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AyaZJaradat/
arabert-base-v02-finetuned-MRC

Name: arabert-base-v02-finetuned-MRC
Availability: InStock

aubmindlab/bert-base-arabertv02

finetune

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arabert-base-v02-finetuned-MRC

Model Description

This model is a fine-tuned version of bert-base-arabertv02 on an expert-annotated Arabic Machine Reading Comprehension (MRC) dataset ArQuAD , for the MRC task.

Model type: Question answering model
Downstream-task: Extractive QA
Language(s) (NLP): Arabic
Finetuned from model : aubmindlab/bert-base-arabertv02

How to Get Started with the Model

Use the code below to get started with the model:

model = AutoModelForQuestionAnswering.from_pretrained("AyaZJaradat/arabert-base-v02-finetuned-MRC")
tokenizer = AutoTokenizer.from_pretrained("AyaZJaradat/arabert-base-v02-finetuned-MRC")

Training Details

Training Data

We use the ArQuAD dataset to fine-tune the model, with 12,816 rows of training.

Preprocessing

We removed the diacritics in the data before starting training.

Training Hyperparameters

Learning Rate: 3e-5
Optimizer: AdamW
Batch size: 12
Epochs: 3

Evaluation

Testing Data

We used the testing data from ArQuAD with 1602 rows.

Metrics

We used the Exact Match (EM) and the F1-score to evaluate the model using the script of SQuAD.

Results

The results for the test data are as follows:

EM: 66.73%
F1-score: 85.52%

Model Card Authors

Aya Jaradat

Model Card Contact

azjaradat23@cit.just.edu.jo