OpenMathInstruct-1

OpenMathInstruct-1 is a math instruction tuning dataset with 1.8M problem-solution pairs generated using permissively licensed Mixtral-8x7B model. The problems are from GSM8K and MATH training subsets and the solutions are synthetically generated by allowing Mixtral model to use a mix of text reasoning and code blocks executed by Python interpreter. The dataset is split into train and validation subsets that we used in the ablations experiments. These two subsets… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathInstruct-1.

OpenMathInstruct-2

OpenMathInstruct-2 is a math instruction tuning dataset with 14M problem-solution pairs generated using the Llama3.1-405B-Instruct model. The training set problems of GSM8K and MATH are used for constructing the dataset in the following ways:

Solution augmentation: Generating chain-of-thought solutions for training set problems in GSM8K and MATH. Problem-Solution augmentation: Generating new problems, followed by solutions for these new problems.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathInstruct-2.

Dataset

This dataset was created by 张鉴鸾

Contents

OpenMathInstruct-1-1.8m-ja-askllm-v1

データセット kunishou/OpenMathInstruct-1-1.8m-ja に対して、 Ask-LLM 手法でスコア付けしたデータセットです。 元データセットのカラムに加え askllm_score というカラムが追加されており、ここに Ask-LLM のスコアが格納されています。 Ask-LLM でスコア付けに使用した LLM は Rakuten/RakutenAI-7B-instruct で、プロンプトは以下の通りです。 ### {data} ###

Does the previous paragraph demarcated within ### and ### contain informative signal for pre-training a large-language model? An informative datapoint should be well-formatted, contain some usable knowledge of the… See the full description on the dataset page: https://huggingface.co/datasets/geniacllm/OpenMathInstruct-1-1.8m-ja-askllm-v1.

marcuscedricridia/OpenMathInstruct-1-1000-processed dataset hosted on Hugging Face and contributed by the HF Datasets community

OpenMath GSM8K Masked

We release a masked version of the MATH solutions. This data can be used to aid synthetic generation of additional solutions for MATH dataset as it is much less likely to lead to inconsistent reasoning compared to using the original solutions directly. This dataset was used to construct OpenMathInstruct-1: a math instruction tuning dataset with 1.8M problem-solution pairs generated using permissively licensed Mixtral-8x7B model. For details of how the masked… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMath-MATH-masked.

gabrielmbmb/OpenMathInstruct-2-sampled dataset hosted on Hugging Face and contributed by the HF Datasets community

OpenMath GSM8K Masked

We release a masked version of the GSM8K solutions. This data can be used to aid synthetic generation of additional solutions for GSM8K dataset as it is much less likely to lead to inconsistent reasoning compared to using the original solutions directly. This dataset was used to construct OpenMathInstruct-1: a math instruction tuning dataset with 1.8M problem-solution pairs generated using permissively licensed Mixtral-8x7B model. For details of how the masked… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMath-GSM8K-masked.

5CD-AI/Vietnamese-nvidia-OpenMathInstruct-1-50k-gg-translated dataset hosted on Hugging Face and contributed by the HF Datasets community

HayatoHongo/OpenMathInstruct1-ja dataset hosted on Hugging Face and contributed by the HF Datasets community

Kendamarron/OpenMathInstruct-2-ja-CoT dataset hosted on Hugging Face and contributed by the HF Datasets community

kunishou/OpenMathInstruct-1-1.8m-jaをPhi-3で解き直したものです｡ 実際にPython scriptを実行し､答えがあっていたもののみをフィルタリングして掲載しています｡

生成コード

データセット情報

このデータセットは、Kendamarron/OpenMathInstruct-2-ja-CoTを、英語と日本語のペアを含めるよう、日本語の応答データを英語の応答データに翻訳しました。 翻訳後のデータをllm-as-a-judgeで翻訳品質を1〜5段階評価し、最高評価5のみをfilterして取得したものです。 その後、訓練データセットとテストデータセットに9:1で分割しました。

  引用データセット情報

"Kendamarron/OpenMathInstruct-2-ja-CoT": 訓練データセットのみ 15282件
Dataset: Dataset({ features: ['problem', 'generated_solution', 'expected_answer', 'problem_source', 'problem_ja', 'thought', 'output', 'evaluation', 'cot_output', 'system']… See the full description on the dataset page: https://huggingface.co/datasets/yasutoshi-lab/open-math-instruct-2-en-ja-cot.

以下のデータ源からランダムに抽出した日本語のテキストをもとに､Phi-3で作文したコーパスです｡ OpenMathInstruct-1-1.8m-ja

  コード

こちら

一部の計算には東京工業大学のスーパーコンピュータTSUBAME4.0を利用しました｡