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CAMeLBERT-DA SA Model

Model description

CAMeLBERT-DA SA Model is a Sentiment Analysis (SA) model that was built by fine-tuning the CAMeLBERT Dialectal Arabic (DA) model. For the fine-tuning, we used the ASTD, ArSAS, and SemEval datasets. Our fine-tuning procedure and the hyperparameters we used can be found in our paper *"The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models."

• Our fine-tuning code can be found here.

Intended uses

You can use the CAMeLBERT-DA SA model directly as part of our CAMeL Tools SA component (recommended) or as part of the transformers pipeline.

How to use

To use the model with the CAMeL Tools SA component:

>>> from camel_tools.sentiment import SentimentAnalyzer
>>> sa = SentimentAnalyzer("CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment")
>>> sentences = ['أنا بخير', 'أنا لست بخير']
>>> sa.predict(sentences)
>>> ['positive', 'negative']

You can also use the SA model directly with a transformers pipeline:

>>> from transformers import pipeline
>>> sa = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment')
>>> sentences = ['أنا بخير', 'أنا لست بخير']
>>> sa(sentences)
[{'label': 'positive', 'score': 0.9616648554801941},
 {'label': 'negative', 'score': 0.9779177904129028}]

Note: to download our models, you would need transformers>=3.5.0. Otherwise, you could download the models manually.

Citation

@inproceedings{inoue-etal-2021-interplay,
    title = "The Interplay of Variant, Size, and Task Type in {A}rabic Pre-trained Language Models",
    a

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