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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.


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


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


The model is available on the HuggingFace model page under the name: boda/ANER. Checkpoints are available only in PyTorch at the time.

Use in python:

from transformers import AutoTokenizer, AutoModelForTokenClassification

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

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


Thanks to 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 at the Faculty of Computing and Information Technology King Abdulaziz University, for providing the dataset which we used to train our model with.


Abdelrahman Atef

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