Dataset: Box and segment doesn't match

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Hi Everyone,
I have created Dataset of license plate of 2 and 4 wheeler vehicle and exported to my local machine to train yolov8 model.
when training got started i have receive error at the initial stage.
please find the error and let me which step I have missed out due to it is giving error

Error 1 :
train: Scanning D:\Pycharm_projects\SmartPark Tracker\Train_dataset\train\labels.cache… 71 images, 0 backgrounds, 0 corrupt: 100%|██████████| 71/71 [00:00<?, ?it/s]
WARNING Box and segment counts should be equal, but got len(segments) = 45, len(boxes) = 75. To resolve this only boxes will be used and all segments will be removed. To avoid this please supply either a detect or segment dataset, not a detect-segment mixed dataset.
Traceback (most recent call last):
Error 2 : File “C:\Users\gurwa\AppData\Local\Programs\Python\Python310\lib\multiprocessing\spawn.py”, line 134, in _check_not_importing_main
raise RuntimeError(‘’’
RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.

    This probably means that you are not using fork to start your
    child processes and you have forgotten to use the proper idiom
    in the main module:

        if __name__ == '__main__':
            freeze_support()
            ...

    The "freeze_support()" line can be omitted if the program
    is not going to be frozen to produce an executable.

Python Script :

from ultralytics import YOLO

# Load a model

model = YOLO(‘./YOLO_Weights/yolov8n.pt’) # load a pretrained model (recommended for training)

results = model.train(data=“D:\Pycharm_projects\SmartPark Tracker\Train_dataset\data.yaml”,epochs=25, imgsz=640)