| | --- |
| | license: mit |
| | --- |
| | # <a name="introduction"></a> BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese |
| |
|
| |
|
| | Two BARTpho versions `BARTpho-syllable` and `BARTpho-word` are the first public large-scale monolingual sequence-to-sequence models pre-trained for Vietnamese. BARTpho uses the "large" architecture and pre-training scheme of the sequence-to-sequence denoising model [BART](https://github.com/pytorch/fairseq/tree/main/examples/bart), thus especially suitable for generative NLP tasks. Experiments on a downstream task of Vietnamese text summarization show that in both automatic and human evaluations, BARTpho outperforms the strong baseline [mBART](https://github.com/pytorch/fairseq/tree/main/examples/mbart) and improves the state-of-the-art. |
| |
|
| | The general architecture and experimental results of BARTpho can be found in our [paper](https://arxiv.org/abs/2109.09701): |
| |
|
| | @article{bartpho, |
| | title = {{BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese}}, |
| | author = {Nguyen Luong Tran and Duong Minh Le and Dat Quoc Nguyen}, |
| | journal = {arXiv preprint}, |
| | volume = {arXiv:2109.09701}, |
| | year = {2021} |
| | } |
| | **Please CITE** our paper when BARTpho is used to help produce published results or incorporated into other software. |
| | |
| | For further information or requests, please go to [BARTpho's homepage](https://github.com/VinAIResearch/BARTpho)! |
