PyTorch-Elmo-BiLSTMCRF

PyTorch Implementation of the BiLSTM-CRF model as described in https://guillaumegenthial.github.io/.

This model builds upon that by adding including ELMO embeddings as a feature representation option. (For more detail about ELMo, please see the publication "Deep contextualized word representations")

For the Keras implementation (without ELMO) please refer to this link.

Usage

1. Requirements:
   a. Packages: Anaconda, Pytorch, AllenNLP (if on linux and using elmo)
   b. Data: Train, valid and test datasets in CoNLL 2003 NER format.
   c. Glove 300B embeddings (If not using Elmo)

2. Configure Settings:
   a. Change settings in model/config.py
   b. Main settings to change: File directories, model hyperparameters etc.

3. Build Data:
   a. Run build_data.py
   i. Builds embedding dictionary, text file of words, chars tags, as well as idx to word and idx to char mapping for the model to read

4. Train Model:
   a. Run train.py

5. Test Model:
   a. Run test.py
   b. Evaluates on test set. Also accepts other arguments to predict on custom string