datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MathNet
Quick Start · Overview · Tasks · Comparison · Dataset Stats · Data Sources · Pipeline · Schema · License · Citation
This is the official MathNet v0. A larger version v1 will be uploaded soon (more countires, problems and richer metadata). Schema is stable but field values may be revised in v1.
Quick start
from datasets import load_dataset
# Default: all problems
ds = load_dataset("ShadenA/MathNet", split="train")
# Or a specific country / competition-body config… See the full description on the dataset page: https://huggingface.co/datasets/ShadenA/MathNet.orca-math-word-problems-200k
Dataset Card
This dataset contains ~200K grade school math word problems. All the answers in this dataset is generated using Azure GPT4-Turbo. Please refer to Orca-Math: Unlocking the potential of
SLMs in Grade School Math for details about the dataset construction.
Dataset Sources
Repository: microsoft/orca-math-word-problems-200k
Paper: Orca-Math: Unlocking the potential of
SLMs in Grade School Math
Direct Use
This dataset has been designed to… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k.MathVista
Dataset Card for MathVista
Dataset Description
Paper Information
Dataset Examples
Leaderboard
Dataset Usage
Data Downloading
Data Format
Data Visualization
Data Source
Automatic Evaluation
License
Citation
Dataset Description
MathVista is a consolidated Mathematical reasoning benchmark within Visual contexts. It consists of three newly created datasets, IQTest, FunctionQA, and PaperQA, which address the missing visual domains and are tailored to evaluate logical… See the full description on the dataset page: https://huggingface.co/datasets/AI4Math/MathVista.AutoMathText🎉 This work, introducing the AutoMathText dataset and the AutoDS method, has been accepted to The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025 Findings)! 🎉
AutoMathText
AutoMathText is an extensive and carefully curated dataset encompassing around 200 GB of mathematical texts. It's a compilation sourced from a diverse range of platforms including various websites, arXiv, and GitHub (OpenWebMath, RedPajama, Algebraic Stack). This rich repository… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/AutoMathText.MathVision
Measuring Multimodal Mathematical Reasoning with the MATH-Vision Dataset
[💻 Github] [🌐 Homepage] [📊 Main Leaderboard ] [📊 Open Source Leaderboard ] [🌿 Wild Leaderboard ] [🔍 Visualization] [📖 Paper]
🌿 NEW: MATH-Vision-Wild
MATH-Vision-Wild is a photographic, real-world variant of MATH-Vision. The same testmini problems are physically captured on printed paper, iPads, laptops, and projectors under varying lighting and angles — the conditions VLMs actually… See the full description on the dataset page: https://huggingface.co/datasets/MathLLMs/MathVision.math-dataset-measuring-mathematical-problem-solvingTo cite the dataset please reference it as
@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}
}
TemplateGSM
TemplateMath: Template-based Data Generation (TDG)
This is the official repository for the paper "Training and Evaluating Language Models with Template-based Data Generation", published at the ICLR 2025 DATA-FM Workshop.
Our work introduces Template-based Data Generation (TDG), a scalable paradigm to address the critical data bottleneck in training LLMs for complex reasoning tasks. We use TDG to create TemplateGSM, a massive dataset designed to unlock the next level of… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/TemplateGSM.Big-Math-RL-Verified
Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
Big-Math is the largest open-source dataset of high-quality mathematical problems, curated specifically for reinforcement learning (RL) training in language models. With over 250,000 rigorously filtered and verified problems, Big-Math bridges the gap between quality and quantity, establishing a robust foundation for advancing reasoning in LLMs.
Request Early Access to Private… See the full description on the dataset page: https://huggingface.co/datasets/SynthLabsAI/Big-Math-RL-Verified.MathVerse
Dataset Card for MathVerse
Dataset Description
Paper Information
Dataset Examples
Leaderboard
Citation
Dataset Description
The capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solvingremain insufficiently evaluated and understood. We investigate current benchmarks to incorporate excessive visual content within textual questions, which potentially assist MLLMs in deducing answers without truly interpreting the input diagrams.
To… See the full description on the dataset page: https://huggingface.co/datasets/AI4Math/MathVerse.MathX-5M
Modotte
Note : This datset is the part of a lineup MathX by Modotte you can get a lots of datasets on this same linup main focus is to provide very high quality datasets for model training
and finetuning
This dataset is curated from high-quality public sources and enhanced with synthetic data from both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the most refined and extensive corpora… See the full description on the dataset page: https://huggingface.co/datasets/Modotte/MathX-5M.We-Math
Dataset Card for WE-MATH (ACL 2025)
GitHub | Paper | Website
Inspired by human-like mathematical reasoning, we introduce We-Math, the first benchmark specifically designed to explore the problem-solving principles beyond the end-to-end performance. We meticulously collect and categorize 6.5K visual math problems, spanning 67 hierarchical knowledge concepts and 5 layers of knowledge granularity.
Citation
If you find the content of this project helpful, please cite our… See the full description on the dataset page: https://huggingface.co/datasets/We-Math/We-Math.math12kThis dataset was converted from https://github.com/openai/prm800k using the following script.
import json
import os
from datasets import Dataset, DatasetDict
def generate_data(data_path: str):
with open(data_path, "r", encoding="utf-8") as f:
for line in f:
data = json.loads(line)
yield {
"problem": data["problem"],
"answer": data["answer"],
}
def main():
trainset = Dataset.from_generator(generate_data… See the full description on the dataset page: https://huggingface.co/datasets/hiyouga/math12k.math_qaThe MathQA dataset without needing to run remote code, so it is compatible with datasets >= 4.0.0.
StackMathQA
StackMathQA
StackMathQA: A Curated Collection of 2 Million Mathematical Questions and Answers Sourced from Stack Exchange
StackMathQA is a meticulously curated collection of 2 million mathematical questions and answers, sourced from various Stack Exchange sites. This repository is designed to serve as a comprehensive resource for researchers, educators, and enthusiasts in the field of mathematics and AI research.
Configs
configs:
- config_name: stackmathqa1600k… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/StackMathQA.MathNet
Quick Start · Overview · Tasks · Comparison · Dataset Stats · Data Sources· Pipeline · Schema · License · Citation
This is the official MathNet v0. A larger version v1 will be uploaded soon (more countires, problems and richer metadata). Schema is stable but field values may be revised in v1.
Quick start
from datasets import load_dataset
# Default: all problems
ds = load_dataset("ShadenA/MathNet", split="train")
# Or a specific country / competition-body config
arg… See the full description on the dataset page: https://huggingface.co/datasets/knowurknottty/MathNet.MathVerse-lmmseval
Dataset Card for MathVerse
This is the version for lmms-eval. This shares the same data with the official dataset.
Dataset Description
Paper Information
Dataset Examples
Leaderboard
Citation
Dataset Description
The capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving remain insufficiently evaluated and understood. We investigate current benchmarks to incorporate excessive visual content within textual questions, which potentially… See the full description on the dataset page: https://huggingface.co/datasets/CaraJ/MathVerse-lmmseval.MathReal
Dataset Card for MathReal
Dataset Description
Paper Information
Dataset Examples
Leaderboard
Citation
Dataset Description
The MathReal dataset is designed to evaluate the performance of Multi-modal Large Language Models (MLLMs)on real-world K-12 mathematical questions. It consists of 2,000 high-quality math problems, each represented as an image captured in authentic educational contexts. The dataset includes various types of questions, such as multiple-choice… See the full description on the dataset page: https://huggingface.co/datasets/junfeng0288/MathReal.Lumina-Math-Foundations-1B
Lumina-Math-Foundations-1B
Lumina-Math-Foundations-1B is an industrial-scale foundational mathematical reasoning dataset in Indonesian,
Dataset Summary
Language: Indonesian (id) with LaTeX mathematical formulas.
Scale: 1 Billion Synthetic High-Fidelity Mathematical Reasoning instances.---
Data Schema & Field Breakdown
Field Name
Type
Description
problem
string
100% pure human natural language problem statement with standard LaTeX math… See the full description on the dataset page: https://huggingface.co/datasets/cloverx-id/Lumina-Math-Foundations-1B.GSM8KInstruct_ParallelGSM8K_zh
Dataset
GSM8K_zh is a dataset for mathematical reasoning in Chinese, question-answer pairs are translated from GSM8K (https://github.com/openai/grade-school-math/tree/master) by GPT-3.5-Turbo with few-shot prompting.
The dataset consists of 7473 training samples and 1319 testing samples. The former is for supervised fine-tuning, while the latter is for evaluation.
for training samples, question_zh and answer_zh are question and answer keys, respectively;
for testing samples, only… See the full description on the dataset page: https://huggingface.co/datasets/meta-math/GSM8K_zh.MM-MathInstruct
MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning
Repo: https://github.com/mathllm/MathCoder
Paper: https://huggingface.co/papers/2505.10557
Introduction
We introduce MathCoder-VL, a series of open-source large multimodal models (LMMs) specifically tailored for general math problem-solving. We also introduce FigCodifier-8B, an image-to-code model.
Base Model
Ours
Mini-InternVL-Chat-2B-V1-5
MathCoder-VL-2B… See the full description on the dataset page: https://huggingface.co/datasets/MathLLMs/MM-MathInstruct.MathX-20M
Modotte
Note : This datset is the part of a lineup MathX by Modotte you can get a lots of datasets on this same linup main focus is to provide very high quality datasets for model training
and finetuning
This dataset is curated from high-quality public sources and enhanced with synthetic data from both closed and open-source models. It serves as a strong foundation for instruction-based model tuning and fine-tuning, offering one of the most refined and extensive corpora… See the full description on the dataset page: https://huggingface.co/datasets/Modotte/MathX-20M.math-code-science-deepseek-r1-en
R1 Dataset Collection
Aggregated high-quality English prompts and model-generated responses from DeepSeek R1 and DeepSeek R1-0528.
Dataset Summary
The R1 Dataset Collection combines multiple public DeepSeek-generated instruction-response corpora into a single, cleaned, English-only JSONL file. Each example consists of a <|user|> prompt and a <|assistant|> response in one "text" field. This release includes:
~21,000 examples from the DeepSeek-R1-0528 Distilled Custom… See the full description on the dataset page: https://huggingface.co/datasets/Hugodonotexit/math-code-science-deepseek-r1-en.MathCanvas-Instruct
MathCanvas-Instruct Dataset
🚀 Data Usage
from datasets import load_dataset
dataset = load_dataset("shiwk24/MathCanvas-Instruct")
print(dataset)
📖 Overview
MathCanvas-Instruct is a high-quality, fine-tuning dataset with 219K examples of interleaved visual-textual reasoning paths. It is the core component for the second phase of the [MathCanvas] framework: Strategic Visual-Aided Reasoning.… See the full description on the dataset page: https://huggingface.co/datasets/shiwk24/MathCanvas-Instruct.Math-RL-Tasks
Ulam AI Math RL Tasks
Forty original, verifier-backed mathematical reasoning tasks packaged as ten
independent RL environments. The collection spans advanced graduate exercises,
research-style exact computation and structural generalization problems in
algebraic geometry, arithmetic geometry, combinatorics, topology, probability
and spectral analysis.
Each suite pairs a runnable rl_env/ with a preserved blind_run/ by
GPT-5.6 Sol Pro. The model name describes the evaluation actor… See the full description on the dataset page: https://huggingface.co/datasets/ulamai/Math-RL-Tasks.VoiceAssistant-Eval
🔥 VoiceAssistant-Eval: Benchmarking AI Assistants across Listening, Speaking, and Viewing
[🌐 Homepage]
[🔮 Visualization]
[💻 Github]
[📖 Paper]
[📊 Leaderboard ]
[📊 Detailed Leaderboard ]
[📊 Roleplay Leaderboard ]
🚀 Data Usage
from datasets import load_dataset
for split in ['listening_general', 'listening_music', 'listening_sound', 'listening_speech',
'speaking_assistant', 'speaking_emotion', 'speaking_instruction_following'… See the full description on the dataset page: https://huggingface.co/datasets/MathLLMs/VoiceAssistant-Eval.gretel-math-gsm8k-v1
Image generated by DALL-E. See prompt for more details
gretelai/synthetic-gsm8k-reflection-405b
This dataset is a synthetically generated version inspired by the GSM8K dataset, created entirely using Gretel Navigator with meta-llama/Meta-Llama-3.1-405B as the agent LLM. It contains Grade School-level reasoning tasks with step-by-step reflections and solutions, focusing on multi-step reasoning problems.
Key Features for AI Developers:
Synthetic Data Generation:… See the full description on the dataset page: https://huggingface.co/datasets/gretelai/gretel-math-gsm8k-v1.math-reasoning-ift-pairs
Reasoning-IFT Pairs (Math Domain)
Paper | Project Page
This dataset provides the largest set of IFT and Reasoning answers pairs for a set of math queries (cf: general-domain).
It is based on the Llama-Nemotron-Post-Training dataset, an extensive and high-quality collection of math instruction fine-tuning data.
We curated 150k queries from the math subset of Llama-Nemotron-Post-Training, which covers multiple domains of math questions.For each query, we used… See the full description on the dataset page: https://huggingface.co/datasets/Scale-or-Reason/math-reasoning-ift-pairs.simple-math
Simple Math: 2+2=4 -1=3 (LoLo: Learning Only Logical Operations)
Just like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models.
It was created with very simple code that is in the repo, if you add more complex operations and so.. please share the code :D thank you
Current Code Version: 20240127.fblgit (A modification over @win10 for progressive and DPO operation)
Does it Works?
34BEAGLES… See the full description on the dataset page: https://huggingface.co/datasets/fblgit/simple-math.math-reasoning-sft-100k
Math Reasoning SFT (100K)
100,000 math problems with detailed step-by-step solutions — ready for supervised fine-tuning of math reasoning models.
Dataset Description
100,000 problems across 8 mathematical categories and 3 difficulty levels:
Categories
Category
Examples
Topics
word_problems
~23,100
Rate/time/distance, work problems, mixture, meeting/catch-up
arithmetic
~15,400
Percentages, profit/loss, ratios
geometry
~15,400
Area… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/math-reasoning-sft-100k.