Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs

This study analyzes fine-tuning strategies for small LLMs, revealing that larger batch sizes with lower learning rates enhance performance. Early-stage training dynamics serve as reliable indicators for final outcomes. These findings offer practical insights for optimizing LLM fine-tuning with limited resources.

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Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs

Training Dataset used in different phases