impoxeur2001/Sentiment_Analysis_Darija

# Sentiment_Analysis_Darija This project implements a sentiment analysis model for the Darija dialect using the BERT model. The model was trained on a training dataset and evaluated on a testing dataset, achieving an accuracy of 92%. The trained model was then deployed as a REST API using Flask. ## Getting Started To get started with this project, follow these steps: ### Prerequisites - Python 3.6 or higher - pip package manager - virtualenv (optional) ### Installation 1. Clone the repository: ``` git clone github.com cd sentiment-analysis-darija ``` 3. Install the required packages: ``` pip install -r requirements.txt ``` ### Usage 1. Start the Flask server: ``` python app.py ``` 2. Make a POST request to the `/predict` endpoint with a JSON payload containing the text to analyze: ```python import requests url = 'localhost' data = 'film mzian hada 3jboni chakhsiat' response = requests.post(url+data, json=data) print(response.json()) ``` The response will be a JSON object containing the predicted sentiment : ```json { "sentiment": "positive" } ``` ## Training and Evaluation The sentiment analysis model was trained using the BERT model and tokenizer from the `transformers` library. The training dataset consisted of 1900 labeled examples, and the testing dataset consisted of 150 labeled examples. The training and evaluation were done in a python notebook that you can find in this repository ## License This project is licensed under the MIT License - see the LICENSE file for details. ## Contributors - Malainine Mohamed Limame - Drhorhi omar - Meryem Boukdimi - Bnou Mohamed