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Dehatebert Mono French

Developed by Hate-speech-CNERG
This model is designed for detecting hate speech in French, fine-tuned from a multilingual BERT model using a monolingual training setup.
Downloads 73
Release Time : 3/2/2022

Model Overview

A deep learning model for French hate speech detection, fine-tuned based on the multilingual BERT architecture and specifically optimized for French content.

Model Features

Monolingual Training Optimization
Specifically trained on French data to optimize hate speech detection performance in French.
BERT-based Architecture
Leverages the powerful language understanding capabilities of multilingual BERT through fine-tuning.
Academic Research Support
Based on research findings published in the ECML-PKDD 2020 conference paper.

Model Capabilities

French Text Classification
Hate Speech Recognition
Social Media Content Analysis

Use Cases

Content Moderation
Social Media Hate Speech Filtering
Automatically identifies and flags hate speech content in French social media.
Validation score of 0.692094
Online Community Management
Assists administrators in quickly identifying and addressing inappropriate remarks in French communities.
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