README.md

---
dataset_info:
  features:
  - name: id
    dtype: int64
  - name: problem
    dtype: string
  - name: solution
    dtype: string
  - name: answer
    dtype: string
  - name: problem_type
    dtype: string
  - name: question_type
    dtype: string
  - name: problem_is_valid
    dtype: string
  - name: solution_is_valid
    dtype: string
  - name: source
    dtype: string
  - name: synthetic
    dtype: bool
  splits:
  - name: train
    num_bytes: 128094696
    num_examples: 75580
  download_size: 57263310
  dataset_size: 128094696
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

This dataset is a curated subset of the original [AI-MO/NuminaMath-1.5](https://huggingface.co/datasets/AI-MO/NuminaMath-1.5) dataset. It has been filtered to create a high-quality corpus of human-authored, validated math problems suitable for training and evaluating language models on mathematical reasoning.

## Filtering Criteria

This subset was created by applying the following conditions to the 'train' split of the original dataset:


  * **Valid Problems:** Includes only problems marked as complete and well-formed.
  * **Human-Authored Content Only:** Excludes all synthetically generated problems.
  * **Cleaned Text:** Removed all entries containing URLs, file links, or markdown images.


## Data Fields

The data fields are inherited from the original dataset and include:

  * `problem`: The mathematical problem statement in LaTeX.
  * `solution`: A step-by-step, Chain-of-Thought style solution.
  * `answer`: The final answer to the problem.
  * `problem_type`: The mathematical domain (e.g., Algebra, Geometry).
  * `question_type`: The style of the problem (e.g., proof, math-word-problem).
  * `source`: The origin of the problem (e.g., olympiads, cn\_k12).