| # MATH | |
| ## Paper | |
| Measuring Mathematical Problem Solving With the MATH Dataset | |
| https://arxiv.org/abs/2103.03874 | |
| Many intellectual endeavors require mathematical problem solving, but this skill remains beyond the capabilities of computers. To measure this ability in machine learning models, we introduce MATH, a new dataset of 12,500 challenging competition mathematics problems. Each problem in MATH has a full step-by-step solution which can be used to teach models to generate answer derivations and explanations. | |
| NOTE: This task corresponds to the MATH (`hendrycks_math`) implementation at https://github.com/EleutherAI/lm-evaluation-harness/tree/master . For the variant which uses the custom 4-shot prompt in the Minerva paper (https://arxiv.org/abs/2206.14858), and SymPy answer checking as done by Minerva, see `lm_eval/tasks/minerva_math`. | |
| Homepage: https://github.com/hendrycks/math | |
| ## Citation | |
| ``` | |
| @article{hendrycksmath2021, | |
| title={Measuring Mathematical Problem Solving With the MATH Dataset}, | |
| author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt}, | |
| journal={NeurIPS}, | |
| year={2021} | |
| } | |
| ``` | |
| ### Groups and Tasks | |
| #### Groups | |
| - `hendrycks_math`: the MATH benchmark from Hendrycks et al. 0- or few-shot. | |
| #### Tasks | |
| - `hendrycks_math_algebra` | |
| - `hendrycks_math_counting_and_prob` | |
| - `hendrycks_math_geometry` | |
| - `hendrycks_math_intermediate_algebra` | |
| - `hendrycks_math_num_theory` | |
| - `hendrycks_math_prealgebra` | |
| - `hendrycks_math_precalc` | |
| ### Checklist | |
| The checklist is the following: | |
| For adding novel benchmarks/datasets to the library: | |
| * [x] Is the task an existing benchmark in the literature? | |
| * [x] Have you referenced the original paper that introduced the task? | |
| * [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test? | |
| * Answer extraction code is taken from the original MATH benchmark paper's repository. | |
| If other tasks on this dataset are already supported: | |
| * [x] Is the "Main" variant of this task clearly denoted? | |
| * [x] Have you provided a short sentence in a README on what each new variant adds / evaluates? | |
| * [x] Have you noted which, if any, published evaluation setups are matched by this variant? | |