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--- |
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base_model: BenjaminOcampo/model-bert__trained-in-ishate__seed-0 |
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datasets: |
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- ISHate |
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language: |
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- en |
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library_name: transformers |
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license: bsl-1.0 |
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metrics: |
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- f1 |
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- accuracy |
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tags: |
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- hate-speech-detection |
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- implicit-hate-speech |
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--- |
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This model card documents the demo paper "PEACE: Providing Explanations and |
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Analysis for Combating Hate Expressions" accepted at the 27th European |
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Conference on Artificial Intelligence: https://www.ecai2024.eu/calls/demos. |
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# The Model |
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This model is a hate speech detector fine-tuned specifically for detecting |
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implicit hate speech. It is based on the paper "PEACE: Providing Explanations |
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and Analysis for Combating Hate Expressions" by Greta Damo, Nicolás Benjamín |
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Ocampo, Elena Cabrio, and Serena Villata, presented at the 27th European |
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Conference on Artificial Intelligence. |
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# Training Parameters and Experimental Info |
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The model was trained using the ISHate dataset, focusing on implicit data. |
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Training parameters included: |
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- Batch size: 32 |
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- Weight decay: 0.01 |
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- Epochs: 4 |
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- Learning rate: 2e-5 |
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For detailed information on the training process, please refer to the [model's |
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paper](https://aclanthology.org/2023.findings-emnlp.441/). |
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# Datasets |
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The model was trained on the [ISHate dataset](https://huggingface.co/datasets/BenjaminOcampo/ISHate), specifically |
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the training part of the dataset which focuses on implicit hate speech. |
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# Evaluation Results |
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The model's performance was evaluated using standard metrics, including F1 score |
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and accuracy. For comprehensive evaluation results, refer to the linked paper. |
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Authors: |
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- [Greta Damo](https://grexit-d.github.io/damo.greta.github.io/) |
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- [Nicolás Benjamín Ocampo](https://www.nicolasbenjaminocampo.com/) |
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- [Elena Cabrio](https://www-sop.inria.fr/members/Elena.Cabrio/) |
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- [Serena Villata](https://webusers.i3s.unice.fr/~villata/Home.html) |
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