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https://github.com/rrayhka/indonesian-ner-spacy
Fine-tuning SpaCy for Indonesian Named Entity Recognition (NER) with custom dataset.
https://github.com/rrayhka/indonesian-ner-spacy
indonesian named-entity-recognition ner nlp spacy
Last synced: 27 days ago
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Fine-tuning SpaCy for Indonesian Named Entity Recognition (NER) with custom dataset.
- Host: GitHub
- URL: https://github.com/rrayhka/indonesian-ner-spacy
- Owner: rrayhka
- Created: 2024-07-02T07:35:17.000Z (4 months ago)
- Default Branch: master
- Last Pushed: 2024-08-15T13:53:42.000Z (3 months ago)
- Last Synced: 2024-09-26T19:40:51.907Z (about 1 month ago)
- Topics: indonesian, named-entity-recognition, ner, nlp, spacy
- Language: Jupyter Notebook
- Homepage:
- Size: 623 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
# Indonesian-NER-Spacy
SpaCy is an open-source Natural Language Processing (NLP) library that offers powerful tools for various language processing tasks. However, it does not natively support a Named Entity Recognition (NER) model for the Indonesian language. This project aims to bridge that gap by fine-tuning a SpaCy model specifically for Indonesian using the available dataset.
## Table of Contents
- [About](#about)
- [Getting Started](#getting-started)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [Contact](#contact)
## About
This project provides a fine-tuned Named Entity Recognition (NER) model for the Indonesian language using SpaCy. By leveraging the available dataset, the model has been trained to recognize various entities within Indonesian text, such as names, organizations, locations, and more.
## Getting Started
To get a local copy up and running, follow these steps.
### Prerequisites
- Python 3.8+
- SpaCy
- Jupyter Notebook
### Installation
1. Clone the repository:
```bash
git clone https://github.com/rrayhka/indonesian-ner-spacy.git
cd indonesian-ner-spacy
```
2. Install SpaCy:
```bash
pip install spacy
```
3. Ensure that SpaCy is correctly installed and the necessary SpaCy components are downloaded:
```bash
python -m spacy download en_core_web_sm
```
## Usage
To fine-tune and test the Indonesian NER model, you can use the provided Jupyter notebooks:
1. **Data Preparation:**
Run the `convert_data.ipynb` notebook to preprocess the dataset and convert it into a format suitable for training.
```bash
jupyter notebook convert_data.ipynb
```
2. **Model Training:**
Use the `modelling.ipynb` notebook to fine-tune the SpaCy model on the Indonesian dataset.
```bash
jupyter notebook modelling.ipynb
```
3. **Testing:**
After training, the model can be tested using the provided test dataset or any custom Indonesian text.
```bash
jupyter notebook modelling.ipynb
```
## Contributing
Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.
1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## Inspiration
This project was inspired by [this post](https://yudanta.github.io/posts/train-an-indonesian-ner-from-a-blank-spacy-model/) by Yudanta, which provides a guide on training an Indonesian NER model from a blank SpaCy model. It served as a valuable reference in the creation and fine-tuning of this project.
## Contact
Akhyar - [[email protected]](mailto:[email protected])