diff --git "a/yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240119_121515.log" "b/yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240119_121515.log" new file mode 100644--- /dev/null +++ "b/yolo_world_v2_s_vlpan_bn_2e-4_80e_8gpus_mask-refine_finetune_coco_20240119_121515.log" @@ -0,0 +1,4425 @@ +2024/01/19 12:15:31 - 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: 810901691 + GPU 0,1,2,3,4,5,6,7: NVIDIA A10 + CUDA_HOME: /usr/local/cuda + NVCC: Cuda compilation tools, release 11.3, V11.3.109 + GCC: gcc (GCC) 7.3.1 20180303 (Red Hat 7.3.1-5) + PyTorch: 1.11.0+cu113 + PyTorch compiling details: PyTorch built with: + - GCC 7.3 + - C++ Version: 201402 + - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications + - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) + - OpenMP 201511 (a.k.a. OpenMP 4.5) + - LAPACK is enabled (usually provided by MKL) + - NNPACK is enabled + - CPU capability usage: AVX2 + - CUDA Runtime 11.3 + - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 + - CuDNN 8.2 + - Magma 2.5.2 + - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, + + TorchVision: 0.12.0+cu113 + OpenCV: 4.9.0 + MMEngine: 0.7.2 + +Runtime environment: + cudnn_benchmark: True + mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} + dist_cfg: {'backend': 'nccl'} + seed: None + Distributed launcher: pytorch + Distributed training: True + GPU number: 8 +------------------------------------------------------------ + +2024/01/19 12:15:33 - 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 = 'outputs/pretrain_yolow-v8_s_clipv2_frozen_te_noprompt_t2i_bn_2e-3adamw_scale_lr_wd_32xb16-100e_obj365v1_goldg_train_lviseval/epoch_100.pth' +resume = False +file_client_args = dict(backend='disk') +_file_client_args = dict(backend='disk') +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', file_client_args=dict(backend='disk')), + 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='YOLOWDetector', + 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='MMTransformer', + 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='HuggingCLIPLanguageBackboneV2', + model_name= + '/group/30042/adriancheng/pretrained_models/clip-vit-base-patch32-projection', + frozen_modules=['all'])), + neck=dict( + type='YOLOWv8PAFPN', + 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='SigmoidAttnCSPLayerWithTwoConv')), + bbox_head=dict( + type='YOLOWv8Head', + head_module=dict( + type='YOLOWv8HeadBNModule', + 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], + 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', file_client_args=dict(backend='disk')), + 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', file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', file_client_args=dict(backend='disk')), + 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/captions/coco_class_captions.json', + pipeline=[ + dict( + type='LoadImageFromFile', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', file_client_args=dict(backend='disk')), + 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='LoadTextFixed'), + 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/captions/coco_class_captions.json', + pipeline=[ + dict( + type='LoadImageFromFile', + file_client_args=dict(backend='disk')), + 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='LoadTextFixed'), + 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/captions/coco_class_captions.json', + pipeline=[ + dict( + type='LoadImageFromFile', + file_client_args=dict(backend='disk')), + 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='LoadTextFixed'), + dict( + type='mmdet.PackDetInputs', + meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', + 'scale_factor', 'pad_param', 'texts')) + ])) +param_scheduler = None +optim_wrapper = dict( + type='AmpOptimWrapper', + clip_grad=dict(max_norm=10.0), + optimizer=dict( + type='AdamW', lr=0.0002, weight_decay=0.05, batch_size_per_gpu=16), + constructor='YOLOWv5OptimizerConstructor', + paramwise_cfg=dict( + bias_decay_mult=0.0, + norm_decay_mult=0.0, + custom_keys=dict({ + 'backbone.text_model': dict(lr_mult=0.01), + 'logit_scale': dict(weight_decay=0.0) + })), + loss_scale='dynamic') +custom_hooks = [ + dict( + type='EMAHook', + ema_type='ExpMomentumEMA', + momentum=0.0001, + update_buffers=True, + strict_load=False, + priority=49), + dict( + type='mmdet.PipelineSwitchHook', + switch_epoch=70, + switch_pipeline=[ + dict( + type='LoadImageFromFile', + file_client_args=dict(backend='disk')), + 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=['projects.YoloW.yolow'], allow_failed_imports=False) +num_training_classes = 80 +text_channels = 512 +neck_embed_channels = [128, 256, 512] +neck_num_heads = [4, 8, 16] +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')) +] +mixup_prob = 0.15 +copypaste_prob = 0.3 +mosaic_affine_transform = [ + dict( + type='MultiModalMosaic', + img_scale=(640, 640), + pad_val=114.0, + pre_transform=[ + dict( + type='LoadImageFromFile', + file_client_args=dict(backend='disk')), + 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/captions/coco_class_captions.json', + pipeline=[ + dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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', + file_client_args=dict(backend='disk')), + 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/captions/coco_class_captions.json', + pipeline=[ + dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')), + 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='LoadTextFixed'), + 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/YoloW/yolov8/finetune_coco/yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune' + +2024/01/19 12:15:36 - mmengine - INFO - Using SyncBatchNorm() +2024/01/19 12:15:36 - 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 + -------------------- +2024/01/19 12:16:05 - mmengine - INFO - Scaled weight_decay to 0.1 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stem.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stem.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.main_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.main_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.final_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.final_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage1.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.main_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.main_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.final_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.final_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.1.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.1.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.1.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage2.1.blocks.1.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage3.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage3.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage3.1.main_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage3.1.main_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage3.1.final_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - 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paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- backbone.image_model.stage4.2.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.main_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.main_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.final_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.final_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.0.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - 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mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.guide_fc.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.top_down_layers.1.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.downsample_layers.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.downsample_layers.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.downsample_layers.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.downsample_layers.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.main_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.main_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.final_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.final_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.guide_fc.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.0.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.main_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.main_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.final_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.final_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv2.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.blocks.0.conv2.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.guide_fc.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.project_conv.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- neck.bottom_up_layers.1.attn_block.project_conv.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.0.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.1.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_preds.2.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.0.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.1.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.0.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.0.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.1.bn.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.1.bn.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.reg_preds.2.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.logit_scale:lr=0.0002 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.logit_scale:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.norm.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.0.norm.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.logit_scale:lr=0.0002 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.logit_scale:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.norm.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.1.norm.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.bias:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.logit_scale:lr=0.0002 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.logit_scale:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.norm.weight:weight_decay=0.0 +2024/01/19 12:16:05 - mmengine - INFO - paramwise_options -- bbox_head.head_module.cls_contrasts.2.norm.bias:weight_decay=0.0 +Name of parameter - Initialization information + +backbone.image_model.stem.conv.weight - torch.Size([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 YOLOWDetector + +backbone.image_model.stem.bn.bias - torch.Size([32]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage1.0.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage1.1.main_conv.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage1.1.final_conv.bn.bias - torch.Size([64]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage2.0.bn.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage2.1.main_conv.bn.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage2.1.final_conv.bn.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage3.0.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage3.1.main_conv.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage3.1.final_conv.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage4.0.bn.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage4.1.main_conv.bn.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage4.1.final_conv.bn.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage4.2.conv1.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +backbone.image_model.stage4.2.conv2.bn.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +backbone.text_model.model.text_projection.weight - torch.Size([512, 512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.0.main_conv.conv.weight - torch.Size([256, 768, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.top_down_layers.0.main_conv.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.0.main_conv.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.0.final_conv.conv.weight - torch.Size([256, 512, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.top_down_layers.0.final_conv.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.0.final_conv.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.0.blocks.0.conv1.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.0.blocks.0.conv2.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.0.attn_block.bias - torch.Size([4]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.0.attn_block.project_conv.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.1.main_conv.conv.weight - torch.Size([128, 384, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.top_down_layers.1.main_conv.bn.weight - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.1.main_conv.bn.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.1.final_conv.conv.weight - torch.Size([128, 256, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.top_down_layers.1.final_conv.bn.weight - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.1.final_conv.bn.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.top_down_layers.1.blocks.0.conv1.conv.weight - torch.Size([64, 64, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.1.blocks.0.conv2.conv.weight - torch.Size([64, 64, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.1.attn_block.bias - torch.Size([2]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +neck.top_down_layers.1.attn_block.project_conv.conv.weight - torch.Size([64, 64, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.downsample_layers.0.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.downsample_layers.0.bn.weight - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.downsample_layers.0.bn.bias - torch.Size([128]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.downsample_layers.1.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.downsample_layers.1.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.downsample_layers.1.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.0.main_conv.conv.weight - torch.Size([256, 384, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.bottom_up_layers.0.main_conv.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.0.main_conv.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.0.final_conv.conv.weight - torch.Size([256, 512, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.bottom_up_layers.0.final_conv.bn.weight - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.0.final_conv.bn.bias - torch.Size([256]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.0.blocks.0.conv1.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.0.blocks.0.conv2.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.0.attn_block.bias - torch.Size([4]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.0.attn_block.project_conv.conv.weight - torch.Size([128, 128, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.1.main_conv.conv.weight - torch.Size([512, 768, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.bottom_up_layers.1.main_conv.bn.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.1.main_conv.bn.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.1.final_conv.conv.weight - torch.Size([512, 1024, 1, 1]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +neck.bottom_up_layers.1.final_conv.bn.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.1.final_conv.bn.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +neck.bottom_up_layers.1.blocks.0.conv1.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.1.blocks.0.conv2.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.1.attn_block.bias - torch.Size([8]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +neck.bottom_up_layers.1.attn_block.project_conv.conv.weight - torch.Size([256, 256, 3, 3]): +Initialized by user-defined `init_weights` in YOLOWv8PAFPN + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +bbox_head.head_module.cls_preds.0.2.bias - torch.Size([512]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +bbox_head.head_module.cls_preds.1.2.bias - torch.Size([512]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +bbox_head.head_module.cls_preds.2.2.bias - torch.Size([512]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +bbox_head.head_module.reg_preds.0.2.bias - torch.Size([64]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +bbox_head.head_module.reg_preds.1.2.bias - torch.Size([64]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +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 YOLOWDetector + +bbox_head.head_module.reg_preds.2.2.bias - torch.Size([64]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +bbox_head.head_module.cls_contrasts.0.bias - torch.Size([]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +bbox_head.head_module.cls_contrasts.0.logit_scale - torch.Size([]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.0.norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.0.norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.1.bias - torch.Size([]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +bbox_head.head_module.cls_contrasts.1.logit_scale - torch.Size([]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.1.norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.1.norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.2.bias - torch.Size([]): +Initialized by user-defined `init_weights` in YOLOWv8HeadBNModule + +bbox_head.head_module.cls_contrasts.2.logit_scale - torch.Size([]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.2.norm.weight - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector + +bbox_head.head_module.cls_contrasts.2.norm.bias - torch.Size([512]): +The value is the same before and after calling `init_weights` of YOLOWDetector +2024/01/19 12:16:22 - mmengine - INFO - Load checkpoint from outputs/pretrain_yolow-v8_s_clipv2_frozen_te_noprompt_t2i_bn_2e-3adamw_scale_lr_wd_32xb16-100e_obj365v1_goldg_train_lviseval/epoch_100.pth +2024/01/19 12:16:22 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io +2024/01/19 12:16:22 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. +2024/01/19 12:16:22 - mmengine - INFO - Checkpoints will be saved to /group/30042/adriancheng/FastDet/work_dirs/YoloW/yolov8/finetune_coco/yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune. +2024/01/19 12:17:02 - mmengine - INFO - Epoch(train) [1][ 50/925] lr: 3.5315e-06 eta: 16:30:05 time: 0.8033 data_time: 0.1720 memory: 13013 grad_norm: nan loss: 551.5294 loss_cls: 232.2199 loss_bbox: 157.1025 loss_dfl: 162.2069 +2024/01/19 12:17:24 - mmengine - INFO - Epoch(train) [1][100/925] lr: 7.1351e-06 eta: 12:47:31 time: 0.4430 data_time: 0.0040 memory: 5428 grad_norm: 1006.9446 loss: 532.3068 loss_cls: 216.8366 loss_bbox: 153.8753 loss_dfl: 161.5948 +2024/01/19 12:17:43 - mmengine - INFO - Epoch(train) [1][150/925] lr: 1.0739e-05 eta: 11:07:59 time: 0.3818 data_time: 0.0099 memory: 5562 grad_norm: 978.3462 loss: 518.2290 loss_cls: 212.4990 loss_bbox: 148.4773 loss_dfl: 157.2527 +2024/01/19 12:18:01 - mmengine - INFO - Epoch(train) [1][200/925] lr: 1.4342e-05 eta: 10:13:01 time: 0.3654 data_time: 0.0038 memory: 5575 grad_norm: 981.8263 loss: 495.5764 loss_cls: 201.5748 loss_bbox: 140.8784 loss_dfl: 153.1232 +2024/01/19 12:18:19 - mmengine - INFO - Epoch(train) [1][250/925] lr: 1.7946e-05 eta: 9:35:55 time: 0.3492 data_time: 0.0042 memory: 5361 grad_norm: 968.2942 loss: 496.5459 loss_cls: 200.4840 loss_bbox: 142.6965 loss_dfl: 153.3653 +2024/01/19 12:18:35 - mmengine - INFO - Epoch(train) [1][300/925] lr: 2.1550e-05 eta: 9:05:08 time: 0.3201 data_time: 0.0094 memory: 5401 grad_norm: inf loss: 486.2083 loss_cls: 195.3627 loss_bbox: 139.4979 loss_dfl: 151.3477 +2024/01/19 12:18:52 - mmengine - INFO - Epoch(train) [1][350/925] lr: 2.5153e-05 eta: 8:46:58 time: 0.3424 data_time: 0.0051 memory: 5575 grad_norm: 931.6073 loss: 482.7512 loss_cls: 193.8847 loss_bbox: 138.3007 loss_dfl: 150.5657 +2024/01/19 12:19:09 - mmengine - INFO - Epoch(train) [1][400/925] lr: 2.8757e-05 eta: 8:32:14 time: 0.3355 data_time: 0.0050 memory: 5521 grad_norm: 969.9020 loss: 475.3782 loss_cls: 189.3341 loss_bbox: 136.8068 loss_dfl: 149.2373 +2024/01/19 12:19:26 - mmengine - INFO - Epoch(train) [1][450/925] lr: 3.2360e-05 eta: 8:20:43 time: 0.3355 data_time: 0.0046 memory: 5682 grad_norm: 940.1365 loss: 479.4567 loss_cls: 191.7792 loss_bbox: 137.3593 loss_dfl: 150.3182 +2024/01/19 12:19:42 - mmengine - INFO - Epoch(train) [1][500/925] lr: 3.5964e-05 eta: 8:10:33 time: 0.3284 data_time: 0.0051 memory: 5615 grad_norm: 970.0785 loss: 480.0754 loss_cls: 189.7730 loss_bbox: 140.2879 loss_dfl: 150.0145 +2024/01/19 12:19:59 - mmengine - INFO - Epoch(train) [1][550/925] lr: 3.9568e-05 eta: 8:03:46 time: 0.3425 data_time: 0.0038 memory: 5175 grad_norm: 941.2535 loss: 469.7868 loss_cls: 184.9797 loss_bbox: 135.3192 loss_dfl: 149.4878 +2024/01/19 12:20:16 - mmengine - INFO - Epoch(train) [1][600/925] lr: 4.3171e-05 eta: 7:57:19 time: 0.3351 data_time: 0.0038 memory: 5241 grad_norm: 1009.3103 loss: 474.8145 loss_cls: 188.7770 loss_bbox: 137.1310 loss_dfl: 148.9065 +2024/01/19 12:20:33 - mmengine - INFO - Epoch(train) [1][650/925] lr: 4.6775e-05 eta: 7:52:13 time: 0.3395 data_time: 0.0085 memory: 5388 grad_norm: 1109.7541 loss: 481.2868 loss_cls: 192.2037 loss_bbox: 138.9382 loss_dfl: 150.1449 +2024/01/19 12:20:51 - mmengine - INFO - Epoch(train) [1][700/925] lr: 5.0378e-05 eta: 7:49:05 time: 0.3540 data_time: 0.0060 memory: 5641 grad_norm: 1209.1306 loss: 472.9033 loss_cls: 185.6896 loss_bbox: 137.5195 loss_dfl: 149.6943 +2024/01/19 12:21:08 - mmengine - INFO - Epoch(train) [1][750/925] lr: 5.3982e-05 eta: 7:45:14 time: 0.3407 data_time: 0.0109 memory: 5401 grad_norm: 1039.3962 loss: 461.4081 loss_cls: 181.0757 loss_bbox: 133.2580 loss_dfl: 147.0744 +2024/01/19 12:21:24 - mmengine - INFO - Epoch(train) [1][800/925] lr: 5.7586e-05 eta: 7:40:58 time: 0.3292 data_time: 0.0045 memory: 5588 grad_norm: 1138.8609 loss: 472.3339 loss_cls: 186.2123 loss_bbox: 137.1721 loss_dfl: 148.9496 +2024/01/19 12:21:42 - mmengine - INFO - Epoch(train) [1][850/925] lr: 6.1189e-05 eta: 7:38:36 time: 0.3492 data_time: 0.0042 memory: 5348 grad_norm: 978.3394 loss: 469.4880 loss_cls: 187.0552 loss_bbox: 133.9148 loss_dfl: 148.5180 +2024/01/19 12:21:59 - mmengine - INFO - Epoch(train) [1][900/925] lr: 6.4793e-05 eta: 7:35:58 time: 0.3420 data_time: 0.0039 memory: 5268 grad_norm: 1177.5829 loss: 475.4735 loss_cls: 187.5580 loss_bbox: 138.2727 loss_dfl: 149.6428 +2024/01/19 12:22:14 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:22:36 - mmengine - INFO - Epoch(train) [2][ 50/925] lr: 6.9329e-05 eta: 7:46:06 time: 0.4238 data_time: 0.0806 memory: 9633 grad_norm: 1120.6996 loss: 463.7744 loss_cls: 181.5754 loss_bbox: 134.4396 loss_dfl: 147.7593 +2024/01/19 12:22:45 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:22:54 - mmengine - INFO - Epoch(train) [2][100/925] lr: 7.2889e-05 eta: 7:44:41 time: 0.3644 data_time: 0.0071 memory: 5721 grad_norm: 1105.6529 loss: 471.5134 loss_cls: 185.7569 loss_bbox: 137.3698 loss_dfl: 148.3867 +2024/01/19 12:23:11 - mmengine - INFO - Epoch(train) [2][150/925] lr: 7.6448e-05 eta: 7:42:39 time: 0.3519 data_time: 0.0038 memory: 5295 grad_norm: 1185.2317 loss: 467.3372 loss_cls: 182.6073 loss_bbox: 135.9462 loss_dfl: 148.7837 +2024/01/19 12:23:29 - mmengine - INFO - Epoch(train) [2][200/925] lr: 8.0007e-05 eta: 7:41:08 time: 0.3584 data_time: 0.0037 memory: 5295 grad_norm: 1062.0878 loss: 472.1402 loss_cls: 184.6125 loss_bbox: 137.6431 loss_dfl: 149.8846 +2024/01/19 12:23:46 - mmengine - INFO - Epoch(train) [2][250/925] lr: 8.3566e-05 eta: 7:38:28 time: 0.3341 data_time: 0.0038 memory: 5601 grad_norm: 1164.9268 loss: 464.4468 loss_cls: 181.7415 loss_bbox: 134.3819 loss_dfl: 148.3234 +2024/01/19 12:24:03 - mmengine - INFO - Epoch(train) [2][300/925] lr: 8.7125e-05 eta: 7:36:35 time: 0.3462 data_time: 0.0036 memory: 5361 grad_n`orm: 1059.9944 loss: 470.0947 loss_cls: 184.8468 loss_bbox: 136.5133 loss_dfl: 148.7346 +2024/01/19 12:24:21 - mmengine - INFO - Epoch(train) [2][350/925] lr: 9.0684e-05 eta: 7:35:13 time: 0.3541 data_time: 0.0040 memory: 5401 grad_norm: 1295.7270 loss: 464.6783 loss_cls: 183.1892 loss_bbox: 133.7755 loss_dfl: 147.7135 +2024/01/19 12:24:39 - mmengine - INFO - Epoch(train) [2][400/925] lr: 9.4243e-05 eta: 7:33:56 time: 0.3545 data_time: 0.0039 memory: 5415 grad_norm: 1154.3769 loss: 473.8617 loss_cls: 187.3619 loss_bbox: 137.1784 loss_dfl: 149.3213 +2024/01/19 12:24:56 - mmengine - INFO - Epoch(train) [2][450/925] lr: 9.7802e-05 eta: 7:32:27 time: 0.3483 data_time: 0.0132 memory: 5202 grad_norm: 1109.7088 loss: 476.1308 loss_cls: 187.2065 loss_bbox: 138.2659 loss_dfl: 150.6584 +2024/01/19 12:25:14 - mmengine - INFO - Epoch(train) [2][500/925] lr: 1.0136e-04 eta: 7:31:30 time: 0.3585 data_time: 0.0037 memory: 5575 grad_norm: 1241.1771 loss: 467.6846 loss_cls: 183.4575 loss_bbox: 135.9742 loss_dfl: 148.2529 +2024/01/19 12:25:33 - mmengine - INFO - Epoch(train) [2][550/925] lr: 1.0492e-04 eta: 7:31:05 time: 0.3708 data_time: 0.0091 memory: 5295 grad_norm: 1137.9459 loss: 467.4240 loss_cls: 183.5372 loss_bbox: 135.6163 loss_dfl: 148.2706 +2024/01/19 12:25:53 - mmengine - INFO - Epoch(train) [2][600/925] lr: 1.0848e-04 eta: 7:31:45 time: 0.3978 data_time: 0.0041 memory: 5175 grad_norm: 1214.6979 loss: 460.9718 loss_cls: 180.7936 loss_bbox: 132.4796 loss_dfl: 147.6986 +2024/01/19 12:26:10 - mmengine - INFO - Epoch(train) [2][650/925] lr: 1.1204e-04 eta: 7:30:26 time: 0.3478 data_time: 0.0056 memory: 5348 grad_norm: 1237.6657 loss: 466.2389 loss_cls: 183.3851 loss_bbox: 134.8236 loss_dfl: 148.0302 +2024/01/19 12:26:29 - mmengine - INFO - Epoch(train) [2][700/925] lr: 1.1560e-04 eta: 7:30:27 time: 0.3823 data_time: 0.0047 memory: 5295 grad_norm: 1156.2779 loss: 463.8797 loss_cls: 181.1684 loss_bbox: 134.6094 loss_dfl: 148.1019 +2024/01/19 12:26:48 - mmengine - INFO - Epoch(train) [2][750/925] lr: 1.1916e-04 eta: 7:30:20 time: 0.3789 data_time: 0.0047 memory: 5242 grad_norm: 1121.4172 loss: 462.5419 loss_cls: 183.3813 loss_bbox: 131.9862 loss_dfl: 147.1744 +2024/01/19 12:27:06 - mmengine - INFO - Epoch(train) [2][800/925] lr: 1.2271e-04 eta: 7:29:36 time: 0.3614 data_time: 0.0061 memory: 5588 grad_norm: 1331.0822 loss: 467.6398 loss_cls: 183.0879 loss_bbox: 135.8276 loss_dfl: 148.7244 +2024/01/19 12:27:24 - mmengine - INFO - Epoch(train) [2][850/925] lr: 1.2627e-04 eta: 7:28:37 time: 0.3534 data_time: 0.0047 memory: 5282 grad_norm: 1370.8657 loss: 460.4038 loss_cls: 179.8410 loss_bbox: 133.3521 loss_dfl: 147.2107 +2024/01/19 12:27:44 - mmengine - INFO - Epoch(train) [2][900/925] lr: 1.2983e-04 eta: 7:29:00 time: 0.3939 data_time: 0.0046 memory: 5295 grad_norm: 1149.5818 loss: 465.5310 loss_cls: 180.5937 loss_bbox: 136.5684 loss_dfl: 148.3689 +2024/01/19 12:27:52 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:28:15 - mmengine - INFO - Epoch(train) [3][ 50/925] lr: 1.3348e-04 eta: 7:30:36 time: 0.4475 data_time: 0.0810 memory: 5375 grad_norm: 1295.5716 loss: 465.5748 loss_cls: 183.7906 loss_bbox: 133.8535 loss_dfl: 147.9307 +2024/01/19 12:28:33 - mmengine - INFO - Epoch(train) [3][100/925] lr: 1.3699e-04 eta: 7:29:51 time: 0.3606 data_time: 0.0097 memory: 5761 grad_norm: 1278.4847 loss: 469.3255 loss_cls: 184.2356 loss_bbox: 136.4447 loss_dfl: 148.6452 +2024/01/19 12:28:52 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:28:52 - mmengine - INFO - Epoch(train) [3][150/925] lr: 1.4051e-04 eta: 7:29:40 time: 0.3792 data_time: 0.0063 memory: 5375 grad_norm: 1228.0405 loss: 469.1061 loss_cls: 184.7743 loss_bbox: 135.4250 loss_dfl: 148.9068 +2024/01/19 12:29:13 - mmengine - INFO - Epoch(train) [3][200/925] lr: 1.4402e-04 eta: 7:30:28 time: 0.4128 data_time: 0.0044 memory: 5335 grad_norm: 1174.4784 loss: 468.4755 loss_cls: 184.1163 loss_bbox: 135.7460 loss_dfl: 148.6132 +2024/01/19 12:29:31 - mmengine - INFO - Epoch(train) [3][250/925] lr: 1.4754e-04 eta: 7:29:54 time: 0.3663 data_time: 0.0038 memory: 5735 grad_norm: 1328.0609 loss: 470.3126 loss_cls: 184.0176 loss_bbox: 138.2631 loss_dfl: 148.0319 +2024/01/19 12:29:50 - mmengine - INFO - Epoch(train) [3][300/925] lr: 1.5105e-04 eta: 7:29:28 time: 0.3716 data_time: 0.0040 memory: 5468 grad_norm: 1154.0099 loss: 470.1488 loss_cls: 183.6823 loss_bbox: 136.9219 loss_dfl: 149.5445 +2024/01/19 12:30:09 - mmengine - INFO - Epoch(train) [3][350/925] lr: 1.5456e-04 eta: 7:29:22 time: 0.3829 data_time: 0.0039 memory: 5415 grad_norm: 1113.7338 loss: 474.5600 loss_cls: 186.7550 loss_bbox: 138.3160 loss_dfl: 149.4890 +2024/01/19 12:30:27 - mmengine - INFO - Epoch(train) [3][400/925] lr: 1.5808e-04 eta: 7:28:45 time: 0.3640 data_time: 0.0055 memory: 5348 grad_norm: 1510.4188 loss: 466.3711 loss_cls: 183.3128 loss_bbox: 135.2114 loss_dfl: 147.8469 +2024/01/19 12:30:44 - mmengine - INFO - Epoch(train) [3][450/925] lr: 1.6159e-04 eta: 7:27:39 time: 0.3451 data_time: 0.0037 memory: 5641 grad_norm: inf loss: 474.0759 loss_cls: 186.9408 loss_bbox: 138.1468 loss_dfl: 148.9882 +2024/01/19 12:31:04 - mmengine - INFO - Epoch(train) [3][500/925] lr: 1.6511e-04 eta: 7:27:41 time: 0.3879 data_time: 0.0069 memory: 5455 grad_norm: 1244.7105 loss: 463.4470 loss_cls: 180.9888 loss_bbox: 134.8660 loss_dfl: 147.5922 +2024/01/19 12:31:23 - mmengine - INFO - Epoch(train) [3][550/925] lr: 1.6862e-04 eta: 7:27:35 time: 0.3837 data_time: 0.0046 memory: 5415 grad_norm: 1284.2432 loss: 475.7543 loss_cls: 188.9074 loss_bbox: 137.6401 loss_dfl: 149.2068 +2024/01/19 12:31:41 - mmengine - INFO - Epoch(train) [3][600/925] lr: 1.7214e-04 eta: 7:26:42 time: 0.3516 data_time: 0.0079 memory: 5335 grad_norm: 1087.5097 loss: 472.5126 loss_cls: 184.5105 loss_bbox: 138.3630 loss_dfl: 149.6390 +2024/01/19 12:31:59 - mmengine - INFO - Epoch(train) [3][650/925] lr: 1.7565e-04 eta: 7:26:13 time: 0.3675 data_time: 0.0039 memory: 5348 grad_norm: 1262.7708 loss: 464.7313 loss_cls: 182.0593 loss_bbox: 135.7431 loss_dfl: 146.9288 +2024/01/19 12:32:19 - mmengine - INFO - Epoch(train) [3][700/925] lr: 1.7916e-04 eta: 7:26:18 time: 0.3912 data_time: 0.0040 memory: 5375 grad_norm: 1235.9309 loss: 467.5356 loss_cls: 182.8225 loss_bbox: 136.2597 loss_dfl: 148.4533 +2024/01/19 12:32:37 - mmengine - INFO - Epoch(train) [3][750/925] lr: 1.8268e-04 eta: 7:25:55 time: 0.3719 data_time: 0.0037 memory: 5295 grad_norm: 1370.9552 loss: 466.2090 loss_cls: 182.8015 loss_bbox: 135.2670 loss_dfl: 148.1406 +2024/01/19 12:32:57 - mmengine - INFO - Epoch(train) [3][800/925] lr: 1.8619e-04 eta: 7:25:58 time: 0.3909 data_time: 0.0146 memory: 5255 grad_norm: 1478.0210 loss: 468.3359 loss_cls: 182.3950 loss_bbox: 136.8799 loss_dfl: 149.0611 +2024/01/19 12:33:16 - mmengine - INFO - Epoch(train) [3][850/925] lr: 1.8971e-04 eta: 7:25:43 time: 0.3774 data_time: 0.0038 memory: 5615 grad_norm: 1249.4402 loss: 471.7304 loss_cls: 185.2438 loss_bbox: 137.0389 loss_dfl: 149.4478 +2024/01/19 12:33:36 - mmengine - INFO - Epoch(train) [3][900/925] lr: 1.9322e-04 eta: 7:26:00 time: 0.4028 data_time: 0.0038 memory: 5495 grad_norm: 1103.6632 loss: 476.6750 loss_cls: 189.6004 loss_bbox: 137.8874 loss_dfl: 149.1872 +2024/01/19 12:33:44 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:34:07 - mmengine - INFO - Epoch(train) [4][ 50/925] lr: 1.9258e-04 eta: 7:26:52 time: 0.4651 data_time: 0.0669 memory: 5282 grad_norm: 1210.6346 loss: 472.5659 loss_cls: 186.8843 loss_bbox: 136.3841 loss_dfl: 149.2975 +2024/01/19 12:34:26 - mmengine - INFO - Epoch(train) [4][100/925] lr: 1.9258e-04 eta: 7:26:37 time: 0.3796 data_time: 0.0018 memory: 5655 grad_norm: 1269.2511 loss: 467.9329 loss_cls: 184.0132 loss_bbox: 136.5846 loss_dfl: 147.3351 +2024/01/19 12:34:46 - mmengine - INFO - Epoch(train) [4][150/925] lr: 1.9258e-04 eta: 7:26:39 time: 0.3939 data_time: 0.0033 memory: 5508 grad_norm: 1316.5952 loss: 472.2080 loss_cls: 186.0055 loss_bbox: 137.3390 loss_dfl: 148.8635 +2024/01/19 12:35:05 - mmengine - INFO - Epoch(train) [4][200/925] lr: 1.9258e-04 eta: 7:26:15 time: 0.3730 data_time: 0.0020 memory: 5388 grad_norm: 1096.6310 loss: 470.9013 loss_cls: 183.8204 loss_bbox: 137.3211 loss_dfl: 149.7598 +2024/01/19 12:35:15 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:35:25 - mmengine - INFO - Epoch(train) [4][250/925] lr: 1.9258e-04 eta: 7:26:21 time: 0.3981 data_time: 0.0031 memory: 5455 grad_norm: 1204.5153 loss: 471.2276 loss_cls: 185.8781 loss_bbox: 136.9522 loss_dfl: 148.3973 +2024/01/19 12:35:44 - mmengine - INFO - Epoch(train) [4][300/925] lr: 1.9258e-04 eta: 7:26:15 time: 0.3886 data_time: 0.0034 memory: 5668 grad_norm: 1127.0476 loss: 475.1022 loss_cls: 187.3887 loss_bbox: 137.6021 loss_dfl: 150.1114 +2024/01/19 12:36:04 - mmengine - INFO - Epoch(train) [4][350/925] lr: 1.9258e-04 eta: 7:26:16 time: 0.3952 data_time: 0.0022 memory: 5415 grad_norm: 1317.1939 loss: 475.8425 loss_cls: 186.8111 loss_bbox: 138.9885 loss_dfl: 150.0429 +2024/01/19 12:36:23 - mmengine - INFO - Epoch(train) [4][400/925] lr: 1.9258e-04 eta: 7:25:57 time: 0.3772 data_time: 0.0019 memory: 5375 grad_norm: 1107.3722 loss: 480.0559 loss_cls: 191.5497 loss_bbox: 138.1706 loss_dfl: 150.3357 +2024/01/19 12:36:43 - mmengine - INFO - Epoch(train) [4][450/925] lr: 1.9258e-04 eta: 7:25:56 time: 0.3947 data_time: 0.0033 memory: 5588 grad_norm: 1283.1440 loss: 469.0230 loss_cls: 182.8744 loss_bbox: 137.1714 loss_dfl: 148.9772 +2024/01/19 12:37:02 - mmengine - INFO - Epoch(train) [4][500/925] lr: 1.9258e-04 eta: 7:25:47 time: 0.3872 data_time: 0.0056 memory: 5428 grad_norm: 1204.6319 loss: 466.9900 loss_cls: 180.2221 loss_bbox: 137.5974 loss_dfl: 149.1705 +2024/01/19 12:37:22 - mmengine - INFO - Epoch(train) [4][550/925] lr: 1.9258e-04 eta: 7:25:45 time: 0.3936 data_time: 0.0026 memory: 5215 grad_norm: 1351.3754 loss: 473.9779 loss_cls: 187.2754 loss_bbox: 137.3442 loss_dfl: 149.3583 +2024/01/19 12:37:40 - mmengine - INFO - Epoch(train) [4][600/925] lr: 1.9258e-04 eta: 7:25:20 time: 0.3726 data_time: 0.0019 memory: 5441 grad_norm: 1126.2126 loss: 483.5458 loss_cls: 191.3158 loss_bbox: 140.6244 loss_dfl: 151.6056 +2024/01/19 12:38:00 - mmengine - INFO - Epoch(train) [4][650/925] lr: 1.9258e-04 eta: 7:25:15 time: 0.3922 data_time: 0.0073 memory: 5681 grad_norm: 1289.5326 loss: 476.6910 loss_cls: 185.1771 loss_bbox: 141.1993 loss_dfl: 150.3146 +2024/01/19 12:38:19 - mmengine - INFO - Epoch(train) [4][700/925] lr: 1.9258e-04 eta: 7:25:03 time: 0.3855 data_time: 0.0028 memory: 5375 grad_norm: 1106.5577 loss: 468.6838 loss_cls: 182.1921 loss_bbox: 136.7533 loss_dfl: 149.7384 +2024/01/19 12:38:39 - mmengine - INFO - Epoch(train) [4][750/925] lr: 1.9258e-04 eta: 7:24:55 time: 0.3897 data_time: 0.0020 memory: 5468 grad_norm: 1145.3579 loss: 471.1559 loss_cls: 184.0495 loss_bbox: 137.4164 loss_dfl: 149.6901 +2024/01/19 12:38:58 - mmengine - INFO - Epoch(train) [4][800/925] lr: 1.9258e-04 eta: 7:24:42 time: 0.3840 data_time: 0.0019 memory: 5561 grad_norm: 1300.6843 loss: 477.6908 loss_cls: 186.0841 loss_bbox: 140.7704 loss_dfl: 150.8363 +2024/01/19 12:39:17 - mmengine - INFO - Epoch(train) [4][850/925] lr: 1.9258e-04 eta: 7:24:16 time: 0.3724 data_time: 0.0021 memory: 5588 grad_norm: 1159.0895 loss: 465.2124 loss_cls: 180.7417 loss_bbox: 135.9159 loss_dfl: 148.5548 +2024/01/19 12:39:36 - mmengine - INFO - Epoch(train) [4][900/925] lr: 1.9258e-04 eta: 7:24:06 time: 0.3879 data_time: 0.0020 memory: 5588 grad_norm: 1144.1775 loss: 470.4735 loss_cls: 184.1989 loss_bbox: 137.9085 loss_dfl: 148.3661 +2024/01/19 12:39:46 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:40:09 - mmengine - INFO - Epoch(train) [5][ 50/925] lr: 1.9258e-04 eta: 7:25:00 time: 0.4630 data_time: 0.0734 memory: 5268 grad_norm: 1294.8055 loss: 467.5397 loss_cls: 180.7097 loss_bbox: 138.5081 loss_dfl: 148.3219 +2024/01/19 12:40:28 - mmengine - INFO - Epoch(train) [5][100/925] lr: 1.9258e-04 eta: 7:24:37 time: 0.3753 data_time: 0.0018 memory: 5215 grad_norm: 1213.4284 loss: 466.1221 loss_cls: 182.7254 loss_bbox: 135.1477 loss_dfl: 148.2490 +2024/01/19 12:40:47 - mmengine - INFO - Epoch(train) [5][150/925] lr: 1.9258e-04 eta: 7:24:17 time: 0.3790 data_time: 0.0059 memory: 5468 grad_norm: 1202.5343 loss: 467.8109 loss_cls: 182.6612 loss_bbox: 136.8248 loss_dfl: 148.3249 +2024/01/19 12:41:06 - mmengine - INFO - Epoch(train) [5][200/925] lr: 1.9258e-04 eta: 7:23:59 time: 0.3812 data_time: 0.0027 memory: 5148 grad_norm: 1104.3115 loss: 473.0142 loss_cls: 185.5255 loss_bbox: 137.8721 loss_dfl: 149.6166 +2024/01/19 12:41:26 - mmengine - INFO - Epoch(train) [5][250/925] lr: 1.9258e-04 eta: 7:23:53 time: 0.3949 data_time: 0.0024 memory: 5348 grad_norm: 1324.0905 loss: 476.0066 loss_cls: 187.7247 loss_bbox: 138.6067 loss_dfl: 149.6752 +2024/01/19 12:41:45 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:41:45 - mmengine - INFO - Epoch(train) [5][300/925] lr: 1.9258e-04 eta: 7:23:40 time: 0.3871 data_time: 0.0018 memory: 5361 grad_norm: 1207.1074 loss: 470.5717 loss_cls: 183.3172 loss_bbox: 137.8497 loss_dfl: 149.4049 +2024/01/19 12:42:04 - mmengine - INFO - Epoch(train) [5][350/925] lr: 1.9258e-04 eta: 7:23:15 time: 0.3737 data_time: 0.0027 memory: 5255 grad_norm: 1307.6471 loss: 467.5081 loss_cls: 181.7030 loss_bbox: 136.7900 loss_dfl: 149.0151 +2024/01/19 12:42:23 - mmengine - INFO - Epoch(train) [5][400/925] lr: 1.9258e-04 eta: 7:23:07 time: 0.3926 data_time: 0.0028 memory: 5242 grad_norm: 1188.8474 loss: 463.8783 loss_cls: 179.7361 loss_bbox: 135.6427 loss_dfl: 148.4996 +2024/01/19 12:42:43 - mmengine - INFO - Epoch(train) [5][450/925] lr: 1.9258e-04 eta: 7:23:00 time: 0.3952 data_time: 0.0023 memory: 5255 grad_norm: 1132.2786 loss: 465.3005 loss_cls: 180.2453 loss_bbox: 136.7923 loss_dfl: 148.2629 +2024/01/19 12:43:02 - mmengine - INFO - Epoch(train) [5][500/925] lr: 1.9258e-04 eta: 7:22:40 time: 0.3788 data_time: 0.0020 memory: 5162 grad_norm: 1207.7174 loss: 466.4505 loss_cls: 181.9781 loss_bbox: 136.3798 loss_dfl: 148.0926 +2024/01/19 12:43:21 - mmengine - INFO - Epoch(train) [5][550/925] lr: 1.9258e-04 eta: 7:22:14 time: 0.3718 data_time: 0.0036 memory: 5308 grad_norm: 1082.7607 loss: 467.0234 loss_cls: 181.6578 loss_bbox: 136.4995 loss_dfl: 148.8661 +2024/01/19 12:43:41 - mmengine - INFO - Epoch(train) [5][600/925] lr: 1.9258e-04 eta: 7:22:08 time: 0.3965 data_time: 0.0029 memory: 5668 grad_norm: 1262.8531 loss: 474.3868 loss_cls: 186.4998 loss_bbox: 138.2757 loss_dfl: 149.6113 +2024/01/19 12:43:59 - mmengine - INFO - Epoch(train) [5][650/925] lr: 1.9258e-04 eta: 7:21:42 time: 0.3717 data_time: 0.0037 memory: 5548 grad_norm: 1031.0251 loss: 466.2839 loss_cls: 181.2615 loss_bbox: 136.7314 loss_dfl: 148.2910 +2024/01/19 12:44:19 - mmengine - INFO - Epoch(train) [5][700/925] lr: 1.9258e-04 eta: 7:21:29 time: 0.3884 data_time: 0.0075 memory: 5295 grad_norm: 1104.5429 loss: 462.3869 loss_cls: 179.3232 loss_bbox: 135.2678 loss_dfl: 147.7959 +2024/01/19 12:44:37 - mmengine - INFO - Epoch(train) [5][750/925] lr: 1.9258e-04 eta: 7:21:07 time: 0.3775 data_time: 0.0018 memory: 5361 grad_norm: 1051.5739 loss: 465.0464 loss_cls: 180.4066 loss_bbox: 136.1351 loss_dfl: 148.5047 +2024/01/19 12:44:57 - mmengine - INFO - Epoch(train) [5][800/925] lr: 1.9258e-04 eta: 7:20:55 time: 0.3892 data_time: 0.0031 memory: 5202 grad_norm: 1108.9487 loss: 470.3042 loss_cls: 181.3289 loss_bbox: 139.7770 loss_dfl: 149.1983 +2024/01/19 12:45:16 - mmengine - INFO - Epoch(train) [5][850/925] lr: 1.9258e-04 eta: 7:20:32 time: 0.3754 data_time: 0.0048 memory: 5641 grad_norm: 1437.2385 loss: 471.7357 loss_cls: 182.5670 loss_bbox: 139.9090 loss_dfl: 149.2597 +2024/01/19 12:45:35 - mmengine - INFO - Epoch(train) [5][900/925] lr: 1.9258e-04 eta: 7:20:16 time: 0.3848 data_time: 0.0022 memory: 5535 grad_norm: 1037.1537 loss: 468.2511 loss_cls: 181.3817 loss_bbox: 137.9454 loss_dfl: 148.9241 +2024/01/19 12:45:44 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:45:45 - mmengine - INFO - Saving checkpoint at 5 epochs +2024/01/19 12:45:48 - mmengine - WARNING - `save_param_scheduler` is True but `self.param_schedulers` is None, so skip saving parameter schedulers +2024/01/19 12:45:55 - mmengine - INFO - Epoch(val) [5][ 50/625] eta: 0:00:46 time: 0.0814 data_time: 0.0069 memory: 9151 +2024/01/19 12:45:57 - mmengine - INFO - Epoch(val) [5][100/625] eta: 0:00:30 time: 0.0350 data_time: 0.0003 memory: 843 +2024/01/19 12:45:58 - mmengine - INFO - Epoch(val) [5][150/625] eta: 0:00:24 time: 0.0360 data_time: 0.0003 memory: 843 +2024/01/19 12:46:00 - mmengine - INFO - Epoch(val) [5][200/625] eta: 0:00:20 time: 0.0369 data_time: 0.0003 memory: 843 +2024/01/19 12:46:02 - mmengine - INFO - Epoch(val) [5][250/625] eta: 0:00:16 time: 0.0353 data_time: 0.0003 memory: 843 +2024/01/19 12:46:04 - mmengine - INFO - Epoch(val) [5][300/625] eta: 0:00:14 time: 0.0341 data_time: 0.0003 memory: 843 +2024/01/19 12:46:05 - mmengine - INFO - Epoch(val) [5][350/625] eta: 0:00:11 time: 0.0337 data_time: 0.0003 memory: 843 +2024/01/19 12:46:07 - mmengine - INFO - Epoch(val) [5][400/625] eta: 0:00:09 time: 0.0340 data_time: 0.0003 memory: 843 +2024/01/19 12:46:09 - mmengine - INFO - Epoch(val) [5][450/625] eta: 0:00:07 time: 0.0339 data_time: 0.0004 memory: 843 +2024/01/19 12:46:10 - mmengine - INFO - Epoch(val) [5][500/625] eta: 0:00:04 time: 0.0265 data_time: 0.0002 memory: 843 +2024/01/19 12:46:11 - mmengine - INFO - Epoch(val) [5][550/625] eta: 0:00:02 time: 0.0261 data_time: 0.0002 memory: 843 +2024/01/19 12:46:13 - mmengine - INFO - Epoch(val) [5][600/625] eta: 0:00:00 time: 0.0257 data_time: 0.0002 memory: 843 +2024/01/19 12:46:28 - mmengine - INFO - Evaluating bbox... +2024/01/19 12:47:49 - mmengine - INFO - bbox_mAP_copypaste: 0.380 0.530 0.415 0.209 0.419 0.510 +2024/01/19 12:47:50 - mmengine - INFO - Epoch(val) [5][625/625] coco/bbox_mAP: 0.3800 coco/bbox_mAP_50: 0.5300 coco/bbox_mAP_75: 0.4150 coco/bbox_mAP_s: 0.2090 coco/bbox_mAP_m: 0.4190 coco/bbox_mAP_l: 0.5100 data_time: 0.0002 time: 0.0256 +2024/01/19 12:48:14 - mmengine - INFO - Epoch(train) [6][ 50/925] lr: 1.9010e-04 eta: 7:20:55 time: 0.4744 data_time: 0.0894 memory: 5586 grad_norm: 1219.7525 loss: 466.8537 loss_cls: 181.8336 loss_bbox: 136.3490 loss_dfl: 148.6710 +2024/01/19 12:48:33 - mmengine - INFO - Epoch(train) [6][100/925] lr: 1.9010e-04 eta: 7:20:35 time: 0.3807 data_time: 0.0020 memory: 5279 grad_norm: 1115.4411 loss: 467.4357 loss_cls: 182.7055 loss_bbox: 135.9890 loss_dfl: 148.7412 +2024/01/19 12:48:52 - mmengine - INFO - Epoch(train) [6][150/925] lr: 1.9010e-04 eta: 7:20:15 time: 0.3796 data_time: 0.0020 memory: 5426 grad_norm: 1159.6029 loss: 465.7641 loss_cls: 183.1958 loss_bbox: 134.4769 loss_dfl: 148.0915 +2024/01/19 12:49:11 - mmengine - INFO - Epoch(train) [6][200/925] lr: 1.9010e-04 eta: 7:19:55 time: 0.3815 data_time: 0.0027 memory: 5412 grad_norm: 1054.1246 loss: 465.8392 loss_cls: 179.8452 loss_bbox: 137.7363 loss_dfl: 148.2578 +2024/01/19 12:49:30 - mmengine - INFO - Epoch(train) [6][250/925] lr: 1.9010e-04 eta: 7:19:40 time: 0.3864 data_time: 0.0025 memory: 5359 grad_norm: 1250.8677 loss: 464.5447 loss_cls: 178.5974 loss_bbox: 137.5724 loss_dfl: 148.3748 +2024/01/19 12:49:49 - mmengine - INFO - Epoch(train) [6][300/925] lr: 1.9010e-04 eta: 7:19:21 time: 0.3821 data_time: 0.0020 memory: 5693 grad_norm: 1147.9950 loss: 465.3669 loss_cls: 179.8620 loss_bbox: 137.0486 loss_dfl: 148.4562 +2024/01/19 12:50:08 - mmengine - INFO - Epoch(train) [6][350/925] lr: 1.9010e-04 eta: 7:19:01 time: 0.3808 data_time: 0.0131 memory: 5319 grad_norm: 962.0220 loss: 464.4975 loss_cls: 180.6008 loss_bbox: 135.8429 loss_dfl: 148.0539 +2024/01/19 12:50:18 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:50:28 - mmengine - INFO - Epoch(train) [6][400/925] lr: 1.9010e-04 eta: 7:18:50 time: 0.3923 data_time: 0.0030 memory: 5279 grad_norm: 1127.5134 loss: 460.2277 loss_cls: 180.0987 loss_bbox: 132.4475 loss_dfl: 147.6815 +2024/01/19 12:50:46 - mmengine - INFO - Epoch(train) [6][450/925] lr: 1.9010e-04 eta: 7:18:14 time: 0.3578 data_time: 0.0022 memory: 5212 grad_norm: inf loss: 466.4622 loss_cls: 182.8903 loss_bbox: 135.0755 loss_dfl: 148.4965 +2024/01/19 12:51:05 - mmengine - INFO - Epoch(train) [6][500/925] lr: 1.9010e-04 eta: 7:17:50 time: 0.3736 data_time: 0.0022 memory: 5412 grad_norm: 1161.8999 loss: 466.3378 loss_cls: 180.3415 loss_bbox: 137.6664 loss_dfl: 148.3299 +2024/01/19 12:51:24 - mmengine - INFO - Epoch(train) [6][550/925] lr: 1.9010e-04 eta: 7:17:39 time: 0.3939 data_time: 0.0022 memory: 5412 grad_norm: 1298.3122 loss: 463.3662 loss_cls: 179.6435 loss_bbox: 135.8712 loss_dfl: 147.8514 +2024/01/19 12:51:44 - mmengine - INFO - Epoch(train) [6][600/925] lr: 1.9010e-04 eta: 7:17:30 time: 0.3963 data_time: 0.0028 memory: 5386 grad_norm: 1090.0276 loss: 471.7928 loss_cls: 183.3003 loss_bbox: 138.6364 loss_dfl: 149.8561 +2024/01/19 12:52:03 - mmengine - INFO - Epoch(train) [6][650/925] lr: 1.9010e-04 eta: 7:17:13 time: 0.3856 data_time: 0.0020 memory: 5492 grad_norm: 1145.7958 loss: 461.6550 loss_cls: 178.6130 loss_bbox: 135.3335 loss_dfl: 147.7086 +2024/01/19 12:52:23 - mmengine - INFO - Epoch(train) [6][700/925] lr: 1.9010e-04 eta: 7:16:57 time: 0.3863 data_time: 0.0021 memory: 5399 grad_norm: 1094.3400 loss: 472.1013 loss_cls: 182.0462 loss_bbox: 140.0478 loss_dfl: 150.0073 +2024/01/19 12:52:41 - mmengine - INFO - Epoch(train) [6][750/925] lr: 1.9010e-04 eta: 7:16:29 time: 0.3681 data_time: 0.0022 memory: 5412 grad_norm: 1229.7724 loss: 465.8121 loss_cls: 180.6491 loss_bbox: 136.0837 loss_dfl: 149.0793 +2024/01/19 12:53:01 - mmengine - INFO - Epoch(train) [6][800/925] lr: 1.9010e-04 eta: 7:16:22 time: 0.3996 data_time: 0.0025 memory: 5239 grad_norm: 1320.7646 loss: 467.7302 loss_cls: 182.8743 loss_bbox: 136.3679 loss_dfl: 148.4880 +2024/01/19 12:53:21 - mmengine - INFO - Epoch(train) [6][850/925] lr: 1.9010e-04 eta: 7:16:06 time: 0.3870 data_time: 0.0020 memory: 5612 grad_norm: 1104.2125 loss: 471.0762 loss_cls: 183.6842 loss_bbox: 137.8803 loss_dfl: 149.5118 +2024/01/19 12:53:40 - mmengine - INFO - Epoch(train) [6][900/925] lr: 1.9010e-04 eta: 7:15:47 time: 0.3827 data_time: 0.0037 memory: 5319 grad_norm: 1234.2124 loss: 458.3484 loss_cls: 176.8089 loss_bbox: 133.2311 loss_dfl: 148.3083 +2024/01/19 12:53:49 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:54:14 - mmengine - INFO - Epoch(train) [7][ 50/925] lr: 1.8762e-04 eta: 7:16:17 time: 0.4841 data_time: 0.0877 memory: 5239 grad_norm: 1294.2602 loss: 467.2840 loss_cls: 181.2360 loss_bbox: 136.1226 loss_dfl: 149.9254 +2024/01/19 12:54:33 - mmengine - INFO - Epoch(train) [7][100/925] lr: 1.8762e-04 eta: 7:15:59 time: 0.3848 data_time: 0.0029 memory: 5999 grad_norm: 1117.3863 loss: 460.9389 loss_cls: 177.4706 loss_bbox: 135.2759 loss_dfl: 148.1924 +2024/01/19 12:54:52 - mmengine - INFO - Epoch(train) [7][150/925] lr: 1.8762e-04 eta: 7:15:42 time: 0.3864 data_time: 0.0022 memory: 5212 grad_norm: 1109.1249 loss: 471.1690 loss_cls: 185.0559 loss_bbox: 136.3842 loss_dfl: 149.7290 +2024/01/19 12:55:11 - mmengine - INFO - Epoch(train) [7][200/925] lr: 1.8762e-04 eta: 7:15:15 time: 0.3693 data_time: 0.0020 memory: 5452 grad_norm: 1113.7213 loss: 473.9286 loss_cls: 184.6223 loss_bbox: 139.1739 loss_dfl: 150.1323 +2024/01/19 12:55:29 - mmengine - INFO - Epoch(train) [7][250/925] lr: 1.8762e-04 eta: 7:14:43 time: 0.3612 data_time: 0.0021 memory: 5586 grad_norm: 1102.1226 loss: 461.0956 loss_cls: 179.3462 loss_bbox: 134.1189 loss_dfl: 147.6305 +2024/01/19 12:55:47 - mmengine - INFO - Epoch(train) [7][300/925] lr: 1.8762e-04 eta: 7:14:19 time: 0.3733 data_time: 0.0022 memory: 5319 grad_norm: 1234.8507 loss: 457.2466 loss_cls: 176.9043 loss_bbox: 133.2231 loss_dfl: 147.1192 +2024/01/19 12:56:07 - mmengine - INFO - Epoch(train) [7][350/925] lr: 1.8762e-04 eta: 7:14:01 time: 0.3841 data_time: 0.0030 memory: 5332 grad_norm: 1146.8358 loss: 468.5880 loss_cls: 182.2168 loss_bbox: 137.0944 loss_dfl: 149.2769 +2024/01/19 12:56:25 - mmengine - INFO - Epoch(train) [7][400/925] lr: 1.8762e-04 eta: 7:13:37 time: 0.3752 data_time: 0.0030 memory: 5666 grad_norm: 1256.3823 loss: 465.2808 loss_cls: 181.5533 loss_bbox: 135.3321 loss_dfl: 148.3954 +2024/01/19 12:56:43 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 12:56:43 - mmengine - INFO - Epoch(train) [7][450/925] lr: 1.8762e-04 eta: 7:13:06 time: 0.3610 data_time: 0.0040 memory: 5239 grad_norm: 1172.2051 loss: 468.4968 loss_cls: 179.9512 loss_bbox: 138.3970 loss_dfl: 150.1486 +2024/01/19 12:57:02 - mmengine - INFO - Epoch(train) [7][500/925] lr: 1.8762e-04 eta: 7:12:37 time: 0.3651 data_time: 0.0024 memory: 5306 grad_norm: 1167.1802 loss: 460.6438 loss_cls: 178.5787 loss_bbox: 134.6034 loss_dfl: 147.4618 +2024/01/19 12:57:21 - mmengine - INFO - Epoch(train) [7][550/925] lr: 1.8762e-04 eta: 7:12:18 time: 0.3806 data_time: 0.0030 memory: 5439 grad_norm: 1151.9273 loss: 458.7199 loss_cls: 177.1162 loss_bbox: 134.0873 loss_dfl: 147.5163 +2024/01/19 12:57:39 - mmengine - INFO - Epoch(train) [7][600/925] lr: 1.8762e-04 eta: 7:11:45 time: 0.3576 data_time: 0.0028 memory: 5346 grad_norm: 1123.1224 loss: 468.0000 loss_cls: 182.0208 loss_bbox: 137.5736 loss_dfl: 148.4056 +2024/01/19 12:57:57 - mmengine - INFO - Epoch(train) [7][650/925] lr: 1.8762e-04 eta: 7:11:19 time: 0.3691 data_time: 0.0022 memory: 5679 grad_norm: 992.5367 loss: 473.8480 loss_cls: 184.4275 loss_bbox: 139.1675 loss_dfl: 150.2530 +2024/01/19 12:58:15 - mmengine - INFO - Epoch(train) [7][700/925] lr: 1.8762e-04 eta: 7:10:42 time: 0.3491 data_time: 0.0023 memory: 5639 grad_norm: 1127.4887 loss: 463.3138 loss_cls: 178.7195 loss_bbox: 136.1752 loss_dfl: 148.4191 +2024/01/19 12:58:33 - mmengine - INFO - Epoch(train) [7][750/925] lr: 1.8762e-04 eta: 7:10:15 time: 0.3670 data_time: 0.0028 memory: 5372 grad_norm: 1014.4891 loss: 464.6092 loss_cls: 180.3302 loss_bbox: 135.6922 loss_dfl: 148.5867 +2024/01/19 12:58:51 - mmengine - INFO - Epoch(train) [7][800/925] lr: 1.8762e-04 eta: 7:09:45 time: 0.3605 data_time: 0.0022 memory: 5359 grad_norm: 1001.6910 loss: 465.1980 loss_cls: 180.2267 loss_bbox: 135.5980 loss_dfl: 149.3733 +2024/01/19 12:59:09 - mmengine - INFO - Epoch(train) [7][850/925] lr: 1.8762e-04 eta: 7:09:16 time: 0.3617 data_time: 0.0023 memory: 5772 grad_norm: 1204.6821 loss: 468.4838 loss_cls: 183.6676 loss_bbox: 136.7260 loss_dfl: 148.0902 +2024/01/19 12:59:27 - mmengine - INFO - Epoch(train) [7][900/925] lr: 1.8762e-04 eta: 7:08:49 time: 0.3663 data_time: 0.0028 memory: 5599 grad_norm: 1115.2909 loss: 462.6397 loss_cls: 178.8861 loss_bbox: 135.0590 loss_dfl: 148.6946 +2024/01/19 12:59:36 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:00:00 - mmengine - INFO - Epoch(train) [8][ 50/925] lr: 1.8515e-04 eta: 7:08:57 time: 0.4586 data_time: 0.1026 memory: 5412 grad_norm: 1096.8573 loss: 459.0042 loss_cls: 176.1235 loss_bbox: 135.2720 loss_dfl: 147.6087 +2024/01/19 13:00:19 - mmengine - INFO - Epoch(train) [8][100/925] lr: 1.8515e-04 eta: 7:08:37 time: 0.3802 data_time: 0.0023 memory: 5372 grad_norm: 1132.1029 loss: 457.7244 loss_cls: 174.9690 loss_bbox: 134.6148 loss_dfl: 148.1405 +2024/01/19 13:00:38 - mmengine - INFO - Epoch(train) [8][150/925] lr: 1.8515e-04 eta: 7:08:20 time: 0.3846 data_time: 0.0021 memory: 5586 grad_norm: 1193.0983 loss: 466.1499 loss_cls: 180.3944 loss_bbox: 136.6420 loss_dfl: 149.1135 +2024/01/19 13:00:56 - mmengine - INFO - Epoch(train) [8][200/925] lr: 1.8515e-04 eta: 7:07:50 time: 0.3604 data_time: 0.0023 memory: 5466 grad_norm: 1185.7946 loss: 458.1426 loss_cls: 175.4598 loss_bbox: 134.9667 loss_dfl: 147.7160 +2024/01/19 13:01:16 - mmengine - INFO - Epoch(train) [8][250/925] lr: 1.8515e-04 eta: 7:07:34 time: 0.3879 data_time: 0.0023 memory: 5732 grad_norm: 1130.8667 loss: 466.4888 loss_cls: 180.2110 loss_bbox: 137.4077 loss_dfl: 148.8701 +2024/01/19 13:01:34 - mmengine - INFO - Epoch(train) [8][300/925] lr: 1.8515e-04 eta: 7:07:12 time: 0.3761 data_time: 0.0020 memory: 5292 grad_norm: 1086.9861 loss: 460.6438 loss_cls: 175.1858 loss_bbox: 136.9774 loss_dfl: 148.4807 +2024/01/19 13:01:52 - mmengine - INFO - Epoch(train) [8][350/925] lr: 1.8515e-04 eta: 7:06:44 time: 0.3617 data_time: 0.0029 memory: 5666 grad_norm: 1111.2755 loss: 463.7049 loss_cls: 179.7705 loss_bbox: 135.7920 loss_dfl: 148.1425 +2024/01/19 13:02:11 - mmengine - INFO - Epoch(train) [8][400/925] lr: 1.8515e-04 eta: 7:06:17 time: 0.3650 data_time: 0.0020 memory: 5132 grad_norm: 1052.9395 loss: 457.3222 loss_cls: 175.6106 loss_bbox: 134.6277 loss_dfl: 147.0839 +2024/01/19 13:02:30 - mmengine - INFO - Epoch(train) [8][450/925] lr: 1.8515e-04 eta: 7:05:57 time: 0.3789 data_time: 0.0022 memory: 5292 grad_norm: 1083.7347 loss: 461.7029 loss_cls: 177.5708 loss_bbox: 135.3726 loss_dfl: 148.7594 +2024/01/19 13:02:49 - mmengine - INFO - Epoch(train) [8][500/925] lr: 1.8515e-04 eta: 7:05:38 time: 0.3820 data_time: 0.0032 memory: 5346 grad_norm: 1139.1307 loss: 466.7215 loss_cls: 181.1768 loss_bbox: 137.0498 loss_dfl: 148.4949 +2024/01/19 13:02:58 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:03:07 - mmengine - INFO - Epoch(train) [8][550/925] lr: 1.8515e-04 eta: 7:05:15 time: 0.3734 data_time: 0.0043 memory: 5479 grad_norm: 1072.3118 loss: 457.8885 loss_cls: 175.4268 loss_bbox: 135.2503 loss_dfl: 147.2114 +2024/01/19 13:03:26 - mmengine - INFO - Epoch(train) [8][600/925] lr: 1.8515e-04 eta: 7:04:51 time: 0.3707 data_time: 0.0021 memory: 5266 grad_norm: 992.0785 loss: 463.0996 loss_cls: 178.4232 loss_bbox: 136.2875 loss_dfl: 148.3889 +2024/01/19 13:03:45 - mmengine - INFO - Epoch(train) [8][650/925] lr: 1.8515e-04 eta: 7:04:36 time: 0.3877 data_time: 0.0021 memory: 5199 grad_norm: 1144.6661 loss: 463.3185 loss_cls: 177.7731 loss_bbox: 136.4146 loss_dfl: 149.1308 +2024/01/19 13:04:03 - mmengine - INFO - Epoch(train) [8][700/925] lr: 1.8515e-04 eta: 7:04:04 time: 0.3547 data_time: 0.0020 memory: 5266 grad_norm: 1241.6421 loss: 461.6115 loss_cls: 175.7546 loss_bbox: 137.3556 loss_dfl: 148.5013 +2024/01/19 13:04:22 - mmengine - INFO - Epoch(train) [8][750/925] lr: 1.8515e-04 eta: 7:03:43 time: 0.3764 data_time: 0.0081 memory: 5652 grad_norm: 1279.5088 loss: 461.3950 loss_cls: 178.1981 loss_bbox: 135.3143 loss_dfl: 147.8826 +2024/01/19 13:04:40 - mmengine - INFO - Epoch(train) [8][800/925] lr: 1.8515e-04 eta: 7:03:17 time: 0.3646 data_time: 0.0022 memory: 5292 grad_norm: 1180.3534 loss: 452.6803 loss_cls: 172.6596 loss_bbox: 133.4703 loss_dfl: 146.5503 +2024/01/19 13:05:00 - mmengine - INFO - Epoch(train) [8][850/925] lr: 1.8515e-04 eta: 7:03:00 time: 0.3853 data_time: 0.0021 memory: 5319 grad_norm: 1074.5351 loss: 462.4809 loss_cls: 179.1749 loss_bbox: 135.5209 loss_dfl: 147.7851 +2024/01/19 13:05:19 - mmengine - INFO - Epoch(train) [8][900/925] lr: 1.8515e-04 eta: 7:02:41 time: 0.3809 data_time: 0.0021 memory: 5252 grad_norm: 1153.6149 loss: 449.2547 loss_cls: 171.9084 loss_bbox: 131.1010 loss_dfl: 146.2452 +2024/01/19 13:05:28 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:05:51 - mmengine - INFO - Epoch(train) [9][ 50/925] lr: 1.8268e-04 eta: 7:02:43 time: 0.4607 data_time: 0.0857 memory: 5359 grad_norm: 1133.8402 loss: 456.0967 loss_cls: 175.0064 loss_bbox: 133.6536 loss_dfl: 147.4367 +2024/01/19 13:06:10 - mmengine - INFO - Epoch(train) [9][100/925] lr: 1.8268e-04 eta: 7:02:27 time: 0.3869 data_time: 0.0023 memory: 5346 grad_norm: 1014.0537 loss: 458.7170 loss_cls: 176.2394 loss_bbox: 134.3824 loss_dfl: 148.0952 +2024/01/19 13:06:29 - mmengine - INFO - Epoch(train) [9][150/925] lr: 1.8268e-04 eta: 7:02:01 time: 0.3656 data_time: 0.0024 memory: 5332 grad_norm: 997.4607 loss: 464.0971 loss_cls: 178.6647 loss_bbox: 137.3713 loss_dfl: 148.0611 +2024/01/19 13:06:47 - mmengine - INFO - Epoch(train) [9][200/925] lr: 1.8268e-04 eta: 7:01:37 time: 0.3701 data_time: 0.0023 memory: 5466 grad_norm: 1117.1228 loss: 467.9694 loss_cls: 179.7901 loss_bbox: 139.2249 loss_dfl: 148.9544 +2024/01/19 13:07:06 - mmengine - INFO - Epoch(train) [9][250/925] lr: 1.8268e-04 eta: 7:01:12 time: 0.3680 data_time: 0.0021 memory: 5346 grad_norm: 1172.7441 loss: 474.2167 loss_cls: 184.3377 loss_bbox: 139.8041 loss_dfl: 150.0749 +2024/01/19 13:07:25 - mmengine - INFO - Epoch(train) [9][300/925] lr: 1.8268e-04 eta: 7:00:54 time: 0.3818 data_time: 0.0022 memory: 5679 grad_norm: 1080.6386 loss: 461.5360 loss_cls: 176.4372 loss_bbox: 136.8518 loss_dfl: 148.2470 +2024/01/19 13:07:43 - mmengine - INFO - Epoch(train) [9][350/925] lr: 1.8268e-04 eta: 7:00:25 time: 0.3585 data_time: 0.0021 memory: 5346 grad_norm: 1099.3014 loss: 463.9937 loss_cls: 179.9214 loss_bbox: 135.2480 loss_dfl: 148.8243 +2024/01/19 13:08:01 - mmengine - INFO - Epoch(train) [9][400/925] lr: 1.8268e-04 eta: 7:00:03 time: 0.3741 data_time: 0.0023 memory: 5239 grad_norm: 1159.1844 loss: 457.5574 loss_cls: 173.6522 loss_bbox: 135.3932 loss_dfl: 148.5120 +2024/01/19 13:08:20 - mmengine - INFO - Epoch(train) [9][450/925] lr: 1.8268e-04 eta: 6:59:42 time: 0.3752 data_time: 0.0032 memory: 5226 grad_norm: 1062.4937 loss: 460.8064 loss_cls: 176.8582 loss_bbox: 136.3004 loss_dfl: 147.6478 +2024/01/19 13:08:38 - mmengine - INFO - Epoch(train) [9][500/925] lr: 1.8268e-04 eta: 6:59:16 time: 0.3652 data_time: 0.0020 memory: 5172 grad_norm: 1035.9756 loss: 459.2492 loss_cls: 176.1947 loss_bbox: 135.4644 loss_dfl: 147.5902 +2024/01/19 13:08:56 - mmengine - INFO - Epoch(train) [9][550/925] lr: 1.8268e-04 eta: 6:58:48 time: 0.3585 data_time: 0.0023 memory: 5506 grad_norm: 1174.0319 loss: 461.6585 loss_cls: 179.0247 loss_bbox: 135.0363 loss_dfl: 147.5975 +2024/01/19 13:09:15 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:09:15 - mmengine - INFO - Epoch(train) [9][600/925] lr: 1.8268e-04 eta: 6:58:23 time: 0.3653 data_time: 0.0020 memory: 5892 grad_norm: 1007.8399 loss: 459.5368 loss_cls: 176.5741 loss_bbox: 134.9772 loss_dfl: 147.9855 +2024/01/19 13:09:33 - mmengine - INFO - Epoch(train) [9][650/925] lr: 1.8268e-04 eta: 6:58:00 time: 0.3696 data_time: 0.0023 memory: 5452 grad_norm: 1120.6854 loss: 457.8457 loss_cls: 173.5379 loss_bbox: 136.3432 loss_dfl: 147.9646 +2024/01/19 13:09:51 - mmengine - INFO - Epoch(train) [9][700/925] lr: 1.8268e-04 eta: 6:57:33 time: 0.3628 data_time: 0.0022 memory: 5479 grad_norm: 1016.0751 loss: 462.3273 loss_cls: 177.8622 loss_bbox: 135.5738 loss_dfl: 148.8912 +2024/01/19 13:10:10 - mmengine - INFO - Epoch(train) [9][750/925] lr: 1.8268e-04 eta: 6:57:11 time: 0.3713 data_time: 0.0023 memory: 5292 grad_norm: 1117.7000 loss: 461.8635 loss_cls: 177.5979 loss_bbox: 136.0836 loss_dfl: 148.1821 +2024/01/19 13:10:28 - mmengine - INFO - Epoch(train) [9][800/925] lr: 1.8268e-04 eta: 6:56:48 time: 0.3706 data_time: 0.0023 memory: 5212 grad_norm: 1153.6469 loss: 461.2947 loss_cls: 176.7402 loss_bbox: 136.2424 loss_dfl: 148.3121 +2024/01/19 13:10:47 - mmengine - INFO - Epoch(train) [9][850/925] lr: 1.8268e-04 eta: 6:56:24 time: 0.3669 data_time: 0.0023 memory: 5892 grad_norm: 1173.7605 loss: 465.0943 loss_cls: 179.3247 loss_bbox: 137.4217 loss_dfl: 148.3478 +2024/01/19 13:11:05 - mmengine - INFO - Epoch(train) [9][900/925] lr: 1.8268e-04 eta: 6:55:58 time: 0.3635 data_time: 0.0021 memory: 5346 grad_norm: 1193.9283 loss: 458.6957 loss_cls: 176.1954 loss_bbox: 134.7518 loss_dfl: 147.7485 +2024/01/19 13:11:14 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:11:38 - mmengine - INFO - Epoch(train) [10][ 50/925] lr: 1.8020e-04 eta: 6:56:05 time: 0.4793 data_time: 0.0878 memory: 5266 grad_norm: 1236.5943 loss: 450.3919 loss_cls: 171.7131 loss_bbox: 131.9829 loss_dfl: 146.6960 +2024/01/19 13:11:57 - mmengine - INFO - Epoch(train) [10][100/925] lr: 1.8020e-04 eta: 6:55:45 time: 0.3776 data_time: 0.0028 memory: 5652 grad_norm: 1033.3423 loss: 463.2267 loss_cls: 176.8185 loss_bbox: 138.2984 loss_dfl: 148.1098 +2024/01/19 13:12:16 - mmengine - INFO - Epoch(train) [10][150/925] lr: 1.8020e-04 eta: 6:55:27 time: 0.3839 data_time: 0.0068 memory: 5212 grad_norm: 1079.3650 loss: 453.9517 loss_cls: 173.8074 loss_bbox: 133.3227 loss_dfl: 146.8216 +2024/01/19 13:12:35 - mmengine - INFO - Epoch(train) [10][200/925] lr: 1.8020e-04 eta: 6:55:06 time: 0.3743 data_time: 0.0056 memory: 5239 grad_norm: 1043.1563 loss: 470.5663 loss_cls: 182.7765 loss_bbox: 137.2056 loss_dfl: 150.5841 +2024/01/19 13:12:54 - mmengine - INFO - Epoch(train) [10][250/925] lr: 1.8020e-04 eta: 6:54:44 time: 0.3727 data_time: 0.0026 memory: 5626 grad_norm: 1099.1828 loss: 462.5326 loss_cls: 177.1573 loss_bbox: 136.4256 loss_dfl: 148.9497 +2024/01/19 13:13:12 - mmengine - INFO - Epoch(train) [10][300/925] lr: 1.8020e-04 eta: 6:54:21 time: 0.3712 data_time: 0.0021 memory: 5426 grad_norm: 1074.9792 loss: 464.6066 loss_cls: 178.9259 loss_bbox: 136.9933 loss_dfl: 148.6874 +2024/01/19 13:13:32 - mmengine - INFO - Epoch(train) [10][350/925] lr: 1.8020e-04 eta: 6:54:03 time: 0.3828 data_time: 0.0062 memory: 5492 grad_norm: 1127.8822 loss: 450.6439 loss_cls: 171.8675 loss_bbox: 131.6115 loss_dfl: 147.1649 +2024/01/19 13:13:51 - mmengine - INFO - Epoch(train) [10][400/925] lr: 1.8020e-04 eta: 6:53:50 time: 0.3952 data_time: 0.0076 memory: 5346 grad_norm: 1152.5949 loss: 456.4563 loss_cls: 173.7515 loss_bbox: 135.3921 loss_dfl: 147.3127 +2024/01/19 13:14:10 - mmengine - INFO - Epoch(train) [10][450/925] lr: 1.8020e-04 eta: 6:53:30 time: 0.3799 data_time: 0.0027 memory: 5199 grad_norm: 1050.1656 loss: 456.9256 loss_cls: 173.5898 loss_bbox: 135.8948 loss_dfl: 147.4410 +2024/01/19 13:14:28 - mmengine - INFO - Epoch(train) [10][500/925] lr: 1.8020e-04 eta: 6:53:02 time: 0.3559 data_time: 0.0022 memory: 5252 grad_norm: 1129.9342 loss: 463.4587 loss_cls: 177.3685 loss_bbox: 136.6738 loss_dfl: 149.4164 +2024/01/19 13:14:47 - mmengine - INFO - Epoch(train) [10][550/925] lr: 1.8020e-04 eta: 6:52:39 time: 0.3679 data_time: 0.0125 memory: 5266 grad_norm: 1122.6943 loss: 454.1045 loss_cls: 174.5086 loss_bbox: 132.7067 loss_dfl: 146.8892 +2024/01/19 13:15:06 - mmengine - INFO - Epoch(train) [10][600/925] lr: 1.8020e-04 eta: 6:52:19 time: 0.3789 data_time: 0.0030 memory: 5666 grad_norm: 1110.2799 loss: 456.0333 loss_cls: 173.4128 loss_bbox: 134.2169 loss_dfl: 148.4036 +2024/01/19 13:15:23 - mmengine - INFO - Epoch(train) [10][650/925] lr: 1.8020e-04 eta: 6:51:47 time: 0.3436 data_time: 0.0029 memory: 5439 grad_norm: 1300.1012 loss: 454.1761 loss_cls: 173.6637 loss_bbox: 133.2681 loss_dfl: 147.2443 +2024/01/19 13:15:32 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:15:41 - mmengine - INFO - Epoch(train) [10][700/925] lr: 1.8020e-04 eta: 6:51:19 time: 0.3552 data_time: 0.0028 memory: 5466 grad_norm: 1053.9145 loss: 464.6478 loss_cls: 178.5937 loss_bbox: 137.0109 loss_dfl: 149.0432 +2024/01/19 13:15:59 - mmengine - INFO - Epoch(train) [10][750/925] lr: 1.8020e-04 eta: 6:50:59 time: 0.3768 data_time: 0.0143 memory: 5452 grad_norm: 1113.3036 loss: 455.3165 loss_cls: 174.5996 loss_bbox: 133.8332 loss_dfl: 146.8837 +2024/01/19 13:16:18 - mmengine - INFO - Epoch(train) [10][800/925] lr: 1.8020e-04 eta: 6:50:35 time: 0.3666 data_time: 0.0022 memory: 5306 grad_norm: 954.0130 loss: 463.8403 loss_cls: 177.2907 loss_bbox: 137.5940 loss_dfl: 148.9557 +2024/01/19 13:16:36 - mmengine - INFO - Epoch(train) [10][850/925] lr: 1.8020e-04 eta: 6:50:10 time: 0.3611 data_time: 0.0021 memory: 5266 grad_norm: 1013.1463 loss: 455.3477 loss_cls: 175.8826 loss_bbox: 132.5802 loss_dfl: 146.8849 +2024/01/19 13:16:55 - mmengine - INFO - Epoch(train) [10][900/925] lr: 1.8020e-04 eta: 6:49:50 time: 0.3757 data_time: 0.0022 memory: 5199 grad_norm: inf loss: 450.3310 loss_cls: 172.9598 loss_bbox: 130.6969 loss_dfl: 146.6743 +2024/01/19 13:17:04 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:17:04 - mmengine - INFO - Saving checkpoint at 10 epochs +2024/01/19 13:17:13 - mmengine - INFO - Epoch(val) [10][ 50/625] eta: 0:00:21 time: 0.0377 data_time: 0.0008 memory: 5212 +2024/01/19 13:17:14 - mmengine - INFO - Epoch(val) [10][100/625] eta: 0:00:19 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 13:17:16 - mmengine - INFO - Epoch(val) [10][150/625] eta: 0:00:17 time: 0.0364 data_time: 0.0004 memory: 843 +2024/01/19 13:17:18 - mmengine - INFO - Epoch(val) [10][200/625] eta: 0:00:15 time: 0.0352 data_time: 0.0003 memory: 843 +2024/01/19 13:17:20 - mmengine - INFO - Epoch(val) [10][250/625] eta: 0:00:13 time: 0.0361 data_time: 0.0003 memory: 843 +2024/01/19 13:17:22 - mmengine - INFO - Epoch(val) [10][300/625] eta: 0:00:11 time: 0.0363 data_time: 0.0003 memory: 843 +2024/01/19 13:17:23 - mmengine - INFO - Epoch(val) [10][350/625] eta: 0:00:09 time: 0.0358 data_time: 0.0003 memory: 843 +2024/01/19 13:17:25 - mmengine - INFO - Epoch(val) [10][400/625] eta: 0:00:08 time: 0.0365 data_time: 0.0003 memory: 843 +2024/01/19 13:17:27 - mmengine - INFO - Epoch(val) [10][450/625] eta: 0:00:06 time: 0.0287 data_time: 0.0002 memory: 843 +2024/01/19 13:17:28 - mmengine - INFO - Epoch(val) [10][500/625] eta: 0:00:04 time: 0.0263 data_time: 0.0002 memory: 843 +2024/01/19 13:17:29 - mmengine - INFO - Epoch(val) [10][550/625] eta: 0:00:02 time: 0.0266 data_time: 0.0002 memory: 843 +2024/01/19 13:17:31 - mmengine - INFO - Epoch(val) [10][600/625] eta: 0:00:00 time: 0.0263 data_time: 0.0002 memory: 843 +2024/01/19 13:17:47 - mmengine - INFO - Evaluating bbox... +2024/01/19 13:19:15 - mmengine - INFO - bbox_mAP_copypaste: 0.415 0.569 0.452 0.223 0.460 0.555 +2024/01/19 13:19:18 - mmengine - INFO - Epoch(val) [10][625/625] coco/bbox_mAP: 0.4150 coco/bbox_mAP_50: 0.5690 coco/bbox_mAP_75: 0.4520 coco/bbox_mAP_s: 0.2230 coco/bbox_mAP_m: 0.4600 coco/bbox_mAP_l: 0.5550 data_time: 0.0002 time: 0.0260 +2024/01/19 13:19:40 - mmengine - INFO - Epoch(train) [11][ 50/925] lr: 1.7772e-04 eta: 6:49:40 time: 0.4429 data_time: 0.1067 memory: 5626 grad_norm: 1040.6961 loss: 461.2597 loss_cls: 176.8970 loss_bbox: 135.5617 loss_dfl: 148.8010 +2024/01/19 13:19:58 - mmengine - INFO - Epoch(train) [11][100/925] lr: 1.7772e-04 eta: 6:49:14 time: 0.3609 data_time: 0.0032 memory: 5492 grad_norm: 1114.7792 loss: 450.6620 loss_cls: 172.1720 loss_bbox: 132.0286 loss_dfl: 146.4614 +2024/01/19 13:20:15 - mmengine - INFO - Epoch(train) [11][150/925] lr: 1.7772e-04 eta: 6:48:46 time: 0.3512 data_time: 0.0061 memory: 5279 grad_norm: 1135.8436 loss: 456.3530 loss_cls: 174.0845 loss_bbox: 134.5834 loss_dfl: 147.6851 +2024/01/19 13:20:34 - mmengine - INFO - Epoch(train) [11][200/925] lr: 1.7772e-04 eta: 6:48:22 time: 0.3655 data_time: 0.0054 memory: 5199 grad_norm: 1159.5989 loss: 460.0344 loss_cls: 176.9848 loss_bbox: 135.0285 loss_dfl: 148.0212 +2024/01/19 13:20:52 - mmengine - INFO - Epoch(train) [11][250/925] lr: 1.7772e-04 eta: 6:47:57 time: 0.3636 data_time: 0.0249 memory: 5346 grad_norm: 1127.3208 loss: 462.0608 loss_cls: 176.6786 loss_bbox: 136.8846 loss_dfl: 148.4977 +2024/01/19 13:21:10 - mmengine - INFO - Epoch(train) [11][300/925] lr: 1.7772e-04 eta: 6:47:33 time: 0.3643 data_time: 0.0033 memory: 5519 grad_norm: 969.4061 loss: 457.8222 loss_cls: 174.6384 loss_bbox: 135.7501 loss_dfl: 147.4338 +2024/01/19 13:21:28 - mmengine - INFO - Epoch(train) [11][350/925] lr: 1.7772e-04 eta: 6:47:10 time: 0.3665 data_time: 0.0024 memory: 5519 grad_norm: 970.6770 loss: 462.7141 loss_cls: 177.7621 loss_bbox: 136.1799 loss_dfl: 148.7720 +2024/01/19 13:21:48 - mmengine - INFO - Epoch(train) [11][400/925] lr: 1.7772e-04 eta: 6:46:54 time: 0.3891 data_time: 0.0031 memory: 5666 grad_norm: 1251.4856 loss: 458.4982 loss_cls: 173.8242 loss_bbox: 136.7000 loss_dfl: 147.9740 +2024/01/19 13:22:06 - mmengine - INFO - Epoch(train) [11][450/925] lr: 1.7772e-04 eta: 6:46:29 time: 0.3613 data_time: 0.0022 memory: 5693 grad_norm: 1009.1225 loss: 460.1483 loss_cls: 176.3206 loss_bbox: 135.8319 loss_dfl: 147.9958 +2024/01/19 13:22:25 - mmengine - INFO - Epoch(train) [11][500/925] lr: 1.7772e-04 eta: 6:46:09 time: 0.3741 data_time: 0.0054 memory: 5226 grad_norm: 1105.4601 loss: 458.4272 loss_cls: 174.6100 loss_bbox: 135.1305 loss_dfl: 148.6867 +2024/01/19 13:22:44 - mmengine - INFO - Epoch(train) [11][550/925] lr: 1.7772e-04 eta: 6:45:52 time: 0.3861 data_time: 0.0034 memory: 5532 grad_norm: 1120.5395 loss: 454.9299 loss_cls: 172.4584 loss_bbox: 135.4021 loss_dfl: 147.0694 +2024/01/19 13:23:03 - mmengine - INFO - Epoch(train) [11][600/925] lr: 1.7772e-04 eta: 6:45:31 time: 0.3727 data_time: 0.0022 memory: 5306 grad_norm: 1021.9547 loss: 455.5531 loss_cls: 174.1691 loss_bbox: 133.6806 loss_dfl: 147.7034 +2024/01/19 13:23:22 - mmengine - INFO - Epoch(train) [11][650/925] lr: 1.7772e-04 eta: 6:45:11 time: 0.3767 data_time: 0.0022 memory: 5572 grad_norm: 1095.4169 loss: 460.6470 loss_cls: 175.5849 loss_bbox: 136.3987 loss_dfl: 148.6633 +2024/01/19 13:23:40 - mmengine - INFO - Epoch(train) [11][700/925] lr: 1.7772e-04 eta: 6:44:52 time: 0.3788 data_time: 0.0020 memory: 5452 grad_norm: 1285.2713 loss: 449.7152 loss_cls: 170.7035 loss_bbox: 132.6588 loss_dfl: 146.3529 +2024/01/19 13:23:59 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:23:59 - mmengine - INFO - Epoch(train) [11][750/925] lr: 1.7772e-04 eta: 6:44:31 time: 0.3721 data_time: 0.0044 memory: 5372 grad_norm: 1246.3394 loss: 450.4078 loss_cls: 170.8411 loss_bbox: 132.7287 loss_dfl: 146.8380 +2024/01/19 13:24:18 - mmengine - INFO - Epoch(train) [11][800/925] lr: 1.7772e-04 eta: 6:44:14 time: 0.3856 data_time: 0.0024 memory: 5466 grad_norm: 1129.9113 loss: 455.6451 loss_cls: 172.8510 loss_bbox: 135.2674 loss_dfl: 147.5267 +2024/01/19 13:24:38 - mmengine - INFO - Epoch(train) [11][850/925] lr: 1.7772e-04 eta: 6:43:57 time: 0.3868 data_time: 0.0023 memory: 5412 grad_norm: 1304.2455 loss: 460.2697 loss_cls: 175.8968 loss_bbox: 135.8994 loss_dfl: 148.4735 +2024/01/19 13:24:56 - mmengine - INFO - Epoch(train) [11][900/925] lr: 1.7772e-04 eta: 6:43:35 time: 0.3691 data_time: 0.0020 memory: 5639 grad_norm: 999.7096 loss: 459.5622 loss_cls: 174.5567 loss_bbox: 136.2666 loss_dfl: 148.7389 +2024/01/19 13:25:05 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:25:29 - mmengine - INFO - Epoch(train) [12][ 50/925] lr: 1.7525e-04 eta: 6:43:32 time: 0.4697 data_time: 0.0815 memory: 5572 grad_norm: 1247.2843 loss: 456.1026 loss_cls: 173.5048 loss_bbox: 134.3620 loss_dfl: 148.2359 +2024/01/19 13:25:48 - mmengine - INFO - Epoch(train) [12][100/925] lr: 1.7525e-04 eta: 6:43:13 time: 0.3813 data_time: 0.0021 memory: 5506 grad_norm: 960.4008 loss: 455.9257 loss_cls: 174.4865 loss_bbox: 133.9623 loss_dfl: 147.4769 +2024/01/19 13:26:07 - mmengine - INFO - Epoch(train) [12][150/925] lr: 1.7525e-04 eta: 6:42:54 time: 0.3784 data_time: 0.0037 memory: 5172 grad_norm: 1037.5590 loss: 453.3545 loss_cls: 174.3026 loss_bbox: 132.8774 loss_dfl: 146.1745 +2024/01/19 13:26:26 - mmengine - INFO - Epoch(train) [12][200/925] lr: 1.7525e-04 eta: 6:42:32 time: 0.3700 data_time: 0.0023 memory: 5386 grad_norm: 1023.0232 loss: 463.4253 loss_cls: 178.0045 loss_bbox: 136.8682 loss_dfl: 148.5526 +2024/01/19 13:26:44 - mmengine - INFO - Epoch(train) [12][250/925] lr: 1.7525e-04 eta: 6:42:07 time: 0.3589 data_time: 0.0023 memory: 5279 grad_norm: 955.3537 loss: 462.1999 loss_cls: 176.9907 loss_bbox: 136.6164 loss_dfl: 148.5928 +2024/01/19 13:27:02 - mmengine - INFO - Epoch(train) [12][300/925] lr: 1.7525e-04 eta: 6:41:42 time: 0.3616 data_time: 0.0021 memory: 5359 grad_norm: 1055.8029 loss: 451.6415 loss_cls: 171.4692 loss_bbox: 133.0549 loss_dfl: 147.1174 +2024/01/19 13:27:20 - mmengine - INFO - Epoch(train) [12][350/925] lr: 1.7525e-04 eta: 6:41:17 time: 0.3597 data_time: 0.0021 memory: 5452 grad_norm: 1040.4264 loss: 459.4067 loss_cls: 177.4290 loss_bbox: 133.3856 loss_dfl: 148.5922 +2024/01/19 13:27:38 - mmengine - INFO - Epoch(train) [12][400/925] lr: 1.7525e-04 eta: 6:40:56 time: 0.3705 data_time: 0.0022 memory: 5279 grad_norm: 978.0295 loss: 458.1389 loss_cls: 175.4678 loss_bbox: 135.3056 loss_dfl: 147.3656 +2024/01/19 13:27:56 - mmengine - INFO - Epoch(train) [12][450/925] lr: 1.7525e-04 eta: 6:40:31 time: 0.3616 data_time: 0.0023 memory: 5639 grad_norm: 1123.9431 loss: 459.7335 loss_cls: 176.3591 loss_bbox: 134.9919 loss_dfl: 148.3826 +2024/01/19 13:28:15 - mmengine - INFO - Epoch(train) [12][500/925] lr: 1.7525e-04 eta: 6:40:09 time: 0.3677 data_time: 0.0025 memory: 5239 grad_norm: 1070.0339 loss: 452.2751 loss_cls: 170.4823 loss_bbox: 134.5901 loss_dfl: 147.2028 +2024/01/19 13:28:32 - mmengine - INFO - Epoch(train) [12][550/925] lr: 1.7525e-04 eta: 6:39:41 time: 0.3493 data_time: 0.0025 memory: 5426 grad_norm: 1010.9621 loss: 450.1854 loss_cls: 171.0438 loss_bbox: 133.1904 loss_dfl: 145.9512 +2024/01/19 13:28:52 - mmengine - INFO - Epoch(train) [12][600/925] lr: 1.7525e-04 eta: 6:39:24 time: 0.3849 data_time: 0.0030 memory: 5292 grad_norm: 1016.1533 loss: 458.7707 loss_cls: 174.2651 loss_bbox: 136.7876 loss_dfl: 147.7181 +2024/01/19 13:29:10 - mmengine - INFO - Epoch(train) [12][650/925] lr: 1.7525e-04 eta: 6:38:59 time: 0.3593 data_time: 0.0020 memory: 5759 grad_norm: 1125.1634 loss: 458.9128 loss_cls: 174.6927 loss_bbox: 135.6040 loss_dfl: 148.6161 +2024/01/19 13:29:29 - mmengine - INFO - Epoch(train) [12][700/925] lr: 1.7525e-04 eta: 6:38:44 time: 0.3917 data_time: 0.0021 memory: 5399 grad_norm: 989.7277 loss: 455.3525 loss_cls: 173.6644 loss_bbox: 134.9381 loss_dfl: 146.7500 +2024/01/19 13:29:47 - mmengine - INFO - Epoch(train) [12][750/925] lr: 1.7525e-04 eta: 6:38:21 time: 0.3664 data_time: 0.0021 memory: 5492 grad_norm: 1016.2145 loss: 458.7628 loss_cls: 175.6752 loss_bbox: 135.6221 loss_dfl: 147.4655 +2024/01/19 13:30:06 - mmengine - INFO - Epoch(train) [12][800/925] lr: 1.7525e-04 eta: 6:38:00 time: 0.3712 data_time: 0.0024 memory: 5626 grad_norm: 1145.7190 loss: 448.4809 loss_cls: 170.0193 loss_bbox: 132.6746 loss_dfl: 145.7871 +2024/01/19 13:30:16 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:30:25 - mmengine - INFO - Epoch(train) [12][850/925] lr: 1.7525e-04 eta: 6:37:42 time: 0.3826 data_time: 0.0026 memory: 5266 grad_norm: 965.4046 loss: 460.6833 loss_cls: 177.2531 loss_bbox: 135.1421 loss_dfl: 148.2882 +2024/01/19 13:30:44 - mmengine - INFO - Epoch(train) [12][900/925] lr: 1.7525e-04 eta: 6:37:24 time: 0.3803 data_time: 0.0022 memory: 5892 grad_norm: 968.7354 loss: 451.7810 loss_cls: 170.0695 loss_bbox: 134.8149 loss_dfl: 146.8966 +2024/01/19 13:30:52 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:31:15 - mmengine - INFO - Epoch(train) [13][ 50/925] lr: 1.7278e-04 eta: 6:37:07 time: 0.4521 data_time: 0.0872 memory: 5572 grad_norm: 1126.6229 loss: 454.8470 loss_cls: 174.6667 loss_bbox: 133.2193 loss_dfl: 146.9610 +2024/01/19 13:31:34 - mmengine - INFO - Epoch(train) [13][100/925] lr: 1.7278e-04 eta: 6:36:50 time: 0.3844 data_time: 0.0025 memory: 5426 grad_norm: inf loss: 448.2939 loss_cls: 170.4188 loss_bbox: 132.7210 loss_dfl: 145.1541 +2024/01/19 13:31:54 - mmengine - INFO - Epoch(train) [13][150/925] lr: 1.7278e-04 eta: 6:36:32 time: 0.3839 data_time: 0.0029 memory: 5866 grad_norm: 1132.0461 loss: 462.3783 loss_cls: 177.6713 loss_bbox: 136.0597 loss_dfl: 148.6472 +2024/01/19 13:32:12 - mmengine - INFO - Epoch(train) [13][200/925] lr: 1.7278e-04 eta: 6:36:10 time: 0.3657 data_time: 0.0022 memory: 5612 grad_norm: 1031.7807 loss: 451.7631 loss_cls: 170.7944 loss_bbox: 134.8519 loss_dfl: 146.1168 +2024/01/19 13:32:30 - mmengine - INFO - Epoch(train) [13][250/925] lr: 1.7278e-04 eta: 6:35:47 time: 0.3663 data_time: 0.0022 memory: 5439 grad_norm: 1068.3379 loss: 449.2007 loss_cls: 171.7189 loss_bbox: 132.4308 loss_dfl: 145.0509 +2024/01/19 13:32:49 - mmengine - INFO - Epoch(train) [13][300/925] lr: 1.7278e-04 eta: 6:35:26 time: 0.3731 data_time: 0.0023 memory: 5359 grad_norm: 1113.0638 loss: 459.7262 loss_cls: 175.3697 loss_bbox: 135.4858 loss_dfl: 148.8706 +2024/01/19 13:33:08 - mmengine - INFO - Epoch(train) [13][350/925] lr: 1.7278e-04 eta: 6:35:07 time: 0.3757 data_time: 0.0025 memory: 5132 grad_norm: 1184.0663 loss: 451.6309 loss_cls: 173.0492 loss_bbox: 132.2966 loss_dfl: 146.2852 +2024/01/19 13:33:26 - mmengine - INFO - Epoch(train) [13][400/925] lr: 1.7278e-04 eta: 6:34:42 time: 0.3585 data_time: 0.0024 memory: 5306 grad_norm: 1041.0272 loss: 456.7901 loss_cls: 174.4826 loss_bbox: 133.7614 loss_dfl: 148.5461 +2024/01/19 13:33:45 - mmengine - INFO - Epoch(train) [13][450/925] lr: 1.7278e-04 eta: 6:34:24 time: 0.3835 data_time: 0.0028 memory: 5479 grad_norm: 1109.4282 loss: 452.4803 loss_cls: 172.0124 loss_bbox: 133.0775 loss_dfl: 147.3904 +2024/01/19 13:34:04 - mmengine - INFO - Epoch(train) [13][500/925] lr: 1.7278e-04 eta: 6:34:08 time: 0.3878 data_time: 0.0028 memory: 5479 grad_norm: 1084.9187 loss: 459.0986 loss_cls: 176.1824 loss_bbox: 134.9198 loss_dfl: 147.9964 +2024/01/19 13:34:22 - mmengine - INFO - Epoch(train) [13][550/925] lr: 1.7278e-04 eta: 6:33:43 time: 0.3568 data_time: 0.0020 memory: 5492 grad_norm: 961.1436 loss: 454.6772 loss_cls: 173.8390 loss_bbox: 133.4777 loss_dfl: 147.3606 +2024/01/19 13:34:41 - mmengine - INFO - Epoch(train) [13][600/925] lr: 1.7278e-04 eta: 6:33:24 time: 0.3774 data_time: 0.0048 memory: 5372 grad_norm: 1028.4434 loss: 456.4023 loss_cls: 173.3798 loss_bbox: 135.0290 loss_dfl: 147.9935 +2024/01/19 13:35:00 - mmengine - INFO - Epoch(train) [13][650/925] lr: 1.7278e-04 eta: 6:33:05 time: 0.3821 data_time: 0.0027 memory: 5386 grad_norm: 1023.0322 loss: 458.0343 loss_cls: 174.7153 loss_bbox: 135.4090 loss_dfl: 147.9100 +2024/01/19 13:35:19 - mmengine - INFO - Epoch(train) [13][700/925] lr: 1.7278e-04 eta: 6:32:43 time: 0.3669 data_time: 0.0021 memory: 5826 grad_norm: 1088.9726 loss: 459.0508 loss_cls: 174.3334 loss_bbox: 137.5211 loss_dfl: 147.1963 +2024/01/19 13:35:38 - mmengine - INFO - Epoch(train) [13][750/925] lr: 1.7278e-04 eta: 6:32:26 time: 0.3865 data_time: 0.0024 memory: 5559 grad_norm: 1163.0576 loss: 446.3136 loss_cls: 169.4144 loss_bbox: 131.5213 loss_dfl: 145.3779 +2024/01/19 13:35:57 - mmengine - INFO - Epoch(train) [13][800/925] lr: 1.7278e-04 eta: 6:32:07 time: 0.3765 data_time: 0.0028 memory: 5679 grad_norm: 972.4904 loss: 448.2473 loss_cls: 168.6804 loss_bbox: 133.5607 loss_dfl: 146.0061 +2024/01/19 13:36:16 - mmengine - INFO - Epoch(train) [13][850/925] lr: 1.7278e-04 eta: 6:31:49 time: 0.3840 data_time: 0.0023 memory: 5292 grad_norm: 1172.1636 loss: 458.7691 loss_cls: 173.6651 loss_bbox: 136.7130 loss_dfl: 148.3911 +2024/01/19 13:36:34 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:36:34 - mmengine - INFO - Epoch(train) [13][900/925] lr: 1.7278e-04 eta: 6:31:26 time: 0.3612 data_time: 0.0021 memory: 5346 grad_norm: 968.1094 loss: 455.3791 loss_cls: 173.9359 loss_bbox: 134.0793 loss_dfl: 147.3638 +2024/01/19 13:36:43 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:37:07 - mmengine - INFO - Epoch(train) [14][ 50/925] lr: 1.7030e-04 eta: 6:31:20 time: 0.4784 data_time: 0.0991 memory: 5439 grad_norm: 966.7072 loss: 457.3516 loss_cls: 174.0184 loss_bbox: 135.3961 loss_dfl: 147.9371 +2024/01/19 13:37:26 - mmengine - INFO - Epoch(train) [14][100/925] lr: 1.7030e-04 eta: 6:31:01 time: 0.3787 data_time: 0.0023 memory: 5266 grad_norm: 1039.4424 loss: 450.6414 loss_cls: 171.3345 loss_bbox: 132.9368 loss_dfl: 146.3702 +2024/01/19 13:37:45 - mmengine - INFO - Epoch(train) [14][150/925] lr: 1.7030e-04 eta: 6:30:40 time: 0.3712 data_time: 0.0029 memory: 5412 grad_norm: 1110.3134 loss: 449.6166 loss_cls: 167.6158 loss_bbox: 135.2039 loss_dfl: 146.7970 +2024/01/19 13:38:04 - mmengine - INFO - Epoch(train) [14][200/925] lr: 1.7030e-04 eta: 6:30:22 time: 0.3839 data_time: 0.0031 memory: 5479 grad_norm: 1075.9178 loss: 456.4026 loss_cls: 172.0447 loss_bbox: 136.0071 loss_dfl: 148.3508 +2024/01/19 13:38:23 - mmengine - INFO - Epoch(train) [14][250/925] lr: 1.7030e-04 eta: 6:30:04 time: 0.3813 data_time: 0.0021 memory: 5506 grad_norm: 1124.1826 loss: 452.1341 loss_cls: 171.6880 loss_bbox: 133.9437 loss_dfl: 146.5025 +2024/01/19 13:38:41 - mmengine - INFO - Epoch(train) [14][300/925] lr: 1.7030e-04 eta: 6:29:41 time: 0.3620 data_time: 0.0021 memory: 5346 grad_norm: 1061.6924 loss: 445.5911 loss_cls: 168.0553 loss_bbox: 131.4468 loss_dfl: 146.0889 +2024/01/19 13:39:00 - mmengine - INFO - Epoch(train) [14][350/925] lr: 1.7030e-04 eta: 6:29:20 time: 0.3711 data_time: 0.0021 memory: 5546 grad_norm: 1084.4789 loss: 454.9827 loss_cls: 173.5220 loss_bbox: 133.9931 loss_dfl: 147.4677 +2024/01/19 13:39:19 - mmengine - INFO - Epoch(train) [14][400/925] lr: 1.7030e-04 eta: 6:29:01 time: 0.3793 data_time: 0.0024 memory: 5546 grad_norm: 1040.0412 loss: 448.8655 loss_cls: 169.8125 loss_bbox: 132.9662 loss_dfl: 146.0868 +2024/01/19 13:39:38 - mmengine - INFO - Epoch(train) [14][450/925] lr: 1.7030e-04 eta: 6:28:43 time: 0.3814 data_time: 0.0024 memory: 5693 grad_norm: 1076.8141 loss: 456.2613 loss_cls: 173.9273 loss_bbox: 133.9308 loss_dfl: 148.4032 +2024/01/19 13:39:56 - mmengine - INFO - Epoch(train) [14][500/925] lr: 1.7030e-04 eta: 6:28:20 time: 0.3632 data_time: 0.0022 memory: 5612 grad_norm: 1073.5510 loss: 452.1197 loss_cls: 171.9910 loss_bbox: 132.9959 loss_dfl: 147.1328 +2024/01/19 13:40:15 - mmengine - INFO - Epoch(train) [14][550/925] lr: 1.7030e-04 eta: 6:28:03 time: 0.3868 data_time: 0.0024 memory: 5506 grad_norm: 942.8552 loss: 452.8432 loss_cls: 173.0194 loss_bbox: 133.2091 loss_dfl: 146.6147 +2024/01/19 13:40:34 - mmengine - INFO - Epoch(train) [14][600/925] lr: 1.7030e-04 eta: 6:27:44 time: 0.3792 data_time: 0.0024 memory: 5439 grad_norm: 1175.2418 loss: 451.3572 loss_cls: 170.0318 loss_bbox: 134.7569 loss_dfl: 146.5685 +2024/01/19 13:40:52 - mmengine - INFO - Epoch(train) [14][650/925] lr: 1.7030e-04 eta: 6:27:19 time: 0.3536 data_time: 0.0022 memory: 5319 grad_norm: 1002.4560 loss: 457.6657 loss_cls: 175.4213 loss_bbox: 134.3596 loss_dfl: 147.8848 +2024/01/19 13:41:11 - mmengine - INFO - Epoch(train) [14][700/925] lr: 1.7030e-04 eta: 6:27:01 time: 0.3864 data_time: 0.0031 memory: 5559 grad_norm: 1024.5428 loss: 443.3840 loss_cls: 166.3511 loss_bbox: 132.0662 loss_dfl: 144.9667 +2024/01/19 13:41:30 - mmengine - INFO - Epoch(train) [14][750/925] lr: 1.7030e-04 eta: 6:26:41 time: 0.3706 data_time: 0.0026 memory: 5466 grad_norm: 1031.4578 loss: 452.8035 loss_cls: 171.5107 loss_bbox: 134.2165 loss_dfl: 147.0764 +2024/01/19 13:41:48 - mmengine - INFO - Epoch(train) [14][800/925] lr: 1.7030e-04 eta: 6:26:18 time: 0.3640 data_time: 0.0028 memory: 5572 grad_norm: 984.1551 loss: 454.7285 loss_cls: 173.2215 loss_bbox: 134.3018 loss_dfl: 147.2052 +2024/01/19 13:42:07 - mmengine - INFO - Epoch(train) [14][850/925] lr: 1.7030e-04 eta: 6:25:57 time: 0.3698 data_time: 0.0029 memory: 5492 grad_norm: 1058.9735 loss: 444.4235 loss_cls: 168.0793 loss_bbox: 131.3024 loss_dfl: 145.0418 +2024/01/19 13:42:26 - mmengine - INFO - Epoch(train) [14][900/925] lr: 1.7030e-04 eta: 6:25:40 time: 0.3871 data_time: 0.0029 memory: 5506 grad_norm: 1044.3852 loss: 443.0089 loss_cls: 165.8018 loss_bbox: 132.0818 loss_dfl: 145.1253 +2024/01/19 13:42:35 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:42:57 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:42:57 - mmengine - INFO - Epoch(train) [15][ 50/925] lr: 1.6783e-04 eta: 6:25:20 time: 0.4329 data_time: 0.0934 memory: 5492 grad_norm: 998.4057 loss: 448.6762 loss_cls: 171.2262 loss_bbox: 131.3877 loss_dfl: 146.0623 +2024/01/19 13:43:15 - mmengine - INFO - Epoch(train) [15][100/925] lr: 1.6783e-04 eta: 6:24:58 time: 0.3642 data_time: 0.0031 memory: 5292 grad_norm: 1075.2435 loss: 453.7638 loss_cls: 172.4640 loss_bbox: 133.8722 loss_dfl: 147.4276 +2024/01/19 13:43:34 - mmengine - INFO - Epoch(train) [15][150/925] lr: 1.6783e-04 eta: 6:24:40 time: 0.3834 data_time: 0.0085 memory: 5159 grad_norm: 1241.1267 loss: 452.4471 loss_cls: 172.2071 loss_bbox: 132.9816 loss_dfl: 147.2585 +2024/01/19 13:43:53 - mmengine - INFO - Epoch(train) [15][200/925] lr: 1.6783e-04 eta: 6:24:19 time: 0.3721 data_time: 0.0030 memory: 5319 grad_norm: 1028.9718 loss: 452.1480 loss_cls: 172.3426 loss_bbox: 133.6938 loss_dfl: 146.1117 +2024/01/19 13:44:09 - mmengine - INFO - Epoch(train) [15][250/925] lr: 1.6783e-04 eta: 6:23:50 time: 0.3333 data_time: 0.0022 memory: 5292 grad_norm: 1093.6356 loss: 452.5170 loss_cls: 171.1852 loss_bbox: 133.6832 loss_dfl: 147.6485 +2024/01/19 13:44:28 - mmengine - INFO - Epoch(train) [15][300/925] lr: 1.6783e-04 eta: 6:23:30 time: 0.3749 data_time: 0.0024 memory: 5612 grad_norm: 1097.8737 loss: 448.3993 loss_cls: 168.8667 loss_bbox: 133.0813 loss_dfl: 146.4514 +2024/01/19 13:44:47 - mmengine - INFO - Epoch(train) [15][350/925] lr: 1.6783e-04 eta: 6:23:08 time: 0.3685 data_time: 0.0030 memory: 5199 grad_norm: inf loss: 455.8651 loss_cls: 173.7991 loss_bbox: 133.9586 loss_dfl: 148.1074 +2024/01/19 13:45:05 - mmengine - INFO - Epoch(train) [15][400/925] lr: 1.6783e-04 eta: 6:22:46 time: 0.3627 data_time: 0.0023 memory: 5532 grad_norm: 1009.8588 loss: 455.5631 loss_cls: 173.0235 loss_bbox: 135.1786 loss_dfl: 147.3610 +2024/01/19 13:45:24 - mmengine - INFO - Epoch(train) [15][450/925] lr: 1.6783e-04 eta: 6:22:28 time: 0.3828 data_time: 0.0021 memory: 5332 grad_norm: 1090.3179 loss: 458.2115 loss_cls: 174.5540 loss_bbox: 135.7321 loss_dfl: 147.9254 +2024/01/19 13:45:44 - mmengine - INFO - Epoch(train) [15][500/925] lr: 1.6783e-04 eta: 6:22:14 time: 0.4003 data_time: 0.0022 memory: 5346 grad_norm: 1069.1379 loss: 445.7994 loss_cls: 167.2630 loss_bbox: 132.6115 loss_dfl: 145.9250 +2024/01/19 13:46:04 - mmengine - INFO - Epoch(train) [15][550/925] lr: 1.6783e-04 eta: 6:21:57 time: 0.3898 data_time: 0.0023 memory: 5359 grad_norm: 1181.9926 loss: 447.0511 loss_cls: 170.4715 loss_bbox: 131.5979 loss_dfl: 144.9817 +2024/01/19 13:46:22 - mmengine - INFO - Epoch(train) [15][600/925] lr: 1.6783e-04 eta: 6:21:36 time: 0.3681 data_time: 0.0023 memory: 5439 grad_norm: 1211.8429 loss: 457.7551 loss_cls: 174.8258 loss_bbox: 135.5390 loss_dfl: 147.3903 +2024/01/19 13:46:40 - mmengine - INFO - Epoch(train) [15][650/925] lr: 1.6783e-04 eta: 6:21:15 time: 0.3681 data_time: 0.0022 memory: 5452 grad_norm: 1048.2472 loss: 448.6724 loss_cls: 169.7198 loss_bbox: 132.4633 loss_dfl: 146.4893 +2024/01/19 13:46:59 - mmengine - INFO - Epoch(train) [15][700/925] lr: 1.6783e-04 eta: 6:20:56 time: 0.3796 data_time: 0.0024 memory: 5319 grad_norm: 967.4551 loss: 450.8936 loss_cls: 170.7836 loss_bbox: 132.9249 loss_dfl: 147.1850 +2024/01/19 13:47:18 - mmengine - INFO - Epoch(train) [15][750/925] lr: 1.6783e-04 eta: 6:20:36 time: 0.3746 data_time: 0.0022 memory: 5732 grad_norm: 1018.3643 loss: 446.7486 loss_cls: 168.4154 loss_bbox: 131.9742 loss_dfl: 146.3590 +2024/01/19 13:47:37 - mmengine - INFO - Epoch(train) [15][800/925] lr: 1.6783e-04 eta: 6:20:18 time: 0.3810 data_time: 0.0022 memory: 5319 grad_norm: 982.1533 loss: 458.2759 loss_cls: 173.6110 loss_bbox: 136.9108 loss_dfl: 147.7541 +2024/01/19 13:47:57 - mmengine - INFO - Epoch(train) [15][850/925] lr: 1.6783e-04 eta: 6:20:01 time: 0.3895 data_time: 0.0022 memory: 5266 grad_norm: 1137.0243 loss: 437.0671 loss_cls: 162.2834 loss_bbox: 129.6910 loss_dfl: 145.0926 +2024/01/19 13:48:16 - mmengine - INFO - Epoch(train) [15][900/925] lr: 1.6783e-04 eta: 6:19:44 time: 0.3893 data_time: 0.0022 memory: 5439 grad_norm: 1249.4638 loss: 450.7292 loss_cls: 168.8987 loss_bbox: 134.8718 loss_dfl: 146.9586 +2024/01/19 13:48:25 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:48:26 - mmengine - INFO - Saving checkpoint at 15 epochs +2024/01/19 13:48:34 - mmengine - INFO - Epoch(val) [15][ 50/625] eta: 0:00:20 time: 0.0358 data_time: 0.0009 memory: 5306 +2024/01/19 13:48:36 - mmengine - INFO - Epoch(val) [15][100/625] eta: 0:00:18 time: 0.0347 data_time: 0.0004 memory: 843 +2024/01/19 13:48:38 - mmengine - INFO - Epoch(val) [15][150/625] eta: 0:00:16 time: 0.0350 data_time: 0.0003 memory: 843 +2024/01/19 13:48:40 - mmengine - INFO - Epoch(val) [15][200/625] eta: 0:00:15 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 13:48:41 - mmengine - INFO - Epoch(val) [15][250/625] eta: 0:00:13 time: 0.0347 data_time: 0.0003 memory: 843 +2024/01/19 13:48:43 - mmengine - INFO - Epoch(val) [15][300/625] eta: 0:00:11 time: 0.0349 data_time: 0.0003 memory: 843 +2024/01/19 13:48:45 - mmengine - INFO - Epoch(val) [15][350/625] eta: 0:00:09 time: 0.0361 data_time: 0.0004 memory: 843 +2024/01/19 13:48:47 - mmengine - INFO - Epoch(val) [15][400/625] eta: 0:00:07 time: 0.0364 data_time: 0.0004 memory: 843 +2024/01/19 13:48:48 - mmengine - INFO - Epoch(val) [15][450/625] eta: 0:00:06 time: 0.0317 data_time: 0.0003 memory: 843 +2024/01/19 13:48:50 - mmengine - INFO - Epoch(val) [15][500/625] eta: 0:00:04 time: 0.0281 data_time: 0.0002 memory: 843 +2024/01/19 13:48:51 - mmengine - INFO - Epoch(val) [15][550/625] eta: 0:00:02 time: 0.0272 data_time: 0.0002 memory: 843 +2024/01/19 13:48:53 - mmengine - INFO - Epoch(val) [15][600/625] eta: 0:00:00 time: 0.0301 data_time: 0.0002 memory: 843 +2024/01/19 13:49:08 - mmengine - INFO - Evaluating bbox... +2024/01/19 13:50:36 - mmengine - INFO - bbox_mAP_copypaste: 0.435 0.592 0.474 0.242 0.481 0.583 +2024/01/19 13:50:39 - mmengine - INFO - Epoch(val) [15][625/625] coco/bbox_mAP: 0.4350 coco/bbox_mAP_50: 0.5920 coco/bbox_mAP_75: 0.4740 coco/bbox_mAP_s: 0.2420 coco/bbox_mAP_m: 0.4810 coco/bbox_mAP_l: 0.5830 data_time: 0.0002 time: 0.0266 +2024/01/19 13:51:02 - mmengine - INFO - Epoch(train) [16][ 50/925] lr: 1.6535e-04 eta: 6:19:33 time: 0.4602 data_time: 0.0831 memory: 5412 grad_norm: 936.9245 loss: 438.0981 loss_cls: 164.4288 loss_bbox: 129.1999 loss_dfl: 144.4694 +2024/01/19 13:51:20 - mmengine - INFO - Epoch(train) [16][100/925] lr: 1.6535e-04 eta: 6:19:10 time: 0.3623 data_time: 0.0021 memory: 5519 grad_norm: 981.9512 loss: 447.6234 loss_cls: 170.0563 loss_bbox: 131.9426 loss_dfl: 145.6245 +2024/01/19 13:51:30 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:51:40 - mmengine - INFO - Epoch(train) [16][150/925] lr: 1.6535e-04 eta: 6:18:53 time: 0.3890 data_time: 0.0025 memory: 5199 grad_norm: 1031.5002 loss: 450.7880 loss_cls: 171.7643 loss_bbox: 132.1806 loss_dfl: 146.8432 +2024/01/19 13:51:58 - mmengine - INFO - Epoch(train) [16][200/925] lr: 1.6535e-04 eta: 6:18:33 time: 0.3713 data_time: 0.0020 memory: 5199 grad_norm: 1064.5512 loss: 444.2553 loss_cls: 165.7945 loss_bbox: 132.9817 loss_dfl: 145.4791 +2024/01/19 13:52:16 - mmengine - INFO - Epoch(train) [16][250/925] lr: 1.6535e-04 eta: 6:18:10 time: 0.3597 data_time: 0.0022 memory: 5399 grad_norm: 905.0029 loss: 445.5433 loss_cls: 168.1909 loss_bbox: 131.9624 loss_dfl: 145.3899 +2024/01/19 13:52:36 - mmengine - INFO - Epoch(train) [16][300/925] lr: 1.6535e-04 eta: 6:17:55 time: 0.3991 data_time: 0.0021 memory: 5306 grad_norm: 1048.3410 loss: 456.0584 loss_cls: 173.1437 loss_bbox: 135.2423 loss_dfl: 147.6724 +2024/01/19 13:52:56 - mmengine - INFO - Epoch(train) [16][350/925] lr: 1.6535e-04 eta: 6:17:39 time: 0.3946 data_time: 0.0021 memory: 5759 grad_norm: 1080.5390 loss: 456.2420 loss_cls: 172.2183 loss_bbox: 136.2743 loss_dfl: 147.7494 +2024/01/19 13:53:15 - mmengine - INFO - Epoch(train) [16][400/925] lr: 1.6535e-04 eta: 6:17:20 time: 0.3770 data_time: 0.0020 memory: 5319 grad_norm: 979.0065 loss: 446.1046 loss_cls: 167.5033 loss_bbox: 133.1488 loss_dfl: 145.4525 +2024/01/19 13:53:34 - mmengine - INFO - Epoch(train) [16][450/925] lr: 1.6535e-04 eta: 6:17:04 time: 0.3937 data_time: 0.0021 memory: 5546 grad_norm: 1022.4675 loss: 450.8435 loss_cls: 170.5852 loss_bbox: 133.7769 loss_dfl: 146.4814 +2024/01/19 13:53:53 - mmengine - INFO - Epoch(train) [16][500/925] lr: 1.6535e-04 eta: 6:16:45 time: 0.3803 data_time: 0.0032 memory: 5346 grad_norm: 1021.7835 loss: 450.3776 loss_cls: 171.2639 loss_bbox: 132.6958 loss_dfl: 146.4179 +2024/01/19 13:54:13 - mmengine - INFO - Epoch(train) [16][550/925] lr: 1.6535e-04 eta: 6:16:28 time: 0.3852 data_time: 0.0022 memory: 5306 grad_norm: 1059.7363 loss: 454.2702 loss_cls: 173.3196 loss_bbox: 133.6763 loss_dfl: 147.2742 +2024/01/19 13:54:32 - mmengine - INFO - Epoch(train) [16][600/925] lr: 1.6535e-04 eta: 6:16:10 time: 0.3843 data_time: 0.0021 memory: 5412 grad_norm: 1133.2994 loss: 447.9219 loss_cls: 168.7788 loss_bbox: 132.8856 loss_dfl: 146.2575 +2024/01/19 13:54:52 - mmengine - INFO - Epoch(train) [16][650/925] lr: 1.6535e-04 eta: 6:15:54 time: 0.3955 data_time: 0.0021 memory: 5839 grad_norm: 1059.5281 loss: 447.5564 loss_cls: 167.3781 loss_bbox: 133.6057 loss_dfl: 146.5726 +2024/01/19 13:55:11 - mmengine - INFO - Epoch(train) [16][700/925] lr: 1.6535e-04 eta: 6:15:35 time: 0.3792 data_time: 0.0021 memory: 5226 grad_norm: 1036.9407 loss: 451.3984 loss_cls: 170.2033 loss_bbox: 133.9414 loss_dfl: 147.2537 +2024/01/19 13:55:30 - mmengine - INFO - Epoch(train) [16][750/925] lr: 1.6535e-04 eta: 6:15:16 time: 0.3761 data_time: 0.0021 memory: 5532 grad_norm: 957.9372 loss: 452.9051 loss_cls: 171.0538 loss_bbox: 134.5141 loss_dfl: 147.3372 +2024/01/19 13:55:49 - mmengine - INFO - Epoch(train) [16][800/925] lr: 1.6535e-04 eta: 6:14:58 time: 0.3843 data_time: 0.0021 memory: 5959 grad_norm: 963.5299 loss: 457.7194 loss_cls: 173.9241 loss_bbox: 136.1412 loss_dfl: 147.6540 +2024/01/19 13:56:08 - mmengine - INFO - Epoch(train) [16][850/925] lr: 1.6535e-04 eta: 6:14:41 time: 0.3905 data_time: 0.0020 memory: 5586 grad_norm: 1179.8958 loss: 451.3734 loss_cls: 171.7894 loss_bbox: 133.4919 loss_dfl: 146.0922 +2024/01/19 13:56:28 - mmengine - INFO - Epoch(train) [16][900/925] lr: 1.6535e-04 eta: 6:14:25 time: 0.3936 data_time: 0.0023 memory: 5292 grad_norm: 1037.4934 loss: 449.2470 loss_cls: 168.8971 loss_bbox: 133.6729 loss_dfl: 146.6770 +2024/01/19 13:56:37 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:57:00 - mmengine - INFO - Epoch(train) [17][ 50/925] lr: 1.6287e-04 eta: 6:14:08 time: 0.4590 data_time: 0.0901 memory: 5706 grad_norm: 1003.3427 loss: 445.7291 loss_cls: 169.1461 loss_bbox: 131.1817 loss_dfl: 145.4013 +2024/01/19 13:57:18 - mmengine - INFO - Epoch(train) [17][100/925] lr: 1.6287e-04 eta: 6:13:47 time: 0.3668 data_time: 0.0021 memory: 5772 grad_norm: 995.9269 loss: 448.0759 loss_cls: 169.2346 loss_bbox: 132.5022 loss_dfl: 146.3392 +2024/01/19 13:57:38 - mmengine - INFO - Epoch(train) [17][150/925] lr: 1.6287e-04 eta: 6:13:29 time: 0.3857 data_time: 0.0021 memory: 5666 grad_norm: 1044.8326 loss: 452.0519 loss_cls: 171.1808 loss_bbox: 133.4611 loss_dfl: 147.4100 +2024/01/19 13:57:56 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 13:57:56 - mmengine - INFO - Epoch(train) [17][200/925] lr: 1.6287e-04 eta: 6:13:06 time: 0.3588 data_time: 0.0020 memory: 5279 grad_norm: 984.4315 loss: 444.8410 loss_cls: 167.8698 loss_bbox: 131.5153 loss_dfl: 145.4558 +2024/01/19 13:58:15 - mmengine - INFO - Epoch(train) [17][250/925] lr: 1.6287e-04 eta: 6:12:48 time: 0.3844 data_time: 0.0021 memory: 5506 grad_norm: 1043.0994 loss: 450.8724 loss_cls: 170.4537 loss_bbox: 133.7979 loss_dfl: 146.6208 +2024/01/19 13:58:34 - mmengine - INFO - Epoch(train) [17][300/925] lr: 1.6287e-04 eta: 6:12:29 time: 0.3795 data_time: 0.0020 memory: 5439 grad_norm: 1052.7876 loss: 450.5231 loss_cls: 170.8992 loss_bbox: 133.0979 loss_dfl: 146.5259 +2024/01/19 13:58:53 - mmengine - INFO - Epoch(train) [17][350/925] lr: 1.6287e-04 eta: 6:12:11 time: 0.3837 data_time: 0.0022 memory: 5693 grad_norm: 1028.7068 loss: 440.4945 loss_cls: 164.9149 loss_bbox: 130.5315 loss_dfl: 145.0481 +2024/01/19 13:59:13 - mmengine - INFO - Epoch(train) [17][400/925] lr: 1.6287e-04 eta: 6:11:55 time: 0.3955 data_time: 0.0020 memory: 5372 grad_norm: 999.0769 loss: 448.9393 loss_cls: 169.3231 loss_bbox: 132.9651 loss_dfl: 146.6511 +2024/01/19 13:59:32 - mmengine - INFO - Epoch(train) [17][450/925] lr: 1.6287e-04 eta: 6:11:39 time: 0.3919 data_time: 0.0021 memory: 5186 grad_norm: 1002.5202 loss: 448.8226 loss_cls: 169.7630 loss_bbox: 132.9846 loss_dfl: 146.0749 +2024/01/19 13:59:52 - mmengine - INFO - Epoch(train) [17][500/925] lr: 1.6287e-04 eta: 6:11:20 time: 0.3816 data_time: 0.0020 memory: 5546 grad_norm: 1068.8609 loss: 438.1324 loss_cls: 162.0840 loss_bbox: 131.3890 loss_dfl: 144.6595 +2024/01/19 14:00:12 - mmengine - INFO - Epoch(train) [17][550/925] lr: 1.6287e-04 eta: 6:11:05 time: 0.3997 data_time: 0.0031 memory: 5479 grad_norm: 1245.1655 loss: 449.3072 loss_cls: 168.6712 loss_bbox: 133.4544 loss_dfl: 147.1817 +2024/01/19 14:00:30 - mmengine - INFO - Epoch(train) [17][600/925] lr: 1.6287e-04 eta: 6:10:45 time: 0.3757 data_time: 0.0020 memory: 5266 grad_norm: inf loss: 450.2566 loss_cls: 170.4324 loss_bbox: 132.7976 loss_dfl: 147.0265 +2024/01/19 14:00:50 - mmengine - INFO - Epoch(train) [17][650/925] lr: 1.6287e-04 eta: 6:10:29 time: 0.3972 data_time: 0.0021 memory: 5452 grad_norm: 945.8153 loss: 446.0581 loss_cls: 166.6314 loss_bbox: 132.4525 loss_dfl: 146.9743 +2024/01/19 14:01:09 - mmengine - INFO - Epoch(train) [17][700/925] lr: 1.6287e-04 eta: 6:10:10 time: 0.3790 data_time: 0.0021 memory: 5399 grad_norm: 987.2918 loss: 441.8436 loss_cls: 164.6334 loss_bbox: 131.9828 loss_dfl: 145.2274 +2024/01/19 14:01:29 - mmengine - INFO - Epoch(train) [17][750/925] lr: 1.6287e-04 eta: 6:09:53 time: 0.3895 data_time: 0.0021 memory: 5186 grad_norm: 1086.3242 loss: 447.0679 loss_cls: 169.1421 loss_bbox: 132.0186 loss_dfl: 145.9072 +2024/01/19 14:01:48 - mmengine - INFO - Epoch(train) [17][800/925] lr: 1.6287e-04 eta: 6:09:34 time: 0.3777 data_time: 0.0025 memory: 5452 grad_norm: 1048.7556 loss: 447.6131 loss_cls: 168.0321 loss_bbox: 133.3098 loss_dfl: 146.2712 +2024/01/19 14:02:07 - mmengine - INFO - Epoch(train) [17][850/925] lr: 1.6287e-04 eta: 6:09:17 time: 0.3927 data_time: 0.0028 memory: 5332 grad_norm: 1157.0967 loss: 446.0627 loss_cls: 169.4836 loss_bbox: 131.3012 loss_dfl: 145.2780 +2024/01/19 14:02:27 - mmengine - INFO - Epoch(train) [17][900/925] lr: 1.6287e-04 eta: 6:09:02 time: 0.3990 data_time: 0.0020 memory: 5159 grad_norm: 1031.4156 loss: 444.5026 loss_cls: 166.2137 loss_bbox: 132.5498 loss_dfl: 145.7391 +2024/01/19 14:02:36 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:02:59 - mmengine - INFO - Epoch(train) [18][ 50/925] lr: 1.6040e-04 eta: 6:08:44 time: 0.4530 data_time: 0.0869 memory: 5306 grad_norm: 1104.0327 loss: 445.8971 loss_cls: 169.1273 loss_bbox: 131.2371 loss_dfl: 145.5327 +2024/01/19 14:03:18 - mmengine - INFO - Epoch(train) [18][100/925] lr: 1.6040e-04 eta: 6:08:24 time: 0.3729 data_time: 0.0022 memory: 5386 grad_norm: 927.0277 loss: 444.5569 loss_cls: 167.7121 loss_bbox: 131.3592 loss_dfl: 145.4857 +2024/01/19 14:03:36 - mmengine - INFO - Epoch(train) [18][150/925] lr: 1.6040e-04 eta: 6:08:04 time: 0.3724 data_time: 0.0024 memory: 5279 grad_norm: 1109.5777 loss: 453.2187 loss_cls: 171.1026 loss_bbox: 134.9547 loss_dfl: 147.1614 +2024/01/19 14:03:54 - mmengine - INFO - Epoch(train) [18][200/925] lr: 1.6040e-04 eta: 6:07:38 time: 0.3468 data_time: 0.0022 memory: 5346 grad_norm: 982.6884 loss: 448.8321 loss_cls: 168.9153 loss_bbox: 133.4769 loss_dfl: 146.4399 +2024/01/19 14:04:12 - mmengine - INFO - Epoch(train) [18][250/925] lr: 1.6040e-04 eta: 6:07:16 time: 0.3602 data_time: 0.0021 memory: 5492 grad_norm: 1012.4727 loss: 447.0247 loss_cls: 168.0089 loss_bbox: 132.9318 loss_dfl: 146.0839 +2024/01/19 14:04:21 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:04:30 - mmengine - INFO - Epoch(train) [18][300/925] lr: 1.6040e-04 eta: 6:06:55 time: 0.3714 data_time: 0.0031 memory: 5559 grad_norm: 1005.3454 loss: 447.3067 loss_cls: 168.7342 loss_bbox: 132.3076 loss_dfl: 146.2649 +2024/01/19 14:04:49 - mmengine - INFO - Epoch(train) [18][350/925] lr: 1.6040e-04 eta: 6:06:35 time: 0.3723 data_time: 0.0037 memory: 5452 grad_norm: 997.3662 loss: 452.9764 loss_cls: 171.1473 loss_bbox: 134.7279 loss_dfl: 147.1012 +2024/01/19 14:05:07 - mmengine - INFO - Epoch(train) [18][400/925] lr: 1.6040e-04 eta: 6:06:11 time: 0.3533 data_time: 0.0022 memory: 5332 grad_norm: 1140.4636 loss: 443.5984 loss_cls: 167.2210 loss_bbox: 131.4547 loss_dfl: 144.9227 +2024/01/19 14:05:25 - mmengine - INFO - Epoch(train) [18][450/925] lr: 1.6040e-04 eta: 6:05:49 time: 0.3595 data_time: 0.0023 memory: 5439 grad_norm: 1123.6835 loss: 447.3711 loss_cls: 169.1508 loss_bbox: 132.3141 loss_dfl: 145.9062 +2024/01/19 14:05:44 - mmengine - INFO - Epoch(train) [18][500/925] lr: 1.6040e-04 eta: 6:05:32 time: 0.3937 data_time: 0.0023 memory: 5812 grad_norm: 1017.2086 loss: 448.3318 loss_cls: 169.7245 loss_bbox: 132.2720 loss_dfl: 146.3354 +2024/01/19 14:06:03 - mmengine - INFO - Epoch(train) [18][550/925] lr: 1.6040e-04 eta: 6:05:11 time: 0.3665 data_time: 0.0021 memory: 5479 grad_norm: 960.6068 loss: 442.1835 loss_cls: 165.3192 loss_bbox: 132.2645 loss_dfl: 144.5998 +2024/01/19 14:06:20 - mmengine - INFO - Epoch(train) [18][600/925] lr: 1.6040e-04 eta: 6:04:47 time: 0.3538 data_time: 0.0021 memory: 5212 grad_norm: 1166.4909 loss: 454.6523 loss_cls: 171.3771 loss_bbox: 135.7014 loss_dfl: 147.5738 +2024/01/19 14:06:40 - mmengine - INFO - Epoch(train) [18][650/925] lr: 1.6040e-04 eta: 6:04:29 time: 0.3851 data_time: 0.0032 memory: 5319 grad_norm: 1057.1252 loss: 440.9543 loss_cls: 165.0741 loss_bbox: 130.6102 loss_dfl: 145.2700 +2024/01/19 14:06:59 - mmengine - INFO - Epoch(train) [18][700/925] lr: 1.6040e-04 eta: 6:04:12 time: 0.3865 data_time: 0.0030 memory: 5586 grad_norm: 991.7705 loss: 450.1567 loss_cls: 169.4429 loss_bbox: 134.4535 loss_dfl: 146.2603 +2024/01/19 14:07:18 - mmengine - INFO - Epoch(train) [18][750/925] lr: 1.6040e-04 eta: 6:03:51 time: 0.3697 data_time: 0.0023 memory: 5466 grad_norm: 1077.3458 loss: 444.5744 loss_cls: 167.9270 loss_bbox: 131.6209 loss_dfl: 145.0266 +2024/01/19 14:07:36 - mmengine - INFO - Epoch(train) [18][800/925] lr: 1.6040e-04 eta: 6:03:31 time: 0.3731 data_time: 0.0021 memory: 5452 grad_norm: 978.6010 loss: 445.8062 loss_cls: 169.2594 loss_bbox: 130.6386 loss_dfl: 145.9082 +2024/01/19 14:07:57 - mmengine - INFO - Epoch(train) [18][850/925] lr: 1.6040e-04 eta: 6:03:17 time: 0.4065 data_time: 0.0031 memory: 5439 grad_norm: 988.4304 loss: 444.5100 loss_cls: 166.3628 loss_bbox: 132.7468 loss_dfl: 145.4004 +2024/01/19 14:08:16 - mmengine - INFO - Epoch(train) [18][900/925] lr: 1.6040e-04 eta: 6:02:58 time: 0.3803 data_time: 0.0020 memory: 5252 grad_norm: 1066.9373 loss: 442.3375 loss_cls: 165.1834 loss_bbox: 131.1891 loss_dfl: 145.9650 +2024/01/19 14:08:24 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:08:48 - mmengine - INFO - Epoch(train) [19][ 50/925] lr: 1.5793e-04 eta: 6:02:40 time: 0.4643 data_time: 0.0877 memory: 5266 grad_norm: 1007.0319 loss: 447.5931 loss_cls: 168.2992 loss_bbox: 132.5690 loss_dfl: 146.7249 +2024/01/19 14:09:07 - mmengine - INFO - Epoch(train) [19][100/925] lr: 1.5793e-04 eta: 6:02:23 time: 0.3891 data_time: 0.0021 memory: 5719 grad_norm: 1050.3870 loss: 438.5560 loss_cls: 164.0345 loss_bbox: 129.4397 loss_dfl: 145.0817 +2024/01/19 14:09:26 - mmengine - INFO - Epoch(train) [19][150/925] lr: 1.5793e-04 eta: 6:02:05 time: 0.3827 data_time: 0.0022 memory: 5306 grad_norm: 1081.2029 loss: 446.0667 loss_cls: 168.1031 loss_bbox: 131.5142 loss_dfl: 146.4493 +2024/01/19 14:09:45 - mmengine - INFO - Epoch(train) [19][200/925] lr: 1.5793e-04 eta: 6:01:44 time: 0.3688 data_time: 0.0021 memory: 5452 grad_norm: 994.6242 loss: 444.9691 loss_cls: 167.7068 loss_bbox: 131.5196 loss_dfl: 145.7427 +2024/01/19 14:10:03 - mmengine - INFO - Epoch(train) [19][250/925] lr: 1.5793e-04 eta: 6:01:24 time: 0.3734 data_time: 0.0021 memory: 5466 grad_norm: 1108.7620 loss: 443.6312 loss_cls: 166.3567 loss_bbox: 131.5628 loss_dfl: 145.7118 +2024/01/19 14:10:22 - mmengine - INFO - Epoch(train) [19][300/925] lr: 1.5793e-04 eta: 6:01:02 time: 0.3647 data_time: 0.0021 memory: 5292 grad_norm: 1023.5230 loss: 447.3604 loss_cls: 169.4342 loss_bbox: 131.8447 loss_dfl: 146.0815 +2024/01/19 14:10:41 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:10:41 - mmengine - INFO - Epoch(train) [19][350/925] lr: 1.5793e-04 eta: 6:00:43 time: 0.3812 data_time: 0.0021 memory: 5279 grad_norm: 1141.4420 loss: 450.3209 loss_cls: 170.8516 loss_bbox: 132.8209 loss_dfl: 146.6484 +2024/01/19 14:10:59 - mmengine - INFO - Epoch(train) [19][400/925] lr: 1.5793e-04 eta: 6:00:23 time: 0.3693 data_time: 0.0022 memory: 5372 grad_norm: 1000.8602 loss: 456.1360 loss_cls: 171.8279 loss_bbox: 136.0183 loss_dfl: 148.2898 +2024/01/19 14:11:18 - mmengine - INFO - Epoch(train) [19][450/925] lr: 1.5793e-04 eta: 6:00:02 time: 0.3714 data_time: 0.0021 memory: 5746 grad_norm: 1004.4393 loss: 449.3642 loss_cls: 169.3537 loss_bbox: 132.8407 loss_dfl: 147.1697 +2024/01/19 14:11:36 - mmengine - INFO - Epoch(train) [19][500/925] lr: 1.5793e-04 eta: 5:59:40 time: 0.3574 data_time: 0.0020 memory: 5626 grad_norm: 918.1414 loss: 448.7047 loss_cls: 168.4401 loss_bbox: 133.9398 loss_dfl: 146.3247 +2024/01/19 14:11:55 - mmengine - INFO - Epoch(train) [19][550/925] lr: 1.5793e-04 eta: 5:59:23 time: 0.3939 data_time: 0.0022 memory: 5146 grad_norm: 1031.9947 loss: 443.7714 loss_cls: 168.4026 loss_bbox: 129.5974 loss_dfl: 145.7714 +2024/01/19 14:12:15 - mmengine - INFO - Epoch(train) [19][600/925] lr: 1.5793e-04 eta: 5:59:05 time: 0.3841 data_time: 0.0029 memory: 5492 grad_norm: 1079.5978 loss: 450.7120 loss_cls: 169.4182 loss_bbox: 134.4246 loss_dfl: 146.8693 +2024/01/19 14:12:33 - mmengine - INFO - Epoch(train) [19][650/925] lr: 1.5793e-04 eta: 5:58:42 time: 0.3576 data_time: 0.0028 memory: 5519 grad_norm: 994.1758 loss: 443.6443 loss_cls: 167.5022 loss_bbox: 131.1696 loss_dfl: 144.9725 +2024/01/19 14:12:52 - mmengine - INFO - Epoch(train) [19][700/925] lr: 1.5793e-04 eta: 5:58:26 time: 0.3964 data_time: 0.0030 memory: 5292 grad_norm: 910.7333 loss: 443.8429 loss_cls: 165.4321 loss_bbox: 132.7824 loss_dfl: 145.6284 +2024/01/19 14:13:11 - mmengine - INFO - Epoch(train) [19][750/925] lr: 1.5793e-04 eta: 5:58:07 time: 0.3793 data_time: 0.0022 memory: 5306 grad_norm: 1180.1277 loss: 445.2573 loss_cls: 167.3923 loss_bbox: 131.8196 loss_dfl: 146.0454 +2024/01/19 14:13:31 - mmengine - INFO - Epoch(train) [19][800/925] lr: 1.5793e-04 eta: 5:57:48 time: 0.3813 data_time: 0.0021 memory: 5319 grad_norm: 1071.4348 loss: 440.8209 loss_cls: 165.0867 loss_bbox: 130.6154 loss_dfl: 145.1188 +2024/01/19 14:13:49 - mmengine - INFO - Epoch(train) [19][850/925] lr: 1.5793e-04 eta: 5:57:28 time: 0.3727 data_time: 0.0021 memory: 5546 grad_norm: 990.0443 loss: 444.9779 loss_cls: 165.5765 loss_bbox: 133.3554 loss_dfl: 146.0459 +2024/01/19 14:14:08 - mmengine - INFO - Epoch(train) [19][900/925] lr: 1.5793e-04 eta: 5:57:10 time: 0.3860 data_time: 0.0023 memory: 5439 grad_norm: inf loss: 439.1419 loss_cls: 162.7767 loss_bbox: 131.3068 loss_dfl: 145.0584 +2024/01/19 14:14:17 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:14:42 - mmengine - INFO - Epoch(train) [20][ 50/925] lr: 1.5545e-04 eta: 5:56:57 time: 0.4878 data_time: 0.0985 memory: 5746 grad_norm: 1039.0137 loss: 438.0960 loss_cls: 163.1894 loss_bbox: 130.1590 loss_dfl: 144.7476 +2024/01/19 14:15:01 - mmengine - INFO - Epoch(train) [20][100/925] lr: 1.5545e-04 eta: 5:56:36 time: 0.3690 data_time: 0.0021 memory: 5679 grad_norm: 924.4832 loss: 444.1333 loss_cls: 166.2022 loss_bbox: 131.7763 loss_dfl: 146.1547 +2024/01/19 14:15:21 - mmengine - INFO - Epoch(train) [20][150/925] lr: 1.5545e-04 eta: 5:56:20 time: 0.3967 data_time: 0.0024 memory: 5546 grad_norm: 1198.6396 loss: 446.3865 loss_cls: 166.8766 loss_bbox: 133.3134 loss_dfl: 146.1965 +2024/01/19 14:15:40 - mmengine - INFO - Epoch(train) [20][200/925] lr: 1.5545e-04 eta: 5:56:02 time: 0.3856 data_time: 0.0022 memory: 5439 grad_norm: 1128.0630 loss: 454.2358 loss_cls: 171.0684 loss_bbox: 135.2533 loss_dfl: 147.9141 +2024/01/19 14:15:59 - mmengine - INFO - Epoch(train) [20][250/925] lr: 1.5545e-04 eta: 5:55:43 time: 0.3815 data_time: 0.0023 memory: 5319 grad_norm: 1102.6111 loss: 446.7670 loss_cls: 168.5163 loss_bbox: 131.9439 loss_dfl: 146.3068 +2024/01/19 14:16:18 - mmengine - INFO - Epoch(train) [20][300/925] lr: 1.5545e-04 eta: 5:55:24 time: 0.3821 data_time: 0.0031 memory: 5799 grad_norm: 972.4246 loss: 443.5150 loss_cls: 166.1516 loss_bbox: 131.9040 loss_dfl: 145.4593 +2024/01/19 14:16:38 - mmengine - INFO - Epoch(train) [20][350/925] lr: 1.5545e-04 eta: 5:55:09 time: 0.4054 data_time: 0.0023 memory: 5746 grad_norm: 1000.2506 loss: 446.0782 loss_cls: 167.0839 loss_bbox: 133.3020 loss_dfl: 145.6922 +2024/01/19 14:16:57 - mmengine - INFO - Epoch(train) [20][400/925] lr: 1.5545e-04 eta: 5:54:48 time: 0.3642 data_time: 0.0023 memory: 5439 grad_norm: 1002.7173 loss: 450.0253 loss_cls: 170.3376 loss_bbox: 132.9953 loss_dfl: 146.6924 +2024/01/19 14:17:06 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:17:16 - mmengine - INFO - Epoch(train) [20][450/925] lr: 1.5545e-04 eta: 5:54:31 time: 0.3961 data_time: 0.0021 memory: 5599 grad_norm: 1012.1931 loss: 452.1924 loss_cls: 170.6678 loss_bbox: 133.5979 loss_dfl: 147.9266 +2024/01/19 14:17:35 - mmengine - INFO - Epoch(train) [20][500/925] lr: 1.5545e-04 eta: 5:54:12 time: 0.3795 data_time: 0.0021 memory: 5386 grad_norm: 1114.3278 loss: 445.0830 loss_cls: 167.1000 loss_bbox: 132.4366 loss_dfl: 145.5464 +2024/01/19 14:17:55 - mmengine - INFO - Epoch(train) [20][550/925] lr: 1.5545e-04 eta: 5:53:54 time: 0.3854 data_time: 0.0023 memory: 5359 grad_norm: 1041.8562 loss: 439.9211 loss_cls: 164.0613 loss_bbox: 131.4334 loss_dfl: 144.4264 +2024/01/19 14:18:14 - mmengine - INFO - Epoch(train) [20][600/925] lr: 1.5545e-04 eta: 5:53:35 time: 0.3798 data_time: 0.0024 memory: 5239 grad_norm: 999.2852 loss: 447.2196 loss_cls: 168.4766 loss_bbox: 132.7735 loss_dfl: 145.9695 +2024/01/19 14:18:33 - mmengine - INFO - Epoch(train) [20][650/925] lr: 1.5545e-04 eta: 5:53:18 time: 0.3933 data_time: 0.0024 memory: 5759 grad_norm: 1144.8233 loss: 448.5239 loss_cls: 168.8846 loss_bbox: 132.7502 loss_dfl: 146.8891 +2024/01/19 14:18:54 - mmengine - INFO - Epoch(train) [20][700/925] lr: 1.5545e-04 eta: 5:53:03 time: 0.4026 data_time: 0.0030 memory: 5399 grad_norm: 1094.7829 loss: 447.2670 loss_cls: 168.5455 loss_bbox: 132.5236 loss_dfl: 146.1979 +2024/01/19 14:19:12 - mmengine - INFO - Epoch(train) [20][750/925] lr: 1.5545e-04 eta: 5:52:43 time: 0.3741 data_time: 0.0021 memory: 5412 grad_norm: 1048.4872 loss: 442.7415 loss_cls: 165.6083 loss_bbox: 131.3070 loss_dfl: 145.8261 +2024/01/19 14:19:32 - mmengine - INFO - Epoch(train) [20][800/925] lr: 1.5545e-04 eta: 5:52:25 time: 0.3896 data_time: 0.0025 memory: 5559 grad_norm: 1003.2151 loss: 443.4551 loss_cls: 166.8241 loss_bbox: 131.0856 loss_dfl: 145.5455 +2024/01/19 14:19:51 - mmengine - INFO - Epoch(train) [20][850/925] lr: 1.5545e-04 eta: 5:52:07 time: 0.3859 data_time: 0.0020 memory: 5399 grad_norm: 1038.1633 loss: 446.5974 loss_cls: 166.9163 loss_bbox: 133.2420 loss_dfl: 146.4390 +2024/01/19 14:20:10 - mmengine - INFO - Epoch(train) [20][900/925] lr: 1.5545e-04 eta: 5:51:48 time: 0.3782 data_time: 0.0022 memory: 5199 grad_norm: 1156.7026 loss: 446.2598 loss_cls: 166.1715 loss_bbox: 133.8875 loss_dfl: 146.2008 +2024/01/19 14:20:19 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:20:20 - mmengine - INFO - Saving checkpoint at 20 epochs +2024/01/19 14:20:28 - mmengine - INFO - Epoch(val) [20][ 50/625] eta: 0:00:21 time: 0.0378 data_time: 0.0008 memory: 5506 +2024/01/19 14:20:30 - mmengine - INFO - Epoch(val) [20][100/625] eta: 0:00:19 time: 0.0360 data_time: 0.0004 memory: 843 +2024/01/19 14:20:32 - mmengine - INFO - Epoch(val) [20][150/625] eta: 0:00:17 time: 0.0353 data_time: 0.0003 memory: 843 +2024/01/19 14:20:34 - mmengine - INFO - Epoch(val) [20][200/625] eta: 0:00:15 time: 0.0350 data_time: 0.0003 memory: 843 +2024/01/19 14:20:35 - mmengine - INFO - Epoch(val) [20][250/625] eta: 0:00:13 time: 0.0368 data_time: 0.0019 memory: 843 +2024/01/19 14:20:37 - mmengine - INFO - Epoch(val) [20][300/625] eta: 0:00:11 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 14:20:39 - mmengine - INFO - Epoch(val) [20][350/625] eta: 0:00:09 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 14:20:41 - mmengine - INFO - Epoch(val) [20][400/625] eta: 0:00:08 time: 0.0361 data_time: 0.0004 memory: 843 +2024/01/19 14:20:42 - mmengine - INFO - Epoch(val) [20][450/625] eta: 0:00:06 time: 0.0306 data_time: 0.0003 memory: 843 +2024/01/19 14:20:44 - mmengine - INFO - Epoch(val) [20][500/625] eta: 0:00:04 time: 0.0258 data_time: 0.0002 memory: 843 +2024/01/19 14:20:45 - mmengine - INFO - Epoch(val) [20][550/625] eta: 0:00:02 time: 0.0259 data_time: 0.0002 memory: 843 +2024/01/19 14:20:46 - mmengine - INFO - Epoch(val) [20][600/625] eta: 0:00:00 time: 0.0259 data_time: 0.0002 memory: 843 +2024/01/19 14:21:01 - mmengine - INFO - Evaluating bbox... +2024/01/19 14:22:26 - mmengine - INFO - bbox_mAP_copypaste: 0.441 0.601 0.480 0.243 0.488 0.592 +2024/01/19 14:22:29 - mmengine - INFO - Epoch(val) [20][625/625] coco/bbox_mAP: 0.4410 coco/bbox_mAP_50: 0.6010 coco/bbox_mAP_75: 0.4800 coco/bbox_mAP_s: 0.2430 coco/bbox_mAP_m: 0.4880 coco/bbox_mAP_l: 0.5920 data_time: 0.0002 time: 0.0258 +2024/01/19 14:22:52 - mmengine - INFO - Epoch(train) [21][ 50/925] lr: 1.5297e-04 eta: 5:51:33 time: 0.4724 data_time: 0.1019 memory: 5786 grad_norm: 961.1192 loss: 441.6931 loss_cls: 165.5231 loss_bbox: 131.0813 loss_dfl: 145.0887 +2024/01/19 14:23:11 - mmengine - INFO - Epoch(train) [21][100/925] lr: 1.5297e-04 eta: 5:51:14 time: 0.3825 data_time: 0.0031 memory: 5346 grad_norm: 939.1675 loss: 443.8611 loss_cls: 166.4553 loss_bbox: 131.8014 loss_dfl: 145.6044 +2024/01/19 14:23:31 - mmengine - INFO - Epoch(train) [21][150/925] lr: 1.5297e-04 eta: 5:50:56 time: 0.3909 data_time: 0.0021 memory: 5626 grad_norm: 940.1892 loss: 439.6021 loss_cls: 162.8093 loss_bbox: 131.3884 loss_dfl: 145.4043 +2024/01/19 14:23:50 - mmengine - INFO - Epoch(train) [21][200/925] lr: 1.5297e-04 eta: 5:50:37 time: 0.3792 data_time: 0.0020 memory: 5559 grad_norm: 946.5082 loss: 442.0218 loss_cls: 165.2076 loss_bbox: 131.8181 loss_dfl: 144.9960 +2024/01/19 14:24:09 - mmengine - INFO - Epoch(train) [21][250/925] lr: 1.5297e-04 eta: 5:50:19 time: 0.3852 data_time: 0.0021 memory: 5519 grad_norm: 1066.5532 loss: 438.5965 loss_cls: 162.9010 loss_bbox: 131.3319 loss_dfl: 144.3636 +2024/01/19 14:24:28 - mmengine - INFO - Epoch(train) [21][300/925] lr: 1.5297e-04 eta: 5:50:00 time: 0.3829 data_time: 0.0023 memory: 5599 grad_norm: 925.6462 loss: 454.9740 loss_cls: 172.9089 loss_bbox: 134.4619 loss_dfl: 147.6032 +2024/01/19 14:24:48 - mmengine - INFO - Epoch(train) [21][350/925] lr: 1.5297e-04 eta: 5:49:42 time: 0.3857 data_time: 0.0021 memory: 5372 grad_norm: 978.8201 loss: 455.0249 loss_cls: 172.6413 loss_bbox: 135.3142 loss_dfl: 147.0695 +2024/01/19 14:25:07 - mmengine - INFO - Epoch(train) [21][400/925] lr: 1.5297e-04 eta: 5:49:23 time: 0.3812 data_time: 0.0025 memory: 5466 grad_norm: 900.5814 loss: 442.4606 loss_cls: 166.7557 loss_bbox: 130.6732 loss_dfl: 145.0317 +2024/01/19 14:25:27 - mmengine - INFO - Epoch(train) [21][450/925] lr: 1.5297e-04 eta: 5:49:06 time: 0.3937 data_time: 0.0023 memory: 5466 grad_norm: 1068.4675 loss: 449.4420 loss_cls: 167.1688 loss_bbox: 135.6462 loss_dfl: 146.6269 +2024/01/19 14:25:46 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:25:46 - mmengine - INFO - Epoch(train) [21][500/925] lr: 1.5297e-04 eta: 5:48:48 time: 0.3851 data_time: 0.0022 memory: 5586 grad_norm: 977.4265 loss: 439.5577 loss_cls: 163.9228 loss_bbox: 130.7025 loss_dfl: 144.9324 +2024/01/19 14:26:04 - mmengine - INFO - Epoch(train) [21][550/925] lr: 1.5297e-04 eta: 5:48:27 time: 0.3722 data_time: 0.0022 memory: 5492 grad_norm: 953.4341 loss: 446.6932 loss_cls: 167.2967 loss_bbox: 132.8573 loss_dfl: 146.5392 +2024/01/19 14:26:24 - mmengine - INFO - Epoch(train) [21][600/925] lr: 1.5297e-04 eta: 5:48:10 time: 0.3915 data_time: 0.0021 memory: 5586 grad_norm: 1053.6202 loss: 446.4575 loss_cls: 167.6403 loss_bbox: 132.4157 loss_dfl: 146.4015 +2024/01/19 14:26:44 - mmengine - INFO - Epoch(train) [21][650/925] lr: 1.5297e-04 eta: 5:47:54 time: 0.3992 data_time: 0.0022 memory: 5399 grad_norm: 1033.6477 loss: 451.2284 loss_cls: 170.0929 loss_bbox: 133.6663 loss_dfl: 147.4692 +2024/01/19 14:27:02 - mmengine - INFO - Epoch(train) [21][700/925] lr: 1.5297e-04 eta: 5:47:32 time: 0.3634 data_time: 0.0023 memory: 5199 grad_norm: 1034.1635 loss: 438.0970 loss_cls: 164.1921 loss_bbox: 128.9822 loss_dfl: 144.9227 +2024/01/19 14:27:21 - mmengine - INFO - Epoch(train) [21][750/925] lr: 1.5297e-04 eta: 5:47:13 time: 0.3826 data_time: 0.0025 memory: 5332 grad_norm: 958.0580 loss: 440.0941 loss_cls: 164.1105 loss_bbox: 131.3434 loss_dfl: 144.6402 +2024/01/19 14:27:41 - mmengine - INFO - Epoch(train) [21][800/925] lr: 1.5297e-04 eta: 5:46:56 time: 0.3946 data_time: 0.0032 memory: 5199 grad_norm: 1090.4529 loss: 444.8612 loss_cls: 166.7178 loss_bbox: 132.3686 loss_dfl: 145.7748 +2024/01/19 14:28:00 - mmengine - INFO - Epoch(train) [21][850/925] lr: 1.5297e-04 eta: 5:46:37 time: 0.3800 data_time: 0.0021 memory: 5879 grad_norm: 899.2331 loss: 438.1663 loss_cls: 163.3026 loss_bbox: 130.4045 loss_dfl: 144.4592 +2024/01/19 14:28:19 - mmengine - INFO - Epoch(train) [21][900/925] lr: 1.5297e-04 eta: 5:46:17 time: 0.3719 data_time: 0.0021 memory: 5266 grad_norm: 912.9257 loss: 437.9602 loss_cls: 162.6671 loss_bbox: 130.6462 loss_dfl: 144.6469 +2024/01/19 14:28:28 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:28:52 - mmengine - INFO - Epoch(train) [22][ 50/925] lr: 1.5050e-04 eta: 5:46:01 time: 0.4685 data_time: 0.0900 memory: 5386 grad_norm: 1080.8201 loss: 444.4227 loss_cls: 165.9590 loss_bbox: 132.5942 loss_dfl: 145.8695 +2024/01/19 14:29:11 - mmengine - INFO - Epoch(train) [22][100/925] lr: 1.5050e-04 eta: 5:45:41 time: 0.3752 data_time: 0.0023 memory: 5506 grad_norm: 1048.9223 loss: 448.6471 loss_cls: 167.6286 loss_bbox: 133.7293 loss_dfl: 147.2892 +2024/01/19 14:29:29 - mmengine - INFO - Epoch(train) [22][150/925] lr: 1.5050e-04 eta: 5:45:20 time: 0.3695 data_time: 0.0022 memory: 5132 grad_norm: 974.6589 loss: 435.6957 loss_cls: 162.4288 loss_bbox: 129.3630 loss_dfl: 143.9039 +2024/01/19 14:29:49 - mmengine - INFO - Epoch(train) [22][200/925] lr: 1.5050e-04 eta: 5:45:01 time: 0.3827 data_time: 0.0023 memory: 5559 grad_norm: 1027.0646 loss: 452.2829 loss_cls: 170.1122 loss_bbox: 135.2498 loss_dfl: 146.9209 +2024/01/19 14:30:08 - mmengine - INFO - Epoch(train) [22][250/925] lr: 1.5050e-04 eta: 5:44:43 time: 0.3842 data_time: 0.0029 memory: 5706 grad_norm: 960.6695 loss: 449.8532 loss_cls: 169.2575 loss_bbox: 134.1323 loss_dfl: 146.4634 +2024/01/19 14:30:27 - mmengine - INFO - Epoch(train) [22][300/925] lr: 1.5050e-04 eta: 5:44:23 time: 0.3779 data_time: 0.0021 memory: 5492 grad_norm: 991.3386 loss: 451.1834 loss_cls: 168.7149 loss_bbox: 135.1637 loss_dfl: 147.3047 +2024/01/19 14:30:45 - mmengine - INFO - Epoch(train) [22][350/925] lr: 1.5050e-04 eta: 5:44:03 time: 0.3730 data_time: 0.0023 memory: 5252 grad_norm: inf loss: 443.5015 loss_cls: 166.3534 loss_bbox: 131.4481 loss_dfl: 145.7000 +2024/01/19 14:31:04 - mmengine - INFO - Epoch(train) [22][400/925] lr: 1.5050e-04 eta: 5:43:44 time: 0.3818 data_time: 0.0027 memory: 5386 grad_norm: 1124.2670 loss: 437.4989 loss_cls: 162.0238 loss_bbox: 130.6158 loss_dfl: 144.8593 +2024/01/19 14:31:23 - mmengine - INFO - Epoch(train) [22][450/925] lr: 1.5050e-04 eta: 5:43:25 time: 0.3748 data_time: 0.0024 memory: 5492 grad_norm: 1024.0063 loss: 438.1233 loss_cls: 164.5872 loss_bbox: 128.6623 loss_dfl: 144.8738 +2024/01/19 14:31:41 - mmengine - INFO - Epoch(train) [22][500/925] lr: 1.5050e-04 eta: 5:43:02 time: 0.3531 data_time: 0.0022 memory: 5506 grad_norm: 1041.7728 loss: 445.7054 loss_cls: 166.0563 loss_bbox: 133.4892 loss_dfl: 146.1599 +2024/01/19 14:31:59 - mmengine - INFO - Epoch(train) [22][550/925] lr: 1.5050e-04 eta: 5:42:39 time: 0.3541 data_time: 0.0020 memory: 5319 grad_norm: 955.4161 loss: 441.8750 loss_cls: 165.5259 loss_bbox: 131.7778 loss_dfl: 144.5712 +2024/01/19 14:32:08 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:32:18 - mmengine - INFO - Epoch(train) [22][600/925] lr: 1.5050e-04 eta: 5:42:20 time: 0.3813 data_time: 0.0023 memory: 5506 grad_norm: 1007.2482 loss: 443.5644 loss_cls: 165.4694 loss_bbox: 132.8455 loss_dfl: 145.2494 +2024/01/19 14:32:36 - mmengine - INFO - Epoch(train) [22][650/925] lr: 1.5050e-04 eta: 5:41:58 time: 0.3588 data_time: 0.0021 memory: 5212 grad_norm: 1053.3192 loss: 443.9311 loss_cls: 165.8779 loss_bbox: 131.7398 loss_dfl: 146.3133 +2024/01/19 14:32:54 - mmengine - INFO - Epoch(train) [22][700/925] lr: 1.5050e-04 eta: 5:41:37 time: 0.3665 data_time: 0.0032 memory: 5519 grad_norm: 1074.5069 loss: 450.0293 loss_cls: 168.3505 loss_bbox: 134.4342 loss_dfl: 147.2446 +2024/01/19 14:33:13 - mmengine - INFO - Epoch(train) [22][750/925] lr: 1.5050e-04 eta: 5:41:20 time: 0.3889 data_time: 0.0023 memory: 5586 grad_norm: 1000.5547 loss: 444.5257 loss_cls: 167.4574 loss_bbox: 130.5671 loss_dfl: 146.5011 +2024/01/19 14:33:32 - mmengine - INFO - Epoch(train) [22][800/925] lr: 1.5050e-04 eta: 5:40:59 time: 0.3692 data_time: 0.0021 memory: 5146 grad_norm: 951.0685 loss: 443.3205 loss_cls: 166.3121 loss_bbox: 131.3112 loss_dfl: 145.6973 +2024/01/19 14:33:50 - mmengine - INFO - Epoch(train) [22][850/925] lr: 1.5050e-04 eta: 5:40:38 time: 0.3671 data_time: 0.0023 memory: 5532 grad_norm: 887.9774 loss: 449.3750 loss_cls: 170.1806 loss_bbox: 132.8694 loss_dfl: 146.3251 +2024/01/19 14:34:09 - mmengine - INFO - Epoch(train) [22][900/925] lr: 1.5050e-04 eta: 5:40:19 time: 0.3788 data_time: 0.0023 memory: 5639 grad_norm: 1042.9399 loss: 435.1813 loss_cls: 162.7248 loss_bbox: 128.8643 loss_dfl: 143.5922 +2024/01/19 14:34:18 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:34:42 - mmengine - INFO - Epoch(train) [23][ 50/925] lr: 1.4803e-04 eta: 5:39:59 time: 0.4596 data_time: 0.0768 memory: 5266 grad_norm: 951.2187 loss: 440.8143 loss_cls: 165.0209 loss_bbox: 129.9677 loss_dfl: 145.8257 +2024/01/19 14:35:01 - mmengine - INFO - Epoch(train) [23][100/925] lr: 1.4803e-04 eta: 5:39:40 time: 0.3787 data_time: 0.0022 memory: 5506 grad_norm: 985.0505 loss: 445.6733 loss_cls: 167.8066 loss_bbox: 131.9834 loss_dfl: 145.8833 +2024/01/19 14:35:19 - mmengine - INFO - Epoch(train) [23][150/925] lr: 1.4803e-04 eta: 5:39:19 time: 0.3667 data_time: 0.0023 memory: 5319 grad_norm: 975.7630 loss: 445.4901 loss_cls: 167.5551 loss_bbox: 132.0963 loss_dfl: 145.8386 +2024/01/19 14:35:37 - mmengine - INFO - Epoch(train) [23][200/925] lr: 1.4803e-04 eta: 5:38:59 time: 0.3705 data_time: 0.0031 memory: 5292 grad_norm: 969.5011 loss: 449.4859 loss_cls: 168.8645 loss_bbox: 133.7373 loss_dfl: 146.8841 +2024/01/19 14:35:56 - mmengine - INFO - Epoch(train) [23][250/925] lr: 1.4803e-04 eta: 5:38:38 time: 0.3674 data_time: 0.0023 memory: 5399 grad_norm: 998.6905 loss: 444.4891 loss_cls: 167.2795 loss_bbox: 131.5236 loss_dfl: 145.6859 +2024/01/19 14:36:14 - mmengine - INFO - Epoch(train) [23][300/925] lr: 1.4803e-04 eta: 5:38:16 time: 0.3582 data_time: 0.0022 memory: 5292 grad_norm: 1060.9848 loss: 446.5799 loss_cls: 167.4518 loss_bbox: 132.7445 loss_dfl: 146.3835 +2024/01/19 14:36:33 - mmengine - INFO - Epoch(train) [23][350/925] lr: 1.4803e-04 eta: 5:37:57 time: 0.3800 data_time: 0.0022 memory: 5292 grad_norm: 918.8517 loss: 448.6485 loss_cls: 167.7420 loss_bbox: 134.2343 loss_dfl: 146.6722 +2024/01/19 14:36:50 - mmengine - INFO - Epoch(train) [23][400/925] lr: 1.4803e-04 eta: 5:37:34 time: 0.3518 data_time: 0.0021 memory: 5399 grad_norm: 990.4249 loss: 446.6136 loss_cls: 166.9950 loss_bbox: 132.9325 loss_dfl: 146.6861 +2024/01/19 14:37:11 - mmengine - INFO - Epoch(train) [23][450/925] lr: 1.4803e-04 eta: 5:37:18 time: 0.4026 data_time: 0.0025 memory: 5892 grad_norm: 1033.2363 loss: 439.1088 loss_cls: 163.9298 loss_bbox: 130.6507 loss_dfl: 144.5283 +2024/01/19 14:37:30 - mmengine - INFO - Epoch(train) [23][500/925] lr: 1.4803e-04 eta: 5:37:01 time: 0.3937 data_time: 0.0021 memory: 5626 grad_norm: 1038.1648 loss: 447.2080 loss_cls: 166.2941 loss_bbox: 134.1410 loss_dfl: 146.7729 +2024/01/19 14:37:49 - mmengine - INFO - Epoch(train) [23][550/925] lr: 1.4803e-04 eta: 5:36:41 time: 0.3772 data_time: 0.0025 memory: 5652 grad_norm: 992.0595 loss: 440.9335 loss_cls: 163.7141 loss_bbox: 131.6641 loss_dfl: 145.5553 +2024/01/19 14:38:08 - mmengine - INFO - Epoch(train) [23][600/925] lr: 1.4803e-04 eta: 5:36:23 time: 0.3831 data_time: 0.0021 memory: 5559 grad_norm: 1107.8045 loss: 446.9795 loss_cls: 167.5049 loss_bbox: 133.1783 loss_dfl: 146.2963 +2024/01/19 14:38:27 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:38:27 - mmengine - INFO - Epoch(train) [23][650/925] lr: 1.4803e-04 eta: 5:36:03 time: 0.3744 data_time: 0.0024 memory: 5679 grad_norm: 877.0703 loss: 441.1765 loss_cls: 166.2799 loss_bbox: 130.2410 loss_dfl: 144.6555 +2024/01/19 14:38:46 - mmengine - INFO - Epoch(train) [23][700/925] lr: 1.4803e-04 eta: 5:35:43 time: 0.3762 data_time: 0.0021 memory: 5386 grad_norm: 1139.8430 loss: 444.9655 loss_cls: 164.6629 loss_bbox: 133.7923 loss_dfl: 146.5102 +2024/01/19 14:39:05 - mmengine - INFO - Epoch(train) [23][750/925] lr: 1.4803e-04 eta: 5:35:25 time: 0.3845 data_time: 0.0025 memory: 5439 grad_norm: 1015.8134 loss: 431.4998 loss_cls: 159.6499 loss_bbox: 128.2649 loss_dfl: 143.5850 +2024/01/19 14:39:24 - mmengine - INFO - Epoch(train) [23][800/925] lr: 1.4803e-04 eta: 5:35:06 time: 0.3853 data_time: 0.0022 memory: 5226 grad_norm: 1003.9677 loss: 443.9096 loss_cls: 167.4581 loss_bbox: 130.7509 loss_dfl: 145.7006 +2024/01/19 14:39:44 - mmengine - INFO - Epoch(train) [23][850/925] lr: 1.4803e-04 eta: 5:34:48 time: 0.3885 data_time: 0.0022 memory: 5466 grad_norm: 954.8342 loss: 444.0091 loss_cls: 166.4424 loss_bbox: 132.2182 loss_dfl: 145.3485 +2024/01/19 14:40:03 - mmengine - INFO - Epoch(train) [23][900/925] lr: 1.4803e-04 eta: 5:34:29 time: 0.3764 data_time: 0.0019 memory: 5346 grad_norm: 1060.0624 loss: 436.3841 loss_cls: 161.9622 loss_bbox: 130.0129 loss_dfl: 144.4090 +2024/01/19 14:40:12 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:40:38 - mmengine - INFO - Epoch(train) [24][ 50/925] lr: 1.4555e-04 eta: 5:34:15 time: 0.5150 data_time: 0.1578 memory: 5412 grad_norm: 1047.8292 loss: 440.0111 loss_cls: 163.6723 loss_bbox: 130.9259 loss_dfl: 145.4128 +2024/01/19 14:40:58 - mmengine - INFO - Epoch(train) [24][100/925] lr: 1.4555e-04 eta: 5:34:00 time: 0.4064 data_time: 0.0342 memory: 5212 grad_norm: 1023.3315 loss: 442.0270 loss_cls: 164.9863 loss_bbox: 131.5995 loss_dfl: 145.4411 +2024/01/19 14:41:17 - mmengine - INFO - Epoch(train) [24][150/925] lr: 1.4555e-04 eta: 5:33:39 time: 0.3691 data_time: 0.0057 memory: 5292 grad_norm: 1206.5361 loss: 444.5877 loss_cls: 165.2819 loss_bbox: 132.2508 loss_dfl: 147.0550 +2024/01/19 14:41:35 - mmengine - INFO - Epoch(train) [24][200/925] lr: 1.4555e-04 eta: 5:33:18 time: 0.3653 data_time: 0.0035 memory: 5612 grad_norm: 973.4270 loss: 442.4242 loss_cls: 165.1147 loss_bbox: 132.1138 loss_dfl: 145.1958 +2024/01/19 14:41:54 - mmengine - INFO - Epoch(train) [24][250/925] lr: 1.4555e-04 eta: 5:33:00 time: 0.3857 data_time: 0.0024 memory: 5452 grad_norm: 996.2298 loss: 440.3933 loss_cls: 164.0971 loss_bbox: 131.0908 loss_dfl: 145.2054 +2024/01/19 14:42:13 - mmengine - INFO - Epoch(train) [24][300/925] lr: 1.4555e-04 eta: 5:32:41 time: 0.3853 data_time: 0.0025 memory: 5279 grad_norm: 1025.4712 loss: 443.1746 loss_cls: 166.5327 loss_bbox: 131.0900 loss_dfl: 145.5519 +2024/01/19 14:42:32 - mmengine - INFO - Epoch(train) [24][350/925] lr: 1.4555e-04 eta: 5:32:22 time: 0.3761 data_time: 0.0024 memory: 5546 grad_norm: 1066.1573 loss: 442.3261 loss_cls: 165.6829 loss_bbox: 131.2825 loss_dfl: 145.3606 +2024/01/19 14:42:51 - mmengine - INFO - Epoch(train) [24][400/925] lr: 1.4555e-04 eta: 5:32:03 time: 0.3827 data_time: 0.0024 memory: 5386 grad_norm: 939.5275 loss: 443.8362 loss_cls: 166.7889 loss_bbox: 131.3064 loss_dfl: 145.7409 +2024/01/19 14:43:11 - mmengine - INFO - Epoch(train) [24][450/925] lr: 1.4555e-04 eta: 5:31:44 time: 0.3833 data_time: 0.0021 memory: 5452 grad_norm: 1030.1422 loss: 444.9514 loss_cls: 167.2032 loss_bbox: 132.0102 loss_dfl: 145.7380 +2024/01/19 14:43:31 - mmengine - INFO - Epoch(train) [24][500/925] lr: 1.4555e-04 eta: 5:31:28 time: 0.4025 data_time: 0.0023 memory: 5732 grad_norm: 926.9604 loss: 444.3864 loss_cls: 165.0463 loss_bbox: 133.4708 loss_dfl: 145.8694 +2024/01/19 14:43:50 - mmengine - INFO - Epoch(train) [24][550/925] lr: 1.4555e-04 eta: 5:31:08 time: 0.3785 data_time: 0.0027 memory: 5679 grad_norm: 980.7147 loss: 437.2651 loss_cls: 162.1973 loss_bbox: 130.0811 loss_dfl: 144.9867 +2024/01/19 14:44:08 - mmengine - INFO - Epoch(train) [24][600/925] lr: 1.4555e-04 eta: 5:30:47 time: 0.3650 data_time: 0.0028 memory: 5612 grad_norm: inf loss: 436.4782 loss_cls: 162.4603 loss_bbox: 129.9042 loss_dfl: 144.1137 +2024/01/19 14:44:27 - mmengine - INFO - Epoch(train) [24][650/925] lr: 1.4555e-04 eta: 5:30:28 time: 0.3759 data_time: 0.0023 memory: 5599 grad_norm: 1067.3331 loss: 441.2060 loss_cls: 165.5661 loss_bbox: 130.7576 loss_dfl: 144.8822 +2024/01/19 14:44:46 - mmengine - INFO - Epoch(train) [24][700/925] lr: 1.4555e-04 eta: 5:30:10 time: 0.3877 data_time: 0.0023 memory: 5439 grad_norm: 985.6957 loss: 443.4483 loss_cls: 164.6780 loss_bbox: 132.9677 loss_dfl: 145.8026 +2024/01/19 14:44:56 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:45:05 - mmengine - INFO - Epoch(train) [24][750/925] lr: 1.4555e-04 eta: 5:29:49 time: 0.3698 data_time: 0.0026 memory: 5732 grad_norm: 974.0560 loss: 436.1122 loss_cls: 162.8515 loss_bbox: 129.4634 loss_dfl: 143.7972 +2024/01/19 14:45:24 - mmengine - INFO - Epoch(train) [24][800/925] lr: 1.4555e-04 eta: 5:29:31 time: 0.3888 data_time: 0.0023 memory: 5186 grad_norm: 910.3463 loss: 434.1045 loss_cls: 160.8412 loss_bbox: 129.6577 loss_dfl: 143.6056 +2024/01/19 14:45:44 - mmengine - INFO - Epoch(train) [24][850/925] lr: 1.4555e-04 eta: 5:29:13 time: 0.3876 data_time: 0.0022 memory: 5106 grad_norm: 1034.8934 loss: 437.2535 loss_cls: 162.7603 loss_bbox: 130.3536 loss_dfl: 144.1396 +2024/01/19 14:46:03 - mmengine - INFO - Epoch(train) [24][900/925] lr: 1.4555e-04 eta: 5:28:54 time: 0.3818 data_time: 0.0024 memory: 5532 grad_norm: 1042.7370 loss: 435.2883 loss_cls: 161.5850 loss_bbox: 129.6911 loss_dfl: 144.0122 +2024/01/19 14:46:11 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:46:34 - mmengine - INFO - Epoch(train) [25][ 50/925] lr: 1.4307e-04 eta: 5:28:31 time: 0.4539 data_time: 0.0793 memory: 5359 grad_norm: 932.5932 loss: 431.7322 loss_cls: 161.0503 loss_bbox: 126.9758 loss_dfl: 143.7061 +2024/01/19 14:46:53 - mmengine - INFO - Epoch(train) [25][100/925] lr: 1.4307e-04 eta: 5:28:12 time: 0.3756 data_time: 0.0033 memory: 5186 grad_norm: 1017.5952 loss: 445.5885 loss_cls: 167.4954 loss_bbox: 132.1162 loss_dfl: 145.9769 +2024/01/19 14:47:12 - mmengine - INFO - Epoch(train) [25][150/925] lr: 1.4307e-04 eta: 5:27:51 time: 0.3705 data_time: 0.0022 memory: 5319 grad_norm: 1024.7513 loss: 445.8441 loss_cls: 166.4969 loss_bbox: 133.4646 loss_dfl: 145.8826 +2024/01/19 14:47:30 - mmengine - INFO - Epoch(train) [25][200/925] lr: 1.4307e-04 eta: 5:27:31 time: 0.3720 data_time: 0.0021 memory: 5239 grad_norm: 1070.7176 loss: 449.4996 loss_cls: 169.9916 loss_bbox: 132.5616 loss_dfl: 146.9465 +2024/01/19 14:47:49 - mmengine - INFO - Epoch(train) [25][250/925] lr: 1.4307e-04 eta: 5:27:12 time: 0.3768 data_time: 0.0028 memory: 5306 grad_norm: 1005.8427 loss: 440.6528 loss_cls: 164.6062 loss_bbox: 131.4189 loss_dfl: 144.6277 +2024/01/19 14:48:11 - mmengine - INFO - Epoch(train) [25][300/925] lr: 1.4307e-04 eta: 5:26:58 time: 0.4297 data_time: 0.0022 memory: 5626 grad_norm: 1046.5253 loss: 443.3756 loss_cls: 165.6119 loss_bbox: 132.3052 loss_dfl: 145.4586 +2024/01/19 14:48:30 - mmengine - INFO - Epoch(train) [25][350/925] lr: 1.4307e-04 eta: 5:26:40 time: 0.3881 data_time: 0.0024 memory: 5679 grad_norm: 988.8804 loss: 442.8788 loss_cls: 167.5128 loss_bbox: 130.8763 loss_dfl: 144.4897 +2024/01/19 14:48:49 - mmengine - INFO - Epoch(train) [25][400/925] lr: 1.4307e-04 eta: 5:26:21 time: 0.3796 data_time: 0.0022 memory: 5666 grad_norm: 1077.2647 loss: 436.8313 loss_cls: 161.5115 loss_bbox: 129.8390 loss_dfl: 145.4808 +2024/01/19 14:49:08 - mmengine - INFO - Epoch(train) [25][450/925] lr: 1.4307e-04 eta: 5:26:02 time: 0.3808 data_time: 0.0022 memory: 5559 grad_norm: 971.3740 loss: 440.5389 loss_cls: 163.5034 loss_bbox: 131.5992 loss_dfl: 145.4363 +2024/01/19 14:49:27 - mmengine - INFO - Epoch(train) [25][500/925] lr: 1.4307e-04 eta: 5:25:43 time: 0.3850 data_time: 0.0024 memory: 5346 grad_norm: 1002.6004 loss: 439.9816 loss_cls: 165.2101 loss_bbox: 130.1709 loss_dfl: 144.6007 +2024/01/19 14:49:46 - mmengine - INFO - Epoch(train) [25][550/925] lr: 1.4307e-04 eta: 5:25:23 time: 0.3711 data_time: 0.0025 memory: 5292 grad_norm: 916.3132 loss: 433.4073 loss_cls: 161.2965 loss_bbox: 128.5122 loss_dfl: 143.5985 +2024/01/19 14:50:05 - mmengine - INFO - Epoch(train) [25][600/925] lr: 1.4307e-04 eta: 5:25:04 time: 0.3762 data_time: 0.0023 memory: 5292 grad_norm: 1109.6721 loss: 445.0252 loss_cls: 164.7337 loss_bbox: 134.3454 loss_dfl: 145.9461 +2024/01/19 14:50:24 - mmengine - INFO - Epoch(train) [25][650/925] lr: 1.4307e-04 eta: 5:24:46 time: 0.3911 data_time: 0.0024 memory: 5572 grad_norm: 1233.5316 loss: 446.1359 loss_cls: 167.1195 loss_bbox: 132.6810 loss_dfl: 146.3354 +2024/01/19 14:50:43 - mmengine - INFO - Epoch(train) [25][700/925] lr: 1.4307e-04 eta: 5:24:26 time: 0.3764 data_time: 0.0032 memory: 5599 grad_norm: 976.7012 loss: 437.2598 loss_cls: 161.2722 loss_bbox: 130.4581 loss_dfl: 145.5295 +2024/01/19 14:51:02 - mmengine - INFO - Epoch(train) [25][750/925] lr: 1.4307e-04 eta: 5:24:07 time: 0.3774 data_time: 0.0023 memory: 5826 grad_norm: 883.3645 loss: 439.1840 loss_cls: 163.3814 loss_bbox: 131.2021 loss_dfl: 144.6006 +2024/01/19 14:51:21 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:51:21 - mmengine - INFO - Epoch(train) [25][800/925] lr: 1.4307e-04 eta: 5:23:48 time: 0.3809 data_time: 0.0019 memory: 5292 grad_norm: 1188.2382 loss: 445.2241 loss_cls: 166.0529 loss_bbox: 132.7263 loss_dfl: 146.4449 +2024/01/19 14:51:41 - mmengine - INFO - Epoch(train) [25][850/925] lr: 1.4307e-04 eta: 5:23:30 time: 0.3895 data_time: 0.0024 memory: 5772 grad_norm: 1158.5113 loss: 434.0489 loss_cls: 159.0416 loss_bbox: 131.1848 loss_dfl: 143.8225 +2024/01/19 14:51:59 - mmengine - INFO - Epoch(train) [25][900/925] lr: 1.4307e-04 eta: 5:23:09 time: 0.3689 data_time: 0.0024 memory: 5346 grad_norm: 912.5573 loss: 439.9826 loss_cls: 163.2230 loss_bbox: 131.5098 loss_dfl: 145.2498 +2024/01/19 14:52:08 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 14:52:08 - mmengine - INFO - Saving checkpoint at 25 epochs +2024/01/19 14:52:17 - mmengine - INFO - Epoch(val) [25][ 50/625] eta: 0:00:20 time: 0.0360 data_time: 0.0009 memory: 5212 +2024/01/19 14:52:19 - mmengine - INFO - Epoch(val) [25][100/625] eta: 0:00:19 time: 0.0374 data_time: 0.0003 memory: 843 +2024/01/19 14:52:21 - mmengine - INFO - Epoch(val) [25][150/625] eta: 0:00:17 time: 0.0362 data_time: 0.0003 memory: 843 +2024/01/19 14:52:23 - mmengine - INFO - Epoch(val) [25][200/625] eta: 0:00:15 time: 0.0371 data_time: 0.0004 memory: 843 +2024/01/19 14:52:25 - mmengine - INFO - Epoch(val) [25][250/625] eta: 0:00:13 time: 0.0379 data_time: 0.0003 memory: 843 +2024/01/19 14:52:26 - mmengine - INFO - Epoch(val) [25][300/625] eta: 0:00:11 time: 0.0353 data_time: 0.0004 memory: 843 +2024/01/19 14:52:28 - mmengine - INFO - Epoch(val) [25][350/625] eta: 0:00:09 time: 0.0338 data_time: 0.0003 memory: 843 +2024/01/19 14:52:30 - mmengine - INFO - Epoch(val) [25][400/625] eta: 0:00:08 time: 0.0359 data_time: 0.0004 memory: 843 +2024/01/19 14:52:31 - mmengine - INFO - Epoch(val) [25][450/625] eta: 0:00:06 time: 0.0278 data_time: 0.0002 memory: 843 +2024/01/19 14:52:33 - mmengine - INFO - Epoch(val) [25][500/625] eta: 0:00:04 time: 0.0257 data_time: 0.0002 memory: 843 +2024/01/19 14:52:34 - mmengine - INFO - Epoch(val) [25][550/625] eta: 0:00:02 time: 0.0260 data_time: 0.0002 memory: 843 +2024/01/19 14:52:35 - mmengine - INFO - Epoch(val) [25][600/625] eta: 0:00:00 time: 0.0258 data_time: 0.0002 memory: 843 +2024/01/19 14:52:51 - mmengine - INFO - Evaluating bbox... +2024/01/19 14:54:16 - mmengine - INFO - bbox_mAP_copypaste: 0.444 0.603 0.482 0.248 0.491 0.600 +2024/01/19 14:54:18 - mmengine - INFO - Epoch(val) [25][625/625] coco/bbox_mAP: 0.4440 coco/bbox_mAP_50: 0.6030 coco/bbox_mAP_75: 0.4820 coco/bbox_mAP_s: 0.2480 coco/bbox_mAP_m: 0.4910 coco/bbox_mAP_l: 0.6000 data_time: 0.0002 time: 0.0259 +2024/01/19 14:54:41 - mmengine - INFO - Epoch(train) [26][ 50/925] lr: 1.4060e-04 eta: 5:22:47 time: 0.4481 data_time: 0.0837 memory: 5706 grad_norm: 1054.8637 loss: 428.4528 loss_cls: 158.3494 loss_bbox: 127.4342 loss_dfl: 142.6692 +2024/01/19 14:54:59 - mmengine - INFO - Epoch(train) [26][100/925] lr: 1.4060e-04 eta: 5:22:25 time: 0.3584 data_time: 0.0022 memory: 5319 grad_norm: 907.2133 loss: 430.3865 loss_cls: 157.5231 loss_bbox: 129.8020 loss_dfl: 143.0614 +2024/01/19 14:55:17 - mmengine - INFO - Epoch(train) [26][150/925] lr: 1.4060e-04 eta: 5:22:04 time: 0.3629 data_time: 0.0022 memory: 5346 grad_norm: 962.3612 loss: 438.5620 loss_cls: 163.2130 loss_bbox: 130.1117 loss_dfl: 145.2372 +2024/01/19 14:55:36 - mmengine - INFO - Epoch(train) [26][200/925] lr: 1.4060e-04 eta: 5:21:44 time: 0.3743 data_time: 0.0025 memory: 5319 grad_norm: 1066.3314 loss: 444.4955 loss_cls: 165.2666 loss_bbox: 133.1756 loss_dfl: 146.0533 +2024/01/19 14:55:54 - mmengine - INFO - Epoch(train) [26][250/925] lr: 1.4060e-04 eta: 5:21:23 time: 0.3586 data_time: 0.0025 memory: 5559 grad_norm: 974.4705 loss: 435.1504 loss_cls: 161.1899 loss_bbox: 129.6251 loss_dfl: 144.3354 +2024/01/19 14:56:12 - mmengine - INFO - Epoch(train) [26][300/925] lr: 1.4060e-04 eta: 5:21:02 time: 0.3682 data_time: 0.0032 memory: 5386 grad_norm: 1049.2245 loss: 448.4635 loss_cls: 166.8884 loss_bbox: 134.1726 loss_dfl: 147.4025 +2024/01/19 14:56:30 - mmengine - INFO - Epoch(train) [26][350/925] lr: 1.4060e-04 eta: 5:20:42 time: 0.3678 data_time: 0.0023 memory: 5346 grad_norm: 991.6819 loss: 441.3251 loss_cls: 163.0375 loss_bbox: 132.5858 loss_dfl: 145.7018 +2024/01/19 14:56:49 - mmengine - INFO - Epoch(train) [26][400/925] lr: 1.4060e-04 eta: 5:20:22 time: 0.3742 data_time: 0.0031 memory: 5399 grad_norm: 997.1180 loss: 437.1995 loss_cls: 161.8349 loss_bbox: 130.6200 loss_dfl: 144.7446 +2024/01/19 14:57:09 - mmengine - INFO - Epoch(train) [26][450/925] lr: 1.4060e-04 eta: 5:20:04 time: 0.3876 data_time: 0.0023 memory: 5292 grad_norm: 1157.8590 loss: 433.5669 loss_cls: 160.2456 loss_bbox: 129.0096 loss_dfl: 144.3116 +2024/01/19 14:57:28 - mmengine - INFO - Epoch(train) [26][500/925] lr: 1.4060e-04 eta: 5:19:46 time: 0.3963 data_time: 0.0022 memory: 5319 grad_norm: 1048.0572 loss: 442.7846 loss_cls: 165.4500 loss_bbox: 131.4117 loss_dfl: 145.9229 +2024/01/19 14:57:48 - mmengine - INFO - Epoch(train) [26][550/925] lr: 1.4060e-04 eta: 5:19:28 time: 0.3852 data_time: 0.0022 memory: 5586 grad_norm: 1032.5821 loss: 437.1817 loss_cls: 163.5607 loss_bbox: 129.1727 loss_dfl: 144.4483 +2024/01/19 14:58:07 - mmengine - INFO - Epoch(train) [26][600/925] lr: 1.4060e-04 eta: 5:19:10 time: 0.3880 data_time: 0.0022 memory: 5452 grad_norm: 900.2637 loss: 442.4433 loss_cls: 165.2940 loss_bbox: 132.0842 loss_dfl: 145.0651 +2024/01/19 14:58:27 - mmengine - INFO - Epoch(train) [26][650/925] lr: 1.4060e-04 eta: 5:18:52 time: 0.3930 data_time: 0.0024 memory: 5359 grad_norm: 956.3264 loss: 445.5211 loss_cls: 166.4161 loss_bbox: 132.4206 loss_dfl: 146.6844 +2024/01/19 14:58:46 - mmengine - INFO - Epoch(train) [26][700/925] lr: 1.4060e-04 eta: 5:18:33 time: 0.3812 data_time: 0.0022 memory: 5506 grad_norm: 1056.1940 loss: 435.8985 loss_cls: 162.9653 loss_bbox: 128.5646 loss_dfl: 144.3686 +2024/01/19 14:59:05 - mmengine - INFO - Epoch(train) [26][750/925] lr: 1.4060e-04 eta: 5:18:14 time: 0.3809 data_time: 0.0023 memory: 5532 grad_norm: 983.2067 loss: 437.3611 loss_cls: 162.2977 loss_bbox: 130.8983 loss_dfl: 144.1651 +2024/01/19 14:59:24 - mmengine - INFO - Epoch(train) [26][800/925] lr: 1.4060e-04 eta: 5:17:55 time: 0.3859 data_time: 0.0032 memory: 5519 grad_norm: inf loss: 433.4115 loss_cls: 160.8967 loss_bbox: 128.7563 loss_dfl: 143.7585 +2024/01/19 14:59:44 - mmengine - INFO - Epoch(train) [26][850/925] lr: 1.4060e-04 eta: 5:17:37 time: 0.3907 data_time: 0.0023 memory: 5159 grad_norm: 966.2823 loss: 440.1799 loss_cls: 163.3455 loss_bbox: 131.7040 loss_dfl: 145.1304 +2024/01/19 14:59:54 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:00:03 - mmengine - INFO - Epoch(train) [26][900/925] lr: 1.4060e-04 eta: 5:17:19 time: 0.3849 data_time: 0.0025 memory: 5319 grad_norm: 930.9505 loss: 431.0239 loss_cls: 160.3080 loss_bbox: 127.7734 loss_dfl: 142.9425 +2024/01/19 15:00:12 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:00:36 - mmengine - INFO - Epoch(train) [27][ 50/925] lr: 1.3813e-04 eta: 5:16:57 time: 0.4605 data_time: 0.0814 memory: 5866 grad_norm: 941.0821 loss: 433.6262 loss_cls: 159.3196 loss_bbox: 129.9949 loss_dfl: 144.3116 +2024/01/19 15:00:55 - mmengine - INFO - Epoch(train) [27][100/925] lr: 1.3813e-04 eta: 5:16:38 time: 0.3831 data_time: 0.0022 memory: 5426 grad_norm: 1012.3814 loss: 439.2362 loss_cls: 162.8846 loss_bbox: 131.2612 loss_dfl: 145.0904 +2024/01/19 15:01:14 - mmengine - INFO - Epoch(train) [27][150/925] lr: 1.3813e-04 eta: 5:16:20 time: 0.3929 data_time: 0.0022 memory: 5226 grad_norm: 944.1075 loss: 428.0928 loss_cls: 157.2706 loss_bbox: 127.0881 loss_dfl: 143.7341 +2024/01/19 15:01:34 - mmengine - INFO - Epoch(train) [27][200/925] lr: 1.3813e-04 eta: 5:16:01 time: 0.3829 data_time: 0.0023 memory: 5186 grad_norm: 929.5591 loss: 446.5151 loss_cls: 167.8976 loss_bbox: 132.8607 loss_dfl: 145.7568 +2024/01/19 15:01:51 - mmengine - INFO - Epoch(train) [27][250/925] lr: 1.3813e-04 eta: 5:15:40 time: 0.3558 data_time: 0.0024 memory: 5666 grad_norm: 1149.6064 loss: 438.6461 loss_cls: 161.8549 loss_bbox: 131.3801 loss_dfl: 145.4112 +2024/01/19 15:02:11 - mmengine - INFO - Epoch(train) [27][300/925] lr: 1.3813e-04 eta: 5:15:22 time: 0.3974 data_time: 0.0025 memory: 5226 grad_norm: 1205.6163 loss: 438.3935 loss_cls: 160.8505 loss_bbox: 132.5490 loss_dfl: 144.9941 +2024/01/19 15:02:31 - mmengine - INFO - Epoch(train) [27][350/925] lr: 1.3813e-04 eta: 5:15:05 time: 0.3964 data_time: 0.0023 memory: 5626 grad_norm: 983.9542 loss: 435.0511 loss_cls: 160.2893 loss_bbox: 130.1709 loss_dfl: 144.5909 +2024/01/19 15:02:49 - mmengine - INFO - Epoch(train) [27][400/925] lr: 1.3813e-04 eta: 5:14:42 time: 0.3483 data_time: 0.0021 memory: 5266 grad_norm: 1028.2033 loss: 441.5056 loss_cls: 163.7766 loss_bbox: 131.7344 loss_dfl: 145.9945 +2024/01/19 15:03:07 - mmengine - INFO - Epoch(train) [27][450/925] lr: 1.3813e-04 eta: 5:14:21 time: 0.3617 data_time: 0.0031 memory: 5492 grad_norm: 1006.4963 loss: 436.2946 loss_cls: 161.1695 loss_bbox: 130.3457 loss_dfl: 144.7794 +2024/01/19 15:03:25 - mmengine - INFO - Epoch(train) [27][500/925] lr: 1.3813e-04 eta: 5:14:02 time: 0.3749 data_time: 0.0033 memory: 5612 grad_norm: 966.3027 loss: 435.7302 loss_cls: 161.2360 loss_bbox: 130.3974 loss_dfl: 144.0968 +2024/01/19 15:03:44 - mmengine - INFO - Epoch(train) [27][550/925] lr: 1.3813e-04 eta: 5:13:41 time: 0.3669 data_time: 0.0031 memory: 5386 grad_norm: 1033.8548 loss: 428.7742 loss_cls: 157.9535 loss_bbox: 127.7222 loss_dfl: 143.0985 +2024/01/19 15:04:01 - mmengine - INFO - Epoch(train) [27][600/925] lr: 1.3813e-04 eta: 5:13:19 time: 0.3487 data_time: 0.0024 memory: 5693 grad_norm: 1190.9543 loss: 439.9134 loss_cls: 162.8726 loss_bbox: 132.2547 loss_dfl: 144.7861 +2024/01/19 15:04:19 - mmengine - INFO - Epoch(train) [27][650/925] lr: 1.3813e-04 eta: 5:12:58 time: 0.3629 data_time: 0.0035 memory: 5292 grad_norm: 1052.2557 loss: 432.0836 loss_cls: 159.9598 loss_bbox: 127.4333 loss_dfl: 144.6905 +2024/01/19 15:04:39 - mmengine - INFO - Epoch(train) [27][700/925] lr: 1.3813e-04 eta: 5:12:40 time: 0.3903 data_time: 0.0031 memory: 5599 grad_norm: 993.3836 loss: 441.5652 loss_cls: 164.7793 loss_bbox: 131.9149 loss_dfl: 144.8709 +2024/01/19 15:04:56 - mmengine - INFO - Epoch(train) [27][750/925] lr: 1.3813e-04 eta: 5:12:17 time: 0.3428 data_time: 0.0022 memory: 5639 grad_norm: 932.8745 loss: 447.7573 loss_cls: 167.1693 loss_bbox: 133.9010 loss_dfl: 146.6870 +2024/01/19 15:05:14 - mmengine - INFO - Epoch(train) [27][800/925] lr: 1.3813e-04 eta: 5:11:57 time: 0.3670 data_time: 0.0024 memory: 5639 grad_norm: 1036.0892 loss: 440.6656 loss_cls: 163.8074 loss_bbox: 132.0027 loss_dfl: 144.8555 +2024/01/19 15:05:34 - mmengine - INFO - Epoch(train) [27][850/925] lr: 1.3813e-04 eta: 5:11:38 time: 0.3814 data_time: 0.0041 memory: 5439 grad_norm: 975.6687 loss: 432.1662 loss_cls: 160.0678 loss_bbox: 129.0865 loss_dfl: 143.0120 +2024/01/19 15:05:51 - mmengine - INFO - Epoch(train) [27][900/925] lr: 1.3813e-04 eta: 5:11:16 time: 0.3492 data_time: 0.0023 memory: 5292 grad_norm: 1132.8616 loss: 431.9558 loss_cls: 161.4039 loss_bbox: 126.9989 loss_dfl: 143.5530 +2024/01/19 15:06:00 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:06:14 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:06:24 - mmengine - INFO - Epoch(train) [28][ 50/925] lr: 1.3565e-04 eta: 5:10:55 time: 0.4792 data_time: 0.0839 memory: 5292 grad_norm: 932.1340 loss: 443.3638 loss_cls: 165.9882 loss_bbox: 131.3966 loss_dfl: 145.9790 +2024/01/19 15:06:44 - mmengine - INFO - Epoch(train) [28][100/925] lr: 1.3565e-04 eta: 5:10:38 time: 0.3975 data_time: 0.0024 memory: 5639 grad_norm: 1067.5492 loss: 441.0372 loss_cls: 163.6969 loss_bbox: 131.5446 loss_dfl: 145.7957 +2024/01/19 15:07:03 - mmengine - INFO - Epoch(train) [28][150/925] lr: 1.3565e-04 eta: 5:10:18 time: 0.3666 data_time: 0.0026 memory: 5279 grad_norm: 1264.3128 loss: 434.3187 loss_cls: 160.8584 loss_bbox: 128.9551 loss_dfl: 144.5053 +2024/01/19 15:07:21 - mmengine - INFO - Epoch(train) [28][200/925] lr: 1.3565e-04 eta: 5:09:57 time: 0.3621 data_time: 0.0024 memory: 5479 grad_norm: 1033.2208 loss: 438.1276 loss_cls: 160.9829 loss_bbox: 131.7257 loss_dfl: 145.4189 +2024/01/19 15:07:40 - mmengine - INFO - Epoch(train) [28][250/925] lr: 1.3565e-04 eta: 5:09:37 time: 0.3794 data_time: 0.0033 memory: 5426 grad_norm: 1059.4959 loss: 434.0779 loss_cls: 161.9811 loss_bbox: 128.7533 loss_dfl: 143.3435 +2024/01/19 15:07:59 - mmengine - INFO - Epoch(train) [28][300/925] lr: 1.3565e-04 eta: 5:09:19 time: 0.3898 data_time: 0.0024 memory: 5332 grad_norm: 974.3053 loss: 435.7747 loss_cls: 162.2901 loss_bbox: 129.2799 loss_dfl: 144.2047 +2024/01/19 15:08:18 - mmengine - INFO - Epoch(train) [28][350/925] lr: 1.3565e-04 eta: 5:08:59 time: 0.3685 data_time: 0.0022 memory: 5092 grad_norm: 929.0655 loss: 435.1079 loss_cls: 161.1130 loss_bbox: 129.6483 loss_dfl: 144.3465 +2024/01/19 15:08:36 - mmengine - INFO - Epoch(train) [28][400/925] lr: 1.3565e-04 eta: 5:08:39 time: 0.3756 data_time: 0.0023 memory: 5346 grad_norm: 976.7719 loss: 435.7503 loss_cls: 162.0348 loss_bbox: 129.5299 loss_dfl: 144.1856 +2024/01/19 15:08:56 - mmengine - INFO - Epoch(train) [28][450/925] lr: 1.3565e-04 eta: 5:08:22 time: 0.3991 data_time: 0.0022 memory: 5306 grad_norm: 1178.1980 loss: 434.8297 loss_cls: 159.8301 loss_bbox: 129.9452 loss_dfl: 145.0545 +2024/01/19 15:09:15 - mmengine - INFO - Epoch(train) [28][500/925] lr: 1.3565e-04 eta: 5:08:03 time: 0.3800 data_time: 0.0022 memory: 5386 grad_norm: 985.9418 loss: 439.7862 loss_cls: 162.7768 loss_bbox: 131.4170 loss_dfl: 145.5925 +2024/01/19 15:09:35 - mmengine - INFO - Epoch(train) [28][550/925] lr: 1.3565e-04 eta: 5:07:45 time: 0.3915 data_time: 0.0023 memory: 5546 grad_norm: 1038.3632 loss: 431.3051 loss_cls: 159.0456 loss_bbox: 128.5076 loss_dfl: 143.7520 +2024/01/19 15:09:55 - mmengine - INFO - Epoch(train) [28][600/925] lr: 1.3565e-04 eta: 5:07:27 time: 0.3915 data_time: 0.0026 memory: 5252 grad_norm: 982.0850 loss: 446.8368 loss_cls: 167.3509 loss_bbox: 132.7668 loss_dfl: 146.7190 +2024/01/19 15:10:14 - mmengine - INFO - Epoch(train) [28][650/925] lr: 1.3565e-04 eta: 5:07:08 time: 0.3846 data_time: 0.0023 memory: 5719 grad_norm: 953.7857 loss: 442.6688 loss_cls: 165.4358 loss_bbox: 131.1441 loss_dfl: 146.0889 +2024/01/19 15:10:33 - mmengine - INFO - Epoch(train) [28][700/925] lr: 1.3565e-04 eta: 5:06:49 time: 0.3815 data_time: 0.0023 memory: 6132 grad_norm: 971.4053 loss: 431.8198 loss_cls: 159.3411 loss_bbox: 129.2945 loss_dfl: 143.1842 +2024/01/19 15:10:53 - mmengine - INFO - Epoch(train) [28][750/925] lr: 1.3565e-04 eta: 5:06:31 time: 0.3917 data_time: 0.0024 memory: 5706 grad_norm: 947.4369 loss: 435.4742 loss_cls: 160.7758 loss_bbox: 130.5987 loss_dfl: 144.0996 +2024/01/19 15:11:12 - mmengine - INFO - Epoch(train) [28][800/925] lr: 1.3565e-04 eta: 5:06:12 time: 0.3776 data_time: 0.0023 memory: 5346 grad_norm: 944.3510 loss: 442.5910 loss_cls: 165.5296 loss_bbox: 131.5464 loss_dfl: 145.5151 +2024/01/19 15:11:30 - mmengine - INFO - Epoch(train) [28][850/925] lr: 1.3565e-04 eta: 5:05:51 time: 0.3663 data_time: 0.0030 memory: 5226 grad_norm: 1026.6265 loss: 442.8609 loss_cls: 163.8741 loss_bbox: 133.3172 loss_dfl: 145.6696 +2024/01/19 15:11:50 - mmengine - INFO - Epoch(train) [28][900/925] lr: 1.3565e-04 eta: 5:05:34 time: 0.3986 data_time: 0.0024 memory: 5386 grad_norm: 1099.6305 loss: 433.6926 loss_cls: 159.8201 loss_bbox: 129.9613 loss_dfl: 143.9113 +2024/01/19 15:11:59 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:12:24 - mmengine - INFO - Epoch(train) [29][ 50/925] lr: 1.3317e-04 eta: 5:05:15 time: 0.4826 data_time: 0.1100 memory: 5852 grad_norm: 909.6177 loss: 437.4135 loss_cls: 163.8135 loss_bbox: 129.4685 loss_dfl: 144.1315 +2024/01/19 15:12:43 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:12:43 - mmengine - INFO - Epoch(train) [29][100/925] lr: 1.3317e-04 eta: 5:04:55 time: 0.3750 data_time: 0.0026 memory: 5146 grad_norm: 967.7923 loss: 435.3743 loss_cls: 161.7239 loss_bbox: 129.2381 loss_dfl: 144.4123 +2024/01/19 15:13:02 - mmengine - INFO - Epoch(train) [29][150/925] lr: 1.3317e-04 eta: 5:04:37 time: 0.3902 data_time: 0.0025 memory: 5466 grad_norm: 1010.1745 loss: 444.0301 loss_cls: 165.0294 loss_bbox: 132.3798 loss_dfl: 146.6209 +2024/01/19 15:13:22 - mmengine - INFO - Epoch(train) [29][200/925] lr: 1.3317e-04 eta: 5:04:19 time: 0.3877 data_time: 0.0101 memory: 5559 grad_norm: 1004.2687 loss: 445.4007 loss_cls: 166.8726 loss_bbox: 132.6064 loss_dfl: 145.9217 +2024/01/19 15:13:41 - mmengine - INFO - Epoch(train) [29][250/925] lr: 1.3317e-04 eta: 5:04:00 time: 0.3890 data_time: 0.0155 memory: 5986 grad_norm: 1182.3950 loss: 438.0044 loss_cls: 163.7725 loss_bbox: 129.9032 loss_dfl: 144.3287 +2024/01/19 15:14:00 - mmengine - INFO - Epoch(train) [29][300/925] lr: 1.3317e-04 eta: 5:03:41 time: 0.3779 data_time: 0.0031 memory: 5599 grad_norm: 1087.0703 loss: 438.9540 loss_cls: 161.9117 loss_bbox: 131.9294 loss_dfl: 145.1129 +2024/01/19 15:14:20 - mmengine - INFO - Epoch(train) [29][350/925] lr: 1.3317e-04 eta: 5:03:24 time: 0.4023 data_time: 0.0039 memory: 5252 grad_norm: 999.3937 loss: 435.5202 loss_cls: 161.7318 loss_bbox: 129.5101 loss_dfl: 144.2782 +2024/01/19 15:14:39 - mmengine - INFO - Epoch(train) [29][400/925] lr: 1.3317e-04 eta: 5:03:04 time: 0.3693 data_time: 0.0025 memory: 5426 grad_norm: 1077.0523 loss: 438.2984 loss_cls: 164.8950 loss_bbox: 128.8330 loss_dfl: 144.5705 +2024/01/19 15:14:57 - mmengine - INFO - Epoch(train) [29][450/925] lr: 1.3317e-04 eta: 5:02:44 time: 0.3754 data_time: 0.0024 memory: 5226 grad_norm: 1047.5242 loss: 435.9494 loss_cls: 158.9887 loss_bbox: 131.7054 loss_dfl: 145.2554 +2024/01/19 15:15:17 - mmengine - INFO - Epoch(train) [29][500/925] lr: 1.3317e-04 eta: 5:02:26 time: 0.3897 data_time: 0.0034 memory: 5452 grad_norm: 1001.0113 loss: 445.6149 loss_cls: 165.7086 loss_bbox: 133.8189 loss_dfl: 146.0874 +2024/01/19 15:15:36 - mmengine - INFO - Epoch(train) [29][550/925] lr: 1.3317e-04 eta: 5:02:06 time: 0.3722 data_time: 0.0024 memory: 5546 grad_norm: 1005.6925 loss: 438.2112 loss_cls: 162.3292 loss_bbox: 130.2475 loss_dfl: 145.6345 +2024/01/19 15:15:54 - mmengine - INFO - Epoch(train) [29][600/925] lr: 1.3317e-04 eta: 5:01:46 time: 0.3741 data_time: 0.0025 memory: 5306 grad_norm: 994.1670 loss: 436.3125 loss_cls: 159.6596 loss_bbox: 131.6304 loss_dfl: 145.0226 +2024/01/19 15:16:14 - mmengine - INFO - Epoch(train) [29][650/925] lr: 1.3317e-04 eta: 5:01:28 time: 0.3876 data_time: 0.0025 memory: 5439 grad_norm: 974.9297 loss: 442.7338 loss_cls: 166.4440 loss_bbox: 130.5171 loss_dfl: 145.7728 +2024/01/19 15:16:33 - mmengine - INFO - Epoch(train) [29][700/925] lr: 1.3317e-04 eta: 5:01:08 time: 0.3789 data_time: 0.0027 memory: 5399 grad_norm: inf loss: 438.0323 loss_cls: 161.0472 loss_bbox: 132.5292 loss_dfl: 144.4559 +2024/01/19 15:16:52 - mmengine - INFO - Epoch(train) [29][750/925] lr: 1.3317e-04 eta: 5:00:49 time: 0.3773 data_time: 0.0029 memory: 5732 grad_norm: 952.2221 loss: 441.5893 loss_cls: 164.3824 loss_bbox: 131.8675 loss_dfl: 145.3393 +2024/01/19 15:17:10 - mmengine - INFO - Epoch(train) [29][800/925] lr: 1.3317e-04 eta: 5:00:29 time: 0.3696 data_time: 0.0024 memory: 5346 grad_norm: 1044.6109 loss: 435.0676 loss_cls: 161.4776 loss_bbox: 129.2358 loss_dfl: 144.3542 +2024/01/19 15:17:30 - mmengine - INFO - Epoch(train) [29][850/925] lr: 1.3317e-04 eta: 5:00:11 time: 0.3978 data_time: 0.0026 memory: 5252 grad_norm: 1070.2791 loss: 438.4136 loss_cls: 162.2783 loss_bbox: 130.5679 loss_dfl: 145.5674 +2024/01/19 15:17:48 - mmengine - INFO - Epoch(train) [29][900/925] lr: 1.3317e-04 eta: 4:59:51 time: 0.3665 data_time: 0.0023 memory: 5132 grad_norm: 1010.9508 loss: 430.6621 loss_cls: 159.8492 loss_bbox: 127.7884 loss_dfl: 143.0245 +2024/01/19 15:17:57 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:18:22 - mmengine - INFO - Epoch(train) [30][ 50/925] lr: 1.3070e-04 eta: 4:59:31 time: 0.4946 data_time: 0.1185 memory: 5412 grad_norm: 1050.0701 loss: 435.9727 loss_cls: 161.5134 loss_bbox: 130.2756 loss_dfl: 144.1837 +2024/01/19 15:18:42 - mmengine - INFO - Epoch(train) [30][100/925] lr: 1.3070e-04 eta: 4:59:13 time: 0.3961 data_time: 0.0029 memory: 5519 grad_norm: 894.5680 loss: 443.4633 loss_cls: 164.8976 loss_bbox: 132.8223 loss_dfl: 145.7434 +2024/01/19 15:19:01 - mmengine - INFO - Epoch(train) [30][150/925] lr: 1.3070e-04 eta: 4:58:54 time: 0.3885 data_time: 0.0024 memory: 5452 grad_norm: 1106.4492 loss: 435.3594 loss_cls: 161.4735 loss_bbox: 129.9408 loss_dfl: 143.9450 +2024/01/19 15:19:11 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:19:21 - mmengine - INFO - Epoch(train) [30][200/925] lr: 1.3070e-04 eta: 4:58:36 time: 0.3862 data_time: 0.0023 memory: 5399 grad_norm: 941.2966 loss: 434.1695 loss_cls: 161.2031 loss_bbox: 128.6102 loss_dfl: 144.3562 +2024/01/19 15:19:40 - mmengine - INFO - Epoch(train) [30][250/925] lr: 1.3070e-04 eta: 4:58:17 time: 0.3911 data_time: 0.0021 memory: 5559 grad_norm: 985.3605 loss: 436.6458 loss_cls: 161.4484 loss_bbox: 130.7053 loss_dfl: 144.4921 +2024/01/19 15:20:00 - mmengine - INFO - Epoch(train) [30][300/925] lr: 1.3070e-04 eta: 4:57:59 time: 0.3937 data_time: 0.0023 memory: 5239 grad_norm: 1026.9302 loss: 434.3731 loss_cls: 159.3808 loss_bbox: 130.2994 loss_dfl: 144.6929 +2024/01/19 15:20:19 - mmengine - INFO - Epoch(train) [30][350/925] lr: 1.3070e-04 eta: 4:57:40 time: 0.3795 data_time: 0.0022 memory: 5466 grad_norm: 1058.8290 loss: 436.4717 loss_cls: 161.7725 loss_bbox: 129.5998 loss_dfl: 145.0994 +2024/01/19 15:20:39 - mmengine - INFO - Epoch(train) [30][400/925] lr: 1.3070e-04 eta: 4:57:22 time: 0.3926 data_time: 0.0025 memory: 5292 grad_norm: 1061.6606 loss: 429.2400 loss_cls: 159.3313 loss_bbox: 126.8508 loss_dfl: 143.0580 +2024/01/19 15:20:57 - mmengine - INFO - Epoch(train) [30][450/925] lr: 1.3070e-04 eta: 4:57:02 time: 0.3691 data_time: 0.0024 memory: 5412 grad_norm: 917.6805 loss: 442.8234 loss_cls: 164.4813 loss_bbox: 132.4550 loss_dfl: 145.8872 +2024/01/19 15:21:17 - mmengine - INFO - Epoch(train) [30][500/925] lr: 1.3070e-04 eta: 4:56:44 time: 0.3896 data_time: 0.0029 memory: 5386 grad_norm: 1054.4437 loss: 436.2146 loss_cls: 159.9035 loss_bbox: 131.0124 loss_dfl: 145.2987 +2024/01/19 15:21:36 - mmengine - INFO - Epoch(train) [30][550/925] lr: 1.3070e-04 eta: 4:56:24 time: 0.3805 data_time: 0.0024 memory: 5172 grad_norm: 915.0155 loss: 432.3607 loss_cls: 160.3624 loss_bbox: 127.9893 loss_dfl: 144.0090 +2024/01/19 15:21:55 - mmengine - INFO - Epoch(train) [30][600/925] lr: 1.3070e-04 eta: 4:56:06 time: 0.3838 data_time: 0.0023 memory: 5319 grad_norm: 919.0880 loss: 433.7153 loss_cls: 160.5160 loss_bbox: 129.4033 loss_dfl: 143.7960 +2024/01/19 15:22:14 - mmengine - INFO - Epoch(train) [30][650/925] lr: 1.3070e-04 eta: 4:55:46 time: 0.3789 data_time: 0.0022 memory: 5279 grad_norm: 979.5320 loss: 441.4928 loss_cls: 164.0298 loss_bbox: 131.8683 loss_dfl: 145.5946 +2024/01/19 15:22:34 - mmengine - INFO - Epoch(train) [30][700/925] lr: 1.3070e-04 eta: 4:55:29 time: 0.3997 data_time: 0.0022 memory: 5306 grad_norm: 1008.3899 loss: 435.4120 loss_cls: 159.3364 loss_bbox: 131.0395 loss_dfl: 145.0360 +2024/01/19 15:22:53 - mmengine - INFO - Epoch(train) [30][750/925] lr: 1.3070e-04 eta: 4:55:10 time: 0.3827 data_time: 0.0021 memory: 5266 grad_norm: 1044.6350 loss: 435.1617 loss_cls: 160.8752 loss_bbox: 129.3649 loss_dfl: 144.9215 +2024/01/19 15:23:12 - mmengine - INFO - Epoch(train) [30][800/925] lr: 1.3070e-04 eta: 4:54:50 time: 0.3764 data_time: 0.0024 memory: 5279 grad_norm: 1040.1342 loss: 434.3583 loss_cls: 160.0956 loss_bbox: 129.9208 loss_dfl: 144.3420 +2024/01/19 15:23:31 - mmengine - INFO - Epoch(train) [30][850/925] lr: 1.3070e-04 eta: 4:54:32 time: 0.3926 data_time: 0.0024 memory: 5492 grad_norm: 1018.5644 loss: 444.3458 loss_cls: 163.9240 loss_bbox: 134.1915 loss_dfl: 146.2303 +2024/01/19 15:23:51 - mmengine - INFO - Epoch(train) [30][900/925] lr: 1.3070e-04 eta: 4:54:14 time: 0.3916 data_time: 0.0024 memory: 5412 grad_norm: 1030.5552 loss: 439.1552 loss_cls: 162.0907 loss_bbox: 131.4433 loss_dfl: 145.6212 +2024/01/19 15:24:00 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:24:00 - mmengine - INFO - Saving checkpoint at 30 epochs +2024/01/19 15:24:09 - mmengine - INFO - Epoch(val) [30][ 50/625] eta: 0:00:21 time: 0.0372 data_time: 0.0009 memory: 5306 +2024/01/19 15:24:11 - mmengine - INFO - Epoch(val) [30][100/625] eta: 0:00:19 time: 0.0366 data_time: 0.0003 memory: 843 +2024/01/19 15:24:12 - mmengine - INFO - Epoch(val) [30][150/625] eta: 0:00:17 time: 0.0346 data_time: 0.0004 memory: 843 +2024/01/19 15:24:14 - mmengine - INFO - Epoch(val) [30][200/625] eta: 0:00:15 time: 0.0343 data_time: 0.0003 memory: 843 +2024/01/19 15:24:16 - mmengine - INFO - Epoch(val) [30][250/625] eta: 0:00:13 time: 0.0348 data_time: 0.0004 memory: 843 +2024/01/19 15:24:18 - mmengine - INFO - Epoch(val) [30][300/625] eta: 0:00:11 time: 0.0355 data_time: 0.0003 memory: 843 +2024/01/19 15:24:19 - mmengine - INFO - Epoch(val) [30][350/625] eta: 0:00:09 time: 0.0353 data_time: 0.0004 memory: 843 +2024/01/19 15:24:21 - mmengine - INFO - Epoch(val) [30][400/625] eta: 0:00:07 time: 0.0356 data_time: 0.0003 memory: 843 +2024/01/19 15:24:23 - mmengine - INFO - Epoch(val) [30][450/625] eta: 0:00:06 time: 0.0285 data_time: 0.0002 memory: 843 +2024/01/19 15:24:24 - mmengine - INFO - Epoch(val) [30][500/625] eta: 0:00:04 time: 0.0260 data_time: 0.0002 memory: 843 +2024/01/19 15:24:25 - mmengine - INFO - Epoch(val) [30][550/625] eta: 0:00:02 time: 0.0300 data_time: 0.0002 memory: 843 +2024/01/19 15:24:27 - mmengine - INFO - Epoch(val) [30][600/625] eta: 0:00:00 time: 0.0308 data_time: 0.0002 memory: 843 +2024/01/19 15:24:42 - mmengine - INFO - Evaluating bbox... +2024/01/19 15:26:06 - mmengine - INFO - bbox_mAP_copypaste: 0.446 0.605 0.485 0.251 0.494 0.603 +2024/01/19 15:26:09 - mmengine - INFO - Epoch(val) [30][625/625] coco/bbox_mAP: 0.4460 coco/bbox_mAP_50: 0.6050 coco/bbox_mAP_75: 0.4850 coco/bbox_mAP_s: 0.2510 coco/bbox_mAP_m: 0.4940 coco/bbox_mAP_l: 0.6030 data_time: 0.0002 time: 0.0307 +2024/01/19 15:26:31 - mmengine - INFO - Epoch(train) [31][ 50/925] lr: 1.2822e-04 eta: 4:53:48 time: 0.4368 data_time: 0.0810 memory: 5506 grad_norm: 922.9911 loss: 432.9629 loss_cls: 160.3375 loss_bbox: 129.0953 loss_dfl: 143.5301 +2024/01/19 15:26:50 - mmengine - INFO - Epoch(train) [31][100/925] lr: 1.2822e-04 eta: 4:53:29 time: 0.3811 data_time: 0.0022 memory: 5439 grad_norm: 880.5435 loss: 443.4615 loss_cls: 164.7696 loss_bbox: 133.1033 loss_dfl: 145.5886 +2024/01/19 15:27:09 - mmengine - INFO - Epoch(train) [31][150/925] lr: 1.2822e-04 eta: 4:53:10 time: 0.3804 data_time: 0.0036 memory: 5212 grad_norm: 977.6259 loss: 434.7164 loss_cls: 160.0913 loss_bbox: 130.4364 loss_dfl: 144.1887 +2024/01/19 15:27:27 - mmengine - INFO - Epoch(train) [31][200/925] lr: 1.2822e-04 eta: 4:52:49 time: 0.3639 data_time: 0.0024 memory: 5319 grad_norm: inf loss: 438.5906 loss_cls: 162.2485 loss_bbox: 131.6177 loss_dfl: 144.7244 +2024/01/19 15:27:45 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:27:45 - mmengine - INFO - Epoch(train) [31][250/925] lr: 1.2822e-04 eta: 4:52:29 time: 0.3637 data_time: 0.0022 memory: 5332 grad_norm: 974.2695 loss: 439.1715 loss_cls: 163.3185 loss_bbox: 130.6151 loss_dfl: 145.2380 +2024/01/19 15:28:04 - mmengine - INFO - Epoch(train) [31][300/925] lr: 1.2822e-04 eta: 4:52:10 time: 0.3809 data_time: 0.0023 memory: 5252 grad_norm: 1011.7168 loss: 437.7800 loss_cls: 162.8912 loss_bbox: 130.2916 loss_dfl: 144.5973 +2024/01/19 15:28:24 - mmengine - INFO - Epoch(train) [31][350/925] lr: 1.2822e-04 eta: 4:51:52 time: 0.3958 data_time: 0.0024 memory: 6092 grad_norm: 929.3095 loss: 437.4489 loss_cls: 161.7244 loss_bbox: 130.7847 loss_dfl: 144.9398 +2024/01/19 15:28:43 - mmengine - INFO - Epoch(train) [31][400/925] lr: 1.2822e-04 eta: 4:51:32 time: 0.3711 data_time: 0.0022 memory: 5666 grad_norm: 919.1072 loss: 441.4631 loss_cls: 164.7995 loss_bbox: 131.4091 loss_dfl: 145.2546 +2024/01/19 15:29:02 - mmengine - INFO - Epoch(train) [31][450/925] lr: 1.2822e-04 eta: 4:51:13 time: 0.3770 data_time: 0.0023 memory: 5226 grad_norm: 977.9559 loss: 440.1355 loss_cls: 164.1594 loss_bbox: 131.4590 loss_dfl: 144.5171 +2024/01/19 15:29:21 - mmengine - INFO - Epoch(train) [31][500/925] lr: 1.2822e-04 eta: 4:50:53 time: 0.3772 data_time: 0.0024 memory: 5386 grad_norm: 1018.0650 loss: 435.6282 loss_cls: 161.1857 loss_bbox: 129.8557 loss_dfl: 144.5868 +2024/01/19 15:29:40 - mmengine - INFO - Epoch(train) [31][550/925] lr: 1.2822e-04 eta: 4:50:34 time: 0.3802 data_time: 0.0021 memory: 5599 grad_norm: 1093.6493 loss: 435.9473 loss_cls: 160.5049 loss_bbox: 130.9407 loss_dfl: 144.5017 +2024/01/19 15:29:58 - mmengine - INFO - Epoch(train) [31][600/925] lr: 1.2822e-04 eta: 4:50:14 time: 0.3714 data_time: 0.0023 memory: 5532 grad_norm: 1127.6712 loss: 440.4687 loss_cls: 163.5454 loss_bbox: 131.5304 loss_dfl: 145.3929 +2024/01/19 15:30:17 - mmengine - INFO - Epoch(train) [31][650/925] lr: 1.2822e-04 eta: 4:49:54 time: 0.3748 data_time: 0.0024 memory: 5186 grad_norm: 1100.3930 loss: 440.3353 loss_cls: 163.1910 loss_bbox: 131.9184 loss_dfl: 145.2259 +2024/01/19 15:30:36 - mmengine - INFO - Epoch(train) [31][700/925] lr: 1.2822e-04 eta: 4:49:35 time: 0.3739 data_time: 0.0023 memory: 5452 grad_norm: 1091.3315 loss: 428.0478 loss_cls: 156.1848 loss_bbox: 129.1139 loss_dfl: 142.7490 +2024/01/19 15:30:55 - mmengine - INFO - Epoch(train) [31][750/925] lr: 1.2822e-04 eta: 4:49:15 time: 0.3778 data_time: 0.0022 memory: 5479 grad_norm: 971.0651 loss: 430.0562 loss_cls: 158.7240 loss_bbox: 128.2692 loss_dfl: 143.0630 +2024/01/19 15:31:13 - mmengine - INFO - Epoch(train) [31][800/925] lr: 1.2822e-04 eta: 4:48:55 time: 0.3705 data_time: 0.0030 memory: 5412 grad_norm: 1179.9255 loss: 437.1676 loss_cls: 164.5580 loss_bbox: 128.2807 loss_dfl: 144.3289 +2024/01/19 15:31:32 - mmengine - INFO - Epoch(train) [31][850/925] lr: 1.2822e-04 eta: 4:48:36 time: 0.3739 data_time: 0.0023 memory: 5532 grad_norm: 1001.5322 loss: 425.4807 loss_cls: 154.7037 loss_bbox: 127.4761 loss_dfl: 143.3009 +2024/01/19 15:31:50 - mmengine - INFO - Epoch(train) [31][900/925] lr: 1.2822e-04 eta: 4:48:16 time: 0.3702 data_time: 0.0023 memory: 5332 grad_norm: 1003.5999 loss: 426.5871 loss_cls: 155.5885 loss_bbox: 127.7706 loss_dfl: 143.2281 +2024/01/19 15:32:00 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:32:24 - mmengine - INFO - Epoch(train) [32][ 50/925] lr: 1.2575e-04 eta: 4:47:54 time: 0.4653 data_time: 0.0813 memory: 5359 grad_norm: 970.8511 loss: 426.3542 loss_cls: 155.6016 loss_bbox: 127.3614 loss_dfl: 143.3912 +2024/01/19 15:32:42 - mmengine - INFO - Epoch(train) [32][100/925] lr: 1.2575e-04 eta: 4:47:34 time: 0.3700 data_time: 0.0022 memory: 5386 grad_norm: 1142.4158 loss: 435.5065 loss_cls: 162.8724 loss_bbox: 128.7975 loss_dfl: 143.8366 +2024/01/19 15:33:02 - mmengine - INFO - Epoch(train) [32][150/925] lr: 1.2575e-04 eta: 4:47:16 time: 0.3952 data_time: 0.0023 memory: 5812 grad_norm: 952.7442 loss: 436.0161 loss_cls: 161.0394 loss_bbox: 130.5027 loss_dfl: 144.4740 +2024/01/19 15:33:22 - mmengine - INFO - Epoch(train) [32][200/925] lr: 1.2575e-04 eta: 4:46:58 time: 0.3919 data_time: 0.0022 memory: 5546 grad_norm: 992.3461 loss: 425.4546 loss_cls: 155.5808 loss_bbox: 127.2700 loss_dfl: 142.6037 +2024/01/19 15:33:41 - mmengine - INFO - Epoch(train) [32][250/925] lr: 1.2575e-04 eta: 4:46:39 time: 0.3876 data_time: 0.0023 memory: 5412 grad_norm: 1107.5492 loss: 430.6773 loss_cls: 158.4257 loss_bbox: 129.1607 loss_dfl: 143.0909 +2024/01/19 15:33:59 - mmengine - INFO - Epoch(train) [32][300/925] lr: 1.2575e-04 eta: 4:46:19 time: 0.3659 data_time: 0.0033 memory: 5572 grad_norm: 1005.7017 loss: 435.9257 loss_cls: 162.1826 loss_bbox: 129.7515 loss_dfl: 143.9915 +2024/01/19 15:34:09 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:34:18 - mmengine - INFO - Epoch(train) [32][350/925] lr: 1.2575e-04 eta: 4:46:00 time: 0.3790 data_time: 0.0023 memory: 5612 grad_norm: 980.2857 loss: 434.5434 loss_cls: 161.0643 loss_bbox: 129.4530 loss_dfl: 144.0261 +2024/01/19 15:34:38 - mmengine - INFO - Epoch(train) [32][400/925] lr: 1.2575e-04 eta: 4:45:41 time: 0.3864 data_time: 0.0022 memory: 5479 grad_norm: 972.2806 loss: 438.1801 loss_cls: 162.9960 loss_bbox: 130.2171 loss_dfl: 144.9671 +2024/01/19 15:34:56 - mmengine - INFO - Epoch(train) [32][450/925] lr: 1.2575e-04 eta: 4:45:21 time: 0.3720 data_time: 0.0023 memory: 5372 grad_norm: 1016.2126 loss: 440.0016 loss_cls: 162.4765 loss_bbox: 132.5508 loss_dfl: 144.9743 +2024/01/19 15:35:16 - mmengine - INFO - Epoch(train) [32][500/925] lr: 1.2575e-04 eta: 4:45:02 time: 0.3855 data_time: 0.0024 memory: 5519 grad_norm: 1181.9733 loss: 428.4632 loss_cls: 156.8668 loss_bbox: 128.2103 loss_dfl: 143.3861 +2024/01/19 15:35:35 - mmengine - INFO - Epoch(train) [32][550/925] lr: 1.2575e-04 eta: 4:44:44 time: 0.3871 data_time: 0.0033 memory: 5466 grad_norm: 895.7778 loss: 436.1219 loss_cls: 161.0779 loss_bbox: 130.2394 loss_dfl: 144.8046 +2024/01/19 15:35:55 - mmengine - INFO - Epoch(train) [32][600/925] lr: 1.2575e-04 eta: 4:44:26 time: 0.3971 data_time: 0.0024 memory: 5292 grad_norm: 1228.0977 loss: 437.9224 loss_cls: 162.5962 loss_bbox: 130.4462 loss_dfl: 144.8801 +2024/01/19 15:36:14 - mmengine - INFO - Epoch(train) [32][650/925] lr: 1.2575e-04 eta: 4:44:07 time: 0.3836 data_time: 0.0023 memory: 5306 grad_norm: 993.0856 loss: 437.8619 loss_cls: 162.9823 loss_bbox: 130.1383 loss_dfl: 144.7413 +2024/01/19 15:36:33 - mmengine - INFO - Epoch(train) [32][700/925] lr: 1.2575e-04 eta: 4:43:47 time: 0.3698 data_time: 0.0023 memory: 5693 grad_norm: 971.7193 loss: 429.3435 loss_cls: 157.5313 loss_bbox: 129.2262 loss_dfl: 142.5859 +2024/01/19 15:36:53 - mmengine - INFO - Epoch(train) [32][750/925] lr: 1.2575e-04 eta: 4:43:29 time: 0.4031 data_time: 0.0023 memory: 5452 grad_norm: 1051.5003 loss: 438.8474 loss_cls: 162.0125 loss_bbox: 131.5948 loss_dfl: 145.2401 +2024/01/19 15:37:12 - mmengine - INFO - Epoch(train) [32][800/925] lr: 1.2575e-04 eta: 4:43:11 time: 0.3903 data_time: 0.0022 memory: 5239 grad_norm: 971.7545 loss: 438.8927 loss_cls: 162.8253 loss_bbox: 130.8844 loss_dfl: 145.1830 +2024/01/19 15:37:31 - mmengine - INFO - Epoch(train) [32][850/925] lr: 1.2575e-04 eta: 4:42:52 time: 0.3819 data_time: 0.0022 memory: 5879 grad_norm: 1028.5563 loss: 430.4684 loss_cls: 157.8385 loss_bbox: 129.3175 loss_dfl: 143.3124 +2024/01/19 15:37:51 - mmengine - INFO - Epoch(train) [32][900/925] lr: 1.2575e-04 eta: 4:42:34 time: 0.3949 data_time: 0.0023 memory: 5426 grad_norm: 894.7315 loss: 430.2050 loss_cls: 157.4194 loss_bbox: 129.4083 loss_dfl: 143.3773 +2024/01/19 15:38:01 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:38:24 - mmengine - INFO - Epoch(train) [33][ 50/925] lr: 1.2328e-04 eta: 4:42:11 time: 0.4608 data_time: 0.0775 memory: 5332 grad_norm: 1013.3427 loss: 432.3107 loss_cls: 160.4043 loss_bbox: 127.7273 loss_dfl: 144.1792 +2024/01/19 15:38:43 - mmengine - INFO - Epoch(train) [33][100/925] lr: 1.2328e-04 eta: 4:41:51 time: 0.3766 data_time: 0.0025 memory: 5279 grad_norm: 956.2325 loss: 424.5200 loss_cls: 154.9068 loss_bbox: 127.1368 loss_dfl: 142.4764 +2024/01/19 15:39:02 - mmengine - INFO - Epoch(train) [33][150/925] lr: 1.2328e-04 eta: 4:41:33 time: 0.3848 data_time: 0.0032 memory: 5546 grad_norm: 950.9589 loss: 442.0782 loss_cls: 164.2626 loss_bbox: 132.2076 loss_dfl: 145.6080 +2024/01/19 15:39:22 - mmengine - INFO - Epoch(train) [33][200/925] lr: 1.2328e-04 eta: 4:41:15 time: 0.3970 data_time: 0.0022 memory: 5693 grad_norm: 1117.8284 loss: 429.8418 loss_cls: 158.7872 loss_bbox: 127.7015 loss_dfl: 143.3532 +2024/01/19 15:39:41 - mmengine - INFO - Epoch(train) [33][250/925] lr: 1.2328e-04 eta: 4:40:56 time: 0.3862 data_time: 0.0021 memory: 5639 grad_norm: 989.1577 loss: 431.4452 loss_cls: 159.5572 loss_bbox: 128.4673 loss_dfl: 143.4208 +2024/01/19 15:40:01 - mmengine - INFO - Epoch(train) [33][300/925] lr: 1.2328e-04 eta: 4:40:37 time: 0.3845 data_time: 0.0023 memory: 5759 grad_norm: 1058.6077 loss: 431.5563 loss_cls: 156.6339 loss_bbox: 130.6256 loss_dfl: 144.2968 +2024/01/19 15:40:20 - mmengine - INFO - Epoch(train) [33][350/925] lr: 1.2328e-04 eta: 4:40:18 time: 0.3814 data_time: 0.0023 memory: 5706 grad_norm: 1011.6674 loss: 430.0268 loss_cls: 155.3213 loss_bbox: 131.0099 loss_dfl: 143.6955 +2024/01/19 15:40:39 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:40:39 - mmengine - INFO - Epoch(train) [33][400/925] lr: 1.2328e-04 eta: 4:39:59 time: 0.3820 data_time: 0.0022 memory: 5439 grad_norm: 1112.3560 loss: 432.9252 loss_cls: 158.7140 loss_bbox: 129.4169 loss_dfl: 144.7944 +2024/01/19 15:40:58 - mmengine - INFO - Epoch(train) [33][450/925] lr: 1.2328e-04 eta: 4:39:39 time: 0.3768 data_time: 0.0021 memory: 5306 grad_norm: 900.7974 loss: 431.6281 loss_cls: 159.1686 loss_bbox: 128.6645 loss_dfl: 143.7950 +2024/01/19 15:41:16 - mmengine - INFO - Epoch(train) [33][500/925] lr: 1.2328e-04 eta: 4:39:18 time: 0.3582 data_time: 0.0022 memory: 5639 grad_norm: 974.2734 loss: 435.5147 loss_cls: 161.7924 loss_bbox: 130.0422 loss_dfl: 143.6801 +2024/01/19 15:41:35 - mmengine - INFO - Epoch(train) [33][550/925] lr: 1.2328e-04 eta: 4:38:59 time: 0.3824 data_time: 0.0030 memory: 5452 grad_norm: 1184.3645 loss: 435.8263 loss_cls: 161.1691 loss_bbox: 129.7995 loss_dfl: 144.8578 +2024/01/19 15:41:53 - mmengine - INFO - Epoch(train) [33][600/925] lr: 1.2328e-04 eta: 4:38:39 time: 0.3611 data_time: 0.0023 memory: 5346 grad_norm: 983.9619 loss: 430.4865 loss_cls: 157.5772 loss_bbox: 129.2263 loss_dfl: 143.6830 +2024/01/19 15:42:12 - mmengine - INFO - Epoch(train) [33][650/925] lr: 1.2328e-04 eta: 4:38:19 time: 0.3771 data_time: 0.0021 memory: 5546 grad_norm: 1078.9187 loss: 436.4965 loss_cls: 162.0030 loss_bbox: 130.1641 loss_dfl: 144.3294 +2024/01/19 15:42:30 - mmengine - INFO - Epoch(train) [33][700/925] lr: 1.2328e-04 eta: 4:37:59 time: 0.3646 data_time: 0.0022 memory: 5239 grad_norm: 964.4543 loss: 433.5533 loss_cls: 161.1900 loss_bbox: 128.4361 loss_dfl: 143.9271 +2024/01/19 15:42:49 - mmengine - INFO - Epoch(train) [33][750/925] lr: 1.2328e-04 eta: 4:37:40 time: 0.3753 data_time: 0.0034 memory: 5412 grad_norm: 1002.7856 loss: 432.1611 loss_cls: 159.1689 loss_bbox: 129.0394 loss_dfl: 143.9527 +2024/01/19 15:43:08 - mmengine - INFO - Epoch(train) [33][800/925] lr: 1.2328e-04 eta: 4:37:20 time: 0.3768 data_time: 0.0027 memory: 5119 grad_norm: 1005.0944 loss: 431.6859 loss_cls: 158.8932 loss_bbox: 129.7887 loss_dfl: 143.0040 +2024/01/19 15:43:27 - mmengine - INFO - Epoch(train) [33][850/925] lr: 1.2328e-04 eta: 4:37:01 time: 0.3780 data_time: 0.0022 memory: 5479 grad_norm: 945.2031 loss: 432.2527 loss_cls: 159.8168 loss_bbox: 128.9333 loss_dfl: 143.5026 +2024/01/19 15:43:45 - mmengine - INFO - Epoch(train) [33][900/925] lr: 1.2328e-04 eta: 4:36:41 time: 0.3748 data_time: 0.0024 memory: 5479 grad_norm: 909.3742 loss: 423.5000 loss_cls: 154.5423 loss_bbox: 127.1618 loss_dfl: 141.7960 +2024/01/19 15:43:55 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:44:18 - mmengine - INFO - Epoch(train) [34][ 50/925] lr: 1.2080e-04 eta: 4:36:17 time: 0.4498 data_time: 0.0879 memory: 5532 grad_norm: 1028.9952 loss: 436.9877 loss_cls: 161.6054 loss_bbox: 131.0009 loss_dfl: 144.3814 +2024/01/19 15:44:36 - mmengine - INFO - Epoch(train) [34][100/925] lr: 1.2080e-04 eta: 4:35:57 time: 0.3729 data_time: 0.0022 memory: 5239 grad_norm: 996.0854 loss: 432.1014 loss_cls: 160.6169 loss_bbox: 127.3762 loss_dfl: 144.1083 +2024/01/19 15:44:55 - mmengine - INFO - Epoch(train) [34][150/925] lr: 1.2080e-04 eta: 4:35:38 time: 0.3758 data_time: 0.0031 memory: 5359 grad_norm: 972.6520 loss: 434.5392 loss_cls: 159.0370 loss_bbox: 131.4516 loss_dfl: 144.0505 +2024/01/19 15:45:14 - mmengine - INFO - Epoch(train) [34][200/925] lr: 1.2080e-04 eta: 4:35:18 time: 0.3727 data_time: 0.0025 memory: 5372 grad_norm: 975.1328 loss: 434.8156 loss_cls: 161.1064 loss_bbox: 129.3542 loss_dfl: 144.3550 +2024/01/19 15:45:32 - mmengine - INFO - Epoch(train) [34][250/925] lr: 1.2080e-04 eta: 4:34:58 time: 0.3650 data_time: 0.0023 memory: 5479 grad_norm: 911.0860 loss: 426.9883 loss_cls: 155.7500 loss_bbox: 128.4349 loss_dfl: 142.8034 +2024/01/19 15:45:50 - mmengine - INFO - Epoch(train) [34][300/925] lr: 1.2080e-04 eta: 4:34:37 time: 0.3641 data_time: 0.0023 memory: 5799 grad_norm: 1080.4795 loss: 431.6796 loss_cls: 157.7346 loss_bbox: 130.0505 loss_dfl: 143.8945 +2024/01/19 15:46:08 - mmengine - INFO - Epoch(train) [34][350/925] lr: 1.2080e-04 eta: 4:34:17 time: 0.3638 data_time: 0.0024 memory: 5452 grad_norm: 1015.2705 loss: 439.9534 loss_cls: 162.0532 loss_bbox: 132.0384 loss_dfl: 145.8618 +2024/01/19 15:46:28 - mmengine - INFO - Epoch(train) [34][400/925] lr: 1.2080e-04 eta: 4:33:59 time: 0.3946 data_time: 0.0023 memory: 5279 grad_norm: 1058.9833 loss: 432.3892 loss_cls: 158.7998 loss_bbox: 129.0234 loss_dfl: 144.5660 +2024/01/19 15:46:46 - mmengine - INFO - Epoch(train) [34][450/925] lr: 1.2080e-04 eta: 4:33:39 time: 0.3652 data_time: 0.0024 memory: 5332 grad_norm: 1074.7950 loss: 435.9509 loss_cls: 159.3852 loss_bbox: 131.8941 loss_dfl: 144.6716 +2024/01/19 15:46:56 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:47:05 - mmengine - INFO - Epoch(train) [34][500/925] lr: 1.2080e-04 eta: 4:33:19 time: 0.3672 data_time: 0.0023 memory: 5226 grad_norm: 1001.5731 loss: 436.2407 loss_cls: 160.1462 loss_bbox: 131.0250 loss_dfl: 145.0696 +2024/01/19 15:47:24 - mmengine - INFO - Epoch(train) [34][550/925] lr: 1.2080e-04 eta: 4:33:00 time: 0.3847 data_time: 0.0022 memory: 5052 grad_norm: 897.3608 loss: 423.6219 loss_cls: 152.2124 loss_bbox: 128.4788 loss_dfl: 142.9307 +2024/01/19 15:47:43 - mmengine - INFO - Epoch(train) [34][600/925] lr: 1.2080e-04 eta: 4:32:40 time: 0.3783 data_time: 0.0023 memory: 5586 grad_norm: 1079.9110 loss: 438.0163 loss_cls: 162.2092 loss_bbox: 130.5363 loss_dfl: 145.2708 +2024/01/19 15:48:01 - mmengine - INFO - Epoch(train) [34][650/925] lr: 1.2080e-04 eta: 4:32:20 time: 0.3610 data_time: 0.0022 memory: 5212 grad_norm: 1001.1325 loss: 436.2079 loss_cls: 160.4743 loss_bbox: 130.9207 loss_dfl: 144.8129 +2024/01/19 15:48:19 - mmengine - INFO - Epoch(train) [34][700/925] lr: 1.2080e-04 eta: 4:32:00 time: 0.3661 data_time: 0.0023 memory: 5266 grad_norm: 1144.6594 loss: 431.5498 loss_cls: 158.7666 loss_bbox: 129.4595 loss_dfl: 143.3237 +2024/01/19 15:48:39 - mmengine - INFO - Epoch(train) [34][750/925] lr: 1.2080e-04 eta: 4:31:41 time: 0.3851 data_time: 0.0024 memory: 5359 grad_norm: 1084.2247 loss: 424.1222 loss_cls: 154.0838 loss_bbox: 127.3655 loss_dfl: 142.6729 +2024/01/19 15:48:57 - mmengine - INFO - Epoch(train) [34][800/925] lr: 1.2080e-04 eta: 4:31:21 time: 0.3695 data_time: 0.0025 memory: 5772 grad_norm: 903.6472 loss: 429.5376 loss_cls: 158.0461 loss_bbox: 128.1953 loss_dfl: 143.2962 +2024/01/19 15:49:16 - mmengine - INFO - Epoch(train) [34][850/925] lr: 1.2080e-04 eta: 4:31:01 time: 0.3729 data_time: 0.0022 memory: 5892 grad_norm: 972.2566 loss: 434.1341 loss_cls: 159.4397 loss_bbox: 130.0999 loss_dfl: 144.5945 +2024/01/19 15:49:35 - mmengine - INFO - Epoch(train) [34][900/925] lr: 1.2080e-04 eta: 4:30:43 time: 0.3854 data_time: 0.0022 memory: 5172 grad_norm: 1067.7347 loss: 433.6644 loss_cls: 158.7201 loss_bbox: 129.6706 loss_dfl: 145.2737 +2024/01/19 15:49:44 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:50:07 - mmengine - INFO - Epoch(train) [35][ 50/925] lr: 1.1833e-04 eta: 4:30:18 time: 0.4460 data_time: 0.0853 memory: 5252 grad_norm: 1109.3162 loss: 425.9827 loss_cls: 155.2138 loss_bbox: 127.3490 loss_dfl: 143.4199 +2024/01/19 15:50:26 - mmengine - INFO - Epoch(train) [35][100/925] lr: 1.1833e-04 eta: 4:29:58 time: 0.3735 data_time: 0.0024 memory: 5386 grad_norm: 1024.2450 loss: 434.0999 loss_cls: 160.3703 loss_bbox: 129.3213 loss_dfl: 144.4083 +2024/01/19 15:50:46 - mmengine - INFO - Epoch(train) [35][150/925] lr: 1.1833e-04 eta: 4:29:40 time: 0.3998 data_time: 0.0026 memory: 5172 grad_norm: 956.7984 loss: 437.6315 loss_cls: 162.5003 loss_bbox: 129.6189 loss_dfl: 145.5123 +2024/01/19 15:51:05 - mmengine - INFO - Epoch(train) [35][200/925] lr: 1.1833e-04 eta: 4:29:22 time: 0.3902 data_time: 0.0024 memory: 5399 grad_norm: 1010.3714 loss: 439.2752 loss_cls: 163.0482 loss_bbox: 130.9839 loss_dfl: 145.2431 +2024/01/19 15:51:24 - mmengine - INFO - Epoch(train) [35][250/925] lr: 1.1833e-04 eta: 4:29:01 time: 0.3622 data_time: 0.0023 memory: 5706 grad_norm: 1002.0123 loss: 435.6886 loss_cls: 160.7194 loss_bbox: 130.7985 loss_dfl: 144.1706 +2024/01/19 15:51:42 - mmengine - INFO - Epoch(train) [35][300/925] lr: 1.1833e-04 eta: 4:28:42 time: 0.3733 data_time: 0.0024 memory: 5119 grad_norm: 967.3231 loss: 432.0352 loss_cls: 157.7788 loss_bbox: 130.0675 loss_dfl: 144.1889 +2024/01/19 15:52:02 - mmengine - INFO - Epoch(train) [35][350/925] lr: 1.1833e-04 eta: 4:28:23 time: 0.3869 data_time: 0.0027 memory: 5239 grad_norm: 1016.7283 loss: 428.8690 loss_cls: 157.4553 loss_bbox: 128.0819 loss_dfl: 143.3318 +2024/01/19 15:52:20 - mmengine - INFO - Epoch(train) [35][400/925] lr: 1.1833e-04 eta: 4:28:03 time: 0.3689 data_time: 0.0023 memory: 5586 grad_norm: 1090.3579 loss: 434.0946 loss_cls: 161.7689 loss_bbox: 128.1652 loss_dfl: 144.1606 +2024/01/19 15:52:38 - mmengine - INFO - Epoch(train) [35][450/925] lr: 1.1833e-04 eta: 4:27:43 time: 0.3642 data_time: 0.0022 memory: 5212 grad_norm: 1082.6196 loss: 433.4375 loss_cls: 160.5022 loss_bbox: 129.3384 loss_dfl: 143.5969 +2024/01/19 15:52:58 - mmengine - INFO - Epoch(train) [35][500/925] lr: 1.1833e-04 eta: 4:27:25 time: 0.3963 data_time: 0.0025 memory: 5279 grad_norm: 943.5283 loss: 430.8058 loss_cls: 156.9367 loss_bbox: 130.3396 loss_dfl: 143.5294 +2024/01/19 15:53:18 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:53:18 - mmengine - INFO - Epoch(train) [35][550/925] lr: 1.1833e-04 eta: 4:27:07 time: 0.3957 data_time: 0.0024 memory: 5426 grad_norm: 1038.7788 loss: 438.7678 loss_cls: 163.5649 loss_bbox: 130.5520 loss_dfl: 144.6508 +2024/01/19 15:53:37 - mmengine - INFO - Epoch(train) [35][600/925] lr: 1.1833e-04 eta: 4:26:47 time: 0.3727 data_time: 0.0024 memory: 5292 grad_norm: 1099.3723 loss: 434.5628 loss_cls: 158.7039 loss_bbox: 130.7930 loss_dfl: 145.0659 +2024/01/19 15:53:57 - mmengine - INFO - Epoch(train) [35][650/925] lr: 1.1833e-04 eta: 4:26:29 time: 0.4013 data_time: 0.0022 memory: 5319 grad_norm: 946.6325 loss: 427.0659 loss_cls: 155.1831 loss_bbox: 129.0739 loss_dfl: 142.8089 +2024/01/19 15:54:17 - mmengine - INFO - Epoch(train) [35][700/925] lr: 1.1833e-04 eta: 4:26:11 time: 0.3964 data_time: 0.0024 memory: 5319 grad_norm: 959.4621 loss: 430.2847 loss_cls: 157.8121 loss_bbox: 128.5612 loss_dfl: 143.9114 +2024/01/19 15:54:36 - mmengine - INFO - Epoch(train) [35][750/925] lr: 1.1833e-04 eta: 4:25:52 time: 0.3789 data_time: 0.0023 memory: 5346 grad_norm: 1090.2751 loss: 427.1711 loss_cls: 157.3921 loss_bbox: 126.6612 loss_dfl: 143.1178 +2024/01/19 15:54:56 - mmengine - INFO - Epoch(train) [35][800/925] lr: 1.1833e-04 eta: 4:25:34 time: 0.4026 data_time: 0.0024 memory: 5492 grad_norm: 926.5257 loss: 437.2097 loss_cls: 161.7947 loss_bbox: 130.8249 loss_dfl: 144.5901 +2024/01/19 15:55:16 - mmengine - INFO - Epoch(train) [35][850/925] lr: 1.1833e-04 eta: 4:25:16 time: 0.4001 data_time: 0.0023 memory: 5292 grad_norm: 956.5938 loss: 430.5936 loss_cls: 156.2847 loss_bbox: 130.2247 loss_dfl: 144.0843 +2024/01/19 15:55:35 - mmengine - INFO - Epoch(train) [35][900/925] lr: 1.1833e-04 eta: 4:24:57 time: 0.3837 data_time: 0.0023 memory: 5599 grad_norm: 1037.5841 loss: 435.9526 loss_cls: 160.6189 loss_bbox: 130.6133 loss_dfl: 144.7204 +2024/01/19 15:55:44 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 15:55:45 - mmengine - INFO - Saving checkpoint at 35 epochs +2024/01/19 15:55:53 - mmengine - INFO - Epoch(val) [35][ 50/625] eta: 0:00:20 time: 0.0355 data_time: 0.0008 memory: 5212 +2024/01/19 15:55:55 - mmengine - INFO - Epoch(val) [35][100/625] eta: 0:00:18 time: 0.0345 data_time: 0.0003 memory: 843 +2024/01/19 15:55:56 - mmengine - INFO - Epoch(val) [35][150/625] eta: 0:00:16 time: 0.0359 data_time: 0.0003 memory: 843 +2024/01/19 15:55:58 - mmengine - INFO - Epoch(val) [35][200/625] eta: 0:00:15 time: 0.0370 data_time: 0.0004 memory: 843 +2024/01/19 15:56:00 - mmengine - INFO - Epoch(val) [35][250/625] eta: 0:00:13 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 15:56:02 - mmengine - INFO - Epoch(val) [35][300/625] eta: 0:00:11 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 15:56:04 - mmengine - INFO - Epoch(val) [35][350/625] eta: 0:00:09 time: 0.0354 data_time: 0.0004 memory: 843 +2024/01/19 15:56:05 - mmengine - INFO - Epoch(val) [35][400/625] eta: 0:00:08 time: 0.0373 data_time: 0.0004 memory: 843 +2024/01/19 15:56:07 - mmengine - INFO - Epoch(val) [35][450/625] eta: 0:00:06 time: 0.0313 data_time: 0.0003 memory: 843 +2024/01/19 15:56:08 - mmengine - INFO - Epoch(val) [35][500/625] eta: 0:00:04 time: 0.0279 data_time: 0.0002 memory: 843 +2024/01/19 15:56:10 - mmengine - INFO - Epoch(val) [35][550/625] eta: 0:00:02 time: 0.0260 data_time: 0.0002 memory: 843 +2024/01/19 15:56:11 - mmengine - INFO - Epoch(val) [35][600/625] eta: 0:00:00 time: 0.0266 data_time: 0.0002 memory: 843 +2024/01/19 15:56:24 - mmengine - INFO - Evaluating bbox... +2024/01/19 15:57:38 - mmengine - INFO - bbox_mAP_copypaste: 0.448 0.608 0.488 0.250 0.497 0.606 +2024/01/19 15:57:40 - mmengine - INFO - Epoch(val) [35][625/625] coco/bbox_mAP: 0.4480 coco/bbox_mAP_50: 0.6080 coco/bbox_mAP_75: 0.4880 coco/bbox_mAP_s: 0.2500 coco/bbox_mAP_m: 0.4970 coco/bbox_mAP_l: 0.6060 data_time: 0.0002 time: 0.0264 +2024/01/19 15:58:01 - mmengine - INFO - Epoch(train) [36][ 50/925] lr: 1.1585e-04 eta: 4:24:31 time: 0.4348 data_time: 0.0798 memory: 5546 grad_norm: 1009.6990 loss: 428.4263 loss_cls: 157.0233 loss_bbox: 128.0699 loss_dfl: 143.3332 +2024/01/19 15:58:21 - mmengine - INFO - Epoch(train) [36][100/925] lr: 1.1585e-04 eta: 4:24:13 time: 0.3867 data_time: 0.0025 memory: 5492 grad_norm: 1121.2967 loss: 427.1090 loss_cls: 156.8729 loss_bbox: 127.4566 loss_dfl: 142.7795 +2024/01/19 15:58:39 - mmengine - INFO - Epoch(train) [36][150/925] lr: 1.1585e-04 eta: 4:23:53 time: 0.3721 data_time: 0.0023 memory: 5426 grad_norm: 1050.9040 loss: 426.9876 loss_cls: 155.6971 loss_bbox: 128.2913 loss_dfl: 142.9992 +2024/01/19 15:58:57 - mmengine - INFO - Epoch(train) [36][200/925] lr: 1.1585e-04 eta: 4:23:32 time: 0.3537 data_time: 0.0023 memory: 5212 grad_norm: 950.6316 loss: 431.4534 loss_cls: 159.5032 loss_bbox: 128.4985 loss_dfl: 143.4516 +2024/01/19 15:59:16 - mmengine - INFO - Epoch(train) [36][250/925] lr: 1.1585e-04 eta: 4:23:13 time: 0.3820 data_time: 0.0023 memory: 5572 grad_norm: 1092.1698 loss: 428.4981 loss_cls: 156.7040 loss_bbox: 129.0515 loss_dfl: 142.7426 +2024/01/19 15:59:36 - mmengine - INFO - Epoch(train) [36][300/925] lr: 1.1585e-04 eta: 4:22:55 time: 0.3935 data_time: 0.0033 memory: 5386 grad_norm: 987.4485 loss: 434.9299 loss_cls: 159.3890 loss_bbox: 131.0901 loss_dfl: 144.4508 +2024/01/19 15:59:55 - mmengine - INFO - Epoch(train) [36][350/925] lr: 1.1585e-04 eta: 4:22:36 time: 0.3900 data_time: 0.0024 memory: 5639 grad_norm: 915.2925 loss: 435.1294 loss_cls: 159.0204 loss_bbox: 131.4380 loss_dfl: 144.6710 +2024/01/19 16:00:14 - mmengine - INFO - Epoch(train) [36][400/925] lr: 1.1585e-04 eta: 4:22:17 time: 0.3774 data_time: 0.0024 memory: 5399 grad_norm: 968.0702 loss: 436.8316 loss_cls: 162.6322 loss_bbox: 129.9670 loss_dfl: 144.2324 +2024/01/19 16:00:33 - mmengine - INFO - Epoch(train) [36][450/925] lr: 1.1585e-04 eta: 4:21:57 time: 0.3691 data_time: 0.0022 memory: 5559 grad_norm: 968.8785 loss: 433.3211 loss_cls: 159.2829 loss_bbox: 130.5018 loss_dfl: 143.5364 +2024/01/19 16:00:53 - mmengine - INFO - Epoch(train) [36][500/925] lr: 1.1585e-04 eta: 4:21:39 time: 0.4015 data_time: 0.0024 memory: 5519 grad_norm: 1026.0923 loss: 432.4471 loss_cls: 159.0546 loss_bbox: 129.1475 loss_dfl: 144.2450 +2024/01/19 16:01:12 - mmengine - INFO - Epoch(train) [36][550/925] lr: 1.1585e-04 eta: 4:21:20 time: 0.3801 data_time: 0.0024 memory: 5732 grad_norm: 1042.3076 loss: 426.5020 loss_cls: 157.9820 loss_bbox: 126.1510 loss_dfl: 142.3690 +2024/01/19 16:01:31 - mmengine - INFO - Epoch(train) [36][600/925] lr: 1.1585e-04 eta: 4:21:01 time: 0.3852 data_time: 0.0023 memory: 5693 grad_norm: 846.9719 loss: 436.7233 loss_cls: 160.7403 loss_bbox: 131.2521 loss_dfl: 144.7309 +2024/01/19 16:01:40 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:01:50 - mmengine - INFO - Epoch(train) [36][650/925] lr: 1.1585e-04 eta: 4:20:42 time: 0.3838 data_time: 0.0022 memory: 5586 grad_norm: 1056.3462 loss: 430.8092 loss_cls: 156.9856 loss_bbox: 129.7420 loss_dfl: 144.0817 +2024/01/19 16:02:09 - mmengine - INFO - Epoch(train) [36][700/925] lr: 1.1585e-04 eta: 4:20:22 time: 0.3672 data_time: 0.0024 memory: 5212 grad_norm: 933.5143 loss: 428.1945 loss_cls: 156.0455 loss_bbox: 128.4173 loss_dfl: 143.7318 +2024/01/19 16:02:29 - mmengine - INFO - Epoch(train) [36][750/925] lr: 1.1585e-04 eta: 4:20:04 time: 0.4013 data_time: 0.0023 memory: 5626 grad_norm: 1009.8401 loss: 429.6661 loss_cls: 157.1702 loss_bbox: 128.7199 loss_dfl: 143.7760 +2024/01/19 16:02:47 - mmengine - INFO - Epoch(train) [36][800/925] lr: 1.1585e-04 eta: 4:19:44 time: 0.3628 data_time: 0.0022 memory: 5626 grad_norm: 1114.3551 loss: 431.4352 loss_cls: 156.9972 loss_bbox: 131.0998 loss_dfl: 143.3382 +2024/01/19 16:03:06 - mmengine - INFO - Epoch(train) [36][850/925] lr: 1.1585e-04 eta: 4:19:25 time: 0.3831 data_time: 0.0023 memory: 5372 grad_norm: 987.5475 loss: 431.6138 loss_cls: 158.6613 loss_bbox: 129.6783 loss_dfl: 143.2742 +2024/01/19 16:03:26 - mmengine - INFO - Epoch(train) [36][900/925] lr: 1.1585e-04 eta: 4:19:06 time: 0.3869 data_time: 0.0023 memory: 5372 grad_norm: 972.2239 loss: 431.3995 loss_cls: 157.5187 loss_bbox: 130.7453 loss_dfl: 143.1355 +2024/01/19 16:03:34 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:03:58 - mmengine - INFO - Epoch(train) [37][ 50/925] lr: 1.1338e-04 eta: 4:18:41 time: 0.4613 data_time: 0.0869 memory: 5292 grad_norm: 961.6543 loss: 428.8257 loss_cls: 156.2976 loss_bbox: 129.1608 loss_dfl: 143.3672 +2024/01/19 16:04:17 - mmengine - INFO - Epoch(train) [37][100/925] lr: 1.1338e-04 eta: 4:18:22 time: 0.3784 data_time: 0.0025 memory: 5572 grad_norm: 1003.5627 loss: 430.2438 loss_cls: 158.1476 loss_bbox: 127.9066 loss_dfl: 144.1896 +2024/01/19 16:04:35 - mmengine - INFO - Epoch(train) [37][150/925] lr: 1.1338e-04 eta: 4:18:02 time: 0.3710 data_time: 0.0034 memory: 5479 grad_norm: 1027.4465 loss: 434.4389 loss_cls: 160.3550 loss_bbox: 129.8684 loss_dfl: 144.2155 +2024/01/19 16:04:54 - mmengine - INFO - Epoch(train) [37][200/925] lr: 1.1338e-04 eta: 4:17:42 time: 0.3690 data_time: 0.0024 memory: 5279 grad_norm: 989.0203 loss: 429.3859 loss_cls: 156.8167 loss_bbox: 128.9513 loss_dfl: 143.6179 +2024/01/19 16:05:13 - mmengine - INFO - Epoch(train) [37][250/925] lr: 1.1338e-04 eta: 4:17:23 time: 0.3708 data_time: 0.0025 memory: 5666 grad_norm: 1037.8530 loss: 434.9744 loss_cls: 159.5654 loss_bbox: 131.0305 loss_dfl: 144.3785 +2024/01/19 16:05:31 - mmengine - INFO - Epoch(train) [37][300/925] lr: 1.1338e-04 eta: 4:17:03 time: 0.3686 data_time: 0.0035 memory: 5572 grad_norm: 955.8476 loss: 432.9527 loss_cls: 161.3759 loss_bbox: 128.0216 loss_dfl: 143.5552 +2024/01/19 16:05:50 - mmengine - INFO - Epoch(train) [37][350/925] lr: 1.1338e-04 eta: 4:16:44 time: 0.3820 data_time: 0.0025 memory: 5519 grad_norm: 980.3685 loss: 431.3149 loss_cls: 159.9811 loss_bbox: 127.7722 loss_dfl: 143.5617 +2024/01/19 16:06:10 - mmengine - INFO - Epoch(train) [37][400/925] lr: 1.1338e-04 eta: 4:16:25 time: 0.3950 data_time: 0.0024 memory: 5839 grad_norm: 1074.4163 loss: 433.1492 loss_cls: 160.4332 loss_bbox: 128.8690 loss_dfl: 143.8471 +2024/01/19 16:06:29 - mmengine - INFO - Epoch(train) [37][450/925] lr: 1.1338e-04 eta: 4:16:07 time: 0.3862 data_time: 0.0023 memory: 5732 grad_norm: 1128.9921 loss: 433.3362 loss_cls: 159.9171 loss_bbox: 129.1674 loss_dfl: 144.2518 +2024/01/19 16:06:48 - mmengine - INFO - Epoch(train) [37][500/925] lr: 1.1338e-04 eta: 4:15:47 time: 0.3820 data_time: 0.0025 memory: 5239 grad_norm: 1058.1189 loss: 429.1086 loss_cls: 157.1461 loss_bbox: 128.7813 loss_dfl: 143.1812 +2024/01/19 16:07:08 - mmengine - INFO - Epoch(train) [37][550/925] lr: 1.1338e-04 eta: 4:15:29 time: 0.3908 data_time: 0.0023 memory: 5226 grad_norm: 951.4914 loss: 430.3835 loss_cls: 157.2284 loss_bbox: 129.3633 loss_dfl: 143.7918 +2024/01/19 16:07:26 - mmengine - INFO - Epoch(train) [37][600/925] lr: 1.1338e-04 eta: 4:15:09 time: 0.3638 data_time: 0.0036 memory: 5412 grad_norm: 1071.2314 loss: 435.8539 loss_cls: 160.8957 loss_bbox: 130.7359 loss_dfl: 144.2223 +2024/01/19 16:07:45 - mmengine - INFO - Epoch(train) [37][650/925] lr: 1.1338e-04 eta: 4:14:50 time: 0.3867 data_time: 0.0026 memory: 5292 grad_norm: 1075.8932 loss: 428.5311 loss_cls: 158.0045 loss_bbox: 127.4321 loss_dfl: 143.0945 +2024/01/19 16:08:03 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:08:03 - mmengine - INFO - Epoch(train) [37][700/925] lr: 1.1338e-04 eta: 4:14:30 time: 0.3594 data_time: 0.0022 memory: 5399 grad_norm: 1032.3475 loss: 434.2903 loss_cls: 158.4035 loss_bbox: 131.0764 loss_dfl: 144.8104 +2024/01/19 16:08:24 - mmengine - INFO - Epoch(train) [37][750/925] lr: 1.1338e-04 eta: 4:14:12 time: 0.4016 data_time: 0.0033 memory: 5759 grad_norm: 1200.8485 loss: 430.8122 loss_cls: 157.4461 loss_bbox: 129.4590 loss_dfl: 143.9071 +2024/01/19 16:08:42 - mmengine - INFO - Epoch(train) [37][800/925] lr: 1.1338e-04 eta: 4:13:52 time: 0.3739 data_time: 0.0023 memory: 5439 grad_norm: 1095.3267 loss: 428.7390 loss_cls: 157.1499 loss_bbox: 128.9792 loss_dfl: 142.6098 +2024/01/19 16:09:01 - mmengine - INFO - Epoch(train) [37][850/925] lr: 1.1338e-04 eta: 4:13:33 time: 0.3759 data_time: 0.0025 memory: 5693 grad_norm: 922.2812 loss: 435.0272 loss_cls: 160.3026 loss_bbox: 130.9727 loss_dfl: 143.7520 +2024/01/19 16:09:21 - mmengine - INFO - Epoch(train) [37][900/925] lr: 1.1338e-04 eta: 4:13:14 time: 0.3881 data_time: 0.0024 memory: 5279 grad_norm: 1013.7770 loss: 426.9982 loss_cls: 156.1596 loss_bbox: 127.5471 loss_dfl: 143.2916 +2024/01/19 16:09:29 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:09:53 - mmengine - INFO - Epoch(train) [38][ 50/925] lr: 1.1090e-04 eta: 4:12:49 time: 0.4671 data_time: 0.0852 memory: 5452 grad_norm: 1028.1052 loss: 429.9434 loss_cls: 157.2111 loss_bbox: 129.2581 loss_dfl: 143.4742 +2024/01/19 16:10:12 - mmengine - INFO - Epoch(train) [38][100/925] lr: 1.1090e-04 eta: 4:12:30 time: 0.3754 data_time: 0.0022 memory: 5399 grad_norm: 931.3774 loss: 421.6163 loss_cls: 153.5692 loss_bbox: 126.1376 loss_dfl: 141.9095 +2024/01/19 16:10:32 - mmengine - INFO - Epoch(train) [38][150/925] lr: 1.1090e-04 eta: 4:12:11 time: 0.3926 data_time: 0.0025 memory: 5226 grad_norm: 1033.3267 loss: 426.0832 loss_cls: 154.9127 loss_bbox: 128.5724 loss_dfl: 142.5982 +2024/01/19 16:10:51 - mmengine - INFO - Epoch(train) [38][200/925] lr: 1.1090e-04 eta: 4:11:53 time: 0.3908 data_time: 0.0023 memory: 5226 grad_norm: 1098.8933 loss: 426.9698 loss_cls: 156.6194 loss_bbox: 128.2652 loss_dfl: 142.0851 +2024/01/19 16:11:11 - mmengine - INFO - Epoch(train) [38][250/925] lr: 1.1090e-04 eta: 4:11:34 time: 0.3875 data_time: 0.0024 memory: 5386 grad_norm: 1031.8561 loss: 430.7571 loss_cls: 159.5549 loss_bbox: 128.6697 loss_dfl: 142.5325 +2024/01/19 16:11:30 - mmengine - INFO - Epoch(train) [38][300/925] lr: 1.1090e-04 eta: 4:11:15 time: 0.3878 data_time: 0.0035 memory: 5506 grad_norm: 1102.0033 loss: 429.6378 loss_cls: 157.5799 loss_bbox: 128.8200 loss_dfl: 143.2379 +2024/01/19 16:11:50 - mmengine - INFO - Epoch(train) [38][350/925] lr: 1.1090e-04 eta: 4:10:57 time: 0.4024 data_time: 0.0036 memory: 5319 grad_norm: 1175.2369 loss: 430.4490 loss_cls: 158.7377 loss_bbox: 127.7203 loss_dfl: 143.9910 +2024/01/19 16:12:10 - mmengine - INFO - Epoch(train) [38][400/925] lr: 1.1090e-04 eta: 4:10:39 time: 0.3857 data_time: 0.0024 memory: 5466 grad_norm: 921.0683 loss: 426.5027 loss_cls: 157.3089 loss_bbox: 127.4387 loss_dfl: 141.7552 +2024/01/19 16:12:29 - mmengine - INFO - Epoch(train) [38][450/925] lr: 1.1090e-04 eta: 4:10:20 time: 0.3948 data_time: 0.0073 memory: 5906 grad_norm: 953.5965 loss: 431.6418 loss_cls: 157.7243 loss_bbox: 130.2199 loss_dfl: 143.6977 +2024/01/19 16:12:49 - mmengine - INFO - Epoch(train) [38][500/925] lr: 1.1090e-04 eta: 4:10:01 time: 0.3837 data_time: 0.0040 memory: 5612 grad_norm: 1106.9773 loss: 430.5277 loss_cls: 156.8099 loss_bbox: 129.9636 loss_dfl: 143.7542 +2024/01/19 16:13:08 - mmengine - INFO - Epoch(train) [38][550/925] lr: 1.1090e-04 eta: 4:09:42 time: 0.3842 data_time: 0.0035 memory: 5439 grad_norm: inf loss: 428.5490 loss_cls: 156.8551 loss_bbox: 127.7261 loss_dfl: 143.9678 +2024/01/19 16:13:28 - mmengine - INFO - Epoch(train) [38][600/925] lr: 1.1090e-04 eta: 4:09:25 time: 0.4088 data_time: 0.0030 memory: 5693 grad_norm: 969.1225 loss: 436.6662 loss_cls: 161.0670 loss_bbox: 130.7396 loss_dfl: 144.8596 +2024/01/19 16:13:48 - mmengine - INFO - Epoch(train) [38][650/925] lr: 1.1090e-04 eta: 4:09:06 time: 0.3986 data_time: 0.0024 memory: 5546 grad_norm: 928.1446 loss: 432.0800 loss_cls: 158.3250 loss_bbox: 129.8041 loss_dfl: 143.9509 +2024/01/19 16:14:07 - mmengine - INFO - Epoch(train) [38][700/925] lr: 1.1090e-04 eta: 4:08:47 time: 0.3765 data_time: 0.0025 memory: 5132 grad_norm: 1006.9998 loss: 429.6606 loss_cls: 157.8925 loss_bbox: 129.1436 loss_dfl: 142.6245 +2024/01/19 16:14:27 - mmengine - INFO - Epoch(train) [38][750/925] lr: 1.1090e-04 eta: 4:08:29 time: 0.3956 data_time: 0.0031 memory: 5426 grad_norm: 995.8171 loss: 429.4046 loss_cls: 156.9411 loss_bbox: 128.9424 loss_dfl: 143.5210 +2024/01/19 16:14:41 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:14:54 - mmengine - INFO - Epoch(train) [38][800/925] lr: 1.1090e-04 eta: 4:08:19 time: 0.5454 data_time: 0.0987 memory: 5706 grad_norm: 967.4272 loss: 430.6353 loss_cls: 157.3682 loss_bbox: 129.5647 loss_dfl: 143.7024 +2024/01/19 16:15:20 - mmengine - INFO - Epoch(train) [38][850/925] lr: 1.1090e-04 eta: 4:08:07 time: 0.5175 data_time: 0.0757 memory: 5266 grad_norm: 977.8034 loss: 429.2320 loss_cls: 156.5298 loss_bbox: 129.2722 loss_dfl: 143.4300 +2024/01/19 16:15:41 - mmengine - INFO - Epoch(train) [38][900/925] lr: 1.1090e-04 eta: 4:07:50 time: 0.4189 data_time: 0.0433 memory: 5226 grad_norm: 965.3270 loss: 416.4624 loss_cls: 150.3671 loss_bbox: 124.9414 loss_dfl: 141.1539 +2024/01/19 16:15:51 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:16:20 - mmengine - INFO - Epoch(train) [39][ 50/925] lr: 1.0842e-04 eta: 4:07:31 time: 0.5614 data_time: 0.1212 memory: 5266 grad_norm: 996.5293 loss: 433.0345 loss_cls: 159.4634 loss_bbox: 128.8831 loss_dfl: 144.6880 +2024/01/19 16:16:51 - mmengine - INFO - Epoch(train) [39][100/925] lr: 1.0842e-04 eta: 4:07:25 time: 0.6218 data_time: 0.0059 memory: 5332 grad_norm: 1332.4081 loss: 427.6057 loss_cls: 155.6469 loss_bbox: 128.7682 loss_dfl: 143.1905 +2024/01/19 16:17:19 - mmengine - INFO - Epoch(train) [39][150/925] lr: 1.0842e-04 eta: 4:07:16 time: 0.5578 data_time: 0.0142 memory: 5479 grad_norm: 957.4691 loss: 433.6368 loss_cls: 158.8548 loss_bbox: 130.2852 loss_dfl: 144.4968 +2024/01/19 16:17:45 - mmengine - INFO - Epoch(train) [39][200/925] lr: 1.0842e-04 eta: 4:07:05 time: 0.5264 data_time: 0.0119 memory: 5279 grad_norm: 944.3901 loss: 430.6820 loss_cls: 158.3434 loss_bbox: 128.9892 loss_dfl: 143.3494 +2024/01/19 16:18:11 - mmengine - INFO - Epoch(train) [39][250/925] lr: 1.0842e-04 eta: 4:06:52 time: 0.5142 data_time: 0.0032 memory: 5532 grad_norm: 892.0489 loss: 435.0101 loss_cls: 159.5876 loss_bbox: 131.3731 loss_dfl: 144.0494 +2024/01/19 16:18:45 - mmengine - INFO - Epoch(train) [39][300/925] lr: 1.0842e-04 eta: 4:06:49 time: 0.6758 data_time: 0.0139 memory: 5439 grad_norm: 1024.0339 loss: 434.6076 loss_cls: 159.0793 loss_bbox: 130.6902 loss_dfl: 144.8381 +2024/01/19 16:19:14 - mmengine - INFO - Epoch(train) [39][350/925] lr: 1.0842e-04 eta: 4:06:41 time: 0.5912 data_time: 0.0022 memory: 5746 grad_norm: 1006.4225 loss: 427.5286 loss_cls: 158.2860 loss_bbox: 126.5218 loss_dfl: 142.7207 +2024/01/19 16:19:43 - mmengine - INFO - Epoch(train) [39][400/925] lr: 1.0842e-04 eta: 4:06:32 time: 0.5684 data_time: 0.0092 memory: 5306 grad_norm: 1117.7668 loss: 435.0297 loss_cls: 159.7011 loss_bbox: 131.2589 loss_dfl: 144.0696 +2024/01/19 16:20:10 - mmengine - INFO - Epoch(train) [39][450/925] lr: 1.0842e-04 eta: 4:06:21 time: 0.5407 data_time: 0.0124 memory: 5532 grad_norm: 1006.3318 loss: 430.3753 loss_cls: 157.0809 loss_bbox: 129.5968 loss_dfl: 143.6976 +2024/01/19 16:20:42 - mmengine - INFO - Epoch(train) [39][500/925] lr: 1.0842e-04 eta: 4:06:16 time: 0.6483 data_time: 0.0252 memory: 5479 grad_norm: 959.9858 loss: 434.2182 loss_cls: 160.4689 loss_bbox: 129.9896 loss_dfl: 143.7597 +2024/01/19 16:21:13 - mmengine - INFO - Epoch(train) [39][550/925] lr: 1.0842e-04 eta: 4:06:10 time: 0.6245 data_time: 0.0022 memory: 5239 grad_norm: 1064.2252 loss: 425.6633 loss_cls: 155.3410 loss_bbox: 127.2806 loss_dfl: 143.0416 +2024/01/19 16:21:42 - mmengine - INFO - Epoch(train) [39][600/925] lr: 1.0842e-04 eta: 4:06:01 time: 0.5797 data_time: 0.0023 memory: 5612 grad_norm: 972.1324 loss: 429.6688 loss_cls: 157.0901 loss_bbox: 128.9604 loss_dfl: 143.6183 +2024/01/19 16:22:07 - mmengine - INFO - Epoch(train) [39][650/925] lr: 1.0842e-04 eta: 4:05:47 time: 0.4952 data_time: 0.0022 memory: 5226 grad_norm: 1076.4358 loss: 433.6114 loss_cls: 158.8607 loss_bbox: 130.7519 loss_dfl: 143.9987 +2024/01/19 16:22:39 - mmengine - INFO - Epoch(train) [39][700/925] lr: 1.0842e-04 eta: 4:05:41 time: 0.6358 data_time: 0.0064 memory: 5226 grad_norm: 967.5465 loss: 434.0495 loss_cls: 159.8894 loss_bbox: 129.5498 loss_dfl: 144.6103 +2024/01/19 16:23:10 - mmengine - INFO - Epoch(train) [39][750/925] lr: 1.0842e-04 eta: 4:05:35 time: 0.6270 data_time: 0.0023 memory: 5346 grad_norm: 971.7864 loss: 424.7461 loss_cls: 153.6815 loss_bbox: 128.6105 loss_dfl: 142.4542 +2024/01/19 16:23:46 - mmengine - INFO - Epoch(train) [39][800/925] lr: 1.0842e-04 eta: 4:05:33 time: 0.7167 data_time: 0.0022 memory: 5199 grad_norm: 974.4419 loss: 426.9734 loss_cls: 156.4486 loss_bbox: 127.2716 loss_dfl: 143.2533 +2024/01/19 16:24:31 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:24:31 - mmengine - INFO - Epoch(train) [39][850/925] lr: 1.0842e-04 eta: 4:05:40 time: 0.8908 data_time: 0.0019 memory: 5279 grad_norm: 998.0331 loss: 434.1024 loss_cls: 159.7337 loss_bbox: 130.2663 loss_dfl: 144.1023 +2024/01/19 16:25:09 - mmengine - INFO - Epoch(train) [39][900/925] lr: 1.0842e-04 eta: 4:05:41 time: 0.7695 data_time: 0.0021 memory: 5506 grad_norm: 1051.4887 loss: 422.8851 loss_cls: 152.7380 loss_bbox: 128.3501 loss_dfl: 141.7970 +2024/01/19 16:25:22 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:25:53 - mmengine - INFO - Epoch(train) [40][ 50/925] lr: 1.0595e-04 eta: 4:05:27 time: 0.6174 data_time: 0.1273 memory: 5426 grad_norm: 1016.6320 loss: 435.1009 loss_cls: 161.3315 loss_bbox: 129.6926 loss_dfl: 144.0768 +2024/01/19 16:26:14 - mmengine - INFO - Epoch(train) [40][100/925] lr: 1.0595e-04 eta: 4:05:08 time: 0.4153 data_time: 0.0022 memory: 5946 grad_norm: 1055.9252 loss: 428.8105 loss_cls: 159.2297 loss_bbox: 126.9747 loss_dfl: 142.6061 +2024/01/19 16:26:36 - mmengine - INFO - Epoch(train) [40][150/925] lr: 1.0595e-04 eta: 4:04:52 time: 0.4487 data_time: 0.0339 memory: 5479 grad_norm: 1050.8857 loss: 429.4089 loss_cls: 156.7887 loss_bbox: 128.3330 loss_dfl: 144.2872 +2024/01/19 16:26:56 - mmengine - INFO - Epoch(train) [40][200/925] lr: 1.0595e-04 eta: 4:04:32 time: 0.3816 data_time: 0.0028 memory: 5172 grad_norm: 1036.7176 loss: 425.8242 loss_cls: 155.4403 loss_bbox: 127.7389 loss_dfl: 142.6450 +2024/01/19 16:27:14 - mmengine - INFO - Epoch(train) [40][250/925] lr: 1.0595e-04 eta: 4:04:12 time: 0.3695 data_time: 0.0035 memory: 5532 grad_norm: 907.1011 loss: 428.8811 loss_cls: 156.7248 loss_bbox: 128.7035 loss_dfl: 143.4528 +2024/01/19 16:27:33 - mmengine - INFO - Epoch(train) [40][300/925] lr: 1.0595e-04 eta: 4:03:52 time: 0.3724 data_time: 0.0022 memory: 5372 grad_norm: 1010.6856 loss: 435.0756 loss_cls: 159.5029 loss_bbox: 131.0542 loss_dfl: 144.5185 +2024/01/19 16:27:52 - mmengine - INFO - Epoch(train) [40][350/925] lr: 1.0595e-04 eta: 4:03:32 time: 0.3780 data_time: 0.0025 memory: 5466 grad_norm: 986.9878 loss: 430.3641 loss_cls: 158.4752 loss_bbox: 128.8398 loss_dfl: 143.0491 +2024/01/19 16:28:12 - mmengine - INFO - Epoch(train) [40][400/925] lr: 1.0595e-04 eta: 4:03:13 time: 0.3970 data_time: 0.0025 memory: 5426 grad_norm: 985.1923 loss: 428.3631 loss_cls: 157.4181 loss_bbox: 127.5474 loss_dfl: 143.3977 +2024/01/19 16:28:30 - mmengine - INFO - Epoch(train) [40][450/925] lr: 1.0595e-04 eta: 4:02:52 time: 0.3619 data_time: 0.0024 memory: 5212 grad_norm: 1081.1842 loss: 436.7538 loss_cls: 162.2019 loss_bbox: 129.8033 loss_dfl: 144.7487 +2024/01/19 16:28:48 - mmengine - INFO - Epoch(train) [40][500/925] lr: 1.0595e-04 eta: 4:02:31 time: 0.3706 data_time: 0.0023 memory: 5626 grad_norm: 996.4519 loss: 430.6181 loss_cls: 157.3680 loss_bbox: 129.5142 loss_dfl: 143.7359 +2024/01/19 16:29:08 - mmengine - INFO - Epoch(train) [40][550/925] lr: 1.0595e-04 eta: 4:02:12 time: 0.3857 data_time: 0.0025 memory: 5506 grad_norm: 1077.3242 loss: 430.2491 loss_cls: 157.8490 loss_bbox: 128.8404 loss_dfl: 143.5597 +2024/01/19 16:29:26 - mmengine - INFO - Epoch(train) [40][600/925] lr: 1.0595e-04 eta: 4:01:51 time: 0.3708 data_time: 0.0023 memory: 5186 grad_norm: 1031.0107 loss: 433.8536 loss_cls: 158.9516 loss_bbox: 130.1937 loss_dfl: 144.7083 +2024/01/19 16:29:46 - mmengine - INFO - Epoch(train) [40][650/925] lr: 1.0595e-04 eta: 4:01:32 time: 0.3883 data_time: 0.0023 memory: 5612 grad_norm: 1001.6664 loss: 429.0815 loss_cls: 156.9270 loss_bbox: 128.3439 loss_dfl: 143.8105 +2024/01/19 16:30:04 - mmengine - INFO - Epoch(train) [40][700/925] lr: 1.0595e-04 eta: 4:01:12 time: 0.3708 data_time: 0.0023 memory: 5359 grad_norm: 1027.7275 loss: 429.1904 loss_cls: 156.4180 loss_bbox: 128.9145 loss_dfl: 143.8579 +2024/01/19 16:30:23 - mmengine - INFO - Epoch(train) [40][750/925] lr: 1.0595e-04 eta: 4:00:52 time: 0.3788 data_time: 0.0025 memory: 5506 grad_norm: 1086.6561 loss: 424.8201 loss_cls: 155.5680 loss_bbox: 126.4203 loss_dfl: 142.8319 +2024/01/19 16:30:42 - mmengine - INFO - Epoch(train) [40][800/925] lr: 1.0595e-04 eta: 4:00:32 time: 0.3789 data_time: 0.0023 memory: 5679 grad_norm: 1090.4006 loss: 421.1330 loss_cls: 152.1208 loss_bbox: 126.6978 loss_dfl: 142.3143 +2024/01/19 16:31:01 - mmengine - INFO - Epoch(train) [40][850/925] lr: 1.0595e-04 eta: 4:00:12 time: 0.3831 data_time: 0.0024 memory: 5572 grad_norm: 991.7855 loss: 425.5714 loss_cls: 156.9804 loss_bbox: 125.9238 loss_dfl: 142.6672 +2024/01/19 16:31:21 - mmengine - INFO - Epoch(train) [40][900/925] lr: 1.0595e-04 eta: 3:59:53 time: 0.3942 data_time: 0.0035 memory: 5372 grad_norm: inf loss: 430.5783 loss_cls: 156.8789 loss_bbox: 129.4415 loss_dfl: 144.2579 +2024/01/19 16:31:29 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:31:30 - mmengine - INFO - Saving checkpoint at 40 epochs +2024/01/19 16:31:38 - mmengine - INFO - Epoch(val) [40][ 50/625] eta: 0:00:20 time: 0.0352 data_time: 0.0009 memory: 5252 +2024/01/19 16:31:40 - mmengine - INFO - Epoch(val) [40][100/625] eta: 0:00:18 time: 0.0355 data_time: 0.0003 memory: 843 +2024/01/19 16:31:42 - mmengine - INFO - Epoch(val) [40][150/625] eta: 0:00:17 time: 0.0371 data_time: 0.0004 memory: 843 +2024/01/19 16:31:43 - mmengine - INFO - Epoch(val) [40][200/625] eta: 0:00:15 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 16:31:45 - mmengine - INFO - Epoch(val) [40][250/625] eta: 0:00:13 time: 0.0355 data_time: 0.0003 memory: 843 +2024/01/19 16:31:47 - mmengine - INFO - Epoch(val) [40][300/625] eta: 0:00:11 time: 0.0345 data_time: 0.0009 memory: 843 +2024/01/19 16:31:49 - mmengine - INFO - Epoch(val) [40][350/625] eta: 0:00:09 time: 0.0353 data_time: 0.0004 memory: 843 +2024/01/19 16:31:50 - mmengine - INFO - Epoch(val) [40][400/625] eta: 0:00:07 time: 0.0345 data_time: 0.0004 memory: 843 +2024/01/19 16:31:52 - mmengine - INFO - Epoch(val) [40][450/625] eta: 0:00:06 time: 0.0319 data_time: 0.0003 memory: 843 +2024/01/19 16:31:53 - mmengine - INFO - Epoch(val) [40][500/625] eta: 0:00:04 time: 0.0257 data_time: 0.0002 memory: 843 +2024/01/19 16:31:55 - mmengine - INFO - Epoch(val) [40][550/625] eta: 0:00:02 time: 0.0261 data_time: 0.0003 memory: 843 +2024/01/19 16:31:56 - mmengine - INFO - Epoch(val) [40][600/625] eta: 0:00:00 time: 0.0260 data_time: 0.0002 memory: 843 +2024/01/19 16:32:10 - mmengine - INFO - Evaluating bbox... +2024/01/19 16:33:33 - mmengine - INFO - bbox_mAP_copypaste: 0.450 0.610 0.490 0.252 0.500 0.608 +2024/01/19 16:33:35 - mmengine - INFO - Epoch(val) [40][625/625] coco/bbox_mAP: 0.4500 coco/bbox_mAP_50: 0.6100 coco/bbox_mAP_75: 0.4900 coco/bbox_mAP_s: 0.2520 coco/bbox_mAP_m: 0.5000 coco/bbox_mAP_l: 0.6080 data_time: 0.0002 time: 0.0259 +2024/01/19 16:34:02 - mmengine - INFO - Epoch(train) [41][ 50/925] lr: 1.0347e-04 eta: 3:59:29 time: 0.5232 data_time: 0.1713 memory: 5586 grad_norm: 1022.4914 loss: 431.5572 loss_cls: 157.1121 loss_bbox: 130.3929 loss_dfl: 144.0522 +2024/01/19 16:34:22 - mmengine - INFO - Epoch(train) [41][100/925] lr: 1.0347e-04 eta: 3:59:10 time: 0.4089 data_time: 0.0428 memory: 5212 grad_norm: 950.7506 loss: 424.3006 loss_cls: 152.6468 loss_bbox: 128.2945 loss_dfl: 143.3593 +2024/01/19 16:34:43 - mmengine - INFO - Epoch(train) [41][150/925] lr: 1.0347e-04 eta: 3:58:52 time: 0.4180 data_time: 0.0386 memory: 5399 grad_norm: 1026.2034 loss: 437.0217 loss_cls: 162.3554 loss_bbox: 129.7198 loss_dfl: 144.9465 +2024/01/19 16:35:00 - mmengine - INFO - Epoch(train) [41][200/925] lr: 1.0347e-04 eta: 3:58:31 time: 0.3469 data_time: 0.0031 memory: 5386 grad_norm: 1041.1923 loss: 434.8735 loss_cls: 161.3518 loss_bbox: 129.5184 loss_dfl: 144.0034 +2024/01/19 16:35:19 - mmengine - INFO - Epoch(train) [41][250/925] lr: 1.0347e-04 eta: 3:58:11 time: 0.3826 data_time: 0.0033 memory: 5559 grad_norm: 1064.9033 loss: 435.7617 loss_cls: 161.5580 loss_bbox: 130.2313 loss_dfl: 143.9723 +2024/01/19 16:35:39 - mmengine - INFO - Epoch(train) [41][300/925] lr: 1.0347e-04 eta: 3:57:52 time: 0.3887 data_time: 0.0025 memory: 5319 grad_norm: 981.4128 loss: 427.0241 loss_cls: 154.4671 loss_bbox: 129.5526 loss_dfl: 143.0044 +2024/01/19 16:36:04 - mmengine - INFO - Epoch(train) [41][350/925] lr: 1.0347e-04 eta: 3:57:37 time: 0.4960 data_time: 0.0025 memory: 5399 grad_norm: 1100.0126 loss: 428.5607 loss_cls: 156.6629 loss_bbox: 127.9115 loss_dfl: 143.9863 +2024/01/19 16:36:23 - mmengine - INFO - Epoch(train) [41][400/925] lr: 1.0347e-04 eta: 3:57:18 time: 0.3898 data_time: 0.0350 memory: 5386 grad_norm: 1149.0990 loss: 433.7687 loss_cls: 159.0245 loss_bbox: 130.6522 loss_dfl: 144.0920 +2024/01/19 16:36:43 - mmengine - INFO - Epoch(train) [41][450/925] lr: 1.0347e-04 eta: 3:56:59 time: 0.3962 data_time: 0.0303 memory: 5266 grad_norm: 968.9180 loss: 442.1819 loss_cls: 163.7630 loss_bbox: 132.5286 loss_dfl: 145.8903 +2024/01/19 16:37:03 - mmengine - INFO - Epoch(train) [41][500/925] lr: 1.0347e-04 eta: 3:56:40 time: 0.3971 data_time: 0.0026 memory: 5452 grad_norm: 954.7044 loss: 433.3439 loss_cls: 159.4518 loss_bbox: 130.1158 loss_dfl: 143.7764 +2024/01/19 16:37:23 - mmengine - INFO - Epoch(train) [41][550/925] lr: 1.0347e-04 eta: 3:56:21 time: 0.3952 data_time: 0.0160 memory: 5586 grad_norm: 902.3317 loss: 427.6352 loss_cls: 155.4205 loss_bbox: 128.9768 loss_dfl: 143.2379 +2024/01/19 16:37:46 - mmengine - INFO - Epoch(train) [41][600/925] lr: 1.0347e-04 eta: 3:56:05 time: 0.4720 data_time: 0.0799 memory: 5612 grad_norm: 986.9887 loss: 432.3519 loss_cls: 157.2579 loss_bbox: 130.4088 loss_dfl: 144.6852 +2024/01/19 16:38:09 - mmengine - INFO - Epoch(train) [41][650/925] lr: 1.0347e-04 eta: 3:55:49 time: 0.4561 data_time: 0.0700 memory: 5372 grad_norm: 952.1863 loss: 431.1025 loss_cls: 158.2278 loss_bbox: 128.1459 loss_dfl: 144.7287 +2024/01/19 16:38:29 - mmengine - INFO - Epoch(train) [41][700/925] lr: 1.0347e-04 eta: 3:55:30 time: 0.4024 data_time: 0.0061 memory: 5439 grad_norm: 1080.3823 loss: 427.1974 loss_cls: 155.5853 loss_bbox: 128.6242 loss_dfl: 142.9878 +2024/01/19 16:38:48 - mmengine - INFO - Epoch(train) [41][750/925] lr: 1.0347e-04 eta: 3:55:10 time: 0.3688 data_time: 0.0031 memory: 5372 grad_norm: 993.2038 loss: 419.7884 loss_cls: 151.9048 loss_bbox: 125.8005 loss_dfl: 142.0831 +2024/01/19 16:39:07 - mmengine - INFO - Epoch(train) [41][800/925] lr: 1.0347e-04 eta: 3:54:50 time: 0.3760 data_time: 0.0024 memory: 5319 grad_norm: 1014.3283 loss: 429.7144 loss_cls: 157.1540 loss_bbox: 128.8335 loss_dfl: 143.7269 +2024/01/19 16:39:26 - mmengine - INFO - Epoch(train) [41][850/925] lr: 1.0347e-04 eta: 3:54:30 time: 0.3759 data_time: 0.0034 memory: 5586 grad_norm: 912.0002 loss: 428.3238 loss_cls: 156.8900 loss_bbox: 128.7892 loss_dfl: 142.6446 +2024/01/19 16:39:44 - mmengine - INFO - Epoch(train) [41][900/925] lr: 1.0347e-04 eta: 3:54:09 time: 0.3749 data_time: 0.0025 memory: 5332 grad_norm: 1025.9506 loss: 427.4854 loss_cls: 156.3331 loss_bbox: 127.5616 loss_dfl: 143.5907 +2024/01/19 16:39:53 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:40:25 - mmengine - INFO - Epoch(train) [42][ 50/925] lr: 1.0100e-04 eta: 3:53:50 time: 0.6232 data_time: 0.1674 memory: 5199 grad_norm: 1091.3426 loss: 422.6980 loss_cls: 151.9777 loss_bbox: 127.6399 loss_dfl: 143.0804 +2024/01/19 16:40:36 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:40:48 - mmengine - INFO - Epoch(train) [42][100/925] lr: 1.0100e-04 eta: 3:53:34 time: 0.4638 data_time: 0.0662 memory: 5132 grad_norm: 1002.5300 loss: 431.7297 loss_cls: 158.5875 loss_bbox: 129.1326 loss_dfl: 144.0095 +2024/01/19 16:41:09 - mmengine - INFO - Epoch(train) [42][150/925] lr: 1.0100e-04 eta: 3:53:16 time: 0.4145 data_time: 0.0339 memory: 5399 grad_norm: 1154.4863 loss: 433.8774 loss_cls: 159.1549 loss_bbox: 130.1336 loss_dfl: 144.5890 +2024/01/19 16:41:30 - mmengine - INFO - Epoch(train) [42][200/925] lr: 1.0100e-04 eta: 3:52:58 time: 0.4154 data_time: 0.0337 memory: 5252 grad_norm: 1069.5651 loss: 427.9528 loss_cls: 156.2323 loss_bbox: 128.4547 loss_dfl: 143.2659 +2024/01/19 16:41:55 - mmengine - INFO - Epoch(train) [42][250/925] lr: 1.0100e-04 eta: 3:52:44 time: 0.5056 data_time: 0.0562 memory: 5292 grad_norm: 911.4358 loss: 428.7224 loss_cls: 156.9947 loss_bbox: 128.4394 loss_dfl: 143.2882 +2024/01/19 16:42:21 - mmengine - INFO - Epoch(train) [42][300/925] lr: 1.0100e-04 eta: 3:52:30 time: 0.5199 data_time: 0.0292 memory: 5839 grad_norm: 965.9415 loss: 426.7108 loss_cls: 155.3251 loss_bbox: 128.2907 loss_dfl: 143.0951 +2024/01/19 16:42:44 - mmengine - INFO - Epoch(train) [42][350/925] lr: 1.0100e-04 eta: 3:52:15 time: 0.4686 data_time: 0.0099 memory: 5426 grad_norm: 953.2244 loss: 424.8977 loss_cls: 156.5732 loss_bbox: 125.9609 loss_dfl: 142.3637 +2024/01/19 16:43:08 - mmengine - INFO - Epoch(train) [42][400/925] lr: 1.0100e-04 eta: 3:51:59 time: 0.4790 data_time: 0.0715 memory: 5412 grad_norm: 1187.0506 loss: 422.4976 loss_cls: 154.1048 loss_bbox: 126.3046 loss_dfl: 142.0882 +2024/01/19 16:43:28 - mmengine - INFO - Epoch(train) [42][450/925] lr: 1.0100e-04 eta: 3:51:40 time: 0.3990 data_time: 0.0157 memory: 5186 grad_norm: 953.8153 loss: 427.2244 loss_cls: 155.3550 loss_bbox: 127.5330 loss_dfl: 144.3364 +2024/01/19 16:43:53 - mmengine - INFO - Epoch(train) [42][500/925] lr: 1.0100e-04 eta: 3:51:26 time: 0.4971 data_time: 0.0025 memory: 5426 grad_norm: 1045.0295 loss: 424.6164 loss_cls: 153.6517 loss_bbox: 128.2823 loss_dfl: 142.6824 +2024/01/19 16:44:19 - mmengine - INFO - Epoch(train) [42][550/925] lr: 1.0100e-04 eta: 3:51:11 time: 0.5068 data_time: 0.0023 memory: 5412 grad_norm: 917.9252 loss: 423.2797 loss_cls: 154.1092 loss_bbox: 126.5598 loss_dfl: 142.6107 +2024/01/19 16:44:42 - mmengine - INFO - Epoch(train) [42][600/925] lr: 1.0100e-04 eta: 3:50:55 time: 0.4651 data_time: 0.0025 memory: 5466 grad_norm: 1120.3965 loss: 425.5848 loss_cls: 155.5618 loss_bbox: 127.2583 loss_dfl: 142.7647 +2024/01/19 16:45:04 - mmengine - INFO - Epoch(train) [42][650/925] lr: 1.0100e-04 eta: 3:50:38 time: 0.4378 data_time: 0.0105 memory: 5399 grad_norm: 909.1722 loss: 427.8950 loss_cls: 155.9650 loss_bbox: 128.9379 loss_dfl: 142.9920 +2024/01/19 16:45:25 - mmengine - INFO - Epoch(train) [42][700/925] lr: 1.0100e-04 eta: 3:50:20 time: 0.4187 data_time: 0.0026 memory: 5706 grad_norm: 947.7891 loss: 415.9186 loss_cls: 150.8078 loss_bbox: 124.2377 loss_dfl: 140.8732 +2024/01/19 16:45:49 - mmengine - INFO - Epoch(train) [42][750/925] lr: 1.0100e-04 eta: 3:50:05 time: 0.4895 data_time: 0.0023 memory: 5439 grad_norm: 1012.3415 loss: 429.1199 loss_cls: 156.7054 loss_bbox: 128.5083 loss_dfl: 143.9063 +2024/01/19 16:46:17 - mmengine - INFO - Epoch(train) [42][800/925] lr: 1.0100e-04 eta: 3:49:52 time: 0.5500 data_time: 0.0505 memory: 5372 grad_norm: 981.6540 loss: 425.7214 loss_cls: 155.1106 loss_bbox: 127.7419 loss_dfl: 142.8690 +2024/01/19 16:46:41 - mmengine - INFO - Epoch(train) [42][850/925] lr: 1.0100e-04 eta: 3:49:37 time: 0.4915 data_time: 0.0106 memory: 5852 grad_norm: 971.3485 loss: 426.5299 loss_cls: 153.3479 loss_bbox: 129.2415 loss_dfl: 143.9405 +2024/01/19 16:47:01 - mmengine - INFO - Epoch(train) [42][900/925] lr: 1.0100e-04 eta: 3:49:18 time: 0.3863 data_time: 0.0040 memory: 5519 grad_norm: 1302.9246 loss: 431.7441 loss_cls: 158.5481 loss_bbox: 128.9675 loss_dfl: 144.2286 +2024/01/19 16:47:10 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:47:34 - mmengine - INFO - Epoch(train) [43][ 50/925] lr: 9.8525e-05 eta: 3:48:52 time: 0.4832 data_time: 0.1140 memory: 5412 grad_norm: 960.9190 loss: 428.6562 loss_cls: 157.1404 loss_bbox: 127.8894 loss_dfl: 143.6264 +2024/01/19 16:47:53 - mmengine - INFO - Epoch(train) [43][100/925] lr: 9.8525e-05 eta: 3:48:31 time: 0.3752 data_time: 0.0026 memory: 5412 grad_norm: 989.3712 loss: 423.7240 loss_cls: 154.2396 loss_bbox: 127.2761 loss_dfl: 142.2083 +2024/01/19 16:48:15 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:48:15 - mmengine - INFO - Epoch(train) [43][150/925] lr: 9.8525e-05 eta: 3:48:14 time: 0.4448 data_time: 0.0177 memory: 5239 grad_norm: 1021.4056 loss: 431.4986 loss_cls: 158.0609 loss_bbox: 129.0025 loss_dfl: 144.4352 +2024/01/19 16:48:35 - mmengine - INFO - Epoch(train) [43][200/925] lr: 9.8525e-05 eta: 3:47:55 time: 0.3992 data_time: 0.0060 memory: 5426 grad_norm: 1093.7843 loss: 423.2468 loss_cls: 153.3319 loss_bbox: 127.3218 loss_dfl: 142.5931 +2024/01/19 16:48:54 - mmengine - INFO - Epoch(train) [43][250/925] lr: 9.8525e-05 eta: 3:47:35 time: 0.3815 data_time: 0.0034 memory: 5626 grad_norm: 943.8474 loss: 424.7759 loss_cls: 153.2003 loss_bbox: 128.9299 loss_dfl: 142.6457 +2024/01/19 16:49:13 - mmengine - INFO - Epoch(train) [43][300/925] lr: 9.8525e-05 eta: 3:47:15 time: 0.3805 data_time: 0.0030 memory: 5492 grad_norm: 957.8952 loss: 421.2659 loss_cls: 153.1129 loss_bbox: 126.6476 loss_dfl: 141.5054 +2024/01/19 16:49:33 - mmengine - INFO - Epoch(train) [43][350/925] lr: 9.8525e-05 eta: 3:46:56 time: 0.3960 data_time: 0.0025 memory: 5346 grad_norm: inf loss: 426.3199 loss_cls: 155.7300 loss_bbox: 127.5835 loss_dfl: 143.0064 +2024/01/19 16:49:52 - mmengine - INFO - Epoch(train) [43][400/925] lr: 9.8525e-05 eta: 3:46:35 time: 0.3674 data_time: 0.0025 memory: 5479 grad_norm: 1023.4291 loss: 427.9252 loss_cls: 157.5260 loss_bbox: 127.3265 loss_dfl: 143.0727 +2024/01/19 16:50:11 - mmengine - INFO - Epoch(train) [43][450/925] lr: 9.8525e-05 eta: 3:46:15 time: 0.3768 data_time: 0.0027 memory: 5039 grad_norm: 1153.4460 loss: 426.2740 loss_cls: 155.8009 loss_bbox: 127.5799 loss_dfl: 142.8931 +2024/01/19 16:50:29 - mmengine - INFO - Epoch(train) [43][500/925] lr: 9.8525e-05 eta: 3:45:54 time: 0.3648 data_time: 0.0024 memory: 5306 grad_norm: 971.1461 loss: 420.2379 loss_cls: 151.2438 loss_bbox: 127.0271 loss_dfl: 141.9671 +2024/01/19 16:50:47 - mmengine - INFO - Epoch(train) [43][550/925] lr: 9.8525e-05 eta: 3:45:33 time: 0.3617 data_time: 0.0025 memory: 5319 grad_norm: 1025.5829 loss: 425.4192 loss_cls: 153.6715 loss_bbox: 128.3025 loss_dfl: 143.4452 +2024/01/19 16:51:06 - mmengine - INFO - Epoch(train) [43][600/925] lr: 9.8525e-05 eta: 3:45:13 time: 0.3779 data_time: 0.0026 memory: 5759 grad_norm: 1002.2013 loss: 431.8462 loss_cls: 156.9897 loss_bbox: 130.8833 loss_dfl: 143.9732 +2024/01/19 16:51:25 - mmengine - INFO - Epoch(train) [43][650/925] lr: 9.8525e-05 eta: 3:44:53 time: 0.3798 data_time: 0.0026 memory: 5359 grad_norm: 943.3719 loss: 427.5357 loss_cls: 156.6262 loss_bbox: 127.8242 loss_dfl: 143.0853 +2024/01/19 16:51:46 - mmengine - INFO - Epoch(train) [43][700/925] lr: 9.8525e-05 eta: 3:44:35 time: 0.4222 data_time: 0.0228 memory: 5946 grad_norm: 913.8296 loss: 424.6048 loss_cls: 154.6282 loss_bbox: 127.7759 loss_dfl: 142.2007 +2024/01/19 16:52:06 - mmengine - INFO - Epoch(train) [43][750/925] lr: 9.8525e-05 eta: 3:44:16 time: 0.4049 data_time: 0.0416 memory: 5252 grad_norm: 987.7527 loss: 422.2375 loss_cls: 153.0234 loss_bbox: 126.7980 loss_dfl: 142.4161 +2024/01/19 16:52:27 - mmengine - INFO - Epoch(train) [43][800/925] lr: 9.8525e-05 eta: 3:43:57 time: 0.4076 data_time: 0.0141 memory: 5719 grad_norm: 992.7624 loss: 425.2627 loss_cls: 153.4270 loss_bbox: 128.8686 loss_dfl: 142.9671 +2024/01/19 16:52:45 - mmengine - INFO - Epoch(train) [43][850/925] lr: 9.8525e-05 eta: 3:43:37 time: 0.3685 data_time: 0.0104 memory: 5492 grad_norm: 1067.6841 loss: 428.4147 loss_cls: 156.6731 loss_bbox: 128.5062 loss_dfl: 143.2353 +2024/01/19 16:53:03 - mmengine - INFO - Epoch(train) [43][900/925] lr: 9.8525e-05 eta: 3:43:15 time: 0.3563 data_time: 0.0025 memory: 5906 grad_norm: 991.0705 loss: 418.7215 loss_cls: 153.0844 loss_bbox: 124.6166 loss_dfl: 141.0204 +2024/01/19 16:53:12 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:53:42 - mmengine - INFO - Epoch(train) [44][ 50/925] lr: 9.6050e-05 eta: 3:42:54 time: 0.5818 data_time: 0.1507 memory: 5546 grad_norm: 1060.4622 loss: 424.3472 loss_cls: 154.4333 loss_bbox: 126.9112 loss_dfl: 143.0027 +2024/01/19 16:54:04 - mmengine - INFO - Epoch(train) [44][100/925] lr: 9.6050e-05 eta: 3:42:36 time: 0.4436 data_time: 0.0730 memory: 5532 grad_norm: 937.8953 loss: 422.0641 loss_cls: 152.4509 loss_bbox: 127.2444 loss_dfl: 142.3687 +2024/01/19 16:54:23 - mmengine - INFO - Epoch(train) [44][150/925] lr: 9.6050e-05 eta: 3:42:17 time: 0.3887 data_time: 0.0554 memory: 5399 grad_norm: 968.8750 loss: 432.6176 loss_cls: 159.3801 loss_bbox: 128.7074 loss_dfl: 144.5301 +2024/01/19 16:54:43 - mmengine - INFO - Epoch(train) [44][200/925] lr: 9.6050e-05 eta: 3:41:57 time: 0.3858 data_time: 0.0026 memory: 5466 grad_norm: 1080.6193 loss: 421.4726 loss_cls: 151.9171 loss_bbox: 127.7543 loss_dfl: 141.8012 +2024/01/19 16:54:53 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:55:02 - mmengine - INFO - Epoch(train) [44][250/925] lr: 9.6050e-05 eta: 3:41:37 time: 0.3908 data_time: 0.0024 memory: 5226 grad_norm: 982.4817 loss: 428.0424 loss_cls: 156.1096 loss_bbox: 128.3290 loss_dfl: 143.6038 +2024/01/19 16:55:21 - mmengine - INFO - Epoch(train) [44][300/925] lr: 9.6050e-05 eta: 3:41:17 time: 0.3688 data_time: 0.0074 memory: 5412 grad_norm: 1158.4676 loss: 427.8469 loss_cls: 156.0837 loss_bbox: 128.1658 loss_dfl: 143.5973 +2024/01/19 16:55:44 - mmengine - INFO - Epoch(train) [44][350/925] lr: 9.6050e-05 eta: 3:41:00 time: 0.4695 data_time: 0.0387 memory: 5759 grad_norm: 940.5451 loss: 424.7875 loss_cls: 153.2060 loss_bbox: 129.3304 loss_dfl: 142.2510 +2024/01/19 16:56:06 - mmengine - INFO - Epoch(train) [44][400/925] lr: 9.6050e-05 eta: 3:40:43 time: 0.4359 data_time: 0.0492 memory: 5372 grad_norm: 955.8895 loss: 422.5685 loss_cls: 153.6327 loss_bbox: 126.8325 loss_dfl: 142.1032 +2024/01/19 16:56:27 - mmengine - INFO - Epoch(train) [44][450/925] lr: 9.6050e-05 eta: 3:40:24 time: 0.4178 data_time: 0.0392 memory: 5693 grad_norm: 1093.5249 loss: 430.5245 loss_cls: 157.8633 loss_bbox: 129.1610 loss_dfl: 143.5002 +2024/01/19 16:56:47 - mmengine - INFO - Epoch(train) [44][500/925] lr: 9.6050e-05 eta: 3:40:05 time: 0.3953 data_time: 0.0278 memory: 5092 grad_norm: 953.3888 loss: 425.8562 loss_cls: 154.6927 loss_bbox: 128.8852 loss_dfl: 142.2783 +2024/01/19 16:57:05 - mmengine - INFO - Epoch(train) [44][550/925] lr: 9.6050e-05 eta: 3:39:45 time: 0.3731 data_time: 0.0027 memory: 5306 grad_norm: 1090.5354 loss: 425.1413 loss_cls: 154.7143 loss_bbox: 127.7592 loss_dfl: 142.6678 +2024/01/19 16:57:25 - mmengine - INFO - Epoch(train) [44][600/925] lr: 9.6050e-05 eta: 3:39:25 time: 0.3911 data_time: 0.0027 memory: 5759 grad_norm: 1036.9228 loss: 426.1070 loss_cls: 155.7483 loss_bbox: 127.9880 loss_dfl: 142.3707 +2024/01/19 16:57:50 - mmengine - INFO - Epoch(train) [44][650/925] lr: 9.6050e-05 eta: 3:39:10 time: 0.5060 data_time: 0.1366 memory: 5693 grad_norm: 1067.8391 loss: 425.6761 loss_cls: 155.3712 loss_bbox: 127.5168 loss_dfl: 142.7881 +2024/01/19 16:58:09 - mmengine - INFO - Epoch(train) [44][700/925] lr: 9.6050e-05 eta: 3:38:50 time: 0.3729 data_time: 0.0028 memory: 5292 grad_norm: 955.3831 loss: 426.3143 loss_cls: 155.0310 loss_bbox: 127.5561 loss_dfl: 143.7273 +2024/01/19 16:58:27 - mmengine - INFO - Epoch(train) [44][750/925] lr: 9.6050e-05 eta: 3:38:29 time: 0.3668 data_time: 0.0024 memory: 5452 grad_norm: 898.5022 loss: 427.3249 loss_cls: 155.7561 loss_bbox: 128.3791 loss_dfl: 143.1897 +2024/01/19 16:58:46 - mmengine - INFO - Epoch(train) [44][800/925] lr: 9.6050e-05 eta: 3:38:09 time: 0.3776 data_time: 0.0027 memory: 5492 grad_norm: 1188.3402 loss: 425.0143 loss_cls: 152.6717 loss_bbox: 128.8638 loss_dfl: 143.4788 +2024/01/19 16:59:06 - mmengine - INFO - Epoch(train) [44][850/925] lr: 9.6050e-05 eta: 3:37:49 time: 0.3835 data_time: 0.0025 memory: 5239 grad_norm: 965.8219 loss: 420.0284 loss_cls: 151.2410 loss_bbox: 126.5919 loss_dfl: 142.1956 +2024/01/19 16:59:24 - mmengine - INFO - Epoch(train) [44][900/925] lr: 9.6050e-05 eta: 3:37:29 time: 0.3699 data_time: 0.0023 memory: 5252 grad_norm: 1146.2157 loss: 425.0973 loss_cls: 154.2245 loss_bbox: 127.6221 loss_dfl: 143.2507 +2024/01/19 16:59:33 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 16:59:58 - mmengine - INFO - Epoch(train) [45][ 50/925] lr: 9.3575e-05 eta: 3:37:02 time: 0.4777 data_time: 0.0897 memory: 5919 grad_norm: 943.2885 loss: 421.7310 loss_cls: 151.8215 loss_bbox: 127.4197 loss_dfl: 142.4899 +2024/01/19 17:00:17 - mmengine - INFO - Epoch(train) [45][100/925] lr: 9.3575e-05 eta: 3:36:43 time: 0.3921 data_time: 0.0025 memory: 5372 grad_norm: 975.7328 loss: 423.0154 loss_cls: 151.9606 loss_bbox: 127.9359 loss_dfl: 143.1189 +2024/01/19 17:00:37 - mmengine - INFO - Epoch(train) [45][150/925] lr: 9.3575e-05 eta: 3:36:23 time: 0.3852 data_time: 0.0022 memory: 5346 grad_norm: 1002.1703 loss: 425.1061 loss_cls: 154.7507 loss_bbox: 127.5127 loss_dfl: 142.8427 +2024/01/19 17:00:57 - mmengine - INFO - Epoch(train) [45][200/925] lr: 9.3575e-05 eta: 3:36:04 time: 0.3983 data_time: 0.0026 memory: 5092 grad_norm: 1073.7666 loss: 425.3436 loss_cls: 155.0277 loss_bbox: 127.1472 loss_dfl: 143.1688 +2024/01/19 17:01:16 - mmengine - INFO - Epoch(train) [45][250/925] lr: 9.3575e-05 eta: 3:35:44 time: 0.3816 data_time: 0.0023 memory: 5466 grad_norm: 944.8502 loss: 427.8697 loss_cls: 157.5521 loss_bbox: 127.4092 loss_dfl: 142.9084 +2024/01/19 17:01:34 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:01:34 - mmengine - INFO - Epoch(train) [45][300/925] lr: 9.3575e-05 eta: 3:35:23 time: 0.3719 data_time: 0.0025 memory: 5666 grad_norm: 928.9158 loss: 428.4834 loss_cls: 157.1426 loss_bbox: 127.7875 loss_dfl: 143.5533 +2024/01/19 17:01:54 - mmengine - INFO - Epoch(train) [45][350/925] lr: 9.3575e-05 eta: 3:35:04 time: 0.3951 data_time: 0.0046 memory: 5372 grad_norm: 1081.6905 loss: 425.6304 loss_cls: 153.9023 loss_bbox: 128.0038 loss_dfl: 143.7242 +2024/01/19 17:02:13 - mmengine - INFO - Epoch(train) [45][400/925] lr: 9.3575e-05 eta: 3:34:43 time: 0.3697 data_time: 0.0025 memory: 5546 grad_norm: 983.4957 loss: 423.1632 loss_cls: 154.5175 loss_bbox: 126.3683 loss_dfl: 142.2774 +2024/01/19 17:02:32 - mmengine - INFO - Epoch(train) [45][450/925] lr: 9.3575e-05 eta: 3:34:23 time: 0.3826 data_time: 0.0032 memory: 5399 grad_norm: 1071.1794 loss: 419.1193 loss_cls: 150.6485 loss_bbox: 125.9612 loss_dfl: 142.5097 +2024/01/19 17:02:51 - mmengine - INFO - Epoch(train) [45][500/925] lr: 9.3575e-05 eta: 3:34:04 time: 0.3833 data_time: 0.0022 memory: 5652 grad_norm: 1061.4695 loss: 422.3502 loss_cls: 152.9285 loss_bbox: 127.2640 loss_dfl: 142.1577 +2024/01/19 17:03:10 - mmengine - INFO - Epoch(train) [45][550/925] lr: 9.3575e-05 eta: 3:33:43 time: 0.3765 data_time: 0.0035 memory: 5626 grad_norm: 943.6127 loss: 421.7062 loss_cls: 153.1112 loss_bbox: 127.2038 loss_dfl: 141.3912 +2024/01/19 17:03:29 - mmengine - INFO - Epoch(train) [45][600/925] lr: 9.3575e-05 eta: 3:33:23 time: 0.3832 data_time: 0.0023 memory: 5332 grad_norm: 1079.0381 loss: 420.7852 loss_cls: 153.8514 loss_bbox: 125.1302 loss_dfl: 141.8036 +2024/01/19 17:03:48 - mmengine - INFO - Epoch(train) [45][650/925] lr: 9.3575e-05 eta: 3:33:04 time: 0.3839 data_time: 0.0026 memory: 5172 grad_norm: 1030.2677 loss: 429.9512 loss_cls: 156.3508 loss_bbox: 129.7175 loss_dfl: 143.8829 +2024/01/19 17:04:08 - mmengine - INFO - Epoch(train) [45][700/925] lr: 9.3575e-05 eta: 3:32:44 time: 0.3951 data_time: 0.0036 memory: 5706 grad_norm: inf loss: 414.0119 loss_cls: 148.5241 loss_bbox: 124.5142 loss_dfl: 140.9737 +2024/01/19 17:04:27 - mmengine - INFO - Epoch(train) [45][750/925] lr: 9.3575e-05 eta: 3:32:24 time: 0.3729 data_time: 0.0022 memory: 5426 grad_norm: 1054.8768 loss: 434.4961 loss_cls: 159.5904 loss_bbox: 130.5528 loss_dfl: 144.3529 +2024/01/19 17:04:45 - mmengine - INFO - Epoch(train) [45][800/925] lr: 9.3575e-05 eta: 3:32:03 time: 0.3708 data_time: 0.0030 memory: 5106 grad_norm: 1014.2952 loss: 424.8677 loss_cls: 154.0873 loss_bbox: 127.3398 loss_dfl: 143.4406 +2024/01/19 17:05:05 - mmengine - INFO - Epoch(train) [45][850/925] lr: 9.3575e-05 eta: 3:31:44 time: 0.3933 data_time: 0.0026 memory: 5279 grad_norm: 1046.4931 loss: 418.5234 loss_cls: 150.7011 loss_bbox: 126.3916 loss_dfl: 141.4307 +2024/01/19 17:05:24 - mmengine - INFO - Epoch(train) [45][900/925] lr: 9.3575e-05 eta: 3:31:24 time: 0.3704 data_time: 0.0041 memory: 5559 grad_norm: 1108.6252 loss: 420.6909 loss_cls: 152.1462 loss_bbox: 126.7739 loss_dfl: 141.7708 +2024/01/19 17:05:33 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:05:33 - mmengine - INFO - Saving checkpoint at 45 epochs +2024/01/19 17:05:42 - mmengine - INFO - Epoch(val) [45][ 50/625] eta: 0:00:20 time: 0.0357 data_time: 0.0009 memory: 5399 +2024/01/19 17:05:44 - mmengine - INFO - Epoch(val) [45][100/625] eta: 0:00:18 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 17:05:46 - mmengine - INFO - Epoch(val) [45][150/625] eta: 0:00:17 time: 0.0369 data_time: 0.0004 memory: 843 +2024/01/19 17:05:47 - mmengine - INFO - Epoch(val) [45][200/625] eta: 0:00:15 time: 0.0363 data_time: 0.0003 memory: 843 +2024/01/19 17:05:49 - mmengine - INFO - Epoch(val) [45][250/625] eta: 0:00:13 time: 0.0343 data_time: 0.0004 memory: 843 +2024/01/19 17:05:51 - mmengine - INFO - Epoch(val) [45][300/625] eta: 0:00:11 time: 0.0364 data_time: 0.0003 memory: 843 +2024/01/19 17:05:53 - mmengine - INFO - Epoch(val) [45][350/625] eta: 0:00:09 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 17:05:54 - mmengine - INFO - Epoch(val) [45][400/625] eta: 0:00:08 time: 0.0356 data_time: 0.0003 memory: 843 +2024/01/19 17:05:56 - mmengine - INFO - Epoch(val) [45][450/625] eta: 0:00:06 time: 0.0305 data_time: 0.0003 memory: 843 +2024/01/19 17:05:57 - mmengine - INFO - Epoch(val) [45][500/625] eta: 0:00:04 time: 0.0259 data_time: 0.0002 memory: 843 +2024/01/19 17:05:59 - mmengine - INFO - Epoch(val) [45][550/625] eta: 0:00:02 time: 0.0257 data_time: 0.0002 memory: 843 +2024/01/19 17:06:00 - mmengine - INFO - Epoch(val) [45][600/625] eta: 0:00:00 time: 0.0255 data_time: 0.0002 memory: 843 +2024/01/19 17:06:14 - mmengine - INFO - Evaluating bbox... +2024/01/19 17:07:34 - mmengine - INFO - bbox_mAP_copypaste: 0.451 0.612 0.492 0.252 0.500 0.610 +2024/01/19 17:07:37 - mmengine - INFO - Epoch(val) [45][625/625] coco/bbox_mAP: 0.4510 coco/bbox_mAP_50: 0.6120 coco/bbox_mAP_75: 0.4920 coco/bbox_mAP_s: 0.2520 coco/bbox_mAP_m: 0.5000 coco/bbox_mAP_l: 0.6100 data_time: 0.0002 time: 0.0257 +2024/01/19 17:07:58 - mmengine - INFO - Epoch(train) [46][ 50/925] lr: 9.1100e-05 eta: 3:30:55 time: 0.4329 data_time: 0.0774 memory: 5439 grad_norm: 1024.1364 loss: 424.3027 loss_cls: 154.4440 loss_bbox: 127.2677 loss_dfl: 142.5910 +2024/01/19 17:08:17 - mmengine - INFO - Epoch(train) [46][100/925] lr: 9.1100e-05 eta: 3:30:35 time: 0.3824 data_time: 0.0041 memory: 5559 grad_norm: 1111.7283 loss: 422.9618 loss_cls: 152.8298 loss_bbox: 127.4846 loss_dfl: 142.6474 +2024/01/19 17:08:35 - mmengine - INFO - Epoch(train) [46][150/925] lr: 9.1100e-05 eta: 3:30:14 time: 0.3549 data_time: 0.0024 memory: 5399 grad_norm: 973.7521 loss: 429.5346 loss_cls: 157.6354 loss_bbox: 128.2747 loss_dfl: 143.6245 +2024/01/19 17:08:54 - mmengine - INFO - Epoch(train) [46][200/925] lr: 9.1100e-05 eta: 3:29:54 time: 0.3744 data_time: 0.0025 memory: 5652 grad_norm: 1062.1877 loss: 417.4262 loss_cls: 150.0073 loss_bbox: 125.6485 loss_dfl: 141.7703 +2024/01/19 17:09:13 - mmengine - INFO - Epoch(train) [46][250/925] lr: 9.1100e-05 eta: 3:29:34 time: 0.3726 data_time: 0.0023 memory: 5826 grad_norm: 1105.5990 loss: 426.0154 loss_cls: 154.2985 loss_bbox: 128.9871 loss_dfl: 142.7299 +2024/01/19 17:09:31 - mmengine - INFO - Epoch(train) [46][300/925] lr: 9.1100e-05 eta: 3:29:13 time: 0.3722 data_time: 0.0026 memory: 5292 grad_norm: 937.6010 loss: 418.5772 loss_cls: 152.5712 loss_bbox: 125.0970 loss_dfl: 140.9090 +2024/01/19 17:09:51 - mmengine - INFO - Epoch(train) [46][350/925] lr: 9.1100e-05 eta: 3:28:54 time: 0.3880 data_time: 0.0025 memory: 5666 grad_norm: 992.4793 loss: 430.0587 loss_cls: 159.0604 loss_bbox: 128.1483 loss_dfl: 142.8500 +2024/01/19 17:10:00 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:10:10 - mmengine - INFO - Epoch(train) [46][400/925] lr: 9.1100e-05 eta: 3:28:34 time: 0.3847 data_time: 0.0025 memory: 5679 grad_norm: 1075.0648 loss: 426.0863 loss_cls: 156.4915 loss_bbox: 126.5838 loss_dfl: 143.0110 +2024/01/19 17:10:29 - mmengine - INFO - Epoch(train) [46][450/925] lr: 9.1100e-05 eta: 3:28:14 time: 0.3730 data_time: 0.0026 memory: 5292 grad_norm: 1051.2337 loss: 430.4007 loss_cls: 155.5282 loss_bbox: 130.9541 loss_dfl: 143.9184 +2024/01/19 17:10:47 - mmengine - INFO - Epoch(train) [46][500/925] lr: 9.1100e-05 eta: 3:27:53 time: 0.3742 data_time: 0.0024 memory: 5612 grad_norm: 1118.2543 loss: 425.6355 loss_cls: 154.2940 loss_bbox: 129.2716 loss_dfl: 142.0699 +2024/01/19 17:11:05 - mmengine - INFO - Epoch(train) [46][550/925] lr: 9.1100e-05 eta: 3:27:32 time: 0.3538 data_time: 0.0023 memory: 5506 grad_norm: 1047.2936 loss: 419.3654 loss_cls: 151.3361 loss_bbox: 126.3492 loss_dfl: 141.6800 +2024/01/19 17:11:24 - mmengine - INFO - Epoch(train) [46][600/925] lr: 9.1100e-05 eta: 3:27:12 time: 0.3775 data_time: 0.0023 memory: 5332 grad_norm: 1080.6444 loss: 426.5864 loss_cls: 156.7702 loss_bbox: 126.5675 loss_dfl: 143.2487 +2024/01/19 17:11:43 - mmengine - INFO - Epoch(train) [46][650/925] lr: 9.1100e-05 eta: 3:26:52 time: 0.3704 data_time: 0.0023 memory: 5492 grad_norm: 1106.8711 loss: 427.5410 loss_cls: 154.7109 loss_bbox: 129.4575 loss_dfl: 143.3726 +2024/01/19 17:12:01 - mmengine - INFO - Epoch(train) [46][700/925] lr: 9.1100e-05 eta: 3:26:32 time: 0.3700 data_time: 0.0026 memory: 5492 grad_norm: 1157.3799 loss: 425.7087 loss_cls: 155.0742 loss_bbox: 128.0070 loss_dfl: 142.6276 +2024/01/19 17:12:21 - mmengine - INFO - Epoch(train) [46][750/925] lr: 9.1100e-05 eta: 3:26:12 time: 0.3903 data_time: 0.0025 memory: 5666 grad_norm: 903.1208 loss: 415.6046 loss_cls: 149.1067 loss_bbox: 125.4274 loss_dfl: 141.0704 +2024/01/19 17:12:39 - mmengine - INFO - Epoch(train) [46][800/925] lr: 9.1100e-05 eta: 3:25:51 time: 0.3565 data_time: 0.0025 memory: 5652 grad_norm: 921.6141 loss: 421.8677 loss_cls: 152.5255 loss_bbox: 126.8812 loss_dfl: 142.4610 +2024/01/19 17:12:57 - mmengine - INFO - Epoch(train) [46][850/925] lr: 9.1100e-05 eta: 3:25:31 time: 0.3608 data_time: 0.0030 memory: 5866 grad_norm: 1120.3894 loss: 420.9307 loss_cls: 153.3785 loss_bbox: 125.8714 loss_dfl: 141.6808 +2024/01/19 17:13:15 - mmengine - INFO - Epoch(train) [46][900/925] lr: 9.1100e-05 eta: 3:25:10 time: 0.3761 data_time: 0.0036 memory: 5372 grad_norm: 911.8440 loss: 423.6058 loss_cls: 154.0492 loss_bbox: 127.3709 loss_dfl: 142.1857 +2024/01/19 17:13:24 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:13:47 - mmengine - INFO - Epoch(train) [47][ 50/925] lr: 8.8625e-05 eta: 3:24:43 time: 0.4524 data_time: 0.1020 memory: 5399 grad_norm: 933.1722 loss: 423.6496 loss_cls: 154.0069 loss_bbox: 127.6352 loss_dfl: 142.0074 +2024/01/19 17:14:05 - mmengine - INFO - Epoch(train) [47][100/925] lr: 8.8625e-05 eta: 3:24:22 time: 0.3630 data_time: 0.0035 memory: 5746 grad_norm: 988.4767 loss: 423.9788 loss_cls: 154.5645 loss_bbox: 127.5598 loss_dfl: 141.8544 +2024/01/19 17:14:24 - mmengine - INFO - Epoch(train) [47][150/925] lr: 8.8625e-05 eta: 3:24:01 time: 0.3620 data_time: 0.0033 memory: 5372 grad_norm: 1010.9789 loss: 434.1612 loss_cls: 157.9462 loss_bbox: 131.3675 loss_dfl: 144.8475 +2024/01/19 17:14:42 - mmengine - INFO - Epoch(train) [47][200/925] lr: 8.8625e-05 eta: 3:23:41 time: 0.3737 data_time: 0.0026 memory: 5266 grad_norm: 1027.3377 loss: 427.1492 loss_cls: 155.1606 loss_bbox: 129.1122 loss_dfl: 142.8764 +2024/01/19 17:15:01 - mmengine - INFO - Epoch(train) [47][250/925] lr: 8.8625e-05 eta: 3:23:21 time: 0.3767 data_time: 0.0055 memory: 5479 grad_norm: 1026.4718 loss: 430.2062 loss_cls: 157.0577 loss_bbox: 129.3257 loss_dfl: 143.8228 +2024/01/19 17:15:19 - mmengine - INFO - Epoch(train) [47][300/925] lr: 8.8625e-05 eta: 3:23:00 time: 0.3491 data_time: 0.0026 memory: 5546 grad_norm: 1091.3977 loss: 427.3825 loss_cls: 155.3916 loss_bbox: 128.0723 loss_dfl: 143.9186 +2024/01/19 17:15:38 - mmengine - INFO - Epoch(train) [47][350/925] lr: 8.8625e-05 eta: 3:22:40 time: 0.3899 data_time: 0.0033 memory: 5719 grad_norm: 1025.5463 loss: 423.5277 loss_cls: 154.0001 loss_bbox: 126.8559 loss_dfl: 142.6717 +2024/01/19 17:15:57 - mmengine - INFO - Epoch(train) [47][400/925] lr: 8.8625e-05 eta: 3:22:20 time: 0.3690 data_time: 0.0025 memory: 5266 grad_norm: 1124.9806 loss: 420.5292 loss_cls: 149.7161 loss_bbox: 128.4225 loss_dfl: 142.3906 +2024/01/19 17:16:15 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:16:15 - mmengine - INFO - Epoch(train) [47][450/925] lr: 8.8625e-05 eta: 3:22:00 time: 0.3666 data_time: 0.0026 memory: 5546 grad_norm: 968.6255 loss: 424.0024 loss_cls: 154.0998 loss_bbox: 127.5751 loss_dfl: 142.3275 +2024/01/19 17:16:33 - mmengine - INFO - Epoch(train) [47][500/925] lr: 8.8625e-05 eta: 3:21:39 time: 0.3641 data_time: 0.0026 memory: 5319 grad_norm: 962.8205 loss: 418.7417 loss_cls: 149.7604 loss_bbox: 127.6942 loss_dfl: 141.2872 +2024/01/19 17:16:52 - mmengine - INFO - Epoch(train) [47][550/925] lr: 8.8625e-05 eta: 3:21:19 time: 0.3824 data_time: 0.0028 memory: 5666 grad_norm: 995.3691 loss: 419.6404 loss_cls: 151.3500 loss_bbox: 126.2468 loss_dfl: 142.0435 +2024/01/19 17:17:11 - mmengine - INFO - Epoch(train) [47][600/925] lr: 8.8625e-05 eta: 3:20:59 time: 0.3749 data_time: 0.0025 memory: 5159 grad_norm: 944.3273 loss: 424.7680 loss_cls: 153.7619 loss_bbox: 128.4456 loss_dfl: 142.5606 +2024/01/19 17:17:29 - mmengine - INFO - Epoch(train) [47][650/925] lr: 8.8625e-05 eta: 3:20:39 time: 0.3599 data_time: 0.0022 memory: 5519 grad_norm: 984.3442 loss: 427.9055 loss_cls: 155.3500 loss_bbox: 128.6496 loss_dfl: 143.9059 +2024/01/19 17:17:49 - mmengine - INFO - Epoch(train) [47][700/925] lr: 8.8625e-05 eta: 3:20:19 time: 0.3856 data_time: 0.0028 memory: 5412 grad_norm: 954.0488 loss: 426.2305 loss_cls: 155.3602 loss_bbox: 128.1980 loss_dfl: 142.6724 +2024/01/19 17:18:09 - mmengine - INFO - Epoch(train) [47][750/925] lr: 8.8625e-05 eta: 3:19:59 time: 0.3980 data_time: 0.0033 memory: 5399 grad_norm: 1035.1897 loss: 416.5553 loss_cls: 149.2661 loss_bbox: 126.2081 loss_dfl: 141.0811 +2024/01/19 17:18:26 - mmengine - INFO - Epoch(train) [47][800/925] lr: 8.8625e-05 eta: 3:19:39 time: 0.3531 data_time: 0.0025 memory: 5719 grad_norm: 992.2572 loss: 426.5475 loss_cls: 155.6263 loss_bbox: 128.2942 loss_dfl: 142.6270 +2024/01/19 17:18:46 - mmengine - INFO - Epoch(train) [47][850/925] lr: 8.8625e-05 eta: 3:19:19 time: 0.3929 data_time: 0.0037 memory: 5519 grad_norm: 1030.6390 loss: 421.2517 loss_cls: 152.0947 loss_bbox: 126.7761 loss_dfl: 142.3809 +2024/01/19 17:19:05 - mmengine - INFO - Epoch(train) [47][900/925] lr: 8.8625e-05 eta: 3:19:00 time: 0.3904 data_time: 0.0028 memory: 5626 grad_norm: 1033.3060 loss: 421.9234 loss_cls: 152.4010 loss_bbox: 127.4760 loss_dfl: 142.0464 +2024/01/19 17:19:15 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:19:38 - mmengine - INFO - Epoch(train) [48][ 50/925] lr: 8.6150e-05 eta: 3:18:32 time: 0.4521 data_time: 0.0902 memory: 5372 grad_norm: inf loss: 418.9040 loss_cls: 150.2031 loss_bbox: 126.6432 loss_dfl: 142.0576 +2024/01/19 17:19:58 - mmengine - INFO - Epoch(train) [48][100/925] lr: 8.6150e-05 eta: 3:18:13 time: 0.3949 data_time: 0.0045 memory: 5386 grad_norm: 995.3564 loss: 428.5511 loss_cls: 155.0233 loss_bbox: 129.9110 loss_dfl: 143.6169 +2024/01/19 17:20:17 - mmengine - INFO - Epoch(train) [48][150/925] lr: 8.6150e-05 eta: 3:17:53 time: 0.3954 data_time: 0.0023 memory: 5159 grad_norm: 997.0174 loss: 419.0779 loss_cls: 151.1272 loss_bbox: 126.5333 loss_dfl: 141.4173 +2024/01/19 17:20:36 - mmengine - INFO - Epoch(train) [48][200/925] lr: 8.6150e-05 eta: 3:17:33 time: 0.3740 data_time: 0.0024 memory: 5386 grad_norm: 1055.0621 loss: 428.0643 loss_cls: 156.6144 loss_bbox: 128.0764 loss_dfl: 143.3735 +2024/01/19 17:20:59 - mmengine - INFO - Epoch(train) [48][250/925] lr: 8.6150e-05 eta: 3:17:16 time: 0.4549 data_time: 0.0820 memory: 5399 grad_norm: 1085.8799 loss: 428.5658 loss_cls: 157.5844 loss_bbox: 127.9720 loss_dfl: 143.0094 +2024/01/19 17:21:23 - mmengine - INFO - Epoch(train) [48][300/925] lr: 8.6150e-05 eta: 3:16:59 time: 0.4780 data_time: 0.0767 memory: 5346 grad_norm: 1021.9713 loss: 427.8777 loss_cls: 155.0697 loss_bbox: 130.1740 loss_dfl: 142.6340 +2024/01/19 17:21:46 - mmengine - INFO - Epoch(train) [48][350/925] lr: 8.6150e-05 eta: 3:16:42 time: 0.4563 data_time: 0.0240 memory: 5506 grad_norm: 995.1363 loss: 418.6220 loss_cls: 150.5867 loss_bbox: 126.0746 loss_dfl: 141.9607 +2024/01/19 17:22:06 - mmengine - INFO - Epoch(train) [48][400/925] lr: 8.6150e-05 eta: 3:16:23 time: 0.4124 data_time: 0.0028 memory: 5186 grad_norm: 953.3519 loss: 427.8154 loss_cls: 157.6224 loss_bbox: 127.0464 loss_dfl: 143.1466 +2024/01/19 17:22:27 - mmengine - INFO - Epoch(train) [48][450/925] lr: 8.6150e-05 eta: 3:16:04 time: 0.4119 data_time: 0.0035 memory: 5292 grad_norm: 958.6341 loss: 426.9783 loss_cls: 155.0143 loss_bbox: 128.2091 loss_dfl: 143.7549 +2024/01/19 17:22:53 - mmengine - INFO - Epoch(train) [48][500/925] lr: 8.6150e-05 eta: 3:15:49 time: 0.5245 data_time: 0.0148 memory: 5332 grad_norm: 946.5057 loss: 430.1934 loss_cls: 156.5431 loss_bbox: 130.4879 loss_dfl: 143.1624 +2024/01/19 17:23:08 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:23:24 - mmengine - INFO - Epoch(train) [48][550/925] lr: 8.6150e-05 eta: 3:15:37 time: 0.6115 data_time: 0.0024 memory: 5639 grad_norm: 1092.7192 loss: 419.3486 loss_cls: 151.3850 loss_bbox: 126.0167 loss_dfl: 141.9469 +2024/01/19 17:23:54 - mmengine - INFO - Epoch(train) [48][600/925] lr: 8.6150e-05 eta: 3:15:25 time: 0.6066 data_time: 0.0023 memory: 5652 grad_norm: 1071.2376 loss: 425.2094 loss_cls: 154.9414 loss_bbox: 127.8789 loss_dfl: 142.3891 +2024/01/19 17:24:27 - mmengine - INFO - Epoch(train) [48][650/925] lr: 8.6150e-05 eta: 3:15:14 time: 0.6518 data_time: 0.0027 memory: 5866 grad_norm: 1099.3046 loss: 426.5886 loss_cls: 155.5229 loss_bbox: 128.2154 loss_dfl: 142.8504 +2024/01/19 17:24:58 - mmengine - INFO - Epoch(train) [48][700/925] lr: 8.6150e-05 eta: 3:15:03 time: 0.6317 data_time: 0.0024 memory: 5452 grad_norm: 1166.9740 loss: 418.6883 loss_cls: 151.5788 loss_bbox: 125.5263 loss_dfl: 141.5832 +2024/01/19 17:25:35 - mmengine - INFO - Epoch(train) [48][750/925] lr: 8.6150e-05 eta: 3:14:54 time: 0.7281 data_time: 0.0022 memory: 5426 grad_norm: 1014.0666 loss: 416.5196 loss_cls: 151.2416 loss_bbox: 123.9882 loss_dfl: 141.2897 +2024/01/19 17:26:01 - mmengine - INFO - Epoch(train) [48][800/925] lr: 8.6150e-05 eta: 3:14:39 time: 0.5285 data_time: 0.0024 memory: 5732 grad_norm: 983.6748 loss: 422.9758 loss_cls: 153.3842 loss_bbox: 126.1517 loss_dfl: 143.4400 +2024/01/19 17:26:28 - mmengine - INFO - Epoch(train) [48][850/925] lr: 8.6150e-05 eta: 3:14:24 time: 0.5371 data_time: 0.0024 memory: 5226 grad_norm: 1078.7655 loss: 422.2527 loss_cls: 151.9706 loss_bbox: 127.8782 loss_dfl: 142.4038 +2024/01/19 17:26:49 - mmengine - INFO - Epoch(train) [48][900/925] lr: 8.6150e-05 eta: 3:14:05 time: 0.4054 data_time: 0.0024 memory: 5292 grad_norm: 939.0622 loss: 416.5238 loss_cls: 151.1582 loss_bbox: 124.7958 loss_dfl: 140.5697 +2024/01/19 17:27:02 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:27:36 - mmengine - INFO - Epoch(train) [49][ 50/925] lr: 8.3675e-05 eta: 3:13:48 time: 0.6878 data_time: 0.1963 memory: 5386 grad_norm: 952.0599 loss: 425.1122 loss_cls: 154.3088 loss_bbox: 128.1659 loss_dfl: 142.6374 +2024/01/19 17:28:02 - mmengine - INFO - Epoch(train) [49][100/925] lr: 8.3675e-05 eta: 3:13:32 time: 0.5069 data_time: 0.0027 memory: 5319 grad_norm: 929.1431 loss: 420.8609 loss_cls: 153.0593 loss_bbox: 126.1862 loss_dfl: 141.6154 +2024/01/19 17:28:24 - mmengine - INFO - Epoch(train) [49][150/925] lr: 8.3675e-05 eta: 3:13:14 time: 0.4522 data_time: 0.0023 memory: 5372 grad_norm: 1051.0843 loss: 420.5177 loss_cls: 152.5688 loss_bbox: 125.7909 loss_dfl: 142.1581 +2024/01/19 17:28:55 - mmengine - INFO - Epoch(train) [49][200/925] lr: 8.3675e-05 eta: 3:13:01 time: 0.6095 data_time: 0.0022 memory: 5346 grad_norm: 1032.9578 loss: 423.8860 loss_cls: 153.7892 loss_bbox: 127.3356 loss_dfl: 142.7612 +2024/01/19 17:29:19 - mmengine - INFO - Epoch(train) [49][250/925] lr: 8.3675e-05 eta: 3:12:45 time: 0.4819 data_time: 0.0068 memory: 5652 grad_norm: 900.1480 loss: 422.1511 loss_cls: 153.3832 loss_bbox: 127.5074 loss_dfl: 141.2605 +2024/01/19 17:29:40 - mmengine - INFO - Epoch(train) [49][300/925] lr: 8.3675e-05 eta: 3:12:25 time: 0.4103 data_time: 0.0024 memory: 5412 grad_norm: 1021.3420 loss: 432.4386 loss_cls: 158.4431 loss_bbox: 130.1379 loss_dfl: 143.8575 +2024/01/19 17:29:58 - mmengine - INFO - Epoch(train) [49][350/925] lr: 8.3675e-05 eta: 3:12:05 time: 0.3593 data_time: 0.0026 memory: 5466 grad_norm: 997.0493 loss: 421.4044 loss_cls: 153.6265 loss_bbox: 126.3766 loss_dfl: 141.4012 +2024/01/19 17:30:22 - mmengine - INFO - Epoch(train) [49][400/925] lr: 8.3675e-05 eta: 3:11:48 time: 0.4827 data_time: 0.0025 memory: 5679 grad_norm: 1031.0426 loss: 423.5364 loss_cls: 154.0920 loss_bbox: 126.5940 loss_dfl: 142.8504 +2024/01/19 17:30:49 - mmengine - INFO - Epoch(train) [49][450/925] lr: 8.3675e-05 eta: 3:11:33 time: 0.5480 data_time: 0.0025 memory: 5386 grad_norm: 990.0308 loss: 428.8101 loss_cls: 156.5428 loss_bbox: 128.8952 loss_dfl: 143.3721 +2024/01/19 17:31:15 - mmengine - INFO - Epoch(train) [49][500/925] lr: 8.3675e-05 eta: 3:11:17 time: 0.5224 data_time: 0.0101 memory: 5266 grad_norm: 969.5722 loss: 427.9517 loss_cls: 156.2356 loss_bbox: 128.9057 loss_dfl: 142.8104 +2024/01/19 17:31:38 - mmengine - INFO - Epoch(train) [49][550/925] lr: 8.3675e-05 eta: 3:11:00 time: 0.4574 data_time: 0.0128 memory: 5279 grad_norm: 977.1953 loss: 426.1856 loss_cls: 154.6798 loss_bbox: 127.8643 loss_dfl: 143.6415 +2024/01/19 17:32:06 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:32:06 - mmengine - INFO - Epoch(train) [49][600/925] lr: 8.3675e-05 eta: 3:10:45 time: 0.5613 data_time: 0.0248 memory: 5826 grad_norm: 1003.8237 loss: 427.2973 loss_cls: 155.5584 loss_bbox: 128.3957 loss_dfl: 143.3432 +2024/01/19 17:32:35 - mmengine - INFO - Epoch(train) [49][650/925] lr: 8.3675e-05 eta: 3:10:31 time: 0.5686 data_time: 0.0728 memory: 5546 grad_norm: 1122.9143 loss: 428.5071 loss_cls: 154.7565 loss_bbox: 129.6537 loss_dfl: 144.0969 +2024/01/19 17:33:02 - mmengine - INFO - Epoch(train) [49][700/925] lr: 8.3675e-05 eta: 3:10:16 time: 0.5347 data_time: 0.1421 memory: 5452 grad_norm: 961.2867 loss: 421.3271 loss_cls: 152.6500 loss_bbox: 126.7978 loss_dfl: 141.8794 +2024/01/19 17:33:23 - mmengine - INFO - Epoch(train) [49][750/925] lr: 8.3675e-05 eta: 3:09:57 time: 0.4219 data_time: 0.0536 memory: 5359 grad_norm: 969.0366 loss: 419.9827 loss_cls: 151.3105 loss_bbox: 126.6538 loss_dfl: 142.0184 +2024/01/19 17:33:54 - mmengine - INFO - Epoch(train) [49][800/925] lr: 8.3675e-05 eta: 3:09:45 time: 0.6194 data_time: 0.2315 memory: 5319 grad_norm: 963.6996 loss: 421.5638 loss_cls: 152.9086 loss_bbox: 126.5758 loss_dfl: 142.0794 +2024/01/19 17:34:20 - mmengine - INFO - Epoch(train) [49][850/925] lr: 8.3675e-05 eta: 3:09:29 time: 0.5347 data_time: 0.1329 memory: 5479 grad_norm: 944.8849 loss: 422.6932 loss_cls: 153.9060 loss_bbox: 126.8170 loss_dfl: 141.9702 +2024/01/19 17:34:47 - mmengine - INFO - Epoch(train) [49][900/925] lr: 8.3675e-05 eta: 3:09:13 time: 0.5230 data_time: 0.0313 memory: 5399 grad_norm: 1085.8040 loss: 426.5688 loss_cls: 155.3324 loss_bbox: 128.0498 loss_dfl: 143.1866 +2024/01/19 17:34:59 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:37:03 - mmengine - INFO - Epoch(train) [50][ 50/925] lr: 8.1200e-05 eta: 3:09:51 time: 2.4620 data_time: 1.9943 memory: 5546 grad_norm: 1077.4771 loss: 416.4352 loss_cls: 149.5480 loss_bbox: 124.8753 loss_dfl: 142.0119 +2024/01/19 17:37:33 - mmengine - INFO - Epoch(train) [50][100/925] lr: 8.1200e-05 eta: 3:09:37 time: 0.5932 data_time: 0.0495 memory: 5239 grad_norm: 946.2511 loss: 421.1670 loss_cls: 152.0839 loss_bbox: 126.2549 loss_dfl: 142.8282 +2024/01/19 17:38:05 - mmengine - INFO - Epoch(train) [50][150/925] lr: 8.1200e-05 eta: 3:09:25 time: 0.6457 data_time: 0.0799 memory: 5346 grad_norm: 939.5787 loss: 421.4323 loss_cls: 151.5150 loss_bbox: 126.9116 loss_dfl: 143.0057 +2024/01/19 17:38:28 - mmengine - INFO - Epoch(train) [50][200/925] lr: 8.1200e-05 eta: 3:09:07 time: 0.4672 data_time: 0.0327 memory: 5346 grad_norm: 1110.7882 loss: 423.4693 loss_cls: 153.3438 loss_bbox: 126.8700 loss_dfl: 143.2556 +2024/01/19 17:38:47 - mmengine - INFO - Epoch(train) [50][250/925] lr: 8.1200e-05 eta: 3:08:47 time: 0.3803 data_time: 0.0030 memory: 5212 grad_norm: 1143.6060 loss: 421.6293 loss_cls: 151.9716 loss_bbox: 127.4367 loss_dfl: 142.2210 +2024/01/19 17:39:05 - mmengine - INFO - Epoch(train) [50][300/925] lr: 8.1200e-05 eta: 3:08:25 time: 0.3618 data_time: 0.0040 memory: 5332 grad_norm: 1118.2218 loss: 420.2017 loss_cls: 153.0170 loss_bbox: 125.2962 loss_dfl: 141.8885 +2024/01/19 17:39:25 - mmengine - INFO - Epoch(train) [50][350/925] lr: 8.1200e-05 eta: 3:08:05 time: 0.3846 data_time: 0.0042 memory: 5532 grad_norm: 1025.5014 loss: 421.4127 loss_cls: 152.1950 loss_bbox: 127.1972 loss_dfl: 142.0205 +2024/01/19 17:39:44 - mmengine - INFO - Epoch(train) [50][400/925] lr: 8.1200e-05 eta: 3:07:45 time: 0.3771 data_time: 0.0050 memory: 5252 grad_norm: inf loss: 415.4481 loss_cls: 149.1121 loss_bbox: 125.2000 loss_dfl: 141.1360 +2024/01/19 17:40:03 - mmengine - INFO - Epoch(train) [50][450/925] lr: 8.1200e-05 eta: 3:07:24 time: 0.3777 data_time: 0.0024 memory: 5399 grad_norm: 1001.3428 loss: 424.9675 loss_cls: 153.6168 loss_bbox: 127.8571 loss_dfl: 143.4936 +2024/01/19 17:40:22 - mmengine - INFO - Epoch(train) [50][500/925] lr: 8.1200e-05 eta: 3:07:03 time: 0.3790 data_time: 0.0028 memory: 5412 grad_norm: 1013.7290 loss: 428.8020 loss_cls: 155.9952 loss_bbox: 129.2352 loss_dfl: 143.5717 +2024/01/19 17:40:40 - mmengine - INFO - Epoch(train) [50][550/925] lr: 8.1200e-05 eta: 3:06:43 time: 0.3661 data_time: 0.0025 memory: 5532 grad_norm: 949.3759 loss: 420.5634 loss_cls: 151.3131 loss_bbox: 126.9085 loss_dfl: 142.3418 +2024/01/19 17:40:59 - mmengine - INFO - Epoch(train) [50][600/925] lr: 8.1200e-05 eta: 3:06:22 time: 0.3791 data_time: 0.0025 memory: 5652 grad_norm: 1032.7236 loss: 425.6065 loss_cls: 154.2457 loss_bbox: 128.5503 loss_dfl: 142.8105 +2024/01/19 17:41:18 - mmengine - INFO - Epoch(train) [50][650/925] lr: 8.1200e-05 eta: 3:06:02 time: 0.3825 data_time: 0.0027 memory: 5319 grad_norm: 1061.7911 loss: 419.0293 loss_cls: 150.4641 loss_bbox: 126.2368 loss_dfl: 142.3283 +2024/01/19 17:41:28 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:41:37 - mmengine - INFO - Epoch(train) [50][700/925] lr: 8.1200e-05 eta: 3:05:41 time: 0.3850 data_time: 0.0044 memory: 5666 grad_norm: 948.9790 loss: 423.0195 loss_cls: 153.0664 loss_bbox: 127.3551 loss_dfl: 142.5980 +2024/01/19 17:41:56 - mmengine - INFO - Epoch(train) [50][750/925] lr: 8.1200e-05 eta: 3:05:21 time: 0.3739 data_time: 0.0025 memory: 5372 grad_norm: 1076.5479 loss: 421.9767 loss_cls: 151.7412 loss_bbox: 128.2354 loss_dfl: 142.0001 +2024/01/19 17:42:16 - mmengine - INFO - Epoch(train) [50][800/925] lr: 8.1200e-05 eta: 3:05:01 time: 0.3938 data_time: 0.0023 memory: 5452 grad_norm: 1052.2817 loss: 421.4925 loss_cls: 152.5850 loss_bbox: 126.8266 loss_dfl: 142.0808 +2024/01/19 17:42:36 - mmengine - INFO - Epoch(train) [50][850/925] lr: 8.1200e-05 eta: 3:04:41 time: 0.4131 data_time: 0.0036 memory: 5306 grad_norm: 997.9146 loss: 422.3343 loss_cls: 153.2365 loss_bbox: 127.3634 loss_dfl: 141.7344 +2024/01/19 17:42:56 - mmengine - INFO - Epoch(train) [50][900/925] lr: 8.1200e-05 eta: 3:04:21 time: 0.3903 data_time: 0.0024 memory: 5399 grad_norm: 1055.6178 loss: 420.0970 loss_cls: 152.5771 loss_bbox: 125.4843 loss_dfl: 142.0356 +2024/01/19 17:43:05 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:43:05 - mmengine - INFO - Saving checkpoint at 50 epochs +2024/01/19 17:43:14 - mmengine - INFO - Epoch(val) [50][ 50/625] eta: 0:00:21 time: 0.0367 data_time: 0.0008 memory: 5612 +2024/01/19 17:43:16 - mmengine - INFO - Epoch(val) [50][100/625] eta: 0:00:18 time: 0.0355 data_time: 0.0004 memory: 843 +2024/01/19 17:43:17 - mmengine - INFO - Epoch(val) [50][150/625] eta: 0:00:17 time: 0.0359 data_time: 0.0004 memory: 843 +2024/01/19 17:43:19 - mmengine - INFO - Epoch(val) [50][200/625] eta: 0:00:15 time: 0.0377 data_time: 0.0004 memory: 843 +2024/01/19 17:43:21 - mmengine - INFO - Epoch(val) [50][250/625] eta: 0:00:13 time: 0.0372 data_time: 0.0004 memory: 843 +2024/01/19 17:43:23 - mmengine - INFO - Epoch(val) [50][300/625] eta: 0:00:11 time: 0.0365 data_time: 0.0003 memory: 843 +2024/01/19 17:43:25 - mmengine - INFO - Epoch(val) [50][350/625] eta: 0:00:10 time: 0.0373 data_time: 0.0004 memory: 843 +2024/01/19 17:43:27 - mmengine - INFO - Epoch(val) [50][400/625] eta: 0:00:08 time: 0.0361 data_time: 0.0004 memory: 843 +2024/01/19 17:43:28 - mmengine - INFO - Epoch(val) [50][450/625] eta: 0:00:06 time: 0.0297 data_time: 0.0003 memory: 843 +2024/01/19 17:43:30 - mmengine - INFO - Epoch(val) [50][500/625] eta: 0:00:04 time: 0.0271 data_time: 0.0003 memory: 843 +2024/01/19 17:43:31 - mmengine - INFO - Epoch(val) [50][550/625] eta: 0:00:02 time: 0.0275 data_time: 0.0003 memory: 843 +2024/01/19 17:43:32 - mmengine - INFO - Epoch(val) [50][600/625] eta: 0:00:00 time: 0.0262 data_time: 0.0002 memory: 843 +2024/01/19 17:43:46 - mmengine - INFO - Evaluating bbox... +2024/01/19 17:44:58 - mmengine - INFO - bbox_mAP_copypaste: 0.452 0.614 0.493 0.253 0.502 0.610 +2024/01/19 17:45:00 - mmengine - INFO - Epoch(val) [50][625/625] coco/bbox_mAP: 0.4520 coco/bbox_mAP_50: 0.6140 coco/bbox_mAP_75: 0.4930 coco/bbox_mAP_s: 0.2530 coco/bbox_mAP_m: 0.5020 coco/bbox_mAP_l: 0.6100 data_time: 0.0002 time: 0.0262 +2024/01/19 17:45:22 - mmengine - INFO - Epoch(train) [51][ 50/925] lr: 7.8725e-05 eta: 3:03:52 time: 0.4433 data_time: 0.0846 memory: 5826 grad_norm: 984.4699 loss: 418.8292 loss_cls: 150.1140 loss_bbox: 126.2028 loss_dfl: 142.5124 +2024/01/19 17:45:42 - mmengine - INFO - Epoch(train) [51][100/925] lr: 7.8725e-05 eta: 3:03:32 time: 0.3931 data_time: 0.0031 memory: 5172 grad_norm: 1019.9755 loss: 421.1895 loss_cls: 151.7312 loss_bbox: 126.9646 loss_dfl: 142.4937 +2024/01/19 17:46:00 - mmengine - INFO - Epoch(train) [51][150/925] lr: 7.8725e-05 eta: 3:03:11 time: 0.3768 data_time: 0.0025 memory: 5279 grad_norm: 1050.2202 loss: 419.2050 loss_cls: 150.4118 loss_bbox: 126.2575 loss_dfl: 142.5358 +2024/01/19 17:46:20 - mmengine - INFO - Epoch(train) [51][200/925] lr: 7.8725e-05 eta: 3:02:51 time: 0.3830 data_time: 0.0028 memory: 5266 grad_norm: 996.3914 loss: 420.9486 loss_cls: 152.1647 loss_bbox: 126.4402 loss_dfl: 142.3437 +2024/01/19 17:46:38 - mmengine - INFO - Epoch(train) [51][250/925] lr: 7.8725e-05 eta: 3:02:30 time: 0.3693 data_time: 0.0026 memory: 5172 grad_norm: 1083.5417 loss: 422.8662 loss_cls: 153.7738 loss_bbox: 126.8387 loss_dfl: 142.2537 +2024/01/19 17:46:58 - mmengine - INFO - Epoch(train) [51][300/925] lr: 7.8725e-05 eta: 3:02:10 time: 0.3867 data_time: 0.0028 memory: 5279 grad_norm: 1047.4268 loss: 422.0419 loss_cls: 152.6652 loss_bbox: 126.8193 loss_dfl: 142.5574 +2024/01/19 17:47:17 - mmengine - INFO - Epoch(train) [51][350/925] lr: 7.8725e-05 eta: 3:01:49 time: 0.3794 data_time: 0.0028 memory: 5319 grad_norm: 948.4921 loss: 424.2814 loss_cls: 154.5228 loss_bbox: 127.2604 loss_dfl: 142.4982 +2024/01/19 17:47:35 - mmengine - INFO - Epoch(train) [51][400/925] lr: 7.8725e-05 eta: 3:01:28 time: 0.3594 data_time: 0.0026 memory: 5639 grad_norm: 933.0175 loss: 419.9491 loss_cls: 151.5700 loss_bbox: 126.4006 loss_dfl: 141.9785 +2024/01/19 17:47:53 - mmengine - INFO - Epoch(train) [51][450/925] lr: 7.8725e-05 eta: 3:01:08 time: 0.3777 data_time: 0.0027 memory: 5586 grad_norm: 1040.0689 loss: 411.8213 loss_cls: 147.2716 loss_bbox: 123.9419 loss_dfl: 140.6078 +2024/01/19 17:48:12 - mmengine - INFO - Epoch(train) [51][500/925] lr: 7.8725e-05 eta: 3:00:47 time: 0.3678 data_time: 0.0027 memory: 5319 grad_norm: 1023.0924 loss: 424.5963 loss_cls: 152.9546 loss_bbox: 128.9334 loss_dfl: 142.7083 +2024/01/19 17:48:30 - mmengine - INFO - Epoch(train) [51][550/925] lr: 7.8725e-05 eta: 3:00:26 time: 0.3681 data_time: 0.0024 memory: 5172 grad_norm: 974.9303 loss: 415.2319 loss_cls: 150.2726 loss_bbox: 123.3678 loss_dfl: 141.5914 +2024/01/19 17:48:49 - mmengine - INFO - Epoch(train) [51][600/925] lr: 7.8725e-05 eta: 3:00:06 time: 0.3768 data_time: 0.0026 memory: 5426 grad_norm: 1119.3905 loss: 420.7725 loss_cls: 152.0329 loss_bbox: 126.5289 loss_dfl: 142.2108 +2024/01/19 17:49:08 - mmengine - INFO - Epoch(train) [51][650/925] lr: 7.8725e-05 eta: 2:59:45 time: 0.3793 data_time: 0.0026 memory: 5199 grad_norm: 1044.4159 loss: 423.8133 loss_cls: 153.3569 loss_bbox: 127.5741 loss_dfl: 142.8823 +2024/01/19 17:49:26 - mmengine - INFO - Epoch(train) [51][700/925] lr: 7.8725e-05 eta: 2:59:24 time: 0.3631 data_time: 0.0037 memory: 5626 grad_norm: 948.8927 loss: 420.5657 loss_cls: 150.9270 loss_bbox: 127.7762 loss_dfl: 141.8625 +2024/01/19 17:49:45 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:49:45 - mmengine - INFO - Epoch(train) [51][750/925] lr: 7.8725e-05 eta: 2:59:04 time: 0.3701 data_time: 0.0026 memory: 5319 grad_norm: 1007.6891 loss: 418.9032 loss_cls: 150.5320 loss_bbox: 126.5379 loss_dfl: 141.8334 +2024/01/19 17:50:04 - mmengine - INFO - Epoch(train) [51][800/925] lr: 7.8725e-05 eta: 2:58:43 time: 0.3821 data_time: 0.0037 memory: 5239 grad_norm: 1050.1877 loss: 417.2117 loss_cls: 149.2954 loss_bbox: 126.4663 loss_dfl: 141.4499 +2024/01/19 17:50:23 - mmengine - INFO - Epoch(train) [51][850/925] lr: 7.8725e-05 eta: 2:58:23 time: 0.3723 data_time: 0.0026 memory: 5239 grad_norm: 1007.3902 loss: 422.0576 loss_cls: 151.9353 loss_bbox: 127.7787 loss_dfl: 142.3436 +2024/01/19 17:50:41 - mmengine - INFO - Epoch(train) [51][900/925] lr: 7.8725e-05 eta: 2:58:02 time: 0.3640 data_time: 0.0026 memory: 5639 grad_norm: 1001.3306 loss: 421.0330 loss_cls: 151.5505 loss_bbox: 127.3278 loss_dfl: 142.1547 +2024/01/19 17:50:50 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:51:13 - mmengine - INFO - Epoch(train) [52][ 50/925] lr: 7.6250e-05 eta: 2:57:33 time: 0.4464 data_time: 0.0890 memory: 5492 grad_norm: 965.3781 loss: 413.6898 loss_cls: 148.7359 loss_bbox: 124.5388 loss_dfl: 140.4151 +2024/01/19 17:51:31 - mmengine - INFO - Epoch(train) [52][100/925] lr: 7.6250e-05 eta: 2:57:12 time: 0.3568 data_time: 0.0027 memory: 5772 grad_norm: 1060.7413 loss: 424.4617 loss_cls: 152.1880 loss_bbox: 129.5378 loss_dfl: 142.7359 +2024/01/19 17:51:49 - mmengine - INFO - Epoch(train) [52][150/925] lr: 7.6250e-05 eta: 2:56:51 time: 0.3713 data_time: 0.0025 memory: 5612 grad_norm: 1002.2958 loss: 423.5913 loss_cls: 154.0607 loss_bbox: 127.2276 loss_dfl: 142.3031 +2024/01/19 17:52:09 - mmengine - INFO - Epoch(train) [52][200/925] lr: 7.6250e-05 eta: 2:56:31 time: 0.3886 data_time: 0.0025 memory: 5319 grad_norm: 973.7524 loss: 415.9609 loss_cls: 150.9864 loss_bbox: 124.1867 loss_dfl: 140.7879 +2024/01/19 17:52:29 - mmengine - INFO - Epoch(train) [52][250/925] lr: 7.6250e-05 eta: 2:56:11 time: 0.3973 data_time: 0.0028 memory: 5639 grad_norm: 928.4858 loss: 425.4850 loss_cls: 154.1480 loss_bbox: 128.5178 loss_dfl: 142.8192 +2024/01/19 17:52:47 - mmengine - INFO - Epoch(train) [52][300/925] lr: 7.6250e-05 eta: 2:55:50 time: 0.3680 data_time: 0.0046 memory: 5106 grad_norm: 947.7569 loss: 424.9088 loss_cls: 153.7498 loss_bbox: 128.2884 loss_dfl: 142.8706 +2024/01/19 17:53:05 - mmengine - INFO - Epoch(train) [52][350/925] lr: 7.6250e-05 eta: 2:55:30 time: 0.3649 data_time: 0.0029 memory: 5426 grad_norm: 1206.4859 loss: 418.6511 loss_cls: 152.3949 loss_bbox: 124.9183 loss_dfl: 141.3379 +2024/01/19 17:53:25 - mmengine - INFO - Epoch(train) [52][400/925] lr: 7.6250e-05 eta: 2:55:09 time: 0.3808 data_time: 0.0035 memory: 5386 grad_norm: 1153.2930 loss: 416.8629 loss_cls: 151.1831 loss_bbox: 124.1880 loss_dfl: 141.4918 +2024/01/19 17:53:44 - mmengine - INFO - Epoch(train) [52][450/925] lr: 7.6250e-05 eta: 2:54:49 time: 0.3900 data_time: 0.0043 memory: 5372 grad_norm: 1056.9196 loss: 418.0003 loss_cls: 150.0568 loss_bbox: 126.0416 loss_dfl: 141.9019 +2024/01/19 17:54:03 - mmengine - INFO - Epoch(train) [52][500/925] lr: 7.6250e-05 eta: 2:54:28 time: 0.3683 data_time: 0.0026 memory: 5212 grad_norm: 1196.1661 loss: 410.4816 loss_cls: 145.2295 loss_bbox: 124.1382 loss_dfl: 141.1140 +2024/01/19 17:54:23 - mmengine - INFO - Epoch(train) [52][550/925] lr: 7.6250e-05 eta: 2:54:09 time: 0.4009 data_time: 0.0029 memory: 5559 grad_norm: 979.6508 loss: 423.0836 loss_cls: 152.6649 loss_bbox: 127.6328 loss_dfl: 142.7859 +2024/01/19 17:54:43 - mmengine - INFO - Epoch(train) [52][600/925] lr: 7.6250e-05 eta: 2:53:49 time: 0.3983 data_time: 0.0040 memory: 5372 grad_norm: inf loss: 424.0787 loss_cls: 153.2841 loss_bbox: 127.6148 loss_dfl: 143.1798 +2024/01/19 17:55:01 - mmengine - INFO - Epoch(train) [52][650/925] lr: 7.6250e-05 eta: 2:53:28 time: 0.3737 data_time: 0.0026 memory: 5252 grad_norm: 1073.6287 loss: 427.1016 loss_cls: 154.9366 loss_bbox: 128.7554 loss_dfl: 143.4096 +2024/01/19 17:55:21 - mmengine - INFO - Epoch(train) [52][700/925] lr: 7.6250e-05 eta: 2:53:08 time: 0.3887 data_time: 0.0026 memory: 5666 grad_norm: 920.1966 loss: 417.0849 loss_cls: 149.7727 loss_bbox: 126.4491 loss_dfl: 140.8631 +2024/01/19 17:55:41 - mmengine - INFO - Epoch(train) [52][750/925] lr: 7.6250e-05 eta: 2:52:48 time: 0.4082 data_time: 0.0036 memory: 5612 grad_norm: 987.4779 loss: 422.9306 loss_cls: 154.3331 loss_bbox: 126.5378 loss_dfl: 142.0597 +2024/01/19 17:55:59 - mmengine - INFO - Epoch(train) [52][800/925] lr: 7.6250e-05 eta: 2:52:28 time: 0.3610 data_time: 0.0027 memory: 5439 grad_norm: 976.7334 loss: 421.2652 loss_cls: 152.1573 loss_bbox: 127.1085 loss_dfl: 141.9994 +2024/01/19 17:56:09 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:56:18 - mmengine - INFO - Epoch(train) [52][850/925] lr: 7.6250e-05 eta: 2:52:07 time: 0.3787 data_time: 0.0026 memory: 5306 grad_norm: 1069.8092 loss: 414.6012 loss_cls: 149.4235 loss_bbox: 123.9128 loss_dfl: 141.2649 +2024/01/19 17:56:38 - mmengine - INFO - Epoch(train) [52][900/925] lr: 7.6250e-05 eta: 2:51:47 time: 0.4025 data_time: 0.0035 memory: 5132 grad_norm: 924.6657 loss: 422.6476 loss_cls: 152.0800 loss_bbox: 127.8555 loss_dfl: 142.7122 +2024/01/19 17:56:48 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 17:57:12 - mmengine - INFO - Epoch(train) [53][ 50/925] lr: 7.3775e-05 eta: 2:51:19 time: 0.4787 data_time: 0.1026 memory: 5479 grad_norm: 981.1206 loss: 414.4810 loss_cls: 148.1781 loss_bbox: 124.8491 loss_dfl: 141.4538 +2024/01/19 17:57:31 - mmengine - INFO - Epoch(train) [53][100/925] lr: 7.3775e-05 eta: 2:50:59 time: 0.3831 data_time: 0.0036 memory: 5386 grad_norm: 1006.4056 loss: 422.2434 loss_cls: 152.2355 loss_bbox: 127.4906 loss_dfl: 142.5173 +2024/01/19 17:57:51 - mmengine - INFO - Epoch(train) [53][150/925] lr: 7.3775e-05 eta: 2:50:39 time: 0.3905 data_time: 0.0043 memory: 5732 grad_norm: 978.6056 loss: 421.6828 loss_cls: 152.3763 loss_bbox: 126.9025 loss_dfl: 142.4040 +2024/01/19 17:58:11 - mmengine - INFO - Epoch(train) [53][200/925] lr: 7.3775e-05 eta: 2:50:19 time: 0.3969 data_time: 0.0028 memory: 5559 grad_norm: 1062.8257 loss: 419.5318 loss_cls: 152.1415 loss_bbox: 125.1832 loss_dfl: 142.2071 +2024/01/19 17:58:29 - mmengine - INFO - Epoch(train) [53][250/925] lr: 7.3775e-05 eta: 2:49:58 time: 0.3665 data_time: 0.0038 memory: 5572 grad_norm: 948.9678 loss: 423.6995 loss_cls: 153.2848 loss_bbox: 127.6708 loss_dfl: 142.7440 +2024/01/19 17:58:48 - mmengine - INFO - Epoch(train) [53][300/925] lr: 7.3775e-05 eta: 2:49:38 time: 0.3810 data_time: 0.0033 memory: 5546 grad_norm: 1085.9776 loss: 421.0312 loss_cls: 150.3336 loss_bbox: 128.3453 loss_dfl: 142.3523 +2024/01/19 17:59:08 - mmengine - INFO - Epoch(train) [53][350/925] lr: 7.3775e-05 eta: 2:49:18 time: 0.3931 data_time: 0.0029 memory: 5946 grad_norm: 994.5515 loss: 428.5890 loss_cls: 156.1196 loss_bbox: 128.5919 loss_dfl: 143.8775 +2024/01/19 17:59:27 - mmengine - INFO - Epoch(train) [53][400/925] lr: 7.3775e-05 eta: 2:48:58 time: 0.3913 data_time: 0.0027 memory: 5212 grad_norm: 998.0891 loss: 419.6325 loss_cls: 152.0847 loss_bbox: 124.8208 loss_dfl: 142.7270 +2024/01/19 17:59:46 - mmengine - INFO - Epoch(train) [53][450/925] lr: 7.3775e-05 eta: 2:48:38 time: 0.3835 data_time: 0.0025 memory: 5466 grad_norm: 971.8920 loss: 413.9454 loss_cls: 148.7064 loss_bbox: 124.6109 loss_dfl: 140.6280 +2024/01/19 18:00:06 - mmengine - INFO - Epoch(train) [53][500/925] lr: 7.3775e-05 eta: 2:48:17 time: 0.3815 data_time: 0.0024 memory: 5506 grad_norm: 1095.1022 loss: 425.9933 loss_cls: 153.4981 loss_bbox: 128.7412 loss_dfl: 143.7540 +2024/01/19 18:00:25 - mmengine - INFO - Epoch(train) [53][550/925] lr: 7.3775e-05 eta: 2:47:57 time: 0.3918 data_time: 0.0041 memory: 5399 grad_norm: 995.8069 loss: 414.4692 loss_cls: 148.3250 loss_bbox: 124.8783 loss_dfl: 141.2660 +2024/01/19 18:00:45 - mmengine - INFO - Epoch(train) [53][600/925] lr: 7.3775e-05 eta: 2:47:37 time: 0.3928 data_time: 0.0030 memory: 5226 grad_norm: 974.1277 loss: 422.7512 loss_cls: 153.3283 loss_bbox: 126.9083 loss_dfl: 142.5146 +2024/01/19 18:01:04 - mmengine - INFO - Epoch(train) [53][650/925] lr: 7.3775e-05 eta: 2:47:17 time: 0.3894 data_time: 0.0024 memory: 5546 grad_norm: 1067.7137 loss: 416.5415 loss_cls: 149.6391 loss_bbox: 125.2402 loss_dfl: 141.6622 +2024/01/19 18:01:24 - mmengine - INFO - Epoch(train) [53][700/925] lr: 7.3775e-05 eta: 2:46:57 time: 0.3969 data_time: 0.0026 memory: 5652 grad_norm: 1007.9980 loss: 421.6914 loss_cls: 151.1187 loss_bbox: 128.0323 loss_dfl: 142.5404 +2024/01/19 18:01:44 - mmengine - INFO - Epoch(train) [53][750/925] lr: 7.3775e-05 eta: 2:46:37 time: 0.3899 data_time: 0.0035 memory: 5626 grad_norm: 1057.5638 loss: 426.4702 loss_cls: 155.9070 loss_bbox: 127.7290 loss_dfl: 142.8342 +2024/01/19 18:02:04 - mmengine - INFO - Epoch(train) [53][800/925] lr: 7.3775e-05 eta: 2:46:18 time: 0.4101 data_time: 0.0477 memory: 5519 grad_norm: 997.2282 loss: 420.6051 loss_cls: 151.3876 loss_bbox: 126.7614 loss_dfl: 142.4561 +2024/01/19 18:02:27 - mmengine - INFO - Epoch(train) [53][850/925] lr: 7.3775e-05 eta: 2:45:59 time: 0.4445 data_time: 0.0647 memory: 5572 grad_norm: 1137.4997 loss: 425.2225 loss_cls: 153.6694 loss_bbox: 128.8617 loss_dfl: 142.6914 +2024/01/19 18:02:47 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:02:47 - mmengine - INFO - Epoch(train) [53][900/925] lr: 7.3775e-05 eta: 2:45:39 time: 0.4056 data_time: 0.0410 memory: 5306 grad_norm: 990.1559 loss: 420.7597 loss_cls: 152.1601 loss_bbox: 125.9172 loss_dfl: 142.6824 +2024/01/19 18:02:56 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:03:25 - mmengine - INFO - Epoch(train) [54][ 50/925] lr: 7.1300e-05 eta: 2:45:14 time: 0.5779 data_time: 0.2064 memory: 5239 grad_norm: 994.2140 loss: 421.0304 loss_cls: 151.5719 loss_bbox: 126.4889 loss_dfl: 142.9696 +2024/01/19 18:03:44 - mmengine - INFO - Epoch(train) [54][100/925] lr: 7.1300e-05 eta: 2:44:53 time: 0.3796 data_time: 0.0025 memory: 5492 grad_norm: 896.6812 loss: 424.7899 loss_cls: 153.9611 loss_bbox: 127.3562 loss_dfl: 143.4726 +2024/01/19 18:04:04 - mmengine - INFO - Epoch(train) [54][150/925] lr: 7.1300e-05 eta: 2:44:33 time: 0.3955 data_time: 0.0023 memory: 5226 grad_norm: 960.2343 loss: 420.2305 loss_cls: 151.2929 loss_bbox: 127.0418 loss_dfl: 141.8959 +2024/01/19 18:04:23 - mmengine - INFO - Epoch(train) [54][200/925] lr: 7.1300e-05 eta: 2:44:13 time: 0.3917 data_time: 0.0027 memory: 5439 grad_norm: 949.0753 loss: 417.8364 loss_cls: 149.9279 loss_bbox: 126.5097 loss_dfl: 141.3987 +2024/01/19 18:04:43 - mmengine - INFO - Epoch(train) [54][250/925] lr: 7.1300e-05 eta: 2:43:53 time: 0.3817 data_time: 0.0027 memory: 5332 grad_norm: 1052.1101 loss: 415.1702 loss_cls: 148.8619 loss_bbox: 125.4737 loss_dfl: 140.8347 +2024/01/19 18:05:01 - mmengine - INFO - Epoch(train) [54][300/925] lr: 7.1300e-05 eta: 2:43:32 time: 0.3715 data_time: 0.0025 memory: 5572 grad_norm: 1035.8893 loss: 422.7949 loss_cls: 151.1307 loss_bbox: 128.5627 loss_dfl: 143.1015 +2024/01/19 18:05:21 - mmengine - INFO - Epoch(train) [54][350/925] lr: 7.1300e-05 eta: 2:43:13 time: 0.3970 data_time: 0.0036 memory: 5759 grad_norm: 976.7914 loss: 422.0204 loss_cls: 152.2120 loss_bbox: 126.4653 loss_dfl: 143.3431 +2024/01/19 18:05:39 - mmengine - INFO - Epoch(train) [54][400/925] lr: 7.1300e-05 eta: 2:42:52 time: 0.3647 data_time: 0.0028 memory: 5386 grad_norm: 978.5083 loss: 412.6014 loss_cls: 149.0240 loss_bbox: 123.5266 loss_dfl: 140.0508 +2024/01/19 18:05:58 - mmengine - INFO - Epoch(train) [54][450/925] lr: 7.1300e-05 eta: 2:42:31 time: 0.3783 data_time: 0.0028 memory: 5159 grad_norm: 1055.8559 loss: 421.8930 loss_cls: 153.0678 loss_bbox: 126.6486 loss_dfl: 142.1766 +2024/01/19 18:06:17 - mmengine - INFO - Epoch(train) [54][500/925] lr: 7.1300e-05 eta: 2:42:11 time: 0.3786 data_time: 0.0025 memory: 5466 grad_norm: 1123.0827 loss: 417.2847 loss_cls: 149.6395 loss_bbox: 126.2549 loss_dfl: 141.3903 +2024/01/19 18:06:37 - mmengine - INFO - Epoch(train) [54][550/925] lr: 7.1300e-05 eta: 2:41:51 time: 0.3856 data_time: 0.0064 memory: 5479 grad_norm: 883.1990 loss: 422.1382 loss_cls: 151.6663 loss_bbox: 127.9857 loss_dfl: 142.4862 +2024/01/19 18:06:56 - mmengine - INFO - Epoch(train) [54][600/925] lr: 7.1300e-05 eta: 2:41:31 time: 0.3921 data_time: 0.0026 memory: 5732 grad_norm: 993.9145 loss: 419.7206 loss_cls: 151.0765 loss_bbox: 126.8769 loss_dfl: 141.7672 +2024/01/19 18:07:16 - mmengine - INFO - Epoch(train) [54][650/925] lr: 7.1300e-05 eta: 2:41:11 time: 0.3911 data_time: 0.0021 memory: 5799 grad_norm: 942.2580 loss: 419.1747 loss_cls: 151.2577 loss_bbox: 126.4693 loss_dfl: 141.4477 +2024/01/19 18:07:36 - mmengine - INFO - Epoch(train) [54][700/925] lr: 7.1300e-05 eta: 2:40:51 time: 0.4033 data_time: 0.0028 memory: 5252 grad_norm: 1027.5659 loss: 413.7625 loss_cls: 150.5939 loss_bbox: 123.2680 loss_dfl: 139.9006 +2024/01/19 18:07:55 - mmengine - INFO - Epoch(train) [54][750/925] lr: 7.1300e-05 eta: 2:40:31 time: 0.3793 data_time: 0.0027 memory: 5759 grad_norm: 961.5989 loss: 417.4814 loss_cls: 149.5712 loss_bbox: 126.8258 loss_dfl: 141.0844 +2024/01/19 18:08:14 - mmengine - INFO - Epoch(train) [54][800/925] lr: 7.1300e-05 eta: 2:40:10 time: 0.3728 data_time: 0.0027 memory: 5412 grad_norm: 985.6430 loss: 416.1442 loss_cls: 149.5909 loss_bbox: 125.3605 loss_dfl: 141.1927 +2024/01/19 18:08:33 - mmengine - INFO - Epoch(train) [54][850/925] lr: 7.1300e-05 eta: 2:39:50 time: 0.3813 data_time: 0.0027 memory: 5572 grad_norm: inf loss: 416.7954 loss_cls: 151.8540 loss_bbox: 123.4596 loss_dfl: 141.4817 +2024/01/19 18:08:51 - mmengine - INFO - Epoch(train) [54][900/925] lr: 7.1300e-05 eta: 2:39:29 time: 0.3687 data_time: 0.0033 memory: 5306 grad_norm: 1092.6372 loss: 420.3414 loss_cls: 152.3393 loss_bbox: 125.6578 loss_dfl: 142.3443 +2024/01/19 18:09:00 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:09:24 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:09:24 - mmengine - INFO - Epoch(train) [55][ 50/925] lr: 6.8825e-05 eta: 2:39:01 time: 0.4641 data_time: 0.0790 memory: 5479 grad_norm: 976.9810 loss: 415.6345 loss_cls: 148.4204 loss_bbox: 125.2453 loss_dfl: 141.9687 +2024/01/19 18:09:43 - mmengine - INFO - Epoch(train) [55][100/925] lr: 6.8825e-05 eta: 2:38:40 time: 0.3828 data_time: 0.0024 memory: 5239 grad_norm: inf loss: 417.0203 loss_cls: 149.0511 loss_bbox: 126.2464 loss_dfl: 141.7228 +2024/01/19 18:10:01 - mmengine - INFO - Epoch(train) [55][150/925] lr: 6.8825e-05 eta: 2:38:20 time: 0.3551 data_time: 0.0026 memory: 5412 grad_norm: 1019.9532 loss: 419.0312 loss_cls: 151.4019 loss_bbox: 125.9861 loss_dfl: 141.6433 +2024/01/19 18:10:19 - mmengine - INFO - Epoch(train) [55][200/925] lr: 6.8825e-05 eta: 2:37:59 time: 0.3667 data_time: 0.0026 memory: 5386 grad_norm: 1024.7820 loss: 419.1913 loss_cls: 151.5152 loss_bbox: 125.9909 loss_dfl: 141.6852 +2024/01/19 18:10:38 - mmengine - INFO - Epoch(train) [55][250/925] lr: 6.8825e-05 eta: 2:37:39 time: 0.3847 data_time: 0.0026 memory: 5506 grad_norm: 919.0775 loss: 414.5068 loss_cls: 150.0120 loss_bbox: 123.7352 loss_dfl: 140.7596 +2024/01/19 18:10:57 - mmengine - INFO - Epoch(train) [55][300/925] lr: 6.8825e-05 eta: 2:37:18 time: 0.3788 data_time: 0.0026 memory: 5359 grad_norm: 993.6360 loss: 414.4631 loss_cls: 149.0865 loss_bbox: 124.6251 loss_dfl: 140.7515 +2024/01/19 18:11:17 - mmengine - INFO - Epoch(train) [55][350/925] lr: 6.8825e-05 eta: 2:36:58 time: 0.3877 data_time: 0.0023 memory: 5786 grad_norm: 1013.5698 loss: 418.9479 loss_cls: 150.9872 loss_bbox: 125.9974 loss_dfl: 141.9633 +2024/01/19 18:11:36 - mmengine - INFO - Epoch(train) [55][400/925] lr: 6.8825e-05 eta: 2:36:38 time: 0.3859 data_time: 0.0024 memory: 5426 grad_norm: 987.6084 loss: 424.9020 loss_cls: 153.8930 loss_bbox: 128.2523 loss_dfl: 142.7567 +2024/01/19 18:11:55 - mmengine - INFO - Epoch(train) [55][450/925] lr: 6.8825e-05 eta: 2:36:18 time: 0.3872 data_time: 0.0024 memory: 5292 grad_norm: 962.2521 loss: 421.7998 loss_cls: 152.6360 loss_bbox: 126.5553 loss_dfl: 142.6085 +2024/01/19 18:12:15 - mmengine - INFO - Epoch(train) [55][500/925] lr: 6.8825e-05 eta: 2:35:58 time: 0.3909 data_time: 0.0027 memory: 5146 grad_norm: 1146.7643 loss: 414.5235 loss_cls: 148.3241 loss_bbox: 125.0959 loss_dfl: 141.1035 +2024/01/19 18:12:34 - mmengine - INFO - Epoch(train) [55][550/925] lr: 6.8825e-05 eta: 2:35:38 time: 0.3804 data_time: 0.0024 memory: 5492 grad_norm: 972.0546 loss: 416.2165 loss_cls: 149.0227 loss_bbox: 126.0420 loss_dfl: 141.1517 +2024/01/19 18:12:53 - mmengine - INFO - Epoch(train) [55][600/925] lr: 6.8825e-05 eta: 2:35:18 time: 0.3789 data_time: 0.0024 memory: 5292 grad_norm: 1011.2827 loss: 416.9458 loss_cls: 149.9371 loss_bbox: 126.2274 loss_dfl: 140.7812 +2024/01/19 18:13:12 - mmengine - INFO - Epoch(train) [55][650/925] lr: 6.8825e-05 eta: 2:34:57 time: 0.3763 data_time: 0.0024 memory: 5626 grad_norm: 985.2408 loss: 419.1225 loss_cls: 151.2481 loss_bbox: 125.8840 loss_dfl: 141.9903 +2024/01/19 18:13:31 - mmengine - INFO - Epoch(train) [55][700/925] lr: 6.8825e-05 eta: 2:34:37 time: 0.3734 data_time: 0.0026 memory: 5426 grad_norm: 1116.8334 loss: 413.7085 loss_cls: 146.9371 loss_bbox: 126.0685 loss_dfl: 140.7030 +2024/01/19 18:13:49 - mmengine - INFO - Epoch(train) [55][750/925] lr: 6.8825e-05 eta: 2:34:16 time: 0.3656 data_time: 0.0038 memory: 5746 grad_norm: 1027.1039 loss: 423.3435 loss_cls: 152.2061 loss_bbox: 128.9112 loss_dfl: 142.2262 +2024/01/19 18:14:10 - mmengine - INFO - Epoch(train) [55][800/925] lr: 6.8825e-05 eta: 2:33:57 time: 0.4269 data_time: 0.0762 memory: 5319 grad_norm: 962.0627 loss: 419.4509 loss_cls: 152.1707 loss_bbox: 125.3202 loss_dfl: 141.9600 +2024/01/19 18:14:33 - mmengine - INFO - Epoch(train) [55][850/925] lr: 6.8825e-05 eta: 2:33:38 time: 0.4522 data_time: 0.0396 memory: 5666 grad_norm: 1063.9937 loss: 419.6549 loss_cls: 152.3199 loss_bbox: 125.9212 loss_dfl: 141.4139 +2024/01/19 18:14:54 - mmengine - INFO - Epoch(train) [55][900/925] lr: 6.8825e-05 eta: 2:33:19 time: 0.4155 data_time: 0.0306 memory: 5279 grad_norm: 1078.0769 loss: 412.4649 loss_cls: 146.2792 loss_bbox: 125.3710 loss_dfl: 140.8147 +2024/01/19 18:15:03 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:15:03 - mmengine - INFO - Saving checkpoint at 55 epochs +2024/01/19 18:15:12 - mmengine - INFO - Epoch(val) [55][ 50/625] eta: 0:00:20 time: 0.0363 data_time: 0.0009 memory: 5186 +2024/01/19 18:15:14 - mmengine - INFO - Epoch(val) [55][100/625] eta: 0:00:19 time: 0.0371 data_time: 0.0014 memory: 843 +2024/01/19 18:15:15 - mmengine - INFO - Epoch(val) [55][150/625] eta: 0:00:17 time: 0.0370 data_time: 0.0018 memory: 843 +2024/01/19 18:15:17 - mmengine - INFO - Epoch(val) [55][200/625] eta: 0:00:15 time: 0.0346 data_time: 0.0008 memory: 843 +2024/01/19 18:15:19 - mmengine - INFO - Epoch(val) [55][250/625] eta: 0:00:13 time: 0.0366 data_time: 0.0013 memory: 843 +2024/01/19 18:15:21 - mmengine - INFO - Epoch(val) [55][300/625] eta: 0:00:11 time: 0.0358 data_time: 0.0003 memory: 843 +2024/01/19 18:15:23 - mmengine - INFO - Epoch(val) [55][350/625] eta: 0:00:09 time: 0.0356 data_time: 0.0007 memory: 843 +2024/01/19 18:15:25 - mmengine - INFO - Epoch(val) [55][400/625] eta: 0:00:08 time: 0.0383 data_time: 0.0025 memory: 843 +2024/01/19 18:15:26 - mmengine - INFO - Epoch(val) [55][450/625] eta: 0:00:06 time: 0.0290 data_time: 0.0002 memory: 843 +2024/01/19 18:15:27 - mmengine - INFO - Epoch(val) [55][500/625] eta: 0:00:04 time: 0.0279 data_time: 0.0024 memory: 843 +2024/01/19 18:15:29 - mmengine - INFO - Epoch(val) [55][550/625] eta: 0:00:02 time: 0.0256 data_time: 0.0002 memory: 843 +2024/01/19 18:15:30 - mmengine - INFO - Epoch(val) [55][600/625] eta: 0:00:00 time: 0.0263 data_time: 0.0008 memory: 843 +2024/01/19 18:15:44 - mmengine - INFO - Evaluating bbox... +2024/01/19 18:17:03 - mmengine - INFO - bbox_mAP_copypaste: 0.452 0.614 0.493 0.259 0.502 0.609 +2024/01/19 18:17:06 - mmengine - INFO - Epoch(val) [55][625/625] coco/bbox_mAP: 0.4520 coco/bbox_mAP_50: 0.6140 coco/bbox_mAP_75: 0.4930 coco/bbox_mAP_s: 0.2590 coco/bbox_mAP_m: 0.5020 coco/bbox_mAP_l: 0.6090 data_time: 0.0033 time: 0.0289 +2024/01/19 18:17:36 - mmengine - INFO - Epoch(train) [56][ 50/925] lr: 6.6350e-05 eta: 2:32:53 time: 0.6037 data_time: 0.2791 memory: 5426 grad_norm: 1035.4754 loss: 413.0733 loss_cls: 147.7182 loss_bbox: 124.6244 loss_dfl: 140.7308 +2024/01/19 18:18:02 - mmengine - INFO - Epoch(train) [56][100/925] lr: 6.6350e-05 eta: 2:32:36 time: 0.5134 data_time: 0.1705 memory: 5452 grad_norm: 1010.5396 loss: 420.1863 loss_cls: 150.8862 loss_bbox: 126.7310 loss_dfl: 142.5692 +2024/01/19 18:18:14 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:18:27 - mmengine - INFO - Epoch(train) [56][150/925] lr: 6.6350e-05 eta: 2:32:18 time: 0.5007 data_time: 0.1436 memory: 5279 grad_norm: 1225.0830 loss: 419.1186 loss_cls: 149.1259 loss_bbox: 128.2997 loss_dfl: 141.6930 +2024/01/19 18:18:49 - mmengine - INFO - Epoch(train) [56][200/925] lr: 6.6350e-05 eta: 2:32:00 time: 0.4471 data_time: 0.1025 memory: 5559 grad_norm: 1101.3076 loss: 420.8203 loss_cls: 150.4700 loss_bbox: 127.2461 loss_dfl: 143.1042 +2024/01/19 18:19:11 - mmengine - INFO - Epoch(train) [56][250/925] lr: 6.6350e-05 eta: 2:31:41 time: 0.4336 data_time: 0.0639 memory: 5319 grad_norm: 1036.1696 loss: 420.7146 loss_cls: 150.8502 loss_bbox: 127.1399 loss_dfl: 142.7245 +2024/01/19 18:19:33 - mmengine - INFO - Epoch(train) [56][300/925] lr: 6.6350e-05 eta: 2:31:21 time: 0.4290 data_time: 0.0461 memory: 5226 grad_norm: 1111.1969 loss: 417.8727 loss_cls: 150.6688 loss_bbox: 125.1718 loss_dfl: 142.0322 +2024/01/19 18:19:58 - mmengine - INFO - Epoch(train) [56][350/925] lr: 6.6350e-05 eta: 2:31:04 time: 0.4991 data_time: 0.0476 memory: 5693 grad_norm: 1085.9951 loss: 419.6891 loss_cls: 151.3305 loss_bbox: 126.6800 loss_dfl: 141.6787 +2024/01/19 18:20:18 - mmengine - INFO - Epoch(train) [56][400/925] lr: 6.6350e-05 eta: 2:30:44 time: 0.4182 data_time: 0.0057 memory: 5412 grad_norm: 952.9146 loss: 417.8488 loss_cls: 150.8637 loss_bbox: 125.1999 loss_dfl: 141.7851 +2024/01/19 18:20:37 - mmengine - INFO - Epoch(train) [56][450/925] lr: 6.6350e-05 eta: 2:30:24 time: 0.3775 data_time: 0.0027 memory: 5279 grad_norm: 1076.4176 loss: 410.9069 loss_cls: 147.6830 loss_bbox: 123.3356 loss_dfl: 139.8883 +2024/01/19 18:20:56 - mmengine - INFO - Epoch(train) [56][500/925] lr: 6.6350e-05 eta: 2:30:04 time: 0.3732 data_time: 0.0035 memory: 5986 grad_norm: 1005.0542 loss: 419.8984 loss_cls: 150.6021 loss_bbox: 127.8820 loss_dfl: 141.4143 +2024/01/19 18:21:15 - mmengine - INFO - Epoch(train) [56][550/925] lr: 6.6350e-05 eta: 2:29:43 time: 0.3692 data_time: 0.0027 memory: 5452 grad_norm: 1010.7313 loss: 418.2776 loss_cls: 150.5826 loss_bbox: 125.5985 loss_dfl: 142.0965 +2024/01/19 18:21:34 - mmengine - INFO - Epoch(train) [56][600/925] lr: 6.6350e-05 eta: 2:29:23 time: 0.3782 data_time: 0.0027 memory: 5412 grad_norm: 972.0039 loss: 419.4185 loss_cls: 150.1606 loss_bbox: 127.0305 loss_dfl: 142.2275 +2024/01/19 18:21:54 - mmengine - INFO - Epoch(train) [56][650/925] lr: 6.6350e-05 eta: 2:29:03 time: 0.4020 data_time: 0.0026 memory: 5546 grad_norm: 944.3440 loss: 417.6477 loss_cls: 150.4400 loss_bbox: 125.1923 loss_dfl: 142.0153 +2024/01/19 18:22:13 - mmengine - INFO - Epoch(train) [56][700/925] lr: 6.6350e-05 eta: 2:28:43 time: 0.3823 data_time: 0.0033 memory: 5399 grad_norm: 1052.8051 loss: 413.7431 loss_cls: 148.0010 loss_bbox: 125.1277 loss_dfl: 140.6145 +2024/01/19 18:22:31 - mmengine - INFO - Epoch(train) [56][750/925] lr: 6.6350e-05 eta: 2:28:22 time: 0.3701 data_time: 0.0036 memory: 5932 grad_norm: 1053.0653 loss: 413.7257 loss_cls: 147.5337 loss_bbox: 125.3037 loss_dfl: 140.8883 +2024/01/19 18:22:51 - mmengine - INFO - Epoch(train) [56][800/925] lr: 6.6350e-05 eta: 2:28:02 time: 0.3883 data_time: 0.0033 memory: 5319 grad_norm: 878.3276 loss: 413.3535 loss_cls: 147.1958 loss_bbox: 125.0529 loss_dfl: 141.1048 +2024/01/19 18:23:10 - mmengine - INFO - Epoch(train) [56][850/925] lr: 6.6350e-05 eta: 2:27:42 time: 0.3730 data_time: 0.0029 memory: 5252 grad_norm: 1135.2147 loss: 421.6209 loss_cls: 151.9984 loss_bbox: 126.9255 loss_dfl: 142.6970 +2024/01/19 18:23:29 - mmengine - INFO - Epoch(train) [56][900/925] lr: 6.6350e-05 eta: 2:27:21 time: 0.3848 data_time: 0.0027 memory: 5306 grad_norm: 1028.7011 loss: 422.0080 loss_cls: 153.6824 loss_bbox: 125.3055 loss_dfl: 143.0201 +2024/01/19 18:23:38 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:24:03 - mmengine - INFO - Epoch(train) [57][ 50/925] lr: 6.3875e-05 eta: 2:26:53 time: 0.4957 data_time: 0.1187 memory: 5466 grad_norm: 1030.8367 loss: 411.5752 loss_cls: 146.7545 loss_bbox: 123.5410 loss_dfl: 141.2798 +2024/01/19 18:24:21 - mmengine - INFO - Epoch(train) [57][100/925] lr: 6.3875e-05 eta: 2:26:33 time: 0.3614 data_time: 0.0025 memory: 5879 grad_norm: 971.4539 loss: 423.3117 loss_cls: 154.1248 loss_bbox: 126.4055 loss_dfl: 142.7814 +2024/01/19 18:24:41 - mmengine - INFO - Epoch(train) [57][150/925] lr: 6.3875e-05 eta: 2:26:13 time: 0.3924 data_time: 0.0026 memory: 5266 grad_norm: 1060.6062 loss: 425.5727 loss_cls: 153.6858 loss_bbox: 128.1949 loss_dfl: 143.6920 +2024/01/19 18:25:01 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:25:01 - mmengine - INFO - Epoch(train) [57][200/925] lr: 6.3875e-05 eta: 2:25:53 time: 0.3952 data_time: 0.0036 memory: 5372 grad_norm: 1184.3285 loss: 411.0375 loss_cls: 146.3773 loss_bbox: 123.2096 loss_dfl: 141.4505 +2024/01/19 18:25:20 - mmengine - INFO - Epoch(train) [57][250/925] lr: 6.3875e-05 eta: 2:25:32 time: 0.3773 data_time: 0.0027 memory: 5279 grad_norm: 1007.1681 loss: 421.1520 loss_cls: 152.1060 loss_bbox: 126.9559 loss_dfl: 142.0900 +2024/01/19 18:25:39 - mmengine - INFO - Epoch(train) [57][300/925] lr: 6.3875e-05 eta: 2:25:12 time: 0.3805 data_time: 0.0031 memory: 5492 grad_norm: 974.2328 loss: 414.3333 loss_cls: 147.7795 loss_bbox: 126.2880 loss_dfl: 140.2658 +2024/01/19 18:25:58 - mmengine - INFO - Epoch(train) [57][350/925] lr: 6.3875e-05 eta: 2:24:52 time: 0.3785 data_time: 0.0026 memory: 5466 grad_norm: 867.8845 loss: 416.1739 loss_cls: 148.8357 loss_bbox: 125.3055 loss_dfl: 142.0327 +2024/01/19 18:26:17 - mmengine - INFO - Epoch(train) [57][400/925] lr: 6.3875e-05 eta: 2:24:32 time: 0.3854 data_time: 0.0028 memory: 5346 grad_norm: 1074.1420 loss: 413.4778 loss_cls: 148.3695 loss_bbox: 123.8426 loss_dfl: 141.2656 +2024/01/19 18:26:36 - mmengine - INFO - Epoch(train) [57][450/925] lr: 6.3875e-05 eta: 2:24:12 time: 0.3890 data_time: 0.0030 memory: 5292 grad_norm: 956.9025 loss: 419.0309 loss_cls: 151.0134 loss_bbox: 126.2919 loss_dfl: 141.7255 +2024/01/19 18:26:56 - mmengine - INFO - Epoch(train) [57][500/925] lr: 6.3875e-05 eta: 2:23:51 time: 0.3814 data_time: 0.0024 memory: 5426 grad_norm: 1043.5647 loss: 422.7499 loss_cls: 153.5040 loss_bbox: 126.7996 loss_dfl: 142.4463 +2024/01/19 18:27:16 - mmengine - INFO - Epoch(train) [57][550/925] lr: 6.3875e-05 eta: 2:23:32 time: 0.4033 data_time: 0.0034 memory: 5172 grad_norm: 977.6803 loss: 418.2105 loss_cls: 149.5857 loss_bbox: 126.8118 loss_dfl: 141.8130 +2024/01/19 18:27:35 - mmengine - INFO - Epoch(train) [57][600/925] lr: 6.3875e-05 eta: 2:23:11 time: 0.3874 data_time: 0.0027 memory: 5639 grad_norm: 1016.6617 loss: 423.6133 loss_cls: 152.6753 loss_bbox: 128.2807 loss_dfl: 142.6573 +2024/01/19 18:27:54 - mmengine - INFO - Epoch(train) [57][650/925] lr: 6.3875e-05 eta: 2:22:51 time: 0.3838 data_time: 0.0034 memory: 5479 grad_norm: 981.5197 loss: 421.7660 loss_cls: 151.2697 loss_bbox: 127.8076 loss_dfl: 142.6887 +2024/01/19 18:28:14 - mmengine - INFO - Epoch(train) [57][700/925] lr: 6.3875e-05 eta: 2:22:31 time: 0.3975 data_time: 0.0025 memory: 5586 grad_norm: 1039.9015 loss: 416.7441 loss_cls: 149.2971 loss_bbox: 126.0320 loss_dfl: 141.4150 +2024/01/19 18:28:34 - mmengine - INFO - Epoch(train) [57][750/925] lr: 6.3875e-05 eta: 2:22:11 time: 0.3986 data_time: 0.0030 memory: 5239 grad_norm: 1031.8292 loss: 405.9243 loss_cls: 144.3282 loss_bbox: 122.0301 loss_dfl: 139.5661 +2024/01/19 18:28:54 - mmengine - INFO - Epoch(train) [57][800/925] lr: 6.3875e-05 eta: 2:21:51 time: 0.3858 data_time: 0.0026 memory: 5519 grad_norm: 1105.8084 loss: 420.0406 loss_cls: 151.1711 loss_bbox: 127.3369 loss_dfl: 141.5326 +2024/01/19 18:29:14 - mmengine - INFO - Epoch(train) [57][850/925] lr: 6.3875e-05 eta: 2:21:32 time: 0.4046 data_time: 0.0047 memory: 5506 grad_norm: 1041.7872 loss: 417.8851 loss_cls: 148.9968 loss_bbox: 126.8497 loss_dfl: 142.0387 +2024/01/19 18:29:33 - mmengine - INFO - Epoch(train) [57][900/925] lr: 6.3875e-05 eta: 2:21:12 time: 0.3870 data_time: 0.0029 memory: 5412 grad_norm: 957.9362 loss: 417.2344 loss_cls: 149.2498 loss_bbox: 125.9353 loss_dfl: 142.0493 +2024/01/19 18:29:43 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:30:07 - mmengine - INFO - Epoch(train) [58][ 50/925] lr: 6.1400e-05 eta: 2:20:43 time: 0.4799 data_time: 0.0984 memory: 5252 grad_norm: 981.0599 loss: 414.2621 loss_cls: 147.5363 loss_bbox: 124.8814 loss_dfl: 141.8443 +2024/01/19 18:30:27 - mmengine - INFO - Epoch(train) [58][100/925] lr: 6.1400e-05 eta: 2:20:23 time: 0.3978 data_time: 0.0025 memory: 5279 grad_norm: 938.3579 loss: 419.3254 loss_cls: 152.9401 loss_bbox: 124.9717 loss_dfl: 141.4136 +2024/01/19 18:30:47 - mmengine - INFO - Epoch(train) [58][150/925] lr: 6.1400e-05 eta: 2:20:03 time: 0.3945 data_time: 0.0026 memory: 5439 grad_norm: 1100.9908 loss: 412.6835 loss_cls: 147.8118 loss_bbox: 123.5470 loss_dfl: 141.3247 +2024/01/19 18:31:06 - mmengine - INFO - Epoch(train) [58][200/925] lr: 6.1400e-05 eta: 2:19:43 time: 0.3824 data_time: 0.0027 memory: 5626 grad_norm: 1021.5648 loss: 413.6700 loss_cls: 147.9448 loss_bbox: 124.7459 loss_dfl: 140.9792 +2024/01/19 18:31:25 - mmengine - INFO - Epoch(train) [58][250/925] lr: 6.1400e-05 eta: 2:19:23 time: 0.3854 data_time: 0.0036 memory: 5292 grad_norm: 1002.6370 loss: 415.0405 loss_cls: 147.5143 loss_bbox: 126.3591 loss_dfl: 141.1671 +2024/01/19 18:31:35 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:31:45 - mmengine - INFO - Epoch(train) [58][300/925] lr: 6.1400e-05 eta: 2:19:03 time: 0.3905 data_time: 0.0027 memory: 5172 grad_norm: 971.7678 loss: 425.5776 loss_cls: 153.1488 loss_bbox: 128.6668 loss_dfl: 143.7619 +2024/01/19 18:32:04 - mmengine - INFO - Epoch(train) [58][350/925] lr: 6.1400e-05 eta: 2:18:43 time: 0.3864 data_time: 0.0026 memory: 5292 grad_norm: 1094.0405 loss: 422.8007 loss_cls: 153.1227 loss_bbox: 126.5760 loss_dfl: 143.1020 +2024/01/19 18:32:23 - mmengine - INFO - Epoch(train) [58][400/925] lr: 6.1400e-05 eta: 2:18:23 time: 0.3815 data_time: 0.0026 memory: 5786 grad_norm: 925.8060 loss: 411.8771 loss_cls: 147.7846 loss_bbox: 123.3348 loss_dfl: 140.7577 +2024/01/19 18:32:43 - mmengine - INFO - Epoch(train) [58][450/925] lr: 6.1400e-05 eta: 2:18:03 time: 0.3945 data_time: 0.0026 memory: 5412 grad_norm: 975.1867 loss: 419.2219 loss_cls: 151.1797 loss_bbox: 125.8572 loss_dfl: 142.1850 +2024/01/19 18:33:02 - mmengine - INFO - Epoch(train) [58][500/925] lr: 6.1400e-05 eta: 2:17:42 time: 0.3815 data_time: 0.0034 memory: 5306 grad_norm: 1042.0991 loss: 418.3817 loss_cls: 149.6939 loss_bbox: 126.3450 loss_dfl: 142.3429 +2024/01/19 18:33:21 - mmengine - INFO - Epoch(train) [58][550/925] lr: 6.1400e-05 eta: 2:17:22 time: 0.3766 data_time: 0.0028 memory: 5439 grad_norm: 1091.2032 loss: 410.0335 loss_cls: 145.0841 loss_bbox: 124.0904 loss_dfl: 140.8590 +2024/01/19 18:33:41 - mmengine - INFO - Epoch(train) [58][600/925] lr: 6.1400e-05 eta: 2:17:02 time: 0.3925 data_time: 0.0028 memory: 5719 grad_norm: 1023.7916 loss: 420.0284 loss_cls: 150.9603 loss_bbox: 127.3303 loss_dfl: 141.7378 +2024/01/19 18:34:00 - mmengine - INFO - Epoch(train) [58][650/925] lr: 6.1400e-05 eta: 2:16:42 time: 0.3904 data_time: 0.0039 memory: 5212 grad_norm: 991.9832 loss: 418.7176 loss_cls: 151.9598 loss_bbox: 124.7997 loss_dfl: 141.9581 +2024/01/19 18:34:20 - mmengine - INFO - Epoch(train) [58][700/925] lr: 6.1400e-05 eta: 2:16:22 time: 0.3970 data_time: 0.0028 memory: 5412 grad_norm: 986.5584 loss: 425.6588 loss_cls: 154.8304 loss_bbox: 128.2295 loss_dfl: 142.5989 +2024/01/19 18:34:39 - mmengine - INFO - Epoch(train) [58][750/925] lr: 6.1400e-05 eta: 2:16:02 time: 0.3743 data_time: 0.0026 memory: 5372 grad_norm: 1029.7986 loss: 412.2933 loss_cls: 146.5460 loss_bbox: 124.6746 loss_dfl: 141.0727 +2024/01/19 18:34:58 - mmengine - INFO - Epoch(train) [58][800/925] lr: 6.1400e-05 eta: 2:15:42 time: 0.3901 data_time: 0.0026 memory: 5426 grad_norm: 956.5026 loss: 417.8458 loss_cls: 150.1692 loss_bbox: 125.6141 loss_dfl: 142.0625 +2024/01/19 18:35:17 - mmengine - INFO - Epoch(train) [58][850/925] lr: 6.1400e-05 eta: 2:15:22 time: 0.3789 data_time: 0.0033 memory: 5786 grad_norm: 1054.9082 loss: 410.5320 loss_cls: 146.9673 loss_bbox: 123.3918 loss_dfl: 140.1729 +2024/01/19 18:35:37 - mmengine - INFO - Epoch(train) [58][900/925] lr: 6.1400e-05 eta: 2:15:02 time: 0.3898 data_time: 0.0025 memory: 5372 grad_norm: 1033.8923 loss: 417.6609 loss_cls: 151.4676 loss_bbox: 125.0309 loss_dfl: 141.1625 +2024/01/19 18:35:46 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:36:12 - mmengine - INFO - Epoch(train) [59][ 50/925] lr: 5.8925e-05 eta: 2:14:33 time: 0.4986 data_time: 0.1272 memory: 5452 grad_norm: 989.6721 loss: 419.1436 loss_cls: 149.0280 loss_bbox: 128.2658 loss_dfl: 141.8498 +2024/01/19 18:36:32 - mmengine - INFO - Epoch(train) [59][100/925] lr: 5.8925e-05 eta: 2:14:14 time: 0.4025 data_time: 0.0027 memory: 5306 grad_norm: 1064.9589 loss: 419.5956 loss_cls: 152.2425 loss_bbox: 125.3182 loss_dfl: 142.0349 +2024/01/19 18:36:51 - mmengine - INFO - Epoch(train) [59][150/925] lr: 5.8925e-05 eta: 2:13:53 time: 0.3745 data_time: 0.0034 memory: 5679 grad_norm: 1023.0568 loss: 411.8196 loss_cls: 147.2549 loss_bbox: 123.6220 loss_dfl: 140.9426 +2024/01/19 18:37:10 - mmengine - INFO - Epoch(train) [59][200/925] lr: 5.8925e-05 eta: 2:13:33 time: 0.3961 data_time: 0.0027 memory: 5532 grad_norm: 968.4129 loss: 415.3698 loss_cls: 148.5532 loss_bbox: 125.5193 loss_dfl: 141.2973 +2024/01/19 18:37:30 - mmengine - INFO - Epoch(train) [59][250/925] lr: 5.8925e-05 eta: 2:13:13 time: 0.3912 data_time: 0.0028 memory: 5386 grad_norm: 998.9424 loss: 413.2883 loss_cls: 147.6217 loss_bbox: 124.5128 loss_dfl: 141.1538 +2024/01/19 18:37:49 - mmengine - INFO - Epoch(train) [59][300/925] lr: 5.8925e-05 eta: 2:12:53 time: 0.3863 data_time: 0.0072 memory: 5372 grad_norm: 988.3930 loss: 416.7842 loss_cls: 148.7202 loss_bbox: 126.0478 loss_dfl: 142.0162 +2024/01/19 18:38:09 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:38:09 - mmengine - INFO - Epoch(train) [59][350/925] lr: 5.8925e-05 eta: 2:12:33 time: 0.3827 data_time: 0.0026 memory: 5212 grad_norm: 1033.3955 loss: 417.5977 loss_cls: 150.2709 loss_bbox: 125.4487 loss_dfl: 141.8781 +2024/01/19 18:38:29 - mmengine - INFO - Epoch(train) [59][400/925] lr: 5.8925e-05 eta: 2:12:13 time: 0.4033 data_time: 0.0037 memory: 5426 grad_norm: 1009.0361 loss: 418.8132 loss_cls: 151.3259 loss_bbox: 125.5797 loss_dfl: 141.9076 +2024/01/19 18:38:48 - mmengine - INFO - Epoch(train) [59][450/925] lr: 5.8925e-05 eta: 2:11:53 time: 0.3833 data_time: 0.0027 memory: 5266 grad_norm: 984.3262 loss: 414.0317 loss_cls: 147.7739 loss_bbox: 125.0644 loss_dfl: 141.1935 +2024/01/19 18:39:08 - mmengine - INFO - Epoch(train) [59][500/925] lr: 5.8925e-05 eta: 2:11:33 time: 0.3911 data_time: 0.0039 memory: 5292 grad_norm: 990.4030 loss: 411.7724 loss_cls: 147.5481 loss_bbox: 123.9123 loss_dfl: 140.3121 +2024/01/19 18:39:27 - mmengine - INFO - Epoch(train) [59][550/925] lr: 5.8925e-05 eta: 2:11:13 time: 0.3840 data_time: 0.0028 memory: 5746 grad_norm: inf loss: 410.7121 loss_cls: 145.9167 loss_bbox: 124.1583 loss_dfl: 140.6371 +2024/01/19 18:39:46 - mmengine - INFO - Epoch(train) [59][600/925] lr: 5.8925e-05 eta: 2:10:53 time: 0.3902 data_time: 0.0086 memory: 5639 grad_norm: 969.3288 loss: 424.5646 loss_cls: 153.0115 loss_bbox: 128.3829 loss_dfl: 143.1702 +2024/01/19 18:40:06 - mmengine - INFO - Epoch(train) [59][650/925] lr: 5.8925e-05 eta: 2:10:33 time: 0.3972 data_time: 0.0028 memory: 5719 grad_norm: 1068.4257 loss: 409.3373 loss_cls: 143.9026 loss_bbox: 125.0235 loss_dfl: 140.4112 +2024/01/19 18:40:26 - mmengine - INFO - Epoch(train) [59][700/925] lr: 5.8925e-05 eta: 2:10:13 time: 0.3865 data_time: 0.0058 memory: 5306 grad_norm: 1152.2359 loss: 413.9258 loss_cls: 147.7432 loss_bbox: 125.2174 loss_dfl: 140.9652 +2024/01/19 18:40:45 - mmengine - INFO - Epoch(train) [59][750/925] lr: 5.8925e-05 eta: 2:09:53 time: 0.3856 data_time: 0.0025 memory: 5372 grad_norm: 990.0305 loss: 407.8402 loss_cls: 144.4299 loss_bbox: 122.9554 loss_dfl: 140.4549 +2024/01/19 18:41:05 - mmengine - INFO - Epoch(train) [59][800/925] lr: 5.8925e-05 eta: 2:09:33 time: 0.3970 data_time: 0.0056 memory: 5199 grad_norm: 1054.4593 loss: 417.8995 loss_cls: 148.8298 loss_bbox: 127.3418 loss_dfl: 141.7278 +2024/01/19 18:41:24 - mmengine - INFO - Epoch(train) [59][850/925] lr: 5.8925e-05 eta: 2:09:13 time: 0.3852 data_time: 0.0026 memory: 5279 grad_norm: 985.2807 loss: 416.8879 loss_cls: 150.4449 loss_bbox: 124.7873 loss_dfl: 141.6557 +2024/01/19 18:41:44 - mmengine - INFO - Epoch(train) [59][900/925] lr: 5.8925e-05 eta: 2:08:53 time: 0.3947 data_time: 0.0027 memory: 5612 grad_norm: 1069.4435 loss: 408.3745 loss_cls: 145.1252 loss_bbox: 123.4607 loss_dfl: 139.7885 +2024/01/19 18:41:53 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:42:19 - mmengine - INFO - Epoch(train) [60][ 50/925] lr: 5.6450e-05 eta: 2:08:25 time: 0.5098 data_time: 0.1261 memory: 5439 grad_norm: 1063.6461 loss: 419.5249 loss_cls: 149.8015 loss_bbox: 127.1045 loss_dfl: 142.6189 +2024/01/19 18:42:38 - mmengine - INFO - Epoch(train) [60][100/925] lr: 5.6450e-05 eta: 2:08:05 time: 0.3797 data_time: 0.0028 memory: 5399 grad_norm: 1110.2283 loss: 413.2981 loss_cls: 147.6958 loss_bbox: 124.4381 loss_dfl: 141.1642 +2024/01/19 18:42:57 - mmengine - INFO - Epoch(train) [60][150/925] lr: 5.6450e-05 eta: 2:07:44 time: 0.3812 data_time: 0.0028 memory: 5346 grad_norm: 973.6438 loss: 421.5880 loss_cls: 151.6133 loss_bbox: 126.9674 loss_dfl: 143.0073 +2024/01/19 18:43:16 - mmengine - INFO - Epoch(train) [60][200/925] lr: 5.6450e-05 eta: 2:07:24 time: 0.3833 data_time: 0.0138 memory: 5386 grad_norm: 1017.6265 loss: 418.4633 loss_cls: 151.1777 loss_bbox: 125.9038 loss_dfl: 141.3818 +2024/01/19 18:43:36 - mmengine - INFO - Epoch(train) [60][250/925] lr: 5.6450e-05 eta: 2:07:04 time: 0.3979 data_time: 0.0175 memory: 5412 grad_norm: 987.9047 loss: 423.3439 loss_cls: 151.8287 loss_bbox: 128.2257 loss_dfl: 143.2894 +2024/01/19 18:43:55 - mmengine - INFO - Epoch(train) [60][300/925] lr: 5.6450e-05 eta: 2:06:44 time: 0.3861 data_time: 0.0030 memory: 5772 grad_norm: 1010.1493 loss: 416.2040 loss_cls: 149.6077 loss_bbox: 125.5693 loss_dfl: 141.0269 +2024/01/19 18:44:14 - mmengine - INFO - Epoch(train) [60][350/925] lr: 5.6450e-05 eta: 2:06:24 time: 0.3747 data_time: 0.0028 memory: 5386 grad_norm: 968.2795 loss: 416.3246 loss_cls: 149.0883 loss_bbox: 126.1873 loss_dfl: 141.0490 +2024/01/19 18:44:34 - mmengine - INFO - Epoch(train) [60][400/925] lr: 5.6450e-05 eta: 2:06:04 time: 0.3892 data_time: 0.0027 memory: 5466 grad_norm: 1044.8322 loss: 419.1020 loss_cls: 151.1002 loss_bbox: 126.1170 loss_dfl: 141.8848 +2024/01/19 18:44:43 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:44:53 - mmengine - INFO - Epoch(train) [60][450/925] lr: 5.6450e-05 eta: 2:05:44 time: 0.3886 data_time: 0.0027 memory: 5652 grad_norm: 1018.5280 loss: 420.8205 loss_cls: 151.4532 loss_bbox: 127.0341 loss_dfl: 142.3333 +2024/01/19 18:45:12 - mmengine - INFO - Epoch(train) [60][500/925] lr: 5.6450e-05 eta: 2:05:24 time: 0.3822 data_time: 0.0217 memory: 5332 grad_norm: 1080.8256 loss: 413.4491 loss_cls: 147.4395 loss_bbox: 125.5775 loss_dfl: 140.4321 +2024/01/19 18:45:31 - mmengine - INFO - Epoch(train) [60][550/925] lr: 5.6450e-05 eta: 2:05:04 time: 0.3838 data_time: 0.0028 memory: 5412 grad_norm: 1049.6185 loss: 414.9947 loss_cls: 148.4600 loss_bbox: 124.8597 loss_dfl: 141.6751 +2024/01/19 18:45:50 - mmengine - INFO - Epoch(train) [60][600/925] lr: 5.6450e-05 eta: 2:04:43 time: 0.3732 data_time: 0.0029 memory: 5506 grad_norm: 1031.2340 loss: 424.5299 loss_cls: 152.8290 loss_bbox: 129.1287 loss_dfl: 142.5722 +2024/01/19 18:46:10 - mmengine - INFO - Epoch(train) [60][650/925] lr: 5.6450e-05 eta: 2:04:24 time: 0.4060 data_time: 0.0320 memory: 5612 grad_norm: 973.4002 loss: 424.4224 loss_cls: 154.0841 loss_bbox: 127.6639 loss_dfl: 142.6744 +2024/01/19 18:46:30 - mmengine - INFO - Epoch(train) [60][700/925] lr: 5.6450e-05 eta: 2:04:04 time: 0.3849 data_time: 0.0033 memory: 5359 grad_norm: 1017.2883 loss: 409.0823 loss_cls: 145.5987 loss_bbox: 123.4445 loss_dfl: 140.0392 +2024/01/19 18:46:50 - mmengine - INFO - Epoch(train) [60][750/925] lr: 5.6450e-05 eta: 2:03:44 time: 0.4088 data_time: 0.0036 memory: 5386 grad_norm: 1132.3970 loss: 413.2392 loss_cls: 147.5801 loss_bbox: 124.4353 loss_dfl: 141.2238 +2024/01/19 18:47:10 - mmengine - INFO - Epoch(train) [60][800/925] lr: 5.6450e-05 eta: 2:03:24 time: 0.3873 data_time: 0.0029 memory: 5319 grad_norm: 953.3789 loss: 410.3419 loss_cls: 146.4336 loss_bbox: 123.8762 loss_dfl: 140.0320 +2024/01/19 18:47:29 - mmengine - INFO - Epoch(train) [60][850/925] lr: 5.6450e-05 eta: 2:03:04 time: 0.3829 data_time: 0.0080 memory: 5626 grad_norm: 1022.3360 loss: 415.7375 loss_cls: 147.7776 loss_bbox: 127.1847 loss_dfl: 140.7752 +2024/01/19 18:48:03 - mmengine - INFO - Epoch(train) [60][900/925] lr: 5.6450e-05 eta: 2:02:49 time: 0.6819 data_time: 0.0212 memory: 5279 grad_norm: 1114.0744 loss: 414.4530 loss_cls: 146.9220 loss_bbox: 125.9433 loss_dfl: 141.5877 +2024/01/19 18:48:17 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:48:18 - mmengine - INFO - Saving checkpoint at 60 epochs +2024/01/19 18:48:26 - mmengine - INFO - Epoch(val) [60][ 50/625] eta: 0:00:21 time: 0.0382 data_time: 0.0034 memory: 5306 +2024/01/19 18:48:28 - mmengine - INFO - Epoch(val) [60][100/625] eta: 0:00:19 time: 0.0361 data_time: 0.0010 memory: 843 +2024/01/19 18:48:30 - mmengine - INFO - Epoch(val) [60][150/625] eta: 0:00:17 time: 0.0347 data_time: 0.0008 memory: 843 +2024/01/19 18:48:32 - mmengine - INFO - Epoch(val) [60][200/625] eta: 0:00:15 time: 0.0354 data_time: 0.0004 memory: 843 +2024/01/19 18:48:33 - mmengine - INFO - Epoch(val) [60][250/625] eta: 0:00:13 time: 0.0376 data_time: 0.0004 memory: 843 +2024/01/19 18:48:35 - mmengine - INFO - Epoch(val) [60][300/625] eta: 0:00:11 time: 0.0346 data_time: 0.0004 memory: 843 +2024/01/19 18:48:37 - mmengine - INFO - Epoch(val) [60][350/625] eta: 0:00:09 time: 0.0353 data_time: 0.0003 memory: 843 +2024/01/19 18:48:39 - mmengine - INFO - Epoch(val) [60][400/625] eta: 0:00:08 time: 0.0351 data_time: 0.0004 memory: 843 +2024/01/19 18:48:40 - mmengine - INFO - Epoch(val) [60][450/625] eta: 0:00:06 time: 0.0337 data_time: 0.0003 memory: 843 +2024/01/19 18:48:42 - mmengine - INFO - Epoch(val) [60][500/625] eta: 0:00:04 time: 0.0262 data_time: 0.0002 memory: 843 +2024/01/19 18:48:43 - mmengine - INFO - Epoch(val) [60][550/625] eta: 0:00:02 time: 0.0264 data_time: 0.0002 memory: 843 +2024/01/19 18:48:44 - mmengine - INFO - Epoch(val) [60][600/625] eta: 0:00:00 time: 0.0262 data_time: 0.0002 memory: 843 +2024/01/19 18:48:58 - mmengine - INFO - Evaluating bbox... +2024/01/19 18:50:21 - mmengine - INFO - bbox_mAP_copypaste: 0.454 0.615 0.494 0.262 0.503 0.613 +2024/01/19 18:50:23 - mmengine - INFO - Epoch(val) [60][625/625] coco/bbox_mAP: 0.4540 coco/bbox_mAP_50: 0.6150 coco/bbox_mAP_75: 0.4940 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5030 coco/bbox_mAP_l: 0.6130 data_time: 0.0002 time: 0.0260 +2024/01/19 18:50:48 - mmengine - INFO - Epoch(train) [61][ 50/925] lr: 5.3975e-05 eta: 2:02:22 time: 0.4928 data_time: 0.1197 memory: 5372 grad_norm: 946.8974 loss: 416.4685 loss_cls: 148.7990 loss_bbox: 126.4215 loss_dfl: 141.2480 +2024/01/19 18:51:06 - mmengine - INFO - Epoch(train) [61][100/925] lr: 5.3975e-05 eta: 2:02:01 time: 0.3637 data_time: 0.0035 memory: 5666 grad_norm: 957.9547 loss: 417.2327 loss_cls: 148.2704 loss_bbox: 127.8700 loss_dfl: 141.0923 +2024/01/19 18:51:26 - mmengine - INFO - Epoch(train) [61][150/925] lr: 5.3975e-05 eta: 2:01:41 time: 0.3910 data_time: 0.0197 memory: 5279 grad_norm: 992.2074 loss: 411.8226 loss_cls: 146.0442 loss_bbox: 125.0389 loss_dfl: 140.7395 +2024/01/19 18:51:47 - mmengine - INFO - Epoch(train) [61][200/925] lr: 5.3975e-05 eta: 2:01:22 time: 0.4088 data_time: 0.0025 memory: 5372 grad_norm: 994.9907 loss: 406.8371 loss_cls: 143.7849 loss_bbox: 123.4713 loss_dfl: 139.5808 +2024/01/19 18:52:04 - mmengine - INFO - Epoch(train) [61][250/925] lr: 5.3975e-05 eta: 2:01:01 time: 0.3485 data_time: 0.0029 memory: 5546 grad_norm: 988.8275 loss: 418.3476 loss_cls: 149.1550 loss_bbox: 127.2324 loss_dfl: 141.9602 +2024/01/19 18:52:25 - mmengine - INFO - Epoch(train) [61][300/925] lr: 5.3975e-05 eta: 2:00:41 time: 0.4108 data_time: 0.0368 memory: 5186 grad_norm: 1057.6488 loss: 416.6875 loss_cls: 149.0540 loss_bbox: 125.7131 loss_dfl: 141.9204 +2024/01/19 18:52:48 - mmengine - INFO - Epoch(train) [61][350/925] lr: 5.3975e-05 eta: 2:00:22 time: 0.4645 data_time: 0.0106 memory: 5426 grad_norm: 951.8755 loss: 417.2032 loss_cls: 150.8127 loss_bbox: 124.6441 loss_dfl: 141.7464 +2024/01/19 18:53:07 - mmengine - INFO - Epoch(train) [61][400/925] lr: 5.3975e-05 eta: 2:00:02 time: 0.3852 data_time: 0.0025 memory: 5319 grad_norm: 1141.4656 loss: 417.1426 loss_cls: 149.4876 loss_bbox: 126.1828 loss_dfl: 141.4722 +2024/01/19 18:53:25 - mmengine - INFO - Epoch(train) [61][450/925] lr: 5.3975e-05 eta: 1:59:42 time: 0.3653 data_time: 0.0032 memory: 5212 grad_norm: 975.2114 loss: 407.1752 loss_cls: 144.5150 loss_bbox: 122.7336 loss_dfl: 139.9266 +2024/01/19 18:53:44 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:53:44 - mmengine - INFO - Epoch(train) [61][500/925] lr: 5.3975e-05 eta: 1:59:22 time: 0.3731 data_time: 0.0026 memory: 5106 grad_norm: 1022.3615 loss: 410.2784 loss_cls: 145.9060 loss_bbox: 124.1934 loss_dfl: 140.1790 +2024/01/19 18:54:03 - mmengine - INFO - Epoch(train) [61][550/925] lr: 5.3975e-05 eta: 1:59:01 time: 0.3798 data_time: 0.0036 memory: 5412 grad_norm: 1027.7542 loss: 414.7764 loss_cls: 147.3317 loss_bbox: 126.1132 loss_dfl: 141.3315 +2024/01/19 18:54:21 - mmengine - INFO - Epoch(train) [61][600/925] lr: 5.3975e-05 eta: 1:58:41 time: 0.3617 data_time: 0.0026 memory: 5252 grad_norm: 944.4075 loss: 418.9236 loss_cls: 149.6071 loss_bbox: 126.8777 loss_dfl: 142.4389 +2024/01/19 18:54:41 - mmengine - INFO - Epoch(train) [61][650/925] lr: 5.3975e-05 eta: 1:58:21 time: 0.4017 data_time: 0.0345 memory: 5546 grad_norm: 1075.7917 loss: 415.8677 loss_cls: 148.6265 loss_bbox: 125.8614 loss_dfl: 141.3797 +2024/01/19 18:55:02 - mmengine - INFO - Epoch(train) [61][700/925] lr: 5.3975e-05 eta: 1:58:01 time: 0.4072 data_time: 0.0028 memory: 5039 grad_norm: 1060.8255 loss: 409.3553 loss_cls: 146.0036 loss_bbox: 123.0819 loss_dfl: 140.2698 +2024/01/19 18:55:21 - mmengine - INFO - Epoch(train) [61][750/925] lr: 5.3975e-05 eta: 1:57:41 time: 0.3776 data_time: 0.0034 memory: 5452 grad_norm: inf loss: 414.2132 loss_cls: 147.8170 loss_bbox: 124.9139 loss_dfl: 141.4823 +2024/01/19 18:55:39 - mmengine - INFO - Epoch(train) [61][800/925] lr: 5.3975e-05 eta: 1:57:21 time: 0.3715 data_time: 0.0024 memory: 5252 grad_norm: 993.0250 loss: 407.5326 loss_cls: 145.1905 loss_bbox: 122.4023 loss_dfl: 139.9398 +2024/01/19 18:55:58 - mmengine - INFO - Epoch(train) [61][850/925] lr: 5.3975e-05 eta: 1:57:01 time: 0.3776 data_time: 0.0028 memory: 5266 grad_norm: 1055.7362 loss: 419.5290 loss_cls: 150.6074 loss_bbox: 127.0494 loss_dfl: 141.8723 +2024/01/19 18:56:17 - mmengine - INFO - Epoch(train) [61][900/925] lr: 5.3975e-05 eta: 1:56:41 time: 0.3843 data_time: 0.0025 memory: 5319 grad_norm: 1050.0133 loss: 416.1895 loss_cls: 149.9752 loss_bbox: 124.9043 loss_dfl: 141.3100 +2024/01/19 18:56:26 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 18:56:50 - mmengine - INFO - Epoch(train) [62][ 50/925] lr: 5.1500e-05 eta: 1:56:11 time: 0.4667 data_time: 0.0860 memory: 5546 grad_norm: 1000.8516 loss: 403.0037 loss_cls: 142.0932 loss_bbox: 120.7777 loss_dfl: 140.1328 +2024/01/19 18:57:09 - mmengine - INFO - Epoch(train) [62][100/925] lr: 5.1500e-05 eta: 1:55:51 time: 0.3830 data_time: 0.0059 memory: 5439 grad_norm: 937.0594 loss: 416.3905 loss_cls: 148.4977 loss_bbox: 126.2736 loss_dfl: 141.6192 +2024/01/19 18:57:28 - mmengine - INFO - Epoch(train) [62][150/925] lr: 5.1500e-05 eta: 1:55:31 time: 0.3846 data_time: 0.0045 memory: 5266 grad_norm: 1014.1813 loss: 417.0854 loss_cls: 149.3494 loss_bbox: 125.3622 loss_dfl: 142.3737 +2024/01/19 18:57:47 - mmengine - INFO - Epoch(train) [62][200/925] lr: 5.1500e-05 eta: 1:55:11 time: 0.3757 data_time: 0.0036 memory: 5519 grad_norm: 1024.2660 loss: 416.5407 loss_cls: 148.0482 loss_bbox: 126.5035 loss_dfl: 141.9890 +2024/01/19 18:58:08 - mmengine - INFO - Epoch(train) [62][250/925] lr: 5.1500e-05 eta: 1:54:51 time: 0.4224 data_time: 0.0158 memory: 5319 grad_norm: 1056.5334 loss: 412.5867 loss_cls: 146.7081 loss_bbox: 125.2394 loss_dfl: 140.6392 +2024/01/19 18:58:33 - mmengine - INFO - Epoch(train) [62][300/925] lr: 5.1500e-05 eta: 1:54:33 time: 0.5065 data_time: 0.0023 memory: 5159 grad_norm: 960.1973 loss: 411.9321 loss_cls: 147.1695 loss_bbox: 123.5995 loss_dfl: 141.1631 +2024/01/19 18:58:56 - mmengine - INFO - Epoch(train) [62][350/925] lr: 5.1500e-05 eta: 1:54:14 time: 0.4533 data_time: 0.0030 memory: 5759 grad_norm: 1095.0317 loss: 418.7415 loss_cls: 150.2903 loss_bbox: 126.2347 loss_dfl: 142.2165 +2024/01/19 18:59:14 - mmengine - INFO - Epoch(train) [62][400/925] lr: 5.1500e-05 eta: 1:53:54 time: 0.3616 data_time: 0.0028 memory: 5572 grad_norm: 913.7624 loss: 415.9839 loss_cls: 148.7861 loss_bbox: 125.3170 loss_dfl: 141.8809 +2024/01/19 18:59:33 - mmengine - INFO - Epoch(train) [62][450/925] lr: 5.1500e-05 eta: 1:53:33 time: 0.3701 data_time: 0.0061 memory: 5426 grad_norm: 1029.6929 loss: 410.2047 loss_cls: 145.5876 loss_bbox: 123.7535 loss_dfl: 140.8636 +2024/01/19 18:59:53 - mmengine - INFO - Epoch(train) [62][500/925] lr: 5.1500e-05 eta: 1:53:13 time: 0.3934 data_time: 0.0073 memory: 5279 grad_norm: 945.9978 loss: 413.5628 loss_cls: 146.7266 loss_bbox: 125.5554 loss_dfl: 141.2808 +2024/01/19 19:00:11 - mmengine - INFO - Epoch(train) [62][550/925] lr: 5.1500e-05 eta: 1:52:53 time: 0.3653 data_time: 0.0027 memory: 5466 grad_norm: 1004.2837 loss: 410.3399 loss_cls: 144.8143 loss_bbox: 124.8532 loss_dfl: 140.6724 +2024/01/19 19:00:20 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:00:30 - mmengine - INFO - Epoch(train) [62][600/925] lr: 5.1500e-05 eta: 1:52:33 time: 0.3785 data_time: 0.0026 memory: 5332 grad_norm: 1009.4006 loss: 419.5471 loss_cls: 151.5648 loss_bbox: 126.8103 loss_dfl: 141.1719 +2024/01/19 19:00:50 - mmengine - INFO - Epoch(train) [62][650/925] lr: 5.1500e-05 eta: 1:52:13 time: 0.3949 data_time: 0.0034 memory: 5693 grad_norm: 1002.1977 loss: 418.0019 loss_cls: 150.2349 loss_bbox: 126.4378 loss_dfl: 141.3292 +2024/01/19 19:01:08 - mmengine - INFO - Epoch(train) [62][700/925] lr: 5.1500e-05 eta: 1:51:53 time: 0.3713 data_time: 0.0027 memory: 5252 grad_norm: 1042.6298 loss: 414.6977 loss_cls: 149.2716 loss_bbox: 124.8794 loss_dfl: 140.5467 +2024/01/19 19:01:27 - mmengine - INFO - Epoch(train) [62][750/925] lr: 5.1500e-05 eta: 1:51:32 time: 0.3816 data_time: 0.0023 memory: 5799 grad_norm: 1072.7527 loss: 411.7019 loss_cls: 146.4591 loss_bbox: 124.2724 loss_dfl: 140.9704 +2024/01/19 19:01:46 - mmengine - INFO - Epoch(train) [62][800/925] lr: 5.1500e-05 eta: 1:51:12 time: 0.3749 data_time: 0.0041 memory: 5319 grad_norm: 1068.8397 loss: 415.7728 loss_cls: 148.1146 loss_bbox: 125.9969 loss_dfl: 141.6613 +2024/01/19 19:02:05 - mmengine - INFO - Epoch(train) [62][850/925] lr: 5.1500e-05 eta: 1:50:52 time: 0.3784 data_time: 0.0028 memory: 5372 grad_norm: 1006.4261 loss: 410.6342 loss_cls: 146.1537 loss_bbox: 124.6138 loss_dfl: 139.8666 +2024/01/19 19:02:24 - mmengine - INFO - Epoch(train) [62][900/925] lr: 5.1500e-05 eta: 1:50:32 time: 0.3787 data_time: 0.0055 memory: 5546 grad_norm: 1113.8298 loss: 415.7211 loss_cls: 148.8381 loss_bbox: 125.6385 loss_dfl: 141.2444 +2024/01/19 19:02:33 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:02:57 - mmengine - INFO - Epoch(train) [63][ 50/925] lr: 4.9025e-05 eta: 1:50:03 time: 0.4624 data_time: 0.0860 memory: 5266 grad_norm: 1021.5418 loss: 404.5453 loss_cls: 143.3506 loss_bbox: 122.1592 loss_dfl: 139.0355 +2024/01/19 19:03:17 - mmengine - INFO - Epoch(train) [63][100/925] lr: 4.9025e-05 eta: 1:49:43 time: 0.3995 data_time: 0.0027 memory: 5306 grad_norm: 1009.8090 loss: 412.4568 loss_cls: 148.2697 loss_bbox: 123.6519 loss_dfl: 140.5351 +2024/01/19 19:03:36 - mmengine - INFO - Epoch(train) [63][150/925] lr: 4.9025e-05 eta: 1:49:23 time: 0.3913 data_time: 0.0024 memory: 5252 grad_norm: 1024.5977 loss: 411.5961 loss_cls: 146.1209 loss_bbox: 124.6256 loss_dfl: 140.8495 +2024/01/19 19:03:55 - mmengine - INFO - Epoch(train) [63][200/925] lr: 4.9025e-05 eta: 1:49:03 time: 0.3841 data_time: 0.0023 memory: 5372 grad_norm: 1052.1782 loss: 417.3140 loss_cls: 148.1035 loss_bbox: 126.8467 loss_dfl: 142.3638 +2024/01/19 19:04:15 - mmengine - INFO - Epoch(train) [63][250/925] lr: 4.9025e-05 eta: 1:48:43 time: 0.3961 data_time: 0.0025 memory: 5466 grad_norm: 1050.5127 loss: 415.3249 loss_cls: 148.2299 loss_bbox: 125.6595 loss_dfl: 141.4355 +2024/01/19 19:04:35 - mmengine - INFO - Epoch(train) [63][300/925] lr: 4.9025e-05 eta: 1:48:23 time: 0.3930 data_time: 0.0024 memory: 5412 grad_norm: 1041.8966 loss: 408.4099 loss_cls: 144.5377 loss_bbox: 124.2711 loss_dfl: 139.6011 +2024/01/19 19:04:54 - mmengine - INFO - Epoch(train) [63][350/925] lr: 4.9025e-05 eta: 1:48:03 time: 0.3775 data_time: 0.0026 memory: 5439 grad_norm: 1026.5264 loss: 417.3173 loss_cls: 150.5488 loss_bbox: 125.7791 loss_dfl: 140.9894 +2024/01/19 19:05:13 - mmengine - INFO - Epoch(train) [63][400/925] lr: 4.9025e-05 eta: 1:47:43 time: 0.3850 data_time: 0.0026 memory: 5079 grad_norm: 986.6680 loss: 412.4099 loss_cls: 147.0124 loss_bbox: 124.2047 loss_dfl: 141.1928 +2024/01/19 19:05:32 - mmengine - INFO - Epoch(train) [63][450/925] lr: 4.9025e-05 eta: 1:47:22 time: 0.3806 data_time: 0.0029 memory: 5746 grad_norm: 971.5771 loss: 417.0586 loss_cls: 150.2092 loss_bbox: 125.5449 loss_dfl: 141.3046 +2024/01/19 19:05:51 - mmengine - INFO - Epoch(train) [63][500/925] lr: 4.9025e-05 eta: 1:47:02 time: 0.3788 data_time: 0.0027 memory: 5386 grad_norm: 1001.9771 loss: 407.0099 loss_cls: 143.9197 loss_bbox: 123.0033 loss_dfl: 140.0869 +2024/01/19 19:06:10 - mmengine - INFO - Epoch(train) [63][550/925] lr: 4.9025e-05 eta: 1:46:42 time: 0.3663 data_time: 0.0026 memory: 5599 grad_norm: 1004.5750 loss: 414.3302 loss_cls: 146.6326 loss_bbox: 126.3694 loss_dfl: 141.3282 +2024/01/19 19:06:29 - mmengine - INFO - Epoch(train) [63][600/925] lr: 4.9025e-05 eta: 1:46:22 time: 0.3901 data_time: 0.0028 memory: 5332 grad_norm: 1035.6471 loss: 414.3337 loss_cls: 147.3455 loss_bbox: 125.6731 loss_dfl: 141.3151 +2024/01/19 19:06:49 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:06:49 - mmengine - INFO - Epoch(train) [63][650/925] lr: 4.9025e-05 eta: 1:46:02 time: 0.4030 data_time: 0.0027 memory: 5492 grad_norm: 1199.4448 loss: 416.5655 loss_cls: 149.1316 loss_bbox: 126.0583 loss_dfl: 141.3755 +2024/01/19 19:07:08 - mmengine - INFO - Epoch(train) [63][700/925] lr: 4.9025e-05 eta: 1:45:42 time: 0.3725 data_time: 0.0025 memory: 5159 grad_norm: 1112.8042 loss: 406.0080 loss_cls: 142.6206 loss_bbox: 123.4063 loss_dfl: 139.9811 +2024/01/19 19:07:27 - mmengine - INFO - Epoch(train) [63][750/925] lr: 4.9025e-05 eta: 1:45:22 time: 0.3830 data_time: 0.0026 memory: 5226 grad_norm: 1030.9679 loss: 410.2450 loss_cls: 146.6737 loss_bbox: 123.6327 loss_dfl: 139.9386 +2024/01/19 19:07:47 - mmengine - INFO - Epoch(train) [63][800/925] lr: 4.9025e-05 eta: 1:45:02 time: 0.3980 data_time: 0.0028 memory: 5639 grad_norm: 1063.9756 loss: 413.4169 loss_cls: 148.2831 loss_bbox: 124.6293 loss_dfl: 140.5044 +2024/01/19 19:08:06 - mmengine - INFO - Epoch(train) [63][850/925] lr: 4.9025e-05 eta: 1:44:42 time: 0.3806 data_time: 0.0026 memory: 5439 grad_norm: 943.8904 loss: 417.0054 loss_cls: 147.7495 loss_bbox: 126.7937 loss_dfl: 142.4623 +2024/01/19 19:08:25 - mmengine - INFO - Epoch(train) [63][900/925] lr: 4.9025e-05 eta: 1:44:22 time: 0.3747 data_time: 0.0024 memory: 5252 grad_norm: inf loss: 414.9295 loss_cls: 148.0642 loss_bbox: 125.7113 loss_dfl: 141.1540 +2024/01/19 19:08:34 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:08:58 - mmengine - INFO - Epoch(train) [64][ 50/925] lr: 4.6550e-05 eta: 1:43:53 time: 0.4731 data_time: 0.0738 memory: 5612 grad_norm: 1072.9776 loss: 416.0051 loss_cls: 149.1036 loss_bbox: 125.6558 loss_dfl: 141.2457 +2024/01/19 19:09:17 - mmengine - INFO - Epoch(train) [64][100/925] lr: 4.6550e-05 eta: 1:43:33 time: 0.3895 data_time: 0.0026 memory: 5946 grad_norm: 1014.9301 loss: 409.3257 loss_cls: 145.3795 loss_bbox: 124.0485 loss_dfl: 139.8976 +2024/01/19 19:09:37 - mmengine - INFO - Epoch(train) [64][150/925] lr: 4.6550e-05 eta: 1:43:13 time: 0.4004 data_time: 0.0026 memory: 5426 grad_norm: 986.9502 loss: 406.4624 loss_cls: 144.4791 loss_bbox: 122.3658 loss_dfl: 139.6175 +2024/01/19 19:09:57 - mmengine - INFO - Epoch(train) [64][200/925] lr: 4.6550e-05 eta: 1:42:53 time: 0.3901 data_time: 0.0026 memory: 5279 grad_norm: 1041.6198 loss: 411.8957 loss_cls: 146.9235 loss_bbox: 124.1509 loss_dfl: 140.8212 +2024/01/19 19:10:15 - mmengine - INFO - Epoch(train) [64][250/925] lr: 4.6550e-05 eta: 1:42:33 time: 0.3685 data_time: 0.0027 memory: 5266 grad_norm: 1154.3696 loss: 407.9002 loss_cls: 144.8391 loss_bbox: 123.2652 loss_dfl: 139.7959 +2024/01/19 19:10:34 - mmengine - INFO - Epoch(train) [64][300/925] lr: 4.6550e-05 eta: 1:42:12 time: 0.3685 data_time: 0.0024 memory: 5292 grad_norm: 1050.3265 loss: 405.5713 loss_cls: 143.7516 loss_bbox: 122.3539 loss_dfl: 139.4658 +2024/01/19 19:10:54 - mmengine - INFO - Epoch(train) [64][350/925] lr: 4.6550e-05 eta: 1:41:52 time: 0.3943 data_time: 0.0028 memory: 5106 grad_norm: 933.5315 loss: 407.8528 loss_cls: 144.0462 loss_bbox: 123.1041 loss_dfl: 140.7025 +2024/01/19 19:11:13 - mmengine - INFO - Epoch(train) [64][400/925] lr: 4.6550e-05 eta: 1:41:32 time: 0.3833 data_time: 0.0025 memory: 5359 grad_norm: 953.7812 loss: 413.9144 loss_cls: 148.2397 loss_bbox: 125.1863 loss_dfl: 140.4884 +2024/01/19 19:11:32 - mmengine - INFO - Epoch(train) [64][450/925] lr: 4.6550e-05 eta: 1:41:12 time: 0.3804 data_time: 0.0025 memory: 5346 grad_norm: 970.3207 loss: 408.9123 loss_cls: 144.8285 loss_bbox: 123.6111 loss_dfl: 140.4727 +2024/01/19 19:11:51 - mmengine - INFO - Epoch(train) [64][500/925] lr: 4.6550e-05 eta: 1:40:52 time: 0.3840 data_time: 0.0025 memory: 5319 grad_norm: 923.8966 loss: 403.4382 loss_cls: 142.4175 loss_bbox: 121.9559 loss_dfl: 139.0648 +2024/01/19 19:12:11 - mmengine - INFO - Epoch(train) [64][550/925] lr: 4.6550e-05 eta: 1:40:32 time: 0.3874 data_time: 0.0026 memory: 5426 grad_norm: 1040.3825 loss: 406.5940 loss_cls: 142.9824 loss_bbox: 123.9624 loss_dfl: 139.6492 +2024/01/19 19:12:29 - mmengine - INFO - Epoch(train) [64][600/925] lr: 4.6550e-05 eta: 1:40:12 time: 0.3724 data_time: 0.0024 memory: 5479 grad_norm: 984.5338 loss: 410.6540 loss_cls: 146.6806 loss_bbox: 123.6261 loss_dfl: 140.3474 +2024/01/19 19:12:48 - mmengine - INFO - Epoch(train) [64][650/925] lr: 4.6550e-05 eta: 1:39:52 time: 0.3793 data_time: 0.0024 memory: 5466 grad_norm: 1105.2204 loss: 416.2192 loss_cls: 148.4986 loss_bbox: 126.2455 loss_dfl: 141.4751 +2024/01/19 19:13:08 - mmengine - INFO - Epoch(train) [64][700/925] lr: 4.6550e-05 eta: 1:39:32 time: 0.3889 data_time: 0.0025 memory: 6012 grad_norm: 1046.6984 loss: 418.2946 loss_cls: 150.9375 loss_bbox: 126.4792 loss_dfl: 140.8779 +2024/01/19 19:13:18 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:13:27 - mmengine - INFO - Epoch(train) [64][750/925] lr: 4.6550e-05 eta: 1:39:12 time: 0.3945 data_time: 0.0024 memory: 5679 grad_norm: 1042.9001 loss: 408.4661 loss_cls: 144.5095 loss_bbox: 123.8699 loss_dfl: 140.0867 +2024/01/19 19:13:47 - mmengine - INFO - Epoch(train) [64][800/925] lr: 4.6550e-05 eta: 1:38:52 time: 0.3841 data_time: 0.0026 memory: 5412 grad_norm: 1073.5390 loss: 409.4694 loss_cls: 145.1638 loss_bbox: 123.9202 loss_dfl: 140.3853 +2024/01/19 19:14:06 - mmengine - INFO - Epoch(train) [64][850/925] lr: 4.6550e-05 eta: 1:38:32 time: 0.3909 data_time: 0.0026 memory: 5146 grad_norm: 1070.4113 loss: 413.6631 loss_cls: 149.1800 loss_bbox: 123.7688 loss_dfl: 140.7143 +2024/01/19 19:14:25 - mmengine - INFO - Epoch(train) [64][900/925] lr: 4.6550e-05 eta: 1:38:12 time: 0.3761 data_time: 0.0031 memory: 5412 grad_norm: 963.3832 loss: 411.5775 loss_cls: 146.2976 loss_bbox: 123.9227 loss_dfl: 141.3572 +2024/01/19 19:14:34 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:14:57 - mmengine - INFO - Epoch(train) [65][ 50/925] lr: 4.4075e-05 eta: 1:37:42 time: 0.4477 data_time: 0.0870 memory: 5292 grad_norm: 1057.4901 loss: 411.2689 loss_cls: 145.4660 loss_bbox: 124.5457 loss_dfl: 141.2572 +2024/01/19 19:15:16 - mmengine - INFO - Epoch(train) [65][100/925] lr: 4.4075e-05 eta: 1:37:22 time: 0.3710 data_time: 0.0027 memory: 5199 grad_norm: 897.6532 loss: 411.3362 loss_cls: 146.0044 loss_bbox: 124.6022 loss_dfl: 140.7296 +2024/01/19 19:15:34 - mmengine - INFO - Epoch(train) [65][150/925] lr: 4.4075e-05 eta: 1:37:02 time: 0.3594 data_time: 0.0025 memory: 5479 grad_norm: 1133.9119 loss: 419.0778 loss_cls: 150.3097 loss_bbox: 126.8107 loss_dfl: 141.9574 +2024/01/19 19:15:52 - mmengine - INFO - Epoch(train) [65][200/925] lr: 4.4075e-05 eta: 1:36:42 time: 0.3680 data_time: 0.0025 memory: 5439 grad_norm: 1028.5400 loss: 404.0544 loss_cls: 142.8438 loss_bbox: 122.1543 loss_dfl: 139.0563 +2024/01/19 19:16:11 - mmengine - INFO - Epoch(train) [65][250/925] lr: 4.4075e-05 eta: 1:36:21 time: 0.3752 data_time: 0.0026 memory: 5319 grad_norm: 1036.9230 loss: 413.5984 loss_cls: 148.6359 loss_bbox: 123.9367 loss_dfl: 141.0258 +2024/01/19 19:16:29 - mmengine - INFO - Epoch(train) [65][300/925] lr: 4.4075e-05 eta: 1:36:01 time: 0.3626 data_time: 0.0028 memory: 5199 grad_norm: 1085.5426 loss: 409.5274 loss_cls: 146.7741 loss_bbox: 122.5454 loss_dfl: 140.2079 +2024/01/19 19:16:48 - mmengine - INFO - Epoch(train) [65][350/925] lr: 4.4075e-05 eta: 1:35:41 time: 0.3717 data_time: 0.0033 memory: 5359 grad_norm: 996.3864 loss: 409.7126 loss_cls: 145.1073 loss_bbox: 123.6601 loss_dfl: 140.9452 +2024/01/19 19:17:07 - mmengine - INFO - Epoch(train) [65][400/925] lr: 4.4075e-05 eta: 1:35:21 time: 0.3799 data_time: 0.0037 memory: 5399 grad_norm: 1103.7535 loss: 413.3795 loss_cls: 147.8656 loss_bbox: 124.4357 loss_dfl: 141.0782 +2024/01/19 19:17:25 - mmengine - INFO - Epoch(train) [65][450/925] lr: 4.4075e-05 eta: 1:35:01 time: 0.3646 data_time: 0.0037 memory: 5452 grad_norm: 1005.6866 loss: 409.9550 loss_cls: 145.2831 loss_bbox: 124.3220 loss_dfl: 140.3499 +2024/01/19 19:17:44 - mmengine - INFO - Epoch(train) [65][500/925] lr: 4.4075e-05 eta: 1:34:41 time: 0.3817 data_time: 0.0055 memory: 5666 grad_norm: 1081.2662 loss: 406.4395 loss_cls: 143.7529 loss_bbox: 123.1566 loss_dfl: 139.5301 +2024/01/19 19:18:02 - mmengine - INFO - Epoch(train) [65][550/925] lr: 4.4075e-05 eta: 1:34:20 time: 0.3656 data_time: 0.0034 memory: 5132 grad_norm: 1063.1682 loss: 406.3358 loss_cls: 144.0892 loss_bbox: 122.5176 loss_dfl: 139.7289 +2024/01/19 19:18:22 - mmengine - INFO - Epoch(train) [65][600/925] lr: 4.4075e-05 eta: 1:34:00 time: 0.3822 data_time: 0.0040 memory: 5346 grad_norm: 987.6373 loss: 412.1999 loss_cls: 146.4827 loss_bbox: 124.8186 loss_dfl: 140.8986 +2024/01/19 19:18:40 - mmengine - INFO - Epoch(train) [65][650/925] lr: 4.4075e-05 eta: 1:33:40 time: 0.3753 data_time: 0.0047 memory: 5786 grad_norm: 1154.1513 loss: 419.5060 loss_cls: 148.4135 loss_bbox: 128.1536 loss_dfl: 142.9389 +2024/01/19 19:19:00 - mmengine - INFO - Epoch(train) [65][700/925] lr: 4.4075e-05 eta: 1:33:20 time: 0.3842 data_time: 0.0040 memory: 5906 grad_norm: 946.3491 loss: 408.0265 loss_cls: 145.5360 loss_bbox: 122.6728 loss_dfl: 139.8178 +2024/01/19 19:19:18 - mmengine - INFO - Epoch(train) [65][750/925] lr: 4.4075e-05 eta: 1:33:00 time: 0.3592 data_time: 0.0032 memory: 5612 grad_norm: 1024.0744 loss: 410.9301 loss_cls: 145.6358 loss_bbox: 124.3744 loss_dfl: 140.9199 +2024/01/19 19:19:37 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:19:37 - mmengine - INFO - Epoch(train) [65][800/925] lr: 4.4075e-05 eta: 1:32:40 time: 0.3856 data_time: 0.0039 memory: 5279 grad_norm: 989.3446 loss: 412.0553 loss_cls: 145.5002 loss_bbox: 125.4927 loss_dfl: 141.0624 +2024/01/19 19:19:55 - mmengine - INFO - Epoch(train) [65][850/925] lr: 4.4075e-05 eta: 1:32:20 time: 0.3650 data_time: 0.0040 memory: 5292 grad_norm: 1018.7508 loss: 412.0178 loss_cls: 145.7497 loss_bbox: 124.7176 loss_dfl: 141.5505 +2024/01/19 19:20:14 - mmengine - INFO - Epoch(train) [65][900/925] lr: 4.4075e-05 eta: 1:31:59 time: 0.3665 data_time: 0.0027 memory: 5732 grad_norm: 1032.3999 loss: 413.9074 loss_cls: 147.7120 loss_bbox: 125.3197 loss_dfl: 140.8757 +2024/01/19 19:20:23 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:20:23 - mmengine - INFO - Saving checkpoint at 65 epochs +2024/01/19 19:20:32 - mmengine - INFO - Epoch(val) [65][ 50/625] eta: 0:00:20 time: 0.0364 data_time: 0.0008 memory: 5372 +2024/01/19 19:20:34 - mmengine - INFO - Epoch(val) [65][100/625] eta: 0:00:18 time: 0.0346 data_time: 0.0004 memory: 843 +2024/01/19 19:20:35 - mmengine - INFO - Epoch(val) [65][150/625] eta: 0:00:17 time: 0.0365 data_time: 0.0004 memory: 843 +2024/01/19 19:20:37 - mmengine - INFO - Epoch(val) [65][200/625] eta: 0:00:15 time: 0.0345 data_time: 0.0004 memory: 843 +2024/01/19 19:20:39 - mmengine - INFO - Epoch(val) [65][250/625] eta: 0:00:13 time: 0.0356 data_time: 0.0004 memory: 843 +2024/01/19 19:20:41 - mmengine - INFO - Epoch(val) [65][300/625] eta: 0:00:11 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 19:20:42 - mmengine - INFO - Epoch(val) [65][350/625] eta: 0:00:09 time: 0.0347 data_time: 0.0004 memory: 843 +2024/01/19 19:20:44 - mmengine - INFO - Epoch(val) [65][400/625] eta: 0:00:07 time: 0.0356 data_time: 0.0004 memory: 843 +2024/01/19 19:20:46 - mmengine - INFO - Epoch(val) [65][450/625] eta: 0:00:06 time: 0.0303 data_time: 0.0003 memory: 843 +2024/01/19 19:20:47 - mmengine - INFO - Epoch(val) [65][500/625] eta: 0:00:04 time: 0.0263 data_time: 0.0002 memory: 843 +2024/01/19 19:20:48 - mmengine - INFO - Epoch(val) [65][550/625] eta: 0:00:02 time: 0.0265 data_time: 0.0002 memory: 843 +2024/01/19 19:20:50 - mmengine - INFO - Epoch(val) [65][600/625] eta: 0:00:00 time: 0.0261 data_time: 0.0002 memory: 843 +2024/01/19 19:21:04 - mmengine - INFO - Evaluating bbox... +2024/01/19 19:22:25 - mmengine - INFO - bbox_mAP_copypaste: 0.455 0.616 0.496 0.260 0.503 0.614 +2024/01/19 19:22:28 - mmengine - INFO - Epoch(val) [65][625/625] coco/bbox_mAP: 0.4550 coco/bbox_mAP_50: 0.6160 coco/bbox_mAP_75: 0.4960 coco/bbox_mAP_s: 0.2600 coco/bbox_mAP_m: 0.5030 coco/bbox_mAP_l: 0.6140 data_time: 0.0002 time: 0.0258 +2024/01/19 19:22:52 - mmengine - INFO - Epoch(train) [66][ 50/925] lr: 4.1600e-05 eta: 1:31:30 time: 0.4931 data_time: 0.1247 memory: 5559 grad_norm: 1075.5439 loss: 407.8119 loss_cls: 143.8379 loss_bbox: 124.0510 loss_dfl: 139.9229 +2024/01/19 19:23:11 - mmengine - INFO - Epoch(train) [66][100/925] lr: 4.1600e-05 eta: 1:31:10 time: 0.3797 data_time: 0.0028 memory: 5319 grad_norm: 958.5163 loss: 412.2857 loss_cls: 147.0785 loss_bbox: 124.3090 loss_dfl: 140.8983 +2024/01/19 19:23:31 - mmengine - INFO - Epoch(train) [66][150/925] lr: 4.1600e-05 eta: 1:30:50 time: 0.3827 data_time: 0.0056 memory: 5559 grad_norm: 1207.7907 loss: 412.9846 loss_cls: 147.8199 loss_bbox: 124.2443 loss_dfl: 140.9204 +2024/01/19 19:23:50 - mmengine - INFO - Epoch(train) [66][200/925] lr: 4.1600e-05 eta: 1:30:30 time: 0.3798 data_time: 0.0029 memory: 5346 grad_norm: 1072.7199 loss: 410.0507 loss_cls: 145.4162 loss_bbox: 123.6966 loss_dfl: 140.9379 +2024/01/19 19:24:09 - mmengine - INFO - Epoch(train) [66][250/925] lr: 4.1600e-05 eta: 1:30:10 time: 0.3903 data_time: 0.0086 memory: 5452 grad_norm: inf loss: 415.5219 loss_cls: 149.8037 loss_bbox: 124.4847 loss_dfl: 141.2335 +2024/01/19 19:24:29 - mmengine - INFO - Epoch(train) [66][300/925] lr: 4.1600e-05 eta: 1:29:51 time: 0.3928 data_time: 0.0038 memory: 5479 grad_norm: 1097.8493 loss: 412.9119 loss_cls: 147.2224 loss_bbox: 124.9975 loss_dfl: 140.6920 +2024/01/19 19:24:48 - mmengine - INFO - Epoch(train) [66][350/925] lr: 4.1600e-05 eta: 1:29:30 time: 0.3801 data_time: 0.0026 memory: 5306 grad_norm: 1112.3106 loss: 415.5713 loss_cls: 147.9622 loss_bbox: 126.1086 loss_dfl: 141.5005 +2024/01/19 19:25:07 - mmengine - INFO - Epoch(train) [66][400/925] lr: 4.1600e-05 eta: 1:29:10 time: 0.3844 data_time: 0.0025 memory: 5412 grad_norm: 1039.6677 loss: 419.2609 loss_cls: 150.2279 loss_bbox: 126.9296 loss_dfl: 142.1034 +2024/01/19 19:25:30 - mmengine - INFO - Epoch(train) [66][450/925] lr: 4.1600e-05 eta: 1:28:51 time: 0.4508 data_time: 0.0505 memory: 5426 grad_norm: 985.1896 loss: 417.0467 loss_cls: 148.8973 loss_bbox: 126.2702 loss_dfl: 141.8792 +2024/01/19 19:25:52 - mmengine - INFO - Epoch(train) [66][500/925] lr: 4.1600e-05 eta: 1:28:32 time: 0.4479 data_time: 0.0605 memory: 5412 grad_norm: 1038.0825 loss: 411.2218 loss_cls: 145.7933 loss_bbox: 124.5293 loss_dfl: 140.8992 +2024/01/19 19:26:11 - mmengine - INFO - Epoch(train) [66][550/925] lr: 4.1600e-05 eta: 1:28:12 time: 0.3839 data_time: 0.0037 memory: 5572 grad_norm: 956.2206 loss: 406.8672 loss_cls: 142.6320 loss_bbox: 124.4231 loss_dfl: 139.8121 +2024/01/19 19:26:31 - mmengine - INFO - Epoch(train) [66][600/925] lr: 4.1600e-05 eta: 1:27:52 time: 0.3805 data_time: 0.0074 memory: 5506 grad_norm: 1082.2773 loss: 410.6798 loss_cls: 146.1291 loss_bbox: 123.8559 loss_dfl: 140.6947 +2024/01/19 19:26:54 - mmengine - INFO - Epoch(train) [66][650/925] lr: 4.1600e-05 eta: 1:27:33 time: 0.4774 data_time: 0.0296 memory: 5439 grad_norm: 939.7013 loss: 411.9307 loss_cls: 145.7889 loss_bbox: 125.6565 loss_dfl: 140.4852 +2024/01/19 19:27:17 - mmengine - INFO - Epoch(train) [66][700/925] lr: 4.1600e-05 eta: 1:27:14 time: 0.4541 data_time: 0.0049 memory: 5186 grad_norm: 1079.1467 loss: 406.7630 loss_cls: 143.8366 loss_bbox: 122.7909 loss_dfl: 140.1355 +2024/01/19 19:27:40 - mmengine - INFO - Epoch(train) [66][750/925] lr: 4.1600e-05 eta: 1:26:54 time: 0.4463 data_time: 0.0036 memory: 5492 grad_norm: 957.5011 loss: 403.7356 loss_cls: 141.6395 loss_bbox: 122.3626 loss_dfl: 139.7335 +2024/01/19 19:27:59 - mmengine - INFO - Epoch(train) [66][800/925] lr: 4.1600e-05 eta: 1:26:34 time: 0.3884 data_time: 0.0029 memory: 5626 grad_norm: 1012.3813 loss: 413.2848 loss_cls: 146.3467 loss_bbox: 125.3215 loss_dfl: 141.6165 +2024/01/19 19:28:19 - mmengine - INFO - Epoch(train) [66][850/925] lr: 4.1600e-05 eta: 1:26:14 time: 0.3906 data_time: 0.0029 memory: 5306 grad_norm: 1022.2569 loss: 409.6741 loss_cls: 145.5206 loss_bbox: 124.0991 loss_dfl: 140.0544 +2024/01/19 19:28:29 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:28:39 - mmengine - INFO - Epoch(train) [66][900/925] lr: 4.1600e-05 eta: 1:25:55 time: 0.4022 data_time: 0.0028 memory: 5252 grad_norm: 970.6136 loss: 403.2478 loss_cls: 141.7809 loss_bbox: 121.9975 loss_dfl: 139.4693 +2024/01/19 19:28:48 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:29:12 - mmengine - INFO - Epoch(train) [67][ 50/925] lr: 3.9125e-05 eta: 1:25:25 time: 0.4770 data_time: 0.0940 memory: 5532 grad_norm: 1090.7735 loss: 408.8858 loss_cls: 144.3391 loss_bbox: 124.3235 loss_dfl: 140.2233 +2024/01/19 19:29:32 - mmengine - INFO - Epoch(train) [67][100/925] lr: 3.9125e-05 eta: 1:25:06 time: 0.3925 data_time: 0.0028 memory: 5279 grad_norm: 1112.6945 loss: 406.9382 loss_cls: 144.0595 loss_bbox: 122.9897 loss_dfl: 139.8889 +2024/01/19 19:29:52 - mmengine - INFO - Epoch(train) [67][150/925] lr: 3.9125e-05 eta: 1:24:46 time: 0.3940 data_time: 0.0028 memory: 5666 grad_norm: 961.6159 loss: 419.1711 loss_cls: 149.5088 loss_bbox: 127.1462 loss_dfl: 142.5160 +2024/01/19 19:30:11 - mmengine - INFO - Epoch(train) [67][200/925] lr: 3.9125e-05 eta: 1:24:26 time: 0.3874 data_time: 0.0039 memory: 5732 grad_norm: 930.2924 loss: 412.6382 loss_cls: 147.1768 loss_bbox: 124.4670 loss_dfl: 140.9944 +2024/01/19 19:30:31 - mmengine - INFO - Epoch(train) [67][250/925] lr: 3.9125e-05 eta: 1:24:06 time: 0.3975 data_time: 0.0029 memory: 5412 grad_norm: 1051.2388 loss: 410.2743 loss_cls: 145.3954 loss_bbox: 124.2762 loss_dfl: 140.6028 +2024/01/19 19:30:51 - mmengine - INFO - Epoch(train) [67][300/925] lr: 3.9125e-05 eta: 1:23:46 time: 0.3965 data_time: 0.0028 memory: 5359 grad_norm: 1034.3450 loss: 414.5305 loss_cls: 146.3966 loss_bbox: 126.9317 loss_dfl: 141.2022 +2024/01/19 19:31:10 - mmengine - INFO - Epoch(train) [67][350/925] lr: 3.9125e-05 eta: 1:23:26 time: 0.3885 data_time: 0.0028 memory: 5693 grad_norm: 1047.0386 loss: 405.9374 loss_cls: 141.9333 loss_bbox: 123.9876 loss_dfl: 140.0165 +2024/01/19 19:31:32 - mmengine - INFO - Epoch(train) [67][400/925] lr: 3.9125e-05 eta: 1:23:07 time: 0.4381 data_time: 0.0058 memory: 5399 grad_norm: 1042.5665 loss: 405.9399 loss_cls: 144.0156 loss_bbox: 122.6004 loss_dfl: 139.3238 +2024/01/19 19:31:55 - mmengine - INFO - Epoch(train) [67][450/925] lr: 3.9125e-05 eta: 1:22:47 time: 0.4605 data_time: 0.0410 memory: 5212 grad_norm: 1065.6669 loss: 416.3696 loss_cls: 148.2747 loss_bbox: 126.5587 loss_dfl: 141.5362 +2024/01/19 19:32:16 - mmengine - INFO - Epoch(train) [67][500/925] lr: 3.9125e-05 eta: 1:22:28 time: 0.4069 data_time: 0.0188 memory: 5239 grad_norm: 1068.1024 loss: 413.2280 loss_cls: 146.7517 loss_bbox: 125.2907 loss_dfl: 141.1857 +2024/01/19 19:32:35 - mmengine - INFO - Epoch(train) [67][550/925] lr: 3.9125e-05 eta: 1:22:07 time: 0.3797 data_time: 0.0036 memory: 5199 grad_norm: 1127.7735 loss: 408.2357 loss_cls: 144.3265 loss_bbox: 123.5001 loss_dfl: 140.4091 +2024/01/19 19:32:54 - mmengine - INFO - Epoch(train) [67][600/925] lr: 3.9125e-05 eta: 1:21:48 time: 0.3921 data_time: 0.0040 memory: 5679 grad_norm: 1165.3919 loss: 421.2902 loss_cls: 150.0956 loss_bbox: 128.4102 loss_dfl: 142.7844 +2024/01/19 19:33:14 - mmengine - INFO - Epoch(train) [67][650/925] lr: 3.9125e-05 eta: 1:21:28 time: 0.3908 data_time: 0.0028 memory: 5346 grad_norm: 1108.0716 loss: 416.5613 loss_cls: 149.0887 loss_bbox: 125.6862 loss_dfl: 141.7864 +2024/01/19 19:33:33 - mmengine - INFO - Epoch(train) [67][700/925] lr: 3.9125e-05 eta: 1:21:08 time: 0.3893 data_time: 0.0028 memory: 5546 grad_norm: 1055.9614 loss: 412.5001 loss_cls: 147.7251 loss_bbox: 124.6683 loss_dfl: 140.1068 +2024/01/19 19:33:53 - mmengine - INFO - Epoch(train) [67][750/925] lr: 3.9125e-05 eta: 1:20:48 time: 0.3889 data_time: 0.0045 memory: 5279 grad_norm: 1076.8116 loss: 407.4705 loss_cls: 143.1977 loss_bbox: 124.0698 loss_dfl: 140.2030 +2024/01/19 19:34:17 - mmengine - INFO - Epoch(train) [67][800/925] lr: 3.9125e-05 eta: 1:20:29 time: 0.4911 data_time: 0.0222 memory: 5506 grad_norm: 954.6576 loss: 412.1852 loss_cls: 144.5244 loss_bbox: 126.9803 loss_dfl: 140.6804 +2024/01/19 19:34:40 - mmengine - INFO - Epoch(train) [67][850/925] lr: 3.9125e-05 eta: 1:20:09 time: 0.4543 data_time: 0.0158 memory: 5479 grad_norm: 973.5542 loss: 405.0628 loss_cls: 143.9027 loss_bbox: 122.1313 loss_dfl: 139.0288 +2024/01/19 19:34:59 - mmengine - INFO - Epoch(train) [67][900/925] lr: 3.9125e-05 eta: 1:19:49 time: 0.3701 data_time: 0.0029 memory: 5532 grad_norm: 1123.0885 loss: 400.7181 loss_cls: 141.1155 loss_bbox: 121.0562 loss_dfl: 138.5464 +2024/01/19 19:35:08 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:35:24 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:35:33 - mmengine - INFO - Epoch(train) [68][ 50/925] lr: 3.6650e-05 eta: 1:19:20 time: 0.4941 data_time: 0.1072 memory: 5439 grad_norm: 1003.5951 loss: 410.4104 loss_cls: 144.3370 loss_bbox: 125.3255 loss_dfl: 140.7479 +2024/01/19 19:35:53 - mmengine - INFO - Epoch(train) [68][100/925] lr: 3.6650e-05 eta: 1:19:00 time: 0.3873 data_time: 0.0029 memory: 5719 grad_norm: 1015.0777 loss: 413.1194 loss_cls: 146.0748 loss_bbox: 125.5695 loss_dfl: 141.4752 +2024/01/19 19:36:13 - mmengine - INFO - Epoch(train) [68][150/925] lr: 3.6650e-05 eta: 1:18:40 time: 0.3931 data_time: 0.0028 memory: 5466 grad_norm: 982.8744 loss: 406.0217 loss_cls: 144.1081 loss_bbox: 121.9948 loss_dfl: 139.9187 +2024/01/19 19:36:32 - mmengine - INFO - Epoch(train) [68][200/925] lr: 3.6650e-05 eta: 1:18:20 time: 0.3807 data_time: 0.0028 memory: 5466 grad_norm: 1042.0707 loss: 414.1408 loss_cls: 146.8043 loss_bbox: 126.0798 loss_dfl: 141.2567 +2024/01/19 19:36:51 - mmengine - INFO - Epoch(train) [68][250/925] lr: 3.6650e-05 eta: 1:18:00 time: 0.3947 data_time: 0.0029 memory: 5239 grad_norm: 1063.1757 loss: 413.9722 loss_cls: 147.9400 loss_bbox: 124.5902 loss_dfl: 141.4420 +2024/01/19 19:37:09 - mmengine - INFO - Epoch(train) [68][300/925] lr: 3.6650e-05 eta: 1:17:40 time: 0.3580 data_time: 0.0027 memory: 5399 grad_norm: 1056.0481 loss: 411.8439 loss_cls: 145.6772 loss_bbox: 125.7795 loss_dfl: 140.3872 +2024/01/19 19:37:29 - mmengine - INFO - Epoch(train) [68][350/925] lr: 3.6650e-05 eta: 1:17:20 time: 0.3958 data_time: 0.0035 memory: 5226 grad_norm: 1061.9979 loss: 403.9515 loss_cls: 142.5467 loss_bbox: 121.8033 loss_dfl: 139.6015 +2024/01/19 19:37:50 - mmengine - INFO - Epoch(train) [68][400/925] lr: 3.6650e-05 eta: 1:17:01 time: 0.4075 data_time: 0.0031 memory: 5426 grad_norm: 1003.0941 loss: 410.2145 loss_cls: 146.1735 loss_bbox: 123.4017 loss_dfl: 140.6393 +2024/01/19 19:38:10 - mmengine - INFO - Epoch(train) [68][450/925] lr: 3.6650e-05 eta: 1:16:41 time: 0.4005 data_time: 0.0196 memory: 5466 grad_norm: inf loss: 410.1365 loss_cls: 146.1676 loss_bbox: 123.2757 loss_dfl: 140.6933 +2024/01/19 19:38:33 - mmengine - INFO - Epoch(train) [68][500/925] lr: 3.6650e-05 eta: 1:16:22 time: 0.4757 data_time: 0.0803 memory: 5306 grad_norm: 984.8321 loss: 410.1164 loss_cls: 144.5481 loss_bbox: 124.7785 loss_dfl: 140.7897 +2024/01/19 19:38:57 - mmengine - INFO - Epoch(train) [68][550/925] lr: 3.6650e-05 eta: 1:16:02 time: 0.4770 data_time: 0.0092 memory: 5506 grad_norm: 987.2461 loss: 416.6860 loss_cls: 148.5909 loss_bbox: 126.4003 loss_dfl: 141.6948 +2024/01/19 19:39:16 - mmengine - INFO - Epoch(train) [68][600/925] lr: 3.6650e-05 eta: 1:15:42 time: 0.3806 data_time: 0.0026 memory: 5492 grad_norm: 988.4049 loss: 410.5438 loss_cls: 146.7770 loss_bbox: 123.4461 loss_dfl: 140.3207 +2024/01/19 19:39:36 - mmengine - INFO - Epoch(train) [68][650/925] lr: 3.6650e-05 eta: 1:15:22 time: 0.3934 data_time: 0.0034 memory: 5492 grad_norm: 965.0472 loss: 409.6219 loss_cls: 146.1583 loss_bbox: 122.7420 loss_dfl: 140.7216 +2024/01/19 19:39:56 - mmengine - INFO - Epoch(train) [68][700/925] lr: 3.6650e-05 eta: 1:15:03 time: 0.3948 data_time: 0.0043 memory: 5466 grad_norm: 1062.3667 loss: 417.7840 loss_cls: 148.9536 loss_bbox: 127.7786 loss_dfl: 141.0518 +2024/01/19 19:40:15 - mmengine - INFO - Epoch(train) [68][750/925] lr: 3.6650e-05 eta: 1:14:42 time: 0.3738 data_time: 0.0035 memory: 5172 grad_norm: 1028.7420 loss: 414.8459 loss_cls: 149.6845 loss_bbox: 124.5762 loss_dfl: 140.5852 +2024/01/19 19:40:33 - mmengine - INFO - Epoch(train) [68][800/925] lr: 3.6650e-05 eta: 1:14:22 time: 0.3707 data_time: 0.0034 memory: 5359 grad_norm: 963.3058 loss: 411.7164 loss_cls: 147.4847 loss_bbox: 124.1007 loss_dfl: 140.1310 +2024/01/19 19:40:53 - mmengine - INFO - Epoch(train) [68][850/925] lr: 3.6650e-05 eta: 1:14:02 time: 0.3878 data_time: 0.0028 memory: 5812 grad_norm: 988.7634 loss: 414.4984 loss_cls: 146.9929 loss_bbox: 126.6540 loss_dfl: 140.8516 +2024/01/19 19:41:13 - mmengine - INFO - Epoch(train) [68][900/925] lr: 3.6650e-05 eta: 1:13:43 time: 0.4038 data_time: 0.0028 memory: 5626 grad_norm: 941.6954 loss: 403.3218 loss_cls: 141.7230 loss_bbox: 122.3804 loss_dfl: 139.2184 +2024/01/19 19:41:21 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:41:46 - mmengine - INFO - Epoch(train) [69][ 50/925] lr: 3.4175e-05 eta: 1:13:13 time: 0.4875 data_time: 0.0998 memory: 5426 grad_norm: 1062.0477 loss: 405.9373 loss_cls: 142.3364 loss_bbox: 123.2219 loss_dfl: 140.3791 +2024/01/19 19:42:06 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:42:06 - mmengine - INFO - Epoch(train) [69][100/925] lr: 3.4175e-05 eta: 1:12:53 time: 0.3958 data_time: 0.0075 memory: 5266 grad_norm: 965.7602 loss: 409.0040 loss_cls: 145.0086 loss_bbox: 123.6077 loss_dfl: 140.3877 +2024/01/19 19:42:25 - mmengine - INFO - Epoch(train) [69][150/925] lr: 3.4175e-05 eta: 1:12:33 time: 0.3773 data_time: 0.0030 memory: 5786 grad_norm: 998.0744 loss: 410.4302 loss_cls: 145.8000 loss_bbox: 124.2089 loss_dfl: 140.4213 +2024/01/19 19:42:44 - mmengine - INFO - Epoch(train) [69][200/925] lr: 3.4175e-05 eta: 1:12:13 time: 0.3838 data_time: 0.0029 memory: 5359 grad_norm: 985.8295 loss: 414.5795 loss_cls: 147.9314 loss_bbox: 125.4225 loss_dfl: 141.2256 +2024/01/19 19:43:03 - mmengine - INFO - Epoch(train) [69][250/925] lr: 3.4175e-05 eta: 1:11:53 time: 0.3787 data_time: 0.0027 memory: 5346 grad_norm: 1056.4859 loss: 408.2294 loss_cls: 144.7713 loss_bbox: 123.3151 loss_dfl: 140.1430 +2024/01/19 19:43:22 - mmengine - INFO - Epoch(train) [69][300/925] lr: 3.4175e-05 eta: 1:11:33 time: 0.3832 data_time: 0.0027 memory: 5386 grad_norm: 1020.9466 loss: 412.9465 loss_cls: 146.4551 loss_bbox: 125.7106 loss_dfl: 140.7809 +2024/01/19 19:43:41 - mmengine - INFO - Epoch(train) [69][350/925] lr: 3.4175e-05 eta: 1:11:13 time: 0.3721 data_time: 0.0026 memory: 5372 grad_norm: 1054.7455 loss: 405.8431 loss_cls: 144.1780 loss_bbox: 122.1660 loss_dfl: 139.4991 +2024/01/19 19:44:00 - mmengine - INFO - Epoch(train) [69][400/925] lr: 3.4175e-05 eta: 1:10:53 time: 0.3839 data_time: 0.0037 memory: 5359 grad_norm: 1096.1799 loss: 406.6274 loss_cls: 144.4046 loss_bbox: 122.5592 loss_dfl: 139.6636 +2024/01/19 19:44:19 - mmengine - INFO - Epoch(train) [69][450/925] lr: 3.4175e-05 eta: 1:10:33 time: 0.3806 data_time: 0.0030 memory: 5199 grad_norm: 1027.7230 loss: 415.3204 loss_cls: 148.1720 loss_bbox: 125.6439 loss_dfl: 141.5045 +2024/01/19 19:44:37 - mmengine - INFO - Epoch(train) [69][500/925] lr: 3.4175e-05 eta: 1:10:13 time: 0.3568 data_time: 0.0027 memory: 5146 grad_norm: 977.7111 loss: 412.2123 loss_cls: 146.6820 loss_bbox: 124.8193 loss_dfl: 140.7110 +2024/01/19 19:44:56 - mmengine - INFO - Epoch(train) [69][550/925] lr: 3.4175e-05 eta: 1:09:53 time: 0.3788 data_time: 0.0037 memory: 5239 grad_norm: 999.8949 loss: 409.9784 loss_cls: 143.9531 loss_bbox: 124.5168 loss_dfl: 141.5085 +2024/01/19 19:45:16 - mmengine - INFO - Epoch(train) [69][600/925] lr: 3.4175e-05 eta: 1:09:33 time: 0.3908 data_time: 0.0034 memory: 5506 grad_norm: 934.3041 loss: 410.7357 loss_cls: 146.0931 loss_bbox: 124.3254 loss_dfl: 140.3172 +2024/01/19 19:45:34 - mmengine - INFO - Epoch(train) [69][650/925] lr: 3.4175e-05 eta: 1:09:13 time: 0.3674 data_time: 0.0034 memory: 5959 grad_norm: 1001.0254 loss: 406.5091 loss_cls: 141.6507 loss_bbox: 124.8607 loss_dfl: 139.9977 +2024/01/19 19:45:52 - mmengine - INFO - Epoch(train) [69][700/925] lr: 3.4175e-05 eta: 1:08:53 time: 0.3631 data_time: 0.0025 memory: 5426 grad_norm: 1023.4852 loss: 411.3384 loss_cls: 145.4909 loss_bbox: 125.4448 loss_dfl: 140.4027 +2024/01/19 19:46:11 - mmengine - INFO - Epoch(train) [69][750/925] lr: 3.4175e-05 eta: 1:08:33 time: 0.3858 data_time: 0.0028 memory: 5386 grad_norm: 1064.1740 loss: 413.8732 loss_cls: 148.3030 loss_bbox: 124.6396 loss_dfl: 140.9307 +2024/01/19 19:46:30 - mmengine - INFO - Epoch(train) [69][800/925] lr: 3.4175e-05 eta: 1:08:13 time: 0.3726 data_time: 0.0035 memory: 5612 grad_norm: 1017.7633 loss: 414.9216 loss_cls: 148.6872 loss_bbox: 124.7495 loss_dfl: 141.4849 +2024/01/19 19:46:48 - mmengine - INFO - Epoch(train) [69][850/925] lr: 3.4175e-05 eta: 1:07:52 time: 0.3547 data_time: 0.0030 memory: 5759 grad_norm: 1127.2700 loss: 403.6938 loss_cls: 141.1429 loss_bbox: 122.7835 loss_dfl: 139.7675 +2024/01/19 19:47:06 - mmengine - INFO - Epoch(train) [69][900/925] lr: 3.4175e-05 eta: 1:07:32 time: 0.3697 data_time: 0.0038 memory: 5466 grad_norm: 1023.6942 loss: 406.1842 loss_cls: 141.6972 loss_bbox: 124.1295 loss_dfl: 140.3575 +2024/01/19 19:47:15 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:47:17 - mmengine - INFO - Epoch(val) [69][ 50/625] eta: 0:00:20 time: 0.0361 data_time: 0.0008 memory: 5266 +2024/01/19 19:47:19 - mmengine - INFO - Epoch(val) [69][100/625] eta: 0:00:18 time: 0.0362 data_time: 0.0003 memory: 843 +2024/01/19 19:47:21 - mmengine - INFO - Epoch(val) [69][150/625] eta: 0:00:17 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 19:47:23 - mmengine - INFO - Epoch(val) [69][200/625] eta: 0:00:15 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 19:47:25 - mmengine - INFO - Epoch(val) [69][250/625] eta: 0:00:13 time: 0.0342 data_time: 0.0003 memory: 843 +2024/01/19 19:47:26 - mmengine - INFO - Epoch(val) [69][300/625] eta: 0:00:11 time: 0.0357 data_time: 0.0003 memory: 843 +2024/01/19 19:47:28 - mmengine - INFO - Epoch(val) [69][350/625] eta: 0:00:09 time: 0.0348 data_time: 0.0004 memory: 843 +2024/01/19 19:47:30 - mmengine - INFO - Epoch(val) [69][400/625] eta: 0:00:07 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 19:47:32 - mmengine - INFO - Epoch(val) [69][450/625] eta: 0:00:06 time: 0.0369 data_time: 0.0004 memory: 843 +2024/01/19 19:47:33 - mmengine - INFO - Epoch(val) [69][500/625] eta: 0:00:04 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 19:47:35 - mmengine - INFO - Epoch(val) [69][550/625] eta: 0:00:02 time: 0.0349 data_time: 0.0004 memory: 843 +2024/01/19 19:47:37 - mmengine - INFO - Epoch(val) [69][600/625] eta: 0:00:00 time: 0.0364 data_time: 0.0003 memory: 843 +2024/01/19 19:47:51 - mmengine - INFO - Evaluating bbox... +2024/01/19 19:49:13 - mmengine - INFO - bbox_mAP_copypaste: 0.455 0.617 0.496 0.261 0.503 0.614 +2024/01/19 19:49:16 - mmengine - INFO - Epoch(val) [69][625/625] coco/bbox_mAP: 0.4550 coco/bbox_mAP_50: 0.6170 coco/bbox_mAP_75: 0.4960 coco/bbox_mAP_s: 0.2610 coco/bbox_mAP_m: 0.5030 coco/bbox_mAP_l: 0.6140 data_time: 0.0003 time: 0.0358 +2024/01/19 19:49:41 - mmengine - INFO - Epoch(train) [70][ 50/925] lr: 3.1700e-05 eta: 1:07:03 time: 0.5035 data_time: 0.1455 memory: 5279 grad_norm: 1046.0854 loss: 407.6095 loss_cls: 143.5399 loss_bbox: 123.4995 loss_dfl: 140.5702 +2024/01/19 19:50:00 - mmengine - INFO - Epoch(train) [70][100/925] lr: 3.1700e-05 eta: 1:06:43 time: 0.3701 data_time: 0.0055 memory: 5439 grad_norm: 966.7515 loss: 411.7509 loss_cls: 145.5639 loss_bbox: 124.9207 loss_dfl: 141.2663 +2024/01/19 19:50:19 - mmengine - INFO - Epoch(train) [70][150/925] lr: 3.1700e-05 eta: 1:06:23 time: 0.3910 data_time: 0.0030 memory: 5266 grad_norm: 1017.1877 loss: 411.9535 loss_cls: 147.1392 loss_bbox: 124.0645 loss_dfl: 140.7498 +2024/01/19 19:50:28 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:50:38 - mmengine - INFO - Epoch(train) [70][200/925] lr: 3.1700e-05 eta: 1:06:03 time: 0.3785 data_time: 0.0028 memory: 5439 grad_norm: 1032.7130 loss: 404.0500 loss_cls: 143.2753 loss_bbox: 121.6074 loss_dfl: 139.1672 +2024/01/19 19:50:56 - mmengine - INFO - Epoch(train) [70][250/925] lr: 3.1700e-05 eta: 1:05:43 time: 0.3597 data_time: 0.0026 memory: 5252 grad_norm: 1010.7128 loss: 400.6221 loss_cls: 141.7085 loss_bbox: 119.9264 loss_dfl: 138.9872 +2024/01/19 19:51:15 - mmengine - INFO - Epoch(train) [70][300/925] lr: 3.1700e-05 eta: 1:05:23 time: 0.3675 data_time: 0.0034 memory: 5239 grad_norm: 1017.9755 loss: 412.7927 loss_cls: 147.6655 loss_bbox: 124.5643 loss_dfl: 140.5629 +2024/01/19 19:51:34 - mmengine - INFO - Epoch(train) [70][350/925] lr: 3.1700e-05 eta: 1:05:03 time: 0.3843 data_time: 0.0027 memory: 5599 grad_norm: 1062.4968 loss: 411.6747 loss_cls: 145.7645 loss_bbox: 124.4615 loss_dfl: 141.4487 +2024/01/19 19:51:54 - mmengine - INFO - Epoch(train) [70][400/925] lr: 3.1700e-05 eta: 1:04:43 time: 0.3968 data_time: 0.0031 memory: 5426 grad_norm: 1073.9732 loss: 413.4715 loss_cls: 147.6414 loss_bbox: 124.6566 loss_dfl: 141.1735 +2024/01/19 19:52:13 - mmengine - INFO - Epoch(train) [70][450/925] lr: 3.1700e-05 eta: 1:04:23 time: 0.3803 data_time: 0.0026 memory: 5586 grad_norm: 1061.5475 loss: 406.7981 loss_cls: 143.9798 loss_bbox: 122.4013 loss_dfl: 140.4171 +2024/01/19 19:52:32 - mmengine - INFO - Epoch(train) [70][500/925] lr: 3.1700e-05 eta: 1:04:03 time: 0.3910 data_time: 0.0029 memory: 5412 grad_norm: 1000.8972 loss: 408.8395 loss_cls: 144.1999 loss_bbox: 124.6261 loss_dfl: 140.0135 +2024/01/19 19:52:52 - mmengine - INFO - Epoch(train) [70][550/925] lr: 3.1700e-05 eta: 1:03:43 time: 0.3979 data_time: 0.0028 memory: 5572 grad_norm: 990.3369 loss: 415.4566 loss_cls: 148.2901 loss_bbox: 125.9879 loss_dfl: 141.1786 +2024/01/19 19:53:11 - mmengine - INFO - Epoch(train) [70][600/925] lr: 3.1700e-05 eta: 1:03:23 time: 0.3748 data_time: 0.0030 memory: 5679 grad_norm: 1056.3135 loss: 409.6812 loss_cls: 144.8348 loss_bbox: 124.5382 loss_dfl: 140.3081 +2024/01/19 19:53:31 - mmengine - INFO - Epoch(train) [70][650/925] lr: 3.1700e-05 eta: 1:03:03 time: 0.3962 data_time: 0.0035 memory: 5399 grad_norm: 1135.8445 loss: 410.2840 loss_cls: 145.9986 loss_bbox: 122.9960 loss_dfl: 141.2893 +2024/01/19 19:53:50 - mmengine - INFO - Epoch(train) [70][700/925] lr: 3.1700e-05 eta: 1:02:43 time: 0.3906 data_time: 0.0036 memory: 5386 grad_norm: 1104.3874 loss: 406.9716 loss_cls: 143.0286 loss_bbox: 123.7832 loss_dfl: 140.1598 +2024/01/19 19:54:09 - mmengine - INFO - Epoch(train) [70][750/925] lr: 3.1700e-05 eta: 1:02:23 time: 0.3739 data_time: 0.0034 memory: 5786 grad_norm: inf loss: 410.0864 loss_cls: 144.8306 loss_bbox: 124.8929 loss_dfl: 140.3629 +2024/01/19 19:54:29 - mmengine - INFO - Epoch(train) [70][800/925] lr: 3.1700e-05 eta: 1:02:04 time: 0.3947 data_time: 0.0024 memory: 5612 grad_norm: 946.2323 loss: 401.7020 loss_cls: 141.5059 loss_bbox: 121.1198 loss_dfl: 139.0763 +2024/01/19 19:54:49 - mmengine - INFO - Epoch(train) [70][850/925] lr: 3.1700e-05 eta: 1:01:44 time: 0.3942 data_time: 0.0027 memory: 5372 grad_norm: 1099.2433 loss: 409.8383 loss_cls: 145.2174 loss_bbox: 124.1254 loss_dfl: 140.4955 +2024/01/19 19:55:07 - mmengine - INFO - Epoch(train) [70][900/925] lr: 3.1700e-05 eta: 1:01:24 time: 0.3634 data_time: 0.0025 memory: 5332 grad_norm: 1029.1798 loss: 405.0809 loss_cls: 142.7343 loss_bbox: 122.7095 loss_dfl: 139.6372 +2024/01/19 19:55:16 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:55:16 - mmengine - INFO - Saving checkpoint at 70 epochs +2024/01/19 19:55:25 - mmengine - INFO - Epoch(val) [70][ 50/625] eta: 0:00:19 time: 0.0348 data_time: 0.0008 memory: 5266 +2024/01/19 19:55:27 - mmengine - INFO - Epoch(val) [70][100/625] eta: 0:00:18 time: 0.0338 data_time: 0.0003 memory: 843 +2024/01/19 19:55:28 - mmengine - INFO - Epoch(val) [70][150/625] eta: 0:00:16 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 19:55:30 - mmengine - INFO - Epoch(val) [70][200/625] eta: 0:00:14 time: 0.0347 data_time: 0.0004 memory: 843 +2024/01/19 19:55:32 - mmengine - INFO - Epoch(val) [70][250/625] eta: 0:00:13 time: 0.0365 data_time: 0.0004 memory: 843 +2024/01/19 19:55:34 - mmengine - INFO - Epoch(val) [70][300/625] eta: 0:00:11 time: 0.0362 data_time: 0.0004 memory: 843 +2024/01/19 19:55:36 - mmengine - INFO - Epoch(val) [70][350/625] eta: 0:00:09 time: 0.0357 data_time: 0.0003 memory: 843 +2024/01/19 19:55:37 - mmengine - INFO - Epoch(val) [70][400/625] eta: 0:00:07 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 19:55:39 - mmengine - INFO - Epoch(val) [70][450/625] eta: 0:00:06 time: 0.0299 data_time: 0.0003 memory: 843 +2024/01/19 19:55:40 - mmengine - INFO - Epoch(val) [70][500/625] eta: 0:00:04 time: 0.0267 data_time: 0.0002 memory: 843 +2024/01/19 19:55:42 - mmengine - INFO - Epoch(val) [70][550/625] eta: 0:00:02 time: 0.0264 data_time: 0.0002 memory: 843 +2024/01/19 19:55:43 - mmengine - INFO - Epoch(val) [70][600/625] eta: 0:00:00 time: 0.0265 data_time: 0.0002 memory: 843 +2024/01/19 19:55:57 - mmengine - INFO - Evaluating bbox... +2024/01/19 19:57:18 - mmengine - INFO - bbox_mAP_copypaste: 0.455 0.617 0.496 0.259 0.503 0.614 +2024/01/19 19:57:21 - mmengine - INFO - Epoch(val) [70][625/625] coco/bbox_mAP: 0.4550 coco/bbox_mAP_50: 0.6170 coco/bbox_mAP_75: 0.4960 coco/bbox_mAP_s: 0.2590 coco/bbox_mAP_m: 0.5030 coco/bbox_mAP_l: 0.6140 data_time: 0.0002 time: 0.0264 +2024/01/19 19:57:21 - mmengine - INFO - Switch pipeline now! +2024/01/19 19:57:40 - mmengine - INFO - Epoch(train) [71][ 50/925] lr: 2.9225e-05 eta: 1:00:54 time: 0.3922 data_time: 0.0496 memory: 4732 grad_norm: nan loss: 398.7544 loss_cls: 133.9073 loss_bbox: 125.0636 loss_dfl: 139.7835 +2024/01/19 19:57:59 - mmengine - INFO - Epoch(train) [71][100/925] lr: 2.9225e-05 eta: 1:00:34 time: 0.3652 data_time: 0.0021 memory: 4972 grad_norm: 2404.9711 loss: 386.1109 loss_cls: 121.7776 loss_bbox: 125.2237 loss_dfl: 139.1096 +2024/01/19 19:58:16 - mmengine - INFO - Epoch(train) [71][150/925] lr: 2.9225e-05 eta: 1:00:13 time: 0.3517 data_time: 0.0023 memory: 5119 grad_norm: 2190.6661 loss: 381.0997 loss_cls: 119.7765 loss_bbox: 122.7305 loss_dfl: 138.5928 +2024/01/19 19:58:34 - mmengine - INFO - Epoch(train) [71][200/925] lr: 2.9225e-05 eta: 0:59:53 time: 0.3421 data_time: 0.0026 memory: 4786 grad_norm: 2293.1136 loss: 376.0726 loss_cls: 116.9059 loss_bbox: 121.1875 loss_dfl: 137.9792 +2024/01/19 19:58:51 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 19:58:51 - mmengine - INFO - Epoch(train) [71][250/925] lr: 2.9225e-05 eta: 0:59:33 time: 0.3553 data_time: 0.0022 memory: 4652 grad_norm: 2227.6972 loss: 372.9021 loss_cls: 114.4804 loss_bbox: 121.0036 loss_dfl: 137.4181 +2024/01/19 19:59:09 - mmengine - INFO - Epoch(train) [71][300/925] lr: 2.9225e-05 eta: 0:59:13 time: 0.3622 data_time: 0.0023 memory: 4839 grad_norm: 2289.3519 loss: 377.0742 loss_cls: 118.8317 loss_bbox: 120.4670 loss_dfl: 137.7755 +2024/01/19 19:59:27 - mmengine - INFO - Epoch(train) [71][350/925] lr: 2.9225e-05 eta: 0:58:53 time: 0.3540 data_time: 0.0032 memory: 4759 grad_norm: 2140.8891 loss: 378.0468 loss_cls: 118.9799 loss_bbox: 122.3231 loss_dfl: 136.7437 +2024/01/19 19:59:45 - mmengine - INFO - Epoch(train) [71][400/925] lr: 2.9225e-05 eta: 0:58:33 time: 0.3617 data_time: 0.0032 memory: 5119 grad_norm: 1903.6963 loss: 371.6089 loss_cls: 115.4302 loss_bbox: 118.9803 loss_dfl: 137.1985 +2024/01/19 20:00:03 - mmengine - INFO - Epoch(train) [71][450/925] lr: 2.9225e-05 eta: 0:58:13 time: 0.3571 data_time: 0.0054 memory: 4706 grad_norm: 2034.3122 loss: 376.8064 loss_cls: 119.2922 loss_bbox: 120.3556 loss_dfl: 137.1586 +2024/01/19 20:00:22 - mmengine - INFO - Epoch(train) [71][500/925] lr: 2.9225e-05 eta: 0:57:53 time: 0.3794 data_time: 0.0023 memory: 4746 grad_norm: 1679.6870 loss: 381.5725 loss_cls: 118.8896 loss_bbox: 124.0616 loss_dfl: 138.6213 +2024/01/19 20:00:41 - mmengine - INFO - Epoch(train) [71][550/925] lr: 2.9225e-05 eta: 0:57:33 time: 0.3673 data_time: 0.0022 memory: 4679 grad_norm: 1933.2209 loss: 375.2509 loss_cls: 117.2972 loss_bbox: 120.0665 loss_dfl: 137.8872 +2024/01/19 20:00:58 - mmengine - INFO - Epoch(train) [71][600/925] lr: 2.9225e-05 eta: 0:57:12 time: 0.3502 data_time: 0.0021 memory: 4719 grad_norm: 1928.3385 loss: 372.3616 loss_cls: 115.5534 loss_bbox: 118.5600 loss_dfl: 138.2483 +2024/01/19 20:01:17 - mmengine - INFO - Epoch(train) [71][650/925] lr: 2.9225e-05 eta: 0:56:52 time: 0.3767 data_time: 0.0024 memory: 4879 grad_norm: 2009.8399 loss: 371.2667 loss_cls: 115.0942 loss_bbox: 119.8512 loss_dfl: 136.3213 +2024/01/19 20:01:35 - mmengine - INFO - Epoch(train) [71][700/925] lr: 2.9225e-05 eta: 0:56:32 time: 0.3632 data_time: 0.0022 memory: 4999 grad_norm: 1889.2269 loss: 377.0909 loss_cls: 118.9461 loss_bbox: 120.5631 loss_dfl: 137.5817 +2024/01/19 20:01:54 - mmengine - INFO - Epoch(train) [71][750/925] lr: 2.9225e-05 eta: 0:56:12 time: 0.3703 data_time: 0.0024 memory: 4732 grad_norm: 1876.1179 loss: 371.0933 loss_cls: 114.2276 loss_bbox: 119.8698 loss_dfl: 136.9959 +2024/01/19 20:02:12 - mmengine - INFO - Epoch(train) [71][800/925] lr: 2.9225e-05 eta: 0:55:52 time: 0.3654 data_time: 0.0022 memory: 4799 grad_norm: 1909.5806 loss: 366.8905 loss_cls: 115.4396 loss_bbox: 115.5048 loss_dfl: 135.9461 +2024/01/19 20:02:31 - mmengine - INFO - Epoch(train) [71][850/925] lr: 2.9225e-05 eta: 0:55:32 time: 0.3833 data_time: 0.0024 memory: 4786 grad_norm: 1809.8864 loss: 378.4966 loss_cls: 118.2947 loss_bbox: 122.5186 loss_dfl: 137.6834 +2024/01/19 20:02:50 - mmengine - INFO - Epoch(train) [71][900/925] lr: 2.9225e-05 eta: 0:55:12 time: 0.3678 data_time: 0.0021 memory: 4679 grad_norm: 2033.7582 loss: 375.9047 loss_cls: 119.0776 loss_bbox: 119.9008 loss_dfl: 136.9263 +2024/01/19 20:02:59 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:03:01 - mmengine - INFO - Epoch(val) [71][ 50/625] eta: 0:00:20 time: 0.0362 data_time: 0.0009 memory: 4906 +2024/01/19 20:03:03 - mmengine - INFO - Epoch(val) [71][100/625] eta: 0:00:19 time: 0.0362 data_time: 0.0004 memory: 843 +2024/01/19 20:03:05 - mmengine - INFO - Epoch(val) [71][150/625] eta: 0:00:16 time: 0.0347 data_time: 0.0003 memory: 843 +2024/01/19 20:03:06 - mmengine - INFO - Epoch(val) [71][200/625] eta: 0:00:15 time: 0.0346 data_time: 0.0003 memory: 843 +2024/01/19 20:03:08 - mmengine - INFO - Epoch(val) [71][250/625] eta: 0:00:13 time: 0.0363 data_time: 0.0004 memory: 843 +2024/01/19 20:03:10 - mmengine - INFO - Epoch(val) [71][300/625] eta: 0:00:11 time: 0.0364 data_time: 0.0004 memory: 843 +2024/01/19 20:03:12 - mmengine - INFO - Epoch(val) [71][350/625] eta: 0:00:09 time: 0.0367 data_time: 0.0004 memory: 843 +2024/01/19 20:03:14 - mmengine - INFO - Epoch(val) [71][400/625] eta: 0:00:08 time: 0.0366 data_time: 0.0004 memory: 843 +2024/01/19 20:03:16 - mmengine - INFO - Epoch(val) [71][450/625] eta: 0:00:06 time: 0.0360 data_time: 0.0004 memory: 843 +2024/01/19 20:03:17 - mmengine - INFO - Epoch(val) [71][500/625] eta: 0:00:04 time: 0.0360 data_time: 0.0003 memory: 843 +2024/01/19 20:03:19 - mmengine - INFO - Epoch(val) [71][550/625] eta: 0:00:02 time: 0.0364 data_time: 0.0004 memory: 843 +2024/01/19 20:03:21 - mmengine - INFO - Epoch(val) [71][600/625] eta: 0:00:00 time: 0.0356 data_time: 0.0004 memory: 843 +2024/01/19 20:03:35 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:04:54 - mmengine - INFO - bbox_mAP_copypaste: 0.455 0.617 0.496 0.260 0.503 0.615 +2024/01/19 20:04:57 - mmengine - INFO - Epoch(val) [71][625/625] coco/bbox_mAP: 0.4550 coco/bbox_mAP_50: 0.6170 coco/bbox_mAP_75: 0.4960 coco/bbox_mAP_s: 0.2600 coco/bbox_mAP_m: 0.5030 coco/bbox_mAP_l: 0.6150 data_time: 0.0004 time: 0.0341 +2024/01/19 20:05:16 - mmengine - INFO - Epoch(train) [72][ 50/925] lr: 2.6750e-05 eta: 0:54:42 time: 0.3899 data_time: 0.0468 memory: 4826 grad_norm: 1828.2417 loss: 373.8081 loss_cls: 116.6811 loss_bbox: 120.1265 loss_dfl: 137.0005 +2024/01/19 20:05:35 - mmengine - INFO - Epoch(train) [72][100/925] lr: 2.6750e-05 eta: 0:54:22 time: 0.3693 data_time: 0.0024 memory: 4839 grad_norm: 1864.2584 loss: 368.6069 loss_cls: 114.2511 loss_bbox: 118.4452 loss_dfl: 135.9106 +2024/01/19 20:05:53 - mmengine - INFO - Epoch(train) [72][150/925] lr: 2.6750e-05 eta: 0:54:02 time: 0.3695 data_time: 0.0099 memory: 4826 grad_norm: 1865.6461 loss: 366.6935 loss_cls: 112.4612 loss_bbox: 118.7988 loss_dfl: 135.4335 +2024/01/19 20:06:11 - mmengine - INFO - Epoch(train) [72][200/925] lr: 2.6750e-05 eta: 0:53:42 time: 0.3568 data_time: 0.0023 memory: 4719 grad_norm: 1795.6722 loss: 372.1462 loss_cls: 116.4506 loss_bbox: 118.3127 loss_dfl: 137.3829 +2024/01/19 20:06:29 - mmengine - INFO - Epoch(train) [72][250/925] lr: 2.6750e-05 eta: 0:53:22 time: 0.3486 data_time: 0.0022 memory: 4746 grad_norm: 1869.8508 loss: 375.7860 loss_cls: 115.9921 loss_bbox: 122.8175 loss_dfl: 136.9764 +2024/01/19 20:06:47 - mmengine - INFO - Epoch(train) [72][300/925] lr: 2.6750e-05 eta: 0:53:02 time: 0.3588 data_time: 0.0024 memory: 4999 grad_norm: 1597.1471 loss: 380.0478 loss_cls: 119.6790 loss_bbox: 121.5408 loss_dfl: 138.8281 +2024/01/19 20:06:55 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:07:05 - mmengine - INFO - Epoch(train) [72][350/925] lr: 2.6750e-05 eta: 0:52:42 time: 0.3591 data_time: 0.0027 memory: 4786 grad_norm: 1675.0305 loss: 366.8276 loss_cls: 111.2568 loss_bbox: 118.4828 loss_dfl: 137.0880 +2024/01/19 20:07:22 - mmengine - INFO - Epoch(train) [72][400/925] lr: 2.6750e-05 eta: 0:52:22 time: 0.3511 data_time: 0.0022 memory: 4666 grad_norm: 1717.7923 loss: 375.9634 loss_cls: 116.4457 loss_bbox: 121.4116 loss_dfl: 138.1061 +2024/01/19 20:07:40 - mmengine - INFO - Epoch(train) [72][450/925] lr: 2.6750e-05 eta: 0:52:02 time: 0.3569 data_time: 0.0023 memory: 4786 grad_norm: 1770.0614 loss: 373.9066 loss_cls: 114.5496 loss_bbox: 121.1021 loss_dfl: 138.2549 +2024/01/19 20:07:59 - mmengine - INFO - Epoch(train) [72][500/925] lr: 2.6750e-05 eta: 0:51:42 time: 0.3684 data_time: 0.0031 memory: 4772 grad_norm: 1711.7644 loss: 366.2948 loss_cls: 113.2604 loss_bbox: 116.9210 loss_dfl: 136.1135 +2024/01/19 20:08:17 - mmengine - INFO - Epoch(train) [72][550/925] lr: 2.6750e-05 eta: 0:51:22 time: 0.3592 data_time: 0.0026 memory: 4692 grad_norm: 1736.9411 loss: 371.8230 loss_cls: 115.7826 loss_bbox: 118.6481 loss_dfl: 137.3923 +2024/01/19 20:08:35 - mmengine - INFO - Epoch(train) [72][600/925] lr: 2.6750e-05 eta: 0:51:02 time: 0.3722 data_time: 0.0068 memory: 5026 grad_norm: 1699.6214 loss: 380.9279 loss_cls: 118.5221 loss_bbox: 123.8889 loss_dfl: 138.5169 +2024/01/19 20:08:53 - mmengine - INFO - Epoch(train) [72][650/925] lr: 2.6750e-05 eta: 0:50:42 time: 0.3572 data_time: 0.0023 memory: 4679 grad_norm: 1567.6446 loss: 384.0931 loss_cls: 123.9076 loss_bbox: 121.8737 loss_dfl: 138.3118 +2024/01/19 20:09:11 - mmengine - INFO - Epoch(train) [72][700/925] lr: 2.6750e-05 eta: 0:50:22 time: 0.3513 data_time: 0.0033 memory: 4839 grad_norm: 1746.5075 loss: 374.4059 loss_cls: 117.3406 loss_bbox: 120.0674 loss_dfl: 136.9980 +2024/01/19 20:09:29 - mmengine - INFO - Epoch(train) [72][750/925] lr: 2.6750e-05 eta: 0:50:02 time: 0.3678 data_time: 0.0051 memory: 4746 grad_norm: 1719.6659 loss: 380.1970 loss_cls: 118.1964 loss_bbox: 122.2514 loss_dfl: 139.7491 +2024/01/19 20:09:47 - mmengine - INFO - Epoch(train) [72][800/925] lr: 2.6750e-05 eta: 0:49:42 time: 0.3513 data_time: 0.0023 memory: 4852 grad_norm: 1797.6014 loss: 366.9307 loss_cls: 111.6737 loss_bbox: 118.2720 loss_dfl: 136.9850 +2024/01/19 20:10:05 - mmengine - INFO - Epoch(train) [72][850/925] lr: 2.6750e-05 eta: 0:49:22 time: 0.3607 data_time: 0.0137 memory: 4799 grad_norm: 1808.3440 loss: 375.0246 loss_cls: 119.0515 loss_bbox: 119.3067 loss_dfl: 136.6664 +2024/01/19 20:10:22 - mmengine - INFO - Epoch(train) [72][900/925] lr: 2.6750e-05 eta: 0:49:02 time: 0.3525 data_time: 0.0024 memory: 4866 grad_norm: 1625.9353 loss: 376.7624 loss_cls: 116.5650 loss_bbox: 121.0155 loss_dfl: 139.1818 +2024/01/19 20:10:32 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:10:34 - mmengine - INFO - Epoch(val) [72][ 50/625] eta: 0:00:20 time: 0.0359 data_time: 0.0009 memory: 4639 +2024/01/19 20:10:36 - mmengine - INFO - Epoch(val) [72][100/625] eta: 0:00:18 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 20:10:37 - mmengine - INFO - Epoch(val) [72][150/625] eta: 0:00:17 time: 0.0365 data_time: 0.0004 memory: 843 +2024/01/19 20:10:39 - mmengine - INFO - Epoch(val) [72][200/625] eta: 0:00:15 time: 0.0359 data_time: 0.0003 memory: 843 +2024/01/19 20:10:41 - mmengine - INFO - Epoch(val) [72][250/625] eta: 0:00:13 time: 0.0345 data_time: 0.0004 memory: 843 +2024/01/19 20:10:43 - mmengine - INFO - Epoch(val) [72][300/625] eta: 0:00:11 time: 0.0374 data_time: 0.0004 memory: 843 +2024/01/19 20:10:45 - mmengine - INFO - Epoch(val) [72][350/625] eta: 0:00:09 time: 0.0340 data_time: 0.0003 memory: 843 +2024/01/19 20:10:46 - mmengine - INFO - Epoch(val) [72][400/625] eta: 0:00:08 time: 0.0361 data_time: 0.0003 memory: 843 +2024/01/19 20:10:48 - mmengine - INFO - Epoch(val) [72][450/625] eta: 0:00:06 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 20:10:50 - mmengine - INFO - Epoch(val) [72][500/625] eta: 0:00:04 time: 0.0354 data_time: 0.0004 memory: 843 +2024/01/19 20:10:52 - mmengine - INFO - Epoch(val) [72][550/625] eta: 0:00:02 time: 0.0355 data_time: 0.0003 memory: 843 +2024/01/19 20:10:54 - mmengine - INFO - Epoch(val) [72][600/625] eta: 0:00:00 time: 0.0366 data_time: 0.0004 memory: 843 +2024/01/19 20:11:08 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:12:27 - mmengine - INFO - bbox_mAP_copypaste: 0.455 0.618 0.496 0.261 0.504 0.615 +2024/01/19 20:12:30 - mmengine - INFO - Epoch(val) [72][625/625] coco/bbox_mAP: 0.4550 coco/bbox_mAP_50: 0.6180 coco/bbox_mAP_75: 0.4960 coco/bbox_mAP_s: 0.2610 coco/bbox_mAP_m: 0.5040 coco/bbox_mAP_l: 0.6150 data_time: 0.0004 time: 0.0354 +2024/01/19 20:12:50 - mmengine - INFO - Epoch(train) [73][ 50/925] lr: 2.4275e-05 eta: 0:48:32 time: 0.4047 data_time: 0.0514 memory: 4599 grad_norm: 1720.4754 loss: 367.5180 loss_cls: 112.3676 loss_bbox: 118.3874 loss_dfl: 136.7631 +2024/01/19 20:13:08 - mmengine - INFO - Epoch(train) [73][100/925] lr: 2.4275e-05 eta: 0:48:12 time: 0.3493 data_time: 0.0036 memory: 4919 grad_norm: 1592.6803 loss: 371.0870 loss_cls: 116.0891 loss_bbox: 119.2890 loss_dfl: 135.7089 +2024/01/19 20:13:25 - mmengine - INFO - Epoch(train) [73][150/925] lr: 2.4275e-05 eta: 0:47:52 time: 0.3505 data_time: 0.0024 memory: 4826 grad_norm: 1767.0523 loss: 371.5802 loss_cls: 114.1938 loss_bbox: 119.6123 loss_dfl: 137.7742 +2024/01/19 20:13:43 - mmengine - INFO - Epoch(train) [73][200/925] lr: 2.4275e-05 eta: 0:47:32 time: 0.3545 data_time: 0.0025 memory: 5119 grad_norm: 1849.6583 loss: 364.7585 loss_cls: 111.8927 loss_bbox: 116.3634 loss_dfl: 136.5024 +2024/01/19 20:14:01 - mmengine - INFO - Epoch(train) [73][250/925] lr: 2.4275e-05 eta: 0:47:12 time: 0.3613 data_time: 0.0022 memory: 4692 grad_norm: 1680.1798 loss: 368.3582 loss_cls: 114.2839 loss_bbox: 118.4382 loss_dfl: 135.6361 +2024/01/19 20:14:18 - mmengine - INFO - Epoch(train) [73][300/925] lr: 2.4275e-05 eta: 0:46:52 time: 0.3442 data_time: 0.0035 memory: 4852 grad_norm: 1623.8992 loss: 370.9082 loss_cls: 113.9720 loss_bbox: 119.6752 loss_dfl: 137.2610 +2024/01/19 20:14:37 - mmengine - INFO - Epoch(train) [73][350/925] lr: 2.4275e-05 eta: 0:46:32 time: 0.3649 data_time: 0.0033 memory: 4959 grad_norm: 1680.3868 loss: 370.7755 loss_cls: 115.9412 loss_bbox: 118.8276 loss_dfl: 136.0067 +2024/01/19 20:14:55 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:14:55 - mmengine - INFO - Epoch(train) [73][400/925] lr: 2.4275e-05 eta: 0:46:12 time: 0.3723 data_time: 0.0022 memory: 4839 grad_norm: 1582.6070 loss: 370.9894 loss_cls: 112.4724 loss_bbox: 122.0767 loss_dfl: 136.4403 +2024/01/19 20:15:13 - mmengine - INFO - Epoch(train) [73][450/925] lr: 2.4275e-05 eta: 0:45:52 time: 0.3556 data_time: 0.0026 memory: 4892 grad_norm: 1569.7708 loss: 374.5824 loss_cls: 114.8488 loss_bbox: 121.9931 loss_dfl: 137.7406 +2024/01/19 20:15:31 - mmengine - INFO - Epoch(train) [73][500/925] lr: 2.4275e-05 eta: 0:45:32 time: 0.3665 data_time: 0.0022 memory: 4959 grad_norm: 1703.9726 loss: 377.0939 loss_cls: 115.4431 loss_bbox: 123.7291 loss_dfl: 137.9218 +2024/01/19 20:15:49 - mmengine - INFO - Epoch(train) [73][550/925] lr: 2.4275e-05 eta: 0:45:12 time: 0.3544 data_time: 0.0024 memory: 4772 grad_norm: 1775.7070 loss: 374.9205 loss_cls: 117.2171 loss_bbox: 120.7111 loss_dfl: 136.9922 +2024/01/19 20:16:07 - mmengine - INFO - Epoch(train) [73][600/925] lr: 2.4275e-05 eta: 0:44:52 time: 0.3570 data_time: 0.0032 memory: 4772 grad_norm: 1558.4899 loss: 373.5400 loss_cls: 115.2824 loss_bbox: 121.1610 loss_dfl: 137.0967 +2024/01/19 20:16:26 - mmengine - INFO - Epoch(train) [73][650/925] lr: 2.4275e-05 eta: 0:44:32 time: 0.3696 data_time: 0.0162 memory: 4746 grad_norm: 1583.9166 loss: 365.6202 loss_cls: 110.8478 loss_bbox: 117.7240 loss_dfl: 137.0484 +2024/01/19 20:16:44 - mmengine - INFO - Epoch(train) [73][700/925] lr: 2.4275e-05 eta: 0:44:12 time: 0.3740 data_time: 0.0074 memory: 4719 grad_norm: 1532.9928 loss: 370.6307 loss_cls: 114.8768 loss_bbox: 118.8258 loss_dfl: 136.9281 +2024/01/19 20:17:02 - mmengine - INFO - Epoch(train) [73][750/925] lr: 2.4275e-05 eta: 0:43:52 time: 0.3602 data_time: 0.0060 memory: 4852 grad_norm: 1699.0827 loss: 376.3951 loss_cls: 117.1548 loss_bbox: 121.5360 loss_dfl: 137.7043 +2024/01/19 20:17:20 - mmengine - INFO - Epoch(train) [73][800/925] lr: 2.4275e-05 eta: 0:43:32 time: 0.3574 data_time: 0.0026 memory: 4839 grad_norm: 1813.0132 loss: 373.2896 loss_cls: 116.6291 loss_bbox: 119.3010 loss_dfl: 137.3594 +2024/01/19 20:17:39 - mmengine - INFO - Epoch(train) [73][850/925] lr: 2.4275e-05 eta: 0:43:12 time: 0.3681 data_time: 0.0023 memory: 4706 grad_norm: 1560.1278 loss: 372.2734 loss_cls: 116.1656 loss_bbox: 118.3817 loss_dfl: 137.7262 +2024/01/19 20:17:57 - mmengine - INFO - Epoch(train) [73][900/925] lr: 2.4275e-05 eta: 0:42:52 time: 0.3580 data_time: 0.0021 memory: 4746 grad_norm: 1622.8410 loss: 371.7868 loss_cls: 115.8331 loss_bbox: 119.4665 loss_dfl: 136.4872 +2024/01/19 20:18:05 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:18:07 - mmengine - INFO - Epoch(val) [73][ 50/625] eta: 0:00:20 time: 0.0353 data_time: 0.0009 memory: 4839 +2024/01/19 20:18:09 - mmengine - INFO - Epoch(val) [73][100/625] eta: 0:00:18 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 20:18:11 - mmengine - INFO - Epoch(val) [73][150/625] eta: 0:00:16 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 20:18:13 - mmengine - INFO - Epoch(val) [73][200/625] eta: 0:00:15 time: 0.0364 data_time: 0.0003 memory: 843 +2024/01/19 20:18:14 - mmengine - INFO - Epoch(val) [73][250/625] eta: 0:00:13 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 20:18:16 - mmengine - INFO - Epoch(val) [73][300/625] eta: 0:00:11 time: 0.0360 data_time: 0.0004 memory: 843 +2024/01/19 20:18:18 - mmengine - INFO - Epoch(val) [73][350/625] eta: 0:00:09 time: 0.0349 data_time: 0.0003 memory: 843 +2024/01/19 20:18:20 - mmengine - INFO - Epoch(val) [73][400/625] eta: 0:00:08 time: 0.0357 data_time: 0.0003 memory: 843 +2024/01/19 20:18:22 - mmengine - INFO - Epoch(val) [73][450/625] eta: 0:00:06 time: 0.0360 data_time: 0.0003 memory: 843 +2024/01/19 20:18:23 - mmengine - INFO - Epoch(val) [73][500/625] eta: 0:00:04 time: 0.0357 data_time: 0.0003 memory: 843 +2024/01/19 20:18:25 - mmengine - INFO - Epoch(val) [73][550/625] eta: 0:00:02 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 20:18:27 - mmengine - INFO - Epoch(val) [73][600/625] eta: 0:00:00 time: 0.0373 data_time: 0.0004 memory: 843 +2024/01/19 20:18:41 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:20:00 - mmengine - INFO - bbox_mAP_copypaste: 0.456 0.619 0.497 0.262 0.505 0.615 +2024/01/19 20:20:02 - mmengine - INFO - Epoch(val) [73][625/625] coco/bbox_mAP: 0.4560 coco/bbox_mAP_50: 0.6190 coco/bbox_mAP_75: 0.4970 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5050 coco/bbox_mAP_l: 0.6150 data_time: 0.0003 time: 0.0359 +2024/01/19 20:20:21 - mmengine - INFO - Epoch(train) [74][ 50/925] lr: 2.1800e-05 eta: 0:42:22 time: 0.3731 data_time: 0.0501 memory: 4639 grad_norm: 1575.5456 loss: 369.2103 loss_cls: 113.2724 loss_bbox: 119.6597 loss_dfl: 136.2782 +2024/01/19 20:20:39 - mmengine - INFO - Epoch(train) [74][100/925] lr: 2.1800e-05 eta: 0:42:02 time: 0.3641 data_time: 0.0022 memory: 4692 grad_norm: 1580.5805 loss: 372.9043 loss_cls: 114.0066 loss_bbox: 121.4642 loss_dfl: 137.4335 +2024/01/19 20:20:57 - mmengine - INFO - Epoch(train) [74][150/925] lr: 2.1800e-05 eta: 0:41:42 time: 0.3537 data_time: 0.0022 memory: 4772 grad_norm: 1687.3176 loss: 373.0875 loss_cls: 114.1391 loss_bbox: 121.1504 loss_dfl: 137.7980 +2024/01/19 20:21:15 - mmengine - INFO - Epoch(train) [74][200/925] lr: 2.1800e-05 eta: 0:41:22 time: 0.3572 data_time: 0.0023 memory: 4786 grad_norm: 1622.1355 loss: 369.6707 loss_cls: 113.4656 loss_bbox: 119.9405 loss_dfl: 136.2645 +2024/01/19 20:21:33 - mmengine - INFO - Epoch(train) [74][250/925] lr: 2.1800e-05 eta: 0:41:02 time: 0.3569 data_time: 0.0023 memory: 4692 grad_norm: 1554.2333 loss: 365.6287 loss_cls: 110.5425 loss_bbox: 119.5764 loss_dfl: 135.5098 +2024/01/19 20:21:51 - mmengine - INFO - Epoch(train) [74][300/925] lr: 2.1800e-05 eta: 0:40:42 time: 0.3694 data_time: 0.0057 memory: 4626 grad_norm: 1601.1929 loss: 370.3405 loss_cls: 114.7787 loss_bbox: 118.9381 loss_dfl: 136.6237 +2024/01/19 20:22:09 - mmengine - INFO - Epoch(train) [74][350/925] lr: 2.1800e-05 eta: 0:40:22 time: 0.3574 data_time: 0.0023 memory: 4732 grad_norm: 1557.0011 loss: 373.4682 loss_cls: 117.1518 loss_bbox: 118.0665 loss_dfl: 138.2499 +2024/01/19 20:22:28 - mmengine - INFO - Epoch(train) [74][400/925] lr: 2.1800e-05 eta: 0:40:03 time: 0.3755 data_time: 0.0034 memory: 4812 grad_norm: 1741.7098 loss: 371.9243 loss_cls: 114.8774 loss_bbox: 120.3197 loss_dfl: 136.7272 +2024/01/19 20:22:46 - mmengine - INFO - Epoch(train) [74][450/925] lr: 2.1800e-05 eta: 0:39:43 time: 0.3480 data_time: 0.0024 memory: 4692 grad_norm: 1518.1641 loss: 370.3538 loss_cls: 115.1929 loss_bbox: 118.6796 loss_dfl: 136.4813 +2024/01/19 20:22:55 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:23:04 - mmengine - INFO - Epoch(train) [74][500/925] lr: 2.1800e-05 eta: 0:39:23 time: 0.3637 data_time: 0.0022 memory: 4786 grad_norm: 1588.8667 loss: 364.0993 loss_cls: 112.7827 loss_bbox: 116.3387 loss_dfl: 134.9779 +2024/01/19 20:23:22 - mmengine - INFO - Epoch(train) [74][550/925] lr: 2.1800e-05 eta: 0:39:03 time: 0.3584 data_time: 0.0022 memory: 4852 grad_norm: 1696.8613 loss: 365.5483 loss_cls: 112.1920 loss_bbox: 118.0557 loss_dfl: 135.3006 +2024/01/19 20:23:40 - mmengine - INFO - Epoch(train) [74][600/925] lr: 2.1800e-05 eta: 0:38:43 time: 0.3691 data_time: 0.0022 memory: 4719 grad_norm: 1571.9538 loss: 360.7177 loss_cls: 109.9441 loss_bbox: 116.6545 loss_dfl: 134.1190 +2024/01/19 20:23:58 - mmengine - INFO - Epoch(train) [74][650/925] lr: 2.1800e-05 eta: 0:38:23 time: 0.3463 data_time: 0.0024 memory: 4706 grad_norm: 1536.9140 loss: 363.6411 loss_cls: 110.6606 loss_bbox: 118.2684 loss_dfl: 134.7121 +2024/01/19 20:24:16 - mmengine - INFO - Epoch(train) [74][700/925] lr: 2.1800e-05 eta: 0:38:03 time: 0.3773 data_time: 0.0024 memory: 5092 grad_norm: 1484.3728 loss: 373.1368 loss_cls: 116.1724 loss_bbox: 119.5212 loss_dfl: 137.4431 +2024/01/19 20:24:35 - mmengine - INFO - Epoch(train) [74][750/925] lr: 2.1800e-05 eta: 0:37:43 time: 0.3609 data_time: 0.0023 memory: 4772 grad_norm: 1450.2580 loss: 369.2422 loss_cls: 113.8862 loss_bbox: 119.5584 loss_dfl: 135.7976 +2024/01/19 20:24:53 - mmengine - INFO - Epoch(train) [74][800/925] lr: 2.1800e-05 eta: 0:37:23 time: 0.3625 data_time: 0.0022 memory: 4719 grad_norm: 1543.0085 loss: 366.1312 loss_cls: 109.5265 loss_bbox: 119.6830 loss_dfl: 136.9217 +2024/01/19 20:25:11 - mmengine - INFO - Epoch(train) [74][850/925] lr: 2.1800e-05 eta: 0:37:03 time: 0.3558 data_time: 0.0023 memory: 4866 grad_norm: 1608.3356 loss: 364.6699 loss_cls: 113.3946 loss_bbox: 116.4134 loss_dfl: 134.8619 +2024/01/19 20:25:29 - mmengine - INFO - Epoch(train) [74][900/925] lr: 2.1800e-05 eta: 0:36:43 time: 0.3755 data_time: 0.0024 memory: 4866 grad_norm: 1702.1945 loss: 376.5363 loss_cls: 115.2622 loss_bbox: 122.4707 loss_dfl: 138.8034 +2024/01/19 20:25:37 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:25:40 - mmengine - INFO - Epoch(val) [74][ 50/625] eta: 0:00:19 time: 0.0342 data_time: 0.0008 memory: 4692 +2024/01/19 20:25:41 - mmengine - INFO - Epoch(val) [74][100/625] eta: 0:00:18 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 20:25:43 - mmengine - INFO - Epoch(val) [74][150/625] eta: 0:00:16 time: 0.0352 data_time: 0.0004 memory: 843 +2024/01/19 20:25:45 - mmengine - INFO - Epoch(val) [74][200/625] eta: 0:00:14 time: 0.0336 data_time: 0.0004 memory: 843 +2024/01/19 20:25:47 - mmengine - INFO - Epoch(val) [74][250/625] eta: 0:00:13 time: 0.0353 data_time: 0.0003 memory: 843 +2024/01/19 20:25:48 - mmengine - INFO - Epoch(val) [74][300/625] eta: 0:00:11 time: 0.0359 data_time: 0.0003 memory: 843 +2024/01/19 20:25:50 - mmengine - INFO - Epoch(val) [74][350/625] eta: 0:00:09 time: 0.0360 data_time: 0.0004 memory: 843 +2024/01/19 20:25:52 - mmengine - INFO - Epoch(val) [74][400/625] eta: 0:00:07 time: 0.0367 data_time: 0.0004 memory: 843 +2024/01/19 20:25:54 - mmengine - INFO - Epoch(val) [74][450/625] eta: 0:00:06 time: 0.0349 data_time: 0.0004 memory: 843 +2024/01/19 20:25:55 - mmengine - INFO - Epoch(val) [74][500/625] eta: 0:00:04 time: 0.0342 data_time: 0.0004 memory: 843 +2024/01/19 20:25:57 - mmengine - INFO - Epoch(val) [74][550/625] eta: 0:00:02 time: 0.0360 data_time: 0.0004 memory: 843 +2024/01/19 20:25:59 - mmengine - INFO - Epoch(val) [74][600/625] eta: 0:00:00 time: 0.0341 data_time: 0.0004 memory: 843 +2024/01/19 20:26:13 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:27:29 - mmengine - INFO - bbox_mAP_copypaste: 0.456 0.619 0.497 0.263 0.505 0.615 +2024/01/19 20:27:32 - mmengine - INFO - Epoch(val) [74][625/625] coco/bbox_mAP: 0.4560 coco/bbox_mAP_50: 0.6190 coco/bbox_mAP_75: 0.4970 coco/bbox_mAP_s: 0.2630 coco/bbox_mAP_m: 0.5050 coco/bbox_mAP_l: 0.6150 data_time: 0.0003 time: 0.0340 +2024/01/19 20:27:51 - mmengine - INFO - Epoch(train) [75][ 50/925] lr: 1.9325e-05 eta: 0:36:14 time: 0.3960 data_time: 0.0509 memory: 4906 grad_norm: 1542.6328 loss: 363.7883 loss_cls: 113.0985 loss_bbox: 115.4786 loss_dfl: 135.2113 +2024/01/19 20:28:08 - mmengine - INFO - Epoch(train) [75][100/925] lr: 1.9325e-05 eta: 0:35:54 time: 0.3373 data_time: 0.0022 memory: 4786 grad_norm: 1523.2512 loss: 365.2008 loss_cls: 111.0536 loss_bbox: 118.2170 loss_dfl: 135.9302 +2024/01/19 20:28:26 - mmengine - INFO - Epoch(train) [75][150/925] lr: 1.9325e-05 eta: 0:35:34 time: 0.3579 data_time: 0.0022 memory: 4652 grad_norm: 1652.4189 loss: 365.5593 loss_cls: 111.3132 loss_bbox: 118.5483 loss_dfl: 135.6978 +2024/01/19 20:28:44 - mmengine - INFO - Epoch(train) [75][200/925] lr: 1.9325e-05 eta: 0:35:14 time: 0.3597 data_time: 0.0022 memory: 4786 grad_norm: 1487.7805 loss: 370.3577 loss_cls: 113.1624 loss_bbox: 121.0841 loss_dfl: 136.1112 +2024/01/19 20:29:02 - mmengine - INFO - Epoch(train) [75][250/925] lr: 1.9325e-05 eta: 0:34:54 time: 0.3532 data_time: 0.0025 memory: 4812 grad_norm: 1542.9608 loss: 371.2684 loss_cls: 113.1950 loss_bbox: 120.8599 loss_dfl: 137.2134 +2024/01/19 20:29:19 - mmengine - INFO - Epoch(train) [75][300/925] lr: 1.9325e-05 eta: 0:34:34 time: 0.3473 data_time: 0.0024 memory: 4679 grad_norm: 1706.0042 loss: 369.3238 loss_cls: 112.4476 loss_bbox: 119.5196 loss_dfl: 137.3566 +2024/01/19 20:29:37 - mmengine - INFO - Epoch(train) [75][350/925] lr: 1.9325e-05 eta: 0:34:14 time: 0.3456 data_time: 0.0024 memory: 4759 grad_norm: 1543.3126 loss: 357.3426 loss_cls: 108.5830 loss_bbox: 114.6147 loss_dfl: 134.1450 +2024/01/19 20:29:55 - mmengine - INFO - Epoch(train) [75][400/925] lr: 1.9325e-05 eta: 0:33:54 time: 0.3641 data_time: 0.0023 memory: 4786 grad_norm: 1623.4591 loss: 372.5307 loss_cls: 114.0651 loss_bbox: 120.4183 loss_dfl: 138.0473 +2024/01/19 20:30:12 - mmengine - INFO - Epoch(train) [75][450/925] lr: 1.9325e-05 eta: 0:33:34 time: 0.3355 data_time: 0.0023 memory: 4746 grad_norm: 1624.2006 loss: 364.3131 loss_cls: 109.7343 loss_bbox: 118.4445 loss_dfl: 136.1342 +2024/01/19 20:30:29 - mmengine - INFO - Epoch(train) [75][500/925] lr: 1.9325e-05 eta: 0:33:14 time: 0.3513 data_time: 0.0024 memory: 4719 grad_norm: 1637.4081 loss: 364.2622 loss_cls: 109.5096 loss_bbox: 119.6165 loss_dfl: 135.1361 +2024/01/19 20:30:47 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:30:47 - mmengine - INFO - Epoch(train) [75][550/925] lr: 1.9325e-05 eta: 0:32:54 time: 0.3469 data_time: 0.0023 memory: 4826 grad_norm: 1531.4639 loss: 369.3199 loss_cls: 114.4886 loss_bbox: 118.3067 loss_dfl: 136.5247 +2024/01/19 20:31:04 - mmengine - INFO - Epoch(train) [75][600/925] lr: 1.9325e-05 eta: 0:32:34 time: 0.3539 data_time: 0.0023 memory: 4799 grad_norm: 1534.5635 loss: 360.3077 loss_cls: 109.9364 loss_bbox: 115.3483 loss_dfl: 135.0230 +2024/01/19 20:31:22 - mmengine - INFO - Epoch(train) [75][650/925] lr: 1.9325e-05 eta: 0:32:15 time: 0.3589 data_time: 0.0023 memory: 4692 grad_norm: 1679.6432 loss: 367.7053 loss_cls: 113.7299 loss_bbox: 118.1721 loss_dfl: 135.8033 +2024/01/19 20:31:40 - mmengine - INFO - Epoch(train) [75][700/925] lr: 1.9325e-05 eta: 0:31:55 time: 0.3501 data_time: 0.0024 memory: 4746 grad_norm: 1534.2715 loss: 369.8694 loss_cls: 114.2576 loss_bbox: 119.1253 loss_dfl: 136.4865 +2024/01/19 20:31:58 - mmengine - INFO - Epoch(train) [75][750/925] lr: 1.9325e-05 eta: 0:31:35 time: 0.3511 data_time: 0.0023 memory: 4866 grad_norm: 1641.9741 loss: 369.8586 loss_cls: 113.8648 loss_bbox: 119.2055 loss_dfl: 136.7883 +2024/01/19 20:32:16 - mmengine - INFO - Epoch(train) [75][800/925] lr: 1.9325e-05 eta: 0:31:15 time: 0.3642 data_time: 0.0022 memory: 4719 grad_norm: 1738.3321 loss: 369.3152 loss_cls: 114.2871 loss_bbox: 118.8988 loss_dfl: 136.1292 +2024/01/19 20:32:33 - mmengine - INFO - Epoch(train) [75][850/925] lr: 1.9325e-05 eta: 0:30:55 time: 0.3495 data_time: 0.0024 memory: 4946 grad_norm: 1618.4176 loss: 371.3055 loss_cls: 113.9944 loss_bbox: 119.5320 loss_dfl: 137.7790 +2024/01/19 20:32:50 - mmengine - INFO - Epoch(train) [75][900/925] lr: 1.9325e-05 eta: 0:30:35 time: 0.3352 data_time: 0.0024 memory: 4826 grad_norm: 1585.2843 loss: 365.2450 loss_cls: 110.3992 loss_bbox: 119.8553 loss_dfl: 134.9905 +2024/01/19 20:32:59 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:32:59 - mmengine - INFO - Saving checkpoint at 75 epochs +2024/01/19 20:33:07 - mmengine - INFO - Epoch(val) [75][ 50/625] eta: 0:00:20 time: 0.0360 data_time: 0.0009 memory: 4839 +2024/01/19 20:33:09 - mmengine - INFO - Epoch(val) [75][100/625] eta: 0:00:18 time: 0.0353 data_time: 0.0004 memory: 843 +2024/01/19 20:33:11 - mmengine - INFO - Epoch(val) [75][150/625] eta: 0:00:16 time: 0.0353 data_time: 0.0004 memory: 843 +2024/01/19 20:33:13 - mmengine - INFO - Epoch(val) [75][200/625] eta: 0:00:15 time: 0.0349 data_time: 0.0004 memory: 843 +2024/01/19 20:33:14 - mmengine - INFO - Epoch(val) [75][250/625] eta: 0:00:13 time: 0.0350 data_time: 0.0004 memory: 843 +2024/01/19 20:33:16 - mmengine - INFO - Epoch(val) [75][300/625] eta: 0:00:11 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 20:33:18 - mmengine - INFO - Epoch(val) [75][350/625] eta: 0:00:09 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 20:33:20 - mmengine - INFO - Epoch(val) [75][400/625] eta: 0:00:07 time: 0.0364 data_time: 0.0004 memory: 843 +2024/01/19 20:33:21 - mmengine - INFO - Epoch(val) [75][450/625] eta: 0:00:06 time: 0.0321 data_time: 0.0003 memory: 843 +2024/01/19 20:33:23 - mmengine - INFO - Epoch(val) [75][500/625] eta: 0:00:04 time: 0.0266 data_time: 0.0002 memory: 843 +2024/01/19 20:33:24 - mmengine - INFO - Epoch(val) [75][550/625] eta: 0:00:02 time: 0.0264 data_time: 0.0002 memory: 843 +2024/01/19 20:33:25 - mmengine - INFO - Epoch(val) [75][600/625] eta: 0:00:00 time: 0.0261 data_time: 0.0002 memory: 843 +2024/01/19 20:33:39 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:34:53 - mmengine - INFO - bbox_mAP_copypaste: 0.456 0.619 0.497 0.262 0.506 0.616 +2024/01/19 20:34:56 - mmengine - INFO - Epoch(val) [75][625/625] coco/bbox_mAP: 0.4560 coco/bbox_mAP_50: 0.6190 coco/bbox_mAP_75: 0.4970 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5060 coco/bbox_mAP_l: 0.6160 data_time: 0.0002 time: 0.0259 +2024/01/19 20:35:17 - mmengine - INFO - Epoch(train) [76][ 50/925] lr: 1.6850e-05 eta: 0:30:05 time: 0.4193 data_time: 0.0521 memory: 4599 grad_norm: 1560.4743 loss: 366.4160 loss_cls: 112.0291 loss_bbox: 118.3710 loss_dfl: 136.0159 +2024/01/19 20:35:34 - mmengine - INFO - Epoch(train) [76][100/925] lr: 1.6850e-05 eta: 0:29:46 time: 0.3388 data_time: 0.0024 memory: 4692 grad_norm: 1482.7130 loss: 375.9863 loss_cls: 116.1116 loss_bbox: 122.6881 loss_dfl: 137.1866 +2024/01/19 20:35:50 - mmengine - INFO - Epoch(train) [76][150/925] lr: 1.6850e-05 eta: 0:29:26 time: 0.3380 data_time: 0.0023 memory: 4826 grad_norm: 1532.8977 loss: 362.5184 loss_cls: 110.5650 loss_bbox: 116.8296 loss_dfl: 135.1237 +2024/01/19 20:36:08 - mmengine - INFO - Epoch(train) [76][200/925] lr: 1.6850e-05 eta: 0:29:06 time: 0.3574 data_time: 0.0025 memory: 4666 grad_norm: 1580.1297 loss: 366.0745 loss_cls: 111.5248 loss_bbox: 118.4366 loss_dfl: 136.1131 +2024/01/19 20:36:26 - mmengine - INFO - Epoch(train) [76][250/925] lr: 1.6850e-05 eta: 0:28:46 time: 0.3541 data_time: 0.0023 memory: 4706 grad_norm: 1495.3501 loss: 367.4111 loss_cls: 110.7765 loss_bbox: 120.8428 loss_dfl: 135.7919 +2024/01/19 20:36:43 - mmengine - INFO - Epoch(train) [76][300/925] lr: 1.6850e-05 eta: 0:28:26 time: 0.3462 data_time: 0.0022 memory: 4866 grad_norm: 1456.6779 loss: 369.2271 loss_cls: 114.2035 loss_bbox: 117.6778 loss_dfl: 137.3458 +2024/01/19 20:37:01 - mmengine - INFO - Epoch(train) [76][350/925] lr: 1.6850e-05 eta: 0:28:06 time: 0.3452 data_time: 0.0024 memory: 4839 grad_norm: 1623.6685 loss: 372.5425 loss_cls: 115.2366 loss_bbox: 120.3419 loss_dfl: 136.9640 +2024/01/19 20:37:19 - mmengine - INFO - Epoch(train) [76][400/925] lr: 1.6850e-05 eta: 0:27:46 time: 0.3554 data_time: 0.0025 memory: 4799 grad_norm: 1531.6996 loss: 376.5694 loss_cls: 115.7569 loss_bbox: 122.7725 loss_dfl: 138.0400 +2024/01/19 20:37:36 - mmengine - INFO - Epoch(train) [76][450/925] lr: 1.6850e-05 eta: 0:27:26 time: 0.3541 data_time: 0.0022 memory: 4652 grad_norm: 1580.2361 loss: 364.4649 loss_cls: 110.2759 loss_bbox: 118.3078 loss_dfl: 135.8812 +2024/01/19 20:37:54 - mmengine - INFO - Epoch(train) [76][500/925] lr: 1.6850e-05 eta: 0:27:07 time: 0.3465 data_time: 0.0023 memory: 4732 grad_norm: 1517.9092 loss: 364.3138 loss_cls: 110.4625 loss_bbox: 117.6472 loss_dfl: 136.2041 +2024/01/19 20:38:11 - mmengine - INFO - Epoch(train) [76][550/925] lr: 1.6850e-05 eta: 0:26:47 time: 0.3448 data_time: 0.0025 memory: 4812 grad_norm: 1596.5061 loss: 365.0077 loss_cls: 110.9573 loss_bbox: 116.9578 loss_dfl: 137.0925 +2024/01/19 20:38:28 - mmengine - INFO - Epoch(train) [76][600/925] lr: 1.6850e-05 eta: 0:26:27 time: 0.3476 data_time: 0.0024 memory: 4826 grad_norm: 1450.1020 loss: 362.1058 loss_cls: 111.7419 loss_bbox: 114.6965 loss_dfl: 135.6674 +2024/01/19 20:38:38 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:38:46 - mmengine - INFO - Epoch(train) [76][650/925] lr: 1.6850e-05 eta: 0:26:07 time: 0.3602 data_time: 0.0021 memory: 4706 grad_norm: 1668.7148 loss: 362.2483 loss_cls: 108.9661 loss_bbox: 118.5726 loss_dfl: 134.7096 +2024/01/19 20:39:04 - mmengine - INFO - Epoch(train) [76][700/925] lr: 1.6850e-05 eta: 0:25:47 time: 0.3500 data_time: 0.0024 memory: 4879 grad_norm: 1702.0714 loss: 366.9557 loss_cls: 112.5780 loss_bbox: 118.4248 loss_dfl: 135.9528 +2024/01/19 20:39:21 - mmengine - INFO - Epoch(train) [76][750/925] lr: 1.6850e-05 eta: 0:25:27 time: 0.3470 data_time: 0.0023 memory: 4612 grad_norm: 1625.0853 loss: 362.7388 loss_cls: 108.4438 loss_bbox: 117.8547 loss_dfl: 136.4402 +2024/01/19 20:39:39 - mmengine - INFO - Epoch(train) [76][800/925] lr: 1.6850e-05 eta: 0:25:08 time: 0.3557 data_time: 0.0025 memory: 4786 grad_norm: 1508.5766 loss: 367.0784 loss_cls: 111.2936 loss_bbox: 119.2021 loss_dfl: 136.5827 +2024/01/19 20:39:57 - mmengine - INFO - Epoch(train) [76][850/925] lr: 1.6850e-05 eta: 0:24:48 time: 0.3480 data_time: 0.0022 memory: 4706 grad_norm: 1512.5069 loss: 358.9680 loss_cls: 108.5551 loss_bbox: 115.7877 loss_dfl: 134.6252 +2024/01/19 20:40:14 - mmengine - INFO - Epoch(train) [76][900/925] lr: 1.6850e-05 eta: 0:24:28 time: 0.3548 data_time: 0.0023 memory: 4732 grad_norm: 1603.5569 loss: 360.8486 loss_cls: 110.8530 loss_bbox: 116.4818 loss_dfl: 133.5138 +2024/01/19 20:40:23 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:40:25 - mmengine - INFO - Epoch(val) [76][ 50/625] eta: 0:00:21 time: 0.0366 data_time: 0.0008 memory: 4852 +2024/01/19 20:40:27 - mmengine - INFO - Epoch(val) [76][100/625] eta: 0:00:19 time: 0.0358 data_time: 0.0003 memory: 843 +2024/01/19 20:40:29 - mmengine - INFO - Epoch(val) [76][150/625] eta: 0:00:17 time: 0.0357 data_time: 0.0003 memory: 843 +2024/01/19 20:40:31 - mmengine - INFO - Epoch(val) [76][200/625] eta: 0:00:15 time: 0.0380 data_time: 0.0004 memory: 843 +2024/01/19 20:40:33 - mmengine - INFO - Epoch(val) [76][250/625] eta: 0:00:13 time: 0.0343 data_time: 0.0004 memory: 843 +2024/01/19 20:40:35 - mmengine - INFO - Epoch(val) [76][300/625] eta: 0:00:11 time: 0.0369 data_time: 0.0004 memory: 843 +2024/01/19 20:40:36 - mmengine - INFO - Epoch(val) [76][350/625] eta: 0:00:09 time: 0.0371 data_time: 0.0004 memory: 843 +2024/01/19 20:40:38 - mmengine - INFO - Epoch(val) [76][400/625] eta: 0:00:08 time: 0.0351 data_time: 0.0003 memory: 843 +2024/01/19 20:40:40 - mmengine - INFO - Epoch(val) [76][450/625] eta: 0:00:06 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 20:40:42 - mmengine - INFO - Epoch(val) [76][500/625] eta: 0:00:04 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 20:40:44 - mmengine - INFO - Epoch(val) [76][550/625] eta: 0:00:02 time: 0.0358 data_time: 0.0003 memory: 843 +2024/01/19 20:40:45 - mmengine - INFO - Epoch(val) [76][600/625] eta: 0:00:00 time: 0.0349 data_time: 0.0004 memory: 843 +2024/01/19 20:40:57 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:42:03 - mmengine - INFO - bbox_mAP_copypaste: 0.457 0.620 0.498 0.262 0.507 0.616 +2024/01/19 20:42:04 - mmengine - INFO - Epoch(val) [76][625/625] coco/bbox_mAP: 0.4570 coco/bbox_mAP_50: 0.6200 coco/bbox_mAP_75: 0.4980 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6160 data_time: 0.0004 time: 0.0344 +2024/01/19 20:42:24 - mmengine - INFO - Epoch(train) [77][ 50/925] lr: 1.4375e-05 eta: 0:23:58 time: 0.3913 data_time: 0.0521 memory: 4799 grad_norm: 1558.9192 loss: 364.8410 loss_cls: 112.6890 loss_bbox: 117.8678 loss_dfl: 134.2842 +2024/01/19 20:42:41 - mmengine - INFO - Epoch(train) [77][100/925] lr: 1.4375e-05 eta: 0:23:38 time: 0.3477 data_time: 0.0026 memory: 4772 grad_norm: 1555.4947 loss: 371.2676 loss_cls: 112.4303 loss_bbox: 122.0664 loss_dfl: 136.7709 +2024/01/19 20:43:00 - mmengine - INFO - Epoch(train) [77][150/925] lr: 1.4375e-05 eta: 0:23:19 time: 0.3752 data_time: 0.0023 memory: 4812 grad_norm: 1525.8408 loss: 364.4681 loss_cls: 110.5666 loss_bbox: 118.8556 loss_dfl: 135.0459 +2024/01/19 20:43:18 - mmengine - INFO - Epoch(train) [77][200/925] lr: 1.4375e-05 eta: 0:22:59 time: 0.3649 data_time: 0.0024 memory: 4612 grad_norm: 1547.4823 loss: 357.4818 loss_cls: 108.3770 loss_bbox: 115.0250 loss_dfl: 134.0798 +2024/01/19 20:43:36 - mmengine - INFO - Epoch(train) [77][250/925] lr: 1.4375e-05 eta: 0:22:39 time: 0.3550 data_time: 0.0023 memory: 4772 grad_norm: 1614.1852 loss: 367.8855 loss_cls: 112.9249 loss_bbox: 119.5339 loss_dfl: 135.4268 +2024/01/19 20:43:55 - mmengine - INFO - Epoch(train) [77][300/925] lr: 1.4375e-05 eta: 0:22:19 time: 0.3674 data_time: 0.0022 memory: 4706 grad_norm: 1546.8370 loss: 364.5611 loss_cls: 110.4260 loss_bbox: 118.8847 loss_dfl: 135.2504 +2024/01/19 20:44:13 - mmengine - INFO - Epoch(train) [77][350/925] lr: 1.4375e-05 eta: 0:22:00 time: 0.3615 data_time: 0.0023 memory: 4652 grad_norm: 1544.7531 loss: 358.1367 loss_cls: 107.4530 loss_bbox: 116.2845 loss_dfl: 134.3992 +2024/01/19 20:44:31 - mmengine - INFO - Epoch(train) [77][400/925] lr: 1.4375e-05 eta: 0:21:40 time: 0.3611 data_time: 0.0021 memory: 4746 grad_norm: 1524.8143 loss: 366.8230 loss_cls: 112.2167 loss_bbox: 119.0736 loss_dfl: 135.5327 +2024/01/19 20:44:48 - mmengine - INFO - Epoch(train) [77][450/925] lr: 1.4375e-05 eta: 0:21:20 time: 0.3500 data_time: 0.0022 memory: 4692 grad_norm: 1480.1741 loss: 356.9627 loss_cls: 107.8638 loss_bbox: 114.4026 loss_dfl: 134.6963 +2024/01/19 20:45:07 - mmengine - INFO - Epoch(train) [77][500/925] lr: 1.4375e-05 eta: 0:21:00 time: 0.3659 data_time: 0.0024 memory: 4679 grad_norm: inf loss: 361.9074 loss_cls: 110.4549 loss_bbox: 116.8665 loss_dfl: 134.5861 +2024/01/19 20:45:25 - mmengine - INFO - Epoch(train) [77][550/925] lr: 1.4375e-05 eta: 0:20:40 time: 0.3590 data_time: 0.0022 memory: 4852 grad_norm: 1521.7614 loss: 361.3969 loss_cls: 109.3450 loss_bbox: 116.4089 loss_dfl: 135.6429 +2024/01/19 20:45:43 - mmengine - INFO - Epoch(train) [77][600/925] lr: 1.4375e-05 eta: 0:20:21 time: 0.3618 data_time: 0.0021 memory: 4839 grad_norm: 1528.5062 loss: 367.7990 loss_cls: 111.6140 loss_bbox: 120.1827 loss_dfl: 136.0023 +2024/01/19 20:46:00 - mmengine - INFO - Epoch(train) [77][650/925] lr: 1.4375e-05 eta: 0:20:01 time: 0.3487 data_time: 0.0024 memory: 4719 grad_norm: 1502.9695 loss: 376.2435 loss_cls: 113.6460 loss_bbox: 123.1334 loss_dfl: 139.4641 +2024/01/19 20:46:18 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:46:18 - mmengine - INFO - Epoch(train) [77][700/925] lr: 1.4375e-05 eta: 0:19:41 time: 0.3642 data_time: 0.0023 memory: 4852 grad_norm: 1430.7927 loss: 360.9083 loss_cls: 109.5553 loss_bbox: 115.6552 loss_dfl: 135.6978 +2024/01/19 20:46:37 - mmengine - INFO - Epoch(train) [77][750/925] lr: 1.4375e-05 eta: 0:19:21 time: 0.3764 data_time: 0.0024 memory: 4799 grad_norm: 1498.4290 loss: 358.7496 loss_cls: 108.4947 loss_bbox: 115.2017 loss_dfl: 135.0531 +2024/01/19 20:46:55 - mmengine - INFO - Epoch(train) [77][800/925] lr: 1.4375e-05 eta: 0:19:02 time: 0.3560 data_time: 0.0022 memory: 4812 grad_norm: 1575.1541 loss: 369.2277 loss_cls: 113.6632 loss_bbox: 118.8967 loss_dfl: 136.6678 +2024/01/19 20:47:13 - mmengine - INFO - Epoch(train) [77][850/925] lr: 1.4375e-05 eta: 0:18:42 time: 0.3510 data_time: 0.0024 memory: 4839 grad_norm: 1458.0755 loss: 366.9264 loss_cls: 113.5142 loss_bbox: 117.2302 loss_dfl: 136.1820 +2024/01/19 20:47:31 - mmengine - INFO - Epoch(train) [77][900/925] lr: 1.4375e-05 eta: 0:18:22 time: 0.3607 data_time: 0.0147 memory: 4772 grad_norm: 1441.0560 loss: 360.6328 loss_cls: 107.4950 loss_bbox: 117.7221 loss_dfl: 135.4158 +2024/01/19 20:47:40 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:47:42 - mmengine - INFO - Epoch(val) [77][ 50/625] eta: 0:00:21 time: 0.0376 data_time: 0.0029 memory: 4599 +2024/01/19 20:47:44 - mmengine - INFO - Epoch(val) [77][100/625] eta: 0:00:19 time: 0.0349 data_time: 0.0003 memory: 843 +2024/01/19 20:47:46 - mmengine - INFO - Epoch(val) [77][150/625] eta: 0:00:17 time: 0.0355 data_time: 0.0004 memory: 843 +2024/01/19 20:47:47 - mmengine - INFO - Epoch(val) [77][200/625] eta: 0:00:15 time: 0.0350 data_time: 0.0003 memory: 843 +2024/01/19 20:47:49 - mmengine - INFO - Epoch(val) [77][250/625] eta: 0:00:13 time: 0.0374 data_time: 0.0014 memory: 843 +2024/01/19 20:47:51 - mmengine - INFO - Epoch(val) [77][300/625] eta: 0:00:11 time: 0.0358 data_time: 0.0004 memory: 843 +2024/01/19 20:47:53 - mmengine - INFO - Epoch(val) [77][350/625] eta: 0:00:10 time: 0.0401 data_time: 0.0031 memory: 843 +2024/01/19 20:47:55 - mmengine - INFO - Epoch(val) [77][400/625] eta: 0:00:08 time: 0.0353 data_time: 0.0003 memory: 843 +2024/01/19 20:47:57 - mmengine - INFO - Epoch(val) [77][450/625] eta: 0:00:06 time: 0.0343 data_time: 0.0003 memory: 843 +2024/01/19 20:47:58 - mmengine - INFO - Epoch(val) [77][500/625] eta: 0:00:04 time: 0.0355 data_time: 0.0009 memory: 843 +2024/01/19 20:48:00 - mmengine - INFO - Epoch(val) [77][550/625] eta: 0:00:02 time: 0.0361 data_time: 0.0004 memory: 843 +2024/01/19 20:48:02 - mmengine - INFO - Epoch(val) [77][600/625] eta: 0:00:00 time: 0.0364 data_time: 0.0021 memory: 843 +2024/01/19 20:48:15 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:49:28 - mmengine - INFO - bbox_mAP_copypaste: 0.457 0.620 0.498 0.262 0.507 0.616 +2024/01/19 20:49:30 - mmengine - INFO - Epoch(val) [77][625/625] coco/bbox_mAP: 0.4570 coco/bbox_mAP_50: 0.6200 coco/bbox_mAP_75: 0.4980 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6160 data_time: 0.0022 time: 0.0360 +2024/01/19 20:49:50 - mmengine - INFO - Epoch(train) [78][ 50/925] lr: 1.1900e-05 eta: 0:17:53 time: 0.3982 data_time: 0.0485 memory: 4732 grad_norm: 1491.1271 loss: 371.1991 loss_cls: 112.5546 loss_bbox: 120.9084 loss_dfl: 137.7360 +2024/01/19 20:50:07 - mmengine - INFO - Epoch(train) [78][100/925] lr: 1.1900e-05 eta: 0:17:33 time: 0.3381 data_time: 0.0025 memory: 4772 grad_norm: 1550.1466 loss: 368.7961 loss_cls: 110.5847 loss_bbox: 121.4332 loss_dfl: 136.7783 +2024/01/19 20:50:25 - mmengine - INFO - Epoch(train) [78][150/925] lr: 1.1900e-05 eta: 0:17:13 time: 0.3453 data_time: 0.0023 memory: 4692 grad_norm: 1522.1636 loss: 368.7495 loss_cls: 112.6024 loss_bbox: 118.9796 loss_dfl: 137.1675 +2024/01/19 20:50:42 - mmengine - INFO - Epoch(train) [78][200/925] lr: 1.1900e-05 eta: 0:16:53 time: 0.3491 data_time: 0.0024 memory: 4759 grad_norm: 1487.4298 loss: 362.7120 loss_cls: 109.8332 loss_bbox: 117.9756 loss_dfl: 134.9032 +2024/01/19 20:50:59 - mmengine - INFO - Epoch(train) [78][250/925] lr: 1.1900e-05 eta: 0:16:33 time: 0.3397 data_time: 0.0024 memory: 4972 grad_norm: 1609.3828 loss: 364.5023 loss_cls: 110.4081 loss_bbox: 118.0893 loss_dfl: 136.0048 +2024/01/19 20:51:16 - mmengine - INFO - Epoch(train) [78][300/925] lr: 1.1900e-05 eta: 0:16:14 time: 0.3435 data_time: 0.0023 memory: 4759 grad_norm: 1495.9841 loss: 362.1878 loss_cls: 110.8356 loss_bbox: 116.0982 loss_dfl: 135.2541 +2024/01/19 20:51:33 - mmengine - INFO - Epoch(train) [78][350/925] lr: 1.1900e-05 eta: 0:15:54 time: 0.3355 data_time: 0.0020 memory: 4959 grad_norm: 1518.2412 loss: 366.6349 loss_cls: 112.1115 loss_bbox: 118.0993 loss_dfl: 136.4240 +2024/01/19 20:51:50 - mmengine - INFO - Epoch(train) [78][400/925] lr: 1.1900e-05 eta: 0:15:34 time: 0.3468 data_time: 0.0022 memory: 4732 grad_norm: 1542.0551 loss: 355.1871 loss_cls: 107.3786 loss_bbox: 112.8530 loss_dfl: 134.9555 +2024/01/19 20:52:07 - mmengine - INFO - Epoch(train) [78][450/925] lr: 1.1900e-05 eta: 0:15:14 time: 0.3385 data_time: 0.0023 memory: 4879 grad_norm: 1546.4233 loss: 362.9343 loss_cls: 109.1448 loss_bbox: 117.3847 loss_dfl: 136.4048 +2024/01/19 20:52:24 - mmengine - INFO - Epoch(train) [78][500/925] lr: 1.1900e-05 eta: 0:14:55 time: 0.3401 data_time: 0.0023 memory: 4706 grad_norm: 1482.5782 loss: 363.7808 loss_cls: 110.8544 loss_bbox: 117.8052 loss_dfl: 135.1212 +2024/01/19 20:52:42 - mmengine - INFO - Epoch(train) [78][550/925] lr: 1.1900e-05 eta: 0:14:35 time: 0.3404 data_time: 0.0023 memory: 4799 grad_norm: 1425.7748 loss: 365.6767 loss_cls: 110.7160 loss_bbox: 117.9581 loss_dfl: 137.0026 +2024/01/19 20:52:59 - mmengine - INFO - Epoch(train) [78][600/925] lr: 1.1900e-05 eta: 0:14:15 time: 0.3458 data_time: 0.0024 memory: 4652 grad_norm: 1486.6718 loss: 362.5758 loss_cls: 109.9723 loss_bbox: 118.1475 loss_dfl: 134.4560 +2024/01/19 20:53:16 - mmengine - INFO - Epoch(train) [78][650/925] lr: 1.1900e-05 eta: 0:13:55 time: 0.3415 data_time: 0.0024 memory: 4746 grad_norm: 1598.2838 loss: 360.8850 loss_cls: 109.6975 loss_bbox: 115.7796 loss_dfl: 135.4080 +2024/01/19 20:53:33 - mmengine - INFO - Epoch(train) [78][700/925] lr: 1.1900e-05 eta: 0:13:36 time: 0.3466 data_time: 0.0024 memory: 4852 grad_norm: 1556.5711 loss: 357.1206 loss_cls: 107.8215 loss_bbox: 115.1665 loss_dfl: 134.1326 +2024/01/19 20:53:50 - mmengine - INFO - Epoch(train) [78][750/925] lr: 1.1900e-05 eta: 0:13:16 time: 0.3395 data_time: 0.0023 memory: 4919 grad_norm: 1608.5107 loss: 367.7478 loss_cls: 111.9109 loss_bbox: 119.9241 loss_dfl: 135.9128 +2024/01/19 20:53:59 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:54:08 - mmengine - INFO - Epoch(train) [78][800/925] lr: 1.1900e-05 eta: 0:12:56 time: 0.3424 data_time: 0.0023 memory: 4666 grad_norm: 1590.9569 loss: 362.4466 loss_cls: 108.8917 loss_bbox: 117.9754 loss_dfl: 135.5794 +2024/01/19 20:54:25 - mmengine - INFO - Epoch(train) [78][850/925] lr: 1.1900e-05 eta: 0:12:36 time: 0.3476 data_time: 0.0023 memory: 4639 grad_norm: 1512.9465 loss: 365.9521 loss_cls: 109.8264 loss_bbox: 119.7814 loss_dfl: 136.3443 +2024/01/19 20:54:41 - mmengine - INFO - Epoch(train) [78][900/925] lr: 1.1900e-05 eta: 0:12:17 time: 0.3295 data_time: 0.0024 memory: 4732 grad_norm: 1556.6511 loss: 370.8605 loss_cls: 112.2299 loss_bbox: 121.8761 loss_dfl: 136.7545 +2024/01/19 20:54:49 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 20:54:51 - mmengine - INFO - Epoch(val) [78][ 50/625] eta: 0:00:20 time: 0.0354 data_time: 0.0008 memory: 4652 +2024/01/19 20:54:53 - mmengine - INFO - Epoch(val) [78][100/625] eta: 0:00:18 time: 0.0341 data_time: 0.0003 memory: 843 +2024/01/19 20:54:55 - mmengine - INFO - Epoch(val) [78][150/625] eta: 0:00:16 time: 0.0368 data_time: 0.0004 memory: 843 +2024/01/19 20:54:57 - mmengine - INFO - Epoch(val) [78][200/625] eta: 0:00:15 time: 0.0363 data_time: 0.0004 memory: 843 +2024/01/19 20:54:58 - mmengine - INFO - Epoch(val) [78][250/625] eta: 0:00:13 time: 0.0354 data_time: 0.0003 memory: 843 +2024/01/19 20:55:00 - mmengine - INFO - Epoch(val) [78][300/625] eta: 0:00:11 time: 0.0363 data_time: 0.0003 memory: 843 +2024/01/19 20:55:02 - mmengine - INFO - Epoch(val) [78][350/625] eta: 0:00:09 time: 0.0366 data_time: 0.0003 memory: 843 +2024/01/19 20:55:04 - mmengine - INFO - Epoch(val) [78][400/625] eta: 0:00:08 time: 0.0338 data_time: 0.0003 memory: 843 +2024/01/19 20:55:05 - mmengine - INFO - Epoch(val) [78][450/625] eta: 0:00:06 time: 0.0346 data_time: 0.0003 memory: 843 +2024/01/19 20:55:07 - mmengine - INFO - Epoch(val) [78][500/625] eta: 0:00:04 time: 0.0356 data_time: 0.0004 memory: 843 +2024/01/19 20:55:09 - mmengine - INFO - Epoch(val) [78][550/625] eta: 0:00:02 time: 0.0370 data_time: 0.0004 memory: 843 +2024/01/19 20:55:11 - mmengine - INFO - Epoch(val) [78][600/625] eta: 0:00:00 time: 0.0355 data_time: 0.0003 memory: 843 +2024/01/19 20:55:24 - mmengine - INFO - Evaluating bbox... +2024/01/19 20:56:39 - mmengine - INFO - bbox_mAP_copypaste: 0.457 0.620 0.498 0.261 0.507 0.616 +2024/01/19 20:56:41 - mmengine - INFO - Epoch(val) [78][625/625] coco/bbox_mAP: 0.4570 coco/bbox_mAP_50: 0.6200 coco/bbox_mAP_75: 0.4980 coco/bbox_mAP_s: 0.2610 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6160 data_time: 0.0004 time: 0.0360 +2024/01/19 20:57:01 - mmengine - INFO - Epoch(train) [79][ 50/925] lr: 9.4250e-06 eta: 0:11:47 time: 0.3870 data_time: 0.0500 memory: 4586 grad_norm: 1446.0792 loss: 361.0236 loss_cls: 108.4826 loss_bbox: 116.0474 loss_dfl: 136.4937 +2024/01/19 20:57:17 - mmengine - INFO - Epoch(train) [79][100/925] lr: 9.4250e-06 eta: 0:11:27 time: 0.3334 data_time: 0.0023 memory: 4706 grad_norm: 1548.1546 loss: 358.9000 loss_cls: 108.2952 loss_bbox: 115.9068 loss_dfl: 134.6979 +2024/01/19 20:57:35 - mmengine - INFO - Epoch(train) [79][150/925] lr: 9.4250e-06 eta: 0:11:08 time: 0.3478 data_time: 0.0024 memory: 4826 grad_norm: 1459.4113 loss: 362.3428 loss_cls: 108.9971 loss_bbox: 118.7116 loss_dfl: 134.6342 +2024/01/19 20:57:51 - mmengine - INFO - Epoch(train) [79][200/925] lr: 9.4250e-06 eta: 0:10:48 time: 0.3249 data_time: 0.0024 memory: 4786 grad_norm: 1439.8494 loss: 358.9314 loss_cls: 107.8774 loss_bbox: 116.3459 loss_dfl: 134.7080 +2024/01/19 20:58:08 - mmengine - INFO - Epoch(train) [79][250/925] lr: 9.4250e-06 eta: 0:10:28 time: 0.3436 data_time: 0.0021 memory: 4826 grad_norm: 1575.3548 loss: 357.9655 loss_cls: 108.2233 loss_bbox: 115.1656 loss_dfl: 134.5766 +2024/01/19 20:58:26 - mmengine - INFO - Epoch(train) [79][300/925] lr: 9.4250e-06 eta: 0:10:09 time: 0.3522 data_time: 0.0024 memory: 4692 grad_norm: 1476.7688 loss: 364.4049 loss_cls: 111.9739 loss_bbox: 117.7762 loss_dfl: 134.6548 +2024/01/19 20:58:44 - mmengine - INFO - Epoch(train) [79][350/925] lr: 9.4250e-06 eta: 0:09:49 time: 0.3591 data_time: 0.0022 memory: 4759 grad_norm: 1451.6224 loss: 361.6965 loss_cls: 109.1284 loss_bbox: 116.3352 loss_dfl: 136.2329 +2024/01/19 20:59:00 - mmengine - INFO - Epoch(train) [79][400/925] lr: 9.4250e-06 eta: 0:09:29 time: 0.3268 data_time: 0.0025 memory: 4772 grad_norm: 1508.0347 loss: 356.1793 loss_cls: 107.8657 loss_bbox: 114.7722 loss_dfl: 133.5413 +2024/01/19 20:59:18 - mmengine - INFO - Epoch(train) [79][450/925] lr: 9.4250e-06 eta: 0:09:09 time: 0.3562 data_time: 0.0021 memory: 4612 grad_norm: 1581.2329 loss: 359.1917 loss_cls: 109.1205 loss_bbox: 115.9221 loss_dfl: 134.1491 +2024/01/19 20:59:36 - mmengine - INFO - Epoch(train) [79][500/925] lr: 9.4250e-06 eta: 0:08:50 time: 0.3478 data_time: 0.0023 memory: 4626 grad_norm: 1449.6993 loss: 366.7505 loss_cls: 111.7050 loss_bbox: 118.9051 loss_dfl: 136.1404 +2024/01/19 20:59:53 - mmengine - INFO - Epoch(train) [79][550/925] lr: 9.4250e-06 eta: 0:08:30 time: 0.3496 data_time: 0.0024 memory: 4919 grad_norm: 1626.9441 loss: 358.5676 loss_cls: 108.6056 loss_bbox: 115.3551 loss_dfl: 134.6068 +2024/01/19 21:00:09 - mmengine - INFO - Epoch(train) [79][600/925] lr: 9.4250e-06 eta: 0:08:10 time: 0.3162 data_time: 0.0023 memory: 4706 grad_norm: 1496.9758 loss: 367.3108 loss_cls: 111.8772 loss_bbox: 119.1844 loss_dfl: 136.2492 +2024/01/19 21:00:26 - mmengine - INFO - Epoch(train) [79][650/925] lr: 9.4250e-06 eta: 0:07:51 time: 0.3462 data_time: 0.0023 memory: 4839 grad_norm: 1569.9803 loss: 362.5702 loss_cls: 110.0598 loss_bbox: 117.6684 loss_dfl: 134.8419 +2024/01/19 21:00:44 - mmengine - INFO - Epoch(train) [79][700/925] lr: 9.4250e-06 eta: 0:07:31 time: 0.3488 data_time: 0.0022 memory: 4826 grad_norm: 1378.3142 loss: 360.7710 loss_cls: 108.2585 loss_bbox: 118.1689 loss_dfl: 134.3436 +2024/01/19 21:01:01 - mmengine - INFO - Epoch(train) [79][750/925] lr: 9.4250e-06 eta: 0:07:11 time: 0.3431 data_time: 0.0024 memory: 4812 grad_norm: 1489.6701 loss: 368.0521 loss_cls: 111.0604 loss_bbox: 120.2225 loss_dfl: 136.7692 +2024/01/19 21:01:18 - mmengine - INFO - Epoch(train) [79][800/925] lr: 9.4250e-06 eta: 0:06:52 time: 0.3299 data_time: 0.0021 memory: 4852 grad_norm: 1504.8629 loss: 355.8831 loss_cls: 106.4342 loss_bbox: 114.3855 loss_dfl: 135.0633 +2024/01/19 21:01:36 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 21:01:36 - mmengine - INFO - Epoch(train) [79][850/925] lr: 9.4250e-06 eta: 0:06:32 time: 0.3640 data_time: 0.0024 memory: 4706 grad_norm: 1516.1138 loss: 358.8046 loss_cls: 108.2791 loss_bbox: 115.5431 loss_dfl: 134.9823 +2024/01/19 21:01:53 - mmengine - INFO - Epoch(train) [79][900/925] lr: 9.4250e-06 eta: 0:06:12 time: 0.3405 data_time: 0.0022 memory: 4692 grad_norm: 1453.0084 loss: 361.7246 loss_cls: 109.4491 loss_bbox: 118.0766 loss_dfl: 134.1989 +2024/01/19 21:02:01 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 21:02:04 - mmengine - INFO - Epoch(val) [79][ 50/625] eta: 0:00:21 time: 0.0367 data_time: 0.0008 memory: 4719 +2024/01/19 21:02:05 - mmengine - INFO - Epoch(val) [79][100/625] eta: 0:00:18 time: 0.0344 data_time: 0.0003 memory: 843 +2024/01/19 21:02:07 - mmengine - INFO - Epoch(val) [79][150/625] eta: 0:00:17 time: 0.0369 data_time: 0.0004 memory: 843 +2024/01/19 21:02:09 - mmengine - INFO - Epoch(val) [79][200/625] eta: 0:00:15 time: 0.0372 data_time: 0.0004 memory: 843 +2024/01/19 21:02:11 - mmengine - INFO - Epoch(val) [79][250/625] eta: 0:00:13 time: 0.0353 data_time: 0.0003 memory: 843 +2024/01/19 21:02:13 - mmengine - INFO - Epoch(val) [79][300/625] eta: 0:00:11 time: 0.0360 data_time: 0.0004 memory: 843 +2024/01/19 21:02:14 - mmengine - INFO - Epoch(val) [79][350/625] eta: 0:00:09 time: 0.0356 data_time: 0.0004 memory: 843 +2024/01/19 21:02:16 - mmengine - INFO - Epoch(val) [79][400/625] eta: 0:00:08 time: 0.0356 data_time: 0.0004 memory: 843 +2024/01/19 21:02:18 - mmengine - INFO - Epoch(val) [79][450/625] eta: 0:00:06 time: 0.0349 data_time: 0.0004 memory: 843 +2024/01/19 21:02:20 - mmengine - INFO - Epoch(val) [79][500/625] eta: 0:00:04 time: 0.0362 data_time: 0.0003 memory: 843 +2024/01/19 21:02:22 - mmengine - INFO - Epoch(val) [79][550/625] eta: 0:00:02 time: 0.0357 data_time: 0.0004 memory: 843 +2024/01/19 21:02:23 - mmengine - INFO - Epoch(val) [79][600/625] eta: 0:00:00 time: 0.0354 data_time: 0.0004 memory: 843 +2024/01/19 21:02:36 - mmengine - INFO - Evaluating bbox... +2024/01/19 21:03:52 - mmengine - INFO - bbox_mAP_copypaste: 0.457 0.620 0.498 0.262 0.507 0.616 +2024/01/19 21:03:54 - mmengine - INFO - Epoch(val) [79][625/625] coco/bbox_mAP: 0.4570 coco/bbox_mAP_50: 0.6200 coco/bbox_mAP_75: 0.4980 coco/bbox_mAP_s: 0.2620 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6160 data_time: 0.0003 time: 0.0333 +2024/01/19 21:04:13 - mmengine - INFO - Epoch(train) [80][ 50/925] lr: 6.9500e-06 eta: 0:05:43 time: 0.3739 data_time: 0.0497 memory: 4706 grad_norm: inf loss: 367.9045 loss_cls: 112.7977 loss_bbox: 119.3005 loss_dfl: 135.8063 +2024/01/19 21:04:31 - mmengine - INFO - Epoch(train) [80][100/925] lr: 6.9500e-06 eta: 0:05:23 time: 0.3554 data_time: 0.0025 memory: 4839 grad_norm: 1533.1238 loss: 357.5594 loss_cls: 108.7975 loss_bbox: 113.7822 loss_dfl: 134.9797 +2024/01/19 21:04:49 - mmengine - INFO - Epoch(train) [80][150/925] lr: 6.9500e-06 eta: 0:05:04 time: 0.3606 data_time: 0.0024 memory: 4919 grad_norm: 1543.8291 loss: 361.2294 loss_cls: 110.9176 loss_bbox: 115.9148 loss_dfl: 134.3969 +2024/01/19 21:05:06 - mmengine - INFO - Epoch(train) [80][200/925] lr: 6.9500e-06 eta: 0:04:44 time: 0.3543 data_time: 0.0023 memory: 4759 grad_norm: 1494.1460 loss: 366.1449 loss_cls: 109.9853 loss_bbox: 120.5436 loss_dfl: 135.6161 +2024/01/19 21:05:24 - mmengine - INFO - Epoch(train) [80][250/925] lr: 6.9500e-06 eta: 0:04:24 time: 0.3491 data_time: 0.0023 memory: 4772 grad_norm: 1472.1815 loss: 356.0855 loss_cls: 108.0361 loss_bbox: 114.2540 loss_dfl: 133.7954 +2024/01/19 21:05:42 - mmengine - INFO - Epoch(train) [80][300/925] lr: 6.9500e-06 eta: 0:04:05 time: 0.3640 data_time: 0.0025 memory: 4692 grad_norm: 1466.0609 loss: 357.3593 loss_cls: 106.7329 loss_bbox: 115.5500 loss_dfl: 135.0764 +2024/01/19 21:06:00 - mmengine - INFO - Epoch(train) [80][350/925] lr: 6.9500e-06 eta: 0:03:45 time: 0.3614 data_time: 0.0027 memory: 4732 grad_norm: 1475.3196 loss: 367.1307 loss_cls: 113.6057 loss_bbox: 117.5117 loss_dfl: 136.0133 +2024/01/19 21:06:18 - mmengine - INFO - Epoch(train) [80][400/925] lr: 6.9500e-06 eta: 0:03:25 time: 0.3457 data_time: 0.0024 memory: 4612 grad_norm: 1481.5082 loss: 364.7908 loss_cls: 110.3559 loss_bbox: 118.6347 loss_dfl: 135.8003 +2024/01/19 21:06:35 - mmengine - INFO - Epoch(train) [80][450/925] lr: 6.9500e-06 eta: 0:03:06 time: 0.3544 data_time: 0.0025 memory: 4666 grad_norm: 1572.5571 loss: 361.5049 loss_cls: 109.3925 loss_bbox: 117.6829 loss_dfl: 134.4295 +2024/01/19 21:06:54 - mmengine - INFO - Epoch(train) [80][500/925] lr: 6.9500e-06 eta: 0:02:46 time: 0.3687 data_time: 0.0025 memory: 4719 grad_norm: 1467.6473 loss: 372.2829 loss_cls: 114.3567 loss_bbox: 119.2809 loss_dfl: 138.6454 +2024/01/19 21:07:11 - mmengine - INFO - Epoch(train) [80][550/925] lr: 6.9500e-06 eta: 0:02:27 time: 0.3485 data_time: 0.0024 memory: 4746 grad_norm: 1518.5932 loss: 356.9288 loss_cls: 107.8983 loss_bbox: 114.1260 loss_dfl: 134.9045 +2024/01/19 21:07:29 - mmengine - INFO - Epoch(train) [80][600/925] lr: 6.9500e-06 eta: 0:02:07 time: 0.3547 data_time: 0.0024 memory: 4719 grad_norm: 1437.3671 loss: 359.2666 loss_cls: 108.8843 loss_bbox: 115.6015 loss_dfl: 134.7809 +2024/01/19 21:07:47 - mmengine - INFO - Epoch(train) [80][650/925] lr: 6.9500e-06 eta: 0:01:47 time: 0.3572 data_time: 0.0023 memory: 4799 grad_norm: 1482.9449 loss: 359.8307 loss_cls: 107.4943 loss_bbox: 116.1423 loss_dfl: 136.1942 +2024/01/19 21:08:05 - mmengine - INFO - Epoch(train) [80][700/925] lr: 6.9500e-06 eta: 0:01:28 time: 0.3534 data_time: 0.0024 memory: 4986 grad_norm: 1619.6194 loss: 353.5664 loss_cls: 107.6824 loss_bbox: 113.4607 loss_dfl: 132.4234 +2024/01/19 21:08:23 - mmengine - INFO - Epoch(train) [80][750/925] lr: 6.9500e-06 eta: 0:01:08 time: 0.3575 data_time: 0.0023 memory: 4799 grad_norm: 1533.5435 loss: 359.5553 loss_cls: 106.1204 loss_bbox: 117.8375 loss_dfl: 135.5973 +2024/01/19 21:08:41 - mmengine - INFO - Epoch(train) [80][800/925] lr: 6.9500e-06 eta: 0:00:49 time: 0.3609 data_time: 0.0023 memory: 5239 grad_norm: 1471.2831 loss: 359.7915 loss_cls: 107.1863 loss_bbox: 118.3152 loss_dfl: 134.2901 +2024/01/19 21:08:59 - mmengine - INFO - Epoch(train) [80][850/925] lr: 6.9500e-06 eta: 0:00:29 time: 0.3626 data_time: 0.0020 memory: 4719 grad_norm: 1501.5161 loss: 359.3650 loss_cls: 107.6593 loss_bbox: 115.5843 loss_dfl: 136.1214 +2024/01/19 21:09:16 - mmengine - INFO - Epoch(train) [80][900/925] lr: 6.9500e-06 eta: 0:00:09 time: 0.3483 data_time: 0.0022 memory: 4812 grad_norm: 1551.7775 loss: 362.4034 loss_cls: 109.9970 loss_bbox: 117.7245 loss_dfl: 134.6819 +2024/01/19 21:09:25 - mmengine - INFO - Exp name: yolow-v8_s_clipv2_frozen_t2i_bn_2e-4adamw_80e_coco_finetune_20240119_121515 +2024/01/19 21:09:25 - mmengine - INFO - Saving checkpoint at 80 epochs +2024/01/19 21:09:34 - mmengine - INFO - Epoch(val) [80][ 50/625] eta: 0:00:21 time: 0.0367 data_time: 0.0008 memory: 4839 +2024/01/19 21:09:36 - mmengine - INFO - Epoch(val) [80][100/625] eta: 0:00:19 time: 0.0366 data_time: 0.0004 memory: 843 +2024/01/19 21:09:37 - mmengine - INFO - Epoch(val) [80][150/625] eta: 0:00:17 time: 0.0356 data_time: 0.0003 memory: 843 +2024/01/19 21:09:39 - mmengine - INFO - Epoch(val) [80][200/625] eta: 0:00:15 time: 0.0370 data_time: 0.0004 memory: 843 +2024/01/19 21:09:41 - mmengine - INFO - Epoch(val) [80][250/625] eta: 0:00:13 time: 0.0362 data_time: 0.0004 memory: 843 +2024/01/19 21:09:43 - mmengine - INFO - Epoch(val) [80][300/625] eta: 0:00:11 time: 0.0368 data_time: 0.0007 memory: 843 +2024/01/19 21:09:45 - mmengine - INFO - Epoch(val) [80][350/625] eta: 0:00:09 time: 0.0346 data_time: 0.0004 memory: 843 +2024/01/19 21:09:47 - mmengine - INFO - Epoch(val) [80][400/625] eta: 0:00:08 time: 0.0364 data_time: 0.0004 memory: 843 +2024/01/19 21:09:48 - mmengine - INFO - Epoch(val) [80][450/625] eta: 0:00:06 time: 0.0311 data_time: 0.0003 memory: 843 +2024/01/19 21:09:50 - mmengine - INFO - Epoch(val) [80][500/625] eta: 0:00:04 time: 0.0276 data_time: 0.0002 memory: 843 +2024/01/19 21:09:51 - mmengine - INFO - Epoch(val) [80][550/625] eta: 0:00:02 time: 0.0288 data_time: 0.0003 memory: 843 +2024/01/19 21:09:52 - mmengine - INFO - Epoch(val) [80][600/625] eta: 0:00:00 time: 0.0265 data_time: 0.0002 memory: 843 +2024/01/19 21:10:05 - mmengine - INFO - Evaluating bbox... +2024/01/19 21:11:10 - mmengine - INFO - bbox_mAP_copypaste: 0.457 0.620 0.498 0.258 0.507 0.615 +2024/01/19 21:11:11 - mmengine - INFO - Epoch(val) [80][625/625] coco/bbox_mAP: 0.4570 coco/bbox_mAP_50: 0.6200 coco/bbox_mAP_75: 0.4980 coco/bbox_mAP_s: 0.2580 coco/bbox_mAP_m: 0.5070 coco/bbox_mAP_l: 0.6150 data_time: 0.0002 time: 0.0265