README.md

---
datasets:
- tarudesu/VOZ-HSD
language:
- vi
---

# <a name="introduction"></a> ViHateT5: Enhancing Hate Speech Detection in Vietnamese with A Unified Text-to-Text Transformer Model | ACL'2024 (Findings)

**Disclaimer**: This paper contains examples from actual content on social media platforms that could be considered toxic and offensive.

ViHateT5 is the state-of-the-art pre-trained text-to-text transformer model for Vietnamese (HSD tasks). Note the this checkpoint need to be fine-tuned on downstream tasks, especially hate speech detection ones ([ViHateT5-HSD](https://huggingface.co/tarudesu/ViHateT5-base-HSD) is the fine-tuned model mentioned in the paper).

The architecture and experimental results of ViHateT5 can be found in the [paper](https://aclanthology.org/2024.findings-acl.355.pdf):

```
@inproceedings{thanh-nguyen-2024-vihatet5,
    title = "{V}i{H}ate{T}5: Enhancing Hate Speech Detection in {V}ietnamese With a Unified Text-to-Text Transformer Model",
    author = "Thanh Nguyen, Luan",
    editor = "Ku, Lun-Wei  and Martins, Andre  and Srikumar, Vivek",
    booktitle = "Findings of the Association for Computational Linguistics ACL 2024",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand and virtual meeting",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.findings-acl.355",
    pages = "5948--5961"
    }
```
    
The pre-training dataset named VOZ-HSD is available at [HERE](https://huggingface.co/datasets/tarudesu/VOZ-HSD).

Kindly **CITE** our paper if you use ViHateT5 to generate published results or integrate it into other software.

**Example usage**
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("tarudesu/ViHateT5-base")
model = AutoModelForSeq2SeqLM.from_pretrained("tarudesu/ViHateT5-base")
```

Please feel free to contact us by email [email protected] if you have any further information!