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Podcast: Arxiv Papers
Episode: [QA] Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism
Description:
This paper proposes adaptive batch size schedules for large-scale language model training, enhancing efficiency and generalization, while outperforming traditional methods in pretraining models, particularly smaller ones.
https://arxiv.org/abs//2412.21124
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