Practical Efficiency of Muon for Pretraining
from Arxiv Papers Hosted by Igor Melnyk
Muon outperforms AdamW in expanding the Pareto frontier for compute-time tradeoff, enhancing data efficiency at large batch sizes while enabling economical training through effective hyperparameter transfer. https://arxiv.org/abs//2505.02222 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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