LLM evaluations
A set of metrics and benchmarks for assessing the performance of large language models (LLMs).
Plain English Explanation
A set of metrics and benchmarks for assessing the performance of large language models (LLMs). At a high level, LLM evaluations: - Help researchers identify areas where LLMs need improvement. - Are useful in comparing different LLMs and identifying the best LLM for a particular task. - Help ensure that LLMs are safe and ethical to use. See Large language models (LLMs) in Machine Learning Crash Course for more information.
How is it used?
Practitioners refer to llm evaluations when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.