gplsi/Toxicity_model_binary

🧠 ToxicitymodelRoBERTa-base-bne– Spanish Toxicity Classifier Binary (Fine-tuned)

📌 Model Description

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 two categories:

• —Non-toxic
• —Toxic

📂 Training Data

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.

Training hyperparameters

• —epochs: 10
• —learning_rate: 2.45e-6
• —beta1: 0.9
• —beta2: 0.95
• —Adam_epsilon: 1.00e-8
• —weight_decay: 0
• —batch_size: 16
• —maxseqlength: 512