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  1. # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
  2. # Hyperparameters for VOC finetuning
  3. # python train.py --batch 64 --weights yolov5m.pt --data VOC.yaml --img 512 --epochs 50
  4. # See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
  5. # Hyperparameter Evolution Results
  6. # Generations: 306
  7. # P R mAP.5 mAP.5:.95 box obj cls
  8. # Metrics: 0.6 0.936 0.896 0.684 0.0115 0.00805 0.00146
  9. lr0: 0.0032
  10. lrf: 0.12
  11. momentum: 0.843
  12. weight_decay: 0.00036
  13. warmup_epochs: 2.0
  14. warmup_momentum: 0.5
  15. warmup_bias_lr: 0.05
  16. box: 0.0296
  17. cls: 0.243
  18. cls_pw: 0.631
  19. obj: 0.301
  20. obj_pw: 0.911
  21. iou_t: 0.2
  22. anchor_t: 2.91
  23. # anchors: 3.63
  24. fl_gamma: 0.0
  25. hsv_h: 0.0138
  26. hsv_s: 0.664
  27. hsv_v: 0.464
  28. degrees: 0.373
  29. translate: 0.245
  30. scale: 0.898
  31. shear: 0.602
  32. perspective: 0.0
  33. flipud: 0.00856
  34. fliplr: 0.5
  35. mosaic: 1.0
  36. mixup: 0.243
  37. copy_paste: 0.0