This project implements a Bidirectional LSTM with Conditional Random Fields (BiLSTM-CRF) and Spacy for Named Entity Recognition (NER) tasks. The model is designed to identify and classify named entities in text, such as locations and seaweed species.
Model Architecture (BiLSTM-CRF)
Model Accuracy for each entity
- Python 3.7+
- TensorFlow 1.15.0
- Keras 2.2.4
- keras-contrib (for CRF layer)
You can install the required packages using:
pip install tensorflow==1.15.0 keras==2.2.4
pip install git+https://www.github.com/keras-team/keras-contrib.git