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