A version represents a point-in-time snapshot of your dataset. By precisely tracking which images, preprocessing steps, and augmentation techniques were employed in each iteration of your model, you retain the capability to reproduce results and conduct scientific testing across different models and frameworks. This practice ensures confidence that any observed outcomes stem from model modifications rather than errors in the data pipeline.
