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.
  
  
  
  ### Digikala
  
  Digikala user comments provided by [Open Data Mining Program (ODMP)](https://www.digikala.com/opendata/). This dataset contains 62,321 user comments with three labels: 
  
  |      Label      |    #   |
  |:---------------:|:------:|
  |     no_idea     |  10394 |
  | not_recommended |  15885 |
  |   recommended   |  36042 |
  
  
  **Download**
  You can download the dataset from [here](https://www.digikala.com/opendata/)
  
  ## 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 |
  |:------------------------:|:-----------:|:-----------:|:-----:|:-------------:|
  |  Digikala User Comments  |    81.72    |    81.74*   | 80.74 |       -       |
  
  
  ## 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.