Maximef/Yologo

1lr0: 0.01  # initial learning rate (SGD=1E-2, Adam=1E-3)2lrf: 0.1  # final OneCycleLR learning rate (lr0 * lrf)3momentum: 0.937  # SGD momentum/Adam beta14weight_decay: 0.0005  # optimizer weight decay 5e-45warmup_epochs: 3.0  # warmup epochs (fractions ok)6warmup_momentum: 0.8  # warmup initial momentum7warmup_bias_lr: 0.1  # warmup initial bias lr8box: 0.05  # box loss gain9cls: 0.3  # cls loss gain10cls_pw: 1.0  # cls BCELoss positive_weight11obj: 0.7  # obj loss gain (scale with pixels)12obj_pw: 1.0  # obj BCELoss positive_weight13iou_t: 0.20  # IoU training threshold14anchor_t: 4.0  # anchor-multiple threshold15# anchors: 3  # anchors per output layer (0 to ignore)16fl_gamma: 0.0  # focal loss gamma (efficientDet default gamma=1.5)17hsv_h: 0.015  # image HSV-Hue augmentation (fraction)18hsv_s: 0.7  # image HSV-Saturation augmentation (fraction)19hsv_v: 0.4  # image HSV-Value augmentation (fraction)20degrees: 0.0  # image rotation (+/- deg)21translate: 0.2  # image translation (+/- fraction)22scale: 0.5  # image scale (+/- gain)23shear: 0.0  # image shear (+/- deg)24perspective: 0.0  # image perspective (+/- fraction), range 0-0.00125flipud: 0.0  # image flip up-down (probability)26fliplr: 0.5  # image flip left-right (probability)27mosaic: 1.0  # image mosaic (probability)28mixup: 0.0  # image mixup (probability)29copy_paste: 0.0  # image copy paste (probability)30paste_in: 0.0  # image copy paste (probability), use 0 for faster training31loss_ota: 1 # use ComputeLossOTA, use 0 for faster training