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.
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