English(EN) How Does Local Landscape Geometry Evolve in Language Model Pre-Training?

新研究探讨语言模型预训练动态并提出调优策略

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

一篇新研究论文从局部景观几何的角度分析了语言模型的预训练动态。该研究确定了两个不同的阶段：第一阶段，学习率过高时，尖锐度会导致不稳定，需要学习率预热；第二阶段，梯度噪声尺度决定了景观。该研究提出了一个动态批次大小调度器，在训练后期增加批次大小，为优化大规模预训练提供了可行的策略。 AI

影响为优化语言模型预训练的效率和稳定性提供了新见解。

排序理由该集群包含一篇研究论文，详细介绍了语言模型预训练的新发现和拟议方法。[lever_c_demoted from research: ic=1 ai=1.0]

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Newsworthiness bucket: Tool; 该集群包含一篇研究论文，详细介绍了语言模型预训练的新发现和拟议方法。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.AI TIER_1 English(EN) · Zhanpeng Zhou, Yuhan Sun, Bingrui Li, Jinbo Wang, Huaijin Wu, Lei Wu, Junchi Yan · 2026-10-01 04:00

语言模型预训练中的局部景观几何如何演变？

arXiv:2609.39767v1 Announce Type: cross Abstract: The scale and expense of pre-training language models make efficient hyperparameter tuning essential, yet a principled guidance is still missing. In this work, we analyze language model pre-training dynamics from a local landscape…