Fine-tuned DistilBERT for NSFW Inappropriate Text Classification
Model Description
DistilBERT is a transformer model that performs sentiment analysis. I fine-tuned the model on Reddit posts with the purpose of classifying not safe for work (NSFW) content, specifically text that is considered inappropriate and unprofessional. The model predicts 2 classes, which are NSFW or safe for work (SFW).
The model is a fine-tuned version of DistilBERT.
It was fine-tuned on 19604 Reddit posts pulled from the Comprehensive Abusiveness Detection Dataset.
How to Use
from transformers import pipeline
classifier = pipeline("sentiment-analysis", model="michellejieli/inappropriate_text_classifier")
classifier("I see you’ve set aside this special time to humiliate yourself in public.")
Output:
[{'label': 'NSFW', 'score': 0.9684491753578186}]
Contact
Please reach out to michelle.li851@duke.edu if you have any questions or feedback.
Reference
Hoyun Song, Soo Hyun Ryu, Huije Lee, and Jong Park. 2021. A Large-scale Comprehensive Abusiveness Detection Dataset with Multifaceted Labels from Reddit. In Proceedings of the 25th Conference on Computational Natural Language Learning, pages 552–561, Online. Association for Computational Linguistics.
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