How deeply does LLMs in Production cover MMLU?

Tests applied knowledge through elementary-to-professional questions, extending beyond surface understanding without detailing question-by-question scoring.

MMLU

As explained in LLMs in Production

MMLU is a benchmark suite that evaluates broad language understanding, world knowledge, and problem-solving across subjects and difficulty levels.

MMLU tests whether a language model can apply knowledge and reasoning across subjects, rather than merely recognize surface-level language patterns. Its questions span history, mathematics, morality, and law, with difficulty ranging from elementary to advanced professional levels. section 4.2.2

MMLU is useful when evaluating:

World knowledge beyond narrow language-understanding tasks. section 4.2.2
Problem-solving and deeper application of language understanding. section 4.2.2
Performance across both general and professionally difficult questions. section 4.2.2

Running an evaluation

A model can be wrapped as a DeepEval language model, moved to CUDA when available, and evaluated with the MMLU benchmark and MMLUTask.

How LLMs in Production covers it

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Also explained in

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Introduction to Generative AI, Second EditionMMLU is a benchmark that evaluates knowledge and reasoning across multiple academic and professional subjects.

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Related concepts

benchmarkkind of · A benchmark is a defined task, dataset, workload, procedure, or reference measure used to assess or compare performance or capability under specified criteria or conditions.
Llamameasured by · Llama is a family of autoregressive large language models developed by Meta and released in multiple versions and sizes.
language modeluses · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
accuracymeasures · Accuracy is the degree to which an output, prediction, or measurement agrees with a correct or reference outcome under a specified criterion.
GLUE Benchmarkcontrasts with · The GLUE Benchmark is a standardized suite of natural-language-understanding tasks for evaluating language models across multiple linguistic domains.

This explainer was generated by Manning's knowledge graph from the text of LLMs in Production. The section links point to the parts of the book it draws on.