# CAMeLBERT-CA POS-EGY Model
## Model description
**CAMeLBERT-CA POS-EGY Model** is a Egyptian Arabic POS tagging model that was built by fine-tuning the [CAMeLBERT-CA](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca/) model.
For the fine-tuning, we used the ARZTB dataset .
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).

## Intended uses
You can use the CAMeLBERT-CA POS-EGY model as part of the transformers pipeline.
This model will also be available in [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) soon.

#### How to use
To use the model with a transformers pipeline:
```python
>>> from transformers import pipeline
>>> pos = pipeline('token-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-egy')
>>> text = 'عامل ايه ؟'
>>> pos(text)
[{'entity': 'adj', 'score': 0.9990943, 'index': 1, 'word': 'عامل', 'start': 0, 'end': 4}, {'entity': 'pron_interrog', 'score': 0.99863535, 'index': 2, 'word': 'ايه', 'start': 5, 'end': 8}, {'entity': 'punc', 'score': 0.99990875, 'index': 3, 'word': '؟', 'start': 9, 'end': 10}]
```
*Note*: to download our models, you would need `transformers>=3.5.0`.
Otherwise, you could download the models manually.
## Citation
```bibtex
@inproceedings{inoue-etal-2021-interplay,
    title = "The Interplay of Variant, Size, and Task Type in {A}rabic Pre-trained Language Models",
    author = "Inoue, Go  and
      Alhafni, Bashar  and
      Baimukan, Nurpeiis  and
      Bouamor, Houda  and
      Habash, Nizar",
    booktitle = "Proceedings of the Sixth Arabic Natural Language Processing Workshop",
    month = apr,
    year = "2021",
    address = "Kyiv, Ukraine (Online)",
    publisher = "Association for Computational Linguistics",
    abstract = "In this paper, we explore the effects of language variants, data sizes, and fine-tuning task types in Arabic pre-trained language models. To do so, we build three pre-trained language models across three variants of Arabic: Modern Standard Arabic (MSA), dialectal Arabic, and classical Arabic, in addition to a fourth language model which is pre-trained on a mix of the three. We also examine the importance of pre-training data size by building additional models that are pre-trained on a scaled-down set of the MSA variant. We compare our different models to each other, as well as to eight publicly available models by fine-tuning them on five NLP tasks spanning 12 datasets. Our results suggest that the variant proximity of pre-training data to fine-tuning data is more important than the pre-training data size. We exploit this insight in defining an optimized system selection model for the studied tasks.",
}
```
{"language": ["ar"], "license": "apache-2.0", "widget": [{"text": "\u0639\u0627\u0645\u0644 \u0627\u064a\u0647 \u061f"}]}
transformers pytorch tf bert token-classification ar arxiv:2103.06678 license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #bert #token-classification #ar #arxiv-2103.06678 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 

# CAMeLBERT-CA POS-EGY Model
## Model description
CAMeLBERT-CA POS-EGY Model is a Egyptian Arabic POS tagging model that was built by fine-tuning the CAMeLBERT-CA model.
For the fine-tuning, we used the ARZTB dataset .
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-CA POS-EGY model as part of the transformers pipeline.
This model will also be available in CAMeL Tools soon.

#### How to use
To use the model with a transformers pipeline:

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

# CAMeLBERT-CA POS-EGY Model ## Model description
CAMeLBERT-CA POS-EGY Model is a Egyptian Arabic POS tagging model that was built by fine-tuning the CAMeLBERT-CA model.
For the fine-tuning, we used the ARZTB dataset .
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-CA POS-EGY model as part of the transformers pipeline.
This model will also be available in CAMeL Tools soon. #### How to use
To use the model with a transformers pipeline:

*Note*: to download our models, you would need 'transformers>=3.5.0'.
Otherwise, you could download the models manually.
TAGS
#transformers #pytorch #tf #bert #token-classification #ar #arxiv-2103.06678 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # CAMeLBERT-CA POS-EGY Model ## Model description
CAMeLBERT-CA POS-EGY Model is a Egyptian Arabic POS tagging model that was built by fine-tuning the CAMeLBERT-CA model.
For the fine-tuning, we used the ARZTB dataset .
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-CA POS-EGY model as part of the transformers pipeline.
This model will also be available in CAMeL Tools soon. #### How to use
To use the model with a transformers pipeline:

*Note*: to download our models, you would need 'transformers>=3.5.0'.
Otherwise, you could download the models manually.
TAGS
#transformers #pytorch #tf #bert #token-classification #ar #arxiv-2103.06678 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# CAMeLBERT-CA POS-EGY Model## Model description
CAMeLBERT-CA POS-EGY Model is a Egyptian Arabic POS tagging model that was built by fine-tuning the CAMeLBERT-CA model.
For the fine-tuning, we used the ARZTB dataset .
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-CA POS-EGY model as part of the transformers pipeline.
This model will also be available in CAMeL Tools soon.#### How to use
To use the model with a transformers pipeline:

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