from ultralytics import YOLO

#base model
model = YOLO("yolov8m.pt")  #for better accuracy


model.train(
    data="data.yaml",       
    epochs=45,                # increased to allow better convergence
    patience=20,               # early stopping if no val improvement
    imgsz=640,                 # image size FOR ACCURACY
    batch=8,                 
    conf=0.25,                 # initial THRESHOLD
    name="detector",
    augment=True,              # enables data augmentation
    auto_augment='randaugment',# advanced augmentation
    lr0=0.001,                 # initial learning rate
    cos_lr=True,               # cosine learning rate schedule (smoother training)
    save=True,                 
    save_period=10,            # save weights every 10 epochs
)