Implemented the paper "Hierarchical Attention Networks for Document Classification" by tensorflow https://www.aclweb.org/anthology/N16-1174.pdf
the Hierarchical Attention Network (HAN) that is designed to capture two basic insights about document structure. First, since documents have a hierarchical structure (words form sentences, sentences form a document), we likewise construct a document representation by first building representations of sentences and then aggregating those into a document representation. Second, it is observed that different words and sentences in a documents are differentially informative.
python 3.6 tensorflow 1.14.0
You can download the IMDB dataset from http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz
You can set the hyperparameters of the model in config.py then run the commond python train.py