This repository contains a re-implementation of Mueller's et al., "Siamese Recurrent Architectures for Learning Sentence Similarity." (AAAI, 2019). For the technical details, please refer to the publication.
To train the classifier, execute similarity_estimator/training.py after modifying the hard-coded values (such as the training corpus filename) to your own specifications.
To evaluate the performance of a trained model, run the similarity_estimator/testing.py script. Again, adjust user-specific values as needed within the script itself.
This re-implementation was completed with personal use in mind and is, as such, not actively maintained. You are, however, very welcome to extend or adjust it according to your own needs, should you find it useful. Happy coding :) .
