[r/ML] [P] Weight Norm Clipping Accelerates Grokking 18-66× | Zero Failures Across 300 Seeds | PDF in Repo

Summary

Independent researchers discovered that applying per-row L2 clipping on decoder weights dramatically accelerates "grokking" in AI models, achieving 18-66x speedups. This simple method, implemented in just five lines of code, also eliminated training failures across 300 seeds and requires no additional memory or weight decay. It offers a highly efficient and reliable way to improve model generalization.

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