How to create custom dataset. (MGN)

Hello, I have a question regarding the datasets used in Learning to Simulate, such as water-3d.

My goal is to build datasets for other types of liquids and train a MeshGraphNet (MGN) model that can predict the dynamics of those materials. I have tried different simulation engines (e.g., PhysX and MPM-based solvers), but the ground-truth data I generated is not ideal, and the trained models do not function properly.

One issue I noticed is that the value ranges of my dataset are very different from the original datasets.
For example:

The original datasets (e.g., water-3d) use values within the range 0.125–0.875

My simulated data has values ranging from 0 to 80

As a result, the predicted outputs of my model differ significantly from the ground truth.

If there are specific requirements or considerations when generating new datasets—such as:

whether the dataset needs to be normalized to a fixed value range,

recommended preprocessing steps,

or how the original ground-truth data (e.g., water-3d) was generated,

I would greatly appreciate any guidance or clarification.

Best regards.