LABEL_0 LABEL_1 LABEL_2 LABEL_3 LABEL_4
---

language: 
  - hu
tags:
- text-classification
license: gpl
metrics:
- accuracy
widget:
- text: "Jó reggelt! majd küldöm az élményhozókat :)."

---

# Hungarian Sentence-level Sentiment Analysis model with XLM-RoBERTa

For further models, scripts and details, see [our repository](https://github.com/nytud/sentiment-analysis) or [our demo site](https://juniper.nytud.hu/demo/nlp).

  - Pretrained model used: XLM-RoBERTa base
  - Finetuned on Hungarian Twitter Sentiment (HTS) Corpus
  - Labels: 1, 2, 3, 4, 5
  	
## Limitations

- max_seq_length = 128

## Results

| Model | HTS2 | HTS5 |
| ------------- | ------------- | ------------- |
| huBERT | 85.55 | 68.99  |
| XLM-RoBERTa| 85.56 | **85.56** |

## Citation
If you use this model, please cite the following paper:

```
@inproceedings {yang-bart,
    title = {Improving Performance of Sentence-level Sentiment Analysis with Data Augmentation Methods},
	booktitle = {Proceedings of 12th IEEE International Conference on Cognitive Infocommunications (CogInfoCom 2021)},
	year = {2021},
	publisher = {IEEE},
	address = {Online},
	author = {{Laki, László and Yang, Zijian Győző}}
	pages = {417--422}
}

```