Deep-EOS PyTorch
Introduction
This is a pytorch implementation of "Deep-EOS: General-Purpose Neural Networks for Sentence Boundary Detection" (Schweter et al, 2019). Go here for the original Keras implementation: https://github.com/stefan-it/deep-eos
Currently only the LSTM and Bi-LSTM models are implemented.
The dataset download script and dataset creation methods are largely copied from Stefan Schweters repository.
Results
Test set
| Language | PyTorch LSTM | PyTorch Bi-LSTM | Original LSTM | Original Bi-LSTM | Original CNN |
|---|---|---|---|---|---|
| German | 0.9763 | 0.9763 | 0.9750 | 0.9760 | 0.9751 |
| English | 0.9862 | 0.9862 | 0.9861 | 0.9860 | 0.9858 |
| Bulgarian | 0.9893 | 0.9891 | 0.9922 | 0.9923 | 0.9919 |
| Bosnian | 0.9917 | 0.9919 | 0.9957 | 0.9959 | 0.9953 |
| Greek | 0.9958 | 0.9957 | 0.9967 | 0.9969 | 0.9963 |
| Croatian | 0.9921 | 0.9918 | 0.9946 | 0.9948 | 0.9943 |
| Macedonian | 0.9772 | 0.9786 | 0.9810 | 0.9811 | 0.9794 |
| Romanian | 0.9875 | 0.9874 | 0.9907 | 0.9906 | 0.9904 |
| Albanian | 0.9922 | 0.9920 | 0.9953 | 0.9949 | 0.9940 |
| Serbian | 0.9843 | 0.9838 | 0.9877 | 0.9877 | 0.9870 |
| Turkish | 0.9824 | 0.9829 | 0.9858 | 0.9854 | 0.9854 |
Download
The trained models can be downloaded in the releases section. The each model 7zip archive contains the best scoring model (on development data) out of 5 epochs, alongside with its corresponding vocabulary.
The datasets can be downloaded with the download_data.sh script from the original implementation.
To-Do
- Implementation:
- LSTM
- Bi-LSTM
- CNN
References
- S. Schweter and S. Ahmed, "Deep-EOS: General-Purpose Neural Networks for Sentence Boundary Detection” in Proceedings of the 15th Conference on Natural Language Processing (KONVENS), 2019.