Evaluation

Overview

Evaluating the performance of LLMs is critical in natural language processing. One key tool for this evaluation is the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics, which are primarily used to assess the quality of text generated by LLMs.

LLMs like GPT-2 often engage in tasks like text completion or summarization. The effectiveness of the generated texts can’t be effectively measured solely by human judgment due to scalability and consistency issues. For instance, run the code below to generate text based on the following prompt. Think about what score could be assigned to it, and try coming up with a standardized metric to score different texts.