[Python] Yolov5 model capturing other objects other than the intended or desired object

I have a YOLO V5 m model for a dataset to detect a certain product but after training a dataset of a variety of pictures for the product in different cases and scenarios and various lighting conditions with no repetition for the cases, on 50 epochs and the Yolo v5 medium architecture and batch size of 16.

What I have noticed is that the model is dependent on the color features, meaning that the objects that are getting detected have colors yellow and its shades. I used the train.py that comes with the yolo github clone. What should I do to fix this problem?

The dataset used in training (approx 450 images) in google drive.

The product desired to be detected:





The other products that are detected:



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