Arabic Model AraBertMo_base_V9

---
language: ar
tags: Fill-Mask 
datasets: OSCAR
widget:
- text: " السلام عليكم ورحمة[MASK] وبركاتة"
- text: " اهلا وسهلا بكم في [MASK] من سيربح المليون"
- text: " مرحبا بك عزيزي الزائر [MASK] موقعنا "

---
# Arabic BERT Model
**AraBERTMo** is an Arabic pre-trained language model based on [Google's BERT architechture](https://github.com/google-research/bert). 
AraBERTMo_base uses the same BERT-Base config. 
AraBERTMo_base now comes in 10 new variants
All models are available on the `HuggingFace` model page under the [Ebtihal](https://huggingface.co/Ebtihal/) name. 
Checkpoints are available in PyTorch formats.

## Pretraining Corpus
`AraBertMo_base_V9' model was pre-trained on ~3 million words:
- [OSCAR](https://traces1.inria.fr/oscar/) - Arabic version "unshuffled_deduplicated_ar". 

## Training results
this model achieves the following results:

| Task | Num examples | Num Epochs  | Batch Size | steps | Wall time  | training loss| 
|:----:|:----:|:----:|:----:|:-----:|:----:|:-----:|
| Fill-Mask| 30024|  9  | 64 | 4230  | 7h 57m 42s | 7.3264  | 

## Load Pretrained Model
You can use this model by installing `torch` or `tensorflow` and Huggingface library `transformers`. And you can use it directly by initializing it like this:  
```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Ebtihal/AraBertMo_base_V9")
model = AutoModelForMaskedLM.from_pretrained("Ebtihal/AraBertMo_base_V9")
```

 ## This model was built for master's degree research in an organization:
- [University of kufa](https://uokufa.edu.iq/).
- [Faculty of Computer Science and Mathematics](https://mathcomp.uokufa.edu.iq/).
- **Department of Computer Science**


{}
transformers pytorch bert fill-mask autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #autotrain_compatible #endpoints_compatible #region-us 

Arabic Model AraBertMo\_base\_V9




---


language: ar
tags: Fill-Mask
datasets: OSCAR
widget:


* text: " السلام عليكم ورحمة[MASK] وبركاتة"
* text: " اهلا وسهلا بكم في [MASK] من سيربح المليون"
* text: " مرحبا بك عزيزي الزائر [MASK] موقعنا "




---


Arabic BERT Model
=================


AraBERTMo is an Arabic pre-trained language model based on Google's BERT architechture.
AraBERTMo\_base uses the same BERT-Base config.
AraBERTMo\_base now comes in 10 new variants
All models are available on the 'HuggingFace' model page under the Ebtihal name.
Checkpoints are available in PyTorch formats.


Pretraining Corpus
------------------


'AraBertMo\_base\_V9' model was pre-trained on ~3 million words:


* OSCAR - Arabic version "unshuffled\_deduplicated\_ar".


Training results
----------------


this model achieves the following results:



Load Pretrained Model
---------------------


You can use this model by installing 'torch' or 'tensorflow' and Huggingface library 'transformers'. And you can use it directly by initializing it like this:


This model was built for master's degree research in an organization:
---------------------------------------------------------------------


* University of kufa.
* Faculty of Computer Science and Mathematics.
* Department of Computer Science



TAGS
#transformers #pytorch #bert #fill-mask #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #fill-mask #autotrain_compatible #endpoints_compatible #region-us 
