---
language:
- ar
thumbnail: url to a thumbnail used in social sharing
tags:
- ner
- token-classification
- Arabic-NER
metrics:
- accuracy
- f1
- precision
- recall
widget:
- text: النجم محمد صلاح لاعب المنتخب المصري يعيش في مصر بالتحديد من نجريج, الشرقية
  example_title: Mohamed Salah
- text: انا ساكن في حدايق الزتون و بدرس في جامعه عين شمس
  example_title: Egyptian Dialect
- text: يقع نهر الأمازون في قارة أمريكا الجنوبية
  example_title: Standard Arabic
datasets:
- Fine-grained-Arabic-Named-Entity-Corpora
pipeline_tag: token-classification
---





# Arabic Named Entity Recognition

This project is made to enrich the Arabic Named Entity Recognition(ANER). Arabic is a tough language to deal with and has alot of difficulties.
We managed to made a model based on Arabert to support 50 entities.

## Paper

Here's the paper that contains all the details for our model, our approach, and the training results

- [ANER Paper](https://drive.google.com/file/d/1jJn3iWqOeLzaNvO-6aKfgidzJlWOtvti/view?usp=sharing)



# Dataset

- [Fine-grained Arabic Named Entity Corpora](https://fsalotaibi.kau.edu.sa/Pages-Arabic-NE-Corpora.aspx)


# Evaluation results

The model achieves the following results:

| Dataset  | WikiFANE Gold | WikiFANE Gold | WikiFANE Gold | NewsFANE Gold | NewsFANE Gold | NewsFANE Gold  
|:--------:|:-------:|:-------:|:------:|:------:|:---------:|:------:|
| (metric) | (Recall)   | (Precision)   | (F1)  | (Recall)  | (Precision)     | (F1) 
|          | 87.0  | 90.5   | 88.7 | 78.1   | 77.4     | 77.7  


# Usage

The model is available on the HuggingFace model page under the name: [boda/ANER](https://huggingface.co/boda/ANER). Checkpoints are available only in PyTorch at the time.

### Use in python:

```python
from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("boda/ANER")

model = AutoModelForTokenClassification.from_pretrained("boda/ANER")
```


# Acknowledgments

Thanks to [Arabert](https://github.com/aub-mind/arabert) for providing the Arabic Bert model, which we used as a base model for our work.

We also would like to thank [Prof. Fahd Saleh S Alotaibi](https://fsalotaibi.kau.edu.sa/Pages-Arabic-NE-Corpora.aspx) at the Faculty of Computing and Information Technology King Abdulaziz University, for providing the dataset which we used to train our model with.

# Contacts

**Abdelrahman Atef**

- [LinkedIn](linkedin.com/in/boda-sadalla)
- [Github](https://github.com/BodaSadalla98)
- <bodasadallah@yahoo.com>