The current FourCastNet training uses modified hyperparameters from the paper "FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators", the paper can be accessed here
The goal is to tune hyperparameters for Modified FourCastNet in Modulus to achieve convergence in fewer timesteps. The current model is trained on 6 months of data and is used to predict a 1-week long prediction for validation.