tags:
- text-classification
- toxicity
- Twitter
base_model: cardiffnlp/twitter-roberta-base-sentiment
widget:
- text: I love AutoTrain
license: mit
language:
- es
pipeline_tag: text-classification
library_name: transformers
Fined-tuned roBERTa for Toxicity Classification in Spanish
This is a fine-tuned roBERTa-base model trained using as a base model Twitter-roBERTa-base for Sentiment Analysis, which was trained on ~58M tweets. The dataset used for training is a gold standard for protest events for toxicity and incivility in Spanish.
The dataset comprises ~5M data points from three Latin American protest events: (a) protests against the coronavirus and judicial reform measures in Argentina during August 2020; (b) protests against education budget cuts in Brazil in May 2019; and (c) the social outburst in Chile stemming from protests against the underground fare hike in October 2019. We are focusing on interactions in Spanish to elaborate a gold standard for digital interactions in this language, therefore, we prioritise Argentinian and Chilean data.
Labels: NONTOXIC and TOXIC.
Example of Classification
WIP
Validation Metrics
- Accuracy: 0.790
- Precision: 0.920
- Recall: 0.657
- F1-Score: 0.767