Create README.md

README.md

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+---
+language: fa
+license: apache-2.0
+---
+
+# ParsBERT (v2.0)
+A Transformer-based Model for Persian Language Understanding
+
+We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
+Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) repo for the latest information about previous and current models.
+
+
+## Persian Sentiment [Digikala, SnappFood, DeepSentiPers]
+
+It aims to classify text, such as comments, based on their emotional bias. We tested three well-known datasets for this task: `Digikala` user comments, `SnappFood` user comments, and `DeepSentiPers` in two binary-form and multi-form types.
+
+
+
+### SnappFood
+
+[Snappfood](https://snappfood.ir/) (an online food delivery company) user comments containing 70,000 comments with two labels (i.e. polarity classification): 
+
+1. Happy
+2. Sad
+
+|   Label  |   #   |
+|:--------:|:-----:|
+| Negative | 35000 |
+| Positive | 35000 |
+
+**Download**
+You can download the dataset from [here](https://drive.google.com/uc?id=15J4zPN1BD7Q_ZIQ39VeFquwSoW8qTxgu)
+
+## Results
+
+The following table summarizes the F1 score obtained by ParsBERT as compared to other models and architectures.
+
+|          Dataset         | ParsBERT v2 | ParsBERT v1 | mBERT | DeepSentiPers |
+|:------------------------:|:-----------:|:-----------:|:-----:|:-------------:|
+|  SnappFood User Comments |    87.98    |    88.12*   | 87.87 |       -       |
+
+
+## How to use :hugs:
+
+| Task                | Notebook                                                                                                                                                                                          |
+|---------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Sentiment Analysis | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/hooshvare/parsbert/blob/master/notebooks/Taaghche_Sentiment_Analysis.ipynb) |
+
+
+### BibTeX entry and citation info
+
+Please cite in publications as the following:
+
+```bibtex
+@article{ParsBERT,
+    title={ParsBERT: Transformer-based Model for Persian Language Understanding},
+    author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri},
+    journal={ArXiv},
+    year={2020},
+    volume={abs/2005.12515}
+}
+```
+
+## Questions?
+Post a Github issue on the [ParsBERT Issues](https://github.com/hooshvare/parsbert/issues) repo.