---
license: mit
language:
- en
- hu
tags:
- text-classification
metrics:
- mae
- rmse
- correlation
widget:
- text: >-
    How much luggage? <sep> Mennyi csomagot Vihetek?
---

# English-Hungarian Qualtiy Estimation with finetuned XLM-RoBERTa model

For further models, scripts and details, see [our demo site](https://juniper.nytud.hu/demo/nlp).

  - Pretrained model used: XLM-RoBERTa base
  - Finetuned on HuQ corpus
  - Labels: regression model
  - Separator: \<sep\>
  	
## Limitations

- max_seq_length = 256
- input format: {src_en_sentence} \<sep\> {tgt_hu_sentence}

## Results

10-fold cross validation on HuQ corpus

| Model | Correlation | MAE | RMSE |
| ------------- | ------------- | ------------- | ------------- |
| baseline | 0.6100 | 0.7459 |  0.9775 |
| **XLM-R** | **0.7948** | **0.6451** | **0.8898** |


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

```
@article{yang-rl,
    title = {Enhancing Machine Translation with Quality Estimation and Reinforcement Learning},
	journal = {Annales Mathematicae et Informaticae},
	year = {2023},
	author = {Yang, Zijian Győző and Laki, László János},
	pages = {Accepted}
}

```