Hierarchical Attention Networks Save

Document classification with Hierarchical Attention Networks in TensorFlow. WARNING: project is currently unmaintained, issues will probably not be addressed.

Project README

Deep Text Classifier

Implementation of document classification model described in Hierarchical Attention Networks for Document Classification (Yang et al., 2016).

How to run

  1. Create a virtual environment, activate it, and install requirements:
python3 -m venv env
source env/bin/activate
pip install -r requirements.txt
  1. Download the English model for spaCy:
python -m spacy download en
  1. Get Yelp review dataset and extract it in this directory.
python3 yelp_prepare.py dataset/review.json
python3 worker.py --mode=train --device=/gpu:0 --batch-size=30

Results

I am getting 65% accuracy on a dev set (16% of data) after 3 epochs. Results reported in the paper are 71% on Yelp'15. No systemic hyperparameter optimization was performed.

Open Source Agenda is not affiliated with "Hierarchical Attention Networks" Project. README Source: ematvey/hierarchical-attention-networks

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