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Why Gradients Rapidly Increase Near the End of Training

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arxiv 2506.02285 v2 pith:FIIRWZ7E submitted 2025-06-02 cs.LG cs.AI

Why Gradients Rapidly Increase Near the End of Training

classification cs.LG cs.AI
keywords trainingincreasenearrapidlybehaviorcorrectiondecayduring
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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During long-duration Large Language Model (LLM) training runs the gradient norm increases rapidly near the end of training. In this short note, we show that this increase is due to an unintended interaction between weight decay, normalization layers, and the learning rate schedule. We propose a simple correction that fixes this behavior while also resulting in lower loss values throughout training.

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