---
license: apache-2.0
language:
- es
metrics:
- f1
- accuracy
- precision
- recall
base_model:
- PlanTL-GOB-ES/roberta-base-bne
pipeline_tag: text-classification
library_name: transformers
datasets:
- gplsi/SocialTOX
---

# 🧠 Toxicity_model_RoBERTa-base-bne– Spanish Toxicity Classifier Multiclass (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 three categories:

- **Non-toxic**
- **Slightly 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 multiclass classifier was developed. 

---

## Training hyperparameters
- epochs: 7
- learning_rate: 1.51E-06
- Adam_epsilon: 2.80E-08
- weight_decay: 3.88E-12
- batch_size: 16
- max_seq_length: 512