metametric 0.2.0

A Unified View of Evaluation Metrics for Structured Prediction

metametric

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 metametric

If 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},
}