train
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data/hyp.finetune.yaml
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data/hyp.finetune.yaml
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# Hyperparameters for VOC finetuning
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# python train.py --batch 64 --weights yolov5m.pt --data voc.yaml --img 512 --epochs 50
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# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
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# Hyperparameter Evolution Results
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# Generations: 306
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# P R mAP.5 mAP.5:.95 box obj cls
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# Metrics: 0.6 0.936 0.896 0.684 0.0115 0.00805 0.00146
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lr0: 0.0032
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lrf: 0.12
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momentum: 0.843
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weight_decay: 0.00036
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warmup_epochs: 2.0
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warmup_momentum: 0.5
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warmup_bias_lr: 0.05
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box: 0.0296
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cls: 0.243
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cls_pw: 0.631
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obj: 0.301
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obj_pw: 0.911
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iou_t: 0.2
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anchor_t: 2.91
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# anchors: 3.63
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fl_gamma: 0.0
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hsv_h: 0.0138
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hsv_s: 0.664
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hsv_v: 0.464
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#degrees: 0.6
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degrees: 0.373
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translate: 0.245
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scale: 0.898
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shear: 0.602
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perspective: 0.0
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flipud: 0.00856
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fliplr: 0.5
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mosaic: 1.0
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mixup: 0.243
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#mixup: 0.8
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