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 methodology that shifts the focus from simply expanding dataset size to improving data quality and appropriatene