s-nlp / roberta_toxicity_classifier

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Total runs: 135.6K
24-hour runs: 5.0K
7-day runs: 10.2K
30-day runs: -126.3K
Model's Last Updated: November 08 2024
text-classification

Introduction of roberta_toxicity_classifier

Model Details of roberta_toxicity_classifier

Toxicity Classification Model

This model is trained for toxicity classification task. The dataset used for training is the merge of the English parts of the three datasets by Jigsaw ( Jigsaw 2018 , Jigsaw 2019 , Jigsaw 2020 ), containing around 2 million examples. We split it into two parts and fine-tune a RoBERTa model ( RoBERTa: A Robustly Optimized BERT Pretraining Approach ) on it. The classifiers perform closely on the test set of the first Jigsaw competition, reaching the AUC-ROC of 0.98 and F1-score of 0.76.

How to use
from transformers import RobertaTokenizer, RobertaForSequenceClassification

# load tokenizer and model weights
tokenizer = RobertaTokenizer.from_pretrained('SkolkovoInstitute/roberta_toxicity_classifier')
model = RobertaForSequenceClassification.from_pretrained('SkolkovoInstitute/roberta_toxicity_classifier')

# prepare the input
batch = tokenizer.encode('you are amazing', return_tensors='pt')

# inference
model(batch)
Licensing Information

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License .

CC BY-NC-SA 4.0

Runs of s-nlp roberta_toxicity_classifier on huggingface.co

135.6K
Total runs
5.0K
24-hour runs
3.9K
3-day runs
10.2K
7-day runs
-126.3K
30-day runs

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roberta_toxicity_classifier install

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