From 3cdf8b7ec2ac7b638bac7495870f1fd152314251 Mon Sep 17 00:00:00 2001
From: Ali Safaya <alisafaya@gmail.com>
Date: Mon, 29 Jun 2020 15:41:41 +0300
Subject: [PATCH] Create model card for asafaya/bert-mini-arabic (#5352)

* Create README.md

* Update model_cards/asafaya/bert-mini-arabic/README.md

Co-authored-by: Julien Chaumond <chaumond@gmail.com>
---
 .../asafaya/bert-mini-arabic/README.md        | 61 +++++++++++++++++++
 1 file changed, 61 insertions(+)
 create mode 100644 model_cards/asafaya/bert-mini-arabic/README.md

diff --git a/model_cards/asafaya/bert-mini-arabic/README.md b/model_cards/asafaya/bert-mini-arabic/README.md
new file mode 100644
index 0000000000..b485704000
--- /dev/null
+++ b/model_cards/asafaya/bert-mini-arabic/README.md
@@ -0,0 +1,61 @@
+---
+language: arabic
+datasets:
+- oscar
+- wikipedia
+---
+
+# Arabic BERT Mini Model
+
+Pretrained BERT Mini language model for Arabic
+
+_If you use this model in your work, please cite this paper (to appear in 2020):_
+
+```
+@inproceedings{
+  title={KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media},
+  author={Safaya, Ali and Abdullatif, Moutasem and Yuret, Deniz},
+  booktitle={Proceedings of the International Workshop on Semantic Evaluation (SemEval)},
+  year={2020}
+}
+```
+
+## Pretraining Corpus
+
+`arabic-bert-mini` model was pretrained on ~8.2 Billion words:
+
+- Arabic version of [OSCAR](https://traces1.inria.fr/oscar/) - filtered from [Common Crawl](http://commoncrawl.org/)
+- Recent dump of Arabic [Wikipedia](https://dumps.wikimedia.org/backup-index.html)
+
+and other Arabic resources which sum up to ~95GB of text.
+
+__Notes on training data:__
+
+- Our final version of corpus contains some non-Arabic words inlines, which we did not remove from sentences since that would affect some tasks like NER.
+- Although non-Arabic characters were lowered as a preprocessing step, since Arabic characters does not have upper or lower case, there is no cased and uncased version of the model.
+- The corpus and vocabulary set are not restricted to Modern Standard Arabic, they contain some dialectical Arabic too.
+
+## Pretraining details
+
+- This model was trained using Google BERT's github [repository](https://github.com/google-research/bert) on a single TPU v3-8 provided for free from [TFRC](https://www.tensorflow.org/tfrc).
+- Our pretraining procedure follows training settings of bert with some changes: trained for 3M training steps with batchsize of 128, instead of 1M with batchsize of 256.
+
+## 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("asafaya/bert-mini-arabic")
+model = AutoModel.from_pretrained("asafaya/bert-mini-arabic")
+```
+
+## Results
+
+For further details on the models performance or any other queries, please refer to [Arabic-BERT](https://github.com/alisafaya/Arabic-BERT)
+
+## Acknowledgement
+
+Thanks to Google for providing free TPU for the training process and for Huggingface for hosting this model on their servers 😊
+