Open-source hate_trained_1234567 model - Super practical for accurately detecting hate speech in tweets

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Hate Trained 1234567

Developed by marcolatella

A hate speech detection model fine-tuned on distilbert-base-uncased, trained on the tweet_eval dataset

Text Classification

Transformers

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

Downloads 15

Release Time : 3/2/2022

Model Overview

This model is specifically designed for detecting hate speech in social media texts, optimized based on the DistilBERT architecture, suitable for English text classification tasks

Model Features

Efficient and Lightweight

Based on the DistilBERT architecture, reducing model size while maintaining high performance

Hate Speech Detection

Specifically optimized for detecting hate speech in social media texts

Excellent Fine-tuning Performance

Achieves an F1 score of 0.775 on the tweet_eval dataset

Model Capabilities

English text classification

Hate speech recognition

Social media text analysis

Use Cases

Content Moderation

Social Media Content Filtering

Automatically detect and flag hate speech on social media platforms

Helps reduce harmful content on platforms

Research and Analysis

Hate Speech Research

Used to analyze patterns and trends of hate speech on social media

Training Loss	Epoch	Step	Validation Loss	F1
0.4835	1.0	563	0.4882	0.7534
0.3236	2.0	1126	0.5286	0.7590
0.2191	3.0	1689	0.6103	0.7717
0.1408	4.0	2252	0.7927	0.7751

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Hate Trained 1234567

Model Overview

Model Features

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🚀 hate_trained_1234567

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📚 Documentation

Model description

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Training and evaluation data

🔧 Technical Details

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