license:apache-2.0 size_categories:1M<n<10M format:json modality:text library:datasets library:dask library:mlcroissant region:us
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license: apache-2.0
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# Lean4 Formal Mathematics Reward Model Training Dataset

## Dataset Overview
This is a specialized dataset designed for training reward models, aimed at evaluating the quality of translations from natural language mathematical problems to Lean4 formal mathematics code. The dataset contains pairs of natural language mathematical statements and their corresponding Lean4 implementations, along with quality status annotations.

## Data Format
Each entry in the dataset contains the following fields:

1. **Natural Language Statement** (`nl_statement`): 
   - Mathematical problems or theorems described in natural language

2. **Lean4 Code Implementation** (`lean_code`):
   - Corresponding Lean4 formal mathematics code
   - Contains:
     - Required import statements
     - Definitions
     - Theorem statements

3. **Quality Status** (`accept`/`reject`):
   - Indicates the quality of code implementation
   - `accept`: Valid and successfully compilable Lean4 code
   - `reject`: Invalid or incomplete implementation

## Applications
This dataset is primarily used for:

- Training reward models to evaluate the quality of natural language to formal mathematics translations
- Optimizing large language models for mathematical formalization tasks

## Usage
Reward Model Training:
- Utilize accept/reject labels as quality indicators
- Model training can be based on features such as code length and structural complexity

## Contact
For questions about the dataset, please contact:

Email: jiaoyang2002@sjtu.edu.cn
