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 repo for the latest information about previous and current models.
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 user comments provided by
Open Data Mining Program (ODMP). This dataset contains 62,321 user comments with three labels:
Download
You can download the dataset from
here
The following table summarizes the F1 score obtained by ParsBERT as compared to other models and architectures.
1@article{ParsBERT,
2 title={ParsBERT: Transformer-based Model for Persian Language Understanding},
3 author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri},
4 journal={ArXiv},
5 year={2020},
6 volume={abs/2005.12515}
7}
Post a Github issue on the
ParsBERT Issues repo.
