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nreimers committed Jun 27, 2018
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Expand Up @@ -4,6 +4,7 @@ This repository contains a BiLSTM-CRF implementation that used for NLP Sequence

The architecture is described in our papers:
- [Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging](https://arxiv.org/abs/1707.09861)
- [Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches](https://arxiv.org/abs/1803.09578)
- [Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks](https://arxiv.org/abs/1707.06799).

The implementation is **highly configurable**, so you can tune the different hyperparameters easily. You can use it for **Single Task Learning** as well as different options for **Multi-Task Learning**. You can also use it for **Multilingual Learning** by using multilingual word embeddings.
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Install the requirements:
```
.env/bin/pip3 install -r requirements.txt
env/bin/pip3 install -r requirements.txt
```

If everything works well, you can run `python3 Train_POS.py` to train a deep POS-tagger for the POS-tagset from universal dependencies.
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