Pre-trained Transformers for Arabic Language Understanding and Generation (Arabic BERT, Arabic GPT2, Arabic ELECTRA)

Fine-tune BERT models to classify Arabic text by different dialects.

Arabic Dialect Identification between 18 country-level Arabic dialects using QADI dataset and pretrained language model AraBERT

Mental health diagnosis tool using NLP and ML for Arabic inputs, with a Laravel web application interface

After collecting 40 thousand tweets and preprocessing it, I used word embeddings with arabert and tf-idf along with two neural network architectures and 5 machine learning algorithms. Due to the huge size of the dataset, I chose Amazon SageMaker to train the models

Arabic Dialect Sentimenal Analysis

Simple Script to undo Farasa Segmentation, compatible with AraBERT pre-segmentation

Easy to use extractive text summarization with AraBERT

Arabic_Dialect_Identification_NLP-AIM-Task

Diacritics are short vowels with a constant length that are spoken. The same word in the Arabic language can have different meanings and different pronunciations based on how it is diacritized. In this project, we implement a pipeline to predict the diacritic of each character in an Arabic text using Natural Language Processing techniques.

An advanced Arabic fake news detection model using LSTM and AraBERT. This project leverages the Arabic Fake News Dataset (AFND) to classify news articles as credible, not credible, or undecided. Includes preprocessing steps, model building, and evaluation using TensorFlow.

This is an experiment for Qur'an QA for the shared task at the OSCAT workshop

This project focuses on developing a sentiment analysis model for Arabic text, leveraging hybrid transformer-based models (AraBERT) and LSTM approaches.

Emotion Prediction in Arabic Text

Dialectical Arabic Sentiment Analysis

Sentiment analysis with arabert in Tunisian dialect

Disambiguation Study for Arabic Applied on Text Classification

Fine-tuning / pre-training AraElectra on a specific domain for QA system.

Sentiment analysis of Arabic hotel feedback using AraBERT. This project leverages AraBERT, a transformer-based model for Arabic text, to classify customer sentiment in hotel reviews. The repository includes the code, training pipeline, and pre-trained model for sentiment classification tasks.