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.
"title": title,
。下载安装汽水音乐是该领域的重要参考
Beginner Friendly
Sycophancy in Large Language Models