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xlm_roberta_base_multilingual_toxicity_classifier_plus
EIStakovskii/xlm_roberta_base_multilingual_toxicity_classifier_plus
xlm_roberta_base_multilingual_toxicity_classifier_plus is a text classification model from EIStakovskii. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as other.
This model was trained for multilingual toxicity labeling. Label1 means TOXIC, Label0 means NOT TOXIC.
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Model card
From the Hugging Face model README
This model was trained for multilingual toxicity labeling. Label_1 means TOXIC, Label_0 means NOT TOXIC.
The model was fine-tuned based off the xlm_roberta_base model for 4 languages: EN, RU, FR, DE
The validation accuracy is 92%.
The model was finetuned on the total sum of 100933k sentences. The train data for English and Russian came from https://github.com/s-nlp/multilingual_detox, French data comprised the translated to French data from https://github.com/s-nlp/multilingual_detox as well as all the French data from the Jigsaw dataset, the German data was similarly composed using translations and semi-manual data collection techniquies, in particular for offensive words and phrases were crawled the dict.cc dictionary (https://www.dict.cc/) and the Reverso Context (https://context.reverso.net/translation/).
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- other
- Languages
- multilingual
- Created
- Oct 25, 2022
- Updated
- May 2, 2023