Muon outperforms every optimizer we tested (AdamW, SOAP, MAGMA). Multi-epoch training matters. And following work by Kotha et al. , scaling to large parameter counts works if you pair it with aggressive regularization -- weight decay up to 16x standard, plus dropout. The baseline sits at ~2.4x data efficiency against modded-nanogpt.
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I always tell people, don’t drop out.