datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MathSpatialMathSpatial
Do MLLMs Really Understand Space? A Mathematical Spatial Reasoning Evaluation
Submitted to ACM Multimedia 2026 — Dataset Track
Overview •
Key Findings •
Statistics •
Getting Started •
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Leaderboard
Overview
MathSpatial is a large-scale, open dataset ecosystem dedicated to mathematical spatial reasoning in Multimodal Large Language Models (MLLMs). It provides 10,000 problems with 26,000+ geometric diagrams, covering… See the full description on the dataset page: https://huggingface.co/datasets/shuolucs/MathSpatial.math_shepherd
Math-Shepherd Dataset
Summary
The Math-Shepherd dataset is a processed version of Math-Shepherd dataset, designed to train models using the TRL library for stepwise supervision tasks. It provides step-by-step solutions to mathematical problems, enabling models to learn and verify each step of a solution, thereby enhancing their reasoning capabilities.
Data Structure
Format: Standard
Type: Stepwise supervision
Columns:
"pompt": The problem statement.… See the full description on the dataset page: https://huggingface.co/datasets/trl-lib/math_shepherd.MathSpatialMathSpatial
Do MLLMs Really Understand Space? A Mathematical Spatial Reasoning Evaluation
Submitted to ACM Multimedia 2026 — Dataset Track
Overview •
Key Findings •
Statistics •
Getting Started •
Annotations •
Leaderboard
Overview
MathSpatial is a large-scale, open dataset ecosystem dedicated to mathematical spatial reasoning in Multimodal Large Language Models (MLLMs). It provides 10,000 problems with 26,000+ geometric diagrams… See the full description on the dataset page: https://huggingface.co/datasets/AnnieLKY/MathSpatial.math-sft-10B
Dataset: math-sft-10B
This dataset was uploaded from /mnt/yulan_pretrain/mount/data_final_train/math-sft-10B/no-curriculum/tmp.
Math-Shepherd
Dataset Card for Math-Shepherd
Project Page: Math-Shepherd
Paper: https://arxiv.org/pdf/2312.08935.pdf
Data Loading
from datasets import load_dataset
dataset = load_dataset("peiyi9979/Math-Shepherd")
Data Instance
Every instance consists of three data fields: "input," "label," and "task".
"input": problem + step-by-step solution, e.g.,
If Buzz bought a pizza with 78 slices at a restaurant and then decided to share it with the waiter in the ratio of 5:8, with… See the full description on the dataset page: https://huggingface.co/datasets/peiyi9979/Math-Shepherd.Maths-CollegeMaths-College
I am releasing a large Mathematics dataset in the instrution format.
This extensive dataset, comprising nearly one million instructions in JSON format, encapsulates a wide array of mathematical disciplines essential for a profound understanding of the subject.
This dataset is very useful to Researchers & Model developers.
Following Fields & sub Fields are covered:
Probability
Statistics
Liner Algebra
Algebra
Group Theory
Topology
Abstract Algebra
Graph Theory
Combinatorics… See the full description on the dataset page: https://huggingface.co/datasets/ajibawa-2023/Maths-College.math_stage2_hard_1Math-Step-DPO-10K
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
🖥️Code | 🤗Data | 📄Paper
This repo contains the Math-Step-DPO-10K dataset for our paper Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs, Step-DPO is a simple, effective, and data-efficient method for boosting the mathematical reasoning ability of LLMs. Notably, Step-DPO, when applied to Qwen2-72B-Instruct, achieves scores of 70.8% and 94.0% on the test sets of MATH and GSM8K… See the full description on the dataset page: https://huggingface.co/datasets/xinlai/Math-Step-DPO-10K.math_stratos_scale_judged_and_annotated_with_difficultyMaths_competition_questionsmath-story-problems
Math Story Problems Dataset
Dataset Description
This dataset contains mathematical word problems presented in multiple formats, from direct equations to complex story-based scenarios. It is designed for training and evaluating language models on mathematical reasoning tasks.
Dataset Structure
The dataset is split into three parts:
Train: 131,072 samples
Validation: 1,024 samples
Test: 3,072 samples
Features
{
"eq_qs": "string", # Equation… See the full description on the dataset page: https://huggingface.co/datasets/azminetoushikwasi/math-story-problems.Maths-Grade-SchoolMaths-Grade-School
I am releasing large Grade School level Mathematics datatset.
This extensive dataset, comprising nearly one million instructions in JSON format, encapsulates a diverse array of topics fundamental to building a strong mathematical foundation.
This dataset is in instruction format so that model developers, researchers etc. can easily use this dataset.
Following Fields & sub Fields are covered:
Calculus
Probability
Algebra
Liner Algebra
Trigonometry
Differential Equations… See the full description on the dataset page: https://huggingface.co/datasets/ajibawa-2023/Maths-Grade-School.math_syntMATH_SFTmath_stackexchange_qa
Math StackExchange Curated (Parquet, CC BY-SA 4.0)
This dataset is a curated collection of Math StackExchange (MSE) Q&A pairs packaged in Parquet format.Each sample contains a problem (title, question_body), its corresponding answer (answer_body), the original MSE tag string (tags), and a flag indicating whether the answer was accepted (accepted).
This dataset includes content derived from the Math StackExchange public data dump (CC BY-SA 4.0, © Stack Exchange Inc.).This derived… See the full description on the dataset page: https://huggingface.co/datasets/glopezas/math_stackexchange_qa.KlearReasoner-MathSub-30K
Dataset Summary
This dataset is a subset of the Klear-Reasoner Math RL dataset.The full dataset contains approximately 88K entries, while this release includes a 30K-entry subset.
The subset was obtained by filtering the outputs of DeepSeek-R1-0120. For each prompt, DeepSeek-R1-0120 generated 16 responses and we retained only the parts where the majority voting results matched the standard answers, in order to filter out the cases that the rule-based validator math_verify cannot… See the full description on the dataset page: https://huggingface.co/datasets/Kwai-Klear/KlearReasoner-MathSub-30K.arXiv-metadata-oai-snapshot-111math-source-forced-recovery-v2Maths-Grade-SchoolMaths-Grade-School
I am releasing large Grade School level Mathematics datatset.
This extensive dataset, comprising nearly one million instructions in JSON format, encapsulates a diverse array of topics fundamental to building a strong mathematical foundation.
This dataset is in instruction format so that model developers, researchers etc. can easily use this dataset.
Following Fields & sub Fields are covered:
Calculus
Probability
Algebra
Liner Algebra
Trigonometry
Differential Equations… See the full description on the dataset page: https://huggingface.co/datasets/pt-sk/Maths-Grade-School.Simple-MathSteps-90K
Introducing Simple-MathSteps-90K:
An open source dataset of 93,325 elementary math problems with step-by-step solutions and multiple choice answers. Designed to enhance mathematical reasoning in models ranging from 1B to 13B parameters.
Key Features
93,325 Math Problems: Generated by paraphrasing the AQuA-RAT dataset using Qwen3 4B Instruct 2507, with a focus on consistency and quality.
Detailed Step-by-Step Solutions: Clear reasoning that breaks down problems… See the full description on the dataset page: https://huggingface.co/datasets/Raymond-dev-546730/Simple-MathSteps-90K.maths-vision-task-splitssat-mathsMATH_SHEPHERD_DPO_FORMATmath_scalingmath-sft-solutions-no-cot
Math SFT Solutions No CoT
A cleaned mathematics supervised fine-tuning dataset containing:
instruction → solution pairs
mathematical proofs
derivations
olympiad-style solutions
theorem reasoning
stepwise mathematical explanations
detailed final solutions
This dataset was built specifically for mathematical supervised fine-tuning (SFT).
Unlike many reasoning datasets, this release removes explicit chain-of-thought tags and hidden thinking traces while preserving high-quality… See the full description on the dataset page: https://huggingface.co/datasets/kaushik-harsh-99/math-sft-solutions-no-cot.math-sft-solutions-no-cot-v3
Math SFT Solutions No CoT V3
Math SFT Solutions No CoT V3 is a large-scale mathematics supervised fine-tuning (SFT) dataset designed for instruction tuning and mathematical capability adaptation.
Version 3 substantially expands mathematical coverage while improving dataset quality through stronger filtering, cleaning, and supervision refinement.
Unlike reasoning-heavy datasets, this release focuses on clean instruction → response pairs without hidden chain-of-thought style… See the full description on the dataset page: https://huggingface.co/datasets/kaushik-harsh-99/math-sft-solutions-no-cot-v3.math-sft-solutions-no-cot-v4
Math SFT Solutions No CoT V4
Math SFT Solutions No CoT V4 is a large-scale mathematics supervised fine-tuning (SFT) dataset designed for instruction tuning and mathematical capability adaptation.
Version 4 expands dataset scale while improving supervision quality through stronger cleaning, deduplication, formatting refinement, and broader mathematical coverage.
Unlike reasoning-oriented datasets, this release focuses on direct instruction → response supervision and removes… See the full description on the dataset page: https://huggingface.co/datasets/kaushik-harsh-99/math-sft-solutions-no-cot-v4.math-speech-datasetMaths
Mathematics Dataset
This dataset code generates mathematical question and answer pairs, from a range
of question types at roughly school-level difficulty. This is designed to test
the mathematical learning and algebraic reasoning skills of learning models.
Original paper: Analysing Mathematical
Reasoning Abilities of Neural Models
(Saxton, Grefenstette, Hill, Kohli).
Example questions
Question: Solve -42*r + 27*c = -1167 and 130*r + 4*c = 372 for r.
Answer: 4… See the full description on the dataset page: https://huggingface.co/datasets/slifeisenjoy/Maths.math_stage1_8