See my deep learning projects on GitHub.
Our paper, "Riding the Polar Express to Convergence," studies Muon optimizers for GPT-2 Small, comparing Polar Express and Newton-Schulz variants and showing how deployment scope (full vs VO/FFN) and hyperparameters affect stability, learning-rate ranges, and loss. Read the paper here.