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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Document classification with Hierarchical Attention Networks in TensorFlow. WARNING: project is currently unmaintained, issues will probably not be addressed.
| Date | Stars |
|---|---|
| 2026-07-24 | 467 |
| 2026-07-25 | 467 |
| 2026-07-28 | 467 |
| 2026-07-30 | 467 |
| 2026-08-06 | 467 |
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growth rate 0.00%/day
# Deep Text Classifier Implementation of document classification model described in [Hierarchical Attention Networks for Document Classification (Yang et al., 2016)](https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf). ## 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 ``` 2. Download the English model for spaCy: ``` python -m spacy download en ``` 3. Get [Yelp review dataset](https://www.yelp.com/dataset_challenge) 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.
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:0e019cdd7820d358, topic:deep-learning, topic:tensorflow
matched fp:0e019cdd7820d358, topic:nlp