Autonlp-text-hateful-memes-36789092 Open Source Model - Free Detection of Hate Speech in Text

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Autonlp Text Hateful Memes 36789092

Developed by am4nsolanki

This is a binary classification model trained via AutoNLP for detecting hate speech content in text.

Text Classification

Transformers

English#Hate speech detection #Binary classification #High AUC score

Downloads 25

Release Time : 3/2/2022

Model Overview

This model is trained using the AutoNLP framework, specifically designed to identify potential hate speech or harmful content in text, suitable for scenarios like content moderation.

Model Features

Efficient Hate Speech Detection

Capable of quickly and accurately identifying hate speech content in text.

AutoNLP Training

Built using Hugging Face's AutoNLP automated training pipeline.

Lightweight Model

CO2 emissions of only 1.43 grams, environmentally friendly.

Model Capabilities

Text classification

Hate speech detection

Content moderation

Use Cases

Social media content moderation

Hate speech filtering

Automatically identifies and filters hate speech content on social media.

Accuracy 76.66%, F1 score 0.653

Online community management

Harmful content detection

Assists community administrators in identifying potentially harmful content.

Property	Details
Problem Type	Binary Classification
Model ID	36789092
CO2 Emissions (in grams)	1.4280361775467445

Metric	Value
Loss	0.5255328416824341
Accuracy	0.7666078777189889
Precision	0.6913123844731978
Recall	0.6192052980132451
AUC	0.7893359070795125
F1	0.6532751091703057

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Autonlp Text Hateful Memes 36789092

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Model Trained Using AutoNLP

📦 Model Information

📊 Validation Metrics

💻 Usage Examples

Basic Usage

Advanced Usage