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MSign: An Optimizer Preventing Training Instability in Large Language Models via Stable Rank Restoration
Training instability remains a critical challenge in large language model (LLM) pretraining, often manifesting as sudden gradient explosions that waste significant computational resources. We study training failures in a 5M-parameter NanoGPT model scaled via $μ$P, identifying two key phenomena prece
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