Update README.md

README.md

@@ -15,4 +15,54 @@ widget:
   example_title: "خليجي"
 - text: "و حضرتك طيبة و شكرا علي الكلام الحلو ده يا مبهجة..."
   example_title: "مصري"
----
+---
+# Dialectical-MSA-detection
+
+## Model description
+
+This model was trained on 108,173 manually annotated User-Generated Content (e.g. tweets and online comments) to classify the Arabic language of the text into one of two categories: 'Dialectical', or 'MSA' (i.e. Modern Standard Arabic).
+
+
+## Training data
+
+Dialectical-MSA-detection was trained on the English-speaking subset of the [The Arabic online commentary dataset (Zaidan, et al 20211)](https://github.com/sjeblee/AOC). 
+The AOC dataset was created by crawling the websites of three Arabic newspapers, and extracting online articles and readers' comments.  
+
+
+
+## Training procedure
+
+`xlm-roberta-base` was trained using the Hugging Face trainer with the following hyperparameters. 
+
+```
+training_args = TrainingArguments(
+    num_train_epochs=4,               # total number of training epochs
+    learning_rate=2e-5,               # learning rate
+    per_device_train_batch_size=32,   # batch size per device during training
+    per_device_eval_batch_size=4,     # batch size for evaluation
+    warmup_steps=0,                   # number of warmup steps for learning rate scheduler
+    weight_decay=0.02,                # strength of weight decay
+    
+)
+```
+
+## Eval results
+
+The model was evaluated using 10% of the sentences (90-10 train-dev split). Accuracy 0.88 on the dev set.
+
+
+## Limitations and bias
+
+The model was trained on sentences from the online commentary domain. Other forms of UGT such as tweet can be different in the degree of dialectness. 
+
+
+### BibTeX entry and citation info
+
+```bibtex
+@article{saadany2022semi,
+  title={A Semi-supervised Approach for a Better Translation of Sentiment in Dialectical Arabic UGT},
+  author={Saadany, Hadeel and Orasan, Constantin and Mohamed, Emad and Tantawy, Ashraf},
+  journal={arXiv preprint arXiv:2210.11899},
+  year={2022}
+}
+```