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  1. # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
  2. # Hyperparameters for VOC training
  3. # python train.py --batch 128 --weights yolov5m6.pt --data VOC.yaml --epochs 50 --img 512 --hyp hyp.scratch-med.yaml --evolve
  4. # See Hyperparameter Evolution tutorial for details https://github.com/ultralytics/yolov5#tutorials
  5. # YOLOv5 Hyperparameter Evolution Results
  6. # Best generation: 467
  7. # Last generation: 996
  8. # metrics/precision, metrics/recall, metrics/mAP_0.5, metrics/mAP_0.5:0.95, val/box_loss, val/obj_loss, val/cls_loss
  9. # 0.87729, 0.85125, 0.91286, 0.72664, 0.0076739, 0.0042529, 0.0013865
  10. lr0: 0.00334
  11. lrf: 0.15135
  12. momentum: 0.74832
  13. weight_decay: 0.00025
  14. warmup_epochs: 3.3835
  15. warmup_momentum: 0.59462
  16. warmup_bias_lr: 0.18657
  17. box: 0.02
  18. cls: 0.21638
  19. cls_pw: 0.5
  20. obj: 0.51728
  21. obj_pw: 0.67198
  22. iou_t: 0.2
  23. anchor_t: 3.3744
  24. fl_gamma: 0.0
  25. hsv_h: 0.01041
  26. hsv_s: 0.54703
  27. hsv_v: 0.27739
  28. degrees: 0.0
  29. translate: 0.04591
  30. scale: 0.75544
  31. shear: 0.0
  32. perspective: 0.0
  33. flipud: 0.0
  34. fliplr: 0.5
  35. mosaic: 0.85834
  36. mixup: 0.04266
  37. copy_paste: 0.0
  38. anchors: 3.412