Dynamic-Classification

Code from the paper: Metric Learning for Dynamic Text Classification

Usage

First install the requirements in requirements.txt

• The distance folder contains the code for the euclidean and hyperbolic metrics.
• model.py file contains code for the RNN encoder and the Prototypical model.
• sampler.pt contains the code for creating episodes.

See train.py for an example on how to train a model.

Cite

@inproceedings{wohlwend-etal-2019-metric,
    title = "Metric Learning for Dynamic Text Classification",
    author = "Wohlwend, Jeremy  and
      Elenberg, Ethan R.  and
      Altschul, Sam  and
      Henry, Shawn  and
      Lei, Tao",
    booktitle = "Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-6116",
    doi = "10.18653/v1/D19-6116",
    pages = "143--152"
}