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🚀 ALBERT Persian

A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language

ALBERT-Persian is the first attempt on ALBERT for the Persian Language. It can also be called "Bert-Kucholo". The model was trained based on Google's ALBERT BASE Version 2.0 over various writing styles from numerous subjects (e.g., scientific, novels, news) with more than 3.9M documents, 73M sentences, and 1.3B words, similar to the approach used for ParsBERT.

Please follow the ALBERT-Persian repo for the latest information about previous and current models.

🚀 Quick Start

This project focuses on self - supervised learning of Persian language representations using the ALBERT architecture. It also involves sentiment analysis on Persian text.

✨ Features

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

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

Download You can download the dataset from:

• SentiPers
• DeepSentiPers

📚 Documentation

Results

The following table summarizes the F1 score obtained as compared to other models and architectures.

BibTeX entry and citation info

Please cite in publications as the following:

@misc{ALBERTPersian,
  author = {Mehrdad Farahani},
  title = {ALBERT-Persian: A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language},
  year = {2020},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/m3hrdadfi/albert-persian}},
}

@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}
}

📄 License

This project is licensed under the Apache - 2.0 license.

💡 Usage Tip

If you have any questions, post a Github issue on the ALBERT - Persian repo.