Skip to content

Code for the EMNLP 2024 paper "Mathador-LM: A Dynamic Benchmark for Mathematical Reasoning on LLMs".

License

Notifications You must be signed in to change notification settings

IST-DASLab/Mathador-LM

Repository files navigation

Mathador-LM: A Dynamic Benchmark for Mathematical Reasoning on Large Language Models

Environment Setup

  1. conda create --name mathador python=3.11 -y
  2. conda activate mathador
  3. pip install -r requirements.txt
  4. Get your personal API key for any of the following providers: OpenAI, TogetherAI, Anthropic.
  5. Open eval.yaml and configure which models to evaluate. We provide examples for all three model providers.

Usage

For convenience, we attach mathador-10000.jsonl dataset that we used for some runs. If you would like to generate a new instance of the dataset, please configure generate_dataset.yaml and run:

python generate_dataset.py generate_dataset.yaml

To run Mathador-LM benchmark, please specify your desired parameters in eval.yaml and run:

TOGETHER_API_KEY=<your_key> python eval.py eval.yaml

If you would like to override arguments from eval.yaml directly from command-line, please use:

TOGETHER_API_KEY=<your_key> python eval.py eval.yaml shots=20

The result of the evaluation will be saved in results.csv.

About

Code for the EMNLP 2024 paper "Mathador-LM: A Dynamic Benchmark for Mathematical Reasoning on LLMs".

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages