Fine-tuning large language models (LLMs) has emerged as a crucial technique to adapt these models for specific applications. Traditionally, fine-tuning relied on massive datasets. However, Data-Centric Fine-Tuning (DCFT) presents a novel strategy that shifts the focus from simply augmenting dataset size to enhancing data quality and relevance for t