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  ## πŸ“Œ Model Description
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- This model is a fine-tuned version** of `RoBERTa-base-bne`, specifically trained to classify the toxicity level of **Spanish-language user comments on news articles**. It distinguishes between three categories:
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  - **Non-toxic**
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  - **Slightly toxic**
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  ## πŸ“‚ Training Data
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- The model was fine-tuned on the **[SocialTOX dataset](https://huggingface.co/datasets/gplsi/SocialTOX)**, a collection of Spanish-language comments annotated for varying levels of toxicity. These comments come from news platforms and represent real-world scenarios of online discourse. In this case, a Binary classifier was developed, where the classes \textit{Slightly toxic} and \textit{Toxic} were merged into a single \textit{Toxic} category.
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  ## πŸ“Œ Model Description
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+ This model is a fine-tuned version of `RoBERTa-base-bne`, specifically trained to classify the toxicity level of **Spanish-language user comments on news articles**. It distinguishes between three categories:
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  - **Non-toxic**
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  - **Slightly toxic**
 
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  ## πŸ“‚ Training Data
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+ The model was fine-tuned on the **[SocialTOX dataset](https://huggingface.co/datasets/gplsi/SocialTOX)**, a collection of Spanish-language comments annotated for varying levels of toxicity. These comments come from news platforms and represent real-world scenarios of online discourse. In this case, a multiclass classifier was developed.
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