This model card documents the demo paper "PEACE: Providing Explanations and Analysis for Combating Hate Expressions" accepted at the 27th European Conference on Artificial Intelligence: https://www.ecai2024.eu/calls/demos.
The Model
This model is a hate speech detector fine-tuned specifically for detecting implicit hate speech. It is based on the paper "PEACE: Providing Explanations and Analysis for Combating Hate Expressions" by Greta Damo, Nicolás Benjamín Ocampo, Elena Cabrio, and Serena Villata, presented at the 27th European Conference on Artificial Intelligence.
Training Parameters and Experimental Info
The model was trained using the ISHate dataset, focusing on implicit data. Training parameters included:
- Batch size: 32
- Weight decay: 0.01
- Epochs: 4
- Learning rate: 2e-5
For detailed information on the training process, please refer to the model's paper.
Datasets
The model was trained on the ISHate dataset, specifically the training part of the dataset which focuses on implicit hate speech.
Evaluation Results
The model's performance was evaluated using standard metrics, including F1 score and accuracy. For comprehensive evaluation results, refer to the linked paper.
Authors: