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---
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 |