Hierarchical-attention-networks-pytorch and bert-han
These tools are **competitors**, as they both aim to implement the Hierarchical Attention Network (HAN) architecture for document classification, with "vietnh1009/Hierarchical-attention-networks-pytorch" additionally integrating the PyTorch deep learning framework and "Hazoom/bert-han" leveraging BERT, each offering distinct approaches to the same core task.
About Hierarchical-attention-networks-pytorch
vietnh1009/Hierarchical-attention-networks-pytorch
Hierarchical Attention Networks for document classification
Implements two-level attention mechanisms at word and sentence levels to capture document structure, with GloVe word embeddings (50-300d) initialized in the embedding layer rather than default random initialization. Built on PyTorch with early stopping regularization and TensorBoard integration for training visualization. Includes a web demo interface and pre-trained models evaluated across eight datasets (AG News, DBPedia, Yelp, Amazon, Yahoo Answers) with configurable batch size, learning rate, and embedding dimensions.
About bert-han
Hazoom/bert-han
Hierarchical-Attention-Network
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