A model which is jointly trained and fine-tuned on Quran, Saheefa and nahj-al-balaqa. All Datasets are available [Here](https://github.com/language-ml/course-nlp-ir-1-text-exploring/tree/main/exploring-datasets/religious_text). Code will be available soon ...

Some Examples for filling the mask:

- ```
ذَلِكَ [MASK] لَا رَيْبَ فِيهِ هُدًى لِلْمُتَّقِينَ
```
- ```
يَا أَيُّهَا النَّاسُ اعْبُدُوا رَبَّكُمُ الَّذِي خَلَقَكُمْ وَالَّذِينَ مِنْ قَبْلِكُمْ لَعَلَّكُمْ [MASK]
```

This model is fine-tuned on [Bert Base Arabic](https://huggingface.co/asafaya/bert-base-arabic) for 30 epochs. We have used `Masked Language Modeling` to fine-tune the model. Also, after each 5 epochs, we have completely masked the words again for the model to learn the embeddings very well and not overfit the data. 

{"language": "ar", "license": "gpl-2.0"}
transformers pytorch bert fill-mask ar license:gpl-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #ar #license-gpl-2.0 #autotrain_compatible #endpoints_compatible #region-us 

A model which is jointly trained and fine-tuned on Quran, Saheefa and nahj-al-balaqa. All Datasets are available Here. Code will be available soon ...

Some Examples for filling the mask:

- 
- 

This model is fine-tuned on Bert Base Arabic for 30 epochs. We have used 'Masked Language Modeling' to fine-tune the model. Also, after each 5 epochs, we have completely masked the words again for the model to learn the embeddings very well and not overfit the data. 

TAGS
#transformers #pytorch #bert #fill-mask #ar #license-gpl-2.0 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #fill-mask #ar #license-gpl-2.0 #autotrain_compatible #endpoints_compatible #region-us 
