Improving Evaluation of Low Resource Models

The chapter focuses on enhancing the evaluation process of Language Model models (LLMs) by discussing custom benchmarks, specific task evaluations, and the importance of trained evaluators. It delves into evolving techniques for evaluating LM models, addressing biases and the challenges of human ratings. The conversation also highlights the role of prompt engineering and automated techniques in improving prompts for a positive user experience.