grad_norm: 798.1626 loss: 423.8849 loss_cls: 149.1751 loss_bbox: 130.8001 loss_dfl: 143.9097 +2024/03/20 22:21:06 - mmengine - INFO - Epoch(train) [12][450/925] lr: 1.7525e-04 eta: 8:33:09 time: 0.4880 data_time: 0.0021 memory: 8042 grad_norm: 700.0112 loss: 420.8412 loss_cls: 148.8319 loss_bbox: 129.1753 loss_dfl: 142.8340 +2024/03/20 22:21:30 - mmengine - INFO - Epoch(train) [12][500/925] lr: 1.7525e-04 eta: 8:32:47 time: 0.4932 data_time: 0.0021 memory: 8015 grad_norm: 776.6792 loss: 425.8991 loss_cls: 150.9693 loss_bbox: 130.2000 loss_dfl: 144.7297 +2024/03/20 22:21:56 - mmengine - INFO - Epoch(train) [12][550/925] lr: 1.7525e-04 eta: 8:32:31 time: 0.5141 data_time: 0.0021 memory: 8109 grad_norm: 745.9705 loss: 422.2086 loss_cls: 150.5558 loss_bbox: 129.2313 loss_dfl: 142.4215 +2024/03/20 22:22:20 - mmengine - INFO - Epoch(train) [12][600/925] lr: 1.7525e-04 eta: 8:32:08 time: 0.4896 data_time: 0.0020 memory: 8415 grad_norm: 718.9040 loss: 426.9266 loss_cls: 149.1819 loss_bbox: 133.2092 loss_dfl: 144.5355 +2024/03/20 22:22:46 - mmengine - INFO - Epoch(train) [12][650/925] lr: 1.7525e-04 eta: 8:31:50 time: 0.5085 data_time: 0.0020 memory: 7762 grad_norm: 740.6900 loss: 421.8987 loss_cls: 150.5950 loss_bbox: 128.6338 loss_dfl: 142.6699 +2024/03/20 22:23:11 - mmengine - INFO - Epoch(train) [12][700/925] lr: 1.7525e-04 eta: 8:31:31 time: 0.5036 data_time: 0.0022 memory: 7962 grad_norm: 787.6391 loss: 417.8044 loss_cls: 145.8715 loss_bbox: 128.4967 loss_dfl: 143.4362 +2024/03/20 22:23:36 - mmengine - INFO - Epoch(train) [12][750/925] lr: 1.7525e-04 eta: 8:31:08 time: 0.4910 data_time: 0.0021 memory: 8042 grad_norm: 787.1288 loss: 417.0884 loss_cls: 148.0244 loss_bbox: 127.2767 loss_dfl: 141.7873 +2024/03/20 22:24:02 - mmengine - INFO - Epoch(train) [12][800/925] lr: 1.7525e-04 eta: 8:30:52 time: 0.5164 data_time: 0.0020 memory: 7815 grad_norm: 738.8642 loss: 424.4573 loss_cls: 150.8980 loss_bbox: 129.7455 loss_dfl: 143.8139 +2024/03/20 22:24:14 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:24:26 - mmengine - INFO - Epoch(train) [12][850/925] lr: 1.7525e-04 eta: 8:30:30 time: 0.4923 data_time: 0.0021 memory: 7722 grad_norm: 714.5764 loss: 417.7900 loss_cls: 148.6344 loss_bbox: 126.5898 loss_dfl: 142.5657 +2024/03/20 22:24:51 - mmengine - INFO - Epoch(train) [12][900/925] lr: 1.7525e-04 eta: 8:30:10 time: 0.5022 data_time: 0.0021 memory: 7989 grad_norm: 770.0916 loss: 418.0148 loss_cls: 146.3904 loss_bbox: 129.3632 loss_dfl: 142.2612 +2024/03/20 22:25:03 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:25:32 - mmengine - INFO - Epoch(train) [13][ 50/925] lr: 1.7278e-04 eta: 8:29:54 time: 0.5605 data_time: 0.0677 memory: 8122 grad_norm: 717.0855 loss: 424.2351 loss_cls: 151.2839 loss_bbox: 130.0710 loss_dfl: 142.8801 +2024/03/20 22:25:56 - mmengine - INFO - Epoch(train) [13][100/925] lr: 1.7278e-04 eta: 8:29:30 time: 0.4887 data_time: 0.0022 memory: 8215 grad_norm: 792.5892 loss: 422.1649 loss_cls: 149.4191 loss_bbox: 129.4560 loss_dfl: 143.2898 +2024/03/20 22:26:22 - mmengine - INFO - Epoch(train) [13][150/925] lr: 1.7278e-04 eta: 8:29:14 time: 0.5160 data_time: 0.0020 memory: 7762 grad_norm: 746.2339 loss: 415.8180 loss_cls: 144.5862 loss_bbox: 128.6806 loss_dfl: 142.5512 +2024/03/20 22:26:47 - mmengine - INFO - Epoch(train) [13][200/925] lr: 1.7278e-04 eta: 8:28:51 time: 0.4909 data_time: 0.0022 memory: 8029 grad_norm: 795.5427 loss: 420.7340 loss_cls: 148.7787 loss_bbox: 128.4450 loss_dfl: 143.5102 +2024/03/20 22:27:12 - mmengine - INFO - Epoch(train) [13][250/925] lr: 1.7278e-04 eta: 8:28:30 time: 0.5015 data_time: 0.0022 memory: 8482 grad_norm: 775.7002 loss: 419.5658 loss_cls: 147.8449 loss_bbox: 128.5926 loss_dfl: 143.1284 +2024/03/20 22:27:37 - mmengine - INFO - Epoch(train) [13][300/925] lr: 1.7278e-04 eta: 8:28:14 time: 0.5142 data_time: 0.0021 memory: 7922 grad_norm: 688.8651 loss: 416.9989 loss_cls: 148.3759 loss_bbox: 127.0228 loss_dfl: 141.6002 +2024/03/20 22:28:02 - mmengine - INFO - Epoch(train) [13][350/925] lr: 1.7278e-04 eta: 8:27:49 time: 0.4854 data_time: 0.0022 memory: 7869 grad_norm: 783.8945 loss: 420.0095 loss_cls: 149.8009 loss_bbox: 128.4563 loss_dfl: 141.7524 +2024/03/20 22:28:27 - mmengine - INFO - Epoch(train) [13][400/925] lr: 1.7278e-04 eta: 8:27:30 time: 0.5074 data_time: 0.0020 memory: 8002 grad_norm: 671.7474 loss: 425.1692 loss_cls: 149.7392 loss_bbox: 131.7470 loss_dfl: 143.6830 +2024/03/20 22:28:52 - mmengine - INFO - Epoch(train) [13][450/925] lr: 1.7278e-04 eta: 8:27:10 time: 0.5032 data_time: 0.0021 memory: 7962 grad_norm: 805.0508 loss: 425.5082 loss_cls: 150.1053 loss_bbox: 130.6886 loss_dfl: 144.7143 +2024/03/20 22:29:17 - mmengine - INFO - Epoch(train) [13][500/925] lr: 1.7278e-04 eta: 8:26:46 time: 0.4878 data_time: 0.0022 memory: 8429 grad_norm: 730.9971 loss: 418.9837 loss_cls: 146.1317 loss_bbox: 130.7039 loss_dfl: 142.1481 +2024/03/20 22:29:43 - mmengine - INFO - Epoch(train) [13][550/925] lr: 1.7278e-04 eta: 8:26:30 time: 0.5194 data_time: 0.0020 memory: 7895 grad_norm: 773.5154 loss: 423.3815 loss_cls: 148.4598 loss_bbox: 131.8759 loss_dfl: 143.0458 +2024/03/20 22:30:08 - mmengine - INFO - Epoch(train) [13][600/925] lr: 1.7278e-04 eta: 8:26:08 time: 0.4968 data_time: 0.0021 memory: 7869 grad_norm: 729.1283 loss: 419.1133 loss_cls: 147.4731 loss_bbox: 129.1897 loss_dfl: 142.4505 +2024/03/20 22:30:33 - mmengine - INFO - Epoch(train) [13][650/925] lr: 1.7278e-04 eta: 8:25:47 time: 0.4989 data_time: 0.0021 memory: 7989 grad_norm: 773.1678 loss: 420.1402 loss_cls: 150.4680 loss_bbox: 126.8888 loss_dfl: 142.7834 +2024/03/20 22:30:58 - mmengine - INFO - Epoch(train) [13][700/925] lr: 1.7278e-04 eta: 8:25:29 time: 0.5137 data_time: 0.0021 memory: 7789 grad_norm: 807.9809 loss: 418.2809 loss_cls: 146.8429 loss_bbox: 128.6135 loss_dfl: 142.8245 +2024/03/20 22:31:23 - mmengine - INFO - Epoch(train) [13][750/925] lr: 1.7278e-04 eta: 8:25:05 time: 0.4889 data_time: 0.0022 memory: 8029 grad_norm: 725.8285 loss: 413.4092 loss_cls: 145.0921 loss_bbox: 126.6514 loss_dfl: 141.6657 +2024/03/20 22:31:48 - mmengine - INFO - Epoch(train) [13][800/925] lr: 1.7278e-04 eta: 8:24:45 time: 0.5033 data_time: 0.0023 memory: 8029 grad_norm: 755.3525 loss: 422.3918 loss_cls: 149.4021 loss_bbox: 129.4120 loss_dfl: 143.5776 +2024/03/20 22:32:13 - mmengine - INFO - Epoch(train) [13][850/925] lr: 1.7278e-04 eta: 8:24:22 time: 0.4942 data_time: 0.0022 memory: 8122 grad_norm: 733.3256 loss: 418.1195 loss_cls: 147.7685 loss_bbox: 128.2790 loss_dfl: 142.0719 +2024/03/20 22:32:38 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:32:38 - mmengine - INFO - Epoch(train) [13][900/925] lr: 1.7278e-04 eta: 8:24:01 time: 0.4991 data_time: 0.0021 memory: 7909 grad_norm: 754.6852 loss: 422.1009 loss_cls: 148.6330 loss_bbox: 129.9467 loss_dfl: 143.5212 +2024/03/20 22:32:49 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:33:18 - mmengine - INFO - Epoch(train) [14][ 50/925] lr: 1.7030e-04 eta: 8:23:42 time: 0.5654 data_time: 0.0630 memory: 8029 grad_norm: 752.3784 loss: 417.0992 loss_cls: 145.2993 loss_bbox: 128.6165 loss_dfl: 143.1834 +2024/03/20 22:33:43 - mmengine - INFO - Epoch(train) [14][100/925] lr: 1.7030e-04 eta: 8:23:19 time: 0.4917 data_time: 0.0021 memory: 7895 grad_norm: 745.6060 loss: 421.6104 loss_cls: 149.2345 loss_bbox: 129.7206 loss_dfl: 142.6553 +2024/03/20 22:34:08 - mmengine - INFO - Epoch(train) [14][150/925] lr: 1.7030e-04 eta: 8:22:58 time: 0.5033 data_time: 0.0021 memory: 8135 grad_norm: 692.8936 loss: 422.2441 loss_cls: 150.4406 loss_bbox: 128.4836 loss_dfl: 143.3199 +2024/03/20 22:34:33 - mmengine - INFO - Epoch(train) [14][200/925] lr: 1.7030e-04 eta: 8:22:38 time: 0.5035 data_time: 0.0021 memory: 7735 grad_norm: 783.2174 loss: 418.2916 loss_cls: 145.5184 loss_bbox: 129.5323 loss_dfl: 143.2409 +2024/03/20 22:34:58 - mmengine - INFO - Epoch(train) [14][250/925] lr: 1.7030e-04 eta: 8:22:14 time: 0.4896 data_time: 0.0021 memory: 7749 grad_norm: 699.8547 loss: 415.7431 loss_cls: 146.3175 loss_bbox: 127.8736 loss_dfl: 141.5520 +2024/03/20 22:35:24 - mmengine - INFO - Epoch(train) [14][300/925] lr: 1.7030e-04 eta: 8:21:57 time: 0.5184 data_time: 0.0021 memory: 7922 grad_norm: 779.9861 loss: 418.8748 loss_cls: 147.3183 loss_bbox: 128.2425 loss_dfl: 143.3140 +2024/03/20 22:35:49 - mmengine - INFO - Epoch(train) [14][350/925] lr: 1.7030e-04 eta: 8:21:37 time: 0.5058 data_time: 0.0020 memory: 7975 grad_norm: 760.8398 loss: 425.6016 loss_cls: 151.3581 loss_bbox: 130.4874 loss_dfl: 143.7562 +2024/03/20 22:36:13 - mmengine - INFO - Epoch(train) [14][400/925] lr: 1.7030e-04 eta: 8:21:13 time: 0.4919 data_time: 0.0020 memory: 7962 grad_norm: 781.3859 loss: 418.4719 loss_cls: 145.8201 loss_bbox: 129.7056 loss_dfl: 142.9463 +2024/03/20 22:36:40 - mmengine - INFO - Epoch(train) [14][450/925] lr: 1.7030e-04 eta: 8:20:58 time: 0.5241 data_time: 0.0020 memory: 8069 grad_norm: 691.7017 loss: 417.8673 loss_cls: 145.4750 loss_bbox: 129.3792 loss_dfl: 143.0131 +2024/03/20 22:37:04 - mmengine - INFO - Epoch(train) [14][500/925] lr: 1.7030e-04 eta: 8:20:34 time: 0.4897 data_time: 0.0020 memory: 7869 grad_norm: 696.1082 loss: 421.3921 loss_cls: 147.9040 loss_bbox: 130.6268 loss_dfl: 142.8614 +2024/03/20 22:37:30 - mmengine - INFO - Epoch(train) [14][550/925] lr: 1.7030e-04 eta: 8:20:14 time: 0.5079 data_time: 0.0021 memory: 8002 grad_norm: 722.4796 loss: 422.1064 loss_cls: 148.7958 loss_bbox: 130.9995 loss_dfl: 142.3111 +2024/03/20 22:37:55 - mmengine - INFO - Epoch(train) [14][600/925] lr: 1.7030e-04 eta: 8:19:54 time: 0.5058 data_time: 0.0022 memory: 7922 grad_norm: 750.1148 loss: 419.6162 loss_cls: 148.1881 loss_bbox: 128.6520 loss_dfl: 142.7761 +2024/03/20 22:38:19 - mmengine - INFO - Epoch(train) [14][650/925] lr: 1.7030e-04 eta: 8:19:27 time: 0.4782 data_time: 0.0020 memory: 7855 grad_norm: 793.9554 loss: 417.6434 loss_cls: 146.3497 loss_bbox: 128.3541 loss_dfl: 142.9397 +2024/03/20 22:38:44 - mmengine - INFO - Epoch(train) [14][700/925] lr: 1.7030e-04 eta: 8:19:07 time: 0.5076 data_time: 0.0020 memory: 7882 grad_norm: 796.9580 loss: 417.0959 loss_cls: 145.5945 loss_bbox: 129.1861 loss_dfl: 142.3152 +2024/03/20 22:39:09 - mmengine - INFO - Epoch(train) [14][750/925] lr: 1.7030e-04 eta: 8:18:44 time: 0.4958 data_time: 0.0020 memory: 8055 grad_norm: 769.2309 loss: 420.0440 loss_cls: 148.1842 loss_bbox: 128.4966 loss_dfl: 143.3632 +2024/03/20 22:39:33 - mmengine - INFO - Epoch(train) [14][800/925] lr: 1.7030e-04 eta: 8:18:16 time: 0.4750 data_time: 0.0021 memory: 8522 grad_norm: 791.4038 loss: 417.4329 loss_cls: 145.4088 loss_bbox: 129.7633 loss_dfl: 142.2608 +2024/03/20 22:39:58 - mmengine - INFO - Epoch(train) [14][850/925] lr: 1.7030e-04 eta: 8:17:57 time: 0.5086 data_time: 0.0020 memory: 7962 grad_norm: 694.1957 loss: 421.4178 loss_cls: 149.8509 loss_bbox: 128.3059 loss_dfl: 143.2610 +2024/03/20 22:40:23 - mmengine - INFO - Epoch(train) [14][900/925] lr: 1.7030e-04 eta: 8:17:34 time: 0.4979 data_time: 0.0020 memory: 8042 grad_norm: 776.6362 loss: 419.4650 loss_cls: 146.3615 loss_bbox: 130.8333 loss_dfl: 142.2702 +2024/03/20 22:40:35 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:41:02 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:41:02 - mmengine - INFO - Epoch(train) [15][ 50/925] lr: 1.6783e-04 eta: 8:17:08 time: 0.5455 data_time: 0.0643 memory: 7775 grad_norm: 784.8804 loss: 408.2830 loss_cls: 140.1466 loss_bbox: 127.6276 loss_dfl: 140.5088 +2024/03/20 22:41:28 - mmengine - INFO - Epoch(train) [15][100/925] lr: 1.6783e-04 eta: 8:16:50 time: 0.5163 data_time: 0.0019 memory: 7909 grad_norm: 743.7313 loss: 420.4181 loss_cls: 147.0673 loss_bbox: 129.7124 loss_dfl: 143.6383 +2024/03/20 22:41:52 - mmengine - INFO - Epoch(train) [15][150/925] lr: 1.6783e-04 eta: 8:16:22 time: 0.4768 data_time: 0.0020 memory: 7775 grad_norm: 703.1275 loss: 420.4064 loss_cls: 147.4389 loss_bbox: 129.9358 loss_dfl: 143.0317 +2024/03/20 22:42:18 - mmengine - INFO - Epoch(train) [15][200/925] lr: 1.6783e-04 eta: 8:16:03 time: 0.5124 data_time: 0.0021 memory: 7922 grad_norm: 754.8496 loss: 411.7965 loss_cls: 142.9425 loss_bbox: 127.7828 loss_dfl: 141.0712 +2024/03/20 22:42:43 - mmengine - INFO - Epoch(train) [15][250/925] lr: 1.6783e-04 eta: 8:15:42 time: 0.5052 data_time: 0.0020 memory: 8015 grad_norm: 744.9903 loss: 410.3651 loss_cls: 141.3877 loss_bbox: 126.8636 loss_dfl: 142.1139 +2024/03/20 22:43:07 - mmengine - INFO - Epoch(train) [15][300/925] lr: 1.6783e-04 eta: 8:15:17 time: 0.4828 data_time: 0.0021 memory: 7815 grad_norm: 725.3621 loss: 415.5899 loss_cls: 145.9337 loss_bbox: 127.0745 loss_dfl: 142.5817 +2024/03/20 22:43:33 - mmengine - INFO - Epoch(train) [15][350/925] lr: 1.6783e-04 eta: 8:14:59 time: 0.5186 data_time: 0.0021 memory: 7989 grad_norm: 714.3966 loss: 421.7593 loss_cls: 148.4161 loss_bbox: 130.0950 loss_dfl: 143.2482 +2024/03/20 22:43:58 - mmengine - INFO - Epoch(train) [15][400/925] lr: 1.6783e-04 eta: 8:14:36 time: 0.4951 data_time: 0.0022 memory: 8295 grad_norm: 789.6069 loss: 413.9671 loss_cls: 144.4387 loss_bbox: 128.1817 loss_dfl: 141.3467 +2024/03/20 22:44:22 - mmengine - INFO - Epoch(train) [15][450/925] lr: 1.6783e-04 eta: 8:14:11 time: 0.4875 data_time: 0.0021 memory: 7869 grad_norm: 744.2172 loss: 422.2764 loss_cls: 149.4316 loss_bbox: 129.4335 loss_dfl: 143.4113 +2024/03/20 22:44:48 - mmengine - INFO - Epoch(train) [15][500/925] lr: 1.6783e-04 eta: 8:13:53 time: 0.5207 data_time: 0.0020 memory: 7949 grad_norm: 802.3542 loss: 420.3797 loss_cls: 145.7722 loss_bbox: 130.7259 loss_dfl: 143.8816 +2024/03/20 22:45:13 - mmengine - INFO - Epoch(train) [15][550/925] lr: 1.6783e-04 eta: 8:13:30 time: 0.4923 data_time: 0.0022 memory: 7762 grad_norm: 714.4640 loss: 414.3444 loss_cls: 144.7618 loss_bbox: 128.2725 loss_dfl: 141.3101 +2024/03/20 22:45:38 - mmengine - INFO - Epoch(train) [15][600/925] lr: 1.6783e-04 eta: 8:13:07 time: 0.4965 data_time: 0.0021 memory: 8042 grad_norm: inf loss: 409.9399 loss_cls: 142.6769 loss_bbox: 126.1221 loss_dfl: 141.1409 +2024/03/20 22:46:04 - mmengine - INFO - Epoch(train) [15][650/925] lr: 1.6783e-04 eta: 8:12:49 time: 0.5188 data_time: 0.0019 memory: 7789 grad_norm: 755.5542 loss: 420.4873 loss_cls: 146.9144 loss_bbox: 130.7463 loss_dfl: 142.8266 +2024/03/20 22:46:28 - mmengine - INFO - Epoch(train) [15][700/925] lr: 1.6783e-04 eta: 8:12:24 time: 0.4894 data_time: 0.0018 memory: 8015 grad_norm: 772.5981 loss: 419.8255 loss_cls: 147.8483 loss_bbox: 129.1257 loss_dfl: 142.8515 +2024/03/20 22:46:53 - mmengine - INFO - Epoch(train) [15][750/925] lr: 1.6783e-04 eta: 8:12:03 time: 0.5035 data_time: 0.0019 memory: 7869 grad_norm: 713.3227 loss: 413.4546 loss_cls: 143.3016 loss_bbox: 128.3577 loss_dfl: 141.7953 +2024/03/20 22:47:18 - mmengine - INFO - Epoch(train) [15][800/925] lr: 1.6783e-04 eta: 8:11:40 time: 0.4969 data_time: 0.0022 memory: 7895 grad_norm: 713.1504 loss: 408.7397 loss_cls: 141.9496 loss_bbox: 126.2243 loss_dfl: 140.5658 +2024/03/20 22:47:43 - mmengine - INFO - Epoch(train) [15][850/925] lr: 1.6783e-04 eta: 8:11:18 time: 0.5015 data_time: 0.0021 memory: 7749 grad_norm: 758.1148 loss: 423.3729 loss_cls: 148.8642 loss_bbox: 130.7539 loss_dfl: 143.7548 +2024/03/20 22:48:09 - mmengine - INFO - Epoch(train) [15][900/925] lr: 1.6783e-04 eta: 8:10:58 time: 0.5114 data_time: 0.0021 memory: 7935 grad_norm: 747.9294 loss: 419.8519 loss_cls: 149.0820 loss_bbox: 127.7712 loss_dfl: 142.9987 +2024/03/20 22:48:21 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:48:21 - mmengine - INFO - Saving checkpoint at 15 epochs +2024/03/20 22:48:30 - mmengine - INFO - Epoch(val) [15][ 50/625] eta: 0:00:19 time: 0.0346 data_time: 0.0008 memory: 8135 +2024/03/20 22:48:32 - mmengine - INFO - Epoch(val) [15][100/625] eta: 0:00:18 time: 0.0366 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:34 - mmengine - INFO - Epoch(val) [15][150/625] eta: 0:00:17 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:35 - mmengine - INFO - Epoch(val) [15][200/625] eta: 0:00:15 time: 0.0359 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:37 - mmengine - INFO - Epoch(val) [15][250/625] eta: 0:00:13 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:39 - mmengine - INFO - Epoch(val) [15][300/625] eta: 0:00:11 time: 0.0349 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:41 - mmengine - INFO - Epoch(val) [15][350/625] eta: 0:00:09 time: 0.0362 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:43 - mmengine - INFO - Epoch(val) [15][400/625] eta: 0:00:08 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:44 - mmengine - INFO - Epoch(val) [15][450/625] eta: 0:00:06 time: 0.0344 data_time: 0.0003 memory: 1244 +2024/03/20 22:48:46 - mmengine - INFO - Epoch(val) [15][500/625] eta: 0:00:04 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/20 22:48:47 - mmengine - INFO - Epoch(val) [15][550/625] eta: 0:00:02 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/20 22:48:49 - mmengine - INFO - Epoch(val) [15][600/625] eta: 0:00:00 time: 0.0289 data_time: 0.0002 memory: 1244 +2024/03/20 22:49:02 - mmengine - INFO - Evaluating bbox... +2024/03/20 22:50:25 - mmengine - INFO - bbox_mAP_copypaste: 0.485 0.648 0.529 0.300 0.535 0.633 +2024/03/20 22:50:27 - mmengine - INFO - Epoch(val) [15][625/625] coco/bbox_mAP: 0.4850 coco/bbox_mAP_50: 0.6480 coco/bbox_mAP_75: 0.5290 coco/bbox_mAP_s: 0.3000 coco/bbox_mAP_m: 0.5350 coco/bbox_mAP_l: 0.6330 data_time: 0.0002 time: 0.0284 +2024/03/20 22:50:54 - mmengine - INFO - Epoch(train) [16][ 50/925] lr: 1.6535e-04 eta: 8:10:30 time: 0.5396 data_time: 0.0614 memory: 8189 grad_norm: 715.7845 loss: 417.9145 loss_cls: 145.2400 loss_bbox: 129.6646 loss_dfl: 143.0099 +2024/03/20 22:51:19 - mmengine - INFO - Epoch(train) [16][100/925] lr: 1.6535e-04 eta: 8:10:07 time: 0.4984 data_time: 0.0020 memory: 7935 grad_norm: 723.5393 loss: 417.3039 loss_cls: 145.0698 loss_bbox: 128.9989 loss_dfl: 143.2352 +2024/03/20 22:51:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:51:44 - mmengine - INFO - Epoch(train) [16][150/925] lr: 1.6535e-04 eta: 8:09:43 time: 0.4930 data_time: 0.0022 memory: 7895 grad_norm: 698.4452 loss: 428.8496 loss_cls: 152.2550 loss_bbox: 132.1066 loss_dfl: 144.4881 +2024/03/20 22:52:08 - mmengine - INFO - Epoch(train) [16][200/925] lr: 1.6535e-04 eta: 8:09:17 time: 0.4836 data_time: 0.0021 memory: 7922 grad_norm: 755.7577 loss: 415.8135 loss_cls: 146.1654 loss_bbox: 127.5918 loss_dfl: 142.0562 +2024/03/20 22:52:34 - mmengine - INFO - Epoch(train) [16][250/925] lr: 1.6535e-04 eta: 8:08:57 time: 0.5093 data_time: 0.0021 memory: 8389 grad_norm: 704.2553 loss: 421.4375 loss_cls: 147.6692 loss_bbox: 130.2832 loss_dfl: 143.4850 +2024/03/20 22:52:58 - mmengine - INFO - Epoch(train) [16][300/925] lr: 1.6535e-04 eta: 8:08:33 time: 0.4916 data_time: 0.0021 memory: 7882 grad_norm: 807.8013 loss: 417.9372 loss_cls: 146.7009 loss_bbox: 128.3758 loss_dfl: 142.8606 +2024/03/20 22:53:23 - mmengine - INFO - Epoch(train) [16][350/925] lr: 1.6535e-04 eta: 8:08:09 time: 0.4925 data_time: 0.0021 memory: 8069 grad_norm: 809.7760 loss: 421.0023 loss_cls: 148.7288 loss_bbox: 129.4065 loss_dfl: 142.8671 +2024/03/20 22:53:49 - mmengine - INFO - Epoch(train) [16][400/925] lr: 1.6535e-04 eta: 8:07:52 time: 0.5258 data_time: 0.0021 memory: 8042 grad_norm: 748.0435 loss: 418.5560 loss_cls: 146.7323 loss_bbox: 128.7558 loss_dfl: 143.0679 +2024/03/20 22:54:14 - mmengine - INFO - Epoch(train) [16][450/925] lr: 1.6535e-04 eta: 8:07:27 time: 0.4894 data_time: 0.0020 memory: 7869 grad_norm: 669.8650 loss: 414.3377 loss_cls: 145.0033 loss_bbox: 128.4521 loss_dfl: 140.8823 +2024/03/20 22:54:38 - mmengine - INFO - Epoch(train) [16][500/925] lr: 1.6535e-04 eta: 8:07:04 time: 0.4955 data_time: 0.0021 memory: 7949 grad_norm: 711.9005 loss: 422.6583 loss_cls: 147.9672 loss_bbox: 130.2453 loss_dfl: 144.4458 +2024/03/20 22:55:05 - mmengine - INFO - Epoch(train) [16][550/925] lr: 1.6535e-04 eta: 8:06:45 time: 0.5204 data_time: 0.0021 memory: 7802 grad_norm: 723.2789 loss: 417.9747 loss_cls: 147.6504 loss_bbox: 127.6426 loss_dfl: 142.6817 +2024/03/20 22:55:29 - mmengine - INFO - Epoch(train) [16][600/925] lr: 1.6535e-04 eta: 8:06:20 time: 0.4847 data_time: 0.0022 memory: 8055 grad_norm: 759.2645 loss: 415.1076 loss_cls: 145.3206 loss_bbox: 128.0024 loss_dfl: 141.7846 +2024/03/20 22:55:54 - mmengine - INFO - Epoch(train) [16][650/925] lr: 1.6535e-04 eta: 8:05:57 time: 0.4999 data_time: 0.0021 memory: 7989 grad_norm: 754.4269 loss: 412.7235 loss_cls: 143.1582 loss_bbox: 128.1009 loss_dfl: 141.4643 +2024/03/20 22:56:19 - mmengine - INFO - Epoch(train) [16][700/925] lr: 1.6535e-04 eta: 8:05:36 time: 0.5053 data_time: 0.0022 memory: 7722 grad_norm: 681.4992 loss: 415.6778 loss_cls: 144.7215 loss_bbox: 128.6296 loss_dfl: 142.3268 +2024/03/20 22:56:44 - mmengine - INFO - Epoch(train) [16][750/925] lr: 1.6535e-04 eta: 8:05:11 time: 0.4901 data_time: 0.0021 memory: 7989 grad_norm: 751.3753 loss: 415.8352 loss_cls: 146.8609 loss_bbox: 127.4445 loss_dfl: 141.5298 +2024/03/20 22:57:09 - mmengine - INFO - Epoch(train) [16][800/925] lr: 1.6535e-04 eta: 8:04:52 time: 0.5169 data_time: 0.0021 memory: 7975 grad_norm: 757.7255 loss: 415.6368 loss_cls: 145.6917 loss_bbox: 127.7672 loss_dfl: 142.1779 +2024/03/20 22:57:34 - mmengine - INFO - Epoch(train) [16][850/925] lr: 1.6535e-04 eta: 8:04:29 time: 0.4952 data_time: 0.0021 memory: 7869 grad_norm: 718.1134 loss: 420.0714 loss_cls: 147.4949 loss_bbox: 129.7904 loss_dfl: 142.7860 +2024/03/20 22:57:59 - mmengine - INFO - Epoch(train) [16][900/925] lr: 1.6535e-04 eta: 8:04:05 time: 0.4973 data_time: 0.0021 memory: 7909 grad_norm: 683.9073 loss: 417.1518 loss_cls: 145.4331 loss_bbox: 128.4779 loss_dfl: 143.2409 +2024/03/20 22:58:11 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:58:39 - mmengine - INFO - Epoch(train) [17][ 50/925] lr: 1.6287e-04 eta: 8:03:40 time: 0.5474 data_time: 0.0661 memory: 8349 grad_norm: 828.7248 loss: 417.9415 loss_cls: 145.6707 loss_bbox: 128.8920 loss_dfl: 143.3788 +2024/03/20 22:59:04 - mmengine - INFO - Epoch(train) [17][100/925] lr: 1.6287e-04 eta: 8:03:16 time: 0.4930 data_time: 0.0021 memory: 7815 grad_norm: 699.3906 loss: 412.1667 loss_cls: 143.2301 loss_bbox: 127.2254 loss_dfl: 141.7113 +2024/03/20 22:59:30 - mmengine - INFO - Epoch(train) [17][150/925] lr: 1.6287e-04 eta: 8:02:56 time: 0.5177 data_time: 0.0021 memory: 7935 grad_norm: 794.0676 loss: 413.1655 loss_cls: 142.7412 loss_bbox: 128.4405 loss_dfl: 141.9839 +2024/03/20 22:59:54 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 22:59:54 - mmengine - INFO - Epoch(train) [17][200/925] lr: 1.6287e-04 eta: 8:02:31 time: 0.4867 data_time: 0.0021 memory: 7922 grad_norm: 713.0349 loss: 417.4490 loss_cls: 146.3935 loss_bbox: 129.5813 loss_dfl: 141.4741 +2024/03/20 23:00:19 - mmengine - INFO - Epoch(train) [17][250/925] lr: 1.6287e-04 eta: 8:02:08 time: 0.4962 data_time: 0.0021 memory: 7842 grad_norm: 776.3170 loss: 414.9519 loss_cls: 146.0270 loss_bbox: 127.2594 loss_dfl: 141.6655 +2024/03/20 23:00:45 - mmengine - INFO - Epoch(train) [17][300/925] lr: 1.6287e-04 eta: 8:01:49 time: 0.5228 data_time: 0.0021 memory: 8042 grad_norm: 747.2379 loss: 411.8212 loss_cls: 144.0937 loss_bbox: 127.4856 loss_dfl: 140.2420 +2024/03/20 23:01:09 - mmengine - INFO - Epoch(train) [17][350/925] lr: 1.6287e-04 eta: 8:01:23 time: 0.4804 data_time: 0.0021 memory: 7842 grad_norm: 746.1266 loss: 410.9800 loss_cls: 142.7890 loss_bbox: 126.7929 loss_dfl: 141.3981 +2024/03/20 23:01:34 - mmengine - INFO - Epoch(train) [17][400/925] lr: 1.6287e-04 eta: 8:00:59 time: 0.4953 data_time: 0.0021 memory: 7989 grad_norm: 699.8921 loss: 414.9477 loss_cls: 143.7495 loss_bbox: 128.5846 loss_dfl: 142.6137 +2024/03/20 23:01:59 - mmengine - INFO - Epoch(train) [17][450/925] lr: 1.6287e-04 eta: 8:00:38 time: 0.5091 data_time: 0.0021 memory: 8015 grad_norm: 751.5219 loss: 415.1727 loss_cls: 144.6616 loss_bbox: 129.1395 loss_dfl: 141.3716 +2024/03/20 23:02:23 - mmengine - INFO - Epoch(train) [17][500/925] lr: 1.6287e-04 eta: 8:00:12 time: 0.4800 data_time: 0.0022 memory: 7935 grad_norm: 721.4935 loss: 417.7113 loss_cls: 146.1110 loss_bbox: 129.3340 loss_dfl: 142.2663 +2024/03/20 23:02:49 - mmengine - INFO - Epoch(train) [17][550/925] lr: 1.6287e-04 eta: 7:59:50 time: 0.5058 data_time: 0.0021 memory: 7989 grad_norm: 787.5514 loss: 415.9592 loss_cls: 144.5721 loss_bbox: 128.8627 loss_dfl: 142.5244 +2024/03/20 23:03:14 - mmengine - INFO - Epoch(train) [17][600/925] lr: 1.6287e-04 eta: 7:59:28 time: 0.5046 data_time: 0.0021 memory: 8242 grad_norm: 672.2573 loss: 413.3861 loss_cls: 143.9386 loss_bbox: 128.0917 loss_dfl: 141.3558 +2024/03/20 23:03:38 - mmengine - INFO - Epoch(train) [17][650/925] lr: 1.6287e-04 eta: 7:59:03 time: 0.4877 data_time: 0.0022 memory: 7829 grad_norm: 679.5549 loss: 417.0575 loss_cls: 144.6203 loss_bbox: 129.5113 loss_dfl: 142.9259 +2024/03/20 23:04:04 - mmengine - INFO - Epoch(train) [17][700/925] lr: 1.6287e-04 eta: 7:58:42 time: 0.5094 data_time: 0.0021 memory: 7895 grad_norm: 713.0346 loss: 416.7594 loss_cls: 146.2066 loss_bbox: 128.1768 loss_dfl: 142.3761 +2024/03/20 23:04:28 - mmengine - INFO - Epoch(train) [17][750/925] lr: 1.6287e-04 eta: 7:58:17 time: 0.4896 data_time: 0.0023 memory: 8189 grad_norm: 720.1060 loss: 409.7883 loss_cls: 143.6837 loss_bbox: 125.7898 loss_dfl: 140.3148 +2024/03/20 23:04:53 - mmengine - INFO - Epoch(train) [17][800/925] lr: 1.6287e-04 eta: 7:57:54 time: 0.5002 data_time: 0.0021 memory: 8002 grad_norm: 686.2153 loss: 414.4742 loss_cls: 142.8909 loss_bbox: 128.8093 loss_dfl: 142.7740 +2024/03/20 23:05:19 - mmengine - INFO - Epoch(train) [17][850/925] lr: 1.6287e-04 eta: 7:57:34 time: 0.5162 data_time: 0.0021 memory: 8002 grad_norm: 720.8103 loss: 408.8856 loss_cls: 141.4661 loss_bbox: 126.2587 loss_dfl: 141.1609 +2024/03/20 23:05:43 - mmengine - INFO - Epoch(train) [17][900/925] lr: 1.6287e-04 eta: 7:57:08 time: 0.4816 data_time: 0.0021 memory: 8015 grad_norm: 732.5908 loss: 411.1723 loss_cls: 142.0997 loss_bbox: 126.5959 loss_dfl: 142.4767 +2024/03/20 23:05:55 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:06:24 - mmengine - INFO - Epoch(train) [18][ 50/925] lr: 1.6040e-04 eta: 7:56:46 time: 0.5749 data_time: 0.0631 memory: 7949 grad_norm: 696.5681 loss: 419.3166 loss_cls: 144.7330 loss_bbox: 131.0939 loss_dfl: 143.4897 +2024/03/20 23:06:49 - mmengine - INFO - Epoch(train) [18][100/925] lr: 1.6040e-04 eta: 7:56:20 time: 0.4888 data_time: 0.0022 memory: 8015 grad_norm: 715.5526 loss: 413.6342 loss_cls: 144.8882 loss_bbox: 126.7407 loss_dfl: 142.0053 +2024/03/20 23:07:14 - mmengine - INFO - Epoch(train) [18][150/925] lr: 1.6040e-04 eta: 7:55:58 time: 0.5010 data_time: 0.0021 memory: 8295 grad_norm: 695.5595 loss: 406.9116 loss_cls: 140.5801 loss_bbox: 125.0961 loss_dfl: 141.2354 +2024/03/20 23:07:40 - mmengine - INFO - Epoch(train) [18][200/925] lr: 1.6040e-04 eta: 7:55:39 time: 0.5218 data_time: 0.0022 memory: 7735 grad_norm: 763.0065 loss: 420.8859 loss_cls: 148.3733 loss_bbox: 130.5473 loss_dfl: 141.9653 +2024/03/20 23:08:05 - mmengine - INFO - Epoch(train) [18][250/925] lr: 1.6040e-04 eta: 7:55:14 time: 0.4898 data_time: 0.0020 memory: 8255 grad_norm: 826.6882 loss: 418.9659 loss_cls: 147.0614 loss_bbox: 129.4373 loss_dfl: 142.4673 +2024/03/20 23:08:17 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:08:30 - mmengine - INFO - Epoch(train) [18][300/925] lr: 1.6040e-04 eta: 7:54:52 time: 0.5047 data_time: 0.0022 memory: 7775 grad_norm: 752.8709 loss: 414.7259 loss_cls: 144.0673 loss_bbox: 129.0811 loss_dfl: 141.5775 +2024/03/20 23:08:55 - mmengine - INFO - Epoch(train) [18][350/925] lr: 1.6040e-04 eta: 7:54:30 time: 0.5051 data_time: 0.0019 memory: 8082 grad_norm: inf loss: 414.0910 loss_cls: 145.0393 loss_bbox: 127.3464 loss_dfl: 141.7053 +2024/03/20 23:09:20 - mmengine - INFO - Epoch(train) [18][400/925] lr: 1.6040e-04 eta: 7:54:04 time: 0.4886 data_time: 0.0021 memory: 7975 grad_norm: 717.7704 loss: 418.3249 loss_cls: 147.7985 loss_bbox: 129.3416 loss_dfl: 141.1848 +2024/03/20 23:09:45 - mmengine - INFO - Epoch(train) [18][450/925] lr: 1.6040e-04 eta: 7:53:43 time: 0.5085 data_time: 0.0022 memory: 8042 grad_norm: 736.7247 loss: 406.7600 loss_cls: 140.5747 loss_bbox: 125.6130 loss_dfl: 140.5723 +2024/03/20 23:10:10 - mmengine - INFO - Epoch(train) [18][500/925] lr: 1.6040e-04 eta: 7:53:19 time: 0.4952 data_time: 0.0020 memory: 7895 grad_norm: 789.5251 loss: 415.3630 loss_cls: 143.2073 loss_bbox: 129.4273 loss_dfl: 142.7285 +2024/03/20 23:10:35 - mmengine - INFO - Epoch(train) [18][550/925] lr: 1.6040e-04 eta: 7:52:57 time: 0.5064 data_time: 0.0020 memory: 8242 grad_norm: 668.3918 loss: 415.2881 loss_cls: 145.8324 loss_bbox: 126.5586 loss_dfl: 142.8972 +2024/03/20 23:11:01 - mmengine - INFO - Epoch(train) [18][600/925] lr: 1.6040e-04 eta: 7:52:35 time: 0.5077 data_time: 0.0021 memory: 8069 grad_norm: 756.1732 loss: 413.6510 loss_cls: 143.1358 loss_bbox: 128.6954 loss_dfl: 141.8198 +2024/03/20 23:11:25 - mmengine - INFO - Epoch(train) [18][650/925] lr: 1.6040e-04 eta: 7:52:10 time: 0.4875 data_time: 0.0022 memory: 7949 grad_norm: 785.3800 loss: 406.4285 loss_cls: 139.8989 loss_bbox: 125.7554 loss_dfl: 140.7743 +2024/03/20 23:11:50 - mmengine - INFO - Epoch(train) [18][700/925] lr: 1.6040e-04 eta: 7:51:48 time: 0.5060 data_time: 0.0022 memory: 7895 grad_norm: 706.1379 loss: 410.4032 loss_cls: 140.2351 loss_bbox: 128.2841 loss_dfl: 141.8839 +2024/03/20 23:12:16 - mmengine - INFO - Epoch(train) [18][750/925] lr: 1.6040e-04 eta: 7:51:26 time: 0.5079 data_time: 0.0022 memory: 7842 grad_norm: 736.7242 loss: 414.7078 loss_cls: 145.2568 loss_bbox: 127.0516 loss_dfl: 142.3994 +2024/03/20 23:12:40 - mmengine - INFO - Epoch(train) [18][800/925] lr: 1.6040e-04 eta: 7:51:02 time: 0.4949 data_time: 0.0022 memory: 8375 grad_norm: 747.2373 loss: 414.5607 loss_cls: 142.8299 loss_bbox: 129.7205 loss_dfl: 142.0103 +2024/03/20 23:13:06 - mmengine - INFO - Epoch(train) [18][850/925] lr: 1.6040e-04 eta: 7:50:41 time: 0.5111 data_time: 0.0020 memory: 7975 grad_norm: 714.3755 loss: 418.2492 loss_cls: 146.8853 loss_bbox: 129.3355 loss_dfl: 142.0284 +2024/03/20 23:13:31 - mmengine - INFO - Epoch(train) [18][900/925] lr: 1.6040e-04 eta: 7:50:18 time: 0.5006 data_time: 0.0020 memory: 7909 grad_norm: 751.2201 loss: 414.7881 loss_cls: 144.1635 loss_bbox: 127.2076 loss_dfl: 143.4170 +2024/03/20 23:13:42 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:14:11 - mmengine - INFO - Epoch(train) [19][ 50/925] lr: 1.5793e-04 eta: 7:49:50 time: 0.5719 data_time: 0.0671 memory: 7975 grad_norm: 723.4043 loss: 420.7398 loss_cls: 147.6580 loss_bbox: 129.2118 loss_dfl: 143.8701 +2024/03/20 23:14:37 - mmengine - INFO - Epoch(train) [19][100/925] lr: 1.5793e-04 eta: 7:49:29 time: 0.5082 data_time: 0.0021 memory: 7829 grad_norm: 722.4217 loss: 415.6967 loss_cls: 145.6617 loss_bbox: 127.4704 loss_dfl: 142.5645 +2024/03/20 23:15:01 - mmengine - INFO - Epoch(train) [19][150/925] lr: 1.5793e-04 eta: 7:49:03 time: 0.4839 data_time: 0.0022 memory: 8015 grad_norm: 761.9915 loss: 416.2079 loss_cls: 145.8834 loss_bbox: 129.0577 loss_dfl: 141.2669 +2024/03/20 23:15:27 - mmengine - INFO - Epoch(train) [19][200/925] lr: 1.5793e-04 eta: 7:48:43 time: 0.5224 data_time: 0.0020 memory: 8322 grad_norm: 750.7482 loss: 410.7527 loss_cls: 143.2587 loss_bbox: 125.7578 loss_dfl: 141.7362 +2024/03/20 23:15:53 - mmengine - INFO - Epoch(train) [19][250/925] lr: 1.5793e-04 eta: 7:48:23 time: 0.5213 data_time: 0.0022 memory: 7882 grad_norm: 800.3489 loss: 409.6611 loss_cls: 143.2332 loss_bbox: 124.9826 loss_dfl: 141.4454 +2024/03/20 23:16:17 - mmengine - INFO - Epoch(train) [19][300/925] lr: 1.5793e-04 eta: 7:47:57 time: 0.4786 data_time: 0.0022 memory: 8189 grad_norm: 702.0853 loss: 414.6111 loss_cls: 145.4751 loss_bbox: 127.2475 loss_dfl: 141.8885 +2024/03/20 23:16:43 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:16:43 - mmengine - INFO - Epoch(train) [19][350/925] lr: 1.5793e-04 eta: 7:47:36 time: 0.5186 data_time: 0.0022 memory: 8002 grad_norm: 729.0948 loss: 410.7006 loss_cls: 141.7532 loss_bbox: 127.5256 loss_dfl: 141.4217 +2024/03/20 23:17:08 - mmengine - INFO - Epoch(train) [19][400/925] lr: 1.5793e-04 eta: 7:47:13 time: 0.4983 data_time: 0.0022 memory: 7882 grad_norm: 731.2734 loss: 414.4781 loss_cls: 143.8224 loss_bbox: 127.9103 loss_dfl: 142.7455 +2024/03/20 23:17:33 - mmengine - INFO - Epoch(train) [19][450/925] lr: 1.5793e-04 eta: 7:46:49 time: 0.4998 data_time: 0.0021 memory: 7829 grad_norm: 709.8738 loss: 418.2488 loss_cls: 146.5459 loss_bbox: 128.5981 loss_dfl: 143.1048 +2024/03/20 23:17:58 - mmengine - INFO - Epoch(train) [19][500/925] lr: 1.5793e-04 eta: 7:46:27 time: 0.5046 data_time: 0.0021 memory: 7882 grad_norm: 724.5287 loss: 408.3607 loss_cls: 139.4989 loss_bbox: 127.3327 loss_dfl: 141.5291 +2024/03/20 23:18:23 - mmengine - INFO - Epoch(train) [19][550/925] lr: 1.5793e-04 eta: 7:46:03 time: 0.4965 data_time: 0.0022 memory: 8269 grad_norm: 768.1148 loss: 414.7213 loss_cls: 142.9765 loss_bbox: 129.1075 loss_dfl: 142.6373 +2024/03/20 23:18:48 - mmengine - INFO - Epoch(train) [19][600/925] lr: 1.5793e-04 eta: 7:45:41 time: 0.5097 data_time: 0.0021 memory: 7842 grad_norm: 762.8245 loss: 419.6182 loss_cls: 146.2315 loss_bbox: 130.0799 loss_dfl: 143.3068 +2024/03/20 23:19:14 - mmengine - INFO - Epoch(train) [19][650/925] lr: 1.5793e-04 eta: 7:45:19 time: 0.5048 data_time: 0.0021 memory: 7842 grad_norm: 770.5539 loss: 412.1683 loss_cls: 143.0527 loss_bbox: 127.2474 loss_dfl: 141.8682 +2024/03/20 23:19:38 - mmengine - INFO - Epoch(train) [19][700/925] lr: 1.5793e-04 eta: 7:44:54 time: 0.4940 data_time: 0.0021 memory: 7975 grad_norm: 722.3792 loss: 413.4058 loss_cls: 144.0649 loss_bbox: 127.9130 loss_dfl: 141.4280 +2024/03/20 23:20:04 - mmengine - INFO - Epoch(train) [19][750/925] lr: 1.5793e-04 eta: 7:44:32 time: 0.5098 data_time: 0.0022 memory: 7869 grad_norm: 673.4083 loss: 409.3173 loss_cls: 142.2112 loss_bbox: 126.4385 loss_dfl: 140.6676 +2024/03/20 23:20:29 - mmengine - INFO - Epoch(train) [19][800/925] lr: 1.5793e-04 eta: 7:44:10 time: 0.5044 data_time: 0.0021 memory: 7709 grad_norm: 682.9226 loss: 414.8059 loss_cls: 144.5171 loss_bbox: 128.2422 loss_dfl: 142.0467 +2024/03/20 23:20:54 - mmengine - INFO - Epoch(train) [19][850/925] lr: 1.5793e-04 eta: 7:43:45 time: 0.4943 data_time: 0.0022 memory: 7962 grad_norm: 692.8714 loss: 411.2289 loss_cls: 145.3021 loss_bbox: 124.9204 loss_dfl: 141.0064 +2024/03/20 23:21:20 - mmengine - INFO - Epoch(train) [19][900/925] lr: 1.5793e-04 eta: 7:43:25 time: 0.5164 data_time: 0.0021 memory: 8082 grad_norm: 797.8780 loss: 410.9115 loss_cls: 140.9209 loss_bbox: 128.6011 loss_dfl: 141.3895 +2024/03/20 23:21:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:21:59 - mmengine - INFO - Epoch(train) [20][ 50/925] lr: 1.5545e-04 eta: 7:42:53 time: 0.5314 data_time: 0.0528 memory: 7749 grad_norm: 761.0663 loss: 406.2733 loss_cls: 141.0726 loss_bbox: 124.1479 loss_dfl: 141.0528 +2024/03/20 23:22:25 - mmengine - INFO - Epoch(train) [20][100/925] lr: 1.5545e-04 eta: 7:42:33 time: 0.5186 data_time: 0.0023 memory: 8042 grad_norm: 704.2792 loss: 414.7500 loss_cls: 146.0478 loss_bbox: 127.5563 loss_dfl: 141.1460 +2024/03/20 23:22:50 - mmengine - INFO - Epoch(train) [20][150/925] lr: 1.5545e-04 eta: 7:42:09 time: 0.4969 data_time: 0.0022 memory: 7949 grad_norm: 769.9966 loss: 413.4479 loss_cls: 142.9094 loss_bbox: 128.2188 loss_dfl: 142.3196 +2024/03/20 23:23:14 - mmengine - INFO - Epoch(train) [20][200/925] lr: 1.5545e-04 eta: 7:41:44 time: 0.4924 data_time: 0.0021 memory: 8055 grad_norm: 818.5862 loss: 412.1393 loss_cls: 143.6746 loss_bbox: 127.2391 loss_dfl: 141.2257 +2024/03/20 23:23:40 - mmengine - INFO - Epoch(train) [20][250/925] lr: 1.5545e-04 eta: 7:41:21 time: 0.5048 data_time: 0.0022 memory: 7949 grad_norm: 709.7301 loss: 408.6560 loss_cls: 139.8316 loss_bbox: 127.5699 loss_dfl: 141.2545 +2024/03/20 23:24:04 - mmengine - INFO - Epoch(train) [20][300/925] lr: 1.5545e-04 eta: 7:40:56 time: 0.4894 data_time: 0.0021 memory: 7962 grad_norm: 762.7873 loss: 413.9689 loss_cls: 143.0040 loss_bbox: 129.8356 loss_dfl: 141.1293 +2024/03/20 23:24:29 - mmengine - INFO - Epoch(train) [20][350/925] lr: 1.5545e-04 eta: 7:40:32 time: 0.4988 data_time: 0.0021 memory: 8015 grad_norm: 811.3244 loss: 409.5183 loss_cls: 141.4622 loss_bbox: 126.4724 loss_dfl: 141.5837 +2024/03/20 23:24:54 - mmengine - INFO - Epoch(train) [20][400/925] lr: 1.5545e-04 eta: 7:40:10 time: 0.5035 data_time: 0.0021 memory: 8002 grad_norm: 669.0141 loss: 409.0171 loss_cls: 141.0506 loss_bbox: 126.6370 loss_dfl: 141.3295 +2024/03/20 23:25:07 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:25:18 - mmengine - INFO - Epoch(train) [20][450/925] lr: 1.5545e-04 eta: 7:39:43 time: 0.4811 data_time: 0.0022 memory: 7869 grad_norm: 682.6728 loss: 411.8847 loss_cls: 143.7449 loss_bbox: 127.0469 loss_dfl: 141.0929 +2024/03/20 23:25:43 - mmengine - INFO - Epoch(train) [20][500/925] lr: 1.5545e-04 eta: 7:39:19 time: 0.4991 data_time: 0.0023 memory: 8015 grad_norm: 679.4546 loss: 410.6080 loss_cls: 141.6332 loss_bbox: 128.1020 loss_dfl: 140.8728 +2024/03/20 23:26:08 - mmengine - INFO - Epoch(train) [20][550/925] lr: 1.5545e-04 eta: 7:38:55 time: 0.4931 data_time: 0.0022 memory: 8389 grad_norm: 731.7251 loss: 416.9724 loss_cls: 144.7900 loss_bbox: 128.9137 loss_dfl: 143.2687 +2024/03/20 23:26:33 - mmengine - INFO - Epoch(train) [20][600/925] lr: 1.5545e-04 eta: 7:38:30 time: 0.4925 data_time: 0.0020 memory: 7989 grad_norm: 722.9012 loss: 414.3237 loss_cls: 145.5128 loss_bbox: 126.9216 loss_dfl: 141.8894 +2024/03/20 23:26:58 - mmengine - INFO - Epoch(train) [20][650/925] lr: 1.5545e-04 eta: 7:38:08 time: 0.5121 data_time: 0.0022 memory: 8149 grad_norm: 735.5419 loss: 414.3279 loss_cls: 142.7764 loss_bbox: 129.3241 loss_dfl: 142.2275 +2024/03/20 23:27:23 - mmengine - INFO - Epoch(train) [20][700/925] lr: 1.5545e-04 eta: 7:37:43 time: 0.4882 data_time: 0.0023 memory: 7975 grad_norm: 759.9860 loss: 406.5511 loss_cls: 139.7071 loss_bbox: 125.8957 loss_dfl: 140.9484 +2024/03/20 23:27:48 - mmengine - INFO - Epoch(train) [20][750/925] lr: 1.5545e-04 eta: 7:37:20 time: 0.5033 data_time: 0.0022 memory: 7962 grad_norm: 719.4139 loss: 414.8778 loss_cls: 144.8298 loss_bbox: 127.7001 loss_dfl: 142.3479 +2024/03/20 23:28:13 - mmengine - INFO - Epoch(train) [20][800/925] lr: 1.5545e-04 eta: 7:36:57 time: 0.5036 data_time: 0.0023 memory: 7949 grad_norm: 723.8506 loss: 407.7690 loss_cls: 140.4416 loss_bbox: 126.7304 loss_dfl: 140.5970 +2024/03/20 23:28:37 - mmengine - INFO - Epoch(train) [20][850/925] lr: 1.5545e-04 eta: 7:36:32 time: 0.4876 data_time: 0.0022 memory: 7962 grad_norm: 769.6407 loss: 417.3809 loss_cls: 144.3853 loss_bbox: 129.4810 loss_dfl: 143.5147 +2024/03/20 23:29:03 - mmengine - INFO - Epoch(train) [20][900/925] lr: 1.5545e-04 eta: 7:36:10 time: 0.5116 data_time: 0.0022 memory: 7735 grad_norm: 732.7426 loss: 414.5491 loss_cls: 144.7073 loss_bbox: 127.6352 loss_dfl: 142.2066 +2024/03/20 23:29:15 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:29:15 - mmengine - INFO - Saving checkpoint at 20 epochs +2024/03/20 23:29:24 - mmengine - INFO - Epoch(val) [20][ 50/625] eta: 0:00:20 time: 0.0348 data_time: 0.0008 memory: 8069 +2024/03/20 23:29:26 - mmengine - INFO - Epoch(val) [20][100/625] eta: 0:00:19 time: 0.0378 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:27 - mmengine - INFO - Epoch(val) [20][150/625] eta: 0:00:17 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:29 - mmengine - INFO - Epoch(val) [20][200/625] eta: 0:00:15 time: 0.0364 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:31 - mmengine - INFO - Epoch(val) [20][250/625] eta: 0:00:13 time: 0.0375 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:33 - mmengine - INFO - Epoch(val) [20][300/625] eta: 0:00:11 time: 0.0368 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:35 - mmengine - INFO - Epoch(val) [20][350/625] eta: 0:00:10 time: 0.0353 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:37 - mmengine - INFO - Epoch(val) [20][400/625] eta: 0:00:08 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:38 - mmengine - INFO - Epoch(val) [20][450/625] eta: 0:00:06 time: 0.0366 data_time: 0.0003 memory: 1244 +2024/03/20 23:29:40 - mmengine - INFO - Epoch(val) [20][500/625] eta: 0:00:04 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/20 23:29:41 - mmengine - INFO - Epoch(val) [20][550/625] eta: 0:00:02 time: 0.0280 data_time: 0.0002 memory: 1244 +2024/03/20 23:29:43 - mmengine - INFO - Epoch(val) [20][600/625] eta: 0:00:00 time: 0.0277 data_time: 0.0002 memory: 1244 +2024/03/20 23:29:55 - mmengine - INFO - Evaluating bbox... +2024/03/20 23:31:03 - mmengine - INFO - bbox_mAP_copypaste: 0.491 0.655 0.537 0.303 0.545 0.643 +2024/03/20 23:31:05 - mmengine - INFO - Epoch(val) [20][625/625] coco/bbox_mAP: 0.4910 coco/bbox_mAP_50: 0.6550 coco/bbox_mAP_75: 0.5370 coco/bbox_mAP_s: 0.3030 coco/bbox_mAP_m: 0.5450 coco/bbox_mAP_l: 0.6430 data_time: 0.0002 time: 0.0280 +2024/03/20 23:31:32 - mmengine - INFO - Epoch(train) [21][ 50/925] lr: 1.5297e-04 eta: 7:35:40 time: 0.5475 data_time: 0.0547 memory: 8042 grad_norm: 735.6658 loss: 412.3762 loss_cls: 142.6665 loss_bbox: 128.0204 loss_dfl: 141.6893 +2024/03/20 23:31:56 - mmengine - INFO - Epoch(train) [21][100/925] lr: 1.5297e-04 eta: 7:35:12 time: 0.4749 data_time: 0.0022 memory: 7802 grad_norm: 732.7057 loss: 412.7876 loss_cls: 143.5314 loss_bbox: 128.6175 loss_dfl: 140.6387 +2024/03/20 23:32:20 - mmengine - INFO - Epoch(train) [21][150/925] lr: 1.5297e-04 eta: 7:34:47 time: 0.4890 data_time: 0.0023 memory: 7882 grad_norm: 730.4886 loss: 410.6335 loss_cls: 141.9455 loss_bbox: 127.0809 loss_dfl: 141.6071 +2024/03/20 23:32:44 - mmengine - INFO - Epoch(train) [21][200/925] lr: 1.5297e-04 eta: 7:34:20 time: 0.4789 data_time: 0.0023 memory: 7935 grad_norm: 732.1944 loss: 411.3757 loss_cls: 142.9266 loss_bbox: 126.2015 loss_dfl: 142.2475 +2024/03/20 23:33:09 - mmengine - INFO - Epoch(train) [21][250/925] lr: 1.5297e-04 eta: 7:33:56 time: 0.4975 data_time: 0.0022 memory: 8162 grad_norm: 745.2756 loss: 410.2103 loss_cls: 142.1769 loss_bbox: 126.6544 loss_dfl: 141.3790 +2024/03/20 23:33:35 - mmengine - INFO - Epoch(train) [21][300/925] lr: 1.5297e-04 eta: 7:33:35 time: 0.5118 data_time: 0.0025 memory: 7909 grad_norm: 713.1339 loss: 411.5871 loss_cls: 142.4403 loss_bbox: 127.1104 loss_dfl: 142.0364 +2024/03/20 23:33:59 - mmengine - INFO - Epoch(train) [21][350/925] lr: 1.5297e-04 eta: 7:33:10 time: 0.4906 data_time: 0.0024 memory: 8029 grad_norm: 737.0943 loss: 410.5066 loss_cls: 140.5679 loss_bbox: 127.4681 loss_dfl: 142.4706 +2024/03/20 23:34:25 - mmengine - INFO - Epoch(train) [21][400/925] lr: 1.5297e-04 eta: 7:32:48 time: 0.5145 data_time: 0.0025 memory: 8029 grad_norm: 722.3137 loss: 409.5382 loss_cls: 139.2051 loss_bbox: 127.9134 loss_dfl: 142.4196 +2024/03/20 23:34:50 - mmengine - INFO - Epoch(train) [21][450/925] lr: 1.5297e-04 eta: 7:32:25 time: 0.5057 data_time: 0.0022 memory: 7935 grad_norm: 722.7727 loss: 404.0394 loss_cls: 138.0512 loss_bbox: 125.9274 loss_dfl: 140.0608 +2024/03/20 23:35:15 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:35:15 - mmengine - INFO - Epoch(train) [21][500/925] lr: 1.5297e-04 eta: 7:31:59 time: 0.4839 data_time: 0.0021 memory: 7949 grad_norm: 770.2353 loss: 414.3674 loss_cls: 142.5095 loss_bbox: 129.2597 loss_dfl: 142.5983 +2024/03/20 23:35:40 - mmengine - INFO - Epoch(train) [21][550/925] lr: 1.5297e-04 eta: 7:31:37 time: 0.5101 data_time: 0.0021 memory: 8015 grad_norm: 729.6192 loss: 412.2715 loss_cls: 141.7912 loss_bbox: 128.9229 loss_dfl: 141.5575 +2024/03/20 23:36:05 - mmengine - INFO - Epoch(train) [21][600/925] lr: 1.5297e-04 eta: 7:31:12 time: 0.4903 data_time: 0.0022 memory: 7815 grad_norm: 719.4822 loss: 413.0186 loss_cls: 143.9985 loss_bbox: 127.5945 loss_dfl: 141.4256 +2024/03/20 23:36:30 - mmengine - INFO - Epoch(train) [21][650/925] lr: 1.5297e-04 eta: 7:30:48 time: 0.5004 data_time: 0.0022 memory: 7935 grad_norm: 755.6693 loss: 404.6739 loss_cls: 139.5058 loss_bbox: 125.4687 loss_dfl: 139.6994 +2024/03/20 23:36:55 - mmengine - INFO - Epoch(train) [21][700/925] lr: 1.5297e-04 eta: 7:30:26 time: 0.5066 data_time: 0.0024 memory: 7975 grad_norm: 713.5282 loss: 409.6684 loss_cls: 142.7246 loss_bbox: 126.8656 loss_dfl: 140.0783 +2024/03/20 23:37:20 - mmengine - INFO - Epoch(train) [21][750/925] lr: 1.5297e-04 eta: 7:30:01 time: 0.4956 data_time: 0.0024 memory: 7855 grad_norm: 698.7345 loss: 411.0889 loss_cls: 142.9730 loss_bbox: 126.3145 loss_dfl: 141.8014 +2024/03/20 23:37:45 - mmengine - INFO - Epoch(train) [21][800/925] lr: 1.5297e-04 eta: 7:29:38 time: 0.5053 data_time: 0.0023 memory: 7642 grad_norm: 682.0546 loss: 408.1202 loss_cls: 140.6057 loss_bbox: 126.3305 loss_dfl: 141.1840 +2024/03/20 23:38:11 - mmengine - INFO - Epoch(train) [21][850/925] lr: 1.5297e-04 eta: 7:29:17 time: 0.5158 data_time: 0.0024 memory: 8282 grad_norm: 702.4633 loss: 414.3033 loss_cls: 143.7121 loss_bbox: 128.7017 loss_dfl: 141.8895 +2024/03/20 23:38:35 - mmengine - INFO - Epoch(train) [21][900/925] lr: 1.5297e-04 eta: 7:28:51 time: 0.4822 data_time: 0.0026 memory: 7749 grad_norm: 768.5107 loss: 408.6345 loss_cls: 139.7932 loss_bbox: 128.1486 loss_dfl: 140.6927 +2024/03/20 23:38:47 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:39:16 - mmengine - INFO - Epoch(train) [22][ 50/925] lr: 1.5050e-04 eta: 7:28:24 time: 0.5682 data_time: 0.0660 memory: 7749 grad_norm: 727.8598 loss: 413.1708 loss_cls: 143.4317 loss_bbox: 127.4332 loss_dfl: 142.3058 +2024/03/20 23:39:42 - mmengine - INFO - Epoch(train) [22][100/925] lr: 1.5050e-04 eta: 7:28:01 time: 0.5074 data_time: 0.0023 memory: 7709 grad_norm: 745.6656 loss: 410.9882 loss_cls: 143.6355 loss_bbox: 126.1952 loss_dfl: 141.1576 +2024/03/20 23:40:07 - mmengine - INFO - Epoch(train) [22][150/925] lr: 1.5050e-04 eta: 7:27:38 time: 0.5098 data_time: 0.0023 memory: 7935 grad_norm: 724.5645 loss: 409.7218 loss_cls: 140.3428 loss_bbox: 128.7732 loss_dfl: 140.6057 +2024/03/20 23:40:33 - mmengine - INFO - Epoch(train) [22][200/925] lr: 1.5050e-04 eta: 7:27:17 time: 0.5144 data_time: 0.0023 memory: 7775 grad_norm: 743.6400 loss: 409.0307 loss_cls: 141.6902 loss_bbox: 125.8108 loss_dfl: 141.5297 +2024/03/20 23:40:58 - mmengine - INFO - Epoch(train) [22][250/925] lr: 1.5050e-04 eta: 7:26:53 time: 0.5009 data_time: 0.0022 memory: 7882 grad_norm: 707.2799 loss: 410.5099 loss_cls: 143.4571 loss_bbox: 125.5764 loss_dfl: 141.4764 +2024/03/20 23:41:24 - mmengine - INFO - Epoch(train) [22][300/925] lr: 1.5050e-04 eta: 7:26:32 time: 0.5204 data_time: 0.0022 memory: 8122 grad_norm: 673.1926 loss: 409.1662 loss_cls: 140.6933 loss_bbox: 126.9630 loss_dfl: 141.5099 +2024/03/20 23:41:50 - mmengine - INFO - Epoch(train) [22][350/925] lr: 1.5050e-04 eta: 7:26:10 time: 0.5132 data_time: 0.0023 memory: 7909 grad_norm: 716.2504 loss: 405.8322 loss_cls: 139.7639 loss_bbox: 125.7867 loss_dfl: 140.2816 +2024/03/20 23:42:14 - mmengine - INFO - Epoch(train) [22][400/925] lr: 1.5050e-04 eta: 7:25:45 time: 0.4924 data_time: 0.0022 memory: 7802 grad_norm: 768.7971 loss: 403.1218 loss_cls: 137.9268 loss_bbox: 125.0775 loss_dfl: 140.1176 +2024/03/20 23:42:40 - mmengine - INFO - Epoch(train) [22][450/925] lr: 1.5050e-04 eta: 7:25:25 time: 0.5240 data_time: 0.0022 memory: 7922 grad_norm: 689.7370 loss: 410.1743 loss_cls: 141.1622 loss_bbox: 128.4426 loss_dfl: 140.5695 +2024/03/20 23:43:05 - mmengine - INFO - Epoch(train) [22][500/925] lr: 1.5050e-04 eta: 7:25:01 time: 0.5010 data_time: 0.0023 memory: 7842 grad_norm: 745.4212 loss: 407.9936 loss_cls: 139.9475 loss_bbox: 127.0664 loss_dfl: 140.9797 +2024/03/20 23:43:30 - mmengine - INFO - Epoch(train) [22][550/925] lr: 1.5050e-04 eta: 7:24:37 time: 0.4978 data_time: 0.0025 memory: 7749 grad_norm: inf loss: 411.7610 loss_cls: 141.8206 loss_bbox: 128.4630 loss_dfl: 141.4774 +2024/03/20 23:43:44 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:43:57 - mmengine - INFO - Epoch(train) [22][600/925] lr: 1.5050e-04 eta: 7:24:17 time: 0.5315 data_time: 0.0025 memory: 8029 grad_norm: 718.4432 loss: 411.4899 loss_cls: 141.5690 loss_bbox: 128.0059 loss_dfl: 141.9151 +2024/03/20 23:44:22 - mmengine - INFO - Epoch(train) [22][650/925] lr: 1.5050e-04 eta: 7:23:54 time: 0.5037 data_time: 0.0023 memory: 8002 grad_norm: 774.5576 loss: 412.3995 loss_cls: 144.4916 loss_bbox: 125.8149 loss_dfl: 142.0930 +2024/03/20 23:44:47 - mmengine - INFO - Epoch(train) [22][700/925] lr: 1.5050e-04 eta: 7:23:30 time: 0.5023 data_time: 0.0022 memory: 8122 grad_norm: 669.2455 loss: 405.4503 loss_cls: 140.4107 loss_bbox: 124.5784 loss_dfl: 140.4611 +2024/03/20 23:45:14 - mmengine - INFO - Epoch(train) [22][750/925] lr: 1.5050e-04 eta: 7:23:11 time: 0.5353 data_time: 0.0023 memory: 8029 grad_norm: 690.6363 loss: 407.1428 loss_cls: 139.6342 loss_bbox: 126.1360 loss_dfl: 141.3726 +2024/03/20 23:45:39 - mmengine - INFO - Epoch(train) [22][800/925] lr: 1.5050e-04 eta: 7:22:47 time: 0.4982 data_time: 0.0024 memory: 8029 grad_norm: 691.8838 loss: 409.9053 loss_cls: 143.0509 loss_bbox: 125.7470 loss_dfl: 141.1075 +2024/03/20 23:46:05 - mmengine - INFO - Epoch(train) [22][850/925] lr: 1.5050e-04 eta: 7:22:25 time: 0.5129 data_time: 0.0023 memory: 8055 grad_norm: 733.9093 loss: 416.5602 loss_cls: 144.6741 loss_bbox: 128.9044 loss_dfl: 142.9817 +2024/03/20 23:46:31 - mmengine - INFO - Epoch(train) [22][900/925] lr: 1.5050e-04 eta: 7:22:03 time: 0.5153 data_time: 0.0023 memory: 7802 grad_norm: 736.9884 loss: 406.1373 loss_cls: 139.8988 loss_bbox: 126.4434 loss_dfl: 139.7951 +2024/03/20 23:46:41 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:47:10 - mmengine - INFO - Epoch(train) [23][ 50/925] lr: 1.4803e-04 eta: 7:21:31 time: 0.5638 data_time: 0.0668 memory: 8109 grad_norm: 719.5081 loss: 407.2385 loss_cls: 139.2717 loss_bbox: 126.7283 loss_dfl: 141.2385 +2024/03/20 23:47:36 - mmengine - INFO - Epoch(train) [23][100/925] lr: 1.4803e-04 eta: 7:21:08 time: 0.5090 data_time: 0.0022 memory: 7922 grad_norm: 687.9251 loss: 416.1782 loss_cls: 144.7708 loss_bbox: 128.1391 loss_dfl: 143.2683 +2024/03/20 23:48:00 - mmengine - INFO - Epoch(train) [23][150/925] lr: 1.4803e-04 eta: 7:20:43 time: 0.4917 data_time: 0.0022 memory: 8269 grad_norm: 717.9956 loss: 410.9310 loss_cls: 141.2669 loss_bbox: 127.9091 loss_dfl: 141.7550 +2024/03/20 23:48:26 - mmengine - INFO - Epoch(train) [23][200/925] lr: 1.4803e-04 eta: 7:20:21 time: 0.5167 data_time: 0.0023 memory: 7789 grad_norm: 715.1328 loss: 411.9247 loss_cls: 143.0941 loss_bbox: 126.9135 loss_dfl: 141.9171 +2024/03/20 23:48:52 - mmengine - INFO - Epoch(train) [23][250/925] lr: 1.4803e-04 eta: 7:19:58 time: 0.5075 data_time: 0.0023 memory: 7935 grad_norm: 696.6141 loss: 408.4986 loss_cls: 140.2236 loss_bbox: 126.4600 loss_dfl: 141.8150 +2024/03/20 23:49:16 - mmengine - INFO - Epoch(train) [23][300/925] lr: 1.4803e-04 eta: 7:19:33 time: 0.4874 data_time: 0.0023 memory: 7789 grad_norm: 684.1480 loss: 413.4761 loss_cls: 143.7493 loss_bbox: 127.2122 loss_dfl: 142.5146 +2024/03/20 23:49:42 - mmengine - INFO - Epoch(train) [23][350/925] lr: 1.4803e-04 eta: 7:19:11 time: 0.5133 data_time: 0.0022 memory: 7949 grad_norm: 718.4747 loss: 414.9934 loss_cls: 142.7903 loss_bbox: 129.3433 loss_dfl: 142.8598 +2024/03/20 23:50:07 - mmengine - INFO - Epoch(train) [23][400/925] lr: 1.4803e-04 eta: 7:18:48 time: 0.5125 data_time: 0.0022 memory: 7815 grad_norm: 710.8456 loss: 407.4843 loss_cls: 140.7918 loss_bbox: 125.1850 loss_dfl: 141.5076 +2024/03/20 23:50:32 - mmengine - INFO - Epoch(train) [23][450/925] lr: 1.4803e-04 eta: 7:18:23 time: 0.4901 data_time: 0.0023 memory: 7722 grad_norm: 740.5681 loss: 407.2310 loss_cls: 140.5308 loss_bbox: 125.3322 loss_dfl: 141.3679 +2024/03/20 23:50:58 - mmengine - INFO - Epoch(train) [23][500/925] lr: 1.4803e-04 eta: 7:18:02 time: 0.5222 data_time: 0.0022 memory: 7775 grad_norm: 693.4256 loss: 405.8099 loss_cls: 139.7629 loss_bbox: 125.1435 loss_dfl: 140.9034 +2024/03/20 23:51:22 - mmengine - INFO - Epoch(train) [23][550/925] lr: 1.4803e-04 eta: 7:17:36 time: 0.4855 data_time: 0.0021 memory: 7655 grad_norm: 708.5671 loss: 407.0058 loss_cls: 138.6314 loss_bbox: 126.4866 loss_dfl: 141.8878 +2024/03/20 23:51:48 - mmengine - INFO - Epoch(train) [23][600/925] lr: 1.4803e-04 eta: 7:17:13 time: 0.5069 data_time: 0.0023 memory: 8109 grad_norm: 773.6090 loss: 399.4805 loss_cls: 136.3419 loss_bbox: 124.1720 loss_dfl: 138.9666 +2024/03/20 23:52:13 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:52:13 - mmengine - INFO - Epoch(train) [23][650/925] lr: 1.4803e-04 eta: 7:16:50 time: 0.5102 data_time: 0.0022 memory: 8335 grad_norm: 681.7012 loss: 408.7144 loss_cls: 141.7413 loss_bbox: 126.1253 loss_dfl: 140.8479 +2024/03/20 23:52:37 - mmengine - INFO - Epoch(train) [23][700/925] lr: 1.4803e-04 eta: 7:16:24 time: 0.4838 data_time: 0.0024 memory: 7909 grad_norm: 714.8207 loss: 408.6216 loss_cls: 138.5247 loss_bbox: 127.9877 loss_dfl: 142.1092 +2024/03/20 23:53:03 - mmengine - INFO - Epoch(train) [23][750/925] lr: 1.4803e-04 eta: 7:16:01 time: 0.5134 data_time: 0.0021 memory: 7989 grad_norm: 704.3164 loss: 402.9884 loss_cls: 139.9699 loss_bbox: 122.9263 loss_dfl: 140.0922 +2024/03/20 23:53:28 - mmengine - INFO - Epoch(train) [23][800/925] lr: 1.4803e-04 eta: 7:15:38 time: 0.5083 data_time: 0.0023 memory: 7669 grad_norm: 679.2732 loss: 406.1921 loss_cls: 140.9339 loss_bbox: 124.4400 loss_dfl: 140.8183 +2024/03/20 23:53:52 - mmengine - INFO - Epoch(train) [23][850/925] lr: 1.4803e-04 eta: 7:15:12 time: 0.4770 data_time: 0.0024 memory: 7829 grad_norm: 686.7301 loss: 416.7404 loss_cls: 143.9695 loss_bbox: 129.8724 loss_dfl: 142.8985 +2024/03/20 23:54:19 - mmengine - INFO - Epoch(train) [23][900/925] lr: 1.4803e-04 eta: 7:14:51 time: 0.5283 data_time: 0.0022 memory: 8029 grad_norm: 688.9825 loss: 407.2925 loss_cls: 140.6270 loss_bbox: 126.1554 loss_dfl: 140.5101 +2024/03/20 23:54:31 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/20 23:54:58 - mmengine - INFO - Epoch(train) [24][ 50/925] lr: 1.4555e-04 eta: 7:14:18 time: 0.5341 data_time: 0.0636 memory: 8002 grad_norm: inf loss: 405.4691 loss_cls: 138.8594 loss_bbox: 125.7194 loss_dfl: 140.8902 +2024/03/20 23:55:24 - mmengine - INFO - Epoch(train) [24][100/925] lr: 1.4555e-04 eta: 7:13:55 time: 0.5111 data_time: 0.0024 memory: 7909 grad_norm: 680.5273 loss: 405.3328 loss_cls: 137.3183 loss_bbox: 126.3810 loss_dfl: 141.6335 +2024/03/20 23:55:49 - mmengine - INFO - Epoch(train) [24][150/925] lr: 1.4555e-04 eta: 7:13:33 time: 0.5126 data_time: 0.0024 memory: 8095 grad_norm: 700.2007 loss: 411.7746 loss_cls: 141.0318 loss_bbox: 128.8109 loss_dfl: 141.9320 +2024/03/20 23:56:13 - mmengine - INFO - Epoch(train) [24][200/925] lr: 1.4555e-04 eta: 7:13:06 time: 0.4808 data_time: 0.0019 memory: 8082 grad_norm: 735.9179 loss: 405.0133 loss_cls: 140.0114 loss_bbox: 124.9575 loss_dfl: 140.0444 +2024/03/20 23:56:39 - mmengine - INFO - Epoch(train) [24][250/925] lr: 1.4555e-04 eta: 7:12:44 time: 0.5106 data_time: 0.0025 memory: 7922 grad_norm: 691.2360 loss: 404.8717 loss_cls: 139.9741 loss_bbox: 124.3660 loss_dfl: 140.5315 +2024/03/20 23:57:05 - mmengine - INFO - Epoch(train) [24][300/925] lr: 1.4555e-04 eta: 7:12:22 time: 0.5203 data_time: 0.0022 memory: 8042 grad_norm: 672.9217 loss: 408.4251 loss_cls: 139.7825 loss_bbox: 127.5275 loss_dfl: 141.1150 +2024/03/20 23:57:30 - mmengine - INFO - Epoch(train) [24][350/925] lr: 1.4555e-04 eta: 7:11:57 time: 0.4914 data_time: 0.0023 memory: 7775 grad_norm: 741.7882 loss: 402.7470 loss_cls: 136.8757 loss_bbox: 126.5084 loss_dfl: 139.3629 +2024/03/20 23:57:55 - mmengine - INFO - Epoch(train) [24][400/925] lr: 1.4555e-04 eta: 7:11:33 time: 0.5070 data_time: 0.0024 memory: 7855 grad_norm: 697.1203 loss: 408.3015 loss_cls: 140.0685 loss_bbox: 126.8454 loss_dfl: 141.3877 +2024/03/20 23:58:21 - mmengine - INFO - Epoch(train) [24][450/925] lr: 1.4555e-04 eta: 7:11:11 time: 0.5108 data_time: 0.0024 memory: 8002 grad_norm: 702.0811 loss: 406.1724 loss_cls: 138.0211 loss_bbox: 127.1267 loss_dfl: 141.0246 +2024/03/20 23:58:46 - mmengine - INFO - Epoch(train) [24][500/925] lr: 1.4555e-04 eta: 7:10:47 time: 0.5021 data_time: 0.0022 memory: 8095 grad_norm: 723.9434 loss: 405.1921 loss_cls: 137.4129 loss_bbox: 126.9652 loss_dfl: 140.8141 +2024/03/20 23:59:11 - mmengine - INFO - Epoch(train) [24][550/925] lr: 1.4555e-04 eta: 7:10:24 time: 0.5108 data_time: 0.0023 memory: 8015 grad_norm: 746.2251 loss: 402.9986 loss_cls: 137.0376 loss_bbox: 125.7329 loss_dfl: 140.2280 +2024/03/20 23:59:36 - mmengine - INFO - Epoch(train) [24][600/925] lr: 1.4555e-04 eta: 7:09:59 time: 0.4931 data_time: 0.0026 memory: 7962 grad_norm: 729.2826 loss: 409.9605 loss_cls: 141.0379 loss_bbox: 127.9027 loss_dfl: 141.0199 +2024/03/21 00:00:02 - mmengine - INFO - Epoch(train) [24][650/925] lr: 1.4555e-04 eta: 7:09:37 time: 0.5146 data_time: 0.0021 memory: 8175 grad_norm: 700.8897 loss: 407.4820 loss_cls: 138.0608 loss_bbox: 128.2092 loss_dfl: 141.2120 +2024/03/21 00:00:27 - mmengine - INFO - Epoch(train) [24][700/925] lr: 1.4555e-04 eta: 7:09:14 time: 0.5151 data_time: 0.0025 memory: 7735 grad_norm: 712.2278 loss: 406.2535 loss_cls: 140.3933 loss_bbox: 125.5460 loss_dfl: 140.3143 +2024/03/21 00:00:39 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:00:52 - mmengine - INFO - Epoch(train) [24][750/925] lr: 1.4555e-04 eta: 7:08:48 time: 0.4853 data_time: 0.0023 memory: 7815 grad_norm: 726.4823 loss: 410.4187 loss_cls: 140.2448 loss_bbox: 127.9873 loss_dfl: 142.1866 +2024/03/21 00:01:18 - mmengine - INFO - Epoch(train) [24][800/925] lr: 1.4555e-04 eta: 7:08:27 time: 0.5245 data_time: 0.0025 memory: 7975 grad_norm: 798.5675 loss: 402.7595 loss_cls: 137.1934 loss_bbox: 125.7742 loss_dfl: 139.7920 +2024/03/21 00:01:43 - mmengine - INFO - Epoch(train) [24][850/925] lr: 1.4555e-04 eta: 7:08:02 time: 0.4947 data_time: 0.0025 memory: 8029 grad_norm: 723.3472 loss: 406.6136 loss_cls: 140.6408 loss_bbox: 124.8973 loss_dfl: 141.0755 +2024/03/21 00:02:08 - mmengine - INFO - Epoch(train) [24][900/925] lr: 1.4555e-04 eta: 7:07:39 time: 0.5056 data_time: 0.0025 memory: 8002 grad_norm: 751.9391 loss: 403.0455 loss_cls: 138.4776 loss_bbox: 124.0981 loss_dfl: 140.4698 +2024/03/21 00:02:21 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:02:50 - mmengine - INFO - Epoch(train) [25][ 50/925] lr: 1.4307e-04 eta: 7:07:12 time: 0.5830 data_time: 0.0706 memory: 8349 grad_norm: 730.4857 loss: 405.1690 loss_cls: 138.3980 loss_bbox: 126.4978 loss_dfl: 140.2732 +2024/03/21 00:03:14 - mmengine - INFO - Epoch(train) [25][100/925] lr: 1.4307e-04 eta: 7:06:46 time: 0.4815 data_time: 0.0023 memory: 8162 grad_norm: 712.1706 loss: 405.0439 loss_cls: 138.6551 loss_bbox: 124.6250 loss_dfl: 141.7638 +2024/03/21 00:03:40 - mmengine - INFO - Epoch(train) [25][150/925] lr: 1.4307e-04 eta: 7:06:22 time: 0.5064 data_time: 0.0023 memory: 7882 grad_norm: 696.0004 loss: 408.0926 loss_cls: 140.4309 loss_bbox: 126.3879 loss_dfl: 141.2737 +2024/03/21 00:04:05 - mmengine - INFO - Epoch(train) [25][200/925] lr: 1.4307e-04 eta: 7:05:58 time: 0.5015 data_time: 0.0023 memory: 7855 grad_norm: 729.5152 loss: 408.5966 loss_cls: 140.8624 loss_bbox: 126.6866 loss_dfl: 141.0476 +2024/03/21 00:04:29 - mmengine - INFO - Epoch(train) [25][250/925] lr: 1.4307e-04 eta: 7:05:33 time: 0.4916 data_time: 0.0023 memory: 8015 grad_norm: 727.7992 loss: 402.7398 loss_cls: 137.3596 loss_bbox: 125.0616 loss_dfl: 140.3186 +2024/03/21 00:04:54 - mmengine - INFO - Epoch(train) [25][300/925] lr: 1.4307e-04 eta: 7:05:09 time: 0.4998 data_time: 0.0022 memory: 7935 grad_norm: 728.6977 loss: 407.6918 loss_cls: 139.0668 loss_bbox: 127.6046 loss_dfl: 141.0204 +2024/03/21 00:05:19 - mmengine - INFO - Epoch(train) [25][350/925] lr: 1.4307e-04 eta: 7:04:44 time: 0.4912 data_time: 0.0023 memory: 7922 grad_norm: 736.3680 loss: 403.7893 loss_cls: 138.0811 loss_bbox: 125.7428 loss_dfl: 139.9654 +2024/03/21 00:05:44 - mmengine - INFO - Epoch(train) [25][400/925] lr: 1.4307e-04 eta: 7:04:19 time: 0.4994 data_time: 0.0022 memory: 7869 grad_norm: 703.2154 loss: 410.8459 loss_cls: 141.7966 loss_bbox: 127.0587 loss_dfl: 141.9905 +2024/03/21 00:06:09 - mmengine - INFO - Epoch(train) [25][450/925] lr: 1.4307e-04 eta: 7:03:56 time: 0.5043 data_time: 0.0023 memory: 8522 grad_norm: 713.0830 loss: 415.8916 loss_cls: 144.3149 loss_bbox: 128.5276 loss_dfl: 143.0491 +2024/03/21 00:06:33 - mmengine - INFO - Epoch(train) [25][500/925] lr: 1.4307e-04 eta: 7:03:29 time: 0.4818 data_time: 0.0023 memory: 8202 grad_norm: 721.9361 loss: 411.2189 loss_cls: 140.4410 loss_bbox: 129.4464 loss_dfl: 141.3315 +2024/03/21 00:06:59 - mmengine - INFO - Epoch(train) [25][550/925] lr: 1.4307e-04 eta: 7:03:05 time: 0.5030 data_time: 0.0023 memory: 7842 grad_norm: 719.1748 loss: 407.9723 loss_cls: 141.1719 loss_bbox: 125.7244 loss_dfl: 141.0760 +2024/03/21 00:07:23 - mmengine - INFO - Epoch(train) [25][600/925] lr: 1.4307e-04 eta: 7:02:41 time: 0.4966 data_time: 0.0022 memory: 8095 grad_norm: 718.8996 loss: 404.1497 loss_cls: 138.2228 loss_bbox: 124.5473 loss_dfl: 141.3796 +2024/03/21 00:07:48 - mmengine - INFO - Epoch(train) [25][650/925] lr: 1.4307e-04 eta: 7:02:15 time: 0.4847 data_time: 0.0021 memory: 7655 grad_norm: 702.3161 loss: 409.8195 loss_cls: 142.7706 loss_bbox: 125.7495 loss_dfl: 141.2994 +2024/03/21 00:08:13 - mmengine - INFO - Epoch(train) [25][700/925] lr: 1.4307e-04 eta: 7:01:50 time: 0.4989 data_time: 0.0023 memory: 7989 grad_norm: 705.4835 loss: 400.9154 loss_cls: 137.1447 loss_bbox: 123.8817 loss_dfl: 139.8890 +2024/03/21 00:08:37 - mmengine - INFO - Epoch(train) [25][750/925] lr: 1.4307e-04 eta: 7:01:25 time: 0.4931 data_time: 0.0022 memory: 7842 grad_norm: 748.5439 loss: 409.9508 loss_cls: 140.5607 loss_bbox: 128.4411 loss_dfl: 140.9490 +2024/03/21 00:09:02 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:09:02 - mmengine - INFO - Epoch(train) [25][800/925] lr: 1.4307e-04 eta: 7:01:00 time: 0.4929 data_time: 0.0024 memory: 8002 grad_norm: 706.3896 loss: 406.7403 loss_cls: 139.2288 loss_bbox: 125.7132 loss_dfl: 141.7983 +2024/03/21 00:09:27 - mmengine - INFO - Epoch(train) [25][850/925] lr: 1.4307e-04 eta: 7:00:37 time: 0.5043 data_time: 0.0028 memory: 8069 grad_norm: 722.7577 loss: 400.2024 loss_cls: 137.7904 loss_bbox: 122.9641 loss_dfl: 139.4479 +2024/03/21 00:09:51 - mmengine - INFO - Epoch(train) [25][900/925] lr: 1.4307e-04 eta: 7:00:11 time: 0.4836 data_time: 0.0024 memory: 8055 grad_norm: 683.2923 loss: 403.8793 loss_cls: 138.1612 loss_bbox: 126.4284 loss_dfl: 139.2897 +2024/03/21 00:10:03 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:10:03 - mmengine - INFO - Saving checkpoint at 25 epochs +2024/03/21 00:10:12 - mmengine - INFO - Epoch(val) [25][ 50/625] eta: 0:00:21 time: 0.0371 data_time: 0.0008 memory: 7949 +2024/03/21 00:10:14 - mmengine - INFO - Epoch(val) [25][100/625] eta: 0:00:19 time: 0.0368 data_time: 0.0004 memory: 1244 +2024/03/21 00:10:16 - mmengine - INFO - Epoch(val) [25][150/625] eta: 0:00:17 time: 0.0373 data_time: 0.0004 memory: 1244 +2024/03/21 00:10:18 - mmengine - INFO - Epoch(val) [25][200/625] eta: 0:00:15 time: 0.0369 data_time: 0.0003 memory: 1244 +2024/03/21 00:10:20 - mmengine - INFO - Epoch(val) [25][250/625] eta: 0:00:13 time: 0.0379 data_time: 0.0003 memory: 1244 +2024/03/21 00:10:22 - mmengine - INFO - Epoch(val) [25][300/625] eta: 0:00:12 time: 0.0379 data_time: 0.0003 memory: 1244 +2024/03/21 00:10:24 - mmengine - INFO - Epoch(val) [25][350/625] eta: 0:00:10 time: 0.0364 data_time: 0.0003 memory: 1244 +2024/03/21 00:10:25 - mmengine - INFO - Epoch(val) [25][400/625] eta: 0:00:08 time: 0.0369 data_time: 0.0004 memory: 1244 +2024/03/21 00:10:27 - mmengine - INFO - Epoch(val) [25][450/625] eta: 0:00:06 time: 0.0344 data_time: 0.0011 memory: 1244 +2024/03/21 00:10:29 - mmengine - INFO - Epoch(val) [25][500/625] eta: 0:00:04 time: 0.0284 data_time: 0.0002 memory: 1244 +2024/03/21 00:10:30 - mmengine - INFO - Epoch(val) [25][550/625] eta: 0:00:02 time: 0.0286 data_time: 0.0002 memory: 1244 +2024/03/21 00:10:31 - mmengine - INFO - Epoch(val) [25][600/625] eta: 0:00:00 time: 0.0289 data_time: 0.0002 memory: 1244 +2024/03/21 00:10:44 - mmengine - INFO - Evaluating bbox... +2024/03/21 00:11:55 - mmengine - INFO - bbox_mAP_copypaste: 0.496 0.659 0.542 0.308 0.549 0.649 +2024/03/21 00:11:57 - mmengine - INFO - Epoch(val) [25][625/625] coco/bbox_mAP: 0.4960 coco/bbox_mAP_50: 0.6590 coco/bbox_mAP_75: 0.5420 coco/bbox_mAP_s: 0.3080 coco/bbox_mAP_m: 0.5490 coco/bbox_mAP_l: 0.6490 data_time: 0.0002 time: 0.0285 +2024/03/21 00:12:26 - mmengine - INFO - Epoch(train) [26][ 50/925] lr: 1.4060e-04 eta: 6:59:40 time: 0.5676 data_time: 0.0729 memory: 7869 grad_norm: 724.5579 loss: 406.0568 loss_cls: 137.2144 loss_bbox: 127.7246 loss_dfl: 141.1178 +2024/03/21 00:12:51 - mmengine - INFO - Epoch(train) [26][100/925] lr: 1.4060e-04 eta: 6:59:15 time: 0.5000 data_time: 0.0022 memory: 7935 grad_norm: 702.6136 loss: 401.7211 loss_cls: 136.1567 loss_bbox: 124.8101 loss_dfl: 140.7543 +2024/03/21 00:13:15 - mmengine - INFO - Epoch(train) [26][150/925] lr: 1.4060e-04 eta: 6:58:49 time: 0.4786 data_time: 0.0022 memory: 8095 grad_norm: 652.5139 loss: 409.2417 loss_cls: 140.3591 loss_bbox: 127.6892 loss_dfl: 141.1934 +2024/03/21 00:13:39 - mmengine - INFO - Epoch(train) [26][200/925] lr: 1.4060e-04 eta: 6:58:22 time: 0.4772 data_time: 0.0022 memory: 7735 grad_norm: 749.6109 loss: 407.0108 loss_cls: 138.6639 loss_bbox: 127.7159 loss_dfl: 140.6310 +2024/03/21 00:14:03 - mmengine - INFO - Epoch(train) [26][250/925] lr: 1.4060e-04 eta: 6:57:57 time: 0.4905 data_time: 0.0023 memory: 8002 grad_norm: 736.3768 loss: 395.1325 loss_cls: 134.2026 loss_bbox: 122.3446 loss_dfl: 138.5854 +2024/03/21 00:14:28 - mmengine - INFO - Epoch(train) [26][300/925] lr: 1.4060e-04 eta: 6:57:31 time: 0.4873 data_time: 0.0022 memory: 7882 grad_norm: 725.7254 loss: 402.6209 loss_cls: 137.7457 loss_bbox: 123.9721 loss_dfl: 140.9032 +2024/03/21 00:14:52 - mmengine - INFO - Epoch(train) [26][350/925] lr: 1.4060e-04 eta: 6:57:05 time: 0.4811 data_time: 0.0023 memory: 7829 grad_norm: 723.0783 loss: 400.8642 loss_cls: 137.2380 loss_bbox: 123.8226 loss_dfl: 139.8036 +2024/03/21 00:15:16 - mmengine - INFO - Epoch(train) [26][400/925] lr: 1.4060e-04 eta: 6:56:38 time: 0.4794 data_time: 0.0022 memory: 8029 grad_norm: 743.5428 loss: 398.6903 loss_cls: 134.6884 loss_bbox: 124.4206 loss_dfl: 139.5813 +2024/03/21 00:15:40 - mmengine - INFO - Epoch(train) [26][450/925] lr: 1.4060e-04 eta: 6:56:13 time: 0.4926 data_time: 0.0023 memory: 8042 grad_norm: 737.2940 loss: 396.6755 loss_cls: 133.6139 loss_bbox: 124.0174 loss_dfl: 139.0442 +2024/03/21 00:16:05 - mmengine - INFO - Epoch(train) [26][500/925] lr: 1.4060e-04 eta: 6:55:48 time: 0.4893 data_time: 0.0022 memory: 7962 grad_norm: 677.5002 loss: 402.5086 loss_cls: 135.7885 loss_bbox: 126.6444 loss_dfl: 140.0756 +2024/03/21 00:16:28 - mmengine - INFO - Epoch(train) [26][550/925] lr: 1.4060e-04 eta: 6:55:21 time: 0.4736 data_time: 0.0022 memory: 7922 grad_norm: 772.1891 loss: 401.3139 loss_cls: 135.7046 loss_bbox: 124.5828 loss_dfl: 141.0265 +2024/03/21 00:16:53 - mmengine - INFO - Epoch(train) [26][600/925] lr: 1.4060e-04 eta: 6:54:55 time: 0.4828 data_time: 0.0022 memory: 7949 grad_norm: 756.4348 loss: 404.6832 loss_cls: 138.9013 loss_bbox: 125.6034 loss_dfl: 140.1785 +2024/03/21 00:17:17 - mmengine - INFO - Epoch(train) [26][650/925] lr: 1.4060e-04 eta: 6:54:29 time: 0.4845 data_time: 0.0023 memory: 8042 grad_norm: 746.7498 loss: 409.4347 loss_cls: 139.2890 loss_bbox: 128.1159 loss_dfl: 142.0298 +2024/03/21 00:17:41 - mmengine - INFO - Epoch(train) [26][700/925] lr: 1.4060e-04 eta: 6:54:03 time: 0.4859 data_time: 0.0024 memory: 7882 grad_norm: 699.3694 loss: 409.3490 loss_cls: 142.0625 loss_bbox: 126.3846 loss_dfl: 140.9018 +2024/03/21 00:18:05 - mmengine - INFO - Epoch(train) [26][750/925] lr: 1.4060e-04 eta: 6:53:37 time: 0.4830 data_time: 0.0023 memory: 8175 grad_norm: 726.9637 loss: 402.2096 loss_cls: 136.1783 loss_bbox: 125.9161 loss_dfl: 140.1152 +2024/03/21 00:18:29 - mmengine - INFO - Epoch(train) [26][800/925] lr: 1.4060e-04 eta: 6:53:10 time: 0.4748 data_time: 0.0023 memory: 8042 grad_norm: 736.1051 loss: 408.5693 loss_cls: 139.4909 loss_bbox: 127.3357 loss_dfl: 141.7427 +2024/03/21 00:18:54 - mmengine - INFO - Epoch(train) [26][850/925] lr: 1.4060e-04 eta: 6:52:46 time: 0.4982 data_time: 0.0023 memory: 8002 grad_norm: 767.8642 loss: 403.9552 loss_cls: 137.8496 loss_bbox: 126.6220 loss_dfl: 139.4836 +2024/03/21 00:19:07 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:19:19 - mmengine - INFO - Epoch(train) [26][900/925] lr: 1.4060e-04 eta: 6:52:21 time: 0.4958 data_time: 0.0023 memory: 8215 grad_norm: 695.7469 loss: 407.0834 loss_cls: 139.1842 loss_bbox: 127.6219 loss_dfl: 140.2773 +2024/03/21 00:19:30 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:19:57 - mmengine - INFO - Epoch(train) [27][ 50/925] lr: 1.3813e-04 eta: 6:51:45 time: 0.5366 data_time: 0.0609 memory: 8055 grad_norm: 718.8377 loss: 410.0905 loss_cls: 141.1460 loss_bbox: 126.6670 loss_dfl: 142.2775 +2024/03/21 00:20:22 - mmengine - INFO - Epoch(train) [27][100/925] lr: 1.3813e-04 eta: 6:51:19 time: 0.4861 data_time: 0.0022 memory: 8122 grad_norm: 686.1027 loss: 403.6145 loss_cls: 138.1799 loss_bbox: 125.0516 loss_dfl: 140.3830 +2024/03/21 00:20:46 - mmengine - INFO - Epoch(train) [27][150/925] lr: 1.3813e-04 eta: 6:50:53 time: 0.4808 data_time: 0.0022 memory: 8015 grad_norm: 749.7877 loss: 406.5478 loss_cls: 141.7513 loss_bbox: 123.0617 loss_dfl: 141.7349 +2024/03/21 00:21:10 - mmengine - INFO - Epoch(train) [27][200/925] lr: 1.3813e-04 eta: 6:50:28 time: 0.4940 data_time: 0.0024 memory: 7842 grad_norm: 828.3742 loss: 401.9987 loss_cls: 137.3739 loss_bbox: 124.7510 loss_dfl: 139.8738 +2024/03/21 00:21:35 - mmengine - INFO - Epoch(train) [27][250/925] lr: 1.3813e-04 eta: 6:50:04 time: 0.4984 data_time: 0.0023 memory: 7989 grad_norm: 687.9586 loss: 400.8117 loss_cls: 137.5126 loss_bbox: 123.2671 loss_dfl: 140.0319 +2024/03/21 00:21:59 - mmengine - INFO - Epoch(train) [27][300/925] lr: 1.3813e-04 eta: 6:49:37 time: 0.4769 data_time: 0.0023 memory: 7949 grad_norm: 712.8991 loss: 412.5686 loss_cls: 142.7861 loss_bbox: 127.4585 loss_dfl: 142.3240 +2024/03/21 00:22:23 - mmengine - INFO - Epoch(train) [27][350/925] lr: 1.3813e-04 eta: 6:49:12 time: 0.4857 data_time: 0.0023 memory: 7922 grad_norm: 702.6912 loss: 401.8912 loss_cls: 135.9913 loss_bbox: 125.1380 loss_dfl: 140.7618 +2024/03/21 00:22:48 - mmengine - INFO - Epoch(train) [27][400/925] lr: 1.3813e-04 eta: 6:48:47 time: 0.5006 data_time: 0.0023 memory: 8015 grad_norm: 754.1801 loss: 401.6821 loss_cls: 138.9863 loss_bbox: 122.8042 loss_dfl: 139.8916 +2024/03/21 00:23:12 - mmengine - INFO - Epoch(train) [27][450/925] lr: 1.3813e-04 eta: 6:48:21 time: 0.4770 data_time: 0.0023 memory: 7922 grad_norm: 656.5000 loss: 401.8159 loss_cls: 137.2598 loss_bbox: 124.5523 loss_dfl: 140.0038 +2024/03/21 00:23:37 - mmengine - INFO - Epoch(train) [27][500/925] lr: 1.3813e-04 eta: 6:47:55 time: 0.4881 data_time: 0.0023 memory: 7709 grad_norm: 720.3087 loss: 402.5032 loss_cls: 136.2610 loss_bbox: 124.5619 loss_dfl: 141.6804 +2024/03/21 00:24:01 - mmengine - INFO - Epoch(train) [27][550/925] lr: 1.3813e-04 eta: 6:47:29 time: 0.4793 data_time: 0.0023 memory: 8175 grad_norm: 708.9224 loss: 395.9506 loss_cls: 133.6165 loss_bbox: 122.5426 loss_dfl: 139.7915 +2024/03/21 00:24:26 - mmengine - INFO - Epoch(train) [27][600/925] lr: 1.3813e-04 eta: 6:47:04 time: 0.4952 data_time: 0.0023 memory: 7882 grad_norm: 739.9516 loss: 407.8882 loss_cls: 138.0147 loss_bbox: 128.0036 loss_dfl: 141.8699 +2024/03/21 00:24:50 - mmengine - INFO - Epoch(train) [27][650/925] lr: 1.3813e-04 eta: 6:46:39 time: 0.4925 data_time: 0.0021 memory: 7735 grad_norm: 720.8764 loss: 402.1681 loss_cls: 137.6721 loss_bbox: 124.3446 loss_dfl: 140.1513 +2024/03/21 00:25:14 - mmengine - INFO - Epoch(train) [27][700/925] lr: 1.3813e-04 eta: 6:46:12 time: 0.4720 data_time: 0.0022 memory: 8002 grad_norm: 758.4674 loss: 406.3343 loss_cls: 138.3237 loss_bbox: 126.6044 loss_dfl: 141.4062 +2024/03/21 00:25:39 - mmengine - INFO - Epoch(train) [27][750/925] lr: 1.3813e-04 eta: 6:45:48 time: 0.4985 data_time: 0.0022 memory: 8482 grad_norm: 694.0168 loss: 403.0096 loss_cls: 139.2602 loss_bbox: 123.5577 loss_dfl: 140.1917 +2024/03/21 00:26:04 - mmengine - INFO - Epoch(train) [27][800/925] lr: 1.3813e-04 eta: 6:45:24 time: 0.4982 data_time: 0.0024 memory: 8122 grad_norm: 735.8958 loss: 404.6104 loss_cls: 138.7633 loss_bbox: 126.0133 loss_dfl: 139.8339 +2024/03/21 00:26:27 - mmengine - INFO - Epoch(train) [27][850/925] lr: 1.3813e-04 eta: 6:44:56 time: 0.4675 data_time: 0.0022 memory: 7855 grad_norm: 756.5105 loss: 399.2535 loss_cls: 136.6132 loss_bbox: 123.6603 loss_dfl: 138.9800 +2024/03/21 00:26:52 - mmengine - INFO - Epoch(train) [27][900/925] lr: 1.3813e-04 eta: 6:44:31 time: 0.4910 data_time: 0.0023 memory: 8069 grad_norm: 739.1012 loss: 408.4058 loss_cls: 139.9946 loss_bbox: 126.9820 loss_dfl: 141.4292 +2024/03/21 00:27:04 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:27:19 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:27:31 - mmengine - INFO - Epoch(train) [28][ 50/925] lr: 1.3565e-04 eta: 6:43:57 time: 0.5253 data_time: 0.0591 memory: 7829 grad_norm: 748.4219 loss: 401.6931 loss_cls: 138.3127 loss_bbox: 123.3174 loss_dfl: 140.0631 +2024/03/21 00:27:56 - mmengine - INFO - Epoch(train) [28][100/925] lr: 1.3565e-04 eta: 6:43:33 time: 0.5005 data_time: 0.0021 memory: 7975 grad_norm: 726.0340 loss: 403.9735 loss_cls: 136.8848 loss_bbox: 126.7682 loss_dfl: 140.3205 +2024/03/21 00:28:21 - mmengine - INFO - Epoch(train) [28][150/925] lr: 1.3565e-04 eta: 6:43:10 time: 0.5073 data_time: 0.0022 memory: 8069 grad_norm: 730.8881 loss: 404.6076 loss_cls: 138.6649 loss_bbox: 126.4054 loss_dfl: 139.5372 +2024/03/21 00:28:45 - mmengine - INFO - Epoch(train) [28][200/925] lr: 1.3565e-04 eta: 6:42:43 time: 0.4794 data_time: 0.0022 memory: 7909 grad_norm: 790.1030 loss: 398.0973 loss_cls: 134.4885 loss_bbox: 124.6807 loss_dfl: 138.9281 +2024/03/21 00:29:10 - mmengine - INFO - Epoch(train) [28][250/925] lr: 1.3565e-04 eta: 6:42:19 time: 0.4998 data_time: 0.0022 memory: 7829 grad_norm: 786.5683 loss: 404.9864 loss_cls: 139.0210 loss_bbox: 124.3782 loss_dfl: 141.5871 +2024/03/21 00:29:36 - mmengine - INFO - Epoch(train) [28][300/925] lr: 1.3565e-04 eta: 6:41:56 time: 0.5090 data_time: 0.0023 memory: 7802 grad_norm: 691.4148 loss: 404.3328 loss_cls: 137.6056 loss_bbox: 126.3934 loss_dfl: 140.3339 +2024/03/21 00:30:00 - mmengine - INFO - Epoch(train) [28][350/925] lr: 1.3565e-04 eta: 6:41:30 time: 0.4858 data_time: 0.0023 memory: 7815 grad_norm: 701.9386 loss: 404.3840 loss_cls: 137.9636 loss_bbox: 126.0280 loss_dfl: 140.3924 +2024/03/21 00:30:25 - mmengine - INFO - Epoch(train) [28][400/925] lr: 1.3565e-04 eta: 6:41:05 time: 0.4960 data_time: 0.0024 memory: 7802 grad_norm: 701.2569 loss: 402.8515 loss_cls: 136.3891 loss_bbox: 126.3722 loss_dfl: 140.0902 +2024/03/21 00:30:49 - mmengine - INFO - Epoch(train) [28][450/925] lr: 1.3565e-04 eta: 6:40:40 time: 0.4854 data_time: 0.0022 memory: 8229 grad_norm: 704.6015 loss: 396.2160 loss_cls: 133.6206 loss_bbox: 123.5315 loss_dfl: 139.0640 +2024/03/21 00:31:15 - mmengine - INFO - Epoch(train) [28][500/925] lr: 1.3565e-04 eta: 6:40:16 time: 0.5057 data_time: 0.0022 memory: 7789 grad_norm: 705.2044 loss: 403.3592 loss_cls: 138.0451 loss_bbox: 124.8421 loss_dfl: 140.4720 +2024/03/21 00:31:40 - mmengine - INFO - Epoch(train) [28][550/925] lr: 1.3565e-04 eta: 6:39:52 time: 0.5035 data_time: 0.0023 memory: 8015 grad_norm: 725.0554 loss: 401.3486 loss_cls: 136.1393 loss_bbox: 124.4835 loss_dfl: 140.7258 +2024/03/21 00:32:04 - mmengine - INFO - Epoch(train) [28][600/925] lr: 1.3565e-04 eta: 6:39:26 time: 0.4837 data_time: 0.0023 memory: 8095 grad_norm: 673.2699 loss: 405.9218 loss_cls: 139.0457 loss_bbox: 127.0346 loss_dfl: 139.8415 +2024/03/21 00:32:29 - mmengine - INFO - Epoch(train) [28][650/925] lr: 1.3565e-04 eta: 6:39:03 time: 0.5045 data_time: 0.0024 memory: 8215 grad_norm: 705.0386 loss: 403.1571 loss_cls: 136.5721 loss_bbox: 126.0823 loss_dfl: 140.5028 +2024/03/21 00:32:55 - mmengine - INFO - Epoch(train) [28][700/925] lr: 1.3565e-04 eta: 6:38:39 time: 0.5059 data_time: 0.0023 memory: 7869 grad_norm: 738.1441 loss: 401.1085 loss_cls: 136.0056 loss_bbox: 125.2402 loss_dfl: 139.8627 +2024/03/21 00:33:19 - mmengine - INFO - Epoch(train) [28][750/925] lr: 1.3565e-04 eta: 6:38:13 time: 0.4858 data_time: 0.0022 memory: 8069 grad_norm: 692.0529 loss: 403.8830 loss_cls: 136.9329 loss_bbox: 126.4504 loss_dfl: 140.4998 +2024/03/21 00:33:44 - mmengine - INFO - Epoch(train) [28][800/925] lr: 1.3565e-04 eta: 6:37:48 time: 0.4952 data_time: 0.0023 memory: 8495 grad_norm: 697.9791 loss: 397.4394 loss_cls: 134.4002 loss_bbox: 124.3279 loss_dfl: 138.7113 +2024/03/21 00:34:08 - mmengine - INFO - Epoch(train) [28][850/925] lr: 1.3565e-04 eta: 6:37:23 time: 0.4869 data_time: 0.0023 memory: 7775 grad_norm: 741.9779 loss: 403.0616 loss_cls: 137.6204 loss_bbox: 125.3259 loss_dfl: 140.1152 +2024/03/21 00:34:34 - mmengine - INFO - Epoch(train) [28][900/925] lr: 1.3565e-04 eta: 6:36:59 time: 0.5081 data_time: 0.0021 memory: 8015 grad_norm: inf loss: 405.0124 loss_cls: 137.2997 loss_bbox: 127.9166 loss_dfl: 139.7961 +2024/03/21 00:34:45 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:35:14 - mmengine - INFO - Epoch(train) [29][ 50/925] lr: 1.3317e-04 eta: 6:36:28 time: 0.5643 data_time: 0.0623 memory: 7962 grad_norm: 797.6411 loss: 400.5592 loss_cls: 135.2603 loss_bbox: 124.6211 loss_dfl: 140.6779 +2024/03/21 00:35:38 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:35:38 - mmengine - INFO - Epoch(train) [29][100/925] lr: 1.3317e-04 eta: 6:36:01 time: 0.4787 data_time: 0.0022 memory: 8042 grad_norm: 670.7509 loss: 401.4915 loss_cls: 136.6735 loss_bbox: 124.9004 loss_dfl: 139.9177 +2024/03/21 00:36:03 - mmengine - INFO - Epoch(train) [29][150/925] lr: 1.3317e-04 eta: 6:35:37 time: 0.4949 data_time: 0.0023 memory: 7869 grad_norm: 716.6659 loss: 403.3252 loss_cls: 137.2601 loss_bbox: 125.2187 loss_dfl: 140.8463 +2024/03/21 00:36:28 - mmengine - INFO - Epoch(train) [29][200/925] lr: 1.3317e-04 eta: 6:35:13 time: 0.5038 data_time: 0.0023 memory: 8149 grad_norm: 737.8199 loss: 404.3943 loss_cls: 137.8586 loss_bbox: 126.3613 loss_dfl: 140.1744 +2024/03/21 00:36:53 - mmengine - INFO - Epoch(train) [29][250/925] lr: 1.3317e-04 eta: 6:34:48 time: 0.4933 data_time: 0.0023 memory: 7922 grad_norm: 744.6989 loss: 407.4349 loss_cls: 139.0474 loss_bbox: 127.4275 loss_dfl: 140.9599 +2024/03/21 00:37:17 - mmengine - INFO - Epoch(train) [29][300/925] lr: 1.3317e-04 eta: 6:34:22 time: 0.4885 data_time: 0.0022 memory: 7922 grad_norm: 757.3049 loss: 408.1462 loss_cls: 139.6907 loss_bbox: 126.9609 loss_dfl: 141.4946 +2024/03/21 00:37:41 - mmengine - INFO - Epoch(train) [29][350/925] lr: 1.3317e-04 eta: 6:33:57 time: 0.4837 data_time: 0.0023 memory: 7815 grad_norm: 683.7938 loss: 403.5631 loss_cls: 137.2195 loss_bbox: 127.0192 loss_dfl: 139.3243 +2024/03/21 00:38:07 - mmengine - INFO - Epoch(train) [29][400/925] lr: 1.3317e-04 eta: 6:33:33 time: 0.5081 data_time: 0.0022 memory: 7909 grad_norm: 673.2231 loss: 402.7647 loss_cls: 136.8039 loss_bbox: 125.6970 loss_dfl: 140.2638 +2024/03/21 00:38:31 - mmengine - INFO - Epoch(train) [29][450/925] lr: 1.3317e-04 eta: 6:33:08 time: 0.4935 data_time: 0.0023 memory: 7762 grad_norm: 739.1883 loss: 401.7452 loss_cls: 136.3639 loss_bbox: 124.9424 loss_dfl: 140.4388 +2024/03/21 00:38:56 - mmengine - INFO - Epoch(train) [29][500/925] lr: 1.3317e-04 eta: 6:32:42 time: 0.4820 data_time: 0.0022 memory: 8135 grad_norm: 733.0454 loss: 397.9293 loss_cls: 133.9502 loss_bbox: 124.8153 loss_dfl: 139.1638 +2024/03/21 00:39:21 - mmengine - INFO - Epoch(train) [29][550/925] lr: 1.3317e-04 eta: 6:32:18 time: 0.5015 data_time: 0.0023 memory: 7829 grad_norm: 775.4665 loss: 407.7175 loss_cls: 138.9749 loss_bbox: 127.3933 loss_dfl: 141.3493 +2024/03/21 00:39:46 - mmengine - INFO - Epoch(train) [29][600/925] lr: 1.3317e-04 eta: 6:31:54 time: 0.5038 data_time: 0.0023 memory: 7895 grad_norm: 688.4305 loss: 394.9819 loss_cls: 134.1503 loss_bbox: 122.7693 loss_dfl: 138.0623 +2024/03/21 00:40:11 - mmengine - INFO - Epoch(train) [29][650/925] lr: 1.3317e-04 eta: 6:31:29 time: 0.4946 data_time: 0.0022 memory: 7909 grad_norm: 708.1519 loss: 402.3984 loss_cls: 137.3504 loss_bbox: 124.2754 loss_dfl: 140.7727 +2024/03/21 00:40:36 - mmengine - INFO - Epoch(train) [29][700/925] lr: 1.3317e-04 eta: 6:31:05 time: 0.4995 data_time: 0.0023 memory: 8055 grad_norm: 741.5030 loss: 405.8565 loss_cls: 139.6593 loss_bbox: 125.6316 loss_dfl: 140.5656 +2024/03/21 00:41:00 - mmengine - INFO - Epoch(train) [29][750/925] lr: 1.3317e-04 eta: 6:30:40 time: 0.4899 data_time: 0.0022 memory: 8029 grad_norm: 705.6520 loss: 406.4334 loss_cls: 140.4188 loss_bbox: 125.6284 loss_dfl: 140.3862 +2024/03/21 00:41:26 - mmengine - INFO - Epoch(train) [29][800/925] lr: 1.3317e-04 eta: 6:30:16 time: 0.5084 data_time: 0.0023 memory: 7789 grad_norm: 734.3943 loss: 403.9833 loss_cls: 137.8703 loss_bbox: 126.8168 loss_dfl: 139.2962 +2024/03/21 00:41:51 - mmengine - INFO - Epoch(train) [29][850/925] lr: 1.3317e-04 eta: 6:29:52 time: 0.5026 data_time: 0.0024 memory: 7922 grad_norm: 724.7238 loss: 405.6678 loss_cls: 138.6047 loss_bbox: 126.7046 loss_dfl: 140.3585 +2024/03/21 00:42:15 - mmengine - INFO - Epoch(train) [29][900/925] lr: 1.3317e-04 eta: 6:29:27 time: 0.4864 data_time: 0.0022 memory: 7949 grad_norm: 667.3808 loss: 401.1152 loss_cls: 135.8552 loss_bbox: 125.4952 loss_dfl: 139.7648 +2024/03/21 00:42:27 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:42:56 - mmengine - INFO - Epoch(train) [30][ 50/925] lr: 1.3070e-04 eta: 6:28:55 time: 0.5690 data_time: 0.0716 memory: 8015 grad_norm: 752.1138 loss: 397.4891 loss_cls: 133.8500 loss_bbox: 124.2516 loss_dfl: 139.3875 +2024/03/21 00:43:20 - mmengine - INFO - Epoch(train) [30][100/925] lr: 1.3070e-04 eta: 6:28:29 time: 0.4793 data_time: 0.0022 memory: 8082 grad_norm: 742.7266 loss: 399.1004 loss_cls: 136.7224 loss_bbox: 121.8965 loss_dfl: 140.4815 +2024/03/21 00:43:45 - mmengine - INFO - Epoch(train) [30][150/925] lr: 1.3070e-04 eta: 6:28:05 time: 0.4989 data_time: 0.0022 memory: 7789 grad_norm: 728.5111 loss: 405.3966 loss_cls: 139.5715 loss_bbox: 124.5399 loss_dfl: 141.2852 +2024/03/21 00:43:57 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:44:10 - mmengine - INFO - Epoch(train) [30][200/925] lr: 1.3070e-04 eta: 6:27:39 time: 0.4876 data_time: 0.0023 memory: 7802 grad_norm: 722.7572 loss: 399.5463 loss_cls: 135.5099 loss_bbox: 124.3447 loss_dfl: 139.6918 +2024/03/21 00:44:33 - mmengine - INFO - Epoch(train) [30][250/925] lr: 1.3070e-04 eta: 6:27:13 time: 0.4782 data_time: 0.0025 memory: 7949 grad_norm: 706.0518 loss: 394.7301 loss_cls: 133.7459 loss_bbox: 122.5329 loss_dfl: 138.4514 +2024/03/21 00:44:59 - mmengine - INFO - Epoch(train) [30][300/925] lr: 1.3070e-04 eta: 6:26:49 time: 0.5012 data_time: 0.0023 memory: 8309 grad_norm: 725.5921 loss: 404.1070 loss_cls: 138.3198 loss_bbox: 126.0476 loss_dfl: 139.7396 +2024/03/21 00:45:23 - mmengine - INFO - Epoch(train) [30][350/925] lr: 1.3070e-04 eta: 6:26:24 time: 0.4897 data_time: 0.0022 memory: 8082 grad_norm: 782.5922 loss: 408.3024 loss_cls: 140.4852 loss_bbox: 126.6098 loss_dfl: 141.2074 +2024/03/21 00:45:47 - mmengine - INFO - Epoch(train) [30][400/925] lr: 1.3070e-04 eta: 6:25:58 time: 0.4820 data_time: 0.0023 memory: 7989 grad_norm: 717.3533 loss: 396.2515 loss_cls: 132.1372 loss_bbox: 123.8484 loss_dfl: 140.2659 +2024/03/21 00:46:11 - mmengine - INFO - Epoch(train) [30][450/925] lr: 1.3070e-04 eta: 6:25:32 time: 0.4819 data_time: 0.0023 memory: 7935 grad_norm: 697.4018 loss: 406.8865 loss_cls: 140.3516 loss_bbox: 125.7435 loss_dfl: 140.7915 +2024/03/21 00:46:36 - mmengine - INFO - Epoch(train) [30][500/925] lr: 1.3070e-04 eta: 6:25:07 time: 0.4923 data_time: 0.0023 memory: 8002 grad_norm: 726.8933 loss: 401.8366 loss_cls: 135.4031 loss_bbox: 126.5789 loss_dfl: 139.8547 +2024/03/21 00:47:01 - mmengine - INFO - Epoch(train) [30][550/925] lr: 1.3070e-04 eta: 6:24:42 time: 0.4952 data_time: 0.0022 memory: 7749 grad_norm: 685.7544 loss: 398.6416 loss_cls: 135.6075 loss_bbox: 123.4881 loss_dfl: 139.5460 +2024/03/21 00:47:25 - mmengine - INFO - Epoch(train) [30][600/925] lr: 1.3070e-04 eta: 6:24:17 time: 0.4874 data_time: 0.0024 memory: 8069 grad_norm: 755.7144 loss: 403.9477 loss_cls: 138.7137 loss_bbox: 124.7936 loss_dfl: 140.4404 +2024/03/21 00:47:49 - mmengine - INFO - Epoch(train) [30][650/925] lr: 1.3070e-04 eta: 6:23:51 time: 0.4791 data_time: 0.0023 memory: 8095 grad_norm: 737.1197 loss: 399.6162 loss_cls: 135.4472 loss_bbox: 124.6239 loss_dfl: 139.5452 +2024/03/21 00:48:14 - mmengine - INFO - Epoch(train) [30][700/925] lr: 1.3070e-04 eta: 6:23:27 time: 0.5053 data_time: 0.0023 memory: 7949 grad_norm: 716.1743 loss: 395.9007 loss_cls: 133.6125 loss_bbox: 122.9798 loss_dfl: 139.3084 +2024/03/21 00:48:39 - mmengine - INFO - Epoch(train) [30][750/925] lr: 1.3070e-04 eta: 6:23:01 time: 0.4854 data_time: 0.0022 memory: 7775 grad_norm: 688.1588 loss: 405.8523 loss_cls: 140.4342 loss_bbox: 124.1848 loss_dfl: 141.2333 +2024/03/21 00:49:03 - mmengine - INFO - Epoch(train) [30][800/925] lr: 1.3070e-04 eta: 6:22:35 time: 0.4778 data_time: 0.0023 memory: 7935 grad_norm: 687.2548 loss: 400.6946 loss_cls: 135.8215 loss_bbox: 125.2750 loss_dfl: 139.5981 +2024/03/21 00:49:28 - mmengine - INFO - Epoch(train) [30][850/925] lr: 1.3070e-04 eta: 6:22:11 time: 0.5012 data_time: 0.0023 memory: 7789 grad_norm: 717.0396 loss: 397.4436 loss_cls: 135.0489 loss_bbox: 123.3274 loss_dfl: 139.0673 +2024/03/21 00:49:52 - mmengine - INFO - Epoch(train) [30][900/925] lr: 1.3070e-04 eta: 6:21:45 time: 0.4876 data_time: 0.0022 memory: 8029 grad_norm: 744.4846 loss: 406.4469 loss_cls: 139.6418 loss_bbox: 126.4656 loss_dfl: 140.3395 +2024/03/21 00:50:03 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:50:04 - mmengine - INFO - Saving checkpoint at 30 epochs +2024/03/21 00:50:12 - mmengine - INFO - Epoch(val) [30][ 50/625] eta: 0:00:20 time: 0.0355 data_time: 0.0008 memory: 7762 +2024/03/21 00:50:14 - mmengine - INFO - Epoch(val) [30][100/625] eta: 0:00:19 time: 0.0369 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:16 - mmengine - INFO - Epoch(val) [30][150/625] eta: 0:00:17 time: 0.0357 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:18 - mmengine - INFO - Epoch(val) [30][200/625] eta: 0:00:15 time: 0.0356 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:20 - mmengine - INFO - Epoch(val) [30][250/625] eta: 0:00:13 time: 0.0356 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:22 - mmengine - INFO - Epoch(val) [30][300/625] eta: 0:00:11 time: 0.0378 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:23 - mmengine - INFO - Epoch(val) [30][350/625] eta: 0:00:09 time: 0.0353 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:25 - mmengine - INFO - Epoch(val) [30][400/625] eta: 0:00:08 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:27 - mmengine - INFO - Epoch(val) [30][450/625] eta: 0:00:06 time: 0.0339 data_time: 0.0003 memory: 1244 +2024/03/21 00:50:28 - mmengine - INFO - Epoch(val) [30][500/625] eta: 0:00:04 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 00:50:30 - mmengine - INFO - Epoch(val) [30][550/625] eta: 0:00:02 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 00:50:31 - mmengine - INFO - Epoch(val) [30][600/625] eta: 0:00:00 time: 0.0282 data_time: 0.0002 memory: 1244 +2024/03/21 00:50:43 - mmengine - INFO - Evaluating bbox... +2024/03/21 00:51:58 - mmengine - INFO - bbox_mAP_copypaste: 0.499 0.663 0.545 0.313 0.551 0.658 +2024/03/21 00:52:00 - mmengine - INFO - Epoch(val) [30][625/625] coco/bbox_mAP: 0.4990 coco/bbox_mAP_50: 0.6630 coco/bbox_mAP_75: 0.5450 coco/bbox_mAP_s: 0.3130 coco/bbox_mAP_m: 0.5510 coco/bbox_mAP_l: 0.6580 data_time: 0.0002 time: 0.0278 +2024/03/21 00:52:28 - mmengine - INFO - Epoch(train) [31][ 50/925] lr: 1.2822e-04 eta: 6:21:11 time: 0.5485 data_time: 0.0614 memory: 7869 grad_norm: 731.8675 loss: 399.3450 loss_cls: 135.3144 loss_bbox: 124.5364 loss_dfl: 139.4942 +2024/03/21 00:52:53 - mmengine - INFO - Epoch(train) [31][100/925] lr: 1.2822e-04 eta: 6:20:46 time: 0.4994 data_time: 0.0025 memory: 8295 grad_norm: 699.7257 loss: 398.9574 loss_cls: 133.0813 loss_bbox: 125.4183 loss_dfl: 140.4578 +2024/03/21 00:53:16 - mmengine - INFO - Epoch(train) [31][150/925] lr: 1.2822e-04 eta: 6:20:20 time: 0.4761 data_time: 0.0023 memory: 7949 grad_norm: 697.4040 loss: 407.2002 loss_cls: 139.7640 loss_bbox: 126.5785 loss_dfl: 140.8576 +2024/03/21 00:53:41 - mmengine - INFO - Epoch(train) [31][200/925] lr: 1.2822e-04 eta: 6:19:56 time: 0.5007 data_time: 0.0023 memory: 7762 grad_norm: 818.1779 loss: 401.2322 loss_cls: 135.4850 loss_bbox: 125.2459 loss_dfl: 140.5012 +2024/03/21 00:54:07 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 00:54:07 - mmengine - INFO - Epoch(train) [31][250/925] lr: 1.2822e-04 eta: 6:19:32 time: 0.5067 data_time: 0.0023 memory: 8442 grad_norm: 756.6604 loss: 403.0518 loss_cls: 135.9214 loss_bbox: 126.1020 loss_dfl: 141.0284 +2024/03/21 00:54:31 - mmengine - INFO - Epoch(train) [31][300/925] lr: 1.2822e-04 eta: 6:19:06 time: 0.4849 data_time: 0.0024 memory: 7935 grad_norm: 786.9780 loss: 394.9866 loss_cls: 132.8028 loss_bbox: 123.2147 loss_dfl: 138.9691 +2024/03/21 00:54:56 - mmengine - INFO - Epoch(train) [31][350/925] lr: 1.2822e-04 eta: 6:18:42 time: 0.5027 data_time: 0.0021 memory: 7882 grad_norm: 705.5742 loss: 399.9050 loss_cls: 135.6695 loss_bbox: 123.7773 loss_dfl: 140.4583 +2024/03/21 00:55:21 - mmengine - INFO - Epoch(train) [31][400/925] lr: 1.2822e-04 eta: 6:18:17 time: 0.4941 data_time: 0.0024 memory: 8002 grad_norm: 741.6746 loss: 394.4602 loss_cls: 133.1909 loss_bbox: 121.2761 loss_dfl: 139.9931 +2024/03/21 00:55:46 - mmengine - INFO - Epoch(train) [31][450/925] lr: 1.2822e-04 eta: 6:17:53 time: 0.5051 data_time: 0.0022 memory: 7935 grad_norm: 700.2966 loss: 404.0191 loss_cls: 138.6195 loss_bbox: 125.1784 loss_dfl: 140.2211 +2024/03/21 00:56:11 - mmengine - INFO - Epoch(train) [31][500/925] lr: 1.2822e-04 eta: 6:17:29 time: 0.5025 data_time: 0.0023 memory: 8202 grad_norm: 724.9571 loss: 399.5046 loss_cls: 134.9711 loss_bbox: 124.8562 loss_dfl: 139.6774 +2024/03/21 00:56:36 - mmengine - INFO - Epoch(train) [31][550/925] lr: 1.2822e-04 eta: 6:17:04 time: 0.4842 data_time: 0.0022 memory: 8282 grad_norm: 748.2576 loss: 403.4081 loss_cls: 137.1595 loss_bbox: 125.9267 loss_dfl: 140.3218 +2024/03/21 00:57:01 - mmengine - INFO - Epoch(train) [31][600/925] lr: 1.2822e-04 eta: 6:16:40 time: 0.5141 data_time: 0.0022 memory: 8069 grad_norm: 715.1693 loss: 397.2791 loss_cls: 135.8198 loss_bbox: 122.2970 loss_dfl: 139.1622 +2024/03/21 00:57:27 - mmengine - INFO - Epoch(train) [31][650/925] lr: 1.2822e-04 eta: 6:16:16 time: 0.5043 data_time: 0.0023 memory: 8069 grad_norm: 682.1002 loss: 400.2874 loss_cls: 135.6058 loss_bbox: 125.2028 loss_dfl: 139.4788 +2024/03/21 00:57:51 - mmengine - INFO - Epoch(train) [31][700/925] lr: 1.2822e-04 eta: 6:15:50 time: 0.4782 data_time: 0.0023 memory: 7775 grad_norm: 725.8877 loss: 400.2169 loss_cls: 135.0762 loss_bbox: 124.2172 loss_dfl: 140.9234 +2024/03/21 00:58:17 - mmengine - INFO - Epoch(train) [31][750/925] lr: 1.2822e-04 eta: 6:15:28 time: 0.5222 data_time: 0.0021 memory: 7802 grad_norm: 707.2992 loss: 396.2148 loss_cls: 134.5657 loss_bbox: 122.2670 loss_dfl: 139.3822 +2024/03/21 00:58:42 - mmengine - INFO - Epoch(train) [31][800/925] lr: 1.2822e-04 eta: 6:15:04 time: 0.5094 data_time: 0.0023 memory: 7829 grad_norm: 691.0043 loss: 397.2054 loss_cls: 134.0783 loss_bbox: 123.8007 loss_dfl: 139.3264 +2024/03/21 00:59:06 - mmengine - INFO - Epoch(train) [31][850/925] lr: 1.2822e-04 eta: 6:14:39 time: 0.4842 data_time: 0.0023 memory: 8189 grad_norm: 697.8072 loss: 401.0033 loss_cls: 137.4329 loss_bbox: 124.3580 loss_dfl: 139.2124 +2024/03/21 00:59:32 - mmengine - INFO - Epoch(train) [31][900/925] lr: 1.2822e-04 eta: 6:14:15 time: 0.5078 data_time: 0.0024 memory: 8255 grad_norm: 697.9225 loss: 400.3106 loss_cls: 134.9028 loss_bbox: 125.2410 loss_dfl: 140.1669 +2024/03/21 00:59:44 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:00:12 - mmengine - INFO - Epoch(train) [32][ 50/925] lr: 1.2575e-04 eta: 6:13:42 time: 0.5527 data_time: 0.0686 memory: 7989 grad_norm: 753.0367 loss: 401.5286 loss_cls: 135.9853 loss_bbox: 125.6090 loss_dfl: 139.9343 +2024/03/21 01:00:38 - mmengine - INFO - Epoch(train) [32][100/925] lr: 1.2575e-04 eta: 6:13:18 time: 0.5053 data_time: 0.0022 memory: 7789 grad_norm: 756.0557 loss: 403.8191 loss_cls: 137.6986 loss_bbox: 125.6227 loss_dfl: 140.4977 +2024/03/21 01:01:03 - mmengine - INFO - Epoch(train) [32][150/925] lr: 1.2575e-04 eta: 6:12:54 time: 0.5056 data_time: 0.0023 memory: 8309 grad_norm: inf loss: 403.0977 loss_cls: 136.6140 loss_bbox: 125.6006 loss_dfl: 140.8831 +2024/03/21 01:01:28 - mmengine - INFO - Epoch(train) [32][200/925] lr: 1.2575e-04 eta: 6:12:29 time: 0.4886 data_time: 0.0023 memory: 8162 grad_norm: 727.6335 loss: 398.1540 loss_cls: 134.8987 loss_bbox: 123.8420 loss_dfl: 139.4133 +2024/03/21 01:01:54 - mmengine - INFO - Epoch(train) [32][250/925] lr: 1.2575e-04 eta: 6:12:07 time: 0.5277 data_time: 0.0022 memory: 8002 grad_norm: 740.5303 loss: 399.1320 loss_cls: 135.2483 loss_bbox: 123.0554 loss_dfl: 140.8283 +2024/03/21 01:02:19 - mmengine - INFO - Epoch(train) [32][300/925] lr: 1.2575e-04 eta: 6:11:42 time: 0.4954 data_time: 0.0022 memory: 7682 grad_norm: 692.4410 loss: 396.9791 loss_cls: 133.1519 loss_bbox: 123.7086 loss_dfl: 140.1186 +2024/03/21 01:02:31 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:02:44 - mmengine - INFO - Epoch(train) [32][350/925] lr: 1.2575e-04 eta: 6:11:18 time: 0.5016 data_time: 0.0023 memory: 7722 grad_norm: 691.0704 loss: 396.0132 loss_cls: 134.0966 loss_bbox: 123.9760 loss_dfl: 137.9407 +2024/03/21 01:03:10 - mmengine - INFO - Epoch(train) [32][400/925] lr: 1.2575e-04 eta: 6:10:55 time: 0.5209 data_time: 0.0023 memory: 8042 grad_norm: 704.7361 loss: 392.2969 loss_cls: 132.9940 loss_bbox: 121.1672 loss_dfl: 138.1356 +2024/03/21 01:03:35 - mmengine - INFO - Epoch(train) [32][450/925] lr: 1.2575e-04 eta: 6:10:30 time: 0.4932 data_time: 0.0023 memory: 7762 grad_norm: 748.5423 loss: 395.4652 loss_cls: 134.5749 loss_bbox: 121.9590 loss_dfl: 138.9313 +2024/03/21 01:04:00 - mmengine - INFO - Epoch(train) [32][500/925] lr: 1.2575e-04 eta: 6:10:07 time: 0.5162 data_time: 0.0023 memory: 7909 grad_norm: 753.0196 loss: 399.5026 loss_cls: 135.1749 loss_bbox: 124.8330 loss_dfl: 139.4946 +2024/03/21 01:04:26 - mmengine - INFO - Epoch(train) [32][550/925] lr: 1.2575e-04 eta: 6:09:43 time: 0.5127 data_time: 0.0023 memory: 7709 grad_norm: 726.9321 loss: 397.1444 loss_cls: 133.8439 loss_bbox: 123.0904 loss_dfl: 140.2101 +2024/03/21 01:04:50 - mmengine - INFO - Epoch(train) [32][600/925] lr: 1.2575e-04 eta: 6:09:18 time: 0.4814 data_time: 0.0023 memory: 8055 grad_norm: 734.4952 loss: 394.1775 loss_cls: 133.5748 loss_bbox: 122.7772 loss_dfl: 137.8255 +2024/03/21 01:05:16 - mmengine - INFO - Epoch(train) [32][650/925] lr: 1.2575e-04 eta: 6:08:55 time: 0.5226 data_time: 0.0022 memory: 7775 grad_norm: 703.2012 loss: 399.7922 loss_cls: 134.7181 loss_bbox: 125.0947 loss_dfl: 139.9794 +2024/03/21 01:05:42 - mmengine - INFO - Epoch(train) [32][700/925] lr: 1.2575e-04 eta: 6:08:31 time: 0.5079 data_time: 0.0024 memory: 7762 grad_norm: 725.6004 loss: 393.4869 loss_cls: 132.1617 loss_bbox: 122.2921 loss_dfl: 139.0332 +2024/03/21 01:06:06 - mmengine - INFO - Epoch(train) [32][750/925] lr: 1.2575e-04 eta: 6:08:06 time: 0.4923 data_time: 0.0023 memory: 8095 grad_norm: 783.0456 loss: 399.8081 loss_cls: 135.7537 loss_bbox: 123.8528 loss_dfl: 140.2016 +2024/03/21 01:06:32 - mmengine - INFO - Epoch(train) [32][800/925] lr: 1.2575e-04 eta: 6:07:42 time: 0.5102 data_time: 0.0023 memory: 8055 grad_norm: 668.3534 loss: 400.0492 loss_cls: 135.2038 loss_bbox: 125.2536 loss_dfl: 139.5917 +2024/03/21 01:06:57 - mmengine - INFO - Epoch(train) [32][850/925] lr: 1.2575e-04 eta: 6:07:18 time: 0.4996 data_time: 0.0023 memory: 7962 grad_norm: 718.6479 loss: 400.0101 loss_cls: 136.3305 loss_bbox: 124.1024 loss_dfl: 139.5772 +2024/03/21 01:07:22 - mmengine - INFO - Epoch(train) [32][900/925] lr: 1.2575e-04 eta: 6:06:54 time: 0.5035 data_time: 0.0023 memory: 7989 grad_norm: 688.0968 loss: 399.1168 loss_cls: 136.8611 loss_bbox: 122.9108 loss_dfl: 139.3448 +2024/03/21 01:07:34 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:08:02 - mmengine - INFO - Epoch(train) [33][ 50/925] lr: 1.2328e-04 eta: 6:06:20 time: 0.5490 data_time: 0.0497 memory: 7855 grad_norm: 730.1586 loss: 397.2433 loss_cls: 134.8052 loss_bbox: 122.6977 loss_dfl: 139.7403 +2024/03/21 01:08:27 - mmengine - INFO - Epoch(train) [33][100/925] lr: 1.2328e-04 eta: 6:05:56 time: 0.5033 data_time: 0.0123 memory: 7775 grad_norm: 689.4097 loss: 407.9757 loss_cls: 141.3747 loss_bbox: 125.3669 loss_dfl: 141.2341 +2024/03/21 01:08:54 - mmengine - INFO - Epoch(train) [33][150/925] lr: 1.2328e-04 eta: 6:05:33 time: 0.5242 data_time: 0.0023 memory: 7829 grad_norm: 727.3112 loss: 402.0118 loss_cls: 137.3693 loss_bbox: 124.2233 loss_dfl: 140.4193 +2024/03/21 01:09:19 - mmengine - INFO - Epoch(train) [33][200/925] lr: 1.2328e-04 eta: 6:05:09 time: 0.4956 data_time: 0.0023 memory: 7895 grad_norm: 762.3030 loss: 395.9624 loss_cls: 134.2818 loss_bbox: 122.7087 loss_dfl: 138.9719 +2024/03/21 01:09:44 - mmengine - INFO - Epoch(train) [33][250/925] lr: 1.2328e-04 eta: 6:04:45 time: 0.5080 data_time: 0.0023 memory: 7962 grad_norm: 732.2996 loss: 398.6308 loss_cls: 132.7576 loss_bbox: 125.0029 loss_dfl: 140.8703 +2024/03/21 01:10:10 - mmengine - INFO - Epoch(train) [33][300/925] lr: 1.2328e-04 eta: 6:04:22 time: 0.5263 data_time: 0.0024 memory: 7895 grad_norm: 824.3843 loss: 406.6389 loss_cls: 138.7234 loss_bbox: 126.5845 loss_dfl: 141.3310 +2024/03/21 01:10:34 - mmengine - INFO - Epoch(train) [33][350/925] lr: 1.2328e-04 eta: 6:03:57 time: 0.4829 data_time: 0.0023 memory: 8002 grad_norm: 752.0353 loss: 397.0234 loss_cls: 133.9708 loss_bbox: 123.6816 loss_dfl: 139.3710 +2024/03/21 01:11:01 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:11:01 - mmengine - INFO - Epoch(train) [33][400/925] lr: 1.2328e-04 eta: 6:03:34 time: 0.5225 data_time: 0.0023 memory: 8095 grad_norm: 775.4778 loss: 402.6146 loss_cls: 136.2075 loss_bbox: 126.2757 loss_dfl: 140.1314 +2024/03/21 01:11:27 - mmengine - INFO - Epoch(train) [33][450/925] lr: 1.2328e-04 eta: 6:03:11 time: 0.5179 data_time: 0.0022 memory: 7989 grad_norm: 665.1526 loss: 399.8818 loss_cls: 136.3800 loss_bbox: 124.2400 loss_dfl: 139.2618 +2024/03/21 01:11:51 - mmengine - INFO - Epoch(train) [33][500/925] lr: 1.2328e-04 eta: 6:02:45 time: 0.4855 data_time: 0.0022 memory: 7842 grad_norm: 745.9696 loss: 402.4133 loss_cls: 137.3228 loss_bbox: 124.9974 loss_dfl: 140.0931 +2024/03/21 01:12:17 - mmengine - INFO - Epoch(train) [33][550/925] lr: 1.2328e-04 eta: 6:02:23 time: 0.5313 data_time: 0.0023 memory: 7802 grad_norm: 737.0011 loss: 401.1339 loss_cls: 136.2728 loss_bbox: 124.9556 loss_dfl: 139.9054 +2024/03/21 01:12:42 - mmengine - INFO - Epoch(train) [33][600/925] lr: 1.2328e-04 eta: 6:01:58 time: 0.4960 data_time: 0.0023 memory: 7935 grad_norm: 737.0675 loss: 396.3058 loss_cls: 134.2119 loss_bbox: 123.2405 loss_dfl: 138.8533 +2024/03/21 01:13:07 - mmengine - INFO - Epoch(train) [33][650/925] lr: 1.2328e-04 eta: 6:01:34 time: 0.5033 data_time: 0.0023 memory: 7975 grad_norm: 757.9208 loss: 402.6709 loss_cls: 137.4021 loss_bbox: 125.0778 loss_dfl: 140.1910 +2024/03/21 01:13:34 - mmengine - INFO - Epoch(train) [33][700/925] lr: 1.2328e-04 eta: 6:01:11 time: 0.5258 data_time: 0.0023 memory: 7775 grad_norm: 725.3230 loss: 404.3163 loss_cls: 137.1275 loss_bbox: 125.8776 loss_dfl: 141.3112 +2024/03/21 01:13:59 - mmengine - INFO - Epoch(train) [33][750/925] lr: 1.2328e-04 eta: 6:00:46 time: 0.4972 data_time: 0.0022 memory: 8082 grad_norm: 687.3714 loss: 397.0195 loss_cls: 133.6457 loss_bbox: 123.1768 loss_dfl: 140.1969 +2024/03/21 01:14:24 - mmengine - INFO - Epoch(train) [33][800/925] lr: 1.2328e-04 eta: 6:00:23 time: 0.5108 data_time: 0.0023 memory: 8095 grad_norm: 696.5028 loss: 396.3899 loss_cls: 133.8094 loss_bbox: 123.1469 loss_dfl: 139.4336 +2024/03/21 01:14:50 - mmengine - INFO - Epoch(train) [33][850/925] lr: 1.2328e-04 eta: 5:59:59 time: 0.5177 data_time: 0.0024 memory: 7789 grad_norm: 723.3035 loss: 393.6145 loss_cls: 133.3653 loss_bbox: 120.9155 loss_dfl: 139.3338 +2024/03/21 01:15:15 - mmengine - INFO - Epoch(train) [33][900/925] lr: 1.2328e-04 eta: 5:59:34 time: 0.4912 data_time: 0.0023 memory: 8002 grad_norm: 782.2249 loss: 403.8474 loss_cls: 136.1051 loss_bbox: 127.4955 loss_dfl: 140.2468 +2024/03/21 01:15:28 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:15:57 - mmengine - INFO - Epoch(train) [34][ 50/925] lr: 1.2080e-04 eta: 5:59:04 time: 0.5840 data_time: 0.0559 memory: 8002 grad_norm: 707.4463 loss: 393.3859 loss_cls: 131.7745 loss_bbox: 122.4790 loss_dfl: 139.1325 +2024/03/21 01:16:22 - mmengine - INFO - Epoch(train) [34][100/925] lr: 1.2080e-04 eta: 5:58:40 time: 0.5024 data_time: 0.0024 memory: 7989 grad_norm: 763.2969 loss: 402.5058 loss_cls: 136.5810 loss_bbox: 125.2658 loss_dfl: 140.6590 +2024/03/21 01:16:47 - mmengine - INFO - Epoch(train) [34][150/925] lr: 1.2080e-04 eta: 5:58:15 time: 0.5020 data_time: 0.0024 memory: 8082 grad_norm: 679.2743 loss: 399.1605 loss_cls: 134.1281 loss_bbox: 125.3055 loss_dfl: 139.7269 +2024/03/21 01:17:13 - mmengine - INFO - Epoch(train) [34][200/925] lr: 1.2080e-04 eta: 5:57:51 time: 0.5070 data_time: 0.0022 memory: 7815 grad_norm: 733.0679 loss: 400.2960 loss_cls: 135.7706 loss_bbox: 124.9808 loss_dfl: 139.5447 +2024/03/21 01:17:37 - mmengine - INFO - Epoch(train) [34][250/925] lr: 1.2080e-04 eta: 5:57:26 time: 0.4910 data_time: 0.0022 memory: 8082 grad_norm: 727.4245 loss: 406.3317 loss_cls: 138.6580 loss_bbox: 127.0403 loss_dfl: 140.6335 +2024/03/21 01:18:03 - mmengine - INFO - Epoch(train) [34][300/925] lr: 1.2080e-04 eta: 5:57:03 time: 0.5157 data_time: 0.0022 memory: 7962 grad_norm: 714.0381 loss: 397.1790 loss_cls: 133.0006 loss_bbox: 124.9930 loss_dfl: 139.1853 +2024/03/21 01:18:29 - mmengine - INFO - Epoch(train) [34][350/925] lr: 1.2080e-04 eta: 5:56:38 time: 0.5063 data_time: 0.0022 memory: 7815 grad_norm: 741.8500 loss: 398.6037 loss_cls: 133.1159 loss_bbox: 125.4963 loss_dfl: 139.9915 +2024/03/21 01:18:53 - mmengine - INFO - Epoch(train) [34][400/925] lr: 1.2080e-04 eta: 5:56:13 time: 0.4845 data_time: 0.0023 memory: 8175 grad_norm: 800.9773 loss: 395.5841 loss_cls: 133.4035 loss_bbox: 122.6262 loss_dfl: 139.5544 +2024/03/21 01:19:19 - mmengine - INFO - Epoch(train) [34][450/925] lr: 1.2080e-04 eta: 5:55:50 time: 0.5230 data_time: 0.0023 memory: 7789 grad_norm: 732.8257 loss: 398.5196 loss_cls: 136.2919 loss_bbox: 123.1272 loss_dfl: 139.1006 +2024/03/21 01:19:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:19:44 - mmengine - INFO - Epoch(train) [34][500/925] lr: 1.2080e-04 eta: 5:55:26 time: 0.5066 data_time: 0.0023 memory: 7842 grad_norm: 758.2619 loss: 397.3634 loss_cls: 133.2312 loss_bbox: 124.9088 loss_dfl: 139.2234 +2024/03/21 01:20:09 - mmengine - INFO - Epoch(train) [34][550/925] lr: 1.2080e-04 eta: 5:55:01 time: 0.4937 data_time: 0.0022 memory: 7949 grad_norm: 674.2236 loss: 402.7376 loss_cls: 137.1555 loss_bbox: 125.5084 loss_dfl: 140.0737 +2024/03/21 01:20:35 - mmengine - INFO - Epoch(train) [34][600/925] lr: 1.2080e-04 eta: 5:54:38 time: 0.5217 data_time: 0.0023 memory: 7789 grad_norm: 712.9678 loss: 399.6333 loss_cls: 136.4389 loss_bbox: 123.6151 loss_dfl: 139.5793 +2024/03/21 01:20:59 - mmengine - INFO - Epoch(train) [34][650/925] lr: 1.2080e-04 eta: 5:54:12 time: 0.4848 data_time: 0.0025 memory: 7802 grad_norm: 673.5788 loss: 396.0182 loss_cls: 134.5938 loss_bbox: 122.0172 loss_dfl: 139.4071 +2024/03/21 01:21:25 - mmengine - INFO - Epoch(train) [34][700/925] lr: 1.2080e-04 eta: 5:53:49 time: 0.5135 data_time: 0.0024 memory: 7949 grad_norm: 691.3615 loss: 396.1286 loss_cls: 132.3146 loss_bbox: 124.1051 loss_dfl: 139.7089 +2024/03/21 01:21:51 - mmengine - INFO - Epoch(train) [34][750/925] lr: 1.2080e-04 eta: 5:53:25 time: 0.5084 data_time: 0.0024 memory: 8002 grad_norm: 704.2504 loss: 390.3034 loss_cls: 130.7544 loss_bbox: 121.0671 loss_dfl: 138.4819 +2024/03/21 01:22:15 - mmengine - INFO - Epoch(train) [34][800/925] lr: 1.2080e-04 eta: 5:52:59 time: 0.4795 data_time: 0.0023 memory: 8002 grad_norm: 675.0206 loss: 401.7692 loss_cls: 134.8742 loss_bbox: 125.7131 loss_dfl: 141.1819 +2024/03/21 01:22:40 - mmengine - INFO - Epoch(train) [34][850/925] lr: 1.2080e-04 eta: 5:52:35 time: 0.5113 data_time: 0.0023 memory: 8002 grad_norm: inf loss: 393.9552 loss_cls: 131.2214 loss_bbox: 122.5990 loss_dfl: 140.1348 +2024/03/21 01:23:06 - mmengine - INFO - Epoch(train) [34][900/925] lr: 1.2080e-04 eta: 5:52:12 time: 0.5192 data_time: 0.0022 memory: 8135 grad_norm: 705.3373 loss: 399.3110 loss_cls: 134.2194 loss_bbox: 124.3678 loss_dfl: 140.7238 +2024/03/21 01:23:17 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:23:46 - mmengine - INFO - Epoch(train) [35][ 50/925] lr: 1.1833e-04 eta: 5:51:37 time: 0.5586 data_time: 0.0590 memory: 7975 grad_norm: 737.2558 loss: 396.8941 loss_cls: 133.5043 loss_bbox: 125.1996 loss_dfl: 138.1902 +2024/03/21 01:24:11 - mmengine - INFO - Epoch(train) [35][100/925] lr: 1.1833e-04 eta: 5:51:13 time: 0.5056 data_time: 0.0021 memory: 7989 grad_norm: 689.9008 loss: 404.9136 loss_cls: 137.8980 loss_bbox: 126.4846 loss_dfl: 140.5310 +2024/03/21 01:24:35 - mmengine - INFO - Epoch(train) [35][150/925] lr: 1.1833e-04 eta: 5:50:47 time: 0.4824 data_time: 0.0023 memory: 7855 grad_norm: 745.1980 loss: 398.8018 loss_cls: 132.8301 loss_bbox: 126.4907 loss_dfl: 139.4810 +2024/03/21 01:25:02 - mmengine - INFO - Epoch(train) [35][200/925] lr: 1.1833e-04 eta: 5:50:24 time: 0.5291 data_time: 0.0024 memory: 7842 grad_norm: 698.5196 loss: 389.7476 loss_cls: 131.2112 loss_bbox: 120.8131 loss_dfl: 137.7233 +2024/03/21 01:25:27 - mmengine - INFO - Epoch(train) [35][250/925] lr: 1.1833e-04 eta: 5:50:01 time: 0.5137 data_time: 0.0025 memory: 8015 grad_norm: 725.3006 loss: 399.7529 loss_cls: 135.0211 loss_bbox: 123.4964 loss_dfl: 141.2354 +2024/03/21 01:25:52 - mmengine - INFO - Epoch(train) [35][300/925] lr: 1.1833e-04 eta: 5:49:35 time: 0.4837 data_time: 0.0024 memory: 7882 grad_norm: 726.7415 loss: 400.2978 loss_cls: 134.5863 loss_bbox: 125.5687 loss_dfl: 140.1428 +2024/03/21 01:26:18 - mmengine - INFO - Epoch(train) [35][350/925] lr: 1.1833e-04 eta: 5:49:12 time: 0.5226 data_time: 0.0024 memory: 7882 grad_norm: 718.7607 loss: 404.6163 loss_cls: 136.7479 loss_bbox: 125.7715 loss_dfl: 142.0969 +2024/03/21 01:26:44 - mmengine - INFO - Epoch(train) [35][400/925] lr: 1.1833e-04 eta: 5:48:48 time: 0.5161 data_time: 0.0023 memory: 8135 grad_norm: 704.9077 loss: 396.8272 loss_cls: 132.3679 loss_bbox: 124.0497 loss_dfl: 140.4096 +2024/03/21 01:27:08 - mmengine - INFO - Epoch(train) [35][450/925] lr: 1.1833e-04 eta: 5:48:23 time: 0.4928 data_time: 0.0022 memory: 7935 grad_norm: 764.6117 loss: 390.7945 loss_cls: 130.8016 loss_bbox: 121.2394 loss_dfl: 138.7534 +2024/03/21 01:27:34 - mmengine - INFO - Epoch(train) [35][500/925] lr: 1.1833e-04 eta: 5:48:00 time: 0.5205 data_time: 0.0023 memory: 8149 grad_norm: 775.7281 loss: 399.5943 loss_cls: 134.7213 loss_bbox: 124.4787 loss_dfl: 140.3943 +2024/03/21 01:27:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:27:59 - mmengine - INFO - Epoch(train) [35][550/925] lr: 1.1833e-04 eta: 5:47:35 time: 0.5010 data_time: 0.0024 memory: 7722 grad_norm: 766.1348 loss: 392.9614 loss_cls: 130.7712 loss_bbox: 123.1906 loss_dfl: 138.9995 +2024/03/21 01:28:24 - mmengine - INFO - Epoch(train) [35][600/925] lr: 1.1833e-04 eta: 5:47:11 time: 0.5015 data_time: 0.0024 memory: 7895 grad_norm: 728.5875 loss: 397.6096 loss_cls: 134.4932 loss_bbox: 123.6882 loss_dfl: 139.4282 +2024/03/21 01:28:51 - mmengine - INFO - Epoch(train) [35][650/925] lr: 1.1833e-04 eta: 5:46:48 time: 0.5218 data_time: 0.0023 memory: 7829 grad_norm: 708.9137 loss: 390.6497 loss_cls: 130.2367 loss_bbox: 121.6501 loss_dfl: 138.7629 +2024/03/21 01:29:15 - mmengine - INFO - Epoch(train) [35][700/925] lr: 1.1833e-04 eta: 5:46:23 time: 0.4933 data_time: 0.0024 memory: 8015 grad_norm: 748.7337 loss: 400.4704 loss_cls: 136.6716 loss_bbox: 124.5949 loss_dfl: 139.2039 +2024/03/21 01:29:41 - mmengine - INFO - Epoch(train) [35][750/925] lr: 1.1833e-04 eta: 5:45:59 time: 0.5078 data_time: 0.0025 memory: 7909 grad_norm: 720.0970 loss: 400.6611 loss_cls: 135.9500 loss_bbox: 124.3500 loss_dfl: 140.3611 +2024/03/21 01:30:06 - mmengine - INFO - Epoch(train) [35][800/925] lr: 1.1833e-04 eta: 5:45:34 time: 0.5047 data_time: 0.0024 memory: 8229 grad_norm: 707.3489 loss: 393.1836 loss_cls: 130.5704 loss_bbox: 124.0708 loss_dfl: 138.5424 +2024/03/21 01:30:30 - mmengine - INFO - Epoch(train) [35][850/925] lr: 1.1833e-04 eta: 5:45:08 time: 0.4799 data_time: 0.0025 memory: 7695 grad_norm: 736.0521 loss: 394.1552 loss_cls: 132.4449 loss_bbox: 122.5784 loss_dfl: 139.1318 +2024/03/21 01:30:56 - mmengine - INFO - Epoch(train) [35][900/925] lr: 1.1833e-04 eta: 5:44:45 time: 0.5216 data_time: 0.0024 memory: 7895 grad_norm: 727.5759 loss: 399.4447 loss_cls: 135.1412 loss_bbox: 124.6459 loss_dfl: 139.6576 +2024/03/21 01:31:08 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:31:09 - mmengine - INFO - Saving checkpoint at 35 epochs +2024/03/21 01:31:18 - mmengine - INFO - Epoch(val) [35][ 50/625] eta: 0:00:21 time: 0.0369 data_time: 0.0008 memory: 7762 +2024/03/21 01:31:19 - mmengine - INFO - Epoch(val) [35][100/625] eta: 0:00:19 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:21 - mmengine - INFO - Epoch(val) [35][150/625] eta: 0:00:17 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:23 - mmengine - INFO - Epoch(val) [35][200/625] eta: 0:00:15 time: 0.0350 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:25 - mmengine - INFO - Epoch(val) [35][250/625] eta: 0:00:13 time: 0.0355 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:27 - mmengine - INFO - Epoch(val) [35][300/625] eta: 0:00:11 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:28 - mmengine - INFO - Epoch(val) [35][350/625] eta: 0:00:09 time: 0.0374 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:30 - mmengine - INFO - Epoch(val) [35][400/625] eta: 0:00:08 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:32 - mmengine - INFO - Epoch(val) [35][450/625] eta: 0:00:06 time: 0.0335 data_time: 0.0003 memory: 1244 +2024/03/21 01:31:33 - mmengine - INFO - Epoch(val) [35][500/625] eta: 0:00:04 time: 0.0281 data_time: 0.0002 memory: 1244 +2024/03/21 01:31:35 - mmengine - INFO - Epoch(val) [35][550/625] eta: 0:00:02 time: 0.0285 data_time: 0.0002 memory: 1244 +2024/03/21 01:31:36 - mmengine - INFO - Epoch(val) [35][600/625] eta: 0:00:00 time: 0.0282 data_time: 0.0002 memory: 1244 +2024/03/21 01:31:48 - mmengine - INFO - Evaluating bbox... +2024/03/21 01:33:01 - mmengine - INFO - bbox_mAP_copypaste: 0.501 0.665 0.546 0.316 0.553 0.659 +2024/03/21 01:33:04 - mmengine - INFO - Epoch(val) [35][625/625] coco/bbox_mAP: 0.5010 coco/bbox_mAP_50: 0.6650 coco/bbox_mAP_75: 0.5460 coco/bbox_mAP_s: 0.3160 coco/bbox_mAP_m: 0.5530 coco/bbox_mAP_l: 0.6590 data_time: 0.0002 time: 0.0283 +2024/03/21 01:33:31 - mmengine - INFO - Epoch(train) [36][ 50/925] lr: 1.1585e-04 eta: 5:44:10 time: 0.5381 data_time: 0.0675 memory: 7735 grad_norm: 731.5171 loss: 391.2459 loss_cls: 129.7209 loss_bbox: 121.9865 loss_dfl: 139.5384 +2024/03/21 01:33:56 - mmengine - INFO - Epoch(train) [36][100/925] lr: 1.1585e-04 eta: 5:43:46 time: 0.5083 data_time: 0.0023 memory: 7922 grad_norm: 753.0020 loss: 396.6308 loss_cls: 133.1232 loss_bbox: 123.9658 loss_dfl: 139.5418 +2024/03/21 01:34:21 - mmengine - INFO - Epoch(train) [36][150/925] lr: 1.1585e-04 eta: 5:43:22 time: 0.5034 data_time: 0.0023 memory: 8029 grad_norm: 703.2998 loss: 399.6770 loss_cls: 134.9239 loss_bbox: 124.4812 loss_dfl: 140.2719 +2024/03/21 01:34:45 - mmengine - INFO - Epoch(train) [36][200/925] lr: 1.1585e-04 eta: 5:42:56 time: 0.4845 data_time: 0.0023 memory: 7882 grad_norm: 709.2901 loss: 393.7673 loss_cls: 132.4395 loss_bbox: 123.2667 loss_dfl: 138.0611 +2024/03/21 01:35:10 - mmengine - INFO - Epoch(train) [36][250/925] lr: 1.1585e-04 eta: 5:42:32 time: 0.4966 data_time: 0.0024 memory: 7962 grad_norm: 676.2921 loss: 397.8895 loss_cls: 134.3764 loss_bbox: 123.8631 loss_dfl: 139.6500 +2024/03/21 01:35:35 - mmengine - INFO - Epoch(train) [36][300/925] lr: 1.1585e-04 eta: 5:42:06 time: 0.4880 data_time: 0.0024 memory: 7909 grad_norm: 722.0320 loss: 398.5309 loss_cls: 134.7357 loss_bbox: 124.3276 loss_dfl: 139.4676 +2024/03/21 01:36:00 - mmengine - INFO - Epoch(train) [36][350/925] lr: 1.1585e-04 eta: 5:41:42 time: 0.5130 data_time: 0.0022 memory: 7789 grad_norm: 701.5015 loss: 399.5696 loss_cls: 134.7869 loss_bbox: 124.6598 loss_dfl: 140.1229 +2024/03/21 01:36:26 - mmengine - INFO - Epoch(train) [36][400/925] lr: 1.1585e-04 eta: 5:41:19 time: 0.5153 data_time: 0.0023 memory: 8042 grad_norm: 704.7452 loss: 405.8514 loss_cls: 137.8254 loss_bbox: 126.7336 loss_dfl: 141.2925 +2024/03/21 01:36:51 - mmengine - INFO - Epoch(train) [36][450/925] lr: 1.1585e-04 eta: 5:40:54 time: 0.4991 data_time: 0.0024 memory: 7895 grad_norm: 732.4875 loss: 398.5207 loss_cls: 134.3065 loss_bbox: 124.5890 loss_dfl: 139.6252 +2024/03/21 01:37:17 - mmengine - INFO - Epoch(train) [36][500/925] lr: 1.1585e-04 eta: 5:40:30 time: 0.5129 data_time: 0.0022 memory: 7802 grad_norm: 729.1301 loss: 401.7638 loss_cls: 135.3161 loss_bbox: 124.8583 loss_dfl: 141.5894 +2024/03/21 01:37:43 - mmengine - INFO - Epoch(train) [36][550/925] lr: 1.1585e-04 eta: 5:40:06 time: 0.5147 data_time: 0.0023 memory: 8202 grad_norm: 691.9806 loss: 399.2989 loss_cls: 135.3919 loss_bbox: 124.1741 loss_dfl: 139.7329 +2024/03/21 01:38:07 - mmengine - INFO - Epoch(train) [36][600/925] lr: 1.1585e-04 eta: 5:39:41 time: 0.4881 data_time: 0.0023 memory: 8122 grad_norm: 681.4908 loss: 396.4245 loss_cls: 133.0326 loss_bbox: 124.2871 loss_dfl: 139.1048 +2024/03/21 01:38:20 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:38:33 - mmengine - INFO - Epoch(train) [36][650/925] lr: 1.1585e-04 eta: 5:39:18 time: 0.5206 data_time: 0.0023 memory: 8109 grad_norm: 741.4714 loss: 398.0343 loss_cls: 133.9229 loss_bbox: 124.8345 loss_dfl: 139.2769 +2024/03/21 01:38:58 - mmengine - INFO - Epoch(train) [36][700/925] lr: 1.1585e-04 eta: 5:38:53 time: 0.4979 data_time: 0.0023 memory: 8135 grad_norm: 710.9588 loss: 399.5726 loss_cls: 133.3529 loss_bbox: 126.5064 loss_dfl: 139.7133 +2024/03/21 01:39:23 - mmengine - INFO - Epoch(train) [36][750/925] lr: 1.1585e-04 eta: 5:38:28 time: 0.4931 data_time: 0.0024 memory: 7775 grad_norm: 724.3896 loss: 396.0774 loss_cls: 132.8650 loss_bbox: 124.6414 loss_dfl: 138.5710 +2024/03/21 01:39:49 - mmengine - INFO - Epoch(train) [36][800/925] lr: 1.1585e-04 eta: 5:38:05 time: 0.5217 data_time: 0.0022 memory: 8322 grad_norm: 672.8046 loss: 397.4201 loss_cls: 133.0193 loss_bbox: 124.8367 loss_dfl: 139.5642 +2024/03/21 01:40:13 - mmengine - INFO - Epoch(train) [36][850/925] lr: 1.1585e-04 eta: 5:37:39 time: 0.4912 data_time: 0.0024 memory: 7829 grad_norm: 716.2468 loss: 396.7215 loss_cls: 133.5058 loss_bbox: 123.7110 loss_dfl: 139.5047 +2024/03/21 01:40:39 - mmengine - INFO - Epoch(train) [36][900/925] lr: 1.1585e-04 eta: 5:37:15 time: 0.5136 data_time: 0.0024 memory: 7949 grad_norm: 741.5114 loss: 396.9149 loss_cls: 132.8702 loss_bbox: 124.3900 loss_dfl: 139.6547 +2024/03/21 01:40:51 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:41:20 - mmengine - INFO - Epoch(train) [37][ 50/925] lr: 1.1338e-04 eta: 5:36:42 time: 0.5569 data_time: 0.0644 memory: 7909 grad_norm: 717.2762 loss: 392.6149 loss_cls: 130.6225 loss_bbox: 123.4911 loss_dfl: 138.5013 +2024/03/21 01:41:44 - mmengine - INFO - Epoch(train) [37][100/925] lr: 1.1338e-04 eta: 5:36:17 time: 0.4921 data_time: 0.0023 memory: 8069 grad_norm: 692.4557 loss: 397.9734 loss_cls: 134.5350 loss_bbox: 123.0796 loss_dfl: 140.3588 +2024/03/21 01:42:10 - mmengine - INFO - Epoch(train) [37][150/925] lr: 1.1338e-04 eta: 5:35:52 time: 0.5031 data_time: 0.0024 memory: 7735 grad_norm: 736.9511 loss: 396.9750 loss_cls: 132.7527 loss_bbox: 123.9059 loss_dfl: 140.3165 +2024/03/21 01:42:34 - mmengine - INFO - Epoch(train) [37][200/925] lr: 1.1338e-04 eta: 5:35:26 time: 0.4831 data_time: 0.0024 memory: 7722 grad_norm: 732.7466 loss: 394.2723 loss_cls: 131.1749 loss_bbox: 123.7407 loss_dfl: 139.3567 +2024/03/21 01:42:59 - mmengine - INFO - Epoch(train) [37][250/925] lr: 1.1338e-04 eta: 5:35:02 time: 0.5065 data_time: 0.0024 memory: 8029 grad_norm: 713.2789 loss: 393.5018 loss_cls: 131.3758 loss_bbox: 123.2957 loss_dfl: 138.8303 +2024/03/21 01:43:25 - mmengine - INFO - Epoch(train) [37][300/925] lr: 1.1338e-04 eta: 5:34:38 time: 0.5087 data_time: 0.0023 memory: 7775 grad_norm: 725.5355 loss: 395.0546 loss_cls: 132.8172 loss_bbox: 123.2469 loss_dfl: 138.9905 +2024/03/21 01:43:48 - mmengine - INFO - Epoch(train) [37][350/925] lr: 1.1338e-04 eta: 5:34:12 time: 0.4767 data_time: 0.0024 memory: 8122 grad_norm: 732.1138 loss: 399.0644 loss_cls: 135.2273 loss_bbox: 124.1563 loss_dfl: 139.6808 +2024/03/21 01:44:14 - mmengine - INFO - Epoch(train) [37][400/925] lr: 1.1338e-04 eta: 5:33:48 time: 0.5161 data_time: 0.0024 memory: 8109 grad_norm: 687.6884 loss: 396.4735 loss_cls: 132.8294 loss_bbox: 122.8911 loss_dfl: 140.7530 +2024/03/21 01:44:39 - mmengine - INFO - Epoch(train) [37][450/925] lr: 1.1338e-04 eta: 5:33:23 time: 0.4980 data_time: 0.0024 memory: 7962 grad_norm: 690.6028 loss: 392.5062 loss_cls: 130.7471 loss_bbox: 122.9935 loss_dfl: 138.7656 +2024/03/21 01:45:03 - mmengine - INFO - Epoch(train) [37][500/925] lr: 1.1338e-04 eta: 5:32:57 time: 0.4784 data_time: 0.0024 memory: 8002 grad_norm: 714.3958 loss: 401.2199 loss_cls: 135.9141 loss_bbox: 124.9499 loss_dfl: 140.3559 +2024/03/21 01:45:29 - mmengine - INFO - Epoch(train) [37][550/925] lr: 1.1338e-04 eta: 5:32:34 time: 0.5199 data_time: 0.0025 memory: 8295 grad_norm: 705.7138 loss: 401.5972 loss_cls: 136.2279 loss_bbox: 125.0098 loss_dfl: 140.3595 +2024/03/21 01:45:54 - mmengine - INFO - Epoch(train) [37][600/925] lr: 1.1338e-04 eta: 5:32:09 time: 0.4897 data_time: 0.0024 memory: 8135 grad_norm: 718.5369 loss: 397.7773 loss_cls: 133.5646 loss_bbox: 124.2763 loss_dfl: 139.9364 +2024/03/21 01:46:18 - mmengine - INFO - Epoch(train) [37][650/925] lr: 1.1338e-04 eta: 5:31:43 time: 0.4866 data_time: 0.0024 memory: 8242 grad_norm: 723.5575 loss: 399.4793 loss_cls: 134.7382 loss_bbox: 124.7156 loss_dfl: 140.0255 +2024/03/21 01:46:44 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:46:44 - mmengine - INFO - Epoch(train) [37][700/925] lr: 1.1338e-04 eta: 5:31:20 time: 0.5234 data_time: 0.0025 memory: 7975 grad_norm: 738.3229 loss: 394.2813 loss_cls: 132.0677 loss_bbox: 122.3381 loss_dfl: 139.8755 +2024/03/21 01:47:08 - mmengine - INFO - Epoch(train) [37][750/925] lr: 1.1338e-04 eta: 5:30:54 time: 0.4752 data_time: 0.0024 memory: 7989 grad_norm: 752.8008 loss: 402.1031 loss_cls: 134.8982 loss_bbox: 126.2696 loss_dfl: 140.9352 +2024/03/21 01:47:33 - mmengine - INFO - Epoch(train) [37][800/925] lr: 1.1338e-04 eta: 5:30:29 time: 0.4997 data_time: 0.0024 memory: 7722 grad_norm: 727.7800 loss: 391.2764 loss_cls: 132.6324 loss_bbox: 120.5549 loss_dfl: 138.0892 +2024/03/21 01:47:58 - mmengine - INFO - Epoch(train) [37][850/925] lr: 1.1338e-04 eta: 5:30:05 time: 0.5057 data_time: 0.0024 memory: 8149 grad_norm: 695.9646 loss: 386.3967 loss_cls: 128.4992 loss_bbox: 120.5178 loss_dfl: 137.3797 +2024/03/21 01:48:22 - mmengine - INFO - Epoch(train) [37][900/925] lr: 1.1338e-04 eta: 5:29:39 time: 0.4803 data_time: 0.0022 memory: 8095 grad_norm: 767.3906 loss: 395.0100 loss_cls: 131.9993 loss_bbox: 123.7319 loss_dfl: 139.2788 +2024/03/21 01:48:35 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:49:04 - mmengine - INFO - Epoch(train) [38][ 50/925] lr: 1.1090e-04 eta: 5:29:06 time: 0.5801 data_time: 0.0658 memory: 7949 grad_norm: 745.3215 loss: 394.8732 loss_cls: 132.9330 loss_bbox: 122.9072 loss_dfl: 139.0330 +2024/03/21 01:49:29 - mmengine - INFO - Epoch(train) [38][100/925] lr: 1.1090e-04 eta: 5:28:41 time: 0.4948 data_time: 0.0026 memory: 7775 grad_norm: 698.1205 loss: 389.9977 loss_cls: 131.7091 loss_bbox: 120.5570 loss_dfl: 137.7316 +2024/03/21 01:49:55 - mmengine - INFO - Epoch(train) [38][150/925] lr: 1.1090e-04 eta: 5:28:17 time: 0.5121 data_time: 0.0022 memory: 8109 grad_norm: 739.9785 loss: 393.5561 loss_cls: 130.5511 loss_bbox: 124.2861 loss_dfl: 138.7189 +2024/03/21 01:50:21 - mmengine - INFO - Epoch(train) [38][200/925] lr: 1.1090e-04 eta: 5:27:54 time: 0.5198 data_time: 0.0023 memory: 7909 grad_norm: 734.4568 loss: 394.3926 loss_cls: 132.5684 loss_bbox: 122.3693 loss_dfl: 139.4549 +2024/03/21 01:50:45 - mmengine - INFO - Epoch(train) [38][250/925] lr: 1.1090e-04 eta: 5:27:29 time: 0.4943 data_time: 0.0023 memory: 8402 grad_norm: 748.7021 loss: 395.2106 loss_cls: 132.9314 loss_bbox: 123.0909 loss_dfl: 139.1883 +2024/03/21 01:51:11 - mmengine - INFO - Epoch(train) [38][300/925] lr: 1.1090e-04 eta: 5:27:05 time: 0.5133 data_time: 0.0023 memory: 8309 grad_norm: 764.2679 loss: 392.5281 loss_cls: 130.8728 loss_bbox: 122.3274 loss_dfl: 139.3279 +2024/03/21 01:51:37 - mmengine - INFO - Epoch(train) [38][350/925] lr: 1.1090e-04 eta: 5:26:41 time: 0.5130 data_time: 0.0024 memory: 8002 grad_norm: 718.4622 loss: 401.3820 loss_cls: 135.3391 loss_bbox: 125.5428 loss_dfl: 140.5002 +2024/03/21 01:52:01 - mmengine - INFO - Epoch(train) [38][400/925] lr: 1.1090e-04 eta: 5:26:15 time: 0.4808 data_time: 0.0024 memory: 8029 grad_norm: 721.7276 loss: 401.6844 loss_cls: 135.2609 loss_bbox: 125.5392 loss_dfl: 140.8842 +2024/03/21 01:52:27 - mmengine - INFO - Epoch(train) [38][450/925] lr: 1.1090e-04 eta: 5:25:51 time: 0.5204 data_time: 0.0023 memory: 7869 grad_norm: 781.6236 loss: 395.8897 loss_cls: 132.2491 loss_bbox: 124.5190 loss_dfl: 139.1216 +2024/03/21 01:52:52 - mmengine - INFO - Epoch(train) [38][500/925] lr: 1.1090e-04 eta: 5:25:27 time: 0.5005 data_time: 0.0022 memory: 7989 grad_norm: 708.7590 loss: 397.7157 loss_cls: 133.2643 loss_bbox: 124.4791 loss_dfl: 139.9722 +2024/03/21 01:53:17 - mmengine - INFO - Epoch(train) [38][550/925] lr: 1.1090e-04 eta: 5:25:02 time: 0.4977 data_time: 0.0023 memory: 7922 grad_norm: 756.8429 loss: 397.3488 loss_cls: 132.0669 loss_bbox: 124.7859 loss_dfl: 140.4959 +2024/03/21 01:53:43 - mmengine - INFO - Epoch(train) [38][600/925] lr: 1.1090e-04 eta: 5:24:38 time: 0.5224 data_time: 0.0023 memory: 7935 grad_norm: 710.8027 loss: 390.2730 loss_cls: 129.8707 loss_bbox: 121.7639 loss_dfl: 138.6384 +2024/03/21 01:54:08 - mmengine - INFO - Epoch(train) [38][650/925] lr: 1.1090e-04 eta: 5:24:14 time: 0.5031 data_time: 0.0024 memory: 8135 grad_norm: 735.7475 loss: 396.8077 loss_cls: 133.3189 loss_bbox: 124.5062 loss_dfl: 138.9825 +2024/03/21 01:54:33 - mmengine - INFO - Epoch(train) [38][700/925] lr: 1.1090e-04 eta: 5:23:49 time: 0.5042 data_time: 0.0022 memory: 8242 grad_norm: 741.1511 loss: 398.1732 loss_cls: 134.3524 loss_bbox: 124.0367 loss_dfl: 139.7841 +2024/03/21 01:54:59 - mmengine - INFO - Epoch(train) [38][750/925] lr: 1.1090e-04 eta: 5:23:26 time: 0.5183 data_time: 0.0024 memory: 7895 grad_norm: 738.5341 loss: 393.8884 loss_cls: 130.8593 loss_bbox: 124.0669 loss_dfl: 138.9622 +2024/03/21 01:55:11 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:55:23 - mmengine - INFO - Epoch(train) [38][800/925] lr: 1.1090e-04 eta: 5:23:00 time: 0.4804 data_time: 0.0025 memory: 7962 grad_norm: 731.0854 loss: 394.7170 loss_cls: 131.4258 loss_bbox: 124.0608 loss_dfl: 139.2304 +2024/03/21 01:55:49 - mmengine - INFO - Epoch(train) [38][850/925] lr: 1.1090e-04 eta: 5:22:36 time: 0.5167 data_time: 0.0023 memory: 7815 grad_norm: 706.8819 loss: 395.3134 loss_cls: 131.5946 loss_bbox: 123.5997 loss_dfl: 140.1191 +2024/03/21 01:56:15 - mmengine - INFO - Epoch(train) [38][900/925] lr: 1.1090e-04 eta: 5:22:12 time: 0.5093 data_time: 0.0023 memory: 8002 grad_norm: 762.4050 loss: 397.0689 loss_cls: 132.3649 loss_bbox: 125.4274 loss_dfl: 139.2766 +2024/03/21 01:56:26 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 01:56:56 - mmengine - INFO - Epoch(train) [39][ 50/925] lr: 1.0842e-04 eta: 5:21:38 time: 0.5826 data_time: 0.0649 memory: 8269 grad_norm: 725.8186 loss: 392.8482 loss_cls: 131.6923 loss_bbox: 122.1625 loss_dfl: 138.9935 +2024/03/21 01:57:21 - mmengine - INFO - Epoch(train) [39][100/925] lr: 1.0842e-04 eta: 5:21:13 time: 0.5003 data_time: 0.0023 memory: 7802 grad_norm: 682.9915 loss: 395.7091 loss_cls: 133.3719 loss_bbox: 122.6565 loss_dfl: 139.6807 +2024/03/21 01:57:45 - mmengine - INFO - Epoch(train) [39][150/925] lr: 1.0842e-04 eta: 5:20:48 time: 0.4938 data_time: 0.0023 memory: 8042 grad_norm: 710.8736 loss: 394.9520 loss_cls: 132.6740 loss_bbox: 122.8251 loss_dfl: 139.4529 +2024/03/21 01:58:12 - mmengine - INFO - Epoch(train) [39][200/925] lr: 1.0842e-04 eta: 5:20:25 time: 0.5221 data_time: 0.0023 memory: 7749 grad_norm: 734.3785 loss: 402.2543 loss_cls: 136.1348 loss_bbox: 126.7394 loss_dfl: 139.3802 +2024/03/21 01:58:37 - mmengine - INFO - Epoch(train) [39][250/925] lr: 1.0842e-04 eta: 5:20:01 time: 0.5066 data_time: 0.0023 memory: 8029 grad_norm: 707.6872 loss: 393.5270 loss_cls: 131.7241 loss_bbox: 122.8006 loss_dfl: 139.0023 +2024/03/21 01:59:02 - mmengine - INFO - Epoch(train) [39][300/925] lr: 1.0842e-04 eta: 5:19:36 time: 0.4969 data_time: 0.0023 memory: 7895 grad_norm: 717.8112 loss: 393.0920 loss_cls: 131.8430 loss_bbox: 123.3888 loss_dfl: 137.8602 +2024/03/21 01:59:28 - mmengine - INFO - Epoch(train) [39][350/925] lr: 1.0842e-04 eta: 5:19:12 time: 0.5213 data_time: 0.0024 memory: 8135 grad_norm: 803.7244 loss: 394.2170 loss_cls: 131.9736 loss_bbox: 123.3574 loss_dfl: 138.8860 +2024/03/21 01:59:53 - mmengine - INFO - Epoch(train) [39][400/925] lr: 1.0842e-04 eta: 5:18:47 time: 0.4979 data_time: 0.0024 memory: 8095 grad_norm: 729.7433 loss: 399.0986 loss_cls: 133.4406 loss_bbox: 125.4977 loss_dfl: 140.1602 +2024/03/21 02:00:18 - mmengine - INFO - Epoch(train) [39][450/925] lr: 1.0842e-04 eta: 5:18:22 time: 0.5000 data_time: 0.0024 memory: 7829 grad_norm: 871.3749 loss: 392.3870 loss_cls: 131.6806 loss_bbox: 121.9514 loss_dfl: 138.7550 +2024/03/21 02:00:44 - mmengine - INFO - Epoch(train) [39][500/925] lr: 1.0842e-04 eta: 5:17:59 time: 0.5257 data_time: 0.0024 memory: 8055 grad_norm: 738.4285 loss: 388.7676 loss_cls: 130.1482 loss_bbox: 121.0088 loss_dfl: 137.6106 +2024/03/21 02:01:08 - mmengine - INFO - Epoch(train) [39][550/925] lr: 1.0842e-04 eta: 5:17:33 time: 0.4822 data_time: 0.0024 memory: 7829 grad_norm: 701.6301 loss: 395.2242 loss_cls: 133.3328 loss_bbox: 122.6870 loss_dfl: 139.2044 +2024/03/21 02:01:34 - mmengine - INFO - Epoch(train) [39][600/925] lr: 1.0842e-04 eta: 5:17:09 time: 0.5143 data_time: 0.0023 memory: 8029 grad_norm: 684.3303 loss: 399.2543 loss_cls: 135.2180 loss_bbox: 125.0060 loss_dfl: 139.0303 +2024/03/21 02:02:00 - mmengine - INFO - Epoch(train) [39][650/925] lr: 1.0842e-04 eta: 5:16:46 time: 0.5178 data_time: 0.0025 memory: 8109 grad_norm: 763.1079 loss: 392.3147 loss_cls: 131.0529 loss_bbox: 123.4258 loss_dfl: 137.8360 +2024/03/21 02:02:24 - mmengine - INFO - Epoch(train) [39][700/925] lr: 1.0842e-04 eta: 5:16:20 time: 0.4815 data_time: 0.0024 memory: 8122 grad_norm: 743.9251 loss: 396.2048 loss_cls: 133.2532 loss_bbox: 123.4760 loss_dfl: 139.4755 +2024/03/21 02:02:50 - mmengine - INFO - Epoch(train) [39][750/925] lr: 1.0842e-04 eta: 5:15:56 time: 0.5228 data_time: 0.0023 memory: 8095 grad_norm: 715.3155 loss: 395.0536 loss_cls: 131.4295 loss_bbox: 124.7988 loss_dfl: 138.8253 +2024/03/21 02:03:16 - mmengine - INFO - Epoch(train) [39][800/925] lr: 1.0842e-04 eta: 5:15:32 time: 0.5066 data_time: 0.0025 memory: 8042 grad_norm: 721.2883 loss: 392.8090 loss_cls: 131.1030 loss_bbox: 123.4862 loss_dfl: 138.2198 +2024/03/21 02:03:41 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:03:41 - mmengine - INFO - Epoch(train) [39][850/925] lr: 1.0842e-04 eta: 5:15:07 time: 0.4999 data_time: 0.0023 memory: 7962 grad_norm: 749.6886 loss: 392.5650 loss_cls: 131.3342 loss_bbox: 123.5082 loss_dfl: 137.7226 +2024/03/21 02:04:07 - mmengine - INFO - Epoch(train) [39][900/925] lr: 1.0842e-04 eta: 5:14:44 time: 0.5219 data_time: 0.0023 memory: 7869 grad_norm: 750.4979 loss: 391.3701 loss_cls: 130.0223 loss_bbox: 122.7199 loss_dfl: 138.6280 +2024/03/21 02:04:19 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:04:48 - mmengine - INFO - Epoch(train) [40][ 50/925] lr: 1.0595e-04 eta: 5:14:10 time: 0.5614 data_time: 0.0727 memory: 8082 grad_norm: 693.0627 loss: 387.6637 loss_cls: 128.2032 loss_bbox: 121.9240 loss_dfl: 137.5365 +2024/03/21 02:05:13 - mmengine - INFO - Epoch(train) [40][100/925] lr: 1.0595e-04 eta: 5:13:46 time: 0.5127 data_time: 0.0023 memory: 7909 grad_norm: 719.8813 loss: 396.0842 loss_cls: 132.1693 loss_bbox: 124.5806 loss_dfl: 139.3343 +2024/03/21 02:05:38 - mmengine - INFO - Epoch(train) [40][150/925] lr: 1.0595e-04 eta: 5:13:21 time: 0.4969 data_time: 0.0023 memory: 7829 grad_norm: 726.7646 loss: 391.6864 loss_cls: 131.7187 loss_bbox: 121.7823 loss_dfl: 138.1853 +2024/03/21 02:06:03 - mmengine - INFO - Epoch(train) [40][200/925] lr: 1.0595e-04 eta: 5:12:55 time: 0.4833 data_time: 0.0024 memory: 7975 grad_norm: 737.9053 loss: 393.7163 loss_cls: 131.9324 loss_bbox: 123.6175 loss_dfl: 138.1664 +2024/03/21 02:06:28 - mmengine - INFO - Epoch(train) [40][250/925] lr: 1.0595e-04 eta: 5:12:31 time: 0.5083 data_time: 0.0024 memory: 8549 grad_norm: 678.5411 loss: 392.6322 loss_cls: 131.8133 loss_bbox: 123.1054 loss_dfl: 137.7135 +2024/03/21 02:06:53 - mmengine - INFO - Epoch(train) [40][300/925] lr: 1.0595e-04 eta: 5:12:06 time: 0.5004 data_time: 0.0023 memory: 8122 grad_norm: 714.1047 loss: 395.0270 loss_cls: 130.9783 loss_bbox: 125.3148 loss_dfl: 138.7340 +2024/03/21 02:07:17 - mmengine - INFO - Epoch(train) [40][350/925] lr: 1.0595e-04 eta: 5:11:40 time: 0.4833 data_time: 0.0023 memory: 7722 grad_norm: 690.7885 loss: 391.7382 loss_cls: 130.0753 loss_bbox: 123.2257 loss_dfl: 138.4372 +2024/03/21 02:07:43 - mmengine - INFO - Epoch(train) [40][400/925] lr: 1.0595e-04 eta: 5:11:16 time: 0.5066 data_time: 0.0024 memory: 8095 grad_norm: 688.6467 loss: 399.5584 loss_cls: 135.0895 loss_bbox: 124.7766 loss_dfl: 139.6924 +2024/03/21 02:08:08 - mmengine - INFO - Epoch(train) [40][450/925] lr: 1.0595e-04 eta: 5:10:51 time: 0.5016 data_time: 0.0023 memory: 7989 grad_norm: inf loss: 399.2701 loss_cls: 134.8289 loss_bbox: 124.7498 loss_dfl: 139.6913 +2024/03/21 02:08:33 - mmengine - INFO - Epoch(train) [40][500/925] lr: 1.0595e-04 eta: 5:10:26 time: 0.4998 data_time: 0.0023 memory: 7882 grad_norm: 754.3680 loss: 394.6756 loss_cls: 131.6431 loss_bbox: 123.7355 loss_dfl: 139.2970 +2024/03/21 02:08:58 - mmengine - INFO - Epoch(train) [40][550/925] lr: 1.0595e-04 eta: 5:10:02 time: 0.5112 data_time: 0.0024 memory: 8109 grad_norm: 715.3645 loss: 400.3591 loss_cls: 134.1039 loss_bbox: 125.8086 loss_dfl: 140.4466 +2024/03/21 02:09:23 - mmengine - INFO - Epoch(train) [40][600/925] lr: 1.0595e-04 eta: 5:09:37 time: 0.4926 data_time: 0.0024 memory: 7949 grad_norm: 755.5991 loss: 394.3325 loss_cls: 132.4877 loss_bbox: 122.7214 loss_dfl: 139.1234 +2024/03/21 02:09:48 - mmengine - INFO - Epoch(train) [40][650/925] lr: 1.0595e-04 eta: 5:09:12 time: 0.5031 data_time: 0.0024 memory: 7975 grad_norm: 731.0132 loss: 395.0136 loss_cls: 132.1139 loss_bbox: 123.4836 loss_dfl: 139.4162 +2024/03/21 02:10:13 - mmengine - INFO - Epoch(train) [40][700/925] lr: 1.0595e-04 eta: 5:08:48 time: 0.5042 data_time: 0.0024 memory: 8095 grad_norm: 732.3419 loss: 396.8318 loss_cls: 133.2475 loss_bbox: 124.5840 loss_dfl: 139.0004 +2024/03/21 02:10:38 - mmengine - INFO - Epoch(train) [40][750/925] lr: 1.0595e-04 eta: 5:08:23 time: 0.4968 data_time: 0.0023 memory: 7935 grad_norm: 738.5076 loss: 393.6458 loss_cls: 130.4687 loss_bbox: 123.7806 loss_dfl: 139.3964 +2024/03/21 02:11:04 - mmengine - INFO - Epoch(train) [40][800/925] lr: 1.0595e-04 eta: 5:07:59 time: 0.5065 data_time: 0.0025 memory: 7815 grad_norm: 710.3206 loss: 391.7987 loss_cls: 130.5748 loss_bbox: 123.2457 loss_dfl: 137.9782 +2024/03/21 02:11:28 - mmengine - INFO - Epoch(train) [40][850/925] lr: 1.0595e-04 eta: 5:07:33 time: 0.4927 data_time: 0.0024 memory: 7975 grad_norm: 731.9950 loss: 391.7049 loss_cls: 131.4802 loss_bbox: 121.2276 loss_dfl: 138.9972 +2024/03/21 02:11:54 - mmengine - INFO - Epoch(train) [40][900/925] lr: 1.0595e-04 eta: 5:07:09 time: 0.5123 data_time: 0.0022 memory: 8042 grad_norm: 745.0980 loss: 395.3571 loss_cls: 133.5596 loss_bbox: 122.3979 loss_dfl: 139.3996 +2024/03/21 02:12:06 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:12:07 - mmengine - INFO - Saving checkpoint at 40 epochs +2024/03/21 02:12:15 - mmengine - INFO - Epoch(val) [40][ 50/625] eta: 0:00:21 time: 0.0377 data_time: 0.0008 memory: 7829 +2024/03/21 02:12:17 - mmengine - INFO - Epoch(val) [40][100/625] eta: 0:00:19 time: 0.0347 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:19 - mmengine - INFO - Epoch(val) [40][150/625] eta: 0:00:17 time: 0.0356 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:20 - mmengine - INFO - Epoch(val) [40][200/625] eta: 0:00:15 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:22 - mmengine - INFO - Epoch(val) [40][250/625] eta: 0:00:13 time: 0.0378 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:24 - mmengine - INFO - Epoch(val) [40][300/625] eta: 0:00:11 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:26 - mmengine - INFO - Epoch(val) [40][350/625] eta: 0:00:09 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:28 - mmengine - INFO - Epoch(val) [40][400/625] eta: 0:00:08 time: 0.0364 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:29 - mmengine - INFO - Epoch(val) [40][450/625] eta: 0:00:06 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 02:12:31 - mmengine - INFO - Epoch(val) [40][500/625] eta: 0:00:04 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 02:12:32 - mmengine - INFO - Epoch(val) [40][550/625] eta: 0:00:02 time: 0.0280 data_time: 0.0002 memory: 1244 +2024/03/21 02:12:34 - mmengine - INFO - Epoch(val) [40][600/625] eta: 0:00:00 time: 0.0277 data_time: 0.0002 memory: 1244 +2024/03/21 02:12:46 - mmengine - INFO - Evaluating bbox... +2024/03/21 02:13:57 - mmengine - INFO - bbox_mAP_copypaste: 0.502 0.667 0.548 0.317 0.554 0.665 +2024/03/21 02:13:59 - mmengine - INFO - Epoch(val) [40][625/625] coco/bbox_mAP: 0.5020 coco/bbox_mAP_50: 0.6670 coco/bbox_mAP_75: 0.5480 coco/bbox_mAP_s: 0.3170 coco/bbox_mAP_m: 0.5540 coco/bbox_mAP_l: 0.6650 data_time: 0.0002 time: 0.0279 +2024/03/21 02:14:30 - mmengine - INFO - Epoch(train) [41][ 50/925] lr: 1.0347e-04 eta: 5:06:38 time: 0.6190 data_time: 0.0972 memory: 8109 grad_norm: 683.5539 loss: 388.4910 loss_cls: 130.1940 loss_bbox: 120.4097 loss_dfl: 137.8873 +2024/03/21 02:14:55 - mmengine - INFO - Epoch(train) [41][100/925] lr: 1.0347e-04 eta: 5:06:13 time: 0.4929 data_time: 0.0025 memory: 8135 grad_norm: 698.6788 loss: 394.4012 loss_cls: 132.4328 loss_bbox: 123.5324 loss_dfl: 138.4361 +2024/03/21 02:15:20 - mmengine - INFO - Epoch(train) [41][150/925] lr: 1.0347e-04 eta: 5:05:48 time: 0.4987 data_time: 0.0026 memory: 8363 grad_norm: 711.1872 loss: 396.8612 loss_cls: 132.2458 loss_bbox: 124.9054 loss_dfl: 139.7100 +2024/03/21 02:15:46 - mmengine - INFO - Epoch(train) [41][200/925] lr: 1.0347e-04 eta: 5:05:24 time: 0.5119 data_time: 0.0024 memory: 7962 grad_norm: 679.3264 loss: 394.0414 loss_cls: 131.3747 loss_bbox: 124.3530 loss_dfl: 138.3137 +2024/03/21 02:16:11 - mmengine - INFO - Epoch(train) [41][250/925] lr: 1.0347e-04 eta: 5:04:59 time: 0.4982 data_time: 0.0025 memory: 7829 grad_norm: 717.4883 loss: 391.4857 loss_cls: 130.1296 loss_bbox: 123.1293 loss_dfl: 138.2268 +2024/03/21 02:16:35 - mmengine - INFO - Epoch(train) [41][300/925] lr: 1.0347e-04 eta: 5:04:34 time: 0.4978 data_time: 0.0024 memory: 7789 grad_norm: 700.4804 loss: 392.1765 loss_cls: 131.3605 loss_bbox: 121.1577 loss_dfl: 139.6584 +2024/03/21 02:17:01 - mmengine - INFO - Epoch(train) [41][350/925] lr: 1.0347e-04 eta: 5:04:09 time: 0.5101 data_time: 0.0024 memory: 8335 grad_norm: 711.0819 loss: 393.1317 loss_cls: 132.0672 loss_bbox: 121.8158 loss_dfl: 139.2487 +2024/03/21 02:17:27 - mmengine - INFO - Epoch(train) [41][400/925] lr: 1.0347e-04 eta: 5:03:45 time: 0.5121 data_time: 0.0023 memory: 7882 grad_norm: 734.3379 loss: 389.2427 loss_cls: 127.8277 loss_bbox: 123.3210 loss_dfl: 138.0940 +2024/03/21 02:17:52 - mmengine - INFO - Epoch(train) [41][450/925] lr: 1.0347e-04 eta: 5:03:20 time: 0.5004 data_time: 0.0023 memory: 8042 grad_norm: 686.2774 loss: 394.2935 loss_cls: 131.3617 loss_bbox: 124.0479 loss_dfl: 138.8839 +2024/03/21 02:18:16 - mmengine - INFO - Epoch(train) [41][500/925] lr: 1.0347e-04 eta: 5:02:55 time: 0.4889 data_time: 0.0025 memory: 8015 grad_norm: 748.5863 loss: 393.5976 loss_cls: 130.9135 loss_bbox: 124.4779 loss_dfl: 138.2062 +2024/03/21 02:18:42 - mmengine - INFO - Epoch(train) [41][550/925] lr: 1.0347e-04 eta: 5:02:31 time: 0.5195 data_time: 0.0023 memory: 7829 grad_norm: 734.1696 loss: 391.3805 loss_cls: 129.6293 loss_bbox: 123.4380 loss_dfl: 138.3133 +2024/03/21 02:19:07 - mmengine - INFO - Epoch(train) [41][600/925] lr: 1.0347e-04 eta: 5:02:06 time: 0.4933 data_time: 0.0024 memory: 8055 grad_norm: 766.4654 loss: 394.1419 loss_cls: 132.3561 loss_bbox: 121.8890 loss_dfl: 139.8967 +2024/03/21 02:19:32 - mmengine - INFO - Epoch(train) [41][650/925] lr: 1.0347e-04 eta: 5:01:41 time: 0.4981 data_time: 0.0025 memory: 7922 grad_norm: 744.8267 loss: 388.5038 loss_cls: 128.6387 loss_bbox: 121.2089 loss_dfl: 138.6563 +2024/03/21 02:19:58 - mmengine - INFO - Epoch(train) [41][700/925] lr: 1.0347e-04 eta: 5:01:17 time: 0.5158 data_time: 0.0024 memory: 8095 grad_norm: 689.6511 loss: 391.0438 loss_cls: 130.5283 loss_bbox: 121.9647 loss_dfl: 138.5508 +2024/03/21 02:20:23 - mmengine - INFO - Epoch(train) [41][750/925] lr: 1.0347e-04 eta: 5:00:53 time: 0.5140 data_time: 0.0023 memory: 8029 grad_norm: 724.7257 loss: 394.1841 loss_cls: 132.7892 loss_bbox: 122.5372 loss_dfl: 138.8578 +2024/03/21 02:20:48 - mmengine - INFO - Epoch(train) [41][800/925] lr: 1.0347e-04 eta: 5:00:28 time: 0.4979 data_time: 0.0025 memory: 7869 grad_norm: 740.6366 loss: 390.7272 loss_cls: 130.7518 loss_bbox: 120.8094 loss_dfl: 139.1660 +2024/03/21 02:21:14 - mmengine - INFO - Epoch(train) [41][850/925] lr: 1.0347e-04 eta: 5:00:04 time: 0.5156 data_time: 0.0024 memory: 8309 grad_norm: 699.3403 loss: 395.6079 loss_cls: 132.5825 loss_bbox: 124.0774 loss_dfl: 138.9480 +2024/03/21 02:21:39 - mmengine - INFO - Epoch(train) [41][900/925] lr: 1.0347e-04 eta: 4:59:40 time: 0.5061 data_time: 0.0024 memory: 7855 grad_norm: 755.7493 loss: 394.3426 loss_cls: 131.8707 loss_bbox: 124.1193 loss_dfl: 138.3526 +2024/03/21 02:21:51 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:22:19 - mmengine - INFO - Epoch(train) [42][ 50/925] lr: 1.0100e-04 eta: 4:59:04 time: 0.5580 data_time: 0.0610 memory: 7815 grad_norm: 708.6208 loss: 393.0166 loss_cls: 131.4435 loss_bbox: 123.5343 loss_dfl: 138.0387 +2024/03/21 02:22:33 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:22:45 - mmengine - INFO - Epoch(train) [42][100/925] lr: 1.0100e-04 eta: 4:58:40 time: 0.5242 data_time: 0.0025 memory: 7975 grad_norm: 742.6751 loss: 392.0693 loss_cls: 130.2599 loss_bbox: 123.1517 loss_dfl: 138.6576 +2024/03/21 02:23:10 - mmengine - INFO - Epoch(train) [42][150/925] lr: 1.0100e-04 eta: 4:58:16 time: 0.5010 data_time: 0.0025 memory: 8309 grad_norm: 723.2952 loss: 395.7337 loss_cls: 130.0063 loss_bbox: 126.4082 loss_dfl: 139.3192 +2024/03/21 02:23:36 - mmengine - INFO - Epoch(train) [42][200/925] lr: 1.0100e-04 eta: 4:57:51 time: 0.5071 data_time: 0.0025 memory: 7802 grad_norm: 741.1843 loss: 391.8526 loss_cls: 130.3538 loss_bbox: 123.2573 loss_dfl: 138.2416 +2024/03/21 02:24:01 - mmengine - INFO - Epoch(train) [42][250/925] lr: 1.0100e-04 eta: 4:57:27 time: 0.5086 data_time: 0.0024 memory: 8215 grad_norm: 803.9125 loss: 395.5092 loss_cls: 133.0493 loss_bbox: 123.7687 loss_dfl: 138.6912 +2024/03/21 02:24:27 - mmengine - INFO - Epoch(train) [42][300/925] lr: 1.0100e-04 eta: 4:57:02 time: 0.5115 data_time: 0.0024 memory: 7962 grad_norm: 728.5699 loss: 391.0820 loss_cls: 131.1146 loss_bbox: 122.0139 loss_dfl: 137.9535 +2024/03/21 02:24:52 - mmengine - INFO - Epoch(train) [42][350/925] lr: 1.0100e-04 eta: 4:56:38 time: 0.5043 data_time: 0.0024 memory: 7855 grad_norm: 757.5292 loss: 386.6699 loss_cls: 127.1813 loss_bbox: 121.3238 loss_dfl: 138.1648 +2024/03/21 02:25:17 - mmengine - INFO - Epoch(train) [42][400/925] lr: 1.0100e-04 eta: 4:56:13 time: 0.4932 data_time: 0.0022 memory: 7975 grad_norm: 717.5301 loss: 394.1308 loss_cls: 131.2462 loss_bbox: 123.7142 loss_dfl: 139.1703 +2024/03/21 02:25:42 - mmengine - INFO - Epoch(train) [42][450/925] lr: 1.0100e-04 eta: 4:55:48 time: 0.5071 data_time: 0.0023 memory: 7762 grad_norm: 707.8283 loss: 393.1780 loss_cls: 132.4665 loss_bbox: 122.1414 loss_dfl: 138.5702 +2024/03/21 02:26:07 - mmengine - INFO - Epoch(train) [42][500/925] lr: 1.0100e-04 eta: 4:55:23 time: 0.5020 data_time: 0.0023 memory: 7829 grad_norm: 736.1396 loss: 392.3412 loss_cls: 128.9570 loss_bbox: 124.2517 loss_dfl: 139.1324 +2024/03/21 02:26:32 - mmengine - INFO - Epoch(train) [42][550/925] lr: 1.0100e-04 eta: 4:54:58 time: 0.4928 data_time: 0.0022 memory: 7869 grad_norm: 724.7108 loss: 392.9314 loss_cls: 131.4904 loss_bbox: 122.6203 loss_dfl: 138.8207 +2024/03/21 02:26:57 - mmengine - INFO - Epoch(train) [42][600/925] lr: 1.0100e-04 eta: 4:54:34 time: 0.5072 data_time: 0.0024 memory: 7922 grad_norm: 735.9563 loss: 391.0564 loss_cls: 131.3662 loss_bbox: 121.7160 loss_dfl: 137.9742 +2024/03/21 02:27:23 - mmengine - INFO - Epoch(train) [42][650/925] lr: 1.0100e-04 eta: 4:54:09 time: 0.5021 data_time: 0.0024 memory: 8015 grad_norm: 728.0956 loss: 391.8437 loss_cls: 131.7516 loss_bbox: 121.9724 loss_dfl: 138.1197 +2024/03/21 02:27:48 - mmengine - INFO - Epoch(train) [42][700/925] lr: 1.0100e-04 eta: 4:53:45 time: 0.5125 data_time: 0.0024 memory: 7869 grad_norm: inf loss: 391.4724 loss_cls: 130.9038 loss_bbox: 122.5673 loss_dfl: 138.0012 +2024/03/21 02:28:14 - mmengine - INFO - Epoch(train) [42][750/925] lr: 1.0100e-04 eta: 4:53:20 time: 0.5121 data_time: 0.0023 memory: 7842 grad_norm: 761.6997 loss: 393.1609 loss_cls: 130.4142 loss_bbox: 123.6457 loss_dfl: 139.1010 +2024/03/21 02:28:38 - mmengine - INFO - Epoch(train) [42][800/925] lr: 1.0100e-04 eta: 4:52:55 time: 0.4895 data_time: 0.0025 memory: 8055 grad_norm: 674.7176 loss: 398.9018 loss_cls: 133.0173 loss_bbox: 125.0713 loss_dfl: 140.8131 +2024/03/21 02:29:04 - mmengine - INFO - Epoch(train) [42][850/925] lr: 1.0100e-04 eta: 4:52:31 time: 0.5125 data_time: 0.0025 memory: 7935 grad_norm: 743.3051 loss: 394.0950 loss_cls: 131.8920 loss_bbox: 123.3021 loss_dfl: 138.9009 +2024/03/21 02:29:30 - mmengine - INFO - Epoch(train) [42][900/925] lr: 1.0100e-04 eta: 4:52:07 time: 0.5159 data_time: 0.0025 memory: 7855 grad_norm: 740.3808 loss: 396.0133 loss_cls: 131.7373 loss_bbox: 125.6679 loss_dfl: 138.6081 +2024/03/21 02:29:41 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:30:09 - mmengine - INFO - Epoch(train) [43][ 50/925] lr: 9.8525e-05 eta: 4:51:31 time: 0.5530 data_time: 0.0540 memory: 7949 grad_norm: 713.7140 loss: 386.9335 loss_cls: 128.0504 loss_bbox: 121.5095 loss_dfl: 137.3735 +2024/03/21 02:30:35 - mmengine - INFO - Epoch(train) [43][100/925] lr: 9.8525e-05 eta: 4:51:06 time: 0.5051 data_time: 0.0025 memory: 7922 grad_norm: 712.8997 loss: 387.0106 loss_cls: 127.0270 loss_bbox: 122.3263 loss_dfl: 137.6573 +2024/03/21 02:30:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:30:59 - mmengine - INFO - Epoch(train) [43][150/925] lr: 9.8525e-05 eta: 4:50:41 time: 0.4964 data_time: 0.0024 memory: 8002 grad_norm: 702.7019 loss: 395.0658 loss_cls: 132.6581 loss_bbox: 122.8304 loss_dfl: 139.5772 +2024/03/21 02:31:25 - mmengine - INFO - Epoch(train) [43][200/925] lr: 9.8525e-05 eta: 4:50:17 time: 0.5106 data_time: 0.0024 memory: 8029 grad_norm: 794.1303 loss: 395.7174 loss_cls: 133.9280 loss_bbox: 124.0231 loss_dfl: 137.7663 +2024/03/21 02:31:51 - mmengine - INFO - Epoch(train) [43][250/925] lr: 9.8525e-05 eta: 4:49:53 time: 0.5230 data_time: 0.0023 memory: 8775 grad_norm: 746.2826 loss: 394.5202 loss_cls: 130.4520 loss_bbox: 124.9441 loss_dfl: 139.1241 +2024/03/21 02:32:15 - mmengine - INFO - Epoch(train) [43][300/925] lr: 9.8525e-05 eta: 4:49:28 time: 0.4845 data_time: 0.0024 memory: 7895 grad_norm: 733.0291 loss: 395.6317 loss_cls: 131.5649 loss_bbox: 124.8150 loss_dfl: 139.2518 +2024/03/21 02:32:41 - mmengine - INFO - Epoch(train) [43][350/925] lr: 9.8525e-05 eta: 4:49:04 time: 0.5217 data_time: 0.0024 memory: 7949 grad_norm: 723.6413 loss: 387.1804 loss_cls: 128.0068 loss_bbox: 122.2457 loss_dfl: 136.9279 +2024/03/21 02:33:07 - mmengine - INFO - Epoch(train) [43][400/925] lr: 9.8525e-05 eta: 4:48:39 time: 0.5129 data_time: 0.0024 memory: 7789 grad_norm: 728.5326 loss: 391.1301 loss_cls: 128.5930 loss_bbox: 123.8338 loss_dfl: 138.7033 +2024/03/21 02:33:32 - mmengine - INFO - Epoch(train) [43][450/925] lr: 9.8525e-05 eta: 4:48:14 time: 0.4899 data_time: 0.0025 memory: 8042 grad_norm: 777.0626 loss: 395.1813 loss_cls: 132.2003 loss_bbox: 124.0716 loss_dfl: 138.9094 +2024/03/21 02:33:58 - mmengine - INFO - Epoch(train) [43][500/925] lr: 9.8525e-05 eta: 4:47:50 time: 0.5199 data_time: 0.0025 memory: 8122 grad_norm: 710.9666 loss: 386.6387 loss_cls: 127.7594 loss_bbox: 121.1524 loss_dfl: 137.7268 +2024/03/21 02:34:23 - mmengine - INFO - Epoch(train) [43][550/925] lr: 9.8525e-05 eta: 4:47:25 time: 0.5006 data_time: 0.0022 memory: 7855 grad_norm: 785.4273 loss: 394.1494 loss_cls: 131.0432 loss_bbox: 124.2351 loss_dfl: 138.8712 +2024/03/21 02:34:48 - mmengine - INFO - Epoch(train) [43][600/925] lr: 9.8525e-05 eta: 4:47:01 time: 0.5086 data_time: 0.0024 memory: 7789 grad_norm: 723.7966 loss: 390.9518 loss_cls: 130.5541 loss_bbox: 122.1860 loss_dfl: 138.2117 +2024/03/21 02:35:14 - mmengine - INFO - Epoch(train) [43][650/925] lr: 9.8525e-05 eta: 4:46:36 time: 0.5118 data_time: 0.0024 memory: 7882 grad_norm: 747.6744 loss: 394.2377 loss_cls: 132.8349 loss_bbox: 122.5040 loss_dfl: 138.8988 +2024/03/21 02:35:38 - mmengine - INFO - Epoch(train) [43][700/925] lr: 9.8525e-05 eta: 4:46:11 time: 0.4860 data_time: 0.0023 memory: 8002 grad_norm: 763.1941 loss: 391.4046 loss_cls: 131.5473 loss_bbox: 122.1376 loss_dfl: 137.7197 +2024/03/21 02:36:04 - mmengine - INFO - Epoch(train) [43][750/925] lr: 9.8525e-05 eta: 4:45:47 time: 0.5185 data_time: 0.0024 memory: 8015 grad_norm: 773.3725 loss: 385.0017 loss_cls: 127.1921 loss_bbox: 120.9521 loss_dfl: 136.8575 +2024/03/21 02:36:30 - mmengine - INFO - Epoch(train) [43][800/925] lr: 9.8525e-05 eta: 4:45:22 time: 0.5075 data_time: 0.0024 memory: 8215 grad_norm: 710.8411 loss: 393.2995 loss_cls: 131.6050 loss_bbox: 123.4283 loss_dfl: 138.2663 +2024/03/21 02:36:54 - mmengine - INFO - Epoch(train) [43][850/925] lr: 9.8525e-05 eta: 4:44:57 time: 0.4928 data_time: 0.0024 memory: 8122 grad_norm: 724.2592 loss: 381.7588 loss_cls: 125.6609 loss_bbox: 119.6332 loss_dfl: 136.4646 +2024/03/21 02:37:20 - mmengine - INFO - Epoch(train) [43][900/925] lr: 9.8525e-05 eta: 4:44:33 time: 0.5168 data_time: 0.0025 memory: 8042 grad_norm: 722.2573 loss: 392.9466 loss_cls: 129.9572 loss_bbox: 124.3514 loss_dfl: 138.6380 +2024/03/21 02:37:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:38:01 - mmengine - INFO - Epoch(train) [44][ 50/925] lr: 9.6050e-05 eta: 4:43:58 time: 0.5680 data_time: 0.0720 memory: 8055 grad_norm: 714.1316 loss: 389.2865 loss_cls: 127.7459 loss_bbox: 121.9989 loss_dfl: 139.5417 +2024/03/21 02:38:26 - mmengine - INFO - Epoch(train) [44][100/925] lr: 9.6050e-05 eta: 4:43:34 time: 0.5062 data_time: 0.0024 memory: 7989 grad_norm: 758.7529 loss: 396.5588 loss_cls: 131.7639 loss_bbox: 124.9447 loss_dfl: 139.8502 +2024/03/21 02:38:52 - mmengine - INFO - Epoch(train) [44][150/925] lr: 9.6050e-05 eta: 4:43:09 time: 0.5129 data_time: 0.0024 memory: 7869 grad_norm: 723.5882 loss: 390.6206 loss_cls: 130.4158 loss_bbox: 122.1085 loss_dfl: 138.0962 +2024/03/21 02:39:17 - mmengine - INFO - Epoch(train) [44][200/925] lr: 9.6050e-05 eta: 4:42:45 time: 0.4991 data_time: 0.0027 memory: 7802 grad_norm: 724.9623 loss: 397.0891 loss_cls: 132.8300 loss_bbox: 124.5639 loss_dfl: 139.6951 +2024/03/21 02:39:30 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:39:43 - mmengine - INFO - Epoch(train) [44][250/925] lr: 9.6050e-05 eta: 4:42:20 time: 0.5120 data_time: 0.0024 memory: 7815 grad_norm: 750.2642 loss: 392.3292 loss_cls: 130.7871 loss_bbox: 123.5192 loss_dfl: 138.0230 +2024/03/21 02:40:08 - mmengine - INFO - Epoch(train) [44][300/925] lr: 9.6050e-05 eta: 4:41:55 time: 0.4983 data_time: 0.0023 memory: 7962 grad_norm: 768.8583 loss: 389.1934 loss_cls: 128.3092 loss_bbox: 121.8039 loss_dfl: 139.0803 +2024/03/21 02:40:33 - mmengine - INFO - Epoch(train) [44][350/925] lr: 9.6050e-05 eta: 4:41:31 time: 0.5113 data_time: 0.0023 memory: 8055 grad_norm: 749.2225 loss: 389.4731 loss_cls: 128.6987 loss_bbox: 122.2221 loss_dfl: 138.5523 +2024/03/21 02:40:58 - mmengine - INFO - Epoch(train) [44][400/925] lr: 9.6050e-05 eta: 4:41:06 time: 0.5027 data_time: 0.0023 memory: 8322 grad_norm: 766.6189 loss: 396.9482 loss_cls: 133.0697 loss_bbox: 124.4171 loss_dfl: 139.4614 +2024/03/21 02:41:23 - mmengine - INFO - Epoch(train) [44][450/925] lr: 9.6050e-05 eta: 4:40:41 time: 0.5003 data_time: 0.0023 memory: 8042 grad_norm: 708.0382 loss: 382.4726 loss_cls: 124.3951 loss_bbox: 121.2124 loss_dfl: 136.8651 +2024/03/21 02:41:50 - mmengine - INFO - Epoch(train) [44][500/925] lr: 9.6050e-05 eta: 4:40:17 time: 0.5224 data_time: 0.0024 memory: 8322 grad_norm: 734.7646 loss: 400.6622 loss_cls: 133.3794 loss_bbox: 127.0147 loss_dfl: 140.2681 +2024/03/21 02:42:15 - mmengine - INFO - Epoch(train) [44][550/925] lr: 9.6050e-05 eta: 4:39:53 time: 0.5056 data_time: 0.0024 memory: 8202 grad_norm: 731.7502 loss: 392.4606 loss_cls: 131.3203 loss_bbox: 122.5235 loss_dfl: 138.6168 +2024/03/21 02:42:39 - mmengine - INFO - Epoch(train) [44][600/925] lr: 9.6050e-05 eta: 4:39:27 time: 0.4877 data_time: 0.0024 memory: 8082 grad_norm: 717.2282 loss: 395.2226 loss_cls: 132.2916 loss_bbox: 124.0887 loss_dfl: 138.8423 +2024/03/21 02:43:05 - mmengine - INFO - Epoch(train) [44][650/925] lr: 9.6050e-05 eta: 4:39:03 time: 0.5205 data_time: 0.0023 memory: 8095 grad_norm: 711.1733 loss: 387.0843 loss_cls: 129.7266 loss_bbox: 119.7512 loss_dfl: 137.6065 +2024/03/21 02:43:31 - mmengine - INFO - Epoch(train) [44][700/925] lr: 9.6050e-05 eta: 4:38:38 time: 0.5035 data_time: 0.0024 memory: 7882 grad_norm: 743.9900 loss: 390.0194 loss_cls: 129.4117 loss_bbox: 121.8044 loss_dfl: 138.8033 +2024/03/21 02:43:56 - mmengine - INFO - Epoch(train) [44][750/925] lr: 9.6050e-05 eta: 4:38:14 time: 0.5027 data_time: 0.0023 memory: 7922 grad_norm: 736.5842 loss: 393.2272 loss_cls: 129.5588 loss_bbox: 124.6103 loss_dfl: 139.0582 +2024/03/21 02:44:21 - mmengine - INFO - Epoch(train) [44][800/925] lr: 9.6050e-05 eta: 4:37:49 time: 0.5107 data_time: 0.0024 memory: 7842 grad_norm: 732.9294 loss: 390.1129 loss_cls: 129.1644 loss_bbox: 123.3136 loss_dfl: 137.6348 +2024/03/21 02:44:46 - mmengine - INFO - Epoch(train) [44][850/925] lr: 9.6050e-05 eta: 4:37:24 time: 0.5014 data_time: 0.0027 memory: 8029 grad_norm: 739.4745 loss: 392.5468 loss_cls: 131.7483 loss_bbox: 121.6031 loss_dfl: 139.1954 +2024/03/21 02:45:12 - mmengine - INFO - Epoch(train) [44][900/925] lr: 9.6050e-05 eta: 4:37:00 time: 0.5167 data_time: 0.0023 memory: 7922 grad_norm: 742.6119 loss: 388.7436 loss_cls: 128.2209 loss_bbox: 122.6123 loss_dfl: 137.9104 +2024/03/21 02:45:24 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:45:53 - mmengine - INFO - Epoch(train) [45][ 50/925] lr: 9.3575e-05 eta: 4:36:25 time: 0.5695 data_time: 0.0613 memory: 7855 grad_norm: 698.1395 loss: 383.9337 loss_cls: 128.0468 loss_bbox: 118.6630 loss_dfl: 137.2239 +2024/03/21 02:46:18 - mmengine - INFO - Epoch(train) [45][100/925] lr: 9.3575e-05 eta: 4:36:00 time: 0.5012 data_time: 0.0028 memory: 7989 grad_norm: 683.0294 loss: 386.4072 loss_cls: 127.5187 loss_bbox: 121.0976 loss_dfl: 137.7910 +2024/03/21 02:46:44 - mmengine - INFO - Epoch(train) [45][150/925] lr: 9.3575e-05 eta: 4:35:36 time: 0.5112 data_time: 0.0024 memory: 7869 grad_norm: 705.9205 loss: 393.2585 loss_cls: 130.5301 loss_bbox: 123.2862 loss_dfl: 139.4422 +2024/03/21 02:47:10 - mmengine - INFO - Epoch(train) [45][200/925] lr: 9.3575e-05 eta: 4:35:12 time: 0.5130 data_time: 0.0025 memory: 8122 grad_norm: 759.9622 loss: 387.2515 loss_cls: 127.4700 loss_bbox: 122.2480 loss_dfl: 137.5335 +2024/03/21 02:47:34 - mmengine - INFO - Epoch(train) [45][250/925] lr: 9.3575e-05 eta: 4:34:47 time: 0.4960 data_time: 0.0025 memory: 8135 grad_norm: 758.5727 loss: 387.0965 loss_cls: 126.4466 loss_bbox: 122.7738 loss_dfl: 137.8762 +2024/03/21 02:48:00 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:48:00 - mmengine - INFO - Epoch(train) [45][300/925] lr: 9.3575e-05 eta: 4:34:22 time: 0.5158 data_time: 0.0025 memory: 7775 grad_norm: 757.1147 loss: 386.9293 loss_cls: 126.5375 loss_bbox: 122.9344 loss_dfl: 137.4574 +2024/03/21 02:48:26 - mmengine - INFO - Epoch(train) [45][350/925] lr: 9.3575e-05 eta: 4:33:58 time: 0.5077 data_time: 0.0025 memory: 8255 grad_norm: 779.1829 loss: 393.2460 loss_cls: 131.8423 loss_bbox: 123.2031 loss_dfl: 138.2006 +2024/03/21 02:48:51 - mmengine - INFO - Epoch(train) [45][400/925] lr: 9.3575e-05 eta: 4:33:33 time: 0.5005 data_time: 0.0023 memory: 7749 grad_norm: 757.1330 loss: 387.8256 loss_cls: 128.5713 loss_bbox: 121.1912 loss_dfl: 138.0631 +2024/03/21 02:49:17 - mmengine - INFO - Epoch(train) [45][450/925] lr: 9.3575e-05 eta: 4:33:09 time: 0.5168 data_time: 0.0024 memory: 8349 grad_norm: 758.1203 loss: 390.0618 loss_cls: 128.7890 loss_bbox: 123.0026 loss_dfl: 138.2702 +2024/03/21 02:49:42 - mmengine - INFO - Epoch(train) [45][500/925] lr: 9.3575e-05 eta: 4:32:44 time: 0.5008 data_time: 0.0025 memory: 8069 grad_norm: 693.5722 loss: 389.5181 loss_cls: 127.9479 loss_bbox: 122.6850 loss_dfl: 138.8852 +2024/03/21 02:50:07 - mmengine - INFO - Epoch(train) [45][550/925] lr: 9.3575e-05 eta: 4:32:19 time: 0.5110 data_time: 0.0026 memory: 7922 grad_norm: 699.3127 loss: 395.5450 loss_cls: 132.2182 loss_bbox: 124.6611 loss_dfl: 138.6657 +2024/03/21 02:50:33 - mmengine - INFO - Epoch(train) [45][600/925] lr: 9.3575e-05 eta: 4:31:55 time: 0.5087 data_time: 0.0024 memory: 7975 grad_norm: inf loss: 385.0951 loss_cls: 126.3604 loss_bbox: 121.6997 loss_dfl: 137.0350 +2024/03/21 02:50:58 - mmengine - INFO - Epoch(train) [45][650/925] lr: 9.3575e-05 eta: 4:31:30 time: 0.5069 data_time: 0.0026 memory: 7949 grad_norm: 734.5018 loss: 387.1372 loss_cls: 128.2534 loss_bbox: 121.3413 loss_dfl: 137.5425 +2024/03/21 02:51:23 - mmengine - INFO - Epoch(train) [45][700/925] lr: 9.3575e-05 eta: 4:31:05 time: 0.5031 data_time: 0.0024 memory: 7975 grad_norm: 717.6956 loss: 392.7584 loss_cls: 130.6340 loss_bbox: 124.0103 loss_dfl: 138.1142 +2024/03/21 02:51:49 - mmengine - INFO - Epoch(train) [45][750/925] lr: 9.3575e-05 eta: 4:30:41 time: 0.5140 data_time: 0.0026 memory: 7882 grad_norm: 713.9468 loss: 389.3586 loss_cls: 129.8866 loss_bbox: 120.8938 loss_dfl: 138.5783 +2024/03/21 02:52:14 - mmengine - INFO - Epoch(train) [45][800/925] lr: 9.3575e-05 eta: 4:30:16 time: 0.5076 data_time: 0.0025 memory: 7935 grad_norm: 714.4154 loss: 389.1196 loss_cls: 130.0747 loss_bbox: 120.7776 loss_dfl: 138.2673 +2024/03/21 02:52:39 - mmengine - INFO - Epoch(train) [45][850/925] lr: 9.3575e-05 eta: 4:29:51 time: 0.4992 data_time: 0.0025 memory: 8015 grad_norm: 735.5004 loss: 391.3199 loss_cls: 130.6598 loss_bbox: 121.5519 loss_dfl: 139.1082 +2024/03/21 02:53:05 - mmengine - INFO - Epoch(train) [45][900/925] lr: 9.3575e-05 eta: 4:29:27 time: 0.5035 data_time: 0.0024 memory: 8082 grad_norm: 720.6818 loss: 399.2896 loss_cls: 134.0739 loss_bbox: 125.2900 loss_dfl: 139.9256 +2024/03/21 02:53:16 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:53:17 - mmengine - INFO - Saving checkpoint at 45 epochs +2024/03/21 02:53:26 - mmengine - INFO - Epoch(val) [45][ 50/625] eta: 0:00:22 time: 0.0386 data_time: 0.0009 memory: 7949 +2024/03/21 02:53:28 - mmengine - INFO - Epoch(val) [45][100/625] eta: 0:00:19 time: 0.0347 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:30 - mmengine - INFO - Epoch(val) [45][150/625] eta: 0:00:17 time: 0.0377 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:31 - mmengine - INFO - Epoch(val) [45][200/625] eta: 0:00:15 time: 0.0357 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:33 - mmengine - INFO - Epoch(val) [45][250/625] eta: 0:00:13 time: 0.0356 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:35 - mmengine - INFO - Epoch(val) [45][300/625] eta: 0:00:11 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:37 - mmengine - INFO - Epoch(val) [45][350/625] eta: 0:00:09 time: 0.0352 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:39 - mmengine - INFO - Epoch(val) [45][400/625] eta: 0:00:08 time: 0.0362 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:40 - mmengine - INFO - Epoch(val) [45][450/625] eta: 0:00:06 time: 0.0331 data_time: 0.0003 memory: 1244 +2024/03/21 02:53:42 - mmengine - INFO - Epoch(val) [45][500/625] eta: 0:00:04 time: 0.0281 data_time: 0.0002 memory: 1244 +2024/03/21 02:53:43 - mmengine - INFO - Epoch(val) [45][550/625] eta: 0:00:02 time: 0.0288 data_time: 0.0002 memory: 1244 +2024/03/21 02:53:45 - mmengine - INFO - Epoch(val) [45][600/625] eta: 0:00:00 time: 0.0281 data_time: 0.0002 memory: 1244 +2024/03/21 02:53:57 - mmengine - INFO - Evaluating bbox... +2024/03/21 02:55:07 - mmengine - INFO - bbox_mAP_copypaste: 0.503 0.669 0.549 0.320 0.555 0.667 +2024/03/21 02:55:09 - mmengine - INFO - Epoch(val) [45][625/625] coco/bbox_mAP: 0.5030 coco/bbox_mAP_50: 0.6690 coco/bbox_mAP_75: 0.5490 coco/bbox_mAP_s: 0.3200 coco/bbox_mAP_m: 0.5550 coco/bbox_mAP_l: 0.6670 data_time: 0.0002 time: 0.0279 +2024/03/21 02:55:38 - mmengine - INFO - Epoch(train) [46][ 50/925] lr: 9.1100e-05 eta: 4:28:52 time: 0.5819 data_time: 0.0701 memory: 7882 grad_norm: 736.2132 loss: 392.9982 loss_cls: 131.5748 loss_bbox: 122.1389 loss_dfl: 139.2844 +2024/03/21 02:56:03 - mmengine - INFO - Epoch(train) [46][100/925] lr: 9.1100e-05 eta: 4:28:27 time: 0.4983 data_time: 0.0025 memory: 7735 grad_norm: 790.6494 loss: 387.7675 loss_cls: 129.0794 loss_bbox: 120.5351 loss_dfl: 138.1530 +2024/03/21 02:56:28 - mmengine - INFO - Epoch(train) [46][150/925] lr: 9.1100e-05 eta: 4:28:02 time: 0.5002 data_time: 0.0026 memory: 8055 grad_norm: 718.9345 loss: 388.7173 loss_cls: 128.5289 loss_bbox: 121.9805 loss_dfl: 138.2079 +2024/03/21 02:56:54 - mmengine - INFO - Epoch(train) [46][200/925] lr: 9.1100e-05 eta: 4:27:38 time: 0.5123 data_time: 0.0024 memory: 7802 grad_norm: 793.1528 loss: 377.7962 loss_cls: 123.7593 loss_bbox: 117.7720 loss_dfl: 136.2650 +2024/03/21 02:57:19 - mmengine - INFO - Epoch(train) [46][250/925] lr: 9.1100e-05 eta: 4:27:13 time: 0.5087 data_time: 0.0025 memory: 8055 grad_norm: 750.7545 loss: 393.3209 loss_cls: 130.9046 loss_bbox: 122.8297 loss_dfl: 139.5866 +2024/03/21 02:57:45 - mmengine - INFO - Epoch(train) [46][300/925] lr: 9.1100e-05 eta: 4:26:48 time: 0.5062 data_time: 0.0025 memory: 8162 grad_norm: 707.8690 loss: 390.2632 loss_cls: 128.6164 loss_bbox: 123.4052 loss_dfl: 138.2416 +2024/03/21 02:58:10 - mmengine - INFO - Epoch(train) [46][350/925] lr: 9.1100e-05 eta: 4:26:23 time: 0.4939 data_time: 0.0025 memory: 7815 grad_norm: 741.7948 loss: 393.1605 loss_cls: 131.2784 loss_bbox: 123.3300 loss_dfl: 138.5521 +2024/03/21 02:58:22 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 02:58:34 - mmengine - INFO - Epoch(train) [46][400/925] lr: 9.1100e-05 eta: 4:25:58 time: 0.4940 data_time: 0.0024 memory: 8029 grad_norm: 734.2596 loss: 391.7082 loss_cls: 131.4261 loss_bbox: 121.8438 loss_dfl: 138.4382 +2024/03/21 02:59:00 - mmengine - INFO - Epoch(train) [46][450/925] lr: 9.1100e-05 eta: 4:25:34 time: 0.5153 data_time: 0.0024 memory: 7789 grad_norm: 781.6886 loss: 388.5375 loss_cls: 129.3728 loss_bbox: 121.1184 loss_dfl: 138.0464 +2024/03/21 02:59:25 - mmengine - INFO - Epoch(train) [46][500/925] lr: 9.1100e-05 eta: 4:25:09 time: 0.4976 data_time: 0.0024 memory: 8482 grad_norm: 736.1466 loss: 399.6769 loss_cls: 133.0185 loss_bbox: 126.5927 loss_dfl: 140.0657 +2024/03/21 02:59:50 - mmengine - INFO - Epoch(train) [46][550/925] lr: 9.1100e-05 eta: 4:24:44 time: 0.5045 data_time: 0.0024 memory: 7842 grad_norm: 756.2917 loss: 391.6222 loss_cls: 131.0598 loss_bbox: 122.0125 loss_dfl: 138.5499 +2024/03/21 03:00:15 - mmengine - INFO - Epoch(train) [46][600/925] lr: 9.1100e-05 eta: 4:24:19 time: 0.5049 data_time: 0.0023 memory: 8095 grad_norm: 733.3364 loss: 388.1429 loss_cls: 128.9679 loss_bbox: 122.0221 loss_dfl: 137.1529 +2024/03/21 03:00:41 - mmengine - INFO - Epoch(train) [46][650/925] lr: 9.1100e-05 eta: 4:23:54 time: 0.5007 data_time: 0.0025 memory: 8082 grad_norm: 791.0526 loss: 387.9611 loss_cls: 129.6090 loss_bbox: 120.5210 loss_dfl: 137.8311 +2024/03/21 03:01:06 - mmengine - INFO - Epoch(train) [46][700/925] lr: 9.1100e-05 eta: 4:23:29 time: 0.5025 data_time: 0.0024 memory: 7869 grad_norm: 712.0117 loss: 390.5839 loss_cls: 130.1545 loss_bbox: 121.8250 loss_dfl: 138.6045 +2024/03/21 03:01:31 - mmengine - INFO - Epoch(train) [46][750/925] lr: 9.1100e-05 eta: 4:23:05 time: 0.5093 data_time: 0.0024 memory: 7935 grad_norm: 724.3348 loss: 387.6363 loss_cls: 127.6654 loss_bbox: 121.9280 loss_dfl: 138.0429 +2024/03/21 03:01:56 - mmengine - INFO - Epoch(train) [46][800/925] lr: 9.1100e-05 eta: 4:22:40 time: 0.4925 data_time: 0.0024 memory: 8135 grad_norm: 666.5828 loss: 386.6770 loss_cls: 126.9113 loss_bbox: 122.1405 loss_dfl: 137.6252 +2024/03/21 03:02:22 - mmengine - INFO - Epoch(train) [46][850/925] lr: 9.1100e-05 eta: 4:22:15 time: 0.5136 data_time: 0.0024 memory: 7882 grad_norm: 740.4502 loss: 386.3187 loss_cls: 126.8290 loss_bbox: 122.5481 loss_dfl: 136.9415 +2024/03/21 03:02:47 - mmengine - INFO - Epoch(train) [46][900/925] lr: 9.1100e-05 eta: 4:21:51 time: 0.5150 data_time: 0.0024 memory: 8055 grad_norm: 753.7207 loss: 390.3279 loss_cls: 130.7822 loss_bbox: 122.1011 loss_dfl: 137.4445 +2024/03/21 03:02:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:03:29 - mmengine - INFO - Epoch(train) [47][ 50/925] lr: 8.8625e-05 eta: 4:21:16 time: 0.5788 data_time: 0.0618 memory: 7922 grad_norm: 740.5630 loss: 389.7247 loss_cls: 128.7105 loss_bbox: 122.6888 loss_dfl: 138.3255 +2024/03/21 03:03:54 - mmengine - INFO - Epoch(train) [47][100/925] lr: 8.8625e-05 eta: 4:20:52 time: 0.5153 data_time: 0.0024 memory: 7802 grad_norm: 767.0241 loss: 385.7395 loss_cls: 127.2736 loss_bbox: 120.9296 loss_dfl: 137.5363 +2024/03/21 03:04:20 - mmengine - INFO - Epoch(train) [47][150/925] lr: 8.8625e-05 eta: 4:20:27 time: 0.5049 data_time: 0.0025 memory: 7962 grad_norm: 755.2842 loss: 386.1044 loss_cls: 127.8879 loss_bbox: 119.7420 loss_dfl: 138.4745 +2024/03/21 03:04:46 - mmengine - INFO - Epoch(train) [47][200/925] lr: 8.8625e-05 eta: 4:20:03 time: 0.5257 data_time: 0.0027 memory: 8042 grad_norm: 700.9381 loss: 383.8936 loss_cls: 125.7261 loss_bbox: 121.1497 loss_dfl: 137.0177 +2024/03/21 03:05:12 - mmengine - INFO - Epoch(train) [47][250/925] lr: 8.8625e-05 eta: 4:19:38 time: 0.5165 data_time: 0.0023 memory: 7975 grad_norm: 750.8557 loss: 390.1122 loss_cls: 129.9574 loss_bbox: 121.9141 loss_dfl: 138.2407 +2024/03/21 03:05:37 - mmengine - INFO - Epoch(train) [47][300/925] lr: 8.8625e-05 eta: 4:19:14 time: 0.5054 data_time: 0.0026 memory: 7989 grad_norm: 770.8058 loss: 392.2553 loss_cls: 130.8056 loss_bbox: 123.1726 loss_dfl: 138.2771 +2024/03/21 03:06:03 - mmengine - INFO - Epoch(train) [47][350/925] lr: 8.8625e-05 eta: 4:18:50 time: 0.5206 data_time: 0.0025 memory: 8175 grad_norm: 716.7253 loss: 388.1738 loss_cls: 128.7138 loss_bbox: 121.7005 loss_dfl: 137.7595 +2024/03/21 03:06:29 - mmengine - INFO - Epoch(train) [47][400/925] lr: 8.8625e-05 eta: 4:18:25 time: 0.5120 data_time: 0.0025 memory: 8189 grad_norm: 743.6892 loss: 394.7069 loss_cls: 131.8248 loss_bbox: 123.1797 loss_dfl: 139.7024 +2024/03/21 03:06:55 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:06:55 - mmengine - INFO - Epoch(train) [47][450/925] lr: 8.8625e-05 eta: 4:18:01 time: 0.5129 data_time: 0.0026 memory: 8095 grad_norm: 753.7545 loss: 387.3362 loss_cls: 128.6344 loss_bbox: 120.5479 loss_dfl: 138.1539 +2024/03/21 03:07:21 - mmengine - INFO - Epoch(train) [47][500/925] lr: 8.8625e-05 eta: 4:17:36 time: 0.5238 data_time: 0.0026 memory: 7735 grad_norm: 773.4189 loss: 386.3481 loss_cls: 126.9383 loss_bbox: 121.1543 loss_dfl: 138.2555 +2024/03/21 03:07:46 - mmengine - INFO - Epoch(train) [47][550/925] lr: 8.8625e-05 eta: 4:17:12 time: 0.5104 data_time: 0.0026 memory: 8069 grad_norm: 733.1742 loss: 394.3020 loss_cls: 131.3919 loss_bbox: 124.0689 loss_dfl: 138.8412 +2024/03/21 03:08:12 - mmengine - INFO - Epoch(train) [47][600/925] lr: 8.8625e-05 eta: 4:16:47 time: 0.5135 data_time: 0.0026 memory: 7949 grad_norm: 775.8036 loss: 389.9054 loss_cls: 129.8630 loss_bbox: 121.9484 loss_dfl: 138.0939 +2024/03/21 03:08:39 - mmengine - INFO - Epoch(train) [47][650/925] lr: 8.8625e-05 eta: 4:16:23 time: 0.5282 data_time: 0.0027 memory: 8189 grad_norm: 753.4662 loss: 383.7014 loss_cls: 126.7213 loss_bbox: 119.4772 loss_dfl: 137.5030 +2024/03/21 03:09:03 - mmengine - INFO - Epoch(train) [47][700/925] lr: 8.8625e-05 eta: 4:15:58 time: 0.4904 data_time: 0.0025 memory: 7789 grad_norm: 769.3710 loss: 381.6912 loss_cls: 125.3201 loss_bbox: 119.0767 loss_dfl: 137.2943 +2024/03/21 03:09:30 - mmengine - INFO - Epoch(train) [47][750/925] lr: 8.8625e-05 eta: 4:15:34 time: 0.5311 data_time: 0.0026 memory: 7935 grad_norm: 717.3986 loss: 388.5277 loss_cls: 129.7032 loss_bbox: 121.4729 loss_dfl: 137.3517 +2024/03/21 03:09:55 - mmengine - INFO - Epoch(train) [47][800/925] lr: 8.8625e-05 eta: 4:15:10 time: 0.5131 data_time: 0.0026 memory: 8029 grad_norm: 713.1449 loss: 393.9677 loss_cls: 130.8364 loss_bbox: 124.6036 loss_dfl: 138.5277 +2024/03/21 03:10:21 - mmengine - INFO - Epoch(train) [47][850/925] lr: 8.8625e-05 eta: 4:14:45 time: 0.5063 data_time: 0.0026 memory: 7962 grad_norm: 738.6393 loss: 385.7292 loss_cls: 126.9313 loss_bbox: 121.1910 loss_dfl: 137.6069 +2024/03/21 03:10:46 - mmengine - INFO - Epoch(train) [47][900/925] lr: 8.8625e-05 eta: 4:14:21 time: 0.5116 data_time: 0.0027 memory: 7922 grad_norm: 695.3931 loss: 385.0990 loss_cls: 125.6760 loss_bbox: 121.9046 loss_dfl: 137.5184 +2024/03/21 03:10:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:11:28 - mmengine - INFO - Epoch(train) [48][ 50/925] lr: 8.6150e-05 eta: 4:13:46 time: 0.5657 data_time: 0.0633 memory: 7962 grad_norm: 743.2036 loss: 390.9756 loss_cls: 128.1140 loss_bbox: 123.8264 loss_dfl: 139.0352 +2024/03/21 03:11:54 - mmengine - INFO - Epoch(train) [48][100/925] lr: 8.6150e-05 eta: 4:13:21 time: 0.5135 data_time: 0.0026 memory: 7989 grad_norm: 705.0305 loss: 390.3269 loss_cls: 128.9975 loss_bbox: 123.1944 loss_dfl: 138.1349 +2024/03/21 03:12:19 - mmengine - INFO - Epoch(train) [48][150/925] lr: 8.6150e-05 eta: 4:12:56 time: 0.4973 data_time: 0.0027 memory: 7975 grad_norm: 715.7479 loss: 389.1691 loss_cls: 128.1183 loss_bbox: 122.6915 loss_dfl: 138.3593 +2024/03/21 03:12:44 - mmengine - INFO - Epoch(train) [48][200/925] lr: 8.6150e-05 eta: 4:12:31 time: 0.5071 data_time: 0.0027 memory: 7789 grad_norm: 696.5459 loss: 397.7678 loss_cls: 132.9331 loss_bbox: 125.2164 loss_dfl: 139.6184 +2024/03/21 03:13:09 - mmengine - INFO - Epoch(train) [48][250/925] lr: 8.6150e-05 eta: 4:12:06 time: 0.5050 data_time: 0.0028 memory: 8402 grad_norm: 722.7919 loss: 388.6737 loss_cls: 128.1482 loss_bbox: 121.5569 loss_dfl: 138.9686 +2024/03/21 03:13:35 - mmengine - INFO - Epoch(train) [48][300/925] lr: 8.6150e-05 eta: 4:11:42 time: 0.5095 data_time: 0.0026 memory: 7922 grad_norm: 709.3056 loss: 383.5888 loss_cls: 126.6631 loss_bbox: 119.0059 loss_dfl: 137.9199 +2024/03/21 03:14:00 - mmengine - INFO - Epoch(train) [48][350/925] lr: 8.6150e-05 eta: 4:11:17 time: 0.5041 data_time: 0.0026 memory: 7962 grad_norm: 775.9754 loss: 389.4778 loss_cls: 128.7202 loss_bbox: 122.6845 loss_dfl: 138.0731 +2024/03/21 03:14:25 - mmengine - INFO - Epoch(train) [48][400/925] lr: 8.6150e-05 eta: 4:10:52 time: 0.5025 data_time: 0.0024 memory: 8242 grad_norm: 711.0365 loss: 383.7932 loss_cls: 126.8875 loss_bbox: 120.6586 loss_dfl: 136.2471 +2024/03/21 03:14:50 - mmengine - INFO - Epoch(train) [48][450/925] lr: 8.6150e-05 eta: 4:10:27 time: 0.4971 data_time: 0.0028 memory: 7975 grad_norm: 765.2253 loss: 392.3577 loss_cls: 130.4720 loss_bbox: 122.7798 loss_dfl: 139.1059 +2024/03/21 03:15:15 - mmengine - INFO - Epoch(train) [48][500/925] lr: 8.6150e-05 eta: 4:10:02 time: 0.5073 data_time: 0.0026 memory: 8055 grad_norm: 724.6287 loss: 387.9559 loss_cls: 127.7022 loss_bbox: 122.4181 loss_dfl: 137.8356 +2024/03/21 03:15:28 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:15:41 - mmengine - INFO - Epoch(train) [48][550/925] lr: 8.6150e-05 eta: 4:09:38 time: 0.5042 data_time: 0.0027 memory: 8069 grad_norm: 797.7758 loss: 388.0072 loss_cls: 128.6291 loss_bbox: 121.5795 loss_dfl: 137.7986 +2024/03/21 03:16:05 - mmengine - INFO - Epoch(train) [48][600/925] lr: 8.6150e-05 eta: 4:09:12 time: 0.4930 data_time: 0.0026 memory: 8135 grad_norm: 729.8190 loss: 385.4631 loss_cls: 125.3569 loss_bbox: 122.8895 loss_dfl: 137.2167 +2024/03/21 03:16:31 - mmengine - INFO - Epoch(train) [48][650/925] lr: 8.6150e-05 eta: 4:08:48 time: 0.5100 data_time: 0.0026 memory: 7922 grad_norm: 761.4557 loss: 389.9824 loss_cls: 128.9102 loss_bbox: 122.9985 loss_dfl: 138.0737 +2024/03/21 03:16:57 - mmengine - INFO - Epoch(train) [48][700/925] lr: 8.6150e-05 eta: 4:08:23 time: 0.5120 data_time: 0.0025 memory: 7949 grad_norm: 722.9294 loss: 390.9031 loss_cls: 129.4254 loss_bbox: 123.6369 loss_dfl: 137.8408 +2024/03/21 03:17:21 - mmengine - INFO - Epoch(train) [48][750/925] lr: 8.6150e-05 eta: 4:07:58 time: 0.4962 data_time: 0.0027 memory: 8029 grad_norm: 702.6526 loss: 388.4348 loss_cls: 128.9418 loss_bbox: 121.5361 loss_dfl: 137.9569 +2024/03/21 03:17:48 - mmengine - INFO - Epoch(train) [48][800/925] lr: 8.6150e-05 eta: 4:07:34 time: 0.5251 data_time: 0.0028 memory: 8109 grad_norm: 727.1838 loss: 385.4217 loss_cls: 127.6379 loss_bbox: 120.3717 loss_dfl: 137.4120 +2024/03/21 03:18:14 - mmengine - INFO - Epoch(train) [48][850/925] lr: 8.6150e-05 eta: 4:07:09 time: 0.5156 data_time: 0.0029 memory: 7882 grad_norm: inf loss: 384.9010 loss_cls: 126.1320 loss_bbox: 121.3735 loss_dfl: 137.3955 +2024/03/21 03:18:39 - mmengine - INFO - Epoch(train) [48][900/925] lr: 8.6150e-05 eta: 4:06:45 time: 0.5043 data_time: 0.0025 memory: 7949 grad_norm: 752.1491 loss: 385.8529 loss_cls: 126.5856 loss_bbox: 121.9548 loss_dfl: 137.3126 +2024/03/21 03:18:51 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:19:20 - mmengine - INFO - Epoch(train) [49][ 50/925] lr: 8.3675e-05 eta: 4:06:09 time: 0.5706 data_time: 0.0710 memory: 7815 grad_norm: 735.7795 loss: 381.1620 loss_cls: 124.8035 loss_bbox: 119.5361 loss_dfl: 136.8224 +2024/03/21 03:19:45 - mmengine - INFO - Epoch(train) [49][100/925] lr: 8.3675e-05 eta: 4:05:44 time: 0.5026 data_time: 0.0024 memory: 8455 grad_norm: 758.7743 loss: 387.5627 loss_cls: 128.0112 loss_bbox: 121.8485 loss_dfl: 137.7029 +2024/03/21 03:20:11 - mmengine - INFO - Epoch(train) [49][150/925] lr: 8.3675e-05 eta: 4:05:20 time: 0.5241 data_time: 0.0026 memory: 7802 grad_norm: 758.5248 loss: 387.9514 loss_cls: 128.6556 loss_bbox: 121.8454 loss_dfl: 137.4504 +2024/03/21 03:20:37 - mmengine - INFO - Epoch(train) [49][200/925] lr: 8.3675e-05 eta: 4:04:55 time: 0.5003 data_time: 0.0023 memory: 7949 grad_norm: 717.9037 loss: 383.0643 loss_cls: 125.8419 loss_bbox: 120.7204 loss_dfl: 136.5020 +2024/03/21 03:21:02 - mmengine - INFO - Epoch(train) [49][250/925] lr: 8.3675e-05 eta: 4:04:30 time: 0.5042 data_time: 0.0025 memory: 8029 grad_norm: 740.3134 loss: 386.7510 loss_cls: 126.5122 loss_bbox: 121.9389 loss_dfl: 138.2999 +2024/03/21 03:21:28 - mmengine - INFO - Epoch(train) [49][300/925] lr: 8.3675e-05 eta: 4:04:06 time: 0.5240 data_time: 0.0025 memory: 7949 grad_norm: 721.2548 loss: 387.4325 loss_cls: 127.5791 loss_bbox: 122.1240 loss_dfl: 137.7295 +2024/03/21 03:21:53 - mmengine - INFO - Epoch(train) [49][350/925] lr: 8.3675e-05 eta: 4:03:41 time: 0.4997 data_time: 0.0025 memory: 7935 grad_norm: 692.7288 loss: 385.7773 loss_cls: 126.5492 loss_bbox: 121.8434 loss_dfl: 137.3847 +2024/03/21 03:22:19 - mmengine - INFO - Epoch(train) [49][400/925] lr: 8.3675e-05 eta: 4:03:17 time: 0.5138 data_time: 0.0025 memory: 7975 grad_norm: 756.9637 loss: 385.8098 loss_cls: 127.7404 loss_bbox: 119.9232 loss_dfl: 138.1462 +2024/03/21 03:22:44 - mmengine - INFO - Epoch(train) [49][450/925] lr: 8.3675e-05 eta: 4:02:52 time: 0.5125 data_time: 0.0025 memory: 8215 grad_norm: 749.2050 loss: 390.0535 loss_cls: 129.2928 loss_bbox: 122.2852 loss_dfl: 138.4755 +2024/03/21 03:23:10 - mmengine - INFO - Epoch(train) [49][500/925] lr: 8.3675e-05 eta: 4:02:28 time: 0.5140 data_time: 0.0025 memory: 7989 grad_norm: 780.8589 loss: 384.4512 loss_cls: 126.7065 loss_bbox: 120.5139 loss_dfl: 137.2308 +2024/03/21 03:23:36 - mmengine - INFO - Epoch(train) [49][550/925] lr: 8.3675e-05 eta: 4:02:03 time: 0.5206 data_time: 0.0025 memory: 7855 grad_norm: 759.2529 loss: 384.3662 loss_cls: 125.5344 loss_bbox: 120.6415 loss_dfl: 138.1903 +2024/03/21 03:24:01 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:24:01 - mmengine - INFO - Epoch(train) [49][600/925] lr: 8.3675e-05 eta: 4:01:38 time: 0.4988 data_time: 0.0025 memory: 7842 grad_norm: 759.6802 loss: 384.1489 loss_cls: 125.5455 loss_bbox: 121.5804 loss_dfl: 137.0229 +2024/03/21 03:24:26 - mmengine - INFO - Epoch(train) [49][650/925] lr: 8.3675e-05 eta: 4:01:13 time: 0.5016 data_time: 0.0025 memory: 7802 grad_norm: 771.2563 loss: 390.2843 loss_cls: 129.6742 loss_bbox: 122.3165 loss_dfl: 138.2936 +2024/03/21 03:24:53 - mmengine - INFO - Epoch(train) [49][700/925] lr: 8.3675e-05 eta: 4:00:49 time: 0.5317 data_time: 0.0024 memory: 8109 grad_norm: 710.5445 loss: 381.9807 loss_cls: 125.7415 loss_bbox: 118.5235 loss_dfl: 137.7157 +2024/03/21 03:25:18 - mmengine - INFO - Epoch(train) [49][750/925] lr: 8.3675e-05 eta: 4:00:24 time: 0.4987 data_time: 0.0025 memory: 7855 grad_norm: 780.4787 loss: 384.7595 loss_cls: 126.7214 loss_bbox: 120.9207 loss_dfl: 137.1174 +2024/03/21 03:25:43 - mmengine - INFO - Epoch(train) [49][800/925] lr: 8.3675e-05 eta: 3:59:59 time: 0.5048 data_time: 0.0024 memory: 7829 grad_norm: 785.0418 loss: 387.9639 loss_cls: 127.5773 loss_bbox: 121.0486 loss_dfl: 139.3379 +2024/03/21 03:26:09 - mmengine - INFO - Epoch(train) [49][850/925] lr: 8.3675e-05 eta: 3:59:35 time: 0.5114 data_time: 0.0025 memory: 8029 grad_norm: 747.4705 loss: 385.8200 loss_cls: 126.9646 loss_bbox: 120.1172 loss_dfl: 138.7382 +2024/03/21 03:26:35 - mmengine - INFO - Epoch(train) [49][900/925] lr: 8.3675e-05 eta: 3:59:10 time: 0.5156 data_time: 0.0027 memory: 7922 grad_norm: 733.3381 loss: 383.0982 loss_cls: 125.7879 loss_bbox: 120.6543 loss_dfl: 136.6560 +2024/03/21 03:26:47 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:27:16 - mmengine - INFO - Epoch(train) [50][ 50/925] lr: 8.1200e-05 eta: 3:58:35 time: 0.5868 data_time: 0.0603 memory: 7842 grad_norm: 785.6591 loss: 390.9742 loss_cls: 130.7687 loss_bbox: 122.0702 loss_dfl: 138.1354 +2024/03/21 03:27:41 - mmengine - INFO - Epoch(train) [50][100/925] lr: 8.1200e-05 eta: 3:58:10 time: 0.4913 data_time: 0.0026 memory: 7842 grad_norm: 762.5656 loss: 381.1012 loss_cls: 124.1025 loss_bbox: 120.2867 loss_dfl: 136.7120 +2024/03/21 03:28:07 - mmengine - INFO - Epoch(train) [50][150/925] lr: 8.1200e-05 eta: 3:57:45 time: 0.5122 data_time: 0.0025 memory: 7909 grad_norm: 766.7844 loss: 393.8023 loss_cls: 131.1581 loss_bbox: 123.4243 loss_dfl: 139.2199 +2024/03/21 03:28:33 - mmengine - INFO - Epoch(train) [50][200/925] lr: 8.1200e-05 eta: 3:57:21 time: 0.5187 data_time: 0.0026 memory: 7762 grad_norm: 750.3087 loss: 381.4998 loss_cls: 124.1800 loss_bbox: 120.1966 loss_dfl: 137.1231 +2024/03/21 03:28:57 - mmengine - INFO - Epoch(train) [50][250/925] lr: 8.1200e-05 eta: 3:56:56 time: 0.4951 data_time: 0.0027 memory: 8015 grad_norm: 751.7883 loss: 386.3198 loss_cls: 128.2194 loss_bbox: 120.5041 loss_dfl: 137.5964 +2024/03/21 03:29:23 - mmengine - INFO - Epoch(train) [50][300/925] lr: 8.1200e-05 eta: 3:56:31 time: 0.5179 data_time: 0.0027 memory: 7922 grad_norm: 737.1470 loss: 388.9972 loss_cls: 128.7239 loss_bbox: 122.0792 loss_dfl: 138.1941 +2024/03/21 03:29:49 - mmengine - INFO - Epoch(train) [50][350/925] lr: 8.1200e-05 eta: 3:56:06 time: 0.5087 data_time: 0.0026 memory: 7815 grad_norm: 717.4607 loss: 383.4096 loss_cls: 125.5325 loss_bbox: 120.6930 loss_dfl: 137.1842 +2024/03/21 03:30:14 - mmengine - INFO - Epoch(train) [50][400/925] lr: 8.1200e-05 eta: 3:55:41 time: 0.5022 data_time: 0.0026 memory: 8069 grad_norm: 752.7485 loss: 391.5329 loss_cls: 128.6279 loss_bbox: 123.5213 loss_dfl: 139.3836 +2024/03/21 03:30:40 - mmengine - INFO - Epoch(train) [50][450/925] lr: 8.1200e-05 eta: 3:55:17 time: 0.5223 data_time: 0.0027 memory: 8042 grad_norm: 719.0110 loss: 388.4384 loss_cls: 128.1795 loss_bbox: 122.1143 loss_dfl: 138.1447 +2024/03/21 03:31:05 - mmengine - INFO - Epoch(train) [50][500/925] lr: 8.1200e-05 eta: 3:54:52 time: 0.5011 data_time: 0.0027 memory: 7842 grad_norm: 742.9590 loss: 385.6978 loss_cls: 127.1034 loss_bbox: 120.0199 loss_dfl: 138.5745 +2024/03/21 03:31:31 - mmengine - INFO - Epoch(train) [50][550/925] lr: 8.1200e-05 eta: 3:54:28 time: 0.5131 data_time: 0.0024 memory: 7829 grad_norm: 807.5423 loss: 383.5126 loss_cls: 126.9012 loss_bbox: 120.4601 loss_dfl: 136.1513 +2024/03/21 03:31:57 - mmengine - INFO - Epoch(train) [50][600/925] lr: 8.1200e-05 eta: 3:54:03 time: 0.5273 data_time: 0.0026 memory: 8202 grad_norm: 757.7689 loss: 381.5414 loss_cls: 126.5259 loss_bbox: 118.9224 loss_dfl: 136.0931 +2024/03/21 03:32:22 - mmengine - INFO - Epoch(train) [50][650/925] lr: 8.1200e-05 eta: 3:53:38 time: 0.5037 data_time: 0.0024 memory: 8149 grad_norm: 754.3033 loss: 386.7192 loss_cls: 126.0671 loss_bbox: 122.7214 loss_dfl: 137.9307 +2024/03/21 03:32:35 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:32:48 - mmengine - INFO - Epoch(train) [50][700/925] lr: 8.1200e-05 eta: 3:53:14 time: 0.5148 data_time: 0.0025 memory: 7762 grad_norm: 773.2929 loss: 390.8204 loss_cls: 128.9165 loss_bbox: 123.4392 loss_dfl: 138.4646 +2024/03/21 03:33:14 - mmengine - INFO - Epoch(train) [50][750/925] lr: 8.1200e-05 eta: 3:52:49 time: 0.5133 data_time: 0.0026 memory: 7829 grad_norm: 764.8916 loss: 381.4649 loss_cls: 123.9205 loss_bbox: 120.1247 loss_dfl: 137.4197 +2024/03/21 03:33:39 - mmengine - INFO - Epoch(train) [50][800/925] lr: 8.1200e-05 eta: 3:52:25 time: 0.5099 data_time: 0.0025 memory: 8015 grad_norm: 771.8540 loss: 378.8607 loss_cls: 122.2606 loss_bbox: 120.0134 loss_dfl: 136.5867 +2024/03/21 03:34:05 - mmengine - INFO - Epoch(train) [50][850/925] lr: 8.1200e-05 eta: 3:52:00 time: 0.5097 data_time: 0.0025 memory: 7815 grad_norm: 727.9400 loss: 388.0294 loss_cls: 130.4086 loss_bbox: 118.8342 loss_dfl: 138.7866 +2024/03/21 03:34:30 - mmengine - INFO - Epoch(train) [50][900/925] lr: 8.1200e-05 eta: 3:51:35 time: 0.5074 data_time: 0.0026 memory: 7975 grad_norm: 758.4962 loss: 387.2682 loss_cls: 128.8963 loss_bbox: 121.1940 loss_dfl: 137.1780 +2024/03/21 03:34:42 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:34:43 - mmengine - INFO - Saving checkpoint at 50 epochs +2024/03/21 03:34:52 - mmengine - INFO - Epoch(val) [50][ 50/625] eta: 0:00:20 time: 0.0359 data_time: 0.0008 memory: 7615 +2024/03/21 03:34:54 - mmengine - INFO - Epoch(val) [50][100/625] eta: 0:00:19 time: 0.0379 data_time: 0.0012 memory: 1244 +2024/03/21 03:34:55 - mmengine - INFO - Epoch(val) [50][150/625] eta: 0:00:17 time: 0.0364 data_time: 0.0003 memory: 1244 +2024/03/21 03:34:57 - mmengine - INFO - Epoch(val) [50][200/625] eta: 0:00:15 time: 0.0369 data_time: 0.0003 memory: 1244 +2024/03/21 03:34:59 - mmengine - INFO - Epoch(val) [50][250/625] eta: 0:00:13 time: 0.0380 data_time: 0.0003 memory: 1244 +2024/03/21 03:35:01 - mmengine - INFO - Epoch(val) [50][300/625] eta: 0:00:11 time: 0.0350 data_time: 0.0003 memory: 1244 +2024/03/21 03:35:04 - mmengine - INFO - Epoch(val) [50][350/625] eta: 0:00:11 time: 0.0619 data_time: 0.0258 memory: 1244 +2024/03/21 03:35:06 - mmengine - INFO - Epoch(val) [50][400/625] eta: 0:00:08 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 03:35:07 - mmengine - INFO - Epoch(val) [50][450/625] eta: 0:00:06 time: 0.0316 data_time: 0.0002 memory: 1244 +2024/03/21 03:35:09 - mmengine - INFO - Epoch(val) [50][500/625] eta: 0:00:04 time: 0.0284 data_time: 0.0002 memory: 1244 +2024/03/21 03:35:10 - mmengine - INFO - Epoch(val) [50][550/625] eta: 0:00:02 time: 0.0286 data_time: 0.0002 memory: 1244 +2024/03/21 03:35:12 - mmengine - INFO - Epoch(val) [50][600/625] eta: 0:00:00 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 03:35:24 - mmengine - INFO - Evaluating bbox... +2024/03/21 03:36:41 - mmengine - INFO - bbox_mAP_copypaste: 0.504 0.669 0.549 0.321 0.555 0.668 +2024/03/21 03:36:43 - mmengine - INFO - Epoch(val) [50][625/625] coco/bbox_mAP: 0.5040 coco/bbox_mAP_50: 0.6690 coco/bbox_mAP_75: 0.5490 coco/bbox_mAP_s: 0.3210 coco/bbox_mAP_m: 0.5550 coco/bbox_mAP_l: 0.6680 data_time: 0.0002 time: 0.0290 +2024/03/21 03:37:12 - mmengine - INFO - Epoch(train) [51][ 50/925] lr: 7.8725e-05 eta: 3:51:00 time: 0.5781 data_time: 0.0824 memory: 8295 grad_norm: 726.1240 loss: 387.9012 loss_cls: 128.1407 loss_bbox: 122.4512 loss_dfl: 137.3093 +2024/03/21 03:37:38 - mmengine - INFO - Epoch(train) [51][100/925] lr: 7.8725e-05 eta: 3:50:35 time: 0.5119 data_time: 0.0027 memory: 7722 grad_norm: 773.9153 loss: 381.2292 loss_cls: 125.3067 loss_bbox: 119.2618 loss_dfl: 136.6607 +2024/03/21 03:38:02 - mmengine - INFO - Epoch(train) [51][150/925] lr: 7.8725e-05 eta: 3:50:10 time: 0.4922 data_time: 0.0026 memory: 7869 grad_norm: 728.6010 loss: 385.8866 loss_cls: 126.5183 loss_bbox: 121.6977 loss_dfl: 137.6705 +2024/03/21 03:38:28 - mmengine - INFO - Epoch(train) [51][200/925] lr: 7.8725e-05 eta: 3:49:45 time: 0.5092 data_time: 0.0024 memory: 7935 grad_norm: 758.6794 loss: 385.9777 loss_cls: 127.1544 loss_bbox: 121.9158 loss_dfl: 136.9075 +2024/03/21 03:38:53 - mmengine - INFO - Epoch(train) [51][250/925] lr: 7.8725e-05 eta: 3:49:20 time: 0.5100 data_time: 0.0024 memory: 7855 grad_norm: 718.4453 loss: 382.2603 loss_cls: 127.1397 loss_bbox: 117.7020 loss_dfl: 137.4186 +2024/03/21 03:39:18 - mmengine - INFO - Epoch(train) [51][300/925] lr: 7.8725e-05 eta: 3:48:55 time: 0.5030 data_time: 0.0025 memory: 7922 grad_norm: 719.5388 loss: 389.4908 loss_cls: 127.0286 loss_bbox: 124.3993 loss_dfl: 138.0629 +2024/03/21 03:39:44 - mmengine - INFO - Epoch(train) [51][350/925] lr: 7.8725e-05 eta: 3:48:31 time: 0.5118 data_time: 0.0024 memory: 8229 grad_norm: 736.5021 loss: 391.7714 loss_cls: 130.0126 loss_bbox: 123.2997 loss_dfl: 138.4590 +2024/03/21 03:40:09 - mmengine - INFO - Epoch(train) [51][400/925] lr: 7.8725e-05 eta: 3:48:05 time: 0.5001 data_time: 0.0026 memory: 7869 grad_norm: 813.1638 loss: 385.2970 loss_cls: 126.5718 loss_bbox: 120.7991 loss_dfl: 137.9261 +2024/03/21 03:40:35 - mmengine - INFO - Epoch(train) [51][450/925] lr: 7.8725e-05 eta: 3:47:41 time: 0.5174 data_time: 0.0026 memory: 8269 grad_norm: 735.0953 loss: 383.9044 loss_cls: 125.3250 loss_bbox: 121.1958 loss_dfl: 137.3837 +2024/03/21 03:41:00 - mmengine - INFO - Epoch(train) [51][500/925] lr: 7.8725e-05 eta: 3:47:16 time: 0.5039 data_time: 0.0026 memory: 7962 grad_norm: 706.2010 loss: 388.9580 loss_cls: 128.7391 loss_bbox: 122.3452 loss_dfl: 137.8737 +2024/03/21 03:41:25 - mmengine - INFO - Epoch(train) [51][550/925] lr: 7.8725e-05 eta: 3:46:51 time: 0.4911 data_time: 0.0026 memory: 7855 grad_norm: 736.9439 loss: 385.7975 loss_cls: 126.8683 loss_bbox: 121.1013 loss_dfl: 137.8279 +2024/03/21 03:41:51 - mmengine - INFO - Epoch(train) [51][600/925] lr: 7.8725e-05 eta: 3:46:26 time: 0.5191 data_time: 0.0025 memory: 7922 grad_norm: 776.8855 loss: 387.9625 loss_cls: 127.7790 loss_bbox: 122.2390 loss_dfl: 137.9445 +2024/03/21 03:42:16 - mmengine - INFO - Epoch(train) [51][650/925] lr: 7.8725e-05 eta: 3:46:01 time: 0.5023 data_time: 0.0025 memory: 8082 grad_norm: 776.2521 loss: 386.2945 loss_cls: 126.3477 loss_bbox: 122.3233 loss_dfl: 137.6236 +2024/03/21 03:42:41 - mmengine - INFO - Epoch(train) [51][700/925] lr: 7.8725e-05 eta: 3:45:36 time: 0.5011 data_time: 0.0025 memory: 7882 grad_norm: 755.5920 loss: 385.4189 loss_cls: 127.1506 loss_bbox: 121.3057 loss_dfl: 136.9625 +2024/03/21 03:43:06 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:43:06 - mmengine - INFO - Epoch(train) [51][750/925] lr: 7.8725e-05 eta: 3:45:11 time: 0.5063 data_time: 0.0024 memory: 8029 grad_norm: 738.5427 loss: 395.6239 loss_cls: 131.0400 loss_bbox: 124.7074 loss_dfl: 139.8765 +2024/03/21 03:43:31 - mmengine - INFO - Epoch(train) [51][800/925] lr: 7.8725e-05 eta: 3:44:46 time: 0.5017 data_time: 0.0026 memory: 8135 grad_norm: 704.4058 loss: 384.3348 loss_cls: 127.1556 loss_bbox: 120.6627 loss_dfl: 136.5165 +2024/03/21 03:43:56 - mmengine - INFO - Epoch(train) [51][850/925] lr: 7.8725e-05 eta: 3:44:21 time: 0.4963 data_time: 0.0025 memory: 8122 grad_norm: inf loss: 385.4300 loss_cls: 127.4377 loss_bbox: 120.2376 loss_dfl: 137.7547 +2024/03/21 03:44:23 - mmengine - INFO - Epoch(train) [51][900/925] lr: 7.8725e-05 eta: 3:43:57 time: 0.5229 data_time: 0.0025 memory: 7815 grad_norm: 730.4380 loss: 389.0052 loss_cls: 127.5789 loss_bbox: 123.5936 loss_dfl: 137.8327 +2024/03/21 03:44:34 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:45:03 - mmengine - INFO - Epoch(train) [52][ 50/925] lr: 7.6250e-05 eta: 3:43:21 time: 0.5589 data_time: 0.0655 memory: 7922 grad_norm: 770.7571 loss: 388.1268 loss_cls: 127.9721 loss_bbox: 121.9843 loss_dfl: 138.1704 +2024/03/21 03:45:28 - mmengine - INFO - Epoch(train) [52][100/925] lr: 7.6250e-05 eta: 3:42:56 time: 0.4967 data_time: 0.0025 memory: 8055 grad_norm: 799.7932 loss: 388.5283 loss_cls: 127.9814 loss_bbox: 121.2238 loss_dfl: 139.3231 +2024/03/21 03:45:52 - mmengine - INFO - Epoch(train) [52][150/925] lr: 7.6250e-05 eta: 3:42:30 time: 0.4903 data_time: 0.0025 memory: 8042 grad_norm: 770.0723 loss: 385.5927 loss_cls: 125.7279 loss_bbox: 121.4427 loss_dfl: 138.4221 +2024/03/21 03:46:18 - mmengine - INFO - Epoch(train) [52][200/925] lr: 7.6250e-05 eta: 3:42:05 time: 0.5020 data_time: 0.0024 memory: 7922 grad_norm: 761.1755 loss: 383.0848 loss_cls: 126.2545 loss_bbox: 118.2154 loss_dfl: 138.6149 +2024/03/21 03:46:43 - mmengine - INFO - Epoch(train) [52][250/925] lr: 7.6250e-05 eta: 3:41:41 time: 0.5084 data_time: 0.0025 memory: 7802 grad_norm: 761.1218 loss: 378.7269 loss_cls: 122.9365 loss_bbox: 119.6641 loss_dfl: 136.1262 +2024/03/21 03:47:07 - mmengine - INFO - Epoch(train) [52][300/925] lr: 7.6250e-05 eta: 3:41:15 time: 0.4868 data_time: 0.0025 memory: 7989 grad_norm: 776.8101 loss: 380.7743 loss_cls: 125.2463 loss_bbox: 118.9386 loss_dfl: 136.5894 +2024/03/21 03:47:32 - mmengine - INFO - Epoch(train) [52][350/925] lr: 7.6250e-05 eta: 3:40:50 time: 0.4984 data_time: 0.0024 memory: 8069 grad_norm: 733.8718 loss: 378.2654 loss_cls: 123.1578 loss_bbox: 118.5523 loss_dfl: 136.5553 +2024/03/21 03:47:58 - mmengine - INFO - Epoch(train) [52][400/925] lr: 7.6250e-05 eta: 3:40:25 time: 0.5101 data_time: 0.0025 memory: 7855 grad_norm: 765.4719 loss: 385.1338 loss_cls: 126.0524 loss_bbox: 120.7965 loss_dfl: 138.2850 +2024/03/21 03:48:22 - mmengine - INFO - Epoch(train) [52][450/925] lr: 7.6250e-05 eta: 3:40:00 time: 0.4811 data_time: 0.0024 memory: 7709 grad_norm: 791.8747 loss: 385.6506 loss_cls: 125.9953 loss_bbox: 121.9568 loss_dfl: 137.6985 +2024/03/21 03:48:47 - mmengine - INFO - Epoch(train) [52][500/925] lr: 7.6250e-05 eta: 3:39:34 time: 0.4917 data_time: 0.0024 memory: 7989 grad_norm: 741.7944 loss: 384.7208 loss_cls: 126.8457 loss_bbox: 121.4324 loss_dfl: 136.4426 +2024/03/21 03:49:12 - mmengine - INFO - Epoch(train) [52][550/925] lr: 7.6250e-05 eta: 3:39:09 time: 0.5022 data_time: 0.0025 memory: 8162 grad_norm: 696.0172 loss: 391.1146 loss_cls: 130.6685 loss_bbox: 123.0290 loss_dfl: 137.4171 +2024/03/21 03:49:36 - mmengine - INFO - Epoch(train) [52][600/925] lr: 7.6250e-05 eta: 3:38:44 time: 0.4892 data_time: 0.0024 memory: 7722 grad_norm: 799.7951 loss: 389.3297 loss_cls: 127.0698 loss_bbox: 123.7208 loss_dfl: 138.5391 +2024/03/21 03:50:01 - mmengine - INFO - Epoch(train) [52][650/925] lr: 7.6250e-05 eta: 3:38:19 time: 0.4969 data_time: 0.0024 memory: 8015 grad_norm: 792.6574 loss: 389.8907 loss_cls: 128.8084 loss_bbox: 122.2103 loss_dfl: 138.8721 +2024/03/21 03:50:26 - mmengine - INFO - Epoch(train) [52][700/925] lr: 7.6250e-05 eta: 3:37:54 time: 0.4971 data_time: 0.0029 memory: 8029 grad_norm: 724.0289 loss: 383.5421 loss_cls: 125.6763 loss_bbox: 120.7336 loss_dfl: 137.1321 +2024/03/21 03:50:50 - mmengine - INFO - Epoch(train) [52][750/925] lr: 7.6250e-05 eta: 3:37:28 time: 0.4839 data_time: 0.0025 memory: 7815 grad_norm: 719.5863 loss: 390.0493 loss_cls: 130.5239 loss_bbox: 121.3319 loss_dfl: 138.1935 +2024/03/21 03:51:14 - mmengine - INFO - Epoch(train) [52][800/925] lr: 7.6250e-05 eta: 3:37:03 time: 0.4857 data_time: 0.0025 memory: 8042 grad_norm: 775.5137 loss: 379.0178 loss_cls: 122.6408 loss_bbox: 120.2003 loss_dfl: 136.1766 +2024/03/21 03:51:27 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:51:39 - mmengine - INFO - Epoch(train) [52][850/925] lr: 7.6250e-05 eta: 3:36:38 time: 0.4967 data_time: 0.0024 memory: 8055 grad_norm: 778.1453 loss: 382.3973 loss_cls: 125.8957 loss_bbox: 119.3064 loss_dfl: 137.1952 +2024/03/21 03:52:04 - mmengine - INFO - Epoch(train) [52][900/925] lr: 7.6250e-05 eta: 3:36:13 time: 0.4880 data_time: 0.0025 memory: 7949 grad_norm: 737.9709 loss: 387.4698 loss_cls: 128.2542 loss_bbox: 121.5625 loss_dfl: 137.6531 +2024/03/21 03:52:15 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:52:43 - mmengine - INFO - Epoch(train) [53][ 50/925] lr: 7.3775e-05 eta: 3:35:36 time: 0.5506 data_time: 0.0544 memory: 7922 grad_norm: 788.0634 loss: 379.5786 loss_cls: 124.6070 loss_bbox: 118.3751 loss_dfl: 136.5965 +2024/03/21 03:53:08 - mmengine - INFO - Epoch(train) [53][100/925] lr: 7.3775e-05 eta: 3:35:10 time: 0.4884 data_time: 0.0025 memory: 8135 grad_norm: 753.3254 loss: 381.8255 loss_cls: 124.5745 loss_bbox: 120.4377 loss_dfl: 136.8133 +2024/03/21 03:53:33 - mmengine - INFO - Epoch(train) [53][150/925] lr: 7.3775e-05 eta: 3:34:46 time: 0.5049 data_time: 0.0024 memory: 8029 grad_norm: 720.9324 loss: 380.0292 loss_cls: 123.3387 loss_bbox: 119.7862 loss_dfl: 136.9043 +2024/03/21 03:53:57 - mmengine - INFO - Epoch(train) [53][200/925] lr: 7.3775e-05 eta: 3:34:20 time: 0.4846 data_time: 0.0026 memory: 7669 grad_norm: 740.1175 loss: 385.2486 loss_cls: 125.8302 loss_bbox: 121.5775 loss_dfl: 137.8410 +2024/03/21 03:54:22 - mmengine - INFO - Epoch(train) [53][250/925] lr: 7.3775e-05 eta: 3:33:55 time: 0.4890 data_time: 0.0027 memory: 7909 grad_norm: 753.5845 loss: 385.8829 loss_cls: 126.1737 loss_bbox: 122.2322 loss_dfl: 137.4771 +2024/03/21 03:54:47 - mmengine - INFO - Epoch(train) [53][300/925] lr: 7.3775e-05 eta: 3:33:30 time: 0.5062 data_time: 0.0024 memory: 7909 grad_norm: 737.1703 loss: 387.5902 loss_cls: 127.5988 loss_bbox: 121.6894 loss_dfl: 138.3019 +2024/03/21 03:55:12 - mmengine - INFO - Epoch(train) [53][350/925] lr: 7.3775e-05 eta: 3:33:05 time: 0.4945 data_time: 0.0024 memory: 7815 grad_norm: 774.6624 loss: 380.2289 loss_cls: 123.1081 loss_bbox: 120.6194 loss_dfl: 136.5014 +2024/03/21 03:55:36 - mmengine - INFO - Epoch(train) [53][400/925] lr: 7.3775e-05 eta: 3:32:39 time: 0.4882 data_time: 0.0023 memory: 8042 grad_norm: 751.6911 loss: 381.7063 loss_cls: 125.9080 loss_bbox: 118.7148 loss_dfl: 137.0836 +2024/03/21 03:56:01 - mmengine - INFO - Epoch(train) [53][450/925] lr: 7.3775e-05 eta: 3:32:14 time: 0.4973 data_time: 0.0025 memory: 9043 grad_norm: 780.1845 loss: 392.3420 loss_cls: 130.0778 loss_bbox: 123.4361 loss_dfl: 138.8282 +2024/03/21 03:56:26 - mmengine - INFO - Epoch(train) [53][500/925] lr: 7.3775e-05 eta: 3:31:49 time: 0.4966 data_time: 0.0024 memory: 7815 grad_norm: 716.5447 loss: 383.8886 loss_cls: 125.4509 loss_bbox: 121.0171 loss_dfl: 137.4207 +2024/03/21 03:56:51 - mmengine - INFO - Epoch(train) [53][550/925] lr: 7.3775e-05 eta: 3:31:24 time: 0.5048 data_time: 0.0023 memory: 7922 grad_norm: 741.3814 loss: 382.9585 loss_cls: 126.1925 loss_bbox: 120.4613 loss_dfl: 136.3047 +2024/03/21 03:57:17 - mmengine - INFO - Epoch(train) [53][600/925] lr: 7.3775e-05 eta: 3:30:59 time: 0.5017 data_time: 0.0026 memory: 7989 grad_norm: 767.5442 loss: 379.4517 loss_cls: 123.2365 loss_bbox: 120.0444 loss_dfl: 136.1708 +2024/03/21 03:57:41 - mmengine - INFO - Epoch(train) [53][650/925] lr: 7.3775e-05 eta: 3:30:34 time: 0.4952 data_time: 0.0025 memory: 7842 grad_norm: 802.4242 loss: 387.2837 loss_cls: 125.7433 loss_bbox: 123.5420 loss_dfl: 137.9984 +2024/03/21 03:58:07 - mmengine - INFO - Epoch(train) [53][700/925] lr: 7.3775e-05 eta: 3:30:10 time: 0.5157 data_time: 0.0026 memory: 7962 grad_norm: 722.2885 loss: 378.8749 loss_cls: 123.8767 loss_bbox: 118.8785 loss_dfl: 136.1197 +2024/03/21 03:58:32 - mmengine - INFO - Epoch(train) [53][750/925] lr: 7.3775e-05 eta: 3:29:45 time: 0.5021 data_time: 0.0026 memory: 7935 grad_norm: 779.3407 loss: 386.7961 loss_cls: 127.2545 loss_bbox: 121.8107 loss_dfl: 137.7309 +2024/03/21 03:58:57 - mmengine - INFO - Epoch(train) [53][800/925] lr: 7.3775e-05 eta: 3:29:20 time: 0.5010 data_time: 0.0025 memory: 8069 grad_norm: 804.4116 loss: 386.6966 loss_cls: 125.1850 loss_bbox: 123.4546 loss_dfl: 138.0570 +2024/03/21 03:59:23 - mmengine - INFO - Epoch(train) [53][850/925] lr: 7.3775e-05 eta: 3:28:55 time: 0.5119 data_time: 0.0025 memory: 7829 grad_norm: 785.1558 loss: 387.6428 loss_cls: 128.8004 loss_bbox: 120.3035 loss_dfl: 138.5389 +2024/03/21 03:59:48 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 03:59:48 - mmengine - INFO - Epoch(train) [53][900/925] lr: 7.3775e-05 eta: 3:28:30 time: 0.5037 data_time: 0.0025 memory: 8202 grad_norm: 742.3408 loss: 378.6989 loss_cls: 125.4531 loss_bbox: 117.6386 loss_dfl: 135.6072 +2024/03/21 04:00:01 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:00:30 - mmengine - INFO - Epoch(train) [54][ 50/925] lr: 7.1300e-05 eta: 3:27:54 time: 0.5703 data_time: 0.0551 memory: 7922 grad_norm: 739.3596 loss: 380.3100 loss_cls: 124.4050 loss_bbox: 118.8266 loss_dfl: 137.0784 +2024/03/21 04:00:54 - mmengine - INFO - Epoch(train) [54][100/925] lr: 7.1300e-05 eta: 3:27:29 time: 0.4869 data_time: 0.0024 memory: 7749 grad_norm: 735.7927 loss: 384.1292 loss_cls: 127.5013 loss_bbox: 118.7382 loss_dfl: 137.8897 +2024/03/21 04:01:20 - mmengine - INFO - Epoch(train) [54][150/925] lr: 7.1300e-05 eta: 3:27:04 time: 0.5207 data_time: 0.0024 memory: 7935 grad_norm: 783.5391 loss: 384.8170 loss_cls: 127.1585 loss_bbox: 120.6565 loss_dfl: 137.0020 +2024/03/21 04:01:45 - mmengine - INFO - Epoch(train) [54][200/925] lr: 7.1300e-05 eta: 3:26:39 time: 0.5092 data_time: 0.0024 memory: 7975 grad_norm: 767.8302 loss: 387.8641 loss_cls: 128.0794 loss_bbox: 121.6739 loss_dfl: 138.1108 +2024/03/21 04:02:10 - mmengine - INFO - Epoch(train) [54][250/925] lr: 7.1300e-05 eta: 3:26:14 time: 0.4937 data_time: 0.0024 memory: 7895 grad_norm: 820.1827 loss: 383.5549 loss_cls: 125.7845 loss_bbox: 121.5187 loss_dfl: 136.2517 +2024/03/21 04:02:37 - mmengine - INFO - Epoch(train) [54][300/925] lr: 7.1300e-05 eta: 3:25:50 time: 0.5266 data_time: 0.0025 memory: 7962 grad_norm: 757.3927 loss: 376.9520 loss_cls: 122.1875 loss_bbox: 118.5885 loss_dfl: 136.1760 +2024/03/21 04:03:02 - mmengine - INFO - Epoch(train) [54][350/925] lr: 7.1300e-05 eta: 3:25:25 time: 0.5143 data_time: 0.0025 memory: 7975 grad_norm: inf loss: 382.3894 loss_cls: 124.3017 loss_bbox: 120.5889 loss_dfl: 137.4988 +2024/03/21 04:03:27 - mmengine - INFO - Epoch(train) [54][400/925] lr: 7.1300e-05 eta: 3:25:00 time: 0.4978 data_time: 0.0026 memory: 7922 grad_norm: 774.3900 loss: 381.2880 loss_cls: 125.8703 loss_bbox: 119.8943 loss_dfl: 135.5234 +2024/03/21 04:03:53 - mmengine - INFO - Epoch(train) [54][450/925] lr: 7.1300e-05 eta: 3:24:35 time: 0.5216 data_time: 0.0025 memory: 8082 grad_norm: 751.8727 loss: 383.9833 loss_cls: 125.5020 loss_bbox: 120.6551 loss_dfl: 137.8262 +2024/03/21 04:04:18 - mmengine - INFO - Epoch(train) [54][500/925] lr: 7.1300e-05 eta: 3:24:10 time: 0.4915 data_time: 0.0024 memory: 7789 grad_norm: 846.4162 loss: 380.0617 loss_cls: 122.7355 loss_bbox: 119.3232 loss_dfl: 138.0030 +2024/03/21 04:04:44 - mmengine - INFO - Epoch(train) [54][550/925] lr: 7.1300e-05 eta: 3:23:46 time: 0.5162 data_time: 0.0026 memory: 8015 grad_norm: 740.0530 loss: 382.0527 loss_cls: 126.2082 loss_bbox: 119.4157 loss_dfl: 136.4288 +2024/03/21 04:05:10 - mmengine - INFO - Epoch(train) [54][600/925] lr: 7.1300e-05 eta: 3:23:21 time: 0.5145 data_time: 0.0025 memory: 8015 grad_norm: 728.3030 loss: 387.7459 loss_cls: 127.3099 loss_bbox: 122.7443 loss_dfl: 137.6917 +2024/03/21 04:05:35 - mmengine - INFO - Epoch(train) [54][650/925] lr: 7.1300e-05 eta: 3:22:56 time: 0.4996 data_time: 0.0025 memory: 8189 grad_norm: 775.9169 loss: 386.0106 loss_cls: 125.8825 loss_bbox: 122.2382 loss_dfl: 137.8898 +2024/03/21 04:06:00 - mmengine - INFO - Epoch(train) [54][700/925] lr: 7.1300e-05 eta: 3:22:31 time: 0.5150 data_time: 0.0027 memory: 7922 grad_norm: 772.2092 loss: 383.9883 loss_cls: 125.3302 loss_bbox: 122.4699 loss_dfl: 136.1882 +2024/03/21 04:06:25 - mmengine - INFO - Epoch(train) [54][750/925] lr: 7.1300e-05 eta: 3:22:06 time: 0.4976 data_time: 0.0026 memory: 7935 grad_norm: 729.8979 loss: 384.1833 loss_cls: 125.8100 loss_bbox: 120.2732 loss_dfl: 138.1002 +2024/03/21 04:06:51 - mmengine - INFO - Epoch(train) [54][800/925] lr: 7.1300e-05 eta: 3:21:41 time: 0.5115 data_time: 0.0026 memory: 8015 grad_norm: 769.2466 loss: 380.1903 loss_cls: 124.0432 loss_bbox: 119.6865 loss_dfl: 136.4605 +2024/03/21 04:07:16 - mmengine - INFO - Epoch(train) [54][850/925] lr: 7.1300e-05 eta: 3:21:17 time: 0.5103 data_time: 0.0025 memory: 7949 grad_norm: 717.5710 loss: 379.8913 loss_cls: 122.8904 loss_bbox: 120.3180 loss_dfl: 136.6829 +2024/03/21 04:07:42 - mmengine - INFO - Epoch(train) [54][900/925] lr: 7.1300e-05 eta: 3:20:52 time: 0.5012 data_time: 0.0025 memory: 7989 grad_norm: 727.8944 loss: 388.3359 loss_cls: 127.9708 loss_bbox: 122.7082 loss_dfl: 137.6568 +2024/03/21 04:07:54 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:08:22 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:08:22 - mmengine - INFO - Epoch(train) [55][ 50/925] lr: 6.8825e-05 eta: 3:20:15 time: 0.5537 data_time: 0.0608 memory: 8042 grad_norm: 795.2571 loss: 385.4494 loss_cls: 126.0776 loss_bbox: 122.1070 loss_dfl: 137.2648 +2024/03/21 04:08:48 - mmengine - INFO - Epoch(train) [55][100/925] lr: 6.8825e-05 eta: 3:19:50 time: 0.5174 data_time: 0.0025 memory: 8202 grad_norm: 830.5080 loss: 387.2807 loss_cls: 127.3395 loss_bbox: 122.3304 loss_dfl: 137.6108 +2024/03/21 04:09:13 - mmengine - INFO - Epoch(train) [55][150/925] lr: 6.8825e-05 eta: 3:19:25 time: 0.4965 data_time: 0.0022 memory: 7949 grad_norm: 749.5028 loss: 381.9158 loss_cls: 126.0031 loss_bbox: 119.0747 loss_dfl: 136.8380 +2024/03/21 04:09:39 - mmengine - INFO - Epoch(train) [55][200/925] lr: 6.8825e-05 eta: 3:19:01 time: 0.5212 data_time: 0.0024 memory: 7909 grad_norm: 785.8272 loss: 380.4079 loss_cls: 124.3555 loss_bbox: 120.3003 loss_dfl: 135.7521 +2024/03/21 04:10:04 - mmengine - INFO - Epoch(train) [55][250/925] lr: 6.8825e-05 eta: 3:18:36 time: 0.5083 data_time: 0.0024 memory: 8029 grad_norm: 738.7502 loss: 378.8705 loss_cls: 121.9022 loss_bbox: 120.1525 loss_dfl: 136.8159 +2024/03/21 04:10:30 - mmengine - INFO - Epoch(train) [55][300/925] lr: 6.8825e-05 eta: 3:18:11 time: 0.5084 data_time: 0.0026 memory: 7842 grad_norm: 722.6067 loss: 386.0696 loss_cls: 127.5407 loss_bbox: 120.1968 loss_dfl: 138.3321 +2024/03/21 04:10:56 - mmengine - INFO - Epoch(train) [55][350/925] lr: 6.8825e-05 eta: 3:17:46 time: 0.5215 data_time: 0.0023 memory: 8029 grad_norm: 722.6193 loss: 378.0704 loss_cls: 122.5511 loss_bbox: 118.4696 loss_dfl: 137.0498 +2024/03/21 04:11:21 - mmengine - INFO - Epoch(train) [55][400/925] lr: 6.8825e-05 eta: 3:17:22 time: 0.5039 data_time: 0.0026 memory: 7709 grad_norm: 824.6521 loss: 383.1391 loss_cls: 124.4818 loss_bbox: 120.5087 loss_dfl: 138.1486 +2024/03/21 04:11:47 - mmengine - INFO - Epoch(train) [55][450/925] lr: 6.8825e-05 eta: 3:16:57 time: 0.5208 data_time: 0.0023 memory: 7935 grad_norm: 712.8522 loss: 383.8968 loss_cls: 126.2953 loss_bbox: 120.3956 loss_dfl: 137.2059 +2024/03/21 04:12:13 - mmengine - INFO - Epoch(train) [55][500/925] lr: 6.8825e-05 eta: 3:16:32 time: 0.5244 data_time: 0.0025 memory: 7949 grad_norm: 752.5707 loss: 384.6536 loss_cls: 125.8132 loss_bbox: 121.2029 loss_dfl: 137.6375 +2024/03/21 04:12:38 - mmengine - INFO - Epoch(train) [55][550/925] lr: 6.8825e-05 eta: 3:16:07 time: 0.5022 data_time: 0.0027 memory: 8122 grad_norm: 717.8978 loss: 376.5565 loss_cls: 122.4943 loss_bbox: 117.8300 loss_dfl: 136.2322 +2024/03/21 04:13:04 - mmengine - INFO - Epoch(train) [55][600/925] lr: 6.8825e-05 eta: 3:15:43 time: 0.5145 data_time: 0.0025 memory: 8069 grad_norm: 740.2754 loss: 380.7307 loss_cls: 124.4456 loss_bbox: 119.4330 loss_dfl: 136.8520 +2024/03/21 04:13:30 - mmengine - INFO - Epoch(train) [55][650/925] lr: 6.8825e-05 eta: 3:15:18 time: 0.5076 data_time: 0.0025 memory: 8109 grad_norm: 771.9398 loss: 384.0490 loss_cls: 127.3659 loss_bbox: 119.9079 loss_dfl: 136.7752 +2024/03/21 04:13:55 - mmengine - INFO - Epoch(train) [55][700/925] lr: 6.8825e-05 eta: 3:14:53 time: 0.5010 data_time: 0.0025 memory: 7829 grad_norm: 761.9262 loss: 379.0506 loss_cls: 122.3660 loss_bbox: 119.6764 loss_dfl: 137.0081 +2024/03/21 04:14:21 - mmengine - INFO - Epoch(train) [55][750/925] lr: 6.8825e-05 eta: 3:14:28 time: 0.5195 data_time: 0.0026 memory: 8002 grad_norm: 736.7923 loss: 385.1835 loss_cls: 126.4464 loss_bbox: 121.4277 loss_dfl: 137.3094 +2024/03/21 04:14:46 - mmengine - INFO - Epoch(train) [55][800/925] lr: 6.8825e-05 eta: 3:14:03 time: 0.5025 data_time: 0.0025 memory: 8109 grad_norm: 818.7670 loss: 382.0217 loss_cls: 124.3644 loss_bbox: 120.8654 loss_dfl: 136.7919 +2024/03/21 04:15:12 - mmengine - INFO - Epoch(train) [55][850/925] lr: 6.8825e-05 eta: 3:13:39 time: 0.5177 data_time: 0.0027 memory: 7882 grad_norm: 747.1270 loss: 384.0103 loss_cls: 127.3874 loss_bbox: 119.2954 loss_dfl: 137.3275 +2024/03/21 04:15:38 - mmengine - INFO - Epoch(train) [55][900/925] lr: 6.8825e-05 eta: 3:13:14 time: 0.5198 data_time: 0.0026 memory: 8109 grad_norm: 755.7506 loss: 378.4787 loss_cls: 122.8973 loss_bbox: 119.0937 loss_dfl: 136.4877 +2024/03/21 04:15:50 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:15:50 - mmengine - INFO - Saving checkpoint at 55 epochs +2024/03/21 04:15:59 - mmengine - INFO - Epoch(val) [55][ 50/625] eta: 0:00:20 time: 0.0359 data_time: 0.0008 memory: 7642 +2024/03/21 04:16:01 - mmengine - INFO - Epoch(val) [55][100/625] eta: 0:00:18 time: 0.0356 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:04 - mmengine - INFO - Epoch(val) [55][150/625] eta: 0:00:21 time: 0.0612 data_time: 0.0266 memory: 1244 +2024/03/21 04:16:06 - mmengine - INFO - Epoch(val) [55][200/625] eta: 0:00:17 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:07 - mmengine - INFO - Epoch(val) [55][250/625] eta: 0:00:15 time: 0.0366 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:09 - mmengine - INFO - Epoch(val) [55][300/625] eta: 0:00:13 time: 0.0374 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:11 - mmengine - INFO - Epoch(val) [55][350/625] eta: 0:00:11 time: 0.0375 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:13 - mmengine - INFO - Epoch(val) [55][400/625] eta: 0:00:08 time: 0.0378 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:15 - mmengine - INFO - Epoch(val) [55][450/625] eta: 0:00:06 time: 0.0344 data_time: 0.0003 memory: 1244 +2024/03/21 04:16:16 - mmengine - INFO - Epoch(val) [55][500/625] eta: 0:00:04 time: 0.0286 data_time: 0.0002 memory: 1244 +2024/03/21 04:16:18 - mmengine - INFO - Epoch(val) [55][550/625] eta: 0:00:02 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 04:16:19 - mmengine - INFO - Epoch(val) [55][600/625] eta: 0:00:00 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 04:16:31 - mmengine - INFO - Evaluating bbox... +2024/03/21 04:17:34 - mmengine - INFO - bbox_mAP_copypaste: 0.505 0.671 0.549 0.325 0.556 0.667 +2024/03/21 04:17:35 - mmengine - INFO - Epoch(val) [55][625/625] coco/bbox_mAP: 0.5050 coco/bbox_mAP_50: 0.6710 coco/bbox_mAP_75: 0.5490 coco/bbox_mAP_s: 0.3250 coco/bbox_mAP_m: 0.5560 coco/bbox_mAP_l: 0.6670 data_time: 0.0002 time: 0.0278 +2024/03/21 04:18:02 - mmengine - INFO - Epoch(train) [56][ 50/925] lr: 6.6350e-05 eta: 3:12:37 time: 0.5460 data_time: 0.0530 memory: 7962 grad_norm: 716.2074 loss: 380.1405 loss_cls: 123.1933 loss_bbox: 120.6172 loss_dfl: 136.3299 +2024/03/21 04:18:27 - mmengine - INFO - Epoch(train) [56][100/925] lr: 6.6350e-05 eta: 3:12:12 time: 0.5019 data_time: 0.0028 memory: 7922 grad_norm: 750.6340 loss: 380.5048 loss_cls: 124.6232 loss_bbox: 119.4031 loss_dfl: 136.4785 +2024/03/21 04:18:41 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:18:53 - mmengine - INFO - Epoch(train) [56][150/925] lr: 6.6350e-05 eta: 3:11:47 time: 0.5060 data_time: 0.0025 memory: 7815 grad_norm: 735.8324 loss: 380.2576 loss_cls: 125.1907 loss_bbox: 117.7799 loss_dfl: 137.2869 +2024/03/21 04:19:17 - mmengine - INFO - Epoch(train) [56][200/925] lr: 6.6350e-05 eta: 3:11:22 time: 0.4923 data_time: 0.0027 memory: 8055 grad_norm: 709.6464 loss: 376.1686 loss_cls: 122.2596 loss_bbox: 118.7732 loss_dfl: 135.1358 +2024/03/21 04:19:43 - mmengine - INFO - Epoch(train) [56][250/925] lr: 6.6350e-05 eta: 3:10:57 time: 0.5058 data_time: 0.0025 memory: 7749 grad_norm: 738.4179 loss: 379.8168 loss_cls: 123.1737 loss_bbox: 119.6529 loss_dfl: 136.9902 +2024/03/21 04:20:08 - mmengine - INFO - Epoch(train) [56][300/925] lr: 6.6350e-05 eta: 3:10:32 time: 0.5069 data_time: 0.0027 memory: 8002 grad_norm: 731.3582 loss: 381.5489 loss_cls: 123.8345 loss_bbox: 120.4646 loss_dfl: 137.2499 +2024/03/21 04:20:34 - mmengine - INFO - Epoch(train) [56][350/925] lr: 6.6350e-05 eta: 3:10:08 time: 0.5185 data_time: 0.0024 memory: 7789 grad_norm: 738.5296 loss: 381.7094 loss_cls: 125.5244 loss_bbox: 119.4723 loss_dfl: 136.7126 +2024/03/21 04:21:00 - mmengine - INFO - Epoch(train) [56][400/925] lr: 6.6350e-05 eta: 3:09:43 time: 0.5140 data_time: 0.0024 memory: 8002 grad_norm: 828.3402 loss: 384.8110 loss_cls: 125.1645 loss_bbox: 121.6907 loss_dfl: 137.9558 +2024/03/21 04:21:25 - mmengine - INFO - Epoch(train) [56][450/925] lr: 6.6350e-05 eta: 3:09:18 time: 0.5066 data_time: 0.0027 memory: 7975 grad_norm: 767.9357 loss: 381.3652 loss_cls: 123.3544 loss_bbox: 120.7871 loss_dfl: 137.2236 +2024/03/21 04:21:51 - mmengine - INFO - Epoch(train) [56][500/925] lr: 6.6350e-05 eta: 3:08:53 time: 0.5183 data_time: 0.0026 memory: 8069 grad_norm: 753.5179 loss: 380.8593 loss_cls: 123.4304 loss_bbox: 120.6987 loss_dfl: 136.7302 +2024/03/21 04:22:17 - mmengine - INFO - Epoch(train) [56][550/925] lr: 6.6350e-05 eta: 3:08:29 time: 0.5148 data_time: 0.0024 memory: 7695 grad_norm: 841.0818 loss: 384.7517 loss_cls: 127.2394 loss_bbox: 119.9533 loss_dfl: 137.5589 +2024/03/21 04:22:42 - mmengine - INFO - Epoch(train) [56][600/925] lr: 6.6350e-05 eta: 3:08:03 time: 0.4964 data_time: 0.0027 memory: 8029 grad_norm: 765.7469 loss: 377.7909 loss_cls: 123.3882 loss_bbox: 117.9783 loss_dfl: 136.4245 +2024/03/21 04:23:08 - mmengine - INFO - Epoch(train) [56][650/925] lr: 6.6350e-05 eta: 3:07:39 time: 0.5224 data_time: 0.0023 memory: 8349 grad_norm: 751.8362 loss: 381.1550 loss_cls: 124.0769 loss_bbox: 120.7807 loss_dfl: 136.2974 +2024/03/21 04:23:33 - mmengine - INFO - Epoch(train) [56][700/925] lr: 6.6350e-05 eta: 3:07:14 time: 0.4990 data_time: 0.0025 memory: 7922 grad_norm: 756.5300 loss: 380.9160 loss_cls: 125.0614 loss_bbox: 119.5043 loss_dfl: 136.3503 +2024/03/21 04:23:58 - mmengine - INFO - Epoch(train) [56][750/925] lr: 6.6350e-05 eta: 3:06:49 time: 0.5032 data_time: 0.0027 memory: 7962 grad_norm: 754.8952 loss: 391.1916 loss_cls: 129.3812 loss_bbox: 122.1397 loss_dfl: 139.6707 +2024/03/21 04:24:24 - mmengine - INFO - Epoch(train) [56][800/925] lr: 6.6350e-05 eta: 3:06:24 time: 0.5190 data_time: 0.0026 memory: 7989 grad_norm: 715.5776 loss: 382.8866 loss_cls: 123.8562 loss_bbox: 121.6409 loss_dfl: 137.3895 +2024/03/21 04:24:49 - mmengine - INFO - Epoch(train) [56][850/925] lr: 6.6350e-05 eta: 3:05:59 time: 0.5042 data_time: 0.0026 memory: 8082 grad_norm: 772.1627 loss: 378.9415 loss_cls: 122.4968 loss_bbox: 119.1560 loss_dfl: 137.2887 +2024/03/21 04:25:15 - mmengine - INFO - Epoch(train) [56][900/925] lr: 6.6350e-05 eta: 3:05:34 time: 0.5145 data_time: 0.0020 memory: 7709 grad_norm: 780.8316 loss: 378.2452 loss_cls: 122.6742 loss_bbox: 119.4764 loss_dfl: 136.0946 +2024/03/21 04:25:27 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:25:56 - mmengine - INFO - Epoch(train) [57][ 50/925] lr: 6.3875e-05 eta: 3:04:58 time: 0.5624 data_time: 0.0541 memory: 7882 grad_norm: 749.9696 loss: 379.5584 loss_cls: 123.6049 loss_bbox: 119.3001 loss_dfl: 136.6534 +2024/03/21 04:26:21 - mmengine - INFO - Epoch(train) [57][100/925] lr: 6.3875e-05 eta: 3:04:33 time: 0.5055 data_time: 0.0024 memory: 8122 grad_norm: 781.7388 loss: 384.4364 loss_cls: 126.1402 loss_bbox: 121.5696 loss_dfl: 136.7266 +2024/03/21 04:26:47 - mmengine - INFO - Epoch(train) [57][150/925] lr: 6.3875e-05 eta: 3:04:08 time: 0.5181 data_time: 0.0027 memory: 7882 grad_norm: 784.0894 loss: 374.5120 loss_cls: 121.8434 loss_bbox: 117.9851 loss_dfl: 134.6834 +2024/03/21 04:27:12 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:27:12 - mmengine - INFO - Epoch(train) [57][200/925] lr: 6.3875e-05 eta: 3:03:43 time: 0.4930 data_time: 0.0027 memory: 8055 grad_norm: 796.3134 loss: 386.9976 loss_cls: 128.1637 loss_bbox: 120.7361 loss_dfl: 138.0978 +2024/03/21 04:27:38 - mmengine - INFO - Epoch(train) [57][250/925] lr: 6.3875e-05 eta: 3:03:18 time: 0.5155 data_time: 0.0028 memory: 7869 grad_norm: 751.8599 loss: 378.5231 loss_cls: 120.8198 loss_bbox: 120.6570 loss_dfl: 137.0464 +2024/03/21 04:28:03 - mmengine - INFO - Epoch(train) [57][300/925] lr: 6.3875e-05 eta: 3:02:53 time: 0.5067 data_time: 0.0027 memory: 8002 grad_norm: 753.4967 loss: 382.4208 loss_cls: 124.0726 loss_bbox: 120.8805 loss_dfl: 137.4677 +2024/03/21 04:28:27 - mmengine - INFO - Epoch(train) [57][350/925] lr: 6.3875e-05 eta: 3:02:28 time: 0.4848 data_time: 0.0024 memory: 8029 grad_norm: 771.1244 loss: 380.0189 loss_cls: 123.0661 loss_bbox: 120.2071 loss_dfl: 136.7457 +2024/03/21 04:28:53 - mmengine - INFO - Epoch(train) [57][400/925] lr: 6.3875e-05 eta: 3:02:03 time: 0.5203 data_time: 0.0025 memory: 7989 grad_norm: 725.6540 loss: 380.1072 loss_cls: 122.4934 loss_bbox: 121.0670 loss_dfl: 136.5468 +2024/03/21 04:29:19 - mmengine - INFO - Epoch(train) [57][450/925] lr: 6.3875e-05 eta: 3:01:38 time: 0.5070 data_time: 0.0027 memory: 8135 grad_norm: 800.6755 loss: 382.9994 loss_cls: 124.9828 loss_bbox: 120.6615 loss_dfl: 137.3550 +2024/03/21 04:29:43 - mmengine - INFO - Epoch(train) [57][500/925] lr: 6.3875e-05 eta: 3:01:13 time: 0.4873 data_time: 0.0024 memory: 7935 grad_norm: 729.3874 loss: 387.4415 loss_cls: 125.4746 loss_bbox: 124.1096 loss_dfl: 137.8572 +2024/03/21 04:30:09 - mmengine - INFO - Epoch(train) [57][550/925] lr: 6.3875e-05 eta: 3:00:48 time: 0.5151 data_time: 0.0026 memory: 8295 grad_norm: inf loss: 378.8771 loss_cls: 123.3506 loss_bbox: 120.3824 loss_dfl: 135.1441 +2024/03/21 04:30:34 - mmengine - INFO - Epoch(train) [57][600/925] lr: 6.3875e-05 eta: 3:00:23 time: 0.5031 data_time: 0.0028 memory: 8095 grad_norm: 774.7777 loss: 377.4792 loss_cls: 122.0044 loss_bbox: 118.9927 loss_dfl: 136.4821 +2024/03/21 04:30:59 - mmengine - INFO - Epoch(train) [57][650/925] lr: 6.3875e-05 eta: 2:59:58 time: 0.5054 data_time: 0.0024 memory: 7935 grad_norm: 732.3711 loss: 386.5270 loss_cls: 126.4490 loss_bbox: 122.2546 loss_dfl: 137.8234 +2024/03/21 04:31:25 - mmengine - INFO - Epoch(train) [57][700/925] lr: 6.3875e-05 eta: 2:59:34 time: 0.5189 data_time: 0.0027 memory: 7949 grad_norm: 727.1284 loss: 381.3394 loss_cls: 122.8870 loss_bbox: 121.0374 loss_dfl: 137.4150 +2024/03/21 04:31:50 - mmengine - INFO - Epoch(train) [57][750/925] lr: 6.3875e-05 eta: 2:59:09 time: 0.5020 data_time: 0.0026 memory: 8095 grad_norm: 757.9297 loss: 377.5022 loss_cls: 122.6521 loss_bbox: 118.7757 loss_dfl: 136.0745 +2024/03/21 04:32:16 - mmengine - INFO - Epoch(train) [57][800/925] lr: 6.3875e-05 eta: 2:58:44 time: 0.5068 data_time: 0.0025 memory: 7882 grad_norm: 817.8800 loss: 379.4770 loss_cls: 124.0504 loss_bbox: 118.6366 loss_dfl: 136.7900 +2024/03/21 04:32:41 - mmengine - INFO - Epoch(train) [57][850/925] lr: 6.3875e-05 eta: 2:58:19 time: 0.5107 data_time: 0.0027 memory: 7749 grad_norm: 731.0002 loss: 377.2832 loss_cls: 122.9068 loss_bbox: 118.7150 loss_dfl: 135.6614 +2024/03/21 04:33:06 - mmengine - INFO - Epoch(train) [57][900/925] lr: 6.3875e-05 eta: 2:57:53 time: 0.4901 data_time: 0.0026 memory: 7882 grad_norm: 763.9015 loss: 377.4974 loss_cls: 121.7991 loss_bbox: 120.2111 loss_dfl: 135.4872 +2024/03/21 04:33:18 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:33:48 - mmengine - INFO - Epoch(train) [58][ 50/925] lr: 6.1400e-05 eta: 2:57:17 time: 0.5798 data_time: 0.0610 memory: 7842 grad_norm: 752.5356 loss: 374.2862 loss_cls: 120.8143 loss_bbox: 117.1745 loss_dfl: 136.2973 +2024/03/21 04:34:13 - mmengine - INFO - Epoch(train) [58][100/925] lr: 6.1400e-05 eta: 2:56:52 time: 0.5070 data_time: 0.0025 memory: 8002 grad_norm: 771.3516 loss: 372.4482 loss_cls: 120.5618 loss_bbox: 117.3272 loss_dfl: 134.5592 +2024/03/21 04:34:39 - mmengine - INFO - Epoch(train) [58][150/925] lr: 6.1400e-05 eta: 2:56:28 time: 0.5129 data_time: 0.0027 memory: 7842 grad_norm: 739.3246 loss: 382.3839 loss_cls: 124.8535 loss_bbox: 120.6334 loss_dfl: 136.8971 +2024/03/21 04:35:05 - mmengine - INFO - Epoch(train) [58][200/925] lr: 6.1400e-05 eta: 2:56:03 time: 0.5139 data_time: 0.0026 memory: 7789 grad_norm: 767.9161 loss: 376.4268 loss_cls: 123.1012 loss_bbox: 117.9691 loss_dfl: 135.3566 +2024/03/21 04:35:30 - mmengine - INFO - Epoch(train) [58][250/925] lr: 6.1400e-05 eta: 2:55:38 time: 0.5022 data_time: 0.0027 memory: 7882 grad_norm: 761.9634 loss: 375.1048 loss_cls: 121.4457 loss_bbox: 118.1592 loss_dfl: 135.4999 +2024/03/21 04:35:42 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:35:55 - mmengine - INFO - Epoch(train) [58][300/925] lr: 6.1400e-05 eta: 2:55:13 time: 0.5132 data_time: 0.0026 memory: 7882 grad_norm: 784.0558 loss: 381.5890 loss_cls: 125.1914 loss_bbox: 120.4412 loss_dfl: 135.9564 +2024/03/21 04:36:21 - mmengine - INFO - Epoch(train) [58][350/925] lr: 6.1400e-05 eta: 2:54:48 time: 0.5111 data_time: 0.0025 memory: 7869 grad_norm: 748.1254 loss: 375.6487 loss_cls: 122.0966 loss_bbox: 117.6605 loss_dfl: 135.8916 +2024/03/21 04:36:46 - mmengine - INFO - Epoch(train) [58][400/925] lr: 6.1400e-05 eta: 2:54:23 time: 0.4998 data_time: 0.0026 memory: 8095 grad_norm: 754.5213 loss: 376.6331 loss_cls: 121.6493 loss_bbox: 119.2419 loss_dfl: 135.7420 +2024/03/21 04:37:12 - mmengine - INFO - Epoch(train) [58][450/925] lr: 6.1400e-05 eta: 2:53:58 time: 0.5225 data_time: 0.0025 memory: 8109 grad_norm: 797.6321 loss: 380.8279 loss_cls: 124.4239 loss_bbox: 120.4755 loss_dfl: 135.9286 +2024/03/21 04:37:38 - mmengine - INFO - Epoch(train) [58][500/925] lr: 6.1400e-05 eta: 2:53:34 time: 0.5164 data_time: 0.0027 memory: 8175 grad_norm: 794.1622 loss: 382.6924 loss_cls: 123.0782 loss_bbox: 121.6837 loss_dfl: 137.9305 +2024/03/21 04:38:04 - mmengine - INFO - Epoch(train) [58][550/925] lr: 6.1400e-05 eta: 2:53:09 time: 0.5097 data_time: 0.0027 memory: 7842 grad_norm: 742.0232 loss: 376.1874 loss_cls: 120.9880 loss_bbox: 119.2540 loss_dfl: 135.9454 +2024/03/21 04:38:30 - mmengine - INFO - Epoch(train) [58][600/925] lr: 6.1400e-05 eta: 2:52:44 time: 0.5223 data_time: 0.0024 memory: 8082 grad_norm: 830.7029 loss: 383.7641 loss_cls: 125.2394 loss_bbox: 121.9971 loss_dfl: 136.5276 +2024/03/21 04:38:55 - mmengine - INFO - Epoch(train) [58][650/925] lr: 6.1400e-05 eta: 2:52:19 time: 0.5022 data_time: 0.0026 memory: 7749 grad_norm: 811.5356 loss: 384.8694 loss_cls: 125.4567 loss_bbox: 122.6404 loss_dfl: 136.7723 +2024/03/21 04:39:21 - mmengine - INFO - Epoch(train) [58][700/925] lr: 6.1400e-05 eta: 2:51:54 time: 0.5178 data_time: 0.0026 memory: 7935 grad_norm: 772.9931 loss: 383.9155 loss_cls: 125.0610 loss_bbox: 121.3082 loss_dfl: 137.5462 +2024/03/21 04:39:47 - mmengine - INFO - Epoch(train) [58][750/925] lr: 6.1400e-05 eta: 2:51:29 time: 0.5189 data_time: 0.0026 memory: 8175 grad_norm: 751.5696 loss: 384.0556 loss_cls: 126.3766 loss_bbox: 120.1320 loss_dfl: 137.5470 +2024/03/21 04:40:12 - mmengine - INFO - Epoch(train) [58][800/925] lr: 6.1400e-05 eta: 2:51:05 time: 0.5060 data_time: 0.0026 memory: 7709 grad_norm: 820.4459 loss: 372.7141 loss_cls: 119.3852 loss_bbox: 116.5436 loss_dfl: 136.7853 +2024/03/21 04:40:38 - mmengine - INFO - Epoch(train) [58][850/925] lr: 6.1400e-05 eta: 2:50:40 time: 0.5185 data_time: 0.0026 memory: 7682 grad_norm: 761.9625 loss: 379.7217 loss_cls: 123.4410 loss_bbox: 119.8600 loss_dfl: 136.4206 +2024/03/21 04:41:04 - mmengine - INFO - Epoch(train) [58][900/925] lr: 6.1400e-05 eta: 2:50:15 time: 0.5127 data_time: 0.0026 memory: 8002 grad_norm: 744.0094 loss: 377.9841 loss_cls: 122.5523 loss_bbox: 119.2860 loss_dfl: 136.1458 +2024/03/21 04:41:16 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:41:45 - mmengine - INFO - Epoch(train) [59][ 50/925] lr: 5.8925e-05 eta: 2:49:39 time: 0.5781 data_time: 0.0653 memory: 8095 grad_norm: 760.1351 loss: 379.9907 loss_cls: 122.9723 loss_bbox: 120.8229 loss_dfl: 136.1955 +2024/03/21 04:42:10 - mmengine - INFO - Epoch(train) [59][100/925] lr: 5.8925e-05 eta: 2:49:14 time: 0.5043 data_time: 0.0025 memory: 8002 grad_norm: 773.2383 loss: 383.7137 loss_cls: 126.0631 loss_bbox: 119.8780 loss_dfl: 137.7726 +2024/03/21 04:42:36 - mmengine - INFO - Epoch(train) [59][150/925] lr: 5.8925e-05 eta: 2:48:48 time: 0.4998 data_time: 0.0025 memory: 7895 grad_norm: 766.3275 loss: 376.7857 loss_cls: 121.8415 loss_bbox: 118.4063 loss_dfl: 136.5379 +2024/03/21 04:43:02 - mmengine - INFO - Epoch(train) [59][200/925] lr: 5.8925e-05 eta: 2:48:24 time: 0.5275 data_time: 0.0027 memory: 7829 grad_norm: 798.3293 loss: 371.0294 loss_cls: 118.6709 loss_bbox: 117.0479 loss_dfl: 135.3105 +2024/03/21 04:43:27 - mmengine - INFO - Epoch(train) [59][250/925] lr: 5.8925e-05 eta: 2:47:59 time: 0.4948 data_time: 0.0026 memory: 7789 grad_norm: 772.5200 loss: 375.7035 loss_cls: 122.2861 loss_bbox: 117.0028 loss_dfl: 136.4146 +2024/03/21 04:43:52 - mmengine - INFO - Epoch(train) [59][300/925] lr: 5.8925e-05 eta: 2:47:34 time: 0.5017 data_time: 0.0025 memory: 7695 grad_norm: 758.0521 loss: 377.6829 loss_cls: 123.2220 loss_bbox: 117.0601 loss_dfl: 137.4008 +2024/03/21 04:44:17 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:44:17 - mmengine - INFO - Epoch(train) [59][350/925] lr: 5.8925e-05 eta: 2:47:09 time: 0.5083 data_time: 0.0024 memory: 8015 grad_norm: 748.0379 loss: 380.7524 loss_cls: 123.5387 loss_bbox: 121.2646 loss_dfl: 135.9490 +2024/03/21 04:44:43 - mmengine - INFO - Epoch(train) [59][400/925] lr: 5.8925e-05 eta: 2:46:44 time: 0.5122 data_time: 0.0028 memory: 7869 grad_norm: 774.0641 loss: 379.6063 loss_cls: 124.2465 loss_bbox: 118.6564 loss_dfl: 136.7034 +2024/03/21 04:45:09 - mmengine - INFO - Epoch(train) [59][450/925] lr: 5.8925e-05 eta: 2:46:19 time: 0.5142 data_time: 0.0026 memory: 8069 grad_norm: 787.2559 loss: 376.7323 loss_cls: 122.4613 loss_bbox: 118.1532 loss_dfl: 136.1177 +2024/03/21 04:45:35 - mmengine - INFO - Epoch(train) [59][500/925] lr: 5.8925e-05 eta: 2:45:54 time: 0.5170 data_time: 0.0026 memory: 8055 grad_norm: 715.1409 loss: 381.6899 loss_cls: 124.1815 loss_bbox: 119.9534 loss_dfl: 137.5551 +2024/03/21 04:46:00 - mmengine - INFO - Epoch(train) [59][550/925] lr: 5.8925e-05 eta: 2:45:29 time: 0.4997 data_time: 0.0026 memory: 7775 grad_norm: 800.9976 loss: 384.2288 loss_cls: 125.2668 loss_bbox: 122.0633 loss_dfl: 136.8986 +2024/03/21 04:46:25 - mmengine - INFO - Epoch(train) [59][600/925] lr: 5.8925e-05 eta: 2:45:04 time: 0.5173 data_time: 0.0026 memory: 8015 grad_norm: 766.0256 loss: 378.6754 loss_cls: 120.8468 loss_bbox: 121.7680 loss_dfl: 136.0606 +2024/03/21 04:46:51 - mmengine - INFO - Epoch(train) [59][650/925] lr: 5.8925e-05 eta: 2:44:39 time: 0.5005 data_time: 0.0026 memory: 8082 grad_norm: 734.1468 loss: 381.2193 loss_cls: 124.0104 loss_bbox: 119.2132 loss_dfl: 137.9956 +2024/03/21 04:47:16 - mmengine - INFO - Epoch(train) [59][700/925] lr: 5.8925e-05 eta: 2:44:14 time: 0.5115 data_time: 0.0026 memory: 7909 grad_norm: 807.2931 loss: 378.5055 loss_cls: 122.7519 loss_bbox: 120.2103 loss_dfl: 135.5433 +2024/03/21 04:47:43 - mmengine - INFO - Epoch(train) [59][750/925] lr: 5.8925e-05 eta: 2:43:50 time: 0.5291 data_time: 0.0024 memory: 7829 grad_norm: 767.2541 loss: 382.2315 loss_cls: 125.5958 loss_bbox: 119.5780 loss_dfl: 137.0578 +2024/03/21 04:48:08 - mmengine - INFO - Epoch(train) [59][800/925] lr: 5.8925e-05 eta: 2:43:25 time: 0.4983 data_time: 0.0024 memory: 7815 grad_norm: 762.5627 loss: 380.8602 loss_cls: 123.2741 loss_bbox: 120.9134 loss_dfl: 136.6728 +2024/03/21 04:48:33 - mmengine - INFO - Epoch(train) [59][850/925] lr: 5.8925e-05 eta: 2:43:00 time: 0.5058 data_time: 0.0027 memory: 8069 grad_norm: inf loss: 378.7161 loss_cls: 121.9953 loss_bbox: 119.8342 loss_dfl: 136.8866 +2024/03/21 04:48:59 - mmengine - INFO - Epoch(train) [59][900/925] lr: 5.8925e-05 eta: 2:42:35 time: 0.5213 data_time: 0.0025 memory: 7802 grad_norm: 710.2905 loss: 384.8532 loss_cls: 125.6980 loss_bbox: 122.3426 loss_dfl: 136.8126 +2024/03/21 04:49:11 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:49:40 - mmengine - INFO - Epoch(train) [60][ 50/925] lr: 5.6450e-05 eta: 2:41:58 time: 0.5633 data_time: 0.0602 memory: 8015 grad_norm: 816.2978 loss: 371.2460 loss_cls: 119.5919 loss_bbox: 116.8766 loss_dfl: 134.7775 +2024/03/21 04:50:06 - mmengine - INFO - Epoch(train) [60][100/925] lr: 5.6450e-05 eta: 2:41:33 time: 0.5215 data_time: 0.0025 memory: 7815 grad_norm: 763.8559 loss: 375.3416 loss_cls: 122.6577 loss_bbox: 116.8749 loss_dfl: 135.8090 +2024/03/21 04:50:31 - mmengine - INFO - Epoch(train) [60][150/925] lr: 5.6450e-05 eta: 2:41:08 time: 0.4976 data_time: 0.0026 memory: 8082 grad_norm: 767.6459 loss: 382.7287 loss_cls: 126.7091 loss_bbox: 119.2086 loss_dfl: 136.8110 +2024/03/21 04:50:56 - mmengine - INFO - Epoch(train) [60][200/925] lr: 5.6450e-05 eta: 2:40:43 time: 0.5018 data_time: 0.0024 memory: 8175 grad_norm: 737.1409 loss: 376.3321 loss_cls: 122.9096 loss_bbox: 117.8585 loss_dfl: 135.5640 +2024/03/21 04:51:22 - mmengine - INFO - Epoch(train) [60][250/925] lr: 5.6450e-05 eta: 2:40:18 time: 0.5271 data_time: 0.0026 memory: 7935 grad_norm: 729.6001 loss: 373.3304 loss_cls: 119.3156 loss_bbox: 118.5071 loss_dfl: 135.5078 +2024/03/21 04:51:47 - mmengine - INFO - Epoch(train) [60][300/925] lr: 5.6450e-05 eta: 2:39:53 time: 0.4909 data_time: 0.0026 memory: 8029 grad_norm: 785.0724 loss: 381.0719 loss_cls: 124.2892 loss_bbox: 120.0453 loss_dfl: 136.7374 +2024/03/21 04:52:12 - mmengine - INFO - Epoch(train) [60][350/925] lr: 5.6450e-05 eta: 2:39:28 time: 0.5087 data_time: 0.0028 memory: 7882 grad_norm: 734.5129 loss: 384.6622 loss_cls: 125.5596 loss_bbox: 122.0606 loss_dfl: 137.0420 +2024/03/21 04:52:38 - mmengine - INFO - Epoch(train) [60][400/925] lr: 5.6450e-05 eta: 2:39:03 time: 0.5158 data_time: 0.0027 memory: 7949 grad_norm: 784.6561 loss: 381.0497 loss_cls: 123.8077 loss_bbox: 120.8655 loss_dfl: 136.3765 +2024/03/21 04:52:50 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:53:03 - mmengine - INFO - Epoch(train) [60][450/925] lr: 5.6450e-05 eta: 2:38:38 time: 0.4934 data_time: 0.0024 memory: 7842 grad_norm: 718.4190 loss: 373.3493 loss_cls: 120.1256 loss_bbox: 117.4402 loss_dfl: 135.7835 +2024/03/21 04:53:28 - mmengine - INFO - Epoch(train) [60][500/925] lr: 5.6450e-05 eta: 2:38:13 time: 0.5116 data_time: 0.0024 memory: 7815 grad_norm: 765.1705 loss: 374.5968 loss_cls: 121.4607 loss_bbox: 116.9066 loss_dfl: 136.2295 +2024/03/21 04:53:53 - mmengine - INFO - Epoch(train) [60][550/925] lr: 5.6450e-05 eta: 2:37:48 time: 0.5038 data_time: 0.0025 memory: 8055 grad_norm: 807.8256 loss: 381.8204 loss_cls: 124.3855 loss_bbox: 120.7660 loss_dfl: 136.6689 +2024/03/21 04:54:18 - mmengine - INFO - Epoch(train) [60][600/925] lr: 5.6450e-05 eta: 2:37:23 time: 0.4960 data_time: 0.0027 memory: 8215 grad_norm: 785.4178 loss: 379.2734 loss_cls: 123.7118 loss_bbox: 119.1997 loss_dfl: 136.3619 +2024/03/21 04:54:44 - mmengine - INFO - Epoch(train) [60][650/925] lr: 5.6450e-05 eta: 2:36:58 time: 0.5165 data_time: 0.0026 memory: 7829 grad_norm: 760.5798 loss: 372.7807 loss_cls: 120.9313 loss_bbox: 116.7727 loss_dfl: 135.0767 +2024/03/21 04:55:09 - mmengine - INFO - Epoch(train) [60][700/925] lr: 5.6450e-05 eta: 2:36:33 time: 0.4968 data_time: 0.0023 memory: 7882 grad_norm: 735.1979 loss: 382.4731 loss_cls: 125.0196 loss_bbox: 120.0539 loss_dfl: 137.3997 +2024/03/21 04:55:35 - mmengine - INFO - Epoch(train) [60][750/925] lr: 5.6450e-05 eta: 2:36:08 time: 0.5095 data_time: 0.0024 memory: 8095 grad_norm: 811.5676 loss: 377.7087 loss_cls: 122.4480 loss_bbox: 119.5971 loss_dfl: 135.6637 +2024/03/21 04:56:00 - mmengine - INFO - Epoch(train) [60][800/925] lr: 5.6450e-05 eta: 2:35:43 time: 0.5030 data_time: 0.0027 memory: 8029 grad_norm: 754.4194 loss: 376.6080 loss_cls: 121.6892 loss_bbox: 119.1928 loss_dfl: 135.7260 +2024/03/21 04:56:24 - mmengine - INFO - Epoch(train) [60][850/925] lr: 5.6450e-05 eta: 2:35:18 time: 0.4923 data_time: 0.0026 memory: 7829 grad_norm: 764.8738 loss: 374.5022 loss_cls: 120.3677 loss_bbox: 118.3818 loss_dfl: 135.7527 +2024/03/21 04:56:51 - mmengine - INFO - Epoch(train) [60][900/925] lr: 5.6450e-05 eta: 2:34:53 time: 0.5223 data_time: 0.0025 memory: 7962 grad_norm: 800.4545 loss: 378.1650 loss_cls: 122.4713 loss_bbox: 119.8430 loss_dfl: 135.8507 +2024/03/21 04:57:02 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 04:57:03 - mmengine - INFO - Saving checkpoint at 60 epochs +2024/03/21 04:57:12 - mmengine - INFO - Epoch(val) [60][ 50/625] eta: 0:00:20 time: 0.0349 data_time: 0.0008 memory: 7629 +2024/03/21 04:57:13 - mmengine - INFO - Epoch(val) [60][100/625] eta: 0:00:18 time: 0.0366 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:15 - mmengine - INFO - Epoch(val) [60][150/625] eta: 0:00:16 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:17 - mmengine - INFO - Epoch(val) [60][200/625] eta: 0:00:15 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:19 - mmengine - INFO - Epoch(val) [60][250/625] eta: 0:00:13 time: 0.0384 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:21 - mmengine - INFO - Epoch(val) [60][300/625] eta: 0:00:11 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:23 - mmengine - INFO - Epoch(val) [60][350/625] eta: 0:00:09 time: 0.0361 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:24 - mmengine - INFO - Epoch(val) [60][400/625] eta: 0:00:08 time: 0.0353 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:26 - mmengine - INFO - Epoch(val) [60][450/625] eta: 0:00:06 time: 0.0341 data_time: 0.0003 memory: 1244 +2024/03/21 04:57:27 - mmengine - INFO - Epoch(val) [60][500/625] eta: 0:00:04 time: 0.0282 data_time: 0.0002 memory: 1244 +2024/03/21 04:57:29 - mmengine - INFO - Epoch(val) [60][550/625] eta: 0:00:02 time: 0.0290 data_time: 0.0002 memory: 1244 +2024/03/21 04:57:30 - mmengine - INFO - Epoch(val) [60][600/625] eta: 0:00:00 time: 0.0290 data_time: 0.0002 memory: 1244 +2024/03/21 04:57:42 - mmengine - INFO - Evaluating bbox... +2024/03/21 04:58:52 - mmengine - INFO - bbox_mAP_copypaste: 0.505 0.672 0.551 0.328 0.557 0.668 +2024/03/21 04:58:54 - mmengine - INFO - Epoch(val) [60][625/625] coco/bbox_mAP: 0.5050 coco/bbox_mAP_50: 0.6720 coco/bbox_mAP_75: 0.5510 coco/bbox_mAP_s: 0.3280 coco/bbox_mAP_m: 0.5570 coco/bbox_mAP_l: 0.6680 data_time: 0.0002 time: 0.0281 +2024/03/21 04:59:22 - mmengine - INFO - Epoch(train) [61][ 50/925] lr: 5.3975e-05 eta: 2:34:16 time: 0.5541 data_time: 0.0616 memory: 7975 grad_norm: 754.9958 loss: 375.8319 loss_cls: 118.9004 loss_bbox: 120.5548 loss_dfl: 136.3768 +2024/03/21 04:59:46 - mmengine - INFO - Epoch(train) [61][100/925] lr: 5.3975e-05 eta: 2:33:51 time: 0.4794 data_time: 0.0025 memory: 7775 grad_norm: 749.7524 loss: 380.6425 loss_cls: 122.9398 loss_bbox: 120.3499 loss_dfl: 137.3528 +2024/03/21 05:00:11 - mmengine - INFO - Epoch(train) [61][150/925] lr: 5.3975e-05 eta: 2:33:26 time: 0.5119 data_time: 0.0024 memory: 7762 grad_norm: 794.0902 loss: 377.5552 loss_cls: 123.9794 loss_bbox: 117.4503 loss_dfl: 136.1255 +2024/03/21 05:00:36 - mmengine - INFO - Epoch(train) [61][200/925] lr: 5.3975e-05 eta: 2:33:00 time: 0.4858 data_time: 0.0025 memory: 7895 grad_norm: 784.0766 loss: 390.5653 loss_cls: 128.2212 loss_bbox: 123.7944 loss_dfl: 138.5497 +2024/03/21 05:01:00 - mmengine - INFO - Epoch(train) [61][250/925] lr: 5.3975e-05 eta: 2:32:35 time: 0.4905 data_time: 0.0026 memory: 8042 grad_norm: 744.9017 loss: 384.2316 loss_cls: 124.4328 loss_bbox: 122.1123 loss_dfl: 137.6865 +2024/03/21 05:01:26 - mmengine - INFO - Epoch(train) [61][300/925] lr: 5.3975e-05 eta: 2:32:10 time: 0.5217 data_time: 0.0026 memory: 7975 grad_norm: 781.5740 loss: 374.3681 loss_cls: 119.8633 loss_bbox: 119.5602 loss_dfl: 134.9445 +2024/03/21 05:01:51 - mmengine - INFO - Epoch(train) [61][350/925] lr: 5.3975e-05 eta: 2:31:45 time: 0.4913 data_time: 0.0023 memory: 7815 grad_norm: 726.7646 loss: 373.3426 loss_cls: 119.3911 loss_bbox: 118.2031 loss_dfl: 135.7484 +2024/03/21 05:02:16 - mmengine - INFO - Epoch(train) [61][400/925] lr: 5.3975e-05 eta: 2:31:20 time: 0.5035 data_time: 0.0027 memory: 7842 grad_norm: 797.1612 loss: 375.3749 loss_cls: 122.2552 loss_bbox: 117.8519 loss_dfl: 135.2678 +2024/03/21 05:02:42 - mmengine - INFO - Epoch(train) [61][450/925] lr: 5.3975e-05 eta: 2:30:55 time: 0.5108 data_time: 0.0025 memory: 7775 grad_norm: 768.8605 loss: 379.9144 loss_cls: 123.8376 loss_bbox: 119.6161 loss_dfl: 136.4607 +2024/03/21 05:03:07 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:03:07 - mmengine - INFO - Epoch(train) [61][500/925] lr: 5.3975e-05 eta: 2:30:30 time: 0.4977 data_time: 0.0025 memory: 7829 grad_norm: 788.7491 loss: 382.5977 loss_cls: 125.1282 loss_bbox: 120.0964 loss_dfl: 137.3731 +2024/03/21 05:03:32 - mmengine - INFO - Epoch(train) [61][550/925] lr: 5.3975e-05 eta: 2:30:05 time: 0.5015 data_time: 0.0027 memory: 7709 grad_norm: 766.3572 loss: 374.4881 loss_cls: 120.6993 loss_bbox: 118.8903 loss_dfl: 134.8985 +2024/03/21 05:03:57 - mmengine - INFO - Epoch(train) [61][600/925] lr: 5.3975e-05 eta: 2:29:40 time: 0.4968 data_time: 0.0025 memory: 7962 grad_norm: 765.6802 loss: 374.8202 loss_cls: 122.0463 loss_bbox: 117.7124 loss_dfl: 135.0615 +2024/03/21 05:04:22 - mmengine - INFO - Epoch(train) [61][650/925] lr: 5.3975e-05 eta: 2:29:15 time: 0.5017 data_time: 0.0026 memory: 7855 grad_norm: 766.7597 loss: 385.8038 loss_cls: 126.0549 loss_bbox: 121.6387 loss_dfl: 138.1101 +2024/03/21 05:04:47 - mmengine - INFO - Epoch(train) [61][700/925] lr: 5.3975e-05 eta: 2:28:50 time: 0.5098 data_time: 0.0025 memory: 7735 grad_norm: 787.7057 loss: 375.7061 loss_cls: 120.1425 loss_bbox: 120.0927 loss_dfl: 135.4708 +2024/03/21 05:05:12 - mmengine - INFO - Epoch(train) [61][750/925] lr: 5.3975e-05 eta: 2:28:24 time: 0.4855 data_time: 0.0025 memory: 7922 grad_norm: 751.0958 loss: 382.7893 loss_cls: 123.9616 loss_bbox: 121.7199 loss_dfl: 137.1077 +2024/03/21 05:05:37 - mmengine - INFO - Epoch(train) [61][800/925] lr: 5.3975e-05 eta: 2:27:59 time: 0.4995 data_time: 0.0024 memory: 8082 grad_norm: 800.0262 loss: 371.5607 loss_cls: 119.9758 loss_bbox: 116.0374 loss_dfl: 135.5475 +2024/03/21 05:06:02 - mmengine - INFO - Epoch(train) [61][850/925] lr: 5.3975e-05 eta: 2:27:34 time: 0.5086 data_time: 0.0024 memory: 7762 grad_norm: 797.7552 loss: 376.5802 loss_cls: 121.6347 loss_bbox: 118.8451 loss_dfl: 136.1004 +2024/03/21 05:06:27 - mmengine - INFO - Epoch(train) [61][900/925] lr: 5.3975e-05 eta: 2:27:09 time: 0.4878 data_time: 0.0025 memory: 7962 grad_norm: 780.4076 loss: 372.7501 loss_cls: 118.4952 loss_bbox: 119.3915 loss_dfl: 134.8634 +2024/03/21 05:06:39 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:07:08 - mmengine - INFO - Epoch(train) [62][ 50/925] lr: 5.1500e-05 eta: 2:26:32 time: 0.5703 data_time: 0.0665 memory: 7975 grad_norm: 723.9727 loss: 375.9390 loss_cls: 121.3791 loss_bbox: 118.9822 loss_dfl: 135.5777 +2024/03/21 05:07:33 - mmengine - INFO - Epoch(train) [62][100/925] lr: 5.1500e-05 eta: 2:26:07 time: 0.5014 data_time: 0.0026 memory: 7735 grad_norm: 767.5908 loss: 370.7965 loss_cls: 118.7012 loss_bbox: 117.0653 loss_dfl: 135.0300 +2024/03/21 05:07:58 - mmengine - INFO - Epoch(train) [62][150/925] lr: 5.1500e-05 eta: 2:25:42 time: 0.5022 data_time: 0.0025 memory: 8122 grad_norm: 742.8640 loss: 375.3671 loss_cls: 119.8775 loss_bbox: 119.1709 loss_dfl: 136.3186 +2024/03/21 05:08:24 - mmengine - INFO - Epoch(train) [62][200/925] lr: 5.1500e-05 eta: 2:25:17 time: 0.5087 data_time: 0.0027 memory: 7989 grad_norm: 755.2263 loss: 376.9003 loss_cls: 121.2189 loss_bbox: 120.1080 loss_dfl: 135.5734 +2024/03/21 05:08:49 - mmengine - INFO - Epoch(train) [62][250/925] lr: 5.1500e-05 eta: 2:24:52 time: 0.4982 data_time: 0.0027 memory: 8175 grad_norm: 788.4098 loss: 372.4840 loss_cls: 118.3635 loss_bbox: 118.6947 loss_dfl: 135.4257 +2024/03/21 05:09:14 - mmengine - INFO - Epoch(train) [62][300/925] lr: 5.1500e-05 eta: 2:24:27 time: 0.5111 data_time: 0.0025 memory: 7802 grad_norm: inf loss: 380.5938 loss_cls: 124.1526 loss_bbox: 119.9127 loss_dfl: 136.5285 +2024/03/21 05:09:40 - mmengine - INFO - Epoch(train) [62][350/925] lr: 5.1500e-05 eta: 2:24:02 time: 0.5095 data_time: 0.0025 memory: 8175 grad_norm: 823.1186 loss: 377.0150 loss_cls: 120.3759 loss_bbox: 120.2521 loss_dfl: 136.3870 +2024/03/21 05:10:05 - mmengine - INFO - Epoch(train) [62][400/925] lr: 5.1500e-05 eta: 2:23:37 time: 0.4979 data_time: 0.0026 memory: 7722 grad_norm: 743.4435 loss: 372.1736 loss_cls: 120.6501 loss_bbox: 116.8373 loss_dfl: 134.6862 +2024/03/21 05:10:31 - mmengine - INFO - Epoch(train) [62][450/925] lr: 5.1500e-05 eta: 2:23:12 time: 0.5187 data_time: 0.0025 memory: 8002 grad_norm: 776.8615 loss: 373.2514 loss_cls: 120.0446 loss_bbox: 118.6378 loss_dfl: 134.5689 +2024/03/21 05:10:55 - mmengine - INFO - Epoch(train) [62][500/925] lr: 5.1500e-05 eta: 2:22:47 time: 0.4898 data_time: 0.0026 memory: 8029 grad_norm: 789.5956 loss: 374.9810 loss_cls: 120.3948 loss_bbox: 119.0375 loss_dfl: 135.5487 +2024/03/21 05:11:21 - mmengine - INFO - Epoch(train) [62][550/925] lr: 5.1500e-05 eta: 2:22:22 time: 0.5091 data_time: 0.0026 memory: 8135 grad_norm: 813.9179 loss: 375.2602 loss_cls: 122.0984 loss_bbox: 118.0359 loss_dfl: 135.1259 +2024/03/21 05:11:34 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:11:47 - mmengine - INFO - Epoch(train) [62][600/925] lr: 5.1500e-05 eta: 2:21:57 time: 0.5185 data_time: 0.0026 memory: 7749 grad_norm: 798.6459 loss: 373.7653 loss_cls: 119.7437 loss_bbox: 118.2447 loss_dfl: 135.7769 +2024/03/21 05:12:11 - mmengine - INFO - Epoch(train) [62][650/925] lr: 5.1500e-05 eta: 2:21:32 time: 0.4906 data_time: 0.0027 memory: 8109 grad_norm: 807.6973 loss: 377.5333 loss_cls: 121.3516 loss_bbox: 120.2666 loss_dfl: 135.9151 +2024/03/21 05:12:37 - mmengine - INFO - Epoch(train) [62][700/925] lr: 5.1500e-05 eta: 2:21:07 time: 0.5074 data_time: 0.0026 memory: 7909 grad_norm: 789.7867 loss: 370.9552 loss_cls: 119.1149 loss_bbox: 116.6944 loss_dfl: 135.1459 +2024/03/21 05:13:02 - mmengine - INFO - Epoch(train) [62][750/925] lr: 5.1500e-05 eta: 2:20:42 time: 0.5099 data_time: 0.0026 memory: 7762 grad_norm: 782.7498 loss: 381.3773 loss_cls: 124.3675 loss_bbox: 120.2758 loss_dfl: 136.7339 +2024/03/21 05:13:27 - mmengine - INFO - Epoch(train) [62][800/925] lr: 5.1500e-05 eta: 2:20:17 time: 0.4952 data_time: 0.0027 memory: 8215 grad_norm: 772.5116 loss: 375.5443 loss_cls: 121.0316 loss_bbox: 118.0992 loss_dfl: 136.4134 +2024/03/21 05:13:53 - mmengine - INFO - Epoch(train) [62][850/925] lr: 5.1500e-05 eta: 2:19:52 time: 0.5132 data_time: 0.0025 memory: 7842 grad_norm: 794.0714 loss: 375.3420 loss_cls: 120.9558 loss_bbox: 117.7737 loss_dfl: 136.6125 +2024/03/21 05:14:18 - mmengine - INFO - Epoch(train) [62][900/925] lr: 5.1500e-05 eta: 2:19:27 time: 0.5003 data_time: 0.0028 memory: 8015 grad_norm: 747.5883 loss: 379.6361 loss_cls: 123.0326 loss_bbox: 120.1387 loss_dfl: 136.4648 +2024/03/21 05:14:30 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:14:58 - mmengine - INFO - Epoch(train) [63][ 50/925] lr: 4.9025e-05 eta: 2:18:50 time: 0.5579 data_time: 0.0629 memory: 7869 grad_norm: 821.9207 loss: 376.9783 loss_cls: 121.4025 loss_bbox: 117.9018 loss_dfl: 137.6740 +2024/03/21 05:15:24 - mmengine - INFO - Epoch(train) [63][100/925] lr: 4.9025e-05 eta: 2:18:25 time: 0.5146 data_time: 0.0027 memory: 7962 grad_norm: 790.0349 loss: 374.0694 loss_cls: 119.6517 loss_bbox: 118.5932 loss_dfl: 135.8245 +2024/03/21 05:15:49 - mmengine - INFO - Epoch(train) [63][150/925] lr: 4.9025e-05 eta: 2:17:59 time: 0.4894 data_time: 0.0028 memory: 7829 grad_norm: 796.1055 loss: 376.0159 loss_cls: 120.2168 loss_bbox: 119.6366 loss_dfl: 136.1624 +2024/03/21 05:16:15 - mmengine - INFO - Epoch(train) [63][200/925] lr: 4.9025e-05 eta: 2:17:35 time: 0.5186 data_time: 0.0026 memory: 7975 grad_norm: 759.9251 loss: 379.4321 loss_cls: 122.4786 loss_bbox: 120.8169 loss_dfl: 136.1367 +2024/03/21 05:16:40 - mmengine - INFO - Epoch(train) [63][250/925] lr: 4.9025e-05 eta: 2:17:10 time: 0.5119 data_time: 0.0023 memory: 8042 grad_norm: 822.3886 loss: 374.6992 loss_cls: 119.7129 loss_bbox: 117.8550 loss_dfl: 137.1312 +2024/03/21 05:17:05 - mmengine - INFO - Epoch(train) [63][300/925] lr: 4.9025e-05 eta: 2:16:44 time: 0.4854 data_time: 0.0024 memory: 7749 grad_norm: 795.2102 loss: 380.3758 loss_cls: 122.2521 loss_bbox: 120.1771 loss_dfl: 137.9466 +2024/03/21 05:17:31 - mmengine - INFO - Epoch(train) [63][350/925] lr: 4.9025e-05 eta: 2:16:20 time: 0.5229 data_time: 0.0027 memory: 7949 grad_norm: 788.0975 loss: 373.8374 loss_cls: 118.2033 loss_bbox: 119.6052 loss_dfl: 136.0289 +2024/03/21 05:17:55 - mmengine - INFO - Epoch(train) [63][400/925] lr: 4.9025e-05 eta: 2:15:54 time: 0.4950 data_time: 0.0025 memory: 7829 grad_norm: 789.2887 loss: 374.2583 loss_cls: 120.3374 loss_bbox: 117.8768 loss_dfl: 136.0441 +2024/03/21 05:18:20 - mmengine - INFO - Epoch(train) [63][450/925] lr: 4.9025e-05 eta: 2:15:29 time: 0.4975 data_time: 0.0025 memory: 8002 grad_norm: 751.7278 loss: 379.2719 loss_cls: 122.3637 loss_bbox: 120.1694 loss_dfl: 136.7387 +2024/03/21 05:18:47 - mmengine - INFO - Epoch(train) [63][500/925] lr: 4.9025e-05 eta: 2:15:04 time: 0.5237 data_time: 0.0027 memory: 7935 grad_norm: 828.1922 loss: 378.4942 loss_cls: 121.9135 loss_bbox: 119.9514 loss_dfl: 136.6293 +2024/03/21 05:19:11 - mmengine - INFO - Epoch(train) [63][550/925] lr: 4.9025e-05 eta: 2:14:39 time: 0.4909 data_time: 0.0026 memory: 7855 grad_norm: 777.2901 loss: 380.9885 loss_cls: 124.1101 loss_bbox: 120.1995 loss_dfl: 136.6790 +2024/03/21 05:19:37 - mmengine - INFO - Epoch(train) [63][600/925] lr: 4.9025e-05 eta: 2:14:14 time: 0.5075 data_time: 0.0027 memory: 7975 grad_norm: 747.4643 loss: 375.7471 loss_cls: 121.6763 loss_bbox: 117.6116 loss_dfl: 136.4592 +2024/03/21 05:20:02 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:20:02 - mmengine - INFO - Epoch(train) [63][650/925] lr: 4.9025e-05 eta: 2:13:49 time: 0.5166 data_time: 0.0026 memory: 7909 grad_norm: 829.2775 loss: 373.4071 loss_cls: 119.6521 loss_bbox: 117.3790 loss_dfl: 136.3760 +2024/03/21 05:20:27 - mmengine - INFO - Epoch(train) [63][700/925] lr: 4.9025e-05 eta: 2:13:24 time: 0.4940 data_time: 0.0026 memory: 7829 grad_norm: 762.9219 loss: 375.5984 loss_cls: 121.7396 loss_bbox: 117.8609 loss_dfl: 135.9979 +2024/03/21 05:20:53 - mmengine - INFO - Epoch(train) [63][750/925] lr: 4.9025e-05 eta: 2:12:59 time: 0.5105 data_time: 0.0027 memory: 8042 grad_norm: 746.0510 loss: 382.1344 loss_cls: 124.9535 loss_bbox: 120.4616 loss_dfl: 136.7193 +2024/03/21 05:21:18 - mmengine - INFO - Epoch(train) [63][800/925] lr: 4.9025e-05 eta: 2:12:34 time: 0.5081 data_time: 0.0027 memory: 7842 grad_norm: 793.3807 loss: 376.7601 loss_cls: 121.8288 loss_bbox: 118.8669 loss_dfl: 136.0643 +2024/03/21 05:21:43 - mmengine - INFO - Epoch(train) [63][850/925] lr: 4.9025e-05 eta: 2:12:09 time: 0.4997 data_time: 0.0026 memory: 7855 grad_norm: 799.5417 loss: 374.3646 loss_cls: 120.3067 loss_bbox: 119.0612 loss_dfl: 134.9967 +2024/03/21 05:22:09 - mmengine - INFO - Epoch(train) [63][900/925] lr: 4.9025e-05 eta: 2:11:44 time: 0.5088 data_time: 0.0025 memory: 8029 grad_norm: 745.0111 loss: 382.2920 loss_cls: 122.8718 loss_bbox: 121.9286 loss_dfl: 137.4916 +2024/03/21 05:22:21 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:22:49 - mmengine - INFO - Epoch(train) [64][ 50/925] lr: 4.6550e-05 eta: 2:11:07 time: 0.5537 data_time: 0.0639 memory: 7895 grad_norm: 860.6304 loss: 376.9610 loss_cls: 121.7285 loss_bbox: 118.1953 loss_dfl: 137.0371 +2024/03/21 05:23:15 - mmengine - INFO - Epoch(train) [64][100/925] lr: 4.6550e-05 eta: 2:10:42 time: 0.5247 data_time: 0.0025 memory: 7829 grad_norm: 813.4297 loss: 370.4696 loss_cls: 119.3258 loss_bbox: 116.1763 loss_dfl: 134.9675 +2024/03/21 05:23:40 - mmengine - INFO - Epoch(train) [64][150/925] lr: 4.6550e-05 eta: 2:10:17 time: 0.5058 data_time: 0.0024 memory: 7842 grad_norm: 785.4205 loss: 376.4802 loss_cls: 121.2506 loss_bbox: 118.8842 loss_dfl: 136.3453 +2024/03/21 05:24:05 - mmengine - INFO - Epoch(train) [64][200/925] lr: 4.6550e-05 eta: 2:09:52 time: 0.4918 data_time: 0.0025 memory: 8135 grad_norm: 750.7864 loss: 379.5065 loss_cls: 122.8172 loss_bbox: 120.1282 loss_dfl: 136.5610 +2024/03/21 05:24:32 - mmengine - INFO - Epoch(train) [64][250/925] lr: 4.6550e-05 eta: 2:09:27 time: 0.5345 data_time: 0.0025 memory: 8455 grad_norm: 780.9939 loss: 378.4448 loss_cls: 122.2163 loss_bbox: 119.6319 loss_dfl: 136.5966 +2024/03/21 05:24:57 - mmengine - INFO - Epoch(train) [64][300/925] lr: 4.6550e-05 eta: 2:09:02 time: 0.4973 data_time: 0.0024 memory: 8175 grad_norm: 812.2128 loss: 383.1163 loss_cls: 124.6523 loss_bbox: 121.3752 loss_dfl: 137.0887 +2024/03/21 05:25:22 - mmengine - INFO - Epoch(train) [64][350/925] lr: 4.6550e-05 eta: 2:08:37 time: 0.4982 data_time: 0.0027 memory: 7829 grad_norm: 754.3228 loss: 378.0094 loss_cls: 121.7788 loss_bbox: 119.7587 loss_dfl: 136.4719 +2024/03/21 05:25:48 - mmengine - INFO - Epoch(train) [64][400/925] lr: 4.6550e-05 eta: 2:08:12 time: 0.5236 data_time: 0.0027 memory: 8055 grad_norm: 781.7615 loss: 374.2631 loss_cls: 119.8570 loss_bbox: 118.4719 loss_dfl: 135.9341 +2024/03/21 05:26:13 - mmengine - INFO - Epoch(train) [64][450/925] lr: 4.6550e-05 eta: 2:07:47 time: 0.4975 data_time: 0.0026 memory: 7815 grad_norm: 769.8450 loss: 375.2407 loss_cls: 121.8009 loss_bbox: 116.5543 loss_dfl: 136.8855 +2024/03/21 05:26:38 - mmengine - INFO - Epoch(train) [64][500/925] lr: 4.6550e-05 eta: 2:07:22 time: 0.5087 data_time: 0.0026 memory: 7855 grad_norm: 736.5428 loss: 381.8006 loss_cls: 124.3276 loss_bbox: 119.4981 loss_dfl: 137.9750 +2024/03/21 05:27:04 - mmengine - INFO - Epoch(train) [64][550/925] lr: 4.6550e-05 eta: 2:06:57 time: 0.5119 data_time: 0.0026 memory: 7975 grad_norm: 769.8808 loss: 376.3652 loss_cls: 121.6435 loss_bbox: 117.8749 loss_dfl: 136.8467 +2024/03/21 05:27:29 - mmengine - INFO - Epoch(train) [64][600/925] lr: 4.6550e-05 eta: 2:06:32 time: 0.4979 data_time: 0.0026 memory: 8442 grad_norm: inf loss: 371.9906 loss_cls: 119.5971 loss_bbox: 117.0487 loss_dfl: 135.3447 +2024/03/21 05:27:54 - mmengine - INFO - Epoch(train) [64][650/925] lr: 4.6550e-05 eta: 2:06:07 time: 0.5114 data_time: 0.0026 memory: 8149 grad_norm: 742.5491 loss: 382.4226 loss_cls: 124.2685 loss_bbox: 120.9761 loss_dfl: 137.1780 +2024/03/21 05:28:20 - mmengine - INFO - Epoch(train) [64][700/925] lr: 4.6550e-05 eta: 2:05:42 time: 0.5121 data_time: 0.0027 memory: 7909 grad_norm: 738.8371 loss: 376.9060 loss_cls: 121.7928 loss_bbox: 118.9847 loss_dfl: 136.1285 +2024/03/21 05:28:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:28:45 - mmengine - INFO - Epoch(train) [64][750/925] lr: 4.6550e-05 eta: 2:05:17 time: 0.4973 data_time: 0.0026 memory: 8002 grad_norm: 793.7392 loss: 375.2010 loss_cls: 120.5768 loss_bbox: 119.2589 loss_dfl: 135.3653 +2024/03/21 05:29:11 - mmengine - INFO - Epoch(train) [64][800/925] lr: 4.6550e-05 eta: 2:04:52 time: 0.5185 data_time: 0.0026 memory: 7962 grad_norm: 789.0264 loss: 376.4461 loss_cls: 121.3353 loss_bbox: 119.1775 loss_dfl: 135.9333 +2024/03/21 05:29:36 - mmengine - INFO - Epoch(train) [64][850/925] lr: 4.6550e-05 eta: 2:04:27 time: 0.5068 data_time: 0.0026 memory: 7935 grad_norm: 730.7503 loss: 380.5249 loss_cls: 122.7320 loss_bbox: 120.7532 loss_dfl: 137.0397 +2024/03/21 05:30:02 - mmengine - INFO - Epoch(train) [64][900/925] lr: 4.6550e-05 eta: 2:04:02 time: 0.5057 data_time: 0.0025 memory: 8215 grad_norm: 761.5557 loss: 382.0935 loss_cls: 123.8713 loss_bbox: 120.1521 loss_dfl: 138.0701 +2024/03/21 05:30:14 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:30:43 - mmengine - INFO - Epoch(train) [65][ 50/925] lr: 4.4075e-05 eta: 2:03:25 time: 0.5596 data_time: 0.0656 memory: 8069 grad_norm: 805.6315 loss: 373.4259 loss_cls: 119.2178 loss_bbox: 119.4250 loss_dfl: 134.7832 +2024/03/21 05:31:07 - mmengine - INFO - Epoch(train) [65][100/925] lr: 4.4075e-05 eta: 2:02:59 time: 0.4915 data_time: 0.0026 memory: 8029 grad_norm: 767.2347 loss: 369.8643 loss_cls: 117.9793 loss_bbox: 116.9660 loss_dfl: 134.9190 +2024/03/21 05:31:33 - mmengine - INFO - Epoch(train) [65][150/925] lr: 4.4075e-05 eta: 2:02:35 time: 0.5150 data_time: 0.0025 memory: 8002 grad_norm: 753.4460 loss: 374.0516 loss_cls: 120.2855 loss_bbox: 117.8014 loss_dfl: 135.9647 +2024/03/21 05:31:58 - mmengine - INFO - Epoch(train) [65][200/925] lr: 4.4075e-05 eta: 2:02:09 time: 0.4902 data_time: 0.0028 memory: 8122 grad_norm: 791.5901 loss: 377.0380 loss_cls: 120.9852 loss_bbox: 120.6309 loss_dfl: 135.4220 +2024/03/21 05:32:22 - mmengine - INFO - Epoch(train) [65][250/925] lr: 4.4075e-05 eta: 2:01:44 time: 0.4914 data_time: 0.0025 memory: 8002 grad_norm: 808.3391 loss: 377.5480 loss_cls: 121.1061 loss_bbox: 120.2261 loss_dfl: 136.2158 +2024/03/21 05:32:48 - mmengine - INFO - Epoch(train) [65][300/925] lr: 4.4075e-05 eta: 2:01:19 time: 0.5170 data_time: 0.0027 memory: 7962 grad_norm: 782.3601 loss: 373.3237 loss_cls: 121.2722 loss_bbox: 116.9638 loss_dfl: 135.0878 +2024/03/21 05:33:12 - mmengine - INFO - Epoch(train) [65][350/925] lr: 4.4075e-05 eta: 2:00:54 time: 0.4843 data_time: 0.0027 memory: 7922 grad_norm: 760.4592 loss: 370.1597 loss_cls: 116.6628 loss_bbox: 119.0110 loss_dfl: 134.4859 +2024/03/21 05:33:38 - mmengine - INFO - Epoch(train) [65][400/925] lr: 4.4075e-05 eta: 2:00:29 time: 0.5031 data_time: 0.0025 memory: 8082 grad_norm: 777.9017 loss: 375.7750 loss_cls: 120.1561 loss_bbox: 119.0562 loss_dfl: 136.5627 +2024/03/21 05:34:02 - mmengine - INFO - Epoch(train) [65][450/925] lr: 4.4075e-05 eta: 2:00:03 time: 0.4910 data_time: 0.0026 memory: 7949 grad_norm: 743.2075 loss: 377.4525 loss_cls: 121.8762 loss_bbox: 118.9931 loss_dfl: 136.5832 +2024/03/21 05:34:27 - mmengine - INFO - Epoch(train) [65][500/925] lr: 4.4075e-05 eta: 1:59:38 time: 0.4965 data_time: 0.0026 memory: 7949 grad_norm: 787.0013 loss: 375.7358 loss_cls: 121.2852 loss_bbox: 117.8889 loss_dfl: 136.5617 +2024/03/21 05:34:52 - mmengine - INFO - Epoch(train) [65][550/925] lr: 4.4075e-05 eta: 1:59:13 time: 0.5087 data_time: 0.0026 memory: 7989 grad_norm: 768.1291 loss: 379.6040 loss_cls: 122.6008 loss_bbox: 120.3341 loss_dfl: 136.6691 +2024/03/21 05:35:18 - mmengine - INFO - Epoch(train) [65][600/925] lr: 4.4075e-05 eta: 1:58:48 time: 0.5006 data_time: 0.0027 memory: 8042 grad_norm: 773.7057 loss: 371.7246 loss_cls: 119.1559 loss_bbox: 116.7067 loss_dfl: 135.8621 +2024/03/21 05:35:42 - mmengine - INFO - Epoch(train) [65][650/925] lr: 4.4075e-05 eta: 1:58:23 time: 0.4922 data_time: 0.0026 memory: 7815 grad_norm: 798.2620 loss: 381.1833 loss_cls: 122.8228 loss_bbox: 121.8705 loss_dfl: 136.4901 +2024/03/21 05:36:07 - mmengine - INFO - Epoch(train) [65][700/925] lr: 4.4075e-05 eta: 1:57:58 time: 0.4974 data_time: 0.0024 memory: 7949 grad_norm: 768.4855 loss: 374.3271 loss_cls: 119.8830 loss_bbox: 118.2421 loss_dfl: 136.2020 +2024/03/21 05:36:32 - mmengine - INFO - Epoch(train) [65][750/925] lr: 4.4075e-05 eta: 1:57:33 time: 0.4903 data_time: 0.0027 memory: 8349 grad_norm: 810.0763 loss: 372.8065 loss_cls: 121.5351 loss_bbox: 116.0379 loss_dfl: 135.2335 +2024/03/21 05:36:56 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:36:56 - mmengine - INFO - Epoch(train) [65][800/925] lr: 4.4075e-05 eta: 1:57:07 time: 0.4962 data_time: 0.0027 memory: 7869 grad_norm: 826.5823 loss: 377.6993 loss_cls: 122.5937 loss_bbox: 119.2046 loss_dfl: 135.9010 +2024/03/21 05:37:22 - mmengine - INFO - Epoch(train) [65][850/925] lr: 4.4075e-05 eta: 1:56:42 time: 0.5004 data_time: 0.0027 memory: 7749 grad_norm: 750.2298 loss: 372.0722 loss_cls: 120.0179 loss_bbox: 116.4557 loss_dfl: 135.5985 +2024/03/21 05:37:46 - mmengine - INFO - Epoch(train) [65][900/925] lr: 4.4075e-05 eta: 1:56:17 time: 0.4937 data_time: 0.0027 memory: 7869 grad_norm: 750.6835 loss: 372.2941 loss_cls: 119.5156 loss_bbox: 118.1850 loss_dfl: 134.5935 +2024/03/21 05:37:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:37:59 - mmengine - INFO - Saving checkpoint at 65 epochs +2024/03/21 05:38:08 - mmengine - INFO - Epoch(val) [65][ 50/625] eta: 0:00:20 time: 0.0363 data_time: 0.0008 memory: 7855 +2024/03/21 05:38:09 - mmengine - INFO - Epoch(val) [65][100/625] eta: 0:00:18 time: 0.0357 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:11 - mmengine - INFO - Epoch(val) [65][150/625] eta: 0:00:17 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:13 - mmengine - INFO - Epoch(val) [65][200/625] eta: 0:00:15 time: 0.0376 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:15 - mmengine - INFO - Epoch(val) [65][250/625] eta: 0:00:13 time: 0.0372 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:17 - mmengine - INFO - Epoch(val) [65][300/625] eta: 0:00:11 time: 0.0370 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:19 - mmengine - INFO - Epoch(val) [65][350/625] eta: 0:00:10 time: 0.0370 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:20 - mmengine - INFO - Epoch(val) [65][400/625] eta: 0:00:08 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:22 - mmengine - INFO - Epoch(val) [65][450/625] eta: 0:00:06 time: 0.0373 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:24 - mmengine - INFO - Epoch(val) [65][500/625] eta: 0:00:04 time: 0.0329 data_time: 0.0003 memory: 1244 +2024/03/21 05:38:25 - mmengine - INFO - Epoch(val) [65][550/625] eta: 0:00:02 time: 0.0286 data_time: 0.0002 memory: 1244 +2024/03/21 05:38:27 - mmengine - INFO - Epoch(val) [65][600/625] eta: 0:00:00 time: 0.0282 data_time: 0.0002 memory: 1244 +2024/03/21 05:38:39 - mmengine - INFO - Evaluating bbox... +2024/03/21 05:39:47 - mmengine - INFO - bbox_mAP_copypaste: 0.506 0.672 0.551 0.329 0.558 0.669 +2024/03/21 05:39:49 - mmengine - INFO - Epoch(val) [65][625/625] coco/bbox_mAP: 0.5060 coco/bbox_mAP_50: 0.6720 coco/bbox_mAP_75: 0.5510 coco/bbox_mAP_s: 0.3290 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6690 data_time: 0.0002 time: 0.0281 +2024/03/21 05:40:17 - mmengine - INFO - Epoch(train) [66][ 50/925] lr: 4.1600e-05 eta: 1:55:40 time: 0.5648 data_time: 0.0694 memory: 7749 grad_norm: 785.9066 loss: 376.3885 loss_cls: 119.9551 loss_bbox: 119.7154 loss_dfl: 136.7180 +2024/03/21 05:40:42 - mmengine - INFO - Epoch(train) [66][100/925] lr: 4.1600e-05 eta: 1:55:15 time: 0.5032 data_time: 0.0026 memory: 8375 grad_norm: 784.5993 loss: 377.9615 loss_cls: 122.0988 loss_bbox: 119.0990 loss_dfl: 136.7637 +2024/03/21 05:41:08 - mmengine - INFO - Epoch(train) [66][150/925] lr: 4.1600e-05 eta: 1:54:50 time: 0.5107 data_time: 0.0026 memory: 7775 grad_norm: 808.6733 loss: 374.6684 loss_cls: 120.5442 loss_bbox: 118.4802 loss_dfl: 135.6440 +2024/03/21 05:41:34 - mmengine - INFO - Epoch(train) [66][200/925] lr: 4.1600e-05 eta: 1:54:25 time: 0.5146 data_time: 0.0027 memory: 7895 grad_norm: 817.8069 loss: 372.3676 loss_cls: 119.5860 loss_bbox: 117.6744 loss_dfl: 135.1072 +2024/03/21 05:41:58 - mmengine - INFO - Epoch(train) [66][250/925] lr: 4.1600e-05 eta: 1:54:00 time: 0.4926 data_time: 0.0025 memory: 7909 grad_norm: 779.3965 loss: 371.8886 loss_cls: 118.5168 loss_bbox: 117.5660 loss_dfl: 135.8058 +2024/03/21 05:42:24 - mmengine - INFO - Epoch(train) [66][300/925] lr: 4.1600e-05 eta: 1:53:35 time: 0.5160 data_time: 0.0027 memory: 7882 grad_norm: 754.4672 loss: 385.3557 loss_cls: 125.4080 loss_bbox: 122.3963 loss_dfl: 137.5514 +2024/03/21 05:42:49 - mmengine - INFO - Epoch(train) [66][350/925] lr: 4.1600e-05 eta: 1:53:10 time: 0.4966 data_time: 0.0026 memory: 8162 grad_norm: 747.0692 loss: 372.2685 loss_cls: 119.2078 loss_bbox: 118.2286 loss_dfl: 134.8322 +2024/03/21 05:43:14 - mmengine - INFO - Epoch(train) [66][400/925] lr: 4.1600e-05 eta: 1:52:45 time: 0.4997 data_time: 0.0027 memory: 7789 grad_norm: 795.2505 loss: 373.9433 loss_cls: 118.3410 loss_bbox: 119.1836 loss_dfl: 136.4188 +2024/03/21 05:43:40 - mmengine - INFO - Epoch(train) [66][450/925] lr: 4.1600e-05 eta: 1:52:20 time: 0.5224 data_time: 0.0025 memory: 7842 grad_norm: 730.5224 loss: 374.8057 loss_cls: 120.0132 loss_bbox: 118.6313 loss_dfl: 136.1612 +2024/03/21 05:44:05 - mmengine - INFO - Epoch(train) [66][500/925] lr: 4.1600e-05 eta: 1:51:55 time: 0.5030 data_time: 0.0027 memory: 7775 grad_norm: 761.8836 loss: 372.2166 loss_cls: 119.1120 loss_bbox: 117.3999 loss_dfl: 135.7048 +2024/03/21 05:44:31 - mmengine - INFO - Epoch(train) [66][550/925] lr: 4.1600e-05 eta: 1:51:30 time: 0.5006 data_time: 0.0025 memory: 8202 grad_norm: 756.7203 loss: 376.7225 loss_cls: 121.1240 loss_bbox: 119.6381 loss_dfl: 135.9604 +2024/03/21 05:44:57 - mmengine - INFO - Epoch(train) [66][600/925] lr: 4.1600e-05 eta: 1:51:05 time: 0.5199 data_time: 0.0024 memory: 8095 grad_norm: 784.1412 loss: 378.6777 loss_cls: 122.6492 loss_bbox: 120.2345 loss_dfl: 135.7940 +2024/03/21 05:45:22 - mmengine - INFO - Epoch(train) [66][650/925] lr: 4.1600e-05 eta: 1:50:39 time: 0.5007 data_time: 0.0025 memory: 7842 grad_norm: 786.9127 loss: 371.1383 loss_cls: 118.1156 loss_bbox: 117.9140 loss_dfl: 135.1087 +2024/03/21 05:45:47 - mmengine - INFO - Epoch(train) [66][700/925] lr: 4.1600e-05 eta: 1:50:14 time: 0.5005 data_time: 0.0026 memory: 8069 grad_norm: 778.0038 loss: 377.8777 loss_cls: 122.2070 loss_bbox: 118.9645 loss_dfl: 136.7061 +2024/03/21 05:46:12 - mmengine - INFO - Epoch(train) [66][750/925] lr: 4.1600e-05 eta: 1:49:49 time: 0.5042 data_time: 0.0026 memory: 7869 grad_norm: 839.8297 loss: 369.9322 loss_cls: 118.2469 loss_bbox: 116.5742 loss_dfl: 135.1111 +2024/03/21 05:46:37 - mmengine - INFO - Epoch(train) [66][800/925] lr: 4.1600e-05 eta: 1:49:24 time: 0.4989 data_time: 0.0025 memory: 7869 grad_norm: 767.8721 loss: 374.6321 loss_cls: 119.8884 loss_bbox: 118.8803 loss_dfl: 135.8633 +2024/03/21 05:47:03 - mmengine - INFO - Epoch(train) [66][850/925] lr: 4.1600e-05 eta: 1:48:59 time: 0.5206 data_time: 0.0026 memory: 8415 grad_norm: 788.2256 loss: 379.8036 loss_cls: 123.7678 loss_bbox: 119.3893 loss_dfl: 136.6465 +2024/03/21 05:47:16 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:47:28 - mmengine - INFO - Epoch(train) [66][900/925] lr: 4.1600e-05 eta: 1:48:34 time: 0.4988 data_time: 0.0025 memory: 8042 grad_norm: 775.9663 loss: 382.7177 loss_cls: 123.1244 loss_bbox: 122.0112 loss_dfl: 137.5820 +2024/03/21 05:47:40 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:48:08 - mmengine - INFO - Epoch(train) [67][ 50/925] lr: 3.9125e-05 eta: 1:47:57 time: 0.5590 data_time: 0.0633 memory: 8189 grad_norm: 777.1267 loss: 369.6479 loss_cls: 118.5963 loss_bbox: 115.7981 loss_dfl: 135.2535 +2024/03/21 05:48:34 - mmengine - INFO - Epoch(train) [67][100/925] lr: 3.9125e-05 eta: 1:47:32 time: 0.5039 data_time: 0.0025 memory: 7842 grad_norm: 756.2103 loss: 368.7420 loss_cls: 117.5415 loss_bbox: 116.7800 loss_dfl: 134.4205 +2024/03/21 05:48:58 - mmengine - INFO - Epoch(train) [67][150/925] lr: 3.9125e-05 eta: 1:47:07 time: 0.4843 data_time: 0.0026 memory: 7935 grad_norm: 798.7495 loss: 377.8900 loss_cls: 123.2445 loss_bbox: 117.9341 loss_dfl: 136.7114 +2024/03/21 05:49:24 - mmengine - INFO - Epoch(train) [67][200/925] lr: 3.9125e-05 eta: 1:46:42 time: 0.5239 data_time: 0.0026 memory: 8015 grad_norm: 735.2083 loss: 373.9122 loss_cls: 118.3895 loss_bbox: 120.4047 loss_dfl: 135.1180 +2024/03/21 05:49:49 - mmengine - INFO - Epoch(train) [67][250/925] lr: 3.9125e-05 eta: 1:46:17 time: 0.5014 data_time: 0.0025 memory: 8015 grad_norm: inf loss: 373.5560 loss_cls: 119.0727 loss_bbox: 118.2634 loss_dfl: 136.2199 +2024/03/21 05:50:13 - mmengine - INFO - Epoch(train) [67][300/925] lr: 3.9125e-05 eta: 1:45:51 time: 0.4820 data_time: 0.0026 memory: 7949 grad_norm: 765.5389 loss: 374.2581 loss_cls: 120.3733 loss_bbox: 118.0392 loss_dfl: 135.8457 +2024/03/21 05:50:40 - mmengine - INFO - Epoch(train) [67][350/925] lr: 3.9125e-05 eta: 1:45:26 time: 0.5353 data_time: 0.0026 memory: 7962 grad_norm: 778.0900 loss: 368.1034 loss_cls: 115.9861 loss_bbox: 117.3099 loss_dfl: 134.8074 +2024/03/21 05:51:05 - mmengine - INFO - Epoch(train) [67][400/925] lr: 3.9125e-05 eta: 1:45:01 time: 0.4941 data_time: 0.0026 memory: 7962 grad_norm: 785.6035 loss: 377.7675 loss_cls: 120.0981 loss_bbox: 120.8236 loss_dfl: 136.8458 +2024/03/21 05:51:29 - mmengine - INFO - Epoch(train) [67][450/925] lr: 3.9125e-05 eta: 1:44:36 time: 0.4859 data_time: 0.0027 memory: 8015 grad_norm: 771.0046 loss: 374.1456 loss_cls: 120.0682 loss_bbox: 117.4932 loss_dfl: 136.5842 +2024/03/21 05:51:55 - mmengine - INFO - Epoch(train) [67][500/925] lr: 3.9125e-05 eta: 1:44:11 time: 0.5221 data_time: 0.0026 memory: 7842 grad_norm: 799.7594 loss: 376.2484 loss_cls: 120.4962 loss_bbox: 118.8401 loss_dfl: 136.9120 +2024/03/21 05:52:20 - mmengine - INFO - Epoch(train) [67][550/925] lr: 3.9125e-05 eta: 1:43:46 time: 0.4887 data_time: 0.0026 memory: 7722 grad_norm: 774.4389 loss: 373.3468 loss_cls: 119.6324 loss_bbox: 117.9575 loss_dfl: 135.7569 +2024/03/21 05:52:45 - mmengine - INFO - Epoch(train) [67][600/925] lr: 3.9125e-05 eta: 1:43:21 time: 0.4991 data_time: 0.0025 memory: 7802 grad_norm: 805.4038 loss: 372.0718 loss_cls: 118.5474 loss_bbox: 117.3496 loss_dfl: 136.1747 +2024/03/21 05:53:10 - mmengine - INFO - Epoch(train) [67][650/925] lr: 3.9125e-05 eta: 1:42:56 time: 0.5087 data_time: 0.0026 memory: 8309 grad_norm: 774.4871 loss: 371.5907 loss_cls: 118.0618 loss_bbox: 117.8805 loss_dfl: 135.6484 +2024/03/21 05:53:35 - mmengine - INFO - Epoch(train) [67][700/925] lr: 3.9125e-05 eta: 1:42:31 time: 0.4968 data_time: 0.0025 memory: 7842 grad_norm: 748.7396 loss: 373.9432 loss_cls: 119.5953 loss_bbox: 118.5414 loss_dfl: 135.8066 +2024/03/21 05:54:01 - mmengine - INFO - Epoch(train) [67][750/925] lr: 3.9125e-05 eta: 1:42:06 time: 0.5114 data_time: 0.0025 memory: 7882 grad_norm: 785.7714 loss: 373.5815 loss_cls: 119.4351 loss_bbox: 117.7341 loss_dfl: 136.4122 +2024/03/21 05:54:26 - mmengine - INFO - Epoch(train) [67][800/925] lr: 3.9125e-05 eta: 1:41:40 time: 0.4967 data_time: 0.0025 memory: 7802 grad_norm: 769.2192 loss: 375.6233 loss_cls: 120.8398 loss_bbox: 118.4797 loss_dfl: 136.3038 +2024/03/21 05:54:50 - mmengine - INFO - Epoch(train) [67][850/925] lr: 3.9125e-05 eta: 1:41:15 time: 0.4910 data_time: 0.0026 memory: 7989 grad_norm: 817.7543 loss: 373.8947 loss_cls: 120.5757 loss_bbox: 117.7540 loss_dfl: 135.5650 +2024/03/21 05:55:16 - mmengine - INFO - Epoch(train) [67][900/925] lr: 3.9125e-05 eta: 1:40:50 time: 0.5222 data_time: 0.0025 memory: 7962 grad_norm: 776.2146 loss: 374.3738 loss_cls: 119.2218 loss_bbox: 118.7586 loss_dfl: 136.3935 +2024/03/21 05:55:28 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:55:44 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 05:55:56 - mmengine - INFO - Epoch(train) [68][ 50/925] lr: 3.6650e-05 eta: 1:40:13 time: 0.5496 data_time: 0.0510 memory: 7815 grad_norm: 794.4132 loss: 378.4416 loss_cls: 120.9502 loss_bbox: 120.9934 loss_dfl: 136.4980 +2024/03/21 05:56:22 - mmengine - INFO - Epoch(train) [68][100/925] lr: 3.6650e-05 eta: 1:39:48 time: 0.5291 data_time: 0.0026 memory: 8029 grad_norm: 771.3096 loss: 375.9817 loss_cls: 120.6454 loss_bbox: 119.0761 loss_dfl: 136.2603 +2024/03/21 05:56:47 - mmengine - INFO - Epoch(train) [68][150/925] lr: 3.6650e-05 eta: 1:39:23 time: 0.4942 data_time: 0.0027 memory: 8175 grad_norm: 768.7964 loss: 375.3978 loss_cls: 120.2822 loss_bbox: 119.3693 loss_dfl: 135.7463 +2024/03/21 05:57:12 - mmengine - INFO - Epoch(train) [68][200/925] lr: 3.6650e-05 eta: 1:38:58 time: 0.5027 data_time: 0.0027 memory: 7789 grad_norm: 764.6823 loss: 364.9066 loss_cls: 114.9649 loss_bbox: 115.2658 loss_dfl: 134.6759 +2024/03/21 05:57:39 - mmengine - INFO - Epoch(train) [68][250/925] lr: 3.6650e-05 eta: 1:38:33 time: 0.5236 data_time: 0.0028 memory: 7735 grad_norm: 789.1074 loss: 376.0585 loss_cls: 120.9365 loss_bbox: 119.2176 loss_dfl: 135.9043 +2024/03/21 05:58:03 - mmengine - INFO - Epoch(train) [68][300/925] lr: 3.6650e-05 eta: 1:38:08 time: 0.4883 data_time: 0.0027 memory: 8042 grad_norm: 813.5895 loss: 370.1280 loss_cls: 117.3406 loss_bbox: 117.9550 loss_dfl: 134.8323 +2024/03/21 05:58:28 - mmengine - INFO - Epoch(train) [68][350/925] lr: 3.6650e-05 eta: 1:37:42 time: 0.4980 data_time: 0.0025 memory: 7869 grad_norm: 822.7992 loss: 374.0214 loss_cls: 118.7946 loss_bbox: 120.2737 loss_dfl: 134.9530 +2024/03/21 05:58:53 - mmengine - INFO - Epoch(train) [68][400/925] lr: 3.6650e-05 eta: 1:37:17 time: 0.5065 data_time: 0.0027 memory: 7842 grad_norm: 769.7751 loss: 376.9548 loss_cls: 120.4749 loss_bbox: 119.5138 loss_dfl: 136.9662 +2024/03/21 05:59:18 - mmengine - INFO - Epoch(train) [68][450/925] lr: 3.6650e-05 eta: 1:36:52 time: 0.4917 data_time: 0.0027 memory: 8482 grad_norm: 800.1144 loss: 371.8425 loss_cls: 117.5961 loss_bbox: 118.3434 loss_dfl: 135.9030 +2024/03/21 05:59:43 - mmengine - INFO - Epoch(train) [68][500/925] lr: 3.6650e-05 eta: 1:36:27 time: 0.5086 data_time: 0.0026 memory: 7895 grad_norm: 753.2522 loss: 372.3719 loss_cls: 120.4655 loss_bbox: 116.2524 loss_dfl: 135.6540 +2024/03/21 06:00:09 - mmengine - INFO - Epoch(train) [68][550/925] lr: 3.6650e-05 eta: 1:36:02 time: 0.5079 data_time: 0.0027 memory: 7935 grad_norm: 803.1417 loss: 366.7657 loss_cls: 116.5146 loss_bbox: 116.1388 loss_dfl: 134.1124 +2024/03/21 06:00:33 - mmengine - INFO - Epoch(train) [68][600/925] lr: 3.6650e-05 eta: 1:35:37 time: 0.4879 data_time: 0.0027 memory: 8002 grad_norm: 782.4965 loss: 367.8473 loss_cls: 116.5563 loss_bbox: 116.7051 loss_dfl: 134.5859 +2024/03/21 06:00:59 - mmengine - INFO - Epoch(train) [68][650/925] lr: 3.6650e-05 eta: 1:35:12 time: 0.5112 data_time: 0.0027 memory: 8055 grad_norm: 756.7681 loss: 371.4022 loss_cls: 118.2810 loss_bbox: 118.5736 loss_dfl: 134.5477 +2024/03/21 06:01:24 - mmengine - INFO - Epoch(train) [68][700/925] lr: 3.6650e-05 eta: 1:34:47 time: 0.4912 data_time: 0.0026 memory: 7815 grad_norm: 853.8932 loss: 366.7836 loss_cls: 115.8689 loss_bbox: 116.5368 loss_dfl: 134.3779 +2024/03/21 06:01:48 - mmengine - INFO - Epoch(train) [68][750/925] lr: 3.6650e-05 eta: 1:34:21 time: 0.4879 data_time: 0.0027 memory: 8189 grad_norm: 804.9522 loss: 376.3251 loss_cls: 121.2813 loss_bbox: 118.7403 loss_dfl: 136.3034 +2024/03/21 06:02:14 - mmengine - INFO - Epoch(train) [68][800/925] lr: 3.6650e-05 eta: 1:33:56 time: 0.5119 data_time: 0.0027 memory: 7869 grad_norm: 792.8295 loss: 371.0268 loss_cls: 118.2967 loss_bbox: 117.5594 loss_dfl: 135.1706 +2024/03/21 06:02:39 - mmengine - INFO - Epoch(train) [68][850/925] lr: 3.6650e-05 eta: 1:33:31 time: 0.5032 data_time: 0.0026 memory: 8229 grad_norm: 799.0915 loss: 369.6627 loss_cls: 117.6092 loss_bbox: 117.3532 loss_dfl: 134.7003 +2024/03/21 06:03:03 - mmengine - INFO - Epoch(train) [68][900/925] lr: 3.6650e-05 eta: 1:33:06 time: 0.4880 data_time: 0.0027 memory: 7869 grad_norm: 804.3294 loss: 374.5006 loss_cls: 120.2315 loss_bbox: 117.8879 loss_dfl: 136.3812 +2024/03/21 06:03:16 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:03:44 - mmengine - INFO - Epoch(train) [69][ 50/925] lr: 3.4175e-05 eta: 1:32:29 time: 0.5568 data_time: 0.0696 memory: 8042 grad_norm: 767.8416 loss: 372.2765 loss_cls: 117.3353 loss_bbox: 118.5147 loss_dfl: 136.4266 +2024/03/21 06:04:09 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:04:09 - mmengine - INFO - Epoch(train) [69][100/925] lr: 3.4175e-05 eta: 1:32:04 time: 0.4930 data_time: 0.0024 memory: 7855 grad_norm: 757.7525 loss: 371.1777 loss_cls: 118.0335 loss_bbox: 117.9964 loss_dfl: 135.1478 +2024/03/21 06:04:34 - mmengine - INFO - Epoch(train) [69][150/925] lr: 3.4175e-05 eta: 1:31:39 time: 0.5112 data_time: 0.0026 memory: 7895 grad_norm: 827.2928 loss: 374.5569 loss_cls: 119.2186 loss_bbox: 119.8500 loss_dfl: 135.4884 +2024/03/21 06:04:59 - mmengine - INFO - Epoch(train) [69][200/925] lr: 3.4175e-05 eta: 1:31:13 time: 0.4920 data_time: 0.0029 memory: 7829 grad_norm: 756.4701 loss: 370.4337 loss_cls: 119.3798 loss_bbox: 116.2418 loss_dfl: 134.8122 +2024/03/21 06:05:24 - mmengine - INFO - Epoch(train) [69][250/925] lr: 3.4175e-05 eta: 1:30:48 time: 0.4939 data_time: 0.0026 memory: 8082 grad_norm: 814.0035 loss: 369.0675 loss_cls: 115.7488 loss_bbox: 118.0731 loss_dfl: 135.2457 +2024/03/21 06:05:49 - mmengine - INFO - Epoch(train) [69][300/925] lr: 3.4175e-05 eta: 1:30:23 time: 0.5075 data_time: 0.0026 memory: 8042 grad_norm: 775.8115 loss: 373.2630 loss_cls: 118.6445 loss_bbox: 119.0981 loss_dfl: 135.5204 +2024/03/21 06:06:13 - mmengine - INFO - Epoch(train) [69][350/925] lr: 3.4175e-05 eta: 1:29:58 time: 0.4875 data_time: 0.0026 memory: 7935 grad_norm: 769.8584 loss: 372.7599 loss_cls: 118.3266 loss_bbox: 119.3619 loss_dfl: 135.0715 +2024/03/21 06:06:39 - mmengine - INFO - Epoch(train) [69][400/925] lr: 3.4175e-05 eta: 1:29:33 time: 0.5085 data_time: 0.0026 memory: 8109 grad_norm: inf loss: 372.8620 loss_cls: 118.7283 loss_bbox: 117.7507 loss_dfl: 136.3829 +2024/03/21 06:07:04 - mmengine - INFO - Epoch(train) [69][450/925] lr: 3.4175e-05 eta: 1:29:08 time: 0.5012 data_time: 0.0025 memory: 7962 grad_norm: 814.8755 loss: 376.2546 loss_cls: 121.2777 loss_bbox: 118.9032 loss_dfl: 136.0738 +2024/03/21 06:07:29 - mmengine - INFO - Epoch(train) [69][500/925] lr: 3.4175e-05 eta: 1:28:43 time: 0.4939 data_time: 0.0023 memory: 7695 grad_norm: 734.1693 loss: 372.5337 loss_cls: 117.3349 loss_bbox: 119.1750 loss_dfl: 136.0238 +2024/03/21 06:07:54 - mmengine - INFO - Epoch(train) [69][550/925] lr: 3.4175e-05 eta: 1:28:17 time: 0.5046 data_time: 0.0026 memory: 7989 grad_norm: 754.0098 loss: 369.3209 loss_cls: 117.0866 loss_bbox: 117.0288 loss_dfl: 135.2055 +2024/03/21 06:08:19 - mmengine - INFO - Epoch(train) [69][600/925] lr: 3.4175e-05 eta: 1:27:52 time: 0.4935 data_time: 0.0028 memory: 7975 grad_norm: 762.8235 loss: 370.9759 loss_cls: 118.7647 loss_bbox: 117.2342 loss_dfl: 134.9770 +2024/03/21 06:08:44 - mmengine - INFO - Epoch(train) [69][650/925] lr: 3.4175e-05 eta: 1:27:27 time: 0.4986 data_time: 0.0026 memory: 8135 grad_norm: 793.4532 loss: 366.7951 loss_cls: 116.8711 loss_bbox: 115.6327 loss_dfl: 134.2914 +2024/03/21 06:09:09 - mmengine - INFO - Epoch(train) [69][700/925] lr: 3.4175e-05 eta: 1:27:02 time: 0.4955 data_time: 0.0026 memory: 7749 grad_norm: 787.7162 loss: 370.0241 loss_cls: 117.2824 loss_bbox: 116.9036 loss_dfl: 135.8381 +2024/03/21 06:09:33 - mmengine - INFO - Epoch(train) [69][750/925] lr: 3.4175e-05 eta: 1:26:37 time: 0.4916 data_time: 0.0027 memory: 7949 grad_norm: 751.8489 loss: 374.9888 loss_cls: 119.6695 loss_bbox: 119.4309 loss_dfl: 135.8884 +2024/03/21 06:09:59 - mmengine - INFO - Epoch(train) [69][800/925] lr: 3.4175e-05 eta: 1:26:12 time: 0.5167 data_time: 0.0025 memory: 7842 grad_norm: 770.3454 loss: 370.6180 loss_cls: 118.4078 loss_bbox: 117.8395 loss_dfl: 134.3707 +2024/03/21 06:10:23 - mmengine - INFO - Epoch(train) [69][850/925] lr: 3.4175e-05 eta: 1:25:46 time: 0.4811 data_time: 0.0028 memory: 8055 grad_norm: 750.6837 loss: 368.1873 loss_cls: 117.0553 loss_bbox: 115.7714 loss_dfl: 135.3606 +2024/03/21 06:10:48 - mmengine - INFO - Epoch(train) [69][900/925] lr: 3.4175e-05 eta: 1:25:21 time: 0.4977 data_time: 0.0027 memory: 8069 grad_norm: 786.0850 loss: 370.8288 loss_cls: 118.3559 loss_bbox: 117.9950 loss_dfl: 134.4779 +2024/03/21 06:11:01 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:11:03 - mmengine - INFO - Epoch(val) [69][ 50/625] eta: 0:00:20 time: 0.0363 data_time: 0.0007 memory: 7655 +2024/03/21 06:11:05 - mmengine - INFO - Epoch(val) [69][100/625] eta: 0:00:19 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:07 - mmengine - INFO - Epoch(val) [69][150/625] eta: 0:00:17 time: 0.0370 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:08 - mmengine - INFO - Epoch(val) [69][200/625] eta: 0:00:15 time: 0.0356 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:10 - mmengine - INFO - Epoch(val) [69][250/625] eta: 0:00:13 time: 0.0343 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:12 - mmengine - INFO - Epoch(val) [69][300/625] eta: 0:00:11 time: 0.0340 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:14 - mmengine - INFO - Epoch(val) [69][350/625] eta: 0:00:09 time: 0.0344 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:15 - mmengine - INFO - Epoch(val) [69][400/625] eta: 0:00:08 time: 0.0364 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:17 - mmengine - INFO - Epoch(val) [69][450/625] eta: 0:00:06 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:19 - mmengine - INFO - Epoch(val) [69][500/625] eta: 0:00:04 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:21 - mmengine - INFO - Epoch(val) [69][550/625] eta: 0:00:02 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/21 06:11:23 - mmengine - INFO - Epoch(val) [69][600/625] eta: 0:00:00 time: 0.0365 data_time: 0.0008 memory: 1244 +2024/03/21 06:11:35 - mmengine - INFO - Evaluating bbox... +2024/03/21 06:12:44 - mmengine - INFO - bbox_mAP_copypaste: 0.506 0.673 0.551 0.328 0.557 0.669 +2024/03/21 06:12:46 - mmengine - INFO - Epoch(val) [69][625/625] coco/bbox_mAP: 0.5060 coco/bbox_mAP_50: 0.6730 coco/bbox_mAP_75: 0.5510 coco/bbox_mAP_s: 0.3280 coco/bbox_mAP_m: 0.5570 coco/bbox_mAP_l: 0.6690 data_time: 0.0003 time: 0.0356 +2024/03/21 06:13:16 - mmengine - INFO - Epoch(train) [70][ 50/925] lr: 3.1700e-05 eta: 1:24:44 time: 0.5817 data_time: 0.0770 memory: 8109 grad_norm: 767.1607 loss: 368.8622 loss_cls: 116.3478 loss_bbox: 117.2769 loss_dfl: 135.2374 +2024/03/21 06:13:40 - mmengine - INFO - Epoch(train) [70][100/925] lr: 3.1700e-05 eta: 1:24:19 time: 0.4935 data_time: 0.0025 memory: 8202 grad_norm: 801.9683 loss: 377.5260 loss_cls: 121.6917 loss_bbox: 120.5238 loss_dfl: 135.3106 +2024/03/21 06:14:05 - mmengine - INFO - Epoch(train) [70][150/925] lr: 3.1700e-05 eta: 1:23:54 time: 0.5008 data_time: 0.0026 memory: 8042 grad_norm: 756.8338 loss: 369.5515 loss_cls: 117.4633 loss_bbox: 117.2163 loss_dfl: 134.8719 +2024/03/21 06:14:18 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:14:30 - mmengine - INFO - Epoch(train) [70][200/925] lr: 3.1700e-05 eta: 1:23:29 time: 0.5010 data_time: 0.0027 memory: 7842 grad_norm: 767.5465 loss: 370.2090 loss_cls: 117.5629 loss_bbox: 117.7963 loss_dfl: 134.8498 +2024/03/21 06:14:55 - mmengine - INFO - Epoch(train) [70][250/925] lr: 3.1700e-05 eta: 1:23:04 time: 0.4976 data_time: 0.0026 memory: 8135 grad_norm: 785.0905 loss: 366.5318 loss_cls: 114.1136 loss_bbox: 117.4705 loss_dfl: 134.9477 +2024/03/21 06:15:21 - mmengine - INFO - Epoch(train) [70][300/925] lr: 3.1700e-05 eta: 1:22:39 time: 0.5164 data_time: 0.0025 memory: 7962 grad_norm: 782.0138 loss: 370.2690 loss_cls: 117.6895 loss_bbox: 116.9005 loss_dfl: 135.6790 +2024/03/21 06:15:46 - mmengine - INFO - Epoch(train) [70][350/925] lr: 3.1700e-05 eta: 1:22:14 time: 0.5010 data_time: 0.0027 memory: 7789 grad_norm: 786.0586 loss: 372.5237 loss_cls: 119.2114 loss_bbox: 117.6762 loss_dfl: 135.6360 +2024/03/21 06:16:11 - mmengine - INFO - Epoch(train) [70][400/925] lr: 3.1700e-05 eta: 1:21:48 time: 0.4973 data_time: 0.0026 memory: 8002 grad_norm: 754.6764 loss: 375.5702 loss_cls: 119.7916 loss_bbox: 119.5767 loss_dfl: 136.2018 +2024/03/21 06:16:38 - mmengine - INFO - Epoch(train) [70][450/925] lr: 3.1700e-05 eta: 1:21:24 time: 0.5347 data_time: 0.0026 memory: 7935 grad_norm: 797.4395 loss: 371.8640 loss_cls: 118.0850 loss_bbox: 117.5905 loss_dfl: 136.1886 +2024/03/21 06:17:02 - mmengine - INFO - Epoch(train) [70][500/925] lr: 3.1700e-05 eta: 1:20:58 time: 0.4888 data_time: 0.0027 memory: 7949 grad_norm: 829.2303 loss: 373.1063 loss_cls: 117.3756 loss_bbox: 120.4445 loss_dfl: 135.2862 +2024/03/21 06:17:28 - mmengine - INFO - Epoch(train) [70][550/925] lr: 3.1700e-05 eta: 1:20:33 time: 0.5162 data_time: 0.0028 memory: 8015 grad_norm: 738.0654 loss: 374.6005 loss_cls: 121.2226 loss_bbox: 117.4008 loss_dfl: 135.9771 +2024/03/21 06:17:54 - mmengine - INFO - Epoch(train) [70][600/925] lr: 3.1700e-05 eta: 1:20:08 time: 0.5181 data_time: 0.0027 memory: 8242 grad_norm: 772.9630 loss: 372.1986 loss_cls: 118.6654 loss_bbox: 118.8073 loss_dfl: 134.7259 +2024/03/21 06:18:20 - mmengine - INFO - Epoch(train) [70][650/925] lr: 3.1700e-05 eta: 1:19:43 time: 0.5045 data_time: 0.0026 memory: 8069 grad_norm: 832.8164 loss: 364.6206 loss_cls: 114.3748 loss_bbox: 115.2280 loss_dfl: 135.0179 +2024/03/21 06:18:46 - mmengine - INFO - Epoch(train) [70][700/925] lr: 3.1700e-05 eta: 1:19:18 time: 0.5213 data_time: 0.0027 memory: 7975 grad_norm: 773.6996 loss: 369.5133 loss_cls: 116.5128 loss_bbox: 117.5975 loss_dfl: 135.4030 +2024/03/21 06:19:11 - mmengine - INFO - Epoch(train) [70][750/925] lr: 3.1700e-05 eta: 1:18:53 time: 0.5157 data_time: 0.0027 memory: 7855 grad_norm: 790.1456 loss: 372.2671 loss_cls: 119.7759 loss_bbox: 118.5799 loss_dfl: 133.9113 +2024/03/21 06:19:37 - mmengine - INFO - Epoch(train) [70][800/925] lr: 3.1700e-05 eta: 1:18:28 time: 0.5017 data_time: 0.0026 memory: 7829 grad_norm: 788.8895 loss: 365.5217 loss_cls: 116.4945 loss_bbox: 115.2216 loss_dfl: 133.8057 +2024/03/21 06:20:03 - mmengine - INFO - Epoch(train) [70][850/925] lr: 3.1700e-05 eta: 1:18:03 time: 0.5275 data_time: 0.0026 memory: 7722 grad_norm: 788.6812 loss: 369.8229 loss_cls: 118.7262 loss_bbox: 115.6884 loss_dfl: 135.4084 +2024/03/21 06:20:28 - mmengine - INFO - Epoch(train) [70][900/925] lr: 3.1700e-05 eta: 1:17:38 time: 0.5018 data_time: 0.0026 memory: 7882 grad_norm: 760.2433 loss: 367.0798 loss_cls: 115.7099 loss_bbox: 116.5875 loss_dfl: 134.7825 +2024/03/21 06:20:40 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:20:41 - mmengine - INFO - Saving checkpoint at 70 epochs +2024/03/21 06:20:50 - mmengine - INFO - Epoch(val) [70][ 50/625] eta: 0:00:20 time: 0.0356 data_time: 0.0008 memory: 7935 +2024/03/21 06:20:51 - mmengine - INFO - Epoch(val) [70][100/625] eta: 0:00:18 time: 0.0354 data_time: 0.0004 memory: 1244 +2024/03/21 06:20:53 - mmengine - INFO - Epoch(val) [70][150/625] eta: 0:00:16 time: 0.0361 data_time: 0.0003 memory: 1244 +2024/03/21 06:20:55 - mmengine - INFO - Epoch(val) [70][200/625] eta: 0:00:15 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 06:20:57 - mmengine - INFO - Epoch(val) [70][250/625] eta: 0:00:13 time: 0.0357 data_time: 0.0004 memory: 1244 +2024/03/21 06:20:59 - mmengine - INFO - Epoch(val) [70][300/625] eta: 0:00:11 time: 0.0353 data_time: 0.0003 memory: 1244 +2024/03/21 06:21:00 - mmengine - INFO - Epoch(val) [70][350/625] eta: 0:00:09 time: 0.0361 data_time: 0.0003 memory: 1244 +2024/03/21 06:21:02 - mmengine - INFO - Epoch(val) [70][400/625] eta: 0:00:08 time: 0.0353 data_time: 0.0003 memory: 1244 +2024/03/21 06:21:04 - mmengine - INFO - Epoch(val) [70][450/625] eta: 0:00:06 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 06:21:05 - mmengine - INFO - Epoch(val) [70][500/625] eta: 0:00:04 time: 0.0282 data_time: 0.0002 memory: 1244 +2024/03/21 06:21:07 - mmengine - INFO - Epoch(val) [70][550/625] eta: 0:00:02 time: 0.0309 data_time: 0.0002 memory: 1244 +2024/03/21 06:21:08 - mmengine - INFO - Epoch(val) [70][600/625] eta: 0:00:00 time: 0.0303 data_time: 0.0002 memory: 1244 +2024/03/21 06:21:21 - mmengine - INFO - Evaluating bbox... +2024/03/21 06:22:32 - mmengine - INFO - bbox_mAP_copypaste: 0.506 0.673 0.552 0.326 0.557 0.670 +2024/03/21 06:22:34 - mmengine - INFO - Epoch(val) [70][625/625] coco/bbox_mAP: 0.5060 coco/bbox_mAP_50: 0.6730 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3260 coco/bbox_mAP_m: 0.5570 coco/bbox_mAP_l: 0.6700 data_time: 0.0002 time: 0.0304 +2024/03/21 06:22:34 - mmengine - INFO - Switch pipeline now! +2024/03/21 06:23:00 - mmengine - INFO - Epoch(train) [71][ 50/925] lr: 2.9225e-05 eta: 1:17:01 time: 0.5159 data_time: 0.0448 memory: 7429 grad_norm: nan loss: 358.9343 loss_cls: 106.3419 loss_bbox: 115.2370 loss_dfl: 137.3553 +2024/03/21 06:23:25 - mmengine - INFO - Epoch(train) [71][100/925] lr: 2.9225e-05 eta: 1:16:35 time: 0.4887 data_time: 0.0022 memory: 7309 grad_norm: 1429.8929 loss: 350.3112 loss_cls: 104.5150 loss_bbox: 109.9789 loss_dfl: 135.8173 +2024/03/21 06:23:49 - mmengine - INFO - Epoch(train) [71][150/925] lr: 2.9225e-05 eta: 1:16:10 time: 0.4841 data_time: 0.0022 memory: 7895 grad_norm: 1462.9293 loss: 356.0443 loss_cls: 103.8786 loss_bbox: 116.1672 loss_dfl: 135.9985 +2024/03/21 06:24:13 - mmengine - INFO - Epoch(train) [71][200/925] lr: 2.9225e-05 eta: 1:15:45 time: 0.4829 data_time: 0.0023 memory: 7362 grad_norm: 1507.0978 loss: 347.0439 loss_cls: 103.0745 loss_bbox: 110.3488 loss_dfl: 133.6206 +2024/03/21 06:24:37 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:24:37 - mmengine - INFO - Epoch(train) [71][250/925] lr: 2.9225e-05 eta: 1:15:20 time: 0.4842 data_time: 0.0022 memory: 7429 grad_norm: 1492.3286 loss: 352.6461 loss_cls: 103.3818 loss_bbox: 114.0831 loss_dfl: 135.1812 +2024/03/21 06:25:02 - mmengine - INFO - Epoch(train) [71][300/925] lr: 2.9225e-05 eta: 1:14:54 time: 0.4830 data_time: 0.0023 memory: 7335 grad_norm: 1421.1702 loss: 346.7531 loss_cls: 102.1362 loss_bbox: 111.3615 loss_dfl: 133.2554 +2024/03/21 06:25:26 - mmengine - INFO - Epoch(train) [71][350/925] lr: 2.9225e-05 eta: 1:14:29 time: 0.4857 data_time: 0.0024 memory: 7442 grad_norm: 1364.3211 loss: 341.6670 loss_cls: 97.5372 loss_bbox: 109.2089 loss_dfl: 134.9209 +2024/03/21 06:25:50 - mmengine - INFO - Epoch(train) [71][400/925] lr: 2.9225e-05 eta: 1:14:04 time: 0.4862 data_time: 0.0025 memory: 7469 grad_norm: 1446.9662 loss: 353.9188 loss_cls: 102.2711 loss_bbox: 116.3751 loss_dfl: 135.2726 +2024/03/21 06:26:15 - mmengine - INFO - Epoch(train) [71][450/925] lr: 2.9225e-05 eta: 1:13:39 time: 0.4893 data_time: 0.0024 memory: 7615 grad_norm: 1387.9025 loss: 351.1261 loss_cls: 104.7947 loss_bbox: 111.6347 loss_dfl: 134.6967 +2024/03/21 06:26:39 - mmengine - INFO - Epoch(train) [71][500/925] lr: 2.9225e-05 eta: 1:13:14 time: 0.4871 data_time: 0.0023 memory: 7282 grad_norm: 1452.6167 loss: 352.7235 loss_cls: 102.3935 loss_bbox: 113.5038 loss_dfl: 136.8262 +2024/03/21 06:27:03 - mmengine - INFO - Epoch(train) [71][550/925] lr: 2.9225e-05 eta: 1:12:48 time: 0.4812 data_time: 0.0021 memory: 7482 grad_norm: 1407.6416 loss: 349.7440 loss_cls: 102.0836 loss_bbox: 112.0194 loss_dfl: 135.6409 +2024/03/21 06:27:27 - mmengine - INFO - Epoch(train) [71][600/925] lr: 2.9225e-05 eta: 1:12:23 time: 0.4844 data_time: 0.0024 memory: 7282 grad_norm: 1349.4221 loss: 341.9087 loss_cls: 100.0059 loss_bbox: 108.9491 loss_dfl: 132.9536 +2024/03/21 06:27:52 - mmengine - INFO - Epoch(train) [71][650/925] lr: 2.9225e-05 eta: 1:11:58 time: 0.4823 data_time: 0.0025 memory: 7335 grad_norm: 1283.2155 loss: 348.7126 loss_cls: 102.0752 loss_bbox: 110.6604 loss_dfl: 135.9770 +2024/03/21 06:28:16 - mmengine - INFO - Epoch(train) [71][700/925] lr: 2.9225e-05 eta: 1:11:33 time: 0.4881 data_time: 0.0023 memory: 7375 grad_norm: 1268.5234 loss: 358.7943 loss_cls: 105.9019 loss_bbox: 115.4668 loss_dfl: 137.4255 +2024/03/21 06:28:41 - mmengine - INFO - Epoch(train) [71][750/925] lr: 2.9225e-05 eta: 1:11:07 time: 0.4926 data_time: 0.0023 memory: 7402 grad_norm: 1242.9373 loss: 347.0451 loss_cls: 101.7550 loss_bbox: 110.4724 loss_dfl: 134.8177 +2024/03/21 06:29:04 - mmengine - INFO - Epoch(train) [71][800/925] lr: 2.9225e-05 eta: 1:10:42 time: 0.4728 data_time: 0.0024 memory: 7522 grad_norm: 1214.8131 loss: 347.2390 loss_cls: 101.7532 loss_bbox: 110.3539 loss_dfl: 135.1318 +2024/03/21 06:29:29 - mmengine - INFO - Epoch(train) [71][850/925] lr: 2.9225e-05 eta: 1:10:17 time: 0.4848 data_time: 0.0023 memory: 7442 grad_norm: 1238.2660 loss: 347.6973 loss_cls: 101.4952 loss_bbox: 110.0662 loss_dfl: 136.1359 +2024/03/21 06:29:54 - mmengine - INFO - Epoch(train) [71][900/925] lr: 2.9225e-05 eta: 1:09:52 time: 0.4975 data_time: 0.0021 memory: 7349 grad_norm: 1288.7724 loss: 347.2498 loss_cls: 100.9489 loss_bbox: 111.7842 loss_dfl: 134.5167 +2024/03/21 06:30:05 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:30:07 - mmengine - INFO - Epoch(val) [71][ 50/625] eta: 0:00:20 time: 0.0357 data_time: 0.0008 memory: 7362 +2024/03/21 06:30:09 - mmengine - INFO - Epoch(val) [71][100/625] eta: 0:00:18 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:11 - mmengine - INFO - Epoch(val) [71][150/625] eta: 0:00:16 time: 0.0364 data_time: 0.0004 memory: 1244 +2024/03/21 06:30:12 - mmengine - INFO - Epoch(val) [71][200/625] eta: 0:00:15 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:14 - mmengine - INFO - Epoch(val) [71][250/625] eta: 0:00:13 time: 0.0355 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:16 - mmengine - INFO - Epoch(val) [71][300/625] eta: 0:00:11 time: 0.0371 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:18 - mmengine - INFO - Epoch(val) [71][350/625] eta: 0:00:09 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:20 - mmengine - INFO - Epoch(val) [71][400/625] eta: 0:00:08 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:21 - mmengine - INFO - Epoch(val) [71][450/625] eta: 0:00:06 time: 0.0372 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:23 - mmengine - INFO - Epoch(val) [71][500/625] eta: 0:00:04 time: 0.0368 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:25 - mmengine - INFO - Epoch(val) [71][550/625] eta: 0:00:02 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:27 - mmengine - INFO - Epoch(val) [71][600/625] eta: 0:00:00 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 06:30:38 - mmengine - INFO - Evaluating bbox... +2024/03/21 06:31:47 - mmengine - INFO - bbox_mAP_copypaste: 0.506 0.673 0.551 0.326 0.557 0.668 +2024/03/21 06:31:49 - mmengine - INFO - Epoch(val) [71][625/625] coco/bbox_mAP: 0.5060 coco/bbox_mAP_50: 0.6730 coco/bbox_mAP_75: 0.5510 coco/bbox_mAP_s: 0.3260 coco/bbox_mAP_m: 0.5570 coco/bbox_mAP_l: 0.6680 data_time: 0.0003 time: 0.0345 +2024/03/21 06:32:15 - mmengine - INFO - Epoch(train) [72][ 50/925] lr: 2.6750e-05 eta: 1:09:14 time: 0.5098 data_time: 0.0486 memory: 7309 grad_norm: 1211.4374 loss: 350.2363 loss_cls: 102.3805 loss_bbox: 112.2351 loss_dfl: 135.6207 +2024/03/21 06:32:39 - mmengine - INFO - Epoch(train) [72][100/925] lr: 2.6750e-05 eta: 1:08:49 time: 0.4841 data_time: 0.0024 memory: 7402 grad_norm: 1203.3158 loss: 349.0336 loss_cls: 100.8720 loss_bbox: 112.6382 loss_dfl: 135.5234 +2024/03/21 06:33:03 - mmengine - INFO - Epoch(train) [72][150/925] lr: 2.6750e-05 eta: 1:08:24 time: 0.4742 data_time: 0.0023 memory: 7562 grad_norm: 1151.4295 loss: 355.2349 loss_cls: 103.8978 loss_bbox: 114.3085 loss_dfl: 137.0286 +2024/03/21 06:33:25 - mmengine - INFO - Epoch(train) [72][200/925] lr: 2.6750e-05 eta: 1:07:58 time: 0.4556 data_time: 0.0024 memory: 7402 grad_norm: 1267.8978 loss: 347.8549 loss_cls: 100.6201 loss_bbox: 111.8255 loss_dfl: 135.4093 +2024/03/21 06:33:51 - mmengine - INFO - Epoch(train) [72][250/925] lr: 2.6750e-05 eta: 1:07:33 time: 0.5184 data_time: 0.0023 memory: 7309 grad_norm: 1224.7422 loss: 338.5183 loss_cls: 96.3670 loss_bbox: 109.8025 loss_dfl: 132.3489 +2024/03/21 06:34:15 - mmengine - INFO - Epoch(train) [72][300/925] lr: 2.6750e-05 eta: 1:07:08 time: 0.4700 data_time: 0.0023 memory: 7389 grad_norm: 1166.9768 loss: 344.9459 loss_cls: 100.8954 loss_bbox: 109.9790 loss_dfl: 134.0715 +2024/03/21 06:34:28 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:34:39 - mmengine - INFO - Epoch(train) [72][350/925] lr: 2.6750e-05 eta: 1:06:43 time: 0.4881 data_time: 0.0024 memory: 7402 grad_norm: 1226.0175 loss: 351.7678 loss_cls: 102.5771 loss_bbox: 113.2217 loss_dfl: 135.9691 +2024/03/21 06:35:05 - mmengine - INFO - Epoch(train) [72][400/925] lr: 2.6750e-05 eta: 1:06:18 time: 0.5018 data_time: 0.0023 memory: 7469 grad_norm: 1237.7831 loss: 350.1601 loss_cls: 103.1075 loss_bbox: 112.7252 loss_dfl: 134.3274 +2024/03/21 06:35:29 - mmengine - INFO - Epoch(train) [72][450/925] lr: 2.6750e-05 eta: 1:05:52 time: 0.4814 data_time: 0.0023 memory: 7549 grad_norm: 1150.4683 loss: 343.1954 loss_cls: 100.0326 loss_bbox: 109.9963 loss_dfl: 133.1665 +2024/03/21 06:35:53 - mmengine - INFO - Epoch(train) [72][500/925] lr: 2.6750e-05 eta: 1:05:27 time: 0.4848 data_time: 0.0022 memory: 7629 grad_norm: 1218.1121 loss: 349.8521 loss_cls: 100.0230 loss_bbox: 113.9012 loss_dfl: 135.9279 +2024/03/21 06:36:17 - mmengine - INFO - Epoch(train) [72][550/925] lr: 2.6750e-05 eta: 1:05:02 time: 0.4890 data_time: 0.0024 memory: 7442 grad_norm: 1261.3131 loss: 352.1292 loss_cls: 104.3520 loss_bbox: 112.5748 loss_dfl: 135.2025 +2024/03/21 06:36:41 - mmengine - INFO - Epoch(train) [72][600/925] lr: 2.6750e-05 eta: 1:04:37 time: 0.4775 data_time: 0.0024 memory: 7429 grad_norm: 1187.9854 loss: 348.3546 loss_cls: 101.4066 loss_bbox: 112.0074 loss_dfl: 134.9407 +2024/03/21 06:37:07 - mmengine - INFO - Epoch(train) [72][650/925] lr: 2.6750e-05 eta: 1:04:12 time: 0.5042 data_time: 0.0023 memory: 7322 grad_norm: 1147.4333 loss: 351.4166 loss_cls: 104.2113 loss_bbox: 111.3083 loss_dfl: 135.8970 +2024/03/21 06:37:32 - mmengine - INFO - Epoch(train) [72][700/925] lr: 2.6750e-05 eta: 1:03:47 time: 0.4982 data_time: 0.0019 memory: 7429 grad_norm: 1286.9233 loss: 343.8751 loss_cls: 99.2161 loss_bbox: 108.9145 loss_dfl: 135.7445 +2024/03/21 06:37:55 - mmengine - INFO - Epoch(train) [72][750/925] lr: 2.6750e-05 eta: 1:03:21 time: 0.4765 data_time: 0.0024 memory: 7482 grad_norm: 1198.1173 loss: 347.0157 loss_cls: 101.3670 loss_bbox: 111.1090 loss_dfl: 134.5396 +2024/03/21 06:38:21 - mmengine - INFO - Epoch(train) [72][800/925] lr: 2.6750e-05 eta: 1:02:56 time: 0.5100 data_time: 0.0025 memory: 7749 grad_norm: 1200.5376 loss: 346.6831 loss_cls: 100.9715 loss_bbox: 111.1792 loss_dfl: 134.5324 +2024/03/21 06:38:45 - mmengine - INFO - Epoch(train) [72][850/925] lr: 2.6750e-05 eta: 1:02:31 time: 0.4772 data_time: 0.0024 memory: 7375 grad_norm: 1207.1129 loss: 345.7201 loss_cls: 99.2005 loss_bbox: 112.6311 loss_dfl: 133.8885 +2024/03/21 06:39:09 - mmengine - INFO - Epoch(train) [72][900/925] lr: 2.6750e-05 eta: 1:02:06 time: 0.4850 data_time: 0.0024 memory: 7415 grad_norm: 1187.9043 loss: 345.2210 loss_cls: 100.4322 loss_bbox: 110.3197 loss_dfl: 134.4690 +2024/03/21 06:39:22 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:39:24 - mmengine - INFO - Epoch(val) [72][ 50/625] eta: 0:00:20 time: 0.0356 data_time: 0.0007 memory: 7442 +2024/03/21 06:39:26 - mmengine - INFO - Epoch(val) [72][100/625] eta: 0:00:18 time: 0.0344 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:27 - mmengine - INFO - Epoch(val) [72][150/625] eta: 0:00:16 time: 0.0335 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:29 - mmengine - INFO - Epoch(val) [72][200/625] eta: 0:00:14 time: 0.0343 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:31 - mmengine - INFO - Epoch(val) [72][250/625] eta: 0:00:12 time: 0.0347 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:33 - mmengine - INFO - Epoch(val) [72][300/625] eta: 0:00:11 time: 0.0356 data_time: 0.0004 memory: 1244 +2024/03/21 06:39:34 - mmengine - INFO - Epoch(val) [72][350/625] eta: 0:00:09 time: 0.0352 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:36 - mmengine - INFO - Epoch(val) [72][400/625] eta: 0:00:07 time: 0.0362 data_time: 0.0004 memory: 1244 +2024/03/21 06:39:38 - mmengine - INFO - Epoch(val) [72][450/625] eta: 0:00:06 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:40 - mmengine - INFO - Epoch(val) [72][500/625] eta: 0:00:04 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:41 - mmengine - INFO - Epoch(val) [72][550/625] eta: 0:00:02 time: 0.0344 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:43 - mmengine - INFO - Epoch(val) [72][600/625] eta: 0:00:00 time: 0.0359 data_time: 0.0003 memory: 1244 +2024/03/21 06:39:55 - mmengine - INFO - Evaluating bbox... +2024/03/21 06:41:03 - mmengine - INFO - bbox_mAP_copypaste: 0.506 0.674 0.552 0.326 0.558 0.670 +2024/03/21 06:41:05 - mmengine - INFO - Epoch(val) [72][625/625] coco/bbox_mAP: 0.5060 coco/bbox_mAP_50: 0.6740 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3260 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6700 data_time: 0.0003 time: 0.0356 +2024/03/21 06:41:31 - mmengine - INFO - Epoch(train) [73][ 50/925] lr: 2.4275e-05 eta: 1:01:28 time: 0.5262 data_time: 0.0511 memory: 7322 grad_norm: 1139.6654 loss: 347.1740 loss_cls: 101.6769 loss_bbox: 110.8004 loss_dfl: 134.6967 +2024/03/21 06:41:55 - mmengine - INFO - Epoch(train) [73][100/925] lr: 2.4275e-05 eta: 1:01:03 time: 0.4722 data_time: 0.0025 memory: 7375 grad_norm: 1216.4549 loss: 345.8514 loss_cls: 99.1514 loss_bbox: 113.7231 loss_dfl: 132.9769 +2024/03/21 06:42:19 - mmengine - INFO - Epoch(train) [73][150/925] lr: 2.4275e-05 eta: 1:00:38 time: 0.4785 data_time: 0.0024 memory: 7455 grad_norm: 1126.4282 loss: 344.7126 loss_cls: 99.9427 loss_bbox: 110.5918 loss_dfl: 134.1782 +2024/03/21 06:42:43 - mmengine - INFO - Epoch(train) [73][200/925] lr: 2.4275e-05 eta: 1:00:13 time: 0.4738 data_time: 0.0024 memory: 7535 grad_norm: 1174.4321 loss: 351.9915 loss_cls: 100.9650 loss_bbox: 114.8542 loss_dfl: 136.1723 +2024/03/21 06:43:07 - mmengine - INFO - Epoch(train) [73][250/925] lr: 2.4275e-05 eta: 0:59:47 time: 0.4817 data_time: 0.0023 memory: 7322 grad_norm: 1216.5624 loss: 348.5418 loss_cls: 101.0795 loss_bbox: 111.7619 loss_dfl: 135.7004 +2024/03/21 06:43:32 - mmengine - INFO - Epoch(train) [73][300/925] lr: 2.4275e-05 eta: 0:59:22 time: 0.4969 data_time: 0.0025 memory: 7322 grad_norm: 1222.2542 loss: 344.6616 loss_cls: 99.3223 loss_bbox: 110.1334 loss_dfl: 135.2058 +2024/03/21 06:43:56 - mmengine - INFO - Epoch(train) [73][350/925] lr: 2.4275e-05 eta: 0:58:57 time: 0.4792 data_time: 0.0025 memory: 7429 grad_norm: 1131.7053 loss: 347.6120 loss_cls: 100.7610 loss_bbox: 111.4606 loss_dfl: 135.3904 +2024/03/21 06:44:21 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:44:21 - mmengine - INFO - Epoch(train) [73][400/925] lr: 2.4275e-05 eta: 0:58:32 time: 0.4954 data_time: 0.0024 memory: 7589 grad_norm: 1129.0609 loss: 344.1462 loss_cls: 99.4617 loss_bbox: 110.3951 loss_dfl: 134.2894 +2024/03/21 06:44:46 - mmengine - INFO - Epoch(train) [73][450/925] lr: 2.4275e-05 eta: 0:58:07 time: 0.4976 data_time: 0.0024 memory: 7589 grad_norm: 1153.8399 loss: 343.7977 loss_cls: 99.7705 loss_bbox: 109.5104 loss_dfl: 134.5168 +2024/03/21 06:45:10 - mmengine - INFO - Epoch(train) [73][500/925] lr: 2.4275e-05 eta: 0:57:42 time: 0.4789 data_time: 0.0024 memory: 7375 grad_norm: 1104.3040 loss: 348.3216 loss_cls: 100.7416 loss_bbox: 111.7477 loss_dfl: 135.8323 +2024/03/21 06:45:34 - mmengine - INFO - Epoch(train) [73][550/925] lr: 2.4275e-05 eta: 0:57:17 time: 0.4952 data_time: 0.0024 memory: 7495 grad_norm: 1174.1933 loss: 346.6100 loss_cls: 98.9222 loss_bbox: 112.2960 loss_dfl: 135.3917 +2024/03/21 06:45:59 - mmengine - INFO - Epoch(train) [73][600/925] lr: 2.4275e-05 eta: 0:56:51 time: 0.4969 data_time: 0.0024 memory: 7469 grad_norm: 1225.6175 loss: 347.5553 loss_cls: 99.9544 loss_bbox: 110.8730 loss_dfl: 136.7279 +2024/03/21 06:46:24 - mmengine - INFO - Epoch(train) [73][650/925] lr: 2.4275e-05 eta: 0:56:26 time: 0.4859 data_time: 0.0025 memory: 7402 grad_norm: 1181.9647 loss: 349.1396 loss_cls: 100.0286 loss_bbox: 113.0190 loss_dfl: 136.0921 +2024/03/21 06:46:49 - mmengine - INFO - Epoch(train) [73][700/925] lr: 2.4275e-05 eta: 0:56:01 time: 0.5016 data_time: 0.0022 memory: 7242 grad_norm: 1155.1015 loss: 349.6300 loss_cls: 102.6820 loss_bbox: 110.9902 loss_dfl: 135.9578 +2024/03/21 06:47:13 - mmengine - INFO - Epoch(train) [73][750/925] lr: 2.4275e-05 eta: 0:55:36 time: 0.4844 data_time: 0.0023 memory: 7482 grad_norm: 1123.1839 loss: 347.8273 loss_cls: 100.9770 loss_bbox: 112.6615 loss_dfl: 134.1888 +2024/03/21 06:47:37 - mmengine - INFO - Epoch(train) [73][800/925] lr: 2.4275e-05 eta: 0:55:11 time: 0.4771 data_time: 0.0022 memory: 7335 grad_norm: 1174.6743 loss: 351.8125 loss_cls: 101.6106 loss_bbox: 114.6826 loss_dfl: 135.5194 +2024/03/21 06:48:02 - mmengine - INFO - Epoch(train) [73][850/925] lr: 2.4275e-05 eta: 0:54:46 time: 0.5068 data_time: 0.0023 memory: 7349 grad_norm: 1272.4353 loss: 345.5169 loss_cls: 100.1093 loss_bbox: 109.5504 loss_dfl: 135.8572 +2024/03/21 06:48:26 - mmengine - INFO - Epoch(train) [73][900/925] lr: 2.4275e-05 eta: 0:54:20 time: 0.4698 data_time: 0.0025 memory: 7575 grad_norm: 1230.1691 loss: 344.9253 loss_cls: 100.6933 loss_bbox: 109.6427 loss_dfl: 134.5894 +2024/03/21 06:48:38 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:48:40 - mmengine - INFO - Epoch(val) [73][ 50/625] eta: 0:00:20 time: 0.0353 data_time: 0.0008 memory: 7215 +2024/03/21 06:48:42 - mmengine - INFO - Epoch(val) [73][100/625] eta: 0:00:18 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:44 - mmengine - INFO - Epoch(val) [73][150/625] eta: 0:00:17 time: 0.0374 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:46 - mmengine - INFO - Epoch(val) [73][200/625] eta: 0:00:15 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:47 - mmengine - INFO - Epoch(val) [73][250/625] eta: 0:00:13 time: 0.0371 data_time: 0.0004 memory: 1244 +2024/03/21 06:48:49 - mmengine - INFO - Epoch(val) [73][300/625] eta: 0:00:11 time: 0.0338 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:51 - mmengine - INFO - Epoch(val) [73][350/625] eta: 0:00:09 time: 0.0355 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:53 - mmengine - INFO - Epoch(val) [73][400/625] eta: 0:00:08 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:55 - mmengine - INFO - Epoch(val) [73][450/625] eta: 0:00:06 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:56 - mmengine - INFO - Epoch(val) [73][500/625] eta: 0:00:04 time: 0.0361 data_time: 0.0003 memory: 1244 +2024/03/21 06:48:58 - mmengine - INFO - Epoch(val) [73][550/625] eta: 0:00:02 time: 0.0347 data_time: 0.0003 memory: 1244 +2024/03/21 06:49:00 - mmengine - INFO - Epoch(val) [73][600/625] eta: 0:00:00 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 06:49:11 - mmengine - INFO - Evaluating bbox... +2024/03/21 06:50:13 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.674 0.552 0.326 0.558 0.670 +2024/03/21 06:50:14 - mmengine - INFO - Epoch(val) [73][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6740 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3260 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6700 data_time: 0.0003 time: 0.0355 +2024/03/21 06:50:41 - mmengine - INFO - Epoch(train) [74][ 50/925] lr: 2.1800e-05 eta: 0:53:43 time: 0.5274 data_time: 0.0386 memory: 7549 grad_norm: 1146.3706 loss: 346.8953 loss_cls: 100.1391 loss_bbox: 111.0095 loss_dfl: 135.7466 +2024/03/21 06:51:05 - mmengine - INFO - Epoch(train) [74][100/925] lr: 2.1800e-05 eta: 0:53:18 time: 0.4807 data_time: 0.0022 memory: 7442 grad_norm: 1244.4157 loss: 340.7838 loss_cls: 98.5684 loss_bbox: 108.6920 loss_dfl: 133.5234 +2024/03/21 06:51:28 - mmengine - INFO - Epoch(train) [74][150/925] lr: 2.1800e-05 eta: 0:52:52 time: 0.4644 data_time: 0.0024 memory: 7602 grad_norm: 1206.7883 loss: 354.4277 loss_cls: 105.2934 loss_bbox: 112.9135 loss_dfl: 136.2208 +2024/03/21 06:51:53 - mmengine - INFO - Epoch(train) [74][200/925] lr: 2.1800e-05 eta: 0:52:27 time: 0.4881 data_time: 0.0023 memory: 7469 grad_norm: 1124.4169 loss: 347.7048 loss_cls: 100.8458 loss_bbox: 111.3115 loss_dfl: 135.5475 +2024/03/21 06:52:16 - mmengine - INFO - Epoch(train) [74][250/925] lr: 2.1800e-05 eta: 0:52:02 time: 0.4665 data_time: 0.0023 memory: 7469 grad_norm: 1101.7529 loss: 340.1804 loss_cls: 97.0584 loss_bbox: 110.2574 loss_dfl: 132.8647 +2024/03/21 06:52:40 - mmengine - INFO - Epoch(train) [74][300/925] lr: 2.1800e-05 eta: 0:51:37 time: 0.4798 data_time: 0.0024 memory: 7309 grad_norm: 1120.9450 loss: 346.5278 loss_cls: 100.4208 loss_bbox: 112.2529 loss_dfl: 133.8541 +2024/03/21 06:53:05 - mmengine - INFO - Epoch(train) [74][350/925] lr: 2.1800e-05 eta: 0:51:12 time: 0.4971 data_time: 0.0023 memory: 7762 grad_norm: 1113.7088 loss: 344.0794 loss_cls: 99.4798 loss_bbox: 111.1182 loss_dfl: 133.4814 +2024/03/21 06:53:28 - mmengine - INFO - Epoch(train) [74][400/925] lr: 2.1800e-05 eta: 0:50:47 time: 0.4710 data_time: 0.0023 memory: 7322 grad_norm: 1154.9490 loss: 341.0612 loss_cls: 98.9058 loss_bbox: 108.6416 loss_dfl: 133.5138 +2024/03/21 06:53:53 - mmengine - INFO - Epoch(train) [74][450/925] lr: 2.1800e-05 eta: 0:50:21 time: 0.4935 data_time: 0.0023 memory: 7415 grad_norm: 1254.1624 loss: 344.2460 loss_cls: 99.5265 loss_bbox: 111.2079 loss_dfl: 133.5116 +2024/03/21 06:54:05 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:54:17 - mmengine - INFO - Epoch(train) [74][500/925] lr: 2.1800e-05 eta: 0:49:56 time: 0.4852 data_time: 0.0025 memory: 7362 grad_norm: 1152.5154 loss: 340.6925 loss_cls: 96.7850 loss_bbox: 108.5670 loss_dfl: 135.3405 +2024/03/21 06:54:41 - mmengine - INFO - Epoch(train) [74][550/925] lr: 2.1800e-05 eta: 0:49:31 time: 0.4771 data_time: 0.0024 memory: 7415 grad_norm: 1148.4499 loss: 349.5599 loss_cls: 99.8411 loss_bbox: 113.7471 loss_dfl: 135.9716 +2024/03/21 06:55:06 - mmengine - INFO - Epoch(train) [74][600/925] lr: 2.1800e-05 eta: 0:49:06 time: 0.4971 data_time: 0.0023 memory: 7295 grad_norm: 1185.2742 loss: 353.0972 loss_cls: 103.5455 loss_bbox: 113.1240 loss_dfl: 136.4277 +2024/03/21 06:55:30 - mmengine - INFO - Epoch(train) [74][650/925] lr: 2.1800e-05 eta: 0:48:41 time: 0.4757 data_time: 0.0022 memory: 7495 grad_norm: 1085.4278 loss: 341.7793 loss_cls: 98.4011 loss_bbox: 110.5303 loss_dfl: 132.8479 +2024/03/21 06:55:54 - mmengine - INFO - Epoch(train) [74][700/925] lr: 2.1800e-05 eta: 0:48:16 time: 0.4746 data_time: 0.0023 memory: 7335 grad_norm: 1220.5868 loss: 339.3677 loss_cls: 96.2721 loss_bbox: 109.1867 loss_dfl: 133.9089 +2024/03/21 06:56:18 - mmengine - INFO - Epoch(train) [74][750/925] lr: 2.1800e-05 eta: 0:47:51 time: 0.4928 data_time: 0.0022 memory: 7455 grad_norm: 1158.6538 loss: 347.9300 loss_cls: 99.8549 loss_bbox: 112.8640 loss_dfl: 135.2110 +2024/03/21 06:56:42 - mmengine - INFO - Epoch(train) [74][800/925] lr: 2.1800e-05 eta: 0:47:25 time: 0.4742 data_time: 0.0023 memory: 7295 grad_norm: 1129.2080 loss: 339.7937 loss_cls: 97.3512 loss_bbox: 108.4257 loss_dfl: 134.0168 +2024/03/21 06:57:07 - mmengine - INFO - Epoch(train) [74][850/925] lr: 2.1800e-05 eta: 0:47:00 time: 0.4851 data_time: 0.0023 memory: 7455 grad_norm: 1198.5018 loss: 346.9646 loss_cls: 100.7205 loss_bbox: 111.6087 loss_dfl: 134.6355 +2024/03/21 06:57:31 - mmengine - INFO - Epoch(train) [74][900/925] lr: 2.1800e-05 eta: 0:46:35 time: 0.4940 data_time: 0.0023 memory: 7349 grad_norm: 1181.4537 loss: 338.1689 loss_cls: 97.3336 loss_bbox: 107.2437 loss_dfl: 133.5917 +2024/03/21 06:57:43 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 06:57:45 - mmengine - INFO - Epoch(val) [74][ 50/625] eta: 0:00:20 time: 0.0352 data_time: 0.0008 memory: 7282 +2024/03/21 06:57:47 - mmengine - INFO - Epoch(val) [74][100/625] eta: 0:00:18 time: 0.0352 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:48 - mmengine - INFO - Epoch(val) [74][150/625] eta: 0:00:16 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:50 - mmengine - INFO - Epoch(val) [74][200/625] eta: 0:00:14 time: 0.0339 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:52 - mmengine - INFO - Epoch(val) [74][250/625] eta: 0:00:13 time: 0.0340 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:54 - mmengine - INFO - Epoch(val) [74][300/625] eta: 0:00:11 time: 0.0342 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:55 - mmengine - INFO - Epoch(val) [74][350/625] eta: 0:00:09 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:57 - mmengine - INFO - Epoch(val) [74][400/625] eta: 0:00:07 time: 0.0359 data_time: 0.0003 memory: 1244 +2024/03/21 06:57:59 - mmengine - INFO - Epoch(val) [74][450/625] eta: 0:00:06 time: 0.0347 data_time: 0.0003 memory: 1244 +2024/03/21 06:58:01 - mmengine - INFO - Epoch(val) [74][500/625] eta: 0:00:04 time: 0.0353 data_time: 0.0003 memory: 1244 +2024/03/21 06:58:02 - mmengine - INFO - Epoch(val) [74][550/625] eta: 0:00:02 time: 0.0362 data_time: 0.0003 memory: 1244 +2024/03/21 06:58:04 - mmengine - INFO - Epoch(val) [74][600/625] eta: 0:00:00 time: 0.0379 data_time: 0.0003 memory: 1244 +2024/03/21 06:58:16 - mmengine - INFO - Evaluating bbox... +2024/03/21 06:59:17 - mmengine - INFO - bbox_mAP_copypaste: 0.506 0.674 0.551 0.325 0.557 0.670 +2024/03/21 06:59:19 - mmengine - INFO - Epoch(val) [74][625/625] coco/bbox_mAP: 0.5060 coco/bbox_mAP_50: 0.6740 coco/bbox_mAP_75: 0.5510 coco/bbox_mAP_s: 0.3250 coco/bbox_mAP_m: 0.5570 coco/bbox_mAP_l: 0.6700 data_time: 0.0003 time: 0.0362 +2024/03/21 06:59:45 - mmengine - INFO - Epoch(train) [75][ 50/925] lr: 1.9325e-05 eta: 0:45:58 time: 0.5242 data_time: 0.0395 memory: 7402 grad_norm: 1172.7493 loss: 343.5907 loss_cls: 96.4835 loss_bbox: 111.8901 loss_dfl: 135.2172 +2024/03/21 07:00:10 - mmengine - INFO - Epoch(train) [75][100/925] lr: 1.9325e-05 eta: 0:45:32 time: 0.4958 data_time: 0.0024 memory: 7335 grad_norm: 1132.7789 loss: 349.6468 loss_cls: 102.3239 loss_bbox: 112.0044 loss_dfl: 135.3185 +2024/03/21 07:00:34 - mmengine - INFO - Epoch(train) [75][150/925] lr: 1.9325e-05 eta: 0:45:07 time: 0.4912 data_time: 0.0023 memory: 7562 grad_norm: 1077.2726 loss: 343.1800 loss_cls: 97.7661 loss_bbox: 111.4968 loss_dfl: 133.9171 +2024/03/21 07:00:59 - mmengine - INFO - Epoch(train) [75][200/925] lr: 1.9325e-05 eta: 0:44:42 time: 0.4889 data_time: 0.0020 memory: 7335 grad_norm: 1112.7650 loss: 348.5170 loss_cls: 103.0230 loss_bbox: 109.8897 loss_dfl: 135.6044 +2024/03/21 07:01:24 - mmengine - INFO - Epoch(train) [75][250/925] lr: 1.9325e-05 eta: 0:44:17 time: 0.5076 data_time: 0.0025 memory: 7282 grad_norm: 1125.4031 loss: 352.1230 loss_cls: 102.0571 loss_bbox: 115.3550 loss_dfl: 134.7109 +2024/03/21 07:01:48 - mmengine - INFO - Epoch(train) [75][300/925] lr: 1.9325e-05 eta: 0:43:52 time: 0.4838 data_time: 0.0023 memory: 7322 grad_norm: 1175.8454 loss: 337.9977 loss_cls: 98.1062 loss_bbox: 106.7289 loss_dfl: 133.1626 +2024/03/21 07:02:13 - mmengine - INFO - Epoch(train) [75][350/925] lr: 1.9325e-05 eta: 0:43:27 time: 0.4915 data_time: 0.0025 memory: 7335 grad_norm: 1141.6496 loss: 343.1926 loss_cls: 99.2469 loss_bbox: 110.3719 loss_dfl: 133.5738 +2024/03/21 07:02:37 - mmengine - INFO - Epoch(train) [75][400/925] lr: 1.9325e-05 eta: 0:43:02 time: 0.4809 data_time: 0.0024 memory: 7295 grad_norm: 1186.2288 loss: 338.2041 loss_cls: 96.3459 loss_bbox: 109.1858 loss_dfl: 132.6724 +2024/03/21 07:03:02 - mmengine - INFO - Epoch(train) [75][450/925] lr: 1.9325e-05 eta: 0:42:37 time: 0.4894 data_time: 0.0023 memory: 7575 grad_norm: 1180.6477 loss: 343.5440 loss_cls: 98.1900 loss_bbox: 111.2744 loss_dfl: 134.0796 +2024/03/21 07:03:26 - mmengine - INFO - Epoch(train) [75][500/925] lr: 1.9325e-05 eta: 0:42:12 time: 0.4926 data_time: 0.0024 memory: 7602 grad_norm: 1117.5682 loss: 341.3351 loss_cls: 97.2591 loss_bbox: 110.0834 loss_dfl: 133.9926 +2024/03/21 07:03:51 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:03:51 - mmengine - INFO - Epoch(train) [75][550/925] lr: 1.9325e-05 eta: 0:41:46 time: 0.4949 data_time: 0.0024 memory: 7429 grad_norm: 1049.9216 loss: 343.2210 loss_cls: 98.0996 loss_bbox: 111.1973 loss_dfl: 133.9241 +2024/03/21 07:04:15 - mmengine - INFO - Epoch(train) [75][600/925] lr: 1.9325e-05 eta: 0:41:21 time: 0.4779 data_time: 0.0024 memory: 7402 grad_norm: 1139.5575 loss: 338.7677 loss_cls: 96.8768 loss_bbox: 109.0766 loss_dfl: 132.8144 +2024/03/21 07:04:40 - mmengine - INFO - Epoch(train) [75][650/925] lr: 1.9325e-05 eta: 0:40:56 time: 0.4994 data_time: 0.0024 memory: 7442 grad_norm: inf loss: 336.6058 loss_cls: 95.5442 loss_bbox: 108.0150 loss_dfl: 133.0466 +2024/03/21 07:05:04 - mmengine - INFO - Epoch(train) [75][700/925] lr: 1.9325e-05 eta: 0:40:31 time: 0.4805 data_time: 0.0023 memory: 7349 grad_norm: 1033.3999 loss: 340.7598 loss_cls: 97.5361 loss_bbox: 108.7115 loss_dfl: 134.5121 +2024/03/21 07:05:29 - mmengine - INFO - Epoch(train) [75][750/925] lr: 1.9325e-05 eta: 0:40:06 time: 0.4953 data_time: 0.0021 memory: 7309 grad_norm: 1080.7615 loss: 346.8942 loss_cls: 101.7070 loss_bbox: 111.4428 loss_dfl: 133.7444 +2024/03/21 07:05:54 - mmengine - INFO - Epoch(train) [75][800/925] lr: 1.9325e-05 eta: 0:39:41 time: 0.4973 data_time: 0.0020 memory: 7455 grad_norm: 1188.6117 loss: 346.0027 loss_cls: 101.1837 loss_bbox: 110.8878 loss_dfl: 133.9313 +2024/03/21 07:06:17 - mmengine - INFO - Epoch(train) [75][850/925] lr: 1.9325e-05 eta: 0:39:16 time: 0.4741 data_time: 0.0023 memory: 7242 grad_norm: 1187.7865 loss: 336.6433 loss_cls: 95.5761 loss_bbox: 107.6975 loss_dfl: 133.3698 +2024/03/21 07:06:42 - mmengine - INFO - Epoch(train) [75][900/925] lr: 1.9325e-05 eta: 0:38:51 time: 0.4982 data_time: 0.0024 memory: 7349 grad_norm: 1142.1570 loss: 345.7655 loss_cls: 98.7683 loss_bbox: 111.5243 loss_dfl: 135.4729 +2024/03/21 07:06:54 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:06:55 - mmengine - INFO - Saving checkpoint at 75 epochs +2024/03/21 07:07:04 - mmengine - INFO - Epoch(val) [75][ 50/625] eta: 0:00:21 time: 0.0365 data_time: 0.0007 memory: 7562 +2024/03/21 07:07:06 - mmengine - INFO - Epoch(val) [75][100/625] eta: 0:00:19 time: 0.0359 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:08 - mmengine - INFO - Epoch(val) [75][150/625] eta: 0:00:16 time: 0.0344 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:09 - mmengine - INFO - Epoch(val) [75][200/625] eta: 0:00:15 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:11 - mmengine - INFO - Epoch(val) [75][250/625] eta: 0:00:13 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:13 - mmengine - INFO - Epoch(val) [75][300/625] eta: 0:00:11 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:15 - mmengine - INFO - Epoch(val) [75][350/625] eta: 0:00:09 time: 0.0355 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:16 - mmengine - INFO - Epoch(val) [75][400/625] eta: 0:00:07 time: 0.0350 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:18 - mmengine - INFO - Epoch(val) [75][450/625] eta: 0:00:06 time: 0.0307 data_time: 0.0003 memory: 1244 +2024/03/21 07:07:19 - mmengine - INFO - Epoch(val) [75][500/625] eta: 0:00:04 time: 0.0283 data_time: 0.0002 memory: 1244 +2024/03/21 07:07:21 - mmengine - INFO - Epoch(val) [75][550/625] eta: 0:00:02 time: 0.0284 data_time: 0.0002 memory: 1244 +2024/03/21 07:07:22 - mmengine - INFO - Epoch(val) [75][600/625] eta: 0:00:00 time: 0.0286 data_time: 0.0002 memory: 1244 +2024/03/21 07:07:33 - mmengine - INFO - Evaluating bbox... +2024/03/21 07:08:36 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.675 0.552 0.326 0.558 0.670 +2024/03/21 07:08:38 - mmengine - INFO - Epoch(val) [75][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6750 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3260 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6700 data_time: 0.0002 time: 0.0284 +2024/03/21 07:09:05 - mmengine - INFO - Epoch(train) [76][ 50/925] lr: 1.6850e-05 eta: 0:38:13 time: 0.5226 data_time: 0.0447 memory: 7309 grad_norm: 1081.1833 loss: 345.7239 loss_cls: 98.9424 loss_bbox: 112.5009 loss_dfl: 134.2806 +2024/03/21 07:09:29 - mmengine - INFO - Epoch(train) [76][100/925] lr: 1.6850e-05 eta: 0:37:48 time: 0.4783 data_time: 0.0022 memory: 7562 grad_norm: 1103.7512 loss: 343.6763 loss_cls: 99.1462 loss_bbox: 110.7628 loss_dfl: 133.7673 +2024/03/21 07:09:54 - mmengine - INFO - Epoch(train) [76][150/925] lr: 1.6850e-05 eta: 0:37:23 time: 0.5066 data_time: 0.0023 memory: 7469 grad_norm: 1106.0323 loss: 348.6272 loss_cls: 101.2668 loss_bbox: 112.1940 loss_dfl: 135.1665 +2024/03/21 07:10:18 - mmengine - INFO - Epoch(train) [76][200/925] lr: 1.6850e-05 eta: 0:36:58 time: 0.4793 data_time: 0.0024 memory: 7309 grad_norm: 1117.4096 loss: 349.6843 loss_cls: 100.9700 loss_bbox: 114.1444 loss_dfl: 134.5700 +2024/03/21 07:10:42 - mmengine - INFO - Epoch(train) [76][250/925] lr: 1.6850e-05 eta: 0:36:33 time: 0.4780 data_time: 0.0022 memory: 7602 grad_norm: 1118.5748 loss: 341.2866 loss_cls: 96.8046 loss_bbox: 110.9138 loss_dfl: 133.5682 +2024/03/21 07:11:07 - mmengine - INFO - Epoch(train) [76][300/925] lr: 1.6850e-05 eta: 0:36:08 time: 0.4973 data_time: 0.0023 memory: 7362 grad_norm: 1151.5821 loss: 341.0428 loss_cls: 96.3634 loss_bbox: 110.2503 loss_dfl: 134.4291 +2024/03/21 07:11:31 - mmengine - INFO - Epoch(train) [76][350/925] lr: 1.6850e-05 eta: 0:35:42 time: 0.4809 data_time: 0.0023 memory: 7429 grad_norm: 1129.1627 loss: 348.7669 loss_cls: 99.9413 loss_bbox: 112.9950 loss_dfl: 135.8306 +2024/03/21 07:11:55 - mmengine - INFO - Epoch(train) [76][400/925] lr: 1.6850e-05 eta: 0:35:17 time: 0.4864 data_time: 0.0024 memory: 7242 grad_norm: 1054.4223 loss: 341.3260 loss_cls: 97.9796 loss_bbox: 109.0826 loss_dfl: 134.2638 +2024/03/21 07:12:20 - mmengine - INFO - Epoch(train) [76][450/925] lr: 1.6850e-05 eta: 0:34:52 time: 0.4963 data_time: 0.0022 memory: 7455 grad_norm: 1146.2744 loss: 342.4009 loss_cls: 98.3718 loss_bbox: 109.2731 loss_dfl: 134.7560 +2024/03/21 07:12:44 - mmengine - INFO - Epoch(train) [76][500/925] lr: 1.6850e-05 eta: 0:34:27 time: 0.4859 data_time: 0.0021 memory: 7415 grad_norm: 1134.5856 loss: 348.2082 loss_cls: 100.4865 loss_bbox: 112.0140 loss_dfl: 135.7076 +2024/03/21 07:13:09 - mmengine - INFO - Epoch(train) [76][550/925] lr: 1.6850e-05 eta: 0:34:02 time: 0.4861 data_time: 0.0024 memory: 7362 grad_norm: 1180.4786 loss: 344.7818 loss_cls: 99.3811 loss_bbox: 110.8201 loss_dfl: 134.5806 +2024/03/21 07:13:33 - mmengine - INFO - Epoch(train) [76][600/925] lr: 1.6850e-05 eta: 0:33:37 time: 0.4894 data_time: 0.0024 memory: 7402 grad_norm: 1079.0943 loss: 340.0826 loss_cls: 95.6707 loss_bbox: 109.9669 loss_dfl: 134.4450 +2024/03/21 07:13:46 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:13:58 - mmengine - INFO - Epoch(train) [76][650/925] lr: 1.6850e-05 eta: 0:33:12 time: 0.4906 data_time: 0.0024 memory: 7629 grad_norm: 1193.9769 loss: 351.2684 loss_cls: 99.7090 loss_bbox: 115.3186 loss_dfl: 136.2408 +2024/03/21 07:14:22 - mmengine - INFO - Epoch(train) [76][700/925] lr: 1.6850e-05 eta: 0:32:47 time: 0.4851 data_time: 0.0023 memory: 7322 grad_norm: 1103.7276 loss: 344.3748 loss_cls: 98.1204 loss_bbox: 111.7254 loss_dfl: 134.5289 +2024/03/21 07:14:47 - mmengine - INFO - Epoch(train) [76][750/925] lr: 1.6850e-05 eta: 0:32:22 time: 0.4894 data_time: 0.0025 memory: 7349 grad_norm: 1168.7341 loss: 342.3269 loss_cls: 100.4911 loss_bbox: 109.1542 loss_dfl: 132.6816 +2024/03/21 07:15:11 - mmengine - INFO - Epoch(train) [76][800/925] lr: 1.6850e-05 eta: 0:31:57 time: 0.4933 data_time: 0.0024 memory: 7455 grad_norm: 1133.7103 loss: 348.3062 loss_cls: 99.4497 loss_bbox: 114.0466 loss_dfl: 134.8100 +2024/03/21 07:15:36 - mmengine - INFO - Epoch(train) [76][850/925] lr: 1.6850e-05 eta: 0:31:31 time: 0.4930 data_time: 0.0025 memory: 7442 grad_norm: 1121.3227 loss: 337.0505 loss_cls: 95.1048 loss_bbox: 108.0481 loss_dfl: 133.8976 +2024/03/21 07:16:00 - mmengine - INFO - Epoch(train) [76][900/925] lr: 1.6850e-05 eta: 0:31:06 time: 0.4889 data_time: 0.0023 memory: 7402 grad_norm: 1148.7492 loss: 343.1090 loss_cls: 96.9337 loss_bbox: 110.8106 loss_dfl: 135.3646 +2024/03/21 07:16:12 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:16:15 - mmengine - INFO - Epoch(val) [76][ 50/625] eta: 0:00:20 time: 0.0357 data_time: 0.0008 memory: 7455 +2024/03/21 07:16:16 - mmengine - INFO - Epoch(val) [76][100/625] eta: 0:00:18 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:18 - mmengine - INFO - Epoch(val) [76][150/625] eta: 0:00:16 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:20 - mmengine - INFO - Epoch(val) [76][200/625] eta: 0:00:15 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:22 - mmengine - INFO - Epoch(val) [76][250/625] eta: 0:00:13 time: 0.0364 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:24 - mmengine - INFO - Epoch(val) [76][300/625] eta: 0:00:11 time: 0.0366 data_time: 0.0004 memory: 1244 +2024/03/21 07:16:26 - mmengine - INFO - Epoch(val) [76][350/625] eta: 0:00:09 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:27 - mmengine - INFO - Epoch(val) [76][400/625] eta: 0:00:08 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:29 - mmengine - INFO - Epoch(val) [76][450/625] eta: 0:00:06 time: 0.0355 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:31 - mmengine - INFO - Epoch(val) [76][500/625] eta: 0:00:04 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:33 - mmengine - INFO - Epoch(val) [76][550/625] eta: 0:00:02 time: 0.0370 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:35 - mmengine - INFO - Epoch(val) [76][600/625] eta: 0:00:00 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 07:16:45 - mmengine - INFO - Evaluating bbox... +2024/03/21 07:17:43 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.675 0.553 0.326 0.559 0.671 +2024/03/21 07:17:44 - mmengine - INFO - Epoch(val) [76][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6750 coco/bbox_mAP_75: 0.5530 coco/bbox_mAP_s: 0.3260 coco/bbox_mAP_m: 0.5590 coco/bbox_mAP_l: 0.6710 data_time: 0.0003 time: 0.0365 +2024/03/21 07:18:11 - mmengine - INFO - Epoch(train) [77][ 50/925] lr: 1.4375e-05 eta: 0:30:29 time: 0.5378 data_time: 0.0410 memory: 7375 grad_norm: 1103.7751 loss: 332.9750 loss_cls: 95.8546 loss_bbox: 104.5786 loss_dfl: 132.5418 +2024/03/21 07:18:35 - mmengine - INFO - Epoch(train) [77][100/925] lr: 1.4375e-05 eta: 0:30:04 time: 0.4867 data_time: 0.0025 memory: 7469 grad_norm: 1071.7150 loss: 347.2556 loss_cls: 98.2463 loss_bbox: 114.0843 loss_dfl: 134.9250 +2024/03/21 07:19:00 - mmengine - INFO - Epoch(train) [77][150/925] lr: 1.4375e-05 eta: 0:29:39 time: 0.4873 data_time: 0.0023 memory: 7482 grad_norm: 1071.3906 loss: 336.5960 loss_cls: 95.0783 loss_bbox: 109.1310 loss_dfl: 132.3867 +2024/03/21 07:19:24 - mmengine - INFO - Epoch(train) [77][200/925] lr: 1.4375e-05 eta: 0:29:14 time: 0.4869 data_time: 0.0024 memory: 7482 grad_norm: 1101.1212 loss: 349.3713 loss_cls: 101.1347 loss_bbox: 112.3716 loss_dfl: 135.8650 +2024/03/21 07:19:48 - mmengine - INFO - Epoch(train) [77][250/925] lr: 1.4375e-05 eta: 0:28:48 time: 0.4833 data_time: 0.0024 memory: 7322 grad_norm: 1125.9973 loss: 347.9054 loss_cls: 101.9764 loss_bbox: 111.2603 loss_dfl: 134.6687 +2024/03/21 07:20:13 - mmengine - INFO - Epoch(train) [77][300/925] lr: 1.4375e-05 eta: 0:28:23 time: 0.4905 data_time: 0.0023 memory: 7349 grad_norm: 1087.4449 loss: 343.6608 loss_cls: 97.4114 loss_bbox: 111.0612 loss_dfl: 135.1882 +2024/03/21 07:20:37 - mmengine - INFO - Epoch(train) [77][350/925] lr: 1.4375e-05 eta: 0:27:58 time: 0.4829 data_time: 0.0022 memory: 7335 grad_norm: 1108.8329 loss: 344.3562 loss_cls: 100.3056 loss_bbox: 110.5704 loss_dfl: 133.4802 +2024/03/21 07:21:01 - mmengine - INFO - Epoch(train) [77][400/925] lr: 1.4375e-05 eta: 0:27:33 time: 0.4774 data_time: 0.0024 memory: 7309 grad_norm: 1112.8524 loss: 336.3553 loss_cls: 96.1401 loss_bbox: 108.8281 loss_dfl: 131.3871 +2024/03/21 07:21:26 - mmengine - INFO - Epoch(train) [77][450/925] lr: 1.4375e-05 eta: 0:27:08 time: 0.5048 data_time: 0.0022 memory: 7562 grad_norm: 1127.8851 loss: 337.5055 loss_cls: 93.8754 loss_bbox: 109.9915 loss_dfl: 133.6386 +2024/03/21 07:21:50 - mmengine - INFO - Epoch(train) [77][500/925] lr: 1.4375e-05 eta: 0:26:43 time: 0.4780 data_time: 0.0024 memory: 7429 grad_norm: 1118.7458 loss: 340.6759 loss_cls: 95.5207 loss_bbox: 111.1940 loss_dfl: 133.9611 +2024/03/21 07:22:14 - mmengine - INFO - Epoch(train) [77][550/925] lr: 1.4375e-05 eta: 0:26:18 time: 0.4812 data_time: 0.0020 memory: 7402 grad_norm: 1138.0497 loss: 342.4645 loss_cls: 97.5358 loss_bbox: 110.3208 loss_dfl: 134.6079 +2024/03/21 07:22:39 - mmengine - INFO - Epoch(train) [77][600/925] lr: 1.4375e-05 eta: 0:25:53 time: 0.4999 data_time: 0.0024 memory: 7389 grad_norm: 1190.7213 loss: 344.8675 loss_cls: 99.6349 loss_bbox: 111.1488 loss_dfl: 134.0838 +2024/03/21 07:23:03 - mmengine - INFO - Epoch(train) [77][650/925] lr: 1.4375e-05 eta: 0:25:28 time: 0.4726 data_time: 0.0023 memory: 7362 grad_norm: inf loss: 339.9797 loss_cls: 95.8514 loss_bbox: 111.4222 loss_dfl: 132.7061 +2024/03/21 07:23:28 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:23:28 - mmengine - INFO - Epoch(train) [77][700/925] lr: 1.4375e-05 eta: 0:25:03 time: 0.4923 data_time: 0.0023 memory: 7295 grad_norm: 1156.7005 loss: 345.1459 loss_cls: 99.4188 loss_bbox: 110.8612 loss_dfl: 134.8660 +2024/03/21 07:23:52 - mmengine - INFO - Epoch(train) [77][750/925] lr: 1.4375e-05 eta: 0:24:38 time: 0.4982 data_time: 0.0025 memory: 7415 grad_norm: 1101.4578 loss: 340.6120 loss_cls: 98.1098 loss_bbox: 109.0531 loss_dfl: 133.4491 +2024/03/21 07:24:16 - mmengine - INFO - Epoch(train) [77][800/925] lr: 1.4375e-05 eta: 0:24:13 time: 0.4713 data_time: 0.0022 memory: 7442 grad_norm: 1129.5680 loss: 338.8587 loss_cls: 94.5683 loss_bbox: 110.2333 loss_dfl: 134.0571 +2024/03/21 07:24:40 - mmengine - INFO - Epoch(train) [77][850/925] lr: 1.4375e-05 eta: 0:23:47 time: 0.4873 data_time: 0.0025 memory: 7495 grad_norm: 1099.4095 loss: 341.1652 loss_cls: 97.2808 loss_bbox: 109.9943 loss_dfl: 133.8901 +2024/03/21 07:25:05 - mmengine - INFO - Epoch(train) [77][900/925] lr: 1.4375e-05 eta: 0:23:22 time: 0.4900 data_time: 0.0024 memory: 7309 grad_norm: 1163.0694 loss: 344.8420 loss_cls: 99.8427 loss_bbox: 110.5956 loss_dfl: 134.4037 +2024/03/21 07:25:17 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:25:19 - mmengine - INFO - Epoch(val) [77][ 50/625] eta: 0:00:20 time: 0.0357 data_time: 0.0007 memory: 7509 +2024/03/21 07:25:21 - mmengine - INFO - Epoch(val) [77][100/625] eta: 0:00:18 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:23 - mmengine - INFO - Epoch(val) [77][150/625] eta: 0:00:17 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:24 - mmengine - INFO - Epoch(val) [77][200/625] eta: 0:00:15 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:26 - mmengine - INFO - Epoch(val) [77][250/625] eta: 0:00:13 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:28 - mmengine - INFO - Epoch(val) [77][300/625] eta: 0:00:11 time: 0.0349 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:30 - mmengine - INFO - Epoch(val) [77][350/625] eta: 0:00:09 time: 0.0352 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:32 - mmengine - INFO - Epoch(val) [77][400/625] eta: 0:00:08 time: 0.0368 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:33 - mmengine - INFO - Epoch(val) [77][450/625] eta: 0:00:06 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:35 - mmengine - INFO - Epoch(val) [77][500/625] eta: 0:00:04 time: 0.0342 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:37 - mmengine - INFO - Epoch(val) [77][550/625] eta: 0:00:02 time: 0.0360 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:39 - mmengine - INFO - Epoch(val) [77][600/625] eta: 0:00:00 time: 0.0348 data_time: 0.0003 memory: 1244 +2024/03/21 07:25:50 - mmengine - INFO - Evaluating bbox... +2024/03/21 07:26:56 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.675 0.552 0.328 0.558 0.671 +2024/03/21 07:26:58 - mmengine - INFO - Epoch(val) [77][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6750 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3280 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6710 data_time: 0.0003 time: 0.0347 +2024/03/21 07:27:24 - mmengine - INFO - Epoch(train) [78][ 50/925] lr: 1.1900e-05 eta: 0:22:45 time: 0.5182 data_time: 0.0443 memory: 7495 grad_norm: 1083.1581 loss: 338.6876 loss_cls: 97.6084 loss_bbox: 108.6306 loss_dfl: 132.4485 +2024/03/21 07:27:48 - mmengine - INFO - Epoch(train) [78][100/925] lr: 1.1900e-05 eta: 0:22:20 time: 0.4943 data_time: 0.0024 memory: 7522 grad_norm: 1063.4223 loss: 348.8927 loss_cls: 102.2479 loss_bbox: 112.4448 loss_dfl: 134.2001 +2024/03/21 07:28:12 - mmengine - INFO - Epoch(train) [78][150/925] lr: 1.1900e-05 eta: 0:21:55 time: 0.4741 data_time: 0.0024 memory: 7575 grad_norm: 1064.1183 loss: 345.2573 loss_cls: 100.5659 loss_bbox: 110.1479 loss_dfl: 134.5436 +2024/03/21 07:28:37 - mmengine - INFO - Epoch(train) [78][200/925] lr: 1.1900e-05 eta: 0:21:30 time: 0.4899 data_time: 0.0024 memory: 7389 grad_norm: 1062.0535 loss: 346.9409 loss_cls: 100.0224 loss_bbox: 111.0364 loss_dfl: 135.8821 +2024/03/21 07:29:02 - mmengine - INFO - Epoch(train) [78][250/925] lr: 1.1900e-05 eta: 0:21:04 time: 0.5013 data_time: 0.0023 memory: 7335 grad_norm: 1088.5000 loss: 340.2724 loss_cls: 96.2464 loss_bbox: 110.2271 loss_dfl: 133.7989 +2024/03/21 07:29:26 - mmengine - INFO - Epoch(train) [78][300/925] lr: 1.1900e-05 eta: 0:20:39 time: 0.4796 data_time: 0.0024 memory: 7415 grad_norm: 1091.7050 loss: 335.8314 loss_cls: 95.2221 loss_bbox: 107.5518 loss_dfl: 133.0575 +2024/03/21 07:29:51 - mmengine - INFO - Epoch(train) [78][350/925] lr: 1.1900e-05 eta: 0:20:14 time: 0.4978 data_time: 0.0025 memory: 7495 grad_norm: 1142.6814 loss: 339.1902 loss_cls: 95.7867 loss_bbox: 110.0579 loss_dfl: 133.3456 +2024/03/21 07:30:15 - mmengine - INFO - Epoch(train) [78][400/925] lr: 1.1900e-05 eta: 0:19:49 time: 0.4886 data_time: 0.0023 memory: 7389 grad_norm: 1149.8474 loss: 332.9923 loss_cls: 94.3901 loss_bbox: 106.6828 loss_dfl: 131.9194 +2024/03/21 07:30:39 - mmengine - INFO - Epoch(train) [78][450/925] lr: 1.1900e-05 eta: 0:19:24 time: 0.4790 data_time: 0.0024 memory: 7322 grad_norm: 1094.9379 loss: 343.9681 loss_cls: 97.5981 loss_bbox: 111.7909 loss_dfl: 134.5790 +2024/03/21 07:31:04 - mmengine - INFO - Epoch(train) [78][500/925] lr: 1.1900e-05 eta: 0:18:59 time: 0.5025 data_time: 0.0023 memory: 7469 grad_norm: 1106.5432 loss: 346.8651 loss_cls: 100.9610 loss_bbox: 112.0087 loss_dfl: 133.8953 +2024/03/21 07:31:28 - mmengine - INFO - Epoch(train) [78][550/925] lr: 1.1900e-05 eta: 0:18:34 time: 0.4728 data_time: 0.0023 memory: 7322 grad_norm: 1136.7100 loss: 338.8026 loss_cls: 97.6202 loss_bbox: 107.6114 loss_dfl: 133.5711 +2024/03/21 07:31:52 - mmengine - INFO - Epoch(train) [78][600/925] lr: 1.1900e-05 eta: 0:18:09 time: 0.4878 data_time: 0.0023 memory: 7295 grad_norm: 1128.2246 loss: 342.0511 loss_cls: 96.5412 loss_bbox: 111.6208 loss_dfl: 133.8891 +2024/03/21 07:32:18 - mmengine - INFO - Epoch(train) [78][650/925] lr: 1.1900e-05 eta: 0:17:44 time: 0.5102 data_time: 0.0021 memory: 7615 grad_norm: 1107.5286 loss: 337.3773 loss_cls: 95.5668 loss_bbox: 109.1153 loss_dfl: 132.6952 +2024/03/21 07:32:41 - mmengine - INFO - Epoch(train) [78][700/925] lr: 1.1900e-05 eta: 0:17:19 time: 0.4656 data_time: 0.0023 memory: 7349 grad_norm: 1098.3353 loss: 334.8478 loss_cls: 94.9400 loss_bbox: 107.3958 loss_dfl: 132.5120 +2024/03/21 07:33:06 - mmengine - INFO - Epoch(train) [78][750/925] lr: 1.1900e-05 eta: 0:16:54 time: 0.4996 data_time: 0.0024 memory: 7495 grad_norm: 1140.1848 loss: 339.7700 loss_cls: 94.5401 loss_bbox: 110.7977 loss_dfl: 134.4322 +2024/03/21 07:33:19 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:33:31 - mmengine - INFO - Epoch(train) [78][800/925] lr: 1.1900e-05 eta: 0:16:29 time: 0.4912 data_time: 0.0024 memory: 7389 grad_norm: 1087.0165 loss: 340.9819 loss_cls: 97.6450 loss_bbox: 108.2842 loss_dfl: 135.0526 +2024/03/21 07:33:55 - mmengine - INFO - Epoch(train) [78][850/925] lr: 1.1900e-05 eta: 0:16:04 time: 0.4796 data_time: 0.0023 memory: 7322 grad_norm: 1124.9732 loss: 337.3832 loss_cls: 95.4937 loss_bbox: 109.0172 loss_dfl: 132.8723 +2024/03/21 07:34:20 - mmengine - INFO - Epoch(train) [78][900/925] lr: 1.1900e-05 eta: 0:15:39 time: 0.5054 data_time: 0.0023 memory: 7322 grad_norm: 1105.1097 loss: 338.9662 loss_cls: 95.3470 loss_bbox: 110.8352 loss_dfl: 132.7840 +2024/03/21 07:34:32 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:34:34 - mmengine - INFO - Epoch(val) [78][ 50/625] eta: 0:00:20 time: 0.0362 data_time: 0.0008 memory: 7389 +2024/03/21 07:34:36 - mmengine - INFO - Epoch(val) [78][100/625] eta: 0:00:18 time: 0.0362 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:38 - mmengine - INFO - Epoch(val) [78][150/625] eta: 0:00:17 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:39 - mmengine - INFO - Epoch(val) [78][200/625] eta: 0:00:15 time: 0.0362 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:41 - mmengine - INFO - Epoch(val) [78][250/625] eta: 0:00:13 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:43 - mmengine - INFO - Epoch(val) [78][300/625] eta: 0:00:11 time: 0.0346 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:45 - mmengine - INFO - Epoch(val) [78][350/625] eta: 0:00:09 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:47 - mmengine - INFO - Epoch(val) [78][400/625] eta: 0:00:08 time: 0.0364 data_time: 0.0004 memory: 1244 +2024/03/21 07:34:48 - mmengine - INFO - Epoch(val) [78][450/625] eta: 0:00:06 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:50 - mmengine - INFO - Epoch(val) [78][500/625] eta: 0:00:04 time: 0.0354 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:52 - mmengine - INFO - Epoch(val) [78][550/625] eta: 0:00:02 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 07:34:54 - mmengine - INFO - Epoch(val) [78][600/625] eta: 0:00:00 time: 0.0339 data_time: 0.0003 memory: 1244 +2024/03/21 07:35:05 - mmengine - INFO - Evaluating bbox... +2024/03/21 07:36:03 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.675 0.552 0.328 0.558 0.671 +2024/03/21 07:36:04 - mmengine - INFO - Epoch(val) [78][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6750 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3280 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6710 data_time: 0.0003 time: 0.0342 +2024/03/21 07:36:30 - mmengine - INFO - Epoch(train) [79][ 50/925] lr: 9.4250e-06 eta: 0:15:01 time: 0.5079 data_time: 0.0426 memory: 7429 grad_norm: 1113.9327 loss: 342.2038 loss_cls: 98.2730 loss_bbox: 109.1827 loss_dfl: 134.7482 +2024/03/21 07:36:54 - mmengine - INFO - Epoch(train) [79][100/925] lr: 9.4250e-06 eta: 0:14:36 time: 0.4817 data_time: 0.0023 memory: 7269 grad_norm: 1105.1754 loss: 342.1320 loss_cls: 97.0176 loss_bbox: 110.1789 loss_dfl: 134.9355 +2024/03/21 07:37:19 - mmengine - INFO - Epoch(train) [79][150/925] lr: 9.4250e-06 eta: 0:14:11 time: 0.4980 data_time: 0.0025 memory: 7349 grad_norm: 1082.1256 loss: 339.0727 loss_cls: 96.7051 loss_bbox: 108.7384 loss_dfl: 133.6292 +2024/03/21 07:37:43 - mmengine - INFO - Epoch(train) [79][200/925] lr: 9.4250e-06 eta: 0:13:46 time: 0.4745 data_time: 0.0022 memory: 7882 grad_norm: 1085.5377 loss: 335.8140 loss_cls: 94.7397 loss_bbox: 107.2115 loss_dfl: 133.8629 +2024/03/21 07:38:08 - mmengine - INFO - Epoch(train) [79][250/925] lr: 9.4250e-06 eta: 0:13:21 time: 0.5021 data_time: 0.0026 memory: 7402 grad_norm: 1056.9276 loss: 346.6803 loss_cls: 101.3038 loss_bbox: 110.0628 loss_dfl: 135.3137 +2024/03/21 07:38:32 - mmengine - INFO - Epoch(train) [79][300/925] lr: 9.4250e-06 eta: 0:12:56 time: 0.4762 data_time: 0.0025 memory: 7429 grad_norm: 1070.4605 loss: 333.1155 loss_cls: 93.7050 loss_bbox: 106.1689 loss_dfl: 133.2416 +2024/03/21 07:38:56 - mmengine - INFO - Epoch(train) [79][350/925] lr: 9.4250e-06 eta: 0:12:31 time: 0.4893 data_time: 0.0022 memory: 7309 grad_norm: 1094.1506 loss: 338.8362 loss_cls: 97.1052 loss_bbox: 108.5071 loss_dfl: 133.2239 +2024/03/21 07:39:21 - mmengine - INFO - Epoch(train) [79][400/925] lr: 9.4250e-06 eta: 0:12:06 time: 0.4980 data_time: 0.0024 memory: 7402 grad_norm: 1114.7156 loss: 342.0782 loss_cls: 96.2793 loss_bbox: 112.3836 loss_dfl: 133.4154 +2024/03/21 07:39:45 - mmengine - INFO - Epoch(train) [79][450/925] lr: 9.4250e-06 eta: 0:11:41 time: 0.4666 data_time: 0.0021 memory: 7442 grad_norm: 1185.8667 loss: 340.0057 loss_cls: 95.3126 loss_bbox: 110.5116 loss_dfl: 134.1815 +2024/03/21 07:40:09 - mmengine - INFO - Epoch(train) [79][500/925] lr: 9.4250e-06 eta: 0:11:16 time: 0.4933 data_time: 0.0023 memory: 7349 grad_norm: 1074.4278 loss: 340.5477 loss_cls: 97.0396 loss_bbox: 109.8097 loss_dfl: 133.6984 +2024/03/21 07:40:34 - mmengine - INFO - Epoch(train) [79][550/925] lr: 9.4250e-06 eta: 0:10:51 time: 0.4879 data_time: 0.0024 memory: 7335 grad_norm: 1124.4207 loss: 344.0484 loss_cls: 99.1771 loss_bbox: 110.1770 loss_dfl: 134.6944 +2024/03/21 07:40:58 - mmengine - INFO - Epoch(train) [79][600/925] lr: 9.4250e-06 eta: 0:10:25 time: 0.4787 data_time: 0.0024 memory: 7455 grad_norm: 1219.4817 loss: 333.2672 loss_cls: 93.2893 loss_bbox: 107.5057 loss_dfl: 132.4722 +2024/03/21 07:41:22 - mmengine - INFO - Epoch(train) [79][650/925] lr: 9.4250e-06 eta: 0:10:00 time: 0.4940 data_time: 0.0025 memory: 7335 grad_norm: 1092.1111 loss: 339.3083 loss_cls: 95.0609 loss_bbox: 110.6416 loss_dfl: 133.6057 +2024/03/21 07:41:47 - mmengine - INFO - Epoch(train) [79][700/925] lr: 9.4250e-06 eta: 0:09:35 time: 0.4830 data_time: 0.0024 memory: 7669 grad_norm: 1099.3555 loss: 338.3198 loss_cls: 94.7411 loss_bbox: 109.2597 loss_dfl: 134.3190 +2024/03/21 07:42:10 - mmengine - INFO - Epoch(train) [79][750/925] lr: 9.4250e-06 eta: 0:09:10 time: 0.4676 data_time: 0.0025 memory: 7669 grad_norm: 1178.6062 loss: 341.5067 loss_cls: 97.9675 loss_bbox: 110.5170 loss_dfl: 133.0223 +2024/03/21 07:42:35 - mmengine - INFO - Epoch(train) [79][800/925] lr: 9.4250e-06 eta: 0:08:45 time: 0.5068 data_time: 0.0023 memory: 7389 grad_norm: 1138.8441 loss: 334.4178 loss_cls: 94.3975 loss_bbox: 106.9733 loss_dfl: 133.0470 +2024/03/21 07:42:59 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:42:59 - mmengine - INFO - Epoch(train) [79][850/925] lr: 9.4250e-06 eta: 0:08:20 time: 0.4801 data_time: 0.0024 memory: 7442 grad_norm: 1080.3673 loss: 335.7899 loss_cls: 95.9239 loss_bbox: 108.2268 loss_dfl: 131.6391 +2024/03/21 07:43:24 - mmengine - INFO - Epoch(train) [79][900/925] lr: 9.4250e-06 eta: 0:07:55 time: 0.4874 data_time: 0.0023 memory: 7322 grad_norm: 1122.2522 loss: 334.5427 loss_cls: 94.3260 loss_bbox: 106.9868 loss_dfl: 133.2299 +2024/03/21 07:43:36 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:43:38 - mmengine - INFO - Epoch(val) [79][ 50/625] eta: 0:00:21 time: 0.0374 data_time: 0.0008 memory: 7282 +2024/03/21 07:43:40 - mmengine - INFO - Epoch(val) [79][100/625] eta: 0:00:19 time: 0.0355 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:42 - mmengine - INFO - Epoch(val) [79][150/625] eta: 0:00:17 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:44 - mmengine - INFO - Epoch(val) [79][200/625] eta: 0:00:15 time: 0.0367 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:46 - mmengine - INFO - Epoch(val) [79][250/625] eta: 0:00:13 time: 0.0351 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:47 - mmengine - INFO - Epoch(val) [79][300/625] eta: 0:00:11 time: 0.0361 data_time: 0.0004 memory: 1244 +2024/03/21 07:43:49 - mmengine - INFO - Epoch(val) [79][350/625] eta: 0:00:09 time: 0.0359 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:51 - mmengine - INFO - Epoch(val) [79][400/625] eta: 0:00:08 time: 0.0338 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:53 - mmengine - INFO - Epoch(val) [79][450/625] eta: 0:00:06 time: 0.0343 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:54 - mmengine - INFO - Epoch(val) [79][500/625] eta: 0:00:04 time: 0.0370 data_time: 0.0004 memory: 1244 +2024/03/21 07:43:56 - mmengine - INFO - Epoch(val) [79][550/625] eta: 0:00:02 time: 0.0369 data_time: 0.0003 memory: 1244 +2024/03/21 07:43:58 - mmengine - INFO - Epoch(val) [79][600/625] eta: 0:00:00 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 07:44:10 - mmengine - INFO - Evaluating bbox... +2024/03/21 07:45:13 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.675 0.552 0.329 0.558 0.672 +2024/03/21 07:45:15 - mmengine - INFO - Epoch(val) [79][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6750 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3290 coco/bbox_mAP_m: 0.5580 coco/bbox_mAP_l: 0.6720 data_time: 0.0003 time: 0.0369 +2024/03/21 07:45:41 - mmengine - INFO - Epoch(train) [80][ 50/925] lr: 6.9500e-06 eta: 0:07:18 time: 0.5164 data_time: 0.0479 memory: 7549 grad_norm: 1095.8577 loss: 342.7867 loss_cls: 97.4319 loss_bbox: 111.4109 loss_dfl: 133.9439 +2024/03/21 07:46:04 - mmengine - INFO - Epoch(train) [80][100/925] lr: 6.9500e-06 eta: 0:06:53 time: 0.4673 data_time: 0.0022 memory: 7269 grad_norm: 1097.7960 loss: 337.3453 loss_cls: 94.1070 loss_bbox: 109.3320 loss_dfl: 133.9064 +2024/03/21 07:46:29 - mmengine - INFO - Epoch(train) [80][150/925] lr: 6.9500e-06 eta: 0:06:28 time: 0.4945 data_time: 0.0023 memory: 7495 grad_norm: 1086.7956 loss: 335.6940 loss_cls: 95.1484 loss_bbox: 108.1743 loss_dfl: 132.3713 +2024/03/21 07:46:53 - mmengine - INFO - Epoch(train) [80][200/925] lr: 6.9500e-06 eta: 0:06:02 time: 0.4784 data_time: 0.0024 memory: 7562 grad_norm: 1125.9955 loss: 342.2758 loss_cls: 97.8215 loss_bbox: 110.3076 loss_dfl: 134.1467 +2024/03/21 07:47:17 - mmengine - INFO - Epoch(train) [80][250/925] lr: 6.9500e-06 eta: 0:05:37 time: 0.4777 data_time: 0.0024 memory: 7309 grad_norm: 1128.5462 loss: 333.4174 loss_cls: 92.2265 loss_bbox: 108.5444 loss_dfl: 132.6465 +2024/03/21 07:47:42 - mmengine - INFO - Epoch(train) [80][300/925] lr: 6.9500e-06 eta: 0:05:12 time: 0.4891 data_time: 0.0023 memory: 7509 grad_norm: 1119.1265 loss: 342.6411 loss_cls: 96.4945 loss_bbox: 111.2475 loss_dfl: 134.8991 +2024/03/21 07:48:05 - mmengine - INFO - Epoch(train) [80][350/925] lr: 6.9500e-06 eta: 0:04:47 time: 0.4667 data_time: 0.0024 memory: 7682 grad_norm: 1053.0310 loss: 345.7054 loss_cls: 98.1763 loss_bbox: 113.4221 loss_dfl: 134.1070 +2024/03/21 07:48:29 - mmengine - INFO - Epoch(train) [80][400/925] lr: 6.9500e-06 eta: 0:04:22 time: 0.4806 data_time: 0.0024 memory: 7375 grad_norm: 1091.2041 loss: 336.6581 loss_cls: 95.8498 loss_bbox: 108.5390 loss_dfl: 132.2694 +2024/03/21 07:48:53 - mmengine - INFO - Epoch(train) [80][450/925] lr: 6.9500e-06 eta: 0:03:57 time: 0.4868 data_time: 0.0023 memory: 7322 grad_norm: 1077.7065 loss: 335.7156 loss_cls: 93.9430 loss_bbox: 108.5855 loss_dfl: 133.1871 +2024/03/21 07:49:17 - mmengine - INFO - Epoch(train) [80][500/925] lr: 6.9500e-06 eta: 0:03:32 time: 0.4677 data_time: 0.0024 memory: 7362 grad_norm: 1122.8503 loss: 338.2428 loss_cls: 95.8613 loss_bbox: 108.8015 loss_dfl: 133.5801 +2024/03/21 07:49:41 - mmengine - INFO - Epoch(train) [80][550/925] lr: 6.9500e-06 eta: 0:03:07 time: 0.4913 data_time: 0.0025 memory: 7442 grad_norm: 1089.3203 loss: 330.7191 loss_cls: 91.8358 loss_bbox: 106.6589 loss_dfl: 132.2244 +2024/03/21 07:50:05 - mmengine - INFO - Epoch(train) [80][600/925] lr: 6.9500e-06 eta: 0:02:42 time: 0.4742 data_time: 0.0023 memory: 7282 grad_norm: 1129.6035 loss: 339.3897 loss_cls: 95.2119 loss_bbox: 109.8296 loss_dfl: 134.3482 +2024/03/21 07:50:29 - mmengine - INFO - Epoch(train) [80][650/925] lr: 6.9500e-06 eta: 0:02:17 time: 0.4734 data_time: 0.0025 memory: 7522 grad_norm: 1060.7076 loss: 336.5306 loss_cls: 97.6240 loss_bbox: 107.2661 loss_dfl: 131.6405 +2024/03/21 07:50:54 - mmengine - INFO - Epoch(train) [80][700/925] lr: 6.9500e-06 eta: 0:01:52 time: 0.4960 data_time: 0.0024 memory: 7309 grad_norm: 1136.2929 loss: 339.3358 loss_cls: 98.2522 loss_bbox: 107.6751 loss_dfl: 133.4085 +2024/03/21 07:51:17 - mmengine - INFO - Epoch(train) [80][750/925] lr: 6.9500e-06 eta: 0:01:27 time: 0.4717 data_time: 0.0023 memory: 7455 grad_norm: 1073.1427 loss: 341.4328 loss_cls: 96.5805 loss_bbox: 110.9475 loss_dfl: 133.9047 +2024/03/21 07:51:41 - mmengine - INFO - Epoch(train) [80][800/925] lr: 6.9500e-06 eta: 0:01:02 time: 0.4780 data_time: 0.0024 memory: 7309 grad_norm: 1034.5925 loss: 330.0637 loss_cls: 91.4028 loss_bbox: 105.9145 loss_dfl: 132.7465 +2024/03/21 07:52:06 - mmengine - INFO - Epoch(train) [80][850/925] lr: 6.9500e-06 eta: 0:00:37 time: 0.4894 data_time: 0.0023 memory: 7455 grad_norm: 1102.0435 loss: 331.0448 loss_cls: 92.4992 loss_bbox: 106.0262 loss_dfl: 132.5194 +2024/03/21 07:52:29 - mmengine - INFO - Epoch(train) [80][900/925] lr: 6.9500e-06 eta: 0:00:12 time: 0.4619 data_time: 0.0024 memory: 7415 grad_norm: 1105.6239 loss: 339.4102 loss_cls: 95.8846 loss_bbox: 110.2189 loss_dfl: 133.3066 +2024/03/21 07:52:40 - mmengine - INFO - Exp name: yolo_world_v2_m_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240320_204957 +2024/03/21 07:52:41 - mmengine - INFO - Saving checkpoint at 80 epochs +2024/03/21 07:52:50 - mmengine - INFO - Epoch(val) [80][ 50/625] eta: 0:00:20 time: 0.0359 data_time: 0.0007 memory: 7562 +2024/03/21 07:52:52 - mmengine - INFO - Epoch(val) [80][100/625] eta: 0:00:19 time: 0.0365 data_time: 0.0003 memory: 1244 +2024/03/21 07:52:53 - mmengine - INFO - Epoch(val) [80][150/625] eta: 0:00:17 time: 0.0363 data_time: 0.0003 memory: 1244 +2024/03/21 07:52:55 - mmengine - INFO - Epoch(val) [80][200/625] eta: 0:00:15 time: 0.0358 data_time: 0.0003 memory: 1244 +2024/03/21 07:52:57 - mmengine - INFO - Epoch(val) [80][250/625] eta: 0:00:13 time: 0.0370 data_time: 0.0003 memory: 1244 +2024/03/21 07:52:59 - mmengine - INFO - Epoch(val) [80][300/625] eta: 0:00:11 time: 0.0335 data_time: 0.0003 memory: 1244 +2024/03/21 07:53:00 - mmengine - INFO - Epoch(val) [80][350/625] eta: 0:00:09 time: 0.0343 data_time: 0.0003 memory: 1244 +2024/03/21 07:53:02 - mmengine - INFO - Epoch(val) [80][400/625] eta: 0:00:08 time: 0.0359 data_time: 0.0003 memory: 1244 +2024/03/21 07:53:04 - mmengine - INFO - Epoch(val) [80][450/625] eta: 0:00:06 time: 0.0312 data_time: 0.0003 memory: 1244 +2024/03/21 07:53:05 - mmengine - INFO - Epoch(val) [80][500/625] eta: 0:00:04 time: 0.0280 data_time: 0.0002 memory: 1244 +2024/03/21 07:53:07 - mmengine - INFO - Epoch(val) [80][550/625] eta: 0:00:02 time: 0.0281 data_time: 0.0002 memory: 1244 +2024/03/21 07:53:08 - mmengine - INFO - Epoch(val) [80][600/625] eta: 0:00:00 time: 0.0279 data_time: 0.0002 memory: 1244 +2024/03/21 07:53:18 - mmengine - INFO - Evaluating bbox... +2024/03/21 07:54:21 - mmengine - INFO - bbox_mAP_copypaste: 0.507 0.675 0.552 0.329 0.557 0.672 +2024/03/21 07:54:23 - mmengine - INFO - Epoch(val) [80][625/625] coco/bbox_mAP: 0.5070 coco/bbox_mAP_50: 0.6750 coco/bbox_mAP_75: 0.5520 coco/bbox_mAP_s: 0.3290 coco/bbox_mAP_m: 0.5570 coco/bbox_mAP_l: 0.6720 data_time: 0.0002 time: 0.0277