Learn how to evaluate the performance of large language models using the ROUGE metric.


In the realm of natural language processing, evaluating the performance of LLMs is a critical aspect. One of the key tools for this evaluation is the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics. ROUGE is primarily used to assess the quality of text generation 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.

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