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  ## Model description
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  **CAMeLBERT-DA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
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  For the fine-tuning, we used the [ASTD](https://aclanthology.org/D15-1299.pdf), [ArSAS](http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf), and [SemEval](https://aclanthology.org/S17-2088.pdf) datasets.
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- 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](https://arxiv.org/abs/2103.06678)."* Our fine-tuning code can be found [here](https://github.com/CAMeL-Lab/CAMeLBERT).
 
 
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  ## Intended uses
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  You can use the CAMeLBERT-DA SA model directly as part of our [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) SA component (*recommended*) or as part of the transformers pipeline.
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  #### How to use
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  You can also use the SA model directly with a transformers pipeline:
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  ```python
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  >>> from transformers import pipeline
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- >>> sa = pipeline('sentiment-analysis', model='CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment')
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  >>> sentences = ['أنا بخير', 'أنا لست بخير']
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  >>> sa(sentences)
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  [{'label': 'positive', 'score': 0.9616648554801941},
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  {'label': 'negative', 'score': 0.9779177904129028}]
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  ```
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- *Note*: to download our models, you would need `transformers>=3.5.0`. Otherwise, you could download the models
 
 
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  ## Citation
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  ```bibtex
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  @inproceedings{inoue-etal-2021-interplay,
 
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  ## Model description
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  **CAMeLBERT-DA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
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  For the fine-tuning, we used the [ASTD](https://aclanthology.org/D15-1299.pdf), [ArSAS](http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf), and [SemEval](https://aclanthology.org/S17-2088.pdf) datasets.
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+ 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](https://arxiv.org/abs/2103.06678)."
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+ * Our fine-tuning code can be found [here](https://github.com/CAMeL-Lab/CAMeLBERT).
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+
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  ## Intended uses
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  You can use the CAMeLBERT-DA SA model directly as part of our [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) SA component (*recommended*) or as part of the transformers pipeline.
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  #### How to use
 
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  You can also use the SA model directly with a transformers pipeline:
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  ```python
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  >>> from transformers import pipeline
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+ >>> sa = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment')
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  >>> sentences = ['أنا بخير', 'أنا لست بخير']
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  >>> sa(sentences)
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  [{'label': 'positive', 'score': 0.9616648554801941},
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  {'label': 'negative', 'score': 0.9779177904129028}]
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  ```
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+ *Note*: to download our models, you would need `transformers>=3.5.0`.
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+ Otherwise, you could download the models manually.
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+
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  ## Citation
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  ```bibtex
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  @inproceedings{inoue-etal-2021-interplay,