AraBert Arabic Sentiment Analysis Model - Open Source and Free, with an Accuracy of 80.03% on the Evaluation Set

Home

Arabert Arabic Sentiment Analysis

Developed by PRAli22

Arabic sentiment analysis model fine-tuned on AraBERT, achieving 80.03% accuracy on the evaluation set

Text Classification

Transformers

ArabicOpen Source License:Apache-2.0 #Arabic Sentiment Analysis #High Accuracy #Fine-tuned AraBERT

Downloads 840

Release Time : 3/13/2024

Model Overview

This model is specialized for sentiment analysis of Arabic text, capable of identifying emotional tendencies in the text.

Model Features

High Accuracy

Achieves 80.03% accuracy on the evaluation set

Arabic Optimization

Specifically optimized for Arabic text

Lightweight Fine-tuning

Efficient fine-tuning based on a pre-trained model

Model Capabilities

Arabic Text Classification

Sentiment Analysis

Natural Language Processing

Use Cases

Social Media Analysis

Arabic Social Media Comment Sentiment Analysis

Analyze user sentiment tendencies in Arabic social media comments

Accurately identifies over 80% of sentiment tendencies

Customer Feedback Analysis

Arabic Customer Review Classification

Classify Arabic customer reviews as positive/negative

Training Loss	Epoch	Step	Validation Loss	Macro F1	Accuracy
No log	1.0	497	0.5337	0.6219	0.7967
0.6177	2.0	994	0.5327	0.6543	0.8003

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご

Arabert Arabic Sentiment Analysis

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 AraBert-Arabic-Sentiment-Analysis

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License