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--- |
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tags: |
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- text-classification |
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- toxicity |
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- Twitter |
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base_model: cardiffnlp/twitter-roberta-base-sentiment |
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widget: |
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- text: I love AutoTrain |
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license: mit |
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language: |
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- es |
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pipeline_tag: text-classification |
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library_name: transformers |
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datasets: |
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- bgonzalezbustamante/toxicity-protests-ES |
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--- |
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# Fined-tuned roBERTa for Toxicity Classification in Spanish |
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This is a fine-tuned roBERTa model trained using as a base model Twitter-roBERTa base-sized for Sentiment Analysis, which was trained on ~58M tweets. The dataset for training this model is a gold standard for protest events for toxicity and incivility in Spanish. |
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The dataset comprises ~5M data points from three Latin American protest events: (a) protests against the coronavirus and judicial reform measures in Argentina during August 2020; (b) protests against education budget cuts in Brazil in May 2019; and (c) the social outburst in Chile stemming from protests against the underground fare hike in October 2019. We are focusing on interactions in Spanish to elaborate a gold standard for digital interactions in this language, therefore, we prioritise Argentinian and Chilean data. |
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- [GitHub repository](https://github.com/training-datalab/gold-standard-toxicity). |
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- [Dataset on Zenodo](https://zenodo.org/doi/10.5281/zenodo.12574288). |
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- [Reference paper](https://arxiv.org/abs/2409.09741) |
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**Labels: NONTOXIC and TOXIC.** |
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**We suggest using [bert-spanish-toxicity](https://huggingface.co/bgonzalezbustamante/bert-spanish-toxicity) or [ft-xlm-roberta-toxicity](https://huggingface.co/bgonzalezbustamante/ft-xlm-roberta-toxicity) instead of this model.** |
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## Validation Metrics |
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- Accuracy: 0.790 |
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- Precision: 0.920 |
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- Recall: 0.657 |
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- F1-Score: 0.767 |
