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Arabart Finetuned Ar

Developed by ahmeddbahaa
A text summarization model fine-tuned on the Arabic summarization dataset xlsum based on the AraBART model
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Release Time : 4/4/2022

Model Overview

This model is designed for generating summaries of Arabic texts. It is obtained by fine-tuning the base AraBART model on the xlsum dataset and can produce high-quality Arabic text summaries.

Model Features

Arabic language optimization
Specially optimized for Arabic texts, better handling the linguistic characteristics of Arabic
High-quality summarization
Achieved a Rouge-1 score of 31.08 on the xlsum evaluation set, capable of generating coherent and accurate summaries
Efficient training
Utilizes techniques like linear learning rate scheduling and label smoothing for stable and efficient training

Model Capabilities

Arabic text summarization generation
Long text compression
Key information extraction

Use Cases

News media
News summarization generation
Automatically generates concise summaries of Arabic news articles
Produces summaries averaging 19.64 tokens, retaining key news points
Content analysis
Document key information extraction
Extracts core content and key information from long documents
Achieves a Bertscore of 73.86, accurately capturing the main ideas of documents
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