readme: ---
  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.
  
  
  ### DeepSentiPers
  
  which is a balanced and augmented version of SentiPers, contains 12,138 user opinions about digital products labeled with five different classes; two positives (i.e., happy and delighted), two negatives (i.e., furious and angry) and one neutral class. Therefore, this dataset can be utilized for both multi-class and binary classification. In the case of binary classification, the neutral class and its corresponding sentences are removed from the dataset.
  
  **Binary:**
  1. Negative (Furious + Angry)
  2. Positive (Happy + Delighted)
  
  **Multi**
  1. Furious
  2. Angry
  3. Neutral
  4. Happy
  5. Delighted
  
  
  |   Label   |   #  |
  |:---------:|:----:|
  |  Furious  |  236 |
  |   Angry   | 1357 |
  |  Neutral  | 2874 |
  |   Happy   | 2848 |
  | Delighted | 2516 |
  
  
  
  **Download**
  You can download the dataset from:
  
  - [SentiPers](https://github.com/phosseini/sentipers)
  - [DeepSentiPers](https://github.com/JoyeBright/DeepSentiPers)
  
  ## 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 |
  |:------------------------:|:-----------:|:-----------:|:-----:|:-------------:|
  |  SentiPers (Multi Class) |    71.31*   |    71.11    |   -   |     69.33     |
  | SentiPers (Binary Class) |    92.42*   |    92.13    |   -   |     91.98     |
  
  
  ## 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.