The metametric Python package offers a set of tools for quickly and easily defining and implementing evaluation metrics for a variety of structured prediction tasks in natural language processing (NLP) based on the framework presented in the following paper:
A Unified View of Evaluation Metrics for Structured Prediction. Yunmo Chen, William Gantt, Tongfei Chen, Aaron Steven White, and Benjamin Van Durme. EMNLP 2023.
The key features of the package include:
- A decorator for automatically defining and implementing a custom metric for an arbitrary
dataclass. - A collection of generic components for defining arbitrary new metrics based on the framework in the paper.
- Implementations of a number of metrics for common structured prediction tasks.
To install, run:
pip install metametricIf you use this codebase in your work, please cite the following paper:
@inproceedings{metametric,
title={A Unified View of Evaluation Metrics for Structured Prediction},
author={Yunmo Chen and William Gantt and Tongfei Chen and Aaron Steven White and Benjamin {Van Durme}},
booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
year={2023},
address={Singapore},
}