This NLP project purpose is to predict the dialect of Arabic language in tweets
The dataset used in this project is a collection of Tweets labeled with their corresponding dialects, The dialects are from 5 countries which are Egypt ('EG'), Lebanon ('LB'), Libya ('LY'), Sudan ('SD'), and Morocco ('MA')
in this project i used variety of models here is a summary of the results:
| Model | F1_score | accuracy_val |
|---|---|---|
| TF-IDF Multinomial Naive Bayes | 0.69 | 0.72 |
| LSTM | 0.82 | 0.82 |
| GRU | 0.79 | 0.79 |
Hybrid Model char and token embeddings |
0.80 | 0.80 |
| Arabert | 0.84 | 0.84 |
- The api created using FastAPI
- tested the app
- Clone the Repository
git clone https://github.com/ronysalem/Arabic-Dialects-Identification
- Navigate to the Project Directory
cd Arabic-Dialects-Identification
- Build and Run the Docker Container
docker-compose up --build
- Accessing the Application Once the application is running, you can access it by opening a web browser and visiting:
http://localhost:8000