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custom_hyp.yaml 1.49 KiB
# Hyperparameters for trainning on spectrogram
lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
lrf: 0.1 # final OneCycleLR learning rate (lr0 * lrf)
momentum: 0.937 # SGD momentum/Adam beta1
weight_decay: 0.0005 # optimizer weight decay 5e-4
warmup_epochs: 3.0 # warmup epochs (fractions ok)
warmup_momentum: 0.8 # warmup initial momentum
warmup_bias_lr: 0.1 # warmup initial bias lr
box: 0.05 # box loss gain
cls: 0.3 # cls loss gain
cls_pw: 1.0 # cls BCELoss positive_weight
obj: 0.7 # obj loss gain (scale with pixels)
obj_pw: 1.0 # obj BCELoss positive_weight
iou_t: 0.20 # IoU training threshold
anchor_t: 4.0 # anchor-multiple threshold
# anchors: 3 # anchors per output layer (0 to ignore)
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
hsv_h: 0.01 # image HSV-Hue augmentation (fraction)
hsv_s: 0.1 # image HSV-Saturation augmentation (fraction)
hsv_v: 0.1 # image HSV-Value augmentation (fraction)
degrees: 0.0 # image rotation (+/- deg)
translate: 0.0 # image translation (+/- fraction)
scale: 0.0 # image scale (+/- gain)
shear: 0.0 # image shear (+/- deg)
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
flipud: 0.0 # image flip up-down (probability)
fliplr: 0.0 # image flip left-right (probability)
mosaic: 0.0 # image mosaic (probability)
mixup: 0.3 # image mixup (probability)
copy_paste: 0.1 # segment copy-paste (probability)
ToGray: 0.0 # image in Grayscale (probability)
GaussNoise: 0.0 # adding Gaussian/white noise (probability)