metadata

license: apache-2.0
datasets:
  - gplsi/SocialTOX
language:
  - es
metrics:
  - accuracy
  - f1
  - precision
  - recall
base_model:
  - BSC-LT/roberta-base-bne
pipeline_tag: text-classification

🧠 Toxicity_model_RoBERTa-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, 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
max_seq_length: 512