Methods to Evaluate Foundation Model Performance

While choosing the right FM for our applications is important, assessing its effectiveness by analyzing its strengths and weaknesses is equally crucial. Large language models are prone to generating hallucinated, toxic, or biased responses, which adds to the evaluation stage’s importance.

Evaluating foundation models ensures they are aligned with desired outcomes regarding accuracy, relevance, and efficiency. For example, a model used in customer support needs to provide accurate responses promptly, while a language model may require a review of fluency and coherence. AWS Bedrock provides tools and services to simplify and enhance evaluation processes, supporting regular monitoring to keep models aligned with organizational needs and user expectations.

Methods to evaluate foundational models

Following are some of the methods we can use to evaluate foundational models:

Human evaluation

In human evaluation, we bring in human judgment to analyze a foundation model in the ...