Fine-tuning Models in Supervised Machine Learning

The chapter explores the process of fine-tuning models in supervised machine learning and its relationship to the workflow of Rag. It emphasizes the need for a gold standard dataset and metrics for performance measurement. The chapter also discusses the challenges of obtaining the necessary data for fine-tuning and the potential role of Fektara in creating a principle Rag setup.