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# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# Hyperparameters for VOC finetuning
# python train.py --batch 64 --weights yolov5m.pt --data VOC.yaml --img 512 --epochs 50
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
# Hyperparameter Evolution Results
# Generations: 306
# P R mAP.5 mAP.5:.95 box obj cls
# Metrics: 0.6 0.936 0.896 0.684 0.0115 0.00805 0.00146
lr0: 0.0032
lrf: 0.12
momentum: 0.843
weight_decay: 0.00036
warmup_epochs: 2.0
warmup_momentum: 0.5
warmup_bias_lr: 0.05
box: 0.0296
cls: 0.243
cls_pw: 0.631
obj: 0.301
obj_pw: 0.911
iou_t: 0.2
anchor_t: 2.91
# anchors: 3.63
fl_gamma: 0.0
hsv_h: 0.0138
hsv_s: 0.664
hsv_v: 0.464
degrees: 0.373
translate: 0.245
scale: 0.898
shear: 0.602
perspective: 0.0
flipud: 0.00856
fliplr: 0.5
mosaic: 1.0
mixup: 0.243
copy_paste: 0.0
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