datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MetaMathQAView the project page:
https://meta-math.github.io/
see our paper at https://arxiv.org/abs/2309.12284
Note
All MetaMathQA data are augmented from the training sets of GSM8K and MATH.
None of the augmented data is from the testing set.
You can check the original_question in meta-math/MetaMathQA, each item is from the GSM8K or MATH train set.
Model Details
MetaMath-Mistral-7B is fully fine-tuned on the MetaMathQA datasets and based on the powerful Mistral-7B model. It is… See the full description on the dataset page: https://huggingface.co/datasets/meta-math/MetaMathQA.MetaMathQA-40Karxiv.org/abs/2309.12284
View the project page:
https://meta-math.github.io/
GSM8K_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.qwen3.5-metamathqaMetaMathQA-R1
oumi-ai/MetaMathQA-R1
MetaMathQA-R1 is a text dataset designed to train Conversational Language Models with DeepSeek-R1 level reasoning.
Prompts were augmented from GSM8K and MATH training sets with responses directly from DeepSeek-R1.
MetaMathQA-R1 was used to train MiniMath-R1-1.5B, which achieves 44.4% accuracy on MMLU-Pro-Math, the highest of any model with <=1.5B parameters.
Curated by: Oumi AI using Oumi inference on Parasail
Language(s) (NLP): English
License:… See the full description on the dataset page: https://huggingface.co/datasets/oumi-ai/MetaMathQA-R1.MetaMathQA_GSM8K_zh
Dataset
MetaMathQA_GSM8K_zh is a dataset for mathematical reasoning in Chinese,
question-answer pairs are translated from MetaMathQA (https://huggingface.co/datasets/meta-math/MetaMathQA) by GPT-3.5-Turbo with few-shot prompting.
The dataset consists of 231685 samples.
Citation
If you find the GSM8K_zh dataset useful for your projects/papers, please cite the following paper.
@article{yu2023metamath,
title={MetaMath: Bootstrap Your Own Mathematical Questions for Large… See the full description on the dataset page: https://huggingface.co/datasets/meta-math/MetaMathQA_GSM8K_zh.MetaMathQA
Meta Math Filtered
This is a combined and filtered (removed all the redundant rows) version of meta-math/MetaMathQA and meta-math/MetaMathQA-40K
Usage
from datasets import load_dataset
dataset = load_dataset("Sharathhebbar24/MetaMathQA", split="train")
details_abacusai__MetaMath-bagel-34b-v0.2-c1500
Dataset Card for Evaluation run of abacusai/MetaMath-bagel-34b-v0.2-c1500
Dataset automatically created during the evaluation run of model abacusai/MetaMath-bagel-34b-v0.2-c1500 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_abacusai__MetaMath-bagel-34b-v0.2-c1500.MetaMathFewshot
A few-shot version of the MetaMath (https://huggingface.co/datasets/meta-math/MetaMathQA) dataset.
Each entry is formatted with 'question' and 'answer' keys. The 'question' key has a random number of query-answer pairs between 0 and 4 inclusive, before a final target query; the expected answer to this is stored in the content of 'answer'.
MetaMathQA-math-500DAPO-Math-17k with the MATH-500 test split converted to the same parquet schema and prompt format.
MetaMath_DPO_FewShot
Dataset Card for "MetaMath_DPO_FewShot"
GSM8K \citep{cobbe2021training} is a dataset of diverse grade school maths word problems, which has been commonly adopted as a measure of the math and reasoning skills of LLMs.
The MetaMath dataset is an extension of the training set of GSM8K using data augmentation.
It is partitioned into queries and responses, where the query is a question involving mathematical calculation or reasoning, and the response is a logical series of steps and… See the full description on the dataset page: https://huggingface.co/datasets/abacusai/MetaMath_DPO_FewShot.details_abacusai__MetaMath-Bagel-DPO-34B
Dataset Card for Evaluation run of abacusai/MetaMath-Bagel-DPO-34B
Dataset automatically created during the evaluation run of model abacusai/MetaMath-Bagel-DPO-34B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_abacusai__MetaMath-Bagel-DPO-34B.details_PulsarAI__MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
Dataset Card for Evaluation run of PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp
Dataset Summary
Dataset automatically created during the evaluation run of model PulsarAI/MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_PulsarAI__MetaMath-OpenHermes-2.5-neural-chat-v3-3-Slerp.metamath-qwen2-math
Dataset Summary
Approximately 900k math problems, where each solution is formatted in a Chain of Thought (CoT) manner. The sources of the dataset range from metamath-qa https://huggingface.co/datasets/meta-math/MetaMathQA and https://huggingface.co/datasets/AI-MO/NuminaMath-CoT with only none-synthetic dataset only. We only use the prompts from metamath-qa and get response with Qwen2-math-72-instruct and rejection-sampling, the solution is filted based on the official evaluation… See the full description on the dataset page: https://huggingface.co/datasets/yingyingzhang/metamath-qwen2-math.details_meta-math__MetaMath-70B-V1.0
Dataset Card for Evaluation run of meta-math/MetaMath-70B-V1.0
Dataset Summary
Dataset automatically created during the evaluation run of model meta-math/MetaMath-70B-V1.0 on the Open LLM Leaderboard.
The dataset is composed of 64 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 2 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train"… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_meta-math__MetaMath-70B-V1.0.details_meta-math__MetaMath-Mistral-7B
Dataset Card for Evaluation run of meta-math/MetaMath-Mistral-7B
Dataset Summary
Dataset automatically created during the evaluation run of model meta-math/MetaMath-Mistral-7B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train"… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_meta-math__MetaMath-Mistral-7B.details_Q-bert__MetaMath-Cybertron
Dataset Card for Evaluation run of Q-bert/MetaMath-Cybertron
Dataset Summary
Dataset automatically created during the evaluation run of model Q-bert/MetaMath-Cybertron on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Q-bert__MetaMath-Cybertron.details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Ties
Dataset Card for Evaluation run of Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Ties
Dataset Summary
Dataset automatically created during the evaluation run of model Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Ties on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Ties.details_Weyaxi__MetaMath-una-cybertron-v2-bf16-Ties
Dataset Card for Evaluation run of Weyaxi/MetaMath-una-cybertron-v2-bf16-Ties
Dataset Summary
Dataset automatically created during the evaluation run of model Weyaxi/MetaMath-una-cybertron-v2-bf16-Ties on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Weyaxi__MetaMath-una-cybertron-v2-bf16-Ties.details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear
Dataset Card for Evaluation run of Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear
Dataset automatically created during the evaluation run of model Weyaxi/MetaMath-NeuralHermes-2.5-Mistral-7B-Linear on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_Weyaxi__MetaMath-NeuralHermes-2.5-Mistral-7B-Linear.GSM8K_Backwardarxiv.org/abs/2309.12284
View the project page:
https://meta-math.github.io/
details_CorticalStack__mistral-7b-metamathqa-sft
Dataset Card for Evaluation run of CorticalStack/mistral-7b-metamathqa-sft
Dataset automatically created during the evaluation run of model CorticalStack/mistral-7b-metamathqa-sft on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_CorticalStack__mistral-7b-metamathqa-sft.metamath_gsm8k
🚀 GSM8K training set
The original answer is "\n#### Value" and now is "\n#### Value\nThe answer is: Value", and the answer is cleaned, which is consistent with the answer format with "meta-math/MetaMathQA".
💻 Dataset Usage
Run the following command to load the data:
from datasets import load_dataset
dataset = load_dataset("shuyuej/metamath_gsm8k")
dataset = dataset['train']
print(dataset)
📝 Dataset modification codes
# coding=utf-8
import re
import… See the full description on the dataset page: https://huggingface.co/datasets/shuyuej/metamath_gsm8k.metamath_refined_step_sftmetamathqa-grouped-splitcotmath_metamathdetails_harshitv804__MetaMath-Mistral-2x7B
Dataset Card for Evaluation run of harshitv804/MetaMath-Mistral-2x7B
Dataset automatically created during the evaluation run of model harshitv804/MetaMath-Mistral-2x7B on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_harshitv804__MetaMath-Mistral-2x7B.MetaMathQAMetaMathQAView the project page:
https://meta-math.github.io/
see our paper at https://arxiv.org/abs/2309.12284
Note
All MetaMathQA data are augmented from the training sets of GSM8K and MATH.
None of the augmented data is from the testing set.
You can check the original_question in meta-math/MetaMathQA, each item is from the GSM8K or MATH train set.
Model Details
MetaMath-Mistral-7B is fully fine-tuned on the MetaMathQA datasets and based on the powerful Mistral-7B model. It is… See the full description on the dataset page: https://huggingface.co/datasets/agicorp/MetaMathQA.Vietnamese-395k-meta-math-MetaMathQA-gg-translated