Exploring Fine-Tuning Challenges and Data Acquisition in Machine Learning

This chapter explores the fine-tuning process for machine learning models, focusing on experiences with the Dolly and Mistral models. It discusses the challenges of acquiring quality data, particularly from reluctant insurance companies, and highlights the use of public California Independent Medical Review data for model enhancement.