2024/03/27 11:04:18 - 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: 1901717788 GPU 0,1,2,3,4,5,6,7: Tesla V100-SXM2-32GB 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 ------------------------------------------------------------ 2024/03/27 11:04:20 - 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_s_clip_t2i_bn_2e-3adamw_32xb16-100e_obj365v1_goldg_train-55b943ea.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 = 0.33 widen_factor = 0.5 strides = [8, 16, 32] last_stage_out_channels = 1024 num_det_layers = 3 norm_cfg = dict(type='BN', momentum=0.03, eps=0.001) affine_scale = 0.5 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=1024, deepen_factor=0.33, widen_factor=0.5, 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=0.33, widen_factor=0.5, in_channels=[256, 512, 1024], out_channels=[256, 512, 1024], 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, 512], num_heads=[4, 8, 16], block_cfg=dict(type='MaxSigmoidCSPLayerWithTwoConv')), bbox_head=dict( type='YOLOWorldHead', head_module=dict( type='YOLOWorldHeadModule', num_classes=80, in_channels=[256, 512, 1024], widen_factor=0.5, 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), border=(-320, -320), border_val=(114, 114, 114), min_area_ratio=0.01, use_mask_refine=True), dict( type='YOLOv5MultiModalMixUp', prob=0.15, 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), 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=(0.5, 1.5), 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), border=(-320, -320), border_val=(114, 114, 114), min_area_ratio=0.01, use_mask_refine=True), dict( type='YOLOv5MultiModalMixUp', prob=0.15, 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), 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( 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=(0.5, 1.5), 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 custom_imports = dict(imports=['yolo_world'], allow_failed_imports=False) num_training_classes = 80 text_channels = 512 neck_embed_channels = [128, 256, 512] neck_num_heads = [4, 8, 16] text_model_name = '../pretrained_models/clip-vit-base-patch32-projection' mixup_prob = 0.15 copypaste_prob = 0.3 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')) ] 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), border=(-320, -320), border_val=(114, 114, 114), min_area_ratio=0.01, use_mask_refine=True) ] 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), border=(-320, -320), border_val=(114, 114, 114), min_area_ratio=0.01, use_mask_refine=True), dict( type='YOLOv5MultiModalMixUp', prob=0.15, 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=0.3), dict( type='YOLOv5RandomAffine', max_rotate_degree=0.0, max_shear_degree=0.0, max_aspect_ratio=100.0, scaling_ratio_range=(0.5, 1.5), 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_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco' 2024/03/27 11:04:23 - mmengine - INFO - Using SyncBatchNorm() 2024/03/27 11:04:23 - 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 -------------------- 2024/03/27 11:04:55 - mmengine - INFO - Scaled weight_decay to 0.1 2024/03/27 11:04:55 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.logit_scale:lr=0.0002 2024/03/27 11:04:55 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.logit_scale:weight_decay=0.0 2024/03/27 11:04:55 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.logit_scale:lr=0.0002 2024/03/27 11:04:55 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.logit_scale:weight_decay=0.0 2024/03/27 11:04:55 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.logit_scale:lr=0.0002 2024/03/27 11:04:55 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.logit_scale:weight_decay=0.0 Name of parameter - Initialization information backbone.image_model.stem.conv.weight - torch.Size([32, 3, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stem.bn.weight - torch.Size([32]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stem.bn.bias - torch.Size([32]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage1.0.conv.weight - torch.Size([64, 32, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage1.0.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage1.0.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage1.1.main_conv.conv.weight - torch.Size([64, 64, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage1.1.main_conv.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage1.1.main_conv.bn.bias - torch.Size([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage1.1.final_conv.conv.weight - torch.Size([64, 96, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage1.1.final_conv.bn.weight - torch.Size([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage1.1.final_conv.bn.bias - torch.Size([64]): 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([32, 32, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage1.1.blocks.0.conv1.bn.weight - torch.Size([32]): 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([32]): 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([32, 32, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage1.1.blocks.0.conv2.bn.weight - torch.Size([32]): 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([32]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage2.0.conv.weight - torch.Size([128, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.0.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage2.0.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage2.1.main_conv.conv.weight - torch.Size([128, 128, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.1.main_conv.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage2.1.main_conv.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage2.1.final_conv.conv.weight - torch.Size([128, 256, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.1.final_conv.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage2.1.final_conv.bn.bias - torch.Size([128]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.1.blocks.0.conv1.bn.weight - torch.Size([64]): 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([64]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.1.blocks.0.conv2.bn.weight - torch.Size([64]): 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([64]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.1.blocks.1.conv1.bn.weight - torch.Size([64]): 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([64]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage2.1.blocks.1.conv2.bn.weight - torch.Size([64]): 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([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage3.0.conv.weight - torch.Size([256, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.0.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage3.0.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage3.1.main_conv.conv.weight - torch.Size([256, 256, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.1.main_conv.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage3.1.main_conv.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage3.1.final_conv.conv.weight - torch.Size([256, 512, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.1.final_conv.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage3.1.final_conv.bn.bias - torch.Size([256]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.1.blocks.0.conv1.bn.weight - torch.Size([128]): 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.1.blocks.0.conv2.bn.weight - torch.Size([128]): 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.1.blocks.1.conv1.bn.weight - torch.Size([128]): 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage3.1.blocks.1.conv2.bn.weight - torch.Size([128]): 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([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.0.conv.weight - torch.Size([512, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.0.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.0.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.1.main_conv.conv.weight - torch.Size([512, 512, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.1.main_conv.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.1.main_conv.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.1.final_conv.conv.weight - torch.Size([512, 768, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.1.final_conv.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.1.final_conv.bn.bias - torch.Size([512]): 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([256, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.1.blocks.0.conv1.bn.weight - torch.Size([256]): 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([256]): 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([256, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.1.blocks.0.conv2.bn.weight - torch.Size([256]): 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([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.2.conv1.conv.weight - torch.Size([256, 512, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.2.conv1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.2.conv1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.2.conv2.conv.weight - torch.Size([512, 1024, 1, 1]): Initialized by user-defined `init_weights` in YOLOv8CSPDarknet backbone.image_model.stage4.2.conv2.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector backbone.image_model.stage4.2.conv2.bn.bias - torch.Size([512]): 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([256, 768, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.0.main_conv.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.0.main_conv.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.0.final_conv.conv.weight - torch.Size([256, 512, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.0.final_conv.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.0.final_conv.bn.bias - torch.Size([256]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.0.blocks.0.conv1.bn.weight - torch.Size([128]): 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.0.blocks.0.conv2.bn.weight - torch.Size([128]): 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([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.0.attn_block.bias - torch.Size([4]): 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([128, 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.0.attn_block.project_conv.bn.weight - torch.Size([128]): 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([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.1.main_conv.conv.weight - torch.Size([128, 384, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.1.main_conv.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.1.main_conv.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.1.final_conv.conv.weight - torch.Size([128, 256, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.1.final_conv.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.1.final_conv.bn.bias - torch.Size([128]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.1.blocks.0.conv1.bn.weight - torch.Size([64]): 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([64]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.1.blocks.0.conv2.bn.weight - torch.Size([64]): 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([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.top_down_layers.1.attn_block.bias - torch.Size([2]): 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([64, 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([64]): 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([64, 64, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.top_down_layers.1.attn_block.project_conv.bn.weight - torch.Size([64]): 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([64]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.downsample_layers.0.conv.weight - torch.Size([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.downsample_layers.0.bn.weight - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.downsample_layers.0.bn.bias - torch.Size([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.downsample_layers.1.conv.weight - torch.Size([256, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.downsample_layers.1.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.downsample_layers.1.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.0.main_conv.conv.weight - torch.Size([256, 384, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.0.main_conv.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.0.main_conv.bn.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.0.final_conv.conv.weight - torch.Size([256, 512, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.0.final_conv.bn.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.0.final_conv.bn.bias - torch.Size([256]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.0.blocks.0.conv1.bn.weight - torch.Size([128]): 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.0.blocks.0.conv2.bn.weight - torch.Size([128]): 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([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.0.attn_block.bias - torch.Size([4]): 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([128, 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([128]): 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([128, 128, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.0.attn_block.project_conv.bn.weight - torch.Size([128]): 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([128]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.1.main_conv.conv.weight - torch.Size([512, 768, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.1.main_conv.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.1.main_conv.bn.bias - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.1.final_conv.conv.weight - torch.Size([512, 1024, 1, 1]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.1.final_conv.bn.weight - torch.Size([512]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.1.final_conv.bn.bias - torch.Size([512]): 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([256, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.1.blocks.0.conv1.bn.weight - torch.Size([256]): 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([256]): 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([256, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.1.blocks.0.conv2.bn.weight - torch.Size([256]): 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([256]): The value is the same before and after calling `init_weights` of YOLOWorldDetector neck.bottom_up_layers.1.attn_block.bias - torch.Size([8]): 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([256, 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([256]): 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([256, 256, 3, 3]): Initialized by user-defined `init_weights` in YOLOWorldPAFPN neck.bottom_up_layers.1.attn_block.project_conv.bn.weight - torch.Size([256]): 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([256]): 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([128, 128, 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([128]): 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([128]): 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([128, 128, 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([128]): 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([128]): 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, 128, 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([128, 256, 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([128]): 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([128]): 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([128, 128, 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([128]): 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([128]): 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, 128, 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([128, 512, 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([128]): 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([128]): 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([128, 128, 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([128]): 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([128]): 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, 128, 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, 128, 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, 256, 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, 512, 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 2024/03/27 11:05:04 - mmengine - INFO - Load checkpoint from pretrained_models/yolo_world_s_clip_t2i_bn_2e-3adamw_32xb16-100e_obj365v1_goldg_train-55b943ea.pth 2024/03/27 11:05:04 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2024/03/27 11:05:04 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2024/03/27 11:05:04 - mmengine - INFO - Checkpoints will be saved to /group/40034/adriancheng/YOLOWorld_Master/work_dirs/yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco. 2024/03/27 11:05:46 - mmengine - INFO - Epoch(train) [1][ 50/925] lr: 3.5315e-06 eta: 17:30:47 time: 0.8526 data_time: 0.2520 memory: 13012 grad_norm: nan loss: 555.0348 loss_cls: 232.1642 loss_bbox: 158.9915 loss_dfl: 163.8791 2024/03/27 11:06:22 - mmengine - INFO - Epoch(train) [1][100/925] lr: 7.1351e-06 eta: 16:06:42 time: 0.7172 data_time: 0.0119 memory: 5288 grad_norm: 1012.2744 loss: 511.8793 loss_cls: 209.0046 loss_bbox: 146.3251 loss_dfl: 156.5496 2024/03/27 11:06:52 - mmengine - INFO - Epoch(train) [1][150/925] lr: 1.0739e-05 eta: 14:47:17 time: 0.5929 data_time: 0.0040 memory: 5475 grad_norm: 879.8209 loss: 503.1238 loss_cls: 204.9316 loss_bbox: 143.8560 loss_dfl: 154.3362 2024/03/27 11:07:24 - mmengine - INFO - Epoch(train) [1][200/925] lr: 1.4342e-05 eta: 14:24:13 time: 0.6478 data_time: 0.0039 memory: 5248 grad_norm: 883.8611 loss: 496.2268 loss_cls: 201.7734 loss_bbox: 142.2944 loss_dfl: 152.1591 2024/03/27 11:07:54 - mmengine - INFO - Epoch(train) [1][250/925] lr: 1.7946e-05 eta: 13:55:12 time: 0.5869 data_time: 0.0038 memory: 5288 grad_norm: 881.7240 loss: 482.5765 loss_cls: 193.7257 loss_bbox: 137.8358 loss_dfl: 151.0150 2024/03/27 11:08:17 - mmengine - INFO - Epoch(train) [1][300/925] lr: 2.1550e-05 eta: 13:10:17 time: 0.4628 data_time: 0.0042 memory: 5208 grad_norm: 901.1472 loss: 485.8289 loss_cls: 196.6126 loss_bbox: 138.5415 loss_dfl: 150.6747 2024/03/27 11:08:42 - mmengine - INFO - Epoch(train) [1][350/925] lr: 2.5153e-05 eta: 12:45:16 time: 0.5038 data_time: 0.0044 memory: 5115 grad_norm: 884.1115 loss: 489.5420 loss_cls: 196.7732 loss_bbox: 140.3587 loss_dfl: 152.4101 2024/03/27 11:09:02 - mmengine - INFO - Epoch(train) [1][400/925] lr: 2.8757e-05 eta: 12:11:29 time: 0.4065 data_time: 0.0047 memory: 5515 grad_norm: 883.7142 loss: 482.1096 loss_cls: 192.6552 loss_bbox: 139.3272 loss_dfl: 150.1272 2024/03/27 11:09:21 - mmengine - INFO - Epoch(train) [1][450/925] lr: 3.2360e-05 eta: 11:41:05 time: 0.3768 data_time: 0.0046 memory: 5168 grad_norm: 850.7541 loss: 477.0488 loss_cls: 189.7898 loss_bbox: 137.6940 loss_dfl: 149.5651 2024/03/27 11:09:41 - mmengine - INFO - Epoch(train) [1][500/925] lr: 3.5964e-05 eta: 11:19:42 time: 0.4012 data_time: 0.0084 memory: 5556 grad_norm: 904.7820 loss: 474.1091 loss_cls: 188.2929 loss_bbox: 136.7781 loss_dfl: 149.0381 2024/03/27 11:10:02 - mmengine - INFO - Epoch(train) [1][550/925] lr: 3.9568e-05 eta: 11:04:14 time: 0.4200 data_time: 0.0168 memory: 5488 grad_norm: 912.3349 loss: 476.8185 loss_cls: 187.8258 loss_bbox: 138.9035 loss_dfl: 150.0893 2024/03/27 11:10:23 - mmengine - INFO - Epoch(train) [1][600/925] lr: 4.3171e-05 eta: 10:51:16 time: 0.4200 data_time: 0.0046 memory: 5382 grad_norm: 986.5156 loss: 475.6419 loss_cls: 189.1389 loss_bbox: 136.9860 loss_dfl: 149.5170 2024/03/27 11:10:45 - mmengine - INFO - Epoch(train) [1][650/925] lr: 4.6775e-05 eta: 10:40:29 time: 0.4224 data_time: 0.0045 memory: 5395 grad_norm: 950.5020 loss: 465.9062 loss_cls: 180.9597 loss_bbox: 136.2555 loss_dfl: 148.6911 2024/03/27 11:11:05 - mmengine - INFO - Epoch(train) [1][700/925] lr: 5.0378e-05 eta: 10:29:10 time: 0.3991 data_time: 0.0045 memory: 5676 grad_norm: 961.3510 loss: 470.2279 loss_cls: 185.3406 loss_bbox: 136.5516 loss_dfl: 148.3357 2024/03/27 11:11:24 - mmengine - INFO - Epoch(train) [1][750/925] lr: 5.3982e-05 eta: 10:18:54 time: 0.3941 data_time: 0.0047 memory: 5368 grad_norm: 932.3065 loss: 467.7731 loss_cls: 182.7551 loss_bbox: 136.4674 loss_dfl: 148.5506 2024/03/27 11:11:44 - mmengine - INFO - Epoch(train) [1][800/925] lr: 5.7586e-05 eta: 10:10:26 time: 0.4016 data_time: 0.0047 memory: 5222 grad_norm: 976.1622 loss: 464.0418 loss_cls: 182.6241 loss_bbox: 133.4666 loss_dfl: 147.9512 2024/03/27 11:12:04 - mmengine - INFO - Epoch(train) [1][850/925] lr: 6.1189e-05 eta: 10:02:58 time: 0.4021 data_time: 0.0046 memory: 5448 grad_norm: 1131.3322 loss: 471.5963 loss_cls: 187.5606 loss_bbox: 135.9760 loss_dfl: 148.0598 2024/03/27 11:12:25 - mmengine - INFO - Epoch(train) [1][900/925] lr: 6.4793e-05 eta: 9:56:39 time: 0.4074 data_time: 0.0045 memory: 5648 grad_norm: 987.0961 loss: 469.2162 loss_cls: 185.5950 loss_bbox: 135.5428 loss_dfl: 148.0785 2024/03/27 11:12:37 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:13:03 - mmengine - INFO - Epoch(train) [2][ 50/925] lr: 6.9329e-05 eta: 9:57:01 time: 0.5031 data_time: 0.0761 memory: 9630 grad_norm: 965.4756 loss: 472.9412 loss_cls: 187.0698 loss_bbox: 136.7738 loss_dfl: 149.0977 2024/03/27 11:13:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:13:22 - mmengine - INFO - Epoch(train) [2][100/925] lr: 7.2889e-05 eta: 9:50:53 time: 0.3940 data_time: 0.0043 memory: 5310 grad_norm: 985.9147 loss: 463.6623 loss_cls: 181.5508 loss_bbox: 134.7904 loss_dfl: 147.3211 2024/03/27 11:13:44 - mmengine - INFO - Epoch(train) [2][150/925] lr: 7.6448e-05 eta: 9:47:30 time: 0.4333 data_time: 0.0046 memory: 5270 grad_norm: 1048.8869 loss: 463.3011 loss_cls: 182.7015 loss_bbox: 133.4100 loss_dfl: 147.1895 2024/03/27 11:14:04 - mmengine - INFO - Epoch(train) [2][200/925] lr: 8.0007e-05 eta: 9:42:06 time: 0.3908 data_time: 0.0046 memory: 5296 grad_norm: 1068.0920 loss: 465.6220 loss_cls: 181.9560 loss_bbox: 135.6931 loss_dfl: 147.9728 2024/03/27 11:14:25 - mmengine - INFO - Epoch(train) [2][250/925] lr: 8.3566e-05 eta: 9:38:41 time: 0.4209 data_time: 0.0044 memory: 5350 grad_norm: 950.1551 loss: 472.9426 loss_cls: 186.3479 loss_bbox: 136.6275 loss_dfl: 149.9672 2024/03/27 11:14:44 - mmengine - INFO - Epoch(train) [2][300/925] lr: 8.7125e-05 eta: 9:33:42 time: 0.3840 data_time: 0.0045 memory: 5376 grad_norm: 1075.0062 loss: 466.9184 loss_cls: 182.0392 loss_bbox: 136.2039 loss_dfl: 148.6753 2024/03/27 11:15:04 - mmengine - INFO - Epoch(train) [2][350/925] lr: 9.0684e-05 eta: 9:29:57 time: 0.4023 data_time: 0.0042 memory: 5243 grad_norm: 1041.5603 loss: 461.2908 loss_cls: 180.9104 loss_bbox: 133.0210 loss_dfl: 147.3595 2024/03/27 11:15:23 - mmengine - INFO - Epoch(train) [2][400/925] lr: 9.4243e-05 eta: 9:25:53 time: 0.3900 data_time: 0.0046 memory: 5376 grad_norm: 1061.7065 loss: 464.6026 loss_cls: 182.6304 loss_bbox: 134.4190 loss_dfl: 147.5532 2024/03/27 11:15:44 - mmengine - INFO - Epoch(train) [2][450/925] lr: 9.7802e-05 eta: 9:23:00 time: 0.4106 data_time: 0.0045 memory: 5616 grad_norm: 1034.5843 loss: 469.9894 loss_cls: 183.1080 loss_bbox: 138.4271 loss_dfl: 148.4544 2024/03/27 11:16:03 - mmengine - INFO - Epoch(train) [2][500/925] lr: 1.0136e-04 eta: 9:19:16 time: 0.3862 data_time: 0.0048 memory: 5256 grad_norm: 1034.5335 loss: 464.3608 loss_cls: 181.5194 loss_bbox: 134.5600 loss_dfl: 148.2814 2024/03/27 11:16:23 - mmengine - INFO - Epoch(train) [2][550/925] lr: 1.0492e-04 eta: 9:16:24 time: 0.4017 data_time: 0.0146 memory: 5550 grad_norm: 1068.7191 loss: 475.5755 loss_cls: 186.9860 loss_bbox: 138.7835 loss_dfl: 149.8060 2024/03/27 11:16:44 - mmengine - INFO - Epoch(train) [2][600/925] lr: 1.0848e-04 eta: 9:14:21 time: 0.4182 data_time: 0.0051 memory: 5390 grad_norm: 1026.5042 loss: 460.0308 loss_cls: 180.3853 loss_bbox: 132.6315 loss_dfl: 147.0140 2024/03/27 11:17:04 - mmengine - INFO - Epoch(train) [2][650/925] lr: 1.1204e-04 eta: 9:11:40 time: 0.3990 data_time: 0.0047 memory: 5750 grad_norm: 1121.1187 loss: 472.8577 loss_cls: 185.8031 loss_bbox: 137.8424 loss_dfl: 149.2121 2024/03/27 11:17:23 - mmengine - INFO - Epoch(train) [2][700/925] lr: 1.1560e-04 eta: 9:08:07 time: 0.3717 data_time: 0.0163 memory: 5630 grad_norm: 1084.6612 loss: 463.5999 loss_cls: 181.9099 loss_bbox: 135.1271 loss_dfl: 146.5629 2024/03/27 11:17:43 - mmengine - INFO - Epoch(train) [2][750/925] lr: 1.1916e-04 eta: 9:05:51 time: 0.4017 data_time: 0.0047 memory: 5363 grad_norm: 1191.5536 loss: 461.3674 loss_cls: 179.0406 loss_bbox: 134.4297 loss_dfl: 147.8971 2024/03/27 11:18:03 - mmengine - INFO - Epoch(train) [2][800/925] lr: 1.2271e-04 eta: 9:03:40 time: 0.4012 data_time: 0.0042 memory: 5216 grad_norm: 1103.4253 loss: 460.3258 loss_cls: 179.5058 loss_bbox: 133.5598 loss_dfl: 147.2603 2024/03/27 11:18:23 - mmengine - INFO - Epoch(train) [2][850/925] lr: 1.2627e-04 eta: 9:01:24 time: 0.3955 data_time: 0.0039 memory: 5256 grad_norm: 1132.0632 loss: 468.6077 loss_cls: 183.6104 loss_bbox: 136.9712 loss_dfl: 148.0261 2024/03/27 11:18:43 - mmengine - INFO - Epoch(train) [2][900/925] lr: 1.2983e-04 eta: 8:59:29 time: 0.4032 data_time: 0.0049 memory: 5203 grad_norm: 1079.8550 loss: 459.4419 loss_cls: 179.4052 loss_bbox: 133.4412 loss_dfl: 146.5955 2024/03/27 11:18:52 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:19:17 - mmengine - INFO - Epoch(train) [3][ 50/925] lr: 1.3348e-04 eta: 8:58:38 time: 0.4783 data_time: 0.0608 memory: 5670 grad_norm: 1183.3286 loss: 465.1488 loss_cls: 181.6738 loss_bbox: 136.2002 loss_dfl: 147.2748 2024/03/27 11:19:38 - mmengine - INFO - Epoch(train) [3][100/925] lr: 1.3699e-04 eta: 8:57:34 time: 0.4257 data_time: 0.0274 memory: 5496 grad_norm: 1285.0601 loss: 465.8563 loss_cls: 182.7262 loss_bbox: 135.1236 loss_dfl: 148.0065 2024/03/27 11:19:57 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:19:57 - mmengine - INFO - Epoch(train) [3][150/925] lr: 1.4051e-04 eta: 8:55:21 time: 0.3863 data_time: 0.0045 memory: 5416 grad_norm: 1074.9794 loss: 465.4501 loss_cls: 181.8989 loss_bbox: 135.9190 loss_dfl: 147.6323 2024/03/27 11:20:17 - mmengine - INFO - Epoch(train) [3][200/925] lr: 1.4402e-04 eta: 8:53:34 time: 0.3979 data_time: 0.0044 memory: 5243 grad_norm: 1007.5399 loss: 469.2701 loss_cls: 184.5309 loss_bbox: 136.0979 loss_dfl: 148.6413 2024/03/27 11:20:39 - mmengine - INFO - Epoch(train) [3][250/925] lr: 1.4754e-04 eta: 8:52:43 time: 0.4284 data_time: 0.0201 memory: 5310 grad_norm: inf loss: 456.2772 loss_cls: 176.5847 loss_bbox: 132.9130 loss_dfl: 146.7795 2024/03/27 11:20:58 - mmengine - INFO - Epoch(train) [3][300/925] lr: 1.5105e-04 eta: 8:50:30 time: 0.3781 data_time: 0.0046 memory: 5483 grad_norm: 1125.8229 loss: 467.0850 loss_cls: 182.2541 loss_bbox: 136.5778 loss_dfl: 148.2531 2024/03/27 11:21:18 - mmengine - INFO - Epoch(train) [3][350/925] lr: 1.5456e-04 eta: 8:49:06 time: 0.4053 data_time: 0.0045 memory: 5363 grad_norm: 1066.6673 loss: 464.5564 loss_cls: 181.7063 loss_bbox: 134.9317 loss_dfl: 147.9183 2024/03/27 11:21:39 - mmengine - INFO - Epoch(train) [3][400/925] lr: 1.5808e-04 eta: 8:47:58 time: 0.4133 data_time: 0.0093 memory: 5443 grad_norm: 1143.9427 loss: 470.1694 loss_cls: 184.9431 loss_bbox: 136.5810 loss_dfl: 148.6453 2024/03/27 11:21:58 - mmengine - INFO - Epoch(train) [3][450/925] lr: 1.6159e-04 eta: 8:46:24 time: 0.3956 data_time: 0.0048 memory: 6003 grad_norm: 1301.2053 loss: 467.3777 loss_cls: 183.5044 loss_bbox: 135.3289 loss_dfl: 148.5445 2024/03/27 11:22:18 - mmengine - INFO - Epoch(train) [3][500/925] lr: 1.6511e-04 eta: 8:44:54 time: 0.3956 data_time: 0.0043 memory: 5256 grad_norm: 1199.1886 loss: 456.8786 loss_cls: 177.1418 loss_bbox: 133.8098 loss_dfl: 145.9269 2024/03/27 11:22:39 - mmengine - INFO - Epoch(train) [3][550/925] lr: 1.6862e-04 eta: 8:43:52 time: 0.4125 data_time: 0.0042 memory: 5231 grad_norm: 1156.9909 loss: 474.4858 loss_cls: 186.9302 loss_bbox: 138.2945 loss_dfl: 149.2611 2024/03/27 11:22:59 - mmengine - INFO - Epoch(train) [3][600/925] lr: 1.7214e-04 eta: 8:42:34 time: 0.4009 data_time: 0.0042 memory: 5750 grad_norm: 1171.3518 loss: 476.4212 loss_cls: 187.7128 loss_bbox: 139.0950 loss_dfl: 149.6133 2024/03/27 11:23:18 - mmengine - INFO - Epoch(train) [3][650/925] lr: 1.7565e-04 eta: 8:40:55 time: 0.3843 data_time: 0.0045 memory: 5736 grad_norm: 1341.6753 loss: 465.8284 loss_cls: 181.3802 loss_bbox: 136.2663 loss_dfl: 148.1819 2024/03/27 11:23:40 - mmengine - INFO - Epoch(train) [3][700/925] lr: 1.7916e-04 eta: 8:40:36 time: 0.4393 data_time: 0.0045 memory: 5563 grad_norm: 1111.7491 loss: 469.6718 loss_cls: 182.3309 loss_bbox: 138.5398 loss_dfl: 148.8010 2024/03/27 11:24:01 - mmengine - INFO - Epoch(train) [3][750/925] lr: 1.8268e-04 eta: 8:39:43 time: 0.4143 data_time: 0.0046 memory: 5217 grad_norm: 1144.7076 loss: 468.5893 loss_cls: 183.4448 loss_bbox: 136.9790 loss_dfl: 148.1656 2024/03/27 11:24:19 - mmengine - INFO - Epoch(train) [3][800/925] lr: 1.8619e-04 eta: 8:37:53 time: 0.3715 data_time: 0.0045 memory: 5163 grad_norm: 1141.6381 loss: 469.4021 loss_cls: 186.1436 loss_bbox: 135.3917 loss_dfl: 147.8667 2024/03/27 11:24:41 - mmengine - INFO - Epoch(train) [3][850/925] lr: 1.8971e-04 eta: 8:37:23 time: 0.4290 data_time: 0.0116 memory: 5310 grad_norm: 1200.9949 loss: 466.8873 loss_cls: 182.1467 loss_bbox: 136.3410 loss_dfl: 148.3996 2024/03/27 11:25:01 - mmengine - INFO - Epoch(train) [3][900/925] lr: 1.9322e-04 eta: 8:36:14 time: 0.3991 data_time: 0.0045 memory: 5350 grad_norm: 1346.2003 loss: 464.0190 loss_cls: 179.9240 loss_bbox: 136.0159 loss_dfl: 148.0791 2024/03/27 11:25:10 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:25:35 - mmengine - INFO - Epoch(train) [4][ 50/925] lr: 1.9258e-04 eta: 8:36:10 time: 0.4922 data_time: 0.0851 memory: 5430 grad_norm: 1202.0768 loss: 467.9830 loss_cls: 183.3799 loss_bbox: 136.2172 loss_dfl: 148.3859 2024/03/27 11:25:55 - mmengine - INFO - Epoch(train) [4][100/925] lr: 1.9258e-04 eta: 8:35:06 time: 0.4010 data_time: 0.0020 memory: 5350 grad_norm: 1280.4293 loss: 474.0265 loss_cls: 184.9758 loss_bbox: 138.0880 loss_dfl: 150.9627 2024/03/27 11:26:15 - mmengine - INFO - Epoch(train) [4][150/925] lr: 1.9258e-04 eta: 8:34:01 time: 0.3994 data_time: 0.0017 memory: 5323 grad_norm: 1234.7142 loss: 462.3128 loss_cls: 183.2891 loss_bbox: 132.3181 loss_dfl: 146.7057 2024/03/27 11:26:35 - mmengine - INFO - Epoch(train) [4][200/925] lr: 1.9258e-04 eta: 8:33:10 time: 0.4089 data_time: 0.0019 memory: 5683 grad_norm: 1164.4290 loss: 468.0203 loss_cls: 182.1849 loss_bbox: 137.7401 loss_dfl: 148.0954 2024/03/27 11:26:45 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:26:55 - mmengine - INFO - Epoch(train) [4][250/925] lr: 1.9258e-04 eta: 8:31:57 time: 0.3900 data_time: 0.0021 memory: 5750 grad_norm: 1164.3211 loss: 476.0331 loss_cls: 187.8377 loss_bbox: 139.1562 loss_dfl: 149.0392 2024/03/27 11:27:16 - mmengine - INFO - Epoch(train) [4][300/925] lr: 1.9258e-04 eta: 8:31:16 time: 0.4163 data_time: 0.0019 memory: 5283 grad_norm: 1067.5445 loss: 470.0617 loss_cls: 183.3983 loss_bbox: 137.6380 loss_dfl: 149.0253 2024/03/27 11:27:36 - mmengine - INFO - Epoch(train) [4][350/925] lr: 1.9258e-04 eta: 8:30:34 time: 0.4146 data_time: 0.0019 memory: 5350 grad_norm: 1083.1184 loss: 469.8188 loss_cls: 185.4971 loss_bbox: 136.5325 loss_dfl: 147.7892 2024/03/27 11:27:56 - mmengine - INFO - Epoch(train) [4][400/925] lr: 1.9258e-04 eta: 8:29:36 time: 0.3997 data_time: 0.0018 memory: 5231 grad_norm: 1174.0955 loss: 480.5900 loss_cls: 189.5485 loss_bbox: 140.4612 loss_dfl: 150.5803 2024/03/27 11:28:16 - mmengine - INFO - Epoch(train) [4][450/925] lr: 1.9258e-04 eta: 8:28:36 time: 0.3965 data_time: 0.0019 memory: 5523 grad_norm: 1231.6279 loss: 470.3336 loss_cls: 184.5829 loss_bbox: 136.3531 loss_dfl: 149.3977 2024/03/27 11:28:38 - mmengine - INFO - Epoch(train) [4][500/925] lr: 1.9258e-04 eta: 8:28:09 time: 0.4259 data_time: 0.0019 memory: 5150 grad_norm: 1272.2819 loss: 473.3131 loss_cls: 185.7242 loss_bbox: 138.0759 loss_dfl: 149.5131 2024/03/27 11:28:58 - mmengine - INFO - Epoch(train) [4][550/925] lr: 1.9258e-04 eta: 8:27:14 time: 0.3994 data_time: 0.0018 memory: 5550 grad_norm: 1067.2736 loss: 471.8324 loss_cls: 184.2415 loss_bbox: 139.4548 loss_dfl: 148.1361 2024/03/27 11:29:18 - mmengine - INFO - Epoch(train) [4][600/925] lr: 1.9258e-04 eta: 8:26:22 time: 0.4015 data_time: 0.0018 memory: 5576 grad_norm: 1223.3011 loss: 471.8713 loss_cls: 184.7414 loss_bbox: 137.6507 loss_dfl: 149.4793 2024/03/27 11:29:38 - mmengine - INFO - Epoch(train) [4][650/925] lr: 1.9258e-04 eta: 8:25:39 time: 0.4101 data_time: 0.0018 memory: 5843 grad_norm: 1269.5330 loss: 472.2640 loss_cls: 182.6883 loss_bbox: 139.5246 loss_dfl: 150.0512 2024/03/27 11:29:59 - mmengine - INFO - Epoch(train) [4][700/925] lr: 1.9258e-04 eta: 8:24:54 time: 0.4061 data_time: 0.0019 memory: 5483 grad_norm: 1212.4193 loss: 466.7596 loss_cls: 183.6430 loss_bbox: 135.2010 loss_dfl: 147.9156 2024/03/27 11:30:18 - mmengine - INFO - Epoch(train) [4][750/925] lr: 1.9258e-04 eta: 8:24:01 time: 0.3982 data_time: 0.0018 memory: 5643 grad_norm: 1097.8765 loss: 470.3770 loss_cls: 182.9631 loss_bbox: 137.5344 loss_dfl: 149.8795 2024/03/27 11:30:39 - mmengine - INFO - Epoch(train) [4][800/925] lr: 1.9258e-04 eta: 8:23:20 time: 0.4096 data_time: 0.0021 memory: 5550 grad_norm: 1235.8249 loss: 470.3641 loss_cls: 186.0348 loss_bbox: 135.2407 loss_dfl: 149.0887 2024/03/27 11:30:59 - mmengine - INFO - Epoch(train) [4][850/925] lr: 1.9258e-04 eta: 8:22:23 time: 0.3917 data_time: 0.0021 memory: 5590 grad_norm: 1107.5716 loss: 468.2150 loss_cls: 182.1988 loss_bbox: 137.3677 loss_dfl: 148.6485 2024/03/27 11:31:18 - mmengine - INFO - Epoch(train) [4][900/925] lr: 1.9258e-04 eta: 8:21:32 time: 0.3979 data_time: 0.0020 memory: 5430 grad_norm: 1075.5782 loss: 478.6839 loss_cls: 187.8223 loss_bbox: 140.0460 loss_dfl: 150.8156 2024/03/27 11:31:28 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:31:52 - mmengine - INFO - Epoch(train) [5][ 50/925] lr: 1.9258e-04 eta: 8:21:21 time: 0.4742 data_time: 0.0912 memory: 5630 grad_norm: 1123.6119 loss: 472.4817 loss_cls: 184.7320 loss_bbox: 137.7033 loss_dfl: 150.0463 2024/03/27 11:32:13 - mmengine - INFO - Epoch(train) [5][100/925] lr: 1.9258e-04 eta: 8:20:42 time: 0.4092 data_time: 0.0019 memory: 5376 grad_norm: 1119.5050 loss: 466.3812 loss_cls: 179.8774 loss_bbox: 136.5872 loss_dfl: 149.9166 2024/03/27 11:32:33 - mmengine - INFO - Epoch(train) [5][150/925] lr: 1.9258e-04 eta: 8:19:55 time: 0.4007 data_time: 0.0096 memory: 5083 grad_norm: 1257.8972 loss: 466.9274 loss_cls: 181.8508 loss_bbox: 136.2356 loss_dfl: 148.8409 2024/03/27 11:32:53 - mmengine - INFO - Epoch(train) [5][200/925] lr: 1.9258e-04 eta: 8:19:08 time: 0.3989 data_time: 0.0018 memory: 5390 grad_norm: 1185.9091 loss: 471.7510 loss_cls: 183.2854 loss_bbox: 138.5338 loss_dfl: 149.9317 2024/03/27 11:33:12 - mmengine - INFO - Epoch(train) [5][250/925] lr: 1.9258e-04 eta: 8:18:14 time: 0.3901 data_time: 0.0019 memory: 5723 grad_norm: 1054.4731 loss: 459.0235 loss_cls: 177.7531 loss_bbox: 134.7124 loss_dfl: 146.5580 2024/03/27 11:33:32 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:33:32 - mmengine - INFO - Epoch(train) [5][300/925] lr: 1.9258e-04 eta: 8:17:26 time: 0.3968 data_time: 0.0020 memory: 5456 grad_norm: 1352.6884 loss: 467.5645 loss_cls: 181.0999 loss_bbox: 137.5615 loss_dfl: 148.9031 2024/03/27 11:33:52 - mmengine - INFO - Epoch(train) [5][350/925] lr: 1.9258e-04 eta: 8:16:41 time: 0.3984 data_time: 0.0020 memory: 5336 grad_norm: 1127.9621 loss: 472.3679 loss_cls: 184.8882 loss_bbox: 138.1173 loss_dfl: 149.3624 2024/03/27 11:34:11 - mmengine - INFO - Epoch(train) [5][400/925] lr: 1.9258e-04 eta: 8:15:48 time: 0.3894 data_time: 0.0017 memory: 5137 grad_norm: 1178.1074 loss: 458.9565 loss_cls: 179.7503 loss_bbox: 131.7605 loss_dfl: 147.4457 2024/03/27 11:34:32 - mmengine - INFO - Epoch(train) [5][450/925] lr: 1.9258e-04 eta: 8:15:12 time: 0.4075 data_time: 0.0017 memory: 5177 grad_norm: 1159.1777 loss: 469.1505 loss_cls: 184.6405 loss_bbox: 136.2624 loss_dfl: 148.2476 2024/03/27 11:34:52 - mmengine - INFO - Epoch(train) [5][500/925] lr: 1.9258e-04 eta: 8:14:33 time: 0.4043 data_time: 0.0018 memory: 5776 grad_norm: inf loss: 474.8197 loss_cls: 184.0843 loss_bbox: 140.3806 loss_dfl: 150.3548 2024/03/27 11:35:12 - mmengine - INFO - Epoch(train) [5][550/925] lr: 1.9258e-04 eta: 8:13:49 time: 0.3968 data_time: 0.0021 memory: 5243 grad_norm: 1229.0844 loss: 470.6235 loss_cls: 183.9824 loss_bbox: 137.5375 loss_dfl: 149.1036 2024/03/27 11:35:32 - mmengine - INFO - Epoch(train) [5][600/925] lr: 1.9258e-04 eta: 8:13:11 time: 0.4045 data_time: 0.0058 memory: 5310 grad_norm: 1167.0731 loss: 460.4410 loss_cls: 177.9452 loss_bbox: 134.6395 loss_dfl: 147.8563 2024/03/27 11:35:52 - mmengine - INFO - Epoch(train) [5][650/925] lr: 1.9258e-04 eta: 8:12:24 time: 0.3924 data_time: 0.0018 memory: 5323 grad_norm: 1194.3069 loss: 468.9114 loss_cls: 181.9453 loss_bbox: 138.1238 loss_dfl: 148.8423 2024/03/27 11:36:12 - mmengine - INFO - Epoch(train) [5][700/925] lr: 1.9258e-04 eta: 8:11:51 time: 0.4092 data_time: 0.0017 memory: 5376 grad_norm: 1168.6392 loss: 459.6264 loss_cls: 176.9326 loss_bbox: 135.2503 loss_dfl: 147.4435 2024/03/27 11:36:32 - mmengine - INFO - Epoch(train) [5][750/925] lr: 1.9258e-04 eta: 8:11:12 time: 0.4008 data_time: 0.0017 memory: 5323 grad_norm: 1151.5845 loss: 470.6454 loss_cls: 183.8067 loss_bbox: 136.4506 loss_dfl: 150.3881 2024/03/27 11:36:52 - mmengine - INFO - Epoch(train) [5][800/925] lr: 1.9258e-04 eta: 8:10:35 time: 0.4039 data_time: 0.0017 memory: 5350 grad_norm: 1167.0469 loss: 458.9559 loss_cls: 178.1511 loss_bbox: 134.0523 loss_dfl: 146.7525 2024/03/27 11:37:12 - mmengine - INFO - Epoch(train) [5][850/925] lr: 1.9258e-04 eta: 8:09:55 time: 0.3990 data_time: 0.0019 memory: 5283 grad_norm: 1244.6376 loss: 466.4759 loss_cls: 182.8736 loss_bbox: 135.1032 loss_dfl: 148.4991 2024/03/27 11:37:34 - mmengine - INFO - Epoch(train) [5][900/925] lr: 1.9258e-04 eta: 8:09:38 time: 0.4291 data_time: 0.0262 memory: 5390 grad_norm: 1099.5558 loss: 466.6744 loss_cls: 181.8566 loss_bbox: 135.9505 loss_dfl: 148.8673 2024/03/27 11:37:44 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:37:44 - mmengine - INFO - Saving checkpoint at 5 epochs 2024/03/27 11:37:47 - mmengine - WARNING - `save_param_scheduler` is True but `self.param_schedulers` is None, so skip saving parameter schedulers 2024/03/27 11:37:53 - mmengine - INFO - Epoch(val) [5][ 50/625] eta: 0:00:43 time: 0.0756 data_time: 0.0081 memory: 9147 2024/03/27 11:37:55 - mmengine - INFO - Epoch(val) [5][100/625] eta: 0:00:31 time: 0.0447 data_time: 0.0004 memory: 838 2024/03/27 11:37:57 - mmengine - INFO - Epoch(val) [5][150/625] eta: 0:00:25 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 11:38:00 - mmengine - INFO - Epoch(val) [5][200/625] eta: 0:00:22 time: 0.0431 data_time: 0.0009 memory: 838 2024/03/27 11:38:02 - mmengine - INFO - Epoch(val) [5][250/625] eta: 0:00:19 time: 0.0463 data_time: 0.0004 memory: 838 2024/03/27 11:38:04 - mmengine - INFO - Epoch(val) [5][300/625] eta: 0:00:16 time: 0.0424 data_time: 0.0004 memory: 838 2024/03/27 11:38:06 - mmengine - INFO - Epoch(val) [5][350/625] eta: 0:00:13 time: 0.0441 data_time: 0.0004 memory: 838 2024/03/27 11:38:08 - mmengine - INFO - Epoch(val) [5][400/625] eta: 0:00:10 time: 0.0437 data_time: 0.0003 memory: 838 2024/03/27 11:38:11 - mmengine - INFO - Epoch(val) [5][450/625] eta: 0:00:08 time: 0.0423 data_time: 0.0004 memory: 838 2024/03/27 11:38:13 - mmengine - INFO - Epoch(val) [5][500/625] eta: 0:00:05 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 11:38:15 - mmengine - INFO - Epoch(val) [5][550/625] eta: 0:00:03 time: 0.0371 data_time: 0.0003 memory: 838 2024/03/27 11:38:16 - mmengine - INFO - Epoch(val) [5][600/625] eta: 0:00:01 time: 0.0352 data_time: 0.0003 memory: 838 2024/03/27 11:38:39 - mmengine - INFO - Evaluating bbox... 2024/03/27 11:40:18 - mmengine - INFO - bbox_mAP_copypaste: 0.380 0.534 0.415 0.217 0.419 0.506 2024/03/27 11:40:20 - mmengine - INFO - Epoch(val) [5][625/625] coco/bbox_mAP: 0.3800 coco/bbox_mAP_50: 0.5340 coco/bbox_mAP_75: 0.4150 coco/bbox_mAP_s: 0.2170 coco/bbox_mAP_m: 0.4190 coco/bbox_mAP_l: 0.5060 data_time: 0.0629 time: 0.0971 2024/03/27 11:40:50 - mmengine - INFO - Epoch(train) [6][ 50/925] lr: 1.9010e-04 eta: 8:11:02 time: 0.5950 data_time: 0.2035 memory: 5470 grad_norm: 1275.5645 loss: 471.6448 loss_cls: 183.7328 loss_bbox: 138.5558 loss_dfl: 149.3562 2024/03/27 11:41:12 - mmengine - INFO - Epoch(train) [6][100/925] lr: 1.9010e-04 eta: 8:10:55 time: 0.4451 data_time: 0.0627 memory: 5336 grad_norm: 1308.7876 loss: 465.3450 loss_cls: 179.3730 loss_bbox: 136.6405 loss_dfl: 149.3315 2024/03/27 11:41:35 - mmengine - INFO - Epoch(train) [6][150/925] lr: 1.9010e-04 eta: 8:11:04 time: 0.4670 data_time: 0.0485 memory: 5283 grad_norm: 1307.1624 loss: 457.6652 loss_cls: 174.6084 loss_bbox: 135.2278 loss_dfl: 147.8289 2024/03/27 11:41:56 - mmengine - INFO - Epoch(train) [6][200/925] lr: 1.9010e-04 eta: 8:10:30 time: 0.4078 data_time: 0.0021 memory: 5136 grad_norm: 1024.1415 loss: 467.0551 loss_cls: 182.6143 loss_bbox: 135.5667 loss_dfl: 148.8741 2024/03/27 11:42:16 - mmengine - INFO - Epoch(train) [6][250/925] lr: 1.9010e-04 eta: 8:09:50 time: 0.3985 data_time: 0.0208 memory: 5430 grad_norm: 1049.3033 loss: 466.7626 loss_cls: 181.6121 loss_bbox: 136.8998 loss_dfl: 148.2507 2024/03/27 11:42:41 - mmengine - INFO - Epoch(train) [6][300/925] lr: 1.9010e-04 eta: 8:10:21 time: 0.5004 data_time: 0.0850 memory: 5350 grad_norm: 1178.8284 loss: 463.1585 loss_cls: 178.2221 loss_bbox: 136.6778 loss_dfl: 148.2586 2024/03/27 11:43:01 - mmengine - INFO - Epoch(train) [6][350/925] lr: 1.9010e-04 eta: 8:09:51 time: 0.4136 data_time: 0.0099 memory: 5496 grad_norm: 1254.0890 loss: 467.4137 loss_cls: 182.0841 loss_bbox: 137.4308 loss_dfl: 147.8987 2024/03/27 11:43:11 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:43:20 - mmengine - INFO - Epoch(train) [6][400/925] lr: 1.9010e-04 eta: 8:08:56 time: 0.3766 data_time: 0.0019 memory: 5510 grad_norm: 1267.0268 loss: 464.5136 loss_cls: 179.8368 loss_bbox: 136.5137 loss_dfl: 148.1632 2024/03/27 11:43:42 - mmengine - INFO - Epoch(train) [6][450/925] lr: 1.9010e-04 eta: 8:08:36 time: 0.4265 data_time: 0.0021 memory: 5510 grad_norm: 1440.5792 loss: 465.3845 loss_cls: 181.3785 loss_bbox: 136.3665 loss_dfl: 147.6394 2024/03/27 11:44:01 - mmengine - INFO - Epoch(train) [6][500/925] lr: 1.9010e-04 eta: 8:07:47 time: 0.3838 data_time: 0.0021 memory: 5536 grad_norm: 1118.0953 loss: 469.1135 loss_cls: 183.6071 loss_bbox: 136.1252 loss_dfl: 149.3812 2024/03/27 11:44:25 - mmengine - INFO - Epoch(train) [6][550/925] lr: 1.9010e-04 eta: 8:07:59 time: 0.4748 data_time: 0.0834 memory: 5283 grad_norm: 1243.8993 loss: 467.8756 loss_cls: 182.0305 loss_bbox: 137.1979 loss_dfl: 148.6472 2024/03/27 11:44:46 - mmengine - INFO - Epoch(train) [6][600/925] lr: 1.9010e-04 eta: 8:07:36 time: 0.4228 data_time: 0.0302 memory: 5483 grad_norm: 1033.8458 loss: 467.9765 loss_cls: 181.8692 loss_bbox: 136.7970 loss_dfl: 149.3103 2024/03/27 11:45:06 - mmengine - INFO - Epoch(train) [6][650/925] lr: 1.9010e-04 eta: 8:06:57 time: 0.3988 data_time: 0.0020 memory: 5456 grad_norm: 1222.5113 loss: 465.8605 loss_cls: 179.6255 loss_bbox: 137.5484 loss_dfl: 148.6867 2024/03/27 11:45:27 - mmengine - INFO - Epoch(train) [6][700/925] lr: 1.9010e-04 eta: 8:06:33 time: 0.4217 data_time: 0.0021 memory: 5323 grad_norm: 1161.8135 loss: 468.8828 loss_cls: 182.7692 loss_bbox: 137.6712 loss_dfl: 148.4424 2024/03/27 11:45:47 - mmengine - INFO - Epoch(train) [6][750/925] lr: 1.9010e-04 eta: 8:06:01 time: 0.4070 data_time: 0.0021 memory: 5723 grad_norm: 1299.5534 loss: 466.1170 loss_cls: 180.0479 loss_bbox: 136.5629 loss_dfl: 149.5062 2024/03/27 11:46:08 - mmengine - INFO - Epoch(train) [6][800/925] lr: 1.9010e-04 eta: 8:05:30 time: 0.4097 data_time: 0.0020 memory: 5390 grad_norm: 1088.4438 loss: 462.2797 loss_cls: 179.3897 loss_bbox: 134.8082 loss_dfl: 148.0817 2024/03/27 11:46:29 - mmengine - INFO - Epoch(train) [6][850/925] lr: 1.9010e-04 eta: 8:05:03 time: 0.4166 data_time: 0.0020 memory: 5416 grad_norm: 1117.8009 loss: 470.2705 loss_cls: 183.8852 loss_bbox: 136.9481 loss_dfl: 149.4372 2024/03/27 11:46:49 - mmengine - INFO - Epoch(train) [6][900/925] lr: 1.9010e-04 eta: 8:04:37 time: 0.4161 data_time: 0.0021 memory: 5376 grad_norm: 1257.7821 loss: 468.6829 loss_cls: 181.0056 loss_bbox: 138.2060 loss_dfl: 149.4712 2024/03/27 11:46:58 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:47:22 - mmengine - INFO - Epoch(train) [7][ 50/925] lr: 1.8762e-04 eta: 8:04:15 time: 0.4793 data_time: 0.0659 memory: 5403 grad_norm: 1285.9197 loss: 467.7396 loss_cls: 180.4687 loss_bbox: 138.2577 loss_dfl: 149.0132 2024/03/27 11:47:43 - mmengine - INFO - Epoch(train) [7][100/925] lr: 1.8762e-04 eta: 8:03:43 time: 0.4054 data_time: 0.0020 memory: 5203 grad_norm: 985.9219 loss: 458.0451 loss_cls: 177.0203 loss_bbox: 133.3995 loss_dfl: 147.6254 2024/03/27 11:48:03 - mmengine - INFO - Epoch(train) [7][150/925] lr: 1.8762e-04 eta: 8:03:04 time: 0.3962 data_time: 0.0020 memory: 5376 grad_norm: 1113.0302 loss: 461.4800 loss_cls: 177.6903 loss_bbox: 135.7786 loss_dfl: 148.0111 2024/03/27 11:48:23 - mmengine - INFO - Epoch(train) [7][200/925] lr: 1.8762e-04 eta: 8:02:28 time: 0.3982 data_time: 0.0019 memory: 5350 grad_norm: 1115.2853 loss: 463.2244 loss_cls: 179.0949 loss_bbox: 136.1091 loss_dfl: 148.0204 2024/03/27 11:48:43 - mmengine - INFO - Epoch(train) [7][250/925] lr: 1.8762e-04 eta: 8:01:58 time: 0.4094 data_time: 0.0021 memory: 5270 grad_norm: 1170.9147 loss: 463.4943 loss_cls: 179.4813 loss_bbox: 136.2619 loss_dfl: 147.7511 2024/03/27 11:49:03 - mmengine - INFO - Epoch(train) [7][300/925] lr: 1.8762e-04 eta: 8:01:23 time: 0.4005 data_time: 0.0019 memory: 5523 grad_norm: 1039.9321 loss: 464.9861 loss_cls: 181.1119 loss_bbox: 135.6873 loss_dfl: 148.1870 2024/03/27 11:49:23 - mmengine - INFO - Epoch(train) [7][350/925] lr: 1.8762e-04 eta: 8:00:47 time: 0.3978 data_time: 0.0073 memory: 5523 grad_norm: 1317.3270 loss: 456.9501 loss_cls: 176.1477 loss_bbox: 134.4652 loss_dfl: 146.3372 2024/03/27 11:49:44 - mmengine - INFO - Epoch(train) [7][400/925] lr: 1.8762e-04 eta: 8:00:22 time: 0.4171 data_time: 0.0021 memory: 5764 grad_norm: 1118.4987 loss: 465.6569 loss_cls: 180.8209 loss_bbox: 135.7144 loss_dfl: 149.1216 2024/03/27 11:50:05 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:50:05 - mmengine - INFO - Epoch(train) [7][450/925] lr: 1.8762e-04 eta: 7:59:55 time: 0.4146 data_time: 0.0020 memory: 5456 grad_norm: 1232.7185 loss: 459.0647 loss_cls: 177.2205 loss_bbox: 134.6519 loss_dfl: 147.1923 2024/03/27 11:50:24 - mmengine - INFO - Epoch(train) [7][500/925] lr: 1.8762e-04 eta: 7:59:18 time: 0.3945 data_time: 0.0099 memory: 5430 grad_norm: 1091.4759 loss: 463.9558 loss_cls: 179.8373 loss_bbox: 135.4500 loss_dfl: 148.6686 2024/03/27 11:50:45 - mmengine - INFO - Epoch(train) [7][550/925] lr: 1.8762e-04 eta: 7:58:48 time: 0.4067 data_time: 0.0021 memory: 5376 grad_norm: 1049.5393 loss: 463.9471 loss_cls: 178.4267 loss_bbox: 137.2137 loss_dfl: 148.3067 2024/03/27 11:51:05 - mmengine - INFO - Epoch(train) [7][600/925] lr: 1.8762e-04 eta: 7:58:14 time: 0.4005 data_time: 0.0019 memory: 5376 grad_norm: 1128.0832 loss: 464.9702 loss_cls: 179.1641 loss_bbox: 137.0871 loss_dfl: 148.7191 2024/03/27 11:51:25 - mmengine - INFO - Epoch(train) [7][650/925] lr: 1.8762e-04 eta: 7:57:39 time: 0.3977 data_time: 0.0020 memory: 5843 grad_norm: 1054.6705 loss: 471.5189 loss_cls: 184.7631 loss_bbox: 137.9306 loss_dfl: 148.8252 2024/03/27 11:51:44 - mmengine - INFO - Epoch(train) [7][700/925] lr: 1.8762e-04 eta: 7:57:00 time: 0.3900 data_time: 0.0021 memory: 5390 grad_norm: inf loss: 463.5804 loss_cls: 179.2079 loss_bbox: 136.3676 loss_dfl: 148.0049 2024/03/27 11:52:04 - mmengine - INFO - Epoch(train) [7][750/925] lr: 1.8762e-04 eta: 7:56:24 time: 0.3945 data_time: 0.0019 memory: 5336 grad_norm: 1171.3013 loss: 464.4522 loss_cls: 178.3684 loss_bbox: 137.8510 loss_dfl: 148.2328 2024/03/27 11:52:24 - mmengine - INFO - Epoch(train) [7][800/925] lr: 1.8762e-04 eta: 7:55:49 time: 0.3963 data_time: 0.0022 memory: 5550 grad_norm: 1175.2397 loss: 457.5604 loss_cls: 176.5856 loss_bbox: 134.2545 loss_dfl: 146.7202 2024/03/27 11:52:44 - mmengine - INFO - Epoch(train) [7][850/925] lr: 1.8762e-04 eta: 7:55:15 time: 0.3980 data_time: 0.0022 memory: 5803 grad_norm: 1125.2116 loss: 470.6144 loss_cls: 182.2741 loss_bbox: 139.1273 loss_dfl: 149.2129 2024/03/27 11:53:04 - mmengine - INFO - Epoch(train) [7][900/925] lr: 1.8762e-04 eta: 7:54:45 time: 0.4048 data_time: 0.0021 memory: 5696 grad_norm: 1122.0833 loss: 463.3738 loss_cls: 178.2783 loss_bbox: 136.4329 loss_dfl: 148.6626 2024/03/27 11:53:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:53:41 - mmengine - INFO - Epoch(train) [8][ 50/925] lr: 1.8515e-04 eta: 7:55:03 time: 0.5404 data_time: 0.1252 memory: 5550 grad_norm: 1091.5107 loss: 468.4183 loss_cls: 182.6711 loss_bbox: 137.0382 loss_dfl: 148.7089 2024/03/27 11:54:01 - mmengine - INFO - Epoch(train) [8][100/925] lr: 1.8515e-04 eta: 7:54:35 time: 0.4095 data_time: 0.0020 memory: 5430 grad_norm: 1046.1247 loss: 455.3768 loss_cls: 175.3696 loss_bbox: 132.5134 loss_dfl: 147.4937 2024/03/27 11:54:22 - mmengine - INFO - Epoch(train) [8][150/925] lr: 1.8515e-04 eta: 7:54:09 time: 0.4121 data_time: 0.0018 memory: 5176 grad_norm: 1087.4007 loss: 467.7871 loss_cls: 183.3783 loss_bbox: 136.6352 loss_dfl: 147.7736 2024/03/27 11:54:43 - mmengine - INFO - Epoch(train) [8][200/925] lr: 1.8515e-04 eta: 7:53:43 time: 0.4142 data_time: 0.0021 memory: 5430 grad_norm: 1358.5783 loss: 462.0656 loss_cls: 178.6018 loss_bbox: 135.9957 loss_dfl: 147.4681 2024/03/27 11:55:02 - mmengine - INFO - Epoch(train) [8][250/925] lr: 1.8515e-04 eta: 7:53:07 time: 0.3914 data_time: 0.0019 memory: 5523 grad_norm: 1161.2629 loss: 462.9350 loss_cls: 179.2193 loss_bbox: 135.3738 loss_dfl: 148.3419 2024/03/27 11:55:22 - mmengine - INFO - Epoch(train) [8][300/925] lr: 1.8515e-04 eta: 7:52:32 time: 0.3933 data_time: 0.0019 memory: 5523 grad_norm: 1049.6236 loss: 462.7791 loss_cls: 178.3181 loss_bbox: 136.7687 loss_dfl: 147.6923 2024/03/27 11:55:43 - mmengine - INFO - Epoch(train) [8][350/925] lr: 1.8515e-04 eta: 7:52:09 time: 0.4177 data_time: 0.0021 memory: 5470 grad_norm: 1121.8757 loss: 458.7495 loss_cls: 176.6969 loss_bbox: 134.3476 loss_dfl: 147.7050 2024/03/27 11:56:02 - mmengine - INFO - Epoch(train) [8][400/925] lr: 1.8515e-04 eta: 7:51:34 time: 0.3943 data_time: 0.0018 memory: 5283 grad_norm: 1059.6174 loss: 463.9846 loss_cls: 178.4427 loss_bbox: 136.5078 loss_dfl: 149.0341 2024/03/27 11:56:22 - mmengine - INFO - Epoch(train) [8][450/925] lr: 1.8515e-04 eta: 7:50:55 time: 0.3853 data_time: 0.0019 memory: 5190 grad_norm: 1300.1722 loss: 459.2644 loss_cls: 177.6668 loss_bbox: 134.3726 loss_dfl: 147.2249 2024/03/27 11:56:43 - mmengine - INFO - Epoch(train) [8][500/925] lr: 1.8515e-04 eta: 7:50:34 time: 0.4213 data_time: 0.0020 memory: 5416 grad_norm: 973.8002 loss: 462.1063 loss_cls: 177.5545 loss_bbox: 135.8687 loss_dfl: 148.6831 2024/03/27 11:56:52 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:57:02 - mmengine - INFO - Epoch(train) [8][550/925] lr: 1.8515e-04 eta: 7:49:58 time: 0.3893 data_time: 0.0021 memory: 5363 grad_norm: 1074.0160 loss: 467.7134 loss_cls: 182.2537 loss_bbox: 136.2504 loss_dfl: 149.2093 2024/03/27 11:57:22 - mmengine - INFO - Epoch(train) [8][600/925] lr: 1.8515e-04 eta: 7:49:24 time: 0.3943 data_time: 0.0020 memory: 5790 grad_norm: 1080.9705 loss: 464.1993 loss_cls: 179.6686 loss_bbox: 136.2004 loss_dfl: 148.3303 2024/03/27 11:57:44 - mmengine - INFO - Epoch(train) [8][650/925] lr: 1.8515e-04 eta: 7:49:09 time: 0.4335 data_time: 0.0129 memory: 5216 grad_norm: 1359.5276 loss: 462.3589 loss_cls: 179.0221 loss_bbox: 135.6612 loss_dfl: 147.6755 2024/03/27 11:58:04 - mmengine - INFO - Epoch(train) [8][700/925] lr: 1.8515e-04 eta: 7:48:40 time: 0.4033 data_time: 0.0020 memory: 5323 grad_norm: 1053.5016 loss: 456.5807 loss_cls: 175.6428 loss_bbox: 134.1855 loss_dfl: 146.7524 2024/03/27 11:58:24 - mmengine - INFO - Epoch(train) [8][750/925] lr: 1.8515e-04 eta: 7:48:10 time: 0.4003 data_time: 0.0018 memory: 5470 grad_norm: 1167.2708 loss: 465.3179 loss_cls: 180.5416 loss_bbox: 136.5074 loss_dfl: 148.2689 2024/03/27 11:58:45 - mmengine - INFO - Epoch(train) [8][800/925] lr: 1.8515e-04 eta: 7:47:46 time: 0.4156 data_time: 0.0019 memory: 5390 grad_norm: 1038.3359 loss: 458.0886 loss_cls: 175.6011 loss_bbox: 135.5107 loss_dfl: 146.9768 2024/03/27 11:59:05 - mmengine - INFO - Epoch(train) [8][850/925] lr: 1.8515e-04 eta: 7:47:20 time: 0.4084 data_time: 0.0019 memory: 5430 grad_norm: 1046.6449 loss: 465.3356 loss_cls: 180.5120 loss_bbox: 136.0727 loss_dfl: 148.7509 2024/03/27 11:59:25 - mmengine - INFO - Epoch(train) [8][900/925] lr: 1.8515e-04 eta: 7:46:43 time: 0.3863 data_time: 0.0018 memory: 5803 grad_norm: 962.5468 loss: 463.4554 loss_cls: 180.1928 loss_bbox: 134.7888 loss_dfl: 148.4739 2024/03/27 11:59:34 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 11:59:58 - mmengine - INFO - Epoch(train) [9][ 50/925] lr: 1.8268e-04 eta: 7:46:24 time: 0.4771 data_time: 0.0632 memory: 5416 grad_norm: 1254.3685 loss: 454.8491 loss_cls: 173.3484 loss_bbox: 134.2241 loss_dfl: 147.2766 2024/03/27 12:00:18 - mmengine - INFO - Epoch(train) [9][100/925] lr: 1.8268e-04 eta: 7:45:52 time: 0.3952 data_time: 0.0019 memory: 5256 grad_norm: 1007.7703 loss: 460.4399 loss_cls: 178.1056 loss_bbox: 134.1009 loss_dfl: 148.2334 2024/03/27 12:00:38 - mmengine - INFO - Epoch(train) [9][150/925] lr: 1.8268e-04 eta: 7:45:27 time: 0.4124 data_time: 0.0020 memory: 5336 grad_norm: 1070.3582 loss: 455.6666 loss_cls: 175.3157 loss_bbox: 133.0305 loss_dfl: 147.3204 2024/03/27 12:00:58 - mmengine - INFO - Epoch(train) [9][200/925] lr: 1.8268e-04 eta: 7:44:55 time: 0.3943 data_time: 0.0020 memory: 5630 grad_norm: 1001.6682 loss: 460.4948 loss_cls: 177.0912 loss_bbox: 135.5100 loss_dfl: 147.8936 2024/03/27 12:01:18 - mmengine - INFO - Epoch(train) [9][250/925] lr: 1.8268e-04 eta: 7:44:28 time: 0.4070 data_time: 0.0022 memory: 5456 grad_norm: 1097.7105 loss: 455.0622 loss_cls: 174.4985 loss_bbox: 133.5455 loss_dfl: 147.0181 2024/03/27 12:01:39 - mmengine - INFO - Epoch(train) [9][300/925] lr: 1.8268e-04 eta: 7:44:04 time: 0.4132 data_time: 0.0021 memory: 5203 grad_norm: 992.5991 loss: 455.7987 loss_cls: 174.8426 loss_bbox: 133.2439 loss_dfl: 147.7122 2024/03/27 12:01:59 - mmengine - INFO - Epoch(train) [9][350/925] lr: 1.8268e-04 eta: 7:43:38 time: 0.4081 data_time: 0.0019 memory: 5470 grad_norm: 1068.4698 loss: 461.2959 loss_cls: 177.4349 loss_bbox: 136.1361 loss_dfl: 147.7250 2024/03/27 12:02:19 - mmengine - INFO - Epoch(train) [9][400/925] lr: 1.8268e-04 eta: 7:43:08 time: 0.3979 data_time: 0.0018 memory: 5670 grad_norm: 1143.5786 loss: 466.6316 loss_cls: 179.0892 loss_bbox: 138.1309 loss_dfl: 149.4116 2024/03/27 12:02:40 - mmengine - INFO - Epoch(train) [9][450/925] lr: 1.8268e-04 eta: 7:42:41 time: 0.4073 data_time: 0.0020 memory: 5843 grad_norm: 1152.9719 loss: 461.1545 loss_cls: 176.5474 loss_bbox: 136.2495 loss_dfl: 148.3575 2024/03/27 12:03:00 - mmengine - INFO - Epoch(train) [9][500/925] lr: 1.8268e-04 eta: 7:42:16 time: 0.4101 data_time: 0.0019 memory: 5376 grad_norm: 1089.2193 loss: 462.6837 loss_cls: 177.7664 loss_bbox: 136.3581 loss_dfl: 148.5592 2024/03/27 12:03:20 - mmengine - INFO - Epoch(train) [9][550/925] lr: 1.8268e-04 eta: 7:41:44 time: 0.3926 data_time: 0.0019 memory: 5256 grad_norm: 1003.9370 loss: 459.0184 loss_cls: 177.2304 loss_bbox: 134.3585 loss_dfl: 147.4296 2024/03/27 12:03:41 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:03:41 - mmengine - INFO - Epoch(train) [9][600/925] lr: 1.8268e-04 eta: 7:41:24 time: 0.4224 data_time: 0.0022 memory: 5403 grad_norm: 1184.9904 loss: 462.7441 loss_cls: 180.4412 loss_bbox: 133.8670 loss_dfl: 148.4359 2024/03/27 12:04:01 - mmengine - INFO - Epoch(train) [9][650/925] lr: 1.8268e-04 eta: 7:40:55 time: 0.3985 data_time: 0.0019 memory: 5630 grad_norm: 1060.7781 loss: 458.9612 loss_cls: 175.9572 loss_bbox: 135.5702 loss_dfl: 147.4338 2024/03/27 12:04:21 - mmengine - INFO - Epoch(train) [9][700/925] lr: 1.8268e-04 eta: 7:40:22 time: 0.3896 data_time: 0.0019 memory: 5283 grad_norm: 1055.1502 loss: 458.3206 loss_cls: 175.2081 loss_bbox: 134.9463 loss_dfl: 148.1662 2024/03/27 12:04:41 - mmengine - INFO - Epoch(train) [9][750/925] lr: 1.8268e-04 eta: 7:39:58 time: 0.4120 data_time: 0.0021 memory: 5216 grad_norm: 1093.8606 loss: 460.2961 loss_cls: 177.0877 loss_bbox: 134.9191 loss_dfl: 148.2893 2024/03/27 12:05:01 - mmengine - INFO - Epoch(train) [9][800/925] lr: 1.8268e-04 eta: 7:39:27 time: 0.3931 data_time: 0.0019 memory: 5430 grad_norm: 1127.0333 loss: 451.9948 loss_cls: 172.3087 loss_bbox: 133.0742 loss_dfl: 146.6119 2024/03/27 12:05:20 - mmengine - INFO - Epoch(train) [9][850/925] lr: 1.8268e-04 eta: 7:38:49 time: 0.3771 data_time: 0.0022 memory: 5230 grad_norm: 1089.2920 loss: 463.0653 loss_cls: 180.2150 loss_bbox: 134.2639 loss_dfl: 148.5864 2024/03/27 12:05:42 - mmengine - INFO - Epoch(train) [9][900/925] lr: 1.8268e-04 eta: 7:38:36 time: 0.4380 data_time: 0.0020 memory: 5203 grad_norm: 1204.6233 loss: 456.3970 loss_cls: 174.6060 loss_bbox: 135.0268 loss_dfl: 146.7641 2024/03/27 12:05:50 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:06:15 - mmengine - INFO - Epoch(train) [10][ 50/925] lr: 1.8020e-04 eta: 7:38:16 time: 0.4880 data_time: 0.0681 memory: 5616 grad_norm: 1102.5953 loss: 460.5919 loss_cls: 175.5227 loss_bbox: 136.9877 loss_dfl: 148.0816 2024/03/27 12:06:35 - mmengine - INFO - Epoch(train) [10][100/925] lr: 1.8020e-04 eta: 7:37:48 time: 0.4015 data_time: 0.0020 memory: 5764 grad_norm: 986.7948 loss: 448.3363 loss_cls: 170.6414 loss_bbox: 132.5286 loss_dfl: 145.1662 2024/03/27 12:06:55 - mmengine - INFO - Epoch(train) [10][150/925] lr: 1.8020e-04 eta: 7:37:23 time: 0.4060 data_time: 0.0020 memory: 5643 grad_norm: 1003.2083 loss: 454.4351 loss_cls: 172.6261 loss_bbox: 134.1639 loss_dfl: 147.6450 2024/03/27 12:07:16 - mmengine - INFO - Epoch(train) [10][200/925] lr: 1.8020e-04 eta: 7:36:55 time: 0.4028 data_time: 0.0019 memory: 5830 grad_norm: 1076.4268 loss: 464.7155 loss_cls: 179.1404 loss_bbox: 137.0287 loss_dfl: 148.5464 2024/03/27 12:07:36 - mmengine - INFO - Epoch(train) [10][250/925] lr: 1.8020e-04 eta: 7:36:34 time: 0.4162 data_time: 0.0019 memory: 5123 grad_norm: 1034.0964 loss: 457.9415 loss_cls: 175.4598 loss_bbox: 135.0787 loss_dfl: 147.4030 2024/03/27 12:07:56 - mmengine - INFO - Epoch(train) [10][300/925] lr: 1.8020e-04 eta: 7:36:04 time: 0.3953 data_time: 0.0019 memory: 5270 grad_norm: inf loss: 454.8923 loss_cls: 174.5263 loss_bbox: 134.0264 loss_dfl: 146.3397 2024/03/27 12:08:16 - mmengine - INFO - Epoch(train) [10][350/925] lr: 1.8020e-04 eta: 7:35:34 time: 0.3951 data_time: 0.0019 memory: 5363 grad_norm: 1164.0906 loss: 457.3606 loss_cls: 175.4684 loss_bbox: 134.6336 loss_dfl: 147.2586 2024/03/27 12:08:37 - mmengine - INFO - Epoch(train) [10][400/925] lr: 1.8020e-04 eta: 7:35:16 time: 0.4264 data_time: 0.0019 memory: 5336 grad_norm: 1173.5617 loss: 457.1277 loss_cls: 174.2868 loss_bbox: 134.8084 loss_dfl: 148.0325 2024/03/27 12:08:58 - mmengine - INFO - Epoch(train) [10][450/925] lr: 1.8020e-04 eta: 7:34:50 time: 0.4050 data_time: 0.0019 memory: 5376 grad_norm: 1145.8700 loss: 450.9318 loss_cls: 170.7134 loss_bbox: 133.8845 loss_dfl: 146.3338 2024/03/27 12:09:18 - mmengine - INFO - Epoch(train) [10][500/925] lr: 1.8020e-04 eta: 7:34:24 time: 0.4052 data_time: 0.0018 memory: 5376 grad_norm: 1078.4791 loss: 453.3096 loss_cls: 172.2202 loss_bbox: 134.6553 loss_dfl: 146.4341 2024/03/27 12:09:39 - mmengine - INFO - Epoch(train) [10][550/925] lr: 1.8020e-04 eta: 7:34:05 time: 0.4232 data_time: 0.0022 memory: 5216 grad_norm: 1049.8650 loss: 461.8203 loss_cls: 178.1992 loss_bbox: 135.5366 loss_dfl: 148.0845 2024/03/27 12:09:59 - mmengine - INFO - Epoch(train) [10][600/925] lr: 1.8020e-04 eta: 7:33:35 time: 0.3940 data_time: 0.0020 memory: 5243 grad_norm: 1166.3349 loss: 468.7903 loss_cls: 179.8819 loss_bbox: 139.5623 loss_dfl: 149.3461 2024/03/27 12:10:19 - mmengine - INFO - Epoch(train) [10][650/925] lr: 1.8020e-04 eta: 7:33:10 time: 0.4062 data_time: 0.0019 memory: 5270 grad_norm: 1196.5171 loss: 450.4402 loss_cls: 170.9114 loss_bbox: 133.3070 loss_dfl: 146.2218 2024/03/27 12:10:29 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:10:40 - mmengine - INFO - Epoch(train) [10][700/925] lr: 1.8020e-04 eta: 7:32:47 time: 0.4135 data_time: 0.0021 memory: 5443 grad_norm: 1068.6973 loss: 457.6473 loss_cls: 173.9718 loss_bbox: 135.8670 loss_dfl: 147.8085 2024/03/27 12:11:00 - mmengine - INFO - Epoch(train) [10][750/925] lr: 1.8020e-04 eta: 7:32:22 time: 0.4057 data_time: 0.0019 memory: 5416 grad_norm: 965.7738 loss: 460.2345 loss_cls: 176.1925 loss_bbox: 135.7386 loss_dfl: 148.3035 2024/03/27 12:11:20 - mmengine - INFO - Epoch(train) [10][800/925] lr: 1.8020e-04 eta: 7:31:51 time: 0.3905 data_time: 0.0019 memory: 5416 grad_norm: 1034.3465 loss: 453.9050 loss_cls: 175.4873 loss_bbox: 132.1171 loss_dfl: 146.3006 2024/03/27 12:11:40 - mmengine - INFO - Epoch(train) [10][850/925] lr: 1.8020e-04 eta: 7:31:29 time: 0.4128 data_time: 0.0019 memory: 5470 grad_norm: 1019.4583 loss: 450.8870 loss_cls: 170.8100 loss_bbox: 133.1998 loss_dfl: 146.8772 2024/03/27 12:12:01 - mmengine - INFO - Epoch(train) [10][900/925] lr: 1.8020e-04 eta: 7:31:05 time: 0.4087 data_time: 0.0019 memory: 5776 grad_norm: 948.5623 loss: 456.4970 loss_cls: 174.3997 loss_bbox: 135.6332 loss_dfl: 146.4641 2024/03/27 12:12:10 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:12:10 - mmengine - INFO - Saving checkpoint at 10 epochs 2024/03/27 12:12:21 - mmengine - INFO - Epoch(val) [10][ 50/625] eta: 0:01:01 time: 0.1068 data_time: 0.0634 memory: 5376 2024/03/27 12:12:24 - mmengine - INFO - Epoch(val) [10][100/625] eta: 0:00:39 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 12:12:26 - mmengine - INFO - Epoch(val) [10][150/625] eta: 0:00:30 time: 0.0435 data_time: 0.0004 memory: 838 2024/03/27 12:12:28 - mmengine - INFO - Epoch(val) [10][200/625] eta: 0:00:25 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 12:12:30 - mmengine - INFO - Epoch(val) [10][250/625] eta: 0:00:21 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 12:12:32 - mmengine - INFO - Epoch(val) [10][300/625] eta: 0:00:17 time: 0.0443 data_time: 0.0004 memory: 838 2024/03/27 12:12:35 - mmengine - INFO - Epoch(val) [10][350/625] eta: 0:00:14 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 12:12:37 - mmengine - INFO - Epoch(val) [10][400/625] eta: 0:00:11 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 12:12:39 - mmengine - INFO - Epoch(val) [10][450/625] eta: 0:00:08 time: 0.0443 data_time: 0.0004 memory: 838 2024/03/27 12:12:41 - mmengine - INFO - Epoch(val) [10][500/625] eta: 0:00:06 time: 0.0420 data_time: 0.0006 memory: 838 2024/03/27 12:12:43 - mmengine - INFO - Epoch(val) [10][550/625] eta: 0:00:03 time: 0.0343 data_time: 0.0004 memory: 838 2024/03/27 12:12:45 - mmengine - INFO - Epoch(val) [10][600/625] eta: 0:00:01 time: 0.0340 data_time: 0.0003 memory: 838 2024/03/27 12:13:02 - mmengine - INFO - Evaluating bbox... 2024/03/27 12:14:45 - mmengine - INFO - bbox_mAP_copypaste: 0.418 0.576 0.457 0.230 0.462 0.559 2024/03/27 12:14:47 - mmengine - INFO - Epoch(val) [10][625/625] coco/bbox_mAP: 0.4180 coco/bbox_mAP_50: 0.5760 coco/bbox_mAP_75: 0.4570 coco/bbox_mAP_s: 0.2300 coco/bbox_mAP_m: 0.4620 coco/bbox_mAP_l: 0.5590 data_time: 0.0003 time: 0.0335 2024/03/27 12:15:11 - mmengine - INFO - Epoch(train) [11][ 50/925] lr: 1.7772e-04 eta: 7:30:47 time: 0.4799 data_time: 0.0744 memory: 5576 grad_norm: 1038.3293 loss: 456.2178 loss_cls: 173.9712 loss_bbox: 135.0796 loss_dfl: 147.1670 2024/03/27 12:15:30 - mmengine - INFO - Epoch(train) [11][100/925] lr: 1.7772e-04 eta: 7:30:15 time: 0.3861 data_time: 0.0021 memory: 5616 grad_norm: 1097.3858 loss: 453.5436 loss_cls: 172.7812 loss_bbox: 133.5847 loss_dfl: 147.1778 2024/03/27 12:15:50 - mmengine - INFO - Epoch(train) [11][150/925] lr: 1.7772e-04 eta: 7:29:44 time: 0.3908 data_time: 0.0023 memory: 5310 grad_norm: 1133.3325 loss: 459.6806 loss_cls: 177.6774 loss_bbox: 133.7710 loss_dfl: 148.2322 2024/03/27 12:16:09 - mmengine - INFO - Epoch(train) [11][200/925] lr: 1.7772e-04 eta: 7:29:14 time: 0.3898 data_time: 0.0024 memory: 5603 grad_norm: 1124.8697 loss: 459.8163 loss_cls: 175.1849 loss_bbox: 136.6478 loss_dfl: 147.9837 2024/03/27 12:16:29 - mmengine - INFO - Epoch(train) [11][250/925] lr: 1.7772e-04 eta: 7:28:43 time: 0.3873 data_time: 0.0027 memory: 5243 grad_norm: 981.9266 loss: 444.1215 loss_cls: 169.1815 loss_bbox: 129.8850 loss_dfl: 145.0550 2024/03/27 12:16:49 - mmengine - INFO - Epoch(train) [11][300/925] lr: 1.7772e-04 eta: 7:28:18 time: 0.4045 data_time: 0.0020 memory: 5123 grad_norm: 929.1465 loss: 460.1872 loss_cls: 178.0816 loss_bbox: 135.1491 loss_dfl: 146.9564 2024/03/27 12:17:08 - mmengine - INFO - Epoch(train) [11][350/925] lr: 1.7772e-04 eta: 7:27:42 time: 0.3736 data_time: 0.0022 memory: 5496 grad_norm: 1069.0019 loss: 451.7667 loss_cls: 172.2970 loss_bbox: 133.5064 loss_dfl: 145.9632 2024/03/27 12:17:28 - mmengine - INFO - Epoch(train) [11][400/925] lr: 1.7772e-04 eta: 7:27:17 time: 0.4042 data_time: 0.0020 memory: 5283 grad_norm: 964.0771 loss: 450.9741 loss_cls: 171.9103 loss_bbox: 132.1711 loss_dfl: 146.8927 2024/03/27 12:17:48 - mmengine - INFO - Epoch(train) [11][450/925] lr: 1.7772e-04 eta: 7:26:51 time: 0.4025 data_time: 0.0021 memory: 5563 grad_norm: 1082.6291 loss: 456.8421 loss_cls: 174.5872 loss_bbox: 135.3574 loss_dfl: 146.8975 2024/03/27 12:18:07 - mmengine - INFO - Epoch(train) [11][500/925] lr: 1.7772e-04 eta: 7:26:19 time: 0.3833 data_time: 0.0019 memory: 5563 grad_norm: 1044.9583 loss: 449.6207 loss_cls: 170.0858 loss_bbox: 133.8004 loss_dfl: 145.7346 2024/03/27 12:18:27 - mmengine - INFO - Epoch(train) [11][550/925] lr: 1.7772e-04 eta: 7:25:53 time: 0.4002 data_time: 0.0021 memory: 5243 grad_norm: 1076.6562 loss: 454.0417 loss_cls: 173.4525 loss_bbox: 134.2178 loss_dfl: 146.3715 2024/03/27 12:18:47 - mmengine - INFO - Epoch(train) [11][600/925] lr: 1.7772e-04 eta: 7:25:26 time: 0.3967 data_time: 0.0022 memory: 5190 grad_norm: 1074.7620 loss: 448.1710 loss_cls: 170.2915 loss_bbox: 132.3859 loss_dfl: 145.4936 2024/03/27 12:19:07 - mmengine - INFO - Epoch(train) [11][650/925] lr: 1.7772e-04 eta: 7:24:59 time: 0.3984 data_time: 0.0027 memory: 5350 grad_norm: 1072.4717 loss: 452.7477 loss_cls: 173.6800 loss_bbox: 132.7420 loss_dfl: 146.3257 2024/03/27 12:19:26 - mmengine - INFO - Epoch(train) [11][700/925] lr: 1.7772e-04 eta: 7:24:30 time: 0.3909 data_time: 0.0021 memory: 5403 grad_norm: 974.6177 loss: 457.6973 loss_cls: 175.0888 loss_bbox: 135.4814 loss_dfl: 147.1271 2024/03/27 12:19:47 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:19:47 - mmengine - INFO - Epoch(train) [11][750/925] lr: 1.7772e-04 eta: 7:24:04 time: 0.4000 data_time: 0.0020 memory: 5496 grad_norm: 1071.0458 loss: 451.7370 loss_cls: 171.4804 loss_bbox: 133.2008 loss_dfl: 147.0559 2024/03/27 12:20:06 - mmengine - INFO - Epoch(train) [11][800/925] lr: 1.7772e-04 eta: 7:23:37 time: 0.3966 data_time: 0.0019 memory: 5470 grad_norm: 1215.3563 loss: 449.0514 loss_cls: 171.1326 loss_bbox: 132.7673 loss_dfl: 145.1515 2024/03/27 12:20:26 - mmengine - INFO - Epoch(train) [11][850/925] lr: 1.7772e-04 eta: 7:23:08 time: 0.3903 data_time: 0.0019 memory: 5296 grad_norm: 1018.5674 loss: 459.0944 loss_cls: 175.5562 loss_bbox: 135.7043 loss_dfl: 147.8339 2024/03/27 12:20:45 - mmengine - INFO - Epoch(train) [11][900/925] lr: 1.7772e-04 eta: 7:22:37 time: 0.3859 data_time: 0.0019 memory: 5150 grad_norm: 1058.0242 loss: 460.7768 loss_cls: 177.0709 loss_bbox: 135.4905 loss_dfl: 148.2154 2024/03/27 12:20:54 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:21:19 - mmengine - INFO - Epoch(train) [12][ 50/925] lr: 1.7525e-04 eta: 7:22:19 time: 0.4823 data_time: 0.0650 memory: 5910 grad_norm: 1178.2115 loss: 450.1162 loss_cls: 170.6089 loss_bbox: 132.9264 loss_dfl: 146.5809 2024/03/27 12:21:39 - mmengine - INFO - Epoch(train) [12][100/925] lr: 1.7525e-04 eta: 7:21:53 time: 0.3989 data_time: 0.0019 memory: 5496 grad_norm: 979.7014 loss: 449.2374 loss_cls: 170.2510 loss_bbox: 133.5319 loss_dfl: 145.4546 2024/03/27 12:21:59 - mmengine - INFO - Epoch(train) [12][150/925] lr: 1.7525e-04 eta: 7:21:25 time: 0.3945 data_time: 0.0020 memory: 5310 grad_norm: 1086.4364 loss: 448.7541 loss_cls: 170.1029 loss_bbox: 131.8302 loss_dfl: 146.8210 2024/03/27 12:22:18 - mmengine - INFO - Epoch(train) [12][200/925] lr: 1.7525e-04 eta: 7:20:56 time: 0.3898 data_time: 0.0020 memory: 5136 grad_norm: 1067.3237 loss: 455.6040 loss_cls: 173.8618 loss_bbox: 134.2781 loss_dfl: 147.4641 2024/03/27 12:22:39 - mmengine - INFO - Epoch(train) [12][250/925] lr: 1.7525e-04 eta: 7:20:37 time: 0.4194 data_time: 0.0027 memory: 5230 grad_norm: 1026.5152 loss: 458.4411 loss_cls: 175.6869 loss_bbox: 135.1963 loss_dfl: 147.5579 2024/03/27 12:23:00 - mmengine - INFO - Epoch(train) [12][300/925] lr: 1.7525e-04 eta: 7:20:14 time: 0.4103 data_time: 0.0021 memory: 5363 grad_norm: 1151.1674 loss: 453.7410 loss_cls: 171.8671 loss_bbox: 134.4316 loss_dfl: 147.4423 2024/03/27 12:23:19 - mmengine - INFO - Epoch(train) [12][350/925] lr: 1.7525e-04 eta: 7:19:45 time: 0.3883 data_time: 0.0017 memory: 5336 grad_norm: 956.5248 loss: 461.0382 loss_cls: 175.9134 loss_bbox: 136.5319 loss_dfl: 148.5929 2024/03/27 12:23:40 - mmengine - INFO - Epoch(train) [12][400/925] lr: 1.7525e-04 eta: 7:19:25 time: 0.4178 data_time: 0.0019 memory: 5323 grad_norm: 958.1103 loss: 456.3867 loss_cls: 174.5299 loss_bbox: 134.4220 loss_dfl: 147.4348 2024/03/27 12:24:00 - mmengine - INFO - Epoch(train) [12][450/925] lr: 1.7525e-04 eta: 7:18:58 time: 0.3942 data_time: 0.0018 memory: 5336 grad_norm: 1100.0877 loss: 458.1410 loss_cls: 175.4100 loss_bbox: 135.6686 loss_dfl: 147.0624 2024/03/27 12:24:19 - mmengine - INFO - Epoch(train) [12][500/925] lr: 1.7525e-04 eta: 7:18:29 time: 0.3894 data_time: 0.0018 memory: 5310 grad_norm: inf loss: 452.3640 loss_cls: 171.0109 loss_bbox: 133.9004 loss_dfl: 147.4528 2024/03/27 12:24:40 - mmengine - INFO - Epoch(train) [12][550/925] lr: 1.7525e-04 eta: 7:18:08 time: 0.4141 data_time: 0.0019 memory: 5390 grad_norm: 1070.3160 loss: 455.5057 loss_cls: 173.9998 loss_bbox: 134.1898 loss_dfl: 147.3161 2024/03/27 12:25:00 - mmengine - INFO - Epoch(train) [12][600/925] lr: 1.7525e-04 eta: 7:17:41 time: 0.3951 data_time: 0.0019 memory: 5643 grad_norm: 1057.2899 loss: 456.9689 loss_cls: 174.5214 loss_bbox: 134.5215 loss_dfl: 147.9260 2024/03/27 12:25:19 - mmengine - INFO - Epoch(train) [12][650/925] lr: 1.7525e-04 eta: 7:17:12 time: 0.3860 data_time: 0.0020 memory: 5590 grad_norm: 1257.8977 loss: 454.3310 loss_cls: 172.9443 loss_bbox: 134.2412 loss_dfl: 147.1455 2024/03/27 12:25:40 - mmengine - INFO - Epoch(train) [12][700/925] lr: 1.7525e-04 eta: 7:16:52 time: 0.4173 data_time: 0.0019 memory: 5030 grad_norm: 899.1524 loss: 453.8461 loss_cls: 174.8281 loss_bbox: 132.3818 loss_dfl: 146.6361 2024/03/27 12:26:00 - mmengine - INFO - Epoch(train) [12][750/925] lr: 1.7525e-04 eta: 7:16:27 time: 0.4020 data_time: 0.0018 memory: 5216 grad_norm: 1045.4655 loss: 459.5506 loss_cls: 176.5121 loss_bbox: 135.5971 loss_dfl: 147.4413 2024/03/27 12:26:20 - mmengine - INFO - Epoch(train) [12][800/925] lr: 1.7525e-04 eta: 7:16:03 time: 0.4037 data_time: 0.0017 memory: 5243 grad_norm: 1046.9027 loss: 450.1194 loss_cls: 171.8547 loss_bbox: 132.6614 loss_dfl: 145.6034 2024/03/27 12:26:30 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:26:40 - mmengine - INFO - Epoch(train) [12][850/925] lr: 1.7525e-04 eta: 7:15:36 time: 0.3915 data_time: 0.0018 memory: 5323 grad_norm: 1040.2056 loss: 451.2320 loss_cls: 171.6878 loss_bbox: 133.7486 loss_dfl: 145.7956 2024/03/27 12:26:59 - mmengine - INFO - Epoch(train) [12][900/925] lr: 1.7525e-04 eta: 7:15:09 time: 0.3924 data_time: 0.0020 memory: 5630 grad_norm: 1067.0945 loss: 456.9403 loss_cls: 174.0876 loss_bbox: 134.4805 loss_dfl: 148.3723 2024/03/27 12:27:09 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:27:33 - mmengine - INFO - Epoch(train) [13][ 50/925] lr: 1.7278e-04 eta: 7:14:47 time: 0.4650 data_time: 0.0604 memory: 5830 grad_norm: 939.4040 loss: 453.6235 loss_cls: 172.2022 loss_bbox: 134.6044 loss_dfl: 146.8168 2024/03/27 12:27:53 - mmengine - INFO - Epoch(train) [13][100/925] lr: 1.7278e-04 eta: 7:14:25 time: 0.4093 data_time: 0.0020 memory: 5230 grad_norm: 954.5499 loss: 450.9562 loss_cls: 173.0839 loss_bbox: 131.6207 loss_dfl: 146.2516 2024/03/27 12:28:12 - mmengine - INFO - Epoch(train) [13][150/925] lr: 1.7278e-04 eta: 7:13:54 time: 0.3807 data_time: 0.0020 memory: 5256 grad_norm: 1011.3105 loss: 449.2146 loss_cls: 171.4777 loss_bbox: 131.5278 loss_dfl: 146.2092 2024/03/27 12:28:33 - mmengine - INFO - Epoch(train) [13][200/925] lr: 1.7278e-04 eta: 7:13:32 time: 0.4103 data_time: 0.0019 memory: 5443 grad_norm: 918.3349 loss: 459.5365 loss_cls: 176.4157 loss_bbox: 136.0470 loss_dfl: 147.0738 2024/03/27 12:28:52 - mmengine - INFO - Epoch(train) [13][250/925] lr: 1.7278e-04 eta: 7:13:02 time: 0.3788 data_time: 0.0019 memory: 5496 grad_norm: 1218.1973 loss: 455.2567 loss_cls: 172.1207 loss_bbox: 135.5702 loss_dfl: 147.5658 2024/03/27 12:29:12 - mmengine - INFO - Epoch(train) [13][300/925] lr: 1.7278e-04 eta: 7:12:38 time: 0.4048 data_time: 0.0021 memory: 5390 grad_norm: 1046.1314 loss: 453.9857 loss_cls: 172.6884 loss_bbox: 134.5874 loss_dfl: 146.7099 2024/03/27 12:29:31 - mmengine - INFO - Epoch(train) [13][350/925] lr: 1.7278e-04 eta: 7:12:10 time: 0.3883 data_time: 0.0019 memory: 5430 grad_norm: 982.1081 loss: 449.8645 loss_cls: 170.3011 loss_bbox: 133.4718 loss_dfl: 146.0915 2024/03/27 12:29:51 - mmengine - INFO - Epoch(train) [13][400/925] lr: 1.7278e-04 eta: 7:11:46 time: 0.4008 data_time: 0.0019 memory: 5230 grad_norm: 965.3722 loss: 441.7000 loss_cls: 166.9276 loss_bbox: 130.1368 loss_dfl: 144.6356 2024/03/27 12:30:12 - mmengine - INFO - Epoch(train) [13][450/925] lr: 1.7278e-04 eta: 7:11:26 time: 0.4169 data_time: 0.0020 memory: 5523 grad_norm: 1005.9942 loss: 458.0666 loss_cls: 175.2033 loss_bbox: 135.4617 loss_dfl: 147.4015 2024/03/27 12:30:33 - mmengine - INFO - Epoch(train) [13][500/925] lr: 1.7278e-04 eta: 7:11:03 time: 0.4055 data_time: 0.0020 memory: 5390 grad_norm: 948.8196 loss: 459.8484 loss_cls: 175.0482 loss_bbox: 137.2595 loss_dfl: 147.5408 2024/03/27 12:30:52 - mmengine - INFO - Epoch(train) [13][550/925] lr: 1.7278e-04 eta: 7:10:36 time: 0.3912 data_time: 0.0021 memory: 5256 grad_norm: 1084.0091 loss: 459.4642 loss_cls: 176.3363 loss_bbox: 135.8269 loss_dfl: 147.3010 2024/03/27 12:31:13 - mmengine - INFO - Epoch(train) [13][600/925] lr: 1.7278e-04 eta: 7:10:13 time: 0.4065 data_time: 0.0019 memory: 5523 grad_norm: 1055.1448 loss: 452.3864 loss_cls: 171.4315 loss_bbox: 133.7777 loss_dfl: 147.1772 2024/03/27 12:31:33 - mmengine - INFO - Epoch(train) [13][650/925] lr: 1.7278e-04 eta: 7:09:49 time: 0.4019 data_time: 0.0020 memory: 5736 grad_norm: 988.1011 loss: 453.9594 loss_cls: 174.5507 loss_bbox: 133.0499 loss_dfl: 146.3588 2024/03/27 12:31:53 - mmengine - INFO - Epoch(train) [13][700/925] lr: 1.7278e-04 eta: 7:09:24 time: 0.3996 data_time: 0.0020 memory: 5470 grad_norm: 948.9578 loss: 448.4279 loss_cls: 168.7163 loss_bbox: 133.9594 loss_dfl: 145.7522 2024/03/27 12:32:13 - mmengine - INFO - Epoch(train) [13][750/925] lr: 1.7278e-04 eta: 7:09:00 time: 0.4022 data_time: 0.0020 memory: 5163 grad_norm: 1040.9153 loss: 456.7895 loss_cls: 173.7668 loss_bbox: 134.9566 loss_dfl: 148.0662 2024/03/27 12:32:34 - mmengine - INFO - Epoch(train) [13][800/925] lr: 1.7278e-04 eta: 7:08:41 time: 0.4188 data_time: 0.0020 memory: 5363 grad_norm: 1141.6805 loss: 451.0899 loss_cls: 171.3543 loss_bbox: 133.0850 loss_dfl: 146.6506 2024/03/27 12:32:53 - mmengine - INFO - Epoch(train) [13][850/925] lr: 1.7278e-04 eta: 7:08:14 time: 0.3921 data_time: 0.0018 memory: 5496 grad_norm: 967.2251 loss: 458.1781 loss_cls: 175.8954 loss_bbox: 134.9057 loss_dfl: 147.3770 2024/03/27 12:33:14 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:33:14 - mmengine - INFO - Epoch(train) [13][900/925] lr: 1.7278e-04 eta: 7:07:51 time: 0.4026 data_time: 0.0019 memory: 5443 grad_norm: 955.4810 loss: 459.4497 loss_cls: 175.1092 loss_bbox: 135.2402 loss_dfl: 149.1003 2024/03/27 12:33:23 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:33:48 - mmengine - INFO - Epoch(train) [14][ 50/925] lr: 1.7030e-04 eta: 7:07:34 time: 0.4797 data_time: 0.0623 memory: 5456 grad_norm: 1038.5975 loss: 456.8522 loss_cls: 173.2875 loss_bbox: 136.2341 loss_dfl: 147.3306 2024/03/27 12:34:07 - mmengine - INFO - Epoch(train) [14][100/925] lr: 1.7030e-04 eta: 7:07:07 time: 0.3918 data_time: 0.0020 memory: 5363 grad_norm: 948.8619 loss: 439.6286 loss_cls: 166.9571 loss_bbox: 128.6096 loss_dfl: 144.0620 2024/03/27 12:34:27 - mmengine - INFO - Epoch(train) [14][150/925] lr: 1.7030e-04 eta: 7:06:43 time: 0.4014 data_time: 0.0020 memory: 5323 grad_norm: 967.1120 loss: 454.8398 loss_cls: 172.7574 loss_bbox: 135.0653 loss_dfl: 147.0171 2024/03/27 12:34:48 - mmengine - INFO - Epoch(train) [14][200/925] lr: 1.7030e-04 eta: 7:06:23 time: 0.4134 data_time: 0.0020 memory: 5563 grad_norm: 1029.4121 loss: 449.0984 loss_cls: 169.8324 loss_bbox: 132.4830 loss_dfl: 146.7830 2024/03/27 12:35:08 - mmengine - INFO - Epoch(train) [14][250/925] lr: 1.7030e-04 eta: 7:05:56 time: 0.3916 data_time: 0.0020 memory: 6056 grad_norm: 1027.7575 loss: 451.4816 loss_cls: 170.1682 loss_bbox: 135.4738 loss_dfl: 145.8396 2024/03/27 12:35:27 - mmengine - INFO - Epoch(train) [14][300/925] lr: 1.7030e-04 eta: 7:05:29 time: 0.3867 data_time: 0.0020 memory: 5683 grad_norm: 1139.6717 loss: 449.5044 loss_cls: 169.9385 loss_bbox: 132.8908 loss_dfl: 146.6751 2024/03/27 12:35:48 - mmengine - INFO - Epoch(train) [14][350/925] lr: 1.7030e-04 eta: 7:05:07 time: 0.4084 data_time: 0.0019 memory: 5296 grad_norm: 924.9980 loss: 447.5288 loss_cls: 170.2004 loss_bbox: 131.5707 loss_dfl: 145.7577 2024/03/27 12:36:07 - mmengine - INFO - Epoch(train) [14][400/925] lr: 1.7030e-04 eta: 7:04:41 time: 0.3933 data_time: 0.0023 memory: 5336 grad_norm: 1053.2223 loss: 451.5067 loss_cls: 171.6321 loss_bbox: 133.4385 loss_dfl: 146.4361 2024/03/27 12:36:27 - mmengine - INFO - Epoch(train) [14][450/925] lr: 1.7030e-04 eta: 7:04:16 time: 0.3972 data_time: 0.0021 memory: 5470 grad_norm: 1046.6319 loss: 453.1793 loss_cls: 172.9448 loss_bbox: 134.1709 loss_dfl: 146.0636 2024/03/27 12:36:47 - mmengine - INFO - Epoch(train) [14][500/925] lr: 1.7030e-04 eta: 7:03:52 time: 0.4017 data_time: 0.0020 memory: 5563 grad_norm: 921.0540 loss: 456.4436 loss_cls: 173.0550 loss_bbox: 135.1874 loss_dfl: 148.2013 2024/03/27 12:37:08 - mmengine - INFO - Epoch(train) [14][550/925] lr: 1.7030e-04 eta: 7:03:30 time: 0.4055 data_time: 0.0020 memory: 5536 grad_norm: 855.7692 loss: 450.1317 loss_cls: 171.5407 loss_bbox: 132.6472 loss_dfl: 145.9438 2024/03/27 12:37:26 - mmengine - INFO - Epoch(train) [14][600/925] lr: 1.7030e-04 eta: 7:03:00 time: 0.3752 data_time: 0.0022 memory: 5536 grad_norm: 1091.7253 loss: 446.4024 loss_cls: 168.1598 loss_bbox: 133.2270 loss_dfl: 145.0157 2024/03/27 12:37:45 - mmengine - INFO - Epoch(train) [14][650/925] lr: 1.7030e-04 eta: 7:02:32 time: 0.3831 data_time: 0.0023 memory: 6549 grad_norm: 1018.1089 loss: 447.7356 loss_cls: 169.1274 loss_bbox: 131.8436 loss_dfl: 146.7646 2024/03/27 12:38:05 - mmengine - INFO - Epoch(train) [14][700/925] lr: 1.7030e-04 eta: 7:02:07 time: 0.3982 data_time: 0.0020 memory: 5336 grad_norm: 871.4477 loss: 457.6357 loss_cls: 175.1116 loss_bbox: 134.6052 loss_dfl: 147.9189 2024/03/27 12:38:24 - mmengine - INFO - Epoch(train) [14][750/925] lr: 1.7030e-04 eta: 7:01:38 time: 0.3759 data_time: 0.0021 memory: 5536 grad_norm: 1032.3974 loss: 446.4759 loss_cls: 168.2448 loss_bbox: 132.6221 loss_dfl: 145.6090 2024/03/27 12:38:43 - mmengine - INFO - Epoch(train) [14][800/925] lr: 1.7030e-04 eta: 7:01:09 time: 0.3794 data_time: 0.0019 memory: 5243 grad_norm: inf loss: 443.7014 loss_cls: 166.8424 loss_bbox: 132.4913 loss_dfl: 144.3677 2024/03/27 12:39:03 - mmengine - INFO - Epoch(train) [14][850/925] lr: 1.7030e-04 eta: 7:00:44 time: 0.3947 data_time: 0.0019 memory: 5643 grad_norm: 1101.8548 loss: 452.2812 loss_cls: 171.3130 loss_bbox: 134.0113 loss_dfl: 146.9569 2024/03/27 12:39:23 - mmengine - INFO - Epoch(train) [14][900/925] lr: 1.7030e-04 eta: 7:00:20 time: 0.4000 data_time: 0.0021 memory: 5376 grad_norm: 945.4943 loss: 454.2581 loss_cls: 171.5776 loss_bbox: 134.9049 loss_dfl: 147.7756 2024/03/27 12:39:31 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:39:55 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:39:55 - mmengine - INFO - Epoch(train) [15][ 50/925] lr: 1.6783e-04 eta: 6:59:50 time: 0.4579 data_time: 0.0717 memory: 5403 grad_norm: 936.5748 loss: 446.6876 loss_cls: 168.9589 loss_bbox: 132.1464 loss_dfl: 145.5823 2024/03/27 12:40:15 - mmengine - INFO - Epoch(train) [15][100/925] lr: 1.6783e-04 eta: 6:59:28 time: 0.4067 data_time: 0.0020 memory: 5216 grad_norm: 1135.7903 loss: 448.5793 loss_cls: 170.6672 loss_bbox: 132.0204 loss_dfl: 145.8917 2024/03/27 12:40:35 - mmengine - INFO - Epoch(train) [15][150/925] lr: 1.6783e-04 eta: 6:59:03 time: 0.3956 data_time: 0.0019 memory: 5256 grad_norm: 1106.4035 loss: 445.4403 loss_cls: 167.1191 loss_bbox: 132.7474 loss_dfl: 145.5738 2024/03/27 12:40:53 - mmengine - INFO - Epoch(train) [15][200/925] lr: 1.6783e-04 eta: 6:58:34 time: 0.3752 data_time: 0.0019 memory: 5403 grad_norm: 1086.6898 loss: 452.5678 loss_cls: 170.9936 loss_bbox: 134.7785 loss_dfl: 146.7956 2024/03/27 12:41:13 - mmengine - INFO - Epoch(train) [15][250/925] lr: 1.6783e-04 eta: 6:58:10 time: 0.3991 data_time: 0.0019 memory: 5430 grad_norm: 968.8314 loss: 449.4594 loss_cls: 169.7405 loss_bbox: 133.6633 loss_dfl: 146.0557 2024/03/27 12:41:34 - mmengine - INFO - Epoch(train) [15][300/925] lr: 1.6783e-04 eta: 6:57:48 time: 0.4048 data_time: 0.0020 memory: 5590 grad_norm: 917.8072 loss: 444.4862 loss_cls: 166.5598 loss_bbox: 133.1654 loss_dfl: 144.7610 2024/03/27 12:41:53 - mmengine - INFO - Epoch(train) [15][350/925] lr: 1.6783e-04 eta: 6:57:21 time: 0.3873 data_time: 0.0021 memory: 5390 grad_norm: 1156.6708 loss: 447.9556 loss_cls: 170.3564 loss_bbox: 132.7178 loss_dfl: 144.8814 2024/03/27 12:42:12 - mmengine - INFO - Epoch(train) [15][400/925] lr: 1.6783e-04 eta: 6:56:55 time: 0.3872 data_time: 0.0019 memory: 5230 grad_norm: 1134.8279 loss: 451.3213 loss_cls: 170.7354 loss_bbox: 133.8888 loss_dfl: 146.6972 2024/03/27 12:42:33 - mmengine - INFO - Epoch(train) [15][450/925] lr: 1.6783e-04 eta: 6:56:31 time: 0.4007 data_time: 0.0021 memory: 5723 grad_norm: 1001.1728 loss: 455.0747 loss_cls: 172.9801 loss_bbox: 135.2961 loss_dfl: 146.7985 2024/03/27 12:42:52 - mmengine - INFO - Epoch(train) [15][500/925] lr: 1.6783e-04 eta: 6:56:04 time: 0.3832 data_time: 0.0022 memory: 5430 grad_norm: 1005.4547 loss: 450.6271 loss_cls: 170.7364 loss_bbox: 132.9920 loss_dfl: 146.8988 2024/03/27 12:43:11 - mmengine - INFO - Epoch(train) [15][550/925] lr: 1.6783e-04 eta: 6:55:36 time: 0.3789 data_time: 0.0020 memory: 5243 grad_norm: 992.2630 loss: 445.9925 loss_cls: 167.0950 loss_bbox: 133.3598 loss_dfl: 145.5376 2024/03/27 12:43:31 - mmengine - INFO - Epoch(train) [15][600/925] lr: 1.6783e-04 eta: 6:55:16 time: 0.4137 data_time: 0.0020 memory: 5243 grad_norm: 1036.8750 loss: 455.5751 loss_cls: 174.8131 loss_bbox: 133.5892 loss_dfl: 147.1728 2024/03/27 12:43:51 - mmengine - INFO - Epoch(train) [15][650/925] lr: 1.6783e-04 eta: 6:54:51 time: 0.3930 data_time: 0.0022 memory: 5456 grad_norm: 978.9190 loss: 452.9725 loss_cls: 171.4868 loss_bbox: 134.4014 loss_dfl: 147.0844 2024/03/27 12:44:11 - mmengine - INFO - Epoch(train) [15][700/925] lr: 1.6783e-04 eta: 6:54:26 time: 0.3920 data_time: 0.0021 memory: 5243 grad_norm: 1187.2640 loss: 451.1413 loss_cls: 168.5701 loss_bbox: 135.4696 loss_dfl: 147.1015 2024/03/27 12:44:32 - mmengine - INFO - Epoch(train) [15][750/925] lr: 1.6783e-04 eta: 6:54:07 time: 0.4171 data_time: 0.0019 memory: 5683 grad_norm: 1035.2608 loss: 449.7670 loss_cls: 171.5262 loss_bbox: 132.1587 loss_dfl: 146.0821 2024/03/27 12:44:52 - mmengine - INFO - Epoch(train) [15][800/925] lr: 1.6783e-04 eta: 6:53:47 time: 0.4151 data_time: 0.0020 memory: 5576 grad_norm: 1035.7242 loss: 445.9998 loss_cls: 168.2874 loss_bbox: 131.7400 loss_dfl: 145.9723 2024/03/27 12:45:12 - mmengine - INFO - Epoch(train) [15][850/925] lr: 1.6783e-04 eta: 6:53:22 time: 0.3918 data_time: 0.0020 memory: 5430 grad_norm: 979.0365 loss: 445.6720 loss_cls: 169.7101 loss_bbox: 130.1145 loss_dfl: 145.8473 2024/03/27 12:45:33 - mmengine - INFO - Epoch(train) [15][900/925] lr: 1.6783e-04 eta: 6:53:01 time: 0.4125 data_time: 0.0019 memory: 5403 grad_norm: 983.9404 loss: 443.5100 loss_cls: 166.5903 loss_bbox: 131.4843 loss_dfl: 145.4354 2024/03/27 12:45:42 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:45:43 - mmengine - INFO - Saving checkpoint at 15 epochs 2024/03/27 12:45:51 - mmengine - INFO - Epoch(val) [15][ 50/625] eta: 0:00:26 time: 0.0467 data_time: 0.0046 memory: 5443 2024/03/27 12:45:53 - mmengine - INFO - Epoch(val) [15][100/625] eta: 0:00:23 time: 0.0438 data_time: 0.0008 memory: 838 2024/03/27 12:45:55 - mmengine - INFO - Epoch(val) [15][150/625] eta: 0:00:21 time: 0.0460 data_time: 0.0013 memory: 838 2024/03/27 12:45:58 - mmengine - INFO - Epoch(val) [15][200/625] eta: 0:00:19 time: 0.0457 data_time: 0.0017 memory: 838 2024/03/27 12:46:00 - mmengine - INFO - Epoch(val) [15][250/625] eta: 0:00:17 time: 0.0447 data_time: 0.0014 memory: 838 2024/03/27 12:46:02 - mmengine - INFO - Epoch(val) [15][300/625] eta: 0:00:14 time: 0.0454 data_time: 0.0004 memory: 838 2024/03/27 12:46:04 - mmengine - INFO - Epoch(val) [15][350/625] eta: 0:00:12 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 12:46:06 - mmengine - INFO - Epoch(val) [15][400/625] eta: 0:00:10 time: 0.0444 data_time: 0.0006 memory: 838 2024/03/27 12:46:09 - mmengine - INFO - Epoch(val) [15][450/625] eta: 0:00:07 time: 0.0445 data_time: 0.0019 memory: 838 2024/03/27 12:46:11 - mmengine - INFO - Epoch(val) [15][500/625] eta: 0:00:05 time: 0.0423 data_time: 0.0016 memory: 838 2024/03/27 12:46:13 - mmengine - INFO - Epoch(val) [15][550/625] eta: 0:00:03 time: 0.0355 data_time: 0.0022 memory: 838 2024/03/27 12:46:14 - mmengine - INFO - Epoch(val) [15][600/625] eta: 0:00:01 time: 0.0362 data_time: 0.0021 memory: 838 2024/03/27 12:46:30 - mmengine - INFO - Evaluating bbox... 2024/03/27 12:47:57 - mmengine - INFO - bbox_mAP_copypaste: 0.436 0.595 0.476 0.240 0.481 0.589 2024/03/27 12:47:59 - mmengine - INFO - Epoch(val) [15][625/625] coco/bbox_mAP: 0.4360 coco/bbox_mAP_50: 0.5950 coco/bbox_mAP_75: 0.4760 coco/bbox_mAP_s: 0.2400 coco/bbox_mAP_m: 0.4810 coco/bbox_mAP_l: 0.5890 data_time: 0.0006 time: 0.0340 2024/03/27 12:48:22 - mmengine - INFO - Epoch(train) [16][ 50/925] lr: 1.6535e-04 eta: 6:52:39 time: 0.4678 data_time: 0.0585 memory: 5496 grad_norm: 975.9138 loss: 449.2785 loss_cls: 170.5863 loss_bbox: 132.5202 loss_dfl: 146.1720 2024/03/27 12:48:42 - mmengine - INFO - Epoch(train) [16][100/925] lr: 1.6535e-04 eta: 6:52:13 time: 0.3857 data_time: 0.0026 memory: 5296 grad_norm: 1040.0270 loss: 443.4495 loss_cls: 167.6490 loss_bbox: 130.2241 loss_dfl: 145.5765 2024/03/27 12:48:51 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:49:01 - mmengine - INFO - Epoch(train) [16][150/925] lr: 1.6535e-04 eta: 6:51:48 time: 0.3921 data_time: 0.0020 memory: 5203 grad_norm: 1253.3012 loss: 448.6725 loss_cls: 169.8405 loss_bbox: 132.2487 loss_dfl: 146.5833 2024/03/27 12:49:21 - mmengine - INFO - Epoch(train) [16][200/925] lr: 1.6535e-04 eta: 6:51:26 time: 0.4051 data_time: 0.0020 memory: 5470 grad_norm: 934.0220 loss: 456.1367 loss_cls: 172.4608 loss_bbox: 135.6050 loss_dfl: 148.0709 2024/03/27 12:49:41 - mmengine - INFO - Epoch(train) [16][250/925] lr: 1.6535e-04 eta: 6:51:01 time: 0.3916 data_time: 0.0021 memory: 5256 grad_norm: 921.3317 loss: 453.7630 loss_cls: 170.9196 loss_bbox: 135.4355 loss_dfl: 147.4078 2024/03/27 12:50:00 - mmengine - INFO - Epoch(train) [16][300/925] lr: 1.6535e-04 eta: 6:50:34 time: 0.3821 data_time: 0.0021 memory: 5363 grad_norm: 943.6036 loss: 445.7031 loss_cls: 169.9342 loss_bbox: 130.9085 loss_dfl: 144.8605 2024/03/27 12:50:20 - mmengine - INFO - Epoch(train) [16][350/925] lr: 1.6535e-04 eta: 6:50:09 time: 0.3916 data_time: 0.0019 memory: 5283 grad_norm: 1069.7880 loss: 443.8523 loss_cls: 166.2711 loss_bbox: 131.7805 loss_dfl: 145.8006 2024/03/27 12:50:40 - mmengine - INFO - Epoch(train) [16][400/925] lr: 1.6535e-04 eta: 6:49:46 time: 0.3989 data_time: 0.0019 memory: 5230 grad_norm: 1016.7781 loss: 447.6400 loss_cls: 168.5008 loss_bbox: 132.5527 loss_dfl: 146.5865 2024/03/27 12:50:59 - mmengine - INFO - Epoch(train) [16][450/925] lr: 1.6535e-04 eta: 6:49:21 time: 0.3890 data_time: 0.0021 memory: 5336 grad_norm: 1042.4415 loss: 450.6945 loss_cls: 168.8091 loss_bbox: 135.4795 loss_dfl: 146.4058 2024/03/27 12:51:19 - mmengine - INFO - Epoch(train) [16][500/925] lr: 1.6535e-04 eta: 6:48:56 time: 0.3895 data_time: 0.0019 memory: 5736 grad_norm: 978.7270 loss: 449.4588 loss_cls: 170.5549 loss_bbox: 132.9633 loss_dfl: 145.9406 2024/03/27 12:51:39 - mmengine - INFO - Epoch(train) [16][550/925] lr: 1.6535e-04 eta: 6:48:33 time: 0.4001 data_time: 0.0019 memory: 5576 grad_norm: 969.7022 loss: 448.8606 loss_cls: 167.8065 loss_bbox: 134.9880 loss_dfl: 146.0662 2024/03/27 12:51:59 - mmengine - INFO - Epoch(train) [16][600/925] lr: 1.6535e-04 eta: 6:48:11 time: 0.4059 data_time: 0.0019 memory: 5203 grad_norm: 1088.4000 loss: 453.7862 loss_cls: 173.8039 loss_bbox: 133.0516 loss_dfl: 146.9306 2024/03/27 12:52:19 - mmengine - INFO - Epoch(train) [16][650/925] lr: 1.6535e-04 eta: 6:47:47 time: 0.3928 data_time: 0.0018 memory: 5283 grad_norm: 928.5150 loss: 441.8631 loss_cls: 166.3547 loss_bbox: 130.6406 loss_dfl: 144.8678 2024/03/27 12:52:39 - mmengine - INFO - Epoch(train) [16][700/925] lr: 1.6535e-04 eta: 6:47:27 time: 0.4142 data_time: 0.0023 memory: 5536 grad_norm: 989.5171 loss: 446.5699 loss_cls: 167.4619 loss_bbox: 133.3366 loss_dfl: 145.7714 2024/03/27 12:52:59 - mmengine - INFO - Epoch(train) [16][750/925] lr: 1.6535e-04 eta: 6:47:01 time: 0.3866 data_time: 0.0023 memory: 5590 grad_norm: 992.1494 loss: 446.7958 loss_cls: 168.4697 loss_bbox: 132.7170 loss_dfl: 145.6091 2024/03/27 12:53:19 - mmengine - INFO - Epoch(train) [16][800/925] lr: 1.6535e-04 eta: 6:46:37 time: 0.3951 data_time: 0.0019 memory: 5670 grad_norm: 1117.7457 loss: 440.6456 loss_cls: 166.5767 loss_bbox: 129.7007 loss_dfl: 144.3683 2024/03/27 12:53:38 - mmengine - INFO - Epoch(train) [16][850/925] lr: 1.6535e-04 eta: 6:46:14 time: 0.3959 data_time: 0.0020 memory: 5603 grad_norm: 943.5725 loss: 448.7918 loss_cls: 170.7374 loss_bbox: 132.2490 loss_dfl: 145.8054 2024/03/27 12:53:58 - mmengine - INFO - Epoch(train) [16][900/925] lr: 1.6535e-04 eta: 6:45:50 time: 0.3964 data_time: 0.0021 memory: 5764 grad_norm: 1048.5428 loss: 443.9645 loss_cls: 165.9548 loss_bbox: 132.9071 loss_dfl: 145.1026 2024/03/27 12:54:07 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:54:31 - mmengine - INFO - Epoch(train) [17][ 50/925] lr: 1.6287e-04 eta: 6:45:25 time: 0.4758 data_time: 0.0534 memory: 5630 grad_norm: 1005.1050 loss: 443.7028 loss_cls: 166.0552 loss_bbox: 132.2069 loss_dfl: 145.4406 2024/03/27 12:54:51 - mmengine - INFO - Epoch(train) [17][100/925] lr: 1.6287e-04 eta: 6:45:04 time: 0.4099 data_time: 0.0023 memory: 5270 grad_norm: 935.0903 loss: 444.7020 loss_cls: 167.3403 loss_bbox: 131.2153 loss_dfl: 146.1464 2024/03/27 12:55:11 - mmengine - INFO - Epoch(train) [17][150/925] lr: 1.6287e-04 eta: 6:44:40 time: 0.3954 data_time: 0.0020 memory: 5510 grad_norm: 992.1402 loss: 442.8310 loss_cls: 166.1646 loss_bbox: 131.5788 loss_dfl: 145.0876 2024/03/27 12:55:31 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 12:55:31 - mmengine - INFO - Epoch(train) [17][200/925] lr: 1.6287e-04 eta: 6:44:17 time: 0.3944 data_time: 0.0020 memory: 5403 grad_norm: 1208.5087 loss: 449.2716 loss_cls: 169.9422 loss_bbox: 134.0003 loss_dfl: 145.3290 2024/03/27 12:55:51 - mmengine - INFO - Epoch(train) [17][250/925] lr: 1.6287e-04 eta: 6:43:53 time: 0.3943 data_time: 0.0021 memory: 5576 grad_norm: 941.7124 loss: 440.4219 loss_cls: 165.0360 loss_bbox: 130.6311 loss_dfl: 144.7548 2024/03/27 12:56:11 - mmengine - INFO - Epoch(train) [17][300/925] lr: 1.6287e-04 eta: 6:43:31 time: 0.4053 data_time: 0.0020 memory: 5656 grad_norm: 900.6524 loss: 445.5738 loss_cls: 168.2592 loss_bbox: 131.5636 loss_dfl: 145.7510 2024/03/27 12:56:31 - mmengine - INFO - Epoch(train) [17][350/925] lr: 1.6287e-04 eta: 6:43:09 time: 0.4019 data_time: 0.0020 memory: 5176 grad_norm: 984.8613 loss: 446.0398 loss_cls: 167.9324 loss_bbox: 133.2310 loss_dfl: 144.8765 2024/03/27 12:56:51 - mmengine - INFO - Epoch(train) [17][400/925] lr: 1.6287e-04 eta: 6:42:44 time: 0.3887 data_time: 0.0020 memory: 5190 grad_norm: 995.9220 loss: 450.0587 loss_cls: 171.9198 loss_bbox: 131.2111 loss_dfl: 146.9279 2024/03/27 12:57:11 - mmengine - INFO - Epoch(train) [17][450/925] lr: 1.6287e-04 eta: 6:42:24 time: 0.4124 data_time: 0.0019 memory: 5803 grad_norm: inf loss: 455.3361 loss_cls: 172.8148 loss_bbox: 134.5830 loss_dfl: 147.9382 2024/03/27 12:57:32 - mmengine - INFO - Epoch(train) [17][500/925] lr: 1.6287e-04 eta: 6:42:03 time: 0.4117 data_time: 0.0020 memory: 5190 grad_norm: 1104.6174 loss: 447.4854 loss_cls: 169.7434 loss_bbox: 131.5801 loss_dfl: 146.1620 2024/03/27 12:57:51 - mmengine - INFO - Epoch(train) [17][550/925] lr: 1.6287e-04 eta: 6:41:39 time: 0.3926 data_time: 0.0020 memory: 5283 grad_norm: 948.1324 loss: 447.7151 loss_cls: 170.3999 loss_bbox: 132.0332 loss_dfl: 145.2821 2024/03/27 12:58:12 - mmengine - INFO - Epoch(train) [17][600/925] lr: 1.6287e-04 eta: 6:41:18 time: 0.4075 data_time: 0.0020 memory: 5416 grad_norm: 1035.0749 loss: 444.5407 loss_cls: 166.9591 loss_bbox: 131.8751 loss_dfl: 145.7066 2024/03/27 12:58:32 - mmengine - INFO - Epoch(train) [17][650/925] lr: 1.6287e-04 eta: 6:40:56 time: 0.4044 data_time: 0.0019 memory: 5296 grad_norm: 997.2788 loss: 448.1717 loss_cls: 168.3952 loss_bbox: 133.4519 loss_dfl: 146.3246 2024/03/27 12:58:52 - mmengine - INFO - Epoch(train) [17][700/925] lr: 1.6287e-04 eta: 6:40:32 time: 0.3904 data_time: 0.0020 memory: 5350 grad_norm: 1061.4126 loss: 454.2699 loss_cls: 173.8288 loss_bbox: 133.2497 loss_dfl: 147.1915 2024/03/27 12:59:12 - mmengine - INFO - Epoch(train) [17][750/925] lr: 1.6287e-04 eta: 6:40:09 time: 0.4007 data_time: 0.0020 memory: 5603 grad_norm: 916.4748 loss: 450.2454 loss_cls: 169.7012 loss_bbox: 133.5712 loss_dfl: 146.9730 2024/03/27 12:59:32 - mmengine - INFO - Epoch(train) [17][800/925] lr: 1.6287e-04 eta: 6:39:48 time: 0.4044 data_time: 0.0021 memory: 5816 grad_norm: 1014.4419 loss: 454.4048 loss_cls: 171.1882 loss_bbox: 135.6357 loss_dfl: 147.5809 2024/03/27 12:59:51 - mmengine - INFO - Epoch(train) [17][850/925] lr: 1.6287e-04 eta: 6:39:23 time: 0.3906 data_time: 0.0020 memory: 5216 grad_norm: 975.7225 loss: 443.5164 loss_cls: 166.1051 loss_bbox: 132.0814 loss_dfl: 145.3299 2024/03/27 13:00:11 - mmengine - INFO - Epoch(train) [17][900/925] lr: 1.6287e-04 eta: 6:38:59 time: 0.3894 data_time: 0.0019 memory: 5336 grad_norm: 1037.9490 loss: 449.6016 loss_cls: 169.5696 loss_bbox: 133.5011 loss_dfl: 146.5309 2024/03/27 13:00:21 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:00:46 - mmengine - INFO - Epoch(train) [18][ 50/925] lr: 1.6040e-04 eta: 6:38:41 time: 0.4959 data_time: 0.0727 memory: 5483 grad_norm: 1123.1212 loss: 449.0540 loss_cls: 170.3180 loss_bbox: 132.1415 loss_dfl: 146.5945 2024/03/27 13:01:06 - mmengine - INFO - Epoch(train) [18][100/925] lr: 1.6040e-04 eta: 6:38:18 time: 0.3989 data_time: 0.0019 memory: 5456 grad_norm: 879.7680 loss: 444.3952 loss_cls: 165.9851 loss_bbox: 132.6322 loss_dfl: 145.7779 2024/03/27 13:01:26 - mmengine - INFO - Epoch(train) [18][150/925] lr: 1.6040e-04 eta: 6:37:56 time: 0.3992 data_time: 0.0021 memory: 5350 grad_norm: 1105.3915 loss: 444.6232 loss_cls: 166.2870 loss_bbox: 132.2762 loss_dfl: 146.0600 2024/03/27 13:01:46 - mmengine - INFO - Epoch(train) [18][200/925] lr: 1.6040e-04 eta: 6:37:35 time: 0.4078 data_time: 0.0020 memory: 5376 grad_norm: 1141.6633 loss: 450.3362 loss_cls: 170.7224 loss_bbox: 133.3852 loss_dfl: 146.2286 2024/03/27 13:02:06 - mmengine - INFO - Epoch(train) [18][250/925] lr: 1.6040e-04 eta: 6:37:14 time: 0.4071 data_time: 0.0020 memory: 5510 grad_norm: 1081.3258 loss: 451.7443 loss_cls: 169.4426 loss_bbox: 134.8965 loss_dfl: 147.4053 2024/03/27 13:02:16 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:02:26 - mmengine - INFO - Epoch(train) [18][300/925] lr: 1.6040e-04 eta: 6:36:48 time: 0.3820 data_time: 0.0019 memory: 5936 grad_norm: 934.0659 loss: 443.7532 loss_cls: 166.6615 loss_bbox: 132.4336 loss_dfl: 144.6581 2024/03/27 13:02:47 - mmengine - INFO - Epoch(train) [18][350/925] lr: 1.6040e-04 eta: 6:36:29 time: 0.4194 data_time: 0.0019 memory: 5216 grad_norm: 1005.2260 loss: 447.5089 loss_cls: 169.5640 loss_bbox: 132.1327 loss_dfl: 145.8123 2024/03/27 13:03:07 - mmengine - INFO - Epoch(train) [18][400/925] lr: 1.6040e-04 eta: 6:36:07 time: 0.4039 data_time: 0.0020 memory: 5323 grad_norm: 948.1654 loss: 442.8763 loss_cls: 166.4813 loss_bbox: 130.8541 loss_dfl: 145.5409 2024/03/27 13:03:26 - mmengine - INFO - Epoch(train) [18][450/925] lr: 1.6040e-04 eta: 6:35:42 time: 0.3844 data_time: 0.0020 memory: 5776 grad_norm: 1009.8428 loss: 444.2946 loss_cls: 165.5085 loss_bbox: 133.2957 loss_dfl: 145.4904 2024/03/27 13:03:46 - mmengine - INFO - Epoch(train) [18][500/925] lr: 1.6040e-04 eta: 6:35:19 time: 0.3949 data_time: 0.0018 memory: 5536 grad_norm: 954.4300 loss: 446.6792 loss_cls: 168.6508 loss_bbox: 131.9815 loss_dfl: 146.0468 2024/03/27 13:04:05 - mmengine - INFO - Epoch(train) [18][550/925] lr: 1.6040e-04 eta: 6:34:55 time: 0.3929 data_time: 0.0021 memory: 5123 grad_norm: 1110.6509 loss: 444.6608 loss_cls: 168.6989 loss_bbox: 130.8652 loss_dfl: 145.0967 2024/03/27 13:04:25 - mmengine - INFO - Epoch(train) [18][600/925] lr: 1.6040e-04 eta: 6:34:31 time: 0.3920 data_time: 0.0021 memory: 5350 grad_norm: 980.5574 loss: 444.4985 loss_cls: 166.6025 loss_bbox: 131.6683 loss_dfl: 146.2277 2024/03/27 13:04:45 - mmengine - INFO - Epoch(train) [18][650/925] lr: 1.6040e-04 eta: 6:34:07 time: 0.3913 data_time: 0.0019 memory: 5630 grad_norm: 1056.6806 loss: 452.0237 loss_cls: 171.0480 loss_bbox: 134.5930 loss_dfl: 146.3827 2024/03/27 13:05:05 - mmengine - INFO - Epoch(train) [18][700/925] lr: 1.6040e-04 eta: 6:33:45 time: 0.4036 data_time: 0.0020 memory: 5443 grad_norm: 1047.0603 loss: 449.5736 loss_cls: 168.8393 loss_bbox: 134.1563 loss_dfl: 146.5780 2024/03/27 13:05:25 - mmengine - INFO - Epoch(train) [18][750/925] lr: 1.6040e-04 eta: 6:33:22 time: 0.3927 data_time: 0.0019 memory: 5603 grad_norm: 979.9058 loss: 454.0446 loss_cls: 171.3052 loss_bbox: 135.4991 loss_dfl: 147.2403 2024/03/27 13:05:44 - mmengine - INFO - Epoch(train) [18][800/925] lr: 1.6040e-04 eta: 6:32:57 time: 0.3846 data_time: 0.0021 memory: 5256 grad_norm: 902.6039 loss: 442.9586 loss_cls: 167.5719 loss_bbox: 130.3387 loss_dfl: 145.0480 2024/03/27 13:06:04 - mmengine - INFO - Epoch(train) [18][850/925] lr: 1.6040e-04 eta: 6:32:36 time: 0.4101 data_time: 0.0018 memory: 5323 grad_norm: 1058.5454 loss: 441.1908 loss_cls: 165.6258 loss_bbox: 130.5584 loss_dfl: 145.0066 2024/03/27 13:06:24 - mmengine - INFO - Epoch(train) [18][900/925] lr: 1.6040e-04 eta: 6:32:14 time: 0.3998 data_time: 0.0019 memory: 5723 grad_norm: 1102.0304 loss: 436.5705 loss_cls: 163.3115 loss_bbox: 128.9681 loss_dfl: 144.2909 2024/03/27 13:06:33 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:06:57 - mmengine - INFO - Epoch(train) [19][ 50/925] lr: 1.5793e-04 eta: 6:31:47 time: 0.4692 data_time: 0.0741 memory: 5656 grad_norm: 924.5924 loss: 448.3565 loss_cls: 168.9830 loss_bbox: 133.6986 loss_dfl: 145.6749 2024/03/27 13:07:17 - mmengine - INFO - Epoch(train) [19][100/925] lr: 1.5793e-04 eta: 6:31:26 time: 0.4055 data_time: 0.0020 memory: 5776 grad_norm: 985.3999 loss: 443.6398 loss_cls: 168.1085 loss_bbox: 130.6848 loss_dfl: 144.8466 2024/03/27 13:07:37 - mmengine - INFO - Epoch(train) [19][150/925] lr: 1.5793e-04 eta: 6:31:02 time: 0.3927 data_time: 0.0022 memory: 5496 grad_norm: 947.8028 loss: 441.1214 loss_cls: 165.0996 loss_bbox: 129.9622 loss_dfl: 146.0595 2024/03/27 13:07:56 - mmengine - INFO - Epoch(train) [19][200/925] lr: 1.5793e-04 eta: 6:30:38 time: 0.3861 data_time: 0.0023 memory: 5323 grad_norm: 1063.8535 loss: 440.5013 loss_cls: 164.0198 loss_bbox: 131.1967 loss_dfl: 145.2848 2024/03/27 13:08:17 - mmengine - INFO - Epoch(train) [19][250/925] lr: 1.5793e-04 eta: 6:30:17 time: 0.4097 data_time: 0.0019 memory: 5590 grad_norm: 955.0547 loss: 441.7985 loss_cls: 166.4788 loss_bbox: 130.8263 loss_dfl: 144.4934 2024/03/27 13:08:37 - mmengine - INFO - Epoch(train) [19][300/925] lr: 1.5793e-04 eta: 6:29:55 time: 0.4019 data_time: 0.0020 memory: 5510 grad_norm: 1028.8535 loss: 435.4897 loss_cls: 163.7316 loss_bbox: 127.8526 loss_dfl: 143.9055 2024/03/27 13:08:56 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:08:56 - mmengine - INFO - Epoch(train) [19][350/925] lr: 1.5793e-04 eta: 6:29:32 time: 0.3944 data_time: 0.0019 memory: 5176 grad_norm: 984.3567 loss: 440.5114 loss_cls: 164.9405 loss_bbox: 130.5777 loss_dfl: 144.9932 2024/03/27 13:09:16 - mmengine - INFO - Epoch(train) [19][400/925] lr: 1.5793e-04 eta: 6:29:09 time: 0.3942 data_time: 0.0017 memory: 5150 grad_norm: 958.6434 loss: 438.8444 loss_cls: 163.5571 loss_bbox: 130.6749 loss_dfl: 144.6124 2024/03/27 13:09:37 - mmengine - INFO - Epoch(train) [19][450/925] lr: 1.5793e-04 eta: 6:28:49 time: 0.4143 data_time: 0.0019 memory: 5616 grad_norm: 960.3969 loss: 450.9242 loss_cls: 170.9927 loss_bbox: 133.4406 loss_dfl: 146.4909 2024/03/27 13:09:56 - mmengine - INFO - Epoch(train) [19][500/925] lr: 1.5793e-04 eta: 6:28:24 time: 0.3810 data_time: 0.0021 memory: 5470 grad_norm: 1068.6189 loss: 447.5449 loss_cls: 169.3465 loss_bbox: 131.9443 loss_dfl: 146.2542 2024/03/27 13:10:16 - mmengine - INFO - Epoch(train) [19][550/925] lr: 1.5793e-04 eta: 6:28:02 time: 0.4023 data_time: 0.0019 memory: 5803 grad_norm: 915.1798 loss: 445.1634 loss_cls: 168.1083 loss_bbox: 132.0821 loss_dfl: 144.9730 2024/03/27 13:10:37 - mmengine - INFO - Epoch(train) [19][600/925] lr: 1.5793e-04 eta: 6:27:43 time: 0.4172 data_time: 0.0027 memory: 5616 grad_norm: 1103.5633 loss: 440.0365 loss_cls: 166.7940 loss_bbox: 128.8420 loss_dfl: 144.4004 2024/03/27 13:10:57 - mmengine - INFO - Epoch(train) [19][650/925] lr: 1.5793e-04 eta: 6:27:22 time: 0.4088 data_time: 0.0021 memory: 5256 grad_norm: 945.1276 loss: 440.8123 loss_cls: 166.3857 loss_bbox: 130.5552 loss_dfl: 143.8714 2024/03/27 13:11:17 - mmengine - INFO - Epoch(train) [19][700/925] lr: 1.5793e-04 eta: 6:26:58 time: 0.3862 data_time: 0.0021 memory: 5430 grad_norm: 1015.2898 loss: 449.0250 loss_cls: 170.4894 loss_bbox: 132.9195 loss_dfl: 145.6161 2024/03/27 13:11:38 - mmengine - INFO - Epoch(train) [19][750/925] lr: 1.5793e-04 eta: 6:26:40 time: 0.4285 data_time: 0.0019 memory: 5470 grad_norm: 957.3505 loss: 448.3329 loss_cls: 168.9650 loss_bbox: 133.9559 loss_dfl: 145.4120 2024/03/27 13:11:59 - mmengine - INFO - Epoch(train) [19][800/925] lr: 1.5793e-04 eta: 6:26:20 time: 0.4105 data_time: 0.0019 memory: 5376 grad_norm: 1034.4848 loss: 436.4594 loss_cls: 163.2230 loss_bbox: 128.5248 loss_dfl: 144.7115 2024/03/27 13:12:19 - mmengine - INFO - Epoch(train) [19][850/925] lr: 1.5793e-04 eta: 6:25:59 time: 0.4041 data_time: 0.0020 memory: 5696 grad_norm: 954.9816 loss: 444.4047 loss_cls: 166.7886 loss_bbox: 132.3537 loss_dfl: 145.2624 2024/03/27 13:12:39 - mmengine - INFO - Epoch(train) [19][900/925] lr: 1.5793e-04 eta: 6:25:38 time: 0.4060 data_time: 0.0020 memory: 5310 grad_norm: 1016.5626 loss: 441.2912 loss_cls: 165.2733 loss_bbox: 131.0663 loss_dfl: 144.9516 2024/03/27 13:12:49 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:13:13 - mmengine - INFO - Epoch(train) [20][ 50/925] lr: 1.5545e-04 eta: 6:25:15 time: 0.4772 data_time: 0.0569 memory: 5430 grad_norm: 956.8203 loss: 438.5968 loss_cls: 164.2446 loss_bbox: 129.8083 loss_dfl: 144.5439 2024/03/27 13:13:33 - mmengine - INFO - Epoch(train) [20][100/925] lr: 1.5545e-04 eta: 6:24:53 time: 0.3992 data_time: 0.0020 memory: 5563 grad_norm: 1066.3591 loss: 445.8482 loss_cls: 167.4991 loss_bbox: 131.9725 loss_dfl: 146.3766 2024/03/27 13:13:53 - mmengine - INFO - Epoch(train) [20][150/925] lr: 1.5545e-04 eta: 6:24:31 time: 0.3988 data_time: 0.0020 memory: 5430 grad_norm: 1062.8528 loss: 444.5421 loss_cls: 166.5972 loss_bbox: 132.7475 loss_dfl: 145.1974 2024/03/27 13:14:14 - mmengine - INFO - Epoch(train) [20][200/925] lr: 1.5545e-04 eta: 6:24:10 time: 0.4123 data_time: 0.0022 memory: 5470 grad_norm: 877.3485 loss: 446.9990 loss_cls: 169.5623 loss_bbox: 131.9163 loss_dfl: 145.5203 2024/03/27 13:14:34 - mmengine - INFO - Epoch(train) [20][250/925] lr: 1.5545e-04 eta: 6:23:49 time: 0.4010 data_time: 0.0020 memory: 5656 grad_norm: 1176.5564 loss: 446.9907 loss_cls: 168.7292 loss_bbox: 132.3292 loss_dfl: 145.9323 2024/03/27 13:14:53 - mmengine - INFO - Epoch(train) [20][300/925] lr: 1.5545e-04 eta: 6:23:25 time: 0.3884 data_time: 0.0020 memory: 5203 grad_norm: inf loss: 442.7241 loss_cls: 167.6228 loss_bbox: 130.2724 loss_dfl: 144.8289 2024/03/27 13:15:13 - mmengine - INFO - Epoch(train) [20][350/925] lr: 1.5545e-04 eta: 6:23:03 time: 0.4053 data_time: 0.0021 memory: 5323 grad_norm: 1036.8539 loss: 451.4109 loss_cls: 171.3753 loss_bbox: 133.3090 loss_dfl: 146.7265 2024/03/27 13:15:33 - mmengine - INFO - Epoch(train) [20][400/925] lr: 1.5545e-04 eta: 6:22:41 time: 0.3944 data_time: 0.0094 memory: 5350 grad_norm: 1114.3793 loss: 435.9302 loss_cls: 162.4133 loss_bbox: 129.2060 loss_dfl: 144.3109 2024/03/27 13:15:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:15:52 - mmengine - INFO - Epoch(train) [20][450/925] lr: 1.5545e-04 eta: 6:22:15 time: 0.3795 data_time: 0.0020 memory: 5643 grad_norm: 955.9616 loss: 444.5536 loss_cls: 167.8369 loss_bbox: 130.9197 loss_dfl: 145.7971 2024/03/27 13:16:12 - mmengine - INFO - Epoch(train) [20][500/925] lr: 1.5545e-04 eta: 6:21:53 time: 0.4006 data_time: 0.0020 memory: 5443 grad_norm: 1001.1046 loss: 439.2361 loss_cls: 166.4077 loss_bbox: 128.5934 loss_dfl: 144.2349 2024/03/27 13:16:32 - mmengine - INFO - Epoch(train) [20][550/925] lr: 1.5545e-04 eta: 6:21:30 time: 0.3885 data_time: 0.0024 memory: 5230 grad_norm: 995.1919 loss: 438.8704 loss_cls: 163.7587 loss_bbox: 130.4624 loss_dfl: 144.6494 2024/03/27 13:16:51 - mmengine - INFO - Epoch(train) [20][600/925] lr: 1.5545e-04 eta: 6:21:05 time: 0.3839 data_time: 0.0021 memory: 5323 grad_norm: 1067.8606 loss: 447.4033 loss_cls: 168.7920 loss_bbox: 132.2008 loss_dfl: 146.4106 2024/03/27 13:17:11 - mmengine - INFO - Epoch(train) [20][650/925] lr: 1.5545e-04 eta: 6:20:43 time: 0.3972 data_time: 0.0020 memory: 5643 grad_norm: 987.0268 loss: 445.1796 loss_cls: 167.2404 loss_bbox: 131.0593 loss_dfl: 146.8799 2024/03/27 13:17:31 - mmengine - INFO - Epoch(train) [20][700/925] lr: 1.5545e-04 eta: 6:20:21 time: 0.3988 data_time: 0.0020 memory: 5416 grad_norm: 880.4288 loss: 437.4864 loss_cls: 161.8648 loss_bbox: 131.5442 loss_dfl: 144.0774 2024/03/27 13:17:49 - mmengine - INFO - Epoch(train) [20][750/925] lr: 1.5545e-04 eta: 6:19:54 time: 0.3709 data_time: 0.0021 memory: 5456 grad_norm: 1024.9308 loss: 453.9065 loss_cls: 170.6153 loss_bbox: 135.9837 loss_dfl: 147.3074 2024/03/27 13:18:09 - mmengine - INFO - Epoch(train) [20][800/925] lr: 1.5545e-04 eta: 6:19:30 time: 0.3854 data_time: 0.0021 memory: 5150 grad_norm: 986.6870 loss: 438.7734 loss_cls: 163.2950 loss_bbox: 130.8118 loss_dfl: 144.6666 2024/03/27 13:18:28 - mmengine - INFO - Epoch(train) [20][850/925] lr: 1.5545e-04 eta: 6:19:08 time: 0.3969 data_time: 0.0021 memory: 5710 grad_norm: 890.4385 loss: 448.0351 loss_cls: 169.9764 loss_bbox: 132.1767 loss_dfl: 145.8819 2024/03/27 13:18:47 - mmengine - INFO - Epoch(train) [20][900/925] lr: 1.5545e-04 eta: 6:18:42 time: 0.3734 data_time: 0.0021 memory: 5764 grad_norm: 976.7364 loss: 439.3170 loss_cls: 163.9495 loss_bbox: 130.8695 loss_dfl: 144.4980 2024/03/27 13:18:56 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:18:56 - mmengine - INFO - Saving checkpoint at 20 epochs 2024/03/27 13:19:05 - mmengine - INFO - Epoch(val) [20][ 50/625] eta: 0:00:25 time: 0.0435 data_time: 0.0009 memory: 5350 2024/03/27 13:19:07 - mmengine - INFO - Epoch(val) [20][100/625] eta: 0:00:22 time: 0.0421 data_time: 0.0004 memory: 838 2024/03/27 13:19:09 - mmengine - INFO - Epoch(val) [20][150/625] eta: 0:00:20 time: 0.0447 data_time: 0.0004 memory: 838 2024/03/27 13:19:11 - mmengine - INFO - Epoch(val) [20][200/625] eta: 0:00:18 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 13:19:13 - mmengine - INFO - Epoch(val) [20][250/625] eta: 0:00:16 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 13:19:15 - mmengine - INFO - Epoch(val) [20][300/625] eta: 0:00:14 time: 0.0430 data_time: 0.0003 memory: 838 2024/03/27 13:19:20 - mmengine - INFO - Epoch(val) [20][350/625] eta: 0:00:14 time: 0.1007 data_time: 0.0583 memory: 838 2024/03/27 13:19:23 - mmengine - INFO - Epoch(val) [20][400/625] eta: 0:00:11 time: 0.0427 data_time: 0.0004 memory: 838 2024/03/27 13:19:25 - mmengine - INFO - Epoch(val) [20][450/625] eta: 0:00:08 time: 0.0438 data_time: 0.0003 memory: 838 2024/03/27 13:19:27 - mmengine - INFO - Epoch(val) [20][500/625] eta: 0:00:06 time: 0.0441 data_time: 0.0044 memory: 838 2024/03/27 13:19:29 - mmengine - INFO - Epoch(val) [20][550/625] eta: 0:00:03 time: 0.0340 data_time: 0.0003 memory: 838 2024/03/27 13:19:31 - mmengine - INFO - Epoch(val) [20][600/625] eta: 0:00:01 time: 0.0353 data_time: 0.0018 memory: 838 2024/03/27 13:19:47 - mmengine - INFO - Evaluating bbox... 2024/03/27 13:21:18 - mmengine - INFO - bbox_mAP_copypaste: 0.442 0.603 0.482 0.246 0.491 0.591 2024/03/27 13:21:20 - mmengine - INFO - Epoch(val) [20][625/625] coco/bbox_mAP: 0.4420 coco/bbox_mAP_50: 0.6030 coco/bbox_mAP_75: 0.4820 coco/bbox_mAP_s: 0.2460 coco/bbox_mAP_m: 0.4910 coco/bbox_mAP_l: 0.5910 data_time: 0.0003 time: 0.0341 2024/03/27 13:21:44 - mmengine - INFO - Epoch(train) [21][ 50/925] lr: 1.5297e-04 eta: 6:18:16 time: 0.4721 data_time: 0.0683 memory: 5443 grad_norm: 924.5635 loss: 437.9373 loss_cls: 164.6234 loss_bbox: 129.7671 loss_dfl: 143.5468 2024/03/27 13:22:04 - mmengine - INFO - Epoch(train) [21][100/925] lr: 1.5297e-04 eta: 6:17:53 time: 0.3980 data_time: 0.0021 memory: 5483 grad_norm: 1138.8861 loss: 437.6257 loss_cls: 161.8334 loss_bbox: 131.4324 loss_dfl: 144.3599 2024/03/27 13:22:23 - mmengine - INFO - Epoch(train) [21][150/925] lr: 1.5297e-04 eta: 6:17:29 time: 0.3841 data_time: 0.0022 memory: 5363 grad_norm: 1132.6777 loss: 439.7755 loss_cls: 165.1073 loss_bbox: 130.6047 loss_dfl: 144.0635 2024/03/27 13:22:42 - mmengine - INFO - Epoch(train) [21][200/925] lr: 1.5297e-04 eta: 6:17:04 time: 0.3777 data_time: 0.0019 memory: 5603 grad_norm: 838.4842 loss: 438.1262 loss_cls: 164.6266 loss_bbox: 129.4268 loss_dfl: 144.0728 2024/03/27 13:23:02 - mmengine - INFO - Epoch(train) [21][250/925] lr: 1.5297e-04 eta: 6:16:43 time: 0.4056 data_time: 0.0021 memory: 5550 grad_norm: 1013.8799 loss: 442.2572 loss_cls: 164.9841 loss_bbox: 131.9102 loss_dfl: 145.3629 2024/03/27 13:23:21 - mmengine - INFO - Epoch(train) [21][300/925] lr: 1.5297e-04 eta: 6:16:19 time: 0.3827 data_time: 0.0020 memory: 5470 grad_norm: 959.9636 loss: 440.3844 loss_cls: 162.0067 loss_bbox: 133.1799 loss_dfl: 145.1979 2024/03/27 13:23:41 - mmengine - INFO - Epoch(train) [21][350/925] lr: 1.5297e-04 eta: 6:15:56 time: 0.3918 data_time: 0.0020 memory: 5563 grad_norm: 1055.3064 loss: 449.6949 loss_cls: 170.1187 loss_bbox: 133.4332 loss_dfl: 146.1430 2024/03/27 13:24:02 - mmengine - INFO - Epoch(train) [21][400/925] lr: 1.5297e-04 eta: 6:15:36 time: 0.4125 data_time: 0.0020 memory: 5283 grad_norm: 1042.6907 loss: 440.4213 loss_cls: 164.2353 loss_bbox: 131.4940 loss_dfl: 144.6921 2024/03/27 13:24:22 - mmengine - INFO - Epoch(train) [21][450/925] lr: 1.5297e-04 eta: 6:15:14 time: 0.4010 data_time: 0.0027 memory: 5323 grad_norm: inf loss: 449.7481 loss_cls: 169.1045 loss_bbox: 133.6636 loss_dfl: 146.9801 2024/03/27 13:24:41 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:24:41 - mmengine - INFO - Epoch(train) [21][500/925] lr: 1.5297e-04 eta: 6:14:51 time: 0.3895 data_time: 0.0018 memory: 5203 grad_norm: 989.6160 loss: 434.2366 loss_cls: 163.4750 loss_bbox: 127.0455 loss_dfl: 143.7161 2024/03/27 13:25:01 - mmengine - INFO - Epoch(train) [21][550/925] lr: 1.5297e-04 eta: 6:14:28 time: 0.3886 data_time: 0.0019 memory: 5376 grad_norm: 985.5265 loss: 444.6289 loss_cls: 165.8283 loss_bbox: 133.6495 loss_dfl: 145.1511 2024/03/27 13:25:20 - mmengine - INFO - Epoch(train) [21][600/925] lr: 1.5297e-04 eta: 6:14:05 time: 0.3948 data_time: 0.0020 memory: 5643 grad_norm: 1034.7966 loss: 445.5942 loss_cls: 167.5182 loss_bbox: 132.4728 loss_dfl: 145.6032 2024/03/27 13:25:40 - mmengine - INFO - Epoch(train) [21][650/925] lr: 1.5297e-04 eta: 6:13:42 time: 0.3900 data_time: 0.0021 memory: 5390 grad_norm: 925.0711 loss: 447.0265 loss_cls: 169.3236 loss_bbox: 131.7436 loss_dfl: 145.9593 2024/03/27 13:26:00 - mmengine - INFO - Epoch(train) [21][700/925] lr: 1.5297e-04 eta: 6:13:21 time: 0.4064 data_time: 0.0020 memory: 5416 grad_norm: 940.3222 loss: 444.3010 loss_cls: 165.2683 loss_bbox: 133.3539 loss_dfl: 145.6787 2024/03/27 13:26:21 - mmengine - INFO - Epoch(train) [21][750/925] lr: 1.5297e-04 eta: 6:13:01 time: 0.4132 data_time: 0.0019 memory: 5510 grad_norm: 994.6732 loss: 439.6525 loss_cls: 165.3003 loss_bbox: 129.4602 loss_dfl: 144.8919 2024/03/27 13:26:41 - mmengine - INFO - Epoch(train) [21][800/925] lr: 1.5297e-04 eta: 6:12:41 time: 0.4074 data_time: 0.0020 memory: 5350 grad_norm: 981.8355 loss: 447.5682 loss_cls: 166.6088 loss_bbox: 134.5777 loss_dfl: 146.3818 2024/03/27 13:27:01 - mmengine - INFO - Epoch(train) [21][850/925] lr: 1.5297e-04 eta: 6:12:17 time: 0.3870 data_time: 0.0019 memory: 5523 grad_norm: 918.1869 loss: 441.9206 loss_cls: 164.5660 loss_bbox: 132.1416 loss_dfl: 145.2130 2024/03/27 13:27:22 - mmengine - INFO - Epoch(train) [21][900/925] lr: 1.5297e-04 eta: 6:11:59 time: 0.4230 data_time: 0.0021 memory: 5350 grad_norm: 1214.4907 loss: 434.5505 loss_cls: 161.1427 loss_bbox: 129.1016 loss_dfl: 144.3061 2024/03/27 13:27:31 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:27:55 - mmengine - INFO - Epoch(train) [22][ 50/925] lr: 1.5050e-04 eta: 6:11:33 time: 0.4719 data_time: 0.0692 memory: 5456 grad_norm: 928.0215 loss: 441.3079 loss_cls: 163.8346 loss_bbox: 131.8518 loss_dfl: 145.6214 2024/03/27 13:28:14 - mmengine - INFO - Epoch(train) [22][100/925] lr: 1.5050e-04 eta: 6:11:11 time: 0.3971 data_time: 0.0020 memory: 5163 grad_norm: 961.6790 loss: 433.8135 loss_cls: 160.9101 loss_bbox: 128.9953 loss_dfl: 143.9081 2024/03/27 13:28:35 - mmengine - INFO - Epoch(train) [22][150/925] lr: 1.5050e-04 eta: 6:10:51 time: 0.4117 data_time: 0.0020 memory: 5376 grad_norm: 961.9221 loss: 441.5769 loss_cls: 165.0965 loss_bbox: 131.2848 loss_dfl: 145.1955 2024/03/27 13:28:55 - mmengine - INFO - Epoch(train) [22][200/925] lr: 1.5050e-04 eta: 6:10:29 time: 0.4025 data_time: 0.0020 memory: 5430 grad_norm: 912.1911 loss: 438.5551 loss_cls: 163.7574 loss_bbox: 129.9892 loss_dfl: 144.8086 2024/03/27 13:29:14 - mmengine - INFO - Epoch(train) [22][250/925] lr: 1.5050e-04 eta: 6:10:06 time: 0.3849 data_time: 0.0020 memory: 5670 grad_norm: 1001.2837 loss: 449.8862 loss_cls: 168.7730 loss_bbox: 134.4709 loss_dfl: 146.6422 2024/03/27 13:29:35 - mmengine - INFO - Epoch(train) [22][300/925] lr: 1.5050e-04 eta: 6:09:45 time: 0.4110 data_time: 0.0020 memory: 5150 grad_norm: 930.1965 loss: 442.4709 loss_cls: 164.8035 loss_bbox: 132.2107 loss_dfl: 145.4568 2024/03/27 13:29:55 - mmengine - INFO - Epoch(train) [22][350/925] lr: 1.5050e-04 eta: 6:09:24 time: 0.4022 data_time: 0.0020 memory: 5523 grad_norm: 980.2487 loss: 445.5372 loss_cls: 167.7211 loss_bbox: 132.5244 loss_dfl: 145.2917 2024/03/27 13:30:15 - mmengine - INFO - Epoch(train) [22][400/925] lr: 1.5050e-04 eta: 6:09:02 time: 0.3997 data_time: 0.0022 memory: 5176 grad_norm: 958.3772 loss: 443.8937 loss_cls: 166.2933 loss_bbox: 131.8331 loss_dfl: 145.7673 2024/03/27 13:30:35 - mmengine - INFO - Epoch(train) [22][450/925] lr: 1.5050e-04 eta: 6:08:41 time: 0.3986 data_time: 0.0020 memory: 5176 grad_norm: 902.2777 loss: 445.0085 loss_cls: 167.4684 loss_bbox: 131.6633 loss_dfl: 145.8768 2024/03/27 13:30:55 - mmengine - INFO - Epoch(train) [22][500/925] lr: 1.5050e-04 eta: 6:08:19 time: 0.4012 data_time: 0.0022 memory: 5403 grad_norm: 1020.4510 loss: 440.7441 loss_cls: 162.8392 loss_bbox: 131.9083 loss_dfl: 145.9966 2024/03/27 13:31:15 - mmengine - INFO - Epoch(train) [22][550/925] lr: 1.5050e-04 eta: 6:07:57 time: 0.3989 data_time: 0.0020 memory: 5363 grad_norm: 913.3751 loss: 438.7624 loss_cls: 165.2518 loss_bbox: 129.6382 loss_dfl: 143.8724 2024/03/27 13:31:25 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:31:35 - mmengine - INFO - Epoch(train) [22][600/925] lr: 1.5050e-04 eta: 6:07:36 time: 0.3993 data_time: 0.0020 memory: 5496 grad_norm: 917.1679 loss: 437.2125 loss_cls: 162.5319 loss_bbox: 130.6672 loss_dfl: 144.0134 2024/03/27 13:31:55 - mmengine - INFO - Epoch(train) [22][650/925] lr: 1.5050e-04 eta: 6:07:14 time: 0.3986 data_time: 0.0020 memory: 5310 grad_norm: 972.9777 loss: 438.9487 loss_cls: 163.0747 loss_bbox: 131.3143 loss_dfl: 144.5596 2024/03/27 13:32:15 - mmengine - INFO - Epoch(train) [22][700/925] lr: 1.5050e-04 eta: 6:06:52 time: 0.3952 data_time: 0.0020 memory: 5310 grad_norm: 1053.8494 loss: 444.0761 loss_cls: 164.5393 loss_bbox: 133.4758 loss_dfl: 146.0610 2024/03/27 13:32:35 - mmengine - INFO - Epoch(train) [22][750/925] lr: 1.5050e-04 eta: 6:06:30 time: 0.4001 data_time: 0.0021 memory: 5696 grad_norm: 1094.5069 loss: 437.1028 loss_cls: 162.9754 loss_bbox: 131.0346 loss_dfl: 143.0928 2024/03/27 13:32:56 - mmengine - INFO - Epoch(train) [22][800/925] lr: 1.5050e-04 eta: 6:06:10 time: 0.4110 data_time: 0.0020 memory: 5563 grad_norm: 858.0721 loss: 436.5740 loss_cls: 160.5026 loss_bbox: 131.3523 loss_dfl: 144.7191 2024/03/27 13:33:15 - mmengine - INFO - Epoch(train) [22][850/925] lr: 1.5050e-04 eta: 6:05:48 time: 0.3974 data_time: 0.0020 memory: 5270 grad_norm: 946.7028 loss: 442.8702 loss_cls: 165.1209 loss_bbox: 131.8152 loss_dfl: 145.9341 2024/03/27 13:33:34 - mmengine - INFO - Epoch(train) [22][900/925] lr: 1.5050e-04 eta: 6:05:23 time: 0.3755 data_time: 0.0020 memory: 5403 grad_norm: 1044.7892 loss: 441.3328 loss_cls: 165.8274 loss_bbox: 130.5313 loss_dfl: 144.9740 2024/03/27 13:33:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:34:08 - mmengine - INFO - Epoch(train) [23][ 50/925] lr: 1.4803e-04 eta: 6:05:00 time: 0.4861 data_time: 0.0595 memory: 5456 grad_norm: 1055.6103 loss: 437.8406 loss_cls: 161.9916 loss_bbox: 131.2437 loss_dfl: 144.6053 2024/03/27 13:34:28 - mmengine - INFO - Epoch(train) [23][100/925] lr: 1.4803e-04 eta: 6:04:39 time: 0.4068 data_time: 0.0020 memory: 5376 grad_norm: 998.9274 loss: 436.3940 loss_cls: 161.8960 loss_bbox: 130.1966 loss_dfl: 144.3014 2024/03/27 13:34:48 - mmengine - INFO - Epoch(train) [23][150/925] lr: 1.4803e-04 eta: 6:04:17 time: 0.3940 data_time: 0.0020 memory: 5443 grad_norm: 853.8684 loss: 447.3080 loss_cls: 168.2433 loss_bbox: 133.2451 loss_dfl: 145.8196 2024/03/27 13:35:08 - mmengine - INFO - Epoch(train) [23][200/925] lr: 1.4803e-04 eta: 6:03:55 time: 0.3974 data_time: 0.0022 memory: 5563 grad_norm: 1037.1645 loss: 444.6338 loss_cls: 166.3608 loss_bbox: 132.0006 loss_dfl: 146.2723 2024/03/27 13:35:28 - mmengine - INFO - Epoch(train) [23][250/925] lr: 1.4803e-04 eta: 6:03:34 time: 0.4015 data_time: 0.0021 memory: 5403 grad_norm: 951.4015 loss: 437.5777 loss_cls: 162.9531 loss_bbox: 130.0718 loss_dfl: 144.5528 2024/03/27 13:35:48 - mmengine - INFO - Epoch(train) [23][300/925] lr: 1.4803e-04 eta: 6:03:12 time: 0.3993 data_time: 0.0022 memory: 5243 grad_norm: 899.6179 loss: 433.5671 loss_cls: 161.1481 loss_bbox: 128.6978 loss_dfl: 143.7212 2024/03/27 13:36:08 - mmengine - INFO - Epoch(train) [23][350/925] lr: 1.4803e-04 eta: 6:02:49 time: 0.3923 data_time: 0.0020 memory: 5296 grad_norm: 937.1991 loss: 442.4783 loss_cls: 164.5012 loss_bbox: 133.1544 loss_dfl: 144.8227 2024/03/27 13:36:29 - mmengine - INFO - Epoch(train) [23][400/925] lr: 1.4803e-04 eta: 6:02:31 time: 0.4254 data_time: 0.0020 memory: 5523 grad_norm: 902.9352 loss: 455.3522 loss_cls: 172.1299 loss_bbox: 134.8928 loss_dfl: 148.3295 2024/03/27 13:36:49 - mmengine - INFO - Epoch(train) [23][450/925] lr: 1.4803e-04 eta: 6:02:10 time: 0.3990 data_time: 0.0020 memory: 5483 grad_norm: 915.2562 loss: 450.6477 loss_cls: 169.7867 loss_bbox: 133.9819 loss_dfl: 146.8791 2024/03/27 13:37:09 - mmengine - INFO - Epoch(train) [23][500/925] lr: 1.4803e-04 eta: 6:01:48 time: 0.4037 data_time: 0.0021 memory: 5470 grad_norm: 967.7427 loss: 445.9790 loss_cls: 167.0644 loss_bbox: 133.5392 loss_dfl: 145.3755 2024/03/27 13:37:30 - mmengine - INFO - Epoch(train) [23][550/925] lr: 1.4803e-04 eta: 6:01:29 time: 0.4153 data_time: 0.0020 memory: 5536 grad_norm: 1193.1031 loss: 437.3497 loss_cls: 163.4440 loss_bbox: 129.2890 loss_dfl: 144.6167 2024/03/27 13:37:51 - mmengine - INFO - Epoch(train) [23][600/925] lr: 1.4803e-04 eta: 6:01:09 time: 0.4126 data_time: 0.0022 memory: 5310 grad_norm: 935.9901 loss: 435.1263 loss_cls: 160.9739 loss_bbox: 129.6151 loss_dfl: 144.5373 2024/03/27 13:38:10 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:38:10 - mmengine - INFO - Epoch(train) [23][650/925] lr: 1.4803e-04 eta: 6:00:46 time: 0.3906 data_time: 0.0020 memory: 5136 grad_norm: 1153.4265 loss: 437.1907 loss_cls: 162.8828 loss_bbox: 129.2974 loss_dfl: 145.0105 2024/03/27 13:38:31 - mmengine - INFO - Epoch(train) [23][700/925] lr: 1.4803e-04 eta: 6:00:27 time: 0.4150 data_time: 0.0020 memory: 5243 grad_norm: 1057.2155 loss: 441.9796 loss_cls: 165.6026 loss_bbox: 131.0585 loss_dfl: 145.3184 2024/03/27 13:38:51 - mmengine - INFO - Epoch(train) [23][750/925] lr: 1.4803e-04 eta: 6:00:06 time: 0.4046 data_time: 0.0019 memory: 5550 grad_norm: 921.3010 loss: 439.7880 loss_cls: 162.8858 loss_bbox: 132.1708 loss_dfl: 144.7314 2024/03/27 13:39:11 - mmengine - INFO - Epoch(train) [23][800/925] lr: 1.4803e-04 eta: 5:59:44 time: 0.4005 data_time: 0.0024 memory: 5550 grad_norm: 968.3525 loss: 439.0575 loss_cls: 162.7714 loss_bbox: 131.9016 loss_dfl: 144.3845 2024/03/27 13:39:31 - mmengine - INFO - Epoch(train) [23][850/925] lr: 1.4803e-04 eta: 5:59:23 time: 0.3981 data_time: 0.0021 memory: 5550 grad_norm: 909.3263 loss: 441.8355 loss_cls: 164.6917 loss_bbox: 131.3996 loss_dfl: 145.7442 2024/03/27 13:39:51 - mmengine - INFO - Epoch(train) [23][900/925] lr: 1.4803e-04 eta: 5:59:01 time: 0.4007 data_time: 0.0021 memory: 6043 grad_norm: 972.1962 loss: 437.7654 loss_cls: 163.7054 loss_bbox: 130.0720 loss_dfl: 143.9880 2024/03/27 13:40:01 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:40:25 - mmengine - INFO - Epoch(train) [24][ 50/925] lr: 1.4555e-04 eta: 5:58:37 time: 0.4716 data_time: 0.0744 memory: 5323 grad_norm: 925.5355 loss: 442.6897 loss_cls: 166.3435 loss_bbox: 131.2563 loss_dfl: 145.0899 2024/03/27 13:40:45 - mmengine - INFO - Epoch(train) [24][100/925] lr: 1.4555e-04 eta: 5:58:16 time: 0.4047 data_time: 0.0021 memory: 5470 grad_norm: 1103.7017 loss: 439.6093 loss_cls: 164.8140 loss_bbox: 129.9608 loss_dfl: 144.8345 2024/03/27 13:41:05 - mmengine - INFO - Epoch(train) [24][150/925] lr: 1.4555e-04 eta: 5:57:55 time: 0.4057 data_time: 0.0020 memory: 5323 grad_norm: 1059.9547 loss: 438.1164 loss_cls: 162.9911 loss_bbox: 130.2177 loss_dfl: 144.9076 2024/03/27 13:41:24 - mmengine - INFO - Epoch(train) [24][200/925] lr: 1.4555e-04 eta: 5:57:30 time: 0.3754 data_time: 0.0021 memory: 5430 grad_norm: 898.5766 loss: 436.6569 loss_cls: 161.0790 loss_bbox: 131.2399 loss_dfl: 144.3381 2024/03/27 13:41:43 - mmengine - INFO - Epoch(train) [24][250/925] lr: 1.4555e-04 eta: 5:57:06 time: 0.3737 data_time: 0.0020 memory: 5630 grad_norm: 1131.4872 loss: 445.6389 loss_cls: 166.5180 loss_bbox: 133.1291 loss_dfl: 145.9918 2024/03/27 13:42:02 - mmengine - INFO - Epoch(train) [24][300/925] lr: 1.4555e-04 eta: 5:56:43 time: 0.3919 data_time: 0.0025 memory: 5496 grad_norm: 876.8102 loss: 448.0704 loss_cls: 167.6398 loss_bbox: 134.3062 loss_dfl: 146.1244 2024/03/27 13:42:22 - mmengine - INFO - Epoch(train) [24][350/925] lr: 1.4555e-04 eta: 5:56:22 time: 0.3965 data_time: 0.0023 memory: 5376 grad_norm: 977.1556 loss: 441.3165 loss_cls: 164.7987 loss_bbox: 131.3592 loss_dfl: 145.1586 2024/03/27 13:42:41 - mmengine - INFO - Epoch(train) [24][400/925] lr: 1.4555e-04 eta: 5:55:58 time: 0.3782 data_time: 0.0021 memory: 5443 grad_norm: 912.6110 loss: 445.1081 loss_cls: 167.1602 loss_bbox: 132.3617 loss_dfl: 145.5862 2024/03/27 13:43:01 - mmengine - INFO - Epoch(train) [24][450/925] lr: 1.4555e-04 eta: 5:55:36 time: 0.3946 data_time: 0.0020 memory: 5456 grad_norm: 966.2930 loss: 436.2523 loss_cls: 163.1570 loss_bbox: 129.4632 loss_dfl: 143.6320 2024/03/27 13:43:21 - mmengine - INFO - Epoch(train) [24][500/925] lr: 1.4555e-04 eta: 5:55:13 time: 0.3937 data_time: 0.0021 memory: 5296 grad_norm: 1021.7566 loss: 446.1757 loss_cls: 168.1992 loss_bbox: 132.7568 loss_dfl: 145.2197 2024/03/27 13:43:40 - mmengine - INFO - Epoch(train) [24][550/925] lr: 1.4555e-04 eta: 5:54:51 time: 0.3912 data_time: 0.0022 memory: 5430 grad_norm: 1024.9502 loss: 440.6080 loss_cls: 164.1090 loss_bbox: 131.4184 loss_dfl: 145.0806 2024/03/27 13:43:59 - mmengine - INFO - Epoch(train) [24][600/925] lr: 1.4555e-04 eta: 5:54:28 time: 0.3857 data_time: 0.0022 memory: 5403 grad_norm: 980.0122 loss: 447.1617 loss_cls: 167.6366 loss_bbox: 133.4174 loss_dfl: 146.1077 2024/03/27 13:44:19 - mmengine - INFO - Epoch(train) [24][650/925] lr: 1.4555e-04 eta: 5:54:06 time: 0.3965 data_time: 0.0021 memory: 5110 grad_norm: 921.8771 loss: 432.3733 loss_cls: 161.1079 loss_bbox: 128.0824 loss_dfl: 143.1829 2024/03/27 13:44:39 - mmengine - INFO - Epoch(train) [24][700/925] lr: 1.4555e-04 eta: 5:53:44 time: 0.3903 data_time: 0.0021 memory: 5150 grad_norm: 1046.0680 loss: 433.0558 loss_cls: 159.9754 loss_bbox: 129.8852 loss_dfl: 143.1952 2024/03/27 13:44:49 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:44:58 - mmengine - INFO - Epoch(train) [24][750/925] lr: 1.4555e-04 eta: 5:53:20 time: 0.3825 data_time: 0.0021 memory: 5363 grad_norm: 1021.1442 loss: 435.8854 loss_cls: 162.1302 loss_bbox: 129.4970 loss_dfl: 144.2582 2024/03/27 13:45:18 - mmengine - INFO - Epoch(train) [24][800/925] lr: 1.4555e-04 eta: 5:52:59 time: 0.4044 data_time: 0.0020 memory: 5443 grad_norm: 921.9272 loss: 442.3724 loss_cls: 166.2329 loss_bbox: 131.0653 loss_dfl: 145.0741 2024/03/27 13:45:38 - mmengine - INFO - Epoch(train) [24][850/925] lr: 1.4555e-04 eta: 5:52:36 time: 0.3850 data_time: 0.0020 memory: 5496 grad_norm: 946.9432 loss: 433.4158 loss_cls: 161.7819 loss_bbox: 128.2929 loss_dfl: 143.3410 2024/03/27 13:45:57 - mmengine - INFO - Epoch(train) [24][900/925] lr: 1.4555e-04 eta: 5:52:14 time: 0.3902 data_time: 0.0020 memory: 5776 grad_norm: 1054.0807 loss: 449.0541 loss_cls: 169.7931 loss_bbox: 132.5565 loss_dfl: 146.7046 2024/03/27 13:46:06 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:46:31 - mmengine - INFO - Epoch(train) [25][ 50/925] lr: 1.4307e-04 eta: 5:51:49 time: 0.4851 data_time: 0.0713 memory: 5323 grad_norm: 924.1199 loss: 440.7372 loss_cls: 164.3299 loss_bbox: 130.9723 loss_dfl: 145.4350 2024/03/27 13:46:50 - mmengine - INFO - Epoch(train) [25][100/925] lr: 1.4307e-04 eta: 5:51:27 time: 0.3941 data_time: 0.0020 memory: 5390 grad_norm: 919.5703 loss: 439.4738 loss_cls: 164.7123 loss_bbox: 129.8064 loss_dfl: 144.9550 2024/03/27 13:47:09 - mmengine - INFO - Epoch(train) [25][150/925] lr: 1.4307e-04 eta: 5:51:03 time: 0.3797 data_time: 0.0021 memory: 5403 grad_norm: 927.9999 loss: 442.0170 loss_cls: 164.8394 loss_bbox: 131.8599 loss_dfl: 145.3177 2024/03/27 13:47:29 - mmengine - INFO - Epoch(train) [25][200/925] lr: 1.4307e-04 eta: 5:50:41 time: 0.3908 data_time: 0.0023 memory: 5710 grad_norm: 1002.4018 loss: 446.5349 loss_cls: 168.5357 loss_bbox: 132.2238 loss_dfl: 145.7754 2024/03/27 13:47:49 - mmengine - INFO - Epoch(train) [25][250/925] lr: 1.4307e-04 eta: 5:50:20 time: 0.4002 data_time: 0.0021 memory: 5310 grad_norm: 913.0378 loss: 440.4882 loss_cls: 162.9737 loss_bbox: 131.2711 loss_dfl: 146.2434 2024/03/27 13:48:09 - mmengine - INFO - Epoch(train) [25][300/925] lr: 1.4307e-04 eta: 5:49:58 time: 0.3922 data_time: 0.0022 memory: 5336 grad_norm: 937.5173 loss: 436.7255 loss_cls: 163.1968 loss_bbox: 129.3680 loss_dfl: 144.1608 2024/03/27 13:48:28 - mmengine - INFO - Epoch(train) [25][350/925] lr: 1.4307e-04 eta: 5:49:34 time: 0.3829 data_time: 0.0021 memory: 5283 grad_norm: 1062.6565 loss: 442.9040 loss_cls: 166.3075 loss_bbox: 131.8150 loss_dfl: 144.7816 2024/03/27 13:48:48 - mmengine - INFO - Epoch(train) [25][400/925] lr: 1.4307e-04 eta: 5:49:13 time: 0.3995 data_time: 0.0020 memory: 5270 grad_norm: 968.7055 loss: 445.1960 loss_cls: 167.4770 loss_bbox: 131.3417 loss_dfl: 146.3773 2024/03/27 13:49:08 - mmengine - INFO - Epoch(train) [25][450/925] lr: 1.4307e-04 eta: 5:48:52 time: 0.3988 data_time: 0.0022 memory: 5764 grad_norm: 898.2088 loss: 431.5084 loss_cls: 160.8077 loss_bbox: 127.2089 loss_dfl: 143.4918 2024/03/27 13:49:27 - mmengine - INFO - Epoch(train) [25][500/925] lr: 1.4307e-04 eta: 5:48:29 time: 0.3916 data_time: 0.0021 memory: 5350 grad_norm: 957.3497 loss: 437.9274 loss_cls: 162.4027 loss_bbox: 130.6592 loss_dfl: 144.8655 2024/03/27 13:49:48 - mmengine - INFO - Epoch(train) [25][550/925] lr: 1.4307e-04 eta: 5:48:10 time: 0.4141 data_time: 0.0021 memory: 5496 grad_norm: 952.9781 loss: 432.8640 loss_cls: 161.0965 loss_bbox: 128.1862 loss_dfl: 143.5813 2024/03/27 13:50:08 - mmengine - INFO - Epoch(train) [25][600/925] lr: 1.4307e-04 eta: 5:47:48 time: 0.3941 data_time: 0.0022 memory: 5310 grad_norm: 1066.1570 loss: 435.0134 loss_cls: 161.2219 loss_bbox: 130.6530 loss_dfl: 143.1385 2024/03/27 13:50:27 - mmengine - INFO - Epoch(train) [25][650/925] lr: 1.4307e-04 eta: 5:47:26 time: 0.3918 data_time: 0.0022 memory: 5256 grad_norm: 935.9940 loss: 436.8806 loss_cls: 161.5184 loss_bbox: 130.5611 loss_dfl: 144.8011 2024/03/27 13:50:49 - mmengine - INFO - Epoch(train) [25][700/925] lr: 1.4307e-04 eta: 5:47:07 time: 0.4239 data_time: 0.0020 memory: 5403 grad_norm: 1040.6887 loss: 435.4451 loss_cls: 161.3535 loss_bbox: 129.3217 loss_dfl: 144.7699 2024/03/27 13:51:08 - mmengine - INFO - Epoch(train) [25][750/925] lr: 1.4307e-04 eta: 5:46:46 time: 0.3985 data_time: 0.0021 memory: 5296 grad_norm: 1109.8922 loss: 437.8063 loss_cls: 162.9662 loss_bbox: 130.5104 loss_dfl: 144.3296 2024/03/27 13:51:28 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:51:28 - mmengine - INFO - Epoch(train) [25][800/925] lr: 1.4307e-04 eta: 5:46:24 time: 0.3998 data_time: 0.0021 memory: 5736 grad_norm: 907.8451 loss: 439.6748 loss_cls: 161.9646 loss_bbox: 132.0824 loss_dfl: 145.6277 2024/03/27 13:51:48 - mmengine - INFO - Epoch(train) [25][850/925] lr: 1.4307e-04 eta: 5:46:03 time: 0.3984 data_time: 0.0021 memory: 5150 grad_norm: 924.9530 loss: 439.1764 loss_cls: 163.9368 loss_bbox: 130.0613 loss_dfl: 145.1784 2024/03/27 13:52:09 - mmengine - INFO - Epoch(train) [25][900/925] lr: 1.4307e-04 eta: 5:45:42 time: 0.4039 data_time: 0.0024 memory: 5456 grad_norm: 900.3780 loss: 436.6325 loss_cls: 161.3804 loss_bbox: 130.6933 loss_dfl: 144.5588 2024/03/27 13:52:18 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 13:52:18 - mmengine - INFO - Saving checkpoint at 25 epochs 2024/03/27 13:52:26 - mmengine - INFO - Epoch(val) [25][ 50/625] eta: 0:00:25 time: 0.0442 data_time: 0.0009 memory: 5363 2024/03/27 13:52:28 - mmengine - INFO - Epoch(val) [25][100/625] eta: 0:00:23 time: 0.0440 data_time: 0.0004 memory: 838 2024/03/27 13:52:31 - mmengine - INFO - Epoch(val) [25][150/625] eta: 0:00:20 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 13:52:33 - mmengine - INFO - Epoch(val) [25][200/625] eta: 0:00:18 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 13:52:35 - mmengine - INFO - Epoch(val) [25][250/625] eta: 0:00:16 time: 0.0435 data_time: 0.0004 memory: 838 2024/03/27 13:52:37 - mmengine - INFO - Epoch(val) [25][300/625] eta: 0:00:14 time: 0.0430 data_time: 0.0004 memory: 838 2024/03/27 13:52:39 - mmengine - INFO - Epoch(val) [25][350/625] eta: 0:00:12 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 13:52:41 - mmengine - INFO - Epoch(val) [25][400/625] eta: 0:00:09 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 13:52:44 - mmengine - INFO - Epoch(val) [25][450/625] eta: 0:00:07 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 13:52:46 - mmengine - INFO - Epoch(val) [25][500/625] eta: 0:00:05 time: 0.0435 data_time: 0.0004 memory: 838 2024/03/27 13:52:48 - mmengine - INFO - Epoch(val) [25][550/625] eta: 0:00:03 time: 0.0401 data_time: 0.0003 memory: 838 2024/03/27 13:52:50 - mmengine - INFO - Epoch(val) [25][600/625] eta: 0:00:01 time: 0.0351 data_time: 0.0003 memory: 838 2024/03/27 13:53:05 - mmengine - INFO - Evaluating bbox... 2024/03/27 13:54:28 - mmengine - INFO - bbox_mAP_copypaste: 0.445 0.607 0.486 0.251 0.493 0.594 2024/03/27 13:54:30 - mmengine - INFO - Epoch(val) [25][625/625] coco/bbox_mAP: 0.4450 coco/bbox_mAP_50: 0.6070 coco/bbox_mAP_75: 0.4860 coco/bbox_mAP_s: 0.2510 coco/bbox_mAP_m: 0.4930 coco/bbox_mAP_l: 0.5940 data_time: 0.0003 time: 0.0346 2024/03/27 13:54:53 - mmengine - INFO - Epoch(train) [26][ 50/925] lr: 1.4060e-04 eta: 5:45:15 time: 0.4627 data_time: 0.0575 memory: 5296 grad_norm: 1057.8389 loss: 439.1553 loss_cls: 163.1500 loss_bbox: 130.6668 loss_dfl: 145.3384 2024/03/27 13:55:12 - mmengine - INFO - Epoch(train) [26][100/925] lr: 1.4060e-04 eta: 5:44:52 time: 0.3805 data_time: 0.0022 memory: 5336 grad_norm: 1006.2093 loss: 432.2127 loss_cls: 159.6344 loss_bbox: 128.5662 loss_dfl: 144.0121 2024/03/27 13:55:31 - mmengine - INFO - Epoch(train) [26][150/925] lr: 1.4060e-04 eta: 5:44:29 time: 0.3887 data_time: 0.0020 memory: 5456 grad_norm: 916.7619 loss: 436.2832 loss_cls: 161.9830 loss_bbox: 130.5566 loss_dfl: 143.7436 2024/03/27 13:55:50 - mmengine - INFO - Epoch(train) [26][200/925] lr: 1.4060e-04 eta: 5:44:06 time: 0.3833 data_time: 0.0020 memory: 5590 grad_norm: 1002.9916 loss: 438.4500 loss_cls: 162.7568 loss_bbox: 131.5516 loss_dfl: 144.1416 2024/03/27 13:56:10 - mmengine - INFO - Epoch(train) [26][250/925] lr: 1.4060e-04 eta: 5:43:44 time: 0.3875 data_time: 0.0020 memory: 5416 grad_norm: 966.8323 loss: 443.6548 loss_cls: 165.8574 loss_bbox: 132.8717 loss_dfl: 144.9257 2024/03/27 13:56:29 - mmengine - INFO - Epoch(train) [26][300/925] lr: 1.4060e-04 eta: 5:43:22 time: 0.3911 data_time: 0.0024 memory: 5496 grad_norm: 955.6698 loss: 446.3274 loss_cls: 165.4386 loss_bbox: 134.5606 loss_dfl: 146.3283 2024/03/27 13:56:50 - mmengine - INFO - Epoch(train) [26][350/925] lr: 1.4060e-04 eta: 5:43:01 time: 0.4024 data_time: 0.0020 memory: 5310 grad_norm: 894.9138 loss: 436.4895 loss_cls: 163.8881 loss_bbox: 128.9863 loss_dfl: 143.6152 2024/03/27 13:57:09 - mmengine - INFO - Epoch(train) [26][400/925] lr: 1.4060e-04 eta: 5:42:39 time: 0.3963 data_time: 0.0019 memory: 5456 grad_norm: 1012.8344 loss: 434.1442 loss_cls: 160.1422 loss_bbox: 129.7479 loss_dfl: 144.2540 2024/03/27 13:57:30 - mmengine - INFO - Epoch(train) [26][450/925] lr: 1.4060e-04 eta: 5:42:19 time: 0.4057 data_time: 0.0020 memory: 5350 grad_norm: 995.9795 loss: 437.6348 loss_cls: 161.2990 loss_bbox: 130.6227 loss_dfl: 145.7131 2024/03/27 13:57:49 - mmengine - INFO - Epoch(train) [26][500/925] lr: 1.4060e-04 eta: 5:41:56 time: 0.3854 data_time: 0.0021 memory: 5776 grad_norm: 862.2378 loss: 441.0051 loss_cls: 164.9999 loss_bbox: 130.5194 loss_dfl: 145.4858 2024/03/27 13:58:10 - mmengine - INFO - Epoch(train) [26][550/925] lr: 1.4060e-04 eta: 5:41:36 time: 0.4163 data_time: 0.0021 memory: 5310 grad_norm: 930.3747 loss: 439.9927 loss_cls: 162.3912 loss_bbox: 133.2804 loss_dfl: 144.3211 2024/03/27 13:58:30 - mmengine - INFO - Epoch(train) [26][600/925] lr: 1.4060e-04 eta: 5:41:16 time: 0.4067 data_time: 0.0019 memory: 5523 grad_norm: 990.4403 loss: 436.9662 loss_cls: 162.1518 loss_bbox: 130.5509 loss_dfl: 144.2635 2024/03/27 13:58:50 - mmengine - INFO - Epoch(train) [26][650/925] lr: 1.4060e-04 eta: 5:40:55 time: 0.4006 data_time: 0.0021 memory: 5363 grad_norm: 895.5133 loss: 443.8664 loss_cls: 166.6106 loss_bbox: 131.4673 loss_dfl: 145.7885 2024/03/27 13:59:10 - mmengine - INFO - Epoch(train) [26][700/925] lr: 1.4060e-04 eta: 5:40:33 time: 0.3937 data_time: 0.0019 memory: 5456 grad_norm: 1023.9319 loss: 434.8716 loss_cls: 162.2062 loss_bbox: 129.0478 loss_dfl: 143.6176 2024/03/27 13:59:30 - mmengine - INFO - Epoch(train) [26][750/925] lr: 1.4060e-04 eta: 5:40:13 time: 0.4068 data_time: 0.0021 memory: 5376 grad_norm: 884.0550 loss: 429.8379 loss_cls: 156.3662 loss_bbox: 129.8485 loss_dfl: 143.6233 2024/03/27 13:59:50 - mmengine - INFO - Epoch(train) [26][800/925] lr: 1.4060e-04 eta: 5:39:51 time: 0.3936 data_time: 0.0020 memory: 5310 grad_norm: 950.8876 loss: 433.7646 loss_cls: 161.7464 loss_bbox: 128.1538 loss_dfl: 143.8645 2024/03/27 14:00:10 - mmengine - INFO - Epoch(train) [26][850/925] lr: 1.4060e-04 eta: 5:39:30 time: 0.3991 data_time: 0.0019 memory: 5190 grad_norm: 967.4864 loss: 438.1062 loss_cls: 162.4978 loss_bbox: 130.9562 loss_dfl: 144.6523 2024/03/27 14:00:20 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:00:30 - mmengine - INFO - Epoch(train) [26][900/925] lr: 1.4060e-04 eta: 5:39:08 time: 0.3928 data_time: 0.0020 memory: 5550 grad_norm: 986.3752 loss: 439.9341 loss_cls: 165.4057 loss_bbox: 129.7288 loss_dfl: 144.7997 2024/03/27 14:00:39 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:01:03 - mmengine - INFO - Epoch(train) [27][ 50/925] lr: 1.3813e-04 eta: 5:38:42 time: 0.4686 data_time: 0.0610 memory: 5470 grad_norm: 1083.4054 loss: 431.1885 loss_cls: 158.4800 loss_bbox: 129.1563 loss_dfl: 143.5522 2024/03/27 14:01:23 - mmengine - INFO - Epoch(train) [27][100/925] lr: 1.3813e-04 eta: 5:38:20 time: 0.3984 data_time: 0.0020 memory: 5416 grad_norm: 947.7678 loss: 440.3601 loss_cls: 164.5289 loss_bbox: 130.1285 loss_dfl: 145.7027 2024/03/27 14:01:43 - mmengine - INFO - Epoch(train) [27][150/925] lr: 1.3813e-04 eta: 5:37:59 time: 0.4003 data_time: 0.0019 memory: 5336 grad_norm: 1000.2844 loss: 444.7354 loss_cls: 165.9103 loss_bbox: 133.0990 loss_dfl: 145.7262 2024/03/27 14:02:03 - mmengine - INFO - Epoch(train) [27][200/925] lr: 1.3813e-04 eta: 5:37:39 time: 0.4050 data_time: 0.0021 memory: 5496 grad_norm: 933.3898 loss: 439.2551 loss_cls: 164.3163 loss_bbox: 130.2558 loss_dfl: 144.6831 2024/03/27 14:02:23 - mmengine - INFO - Epoch(train) [27][250/925] lr: 1.3813e-04 eta: 5:37:18 time: 0.4053 data_time: 0.0021 memory: 5510 grad_norm: 966.6825 loss: 432.9451 loss_cls: 159.3418 loss_bbox: 129.7192 loss_dfl: 143.8841 2024/03/27 14:02:43 - mmengine - INFO - Epoch(train) [27][300/925] lr: 1.3813e-04 eta: 5:36:57 time: 0.3947 data_time: 0.0019 memory: 5496 grad_norm: 832.7528 loss: 435.2144 loss_cls: 160.6088 loss_bbox: 130.6629 loss_dfl: 143.9427 2024/03/27 14:03:04 - mmengine - INFO - Epoch(train) [27][350/925] lr: 1.3813e-04 eta: 5:36:36 time: 0.4094 data_time: 0.0020 memory: 5416 grad_norm: 977.7030 loss: 435.3467 loss_cls: 163.3430 loss_bbox: 128.7607 loss_dfl: 143.2430 2024/03/27 14:03:23 - mmengine - INFO - Epoch(train) [27][400/925] lr: 1.3813e-04 eta: 5:36:15 time: 0.3958 data_time: 0.0022 memory: 5403 grad_norm: 926.0117 loss: 431.0069 loss_cls: 159.7706 loss_bbox: 128.2056 loss_dfl: 143.0308 2024/03/27 14:03:43 - mmengine - INFO - Epoch(train) [27][450/925] lr: 1.3813e-04 eta: 5:35:53 time: 0.3926 data_time: 0.0020 memory: 5443 grad_norm: 1001.2355 loss: 441.5744 loss_cls: 163.9512 loss_bbox: 132.3772 loss_dfl: 145.2460 2024/03/27 14:04:03 - mmengine - INFO - Epoch(train) [27][500/925] lr: 1.3813e-04 eta: 5:35:32 time: 0.3964 data_time: 0.0021 memory: 5456 grad_norm: 1042.5236 loss: 438.4926 loss_cls: 164.9842 loss_bbox: 129.4447 loss_dfl: 144.0638 2024/03/27 14:04:22 - mmengine - INFO - Epoch(train) [27][550/925] lr: 1.3813e-04 eta: 5:35:09 time: 0.3876 data_time: 0.0021 memory: 5403 grad_norm: 1029.7367 loss: 441.3639 loss_cls: 164.1791 loss_bbox: 131.6234 loss_dfl: 145.5614 2024/03/27 14:04:42 - mmengine - INFO - Epoch(train) [27][600/925] lr: 1.3813e-04 eta: 5:34:48 time: 0.3966 data_time: 0.0020 memory: 5296 grad_norm: 875.3494 loss: 441.0890 loss_cls: 163.6440 loss_bbox: 132.2617 loss_dfl: 145.1834 2024/03/27 14:05:02 - mmengine - INFO - Epoch(train) [27][650/925] lr: 1.3813e-04 eta: 5:34:25 time: 0.3858 data_time: 0.0020 memory: 5616 grad_norm: 968.7747 loss: 436.9460 loss_cls: 161.9110 loss_bbox: 130.1825 loss_dfl: 144.8525 2024/03/27 14:05:21 - mmengine - INFO - Epoch(train) [27][700/925] lr: 1.3813e-04 eta: 5:34:04 time: 0.3973 data_time: 0.0019 memory: 5203 grad_norm: 996.3708 loss: 439.2915 loss_cls: 164.5942 loss_bbox: 129.5699 loss_dfl: 145.1274 2024/03/27 14:05:42 - mmengine - INFO - Epoch(train) [27][750/925] lr: 1.3813e-04 eta: 5:33:44 time: 0.4055 data_time: 0.0021 memory: 5830 grad_norm: 930.7276 loss: 434.3476 loss_cls: 160.1051 loss_bbox: 130.0077 loss_dfl: 144.2348 2024/03/27 14:06:01 - mmengine - INFO - Epoch(train) [27][800/925] lr: 1.3813e-04 eta: 5:33:22 time: 0.3922 data_time: 0.0021 memory: 5496 grad_norm: 924.2177 loss: 425.0922 loss_cls: 154.3940 loss_bbox: 127.6979 loss_dfl: 143.0003 2024/03/27 14:06:22 - mmengine - INFO - Epoch(train) [27][850/925] lr: 1.3813e-04 eta: 5:33:02 time: 0.4123 data_time: 0.0021 memory: 5310 grad_norm: 906.7534 loss: 433.8780 loss_cls: 159.2991 loss_bbox: 130.2689 loss_dfl: 144.3099 2024/03/27 14:06:42 - mmengine - INFO - Epoch(train) [27][900/925] lr: 1.3813e-04 eta: 5:32:40 time: 0.3927 data_time: 0.0020 memory: 5470 grad_norm: 881.5279 loss: 437.3857 loss_cls: 161.8432 loss_bbox: 130.0721 loss_dfl: 145.4705 2024/03/27 14:06:51 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:07:05 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:07:15 - mmengine - INFO - Epoch(train) [28][ 50/925] lr: 1.3565e-04 eta: 5:32:15 time: 0.4866 data_time: 0.0616 memory: 5403 grad_norm: 907.3568 loss: 436.0616 loss_cls: 161.3690 loss_bbox: 129.7470 loss_dfl: 144.9456 2024/03/27 14:07:35 - mmengine - INFO - Epoch(train) [28][100/925] lr: 1.3565e-04 eta: 5:31:54 time: 0.3961 data_time: 0.0020 memory: 5643 grad_norm: 943.7740 loss: 438.6499 loss_cls: 164.1811 loss_bbox: 129.6304 loss_dfl: 144.8383 2024/03/27 14:07:55 - mmengine - INFO - Epoch(train) [28][150/925] lr: 1.3565e-04 eta: 5:31:32 time: 0.3946 data_time: 0.0021 memory: 5110 grad_norm: 971.1527 loss: 431.7378 loss_cls: 158.9353 loss_bbox: 128.9143 loss_dfl: 143.8882 2024/03/27 14:08:15 - mmengine - INFO - Epoch(train) [28][200/925] lr: 1.3565e-04 eta: 5:31:11 time: 0.3977 data_time: 0.0020 memory: 5536 grad_norm: inf loss: 440.3354 loss_cls: 162.0527 loss_bbox: 132.8043 loss_dfl: 145.4783 2024/03/27 14:08:35 - mmengine - INFO - Epoch(train) [28][250/925] lr: 1.3565e-04 eta: 5:30:50 time: 0.4024 data_time: 0.0022 memory: 5230 grad_norm: 900.8169 loss: 440.0217 loss_cls: 164.2163 loss_bbox: 130.6678 loss_dfl: 145.1376 2024/03/27 14:08:54 - mmengine - INFO - Epoch(train) [28][300/925] lr: 1.3565e-04 eta: 5:30:28 time: 0.3851 data_time: 0.0021 memory: 5176 grad_norm: 873.0258 loss: 433.5239 loss_cls: 160.1286 loss_bbox: 129.6042 loss_dfl: 143.7911 2024/03/27 14:09:14 - mmengine - INFO - Epoch(train) [28][350/925] lr: 1.3565e-04 eta: 5:30:07 time: 0.3973 data_time: 0.0021 memory: 5683 grad_norm: 857.9730 loss: 437.1525 loss_cls: 163.0137 loss_bbox: 129.4189 loss_dfl: 144.7199 2024/03/27 14:09:35 - mmengine - INFO - Epoch(train) [28][400/925] lr: 1.3565e-04 eta: 5:29:46 time: 0.4048 data_time: 0.0021 memory: 5523 grad_norm: 944.0242 loss: 441.4900 loss_cls: 166.5571 loss_bbox: 130.0405 loss_dfl: 144.8924 2024/03/27 14:09:54 - mmengine - INFO - Epoch(train) [28][450/925] lr: 1.3565e-04 eta: 5:29:25 time: 0.3952 data_time: 0.0021 memory: 5670 grad_norm: 952.1924 loss: 430.3585 loss_cls: 160.3540 loss_bbox: 127.5194 loss_dfl: 142.4852 2024/03/27 14:10:15 - mmengine - INFO - Epoch(train) [28][500/925] lr: 1.3565e-04 eta: 5:29:04 time: 0.4068 data_time: 0.0019 memory: 5416 grad_norm: 977.1432 loss: 441.9282 loss_cls: 163.9082 loss_bbox: 132.9642 loss_dfl: 145.0559 2024/03/27 14:10:34 - mmengine - INFO - Epoch(train) [28][550/925] lr: 1.3565e-04 eta: 5:28:42 time: 0.3883 data_time: 0.0019 memory: 5283 grad_norm: 973.3654 loss: 434.1052 loss_cls: 160.0463 loss_bbox: 129.6835 loss_dfl: 144.3755 2024/03/27 14:10:54 - mmengine - INFO - Epoch(train) [28][600/925] lr: 1.3565e-04 eta: 5:28:22 time: 0.4054 data_time: 0.0021 memory: 5443 grad_norm: 897.0318 loss: 439.3453 loss_cls: 164.4518 loss_bbox: 130.6225 loss_dfl: 144.2710 2024/03/27 14:11:14 - mmengine - INFO - Epoch(train) [28][650/925] lr: 1.3565e-04 eta: 5:28:00 time: 0.3971 data_time: 0.0020 memory: 5203 grad_norm: 967.8978 loss: 429.2894 loss_cls: 157.4313 loss_bbox: 128.2894 loss_dfl: 143.5686 2024/03/27 14:11:34 - mmengine - INFO - Epoch(train) [28][700/925] lr: 1.3565e-04 eta: 5:27:39 time: 0.3929 data_time: 0.0025 memory: 5416 grad_norm: 941.4597 loss: 436.9148 loss_cls: 161.7657 loss_bbox: 130.4643 loss_dfl: 144.6848 2024/03/27 14:11:54 - mmengine - INFO - Epoch(train) [28][750/925] lr: 1.3565e-04 eta: 5:27:18 time: 0.3990 data_time: 0.0022 memory: 5283 grad_norm: 860.0383 loss: 443.0930 loss_cls: 165.2884 loss_bbox: 132.2988 loss_dfl: 145.5058 2024/03/27 14:12:13 - mmengine - INFO - Epoch(train) [28][800/925] lr: 1.3565e-04 eta: 5:26:55 time: 0.3802 data_time: 0.0019 memory: 5470 grad_norm: 914.5289 loss: 433.7857 loss_cls: 160.2531 loss_bbox: 129.6848 loss_dfl: 143.8477 2024/03/27 14:12:33 - mmengine - INFO - Epoch(train) [28][850/925] lr: 1.3565e-04 eta: 5:26:34 time: 0.4067 data_time: 0.0022 memory: 5310 grad_norm: 899.8405 loss: 440.1451 loss_cls: 164.9931 loss_bbox: 130.5073 loss_dfl: 144.6446 2024/03/27 14:12:53 - mmengine - INFO - Epoch(train) [28][900/925] lr: 1.3565e-04 eta: 5:26:13 time: 0.3916 data_time: 0.0021 memory: 5523 grad_norm: 1079.9043 loss: 436.5783 loss_cls: 161.4085 loss_bbox: 130.5570 loss_dfl: 144.6127 2024/03/27 14:13:02 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:13:27 - mmengine - INFO - Epoch(train) [29][ 50/925] lr: 1.3317e-04 eta: 5:25:47 time: 0.4828 data_time: 0.0668 memory: 5590 grad_norm: 998.3578 loss: 435.1104 loss_cls: 161.9533 loss_bbox: 128.9953 loss_dfl: 144.1618 2024/03/27 14:13:46 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:13:46 - mmengine - INFO - Epoch(train) [29][100/925] lr: 1.3317e-04 eta: 5:25:25 time: 0.3888 data_time: 0.0021 memory: 5390 grad_norm: 916.9647 loss: 427.3283 loss_cls: 158.4357 loss_bbox: 126.7944 loss_dfl: 142.0982 2024/03/27 14:14:07 - mmengine - INFO - Epoch(train) [29][150/925] lr: 1.3317e-04 eta: 5:25:05 time: 0.4122 data_time: 0.0020 memory: 5843 grad_norm: 1072.2404 loss: 429.0655 loss_cls: 156.9204 loss_bbox: 128.7120 loss_dfl: 143.4331 2024/03/27 14:14:26 - mmengine - INFO - Epoch(train) [29][200/925] lr: 1.3317e-04 eta: 5:24:43 time: 0.3857 data_time: 0.0020 memory: 5656 grad_norm: 1010.2382 loss: 437.8722 loss_cls: 161.6062 loss_bbox: 131.2087 loss_dfl: 145.0573 2024/03/27 14:14:46 - mmengine - INFO - Epoch(train) [29][250/925] lr: 1.3317e-04 eta: 5:24:22 time: 0.4053 data_time: 0.0023 memory: 5630 grad_norm: 930.8637 loss: 439.4853 loss_cls: 162.4153 loss_bbox: 131.6278 loss_dfl: 145.4422 2024/03/27 14:15:06 - mmengine - INFO - Epoch(train) [29][300/925] lr: 1.3317e-04 eta: 5:24:02 time: 0.4034 data_time: 0.0020 memory: 5416 grad_norm: 921.3129 loss: 434.9460 loss_cls: 161.3708 loss_bbox: 129.2796 loss_dfl: 144.2955 2024/03/27 14:15:26 - mmengine - INFO - Epoch(train) [29][350/925] lr: 1.3317e-04 eta: 5:23:40 time: 0.3884 data_time: 0.0021 memory: 5550 grad_norm: 1043.4533 loss: 445.8685 loss_cls: 166.6939 loss_bbox: 132.9046 loss_dfl: 146.2701 2024/03/27 14:15:46 - mmengine - INFO - Epoch(train) [29][400/925] lr: 1.3317e-04 eta: 5:23:19 time: 0.4000 data_time: 0.0020 memory: 5283 grad_norm: 932.1496 loss: 434.2469 loss_cls: 159.7295 loss_bbox: 130.3790 loss_dfl: 144.1383 2024/03/27 14:16:06 - mmengine - INFO - Epoch(train) [29][450/925] lr: 1.3317e-04 eta: 5:22:58 time: 0.4005 data_time: 0.0020 memory: 5310 grad_norm: 899.4158 loss: 439.4560 loss_cls: 164.0791 loss_bbox: 130.1285 loss_dfl: 145.2484 2024/03/27 14:16:26 - mmengine - INFO - Epoch(train) [29][500/925] lr: 1.3317e-04 eta: 5:22:38 time: 0.4111 data_time: 0.0020 memory: 5203 grad_norm: 941.4003 loss: 436.8629 loss_cls: 163.2029 loss_bbox: 128.5574 loss_dfl: 145.1026 2024/03/27 14:16:46 - mmengine - INFO - Epoch(train) [29][550/925] lr: 1.3317e-04 eta: 5:22:17 time: 0.3979 data_time: 0.0019 memory: 5216 grad_norm: 872.9157 loss: 433.0603 loss_cls: 160.4907 loss_bbox: 129.1893 loss_dfl: 143.3803 2024/03/27 14:17:07 - mmengine - INFO - Epoch(train) [29][600/925] lr: 1.3317e-04 eta: 5:21:57 time: 0.4151 data_time: 0.0021 memory: 5350 grad_norm: 901.6218 loss: 429.6414 loss_cls: 159.0154 loss_bbox: 127.5974 loss_dfl: 143.0285 2024/03/27 14:17:27 - mmengine - INFO - Epoch(train) [29][650/925] lr: 1.3317e-04 eta: 5:21:36 time: 0.4019 data_time: 0.0021 memory: 5256 grad_norm: 1100.3895 loss: 440.5800 loss_cls: 164.0211 loss_bbox: 131.8528 loss_dfl: 144.7060 2024/03/27 14:17:48 - mmengine - INFO - Epoch(train) [29][700/925] lr: 1.3317e-04 eta: 5:21:16 time: 0.4048 data_time: 0.0020 memory: 5283 grad_norm: 933.8746 loss: 437.0206 loss_cls: 160.8631 loss_bbox: 131.4134 loss_dfl: 144.7441 2024/03/27 14:18:08 - mmengine - INFO - Epoch(train) [29][750/925] lr: 1.3317e-04 eta: 5:20:56 time: 0.4147 data_time: 0.0020 memory: 5696 grad_norm: 943.4504 loss: 432.6376 loss_cls: 158.7428 loss_bbox: 129.9713 loss_dfl: 143.9235 2024/03/27 14:18:28 - mmengine - INFO - Epoch(train) [29][800/925] lr: 1.3317e-04 eta: 5:20:35 time: 0.3969 data_time: 0.0019 memory: 5270 grad_norm: 1036.9285 loss: 430.9624 loss_cls: 158.2640 loss_bbox: 129.4672 loss_dfl: 143.2312 2024/03/27 14:18:49 - mmengine - INFO - Epoch(train) [29][850/925] lr: 1.3317e-04 eta: 5:20:15 time: 0.4097 data_time: 0.0021 memory: 5656 grad_norm: 895.0539 loss: 439.9830 loss_cls: 163.2147 loss_bbox: 131.2601 loss_dfl: 145.5082 2024/03/27 14:19:09 - mmengine - INFO - Epoch(train) [29][900/925] lr: 1.3317e-04 eta: 5:19:55 time: 0.4093 data_time: 0.0021 memory: 5736 grad_norm: 853.7800 loss: 439.8321 loss_cls: 162.4752 loss_bbox: 133.0509 loss_dfl: 144.3060 2024/03/27 14:19:18 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:19:43 - mmengine - INFO - Epoch(train) [30][ 50/925] lr: 1.3070e-04 eta: 5:19:30 time: 0.4876 data_time: 0.0578 memory: 5523 grad_norm: 975.5901 loss: 424.9335 loss_cls: 155.4234 loss_bbox: 127.3540 loss_dfl: 142.1561 2024/03/27 14:20:03 - mmengine - INFO - Epoch(train) [30][100/925] lr: 1.3070e-04 eta: 5:19:09 time: 0.3984 data_time: 0.0020 memory: 5416 grad_norm: 1112.6361 loss: 433.8353 loss_cls: 159.8136 loss_bbox: 130.1094 loss_dfl: 143.9123 2024/03/27 14:20:24 - mmengine - INFO - Epoch(train) [30][150/925] lr: 1.3070e-04 eta: 5:18:49 time: 0.4079 data_time: 0.0022 memory: 5536 grad_norm: 910.1567 loss: 435.3161 loss_cls: 161.9884 loss_bbox: 129.4084 loss_dfl: 143.9193 2024/03/27 14:20:34 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:20:44 - mmengine - INFO - Epoch(train) [30][200/925] lr: 1.3070e-04 eta: 5:18:28 time: 0.4034 data_time: 0.0020 memory: 5536 grad_norm: 872.8036 loss: 434.3571 loss_cls: 159.6495 loss_bbox: 130.9203 loss_dfl: 143.7872 2024/03/27 14:21:04 - mmengine - INFO - Epoch(train) [30][250/925] lr: 1.3070e-04 eta: 5:18:07 time: 0.4042 data_time: 0.0019 memory: 5350 grad_norm: 938.5408 loss: 429.1005 loss_cls: 158.8469 loss_bbox: 126.8443 loss_dfl: 143.4093 2024/03/27 14:21:24 - mmengine - INFO - Epoch(train) [30][300/925] lr: 1.3070e-04 eta: 5:17:47 time: 0.4028 data_time: 0.0020 memory: 5550 grad_norm: 1017.0927 loss: 431.5957 loss_cls: 158.2178 loss_bbox: 129.8535 loss_dfl: 143.5244 2024/03/27 14:21:44 - mmengine - INFO - Epoch(train) [30][350/925] lr: 1.3070e-04 eta: 5:17:26 time: 0.4033 data_time: 0.0021 memory: 5323 grad_norm: 1011.3484 loss: 433.5974 loss_cls: 159.7357 loss_bbox: 129.9611 loss_dfl: 143.9006 2024/03/27 14:22:05 - mmengine - INFO - Epoch(train) [30][400/925] lr: 1.3070e-04 eta: 5:17:06 time: 0.4116 data_time: 0.0020 memory: 5270 grad_norm: inf loss: 439.3494 loss_cls: 164.6344 loss_bbox: 130.0974 loss_dfl: 144.6176 2024/03/27 14:22:25 - mmengine - INFO - Epoch(train) [30][450/925] lr: 1.3070e-04 eta: 5:16:46 time: 0.4072 data_time: 0.0020 memory: 5536 grad_norm: 941.5476 loss: 437.2761 loss_cls: 162.6626 loss_bbox: 130.2925 loss_dfl: 144.3210 2024/03/27 14:22:46 - mmengine - INFO - Epoch(train) [30][500/925] lr: 1.3070e-04 eta: 5:16:25 time: 0.4033 data_time: 0.0020 memory: 5390 grad_norm: 1055.5791 loss: 432.3473 loss_cls: 158.8837 loss_bbox: 130.4964 loss_dfl: 142.9672 2024/03/27 14:23:06 - mmengine - INFO - Epoch(train) [30][550/925] lr: 1.3070e-04 eta: 5:16:05 time: 0.4123 data_time: 0.0021 memory: 5363 grad_norm: 863.2405 loss: 434.6664 loss_cls: 161.6666 loss_bbox: 128.6996 loss_dfl: 144.3003 2024/03/27 14:23:27 - mmengine - INFO - Epoch(train) [30][600/925] lr: 1.3070e-04 eta: 5:15:45 time: 0.4080 data_time: 0.0021 memory: 5563 grad_norm: 933.6967 loss: 427.8751 loss_cls: 157.0412 loss_bbox: 128.0108 loss_dfl: 142.8231 2024/03/27 14:23:47 - mmengine - INFO - Epoch(train) [30][650/925] lr: 1.3070e-04 eta: 5:15:25 time: 0.4104 data_time: 0.0019 memory: 5363 grad_norm: 912.2096 loss: 431.8400 loss_cls: 158.3516 loss_bbox: 130.1357 loss_dfl: 143.3526 2024/03/27 14:24:08 - mmengine - INFO - Epoch(train) [30][700/925] lr: 1.3070e-04 eta: 5:15:05 time: 0.4085 data_time: 0.0022 memory: 5336 grad_norm: 975.3795 loss: 434.9353 loss_cls: 159.1156 loss_bbox: 131.2934 loss_dfl: 144.5263 2024/03/27 14:24:28 - mmengine - INFO - Epoch(train) [30][750/925] lr: 1.3070e-04 eta: 5:14:45 time: 0.4088 data_time: 0.0021 memory: 5776 grad_norm: 1008.9270 loss: 432.3287 loss_cls: 158.7491 loss_bbox: 129.3210 loss_dfl: 144.2586 2024/03/27 14:24:49 - mmengine - INFO - Epoch(train) [30][800/925] lr: 1.3070e-04 eta: 5:14:25 time: 0.4185 data_time: 0.0021 memory: 5336 grad_norm: 970.1807 loss: 430.8134 loss_cls: 158.1018 loss_bbox: 129.1665 loss_dfl: 143.5451 2024/03/27 14:25:09 - mmengine - INFO - Epoch(train) [30][850/925] lr: 1.3070e-04 eta: 5:14:04 time: 0.3958 data_time: 0.0023 memory: 5283 grad_norm: 980.3847 loss: 424.5875 loss_cls: 155.1970 loss_bbox: 127.2744 loss_dfl: 142.1161 2024/03/27 14:25:29 - mmengine - INFO - Epoch(train) [30][900/925] lr: 1.3070e-04 eta: 5:13:43 time: 0.3959 data_time: 0.0020 memory: 5363 grad_norm: 916.4641 loss: 435.1506 loss_cls: 159.9080 loss_bbox: 130.9659 loss_dfl: 144.2768 2024/03/27 14:25:38 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:25:38 - mmengine - INFO - Saving checkpoint at 30 epochs 2024/03/27 14:25:47 - mmengine - INFO - Epoch(val) [30][ 50/625] eta: 0:00:25 time: 0.0447 data_time: 0.0009 memory: 5283 2024/03/27 14:25:49 - mmengine - INFO - Epoch(val) [30][100/625] eta: 0:00:23 time: 0.0451 data_time: 0.0004 memory: 838 2024/03/27 14:25:51 - mmengine - INFO - Epoch(val) [30][150/625] eta: 0:00:21 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 14:25:53 - mmengine - INFO - Epoch(val) [30][200/625] eta: 0:00:18 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 14:25:56 - mmengine - INFO - Epoch(val) [30][250/625] eta: 0:00:16 time: 0.0442 data_time: 0.0004 memory: 838 2024/03/27 14:25:58 - mmengine - INFO - Epoch(val) [30][300/625] eta: 0:00:14 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 14:26:00 - mmengine - INFO - Epoch(val) [30][350/625] eta: 0:00:12 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 14:26:02 - mmengine - INFO - Epoch(val) [30][400/625] eta: 0:00:09 time: 0.0435 data_time: 0.0004 memory: 838 2024/03/27 14:26:04 - mmengine - INFO - Epoch(val) [30][450/625] eta: 0:00:07 time: 0.0455 data_time: 0.0004 memory: 838 2024/03/27 14:26:06 - mmengine - INFO - Epoch(val) [30][500/625] eta: 0:00:05 time: 0.0396 data_time: 0.0003 memory: 838 2024/03/27 14:26:08 - mmengine - INFO - Epoch(val) [30][550/625] eta: 0:00:03 time: 0.0349 data_time: 0.0003 memory: 838 2024/03/27 14:26:10 - mmengine - INFO - Epoch(val) [30][600/625] eta: 0:00:01 time: 0.0340 data_time: 0.0003 memory: 838 2024/03/27 14:26:26 - mmengine - INFO - Evaluating bbox... 2024/03/27 14:27:56 - mmengine - INFO - bbox_mAP_copypaste: 0.447 0.610 0.488 0.253 0.497 0.600 2024/03/27 14:27:58 - mmengine - INFO - Epoch(val) [30][625/625] coco/bbox_mAP: 0.4470 coco/bbox_mAP_50: 0.6100 coco/bbox_mAP_75: 0.4880 coco/bbox_mAP_s: 0.2530 coco/bbox_mAP_m: 0.4970 coco/bbox_mAP_l: 0.6000 data_time: 0.0003 time: 0.0332 2024/03/27 14:28:22 - mmengine - INFO - Epoch(train) [31][ 50/925] lr: 1.2822e-04 eta: 5:13:16 time: 0.4723 data_time: 0.0840 memory: 5456 grad_norm: 993.1802 loss: 428.6658 loss_cls: 157.6938 loss_bbox: 128.0837 loss_dfl: 142.8882 2024/03/27 14:28:42 - mmengine - INFO - Epoch(train) [31][100/925] lr: 1.2822e-04 eta: 5:12:55 time: 0.3914 data_time: 0.0020 memory: 5456 grad_norm: 999.3444 loss: 430.2037 loss_cls: 158.4625 loss_bbox: 128.1836 loss_dfl: 143.5576 2024/03/27 14:29:01 - mmengine - INFO - Epoch(train) [31][150/925] lr: 1.2822e-04 eta: 5:12:33 time: 0.3943 data_time: 0.0021 memory: 5190 grad_norm: 1031.8118 loss: 433.4376 loss_cls: 160.1167 loss_bbox: 128.6549 loss_dfl: 144.6659 2024/03/27 14:29:22 - mmengine - INFO - Epoch(train) [31][200/925] lr: 1.2822e-04 eta: 5:12:13 time: 0.4104 data_time: 0.0022 memory: 5416 grad_norm: 932.5051 loss: 437.3576 loss_cls: 161.9972 loss_bbox: 130.8008 loss_dfl: 144.5596 2024/03/27 14:29:42 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:29:42 - mmengine - INFO - Epoch(train) [31][250/925] lr: 1.2822e-04 eta: 5:11:52 time: 0.3943 data_time: 0.0020 memory: 5510 grad_norm: 961.4318 loss: 433.4294 loss_cls: 160.1720 loss_bbox: 129.1100 loss_dfl: 144.1474 2024/03/27 14:30:02 - mmengine - INFO - Epoch(train) [31][300/925] lr: 1.2822e-04 eta: 5:11:31 time: 0.4002 data_time: 0.0021 memory: 5230 grad_norm: 935.2440 loss: 429.9775 loss_cls: 157.3870 loss_bbox: 129.2104 loss_dfl: 143.3801 2024/03/27 14:30:22 - mmengine - INFO - Epoch(train) [31][350/925] lr: 1.2822e-04 eta: 5:11:11 time: 0.4109 data_time: 0.0019 memory: 5403 grad_norm: 873.3314 loss: 429.4995 loss_cls: 159.1808 loss_bbox: 126.6923 loss_dfl: 143.6263 2024/03/27 14:30:43 - mmengine - INFO - Epoch(train) [31][400/925] lr: 1.2822e-04 eta: 5:10:51 time: 0.4169 data_time: 0.0022 memory: 5190 grad_norm: 890.7027 loss: 431.6179 loss_cls: 160.2809 loss_bbox: 127.7188 loss_dfl: 143.6183 2024/03/27 14:31:03 - mmengine - INFO - Epoch(train) [31][450/925] lr: 1.2822e-04 eta: 5:10:30 time: 0.3981 data_time: 0.0020 memory: 5483 grad_norm: 889.8980 loss: 432.7183 loss_cls: 160.1405 loss_bbox: 129.2581 loss_dfl: 143.3197 2024/03/27 14:31:23 - mmengine - INFO - Epoch(train) [31][500/925] lr: 1.2822e-04 eta: 5:10:10 time: 0.4067 data_time: 0.0021 memory: 5723 grad_norm: 971.6107 loss: 425.7611 loss_cls: 156.0675 loss_bbox: 127.0060 loss_dfl: 142.6875 2024/03/27 14:31:44 - mmengine - INFO - Epoch(train) [31][550/925] lr: 1.2822e-04 eta: 5:09:50 time: 0.4080 data_time: 0.0020 memory: 5403 grad_norm: 930.0700 loss: 437.8896 loss_cls: 161.6700 loss_bbox: 131.2731 loss_dfl: 144.9466 2024/03/27 14:32:03 - mmengine - INFO - Epoch(train) [31][600/925] lr: 1.2822e-04 eta: 5:09:28 time: 0.3918 data_time: 0.0020 memory: 5523 grad_norm: 929.5507 loss: 431.8273 loss_cls: 160.2635 loss_bbox: 128.3407 loss_dfl: 143.2231 2024/03/27 14:32:23 - mmengine - INFO - Epoch(train) [31][650/925] lr: 1.2822e-04 eta: 5:09:07 time: 0.3947 data_time: 0.0020 memory: 5723 grad_norm: 975.8155 loss: 441.1687 loss_cls: 164.7725 loss_bbox: 131.0517 loss_dfl: 145.3445 2024/03/27 14:32:43 - mmengine - INFO - Epoch(train) [31][700/925] lr: 1.2822e-04 eta: 5:08:47 time: 0.4059 data_time: 0.0021 memory: 5243 grad_norm: 869.5194 loss: 433.0139 loss_cls: 160.3696 loss_bbox: 129.2329 loss_dfl: 143.4115 2024/03/27 14:33:03 - mmengine - INFO - Epoch(train) [31][750/925] lr: 1.2822e-04 eta: 5:08:26 time: 0.3982 data_time: 0.0022 memory: 5216 grad_norm: 1020.0708 loss: 432.4068 loss_cls: 161.3477 loss_bbox: 128.2313 loss_dfl: 142.8278 2024/03/27 14:33:24 - mmengine - INFO - Epoch(train) [31][800/925] lr: 1.2822e-04 eta: 5:08:06 time: 0.4129 data_time: 0.0020 memory: 5630 grad_norm: 837.7324 loss: 435.2114 loss_cls: 161.3101 loss_bbox: 129.9377 loss_dfl: 143.9636 2024/03/27 14:33:44 - mmengine - INFO - Epoch(train) [31][850/925] lr: 1.2822e-04 eta: 5:07:45 time: 0.4056 data_time: 0.0020 memory: 5390 grad_norm: 982.4925 loss: 431.5566 loss_cls: 160.2061 loss_bbox: 127.9192 loss_dfl: 143.4313 2024/03/27 14:34:04 - mmengine - INFO - Epoch(train) [31][900/925] lr: 1.2822e-04 eta: 5:07:24 time: 0.3953 data_time: 0.0020 memory: 5670 grad_norm: 1092.2559 loss: 437.7952 loss_cls: 161.2659 loss_bbox: 131.3846 loss_dfl: 145.1447 2024/03/27 14:34:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:34:38 - mmengine - INFO - Epoch(train) [32][ 50/925] lr: 1.2575e-04 eta: 5:06:57 time: 0.4804 data_time: 0.0575 memory: 5310 grad_norm: 934.9646 loss: 436.1204 loss_cls: 160.1667 loss_bbox: 131.4278 loss_dfl: 144.5258 2024/03/27 14:34:58 - mmengine - INFO - Epoch(train) [32][100/925] lr: 1.2575e-04 eta: 5:06:37 time: 0.4073 data_time: 0.0020 memory: 5403 grad_norm: 914.5544 loss: 434.7424 loss_cls: 161.0912 loss_bbox: 129.9106 loss_dfl: 143.7406 2024/03/27 14:35:18 - mmengine - INFO - Epoch(train) [32][150/925] lr: 1.2575e-04 eta: 5:06:17 time: 0.4058 data_time: 0.0022 memory: 5150 grad_norm: 1009.2836 loss: 429.9175 loss_cls: 158.9957 loss_bbox: 127.4869 loss_dfl: 143.4350 2024/03/27 14:35:38 - mmengine - INFO - Epoch(train) [32][200/925] lr: 1.2575e-04 eta: 5:05:56 time: 0.3998 data_time: 0.0022 memory: 5550 grad_norm: 929.6399 loss: 430.3432 loss_cls: 158.4481 loss_bbox: 128.1230 loss_dfl: 143.7721 2024/03/27 14:35:59 - mmengine - INFO - Epoch(train) [32][250/925] lr: 1.2575e-04 eta: 5:05:35 time: 0.4055 data_time: 0.0020 memory: 5190 grad_norm: 925.8205 loss: 432.4963 loss_cls: 159.0504 loss_bbox: 129.7493 loss_dfl: 143.6966 2024/03/27 14:36:19 - mmengine - INFO - Epoch(train) [32][300/925] lr: 1.2575e-04 eta: 5:05:14 time: 0.3993 data_time: 0.0023 memory: 5296 grad_norm: 1144.1040 loss: 428.6956 loss_cls: 156.4180 loss_bbox: 128.9195 loss_dfl: 143.3581 2024/03/27 14:36:29 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:36:39 - mmengine - INFO - Epoch(train) [32][350/925] lr: 1.2575e-04 eta: 5:04:54 time: 0.4030 data_time: 0.0021 memory: 5350 grad_norm: 943.1599 loss: 431.7941 loss_cls: 159.9900 loss_bbox: 128.2644 loss_dfl: 143.5397 2024/03/27 14:36:59 - mmengine - INFO - Epoch(train) [32][400/925] lr: 1.2575e-04 eta: 5:04:33 time: 0.3952 data_time: 0.0022 memory: 5310 grad_norm: 962.2499 loss: 435.8679 loss_cls: 160.5367 loss_bbox: 131.1251 loss_dfl: 144.2061 2024/03/27 14:37:19 - mmengine - INFO - Epoch(train) [32][450/925] lr: 1.2575e-04 eta: 5:04:12 time: 0.4090 data_time: 0.0022 memory: 5403 grad_norm: 1060.5767 loss: 440.3395 loss_cls: 162.6123 loss_bbox: 132.4170 loss_dfl: 145.3101 2024/03/27 14:37:39 - mmengine - INFO - Epoch(train) [32][500/925] lr: 1.2575e-04 eta: 5:03:52 time: 0.4055 data_time: 0.0020 memory: 5470 grad_norm: 933.9402 loss: 433.4089 loss_cls: 159.8149 loss_bbox: 129.3482 loss_dfl: 144.2458 2024/03/27 14:37:59 - mmengine - INFO - Epoch(train) [32][550/925] lr: 1.2575e-04 eta: 5:03:30 time: 0.3844 data_time: 0.0021 memory: 5430 grad_norm: 891.9043 loss: 433.1330 loss_cls: 159.7882 loss_bbox: 129.0994 loss_dfl: 144.2454 2024/03/27 14:38:20 - mmengine - INFO - Epoch(train) [32][600/925] lr: 1.2575e-04 eta: 5:03:11 time: 0.4187 data_time: 0.0020 memory: 5376 grad_norm: 942.8733 loss: 432.4888 loss_cls: 160.0877 loss_bbox: 128.8578 loss_dfl: 143.5432 2024/03/27 14:38:40 - mmengine - INFO - Epoch(train) [32][650/925] lr: 1.2575e-04 eta: 5:02:50 time: 0.4038 data_time: 0.0021 memory: 5350 grad_norm: 932.1392 loss: 440.0911 loss_cls: 162.1396 loss_bbox: 132.6830 loss_dfl: 145.2685 2024/03/27 14:38:59 - mmengine - INFO - Epoch(train) [32][700/925] lr: 1.2575e-04 eta: 5:02:28 time: 0.3903 data_time: 0.0020 memory: 5270 grad_norm: 1021.2289 loss: 433.7782 loss_cls: 159.3268 loss_bbox: 130.3156 loss_dfl: 144.1358 2024/03/27 14:39:20 - mmengine - INFO - Epoch(train) [32][750/925] lr: 1.2575e-04 eta: 5:02:08 time: 0.4082 data_time: 0.0021 memory: 5230 grad_norm: 907.3508 loss: 434.9029 loss_cls: 160.5676 loss_bbox: 130.5308 loss_dfl: 143.8046 2024/03/27 14:39:40 - mmengine - INFO - Epoch(train) [32][800/925] lr: 1.2575e-04 eta: 5:01:47 time: 0.3957 data_time: 0.0021 memory: 5230 grad_norm: 928.7380 loss: 431.4161 loss_cls: 160.1126 loss_bbox: 127.6653 loss_dfl: 143.6382 2024/03/27 14:40:00 - mmengine - INFO - Epoch(train) [32][850/925] lr: 1.2575e-04 eta: 5:01:26 time: 0.4008 data_time: 0.0020 memory: 5150 grad_norm: 997.9717 loss: 431.9456 loss_cls: 159.3556 loss_bbox: 128.3887 loss_dfl: 144.2014 2024/03/27 14:40:19 - mmengine - INFO - Epoch(train) [32][900/925] lr: 1.2575e-04 eta: 5:01:05 time: 0.3933 data_time: 0.0020 memory: 5430 grad_norm: 998.8653 loss: 423.6306 loss_cls: 156.5827 loss_bbox: 125.3488 loss_dfl: 141.6990 2024/03/27 14:40:29 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:40:53 - mmengine - INFO - Epoch(train) [33][ 50/925] lr: 1.2328e-04 eta: 5:00:39 time: 0.4776 data_time: 0.0700 memory: 5323 grad_norm: 1035.4121 loss: 434.1359 loss_cls: 160.2044 loss_bbox: 129.5253 loss_dfl: 144.4062 2024/03/27 14:41:13 - mmengine - INFO - Epoch(train) [33][100/925] lr: 1.2328e-04 eta: 5:00:18 time: 0.4031 data_time: 0.0020 memory: 5243 grad_norm: 908.8598 loss: 426.2531 loss_cls: 156.8264 loss_bbox: 127.1252 loss_dfl: 142.3015 2024/03/27 14:41:33 - mmengine - INFO - Epoch(train) [33][150/925] lr: 1.2328e-04 eta: 4:59:57 time: 0.3995 data_time: 0.0021 memory: 5443 grad_norm: 822.1167 loss: 431.2861 loss_cls: 158.9497 loss_bbox: 128.9095 loss_dfl: 143.4269 2024/03/27 14:41:53 - mmengine - INFO - Epoch(train) [33][200/925] lr: 1.2328e-04 eta: 4:59:36 time: 0.3931 data_time: 0.0023 memory: 5163 grad_norm: inf loss: 434.5943 loss_cls: 159.3834 loss_bbox: 131.4332 loss_dfl: 143.7777 2024/03/27 14:42:13 - mmengine - INFO - Epoch(train) [33][250/925] lr: 1.2328e-04 eta: 4:59:15 time: 0.4013 data_time: 0.0021 memory: 5296 grad_norm: 968.6953 loss: 428.7508 loss_cls: 157.4976 loss_bbox: 128.5715 loss_dfl: 142.6817 2024/03/27 14:42:32 - mmengine - INFO - Epoch(train) [33][300/925] lr: 1.2328e-04 eta: 4:58:53 time: 0.3802 data_time: 0.0022 memory: 5416 grad_norm: 931.9154 loss: 432.5509 loss_cls: 158.9983 loss_bbox: 129.3220 loss_dfl: 144.2306 2024/03/27 14:42:53 - mmengine - INFO - Epoch(train) [33][350/925] lr: 1.2328e-04 eta: 4:58:33 time: 0.4136 data_time: 0.0021 memory: 5190 grad_norm: 985.3887 loss: 425.9667 loss_cls: 157.3471 loss_bbox: 126.5913 loss_dfl: 142.0282 2024/03/27 14:43:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:43:13 - mmengine - INFO - Epoch(train) [33][400/925] lr: 1.2328e-04 eta: 4:58:13 time: 0.4074 data_time: 0.0023 memory: 5990 grad_norm: 830.7653 loss: 428.0503 loss_cls: 157.2725 loss_bbox: 128.1614 loss_dfl: 142.6163 2024/03/27 14:43:33 - mmengine - INFO - Epoch(train) [33][450/925] lr: 1.2328e-04 eta: 4:57:51 time: 0.3922 data_time: 0.0023 memory: 5790 grad_norm: 897.4069 loss: 431.9029 loss_cls: 159.5307 loss_bbox: 129.5311 loss_dfl: 142.8410 2024/03/27 14:43:54 - mmengine - INFO - Epoch(train) [33][500/925] lr: 1.2328e-04 eta: 4:57:31 time: 0.4120 data_time: 0.0021 memory: 5323 grad_norm: 903.9749 loss: 432.5927 loss_cls: 158.6523 loss_bbox: 129.5754 loss_dfl: 144.3650 2024/03/27 14:44:13 - mmengine - INFO - Epoch(train) [33][550/925] lr: 1.2328e-04 eta: 4:57:09 time: 0.3847 data_time: 0.0021 memory: 5363 grad_norm: 982.9019 loss: 427.9967 loss_cls: 156.4060 loss_bbox: 127.8258 loss_dfl: 143.7650 2024/03/27 14:44:33 - mmengine - INFO - Epoch(train) [33][600/925] lr: 1.2328e-04 eta: 4:56:48 time: 0.3948 data_time: 0.0020 memory: 5523 grad_norm: 877.9391 loss: 435.6736 loss_cls: 160.2739 loss_bbox: 131.4526 loss_dfl: 143.9470 2024/03/27 14:44:52 - mmengine - INFO - Epoch(train) [33][650/925] lr: 1.2328e-04 eta: 4:56:27 time: 0.3947 data_time: 0.0020 memory: 5123 grad_norm: 853.1048 loss: 433.9787 loss_cls: 161.0784 loss_bbox: 128.6231 loss_dfl: 144.2771 2024/03/27 14:45:12 - mmengine - INFO - Epoch(train) [33][700/925] lr: 1.2328e-04 eta: 4:56:06 time: 0.4022 data_time: 0.0021 memory: 5230 grad_norm: 843.9273 loss: 434.9947 loss_cls: 160.4752 loss_bbox: 130.6481 loss_dfl: 143.8714 2024/03/27 14:45:33 - mmengine - INFO - Epoch(train) [33][750/925] lr: 1.2328e-04 eta: 4:55:46 time: 0.4072 data_time: 0.0026 memory: 5190 grad_norm: 885.2957 loss: 427.1482 loss_cls: 157.9600 loss_bbox: 126.0354 loss_dfl: 143.1528 2024/03/27 14:45:53 - mmengine - INFO - Epoch(train) [33][800/925] lr: 1.2328e-04 eta: 4:55:25 time: 0.3962 data_time: 0.0021 memory: 5270 grad_norm: 949.4507 loss: 428.9920 loss_cls: 157.9527 loss_bbox: 128.1919 loss_dfl: 142.8473 2024/03/27 14:46:13 - mmengine - INFO - Epoch(train) [33][850/925] lr: 1.2328e-04 eta: 4:55:04 time: 0.3990 data_time: 0.0020 memory: 5456 grad_norm: 926.8848 loss: 428.5486 loss_cls: 158.5240 loss_bbox: 126.4787 loss_dfl: 143.5460 2024/03/27 14:46:32 - mmengine - INFO - Epoch(train) [33][900/925] lr: 1.2328e-04 eta: 4:54:43 time: 0.3954 data_time: 0.0021 memory: 5256 grad_norm: 919.0164 loss: 430.9265 loss_cls: 158.6122 loss_bbox: 128.9489 loss_dfl: 143.3654 2024/03/27 14:46:41 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:47:05 - mmengine - INFO - Epoch(train) [34][ 50/925] lr: 1.2080e-04 eta: 4:54:15 time: 0.4741 data_time: 0.0645 memory: 5443 grad_norm: 1089.8747 loss: 431.9774 loss_cls: 158.7463 loss_bbox: 130.1086 loss_dfl: 143.1225 2024/03/27 14:47:25 - mmengine - INFO - Epoch(train) [34][100/925] lr: 1.2080e-04 eta: 4:53:54 time: 0.4029 data_time: 0.0021 memory: 5216 grad_norm: 969.5536 loss: 431.7284 loss_cls: 157.8452 loss_bbox: 129.6577 loss_dfl: 144.2255 2024/03/27 14:47:45 - mmengine - INFO - Epoch(train) [34][150/925] lr: 1.2080e-04 eta: 4:53:33 time: 0.3880 data_time: 0.0021 memory: 5230 grad_norm: 970.4238 loss: 435.9099 loss_cls: 162.2896 loss_bbox: 129.1953 loss_dfl: 144.4250 2024/03/27 14:48:04 - mmengine - INFO - Epoch(train) [34][200/925] lr: 1.2080e-04 eta: 4:53:12 time: 0.3971 data_time: 0.0021 memory: 5416 grad_norm: 892.8971 loss: 434.0437 loss_cls: 159.5118 loss_bbox: 130.6104 loss_dfl: 143.9215 2024/03/27 14:48:24 - mmengine - INFO - Epoch(train) [34][250/925] lr: 1.2080e-04 eta: 4:52:51 time: 0.3970 data_time: 0.0020 memory: 5376 grad_norm: 923.0492 loss: 423.6817 loss_cls: 155.3493 loss_bbox: 126.2845 loss_dfl: 142.0478 2024/03/27 14:48:44 - mmengine - INFO - Epoch(train) [34][300/925] lr: 1.2080e-04 eta: 4:52:30 time: 0.3982 data_time: 0.0021 memory: 5363 grad_norm: 814.8893 loss: 429.0345 loss_cls: 156.7386 loss_bbox: 129.0909 loss_dfl: 143.2050 2024/03/27 14:49:04 - mmengine - INFO - Epoch(train) [34][350/925] lr: 1.2080e-04 eta: 4:52:09 time: 0.3985 data_time: 0.0022 memory: 5456 grad_norm: 920.8364 loss: 432.4978 loss_cls: 160.5006 loss_bbox: 129.6635 loss_dfl: 142.3338 2024/03/27 14:49:24 - mmengine - INFO - Epoch(train) [34][400/925] lr: 1.2080e-04 eta: 4:51:48 time: 0.4045 data_time: 0.0020 memory: 5416 grad_norm: 952.9628 loss: 433.1915 loss_cls: 158.7763 loss_bbox: 129.8933 loss_dfl: 144.5220 2024/03/27 14:49:44 - mmengine - INFO - Epoch(train) [34][450/925] lr: 1.2080e-04 eta: 4:51:27 time: 0.3991 data_time: 0.0021 memory: 5630 grad_norm: 983.8705 loss: 424.8342 loss_cls: 154.5118 loss_bbox: 127.7402 loss_dfl: 142.5822 2024/03/27 14:49:55 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:50:05 - mmengine - INFO - Epoch(train) [34][500/925] lr: 1.2080e-04 eta: 4:51:08 time: 0.4181 data_time: 0.0021 memory: 5336 grad_norm: 899.3178 loss: 435.4097 loss_cls: 160.8044 loss_bbox: 131.1576 loss_dfl: 143.4476 2024/03/27 14:50:25 - mmengine - INFO - Epoch(train) [34][550/925] lr: 1.2080e-04 eta: 4:50:47 time: 0.3951 data_time: 0.0021 memory: 5310 grad_norm: 984.8916 loss: 432.9001 loss_cls: 158.8683 loss_bbox: 129.7903 loss_dfl: 144.2415 2024/03/27 14:50:46 - mmengine - INFO - Epoch(train) [34][600/925] lr: 1.2080e-04 eta: 4:50:27 time: 0.4087 data_time: 0.0021 memory: 5443 grad_norm: 900.1949 loss: 429.0529 loss_cls: 157.8308 loss_bbox: 128.0355 loss_dfl: 143.1867 2024/03/27 14:51:06 - mmengine - INFO - Epoch(train) [34][650/925] lr: 1.2080e-04 eta: 4:50:07 time: 0.4087 data_time: 0.0020 memory: 5336 grad_norm: 832.6087 loss: 433.3334 loss_cls: 159.6651 loss_bbox: 129.9621 loss_dfl: 143.7062 2024/03/27 14:51:26 - mmengine - INFO - Epoch(train) [34][700/925] lr: 1.2080e-04 eta: 4:49:45 time: 0.3884 data_time: 0.0021 memory: 5283 grad_norm: 975.5732 loss: 425.0495 loss_cls: 155.3720 loss_bbox: 127.8607 loss_dfl: 141.8168 2024/03/27 14:51:46 - mmengine - INFO - Epoch(train) [34][750/925] lr: 1.2080e-04 eta: 4:49:25 time: 0.4052 data_time: 0.0021 memory: 5656 grad_norm: 941.1658 loss: 429.6143 loss_cls: 158.9876 loss_bbox: 127.7722 loss_dfl: 142.8544 2024/03/27 14:52:06 - mmengine - INFO - Epoch(train) [34][800/925] lr: 1.2080e-04 eta: 4:49:04 time: 0.3990 data_time: 0.0021 memory: 5483 grad_norm: 1407.3695 loss: 432.8420 loss_cls: 159.4916 loss_bbox: 129.5864 loss_dfl: 143.7640 2024/03/27 14:52:26 - mmengine - INFO - Epoch(train) [34][850/925] lr: 1.2080e-04 eta: 4:48:43 time: 0.4061 data_time: 0.0021 memory: 5643 grad_norm: 982.5214 loss: 433.9020 loss_cls: 159.5736 loss_bbox: 129.5015 loss_dfl: 144.8269 2024/03/27 14:52:46 - mmengine - INFO - Epoch(train) [34][900/925] lr: 1.2080e-04 eta: 4:48:22 time: 0.3967 data_time: 0.0022 memory: 5176 grad_norm: 986.5721 loss: 426.8296 loss_cls: 155.9107 loss_bbox: 127.6218 loss_dfl: 143.2970 2024/03/27 14:52:55 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:53:20 - mmengine - INFO - Epoch(train) [35][ 50/925] lr: 1.1833e-04 eta: 4:47:56 time: 0.4842 data_time: 0.0700 memory: 5470 grad_norm: 866.1114 loss: 431.9769 loss_cls: 158.5252 loss_bbox: 130.2992 loss_dfl: 143.1524 2024/03/27 14:53:39 - mmengine - INFO - Epoch(train) [35][100/925] lr: 1.1833e-04 eta: 4:47:35 time: 0.3920 data_time: 0.0021 memory: 5950 grad_norm: 1041.7954 loss: 425.6788 loss_cls: 155.9305 loss_bbox: 126.8436 loss_dfl: 142.9046 2024/03/27 14:53:59 - mmengine - INFO - Epoch(train) [35][150/925] lr: 1.1833e-04 eta: 4:47:14 time: 0.3988 data_time: 0.0023 memory: 5403 grad_norm: 926.5403 loss: 429.7010 loss_cls: 158.7839 loss_bbox: 127.7119 loss_dfl: 143.2052 2024/03/27 14:54:19 - mmengine - INFO - Epoch(train) [35][200/925] lr: 1.1833e-04 eta: 4:46:53 time: 0.3942 data_time: 0.0020 memory: 5323 grad_norm: 895.4407 loss: 432.0854 loss_cls: 160.5182 loss_bbox: 127.9023 loss_dfl: 143.6648 2024/03/27 14:54:39 - mmengine - INFO - Epoch(train) [35][250/925] lr: 1.1833e-04 eta: 4:46:32 time: 0.4035 data_time: 0.0022 memory: 5203 grad_norm: 898.1854 loss: 426.4721 loss_cls: 155.5029 loss_bbox: 127.7121 loss_dfl: 143.2572 2024/03/27 14:54:59 - mmengine - INFO - Epoch(train) [35][300/925] lr: 1.1833e-04 eta: 4:46:11 time: 0.3876 data_time: 0.0020 memory: 5230 grad_norm: 1099.3334 loss: 428.6571 loss_cls: 156.4439 loss_bbox: 129.1974 loss_dfl: 143.0158 2024/03/27 14:55:19 - mmengine - INFO - Epoch(train) [35][350/925] lr: 1.1833e-04 eta: 4:45:50 time: 0.3973 data_time: 0.0021 memory: 5443 grad_norm: 1033.3432 loss: 434.4713 loss_cls: 158.7833 loss_bbox: 130.5387 loss_dfl: 145.1493 2024/03/27 14:55:39 - mmengine - INFO - Epoch(train) [35][400/925] lr: 1.1833e-04 eta: 4:45:29 time: 0.4061 data_time: 0.0021 memory: 5336 grad_norm: 848.0625 loss: 438.0200 loss_cls: 161.4438 loss_bbox: 131.5812 loss_dfl: 144.9950 2024/03/27 14:55:58 - mmengine - INFO - Epoch(train) [35][450/925] lr: 1.1833e-04 eta: 4:45:07 time: 0.3787 data_time: 0.0022 memory: 5590 grad_norm: inf loss: 439.6261 loss_cls: 163.3193 loss_bbox: 131.0490 loss_dfl: 145.2578 2024/03/27 14:56:18 - mmengine - INFO - Epoch(train) [35][500/925] lr: 1.1833e-04 eta: 4:44:46 time: 0.3950 data_time: 0.0021 memory: 5310 grad_norm: 960.7878 loss: 431.6187 loss_cls: 157.9701 loss_bbox: 129.5005 loss_dfl: 144.1481 2024/03/27 14:56:37 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:56:37 - mmengine - INFO - Epoch(train) [35][550/925] lr: 1.1833e-04 eta: 4:44:24 time: 0.3863 data_time: 0.0021 memory: 5243 grad_norm: 829.6205 loss: 419.5731 loss_cls: 152.2475 loss_bbox: 125.7431 loss_dfl: 141.5825 2024/03/27 14:56:57 - mmengine - INFO - Epoch(train) [35][600/925] lr: 1.1833e-04 eta: 4:44:03 time: 0.3974 data_time: 0.0023 memory: 5643 grad_norm: 881.0348 loss: 431.0288 loss_cls: 159.2461 loss_bbox: 128.8831 loss_dfl: 142.8996 2024/03/27 14:57:17 - mmengine - INFO - Epoch(train) [35][650/925] lr: 1.1833e-04 eta: 4:43:43 time: 0.4002 data_time: 0.0021 memory: 5510 grad_norm: 969.9801 loss: 423.0757 loss_cls: 153.4003 loss_bbox: 127.0178 loss_dfl: 142.6576 2024/03/27 14:57:37 - mmengine - INFO - Epoch(train) [35][700/925] lr: 1.1833e-04 eta: 4:43:22 time: 0.4014 data_time: 0.0020 memory: 5390 grad_norm: 875.6374 loss: 429.7512 loss_cls: 156.1759 loss_bbox: 130.0429 loss_dfl: 143.5324 2024/03/27 14:57:58 - mmengine - INFO - Epoch(train) [35][750/925] lr: 1.1833e-04 eta: 4:43:02 time: 0.4079 data_time: 0.0022 memory: 5643 grad_norm: 1140.1711 loss: 432.6594 loss_cls: 159.3013 loss_bbox: 129.1302 loss_dfl: 144.2278 2024/03/27 14:58:17 - mmengine - INFO - Epoch(train) [35][800/925] lr: 1.1833e-04 eta: 4:42:41 time: 0.3909 data_time: 0.0021 memory: 5283 grad_norm: 910.8513 loss: 429.0406 loss_cls: 157.2977 loss_bbox: 129.0725 loss_dfl: 142.6704 2024/03/27 14:58:37 - mmengine - INFO - Epoch(train) [35][850/925] lr: 1.1833e-04 eta: 4:42:20 time: 0.4031 data_time: 0.0021 memory: 5603 grad_norm: 866.3679 loss: 428.6114 loss_cls: 156.8409 loss_bbox: 128.6986 loss_dfl: 143.0718 2024/03/27 14:58:58 - mmengine - INFO - Epoch(train) [35][900/925] lr: 1.1833e-04 eta: 4:42:00 time: 0.4133 data_time: 0.0023 memory: 5430 grad_norm: 1039.7875 loss: 434.0688 loss_cls: 160.1128 loss_bbox: 130.1308 loss_dfl: 143.8251 2024/03/27 14:59:06 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 14:59:07 - mmengine - INFO - Saving checkpoint at 35 epochs 2024/03/27 14:59:15 - mmengine - INFO - Epoch(val) [35][ 50/625] eta: 0:00:25 time: 0.0435 data_time: 0.0009 memory: 5710 2024/03/27 14:59:17 - mmengine - INFO - Epoch(val) [35][100/625] eta: 0:00:22 time: 0.0429 data_time: 0.0006 memory: 838 2024/03/27 14:59:22 - mmengine - INFO - Epoch(val) [35][150/625] eta: 0:00:27 time: 0.0870 data_time: 0.0436 memory: 838 2024/03/27 14:59:24 - mmengine - INFO - Epoch(val) [35][200/625] eta: 0:00:23 time: 0.0437 data_time: 0.0006 memory: 838 2024/03/27 14:59:26 - mmengine - INFO - Epoch(val) [35][250/625] eta: 0:00:19 time: 0.0449 data_time: 0.0004 memory: 838 2024/03/27 14:59:28 - mmengine - INFO - Epoch(val) [35][300/625] eta: 0:00:16 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 14:59:30 - mmengine - INFO - Epoch(val) [35][350/625] eta: 0:00:13 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 14:59:33 - mmengine - INFO - Epoch(val) [35][400/625] eta: 0:00:11 time: 0.0441 data_time: 0.0004 memory: 838 2024/03/27 14:59:35 - mmengine - INFO - Epoch(val) [35][450/625] eta: 0:00:08 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 14:59:37 - mmengine - INFO - Epoch(val) [35][500/625] eta: 0:00:05 time: 0.0403 data_time: 0.0003 memory: 838 2024/03/27 14:59:38 - mmengine - INFO - Epoch(val) [35][550/625] eta: 0:00:03 time: 0.0356 data_time: 0.0003 memory: 838 2024/03/27 14:59:40 - mmengine - INFO - Epoch(val) [35][600/625] eta: 0:00:01 time: 0.0342 data_time: 0.0006 memory: 838 2024/03/27 14:59:55 - mmengine - INFO - Evaluating bbox... 2024/03/27 15:01:15 - mmengine - INFO - bbox_mAP_copypaste: 0.449 0.611 0.491 0.254 0.498 0.603 2024/03/27 15:01:16 - mmengine - INFO - Epoch(val) [35][625/625] coco/bbox_mAP: 0.4490 coco/bbox_mAP_50: 0.6110 coco/bbox_mAP_75: 0.4910 coco/bbox_mAP_s: 0.2540 coco/bbox_mAP_m: 0.4980 coco/bbox_mAP_l: 0.6030 data_time: 0.0012 time: 0.0347 2024/03/27 15:01:41 - mmengine - INFO - Epoch(train) [36][ 50/925] lr: 1.1585e-04 eta: 4:41:34 time: 0.5108 data_time: 0.0998 memory: 5576 grad_norm: 898.0649 loss: 435.8740 loss_cls: 161.9330 loss_bbox: 130.0792 loss_dfl: 143.8617 2024/03/27 15:02:02 - mmengine - INFO - Epoch(train) [36][100/925] lr: 1.1585e-04 eta: 4:41:14 time: 0.4071 data_time: 0.0022 memory: 5496 grad_norm: 889.3167 loss: 427.0074 loss_cls: 155.9579 loss_bbox: 128.3911 loss_dfl: 142.6584 2024/03/27 15:02:22 - mmengine - INFO - Epoch(train) [36][150/925] lr: 1.1585e-04 eta: 4:40:53 time: 0.3966 data_time: 0.0021 memory: 5456 grad_norm: 941.6108 loss: 434.7060 loss_cls: 160.0714 loss_bbox: 130.5229 loss_dfl: 144.1118 2024/03/27 15:02:41 - mmengine - INFO - Epoch(train) [36][200/925] lr: 1.1585e-04 eta: 4:40:32 time: 0.3973 data_time: 0.0024 memory: 5390 grad_norm: 901.6159 loss: 436.4834 loss_cls: 161.6042 loss_bbox: 130.5894 loss_dfl: 144.2898 2024/03/27 15:03:01 - mmengine - INFO - Epoch(train) [36][250/925] lr: 1.1585e-04 eta: 4:40:11 time: 0.3892 data_time: 0.0022 memory: 5643 grad_norm: 956.0594 loss: 425.4601 loss_cls: 154.8133 loss_bbox: 127.9536 loss_dfl: 142.6933 2024/03/27 15:03:20 - mmengine - INFO - Epoch(train) [36][300/925] lr: 1.1585e-04 eta: 4:39:49 time: 0.3879 data_time: 0.0022 memory: 5470 grad_norm: 949.3280 loss: 431.3390 loss_cls: 158.8005 loss_bbox: 128.6174 loss_dfl: 143.9211 2024/03/27 15:03:41 - mmengine - INFO - Epoch(train) [36][350/925] lr: 1.1585e-04 eta: 4:39:29 time: 0.4067 data_time: 0.0023 memory: 5350 grad_norm: 899.8870 loss: 428.9995 loss_cls: 157.4482 loss_bbox: 128.1390 loss_dfl: 143.4122 2024/03/27 15:04:00 - mmengine - INFO - Epoch(train) [36][400/925] lr: 1.1585e-04 eta: 4:39:07 time: 0.3826 data_time: 0.0020 memory: 5310 grad_norm: 1007.9553 loss: 430.3512 loss_cls: 158.3210 loss_bbox: 128.8310 loss_dfl: 143.1992 2024/03/27 15:04:20 - mmengine - INFO - Epoch(train) [36][450/925] lr: 1.1585e-04 eta: 4:38:46 time: 0.3991 data_time: 0.0029 memory: 5764 grad_norm: 885.6564 loss: 433.3633 loss_cls: 159.6319 loss_bbox: 129.9936 loss_dfl: 143.7378 2024/03/27 15:04:39 - mmengine - INFO - Epoch(train) [36][500/925] lr: 1.1585e-04 eta: 4:38:25 time: 0.3856 data_time: 0.0024 memory: 5270 grad_norm: 838.6302 loss: 428.4366 loss_cls: 158.4241 loss_bbox: 126.9574 loss_dfl: 143.0550 2024/03/27 15:04:59 - mmengine - INFO - Epoch(train) [36][550/925] lr: 1.1585e-04 eta: 4:38:03 time: 0.3910 data_time: 0.0022 memory: 5496 grad_norm: 1002.7482 loss: 427.7580 loss_cls: 156.3554 loss_bbox: 128.7835 loss_dfl: 142.6190 2024/03/27 15:05:19 - mmengine - INFO - Epoch(train) [36][600/925] lr: 1.1585e-04 eta: 4:37:43 time: 0.3968 data_time: 0.0021 memory: 5510 grad_norm: 892.1103 loss: 429.6755 loss_cls: 157.3420 loss_bbox: 129.0943 loss_dfl: 143.2391 2024/03/27 15:05:29 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:05:39 - mmengine - INFO - Epoch(train) [36][650/925] lr: 1.1585e-04 eta: 4:37:22 time: 0.4069 data_time: 0.0021 memory: 5470 grad_norm: 919.1284 loss: 432.2448 loss_cls: 159.7048 loss_bbox: 129.1768 loss_dfl: 143.3631 2024/03/27 15:05:59 - mmengine - INFO - Epoch(train) [36][700/925] lr: 1.1585e-04 eta: 4:37:01 time: 0.3976 data_time: 0.0020 memory: 5550 grad_norm: 901.4442 loss: 431.0919 loss_cls: 158.8955 loss_bbox: 129.0123 loss_dfl: 143.1841 2024/03/27 15:06:19 - mmengine - INFO - Epoch(train) [36][750/925] lr: 1.1585e-04 eta: 4:36:41 time: 0.4033 data_time: 0.0022 memory: 5376 grad_norm: 920.5134 loss: 432.3466 loss_cls: 157.9961 loss_bbox: 129.9695 loss_dfl: 144.3811 2024/03/27 15:06:40 - mmengine - INFO - Epoch(train) [36][800/925] lr: 1.1585e-04 eta: 4:36:21 time: 0.4086 data_time: 0.0022 memory: 5323 grad_norm: 887.8825 loss: 428.8698 loss_cls: 158.7987 loss_bbox: 127.0768 loss_dfl: 142.9943 2024/03/27 15:06:59 - mmengine - INFO - Epoch(train) [36][850/925] lr: 1.1585e-04 eta: 4:36:00 time: 0.3934 data_time: 0.0022 memory: 5243 grad_norm: 1033.8803 loss: 432.9925 loss_cls: 159.8371 loss_bbox: 128.9361 loss_dfl: 144.2193 2024/03/27 15:07:20 - mmengine - INFO - Epoch(train) [36][900/925] lr: 1.1585e-04 eta: 4:35:39 time: 0.4052 data_time: 0.0022 memory: 5336 grad_norm: 869.0073 loss: 426.6433 loss_cls: 156.1566 loss_bbox: 128.0595 loss_dfl: 142.4271 2024/03/27 15:07:29 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:07:54 - mmengine - INFO - Epoch(train) [37][ 50/925] lr: 1.1338e-04 eta: 4:35:13 time: 0.4801 data_time: 0.0619 memory: 5296 grad_norm: 881.6414 loss: 432.4181 loss_cls: 158.6711 loss_bbox: 129.6140 loss_dfl: 144.1330 2024/03/27 15:08:14 - mmengine - INFO - Epoch(train) [37][100/925] lr: 1.1338e-04 eta: 4:34:53 time: 0.4130 data_time: 0.0023 memory: 5483 grad_norm: 900.4702 loss: 430.4726 loss_cls: 159.6700 loss_bbox: 128.2750 loss_dfl: 142.5276 2024/03/27 15:08:35 - mmengine - INFO - Epoch(train) [37][150/925] lr: 1.1338e-04 eta: 4:34:33 time: 0.4107 data_time: 0.0021 memory: 5336 grad_norm: 971.6815 loss: 428.0800 loss_cls: 156.2079 loss_bbox: 128.4987 loss_dfl: 143.3735 2024/03/27 15:08:55 - mmengine - INFO - Epoch(train) [37][200/925] lr: 1.1338e-04 eta: 4:34:12 time: 0.3961 data_time: 0.0021 memory: 5590 grad_norm: 835.4741 loss: 425.4096 loss_cls: 155.2632 loss_bbox: 128.0326 loss_dfl: 142.1138 2024/03/27 15:09:14 - mmengine - INFO - Epoch(train) [37][250/925] lr: 1.1338e-04 eta: 4:33:51 time: 0.3953 data_time: 0.0023 memory: 5456 grad_norm: 979.7577 loss: 429.5070 loss_cls: 157.9039 loss_bbox: 128.7329 loss_dfl: 142.8702 2024/03/27 15:09:35 - mmengine - INFO - Epoch(train) [37][300/925] lr: 1.1338e-04 eta: 4:33:30 time: 0.4021 data_time: 0.0020 memory: 5576 grad_norm: 840.4198 loss: 431.3873 loss_cls: 157.4289 loss_bbox: 130.3221 loss_dfl: 143.6362 2024/03/27 15:09:54 - mmengine - INFO - Epoch(train) [37][350/925] lr: 1.1338e-04 eta: 4:33:09 time: 0.3892 data_time: 0.0022 memory: 5310 grad_norm: 951.7560 loss: 427.6940 loss_cls: 155.9926 loss_bbox: 129.3505 loss_dfl: 142.3508 2024/03/27 15:10:14 - mmengine - INFO - Epoch(train) [37][400/925] lr: 1.1338e-04 eta: 4:32:48 time: 0.3974 data_time: 0.0022 memory: 5523 grad_norm: 1011.9981 loss: 425.6277 loss_cls: 155.1808 loss_bbox: 127.6360 loss_dfl: 142.8109 2024/03/27 15:10:34 - mmengine - INFO - Epoch(train) [37][450/925] lr: 1.1338e-04 eta: 4:32:28 time: 0.4019 data_time: 0.0022 memory: 5456 grad_norm: 1033.0954 loss: 425.4667 loss_cls: 155.9799 loss_bbox: 126.6524 loss_dfl: 142.8344 2024/03/27 15:10:54 - mmengine - INFO - Epoch(train) [37][500/925] lr: 1.1338e-04 eta: 4:32:06 time: 0.3909 data_time: 0.0021 memory: 5190 grad_norm: 977.8442 loss: 432.8076 loss_cls: 158.9287 loss_bbox: 130.0471 loss_dfl: 143.8318 2024/03/27 15:11:14 - mmengine - INFO - Epoch(train) [37][550/925] lr: 1.1338e-04 eta: 4:31:46 time: 0.4130 data_time: 0.0020 memory: 6070 grad_norm: 857.0144 loss: 432.2841 loss_cls: 158.0475 loss_bbox: 130.6844 loss_dfl: 143.5522 2024/03/27 15:11:34 - mmengine - INFO - Epoch(train) [37][600/925] lr: 1.1338e-04 eta: 4:31:26 time: 0.3950 data_time: 0.0019 memory: 5350 grad_norm: inf loss: 430.3922 loss_cls: 157.0188 loss_bbox: 130.0476 loss_dfl: 143.3258 2024/03/27 15:11:54 - mmengine - INFO - Epoch(train) [37][650/925] lr: 1.1338e-04 eta: 4:31:05 time: 0.3998 data_time: 0.0026 memory: 5376 grad_norm: 906.2325 loss: 424.9342 loss_cls: 153.8161 loss_bbox: 128.0719 loss_dfl: 143.0463 2024/03/27 15:12:14 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:12:14 - mmengine - INFO - Epoch(train) [37][700/925] lr: 1.1338e-04 eta: 4:30:44 time: 0.3987 data_time: 0.0020 memory: 5336 grad_norm: 935.4029 loss: 434.6081 loss_cls: 159.7429 loss_bbox: 131.0361 loss_dfl: 143.8290 2024/03/27 15:12:35 - mmengine - INFO - Epoch(train) [37][750/925] lr: 1.1338e-04 eta: 4:30:24 time: 0.4089 data_time: 0.0020 memory: 5296 grad_norm: 945.7348 loss: 429.1667 loss_cls: 157.2996 loss_bbox: 129.1747 loss_dfl: 142.6924 2024/03/27 15:12:55 - mmengine - INFO - Epoch(train) [37][800/925] lr: 1.1338e-04 eta: 4:30:04 time: 0.4068 data_time: 0.0026 memory: 5070 grad_norm: 835.2931 loss: 431.5680 loss_cls: 158.6931 loss_bbox: 129.1731 loss_dfl: 143.7018 2024/03/27 15:13:15 - mmengine - INFO - Epoch(train) [37][850/925] lr: 1.1338e-04 eta: 4:29:43 time: 0.3929 data_time: 0.0021 memory: 5136 grad_norm: 882.2222 loss: 435.1105 loss_cls: 160.8206 loss_bbox: 129.2323 loss_dfl: 145.0576 2024/03/27 15:13:35 - mmengine - INFO - Epoch(train) [37][900/925] lr: 1.1338e-04 eta: 4:29:22 time: 0.3975 data_time: 0.0021 memory: 5790 grad_norm: 869.8505 loss: 424.0235 loss_cls: 155.0091 loss_bbox: 126.4573 loss_dfl: 142.5571 2024/03/27 15:13:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:14:08 - mmengine - INFO - Epoch(train) [38][ 50/925] lr: 1.1090e-04 eta: 4:28:54 time: 0.4830 data_time: 0.0631 memory: 5616 grad_norm: 1040.1682 loss: 433.6805 loss_cls: 159.3931 loss_bbox: 130.8916 loss_dfl: 143.3958 2024/03/27 15:14:27 - mmengine - INFO - Epoch(train) [38][100/925] lr: 1.1090e-04 eta: 4:28:33 time: 0.3954 data_time: 0.0021 memory: 5563 grad_norm: 956.4315 loss: 426.5867 loss_cls: 154.3188 loss_bbox: 128.8054 loss_dfl: 143.4625 2024/03/27 15:14:47 - mmengine - INFO - Epoch(train) [38][150/925] lr: 1.1090e-04 eta: 4:28:12 time: 0.4004 data_time: 0.0021 memory: 5310 grad_norm: 939.1428 loss: 434.3023 loss_cls: 159.6316 loss_bbox: 130.2126 loss_dfl: 144.4582 2024/03/27 15:15:08 - mmengine - INFO - Epoch(train) [38][200/925] lr: 1.1090e-04 eta: 4:27:52 time: 0.4141 data_time: 0.0023 memory: 5430 grad_norm: 962.9047 loss: 431.0019 loss_cls: 160.0765 loss_bbox: 128.0973 loss_dfl: 142.8281 2024/03/27 15:15:28 - mmengine - INFO - Epoch(train) [38][250/925] lr: 1.1090e-04 eta: 4:27:32 time: 0.3961 data_time: 0.0022 memory: 5523 grad_norm: 942.7765 loss: 425.0720 loss_cls: 154.5717 loss_bbox: 128.0545 loss_dfl: 142.4458 2024/03/27 15:15:49 - mmengine - INFO - Epoch(train) [38][300/925] lr: 1.1090e-04 eta: 4:27:12 time: 0.4144 data_time: 0.0021 memory: 5430 grad_norm: 919.2907 loss: 423.6633 loss_cls: 154.0345 loss_bbox: 127.5988 loss_dfl: 142.0300 2024/03/27 15:16:10 - mmengine - INFO - Epoch(train) [38][350/925] lr: 1.1090e-04 eta: 4:26:52 time: 0.4188 data_time: 0.0022 memory: 5764 grad_norm: 981.4618 loss: 433.4659 loss_cls: 160.5728 loss_bbox: 129.3041 loss_dfl: 143.5891 2024/03/27 15:16:30 - mmengine - INFO - Epoch(train) [38][400/925] lr: 1.1090e-04 eta: 4:26:32 time: 0.4032 data_time: 0.0020 memory: 5216 grad_norm: 942.0629 loss: 419.6018 loss_cls: 151.6469 loss_bbox: 125.6717 loss_dfl: 142.2831 2024/03/27 15:16:50 - mmengine - INFO - Epoch(train) [38][450/925] lr: 1.1090e-04 eta: 4:26:12 time: 0.4096 data_time: 0.0021 memory: 5190 grad_norm: 903.3175 loss: 426.9501 loss_cls: 155.4521 loss_bbox: 128.3888 loss_dfl: 143.1092 2024/03/27 15:17:11 - mmengine - INFO - Epoch(train) [38][500/925] lr: 1.1090e-04 eta: 4:25:51 time: 0.4084 data_time: 0.0020 memory: 5363 grad_norm: 901.3824 loss: 420.9463 loss_cls: 153.3926 loss_bbox: 126.0617 loss_dfl: 141.4919 2024/03/27 15:17:31 - mmengine - INFO - Epoch(train) [38][550/925] lr: 1.1090e-04 eta: 4:25:31 time: 0.4116 data_time: 0.0021 memory: 5670 grad_norm: 885.4756 loss: 432.4929 loss_cls: 159.1196 loss_bbox: 129.5995 loss_dfl: 143.7738 2024/03/27 15:17:52 - mmengine - INFO - Epoch(train) [38][600/925] lr: 1.1090e-04 eta: 4:25:11 time: 0.4041 data_time: 0.0021 memory: 5643 grad_norm: 1018.4974 loss: 435.7436 loss_cls: 162.5499 loss_bbox: 129.3380 loss_dfl: 143.8557 2024/03/27 15:18:12 - mmengine - INFO - Epoch(train) [38][650/925] lr: 1.1090e-04 eta: 4:24:51 time: 0.4113 data_time: 0.0021 memory: 5243 grad_norm: 893.4951 loss: 429.0125 loss_cls: 156.4579 loss_bbox: 128.9682 loss_dfl: 143.5864 2024/03/27 15:18:33 - mmengine - INFO - Epoch(train) [38][700/925] lr: 1.1090e-04 eta: 4:24:31 time: 0.4069 data_time: 0.0020 memory: 5643 grad_norm: 898.6469 loss: 429.0861 loss_cls: 156.5991 loss_bbox: 129.4070 loss_dfl: 143.0799 2024/03/27 15:18:53 - mmengine - INFO - Epoch(train) [38][750/925] lr: 1.1090e-04 eta: 4:24:10 time: 0.3962 data_time: 0.0021 memory: 5923 grad_norm: 1131.8140 loss: 431.2715 loss_cls: 157.2489 loss_bbox: 129.7258 loss_dfl: 144.2968 2024/03/27 15:19:03 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:19:13 - mmengine - INFO - Epoch(train) [38][800/925] lr: 1.1090e-04 eta: 4:23:50 time: 0.4070 data_time: 0.0021 memory: 5376 grad_norm: 852.1189 loss: 417.2454 loss_cls: 151.6424 loss_bbox: 124.4035 loss_dfl: 141.1996 2024/03/27 15:19:33 - mmengine - INFO - Epoch(train) [38][850/925] lr: 1.1090e-04 eta: 4:23:29 time: 0.3951 data_time: 0.0020 memory: 5536 grad_norm: 936.5140 loss: 431.6360 loss_cls: 160.0156 loss_bbox: 128.5425 loss_dfl: 143.0779 2024/03/27 15:19:53 - mmengine - INFO - Epoch(train) [38][900/925] lr: 1.1090e-04 eta: 4:23:08 time: 0.4005 data_time: 0.0022 memory: 5816 grad_norm: 943.0975 loss: 429.9738 loss_cls: 157.2731 loss_bbox: 128.8147 loss_dfl: 143.8860 2024/03/27 15:20:02 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:20:26 - mmengine - INFO - Epoch(train) [39][ 50/925] lr: 1.0842e-04 eta: 4:22:40 time: 0.4761 data_time: 0.0597 memory: 6083 grad_norm: 1004.8605 loss: 425.7297 loss_cls: 156.6752 loss_bbox: 126.3568 loss_dfl: 142.6976 2024/03/27 15:20:46 - mmengine - INFO - Epoch(train) [39][100/925] lr: 1.0842e-04 eta: 4:22:19 time: 0.3967 data_time: 0.0019 memory: 5576 grad_norm: 906.2597 loss: 428.8443 loss_cls: 156.3507 loss_bbox: 128.5051 loss_dfl: 143.9885 2024/03/27 15:21:06 - mmengine - INFO - Epoch(train) [39][150/925] lr: 1.0842e-04 eta: 4:21:59 time: 0.4105 data_time: 0.0021 memory: 5203 grad_norm: 974.8762 loss: 420.9672 loss_cls: 152.5225 loss_bbox: 126.6143 loss_dfl: 141.8303 2024/03/27 15:21:26 - mmengine - INFO - Epoch(train) [39][200/925] lr: 1.0842e-04 eta: 4:21:38 time: 0.3932 data_time: 0.0022 memory: 5430 grad_norm: 962.7250 loss: 428.0205 loss_cls: 155.8759 loss_bbox: 128.6735 loss_dfl: 143.4712 2024/03/27 15:21:46 - mmengine - INFO - Epoch(train) [39][250/925] lr: 1.0842e-04 eta: 4:21:18 time: 0.4015 data_time: 0.0018 memory: 5376 grad_norm: 876.1245 loss: 426.8195 loss_cls: 156.9223 loss_bbox: 126.8642 loss_dfl: 143.0331 2024/03/27 15:22:06 - mmengine - INFO - Epoch(train) [39][300/925] lr: 1.0842e-04 eta: 4:20:57 time: 0.4011 data_time: 0.0020 memory: 5403 grad_norm: 936.8062 loss: 429.9856 loss_cls: 156.6708 loss_bbox: 129.6319 loss_dfl: 143.6830 2024/03/27 15:22:26 - mmengine - INFO - Epoch(train) [39][350/925] lr: 1.0842e-04 eta: 4:20:36 time: 0.3947 data_time: 0.0021 memory: 5363 grad_norm: 918.8429 loss: 431.8949 loss_cls: 160.2488 loss_bbox: 128.9259 loss_dfl: 142.7202 2024/03/27 15:22:46 - mmengine - INFO - Epoch(train) [39][400/925] lr: 1.0842e-04 eta: 4:20:15 time: 0.3913 data_time: 0.0022 memory: 5350 grad_norm: 945.3450 loss: 428.3102 loss_cls: 156.4364 loss_bbox: 129.8010 loss_dfl: 142.0729 2024/03/27 15:23:06 - mmengine - INFO - Epoch(train) [39][450/925] lr: 1.0842e-04 eta: 4:19:54 time: 0.4022 data_time: 0.0023 memory: 5310 grad_norm: 829.8960 loss: 430.2893 loss_cls: 157.5366 loss_bbox: 129.4276 loss_dfl: 143.3252 2024/03/27 15:23:25 - mmengine - INFO - Epoch(train) [39][500/925] lr: 1.0842e-04 eta: 4:19:33 time: 0.3879 data_time: 0.0021 memory: 5576 grad_norm: 874.4039 loss: 428.7338 loss_cls: 155.6270 loss_bbox: 129.8684 loss_dfl: 143.2384 2024/03/27 15:23:45 - mmengine - INFO - Epoch(train) [39][550/925] lr: 1.0842e-04 eta: 4:19:13 time: 0.4038 data_time: 0.0021 memory: 5323 grad_norm: 915.8558 loss: 435.0906 loss_cls: 161.0589 loss_bbox: 129.7365 loss_dfl: 144.2952 2024/03/27 15:24:05 - mmengine - INFO - Epoch(train) [39][600/925] lr: 1.0842e-04 eta: 4:18:51 time: 0.3893 data_time: 0.0022 memory: 5363 grad_norm: 934.9616 loss: 428.4084 loss_cls: 157.3931 loss_bbox: 127.8875 loss_dfl: 143.1278 2024/03/27 15:24:25 - mmengine - INFO - Epoch(train) [39][650/925] lr: 1.0842e-04 eta: 4:18:31 time: 0.3977 data_time: 0.0022 memory: 5310 grad_norm: 919.3801 loss: 429.0573 loss_cls: 157.0453 loss_bbox: 128.7586 loss_dfl: 143.2535 2024/03/27 15:24:44 - mmengine - INFO - Epoch(train) [39][700/925] lr: 1.0842e-04 eta: 4:18:09 time: 0.3865 data_time: 0.0021 memory: 5723 grad_norm: 964.1357 loss: 434.8590 loss_cls: 159.6166 loss_bbox: 130.8008 loss_dfl: 144.4416 2024/03/27 15:25:04 - mmengine - INFO - Epoch(train) [39][750/925] lr: 1.0842e-04 eta: 4:17:49 time: 0.4020 data_time: 0.0024 memory: 5376 grad_norm: 856.2022 loss: 422.7553 loss_cls: 153.5264 loss_bbox: 126.6106 loss_dfl: 142.6183 2024/03/27 15:25:24 - mmengine - INFO - Epoch(train) [39][800/925] lr: 1.0842e-04 eta: 4:17:28 time: 0.3949 data_time: 0.0020 memory: 5803 grad_norm: 1004.6266 loss: 426.2957 loss_cls: 155.7644 loss_bbox: 127.3428 loss_dfl: 143.1884 2024/03/27 15:25:44 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:25:44 - mmengine - INFO - Epoch(train) [39][850/925] lr: 1.0842e-04 eta: 4:17:07 time: 0.3950 data_time: 0.0025 memory: 5590 grad_norm: 988.2044 loss: 432.4290 loss_cls: 158.6708 loss_bbox: 129.5855 loss_dfl: 144.1728 2024/03/27 15:26:04 - mmengine - INFO - Epoch(train) [39][900/925] lr: 1.0842e-04 eta: 4:16:47 time: 0.4080 data_time: 0.0021 memory: 5443 grad_norm: 865.5068 loss: 433.0754 loss_cls: 159.6023 loss_bbox: 129.9626 loss_dfl: 143.5105 2024/03/27 15:26:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:26:37 - mmengine - INFO - Epoch(train) [40][ 50/925] lr: 1.0595e-04 eta: 4:16:19 time: 0.4743 data_time: 0.0617 memory: 5296 grad_norm: 826.7920 loss: 425.8386 loss_cls: 154.3612 loss_bbox: 128.4354 loss_dfl: 143.0420 2024/03/27 15:26:58 - mmengine - INFO - Epoch(train) [40][100/925] lr: 1.0595e-04 eta: 4:15:58 time: 0.4057 data_time: 0.0023 memory: 5590 grad_norm: 868.4080 loss: 427.1760 loss_cls: 156.3952 loss_bbox: 127.6152 loss_dfl: 143.1656 2024/03/27 15:27:18 - mmengine - INFO - Epoch(train) [40][150/925] lr: 1.0595e-04 eta: 4:15:38 time: 0.4037 data_time: 0.0020 memory: 5216 grad_norm: 901.4340 loss: 423.6053 loss_cls: 154.8647 loss_bbox: 127.3694 loss_dfl: 141.3711 2024/03/27 15:27:39 - mmengine - INFO - Epoch(train) [40][200/925] lr: 1.0595e-04 eta: 4:15:18 time: 0.4155 data_time: 0.0020 memory: 5483 grad_norm: 961.1846 loss: 429.1900 loss_cls: 156.1357 loss_bbox: 129.7739 loss_dfl: 143.2804 2024/03/27 15:27:59 - mmengine - INFO - Epoch(train) [40][250/925] lr: 1.0595e-04 eta: 4:14:58 time: 0.4080 data_time: 0.0021 memory: 5470 grad_norm: 1070.9682 loss: 426.7860 loss_cls: 154.8885 loss_bbox: 128.7162 loss_dfl: 143.1812 2024/03/27 15:28:19 - mmengine - INFO - Epoch(train) [40][300/925] lr: 1.0595e-04 eta: 4:14:38 time: 0.4039 data_time: 0.0021 memory: 5416 grad_norm: 939.1190 loss: 428.9793 loss_cls: 157.4503 loss_bbox: 128.8560 loss_dfl: 142.6730 2024/03/27 15:28:40 - mmengine - INFO - Epoch(train) [40][350/925] lr: 1.0595e-04 eta: 4:14:17 time: 0.4085 data_time: 0.0020 memory: 5336 grad_norm: 952.1950 loss: 431.0223 loss_cls: 159.4003 loss_bbox: 128.3443 loss_dfl: 143.2777 2024/03/27 15:29:00 - mmengine - INFO - Epoch(train) [40][400/925] lr: 1.0595e-04 eta: 4:13:57 time: 0.3984 data_time: 0.0019 memory: 5256 grad_norm: 908.6440 loss: 429.4065 loss_cls: 157.2619 loss_bbox: 128.8269 loss_dfl: 143.3177 2024/03/27 15:29:20 - mmengine - INFO - Epoch(train) [40][450/925] lr: 1.0595e-04 eta: 4:13:37 time: 0.4113 data_time: 0.0021 memory: 5336 grad_norm: 889.6179 loss: 419.5440 loss_cls: 151.7914 loss_bbox: 126.4712 loss_dfl: 141.2814 2024/03/27 15:29:41 - mmengine - INFO - Epoch(train) [40][500/925] lr: 1.0595e-04 eta: 4:13:17 time: 0.4136 data_time: 0.0024 memory: 5363 grad_norm: 984.1760 loss: 426.2756 loss_cls: 157.2874 loss_bbox: 126.9275 loss_dfl: 142.0608 2024/03/27 15:30:01 - mmengine - INFO - Epoch(train) [40][550/925] lr: 1.0595e-04 eta: 4:12:57 time: 0.4084 data_time: 0.0024 memory: 5310 grad_norm: 890.3387 loss: 433.3139 loss_cls: 158.1753 loss_bbox: 130.9327 loss_dfl: 144.2058 2024/03/27 15:30:22 - mmengine - INFO - Epoch(train) [40][600/925] lr: 1.0595e-04 eta: 4:12:36 time: 0.4079 data_time: 0.0019 memory: 5283 grad_norm: 904.6874 loss: 426.1852 loss_cls: 157.0117 loss_bbox: 127.0825 loss_dfl: 142.0910 2024/03/27 15:30:42 - mmengine - INFO - Epoch(train) [40][650/925] lr: 1.0595e-04 eta: 4:12:16 time: 0.4018 data_time: 0.0020 memory: 5296 grad_norm: 922.1761 loss: 426.1429 loss_cls: 154.5340 loss_bbox: 127.7404 loss_dfl: 143.8685 2024/03/27 15:31:02 - mmengine - INFO - Epoch(train) [40][700/925] lr: 1.0595e-04 eta: 4:11:55 time: 0.3969 data_time: 0.0020 memory: 5683 grad_norm: 1050.2566 loss: 433.5948 loss_cls: 159.0946 loss_bbox: 130.9481 loss_dfl: 143.5521 2024/03/27 15:31:22 - mmengine - INFO - Epoch(train) [40][750/925] lr: 1.0595e-04 eta: 4:11:34 time: 0.4004 data_time: 0.0021 memory: 5470 grad_norm: 964.6354 loss: 423.1564 loss_cls: 154.5158 loss_bbox: 126.2579 loss_dfl: 142.3827 2024/03/27 15:31:42 - mmengine - INFO - Epoch(train) [40][800/925] lr: 1.0595e-04 eta: 4:11:14 time: 0.3966 data_time: 0.0022 memory: 5363 grad_norm: 941.2968 loss: 430.3651 loss_cls: 160.0861 loss_bbox: 126.9249 loss_dfl: 143.3541 2024/03/27 15:32:02 - mmengine - INFO - Epoch(train) [40][850/925] lr: 1.0595e-04 eta: 4:10:53 time: 0.4015 data_time: 0.0021 memory: 5363 grad_norm: 969.2106 loss: 425.4281 loss_cls: 155.4736 loss_bbox: 127.1256 loss_dfl: 142.8289 2024/03/27 15:32:21 - mmengine - INFO - Epoch(train) [40][900/925] lr: 1.0595e-04 eta: 4:10:32 time: 0.3935 data_time: 0.0020 memory: 5670 grad_norm: 925.2054 loss: 417.9444 loss_cls: 151.0048 loss_bbox: 125.9200 loss_dfl: 141.0196 2024/03/27 15:32:31 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:32:32 - mmengine - INFO - Saving checkpoint at 40 epochs 2024/03/27 15:32:40 - mmengine - INFO - Epoch(val) [40][ 50/625] eta: 0:00:24 time: 0.0429 data_time: 0.0009 memory: 5456 2024/03/27 15:32:42 - mmengine - INFO - Epoch(val) [40][100/625] eta: 0:00:22 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 15:32:44 - mmengine - INFO - Epoch(val) [40][150/625] eta: 0:00:20 time: 0.0443 data_time: 0.0004 memory: 838 2024/03/27 15:32:47 - mmengine - INFO - Epoch(val) [40][200/625] eta: 0:00:18 time: 0.0452 data_time: 0.0004 memory: 838 2024/03/27 15:32:49 - mmengine - INFO - Epoch(val) [40][250/625] eta: 0:00:16 time: 0.0427 data_time: 0.0004 memory: 838 2024/03/27 15:32:51 - mmengine - INFO - Epoch(val) [40][300/625] eta: 0:00:14 time: 0.0432 data_time: 0.0003 memory: 838 2024/03/27 15:32:53 - mmengine - INFO - Epoch(val) [40][350/625] eta: 0:00:12 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 15:32:55 - mmengine - INFO - Epoch(val) [40][400/625] eta: 0:00:09 time: 0.0440 data_time: 0.0004 memory: 838 2024/03/27 15:32:57 - mmengine - INFO - Epoch(val) [40][450/625] eta: 0:00:07 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 15:32:59 - mmengine - INFO - Epoch(val) [40][500/625] eta: 0:00:05 time: 0.0393 data_time: 0.0003 memory: 838 2024/03/27 15:33:01 - mmengine - INFO - Epoch(val) [40][550/625] eta: 0:00:03 time: 0.0338 data_time: 0.0003 memory: 838 2024/03/27 15:33:03 - mmengine - INFO - Epoch(val) [40][600/625] eta: 0:00:01 time: 0.0353 data_time: 0.0003 memory: 838 2024/03/27 15:33:19 - mmengine - INFO - Evaluating bbox... 2024/03/27 15:34:44 - mmengine - INFO - bbox_mAP_copypaste: 0.451 0.613 0.492 0.255 0.499 0.604 2024/03/27 15:34:45 - mmengine - INFO - Epoch(val) [40][625/625] coco/bbox_mAP: 0.4510 coco/bbox_mAP_50: 0.6130 coco/bbox_mAP_75: 0.4920 coco/bbox_mAP_s: 0.2550 coco/bbox_mAP_m: 0.4990 coco/bbox_mAP_l: 0.6040 data_time: 0.0003 time: 0.0352 2024/03/27 15:35:09 - mmengine - INFO - Epoch(train) [41][ 50/925] lr: 1.0347e-04 eta: 4:10:05 time: 0.4830 data_time: 0.0640 memory: 5550 grad_norm: 940.9702 loss: 427.6859 loss_cls: 155.9717 loss_bbox: 128.8275 loss_dfl: 142.8866 2024/03/27 15:35:29 - mmengine - INFO - Epoch(train) [41][100/925] lr: 1.0347e-04 eta: 4:09:44 time: 0.3976 data_time: 0.0024 memory: 5216 grad_norm: 849.0726 loss: 423.8268 loss_cls: 155.2211 loss_bbox: 126.3490 loss_dfl: 142.2566 2024/03/27 15:35:49 - mmengine - INFO - Epoch(train) [41][150/925] lr: 1.0347e-04 eta: 4:09:23 time: 0.3916 data_time: 0.0022 memory: 5323 grad_norm: 945.1999 loss: 430.5802 loss_cls: 157.1815 loss_bbox: 129.1813 loss_dfl: 144.2173 2024/03/27 15:36:09 - mmengine - INFO - Epoch(train) [41][200/925] lr: 1.0347e-04 eta: 4:09:03 time: 0.4029 data_time: 0.0022 memory: 5510 grad_norm: 909.3864 loss: 428.8837 loss_cls: 156.3767 loss_bbox: 129.5049 loss_dfl: 143.0021 2024/03/27 15:36:29 - mmengine - INFO - Epoch(train) [41][250/925] lr: 1.0347e-04 eta: 4:08:43 time: 0.4114 data_time: 0.0024 memory: 5563 grad_norm: 876.5015 loss: 424.2884 loss_cls: 154.9738 loss_bbox: 126.8241 loss_dfl: 142.4905 2024/03/27 15:36:49 - mmengine - INFO - Epoch(train) [41][300/925] lr: 1.0347e-04 eta: 4:08:22 time: 0.3915 data_time: 0.0025 memory: 5363 grad_norm: inf loss: 423.5958 loss_cls: 155.1292 loss_bbox: 126.3790 loss_dfl: 142.0876 2024/03/27 15:37:10 - mmengine - INFO - Epoch(train) [41][350/925] lr: 1.0347e-04 eta: 4:08:02 time: 0.4124 data_time: 0.0021 memory: 5310 grad_norm: 865.4427 loss: 431.7133 loss_cls: 159.1305 loss_bbox: 128.7668 loss_dfl: 143.8159 2024/03/27 15:37:30 - mmengine - INFO - Epoch(train) [41][400/925] lr: 1.0347e-04 eta: 4:07:42 time: 0.4098 data_time: 0.0022 memory: 5563 grad_norm: 902.0218 loss: 433.5514 loss_cls: 158.4899 loss_bbox: 131.3423 loss_dfl: 143.7192 2024/03/27 15:37:50 - mmengine - INFO - Epoch(train) [41][450/925] lr: 1.0347e-04 eta: 4:07:21 time: 0.4038 data_time: 0.0023 memory: 5203 grad_norm: 932.7365 loss: 423.9393 loss_cls: 154.6298 loss_bbox: 127.3728 loss_dfl: 141.9367 2024/03/27 15:38:11 - mmengine - INFO - Epoch(train) [41][500/925] lr: 1.0347e-04 eta: 4:07:01 time: 0.4052 data_time: 0.0021 memory: 5403 grad_norm: 897.0392 loss: 422.2448 loss_cls: 152.4889 loss_bbox: 126.5720 loss_dfl: 143.1839 2024/03/27 15:38:31 - mmengine - INFO - Epoch(train) [41][550/925] lr: 1.0347e-04 eta: 4:06:41 time: 0.4109 data_time: 0.0022 memory: 5243 grad_norm: 903.1326 loss: 423.1684 loss_cls: 154.0851 loss_bbox: 126.0751 loss_dfl: 143.0082 2024/03/27 15:38:51 - mmengine - INFO - Epoch(train) [41][600/925] lr: 1.0347e-04 eta: 4:06:20 time: 0.4007 data_time: 0.0020 memory: 5576 grad_norm: 900.7871 loss: 435.8897 loss_cls: 161.8624 loss_bbox: 129.8139 loss_dfl: 144.2134 2024/03/27 15:39:12 - mmengine - INFO - Epoch(train) [41][650/925] lr: 1.0347e-04 eta: 4:06:00 time: 0.4068 data_time: 0.0021 memory: 5243 grad_norm: 888.5392 loss: 423.8444 loss_cls: 154.9141 loss_bbox: 126.5086 loss_dfl: 142.4216 2024/03/27 15:39:33 - mmengine - INFO - Epoch(train) [41][700/925] lr: 1.0347e-04 eta: 4:05:41 time: 0.4256 data_time: 0.0023 memory: 5563 grad_norm: 1009.0774 loss: 432.3100 loss_cls: 157.8851 loss_bbox: 130.4555 loss_dfl: 143.9694 2024/03/27 15:39:53 - mmengine - INFO - Epoch(train) [41][750/925] lr: 1.0347e-04 eta: 4:05:20 time: 0.3910 data_time: 0.0022 memory: 5336 grad_norm: 886.3258 loss: 430.8729 loss_cls: 159.0266 loss_bbox: 128.3361 loss_dfl: 143.5101 2024/03/27 15:40:13 - mmengine - INFO - Epoch(train) [41][800/925] lr: 1.0347e-04 eta: 4:04:59 time: 0.4067 data_time: 0.0021 memory: 5456 grad_norm: 906.0929 loss: 428.2758 loss_cls: 156.8183 loss_bbox: 128.8343 loss_dfl: 142.6232 2024/03/27 15:40:33 - mmengine - INFO - Epoch(train) [41][850/925] lr: 1.0347e-04 eta: 4:04:39 time: 0.4088 data_time: 0.0021 memory: 5150 grad_norm: 967.0702 loss: 426.7659 loss_cls: 157.4739 loss_bbox: 126.7372 loss_dfl: 142.5549 2024/03/27 15:40:54 - mmengine - INFO - Epoch(train) [41][900/925] lr: 1.0347e-04 eta: 4:04:19 time: 0.4045 data_time: 0.0022 memory: 5243 grad_norm: 848.8776 loss: 421.1935 loss_cls: 152.8984 loss_bbox: 126.7381 loss_dfl: 141.5570 2024/03/27 15:41:03 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:41:27 - mmengine - INFO - Epoch(train) [42][ 50/925] lr: 1.0100e-04 eta: 4:03:50 time: 0.4693 data_time: 0.0625 memory: 5576 grad_norm: 964.4827 loss: 428.6987 loss_cls: 156.7524 loss_bbox: 128.6298 loss_dfl: 143.3165 2024/03/27 15:41:37 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:41:48 - mmengine - INFO - Epoch(train) [42][100/925] lr: 1.0100e-04 eta: 4:03:31 time: 0.4170 data_time: 0.0021 memory: 5470 grad_norm: 974.6209 loss: 426.4147 loss_cls: 156.1281 loss_bbox: 128.0678 loss_dfl: 142.2189 2024/03/27 15:42:07 - mmengine - INFO - Epoch(train) [42][150/925] lr: 1.0100e-04 eta: 4:03:10 time: 0.3935 data_time: 0.0022 memory: 5470 grad_norm: 1002.7711 loss: 426.8206 loss_cls: 155.6487 loss_bbox: 127.8017 loss_dfl: 143.3702 2024/03/27 15:42:27 - mmengine - INFO - Epoch(train) [42][200/925] lr: 1.0100e-04 eta: 4:02:49 time: 0.4035 data_time: 0.0021 memory: 5616 grad_norm: 931.5877 loss: 414.9779 loss_cls: 149.5777 loss_bbox: 123.9589 loss_dfl: 141.4413 2024/03/27 15:42:47 - mmengine - INFO - Epoch(train) [42][250/925] lr: 1.0100e-04 eta: 4:02:28 time: 0.3924 data_time: 0.0021 memory: 5483 grad_norm: 897.2135 loss: 423.8105 loss_cls: 155.2749 loss_bbox: 126.7036 loss_dfl: 141.8320 2024/03/27 15:43:08 - mmengine - INFO - Epoch(train) [42][300/925] lr: 1.0100e-04 eta: 4:02:09 time: 0.4255 data_time: 0.0021 memory: 5256 grad_norm: 935.5286 loss: 427.1853 loss_cls: 156.1860 loss_bbox: 128.9694 loss_dfl: 142.0298 2024/03/27 15:43:29 - mmengine - INFO - Epoch(train) [42][350/925] lr: 1.0100e-04 eta: 4:01:48 time: 0.4046 data_time: 0.0021 memory: 5510 grad_norm: 957.7265 loss: 425.9915 loss_cls: 155.4320 loss_bbox: 127.3276 loss_dfl: 143.2319 2024/03/27 15:43:49 - mmengine - INFO - Epoch(train) [42][400/925] lr: 1.0100e-04 eta: 4:01:28 time: 0.4104 data_time: 0.0022 memory: 5430 grad_norm: 893.3114 loss: 427.5723 loss_cls: 156.6561 loss_bbox: 128.0295 loss_dfl: 142.8867 2024/03/27 15:44:10 - mmengine - INFO - Epoch(train) [42][450/925] lr: 1.0100e-04 eta: 4:01:09 time: 0.4193 data_time: 0.0022 memory: 5070 grad_norm: 991.7139 loss: 422.2077 loss_cls: 153.3687 loss_bbox: 126.4134 loss_dfl: 142.4256 2024/03/27 15:44:30 - mmengine - INFO - Epoch(train) [42][500/925] lr: 1.0100e-04 eta: 4:00:48 time: 0.4016 data_time: 0.0022 memory: 5403 grad_norm: 852.3686 loss: 432.4082 loss_cls: 159.9077 loss_bbox: 128.4949 loss_dfl: 144.0056 2024/03/27 15:44:50 - mmengine - INFO - Epoch(train) [42][550/925] lr: 1.0100e-04 eta: 4:00:28 time: 0.4005 data_time: 0.0022 memory: 5510 grad_norm: 956.3324 loss: 425.5545 loss_cls: 154.3018 loss_bbox: 128.4841 loss_dfl: 142.7685 2024/03/27 15:45:11 - mmengine - INFO - Epoch(train) [42][600/925] lr: 1.0100e-04 eta: 4:00:08 time: 0.4161 data_time: 0.0021 memory: 5510 grad_norm: 848.3944 loss: 430.7873 loss_cls: 158.1314 loss_bbox: 129.3078 loss_dfl: 143.3480 2024/03/27 15:45:31 - mmengine - INFO - Epoch(train) [42][650/925] lr: 1.0100e-04 eta: 3:59:47 time: 0.4041 data_time: 0.0022 memory: 5256 grad_norm: 903.1449 loss: 418.9943 loss_cls: 151.0132 loss_bbox: 126.1105 loss_dfl: 141.8706 2024/03/27 15:45:51 - mmengine - INFO - Epoch(train) [42][700/925] lr: 1.0100e-04 eta: 3:59:26 time: 0.3871 data_time: 0.0025 memory: 5283 grad_norm: 913.4877 loss: 423.7081 loss_cls: 154.3428 loss_bbox: 127.0442 loss_dfl: 142.3211 2024/03/27 15:46:12 - mmengine - INFO - Epoch(train) [42][750/925] lr: 1.0100e-04 eta: 3:59:06 time: 0.4137 data_time: 0.0022 memory: 5230 grad_norm: 882.6818 loss: 425.0179 loss_cls: 154.5660 loss_bbox: 127.2763 loss_dfl: 143.1757 2024/03/27 15:46:32 - mmengine - INFO - Epoch(train) [42][800/925] lr: 1.0100e-04 eta: 3:58:46 time: 0.4127 data_time: 0.0022 memory: 5603 grad_norm: 891.0279 loss: 426.6391 loss_cls: 156.2476 loss_bbox: 127.3935 loss_dfl: 142.9981 2024/03/27 15:46:52 - mmengine - INFO - Epoch(train) [42][850/925] lr: 1.0100e-04 eta: 3:58:25 time: 0.3949 data_time: 0.0022 memory: 5603 grad_norm: 860.7789 loss: 421.4012 loss_cls: 153.6307 loss_bbox: 125.8410 loss_dfl: 141.9294 2024/03/27 15:47:13 - mmengine - INFO - Epoch(train) [42][900/925] lr: 1.0100e-04 eta: 3:58:05 time: 0.4139 data_time: 0.0021 memory: 5350 grad_norm: 946.1033 loss: 420.7527 loss_cls: 151.7309 loss_bbox: 127.0971 loss_dfl: 141.9246 2024/03/27 15:47:22 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:47:47 - mmengine - INFO - Epoch(train) [43][ 50/925] lr: 9.8525e-05 eta: 3:57:38 time: 0.4787 data_time: 0.0618 memory: 5403 grad_norm: 907.3934 loss: 418.7980 loss_cls: 151.9217 loss_bbox: 125.9867 loss_dfl: 140.8897 2024/03/27 15:48:07 - mmengine - INFO - Epoch(train) [43][100/925] lr: 9.8525e-05 eta: 3:57:17 time: 0.4114 data_time: 0.0022 memory: 5390 grad_norm: 977.0351 loss: 422.1921 loss_cls: 153.0719 loss_bbox: 126.7832 loss_dfl: 142.3370 2024/03/27 15:48:27 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:48:27 - mmengine - INFO - Epoch(train) [43][150/925] lr: 9.8525e-05 eta: 3:56:57 time: 0.4059 data_time: 0.0020 memory: 5336 grad_norm: 982.7483 loss: 433.7119 loss_cls: 157.8570 loss_bbox: 131.3826 loss_dfl: 144.4723 2024/03/27 15:48:48 - mmengine - INFO - Epoch(train) [43][200/925] lr: 9.8525e-05 eta: 3:56:37 time: 0.4111 data_time: 0.0023 memory: 5256 grad_norm: 912.2915 loss: 422.1876 loss_cls: 153.2346 loss_bbox: 126.6817 loss_dfl: 142.2713 2024/03/27 15:49:08 - mmengine - INFO - Epoch(train) [43][250/925] lr: 9.8525e-05 eta: 3:56:16 time: 0.3994 data_time: 0.0022 memory: 5510 grad_norm: 978.2270 loss: 426.7579 loss_cls: 155.6758 loss_bbox: 128.3840 loss_dfl: 142.6982 2024/03/27 15:49:28 - mmengine - INFO - Epoch(train) [43][300/925] lr: 9.8525e-05 eta: 3:55:56 time: 0.4017 data_time: 0.0023 memory: 5123 grad_norm: 1008.4906 loss: 423.8673 loss_cls: 154.8749 loss_bbox: 126.2667 loss_dfl: 142.7258 2024/03/27 15:49:49 - mmengine - INFO - Epoch(train) [43][350/925] lr: 9.8525e-05 eta: 3:55:36 time: 0.4130 data_time: 0.0021 memory: 5550 grad_norm: 923.2121 loss: 421.2395 loss_cls: 151.9386 loss_bbox: 127.1133 loss_dfl: 142.1876 2024/03/27 15:50:09 - mmengine - INFO - Epoch(train) [43][400/925] lr: 9.8525e-05 eta: 3:55:15 time: 0.3996 data_time: 0.0022 memory: 5510 grad_norm: 890.7556 loss: 420.4386 loss_cls: 153.7386 loss_bbox: 125.5938 loss_dfl: 141.1061 2024/03/27 15:50:28 - mmengine - INFO - Epoch(train) [43][450/925] lr: 9.8525e-05 eta: 3:54:54 time: 0.3828 data_time: 0.0021 memory: 5576 grad_norm: 862.7481 loss: 431.0833 loss_cls: 158.0985 loss_bbox: 129.5758 loss_dfl: 143.4089 2024/03/27 15:50:48 - mmengine - INFO - Epoch(train) [43][500/925] lr: 9.8525e-05 eta: 3:54:34 time: 0.4042 data_time: 0.0020 memory: 5390 grad_norm: 938.1946 loss: 428.9864 loss_cls: 155.3197 loss_bbox: 130.4371 loss_dfl: 143.2295 2024/03/27 15:51:09 - mmengine - INFO - Epoch(train) [43][550/925] lr: 9.8525e-05 eta: 3:54:13 time: 0.4083 data_time: 0.0020 memory: 5363 grad_norm: 885.3403 loss: 434.0883 loss_cls: 159.2734 loss_bbox: 130.6783 loss_dfl: 144.1365 2024/03/27 15:51:29 - mmengine - INFO - Epoch(train) [43][600/925] lr: 9.8525e-05 eta: 3:53:53 time: 0.4100 data_time: 0.0021 memory: 5350 grad_norm: 926.8353 loss: 428.1718 loss_cls: 155.5889 loss_bbox: 129.2360 loss_dfl: 143.3469 2024/03/27 15:51:49 - mmengine - INFO - Epoch(train) [43][650/925] lr: 9.8525e-05 eta: 3:53:32 time: 0.3937 data_time: 0.0021 memory: 5696 grad_norm: 856.9823 loss: 428.1389 loss_cls: 156.1040 loss_bbox: 129.2751 loss_dfl: 142.7598 2024/03/27 15:52:09 - mmengine - INFO - Epoch(train) [43][700/925] lr: 9.8525e-05 eta: 3:53:12 time: 0.4062 data_time: 0.0022 memory: 5336 grad_norm: 839.7643 loss: 418.9315 loss_cls: 150.4127 loss_bbox: 126.7382 loss_dfl: 141.7806 2024/03/27 15:52:30 - mmengine - INFO - Epoch(train) [43][750/925] lr: 9.8525e-05 eta: 3:52:52 time: 0.4061 data_time: 0.0022 memory: 5323 grad_norm: 945.4999 loss: 425.4576 loss_cls: 154.7467 loss_bbox: 127.3953 loss_dfl: 143.3157 2024/03/27 15:52:49 - mmengine - INFO - Epoch(train) [43][800/925] lr: 9.8525e-05 eta: 3:52:31 time: 0.3913 data_time: 0.0023 memory: 5430 grad_norm: inf loss: 426.9242 loss_cls: 155.5300 loss_bbox: 128.1308 loss_dfl: 143.2634 2024/03/27 15:53:10 - mmengine - INFO - Epoch(train) [43][850/925] lr: 9.8525e-05 eta: 3:52:11 time: 0.4133 data_time: 0.0023 memory: 5310 grad_norm: 978.2117 loss: 423.1147 loss_cls: 154.6213 loss_bbox: 126.4114 loss_dfl: 142.0820 2024/03/27 15:53:30 - mmengine - INFO - Epoch(train) [43][900/925] lr: 9.8525e-05 eta: 3:51:50 time: 0.3942 data_time: 0.0021 memory: 5803 grad_norm: 980.2278 loss: 432.6121 loss_cls: 156.9376 loss_bbox: 131.8786 loss_dfl: 143.7960 2024/03/27 15:53:39 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:54:03 - mmengine - INFO - Epoch(train) [44][ 50/925] lr: 9.6050e-05 eta: 3:51:22 time: 0.4839 data_time: 0.0619 memory: 5323 grad_norm: 946.0797 loss: 431.0522 loss_cls: 159.8974 loss_bbox: 127.6341 loss_dfl: 143.5208 2024/03/27 15:54:23 - mmengine - INFO - Epoch(train) [44][100/925] lr: 9.6050e-05 eta: 3:51:01 time: 0.4045 data_time: 0.0022 memory: 5283 grad_norm: 852.7949 loss: 421.8149 loss_cls: 153.8085 loss_bbox: 125.6116 loss_dfl: 142.3948 2024/03/27 15:54:43 - mmengine - INFO - Epoch(train) [44][150/925] lr: 9.6050e-05 eta: 3:50:41 time: 0.3992 data_time: 0.0023 memory: 5470 grad_norm: 870.8468 loss: 426.9806 loss_cls: 157.4372 loss_bbox: 127.2243 loss_dfl: 142.3191 2024/03/27 15:55:04 - mmengine - INFO - Epoch(train) [44][200/925] lr: 9.6050e-05 eta: 3:50:20 time: 0.4033 data_time: 0.0021 memory: 5470 grad_norm: 883.3358 loss: 424.1470 loss_cls: 154.6526 loss_bbox: 127.2048 loss_dfl: 142.2896 2024/03/27 15:55:14 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 15:55:24 - mmengine - INFO - Epoch(train) [44][250/925] lr: 9.6050e-05 eta: 3:50:00 time: 0.4024 data_time: 0.0022 memory: 5243 grad_norm: 912.0582 loss: 417.0591 loss_cls: 150.7026 loss_bbox: 125.1231 loss_dfl: 141.2335 2024/03/27 15:55:44 - mmengine - INFO - Epoch(train) [44][300/925] lr: 9.6050e-05 eta: 3:49:40 time: 0.4132 data_time: 0.0023 memory: 5883 grad_norm: 900.4482 loss: 426.7928 loss_cls: 154.4386 loss_bbox: 129.8873 loss_dfl: 142.4669 2024/03/27 15:56:04 - mmengine - INFO - Epoch(train) [44][350/925] lr: 9.6050e-05 eta: 3:49:19 time: 0.3924 data_time: 0.0022 memory: 5350 grad_norm: 874.9051 loss: 425.4078 loss_cls: 155.1668 loss_bbox: 127.7077 loss_dfl: 142.5333 2024/03/27 15:56:24 - mmengine - INFO - Epoch(train) [44][400/925] lr: 9.6050e-05 eta: 3:48:58 time: 0.3973 data_time: 0.0026 memory: 5443 grad_norm: 876.3053 loss: 424.3325 loss_cls: 153.9332 loss_bbox: 127.3135 loss_dfl: 143.0858 2024/03/27 15:56:44 - mmengine - INFO - Epoch(train) [44][450/925] lr: 9.6050e-05 eta: 3:48:38 time: 0.4081 data_time: 0.0021 memory: 5443 grad_norm: 879.8628 loss: 421.3468 loss_cls: 152.4718 loss_bbox: 126.7871 loss_dfl: 142.0880 2024/03/27 15:57:04 - mmengine - INFO - Epoch(train) [44][500/925] lr: 9.6050e-05 eta: 3:48:17 time: 0.3927 data_time: 0.0022 memory: 5110 grad_norm: 939.3688 loss: 416.1460 loss_cls: 150.0982 loss_bbox: 124.9331 loss_dfl: 141.1147 2024/03/27 15:57:25 - mmengine - INFO - Epoch(train) [44][550/925] lr: 9.6050e-05 eta: 3:47:57 time: 0.4093 data_time: 0.0021 memory: 5256 grad_norm: 885.2839 loss: 424.6028 loss_cls: 154.6215 loss_bbox: 127.2367 loss_dfl: 142.7446 2024/03/27 15:57:45 - mmengine - INFO - Epoch(train) [44][600/925] lr: 9.6050e-05 eta: 3:47:37 time: 0.4133 data_time: 0.0021 memory: 5390 grad_norm: 877.0635 loss: 420.7826 loss_cls: 151.7028 loss_bbox: 126.6582 loss_dfl: 142.4216 2024/03/27 15:58:06 - mmengine - INFO - Epoch(train) [44][650/925] lr: 9.6050e-05 eta: 3:47:17 time: 0.4094 data_time: 0.0021 memory: 5283 grad_norm: 866.2943 loss: 418.5321 loss_cls: 149.6519 loss_bbox: 127.1568 loss_dfl: 141.7234 2024/03/27 15:58:26 - mmengine - INFO - Epoch(train) [44][700/925] lr: 9.6050e-05 eta: 3:46:56 time: 0.4010 data_time: 0.0023 memory: 5376 grad_norm: 902.7543 loss: 426.1342 loss_cls: 155.5931 loss_bbox: 128.3135 loss_dfl: 142.2276 2024/03/27 15:58:47 - mmengine - INFO - Epoch(train) [44][750/925] lr: 9.6050e-05 eta: 3:46:36 time: 0.4131 data_time: 0.0022 memory: 5656 grad_norm: 1044.1355 loss: 426.2958 loss_cls: 153.9583 loss_bbox: 129.4097 loss_dfl: 142.9278 2024/03/27 15:59:07 - mmengine - INFO - Epoch(train) [44][800/925] lr: 9.6050e-05 eta: 3:46:16 time: 0.4079 data_time: 0.0022 memory: 5683 grad_norm: 912.8577 loss: 420.9201 loss_cls: 152.6239 loss_bbox: 126.8232 loss_dfl: 141.4730 2024/03/27 15:59:26 - mmengine - INFO - Epoch(train) [44][850/925] lr: 9.6050e-05 eta: 3:45:55 time: 0.3837 data_time: 0.0022 memory: 5256 grad_norm: 844.6141 loss: 425.4757 loss_cls: 157.1378 loss_bbox: 125.9828 loss_dfl: 142.3551 2024/03/27 15:59:47 - mmengine - INFO - Epoch(train) [44][900/925] lr: 9.6050e-05 eta: 3:45:35 time: 0.4088 data_time: 0.0022 memory: 5310 grad_norm: 950.2537 loss: 424.9981 loss_cls: 154.8244 loss_bbox: 127.4131 loss_dfl: 142.7606 2024/03/27 15:59:56 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:00:21 - mmengine - INFO - Epoch(train) [45][ 50/925] lr: 9.3575e-05 eta: 3:45:07 time: 0.4861 data_time: 0.0636 memory: 5416 grad_norm: 1035.6961 loss: 420.7711 loss_cls: 153.0920 loss_bbox: 125.9728 loss_dfl: 141.7062 2024/03/27 16:00:40 - mmengine - INFO - Epoch(train) [45][100/925] lr: 9.3575e-05 eta: 3:44:45 time: 0.3759 data_time: 0.0022 memory: 5296 grad_norm: 1031.9377 loss: 423.3969 loss_cls: 153.0109 loss_bbox: 127.1107 loss_dfl: 143.2753 2024/03/27 16:01:01 - mmengine - INFO - Epoch(train) [45][150/925] lr: 9.3575e-05 eta: 3:44:26 time: 0.4223 data_time: 0.0021 memory: 5416 grad_norm: 878.1605 loss: 424.8451 loss_cls: 154.0152 loss_bbox: 127.9661 loss_dfl: 142.8638 2024/03/27 16:01:22 - mmengine - INFO - Epoch(train) [45][200/925] lr: 9.3575e-05 eta: 3:44:06 time: 0.4123 data_time: 0.0022 memory: 5416 grad_norm: 949.5826 loss: 421.9848 loss_cls: 152.1163 loss_bbox: 128.1022 loss_dfl: 141.7663 2024/03/27 16:01:41 - mmengine - INFO - Epoch(train) [45][250/925] lr: 9.3575e-05 eta: 3:43:45 time: 0.3961 data_time: 0.0022 memory: 5616 grad_norm: 928.3259 loss: 424.9615 loss_cls: 156.4497 loss_bbox: 126.0717 loss_dfl: 142.4400 2024/03/27 16:02:02 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:02:02 - mmengine - INFO - Epoch(train) [45][300/925] lr: 9.3575e-05 eta: 3:43:25 time: 0.4053 data_time: 0.0022 memory: 5296 grad_norm: 986.6940 loss: 424.8635 loss_cls: 155.1475 loss_bbox: 127.1910 loss_dfl: 142.5250 2024/03/27 16:02:22 - mmengine - INFO - Epoch(train) [45][350/925] lr: 9.3575e-05 eta: 3:43:04 time: 0.4115 data_time: 0.0022 memory: 5443 grad_norm: 916.8654 loss: 426.2274 loss_cls: 154.2420 loss_bbox: 129.3953 loss_dfl: 142.5901 2024/03/27 16:02:42 - mmengine - INFO - Epoch(train) [45][400/925] lr: 9.3575e-05 eta: 3:42:44 time: 0.3998 data_time: 0.0022 memory: 5843 grad_norm: 879.6424 loss: 425.4015 loss_cls: 154.7537 loss_bbox: 127.6572 loss_dfl: 142.9905 2024/03/27 16:03:02 - mmengine - INFO - Epoch(train) [45][450/925] lr: 9.3575e-05 eta: 3:42:23 time: 0.4032 data_time: 0.0021 memory: 5550 grad_norm: 985.9806 loss: 420.8505 loss_cls: 152.5819 loss_bbox: 126.6654 loss_dfl: 141.6032 2024/03/27 16:03:23 - mmengine - INFO - Epoch(train) [45][500/925] lr: 9.3575e-05 eta: 3:42:03 time: 0.4002 data_time: 0.0021 memory: 5483 grad_norm: 920.7486 loss: 426.9298 loss_cls: 155.5156 loss_bbox: 128.1526 loss_dfl: 143.2616 2024/03/27 16:03:43 - mmengine - INFO - Epoch(train) [45][550/925] lr: 9.3575e-05 eta: 3:41:43 time: 0.4066 data_time: 0.0025 memory: 5350 grad_norm: 918.3861 loss: 419.6231 loss_cls: 152.7188 loss_bbox: 125.0621 loss_dfl: 141.8421 2024/03/27 16:04:03 - mmengine - INFO - Epoch(train) [45][600/925] lr: 9.3575e-05 eta: 3:41:22 time: 0.3998 data_time: 0.0022 memory: 5576 grad_norm: 917.1041 loss: 424.4220 loss_cls: 154.1769 loss_bbox: 128.2290 loss_dfl: 142.0161 2024/03/27 16:04:23 - mmengine - INFO - Epoch(train) [45][650/925] lr: 9.3575e-05 eta: 3:41:02 time: 0.4060 data_time: 0.0021 memory: 5323 grad_norm: 1003.3291 loss: 426.2097 loss_cls: 155.3066 loss_bbox: 128.1503 loss_dfl: 142.7528 2024/03/27 16:04:43 - mmengine - INFO - Epoch(train) [45][700/925] lr: 9.3575e-05 eta: 3:40:41 time: 0.3987 data_time: 0.0022 memory: 5350 grad_norm: 904.2969 loss: 423.3251 loss_cls: 153.9579 loss_bbox: 127.3981 loss_dfl: 141.9691 2024/03/27 16:05:03 - mmengine - INFO - Epoch(train) [45][750/925] lr: 9.3575e-05 eta: 3:40:21 time: 0.4039 data_time: 0.0023 memory: 5736 grad_norm: 1123.6603 loss: 417.7206 loss_cls: 151.6570 loss_bbox: 124.5638 loss_dfl: 141.4998 2024/03/27 16:05:24 - mmengine - INFO - Epoch(train) [45][800/925] lr: 9.3575e-05 eta: 3:40:00 time: 0.4030 data_time: 0.0021 memory: 5336 grad_norm: 1125.3990 loss: 417.7993 loss_cls: 152.3634 loss_bbox: 124.0171 loss_dfl: 141.4187 2024/03/27 16:05:44 - mmengine - INFO - Epoch(train) [45][850/925] lr: 9.3575e-05 eta: 3:39:40 time: 0.4006 data_time: 0.0021 memory: 5443 grad_norm: 833.1007 loss: 428.2019 loss_cls: 157.5390 loss_bbox: 127.9665 loss_dfl: 142.6964 2024/03/27 16:06:04 - mmengine - INFO - Epoch(train) [45][900/925] lr: 9.3575e-05 eta: 3:39:19 time: 0.4011 data_time: 0.0022 memory: 5830 grad_norm: 949.7780 loss: 423.3110 loss_cls: 152.9751 loss_bbox: 128.5957 loss_dfl: 141.7402 2024/03/27 16:06:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:06:14 - mmengine - INFO - Saving checkpoint at 45 epochs 2024/03/27 16:06:22 - mmengine - INFO - Epoch(val) [45][ 50/625] eta: 0:00:33 time: 0.0578 data_time: 0.0166 memory: 5323 2024/03/27 16:06:24 - mmengine - INFO - Epoch(val) [45][100/625] eta: 0:00:26 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 16:06:26 - mmengine - INFO - Epoch(val) [45][150/625] eta: 0:00:23 time: 0.0450 data_time: 0.0004 memory: 838 2024/03/27 16:06:29 - mmengine - INFO - Epoch(val) [45][200/625] eta: 0:00:20 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 16:06:31 - mmengine - INFO - Epoch(val) [45][250/625] eta: 0:00:17 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 16:06:33 - mmengine - INFO - Epoch(val) [45][300/625] eta: 0:00:15 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 16:06:35 - mmengine - INFO - Epoch(val) [45][350/625] eta: 0:00:12 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 16:06:37 - mmengine - INFO - Epoch(val) [45][400/625] eta: 0:00:10 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 16:06:40 - mmengine - INFO - Epoch(val) [45][450/625] eta: 0:00:07 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 16:06:42 - mmengine - INFO - Epoch(val) [45][500/625] eta: 0:00:05 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 16:06:44 - mmengine - INFO - Epoch(val) [45][550/625] eta: 0:00:03 time: 0.0396 data_time: 0.0003 memory: 838 2024/03/27 16:06:45 - mmengine - INFO - Epoch(val) [45][600/625] eta: 0:00:01 time: 0.0347 data_time: 0.0003 memory: 838 2024/03/27 16:07:00 - mmengine - INFO - Evaluating bbox... 2024/03/27 16:08:19 - mmengine - INFO - bbox_mAP_copypaste: 0.451 0.613 0.494 0.255 0.500 0.604 2024/03/27 16:08:20 - mmengine - INFO - Epoch(val) [45][625/625] coco/bbox_mAP: 0.4510 coco/bbox_mAP_50: 0.6130 coco/bbox_mAP_75: 0.4940 coco/bbox_mAP_s: 0.2550 coco/bbox_mAP_m: 0.5000 coco/bbox_mAP_l: 0.6040 data_time: 0.0003 time: 0.0348 2024/03/27 16:08:45 - mmengine - INFO - Epoch(train) [46][ 50/925] lr: 9.1100e-05 eta: 3:38:51 time: 0.4906 data_time: 0.0732 memory: 5296 grad_norm: 951.2338 loss: 425.5689 loss_cls: 156.0603 loss_bbox: 126.9179 loss_dfl: 142.5908 2024/03/27 16:09:04 - mmengine - INFO - Epoch(train) [46][100/925] lr: 9.1100e-05 eta: 3:38:30 time: 0.3884 data_time: 0.0022 memory: 5136 grad_norm: 938.4154 loss: 420.5388 loss_cls: 153.1185 loss_bbox: 125.7643 loss_dfl: 141.6560 2024/03/27 16:09:24 - mmengine - INFO - Epoch(train) [46][150/925] lr: 9.1100e-05 eta: 3:38:10 time: 0.4010 data_time: 0.0023 memory: 5456 grad_norm: 1017.7338 loss: 418.9386 loss_cls: 150.0833 loss_bbox: 126.3654 loss_dfl: 142.4899 2024/03/27 16:09:44 - mmengine - INFO - Epoch(train) [46][200/925] lr: 9.1100e-05 eta: 3:37:49 time: 0.3904 data_time: 0.0023 memory: 5323 grad_norm: 1033.2257 loss: 427.2477 loss_cls: 154.9502 loss_bbox: 128.1518 loss_dfl: 144.1457 2024/03/27 16:10:04 - mmengine - INFO - Epoch(train) [46][250/925] lr: 9.1100e-05 eta: 3:37:29 time: 0.4050 data_time: 0.0022 memory: 5376 grad_norm: 984.8685 loss: 420.9535 loss_cls: 153.2102 loss_bbox: 126.3128 loss_dfl: 141.4304 2024/03/27 16:10:25 - mmengine - INFO - Epoch(train) [46][300/925] lr: 9.1100e-05 eta: 3:37:09 time: 0.4152 data_time: 0.0022 memory: 5203 grad_norm: inf loss: 423.6297 loss_cls: 152.8415 loss_bbox: 128.0545 loss_dfl: 142.7337 2024/03/27 16:10:45 - mmengine - INFO - Epoch(train) [46][350/925] lr: 9.1100e-05 eta: 3:36:48 time: 0.3985 data_time: 0.0022 memory: 5616 grad_norm: 960.4691 loss: 425.3890 loss_cls: 155.7124 loss_bbox: 126.9240 loss_dfl: 142.7526 2024/03/27 16:10:55 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:11:06 - mmengine - INFO - Epoch(train) [46][400/925] lr: 9.1100e-05 eta: 3:36:28 time: 0.4132 data_time: 0.0022 memory: 5563 grad_norm: 894.0700 loss: 425.4855 loss_cls: 154.3429 loss_bbox: 128.1733 loss_dfl: 142.9694 2024/03/27 16:11:26 - mmengine - INFO - Epoch(train) [46][450/925] lr: 9.1100e-05 eta: 3:36:08 time: 0.4104 data_time: 0.0022 memory: 5683 grad_norm: 851.9891 loss: 421.3768 loss_cls: 151.9110 loss_bbox: 127.0703 loss_dfl: 142.3955 2024/03/27 16:11:46 - mmengine - INFO - Epoch(train) [46][500/925] lr: 9.1100e-05 eta: 3:35:47 time: 0.3893 data_time: 0.0022 memory: 5136 grad_norm: 921.6990 loss: 429.2584 loss_cls: 156.0410 loss_bbox: 129.5315 loss_dfl: 143.6859 2024/03/27 16:12:06 - mmengine - INFO - Epoch(train) [46][550/925] lr: 9.1100e-05 eta: 3:35:26 time: 0.4029 data_time: 0.0022 memory: 5764 grad_norm: 939.5559 loss: 422.8610 loss_cls: 153.3918 loss_bbox: 127.4332 loss_dfl: 142.0360 2024/03/27 16:12:26 - mmengine - INFO - Epoch(train) [46][600/925] lr: 9.1100e-05 eta: 3:35:06 time: 0.3986 data_time: 0.0022 memory: 5710 grad_norm: 867.9743 loss: 427.9572 loss_cls: 156.4639 loss_bbox: 128.1311 loss_dfl: 143.3622 2024/03/27 16:12:46 - mmengine - INFO - Epoch(train) [46][650/925] lr: 9.1100e-05 eta: 3:34:45 time: 0.3934 data_time: 0.0022 memory: 5456 grad_norm: 880.3032 loss: 425.4359 loss_cls: 154.9180 loss_bbox: 127.5669 loss_dfl: 142.9510 2024/03/27 16:13:06 - mmengine - INFO - Epoch(train) [46][700/925] lr: 9.1100e-05 eta: 3:34:25 time: 0.4132 data_time: 0.0021 memory: 5203 grad_norm: 863.2947 loss: 429.0285 loss_cls: 157.0694 loss_bbox: 128.8318 loss_dfl: 143.1273 2024/03/27 16:13:26 - mmengine - INFO - Epoch(train) [46][750/925] lr: 9.1100e-05 eta: 3:34:04 time: 0.3897 data_time: 0.0023 memory: 5470 grad_norm: 861.7821 loss: 426.4539 loss_cls: 153.9817 loss_bbox: 129.7599 loss_dfl: 142.7123 2024/03/27 16:13:46 - mmengine - INFO - Epoch(train) [46][800/925] lr: 9.1100e-05 eta: 3:33:43 time: 0.3968 data_time: 0.0022 memory: 5510 grad_norm: 891.2367 loss: 421.3818 loss_cls: 150.9260 loss_bbox: 128.1665 loss_dfl: 142.2892 2024/03/27 16:14:05 - mmengine - INFO - Epoch(train) [46][850/925] lr: 9.1100e-05 eta: 3:33:22 time: 0.3843 data_time: 0.0022 memory: 5150 grad_norm: 916.6316 loss: 423.6195 loss_cls: 153.7549 loss_bbox: 127.6176 loss_dfl: 142.2470 2024/03/27 16:14:25 - mmengine - INFO - Epoch(train) [46][900/925] lr: 9.1100e-05 eta: 3:33:02 time: 0.3941 data_time: 0.0023 memory: 5630 grad_norm: 1094.4844 loss: 425.2122 loss_cls: 154.5658 loss_bbox: 128.2886 loss_dfl: 142.3578 2024/03/27 16:14:33 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:14:57 - mmengine - INFO - Epoch(train) [47][ 50/925] lr: 8.8625e-05 eta: 3:32:32 time: 0.4631 data_time: 0.0602 memory: 5550 grad_norm: 887.3140 loss: 424.1684 loss_cls: 153.6992 loss_bbox: 127.6973 loss_dfl: 142.7719 2024/03/27 16:15:16 - mmengine - INFO - Epoch(train) [47][100/925] lr: 8.8625e-05 eta: 3:32:11 time: 0.3880 data_time: 0.0022 memory: 5416 grad_norm: 965.1790 loss: 422.2917 loss_cls: 153.4589 loss_bbox: 126.7192 loss_dfl: 142.1136 2024/03/27 16:15:36 - mmengine - INFO - Epoch(train) [47][150/925] lr: 8.8625e-05 eta: 3:31:51 time: 0.4035 data_time: 0.0022 memory: 5390 grad_norm: 845.9218 loss: 412.5979 loss_cls: 149.3872 loss_bbox: 122.8007 loss_dfl: 140.4099 2024/03/27 16:15:56 - mmengine - INFO - Epoch(train) [47][200/925] lr: 8.8625e-05 eta: 3:31:30 time: 0.3977 data_time: 0.0021 memory: 5416 grad_norm: 974.4526 loss: 427.8554 loss_cls: 156.7622 loss_bbox: 127.8015 loss_dfl: 143.2917 2024/03/27 16:16:16 - mmengine - INFO - Epoch(train) [47][250/925] lr: 8.8625e-05 eta: 3:31:10 time: 0.4040 data_time: 0.0022 memory: 5523 grad_norm: 1006.5414 loss: 418.9545 loss_cls: 151.1562 loss_bbox: 125.9284 loss_dfl: 141.8698 2024/03/27 16:16:37 - mmengine - INFO - Epoch(train) [47][300/925] lr: 8.8625e-05 eta: 3:30:50 time: 0.4132 data_time: 0.0023 memory: 5430 grad_norm: 918.0920 loss: 420.7519 loss_cls: 152.5006 loss_bbox: 126.1334 loss_dfl: 142.1179 2024/03/27 16:16:58 - mmengine - INFO - Epoch(train) [47][350/925] lr: 8.8625e-05 eta: 3:30:29 time: 0.4112 data_time: 0.0019 memory: 5536 grad_norm: 876.9764 loss: 423.0314 loss_cls: 153.7841 loss_bbox: 127.1051 loss_dfl: 142.1422 2024/03/27 16:17:18 - mmengine - INFO - Epoch(train) [47][400/925] lr: 8.8625e-05 eta: 3:30:09 time: 0.3969 data_time: 0.0022 memory: 5536 grad_norm: 924.5113 loss: 425.0901 loss_cls: 154.1863 loss_bbox: 127.6757 loss_dfl: 143.2281 2024/03/27 16:17:38 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:17:38 - mmengine - INFO - Epoch(train) [47][450/925] lr: 8.8625e-05 eta: 3:29:49 time: 0.4127 data_time: 0.0021 memory: 5550 grad_norm: 938.8899 loss: 429.7672 loss_cls: 158.7139 loss_bbox: 128.2018 loss_dfl: 142.8515 2024/03/27 16:17:58 - mmengine - INFO - Epoch(train) [47][500/925] lr: 8.8625e-05 eta: 3:29:28 time: 0.3989 data_time: 0.0022 memory: 5523 grad_norm: 877.1257 loss: 427.0711 loss_cls: 155.6016 loss_bbox: 127.8843 loss_dfl: 143.5853 2024/03/27 16:18:19 - mmengine - INFO - Epoch(train) [47][550/925] lr: 8.8625e-05 eta: 3:29:08 time: 0.4102 data_time: 0.0023 memory: 5403 grad_norm: 940.3542 loss: 422.8259 loss_cls: 152.6234 loss_bbox: 127.1153 loss_dfl: 143.0872 2024/03/27 16:18:39 - mmengine - INFO - Epoch(train) [47][600/925] lr: 8.8625e-05 eta: 3:28:48 time: 0.4041 data_time: 0.0021 memory: 5336 grad_norm: 850.9329 loss: 422.3274 loss_cls: 153.9216 loss_bbox: 126.7019 loss_dfl: 141.7038 2024/03/27 16:18:59 - mmengine - INFO - Epoch(train) [47][650/925] lr: 8.8625e-05 eta: 3:28:27 time: 0.4003 data_time: 0.0023 memory: 5643 grad_norm: 886.4935 loss: 420.3577 loss_cls: 150.8517 loss_bbox: 126.7942 loss_dfl: 142.7119 2024/03/27 16:19:19 - mmengine - INFO - Epoch(train) [47][700/925] lr: 8.8625e-05 eta: 3:28:06 time: 0.3973 data_time: 0.0021 memory: 5736 grad_norm: 902.2534 loss: 419.9740 loss_cls: 153.2568 loss_bbox: 124.4525 loss_dfl: 142.2647 2024/03/27 16:19:39 - mmengine - INFO - Epoch(train) [47][750/925] lr: 8.8625e-05 eta: 3:27:46 time: 0.4011 data_time: 0.0022 memory: 5190 grad_norm: 856.0809 loss: 420.7465 loss_cls: 152.6419 loss_bbox: 126.6468 loss_dfl: 141.4578 2024/03/27 16:19:59 - mmengine - INFO - Epoch(train) [47][800/925] lr: 8.8625e-05 eta: 3:27:26 time: 0.4059 data_time: 0.0022 memory: 5350 grad_norm: 865.1768 loss: 422.7904 loss_cls: 152.9119 loss_bbox: 127.5508 loss_dfl: 142.3277 2024/03/27 16:20:19 - mmengine - INFO - Epoch(train) [47][850/925] lr: 8.8625e-05 eta: 3:27:05 time: 0.3936 data_time: 0.0024 memory: 5216 grad_norm: 938.7895 loss: 419.6091 loss_cls: 153.3024 loss_bbox: 124.6970 loss_dfl: 141.6097 2024/03/27 16:20:39 - mmengine - INFO - Epoch(train) [47][900/925] lr: 8.8625e-05 eta: 3:26:45 time: 0.4039 data_time: 0.0031 memory: 5603 grad_norm: 903.8764 loss: 421.9994 loss_cls: 151.4424 loss_bbox: 128.0492 loss_dfl: 142.5079 2024/03/27 16:20:49 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:21:13 - mmengine - INFO - Epoch(train) [48][ 50/925] lr: 8.6150e-05 eta: 3:26:16 time: 0.4853 data_time: 0.0638 memory: 5430 grad_norm: 899.8468 loss: 422.2821 loss_cls: 151.8962 loss_bbox: 127.7780 loss_dfl: 142.6078 2024/03/27 16:21:34 - mmengine - INFO - Epoch(train) [48][100/925] lr: 8.6150e-05 eta: 3:25:56 time: 0.4091 data_time: 0.0022 memory: 5803 grad_norm: 895.6895 loss: 417.9226 loss_cls: 151.2926 loss_bbox: 125.3792 loss_dfl: 141.2509 2024/03/27 16:21:55 - mmengine - INFO - Epoch(train) [48][150/925] lr: 8.6150e-05 eta: 3:25:36 time: 0.4185 data_time: 0.0022 memory: 5270 grad_norm: 894.7567 loss: 415.8365 loss_cls: 149.4496 loss_bbox: 125.0172 loss_dfl: 141.3697 2024/03/27 16:22:15 - mmengine - INFO - Epoch(train) [48][200/925] lr: 8.6150e-05 eta: 3:25:16 time: 0.4102 data_time: 0.0022 memory: 5390 grad_norm: 959.2447 loss: 430.7147 loss_cls: 158.1972 loss_bbox: 128.8967 loss_dfl: 143.6208 2024/03/27 16:22:35 - mmengine - INFO - Epoch(train) [48][250/925] lr: 8.6150e-05 eta: 3:24:55 time: 0.3979 data_time: 0.0021 memory: 5123 grad_norm: 848.3359 loss: 418.6330 loss_cls: 150.2726 loss_bbox: 126.7370 loss_dfl: 141.6234 2024/03/27 16:22:56 - mmengine - INFO - Epoch(train) [48][300/925] lr: 8.6150e-05 eta: 3:24:35 time: 0.4054 data_time: 0.0023 memory: 5403 grad_norm: 937.7400 loss: 425.6184 loss_cls: 155.1230 loss_bbox: 127.9531 loss_dfl: 142.5423 2024/03/27 16:23:16 - mmengine - INFO - Epoch(train) [48][350/925] lr: 8.6150e-05 eta: 3:24:15 time: 0.4082 data_time: 0.0024 memory: 5323 grad_norm: 1064.2893 loss: 416.3008 loss_cls: 149.8239 loss_bbox: 124.9962 loss_dfl: 141.4807 2024/03/27 16:23:36 - mmengine - INFO - Epoch(train) [48][400/925] lr: 8.6150e-05 eta: 3:23:54 time: 0.4010 data_time: 0.0021 memory: 5496 grad_norm: 915.5899 loss: 417.2687 loss_cls: 151.4492 loss_bbox: 124.5742 loss_dfl: 141.2454 2024/03/27 16:23:57 - mmengine - INFO - Epoch(train) [48][450/925] lr: 8.6150e-05 eta: 3:23:34 time: 0.4077 data_time: 0.0022 memory: 5856 grad_norm: 1075.4385 loss: 422.5457 loss_cls: 152.8029 loss_bbox: 127.3245 loss_dfl: 142.4184 2024/03/27 16:24:17 - mmengine - INFO - Epoch(train) [48][500/925] lr: 8.6150e-05 eta: 3:23:14 time: 0.4156 data_time: 0.0021 memory: 5430 grad_norm: 978.6473 loss: 429.0214 loss_cls: 156.8131 loss_bbox: 128.3953 loss_dfl: 143.8130 2024/03/27 16:24:28 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:24:38 - mmengine - INFO - Epoch(train) [48][550/925] lr: 8.6150e-05 eta: 3:22:54 time: 0.4086 data_time: 0.0021 memory: 5363 grad_norm: 881.8812 loss: 416.2008 loss_cls: 150.4871 loss_bbox: 124.9497 loss_dfl: 140.7641 2024/03/27 16:24:57 - mmengine - INFO - Epoch(train) [48][600/925] lr: 8.6150e-05 eta: 3:22:33 time: 0.3865 data_time: 0.0022 memory: 5776 grad_norm: 900.1540 loss: 420.7036 loss_cls: 152.1475 loss_bbox: 126.8968 loss_dfl: 141.6594 2024/03/27 16:25:18 - mmengine - INFO - Epoch(train) [48][650/925] lr: 8.6150e-05 eta: 3:22:13 time: 0.4125 data_time: 0.0022 memory: 5336 grad_norm: 868.0715 loss: 420.8949 loss_cls: 152.0316 loss_bbox: 127.0881 loss_dfl: 141.7751 2024/03/27 16:25:38 - mmengine - INFO - Epoch(train) [48][700/925] lr: 8.6150e-05 eta: 3:21:53 time: 0.4105 data_time: 0.0085 memory: 5470 grad_norm: inf loss: 426.7497 loss_cls: 153.6855 loss_bbox: 129.7321 loss_dfl: 143.3321 2024/03/27 16:25:59 - mmengine - INFO - Epoch(train) [48][750/925] lr: 8.6150e-05 eta: 3:21:32 time: 0.4077 data_time: 0.0032 memory: 5376 grad_norm: 910.4898 loss: 422.1241 loss_cls: 152.2208 loss_bbox: 128.2144 loss_dfl: 141.6889 2024/03/27 16:26:20 - mmengine - INFO - Epoch(train) [48][800/925] lr: 8.6150e-05 eta: 3:21:12 time: 0.4142 data_time: 0.0027 memory: 5403 grad_norm: 926.2746 loss: 421.8113 loss_cls: 153.1117 loss_bbox: 127.9270 loss_dfl: 140.7727 2024/03/27 16:26:40 - mmengine - INFO - Epoch(train) [48][850/925] lr: 8.6150e-05 eta: 3:20:52 time: 0.4154 data_time: 0.0024 memory: 5283 grad_norm: 987.1299 loss: 421.4280 loss_cls: 153.2739 loss_bbox: 126.3758 loss_dfl: 141.7783 2024/03/27 16:27:01 - mmengine - INFO - Epoch(train) [48][900/925] lr: 8.6150e-05 eta: 3:20:32 time: 0.4103 data_time: 0.0039 memory: 5616 grad_norm: 920.2233 loss: 419.5410 loss_cls: 151.7302 loss_bbox: 125.7045 loss_dfl: 142.1063 2024/03/27 16:27:10 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:27:36 - mmengine - INFO - Epoch(train) [49][ 50/925] lr: 8.3675e-05 eta: 3:20:04 time: 0.5033 data_time: 0.0758 memory: 5656 grad_norm: 905.0851 loss: 427.0368 loss_cls: 154.9443 loss_bbox: 129.1244 loss_dfl: 142.9681 2024/03/27 16:27:56 - mmengine - INFO - Epoch(train) [49][100/925] lr: 8.3675e-05 eta: 3:19:44 time: 0.4020 data_time: 0.0036 memory: 5736 grad_norm: 899.4506 loss: 421.1837 loss_cls: 152.2872 loss_bbox: 127.3141 loss_dfl: 141.5824 2024/03/27 16:28:16 - mmengine - INFO - Epoch(train) [49][150/925] lr: 8.3675e-05 eta: 3:19:23 time: 0.4030 data_time: 0.0029 memory: 5376 grad_norm: 876.0950 loss: 422.0858 loss_cls: 150.9167 loss_bbox: 128.2987 loss_dfl: 142.8704 2024/03/27 16:28:36 - mmengine - INFO - Epoch(train) [49][200/925] lr: 8.3675e-05 eta: 3:19:03 time: 0.4002 data_time: 0.0034 memory: 5376 grad_norm: 999.9294 loss: 421.8673 loss_cls: 151.5125 loss_bbox: 127.9355 loss_dfl: 142.4193 2024/03/27 16:28:56 - mmengine - INFO - Epoch(train) [49][250/925] lr: 8.3675e-05 eta: 3:18:42 time: 0.4009 data_time: 0.0033 memory: 5230 grad_norm: 942.9540 loss: 414.6594 loss_cls: 149.1771 loss_bbox: 125.0552 loss_dfl: 140.4271 2024/03/27 16:29:15 - mmengine - INFO - Epoch(train) [49][300/925] lr: 8.3675e-05 eta: 3:18:22 time: 0.3865 data_time: 0.0026 memory: 5430 grad_norm: 873.8855 loss: 413.7837 loss_cls: 148.1321 loss_bbox: 124.9657 loss_dfl: 140.6859 2024/03/27 16:29:35 - mmengine - INFO - Epoch(train) [49][350/925] lr: 8.3675e-05 eta: 3:18:01 time: 0.3948 data_time: 0.0032 memory: 5270 grad_norm: 882.4086 loss: 419.3672 loss_cls: 152.5732 loss_bbox: 125.3587 loss_dfl: 141.4353 2024/03/27 16:29:55 - mmengine - INFO - Epoch(train) [49][400/925] lr: 8.3675e-05 eta: 3:17:40 time: 0.3975 data_time: 0.0026 memory: 5470 grad_norm: 887.4550 loss: 424.2618 loss_cls: 153.7748 loss_bbox: 128.2393 loss_dfl: 142.2478 2024/03/27 16:30:14 - mmengine - INFO - Epoch(train) [49][450/925] lr: 8.3675e-05 eta: 3:17:19 time: 0.3766 data_time: 0.0023 memory: 5470 grad_norm: 995.5169 loss: 417.9341 loss_cls: 149.0750 loss_bbox: 127.7475 loss_dfl: 141.1116 2024/03/27 16:31:01 - mmengine - INFO - Epoch(train) [49][500/925] lr: 8.3675e-05 eta: 3:17:16 time: 0.9405 data_time: 0.1722 memory: 5216 grad_norm: 989.7809 loss: 419.5385 loss_cls: 150.3870 loss_bbox: 127.1032 loss_dfl: 142.0483 2024/03/27 16:31:22 - mmengine - INFO - Epoch(train) [49][550/925] lr: 8.3675e-05 eta: 3:16:56 time: 0.4176 data_time: 0.0023 memory: 5430 grad_norm: 878.7512 loss: 423.4027 loss_cls: 152.5792 loss_bbox: 127.9944 loss_dfl: 142.8291 2024/03/27 16:31:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:31:43 - mmengine - INFO - Epoch(train) [49][600/925] lr: 8.3675e-05 eta: 3:16:36 time: 0.4130 data_time: 0.0022 memory: 5203 grad_norm: 936.5829 loss: 422.0845 loss_cls: 155.0973 loss_bbox: 125.4447 loss_dfl: 141.5426 2024/03/27 16:32:03 - mmengine - INFO - Epoch(train) [49][650/925] lr: 8.3675e-05 eta: 3:16:15 time: 0.4015 data_time: 0.0025 memory: 5256 grad_norm: 933.9711 loss: 417.8559 loss_cls: 149.9001 loss_bbox: 126.3369 loss_dfl: 141.6190 2024/03/27 16:32:22 - mmengine - INFO - Epoch(train) [49][700/925] lr: 8.3675e-05 eta: 3:15:54 time: 0.3905 data_time: 0.0022 memory: 5443 grad_norm: 919.1097 loss: 420.3441 loss_cls: 149.5623 loss_bbox: 128.4569 loss_dfl: 142.3249 2024/03/27 16:32:43 - mmengine - INFO - Epoch(train) [49][750/925] lr: 8.3675e-05 eta: 3:15:34 time: 0.4115 data_time: 0.0023 memory: 5310 grad_norm: 939.9339 loss: 427.7487 loss_cls: 156.0296 loss_bbox: 128.6289 loss_dfl: 143.0902 2024/03/27 16:33:03 - mmengine - INFO - Epoch(train) [49][800/925] lr: 8.3675e-05 eta: 3:15:14 time: 0.3960 data_time: 0.0022 memory: 5270 grad_norm: 1080.3706 loss: 417.8277 loss_cls: 149.6143 loss_bbox: 125.9550 loss_dfl: 142.2585 2024/03/27 16:33:23 - mmengine - INFO - Epoch(train) [49][850/925] lr: 8.3675e-05 eta: 3:14:53 time: 0.3984 data_time: 0.0023 memory: 5190 grad_norm: 963.6704 loss: 417.0131 loss_cls: 150.7344 loss_bbox: 124.7164 loss_dfl: 141.5623 2024/03/27 16:33:43 - mmengine - INFO - Epoch(train) [49][900/925] lr: 8.3675e-05 eta: 3:14:33 time: 0.4066 data_time: 0.0024 memory: 5670 grad_norm: 895.7333 loss: 423.3582 loss_cls: 152.9691 loss_bbox: 127.7211 loss_dfl: 142.6680 2024/03/27 16:33:52 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:34:17 - mmengine - INFO - Epoch(train) [50][ 50/925] lr: 8.1200e-05 eta: 3:14:04 time: 0.4896 data_time: 0.0779 memory: 5710 grad_norm: 901.0455 loss: 424.1153 loss_cls: 153.8341 loss_bbox: 127.4952 loss_dfl: 142.7860 2024/03/27 16:34:37 - mmengine - INFO - Epoch(train) [50][100/925] lr: 8.1200e-05 eta: 3:13:44 time: 0.4032 data_time: 0.0026 memory: 5563 grad_norm: 918.3903 loss: 421.9885 loss_cls: 151.9792 loss_bbox: 127.9990 loss_dfl: 142.0104 2024/03/27 16:34:58 - mmengine - INFO - Epoch(train) [50][150/925] lr: 8.1200e-05 eta: 3:13:23 time: 0.4148 data_time: 0.0022 memory: 5283 grad_norm: 835.6184 loss: 423.3707 loss_cls: 152.8886 loss_bbox: 127.5920 loss_dfl: 142.8901 2024/03/27 16:35:18 - mmengine - INFO - Epoch(train) [50][200/925] lr: 8.1200e-05 eta: 3:13:03 time: 0.3992 data_time: 0.0020 memory: 5336 grad_norm: 1052.0063 loss: 423.0910 loss_cls: 153.4677 loss_bbox: 127.1778 loss_dfl: 142.4455 2024/03/27 16:35:39 - mmengine - INFO - Epoch(train) [50][250/925] lr: 8.1200e-05 eta: 3:12:43 time: 0.4148 data_time: 0.0022 memory: 5470 grad_norm: 855.1812 loss: 419.7453 loss_cls: 151.4507 loss_bbox: 126.6053 loss_dfl: 141.6892 2024/03/27 16:36:00 - mmengine - INFO - Epoch(train) [50][300/925] lr: 8.1200e-05 eta: 3:12:23 time: 0.4146 data_time: 0.0023 memory: 5096 grad_norm: 876.2622 loss: 422.7129 loss_cls: 154.0175 loss_bbox: 126.5664 loss_dfl: 142.1291 2024/03/27 16:36:20 - mmengine - INFO - Epoch(train) [50][350/925] lr: 8.1200e-05 eta: 3:12:02 time: 0.4091 data_time: 0.0021 memory: 5376 grad_norm: 960.2559 loss: 420.0185 loss_cls: 152.5848 loss_bbox: 126.0331 loss_dfl: 141.4005 2024/03/27 16:36:40 - mmengine - INFO - Epoch(train) [50][400/925] lr: 8.1200e-05 eta: 3:11:42 time: 0.3966 data_time: 0.0021 memory: 5376 grad_norm: 1005.0875 loss: 422.0219 loss_cls: 153.9982 loss_bbox: 126.1270 loss_dfl: 141.8967 2024/03/27 16:37:01 - mmengine - INFO - Epoch(train) [50][450/925] lr: 8.1200e-05 eta: 3:11:22 time: 0.4258 data_time: 0.0022 memory: 5416 grad_norm: 988.5942 loss: 420.8315 loss_cls: 152.0511 loss_bbox: 126.9826 loss_dfl: 141.7978 2024/03/27 16:37:21 - mmengine - INFO - Epoch(train) [50][500/925] lr: 8.1200e-05 eta: 3:11:01 time: 0.3948 data_time: 0.0021 memory: 5443 grad_norm: 902.8538 loss: 423.4828 loss_cls: 154.7593 loss_bbox: 126.3465 loss_dfl: 142.3770 2024/03/27 16:37:42 - mmengine - INFO - Epoch(train) [50][550/925] lr: 8.1200e-05 eta: 3:10:42 time: 0.4290 data_time: 0.0024 memory: 5350 grad_norm: 871.3800 loss: 422.5701 loss_cls: 152.8773 loss_bbox: 127.3836 loss_dfl: 142.3093 2024/03/27 16:38:03 - mmengine - INFO - Epoch(train) [50][600/925] lr: 8.1200e-05 eta: 3:10:21 time: 0.4080 data_time: 0.0021 memory: 5323 grad_norm: 1003.7386 loss: 419.5424 loss_cls: 149.7943 loss_bbox: 127.9938 loss_dfl: 141.7543 2024/03/27 16:38:24 - mmengine - INFO - Epoch(train) [50][650/925] lr: 8.1200e-05 eta: 3:10:01 time: 0.4121 data_time: 0.0025 memory: 5350 grad_norm: 975.8386 loss: 420.1285 loss_cls: 151.0896 loss_bbox: 126.7754 loss_dfl: 142.2635 2024/03/27 16:38:34 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:38:44 - mmengine - INFO - Epoch(train) [50][700/925] lr: 8.1200e-05 eta: 3:09:41 time: 0.4041 data_time: 0.0023 memory: 5310 grad_norm: 1004.2908 loss: 424.9785 loss_cls: 153.8758 loss_bbox: 128.5253 loss_dfl: 142.5774 2024/03/27 16:39:04 - mmengine - INFO - Epoch(train) [50][750/925] lr: 8.1200e-05 eta: 3:09:21 time: 0.4118 data_time: 0.0022 memory: 5670 grad_norm: 1044.2041 loss: 416.8378 loss_cls: 148.5092 loss_bbox: 126.6078 loss_dfl: 141.7208 2024/03/27 16:39:25 - mmengine - INFO - Epoch(train) [50][800/925] lr: 8.1200e-05 eta: 3:09:00 time: 0.4061 data_time: 0.0024 memory: 5350 grad_norm: 950.9523 loss: 416.2365 loss_cls: 149.2572 loss_bbox: 125.7226 loss_dfl: 141.2566 2024/03/27 16:39:45 - mmengine - INFO - Epoch(train) [50][850/925] lr: 8.1200e-05 eta: 3:08:40 time: 0.4051 data_time: 0.0022 memory: 5390 grad_norm: 883.2210 loss: 427.0591 loss_cls: 155.8140 loss_bbox: 128.6150 loss_dfl: 142.6301 2024/03/27 16:40:05 - mmengine - INFO - Epoch(train) [50][900/925] lr: 8.1200e-05 eta: 3:08:19 time: 0.4072 data_time: 0.0022 memory: 5310 grad_norm: 933.9850 loss: 416.7299 loss_cls: 149.4613 loss_bbox: 125.1131 loss_dfl: 142.1555 2024/03/27 16:40:15 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:40:15 - mmengine - INFO - Saving checkpoint at 50 epochs 2024/03/27 16:40:24 - mmengine - INFO - Epoch(val) [50][ 50/625] eta: 0:00:26 time: 0.0456 data_time: 0.0029 memory: 5336 2024/03/27 16:40:26 - mmengine - INFO - Epoch(val) [50][100/625] eta: 0:00:23 time: 0.0458 data_time: 0.0025 memory: 838 2024/03/27 16:40:28 - mmengine - INFO - Epoch(val) [50][150/625] eta: 0:00:21 time: 0.0440 data_time: 0.0006 memory: 838 2024/03/27 16:40:30 - mmengine - INFO - Epoch(val) [50][200/625] eta: 0:00:18 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 16:40:32 - mmengine - INFO - Epoch(val) [50][250/625] eta: 0:00:16 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 16:40:35 - mmengine - INFO - Epoch(val) [50][300/625] eta: 0:00:14 time: 0.0441 data_time: 0.0004 memory: 838 2024/03/27 16:40:37 - mmengine - INFO - Epoch(val) [50][350/625] eta: 0:00:12 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 16:40:39 - mmengine - INFO - Epoch(val) [50][400/625] eta: 0:00:09 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 16:40:41 - mmengine - INFO - Epoch(val) [50][450/625] eta: 0:00:07 time: 0.0439 data_time: 0.0004 memory: 838 2024/03/27 16:40:43 - mmengine - INFO - Epoch(val) [50][500/625] eta: 0:00:05 time: 0.0442 data_time: 0.0004 memory: 838 2024/03/27 16:40:45 - mmengine - INFO - Epoch(val) [50][550/625] eta: 0:00:03 time: 0.0403 data_time: 0.0004 memory: 838 2024/03/27 16:40:47 - mmengine - INFO - Epoch(val) [50][600/625] eta: 0:00:01 time: 0.0337 data_time: 0.0003 memory: 838 2024/03/27 16:41:01 - mmengine - INFO - Evaluating bbox... 2024/03/27 16:42:18 - mmengine - INFO - bbox_mAP_copypaste: 0.451 0.613 0.493 0.256 0.500 0.606 2024/03/27 16:42:19 - mmengine - INFO - Epoch(val) [50][625/625] coco/bbox_mAP: 0.4510 coco/bbox_mAP_50: 0.6130 coco/bbox_mAP_75: 0.4930 coco/bbox_mAP_s: 0.2560 coco/bbox_mAP_m: 0.5000 coco/bbox_mAP_l: 0.6060 data_time: 0.0003 time: 0.0345 2024/03/27 16:42:43 - mmengine - INFO - Epoch(train) [51][ 50/925] lr: 7.8725e-05 eta: 3:07:51 time: 0.4805 data_time: 0.0579 memory: 5256 grad_norm: inf loss: 425.0693 loss_cls: 154.0788 loss_bbox: 127.4936 loss_dfl: 143.4968 2024/03/27 16:43:03 - mmengine - INFO - Epoch(train) [51][100/925] lr: 7.8725e-05 eta: 3:07:30 time: 0.3995 data_time: 0.0021 memory: 5456 grad_norm: 921.7544 loss: 409.9791 loss_cls: 147.0871 loss_bbox: 123.1160 loss_dfl: 139.7759 2024/03/27 16:43:23 - mmengine - INFO - Epoch(train) [51][150/925] lr: 7.8725e-05 eta: 3:07:10 time: 0.3999 data_time: 0.0023 memory: 5483 grad_norm: 916.2368 loss: 424.0590 loss_cls: 154.1056 loss_bbox: 127.3974 loss_dfl: 142.5560 2024/03/27 16:43:43 - mmengine - INFO - Epoch(train) [51][200/925] lr: 7.8725e-05 eta: 3:06:49 time: 0.4056 data_time: 0.0022 memory: 5283 grad_norm: 943.5438 loss: 417.4739 loss_cls: 150.3641 loss_bbox: 126.0162 loss_dfl: 141.0936 2024/03/27 16:44:04 - mmengine - INFO - Epoch(train) [51][250/925] lr: 7.8725e-05 eta: 3:06:29 time: 0.4139 data_time: 0.0022 memory: 5536 grad_norm: 897.3882 loss: 424.3698 loss_cls: 154.0313 loss_bbox: 127.8575 loss_dfl: 142.4811 2024/03/27 16:44:24 - mmengine - INFO - Epoch(train) [51][300/925] lr: 7.8725e-05 eta: 3:06:09 time: 0.4031 data_time: 0.0020 memory: 5523 grad_norm: 907.6134 loss: 419.5501 loss_cls: 152.1736 loss_bbox: 125.5415 loss_dfl: 141.8349 2024/03/27 16:44:44 - mmengine - INFO - Epoch(train) [51][350/925] lr: 7.8725e-05 eta: 3:05:48 time: 0.4083 data_time: 0.0025 memory: 5350 grad_norm: 827.6487 loss: 420.7222 loss_cls: 152.3151 loss_bbox: 126.3073 loss_dfl: 142.0998 2024/03/27 16:45:05 - mmengine - INFO - Epoch(train) [51][400/925] lr: 7.8725e-05 eta: 3:05:28 time: 0.4133 data_time: 0.0020 memory: 5230 grad_norm: 861.3825 loss: 419.2371 loss_cls: 151.7636 loss_bbox: 125.9866 loss_dfl: 141.4869 2024/03/27 16:45:26 - mmengine - INFO - Epoch(train) [51][450/925] lr: 7.8725e-05 eta: 3:05:08 time: 0.4113 data_time: 0.0020 memory: 5550 grad_norm: 879.9726 loss: 414.8751 loss_cls: 148.6742 loss_bbox: 124.9860 loss_dfl: 141.2149 2024/03/27 16:45:46 - mmengine - INFO - Epoch(train) [51][500/925] lr: 7.8725e-05 eta: 3:04:48 time: 0.4124 data_time: 0.0021 memory: 5456 grad_norm: 866.5975 loss: 420.4729 loss_cls: 152.0068 loss_bbox: 126.7286 loss_dfl: 141.7376 2024/03/27 16:46:08 - mmengine - INFO - Epoch(train) [51][550/925] lr: 7.8725e-05 eta: 3:04:28 time: 0.4231 data_time: 0.0022 memory: 5470 grad_norm: 933.2158 loss: 415.2650 loss_cls: 150.3832 loss_bbox: 124.4152 loss_dfl: 140.4665 2024/03/27 16:46:27 - mmengine - INFO - Epoch(train) [51][600/925] lr: 7.8725e-05 eta: 3:04:07 time: 0.3941 data_time: 0.0021 memory: 5483 grad_norm: 1069.8438 loss: 417.3099 loss_cls: 148.5226 loss_bbox: 127.3030 loss_dfl: 141.4843 2024/03/27 16:46:48 - mmengine - INFO - Epoch(train) [51][650/925] lr: 7.8725e-05 eta: 3:03:47 time: 0.4065 data_time: 0.0020 memory: 5430 grad_norm: 937.4820 loss: 424.7088 loss_cls: 153.7500 loss_bbox: 128.3657 loss_dfl: 142.5931 2024/03/27 16:47:08 - mmengine - INFO - Epoch(train) [51][700/925] lr: 7.8725e-05 eta: 3:03:27 time: 0.4142 data_time: 0.0021 memory: 5683 grad_norm: 915.9129 loss: 422.6232 loss_cls: 152.1094 loss_bbox: 127.3607 loss_dfl: 143.1532 2024/03/27 16:47:28 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:47:28 - mmengine - INFO - Epoch(train) [51][750/925] lr: 7.8725e-05 eta: 3:03:06 time: 0.3999 data_time: 0.0023 memory: 5616 grad_norm: 876.7415 loss: 409.5728 loss_cls: 147.0122 loss_bbox: 123.6959 loss_dfl: 138.8646 2024/03/27 16:47:49 - mmengine - INFO - Epoch(train) [51][800/925] lr: 7.8725e-05 eta: 3:02:46 time: 0.4112 data_time: 0.0022 memory: 5390 grad_norm: 924.7864 loss: 422.4067 loss_cls: 151.6386 loss_bbox: 128.0224 loss_dfl: 142.7457 2024/03/27 16:48:10 - mmengine - INFO - Epoch(train) [51][850/925] lr: 7.8725e-05 eta: 3:02:26 time: 0.4125 data_time: 0.0023 memory: 5403 grad_norm: 909.0890 loss: 420.6408 loss_cls: 150.8012 loss_bbox: 128.2074 loss_dfl: 141.6322 2024/03/27 16:48:30 - mmengine - INFO - Epoch(train) [51][900/925] lr: 7.8725e-05 eta: 3:02:05 time: 0.4134 data_time: 0.0023 memory: 5576 grad_norm: 1000.8913 loss: 422.7511 loss_cls: 152.3671 loss_bbox: 128.2865 loss_dfl: 142.0975 2024/03/27 16:48:39 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:49:04 - mmengine - INFO - Epoch(train) [52][ 50/925] lr: 7.6250e-05 eta: 3:01:37 time: 0.4903 data_time: 0.0794 memory: 5603 grad_norm: 1037.6623 loss: 426.0617 loss_cls: 153.4695 loss_bbox: 129.4603 loss_dfl: 143.1318 2024/03/27 16:49:25 - mmengine - INFO - Epoch(train) [52][100/925] lr: 7.6250e-05 eta: 3:01:16 time: 0.4036 data_time: 0.0022 memory: 5310 grad_norm: 941.1873 loss: 415.8706 loss_cls: 149.6509 loss_bbox: 125.2628 loss_dfl: 140.9569 2024/03/27 16:49:45 - mmengine - INFO - Epoch(train) [52][150/925] lr: 7.6250e-05 eta: 3:00:56 time: 0.4006 data_time: 0.0022 memory: 5350 grad_norm: 881.7586 loss: 419.4673 loss_cls: 150.9090 loss_bbox: 126.7806 loss_dfl: 141.7777 2024/03/27 16:50:05 - mmengine - INFO - Epoch(train) [52][200/925] lr: 7.6250e-05 eta: 3:00:35 time: 0.4113 data_time: 0.0022 memory: 5403 grad_norm: 913.7694 loss: 419.8661 loss_cls: 150.0520 loss_bbox: 127.5289 loss_dfl: 142.2851 2024/03/27 16:50:25 - mmengine - INFO - Epoch(train) [52][250/925] lr: 7.6250e-05 eta: 3:00:15 time: 0.4003 data_time: 0.0022 memory: 5323 grad_norm: 869.9717 loss: 416.2338 loss_cls: 150.3062 loss_bbox: 125.4915 loss_dfl: 140.4362 2024/03/27 16:50:46 - mmengine - INFO - Epoch(train) [52][300/925] lr: 7.6250e-05 eta: 2:59:55 time: 0.4119 data_time: 0.0022 memory: 5203 grad_norm: 887.7617 loss: 413.4951 loss_cls: 148.7736 loss_bbox: 124.1084 loss_dfl: 140.6131 2024/03/27 16:51:07 - mmengine - INFO - Epoch(train) [52][350/925] lr: 7.6250e-05 eta: 2:59:35 time: 0.4143 data_time: 0.0021 memory: 5510 grad_norm: 989.4142 loss: 415.0832 loss_cls: 149.2635 loss_bbox: 125.1303 loss_dfl: 140.6894 2024/03/27 16:51:27 - mmengine - INFO - Epoch(train) [52][400/925] lr: 7.6250e-05 eta: 2:59:14 time: 0.4007 data_time: 0.0022 memory: 5363 grad_norm: 939.2268 loss: 418.7260 loss_cls: 151.8757 loss_bbox: 125.9556 loss_dfl: 140.8946 2024/03/27 16:51:48 - mmengine - INFO - Epoch(train) [52][450/925] lr: 7.6250e-05 eta: 2:58:54 time: 0.4180 data_time: 0.0023 memory: 5590 grad_norm: 875.0118 loss: 431.6024 loss_cls: 157.8968 loss_bbox: 129.8852 loss_dfl: 143.8203 2024/03/27 16:52:08 - mmengine - INFO - Epoch(train) [52][500/925] lr: 7.6250e-05 eta: 2:58:33 time: 0.3977 data_time: 0.0021 memory: 5256 grad_norm: 994.7432 loss: 419.7852 loss_cls: 152.0567 loss_bbox: 125.7440 loss_dfl: 141.9845 2024/03/27 16:52:27 - mmengine - INFO - Epoch(train) [52][550/925] lr: 7.6250e-05 eta: 2:58:13 time: 0.3897 data_time: 0.0022 memory: 5363 grad_norm: 917.2691 loss: 411.7159 loss_cls: 148.0398 loss_bbox: 124.3545 loss_dfl: 139.3216 2024/03/27 16:52:47 - mmengine - INFO - Epoch(train) [52][600/925] lr: 7.6250e-05 eta: 2:57:52 time: 0.4061 data_time: 0.0021 memory: 5256 grad_norm: 974.0324 loss: 418.4830 loss_cls: 150.2793 loss_bbox: 126.9328 loss_dfl: 141.2709 2024/03/27 16:53:08 - mmengine - INFO - Epoch(train) [52][650/925] lr: 7.6250e-05 eta: 2:57:32 time: 0.4022 data_time: 0.0021 memory: 5856 grad_norm: 962.4435 loss: 414.1287 loss_cls: 147.9086 loss_bbox: 125.4962 loss_dfl: 140.7238 2024/03/27 16:53:27 - mmengine - INFO - Epoch(train) [52][700/925] lr: 7.6250e-05 eta: 2:57:11 time: 0.3986 data_time: 0.0024 memory: 5136 grad_norm: 898.9312 loss: 421.9915 loss_cls: 153.1714 loss_bbox: 126.3317 loss_dfl: 142.4884 2024/03/27 16:53:48 - mmengine - INFO - Epoch(train) [52][750/925] lr: 7.6250e-05 eta: 2:56:51 time: 0.4117 data_time: 0.0022 memory: 5710 grad_norm: 883.9172 loss: 416.9794 loss_cls: 149.8609 loss_bbox: 126.0446 loss_dfl: 141.0739 2024/03/27 16:54:09 - mmengine - INFO - Epoch(train) [52][800/925] lr: 7.6250e-05 eta: 2:56:31 time: 0.4145 data_time: 0.0022 memory: 5190 grad_norm: 919.4455 loss: 418.0073 loss_cls: 151.1281 loss_bbox: 125.4136 loss_dfl: 141.4657 2024/03/27 16:54:19 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:54:29 - mmengine - INFO - Epoch(train) [52][850/925] lr: 7.6250e-05 eta: 2:56:10 time: 0.4072 data_time: 0.0022 memory: 5523 grad_norm: 939.5777 loss: 426.9240 loss_cls: 154.3076 loss_bbox: 129.5806 loss_dfl: 143.0358 2024/03/27 16:54:50 - mmengine - INFO - Epoch(train) [52][900/925] lr: 7.6250e-05 eta: 2:55:50 time: 0.4143 data_time: 0.0023 memory: 5764 grad_norm: 868.4052 loss: 425.5671 loss_cls: 154.9002 loss_bbox: 127.4889 loss_dfl: 143.1780 2024/03/27 16:54:59 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 16:55:25 - mmengine - INFO - Epoch(train) [53][ 50/925] lr: 7.3775e-05 eta: 2:55:22 time: 0.5018 data_time: 0.0757 memory: 5483 grad_norm: 928.6862 loss: 419.7057 loss_cls: 152.4093 loss_bbox: 124.7342 loss_dfl: 142.5622 2024/03/27 16:55:45 - mmengine - INFO - Epoch(train) [53][100/925] lr: 7.3775e-05 eta: 2:55:01 time: 0.3963 data_time: 0.0026 memory: 5496 grad_norm: 998.6560 loss: 413.1679 loss_cls: 147.5449 loss_bbox: 124.5654 loss_dfl: 141.0577 2024/03/27 16:56:05 - mmengine - INFO - Epoch(train) [53][150/925] lr: 7.3775e-05 eta: 2:54:41 time: 0.4100 data_time: 0.0023 memory: 5163 grad_norm: 894.7752 loss: 420.4975 loss_cls: 153.0661 loss_bbox: 125.0446 loss_dfl: 142.3868 2024/03/27 16:56:26 - mmengine - INFO - Epoch(train) [53][200/925] lr: 7.3775e-05 eta: 2:54:21 time: 0.4170 data_time: 0.0021 memory: 5470 grad_norm: 926.4019 loss: 422.0219 loss_cls: 151.9323 loss_bbox: 127.8902 loss_dfl: 142.1994 2024/03/27 16:56:46 - mmengine - INFO - Epoch(train) [53][250/925] lr: 7.3775e-05 eta: 2:54:00 time: 0.3977 data_time: 0.0022 memory: 5456 grad_norm: 905.3857 loss: 421.9543 loss_cls: 152.0197 loss_bbox: 127.3678 loss_dfl: 142.5668 2024/03/27 16:57:06 - mmengine - INFO - Epoch(train) [53][300/925] lr: 7.3775e-05 eta: 2:53:40 time: 0.4033 data_time: 0.0023 memory: 5816 grad_norm: 967.8710 loss: 415.3461 loss_cls: 149.1519 loss_bbox: 124.0275 loss_dfl: 142.1667 2024/03/27 16:57:27 - mmengine - INFO - Epoch(train) [53][350/925] lr: 7.3775e-05 eta: 2:53:19 time: 0.4099 data_time: 0.0022 memory: 5390 grad_norm: 1018.8556 loss: 415.4107 loss_cls: 149.9571 loss_bbox: 124.9178 loss_dfl: 140.5358 2024/03/27 16:57:47 - mmengine - INFO - Epoch(train) [53][400/925] lr: 7.3775e-05 eta: 2:52:59 time: 0.4062 data_time: 0.0024 memory: 5963 grad_norm: 888.4032 loss: 421.1483 loss_cls: 153.4596 loss_bbox: 126.2174 loss_dfl: 141.4713 2024/03/27 16:58:07 - mmengine - INFO - Epoch(train) [53][450/925] lr: 7.3775e-05 eta: 2:52:38 time: 0.3942 data_time: 0.0022 memory: 5230 grad_norm: 892.5565 loss: 425.7196 loss_cls: 154.2041 loss_bbox: 127.9874 loss_dfl: 143.5281 2024/03/27 16:58:27 - mmengine - INFO - Epoch(train) [53][500/925] lr: 7.3775e-05 eta: 2:52:18 time: 0.4045 data_time: 0.0027 memory: 5563 grad_norm: 932.8863 loss: 421.3990 loss_cls: 151.6561 loss_bbox: 127.3241 loss_dfl: 142.4188 2024/03/27 16:58:47 - mmengine - INFO - Epoch(train) [53][550/925] lr: 7.3775e-05 eta: 2:51:57 time: 0.3988 data_time: 0.0022 memory: 5270 grad_norm: 932.1692 loss: 418.4002 loss_cls: 150.5040 loss_bbox: 126.9497 loss_dfl: 140.9466 2024/03/27 16:59:07 - mmengine - INFO - Epoch(train) [53][600/925] lr: 7.3775e-05 eta: 2:51:37 time: 0.3943 data_time: 0.0025 memory: 5443 grad_norm: 943.8958 loss: 424.2582 loss_cls: 152.6934 loss_bbox: 128.6973 loss_dfl: 142.8676 2024/03/27 16:59:27 - mmengine - INFO - Epoch(train) [53][650/925] lr: 7.3775e-05 eta: 2:51:16 time: 0.4063 data_time: 0.0025 memory: 5510 grad_norm: 925.9312 loss: 420.3724 loss_cls: 150.0343 loss_bbox: 127.7004 loss_dfl: 142.6378 2024/03/27 16:59:47 - mmengine - INFO - Epoch(train) [53][700/925] lr: 7.3775e-05 eta: 2:50:56 time: 0.4013 data_time: 0.0025 memory: 5270 grad_norm: 1019.3743 loss: 426.8780 loss_cls: 153.8281 loss_bbox: 130.1397 loss_dfl: 142.9102 2024/03/27 17:00:07 - mmengine - INFO - Epoch(train) [53][750/925] lr: 7.3775e-05 eta: 2:50:35 time: 0.3971 data_time: 0.0022 memory: 5430 grad_norm: 905.2165 loss: 413.3832 loss_cls: 146.9449 loss_bbox: 125.4827 loss_dfl: 140.9555 2024/03/27 17:00:28 - mmengine - INFO - Epoch(train) [53][800/925] lr: 7.3775e-05 eta: 2:50:15 time: 0.4072 data_time: 0.0022 memory: 5296 grad_norm: 907.0180 loss: 415.1688 loss_cls: 148.6618 loss_bbox: 125.6174 loss_dfl: 140.8896 2024/03/27 17:00:48 - mmengine - INFO - Epoch(train) [53][850/925] lr: 7.3775e-05 eta: 2:49:55 time: 0.4107 data_time: 0.0023 memory: 5616 grad_norm: 949.0840 loss: 413.1991 loss_cls: 146.2971 loss_bbox: 125.2332 loss_dfl: 141.6687 2024/03/27 17:01:08 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:01:08 - mmengine - INFO - Epoch(train) [53][900/925] lr: 7.3775e-05 eta: 2:49:34 time: 0.4035 data_time: 0.0021 memory: 5443 grad_norm: 839.0242 loss: 415.5080 loss_cls: 149.2009 loss_bbox: 125.5049 loss_dfl: 140.8023 2024/03/27 17:01:18 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:01:43 - mmengine - INFO - Epoch(train) [54][ 50/925] lr: 7.1300e-05 eta: 2:49:06 time: 0.5080 data_time: 0.0677 memory: 5496 grad_norm: 921.5641 loss: 419.7493 loss_cls: 152.0036 loss_bbox: 126.3225 loss_dfl: 141.4232 2024/03/27 17:02:08 - mmengine - INFO - Epoch(train) [54][100/925] lr: 7.1300e-05 eta: 2:48:47 time: 0.4849 data_time: 0.0078 memory: 5523 grad_norm: inf loss: 414.1684 loss_cls: 148.3382 loss_bbox: 124.9961 loss_dfl: 140.8341 2024/03/27 17:02:28 - mmengine - INFO - Epoch(train) [54][150/925] lr: 7.1300e-05 eta: 2:48:27 time: 0.4112 data_time: 0.0025 memory: 5416 grad_norm: 866.9255 loss: 418.0704 loss_cls: 150.3949 loss_bbox: 126.0339 loss_dfl: 141.6416 2024/03/27 17:02:49 - mmengine - INFO - Epoch(train) [54][200/925] lr: 7.1300e-05 eta: 2:48:07 time: 0.4086 data_time: 0.0024 memory: 5350 grad_norm: 904.7565 loss: 421.3741 loss_cls: 152.3848 loss_bbox: 127.5343 loss_dfl: 141.4550 2024/03/27 17:03:09 - mmengine - INFO - Epoch(train) [54][250/925] lr: 7.1300e-05 eta: 2:47:46 time: 0.4097 data_time: 0.0023 memory: 5190 grad_norm: 945.9982 loss: 414.7649 loss_cls: 148.3052 loss_bbox: 125.6211 loss_dfl: 140.8386 2024/03/27 17:03:29 - mmengine - INFO - Epoch(train) [54][300/925] lr: 7.1300e-05 eta: 2:47:26 time: 0.4011 data_time: 0.0025 memory: 5576 grad_norm: 882.4968 loss: 421.1128 loss_cls: 152.9958 loss_bbox: 126.8703 loss_dfl: 141.2467 2024/03/27 17:03:49 - mmengine - INFO - Epoch(train) [54][350/925] lr: 7.1300e-05 eta: 2:47:05 time: 0.3893 data_time: 0.0024 memory: 5363 grad_norm: 911.6322 loss: 414.6050 loss_cls: 148.7628 loss_bbox: 125.3434 loss_dfl: 140.4988 2024/03/27 17:04:09 - mmengine - INFO - Epoch(train) [54][400/925] lr: 7.1300e-05 eta: 2:46:45 time: 0.3950 data_time: 0.0026 memory: 5710 grad_norm: 857.2283 loss: 418.1332 loss_cls: 152.5245 loss_bbox: 124.1672 loss_dfl: 141.4416 2024/03/27 17:04:29 - mmengine - INFO - Epoch(train) [54][450/925] lr: 7.1300e-05 eta: 2:46:24 time: 0.4096 data_time: 0.0023 memory: 5416 grad_norm: 964.1616 loss: 415.9354 loss_cls: 150.5816 loss_bbox: 124.3902 loss_dfl: 140.9636 2024/03/27 17:04:49 - mmengine - INFO - Epoch(train) [54][500/925] lr: 7.1300e-05 eta: 2:46:03 time: 0.3883 data_time: 0.0023 memory: 5510 grad_norm: 977.7844 loss: 419.9224 loss_cls: 151.3567 loss_bbox: 126.0853 loss_dfl: 142.4804 2024/03/27 17:05:09 - mmengine - INFO - Epoch(train) [54][550/925] lr: 7.1300e-05 eta: 2:45:43 time: 0.4095 data_time: 0.0023 memory: 5643 grad_norm: 983.9994 loss: 420.2130 loss_cls: 151.9565 loss_bbox: 126.6110 loss_dfl: 141.6454 2024/03/27 17:05:29 - mmengine - INFO - Epoch(train) [54][600/925] lr: 7.1300e-05 eta: 2:45:23 time: 0.4050 data_time: 0.0022 memory: 5230 grad_norm: 1090.1377 loss: 410.1462 loss_cls: 146.3590 loss_bbox: 123.6554 loss_dfl: 140.1318 2024/03/27 17:05:49 - mmengine - INFO - Epoch(train) [54][650/925] lr: 7.1300e-05 eta: 2:45:02 time: 0.3955 data_time: 0.0023 memory: 5083 grad_norm: 950.4853 loss: 415.6861 loss_cls: 149.3355 loss_bbox: 125.6736 loss_dfl: 140.6770 2024/03/27 17:06:09 - mmengine - INFO - Epoch(train) [54][700/925] lr: 7.1300e-05 eta: 2:44:41 time: 0.3954 data_time: 0.0023 memory: 5563 grad_norm: 900.3625 loss: 417.0877 loss_cls: 149.8048 loss_bbox: 125.8542 loss_dfl: 141.4287 2024/03/27 17:06:30 - mmengine - INFO - Epoch(train) [54][750/925] lr: 7.1300e-05 eta: 2:44:21 time: 0.4146 data_time: 0.0022 memory: 5643 grad_norm: 901.1570 loss: 419.6775 loss_cls: 150.8365 loss_bbox: 126.6663 loss_dfl: 142.1746 2024/03/27 17:06:50 - mmengine - INFO - Epoch(train) [54][800/925] lr: 7.1300e-05 eta: 2:44:01 time: 0.4075 data_time: 0.0025 memory: 5683 grad_norm: 983.2853 loss: 427.7587 loss_cls: 154.7052 loss_bbox: 130.2617 loss_dfl: 142.7918 2024/03/27 17:07:10 - mmengine - INFO - Epoch(train) [54][850/925] lr: 7.1300e-05 eta: 2:43:40 time: 0.3950 data_time: 0.0022 memory: 5430 grad_norm: 851.5718 loss: 425.2385 loss_cls: 152.6628 loss_bbox: 129.7281 loss_dfl: 142.8476 2024/03/27 17:07:30 - mmengine - INFO - Epoch(train) [54][900/925] lr: 7.1300e-05 eta: 2:43:20 time: 0.4058 data_time: 0.0022 memory: 5243 grad_norm: 1005.8211 loss: 414.2723 loss_cls: 148.3904 loss_bbox: 124.5698 loss_dfl: 141.3121 2024/03/27 17:07:40 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:08:04 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:08:04 - mmengine - INFO - Epoch(train) [55][ 50/925] lr: 6.8825e-05 eta: 2:42:51 time: 0.4765 data_time: 0.0630 memory: 5723 grad_norm: 990.1162 loss: 419.5356 loss_cls: 151.6831 loss_bbox: 125.9981 loss_dfl: 141.8545 2024/03/27 17:08:24 - mmengine - INFO - Epoch(train) [55][100/925] lr: 6.8825e-05 eta: 2:42:30 time: 0.3900 data_time: 0.0023 memory: 5163 grad_norm: 906.1924 loss: 408.5345 loss_cls: 145.9081 loss_bbox: 122.4989 loss_dfl: 140.1275 2024/03/27 17:08:45 - mmengine - INFO - Epoch(train) [55][150/925] lr: 6.8825e-05 eta: 2:42:10 time: 0.4227 data_time: 0.0023 memory: 5576 grad_norm: 927.3488 loss: 418.8418 loss_cls: 152.2347 loss_bbox: 125.1232 loss_dfl: 141.4840 2024/03/27 17:09:06 - mmengine - INFO - Epoch(train) [55][200/925] lr: 6.8825e-05 eta: 2:41:50 time: 0.4106 data_time: 0.0019 memory: 5336 grad_norm: 947.0785 loss: 413.0861 loss_cls: 148.4643 loss_bbox: 124.4681 loss_dfl: 140.1537 2024/03/27 17:09:27 - mmengine - INFO - Epoch(train) [55][250/925] lr: 6.8825e-05 eta: 2:41:30 time: 0.4201 data_time: 0.0054 memory: 5936 grad_norm: 1039.6607 loss: 420.4070 loss_cls: 150.9838 loss_bbox: 126.9461 loss_dfl: 142.4771 2024/03/27 17:09:48 - mmengine - INFO - Epoch(train) [55][300/925] lr: 6.8825e-05 eta: 2:41:10 time: 0.4176 data_time: 0.0024 memory: 5270 grad_norm: 910.5640 loss: 417.3940 loss_cls: 149.5367 loss_bbox: 125.8114 loss_dfl: 142.0459 2024/03/27 17:10:09 - mmengine - INFO - Epoch(train) [55][350/925] lr: 6.8825e-05 eta: 2:40:49 time: 0.4186 data_time: 0.0024 memory: 5363 grad_norm: 904.7413 loss: 414.2237 loss_cls: 146.7706 loss_bbox: 126.4110 loss_dfl: 141.0421 2024/03/27 17:10:29 - mmengine - INFO - Epoch(train) [55][400/925] lr: 6.8825e-05 eta: 2:40:29 time: 0.4095 data_time: 0.0025 memory: 5390 grad_norm: 907.5655 loss: 412.3825 loss_cls: 146.8664 loss_bbox: 124.5007 loss_dfl: 141.0155 2024/03/27 17:10:49 - mmengine - INFO - Epoch(train) [55][450/925] lr: 6.8825e-05 eta: 2:40:09 time: 0.4023 data_time: 0.0020 memory: 5710 grad_norm: 900.6478 loss: 418.5735 loss_cls: 151.5568 loss_bbox: 124.8710 loss_dfl: 142.1457 2024/03/27 17:11:10 - mmengine - INFO - Epoch(train) [55][500/925] lr: 6.8825e-05 eta: 2:39:48 time: 0.4095 data_time: 0.0022 memory: 5270 grad_norm: 950.3881 loss: 418.2501 loss_cls: 149.0870 loss_bbox: 127.9248 loss_dfl: 141.2383 2024/03/27 17:11:31 - mmengine - INFO - Epoch(train) [55][550/925] lr: 6.8825e-05 eta: 2:39:28 time: 0.4190 data_time: 0.0023 memory: 5363 grad_norm: 980.3134 loss: 425.8062 loss_cls: 156.2211 loss_bbox: 126.4985 loss_dfl: 143.0866 2024/03/27 17:11:51 - mmengine - INFO - Epoch(train) [55][600/925] lr: 6.8825e-05 eta: 2:39:08 time: 0.3983 data_time: 0.0023 memory: 5123 grad_norm: 908.7924 loss: 414.2622 loss_cls: 148.4480 loss_bbox: 124.6464 loss_dfl: 141.1677 2024/03/27 17:12:11 - mmengine - INFO - Epoch(train) [55][650/925] lr: 6.8825e-05 eta: 2:38:47 time: 0.4044 data_time: 0.0022 memory: 5510 grad_norm: 891.8678 loss: 422.6956 loss_cls: 153.4182 loss_bbox: 127.0273 loss_dfl: 142.2501 2024/03/27 17:12:31 - mmengine - INFO - Epoch(train) [55][700/925] lr: 6.8825e-05 eta: 2:38:27 time: 0.4109 data_time: 0.0022 memory: 5203 grad_norm: 860.2692 loss: 417.3768 loss_cls: 150.6442 loss_bbox: 125.8781 loss_dfl: 140.8545 2024/03/27 17:12:51 - mmengine - INFO - Epoch(train) [55][750/925] lr: 6.8825e-05 eta: 2:38:06 time: 0.3935 data_time: 0.0023 memory: 5456 grad_norm: 1032.0622 loss: 421.9459 loss_cls: 152.6358 loss_bbox: 127.3499 loss_dfl: 141.9602 2024/03/27 17:13:12 - mmengine - INFO - Epoch(train) [55][800/925] lr: 6.8825e-05 eta: 2:37:46 time: 0.4105 data_time: 0.0021 memory: 5456 grad_norm: 981.6683 loss: 417.1961 loss_cls: 150.5471 loss_bbox: 125.2428 loss_dfl: 141.4062 2024/03/27 17:13:33 - mmengine - INFO - Epoch(train) [55][850/925] lr: 6.8825e-05 eta: 2:37:26 time: 0.4183 data_time: 0.0024 memory: 5230 grad_norm: 878.4749 loss: 421.3851 loss_cls: 151.9549 loss_bbox: 127.3169 loss_dfl: 142.1133 2024/03/27 17:13:53 - mmengine - INFO - Epoch(train) [55][900/925] lr: 6.8825e-05 eta: 2:37:06 time: 0.4062 data_time: 0.0025 memory: 5470 grad_norm: 1016.5259 loss: 419.9915 loss_cls: 151.1147 loss_bbox: 126.6205 loss_dfl: 142.2563 2024/03/27 17:14:02 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:14:02 - mmengine - INFO - Saving checkpoint at 55 epochs 2024/03/27 17:14:11 - mmengine - INFO - Epoch(val) [55][ 50/625] eta: 0:00:25 time: 0.0439 data_time: 0.0010 memory: 5403 2024/03/27 17:14:13 - mmengine - INFO - Epoch(val) [55][100/625] eta: 0:00:23 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 17:14:16 - mmengine - INFO - Epoch(val) [55][150/625] eta: 0:00:21 time: 0.0454 data_time: 0.0004 memory: 838 2024/03/27 17:14:20 - mmengine - INFO - Epoch(val) [55][200/625] eta: 0:00:23 time: 0.0869 data_time: 0.0428 memory: 838 2024/03/27 17:14:22 - mmengine - INFO - Epoch(val) [55][250/625] eta: 0:00:19 time: 0.0439 data_time: 0.0004 memory: 838 2024/03/27 17:14:24 - mmengine - INFO - Epoch(val) [55][300/625] eta: 0:00:16 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 17:14:27 - mmengine - INFO - Epoch(val) [55][350/625] eta: 0:00:13 time: 0.0450 data_time: 0.0004 memory: 838 2024/03/27 17:14:29 - mmengine - INFO - Epoch(val) [55][400/625] eta: 0:00:11 time: 0.0422 data_time: 0.0003 memory: 838 2024/03/27 17:14:31 - mmengine - INFO - Epoch(val) [55][450/625] eta: 0:00:08 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 17:14:33 - mmengine - INFO - Epoch(val) [55][500/625] eta: 0:00:05 time: 0.0379 data_time: 0.0003 memory: 838 2024/03/27 17:14:35 - mmengine - INFO - Epoch(val) [55][550/625] eta: 0:00:03 time: 0.0349 data_time: 0.0003 memory: 838 2024/03/27 17:14:36 - mmengine - INFO - Epoch(val) [55][600/625] eta: 0:00:01 time: 0.0357 data_time: 0.0003 memory: 838 2024/03/27 17:14:50 - mmengine - INFO - Evaluating bbox... 2024/03/27 17:16:06 - mmengine - INFO - bbox_mAP_copypaste: 0.453 0.615 0.494 0.260 0.502 0.607 2024/03/27 17:16:07 - mmengine - INFO - Epoch(val) [55][625/625] coco/bbox_mAP: 0.4530 coco/bbox_mAP_50: 0.6150 coco/bbox_mAP_75: 0.4940 coco/bbox_mAP_s: 0.2600 coco/bbox_mAP_m: 0.5020 coco/bbox_mAP_l: 0.6070 data_time: 0.0003 time: 0.0354 2024/03/27 17:16:31 - mmengine - INFO - Epoch(train) [56][ 50/925] lr: 6.6350e-05 eta: 2:36:36 time: 0.4659 data_time: 0.0614 memory: 5190 grad_norm: 887.8038 loss: 419.2859 loss_cls: 150.5707 loss_bbox: 127.2607 loss_dfl: 141.4545 2024/03/27 17:16:50 - mmengine - INFO - Epoch(train) [56][100/925] lr: 6.6350e-05 eta: 2:36:15 time: 0.3921 data_time: 0.0025 memory: 5616 grad_norm: 1034.3522 loss: 419.7759 loss_cls: 152.0540 loss_bbox: 126.1503 loss_dfl: 141.5717 2024/03/27 17:17:00 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:17:11 - mmengine - INFO - Epoch(train) [56][150/925] lr: 6.6350e-05 eta: 2:35:55 time: 0.4066 data_time: 0.0023 memory: 5323 grad_norm: 854.7305 loss: 409.8365 loss_cls: 146.1817 loss_bbox: 123.8580 loss_dfl: 139.7968 2024/03/27 17:17:31 - mmengine - INFO - Epoch(train) [56][200/925] lr: 6.6350e-05 eta: 2:35:34 time: 0.4009 data_time: 0.0023 memory: 5510 grad_norm: 890.3282 loss: 420.7310 loss_cls: 150.3502 loss_bbox: 128.6023 loss_dfl: 141.7785 2024/03/27 17:17:51 - mmengine - INFO - Epoch(train) [56][250/925] lr: 6.6350e-05 eta: 2:35:14 time: 0.3991 data_time: 0.0023 memory: 5203 grad_norm: 920.0457 loss: 410.4016 loss_cls: 147.5170 loss_bbox: 122.7919 loss_dfl: 140.0926 2024/03/27 17:18:11 - mmengine - INFO - Epoch(train) [56][300/925] lr: 6.6350e-05 eta: 2:34:53 time: 0.3960 data_time: 0.0023 memory: 5270 grad_norm: 956.0098 loss: 405.9659 loss_cls: 142.7227 loss_bbox: 124.0639 loss_dfl: 139.1793 2024/03/27 17:18:30 - mmengine - INFO - Epoch(train) [56][350/925] lr: 6.6350e-05 eta: 2:34:32 time: 0.3927 data_time: 0.0023 memory: 5310 grad_norm: 942.1626 loss: 426.5354 loss_cls: 153.6961 loss_bbox: 129.6210 loss_dfl: 143.2183 2024/03/27 17:18:51 - mmengine - INFO - Epoch(train) [56][400/925] lr: 6.6350e-05 eta: 2:34:12 time: 0.4074 data_time: 0.0023 memory: 5350 grad_norm: 883.9058 loss: 419.1922 loss_cls: 150.5190 loss_bbox: 126.2541 loss_dfl: 142.4191 2024/03/27 17:19:10 - mmengine - INFO - Epoch(train) [56][450/925] lr: 6.6350e-05 eta: 2:33:51 time: 0.3934 data_time: 0.0022 memory: 5416 grad_norm: 942.4385 loss: 417.8448 loss_cls: 150.8411 loss_bbox: 125.4820 loss_dfl: 141.5216 2024/03/27 17:19:31 - mmengine - INFO - Epoch(train) [56][500/925] lr: 6.6350e-05 eta: 2:33:31 time: 0.4071 data_time: 0.0023 memory: 5523 grad_norm: 910.9267 loss: 416.8596 loss_cls: 150.5576 loss_bbox: 125.1017 loss_dfl: 141.2002 2024/03/27 17:19:52 - mmengine - INFO - Epoch(train) [56][550/925] lr: 6.6350e-05 eta: 2:33:11 time: 0.4164 data_time: 0.0023 memory: 5283 grad_norm: inf loss: 417.5820 loss_cls: 150.3190 loss_bbox: 125.8472 loss_dfl: 141.4159 2024/03/27 17:20:11 - mmengine - INFO - Epoch(train) [56][600/925] lr: 6.6350e-05 eta: 2:32:50 time: 0.3910 data_time: 0.0022 memory: 5416 grad_norm: 889.1318 loss: 416.7257 loss_cls: 149.7768 loss_bbox: 126.1856 loss_dfl: 140.7632 2024/03/27 17:20:32 - mmengine - INFO - Epoch(train) [56][650/925] lr: 6.6350e-05 eta: 2:32:30 time: 0.4104 data_time: 0.0023 memory: 5270 grad_norm: 880.1097 loss: 415.2781 loss_cls: 147.2352 loss_bbox: 126.5048 loss_dfl: 141.5381 2024/03/27 17:20:52 - mmengine - INFO - Epoch(train) [56][700/925] lr: 6.6350e-05 eta: 2:32:09 time: 0.4032 data_time: 0.0023 memory: 5456 grad_norm: 885.5119 loss: 416.0916 loss_cls: 150.7424 loss_bbox: 124.4595 loss_dfl: 140.8897 2024/03/27 17:21:11 - mmengine - INFO - Epoch(train) [56][750/925] lr: 6.6350e-05 eta: 2:31:49 time: 0.3862 data_time: 0.0040 memory: 5630 grad_norm: 919.8245 loss: 418.7098 loss_cls: 148.0904 loss_bbox: 128.4018 loss_dfl: 142.2176 2024/03/27 17:21:31 - mmengine - INFO - Epoch(train) [56][800/925] lr: 6.6350e-05 eta: 2:31:28 time: 0.3928 data_time: 0.0026 memory: 5350 grad_norm: 949.4072 loss: 427.8473 loss_cls: 155.7992 loss_bbox: 128.7958 loss_dfl: 143.2522 2024/03/27 17:21:51 - mmengine - INFO - Epoch(train) [56][850/925] lr: 6.6350e-05 eta: 2:31:07 time: 0.3922 data_time: 0.0037 memory: 5350 grad_norm: 886.5934 loss: 417.4614 loss_cls: 150.4747 loss_bbox: 125.4432 loss_dfl: 141.5436 2024/03/27 17:22:10 - mmengine - INFO - Epoch(train) [56][900/925] lr: 6.6350e-05 eta: 2:30:47 time: 0.3969 data_time: 0.0022 memory: 5283 grad_norm: 930.2453 loss: 419.0682 loss_cls: 150.6309 loss_bbox: 126.8804 loss_dfl: 141.5569 2024/03/27 17:22:18 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:22:43 - mmengine - INFO - Epoch(train) [57][ 50/925] lr: 6.3875e-05 eta: 2:30:17 time: 0.4803 data_time: 0.0586 memory: 5216 grad_norm: 878.4464 loss: 410.2018 loss_cls: 146.6780 loss_bbox: 123.3707 loss_dfl: 140.1530 2024/03/27 17:23:03 - mmengine - INFO - Epoch(train) [57][100/925] lr: 6.3875e-05 eta: 2:29:56 time: 0.3966 data_time: 0.0023 memory: 5776 grad_norm: 897.1093 loss: 412.7340 loss_cls: 146.8678 loss_bbox: 125.0149 loss_dfl: 140.8513 2024/03/27 17:23:23 - mmengine - INFO - Epoch(train) [57][150/925] lr: 6.3875e-05 eta: 2:29:36 time: 0.4066 data_time: 0.0024 memory: 5403 grad_norm: 900.9240 loss: 408.8484 loss_cls: 146.7341 loss_bbox: 122.2281 loss_dfl: 139.8862 2024/03/27 17:23:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:23:43 - mmengine - INFO - Epoch(train) [57][200/925] lr: 6.3875e-05 eta: 2:29:15 time: 0.3964 data_time: 0.0025 memory: 5456 grad_norm: 945.0372 loss: 418.2361 loss_cls: 148.9636 loss_bbox: 127.5613 loss_dfl: 141.7111 2024/03/27 17:24:03 - mmengine - INFO - Epoch(train) [57][250/925] lr: 6.3875e-05 eta: 2:28:55 time: 0.4045 data_time: 0.0023 memory: 5336 grad_norm: 958.9646 loss: 419.3018 loss_cls: 150.1600 loss_bbox: 127.0696 loss_dfl: 142.0722 2024/03/27 17:24:25 - mmengine - INFO - Epoch(train) [57][300/925] lr: 6.3875e-05 eta: 2:28:35 time: 0.4242 data_time: 0.0023 memory: 5336 grad_norm: 899.1726 loss: 412.3512 loss_cls: 148.7843 loss_bbox: 123.5376 loss_dfl: 140.0294 2024/03/27 17:24:44 - mmengine - INFO - Epoch(train) [57][350/925] lr: 6.3875e-05 eta: 2:28:14 time: 0.3910 data_time: 0.0022 memory: 5323 grad_norm: 898.6208 loss: 416.9371 loss_cls: 151.0632 loss_bbox: 124.9486 loss_dfl: 140.9253 2024/03/27 17:25:04 - mmengine - INFO - Epoch(train) [57][400/925] lr: 6.3875e-05 eta: 2:27:54 time: 0.4063 data_time: 0.0023 memory: 5136 grad_norm: 911.3336 loss: 420.1734 loss_cls: 150.4195 loss_bbox: 127.1919 loss_dfl: 142.5620 2024/03/27 17:25:24 - mmengine - INFO - Epoch(train) [57][450/925] lr: 6.3875e-05 eta: 2:27:33 time: 0.3983 data_time: 0.0021 memory: 5590 grad_norm: 935.1353 loss: 418.7238 loss_cls: 149.6801 loss_bbox: 127.0271 loss_dfl: 142.0167 2024/03/27 17:25:45 - mmengine - INFO - Epoch(train) [57][500/925] lr: 6.3875e-05 eta: 2:27:13 time: 0.4044 data_time: 0.0023 memory: 5403 grad_norm: 915.1674 loss: 421.9363 loss_cls: 152.5573 loss_bbox: 126.9071 loss_dfl: 142.4719 2024/03/27 17:26:04 - mmengine - INFO - Epoch(train) [57][550/925] lr: 6.3875e-05 eta: 2:26:52 time: 0.3898 data_time: 0.0022 memory: 5403 grad_norm: 996.5304 loss: 420.0859 loss_cls: 151.8628 loss_bbox: 125.8117 loss_dfl: 142.4114 2024/03/27 17:26:25 - mmengine - INFO - Epoch(train) [57][600/925] lr: 6.3875e-05 eta: 2:26:32 time: 0.4056 data_time: 0.0022 memory: 5456 grad_norm: 874.0725 loss: 417.8156 loss_cls: 150.2754 loss_bbox: 126.1706 loss_dfl: 141.3697 2024/03/27 17:26:45 - mmengine - INFO - Epoch(train) [57][650/925] lr: 6.3875e-05 eta: 2:26:11 time: 0.4012 data_time: 0.0024 memory: 5390 grad_norm: 931.9554 loss: 414.9416 loss_cls: 147.9494 loss_bbox: 125.4140 loss_dfl: 141.5782 2024/03/27 17:27:04 - mmengine - INFO - Epoch(train) [57][700/925] lr: 6.3875e-05 eta: 2:25:51 time: 0.3962 data_time: 0.0023 memory: 5256 grad_norm: 898.7791 loss: 410.6018 loss_cls: 147.1859 loss_bbox: 123.1341 loss_dfl: 140.2818 2024/03/27 17:27:24 - mmengine - INFO - Epoch(train) [57][750/925] lr: 6.3875e-05 eta: 2:25:30 time: 0.3974 data_time: 0.0023 memory: 5376 grad_norm: 998.8108 loss: 410.6959 loss_cls: 145.3857 loss_bbox: 124.9603 loss_dfl: 140.3499 2024/03/27 17:27:45 - mmengine - INFO - Epoch(train) [57][800/925] lr: 6.3875e-05 eta: 2:25:10 time: 0.4100 data_time: 0.0021 memory: 5856 grad_norm: 905.3807 loss: 415.0070 loss_cls: 149.1579 loss_bbox: 124.7746 loss_dfl: 141.0745 2024/03/27 17:28:05 - mmengine - INFO - Epoch(train) [57][850/925] lr: 6.3875e-05 eta: 2:24:49 time: 0.3977 data_time: 0.0023 memory: 5430 grad_norm: 916.0026 loss: 419.3209 loss_cls: 150.8280 loss_bbox: 127.1748 loss_dfl: 141.3181 2024/03/27 17:28:25 - mmengine - INFO - Epoch(train) [57][900/925] lr: 6.3875e-05 eta: 2:24:29 time: 0.3939 data_time: 0.0023 memory: 5310 grad_norm: 879.1865 loss: 417.6570 loss_cls: 150.4609 loss_bbox: 125.1567 loss_dfl: 142.0394 2024/03/27 17:28:34 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:29:00 - mmengine - INFO - Epoch(train) [58][ 50/925] lr: 6.1400e-05 eta: 2:24:00 time: 0.5073 data_time: 0.0593 memory: 5803 grad_norm: 896.8756 loss: 414.9565 loss_cls: 149.1660 loss_bbox: 124.6162 loss_dfl: 141.1743 2024/03/27 17:29:20 - mmengine - INFO - Epoch(train) [58][100/925] lr: 6.1400e-05 eta: 2:23:39 time: 0.3961 data_time: 0.0021 memory: 5576 grad_norm: 947.4826 loss: 417.3719 loss_cls: 151.8341 loss_bbox: 123.8520 loss_dfl: 141.6858 2024/03/27 17:29:39 - mmengine - INFO - Epoch(train) [58][150/925] lr: 6.1400e-05 eta: 2:23:19 time: 0.3950 data_time: 0.0025 memory: 5323 grad_norm: 903.4975 loss: 417.7148 loss_cls: 149.3290 loss_bbox: 126.4741 loss_dfl: 141.9117 2024/03/27 17:30:00 - mmengine - INFO - Epoch(train) [58][200/925] lr: 6.1400e-05 eta: 2:22:58 time: 0.4025 data_time: 0.0022 memory: 5416 grad_norm: 943.6931 loss: 417.0903 loss_cls: 149.1689 loss_bbox: 126.0604 loss_dfl: 141.8611 2024/03/27 17:30:20 - mmengine - INFO - Epoch(train) [58][250/925] lr: 6.1400e-05 eta: 2:22:38 time: 0.4012 data_time: 0.0024 memory: 5470 grad_norm: 863.5853 loss: 410.9648 loss_cls: 146.5401 loss_bbox: 124.3215 loss_dfl: 140.1033 2024/03/27 17:30:29 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:30:39 - mmengine - INFO - Epoch(train) [58][300/925] lr: 6.1400e-05 eta: 2:22:17 time: 0.3893 data_time: 0.0022 memory: 5456 grad_norm: 876.0166 loss: 419.2444 loss_cls: 150.1695 loss_bbox: 126.8803 loss_dfl: 142.1946 2024/03/27 17:30:59 - mmengine - INFO - Epoch(train) [58][350/925] lr: 6.1400e-05 eta: 2:21:57 time: 0.3968 data_time: 0.0025 memory: 5496 grad_norm: 1019.4981 loss: 413.3888 loss_cls: 147.2507 loss_bbox: 125.1295 loss_dfl: 141.0086 2024/03/27 17:31:19 - mmengine - INFO - Epoch(train) [58][400/925] lr: 6.1400e-05 eta: 2:21:36 time: 0.4065 data_time: 0.0024 memory: 5256 grad_norm: 904.0234 loss: 410.0557 loss_cls: 146.3698 loss_bbox: 123.9038 loss_dfl: 139.7820 2024/03/27 17:31:39 - mmengine - INFO - Epoch(train) [58][450/925] lr: 6.1400e-05 eta: 2:21:16 time: 0.3886 data_time: 0.0024 memory: 5243 grad_norm: 929.1226 loss: 422.5893 loss_cls: 153.4283 loss_bbox: 126.8129 loss_dfl: 142.3480 2024/03/27 17:31:59 - mmengine - INFO - Epoch(train) [58][500/925] lr: 6.1400e-05 eta: 2:20:55 time: 0.3959 data_time: 0.0023 memory: 5363 grad_norm: 849.9643 loss: 421.1362 loss_cls: 151.1308 loss_bbox: 127.3811 loss_dfl: 142.6244 2024/03/27 17:32:19 - mmengine - INFO - Epoch(train) [58][550/925] lr: 6.1400e-05 eta: 2:20:35 time: 0.4153 data_time: 0.0022 memory: 5256 grad_norm: 962.9806 loss: 417.5926 loss_cls: 149.1456 loss_bbox: 126.8075 loss_dfl: 141.6395 2024/03/27 17:32:40 - mmengine - INFO - Epoch(train) [58][600/925] lr: 6.1400e-05 eta: 2:20:14 time: 0.4015 data_time: 0.0022 memory: 5296 grad_norm: 894.0104 loss: 411.1947 loss_cls: 145.7135 loss_bbox: 125.2488 loss_dfl: 140.2323 2024/03/27 17:32:59 - mmengine - INFO - Epoch(train) [58][650/925] lr: 6.1400e-05 eta: 2:19:54 time: 0.3926 data_time: 0.0022 memory: 5216 grad_norm: 935.3963 loss: 416.6443 loss_cls: 148.9263 loss_bbox: 126.3143 loss_dfl: 141.4037 2024/03/27 17:33:20 - mmengine - INFO - Epoch(train) [58][700/925] lr: 6.1400e-05 eta: 2:19:34 time: 0.4221 data_time: 0.0022 memory: 5523 grad_norm: 902.4571 loss: 421.2943 loss_cls: 150.5118 loss_bbox: 128.0758 loss_dfl: 142.7068 2024/03/27 17:33:41 - mmengine - INFO - Epoch(train) [58][750/925] lr: 6.1400e-05 eta: 2:19:13 time: 0.4172 data_time: 0.0022 memory: 5430 grad_norm: 947.0579 loss: 409.9015 loss_cls: 147.1314 loss_bbox: 122.6911 loss_dfl: 140.0790 2024/03/27 17:34:01 - mmengine - INFO - Epoch(train) [58][800/925] lr: 6.1400e-05 eta: 2:18:53 time: 0.3905 data_time: 0.0023 memory: 5443 grad_norm: 952.7973 loss: 412.3355 loss_cls: 147.0121 loss_bbox: 124.1069 loss_dfl: 141.2165 2024/03/27 17:34:22 - mmengine - INFO - Epoch(train) [58][850/925] lr: 6.1400e-05 eta: 2:18:33 time: 0.4144 data_time: 0.0022 memory: 5323 grad_norm: 949.7591 loss: 410.9373 loss_cls: 147.1553 loss_bbox: 123.0395 loss_dfl: 140.7426 2024/03/27 17:34:42 - mmengine - INFO - Epoch(train) [58][900/925] lr: 6.1400e-05 eta: 2:18:12 time: 0.4109 data_time: 0.0022 memory: 5256 grad_norm: 930.8299 loss: 417.1460 loss_cls: 150.4208 loss_bbox: 125.5074 loss_dfl: 141.2177 2024/03/27 17:34:51 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:35:16 - mmengine - INFO - Epoch(train) [59][ 50/925] lr: 5.8925e-05 eta: 2:17:43 time: 0.4792 data_time: 0.0630 memory: 5696 grad_norm: 885.4069 loss: 415.2280 loss_cls: 148.8126 loss_bbox: 124.9233 loss_dfl: 141.4921 2024/03/27 17:35:36 - mmengine - INFO - Epoch(train) [59][100/925] lr: 5.8925e-05 eta: 2:17:22 time: 0.3979 data_time: 0.0021 memory: 5550 grad_norm: 930.1060 loss: 408.1499 loss_cls: 143.7927 loss_bbox: 124.4765 loss_dfl: 139.8807 2024/03/27 17:35:56 - mmengine - INFO - Epoch(train) [59][150/925] lr: 5.8925e-05 eta: 2:17:02 time: 0.4116 data_time: 0.0021 memory: 5470 grad_norm: 967.4855 loss: 412.6711 loss_cls: 148.3421 loss_bbox: 123.8613 loss_dfl: 140.4678 2024/03/27 17:36:16 - mmengine - INFO - Epoch(train) [59][200/925] lr: 5.8925e-05 eta: 2:16:41 time: 0.3964 data_time: 0.0022 memory: 5363 grad_norm: 1017.1760 loss: 408.9048 loss_cls: 145.5920 loss_bbox: 123.4767 loss_dfl: 139.8361 2024/03/27 17:36:37 - mmengine - INFO - Epoch(train) [59][250/925] lr: 5.8925e-05 eta: 2:16:21 time: 0.4097 data_time: 0.0022 memory: 5536 grad_norm: 972.7553 loss: 415.4321 loss_cls: 148.6011 loss_bbox: 125.8190 loss_dfl: 141.0120 2024/03/27 17:36:58 - mmengine - INFO - Epoch(train) [59][300/925] lr: 5.8925e-05 eta: 2:16:01 time: 0.4208 data_time: 0.0022 memory: 5550 grad_norm: 864.7909 loss: 414.6766 loss_cls: 148.7456 loss_bbox: 125.1076 loss_dfl: 140.8234 2024/03/27 17:37:18 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:37:18 - mmengine - INFO - Epoch(train) [59][350/925] lr: 5.8925e-05 eta: 2:15:41 time: 0.4046 data_time: 0.0021 memory: 5536 grad_norm: 881.0841 loss: 417.0741 loss_cls: 148.7561 loss_bbox: 126.6601 loss_dfl: 141.6579 2024/03/27 17:37:38 - mmengine - INFO - Epoch(train) [59][400/925] lr: 5.8925e-05 eta: 2:15:20 time: 0.4040 data_time: 0.0022 memory: 5443 grad_norm: 948.3873 loss: 407.4651 loss_cls: 146.1073 loss_bbox: 121.6920 loss_dfl: 139.6657 2024/03/27 17:37:59 - mmengine - INFO - Epoch(train) [59][450/925] lr: 5.8925e-05 eta: 2:15:00 time: 0.4240 data_time: 0.0023 memory: 5790 grad_norm: 1012.7374 loss: 413.2904 loss_cls: 148.2051 loss_bbox: 124.8269 loss_dfl: 140.2584 2024/03/27 17:38:20 - mmengine - INFO - Epoch(train) [59][500/925] lr: 5.8925e-05 eta: 2:14:40 time: 0.4124 data_time: 0.0024 memory: 5323 grad_norm: 937.0601 loss: 413.6328 loss_cls: 148.9640 loss_bbox: 124.1765 loss_dfl: 140.4922 2024/03/27 17:38:40 - mmengine - INFO - Epoch(train) [59][550/925] lr: 5.8925e-05 eta: 2:14:19 time: 0.3901 data_time: 0.0019 memory: 5230 grad_norm: 907.7226 loss: 415.1845 loss_cls: 149.5148 loss_bbox: 125.2593 loss_dfl: 140.4105 2024/03/27 17:39:00 - mmengine - INFO - Epoch(train) [59][600/925] lr: 5.8925e-05 eta: 2:13:59 time: 0.4163 data_time: 0.0020 memory: 5670 grad_norm: inf loss: 421.4364 loss_cls: 151.3405 loss_bbox: 127.8082 loss_dfl: 142.2878 2024/03/27 17:39:21 - mmengine - INFO - Epoch(train) [59][650/925] lr: 5.8925e-05 eta: 2:13:39 time: 0.4083 data_time: 0.0022 memory: 5456 grad_norm: 916.7942 loss: 412.3315 loss_cls: 146.8161 loss_bbox: 124.8673 loss_dfl: 140.6481 2024/03/27 17:39:41 - mmengine - INFO - Epoch(train) [59][700/925] lr: 5.8925e-05 eta: 2:13:18 time: 0.3983 data_time: 0.0024 memory: 5443 grad_norm: 1058.0858 loss: 408.5180 loss_cls: 146.2205 loss_bbox: 122.6703 loss_dfl: 139.6272 2024/03/27 17:40:01 - mmengine - INFO - Epoch(train) [59][750/925] lr: 5.8925e-05 eta: 2:12:58 time: 0.4013 data_time: 0.0021 memory: 6216 grad_norm: 863.2311 loss: 411.8560 loss_cls: 147.7519 loss_bbox: 123.5980 loss_dfl: 140.5061 2024/03/27 17:40:21 - mmengine - INFO - Epoch(train) [59][800/925] lr: 5.8925e-05 eta: 2:12:37 time: 0.4094 data_time: 0.0024 memory: 5136 grad_norm: 953.3274 loss: 412.6499 loss_cls: 148.0896 loss_bbox: 123.2045 loss_dfl: 141.3558 2024/03/27 17:40:41 - mmengine - INFO - Epoch(train) [59][850/925] lr: 5.8925e-05 eta: 2:12:17 time: 0.3975 data_time: 0.0024 memory: 5403 grad_norm: 938.4111 loss: 417.5461 loss_cls: 151.1331 loss_bbox: 125.2926 loss_dfl: 141.1205 2024/03/27 17:41:01 - mmengine - INFO - Epoch(train) [59][900/925] lr: 5.8925e-05 eta: 2:11:56 time: 0.4007 data_time: 0.0024 memory: 5510 grad_norm: 849.9387 loss: 413.7304 loss_cls: 148.5501 loss_bbox: 124.3690 loss_dfl: 140.8112 2024/03/27 17:41:11 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:41:39 - mmengine - INFO - Epoch(train) [60][ 50/925] lr: 5.6450e-05 eta: 2:11:28 time: 0.5524 data_time: 0.1369 memory: 5456 grad_norm: 919.6885 loss: 416.5760 loss_cls: 149.0269 loss_bbox: 126.1846 loss_dfl: 141.3644 2024/03/27 17:41:58 - mmengine - INFO - Epoch(train) [60][100/925] lr: 5.6450e-05 eta: 2:11:07 time: 0.3737 data_time: 0.0027 memory: 5936 grad_norm: 902.2039 loss: 420.1032 loss_cls: 151.7157 loss_bbox: 126.1264 loss_dfl: 142.2610 2024/03/27 17:42:18 - mmengine - INFO - Epoch(train) [60][150/925] lr: 5.6450e-05 eta: 2:10:47 time: 0.3960 data_time: 0.0024 memory: 5216 grad_norm: 833.6082 loss: 412.8895 loss_cls: 147.4865 loss_bbox: 124.6947 loss_dfl: 140.7082 2024/03/27 17:42:38 - mmengine - INFO - Epoch(train) [60][200/925] lr: 5.6450e-05 eta: 2:10:27 time: 0.4093 data_time: 0.0025 memory: 5283 grad_norm: 880.5529 loss: 414.5522 loss_cls: 147.6499 loss_bbox: 125.3704 loss_dfl: 141.5319 2024/03/27 17:42:58 - mmengine - INFO - Epoch(train) [60][250/925] lr: 5.6450e-05 eta: 2:10:06 time: 0.3968 data_time: 0.0024 memory: 5256 grad_norm: 911.5921 loss: 406.2036 loss_cls: 144.1644 loss_bbox: 122.5516 loss_dfl: 139.4877 2024/03/27 17:43:18 - mmengine - INFO - Epoch(train) [60][300/925] lr: 5.6450e-05 eta: 2:09:45 time: 0.3908 data_time: 0.0022 memory: 5110 grad_norm: 909.2363 loss: 408.8369 loss_cls: 145.5535 loss_bbox: 123.1624 loss_dfl: 140.1210 2024/03/27 17:43:38 - mmengine - INFO - Epoch(train) [60][350/925] lr: 5.6450e-05 eta: 2:09:25 time: 0.4133 data_time: 0.0022 memory: 5216 grad_norm: 901.7686 loss: 415.0678 loss_cls: 147.8126 loss_bbox: 126.1231 loss_dfl: 141.1322 2024/03/27 17:43:58 - mmengine - INFO - Epoch(train) [60][400/925] lr: 5.6450e-05 eta: 2:09:04 time: 0.3842 data_time: 0.0023 memory: 5736 grad_norm: 874.8004 loss: 415.4167 loss_cls: 149.6528 loss_bbox: 124.9189 loss_dfl: 140.8450 2024/03/27 17:44:08 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:44:17 - mmengine - INFO - Epoch(train) [60][450/925] lr: 5.6450e-05 eta: 2:08:43 time: 0.3775 data_time: 0.0023 memory: 5310 grad_norm: 982.8831 loss: 416.8799 loss_cls: 148.2209 loss_bbox: 127.4611 loss_dfl: 141.1980 2024/03/27 17:44:37 - mmengine - INFO - Epoch(train) [60][500/925] lr: 5.6450e-05 eta: 2:08:23 time: 0.4108 data_time: 0.0023 memory: 5310 grad_norm: 890.9761 loss: 414.2455 loss_cls: 148.0266 loss_bbox: 125.6127 loss_dfl: 140.6062 2024/03/27 17:44:57 - mmengine - INFO - Epoch(train) [60][550/925] lr: 5.6450e-05 eta: 2:08:03 time: 0.3998 data_time: 0.0023 memory: 5523 grad_norm: 895.1842 loss: 413.6607 loss_cls: 146.8261 loss_bbox: 125.1274 loss_dfl: 141.7073 2024/03/27 17:45:17 - mmengine - INFO - Epoch(train) [60][600/925] lr: 5.6450e-05 eta: 2:07:42 time: 0.3857 data_time: 0.0023 memory: 5483 grad_norm: 852.8124 loss: 412.7255 loss_cls: 147.9857 loss_bbox: 124.4565 loss_dfl: 140.2833 2024/03/27 17:45:36 - mmengine - INFO - Epoch(train) [60][650/925] lr: 5.6450e-05 eta: 2:07:21 time: 0.3897 data_time: 0.0024 memory: 5416 grad_norm: 955.3725 loss: 410.9184 loss_cls: 146.8858 loss_bbox: 123.8666 loss_dfl: 140.1660 2024/03/27 17:45:56 - mmengine - INFO - Epoch(train) [60][700/925] lr: 5.6450e-05 eta: 2:07:01 time: 0.3994 data_time: 0.0023 memory: 5203 grad_norm: 940.0611 loss: 421.1939 loss_cls: 153.9755 loss_bbox: 124.6195 loss_dfl: 142.5989 2024/03/27 17:46:16 - mmengine - INFO - Epoch(train) [60][750/925] lr: 5.6450e-05 eta: 2:06:40 time: 0.3915 data_time: 0.0022 memory: 5190 grad_norm: 877.6889 loss: 408.7255 loss_cls: 145.9213 loss_bbox: 123.8755 loss_dfl: 138.9287 2024/03/27 17:46:36 - mmengine - INFO - Epoch(train) [60][800/925] lr: 5.6450e-05 eta: 2:06:20 time: 0.3955 data_time: 0.0023 memory: 5670 grad_norm: 920.4618 loss: 417.7772 loss_cls: 149.5190 loss_bbox: 126.6712 loss_dfl: 141.5869 2024/03/27 17:46:56 - mmengine - INFO - Epoch(train) [60][850/925] lr: 5.6450e-05 eta: 2:05:59 time: 0.4095 data_time: 0.0023 memory: 5523 grad_norm: 903.3856 loss: 413.0445 loss_cls: 147.5345 loss_bbox: 124.7292 loss_dfl: 140.7808 2024/03/27 17:47:16 - mmengine - INFO - Epoch(train) [60][900/925] lr: 5.6450e-05 eta: 2:05:39 time: 0.3964 data_time: 0.0023 memory: 5230 grad_norm: 930.1307 loss: 414.1305 loss_cls: 148.5797 loss_bbox: 124.6047 loss_dfl: 140.9461 2024/03/27 17:47:24 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:47:24 - mmengine - INFO - Saving checkpoint at 60 epochs 2024/03/27 17:47:33 - mmengine - INFO - Epoch(val) [60][ 50/625] eta: 0:00:25 time: 0.0452 data_time: 0.0009 memory: 5443 2024/03/27 17:47:35 - mmengine - INFO - Epoch(val) [60][100/625] eta: 0:00:23 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 17:47:37 - mmengine - INFO - Epoch(val) [60][150/625] eta: 0:00:21 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 17:47:39 - mmengine - INFO - Epoch(val) [60][200/625] eta: 0:00:18 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 17:47:42 - mmengine - INFO - Epoch(val) [60][250/625] eta: 0:00:16 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 17:47:44 - mmengine - INFO - Epoch(val) [60][300/625] eta: 0:00:14 time: 0.0427 data_time: 0.0004 memory: 838 2024/03/27 17:47:46 - mmengine - INFO - Epoch(val) [60][350/625] eta: 0:00:12 time: 0.0439 data_time: 0.0004 memory: 838 2024/03/27 17:47:48 - mmengine - INFO - Epoch(val) [60][400/625] eta: 0:00:09 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 17:47:50 - mmengine - INFO - Epoch(val) [60][450/625] eta: 0:00:07 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 17:47:52 - mmengine - INFO - Epoch(val) [60][500/625] eta: 0:00:05 time: 0.0398 data_time: 0.0004 memory: 838 2024/03/27 17:47:54 - mmengine - INFO - Epoch(val) [60][550/625] eta: 0:00:03 time: 0.0372 data_time: 0.0022 memory: 838 2024/03/27 17:47:56 - mmengine - INFO - Epoch(val) [60][600/625] eta: 0:00:01 time: 0.0358 data_time: 0.0003 memory: 838 2024/03/27 17:48:09 - mmengine - INFO - Evaluating bbox... 2024/03/27 17:49:24 - mmengine - INFO - bbox_mAP_copypaste: 0.454 0.616 0.496 0.264 0.503 0.611 2024/03/27 17:49:26 - mmengine - INFO - Epoch(val) [60][625/625] coco/bbox_mAP: 0.4540 coco/bbox_mAP_50: 0.6160 coco/bbox_mAP_75: 0.4960 coco/bbox_mAP_s: 0.2640 coco/bbox_mAP_m: 0.5030 coco/bbox_mAP_l: 0.6110 data_time: 0.0003 time: 0.0356 2024/03/27 17:49:49 - mmengine - INFO - Epoch(train) [61][ 50/925] lr: 5.3975e-05 eta: 2:05:09 time: 0.4766 data_time: 0.0827 memory: 5683 grad_norm: 878.1329 loss: 413.5962 loss_cls: 147.1060 loss_bbox: 125.7258 loss_dfl: 140.7644 2024/03/27 17:50:10 - mmengine - INFO - Epoch(train) [61][100/925] lr: 5.3975e-05 eta: 2:04:48 time: 0.4080 data_time: 0.0026 memory: 5390 grad_norm: 986.9555 loss: 409.6835 loss_cls: 146.5761 loss_bbox: 122.8314 loss_dfl: 140.2761 2024/03/27 17:50:30 - mmengine - INFO - Epoch(train) [61][150/925] lr: 5.3975e-05 eta: 2:04:28 time: 0.4084 data_time: 0.0025 memory: 5350 grad_norm: 931.3370 loss: 415.1643 loss_cls: 148.5346 loss_bbox: 125.0027 loss_dfl: 141.6270 2024/03/27 17:50:50 - mmengine - INFO - Epoch(train) [61][200/925] lr: 5.3975e-05 eta: 2:04:08 time: 0.3959 data_time: 0.0024 memory: 5270 grad_norm: 842.4954 loss: 412.3858 loss_cls: 146.3888 loss_bbox: 125.6787 loss_dfl: 140.3183 2024/03/27 17:51:10 - mmengine - INFO - Epoch(train) [61][250/925] lr: 5.3975e-05 eta: 2:03:47 time: 0.4050 data_time: 0.0023 memory: 5350 grad_norm: 915.8529 loss: 406.1646 loss_cls: 143.3702 loss_bbox: 123.7416 loss_dfl: 139.0528 2024/03/27 17:51:31 - mmengine - INFO - Epoch(train) [61][300/925] lr: 5.3975e-05 eta: 2:03:27 time: 0.4107 data_time: 0.0023 memory: 5163 grad_norm: 917.9889 loss: 411.1482 loss_cls: 146.6861 loss_bbox: 124.3285 loss_dfl: 140.1336 2024/03/27 17:51:51 - mmengine - INFO - Epoch(train) [61][350/925] lr: 5.3975e-05 eta: 2:03:07 time: 0.4073 data_time: 0.0020 memory: 5363 grad_norm: 989.0558 loss: 412.4709 loss_cls: 147.4178 loss_bbox: 124.9825 loss_dfl: 140.0706 2024/03/27 17:52:12 - mmengine - INFO - Epoch(train) [61][400/925] lr: 5.3975e-05 eta: 2:02:46 time: 0.4092 data_time: 0.0022 memory: 5256 grad_norm: 848.9946 loss: 410.1887 loss_cls: 145.8645 loss_bbox: 123.8557 loss_dfl: 140.4685 2024/03/27 17:52:33 - mmengine - INFO - Epoch(train) [61][450/925] lr: 5.3975e-05 eta: 2:02:26 time: 0.4185 data_time: 0.0023 memory: 5283 grad_norm: 881.6788 loss: 413.2488 loss_cls: 147.9849 loss_bbox: 124.2932 loss_dfl: 140.9707 2024/03/27 17:52:53 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:52:53 - mmengine - INFO - Epoch(train) [61][500/925] lr: 5.3975e-05 eta: 2:02:06 time: 0.4076 data_time: 0.0021 memory: 5163 grad_norm: 989.0044 loss: 414.0043 loss_cls: 147.6619 loss_bbox: 124.9917 loss_dfl: 141.3506 2024/03/27 17:53:13 - mmengine - INFO - Epoch(train) [61][550/925] lr: 5.3975e-05 eta: 2:01:45 time: 0.3980 data_time: 0.0024 memory: 5416 grad_norm: 996.2955 loss: 411.6036 loss_cls: 145.9830 loss_bbox: 124.3534 loss_dfl: 141.2672 2024/03/27 17:53:34 - mmengine - INFO - Epoch(train) [61][600/925] lr: 5.3975e-05 eta: 2:01:25 time: 0.4105 data_time: 0.0024 memory: 5696 grad_norm: 913.9110 loss: 415.7384 loss_cls: 148.4318 loss_bbox: 125.8265 loss_dfl: 141.4801 2024/03/27 17:53:55 - mmengine - INFO - Epoch(train) [61][650/925] lr: 5.3975e-05 eta: 2:01:05 time: 0.4164 data_time: 0.0023 memory: 5550 grad_norm: 908.7958 loss: 418.9587 loss_cls: 149.9644 loss_bbox: 126.8570 loss_dfl: 142.1373 2024/03/27 17:54:15 - mmengine - INFO - Epoch(train) [61][700/925] lr: 5.3975e-05 eta: 2:00:44 time: 0.4040 data_time: 0.0021 memory: 5856 grad_norm: 885.3167 loss: 417.7375 loss_cls: 149.1943 loss_bbox: 126.9587 loss_dfl: 141.5845 2024/03/27 17:54:35 - mmengine - INFO - Epoch(train) [61][750/925] lr: 5.3975e-05 eta: 2:00:24 time: 0.4051 data_time: 0.0033 memory: 5270 grad_norm: 951.1172 loss: 410.6088 loss_cls: 145.1604 loss_bbox: 124.9444 loss_dfl: 140.5040 2024/03/27 17:54:56 - mmengine - INFO - Epoch(train) [61][800/925] lr: 5.3975e-05 eta: 2:00:04 time: 0.4083 data_time: 0.0021 memory: 5230 grad_norm: 860.4051 loss: 412.0308 loss_cls: 147.0261 loss_bbox: 124.6910 loss_dfl: 140.3137 2024/03/27 17:55:16 - mmengine - INFO - Epoch(train) [61][850/925] lr: 5.3975e-05 eta: 1:59:43 time: 0.4163 data_time: 0.0024 memory: 5590 grad_norm: 900.1169 loss: 410.7666 loss_cls: 147.3438 loss_bbox: 123.3732 loss_dfl: 140.0495 2024/03/27 17:55:37 - mmengine - INFO - Epoch(train) [61][900/925] lr: 5.3975e-05 eta: 1:59:23 time: 0.4003 data_time: 0.0020 memory: 5083 grad_norm: 1006.7996 loss: 413.2889 loss_cls: 147.0482 loss_bbox: 125.5619 loss_dfl: 140.6787 2024/03/27 17:55:45 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:56:11 - mmengine - INFO - Epoch(train) [62][ 50/925] lr: 5.1500e-05 eta: 1:58:53 time: 0.4931 data_time: 0.0692 memory: 5456 grad_norm: 895.7830 loss: 416.2391 loss_cls: 149.8524 loss_bbox: 124.5534 loss_dfl: 141.8333 2024/03/27 17:56:31 - mmengine - INFO - Epoch(train) [62][100/925] lr: 5.1500e-05 eta: 1:58:33 time: 0.4113 data_time: 0.0022 memory: 5216 grad_norm: 968.8349 loss: 413.5546 loss_cls: 146.2091 loss_bbox: 126.1325 loss_dfl: 141.2131 2024/03/27 17:56:51 - mmengine - INFO - Epoch(train) [62][150/925] lr: 5.1500e-05 eta: 1:58:13 time: 0.4024 data_time: 0.0022 memory: 5336 grad_norm: 995.3508 loss: 407.6248 loss_cls: 145.7541 loss_bbox: 122.0160 loss_dfl: 139.8547 2024/03/27 17:57:12 - mmengine - INFO - Epoch(train) [62][200/925] lr: 5.1500e-05 eta: 1:57:52 time: 0.4078 data_time: 0.0023 memory: 5283 grad_norm: 1115.9221 loss: 417.2027 loss_cls: 148.6767 loss_bbox: 126.9178 loss_dfl: 141.6082 2024/03/27 17:57:33 - mmengine - INFO - Epoch(train) [62][250/925] lr: 5.1500e-05 eta: 1:57:32 time: 0.4192 data_time: 0.0023 memory: 5576 grad_norm: 839.5791 loss: 416.2553 loss_cls: 148.8065 loss_bbox: 126.2475 loss_dfl: 141.2013 2024/03/27 17:57:52 - mmengine - INFO - Epoch(train) [62][300/925] lr: 5.1500e-05 eta: 1:57:12 time: 0.3904 data_time: 0.0021 memory: 5443 grad_norm: 889.8073 loss: 411.1009 loss_cls: 147.7250 loss_bbox: 122.9792 loss_dfl: 140.3968 2024/03/27 17:58:13 - mmengine - INFO - Epoch(train) [62][350/925] lr: 5.1500e-05 eta: 1:56:51 time: 0.4092 data_time: 0.0023 memory: 5483 grad_norm: 949.2171 loss: 408.0954 loss_cls: 143.8221 loss_bbox: 124.3947 loss_dfl: 139.8786 2024/03/27 17:58:34 - mmengine - INFO - Epoch(train) [62][400/925] lr: 5.1500e-05 eta: 1:56:31 time: 0.4202 data_time: 0.0023 memory: 5750 grad_norm: 938.8079 loss: 409.0195 loss_cls: 144.4947 loss_bbox: 123.9671 loss_dfl: 140.5577 2024/03/27 17:58:54 - mmengine - INFO - Epoch(train) [62][450/925] lr: 5.1500e-05 eta: 1:56:11 time: 0.4055 data_time: 0.0026 memory: 5323 grad_norm: 897.3802 loss: 409.6885 loss_cls: 145.6823 loss_bbox: 124.2628 loss_dfl: 139.7434 2024/03/27 17:59:15 - mmengine - INFO - Epoch(train) [62][500/925] lr: 5.1500e-05 eta: 1:55:51 time: 0.4163 data_time: 0.0024 memory: 5163 grad_norm: 850.2593 loss: 410.6173 loss_cls: 145.8655 loss_bbox: 124.2908 loss_dfl: 140.4611 2024/03/27 17:59:36 - mmengine - INFO - Epoch(train) [62][550/925] lr: 5.1500e-05 eta: 1:55:30 time: 0.4166 data_time: 0.0024 memory: 5443 grad_norm: 891.2353 loss: 413.4135 loss_cls: 146.8398 loss_bbox: 125.6025 loss_dfl: 140.9712 2024/03/27 17:59:46 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 17:59:56 - mmengine - INFO - Epoch(train) [62][600/925] lr: 5.1500e-05 eta: 1:55:10 time: 0.4070 data_time: 0.0023 memory: 5616 grad_norm: 872.6458 loss: 412.3109 loss_cls: 147.6698 loss_bbox: 124.1751 loss_dfl: 140.4661 2024/03/27 18:00:17 - mmengine - INFO - Epoch(train) [62][650/925] lr: 5.1500e-05 eta: 1:54:50 time: 0.4088 data_time: 0.0023 memory: 5243 grad_norm: 880.9371 loss: 414.7697 loss_cls: 148.2293 loss_bbox: 126.0310 loss_dfl: 140.5094 2024/03/27 18:00:37 - mmengine - INFO - Epoch(train) [62][700/925] lr: 5.1500e-05 eta: 1:54:29 time: 0.4077 data_time: 0.0024 memory: 5243 grad_norm: 906.3564 loss: 417.7370 loss_cls: 151.1766 loss_bbox: 125.5310 loss_dfl: 141.0293 2024/03/27 18:00:58 - mmengine - INFO - Epoch(train) [62][750/925] lr: 5.1500e-05 eta: 1:54:09 time: 0.4101 data_time: 0.0025 memory: 5510 grad_norm: 937.7237 loss: 410.7082 loss_cls: 145.6322 loss_bbox: 124.5596 loss_dfl: 140.5163 2024/03/27 18:01:18 - mmengine - INFO - Epoch(train) [62][800/925] lr: 5.1500e-05 eta: 1:53:49 time: 0.4024 data_time: 0.0023 memory: 5456 grad_norm: inf loss: 411.6274 loss_cls: 145.8840 loss_bbox: 124.6558 loss_dfl: 141.0876 2024/03/27 18:01:39 - mmengine - INFO - Epoch(train) [62][850/925] lr: 5.1500e-05 eta: 1:53:28 time: 0.4129 data_time: 0.0024 memory: 5550 grad_norm: 886.9183 loss: 410.9247 loss_cls: 145.8995 loss_bbox: 125.0119 loss_dfl: 140.0132 2024/03/27 18:01:59 - mmengine - INFO - Epoch(train) [62][900/925] lr: 5.1500e-05 eta: 1:53:08 time: 0.4049 data_time: 0.0022 memory: 5630 grad_norm: 922.1562 loss: 415.4532 loss_cls: 147.6020 loss_bbox: 126.4228 loss_dfl: 141.4284 2024/03/27 18:02:07 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:02:31 - mmengine - INFO - Epoch(train) [63][ 50/925] lr: 4.9025e-05 eta: 1:52:38 time: 0.4693 data_time: 0.0758 memory: 5390 grad_norm: 987.7515 loss: 410.8748 loss_cls: 145.1795 loss_bbox: 124.5156 loss_dfl: 141.1797 2024/03/27 18:02:52 - mmengine - INFO - Epoch(train) [63][100/925] lr: 4.9025e-05 eta: 1:52:18 time: 0.4147 data_time: 0.0024 memory: 5230 grad_norm: 992.9510 loss: 414.9018 loss_cls: 148.2605 loss_bbox: 125.2889 loss_dfl: 141.3524 2024/03/27 18:03:12 - mmengine - INFO - Epoch(train) [63][150/925] lr: 4.9025e-05 eta: 1:51:57 time: 0.4009 data_time: 0.0023 memory: 5336 grad_norm: 1116.9012 loss: 403.4415 loss_cls: 142.4332 loss_bbox: 121.9733 loss_dfl: 139.0350 2024/03/27 18:03:32 - mmengine - INFO - Epoch(train) [63][200/925] lr: 4.9025e-05 eta: 1:51:37 time: 0.3957 data_time: 0.0023 memory: 5496 grad_norm: 950.4595 loss: 414.2951 loss_cls: 149.3417 loss_bbox: 123.9571 loss_dfl: 140.9962 2024/03/27 18:03:52 - mmengine - INFO - Epoch(train) [63][250/925] lr: 4.9025e-05 eta: 1:51:16 time: 0.4052 data_time: 0.0024 memory: 5416 grad_norm: 890.7059 loss: 412.6170 loss_cls: 146.0033 loss_bbox: 126.0145 loss_dfl: 140.5993 2024/03/27 18:04:13 - mmengine - INFO - Epoch(train) [63][300/925] lr: 4.9025e-05 eta: 1:50:56 time: 0.4154 data_time: 0.0026 memory: 5576 grad_norm: 934.3302 loss: 415.5502 loss_cls: 149.2486 loss_bbox: 125.2883 loss_dfl: 141.0133 2024/03/27 18:04:34 - mmengine - INFO - Epoch(train) [63][350/925] lr: 4.9025e-05 eta: 1:50:36 time: 0.4099 data_time: 0.0025 memory: 5363 grad_norm: 929.8900 loss: 408.6175 loss_cls: 145.1442 loss_bbox: 123.2632 loss_dfl: 140.2100 2024/03/27 18:04:54 - mmengine - INFO - Epoch(train) [63][400/925] lr: 4.9025e-05 eta: 1:50:15 time: 0.4007 data_time: 0.0023 memory: 5230 grad_norm: 896.3975 loss: 411.2400 loss_cls: 145.6614 loss_bbox: 124.7098 loss_dfl: 140.8689 2024/03/27 18:05:14 - mmengine - INFO - Epoch(train) [63][450/925] lr: 4.9025e-05 eta: 1:49:55 time: 0.4098 data_time: 0.0022 memory: 5776 grad_norm: 876.2624 loss: 412.9354 loss_cls: 147.2886 loss_bbox: 124.9290 loss_dfl: 140.7178 2024/03/27 18:05:35 - mmengine - INFO - Epoch(train) [63][500/925] lr: 4.9025e-05 eta: 1:49:35 time: 0.4145 data_time: 0.0023 memory: 5163 grad_norm: 865.2770 loss: 408.4240 loss_cls: 145.7349 loss_bbox: 121.9744 loss_dfl: 140.7147 2024/03/27 18:05:56 - mmengine - INFO - Epoch(train) [63][550/925] lr: 4.9025e-05 eta: 1:49:14 time: 0.4215 data_time: 0.0023 memory: 5283 grad_norm: 918.4071 loss: 413.3415 loss_cls: 147.6206 loss_bbox: 124.6590 loss_dfl: 141.0619 2024/03/27 18:06:16 - mmengine - INFO - Epoch(train) [63][600/925] lr: 4.9025e-05 eta: 1:48:54 time: 0.4005 data_time: 0.0023 memory: 5456 grad_norm: 911.8902 loss: 418.9657 loss_cls: 149.9870 loss_bbox: 127.6495 loss_dfl: 141.3293 2024/03/27 18:06:37 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:06:37 - mmengine - INFO - Epoch(train) [63][650/925] lr: 4.9025e-05 eta: 1:48:34 time: 0.4171 data_time: 0.0023 memory: 5216 grad_norm: 1000.1709 loss: 413.1947 loss_cls: 145.7190 loss_bbox: 126.5799 loss_dfl: 140.8958 2024/03/27 18:06:57 - mmengine - INFO - Epoch(train) [63][700/925] lr: 4.9025e-05 eta: 1:48:13 time: 0.3999 data_time: 0.0022 memory: 5616 grad_norm: 891.6165 loss: 415.9516 loss_cls: 146.5255 loss_bbox: 126.8107 loss_dfl: 142.6154 2024/03/27 18:07:17 - mmengine - INFO - Epoch(train) [63][750/925] lr: 4.9025e-05 eta: 1:47:53 time: 0.4026 data_time: 0.0022 memory: 5270 grad_norm: 976.6412 loss: 413.2335 loss_cls: 146.9428 loss_bbox: 125.4365 loss_dfl: 140.8542 2024/03/27 18:07:38 - mmengine - INFO - Epoch(train) [63][800/925] lr: 4.9025e-05 eta: 1:47:33 time: 0.4134 data_time: 0.0023 memory: 5470 grad_norm: 938.7284 loss: 406.2204 loss_cls: 145.1852 loss_bbox: 121.3371 loss_dfl: 139.6981 2024/03/27 18:07:58 - mmengine - INFO - Epoch(train) [63][850/925] lr: 4.9025e-05 eta: 1:47:12 time: 0.4093 data_time: 0.0022 memory: 5536 grad_norm: 971.0394 loss: 413.0458 loss_cls: 147.4836 loss_bbox: 124.4731 loss_dfl: 141.0891 2024/03/27 18:08:18 - mmengine - INFO - Epoch(train) [63][900/925] lr: 4.9025e-05 eta: 1:46:52 time: 0.3882 data_time: 0.0022 memory: 5443 grad_norm: 942.6516 loss: 411.3085 loss_cls: 146.8873 loss_bbox: 124.4138 loss_dfl: 140.0075 2024/03/27 18:08:28 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:08:52 - mmengine - INFO - Epoch(train) [64][ 50/925] lr: 4.6550e-05 eta: 1:46:22 time: 0.4786 data_time: 0.0696 memory: 5563 grad_norm: 956.0101 loss: 412.7455 loss_cls: 146.1039 loss_bbox: 125.2758 loss_dfl: 141.3658 2024/03/27 18:09:12 - mmengine - INFO - Epoch(train) [64][100/925] lr: 4.6550e-05 eta: 1:46:01 time: 0.3887 data_time: 0.0022 memory: 5376 grad_norm: 969.3327 loss: 410.7545 loss_cls: 146.5195 loss_bbox: 123.7919 loss_dfl: 140.4430 2024/03/27 18:09:32 - mmengine - INFO - Epoch(train) [64][150/925] lr: 4.6550e-05 eta: 1:45:41 time: 0.4000 data_time: 0.0023 memory: 5150 grad_norm: 849.1747 loss: 409.7723 loss_cls: 146.0598 loss_bbox: 123.1365 loss_dfl: 140.5760 2024/03/27 18:09:52 - mmengine - INFO - Epoch(train) [64][200/925] lr: 4.6550e-05 eta: 1:45:21 time: 0.4124 data_time: 0.0023 memory: 6096 grad_norm: 970.9771 loss: 408.7307 loss_cls: 145.8748 loss_bbox: 123.1669 loss_dfl: 139.6890 2024/03/27 18:10:12 - mmengine - INFO - Epoch(train) [64][250/925] lr: 4.6550e-05 eta: 1:45:00 time: 0.3975 data_time: 0.0023 memory: 5496 grad_norm: 957.4841 loss: 408.9352 loss_cls: 143.7685 loss_bbox: 124.4008 loss_dfl: 140.7659 2024/03/27 18:10:32 - mmengine - INFO - Epoch(train) [64][300/925] lr: 4.6550e-05 eta: 1:44:40 time: 0.4023 data_time: 0.0024 memory: 5283 grad_norm: 945.5354 loss: 413.1394 loss_cls: 147.3136 loss_bbox: 124.6837 loss_dfl: 141.1422 2024/03/27 18:10:52 - mmengine - INFO - Epoch(train) [64][350/925] lr: 4.6550e-05 eta: 1:44:19 time: 0.3999 data_time: 0.0022 memory: 5256 grad_norm: 887.5044 loss: 406.4779 loss_cls: 143.4262 loss_bbox: 122.7846 loss_dfl: 140.2670 2024/03/27 18:11:13 - mmengine - INFO - Epoch(train) [64][400/925] lr: 4.6550e-05 eta: 1:43:59 time: 0.4044 data_time: 0.0023 memory: 5270 grad_norm: 897.6143 loss: 411.9268 loss_cls: 145.8835 loss_bbox: 125.0079 loss_dfl: 141.0355 2024/03/27 18:11:33 - mmengine - INFO - Epoch(train) [64][450/925] lr: 4.6550e-05 eta: 1:43:39 time: 0.4063 data_time: 0.0024 memory: 5603 grad_norm: 880.1297 loss: 407.7820 loss_cls: 145.1996 loss_bbox: 122.4127 loss_dfl: 140.1698 2024/03/27 18:11:52 - mmengine - INFO - Epoch(train) [64][500/925] lr: 4.6550e-05 eta: 1:43:18 time: 0.3865 data_time: 0.0023 memory: 5216 grad_norm: 885.9567 loss: 415.4299 loss_cls: 148.9031 loss_bbox: 125.0448 loss_dfl: 141.4819 2024/03/27 18:12:13 - mmengine - INFO - Epoch(train) [64][550/925] lr: 4.6550e-05 eta: 1:42:58 time: 0.4146 data_time: 0.0024 memory: 5176 grad_norm: 905.2659 loss: 409.3908 loss_cls: 144.3190 loss_bbox: 124.9025 loss_dfl: 140.1693 2024/03/27 18:12:33 - mmengine - INFO - Epoch(train) [64][600/925] lr: 4.6550e-05 eta: 1:42:37 time: 0.4027 data_time: 0.0023 memory: 5536 grad_norm: 972.5103 loss: 410.8447 loss_cls: 146.6925 loss_bbox: 123.8820 loss_dfl: 140.2702 2024/03/27 18:12:53 - mmengine - INFO - Epoch(train) [64][650/925] lr: 4.6550e-05 eta: 1:42:17 time: 0.3879 data_time: 0.0022 memory: 5430 grad_norm: 897.7595 loss: 417.8673 loss_cls: 149.4722 loss_bbox: 126.5300 loss_dfl: 141.8651 2024/03/27 18:13:13 - mmengine - INFO - Epoch(train) [64][700/925] lr: 4.6550e-05 eta: 1:41:56 time: 0.4155 data_time: 0.0022 memory: 5603 grad_norm: 948.7533 loss: 412.0083 loss_cls: 146.6928 loss_bbox: 125.0407 loss_dfl: 140.2748 2024/03/27 18:13:24 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:13:34 - mmengine - INFO - Epoch(train) [64][750/925] lr: 4.6550e-05 eta: 1:41:36 time: 0.4032 data_time: 0.0022 memory: 5443 grad_norm: 968.6644 loss: 419.2863 loss_cls: 149.9391 loss_bbox: 127.4063 loss_dfl: 141.9409 2024/03/27 18:13:54 - mmengine - INFO - Epoch(train) [64][800/925] lr: 4.6550e-05 eta: 1:41:16 time: 0.4058 data_time: 0.0023 memory: 5816 grad_norm: 965.8832 loss: 419.3594 loss_cls: 149.7284 loss_bbox: 127.5869 loss_dfl: 142.0441 2024/03/27 18:14:14 - mmengine - INFO - Epoch(train) [64][850/925] lr: 4.6550e-05 eta: 1:40:55 time: 0.4059 data_time: 0.0023 memory: 5336 grad_norm: 991.3191 loss: 412.1533 loss_cls: 147.3610 loss_bbox: 124.1680 loss_dfl: 140.6244 2024/03/27 18:14:34 - mmengine - INFO - Epoch(train) [64][900/925] lr: 4.6550e-05 eta: 1:40:35 time: 0.3946 data_time: 0.0023 memory: 5270 grad_norm: 908.1365 loss: 409.4382 loss_cls: 145.2245 loss_bbox: 123.4727 loss_dfl: 140.7410 2024/03/27 18:14:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:15:08 - mmengine - INFO - Epoch(train) [65][ 50/925] lr: 4.4075e-05 eta: 1:40:05 time: 0.4841 data_time: 0.0553 memory: 5296 grad_norm: 915.5426 loss: 413.7654 loss_cls: 147.1547 loss_bbox: 125.5549 loss_dfl: 141.0558 2024/03/27 18:15:28 - mmengine - INFO - Epoch(train) [65][100/925] lr: 4.4075e-05 eta: 1:39:45 time: 0.4029 data_time: 0.0023 memory: 5656 grad_norm: 879.4693 loss: 408.4615 loss_cls: 146.3975 loss_bbox: 122.1273 loss_dfl: 139.9367 2024/03/27 18:15:48 - mmengine - INFO - Epoch(train) [65][150/925] lr: 4.4075e-05 eta: 1:39:24 time: 0.4087 data_time: 0.0021 memory: 5390 grad_norm: 922.7472 loss: 411.5156 loss_cls: 145.2612 loss_bbox: 124.7382 loss_dfl: 141.5163 2024/03/27 18:16:09 - mmengine - INFO - Epoch(train) [65][200/925] lr: 4.4075e-05 eta: 1:39:04 time: 0.4032 data_time: 0.0023 memory: 5603 grad_norm: 939.2847 loss: 422.3252 loss_cls: 152.5157 loss_bbox: 127.2393 loss_dfl: 142.5701 2024/03/27 18:16:28 - mmengine - INFO - Epoch(train) [65][250/925] lr: 4.4075e-05 eta: 1:38:43 time: 0.3931 data_time: 0.0022 memory: 5510 grad_norm: 894.1489 loss: 406.1813 loss_cls: 143.5394 loss_bbox: 123.3105 loss_dfl: 139.3314 2024/03/27 18:16:49 - mmengine - INFO - Epoch(train) [65][300/925] lr: 4.4075e-05 eta: 1:38:23 time: 0.4097 data_time: 0.0023 memory: 5336 grad_norm: 965.3474 loss: 409.6536 loss_cls: 146.1276 loss_bbox: 123.4553 loss_dfl: 140.0707 2024/03/27 18:17:10 - mmengine - INFO - Epoch(train) [65][350/925] lr: 4.4075e-05 eta: 1:38:03 time: 0.4145 data_time: 0.0022 memory: 5803 grad_norm: 908.6108 loss: 409.4144 loss_cls: 144.6521 loss_bbox: 124.1797 loss_dfl: 140.5826 2024/03/27 18:17:29 - mmengine - INFO - Epoch(train) [65][400/925] lr: 4.4075e-05 eta: 1:37:42 time: 0.3906 data_time: 0.0024 memory: 5390 grad_norm: 912.6613 loss: 409.4795 loss_cls: 144.8856 loss_bbox: 124.0779 loss_dfl: 140.5160 2024/03/27 18:17:50 - mmengine - INFO - Epoch(train) [65][450/925] lr: 4.4075e-05 eta: 1:37:22 time: 0.4106 data_time: 0.0023 memory: 5750 grad_norm: 909.0193 loss: 415.4979 loss_cls: 147.5800 loss_bbox: 126.7702 loss_dfl: 141.1476 2024/03/27 18:18:10 - mmengine - INFO - Epoch(train) [65][500/925] lr: 4.4075e-05 eta: 1:37:01 time: 0.4016 data_time: 0.0024 memory: 5456 grad_norm: 901.2044 loss: 418.8710 loss_cls: 149.9399 loss_bbox: 126.7910 loss_dfl: 142.1402 2024/03/27 18:18:30 - mmengine - INFO - Epoch(train) [65][550/925] lr: 4.4075e-05 eta: 1:36:41 time: 0.4018 data_time: 0.0022 memory: 5270 grad_norm: 905.0548 loss: 409.5716 loss_cls: 146.9540 loss_bbox: 122.5152 loss_dfl: 140.1024 2024/03/27 18:18:51 - mmengine - INFO - Epoch(train) [65][600/925] lr: 4.4075e-05 eta: 1:36:21 time: 0.4169 data_time: 0.0022 memory: 5616 grad_norm: 865.7884 loss: 410.3585 loss_cls: 145.6818 loss_bbox: 124.1568 loss_dfl: 140.5199 2024/03/27 18:19:11 - mmengine - INFO - Epoch(train) [65][650/925] lr: 4.4075e-05 eta: 1:36:00 time: 0.4034 data_time: 0.0023 memory: 5496 grad_norm: 926.7857 loss: 412.1075 loss_cls: 148.4166 loss_bbox: 124.2358 loss_dfl: 139.4551 2024/03/27 18:19:31 - mmengine - INFO - Epoch(train) [65][700/925] lr: 4.4075e-05 eta: 1:35:40 time: 0.4043 data_time: 0.0022 memory: 5390 grad_norm: 953.4947 loss: 414.9178 loss_cls: 148.3377 loss_bbox: 125.3070 loss_dfl: 141.2731 2024/03/27 18:19:51 - mmengine - INFO - Epoch(train) [65][750/925] lr: 4.4075e-05 eta: 1:35:19 time: 0.4007 data_time: 0.0022 memory: 5470 grad_norm: 1054.8335 loss: 410.5826 loss_cls: 145.5414 loss_bbox: 124.4950 loss_dfl: 140.5462 2024/03/27 18:20:12 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:20:12 - mmengine - INFO - Epoch(train) [65][800/925] lr: 4.4075e-05 eta: 1:34:59 time: 0.4182 data_time: 0.0024 memory: 5523 grad_norm: 921.7770 loss: 405.9533 loss_cls: 144.9608 loss_bbox: 121.7157 loss_dfl: 139.2768 2024/03/27 18:20:33 - mmengine - INFO - Epoch(train) [65][850/925] lr: 4.4075e-05 eta: 1:34:39 time: 0.4023 data_time: 0.0022 memory: 5563 grad_norm: 921.3763 loss: 409.4636 loss_cls: 145.4591 loss_bbox: 123.3975 loss_dfl: 140.6069 2024/03/27 18:20:52 - mmengine - INFO - Epoch(train) [65][900/925] lr: 4.4075e-05 eta: 1:34:18 time: 0.3981 data_time: 0.0023 memory: 6056 grad_norm: inf loss: 418.2734 loss_cls: 149.4177 loss_bbox: 126.6824 loss_dfl: 142.1733 2024/03/27 18:21:02 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:21:02 - mmengine - INFO - Saving checkpoint at 65 epochs 2024/03/27 18:21:10 - mmengine - INFO - Epoch(val) [65][ 50/625] eta: 0:00:24 time: 0.0432 data_time: 0.0010 memory: 5203 2024/03/27 18:21:13 - mmengine - INFO - Epoch(val) [65][100/625] eta: 0:00:22 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 18:21:15 - mmengine - INFO - Epoch(val) [65][150/625] eta: 0:00:20 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 18:21:17 - mmengine - INFO - Epoch(val) [65][200/625] eta: 0:00:18 time: 0.0442 data_time: 0.0004 memory: 838 2024/03/27 18:21:21 - mmengine - INFO - Epoch(val) [65][250/625] eta: 0:00:19 time: 0.0905 data_time: 0.0472 memory: 838 2024/03/27 18:21:24 - mmengine - INFO - Epoch(val) [65][300/625] eta: 0:00:16 time: 0.0422 data_time: 0.0004 memory: 838 2024/03/27 18:21:26 - mmengine - INFO - Epoch(val) [65][350/625] eta: 0:00:13 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 18:21:28 - mmengine - INFO - Epoch(val) [65][400/625] eta: 0:00:11 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 18:21:30 - mmengine - INFO - Epoch(val) [65][450/625] eta: 0:00:08 time: 0.0426 data_time: 0.0004 memory: 838 2024/03/27 18:21:32 - mmengine - INFO - Epoch(val) [65][500/625] eta: 0:00:05 time: 0.0400 data_time: 0.0003 memory: 838 2024/03/27 18:21:34 - mmengine - INFO - Epoch(val) [65][550/625] eta: 0:00:03 time: 0.0346 data_time: 0.0003 memory: 838 2024/03/27 18:21:36 - mmengine - INFO - Epoch(val) [65][600/625] eta: 0:00:01 time: 0.0350 data_time: 0.0003 memory: 838 2024/03/27 18:21:50 - mmengine - INFO - Evaluating bbox... 2024/03/27 18:23:15 - mmengine - INFO - bbox_mAP_copypaste: 0.455 0.617 0.497 0.262 0.504 0.614 2024/03/27 18:23:16 - mmengine - INFO - Epoch(val) [65][625/625] coco/bbox_mAP: 0.4550 coco/bbox_mAP_50: 0.6170 coco/bbox_mAP_75: 0.4970 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5040 coco/bbox_mAP_l: 0.6140 data_time: 0.0003 time: 0.0355 2024/03/27 18:23:40 - mmengine - INFO - Epoch(train) [66][ 50/925] lr: 4.1600e-05 eta: 1:33:48 time: 0.4751 data_time: 0.0686 memory: 5470 grad_norm: 930.9133 loss: 413.4951 loss_cls: 147.4796 loss_bbox: 124.9868 loss_dfl: 141.0287 2024/03/27 18:24:00 - mmengine - INFO - Epoch(train) [66][100/925] lr: 4.1600e-05 eta: 1:33:28 time: 0.3974 data_time: 0.0023 memory: 5470 grad_norm: 899.0149 loss: 407.1478 loss_cls: 143.4864 loss_bbox: 123.1925 loss_dfl: 140.4689 2024/03/27 18:24:19 - mmengine - INFO - Epoch(train) [66][150/925] lr: 4.1600e-05 eta: 1:33:07 time: 0.3829 data_time: 0.0027 memory: 5336 grad_norm: 866.8958 loss: 404.1212 loss_cls: 142.9289 loss_bbox: 122.2378 loss_dfl: 138.9545 2024/03/27 18:24:39 - mmengine - INFO - Epoch(train) [66][200/925] lr: 4.1600e-05 eta: 1:32:47 time: 0.3994 data_time: 0.0022 memory: 5150 grad_norm: 995.4661 loss: 410.9589 loss_cls: 145.1918 loss_bbox: 124.8319 loss_dfl: 140.9352 2024/03/27 18:24:59 - mmengine - INFO - Epoch(train) [66][250/925] lr: 4.1600e-05 eta: 1:32:26 time: 0.3971 data_time: 0.0023 memory: 5283 grad_norm: 883.1368 loss: 406.8714 loss_cls: 144.6133 loss_bbox: 122.2494 loss_dfl: 140.0086 2024/03/27 18:25:18 - mmengine - INFO - Epoch(train) [66][300/925] lr: 4.1600e-05 eta: 1:32:06 time: 0.3777 data_time: 0.0023 memory: 5336 grad_norm: 861.6743 loss: 413.3064 loss_cls: 147.4574 loss_bbox: 125.0485 loss_dfl: 140.8005 2024/03/27 18:25:38 - mmengine - INFO - Epoch(train) [66][350/925] lr: 4.1600e-05 eta: 1:31:45 time: 0.4025 data_time: 0.0022 memory: 5603 grad_norm: 901.4452 loss: 409.5073 loss_cls: 145.3964 loss_bbox: 124.7702 loss_dfl: 139.3407 2024/03/27 18:25:58 - mmengine - INFO - Epoch(train) [66][400/925] lr: 4.1600e-05 eta: 1:31:25 time: 0.4024 data_time: 0.0023 memory: 5376 grad_norm: 927.6028 loss: 416.3733 loss_cls: 148.3356 loss_bbox: 126.4967 loss_dfl: 141.5410 2024/03/27 18:26:18 - mmengine - INFO - Epoch(train) [66][450/925] lr: 4.1600e-05 eta: 1:31:04 time: 0.3960 data_time: 0.0022 memory: 5190 grad_norm: 908.2634 loss: 405.8657 loss_cls: 143.3027 loss_bbox: 122.6887 loss_dfl: 139.8743 2024/03/27 18:26:38 - mmengine - INFO - Epoch(train) [66][500/925] lr: 4.1600e-05 eta: 1:30:44 time: 0.3972 data_time: 0.0022 memory: 5563 grad_norm: 953.3088 loss: 407.3732 loss_cls: 144.4683 loss_bbox: 122.3560 loss_dfl: 140.5489 2024/03/27 18:26:57 - mmengine - INFO - Epoch(train) [66][550/925] lr: 4.1600e-05 eta: 1:30:23 time: 0.3894 data_time: 0.0022 memory: 5216 grad_norm: 940.1988 loss: 410.5707 loss_cls: 147.0097 loss_bbox: 123.6043 loss_dfl: 139.9567 2024/03/27 18:27:17 - mmengine - INFO - Epoch(train) [66][600/925] lr: 4.1600e-05 eta: 1:30:03 time: 0.3961 data_time: 0.0023 memory: 5496 grad_norm: 1003.7322 loss: 412.3201 loss_cls: 146.3476 loss_bbox: 125.3532 loss_dfl: 140.6193 2024/03/27 18:27:37 - mmengine - INFO - Epoch(train) [66][650/925] lr: 4.1600e-05 eta: 1:29:42 time: 0.3959 data_time: 0.0028 memory: 5616 grad_norm: 916.3937 loss: 406.9192 loss_cls: 143.6003 loss_bbox: 123.6477 loss_dfl: 139.6711 2024/03/27 18:27:57 - mmengine - INFO - Epoch(train) [66][700/925] lr: 4.1600e-05 eta: 1:29:22 time: 0.3999 data_time: 0.0022 memory: 5603 grad_norm: 912.3642 loss: 412.1887 loss_cls: 146.6374 loss_bbox: 125.4601 loss_dfl: 140.0911 2024/03/27 18:28:17 - mmengine - INFO - Epoch(train) [66][750/925] lr: 4.1600e-05 eta: 1:29:01 time: 0.3867 data_time: 0.0023 memory: 5523 grad_norm: 898.5504 loss: 416.0485 loss_cls: 148.3812 loss_bbox: 126.4129 loss_dfl: 141.2544 2024/03/27 18:28:36 - mmengine - INFO - Epoch(train) [66][800/925] lr: 4.1600e-05 eta: 1:28:41 time: 0.3965 data_time: 0.0023 memory: 5950 grad_norm: 952.3906 loss: 414.4789 loss_cls: 147.5459 loss_bbox: 126.1269 loss_dfl: 140.8061 2024/03/27 18:28:56 - mmengine - INFO - Epoch(train) [66][850/925] lr: 4.1600e-05 eta: 1:28:21 time: 0.3988 data_time: 0.0023 memory: 5256 grad_norm: 934.3225 loss: 405.3793 loss_cls: 144.9402 loss_bbox: 120.4758 loss_dfl: 139.9633 2024/03/27 18:29:07 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:29:16 - mmengine - INFO - Epoch(train) [66][900/925] lr: 4.1600e-05 eta: 1:28:00 time: 0.3977 data_time: 0.0024 memory: 5403 grad_norm: 943.1123 loss: 413.1618 loss_cls: 147.4006 loss_bbox: 124.6264 loss_dfl: 141.1348 2024/03/27 18:29:26 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:29:50 - mmengine - INFO - Epoch(train) [67][ 50/925] lr: 3.9125e-05 eta: 1:27:30 time: 0.4727 data_time: 0.0599 memory: 5336 grad_norm: 866.9033 loss: 402.1997 loss_cls: 140.8474 loss_bbox: 122.1006 loss_dfl: 139.2517 2024/03/27 18:30:10 - mmengine - INFO - Epoch(train) [67][100/925] lr: 3.9125e-05 eta: 1:27:10 time: 0.4008 data_time: 0.0023 memory: 5470 grad_norm: 926.6508 loss: 404.3433 loss_cls: 141.9518 loss_bbox: 122.2070 loss_dfl: 140.1845 2024/03/27 18:30:30 - mmengine - INFO - Epoch(train) [67][150/925] lr: 3.9125e-05 eta: 1:26:49 time: 0.4138 data_time: 0.0023 memory: 5203 grad_norm: 968.3607 loss: 410.6891 loss_cls: 145.1078 loss_bbox: 124.5698 loss_dfl: 141.0115 2024/03/27 18:30:50 - mmengine - INFO - Epoch(train) [67][200/925] lr: 3.9125e-05 eta: 1:26:29 time: 0.3969 data_time: 0.0024 memory: 5323 grad_norm: 911.4983 loss: 404.7195 loss_cls: 143.4847 loss_bbox: 121.7039 loss_dfl: 139.5309 2024/03/27 18:31:11 - mmengine - INFO - Epoch(train) [67][250/925] lr: 3.9125e-05 eta: 1:26:09 time: 0.4074 data_time: 0.0022 memory: 5416 grad_norm: 905.6933 loss: 410.3588 loss_cls: 145.0912 loss_bbox: 124.3411 loss_dfl: 140.9265 2024/03/27 18:31:30 - mmengine - INFO - Epoch(train) [67][300/925] lr: 3.9125e-05 eta: 1:25:48 time: 0.3880 data_time: 0.0026 memory: 5496 grad_norm: 889.4952 loss: 409.8027 loss_cls: 144.9289 loss_bbox: 124.7464 loss_dfl: 140.1274 2024/03/27 18:31:51 - mmengine - INFO - Epoch(train) [67][350/925] lr: 3.9125e-05 eta: 1:25:28 time: 0.4081 data_time: 0.0027 memory: 5376 grad_norm: 1011.6824 loss: 408.7783 loss_cls: 144.0494 loss_bbox: 123.8690 loss_dfl: 140.8599 2024/03/27 18:32:11 - mmengine - INFO - Epoch(train) [67][400/925] lr: 3.9125e-05 eta: 1:25:07 time: 0.4000 data_time: 0.0023 memory: 5323 grad_norm: 1012.8854 loss: 406.1895 loss_cls: 143.8704 loss_bbox: 122.0623 loss_dfl: 140.2568 2024/03/27 18:32:31 - mmengine - INFO - Epoch(train) [67][450/925] lr: 3.9125e-05 eta: 1:24:47 time: 0.3972 data_time: 0.0023 memory: 5443 grad_norm: 889.4128 loss: 413.7820 loss_cls: 147.5308 loss_bbox: 125.2408 loss_dfl: 141.0104 2024/03/27 18:32:51 - mmengine - INFO - Epoch(train) [67][500/925] lr: 3.9125e-05 eta: 1:24:26 time: 0.4087 data_time: 0.0024 memory: 5376 grad_norm: 849.1109 loss: 413.5244 loss_cls: 147.2756 loss_bbox: 124.7682 loss_dfl: 141.4805 2024/03/27 18:33:11 - mmengine - INFO - Epoch(train) [67][550/925] lr: 3.9125e-05 eta: 1:24:06 time: 0.3974 data_time: 0.0021 memory: 5190 grad_norm: 894.6512 loss: 414.0412 loss_cls: 149.1604 loss_bbox: 123.4624 loss_dfl: 141.4184 2024/03/27 18:33:31 - mmengine - INFO - Epoch(train) [67][600/925] lr: 3.9125e-05 eta: 1:23:46 time: 0.4057 data_time: 0.0024 memory: 5670 grad_norm: 916.7991 loss: 410.3527 loss_cls: 144.1349 loss_bbox: 126.1782 loss_dfl: 140.0397 2024/03/27 18:33:51 - mmengine - INFO - Epoch(train) [67][650/925] lr: 3.9125e-05 eta: 1:23:25 time: 0.3972 data_time: 0.0024 memory: 5523 grad_norm: 900.6301 loss: 413.1165 loss_cls: 146.5831 loss_bbox: 125.0909 loss_dfl: 141.4424 2024/03/27 18:34:11 - mmengine - INFO - Epoch(train) [67][700/925] lr: 3.9125e-05 eta: 1:23:05 time: 0.3936 data_time: 0.0022 memory: 5216 grad_norm: 873.2479 loss: 408.3891 loss_cls: 145.3668 loss_bbox: 122.9281 loss_dfl: 140.0943 2024/03/27 18:34:31 - mmengine - INFO - Epoch(train) [67][750/925] lr: 3.9125e-05 eta: 1:22:44 time: 0.3993 data_time: 0.0024 memory: 5390 grad_norm: 993.0388 loss: 417.5747 loss_cls: 149.3363 loss_bbox: 126.6829 loss_dfl: 141.5554 2024/03/27 18:34:51 - mmengine - INFO - Epoch(train) [67][800/925] lr: 3.9125e-05 eta: 1:22:24 time: 0.3994 data_time: 0.0030 memory: 5230 grad_norm: 920.2797 loss: 407.0934 loss_cls: 143.4621 loss_bbox: 123.3914 loss_dfl: 140.2399 2024/03/27 18:35:12 - mmengine - INFO - Epoch(train) [67][850/925] lr: 3.9125e-05 eta: 1:22:04 time: 0.4150 data_time: 0.0024 memory: 5390 grad_norm: 933.9703 loss: 412.9016 loss_cls: 146.4959 loss_bbox: 124.9273 loss_dfl: 141.4784 2024/03/27 18:35:32 - mmengine - INFO - Epoch(train) [67][900/925] lr: 3.9125e-05 eta: 1:21:43 time: 0.3978 data_time: 0.0022 memory: 5230 grad_norm: 925.0426 loss: 406.2726 loss_cls: 144.0740 loss_bbox: 123.1672 loss_dfl: 139.0314 2024/03/27 18:35:41 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:35:55 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:36:06 - mmengine - INFO - Epoch(train) [68][ 50/925] lr: 3.6650e-05 eta: 1:21:13 time: 0.4860 data_time: 0.0543 memory: 5550 grad_norm: 875.2420 loss: 410.5139 loss_cls: 144.0113 loss_bbox: 125.5117 loss_dfl: 140.9909 2024/03/27 18:36:26 - mmengine - INFO - Epoch(train) [68][100/925] lr: 3.6650e-05 eta: 1:20:53 time: 0.4045 data_time: 0.0026 memory: 5656 grad_norm: 901.7040 loss: 412.5682 loss_cls: 147.2883 loss_bbox: 123.6279 loss_dfl: 141.6519 2024/03/27 18:36:46 - mmengine - INFO - Epoch(train) [68][150/925] lr: 3.6650e-05 eta: 1:20:32 time: 0.3970 data_time: 0.0023 memory: 5203 grad_norm: 986.0339 loss: 412.5330 loss_cls: 145.9323 loss_bbox: 125.6785 loss_dfl: 140.9222 2024/03/27 18:37:06 - mmengine - INFO - Epoch(train) [68][200/925] lr: 3.6650e-05 eta: 1:20:12 time: 0.4129 data_time: 0.0022 memory: 5216 grad_norm: 877.7417 loss: 406.2217 loss_cls: 144.9000 loss_bbox: 121.5850 loss_dfl: 139.7366 2024/03/27 18:37:26 - mmengine - INFO - Epoch(train) [68][250/925] lr: 3.6650e-05 eta: 1:19:52 time: 0.3986 data_time: 0.0022 memory: 5510 grad_norm: 878.6098 loss: 408.1215 loss_cls: 144.0418 loss_bbox: 124.2869 loss_dfl: 139.7928 2024/03/27 18:37:46 - mmengine - INFO - Epoch(train) [68][300/925] lr: 3.6650e-05 eta: 1:19:31 time: 0.3978 data_time: 0.0022 memory: 5336 grad_norm: inf loss: 408.0227 loss_cls: 144.2599 loss_bbox: 123.9396 loss_dfl: 139.8232 2024/03/27 18:38:07 - mmengine - INFO - Epoch(train) [68][350/925] lr: 3.6650e-05 eta: 1:19:11 time: 0.4110 data_time: 0.0024 memory: 5150 grad_norm: 941.0598 loss: 408.6817 loss_cls: 144.8534 loss_bbox: 123.7383 loss_dfl: 140.0899 2024/03/27 18:38:27 - mmengine - INFO - Epoch(train) [68][400/925] lr: 3.6650e-05 eta: 1:18:51 time: 0.4019 data_time: 0.0024 memory: 5350 grad_norm: 1001.1155 loss: 408.8892 loss_cls: 146.1747 loss_bbox: 123.1362 loss_dfl: 139.5783 2024/03/27 18:38:46 - mmengine - INFO - Epoch(train) [68][450/925] lr: 3.6650e-05 eta: 1:18:30 time: 0.3863 data_time: 0.0023 memory: 5696 grad_norm: 939.7687 loss: 408.9557 loss_cls: 144.0555 loss_bbox: 124.9773 loss_dfl: 139.9229 2024/03/27 18:39:07 - mmengine - INFO - Epoch(train) [68][500/925] lr: 3.6650e-05 eta: 1:18:10 time: 0.4055 data_time: 0.0023 memory: 5323 grad_norm: 959.4275 loss: 406.6969 loss_cls: 143.8285 loss_bbox: 122.9640 loss_dfl: 139.9044 2024/03/27 18:39:27 - mmengine - INFO - Epoch(train) [68][550/925] lr: 3.6650e-05 eta: 1:17:49 time: 0.3979 data_time: 0.0026 memory: 5536 grad_norm: 958.8066 loss: 407.7152 loss_cls: 143.1157 loss_bbox: 124.1527 loss_dfl: 140.4467 2024/03/27 18:39:47 - mmengine - INFO - Epoch(train) [68][600/925] lr: 3.6650e-05 eta: 1:17:29 time: 0.4027 data_time: 0.0024 memory: 5243 grad_norm: 882.7126 loss: 408.2495 loss_cls: 144.4562 loss_bbox: 123.7441 loss_dfl: 140.0492 2024/03/27 18:40:07 - mmengine - INFO - Epoch(train) [68][650/925] lr: 3.6650e-05 eta: 1:17:08 time: 0.3989 data_time: 0.0023 memory: 5230 grad_norm: 947.8486 loss: 408.1874 loss_cls: 142.5287 loss_bbox: 124.9286 loss_dfl: 140.7301 2024/03/27 18:40:27 - mmengine - INFO - Epoch(train) [68][700/925] lr: 3.6650e-05 eta: 1:16:48 time: 0.3950 data_time: 0.0024 memory: 5376 grad_norm: 920.7111 loss: 407.0251 loss_cls: 143.4484 loss_bbox: 124.1158 loss_dfl: 139.4608 2024/03/27 18:40:47 - mmengine - INFO - Epoch(train) [68][750/925] lr: 3.6650e-05 eta: 1:16:28 time: 0.4026 data_time: 0.0025 memory: 5843 grad_norm: 942.8588 loss: 414.9406 loss_cls: 148.2081 loss_bbox: 125.4340 loss_dfl: 141.2985 2024/03/27 18:41:06 - mmengine - INFO - Epoch(train) [68][800/925] lr: 3.6650e-05 eta: 1:16:07 time: 0.3904 data_time: 0.0022 memory: 5270 grad_norm: 866.0717 loss: 404.0762 loss_cls: 142.5117 loss_bbox: 122.0874 loss_dfl: 139.4771 2024/03/27 18:41:27 - mmengine - INFO - Epoch(train) [68][850/925] lr: 3.6650e-05 eta: 1:15:47 time: 0.4052 data_time: 0.0024 memory: 5190 grad_norm: 1026.3282 loss: 411.7169 loss_cls: 148.3994 loss_bbox: 123.4154 loss_dfl: 139.9021 2024/03/27 18:41:47 - mmengine - INFO - Epoch(train) [68][900/925] lr: 3.6650e-05 eta: 1:15:26 time: 0.4144 data_time: 0.0023 memory: 5470 grad_norm: 917.0530 loss: 411.9014 loss_cls: 147.0623 loss_bbox: 123.9731 loss_dfl: 140.8660 2024/03/27 18:41:56 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:42:20 - mmengine - INFO - Epoch(train) [69][ 50/925] lr: 3.4175e-05 eta: 1:14:56 time: 0.4799 data_time: 0.0612 memory: 5576 grad_norm: 992.0440 loss: 411.5330 loss_cls: 145.2552 loss_bbox: 125.3496 loss_dfl: 140.9282 2024/03/27 18:42:41 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:42:41 - mmengine - INFO - Epoch(train) [69][100/925] lr: 3.4175e-05 eta: 1:14:36 time: 0.4101 data_time: 0.0024 memory: 5950 grad_norm: 939.7084 loss: 410.1771 loss_cls: 144.8106 loss_bbox: 124.7100 loss_dfl: 140.6565 2024/03/27 18:43:00 - mmengine - INFO - Epoch(train) [69][150/925] lr: 3.4175e-05 eta: 1:14:16 time: 0.3959 data_time: 0.0023 memory: 5283 grad_norm: 980.9941 loss: 407.8284 loss_cls: 144.2565 loss_bbox: 123.6900 loss_dfl: 139.8819 2024/03/27 18:43:20 - mmengine - INFO - Epoch(train) [69][200/925] lr: 3.4175e-05 eta: 1:13:55 time: 0.3874 data_time: 0.0023 memory: 5430 grad_norm: 946.4709 loss: 399.1548 loss_cls: 140.0845 loss_bbox: 120.4501 loss_dfl: 138.6202 2024/03/27 18:43:40 - mmengine - INFO - Epoch(train) [69][250/925] lr: 3.4175e-05 eta: 1:13:35 time: 0.3983 data_time: 0.0023 memory: 5096 grad_norm: 895.4497 loss: 409.1494 loss_cls: 143.6640 loss_bbox: 124.1003 loss_dfl: 141.3852 2024/03/27 18:43:59 - mmengine - INFO - Epoch(train) [69][300/925] lr: 3.4175e-05 eta: 1:13:14 time: 0.3815 data_time: 0.0023 memory: 5416 grad_norm: 900.8426 loss: 411.6759 loss_cls: 144.8213 loss_bbox: 125.9477 loss_dfl: 140.9068 2024/03/27 18:44:19 - mmengine - INFO - Epoch(train) [69][350/925] lr: 3.4175e-05 eta: 1:12:54 time: 0.3959 data_time: 0.0023 memory: 5630 grad_norm: 924.4197 loss: 405.8587 loss_cls: 143.3815 loss_bbox: 123.0041 loss_dfl: 139.4731 2024/03/27 18:44:39 - mmengine - INFO - Epoch(train) [69][400/925] lr: 3.4175e-05 eta: 1:12:33 time: 0.3936 data_time: 0.0025 memory: 5883 grad_norm: 883.7918 loss: 412.6895 loss_cls: 145.7265 loss_bbox: 126.1482 loss_dfl: 140.8148 2024/03/27 18:44:58 - mmengine - INFO - Epoch(train) [69][450/925] lr: 3.4175e-05 eta: 1:12:13 time: 0.3909 data_time: 0.0022 memory: 5163 grad_norm: 899.8092 loss: 411.7870 loss_cls: 145.6253 loss_bbox: 125.0272 loss_dfl: 141.1345 2024/03/27 18:45:18 - mmengine - INFO - Epoch(train) [69][500/925] lr: 3.4175e-05 eta: 1:11:52 time: 0.3983 data_time: 0.0022 memory: 5403 grad_norm: 878.7240 loss: 413.0686 loss_cls: 146.4077 loss_bbox: 124.7832 loss_dfl: 141.8778 2024/03/27 18:45:37 - mmengine - INFO - Epoch(train) [69][550/925] lr: 3.4175e-05 eta: 1:11:32 time: 0.3795 data_time: 0.0022 memory: 5256 grad_norm: 1023.4431 loss: 409.8652 loss_cls: 145.2146 loss_bbox: 124.4078 loss_dfl: 140.2428 2024/03/27 18:45:57 - mmengine - INFO - Epoch(train) [69][600/925] lr: 3.4175e-05 eta: 1:11:11 time: 0.3985 data_time: 0.0024 memory: 5270 grad_norm: 953.6576 loss: 415.5808 loss_cls: 147.9701 loss_bbox: 126.5846 loss_dfl: 141.0261 2024/03/27 18:46:17 - mmengine - INFO - Epoch(train) [69][650/925] lr: 3.4175e-05 eta: 1:10:51 time: 0.4030 data_time: 0.0023 memory: 5230 grad_norm: 908.6822 loss: 416.7273 loss_cls: 149.2358 loss_bbox: 125.3292 loss_dfl: 142.1624 2024/03/27 18:46:37 - mmengine - INFO - Epoch(train) [69][700/925] lr: 3.4175e-05 eta: 1:10:30 time: 0.3905 data_time: 0.0044 memory: 5203 grad_norm: 873.4150 loss: 406.3260 loss_cls: 143.7232 loss_bbox: 122.9645 loss_dfl: 139.6383 2024/03/27 18:46:57 - mmengine - INFO - Epoch(train) [69][750/925] lr: 3.4175e-05 eta: 1:10:10 time: 0.3986 data_time: 0.0024 memory: 5523 grad_norm: 885.4428 loss: 408.0015 loss_cls: 142.7472 loss_bbox: 124.9329 loss_dfl: 140.3214 2024/03/27 18:47:17 - mmengine - INFO - Epoch(train) [69][800/925] lr: 3.4175e-05 eta: 1:09:50 time: 0.3959 data_time: 0.0031 memory: 5230 grad_norm: 937.6606 loss: 406.9265 loss_cls: 143.1553 loss_bbox: 123.5398 loss_dfl: 140.2315 2024/03/27 18:47:37 - mmengine - INFO - Epoch(train) [69][850/925] lr: 3.4175e-05 eta: 1:09:29 time: 0.4007 data_time: 0.0026 memory: 5203 grad_norm: 916.8249 loss: 406.8027 loss_cls: 143.9639 loss_bbox: 122.1845 loss_dfl: 140.6543 2024/03/27 18:47:57 - mmengine - INFO - Epoch(train) [69][900/925] lr: 3.4175e-05 eta: 1:09:09 time: 0.4046 data_time: 0.0024 memory: 5336 grad_norm: 870.4055 loss: 407.0438 loss_cls: 143.8582 loss_bbox: 123.4490 loss_dfl: 139.7365 2024/03/27 18:48:05 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:48:08 - mmengine - INFO - Epoch(val) [69][ 50/625] eta: 0:00:25 time: 0.0437 data_time: 0.0008 memory: 5203 2024/03/27 18:48:10 - mmengine - INFO - Epoch(val) [69][100/625] eta: 0:00:22 time: 0.0428 data_time: 0.0003 memory: 838 2024/03/27 18:48:12 - mmengine - INFO - Epoch(val) [69][150/625] eta: 0:00:20 time: 0.0439 data_time: 0.0003 memory: 838 2024/03/27 18:48:15 - mmengine - INFO - Epoch(val) [69][200/625] eta: 0:00:18 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 18:48:17 - mmengine - INFO - Epoch(val) [69][250/625] eta: 0:00:16 time: 0.0446 data_time: 0.0004 memory: 838 2024/03/27 18:48:19 - mmengine - INFO - Epoch(val) [69][300/625] eta: 0:00:14 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 18:48:21 - mmengine - INFO - Epoch(val) [69][350/625] eta: 0:00:11 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 18:48:23 - mmengine - INFO - Epoch(val) [69][400/625] eta: 0:00:09 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 18:48:26 - mmengine - INFO - Epoch(val) [69][450/625] eta: 0:00:07 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 18:48:28 - mmengine - INFO - Epoch(val) [69][500/625] eta: 0:00:05 time: 0.0430 data_time: 0.0004 memory: 838 2024/03/27 18:48:30 - mmengine - INFO - Epoch(val) [69][550/625] eta: 0:00:03 time: 0.0418 data_time: 0.0004 memory: 838 2024/03/27 18:48:32 - mmengine - INFO - Epoch(val) [69][600/625] eta: 0:00:01 time: 0.0435 data_time: 0.0004 memory: 838 2024/03/27 18:48:46 - mmengine - INFO - Evaluating bbox... 2024/03/27 18:50:01 - mmengine - INFO - bbox_mAP_copypaste: 0.456 0.619 0.499 0.262 0.504 0.614 2024/03/27 18:50:02 - mmengine - INFO - Epoch(val) [69][625/625] coco/bbox_mAP: 0.4560 coco/bbox_mAP_50: 0.6190 coco/bbox_mAP_75: 0.4990 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5040 coco/bbox_mAP_l: 0.6140 data_time: 0.0004 time: 0.0424 2024/03/27 18:50:29 - mmengine - INFO - Epoch(train) [70][ 50/925] lr: 3.1700e-05 eta: 1:08:39 time: 0.5400 data_time: 0.1029 memory: 5723 grad_norm: 915.2101 loss: 411.2534 loss_cls: 144.4709 loss_bbox: 125.8384 loss_dfl: 140.9440 2024/03/27 18:50:48 - mmengine - INFO - Epoch(train) [70][100/925] lr: 3.1700e-05 eta: 1:08:19 time: 0.3759 data_time: 0.0026 memory: 5203 grad_norm: 1008.2551 loss: 401.3939 loss_cls: 142.8996 loss_bbox: 119.5991 loss_dfl: 138.8952 2024/03/27 18:51:09 - mmengine - INFO - Epoch(train) [70][150/925] lr: 3.1700e-05 eta: 1:07:58 time: 0.4090 data_time: 0.0026 memory: 5350 grad_norm: 886.3052 loss: 407.0898 loss_cls: 142.8175 loss_bbox: 124.2974 loss_dfl: 139.9749 2024/03/27 18:51:18 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:51:29 - mmengine - INFO - Epoch(train) [70][200/925] lr: 3.1700e-05 eta: 1:07:38 time: 0.4050 data_time: 0.0024 memory: 5270 grad_norm: 1082.6924 loss: 401.7809 loss_cls: 140.3353 loss_bbox: 122.2235 loss_dfl: 139.2220 2024/03/27 18:51:50 - mmengine - INFO - Epoch(train) [70][250/925] lr: 3.1700e-05 eta: 1:07:18 time: 0.4222 data_time: 0.0025 memory: 5416 grad_norm: 892.7605 loss: 419.1126 loss_cls: 148.9469 loss_bbox: 127.7844 loss_dfl: 142.3814 2024/03/27 18:52:10 - mmengine - INFO - Epoch(train) [70][300/925] lr: 3.1700e-05 eta: 1:06:57 time: 0.4013 data_time: 0.0024 memory: 5510 grad_norm: 895.9270 loss: 406.0364 loss_cls: 143.1731 loss_bbox: 122.7736 loss_dfl: 140.0898 2024/03/27 18:52:30 - mmengine - INFO - Epoch(train) [70][350/925] lr: 3.1700e-05 eta: 1:06:37 time: 0.4023 data_time: 0.0025 memory: 5363 grad_norm: 946.3750 loss: 406.9030 loss_cls: 143.0572 loss_bbox: 123.7237 loss_dfl: 140.1220 2024/03/27 18:52:51 - mmengine - INFO - Epoch(train) [70][400/925] lr: 3.1700e-05 eta: 1:06:17 time: 0.4189 data_time: 0.0024 memory: 5496 grad_norm: 880.4732 loss: 411.0792 loss_cls: 146.3220 loss_bbox: 124.1514 loss_dfl: 140.6058 2024/03/27 18:53:11 - mmengine - INFO - Epoch(train) [70][450/925] lr: 3.1700e-05 eta: 1:05:56 time: 0.3872 data_time: 0.0025 memory: 5403 grad_norm: 952.0559 loss: 411.8351 loss_cls: 145.1534 loss_bbox: 126.3894 loss_dfl: 140.2922 2024/03/27 18:53:31 - mmengine - INFO - Epoch(train) [70][500/925] lr: 3.1700e-05 eta: 1:05:36 time: 0.3960 data_time: 0.0023 memory: 5136 grad_norm: inf loss: 399.3911 loss_cls: 140.7122 loss_bbox: 119.9250 loss_dfl: 138.7539 2024/03/27 18:53:51 - mmengine - INFO - Epoch(train) [70][550/925] lr: 3.1700e-05 eta: 1:05:15 time: 0.4136 data_time: 0.0024 memory: 5456 grad_norm: 894.6185 loss: 406.9188 loss_cls: 144.7837 loss_bbox: 123.2083 loss_dfl: 138.9268 2024/03/27 18:54:11 - mmengine - INFO - Epoch(train) [70][600/925] lr: 3.1700e-05 eta: 1:04:55 time: 0.3997 data_time: 0.0024 memory: 5216 grad_norm: 946.5565 loss: 408.6020 loss_cls: 144.0210 loss_bbox: 123.6840 loss_dfl: 140.8970 2024/03/27 18:54:31 - mmengine - INFO - Epoch(train) [70][650/925] lr: 3.1700e-05 eta: 1:04:35 time: 0.3967 data_time: 0.0023 memory: 5350 grad_norm: 913.5084 loss: 407.2658 loss_cls: 143.2573 loss_bbox: 123.7960 loss_dfl: 140.2125 2024/03/27 18:54:51 - mmengine - INFO - Epoch(train) [70][700/925] lr: 3.1700e-05 eta: 1:04:14 time: 0.3911 data_time: 0.0022 memory: 5510 grad_norm: 945.6672 loss: 404.1754 loss_cls: 141.1523 loss_bbox: 123.2078 loss_dfl: 139.8153 2024/03/27 18:55:11 - mmengine - INFO - Epoch(train) [70][750/925] lr: 3.1700e-05 eta: 1:03:54 time: 0.4003 data_time: 0.0024 memory: 5403 grad_norm: 907.6339 loss: 408.3694 loss_cls: 145.1183 loss_bbox: 123.1652 loss_dfl: 140.0859 2024/03/27 18:55:30 - mmengine - INFO - Epoch(train) [70][800/925] lr: 3.1700e-05 eta: 1:03:33 time: 0.3884 data_time: 0.0024 memory: 5550 grad_norm: 961.0122 loss: 406.3617 loss_cls: 144.1875 loss_bbox: 122.4933 loss_dfl: 139.6809 2024/03/27 18:55:50 - mmengine - INFO - Epoch(train) [70][850/925] lr: 3.1700e-05 eta: 1:03:13 time: 0.3953 data_time: 0.0021 memory: 5496 grad_norm: 902.1079 loss: 406.6400 loss_cls: 143.1797 loss_bbox: 123.5587 loss_dfl: 139.9015 2024/03/27 18:56:11 - mmengine - INFO - Epoch(train) [70][900/925] lr: 3.1700e-05 eta: 1:02:53 time: 0.4247 data_time: 0.0025 memory: 5470 grad_norm: 872.1083 loss: 411.5592 loss_cls: 144.7818 loss_bbox: 125.7929 loss_dfl: 140.9845 2024/03/27 18:56:20 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:56:20 - mmengine - INFO - Saving checkpoint at 70 epochs 2024/03/27 18:56:28 - mmengine - INFO - Epoch(val) [70][ 50/625] eta: 0:00:24 time: 0.0421 data_time: 0.0009 memory: 5083 2024/03/27 18:56:31 - mmengine - INFO - Epoch(val) [70][100/625] eta: 0:00:22 time: 0.0443 data_time: 0.0004 memory: 838 2024/03/27 18:56:33 - mmengine - INFO - Epoch(val) [70][150/625] eta: 0:00:20 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 18:56:35 - mmengine - INFO - Epoch(val) [70][200/625] eta: 0:00:18 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 18:56:37 - mmengine - INFO - Epoch(val) [70][250/625] eta: 0:00:16 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 18:56:39 - mmengine - INFO - Epoch(val) [70][300/625] eta: 0:00:14 time: 0.0446 data_time: 0.0004 memory: 838 2024/03/27 18:56:42 - mmengine - INFO - Epoch(val) [70][350/625] eta: 0:00:12 time: 0.0450 data_time: 0.0004 memory: 838 2024/03/27 18:56:44 - mmengine - INFO - Epoch(val) [70][400/625] eta: 0:00:09 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 18:56:46 - mmengine - INFO - Epoch(val) [70][450/625] eta: 0:00:07 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 18:56:48 - mmengine - INFO - Epoch(val) [70][500/625] eta: 0:00:05 time: 0.0403 data_time: 0.0003 memory: 838 2024/03/27 18:56:50 - mmengine - INFO - Epoch(val) [70][550/625] eta: 0:00:03 time: 0.0347 data_time: 0.0003 memory: 838 2024/03/27 18:56:52 - mmengine - INFO - Epoch(val) [70][600/625] eta: 0:00:01 time: 0.0345 data_time: 0.0003 memory: 838 2024/03/27 18:57:05 - mmengine - INFO - Evaluating bbox... 2024/03/27 18:58:20 - mmengine - INFO - bbox_mAP_copypaste: 0.456 0.619 0.499 0.262 0.504 0.613 2024/03/27 18:58:22 - mmengine - INFO - Epoch(val) [70][625/625] coco/bbox_mAP: 0.4560 coco/bbox_mAP_50: 0.6190 coco/bbox_mAP_75: 0.4990 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5040 coco/bbox_mAP_l: 0.6130 data_time: 0.0003 time: 0.0344 2024/03/27 18:58:22 - mmengine - INFO - Switch pipeline now! 2024/03/27 18:58:42 - mmengine - INFO - Epoch(train) [71][ 50/925] lr: 2.9225e-05 eta: 1:02:22 time: 0.4039 data_time: 0.0372 memory: 4630 grad_norm: inf loss: 396.1322 loss_cls: 131.1022 loss_bbox: 125.4833 loss_dfl: 139.5467 2024/03/27 18:59:00 - mmengine - INFO - Epoch(train) [71][100/925] lr: 2.9225e-05 eta: 1:02:01 time: 0.3623 data_time: 0.0022 memory: 4830 grad_norm: 2072.1851 loss: 377.8915 loss_cls: 119.4922 loss_bbox: 120.6550 loss_dfl: 137.7444 2024/03/27 18:59:19 - mmengine - INFO - Epoch(train) [71][150/925] lr: 2.9225e-05 eta: 1:01:41 time: 0.3757 data_time: 0.0018 memory: 4656 grad_norm: 1992.8828 loss: 380.0523 loss_cls: 119.9456 loss_bbox: 122.8124 loss_dfl: 137.2943 2024/03/27 18:59:36 - mmengine - INFO - Epoch(train) [71][200/925] lr: 2.9225e-05 eta: 1:01:20 time: 0.3507 data_time: 0.0019 memory: 4710 grad_norm: 1729.1915 loss: 376.4616 loss_cls: 119.1377 loss_bbox: 119.9919 loss_dfl: 137.3320 2024/03/27 18:59:54 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 18:59:54 - mmengine - INFO - Epoch(train) [71][250/925] lr: 2.9225e-05 eta: 1:00:59 time: 0.3516 data_time: 0.0018 memory: 4590 grad_norm: 1872.9734 loss: 376.5028 loss_cls: 116.6848 loss_bbox: 121.7965 loss_dfl: 138.0216 2024/03/27 19:00:12 - mmengine - INFO - Epoch(train) [71][300/925] lr: 2.9225e-05 eta: 1:00:39 time: 0.3600 data_time: 0.0019 memory: 4830 grad_norm: 1676.6852 loss: 378.3177 loss_cls: 118.9120 loss_bbox: 121.7590 loss_dfl: 137.6467 2024/03/27 19:00:31 - mmengine - INFO - Epoch(train) [71][350/925] lr: 2.9225e-05 eta: 1:00:18 time: 0.3700 data_time: 0.0019 memory: 4763 grad_norm: 1773.6135 loss: 378.0688 loss_cls: 119.3850 loss_bbox: 121.1533 loss_dfl: 137.5304 2024/03/27 19:00:49 - mmengine - INFO - Epoch(train) [71][400/925] lr: 2.9225e-05 eta: 0:59:57 time: 0.3626 data_time: 0.0018 memory: 4656 grad_norm: 1722.2733 loss: 380.0972 loss_cls: 120.3016 loss_bbox: 121.9783 loss_dfl: 137.8173 2024/03/27 19:01:07 - mmengine - INFO - Epoch(train) [71][450/925] lr: 2.9225e-05 eta: 0:59:37 time: 0.3595 data_time: 0.0019 memory: 4816 grad_norm: 1818.6025 loss: 372.4195 loss_cls: 117.4281 loss_bbox: 118.6465 loss_dfl: 136.3449 2024/03/27 19:01:25 - mmengine - INFO - Epoch(train) [71][500/925] lr: 2.9225e-05 eta: 0:59:16 time: 0.3613 data_time: 0.0018 memory: 4723 grad_norm: 1713.7203 loss: 375.9358 loss_cls: 118.5294 loss_bbox: 120.1859 loss_dfl: 137.2205 2024/03/27 19:01:43 - mmengine - INFO - Epoch(train) [71][550/925] lr: 2.9225e-05 eta: 0:58:55 time: 0.3713 data_time: 0.0018 memory: 4856 grad_norm: 1714.4885 loss: 380.0407 loss_cls: 118.3053 loss_bbox: 123.6784 loss_dfl: 138.0569 2024/03/27 19:02:02 - mmengine - INFO - Epoch(train) [71][600/925] lr: 2.9225e-05 eta: 0:58:35 time: 0.3666 data_time: 0.0019 memory: 4763 grad_norm: 1454.6933 loss: 365.3095 loss_cls: 113.2304 loss_bbox: 117.0045 loss_dfl: 135.0746 2024/03/27 19:02:20 - mmengine - INFO - Epoch(train) [71][650/925] lr: 2.9225e-05 eta: 0:58:14 time: 0.3648 data_time: 0.0018 memory: 4736 grad_norm: 1600.0967 loss: 375.3432 loss_cls: 118.3837 loss_bbox: 120.0151 loss_dfl: 136.9444 2024/03/27 19:02:37 - mmengine - INFO - Epoch(train) [71][700/925] lr: 2.9225e-05 eta: 0:57:54 time: 0.3420 data_time: 0.0019 memory: 4763 grad_norm: 1630.4095 loss: 375.0002 loss_cls: 117.4828 loss_bbox: 120.0458 loss_dfl: 137.4716 2024/03/27 19:02:55 - mmengine - INFO - Epoch(train) [71][750/925] lr: 2.9225e-05 eta: 0:57:33 time: 0.3635 data_time: 0.0019 memory: 4910 grad_norm: 1673.0845 loss: 378.7315 loss_cls: 117.6370 loss_bbox: 122.3146 loss_dfl: 138.7799 2024/03/27 19:03:14 - mmengine - INFO - Epoch(train) [71][800/925] lr: 2.9225e-05 eta: 0:57:12 time: 0.3663 data_time: 0.0018 memory: 4736 grad_norm: inf loss: 374.4853 loss_cls: 116.4243 loss_bbox: 120.6371 loss_dfl: 137.4240 2024/03/27 19:03:31 - mmengine - INFO - Epoch(train) [71][850/925] lr: 2.9225e-05 eta: 0:56:52 time: 0.3541 data_time: 0.0019 memory: 4656 grad_norm: 1738.1491 loss: 378.8028 loss_cls: 118.8508 loss_bbox: 120.7562 loss_dfl: 139.1958 2024/03/27 19:03:49 - mmengine - INFO - Epoch(train) [71][900/925] lr: 2.9225e-05 eta: 0:56:31 time: 0.3538 data_time: 0.0019 memory: 4803 grad_norm: 1489.3712 loss: 369.5956 loss_cls: 114.6572 loss_bbox: 118.4277 loss_dfl: 136.5106 2024/03/27 19:03:58 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:04:01 - mmengine - INFO - Epoch(val) [71][ 50/625] eta: 0:00:25 time: 0.0444 data_time: 0.0009 memory: 4550 2024/03/27 19:04:03 - mmengine - INFO - Epoch(val) [71][100/625] eta: 0:00:22 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 19:04:05 - mmengine - INFO - Epoch(val) [71][150/625] eta: 0:00:20 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 19:04:07 - mmengine - INFO - Epoch(val) [71][200/625] eta: 0:00:18 time: 0.0421 data_time: 0.0004 memory: 838 2024/03/27 19:04:09 - mmengine - INFO - Epoch(val) [71][250/625] eta: 0:00:16 time: 0.0422 data_time: 0.0004 memory: 838 2024/03/27 19:04:11 - mmengine - INFO - Epoch(val) [71][300/625] eta: 0:00:13 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 19:04:13 - mmengine - INFO - Epoch(val) [71][350/625] eta: 0:00:11 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 19:04:16 - mmengine - INFO - Epoch(val) [71][400/625] eta: 0:00:09 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 19:04:18 - mmengine - INFO - Epoch(val) [71][450/625] eta: 0:00:07 time: 0.0425 data_time: 0.0004 memory: 838 2024/03/27 19:04:20 - mmengine - INFO - Epoch(val) [71][500/625] eta: 0:00:05 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 19:04:22 - mmengine - INFO - Epoch(val) [71][550/625] eta: 0:00:03 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 19:04:24 - mmengine - INFO - Epoch(val) [71][600/625] eta: 0:00:01 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 19:04:39 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:06:02 - mmengine - INFO - bbox_mAP_copypaste: 0.457 0.620 0.500 0.261 0.505 0.615 2024/03/27 19:06:03 - mmengine - INFO - Epoch(val) [71][625/625] coco/bbox_mAP: 0.4570 coco/bbox_mAP_50: 0.6200 coco/bbox_mAP_75: 0.5000 coco/bbox_mAP_s: 0.2610 coco/bbox_mAP_m: 0.5050 coco/bbox_mAP_l: 0.6150 data_time: 0.0004 time: 0.0421 2024/03/27 19:06:23 - mmengine - INFO - Epoch(train) [72][ 50/925] lr: 2.6750e-05 eta: 0:56:00 time: 0.3945 data_time: 0.0423 memory: 4710 grad_norm: 1531.3934 loss: 366.3104 loss_cls: 116.3251 loss_bbox: 114.7436 loss_dfl: 135.2416 2024/03/27 19:06:41 - mmengine - INFO - Epoch(train) [72][100/925] lr: 2.6750e-05 eta: 0:55:40 time: 0.3618 data_time: 0.0020 memory: 4643 grad_norm: 1579.4113 loss: 367.3793 loss_cls: 114.4886 loss_bbox: 117.1945 loss_dfl: 135.6962 2024/03/27 19:06:59 - mmengine - INFO - Epoch(train) [72][150/925] lr: 2.6750e-05 eta: 0:55:19 time: 0.3489 data_time: 0.0019 memory: 4830 grad_norm: 1681.9504 loss: 369.0128 loss_cls: 114.1545 loss_bbox: 118.5468 loss_dfl: 136.3115 2024/03/27 19:07:18 - mmengine - INFO - Epoch(train) [72][200/925] lr: 2.6750e-05 eta: 0:54:59 time: 0.3797 data_time: 0.0020 memory: 4830 grad_norm: 1542.3798 loss: 376.3522 loss_cls: 116.5131 loss_bbox: 122.6148 loss_dfl: 137.2243 2024/03/27 19:07:36 - mmengine - INFO - Epoch(train) [72][250/925] lr: 2.6750e-05 eta: 0:54:38 time: 0.3687 data_time: 0.0030 memory: 4630 grad_norm: 1598.2758 loss: 369.0422 loss_cls: 114.3340 loss_bbox: 117.9666 loss_dfl: 136.7415 2024/03/27 19:07:54 - mmengine - INFO - Epoch(train) [72][300/925] lr: 2.6750e-05 eta: 0:54:18 time: 0.3634 data_time: 0.0018 memory: 4550 grad_norm: 1680.0816 loss: 367.0783 loss_cls: 112.6558 loss_bbox: 118.3782 loss_dfl: 136.0442 2024/03/27 19:08:03 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:08:12 - mmengine - INFO - Epoch(train) [72][350/925] lr: 2.6750e-05 eta: 0:53:57 time: 0.3602 data_time: 0.0019 memory: 4830 grad_norm: 1499.2064 loss: 371.4962 loss_cls: 116.0009 loss_bbox: 118.6129 loss_dfl: 136.8824 2024/03/27 19:08:31 - mmengine - INFO - Epoch(train) [72][400/925] lr: 2.6750e-05 eta: 0:53:36 time: 0.3662 data_time: 0.0019 memory: 4643 grad_norm: 1504.7511 loss: 370.8151 loss_cls: 112.7603 loss_bbox: 120.2269 loss_dfl: 137.8279 2024/03/27 19:08:50 - mmengine - INFO - Epoch(train) [72][450/925] lr: 2.6750e-05 eta: 0:53:16 time: 0.3739 data_time: 0.0019 memory: 4696 grad_norm: 1490.0373 loss: 372.1802 loss_cls: 116.4055 loss_bbox: 119.1513 loss_dfl: 136.6234 2024/03/27 19:09:08 - mmengine - INFO - Epoch(train) [72][500/925] lr: 2.6750e-05 eta: 0:52:55 time: 0.3691 data_time: 0.0020 memory: 4870 grad_norm: 1476.4670 loss: 378.8733 loss_cls: 115.9223 loss_bbox: 124.8648 loss_dfl: 138.0861 2024/03/27 19:09:27 - mmengine - INFO - Epoch(train) [72][550/925] lr: 2.6750e-05 eta: 0:52:35 time: 0.3717 data_time: 0.0019 memory: 4696 grad_norm: 1510.8169 loss: 369.8846 loss_cls: 114.3371 loss_bbox: 119.9509 loss_dfl: 135.5966 2024/03/27 19:09:45 - mmengine - INFO - Epoch(train) [72][600/925] lr: 2.6750e-05 eta: 0:52:14 time: 0.3597 data_time: 0.0020 memory: 4843 grad_norm: 1445.5311 loss: 370.4569 loss_cls: 115.5187 loss_bbox: 119.4487 loss_dfl: 135.4894 2024/03/27 19:10:03 - mmengine - INFO - Epoch(train) [72][650/925] lr: 2.6750e-05 eta: 0:51:54 time: 0.3745 data_time: 0.0020 memory: 4736 grad_norm: 1444.4484 loss: 372.2869 loss_cls: 114.6877 loss_bbox: 120.2187 loss_dfl: 137.3806 2024/03/27 19:10:22 - mmengine - INFO - Epoch(train) [72][700/925] lr: 2.6750e-05 eta: 0:51:33 time: 0.3739 data_time: 0.0020 memory: 4696 grad_norm: 1480.8677 loss: 368.4403 loss_cls: 114.0169 loss_bbox: 118.2072 loss_dfl: 136.2162 2024/03/27 19:10:40 - mmengine - INFO - Epoch(train) [72][750/925] lr: 2.6750e-05 eta: 0:51:13 time: 0.3609 data_time: 0.0019 memory: 4896 grad_norm: 1534.2656 loss: 373.2578 loss_cls: 117.1647 loss_bbox: 117.9042 loss_dfl: 138.1889 2024/03/27 19:10:58 - mmengine - INFO - Epoch(train) [72][800/925] lr: 2.6750e-05 eta: 0:50:52 time: 0.3608 data_time: 0.0019 memory: 4736 grad_norm: 1589.3640 loss: 367.1120 loss_cls: 112.6429 loss_bbox: 118.2375 loss_dfl: 136.2315 2024/03/27 19:11:17 - mmengine - INFO - Epoch(train) [72][850/925] lr: 2.6750e-05 eta: 0:50:32 time: 0.3656 data_time: 0.0020 memory: 4843 grad_norm: 1468.6800 loss: 369.9909 loss_cls: 114.1443 loss_bbox: 118.6954 loss_dfl: 137.1511 2024/03/27 19:11:35 - mmengine - INFO - Epoch(train) [72][900/925] lr: 2.6750e-05 eta: 0:50:11 time: 0.3648 data_time: 0.0020 memory: 4670 grad_norm: 1374.8473 loss: 367.6114 loss_cls: 115.3409 loss_bbox: 116.4515 loss_dfl: 135.8190 2024/03/27 19:11:43 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:11:46 - mmengine - INFO - Epoch(val) [72][ 50/625] eta: 0:00:25 time: 0.0440 data_time: 0.0008 memory: 4790 2024/03/27 19:11:48 - mmengine - INFO - Epoch(val) [72][100/625] eta: 0:00:23 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 19:11:50 - mmengine - INFO - Epoch(val) [72][150/625] eta: 0:00:20 time: 0.0420 data_time: 0.0004 memory: 838 2024/03/27 19:11:52 - mmengine - INFO - Epoch(val) [72][200/625] eta: 0:00:18 time: 0.0420 data_time: 0.0003 memory: 838 2024/03/27 19:11:55 - mmengine - INFO - Epoch(val) [72][250/625] eta: 0:00:16 time: 0.0432 data_time: 0.0004 memory: 838 2024/03/27 19:11:57 - mmengine - INFO - Epoch(val) [72][300/625] eta: 0:00:14 time: 0.0440 data_time: 0.0004 memory: 838 2024/03/27 19:11:59 - mmengine - INFO - Epoch(val) [72][350/625] eta: 0:00:11 time: 0.0443 data_time: 0.0004 memory: 838 2024/03/27 19:12:01 - mmengine - INFO - Epoch(val) [72][400/625] eta: 0:00:09 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 19:12:04 - mmengine - INFO - Epoch(val) [72][450/625] eta: 0:00:07 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 19:12:06 - mmengine - INFO - Epoch(val) [72][500/625] eta: 0:00:05 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 19:12:08 - mmengine - INFO - Epoch(val) [72][550/625] eta: 0:00:03 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 19:12:10 - mmengine - INFO - Epoch(val) [72][600/625] eta: 0:00:01 time: 0.0430 data_time: 0.0003 memory: 838 2024/03/27 19:12:24 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:13:44 - mmengine - INFO - bbox_mAP_copypaste: 0.458 0.621 0.500 0.263 0.506 0.616 2024/03/27 19:13:46 - mmengine - INFO - Epoch(val) [72][625/625] coco/bbox_mAP: 0.4580 coco/bbox_mAP_50: 0.6210 coco/bbox_mAP_75: 0.5000 coco/bbox_mAP_s: 0.2630 coco/bbox_mAP_m: 0.5060 coco/bbox_mAP_l: 0.6160 data_time: 0.0003 time: 0.0421 2024/03/27 19:14:06 - mmengine - INFO - Epoch(train) [73][ 50/925] lr: 2.4275e-05 eta: 0:49:41 time: 0.3999 data_time: 0.0439 memory: 5216 grad_norm: 1424.8470 loss: 369.0111 loss_cls: 113.5702 loss_bbox: 118.7432 loss_dfl: 136.6977 2024/03/27 19:14:24 - mmengine - INFO - Epoch(train) [73][100/925] lr: 2.4275e-05 eta: 0:49:20 time: 0.3578 data_time: 0.0020 memory: 4736 grad_norm: 1362.7591 loss: 367.6444 loss_cls: 112.6622 loss_bbox: 119.1052 loss_dfl: 135.8770 2024/03/27 19:14:42 - mmengine - INFO - Epoch(train) [73][150/925] lr: 2.4275e-05 eta: 0:49:00 time: 0.3695 data_time: 0.0019 memory: 4696 grad_norm: 1527.8307 loss: 365.4372 loss_cls: 112.4145 loss_bbox: 117.3324 loss_dfl: 135.6902 2024/03/27 19:15:00 - mmengine - INFO - Epoch(train) [73][200/925] lr: 2.4275e-05 eta: 0:48:39 time: 0.3480 data_time: 0.0019 memory: 4803 grad_norm: 1418.5652 loss: 376.2026 loss_cls: 117.6077 loss_bbox: 120.6143 loss_dfl: 137.9806 2024/03/27 19:15:18 - mmengine - INFO - Epoch(train) [73][250/925] lr: 2.4275e-05 eta: 0:48:19 time: 0.3697 data_time: 0.0020 memory: 4830 grad_norm: 1418.8224 loss: 367.2936 loss_cls: 112.5506 loss_bbox: 118.9282 loss_dfl: 135.8147 2024/03/27 19:15:37 - mmengine - INFO - Epoch(train) [73][300/925] lr: 2.4275e-05 eta: 0:47:58 time: 0.3788 data_time: 0.0019 memory: 4763 grad_norm: 1517.9677 loss: 367.6609 loss_cls: 114.4990 loss_bbox: 117.5854 loss_dfl: 135.5765 2024/03/27 19:15:55 - mmengine - INFO - Epoch(train) [73][350/925] lr: 2.4275e-05 eta: 0:47:38 time: 0.3618 data_time: 0.0020 memory: 4830 grad_norm: 1357.8640 loss: 361.4890 loss_cls: 110.0766 loss_bbox: 115.9377 loss_dfl: 135.4748 2024/03/27 19:16:13 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:16:13 - mmengine - INFO - Epoch(train) [73][400/925] lr: 2.4275e-05 eta: 0:47:17 time: 0.3522 data_time: 0.0020 memory: 4790 grad_norm: 1400.6177 loss: 365.0150 loss_cls: 111.1549 loss_bbox: 118.5692 loss_dfl: 135.2910 2024/03/27 19:16:32 - mmengine - INFO - Epoch(train) [73][450/925] lr: 2.4275e-05 eta: 0:46:57 time: 0.3727 data_time: 0.0020 memory: 4616 grad_norm: 1394.9299 loss: 374.3530 loss_cls: 115.3974 loss_bbox: 121.1242 loss_dfl: 137.8315 2024/03/27 19:16:50 - mmengine - INFO - Epoch(train) [73][500/925] lr: 2.4275e-05 eta: 0:46:36 time: 0.3711 data_time: 0.0019 memory: 4723 grad_norm: 1445.5926 loss: 362.7163 loss_cls: 112.1978 loss_bbox: 116.6628 loss_dfl: 133.8557 2024/03/27 19:17:09 - mmengine - INFO - Epoch(train) [73][550/925] lr: 2.4275e-05 eta: 0:46:16 time: 0.3639 data_time: 0.0020 memory: 4803 grad_norm: 1406.9942 loss: 373.4967 loss_cls: 116.7209 loss_bbox: 120.5694 loss_dfl: 136.2065 2024/03/27 19:17:27 - mmengine - INFO - Epoch(train) [73][600/925] lr: 2.4275e-05 eta: 0:45:55 time: 0.3591 data_time: 0.0019 memory: 4723 grad_norm: 1429.6682 loss: 365.1615 loss_cls: 110.0545 loss_bbox: 118.5472 loss_dfl: 136.5598 2024/03/27 19:17:45 - mmengine - INFO - Epoch(train) [73][650/925] lr: 2.4275e-05 eta: 0:45:35 time: 0.3647 data_time: 0.0019 memory: 4830 grad_norm: 1427.2033 loss: 376.0614 loss_cls: 115.3700 loss_bbox: 122.9890 loss_dfl: 137.7024 2024/03/27 19:18:03 - mmengine - INFO - Epoch(train) [73][700/925] lr: 2.4275e-05 eta: 0:45:14 time: 0.3681 data_time: 0.0019 memory: 4683 grad_norm: 1534.1270 loss: 362.7057 loss_cls: 110.4544 loss_bbox: 118.0294 loss_dfl: 134.2219 2024/03/27 19:18:21 - mmengine - INFO - Epoch(train) [73][750/925] lr: 2.4275e-05 eta: 0:44:54 time: 0.3622 data_time: 0.0020 memory: 4683 grad_norm: 1550.7439 loss: 364.4273 loss_cls: 111.4785 loss_bbox: 116.2584 loss_dfl: 136.6904 2024/03/27 19:18:40 - mmengine - INFO - Epoch(train) [73][800/925] lr: 2.4275e-05 eta: 0:44:34 time: 0.3678 data_time: 0.0020 memory: 4683 grad_norm: 1490.6148 loss: 368.3319 loss_cls: 113.8069 loss_bbox: 119.0404 loss_dfl: 135.4845 2024/03/27 19:18:58 - mmengine - INFO - Epoch(train) [73][850/925] lr: 2.4275e-05 eta: 0:44:13 time: 0.3539 data_time: 0.0021 memory: 4883 grad_norm: 1538.0800 loss: 371.8596 loss_cls: 114.7226 loss_bbox: 120.1254 loss_dfl: 137.0116 2024/03/27 19:19:16 - mmengine - INFO - Epoch(train) [73][900/925] lr: 2.4275e-05 eta: 0:43:53 time: 0.3634 data_time: 0.0020 memory: 4803 grad_norm: 1483.3568 loss: 369.2199 loss_cls: 114.7920 loss_bbox: 118.8015 loss_dfl: 135.6264 2024/03/27 19:19:24 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:19:27 - mmengine - INFO - Epoch(val) [73][ 50/625] eta: 0:00:25 time: 0.0436 data_time: 0.0009 memory: 4536 2024/03/27 19:19:29 - mmengine - INFO - Epoch(val) [73][100/625] eta: 0:00:24 time: 0.0497 data_time: 0.0004 memory: 838 2024/03/27 19:19:31 - mmengine - INFO - Epoch(val) [73][150/625] eta: 0:00:21 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 19:19:34 - mmengine - INFO - Epoch(val) [73][200/625] eta: 0:00:19 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 19:19:36 - mmengine - INFO - Epoch(val) [73][250/625] eta: 0:00:16 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 19:19:38 - mmengine - INFO - Epoch(val) [73][300/625] eta: 0:00:14 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 19:19:40 - mmengine - INFO - Epoch(val) [73][350/625] eta: 0:00:12 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 19:19:42 - mmengine - INFO - Epoch(val) [73][400/625] eta: 0:00:09 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 19:19:45 - mmengine - INFO - Epoch(val) [73][450/625] eta: 0:00:07 time: 0.0442 data_time: 0.0004 memory: 838 2024/03/27 19:19:47 - mmengine - INFO - Epoch(val) [73][500/625] eta: 0:00:05 time: 0.0439 data_time: 0.0003 memory: 838 2024/03/27 19:19:49 - mmengine - INFO - Epoch(val) [73][550/625] eta: 0:00:03 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 19:19:51 - mmengine - INFO - Epoch(val) [73][600/625] eta: 0:00:01 time: 0.0430 data_time: 0.0004 memory: 838 2024/03/27 19:20:04 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:21:17 - mmengine - INFO - bbox_mAP_copypaste: 0.458 0.622 0.501 0.268 0.507 0.617 2024/03/27 19:21:18 - mmengine - INFO - Epoch(val) [73][625/625] coco/bbox_mAP: 0.4580 coco/bbox_mAP_50: 0.6220 coco/bbox_mAP_75: 0.5010 coco/bbox_mAP_s: 0.2680 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6170 data_time: 0.0004 time: 0.0406 2024/03/27 19:21:38 - mmengine - INFO - Epoch(train) [74][ 50/925] lr: 2.1800e-05 eta: 0:43:22 time: 0.3902 data_time: 0.0408 memory: 4630 grad_norm: 1408.8266 loss: 367.8359 loss_cls: 113.1419 loss_bbox: 118.2081 loss_dfl: 136.4859 2024/03/27 19:21:56 - mmengine - INFO - Epoch(train) [74][100/925] lr: 2.1800e-05 eta: 0:43:01 time: 0.3614 data_time: 0.0019 memory: 4736 grad_norm: 1457.2740 loss: 370.5204 loss_cls: 113.2714 loss_bbox: 120.9896 loss_dfl: 136.2594 2024/03/27 19:22:15 - mmengine - INFO - Epoch(train) [74][150/925] lr: 2.1800e-05 eta: 0:42:41 time: 0.3704 data_time: 0.0019 memory: 4776 grad_norm: 1485.4506 loss: 370.5458 loss_cls: 114.0015 loss_bbox: 119.2981 loss_dfl: 137.2462 2024/03/27 19:22:32 - mmengine - INFO - Epoch(train) [74][200/925] lr: 2.1800e-05 eta: 0:42:21 time: 0.3519 data_time: 0.0020 memory: 4830 grad_norm: 1339.0206 loss: 370.0942 loss_cls: 113.5867 loss_bbox: 120.0017 loss_dfl: 136.5058 2024/03/27 19:22:50 - mmengine - INFO - Epoch(train) [74][250/925] lr: 2.1800e-05 eta: 0:42:00 time: 0.3481 data_time: 0.0021 memory: 4630 grad_norm: 1452.6306 loss: 365.4667 loss_cls: 112.6208 loss_bbox: 116.7544 loss_dfl: 136.0915 2024/03/27 19:23:08 - mmengine - INFO - Epoch(train) [74][300/925] lr: 2.1800e-05 eta: 0:41:40 time: 0.3641 data_time: 0.0020 memory: 4816 grad_norm: 1352.0168 loss: 366.8793 loss_cls: 110.6583 loss_bbox: 119.5645 loss_dfl: 136.6566 2024/03/27 19:23:26 - mmengine - INFO - Epoch(train) [74][350/925] lr: 2.1800e-05 eta: 0:41:19 time: 0.3633 data_time: 0.0020 memory: 5016 grad_norm: 1516.9642 loss: 370.7898 loss_cls: 111.5024 loss_bbox: 122.4395 loss_dfl: 136.8480 2024/03/27 19:23:44 - mmengine - INFO - Epoch(train) [74][400/925] lr: 2.1800e-05 eta: 0:40:59 time: 0.3640 data_time: 0.0020 memory: 4843 grad_norm: 1410.7934 loss: 374.6824 loss_cls: 116.2900 loss_bbox: 121.0910 loss_dfl: 137.3014 2024/03/27 19:24:03 - mmengine - INFO - Epoch(train) [74][450/925] lr: 2.1800e-05 eta: 0:40:38 time: 0.3631 data_time: 0.0021 memory: 4710 grad_norm: 1490.6944 loss: 370.0348 loss_cls: 114.0265 loss_bbox: 119.7146 loss_dfl: 136.2937 2024/03/27 19:24:12 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:24:21 - mmengine - INFO - Epoch(train) [74][500/925] lr: 2.1800e-05 eta: 0:40:18 time: 0.3583 data_time: 0.0019 memory: 4710 grad_norm: 1441.3876 loss: 372.9834 loss_cls: 113.7891 loss_bbox: 121.4532 loss_dfl: 137.7412 2024/03/27 19:24:38 - mmengine - INFO - Epoch(train) [74][550/925] lr: 2.1800e-05 eta: 0:39:57 time: 0.3561 data_time: 0.0020 memory: 4816 grad_norm: 1527.2759 loss: 367.2086 loss_cls: 111.8244 loss_bbox: 118.9579 loss_dfl: 136.4263 2024/03/27 19:24:56 - mmengine - INFO - Epoch(train) [74][600/925] lr: 2.1800e-05 eta: 0:39:37 time: 0.3589 data_time: 0.0019 memory: 4803 grad_norm: 1392.6486 loss: 362.2003 loss_cls: 109.7933 loss_bbox: 118.0300 loss_dfl: 134.3770 2024/03/27 19:25:14 - mmengine - INFO - Epoch(train) [74][650/925] lr: 2.1800e-05 eta: 0:39:17 time: 0.3598 data_time: 0.0020 memory: 4776 grad_norm: 1427.0507 loss: 367.0659 loss_cls: 111.5027 loss_bbox: 119.6586 loss_dfl: 135.9047 2024/03/27 19:25:32 - mmengine - INFO - Epoch(train) [74][700/925] lr: 2.1800e-05 eta: 0:38:56 time: 0.3530 data_time: 0.0020 memory: 4776 grad_norm: 1514.2920 loss: 361.4053 loss_cls: 109.4818 loss_bbox: 117.3256 loss_dfl: 134.5979 2024/03/27 19:25:49 - mmengine - INFO - Epoch(train) [74][750/925] lr: 2.1800e-05 eta: 0:38:36 time: 0.3460 data_time: 0.0020 memory: 4670 grad_norm: 1390.8839 loss: 368.9282 loss_cls: 112.8880 loss_bbox: 118.1193 loss_dfl: 137.9208 2024/03/27 19:26:08 - mmengine - INFO - Epoch(train) [74][800/925] lr: 2.1800e-05 eta: 0:38:15 time: 0.3732 data_time: 0.0019 memory: 4843 grad_norm: 1479.8229 loss: 360.0905 loss_cls: 109.7226 loss_bbox: 115.3532 loss_dfl: 135.0146 2024/03/27 19:26:26 - mmengine - INFO - Epoch(train) [74][850/925] lr: 2.1800e-05 eta: 0:37:55 time: 0.3604 data_time: 0.0021 memory: 4963 grad_norm: 1356.0538 loss: 374.6563 loss_cls: 116.8583 loss_bbox: 121.1560 loss_dfl: 136.6420 2024/03/27 19:26:43 - mmengine - INFO - Epoch(train) [74][900/925] lr: 2.1800e-05 eta: 0:37:34 time: 0.3442 data_time: 0.0020 memory: 4656 grad_norm: 1412.9926 loss: 368.7428 loss_cls: 114.5555 loss_bbox: 117.8211 loss_dfl: 136.3662 2024/03/27 19:26:52 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:26:55 - mmengine - INFO - Epoch(val) [74][ 50/625] eta: 0:00:25 time: 0.0436 data_time: 0.0009 memory: 4630 2024/03/27 19:26:57 - mmengine - INFO - Epoch(val) [74][100/625] eta: 0:00:22 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 19:26:59 - mmengine - INFO - Epoch(val) [74][150/625] eta: 0:00:20 time: 0.0444 data_time: 0.0004 memory: 838 2024/03/27 19:27:01 - mmengine - INFO - Epoch(val) [74][200/625] eta: 0:00:18 time: 0.0447 data_time: 0.0004 memory: 838 2024/03/27 19:27:03 - mmengine - INFO - Epoch(val) [74][250/625] eta: 0:00:16 time: 0.0443 data_time: 0.0004 memory: 838 2024/03/27 19:27:06 - mmengine - INFO - Epoch(val) [74][300/625] eta: 0:00:14 time: 0.0437 data_time: 0.0004 memory: 838 2024/03/27 19:27:08 - mmengine - INFO - Epoch(val) [74][350/625] eta: 0:00:12 time: 0.0440 data_time: 0.0004 memory: 838 2024/03/27 19:27:10 - mmengine - INFO - Epoch(val) [74][400/625] eta: 0:00:09 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 19:27:12 - mmengine - INFO - Epoch(val) [74][450/625] eta: 0:00:07 time: 0.0420 data_time: 0.0004 memory: 838 2024/03/27 19:27:14 - mmengine - INFO - Epoch(val) [74][500/625] eta: 0:00:05 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 19:27:17 - mmengine - INFO - Epoch(val) [74][550/625] eta: 0:00:03 time: 0.0434 data_time: 0.0004 memory: 838 2024/03/27 19:27:19 - mmengine - INFO - Epoch(val) [74][600/625] eta: 0:00:01 time: 0.0433 data_time: 0.0004 memory: 838 2024/03/27 19:27:33 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:28:53 - mmengine - INFO - bbox_mAP_copypaste: 0.459 0.622 0.501 0.268 0.507 0.618 2024/03/27 19:28:55 - mmengine - INFO - Epoch(val) [74][625/625] coco/bbox_mAP: 0.4590 coco/bbox_mAP_50: 0.6220 coco/bbox_mAP_75: 0.5010 coco/bbox_mAP_s: 0.2680 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6180 data_time: 0.0003 time: 0.0417 2024/03/27 19:29:14 - mmengine - INFO - Epoch(train) [75][ 50/925] lr: 1.9325e-05 eta: 0:37:04 time: 0.3828 data_time: 0.0470 memory: 4883 grad_norm: 1387.2249 loss: 359.4847 loss_cls: 106.8476 loss_bbox: 117.2914 loss_dfl: 135.3457 2024/03/27 19:29:31 - mmengine - INFO - Epoch(train) [75][100/925] lr: 1.9325e-05 eta: 0:36:43 time: 0.3454 data_time: 0.0020 memory: 4670 grad_norm: 1360.8060 loss: 362.9997 loss_cls: 108.1080 loss_bbox: 118.5314 loss_dfl: 136.3602 2024/03/27 19:29:48 - mmengine - INFO - Epoch(train) [75][150/925] lr: 1.9325e-05 eta: 0:36:23 time: 0.3319 data_time: 0.0020 memory: 4803 grad_norm: 1424.5565 loss: 364.8400 loss_cls: 111.2191 loss_bbox: 118.3858 loss_dfl: 135.2351 2024/03/27 19:30:05 - mmengine - INFO - Epoch(train) [75][200/925] lr: 1.9325e-05 eta: 0:36:02 time: 0.3418 data_time: 0.0020 memory: 4683 grad_norm: 1353.9935 loss: 366.0250 loss_cls: 109.2204 loss_bbox: 120.2039 loss_dfl: 136.6007 2024/03/27 19:30:23 - mmengine - INFO - Epoch(train) [75][250/925] lr: 1.9325e-05 eta: 0:35:42 time: 0.3496 data_time: 0.0020 memory: 4723 grad_norm: 1357.6434 loss: 364.0970 loss_cls: 110.7203 loss_bbox: 118.3288 loss_dfl: 135.0479 2024/03/27 19:30:40 - mmengine - INFO - Epoch(train) [75][300/925] lr: 1.9325e-05 eta: 0:35:22 time: 0.3487 data_time: 0.0019 memory: 4723 grad_norm: 1389.4959 loss: 367.5626 loss_cls: 111.0129 loss_bbox: 119.7281 loss_dfl: 136.8216 2024/03/27 19:30:58 - mmengine - INFO - Epoch(train) [75][350/925] lr: 1.9325e-05 eta: 0:35:01 time: 0.3542 data_time: 0.0020 memory: 4990 grad_norm: 1486.9704 loss: 371.3594 loss_cls: 117.2331 loss_bbox: 117.5244 loss_dfl: 136.6019 2024/03/27 19:31:16 - mmengine - INFO - Epoch(train) [75][400/925] lr: 1.9325e-05 eta: 0:34:41 time: 0.3616 data_time: 0.0020 memory: 4763 grad_norm: 1356.6302 loss: 370.6952 loss_cls: 113.4183 loss_bbox: 120.0852 loss_dfl: 137.1917 2024/03/27 19:31:33 - mmengine - INFO - Epoch(train) [75][450/925] lr: 1.9325e-05 eta: 0:34:20 time: 0.3380 data_time: 0.0020 memory: 4710 grad_norm: 1395.1113 loss: 361.8523 loss_cls: 111.0851 loss_bbox: 115.5840 loss_dfl: 135.1833 2024/03/27 19:31:51 - mmengine - INFO - Epoch(train) [75][500/925] lr: 1.9325e-05 eta: 0:34:00 time: 0.3541 data_time: 0.0019 memory: 4843 grad_norm: 1389.0195 loss: 360.6526 loss_cls: 109.0507 loss_bbox: 116.5658 loss_dfl: 135.0361 2024/03/27 19:32:08 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:32:08 - mmengine - INFO - Epoch(train) [75][550/925] lr: 1.9325e-05 eta: 0:33:40 time: 0.3399 data_time: 0.0020 memory: 4856 grad_norm: 1426.8603 loss: 368.2926 loss_cls: 111.6586 loss_bbox: 119.6789 loss_dfl: 136.9552 2024/03/27 19:32:25 - mmengine - INFO - Epoch(train) [75][600/925] lr: 1.9325e-05 eta: 0:33:19 time: 0.3407 data_time: 0.0020 memory: 4790 grad_norm: 1404.0777 loss: 366.0742 loss_cls: 111.5901 loss_bbox: 118.8490 loss_dfl: 135.6351 2024/03/27 19:32:41 - mmengine - INFO - Epoch(train) [75][650/925] lr: 1.9325e-05 eta: 0:32:59 time: 0.3309 data_time: 0.0020 memory: 4750 grad_norm: 1426.1253 loss: 361.9470 loss_cls: 111.4351 loss_bbox: 115.0398 loss_dfl: 135.4721 2024/03/27 19:32:59 - mmengine - INFO - Epoch(train) [75][700/925] lr: 1.9325e-05 eta: 0:32:38 time: 0.3515 data_time: 0.0021 memory: 4843 grad_norm: 1352.8900 loss: 363.1502 loss_cls: 110.3932 loss_bbox: 117.9193 loss_dfl: 134.8378 2024/03/27 19:33:16 - mmengine - INFO - Epoch(train) [75][750/925] lr: 1.9325e-05 eta: 0:32:18 time: 0.3491 data_time: 0.0020 memory: 4723 grad_norm: 1331.9882 loss: 359.0522 loss_cls: 110.3572 loss_bbox: 115.5086 loss_dfl: 133.1864 2024/03/27 19:33:33 - mmengine - INFO - Epoch(train) [75][800/925] lr: 1.9325e-05 eta: 0:31:58 time: 0.3374 data_time: 0.0020 memory: 4723 grad_norm: 1407.3616 loss: 364.6564 loss_cls: 111.0166 loss_bbox: 118.1315 loss_dfl: 135.5082 2024/03/27 19:33:50 - mmengine - INFO - Epoch(train) [75][850/925] lr: 1.9325e-05 eta: 0:31:37 time: 0.3427 data_time: 0.0020 memory: 4683 grad_norm: 1428.1202 loss: 365.4724 loss_cls: 110.3455 loss_bbox: 117.8960 loss_dfl: 137.2310 2024/03/27 19:34:08 - mmengine - INFO - Epoch(train) [75][900/925] lr: 1.9325e-05 eta: 0:31:17 time: 0.3565 data_time: 0.0019 memory: 4670 grad_norm: 1462.8966 loss: 368.3244 loss_cls: 110.5376 loss_bbox: 120.2999 loss_dfl: 137.4868 2024/03/27 19:34:16 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:34:16 - mmengine - INFO - Saving checkpoint at 75 epochs 2024/03/27 19:34:25 - mmengine - INFO - Epoch(val) [75][ 50/625] eta: 0:00:24 time: 0.0425 data_time: 0.0009 memory: 4830 2024/03/27 19:34:27 - mmengine - INFO - Epoch(val) [75][100/625] eta: 0:00:22 time: 0.0424 data_time: 0.0004 memory: 838 2024/03/27 19:34:29 - mmengine - INFO - Epoch(val) [75][150/625] eta: 0:00:20 time: 0.0429 data_time: 0.0004 memory: 838 2024/03/27 19:34:31 - mmengine - INFO - Epoch(val) [75][200/625] eta: 0:00:18 time: 0.0431 data_time: 0.0004 memory: 838 2024/03/27 19:34:33 - mmengine - INFO - Epoch(val) [75][250/625] eta: 0:00:16 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 19:34:35 - mmengine - INFO - Epoch(val) [75][300/625] eta: 0:00:13 time: 0.0418 data_time: 0.0003 memory: 838 2024/03/27 19:34:38 - mmengine - INFO - Epoch(val) [75][350/625] eta: 0:00:11 time: 0.0428 data_time: 0.0004 memory: 838 2024/03/27 19:34:40 - mmengine - INFO - Epoch(val) [75][400/625] eta: 0:00:09 time: 0.0427 data_time: 0.0004 memory: 838 2024/03/27 19:34:42 - mmengine - INFO - Epoch(val) [75][450/625] eta: 0:00:07 time: 0.0435 data_time: 0.0004 memory: 838 2024/03/27 19:34:44 - mmengine - INFO - Epoch(val) [75][500/625] eta: 0:00:05 time: 0.0402 data_time: 0.0004 memory: 838 2024/03/27 19:34:46 - mmengine - INFO - Epoch(val) [75][550/625] eta: 0:00:03 time: 0.0355 data_time: 0.0003 memory: 838 2024/03/27 19:34:47 - mmengine - INFO - Epoch(val) [75][600/625] eta: 0:00:01 time: 0.0346 data_time: 0.0003 memory: 838 2024/03/27 19:35:00 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:36:14 - mmengine - INFO - bbox_mAP_copypaste: 0.460 0.623 0.502 0.269 0.508 0.620 2024/03/27 19:36:15 - mmengine - INFO - Epoch(val) [75][625/625] coco/bbox_mAP: 0.4600 coco/bbox_mAP_50: 0.6230 coco/bbox_mAP_75: 0.5020 coco/bbox_mAP_s: 0.2690 coco/bbox_mAP_m: 0.5080 coco/bbox_mAP_l: 0.6200 data_time: 0.0003 time: 0.0337 2024/03/27 19:36:34 - mmengine - INFO - Epoch(train) [76][ 50/925] lr: 1.6850e-05 eta: 0:30:46 time: 0.3767 data_time: 0.0410 memory: 4710 grad_norm: 1360.4833 loss: 360.8807 loss_cls: 109.3440 loss_bbox: 114.9950 loss_dfl: 136.5417 2024/03/27 19:36:52 - mmengine - INFO - Epoch(train) [76][100/925] lr: 1.6850e-05 eta: 0:30:26 time: 0.3637 data_time: 0.0019 memory: 4776 grad_norm: 1341.9149 loss: 366.1379 loss_cls: 113.3026 loss_bbox: 117.3114 loss_dfl: 135.5239 2024/03/27 19:37:11 - mmengine - INFO - Epoch(train) [76][150/925] lr: 1.6850e-05 eta: 0:30:06 time: 0.3769 data_time: 0.0019 memory: 4683 grad_norm: 1460.2782 loss: 362.7988 loss_cls: 111.1530 loss_bbox: 116.3515 loss_dfl: 135.2943 2024/03/27 19:37:28 - mmengine - INFO - Epoch(train) [76][200/925] lr: 1.6850e-05 eta: 0:29:45 time: 0.3432 data_time: 0.0020 memory: 4830 grad_norm: inf loss: 366.4531 loss_cls: 111.2367 loss_bbox: 119.6057 loss_dfl: 135.6107 2024/03/27 19:37:45 - mmengine - INFO - Epoch(train) [76][250/925] lr: 1.6850e-05 eta: 0:29:25 time: 0.3360 data_time: 0.0019 memory: 4683 grad_norm: 1399.4464 loss: 367.8230 loss_cls: 113.1075 loss_bbox: 119.0073 loss_dfl: 135.7082 2024/03/27 19:38:03 - mmengine - INFO - Epoch(train) [76][300/925] lr: 1.6850e-05 eta: 0:29:05 time: 0.3664 data_time: 0.0020 memory: 4710 grad_norm: 1372.0234 loss: 365.0326 loss_cls: 111.7207 loss_bbox: 117.4867 loss_dfl: 135.8251 2024/03/27 19:38:21 - mmengine - INFO - Epoch(train) [76][350/925] lr: 1.6850e-05 eta: 0:28:44 time: 0.3606 data_time: 0.0020 memory: 4856 grad_norm: 1487.5837 loss: 362.4434 loss_cls: 110.9311 loss_bbox: 115.7800 loss_dfl: 135.7323 2024/03/27 19:38:39 - mmengine - INFO - Epoch(train) [76][400/925] lr: 1.6850e-05 eta: 0:28:24 time: 0.3497 data_time: 0.0019 memory: 4710 grad_norm: 1313.5961 loss: 361.9162 loss_cls: 111.2912 loss_bbox: 114.5502 loss_dfl: 136.0748 2024/03/27 19:38:58 - mmengine - INFO - Epoch(train) [76][450/925] lr: 1.6850e-05 eta: 0:28:04 time: 0.3810 data_time: 0.0020 memory: 4576 grad_norm: 1468.2441 loss: 361.3581 loss_cls: 108.6807 loss_bbox: 116.8016 loss_dfl: 135.8758 2024/03/27 19:39:16 - mmengine - INFO - Epoch(train) [76][500/925] lr: 1.6850e-05 eta: 0:27:43 time: 0.3697 data_time: 0.0020 memory: 5043 grad_norm: 1472.2663 loss: 359.9073 loss_cls: 110.0502 loss_bbox: 115.1507 loss_dfl: 134.7064 2024/03/27 19:39:35 - mmengine - INFO - Epoch(train) [76][550/925] lr: 1.6850e-05 eta: 0:27:23 time: 0.3660 data_time: 0.0020 memory: 4656 grad_norm: 1463.6667 loss: 364.4221 loss_cls: 110.2646 loss_bbox: 118.5664 loss_dfl: 135.5911 2024/03/27 19:39:53 - mmengine - INFO - Epoch(train) [76][600/925] lr: 1.6850e-05 eta: 0:27:03 time: 0.3710 data_time: 0.0020 memory: 4843 grad_norm: 1429.9744 loss: 367.7810 loss_cls: 111.6300 loss_bbox: 120.0842 loss_dfl: 136.0669 2024/03/27 19:40:03 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:40:12 - mmengine - INFO - Epoch(train) [76][650/925] lr: 1.6850e-05 eta: 0:26:43 time: 0.3746 data_time: 0.0020 memory: 4976 grad_norm: 1421.6309 loss: 364.4347 loss_cls: 110.0340 loss_bbox: 119.5315 loss_dfl: 134.8692 2024/03/27 19:40:30 - mmengine - INFO - Epoch(train) [76][700/925] lr: 1.6850e-05 eta: 0:26:22 time: 0.3659 data_time: 0.0021 memory: 4696 grad_norm: 1336.4969 loss: 365.0355 loss_cls: 110.2649 loss_bbox: 119.6681 loss_dfl: 135.1026 2024/03/27 19:40:49 - mmengine - INFO - Epoch(train) [76][750/925] lr: 1.6850e-05 eta: 0:26:02 time: 0.3783 data_time: 0.0020 memory: 4643 grad_norm: 1443.4067 loss: 353.9183 loss_cls: 106.1833 loss_bbox: 113.7054 loss_dfl: 134.0297 2024/03/27 19:41:08 - mmengine - INFO - Epoch(train) [76][800/925] lr: 1.6850e-05 eta: 0:25:42 time: 0.3700 data_time: 0.0021 memory: 4976 grad_norm: 1370.2890 loss: 369.0205 loss_cls: 112.1061 loss_bbox: 120.8067 loss_dfl: 136.1078 2024/03/27 19:41:26 - mmengine - INFO - Epoch(train) [76][850/925] lr: 1.6850e-05 eta: 0:25:22 time: 0.3727 data_time: 0.0021 memory: 4696 grad_norm: inf loss: 366.3135 loss_cls: 111.5955 loss_bbox: 117.9075 loss_dfl: 136.8106 2024/03/27 19:41:45 - mmengine - INFO - Epoch(train) [76][900/925] lr: 1.6850e-05 eta: 0:25:01 time: 0.3635 data_time: 0.0020 memory: 4670 grad_norm: 1411.5103 loss: 361.2893 loss_cls: 110.3817 loss_bbox: 115.6863 loss_dfl: 135.2214 2024/03/27 19:41:54 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:41:56 - mmengine - INFO - Epoch(val) [76][ 50/625] eta: 0:00:25 time: 0.0441 data_time: 0.0009 memory: 4616 2024/03/27 19:41:58 - mmengine - INFO - Epoch(val) [76][100/625] eta: 0:00:23 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 19:42:01 - mmengine - INFO - Epoch(val) [76][150/625] eta: 0:00:21 time: 0.0466 data_time: 0.0004 memory: 838 2024/03/27 19:42:03 - mmengine - INFO - Epoch(val) [76][200/625] eta: 0:00:19 time: 0.0451 data_time: 0.0004 memory: 838 2024/03/27 19:42:05 - mmengine - INFO - Epoch(val) [76][250/625] eta: 0:00:16 time: 0.0451 data_time: 0.0004 memory: 838 2024/03/27 19:42:08 - mmengine - INFO - Epoch(val) [76][300/625] eta: 0:00:14 time: 0.0449 data_time: 0.0004 memory: 838 2024/03/27 19:42:10 - mmengine - INFO - Epoch(val) [76][350/625] eta: 0:00:12 time: 0.0446 data_time: 0.0004 memory: 838 2024/03/27 19:42:12 - mmengine - INFO - Epoch(val) [76][400/625] eta: 0:00:10 time: 0.0440 data_time: 0.0004 memory: 838 2024/03/27 19:42:14 - mmengine - INFO - Epoch(val) [76][450/625] eta: 0:00:07 time: 0.0465 data_time: 0.0004 memory: 838 2024/03/27 19:42:17 - mmengine - INFO - Epoch(val) [76][500/625] eta: 0:00:05 time: 0.0436 data_time: 0.0004 memory: 838 2024/03/27 19:42:19 - mmengine - INFO - Epoch(val) [76][550/625] eta: 0:00:03 time: 0.0452 data_time: 0.0004 memory: 838 2024/03/27 19:42:21 - mmengine - INFO - Epoch(val) [76][600/625] eta: 0:00:01 time: 0.0438 data_time: 0.0004 memory: 838 2024/03/27 19:42:35 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:43:50 - mmengine - INFO - bbox_mAP_copypaste: 0.460 0.624 0.503 0.269 0.508 0.620 2024/03/27 19:43:51 - mmengine - INFO - Epoch(val) [76][625/625] coco/bbox_mAP: 0.4600 coco/bbox_mAP_50: 0.6240 coco/bbox_mAP_75: 0.5030 coco/bbox_mAP_s: 0.2690 coco/bbox_mAP_m: 0.5080 coco/bbox_mAP_l: 0.6200 data_time: 0.0004 time: 0.0443 2024/03/27 19:44:13 - mmengine - INFO - Epoch(train) [77][ 50/925] lr: 1.4375e-05 eta: 0:24:31 time: 0.4240 data_time: 0.0367 memory: 4763 grad_norm: 1438.8038 loss: 365.0984 loss_cls: 110.8084 loss_bbox: 117.4357 loss_dfl: 136.8543 2024/03/27 19:44:31 - mmengine - INFO - Epoch(train) [77][100/925] lr: 1.4375e-05 eta: 0:24:11 time: 0.3679 data_time: 0.0021 memory: 4710 grad_norm: 1380.0590 loss: 355.8709 loss_cls: 105.5069 loss_bbox: 114.4691 loss_dfl: 135.8949 2024/03/27 19:44:49 - mmengine - INFO - Epoch(train) [77][150/925] lr: 1.4375e-05 eta: 0:23:51 time: 0.3621 data_time: 0.0022 memory: 4803 grad_norm: 1367.4253 loss: 354.0525 loss_cls: 105.4249 loss_bbox: 114.3693 loss_dfl: 134.2584 2024/03/27 19:45:08 - mmengine - INFO - Epoch(train) [77][200/925] lr: 1.4375e-05 eta: 0:23:30 time: 0.3804 data_time: 0.0021 memory: 5110 grad_norm: 1502.0504 loss: 359.8616 loss_cls: 107.0957 loss_bbox: 117.2218 loss_dfl: 135.5441 2024/03/27 19:45:27 - mmengine - INFO - Epoch(train) [77][250/925] lr: 1.4375e-05 eta: 0:23:10 time: 0.3757 data_time: 0.0021 memory: 4736 grad_norm: 1381.2299 loss: 361.1194 loss_cls: 108.5940 loss_bbox: 116.2167 loss_dfl: 136.3087 2024/03/27 19:45:46 - mmengine - INFO - Epoch(train) [77][300/925] lr: 1.4375e-05 eta: 0:22:50 time: 0.3700 data_time: 0.0021 memory: 4696 grad_norm: 1340.8077 loss: 360.7121 loss_cls: 108.8035 loss_bbox: 116.0901 loss_dfl: 135.8185 2024/03/27 19:46:04 - mmengine - INFO - Epoch(train) [77][350/925] lr: 1.4375e-05 eta: 0:22:30 time: 0.3751 data_time: 0.0021 memory: 4776 grad_norm: 1392.5170 loss: 363.3890 loss_cls: 110.1626 loss_bbox: 117.2720 loss_dfl: 135.9544 2024/03/27 19:46:23 - mmengine - INFO - Epoch(train) [77][400/925] lr: 1.4375e-05 eta: 0:22:10 time: 0.3810 data_time: 0.0021 memory: 4776 grad_norm: 1272.5921 loss: 364.5022 loss_cls: 110.2036 loss_bbox: 118.5659 loss_dfl: 135.7327 2024/03/27 19:46:41 - mmengine - INFO - Epoch(train) [77][450/925] lr: 1.4375e-05 eta: 0:21:49 time: 0.3580 data_time: 0.0022 memory: 4696 grad_norm: 1459.3167 loss: 359.3101 loss_cls: 108.7463 loss_bbox: 114.8739 loss_dfl: 135.6899 2024/03/27 19:47:00 - mmengine - INFO - Epoch(train) [77][500/925] lr: 1.4375e-05 eta: 0:21:29 time: 0.3761 data_time: 0.0022 memory: 4830 grad_norm: 1308.3449 loss: 368.7995 loss_cls: 112.3581 loss_bbox: 119.6890 loss_dfl: 136.7525 2024/03/27 19:47:19 - mmengine - INFO - Epoch(train) [77][550/925] lr: 1.4375e-05 eta: 0:21:09 time: 0.3720 data_time: 0.0022 memory: 4843 grad_norm: 1309.6654 loss: 363.7662 loss_cls: 110.3642 loss_bbox: 117.6606 loss_dfl: 135.7414 2024/03/27 19:47:37 - mmengine - INFO - Epoch(train) [77][600/925] lr: 1.4375e-05 eta: 0:20:49 time: 0.3721 data_time: 0.0021 memory: 4536 grad_norm: 1340.0025 loss: 360.0400 loss_cls: 109.7303 loss_bbox: 116.0002 loss_dfl: 134.3094 2024/03/27 19:47:56 - mmengine - INFO - Epoch(train) [77][650/925] lr: 1.4375e-05 eta: 0:20:28 time: 0.3621 data_time: 0.0022 memory: 4736 grad_norm: 1329.8352 loss: 355.7764 loss_cls: 105.3416 loss_bbox: 115.8266 loss_dfl: 134.6081 2024/03/27 19:48:14 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:48:14 - mmengine - INFO - Epoch(train) [77][700/925] lr: 1.4375e-05 eta: 0:20:08 time: 0.3708 data_time: 0.0022 memory: 4736 grad_norm: 1393.8561 loss: 363.3153 loss_cls: 110.8244 loss_bbox: 117.6836 loss_dfl: 134.8073 2024/03/27 19:48:33 - mmengine - INFO - Epoch(train) [77][750/925] lr: 1.4375e-05 eta: 0:19:48 time: 0.3747 data_time: 0.0021 memory: 4670 grad_norm: 1382.9136 loss: 359.5411 loss_cls: 108.9589 loss_bbox: 116.3980 loss_dfl: 134.1842 2024/03/27 19:48:51 - mmengine - INFO - Epoch(train) [77][800/925] lr: 1.4375e-05 eta: 0:19:28 time: 0.3618 data_time: 0.0023 memory: 4976 grad_norm: 1445.7447 loss: 360.6750 loss_cls: 108.8915 loss_bbox: 117.8147 loss_dfl: 133.9688 2024/03/27 19:49:10 - mmengine - INFO - Epoch(train) [77][850/925] lr: 1.4375e-05 eta: 0:19:08 time: 0.3683 data_time: 0.0022 memory: 4816 grad_norm: 1362.1781 loss: 363.1719 loss_cls: 109.7933 loss_bbox: 117.5579 loss_dfl: 135.8207 2024/03/27 19:49:28 - mmengine - INFO - Epoch(train) [77][900/925] lr: 1.4375e-05 eta: 0:18:47 time: 0.3692 data_time: 0.0021 memory: 4696 grad_norm: 1280.0209 loss: 362.6761 loss_cls: 107.9563 loss_bbox: 119.0237 loss_dfl: 135.6961 2024/03/27 19:49:37 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:49:39 - mmengine - INFO - Epoch(val) [77][ 50/625] eta: 0:00:27 time: 0.0474 data_time: 0.0009 memory: 4576 2024/03/27 19:49:42 - mmengine - INFO - Epoch(val) [77][100/625] eta: 0:00:24 time: 0.0451 data_time: 0.0004 memory: 838 2024/03/27 19:49:44 - mmengine - INFO - Epoch(val) [77][150/625] eta: 0:00:22 time: 0.0465 data_time: 0.0004 memory: 838 2024/03/27 19:49:46 - mmengine - INFO - Epoch(val) [77][200/625] eta: 0:00:19 time: 0.0462 data_time: 0.0004 memory: 838 2024/03/27 19:49:49 - mmengine - INFO - Epoch(val) [77][250/625] eta: 0:00:17 time: 0.0462 data_time: 0.0004 memory: 838 2024/03/27 19:49:51 - mmengine - INFO - Epoch(val) [77][300/625] eta: 0:00:15 time: 0.0459 data_time: 0.0004 memory: 838 2024/03/27 19:49:53 - mmengine - INFO - Epoch(val) [77][350/625] eta: 0:00:12 time: 0.0469 data_time: 0.0004 memory: 838 2024/03/27 19:49:56 - mmengine - INFO - Epoch(val) [77][400/625] eta: 0:00:10 time: 0.0461 data_time: 0.0004 memory: 838 2024/03/27 19:49:58 - mmengine - INFO - Epoch(val) [77][450/625] eta: 0:00:08 time: 0.0460 data_time: 0.0004 memory: 838 2024/03/27 19:50:00 - mmengine - INFO - Epoch(val) [77][500/625] eta: 0:00:05 time: 0.0467 data_time: 0.0004 memory: 838 2024/03/27 19:50:03 - mmengine - INFO - Epoch(val) [77][550/625] eta: 0:00:03 time: 0.0461 data_time: 0.0004 memory: 838 2024/03/27 19:50:05 - mmengine - INFO - Epoch(val) [77][600/625] eta: 0:00:01 time: 0.0456 data_time: 0.0004 memory: 838 2024/03/27 19:50:19 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:51:46 - mmengine - INFO - bbox_mAP_copypaste: 0.461 0.624 0.502 0.271 0.508 0.621 2024/03/27 19:51:48 - mmengine - INFO - Epoch(val) [77][625/625] coco/bbox_mAP: 0.4610 coco/bbox_mAP_50: 0.6240 coco/bbox_mAP_75: 0.5020 coco/bbox_mAP_s: 0.2710 coco/bbox_mAP_m: 0.5080 coco/bbox_mAP_l: 0.6210 data_time: 0.0004 time: 0.0440 2024/03/27 19:52:07 - mmengine - INFO - Epoch(train) [78][ 50/925] lr: 1.1900e-05 eta: 0:18:17 time: 0.3919 data_time: 0.0478 memory: 4790 grad_norm: 1326.3913 loss: 364.8983 loss_cls: 108.6581 loss_bbox: 120.4704 loss_dfl: 135.7699 2024/03/27 19:52:25 - mmengine - INFO - Epoch(train) [78][100/925] lr: 1.1900e-05 eta: 0:17:57 time: 0.3586 data_time: 0.0021 memory: 4616 grad_norm: 1291.8711 loss: 364.8245 loss_cls: 111.9156 loss_bbox: 117.2983 loss_dfl: 135.6106 2024/03/27 19:52:43 - mmengine - INFO - Epoch(train) [78][150/925] lr: 1.1900e-05 eta: 0:17:37 time: 0.3593 data_time: 0.0021 memory: 5016 grad_norm: 1282.4301 loss: 359.4913 loss_cls: 107.8153 loss_bbox: 116.8382 loss_dfl: 134.8379 2024/03/27 19:53:01 - mmengine - INFO - Epoch(train) [78][200/925] lr: 1.1900e-05 eta: 0:17:16 time: 0.3513 data_time: 0.0021 memory: 4710 grad_norm: 1311.2698 loss: 362.6333 loss_cls: 110.5384 loss_bbox: 117.5053 loss_dfl: 134.5897 2024/03/27 19:53:19 - mmengine - INFO - Epoch(train) [78][250/925] lr: 1.1900e-05 eta: 0:16:56 time: 0.3661 data_time: 0.0021 memory: 4763 grad_norm: 1395.1315 loss: 363.8322 loss_cls: 110.9208 loss_bbox: 117.9904 loss_dfl: 134.9211 2024/03/27 19:53:39 - mmengine - INFO - Epoch(train) [78][300/925] lr: 1.1900e-05 eta: 0:16:36 time: 0.3854 data_time: 0.0021 memory: 4723 grad_norm: 1310.2317 loss: 355.1486 loss_cls: 107.7437 loss_bbox: 114.5936 loss_dfl: 132.8113 2024/03/27 19:53:57 - mmengine - INFO - Epoch(train) [78][350/925] lr: 1.1900e-05 eta: 0:16:16 time: 0.3756 data_time: 0.0021 memory: 4643 grad_norm: 1343.9501 loss: 351.6859 loss_cls: 104.9340 loss_bbox: 113.5331 loss_dfl: 133.2187 2024/03/27 19:54:16 - mmengine - INFO - Epoch(train) [78][400/925] lr: 1.1900e-05 eta: 0:15:56 time: 0.3717 data_time: 0.0021 memory: 4656 grad_norm: 1338.8112 loss: 353.9859 loss_cls: 106.6896 loss_bbox: 113.0475 loss_dfl: 134.2487 2024/03/27 19:54:35 - mmengine - INFO - Epoch(train) [78][450/925] lr: 1.1900e-05 eta: 0:15:35 time: 0.3799 data_time: 0.0021 memory: 4656 grad_norm: 1382.7533 loss: 360.5887 loss_cls: 107.6277 loss_bbox: 117.9568 loss_dfl: 135.0042 2024/03/27 19:54:54 - mmengine - INFO - Epoch(train) [78][500/925] lr: 1.1900e-05 eta: 0:15:15 time: 0.3816 data_time: 0.0021 memory: 4603 grad_norm: 1253.3670 loss: 362.7686 loss_cls: 111.2387 loss_bbox: 117.3164 loss_dfl: 134.2135 2024/03/27 19:55:13 - mmengine - INFO - Epoch(train) [78][550/925] lr: 1.1900e-05 eta: 0:14:55 time: 0.3685 data_time: 0.0020 memory: 4656 grad_norm: 1495.5097 loss: 354.7435 loss_cls: 106.9643 loss_bbox: 112.9624 loss_dfl: 134.8168 2024/03/27 19:55:31 - mmengine - INFO - Epoch(train) [78][600/925] lr: 1.1900e-05 eta: 0:14:35 time: 0.3746 data_time: 0.0021 memory: 4723 grad_norm: 1439.6009 loss: 362.4047 loss_cls: 111.7268 loss_bbox: 115.6472 loss_dfl: 135.0307 2024/03/27 19:55:50 - mmengine - INFO - Epoch(train) [78][650/925] lr: 1.1900e-05 eta: 0:14:15 time: 0.3696 data_time: 0.0020 memory: 4750 grad_norm: 1423.1635 loss: 357.4595 loss_cls: 108.3014 loss_bbox: 114.4434 loss_dfl: 134.7147 2024/03/27 19:56:09 - mmengine - INFO - Epoch(train) [78][700/925] lr: 1.1900e-05 eta: 0:13:55 time: 0.3735 data_time: 0.0020 memory: 4790 grad_norm: 1328.6849 loss: 361.5626 loss_cls: 110.1609 loss_bbox: 116.7341 loss_dfl: 134.6676 2024/03/27 19:56:27 - mmengine - INFO - Epoch(train) [78][750/925] lr: 1.1900e-05 eta: 0:13:34 time: 0.3689 data_time: 0.0021 memory: 4776 grad_norm: 1316.9647 loss: 363.0529 loss_cls: 110.1246 loss_bbox: 117.1311 loss_dfl: 135.7972 2024/03/27 19:56:36 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:56:45 - mmengine - INFO - Epoch(train) [78][800/925] lr: 1.1900e-05 eta: 0:13:14 time: 0.3535 data_time: 0.0021 memory: 4736 grad_norm: 1317.1975 loss: 351.1357 loss_cls: 104.3183 loss_bbox: 114.5028 loss_dfl: 132.3147 2024/03/27 19:57:03 - mmengine - INFO - Epoch(train) [78][850/925] lr: 1.1900e-05 eta: 0:12:54 time: 0.3658 data_time: 0.0021 memory: 4696 grad_norm: 1441.8400 loss: 361.4889 loss_cls: 109.8272 loss_bbox: 116.1548 loss_dfl: 135.5069 2024/03/27 19:57:22 - mmengine - INFO - Epoch(train) [78][900/925] lr: 1.1900e-05 eta: 0:12:34 time: 0.3729 data_time: 0.0021 memory: 4830 grad_norm: 1370.0262 loss: 366.8054 loss_cls: 110.8082 loss_bbox: 119.5313 loss_dfl: 136.4659 2024/03/27 19:57:31 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 19:57:33 - mmengine - INFO - Epoch(val) [78][ 50/625] eta: 0:00:26 time: 0.0466 data_time: 0.0009 memory: 4750 2024/03/27 19:57:36 - mmengine - INFO - Epoch(val) [78][100/625] eta: 0:00:24 time: 0.0452 data_time: 0.0004 memory: 838 2024/03/27 19:57:38 - mmengine - INFO - Epoch(val) [78][150/625] eta: 0:00:21 time: 0.0450 data_time: 0.0004 memory: 838 2024/03/27 19:57:40 - mmengine - INFO - Epoch(val) [78][200/625] eta: 0:00:19 time: 0.0465 data_time: 0.0004 memory: 838 2024/03/27 19:57:42 - mmengine - INFO - Epoch(val) [78][250/625] eta: 0:00:17 time: 0.0449 data_time: 0.0004 memory: 838 2024/03/27 19:57:45 - mmengine - INFO - Epoch(val) [78][300/625] eta: 0:00:14 time: 0.0439 data_time: 0.0004 memory: 838 2024/03/27 19:57:47 - mmengine - INFO - Epoch(val) [78][350/625] eta: 0:00:12 time: 0.0457 data_time: 0.0004 memory: 838 2024/03/27 19:57:49 - mmengine - INFO - Epoch(val) [78][400/625] eta: 0:00:10 time: 0.0451 data_time: 0.0004 memory: 838 2024/03/27 19:57:52 - mmengine - INFO - Epoch(val) [78][450/625] eta: 0:00:07 time: 0.0466 data_time: 0.0004 memory: 838 2024/03/27 19:57:54 - mmengine - INFO - Epoch(val) [78][500/625] eta: 0:00:05 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 19:57:56 - mmengine - INFO - Epoch(val) [78][550/625] eta: 0:00:03 time: 0.0452 data_time: 0.0004 memory: 838 2024/03/27 19:57:58 - mmengine - INFO - Epoch(val) [78][600/625] eta: 0:00:01 time: 0.0445 data_time: 0.0004 memory: 838 2024/03/27 19:58:13 - mmengine - INFO - Evaluating bbox... 2024/03/27 19:59:33 - mmengine - INFO - bbox_mAP_copypaste: 0.461 0.625 0.503 0.272 0.509 0.622 2024/03/27 19:59:34 - mmengine - INFO - Epoch(val) [78][625/625] coco/bbox_mAP: 0.4610 coco/bbox_mAP_50: 0.6250 coco/bbox_mAP_75: 0.5030 coco/bbox_mAP_s: 0.2720 coco/bbox_mAP_m: 0.5090 coco/bbox_mAP_l: 0.6220 data_time: 0.0004 time: 0.0442 2024/03/27 19:59:56 - mmengine - INFO - Epoch(train) [79][ 50/925] lr: 9.4250e-06 eta: 0:12:04 time: 0.4229 data_time: 0.0475 memory: 4736 grad_norm: 1269.5967 loss: 362.0110 loss_cls: 108.0764 loss_bbox: 118.7904 loss_dfl: 135.1442 2024/03/27 20:00:14 - mmengine - INFO - Epoch(train) [79][100/925] lr: 9.4250e-06 eta: 0:11:44 time: 0.3667 data_time: 0.0021 memory: 4683 grad_norm: 1259.9922 loss: 359.2317 loss_cls: 109.3643 loss_bbox: 115.9639 loss_dfl: 133.9034 2024/03/27 20:00:32 - mmengine - INFO - Epoch(train) [79][150/925] lr: 9.4250e-06 eta: 0:11:23 time: 0.3635 data_time: 0.0021 memory: 4763 grad_norm: 1391.3785 loss: 359.4587 loss_cls: 108.1072 loss_bbox: 115.5479 loss_dfl: 135.8036 2024/03/27 20:00:50 - mmengine - INFO - Epoch(train) [79][200/925] lr: 9.4250e-06 eta: 0:11:03 time: 0.3623 data_time: 0.0020 memory: 4736 grad_norm: 1320.7315 loss: 363.3483 loss_cls: 108.3380 loss_bbox: 118.2735 loss_dfl: 136.7367 2024/03/27 20:01:09 - mmengine - INFO - Epoch(train) [79][250/925] lr: 9.4250e-06 eta: 0:10:43 time: 0.3625 data_time: 0.0021 memory: 4656 grad_norm: 1375.4938 loss: 359.5661 loss_cls: 108.9668 loss_bbox: 116.4205 loss_dfl: 134.1788 2024/03/27 20:01:27 - mmengine - INFO - Epoch(train) [79][300/925] lr: 9.4250e-06 eta: 0:10:23 time: 0.3740 data_time: 0.0021 memory: 5110 grad_norm: 1323.6862 loss: 362.7502 loss_cls: 109.0940 loss_bbox: 117.5912 loss_dfl: 136.0649 2024/03/27 20:01:46 - mmengine - INFO - Epoch(train) [79][350/925] lr: 9.4250e-06 eta: 0:10:03 time: 0.3719 data_time: 0.0020 memory: 4843 grad_norm: 1332.5994 loss: 366.7867 loss_cls: 111.5073 loss_bbox: 118.3092 loss_dfl: 136.9702 2024/03/27 20:02:04 - mmengine - INFO - Epoch(train) [79][400/925] lr: 9.4250e-06 eta: 0:09:43 time: 0.3595 data_time: 0.0021 memory: 4763 grad_norm: 1361.1950 loss: 361.0508 loss_cls: 109.6538 loss_bbox: 116.7863 loss_dfl: 134.6107 2024/03/27 20:02:22 - mmengine - INFO - Epoch(train) [79][450/925] lr: 9.4250e-06 eta: 0:09:23 time: 0.3679 data_time: 0.0020 memory: 4590 grad_norm: 1367.3711 loss: 359.0280 loss_cls: 109.9079 loss_bbox: 115.4449 loss_dfl: 133.6751 2024/03/27 20:02:41 - mmengine - INFO - Epoch(train) [79][500/925] lr: 9.4250e-06 eta: 0:09:02 time: 0.3729 data_time: 0.0021 memory: 4843 grad_norm: 1360.7291 loss: 362.3610 loss_cls: 109.1330 loss_bbox: 119.0336 loss_dfl: 134.1944 2024/03/27 20:03:00 - mmengine - INFO - Epoch(train) [79][550/925] lr: 9.4250e-06 eta: 0:08:42 time: 0.3708 data_time: 0.0022 memory: 4670 grad_norm: 1314.9847 loss: 361.8761 loss_cls: 111.0488 loss_bbox: 116.2410 loss_dfl: 134.5863 2024/03/27 20:03:18 - mmengine - INFO - Epoch(train) [79][600/925] lr: 9.4250e-06 eta: 0:08:22 time: 0.3691 data_time: 0.0020 memory: 4683 grad_norm: 1319.0448 loss: 361.1725 loss_cls: 108.0495 loss_bbox: 118.1768 loss_dfl: 134.9462 2024/03/27 20:03:37 - mmengine - INFO - Epoch(train) [79][650/925] lr: 9.4250e-06 eta: 0:08:02 time: 0.3716 data_time: 0.0019 memory: 4643 grad_norm: 1269.9711 loss: 368.5156 loss_cls: 111.2284 loss_bbox: 120.9982 loss_dfl: 136.2890 2024/03/27 20:03:55 - mmengine - INFO - Epoch(train) [79][700/925] lr: 9.4250e-06 eta: 0:07:42 time: 0.3597 data_time: 0.0020 memory: 4643 grad_norm: 1442.4786 loss: 358.6856 loss_cls: 108.3534 loss_bbox: 114.9084 loss_dfl: 135.4239 2024/03/27 20:04:13 - mmengine - INFO - Epoch(train) [79][750/925] lr: 9.4250e-06 eta: 0:07:22 time: 0.3673 data_time: 0.0021 memory: 4763 grad_norm: 1294.7633 loss: 360.3077 loss_cls: 108.1338 loss_bbox: 117.3804 loss_dfl: 134.7935 2024/03/27 20:04:31 - mmengine - INFO - Epoch(train) [79][800/925] lr: 9.4250e-06 eta: 0:07:02 time: 0.3596 data_time: 0.0021 memory: 4790 grad_norm: 1369.7059 loss: 360.3647 loss_cls: 109.0976 loss_bbox: 116.8134 loss_dfl: 134.4537 2024/03/27 20:04:49 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 20:04:49 - mmengine - INFO - Epoch(train) [79][850/925] lr: 9.4250e-06 eta: 0:06:41 time: 0.3511 data_time: 0.0021 memory: 4723 grad_norm: 1318.7135 loss: 364.0622 loss_cls: 109.2320 loss_bbox: 118.8217 loss_dfl: 136.0086 2024/03/27 20:05:06 - mmengine - INFO - Epoch(train) [79][900/925] lr: 9.4250e-06 eta: 0:06:21 time: 0.3550 data_time: 0.0021 memory: 4843 grad_norm: 1318.5745 loss: 357.5499 loss_cls: 106.8755 loss_bbox: 116.2291 loss_dfl: 134.4453 2024/03/27 20:05:15 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 20:05:18 - mmengine - INFO - Epoch(val) [79][ 50/625] eta: 0:00:26 time: 0.0453 data_time: 0.0010 memory: 4830 2024/03/27 20:05:20 - mmengine - INFO - Epoch(val) [79][100/625] eta: 0:00:23 time: 0.0455 data_time: 0.0004 memory: 838 2024/03/27 20:05:22 - mmengine - INFO - Epoch(val) [79][150/625] eta: 0:00:21 time: 0.0449 data_time: 0.0004 memory: 838 2024/03/27 20:05:25 - mmengine - INFO - Epoch(val) [79][200/625] eta: 0:00:19 time: 0.0461 data_time: 0.0004 memory: 838 2024/03/27 20:05:27 - mmengine - INFO - Epoch(val) [79][250/625] eta: 0:00:17 time: 0.0453 data_time: 0.0004 memory: 838 2024/03/27 20:05:29 - mmengine - INFO - Epoch(val) [79][300/625] eta: 0:00:14 time: 0.0453 data_time: 0.0004 memory: 838 2024/03/27 20:05:31 - mmengine - INFO - Epoch(val) [79][350/625] eta: 0:00:12 time: 0.0458 data_time: 0.0004 memory: 838 2024/03/27 20:05:34 - mmengine - INFO - Epoch(val) [79][400/625] eta: 0:00:10 time: 0.0448 data_time: 0.0004 memory: 838 2024/03/27 20:05:36 - mmengine - INFO - Epoch(val) [79][450/625] eta: 0:00:07 time: 0.0461 data_time: 0.0004 memory: 838 2024/03/27 20:05:38 - mmengine - INFO - Epoch(val) [79][500/625] eta: 0:00:05 time: 0.0446 data_time: 0.0004 memory: 838 2024/03/27 20:05:41 - mmengine - INFO - Epoch(val) [79][550/625] eta: 0:00:03 time: 0.0452 data_time: 0.0004 memory: 838 2024/03/27 20:05:43 - mmengine - INFO - Epoch(val) [79][600/625] eta: 0:00:01 time: 0.0454 data_time: 0.0004 memory: 838 2024/03/27 20:05:57 - mmengine - INFO - Evaluating bbox... 2024/03/27 20:07:15 - mmengine - INFO - bbox_mAP_copypaste: 0.461 0.625 0.503 0.273 0.508 0.622 2024/03/27 20:07:16 - mmengine - INFO - Epoch(val) [79][625/625] coco/bbox_mAP: 0.4610 coco/bbox_mAP_50: 0.6250 coco/bbox_mAP_75: 0.5030 coco/bbox_mAP_s: 0.2730 coco/bbox_mAP_m: 0.5080 coco/bbox_mAP_l: 0.6220 data_time: 0.0004 time: 0.0507 2024/03/27 20:07:37 - mmengine - INFO - Epoch(train) [80][ 50/925] lr: 6.9500e-06 eta: 0:05:51 time: 0.4179 data_time: 0.0401 memory: 4630 grad_norm: 1300.0439 loss: 358.5503 loss_cls: 107.4407 loss_bbox: 116.7749 loss_dfl: 134.3347 2024/03/27 20:07:55 - mmengine - INFO - Epoch(train) [80][100/925] lr: 6.9500e-06 eta: 0:05:31 time: 0.3646 data_time: 0.0021 memory: 4830 grad_norm: 1300.4694 loss: 357.5330 loss_cls: 106.9089 loss_bbox: 116.5775 loss_dfl: 134.0465 2024/03/27 20:08:13 - mmengine - INFO - Epoch(train) [80][150/925] lr: 6.9500e-06 eta: 0:05:11 time: 0.3576 data_time: 0.0021 memory: 4723 grad_norm: 1256.2368 loss: 361.7292 loss_cls: 111.0993 loss_bbox: 116.4970 loss_dfl: 134.1329 2024/03/27 20:08:33 - mmengine - INFO - Epoch(train) [80][200/925] lr: 6.9500e-06 eta: 0:04:51 time: 0.3938 data_time: 0.0021 memory: 4990 grad_norm: 1396.9369 loss: 357.8740 loss_cls: 107.6183 loss_bbox: 115.9832 loss_dfl: 134.2724 2024/03/27 20:08:52 - mmengine - INFO - Epoch(train) [80][250/925] lr: 6.9500e-06 eta: 0:04:31 time: 0.3787 data_time: 0.0021 memory: 5216 grad_norm: 1271.6387 loss: 358.7562 loss_cls: 106.8012 loss_bbox: 117.3675 loss_dfl: 134.5876 2024/03/27 20:09:10 - mmengine - INFO - Epoch(train) [80][300/925] lr: 6.9500e-06 eta: 0:04:11 time: 0.3750 data_time: 0.0021 memory: 4803 grad_norm: 1344.3156 loss: 350.3593 loss_cls: 104.0366 loss_bbox: 114.0766 loss_dfl: 132.2461 2024/03/27 20:09:28 - mmengine - INFO - Epoch(train) [80][350/925] lr: 6.9500e-06 eta: 0:03:51 time: 0.3586 data_time: 0.0021 memory: 4750 grad_norm: 1365.8112 loss: 358.7542 loss_cls: 106.6252 loss_bbox: 117.4414 loss_dfl: 134.6876 2024/03/27 20:09:47 - mmengine - INFO - Epoch(train) [80][400/925] lr: 6.9500e-06 eta: 0:03:30 time: 0.3783 data_time: 0.0022 memory: 4790 grad_norm: 1294.7221 loss: 364.3727 loss_cls: 110.3382 loss_bbox: 118.3519 loss_dfl: 135.6825 2024/03/27 20:10:06 - mmengine - INFO - Epoch(train) [80][450/925] lr: 6.9500e-06 eta: 0:03:10 time: 0.3705 data_time: 0.0021 memory: 4870 grad_norm: 1307.0051 loss: 361.9539 loss_cls: 108.8518 loss_bbox: 118.0871 loss_dfl: 135.0151 2024/03/27 20:10:24 - mmengine - INFO - Epoch(train) [80][500/925] lr: 6.9500e-06 eta: 0:02:50 time: 0.3632 data_time: 0.0021 memory: 4776 grad_norm: 1323.6889 loss: 353.5837 loss_cls: 105.6400 loss_bbox: 114.1610 loss_dfl: 133.7827 2024/03/27 20:10:42 - mmengine - INFO - Epoch(train) [80][550/925] lr: 6.9500e-06 eta: 0:02:30 time: 0.3647 data_time: 0.0021 memory: 4816 grad_norm: 1317.8646 loss: 360.0070 loss_cls: 108.9213 loss_bbox: 116.4855 loss_dfl: 134.6002 2024/03/27 20:11:01 - mmengine - INFO - Epoch(train) [80][600/925] lr: 6.9500e-06 eta: 0:02:10 time: 0.3724 data_time: 0.0021 memory: 4710 grad_norm: 1290.6686 loss: 353.6523 loss_cls: 104.4757 loss_bbox: 114.9020 loss_dfl: 134.2746 2024/03/27 20:11:19 - mmengine - INFO - Epoch(train) [80][650/925] lr: 6.9500e-06 eta: 0:01:50 time: 0.3647 data_time: 0.0021 memory: 4963 grad_norm: 1308.3733 loss: 358.2617 loss_cls: 107.2167 loss_bbox: 115.8959 loss_dfl: 135.1491 2024/03/27 20:11:37 - mmengine - INFO - Epoch(train) [80][700/925] lr: 6.9500e-06 eta: 0:01:30 time: 0.3649 data_time: 0.0023 memory: 4976 grad_norm: 1396.9795 loss: 358.0872 loss_cls: 106.2671 loss_bbox: 117.3602 loss_dfl: 134.4598 2024/03/27 20:11:56 - mmengine - INFO - Epoch(train) [80][750/925] lr: 6.9500e-06 eta: 0:01:10 time: 0.3663 data_time: 0.0021 memory: 4910 grad_norm: 1376.2448 loss: 355.2313 loss_cls: 105.2869 loss_bbox: 114.8589 loss_dfl: 135.0855 2024/03/27 20:12:14 - mmengine - INFO - Epoch(train) [80][800/925] lr: 6.9500e-06 eta: 0:00:50 time: 0.3674 data_time: 0.0021 memory: 4883 grad_norm: 1328.7873 loss: 365.4751 loss_cls: 110.0189 loss_bbox: 118.4718 loss_dfl: 136.9844 2024/03/27 20:12:33 - mmengine - INFO - Epoch(train) [80][850/925] lr: 6.9500e-06 eta: 0:00:30 time: 0.3824 data_time: 0.0022 memory: 4750 grad_norm: 1407.9402 loss: 357.6485 loss_cls: 108.1305 loss_bbox: 115.7247 loss_dfl: 133.7933 2024/03/27 20:12:51 - mmengine - INFO - Epoch(train) [80][900/925] lr: 6.9500e-06 eta: 0:00:10 time: 0.3517 data_time: 0.0022 memory: 4790 grad_norm: 1365.2024 loss: 359.4837 loss_cls: 106.7698 loss_bbox: 117.1466 loss_dfl: 135.5673 2024/03/27 20:13:00 - mmengine - INFO - Exp name: yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_adddecay_coco_20240327_110411 2024/03/27 20:13:00 - mmengine - INFO - Saving checkpoint at 80 epochs 2024/03/27 20:13:09 - mmengine - INFO - Epoch(val) [80][ 50/625] eta: 0:00:26 time: 0.0462 data_time: 0.0011 memory: 4496 2024/03/27 20:13:11 - mmengine - INFO - Epoch(val) [80][100/625] eta: 0:00:24 time: 0.0459 data_time: 0.0004 memory: 838 2024/03/27 20:13:14 - mmengine - INFO - Epoch(val) [80][150/625] eta: 0:00:21 time: 0.0465 data_time: 0.0004 memory: 838 2024/03/27 20:13:16 - mmengine - INFO - Epoch(val) [80][200/625] eta: 0:00:19 time: 0.0472 data_time: 0.0004 memory: 838 2024/03/27 20:13:18 - mmengine - INFO - Epoch(val) [80][250/625] eta: 0:00:17 time: 0.0459 data_time: 0.0004 memory: 838 2024/03/27 20:13:21 - mmengine - INFO - Epoch(val) [80][300/625] eta: 0:00:15 time: 0.0457 data_time: 0.0004 memory: 838 2024/03/27 20:13:23 - mmengine - INFO - Epoch(val) [80][350/625] eta: 0:00:12 time: 0.0451 data_time: 0.0004 memory: 838 2024/03/27 20:13:25 - mmengine - INFO - Epoch(val) [80][400/625] eta: 0:00:10 time: 0.0449 data_time: 0.0004 memory: 838 2024/03/27 20:13:28 - mmengine - INFO - Epoch(val) [80][450/625] eta: 0:00:08 time: 0.0460 data_time: 0.0004 memory: 838 2024/03/27 20:13:30 - mmengine - INFO - Epoch(val) [80][500/625] eta: 0:00:05 time: 0.0418 data_time: 0.0004 memory: 838 2024/03/27 20:13:32 - mmengine - INFO - Epoch(val) [80][550/625] eta: 0:00:03 time: 0.0373 data_time: 0.0004 memory: 838 2024/03/27 20:13:34 - mmengine - INFO - Epoch(val) [80][600/625] eta: 0:00:01 time: 0.0390 data_time: 0.0004 memory: 838 2024/03/27 20:13:49 - mmengine - INFO - Evaluating bbox... 2024/03/27 20:15:10 - mmengine - INFO - bbox_mAP_copypaste: 0.461 0.625 0.503 0.272 0.509 0.622 2024/03/27 20:15:11 - mmengine - INFO - Epoch(val) [80][625/625] coco/bbox_mAP: 0.4610 coco/bbox_mAP_50: 0.6250 coco/bbox_mAP_75: 0.5030 coco/bbox_mAP_s: 0.2720 coco/bbox_mAP_m: 0.5090 coco/bbox_mAP_l: 0.6220 data_time: 0.0004 time: 0.0382