bottlneck_cnn_text_classification

This is a deep CNN architecture with bottleneck CNN for binary text classification. SentencePiece is used to split the text.

Getting Started

To get the summarizer to work one first has to install requiered libraries and run some preprocessings

Prerequisites

Besides Python 3.x and tensorflow 1.3 following libraries are additionally requiered, run the following commands in your shell

pip install numpy
pip install tqdm
pip install sentencepiece

The default for all following instructions is to have the project folder as cd.

First run the following commands

mkdir ./data
mkdir ./ckpt
mkdir ./log

Preprocess Data

To test the architecture for hatespeech on tweets, put hate-speech-and-offensive-language/data/labeled_data.csv from

https://github.com/t-davidson/hate-speech-and-offensive-language

into your ./data folder.

Then run the following code via

cd src/
python3 preprocess.py

Running the classification

To run the classification you can adapt the hyperparameters in hyperparameters.py Then execute

cd src/
python3 summarize.py