datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MATH-500
Dataset Card for MATH-500
This dataset contains a subset of 500 problems from the MATH benchmark that OpenAI created in their Let's Verify Step by Step paper. See their GitHub repo for the source file: https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#math-splits
math-500math500
Dataset Card for MATH-500
This dataset contains a subset of 500 problems from the MATH benchmark that OpenAI created in their Let's Verify Step by Step paper. See their GitHub repo for the source file: https://github.com/openai/prm800k/tree/main?tab=readme-ov-file#math-splits
math500math500MATH500https://github.com/openai/prm800k/blob/main/prm800k/math_splits/test.jsonl
MATH-500MATH-500 test set with the remaining 12000 examples in train.
import datasets
# https://github.com/volcengine/verl/blob/30911f133aa300ae9d8e341dba8e63192335705e/verl/utils/reward_score/math.py
from math_utils import last_boxed_only_string, remove_boxed
math = datasets.load_dataset('DigitalLearningGmbH/MATH-lighteval', 'default')
math500 = datasets.load_dataset('HuggingFaceH4/MATH-500')
# convert math to math500 format
def map_to_500(example):
return {
'problem':… See the full description on the dataset page: https://huggingface.co/datasets/ricdomolm/MATH-500.math-500_Qwen3-30B-A3B_moe_patternsmath500MATH-500Eval-MATH500math500math_full_minus_math500
MATH (minus MATH-500)
This dataset is derived from the original MATH dataset by Hendrycks et al.
(qwedsacf/competition_math) with all problems from the MATH-500 benchmark set removed.
Construction
Source: 12,500 problems from the MATH dataset by Hendrycks et al. (qwedsacf/competition_math)
Benchmark held out: 500 problems from the MATH-500 dataset (HuggingFaceH4/MATH-500)
Matching criterion: exact match on the problem field (see… See the full description on the dataset page: https://huggingface.co/datasets/rasbt/math_full_minus_math500.MATH-500-multilingual
MATH-500 Multilingual Problem Set 🌍➗
A multilingual subset from OpenAI's MATH benchmark. Perfect for testing math skills across languages, this dataset includes same problems in English, French, Italian, Turkish and Spanish.
🌐 Available Languages
English 🇬🇧
French 🇫🇷
Italian 🇮🇹
Turkish 🇹🇷
Spanish 🇪🇸
📂 Source & Attribution
Original Dataset: Sourced from HuggingFaceH4/MATH-500.
🚀 Quick Start
Load the dataset… See the full description on the dataset page: https://huggingface.co/datasets/bezir/MATH-500-multilingual.MATH500_with_Llama_3.1_8B_Instruct_v1
MATH-500 with Llama-3.1-8B-Instruct
This dataset contains 500 mathematical reasoning problems from the MATH benchmark with 100 candidate responses generated by Llama-3.1-8B-Instruct for each problem. Each response has been evaluated for correctness using a mixture of GPT-4o-mini and procedural Python code to robustly parse different answer formats, and scored by multiple reward models (scalar values) and LM judges (boolean verdicts).
Dataset Structure
Split: Single… See the full description on the dataset page: https://huggingface.co/datasets/hazyresearch/MATH500_with_Llama_3.1_8B_Instruct_v1.MATH500_with_Llama_3.1_70B_Instruct_v1
MATH-500 with Llama-3.1-70B-Instruct
This dataset contains 500 mathematical reasoning problems from the MATH benchmark with 100 candidate responses generated by Llama-3.1-70B-Instruct for each problem. Each response has been evaluated for correctness using a mixture of GPT-4o-mini and procedural Python code to robustly parse different answer formats, and scored by multiple reward models (scalar values) and LM judges (boolean verdicts).
Dataset Structure
Split: Single… See the full description on the dataset page: https://huggingface.co/datasets/hazyresearch/MATH500_with_Llama_3.1_70B_Instruct_v1.math-500_deepseek-moe-16b-chat_moe_patternsR-HORIZON-Math500
R-HORIZON
How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?
📃 Paper • 🌐 Project Page • 🤗 Dataset
R-HORIZON is a novel method designed to stimulate long-horizon reasoning behaviors in Large Reasoning Models (LRMs) through query composition. We transform isolated problems into complex multi-step reasoning scenarios, revealing that even the most advanced LRMs suffer significant performance degradation when facing interdependent problems that span… See the full description on the dataset page: https://huggingface.co/datasets/meituan-longcat/R-HORIZON-Math500.math-500-th
Math-500-th
A Thai translation of MATH-500: the 500-problem subset of the MATH benchmark used
in OpenAI's Let's Verify Step by Step. Every row corresponds 1:1, in order, to a
row of the English original, so the Thai and English scores of a model are directly
comparable.
Source and licence
Original benchmark
hendrycks/math — MIT
500-problem subset
openai/prm800k — MIT
File we translated from
HuggingFaceH4/MATH-500
This dataset
MIT, see LICENSE… See the full description on the dataset page: https://huggingface.co/datasets/iapp/math-500-th.R-HORIZON-Math500MATH-500_with_Llama_3.1_8B_Instruct_v1Qwen2.5-1.5B-Instruct-uPRM-70B-T80-math500-best_of_n-completionsDeepseek-MATH500-Testmath500-cot-experiment
MATH-500 Chain of Thought Experiment Dataset
This dataset contains the results of an experiment testing different prompting strategies (standard, chain of thought, and gibberish chain of thought) on the MATH-500 benchmark using the Llama-3.2-1B-Instruct model.
Dataset Structure
The dataset is split into three parts:
standard: Direct prompting with no reasoning steps (500 examples)
cot: Chain of thought prompting with structured reasoning (500 examples)
gibberish:… See the full description on the dataset page: https://huggingface.co/datasets/codelion/math500-cot-experiment.MATH-500-Russian
Карточка датасета MATH-500-Russian
Перевод датасета HuggingFaceH4/MATH-500 на русский язык,
был выполнен моделью qwen2.5:32b через
скрипты EvilFreelancer/datasets-translator.
Данный набор данных содержит подмножество из 500 задач из теста MATH, который OpenAI создал для статьи Let's Verify
Step by Step и переведённых на русский язык.
Подробности в их репозиторий на GitHub.
Mistral-MATH500-Testmath500-floatExtracted 316 examples with plain‐decimal answers from the original dataset loaded by datasets.load_dataset("HuggingFaceH4/MATH-500", split="test"). The processing code demonstrates in the notebook file.
Llama-3.2-1B-Instruct-uPRM-32B-T80-math500-best_of_n-completionsmath-500_deepseek_moe_16b_token_patternsLlama-3.2-1B-Instruct-uPRM-70B-T80-math500-best_of_n-completions