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language: fa |
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license: apache-2.0 |
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# ParsBERT (v2.0) |
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A Transformer-based Model for Persian Language Understanding |
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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! |
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Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) repo for the latest information about previous and current models. |
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## Persian Sentiment [Digikala, SnappFood, DeepSentiPers] |
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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. |
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### DeepSentiPers |
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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. |
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**Binary:** |
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1. Negative (Furious + Angry) |
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2. Positive (Happy + Delighted) |
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**Multi** |
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1. Furious |
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2. Angry |
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3. Neutral |
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4. Happy |
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5. Delighted |
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| Label | # | |
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|:---------:|:----:| |
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| Furious | 236 | |
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| Angry | 1357 | |
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| Neutral | 2874 | |
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| Happy | 2848 | |
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| Delighted | 2516 | |
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**Download** |
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You can download the dataset from: |
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- [SentiPers](https://github.com/phosseini/sentipers) |
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- [DeepSentiPers](https://github.com/JoyeBright/DeepSentiPers) |
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## Results |
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The following table summarizes the F1 score obtained by ParsBERT as compared to other models and architectures. |
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| Dataset | ParsBERT v2 | ParsBERT v1 | mBERT | DeepSentiPers | |
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|:------------------------:|:-----------:|:-----------:|:-----:|:-------------:| |
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| SentiPers (Multi Class) | 71.31* | 71.11 | - | 69.33 | |
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| SentiPers (Binary Class) | 92.42* | 92.13 | - | 91.98 | |
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## How to use :hugs: |
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| Task | Notebook | |
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|---------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| |
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| Sentiment Analysis | [](https://colab.research.google.com/github/hooshvare/parsbert/blob/master/notebooks/Taaghche_Sentiment_Analysis.ipynb) | |
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### BibTeX entry and citation info |
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Please cite in publications as the following: |
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```bibtex |
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@article{ParsBERT, |
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title={ParsBERT: Transformer-based Model for Persian Language Understanding}, |
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author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri}, |
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journal={ArXiv}, |
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year={2020}, |
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volume={abs/2005.12515} |
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} |
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``` |
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## Questions? |
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Post a Github issue on the [ParsBERT Issues](https://github.com/hooshvare/parsbert/issues) repo. |
