# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
# Hyperparameters for VOC training
# python train.py --batch 128 --weights yolov5m6.pt --data VOC.yaml --epochs 50 --img 512 --hyp hyp.scratch-med.yaml --evolve
# See Hyperparameter Evolution tutorial for details https://github.com/ultralytics/yolov5#tutorials

# YOLOv5 Hyperparameter Evolution Results
# Best generation: 319
# Last generation: 434
#    metrics/precision,       metrics/recall,      metrics/mAP_0.5, metrics/mAP_0.5:0.95,         val/box_loss,         val/obj_loss,         val/cls_loss
#              0.86236,              0.86184,              0.91274,              0.72647,            0.0077056,            0.0042449,            0.0013846

lr0: 0.0033
lrf: 0.15184
momentum: 0.74747
weight_decay: 0.00025
warmup_epochs: 3.4278
warmup_momentum: 0.59032
warmup_bias_lr: 0.18742
box: 0.02
cls: 0.21563
cls_pw: 0.5
obj: 0.50843
obj_pw: 0.6729
iou_t: 0.2
anchor_t: 3.4172
fl_gamma: 0.0
hsv_h: 0.01032
hsv_s: 0.5562
hsv_v: 0.28255
degrees: 0.0
translate: 0.04575
scale: 0.73711
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
mosaic: 0.87158
mixup: 0.04294
copy_paste: 0.0
anchors: 3.3556