distilbert-base-uncased Open-Source Hate Speech Detection Model - Free Deployment for Accurate Identification of Inappropriate Speech

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Distilbert Base Uncased Hate Speech Offensive Train 8 9

Developed by SetFit

Hate speech detection model fine-tuned based on distilbert-base-uncased

Text Classification

Transformers

Open Source License:Apache-2.0 #Hate speech detection #Text classification #Lightweight BERT

Downloads 17

Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of distilbert-base-uncased for hate speech detection tasks, used to identify hateful and offensive content in text.

Model Features

Lightweight model

Based on the DistilBERT architecture, smaller and faster than standard BERT models while maintaining good performance

Hate speech detection

Specifically optimized for hate speech and offensive content detection tasks

Model Capabilities

Text classification

Hate speech recognition

Offensive content detection

Use Cases

Content moderation

Social media content filtering

Automatically detect and filter hate speech and offensive content on social media

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1068	1.0	5	1.1545	0.0
1.0494	2.0	10	1.1971	0.0
1.0612	3.0	15	1.2164	0.0
0.9517	4.0	20	1.2545	0.0
0.8874	5.0	25	1.2699	0.0
0.8598	6.0	30	1.2835	0.0
0.7006	7.0	35	1.3139	0.0
0.5969	8.0	40	1.3116	0.2
0.4769	9.0	45	1.3124	0.4
0.4352	10.0	50	1.3541	0.4
0.3231	11.0	55	1.3919	0.4

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Distilbert Base Uncased Hate Speech Offensive Train 8 9

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 distilbert-base-uncased__hate_speech_offensive__train-8-9

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