Character Level CNNs in Keras

This repository contains Keras implementations for two Character-level Convolutional Neural Networks for text classification on AG's News Topic Classification Dataset.

The following models have been implemented:

1. Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. NIPS 2015
2. Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush. Character-Aware Neural Language Models. AAAI 2016

Kim's CharCNN (a standard time-delay neural network) was originally part of an end-to-end trained pipeline for language modelling, but has been adapted for text classification.

Usage

1. Install dependencies:

$ pip install -r requirements.txt

2. Specify the training and testing data sources and model hyperparameters in the config.json file.

3. Run the main.py file as below:

$ python main.py --model [model_name]

Replace [model_name] with either zhang or kim to run the desired model.

Results

Coming soon.