Take an image, add some text: you've got a meme. Internet memes are often harmless and sometimes hilarious. However, by using certain types of images, text, or combinations of each of these data modalities, the seemingly non-hateful meme becomes a multimodal type of hate speech, a hateful meme.
This repository is an implementation of the Hateful Memes detection competition where the goal is to build a binary classifier for detecting hateful memes over the internet using an annotated data set.
Competition details: https://www.drivendata.org/competitions/64/hateful-memes/
Create a new Python 3.7 virtual environment:
python3.7 -m venv .venv
Activate the virtual environment:
source .venv/bin/activate
Install dependencies:
pip install -r requirements.txt
Add the project directory to python PATH, in ~/.bashrc or ~/.zshrc:
export PYTHONPATH=/your/path/to/hateful-memes:$PYTHONPATH
Run black:
make black_check
The project is based on AllenNLP library as an infrastructure for training.
One should create a new config file or use one from the already existing config files inside training_configs and run the following command, for example:
python main_allennlp.py train training_configs/hateful_memes_bert.jsonnet --include-package src -s experiments/your_experiment