Codesota · Natural Language Processing · Language Modeling · MATH 500Tasks/Natural Language Processing/Language Modeling
Language Modeling · benchmark dataset · EN

MATH 500.

The MATH 500 dataset is an academic math benchmark focusing on probability, algebra, and trigonometry. It is designed to evaluate language models on their ability to solve mathematical problems. The dataset includes questions from various subjects such as Algebra, Intermediate Algebra, Precalculus, Geometry, Number Theory, Prealgebra, and Counting & Probability, across different difficulty levels (1 to 5).

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§ 01 · Leaderboard

Best published scores.

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§ 06 · Contribute

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this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

Submit a result Read submission guide
What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies