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in the context of evaluating LLMs, what do these scores technically mean? (alien.top)

submitted 11 months ago by Life_Ask2806@alien.top to c/localllama@poweruser.forum

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when we benchmark different LLMs on different datasets (MMLU, TriviaQA, MATH, HellaSwag, etc.), what are the the signification of these scores? the accuracy? another metric? how can i know the metrics of each dataset (MMLU, etc.)

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[–] RexRecruiting@alien.top 1 points 11 months ago (1 children)

My understanding is basically, they are data sets the model is compared to. Say you wanted to see how well you knew math. You took a math test, and then your answers were compared to a key of answers...

Some of my notes about those benchmarks

GSM8K is a dataset of 8.5K high-quality linguistically diverse grade school math word problems created by human problem writers

HellaSwag is the large language model benchmark for commonsense reasoning.

Truful QA: is a benchmark to measure whether a language model is truthful in generating answers to questions.

Winogrande - Common sense reasoning

[–] shaman-warrior@alien.top 1 points 11 months ago

Everything is common sense reasoning, we need better definitions

[–] ThisGonBHard@alien.top 1 points 11 months ago

Nothing, sadly.

Models are trained on the questions, to improve performance, making the tests moot.