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Small-scale proxies for large-scale Transformer training instabilities
The paper investigates training instabilities in large Transformer-based models and explores ways to reproduce and study these instabilities at smaller scales. It examines sources of instability, explores the impact of learning rate and other interventions, and studies cases where instabilities can be predicted.
https://arxiv.org/abs//2309.14322
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
The paper investigates training instabilities in large Transformer-based models and explores ways to reproduce and study these instabilities at smaller scales. It examines sources of instability, explores the impact of learning rate and other interventions, and studies cases where instabilities can be predicted.
https://arxiv.org/abs//2309.14322
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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