In training LLMs, SNR indicates the importance and effectiveness of each layer's contribution to the model's performance. High SNR layers offer significant improvements, while low SNR layers add minimal value and can introduce unnecessary complexity. Focusing on high SNR layers optimizes training efficiency and effectiveness.
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