metadata

license: mit
language:
  - en
  - fr
metrics:
  - bleu
library_name: transformers
pipeline_tag: translation

French to English Machine Translation

Author: Kamelia Zaman Moon
Project link: https://huggingface.co/spaces/KameliaZaman/French-to-English-Translation
Language(s): Python
License: MIT
Contact: kamelia.stu2017@juniv.edu

Introduction
Model Architecture
How-to Guide
License
Contributors

1. Introduction

This project aims to develop a machine translation system for translating French text into English. The system utilizes state-of-the-art neural network architectures and techniques in natural language processing (NLP) to accurately translate French sentences into their corresponding English equivalents.

2. Model Architecture

The machine translation model employs a sequence-to-sequence architecture, specifically utilizing a recurrent neural network (RNN) with an attention mechanism. The model is trained on a parallel corpus consisting of aligned French and English sentences. Key components of the model include encoder and decoder networks, attention mechanism, and tokenization for text processing.

──  eng_-french.csv - text dataset.

──  french_to_english_translator.h5 - generated model.

──  french_to_english_translation_using_seq2seq.ipynb - preprocesses input, trains, saves and evaluates the model.

──  app.py - this module starts the app interface.

──  README.md - readme file of this project.

──  requirements.txt - list of required packages.

3. How-to Guide

3.1. Data Preparation

The parallel corpus containing French and English sentences is preprocessed.
Text is tokenized and converted into numerical representations suitable for input to the neural network.

3.2. Model Training

The sequence-to-sequence model is constructed, comprising an encoder and decoder.
Training data is fed into the model, and parameters are optimized using backpropagation and gradient descent algorithms.

3.3. Model Evaluation

The trained model is evaluated on the test set to measure its accuracy.
Metrics such as BLEU score has been used to quantify the quality of translations.

3.4. Deployment

Gradio is utilized for deploying the trained model.
Users can input a French text, and the model will translate it to English.

# clone project   
git clone https://huggingface.co/spaces/KameliaZaman/French-to-English-Translation/tree/main

# go inside the project directory 
cd French-to-English-Translation

# install the required packages
pip install -r requirements.txt

# run the gradio app
python app.py

4. License

This project is licensed under the MIT License.

5. Contributors

Kamelia Zaman Moon - kamelia.stu2017@juniv.edu

KameliaZaman
/

French-to-English-Translation