fcollova / fasttext

Unofficial implementation of the paper "Bag of Tricks for Efficient Text Classification" by Joulin et al.

FastText

Unofficial implementation of the paper Bag of Tricks for Efficient Text Classification by Joulin et al.

Prerequisites

FastText requires Python 3 with Keras installed.

Obtain the Yelp Dataset from here and place yelp_academic_dataset_review.json in the base directory.

Training

Train the model using the following command:

./train.py

It generates data.csv which represents the model's embedding space of the validation set. It is obtained by removing the last layer of the model and using t-SNE for the dimensionality reduction.

index.html implements a D3 visualisation to view the embedding space. You need to run a local web server because browsers don't allow file accesses:

python -m http.server 8000

Now point your browser to: localhost:8000.

License

FastText is licensed under the terms of the Apache v2.0 license.

Authors

• Ihor Kroosh
• Tim Nieradzik