correct config, update model card

README.md

@@ -12,23 +12,19 @@ Pretrained BERT base language model for Arabic
 
 _If you use this model in your work, please cite this paper:_
 
-<!--```
-@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}
-}
-```-->
-
 ```
-@misc{safaya2020kuisail,
-    title={KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media},
-    author={Ali Safaya and Moutasem Abdullatif and Deniz Yuret},
-    year={2020},
-    eprint={2007.13184},
-    archivePrefix={arXiv},
-    primaryClass={cs.CL}
+@inproceedings{safaya-etal-2020-kuisail,
+    title = "{KUISAIL} at {S}em{E}val-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 Fourteenth Workshop on Semantic Evaluation",
+    month = dec,
+    year = "2020",
+    address = "Barcelona (online)",
+    publisher = "International Committee for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/2020.semeval-1.271",
+    pages = "2054--2059",
 }
 ```
 
@@ -60,7 +56,7 @@ You can use this model by installing `torch` or `tensorflow` and Huggingface lib
 from transformers import AutoTokenizer, AutoModel
 
 tokenizer = AutoTokenizer.from_pretrained("asafaya/bert-base-arabic")
-model = AutoModel.from_pretrained("asafaya/bert-base-arabic")
+model = AutoModelForMaskedLM.from_pretrained("asafaya/bert-base-arabic")
 ```
 
 ## Results

config.json

@@ -1,6 +1,6 @@
 {
   "architectures": [
-    "BertModel"
+    "BertForMaskedLM"
   ],
   "attention_probs_dropout_prob": 0.1,
   "gradient_checkpointing": false,